From 5bdb01ecfcf4d0b10888624fc6d2572800f4a7d4 Mon Sep 17 00:00:00 2001
From: Jaysukh Makvana <111515433+Jaysukh-409@users.noreply.github.com>
Date: Thu, 2 Jan 2025 13:59:54 +0530
Subject: [PATCH 01/87] feat: add `stats/base/dists/planck/mode`

PR-URL: https://github.com/stdlib-js/stdlib/pull/4350
Co-authored-by: Athan Reines <kgryte@gmail.com>
Reviewed-by: Athan Reines <kgryte@gmail.com>
Co-authored-by: stdlib-bot <82920195+stdlib-bot@users.noreply.github.com>
---
 .../stats/base/dists/planck/mode/README.md    | 137 ++++++++++++++++++
 .../dists/planck/mode/benchmark/benchmark.js  |  52 +++++++
 .../base/dists/planck/mode/docs/repl.txt      |  26 ++++
 .../dists/planck/mode/docs/types/index.d.ts   |  52 +++++++
 .../base/dists/planck/mode/docs/types/test.ts |  44 ++++++
 .../base/dists/planck/mode/examples/index.js  |  31 ++++
 .../stats/base/dists/planck/mode/lib/index.js |  43 ++++++
 .../stats/base/dists/planck/mode/lib/main.js  |  60 ++++++++
 .../stats/base/dists/planck/mode/package.json |  68 +++++++++
 .../stats/base/dists/planck/mode/test/test.js |  67 +++++++++
 10 files changed, 580 insertions(+)
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/mode/README.md
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/mode/benchmark/benchmark.js
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/mode/docs/repl.txt
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/mode/docs/types/index.d.ts
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/mode/docs/types/test.ts
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/mode/examples/index.js
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/mode/lib/index.js
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/mode/lib/main.js
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/mode/package.json
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/mode/test/test.js

diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/mode/README.md b/lib/node_modules/@stdlib/stats/base/dists/planck/mode/README.md
new file mode 100644
index 000000000000..0d62c5c213a4
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/mode/README.md
@@ -0,0 +1,137 @@
+<!--
+
+@license Apache-2.0
+
+Copyright (c) 2025 The Stdlib Authors.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+   http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+
+-->
+
+# Mode
+
+> Planck (discrete exponential) distribution [mode][mode].
+
+<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->
+
+<section class="intro">
+
+The [mode][mode] for a Planck random variable with shape parameter `λ` is
+
+<!-- <equation class="equation" label="eq:planck_mode" align="center" raw="\operatorname{mode}\left( X \right) = 0" alt="Mode for a Planck distribution."> -->
+
+```math
+\mathop{\mathrm{mode}}\left( X \right) = 0
+```
+
+<!-- </equation> -->
+
+</section>
+
+<!-- /.intro -->
+
+<!-- Package usage documentation. -->
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var mode = require( '@stdlib/stats/base/dists/planck/mode' );
+```
+
+#### mode( lambda )
+
+Returns the [mode][mode] of a Planck distribution with shape parameter `lambda`.
+
+```javascript
+var v = mode( 0.1 );
+// returns 0
+
+v = mode( 1.5 );
+// returns 0
+```
+
+If provided a shape parameter `lambda` is nonpositive or `NaN`, the function returns `NaN`.
+
+```javascript
+var v = mode( NaN );
+// returns NaN
+
+v = mode( -1.5 );
+// returns NaN
+```
+
+</section>
+
+<!-- /.usage -->
+
+<!-- Package usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="notes">
+
+</section>
+
+<!-- /.notes -->
+
+<!-- Package usage examples. -->
+
+<section class="examples">
+
+## Examples
+
+<!-- eslint no-undef: "error" -->
+
+```javascript
+var uniform = require( '@stdlib/random/array/uniform' );
+var mode = require( '@stdlib/stats/base/dists/planck/mode' );
+
+var lambda = uniform( 10, 0.1, 5.0 );
+
+var v;
+var i;
+for ( i = 0; i < lambda.length; i++ ) {
+    v = mode( lambda[ i ] );
+    console.log( 'λ: %d, mode(X;λ): %d', lambda[ i ].toFixed( 4 ), v.toFixed( 4 ) );
+}
+```
+
+</section>
+
+<!-- /.examples -->
+
+<!-- Section to include cited references. If references are included, add a horizontal rule *before* the section. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="references">
+
+</section>
+
+<!-- /.references -->
+
+<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
+
+<section class="related">
+
+</section>
+
+<!-- /.related -->
+
+<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="links">
+
+[mode]: https://en.wikipedia.org/wiki/Mode_%28statistics%29
+
+</section>
+
+<!-- /.links -->
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/mode/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/planck/mode/benchmark/benchmark.js
new file mode 100644
index 000000000000..8e8500b8b07b
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/mode/benchmark/benchmark.js
@@ -0,0 +1,52 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pkg = require( './../package.json' ).name;
+var mode = require( './../lib' );
+
+
+// MAIN //
+
+bench( pkg, function benchmark( b ) {
+	var lambda;
+	var y;
+	var i;
+
+	lambda = uniform( 100, 0.1, 10.0 );
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		y = mode( lambda[ i % lambda.length ] );
+		if ( isnan( y ) ) {
+			b.fail( 'should not return NaN' );
+		}
+	}
+	b.toc();
+	if ( isnan( y ) ) {
+		b.fail( 'should not return NaN' );
+	}
+	b.pass( 'benchmark finished' );
+	b.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/mode/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dists/planck/mode/docs/repl.txt
new file mode 100644
index 000000000000..b4567e8a667f
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/mode/docs/repl.txt
@@ -0,0 +1,26 @@
+
+{{alias}}( λ )
+    Returns the mode of a Planck distribution with shape parameter `λ`.
+
+    If `lambda <= 0`, the function returns `NaN`.
+
+    Parameters
+    ----------
+    λ: number
+        Shape parameter.
+
+    Returns
+    -------
+    out: integer
+        Mode.
+
+    Examples
+    --------
+    > var v = {{alias}}( 0.1 )
+    0
+    > v = {{alias}}( 1.5 )
+    0
+
+    See Also
+    --------
+
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/mode/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/planck/mode/docs/types/index.d.ts
new file mode 100644
index 000000000000..488fb5289de0
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/mode/docs/types/index.d.ts
@@ -0,0 +1,52 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+// TypeScript Version: 4.1
+
+/**
+* Returns the mode of a Planck distribution.
+*
+* ## Notes
+*
+* -   If `lambda <= 0`, the function returns `NaN`.
+*
+* @param lambda - shape parameter
+* @returns mode
+*
+* @example
+* var v = mode( 0.1 );
+* // returns 0
+*
+* @example
+* var v = mode( 1.5 );
+* // returns 0
+*
+* @example
+* var v = mode( -1.1 );
+* // returns NaN
+*
+* @example
+* var v = mode( NaN );
+* // returns NaN
+*/
+declare function mode( lambda: number ): number;
+
+
+// EXPORTS //
+
+export = mode;
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/mode/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/dists/planck/mode/docs/types/test.ts
new file mode 100644
index 000000000000..a1f70068852e
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/mode/docs/types/test.ts
@@ -0,0 +1,44 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+import mode = require( './index' );
+
+
+// TESTS //
+
+// The function returns a number...
+{
+	mode( 0.3 ); // $ExpectType number
+}
+
+// The compiler throws an error if the function is provided a value other than a number...
+{
+	mode( true ); // $ExpectError
+	mode( false ); // $ExpectError
+	mode( null ); // $ExpectError
+	mode( undefined ); // $ExpectError
+	mode( '5' ); // $ExpectError
+	mode( [] ); // $ExpectError
+	mode( {} ); // $ExpectError
+	mode( ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided insufficient arguments...
+{
+	mode(); // $ExpectError
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/mode/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/planck/mode/examples/index.js
new file mode 100644
index 000000000000..987223b2b815
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/mode/examples/index.js
@@ -0,0 +1,31 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+var uniform = require( '@stdlib/random/array/uniform' );
+var mode = require( './../lib' );
+
+var lambda = uniform( 10, 0.1, 5.0 );
+
+var v;
+var i;
+for ( i = 0; i < lambda.length; i++ ) {
+	v = mode( lambda[ i ] );
+	console.log( 'λ: %d, mode(X;λ): %d', lambda[ i ].toFixed( 4 ), v.toFixed( 4 ) );
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/mode/lib/index.js b/lib/node_modules/@stdlib/stats/base/dists/planck/mode/lib/index.js
new file mode 100644
index 000000000000..06b9e6b178ba
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/mode/lib/index.js
@@ -0,0 +1,43 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+/**
+* Planck distribution mode.
+*
+* @module @stdlib/stats/base/dists/planck/mode
+*
+* @example
+* var mode = require( '@stdlib/stats/base/dists/planck/mode' );
+*
+* var v = mode( 0.1 );
+* // returns 0
+*
+* v = mode( 1.5 );
+* // returns 0
+*/
+
+// MODULES //
+
+var mode = require( './main.js' );
+
+
+// EXPORTS //
+
+module.exports = mode;
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/mode/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/planck/mode/lib/main.js
new file mode 100644
index 000000000000..59a3282ae45b
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/mode/lib/main.js
@@ -0,0 +1,60 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+
+
+// MAIN //
+
+/**
+* Returns the mode of a Planck distribution.
+*
+* @param {PositiveNumber} lambda - shape parameter
+* @returns {NonNegativeInteger} mode
+*
+* @example
+* var v = mode( 0.1 );
+* // returns 0
+*
+* @example
+* var v = mode( 1.5 );
+* // returns 0
+*
+* @example
+* var v = mode( -1.1 );
+* // returns NaN
+*
+* @example
+* var v = mode( NaN );
+* // returns NaN
+*/
+function mode( lambda ) {
+	if ( isnan( lambda ) || lambda <= 0.0 ) {
+		return NaN;
+	}
+	return 0;
+}
+
+
+// EXPORTS //
+
+module.exports = mode;
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/mode/package.json b/lib/node_modules/@stdlib/stats/base/dists/planck/mode/package.json
new file mode 100644
index 000000000000..04c5b8bceac3
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/mode/package.json
@@ -0,0 +1,68 @@
+{
+  "name": "@stdlib/stats/base/dists/planck/mode",
+  "version": "0.0.0",
+  "description": "Planck (discrete exponential) distribution mode.",
+  "license": "Apache-2.0",
+  "author": {
+    "name": "The Stdlib Authors",
+    "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+  },
+  "contributors": [
+    {
+      "name": "The Stdlib Authors",
+      "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+    }
+  ],
+  "main": "./lib",
+  "directories": {
+    "benchmark": "./benchmark",
+    "doc": "./docs",
+    "example": "./examples",
+    "lib": "./lib",
+    "test": "./test"
+  },
+  "types": "./docs/types",
+  "scripts": {},
+  "homepage": "https://github.com/stdlib-js/stdlib",
+  "repository": {
+    "type": "git",
+    "url": "git://github.com/stdlib-js/stdlib.git"
+  },
+  "bugs": {
+    "url": "https://github.com/stdlib-js/stdlib/issues"
+  },
+  "dependencies": {},
+  "devDependencies": {},
+  "engines": {
+    "node": ">=0.10.0",
+    "npm": ">2.7.0"
+  },
+  "os": [
+    "aix",
+    "darwin",
+    "freebsd",
+    "linux",
+    "macos",
+    "openbsd",
+    "sunos",
+    "win32",
+    "windows"
+  ],
+  "keywords": [
+    "stdlib",
+    "stdmath",
+    "statistics",
+    "stats",
+    "distribution",
+    "dist",
+    "planck",
+    "parameter",
+    "memoryless",
+    "life-time",
+    "discrete",
+    "location",
+    "center",
+    "mode",
+    "univariate"
+  ]
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/mode/test/test.js b/lib/node_modules/@stdlib/stats/base/dists/planck/mode/test/test.js
new file mode 100644
index 000000000000..1a9f3da7a9e6
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/mode/test/test.js
@@ -0,0 +1,67 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var mode = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof mode, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'if provided `NaN` for `lambda`, the function returns `NaN`', function test( t ) {
+	var v = mode( NaN );
+	t.equal( isnan( v ), true, 'returns expected value' );
+	t.end();
+});
+
+tape( 'if provided a shape parameter `lambda` which is nonpositive, the function returns `NaN`', function test( t ) {
+	var v;
+
+	v = mode( 0.0 );
+	t.equal( isnan( v ), true, 'returns expected value' );
+
+	v = mode( -1.5 );
+	t.equal( isnan( v ), true, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function returns `0.0` as the mode of a Planck distribution', function test( t ) {
+	var lambda;
+	var i;
+	var y;
+
+	lambda = uniform( 10, 0.1, 10.0 );
+
+	for ( i = 0; i < lambda.length; i++ ) {
+		y = mode( lambda[ i ] );
+		t.equal( y, 0.0, 'returns expected value' );
+	}
+	t.end();
+});

From 28ad0864fff4451b470bd107c69301ba9e059898 Mon Sep 17 00:00:00 2001
From: Jaysukh Makvana <111515433+Jaysukh-409@users.noreply.github.com>
Date: Thu, 2 Jan 2025 14:02:44 +0530
Subject: [PATCH 02/87] feat: add `stats/base/dists/planck/logpmf`

PR-URL: https://github.com/stdlib-js/stdlib/pull/4182
Co-authored-by: Athan Reines <kgryte@gmail.com>
Reviewed-by: Athan Reines <kgryte@gmail.com>
Co-authored-by: stdlib-bot <82920195+stdlib-bot@users.noreply.github.com>
---
 .../stats/base/dists/planck/logpmf/README.md  | 152 ++++++++++++++
 .../planck/logpmf/benchmark/benchmark.js      |  79 ++++++++
 .../base/dists/planck/logpmf/docs/repl.txt    |  64 ++++++
 .../dists/planck/logpmf/docs/types/index.d.ts | 114 +++++++++++
 .../dists/planck/logpmf/docs/types/test.ts    |  98 +++++++++
 .../dists/planck/logpmf/examples/index.js     |  33 +++
 .../base/dists/planck/logpmf/lib/factory.js   |  78 +++++++
 .../base/dists/planck/logpmf/lib/index.js     |  60 ++++++
 .../base/dists/planck/logpmf/lib/main.js      |  77 +++++++
 .../base/dists/planck/logpmf/package.json     |  67 ++++++
 .../test/fixtures/python/large_lambda.json    |   1 +
 .../logpmf/test/fixtures/python/runner.py     |  87 ++++++++
 .../test/fixtures/python/small_lambda.json    |   1 +
 .../dists/planck/logpmf/test/test.factory.js  | 190 ++++++++++++++++++
 .../base/dists/planck/logpmf/test/test.js     |  38 ++++
 .../dists/planck/logpmf/test/test.logpmf.js   | 140 +++++++++++++
 16 files changed, 1279 insertions(+)
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/README.md
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/benchmark/benchmark.js
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/docs/repl.txt
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/docs/types/index.d.ts
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/docs/types/test.ts
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/examples/index.js
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/lib/factory.js
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/lib/index.js
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/lib/main.js
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/package.json
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/test/fixtures/python/large_lambda.json
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/test/fixtures/python/runner.py
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/test/fixtures/python/small_lambda.json
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/test/test.factory.js
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/test/test.js
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/test/test.logpmf.js

diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/README.md b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/README.md
new file mode 100644
index 000000000000..bd177c1db4d7
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/README.md
@@ -0,0 +1,152 @@
+<!--
+
+@license Apache-2.0
+
+Copyright (c) 2025 The Stdlib Authors.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+   http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+
+-->
+
+# Logarithm of Probability Mass Function
+
+> Evaluate the logarithm of the [probability mass function][pmf] (PMF) for a Planck (discrete exponential) distribution.
+
+<section class="intro">
+
+The [probability mass function][pmf] (PMF) for a Planck random variable is defined as
+
+<!-- <equation class="equation" label="eq:planck_pmf" align="center" raw="\Pr(X = x, \lambda) = \begin{cases}(1 - e^{-\lambda})e^{-\lambda x} & \text{for } x = 0, 1, 2, \ldots \\ 0 & \text{otherwise} \end{cases}" alt="Probability mass function (PMF) for a Planck distribution."> -->
+
+```math
+\Pr(X = x, \lambda) = \begin{cases}(1 - e^{-\lambda})e^{-\lambda x} & \text{for } x = 0, 1, 2, \ldots \\ 0 & \text{otherwise} \end{cases}
+```
+
+<!-- </equation> -->
+
+where `λ` is the shape parameter and `x` denotes the count of events in a quantized system.
+
+</section>
+
+<!-- /.intro -->
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var logpmf = require( '@stdlib/stats/base/dists/planck/logpmf' );
+```
+
+#### logpmf( x, lambda )
+
+Evaluates the logarithm of the [probability mass function][pmf] (PMF) of a Planck (discrete exponential) distribution with shape parameter `lambda`.
+
+```javascript
+var y = logpmf( 4.0, 0.3 );
+// returns ~-2.5502
+
+y = logpmf( 2.0, 1.7 );
+// returns ~-3.6017
+
+y = logpmf( -1.0, 2.5 );
+// returns -Infinity
+```
+
+If provided `NaN` as any argument, the function returns `NaN`.
+
+```javascript
+var y = logpmf( NaN, 0.0 );
+// returns NaN
+
+y = logpmf( 0.0, NaN );
+// returns NaN
+```
+
+If provided a shape parameter `lambda` which is nonpositive number, the function returns `NaN`.
+
+```javascript
+var y = logpmf( 2.0, -1.0 );
+// returns NaN
+```
+
+#### logpmf.factory( lambda )
+
+Returns a function for evaluating the logarithm of the [probability mass function][pmf] (PMF) of a Planck (discrete exponential) distribution with shape parameter `lambda`.
+
+```javascript
+var mylogpmf = logpmf.factory( 0.5 );
+var y = mylogpmf( 3.0 );
+// returns ~-2.4328
+
+y = mylogpmf( 1.0 );
+// returns ~-1.4328
+```
+
+</section>
+
+<!-- /.usage -->
+
+<section class="notes">
+
+## Notes
+
+-   In virtually all cases, using the `logpmf` or `logcdf` functions is preferable to manually computing the logarithm of the `pmf` or `cdf`, respectively, since the latter is prone to overflow and underflow.
+
+</section>
+
+<!-- /.notes -->
+
+<section class="examples">
+
+## Examples
+
+<!-- eslint no-undef: "error" -->
+
+```javascript
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var logpmf = require( '@stdlib/stats/base/dists/planck/logpmf' );
+
+var x = discreteUniform( 10, 0, 5 );
+var lambda = uniform( 10, 0.1, 5.0 );
+
+var y;
+var i;
+for ( i = 0; i < lambda.length; i++ ) {
+    y = logpmf( x[ i ], lambda[ i ] );
+    console.log( 'x: %d, λ: %d, ln( P( X = x; λ ) ): %d', x[ i ], lambda[ i ].toFixed( 4 ), y.toFixed( 4 ) );
+}
+```
+
+</section>
+
+<!-- /.examples -->
+
+<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
+
+<section class="related">
+
+</section>
+
+<!-- /.related -->
+
+<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="links">
+
+[pmf]: https://en.wikipedia.org/wiki/Probability_mass_function
+
+</section>
+
+<!-- /.links -->
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/benchmark/benchmark.js
new file mode 100644
index 000000000000..2d48249bfa8f
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/benchmark/benchmark.js
@@ -0,0 +1,79 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pkg = require( './../package.json' ).name;
+var logpmf = require( './../lib' );
+
+
+// MAIN //
+
+bench( pkg, function benchmark( b ) {
+	var lambda;
+	var x;
+	var y;
+	var i;
+
+	x = discreteUniform( 100, 0, 40 );
+	lambda = uniform( 100, 0.1, 10.0 );
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		y = logpmf( x[ i % x.length ], lambda[ i % lambda.length ] );
+		if ( isnan( y ) ) {
+			b.fail( 'should not return NaN' );
+		}
+	}
+	b.toc();
+	if ( isnan( y ) ) {
+		b.fail( 'should not return NaN' );
+	}
+	b.pass( 'benchmark finished' );
+	b.end();
+});
+
+bench( pkg+':factory', function benchmark( b ) {
+	var mylogpmf;
+	var x;
+	var y;
+	var i;
+
+	x = discreteUniform( 100, 0, 40 );
+	mylogpmf = logpmf.factory( 0.3 );
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		y = mylogpmf( x[ i % x.length ] );
+		if ( isnan( y ) ) {
+			b.fail( 'should not return NaN' );
+		}
+	}
+	b.toc();
+	if ( isnan( y ) ) {
+		b.fail( 'should not return NaN' );
+	}
+	b.pass( 'benchmark finished' );
+	b.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/docs/repl.txt
new file mode 100644
index 000000000000..1ae67dfc813e
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/docs/repl.txt
@@ -0,0 +1,64 @@
+
+{{alias}}( x, λ )
+    Evaluates the logarithm of the probability mass function (PMF) for a Planck
+    distribution with shape parameter `λ` at a value `x`.
+
+    If provided `NaN` as any argument, the function returns `NaN`.
+
+    If `λ <= 0`, the function returns `NaN`.
+
+    Parameters
+    ----------
+    x: number
+        Input value.
+
+    λ: number
+        Shape parameter.
+
+    Returns
+    -------
+    out: number
+        Evaluated logPMF.
+
+    Examples
+    --------
+    > var y = {{alias}}( 4.0, 0.3 )
+    ~-2.5502
+    > y = {{alias}}( 2.0, 1.7 )
+    ~-3.6017
+    > y = {{alias}}( -1.0, 2.5 )
+    -Infinity
+    > y = {{alias}}( 0.0, NaN )
+    NaN
+    > y = {{alias}}( NaN, 0.5 )
+    NaN
+    // Invalid shape parameter:
+    > y = {{alias}}( 2.0, -1.0 )
+    NaN
+
+
+{{alias}}.factory( λ )
+    Returns a function for evaluating the logarithm of the probability mass
+    function (PMF) of a Planck distribution with shape parameter `λ`.
+
+    Parameters
+    ----------
+    λ: number
+        Shape parameter.
+
+    Returns
+    -------
+    logpmf: Function
+        Logarithm of the probability mass function (PMF).
+
+    Examples
+    --------
+    > var mylogpmf = {{alias}}.factory( 0.5 );
+    > var y = mylogpmf( 3.0 )
+    ~-2.4328
+    > y = mylogpmf( 1.0 )
+    ~-1.4328
+
+    See Also
+    --------
+
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/docs/types/index.d.ts
new file mode 100644
index 000000000000..387dba3e316d
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/docs/types/index.d.ts
@@ -0,0 +1,114 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+// TypeScript Version: 4.1
+
+/**
+* Evaluates the natural logarithm of the probability mass function (PMF) for a Planck distribution.
+*
+* @param x - input value
+* @returns evaluated PMF
+*/
+type Unary = ( x: number ) => number;
+
+/**
+* Interface for the natural logarithm of the probability mass function (PMF) of a Planck distribution.
+*/
+interface LogPMF {
+	/**
+	* Evaluates the logarithm of the probability mass function (PMF) for a Planck distribution with shape parameter `lambda` at a value `x`.
+	*
+	* ## Notes
+	*
+	* -   If `lambda <= 0`, the function returns `NaN`.
+	*
+	* @param x - input value
+	* @param lambda - shape parameter
+	* @returns logarithm of PMF
+	*
+	* @example
+	* var y = logpmf( 4.0, 0.3 );
+	* // returns ~-2.5502
+	*
+	* @example
+	* var y = logpmf( 2.0, 1.7 );
+	* // returns ~-3.6017
+	*
+	* @example
+	* var y = logpmf( -1.0, 2.5 );
+	* // returns -Infinity
+	*
+	* @example
+	* var y = logpmf( 0.0, NaN );
+	* // returns NaN
+	*
+	* @example
+	* var y = logpmf( NaN, 0.5 );
+	* // returns NaN
+	*
+	* @example
+	* // Invalid shape parameter:
+	* var y = logpmf( 2.0, -1.0 );
+	* // returns NaN
+	*/
+	( x: number, lambda: number ): number;
+
+	/**
+	* Returns a function for evaluating the logarithm of the probability mass function (PMF) for a Planck distribution with shape parameter `lambda`.
+	*
+	* @param lambda - shape parameter
+	* @returns logPMF
+	*
+	* @example
+	* var mylogpmf = logpmf.factory( 0.5 );
+	* var y = mylogpmf( 3.0 );
+	* // returns ~-2.4327
+	*
+	* y = mylogpmf( 1.0 );
+	* // returns ~-1.4327
+	*/
+	factory( lambda: number ): Unary;
+}
+
+/**
+* Evaluates the natural logarithm of the probability mass function (PMF) for a Planck distribution.
+*
+* @param x - input value
+* @param lambda - shape parameter
+* @returns evaluated logPMF
+*
+* @example
+* var y = logpmf( 4.0, 0.3 );
+* // returns ~-2.5502
+*
+* y = logpmf( 2.0, 1.7 );
+* // returns ~-3.6017
+*
+* var mylogpmf = logpmf.factory( 0.5 );
+* y = mylogpmf( 3.0 );
+* // returns ~-2.4327
+*
+* y = mylogpmf( 1.0 );
+* // returns ~-1.4327
+*/
+declare var logPMF: LogPMF;
+
+
+// EXPORTS //
+
+export = logPMF;
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/docs/types/test.ts
new file mode 100644
index 000000000000..344fadf696c9
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/docs/types/test.ts
@@ -0,0 +1,98 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+import logpmf = require( './index' );
+
+
+// TESTS //
+
+// The function returns a number...
+{
+	logpmf( 2.0, 0.4 ); // $ExpectType number
+	logpmf( 1.0, 0.2 ); // $ExpectType number
+}
+
+// The compiler throws an error if the function is provided values other than two numbers...
+{
+	logpmf( true, 0.3 ); // $ExpectError
+	logpmf( false, 0.2 ); // $ExpectError
+	logpmf( '5', 0.1 ); // $ExpectError
+	logpmf( [], 0.1 ); // $ExpectError
+	logpmf( {}, 0.4 ); // $ExpectError
+	logpmf( ( x: number ): number => x, 0.2 ); // $ExpectError
+
+	logpmf( 0.0, true ); // $ExpectError
+	logpmf( 1.0, false ); // $ExpectError
+	logpmf( 0.0, '5' ); // $ExpectError
+	logpmf( 1.0, [] ); // $ExpectError
+	logpmf( 2.0, {} ); // $ExpectError
+	logpmf( 3.0, ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided an unsupported number of arguments...
+{
+	logpmf(); // $ExpectError
+	logpmf( 0.0 ); // $ExpectError
+	logpmf( 1.0, 0.3, 4.0 ); // $ExpectError
+}
+
+// Attached to main export is a `factory` method which returns a function...
+{
+	logpmf.factory( 0.4 ); // $ExpectType Unary
+}
+
+// The `factory` method returns a function which returns a number...
+{
+	const fcn = logpmf.factory( 0.4 );
+	fcn( 2.0 ); // $ExpectType number
+}
+
+// The compiler throws an error if the function returned by the `factory` method is provided an invalid argument...
+{
+	const fcn = logpmf.factory( 0.4 );
+	fcn( true ); // $ExpectError
+	fcn( false ); // $ExpectError
+	fcn( '5' ); // $ExpectError
+	fcn( [] ); // $ExpectError
+	fcn( {} ); // $ExpectError
+	fcn( ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the function returned by the `factory` method is provided an unsupported number of arguments...
+{
+	const fcn = logpmf.factory( 0.4 );
+	fcn(); // $ExpectError
+	fcn( 2.0, 0.0 ); // $ExpectError
+	fcn( 2.0, 0.0, 1.0 ); // $ExpectError
+}
+
+// The compiler throws an error if the `factory` method is provided a value other than a number...
+{
+	logpmf.factory( true ); // $ExpectError
+	logpmf.factory( false ); // $ExpectError
+	logpmf.factory( '5' ); // $ExpectError
+	logpmf.factory( [] ); // $ExpectError
+	logpmf.factory( {} ); // $ExpectError
+	logpmf.factory( ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the `factory` method is provided an unsupported number of arguments...
+{
+	logpmf.factory( 0.0, 0.2 ); // $ExpectError
+	logpmf.factory( 0.0, 0.4, 8.0 ); // $ExpectError
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/examples/index.js
new file mode 100644
index 000000000000..5f47a89e33a2
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/examples/index.js
@@ -0,0 +1,33 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var logpmf = require( './../lib' );
+
+var x = discreteUniform( 10, 0, 5 );
+var lambda = uniform( 10, 0.1, 5.0 );
+
+var y;
+var i;
+for ( i = 0; i < lambda.length; i++ ) {
+	y = logpmf( x[ i ], lambda[ i ] );
+	console.log( 'x: %d, λ: %d, ln( P( X = x; λ ) ): %d', x[ i ], lambda[ i ].toFixed( 4 ), y.toFixed( 4 ) );
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/lib/factory.js b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/lib/factory.js
new file mode 100644
index 000000000000..9a02a76317c8
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/lib/factory.js
@@ -0,0 +1,78 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var constantFunction = require( '@stdlib/utils/constant-function' );
+var isNonNegativeInteger = require( '@stdlib/math/base/assert/is-nonnegative-integer' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var expm1 = require( '@stdlib/math/base/special/expm1' );
+var ln = require( '@stdlib/math/base/special/ln' );
+var NINF = require( '@stdlib/constants/float64/ninf' );
+
+
+// MAIN //
+
+/**
+* Returns a function for evaluating the logarithm of the probability mass function (PMF) for a Planck distribution with shape parameter `lambda`.
+*
+* @param {PositiveNumber} lambda - shape parameter
+* @returns {Function} logPMF
+*
+* @example
+* var logpmf = factory( 0.5 );
+* var y = logpmf( 3.0 );
+* // returns ~-2.4328
+*
+* y = logpmf( 1.0 );
+* // returns ~-1.4328
+*/
+function factory( lambda ) {
+	if ( isnan( lambda ) || lambda <= 0.0 ) {
+		return constantFunction( NaN );
+	}
+	return logpmf;
+
+	/**
+	* Evaluates the logarithm of the probability mass function (PMF) for a Planck distribution.
+	*
+	* @private
+	* @param {number} x - input value
+	* @returns {NonPositiveNumber} evaluated logPMF
+	*
+	* @example
+	* var y = logpmf( 2.0 );
+	* // returns <number>
+	*/
+	function logpmf( x ) {
+		if ( isnan( x ) ) {
+			return NaN;
+		}
+		if ( isNonNegativeInteger( x ) ) {
+			return ln( -expm1( -lambda ) ) - ( lambda * x );
+		}
+		return NINF;
+	}
+}
+
+
+// EXPORTS //
+
+module.exports = factory;
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/lib/index.js b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/lib/index.js
new file mode 100644
index 000000000000..1084bd9a8c43
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/lib/index.js
@@ -0,0 +1,60 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+/**
+* Evaluate the logarithm of the probability mass function (PMF) for a Planck distribution.
+*
+* @module @stdlib/stats/base/dists/planck/logpmf
+*
+* @example
+* var logpmf = require( '@stdlib/stats/base/dists/planck/logpmf' );
+*
+* var y = logpmf( 4.0, 0.3 );
+* // returns ~-2.5502
+*
+* y = logpmf( 2.0, 1.7 );
+* // returns ~-3.6017
+*
+* y = logpmf( -1.0, 0.5 );
+* // returns 0.0
+*
+* var mylogpmf = logpmf.factory( 0.5 );
+* y = mylogpmf( 3.0 );
+* // returns ~-2.4328
+*
+* y = mylogpmf( 1.0 );
+* // returns ~-1.4328
+*/
+
+// MODULES //
+
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
+var main = require( './main.js' );
+var factory = require( './factory.js' );
+
+
+// MAIN //
+
+setReadOnly( main, 'factory', factory );
+
+
+// EXPORTS //
+
+module.exports = main;
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/lib/main.js
new file mode 100644
index 000000000000..be92ba4b2b82
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/lib/main.js
@@ -0,0 +1,77 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var isNonNegativeInteger = require( '@stdlib/math/base/assert/is-nonnegative-integer' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var expm1 = require( '@stdlib/math/base/special/expm1' );
+var ln = require( '@stdlib/math/base/special/ln' );
+var NINF = require( '@stdlib/constants/float64/ninf' );
+
+
+// MAIN //
+
+/**
+* Evaluates the logarithm of the probability mass function (PMF) for a Planck distribution with shape parameter `lambda` at a value `x`.
+*
+* @param {number} x - input value
+* @param {PositiveNumber} lambda - shape parameter
+* @returns {NonPositiveNumber} logarithm of PMF
+*
+* @example
+* var y = logpmf( 4.0, 0.3 );
+* // returns ~-2.5502
+*
+* @example
+* var y = logpmf( 2.0, 1.7 );
+* // returns ~-3.6017
+*
+* @example
+* var y = logpmf( -1.0, 2.5 );
+* // returns -Infinity
+*
+* @example
+* var y = logpmf( 0.0, NaN );
+* // returns NaN
+*
+* @example
+* var y = logpmf( NaN, 0.5 );
+* // returns NaN
+*
+* @example
+* // Invalid shape parameter:
+* var y = logpmf( 2.0, -1.0 );
+* // returns NaN
+*/
+function logpmf( x, lambda ) {
+	if ( isnan( x ) || isnan( lambda ) || lambda <= 0.0 ) {
+		return NaN;
+	}
+	if ( isNonNegativeInteger( x ) ) {
+		return ln( -expm1( -lambda ) ) - ( lambda * x );
+	}
+	return NINF;
+}
+
+
+// EXPORTS //
+
+module.exports = logpmf;
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/package.json b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/package.json
new file mode 100644
index 000000000000..e13245ee25e9
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/package.json
@@ -0,0 +1,67 @@
+{
+  "name": "@stdlib/stats/base/dists/planck/logpmf",
+  "version": "0.0.0",
+  "description": "Evaluate the logarithm of the probability mass function (PMF) for a Planck (discrete exponential) distribution.",
+  "license": "Apache-2.0",
+  "author": {
+    "name": "The Stdlib Authors",
+    "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+  },
+  "contributors": [
+    {
+      "name": "The Stdlib Authors",
+      "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+    }
+  ],
+  "main": "./lib",
+  "directories": {
+    "benchmark": "./benchmark",
+    "doc": "./docs",
+    "example": "./examples",
+    "lib": "./lib",
+    "test": "./test"
+  },
+  "types": "./docs/types",
+  "scripts": {},
+  "homepage": "https://github.com/stdlib-js/stdlib",
+  "repository": {
+    "type": "git",
+    "url": "git://github.com/stdlib-js/stdlib.git"
+  },
+  "bugs": {
+    "url": "https://github.com/stdlib-js/stdlib/issues"
+  },
+  "dependencies": {},
+  "devDependencies": {},
+  "engines": {
+    "node": ">=0.10.0",
+    "npm": ">2.7.0"
+  },
+  "os": [
+    "aix",
+    "darwin",
+    "freebsd",
+    "linux",
+    "macos",
+    "openbsd",
+    "sunos",
+    "win32",
+    "windows"
+  ],
+  "keywords": [
+    "stdlib",
+    "stdmath",
+    "statistics",
+    "stats",
+    "distribution",
+    "dist",
+    "probability",
+    "pmf",
+    "discrete distribution",
+    "logarithm",
+    "log",
+    "planck",
+    "univariate",
+    "discrete"
+  ]
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/test/fixtures/python/large_lambda.json b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/test/fixtures/python/large_lambda.json
new file mode 100644
index 000000000000..d4cd2afb2208
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/test/fixtures/python/large_lambda.json
@@ -0,0 +1 @@
+{"x": [9.0, 9.0, 2.0, 6.0, 0.0, 7.0, 3.0, 4.0, 5.0, 7.0, 1.0, 5.0, 10.0, 3.0, 1.0, 4.0, 6.0, 10.0, 5.0, 1.0, 5.0, 1.0, 6.0, 9.0, 0.0, 5.0, 3.0, 2.0, 3.0, 5.0, 8.0, 2.0, 3.0, 7.0, 9.0, 2.0, 1.0, 4.0, 7.0, 9.0, 5.0, 7.0, 9.0, 8.0, 6.0, 4.0, 4.0, 1.0, 9.0, 3.0, 0.0, 4.0, 9.0, 9.0, 6.0, 2.0, 2.0, 3.0, 5.0, 0.0, 7.0, 3.0, 2.0, 1.0, 1.0, 6.0, 7.0, 2.0, 8.0, 8.0, 8.0, 10.0, 6.0, 5.0, 0.0, 8.0, 9.0, 7.0, 1.0, 9.0, 1.0, 1.0, 8.0, 5.0, 3.0, 2.0, 0.0, 2.0, 9.0, 4.0, 3.0, 6.0, 5.0, 8.0, 1.0, 1.0, 5.0, 5.0, 6.0, 7.0, 9.0, 1.0, 5.0, 8.0, 2.0, 8.0, 9.0, 7.0, 4.0, 4.0, 7.0, 8.0, 6.0, 4.0, 4.0, 5.0, 5.0, 7.0, 10.0, 6.0, 7.0, 2.0, 2.0, 3.0, 9.0, 3.0, 4.0, 2.0, 3.0, 3.0, 6.0, 2.0, 6.0, 8.0, 9.0, 4.0, 2.0, 10.0, 1.0, 5.0, 0.0, 4.0, 8.0, 6.0, 8.0, 3.0, 1.0, 5.0, 10.0, 1.0, 4.0, 7.0, 3.0, 7.0, 3.0, 4.0, 6.0, 0.0, 2.0, 10.0, 2.0, 4.0, 5.0, 5.0, 4.0, 7.0, 9.0, 3.0, 4.0, 7.0, 0.0, 4.0, 3.0, 0.0, 4.0, 0.0, 0.0, 5.0, 4.0, 9.0, 0.0, 9.0, 1.0, 4.0, 4.0, 8.0, 10.0, 6.0, 3.0, 8.0, 2.0, 6.0, 2.0, 4.0, 10.0, 9.0, 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diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/test/fixtures/python/runner.py b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/test/fixtures/python/runner.py
new file mode 100644
index 000000000000..1ccc2449f54e
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/test/fixtures/python/runner.py
@@ -0,0 +1,87 @@
+#!/usr/bin/env python
+#
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""Generate fixtures."""
+
+import os
+import json
+import numpy as np
+from scipy.stats import planck
+
+# Get the file path:
+FILE = os.path.realpath(__file__)
+
+# Extract the directory in which this file resides:
+DIR = os.path.dirname(FILE)
+
+
+def gen(x, lam, name):
+    """
+    Generate fixture data and write to file.
+
+    # Arguments
+
+    * `x`: input values.
+    * `lam`: shape parameter.
+    * `name::str`: output filename.
+
+    # Examples
+
+    ```python
+    python> x = np.random.rand(1000) * 10.0
+    python> lam = np.random.rand(1000)
+    python> gen(x, lam, "data.json")
+    ```
+    """
+    # Compute PDF values:
+    z = np.array(planck.logpmf(x, lam))
+
+    # Store data to be written to file as a dictionary:
+    data = {
+        "x": x.tolist(),
+        "lambda": lam.tolist(),
+        "expected": z.tolist()
+    }
+
+    # Based on the script directory, create an output filepath:
+    filepath = os.path.join(DIR, name)
+
+    # Write the data to the output filepath as JSON:
+    with open(filepath, "w", encoding='utf-8') as outfile:
+        json.dump(data, outfile)
+
+    # Include trailing newline:
+    with open(filepath, "a", encoding='utf-8') as outfile:
+        outfile.write("\n")
+
+
+def main():
+    """Generate fixture data."""
+    # Large shape parameter:
+    x = np.round(np.random.rand(1000) * 10.0)
+    lam = (np.random.rand(1000) * 10.0) + 10.0
+    gen(x, lam, "large_lambda.json")
+
+    # Small shape parameter:
+    x = np.round(np.random.rand(1000) * 10.0)
+    lam = np.random.rand(1000) * 0.5
+    gen(x, lam, "small_lambda.json")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/test/fixtures/python/small_lambda.json b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/test/fixtures/python/small_lambda.json
new file mode 100644
index 000000000000..e80bd8696bdd
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/test/fixtures/python/small_lambda.json
@@ -0,0 +1 @@
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diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/test/test.factory.js b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/test/test.factory.js
new file mode 100644
index 000000000000..c697773630ab
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/test/test.factory.js
@@ -0,0 +1,190 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var abs = require( '@stdlib/math/base/special/abs' );
+var PINF = require( '@stdlib/constants/float64/pinf' );
+var NINF = require( '@stdlib/constants/float64/ninf' );
+var EPS = require( '@stdlib/constants/float64/eps' );
+var factory = require( './../lib/factory.js' );
+
+
+// FIXTURES //
+
+var smallLambda = require( './fixtures/python/small_lambda.json' );
+var largeLambda = require( './fixtures/python/large_lambda.json' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof factory, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function returns a function', function test( t ) {
+	var logpmf = factory( 0.5 );
+	t.equal( typeof logpmf, 'function', 'returns a function' );
+	t.end();
+});
+
+tape( 'if provided `NaN` for any parameter, the returned function returns `NaN`', function test( t ) {
+	var logpmf;
+	var y;
+
+	logpmf = factory( 0.5 );
+	y = logpmf( NaN );
+	t.equal( isnan( y ), true, 'returns expected value' );
+
+	logpmf = factory( NaN );
+	y = logpmf( 0.0 );
+	t.equal( isnan( y ), true, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'if provided a finite `lambda`, the function returns a function which returns `-Infinity` when provided `+infinity` for `x`', function test( t ) {
+	var logpmf;
+	var y;
+
+	logpmf = factory( 1.0 );
+	y = logpmf( PINF );
+	t.equal( y, NINF, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'if provided a finite `lambda`, the function returns a function which returns `-Infinity` when provided a negative integer for `x`', function test( t ) {
+	var logpmf;
+	var y;
+
+	logpmf = factory( 0.4 );
+	y = logpmf( -4.0 );
+	t.equal( y, NINF, 'returns expected value' );
+
+	y = logpmf( -1.0 );
+	t.equal( y, NINF, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'if provided a finite `lambda`, the function returns a function which returns `-Infinity` when provided a non-integer for `x`', function test( t ) {
+	var logpmf;
+	var y;
+
+	logpmf = factory( 0.4 );
+	y = logpmf( 1.3 );
+	t.equal( y, NINF, 'returns expected value' );
+
+	y = logpmf( 1.4 );
+	t.equal( y, NINF, 'returns expected value' );
+
+	y = logpmf( 3.2 );
+	t.equal( y, NINF, 'returns expected value' );
+
+	y = logpmf( 4.8 );
+	t.equal( y, NINF, 'returns expected value' );
+
+	y = logpmf( -1.2 );
+	t.equal( y, NINF, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'if provided a `lambda` which is nonpositive, the returned function always returns `NaN`', function test( t ) {
+	var logpmf;
+	var y;
+
+	logpmf = factory( 0.0 );
+
+	y = logpmf( 2.0 );
+	t.equal( isnan( y ), true, 'returns expected value' );
+
+	y = logpmf( 0.0 );
+	t.equal( isnan( y ), true, 'returns expected value' );
+
+	logpmf = factory( -1.5 );
+
+	y = logpmf( 2.0 );
+	t.equal( isnan( y ), true, 'returns expected value' );
+
+	y = logpmf( 0.0 );
+	t.equal( isnan( y ), true, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the returned function evaluates the logpmf for `x` given small `lambda`', function test( t ) {
+	var expected;
+	var logpmf;
+	var lambda;
+	var delta;
+	var tol;
+	var i;
+	var x;
+	var y;
+
+	expected = smallLambda.expected;
+	x = smallLambda.x;
+	lambda = smallLambda.lambda;
+	for ( i = 0; i < x.length; i++ ) {
+		logpmf = factory( lambda[ i ] );
+		y = logpmf( x[ i ] );
+		if ( y === expected[ i ] ) {
+			t.equal( y, expected[i], 'x: '+x[ i ]+'. lambda: '+lambda[ i ]+', y: '+y+', expected: '+expected[ i ] );
+		} else {
+			delta = abs( y - expected[ i ] );
+			tol = 1.0 * EPS * abs( expected[ i ] );
+			t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. lambda: '+lambda[ i ]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
+		}
+	}
+	t.end();
+});
+
+tape( 'the returned function evaluates the logpmf for `x` given large `lambda`', function test( t ) {
+	var expected;
+	var logpmf;
+	var lambda;
+	var delta;
+	var tol;
+	var i;
+	var x;
+	var y;
+
+	expected = largeLambda.expected;
+	x = largeLambda.x;
+	lambda = largeLambda.lambda;
+	for ( i = 0; i < x.length; i++ ) {
+		logpmf = factory( lambda[ i ] );
+		y = logpmf( x[ i ] );
+		if ( y === expected[ i ] ) {
+			t.equal( y, expected[i], 'x: '+x[ i ]+'. lambda: '+lambda[ i ]+', y: '+y+', expected: '+expected[ i ] );
+		} else {
+			delta = abs( y - expected[ i ] );
+			tol = 1.0 * EPS * abs( expected[ i ] );
+			t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. lambda: '+lambda[ i ]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
+		}
+	}
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/test/test.js b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/test/test.js
new file mode 100644
index 000000000000..5d2d6e2f6a68
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/test/test.js
@@ -0,0 +1,38 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var logpmf = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof logpmf, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'attached to the main export is a factory method for generating `logpmf` functions', function test( t ) {
+	t.equal( typeof logpmf.factory, 'function', 'exports a factory method' );
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/test/test.logpmf.js b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/test/test.logpmf.js
new file mode 100644
index 000000000000..42721405ea14
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/logpmf/test/test.logpmf.js
@@ -0,0 +1,140 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var abs = require( '@stdlib/math/base/special/abs' );
+var PINF = require( '@stdlib/constants/float64/pinf' );
+var NINF = require( '@stdlib/constants/float64/ninf' );
+var EPS = require( '@stdlib/constants/float64/eps' );
+var logpmf = require( './../lib' );
+
+
+// FIXTURES //
+
+var smallLambda = require( './fixtures/python/small_lambda.json' );
+var largeLambda = require( './fixtures/python/large_lambda.json' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof logpmf, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'if provided `NaN` for any parameter, the function returns `NaN`', function test( t ) {
+	var y = logpmf( NaN, 1.0 );
+	t.equal( isnan( y ), true, 'returns expected value' );
+	y = logpmf( 0.0, NaN );
+	t.equal( isnan( y ), true, 'returns expected value' );
+	t.end();
+});
+
+tape( 'if provided `+infinity` for `x` and a valid `lambda`, the function returns `-Infinity`', function test( t ) {
+	var y = logpmf( PINF, 0.01 );
+	t.equal( y, NINF, 'returns -Infinity' );
+	t.end();
+});
+
+tape( 'if provided a negative integer for `x` and a valid `lambda`, the function returns `-Infinity`', function test( t ) {
+	var y = logpmf( -20.0, 0.5 );
+	t.equal( y, NINF, 'returns expected value' );
+
+	y = logpmf( -4.0, 0.5 );
+	t.equal( y, NINF, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'if provided a non-integer for `x` and a valid `lambda`, the function returns `-Infinity`', function test( t ) {
+	var y = logpmf( -1.3, 0.5 );
+	t.equal( y, NINF, 'returns expected value' );
+
+	y = logpmf( 2.4, 0.5 );
+	t.equal( y, NINF, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'if provided a shape parameter `lambda` which is nonpositive, the function always returns `NaN`', function test( t ) {
+	var y;
+
+	y = logpmf( 2.0, 0.0 );
+	t.equal( isnan( y ), true, 'returns expected value' );
+
+	y = logpmf( 0.0, -1.5 );
+	t.equal( isnan( y ), true, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function evaluates the logpmf for `x` given small parameter `lambda`', function test( t ) {
+	var expected;
+	var lambda;
+	var delta;
+	var tol;
+	var x;
+	var y;
+	var i;
+
+	expected = smallLambda.expected;
+	x = smallLambda.x;
+	lambda = smallLambda.lambda;
+	for ( i = 0; i < x.length; i++ ) {
+		y = logpmf( x[ i ], lambda[ i ] );
+		if ( y === expected[ i ] ) {
+			t.equal( y, expected[ i ], 'x: '+x[ i ]+'. lambda:'+lambda[ i ]+', y: '+y+', expected: '+expected[ i ] );
+		} else {
+			delta = abs( y - expected[ i ] );
+			tol = 1.0 * EPS * abs( expected[ i ] );
+			t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. lambda: '+lambda[ i ]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
+		}
+	}
+	t.end();
+});
+
+tape( 'the function evaluates the logpmf for `x` given large parameter `lambda`', function test( t ) {
+	var expected;
+	var lambda;
+	var delta;
+	var tol;
+	var x;
+	var y;
+	var i;
+
+	expected = largeLambda.expected;
+	x = largeLambda.x;
+	lambda = largeLambda.lambda;
+	for ( i = 0; i < x.length; i++ ) {
+		y = logpmf( x[ i ], lambda[ i ] );
+		if ( y === expected[ i ] ) {
+			t.equal( y, expected[ i ], 'x: '+x[ i ]+'. lambda:'+lambda[ i ]+', y: '+y+', expected: '+expected[ i ] );
+		} else {
+			delta = abs( y - expected[ i ] );
+			tol = 1.0 * EPS * abs( expected[ i ] );
+			t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. lambda: '+lambda[ i ]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
+		}
+	}
+	t.end();
+});

From cc7736de62cf48e0f31053dc172f78df36920e38 Mon Sep 17 00:00:00 2001
From: Jaysukh Makvana <111515433+Jaysukh-409@users.noreply.github.com>
Date: Thu, 2 Jan 2025 14:33:59 +0530
Subject: [PATCH 03/87] feat: add `stats/base/dists/planck/entropy`

PR-URL: https://github.com/stdlib-js/stdlib/pull/4325
Co-authored-by: Athan Reines <kgryte@gmail.com>
Reviewed-by: Athan Reines <kgryte@gmail.com>
Co-authored-by: stdlib-bot <82920195+stdlib-bot@users.noreply.github.com>
---
 .../stats/base/dists/planck/entropy/README.md | 141 ++++++++++++++++++
 .../planck/entropy/benchmark/benchmark.js     |  52 +++++++
 .../base/dists/planck/entropy/docs/repl.txt   |  27 ++++
 .../planck/entropy/docs/types/index.d.ts      |  56 +++++++
 .../dists/planck/entropy/docs/types/test.ts   |  44 ++++++
 .../dists/planck/entropy/examples/index.js    |  31 ++++
 .../base/dists/planck/entropy/lib/index.js    |  43 ++++++
 .../base/dists/planck/entropy/lib/main.js     |  69 +++++++++
 .../base/dists/planck/entropy/package.json    |  69 +++++++++
 .../entropy/test/fixtures/python/data.json    |   1 +
 .../entropy/test/fixtures/python/runner.py    |  77 ++++++++++
 .../base/dists/planck/entropy/test/test.js    |  82 ++++++++++
 12 files changed, 692 insertions(+)
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/entropy/README.md
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/entropy/benchmark/benchmark.js
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/entropy/docs/repl.txt
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/entropy/docs/types/index.d.ts
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/entropy/docs/types/test.ts
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/entropy/examples/index.js
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/entropy/lib/index.js
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/entropy/lib/main.js
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/entropy/package.json
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/entropy/test/fixtures/python/data.json
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/entropy/test/fixtures/python/runner.py
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/entropy/test/test.js

diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/README.md b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/README.md
new file mode 100644
index 000000000000..f00b69fe23d3
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/README.md
@@ -0,0 +1,141 @@
+<!--
+
+@license Apache-2.0
+
+Copyright (c) 2025 The Stdlib Authors.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+   http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+
+-->
+
+# Entropy
+
+> Planck (discrete exponential) distribution [differential entropy][entropy].
+
+<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->
+
+<section class="intro">
+
+The [differential entropy][entropy] (in [nats][nats]) for a Planck random variable is
+
+<!-- <equation class="equation" label="eq:planck_entropy" align="center" raw="H\left( X \right) = \frac{\lambda e^{-\lambda}}{1 - e^{-\lambda}} - \log\left( 1 - e^{-\lambda} \right)" alt="Differential entropy for a Planck distribution."> -->
+
+```math
+H\left( X \right) = \frac{\lambda e^{-\lambda}}{1 - e^{-\lambda}} - \log\left( 1 - e^{-\lambda} \right)
+```
+
+<!-- </equation> -->
+
+where `λ` is the shape parameter.
+
+</section>
+
+<!-- /.intro -->
+
+<!-- Package usage documentation. -->
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var entropy = require( '@stdlib/stats/base/dists/planck/entropy' );
+```
+
+#### entropy( lambda )
+
+Returns the [differential entropy][entropy] of a Planck distribution with shape parameter `lambda` (in [nats][nats]).
+
+```javascript
+var v = entropy( 0.1 );
+// returns ~3.3030
+
+v = entropy( 1.5 );
+// returns ~0.6833
+```
+
+If provided a shape parameter `lambda` which is `NaN` or nonpositive, the function returns `NaN`.
+
+```javascript
+var v = entropy( NaN );
+// returns NaN
+
+v = entropy( -1.5 );
+// returns NaN
+```
+
+</section>
+
+<!-- /.usage -->
+
+<!-- Package usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="notes">
+
+</section>
+
+<!-- /.notes -->
+
+<!-- Package usage examples. -->
+
+<section class="examples">
+
+## Examples
+
+<!-- eslint no-undef: "error" -->
+
+```javascript
+var uniform = require( '@stdlib/random/array/uniform' );
+var entropy = require( '@stdlib/stats/base/dists/planck/entropy' );
+
+var lambda = uniform( 10, 0.1, 5.0 );
+
+var v;
+var i;
+for ( i = 0; i < lambda.length; i++ ) {
+    v = entropy( lambda[ i ] );
+    console.log( 'λ: %d, H(X;λ): %d', lambda[ i ].toFixed( 4 ), v.toFixed( 4 ) );
+}
+```
+
+</section>
+
+<!-- /.examples -->
+
+<!-- Section to include cited references. If references are included, add a horizontal rule *before* the section. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="references">
+
+</section>
+
+<!-- /.references -->
+
+<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
+
+<section class="related">
+
+</section>
+
+<!-- /.related -->
+
+<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="links">
+
+[entropy]: https://en.wikipedia.org/wiki/Entropy_%28information_theory%29
+
+[nats]: https://en.wikipedia.org/wiki/Nat_%28unit%29
+
+</section>
+
+<!-- /.links -->
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/benchmark/benchmark.js
new file mode 100644
index 000000000000..ce171ab4f102
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/benchmark/benchmark.js
@@ -0,0 +1,52 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pkg = require( './../package.json' ).name;
+var entropy = require( './../lib' );
+
+
+// MAIN //
+
+bench( pkg, function benchmark( b ) {
+	var lambda;
+	var y;
+	var i;
+
+	lambda = uniform( 100, 0.1, 10.0 );
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		y = entropy( lambda[ i % lambda.length ] );
+		if ( isnan( y ) ) {
+			b.fail( 'should not return NaN' );
+		}
+	}
+	b.toc();
+	if ( isnan( y ) ) {
+		b.fail( 'should not return NaN' );
+	}
+	b.pass( 'benchmark finished' );
+	b.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/docs/repl.txt
new file mode 100644
index 000000000000..4e26e6fc5a4d
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/docs/repl.txt
@@ -0,0 +1,27 @@
+
+{{alias}}( λ )
+    Returns the differential entropy of a Planck distribution with shape
+    parameter `λ` (in nats).
+
+    If `λ <= 0`, the function returns `NaN`.
+
+    Parameters
+    ----------
+    λ: number
+        Shape parameter.
+
+    Returns
+    -------
+    out: number
+        Entropy.
+
+    Examples
+    --------
+    > var v = {{alias}}( 0.1 )
+    ~3.3030
+    > v = {{alias}}( 1.5 )
+    ~0.6833
+
+    See Also
+    --------
+
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/docs/types/index.d.ts
new file mode 100644
index 000000000000..0dafc84dc065
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/docs/types/index.d.ts
@@ -0,0 +1,56 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+// TypeScript Version: 4.1
+
+/**
+* Returns the differential entropy of a Planck distribution.
+*
+* ## Notes
+*
+* -   If `lambda <= 0`, the function returns `NaN`.
+*
+* @param lambda - shape parameter
+* @returns differential entropy
+*
+* @example
+* var v = entropy( 0.1 );
+* // returns ~3.3030
+*
+* @example
+* var v = entropy( 1.5 );
+* // returns ~0.6833
+*
+* @example
+* var v = entropy( 2.9 );
+* // returns ~0.2255
+*
+* @example
+* var v = entropy( -1.1 );
+* // returns NaN
+*
+* @example
+* var v = entropy( NaN );
+* // returns NaN
+*/
+declare function entropy( lambda: number ): number;
+
+
+// EXPORTS //
+
+export = entropy;
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/docs/types/test.ts
new file mode 100644
index 000000000000..73b13b540212
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/docs/types/test.ts
@@ -0,0 +1,44 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+import entropy = require( './index' );
+
+
+// TESTS //
+
+// The function returns a number...
+{
+	entropy( 0.3 ); // $ExpectType number
+}
+
+// The compiler throws an error if the function is provided a value other than a number...
+{
+	entropy( true ); // $ExpectError
+	entropy( false ); // $ExpectError
+	entropy( null ); // $ExpectError
+	entropy( undefined ); // $ExpectError
+	entropy( '5' ); // $ExpectError
+	entropy( [] ); // $ExpectError
+	entropy( {} ); // $ExpectError
+	entropy( ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided insufficient arguments...
+{
+	entropy(); // $ExpectError
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/examples/index.js
new file mode 100644
index 000000000000..acdbbbc7cf6b
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/examples/index.js
@@ -0,0 +1,31 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+var uniform = require( '@stdlib/random/array/uniform' );
+var entropy = require( './../lib' );
+
+var lambda = uniform( 10, 0.1, 5.0 );
+
+var v;
+var i;
+for ( i = 0; i < lambda.length; i++ ) {
+	v = entropy( lambda[ i ] );
+	console.log( 'λ: %d, H(X;λ): %d', lambda[ i ].toFixed( 4 ), v.toFixed( 4 ) );
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/lib/index.js b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/lib/index.js
new file mode 100644
index 000000000000..44dd7cf7b679
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/lib/index.js
@@ -0,0 +1,43 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+/**
+* Planck distribution differential entropy.
+*
+* @module @stdlib/stats/base/dists/planck/entropy
+*
+* @example
+* var entropy = require( '@stdlib/stats/base/dists/planck/entropy' );
+*
+* var v = entropy( 0.1 );
+* // returns ~3.3030
+*
+* v = entropy( 1.5 );
+* // returns ~0.6833
+*/
+
+// MODULES //
+
+var main = require( './main.js' );
+
+
+// EXPORTS //
+
+module.exports = main;
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/lib/main.js
new file mode 100644
index 000000000000..ac3db097a539
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/lib/main.js
@@ -0,0 +1,69 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var exp = require( '@stdlib/math/base/special/exp' );
+var expm1 = require( '@stdlib/math/base/special/expm1' );
+var ln = require( '@stdlib/math/base/special/ln' );
+
+
+// MAIN //
+
+/**
+* Returns the differential entropy of a Planck distribution.
+*
+* @param {PositiveNumber} lambda - shape parameter
+* @returns {PositiveNumber} differential entropy
+*
+* @example
+* var v = entropy( 0.1 );
+* // returns ~3.3030
+*
+* @example
+* var v = entropy( 1.5 );
+* // returns ~0.6833
+*
+* @example
+* var v = entropy( 2.9 );
+* // returns ~0.2255
+*
+* @example
+* var v = entropy( -1.1 );
+* // returns NaN
+*
+* @example
+* var v = entropy( NaN );
+* // returns NaN
+*/
+function entropy( lambda ) {
+	var c;
+	if ( isnan( lambda ) || lambda <= 0.0 ) {
+		return NaN;
+	}
+	c = -expm1( -lambda );
+	return ( lambda * exp( -lambda ) / c ) - ln( c );
+}
+
+
+// EXPORTS //
+
+module.exports = entropy;
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/package.json b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/package.json
new file mode 100644
index 000000000000..1c6b072fbcf1
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/package.json
@@ -0,0 +1,69 @@
+{
+  "name": "@stdlib/stats/base/dists/planck/entropy",
+  "version": "0.0.0",
+  "description": "Planck (discrete exponential) distribution differential entropy.",
+  "license": "Apache-2.0",
+  "author": {
+    "name": "The Stdlib Authors",
+    "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+  },
+  "contributors": [
+    {
+      "name": "The Stdlib Authors",
+      "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+    }
+  ],
+  "main": "./lib",
+  "directories": {
+    "benchmark": "./benchmark",
+    "doc": "./docs",
+    "example": "./examples",
+    "lib": "./lib",
+    "test": "./test"
+  },
+  "types": "./docs/types",
+  "scripts": {},
+  "homepage": "https://github.com/stdlib-js/stdlib",
+  "repository": {
+    "type": "git",
+    "url": "git://github.com/stdlib-js/stdlib.git"
+  },
+  "bugs": {
+    "url": "https://github.com/stdlib-js/stdlib/issues"
+  },
+  "dependencies": {},
+  "devDependencies": {},
+  "engines": {
+    "node": ">=0.10.0",
+    "npm": ">2.7.0"
+  },
+  "os": [
+    "aix",
+    "darwin",
+    "freebsd",
+    "linux",
+    "macos",
+    "openbsd",
+    "sunos",
+    "win32",
+    "windows"
+  ],
+  "keywords": [
+    "stdlib",
+    "stdmath",
+    "statistics",
+    "stats",
+    "distribution",
+    "dist",
+    "parameter",
+    "memoryless",
+    "life-time",
+    "discrete",
+    "entropy",
+    "shannon",
+    "information",
+    "nats",
+    "planck",
+    "univariate"
+  ]
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/test/fixtures/python/data.json b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/test/fixtures/python/data.json
new file mode 100644
index 000000000000..14e43954d8c1
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/test/fixtures/python/data.json
@@ -0,0 +1 @@
+{"lambda": [11.455931688414339, 12.049886662295279, 19.686522775043272, 11.015032049363455, 17.296911359484074, 15.689532162118596, 3.3145508589156147, 5.504482683615719, 6.576128114123461, 13.375086796004984, 10.34069873156734, 9.72980253893475, 11.348605319802008, 6.667030734470609, 11.327226583010956, 18.735451535117857, 1.3853781760477135, 12.9034695366267, 12.229488830745638, 11.965908082806129, 5.264935976789071, 2.6688592326814997, 13.420190489773617, 15.02336736559425, 18.62421960884803, 3.3246336724638903, 16.642827792190545, 7.838647648093957, 19.32238077907249, 8.713855968469682, 13.151286309768249, 12.72787815708906, 1.8364861594947568, 19.45541941060595, 10.207110298518419, 13.101057171120772, 16.198836821780027, 16.02139631723581, 11.327805373182079, 11.719271917838153, 19.27900725230956, 15.14949615392188, 10.788035015716083, 4.629952031050896, 7.967138676369714, 16.388013653758854, 9.781777196936668, 1.489720133199488, 4.762911375368262, 17.085111042135125, 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diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/test/fixtures/python/runner.py b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/test/fixtures/python/runner.py
new file mode 100644
index 000000000000..8b3d34e9c760
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/test/fixtures/python/runner.py
@@ -0,0 +1,77 @@
+#!/usr/bin/env python
+#
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""Generate fixtures."""
+
+import os
+import json
+import numpy as np
+from scipy.stats import planck
+
+# Get the file path:
+FILE = os.path.realpath(__file__)
+
+# Extract the directory in which this file resides:
+DIR = os.path.dirname(FILE)
+
+
+def gen(lam, name):
+    """
+    Generate fixture data and write to file.
+
+    # Arguments
+
+    * `lam`: shape parameter.
+    * `name::str`: output filename.
+
+    # Examples
+
+    ```python
+    python> lam = np.random.rand(1000) * 20.0
+    python> gen(lam, "data.json")
+    ```
+    """
+    # Compute entropy values:
+    z = np.array(planck.entropy(lam))
+
+    # Store data to be written to file as a dictionary:
+    data = {
+        "lambda": lam.tolist(),
+        "expected": z.tolist()
+    }
+
+    # Based on the script directory, create an output filepath:
+    filepath = os.path.join(DIR, name)
+
+    # Write the data to the output filepath as JSON:
+    with open(filepath, "w", encoding='utf-8') as outfile:
+        json.dump(data, outfile)
+
+    # Include trailing newline:
+    with open(filepath, "a", encoding='utf-8') as outfile:
+        outfile.write("\n")
+
+
+def main():
+    """Generate fixture data."""
+    lam = np.random.rand(1000) * 20.0
+    gen(lam, "data.json")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/test/test.js b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/test/test.js
new file mode 100644
index 000000000000..4901f2c3368f
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/entropy/test/test.js
@@ -0,0 +1,82 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var abs = require( '@stdlib/math/base/special/abs' );
+var EPS = require( '@stdlib/constants/float64/eps' );
+var entropy = require( './../lib' );
+
+
+// FIXTURES //
+
+var data = require( './fixtures/python/data.json' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof entropy, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'if provided `NaN` for `lambda`, the function returns `NaN`', function test( t ) {
+	var v = entropy( NaN );
+	t.equal( isnan( v ), true, 'returns expected value' );
+	t.end();
+});
+
+tape( 'if provided a shape parameter `lambda` which is nonpositive, the function returns `NaN`', function test( t ) {
+	var v;
+
+	v = entropy( 0.0 );
+	t.equal( isnan( v ), true, 'returns expected value' );
+
+	v = entropy( -1.0 );
+	t.equal( isnan( v ), true, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function returns the entropy of a Planck distribution', function test( t ) {
+	var expected;
+	var lambda;
+	var delta;
+	var tol;
+	var i;
+	var y;
+
+	expected = data.expected;
+	lambda = data.lambda;
+	for ( i = 0; i < expected.length; i++ ) {
+		y = entropy( lambda[ i ] );
+		if ( y === expected[ i ] ) {
+			t.equal( y, expected[ i ], 'lambda: '+lambda[ i ]+', y: '+y+', expected: '+expected[ i ] );
+		} else {
+			delta = abs( y - expected[ i ] );
+			tol = 2.0 * EPS * abs( expected[ i ] );
+			t.ok( delta <= tol, 'within tolerance. lambda: '+lambda[ i ]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
+		}
+	}
+	t.end();
+});

From 0e7298ca00456449550fc4af203d60068f5175bd Mon Sep 17 00:00:00 2001
From: Jaysukh Makvana <111515433+Jaysukh-409@users.noreply.github.com>
Date: Thu, 2 Jan 2025 14:40:39 +0530
Subject: [PATCH 04/87] feat: add `stats/base/dists/planck/quantile`

PR-URL: https://github.com/stdlib-js/stdlib/pull/4392
Co-authored-by: Athan Reines <kgryte@gmail.com>
Reviewed-by: Athan Reines <kgryte@gmail.com>
Co-authored-by: stdlib-bot <82920195+stdlib-bot@users.noreply.github.com>
---
 .../base/dists/planck/quantile/README.md      | 154 ++++++++++++++++++
 .../planck/quantile/benchmark/benchmark.js    |  78 +++++++++
 .../base/dists/planck/quantile/docs/repl.txt  |  74 +++++++++
 .../planck/quantile/docs/types/index.d.ts     | 132 +++++++++++++++
 .../dists/planck/quantile/docs/types/test.ts  |  98 +++++++++++
 .../dists/planck/quantile/examples/index.js   |  32 ++++
 .../base/dists/planck/quantile/lib/factory.js |  80 +++++++++
 .../base/dists/planck/quantile/lib/index.js   |  60 +++++++
 .../base/dists/planck/quantile/lib/main.js    |  83 ++++++++++
 .../base/dists/planck/quantile/package.json   |  67 ++++++++
 .../test/fixtures/python/large_lambda.json    |   1 +
 .../quantile/test/fixtures/python/runner.py   |  87 ++++++++++
 .../test/fixtures/python/small_lambda.json    |   1 +
 .../planck/quantile/test/test.factory.js      | 148 +++++++++++++++++
 .../base/dists/planck/quantile/test/test.js   |  38 +++++
 .../planck/quantile/test/test.quantile.js     | 111 +++++++++++++
 16 files changed, 1244 insertions(+)
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/quantile/README.md
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/quantile/benchmark/benchmark.js
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/quantile/docs/repl.txt
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/quantile/docs/types/index.d.ts
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/quantile/docs/types/test.ts
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/quantile/examples/index.js
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/quantile/lib/factory.js
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/quantile/lib/index.js
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/quantile/lib/main.js
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/quantile/package.json
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/quantile/test/fixtures/python/large_lambda.json
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/quantile/test/fixtures/python/runner.py
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/quantile/test/fixtures/python/small_lambda.json
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/quantile/test/test.factory.js
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/quantile/test/test.js
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/planck/quantile/test/test.quantile.js

diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/README.md b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/README.md
new file mode 100644
index 000000000000..68e2a38f95bb
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/README.md
@@ -0,0 +1,154 @@
+<!--
+
+@license Apache-2.0
+
+Copyright (c) 2025 The Stdlib Authors.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+   http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+
+-->
+
+# Quantile Function
+
+> Planck (discrete exponential) distribution [quantile function][quantile-function].
+
+<section class="intro">
+
+The [quantile function][quantile-function] for a Planck random variable is
+
+<!-- <equation class="equation" label="eq:planck_quantile_function" align="center" raw="Q(p;\lambda) = \left\lceil -\frac{\ln(1-p)}{\lambda} - 1 \right\rceil" alt="Quantile function for a Planck distribution."> -->
+
+```math
+Q(p;\lambda) = \left\lceil -\frac{\ln(1-p)}{\lambda} \right\rceil \!-1
+```
+
+<!-- </equation> -->
+
+for `0 < p < 1` and where `λ` is the shape parameter.
+
+</section>
+
+<!-- /.intro -->
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var quantile = require( '@stdlib/stats/base/dists/planck/quantile' );
+```
+
+#### quantile( p, lambda )
+
+Evaluates the [quantile function][quantile-function] for a Planck distribution with shape parameter `lambda` at a probability `p`.
+
+```javascript
+var y = quantile( 0.8, 0.4 );
+// returns 4
+
+y = quantile( 0.5, 1.4 );
+// returns 0
+
+y = quantile( 0.9, 2.1 );
+// returns 1
+```
+
+If provided an input probability `p` outside the interval `[0,1]`, the function returns `NaN`.
+
+```javascript
+var y = quantile( 1.9, 0.5 );
+// returns NaN
+
+y = quantile( -0.1, 0.5 );
+// returns NaN
+```
+
+If provided `NaN` as any argument, the function returns `NaN`.
+
+```javascript
+var y = quantile( NaN, 1.0 );
+// returns NaN
+
+y = quantile( 0.0, NaN );
+// returns NaN
+```
+
+If provided a shape parameter `lambda` which is nonpositive, the function returns `NaN`.
+
+```javascript
+var y = quantile( 0.4, -1.0 );
+// returns NaN
+```
+
+#### quantile.factory( lambda )
+
+Returns a function for evaluating the [quantile function][quantile-function] for a Planck distribution with shape parameter `lambda`.
+
+```javascript
+var myquantile = quantile.factory( 0.4 );
+var y = myquantile( 0.4 );
+// returns 1
+
+y = myquantile( 0.8 );
+// returns 4
+
+y = myquantile( 1.0 );
+// returns Infinity
+```
+
+</section>
+
+<!-- /.usage -->
+
+<section class="examples">
+
+## Examples
+
+<!-- eslint no-undef: "error" -->
+
+```javascript
+var uniform = require( '@stdlib/random/array/uniform' );
+var quantile = require( '@stdlib/stats/base/dists/planck/quantile' );
+
+var lambda = uniform( 10, 0.1, 10.0 );
+var p = uniform( 10, 0.0, 1.0 );
+
+var y;
+var i;
+for ( i = 0; i < lambda.length; i++ ) {
+    y = quantile( p[ i ], lambda[ i ] );
+    console.log( 'p: %d, λ: %d, Q(p;λ): %d', p[ i ].toFixed( 4 ), lambda[ i ].toFixed( 4 ), y.toFixed( 4 ) );
+}
+```
+
+</section>
+
+<!-- /.examples -->
+
+<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
+
+<section class="related">
+
+</section>
+
+<!-- /.related -->
+
+<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="links">
+
+[quantile-function]: https://en.wikipedia.org/wiki/Quantile_function
+
+</section>
+
+<!-- /.links -->
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/benchmark/benchmark.js
new file mode 100644
index 000000000000..c4882aa6ecdb
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/benchmark/benchmark.js
@@ -0,0 +1,78 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pkg = require( './../package.json' ).name;
+var quantile = require( './../lib' );
+
+
+// MAIN //
+
+bench( pkg, function benchmark( b ) {
+	var lambda;
+	var p;
+	var y;
+	var i;
+
+	p = uniform( 100, 0.0, 1.0 );
+	lambda = uniform( 100, 0.1, 10.0 );
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		y = quantile( p[ i % p.length ], lambda[ i % lambda.length ] );
+		if ( isnan( y ) ) {
+			b.fail( 'should not return NaN' );
+		}
+	}
+	b.toc();
+	if ( isnan( y ) ) {
+		b.fail( 'should not return NaN' );
+	}
+	b.pass( 'benchmark finished' );
+	b.end();
+});
+
+bench( pkg+':factory', function benchmark( b ) {
+	var myquantile;
+	var p;
+	var y;
+	var i;
+
+	myquantile = quantile.factory( 0.3 );
+	p = uniform( 100, 0.0, 1.0 );
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		y = myquantile( p[ i % p.length ] );
+		if ( isnan( y ) ) {
+			b.fail( 'should not return NaN' );
+		}
+	}
+	b.toc();
+	if ( isnan( y ) ) {
+		b.fail( 'should not return NaN' );
+	}
+	b.pass( 'benchmark finished' );
+	b.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/docs/repl.txt
new file mode 100644
index 000000000000..7ef7c3b90665
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/docs/repl.txt
@@ -0,0 +1,74 @@
+
+{{alias}}( p, λ )
+    Evaluates the quantile function for a Planck distribution with shape
+    parameter `λ` at a probability `p`.
+
+    If `p < 0` or `p > 1`, the function returns `NaN`.
+
+    If `λ <= 0`, the function returns `NaN`.
+
+    If provided `NaN` as any argument, the function returns `NaN`.
+
+    Parameters
+    ----------
+    p: number
+        Input probability.
+
+    λ: number
+        Shape parameter.
+
+    Returns
+    -------
+    out: number
+        Evaluated quantile function.
+
+    Examples
+    --------
+    > var y = {{alias}}( 0.8, 0.4 )
+    4
+    > y = {{alias}}( 0.5, 1.4 )
+    0
+    > y = {{alias}}( 0.9, 2.1 )
+    1
+
+    > y = {{alias}}( 0.2, -0.1 )
+    NaN
+
+    > y = {{alias}}( NaN, 0.8 )
+    NaN
+    > y = {{alias}}( 0.4, NaN )
+    NaN
+
+    > y = {{alias}}( -0.5, 1.0 )
+    NaN
+    > y = {{alias}}( 1.5, 1.0 )
+    NaN
+
+
+{{alias}}.factory( λ )
+    Returns a function for evaluating the quantile function of a Planck
+    distribution with shape parameter `λ`.
+
+    Parameters
+    ----------
+    λ: number
+        Shape parameter.
+
+    Returns
+    -------
+    quantile: Function
+        Quantile function.
+
+    Examples
+    --------
+    > var myquantile = {{alias}}.factory( 0.4 );
+    > var y = myquantile( 0.4 )
+    1
+    > y = myquantile( 0.8 )
+    4
+    > y = myquantile( 1.0 )
+    Infinity
+
+    See Also
+    --------
+
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/docs/types/index.d.ts
new file mode 100644
index 000000000000..190f02fb9c86
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/docs/types/index.d.ts
@@ -0,0 +1,132 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+// TypeScript Version: 4.1
+
+/**
+* Evaluates the quantile function for a Planck distribution.
+*
+* ## Notes
+*
+* -   If `p < 0` or `p > 1`, the function returns `NaN`.
+*
+* @param p - input value
+* @returns evaluated quantile function
+*/
+type Unary = ( p: number ) => number;
+
+/**
+* Interface for the quantile function of a Planck distribution.
+*/
+interface Quantile {
+	/**
+	* Evaluates the quantile function for a Planck distribution with shape parameter `lambda` at a probability `p`.
+	*
+	* ## Notes
+	*
+	* -   If `p < 0` or `p > 1`, the function returns `NaN`.
+	* -   If `lambda <= 0`, the function returns `NaN`.
+	*
+	* @param p - input value
+	* @param lambda - shape parameter
+	* @returns evaluated quantile function
+	*
+	* @example
+	* var y = quantile( 0.8, 0.4 );
+	* // returns 4
+	*
+	* @example
+	* var y = quantile( 0.5, 1.4 );
+	* // returns 0
+	*
+	* @example
+	* var y = quantile( 0.9, 2.1 );
+	* // returns 1
+	*
+	* @example
+	* var y = quantile( 0.2, -0.1 );
+	* // returns NaN
+	*
+	* @example
+	* var y = quantile( NaN, 0.8 );
+	* // returns NaN
+	*
+	* @example
+	* var y = quantile( 0.4, NaN );
+	* // returns NaN
+	*
+	* @example
+	* var y = quantile( -0.5, 1.0 );
+	* // returns NaN
+	*
+	* @example
+	* var y = quantile( 1.5, 1.0 );
+	* // returns NaN
+	*/
+	( p: number, lambda: number ): number;
+
+	/**
+	* Returns a function for evaluating the quantile function for a Planck distribution with shape parameter `lambda`.
+	*
+	* @param lambda - shape parameter
+	* @returns quantile function
+	*
+	* @example
+	* var myquantile = quantile.factory( 0.4 );
+	* var y = myquantile( 0.4 );
+	* // returns 1
+	*
+	* y = myquantile( 0.8 );
+	* // returns 4
+	*
+	* y = myquantile( 1.0 );
+	* // returns Infinity
+	*/
+	factory( lambda: number ): Unary;
+}
+
+/**
+* Evaluates the quantile function for a Planck distribution with shape parameter `lambda` at a probability `p`.
+*
+* @param p - input value
+* @param lambda - shape parameter
+* @returns evaluated quantile function
+*
+* @example
+* var y = quantile( 0.8, 0.4 );
+* // returns 4
+*
+* y = quantile( 0.5, 1.4 );
+* // returns 0
+*
+* var myquantile = quantile.factory( 0.4 );
+* y = myquantile( 0.4 );
+* // returns 1
+*
+* y = myquantile( 0.8 );
+* // returns 4
+*
+* y = myquantile( 1.0 );
+* // returns Infinity
+*/
+declare var quantile: Quantile;
+
+
+// EXPORTS //
+
+export = quantile;
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/docs/types/test.ts b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/docs/types/test.ts
new file mode 100644
index 000000000000..99fbca207304
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/docs/types/test.ts
@@ -0,0 +1,98 @@
+/*
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+import quantile = require( './index' );
+
+
+// TESTS //
+
+// The function returns a number...
+{
+	quantile( 0.2, 0.2 ); // $ExpectType number
+	quantile( 0.1, 0.2 ); // $ExpectType number
+}
+
+// The compiler throws an error if the function is provided values other than two numbers...
+{
+	quantile( true, 0.3 ); // $ExpectError
+	quantile( false, 0.2 ); // $ExpectError
+	quantile( '5', 0.1 ); // $ExpectError
+	quantile( [], 0.1 ); // $ExpectError
+	quantile( {}, 0.2 ); // $ExpectError
+	quantile( ( x: number ): number => x, 0.2 ); // $ExpectError
+
+	quantile( 0.9, true ); // $ExpectError
+	quantile( 0.9, false ); // $ExpectError
+	quantile( 0.5, '5' ); // $ExpectError
+	quantile( 0.8, [] ); // $ExpectError
+	quantile( 0.9, {} ); // $ExpectError
+	quantile( 0.8, ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the function is provided an unsupported number of arguments...
+{
+	quantile(); // $ExpectError
+	quantile( 0.2 ); // $ExpectError
+	quantile( 0.2, 0.8, 4.0 ); // $ExpectError
+}
+
+// Attached to main export is a `factory` method which returns a function...
+{
+	quantile.factory( 0.3 ); // $ExpectType Unary
+}
+
+// The `factory` method returns a function which returns a number...
+{
+	const fcn = quantile.factory( 0.3 );
+	fcn( 0.2 ); // $ExpectType number
+}
+
+// The compiler throws an error if the function returned by the `factory` method is provided an invalid argument...
+{
+	const fcn = quantile.factory( 0.3 );
+	fcn( true ); // $ExpectError
+	fcn( false ); // $ExpectError
+	fcn( '5' ); // $ExpectError
+	fcn( [] ); // $ExpectError
+	fcn( {} ); // $ExpectError
+	fcn( ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the function returned by the `factory` method is provided an unsupported number of arguments...
+{
+	const fcn = quantile.factory( 0.3 );
+	fcn(); // $ExpectError
+	fcn( 0.2, 0.8 ); // $ExpectError
+	fcn( 0.2, 0.8, 1.0 ); // $ExpectError
+}
+
+// The compiler throws an error if the `factory` method is provided a value other than a number...
+{
+	quantile.factory( true ); // $ExpectError
+	quantile.factory( false ); // $ExpectError
+	quantile.factory( '5' ); // $ExpectError
+	quantile.factory( [] ); // $ExpectError
+	quantile.factory( {} ); // $ExpectError
+	quantile.factory( ( x: number ): number => x ); // $ExpectError
+}
+
+// The compiler throws an error if the `factory` method is provided an unsupported number of arguments...
+{
+	quantile.factory( 0.2, 0.2 ); // $ExpectError
+	quantile.factory( 0.3, 0.4, 8.0 ); // $ExpectError
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/examples/index.js b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/examples/index.js
new file mode 100644
index 000000000000..a6d226c46b3f
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/examples/index.js
@@ -0,0 +1,32 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+var uniform = require( '@stdlib/random/array/uniform' );
+var quantile = require( './../lib' );
+
+var lambda = uniform( 10, 0.1, 10.0 );
+var p = uniform( 10, 0.0, 1.0 );
+
+var y;
+var i;
+for ( i = 0; i < lambda.length; i++ ) {
+	y = quantile( p[ i ], lambda[ i ] );
+	console.log( 'p: %d, λ: %d, Q(p;λ): %d', p[ i ].toFixed( 4 ), lambda[ i ].toFixed( 4 ), y.toFixed( 4 ) );
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/lib/factory.js b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/lib/factory.js
new file mode 100644
index 000000000000..07c75e225c4a
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/lib/factory.js
@@ -0,0 +1,80 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var constantFunction = require( '@stdlib/utils/constant-function' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var ceil = require( '@stdlib/math/base/special/ceil' );
+var ln = require( '@stdlib/math/base/special/ln' );
+var PINF = require( '@stdlib/constants/float64/pinf' );
+
+
+// MAIN //
+
+/**
+* Returns a function for evaluating the quantile function for a Planck distribution with shape parameter `lambda`.
+*
+* @param {PositiveNumber} lambda - success probability
+* @returns {Function} quantile function
+*
+* @example
+* var quantile = factory( 0.4 );
+* var y = quantile( 0.4 );
+* // returns 1
+*
+* y = quantile( 0.8 );
+* // returns 4
+*
+* y = quantile( 1.0 );
+* // returns Infinity
+*/
+function factory( lambda ) {
+	if ( isnan( lambda ) || lambda <= 0.0 ) {
+		return constantFunction( NaN );
+	}
+	return quantile;
+
+	/**
+	* Evaluates the quantile function for a Planck distribution.
+	*
+	* @private
+	* @param {Probability} p - input value
+	* @returns {NonNegativeInteger} evaluated quantile function
+	*
+	* @example
+	* var y = quantile( 0.3 );
+	* // returns <number>
+	*/
+	function quantile( p ) {
+		if ( isnan( p ) || p < 0.0 || p > 1.0 ) {
+			return NaN;
+		}
+		if ( p === 1.0 ) {
+			return PINF;
+		}
+		return ceil( -ln( 1.0-p ) / lambda ) - 1.0;
+	}
+}
+
+
+// EXPORTS //
+
+module.exports = factory;
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/lib/index.js b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/lib/index.js
new file mode 100644
index 000000000000..fed299058b43
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/lib/index.js
@@ -0,0 +1,60 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+/**
+* Planck distribution quantile function.
+*
+* @module @stdlib/stats/base/dists/planck/quantile
+*
+* @example
+* var quantile = require( '@stdlib/stats/base/dists/planck/quantile' );
+*
+* var y = quantile( 0.8, 0.4 );
+* // returns 4
+*
+* y = quantile( 0.5, 1.4 );
+* // returns 0
+*
+* var myquantile = quantile.factory( 0.4 );
+* y = myquantile( 0.4 );
+* // returns 1
+*
+* y = myquantile( 0.8 );
+* // returns 4
+*
+* y = myquantile( 1.0 );
+* // returns Infinity
+*/
+
+// MODULES //
+
+var setReadOnly = require( '@stdlib/utils/define-nonenumerable-read-only-property' );
+var main = require( './main.js' );
+var factory = require( './factory.js' );
+
+
+// MAIN //
+
+setReadOnly( main, 'factory', factory );
+
+
+// EXPORTS //
+
+module.exports = main;
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/lib/main.js
new file mode 100644
index 000000000000..52f5fef9da70
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/lib/main.js
@@ -0,0 +1,83 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var ceil = require( '@stdlib/math/base/special/ceil' );
+var ln = require( '@stdlib/math/base/special/ln' );
+var PINF = require( '@stdlib/constants/float64/pinf' );
+
+
+// MAIN //
+
+/**
+* Evaluates the quantile function for a Planck distribution with shape parameter `lambda` at a probability `p`.
+*
+* @param {Probability} p - input value
+* @param {PositiveNumber} lambda - shape parameter
+* @returns {NonNegativeInteger} evaluated quantile function
+*
+* @example
+* var y = quantile( 0.8, 0.4 );
+* // returns 4
+*
+* @example
+* var y = quantile( 0.5, 1.4 );
+* // returns 0
+*
+* @example
+* var y = quantile( 0.9, 2.1 );
+* // returns 1
+*
+* @example
+* var y = quantile( 0.2, -0.1 );
+* // returns NaN
+*
+* @example
+* var y = quantile( NaN, 0.8 );
+* // returns NaN
+*
+* @example
+* var y = quantile( 0.4, NaN );
+* // returns NaN
+*
+* @example
+* var y = quantile( -0.5, 1.0 );
+* // returns NaN
+*
+* @example
+* var y = quantile( 1.5, 1.0 );
+* // returns NaN
+*/
+function quantile( p, lambda ) {
+	if ( isnan( lambda ) || isnan( p ) || lambda <= 0.0 || p < 0.0 || p > 1.0 ) { // eslint-disable-line max-len
+		return NaN;
+	}
+	if ( p === 1.0 ) {
+		return PINF;
+	}
+	return ceil( -ln( 1.0-p ) / lambda ) - 1.0;
+}
+
+
+// EXPORTS //
+
+module.exports = quantile;
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/package.json b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/package.json
new file mode 100644
index 000000000000..84ddb4a3d480
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/package.json
@@ -0,0 +1,67 @@
+{
+  "name": "@stdlib/stats/base/dists/planck/quantile",
+  "version": "0.0.0",
+  "description": "Planck (discrete exponential) distribution quantile function.",
+  "license": "Apache-2.0",
+  "author": {
+    "name": "The Stdlib Authors",
+    "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+  },
+  "contributors": [
+    {
+      "name": "The Stdlib Authors",
+      "url": "https://github.com/stdlib-js/stdlib/graphs/contributors"
+    }
+  ],
+  "main": "./lib",
+  "directories": {
+    "benchmark": "./benchmark",
+    "doc": "./docs",
+    "example": "./examples",
+    "lib": "./lib",
+    "test": "./test"
+  },
+  "types": "./docs/types",
+  "scripts": {},
+  "homepage": "https://github.com/stdlib-js/stdlib",
+  "repository": {
+    "type": "git",
+    "url": "git://github.com/stdlib-js/stdlib.git"
+  },
+  "bugs": {
+    "url": "https://github.com/stdlib-js/stdlib/issues"
+  },
+  "dependencies": {},
+  "devDependencies": {},
+  "engines": {
+    "node": ">=0.10.0",
+    "npm": ">2.7.0"
+  },
+  "os": [
+    "aix",
+    "darwin",
+    "freebsd",
+    "linux",
+    "macos",
+    "openbsd",
+    "sunos",
+    "win32",
+    "windows"
+  ],
+  "keywords": [
+    "stdlib",
+    "stdmath",
+    "statistics",
+    "stats",
+    "distribution",
+    "dist",
+    "probability",
+    "cdf",
+    "inverse",
+    "failure times",
+    "memoryless property",
+    "discrete",
+    "planck",
+    "univariate"
+  ]
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/test/fixtures/python/large_lambda.json b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/test/fixtures/python/large_lambda.json
new file mode 100644
index 000000000000..1f8d1bd1ebe6
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/test/fixtures/python/large_lambda.json
@@ -0,0 +1 @@
+{"r": [0.9544555848274979, 0.7403580906863967, 0.2519726241201691, 0.9066083415025643, 0.10472160992685564, 0.17746797020152416, 0.9591828428488697, 0.7304673004774859, 0.635565019532496, 0.39282381518757303, 0.4342203791048863, 0.21925873707696664, 0.7533254901997656, 0.9177567133953949, 0.06207527148340519, 0.317107207060741, 0.8223198170589929, 0.5283732324772701, 0.1614598319686854, 0.6686071724611999, 0.8169267398292239, 0.042033087993004425, 0.780506415802706, 0.8868025369421134, 0.14518278699465836, 0.6013787715088863, 0.4273210250402978, 0.2756699240950683, 0.1759593701987915, 0.23163581285215884, 0.24775025776554183, 0.1549499044997137, 0.8839846451544837, 0.16823237306824246, 0.07461839268650572, 0.9129877527174196, 0.4076927432913836, 0.43643543977611576, 0.7884021058143497, 0.5531586070578656, 0.8751417613252777, 0.12481549351198806, 0.8549237378239185, 0.21318434378215012, 0.007827108820905981, 0.03309542095571594, 0.9005305401667352, 0.4291683395170298, 0.042759531655934935, 0.9501902588323883, 0.4810228819919401, 0.4941627251415758, 0.8965897060168878, 0.1377988383125328, 0.6631699406355545, 0.4186391484678994, 0.17073572969163264, 0.8279123511189063, 0.5797688649485492, 0.5966264660743866, 0.16994069084040753, 0.09523572082621146, 0.05427273742722638, 0.9761650309531114, 0.26897955574664456, 0.6901836132088518, 0.37367553303509027, 0.12079493858635781, 0.09204159010612012, 0.6622925808038305, 0.09022398616874594, 0.6275171224837608, 0.8272869195279748, 0.016452105779083848, 0.5984856275971281, 0.08178684809601466, 0.3495744781905695, 0.2013859253761504, 0.9690800010631048, 0.18132349309616191, 0.11950144359254733, 0.12729153196596377, 0.5698557061146327, 0.45611478299972164, 0.8003493939447622, 0.5322317625732769, 0.07054389088868873, 0.14901169215991106, 0.6280833204346117, 0.605316111379996, 0.23684720523700153, 0.053575685743366463, 0.579608898201778, 0.5241481067933355, 0.3917847074759454, 0.9821917380752108, 0.15744429838209373, 0.8904051177102867, 0.9996922539902703, 0.49761196910095007, 0.6188648832751831, 0.06840736378637113, 0.17016400262944198, 0.7204086858683758, 0.9903701261927274, 0.41671729969797267, 0.3731318937142717, 0.2918054772375278, 0.5804303054077983, 0.09043978994369983, 0.7104915043954665, 0.9408814051587858, 0.06609737716740371, 0.18864212554170356, 0.20098788460686856, 0.39087779508615295, 0.43559137957645877, 0.8180935539971042, 0.378152108932039, 0.5202737798238333, 0.2607998399624405, 0.6610476261694279, 0.279741026385396, 0.6984025350272727, 0.8379216646052672, 0.6183665320047211, 0.33855163035899494, 0.9137593260740818, 0.4424961407937579, 0.23063911182349284, 0.9553761789496812, 0.3986303898391891, 0.431473149477129, 0.06951053643354765, 0.17521439897021274, 0.25508549472311404, 0.3668454727262611, 0.3780250702729926, 0.2588493004995315, 0.11767379495387431, 0.6743467268464577, 0.12775651343437677, 0.6154068406003567, 0.7778870992661352, 0.08078358949913012, 0.10314977400212233, 0.36654207823600204, 0.2832565347124395, 0.18492498435134652, 0.7143114292485556, 0.7527501462134853, 0.7242625134047287, 0.9071346752916971, 0.2676443856151459, 0.9906997532108772, 0.6009670366238961, 0.5643890138246974, 0.9540917307352753, 0.6730226495232922, 0.7837448832278171, 0.9905521011656488, 0.810467573964875, 0.48239383675983005, 0.648068523229573, 0.6145483046932879, 0.5741120864168191, 0.4038078262125615, 0.42644200078978656, 0.6374993536204376, 0.3534703176857811, 0.6963738895040151, 0.8949055438535621, 0.044731905885125545, 0.4685211726094758, 0.8986753697340045, 0.4614026511071374, 0.6460808785256439, 0.0934692143389162, 0.5260559468343587, 0.5470169316904766, 0.35003798504907135, 0.3947449215703206, 0.8687929477999942, 0.8612764940958464, 0.809632784012324, 0.20324278986453603, 0.5871114827976872, 0.6337471655213693, 0.01789081178831675, 0.8775392469317896, 0.4303173279841763, 0.4504004351918296, 0.5715842358767452, 0.24816787171039034, 0.8345900025729356, 0.4204083834979071, 0.48082726389359987, 0.8962695754660712, 0.5509359674545503, 0.900293435069848, 0.49803004695431297, 0.9592123436575225, 0.7197896056812687, 0.663512260604006, 0.24671596824031905, 0.04435449642575584, 0.7489436338767156, 0.8942620781577427, 0.10982654165787609, 0.7309359345915588, 0.09805112287692752, 0.7612158674636504, 0.6491543485784098, 0.4396606922088464, 0.7873692622868186, 0.21747321676179543, 0.27819978467955697, 0.025859952034126277, 0.07369535293179252, 0.2332950590924373, 0.2807993386343115, 0.780907869685212, 0.6275810987026325, 0.8181344558347825, 0.3257909457189473, 0.5782287766784618, 0.4000159832728678, 0.7889837221179912, 0.23825799859099672, 0.7288098732098229, 0.9236659819669766, 0.8404137227938077, 0.6845162466664836, 0.5033302841847802, 0.7903054656220869, 0.09113763345188708, 0.5814958327054145, 0.8809116832409908, 0.9122823453363125, 0.40810224895261027, 0.4993163281026095, 0.4982581239593208, 0.2438053546265364, 0.5895115366310014, 0.41462421011230177, 0.08018617084902369, 0.08344834470301987, 0.9537411798415036, 0.4024424493128791, 0.4349033379456855, 0.5894778789168267, 0.525395259759944, 0.742384062268148, 0.5897518228228003, 0.5746091605842067, 0.48455023970844235, 0.9971742090272192, 0.5801216779588502, 0.3453488874633682, 0.837271110948858, 0.5720494726169524, 0.5510882378156213, 0.1474026712307962, 0.8792405390394964, 0.1545575358395126, 0.277307496159071, 0.21178304134292902, 0.42008334024706895, 0.4844438199874551, 0.7629227286347695, 0.018191150533511613, 0.559724892006026, 0.31959801497719054, 0.42484124055468686, 0.5045022335945112, 0.41792277630394237, 0.8406756874397227, 0.7584689612373772, 0.6627959232140231, 0.4504234556891311, 0.6188812086557282, 0.2520511112897321, 0.6768894585664594, 0.3661259749132949, 0.9116865527641543, 0.23213232856306942, 0.4908392834870331, 0.738939475306359, 0.5620610076127113, 0.8266539544720171, 0.01875064686052219, 0.6833938264409025, 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diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/test/fixtures/python/runner.py b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/test/fixtures/python/runner.py
new file mode 100644
index 000000000000..b1744111ade9
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/test/fixtures/python/runner.py
@@ -0,0 +1,87 @@
+#!/usr/bin/env python
+#
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""Generate fixtures."""
+
+import os
+import json
+import numpy as np
+from scipy.stats import planck
+
+# Get the file path:
+FILE = os.path.realpath(__file__)
+
+# Extract the directory in which this file resides:
+DIR = os.path.dirname(FILE)
+
+
+def gen(r, lam, name):
+    """
+    Generate fixture data and write to file.
+
+    # Arguments
+
+    * `r`: input values.
+    * `lam`: shape parameter.
+    * `name::str`: output filename.
+
+    # Examples
+
+    ```python
+    python> r = np.random.rand(1000)
+    python> lam = np.random.rand(1000)
+    python> gen(r, lam, "data.json")
+    ```
+    """
+    # Compute quantile values:
+    z = np.array(planck.ppf(r, lam))
+
+    # Store data to be written to file as a dictionary:
+    data = {
+        "r": r.tolist(),
+        "lambda": lam.tolist(),
+        "expected": z.tolist()
+    }
+
+    # Based on the script directory, create an output filepath:
+    filepath = os.path.join(DIR, name)
+
+    # Write the data to the output filepath as JSON:
+    with open(filepath, "w", encoding='utf-8') as outfile:
+        json.dump(data, outfile)
+
+    # Include trailing newline:
+    with open(filepath, "a", encoding='utf-8') as outfile:
+        outfile.write("\n")
+
+
+def main():
+    """Generate fixture data."""
+    # Large shape parameter:
+    r = np.random.rand(1000)
+    lam = (np.random.rand(1000) * 10.0) + 10.0
+    gen(r, lam, "large_lambda.json")
+
+    # Small shape parameter:
+    r = np.random.rand(1000)
+    lam = np.random.rand(1000) * 0.5
+    gen(r, lam, "small_lambda.json")
+
+
+if __name__ == "__main__":
+    main()
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/test/fixtures/python/small_lambda.json b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/test/fixtures/python/small_lambda.json
new file mode 100644
index 000000000000..cbf983cd1c69
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/test/fixtures/python/small_lambda.json
@@ -0,0 +1 @@
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0.3432418493954254, 0.15888072654854968, 0.4297017037767549, 0.43570895607747695, 0.11194432569424495, 0.024789451634363302, 0.06515441580042775, 0.05634555983527506, 0.043675643780008044, 0.32234356858552116, 0.36792766229383683, 0.10602691236942124, 0.42410530968172067, 0.4848920026227695, 0.05820648366105702], "expected": [11.0, 6.0, 12.0, 7.0, 3.0, 0.0, 3.0, 2.0, 1.0, 1.0, 11.0, 2.0, 31.0, 9.0, 10.0, 3.0, 1.0, 3.0, 3.0, 0.0, 1.0, 204.0, 2.0, 2.0, 1.0, 7.0, 0.0, 6.0, 7.0, 1.0, 0.0, 13.0, 32.0, 2.0, 3.0, 9.0, 21.0, 2.0, 11.0, 2.0, 552.0, 16.0, 34.0, 17.0, 2.0, 2.0, 1.0, 27.0, 5.0, 4.0, 54.0, 3.0, 7.0, 1.0, 57.0, 66.0, 1.0, 1.0, 6.0, 2.0, 0.0, 0.0, 0.0, 5.0, 38.0, 30.0, 3.0, 5.0, 0.0, 0.0, 0.0, 1.0, 63.0, 4.0, 2.0, 32.0, 6.0, 1.0, 8.0, 0.0, 11.0, 4.0, 11.0, 0.0, 0.0, 2.0, 3.0, 3.0, 0.0, 310.0, 0.0, 0.0, 4.0, 3.0, 19.0, 0.0, 0.0, 7.0, 0.0, 0.0, 3.0, 10.0, 5.0, 1.0, 0.0, 25.0, 0.0, 19.0, 1.0, 605.0, 0.0, 6.0, 0.0, 0.0, 0.0, 1.0, 30.0, 5.0, 6.0, 3.0, 0.0, 1.0, 6.0, 4.0, 1.0, 0.0, 0.0, 19.0, 8.0, 7.0, 2.0, 6.0, 4.0, 0.0, 0.0, 1.0, 36.0, 0.0, 13.0, 61.0, 1.0, 0.0, 0.0, 9.0, 4.0, 3.0, 0.0, 4.0, 1.0, 13.0, 10.0, 71.0, 2.0, 14.0, 6.0, 1.0, 9.0, 1.0, 0.0, 5.0, 0.0, 1.0, 1.0, 5.0, 10.0, 18.0, 3.0, 3.0, 6.0, 4.0, 0.0, 2.0, 2.0, 0.0, 7.0, 0.0, 74.0, 1.0, 3.0, 1.0, 21.0, 0.0, 2.0, 0.0, 59.0, 0.0, 0.0, 3.0, 1.0, 5.0, 4.0, 4.0, 5.0, 0.0, 6.0, 0.0, 2.0, 7.0, 14.0, 1.0, 29.0, 5.0, 0.0, 1.0, 0.0, 4.0, 5.0, 18.0, 22.0, 9.0, 474.0, 1.0, 2.0, 1.0, 1.0, 16.0, 4.0, 8.0, 54.0, 2.0, 0.0, 21.0, 3.0, 5.0, 5.0, 2.0, 0.0, 2.0, 101.0, 0.0, 3.0, 2.0, 11.0, 25.0, 2.0, 1.0, 3.0, 21.0, 2.0, 1.0, 1.0, 10.0, 1.0, 1.0, 1.0, 3.0, 2.0, 4.0, 109.0, 0.0, 10.0, 2.0, 6.0, 11.0, 0.0, 7.0, 1.0, 27.0, 5.0, 8.0, 1.0, 5.0, 5.0, 0.0, 5.0, 10.0, 4.0, 4.0, 6.0, 11.0, 1.0, 9.0, 7.0, 1.0, 0.0, 0.0, 1.0, 1.0, 5.0, 1.0, 15.0, 10.0, 3.0, 0.0, 0.0, 28.0, 6.0, 39.0, 0.0, 0.0, 0.0, 28.0, 0.0, 11.0, 2.0, 1.0, 0.0, 517.0, 14.0, 0.0, 0.0, 2.0, 1.0, 0.0, 2.0, 11.0, 14.0, 0.0, 0.0, 1.0, 0.0, 6.0, 1.0, 7.0, 7.0, 6.0, 8.0, 8.0, 8.0, 3.0, 2.0, 0.0, 4.0, 3.0, 5.0, 0.0, 11.0, 9.0, 3.0, 4.0, 0.0, 16.0, 0.0, 8.0, 0.0, 5.0, 1.0, 7.0, 0.0, 3.0, 4.0, 0.0, 0.0, 3.0, 2.0, 0.0, 552.0, 0.0, 0.0, 81.0, 8.0, 0.0, 5.0, 2.0, 69.0, 8.0, 8.0, 34.0, 0.0, 3.0, 0.0, 13.0, 1.0, 18.0, 2.0, 0.0, 0.0, 4.0, 4.0, 3.0, 47.0, 0.0, 4.0, 11.0, 6.0, 7.0, 3.0, 59.0, 3.0, 0.0, 0.0, 5.0, 2.0, 1.0, 0.0, 2.0, 24.0, 8.0, 0.0, 77.0, 15.0, 4.0, 18.0, 1.0, 0.0, 4.0, 0.0, 3.0, 0.0, 0.0, 2.0, 0.0, 1.0, 4.0, 0.0, 3.0, 4.0, 0.0, 0.0, 1.0, 0.0, 1.0, 1.0, 8.0, 4.0, 2.0, 0.0, 0.0, 2.0, 13.0, 0.0, 1.0, 29.0, 2.0, 14.0, 6.0, 56.0, 9.0, 4.0, 1.0, 1.0, 2.0, 6.0, 2.0, 11.0, 8.0, 5.0, 5.0, 2.0, 6.0, 0.0, 42.0, 63.0, 19.0, 2.0, 78.0, 112.0, 0.0, 0.0, 0.0, 12.0, 0.0, 2.0, 0.0, 0.0, 1.0, 16.0, 8.0, 6.0, 5.0, 1.0, 8.0, 6.0, 2.0, 1.0, 1.0, 0.0, 16.0, 13313.0, 42.0, 0.0, 4.0, 0.0, 9.0, 4.0, 6.0, 1.0, 5.0, 0.0, 4.0, 5.0, 2.0, 1.0, 0.0, 2.0, 0.0, 2.0, 4.0, 5.0, 7.0, 1.0, 0.0, 9.0, 28.0, 17.0, 2.0, 0.0, 0.0, 2.0, 1.0, 5.0, 6.0, 52.0, 1.0, 39.0, 0.0, 6.0, 0.0, 2.0, 0.0, 0.0, 1.0, 0.0, 5.0, 5.0, 0.0, 5.0, 1.0, 0.0, 0.0, 7.0, 0.0, 6.0, 44.0, 36.0, 3.0, 14.0, 7.0, 7.0, 3.0, 3.0, 7.0, 101.0, 12.0, 0.0, 3.0, 3.0, 0.0, 1.0, 0.0, 3.0, 7.0, 1.0, 4.0, 5.0, 3.0, 37.0, 1.0, 3.0, 2.0, 4.0, 6.0, 2.0, 0.0, 2.0, 1.0, 1.0, 0.0, 16.0, 0.0, 2.0, 10.0, 0.0, 3.0, 6.0, 9.0, 2.0, 0.0, 102.0, 2.0, 3.0, 3.0, 0.0, 4.0, 5.0, 66.0, 0.0, 2.0, 10.0, 0.0, 329.0, 7.0, 0.0, 17.0, 136.0, 1.0, 3.0, 11.0, 3.0, 6.0, 3.0, 4.0, 0.0, 6.0, 4.0, 0.0, 0.0, 7.0, 0.0, 9.0, 8.0, 1.0, 9.0, 5.0, 2.0, 1.0, 0.0, 19.0, 2.0, 8.0, 2.0, 0.0, 0.0, 18.0, 1.0, 3.0, 4.0, 4.0, 10.0, 7.0, 9.0, 13.0, 0.0, 4.0, 4.0, 2.0, 2.0, 0.0, 5.0, 3.0, 0.0, 22.0, 1.0, 17.0, 8.0, 187.0, 4.0, 0.0, 10.0, 108.0, 2.0, 78.0, 13.0, 47.0, 1.0, 3.0, 0.0, 0.0, 5.0, 2.0, 3.0, 3.0, 4.0, 57.0, 74.0, 0.0, 1.0, 0.0, 4.0, 5.0, 3.0, 3.0, 3.0, 2.0, 3.0, 1.0, 2.0, 12.0, 5.0, 0.0, 7.0, 5.0, 2.0, 5.0, 7.0, 0.0, 2.0, 1.0, 2.0, 0.0, 7.0, 1.0, 3.0, 0.0, 3.0, 0.0, 2.0, 1.0, 7.0, 0.0, 36.0, 0.0, 19.0, 12.0, 12.0, 4.0, 0.0, 3.0, 7.0, 2.0, 25.0, 7.0, 4.0, 1.0, 1.0, 1.0, 4.0, 1.0, 23.0, 11.0, 9.0, 15.0, 1.0, 11.0, 0.0, 12.0, 5.0, 21.0, 12.0, 4.0, 2.0, 0.0, 2.0, 3.0, 4.0, 2.0, 12.0, 16.0, 6.0, 2.0, 15.0, 7.0, 1.0, 6.0, 0.0, 1.0, 40.0, 0.0, 3.0, 0.0, 4.0, 15.0, 2.0, 14.0, 5.0, 2.0, 10.0, 4.0, 17.0, 2.0, 0.0, 6.0, 2.0, 7.0, 6.0, 10.0, 0.0, 3.0, 7.0, 1.0, 1.0, 1.0, 0.0, 28.0, 1.0, 3.0, 0.0, 7.0, 0.0, 2.0, 0.0, 24.0, 1.0, 4.0, 7.0, 1.0, 1.0, 25.0, 8.0, 6.0, 4.0, 1.0, 2.0, 1.0, 4.0, 12.0, 286.0, 1.0, 20.0, 0.0, 34.0, 1.0, 0.0, 1.0, 5.0, 4.0, 6.0, 2.0, 5.0, 0.0, 0.0, 0.0, 4.0, 0.0, 18.0, 0.0, 1.0, 1.0, 0.0, 0.0, 5.0, 3.0, 20.0, 10.0, 14.0, 54.0, 6.0, 1.0, 4.0, 0.0, 7.0, 1.0, 3.0, 8.0, 28.0, 0.0, 1.0, 0.0, 0.0, 5.0, 4.0, 2.0, 7.0, 0.0, 11.0, 0.0, 1.0, 5.0, 1.0, 10.0, 3.0, 0.0, 11.0, 2.0, 2.0, 0.0, 6.0, 13.0, 6.0, 1321.0, 1.0, 19.0, 2.0, 19.0, 1.0, 1.0, 0.0, 1.0, 1.0, 8.0, 10.0, 1.0, 1.0, 19.0, 3.0, 1.0, 4.0, 0.0, 7.0, 24.0, 2.0, 55.0, 1.0, 1.0, 77.0, 4.0, 4.0, 0.0, 4.0, 3.0, 1.0, 189.0, 28.0, 2.0, 0.0, 13.0, 6.0, 14.0, 10.0, 9.0, 94.0, 7.0, 3.0, 17.0, 3.0, 1.0, 3.0, 2.0, 1.0, 0.0, 0.0, 0.0, 1.0, 5.0, 149.0, 11.0, 2.0, 0.0, 0.0, 147.0, 10.0, 9.0, 2.0, 1.0, 39.0, 4.0, 5.0, 1.0, 1.0, 5.0, 9.0, 35.0, 0.0, 6.0, 2.0, 2.0, 21.0, 114.0, 1.0, 0.0, 7.0, 0.0, 1.0, 7.0, 2.0, 0.0, 0.0, 0.0, 2.0, 38.0, 9.0, 4.0, 3.0, 2.0, 13.0, 1.0, 0.0, 2.0, 11.0, 2.0, 6.0, 2.0, 3.0, 5.0, 3.0, 3.0, 2.0, 0.0, 6.0, 2.0, 4.0, 0.0, 3.0, 7.0, 1.0, 45.0, 3.0, 1.0, 1.0, 2.0, 0.0, 1230.0, 1.0, 0.0, 0.0, 2.0, 5.0, 1.0, 0.0, 2.0, 2.0, 8.0, 6.0, 0.0, 2.0, 4.0, 16.0, 6.0, 3.0, 3.0, 12.0, 77.0, 8.0, 3.0, 1.0, 6.0, 7.0, 0.0, 0.0, 1.0]}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/test/test.factory.js b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/test/test.factory.js
new file mode 100644
index 000000000000..c2d4f8ddfa2b
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/test/test.factory.js
@@ -0,0 +1,148 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var PINF = require( '@stdlib/constants/float64/pinf' );
+var factory = require( './../lib/factory.js' );
+
+
+// FIXTURES //
+
+var smallLambda = require( './fixtures/python/small_lambda.json' );
+var largeLambda = require( './fixtures/python/large_lambda.json' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof factory, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'the function returns a function', function test( t ) {
+	var quantile = factory( 1.0 );
+	t.equal( typeof quantile, 'function', 'returns a function' );
+	t.end();
+});
+
+tape( 'if provided `NaN` for any parameter, the returned function returns `NaN`', function test( t ) {
+	var quantile;
+	var y;
+
+	quantile = factory( 1.0 );
+	y = quantile( NaN );
+	t.equal( isnan( y ), true, 'returns expected value' );
+
+	quantile = factory( NaN );
+	y = quantile( 0.0 );
+	t.equal( isnan( y ), true, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'if provided a valid shape parameter `lambda`, the function returns a function which returns `NaN` when provided a number outside `[0,1]` for `p`', function test( t ) {
+	var quantile;
+	var y;
+
+	quantile = factory( 0.8 );
+	y = quantile( -0.1 );
+	t.equal( isnan( y ), true, 'returns expected value' );
+
+	y = quantile( 1.1 );
+	t.equal( isnan( y ), true, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'if provided a valid shape parameter `lambda`, the function returns a function which returns `+Infinity` when provided `1.0` for `p`', function test( t ) {
+	var quantile;
+	var y;
+
+	quantile = factory( 0.5 );
+	y = quantile( 1.0 );
+	t.equal( y, PINF, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'if provided a shape parameter `lambda` which is nonpositive, the returned function always returns `NaN`', function test( t ) {
+	var quantile;
+	var y;
+
+	quantile = factory( -1.0 );
+
+	y = quantile( 0.4 );
+	t.equal( isnan( y ), true, 'returns expected value' );
+
+	y = quantile( 0.8 );
+	t.equal( isnan( y ), true, 'returns expected value' );
+
+	quantile = factory( 0.0 );
+
+	y = quantile( 0.4 );
+	t.equal( isnan( y ), true, 'returns expected value' );
+
+	y = quantile( 0.8 );
+	t.equal( isnan( y ), true, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the returned function evaluates the quantile for `p` given small parameter `lambda`', function test( t ) {
+	var quantile;
+	var expected;
+	var lambda;
+	var p;
+	var y;
+	var i;
+
+	expected = smallLambda.expected;
+	p = smallLambda.r;
+	lambda = smallLambda.lambda;
+	for ( i = 0; i < p.length; i++ ) {
+		quantile = factory( lambda[ i ] );
+		y = quantile( p[ i ] );
+		t.equal( y, expected[ i ], 'p: '+p[ i ]+', lambda: '+lambda[ i ]+', y: '+y+', expected: '+expected[ i ] );
+	}
+	t.end();
+});
+
+tape( 'the returned function evaluates the quantile for `p` given large parameter `lambda`', function test( t ) {
+	var quantile;
+	var expected;
+	var lambda;
+	var p;
+	var y;
+	var i;
+
+	expected = largeLambda.expected;
+	p = largeLambda.r;
+	lambda = largeLambda.lambda;
+	for ( i = 0; i < p.length; i++ ) {
+		quantile = factory( lambda[ i ] );
+		y = quantile( p[ i ] );
+		t.equal( y, expected[ i ], 'p: '+p[ i ]+', lambda: '+lambda[ i ]+', y: '+y+', expected: '+expected[ i ] );
+	}
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/test/test.js b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/test/test.js
new file mode 100644
index 000000000000..6ad40b0c38e2
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/test/test.js
@@ -0,0 +1,38 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var quantile = require( './../lib' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof quantile, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'attached to the main export is a factory method for generating `quantile` functions', function test( t ) {
+	t.equal( typeof quantile.factory, 'function', 'exports a factory method' );
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/test/test.quantile.js b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/test/test.quantile.js
new file mode 100644
index 000000000000..a76f7130beaa
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/planck/quantile/test/test.quantile.js
@@ -0,0 +1,111 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var tape = require( 'tape' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var PINF = require( '@stdlib/constants/float64/pinf' );
+var quantile = require( './../lib' );
+
+
+// FIXTURES //
+
+var smallLambda = require( './fixtures/python/small_lambda.json' );
+var largeLambda = require( './fixtures/python/large_lambda.json' );
+
+
+// TESTS //
+
+tape( 'main export is a function', function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof quantile, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'if provided `NaN` for any parameter, the function returns `NaN`', function test( t ) {
+	var y = quantile( NaN, 1.0 );
+	t.equal( isnan( y ), true, 'returns expected value' );
+	y = quantile( 0.0, NaN );
+	t.equal( isnan( y ), true, 'returns expected value' );
+	t.end();
+});
+
+tape( 'if provided a number outside `[0,1]` for `p` and a valid `lambda`, the function returns `NaN`', function test( t ) {
+	var y = quantile( 2.2, 0.8 );
+	t.equal( isnan( y ), true, 'returns expected value' );
+	y = quantile( -0.2, 0.8 );
+	t.equal( isnan( y ), true, 'returns expected value' );
+	t.end();
+});
+
+tape( 'if provided `1.0` for `p` and a valid `lambda`, the function returns `+Infinity`', function test( t ) {
+	var y = quantile( 1.0, 0.5 );
+	t.equal( y, PINF, 'returns expected value' );
+	y = quantile( 1.0, 1.5 );
+	t.equal( y, PINF, 'returns expected value' );
+	t.end();
+});
+
+tape( 'if provided a shape parameter `lambda` which is nonpositive, the function always returns `NaN`', function test( t ) {
+	var y;
+
+	y = quantile( 0.8, -1.5 );
+	t.equal( isnan( y ), true, 'returns expected value' );
+
+	y = quantile( 0.9, 0.0 );
+	t.equal( isnan( y ), true, 'returns expected value' );
+
+	t.end();
+});
+
+tape( 'the function evaluates the quantile for `p` given small parameter `lambda`', function test( t ) {
+	var expected;
+	var lambda;
+	var p;
+	var y;
+	var i;
+
+	expected = smallLambda.expected;
+	p = smallLambda.r;
+	lambda = smallLambda.lambda;
+	for ( i = 0; i < p.length; i++ ) {
+		y = quantile( p[ i ], lambda[ i ] );
+		t.equal( y, expected[ i ], 'p: '+p[ i ]+', lambda: '+lambda[ i ]+', y: '+y+', expected: '+expected[ i ] );
+	}
+	t.end();
+});
+
+tape( 'the function evaluates the quantile for `p` given large parameter `lambda`', function test( t ) {
+	var expected;
+	var lambda;
+	var p;
+	var y;
+	var i;
+
+	expected = largeLambda.expected;
+	p = largeLambda.r;
+	lambda = largeLambda.lambda;
+	for ( i = 0; i < p.length; i++ ) {
+		y = quantile( p[ i ], lambda[ i ] );
+		t.equal( y, expected[ i ], 'p: '+p[ i ]+', lambda: '+lambda[ i ]+', y: '+y+', expected: '+expected[ i ] );
+	}
+	t.end();
+});

From 768f5dc17c4623169146069387a380bda219e2c7 Mon Sep 17 00:00:00 2001
From: Aayush Khanna <96649223+aayush0325@users.noreply.github.com>
Date: Thu, 2 Jan 2025 15:55:32 +0530
Subject: [PATCH 05/87] feat: add C ndarray interface and refactor
 implementation for `stats/base/smskrange`

PR-URL: https://github.com/stdlib-js/stdlib/pull/4404
Co-authored-by: Athan Reines <kgryte@gmail.com>
Reviewed-by: Athan Reines <kgryte@gmail.com>
Co-authored-by: stdlib-bot <82920195+stdlib-bot@users.noreply.github.com>
---
 .../@stdlib/stats/base/smskrange/README.md    | 173 ++++++++++++++----
 .../base/smskrange/benchmark/benchmark.js     |  31 ++--
 .../smskrange/benchmark/benchmark.native.js   |  27 +--
 .../smskrange/benchmark/benchmark.ndarray.js  |  31 ++--
 .../benchmark/benchmark.ndarray.native.js     |  27 +--
 .../smskrange/benchmark/c/benchmark.length.c  |  56 +++++-
 .../stats/base/smskrange/docs/repl.txt        |  22 +--
 .../stats/base/smskrange/examples/c/example.c |  10 +-
 .../stats/base/smskrange/examples/index.js    |  27 +--
 .../@stdlib/stats/base/smskrange/include.gypi |   2 +-
 .../include/stdlib/stats/base/smskrange.h     |   8 +-
 .../@stdlib/stats/base/smskrange/lib/index.js |   4 +-
 .../stats/base/smskrange/lib/ndarray.js       |   4 +-
 .../base/smskrange/lib/ndarray.native.js      |  20 +-
 .../stats/base/smskrange/lib/smskrange.js     |  60 +-----
 .../stats/base/smskrange/manifest.json        |  70 ++++++-
 .../@stdlib/stats/base/smskrange/src/addon.c  |  66 +++++++
 .../stats/base/smskrange/src/addon.cpp        | 153 ----------------
 .../smskrange/src/{smskrange.c => main.c}     |  40 ++--
 .../stats/base/smskrange/test/test.ndarray.js |  13 +-
 .../smskrange/test/test.ndarray.native.js     |  15 +-
 .../base/smskrange/test/test.smskrange.js     |  13 +-
 .../smskrange/test/test.smskrange.native.js   |  13 +-
 23 files changed, 455 insertions(+), 430 deletions(-)
 create mode 100644 lib/node_modules/@stdlib/stats/base/smskrange/src/addon.c
 delete mode 100644 lib/node_modules/@stdlib/stats/base/smskrange/src/addon.cpp
 rename lib/node_modules/@stdlib/stats/base/smskrange/src/{smskrange.c => main.c} (57%)

diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/README.md b/lib/node_modules/@stdlib/stats/base/smskrange/README.md
index b2816e520d9c..e63c44af60bb 100644
--- a/lib/node_modules/@stdlib/stats/base/smskrange/README.md
+++ b/lib/node_modules/@stdlib/stats/base/smskrange/README.md
@@ -40,7 +40,7 @@ var smskrange = require( '@stdlib/stats/base/smskrange' );
 
 #### smskrange( N, x, strideX, mask, strideMask )
 
-Computes the [range][range] of a single-precision floating-point strided array `x` according to a `mask`.
+Computes the [range][range] of a single-precision floating-point strided array according to a mask.
 
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
@@ -57,22 +57,20 @@ The function has the following parameters:
 
 -   **N**: number of indexed elements.
 -   **x**: input [`Float32Array`][@stdlib/array/float32].
--   **strideX**: index increment for `x`.
+-   **strideX**: stride length for `x`.
 -   **mask**: mask [`Uint8Array`][@stdlib/array/uint8]. If a `mask` array element is `0`, the corresponding element in `x` is considered valid and **included** in computation. If a `mask` array element is `1`, the corresponding element in `x` is considered invalid/missing and **excluded** from computation.
--   **strideMask**: index increment for `mask`.
+-   **strideMask**: stride length for `mask`.
 
-The `N` and `stride` parameters determine which elements are accessed at runtime. For example, to compute the [range][range] of every other element in `x`,
+The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the [range][range] of every other element in `x`,
 
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
 var Uint8Array = require( '@stdlib/array/uint8' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x = new Float32Array( [ 1.0, 2.0, -7.0, -2.0, 4.0, 3.0, 5.0, 6.0 ] );
 var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] );
-var N = floor( x.length / 2 );
 
-var v = smskrange( N, x, 2, mask, 2 );
+var v = smskrange( 4, x, 2, mask, 2 );
 // returns 11.0
 ```
 
@@ -83,7 +81,6 @@ Note that indexing is relative to the first index. To introduce offsets, use [`t
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
 var Uint8Array = require( '@stdlib/array/uint8' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x0 = new Float32Array( [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, 5.0, 6.0 ] );
 var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
@@ -91,15 +88,13 @@ var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd
 var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] );
 var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
 
-var N = floor( x0.length / 2 );
-
-var v = smskrange( N, x1, 2, mask1, 2 );
+var v = smskrange( 4, x1, 2, mask1, 2 );
 // returns 6.0
 ```
 
 #### smskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )
 
-Computes the [range][range] of a single-precision floating-point strided array according to a `mask` and using alternative indexing semantics.
+Computes the [range][range] of a single-precision floating-point strided array according to a mask and using alternative indexing semantics.
 
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
@@ -117,18 +112,16 @@ The function has the following additional parameters:
 -   **offsetX**: starting index for `x`.
 -   **offsetMask**: starting index for `mask`.
 
-While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the [range][range] for every other value in `x` starting from the second value
+While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on a starting indices. For example, to calculate the [range][range] for every other element in `x` starting from the second element
 
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
 var Uint8Array = require( '@stdlib/array/uint8' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x = new Float32Array( [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, 5.0, 6.0 ] );
 var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] );
-var N = floor( x.length / 2 );
 
-var v = smskrange.ndarray( N, x, 2, 1, mask, 2, 1 );
+var v = smskrange.ndarray( 4, x, 2, 1, mask, 2, 1 );
 // returns 6.0
 ```
 
@@ -153,26 +146,19 @@ var v = smskrange.ndarray( N, x, 2, 1, mask, 2, 1 );
 <!-- eslint no-undef: "error" -->
 
 ```javascript
-var randu = require( '@stdlib/random/base/randu' );
-var round = require( '@stdlib/math/base/special/round' );
-var Float32Array = require( '@stdlib/array/float32' );
-var Uint8Array = require( '@stdlib/array/uint8' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var bernoulli = require( '@stdlib/random/array/bernoulli' );
 var smskrange = require( '@stdlib/stats/base/smskrange' );
 
-var mask;
-var x;
-var i;
-
-x = new Float32Array( 10 );
-mask = new Uint8Array( x.length );
-for ( i = 0; i < x.length; i++ ) {
-    if ( randu() < 0.2 ) {
-        mask[ i ] = 1;
-    } else {
-        mask[ i ] = 0;
-    }
-    x[ i ] = round( (randu()*100.0) - 50.0 );
-}
+var uniformOptions = {
+    'dtype': 'float32'
+};
+var bernoulliOptions = {
+    'dtype': 'uint8'
+};
+
+var x = uniform( 10, -50.0, 50.0, uniformOptions );
+var mask = bernoulli( x.length, 0.2, bernoulliOptions );
 console.log( x );
 console.log( mask );
 
@@ -184,6 +170,125 @@ console.log( v );
 
 <!-- /.examples -->
 
+<!-- C usage documentation. -->
+
+<section class="usage">
+
+### Usage
+
+```c
+#include "stdlib/stats/base/smskrange.h"
+```
+
+#### stdlib_strided_smskrange( N, \*X, strideX, \*Mask, strideMask )
+
+Computes the [range][range] of a single-precision floating-point strided array according to a mask.
+
+```c
+#include <stdint.h>
+
+const float x[] = { 1.0f, -2.0f, 2.0f };
+const uint8_t mask[] = { 0, 1, 0 };
+
+float v = stdlib_strided_smskrange( 3, x, 1, mask, 1 );
+// returns 1.0f
+```
+
+The function accepts the following arguments:
+
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **X**: `[in] float*` input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+-   **Mask**: `[in] uint8_t*` mask array. If a `Mask` array element is `0`, the corresponding element in `X` is considered valid and included in computation. If a `Mask` array element is `1`, the corresponding element in `X` is considered invalid/missing and excluded from computation.
+-   **strideMask**: `[in] CBLAS_INT` stride length for `Mask`.
+
+```c
+float stdlib_strided_smskrange( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const uint8_t *Mask, const CBLAS_INT strideMask );
+```
+
+<!-- lint disable maximum-heading-length -->
+
+#### stdlib_strided_smskrange_ndarray( N, \*X, strideX, offsetX, \*Mask, strideMask, offsetMask )
+
+Computes the [range][range] of a single-precision floating-point strided array according to a mask and using alternative indexing semantics.
+
+```c
+#include <stdint.h>
+
+const float x[] = { 1.0f, -2.0f, 2.0f };
+const uint8_t mask[] = { 0, 1, 0 };
+
+float v = stdlib_strided_smskrange( 3, x, 1, 0, mask, 1, 0 );
+// returns 1.0f
+```
+
+The function accepts the following arguments:
+
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **X**: `[in] float*` input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+-   **offsetX**: `[in] CBLAS_INT` starting index for `X`.
+-   **Mask**: `[in] uint8_t*` mask array. If a `Mask` array element is `0`, the corresponding element in `X` is considered valid and included in computation. If a `Mask` array element is `1`, the corresponding element in `X` is considered invalid/missing and excluded from computation.
+-   **strideMask**: `[in] CBLAS_INT` stride length for `Mask`.
+-   **offsetMask**: `[in] CBLAS_INT` starting index for `Mask`.
+
+```c
+float stdlib_strided_smskrange_ndarray( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const uint8_t *Mask, const CBLAS_INT strideMask, const CBLAS_INT offsetMask );
+```
+
+</section>
+
+<!-- /.usage -->
+
+<!-- C API usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="notes">
+
+</section>
+
+<!-- /.notes -->
+
+<!-- C API usage examples. -->
+
+<section class="examples">
+
+### Examples
+
+```c
+#include "stdlib/stats/base/smskrange.h"
+#include <stdint.h>
+#include <stdio.h>
+
+int main( void ) {
+    // Create a strided array:
+    const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f };
+
+    // Create a mask array:
+    const uint8_t mask[] = { 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 };
+
+    // Specify the number of elements:
+    const int N = 5;
+
+    // Specify the stride lengths:
+    const int strideX = 2;
+    const int strideMask = 2;
+
+    // Compute the range:
+    float v = stdlib_strided_smskrange( N, x, strideX, mask, strideMask );
+
+    // Print the result:
+    printf( "range: %f\n", v );
+}
+```
+
+</section>
+
+<!-- /.examples -->
+
+</section>
+
+<!-- /.c -->
+
 <!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
 
 <section class="related">
diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/smskrange/benchmark/benchmark.js
index 5a5b591a0bfa..62f5bb0783f6 100644
--- a/lib/node_modules/@stdlib/stats/base/smskrange/benchmark/benchmark.js
+++ b/lib/node_modules/@stdlib/stats/base/smskrange/benchmark/benchmark.js
@@ -21,15 +21,24 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var bernoulli = require( '@stdlib/random/array/bernoulli' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float32Array = require( '@stdlib/array/float32' );
-var Uint8Array = require( '@stdlib/array/uint8' );
 var pkg = require( './../package.json' ).name;
 var smskrange = require( './../lib/smskrange.js' );
 
 
+// VARIABLES //
+
+var uniformOptions = {
+	'dtype': 'float32'
+};
+var bernoulliOptions = {
+	'dtype': 'uint8'
+};
+
+
 // FUNCTIONS //
 
 /**
@@ -40,20 +49,8 @@ var smskrange = require( './../lib/smskrange.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var mask;
-	var x;
-	var i;
-
-	x = new Float32Array( len );
-	mask = new Uint8Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		if ( randu() < 0.2 ) {
-			mask[ i ] = 1;
-		} else {
-			mask[ i ] = 0;
-		}
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
+	var mask = bernoulli( len, 0.2, bernoulliOptions );
+	var x = uniform( len, -10.0, 10.0, uniformOptions );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/smskrange/benchmark/benchmark.native.js
index c17bcdd06803..f88173beb42d 100644
--- a/lib/node_modules/@stdlib/stats/base/smskrange/benchmark/benchmark.native.js
+++ b/lib/node_modules/@stdlib/stats/base/smskrange/benchmark/benchmark.native.js
@@ -22,11 +22,10 @@
 
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var bernoulli = require( '@stdlib/random/array/bernoulli' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float32Array = require( '@stdlib/array/float32' );
-var Uint8Array = require( '@stdlib/array/uint8' );
 var tryRequire = require( '@stdlib/utils/try-require' );
 var pkg = require( './../package.json' ).name;
 
@@ -37,6 +36,12 @@ var smskrange = tryRequire( resolve( __dirname, './../lib/smskrange.native.js' )
 var opts = {
 	'skip': ( smskrange instanceof Error )
 };
+var uniformOptions = {
+	'dtype': 'float32'
+};
+var bernoulliOptions = {
+	'dtype': 'uint8'
+};
 
 
 // FUNCTIONS //
@@ -49,20 +54,8 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var mask;
-	var x;
-	var i;
-
-	x = new Float32Array( len );
-	mask = new Uint8Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		if ( randu() < 0.2 ) {
-			mask[ i ] = 1;
-		} else {
-			mask[ i ] = 0;
-		}
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
+	var mask = bernoulli( len, 0.2, bernoulliOptions );
+	var x = uniform( len, -10.0, 10.0, uniformOptions );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/smskrange/benchmark/benchmark.ndarray.js
index bf308f0f9834..7a4187e30aec 100644
--- a/lib/node_modules/@stdlib/stats/base/smskrange/benchmark/benchmark.ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/smskrange/benchmark/benchmark.ndarray.js
@@ -21,15 +21,24 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var bernoulli = require( '@stdlib/random/array/bernoulli' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float32Array = require( '@stdlib/array/float32' );
-var Uint8Array = require( '@stdlib/array/uint8' );
 var pkg = require( './../package.json' ).name;
 var smskrange = require( './../lib/ndarray.js' );
 
 
+// VARIABLES //
+
+var uniformOptions = {
+	'dtype': 'float32'
+};
+var bernoulliOptions = {
+	'dtype': 'uint8'
+};
+
+
 // FUNCTIONS //
 
 /**
@@ -40,20 +49,8 @@ var smskrange = require( './../lib/ndarray.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var mask;
-	var x;
-	var i;
-
-	x = new Float32Array( len );
-	mask = new Uint8Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		if ( randu() < 0.2 ) {
-			mask[ i ] = 1;
-		} else {
-			mask[ i ] = 0;
-		}
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
+	var mask = bernoulli( len, 0.2, bernoulliOptions );
+	var x = uniform( len, -10.0, 10.0, uniformOptions );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/smskrange/benchmark/benchmark.ndarray.native.js
index 9d761ad414ce..2dbfb2c311fe 100644
--- a/lib/node_modules/@stdlib/stats/base/smskrange/benchmark/benchmark.ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/smskrange/benchmark/benchmark.ndarray.native.js
@@ -22,11 +22,10 @@
 
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var bernoulli = require( '@stdlib/random/array/bernoulli' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float32Array = require( '@stdlib/array/float32' );
-var Uint8Array = require( '@stdlib/array/uint8' );
 var tryRequire = require( '@stdlib/utils/try-require' );
 var pkg = require( './../package.json' ).name;
 
@@ -37,6 +36,12 @@ var smskrange = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) )
 var opts = {
 	'skip': ( smskrange instanceof Error )
 };
+var uniformOptions = {
+	'dtype': 'float32'
+};
+var bernoulliOptions = {
+	'dtype': 'uint8'
+};
 
 
 // FUNCTIONS //
@@ -49,20 +54,8 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var mask;
-	var x;
-	var i;
-
-	x = new Float32Array( len );
-	mask = new Uint8Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		if ( randu() < 0.2 ) {
-			mask[ i ] = 1;
-		} else {
-			mask[ i ] = 0;
-		}
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
+	var mask = bernoulli( len, 0.2, bernoulliOptions );
+	var x = uniform( len, -10.0, 10.0, uniformOptions );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/smskrange/benchmark/c/benchmark.length.c
index 8530c1a782eb..f71175f6c01f 100644
--- a/lib/node_modules/@stdlib/stats/base/smskrange/benchmark/c/benchmark.length.c
+++ b/lib/node_modules/@stdlib/stats/base/smskrange/benchmark/c/benchmark.length.c
@@ -94,7 +94,7 @@ static float rand_float( void ) {
 * @param len          array length
 * @return             elapsed time in seconds
 */
-static double benchmark( int iterations, int len ) {
+static double benchmark1( int iterations, int len ) {
 	unsigned char mask[ len ];
 	double elapsed;
 	float x[ len ];
@@ -113,6 +113,7 @@ static double benchmark( int iterations, int len ) {
 	v = 0.0f;
 	t = tic();
 	for ( i = 0; i < iterations; i++ ) {
+		// cppcheck-suppress uninitvar
 		v = stdlib_strided_smskrange( len, x, 1, mask, 1 );
 		if ( v != v ) {
 			printf( "should not return NaN\n" );
@@ -126,6 +127,46 @@ static double benchmark( int iterations, int len ) {
 	return elapsed;
 }
 
+/**
+* Runs a benchmark.
+*
+* @param iterations   number of iterations
+* @param len          array length
+* @return             elapsed time in seconds
+*/
+static double benchmark2( int iterations, int len ) {
+	unsigned char mask[ len ];
+	double elapsed;
+	float x[ len ];
+	float v;
+	double t;
+	int i;
+
+	for ( i = 0; i < len; i++ ) {
+		if ( rand_float() < 0.2f ) {
+			mask[ i ] = 1; // missing
+		} else {
+			mask[ i ] = 0;
+		}
+		x[ i ] = ( rand_float() * 20000.0f ) - 10000.0f;
+	}
+	v = 0.0f;
+	t = tic();
+	for ( i = 0; i < iterations; i++ ) {
+		// cppcheck-suppress uninitvar
+		v = stdlib_strided_smskrange_ndarray( len, x, 1, 0, mask, 1, 0 );
+		if ( v != v ) {
+			printf( "should not return NaN\n" );
+			break;
+		}
+	}
+	elapsed = tic() - t;
+	if ( v != v ) {
+		printf( "should not return NaN\n" );
+	}
+	return elapsed;
+}
+
 /**
 * Main execution sequence.
 */
@@ -148,7 +189,18 @@ int main( void ) {
 		for ( j = 0; j < REPEATS; j++ ) {
 			count += 1;
 			printf( "# c::%s:len=%d\n", NAME, len );
-			elapsed = benchmark( iter, len );
+			elapsed = benchmark1( iter, len );
+			print_results( iter, elapsed );
+			printf( "ok %d benchmark finished\n", count );
+		}
+	}
+	for ( i = MIN; i <= MAX; i++ ) {
+		len = pow( 10, i );
+		iter = ITERATIONS / pow( 10, i-1 );
+		for ( j = 0; j < REPEATS; j++ ) {
+			count += 1;
+			printf( "# c::%s:ndarray:len=%d\n", NAME, len );
+			elapsed = benchmark2( iter, len );
 			print_results( iter, elapsed );
 			printf( "ok %d benchmark finished\n", count );
 		}
diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/smskrange/docs/repl.txt
index b8fdf5db347b..7eeccb40a7a7 100644
--- a/lib/node_modules/@stdlib/stats/base/smskrange/docs/repl.txt
+++ b/lib/node_modules/@stdlib/stats/base/smskrange/docs/repl.txt
@@ -3,8 +3,8 @@
     Computes the range of a single-precision floating-point strided array
     according to a mask.
 
-    The `N` and `stride` parameters determine which elements are accessed at
-    runtime.
+    The `N` and stride parameters determine which elements in the strided arrays
+    are accessed at runtime.
 
     Indexing is relative to the first index. To introduce offsets, use a typed
     array views.
@@ -26,13 +26,13 @@
         Input array.
 
     strideX: integer
-        Index increment for `x`.
+        Stride Length for `x`.
 
     mask: Uint8Array
         Mask array.
 
     strideMask: integer
-        Index increment for `mask`.
+        Stride Length for `mask`.
 
     Returns
     -------
@@ -50,8 +50,7 @@
     // Using `N` and `stride` parameters:
     > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );
     > mask = new {{alias:@stdlib/array/uint8}}( [ 0, 0, 0, 0, 0, 0, 1 ] );
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > {{alias}}( N, x, 2, mask, 2 )
+    > {{alias}}( 3, x, 2, mask, 2 )
     4.0
 
     // Using view offsets:
@@ -59,10 +58,10 @@
     > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );
     > var mask0 = new {{alias:@stdlib/array/uint8}}( [ 0, 0, 0, 0, 0, 0, 1 ] );
     > var mask1 = new {{alias:@stdlib/array/uint8}}( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );
-    > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );
-    > {{alias}}( N, x1, 2, mask1, 2 )
+    > {{alias}}( 3, x1, 2, mask1, 2 )
     4.0
 
+
 {{alias}}.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )
     Computes the range of a single-precision floating-point strided array
     according to a mask and using alternative indexing semantics.
@@ -80,7 +79,7 @@
         Input array.
 
     strideX: integer
-        Index increment for `x`.
+        Stride Length for `x`.
 
     offsetX: integer
         Starting index for `x`.
@@ -89,7 +88,7 @@
         Mask array.
 
     strideMask: integer
-        Index increment for `mask`.
+        Stride Length for `mask`.
 
     offsetMask: integer
         Starting index for `mask`.
@@ -110,8 +109,7 @@
     // Using offset parameter:
     > x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );
     > mask = new {{alias:@stdlib/array/uint8}}( [ 0, 0, 0, 0, 0, 0, 1 ] );
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > {{alias}}.ndarray( N, x, 2, 1, mask, 2, 1 )
+    > {{alias}}.ndarray( 3, x, 2, 1, mask, 2, 1 )
     4.0
 
     See Also
diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/smskrange/examples/c/example.c
index a0c6f6f8148a..66cea0336e64 100644
--- a/lib/node_modules/@stdlib/stats/base/smskrange/examples/c/example.c
+++ b/lib/node_modules/@stdlib/stats/base/smskrange/examples/c/example.c
@@ -22,17 +22,17 @@
 
 int main( void ) {
 	// Create a strided array:
-	float x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 };
+	const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f };
 
 	// Create a mask array:
-	uint8_t mask[] = { 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 };
+	const uint8_t mask[] = { 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 };
 
 	// Specify the number of elements:
-	int64_t N = 5;
+	const int N = 5;
 
 	// Specify the stride lengths:
-	int64_t strideX = 2;
-	int64_t strideMask = 2;
+	const int strideX = 2;
+	const int strideMask = 2;
 
 	// Compute the range:
 	float v = stdlib_strided_smskrange( N, x, strideX, mask, strideMask );
diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/examples/index.js b/lib/node_modules/@stdlib/stats/base/smskrange/examples/index.js
index 4d2c7d22f6dc..f39eab3a7777 100644
--- a/lib/node_modules/@stdlib/stats/base/smskrange/examples/index.js
+++ b/lib/node_modules/@stdlib/stats/base/smskrange/examples/index.js
@@ -18,26 +18,19 @@
 
 'use strict';
 
-var randu = require( '@stdlib/random/base/randu' );
-var round = require( '@stdlib/math/base/special/round' );
-var Float32Array = require( '@stdlib/array/float32' );
-var Uint8Array = require( '@stdlib/array/uint8' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var bernoulli = require( '@stdlib/random/array/bernoulli' );
 var smskrange = require( './../lib' );
 
-var mask;
-var x;
-var i;
+var uniformOptions = {
+	'dtype': 'float32'
+};
+var bernoulliOptions = {
+	'dtype': 'uint8'
+};
 
-x = new Float32Array( 10 );
-mask = new Uint8Array( x.length );
-for ( i = 0; i < x.length; i++ ) {
-	if ( randu() < 0.2 ) {
-		mask[ i ] = 1;
-	} else {
-		mask[ i ] = 0;
-	}
-	x[ i ] = round( (randu()*100.0) - 50.0 );
-}
+var x = uniform( 10, -50.0, 50.0, uniformOptions );
+var mask = bernoulli( x.length, 0.2, bernoulliOptions );
 console.log( x );
 console.log( mask );
 
diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/include.gypi b/lib/node_modules/@stdlib/stats/base/smskrange/include.gypi
index 868c5c12e852..26476a8c2655 100644
--- a/lib/node_modules/@stdlib/stats/base/smskrange/include.gypi
+++ b/lib/node_modules/@stdlib/stats/base/smskrange/include.gypi
@@ -36,7 +36,7 @@
 
     # Source files:
     'src_files': [
-      '<(src_dir)/addon.cpp',
+      '<(src_dir)/addon.c',
       '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).src; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
     ],
 
diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/include/stdlib/stats/base/smskrange.h b/lib/node_modules/@stdlib/stats/base/smskrange/include/stdlib/stats/base/smskrange.h
index 3d04b7a536cc..7dbc1b899814 100644
--- a/lib/node_modules/@stdlib/stats/base/smskrange/include/stdlib/stats/base/smskrange.h
+++ b/lib/node_modules/@stdlib/stats/base/smskrange/include/stdlib/stats/base/smskrange.h
@@ -19,6 +19,7 @@
 #ifndef STDLIB_STATS_BASE_SMSKRANGE_H
 #define STDLIB_STATS_BASE_SMSKRANGE_H
 
+#include "stdlib/blas/base/shared.h"
 #include <stdint.h>
 
 /*
@@ -31,7 +32,12 @@ extern "C" {
 /**
 * Computes the range of a single-precision floating-point strided array according to a mask.
 */
-float stdlib_strided_smskrange( const int64_t N, const float *X, const int64_t strideX, const uint8_t *Mask, const int64_t strideMask );
+float API_SUFFIX(stdlib_strided_smskrange)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const uint8_t *Mask, const CBLAS_INT strideMask );
+
+/**
+* Computes the range of a single-precision floating-point strided array according to a mask and using alternative indexing semantics.
+*/
+float API_SUFFIX(stdlib_strided_smskrange_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const uint8_t *Mask, const CBLAS_INT strideMask, const CBLAS_INT offsetMask );
 
 #ifdef __cplusplus
 }
diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/lib/index.js b/lib/node_modules/@stdlib/stats/base/smskrange/lib/index.js
index 7d80a61a3b01..706215b9af9d 100644
--- a/lib/node_modules/@stdlib/stats/base/smskrange/lib/index.js
+++ b/lib/node_modules/@stdlib/stats/base/smskrange/lib/index.js
@@ -37,14 +37,12 @@
 * @example
 * var Float32Array = require( '@stdlib/array/float32' );
 * var Uint8Array = require( '@stdlib/array/uint8' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 * var smskrange = require( '@stdlib/stats/base/smskrange' );
 *
 * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
 * var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 ] );
-* var N = floor( x.length / 2 );
 *
-* var v = smskrange.ndarray( N, x, 2, 1, mask, 2, 1 );
+* var v = smskrange.ndarray( 5, x, 2, 1, mask, 2, 1 );
 * // returns 6.0
 */
 
diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/smskrange/lib/ndarray.js
index 6adc0019d3b8..b5e440b85c6b 100644
--- a/lib/node_modules/@stdlib/stats/base/smskrange/lib/ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/smskrange/lib/ndarray.js
@@ -41,13 +41,11 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
 * @example
 * var Float32Array = require( '@stdlib/array/float32' );
 * var Uint8Array = require( '@stdlib/array/uint8' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 *
 * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
 * var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 ] );
-* var N = floor( x.length / 2 );
 *
-* var v = smskrange( N, x, 2, 1, mask, 2, 1 );
+* var v = smskrange( 5, x, 2, 1, mask, 2, 1 );
 * // returns 6.0
 */
 function smskrange( N, x, strideX, offsetX, mask, strideMask, offsetMask ) {
diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/smskrange/lib/ndarray.native.js
index fd585dddcb46..a78caef56b78 100644
--- a/lib/node_modules/@stdlib/stats/base/smskrange/lib/ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/smskrange/lib/ndarray.native.js
@@ -20,9 +20,7 @@
 
 // MODULES //
 
-var Float32Array = require( '@stdlib/array/float32' );
-var Uint8Array = require( '@stdlib/array/uint8' );
-var addon = require( './smskrange.native.js' );
+var addon = require( './../src/addon.node' );
 
 
 // MAIN //
@@ -42,27 +40,15 @@ var addon = require( './smskrange.native.js' );
 * @example
 * var Float32Array = require( '@stdlib/array/float32' );
 * var Uint8Array = require( '@stdlib/array/uint8' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 *
 * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
 * var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 ] );
-* var N = floor( x.length / 2 );
 *
-* var v = smskrange( N, x, 2, 1, mask, 2, 1 );
+* var v = smskrange( 5, x, 2, 1, mask, 2, 1 );
 * // returns 6.0
 */
 function smskrange( N, x, strideX, offsetX, mask, strideMask, offsetMask ) {
-	var viewX;
-	var viewM;
-	if ( strideX < 0 ) {
-		offsetX += (N-1) * strideX;
-	}
-	if ( strideMask < 0 ) {
-		offsetMask += (N-1) * strideMask;
-	}
-	viewX = new Float32Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offsetX), x.length-offsetX ); // eslint-disable-line max-len
-	viewM = new Uint8Array( mask.buffer, mask.byteOffset+(mask.BYTES_PER_ELEMENT*offsetMask), mask.length-offsetMask ); // eslint-disable-line max-len
-	return addon( N, viewX, strideX, viewM, strideMask );
+	return addon.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask ); // eslint-disable-line max-len
 }
 
 
diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/lib/smskrange.js b/lib/node_modules/@stdlib/stats/base/smskrange/lib/smskrange.js
index 4271ae2074a7..2ebbc7254dc4 100644
--- a/lib/node_modules/@stdlib/stats/base/smskrange/lib/smskrange.js
+++ b/lib/node_modules/@stdlib/stats/base/smskrange/lib/smskrange.js
@@ -20,8 +20,8 @@
 
 // MODULES //
 
-var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' );
-var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
+var stride2offset = require( '@stdlib/strided/base/stride2offset' );
+var ndarray = require( './ndarray.js' );
 
 
 // MAIN //
@@ -47,59 +47,9 @@ var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
 * // returns 4.0
 */
 function smskrange( N, x, strideX, mask, strideMask ) {
-	var max;
-	var min;
-	var ix;
-	var im;
-	var v;
-	var i;
-
-	if ( N <= 0 ) {
-		return NaN;
-	}
-	if ( strideX < 0 ) {
-		ix = (1-N) * strideX;
-	} else {
-		ix = 0;
-	}
-	if ( strideMask < 0 ) {
-		im = (1-N) * strideMask;
-	} else {
-		im = 0;
-	}
-	for ( i = 0; i < N; i++ ) {
-		if ( mask[ im ] === 0 ) {
-			break;
-		}
-		ix += strideX;
-		im += strideMask;
-	}
-	if ( i === N ) {
-		return NaN;
-	}
-	min = x[ ix ];
-	if ( isnanf( min ) ) {
-		return min;
-	}
-	max = min;
-	i += 1;
-	for ( i; i < N; i++ ) {
-		ix += strideX;
-		im += strideMask;
-		if ( mask[ im ] ) {
-			continue;
-		}
-		v = x[ ix ];
-		if ( isnanf( v ) ) {
-			return v;
-		}
-		if ( v < min ) {
-			min = v;
-		} else if ( v > max ) {
-			max = v;
-		}
-	}
-	return float64ToFloat32( max - min );
+	var ox = stride2offset( N, strideX );
+	var om = stride2offset( N, strideMask );
+	return ndarray( N, x, strideX, ox, mask, strideMask, om );
 }
 
 
diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/manifest.json b/lib/node_modules/@stdlib/stats/base/smskrange/manifest.json
index c7df6f471c22..e0c0f648c89a 100644
--- a/lib/node_modules/@stdlib/stats/base/smskrange/manifest.json
+++ b/lib/node_modules/@stdlib/stats/base/smskrange/manifest.json
@@ -1,5 +1,8 @@
 {
-  "options": {},
+  "options": {
+    "task": "build",
+    "wasm": false
+  },
   "fields": [
     {
       "field": "src",
@@ -24,17 +27,76 @@
   ],
   "confs": [
     {
+      "task": "build",
+      "wasm": false,
       "src": [
-        "./src/smskrange.c"
+        "./src/main.c"
       ],
       "include": [
         "./include"
       ],
-      "libraries": [
-        "-lm"
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset",
+        "@stdlib/math/base/assert/is-nanf",
+        "@stdlib/napi/export",
+        "@stdlib/napi/argv",
+        "@stdlib/napi/argv-int64",
+        "@stdlib/napi/argv-strided-float32array",
+        "@stdlib/napi/argv-strided-uint8array",
+        "@stdlib/napi/create-double"
+      ]
+    },
+    {
+      "task": "benchmark",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset",
+        "@stdlib/math/base/assert/is-nanf"
+      ]
+    },
+    {
+      "task": "examples",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset",
+        "@stdlib/math/base/assert/is-nanf"
+      ]
+    },
+    {
+      "task": "",
+      "wasm": true,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
       ],
+      "libraries": [],
       "libpath": [],
       "dependencies": [
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset",
         "@stdlib/math/base/assert/is-nanf"
       ]
     }
diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/src/addon.c b/lib/node_modules/@stdlib/stats/base/smskrange/src/addon.c
new file mode 100644
index 000000000000..2763cecc3def
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/smskrange/src/addon.c
@@ -0,0 +1,66 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/smskrange.h"
+#include "stdlib/napi/export.h"
+#include "stdlib/napi/argv.h"
+#include "stdlib/napi/argv_int64.h"
+#include "stdlib/napi/argv_strided_float32array.h"
+#include "stdlib/napi/argv_strided_uint8array.h"
+#include "stdlib/napi/create_double.h"
+#include <node_api.h>
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 5 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 );
+	STDLIB_NAPI_ARGV_INT64( env, strideMask, argv, 4 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 );
+	STDLIB_NAPI_ARGV_STRIDED_UINT8ARRAY( env, Mask, N, strideMask, argv, 3 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_smskrange( N, X, strideX, Mask, strideMask ), v );
+	return v;
+}
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon_method( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 7 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 );
+	STDLIB_NAPI_ARGV_INT64( env, strideMask, argv, 5 );
+	STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 );
+	STDLIB_NAPI_ARGV_INT64( env, offsetMask, argv, 6 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 );
+	STDLIB_NAPI_ARGV_STRIDED_UINT8ARRAY( env, Mask, N, strideMask, argv, 4 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_smskrange_ndarray( N, X, strideX, offsetX, Mask, strideMask, offsetMask ), v );
+	return v;
+}
+
+STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method )
diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/smskrange/src/addon.cpp
deleted file mode 100644
index 5293805d7560..000000000000
--- a/lib/node_modules/@stdlib/stats/base/smskrange/src/addon.cpp
+++ /dev/null
@@ -1,153 +0,0 @@
-/**
-* @license Apache-2.0
-*
-* Copyright (c) 2020 The Stdlib Authors.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-*    http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-
-#include "stdlib/stats/base/smskrange.h"
-#include <node_api.h>
-#include <stdint.h>
-#include <stdlib.h>
-#include <stdbool.h>
-#include <assert.h>
-
-/**
-* Add-on namespace.
-*/
-namespace stdlib_stats_base_smskrange {
-
-	/**
-	* Computes the range of a single-precision floating-point strided array according to a mask.
-	*
-	* ## Notes
-	*
-	* -   When called from JavaScript, the function expects five arguments:
-	*
-	*     -   `N`: number of indexed elements
-	*     -   `X`: input array
-	*     -   `strideX`: `X` stride length
-	*     -   `Mask`: mask array
-	*     -   `strideMask`: `Mask` stride length
-	*/
-	napi_value node_smskrange( napi_env env, napi_callback_info info ) {
-		napi_status status;
-
-		size_t argc = 5;
-		napi_value argv[ 5 ];
-		status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr );
-		assert( status == napi_ok );
-
-		if ( argc < 5 ) {
-			napi_throw_error( env, nullptr, "invalid invocation. Must provide 5 arguments." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype0;
-		status = napi_typeof( env, argv[ 0 ], &vtype0 );
-		assert( status == napi_ok );
-		if ( vtype0 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." );
-			return nullptr;
-		}
-
-		bool res1;
-		status = napi_is_typedarray( env, argv[ 1 ], &res1 );
-		assert( status == napi_ok );
-		if ( res1 == false ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype2;
-		status = napi_typeof( env, argv[ 2 ], &vtype2 );
-		assert( status == napi_ok );
-		if ( vtype2 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." );
-			return nullptr;
-		}
-
-		bool res3;
-		status = napi_is_typedarray( env, argv[ 3 ], &res3 );
-		assert( status == napi_ok );
-		if ( res3 == false ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a Uint8Array." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype4;
-		status = napi_typeof( env, argv[ 4 ], &vtype4 );
-		assert( status == napi_ok );
-		if ( vtype4 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Fifth argument must be a number." );
-			return nullptr;
-		}
-
-		int64_t N;
-		status = napi_get_value_int64( env, argv[ 0 ], &N );
-		assert( status == napi_ok );
-
-		int64_t strideX;
-		status = napi_get_value_int64( env, argv[ 2 ], &strideX );
-		assert( status == napi_ok );
-
-		int64_t strideMask;
-		status = napi_get_value_int64( env, argv[ 4 ], &strideMask );
-		assert( status == napi_ok );
-
-		napi_typedarray_type vtype1;
-		size_t xlen;
-		void *X;
-		status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr );
-		assert( status == napi_ok );
-		if ( vtype1 != napi_float32_array ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." );
-			return nullptr;
-		}
-		if ( (N-1)*llabs(strideX) >= (int64_t)xlen ) {
-			napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." );
-			return nullptr;
-		}
-
-		napi_typedarray_type vtype3;
-		size_t mlen;
-		void *Mask;
-		status = napi_get_typedarray_info( env, argv[ 3 ], &vtype3, &mlen, &Mask, nullptr, nullptr );
-		assert( status == napi_ok );
-		if ( vtype3 != napi_uint8_array ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a Uint8Array." );
-			return nullptr;
-		}
-		if ( (N-1)*llabs(strideMask) >= (int64_t)mlen ) {
-			napi_throw_range_error( env, nullptr, "invalid argument. Fourth argument has insufficient elements based on the associated stride and the number of indexed elements." );
-			return nullptr;
-		}
-
-		napi_value v;
-		status = napi_create_double( env, (double)stdlib_strided_smskrange( N, (float *)X, strideX, (uint8_t *)Mask, strideMask ), &v );
-		assert( status == napi_ok );
-
-		return v;
-	}
-
-	napi_value Init( napi_env env, napi_value exports ) {
-		napi_status status;
-		napi_value fcn;
-		status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_smskrange, NULL, &fcn );
-		assert( status == napi_ok );
-		return fcn;
-	}
-
-	NAPI_MODULE( NODE_GYP_MODULE_NAME, Init )
-} // end namespace stdlib_stats_base_smskrange
diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/src/smskrange.c b/lib/node_modules/@stdlib/stats/base/smskrange/src/main.c
similarity index 57%
rename from lib/node_modules/@stdlib/stats/base/smskrange/src/smskrange.c
rename to lib/node_modules/@stdlib/stats/base/smskrange/src/main.c
index 76f8f58b90ec..f77c8b190320 100644
--- a/lib/node_modules/@stdlib/stats/base/smskrange/src/smskrange.c
+++ b/lib/node_modules/@stdlib/stats/base/smskrange/src/main.c
@@ -18,6 +18,8 @@
 
 #include "stdlib/stats/base/smskrange.h"
 #include "stdlib/math/base/assert/is_nanf.h"
+#include "stdlib/blas/base/shared.h"
+#include "stdlib/strided/base/stride2offset.h"
 #include <stdint.h>
 
 /**
@@ -30,10 +32,28 @@
 * @param strideMask  Mask stride length
 * @return            output value
 */
-float stdlib_strided_smskrange( const int64_t N, const float *X, const int64_t strideX, const uint8_t *Mask, const int64_t strideMask ) {
-	int64_t ix;
-	int64_t im;
-	int64_t i;
+float API_SUFFIX(stdlib_strided_smskrange)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const uint8_t *Mask, const CBLAS_INT strideMask ) {
+	const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX );
+	const CBLAS_INT om = stdlib_strided_stride2offset( N, strideMask );
+	return API_SUFFIX(stdlib_strided_smskrange_ndarray)( N, X, strideX, ox, Mask, strideMask, om );
+}
+
+/**
+* Computes the range of a single-precision floating-point strided array according to a mask and using alternative indexing semantics.
+*
+* @param N           number of indexed elements
+* @param X           input array
+* @param strideX     X stride length
+* @param offsetX     starting index for X
+* @param Mask        mask array
+* @param strideMask  Mask stride length
+* @param offsetMask  starting index for Mask
+* @return            output value
+*/
+float API_SUFFIX(stdlib_strided_smskrange_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const uint8_t *Mask, const CBLAS_INT strideMask, const CBLAS_INT offsetMask ) {
+	CBLAS_INT ix;
+	CBLAS_INT im;
+	CBLAS_INT i;
 	float max;
 	float min;
 	float v;
@@ -41,16 +61,8 @@ float stdlib_strided_smskrange( const int64_t N, const float *X, const int64_t s
 	if ( N <= 0 ) {
 		return 0.0f / 0.0f; // NaN
 	}
-	if ( strideX < 0 ) {
-		ix = (1-N) * strideX;
-	} else {
-		ix = 0;
-	}
-	if ( strideMask < 0 ) {
-		im = (1-N) * strideMask;
-	} else {
-		im = 0;
-	}
+	ix = offsetX;
+	im = offsetMask;
 	for ( i = 0; i < N; i++ ) {
 		if ( Mask[ im ] == 0 ) {
 			break;
diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/smskrange/test/test.ndarray.js
index a6cd963b305a..c76c1e7e3649 100644
--- a/lib/node_modules/@stdlib/stats/base/smskrange/test/test.ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/smskrange/test/test.ndarray.js
@@ -21,7 +21,6 @@
 // MODULES //
 
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
 var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' );
 var Float32Array = require( '@stdlib/array/float32' );
@@ -133,7 +132,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns `0`', fun
 
 tape( 'the function supports `stride` parameters', function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -162,8 +160,7 @@ tape( 'the function supports `stride` parameters', function test( t ) {
 		1
 	]);
 
-	N = floor( x.length / 2 );
-	v = smskrange( N, x, 2, 0, mask, 2, 0 );
+	v = smskrange( 5, x, 2, 0, mask, 2, 0 );
 
 	t.strictEqual( v, 6.0, 'returns expected value' );
 	t.end();
@@ -171,7 +168,6 @@ tape( 'the function supports `stride` parameters', function test( t ) {
 
 tape( 'the function supports negative `stride` parameters', function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -200,8 +196,7 @@ tape( 'the function supports negative `stride` parameters', function test( t ) {
 		0
 	]);
 
-	N = floor( x.length / 2 );
-	v = smskrange( N, x, -2, 8, mask, -2, 8 );
+	v = smskrange( 5, x, -2, 8, mask, -2, 8 );
 
 	t.strictEqual( v, 6.0, 'returns expected value' );
 	t.end();
@@ -209,7 +204,6 @@ tape( 'the function supports negative `stride` parameters', function test( t ) {
 
 tape( 'the function supports `offset` parameters', function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -237,9 +231,8 @@ tape( 'the function supports `offset` parameters', function test( t ) {
 		1,
 		1  // 4
 	]);
-	N = floor( x.length / 2 );
 
-	v = smskrange( N, x, 2, 1, mask, 2, 1 );
+	v = smskrange( 5, x, 2, 1, mask, 2, 1 );
 	t.strictEqual( v, 6.0, 'returns expected value' );
 
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/smskrange/test/test.ndarray.native.js
index d917632f957c..ff73ab2f459e 100644
--- a/lib/node_modules/@stdlib/stats/base/smskrange/test/test.ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/smskrange/test/test.ndarray.native.js
@@ -22,7 +22,6 @@
 
 var resolve = require( 'path' ).resolve;
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
 var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' );
 var Float32Array = require( '@stdlib/array/float32' );
@@ -120,7 +119,7 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu
 	v = smskrange( 0, x, 1, 0, mask, 1, 0 );
 	t.strictEqual( isnanf( v ), true, 'returns expected value' );
 
-	v = smskrange( -1, x, 1, 0, mask, 1 );
+	v = smskrange( -1, x, 1, 0, mask, 1, 0 );
 	t.strictEqual( isnanf( v ), true, 'returns expected value' );
 
 	t.end();
@@ -142,7 +141,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns `0`', opt
 
 tape( 'the function supports `stride` parameters', opts, function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -171,8 +169,7 @@ tape( 'the function supports `stride` parameters', opts, function test( t ) {
 		1
 	]);
 
-	N = floor( x.length / 2 );
-	v = smskrange( N, x, 2, 0, mask, 2, 0 );
+	v = smskrange( 5, x, 2, 0, mask, 2, 0 );
 
 	t.strictEqual( v, 6.0, 'returns expected value' );
 	t.end();
@@ -180,7 +177,6 @@ tape( 'the function supports `stride` parameters', opts, function test( t ) {
 
 tape( 'the function supports negative `stride` parameters', opts, function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -209,8 +205,7 @@ tape( 'the function supports negative `stride` parameters', opts, function test(
 		0
 	]);
 
-	N = floor( x.length / 2 );
-	v = smskrange( N, x, -2, 8, mask, -2, 8 );
+	v = smskrange( 5, x, -2, 8, mask, -2, 8 );
 
 	t.strictEqual( v, 6.0, 'returns expected value' );
 	t.end();
@@ -218,7 +213,6 @@ tape( 'the function supports negative `stride` parameters', opts, function test(
 
 tape( 'the function supports `offset` parameters', opts, function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -246,9 +240,8 @@ tape( 'the function supports `offset` parameters', opts, function test( t ) {
 		1,
 		1  // 4
 	]);
-	N = floor( x.length / 2 );
 
-	v = smskrange( N, x, 2, 1, mask, 2, 1 );
+	v = smskrange( 5, x, 2, 1, mask, 2, 1 );
 	t.strictEqual( v, 6.0, 'returns expected value' );
 
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/test/test.smskrange.js b/lib/node_modules/@stdlib/stats/base/smskrange/test/test.smskrange.js
index e1b424e0a57b..829148a81b61 100644
--- a/lib/node_modules/@stdlib/stats/base/smskrange/test/test.smskrange.js
+++ b/lib/node_modules/@stdlib/stats/base/smskrange/test/test.smskrange.js
@@ -21,7 +21,6 @@
 // MODULES //
 
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
 var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' );
 var Float32Array = require( '@stdlib/array/float32' );
@@ -133,7 +132,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns `0`', fun
 
 tape( 'the function supports `stride` parameters', function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -162,8 +160,7 @@ tape( 'the function supports `stride` parameters', function test( t ) {
 		1
 	]);
 
-	N = floor( x.length / 2 );
-	v = smskrange( N, x, 2, mask, 2 );
+	v = smskrange( 5, x, 2, mask, 2 );
 
 	t.strictEqual( v, 6.0, 'returns expected value' );
 	t.end();
@@ -171,7 +168,6 @@ tape( 'the function supports `stride` parameters', function test( t ) {
 
 tape( 'the function supports negative `stride` parameters', function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -200,8 +196,7 @@ tape( 'the function supports negative `stride` parameters', function test( t ) {
 		0
 	]);
 
-	N = floor( x.length / 2 );
-	v = smskrange( N, x, -2, mask, -2 );
+	v = smskrange( 5, x, -2, mask, -2 );
 
 	t.strictEqual( v, 6.0, 'returns expected value' );
 	t.end();
@@ -212,7 +207,6 @@ tape( 'the function supports view offsets', function test( t ) {
 	var mask1;
 	var x0;
 	var x1;
-	var N;
 	var v;
 
 	x0 = new Float32Array([
@@ -244,9 +238,8 @@ tape( 'the function supports view offsets', function test( t ) {
 
 	x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
 	mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
-	N = floor( x1.length/2 );
 
-	v = smskrange( N, x1, 2, mask1, 2 );
+	v = smskrange( 5, x1, 2, mask1, 2 );
 	t.strictEqual( v, 6.0, 'returns expected value' );
 
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/smskrange/test/test.smskrange.native.js b/lib/node_modules/@stdlib/stats/base/smskrange/test/test.smskrange.native.js
index 99aebd738b93..4dad84d3ec10 100644
--- a/lib/node_modules/@stdlib/stats/base/smskrange/test/test.smskrange.native.js
+++ b/lib/node_modules/@stdlib/stats/base/smskrange/test/test.smskrange.native.js
@@ -22,7 +22,6 @@
 
 var resolve = require( 'path' ).resolve;
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
 var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' );
 var Float32Array = require( '@stdlib/array/float32' );
@@ -142,7 +141,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns `0`', opt
 
 tape( 'the function supports `stride` parameters', opts, function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -171,8 +169,7 @@ tape( 'the function supports `stride` parameters', opts, function test( t ) {
 		1
 	]);
 
-	N = floor( x.length / 2 );
-	v = smskrange( N, x, 2, mask, 2 );
+	v = smskrange( 5, x, 2, mask, 2 );
 
 	t.strictEqual( v, 6.0, 'returns expected value' );
 	t.end();
@@ -180,7 +177,6 @@ tape( 'the function supports `stride` parameters', opts, function test( t ) {
 
 tape( 'the function supports negative `stride` parameters', opts, function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -209,8 +205,7 @@ tape( 'the function supports negative `stride` parameters', opts, function test(
 		0
 	]);
 
-	N = floor( x.length / 2 );
-	v = smskrange( N, x, -2, mask, -2 );
+	v = smskrange( 5, x, -2, mask, -2 );
 
 	t.strictEqual( v, 6.0, 'returns expected value' );
 	t.end();
@@ -221,7 +216,6 @@ tape( 'the function supports view offsets', opts, function test( t ) {
 	var mask1;
 	var x0;
 	var x1;
-	var N;
 	var v;
 
 	x0 = new Float32Array([
@@ -253,9 +247,8 @@ tape( 'the function supports view offsets', opts, function test( t ) {
 
 	x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
 	mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
-	N = floor( x1.length/2 );
 
-	v = smskrange( N, x1, 2, mask1, 2 );
+	v = smskrange( 5, x1, 2, mask1, 2 );
 	t.strictEqual( v, 6.0, 'returns expected value' );
 
 	t.end();

From e00710bdd16ec882eda01565cbe2c752db48cf42 Mon Sep 17 00:00:00 2001
From: Athan Reines <kgryte@gmail.com>
Date: Thu, 2 Jan 2025 02:29:50 -0800
Subject: [PATCH 06/87] style: align comments

---
type: pre_commit_static_analysis_report
description: Results of running static analysis checks when committing changes.
report:
  - task: lint_filenames
    status: passed
  - task: lint_editorconfig
    status: passed
  - task: lint_markdown
    status: na
  - task: lint_package_json
    status: na
  - task: lint_repl_help
    status: na
  - task: lint_javascript_src
    status: na
  - task: lint_javascript_cli
    status: na
  - task: lint_javascript_examples
    status: na
  - task: lint_javascript_tests
    status: passed
  - task: lint_javascript_benchmarks
    status: na
  - task: lint_python
    status: na
  - task: lint_r
    status: na
  - task: lint_c_src
    status: na
  - task: lint_c_examples
    status: na
  - task: lint_c_benchmarks
    status: na
  - task: lint_c_tests_fixtures
    status: na
  - task: lint_shell
    status: na
  - task: lint_typescript_declarations
    status: na
  - task: lint_typescript_tests
    status: na
  - task: lint_license_headers
    status: passed
---

---
type: pre_push_report
description: Results of running various checks prior to pushing changes.
report:
  - task: run_javascript_examples
    status: na
  - task: run_c_examples
    status: na
  - task: run_cpp_examples
    status: na
  - task: run_javascript_readme_examples
    status: na
  - task: run_c_benchmarks
    status: na
  - task: run_cpp_benchmarks
    status: na
  - task: run_fortran_benchmarks
    status: na
  - task: run_javascript_benchmarks
    status: na
  - task: run_julia_benchmarks
    status: na
  - task: run_python_benchmarks
    status: na
  - task: run_r_benchmarks
    status: na
  - task: run_javascript_tests
    status: passed
---
---
 .../@stdlib/stats/base/dmaxsorted/test/test.ndarray.js        | 4 ++--
 .../@stdlib/stats/base/dmaxsorted/test/test.ndarray.native.js | 4 ++--
 2 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dmaxsorted/test/test.ndarray.js
index 546d36c8f705..53c3c94950d5 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/test/test.ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/test/test.ndarray.js
@@ -125,7 +125,7 @@ tape( 'the function supports a `stride` parameter', function test( t ) {
 		2.0,
 		2.0,  // 1
 		-7.0,
-		3.0, // 2
+		3.0,  // 2
 		3.0,
 		4.0,  // 3
 		2.0
@@ -148,7 +148,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t )
 		2.0,
 		2.0,  // 2
 		-7.0,
-		3.0, // 1
+		3.0,  // 1
 		3.0,
 		4.0,  // 0
 		2.0
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmaxsorted/test/test.ndarray.native.js
index b18bc5d2b7aa..5c9980a47918 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/test/test.ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/test/test.ndarray.native.js
@@ -134,7 +134,7 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) {
 		2.0,
 		2.0,  // 1
 		-7.0,
-		3.0, // 2
+		3.0,  // 2
 		3.0,
 		4.0,  // 3
 		2.0
@@ -157,7 +157,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test
 		2.0,
 		2.0,  // 2
 		-7.0,
-		3.0, // 1
+		3.0,  // 1
 		3.0,
 		4.0,  // 0
 		2.0

From 0959d55ce1004f9a1b36164998407dfa38c149c3 Mon Sep 17 00:00:00 2001
From: Aayush Khanna <96649223+aayush0325@users.noreply.github.com>
Date: Thu, 2 Jan 2025 23:34:11 +0530
Subject: [PATCH 07/87] feat: add C ndarray interface and refactor
 implementation for `stats/base/dmskmin`

PR-URL: https://github.com/stdlib-js/stdlib/pull/4371
Reviewed-by: Athan Reines <kgryte@gmail.com>
Co-authored-by: stdlib-bot <82920195+stdlib-bot@users.noreply.github.com>
---
 .../@stdlib/stats/base/dmskmin/README.md      | 173 ++++++++++++++----
 .../stats/base/dmskmin/benchmark/benchmark.js |  31 ++--
 .../dmskmin/benchmark/benchmark.native.js     |  27 +--
 .../dmskmin/benchmark/benchmark.ndarray.js    |  31 ++--
 .../benchmark/benchmark.ndarray.native.js     |  27 +--
 .../dmskmin/benchmark/c/benchmark.length.c    |  56 +++++-
 .../@stdlib/stats/base/dmskmin/docs/repl.txt  |  24 ++-
 .../stats/base/dmskmin/examples/c/example.c   |  10 +-
 .../stats/base/dmskmin/examples/index.js      |  27 +--
 .../@stdlib/stats/base/dmskmin/include.gypi   |   2 +-
 .../include/stdlib/stats/base/dmskmin.h       |   8 +-
 .../@stdlib/stats/base/dmskmin/lib/dmskmin.js |  56 +-----
 .../@stdlib/stats/base/dmskmin/lib/index.js   |   4 +-
 .../@stdlib/stats/base/dmskmin/lib/ndarray.js |   3 +-
 .../stats/base/dmskmin/lib/ndarray.native.js  |  20 +-
 .../@stdlib/stats/base/dmskmin/manifest.json  |  73 +++++++-
 .../@stdlib/stats/base/dmskmin/src/addon.c    |  66 +++++++
 .../@stdlib/stats/base/dmskmin/src/addon.cpp  | 153 ----------------
 .../base/dmskmin/src/{dmskmin.c => main.c}    |  42 +++--
 .../stats/base/dmskmin/test/test.dmskmin.js   |  13 +-
 .../base/dmskmin/test/test.dmskmin.native.js  |  13 +-
 .../stats/base/dmskmin/test/test.ndarray.js   |  13 +-
 .../base/dmskmin/test/test.ndarray.native.js  |  15 +-
 23 files changed, 460 insertions(+), 427 deletions(-)
 create mode 100644 lib/node_modules/@stdlib/stats/base/dmskmin/src/addon.c
 delete mode 100644 lib/node_modules/@stdlib/stats/base/dmskmin/src/addon.cpp
 rename lib/node_modules/@stdlib/stats/base/dmskmin/src/{dmskmin.c => main.c} (56%)

diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/README.md b/lib/node_modules/@stdlib/stats/base/dmskmin/README.md
index 7f15599fe02c..7886fb7cb0e3 100644
--- a/lib/node_modules/@stdlib/stats/base/dmskmin/README.md
+++ b/lib/node_modules/@stdlib/stats/base/dmskmin/README.md
@@ -38,7 +38,7 @@ var dmskmin = require( '@stdlib/stats/base/dmskmin' );
 
 #### dmskmin( N, x, strideX, mask, strideMask )
 
-Computes the minimum value of a double-precision floating-point strided array `x` according to a `mask`.
+Computes the minimum value of a double-precision floating-point strided array according to a mask.
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
@@ -55,22 +55,20 @@ The function has the following parameters:
 
 -   **N**: number of indexed elements.
 -   **x**: input [`Float64Array`][@stdlib/array/float64].
--   **strideX**: index increment for `x`.
+-   **strideX**: stride length for `x`.
 -   **mask**: mask [`Uint8Array`][@stdlib/array/uint8]. If a `mask` array element is `0`, the corresponding element in `x` is considered valid and **included** in computation. If a `mask` array element is `1`, the corresponding element in `x` is considered invalid/missing and **excluded** from computation.
--   **strideMask**: index increment for `mask`.
+-   **strideMask**: stride length for `mask`.
 
-The `N` and `stride` parameters determine which elements are accessed at runtime. For example, to compute the minimum value of every other element in `x`,
+The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the minimum value of every other element in `x`,
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
 var Uint8Array = require( '@stdlib/array/uint8' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x = new Float64Array( [ 1.0, 2.0, 7.0, -2.0, -4.0, 3.0, -5.0, -6.0 ] );
 var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] );
-var N = floor( x.length / 2 );
 
-var v = dmskmin( N, x, 2, mask, 2 );
+var v = dmskmin( 4, x, 2, mask, 2 );
 // returns -4.0
 ```
 
@@ -81,7 +79,6 @@ Note that indexing is relative to the first index. To introduce offsets, use [`t
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
 var Uint8Array = require( '@stdlib/array/uint8' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x0 = new Float64Array( [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, -5.0, -6.0 ] );
 var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
@@ -89,15 +86,13 @@ var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd
 var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] );
 var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
 
-var N = floor( x0.length / 2 );
-
-var v = dmskmin( N, x1, 2, mask1, 2 );
+var v = dmskmin( 4, x1, 2, mask1, 2 );
 // returns -2.0
 ```
 
 #### dmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )
 
-Computes the minimum value of a double-precision floating-point strided array according to a `mask` and using alternative indexing semantics.
+Computes the minimum value of a double-precision floating-point strided array according to a mask and using alternative indexing semantics.
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
@@ -115,18 +110,16 @@ The function has the following additional parameters:
 -   **offsetX**: starting index for `x`.
 -   **offsetMask**: starting index for `mask`.
 
-While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the minimum value for every other value in `x` starting from the second value
+While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on a starting indices. For example, to calculate the minimum value for every other element in `x` starting from the second element
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
 var Uint8Array = require( '@stdlib/array/uint8' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x = new Float64Array( [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, -5.0, -6.0 ] );
 var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] );
-var N = floor( x.length / 2 );
 
-var v = dmskmin.ndarray( N, x, 2, 1, mask, 2, 1 );
+var v = dmskmin.ndarray( 4, x, 2, 1, mask, 2, 1 );
 // returns -2.0
 ```
 
@@ -151,26 +144,19 @@ var v = dmskmin.ndarray( N, x, 2, 1, mask, 2, 1 );
 <!-- eslint no-undef: "error" -->
 
 ```javascript
-var randu = require( '@stdlib/random/base/randu' );
-var round = require( '@stdlib/math/base/special/round' );
-var Float64Array = require( '@stdlib/array/float64' );
-var Uint8Array = require( '@stdlib/array/uint8' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var bernoulli = require( '@stdlib/random/array/bernoulli' );
 var dmskmin = require( '@stdlib/stats/base/dmskmin' );
 
-var mask;
-var x;
-var i;
-
-x = new Float64Array( 10 );
-mask = new Uint8Array( x.length );
-for ( i = 0; i < x.length; i++ ) {
-    if ( randu() < 0.2 ) {
-        mask[ i ] = 1;
-    } else {
-        mask[ i ] = 0;
-    }
-    x[ i ] = round( (randu()*100.0) - 50.0 );
-}
+var uniformOptions = {
+    'dtype': 'float64'
+};
+var bernoulliOptions = {
+    'dtype': 'uint8'
+};
+
+var x = uniform( 10, -50.0, 50.0, uniformOptions );
+var mask = bernoulli( x.length, 0.2, bernoulliOptions );
 console.log( x );
 console.log( mask );
 
@@ -182,6 +168,125 @@ console.log( v );
 
 <!-- /.examples -->
 
+<!-- C usage documentation. -->
+
+<section class="usage">
+
+### Usage
+
+```c
+#include "stdlib/stats/base/dmskmin.h"
+```
+
+#### stdlib_strided_dmskmin( N, \*X, strideX, \*Mask, strideMask )
+
+Computes the minimum value of a double-precision floating-point strided array according to a mask.
+
+```c
+#include <stdint.h>
+
+const double x[] = { 1.0, -2.0, 2.0 };
+const uint8_t mask[] = { 0, 1, 0 };
+
+double v = stdlib_strided_dmskmin( 3, x, 1, mask, 1 );
+// returns 1.0
+```
+
+The function accepts the following arguments:
+
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **X**: `[in] double*` input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+-   **Mask**: `[in] uint8_t*` mask array. If a `Mask` array element is `0`, the corresponding element in `X` is considered valid and included in computation. If a `Mask` array element is `1`, the corresponding element in `X` is considered invalid/missing and excluded from computation.
+-   **strideMask**: `[in] CBLAS_INT` stride length for `Mask`.
+
+```c
+double stdlib_strided_dmskmin( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const uint8_t *Mask, const CBLAS_INT strideMask );
+```
+
+<!-- lint disable maximum-heading-length -->
+
+#### stdlib_strided_dmskmin_ndarray( N, \*X, strideX, offsetX, \*Mask, strideMask, offsetMask )
+
+Computes the minimum value of a double-precision floating-point strided array according to a mask and using alternative indexing semantics.
+
+```c
+#include <stdint.h>
+
+const double x[] = { 1.0, -2.0, 2.0 };
+const uint8_t mask[] = { 0, 1, 0 };
+
+double v = stdlib_strided_dmskmin( 3, x, 1, 0, mask, 1, 0 );
+// returns 1.0
+```
+
+The function accepts the following arguments:
+
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **X**: `[in] double*` input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+-   **offsetX**: `[in] CBLAS_INT` starting index for `X`.
+-   **Mask**: `[in] uint8_t*` mask array. If a `Mask` array element is `0`, the corresponding element in `X` is considered valid and included in computation. If a `Mask` array element is `1`, the corresponding element in `X` is considered invalid/missing and excluded from computation.
+-   **strideMask**: `[in] CBLAS_INT` stride length for `Mask`.
+-   **offsetMask**: `[in] CBLAS_INT` starting index for `Mask`.
+
+```c
+double stdlib_strided_dmskmin_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const uint8_t *Mask, const CBLAS_INT strideMask, const CBLAS_INT offsetMask );
+```
+
+</section>
+
+<!-- /.usage -->
+
+<!-- C API usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="notes">
+
+</section>
+
+<!-- /.notes -->
+
+<!-- C API usage examples. -->
+
+<section class="examples">
+
+### Examples
+
+```c
+#include "stdlib/stats/base/dmskmin.h"
+#include <stdint.h>
+#include <stdio.h>
+
+int main( void ) {
+    // Create a strided array:
+    const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 };
+
+    // Create a mask array:
+    const uint8_t mask[] = { 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 };
+
+    // Specify the number of elements:
+    const int N = 5;
+
+    // Specify the stride lengths:
+    const int strideX = 2;
+    const int strideMask = 2;
+
+    // Compute the minimum value:
+    double v = stdlib_strided_dmskmin( N, x, strideX, mask, strideMask );
+
+    // Print the result:
+    printf( "min: %lf\n", v );
+}
+```
+
+</section>
+
+<!-- /.examples -->
+
+</section>
+
+<!-- /.c -->
+
 <!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
 
 <section class="related">
diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dmskmin/benchmark/benchmark.js
index 50b44e6d5266..3dd78bbe6c98 100644
--- a/lib/node_modules/@stdlib/stats/base/dmskmin/benchmark/benchmark.js
+++ b/lib/node_modules/@stdlib/stats/base/dmskmin/benchmark/benchmark.js
@@ -21,15 +21,24 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var bernoulli = require( '@stdlib/random/array/bernoulli' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float64Array = require( '@stdlib/array/float64' );
-var Uint8Array = require( '@stdlib/array/uint8' );
 var pkg = require( './../package.json' ).name;
 var dmskmin = require( './../lib/dmskmin.js' );
 
 
+// VARIABLES //
+
+var uniformOptions = {
+	'dtype': 'float64'
+};
+var bernoulliOptions = {
+	'dtype': 'uint8'
+};
+
+
 // FUNCTIONS //
 
 /**
@@ -40,20 +49,8 @@ var dmskmin = require( './../lib/dmskmin.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var mask;
-	var x;
-	var i;
-
-	x = new Float64Array( len );
-	mask = new Uint8Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		if ( randu() < 0.2 ) {
-			mask[ i ] = 1;
-		} else {
-			mask[ i ] = 0;
-		}
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
+	var mask = bernoulli( len, 0.2, bernoulliOptions );
+	var x = uniform( len, -10.0, 10.0, uniformOptions );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dmskmin/benchmark/benchmark.native.js
index b757c6df95d4..b5774740b75e 100644
--- a/lib/node_modules/@stdlib/stats/base/dmskmin/benchmark/benchmark.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dmskmin/benchmark/benchmark.native.js
@@ -22,11 +22,10 @@
 
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var bernoulli = require( '@stdlib/random/array/bernoulli' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float64Array = require( '@stdlib/array/float64' );
-var Uint8Array = require( '@stdlib/array/uint8' );
 var tryRequire = require( '@stdlib/utils/try-require' );
 var pkg = require( './../package.json' ).name;
 
@@ -37,6 +36,12 @@ var dmskmin = tryRequire( resolve( __dirname, './../lib/dmskmin.native.js' ) );
 var opts = {
 	'skip': ( dmskmin instanceof Error )
 };
+var uniformOptions = {
+	'dtype': 'float64'
+};
+var bernoulliOptions = {
+	'dtype': 'uint8'
+};
 
 
 // FUNCTIONS //
@@ -49,20 +54,8 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var mask;
-	var x;
-	var i;
-
-	x = new Float64Array( len );
-	mask = new Uint8Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		if ( randu() < 0.2 ) {
-			mask[ i ] = 1;
-		} else {
-			mask[ i ] = 0;
-		}
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
+	var mask = bernoulli( len, 0.2, bernoulliOptions );
+	var x = uniform( len, -10.0, 10.0, uniformOptions );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/dmskmin/benchmark/benchmark.ndarray.js
index 902a67af63eb..da95dc91adf4 100644
--- a/lib/node_modules/@stdlib/stats/base/dmskmin/benchmark/benchmark.ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/dmskmin/benchmark/benchmark.ndarray.js
@@ -21,15 +21,24 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var bernoulli = require( '@stdlib/random/array/bernoulli' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float64Array = require( '@stdlib/array/float64' );
-var Uint8Array = require( '@stdlib/array/uint8' );
 var pkg = require( './../package.json' ).name;
 var dmskmin = require( './../lib/ndarray.js' );
 
 
+// VARIABLES //
+
+var uniformOptions = {
+	'dtype': 'float64'
+};
+var bernoulliOptions = {
+	'dtype': 'uint8'
+};
+
+
 // FUNCTIONS //
 
 /**
@@ -40,20 +49,8 @@ var dmskmin = require( './../lib/ndarray.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var mask;
-	var x;
-	var i;
-
-	x = new Float64Array( len );
-	mask = new Uint8Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		if ( randu() < 0.2 ) {
-			mask[ i ] = 1;
-		} else {
-			mask[ i ] = 0;
-		}
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
+	var mask = bernoulli( len, 0.2, bernoulliOptions );
+	var x = uniform( len, -10.0, 10.0, uniformOptions );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmskmin/benchmark/benchmark.ndarray.native.js
index 6d8897c6dd31..6e7b504fd865 100644
--- a/lib/node_modules/@stdlib/stats/base/dmskmin/benchmark/benchmark.ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dmskmin/benchmark/benchmark.ndarray.native.js
@@ -22,11 +22,10 @@
 
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var bernoulli = require( '@stdlib/random/array/bernoulli' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float64Array = require( '@stdlib/array/float64' );
-var Uint8Array = require( '@stdlib/array/uint8' );
 var tryRequire = require( '@stdlib/utils/try-require' );
 var pkg = require( './../package.json' ).name;
 
@@ -37,6 +36,12 @@ var dmskmin = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) );
 var opts = {
 	'skip': ( dmskmin instanceof Error )
 };
+var uniformOptions = {
+	'dtype': 'float64'
+};
+var bernoulliOptions = {
+	'dtype': 'uint8'
+};
 
 
 // FUNCTIONS //
@@ -49,20 +54,8 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var mask;
-	var x;
-	var i;
-
-	x = new Float64Array( len );
-	mask = new Uint8Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		if ( randu() < 0.2 ) {
-			mask[ i ] = 1;
-		} else {
-			mask[ i ] = 0;
-		}
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
+	var mask = bernoulli( len, 0.2, bernoulliOptions );
+	var x = uniform( len, -10.0, 10.0, uniformOptions );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dmskmin/benchmark/c/benchmark.length.c
index 81bbf03e14a5..eb44fa95f589 100644
--- a/lib/node_modules/@stdlib/stats/base/dmskmin/benchmark/c/benchmark.length.c
+++ b/lib/node_modules/@stdlib/stats/base/dmskmin/benchmark/c/benchmark.length.c
@@ -94,7 +94,7 @@ static double rand_double( void ) {
 * @param len          array length
 * @return             elapsed time in seconds
 */
-static double benchmark( int iterations, int len ) {
+static double benchmark1( int iterations, int len ) {
 	unsigned char mask[ len ];
 	double elapsed;
 	double x[ len ];
@@ -113,6 +113,7 @@ static double benchmark( int iterations, int len ) {
 	v = 0.0;
 	t = tic();
 	for ( i = 0; i < iterations; i++ ) {
+		// cppcheck-suppress uninitvar
 		v = stdlib_strided_dmskmin( len, x, 1, mask, 1 );
 		if ( v != v ) {
 			printf( "should not return NaN\n" );
@@ -126,6 +127,46 @@ static double benchmark( int iterations, int len ) {
 	return elapsed;
 }
 
+/**
+* Runs a benchmark.
+*
+* @param iterations   number of iterations
+* @param len          array length
+* @return             elapsed time in seconds
+*/
+static double benchmark2( int iterations, int len ) {
+	unsigned char mask[ len ];
+	double elapsed;
+	double x[ len ];
+	double v;
+	double t;
+	int i;
+
+	for ( i = 0; i < len; i++ ) {
+		if ( rand_double() < 0.2 ) {
+			mask[ i ] = 1; // missing
+		} else {
+			mask[ i ] = 0;
+		}
+		x[ i ] = ( rand_double() * 20000.0 ) - 10000.0;
+	}
+	v = 0.0;
+	t = tic();
+	for ( i = 0; i < iterations; i++ ) {
+		// cppcheck-suppress uninitvar
+		v = stdlib_strided_dmskmin_ndarray( len, x, 1, 0, mask, 1, 0 );
+		if ( v != v ) {
+			printf( "should not return NaN\n" );
+			break;
+		}
+	}
+	elapsed = tic() - t;
+	if ( v != v ) {
+		printf( "should not return NaN\n" );
+	}
+	return elapsed;
+}
+
 /**
 * Main execution sequence.
 */
@@ -148,7 +189,18 @@ int main( void ) {
 		for ( j = 0; j < REPEATS; j++ ) {
 			count += 1;
 			printf( "# c::%s:len=%d\n", NAME, len );
-			elapsed = benchmark( iter, len );
+			elapsed = benchmark1( iter, len );
+			print_results( iter, elapsed );
+			printf( "ok %d benchmark finished\n", count );
+		}
+	}
+	for ( i = MIN; i <= MAX; i++ ) {
+		len = pow( 10, i );
+		iter = ITERATIONS / pow( 10, i-1 );
+		for ( j = 0; j < REPEATS; j++ ) {
+			count += 1;
+			printf( "# c::%s:ndarray:len=%d\n", NAME, len );
+			elapsed = benchmark2( iter, len );
 			print_results( iter, elapsed );
 			printf( "ok %d benchmark finished\n", count );
 		}
diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dmskmin/docs/repl.txt
index 8205792a6759..573087eb0ff6 100644
--- a/lib/node_modules/@stdlib/stats/base/dmskmin/docs/repl.txt
+++ b/lib/node_modules/@stdlib/stats/base/dmskmin/docs/repl.txt
@@ -3,8 +3,8 @@
     Computes the minimum value of a double-precision floating-point strided
     array according to a mask.
 
-    The `N` and `stride` parameters determine which elements are accessed at
-    runtime.
+    The `N` and stride parameters determine which elements in the strided arrays
+    are accessed at runtime.
 
     Indexing is relative to the first index. To introduce offsets, use a typed
     array views.
@@ -26,13 +26,13 @@
         Input array.
 
     strideX: integer
-        Index increment for `x`.
+        Stride Length for `x`.
 
     mask: Uint8Array
         Mask array.
 
     strideMask: integer
-        Index increment for `mask`.
+        Stride Length for `mask`.
 
     Returns
     -------
@@ -47,11 +47,10 @@
     > {{alias}}( x.length, x, 1, mask, 1 )
     -2.0
 
-    // Using `N` and `stride` parameters:
+    // Using `N` and stride parameters:
     > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );
     > mask = new {{alias:@stdlib/array/uint8}}( [ 0, 0, 0, 0, 0, 0, 1 ] );
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > {{alias}}( N, x, 2, mask, 2 )
+    > {{alias}}( 3, x, 2, mask, 2 )
     -2.0
 
     // Using view offsets:
@@ -59,10 +58,10 @@
     > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );
     > var mask0 = new {{alias:@stdlib/array/uint8}}( [ 0, 0, 0, 0, 0, 0, 1 ] );
     > var mask1 = new {{alias:@stdlib/array/uint8}}( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );
-    > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );
-    > {{alias}}( N, x1, 2, mask1, 2 )
+    > {{alias}}( 3, x1, 2, mask1, 2 )
     -2.0
 
+
 {{alias}}.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )
     Computes the minimum value of a double-precision floating-point strided
     array according to a mask and using alternative indexing semantics.
@@ -80,7 +79,7 @@
         Input array.
 
     strideX: integer
-        Index increment for `x`.
+        Stride Length for `x`.
 
     offsetX: integer
         Starting index for `x`.
@@ -89,7 +88,7 @@
         Mask array.
 
     strideMask: integer
-        Index increment for `mask`.
+        Stride Length for `mask`.
 
     offsetMask: integer
         Starting index for `mask`.
@@ -110,8 +109,7 @@
     // Using offset parameter:
     > x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );
     > mask = new {{alias:@stdlib/array/uint8}}( [ 0, 0, 0, 0, 0, 0, 1 ] );
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > {{alias}}.ndarray( N, x, 2, 1, mask, 2, 1 )
+    > {{alias}}.ndarray( 3, x, 2, 1, mask, 2, 1 )
     -2.0
 
     See Also
diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dmskmin/examples/c/example.c
index 5d83cdd2c079..9fa5cafa30f6 100644
--- a/lib/node_modules/@stdlib/stats/base/dmskmin/examples/c/example.c
+++ b/lib/node_modules/@stdlib/stats/base/dmskmin/examples/c/example.c
@@ -22,17 +22,17 @@
 
 int main( void ) {
 	// Create a strided array:
-	double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 };
+	const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 };
 
 	// Create a mask array:
-	uint8_t mask[] = { 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 };
+	const uint8_t mask[] = { 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 };
 
 	// Specify the number of elements:
-	int64_t N = 5;
+	const int N = 5;
 
 	// Specify the stride lengths:
-	int64_t strideX = 2;
-	int64_t strideMask = 2;
+	const int strideX = 2;
+	const int strideMask = 2;
 
 	// Compute the minimum value:
 	double v = stdlib_strided_dmskmin( N, x, strideX, mask, strideMask );
diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/examples/index.js b/lib/node_modules/@stdlib/stats/base/dmskmin/examples/index.js
index ccdc244a1c2b..cd17ef2d8fd1 100644
--- a/lib/node_modules/@stdlib/stats/base/dmskmin/examples/index.js
+++ b/lib/node_modules/@stdlib/stats/base/dmskmin/examples/index.js
@@ -18,26 +18,19 @@
 
 'use strict';
 
-var randu = require( '@stdlib/random/base/randu' );
-var round = require( '@stdlib/math/base/special/round' );
-var Float64Array = require( '@stdlib/array/float64' );
-var Uint8Array = require( '@stdlib/array/uint8' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var bernoulli = require( '@stdlib/random/array/bernoulli' );
 var dmskmin = require( './../lib' );
 
-var mask;
-var x;
-var i;
+var uniformOptions = {
+	'dtype': 'float64'
+};
+var bernoulliOptions = {
+	'dtype': 'uint8'
+};
 
-x = new Float64Array( 10 );
-mask = new Uint8Array( x.length );
-for ( i = 0; i < x.length; i++ ) {
-	if ( randu() < 0.2 ) {
-		mask[ i ] = 1;
-	} else {
-		mask[ i ] = 0;
-	}
-	x[ i ] = round( (randu()*100.0) - 50.0 );
-}
+var x = uniform( 10, -50.0, 50.0, uniformOptions );
+var mask = bernoulli( x.length, 0.2, bernoulliOptions );
 console.log( x );
 console.log( mask );
 
diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/include.gypi b/lib/node_modules/@stdlib/stats/base/dmskmin/include.gypi
index 868c5c12e852..26476a8c2655 100644
--- a/lib/node_modules/@stdlib/stats/base/dmskmin/include.gypi
+++ b/lib/node_modules/@stdlib/stats/base/dmskmin/include.gypi
@@ -36,7 +36,7 @@
 
     # Source files:
     'src_files': [
-      '<(src_dir)/addon.cpp',
+      '<(src_dir)/addon.c',
       '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).src; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
     ],
 
diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/include/stdlib/stats/base/dmskmin.h b/lib/node_modules/@stdlib/stats/base/dmskmin/include/stdlib/stats/base/dmskmin.h
index 84b9e8a2c1a4..5485649e2ab0 100644
--- a/lib/node_modules/@stdlib/stats/base/dmskmin/include/stdlib/stats/base/dmskmin.h
+++ b/lib/node_modules/@stdlib/stats/base/dmskmin/include/stdlib/stats/base/dmskmin.h
@@ -19,6 +19,7 @@
 #ifndef STDLIB_STATS_BASE_DMSKMIN_H
 #define STDLIB_STATS_BASE_DMSKMIN_H
 
+#include "stdlib/blas/base/shared.h"
 #include <stdint.h>
 
 /*
@@ -31,7 +32,12 @@ extern "C" {
 /**
 * Computes the minimum value of a double-precision floating-point strided array according to a mask.
 */
-double stdlib_strided_dmskmin( const int64_t N, const double *X, const int64_t strideX, const uint8_t *Mask, const int64_t strideMask );
+double API_SUFFIX(stdlib_strided_dmskmin)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const uint8_t *Mask, const CBLAS_INT strideMask );
+
+/**
+* Computes the minimum value of a double-precision floating-point strided array according to a mask and using alternative indexing semantics.
+*/
+double API_SUFFIX(stdlib_strided_dmskmin_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const uint8_t *Mask, const CBLAS_INT strideMask, const CBLAS_INT offsetMask );
 
 #ifdef __cplusplus
 }
diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/lib/dmskmin.js b/lib/node_modules/@stdlib/stats/base/dmskmin/lib/dmskmin.js
index 86d2e78c4626..c3d59d082840 100644
--- a/lib/node_modules/@stdlib/stats/base/dmskmin/lib/dmskmin.js
+++ b/lib/node_modules/@stdlib/stats/base/dmskmin/lib/dmskmin.js
@@ -20,8 +20,8 @@
 
 // MODULES //
 
-var isnan = require( '@stdlib/math/base/assert/is-nan' );
-var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' );
+var stride2offset = require( '@stdlib/strided/base/stride2offset' );
+var ndarray = require( './ndarray.js' );
 
 
 // MAIN //
@@ -47,55 +47,9 @@ var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' );
 * // returns -2.0
 */
 function dmskmin( N, x, strideX, mask, strideMask ) {
-	var min;
-	var ix;
-	var im;
-	var v;
-	var i;
-
-	if ( N <= 0 ) {
-		return NaN;
-	}
-	if ( strideX < 0 ) {
-		ix = (1-N) * strideX;
-	} else {
-		ix = 0;
-	}
-	if ( strideMask < 0 ) {
-		im = (1-N) * strideMask;
-	} else {
-		im = 0;
-	}
-	for ( i = 0; i < N; i++ ) {
-		if ( mask[ im ] === 0 ) {
-			break;
-		}
-		ix += strideX;
-		im += strideMask;
-	}
-	if ( i === N ) {
-		return NaN;
-	}
-	min = x[ ix ];
-	if ( isnan( min ) ) {
-		return min;
-	}
-	i += 1;
-	for ( i; i < N; i++ ) {
-		ix += strideX;
-		im += strideMask;
-		if ( mask[ im ] ) {
-			continue;
-		}
-		v = x[ ix ];
-		if ( isnan( v ) ) {
-			return v;
-		}
-		if ( v < min || ( v === min && isNegativeZero( v ) ) ) {
-			min = v;
-		}
-	}
-	return min;
+	var ox = stride2offset( N, strideX );
+	var om = stride2offset( N, strideMask );
+	return ndarray( N, x, strideX, ox, mask, strideMask, om );
 }
 
 
diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/lib/index.js b/lib/node_modules/@stdlib/stats/base/dmskmin/lib/index.js
index 12a4a30d4a40..8bfd1833449b 100644
--- a/lib/node_modules/@stdlib/stats/base/dmskmin/lib/index.js
+++ b/lib/node_modules/@stdlib/stats/base/dmskmin/lib/index.js
@@ -37,14 +37,12 @@
 * @example
 * var Float64Array = require( '@stdlib/array/float64' );
 * var Uint8Array = require( '@stdlib/array/uint8' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 * var dmskmin = require( '@stdlib/stats/base/dmskmin' );
 *
 * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, -5.0, -6.0 ] );
 * var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 ] );
-* var N = floor( x.length / 2 );
 *
-* var v = dmskmin.ndarray( N, x, 2, 1, mask, 2, 1 );
+* var v = dmskmin.ndarray( 5, x, 2, 1, mask, 2, 1 );
 * // returns -2.0
 */
 
diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/dmskmin/lib/ndarray.js
index 6bcbe3bbe996..20258d249ac7 100644
--- a/lib/node_modules/@stdlib/stats/base/dmskmin/lib/ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/dmskmin/lib/ndarray.js
@@ -45,9 +45,8 @@ var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' );
 *
 * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, -5.0, -6.0 ] );
 * var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 ] );
-* var N = floor( x.length / 2 );
 *
-* var v = dmskmin( N, x, 2, 1, mask, 2, 1 );
+* var v = dmskmin( 5, x, 2, 1, mask, 2, 1 );
 * // returns -2.0
 */
 function dmskmin( N, x, strideX, offsetX, mask, strideMask, offsetMask ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmskmin/lib/ndarray.native.js
index 3a19aef5489e..46405c90df59 100644
--- a/lib/node_modules/@stdlib/stats/base/dmskmin/lib/ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dmskmin/lib/ndarray.native.js
@@ -20,9 +20,7 @@
 
 // MODULES //
 
-var Float64Array = require( '@stdlib/array/float64' );
-var Uint8Array = require( '@stdlib/array/uint8' );
-var addon = require( './dmskmin.native.js' );
+var addon = require( './../src/addon.node' );
 
 
 // MAIN //
@@ -42,27 +40,15 @@ var addon = require( './dmskmin.native.js' );
 * @example
 * var Float64Array = require( '@stdlib/array/float64' );
 * var Uint8Array = require( '@stdlib/array/uint8' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 *
 * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, -5.0, -6.0 ] );
 * var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 ] );
-* var N = floor( x.length / 2 );
 *
-* var v = dmskmin( N, x, 2, 1, mask, 2, 1 );
+* var v = dmskmin( 5, x, 2, 1, mask, 2, 1 );
 * // returns -2.0
 */
 function dmskmin( N, x, strideX, offsetX, mask, strideMask, offsetMask ) {
-	var viewX;
-	var viewM;
-	if ( strideX < 0 ) {
-		offsetX += (N-1) * strideX;
-	}
-	if ( strideMask < 0 ) {
-		offsetMask += (N-1) * strideMask;
-	}
-	viewX = new Float64Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offsetX), x.length-offsetX ); // eslint-disable-line max-len
-	viewM = new Uint8Array( mask.buffer, mask.byteOffset+(mask.BYTES_PER_ELEMENT*offsetMask), mask.length-offsetMask ); // eslint-disable-line max-len
-	return addon( N, viewX, strideX, viewM, strideMask );
+	return addon.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask ); // eslint-disable-line max-len
 }
 
 
diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/manifest.json b/lib/node_modules/@stdlib/stats/base/dmskmin/manifest.json
index 6481051a91a9..3f0b4cbbc446 100644
--- a/lib/node_modules/@stdlib/stats/base/dmskmin/manifest.json
+++ b/lib/node_modules/@stdlib/stats/base/dmskmin/manifest.json
@@ -1,5 +1,8 @@
 {
-  "options": {},
+  "options": {
+    "task": "build",
+    "wasm": false
+  },
   "fields": [
     {
       "field": "src",
@@ -24,17 +27,79 @@
   ],
   "confs": [
     {
+      "task": "build",
+      "wasm": false,
       "src": [
-        "./src/dmskmin.c"
+        "./src/main.c"
       ],
       "include": [
         "./include"
       ],
-      "libraries": [
-        "-lm"
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset",
+        "@stdlib/math/base/assert/is-negative-zero",
+        "@stdlib/math/base/assert/is-nan",
+        "@stdlib/napi/export",
+        "@stdlib/napi/argv",
+        "@stdlib/napi/argv-int64",
+        "@stdlib/napi/argv-strided-float64array",
+        "@stdlib/napi/argv-strided-uint8array",
+        "@stdlib/napi/create-double"
+      ]
+    },
+    {
+      "task": "benchmark",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset",
+        "@stdlib/math/base/assert/is-nan",
+        "@stdlib/math/base/assert/is-negative-zero"
+      ]
+    },
+    {
+      "task": "examples",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset",
+        "@stdlib/math/base/assert/is-nan",
+        "@stdlib/math/base/assert/is-negative-zero"
+      ]
+    },
+    {
+      "task": "",
+      "wasm": true,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
       ],
+      "libraries": [],
       "libpath": [],
       "dependencies": [
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset",
         "@stdlib/math/base/assert/is-nan",
         "@stdlib/math/base/assert/is-negative-zero"
       ]
diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/src/addon.c b/lib/node_modules/@stdlib/stats/base/dmskmin/src/addon.c
new file mode 100644
index 000000000000..d56a9c13acd5
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dmskmin/src/addon.c
@@ -0,0 +1,66 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/dmskmin.h"
+#include "stdlib/napi/export.h"
+#include "stdlib/napi/argv.h"
+#include "stdlib/napi/argv_int64.h"
+#include "stdlib/napi/argv_strided_float64array.h"
+#include "stdlib/napi/argv_strided_uint8array.h"
+#include "stdlib/napi/create_double.h"
+#include <node_api.h>
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 5 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 );
+	STDLIB_NAPI_ARGV_INT64( env, strideMask, argv, 4 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 );
+	STDLIB_NAPI_ARGV_STRIDED_UINT8ARRAY( env, Mask, N, strideMask, argv, 3 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dmskmin( N, X, strideX, Mask, strideMask ), v );
+	return v;
+}
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon_method( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 7 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 );
+	STDLIB_NAPI_ARGV_INT64( env, strideMask, argv, 5 );
+	STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 );
+	STDLIB_NAPI_ARGV_INT64( env, offsetMask, argv, 6 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 );
+	STDLIB_NAPI_ARGV_STRIDED_UINT8ARRAY( env, Mask, N, strideMask, argv, 4 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dmskmin_ndarray( N, X, strideX, offsetX, Mask, strideMask, offsetMask ), v );
+	return v;
+}
+
+STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method )
diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/dmskmin/src/addon.cpp
deleted file mode 100644
index 86acb4265ca2..000000000000
--- a/lib/node_modules/@stdlib/stats/base/dmskmin/src/addon.cpp
+++ /dev/null
@@ -1,153 +0,0 @@
-/**
-* @license Apache-2.0
-*
-* Copyright (c) 2020 The Stdlib Authors.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-*    http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-
-#include "stdlib/stats/base/dmskmin.h"
-#include <node_api.h>
-#include <stdint.h>
-#include <stdlib.h>
-#include <stdbool.h>
-#include <assert.h>
-
-/**
-* Add-on namespace.
-*/
-namespace stdlib_stats_base_dmskmin {
-
-	/**
-	* Computes the minimum value of a double-precision floating-point strided array according to a mask.
-	*
-	* ## Notes
-	*
-	* -   When called from JavaScript, the function expects five arguments:
-	*
-	*     -   `N`: number of indexed elements
-	*     -   `X`: input array
-	*     -   `strideX`: `X` stride length
-	*     -   `Mask`: mask array
-	*     -   `strideMask`: `Mask` stride length
-	*/
-	napi_value node_dmskmin( napi_env env, napi_callback_info info ) {
-		napi_status status;
-
-		size_t argc = 5;
-		napi_value argv[ 5 ];
-		status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr );
-		assert( status == napi_ok );
-
-		if ( argc < 5 ) {
-			napi_throw_error( env, nullptr, "invalid invocation. Must provide 5 arguments." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype0;
-		status = napi_typeof( env, argv[ 0 ], &vtype0 );
-		assert( status == napi_ok );
-		if ( vtype0 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." );
-			return nullptr;
-		}
-
-		bool res1;
-		status = napi_is_typedarray( env, argv[ 1 ], &res1 );
-		assert( status == napi_ok );
-		if ( res1 == false ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float64Array." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype2;
-		status = napi_typeof( env, argv[ 2 ], &vtype2 );
-		assert( status == napi_ok );
-		if ( vtype2 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." );
-			return nullptr;
-		}
-
-		bool res3;
-		status = napi_is_typedarray( env, argv[ 3 ], &res3 );
-		assert( status == napi_ok );
-		if ( res3 == false ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a Uint8Array." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype4;
-		status = napi_typeof( env, argv[ 4 ], &vtype4 );
-		assert( status == napi_ok );
-		if ( vtype4 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Fifth argument must be a number." );
-			return nullptr;
-		}
-
-		int64_t N;
-		status = napi_get_value_int64( env, argv[ 0 ], &N );
-		assert( status == napi_ok );
-
-		int64_t strideX;
-		status = napi_get_value_int64( env, argv[ 2 ], &strideX );
-		assert( status == napi_ok );
-
-		int64_t strideMask;
-		status = napi_get_value_int64( env, argv[ 4 ], &strideMask );
-		assert( status == napi_ok );
-
-		napi_typedarray_type vtype1;
-		size_t xlen;
-		void *X;
-		status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr );
-		assert( status == napi_ok );
-		if ( vtype1 != napi_float64_array ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float64Array." );
-			return nullptr;
-		}
-		if ( (N-1)*llabs(strideX) >= (int64_t)xlen ) {
-			napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." );
-			return nullptr;
-		}
-
-		napi_typedarray_type vtype3;
-		size_t mlen;
-		void *Mask;
-		status = napi_get_typedarray_info( env, argv[ 3 ], &vtype3, &mlen, &Mask, nullptr, nullptr );
-		assert( status == napi_ok );
-		if ( vtype3 != napi_uint8_array ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a Uint8Array." );
-			return nullptr;
-		}
-		if ( (N-1)*llabs(strideMask) >= (int64_t)mlen ) {
-			napi_throw_range_error( env, nullptr, "invalid argument. Fourth argument has insufficient elements based on the associated stride and the number of indexed elements." );
-			return nullptr;
-		}
-
-		napi_value v;
-		status = napi_create_double( env, stdlib_strided_dmskmin( N, (double *)X, strideX, (uint8_t *)Mask, strideMask ), &v );
-		assert( status == napi_ok );
-
-		return v;
-	}
-
-	napi_value Init( napi_env env, napi_value exports ) {
-		napi_status status;
-		napi_value fcn;
-		status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_dmskmin, NULL, &fcn );
-		assert( status == napi_ok );
-		return fcn;
-	}
-
-	NAPI_MODULE( NODE_GYP_MODULE_NAME, Init )
-} // end namespace stdlib_stats_base_dmskmin
diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/src/dmskmin.c b/lib/node_modules/@stdlib/stats/base/dmskmin/src/main.c
similarity index 56%
rename from lib/node_modules/@stdlib/stats/base/dmskmin/src/dmskmin.c
rename to lib/node_modules/@stdlib/stats/base/dmskmin/src/main.c
index dab8ccf3c9eb..5d1dd57d6b8d 100644
--- a/lib/node_modules/@stdlib/stats/base/dmskmin/src/dmskmin.c
+++ b/lib/node_modules/@stdlib/stats/base/dmskmin/src/main.c
@@ -1,7 +1,7 @@
 /**
 * @license Apache-2.0
 *
-* Copyright (c) 2020 The Stdlib Authors.
+* Copyright (c) 2024 The Stdlib Authors.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
@@ -19,6 +19,8 @@
 #include "stdlib/stats/base/dmskmin.h"
 #include "stdlib/math/base/assert/is_nan.h"
 #include "stdlib/math/base/assert/is_negative_zero.h"
+#include "stdlib/blas/base/shared.h"
+#include "stdlib/strided/base/stride2offset.h"
 #include <stdint.h>
 
 /**
@@ -31,26 +33,36 @@
 * @param strideMask  Mask stride length
 * @return            output value
 */
-double stdlib_strided_dmskmin( const int64_t N, const double *X, const int64_t strideX, const uint8_t *Mask, const int64_t strideMask ) {
+double API_SUFFIX(stdlib_strided_dmskmin)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const uint8_t *Mask, const CBLAS_INT strideMask ) {
+	const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX );
+	const CBLAS_INT om = stdlib_strided_stride2offset( N, strideMask );
+	return API_SUFFIX(stdlib_strided_dmskmin_ndarray)( N, X, strideX, ox, Mask, strideMask, om );
+}
+
+/**
+* Computes the minimum value of a double-precision floating-point strided array according to a mask and using alternative indexing semantics.
+*
+* @param N           number of indexed elements
+* @param X           input array
+* @param strideX     X stride length
+* @param offsetX     starting index for X
+* @param Mask        mask array
+* @param strideMask  Mask stride length
+* @param offsetMask  starting index for Mask
+* @return            output value
+*/
+double API_SUFFIX(stdlib_strided_dmskmin_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const uint8_t *Mask, const CBLAS_INT strideMask, const CBLAS_INT offsetMask ) {
+	CBLAS_INT ix;
+	CBLAS_INT im;
+	CBLAS_INT i;
 	double min;
-	int64_t ix;
-	int64_t im;
-	int64_t i;
 	double v;
 
 	if ( N <= 0 ) {
 		return 0.0 / 0.0; // NaN
 	}
-	if ( strideX < 0 ) {
-		ix = (1-N) * strideX;
-	} else {
-		ix = 0;
-	}
-	if ( strideMask < 0 ) {
-		im = (1-N) * strideMask;
-	} else {
-		im = 0;
-	}
+	ix = offsetX;
+	im = offsetMask;
 	for ( i = 0; i < N; i++ ) {
 		if ( Mask[ im ] == 0 ) {
 			break;
diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/test/test.dmskmin.js b/lib/node_modules/@stdlib/stats/base/dmskmin/test/test.dmskmin.js
index 0ef22637413f..5fbaf3ed47b2 100644
--- a/lib/node_modules/@stdlib/stats/base/dmskmin/test/test.dmskmin.js
+++ b/lib/node_modules/@stdlib/stats/base/dmskmin/test/test.dmskmin.js
@@ -21,7 +21,6 @@
 // MODULES //
 
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' );
 var Float64Array = require( '@stdlib/array/float64' );
@@ -133,7 +132,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 
 tape( 'the function supports `stride` parameters', function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -162,8 +160,7 @@ tape( 'the function supports `stride` parameters', function test( t ) {
 		1
 	]);
 
-	N = floor( x.length / 2 );
-	v = dmskmin( N, x, 2, mask, 2 );
+	v = dmskmin( 5, x, 2, mask, 2 );
 
 	t.strictEqual( v, -2.0, 'returns expected value' );
 	t.end();
@@ -171,7 +168,6 @@ tape( 'the function supports `stride` parameters', function test( t ) {
 
 tape( 'the function supports negative `stride` parameters', function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -200,8 +196,7 @@ tape( 'the function supports negative `stride` parameters', function test( t ) {
 		0
 	]);
 
-	N = floor( x.length / 2 );
-	v = dmskmin( N, x, -2, mask, -2 );
+	v = dmskmin( 5, x, -2, mask, -2 );
 
 	t.strictEqual( v, -2.0, 'returns expected value' );
 	t.end();
@@ -212,7 +207,6 @@ tape( 'the function supports view offsets', function test( t ) {
 	var mask1;
 	var x0;
 	var x1;
-	var N;
 	var v;
 
 	x0 = new Float64Array([
@@ -244,9 +238,8 @@ tape( 'the function supports view offsets', function test( t ) {
 
 	x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
 	mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
-	N = floor( x1.length/2 );
 
-	v = dmskmin( N, x1, 2, mask1, 2 );
+	v = dmskmin( 5, x1, 2, mask1, 2 );
 	t.strictEqual( v, -2.0, 'returns expected value' );
 
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/test/test.dmskmin.native.js b/lib/node_modules/@stdlib/stats/base/dmskmin/test/test.dmskmin.native.js
index dfb405f17387..a31ba1a8d3b8 100644
--- a/lib/node_modules/@stdlib/stats/base/dmskmin/test/test.dmskmin.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dmskmin/test/test.dmskmin.native.js
@@ -22,7 +22,6 @@
 
 var resolve = require( 'path' ).resolve;
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' );
 var Float64Array = require( '@stdlib/array/float64' );
@@ -142,7 +141,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 
 tape( 'the function supports `stride` parameters', opts, function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -171,8 +169,7 @@ tape( 'the function supports `stride` parameters', opts, function test( t ) {
 		1
 	]);
 
-	N = floor( x.length / 2 );
-	v = dmskmin( N, x, 2, mask, 2 );
+	v = dmskmin( 5, x, 2, mask, 2 );
 
 	t.strictEqual( v, -2.0, 'returns expected value' );
 	t.end();
@@ -180,7 +177,6 @@ tape( 'the function supports `stride` parameters', opts, function test( t ) {
 
 tape( 'the function supports negative `stride` parameters', opts, function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -209,8 +205,7 @@ tape( 'the function supports negative `stride` parameters', opts, function test(
 		0
 	]);
 
-	N = floor( x.length / 2 );
-	v = dmskmin( N, x, -2, mask, -2 );
+	v = dmskmin( 5, x, -2, mask, -2 );
 
 	t.strictEqual( v, -2.0, 'returns expected value' );
 	t.end();
@@ -221,7 +216,6 @@ tape( 'the function supports view offsets', opts, function test( t ) {
 	var mask1;
 	var x0;
 	var x1;
-	var N;
 	var v;
 
 	x0 = new Float64Array([
@@ -253,9 +247,8 @@ tape( 'the function supports view offsets', opts, function test( t ) {
 
 	x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
 	mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
-	N = floor( x1.length/2 );
 
-	v = dmskmin( N, x1, 2, mask1, 2 );
+	v = dmskmin( 5, x1, 2, mask1, 2 );
 	t.strictEqual( v, -2.0, 'returns expected value' );
 
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dmskmin/test/test.ndarray.js
index 2756d56e6da2..cb0c228316bf 100644
--- a/lib/node_modules/@stdlib/stats/base/dmskmin/test/test.ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/dmskmin/test/test.ndarray.js
@@ -21,7 +21,6 @@
 // MODULES //
 
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' );
 var Float64Array = require( '@stdlib/array/float64' );
@@ -133,7 +132,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 
 tape( 'the function supports `stride` parameters', function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -162,8 +160,7 @@ tape( 'the function supports `stride` parameters', function test( t ) {
 		1
 	]);
 
-	N = floor( x.length / 2 );
-	v = dmskmin( N, x, 2, 0, mask, 2, 0 );
+	v = dmskmin( 5, x, 2, 0, mask, 2, 0 );
 
 	t.strictEqual( v, -2.0, 'returns expected value' );
 	t.end();
@@ -171,7 +168,6 @@ tape( 'the function supports `stride` parameters', function test( t ) {
 
 tape( 'the function supports negative `stride` parameters', function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -200,8 +196,7 @@ tape( 'the function supports negative `stride` parameters', function test( t ) {
 		0
 	]);
 
-	N = floor( x.length / 2 );
-	v = dmskmin( N, x, -2, 8, mask, -2, 8 );
+	v = dmskmin( 5, x, -2, 8, mask, -2, 8 );
 
 	t.strictEqual( v, -2.0, 'returns expected value' );
 	t.end();
@@ -209,7 +204,6 @@ tape( 'the function supports negative `stride` parameters', function test( t ) {
 
 tape( 'the function supports `offset` parameters', function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -237,9 +231,8 @@ tape( 'the function supports `offset` parameters', function test( t ) {
 		1,
 		1  // 4
 	]);
-	N = floor( x.length / 2 );
 
-	v = dmskmin( N, x, 2, 1, mask, 2, 1 );
+	v = dmskmin( 5, x, 2, 1, mask, 2, 1 );
 	t.strictEqual( v, -2.0, 'returns expected value' );
 
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/dmskmin/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmskmin/test/test.ndarray.native.js
index 2c8edd097d19..ab53ffece127 100644
--- a/lib/node_modules/@stdlib/stats/base/dmskmin/test/test.ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dmskmin/test/test.ndarray.native.js
@@ -22,7 +22,6 @@
 
 var resolve = require( 'path' ).resolve;
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' );
 var Float64Array = require( '@stdlib/array/float64' );
@@ -120,7 +119,7 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu
 	v = dmskmin( 0, x, 1, 0, mask, 1, 0 );
 	t.strictEqual( isnan( v ), true, 'returns expected value' );
 
-	v = dmskmin( -1, x, 1, 0, mask, 1 );
+	v = dmskmin( -1, x, 1, 0, mask, 1, 0 );
 	t.strictEqual( isnan( v ), true, 'returns expected value' );
 
 	t.end();
@@ -142,7 +141,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 
 tape( 'the function supports `stride` parameters', opts, function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -171,8 +169,7 @@ tape( 'the function supports `stride` parameters', opts, function test( t ) {
 		1
 	]);
 
-	N = floor( x.length / 2 );
-	v = dmskmin( N, x, 2, 0, mask, 2, 0 );
+	v = dmskmin( 5, x, 2, 0, mask, 2, 0 );
 
 	t.strictEqual( v, -2.0, 'returns expected value' );
 	t.end();
@@ -180,7 +177,6 @@ tape( 'the function supports `stride` parameters', opts, function test( t ) {
 
 tape( 'the function supports negative `stride` parameters', opts, function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -209,8 +205,7 @@ tape( 'the function supports negative `stride` parameters', opts, function test(
 		0
 	]);
 
-	N = floor( x.length / 2 );
-	v = dmskmin( N, x, -2, 8, mask, -2, 8 );
+	v = dmskmin( 5, x, -2, 8, mask, -2, 8 );
 
 	t.strictEqual( v, -2.0, 'returns expected value' );
 	t.end();
@@ -218,7 +213,6 @@ tape( 'the function supports negative `stride` parameters', opts, function test(
 
 tape( 'the function supports `offset` parameters', opts, function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -246,9 +240,8 @@ tape( 'the function supports `offset` parameters', opts, function test( t ) {
 		1,
 		1  // 4
 	]);
-	N = floor( x.length / 2 );
 
-	v = dmskmin( N, x, 2, 1, mask, 2, 1 );
+	v = dmskmin( 5, x, 2, 1, mask, 2, 1 );
 	t.strictEqual( v, -2.0, 'returns expected value' );
 
 	t.end();

From 76bc4d8184890b6b2e895db3ec2a06a72e7154ca Mon Sep 17 00:00:00 2001
From: Aayush Khanna <96649223+aayush0325@users.noreply.github.com>
Date: Thu, 2 Jan 2025 23:36:30 +0530
Subject: [PATCH 08/87] feat: add C ndarray interface and refactor
 implementation for `stats/base/dmaxsorted`

PR-URL: https://github.com/stdlib-js/stdlib/pull/4456
Reviewed-by: Athan Reines <kgryte@gmail.com>
---
 .../@stdlib/stats/base/dmaxsorted/README.md   | 164 ++++++++++++++----
 .../base/dmaxsorted/benchmark/benchmark.js    |  17 +-
 .../dmaxsorted/benchmark/benchmark.native.js  |  13 +-
 .../dmaxsorted/benchmark/benchmark.ndarray.js |  17 +-
 .../benchmark/benchmark.ndarray.native.js     |  13 +-
 .../dmaxsorted/benchmark/c/benchmark.length.c |  50 +++++-
 .../stats/base/dmaxsorted/docs/repl.txt       |  32 ++--
 .../base/dmaxsorted/docs/types/index.d.ts     |  12 +-
 .../base/dmaxsorted/examples/c/example.c      |   9 +-
 .../stats/base/dmaxsorted/examples/index.js   |  13 +-
 .../include/stdlib/stats/base/dmaxsorted.h    |   9 +-
 .../stats/base/dmaxsorted/lib/dmaxsorted.js   |  41 +----
 .../base/dmaxsorted/lib/dmaxsorted.native.js  |   9 +-
 .../stats/base/dmaxsorted/lib/index.js        |   7 +-
 .../stats/base/dmaxsorted/lib/ndarray.js      |  16 +-
 .../base/dmaxsorted/lib/ndarray.native.js     |  20 +--
 .../stats/base/dmaxsorted/manifest.json       |  52 ++++--
 .../@stdlib/stats/base/dmaxsorted/src/addon.c |  25 ++-
 .../dmaxsorted/src/{dmaxsorted.c => main.c}   |  38 ++--
 .../base/dmaxsorted/test/test.dmaxsorted.js   |  13 +-
 .../dmaxsorted/test/test.dmaxsorted.native.js |  13 +-
 .../base/dmaxsorted/test/test.ndarray.js      |  13 +-
 .../dmaxsorted/test/test.ndarray.native.js    |  13 +-
 23 files changed, 365 insertions(+), 244 deletions(-)
 rename lib/node_modules/@stdlib/stats/base/dmaxsorted/src/{dmaxsorted.c => main.c} (55%)

diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/README.md b/lib/node_modules/@stdlib/stats/base/dmaxsorted/README.md
index 749f8a8b95cf..39f2f6cfd0cd 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/README.md
+++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/README.md
@@ -36,7 +36,7 @@ limitations under the License.
 var dmaxsorted = require( '@stdlib/stats/base/dmaxsorted' );
 ```
 
-#### dmaxsorted( N, x, stride )
+#### dmaxsorted( N, x, strideX )
 
 Computes the maximum value of a sorted double-precision floating-point strided array `x`.
 
@@ -44,15 +44,13 @@ Computes the maximum value of a sorted double-precision floating-point strided a
 var Float64Array = require( '@stdlib/array/float64' );
 
 var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );
-var N = x.length;
 
-var v = dmaxsorted( N, x, 1 );
+var v = dmaxsorted( x.length, x, 1 );
 // returns 3.0
 
 x = new Float64Array( [ 3.0, 2.0, 1.0 ] );
-N = x.length;
 
-v = dmaxsorted( N, x, 1 );
+v = dmaxsorted( x.length, x, 1 );
 // returns 3.0
 ```
 
@@ -60,18 +58,16 @@ The function has the following parameters:
 
 -   **N**: number of indexed elements.
 -   **x**: sorted input [`Float64Array`][@stdlib/array/float64].
--   **stride**: index increment for `x`.
+-   **strideX**: stride length for `x`.
 
-The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the maximum value of every other element in `x`,
+The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the maximum value of every other element in `x`,
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, 3.0, 3.0, 4.0, 2.0 ] );
-var N = floor( x.length / 2 );
 
-var v = dmaxsorted( N, x, 2 );
+var v = dmaxsorted( 4, x, 2 );
 // returns 4.0
 ```
 
@@ -81,18 +77,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x0 = new Float64Array( [ 2.0, 1.0, 2.0, 2.0, -2.0, 2.0, 3.0, 4.0 ] );
 var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
 
-var N = floor( x0.length / 2 );
-
-var v = dmaxsorted( N, x1, 2 );
+var v = dmaxsorted( 4, x1, 2 );
 // returns 4.0
 ```
 
-#### dmaxsorted.ndarray( N, x, stride, offset )
+#### dmaxsorted.ndarray( N, x, strideX, offsetX )
 
 Computes the maximum value of a sorted double-precision floating-point strided array using alternative indexing semantics.
 
@@ -100,26 +93,23 @@ Computes the maximum value of a sorted double-precision floating-point strided a
 var Float64Array = require( '@stdlib/array/float64' );
 
 var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );
-var N = x.length;
 
-var v = dmaxsorted.ndarray( N, x, 1, 0 );
+var v = dmaxsorted.ndarray( x.length, x, 1, 0 );
 // returns 3.0
 ```
 
 The function has the following additional parameters:
 
--   **offset**: starting index for `x`.
+-   **offsetX**: starting index for `x`.
 
-While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the maximum value for every other value in `x` starting from the second value
+While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the maximum value for every other element in `x` starting from the second element
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x = new Float64Array( [ 2.0, 1.0, 2.0, 2.0, -2.0, 2.0, 3.0, 4.0 ] );
-var N = floor( x.length / 2 );
 
-var v = dmaxsorted.ndarray( N, x, 2, 1 );
+var v = dmaxsorted.ndarray( 4, x, 2, 1 );
 // returns 4.0
 ```
 
@@ -145,16 +135,13 @@ var v = dmaxsorted.ndarray( N, x, 2, 1 );
 <!-- eslint no-undef: "error" -->
 
 ```javascript
-var Float64Array = require( '@stdlib/array/float64' );
+var linspace = require( '@stdlib/array/linspace' );
 var dmaxsorted = require( '@stdlib/stats/base/dmaxsorted' );
 
-var x;
-var i;
-
-x = new Float64Array( 10 );
-for ( i = 0; i < x.length; i++ ) {
-    x[ i ] = i - 5.0;
-}
+var options = {
+    'dtype': 'float64'
+};
+var x = linspace( -5.0, 5.0, 10, options );
 console.log( x );
 
 var v = dmaxsorted( x.length, x, 1 );
@@ -165,6 +152,123 @@ console.log( v );
 
 <!-- /.examples -->
 
+<!-- C interface documentation. -->
+
+* * *
+
+<section class="c">
+
+## C APIs
+
+<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<!-- C usage documentation. -->
+
+<section class="usage">
+
+### Usage
+
+```c
+#include "stdlib/stats/base/dmaxsorted.h"
+```
+
+#### stdlib_strided_dmaxsorted( N, \*X, strideX )
+
+Computes the maximum value of a sorted double-precision floating-point strided array.
+
+```c
+const double x[] = { 1.0, 2.0, 3.0 };
+
+double v = stdlib_strided_dmaxsorted( 3, x, 1 );
+// returns 3.0
+```
+
+The function accepts the following arguments:
+
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **X**: `[in] double*` input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+
+```c
+double stdlib_strided_dmaxsorted( const CBLAS_INT N, const double *X, const CBLAS_INT strideX );
+```
+
+#### stdlib_strided_dmaxsorted_ndarray( N, \*X, strideX, offsetX )
+
+Computes the maximum value of a sorted double-precision floating-point strided array using alternative indexing semantics.
+
+```c
+const double x[] = { 1.0, 2.0, 3.0 };
+
+double v = stdlib_strided_dmaxsorted_ndarray( 3, x, 1, 0 );
+// returns 3.0
+```
+
+The function accepts the following arguments:
+
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **X**: `[in] double*` input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+-   **offsetX**: `[in] CBLAS_INT` starting index for `X`.
+
+```c
+double stdlib_strided_dmaxsorted_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX );
+```
+
+</section>
+
+<!-- /.usage -->
+
+<!-- C API usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="notes">
+
+</section>
+
+<!-- /.notes -->
+
+<!-- C API usage examples. -->
+
+<section class="examples">
+
+### Examples
+
+```c
+#include "stdlib/stats/base/dmaxsorted.h"
+#include <stdio.h>
+
+int main( void ) {
+    // Create a strided array:
+    const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 };
+
+    // Specify the number of elements:
+    const int N = 4;
+
+    // Specify the stride length:
+    const int strideX = 2;
+
+    // Compute the maximum value:
+    double v = stdlib_strided_dmaxsorted( N, x, strideX );
+
+    // Print the result:
+    printf( "max: %lf\n", v );
+}
+```
+
+</section>
+
+<!-- /.examples -->
+
+</section>
+
+<!-- /.c -->
+
 <!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
 
 <section class="related">
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dmaxsorted/benchmark/benchmark.js
index 0726a05b9bc3..7cd40722fd2b 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/benchmark/benchmark.js
+++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/benchmark/benchmark.js
@@ -22,12 +22,19 @@
 
 var bench = require( '@stdlib/bench' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var linspace = require( '@stdlib/array/linspace' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float64Array = require( '@stdlib/array/float64' );
 var pkg = require( './../package.json' ).name;
 var dmaxsorted = require( './../lib/dmaxsorted.js' );
 
 
+// VARIABLES //
+
+var options = {
+	'dtype': 'float64'
+};
+
+
 // FUNCTIONS //
 
 /**
@@ -38,13 +45,7 @@ var dmaxsorted = require( './../lib/dmaxsorted.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float64Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = i;
-	}
+	var x = linspace( -len/2, len/2, len, options );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dmaxsorted/benchmark/benchmark.native.js
index 5e49fb7244cc..10835ad82014 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/benchmark/benchmark.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/benchmark/benchmark.native.js
@@ -23,8 +23,8 @@
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var linspace = require( '@stdlib/array/linspace' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float64Array = require( '@stdlib/array/float64' );
 var tryRequire = require( '@stdlib/utils/try-require' );
 var pkg = require( './../package.json' ).name;
 
@@ -35,6 +35,9 @@ var dmaxsorted = tryRequire( resolve( __dirname, './../lib/dmaxsorted.native.js'
 var opts = {
 	'skip': ( dmaxsorted instanceof Error )
 };
+var options = {
+	'dtype': 'float64'
+};
 
 
 // FUNCTIONS //
@@ -47,13 +50,7 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float64Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = i;
-	}
+	var x = linspace( -len/2, len/2, len, options );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/dmaxsorted/benchmark/benchmark.ndarray.js
index 17609b252d90..6d3290ead750 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/benchmark/benchmark.ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/benchmark/benchmark.ndarray.js
@@ -22,12 +22,19 @@
 
 var bench = require( '@stdlib/bench' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var linspace = require( '@stdlib/array/linspace' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float64Array = require( '@stdlib/array/float64' );
 var pkg = require( './../package.json' ).name;
 var dmaxsorted = require( './../lib/ndarray.js' );
 
 
+// VARIABLES //
+
+var options = {
+	'dtype': 'float64'
+};
+
+
 // FUNCTIONS //
 
 /**
@@ -38,13 +45,7 @@ var dmaxsorted = require( './../lib/ndarray.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float64Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = i;
-	}
+	var x = linspace( -len/2, len/2, len, options );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmaxsorted/benchmark/benchmark.ndarray.native.js
index f02448bd23a0..96436d79fe29 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/benchmark/benchmark.ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/benchmark/benchmark.ndarray.native.js
@@ -23,8 +23,8 @@
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var linspace = require( '@stdlib/array/linspace' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float64Array = require( '@stdlib/array/float64' );
 var tryRequire = require( '@stdlib/utils/try-require' );
 var pkg = require( './../package.json' ).name;
 
@@ -35,6 +35,9 @@ var dmaxsorted = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' )
 var opts = {
 	'skip': ( dmaxsorted instanceof Error )
 };
+var options = {
+	'dtype': 'float64'
+};
 
 
 // FUNCTIONS //
@@ -47,13 +50,7 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float64Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = i;
-	}
+	var x = linspace( -len/2, len/2, len, options );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dmaxsorted/benchmark/c/benchmark.length.c
index f2c96f345e6a..285e7691b37a 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/benchmark/c/benchmark.length.c
+++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/benchmark/c/benchmark.length.c
@@ -94,7 +94,7 @@ static double rand_double( void ) {
 * @param len          array length
 * @return             elapsed time in seconds
 */
-static double benchmark( int iterations, int len ) {
+static double benchmark1( int iterations, int len ) {
 	double elapsed;
 	double x[ len ];
 	double v;
@@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) {
 	v = 0.0;
 	t = tic();
 	for ( i = 0; i < iterations; i++ ) {
+		// cppcheck-suppress uninitvar
 		v = stdlib_strided_dmaxsorted( len, x, 1 );
 		if ( v != v ) {
 			printf( "should not return NaN\n" );
@@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) {
 	return elapsed;
 }
 
+/**
+* Runs a benchmark.
+*
+* @param iterations   number of iterations
+* @param len          array length
+* @return             elapsed time in seconds
+*/
+static double benchmark2( int iterations, int len ) {
+	double elapsed;
+	double x[ len ];
+	double v;
+	double t;
+	int i;
+
+	for ( i = 0; i < len; i++ ) {
+		x[ i ] = i;
+	}
+	v = 0.0;
+	t = tic();
+	for ( i = 0; i < iterations; i++ ) {
+		// cppcheck-suppress uninitvar
+		v = stdlib_strided_dmaxsorted_ndarray( len, x, 1, 0 );
+		if ( v != v ) {
+			printf( "should not return NaN\n" );
+			break;
+		}
+	}
+	elapsed = tic() - t;
+	if ( v != v ) {
+		printf( "should not return NaN\n" );
+	}
+	return elapsed;
+}
+
 /**
 * Main execution sequence.
 */
@@ -142,7 +177,18 @@ int main( void ) {
 		for ( j = 0; j < REPEATS; j++ ) {
 			count += 1;
 			printf( "# c::%s:len=%d\n", NAME, len );
-			elapsed = benchmark( iter, len );
+			elapsed = benchmark1( iter, len );
+			print_results( iter, elapsed );
+			printf( "ok %d benchmark finished\n", count );
+		}
+	}
+	for ( i = MIN; i <= MAX; i++ ) {
+		len = pow( 10, i );
+		iter = ITERATIONS / pow( 10, i-1 );
+		for ( j = 0; j < REPEATS; j++ ) {
+			count += 1;
+			printf( "# c::%s:ndarray:len=%d\n", NAME, len );
+			elapsed = benchmark2( iter, len );
 			print_results( iter, elapsed );
 			printf( "ok %d benchmark finished\n", count );
 		}
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dmaxsorted/docs/repl.txt
index d1483c778af7..85763dcd4715 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/docs/repl.txt
+++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/docs/repl.txt
@@ -1,13 +1,13 @@
 
-{{alias}}( N, x, stride )
+{{alias}}( N, x, strideX )
     Computes the maximum value of a sorted double-precision floating-point
     strided array.
 
     The input strided array must be sorted in either strictly ascending or
     descending order.
 
-    The `N` and `stride` parameters determine which elements in `x` are accessed
-    at runtime.
+    The `N` and stride parameters determine which elements in the strided array
+    are accessed at runtime.
 
     Indexing is relative to the first index. To introduce an offset, use a typed
     array view.
@@ -22,8 +22,8 @@
     x: Float64Array
         Sorted input array.
 
-    stride: integer
-        Index increment.
+    strideX: integer
+        Stride Length.
 
     Returns
     -------
@@ -37,22 +37,19 @@
     > {{alias}}( x.length, x, 1 )
     3.0
 
-    // Using `N` and `stride` parameters:
+    // Using `N` and stride parameters:
     > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > var stride = 2;
-    > {{alias}}( N, x, stride )
+    > {{alias}}( 3, x, 2 )
     2.0
 
     // Using view offsets:
     > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );
     > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );
-    > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );
-    > stride = 2;
-    > {{alias}}( N, x1, stride )
+    > {{alias}}( 3, x1, 2 )
     3.0
 
-{{alias}}.ndarray( N, x, stride, offset )
+
+{{alias}}.ndarray( N, x, strideX, offsetX )
     Computes the maximum value of a sorted double-precision floating-point
     strided array using alternative indexing semantics.
 
@@ -68,10 +65,10 @@
     x: Float64Array
         Sorted input array.
 
-    stride: integer
-        Index increment.
+    strideX: integer
+        Stride Length.
 
-    offset: integer
+    offsetX: integer
         Starting index.
 
     Returns
@@ -88,8 +85,7 @@
 
     // Using offset parameter:
     > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > {{alias}}.ndarray( N, x, 2, 1 )
+    > {{alias}}.ndarray( 3, x, 2, 1 )
     3.0
 
     See Also
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dmaxsorted/docs/types/index.d.ts
index 8da4da37c2e8..9ccb5a79afc3 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/docs/types/index.d.ts
@@ -27,7 +27,7 @@ interface Routine {
 	*
 	* @param N - number of indexed elements
 	* @param x - sorted input array
-	* @param stride - stride length
+	* @param strideX - stride length
 	* @returns maximum value
 	*
 	* @example
@@ -38,15 +38,15 @@ interface Routine {
 	* var v = dmaxsorted( x.length, x, 1 );
 	* // returns 3.0
 	*/
-	( N: number, x: Float64Array, stride: number ): number;
+	( N: number, x: Float64Array, strideX: number ): number;
 
 	/**
 	* Computes the maximum value of a sorted double-precision floating-point strided array using alternative indexing semantics.
 	*
 	* @param N - number of indexed elements
 	* @param x - sorted input array
-	* @param stride - stride length
-	* @param offset - starting index
+	* @param strideX - stride length
+	* @param offsetX - starting index
 	* @returns maximum value
 	*
 	* @example
@@ -57,7 +57,7 @@ interface Routine {
 	* var v = dmaxsorted.ndarray( x.length, x, 1, 0 );
 	* // returns 3.0
 	*/
-	ndarray( N: number, x: Float64Array, stride: number, offset: number ): number;
+	ndarray( N: number, x: Float64Array, strideX: number, offsetX: number ): number;
 }
 
 /**
@@ -65,7 +65,7 @@ interface Routine {
 *
 * @param N - number of indexed elements
 * @param x - sorted input array
-* @param stride - stride length
+* @param strideX - stride length
 * @returns maximum value
 *
 * @example
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dmaxsorted/examples/c/example.c
index b0e839fdacb0..f4b35e787d0a 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/examples/c/example.c
+++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/examples/c/example.c
@@ -17,21 +17,20 @@
 */
 
 #include "stdlib/stats/base/dmaxsorted.h"
-#include <stdint.h>
 #include <stdio.h>
 
 int main( void ) {
 	// Create a strided array:
-	double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 };
+	const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 };
 
 	// Specify the number of elements:
-	int64_t N = 4;
+	const int N = 4;
 
 	// Specify the stride length:
-	int64_t stride = 2;
+	const int strideX = 2;
 
 	// Compute the maximum value:
-	double v = stdlib_strided_dmaxsorted( N, x, stride );
+	double v = stdlib_strided_dmaxsorted( N, x, strideX );
 
 	// Print the result:
 	printf( "max: %lf\n", v );
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/examples/index.js b/lib/node_modules/@stdlib/stats/base/dmaxsorted/examples/index.js
index a1517627f936..b76928ded2a6 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/examples/index.js
+++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/examples/index.js
@@ -18,16 +18,13 @@
 
 'use strict';
 
-var Float64Array = require( '@stdlib/array/float64' );
+var linspace = require( '@stdlib/array/linspace' );
 var dmaxsorted = require( './../lib' );
 
-var x;
-var i;
-
-x = new Float64Array( 10 );
-for ( i = 0; i < x.length; i++ ) {
-	x[ i ] = i - 5.0;
-}
+var options = {
+	'dtype': 'float64'
+};
+var x = linspace( -5.0, 5.0, 10, options );
 console.log( x );
 
 var v = dmaxsorted( x.length, x, 1 );
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/include/stdlib/stats/base/dmaxsorted.h b/lib/node_modules/@stdlib/stats/base/dmaxsorted/include/stdlib/stats/base/dmaxsorted.h
index 3f6b84867480..ced00e5df072 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/include/stdlib/stats/base/dmaxsorted.h
+++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/include/stdlib/stats/base/dmaxsorted.h
@@ -19,7 +19,7 @@
 #ifndef STDLIB_STATS_BASE_DMAXSORTED_H
 #define STDLIB_STATS_BASE_DMAXSORTED_H
 
-#include <stdint.h>
+#include "stdlib/blas/base/shared.h"
 
 /*
 * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler.
@@ -31,7 +31,12 @@ extern "C" {
 /**
 * Computes the maximum value of a sorted double-precision floating-point strided array.
 */
-double stdlib_strided_dmaxsorted( const int64_t N, const double *X, const int64_t stride );
+double API_SUFFIX(stdlib_strided_dmaxsorted)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX );
+
+/**
+* Computes the maximum value of a sorted double-precision floating-point strided array using alternative indexing semantics.
+*/
+double API_SUFFIX(stdlib_strided_dmaxsorted_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX );
 
 #ifdef __cplusplus
 }
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/lib/dmaxsorted.js b/lib/node_modules/@stdlib/stats/base/dmaxsorted/lib/dmaxsorted.js
index b971b79e02e2..d4f61fc852cd 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/lib/dmaxsorted.js
+++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/lib/dmaxsorted.js
@@ -20,8 +20,8 @@
 
 // MODULES //
 
-var isnan = require( '@stdlib/math/base/assert/is-nan' );
-var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' );
+var stride2offset = require( '@stdlib/strided/base/stride2offset' );
+var ndarray = require( './ndarray.js' );
 
 
 // MAIN //
@@ -31,48 +31,19 @@ var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' );
 *
 * @param {PositiveInteger} N - number of indexed elements
 * @param {Float64Array} x - sorted input array
-* @param {integer} stride - stride length
+* @param {integer} strideX - stride length
 * @returns {number} maximum value
 *
 * @example
 * var Float64Array = require( '@stdlib/array/float64' );
 *
 * var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );
-* var N = x.length;
 *
-* var v = dmaxsorted( N, x, 1 );
+* var v = dmaxsorted( x.length, x, 1 );
 * // returns 3.0
 */
-function dmaxsorted( N, x, stride ) {
-	var v1;
-	var v2;
-
-	if ( N <= 0 ) {
-		return NaN;
-	}
-	if ( N === 1 || stride === 0 ) {
-		return x[ 0 ];
-	}
-	if ( stride < 0 ) {
-		v1 = x[ (1-N) * stride ];
-		v2 = x[ 0 ];
-	} else {
-		v1 = x[ 0 ];
-		v2 = x[ (N-1) * stride ];
-	}
-	if ( isnan( v1 ) || isnan( v2 ) ) {
-		return NaN;
-	}
-	if ( v1 === v2 ) {
-		if ( isPositiveZero( v1 ) || isPositiveZero( v2 ) ) {
-			return 0.0;
-		}
-		return v1;
-	}
-	if ( v1 > v2 ) {
-		return v1;
-	}
-	return v2;
+function dmaxsorted( N, x, strideX ) {
+	return ndarray( N, x, strideX, stride2offset( N, strideX ) );
 }
 
 
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/lib/dmaxsorted.native.js b/lib/node_modules/@stdlib/stats/base/dmaxsorted/lib/dmaxsorted.native.js
index e28f2c171be5..bbfbda92dd2a 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/lib/dmaxsorted.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/lib/dmaxsorted.native.js
@@ -30,20 +30,19 @@ var addon = require( './../src/addon.node' );
 *
 * @param {PositiveInteger} N - number of indexed elements
 * @param {Float64Array} x - sorted input array
-* @param {integer} stride - stride length
+* @param {integer} strideX - stride length
 * @returns {number} maximum value
 *
 * @example
 * var Float64Array = require( '@stdlib/array/float64' );
 *
 * var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );
-* var N = x.length;
 *
-* var v = dmaxsorted( N, x, 1 );
+* var v = dmaxsorted( x.length, x, 1 );
 * // returns 3.0
 */
-function dmaxsorted( N, x, stride ) {
-	return addon( N, x, stride );
+function dmaxsorted( N, x, strideX ) {
+	return addon( N, x, strideX );
 }
 
 
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/lib/index.js b/lib/node_modules/@stdlib/stats/base/dmaxsorted/lib/index.js
index b083a5b78157..76a8823d27ae 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/lib/index.js
+++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/lib/index.js
@@ -28,20 +28,17 @@
 * var dmaxsorted = require( '@stdlib/stats/base/dmaxsorted' );
 *
 * var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );
-* var N = x.length;
 *
-* var v = dmaxsorted( N, x, 1 );
+* var v = dmaxsorted( x.length, x, 1 );
 * // returns 3.0
 *
 * @example
 * var Float64Array = require( '@stdlib/array/float64' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 * var dmaxsorted = require( '@stdlib/stats/base/dmaxsorted' );
 *
 * var x = new Float64Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
-* var N = floor( x.length / 2 );
 *
-* var v = dmaxsorted.ndarray( N, x, 2, 1 );
+* var v = dmaxsorted.ndarray( 4, x, 2, 1 );
 * // returns 4.0
 */
 
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/dmaxsorted/lib/ndarray.js
index ea52a26e0776..e5f5369fbbac 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/lib/ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/lib/ndarray.js
@@ -31,32 +31,30 @@ var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' );
 *
 * @param {PositiveInteger} N - number of indexed elements
 * @param {Float64Array} x - sorted input array
-* @param {integer} stride - stride length
-* @param {NonNegativeInteger} offset - starting index
+* @param {integer} strideX - stride length
+* @param {NonNegativeInteger} offsetX - starting index
 * @returns {number} maximum value
 *
 * @example
 * var Float64Array = require( '@stdlib/array/float64' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 *
 * var x = new Float64Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
-* var N = floor( x.length / 2 );
 *
-* var v = dmaxsorted( N, x, 2, 1 );
+* var v = dmaxsorted( 4, x, 2, 1 );
 * // returns 4.0
 */
-function dmaxsorted( N, x, stride, offset ) {
+function dmaxsorted( N, x, strideX, offsetX ) {
 	var v1;
 	var v2;
 
 	if ( N <= 0 ) {
 		return NaN;
 	}
-	if ( N === 1 || stride === 0 ) {
+	if ( N === 1 || strideX === 0 ) {
 		return x[ 0 ];
 	}
-	v1 = x[ offset ];
-	v2 = x[ offset + ((N-1)*stride) ];
+	v1 = x[ offsetX ];
+	v2 = x[ offsetX + ((N-1)*strideX) ];
 	if ( isnan( v1 ) || isnan( v2 ) ) {
 		return NaN;
 	}
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmaxsorted/lib/ndarray.native.js
index 8938dd264060..2810650cfbec 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/lib/ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/lib/ndarray.native.js
@@ -20,8 +20,7 @@
 
 // MODULES //
 
-var Float64Array = require( '@stdlib/array/float64' );
-var addon = require( './dmaxsorted.native.js' );
+var addon = require( './../src/addon.node' );
 
 
 // MAIN //
@@ -31,27 +30,20 @@ var addon = require( './dmaxsorted.native.js' );
 *
 * @param {PositiveInteger} N - number of indexed elements
 * @param {Float64Array} x - sorted input array
-* @param {integer} stride - stride length
-* @param {NonNegativeInteger} offset - starting index
+* @param {integer} strideX - stride length
+* @param {NonNegativeInteger} offsetX - starting index
 * @returns {number} maximum value
 *
 * @example
 * var Float64Array = require( '@stdlib/array/float64' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 *
 * var x = new Float64Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
-* var N = floor( x.length / 2 );
 *
-* var v = dmaxsorted( N, x, 2, 1 );
+* var v = dmaxsorted( 4, x, 2, 1 );
 * // returns 4.0
 */
-function dmaxsorted( N, x, stride, offset ) {
-	var view;
-	if ( stride < 0 ) {
-		offset += (N-1) * stride;
-	}
-	view = new Float64Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len
-	return addon( N, view, stride );
+function dmaxsorted( N, x, strideX, offsetX ) {
+	return addon.ndarray( N, x, strideX, offsetX );
 }
 
 
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/manifest.json b/lib/node_modules/@stdlib/stats/base/dmaxsorted/manifest.json
index eac9da6f48c9..61565b33b0a3 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/manifest.json
+++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/manifest.json
@@ -1,6 +1,7 @@
 {
   "options": {
-    "task": "build"
+    "task": "build",
+    "wasm": false
   },
   "fields": [
     {
@@ -27,19 +28,20 @@
   "confs": [
     {
       "task": "build",
+      "wasm": false,
       "src": [
-        "./src/dmaxsorted.c"
+        "./src/main.c"
       ],
       "include": [
         "./include"
       ],
-      "libraries": [
-        "-lm"
-      ],
+      "libraries": [],
       "libpath": [],
       "dependencies": [
-        "@stdlib/math/base/assert/is-positive-zero",
         "@stdlib/math/base/assert/is-nan",
+        "@stdlib/math/base/assert/is-positive-zero",
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset",
         "@stdlib/napi/export",
         "@stdlib/napi/argv",
         "@stdlib/napi/argv-int64",
@@ -49,36 +51,56 @@
     },
     {
       "task": "benchmark",
+      "wasm": false,
       "src": [
-        "./src/dmaxsorted.c"
+        "./src/main.c"
       ],
       "include": [
         "./include"
       ],
-      "libraries": [
-        "-lm"
-      ],
+      "libraries": [],
       "libpath": [],
       "dependencies": [
+        "@stdlib/math/base/assert/is-nan",
         "@stdlib/math/base/assert/is-positive-zero",
-        "@stdlib/math/base/assert/is-nan"
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset"
       ]
     },
     {
       "task": "examples",
+      "wasm": false,
       "src": [
-        "./src/dmaxsorted.c"
+        "./src/main.c"
       ],
       "include": [
         "./include"
       ],
-      "libraries": [
-        "-lm"
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/math/base/assert/is-nan",
+        "@stdlib/math/base/assert/is-positive-zero",
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset"
+      ]
+    },
+    {
+      "task": "",
+      "wasm": true,
+      "src": [
+        "./src/main.c"
       ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
       "libpath": [],
       "dependencies": [
         "@stdlib/math/base/assert/is-nan",
-        "@stdlib/math/base/assert/is-positive-zero"
+        "@stdlib/math/base/assert/is-positive-zero",
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset"
       ]
     }
   ]
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/src/addon.c b/lib/node_modules/@stdlib/stats/base/dmaxsorted/src/addon.c
index 29545a3b5e21..3ebe86dcddb7 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/src/addon.c
+++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/src/addon.c
@@ -34,10 +34,27 @@
 static napi_value addon( napi_env env, napi_callback_info info ) {
 	STDLIB_NAPI_ARGV( env, info, argv, argc, 3 );
 	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
-	STDLIB_NAPI_ARGV_INT64( env, stride, argv, 2 );
-	STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, stride, argv, 1 );
-	STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dmaxsorted( N, X, stride ), v );
+	STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dmaxsorted( N, X, strideX ), v );
 	return v;
 }
 
-STDLIB_NAPI_MODULE_EXPORT_FCN( addon )
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon_method( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 4 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 );
+	STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dmaxsorted_ndarray( N, X, strideX, offsetX ), v );
+	return v;
+}
+
+STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method )
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/src/dmaxsorted.c b/lib/node_modules/@stdlib/stats/base/dmaxsorted/src/main.c
similarity index 55%
rename from lib/node_modules/@stdlib/stats/base/dmaxsorted/src/dmaxsorted.c
rename to lib/node_modules/@stdlib/stats/base/dmaxsorted/src/main.c
index e9ad7acb5908..d7bc211b74f6 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/src/dmaxsorted.c
+++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/src/main.c
@@ -19,33 +19,43 @@
 #include "stdlib/stats/base/dmaxsorted.h"
 #include "stdlib/math/base/assert/is_nan.h"
 #include "stdlib/math/base/assert/is_positive_zero.h"
-#include <stdint.h>
+#include "stdlib/blas/base/shared.h"
+#include "stdlib/strided/base/stride2offset.h"
 
 /**
 * Computes the maximum value of a sorted double-precision floating-point strided array.
 *
-* @param N       number of indexed elements
-* @param X       sorted input array
-* @param stride  stride length
-* @return        output value
+* @param N        number of indexed elements
+* @param X        sorted input array
+* @param strideX  stride length
+* @return         output value
 */
-double stdlib_strided_dmaxsorted( const int64_t N, const double *X, const int64_t stride ) {
+double API_SUFFIX(stdlib_strided_dmaxsorted)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ) {
+	const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX );
+	return API_SUFFIX(stdlib_strided_dmaxsorted_ndarray)( N, X, strideX, ox );
+}
+
+/**
+* Computes the maximum value of a sorted double-precision floating-point strided array.
+*
+* @param N        number of indexed elements
+* @param X        sorted input array
+* @param strideX  stride length
+* @param offsetX  starting index for X
+* @return         output value
+*/
+double API_SUFFIX(stdlib_strided_dmaxsorted_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) {
 	double v1;
 	double v2;
 
 	if ( N <= 0 ) {
 		return 0.0 / 0.0; // NaN
 	}
-	if ( N == 1 || stride == 0 ) {
+	if ( N == 1 || strideX == 0 ) {
 		return X[ 0 ];
 	}
-	if ( stride < 0 ) {
-		v1 = X[ (1-N) * stride ];
-		v2 = X[ 0 ];
-	} else {
-		v1 = X[ 0 ];
-		v2 = X[ (N-1) * stride ];
-	}
+	v1 = X[ offsetX ];
+	v2 = X[ (N-1) * strideX + offsetX ];
 	if ( stdlib_base_is_nan( v1 ) || stdlib_base_is_nan( v2 ) ) {
 		return 0.0 / 0.0; // NaN
 	}
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/test/test.dmaxsorted.js b/lib/node_modules/@stdlib/stats/base/dmaxsorted/test/test.dmaxsorted.js
index 9decf6e9e4b3..eb4b224b3c83 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/test/test.dmaxsorted.js
+++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/test/test.dmaxsorted.js
@@ -21,7 +21,6 @@
 // MODULES //
 
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' );
 var Float64Array = require( '@stdlib/array/float64' );
@@ -116,7 +115,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 });
 
 tape( 'the function supports a `stride` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -131,15 +129,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) {
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = dmaxsorted( N, x, 2 );
+	v = dmaxsorted( 4, x, 2 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
 });
 
 tape( 'the function supports a negative `stride` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -154,8 +150,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t )
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = dmaxsorted( N, x, -2 );
+	v = dmaxsorted( 4, x, -2 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
@@ -176,7 +171,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f
 tape( 'the function supports view offsets', function test( t ) {
 	var x0;
 	var x1;
-	var N;
 	var v;
 
 	x0 = new Float64Array([
@@ -192,9 +186,8 @@ tape( 'the function supports view offsets', function test( t ) {
 	]);
 
 	x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
-	N = floor(x1.length / 2);
 
-	v = dmaxsorted( N, x1, 2 );
+	v = dmaxsorted( 4, x1, 2 );
 	t.strictEqual( v, 4.0, 'returns expected value' );
 
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/test/test.dmaxsorted.native.js b/lib/node_modules/@stdlib/stats/base/dmaxsorted/test/test.dmaxsorted.native.js
index 7946ef28b215..e26985fbf933 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/test/test.dmaxsorted.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/test/test.dmaxsorted.native.js
@@ -22,7 +22,6 @@
 
 var resolve = require( 'path' ).resolve;
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' );
 var Float64Array = require( '@stdlib/array/float64' );
@@ -125,7 +124,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 });
 
 tape( 'the function supports a `stride` parameter', opts, function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -140,15 +138,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) {
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = dmaxsorted( N, x, 2 );
+	v = dmaxsorted( 4, x, 2 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
 });
 
 tape( 'the function supports a negative `stride` parameter', opts, function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -163,8 +159,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = dmaxsorted( N, x, -2 );
+	v = dmaxsorted( 4, x, -2 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
@@ -185,7 +180,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f
 tape( 'the function supports view offsets', opts, function test( t ) {
 	var x0;
 	var x1;
-	var N;
 	var v;
 
 	x0 = new Float64Array([
@@ -201,9 +195,8 @@ tape( 'the function supports view offsets', opts, function test( t ) {
 	]);
 
 	x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
-	N = floor(x1.length / 2);
 
-	v = dmaxsorted( N, x1, 2 );
+	v = dmaxsorted( 4, x1, 2 );
 	t.strictEqual( v, 4.0, 'returns expected value' );
 
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dmaxsorted/test/test.ndarray.js
index 53c3c94950d5..52eef5af97b8 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/test/test.ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/test/test.ndarray.js
@@ -21,7 +21,6 @@
 // MODULES //
 
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' );
 var Float64Array = require( '@stdlib/array/float64' );
@@ -116,7 +115,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 });
 
 tape( 'the function supports a `stride` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -131,15 +129,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) {
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = dmaxsorted( N, x, 2, 0 );
+	v = dmaxsorted( 4, x, 2, 0 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
 });
 
 tape( 'the function supports a negative `stride` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -154,8 +150,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t )
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = dmaxsorted( N, x, -2, 6 );
+	v = dmaxsorted( 4, x, -2, 6 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
@@ -174,7 +169,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f
 });
 
 tape( 'the function supports an `offset` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -188,9 +182,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) {
 		3.0,
 		4.0   // 3
 	]);
-	N = floor( x.length / 2 );
 
-	v = dmaxsorted( N, x, 2, 1 );
+	v = dmaxsorted( 4, x, 2, 1 );
 	t.strictEqual( v, 4.0, 'returns expected value' );
 
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmaxsorted/test/test.ndarray.native.js
index 5c9980a47918..77cb453e7b0c 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/test/test.ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/test/test.ndarray.native.js
@@ -22,7 +22,6 @@
 
 var resolve = require( 'path' ).resolve;
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' );
 var Float64Array = require( '@stdlib/array/float64' );
@@ -125,7 +124,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 });
 
 tape( 'the function supports a `stride` parameter', opts, function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -140,15 +138,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) {
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = dmaxsorted( N, x, 2, 0 );
+	v = dmaxsorted( 4, x, 2, 0 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
 });
 
 tape( 'the function supports a negative `stride` parameter', opts, function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -163,8 +159,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = dmaxsorted( N, x, -2, 6 );
+	v = dmaxsorted( 4, x, -2, 6 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
@@ -183,7 +178,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f
 });
 
 tape( 'the function supports an `offset` parameter', opts, function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -197,9 +191,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) {
 		3.0,
 		4.0   // 3
 	]);
-	N = floor( x.length / 2 );
 
-	v = dmaxsorted( N, x, 2, 1 );
+	v = dmaxsorted( 4, x, 2, 1 );
 	t.strictEqual( v, 4.0, 'returns expected value' );
 
 	t.end();

From 3d3e5e078748af42134ec2abf9e0f425a5efd812 Mon Sep 17 00:00:00 2001
From: Snehil Shah <snehilshah.989@gmail.com>
Date: Fri, 3 Jan 2025 01:00:09 +0530
Subject: [PATCH 09/87] fix: guard against proxy traps raising exceptions in
 REPL tokenizer

PR-URL: https://github.com/stdlib-js/stdlib/pull/4457
Reviewed-by: Athan Reines <kgryte@gmail.com>
---
 .../@stdlib/repl/lib/tokenizer.js             | 37 +++++++++++++------
 1 file changed, 25 insertions(+), 12 deletions(-)

diff --git a/lib/node_modules/@stdlib/repl/lib/tokenizer.js b/lib/node_modules/@stdlib/repl/lib/tokenizer.js
index 188ae75ce857..825aba460bbd 100644
--- a/lib/node_modules/@stdlib/repl/lib/tokenizer.js
+++ b/lib/node_modules/@stdlib/repl/lib/tokenizer.js
@@ -24,6 +24,7 @@
 
 var parse = require( 'acorn-loose' ).parse;
 var walk = require( 'acorn-walk' );
+var hasProp = require( '@stdlib/assert/has-property' );
 var linkedList = require( '@stdlib/utils/linked-list' );
 var contains = require( '@stdlib/array/base/assert/contains' );
 var resolveLocalScopes = require( './resolve_local_scopes.js' );
@@ -227,7 +228,7 @@ function tokenizer( line, context ) {
 		for ( i = 0; i < COMMANDS.length; i++ ) {
 			command = COMMANDS[ i ];
 			if ( node.name === command[ 0 ] ) {
-				tokens.push( {
+				tokens.push({
 					'value': node.name,
 					'type': 'command',
 					'start': node.start,
@@ -240,14 +241,14 @@ function tokenizer( line, context ) {
 		identifier = context[ node.name ];
 		if ( identifier ) {
 			if ( isLiteralType( typeof identifier ) ) {
-				tokens.push( {
+				tokens.push({
 					'value': node.name,
 					'type': 'variable',
 					'start': node.start,
 					'end': node.end
 				});
 			} else {
-				tokens.push( {
+				tokens.push({
 					'value': node.name,
 					'type': typeof identifier,
 					'start': node.start,
@@ -313,9 +314,13 @@ function tokenizer( line, context ) {
 			}
 			// Case: 'bar' in `foo['bar']` - property already pushed as a string token. Ignore...
 			if ( property.value.type === 'Literal' ) {
-				obj = obj[ property.value.value ];
-				if ( !obj ) {
-					// Property not found in context:
+				try {
+					if ( !hasProp( obj, property.value.value ) ) {
+						// Property not found in context:
+						break;
+					}
+					obj = obj[ property.value.value ];
+				} catch ( error ) { // eslint-disable-line no-unused-vars
 					break;
 				}
 				property = properties.next();
@@ -323,9 +328,13 @@ function tokenizer( line, context ) {
 			}
 			// Case: `foo.bar` - resolve property and push it as a token...
 			if ( property.value.type === 'Identifier' ) {
-				obj = obj[ property.value.name ];
-				if ( !obj ) {
-					// Property not found in context:
+				try {
+					if ( !hasProp( obj, property.value.name ) ) {
+						// Property not found in context:
+						break;
+					}
+					obj = obj[ property.value.name ];
+				} catch ( error ) { // eslint-disable-line no-unused-vars
 					break;
 				}
 				if ( !compute ) {
@@ -356,9 +365,13 @@ function tokenizer( line, context ) {
 					// Couldn't compute the internal `MemberExpression` into a definite name:
 					break;
 				}
-				obj = obj[ computed ];
-				if ( !obj ) {
-					// Property not found in context:
+				try {
+					if ( !hasProp( obj, computed ) ) {
+						// Property not found in context:
+						break;
+					}
+					obj = obj[ computed ];
+				} catch ( error ) { // eslint-disable-line no-unused-vars
 					break;
 				}
 				property = properties.next();

From 2587ed985583913dc49d9e47955a91da14442f83 Mon Sep 17 00:00:00 2001
From: Athan Reines <kgryte@gmail.com>
Date: Thu, 2 Jan 2025 11:46:56 -0800
Subject: [PATCH 10/87] style: add missing parentheses

---
type: pre_commit_static_analysis_report
description: Results of running static analysis checks when committing changes.
report:
  - task: lint_filenames
    status: passed
  - task: lint_editorconfig
    status: passed
  - task: lint_markdown
    status: na
  - task: lint_package_json
    status: na
  - task: lint_repl_help
    status: na
  - task: lint_javascript_src
    status: na
  - task: lint_javascript_cli
    status: na
  - task: lint_javascript_examples
    status: na
  - task: lint_javascript_tests
    status: na
  - task: lint_javascript_benchmarks
    status: na
  - task: lint_python
    status: na
  - task: lint_r
    status: na
  - task: lint_c_src
    status: passed
  - task: lint_c_examples
    status: na
  - task: lint_c_benchmarks
    status: na
  - task: lint_c_tests_fixtures
    status: na
  - task: lint_shell
    status: na
  - task: lint_typescript_declarations
    status: na
  - task: lint_typescript_tests
    status: na
  - task: lint_license_headers
    status: passed
---

---
type: pre_push_report
description: Results of running various checks prior to pushing changes.
report:
  - task: run_javascript_examples
    status: na
  - task: run_c_examples
    status: na
  - task: run_cpp_examples
    status: na
  - task: run_javascript_readme_examples
    status: na
  - task: run_c_benchmarks
    status: na
  - task: run_cpp_benchmarks
    status: na
  - task: run_fortran_benchmarks
    status: na
  - task: run_javascript_benchmarks
    status: na
  - task: run_julia_benchmarks
    status: na
  - task: run_python_benchmarks
    status: na
  - task: run_r_benchmarks
    status: na
  - task: run_javascript_tests
    status: na
---
---
 lib/node_modules/@stdlib/stats/base/dmaxsorted/src/main.c | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/lib/node_modules/@stdlib/stats/base/dmaxsorted/src/main.c b/lib/node_modules/@stdlib/stats/base/dmaxsorted/src/main.c
index d7bc211b74f6..bc731204b781 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxsorted/src/main.c
+++ b/lib/node_modules/@stdlib/stats/base/dmaxsorted/src/main.c
@@ -55,7 +55,7 @@ double API_SUFFIX(stdlib_strided_dmaxsorted_ndarray)( const CBLAS_INT N, const d
 		return X[ 0 ];
 	}
 	v1 = X[ offsetX ];
-	v2 = X[ (N-1) * strideX + offsetX ];
+	v2 = X[ ( (N-1)*strideX ) + offsetX ];
 	if ( stdlib_base_is_nan( v1 ) || stdlib_base_is_nan( v2 ) ) {
 		return 0.0 / 0.0; // NaN
 	}

From 1256364988bdd9cf138eb05be7f1164df9b8d73a Mon Sep 17 00:00:00 2001
From: Vivek maurya <155618190+vivekmaurya001@users.noreply.github.com>
Date: Fri, 3 Jan 2025 01:18:48 +0530
Subject: [PATCH 11/87] refactor: update `stats/base/smeanli` native addon from
 C++ to C

PR-URL: https://github.com/stdlib-js/stdlib/pull/4465
Reviewed-by: Athan Reines <kgryte@gmail.com>
---
 .../@stdlib/stats/base/smeanli/include.gypi   |   2 +-
 .../@stdlib/stats/base/smeanli/manifest.json  |  42 ++++++-
 .../@stdlib/stats/base/smeanli/src/addon.c    |  43 +++++++
 .../@stdlib/stats/base/smeanli/src/addon.cpp  | 117 ------------------
 4 files changed, 85 insertions(+), 119 deletions(-)
 create mode 100644 lib/node_modules/@stdlib/stats/base/smeanli/src/addon.c
 delete mode 100644 lib/node_modules/@stdlib/stats/base/smeanli/src/addon.cpp

diff --git a/lib/node_modules/@stdlib/stats/base/smeanli/include.gypi b/lib/node_modules/@stdlib/stats/base/smeanli/include.gypi
index 868c5c12e852..26476a8c2655 100644
--- a/lib/node_modules/@stdlib/stats/base/smeanli/include.gypi
+++ b/lib/node_modules/@stdlib/stats/base/smeanli/include.gypi
@@ -36,7 +36,7 @@
 
     # Source files:
     'src_files': [
-      '<(src_dir)/addon.cpp',
+      '<(src_dir)/addon.c',
       '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).src; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
     ],
 
diff --git a/lib/node_modules/@stdlib/stats/base/smeanli/manifest.json b/lib/node_modules/@stdlib/stats/base/smeanli/manifest.json
index 30f69fc760e7..df6011b4377f 100644
--- a/lib/node_modules/@stdlib/stats/base/smeanli/manifest.json
+++ b/lib/node_modules/@stdlib/stats/base/smeanli/manifest.json
@@ -1,5 +1,7 @@
 {
-  "options": {},
+  "options": {
+    "task": "build"
+  },
   "fields": [
     {
       "field": "src",
@@ -24,6 +26,44 @@
   ],
   "confs": [
     {
+      "task": "build",
+      "src": [
+        "./src/smeanli.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [
+        "-lm"
+      ],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/blas/ext/base/sapxsum",
+        "@stdlib/napi/export",
+        "@stdlib/napi/argv",
+        "@stdlib/napi/argv-int64",
+        "@stdlib/napi/argv-strided-float32array",
+        "@stdlib/napi/create-double"
+      ]
+    },
+    {
+      "task": "benchmark",
+      "src": [
+        "./src/smeanli.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [
+        "-lm"
+      ],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/blas/ext/base/sapxsum"
+      ]
+    },
+    {
+      "task": "examples",
       "src": [
         "./src/smeanli.c"
       ],
diff --git a/lib/node_modules/@stdlib/stats/base/smeanli/src/addon.c b/lib/node_modules/@stdlib/stats/base/smeanli/src/addon.c
new file mode 100644
index 000000000000..c4600c9b30c6
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/smeanli/src/addon.c
@@ -0,0 +1,43 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/smeanli.h"
+#include "stdlib/napi/export.h"
+#include "stdlib/napi/argv.h"
+#include "stdlib/napi/argv_int64.h"
+#include "stdlib/napi/argv_strided_float32array.h"
+#include "stdlib/napi/create_double.h"
+#include <node_api.h>
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 3 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_INT64( env, stride, argv, 2 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 1 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_smeanli( N, X, stride ), v );
+	return v;
+}
+
+STDLIB_NAPI_MODULE_EXPORT_FCN( addon )
diff --git a/lib/node_modules/@stdlib/stats/base/smeanli/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/smeanli/src/addon.cpp
deleted file mode 100644
index f7869e9451aa..000000000000
--- a/lib/node_modules/@stdlib/stats/base/smeanli/src/addon.cpp
+++ /dev/null
@@ -1,117 +0,0 @@
-/**
-* @license Apache-2.0
-*
-* Copyright (c) 2020 The Stdlib Authors.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-*    http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-
-#include "stdlib/stats/base/smeanli.h"
-#include <node_api.h>
-#include <stdint.h>
-#include <stdlib.h>
-#include <stdbool.h>
-#include <assert.h>
-
-/**
-* Add-on namespace.
-*/
-namespace stdlib_stats_base_smeanli {
-
-	/**
-	* Computes the arithmetic mean of a single-precision floating-point strided array using a one-pass trial mean algorithm.
-	*
-	* ## Notes
-	*
-	* -   When called from JavaScript, the function expects three arguments:
-	*
-	*     -   `N`: number of indexed elements
-	*     -   `X`: input array
-	*     -   `stride`: stride length
-	*/
-	napi_value node_smeanli( napi_env env, napi_callback_info info ) {
-		napi_status status;
-
-		size_t argc = 3;
-		napi_value argv[ 3 ];
-		status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr );
-		assert( status == napi_ok );
-
-		if ( argc < 3 ) {
-			napi_throw_error( env, nullptr, "invalid invocation. Must provide 3 arguments." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype0;
-		status = napi_typeof( env, argv[ 0 ], &vtype0 );
-		assert( status == napi_ok );
-		if ( vtype0 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." );
-			return nullptr;
-		}
-
-		bool res;
-		status = napi_is_typedarray( env, argv[ 1 ], &res );
-		assert( status == napi_ok );
-		if ( res == false ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype2;
-		status = napi_typeof( env, argv[ 2 ], &vtype2 );
-		assert( status == napi_ok );
-		if ( vtype2 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." );
-			return nullptr;
-		}
-
-		int64_t N;
-		status = napi_get_value_int64( env, argv[ 0 ], &N );
-		assert( status == napi_ok );
-
-		int64_t stride;
-		status = napi_get_value_int64( env, argv[ 2 ], &stride );
-		assert( status == napi_ok );
-
-		napi_typedarray_type vtype1;
-		size_t xlen;
-		void *X;
-		status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr );
-		assert( status == napi_ok );
-		if ( vtype1 != napi_float32_array ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." );
-			return nullptr;
-		}
-		if ( (N-1)*llabs(stride) >= (int64_t)xlen ) {
-			napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." );
-			return nullptr;
-		}
-
-		napi_value v;
-		status = napi_create_double( env, (double)stdlib_strided_smeanli( N, (float *)X, stride ), &v );
-		assert( status == napi_ok );
-
-		return v;
-	}
-
-	napi_value Init( napi_env env, napi_value exports ) {
-		napi_status status;
-		napi_value fcn;
-		status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_smeanli, NULL, &fcn );
-		assert( status == napi_ok );
-		return fcn;
-	}
-
-	NAPI_MODULE( NODE_GYP_MODULE_NAME, Init )
-} // end namespace stdlib_stats_base_smeanli

From ae1ea187db160fe25e42fb000550a61237c3066c Mon Sep 17 00:00:00 2001
From: Vivek maurya <155618190+vivekmaurya001@users.noreply.github.com>
Date: Fri, 3 Jan 2025 01:20:30 +0530
Subject: [PATCH 12/87] refactor: update `stats/base/smeankbn2` native addon
 from C++ to C

PR-URL: https://github.com/stdlib-js/stdlib/pull/4464
Reviewed-by: Athan Reines <kgryte@gmail.com>
---
 .../@stdlib/stats/base/smeankbn2/include.gypi |   2 +-
 .../stats/base/smeankbn2/manifest.json        |  42 ++++++-
 .../@stdlib/stats/base/smeankbn2/src/addon.c  |  43 +++++++
 .../stats/base/smeankbn2/src/addon.cpp        | 117 ------------------
 4 files changed, 85 insertions(+), 119 deletions(-)
 create mode 100644 lib/node_modules/@stdlib/stats/base/smeankbn2/src/addon.c
 delete mode 100644 lib/node_modules/@stdlib/stats/base/smeankbn2/src/addon.cpp

diff --git a/lib/node_modules/@stdlib/stats/base/smeankbn2/include.gypi b/lib/node_modules/@stdlib/stats/base/smeankbn2/include.gypi
index 868c5c12e852..26476a8c2655 100644
--- a/lib/node_modules/@stdlib/stats/base/smeankbn2/include.gypi
+++ b/lib/node_modules/@stdlib/stats/base/smeankbn2/include.gypi
@@ -36,7 +36,7 @@
 
     # Source files:
     'src_files': [
-      '<(src_dir)/addon.cpp',
+      '<(src_dir)/addon.c',
       '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).src; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
     ],
 
diff --git a/lib/node_modules/@stdlib/stats/base/smeankbn2/manifest.json b/lib/node_modules/@stdlib/stats/base/smeankbn2/manifest.json
index 5a2a1012abec..034ca8435340 100644
--- a/lib/node_modules/@stdlib/stats/base/smeankbn2/manifest.json
+++ b/lib/node_modules/@stdlib/stats/base/smeankbn2/manifest.json
@@ -1,5 +1,7 @@
 {
-  "options": {},
+  "options": {
+    "task": "build"
+  },
   "fields": [
     {
       "field": "src",
@@ -24,6 +26,44 @@
   ],
   "confs": [
     {
+      "task": "build",
+      "src": [
+        "./src/smeankbn2.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [
+        "-lm"
+      ],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/blas/ext/base/ssumkbn2",
+        "@stdlib/napi/export",
+        "@stdlib/napi/argv",
+        "@stdlib/napi/argv-int64",
+        "@stdlib/napi/argv-strided-float32array",
+        "@stdlib/napi/create-double"
+      ]
+    },
+    {
+      "task": "benchmark",
+      "src": [
+        "./src/smeankbn2.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [
+        "-lm"
+      ],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/blas/ext/base/ssumkbn2"
+      ]
+    },
+    {
+      "task": "examples",
       "src": [
         "./src/smeankbn2.c"
       ],
diff --git a/lib/node_modules/@stdlib/stats/base/smeankbn2/src/addon.c b/lib/node_modules/@stdlib/stats/base/smeankbn2/src/addon.c
new file mode 100644
index 000000000000..3a8c14423661
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/smeankbn2/src/addon.c
@@ -0,0 +1,43 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/smeankbn2.h"
+#include "stdlib/napi/export.h"
+#include "stdlib/napi/argv.h"
+#include "stdlib/napi/argv_int64.h"
+#include "stdlib/napi/argv_strided_float32array.h"
+#include "stdlib/napi/create_double.h"
+#include <node_api.h>
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 3 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_INT64( env, stride, argv, 2 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 1 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_smeankbn2( N, X, stride ), v );
+	return v;
+}
+
+STDLIB_NAPI_MODULE_EXPORT_FCN( addon )
diff --git a/lib/node_modules/@stdlib/stats/base/smeankbn2/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/smeankbn2/src/addon.cpp
deleted file mode 100644
index b3137e597900..000000000000
--- a/lib/node_modules/@stdlib/stats/base/smeankbn2/src/addon.cpp
+++ /dev/null
@@ -1,117 +0,0 @@
-/**
-* @license Apache-2.0
-*
-* Copyright (c) 2020 The Stdlib Authors.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-*    http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-
-#include "stdlib/stats/base/smeankbn2.h"
-#include <node_api.h>
-#include <stdint.h>
-#include <stdlib.h>
-#include <stdbool.h>
-#include <assert.h>
-
-/**
-* Add-on namespace.
-*/
-namespace stdlib_stats_base_smeankbn2 {
-
-	/**
-	* Computes the arithmetic mean of a single-precision floating-point strided array using a second-order iterative Kahan–Babuška algorithm.
-	*
-	* ## Notes
-	*
-	* -   When called from JavaScript, the function expects three arguments:
-	*
-	*     -   `N`: number of indexed elements
-	*     -   `X`: input array
-	*     -   `stride`: stride length
-	*/
-	napi_value node_smeankbn2( napi_env env, napi_callback_info info ) {
-		napi_status status;
-
-		size_t argc = 3;
-		napi_value argv[ 3 ];
-		status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr );
-		assert( status == napi_ok );
-
-		if ( argc < 3 ) {
-			napi_throw_error( env, nullptr, "invalid invocation. Must provide 3 arguments." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype0;
-		status = napi_typeof( env, argv[ 0 ], &vtype0 );
-		assert( status == napi_ok );
-		if ( vtype0 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." );
-			return nullptr;
-		}
-
-		bool res;
-		status = napi_is_typedarray( env, argv[ 1 ], &res );
-		assert( status == napi_ok );
-		if ( res == false ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype2;
-		status = napi_typeof( env, argv[ 2 ], &vtype2 );
-		assert( status == napi_ok );
-		if ( vtype2 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." );
-			return nullptr;
-		}
-
-		int64_t N;
-		status = napi_get_value_int64( env, argv[ 0 ], &N );
-		assert( status == napi_ok );
-
-		int64_t stride;
-		status = napi_get_value_int64( env, argv[ 2 ], &stride );
-		assert( status == napi_ok );
-
-		napi_typedarray_type vtype1;
-		size_t xlen;
-		void *X;
-		status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr );
-		assert( status == napi_ok );
-		if ( vtype1 != napi_float32_array ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." );
-			return nullptr;
-		}
-		if ( (N-1)*llabs(stride) >= (int64_t)xlen ) {
-			napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." );
-			return nullptr;
-		}
-
-		napi_value v;
-		status = napi_create_double( env, (double)stdlib_strided_smeankbn2( N, (float *)X, stride ), &v );
-		assert( status == napi_ok );
-
-		return v;
-	}
-
-	napi_value Init( napi_env env, napi_value exports ) {
-		napi_status status;
-		napi_value fcn;
-		status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_smeankbn2, NULL, &fcn );
-		assert( status == napi_ok );
-		return fcn;
-	}
-
-	NAPI_MODULE( NODE_GYP_MODULE_NAME, Init )
-} // end namespace stdlib_stats_base_smeankbn2

From 082627dece5a65f18df4a200b92c1396d4b26ce5 Mon Sep 17 00:00:00 2001
From: Vivek maurya <155618190+vivekmaurya001@users.noreply.github.com>
Date: Fri, 3 Jan 2025 01:21:32 +0530
Subject: [PATCH 13/87] refactor: update `stats/base/smeankbn` native addon
 from C++ to C

PR-URL: https://github.com/stdlib-js/stdlib/pull/4463
Reviewed-by: Athan Reines <kgryte@gmail.com>
---
 .../@stdlib/stats/base/smeankbn/include.gypi  |   2 +-
 .../@stdlib/stats/base/smeankbn/manifest.json |  42 ++++++-
 .../@stdlib/stats/base/smeankbn/src/addon.c   |  43 +++++++
 .../@stdlib/stats/base/smeankbn/src/addon.cpp | 117 ------------------
 4 files changed, 85 insertions(+), 119 deletions(-)
 create mode 100644 lib/node_modules/@stdlib/stats/base/smeankbn/src/addon.c
 delete mode 100644 lib/node_modules/@stdlib/stats/base/smeankbn/src/addon.cpp

diff --git a/lib/node_modules/@stdlib/stats/base/smeankbn/include.gypi b/lib/node_modules/@stdlib/stats/base/smeankbn/include.gypi
index 868c5c12e852..26476a8c2655 100644
--- a/lib/node_modules/@stdlib/stats/base/smeankbn/include.gypi
+++ b/lib/node_modules/@stdlib/stats/base/smeankbn/include.gypi
@@ -36,7 +36,7 @@
 
     # Source files:
     'src_files': [
-      '<(src_dir)/addon.cpp',
+      '<(src_dir)/addon.c',
       '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).src; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
     ],
 
diff --git a/lib/node_modules/@stdlib/stats/base/smeankbn/manifest.json b/lib/node_modules/@stdlib/stats/base/smeankbn/manifest.json
index b5e3b65a50be..8b4d2c24dcae 100644
--- a/lib/node_modules/@stdlib/stats/base/smeankbn/manifest.json
+++ b/lib/node_modules/@stdlib/stats/base/smeankbn/manifest.json
@@ -1,5 +1,7 @@
 {
-  "options": {},
+  "options": {
+    "task": "build"
+  },
   "fields": [
     {
       "field": "src",
@@ -24,6 +26,44 @@
   ],
   "confs": [
     {
+      "task": "build",
+      "src": [
+        "./src/smeankbn.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [
+        "-lm"
+      ],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/blas/ext/base/ssum",
+        "@stdlib/napi/export",
+        "@stdlib/napi/argv",
+        "@stdlib/napi/argv-int64",
+        "@stdlib/napi/argv-strided-float32array",
+        "@stdlib/napi/create-double"
+      ]
+    },
+    {
+      "task": "benchmark",
+      "src": [
+        "./src/smeankbn.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [
+        "-lm"
+      ],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/blas/ext/base/ssum"
+      ]
+    },
+    {
+      "task": "examples",
       "src": [
         "./src/smeankbn.c"
       ],
diff --git a/lib/node_modules/@stdlib/stats/base/smeankbn/src/addon.c b/lib/node_modules/@stdlib/stats/base/smeankbn/src/addon.c
new file mode 100644
index 000000000000..29fefbfde965
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/smeankbn/src/addon.c
@@ -0,0 +1,43 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/smeankbn.h"
+#include "stdlib/napi/export.h"
+#include "stdlib/napi/argv.h"
+#include "stdlib/napi/argv_int64.h"
+#include "stdlib/napi/argv_strided_float32array.h"
+#include "stdlib/napi/create_double.h"
+#include <node_api.h>
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 3 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_INT64( env, stride, argv, 2 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 1 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_smeankbn( N, X, stride ), v );
+	return v;
+}
+
+STDLIB_NAPI_MODULE_EXPORT_FCN( addon )
diff --git a/lib/node_modules/@stdlib/stats/base/smeankbn/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/smeankbn/src/addon.cpp
deleted file mode 100644
index f81f6b55202d..000000000000
--- a/lib/node_modules/@stdlib/stats/base/smeankbn/src/addon.cpp
+++ /dev/null
@@ -1,117 +0,0 @@
-/**
-* @license Apache-2.0
-*
-* Copyright (c) 2020 The Stdlib Authors.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-*    http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-
-#include "stdlib/stats/base/smeankbn.h"
-#include <node_api.h>
-#include <stdint.h>
-#include <stdlib.h>
-#include <stdbool.h>
-#include <assert.h>
-
-/**
-* Add-on namespace.
-*/
-namespace stdlib_stats_base_smeankbn {
-
-	/**
-	* Computes the arithmetic mean of a single-precision floating-point strided array using an improved Kahan–Babuška algorithm.
-	*
-	* ## Notes
-	*
-	* -   When called from JavaScript, the function expects three arguments:
-	*
-	*     -   `N`: number of indexed elements
-	*     -   `X`: input array
-	*     -   `stride`: stride length
-	*/
-	napi_value node_smeankbn( napi_env env, napi_callback_info info ) {
-		napi_status status;
-
-		size_t argc = 3;
-		napi_value argv[ 3 ];
-		status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr );
-		assert( status == napi_ok );
-
-		if ( argc < 3 ) {
-			napi_throw_error( env, nullptr, "invalid invocation. Must provide 3 arguments." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype0;
-		status = napi_typeof( env, argv[ 0 ], &vtype0 );
-		assert( status == napi_ok );
-		if ( vtype0 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." );
-			return nullptr;
-		}
-
-		bool res;
-		status = napi_is_typedarray( env, argv[ 1 ], &res );
-		assert( status == napi_ok );
-		if ( res == false ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype2;
-		status = napi_typeof( env, argv[ 2 ], &vtype2 );
-		assert( status == napi_ok );
-		if ( vtype2 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." );
-			return nullptr;
-		}
-
-		int64_t N;
-		status = napi_get_value_int64( env, argv[ 0 ], &N );
-		assert( status == napi_ok );
-
-		int64_t stride;
-		status = napi_get_value_int64( env, argv[ 2 ], &stride );
-		assert( status == napi_ok );
-
-		napi_typedarray_type vtype1;
-		size_t xlen;
-		void *X;
-		status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr );
-		assert( status == napi_ok );
-		if ( vtype1 != napi_float32_array ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." );
-			return nullptr;
-		}
-		if ( (N-1)*llabs(stride) >= (int64_t)xlen ) {
-			napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." );
-			return nullptr;
-		}
-
-		napi_value v;
-		status = napi_create_double( env, (double)stdlib_strided_smeankbn( N, (float *)X, stride ), &v );
-		assert( status == napi_ok );
-
-		return v;
-	}
-
-	napi_value Init( napi_env env, napi_value exports ) {
-		napi_status status;
-		napi_value fcn;
-		status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_smeankbn, NULL, &fcn );
-		assert( status == napi_ok );
-		return fcn;
-	}
-
-	NAPI_MODULE( NODE_GYP_MODULE_NAME, Init )
-} // end namespace stdlib_stats_base_smeankbn

From 82c864a50fc39b653e59dcf7a3b9bfde47dfa50b Mon Sep 17 00:00:00 2001
From: Vivek maurya <155618190+vivekmaurya001@users.noreply.github.com>
Date: Fri, 3 Jan 2025 01:22:27 +0530
Subject: [PATCH 14/87] refactor: update `stats/base/smean` native addon from
 C++ to C

PR-URL: https://github.com/stdlib-js/stdlib/pull/4462
Reviewed-by: Athan Reines <kgryte@gmail.com>
---
 .../@stdlib/stats/base/smean/include.gypi     |   2 +-
 .../@stdlib/stats/base/smean/manifest.json    |  42 ++++++-
 .../@stdlib/stats/base/smean/src/addon.c      |  43 +++++++
 .../@stdlib/stats/base/smean/src/addon.cpp    | 117 ------------------
 4 files changed, 85 insertions(+), 119 deletions(-)
 create mode 100644 lib/node_modules/@stdlib/stats/base/smean/src/addon.c
 delete mode 100644 lib/node_modules/@stdlib/stats/base/smean/src/addon.cpp

diff --git a/lib/node_modules/@stdlib/stats/base/smean/include.gypi b/lib/node_modules/@stdlib/stats/base/smean/include.gypi
index 868c5c12e852..26476a8c2655 100644
--- a/lib/node_modules/@stdlib/stats/base/smean/include.gypi
+++ b/lib/node_modules/@stdlib/stats/base/smean/include.gypi
@@ -36,7 +36,7 @@
 
     # Source files:
     'src_files': [
-      '<(src_dir)/addon.cpp',
+      '<(src_dir)/addon.c',
       '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).src; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
     ],
 
diff --git a/lib/node_modules/@stdlib/stats/base/smean/manifest.json b/lib/node_modules/@stdlib/stats/base/smean/manifest.json
index b90b9aa6fe41..2c235970fe47 100644
--- a/lib/node_modules/@stdlib/stats/base/smean/manifest.json
+++ b/lib/node_modules/@stdlib/stats/base/smean/manifest.json
@@ -1,5 +1,7 @@
 {
-  "options": {},
+  "options": {
+    "task": "build"
+  },
   "fields": [
     {
       "field": "src",
@@ -24,6 +26,44 @@
   ],
   "confs": [
     {
+      "task": "build",
+      "src": [
+        "./src/smean.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [
+        "-lm"
+      ],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/stats/base/smeanpn",
+        "@stdlib/napi/export",
+        "@stdlib/napi/argv",
+        "@stdlib/napi/argv-int64",
+        "@stdlib/napi/argv-strided-float32array",
+        "@stdlib/napi/create-double"
+      ]
+    },
+    {
+      "task": "benchmark",
+      "src": [
+        "./src/smean.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [
+        "-lm"
+      ],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/stats/base/smeanpn"
+      ]
+    },
+    {
+      "task": "examples",
       "src": [
         "./src/smean.c"
       ],
diff --git a/lib/node_modules/@stdlib/stats/base/smean/src/addon.c b/lib/node_modules/@stdlib/stats/base/smean/src/addon.c
new file mode 100644
index 000000000000..ac2eaade3c79
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/smean/src/addon.c
@@ -0,0 +1,43 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/smean.h"
+#include "stdlib/napi/export.h"
+#include "stdlib/napi/argv.h"
+#include "stdlib/napi/argv_int64.h"
+#include "stdlib/napi/argv_strided_float32array.h"
+#include "stdlib/napi/create_double.h"
+#include <node_api.h>
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 3 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_INT64( env, stride, argv, 2 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 1 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_smean( N, X, stride ), v );
+	return v;
+}
+
+STDLIB_NAPI_MODULE_EXPORT_FCN( addon )
diff --git a/lib/node_modules/@stdlib/stats/base/smean/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/smean/src/addon.cpp
deleted file mode 100644
index f6e2a81d05e3..000000000000
--- a/lib/node_modules/@stdlib/stats/base/smean/src/addon.cpp
+++ /dev/null
@@ -1,117 +0,0 @@
-/**
-* @license Apache-2.0
-*
-* Copyright (c) 2020 The Stdlib Authors.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-*    http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-
-#include "stdlib/stats/base/smean.h"
-#include <node_api.h>
-#include <stdint.h>
-#include <stdlib.h>
-#include <stdbool.h>
-#include <assert.h>
-
-/**
-* Add-on namespace.
-*/
-namespace stdlib_stats_base_smean {
-
-	/**
-	* Computes the arithmetic mean of a single-precision floating-point strided array.
-	*
-	* ## Notes
-	*
-	* -   When called from JavaScript, the function expects three arguments:
-	*
-	*     -   `N`: number of indexed elements
-	*     -   `X`: input array
-	*     -   `stride`: stride length
-	*/
-	napi_value node_smean( napi_env env, napi_callback_info info ) {
-		napi_status status;
-
-		size_t argc = 3;
-		napi_value argv[ 3 ];
-		status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr );
-		assert( status == napi_ok );
-
-		if ( argc < 3 ) {
-			napi_throw_error( env, nullptr, "invalid invocation. Must provide 3 arguments." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype0;
-		status = napi_typeof( env, argv[ 0 ], &vtype0 );
-		assert( status == napi_ok );
-		if ( vtype0 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." );
-			return nullptr;
-		}
-
-		bool res;
-		status = napi_is_typedarray( env, argv[ 1 ], &res );
-		assert( status == napi_ok );
-		if ( res == false ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype2;
-		status = napi_typeof( env, argv[ 2 ], &vtype2 );
-		assert( status == napi_ok );
-		if ( vtype2 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." );
-			return nullptr;
-		}
-
-		int64_t N;
-		status = napi_get_value_int64( env, argv[ 0 ], &N );
-		assert( status == napi_ok );
-
-		int64_t stride;
-		status = napi_get_value_int64( env, argv[ 2 ], &stride );
-		assert( status == napi_ok );
-
-		napi_typedarray_type vtype1;
-		size_t xlen;
-		void *X;
-		status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr );
-		assert( status == napi_ok );
-		if ( vtype1 != napi_float32_array ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." );
-			return nullptr;
-		}
-		if ( (N-1)*llabs(stride) >= (int64_t)xlen ) {
-			napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." );
-			return nullptr;
-		}
-
-		napi_value v;
-		status = napi_create_double( env, (double)stdlib_strided_smean( N, (float *)X, stride ), &v );
-		assert( status == napi_ok );
-
-		return v;
-	}
-
-	napi_value Init( napi_env env, napi_value exports ) {
-		napi_status status;
-		napi_value fcn;
-		status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_smean, NULL, &fcn );
-		assert( status == napi_ok );
-		return fcn;
-	}
-
-	NAPI_MODULE( NODE_GYP_MODULE_NAME, Init )
-} // end namespace stdlib_stats_base_smean

From 5156694851cf089357576044c79295fdd5ebfadd Mon Sep 17 00:00:00 2001
From: Aayush Khanna <96649223+aayush0325@users.noreply.github.com>
Date: Fri, 3 Jan 2025 01:23:15 +0530
Subject: [PATCH 15/87] feat: add C ndarray interface and refactor
 implementation for `stats/base/dminsorted`

PR-URL: https://github.com/stdlib-js/stdlib/pull/4201
Co-authored-by: Athan Reines <kgryte@gmail.com>
Reviewed-by: Athan Reines <kgryte@gmail.com>
Co-authored-by: stdlib-bot <82920195+stdlib-bot@users.noreply.github.com>
---
 .../@stdlib/stats/base/dminsorted/README.md   | 148 ++++++++++++++----
 .../base/dminsorted/benchmark/benchmark.js    |  17 +-
 .../dminsorted/benchmark/benchmark.native.js  |  13 +-
 .../dminsorted/benchmark/benchmark.ndarray.js |  17 +-
 .../benchmark/benchmark.ndarray.native.js     |  13 +-
 .../dminsorted/benchmark/c/benchmark.length.c |  50 +++++-
 .../stats/base/dminsorted/docs/repl.txt       |  30 ++--
 .../base/dminsorted/docs/types/index.d.ts     |  12 +-
 .../base/dminsorted/examples/c/example.c      |   9 +-
 .../stats/base/dminsorted/examples/index.js   |  13 +-
 .../stats/base/dminsorted/include.gypi        |   2 +-
 .../include/stdlib/stats/base/dminsorted.h    |   9 +-
 .../stats/base/dminsorted/lib/dminsorted.js   |  41 +----
 .../base/dminsorted/lib/dminsorted.native.js  |   9 +-
 .../stats/base/dminsorted/lib/index.js        |   7 +-
 .../stats/base/dminsorted/lib/ndarray.js      |  16 +-
 .../base/dminsorted/lib/ndarray.native.js     |  20 +--
 .../stats/base/dminsorted/manifest.json       |  74 ++++++++-
 .../@stdlib/stats/base/dminsorted/src/addon.c |  60 +++++++
 .../stats/base/dminsorted/src/addon.cpp       | 117 --------------
 .../dminsorted/src/{dminsorted.c => main.c}   |  38 +++--
 .../base/dminsorted/test/test.dminsorted.js   |  13 +-
 .../dminsorted/test/test.dminsorted.native.js |  13 +-
 .../base/dminsorted/test/test.ndarray.js      |  13 +-
 .../dminsorted/test/test.ndarray.native.js    |  13 +-
 25 files changed, 420 insertions(+), 347 deletions(-)
 create mode 100644 lib/node_modules/@stdlib/stats/base/dminsorted/src/addon.c
 delete mode 100644 lib/node_modules/@stdlib/stats/base/dminsorted/src/addon.cpp
 rename lib/node_modules/@stdlib/stats/base/dminsorted/src/{dminsorted.c => main.c} (54%)

diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/README.md b/lib/node_modules/@stdlib/stats/base/dminsorted/README.md
index dd2101aa24ec..2d6641d11787 100644
--- a/lib/node_modules/@stdlib/stats/base/dminsorted/README.md
+++ b/lib/node_modules/@stdlib/stats/base/dminsorted/README.md
@@ -36,7 +36,7 @@ limitations under the License.
 var dminsorted = require( '@stdlib/stats/base/dminsorted' );
 ```
 
-#### dminsorted( N, x, stride )
+#### dminsorted( N, x, strideX )
 
 Computes the minimum value of a sorted double-precision floating-point strided array `x`.
 
@@ -44,15 +44,13 @@ Computes the minimum value of a sorted double-precision floating-point strided a
 var Float64Array = require( '@stdlib/array/float64' );
 
 var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );
-var N = x.length;
 
-var v = dminsorted( N, x, 1 );
+var v = dminsorted( x.length, x, 1 );
 // returns 1.0
 
 x = new Float64Array( [ 3.0, 2.0, 1.0 ] );
-N = x.length;
 
-v = dminsorted( N, x, 1 );
+v = dminsorted( x.length, x, 1 );
 // returns 1.0
 ```
 
@@ -60,18 +58,16 @@ The function has the following parameters:
 
 -   **N**: number of indexed elements.
 -   **x**: sorted input [`Float64Array`][@stdlib/array/float64].
--   **stride**: index increment for `x`.
+-   **strideX**: stride length for `x`.
 
-The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the minimum value of every other element in `x`,
+The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the minimum value of every other element in `x`,
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, 3.0, 3.0, 4.0, 2.0 ] );
-var N = floor( x.length / 2 );
 
-var v = dminsorted( N, x, 2 );
+var v = dminsorted( 4, x, 2 );
 // returns 1.0
 ```
 
@@ -81,18 +77,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x0 = new Float64Array( [ 2.0, 1.0, 2.0, 2.0, -2.0, 2.0, 3.0, 4.0 ] );
 var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
 
-var N = floor( x0.length / 2 );
-
-var v = dminsorted( N, x1, 2 );
+var v = dminsorted( 4, x1, 2 );
 // returns 1.0
 ```
 
-#### dminsorted.ndarray( N, x, stride, offset )
+#### dminsorted.ndarray( N, x, strideX, offsetX )
 
 Computes the minimum value of a sorted double-precision floating-point strided array using alternative indexing semantics.
 
@@ -100,26 +93,23 @@ Computes the minimum value of a sorted double-precision floating-point strided a
 var Float64Array = require( '@stdlib/array/float64' );
 
 var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );
-var N = x.length;
 
-var v = dminsorted.ndarray( N, x, 1, 0 );
+var v = dminsorted.ndarray( x.length, x, 1, 0 );
 // returns 1.0
 ```
 
 The function has the following additional parameters:
 
--   **offset**: starting index for `x`.
+-   **offsetX**: starting index for `x`.
 
-While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the minimum value for every other value in `x` starting from the second value
+While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the minimum value for every other element in `x` starting from the second element
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x = new Float64Array( [ 2.0, 1.0, 2.0, 2.0, -2.0, 2.0, 3.0, 4.0 ] );
-var N = floor( x.length / 2 );
 
-var v = dminsorted.ndarray( N, x, 2, 1 );
+var v = dminsorted.ndarray( 4, x, 2, 1 );
 // returns 1.0
 ```
 
@@ -145,16 +135,13 @@ var v = dminsorted.ndarray( N, x, 2, 1 );
 <!-- eslint no-undef: "error" -->
 
 ```javascript
-var Float64Array = require( '@stdlib/array/float64' );
+var linspace = require( '@stdlib/array/linspace' );
 var dminsorted = require( '@stdlib/stats/base/dminsorted' );
 
-var x;
-var i;
-
-x = new Float64Array( 10 );
-for ( i = 0; i < x.length; i++ ) {
-    x[ i ] = i - 5.0;
-}
+var options = {
+    'dtype': 'float64'
+};
+var x = linspace( -5.0, 5.0, 10, options );
 console.log( x );
 
 var v = dminsorted( x.length, x, 1 );
@@ -165,6 +152,107 @@ console.log( v );
 
 <!-- /.examples -->
 
+<!-- C usage documentation. -->
+
+<section class="usage">
+
+### Usage
+
+```c
+#include "stdlib/stats/base/dminsorted.h"
+```
+
+#### stdlib_strided_dminsorted( N, \*X, strideX )
+
+Computes the minimum value of a sorted double-precision floating-point strided array.
+
+```c
+const double x[] = { 1.0, 2.0, 3.0 };
+
+double v = stdlib_strided_dmax( 3, x, 1 );
+// returns 1.0
+```
+
+The function accepts the following arguments:
+
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **X**: `[in] double*` input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+
+```c
+double stdlib_strided_dminsorted( const CBLAS_INT N, const double *X, const CBLAS_INT strideX );
+```
+
+#### stdlib_strided_dminsorted_ndarray( N, \*X, strideX, offsetX )
+
+Computes the minimum value of a sorted double-precision floating-point strided array using alternative indexing semantics.
+
+```c
+const double x[] = { 1.0, 2.0, 3.0 };
+
+double v = stdlib_strided_dminsorted_ndarray( 3, x, 1, 0 );
+// returns 1.0
+```
+
+The function accepts the following arguments:
+
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **X**: `[in] double*` input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+-   **offsetX**: `[in] CBLAS_INT` starting index for `X`.
+
+```c
+double stdlib_strided_dminsorted_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX );
+```
+
+</section>
+
+<!-- /.usage -->
+
+<!-- C API usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="notes">
+
+</section>
+
+<!-- /.notes -->
+
+<!-- C API usage examples. -->
+
+<section class="examples">
+
+### Examples
+
+```c
+#include "stdlib/stats/base/dminsorted.h"
+#include <stdio.h>
+
+int main( void ) {
+    // Create a strided array:
+    const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 };
+
+    // Specify the number of elements:
+    const int N = 4;
+
+    // Specify the stride length:
+    const int strideX = 2;
+
+    // Compute the minimum value:
+    double v = stdlib_strided_dminsorted( N, x, strideX );
+
+    // Print the result:
+    printf( "min: %lf\n", v );
+}
+```
+
+</section>
+
+<!-- /.examples -->
+
+</section>
+
+<!-- /.c -->
+
 <!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
 
 <section class="related">
diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dminsorted/benchmark/benchmark.js
index aadd35b05c54..e3e721d8f786 100644
--- a/lib/node_modules/@stdlib/stats/base/dminsorted/benchmark/benchmark.js
+++ b/lib/node_modules/@stdlib/stats/base/dminsorted/benchmark/benchmark.js
@@ -22,12 +22,19 @@
 
 var bench = require( '@stdlib/bench' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var linspace = require( '@stdlib/array/linspace' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float64Array = require( '@stdlib/array/float64' );
 var pkg = require( './../package.json' ).name;
 var dminsorted = require( './../lib/dminsorted.js' );
 
 
+// VARIABLES //
+
+var options = {
+	'dtype': 'float64'
+};
+
+
 // FUNCTIONS //
 
 /**
@@ -38,13 +45,7 @@ var dminsorted = require( './../lib/dminsorted.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float64Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = i;
-	}
+	var x = linspace( -len/2, len/2, len, options );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dminsorted/benchmark/benchmark.native.js
index 217b78e07218..899273284846 100644
--- a/lib/node_modules/@stdlib/stats/base/dminsorted/benchmark/benchmark.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dminsorted/benchmark/benchmark.native.js
@@ -23,8 +23,8 @@
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var linspace = require( '@stdlib/array/linspace' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float64Array = require( '@stdlib/array/float64' );
 var tryRequire = require( '@stdlib/utils/try-require' );
 var pkg = require( './../package.json' ).name;
 
@@ -35,6 +35,9 @@ var dminsorted = tryRequire( resolve( __dirname, './../lib/dminsorted.native.js'
 var opts = {
 	'skip': ( dminsorted instanceof Error )
 };
+var options = {
+	'dtype': 'float64'
+};
 
 
 // FUNCTIONS //
@@ -47,13 +50,7 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float64Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = i;
-	}
+	var x = linspace( -len/2, len/2, len, options );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/dminsorted/benchmark/benchmark.ndarray.js
index 52be5dc90355..5665272757d6 100644
--- a/lib/node_modules/@stdlib/stats/base/dminsorted/benchmark/benchmark.ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/dminsorted/benchmark/benchmark.ndarray.js
@@ -22,12 +22,19 @@
 
 var bench = require( '@stdlib/bench' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var linspace = require( '@stdlib/array/linspace' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float64Array = require( '@stdlib/array/float64' );
 var pkg = require( './../package.json' ).name;
 var dminsorted = require( './../lib/ndarray.js' );
 
 
+// VARIABLES //
+
+var options = {
+	'dtype': 'float64'
+};
+
+
 // FUNCTIONS //
 
 /**
@@ -38,13 +45,7 @@ var dminsorted = require( './../lib/ndarray.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float64Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = i;
-	}
+	var x = linspace( -len/2, len/2, len, options );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dminsorted/benchmark/benchmark.ndarray.native.js
index 47c7a80f80c3..a01ecfba9c49 100644
--- a/lib/node_modules/@stdlib/stats/base/dminsorted/benchmark/benchmark.ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dminsorted/benchmark/benchmark.ndarray.native.js
@@ -23,8 +23,8 @@
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var linspace = require( '@stdlib/array/linspace' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float64Array = require( '@stdlib/array/float64' );
 var tryRequire = require( '@stdlib/utils/try-require' );
 var pkg = require( './../package.json' ).name;
 
@@ -35,6 +35,9 @@ var dminsorted = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' )
 var opts = {
 	'skip': ( dminsorted instanceof Error )
 };
+var options = {
+	'dtype': 'float64'
+};
 
 
 // FUNCTIONS //
@@ -47,13 +50,7 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float64Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = i;
-	}
+	var x = linspace( -len/2, len/2, len, options );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dminsorted/benchmark/c/benchmark.length.c
index 285c5fe8b2b2..11f4b5a044c5 100644
--- a/lib/node_modules/@stdlib/stats/base/dminsorted/benchmark/c/benchmark.length.c
+++ b/lib/node_modules/@stdlib/stats/base/dminsorted/benchmark/c/benchmark.length.c
@@ -94,7 +94,7 @@ static double rand_double( void ) {
 * @param len          array length
 * @return             elapsed time in seconds
 */
-static double benchmark( int iterations, int len ) {
+static double benchmark1( int iterations, int len ) {
 	double elapsed;
 	double x[ len ];
 	double v;
@@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) {
 	v = 0.0;
 	t = tic();
 	for ( i = 0; i < iterations; i++ ) {
+		// cppcheck-suppress uninitvar
 		v = stdlib_strided_dminsorted( len, x, 1 );
 		if ( v != v ) {
 			printf( "should not return NaN\n" );
@@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) {
 	return elapsed;
 }
 
+/**
+* Runs a benchmark.
+*
+* @param iterations   number of iterations
+* @param len          array length
+* @return             elapsed time in seconds
+*/
+static double benchmark2( int iterations, int len ) {
+	double elapsed;
+	double x[ len ];
+	double v;
+	double t;
+	int i;
+
+	for ( i = 0; i < len; i++ ) {
+		x[ i ] = i;
+	}
+	v = 0.0;
+	t = tic();
+	for ( i = 0; i < iterations; i++ ) {
+		// cppcheck-suppress uninitvar
+		v = stdlib_strided_dminsorted_ndarray( len, x, 1, 0 );
+		if ( v != v ) {
+			printf( "should not return NaN\n" );
+			break;
+		}
+	}
+	elapsed = tic() - t;
+	if ( v != v ) {
+		printf( "should not return NaN\n" );
+	}
+	return elapsed;
+}
+
 /**
 * Main execution sequence.
 */
@@ -142,7 +177,18 @@ int main( void ) {
 		for ( j = 0; j < REPEATS; j++ ) {
 			count += 1;
 			printf( "# c::%s:len=%d\n", NAME, len );
-			elapsed = benchmark( iter, len );
+			elapsed = benchmark1( iter, len );
+			print_results( iter, elapsed );
+			printf( "ok %d benchmark finished\n", count );
+		}
+	}
+	for ( i = MIN; i <= MAX; i++ ) {
+		len = pow( 10, i );
+		iter = ITERATIONS / pow( 10, i-1 );
+		for ( j = 0; j < REPEATS; j++ ) {
+			count += 1;
+			printf( "# c::%s:ndarray:len=%d\n", NAME, len );
+			elapsed = benchmark2( iter, len );
 			print_results( iter, elapsed );
 			printf( "ok %d benchmark finished\n", count );
 		}
diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dminsorted/docs/repl.txt
index a8c75a6241ff..332ba146d0af 100644
--- a/lib/node_modules/@stdlib/stats/base/dminsorted/docs/repl.txt
+++ b/lib/node_modules/@stdlib/stats/base/dminsorted/docs/repl.txt
@@ -1,12 +1,12 @@
 
-{{alias}}( N, x, stride )
+{{alias}}( N, x, strideX )
     Computes the minimum value of a sorted double-precision floating-point
     strided array.
 
     The input strided array must be sorted in either strictly ascending or
     descending order.
 
-    The `N` and `stride` parameters determine which elements in `x` are accessed
+    The `N` and stride parameters determine which elements in `x` are accessed
     at runtime.
 
     Indexing is relative to the first index. To introduce an offset, use a typed
@@ -22,8 +22,8 @@
     x: Float64Array
         Sorted input array.
 
-    stride: integer
-        Index increment.
+    strideX: integer
+        Stride Length.
 
     Returns
     -------
@@ -37,22 +37,19 @@
     > {{alias}}( x.length, x, 1 )
     1.0
 
-    // Using `N` and `stride` parameters:
+    // Using `N` and stride parameters:
     > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > var stride = 2;
-    > {{alias}}( N, x, stride )
+    > {{alias}}( 3, x, 2 )
     -2.0
 
     // Using view offsets:
     > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );
     > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );
-    > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );
-    > stride = 2;
-    > {{alias}}( N, x1, stride )
+    > {{alias}}( 3, x1, 2 )
     -2.0
 
-{{alias}}.ndarray( N, x, stride, offset )
+
+{{alias}}.ndarray( N, x, strideX, offsetX )
     Computes the minimum value of a sorted double-precision floating-point
     strided array using alternative indexing semantics.
 
@@ -68,10 +65,10 @@
     x: Float64Array
         Sorted input array.
 
-    stride: integer
-        Index increment.
+    strideX: integer
+        Stride Length.
 
-    offset: integer
+    offsetX: integer
         Starting index.
 
     Returns
@@ -88,8 +85,7 @@
 
     // Using offset parameter:
     > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > {{alias}}.ndarray( N, x, 2, 1 )
+    > {{alias}}.ndarray( 3, x, 2, 1 )
     -2.0
 
     See Also
diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dminsorted/docs/types/index.d.ts
index 509a175c89aa..dc1fc8470079 100644
--- a/lib/node_modules/@stdlib/stats/base/dminsorted/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dminsorted/docs/types/index.d.ts
@@ -27,7 +27,7 @@ interface Routine {
 	*
 	* @param N - number of indexed elements
 	* @param x - sorted input array
-	* @param stride - stride length
+	* @param strideX - stride length
 	* @returns minimum value
 	*
 	* @example
@@ -38,15 +38,15 @@ interface Routine {
 	* var v = dminsorted( x.length, x, 1 );
 	* // returns 1.0
 	*/
-	( N: number, x: Float64Array, stride: number ): number;
+	( N: number, x: Float64Array, strideX: number ): number;
 
 	/**
 	* Computes the minimum value of a sorted double-precision floating-point strided array using alternative indexing semantics.
 	*
 	* @param N - number of indexed elements
 	* @param x - sorted input array
-	* @param stride - stride length
-	* @param offset - starting index
+	* @param strideX - stride length
+	* @param offsetX - starting index
 	* @returns minimum value
 	*
 	* @example
@@ -57,7 +57,7 @@ interface Routine {
 	* var v = dminsorted.ndarray( x.length, x, 1, 0 );
 	* // returns 1.0
 	*/
-	ndarray( N: number, x: Float64Array, stride: number, offset: number ): number;
+	ndarray( N: number, x: Float64Array, strideX: number, offsetX: number ): number;
 }
 
 /**
@@ -65,7 +65,7 @@ interface Routine {
 *
 * @param N - number of indexed elements
 * @param x - sorted input array
-* @param stride - stride length
+* @param strideX - stride length
 * @returns minimum value
 *
 * @example
diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dminsorted/examples/c/example.c
index 2673519870b3..0e5c657e2864 100644
--- a/lib/node_modules/@stdlib/stats/base/dminsorted/examples/c/example.c
+++ b/lib/node_modules/@stdlib/stats/base/dminsorted/examples/c/example.c
@@ -17,21 +17,20 @@
 */
 
 #include "stdlib/stats/base/dminsorted.h"
-#include <stdint.h>
 #include <stdio.h>
 
 int main( void ) {
 	// Create a strided array:
-	double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 };
+	const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 };
 
 	// Specify the number of elements:
-	int64_t N = 4;
+	const int N = 4;
 
 	// Specify the stride length:
-	int64_t stride = 2;
+	const int strideX = 2;
 
 	// Compute the minimum value:
-	double v = stdlib_strided_dminsorted( N, x, stride );
+	double v = stdlib_strided_dminsorted( N, x, strideX );
 
 	// Print the result:
 	printf( "min: %lf\n", v );
diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/examples/index.js b/lib/node_modules/@stdlib/stats/base/dminsorted/examples/index.js
index c4a9be487cce..7acfb4f24877 100644
--- a/lib/node_modules/@stdlib/stats/base/dminsorted/examples/index.js
+++ b/lib/node_modules/@stdlib/stats/base/dminsorted/examples/index.js
@@ -18,16 +18,13 @@
 
 'use strict';
 
-var Float64Array = require( '@stdlib/array/float64' );
+var linspace = require( '@stdlib/array/linspace' );
 var dminsorted = require( './../lib' );
 
-var x;
-var i;
-
-x = new Float64Array( 10 );
-for ( i = 0; i < x.length; i++ ) {
-	x[ i ] = i - 5.0;
-}
+var options = {
+	'dtype': 'float64'
+};
+var x = linspace( -5.0, 5.0, 10, options );
 console.log( x );
 
 var v = dminsorted( x.length, x, 1 );
diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/include.gypi b/lib/node_modules/@stdlib/stats/base/dminsorted/include.gypi
index 868c5c12e852..26476a8c2655 100644
--- a/lib/node_modules/@stdlib/stats/base/dminsorted/include.gypi
+++ b/lib/node_modules/@stdlib/stats/base/dminsorted/include.gypi
@@ -36,7 +36,7 @@
 
     # Source files:
     'src_files': [
-      '<(src_dir)/addon.cpp',
+      '<(src_dir)/addon.c',
       '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).src; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
     ],
 
diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/include/stdlib/stats/base/dminsorted.h b/lib/node_modules/@stdlib/stats/base/dminsorted/include/stdlib/stats/base/dminsorted.h
index 2825e2f1eb08..e980cad74071 100644
--- a/lib/node_modules/@stdlib/stats/base/dminsorted/include/stdlib/stats/base/dminsorted.h
+++ b/lib/node_modules/@stdlib/stats/base/dminsorted/include/stdlib/stats/base/dminsorted.h
@@ -19,7 +19,7 @@
 #ifndef STDLIB_STATS_BASE_DMINSORTED_H
 #define STDLIB_STATS_BASE_DMINSORTED_H
 
-#include <stdint.h>
+#include "stdlib/blas/base/shared.h"
 
 /*
 * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler.
@@ -31,7 +31,12 @@ extern "C" {
 /**
 * Computes the minimum value of a sorted double-precision floating-point strided array.
 */
-double stdlib_strided_dminsorted( const int64_t N, const double *X, const int64_t stride );
+double API_SUFFIX(stdlib_strided_dminsorted)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX );
+
+/**
+* Computes the minimum value of a sorted double-precision floating-point strided array using alternative indexing semantics.
+*/
+double API_SUFFIX(stdlib_strided_dminsorted_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX );
 
 #ifdef __cplusplus
 }
diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/lib/dminsorted.js b/lib/node_modules/@stdlib/stats/base/dminsorted/lib/dminsorted.js
index b3e5d95f53fe..9d4deae34b6c 100644
--- a/lib/node_modules/@stdlib/stats/base/dminsorted/lib/dminsorted.js
+++ b/lib/node_modules/@stdlib/stats/base/dminsorted/lib/dminsorted.js
@@ -20,8 +20,8 @@
 
 // MODULES //
 
-var isnan = require( '@stdlib/math/base/assert/is-nan' );
-var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' );
+var stride2offset = require( '@stdlib/strided/base/stride2offset' );
+var ndarray = require( './ndarray.js' );
 
 
 // MAIN //
@@ -31,48 +31,19 @@ var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' );
 *
 * @param {PositiveInteger} N - number of indexed elements
 * @param {Float64Array} x - sorted input array
-* @param {integer} stride - stride length
+* @param {integer} strideX - stride length
 * @returns {number} minimum value
 *
 * @example
 * var Float64Array = require( '@stdlib/array/float64' );
 *
 * var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );
-* var N = x.length;
 *
-* var v = dminsorted( N, x, 1 );
+* var v = dminsorted( x.length, x, 1 );
 * // returns 1.0
 */
-function dminsorted( N, x, stride ) {
-	var v1;
-	var v2;
-
-	if ( N <= 0 ) {
-		return NaN;
-	}
-	if ( N === 1 || stride === 0 ) {
-		return x[ 0 ];
-	}
-	if ( stride < 0 ) {
-		v1 = x[ (1-N) * stride ];
-		v2 = x[ 0 ];
-	} else {
-		v1 = x[ 0 ];
-		v2 = x[ (N-1) * stride ];
-	}
-	if ( isnan( v1 ) || isnan( v2 ) ) {
-		return NaN;
-	}
-	if ( v1 === v2 ) {
-		if ( isNegativeZero( v1 ) || isNegativeZero( v2 ) ) {
-			return -0.0;
-		}
-		return v1;
-	}
-	if ( v1 < v2 ) {
-		return v1;
-	}
-	return v2;
+function dminsorted( N, x, strideX ) {
+	return ndarray( N, x, strideX, stride2offset( N, strideX ) );
 }
 
 
diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/lib/dminsorted.native.js b/lib/node_modules/@stdlib/stats/base/dminsorted/lib/dminsorted.native.js
index 058184aa2c07..514252613c15 100644
--- a/lib/node_modules/@stdlib/stats/base/dminsorted/lib/dminsorted.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dminsorted/lib/dminsorted.native.js
@@ -30,20 +30,19 @@ var addon = require( './../src/addon.node' );
 *
 * @param {PositiveInteger} N - number of indexed elements
 * @param {Float64Array} x - sorted input array
-* @param {integer} stride - stride length
+* @param {integer} strideX - stride length
 * @returns {number} minimum value
 *
 * @example
 * var Float64Array = require( '@stdlib/array/float64' );
 *
 * var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );
-* var N = x.length;
 *
-* var v = dminsorted( N, x, 1 );
+* var v = dminsorted( x.length, x, 1 );
 * // returns 1.0
 */
-function dminsorted( N, x, stride ) {
-	return addon( N, x, stride );
+function dminsorted( N, x, strideX ) {
+	return addon( N, x, strideX );
 }
 
 
diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/lib/index.js b/lib/node_modules/@stdlib/stats/base/dminsorted/lib/index.js
index 4f5a123bf49e..49d6559c2f25 100644
--- a/lib/node_modules/@stdlib/stats/base/dminsorted/lib/index.js
+++ b/lib/node_modules/@stdlib/stats/base/dminsorted/lib/index.js
@@ -28,20 +28,17 @@
 * var dminsorted = require( '@stdlib/stats/base/dminsorted' );
 *
 * var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );
-* var N = x.length;
 *
-* var v = dminsorted( N, x, 1 );
+* var v = dminsorted( x.length, x, 1 );
 * // returns 1.0
 *
 * @example
 * var Float64Array = require( '@stdlib/array/float64' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 * var dminsorted = require( '@stdlib/stats/base/dminsorted' );
 *
 * var x = new Float64Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
-* var N = floor( x.length / 2 );
 *
-* var v = dminsorted.ndarray( N, x, 2, 1 );
+* var v = dminsorted.ndarray( 4, x, 2, 1 );
 * // returns -3.0
 */
 
diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/dminsorted/lib/ndarray.js
index 65427fab99ea..7f6d85781721 100644
--- a/lib/node_modules/@stdlib/stats/base/dminsorted/lib/ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/dminsorted/lib/ndarray.js
@@ -31,32 +31,30 @@ var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' );
 *
 * @param {PositiveInteger} N - number of indexed elements
 * @param {Float64Array} x - sorted input array
-* @param {integer} stride - stride length
-* @param {NonNegativeInteger} offset - starting index
+* @param {integer} strideX - stride length
+* @param {NonNegativeInteger} offsetX - starting index
 * @returns {number} minimum value
 *
 * @example
 * var Float64Array = require( '@stdlib/array/float64' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 *
 * var x = new Float64Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
-* var N = floor( x.length / 2 );
 *
-* var v = dminsorted( N, x, 2, 1 );
+* var v = dminsorted( 4, x, 2, 1 );
 * // returns -3.0
 */
-function dminsorted( N, x, stride, offset ) {
+function dminsorted( N, x, strideX, offsetX ) {
 	var v1;
 	var v2;
 
 	if ( N <= 0 ) {
 		return NaN;
 	}
-	if ( N === 1 || stride === 0 ) {
+	if ( N === 1 || strideX === 0 ) {
 		return x[ 0 ];
 	}
-	v1 = x[ offset ];
-	v2 = x[ offset + ((N-1)*stride) ];
+	v1 = x[ offsetX ];
+	v2 = x[ offsetX + ((N-1)*strideX) ];
 	if ( isnan( v1 ) || isnan( v2 ) ) {
 		return NaN;
 	}
diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dminsorted/lib/ndarray.native.js
index 2503636150dc..2e898ee3cdbe 100644
--- a/lib/node_modules/@stdlib/stats/base/dminsorted/lib/ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dminsorted/lib/ndarray.native.js
@@ -20,8 +20,7 @@
 
 // MODULES //
 
-var Float64Array = require( '@stdlib/array/float64' );
-var addon = require( './dminsorted.native.js' );
+var addon = require( './../src/addon.node' );
 
 
 // MAIN //
@@ -31,27 +30,20 @@ var addon = require( './dminsorted.native.js' );
 *
 * @param {PositiveInteger} N - number of indexed elements
 * @param {Float64Array} x - sorted input array
-* @param {integer} stride - stride length
-* @param {NonNegativeInteger} offset - starting index
+* @param {integer} strideX - stride length
+* @param {NonNegativeInteger} offsetX - starting index
 * @returns {number} minimum value
 *
 * @example
 * var Float64Array = require( '@stdlib/array/float64' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 *
 * var x = new Float64Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
-* var N = floor( x.length / 2 );
 *
-* var v = dminsorted( N, x, 2, 1 );
+* var v = dminsorted( 4, x, 2, 1 );
 * // returns -3.0
 */
-function dminsorted( N, x, stride, offset ) {
-	var view;
-	if ( stride < 0 ) {
-		offset += (N-1) * stride;
-	}
-	view = new Float64Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len
-	return addon( N, view, stride );
+function dminsorted( N, x, strideX, offsetX ) {
+	return addon.ndarray( N, x, strideX, offsetX );
 }
 
 
diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/manifest.json b/lib/node_modules/@stdlib/stats/base/dminsorted/manifest.json
index 4e090b2f2400..badf40fc022a 100644
--- a/lib/node_modules/@stdlib/stats/base/dminsorted/manifest.json
+++ b/lib/node_modules/@stdlib/stats/base/dminsorted/manifest.json
@@ -1,5 +1,8 @@
 {
-  "options": {},
+  "options": {
+    "task": "build",
+    "wasm": false
+  },
   "fields": [
     {
       "field": "src",
@@ -24,19 +27,80 @@
   ],
   "confs": [
     {
+      "task": "build",
+      "wasm": false,
       "src": [
-        "./src/dminsorted.c"
+        "./src/main.c"
       ],
       "include": [
         "./include"
       ],
-      "libraries": [
-        "-lm"
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/math/base/assert/is-nan",
+        "@stdlib/math/base/assert/is-negative-zero",
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset",
+        "@stdlib/napi/export",
+        "@stdlib/napi/argv",
+        "@stdlib/napi/argv-int64",
+        "@stdlib/napi/argv-strided-float64array",
+        "@stdlib/napi/create-double"
+      ]
+    },
+    {
+      "task": "benchmark",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/math/base/assert/is-nan",
+        "@stdlib/math/base/assert/is-negative-zero",
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset"
+      ]
+    },
+    {
+      "task": "examples",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/math/base/assert/is-nan",
+        "@stdlib/math/base/assert/is-negative-zero",
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset"
+      ]
+    },
+    {
+      "task": "",
+      "wasm": true,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
       ],
+      "libraries": [],
       "libpath": [],
       "dependencies": [
         "@stdlib/math/base/assert/is-nan",
-        "@stdlib/math/base/assert/is-negative-zero"
+        "@stdlib/math/base/assert/is-negative-zero",
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset"
       ]
     }
   ]
diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/src/addon.c b/lib/node_modules/@stdlib/stats/base/dminsorted/src/addon.c
new file mode 100644
index 000000000000..7d845a2f0f0e
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dminsorted/src/addon.c
@@ -0,0 +1,60 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/dminsorted.h"
+#include "stdlib/napi/export.h"
+#include "stdlib/napi/argv.h"
+#include "stdlib/napi/argv_int64.h"
+#include "stdlib/napi/argv_strided_float64array.h"
+#include "stdlib/napi/create_double.h"
+#include <node_api.h>
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 3 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dminsorted( N, X, strideX ), v );
+	return v;
+}
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon_method( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 4 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 );
+	STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dminsorted_ndarray( N, X, strideX, offsetX ), v );
+	return v;
+}
+
+STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method )
diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/dminsorted/src/addon.cpp
deleted file mode 100644
index 756f45cb695e..000000000000
--- a/lib/node_modules/@stdlib/stats/base/dminsorted/src/addon.cpp
+++ /dev/null
@@ -1,117 +0,0 @@
-/**
-* @license Apache-2.0
-*
-* Copyright (c) 2020 The Stdlib Authors.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-*    http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-
-#include "stdlib/stats/base/dminsorted.h"
-#include <node_api.h>
-#include <stdint.h>
-#include <stdlib.h>
-#include <stdbool.h>
-#include <assert.h>
-
-/**
-* Add-on namespace.
-*/
-namespace stdlib_stats_base_dminsorted {
-
-	/**
-	* Computes the minimum value of a sorted double-precision floating-point strided array.
-	*
-	* ## Notes
-	*
-	* -   When called from JavaScript, the function expects three arguments:
-	*
-	*     -   `N`: number of indexed elements
-	*     -   `X`: sorted input array
-	*     -   `stride`: stride length
-	*/
-	napi_value node_dminsorted( napi_env env, napi_callback_info info ) {
-		napi_status status;
-
-		size_t argc = 3;
-		napi_value argv[ 3 ];
-		status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr );
-		assert( status == napi_ok );
-
-		if ( argc < 3 ) {
-			napi_throw_error( env, nullptr, "invalid invocation. Must provide 3 arguments." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype0;
-		status = napi_typeof( env, argv[ 0 ], &vtype0 );
-		assert( status == napi_ok );
-		if ( vtype0 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." );
-			return nullptr;
-		}
-
-		bool res;
-		status = napi_is_typedarray( env, argv[ 1 ], &res );
-		assert( status == napi_ok );
-		if ( res == false ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float64Array." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype2;
-		status = napi_typeof( env, argv[ 2 ], &vtype2 );
-		assert( status == napi_ok );
-		if ( vtype2 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." );
-			return nullptr;
-		}
-
-		int64_t N;
-		status = napi_get_value_int64( env, argv[ 0 ], &N );
-		assert( status == napi_ok );
-
-		int64_t stride;
-		status = napi_get_value_int64( env, argv[ 2 ], &stride );
-		assert( status == napi_ok );
-
-		napi_typedarray_type vtype1;
-		size_t xlen;
-		void *X;
-		status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr );
-		assert( status == napi_ok );
-		if ( vtype1 != napi_float64_array ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float64Array." );
-			return nullptr;
-		}
-		if ( (N-1)*llabs(stride) >= (int64_t)xlen ) {
-			napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." );
-			return nullptr;
-		}
-
-		napi_value v;
-		status = napi_create_double( env, stdlib_strided_dminsorted( N, (double *)X, stride ), &v );
-		assert( status == napi_ok );
-
-		return v;
-	}
-
-	napi_value Init( napi_env env, napi_value exports ) {
-		napi_status status;
-		napi_value fcn;
-		status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_dminsorted, NULL, &fcn );
-		assert( status == napi_ok );
-		return fcn;
-	}
-
-	NAPI_MODULE( NODE_GYP_MODULE_NAME, Init )
-} // end namespace stdlib_stats_base_dminsorted
diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/src/dminsorted.c b/lib/node_modules/@stdlib/stats/base/dminsorted/src/main.c
similarity index 54%
rename from lib/node_modules/@stdlib/stats/base/dminsorted/src/dminsorted.c
rename to lib/node_modules/@stdlib/stats/base/dminsorted/src/main.c
index 36161f0d450c..08a046f60271 100644
--- a/lib/node_modules/@stdlib/stats/base/dminsorted/src/dminsorted.c
+++ b/lib/node_modules/@stdlib/stats/base/dminsorted/src/main.c
@@ -19,33 +19,43 @@
 #include "stdlib/stats/base/dminsorted.h"
 #include "stdlib/math/base/assert/is_nan.h"
 #include "stdlib/math/base/assert/is_negative_zero.h"
-#include <stdint.h>
+#include "stdlib/blas/base/shared.h"
+#include "stdlib/strided/base/stride2offset.h"
 
 /**
 * Computes the minimum value of a sorted double-precision floating-point strided array.
 *
-* @param N       number of indexed elements
-* @param X       sorted input array
-* @param stride  stride length
-* @return        output value
+* @param N        number of indexed elements
+* @param X        sorted input array
+* @param strideX  stride length
+* @return         output value
 */
-double stdlib_strided_dminsorted( const int64_t N, const double *X, const int64_t stride ) {
+double API_SUFFIX(stdlib_strided_dminsorted)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ) {
+	const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX );
+	return API_SUFFIX(stdlib_strided_dminsorted_ndarray)( N, X, strideX, ox );
+}
+
+/**
+* Computes the minimum value of a sorted double-precision floating-point strided array using alternative indexing semantics.
+*
+* @param N        number of indexed elements
+* @param X        sorted input array
+* @param strideX  stride length
+* @param offsetX  starting index for X
+* @return         output value
+*/
+double API_SUFFIX(stdlib_strided_dminsorted_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) {
 	double v1;
 	double v2;
 
 	if ( N <= 0 ) {
 		return 0.0 / 0.0; // NaN
 	}
-	if ( N == 1 || stride == 0 ) {
+	if ( N == 1 || strideX == 0 ) {
 		return X[ 0 ];
 	}
-	if ( stride < 0 ) {
-		v1 = X[ (1-N) * stride ];
-		v2 = X[ 0 ];
-	} else {
-		v1 = X[ 0 ];
-		v2 = X[ (N-1) * stride ];
-	}
+	v1 = X[ offsetX ];
+	v2 = X[ ( (N-1)*strideX ) + offsetX ];
 	if ( stdlib_base_is_nan( v1 ) || stdlib_base_is_nan( v2 ) ) {
 		return 0.0 / 0.0; // NaN
 	}
diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/test/test.dminsorted.js b/lib/node_modules/@stdlib/stats/base/dminsorted/test/test.dminsorted.js
index 3eda0ff9c531..1232989ca5d3 100644
--- a/lib/node_modules/@stdlib/stats/base/dminsorted/test/test.dminsorted.js
+++ b/lib/node_modules/@stdlib/stats/base/dminsorted/test/test.dminsorted.js
@@ -21,7 +21,6 @@
 // MODULES //
 
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' );
 var Float64Array = require( '@stdlib/array/float64' );
@@ -116,7 +115,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 });
 
 tape( 'the function supports a `stride` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -131,15 +129,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) {
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = dminsorted( N, x, 2 );
+	v = dminsorted( 3, x, 2 );
 
 	t.strictEqual( v, 1.0, 'returns expected value' );
 	t.end();
 });
 
 tape( 'the function supports a negative `stride` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -154,8 +150,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t )
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = dminsorted( N, x, -2 );
+	v = dminsorted( 4, x, -2 );
 
 	t.strictEqual( v, 1.0, 'returns expected value' );
 	t.end();
@@ -176,7 +171,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f
 tape( 'the function supports view offsets', function test( t ) {
 	var x0;
 	var x1;
-	var N;
 	var v;
 
 	x0 = new Float64Array([
@@ -192,9 +186,8 @@ tape( 'the function supports view offsets', function test( t ) {
 	]);
 
 	x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
-	N = floor(x1.length / 2);
 
-	v = dminsorted( N, x1, 2 );
+	v = dminsorted( 4, x1, 2 );
 	t.strictEqual( v, 1.0, 'returns expected value' );
 
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/test/test.dminsorted.native.js b/lib/node_modules/@stdlib/stats/base/dminsorted/test/test.dminsorted.native.js
index 9388005816c1..022906bbf870 100644
--- a/lib/node_modules/@stdlib/stats/base/dminsorted/test/test.dminsorted.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dminsorted/test/test.dminsorted.native.js
@@ -22,7 +22,6 @@
 
 var resolve = require( 'path' ).resolve;
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' );
 var Float64Array = require( '@stdlib/array/float64' );
@@ -125,7 +124,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 });
 
 tape( 'the function supports a `stride` parameter', opts, function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -140,15 +138,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) {
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = dminsorted( N, x, 2 );
+	v = dminsorted( 4, x, 2 );
 
 	t.strictEqual( v, 1.0, 'returns expected value' );
 	t.end();
 });
 
 tape( 'the function supports a negative `stride` parameter', opts, function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -163,8 +159,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = dminsorted( N, x, -2 );
+	v = dminsorted( 4, x, -2 );
 
 	t.strictEqual( v, 1.0, 'returns expected value' );
 	t.end();
@@ -185,7 +180,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f
 tape( 'the function supports view offsets', opts, function test( t ) {
 	var x0;
 	var x1;
-	var N;
 	var v;
 
 	x0 = new Float64Array([
@@ -201,9 +195,8 @@ tape( 'the function supports view offsets', opts, function test( t ) {
 	]);
 
 	x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
-	N = floor(x1.length / 2);
 
-	v = dminsorted( N, x1, 2 );
+	v = dminsorted( 4, x1, 2 );
 	t.strictEqual( v, 1.0, 'returns expected value' );
 
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dminsorted/test/test.ndarray.js
index ea49cf494c20..7d289d3f98a5 100644
--- a/lib/node_modules/@stdlib/stats/base/dminsorted/test/test.ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/dminsorted/test/test.ndarray.js
@@ -21,7 +21,6 @@
 // MODULES //
 
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' );
 var Float64Array = require( '@stdlib/array/float64' );
@@ -116,7 +115,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 });
 
 tape( 'the function supports a `stride` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -131,15 +129,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) {
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = dminsorted( N, x, 2, 0 );
+	v = dminsorted( 4, x, 2, 0 );
 
 	t.strictEqual( v, 1.0, 'returns expected value' );
 	t.end();
 });
 
 tape( 'the function supports a negative `stride` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -154,8 +150,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t )
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = dminsorted( N, x, -2, 6 );
+	v = dminsorted( 4, x, -2, 6 );
 
 	t.strictEqual( v, 1.0, 'returns expected value' );
 	t.end();
@@ -174,7 +169,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f
 });
 
 tape( 'the function supports an `offset` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -188,9 +182,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) {
 		3.0,
 		4.0   // 3
 	]);
-	N = floor( x.length / 2 );
 
-	v = dminsorted( N, x, 2, 1 );
+	v = dminsorted( 4, x, 2, 1 );
 	t.strictEqual( v, 1.0, 'returns expected value' );
 
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/dminsorted/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dminsorted/test/test.ndarray.native.js
index 5dc9eb0b6d7c..01bfaffeaa52 100644
--- a/lib/node_modules/@stdlib/stats/base/dminsorted/test/test.ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dminsorted/test/test.ndarray.native.js
@@ -22,7 +22,6 @@
 
 var resolve = require( 'path' ).resolve;
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' );
 var Float64Array = require( '@stdlib/array/float64' );
@@ -125,7 +124,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 });
 
 tape( 'the function supports a `stride` parameter', opts, function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -140,15 +138,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) {
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = dminsorted( N, x, 2, 0 );
+	v = dminsorted( 4, x, 2, 0 );
 
 	t.strictEqual( v, 1.0, 'returns expected value' );
 	t.end();
 });
 
 tape( 'the function supports a negative `stride` parameter', opts, function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -163,8 +159,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = dminsorted( N, x, -2, 6 );
+	v = dminsorted( 4, x, -2, 6 );
 
 	t.strictEqual( v, 1.0, 'returns expected value' );
 	t.end();
@@ -183,7 +178,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f
 });
 
 tape( 'the function supports an `offset` parameter', opts, function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -197,9 +191,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) {
 		3.0,
 		4.0   // 3
 	]);
-	N = floor( x.length / 2 );
 
-	v = dminsorted( N, x, 2, 1 );
+	v = dminsorted( 4, x, 2, 1 );
 	t.strictEqual( v, 1.0, 'returns expected value' );
 
 	t.end();

From adfad158bb08f220fc104eaefb40060b01feb702 Mon Sep 17 00:00:00 2001
From: Vivek maurya <155618190+vivekmaurya001@users.noreply.github.com>
Date: Fri, 3 Jan 2025 01:26:40 +0530
Subject: [PATCH 16/87] refactor: update `stats/base/sdsnanmeanors` native
 addon from C++ to C

PR-URL: https://github.com/stdlib-js/stdlib/pull/4459
Reviewed-by: Athan Reines <kgryte@gmail.com>
---
 .../stats/base/sdsnanmeanors/include.gypi     |   2 +-
 .../stats/base/sdsnanmeanors/manifest.json    |  39 +++++-
 .../stats/base/sdsnanmeanors/src/addon.c      |  43 +++++++
 .../stats/base/sdsnanmeanors/src/addon.cpp    | 117 ------------------
 4 files changed, 82 insertions(+), 119 deletions(-)
 create mode 100644 lib/node_modules/@stdlib/stats/base/sdsnanmeanors/src/addon.c
 delete mode 100644 lib/node_modules/@stdlib/stats/base/sdsnanmeanors/src/addon.cpp

diff --git a/lib/node_modules/@stdlib/stats/base/sdsnanmeanors/include.gypi b/lib/node_modules/@stdlib/stats/base/sdsnanmeanors/include.gypi
index 868c5c12e852..26476a8c2655 100644
--- a/lib/node_modules/@stdlib/stats/base/sdsnanmeanors/include.gypi
+++ b/lib/node_modules/@stdlib/stats/base/sdsnanmeanors/include.gypi
@@ -36,7 +36,7 @@
 
     # Source files:
     'src_files': [
-      '<(src_dir)/addon.cpp',
+      '<(src_dir)/addon.c',
       '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).src; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
     ],
 
diff --git a/lib/node_modules/@stdlib/stats/base/sdsnanmeanors/manifest.json b/lib/node_modules/@stdlib/stats/base/sdsnanmeanors/manifest.json
index 8a3d9b97a92d..353bd0d20dcd 100644
--- a/lib/node_modules/@stdlib/stats/base/sdsnanmeanors/manifest.json
+++ b/lib/node_modules/@stdlib/stats/base/sdsnanmeanors/manifest.json
@@ -1,5 +1,7 @@
 {
-  "options": {},
+  "options": {
+    "task": "build"
+  },
   "fields": [
     {
       "field": "src",
@@ -24,6 +26,41 @@
   ],
   "confs": [
     {
+      "task": "build",
+      "src": [
+        "./src/sdsnanmeanors.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [
+        "-lm"
+      ],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/napi/export",
+        "@stdlib/napi/argv",
+        "@stdlib/napi/argv-int64",
+        "@stdlib/napi/argv-strided-float32array",
+        "@stdlib/napi/create-double"
+      ]
+    },
+    {
+      "task": "benchmark",
+      "src": [
+        "./src/sdsnanmeanors.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [
+        "-lm"
+      ],
+      "libpath": [],
+      "dependencies": []
+    },
+    {
+      "task": "examples",
       "src": [
         "./src/sdsnanmeanors.c"
       ],
diff --git a/lib/node_modules/@stdlib/stats/base/sdsnanmeanors/src/addon.c b/lib/node_modules/@stdlib/stats/base/sdsnanmeanors/src/addon.c
new file mode 100644
index 000000000000..9b405aaf85d8
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/sdsnanmeanors/src/addon.c
@@ -0,0 +1,43 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/sdsnanmeanors.h"
+#include "stdlib/napi/export.h"
+#include "stdlib/napi/argv.h"
+#include "stdlib/napi/argv_int64.h"
+#include "stdlib/napi/argv_strided_float32array.h"
+#include "stdlib/napi/create_double.h"
+#include <node_api.h>
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 3 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_INT64( env, stride, argv, 2 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 1 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_sdsnanmeanors( N, X, stride ), v );
+	return v;
+}
+
+STDLIB_NAPI_MODULE_EXPORT_FCN( addon )
diff --git a/lib/node_modules/@stdlib/stats/base/sdsnanmeanors/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/sdsnanmeanors/src/addon.cpp
deleted file mode 100644
index e0608f28d7dd..000000000000
--- a/lib/node_modules/@stdlib/stats/base/sdsnanmeanors/src/addon.cpp
+++ /dev/null
@@ -1,117 +0,0 @@
-/**
-* @license Apache-2.0
-*
-* Copyright (c) 2020 The Stdlib Authors.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-*    http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-
-#include "stdlib/stats/base/sdsnanmeanors.h"
-#include <node_api.h>
-#include <stdint.h>
-#include <stdlib.h>
-#include <stdbool.h>
-#include <assert.h>
-
-/**
-* Add-on namespace.
-*/
-namespace stdlib_stats_base_sdsnanmeanors {
-
-	/**
-	* Computes the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values and using ordinary recursive summation with extended accumulation.
-	*
-	* ## Notes
-	*
-	* -   When called from JavaScript, the function expects three arguments:
-	*
-	*     -   `N`: number of indexed elements
-	*     -   `X`: input array
-	*     -   `stride`: stride length
-	*/
-	napi_value node_sdsnanmeanors( napi_env env, napi_callback_info info ) {
-		napi_status status;
-
-		size_t argc = 3;
-		napi_value argv[ 3 ];
-		status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr );
-		assert( status == napi_ok );
-
-		if ( argc < 3 ) {
-			napi_throw_error( env, nullptr, "invalid invocation. Must provide 3 arguments." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype0;
-		status = napi_typeof( env, argv[ 0 ], &vtype0 );
-		assert( status == napi_ok );
-		if ( vtype0 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." );
-			return nullptr;
-		}
-
-		bool res;
-		status = napi_is_typedarray( env, argv[ 1 ], &res );
-		assert( status == napi_ok );
-		if ( res == false ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype2;
-		status = napi_typeof( env, argv[ 2 ], &vtype2 );
-		assert( status == napi_ok );
-		if ( vtype2 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." );
-			return nullptr;
-		}
-
-		int64_t N;
-		status = napi_get_value_int64( env, argv[ 0 ], &N );
-		assert( status == napi_ok );
-
-		int64_t stride;
-		status = napi_get_value_int64( env, argv[ 2 ], &stride );
-		assert( status == napi_ok );
-
-		napi_typedarray_type vtype1;
-		size_t xlen;
-		void *X;
-		status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr );
-		assert( status == napi_ok );
-		if ( vtype1 != napi_float32_array ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." );
-			return nullptr;
-		}
-		if ( (N-1)*llabs(stride) >= (int64_t)xlen ) {
-			napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." );
-			return nullptr;
-		}
-
-		napi_value v;
-		status = napi_create_double( env, (double)stdlib_strided_sdsnanmeanors( N, (float *)X, stride ), &v );
-		assert( status == napi_ok );
-
-		return v;
-	}
-
-	napi_value Init( napi_env env, napi_value exports ) {
-		napi_status status;
-		napi_value fcn;
-		status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_sdsnanmeanors, NULL, &fcn );
-		assert( status == napi_ok );
-		return fcn;
-	}
-
-	NAPI_MODULE( NODE_GYP_MODULE_NAME, Init )
-} // end namespace stdlib_stats_base_sdsnanmeanors

From 858583d337a28fc2e7f2e195c12f00fb119bb8e1 Mon Sep 17 00:00:00 2001
From: Vivek maurya <155618190+vivekmaurya001@users.noreply.github.com>
Date: Fri, 3 Jan 2025 01:27:48 +0530
Subject: [PATCH 17/87] refactor: update `stats/base/sdsnanmean` native addon
 from C++ to C

PR-URL: https://github.com/stdlib-js/stdlib/pull/4458
Reviewed-by: Athan Reines <kgryte@gmail.com>
---
 .../stats/base/sdsnanmean/include.gypi        |   2 +-
 .../stats/base/sdsnanmean/manifest.json       |  42 ++++++-
 .../@stdlib/stats/base/sdsnanmean/src/addon.c |  43 +++++++
 .../stats/base/sdsnanmean/src/addon.cpp       | 117 ------------------
 4 files changed, 85 insertions(+), 119 deletions(-)
 create mode 100644 lib/node_modules/@stdlib/stats/base/sdsnanmean/src/addon.c
 delete mode 100644 lib/node_modules/@stdlib/stats/base/sdsnanmean/src/addon.cpp

diff --git a/lib/node_modules/@stdlib/stats/base/sdsnanmean/include.gypi b/lib/node_modules/@stdlib/stats/base/sdsnanmean/include.gypi
index 868c5c12e852..26476a8c2655 100644
--- a/lib/node_modules/@stdlib/stats/base/sdsnanmean/include.gypi
+++ b/lib/node_modules/@stdlib/stats/base/sdsnanmean/include.gypi
@@ -36,7 +36,7 @@
 
     # Source files:
     'src_files': [
-      '<(src_dir)/addon.cpp',
+      '<(src_dir)/addon.c',
       '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).src; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
     ],
 
diff --git a/lib/node_modules/@stdlib/stats/base/sdsnanmean/manifest.json b/lib/node_modules/@stdlib/stats/base/sdsnanmean/manifest.json
index 0e9d9ad25402..7f39cb74b530 100644
--- a/lib/node_modules/@stdlib/stats/base/sdsnanmean/manifest.json
+++ b/lib/node_modules/@stdlib/stats/base/sdsnanmean/manifest.json
@@ -1,5 +1,7 @@
 {
-  "options": {},
+  "options": {
+    "task": "build"
+  },
   "fields": [
     {
       "field": "src",
@@ -24,6 +26,44 @@
   ],
   "confs": [
     {
+      "task": "build",
+      "src": [
+        "./src/sdsnanmean.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [
+        "-lm"
+      ],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/stats/base/sdsnanmeanors",
+        "@stdlib/napi/export",
+        "@stdlib/napi/argv",
+        "@stdlib/napi/argv-int64",
+        "@stdlib/napi/argv-strided-float32array",
+        "@stdlib/napi/create-double"
+      ]
+    },
+    {
+      "task": "benchmark",
+      "src": [
+        "./src/sdsnanmean.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [
+        "-lm"
+      ],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/stats/base/sdsnanmeanors"
+      ]
+    },
+    {
+      "task": "examples",
       "src": [
         "./src/sdsnanmean.c"
       ],
diff --git a/lib/node_modules/@stdlib/stats/base/sdsnanmean/src/addon.c b/lib/node_modules/@stdlib/stats/base/sdsnanmean/src/addon.c
new file mode 100644
index 000000000000..9adbd5281f76
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/sdsnanmean/src/addon.c
@@ -0,0 +1,43 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/sdsnanmean.h"
+#include "stdlib/napi/export.h"
+#include "stdlib/napi/argv.h"
+#include "stdlib/napi/argv_int64.h"
+#include "stdlib/napi/argv_strided_float32array.h"
+#include "stdlib/napi/create_double.h"
+#include <node_api.h>
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 3 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_INT64( env, stride, argv, 2 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 1 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_sdsnanmean( N, X, stride ), v );
+	return v;
+}
+
+STDLIB_NAPI_MODULE_EXPORT_FCN( addon )
diff --git a/lib/node_modules/@stdlib/stats/base/sdsnanmean/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/sdsnanmean/src/addon.cpp
deleted file mode 100644
index d4114ff4f966..000000000000
--- a/lib/node_modules/@stdlib/stats/base/sdsnanmean/src/addon.cpp
+++ /dev/null
@@ -1,117 +0,0 @@
-/**
-* @license Apache-2.0
-*
-* Copyright (c) 2020 The Stdlib Authors.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-*    http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-
-#include "stdlib/stats/base/sdsnanmean.h"
-#include <node_api.h>
-#include <stdint.h>
-#include <stdlib.h>
-#include <stdbool.h>
-#include <assert.h>
-
-/**
-* Add-on namespace.
-*/
-namespace stdlib_stats_base_sdsnanmean {
-
-	/**
-	* Computes the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values and using extended accumulation.
-	*
-	* ## Notes
-	*
-	* -   When called from JavaScript, the function expects three arguments:
-	*
-	*     -   `N`: number of indexed elements
-	*     -   `X`: input array
-	*     -   `stride`: stride length
-	*/
-	napi_value node_sdsnanmean( napi_env env, napi_callback_info info ) {
-		napi_status status;
-
-		size_t argc = 3;
-		napi_value argv[ 3 ];
-		status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr );
-		assert( status == napi_ok );
-
-		if ( argc < 3 ) {
-			napi_throw_error( env, nullptr, "invalid invocation. Must provide 3 arguments." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype0;
-		status = napi_typeof( env, argv[ 0 ], &vtype0 );
-		assert( status == napi_ok );
-		if ( vtype0 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." );
-			return nullptr;
-		}
-
-		bool res;
-		status = napi_is_typedarray( env, argv[ 1 ], &res );
-		assert( status == napi_ok );
-		if ( res == false ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype2;
-		status = napi_typeof( env, argv[ 2 ], &vtype2 );
-		assert( status == napi_ok );
-		if ( vtype2 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." );
-			return nullptr;
-		}
-
-		int64_t N;
-		status = napi_get_value_int64( env, argv[ 0 ], &N );
-		assert( status == napi_ok );
-
-		int64_t stride;
-		status = napi_get_value_int64( env, argv[ 2 ], &stride );
-		assert( status == napi_ok );
-
-		napi_typedarray_type vtype1;
-		size_t xlen;
-		void *X;
-		status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr );
-		assert( status == napi_ok );
-		if ( vtype1 != napi_float32_array ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." );
-			return nullptr;
-		}
-		if ( (N-1)*llabs(stride) >= (int64_t)xlen ) {
-			napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." );
-			return nullptr;
-		}
-
-		napi_value v;
-		status = napi_create_double( env, (double)stdlib_strided_sdsnanmean( N, (float *)X, stride ), &v );
-		assert( status == napi_ok );
-
-		return v;
-	}
-
-	napi_value Init( napi_env env, napi_value exports ) {
-		napi_status status;
-		napi_value fcn;
-		status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_sdsnanmean, NULL, &fcn );
-		assert( status == napi_ok );
-		return fcn;
-	}
-
-	NAPI_MODULE( NODE_GYP_MODULE_NAME, Init )
-} // end namespace stdlib_stats_base_sdsnanmean

From 428598347c87e7e59042f282a29ec5c4c2d830b8 Mon Sep 17 00:00:00 2001
From: Aayush Khanna <96649223+aayush0325@users.noreply.github.com>
Date: Fri, 3 Jan 2025 01:52:16 +0530
Subject: [PATCH 18/87] feat: add C ndarray interface and refactor
 implementation for `stats/base/smskmin`

PR-URL: https://github.com/stdlib-js/stdlib/pull/4403
Reviewed-by: Athan Reines <kgryte@gmail.com>
Co-authored-by: stdlib-bot <82920195+stdlib-bot@users.noreply.github.com>
---
 .../@stdlib/stats/base/smskmin/README.md      | 173 ++++++++++++++----
 .../stats/base/smskmin/benchmark/benchmark.js |  31 ++--
 .../smskmin/benchmark/benchmark.native.js     |  27 +--
 .../smskmin/benchmark/benchmark.ndarray.js    |  31 ++--
 .../benchmark/benchmark.ndarray.native.js     |  27 +--
 .../smskmin/benchmark/c/benchmark.length.c    |  56 +++++-
 .../@stdlib/stats/base/smskmin/docs/repl.txt  |  24 ++-
 .../stats/base/smskmin/examples/c/example.c   |  10 +-
 .../stats/base/smskmin/examples/index.js      |  27 +--
 .../@stdlib/stats/base/smskmin/include.gypi   |   2 +-
 .../include/stdlib/stats/base/smskmin.h       |   8 +-
 .../@stdlib/stats/base/smskmin/lib/index.js   |   4 +-
 .../@stdlib/stats/base/smskmin/lib/ndarray.js |   4 +-
 .../stats/base/smskmin/lib/ndarray.native.js  |  16 +-
 .../@stdlib/stats/base/smskmin/lib/smskmin.js |  56 +-----
 .../@stdlib/stats/base/smskmin/manifest.json  |  73 +++++++-
 .../@stdlib/stats/base/smskmin/src/addon.c    |  66 +++++++
 .../@stdlib/stats/base/smskmin/src/addon.cpp  | 153 ----------------
 .../base/smskmin/src/{smskmin.c => main.c}    |  40 ++--
 .../stats/base/smskmin/test/test.ndarray.js   |  13 +-
 .../base/smskmin/test/test.ndarray.native.js  |  15 +-
 .../stats/base/smskmin/test/test.smskmin.js   |  13 +-
 .../base/smskmin/test/test.smskmin.native.js  |  13 +-
 23 files changed, 458 insertions(+), 424 deletions(-)
 create mode 100644 lib/node_modules/@stdlib/stats/base/smskmin/src/addon.c
 delete mode 100644 lib/node_modules/@stdlib/stats/base/smskmin/src/addon.cpp
 rename lib/node_modules/@stdlib/stats/base/smskmin/src/{smskmin.c => main.c} (58%)

diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/README.md b/lib/node_modules/@stdlib/stats/base/smskmin/README.md
index 438ef08759dd..b0148329d337 100644
--- a/lib/node_modules/@stdlib/stats/base/smskmin/README.md
+++ b/lib/node_modules/@stdlib/stats/base/smskmin/README.md
@@ -38,7 +38,7 @@ var smskmin = require( '@stdlib/stats/base/smskmin' );
 
 #### smskmin( N, x, strideX, mask, strideMask )
 
-Computes the minimum value of a single-precision floating-point strided array `x` according to a `mask`.
+Computes the minimum value of a single-precision floating-point strided array according to a mask.
 
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
@@ -55,22 +55,20 @@ The function has the following parameters:
 
 -   **N**: number of indexed elements.
 -   **x**: input [`Float32Array`][@stdlib/array/float32].
--   **strideX**: index increment for `x`.
+-   **strideX**: stride length for `x`.
 -   **mask**: mask [`Uint8Array`][@stdlib/array/uint8]. If a `mask` array element is `0`, the corresponding element in `x` is considered valid and **included** in computation. If a `mask` array element is `1`, the corresponding element in `x` is considered invalid/missing and **excluded** from computation.
--   **strideMask**: index increment for `mask`.
+-   **strideMask**: stride length for `mask`.
 
-The `N` and `stride` parameters determine which elements are accessed at runtime. For example, to compute the minimum value of every other element in `x`,
+The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the minimum value of every other element in `x`,
 
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
 var Uint8Array = require( '@stdlib/array/uint8' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x = new Float32Array( [ 1.0, 2.0, 7.0, -2.0, -4.0, 3.0, -5.0, -6.0 ] );
 var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] );
-var N = floor( x.length / 2 );
 
-var v = smskmin( N, x, 2, mask, 2 );
+var v = smskmin( 4, x, 2, mask, 2 );
 // returns -4.0
 ```
 
@@ -81,7 +79,6 @@ Note that indexing is relative to the first index. To introduce offsets, use [`t
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
 var Uint8Array = require( '@stdlib/array/uint8' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x0 = new Float32Array( [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, -5.0, -6.0 ] );
 var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
@@ -89,15 +86,13 @@ var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd
 var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] );
 var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
 
-var N = floor( x0.length / 2 );
-
-var v = smskmin( N, x1, 2, mask1, 2 );
+var v = smskmin( 4, x1, 2, mask1, 2 );
 // returns -2.0
 ```
 
 #### smskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )
 
-Computes the minimum value of a single-precision floating-point strided array according to a `mask` and using alternative indexing semantics.
+Computes the minimum value of a single-precision floating-point strided array according to a mask and using alternative indexing semantics.
 
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
@@ -115,18 +110,16 @@ The function has the following additional parameters:
 -   **offsetX**: starting index for `x`.
 -   **offsetMask**: starting index for `mask`.
 
-While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the minimum value for every other value in `x` starting from the second value
+While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to calculate the minimum value for every other element in `x` starting from the second element
 
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
 var Uint8Array = require( '@stdlib/array/uint8' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x = new Float32Array( [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, -5.0, -6.0 ] );
 var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] );
-var N = floor( x.length / 2 );
 
-var v = smskmin.ndarray( N, x, 2, 1, mask, 2, 1 );
+var v = smskmin.ndarray( 4, x, 2, 1, mask, 2, 1 );
 // returns -2.0
 ```
 
@@ -151,26 +144,19 @@ var v = smskmin.ndarray( N, x, 2, 1, mask, 2, 1 );
 <!-- eslint no-undef: "error" -->
 
 ```javascript
-var randu = require( '@stdlib/random/base/randu' );
-var round = require( '@stdlib/math/base/special/round' );
-var Float32Array = require( '@stdlib/array/float32' );
-var Uint8Array = require( '@stdlib/array/uint8' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var bernoulli = require( '@stdlib/random/array/bernoulli' );
 var smskmin = require( '@stdlib/stats/base/smskmin' );
 
-var mask;
-var x;
-var i;
-
-x = new Float32Array( 10 );
-mask = new Uint8Array( x.length );
-for ( i = 0; i < x.length; i++ ) {
-    if ( randu() < 0.2 ) {
-        mask[ i ] = 1;
-    } else {
-        mask[ i ] = 0;
-    }
-    x[ i ] = round( (randu()*100.0) - 50.0 );
-}
+var uniformOptions = {
+    'dtype': 'float32'
+};
+var bernoulliOptions = {
+    'dtype': 'uint8'
+};
+
+var x = uniform( 10, -50.0, 50.0, uniformOptions );
+var mask = bernoulli( x.length, 0.2, bernoulliOptions );
 console.log( x );
 console.log( mask );
 
@@ -182,6 +168,125 @@ console.log( v );
 
 <!-- /.examples -->
 
+<!-- C usage documentation. -->
+
+<section class="usage">
+
+### Usage
+
+```c
+#include "stdlib/stats/base/smskmin.h"
+```
+
+#### stdlib_strided_smskmin( N, \*X, strideX, \*Mask, strideMask )
+
+Computes the minimum value of a single-precision floating-point strided array according to a mask.
+
+```c
+#include <stdint.h>
+
+const float x[] = { 1.0f, -2.0f, 2.0f };
+const uint8_t mask[] = { 0, 1, 0 };
+
+float v = stdlib_strided_smskmin( 3, x, 1, mask, 1 );
+// returns 1.0f
+```
+
+The function accepts the following arguments:
+
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **X**: `[in] float*` input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+-   **Mask**: `[in] uint8_t*` mask array. If a `Mask` array element is `0`, the corresponding element in `X` is considered valid and included in computation. If a `Mask` array element is `1`, the corresponding element in `X` is considered invalid/missing and excluded from computation.
+-   **strideMask**: `[in] CBLAS_INT` stride length for `Mask`.
+
+```c
+float stdlib_strided_smskmin( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const uint8_t *Mask, const CBLAS_INT strideMask );
+```
+
+<!-- lint disable maximum-heading-length -->
+
+#### stdlib_strided_smskmin_ndarray( N, \*X, strideX, offsetX, \*Mask, strideMask, offsetMask )
+
+Computes the minimum value of a single-precision floating-point strided array according to a mask and using alternative indexing semantics.
+
+```c
+#include <stdint.h>
+
+const float x[] = { 1.0f, -2.0f, 2.0f };
+const uint8_t mask[] = { 0, 1, 0 };
+
+float v = stdlib_strided_smskmin( 3, x, 1, 0, mask, 1, 0 );
+// returns 1.0f
+```
+
+The function accepts the following arguments:
+
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **X**: `[in] float*` input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+-   **offsetX**: `[in] CBLAS_INT` starting index for `X`.
+-   **Mask**: `[in] uint8_t*` mask array. If a `Mask` array element is `0`, the corresponding element in `X` is considered valid and included in computation. If a `Mask` array element is `1`, the corresponding element in `X` is considered invalid/missing and excluded from computation.
+-   **strideMask**: `[in] CBLAS_INT` stride length for `Mask`.
+-   **offsetMask**: `[in] CBLAS_INT` starting index for `Mask`.
+
+```c
+float stdlib_strided_smskmin_ndarray( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const uint8_t *Mask, const CBLAS_INT strideMask, const CBLAS_INT offsetMask );
+```
+
+</section>
+
+<!-- /.usage -->
+
+<!-- C API usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="notes">
+
+</section>
+
+<!-- /.notes -->
+
+<!-- C API usage examples. -->
+
+<section class="examples">
+
+### Examples
+
+```c
+#include "stdlib/stats/base/smskmin.h"
+#include <stdint.h>
+#include <stdio.h>
+
+int main( void ) {
+    // Create a strided array:
+    const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f };
+
+    // Create a mask array:
+    const uint8_t mask[] = { 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 };
+
+    // Specify the number of elements:
+    const int N = 5;
+
+    // Specify the stride lengths:
+    const int strideX = 2;
+    const int strideMask = 2;
+
+    // Compute the minimum value:
+    float v = stdlib_strided_smskmin( N, x, strideX, mask, strideMask );
+
+    // Print the result:
+    printf( "min: %f\n", v );
+}
+```
+
+</section>
+
+<!-- /.examples -->
+
+</section>
+
+<!-- /.c -->
+
 <!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
 
 <section class="related">
diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/smskmin/benchmark/benchmark.js
index 471c2ac0c4a9..3fafcab185f0 100644
--- a/lib/node_modules/@stdlib/stats/base/smskmin/benchmark/benchmark.js
+++ b/lib/node_modules/@stdlib/stats/base/smskmin/benchmark/benchmark.js
@@ -21,15 +21,24 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var bernoulli = require( '@stdlib/random/array/bernoulli' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float32Array = require( '@stdlib/array/float32' );
-var Uint8Array = require( '@stdlib/array/uint8' );
 var pkg = require( './../package.json' ).name;
 var smskmin = require( './../lib/smskmin.js' );
 
 
+// VARIABLES //
+
+var uniformOptions = {
+	'dtype': 'float32'
+};
+var bernoulliOptions = {
+	'dtype': 'uint8'
+};
+
+
 // FUNCTIONS //
 
 /**
@@ -40,20 +49,8 @@ var smskmin = require( './../lib/smskmin.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var mask;
-	var x;
-	var i;
-
-	x = new Float32Array( len );
-	mask = new Uint8Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		if ( randu() < 0.2 ) {
-			mask[ i ] = 1;
-		} else {
-			mask[ i ] = 0;
-		}
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
+	var mask = bernoulli( len, 0.2, bernoulliOptions );
+	var x = uniform( len, -10.0, 10.0, uniformOptions );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/smskmin/benchmark/benchmark.native.js
index e1bfc310b5c6..4867be6bec1c 100644
--- a/lib/node_modules/@stdlib/stats/base/smskmin/benchmark/benchmark.native.js
+++ b/lib/node_modules/@stdlib/stats/base/smskmin/benchmark/benchmark.native.js
@@ -22,11 +22,10 @@
 
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var bernoulli = require( '@stdlib/random/array/bernoulli' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float32Array = require( '@stdlib/array/float32' );
-var Uint8Array = require( '@stdlib/array/uint8' );
 var tryRequire = require( '@stdlib/utils/try-require' );
 var pkg = require( './../package.json' ).name;
 
@@ -37,6 +36,12 @@ var smskmin = tryRequire( resolve( __dirname, './../lib/smskmin.native.js' ) );
 var opts = {
 	'skip': ( smskmin instanceof Error )
 };
+var uniformOptions = {
+	'dtype': 'float32'
+};
+var bernoulliOptions = {
+	'dtype': 'uint8'
+};
 
 
 // FUNCTIONS //
@@ -49,20 +54,8 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var mask;
-	var x;
-	var i;
-
-	x = new Float32Array( len );
-	mask = new Uint8Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		if ( randu() < 0.2 ) {
-			mask[ i ] = 1;
-		} else {
-			mask[ i ] = 0;
-		}
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
+	var mask = bernoulli( len, 0.2, bernoulliOptions );
+	var x = uniform( len, -10.0, 10.0, uniformOptions );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/smskmin/benchmark/benchmark.ndarray.js
index c5c025a0b737..369e4216d24a 100644
--- a/lib/node_modules/@stdlib/stats/base/smskmin/benchmark/benchmark.ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/smskmin/benchmark/benchmark.ndarray.js
@@ -21,15 +21,24 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var bernoulli = require( '@stdlib/random/array/bernoulli' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float32Array = require( '@stdlib/array/float32' );
-var Uint8Array = require( '@stdlib/array/uint8' );
 var pkg = require( './../package.json' ).name;
 var smskmin = require( './../lib/ndarray.js' );
 
 
+// VARIABLES //
+
+var uniformOptions = {
+	'dtype': 'float32'
+};
+var bernoulliOptions = {
+	'dtype': 'uint8'
+};
+
+
 // FUNCTIONS //
 
 /**
@@ -40,20 +49,8 @@ var smskmin = require( './../lib/ndarray.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var mask;
-	var x;
-	var i;
-
-	x = new Float32Array( len );
-	mask = new Uint8Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		if ( randu() < 0.2 ) {
-			mask[ i ] = 1;
-		} else {
-			mask[ i ] = 0;
-		}
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
+	var mask = bernoulli( len, 0.2, bernoulliOptions );
+	var x = uniform( len, -10.0, 10.0, uniformOptions );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/smskmin/benchmark/benchmark.ndarray.native.js
index f33919372b7c..150638f7797a 100644
--- a/lib/node_modules/@stdlib/stats/base/smskmin/benchmark/benchmark.ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/smskmin/benchmark/benchmark.ndarray.native.js
@@ -22,11 +22,10 @@
 
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var bernoulli = require( '@stdlib/random/array/bernoulli' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float32Array = require( '@stdlib/array/float32' );
-var Uint8Array = require( '@stdlib/array/uint8' );
 var tryRequire = require( '@stdlib/utils/try-require' );
 var pkg = require( './../package.json' ).name;
 
@@ -37,6 +36,12 @@ var smskmin = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) );
 var opts = {
 	'skip': ( smskmin instanceof Error )
 };
+var uniformOptions = {
+	'dtype': 'float32'
+};
+var bernoulliOptions = {
+	'dtype': 'uint8'
+};
 
 
 // FUNCTIONS //
@@ -49,20 +54,8 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var mask;
-	var x;
-	var i;
-
-	x = new Float32Array( len );
-	mask = new Uint8Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		if ( randu() < 0.2 ) {
-			mask[ i ] = 1;
-		} else {
-			mask[ i ] = 0;
-		}
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
+	var mask = bernoulli( len, 0.2, bernoulliOptions );
+	var x = uniform( len, -10.0, 10.0, uniformOptions );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/smskmin/benchmark/c/benchmark.length.c
index 00ce0704edd4..7fca587720f6 100644
--- a/lib/node_modules/@stdlib/stats/base/smskmin/benchmark/c/benchmark.length.c
+++ b/lib/node_modules/@stdlib/stats/base/smskmin/benchmark/c/benchmark.length.c
@@ -94,7 +94,7 @@ static float rand_float( void ) {
 * @param len          array length
 * @return             elapsed time in seconds
 */
-static double benchmark( int iterations, int len ) {
+static double benchmark1( int iterations, int len ) {
 	unsigned char mask[ len ];
 	double elapsed;
 	float x[ len ];
@@ -113,6 +113,7 @@ static double benchmark( int iterations, int len ) {
 	v = 0.0f;
 	t = tic();
 	for ( i = 0; i < iterations; i++ ) {
+		// cppcheck-suppress uninitvar
 		v = stdlib_strided_smskmin( len, x, 1, mask, 1 );
 		if ( v != v ) {
 			printf( "should not return NaN\n" );
@@ -126,6 +127,46 @@ static double benchmark( int iterations, int len ) {
 	return elapsed;
 }
 
+/**
+* Runs a benchmark.
+*
+* @param iterations   number of iterations
+* @param len          array length
+* @return             elapsed time in seconds
+*/
+static double benchmark2( int iterations, int len ) {
+	unsigned char mask[ len ];
+	double elapsed;
+	float x[ len ];
+	float v;
+	double t;
+	int i;
+
+	for ( i = 0; i < len; i++ ) {
+		if ( rand_float() < 0.2f ) {
+			mask[ i ] = 1; // missing
+		} else {
+			mask[ i ] = 0;
+		}
+		x[ i ] = ( rand_float() * 20000.0f ) - 10000.0f;
+	}
+	v = 0.0f;
+	t = tic();
+	for ( i = 0; i < iterations; i++ ) {
+		// cppcheck-suppress uninitvar
+		v = stdlib_strided_smskmin_ndarray( len, x, 1, 0, mask, 1, 0 );
+		if ( v != v ) {
+			printf( "should not return NaN\n" );
+			break;
+		}
+	}
+	elapsed = tic() - t;
+	if ( v != v ) {
+		printf( "should not return NaN\n" );
+	}
+	return elapsed;
+}
+
 /**
 * Main execution sequence.
 */
@@ -148,7 +189,18 @@ int main( void ) {
 		for ( j = 0; j < REPEATS; j++ ) {
 			count += 1;
 			printf( "# c::%s:len=%d\n", NAME, len );
-			elapsed = benchmark( iter, len );
+			elapsed = benchmark1( iter, len );
+			print_results( iter, elapsed );
+			printf( "ok %d benchmark finished\n", count );
+		}
+	}
+	for ( i = MIN; i <= MAX; i++ ) {
+		len = pow( 10, i );
+		iter = ITERATIONS / pow( 10, i-1 );
+		for ( j = 0; j < REPEATS; j++ ) {
+			count += 1;
+			printf( "# c::%s:ndarray:len=%d\n", NAME, len );
+			elapsed = benchmark2( iter, len );
 			print_results( iter, elapsed );
 			printf( "ok %d benchmark finished\n", count );
 		}
diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/smskmin/docs/repl.txt
index 636adf41126f..6eb997450299 100644
--- a/lib/node_modules/@stdlib/stats/base/smskmin/docs/repl.txt
+++ b/lib/node_modules/@stdlib/stats/base/smskmin/docs/repl.txt
@@ -3,8 +3,8 @@
     Computes the minimum value of a single-precision floating-point strided
     array according to a mask.
 
-    The `N` and `stride` parameters determine which elements are accessed at
-    runtime.
+    The `N` and stride parameters determine which elements in the strided arrays
+    are accessed at runtime.
 
     Indexing is relative to the first index. To introduce offsets, use a typed
     array views.
@@ -26,13 +26,13 @@
         Input array.
 
     strideX: integer
-        Index increment for `x`.
+        Stride Length for `x`.
 
     mask: Uint8Array
         Mask array.
 
     strideMask: integer
-        Index increment for `mask`.
+        Stride Length for `mask`.
 
     Returns
     -------
@@ -47,11 +47,10 @@
     > {{alias}}( x.length, x, 1, mask, 1 )
     -2.0
 
-    // Using `N` and `stride` parameters:
+    // Using `N` and stride parameters:
     > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );
     > mask = new {{alias:@stdlib/array/uint8}}( [ 0, 0, 0, 0, 0, 0, 1 ] );
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > {{alias}}( N, x, 2, mask, 2 )
+    > {{alias}}( 3, x, 2, mask, 2 )
     -2.0
 
     // Using view offsets:
@@ -59,10 +58,10 @@
     > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );
     > var mask0 = new {{alias:@stdlib/array/uint8}}( [ 0, 0, 0, 0, 0, 0, 1 ] );
     > var mask1 = new {{alias:@stdlib/array/uint8}}( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );
-    > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );
-    > {{alias}}( N, x1, 2, mask1, 2 )
+    > {{alias}}( 3, x1, 2, mask1, 2 )
     -2.0
 
+
 {{alias}}.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )
     Computes the minimum value of a single-precision floating-point strided
     array according to a mask and using alternative indexing semantics.
@@ -80,7 +79,7 @@
         Input array.
 
     strideX: integer
-        Index increment for `x`.
+        Stride Length for `x`.
 
     offsetX: integer
         Starting index for `x`.
@@ -89,7 +88,7 @@
         Mask array.
 
     strideMask: integer
-        Index increment for `mask`.
+        Stride Length for `mask`.
 
     offsetMask: integer
         Starting index for `mask`.
@@ -110,8 +109,7 @@
     // Using offset parameter:
     > x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );
     > mask = new {{alias:@stdlib/array/uint8}}( [ 0, 0, 0, 0, 0, 0, 1 ] );
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > {{alias}}.ndarray( N, x, 2, 1, mask, 2, 1 )
+    > {{alias}}.ndarray( 3, x, 2, 1, mask, 2, 1 )
     -2.0
 
     See Also
diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/smskmin/examples/c/example.c
index 551febff6aad..0d1e8106827e 100644
--- a/lib/node_modules/@stdlib/stats/base/smskmin/examples/c/example.c
+++ b/lib/node_modules/@stdlib/stats/base/smskmin/examples/c/example.c
@@ -22,17 +22,17 @@
 
 int main( void ) {
 	// Create a strided array:
-	float x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 };
+	const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f };
 
 	// Create a mask array:
-	uint8_t mask[] = { 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 };
+	const uint8_t mask[] = { 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 };
 
 	// Specify the number of elements:
-	int64_t N = 5;
+	const int N = 5;
 
 	// Specify the stride lengths:
-	int64_t strideX = 2;
-	int64_t strideMask = 2;
+	const int strideX = 2;
+	const int strideMask = 2;
 
 	// Compute the minimum value:
 	float v = stdlib_strided_smskmin( N, x, strideX, mask, strideMask );
diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/examples/index.js b/lib/node_modules/@stdlib/stats/base/smskmin/examples/index.js
index 8c2afc2c7d38..8d8fb3138e8f 100644
--- a/lib/node_modules/@stdlib/stats/base/smskmin/examples/index.js
+++ b/lib/node_modules/@stdlib/stats/base/smskmin/examples/index.js
@@ -18,26 +18,19 @@
 
 'use strict';
 
-var randu = require( '@stdlib/random/base/randu' );
-var round = require( '@stdlib/math/base/special/round' );
-var Float32Array = require( '@stdlib/array/float32' );
-var Uint8Array = require( '@stdlib/array/uint8' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var bernoulli = require( '@stdlib/random/array/bernoulli' );
 var smskmin = require( './../lib' );
 
-var mask;
-var x;
-var i;
+var uniformOptions = {
+	'dtype': 'float32'
+};
+var bernoulliOptions = {
+	'dtype': 'uint8'
+};
 
-x = new Float32Array( 10 );
-mask = new Uint8Array( x.length );
-for ( i = 0; i < x.length; i++ ) {
-	if ( randu() < 0.2 ) {
-		mask[ i ] = 1;
-	} else {
-		mask[ i ] = 0;
-	}
-	x[ i ] = round( (randu()*100.0) - 50.0 );
-}
+var x = uniform( 10, -50.0, 50.0, uniformOptions );
+var mask = bernoulli( x.length, 0.2, bernoulliOptions );
 console.log( x );
 console.log( mask );
 
diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/include.gypi b/lib/node_modules/@stdlib/stats/base/smskmin/include.gypi
index 868c5c12e852..26476a8c2655 100644
--- a/lib/node_modules/@stdlib/stats/base/smskmin/include.gypi
+++ b/lib/node_modules/@stdlib/stats/base/smskmin/include.gypi
@@ -36,7 +36,7 @@
 
     # Source files:
     'src_files': [
-      '<(src_dir)/addon.cpp',
+      '<(src_dir)/addon.c',
       '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).src; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
     ],
 
diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/include/stdlib/stats/base/smskmin.h b/lib/node_modules/@stdlib/stats/base/smskmin/include/stdlib/stats/base/smskmin.h
index e26dc0d9d533..518e15579033 100644
--- a/lib/node_modules/@stdlib/stats/base/smskmin/include/stdlib/stats/base/smskmin.h
+++ b/lib/node_modules/@stdlib/stats/base/smskmin/include/stdlib/stats/base/smskmin.h
@@ -19,6 +19,7 @@
 #ifndef STDLIB_STATS_BASE_SMSKMIN_H
 #define STDLIB_STATS_BASE_SMSKMIN_H
 
+#include "stdlib/blas/base/shared.h"
 #include <stdint.h>
 
 /*
@@ -31,7 +32,12 @@ extern "C" {
 /**
 * Computes the minimum value of a single-precision floating-point strided array according to a mask.
 */
-float stdlib_strided_smskmin( const int64_t N, const float *X, const int64_t strideX, const uint8_t *Mask, const int64_t strideMask );
+float API_SUFFIX(stdlib_strided_smskmin)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const uint8_t *Mask, const CBLAS_INT strideMask );
+
+/**
+* Computes the minimum value of a single-precision floating-point strided array according to a mask and using alternative indexing semantics.
+*/
+float API_SUFFIX(stdlib_strided_smskmin_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const uint8_t *Mask, const CBLAS_INT strideMask, const CBLAS_INT offsetMask );
 
 #ifdef __cplusplus
 }
diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/lib/index.js b/lib/node_modules/@stdlib/stats/base/smskmin/lib/index.js
index ed69d14be484..bc09c6e5c326 100644
--- a/lib/node_modules/@stdlib/stats/base/smskmin/lib/index.js
+++ b/lib/node_modules/@stdlib/stats/base/smskmin/lib/index.js
@@ -37,14 +37,12 @@
 * @example
 * var Float32Array = require( '@stdlib/array/float32' );
 * var Uint8Array = require( '@stdlib/array/uint8' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 * var smskmin = require( '@stdlib/stats/base/smskmin' );
 *
 * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, -5.0, -6.0 ] );
 * var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 ] );
-* var N = floor( x.length / 2 );
 *
-* var v = smskmin.ndarray( N, x, 2, 1, mask, 2, 1 );
+* var v = smskmin.ndarray( 5, x, 2, 1, mask, 2, 1 );
 * // returns -2.0
 */
 
diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/smskmin/lib/ndarray.js
index c8c4ecdfa914..35b86124278b 100644
--- a/lib/node_modules/@stdlib/stats/base/smskmin/lib/ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/smskmin/lib/ndarray.js
@@ -41,13 +41,11 @@ var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' );
 * @example
 * var Float32Array = require( '@stdlib/array/float32' );
 * var Uint8Array = require( '@stdlib/array/uint8' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 *
 * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, -5.0, -6.0 ] );
 * var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 ] );
-* var N = floor( x.length / 2 );
 *
-* var v = smskmin( N, x, 2, 1, mask, 2, 1 );
+* var v = smskmin( 5, x, 2, 1, mask, 2, 1 );
 * // returns -2.0
 */
 function smskmin( N, x, strideX, offsetX, mask, strideMask, offsetMask ) {
diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/smskmin/lib/ndarray.native.js
index f473b63a9a7c..7dc599165947 100644
--- a/lib/node_modules/@stdlib/stats/base/smskmin/lib/ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/smskmin/lib/ndarray.native.js
@@ -20,9 +20,7 @@
 
 // MODULES //
 
-var Float32Array = require( '@stdlib/array/float32' );
-var Uint8Array = require( '@stdlib/array/uint8' );
-var addon = require( './smskmin.native.js' );
+var addon = require( './../src/addon.node' );
 
 
 // MAIN //
@@ -52,17 +50,7 @@ var addon = require( './smskmin.native.js' );
 * // returns -2.0
 */
 function smskmin( N, x, strideX, offsetX, mask, strideMask, offsetMask ) {
-	var viewX;
-	var viewM;
-	if ( strideX < 0 ) {
-		offsetX += (N-1) * strideX;
-	}
-	if ( strideMask < 0 ) {
-		offsetMask += (N-1) * strideMask;
-	}
-	viewX = new Float32Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offsetX), x.length-offsetX ); // eslint-disable-line max-len
-	viewM = new Uint8Array( mask.buffer, mask.byteOffset+(mask.BYTES_PER_ELEMENT*offsetMask), mask.length-offsetMask ); // eslint-disable-line max-len
-	return addon( N, viewX, strideX, viewM, strideMask );
+	return addon.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask ); // eslint-disable-line max-len
 }
 
 
diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/lib/smskmin.js b/lib/node_modules/@stdlib/stats/base/smskmin/lib/smskmin.js
index e673b47c6137..899799e0850c 100644
--- a/lib/node_modules/@stdlib/stats/base/smskmin/lib/smskmin.js
+++ b/lib/node_modules/@stdlib/stats/base/smskmin/lib/smskmin.js
@@ -20,8 +20,8 @@
 
 // MODULES //
 
-var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
-var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' );
+var stride2offset = require( '@stdlib/strided/base/stride2offset' );
+var ndarray = require( './ndarray.js' );
 
 
 // MAIN //
@@ -47,55 +47,9 @@ var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' );
 * // returns -2.0
 */
 function smskmin( N, x, strideX, mask, strideMask ) {
-	var min;
-	var ix;
-	var im;
-	var v;
-	var i;
-
-	if ( N <= 0 ) {
-		return NaN;
-	}
-	if ( strideX < 0 ) {
-		ix = (1-N) * strideX;
-	} else {
-		ix = 0;
-	}
-	if ( strideMask < 0 ) {
-		im = (1-N) * strideMask;
-	} else {
-		im = 0;
-	}
-	for ( i = 0; i < N; i++ ) {
-		if ( mask[ im ] === 0 ) {
-			break;
-		}
-		ix += strideX;
-		im += strideMask;
-	}
-	if ( i === N ) {
-		return NaN;
-	}
-	min = x[ ix ];
-	if ( isnanf( min ) ) {
-		return min;
-	}
-	i += 1;
-	for ( i; i < N; i++ ) {
-		ix += strideX;
-		im += strideMask;
-		if ( mask[ im ] ) {
-			continue;
-		}
-		v = x[ ix ];
-		if ( isnanf( v ) ) {
-			return v;
-		}
-		if ( v < min || ( v === min && isNegativeZerof( v ) ) ) {
-			min = v;
-		}
-	}
-	return min;
+	var ox = stride2offset( N, strideX );
+	var om = stride2offset( N, strideMask );
+	return ndarray( N, x, strideX, ox, mask, strideMask, om );
 }
 
 
diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/manifest.json b/lib/node_modules/@stdlib/stats/base/smskmin/manifest.json
index e277545bd6d8..6fdc59ed195e 100644
--- a/lib/node_modules/@stdlib/stats/base/smskmin/manifest.json
+++ b/lib/node_modules/@stdlib/stats/base/smskmin/manifest.json
@@ -1,5 +1,8 @@
 {
-  "options": {},
+  "options": {
+    "task": "build",
+    "wasm": false
+  },
   "fields": [
     {
       "field": "src",
@@ -24,17 +27,79 @@
   ],
   "confs": [
     {
+      "task": "build",
+      "wasm": false,
       "src": [
-        "./src/smskmin.c"
+        "./src/main.c"
       ],
       "include": [
         "./include"
       ],
-      "libraries": [
-        "-lm"
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset",
+        "@stdlib/math/base/assert/is-negative-zerof",
+        "@stdlib/math/base/assert/is-nanf",
+        "@stdlib/napi/export",
+        "@stdlib/napi/argv",
+        "@stdlib/napi/argv-int64",
+        "@stdlib/napi/argv-strided-float32array",
+        "@stdlib/napi/argv-strided-uint8array",
+        "@stdlib/napi/create-double"
+      ]
+    },
+    {
+      "task": "benchmark",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset",
+        "@stdlib/math/base/assert/is-nanf",
+        "@stdlib/math/base/assert/is-negative-zerof"
+      ]
+    },
+    {
+      "task": "examples",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset",
+        "@stdlib/math/base/assert/is-nanf",
+        "@stdlib/math/base/assert/is-negative-zerof"
+      ]
+    },
+    {
+      "task": "",
+      "wasm": true,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
       ],
+      "libraries": [],
       "libpath": [],
       "dependencies": [
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset",
         "@stdlib/math/base/assert/is-nanf",
         "@stdlib/math/base/assert/is-negative-zerof"
       ]
diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/src/addon.c b/lib/node_modules/@stdlib/stats/base/smskmin/src/addon.c
new file mode 100644
index 000000000000..d6785b05e17a
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/smskmin/src/addon.c
@@ -0,0 +1,66 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/smskmin.h"
+#include "stdlib/napi/export.h"
+#include "stdlib/napi/argv.h"
+#include "stdlib/napi/argv_int64.h"
+#include "stdlib/napi/argv_strided_float32array.h"
+#include "stdlib/napi/argv_strided_uint8array.h"
+#include "stdlib/napi/create_double.h"
+#include <node_api.h>
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 5 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 );
+	STDLIB_NAPI_ARGV_INT64( env, strideMask, argv, 4 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 );
+	STDLIB_NAPI_ARGV_STRIDED_UINT8ARRAY( env, Mask, N, strideMask, argv, 3 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_smskmin( N, X, strideX, Mask, strideMask ), v );
+	return v;
+}
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon_method( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 7 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 );
+	STDLIB_NAPI_ARGV_INT64( env, strideMask, argv, 5 );
+	STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 );
+	STDLIB_NAPI_ARGV_INT64( env, offsetMask, argv, 6 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 );
+	STDLIB_NAPI_ARGV_STRIDED_UINT8ARRAY( env, Mask, N, strideMask, argv, 4 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_smskmin_ndarray( N, X, strideX, offsetX, Mask, strideMask, offsetMask ), v );
+	return v;
+}
+
+STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method )
diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/smskmin/src/addon.cpp
deleted file mode 100644
index b8a4e250d35f..000000000000
--- a/lib/node_modules/@stdlib/stats/base/smskmin/src/addon.cpp
+++ /dev/null
@@ -1,153 +0,0 @@
-/**
-* @license Apache-2.0
-*
-* Copyright (c) 2020 The Stdlib Authors.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-*    http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-
-#include "stdlib/stats/base/smskmin.h"
-#include <node_api.h>
-#include <stdint.h>
-#include <stdlib.h>
-#include <stdbool.h>
-#include <assert.h>
-
-/**
-* Add-on namespace.
-*/
-namespace stdlib_stats_base_smskmin {
-
-	/**
-	* Computes the minimum value of a single-precision floating-point strided array according to a mask.
-	*
-	* ## Notes
-	*
-	* -   When called from JavaScript, the function expects five arguments:
-	*
-	*     -   `N`: number of indexed elements
-	*     -   `X`: input array
-	*     -   `strideX`: `X` stride length
-	*     -   `Mask`: mask array
-	*     -   `strideMask`: `Mask` stride length
-	*/
-	napi_value node_smskmin( napi_env env, napi_callback_info info ) {
-		napi_status status;
-
-		size_t argc = 5;
-		napi_value argv[ 5 ];
-		status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr );
-		assert( status == napi_ok );
-
-		if ( argc < 5 ) {
-			napi_throw_error( env, nullptr, "invalid invocation. Must provide 5 arguments." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype0;
-		status = napi_typeof( env, argv[ 0 ], &vtype0 );
-		assert( status == napi_ok );
-		if ( vtype0 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." );
-			return nullptr;
-		}
-
-		bool res1;
-		status = napi_is_typedarray( env, argv[ 1 ], &res1 );
-		assert( status == napi_ok );
-		if ( res1 == false ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype2;
-		status = napi_typeof( env, argv[ 2 ], &vtype2 );
-		assert( status == napi_ok );
-		if ( vtype2 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." );
-			return nullptr;
-		}
-
-		bool res3;
-		status = napi_is_typedarray( env, argv[ 3 ], &res3 );
-		assert( status == napi_ok );
-		if ( res3 == false ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a Uint8Array." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype4;
-		status = napi_typeof( env, argv[ 4 ], &vtype4 );
-		assert( status == napi_ok );
-		if ( vtype4 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Fifth argument must be a number." );
-			return nullptr;
-		}
-
-		int64_t N;
-		status = napi_get_value_int64( env, argv[ 0 ], &N );
-		assert( status == napi_ok );
-
-		int64_t strideX;
-		status = napi_get_value_int64( env, argv[ 2 ], &strideX );
-		assert( status == napi_ok );
-
-		int64_t strideMask;
-		status = napi_get_value_int64( env, argv[ 4 ], &strideMask );
-		assert( status == napi_ok );
-
-		napi_typedarray_type vtype1;
-		size_t xlen;
-		void *X;
-		status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr );
-		assert( status == napi_ok );
-		if ( vtype1 != napi_float32_array ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." );
-			return nullptr;
-		}
-		if ( (N-1)*llabs(strideX) >= (int64_t)xlen ) {
-			napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." );
-			return nullptr;
-		}
-
-		napi_typedarray_type vtype3;
-		size_t mlen;
-		void *Mask;
-		status = napi_get_typedarray_info( env, argv[ 3 ], &vtype3, &mlen, &Mask, nullptr, nullptr );
-		assert( status == napi_ok );
-		if ( vtype3 != napi_uint8_array ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a Uint8Array." );
-			return nullptr;
-		}
-		if ( (N-1)*llabs(strideMask) >= (int64_t)mlen ) {
-			napi_throw_range_error( env, nullptr, "invalid argument. Fourth argument has insufficient elements based on the associated stride and the number of indexed elements." );
-			return nullptr;
-		}
-
-		napi_value v;
-		status = napi_create_double( env, (double)stdlib_strided_smskmin( N, (float *)X, strideX, (uint8_t *)Mask, strideMask ), &v );
-		assert( status == napi_ok );
-
-		return v;
-	}
-
-	napi_value Init( napi_env env, napi_value exports ) {
-		napi_status status;
-		napi_value fcn;
-		status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_smskmin, NULL, &fcn );
-		assert( status == napi_ok );
-		return fcn;
-	}
-
-	NAPI_MODULE( NODE_GYP_MODULE_NAME, Init )
-} // end namespace stdlib_stats_base_smskmin
diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/src/smskmin.c b/lib/node_modules/@stdlib/stats/base/smskmin/src/main.c
similarity index 58%
rename from lib/node_modules/@stdlib/stats/base/smskmin/src/smskmin.c
rename to lib/node_modules/@stdlib/stats/base/smskmin/src/main.c
index fabb56941c92..ace83332caf5 100644
--- a/lib/node_modules/@stdlib/stats/base/smskmin/src/smskmin.c
+++ b/lib/node_modules/@stdlib/stats/base/smskmin/src/main.c
@@ -19,6 +19,8 @@
 #include "stdlib/stats/base/smskmin.h"
 #include "stdlib/math/base/assert/is_nanf.h"
 #include "stdlib/math/base/assert/is_negative_zerof.h"
+#include "stdlib/blas/base/shared.h"
+#include "stdlib/strided/base/stride2offset.h"
 #include <stdint.h>
 
 /**
@@ -31,26 +33,36 @@
 * @param strideMask  Mask stride length
 * @return            output value
 */
-float stdlib_strided_smskmin( const int64_t N, const float *X, const int64_t strideX, const uint8_t *Mask, const int64_t strideMask ) {
-	int64_t ix;
-	int64_t im;
-	int64_t i;
+float API_SUFFIX(stdlib_strided_smskmin)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const uint8_t *Mask, const CBLAS_INT strideMask ) {
+	const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX );
+	const CBLAS_INT om = stdlib_strided_stride2offset( N, strideMask );
+	return API_SUFFIX(stdlib_strided_smskmin_ndarray)( N, X, strideX, ox, Mask, strideMask, om );
+}
+
+/**
+* Computes the minimum value of a single-precision floating-point strided array according to a mask and using alternative indexing semantics.
+*
+* @param N           number of indexed elements
+* @param X           input array
+* @param strideX     X stride length
+* @param offsetX     starting index for X
+* @param Mask        mask array
+* @param strideMask  Mask stride length
+* @param offsetMask  starting index for Mask
+* @return            output value
+*/
+float API_SUFFIX(stdlib_strided_smskmin_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const uint8_t *Mask, const CBLAS_INT strideMask, const CBLAS_INT offsetMask ) {
+	CBLAS_INT ix;
+	CBLAS_INT im;
+	CBLAS_INT i;
 	float min;
 	float v;
 
 	if ( N <= 0 ) {
 		return 0.0f / 0.0f; // NaN
 	}
-	if ( strideX < 0 ) {
-		ix = (1-N) * strideX;
-	} else {
-		ix = 0;
-	}
-	if ( strideMask < 0 ) {
-		im = (1-N) * strideMask;
-	} else {
-		im = 0;
-	}
+	ix = offsetX;
+	im = offsetMask;
 	for ( i = 0; i < N; i++ ) {
 		if ( Mask[ im ] == 0 ) {
 			break;
diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/smskmin/test/test.ndarray.js
index 2b365f6f8315..083be7f8dce7 100644
--- a/lib/node_modules/@stdlib/stats/base/smskmin/test/test.ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/smskmin/test/test.ndarray.js
@@ -21,7 +21,6 @@
 // MODULES //
 
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
 var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' );
 var Float32Array = require( '@stdlib/array/float32' );
@@ -133,7 +132,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 
 tape( 'the function supports `stride` parameters', function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -162,8 +160,7 @@ tape( 'the function supports `stride` parameters', function test( t ) {
 		1
 	]);
 
-	N = floor( x.length / 2 );
-	v = smskmin( N, x, 2, 0, mask, 2, 0 );
+	v = smskmin( 5, x, 2, 0, mask, 2, 0 );
 
 	t.strictEqual( v, -2.0, 'returns expected value' );
 	t.end();
@@ -171,7 +168,6 @@ tape( 'the function supports `stride` parameters', function test( t ) {
 
 tape( 'the function supports negative `stride` parameters', function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -200,8 +196,7 @@ tape( 'the function supports negative `stride` parameters', function test( t ) {
 		0
 	]);
 
-	N = floor( x.length / 2 );
-	v = smskmin( N, x, -2, 8, mask, -2, 8 );
+	v = smskmin( 5, x, -2, 8, mask, -2, 8 );
 
 	t.strictEqual( v, -2.0, 'returns expected value' );
 	t.end();
@@ -209,7 +204,6 @@ tape( 'the function supports negative `stride` parameters', function test( t ) {
 
 tape( 'the function supports `offset` parameters', function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -237,9 +231,8 @@ tape( 'the function supports `offset` parameters', function test( t ) {
 		1,
 		1  // 4
 	]);
-	N = floor( x.length / 2 );
 
-	v = smskmin( N, x, 2, 1, mask, 2, 1 );
+	v = smskmin( 5, x, 2, 1, mask, 2, 1 );
 	t.strictEqual( v, -2.0, 'returns expected value' );
 
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/smskmin/test/test.ndarray.native.js
index 5242fea20c17..03603c536c73 100644
--- a/lib/node_modules/@stdlib/stats/base/smskmin/test/test.ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/smskmin/test/test.ndarray.native.js
@@ -22,7 +22,6 @@
 
 var resolve = require( 'path' ).resolve;
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
 var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' );
 var Float32Array = require( '@stdlib/array/float32' );
@@ -120,7 +119,7 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu
 	v = smskmin( 0, x, 1, 0, mask, 1, 0 );
 	t.strictEqual( isnanf( v ), true, 'returns expected value' );
 
-	v = smskmin( -1, x, 1, 0, mask, 1 );
+	v = smskmin( -1, x, 1, 0, mask, 1, 0 );
 	t.strictEqual( isnanf( v ), true, 'returns expected value' );
 
 	t.end();
@@ -142,7 +141,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 
 tape( 'the function supports `stride` parameters', opts, function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -171,8 +169,7 @@ tape( 'the function supports `stride` parameters', opts, function test( t ) {
 		1
 	]);
 
-	N = floor( x.length / 2 );
-	v = smskmin( N, x, 2, 0, mask, 2, 0 );
+	v = smskmin( 5, x, 2, 0, mask, 2, 0 );
 
 	t.strictEqual( v, -2.0, 'returns expected value' );
 	t.end();
@@ -180,7 +177,6 @@ tape( 'the function supports `stride` parameters', opts, function test( t ) {
 
 tape( 'the function supports negative `stride` parameters', opts, function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -209,8 +205,7 @@ tape( 'the function supports negative `stride` parameters', opts, function test(
 		0
 	]);
 
-	N = floor( x.length / 2 );
-	v = smskmin( N, x, -2, 8, mask, -2, 8 );
+	v = smskmin( 5, x, -2, 8, mask, -2, 8 );
 
 	t.strictEqual( v, -2.0, 'returns expected value' );
 	t.end();
@@ -218,7 +213,6 @@ tape( 'the function supports negative `stride` parameters', opts, function test(
 
 tape( 'the function supports `offset` parameters', opts, function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -246,9 +240,8 @@ tape( 'the function supports `offset` parameters', opts, function test( t ) {
 		1,
 		1  // 4
 	]);
-	N = floor( x.length / 2 );
 
-	v = smskmin( N, x, 2, 1, mask, 2, 1 );
+	v = smskmin( 5, x, 2, 1, mask, 2, 1 );
 	t.strictEqual( v, -2.0, 'returns expected value' );
 
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/test/test.smskmin.js b/lib/node_modules/@stdlib/stats/base/smskmin/test/test.smskmin.js
index 9555714033a1..e9c3b38ad928 100644
--- a/lib/node_modules/@stdlib/stats/base/smskmin/test/test.smskmin.js
+++ b/lib/node_modules/@stdlib/stats/base/smskmin/test/test.smskmin.js
@@ -21,7 +21,6 @@
 // MODULES //
 
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
 var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' );
 var Float32Array = require( '@stdlib/array/float32' );
@@ -133,7 +132,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 
 tape( 'the function supports `stride` parameters', function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -162,8 +160,7 @@ tape( 'the function supports `stride` parameters', function test( t ) {
 		1
 	]);
 
-	N = floor( x.length / 2 );
-	v = smskmin( N, x, 2, mask, 2 );
+	v = smskmin( 5, x, 2, mask, 2 );
 
 	t.strictEqual( v, -2.0, 'returns expected value' );
 	t.end();
@@ -171,7 +168,6 @@ tape( 'the function supports `stride` parameters', function test( t ) {
 
 tape( 'the function supports negative `stride` parameters', function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -200,8 +196,7 @@ tape( 'the function supports negative `stride` parameters', function test( t ) {
 		0
 	]);
 
-	N = floor( x.length / 2 );
-	v = smskmin( N, x, -2, mask, -2 );
+	v = smskmin( 5, x, -2, mask, -2 );
 
 	t.strictEqual( v, -2.0, 'returns expected value' );
 	t.end();
@@ -212,7 +207,6 @@ tape( 'the function supports view offsets', function test( t ) {
 	var mask1;
 	var x0;
 	var x1;
-	var N;
 	var v;
 
 	x0 = new Float32Array([
@@ -244,9 +238,8 @@ tape( 'the function supports view offsets', function test( t ) {
 
 	x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
 	mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
-	N = floor( x1.length/2 );
 
-	v = smskmin( N, x1, 2, mask1, 2 );
+	v = smskmin( 5, x1, 2, mask1, 2 );
 	t.strictEqual( v, -2.0, 'returns expected value' );
 
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/smskmin/test/test.smskmin.native.js b/lib/node_modules/@stdlib/stats/base/smskmin/test/test.smskmin.native.js
index b529948e34e9..be0553016e32 100644
--- a/lib/node_modules/@stdlib/stats/base/smskmin/test/test.smskmin.native.js
+++ b/lib/node_modules/@stdlib/stats/base/smskmin/test/test.smskmin.native.js
@@ -22,7 +22,6 @@
 
 var resolve = require( 'path' ).resolve;
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
 var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' );
 var Float32Array = require( '@stdlib/array/float32' );
@@ -142,7 +141,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 
 tape( 'the function supports `stride` parameters', opts, function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -171,8 +169,7 @@ tape( 'the function supports `stride` parameters', opts, function test( t ) {
 		1
 	]);
 
-	N = floor( x.length / 2 );
-	v = smskmin( N, x, 2, mask, 2 );
+	v = smskmin( 5, x, 2, mask, 2 );
 
 	t.strictEqual( v, -2.0, 'returns expected value' );
 	t.end();
@@ -180,7 +177,6 @@ tape( 'the function supports `stride` parameters', opts, function test( t ) {
 
 tape( 'the function supports negative `stride` parameters', opts, function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -209,8 +205,7 @@ tape( 'the function supports negative `stride` parameters', opts, function test(
 		0
 	]);
 
-	N = floor( x.length / 2 );
-	v = smskmin( N, x, -2, mask, -2 );
+	v = smskmin( 5, x, -2, mask, -2 );
 
 	t.strictEqual( v, -2.0, 'returns expected value' );
 	t.end();
@@ -221,7 +216,6 @@ tape( 'the function supports view offsets', opts, function test( t ) {
 	var mask1;
 	var x0;
 	var x1;
-	var N;
 	var v;
 
 	x0 = new Float32Array([
@@ -253,9 +247,8 @@ tape( 'the function supports view offsets', opts, function test( t ) {
 
 	x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
 	mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
-	N = floor( x1.length/2 );
 
-	v = smskmin( N, x1, 2, mask1, 2 );
+	v = smskmin( 5, x1, 2, mask1, 2 );
 	t.strictEqual( v, -2.0, 'returns expected value' );
 
 	t.end();

From 0ac69f70474250ec158cc68fad504a589e40276c Mon Sep 17 00:00:00 2001
From: Aayush Khanna <96649223+aayush0325@users.noreply.github.com>
Date: Fri, 3 Jan 2025 01:52:47 +0530
Subject: [PATCH 19/87] feat: add C ndarray interface and refactor
 implementation for `stats/base/dmediansorted`

PR-URL: https://github.com/stdlib-js/stdlib/pull/4466
Co-authored-by: Athan Reines <kgryte@gmail.com>
Reviewed-by: Athan Reines <kgryte@gmail.com>
Co-authored-by: stdlib-bot <82920195+stdlib-bot@users.noreply.github.com>
---
 .../stats/base/dmediansorted/README.md        | 154 +++++++++++++++---
 .../base/dmediansorted/benchmark/benchmark.js |  17 +-
 .../benchmark/benchmark.native.js             |  13 +-
 .../benchmark/benchmark.ndarray.js            |  17 +-
 .../benchmark/benchmark.ndarray.native.js     |  13 +-
 .../benchmark/c/benchmark.length.c            |  50 +++++-
 .../stats/base/dmediansorted/docs/repl.txt    |  30 ++--
 .../base/dmediansorted/docs/types/index.d.ts  |  12 +-
 .../base/dmediansorted/examples/c/example.c   |   9 +-
 .../base/dmediansorted/examples/index.js      |  13 +-
 .../stats/base/dmediansorted/include.gypi     |   2 +-
 .../include/stdlib/stats/base/dmediansorted.h |   9 +-
 .../base/dmediansorted/lib/dmediansorted.js   |  28 +---
 .../dmediansorted/lib/dmediansorted.native.js |   6 +-
 .../stats/base/dmediansorted/lib/index.js     |   4 +-
 .../stats/base/dmediansorted/lib/ndarray.js   |  14 +-
 .../base/dmediansorted/lib/ndarray.native.js  |  20 +--
 .../stats/base/dmediansorted/manifest.json    |  69 +++++++-
 .../stats/base/dmediansorted/src/addon.c      |  60 +++++++
 .../stats/base/dmediansorted/src/addon.cpp    | 117 -------------
 .../base/dmediansorted/src/dmediansorted.c    |  49 ------
 .../stats/base/dmediansorted/src/main.c       |  58 +++++++
 .../dmediansorted/test/test.dmediansorted.js  |  13 +-
 .../test/test.dmediansorted.native.js         |  13 +-
 .../base/dmediansorted/test/test.ndarray.js   |  13 +-
 .../dmediansorted/test/test.ndarray.native.js |  13 +-
 26 files changed, 458 insertions(+), 358 deletions(-)
 create mode 100644 lib/node_modules/@stdlib/stats/base/dmediansorted/src/addon.c
 delete mode 100644 lib/node_modules/@stdlib/stats/base/dmediansorted/src/addon.cpp
 delete mode 100644 lib/node_modules/@stdlib/stats/base/dmediansorted/src/dmediansorted.c
 create mode 100644 lib/node_modules/@stdlib/stats/base/dmediansorted/src/main.c

diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/README.md b/lib/node_modules/@stdlib/stats/base/dmediansorted/README.md
index a86ace776024..c2c224047c75 100644
--- a/lib/node_modules/@stdlib/stats/base/dmediansorted/README.md
+++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/README.md
@@ -36,7 +36,7 @@ limitations under the License.
 var dmediansorted = require( '@stdlib/stats/base/dmediansorted' );
 ```
 
-#### dmediansorted( N, x, stride )
+#### dmediansorted( N, x, strideX )
 
 Computes the median value of a sorted double-precision floating-point strided array `x`.
 
@@ -56,18 +56,16 @@ The function has the following parameters:
 
 -   **N**: number of indexed elements.
 -   **x**: sorted input [`Float64Array`][@stdlib/array/float64].
--   **stride**: index increment for `x`.
+-   **strideX**: index increment for `x`.
 
-The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the median value of every other element in `x`,
+The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the median value of every other element in `x`,
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, 3.0, 3.0, 4.0, 2.0 ] );
-var N = floor( x.length / 2 );
 
-var v = dmediansorted( N, x, 2 );
+var v = dmediansorted( 4, x, 2 );
 // returns 2.5
 ```
 
@@ -77,18 +75,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x0 = new Float64Array( [ 2.0, 1.0, 2.0, 2.0, -2.0, 2.0, 3.0, 4.0 ] );
 var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
 
-var N = floor( x0.length / 2 );
-
-var v = dmediansorted( N, x1, 2 );
+var v = dmediansorted( 4, x1, 2 );
 // returns 2.0
 ```
 
-#### dmediansorted.ndarray( N, x, stride, offset )
+#### dmediansorted.ndarray( N, x, strideX, offsetX )
 
 Computes the median value of a sorted double-precision floating-point strided array using alternative indexing semantics.
 
@@ -96,9 +91,8 @@ Computes the median value of a sorted double-precision floating-point strided ar
 var Float64Array = require( '@stdlib/array/float64' );
 
 var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );
-var N = x.length;
 
-var v = dmediansorted.ndarray( N, x, 1, 0 );
+var v = dmediansorted.ndarray( x.length, x, 1, 0 );
 // returns 2.0
 ```
 
@@ -110,12 +104,10 @@ While [`typed array`][mdn-typed-array] views mandate a view offset based on the
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x = new Float64Array( [ 2.0, 1.0, 2.0, 2.0, -2.0, 2.0, 3.0, 4.0 ] );
-var N = floor( x.length / 2 );
 
-var v = dmediansorted.ndarray( N, x, 2, 1 );
+var v = dmediansorted.ndarray( 4, x, 2, 1 );
 // returns 2.0
 ```
 
@@ -141,16 +133,13 @@ var v = dmediansorted.ndarray( N, x, 2, 1 );
 <!-- eslint no-undef: "error" -->
 
 ```javascript
-var Float64Array = require( '@stdlib/array/float64' );
+var linspace = require( '@stdlib/array/linspace' );
 var dmediansorted = require( '@stdlib/stats/base/dmediansorted' );
 
-var x;
-var i;
-
-x = new Float64Array( 10 );
-for ( i = 0; i < x.length; i++ ) {
-    x[ i ] = i - 5.0;
-}
+var options = {
+    'dtype': 'float64'
+};
+var x = linspace( -5.0, 5.0, 10, options );
 console.log( x );
 
 var v = dmediansorted( x.length, x, 1 );
@@ -161,6 +150,123 @@ console.log( v );
 
 <!-- /.examples -->
 
+<!-- C interface documentation. -->
+
+* * *
+
+<section class="c">
+
+## C APIs
+
+<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<!-- C usage documentation. -->
+
+<section class="usage">
+
+### Usage
+
+```c
+#include "stdlib/stats/base/dmediansorted.h"
+```
+
+#### stdlib_strided_dmediansorted( N, \*X, strideX )
+
+Computes the median value of a sorted double-precision floating-point strided array.
+
+```c
+const double x[] = { 1.0, 2.0, 3.0 };
+
+double v = stdlib_strided_dmediansorted( 3, x, 1 );
+// returns 2.0
+```
+
+The function accepts the following arguments:
+
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **X**: `[in] double*` input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+
+```c
+double stdlib_strided_dmediansorted( const CBLAS_INT N, const double *X, const CBLAS_INT strideX );
+```
+
+#### stdlib_strided_dmediansorted_ndarray( N, \*X, strideX, offsetX )
+
+Computes the median value of a sorted double-precision floating-point strided array using alternative indexing semantics.
+
+```c
+const double x[] = { 1.0, 2.0, 3.0 };
+
+double v = stdlib_strided_dmediansorted_ndarray( 3, x, 1, 0 );
+// returns 2.0
+```
+
+The function accepts the following arguments:
+
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **X**: `[in] double*` input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+-   **offsetX**: `[in] CBLAS_INT` starting index for `X`.
+
+```c
+double stdlib_strided_dmediansorted_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX );
+```
+
+</section>
+
+<!-- /.usage -->
+
+<!-- C API usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="notes">
+
+</section>
+
+<!-- /.notes -->
+
+<!-- C API usage examples. -->
+
+<section class="examples">
+
+### Examples
+
+```c
+#include "stdlib/stats/base/dmediansorted.h"
+#include <stdio.h>
+
+int main( void ) {
+    // Create a strided array:
+    const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 };
+
+    // Specify the number of elements:
+    const int N = 4;
+
+    // Specify the stride length:
+    const int strideX = 2;
+
+    // Compute the median value:
+    double v = stdlib_strided_dmediansorted( N, x, strideX );
+
+    // Print the result:
+    printf( "median: %lf\n", v );
+}
+```
+
+</section>
+
+<!-- /.examples -->
+
+</section>
+
+<!-- /.c -->
+
 <!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
 
 <section class="related">
diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dmediansorted/benchmark/benchmark.js
index 184b2c1efdef..7693a0f7e852 100644
--- a/lib/node_modules/@stdlib/stats/base/dmediansorted/benchmark/benchmark.js
+++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/benchmark/benchmark.js
@@ -22,12 +22,19 @@
 
 var bench = require( '@stdlib/bench' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var linspace = require( '@stdlib/array/linspace' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float64Array = require( '@stdlib/array/float64' );
 var pkg = require( './../package.json' ).name;
 var dmediansorted = require( './../lib/dmediansorted.js' );
 
 
+// VARIABLES //
+
+var options = {
+	'dtype': 'float64'
+};
+
+
 // FUNCTIONS //
 
 /**
@@ -38,13 +45,7 @@ var dmediansorted = require( './../lib/dmediansorted.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float64Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = i;
-	}
+	var x = linspace( -len/2, len/2, len, options );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dmediansorted/benchmark/benchmark.native.js
index 4f202cb30343..578bcca1f3e3 100644
--- a/lib/node_modules/@stdlib/stats/base/dmediansorted/benchmark/benchmark.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/benchmark/benchmark.native.js
@@ -23,8 +23,8 @@
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var linspace = require( '@stdlib/array/linspace' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float64Array = require( '@stdlib/array/float64' );
 var tryRequire = require( '@stdlib/utils/try-require' );
 var pkg = require( './../package.json' ).name;
 
@@ -35,6 +35,9 @@ var dmediansorted = tryRequire( resolve( __dirname, './../lib/dmediansorted.nati
 var opts = {
 	'skip': ( dmediansorted instanceof Error )
 };
+var options = {
+	'dtype': 'float64'
+};
 
 
 // FUNCTIONS //
@@ -47,13 +50,7 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float64Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = i;
-	}
+	var x = linspace( -len/2, len/2, len, options );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/dmediansorted/benchmark/benchmark.ndarray.js
index 97ccf335dda8..e4132087b0be 100644
--- a/lib/node_modules/@stdlib/stats/base/dmediansorted/benchmark/benchmark.ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/benchmark/benchmark.ndarray.js
@@ -22,12 +22,19 @@
 
 var bench = require( '@stdlib/bench' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var linspace = require( '@stdlib/array/linspace' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float64Array = require( '@stdlib/array/float64' );
 var pkg = require( './../package.json' ).name;
 var dmediansorted = require( './../lib/ndarray.js' );
 
 
+// VARIABLES //
+
+var options = {
+	'dtype': 'float64'
+};
+
+
 // FUNCTIONS //
 
 /**
@@ -38,13 +45,7 @@ var dmediansorted = require( './../lib/ndarray.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float64Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = i;
-	}
+	var x = linspace( -len/2, len/2, len, options );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmediansorted/benchmark/benchmark.ndarray.native.js
index fe0ffcb7aa53..dd02a5b23a63 100644
--- a/lib/node_modules/@stdlib/stats/base/dmediansorted/benchmark/benchmark.ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/benchmark/benchmark.ndarray.native.js
@@ -23,8 +23,8 @@
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var linspace = require( '@stdlib/array/linspace' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float64Array = require( '@stdlib/array/float64' );
 var tryRequire = require( '@stdlib/utils/try-require' );
 var pkg = require( './../package.json' ).name;
 
@@ -35,6 +35,9 @@ var dmediansorted = tryRequire( resolve( __dirname, './../lib/ndarray.native.js'
 var opts = {
 	'skip': ( dmediansorted instanceof Error )
 };
+var options = {
+	'dtype': 'float64'
+};
 
 
 // FUNCTIONS //
@@ -47,13 +50,7 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float64Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = i;
-	}
+	var x = linspace( -len/2, len/2, len, options );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dmediansorted/benchmark/c/benchmark.length.c
index b8e5967e30a8..061ceba5905a 100644
--- a/lib/node_modules/@stdlib/stats/base/dmediansorted/benchmark/c/benchmark.length.c
+++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/benchmark/c/benchmark.length.c
@@ -94,7 +94,7 @@ static double rand_double( void ) {
 * @param len          array length
 * @return             elapsed time in seconds
 */
-static double benchmark( int iterations, int len ) {
+static double benchmark1( int iterations, int len ) {
 	double elapsed;
 	double x[ len ];
 	double v;
@@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) {
 	v = 0.0;
 	t = tic();
 	for ( i = 0; i < iterations; i++ ) {
+		// cppcheck-suppress uninitvar
 		v = stdlib_strided_dmediansorted( len, x, 1 );
 		if ( v != v ) {
 			printf( "should not return NaN\n" );
@@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) {
 	return elapsed;
 }
 
+/**
+* Runs a benchmark.
+*
+* @param iterations   number of iterations
+* @param len          array length
+* @return             elapsed time in seconds
+*/
+static double benchmark2( int iterations, int len ) {
+	double elapsed;
+	double x[ len ];
+	double v;
+	double t;
+	int i;
+
+	for ( i = 0; i < len; i++ ) {
+		x[ i ] = i;
+	}
+	v = 0.0;
+	t = tic();
+	for ( i = 0; i < iterations; i++ ) {
+		// cppcheck-suppress uninitvar
+		v = stdlib_strided_dmediansorted_ndarray( len, x, 1, 0 );
+		if ( v != v ) {
+			printf( "should not return NaN\n" );
+			break;
+		}
+	}
+	elapsed = tic() - t;
+	if ( v != v ) {
+		printf( "should not return NaN\n" );
+	}
+	return elapsed;
+}
+
 /**
 * Main execution sequence.
 */
@@ -142,7 +177,18 @@ int main( void ) {
 		for ( j = 0; j < REPEATS; j++ ) {
 			count += 1;
 			printf( "# c::%s:len=%d\n", NAME, len );
-			elapsed = benchmark( iter, len );
+			elapsed = benchmark1( iter, len );
+			print_results( iter, elapsed );
+			printf( "ok %d benchmark finished\n", count );
+		}
+	}
+	for ( i = MIN; i <= MAX; i++ ) {
+		len = pow( 10, i );
+		iter = ITERATIONS / pow( 10, i-1 );
+		for ( j = 0; j < REPEATS; j++ ) {
+			count += 1;
+			printf( "# c::%s:ndarray:len=%d\n", NAME, len );
+			elapsed = benchmark2( iter, len );
 			print_results( iter, elapsed );
 			printf( "ok %d benchmark finished\n", count );
 		}
diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dmediansorted/docs/repl.txt
index fd26c4058719..df46c4b439ae 100644
--- a/lib/node_modules/@stdlib/stats/base/dmediansorted/docs/repl.txt
+++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/docs/repl.txt
@@ -1,13 +1,13 @@
 
-{{alias}}( N, x, stride )
+{{alias}}( N, x, strideX )
     Computes the median value of a sorted double-precision floating-point
     strided array.
 
     The input strided array must be sorted in either strictly ascending or
     descending order.
 
-    The `N` and `stride` parameters determine which elements in `x` are accessed
-    at runtime.
+    The `N` and stride parameters determine which elements in the strided array
+    are accessed at runtime.
 
     Indexing is relative to the first index. To introduce an offset, use a typed
     array view.
@@ -22,8 +22,8 @@
     x: Float64Array
         Sorted input array.
 
-    stride: integer
-        Index increment.
+    strideX: integer
+        Stride Length.
 
     Returns
     -------
@@ -37,20 +37,19 @@
     > {{alias}}( x.length, x, 1 )
     2.0
 
-    // Using `N` and `stride` parameters:
+    // Using `N` and stride parameters:
     > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > {{alias}}( N, x, 2 )
+    > {{alias}}( 3, x, 2 )
     1.0
 
     // Using view offsets:
     > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );
     > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );
-    > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );
-    > {{alias}}( N, x1, 2 )
+    > {{alias}}( 3, x1, 2 )
     2.0
 
-{{alias}}.ndarray( N, x, stride, offset )
+
+{{alias}}.ndarray( N, x, strideX, offsetX )
     Computes the median value of a sorted double-precision floating-point
     strided array using alternative indexing semantics.
 
@@ -66,10 +65,10 @@
     x: Float64Array
         Sorted input array.
 
-    stride: integer
-        Index increment.
+    strideX: integer
+        Stride Length.
 
-    offset: integer
+    offsetX: integer
         Starting index.
 
     Returns
@@ -86,8 +85,7 @@
 
     // Using offset parameter:
     > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > {{alias}}.ndarray( N, x, 2, 1 )
+    > {{alias}}.ndarray( 3, x, 2, 1 )
     2.0
 
     See Also
diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dmediansorted/docs/types/index.d.ts
index b05f9ba8b8da..e5711bd766c1 100644
--- a/lib/node_modules/@stdlib/stats/base/dmediansorted/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/docs/types/index.d.ts
@@ -27,7 +27,7 @@ interface Routine {
 	*
 	* @param N - number of indexed elements
 	* @param x - sorted input array
-	* @param stride - stride length
+	* @param strideX - stride length
 	* @returns median value
 	*
 	* @example
@@ -38,15 +38,15 @@ interface Routine {
 	* var v = dmediansorted( x.length, x, 1 );
 	* // returns 2.0
 	*/
-	( N: number, x: Float64Array, stride: number ): number;
+	( N: number, x: Float64Array, strideX: number ): number;
 
 	/**
 	* Computes the median value of a sorted double-precision floating-point strided array using alternative indexing semantics.
 	*
 	* @param N - number of indexed elements
 	* @param x - sorted input array
-	* @param stride - stride length
-	* @param offset - starting index
+	* @param strideX - stride length
+	* @param offsetX - starting index
 	* @returns median value
 	*
 	* @example
@@ -57,7 +57,7 @@ interface Routine {
 	* var v = dmediansorted.ndarray( x.length, x, 1, 0 );
 	* // returns 2.0
 	*/
-	ndarray( N: number, x: Float64Array, stride: number, offset: number ): number;
+	ndarray( N: number, x: Float64Array, strideX: number, offsetX: number ): number;
 }
 
 /**
@@ -65,7 +65,7 @@ interface Routine {
 *
 * @param N - number of indexed elements
 * @param x - sorted input array
-* @param stride - stride length
+* @param strideX - stride length
 * @returns median value
 *
 * @example
diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dmediansorted/examples/c/example.c
index 42339fe8638d..feabfd7f96f7 100644
--- a/lib/node_modules/@stdlib/stats/base/dmediansorted/examples/c/example.c
+++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/examples/c/example.c
@@ -17,21 +17,20 @@
 */
 
 #include "stdlib/stats/base/dmediansorted.h"
-#include <stdint.h>
 #include <stdio.h>
 
 int main( void ) {
 	// Create a strided array:
-	double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 };
+	const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 };
 
 	// Specify the number of elements:
-	int64_t N = 4;
+	const int N = 4;
 
 	// Specify the stride length:
-	int64_t stride = 2;
+	const int strideX = 2;
 
 	// Compute the median value:
-	double v = stdlib_strided_dmediansorted( N, x, stride );
+	double v = stdlib_strided_dmediansorted( N, x, strideX );
 
 	// Print the result:
 	printf( "median: %lf\n", v );
diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/examples/index.js b/lib/node_modules/@stdlib/stats/base/dmediansorted/examples/index.js
index 405145bb3c3d..3dcbbbecf3ef 100644
--- a/lib/node_modules/@stdlib/stats/base/dmediansorted/examples/index.js
+++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/examples/index.js
@@ -18,16 +18,13 @@
 
 'use strict';
 
-var Float64Array = require( '@stdlib/array/float64' );
+var linspace = require( '@stdlib/array/linspace' );
 var dmediansorted = require( './../lib' );
 
-var x;
-var i;
-
-x = new Float64Array( 10 );
-for ( i = 0; i < x.length; i++ ) {
-	x[ i ] = i - 5.0;
-}
+var options = {
+	'dtype': 'float64'
+};
+var x = linspace( -5.0, 5.0, 10, options );
 console.log( x );
 
 var v = dmediansorted( x.length, x, 1 );
diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/include.gypi b/lib/node_modules/@stdlib/stats/base/dmediansorted/include.gypi
index 868c5c12e852..26476a8c2655 100644
--- a/lib/node_modules/@stdlib/stats/base/dmediansorted/include.gypi
+++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/include.gypi
@@ -36,7 +36,7 @@
 
     # Source files:
     'src_files': [
-      '<(src_dir)/addon.cpp',
+      '<(src_dir)/addon.c',
       '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).src; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
     ],
 
diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/include/stdlib/stats/base/dmediansorted.h b/lib/node_modules/@stdlib/stats/base/dmediansorted/include/stdlib/stats/base/dmediansorted.h
index 2c4f727807f1..1e27651ebb52 100644
--- a/lib/node_modules/@stdlib/stats/base/dmediansorted/include/stdlib/stats/base/dmediansorted.h
+++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/include/stdlib/stats/base/dmediansorted.h
@@ -19,7 +19,7 @@
 #ifndef STDLIB_STATS_BASE_DMEDIANSORTED_H
 #define STDLIB_STATS_BASE_DMEDIANSORTED_H
 
-#include <stdint.h>
+#include "stdlib/blas/base/shared.h"
 
 /*
 * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler.
@@ -31,7 +31,12 @@ extern "C" {
 /**
 * Computes the median value of a sorted double-precision floating-point strided array.
 */
-double stdlib_strided_dmediansorted( const int64_t N, const double *X, const int64_t stride );
+double API_SUFFIX(stdlib_strided_dmediansorted)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX );
+
+/**
+* Computes the median value of a sorted double-precision floating-point strided array using alternative indexing semantics.
+*/
+double API_SUFFIX(stdlib_strided_dmediansorted_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX );
 
 #ifdef __cplusplus
 }
diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/lib/dmediansorted.js b/lib/node_modules/@stdlib/stats/base/dmediansorted/lib/dmediansorted.js
index e14e0db0fe2c..b4bfee2cfa35 100644
--- a/lib/node_modules/@stdlib/stats/base/dmediansorted/lib/dmediansorted.js
+++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/lib/dmediansorted.js
@@ -20,7 +20,8 @@
 
 // MODULES //
 
-var floor = require( '@stdlib/math/base/special/floor' );
+var stride2offset = require( '@stdlib/strided/base/stride2offset' );
+var ndarray = require( './ndarray.js' );
 
 
 // MAIN //
@@ -30,7 +31,7 @@ var floor = require( '@stdlib/math/base/special/floor' );
 *
 * @param {PositiveInteger} N - number of indexed elements
 * @param {Float64Array} x - sorted input array
-* @param {integer} stride - stride length
+* @param {integer} strideX - stride length
 * @returns {number} median value
 *
 * @example
@@ -41,27 +42,8 @@ var floor = require( '@stdlib/math/base/special/floor' );
 * var v = dmediansorted( x.length, x, 1 );
 * // returns 2.0
 */
-function dmediansorted( N, x, stride ) {
-	var offset;
-	var n;
-	var m;
-
-	if ( N <= 0 ) {
-		return NaN;
-	}
-	if ( stride < 0 ) {
-		offset = (1-N) * stride;
-	} else {
-		offset = 0;
-	}
-	n = N / 2;
-	m = floor( n );
-	if ( n === m ) {
-		// Even number of elements...
-		return ( x[ offset+(m*stride) ] + x[ offset+((m-1)*stride) ] ) / 2.0;
-	}
-	// Odd number of elements...
-	return x[ offset+(m*stride) ];
+function dmediansorted( N, x, strideX ) {
+	return ndarray( N, x, strideX, stride2offset( N, strideX ) );
 }
 
 
diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/lib/dmediansorted.native.js b/lib/node_modules/@stdlib/stats/base/dmediansorted/lib/dmediansorted.native.js
index 70e8bbae3ca2..38fdc86ea147 100644
--- a/lib/node_modules/@stdlib/stats/base/dmediansorted/lib/dmediansorted.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/lib/dmediansorted.native.js
@@ -30,7 +30,7 @@ var addon = require( './../src/addon.node' );
 *
 * @param {PositiveInteger} N - number of indexed elements
 * @param {Float64Array} x - sorted input array
-* @param {integer} stride - stride length
+* @param {integer} strideX - stride length
 * @returns {number} median value
 *
 * @example
@@ -41,8 +41,8 @@ var addon = require( './../src/addon.node' );
 * var v = dmediansorted( x.length, x, 1 );
 * // returns 2.0
 */
-function dmediansorted( N, x, stride ) {
-	return addon( N, x, stride );
+function dmediansorted( N, x, strideX ) {
+	return addon( N, x, strideX );
 }
 
 
diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/lib/index.js b/lib/node_modules/@stdlib/stats/base/dmediansorted/lib/index.js
index 1af139ee2952..b2c68a1171ac 100644
--- a/lib/node_modules/@stdlib/stats/base/dmediansorted/lib/index.js
+++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/lib/index.js
@@ -34,13 +34,11 @@
 *
 * @example
 * var Float64Array = require( '@stdlib/array/float64' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 * var dmediansorted = require( '@stdlib/stats/base/dmediansorted' );
 *
 * var x = new Float64Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
-* var N = floor( x.length / 2 );
 *
-* var v = dmediansorted.ndarray( N, x, 2, 1 );
+* var v = dmediansorted.ndarray( 4, x, 2, 1 );
 * // returns 0.0
 */
 
diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/dmediansorted/lib/ndarray.js
index 44227e8ef762..06c316be96aa 100644
--- a/lib/node_modules/@stdlib/stats/base/dmediansorted/lib/ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/lib/ndarray.js
@@ -30,21 +30,19 @@ var floor = require( '@stdlib/math/base/special/floor' );
 *
 * @param {PositiveInteger} N - number of indexed elements
 * @param {Float64Array} x - sorted input array
-* @param {integer} stride - stride length
-* @param {NonNegativeInteger} offset - starting index
+* @param {integer} strideX - stride length
+* @param {NonNegativeInteger} offsetX - starting index
 * @returns {number} median value
 *
 * @example
 * var Float64Array = require( '@stdlib/array/float64' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 *
 * var x = new Float64Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
-* var N = floor( x.length / 2 );
 *
-* var v = dmediansorted( N, x, 2, 1 );
+* var v = dmediansorted( 4, x, 2, 1 );
 * // returns 0.0
 */
-function dmediansorted( N, x, stride, offset ) {
+function dmediansorted( N, x, strideX, offsetX ) {
 	var n;
 	var m;
 
@@ -55,10 +53,10 @@ function dmediansorted( N, x, stride, offset ) {
 	m = floor( n );
 	if ( n === m ) {
 		// Even number of elements...
-		return ( x[ offset+(m*stride) ] + x[ offset+((m-1)*stride) ] ) / 2.0;
+		return ( x[ offsetX+(m*strideX) ] + x[ offsetX+((m-1)*strideX) ] ) / 2.0; // eslint-disable-line max-len
 	}
 	// Odd number of elements...
-	return x[ offset+(m*stride) ];
+	return x[ offsetX+(m*strideX) ];
 }
 
 
diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmediansorted/lib/ndarray.native.js
index 382a5046d062..4d196eeae4d2 100644
--- a/lib/node_modules/@stdlib/stats/base/dmediansorted/lib/ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/lib/ndarray.native.js
@@ -20,8 +20,7 @@
 
 // MODULES //
 
-var Float64Array = require( '@stdlib/array/float64' );
-var addon = require( './dmediansorted.native.js' );
+var addon = require( './../src/addon.node' );
 
 
 // MAIN //
@@ -31,27 +30,20 @@ var addon = require( './dmediansorted.native.js' );
 *
 * @param {PositiveInteger} N - number of indexed elements
 * @param {Float64Array} x - sorted input array
-* @param {integer} stride - stride length
-* @param {NonNegativeInteger} offset - starting index
+* @param {integer} strideX - stride length
+* @param {NonNegativeInteger} offsetX - starting index
 * @returns {number} median value
 *
 * @example
 * var Float64Array = require( '@stdlib/array/float64' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 *
 * var x = new Float64Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
-* var N = floor( x.length / 2 );
 *
-* var v = dmediansorted( N, x, 2, 1 );
+* var v = dmediansorted( 4, x, 2, 1 );
 * // returns 0.0
 */
-function dmediansorted( N, x, stride, offset ) {
-	var view;
-	if ( stride < 0 ) {
-		offset += (N-1) * stride;
-	}
-	view = new Float64Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len
-	return addon( N, view, stride );
+function dmediansorted( N, x, strideX, offsetX ) {
+	return addon.ndarray( N, x, strideX, offsetX );
 }
 
 
diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/manifest.json b/lib/node_modules/@stdlib/stats/base/dmediansorted/manifest.json
index 24ca1524a6d3..99aaf0c4da72 100644
--- a/lib/node_modules/@stdlib/stats/base/dmediansorted/manifest.json
+++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/manifest.json
@@ -1,5 +1,8 @@
 {
-  "options": {},
+  "options": {
+    "task": "build",
+    "wasm": false
+  },
   "fields": [
     {
       "field": "src",
@@ -24,17 +27,73 @@
   ],
   "confs": [
     {
+      "task": "build",
+      "wasm": false,
       "src": [
-        "./src/dmediansorted.c"
+        "./src/main.c"
       ],
       "include": [
         "./include"
       ],
-      "libraries": [
-        "-lm"
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset",
+        "@stdlib/napi/export",
+        "@stdlib/napi/argv",
+        "@stdlib/napi/argv-int64",
+        "@stdlib/napi/argv-strided-float64array",
+        "@stdlib/napi/create-double"
+      ]
+    },
+    {
+      "task": "benchmark",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset"
+      ]
+    },
+    {
+      "task": "examples",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset"
+      ]
+    },
+    {
+      "task": "",
+      "wasm": true,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
       ],
+      "libraries": [],
       "libpath": [],
-      "dependencies": []
+      "dependencies": [
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset"
+      ]
     }
   ]
 }
diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/src/addon.c b/lib/node_modules/@stdlib/stats/base/dmediansorted/src/addon.c
new file mode 100644
index 000000000000..9ff9a1338187
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/src/addon.c
@@ -0,0 +1,60 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/dmediansorted.h"
+#include "stdlib/napi/export.h"
+#include "stdlib/napi/argv.h"
+#include "stdlib/napi/argv_int64.h"
+#include "stdlib/napi/argv_strided_float64array.h"
+#include "stdlib/napi/create_double.h"
+#include <node_api.h>
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 3 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dmediansorted( N, X, strideX ), v );
+	return v;
+}
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon_method( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 4 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 );
+	STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dmediansorted_ndarray( N, X, strideX, offsetX ), v );
+	return v;
+}
+
+STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method )
diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/dmediansorted/src/addon.cpp
deleted file mode 100644
index 543b559d8533..000000000000
--- a/lib/node_modules/@stdlib/stats/base/dmediansorted/src/addon.cpp
+++ /dev/null
@@ -1,117 +0,0 @@
-/**
-* @license Apache-2.0
-*
-* Copyright (c) 2020 The Stdlib Authors.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-*    http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-
-#include "stdlib/stats/base/dmediansorted.h"
-#include <node_api.h>
-#include <stdint.h>
-#include <stdlib.h>
-#include <stdbool.h>
-#include <assert.h>
-
-/**
-* Add-on namespace.
-*/
-namespace stdlib_stats_base_dmediansorted {
-
-	/**
-	* Computes the median value of a sorted double-precision floating-point strided array.
-	*
-	* ## Notes
-	*
-	* -   When called from JavaScript, the function expects three arguments:
-	*
-	*     -   `N`: number of indexed elements
-	*     -   `X`: sorted input array
-	*     -   `stride`: stride length
-	*/
-	napi_value node_dmediansorted( napi_env env, napi_callback_info info ) {
-		napi_status status;
-
-		size_t argc = 3;
-		napi_value argv[ 3 ];
-		status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr );
-		assert( status == napi_ok );
-
-		if ( argc < 3 ) {
-			napi_throw_error( env, nullptr, "invalid invocation. Must provide 3 arguments." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype0;
-		status = napi_typeof( env, argv[ 0 ], &vtype0 );
-		assert( status == napi_ok );
-		if ( vtype0 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." );
-			return nullptr;
-		}
-
-		bool res;
-		status = napi_is_typedarray( env, argv[ 1 ], &res );
-		assert( status == napi_ok );
-		if ( res == false ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float64Array." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype2;
-		status = napi_typeof( env, argv[ 2 ], &vtype2 );
-		assert( status == napi_ok );
-		if ( vtype2 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." );
-			return nullptr;
-		}
-
-		int64_t N;
-		status = napi_get_value_int64( env, argv[ 0 ], &N );
-		assert( status == napi_ok );
-
-		int64_t stride;
-		status = napi_get_value_int64( env, argv[ 2 ], &stride );
-		assert( status == napi_ok );
-
-		napi_typedarray_type vtype1;
-		size_t xlen;
-		void *X;
-		status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr );
-		assert( status == napi_ok );
-		if ( vtype1 != napi_float64_array ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float64Array." );
-			return nullptr;
-		}
-		if ( (N-1)*llabs(stride) >= (int64_t)xlen ) {
-			napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." );
-			return nullptr;
-		}
-
-		napi_value v;
-		status = napi_create_double( env, stdlib_strided_dmediansorted( N, (double *)X, stride ), &v );
-		assert( status == napi_ok );
-
-		return v;
-	}
-
-	napi_value Init( napi_env env, napi_value exports ) {
-		napi_status status;
-		napi_value fcn;
-		status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_dmediansorted, NULL, &fcn );
-		assert( status == napi_ok );
-		return fcn;
-	}
-
-	NAPI_MODULE( NODE_GYP_MODULE_NAME, Init )
-} // end namespace stdlib_stats_base_dmediansorted
diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/src/dmediansorted.c b/lib/node_modules/@stdlib/stats/base/dmediansorted/src/dmediansorted.c
deleted file mode 100644
index ca291663021b..000000000000
--- a/lib/node_modules/@stdlib/stats/base/dmediansorted/src/dmediansorted.c
+++ /dev/null
@@ -1,49 +0,0 @@
-/**
-* @license Apache-2.0
-*
-* Copyright (c) 2020 The Stdlib Authors.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-*    http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-
-#include "stdlib/stats/base/dmediansorted.h"
-#include <stdint.h>
-
-/**
-* Computes the median value of a sorted double-precision floating-point strided array.
-*
-* @param N       number of indexed elements
-* @param X       sorted input array
-* @param stride  stride length
-* @return        output value
-*/
-double stdlib_strided_dmediansorted( const int64_t N, const double *X, const int64_t stride ) {
-	int64_t offset;
-	int64_t n;
-
-	if ( N <= 0 ) {
-		return 0.0/0.0; // NaN
-	}
-	if ( stride < 0 ) {
-		offset = (1-N) * stride;
-	} else {
-		offset = 0;
-	}
-	n = N >> 1;
-	if ( N & 1 ) {
-		// Odd number of elements...
-		return X[ offset+(n*stride) ];
-	}
-	// Even number of elements...
-	return ( X[ offset+(n*stride) ] + X[ offset+((n-1)*stride) ] ) / 2.0;
-}
diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/src/main.c b/lib/node_modules/@stdlib/stats/base/dmediansorted/src/main.c
new file mode 100644
index 000000000000..b19689cc85bf
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/src/main.c
@@ -0,0 +1,58 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/dmediansorted.h"
+#include "stdlib/blas/base/shared.h"
+#include "stdlib/strided/base/stride2offset.h"
+
+/**
+* Computes the median value of a sorted double-precision floating-point strided array.
+*
+* @param N        number of indexed elements
+* @param X        sorted input array
+* @param strideX  stride length
+* @return         output value
+*/
+double API_SUFFIX(stdlib_strided_dmediansorted)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ) {
+	const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX );
+	return API_SUFFIX(stdlib_strided_dmediansorted_ndarray)( N, X, strideX, ox );
+}
+
+/**
+* Computes the median value of a sorted double-precision floating-point strided array using alternative indexing semantics.
+*
+* @param N        number of indexed elements
+* @param X        sorted input array
+* @param strideX  stride length
+* @param offsetX  starting index for X
+* @return         output value
+*/
+double API_SUFFIX(stdlib_strided_dmediansorted_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) {
+	CBLAS_INT n;
+
+	if ( N <= 0 ) {
+		return 0.0 / 0.0; // NaN
+	}
+	n = N >> 1;
+	if ( N & 1 ) {
+		// Odd number of elements...
+		return X[ offsetX+(n*strideX)  ];
+	}
+	// Even number of elements...
+	return ( X[ offsetX+(n*strideX) ] + X[ offsetX+((n-1)*strideX) ] ) / 2.0;
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/test/test.dmediansorted.js b/lib/node_modules/@stdlib/stats/base/dmediansorted/test/test.dmediansorted.js
index b50972545782..3a34bce746bd 100644
--- a/lib/node_modules/@stdlib/stats/base/dmediansorted/test/test.dmediansorted.js
+++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/test/test.dmediansorted.js
@@ -21,7 +21,6 @@
 // MODULES //
 
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' );
 var Float64Array = require( '@stdlib/array/float64' );
@@ -120,7 +119,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 });
 
 tape( 'the function supports a `stride` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -135,15 +133,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) {
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = dmediansorted( N, x, 2 );
+	v = dmediansorted( 4, x, 2 );
 
 	t.strictEqual( v, 2.5, 'returns expected value' );
 	t.end();
 });
 
 tape( 'the function supports a negative `stride` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -158,8 +154,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t )
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = dmediansorted( N, x, -2 );
+	v = dmediansorted( 4, x, -2 );
 
 	t.strictEqual( v, 2.5, 'returns expected value' );
 	t.end();
@@ -180,7 +175,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f
 tape( 'the function supports view offsets', function test( t ) {
 	var x0;
 	var x1;
-	var N;
 	var v;
 
 	x0 = new Float64Array([
@@ -196,9 +190,8 @@ tape( 'the function supports view offsets', function test( t ) {
 	]);
 
 	x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
-	N = floor(x1.length / 2);
 
-	v = dmediansorted( N, x1, 2 );
+	v = dmediansorted( 4, x1, 2 );
 	t.strictEqual( v, 2.5, 'returns expected value' );
 
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/test/test.dmediansorted.native.js b/lib/node_modules/@stdlib/stats/base/dmediansorted/test/test.dmediansorted.native.js
index ef6ef5d73c57..a4d235fe97a1 100644
--- a/lib/node_modules/@stdlib/stats/base/dmediansorted/test/test.dmediansorted.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/test/test.dmediansorted.native.js
@@ -22,7 +22,6 @@
 
 var resolve = require( 'path' ).resolve;
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' );
 var Float64Array = require( '@stdlib/array/float64' );
@@ -129,7 +128,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 });
 
 tape( 'the function supports a `stride` parameter', opts, function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -144,15 +142,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) {
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = dmediansorted( N, x, 2 );
+	v = dmediansorted( 4, x, 2 );
 
 	t.strictEqual( v, 2.5, 'returns expected value' );
 	t.end();
 });
 
 tape( 'the function supports a negative `stride` parameter', opts, function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -167,8 +163,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = dmediansorted( N, x, -2 );
+	v = dmediansorted( 4, x, -2 );
 
 	t.strictEqual( v, 2.5, 'returns expected value' );
 	t.end();
@@ -189,7 +184,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f
 tape( 'the function supports view offsets', opts, function test( t ) {
 	var x0;
 	var x1;
-	var N;
 	var v;
 
 	x0 = new Float64Array([
@@ -205,9 +199,8 @@ tape( 'the function supports view offsets', opts, function test( t ) {
 	]);
 
 	x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
-	N = floor(x1.length / 2);
 
-	v = dmediansorted( N, x1, 2 );
+	v = dmediansorted( 4, x1, 2 );
 	t.strictEqual( v, 2.5, 'returns expected value' );
 
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dmediansorted/test/test.ndarray.js
index 4f876c6ee511..63ed480c3d3f 100644
--- a/lib/node_modules/@stdlib/stats/base/dmediansorted/test/test.ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/test/test.ndarray.js
@@ -21,7 +21,6 @@
 // MODULES //
 
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' );
 var Float64Array = require( '@stdlib/array/float64' );
@@ -120,7 +119,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 });
 
 tape( 'the function supports a `stride` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -135,15 +133,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) {
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = dmediansorted( N, x, 2, 0 );
+	v = dmediansorted( 4, x, 2, 0 );
 
 	t.strictEqual( v, 2.5, 'returns expected value' );
 	t.end();
 });
 
 tape( 'the function supports a negative `stride` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -158,8 +154,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t )
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = dmediansorted( N, x, -2, 6 );
+	v = dmediansorted( 4, x, -2, 6 );
 
 	t.strictEqual( v, 2.5, 'returns expected value' );
 	t.end();
@@ -178,7 +173,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f
 });
 
 tape( 'the function supports an `offset` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -192,9 +186,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) {
 		3.0,
 		4.0   // 3
 	]);
-	N = floor( x.length / 2 );
 
-	v = dmediansorted( N, x, 2, 1 );
+	v = dmediansorted( 4, x, 2, 1 );
 	t.strictEqual( v, 2.5, 'returns expected value' );
 
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/dmediansorted/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmediansorted/test/test.ndarray.native.js
index 90c791eaac10..ecd1bc06391d 100644
--- a/lib/node_modules/@stdlib/stats/base/dmediansorted/test/test.ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dmediansorted/test/test.ndarray.native.js
@@ -22,7 +22,6 @@
 
 var resolve = require( 'path' ).resolve;
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' );
 var Float64Array = require( '@stdlib/array/float64' );
@@ -129,7 +128,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 });
 
 tape( 'the function supports a `stride` parameter', opts, function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -144,15 +142,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) {
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = dmediansorted( N, x, 2, 0 );
+	v = dmediansorted( 4, x, 2, 0 );
 
 	t.strictEqual( v, 2.5, 'returns expected value' );
 	t.end();
 });
 
 tape( 'the function supports a negative `stride` parameter', opts, function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -167,8 +163,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = dmediansorted( N, x, -2, 6 );
+	v = dmediansorted( 4, x, -2, 6 );
 
 	t.strictEqual( v, 2.5, 'returns expected value' );
 	t.end();
@@ -187,7 +182,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f
 });
 
 tape( 'the function supports an `offset` parameter', opts, function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -201,9 +195,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) {
 		3.0,
 		4.0   // 3
 	]);
-	N = floor( x.length / 2 );
 
-	v = dmediansorted( N, x, 2, 1 );
+	v = dmediansorted( 4, x, 2, 1 );
 	t.strictEqual( v, 2.5, 'returns expected value' );
 
 	t.end();

From ec70be139de54dd11bb9a32e5b15c35cc80cf56d Mon Sep 17 00:00:00 2001
From: Aayush Khanna <96649223+aayush0325@users.noreply.github.com>
Date: Fri, 3 Jan 2025 01:59:11 +0530
Subject: [PATCH 20/87] feat: add C ndarray interface and refactor
 implementation for `stats/base/smaxsorted`

PR-URL: https://github.com/stdlib-js/stdlib/pull/4481
Reviewed-by: Athan Reines <kgryte@gmail.com>
Co-authored-by: stdlib-bot <82920195+stdlib-bot@users.noreply.github.com>
---
 .../@stdlib/stats/base/smaxsorted/README.md   | 162 ++++++++++++++----
 .../base/smaxsorted/benchmark/benchmark.js    |  17 +-
 .../smaxsorted/benchmark/benchmark.native.js  |  13 +-
 .../smaxsorted/benchmark/benchmark.ndarray.js |  17 +-
 .../benchmark/benchmark.ndarray.native.js     |  13 +-
 .../smaxsorted/benchmark/c/benchmark.length.c |  50 +++++-
 .../stats/base/smaxsorted/docs/repl.txt       |  32 ++--
 .../base/smaxsorted/docs/types/index.d.ts     |  12 +-
 .../base/smaxsorted/examples/c/example.c      |   9 +-
 .../stats/base/smaxsorted/examples/index.js   |  13 +-
 .../stats/base/smaxsorted/include.gypi        |   2 +-
 .../include/stdlib/stats/base/smaxsorted.h    |   9 +-
 .../stats/base/smaxsorted/lib/index.js        |   7 +-
 .../stats/base/smaxsorted/lib/ndarray.js      |  16 +-
 .../base/smaxsorted/lib/ndarray.native.js     |  20 +--
 .../stats/base/smaxsorted/lib/smaxsorted.js   |  41 +----
 .../base/smaxsorted/lib/smaxsorted.native.js  |   9 +-
 .../stats/base/smaxsorted/manifest.json       |  74 +++++++-
 .../@stdlib/stats/base/smaxsorted/src/addon.c |  60 +++++++
 .../stats/base/smaxsorted/src/addon.cpp       | 117 -------------
 .../smaxsorted/src/{smaxsorted.c => main.c}   |  38 ++--
 .../base/smaxsorted/test/test.ndarray.js      |  17 +-
 .../smaxsorted/test/test.ndarray.native.js    |  17 +-
 .../base/smaxsorted/test/test.smaxsorted.js   |  13 +-
 .../smaxsorted/test/test.smaxsorted.native.js |  13 +-
 25 files changed, 440 insertions(+), 351 deletions(-)
 create mode 100644 lib/node_modules/@stdlib/stats/base/smaxsorted/src/addon.c
 delete mode 100644 lib/node_modules/@stdlib/stats/base/smaxsorted/src/addon.cpp
 rename lib/node_modules/@stdlib/stats/base/smaxsorted/src/{smaxsorted.c => main.c} (54%)

diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/README.md b/lib/node_modules/@stdlib/stats/base/smaxsorted/README.md
index de8c418d00a0..f20f04d3a85d 100644
--- a/lib/node_modules/@stdlib/stats/base/smaxsorted/README.md
+++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/README.md
@@ -44,15 +44,13 @@ Computes the maximum value of a sorted single-precision floating-point strided a
 var Float32Array = require( '@stdlib/array/float32' );
 
 var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );
-var N = x.length;
 
-var v = smaxsorted( N, x, 1 );
+var v = smaxsorted( x.length, x, 1 );
 // returns 3.0
 
 x = new Float32Array( [ 3.0, 2.0, 1.0 ] );
-N = x.length;
 
-v = smaxsorted( N, x, 1 );
+v = smaxsorted( x.length, x, 1 );
 // returns 3.0
 ```
 
@@ -60,18 +58,16 @@ The function has the following parameters:
 
 -   **N**: number of indexed elements.
 -   **x**: sorted input [`Float32Array`][@stdlib/array/float32].
--   **stride**: index increment for `x`.
+-   **strideX**: stride length for `x`.
 
-The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the maximum value of every other element in `x`,
+The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the maximum value of every other element in `x`,
 
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x = new Float32Array( [ 1.0, 2.0, 2.0, -7.0, 3.0, 3.0, 4.0, 2.0 ] );
-var N = floor( x.length / 2 );
 
-var v = smaxsorted( N, x, 2 );
+var v = smaxsorted( 4, x, 2 );
 // returns 4.0
 ```
 
@@ -81,18 +77,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [
 
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x0 = new Float32Array( [ 2.0, 1.0, 2.0, 2.0, -2.0, 2.0, 3.0, 4.0 ] );
 var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
 
-var N = floor( x0.length / 2 );
-
-var v = smaxsorted( N, x1, 2 );
+var v = smaxsorted( 4, x1, 2 );
 // returns 4.0
 ```
 
-#### smaxsorted.ndarray( N, x, stride, offset )
+#### smaxsorted.ndarray( N, x, strideX, offsetX )
 
 Computes the maximum value of a sorted single-precision floating-point strided array using alternative indexing semantics.
 
@@ -100,26 +93,23 @@ Computes the maximum value of a sorted single-precision floating-point strided a
 var Float32Array = require( '@stdlib/array/float32' );
 
 var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );
-var N = x.length;
 
-var v = smaxsorted.ndarray( N, x, 1, 0 );
+var v = smaxsorted.ndarray( x.length, x, 1, 0 );
 // returns 3.0
 ```
 
 The function has the following additional parameters:
 
--   **offset**: starting index for `x`.
+-   **offsetX**: starting index for `x`.
 
-While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the maximum value for every other value in `x` starting from the second value
+While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the maximum value for every other element in `x` starting from the second element
 
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x = new Float32Array( [ 2.0, 1.0, 2.0, 2.0, -2.0, 2.0, 3.0, 4.0 ] );
-var N = floor( x.length / 2 );
 
-var v = smaxsorted.ndarray( N, x, 2, 1 );
+var v = smaxsorted.ndarray( 4, x, 2, 1 );
 // returns 4.0
 ```
 
@@ -145,16 +135,13 @@ var v = smaxsorted.ndarray( N, x, 2, 1 );
 <!-- eslint no-undef: "error" -->
 
 ```javascript
-var Float32Array = require( '@stdlib/array/float32' );
+var linspace = require( '@stdlib/array/linspace' );
 var smaxsorted = require( '@stdlib/stats/base/smaxsorted' );
 
-var x;
-var i;
-
-x = new Float32Array( 10 );
-for ( i = 0; i < x.length; i++ ) {
-    x[ i ] = i - 5.0;
-}
+var options = {
+    'dtype': 'float32'
+};
+var x = linspace( -5.0, 5.0, 10, options );
 console.log( x );
 
 var v = smaxsorted( x.length, x, 1 );
@@ -165,6 +152,123 @@ console.log( v );
 
 <!-- /.examples -->
 
+<!-- C interface documentation. -->
+
+* * *
+
+<section class="c">
+
+## C APIs
+
+<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<!-- C usage documentation. -->
+
+<section class="usage">
+
+### Usage
+
+```c
+#include "stdlib/stats/base/smaxsorted.h"
+```
+
+#### stdlib_strided_smaxsorted( N, \*X, strideX )
+
+Computes the maximum value of a sorted single-precision floating-point strided array.
+
+```c
+const float x[] = { 1.0f, 2.0f, 3.0f };
+
+float v = stdlib_strided_smaxsorted( 3, x, 1 );
+// returns 3.0f
+```
+
+The function accepts the following arguments:
+
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **X**: `[in] float*` input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+
+```c
+float stdlib_strided_smaxsorted( const CBLAS_INT N, const float *X, const CBLAS_INT strideX );
+```
+
+#### stdlib_strided_smaxsorted_ndarray( N, \*X, strideX, offsetX )
+
+Computes the maximum value of a sorted single-precision floating-point strided array using alternative indexing semantics.
+
+```c
+const float x[] = { 1.0f, 2.0f, 3.0f };
+
+float v = stdlib_strided_smaxsorted_ndarray( 3, x, 1, 0 );
+// returns 3.0f
+```
+
+The function accepts the following arguments:
+
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **X**: `[in] float*` input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+-   **offsetX**: `[in] CBLAS_INT` starting index for `X`.
+
+```c
+float stdlib_strided_smaxsorted_ndarray( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX );
+```
+
+</section>
+
+<!-- /.usage -->
+
+<!-- C API usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="notes">
+
+</section>
+
+<!-- /.notes -->
+
+<!-- C API usage examples. -->
+
+<section class="examples">
+
+### Examples
+
+```c
+#include "stdlib/stats/base/smaxsorted.h"
+#include <stdio.h>
+
+int main( void ) {
+    // Create a strided array:
+    const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f };
+
+    // Specify the number of elements:
+    const int N = 4;
+
+    // Specify the stride length:
+    const int strideX = 2;
+
+    // Compute the maximum value:
+    float v = stdlib_strided_smaxsorted( N, x, strideX );
+
+    // Print the result:
+    printf( "max: %f\n", v );
+}
+```
+
+</section>
+
+<!-- /.examples -->
+
+</section>
+
+<!-- /.c -->
+
 <!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
 
 <section class="related">
diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/smaxsorted/benchmark/benchmark.js
index 3dca715f1b1d..c32e45d8a078 100644
--- a/lib/node_modules/@stdlib/stats/base/smaxsorted/benchmark/benchmark.js
+++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/benchmark/benchmark.js
@@ -22,12 +22,19 @@
 
 var bench = require( '@stdlib/bench' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
+var linspace = require( '@stdlib/array/linspace' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float32Array = require( '@stdlib/array/float32' );
 var pkg = require( './../package.json' ).name;
 var smaxsorted = require( './../lib/smaxsorted.js' );
 
 
+// VARIABLES //
+
+var options = {
+	'dtype': 'float32'
+};
+
+
 // FUNCTIONS //
 
 /**
@@ -38,13 +45,7 @@ var smaxsorted = require( './../lib/smaxsorted.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float32Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = i;
-	}
+	var x = linspace( -len/2, len/2, len, options );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/smaxsorted/benchmark/benchmark.native.js
index 0bed96875d2b..55f8e8fbab28 100644
--- a/lib/node_modules/@stdlib/stats/base/smaxsorted/benchmark/benchmark.native.js
+++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/benchmark/benchmark.native.js
@@ -23,8 +23,8 @@
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
+var linspace = require( '@stdlib/array/linspace' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float32Array = require( '@stdlib/array/float32' );
 var tryRequire = require( '@stdlib/utils/try-require' );
 var pkg = require( './../package.json' ).name;
 
@@ -35,6 +35,9 @@ var smaxsorted = tryRequire( resolve( __dirname, './../lib/smaxsorted.native.js'
 var opts = {
 	'skip': ( smaxsorted instanceof Error )
 };
+var options = {
+	'dtype': 'float32'
+};
 
 
 // FUNCTIONS //
@@ -47,13 +50,7 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float32Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = i;
-	}
+	var x = linspace( -len/2, len/2, len, options );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/smaxsorted/benchmark/benchmark.ndarray.js
index 29673890359b..5fc048214ead 100644
--- a/lib/node_modules/@stdlib/stats/base/smaxsorted/benchmark/benchmark.ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/benchmark/benchmark.ndarray.js
@@ -22,12 +22,19 @@
 
 var bench = require( '@stdlib/bench' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
+var linspace = require( '@stdlib/array/linspace' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float32Array = require( '@stdlib/array/float32' );
 var pkg = require( './../package.json' ).name;
 var smaxsorted = require( './../lib/ndarray.js' );
 
 
+// VARIABLES //
+
+var options = {
+	'dtype': 'float32'
+};
+
+
 // FUNCTIONS //
 
 /**
@@ -38,13 +45,7 @@ var smaxsorted = require( './../lib/ndarray.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float32Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = i;
-	}
+	var x = linspace( -len/2, len/2, len, options );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/smaxsorted/benchmark/benchmark.ndarray.native.js
index a75a00fa15e7..6d9dd607368b 100644
--- a/lib/node_modules/@stdlib/stats/base/smaxsorted/benchmark/benchmark.ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/benchmark/benchmark.ndarray.native.js
@@ -23,8 +23,8 @@
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
+var linspace = require( '@stdlib/array/linspace' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float32Array = require( '@stdlib/array/float32' );
 var tryRequire = require( '@stdlib/utils/try-require' );
 var pkg = require( './../package.json' ).name;
 
@@ -35,6 +35,9 @@ var smaxsorted = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' )
 var opts = {
 	'skip': ( smaxsorted instanceof Error )
 };
+var options = {
+	'dtype': 'float32'
+};
 
 
 // FUNCTIONS //
@@ -47,13 +50,7 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float32Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = i;
-	}
+	var x = linspace( -len/2, len/2, len, options );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/smaxsorted/benchmark/c/benchmark.length.c
index 705880dd25c5..1252ee68d5fc 100644
--- a/lib/node_modules/@stdlib/stats/base/smaxsorted/benchmark/c/benchmark.length.c
+++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/benchmark/c/benchmark.length.c
@@ -94,7 +94,7 @@ static float rand_float( void ) {
 * @param len          array length
 * @return             elapsed time in seconds
 */
-static double benchmark( int iterations, int len ) {
+static double benchmark1( int iterations, int len ) {
 	double elapsed;
 	float x[ len ];
 	float v;
@@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) {
 	v = 0.0f;
 	t = tic();
 	for ( i = 0; i < iterations; i++ ) {
+		// cppcheck-suppress uninitvar
 		v = stdlib_strided_smaxsorted( len, x, 1 );
 		if ( v != v ) {
 			printf( "should not return NaN\n" );
@@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) {
 	return elapsed;
 }
 
+/**
+* Runs a benchmark.
+*
+* @param iterations   number of iterations
+* @param len          array length
+* @return             elapsed time in seconds
+*/
+static double benchmark2( int iterations, int len ) {
+	double elapsed;
+	float x[ len ];
+	float v;
+	double t;
+	int i;
+
+	for ( i = 0; i < len; i++ ) {
+		x[ i ] = i;
+	}
+	v = 0.0f;
+	t = tic();
+	for ( i = 0; i < iterations; i++ ) {
+		// cppcheck-suppress uninitvar
+		v = stdlib_strided_smaxsorted_ndarray( len, x, 1, 0 );
+		if ( v != v ) {
+			printf( "should not return NaN\n" );
+			break;
+		}
+	}
+	elapsed = tic() - t;
+	if ( v != v ) {
+		printf( "should not return NaN\n" );
+	}
+	return elapsed;
+}
+
 /**
 * Main execution sequence.
 */
@@ -142,7 +177,18 @@ int main( void ) {
 		for ( j = 0; j < REPEATS; j++ ) {
 			count += 1;
 			printf( "# c::%s:len=%d\n", NAME, len );
-			elapsed = benchmark( iter, len );
+			elapsed = benchmark1( iter, len );
+			print_results( iter, elapsed );
+			printf( "ok %d benchmark finished\n", count );
+		}
+	}
+	for ( i = MIN; i <= MAX; i++ ) {
+		len = pow( 10, i );
+		iter = ITERATIONS;
+		for ( j = 0; j < REPEATS; j++ ) {
+			count += 1;
+			printf( "# c::%s:ndarray:len=%d\n", NAME, len );
+			elapsed = benchmark2( iter, len );
 			print_results( iter, elapsed );
 			printf( "ok %d benchmark finished\n", count );
 		}
diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/smaxsorted/docs/repl.txt
index 26df328ced96..6f48a99e6b8b 100644
--- a/lib/node_modules/@stdlib/stats/base/smaxsorted/docs/repl.txt
+++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/docs/repl.txt
@@ -1,13 +1,13 @@
 
-{{alias}}( N, x, stride )
+{{alias}}( N, x, strideX )
     Computes the maximum value of a sorted single-precision floating-point
     strided array.
 
     The input strided array must be sorted in either strictly ascending or
     descending order.
 
-    The `N` and `stride` parameters determine which elements in `x` are accessed
-    at runtime.
+    The `N` and stride parameters determine which elements in the strided array
+    are accessed at runtime.
 
     Indexing is relative to the first index. To introduce an offset, use a typed
     array view.
@@ -22,8 +22,8 @@
     x: Float32Array
         Sorted input array.
 
-    stride: integer
-        Index increment.
+    strideX: integer
+        Stride Length.
 
     Returns
     -------
@@ -37,22 +37,19 @@
     > {{alias}}( x.length, x, 1 )
     3.0
 
-    // Using `N` and `stride` parameters:
+    // Using `N` and stride parameters:
     > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > var stride = 2;
-    > {{alias}}( N, x, stride )
+    > {{alias}}( 3, x, 2 )
     2.0
 
     // Using view offsets:
     > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );
     > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );
-    > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );
-    > stride = 2;
-    > {{alias}}( N, x1, stride )
+    > {{alias}}( 3, x1, 2 )
     3.0
 
-{{alias}}.ndarray( N, x, stride, offset )
+
+{{alias}}.ndarray( N, x, strideX, offsetX )
     Computes the maximum value of a sorted single-precision floating-point
     strided array using alternative indexing semantics.
 
@@ -68,10 +65,10 @@
     x: Float32Array
         Sorted input array.
 
-    stride: integer
-        Index increment.
+    strideX: integer
+        Stride Length.
 
-    offset: integer
+    offsetX: integer
         Starting index.
 
     Returns
@@ -88,8 +85,7 @@
 
     // Using offset parameter:
     > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > {{alias}}.ndarray( N, x, 2, 1 )
+    > {{alias}}.ndarray( 3, x, 2, 1 )
     3.0
 
     See Also
diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/smaxsorted/docs/types/index.d.ts
index 1defad939e3f..f9aef7b6f035 100644
--- a/lib/node_modules/@stdlib/stats/base/smaxsorted/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/docs/types/index.d.ts
@@ -27,7 +27,7 @@ interface Routine {
 	*
 	* @param N - number of indexed elements
 	* @param x - sorted input array
-	* @param stride - stride length
+	* @param strideX - stride length
 	* @returns maximum value
 	*
 	* @example
@@ -38,15 +38,15 @@ interface Routine {
 	* var v = smaxsorted( x.length, x, 1 );
 	* // returns 3.0
 	*/
-	( N: number, x: Float32Array, stride: number ): number;
+	( N: number, x: Float32Array, strideX: number ): number;
 
 	/**
 	* Computes the maximum value of a sorted single-precision floating-point strided array using alternative indexing semantics.
 	*
 	* @param N - number of indexed elements
 	* @param x - sorted input array
-	* @param stride - stride length
-	* @param offset - starting index
+	* @param strideX - stride length
+	* @param offsetX - starting index
 	* @returns maximum value
 	*
 	* @example
@@ -57,7 +57,7 @@ interface Routine {
 	* var v = smaxsorted.ndarray( x.length, x, 1, 0 );
 	* // returns 3.0
 	*/
-	ndarray( N: number, x: Float32Array, stride: number, offset: number ): number;
+	ndarray( N: number, x: Float32Array, strideX: number, offsetX: number ): number;
 }
 
 /**
@@ -65,7 +65,7 @@ interface Routine {
 *
 * @param N - number of indexed elements
 * @param x - sorted input array
-* @param stride - stride length
+* @param strideX - stride length
 * @returns maximum value
 *
 * @example
diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/smaxsorted/examples/c/example.c
index f793a54a9fec..1874db46dd28 100644
--- a/lib/node_modules/@stdlib/stats/base/smaxsorted/examples/c/example.c
+++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/examples/c/example.c
@@ -17,21 +17,20 @@
 */
 
 #include "stdlib/stats/base/smaxsorted.h"
-#include <stdint.h>
 #include <stdio.h>
 
 int main( void ) {
 	// Create a strided array:
-	float x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 };
+	const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f };
 
 	// Specify the number of elements:
-	int64_t N = 4;
+	const int N = 4;
 
 	// Specify the stride length:
-	int64_t stride = 2;
+	const int strideX = 2;
 
 	// Compute the maximum value:
-	float v = stdlib_strided_smaxsorted( N, x, stride );
+	float v = stdlib_strided_smaxsorted( N, x, strideX );
 
 	// Print the result:
 	printf( "max: %f\n", v );
diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/examples/index.js b/lib/node_modules/@stdlib/stats/base/smaxsorted/examples/index.js
index 4dc04539dfeb..7c8da27dbea5 100644
--- a/lib/node_modules/@stdlib/stats/base/smaxsorted/examples/index.js
+++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/examples/index.js
@@ -18,16 +18,13 @@
 
 'use strict';
 
-var Float32Array = require( '@stdlib/array/float32' );
+var linspace = require( '@stdlib/array/linspace' );
 var smaxsorted = require( './../lib' );
 
-var x;
-var i;
-
-x = new Float32Array( 10 );
-for ( i = 0; i < x.length; i++ ) {
-	x[ i ] = i - 5.0;
-}
+var options = {
+	'dtype': 'float32'
+};
+var x = linspace( -5.0, 5.0, 10, options );
 console.log( x );
 
 var v = smaxsorted( x.length, x, 1 );
diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/include.gypi b/lib/node_modules/@stdlib/stats/base/smaxsorted/include.gypi
index 868c5c12e852..26476a8c2655 100644
--- a/lib/node_modules/@stdlib/stats/base/smaxsorted/include.gypi
+++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/include.gypi
@@ -36,7 +36,7 @@
 
     # Source files:
     'src_files': [
-      '<(src_dir)/addon.cpp',
+      '<(src_dir)/addon.c',
       '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).src; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
     ],
 
diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/include/stdlib/stats/base/smaxsorted.h b/lib/node_modules/@stdlib/stats/base/smaxsorted/include/stdlib/stats/base/smaxsorted.h
index dcfec8841ab2..a2038a6ab937 100644
--- a/lib/node_modules/@stdlib/stats/base/smaxsorted/include/stdlib/stats/base/smaxsorted.h
+++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/include/stdlib/stats/base/smaxsorted.h
@@ -19,7 +19,7 @@
 #ifndef STDLIB_STATS_BASE_SMAXSORTED_H
 #define STDLIB_STATS_BASE_SMAXSORTED_H
 
-#include <stdint.h>
+#include "stdlib/blas/base/shared.h"
 
 /*
 * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler.
@@ -31,7 +31,12 @@ extern "C" {
 /**
 * Computes the maximum value of a sorted single-precision floating-point strided array.
 */
-float stdlib_strided_smaxsorted( const int64_t N, const float *X, const int64_t stride );
+float API_SUFFIX(stdlib_strided_smaxsorted)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX );
+
+/**
+* Computes the maximum value of a sorted single-precision floating-point strided array using alternative indexing semantics.
+*/
+float API_SUFFIX(stdlib_strided_smaxsorted_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX );
 
 #ifdef __cplusplus
 }
diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/lib/index.js b/lib/node_modules/@stdlib/stats/base/smaxsorted/lib/index.js
index 844e74130978..3ece51392ad3 100644
--- a/lib/node_modules/@stdlib/stats/base/smaxsorted/lib/index.js
+++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/lib/index.js
@@ -28,20 +28,17 @@
 * var smaxsorted = require( '@stdlib/stats/base/smaxsorted' );
 *
 * var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );
-* var N = x.length;
 *
-* var v = smaxsorted( N, x, 1 );
+* var v = smaxsorted( x.length, x, 1 );
 * // returns 3.0
 *
 * @example
 * var Float32Array = require( '@stdlib/array/float32' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 * var smaxsorted = require( '@stdlib/stats/base/smaxsorted' );
 *
 * var x = new Float32Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
-* var N = floor( x.length / 2 );
 *
-* var v = smaxsorted.ndarray( N, x, 2, 1 );
+* var v = smaxsorted.ndarray( 4, x, 2, 1 );
 * // returns 4.0
 */
 
diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/smaxsorted/lib/ndarray.js
index 3c97d9993abf..3e8759112cd7 100644
--- a/lib/node_modules/@stdlib/stats/base/smaxsorted/lib/ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/lib/ndarray.js
@@ -31,32 +31,30 @@ var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' );
 *
 * @param {PositiveInteger} N - number of indexed elements
 * @param {Float32Array} x - sorted input array
-* @param {integer} stride - stride length
-* @param {NonNegativeInteger} offset - starting index
+* @param {integer} strideX - stride length
+* @param {NonNegativeInteger} offsetX - starting index
 * @returns {number} maximum value
 *
 * @example
 * var Float32Array = require( '@stdlib/array/float32' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 *
 * var x = new Float32Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
-* var N = floor( x.length / 2 );
 *
-* var v = smaxsorted( N, x, 2, 1 );
+* var v = smaxsorted( 4, x, 2, 1 );
 * // returns 4.0
 */
-function smaxsorted( N, x, stride, offset ) {
+function smaxsorted( N, x, strideX, offsetX ) {
 	var v1;
 	var v2;
 
 	if ( N <= 0 ) {
 		return NaN;
 	}
-	if ( N === 1 || stride === 0 ) {
+	if ( N === 1 || strideX === 0 ) {
 		return x[ 0 ];
 	}
-	v1 = x[ offset ];
-	v2 = x[ offset + ((N-1)*stride) ];
+	v1 = x[ offsetX ];
+	v2 = x[ offsetX + ((N-1)*strideX) ];
 	if ( isnanf( v1 ) || isnanf( v2 ) ) {
 		return NaN;
 	}
diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/smaxsorted/lib/ndarray.native.js
index e9b33c63c0e3..b332e2ba874d 100644
--- a/lib/node_modules/@stdlib/stats/base/smaxsorted/lib/ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/lib/ndarray.native.js
@@ -20,8 +20,7 @@
 
 // MODULES //
 
-var Float32Array = require( '@stdlib/array/float32' );
-var addon = require( './smaxsorted.native.js' );
+var addon = require( './../src/addon.node' );
 
 
 // MAIN //
@@ -31,27 +30,20 @@ var addon = require( './smaxsorted.native.js' );
 *
 * @param {PositiveInteger} N - number of indexed elements
 * @param {Float32Array} x - sorted input array
-* @param {integer} stride - stride length
-* @param {NonNegativeInteger} offset - starting index
+* @param {integer} strideX - stride length
+* @param {NonNegativeInteger} offsetX - starting index
 * @returns {number} maximum value
 *
 * @example
 * var Float32Array = require( '@stdlib/array/float32' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 *
 * var x = new Float32Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
-* var N = floor( x.length / 2 );
 *
-* var v = smaxsorted( N, x, 2, 1 );
+* var v = smaxsorted( 4, x, 2, 1 );
 * // returns 4.0
 */
-function smaxsorted( N, x, stride, offset ) {
-	var view;
-	if ( stride < 0 ) {
-		offset += (N-1) * stride;
-	}
-	view = new Float32Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len
-	return addon( N, view, stride );
+function smaxsorted( N, x, strideX, offsetX ) {
+	return addon.ndarray( N, x, strideX, offsetX );
 }
 
 
diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/lib/smaxsorted.js b/lib/node_modules/@stdlib/stats/base/smaxsorted/lib/smaxsorted.js
index 9ada465ae2d1..2f2dbcacea2d 100644
--- a/lib/node_modules/@stdlib/stats/base/smaxsorted/lib/smaxsorted.js
+++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/lib/smaxsorted.js
@@ -20,8 +20,8 @@
 
 // MODULES //
 
-var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
-var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' );
+var stride2offset = require( '@stdlib/strided/base/stride2offset' );
+var ndarray = require( './ndarray.js' );
 
 
 // MAIN //
@@ -31,48 +31,19 @@ var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' );
 *
 * @param {PositiveInteger} N - number of indexed elements
 * @param {Float32Array} x - sorted input array
-* @param {integer} stride - stride length
+* @param {integer} strideX - stride length
 * @returns {number} maximum value
 *
 * @example
 * var Float32Array = require( '@stdlib/array/float32' );
 *
 * var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );
-* var N = x.length;
 *
-* var v = smaxsorted( N, x, 1 );
+* var v = smaxsorted( x.length, x, 1 );
 * // returns 3.0
 */
-function smaxsorted( N, x, stride ) {
-	var v1;
-	var v2;
-
-	if ( N <= 0 ) {
-		return NaN;
-	}
-	if ( N === 1 || stride === 0 ) {
-		return x[ 0 ];
-	}
-	if ( stride < 0 ) {
-		v1 = x[ (1-N) * stride ];
-		v2 = x[ 0 ];
-	} else {
-		v1 = x[ 0 ];
-		v2 = x[ (N-1) * stride ];
-	}
-	if ( isnanf( v1 ) || isnanf( v2 ) ) {
-		return NaN;
-	}
-	if ( v1 === v2 ) {
-		if ( isPositiveZerof( v1 ) || isPositiveZerof( v2 ) ) {
-			return 0.0;
-		}
-		return v1;
-	}
-	if ( v1 > v2 ) {
-		return v1;
-	}
-	return v2;
+function smaxsorted( N, x, strideX ) {
+	return ndarray( N, x, strideX, stride2offset( N, strideX ) );
 }
 
 
diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/lib/smaxsorted.native.js b/lib/node_modules/@stdlib/stats/base/smaxsorted/lib/smaxsorted.native.js
index 3d3aa222d40c..ed41c91b40f2 100644
--- a/lib/node_modules/@stdlib/stats/base/smaxsorted/lib/smaxsorted.native.js
+++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/lib/smaxsorted.native.js
@@ -30,20 +30,19 @@ var addon = require( './../src/addon.node' );
 *
 * @param {PositiveInteger} N - number of indexed elements
 * @param {Float32Array} x - sorted input array
-* @param {integer} stride - stride length
+* @param {integer} strideX - stride length
 * @returns {number} maximum value
 *
 * @example
 * var Float32Array = require( '@stdlib/array/float32' );
 *
 * var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );
-* var N = x.length;
 *
-* var v = smaxsorted( N, x, 1 );
+* var v = smaxsorted( x.length, x, 1 );
 * // returns 3.0
 */
-function smaxsorted( N, x, stride ) {
-	return addon( N, x, stride );
+function smaxsorted( N, x, strideX ) {
+	return addon( N, x, strideX );
 }
 
 
diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/manifest.json b/lib/node_modules/@stdlib/stats/base/smaxsorted/manifest.json
index 0584a64076ec..da756d76a756 100644
--- a/lib/node_modules/@stdlib/stats/base/smaxsorted/manifest.json
+++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/manifest.json
@@ -1,5 +1,8 @@
 {
-  "options": {},
+  "options": {
+    "task": "build",
+    "wasm": false
+  },
   "fields": [
     {
       "field": "src",
@@ -24,19 +27,80 @@
   ],
   "confs": [
     {
+      "task": "build",
+      "wasm": false,
       "src": [
-        "./src/smaxsorted.c"
+        "./src/main.c"
       ],
       "include": [
         "./include"
       ],
-      "libraries": [
-        "-lm"
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/math/base/assert/is-nanf",
+        "@stdlib/math/base/assert/is-positive-zerof",
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset",
+        "@stdlib/napi/export",
+        "@stdlib/napi/argv",
+        "@stdlib/napi/argv-int64",
+        "@stdlib/napi/argv-strided-float32array",
+        "@stdlib/napi/create-double"
+      ]
+    },
+    {
+      "task": "benchmark",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/math/base/assert/is-nanf",
+        "@stdlib/math/base/assert/is-positive-zerof",
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset"
+      ]
+    },
+    {
+      "task": "examples",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/math/base/assert/is-nanf",
+        "@stdlib/math/base/assert/is-positive-zerof",
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset"
+      ]
+    },
+    {
+      "task": "",
+      "wasm": true,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
       ],
+      "libraries": [],
       "libpath": [],
       "dependencies": [
         "@stdlib/math/base/assert/is-nanf",
-        "@stdlib/math/base/assert/is-positive-zerof"
+        "@stdlib/math/base/assert/is-positive-zerof",
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset"
       ]
     }
   ]
diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/src/addon.c b/lib/node_modules/@stdlib/stats/base/smaxsorted/src/addon.c
new file mode 100644
index 000000000000..804818917744
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/src/addon.c
@@ -0,0 +1,60 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/smaxsorted.h"
+#include "stdlib/napi/export.h"
+#include "stdlib/napi/argv.h"
+#include "stdlib/napi/argv_int64.h"
+#include "stdlib/napi/argv_strided_float32array.h"
+#include "stdlib/napi/create_double.h"
+#include <node_api.h>
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 3 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_smaxsorted( N, X, strideX ), v );
+	return v;
+}
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon_method( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 4 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 );
+	STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_smaxsorted_ndarray( N, X, strideX, offsetX ), v );
+	return v;
+}
+
+STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method )
diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/smaxsorted/src/addon.cpp
deleted file mode 100644
index 0fa5695cafe5..000000000000
--- a/lib/node_modules/@stdlib/stats/base/smaxsorted/src/addon.cpp
+++ /dev/null
@@ -1,117 +0,0 @@
-/**
-* @license Apache-2.0
-*
-* Copyright (c) 2020 The Stdlib Authors.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-*    http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-
-#include "stdlib/stats/base/smaxsorted.h"
-#include <node_api.h>
-#include <stdint.h>
-#include <stdlib.h>
-#include <stdbool.h>
-#include <assert.h>
-
-/**
-* Add-on namespace.
-*/
-namespace stdlib_stats_base_smaxsorted {
-
-	/**
-	* Computes the maximum value of a sorted single-precision floating-point strided array.
-	*
-	* ## Notes
-	*
-	* -   When called from JavaScript, the function expects three arguments:
-	*
-	*     -   `N`: number of indexed elements
-	*     -   `X`: sorted input array
-	*     -   `stride`: stride length
-	*/
-	napi_value node_smaxsorted( napi_env env, napi_callback_info info ) {
-		napi_status status;
-
-		size_t argc = 3;
-		napi_value argv[ 3 ];
-		status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr );
-		assert( status == napi_ok );
-
-		if ( argc < 3 ) {
-			napi_throw_error( env, nullptr, "invalid invocation. Must provide 3 arguments." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype0;
-		status = napi_typeof( env, argv[ 0 ], &vtype0 );
-		assert( status == napi_ok );
-		if ( vtype0 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." );
-			return nullptr;
-		}
-
-		bool res;
-		status = napi_is_typedarray( env, argv[ 1 ], &res );
-		assert( status == napi_ok );
-		if ( res == false ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype2;
-		status = napi_typeof( env, argv[ 2 ], &vtype2 );
-		assert( status == napi_ok );
-		if ( vtype2 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." );
-			return nullptr;
-		}
-
-		int64_t N;
-		status = napi_get_value_int64( env, argv[ 0 ], &N );
-		assert( status == napi_ok );
-
-		int64_t stride;
-		status = napi_get_value_int64( env, argv[ 2 ], &stride );
-		assert( status == napi_ok );
-
-		napi_typedarray_type vtype1;
-		size_t xlen;
-		void *X;
-		status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr );
-		assert( status == napi_ok );
-		if ( vtype1 != napi_float32_array ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." );
-			return nullptr;
-		}
-		if ( (N-1)*llabs(stride) >= (int64_t)xlen ) {
-			napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." );
-			return nullptr;
-		}
-
-		napi_value v;
-		status = napi_create_double( env, (double)stdlib_strided_smaxsorted( N, (float *)X, stride ), &v );
-		assert( status == napi_ok );
-
-		return v;
-	}
-
-	napi_value Init( napi_env env, napi_value exports ) {
-		napi_status status;
-		napi_value fcn;
-		status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_smaxsorted, NULL, &fcn );
-		assert( status == napi_ok );
-		return fcn;
-	}
-
-	NAPI_MODULE( NODE_GYP_MODULE_NAME, Init )
-} // end namespace stdlib_stats_base_smaxsorted
diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/src/smaxsorted.c b/lib/node_modules/@stdlib/stats/base/smaxsorted/src/main.c
similarity index 54%
rename from lib/node_modules/@stdlib/stats/base/smaxsorted/src/smaxsorted.c
rename to lib/node_modules/@stdlib/stats/base/smaxsorted/src/main.c
index 10fc5f943862..40c85be416fc 100644
--- a/lib/node_modules/@stdlib/stats/base/smaxsorted/src/smaxsorted.c
+++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/src/main.c
@@ -19,33 +19,43 @@
 #include "stdlib/stats/base/smaxsorted.h"
 #include "stdlib/math/base/assert/is_nanf.h"
 #include "stdlib/math/base/assert/is_positive_zerof.h"
-#include <stdint.h>
+#include "stdlib/blas/base/shared.h"
+#include "stdlib/strided/base/stride2offset.h"
 
 /**
 * Computes the maximum value of a sorted single-precision floating-point strided array.
 *
-* @param N       number of indexed elements
-* @param X       sorted input array
-* @param stride  stride length
-* @return        output value
+* @param N        number of indexed elements
+* @param X        sorted input array
+* @param strideX  stride length
+* @return         output value
 */
-float stdlib_strided_smaxsorted( const int64_t N, const float *X, const int64_t stride ) {
+float API_SUFFIX(stdlib_strided_smaxsorted)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX ) {
+	const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX );
+	return API_SUFFIX(stdlib_strided_smaxsorted_ndarray)( N, X, strideX, ox );
+}
+
+/**
+* Computes the maximum value of a sorted single-precision floating-point strided array using alternative indexing semantics.
+*
+* @param N        number of indexed elements
+* @param X        sorted input array
+* @param strideX  stride length
+* @param offsetX  starting index for X
+* @return         output value
+*/
+float API_SUFFIX(stdlib_strided_smaxsorted_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) {
 	float v1;
 	float v2;
 
 	if ( N <= 0 ) {
 		return 0.0f / 0.0f; // NaN
 	}
-	if ( N == 1 || stride == 0 ) {
+	if ( N == 1 || strideX == 0 ) {
 		return X[ 0 ];
 	}
-	if ( stride < 0 ) {
-		v1 = X[ (1-N) * stride ];
-		v2 = X[ 0 ];
-	} else {
-		v1 = X[ 0 ];
-		v2 = X[ (N-1) * stride ];
-	}
+	v1 = X[ offsetX ];
+	v2 = X[ ( ( N - 1 ) * strideX ) + offsetX ];
 	if ( stdlib_base_is_nanf( v1 ) || stdlib_base_is_nanf( v2 ) ) {
 		return 0.0f / 0.0f; // NaN
 	}
diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/smaxsorted/test/test.ndarray.js
index 68347035884d..73712bd07b51 100644
--- a/lib/node_modules/@stdlib/stats/base/smaxsorted/test/test.ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/test/test.ndarray.js
@@ -21,7 +21,6 @@
 // MODULES //
 
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
 var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' );
 var Float32Array = require( '@stdlib/array/float32' );
@@ -116,7 +115,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 });
 
 tape( 'the function supports a `stride` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -125,21 +123,19 @@ tape( 'the function supports a `stride` parameter', function test( t ) {
 		2.0,
 		2.0,  // 1
 		-7.0,
-		3.0, // 2
+		3.0,  // 2
 		3.0,
 		4.0,  // 3
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = smaxsorted( N, x, 2, 0 );
+	v = smaxsorted( 4, x, 2, 0 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
 });
 
 tape( 'the function supports a negative `stride` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -148,14 +144,13 @@ tape( 'the function supports a negative `stride` parameter', function test( t )
 		2.0,
 		2.0,  // 2
 		-7.0,
-		3.0, // 1
+		3.0,  // 1
 		3.0,
 		4.0,  // 0
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = smaxsorted( N, x, -2, 6 );
+	v = smaxsorted( 4, x, -2, 6 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
@@ -174,7 +169,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f
 });
 
 tape( 'the function supports an `offset` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -188,9 +182,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) {
 		3.0,
 		4.0   // 3
 	]);
-	N = floor( x.length / 2 );
 
-	v = smaxsorted( N, x, 2, 1 );
+	v = smaxsorted( 4, x, 2, 1 );
 	t.strictEqual( v, 4.0, 'returns expected value' );
 
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/smaxsorted/test/test.ndarray.native.js
index ade40cf702c1..a4cb3681fe00 100644
--- a/lib/node_modules/@stdlib/stats/base/smaxsorted/test/test.ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/test/test.ndarray.native.js
@@ -22,7 +22,6 @@
 
 var resolve = require( 'path' ).resolve;
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
 var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' );
 var Float32Array = require( '@stdlib/array/float32' );
@@ -125,7 +124,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 });
 
 tape( 'the function supports a `stride` parameter', opts, function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -134,21 +132,19 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) {
 		2.0,
 		2.0,  // 1
 		-7.0,
-		3.0, // 2
+		3.0,  // 2
 		3.0,
 		4.0,  // 3
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = smaxsorted( N, x, 2, 0 );
+	v = smaxsorted( 4, x, 2, 0 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
 });
 
 tape( 'the function supports a negative `stride` parameter', opts, function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -157,14 +153,13 @@ tape( 'the function supports a negative `stride` parameter', opts, function test
 		2.0,
 		2.0,  // 2
 		-7.0,
-		3.0, // 1
+		3.0,  // 1
 		3.0,
 		4.0,  // 0
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = smaxsorted( N, x, -2, 6 );
+	v = smaxsorted( 4, x, -2, 6 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
@@ -183,7 +178,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f
 });
 
 tape( 'the function supports an `offset` parameter', opts, function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -197,9 +191,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) {
 		3.0,
 		4.0   // 3
 	]);
-	N = floor( x.length / 2 );
 
-	v = smaxsorted( N, x, 2, 1 );
+	v = smaxsorted( 4, x, 2, 1 );
 	t.strictEqual( v, 4.0, 'returns expected value' );
 
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/test/test.smaxsorted.js b/lib/node_modules/@stdlib/stats/base/smaxsorted/test/test.smaxsorted.js
index 73d5cfac8e45..646a72f5da66 100644
--- a/lib/node_modules/@stdlib/stats/base/smaxsorted/test/test.smaxsorted.js
+++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/test/test.smaxsorted.js
@@ -21,7 +21,6 @@
 // MODULES //
 
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
 var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' );
 var Float32Array = require( '@stdlib/array/float32' );
@@ -116,7 +115,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 });
 
 tape( 'the function supports a `stride` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -131,15 +129,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) {
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = smaxsorted( N, x, 2 );
+	v = smaxsorted( 4, x, 2 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
 });
 
 tape( 'the function supports a negative `stride` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -154,8 +150,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t )
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = smaxsorted( N, x, -2 );
+	v = smaxsorted( 4, x, -2 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
@@ -176,7 +171,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f
 tape( 'the function supports view offsets', function test( t ) {
 	var x0;
 	var x1;
-	var N;
 	var v;
 
 	x0 = new Float32Array([
@@ -192,9 +186,8 @@ tape( 'the function supports view offsets', function test( t ) {
 	]);
 
 	x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
-	N = floor(x1.length / 2);
 
-	v = smaxsorted( N, x1, 2 );
+	v = smaxsorted( 4, x1, 2 );
 	t.strictEqual( v, 4.0, 'returns expected value' );
 
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/smaxsorted/test/test.smaxsorted.native.js b/lib/node_modules/@stdlib/stats/base/smaxsorted/test/test.smaxsorted.native.js
index 0749b49ced0c..6a74d1f6f012 100644
--- a/lib/node_modules/@stdlib/stats/base/smaxsorted/test/test.smaxsorted.native.js
+++ b/lib/node_modules/@stdlib/stats/base/smaxsorted/test/test.smaxsorted.native.js
@@ -22,7 +22,6 @@
 
 var resolve = require( 'path' ).resolve;
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
 var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' );
 var Float32Array = require( '@stdlib/array/float32' );
@@ -125,7 +124,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 });
 
 tape( 'the function supports a `stride` parameter', opts, function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -140,15 +138,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) {
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = smaxsorted( N, x, 2 );
+	v = smaxsorted( 4, x, 2 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
 });
 
 tape( 'the function supports a negative `stride` parameter', opts, function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -163,8 +159,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = smaxsorted( N, x, -2 );
+	v = smaxsorted( 4, x, -2 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
@@ -185,7 +180,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f
 tape( 'the function supports view offsets', opts, function test( t ) {
 	var x0;
 	var x1;
-	var N;
 	var v;
 
 	x0 = new Float32Array([
@@ -201,9 +195,8 @@ tape( 'the function supports view offsets', opts, function test( t ) {
 	]);
 
 	x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
-	N = floor(x1.length / 2);
 
-	v = smaxsorted( N, x1, 2 );
+	v = smaxsorted( 4, x1, 2 );
 	t.strictEqual( v, 4.0, 'returns expected value' );
 
 	t.end();

From e3ed80c68e05214a77bec70dc323c3621b4b5df6 Mon Sep 17 00:00:00 2001
From: Aayush Khanna <96649223+aayush0325@users.noreply.github.com>
Date: Fri, 3 Jan 2025 02:45:49 +0530
Subject: [PATCH 21/87] feat: add C ndarray interface and refactor
 implementation for `stats/base/dmskmax`

PR-URL: https://github.com/stdlib-js/stdlib/pull/4366
Reviewed-by: Athan Reines <kgryte@gmail.com>
Co-authored-by: stdlib-bot <82920195+stdlib-bot@users.noreply.github.com>
---
 .../@stdlib/stats/base/dmskmax/README.md      | 173 ++++++++++++++----
 .../stats/base/dmskmax/benchmark/benchmark.js |  31 ++--
 .../dmskmax/benchmark/benchmark.native.js     |  27 +--
 .../dmskmax/benchmark/benchmark.ndarray.js    |  31 ++--
 .../benchmark/benchmark.ndarray.native.js     |  27 +--
 .../dmskmax/benchmark/c/benchmark.length.c    |  56 +++++-
 .../@stdlib/stats/base/dmskmax/docs/repl.txt  |  22 +--
 .../stats/base/dmskmax/examples/c/example.c   |  10 +-
 .../stats/base/dmskmax/examples/index.js      |  27 +--
 .../@stdlib/stats/base/dmskmax/include.gypi   |   2 +-
 .../include/stdlib/stats/base/dmskmax.h       |   8 +-
 .../@stdlib/stats/base/dmskmax/lib/dmskmax.js |  56 +-----
 .../@stdlib/stats/base/dmskmax/lib/index.js   |   4 +-
 .../@stdlib/stats/base/dmskmax/lib/ndarray.js |   4 +-
 .../stats/base/dmskmax/lib/ndarray.native.js  |  16 +-
 .../@stdlib/stats/base/dmskmax/manifest.json  |  73 +++++++-
 .../@stdlib/stats/base/dmskmax/src/addon.c    |  66 +++++++
 .../@stdlib/stats/base/dmskmax/src/addon.cpp  | 153 ----------------
 .../base/dmskmax/src/{dmskmax.c => main.c}    |  40 ++--
 .../stats/base/dmskmax/test/test.dmskmax.js   |  13 +-
 .../base/dmskmax/test/test.dmskmax.native.js  |  13 +-
 .../stats/base/dmskmax/test/test.ndarray.js   |  13 +-
 .../base/dmskmax/test/test.ndarray.native.js  |  15 +-
 23 files changed, 457 insertions(+), 423 deletions(-)
 create mode 100644 lib/node_modules/@stdlib/stats/base/dmskmax/src/addon.c
 delete mode 100644 lib/node_modules/@stdlib/stats/base/dmskmax/src/addon.cpp
 rename lib/node_modules/@stdlib/stats/base/dmskmax/src/{dmskmax.c => main.c} (58%)

diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/README.md b/lib/node_modules/@stdlib/stats/base/dmskmax/README.md
index c9adb5ed4497..bc35eb782dfa 100644
--- a/lib/node_modules/@stdlib/stats/base/dmskmax/README.md
+++ b/lib/node_modules/@stdlib/stats/base/dmskmax/README.md
@@ -38,7 +38,7 @@ var dmskmax = require( '@stdlib/stats/base/dmskmax' );
 
 #### dmskmax( N, x, strideX, mask, strideMask )
 
-Computes the maximum value of a double-precision floating-point strided array `x` according to a `mask`.
+Computes the maximum value of a double-precision floating-point strided array according to a mask.
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
@@ -55,22 +55,20 @@ The function has the following parameters:
 
 -   **N**: number of indexed elements.
 -   **x**: input [`Float64Array`][@stdlib/array/float64].
--   **strideX**: index increment for `x`.
+-   **strideX**: stride length for `x`.
 -   **mask**: mask [`Uint8Array`][@stdlib/array/uint8]. If a `mask` array element is `0`, the corresponding element in `x` is considered valid and **included** in computation. If a `mask` array element is `1`, the corresponding element in `x` is considered invalid/missing and **excluded** from computation.
--   **strideMask**: index increment for `mask`.
+-   **strideMask**: stride length for `mask`.
 
-The `N` and `stride` parameters determine which elements are accessed at runtime. For example, to compute the maximum value of every other element in `x`,
+The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the maximum value of every other element in `x`,
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
 var Uint8Array = require( '@stdlib/array/uint8' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x = new Float64Array( [ 1.0, 2.0, -7.0, -2.0, 4.0, 3.0, 5.0, 6.0 ] );
 var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] );
-var N = floor( x.length / 2 );
 
-var v = dmskmax( N, x, 2, mask, 2 );
+var v = dmskmax( 4, x, 2, mask, 2 );
 // returns 4.0
 ```
 
@@ -81,7 +79,6 @@ Note that indexing is relative to the first index. To introduce offsets, use [`t
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
 var Uint8Array = require( '@stdlib/array/uint8' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x0 = new Float64Array( [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, 5.0, 6.0 ] );
 var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
@@ -89,15 +86,13 @@ var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd
 var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] );
 var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
 
-var N = floor( x0.length / 2 );
-
-var v = dmskmax( N, x1, 2, mask1, 2 );
+var v = dmskmax( 4, x1, 2, mask1, 2 );
 // returns 4.0
 ```
 
 #### dmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )
 
-Computes the maximum value of a double-precision floating-point strided array according to a `mask` and using alternative indexing semantics.
+Computes the maximum value of a double-precision floating-point strided array according to a mask and using alternative indexing semantics.
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
@@ -115,18 +110,16 @@ The function has the following additional parameters:
 -   **offsetX**: starting index for `x`.
 -   **offsetMask**: starting index for `mask`.
 
-While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the maximum value for every other value in `x` starting from the second value
+While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on a starting indices. For example, to calculate the maximum value for every other element in `x` starting from the second element
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
 var Uint8Array = require( '@stdlib/array/uint8' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x = new Float64Array( [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, 5.0, 6.0 ] );
 var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] );
-var N = floor( x.length / 2 );
 
-var v = dmskmax.ndarray( N, x, 2, 1, mask, 2, 1 );
+var v = dmskmax.ndarray( 4, x, 2, 1, mask, 2, 1 );
 // returns 4.0
 ```
 
@@ -151,26 +144,19 @@ var v = dmskmax.ndarray( N, x, 2, 1, mask, 2, 1 );
 <!-- eslint no-undef: "error" -->
 
 ```javascript
-var randu = require( '@stdlib/random/base/randu' );
-var round = require( '@stdlib/math/base/special/round' );
-var Float64Array = require( '@stdlib/array/float64' );
-var Uint8Array = require( '@stdlib/array/uint8' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var bernoulli = require( '@stdlib/random/array/bernoulli' );
 var dmskmax = require( '@stdlib/stats/base/dmskmax' );
 
-var mask;
-var x;
-var i;
-
-x = new Float64Array( 10 );
-mask = new Uint8Array( x.length );
-for ( i = 0; i < x.length; i++ ) {
-    if ( randu() < 0.2 ) {
-        mask[ i ] = 1;
-    } else {
-        mask[ i ] = 0;
-    }
-    x[ i ] = round( (randu()*100.0) - 50.0 );
-}
+var uniformOptions = {
+    'dtype': 'float64'
+};
+var bernoulliOptions = {
+    'dtype': 'uint8'
+};
+
+var x = uniform( 10, -50.0, 50.0, uniformOptions );
+var mask = bernoulli( x.length, 0.2, bernoulliOptions );
 console.log( x );
 console.log( mask );
 
@@ -182,6 +168,125 @@ console.log( v );
 
 <!-- /.examples -->
 
+<!-- C usage documentation. -->
+
+<section class="usage">
+
+### Usage
+
+```c
+#include "stdlib/stats/base/dmskmax.h"
+```
+
+#### stdlib_strided_dmskmax( N, \*X, strideX, \*Mask, strideMask )
+
+Computes the maximum value of a double-precision floating-point strided array according to a mask.
+
+```c
+#include <stdint.h>
+
+const double x[] = { 1.0, -2.0, 2.0 };
+const uint8_t mask[] = { 0, 1, 0 };
+
+double v = stdlib_strided_dmskmax( 3, x, 1, mask, 1 );
+// returns 2.0
+```
+
+The function accepts the following arguments:
+
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **X**: `[in] double*` input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+-   **Mask**: `[in] uint8_t*` mask array. If a `Mask` array element is `0`, the corresponding element in `X` is considered valid and included in computation. If a `Mask` array element is `1`, the corresponding element in `X` is considered invalid/missing and excluded from computation.
+-   **strideMask**: `[in] CBLAS_INT` stride length for `Mask`.
+
+```c
+double stdlib_strided_dmskmax( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const uint8_t *Mask, const CBLAS_INT strideMask );
+```
+
+<!-- lint disable maximum-heading-length -->
+
+#### stdlib_strided_dmskmax_ndarray( N, \*X, strideX, offsetX, \*Mask, strideMask, offsetMask )
+
+Computes the maximum value of a double-precision floating-point strided array according to a mask and using alternative indexing semantics.
+
+```c
+#include <stdint.h>
+
+const double x[] = { 1.0, -2.0, 2.0 };
+const uint8_t mask[] = { 0, 1, 0 };
+
+double v = stdlib_strided_dmskmax_ndarray( 3, x, 1, 0, mask, 1, 0 );
+// returns 2.0
+```
+
+The function accepts the following arguments:
+
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **X**: `[in] double*` input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+-   **offsetX**: `[in] CBLAS_INT` starting index for `X`.
+-   **Mask**: `[in] uint8_t*` mask array. If a `Mask` array element is `0`, the corresponding element in `X` is considered valid and included in computation. If a `Mask` array element is `1`, the corresponding element in `X` is considered invalid/missing and excluded from computation.
+-   **strideMask**: `[in] CBLAS_INT` stride length for `Mask`.
+-   **offsetMask**: `[in] CBLAS_INT` starting index for `Mask`.
+
+```c
+double stdlib_strided_dmskmax_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const uint8_t *Mask, const CBLAS_INT strideMask, const CBLAS_INT offsetMask );
+```
+
+</section>
+
+<!-- /.usage -->
+
+<!-- C API usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="notes">
+
+</section>
+
+<!-- /.notes -->
+
+<!-- C API usage examples. -->
+
+<section class="examples">
+
+### Examples
+
+```c
+#include "stdlib/stats/base/dmskmax.h"
+#include <stdint.h>
+#include <stdio.h>
+
+int main( void ) {
+    // Create a strided array:
+    const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 };
+
+    // Create a mask array:
+    const uint8_t mask[] = { 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 };
+
+    // Specify the number of elements:
+    const int N = 5;
+
+    // Specify the stride lengths:
+    const int strideX = 2;
+    const int strideMask = 2;
+
+    // Compute the maximum value:
+    double v = stdlib_strided_dmskmax( N, x, strideX, mask, strideMask );
+
+    // Print the result:
+    printf( "max: %lf\n", v );
+}
+```
+
+</section>
+
+<!-- /.examples -->
+
+</section>
+
+<!-- /.c -->
+
 <!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
 
 <section class="related">
diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dmskmax/benchmark/benchmark.js
index 017bba33ab46..b3b88720cac8 100644
--- a/lib/node_modules/@stdlib/stats/base/dmskmax/benchmark/benchmark.js
+++ b/lib/node_modules/@stdlib/stats/base/dmskmax/benchmark/benchmark.js
@@ -21,15 +21,24 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var bernoulli = require( '@stdlib/random/array/bernoulli' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float64Array = require( '@stdlib/array/float64' );
-var Uint8Array = require( '@stdlib/array/uint8' );
 var pkg = require( './../package.json' ).name;
 var dmskmax = require( './../lib/dmskmax.js' );
 
 
+// VARIABLES //
+
+var uniformOptions = {
+	'dtype': 'float64'
+};
+var bernoulliOptions = {
+	'dtype': 'uint8'
+};
+
+
 // FUNCTIONS //
 
 /**
@@ -40,20 +49,8 @@ var dmskmax = require( './../lib/dmskmax.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var mask;
-	var x;
-	var i;
-
-	x = new Float64Array( len );
-	mask = new Uint8Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		if ( randu() < 0.2 ) {
-			mask[ i ] = 1;
-		} else {
-			mask[ i ] = 0;
-		}
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
+	var mask = bernoulli( len, 0.2, bernoulliOptions );
+	var x = uniform( len, -10.0, 10.0, uniformOptions );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dmskmax/benchmark/benchmark.native.js
index f7d94111729f..f0bc0231eee6 100644
--- a/lib/node_modules/@stdlib/stats/base/dmskmax/benchmark/benchmark.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dmskmax/benchmark/benchmark.native.js
@@ -22,11 +22,10 @@
 
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var bernoulli = require( '@stdlib/random/array/bernoulli' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float64Array = require( '@stdlib/array/float64' );
-var Uint8Array = require( '@stdlib/array/uint8' );
 var tryRequire = require( '@stdlib/utils/try-require' );
 var pkg = require( './../package.json' ).name;
 
@@ -37,6 +36,12 @@ var dmskmax = tryRequire( resolve( __dirname, './../lib/dmskmax.native.js' ) );
 var opts = {
 	'skip': ( dmskmax instanceof Error )
 };
+var uniformOptions = {
+	'dtype': 'float64'
+};
+var bernoulliOptions = {
+	'dtype': 'uint8'
+};
 
 
 // FUNCTIONS //
@@ -49,20 +54,8 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var mask;
-	var x;
-	var i;
-
-	x = new Float64Array( len );
-	mask = new Uint8Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		if ( randu() < 0.2 ) {
-			mask[ i ] = 1;
-		} else {
-			mask[ i ] = 0;
-		}
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
+	var mask = bernoulli( len, 0.2, bernoulliOptions );
+	var x = uniform( len, -10.0, 10.0, uniformOptions );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/dmskmax/benchmark/benchmark.ndarray.js
index 6316a49b6db5..33ecb4344641 100644
--- a/lib/node_modules/@stdlib/stats/base/dmskmax/benchmark/benchmark.ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/dmskmax/benchmark/benchmark.ndarray.js
@@ -21,15 +21,24 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var bernoulli = require( '@stdlib/random/array/bernoulli' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float64Array = require( '@stdlib/array/float64' );
-var Uint8Array = require( '@stdlib/array/uint8' );
 var pkg = require( './../package.json' ).name;
 var dmskmax = require( './../lib/ndarray.js' );
 
 
+// VARIABLES //
+
+var uniformOptions = {
+	'dtype': 'float64'
+};
+var bernoulliOptions = {
+	'dtype': 'uint8'
+};
+
+
 // FUNCTIONS //
 
 /**
@@ -40,20 +49,8 @@ var dmskmax = require( './../lib/ndarray.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var mask;
-	var x;
-	var i;
-
-	x = new Float64Array( len );
-	mask = new Uint8Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		if ( randu() < 0.2 ) {
-			mask[ i ] = 1;
-		} else {
-			mask[ i ] = 0;
-		}
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
+	var mask = bernoulli( len, 0.2, bernoulliOptions );
+	var x = uniform( len, -10.0, 10.0, uniformOptions );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmskmax/benchmark/benchmark.ndarray.native.js
index 56e85488a506..bd313639b6bb 100644
--- a/lib/node_modules/@stdlib/stats/base/dmskmax/benchmark/benchmark.ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dmskmax/benchmark/benchmark.ndarray.native.js
@@ -22,11 +22,10 @@
 
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var bernoulli = require( '@stdlib/random/array/bernoulli' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float64Array = require( '@stdlib/array/float64' );
-var Uint8Array = require( '@stdlib/array/uint8' );
 var tryRequire = require( '@stdlib/utils/try-require' );
 var pkg = require( './../package.json' ).name;
 
@@ -37,6 +36,12 @@ var dmskmax = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) );
 var opts = {
 	'skip': ( dmskmax instanceof Error )
 };
+var uniformOptions = {
+	'dtype': 'float64'
+};
+var bernoulliOptions = {
+	'dtype': 'uint8'
+};
 
 
 // FUNCTIONS //
@@ -49,20 +54,8 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var mask;
-	var x;
-	var i;
-
-	x = new Float64Array( len );
-	mask = new Uint8Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		if ( randu() < 0.2 ) {
-			mask[ i ] = 1;
-		} else {
-			mask[ i ] = 0;
-		}
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
+	var mask = bernoulli( len, 0.2, bernoulliOptions );
+	var x = uniform( len, -10.0, 10.0, uniformOptions );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dmskmax/benchmark/c/benchmark.length.c
index ce221703a44d..5a75cd73545b 100644
--- a/lib/node_modules/@stdlib/stats/base/dmskmax/benchmark/c/benchmark.length.c
+++ b/lib/node_modules/@stdlib/stats/base/dmskmax/benchmark/c/benchmark.length.c
@@ -94,7 +94,7 @@ static double rand_double( void ) {
 * @param len          array length
 * @return             elapsed time in seconds
 */
-static double benchmark( int iterations, int len ) {
+static double benchmark1( int iterations, int len ) {
 	unsigned char mask[ len ];
 	double elapsed;
 	double x[ len ];
@@ -113,6 +113,7 @@ static double benchmark( int iterations, int len ) {
 	v = 0.0;
 	t = tic();
 	for ( i = 0; i < iterations; i++ ) {
+		// cppcheck-suppress uninitvar
 		v = stdlib_strided_dmskmax( len, x, 1, mask, 1 );
 		if ( v != v ) {
 			printf( "should not return NaN\n" );
@@ -126,6 +127,46 @@ static double benchmark( int iterations, int len ) {
 	return elapsed;
 }
 
+/**
+* Runs a benchmark.
+*
+* @param iterations   number of iterations
+* @param len          array length
+* @return             elapsed time in seconds
+*/
+static double benchmark2( int iterations, int len ) {
+	unsigned char mask[ len ];
+	double elapsed;
+	double x[ len ];
+	double v;
+	double t;
+	int i;
+
+	for ( i = 0; i < len; i++ ) {
+		if ( rand_double() < 0.2 ) {
+			mask[ i ] = 1; // missing
+		} else {
+			mask[ i ] = 0;
+		}
+		x[ i ] = ( rand_double() * 20000.0 ) - 10000.0;
+	}
+	v = 0.0;
+	t = tic();
+	for ( i = 0; i < iterations; i++ ) {
+		// cppcheck-suppress uninitvar
+		v = stdlib_strided_dmskmax_ndarray( len, x, 1, 0, mask, 1, 0 );
+		if ( v != v ) {
+			printf( "should not return NaN\n" );
+			break;
+		}
+	}
+	elapsed = tic() - t;
+	if ( v != v ) {
+		printf( "should not return NaN\n" );
+	}
+	return elapsed;
+}
+
 /**
 * Main execution sequence.
 */
@@ -148,7 +189,18 @@ int main( void ) {
 		for ( j = 0; j < REPEATS; j++ ) {
 			count += 1;
 			printf( "# c::%s:len=%d\n", NAME, len );
-			elapsed = benchmark( iter, len );
+			elapsed = benchmark1( iter, len );
+			print_results( iter, elapsed );
+			printf( "ok %d benchmark finished\n", count );
+		}
+	}
+	for ( i = MIN; i <= MAX; i++ ) {
+		len = pow( 10, i );
+		iter = ITERATIONS / pow( 10, i-1 );
+		for ( j = 0; j < REPEATS; j++ ) {
+			count += 1;
+			printf( "# c::%s:ndarray:len=%d\n", NAME, len );
+			elapsed = benchmark2( iter, len );
 			print_results( iter, elapsed );
 			printf( "ok %d benchmark finished\n", count );
 		}
diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dmskmax/docs/repl.txt
index 88c817fd423e..12e92f4235de 100644
--- a/lib/node_modules/@stdlib/stats/base/dmskmax/docs/repl.txt
+++ b/lib/node_modules/@stdlib/stats/base/dmskmax/docs/repl.txt
@@ -3,8 +3,8 @@
     Computes the maximum value of a double-precision floating-point strided
     array according to a mask.
 
-    The `N` and `stride` parameters determine which elements are accessed at
-    runtime.
+    The `N` and stride parameters determine which elements in the strided
+    arrays are accessed at runtime.
 
     Indexing is relative to the first index. To introduce offsets, use a typed
     array views.
@@ -26,13 +26,13 @@
         Input array.
 
     strideX: integer
-        Index increment for `x`.
+        Stride Length for `x`.
 
     mask: Uint8Array
         Mask array.
 
     strideMask: integer
-        Index increment for `mask`.
+        Stride Length for `mask`.
 
     Returns
     -------
@@ -50,8 +50,7 @@
     // Using `N` and `stride` parameters:
     > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );
     > mask = new {{alias:@stdlib/array/uint8}}( [ 0, 0, 0, 0, 0, 0, 1 ] );
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > {{alias}}( N, x, 2, mask, 2 )
+    > {{alias}}( 3, x, 2, mask, 2 )
     2.0
 
     // Using view offsets:
@@ -59,10 +58,10 @@
     > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );
     > var mask0 = new {{alias:@stdlib/array/uint8}}( [ 0, 0, 0, 0, 0, 0, 1 ] );
     > var mask1 = new {{alias:@stdlib/array/uint8}}( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );
-    > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );
-    > {{alias}}( N, x1, 2, mask1, 2 )
+    > {{alias}}( 3, x1, 2, mask1, 2 )
     2.0
 
+
 {{alias}}.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )
     Computes the maximum value of a double-precision floating-point strided
     array according to a mask and using alternative indexing semantics.
@@ -80,7 +79,7 @@
         Input array.
 
     strideX: integer
-        Index increment for `x`.
+        Stride Length for `x`.
 
     offsetX: integer
         Starting index for `x`.
@@ -89,7 +88,7 @@
         Mask array.
 
     strideMask: integer
-        Index increment for `mask`.
+        Stride Length for `mask`.
 
     offsetMask: integer
         Starting index for `mask`.
@@ -110,8 +109,7 @@
     // Using offset parameter:
     > x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );
     > mask = new {{alias:@stdlib/array/uint8}}( [ 0, 0, 0, 0, 0, 0, 1 ] );
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > {{alias}}.ndarray( N, x, 2, 1, mask, 2, 1 )
+    > {{alias}}.ndarray( 3, x, 2, 1, mask, 2, 1 )
     2.0
 
     See Also
diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dmskmax/examples/c/example.c
index dc059d8a4d77..ba6fb4c28a3d 100644
--- a/lib/node_modules/@stdlib/stats/base/dmskmax/examples/c/example.c
+++ b/lib/node_modules/@stdlib/stats/base/dmskmax/examples/c/example.c
@@ -22,17 +22,17 @@
 
 int main( void ) {
 	// Create a strided array:
-	double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 };
+	const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 };
 
 	// Create a mask array:
-	uint8_t mask[] = { 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 };
+	const uint8_t mask[] = { 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 };
 
 	// Specify the number of elements:
-	int64_t N = 5;
+	const int N = 5;
 
 	// Specify the stride lengths:
-	int64_t strideX = 2;
-	int64_t strideMask = 2;
+	const int strideX = 2;
+	const int strideMask = 2;
 
 	// Compute the maximum value:
 	double v = stdlib_strided_dmskmax( N, x, strideX, mask, strideMask );
diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/examples/index.js b/lib/node_modules/@stdlib/stats/base/dmskmax/examples/index.js
index 5bf314a934d6..f6bb694a5032 100644
--- a/lib/node_modules/@stdlib/stats/base/dmskmax/examples/index.js
+++ b/lib/node_modules/@stdlib/stats/base/dmskmax/examples/index.js
@@ -18,26 +18,19 @@
 
 'use strict';
 
-var randu = require( '@stdlib/random/base/randu' );
-var round = require( '@stdlib/math/base/special/round' );
-var Float64Array = require( '@stdlib/array/float64' );
-var Uint8Array = require( '@stdlib/array/uint8' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var bernoulli = require( '@stdlib/random/array/bernoulli' );
 var dmskmax = require( './../lib' );
 
-var mask;
-var x;
-var i;
+var uniformOptions = {
+	'dtype': 'float64'
+};
+var bernoulliOptions = {
+	'dtype': 'uint8'
+};
 
-x = new Float64Array( 10 );
-mask = new Uint8Array( x.length );
-for ( i = 0; i < x.length; i++ ) {
-	if ( randu() < 0.2 ) {
-		mask[ i ] = 1;
-	} else {
-		mask[ i ] = 0;
-	}
-	x[ i ] = round( (randu()*100.0) - 50.0 );
-}
+var x = uniform( 10, -50.0, 50.0, uniformOptions );
+var mask = bernoulli( x.length, 0.2, bernoulliOptions );
 console.log( x );
 console.log( mask );
 
diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/include.gypi b/lib/node_modules/@stdlib/stats/base/dmskmax/include.gypi
index 868c5c12e852..26476a8c2655 100644
--- a/lib/node_modules/@stdlib/stats/base/dmskmax/include.gypi
+++ b/lib/node_modules/@stdlib/stats/base/dmskmax/include.gypi
@@ -36,7 +36,7 @@
 
     # Source files:
     'src_files': [
-      '<(src_dir)/addon.cpp',
+      '<(src_dir)/addon.c',
       '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).src; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
     ],
 
diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/include/stdlib/stats/base/dmskmax.h b/lib/node_modules/@stdlib/stats/base/dmskmax/include/stdlib/stats/base/dmskmax.h
index 16493fd9c42c..353790edb177 100644
--- a/lib/node_modules/@stdlib/stats/base/dmskmax/include/stdlib/stats/base/dmskmax.h
+++ b/lib/node_modules/@stdlib/stats/base/dmskmax/include/stdlib/stats/base/dmskmax.h
@@ -19,6 +19,7 @@
 #ifndef STDLIB_STATS_BASE_DMSKMAX_H
 #define STDLIB_STATS_BASE_DMSKMAX_H
 
+#include "stdlib/blas/base/shared.h"
 #include <stdint.h>
 
 /*
@@ -31,7 +32,12 @@ extern "C" {
 /**
 * Computes the maximum value of a double-precision floating-point strided array according to a mask.
 */
-double stdlib_strided_dmskmax( const int64_t N, const double *X, const int64_t strideX, const uint8_t *Mask, const int64_t strideMask );
+double API_SUFFIX(stdlib_strided_dmskmax)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const uint8_t *Mask, const CBLAS_INT strideMask );
+
+/**
+* Computes the maximum value of a double-precision floating-point strided array according to a mask and using alternative indexing semantics.
+*/
+double API_SUFFIX(stdlib_strided_dmskmax_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const uint8_t *Mask, const CBLAS_INT strideMask, const CBLAS_INT offsetMask );
 
 #ifdef __cplusplus
 }
diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/lib/dmskmax.js b/lib/node_modules/@stdlib/stats/base/dmskmax/lib/dmskmax.js
index bdb0e82c57b4..bf50963f901c 100644
--- a/lib/node_modules/@stdlib/stats/base/dmskmax/lib/dmskmax.js
+++ b/lib/node_modules/@stdlib/stats/base/dmskmax/lib/dmskmax.js
@@ -20,8 +20,8 @@
 
 // MODULES //
 
-var isnan = require( '@stdlib/math/base/assert/is-nan' );
-var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' );
+var stride2offset = require( '@stdlib/strided/base/stride2offset' );
+var ndarray = require( './ndarray.js' );
 
 
 // MAIN //
@@ -47,55 +47,9 @@ var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' );
 * // returns 2.0
 */
 function dmskmax( N, x, strideX, mask, strideMask ) {
-	var max;
-	var ix;
-	var im;
-	var v;
-	var i;
-
-	if ( N <= 0 ) {
-		return NaN;
-	}
-	if ( strideX < 0 ) {
-		ix = (1-N) * strideX;
-	} else {
-		ix = 0;
-	}
-	if ( strideMask < 0 ) {
-		im = (1-N) * strideMask;
-	} else {
-		im = 0;
-	}
-	for ( i = 0; i < N; i++ ) {
-		if ( mask[ im ] === 0 ) {
-			break;
-		}
-		ix += strideX;
-		im += strideMask;
-	}
-	if ( i === N ) {
-		return NaN;
-	}
-	max = x[ ix ];
-	if ( isnan( max ) ) {
-		return max;
-	}
-	i += 1;
-	for ( i; i < N; i++ ) {
-		ix += strideX;
-		im += strideMask;
-		if ( mask[ im ] ) {
-			continue;
-		}
-		v = x[ ix ];
-		if ( isnan( v ) ) {
-			return v;
-		}
-		if ( v > max || ( v === max && isPositiveZero( v ) ) ) {
-			max = v;
-		}
-	}
-	return max;
+	var ox = stride2offset( N, strideX );
+	var om = stride2offset( N, strideMask );
+	return ndarray( N, x, strideX, ox, mask, strideMask, om );
 }
 
 
diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/lib/index.js b/lib/node_modules/@stdlib/stats/base/dmskmax/lib/index.js
index e6745a966dd8..d6901bc4dd38 100644
--- a/lib/node_modules/@stdlib/stats/base/dmskmax/lib/index.js
+++ b/lib/node_modules/@stdlib/stats/base/dmskmax/lib/index.js
@@ -37,14 +37,12 @@
 * @example
 * var Float64Array = require( '@stdlib/array/float64' );
 * var Uint8Array = require( '@stdlib/array/uint8' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 * var dmskmax = require( '@stdlib/stats/base/dmskmax' );
 *
 * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
 * var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 ] );
-* var N = floor( x.length / 2 );
 *
-* var v = dmskmax.ndarray( N, x, 2, 1, mask, 2, 1 );
+* var v = dmskmax.ndarray( 5, x, 2, 1, mask, 2, 1 );
 * // returns 4.0
 */
 
diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/dmskmax/lib/ndarray.js
index c5217a702896..59d7252f3db1 100644
--- a/lib/node_modules/@stdlib/stats/base/dmskmax/lib/ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/dmskmax/lib/ndarray.js
@@ -41,13 +41,11 @@ var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' );
 * @example
 * var Float64Array = require( '@stdlib/array/float64' );
 * var Uint8Array = require( '@stdlib/array/uint8' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 *
 * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
 * var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 ] );
-* var N = floor( x.length / 2 );
 *
-* var v = dmskmax( N, x, 2, 1, mask, 2, 1 );
+* var v = dmskmax( 5, x, 2, 1, mask, 2, 1 );
 * // returns 4.0
 */
 function dmskmax( N, x, strideX, offsetX, mask, strideMask, offsetMask ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmskmax/lib/ndarray.native.js
index 07cf4389d730..7d498b936dad 100644
--- a/lib/node_modules/@stdlib/stats/base/dmskmax/lib/ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dmskmax/lib/ndarray.native.js
@@ -20,9 +20,7 @@
 
 // MODULES //
 
-var Float64Array = require( '@stdlib/array/float64' );
-var Uint8Array = require( '@stdlib/array/uint8' );
-var addon = require( './dmskmax.native.js' );
+var addon = require( './../src/addon.node' );
 
 
 // MAIN //
@@ -52,17 +50,7 @@ var addon = require( './dmskmax.native.js' );
 * // returns 4.0
 */
 function dmskmax( N, x, strideX, offsetX, mask, strideMask, offsetMask ) {
-	var viewX;
-	var viewM;
-	if ( strideX < 0 ) {
-		offsetX += (N-1) * strideX;
-	}
-	if ( strideMask < 0 ) {
-		offsetMask += (N-1) * strideMask;
-	}
-	viewX = new Float64Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offsetX), x.length-offsetX ); // eslint-disable-line max-len
-	viewM = new Uint8Array( mask.buffer, mask.byteOffset+(mask.BYTES_PER_ELEMENT*offsetMask), mask.length-offsetMask ); // eslint-disable-line max-len
-	return addon( N, viewX, strideX, viewM, strideMask );
+	return addon.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask ); // eslint-disable-line max-len
 }
 
 
diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/manifest.json b/lib/node_modules/@stdlib/stats/base/dmskmax/manifest.json
index 02276c182f12..b2a745931681 100644
--- a/lib/node_modules/@stdlib/stats/base/dmskmax/manifest.json
+++ b/lib/node_modules/@stdlib/stats/base/dmskmax/manifest.json
@@ -1,5 +1,8 @@
 {
-  "options": {},
+  "options": {
+    "task": "build",
+    "wasm": false
+  },
   "fields": [
     {
       "field": "src",
@@ -24,17 +27,79 @@
   ],
   "confs": [
     {
+      "task": "build",
+      "wasm": false,
       "src": [
-        "./src/dmskmax.c"
+        "./src/main.c"
       ],
       "include": [
         "./include"
       ],
-      "libraries": [
-        "-lm"
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset",
+        "@stdlib/math/base/assert/is-positive-zero",
+        "@stdlib/math/base/assert/is-nan",
+        "@stdlib/napi/export",
+        "@stdlib/napi/argv",
+        "@stdlib/napi/argv-int64",
+        "@stdlib/napi/argv-strided-float64array",
+        "@stdlib/napi/argv-strided-uint8array",
+        "@stdlib/napi/create-double"
+      ]
+    },
+    {
+      "task": "benchmark",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset",
+        "@stdlib/math/base/assert/is-nan",
+        "@stdlib/math/base/assert/is-positive-zero"
+      ]
+    },
+    {
+      "task": "examples",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset",
+        "@stdlib/math/base/assert/is-nan",
+        "@stdlib/math/base/assert/is-positive-zero"
+      ]
+    },
+    {
+      "task": "",
+      "wasm": true,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
       ],
+      "libraries": [],
       "libpath": [],
       "dependencies": [
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset",
         "@stdlib/math/base/assert/is-nan",
         "@stdlib/math/base/assert/is-positive-zero"
       ]
diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/src/addon.c b/lib/node_modules/@stdlib/stats/base/dmskmax/src/addon.c
new file mode 100644
index 000000000000..15f8916fa93a
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dmskmax/src/addon.c
@@ -0,0 +1,66 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/dmskmax.h"
+#include "stdlib/napi/export.h"
+#include "stdlib/napi/argv.h"
+#include "stdlib/napi/argv_int64.h"
+#include "stdlib/napi/argv_strided_float64array.h"
+#include "stdlib/napi/argv_strided_uint8array.h"
+#include "stdlib/napi/create_double.h"
+#include <node_api.h>
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 5 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 );
+	STDLIB_NAPI_ARGV_INT64( env, strideMask, argv, 4 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 );
+	STDLIB_NAPI_ARGV_STRIDED_UINT8ARRAY( env, Mask, N, strideMask, argv, 3 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dmskmax( N, X, strideX, Mask, strideMask ), v );
+	return v;
+}
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon_method( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 7 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 );
+	STDLIB_NAPI_ARGV_INT64( env, strideMask, argv, 5 );
+	STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 );
+	STDLIB_NAPI_ARGV_INT64( env, offsetMask, argv, 6 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 );
+	STDLIB_NAPI_ARGV_STRIDED_UINT8ARRAY( env, Mask, N, strideMask, argv, 4 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dmskmax_ndarray( N, X, strideX, offsetX, Mask, strideMask, offsetMask ), v );
+	return v;
+}
+
+STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method )
diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/dmskmax/src/addon.cpp
deleted file mode 100644
index 19c5d537daf3..000000000000
--- a/lib/node_modules/@stdlib/stats/base/dmskmax/src/addon.cpp
+++ /dev/null
@@ -1,153 +0,0 @@
-/**
-* @license Apache-2.0
-*
-* Copyright (c) 2020 The Stdlib Authors.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-*    http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-
-#include "stdlib/stats/base/dmskmax.h"
-#include <node_api.h>
-#include <stdint.h>
-#include <stdlib.h>
-#include <stdbool.h>
-#include <assert.h>
-
-/**
-* Add-on namespace.
-*/
-namespace stdlib_stats_base_dmskmax {
-
-	/**
-	* Computes the maximum value of a double-precision floating-point strided array according to a mask.
-	*
-	* ## Notes
-	*
-	* -   When called from JavaScript, the function expects five arguments:
-	*
-	*     -   `N`: number of indexed elements
-	*     -   `X`: input array
-	*     -   `strideX`: `X` stride length
-	*     -   `Mask`: mask array
-	*     -   `strideMask`: `Mask` stride length
-	*/
-	napi_value node_dmskmax( napi_env env, napi_callback_info info ) {
-		napi_status status;
-
-		size_t argc = 5;
-		napi_value argv[ 5 ];
-		status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr );
-		assert( status == napi_ok );
-
-		if ( argc < 5 ) {
-			napi_throw_error( env, nullptr, "invalid invocation. Must provide 5 arguments." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype0;
-		status = napi_typeof( env, argv[ 0 ], &vtype0 );
-		assert( status == napi_ok );
-		if ( vtype0 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." );
-			return nullptr;
-		}
-
-		bool res1;
-		status = napi_is_typedarray( env, argv[ 1 ], &res1 );
-		assert( status == napi_ok );
-		if ( res1 == false ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float64Array." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype2;
-		status = napi_typeof( env, argv[ 2 ], &vtype2 );
-		assert( status == napi_ok );
-		if ( vtype2 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." );
-			return nullptr;
-		}
-
-		bool res3;
-		status = napi_is_typedarray( env, argv[ 3 ], &res3 );
-		assert( status == napi_ok );
-		if ( res3 == false ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a Uint8Array." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype4;
-		status = napi_typeof( env, argv[ 4 ], &vtype4 );
-		assert( status == napi_ok );
-		if ( vtype4 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Fifth argument must be a number." );
-			return nullptr;
-		}
-
-		int64_t N;
-		status = napi_get_value_int64( env, argv[ 0 ], &N );
-		assert( status == napi_ok );
-
-		int64_t strideX;
-		status = napi_get_value_int64( env, argv[ 2 ], &strideX );
-		assert( status == napi_ok );
-
-		int64_t strideMask;
-		status = napi_get_value_int64( env, argv[ 4 ], &strideMask );
-		assert( status == napi_ok );
-
-		napi_typedarray_type vtype1;
-		size_t xlen;
-		void *X;
-		status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr );
-		assert( status == napi_ok );
-		if ( vtype1 != napi_float64_array ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float64Array." );
-			return nullptr;
-		}
-		if ( (N-1)*llabs(strideX) >= (int64_t)xlen ) {
-			napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." );
-			return nullptr;
-		}
-
-		napi_typedarray_type vtype3;
-		size_t mlen;
-		void *Mask;
-		status = napi_get_typedarray_info( env, argv[ 3 ], &vtype3, &mlen, &Mask, nullptr, nullptr );
-		assert( status == napi_ok );
-		if ( vtype3 != napi_uint8_array ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a Uint8Array." );
-			return nullptr;
-		}
-		if ( (N-1)*llabs(strideMask) >= (int64_t)mlen ) {
-			napi_throw_range_error( env, nullptr, "invalid argument. Fourth argument has insufficient elements based on the associated stride and the number of indexed elements." );
-			return nullptr;
-		}
-
-		napi_value v;
-		status = napi_create_double( env, stdlib_strided_dmskmax( N, (double *)X, strideX, (uint8_t *)Mask, strideMask ), &v );
-		assert( status == napi_ok );
-
-		return v;
-	}
-
-	napi_value Init( napi_env env, napi_value exports ) {
-		napi_status status;
-		napi_value fcn;
-		status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_dmskmax, NULL, &fcn );
-		assert( status == napi_ok );
-		return fcn;
-	}
-
-	NAPI_MODULE( NODE_GYP_MODULE_NAME, Init )
-} // end namespace stdlib_stats_base_dmskmax
diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/src/dmskmax.c b/lib/node_modules/@stdlib/stats/base/dmskmax/src/main.c
similarity index 58%
rename from lib/node_modules/@stdlib/stats/base/dmskmax/src/dmskmax.c
rename to lib/node_modules/@stdlib/stats/base/dmskmax/src/main.c
index d3848b86b995..63f2bfc3297f 100644
--- a/lib/node_modules/@stdlib/stats/base/dmskmax/src/dmskmax.c
+++ b/lib/node_modules/@stdlib/stats/base/dmskmax/src/main.c
@@ -19,6 +19,8 @@
 #include "stdlib/stats/base/dmskmax.h"
 #include "stdlib/math/base/assert/is_nan.h"
 #include "stdlib/math/base/assert/is_positive_zero.h"
+#include "stdlib/blas/base/shared.h"
+#include "stdlib/strided/base/stride2offset.h"
 #include <stdint.h>
 
 /**
@@ -31,26 +33,36 @@
 * @param strideMask  Mask stride length
 * @return            output value
 */
-double stdlib_strided_dmskmax( const int64_t N, const double *X, const int64_t strideX, const uint8_t *Mask, const int64_t strideMask ) {
+double API_SUFFIX(stdlib_strided_dmskmax)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const uint8_t *Mask, const CBLAS_INT strideMask ) {
+	const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX );
+	const CBLAS_INT om = stdlib_strided_stride2offset( N, strideMask );
+	return API_SUFFIX(stdlib_strided_dmskmax_ndarray)( N, X, strideX, ox, Mask, strideMask, om );
+}
+
+/**
+* Computes the maximum value of a double-precision floating-point strided array according to a mask and using alternative indexing semantics.
+*
+* @param N           number of indexed elements
+* @param X           input array
+* @param strideX     X stride length
+* @param offsetX     starting index for X
+* @param Mask        mask array
+* @param strideMask  Mask stride length
+* @param offsetMask  starting index for Mask
+* @return            output value
+*/
+double API_SUFFIX(stdlib_strided_dmskmax_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const uint8_t *Mask, const CBLAS_INT strideMask, const CBLAS_INT offsetMask ) {
+	CBLAS_INT ix;
+	CBLAS_INT im;
+	CBLAS_INT i;
 	double max;
-	int64_t ix;
-	int64_t im;
-	int64_t i;
 	double v;
 
 	if ( N <= 0 ) {
 		return 0.0 / 0.0; // NaN
 	}
-	if ( strideX < 0 ) {
-		ix = (1-N) * strideX;
-	} else {
-		ix = 0;
-	}
-	if ( strideMask < 0 ) {
-		im = (1-N) * strideMask;
-	} else {
-		im = 0;
-	}
+	ix = offsetX;
+	im = offsetMask;
 	for ( i = 0; i < N; i++ ) {
 		if ( Mask[ im ] == 0 ) {
 			break;
diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/test/test.dmskmax.js b/lib/node_modules/@stdlib/stats/base/dmskmax/test/test.dmskmax.js
index c3c6c35d213e..9b89cea89358 100644
--- a/lib/node_modules/@stdlib/stats/base/dmskmax/test/test.dmskmax.js
+++ b/lib/node_modules/@stdlib/stats/base/dmskmax/test/test.dmskmax.js
@@ -21,7 +21,6 @@
 // MODULES //
 
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' );
 var Float64Array = require( '@stdlib/array/float64' );
@@ -133,7 +132,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 
 tape( 'the function supports `stride` parameters', function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -162,8 +160,7 @@ tape( 'the function supports `stride` parameters', function test( t ) {
 		1
 	]);
 
-	N = floor( x.length / 2 );
-	v = dmskmax( N, x, 2, mask, 2 );
+	v = dmskmax( 5, x, 2, mask, 2 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
@@ -171,7 +168,6 @@ tape( 'the function supports `stride` parameters', function test( t ) {
 
 tape( 'the function supports negative `stride` parameters', function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -200,8 +196,7 @@ tape( 'the function supports negative `stride` parameters', function test( t ) {
 		0
 	]);
 
-	N = floor( x.length / 2 );
-	v = dmskmax( N, x, -2, mask, -2 );
+	v = dmskmax( 5, x, -2, mask, -2 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
@@ -212,7 +207,6 @@ tape( 'the function supports view offsets', function test( t ) {
 	var mask1;
 	var x0;
 	var x1;
-	var N;
 	var v;
 
 	x0 = new Float64Array([
@@ -244,9 +238,8 @@ tape( 'the function supports view offsets', function test( t ) {
 
 	x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
 	mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
-	N = floor( x1.length/2 );
 
-	v = dmskmax( N, x1, 2, mask1, 2 );
+	v = dmskmax( 5, x1, 2, mask1, 2 );
 	t.strictEqual( v, 4.0, 'returns expected value' );
 
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/test/test.dmskmax.native.js b/lib/node_modules/@stdlib/stats/base/dmskmax/test/test.dmskmax.native.js
index 8630ceda8a96..583a745ead4f 100644
--- a/lib/node_modules/@stdlib/stats/base/dmskmax/test/test.dmskmax.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dmskmax/test/test.dmskmax.native.js
@@ -22,7 +22,6 @@
 
 var resolve = require( 'path' ).resolve;
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' );
 var Float64Array = require( '@stdlib/array/float64' );
@@ -142,7 +141,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 
 tape( 'the function supports `stride` parameters', opts, function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -171,8 +169,7 @@ tape( 'the function supports `stride` parameters', opts, function test( t ) {
 		1
 	]);
 
-	N = floor( x.length / 2 );
-	v = dmskmax( N, x, 2, mask, 2 );
+	v = dmskmax( 5, x, 2, mask, 2 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
@@ -180,7 +177,6 @@ tape( 'the function supports `stride` parameters', opts, function test( t ) {
 
 tape( 'the function supports negative `stride` parameters', opts, function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -209,8 +205,7 @@ tape( 'the function supports negative `stride` parameters', opts, function test(
 		0
 	]);
 
-	N = floor( x.length / 2 );
-	v = dmskmax( N, x, -2, mask, -2 );
+	v = dmskmax( 5, x, -2, mask, -2 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
@@ -221,7 +216,6 @@ tape( 'the function supports view offsets', opts, function test( t ) {
 	var mask1;
 	var x0;
 	var x1;
-	var N;
 	var v;
 
 	x0 = new Float64Array([
@@ -253,9 +247,8 @@ tape( 'the function supports view offsets', opts, function test( t ) {
 
 	x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
 	mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
-	N = floor( x1.length/2 );
 
-	v = dmskmax( N, x1, 2, mask1, 2 );
+	v = dmskmax( 5, x1, 2, mask1, 2 );
 	t.strictEqual( v, 4.0, 'returns expected value' );
 
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dmskmax/test/test.ndarray.js
index abd8a7319f58..57945b91c24a 100644
--- a/lib/node_modules/@stdlib/stats/base/dmskmax/test/test.ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/dmskmax/test/test.ndarray.js
@@ -21,7 +21,6 @@
 // MODULES //
 
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' );
 var Float64Array = require( '@stdlib/array/float64' );
@@ -133,7 +132,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 
 tape( 'the function supports `stride` parameters', function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -162,8 +160,7 @@ tape( 'the function supports `stride` parameters', function test( t ) {
 		1
 	]);
 
-	N = floor( x.length / 2 );
-	v = dmskmax( N, x, 2, 0, mask, 2, 0 );
+	v = dmskmax( 5, x, 2, 0, mask, 2, 0 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
@@ -171,7 +168,6 @@ tape( 'the function supports `stride` parameters', function test( t ) {
 
 tape( 'the function supports negative `stride` parameters', function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -200,8 +196,7 @@ tape( 'the function supports negative `stride` parameters', function test( t ) {
 		0
 	]);
 
-	N = floor( x.length / 2 );
-	v = dmskmax( N, x, -2, 8, mask, -2, 8 );
+	v = dmskmax( 5, x, -2, 8, mask, -2, 8 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
@@ -209,7 +204,6 @@ tape( 'the function supports negative `stride` parameters', function test( t ) {
 
 tape( 'the function supports `offset` parameters', function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -237,9 +231,8 @@ tape( 'the function supports `offset` parameters', function test( t ) {
 		1,
 		1  // 4
 	]);
-	N = floor( x.length / 2 );
 
-	v = dmskmax( N, x, 2, 1, mask, 2, 1 );
+	v = dmskmax( 5, x, 2, 1, mask, 2, 1 );
 	t.strictEqual( v, 4.0, 'returns expected value' );
 
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/dmskmax/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmskmax/test/test.ndarray.native.js
index ed6c5d1b9010..aaa0cc9723ae 100644
--- a/lib/node_modules/@stdlib/stats/base/dmskmax/test/test.ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dmskmax/test/test.ndarray.native.js
@@ -22,7 +22,6 @@
 
 var resolve = require( 'path' ).resolve;
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' );
 var Float64Array = require( '@stdlib/array/float64' );
@@ -120,7 +119,7 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu
 	v = dmskmax( 0, x, 1, 0, mask, 1, 0 );
 	t.strictEqual( isnan( v ), true, 'returns expected value' );
 
-	v = dmskmax( -1, x, 1, 0, mask, 1 );
+	v = dmskmax( -1, x, 1, 0, mask, 1, 0 );
 	t.strictEqual( isnan( v ), true, 'returns expected value' );
 
 	t.end();
@@ -142,7 +141,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 
 tape( 'the function supports `stride` parameters', opts, function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -171,8 +169,7 @@ tape( 'the function supports `stride` parameters', opts, function test( t ) {
 		1
 	]);
 
-	N = floor( x.length / 2 );
-	v = dmskmax( N, x, 2, 0, mask, 2, 0 );
+	v = dmskmax( 5, x, 2, 0, mask, 2, 0 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
@@ -180,7 +177,6 @@ tape( 'the function supports `stride` parameters', opts, function test( t ) {
 
 tape( 'the function supports negative `stride` parameters', opts, function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -209,8 +205,7 @@ tape( 'the function supports negative `stride` parameters', opts, function test(
 		0
 	]);
 
-	N = floor( x.length / 2 );
-	v = dmskmax( N, x, -2, 8, mask, -2, 8 );
+	v = dmskmax( 5, x, -2, 8, mask, -2, 8 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
@@ -218,7 +213,6 @@ tape( 'the function supports negative `stride` parameters', opts, function test(
 
 tape( 'the function supports `offset` parameters', opts, function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -246,9 +240,8 @@ tape( 'the function supports `offset` parameters', opts, function test( t ) {
 		1,
 		1  // 4
 	]);
-	N = floor( x.length / 2 );
 
-	v = dmskmax( N, x, 2, 1, mask, 2, 1 );
+	v = dmskmax( 5, x, 2, 1, mask, 2, 1 );
 	t.strictEqual( v, 4.0, 'returns expected value' );
 
 	t.end();

From f6ea60722b203a110dc5b1fc9b4c9ddc4cdaacef Mon Sep 17 00:00:00 2001
From: Dhruv/ <154677013+DhruvArvindSingh@users.noreply.github.com>
Date: Fri, 3 Jan 2025 02:46:34 +0530
Subject: [PATCH 22/87] refactor: update `stats/base/snanvariance` native addon
 from C++ to C

PR-URL: https://github.com/stdlib-js/stdlib/pull/4471
Reviewed-by: Athan Reines <kgryte@gmail.com>
---
 .../stats/base/snanvariance/include.gypi      |   2 +-
 .../stats/base/snanvariance/manifest.json     |  43 +++++-
 .../stats/base/snanvariance/src/addon.c       |  45 ++++++
 .../stats/base/snanvariance/src/addon.cpp     | 130 ------------------
 4 files changed, 88 insertions(+), 132 deletions(-)
 create mode 100644 lib/node_modules/@stdlib/stats/base/snanvariance/src/addon.c
 delete mode 100644 lib/node_modules/@stdlib/stats/base/snanvariance/src/addon.cpp

diff --git a/lib/node_modules/@stdlib/stats/base/snanvariance/include.gypi b/lib/node_modules/@stdlib/stats/base/snanvariance/include.gypi
index 868c5c12e852..26476a8c2655 100644
--- a/lib/node_modules/@stdlib/stats/base/snanvariance/include.gypi
+++ b/lib/node_modules/@stdlib/stats/base/snanvariance/include.gypi
@@ -36,7 +36,7 @@
 
     # Source files:
     'src_files': [
-      '<(src_dir)/addon.cpp',
+      '<(src_dir)/addon.c',
       '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).src; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
     ],
 
diff --git a/lib/node_modules/@stdlib/stats/base/snanvariance/manifest.json b/lib/node_modules/@stdlib/stats/base/snanvariance/manifest.json
index 9aec45758e9d..c73cc59b6e70 100644
--- a/lib/node_modules/@stdlib/stats/base/snanvariance/manifest.json
+++ b/lib/node_modules/@stdlib/stats/base/snanvariance/manifest.json
@@ -1,5 +1,7 @@
 {
-  "options": {},
+  "options": {
+    "task": "build"
+  },
   "fields": [
     {
       "field": "src",
@@ -24,6 +26,45 @@
   ],
   "confs": [
     {
+      "task": "build",
+      "src": [
+        "./src/snanvariance.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [
+        "-lm"
+      ],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/napi/export",
+        "@stdlib/napi/argv",
+        "@stdlib/napi/argv-int64",
+        "@stdlib/napi/argv-float",
+        "@stdlib/napi/argv-strided-float32array",
+        "@stdlib/stats/base/snanvariancepn",
+        "@stdlib/napi/create-double"
+      ]
+    },
+    {
+      "task": "benchmark",
+      "src": [
+        "./src/snanvariance.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [
+        "-lm"
+      ],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/stats/base/snanvariancepn"
+      ]
+    },
+    {
+      "task": "examples",
       "src": [
         "./src/snanvariance.c"
       ],
diff --git a/lib/node_modules/@stdlib/stats/base/snanvariance/src/addon.c b/lib/node_modules/@stdlib/stats/base/snanvariance/src/addon.c
new file mode 100644
index 000000000000..bde260f3d357
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/snanvariance/src/addon.c
@@ -0,0 +1,45 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/snanvariance.h"
+#include "stdlib/napi/export.h"
+#include "stdlib/napi/argv.h"
+#include "stdlib/napi/argv_int64.h"
+#include "stdlib/napi/argv_float.h"
+#include "stdlib/napi/argv_strided_float32array.h"
+#include "stdlib/napi/create_double.h"
+#include <node_api.h>
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 4 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_FLOAT( env, correction, argv, 1 );
+	STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 2 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_snanvariance( N, correction, X, stride ), v );
+	return v;
+}
+
+STDLIB_NAPI_MODULE_EXPORT_FCN( addon )
diff --git a/lib/node_modules/@stdlib/stats/base/snanvariance/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/snanvariance/src/addon.cpp
deleted file mode 100644
index 43eb6036c054..000000000000
--- a/lib/node_modules/@stdlib/stats/base/snanvariance/src/addon.cpp
+++ /dev/null
@@ -1,130 +0,0 @@
-/**
-* @license Apache-2.0
-*
-* Copyright (c) 2020 The Stdlib Authors.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-*    http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-
-#include "stdlib/stats/base/snanvariance.h"
-#include <node_api.h>
-#include <stdint.h>
-#include <stdlib.h>
-#include <stdbool.h>
-#include <assert.h>
-
-/**
-* Add-on namespace.
-*/
-namespace stdlib_stats_base_snanvariance {
-
-	/**
-	* Computes the variance of a single-precision floating-point strided array ignoring `NaN` values.
-	*
-	* ## Notes
-	*
-	* -   When called from JavaScript, the function expects four arguments:
-	*
-	*     -   `N`: number of indexed elements
-	*     -   `correction`: degrees of freedom adjustment
-	*     -   `X`: input array
-	*     -   `stride`: stride length
-	*/
-	napi_value node_snanvariance( napi_env env, napi_callback_info info ) {
-		napi_status status;
-
-		size_t argc = 4;
-		napi_value argv[ 4 ];
-		status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr );
-		assert( status == napi_ok );
-
-		if ( argc < 4 ) {
-			napi_throw_error( env, nullptr, "invalid invocation. Must provide 4 arguments." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype0;
-		status = napi_typeof( env, argv[ 0 ], &vtype0 );
-		assert( status == napi_ok );
-		if ( vtype0 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype1;
-		status = napi_typeof( env, argv[ 1 ], &vtype1 );
-		assert( status == napi_ok );
-		if ( vtype1 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." );
-			return nullptr;
-		}
-
-		bool res;
-		status = napi_is_typedarray( env, argv[ 2 ], &res );
-		assert( status == napi_ok );
-		if ( res == false ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype3;
-		status = napi_typeof( env, argv[ 3 ], &vtype3 );
-		assert( status == napi_ok );
-		if ( vtype3 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." );
-			return nullptr;
-		}
-
-		int64_t N;
-		status = napi_get_value_int64( env, argv[ 0 ], &N );
-		assert( status == napi_ok );
-
-		double correction;
-		status = napi_get_value_double( env, argv[ 1 ], &correction );
-		assert( status == napi_ok );
-
-		int64_t stride;
-		status = napi_get_value_int64( env, argv[ 3 ], &stride );
-		assert( status == napi_ok );
-
-		napi_typedarray_type vtype2;
-		size_t xlen;
-		void *X;
-		status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr );
-		assert( status == napi_ok );
-		if ( vtype2 != napi_float32_array ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." );
-			return nullptr;
-		}
-		if ( (N-1)*llabs(stride) >= (int64_t)xlen ) {
-			napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." );
-			return nullptr;
-		}
-
-		napi_value v;
-		status = napi_create_double( env, (double)stdlib_strided_snanvariance( N, (float)correction, (float *)X, stride ), &v );
-		assert( status == napi_ok );
-
-		return v;
-	}
-
-	napi_value Init( napi_env env, napi_value exports ) {
-		napi_status status;
-		napi_value fcn;
-		status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_snanvariance, NULL, &fcn );
-		assert( status == napi_ok );
-		return fcn;
-	}
-
-	NAPI_MODULE( NODE_GYP_MODULE_NAME, Init )
-} // end namespace stdlib_stats_base_snanvariance

From 2d6423c72f094c554abdf61ecb9bb188846edc7c Mon Sep 17 00:00:00 2001
From: Aayush Khanna <96649223+aayush0325@users.noreply.github.com>
Date: Fri, 3 Jan 2025 02:56:37 +0530
Subject: [PATCH 23/87] feat: add C ndarray interface and refactor
 implementation for `stats/base/smskmax`

PR-URL: https://github.com/stdlib-js/stdlib/pull/4401
Co-authored-by: Athan Reines <kgryte@gmail.com>
Reviewed-by: Athan Reines <kgryte@gmail.com>
Co-authored-by: stdlib-bot <82920195+stdlib-bot@users.noreply.github.com>
---
 .../@stdlib/stats/base/smskmax/README.md      | 173 ++++++++++++++----
 .../stats/base/smskmax/benchmark/benchmark.js |  31 ++--
 .../smskmax/benchmark/benchmark.native.js     |  27 +--
 .../smskmax/benchmark/benchmark.ndarray.js    |  31 ++--
 .../benchmark/benchmark.ndarray.native.js     |  27 +--
 .../smskmax/benchmark/c/benchmark.length.c    |  56 +++++-
 .../@stdlib/stats/base/smskmax/docs/repl.txt  |  22 +--
 .../stats/base/smskmax/examples/c/example.c   |  10 +-
 .../stats/base/smskmax/examples/index.js      |  27 +--
 .../@stdlib/stats/base/smskmax/include.gypi   |   2 +-
 .../include/stdlib/stats/base/smskmax.h       |   8 +-
 .../@stdlib/stats/base/smskmax/lib/index.js   |   4 +-
 .../@stdlib/stats/base/smskmax/lib/ndarray.js |   4 +-
 .../stats/base/smskmax/lib/ndarray.native.js  |  20 +-
 .../@stdlib/stats/base/smskmax/lib/smskmax.js |  56 +-----
 .../@stdlib/stats/base/smskmax/manifest.json  |  73 +++++++-
 .../@stdlib/stats/base/smskmax/src/addon.c    |  66 +++++++
 .../@stdlib/stats/base/smskmax/src/addon.cpp  | 153 ----------------
 .../base/smskmax/src/{smskmax.c => main.c}    |  40 ++--
 .../stats/base/smskmax/test/test.ndarray.js   |  13 +-
 .../base/smskmax/test/test.ndarray.native.js  |  15 +-
 .../stats/base/smskmax/test/test.smskmax.js   |  13 +-
 .../base/smskmax/test/test.smskmax.native.js  |  13 +-
 23 files changed, 458 insertions(+), 426 deletions(-)
 create mode 100644 lib/node_modules/@stdlib/stats/base/smskmax/src/addon.c
 delete mode 100644 lib/node_modules/@stdlib/stats/base/smskmax/src/addon.cpp
 rename lib/node_modules/@stdlib/stats/base/smskmax/src/{smskmax.c => main.c} (58%)

diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/README.md b/lib/node_modules/@stdlib/stats/base/smskmax/README.md
index e2ad2ab9bbfa..71bb372c047c 100644
--- a/lib/node_modules/@stdlib/stats/base/smskmax/README.md
+++ b/lib/node_modules/@stdlib/stats/base/smskmax/README.md
@@ -38,7 +38,7 @@ var smskmax = require( '@stdlib/stats/base/smskmax' );
 
 #### smskmax( N, x, strideX, mask, strideMask )
 
-Computes the maximum value of a single-precision floating-point strided array `x` according to a `mask`.
+Computes the maximum value of a single-precision floating-point strided array according to a mask.
 
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
@@ -55,22 +55,20 @@ The function has the following parameters:
 
 -   **N**: number of indexed elements.
 -   **x**: input [`Float32Array`][@stdlib/array/float32].
--   **strideX**: index increment for `x`.
+-   **strideX**: stride length for `x`.
 -   **mask**: mask [`Uint8Array`][@stdlib/array/uint8]. If a `mask` array element is `0`, the corresponding element in `x` is considered valid and **included** in computation. If a `mask` array element is `1`, the corresponding element in `x` is considered invalid/missing and **excluded** from computation.
--   **strideMask**: index increment for `mask`.
+-   **strideMask**: stride length for `mask`.
 
-The `N` and `stride` parameters determine which elements are accessed at runtime. For example, to compute the maximum value of every other element in `x`,
+The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the maximum value of every other element in `x`,
 
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
 var Uint8Array = require( '@stdlib/array/uint8' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x = new Float32Array( [ 1.0, 2.0, -7.0, -2.0, 4.0, 3.0, 5.0, 6.0 ] );
 var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] );
-var N = floor( x.length / 2 );
 
-var v = smskmax( N, x, 2, mask, 2 );
+var v = smskmax( 4, x, 2, mask, 2 );
 // returns 4.0
 ```
 
@@ -81,7 +79,6 @@ Note that indexing is relative to the first index. To introduce offsets, use [`t
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
 var Uint8Array = require( '@stdlib/array/uint8' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x0 = new Float32Array( [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, 5.0, 6.0 ] );
 var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
@@ -89,15 +86,13 @@ var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd
 var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] );
 var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
 
-var N = floor( x0.length / 2 );
-
-var v = smskmax( N, x1, 2, mask1, 2 );
+var v = smskmax( 4, x1, 2, mask1, 2 );
 // returns 4.0
 ```
 
 #### smskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )
 
-Computes the maximum value of a single-precision floating-point strided array according to a `mask` and using alternative indexing semantics.
+Computes the maximum value of a single-precision floating-point strided array according to a mask and using alternative indexing semantics.
 
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
@@ -115,18 +110,16 @@ The function has the following additional parameters:
 -   **offsetX**: starting index for `x`.
 -   **offsetMask**: starting index for `mask`.
 
-While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the maximum value for every other value in `x` starting from the second value
+While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on a starting indices. For example, to calculate the maximum value for every other element in `x` starting from the second element
 
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
 var Uint8Array = require( '@stdlib/array/uint8' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x = new Float32Array( [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, 5.0, 6.0 ] );
 var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] );
-var N = floor( x.length / 2 );
 
-var v = smskmax.ndarray( N, x, 2, 1, mask, 2, 1 );
+var v = smskmax.ndarray( 4, x, 2, 1, mask, 2, 1 );
 // returns 4.0
 ```
 
@@ -151,26 +144,19 @@ var v = smskmax.ndarray( N, x, 2, 1, mask, 2, 1 );
 <!-- eslint no-undef: "error" -->
 
 ```javascript
-var randu = require( '@stdlib/random/base/randu' );
-var round = require( '@stdlib/math/base/special/round' );
-var Float32Array = require( '@stdlib/array/float32' );
-var Uint8Array = require( '@stdlib/array/uint8' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var bernoulli = require( '@stdlib/random/array/bernoulli' );
 var smskmax = require( '@stdlib/stats/base/smskmax' );
 
-var mask;
-var x;
-var i;
-
-x = new Float32Array( 10 );
-mask = new Uint8Array( x.length );
-for ( i = 0; i < x.length; i++ ) {
-    if ( randu() < 0.2 ) {
-        mask[ i ] = 1;
-    } else {
-        mask[ i ] = 0;
-    }
-    x[ i ] = round( (randu()*100.0) - 50.0 );
-}
+var uniformOptions = {
+    'dtype': 'float32'
+};
+var bernoulliOptions = {
+    'dtype': 'uint8'
+};
+
+var x = uniform( 10, -50.0, 50.0, uniformOptions );
+var mask = bernoulli( x.length, 0.2, bernoulliOptions );
 console.log( x );
 console.log( mask );
 
@@ -182,6 +168,125 @@ console.log( v );
 
 <!-- /.examples -->
 
+<!-- C usage documentation. -->
+
+<section class="usage">
+
+### Usage
+
+```c
+#include "stdlib/stats/base/smskmax.h"
+```
+
+#### stdlib_strided_smskmax( N, \*X, strideX, \*Mask, strideMask )
+
+Computes the maximum value of a single-precision floating-point strided array according to a mask.
+
+```c
+#include <stdint.h>
+
+const float x[] = { 1.0f, -2.0f, 2.0f };
+const uint8_t mask[] = { 0, 1, 0 };
+
+float v = stdlib_strided_smskmax( 3, x, 1, mask, 1 );
+// returns 2.0f
+```
+
+The function accepts the following arguments:
+
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **X**: `[in] float*` input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+-   **Mask**: `[in] uint8_t*` mask array. If a `Mask` array element is `0`, the corresponding element in `X` is considered valid and included in computation. If a `Mask` array element is `1`, the corresponding element in `X` is considered invalid/missing and excluded from computation.
+-   **strideMask**: `[in] CBLAS_INT` stride length for `Mask`.
+
+```c
+float stdlib_strided_smskmax( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const uint8_t *Mask, const CBLAS_INT strideMask );
+```
+
+<!-- lint disable maximum-heading-length -->
+
+#### stdlib_strided_smskmax_ndarray( N, \*X, strideX, offsetX, \*Mask, strideMask, offsetMask )
+
+Computes the maximum value of a single-precision floating-point strided array according to a mask and using alternative indexing semantics.
+
+```c
+#include <stdint.h>
+
+const float x[] = { 1.0f, -2.0f, 2.0f };
+const uint8_t mask[] = { 0, 1, 0 };
+
+float v = stdlib_strided_smskmax( 3, x, 1, 0, mask, 1, 0 );
+// returns 2.0f
+```
+
+The function accepts the following arguments:
+
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **X**: `[in] float*` input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+-   **offsetX**: `[in] CBLAS_INT` starting index for `X`.
+-   **Mask**: `[in] uint8_t*` mask array. If a `Mask` array element is `0`, the corresponding element in `X` is considered valid and included in computation. If a `Mask` array element is `1`, the corresponding element in `X` is considered invalid/missing and excluded from computation.
+-   **strideMask**: `[in] CBLAS_INT` stride length for `Mask`.
+-   **offsetMask**: `[in] CBLAS_INT` starting index for `Mask`.
+
+```c
+float stdlib_strided_smskmax_ndarray( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const uint8_t *Mask, const CBLAS_INT strideMask, const CBLAS_INT offsetMask );
+```
+
+</section>
+
+<!-- /.usage -->
+
+<!-- C API usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="notes">
+
+</section>
+
+<!-- /.notes -->
+
+<!-- C API usage examples. -->
+
+<section class="examples">
+
+### Examples
+
+```c
+#include "stdlib/stats/base/smskmax.h"
+#include <stdint.h>
+#include <stdio.h>
+
+int main( void ) {
+    // Create a strided array:
+    const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f };
+
+    // Create a mask array:
+    const uint8_t mask[] = { 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 };
+
+    // Specify the number of elements:
+    const int N = 5;
+
+    // Specify the stride lengths:
+    const int strideX = 2;
+    const int strideMask = 2;
+
+    // Compute the maximum value:
+    float v = stdlib_strided_smskmax( N, x, strideX, mask, strideMask );
+
+    // Print the result:
+    printf( "max: %f\n", v );
+}
+```
+
+</section>
+
+<!-- /.examples -->
+
+</section>
+
+<!-- /.c -->
+
 <!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
 
 <section class="related">
diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/smskmax/benchmark/benchmark.js
index 47997f5b23a1..b254209a6c8f 100644
--- a/lib/node_modules/@stdlib/stats/base/smskmax/benchmark/benchmark.js
+++ b/lib/node_modules/@stdlib/stats/base/smskmax/benchmark/benchmark.js
@@ -21,15 +21,24 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var bernoulli = require( '@stdlib/random/array/bernoulli' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float32Array = require( '@stdlib/array/float32' );
-var Uint8Array = require( '@stdlib/array/uint8' );
 var pkg = require( './../package.json' ).name;
 var smskmax = require( './../lib/smskmax.js' );
 
 
+// VARIABLES //
+
+var uniformOptions = {
+	'dtype': 'float32'
+};
+var bernoulliOptions = {
+	'dtype': 'uint8'
+};
+
+
 // FUNCTIONS //
 
 /**
@@ -40,20 +49,8 @@ var smskmax = require( './../lib/smskmax.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var mask;
-	var x;
-	var i;
-
-	x = new Float32Array( len );
-	mask = new Uint8Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		if ( randu() < 0.2 ) {
-			mask[ i ] = 1;
-		} else {
-			mask[ i ] = 0;
-		}
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
+	var mask = bernoulli( len, 0.2, bernoulliOptions );
+	var x = uniform( len, -10.0, 10.0, uniformOptions );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/smskmax/benchmark/benchmark.native.js
index 1dda873319e0..34565afb2736 100644
--- a/lib/node_modules/@stdlib/stats/base/smskmax/benchmark/benchmark.native.js
+++ b/lib/node_modules/@stdlib/stats/base/smskmax/benchmark/benchmark.native.js
@@ -22,11 +22,10 @@
 
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var bernoulli = require( '@stdlib/random/array/bernoulli' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float32Array = require( '@stdlib/array/float32' );
-var Uint8Array = require( '@stdlib/array/uint8' );
 var tryRequire = require( '@stdlib/utils/try-require' );
 var pkg = require( './../package.json' ).name;
 
@@ -37,6 +36,12 @@ var smskmax = tryRequire( resolve( __dirname, './../lib/smskmax.native.js' ) );
 var opts = {
 	'skip': ( smskmax instanceof Error )
 };
+var uniformOptions = {
+	'dtype': 'float32'
+};
+var bernoulliOptions = {
+	'dtype': 'uint8'
+};
 
 
 // FUNCTIONS //
@@ -49,20 +54,8 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var mask;
-	var x;
-	var i;
-
-	x = new Float32Array( len );
-	mask = new Uint8Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		if ( randu() < 0.2 ) {
-			mask[ i ] = 1;
-		} else {
-			mask[ i ] = 0;
-		}
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
+	var mask = bernoulli( len, 0.2, bernoulliOptions );
+	var x = uniform( len, -10.0, 10.0, uniformOptions );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/smskmax/benchmark/benchmark.ndarray.js
index 8688bb4b952f..9973aec76ca4 100644
--- a/lib/node_modules/@stdlib/stats/base/smskmax/benchmark/benchmark.ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/smskmax/benchmark/benchmark.ndarray.js
@@ -21,15 +21,24 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var bernoulli = require( '@stdlib/random/array/bernoulli' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float32Array = require( '@stdlib/array/float32' );
-var Uint8Array = require( '@stdlib/array/uint8' );
 var pkg = require( './../package.json' ).name;
 var smskmax = require( './../lib/ndarray.js' );
 
 
+// VARIABLES //
+
+var uniformOptions = {
+	'dtype': 'float32'
+};
+var bernoulliOptions = {
+	'dtype': 'uint8'
+};
+
+
 // FUNCTIONS //
 
 /**
@@ -40,20 +49,8 @@ var smskmax = require( './../lib/ndarray.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var mask;
-	var x;
-	var i;
-
-	x = new Float32Array( len );
-	mask = new Uint8Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		if ( randu() < 0.2 ) {
-			mask[ i ] = 1;
-		} else {
-			mask[ i ] = 0;
-		}
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
+	var mask = bernoulli( len, 0.2, bernoulliOptions );
+	var x = uniform( len, -10.0, 10.0, uniformOptions );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/smskmax/benchmark/benchmark.ndarray.native.js
index 428acc411123..bbb9f4179406 100644
--- a/lib/node_modules/@stdlib/stats/base/smskmax/benchmark/benchmark.ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/smskmax/benchmark/benchmark.ndarray.native.js
@@ -22,11 +22,10 @@
 
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var bernoulli = require( '@stdlib/random/array/bernoulli' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float32Array = require( '@stdlib/array/float32' );
-var Uint8Array = require( '@stdlib/array/uint8' );
 var tryRequire = require( '@stdlib/utils/try-require' );
 var pkg = require( './../package.json' ).name;
 
@@ -37,6 +36,12 @@ var smskmax = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) );
 var opts = {
 	'skip': ( smskmax instanceof Error )
 };
+var uniformOptions = {
+	'dtype': 'float32'
+};
+var bernoulliOptions = {
+	'dtype': 'uint8'
+};
 
 
 // FUNCTIONS //
@@ -49,20 +54,8 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var mask;
-	var x;
-	var i;
-
-	x = new Float32Array( len );
-	mask = new Uint8Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		if ( randu() < 0.2 ) {
-			mask[ i ] = 1;
-		} else {
-			mask[ i ] = 0;
-		}
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
+	var mask = bernoulli( len, 0.2, bernoulliOptions );
+	var x = uniform( len, -10.0, 10.0, uniformOptions );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/smskmax/benchmark/c/benchmark.length.c
index ec8aea961efe..93db04f3976e 100644
--- a/lib/node_modules/@stdlib/stats/base/smskmax/benchmark/c/benchmark.length.c
+++ b/lib/node_modules/@stdlib/stats/base/smskmax/benchmark/c/benchmark.length.c
@@ -94,7 +94,7 @@ static float rand_float( void ) {
 * @param len          array length
 * @return             elapsed time in seconds
 */
-static double benchmark( int iterations, int len ) {
+static double benchmark1( int iterations, int len ) {
 	unsigned char mask[ len ];
 	double elapsed;
 	float x[ len ];
@@ -113,6 +113,7 @@ static double benchmark( int iterations, int len ) {
 	v = 0.0f;
 	t = tic();
 	for ( i = 0; i < iterations; i++ ) {
+		// cppcheck-suppress uninitvar
 		v = stdlib_strided_smskmax( len, x, 1, mask, 1 );
 		if ( v != v ) {
 			printf( "should not return NaN\n" );
@@ -126,6 +127,46 @@ static double benchmark( int iterations, int len ) {
 	return elapsed;
 }
 
+/**
+* Runs a benchmark.
+*
+* @param iterations   number of iterations
+* @param len          array length
+* @return             elapsed time in seconds
+*/
+static double benchmark2( int iterations, int len ) {
+	unsigned char mask[ len ];
+	double elapsed;
+	float x[ len ];
+	float v;
+	double t;
+	int i;
+
+	for ( i = 0; i < len; i++ ) {
+		if ( rand_float() < 0.2f ) {
+			mask[ i ] = 1; // missing
+		} else {
+			mask[ i ] = 0;
+		}
+		x[ i ] = ( rand_float() * 20000.0f ) - 10000.0f;
+	}
+	v = 0.0f;
+	t = tic();
+	for ( i = 0; i < iterations; i++ ) {
+		// cppcheck-suppress uninitvar
+		v = stdlib_strided_smskmax_ndarray( len, x, 1, 0, mask, 1, 0 );
+		if ( v != v ) {
+			printf( "should not return NaN\n" );
+			break;
+		}
+	}
+	elapsed = tic() - t;
+	if ( v != v ) {
+		printf( "should not return NaN\n" );
+	}
+	return elapsed;
+}
+
 /**
 * Main execution sequence.
 */
@@ -148,7 +189,18 @@ int main( void ) {
 		for ( j = 0; j < REPEATS; j++ ) {
 			count += 1;
 			printf( "# c::%s:len=%d\n", NAME, len );
-			elapsed = benchmark( iter, len );
+			elapsed = benchmark1( iter, len );
+			print_results( iter, elapsed );
+			printf( "ok %d benchmark finished\n", count );
+		}
+	}
+	for ( i = MIN; i <= MAX; i++ ) {
+		len = pow( 10, i );
+		iter = ITERATIONS / pow( 10, i-1 );
+		for ( j = 0; j < REPEATS; j++ ) {
+			count += 1;
+			printf( "# c::%s:ndarray:len=%d\n", NAME, len );
+			elapsed = benchmark2( iter, len );
 			print_results( iter, elapsed );
 			printf( "ok %d benchmark finished\n", count );
 		}
diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/smskmax/docs/repl.txt
index fdf6aeed93b9..1f760374fe79 100644
--- a/lib/node_modules/@stdlib/stats/base/smskmax/docs/repl.txt
+++ b/lib/node_modules/@stdlib/stats/base/smskmax/docs/repl.txt
@@ -3,8 +3,8 @@
     Computes the maximum value of a single-precision floating-point strided
     array according to a mask.
 
-    The `N` and `stride` parameters determine which elements are accessed at
-    runtime.
+    The `N` and stride parameters determine which elements in the strided arrays
+    are accessed at runtime.
 
     Indexing is relative to the first index. To introduce offsets, use a typed
     array views.
@@ -26,13 +26,13 @@
         Input array.
 
     strideX: integer
-        Index increment for `x`.
+        Stride Length for `x`.
 
     mask: Uint8Array
         Mask array.
 
     strideMask: integer
-        Index increment for `mask`.
+        Stride Length for `mask`.
 
     Returns
     -------
@@ -50,8 +50,7 @@
     // Using `N` and `stride` parameters:
     > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );
     > mask = new {{alias:@stdlib/array/uint8}}( [ 0, 0, 0, 0, 0, 0, 1 ] );
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > {{alias}}( N, x, 2, mask, 2 )
+    > {{alias}}( 3, x, 2, mask, 2 )
     2.0
 
     // Using view offsets:
@@ -59,10 +58,10 @@
     > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );
     > var mask0 = new {{alias:@stdlib/array/uint8}}( [ 0, 0, 0, 0, 0, 0, 1 ] );
     > var mask1 = new {{alias:@stdlib/array/uint8}}( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );
-    > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );
-    > {{alias}}( N, x1, 2, mask1, 2 )
+    > {{alias}}( 3, x1, 2, mask1, 2 )
     2.0
 
+
 {{alias}}.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )
     Computes the maximum value of a single-precision floating-point strided
     array according to a mask and using alternative indexing semantics.
@@ -80,7 +79,7 @@
         Input array.
 
     strideX: integer
-        Index increment for `x`.
+        Stride Length for `x`.
 
     offsetX: integer
         Starting index for `x`.
@@ -89,7 +88,7 @@
         Mask array.
 
     strideMask: integer
-        Index increment for `mask`.
+        Stride Length for `mask`.
 
     offsetMask: integer
         Starting index for `mask`.
@@ -110,8 +109,7 @@
     // Using offset parameter:
     > x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );
     > mask = new {{alias:@stdlib/array/uint8}}( [ 0, 0, 0, 0, 0, 0, 1 ] );
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > {{alias}}.ndarray( N, x, 2, 1, mask, 2, 1 )
+    > {{alias}}.ndarray( 3, x, 2, 1, mask, 2, 1 )
     2.0
 
     See Also
diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/smskmax/examples/c/example.c
index 7104cc61b476..ef9f92b60f1a 100644
--- a/lib/node_modules/@stdlib/stats/base/smskmax/examples/c/example.c
+++ b/lib/node_modules/@stdlib/stats/base/smskmax/examples/c/example.c
@@ -22,17 +22,17 @@
 
 int main( void ) {
 	// Create a strided array:
-	float x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 };
+	const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 9.0f, 10.0f };
 
 	// Create a mask array:
-	uint8_t mask[] = { 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 };
+	const uint8_t mask[] = { 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 };
 
 	// Specify the number of elements:
-	int64_t N = 5;
+	const int N = 5;
 
 	// Specify the stride lengths:
-	int64_t strideX = 2;
-	int64_t strideMask = 2;
+	const int strideX = 2;
+	const int strideMask = 2;
 
 	// Compute the maximum value:
 	float v = stdlib_strided_smskmax( N, x, strideX, mask, strideMask );
diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/examples/index.js b/lib/node_modules/@stdlib/stats/base/smskmax/examples/index.js
index f591561cf536..08c7e8393443 100644
--- a/lib/node_modules/@stdlib/stats/base/smskmax/examples/index.js
+++ b/lib/node_modules/@stdlib/stats/base/smskmax/examples/index.js
@@ -18,26 +18,19 @@
 
 'use strict';
 
-var randu = require( '@stdlib/random/base/randu' );
-var round = require( '@stdlib/math/base/special/round' );
-var Float32Array = require( '@stdlib/array/float32' );
-var Uint8Array = require( '@stdlib/array/uint8' );
+var uniform = require( '@stdlib/random/array/uniform' );
+var bernoulli = require( '@stdlib/random/array/bernoulli' );
 var smskmax = require( './../lib' );
 
-var mask;
-var x;
-var i;
+var uniformOptions = {
+	'dtype': 'float32'
+};
+var bernoulliOptions = {
+	'dtype': 'uint8'
+};
 
-x = new Float32Array( 10 );
-mask = new Uint8Array( x.length );
-for ( i = 0; i < x.length; i++ ) {
-	if ( randu() < 0.2 ) {
-		mask[ i ] = 1;
-	} else {
-		mask[ i ] = 0;
-	}
-	x[ i ] = round( (randu()*100.0) - 50.0 );
-}
+var x = uniform( 10, -50.0, 50.0, uniformOptions );
+var mask = bernoulli( x.length, 0.2, bernoulliOptions );
 console.log( x );
 console.log( mask );
 
diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/include.gypi b/lib/node_modules/@stdlib/stats/base/smskmax/include.gypi
index 868c5c12e852..26476a8c2655 100644
--- a/lib/node_modules/@stdlib/stats/base/smskmax/include.gypi
+++ b/lib/node_modules/@stdlib/stats/base/smskmax/include.gypi
@@ -36,7 +36,7 @@
 
     # Source files:
     'src_files': [
-      '<(src_dir)/addon.cpp',
+      '<(src_dir)/addon.c',
       '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).src; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
     ],
 
diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/include/stdlib/stats/base/smskmax.h b/lib/node_modules/@stdlib/stats/base/smskmax/include/stdlib/stats/base/smskmax.h
index e10140426aba..e7ea5308e1f0 100644
--- a/lib/node_modules/@stdlib/stats/base/smskmax/include/stdlib/stats/base/smskmax.h
+++ b/lib/node_modules/@stdlib/stats/base/smskmax/include/stdlib/stats/base/smskmax.h
@@ -19,6 +19,7 @@
 #ifndef STDLIB_STATS_BASE_SMSKMAX_H
 #define STDLIB_STATS_BASE_SMSKMAX_H
 
+#include "stdlib/blas/base/shared.h"
 #include <stdint.h>
 
 /*
@@ -31,7 +32,12 @@ extern "C" {
 /**
 * Computes the maximum value of a single-precision floating-point strided array according to a mask.
 */
-float stdlib_strided_smskmax( const int64_t N, const float *X, const int64_t strideX, const uint8_t *Mask, const int64_t strideMask );
+float API_SUFFIX(stdlib_strided_smskmax)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const uint8_t *Mask, const CBLAS_INT strideMask );
+
+/**
+* Computes the maximum value of a single-precision floating-point strided array according to a mask and using alternative indexing semantics.
+*/
+float API_SUFFIX(stdlib_strided_smskmax_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const uint8_t *Mask, const CBLAS_INT strideMask, const CBLAS_INT offsetMask );
 
 #ifdef __cplusplus
 }
diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/lib/index.js b/lib/node_modules/@stdlib/stats/base/smskmax/lib/index.js
index dac40cd51c57..dcd23b298e2d 100644
--- a/lib/node_modules/@stdlib/stats/base/smskmax/lib/index.js
+++ b/lib/node_modules/@stdlib/stats/base/smskmax/lib/index.js
@@ -37,14 +37,12 @@
 * @example
 * var Float32Array = require( '@stdlib/array/float32' );
 * var Uint8Array = require( '@stdlib/array/uint8' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 * var smskmax = require( '@stdlib/stats/base/smskmax' );
 *
 * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
 * var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 ] );
-* var N = floor( x.length / 2 );
 *
-* var v = smskmax.ndarray( N, x, 2, 1, mask, 2, 1 );
+* var v = smskmax.ndarray( 5, x, 2, 1, mask, 2, 1 );
 * // returns 4.0
 */
 
diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/smskmax/lib/ndarray.js
index 645818caaa6b..5223d6302d3c 100644
--- a/lib/node_modules/@stdlib/stats/base/smskmax/lib/ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/smskmax/lib/ndarray.js
@@ -41,13 +41,11 @@ var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' );
 * @example
 * var Float32Array = require( '@stdlib/array/float32' );
 * var Uint8Array = require( '@stdlib/array/uint8' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 *
 * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
 * var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 ] );
-* var N = floor( x.length / 2 );
 *
-* var v = smskmax( N, x, 2, 1, mask, 2, 1 );
+* var v = smskmax( 5, x, 2, 1, mask, 2, 1 );
 * // returns 4.0
 */
 function smskmax( N, x, strideX, offsetX, mask, strideMask, offsetMask ) {
diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/smskmax/lib/ndarray.native.js
index ea92fb555efb..837b973303ec 100644
--- a/lib/node_modules/@stdlib/stats/base/smskmax/lib/ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/smskmax/lib/ndarray.native.js
@@ -20,9 +20,7 @@
 
 // MODULES //
 
-var Float32Array = require( '@stdlib/array/float32' );
-var Uint8Array = require( '@stdlib/array/uint8' );
-var addon = require( './smskmax.native.js' );
+var addon = require( './../src/addon.node' );
 
 
 // MAIN //
@@ -42,27 +40,15 @@ var addon = require( './smskmax.native.js' );
 * @example
 * var Float32Array = require( '@stdlib/array/float32' );
 * var Uint8Array = require( '@stdlib/array/uint8' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 *
 * var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
 * var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 0, 0, 1, 1 ] );
-* var N = floor( x.length / 2 );
 *
-* var v = smskmax( N, x, 2, 1, mask, 2, 1 );
+* var v = smskmax( 5, x, 2, 1, mask, 2, 1 );
 * // returns 4.0
 */
 function smskmax( N, x, strideX, offsetX, mask, strideMask, offsetMask ) {
-	var viewX;
-	var viewM;
-	if ( strideX < 0 ) {
-		offsetX += (N-1) * strideX;
-	}
-	if ( strideMask < 0 ) {
-		offsetMask += (N-1) * strideMask;
-	}
-	viewX = new Float32Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offsetX), x.length-offsetX ); // eslint-disable-line max-len
-	viewM = new Uint8Array( mask.buffer, mask.byteOffset+(mask.BYTES_PER_ELEMENT*offsetMask), mask.length-offsetMask ); // eslint-disable-line max-len
-	return addon( N, viewX, strideX, viewM, strideMask );
+	return addon.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask ); // eslint-disable-line max-len
 }
 
 
diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/lib/smskmax.js b/lib/node_modules/@stdlib/stats/base/smskmax/lib/smskmax.js
index f7f26f8618fb..11616551b44d 100644
--- a/lib/node_modules/@stdlib/stats/base/smskmax/lib/smskmax.js
+++ b/lib/node_modules/@stdlib/stats/base/smskmax/lib/smskmax.js
@@ -20,8 +20,8 @@
 
 // MODULES //
 
-var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
-var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' );
+var stride2offset = require( '@stdlib/strided/base/stride2offset' );
+var ndarray = require( './ndarray.js' );
 
 
 // MAIN //
@@ -47,55 +47,9 @@ var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' );
 * // returns 2.0
 */
 function smskmax( N, x, strideX, mask, strideMask ) {
-	var max;
-	var ix;
-	var im;
-	var v;
-	var i;
-
-	if ( N <= 0 ) {
-		return NaN;
-	}
-	if ( strideX < 0 ) {
-		ix = (1-N) * strideX;
-	} else {
-		ix = 0;
-	}
-	if ( strideMask < 0 ) {
-		im = (1-N) * strideMask;
-	} else {
-		im = 0;
-	}
-	for ( i = 0; i < N; i++ ) {
-		if ( mask[ im ] === 0 ) {
-			break;
-		}
-		ix += strideX;
-		im += strideMask;
-	}
-	if ( i === N ) {
-		return NaN;
-	}
-	max = x[ ix ];
-	if ( isnanf( max ) ) {
-		return max;
-	}
-	i += 1;
-	for ( i; i < N; i++ ) {
-		ix += strideX;
-		im += strideMask;
-		if ( mask[ im ] ) {
-			continue;
-		}
-		v = x[ ix ];
-		if ( isnanf( v ) ) {
-			return v;
-		}
-		if ( v > max || ( v === max && isPositiveZerof( v ) ) ) {
-			max = v;
-		}
-	}
-	return max;
+	var ox = stride2offset( N, strideX );
+	var om = stride2offset( N, strideMask );
+	return ndarray( N, x, strideX, ox, mask, strideMask, om );
 }
 
 
diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/manifest.json b/lib/node_modules/@stdlib/stats/base/smskmax/manifest.json
index 28dc8675bba9..cce54abfb135 100644
--- a/lib/node_modules/@stdlib/stats/base/smskmax/manifest.json
+++ b/lib/node_modules/@stdlib/stats/base/smskmax/manifest.json
@@ -1,5 +1,8 @@
 {
-  "options": {},
+  "options": {
+    "task": "build",
+    "wasm": false
+  },
   "fields": [
     {
       "field": "src",
@@ -24,17 +27,79 @@
   ],
   "confs": [
     {
+      "task": "build",
+      "wasm": false,
       "src": [
-        "./src/smskmax.c"
+        "./src/main.c"
       ],
       "include": [
         "./include"
       ],
-      "libraries": [
-        "-lm"
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset",
+        "@stdlib/math/base/assert/is-positive-zerof",
+        "@stdlib/math/base/assert/is-nanf",
+        "@stdlib/napi/export",
+        "@stdlib/napi/argv",
+        "@stdlib/napi/argv-int64",
+        "@stdlib/napi/argv-strided-float32array",
+        "@stdlib/napi/argv-strided-uint8array",
+        "@stdlib/napi/create-double"
+      ]
+    },
+    {
+      "task": "benchmark",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset",
+        "@stdlib/math/base/assert/is-nanf",
+        "@stdlib/math/base/assert/is-positive-zerof"
+      ]
+    },
+    {
+      "task": "examples",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset",
+        "@stdlib/math/base/assert/is-nanf",
+        "@stdlib/math/base/assert/is-positive-zerof"
+      ]
+    },
+    {
+      "task": "",
+      "wasm": true,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
       ],
+      "libraries": [],
       "libpath": [],
       "dependencies": [
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset",
         "@stdlib/math/base/assert/is-nanf",
         "@stdlib/math/base/assert/is-positive-zerof"
       ]
diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/src/addon.c b/lib/node_modules/@stdlib/stats/base/smskmax/src/addon.c
new file mode 100644
index 000000000000..cf603f7fe5a2
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/smskmax/src/addon.c
@@ -0,0 +1,66 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/smskmax.h"
+#include "stdlib/napi/export.h"
+#include "stdlib/napi/argv.h"
+#include "stdlib/napi/argv_int64.h"
+#include "stdlib/napi/argv_strided_float32array.h"
+#include "stdlib/napi/argv_strided_uint8array.h"
+#include "stdlib/napi/create_double.h"
+#include <node_api.h>
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 5 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 );
+	STDLIB_NAPI_ARGV_INT64( env, strideMask, argv, 4 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 );
+	STDLIB_NAPI_ARGV_STRIDED_UINT8ARRAY( env, Mask, N, strideMask, argv, 3 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_smskmax( N, X, strideX, Mask, strideMask ), v );
+	return v;
+}
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon_method( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 7 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 );
+	STDLIB_NAPI_ARGV_INT64( env, strideMask, argv, 5 );
+	STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 );
+	STDLIB_NAPI_ARGV_INT64( env, offsetMask, argv, 6 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 );
+	STDLIB_NAPI_ARGV_STRIDED_UINT8ARRAY( env, Mask, N, strideMask, argv, 4 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_smskmax_ndarray( N, X, strideX, offsetX, Mask, strideMask, offsetMask ), v );
+	return v;
+}
+
+STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method )
diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/smskmax/src/addon.cpp
deleted file mode 100644
index d886197df62e..000000000000
--- a/lib/node_modules/@stdlib/stats/base/smskmax/src/addon.cpp
+++ /dev/null
@@ -1,153 +0,0 @@
-/**
-* @license Apache-2.0
-*
-* Copyright (c) 2020 The Stdlib Authors.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-*    http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-
-#include "stdlib/stats/base/smskmax.h"
-#include <node_api.h>
-#include <stdint.h>
-#include <stdlib.h>
-#include <stdbool.h>
-#include <assert.h>
-
-/**
-* Add-on namespace.
-*/
-namespace stdlib_stats_base_smskmax {
-
-	/**
-	* Computes the maximum value of a single-precision floating-point strided array according to a mask.
-	*
-	* ## Notes
-	*
-	* -   When called from JavaScript, the function expects five arguments:
-	*
-	*     -   `N`: number of indexed elements
-	*     -   `X`: input array
-	*     -   `strideX`: `X` stride length
-	*     -   `Mask`: mask array
-	*     -   `strideMask`: `Mask` stride length
-	*/
-	napi_value node_smskmax( napi_env env, napi_callback_info info ) {
-		napi_status status;
-
-		size_t argc = 5;
-		napi_value argv[ 5 ];
-		status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr );
-		assert( status == napi_ok );
-
-		if ( argc < 5 ) {
-			napi_throw_error( env, nullptr, "invalid invocation. Must provide 5 arguments." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype0;
-		status = napi_typeof( env, argv[ 0 ], &vtype0 );
-		assert( status == napi_ok );
-		if ( vtype0 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." );
-			return nullptr;
-		}
-
-		bool res1;
-		status = napi_is_typedarray( env, argv[ 1 ], &res1 );
-		assert( status == napi_ok );
-		if ( res1 == false ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype2;
-		status = napi_typeof( env, argv[ 2 ], &vtype2 );
-		assert( status == napi_ok );
-		if ( vtype2 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." );
-			return nullptr;
-		}
-
-		bool res3;
-		status = napi_is_typedarray( env, argv[ 3 ], &res3 );
-		assert( status == napi_ok );
-		if ( res3 == false ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a Uint8Array." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype4;
-		status = napi_typeof( env, argv[ 4 ], &vtype4 );
-		assert( status == napi_ok );
-		if ( vtype4 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Fifth argument must be a number." );
-			return nullptr;
-		}
-
-		int64_t N;
-		status = napi_get_value_int64( env, argv[ 0 ], &N );
-		assert( status == napi_ok );
-
-		int64_t strideX;
-		status = napi_get_value_int64( env, argv[ 2 ], &strideX );
-		assert( status == napi_ok );
-
-		int64_t strideMask;
-		status = napi_get_value_int64( env, argv[ 4 ], &strideMask );
-		assert( status == napi_ok );
-
-		napi_typedarray_type vtype1;
-		size_t xlen;
-		void *X;
-		status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr );
-		assert( status == napi_ok );
-		if ( vtype1 != napi_float32_array ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." );
-			return nullptr;
-		}
-		if ( (N-1)*llabs(strideX) >= (int64_t)xlen ) {
-			napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." );
-			return nullptr;
-		}
-
-		napi_typedarray_type vtype3;
-		size_t mlen;
-		void *Mask;
-		status = napi_get_typedarray_info( env, argv[ 3 ], &vtype3, &mlen, &Mask, nullptr, nullptr );
-		assert( status == napi_ok );
-		if ( vtype3 != napi_uint8_array ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a Uint8Array." );
-			return nullptr;
-		}
-		if ( (N-1)*llabs(strideMask) >= (int64_t)mlen ) {
-			napi_throw_range_error( env, nullptr, "invalid argument. Fourth argument has insufficient elements based on the associated stride and the number of indexed elements." );
-			return nullptr;
-		}
-
-		napi_value v;
-		status = napi_create_double( env, (double)stdlib_strided_smskmax( N, (float *)X, strideX, (uint8_t *)Mask, strideMask ), &v );
-		assert( status == napi_ok );
-
-		return v;
-	}
-
-	napi_value Init( napi_env env, napi_value exports ) {
-		napi_status status;
-		napi_value fcn;
-		status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_smskmax, NULL, &fcn );
-		assert( status == napi_ok );
-		return fcn;
-	}
-
-	NAPI_MODULE( NODE_GYP_MODULE_NAME, Init )
-} // end namespace stdlib_stats_base_smskmax
diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/src/smskmax.c b/lib/node_modules/@stdlib/stats/base/smskmax/src/main.c
similarity index 58%
rename from lib/node_modules/@stdlib/stats/base/smskmax/src/smskmax.c
rename to lib/node_modules/@stdlib/stats/base/smskmax/src/main.c
index ad890d782b67..ab94f2006259 100644
--- a/lib/node_modules/@stdlib/stats/base/smskmax/src/smskmax.c
+++ b/lib/node_modules/@stdlib/stats/base/smskmax/src/main.c
@@ -19,6 +19,8 @@
 #include "stdlib/stats/base/smskmax.h"
 #include "stdlib/math/base/assert/is_nanf.h"
 #include "stdlib/math/base/assert/is_positive_zerof.h"
+#include "stdlib/blas/base/shared.h"
+#include "stdlib/strided/base/stride2offset.h"
 #include <stdint.h>
 
 /**
@@ -31,26 +33,36 @@
 * @param strideMask  Mask stride length
 * @return            output value
 */
-float stdlib_strided_smskmax( const int64_t N, const float *X, const int64_t strideX, const uint8_t *Mask, const int64_t strideMask ) {
-	int64_t ix;
-	int64_t im;
-	int64_t i;
+float API_SUFFIX(stdlib_strided_smskmax)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const uint8_t *Mask, const CBLAS_INT strideMask ) {
+	const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX );
+	const CBLAS_INT om = stdlib_strided_stride2offset( N, strideMask );
+	return API_SUFFIX(stdlib_strided_smskmax_ndarray)( N, X, strideX, ox, Mask, strideMask, om );
+}
+
+/**
+* Computes the maximum value of a single-precision floating-point strided array according to a mask and using alternative indexing semantics.
+*
+* @param N           number of indexed elements
+* @param X           input array
+* @param strideX     X stride length
+* @param offsetX     starting index for X
+* @param Mask        mask array
+* @param strideMask  Mask stride length
+* @param offsetMask  starting index for Mask
+* @return            output value
+*/
+float API_SUFFIX(stdlib_strided_smskmax_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, const uint8_t *Mask, const CBLAS_INT strideMask, const CBLAS_INT offsetMask ) {
+	CBLAS_INT ix;
+	CBLAS_INT im;
+	CBLAS_INT i;
 	float max;
 	float v;
 
 	if ( N <= 0 ) {
 		return 0.0f / 0.0f; // NaN
 	}
-	if ( strideX < 0 ) {
-		ix = (1-N) * strideX;
-	} else {
-		ix = 0;
-	}
-	if ( strideMask < 0 ) {
-		im = (1-N) * strideMask;
-	} else {
-		im = 0;
-	}
+	ix = offsetX;
+	im = offsetMask;
 	for ( i = 0; i < N; i++ ) {
 		if ( Mask[ im ] == 0 ) {
 			break;
diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/smskmax/test/test.ndarray.js
index d08097930cb4..509a5f2a53c2 100644
--- a/lib/node_modules/@stdlib/stats/base/smskmax/test/test.ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/smskmax/test/test.ndarray.js
@@ -21,7 +21,6 @@
 // MODULES //
 
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
 var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' );
 var Float32Array = require( '@stdlib/array/float32' );
@@ -133,7 +132,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 
 tape( 'the function supports `stride` parameters', function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -162,8 +160,7 @@ tape( 'the function supports `stride` parameters', function test( t ) {
 		1
 	]);
 
-	N = floor( x.length / 2 );
-	v = smskmax( N, x, 2, 0, mask, 2, 0 );
+	v = smskmax( 5, x, 2, 0, mask, 2, 0 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
@@ -171,7 +168,6 @@ tape( 'the function supports `stride` parameters', function test( t ) {
 
 tape( 'the function supports negative `stride` parameters', function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -200,8 +196,7 @@ tape( 'the function supports negative `stride` parameters', function test( t ) {
 		0
 	]);
 
-	N = floor( x.length / 2 );
-	v = smskmax( N, x, -2, 8, mask, -2, 8 );
+	v = smskmax( 5, x, -2, 8, mask, -2, 8 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
@@ -209,7 +204,6 @@ tape( 'the function supports negative `stride` parameters', function test( t ) {
 
 tape( 'the function supports `offset` parameters', function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -237,9 +231,8 @@ tape( 'the function supports `offset` parameters', function test( t ) {
 		1,
 		1  // 4
 	]);
-	N = floor( x.length / 2 );
 
-	v = smskmax( N, x, 2, 1, mask, 2, 1 );
+	v = smskmax( 5, x, 2, 1, mask, 2, 1 );
 	t.strictEqual( v, 4.0, 'returns expected value' );
 
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/smskmax/test/test.ndarray.native.js
index e280af72a159..de09098a5eab 100644
--- a/lib/node_modules/@stdlib/stats/base/smskmax/test/test.ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/smskmax/test/test.ndarray.native.js
@@ -22,7 +22,6 @@
 
 var resolve = require( 'path' ).resolve;
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
 var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' );
 var Float32Array = require( '@stdlib/array/float32' );
@@ -120,7 +119,7 @@ tape( 'if provided an `N` parameter less than or equal to `0`, the function retu
 	v = smskmax( 0, x, 1, 0, mask, 1, 0 );
 	t.strictEqual( isnanf( v ), true, 'returns expected value' );
 
-	v = smskmax( -1, x, 1, 0, mask, 1 );
+	v = smskmax( -1, x, 1, 0, mask, 1, 0 );
 	t.strictEqual( isnanf( v ), true, 'returns expected value' );
 
 	t.end();
@@ -142,7 +141,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 
 tape( 'the function supports `stride` parameters', opts, function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -171,8 +169,7 @@ tape( 'the function supports `stride` parameters', opts, function test( t ) {
 		1
 	]);
 
-	N = floor( x.length / 2 );
-	v = smskmax( N, x, 2, 0, mask, 2, 0 );
+	v = smskmax( 5, x, 2, 0, mask, 2, 0 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
@@ -180,7 +177,6 @@ tape( 'the function supports `stride` parameters', opts, function test( t ) {
 
 tape( 'the function supports negative `stride` parameters', opts, function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -209,8 +205,7 @@ tape( 'the function supports negative `stride` parameters', opts, function test(
 		0
 	]);
 
-	N = floor( x.length / 2 );
-	v = smskmax( N, x, -2, 8, mask, -2, 8 );
+	v = smskmax( 5, x, -2, 8, mask, -2, 8 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
@@ -218,7 +213,6 @@ tape( 'the function supports negative `stride` parameters', opts, function test(
 
 tape( 'the function supports `offset` parameters', opts, function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -246,9 +240,8 @@ tape( 'the function supports `offset` parameters', opts, function test( t ) {
 		1,
 		1  // 4
 	]);
-	N = floor( x.length / 2 );
 
-	v = smskmax( N, x, 2, 1, mask, 2, 1 );
+	v = smskmax( 5, x, 2, 1, mask, 2, 1 );
 	t.strictEqual( v, 4.0, 'returns expected value' );
 
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/test/test.smskmax.js b/lib/node_modules/@stdlib/stats/base/smskmax/test/test.smskmax.js
index 841e5625dad0..1e1507f85132 100644
--- a/lib/node_modules/@stdlib/stats/base/smskmax/test/test.smskmax.js
+++ b/lib/node_modules/@stdlib/stats/base/smskmax/test/test.smskmax.js
@@ -21,7 +21,6 @@
 // MODULES //
 
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
 var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' );
 var Float32Array = require( '@stdlib/array/float32' );
@@ -133,7 +132,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 
 tape( 'the function supports `stride` parameters', function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -162,8 +160,7 @@ tape( 'the function supports `stride` parameters', function test( t ) {
 		1
 	]);
 
-	N = floor( x.length / 2 );
-	v = smskmax( N, x, 2, mask, 2 );
+	v = smskmax( 5, x, 2, mask, 2 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
@@ -171,7 +168,6 @@ tape( 'the function supports `stride` parameters', function test( t ) {
 
 tape( 'the function supports negative `stride` parameters', function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -200,8 +196,7 @@ tape( 'the function supports negative `stride` parameters', function test( t ) {
 		0
 	]);
 
-	N = floor( x.length / 2 );
-	v = smskmax( N, x, -2, mask, -2 );
+	v = smskmax( 5, x, -2, mask, -2 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
@@ -212,7 +207,6 @@ tape( 'the function supports view offsets', function test( t ) {
 	var mask1;
 	var x0;
 	var x1;
-	var N;
 	var v;
 
 	x0 = new Float32Array([
@@ -244,9 +238,8 @@ tape( 'the function supports view offsets', function test( t ) {
 
 	x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
 	mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
-	N = floor( x1.length/2 );
 
-	v = smskmax( N, x1, 2, mask1, 2 );
+	v = smskmax( 5, x1, 2, mask1, 2 );
 	t.strictEqual( v, 4.0, 'returns expected value' );
 
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/smskmax/test/test.smskmax.native.js b/lib/node_modules/@stdlib/stats/base/smskmax/test/test.smskmax.native.js
index 56ed75b21da2..921cc8928926 100644
--- a/lib/node_modules/@stdlib/stats/base/smskmax/test/test.smskmax.native.js
+++ b/lib/node_modules/@stdlib/stats/base/smskmax/test/test.smskmax.native.js
@@ -22,7 +22,6 @@
 
 var resolve = require( 'path' ).resolve;
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
 var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' );
 var Float32Array = require( '@stdlib/array/float32' );
@@ -142,7 +141,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 
 tape( 'the function supports `stride` parameters', opts, function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -171,8 +169,7 @@ tape( 'the function supports `stride` parameters', opts, function test( t ) {
 		1
 	]);
 
-	N = floor( x.length / 2 );
-	v = smskmax( N, x, 2, mask, 2 );
+	v = smskmax( 5, x, 2, mask, 2 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
@@ -180,7 +177,6 @@ tape( 'the function supports `stride` parameters', opts, function test( t ) {
 
 tape( 'the function supports negative `stride` parameters', opts, function test( t ) {
 	var mask;
-	var N;
 	var x;
 	var v;
 
@@ -209,8 +205,7 @@ tape( 'the function supports negative `stride` parameters', opts, function test(
 		0
 	]);
 
-	N = floor( x.length / 2 );
-	v = smskmax( N, x, -2, mask, -2 );
+	v = smskmax( 5, x, -2, mask, -2 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
@@ -221,7 +216,6 @@ tape( 'the function supports view offsets', opts, function test( t ) {
 	var mask1;
 	var x0;
 	var x1;
-	var N;
 	var v;
 
 	x0 = new Float32Array([
@@ -253,9 +247,8 @@ tape( 'the function supports view offsets', opts, function test( t ) {
 
 	x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
 	mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
-	N = floor( x1.length/2 );
 
-	v = smskmax( N, x1, 2, mask1, 2 );
+	v = smskmax( 5, x1, 2, mask1, 2 );
 	t.strictEqual( v, 4.0, 'returns expected value' );
 
 	t.end();

From bd7bc8f9f253ee45f3c00588672fc6892732756d Mon Sep 17 00:00:00 2001
From: Aayush Khanna <96649223+aayush0325@users.noreply.github.com>
Date: Fri, 3 Jan 2025 03:38:38 +0530
Subject: [PATCH 24/87] feat: add C ndarray interface and refactor
 implementation for `stats/base/dmaxabssorted`

PR-URL: https://github.com/stdlib-js/stdlib/pull/4181
Reviewed-by: Athan Reines <kgryte@gmail.com>
Co-authored-by: stdlib-bot <82920195+stdlib-bot@users.noreply.github.com>
---
 .../stats/base/dmaxabssorted/README.md        | 155 +++++++++++++++---
 .../base/dmaxabssorted/benchmark/benchmark.js |  17 +-
 .../benchmark/benchmark.native.js             |  13 +-
 .../benchmark/benchmark.ndarray.js            |  17 +-
 .../benchmark/benchmark.ndarray.native.js     |  13 +-
 .../benchmark/c/benchmark.length.c            |  50 +++++-
 .../stats/base/dmaxabssorted/docs/repl.txt    |  32 ++--
 .../base/dmaxabssorted/docs/types/index.d.ts  |  12 +-
 .../base/dmaxabssorted/examples/c/example.c   |   9 +-
 .../base/dmaxabssorted/examples/index.js      |  13 +-
 .../include/stdlib/stats/base/dmaxabssorted.h |   9 +-
 .../base/dmaxabssorted/lib/dmaxabssorted.js   |  37 +----
 .../dmaxabssorted/lib/dmaxabssorted.native.js |   9 +-
 .../stats/base/dmaxabssorted/lib/index.js     |   7 +-
 .../stats/base/dmaxabssorted/lib/ndarray.js   |  16 +-
 .../base/dmaxabssorted/lib/ndarray.native.js  |  20 +--
 .../stats/base/dmaxabssorted/manifest.json    |  53 ++++--
 .../stats/base/dmaxabssorted/src/addon.c      |  25 ++-
 .../base/dmaxabssorted/src/dmaxabssorted.c    |  58 -------
 .../stats/base/dmaxabssorted/src/main.c       |  68 ++++++++
 .../dmaxabssorted/test/test.dmaxabssorted.js  |  13 +-
 .../test/test.dmaxabssorted.native.js         |  13 +-
 .../base/dmaxabssorted/test/test.ndarray.js   |  13 +-
 .../dmaxabssorted/test/test.ndarray.native.js |  13 +-
 24 files changed, 408 insertions(+), 277 deletions(-)
 delete mode 100644 lib/node_modules/@stdlib/stats/base/dmaxabssorted/src/dmaxabssorted.c
 create mode 100644 lib/node_modules/@stdlib/stats/base/dmaxabssorted/src/main.c

diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/README.md b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/README.md
index e636b54a135d..bae86b03493e 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/README.md
+++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/README.md
@@ -36,7 +36,7 @@ limitations under the License.
 var dmaxabssorted = require( '@stdlib/stats/base/dmaxabssorted' );
 ```
 
-#### dmaxabssorted( N, x, stride )
+#### dmaxabssorted( N, x, strideX )
 
 Computes the maximum absolute value of a sorted double-precision floating-point strided array `x`.
 
@@ -56,18 +56,16 @@ The function has the following parameters:
 
 -   **N**: number of indexed elements.
 -   **x**: sorted input [`Float64Array`][@stdlib/array/float64].
--   **stride**: index increment for `x`.
+-   **strideX**: stride length for `x`.
 
-The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the maximum absolute value of every other element in `x`,
+The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the maximum absolute value of every other element in `x`,
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, 3.0, 3.0, 4.0, 2.0 ] );
-var N = floor( x.length / 2 );
 
-var v = dmaxabssorted( N, x, 2 );
+var v = dmaxabssorted( 4, x, 2 );
 // returns 4.0
 ```
 
@@ -77,18 +75,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x0 = new Float64Array( [ 2.0, 1.0, 2.0, 2.0, -2.0, 2.0, 3.0, 4.0 ] );
 var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
 
-var N = floor( x0.length / 2 );
-
-var v = dmaxabssorted( N, x1, 2 );
+var v = dmaxabssorted( 4, x1, 2 );
 // returns 4.0
 ```
 
-#### dmaxabssorted.ndarray( N, x, stride, offset )
+#### dmaxabssorted.ndarray( N, x, strideX, offsetX )
 
 Computes the maximum absolute value of a sorted double-precision floating-point strided array using alternative indexing semantics.
 
@@ -102,18 +97,16 @@ var v = dmaxabssorted.ndarray( x.length, x, 1, 0 );
 
 The function has the following additional parameters:
 
--   **offset**: starting index for `x`.
+-   **offsetX**: starting index for `x`.
 
-While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the maximum absolute value for every other value in `x` starting from the second value
+While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the maximum absolute value for every other element in `x` starting from the second element
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x = new Float64Array( [ 2.0, 1.0, 2.0, 2.0, -2.0, 2.0, 3.0, 4.0 ] );
-var N = floor( x.length / 2 );
 
-var v = dmaxabssorted.ndarray( N, x, 2, 1 );
+var v = dmaxabssorted.ndarray( 4, x, 2, 1 );
 // returns 4.0
 ```
 
@@ -139,16 +132,13 @@ var v = dmaxabssorted.ndarray( N, x, 2, 1 );
 <!-- eslint no-undef: "error" -->
 
 ```javascript
-var Float64Array = require( '@stdlib/array/float64' );
+var linspace = require( '@stdlib/array/linspace' );
 var dmaxabssorted = require( '@stdlib/stats/base/dmaxabssorted' );
 
-var x;
-var i;
-
-x = new Float64Array( 10 );
-for ( i = 0; i < x.length; i++ ) {
-    x[ i ] = i - 5.0;
-}
+var options = {
+    'dtype': 'float64'
+};
+var x = linspace( -5.0, 5.0, 10, options );
 console.log( x );
 
 var v = dmaxabssorted( x.length, x, 1 );
@@ -159,6 +149,123 @@ console.log( v );
 
 <!-- /.examples -->
 
+<!-- C interface documentation. -->
+
+* * *
+
+<section class="c">
+
+## C APIs
+
+<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<!-- C usage documentation. -->
+
+<section class="usage">
+
+### Usage
+
+```c
+#include "stdlib/stats/base/dmaxabssorted.h"
+```
+
+#### stdlib_strided_dmaxabssorted( N, \*X, strideX )
+
+Computes the maximum absolute value of a sorted double-precision floating-point strided array.
+
+```c
+const double x[] = { -1.0, -2.0, -3.0, -4.0, -5.0, -6.0, -7.0, -8.0 };
+
+double v = stdlib_strided_dmaxabssorted( 4, x, 2 );
+// returns 7.0
+```
+
+The function accepts the following arguments:
+
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **X**: `[in] double*` input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+
+```c
+double stdlib_strided_dmaxabssorted( const CBLAS_INT N, const double *X, const CBLAS_INT strideX );
+```
+
+#### stdlib_strided_dmaxabssorted_ndarray( N, \*X, strideX, offsetX )
+
+Computes the maximum absolute value of a sorted double-precision floating-point strided array using alternative indexing semantics.
+
+```c
+const double x[] = { -1.0, -2.0, -3.0, -4.0, -5.0, -6.0, -7.0, -8.0 };
+
+double v = stdlib_strided_dmaxabssorted_ndarray( 4, x, 2, 0 );
+// returns 7.0
+```
+
+The function accepts the following arguments:
+
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **X**: `[in] double*` input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+-   **offsetX**: `[in] CBLAS_INT` starting index for `X`.
+
+```c
+double stdlib_strided_dmaxabssorted_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX );
+```
+
+</section>
+
+<!-- /.usage -->
+
+<!-- C API usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="notes">
+
+</section>
+
+<!-- /.notes -->
+
+<!-- C API usage examples. -->
+
+<section class="examples">
+
+### Examples
+
+```c
+#include "stdlib/stats/base/dmaxabssorted.h"
+#include <stdio.h>
+
+int main( void ) {
+    // Create a strided array:
+    const double x[] = { -1.0, -2.0, -3.0, -4.0, -5.0, -6.0, -7.0, -8.0 };
+
+    // Specify the number of elements:
+    const int N = 4;
+
+    // Specify the stride length:
+    const int strideX = 2;
+
+    // Compute the maximum absolute value:
+    double v = stdlib_strided_dmaxabssorted( N, x, strideX );
+
+    // Print the result:
+    printf( "maxabs: %lf\n", v );
+}
+```
+
+</section>
+
+<!-- /.examples -->
+
+</section>
+
+<!-- /.c -->
+
 <!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
 
 <section class="related">
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/benchmark/benchmark.js
index 4e8df530c306..1eb995830a5b 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/benchmark/benchmark.js
+++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/benchmark/benchmark.js
@@ -22,12 +22,19 @@
 
 var bench = require( '@stdlib/bench' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var linspace = require( '@stdlib/array/linspace' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float64Array = require( '@stdlib/array/float64' );
 var pkg = require( './../package.json' ).name;
 var dmaxabssorted = require( './../lib/dmaxabssorted.js' );
 
 
+// VARIABLES //
+
+var options = {
+	'dtype': 'float64'
+};
+
+
 // FUNCTIONS //
 
 /**
@@ -38,13 +45,7 @@ var dmaxabssorted = require( './../lib/dmaxabssorted.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float64Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = i - (len/2);
-	}
+	var x = linspace( -len/2, len/2, len, options );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/benchmark/benchmark.native.js
index 9ef830eda3a4..07fd755c16be 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/benchmark/benchmark.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/benchmark/benchmark.native.js
@@ -23,8 +23,8 @@
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var linspace = require( '@stdlib/array/linspace' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float64Array = require( '@stdlib/array/float64' );
 var tryRequire = require( '@stdlib/utils/try-require' );
 var pkg = require( './../package.json' ).name;
 
@@ -35,6 +35,9 @@ var dmaxabssorted = tryRequire( resolve( __dirname, './../lib/dmaxabssorted.nati
 var opts = {
 	'skip': ( dmaxabssorted instanceof Error )
 };
+var options = {
+	'dtype': 'float64'
+};
 
 
 // FUNCTIONS //
@@ -47,13 +50,7 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float64Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = i - (len/2);
-	}
+	var x = linspace( -len/2, len/2, len, options );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/benchmark/benchmark.ndarray.js
index a620612645ee..230a464a14fe 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/benchmark/benchmark.ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/benchmark/benchmark.ndarray.js
@@ -22,12 +22,19 @@
 
 var bench = require( '@stdlib/bench' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var linspace = require( '@stdlib/array/linspace' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float64Array = require( '@stdlib/array/float64' );
 var pkg = require( './../package.json' ).name;
 var dmaxabssorted = require( './../lib/ndarray.js' );
 
 
+// VARIABLES //
+
+var options = {
+	'dtype': 'float64'
+};
+
+
 // FUNCTIONS //
 
 /**
@@ -38,13 +45,7 @@ var dmaxabssorted = require( './../lib/ndarray.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float64Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = i - (len/2);
-	}
+	var x = linspace( -len/2, len/2, len, options );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/benchmark/benchmark.ndarray.native.js
index a497940daed0..f45700dff534 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/benchmark/benchmark.ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/benchmark/benchmark.ndarray.native.js
@@ -23,8 +23,8 @@
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var linspace = require( '@stdlib/array/linspace' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float64Array = require( '@stdlib/array/float64' );
 var tryRequire = require( '@stdlib/utils/try-require' );
 var pkg = require( './../package.json' ).name;
 
@@ -35,6 +35,9 @@ var dmaxabssorted = tryRequire( resolve( __dirname, './../lib/ndarray.native.js'
 var opts = {
 	'skip': ( dmaxabssorted instanceof Error )
 };
+var options = {
+	'dtype': 'float64'
+};
 
 
 // FUNCTIONS //
@@ -47,13 +50,7 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float64Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = i - (len/2);
-	}
+	var x = linspace( -len/2, len/2, len, options );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/benchmark/c/benchmark.length.c
index 81b461c7d421..0623aab79d4d 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/benchmark/c/benchmark.length.c
+++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/benchmark/c/benchmark.length.c
@@ -94,7 +94,7 @@ static double rand_double( void ) {
 * @param len          array length
 * @return             elapsed time in seconds
 */
-static double benchmark( int iterations, int len ) {
+static double benchmark1( int iterations, int len ) {
 	double elapsed;
 	double x[ len ];
 	double v;
@@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) {
 	v = 0.0;
 	t = tic();
 	for ( i = 0; i < iterations; i++ ) {
+		// cppcheck-suppress uninitvar
 		v = stdlib_strided_dmaxabssorted( len, x, 1 );
 		if ( v != v ) {
 			printf( "should not return NaN\n" );
@@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) {
 	return elapsed;
 }
 
+/**
+* Runs a benchmark.
+*
+* @param iterations   number of iterations
+* @param len          array length
+* @return             elapsed time in seconds
+*/
+static double benchmark2( int iterations, int len ) {
+	double elapsed;
+	double x[ len ];
+	double v;
+	double t;
+	int i;
+
+	for ( i = 0; i < len; i++ ) {
+		x[ i ] = i - (len/2);
+	}
+	v = 0.0;
+	t = tic();
+	for ( i = 0; i < iterations; i++ ) {
+		// cppcheck-suppress uninitvar
+		v = stdlib_strided_dmaxabssorted_ndarray( len, x, 1, 0 );
+		if ( v != v ) {
+			printf( "should not return NaN\n" );
+			break;
+		}
+	}
+	elapsed = tic() - t;
+	if ( v != v ) {
+		printf( "should not return NaN\n" );
+	}
+	return elapsed;
+}
+
 /**
 * Main execution sequence.
 */
@@ -142,7 +177,18 @@ int main( void ) {
 		for ( j = 0; j < REPEATS; j++ ) {
 			count += 1;
 			printf( "# c::%s:len=%d\n", NAME, len );
-			elapsed = benchmark( iter, len );
+			elapsed = benchmark1( iter, len );
+			print_results( iter, elapsed );
+			printf( "ok %d benchmark finished\n", count );
+		}
+	}
+	for ( i = MIN; i <= MAX; i++ ) {
+		len = pow( 10, i );
+		iter = ITERATIONS / pow( 10, i-1 );
+		for ( j = 0; j < REPEATS; j++ ) {
+			count += 1;
+			printf( "# c::%s:ndarray:len=%d\n", NAME, len );
+			elapsed = benchmark2( iter, len );
 			print_results( iter, elapsed );
 			printf( "ok %d benchmark finished\n", count );
 		}
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/docs/repl.txt
index 9a05d38c550b..9682affaa15a 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/docs/repl.txt
+++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/docs/repl.txt
@@ -1,13 +1,13 @@
 
-{{alias}}( N, x, stride )
+{{alias}}( N, x, strideX )
     Computes the maximum absolute value of a sorted double-precision floating-
     point strided array.
 
     The input strided array must be sorted in either strictly ascending or
     descending order.
 
-    The `N` and `stride` parameters determine which elements in `x` are accessed
-    at runtime.
+    The `N` and stride parameters determine which elements in the strided array
+    are accessed at runtime.
 
     Indexing is relative to the first index. To introduce an offset, use a typed
     array view.
@@ -22,8 +22,8 @@
     x: Float64Array
         Sorted input array.
 
-    stride: integer
-        Index increment.
+    strideX: integer
+        Stride Length.
 
     Returns
     -------
@@ -37,22 +37,19 @@
     > {{alias}}( x.length, x, 1 )
     3.0
 
-    // Using `N` and `stride` parameters:
+    // Using `N` and stride parameters:
     > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > var stride = 2;
-    > {{alias}}( N, x, stride )
+    > {{alias}}( 3, x, 2 )
     2.0
 
     // Using view offsets:
     > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );
     > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );
-    > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );
-    > stride = 2;
-    > {{alias}}( N, x1, stride )
+    > {{alias}}( 3, x1, 2 )
     3.0
 
-{{alias}}.ndarray( N, x, stride, offset )
+
+{{alias}}.ndarray( N, x, strideX, offsetX )
     Computes the maximum absolute value of a sorted double-precision floating-
     point strided array using alternative indexing semantics.
 
@@ -68,10 +65,10 @@
     x: Float64Array
         Sorted input array.
 
-    stride: integer
-        Index increment.
+    strideX: integer
+        Stride Length.
 
-    offset: integer
+    offsetX: integer
         Starting index.
 
     Returns
@@ -88,8 +85,7 @@
 
     // Using offset parameter:
     > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > {{alias}}.ndarray( N, x, 2, 1 )
+    > {{alias}}.ndarray( 3, x, 2, 1 )
     3.0
 
     See Also
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/docs/types/index.d.ts
index 72bcb1bd6bcd..9970a5e2144e 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/docs/types/index.d.ts
@@ -27,7 +27,7 @@ interface Routine {
 	*
 	* @param N - number of indexed elements
 	* @param x - sorted input array
-	* @param stride - stride length
+	* @param strideX - stride length
 	* @returns maximum absolute value
 	*
 	* @example
@@ -38,15 +38,15 @@ interface Routine {
 	* var v = dmaxabssorted( x.length, x, 1 );
 	* // returns 3.0
 	*/
-	( N: number, x: Float64Array, stride: number ): number;
+	( N: number, x: Float64Array, strideX: number ): number;
 
 	/**
 	* Computes the maximum absolute value of a sorted double-precision floating-point strided array using alternative indexing semantics.
 	*
 	* @param N - number of indexed elements
 	* @param x - sorted input array
-	* @param stride - stride length
-	* @param offset - starting index
+	* @param strideX - stride length
+	* @param offsetX - starting index
 	* @returns maximum absolute value
 	*
 	* @example
@@ -57,7 +57,7 @@ interface Routine {
 	* var v = dmaxabssorted.ndarray( x.length, x, 1, 0 );
 	* // returns 3.0
 	*/
-	ndarray( N: number, x: Float64Array, stride: number, offset: number ): number;
+	ndarray( N: number, x: Float64Array, strideX: number, offsetX: number ): number;
 }
 
 /**
@@ -65,7 +65,7 @@ interface Routine {
 *
 * @param N - number of indexed elements
 * @param x - sorted input array
-* @param stride - stride length
+* @param strideX - stride length
 * @returns maximum absolute value
 *
 * @example
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/examples/c/example.c
index 0417e40b9812..8ce3bc40c15b 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/examples/c/example.c
+++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/examples/c/example.c
@@ -17,21 +17,20 @@
 */
 
 #include "stdlib/stats/base/dmaxabssorted.h"
-#include <stdint.h>
 #include <stdio.h>
 
 int main( void ) {
 	// Create a strided array:
-	double x[] = { -1.0, -2.0, -3.0, -4.0, -5.0, -6.0, -7.0, -8.0 };
+	const double x[] = { -1.0, -2.0, -3.0, -4.0, -5.0, -6.0, -7.0, -8.0 };
 
 	// Specify the number of elements:
-	int64_t N = 4;
+	const int N = 4;
 
 	// Specify the stride length:
-	int64_t stride = 2;
+	const int strideX = 2;
 
 	// Compute the maximum absolute value:
-	double v = stdlib_strided_dmaxabssorted( N, x, stride );
+	double v = stdlib_strided_dmaxabssorted( N, x, strideX );
 
 	// Print the result:
 	printf( "maxabs: %lf\n", v );
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/examples/index.js b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/examples/index.js
index 5ab49c15d1ec..7646a057a54f 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/examples/index.js
+++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/examples/index.js
@@ -18,16 +18,13 @@
 
 'use strict';
 
-var Float64Array = require( '@stdlib/array/float64' );
+var linspace = require( '@stdlib/array/linspace' );
 var dmaxabssorted = require( './../lib' );
 
-var x;
-var i;
-
-x = new Float64Array( 10 );
-for ( i = 0; i < x.length; i++ ) {
-	x[ i ] = i - x.length;
-}
+var options = {
+	'dtype': 'float64'
+};
+var x = linspace( -5.0, 5.0, 10, options );
 console.log( x );
 
 var v = dmaxabssorted( x.length, x, 1 );
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/include/stdlib/stats/base/dmaxabssorted.h b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/include/stdlib/stats/base/dmaxabssorted.h
index 8bb1138d13c5..f8fafdabed17 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/include/stdlib/stats/base/dmaxabssorted.h
+++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/include/stdlib/stats/base/dmaxabssorted.h
@@ -19,7 +19,7 @@
 #ifndef STDLIB_STATS_BASE_DMAXABSSORTED_H
 #define STDLIB_STATS_BASE_DMAXABSSORTED_H
 
-#include <stdint.h>
+#include "stdlib/blas/base/shared.h"
 
 /*
 * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler.
@@ -31,7 +31,12 @@ extern "C" {
 /**
 * Computes the maximum absolute value of a sorted double-precision floating-point strided array.
 */
-double stdlib_strided_dmaxabssorted( const int64_t N, const double *X, const int64_t stride );
+double API_SUFFIX(stdlib_strided_dmaxabssorted)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX );
+
+/**
+* Computes the maximum absolute value of a sorted double-precision floating-point strided array using alternative indexing semantics.
+*/
+double API_SUFFIX(stdlib_strided_dmaxabssorted_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX );
 
 #ifdef __cplusplus
 }
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/lib/dmaxabssorted.js b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/lib/dmaxabssorted.js
index 9a91fbbc1605..533e9da91cf2 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/lib/dmaxabssorted.js
+++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/lib/dmaxabssorted.js
@@ -20,8 +20,8 @@
 
 // MODULES //
 
-var isnan = require( '@stdlib/math/base/assert/is-nan' );
-var abs = require( '@stdlib/math/base/special/abs' );
+var stride2offset = require( '@stdlib/strided/base/stride2offset' );
+var ndarray = require( './ndarray.js' );
 
 
 // MAIN //
@@ -31,44 +31,19 @@ var abs = require( '@stdlib/math/base/special/abs' );
 *
 * @param {PositiveInteger} N - number of indexed elements
 * @param {Float64Array} x - sorted input array
-* @param {integer} stride - stride length
+* @param {integer} strideX - stride length
 * @returns {number} maximum absolute value
 *
 * @example
 * var Float64Array = require( '@stdlib/array/float64' );
 *
 * var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );
-* var N = x.length;
 *
-* var v = dmaxabssorted( N, x, 1 );
+* var v = dmaxabssorted( x.length, x, 1 );
 * // returns 3.0
 */
-function dmaxabssorted( N, x, stride ) {
-	var v1;
-	var v2;
-
-	if ( N <= 0 ) {
-		return NaN;
-	}
-	if ( N === 1 || stride === 0 ) {
-		return x[ 0 ];
-	}
-	if ( stride < 0 ) {
-		v1 = x[ (1-N) * stride ];
-		v2 = x[ 0 ];
-	} else {
-		v1 = x[ 0 ];
-		v2 = x[ (N-1) * stride ];
-	}
-	if ( isnan( v1 ) || isnan( v2 ) ) {
-		return NaN;
-	}
-	v1 = abs( v1 );
-	v2 = abs( v2 );
-	if ( v1 > v2 ) {
-		return v1;
-	}
-	return v2;
+function dmaxabssorted( N, x, strideX ) {
+	return ndarray( N, x, strideX, stride2offset( N, strideX ) );
 }
 
 
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/lib/dmaxabssorted.native.js b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/lib/dmaxabssorted.native.js
index 5ed23b5c8fad..9e3ead8a17b5 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/lib/dmaxabssorted.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/lib/dmaxabssorted.native.js
@@ -30,20 +30,19 @@ var addon = require( './../src/addon.node' );
 *
 * @param {PositiveInteger} N - number of indexed elements
 * @param {Float64Array} x - sorted input array
-* @param {integer} stride - stride length
+* @param {integer} strideX - stride length
 * @returns {number} maximum absolute value
 *
 * @example
 * var Float64Array = require( '@stdlib/array/float64' );
 *
 * var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );
-* var N = x.length;
 *
-* var v = dmaxabssorted( N, x, 1 );
+* var v = dmaxabssorted( x.length, x, 1 );
 * // returns 3.0
 */
-function dmaxabssorted( N, x, stride ) {
-	return addon( N, x, stride );
+function dmaxabssorted( N, x, strideX ) {
+	return addon( N, x, strideX );
 }
 
 
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/lib/index.js b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/lib/index.js
index 48313ac1b150..b0116bda24b4 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/lib/index.js
+++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/lib/index.js
@@ -28,20 +28,17 @@
 * var dmaxabssorted = require( '@stdlib/stats/base/dmaxabssorted' );
 *
 * var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );
-* var N = x.length;
 *
-* var v = dmaxabssorted( N, x, 1 );
+* var v = dmaxabssorted( x.length, x, 1 );
 * // returns 3.0
 *
 * @example
 * var Float64Array = require( '@stdlib/array/float64' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 * var dmaxabssorted = require( '@stdlib/stats/base/dmaxabssorted' );
 *
 * var x = new Float64Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
-* var N = floor( x.length / 2 );
 *
-* var v = dmaxabssorted.ndarray( N, x, 2, 1 );
+* var v = dmaxabssorted.ndarray( 4, x, 2, 1 );
 * // returns 4.0
 */
 
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/lib/ndarray.js
index a916d1a6b1ed..5d21803e898e 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/lib/ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/lib/ndarray.js
@@ -31,32 +31,30 @@ var abs = require( '@stdlib/math/base/special/abs' );
 *
 * @param {PositiveInteger} N - number of indexed elements
 * @param {Float64Array} x - sorted input array
-* @param {integer} stride - stride length
-* @param {NonNegativeInteger} offset - starting index
+* @param {integer} strideX - stride length
+* @param {NonNegativeInteger} offsetX - starting index
 * @returns {number} maximum absolute value
 *
 * @example
 * var Float64Array = require( '@stdlib/array/float64' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 *
 * var x = new Float64Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
-* var N = floor( x.length / 2 );
 *
-* var v = dmaxabssorted( N, x, 2, 1 );
+* var v = dmaxabssorted( 4, x, 2, 1 );
 * // returns 4.0
 */
-function dmaxabssorted( N, x, stride, offset ) {
+function dmaxabssorted( N, x, strideX, offsetX ) {
 	var v1;
 	var v2;
 
 	if ( N <= 0 ) {
 		return NaN;
 	}
-	if ( N === 1 || stride === 0 ) {
+	if ( N === 1 || strideX === 0 ) {
 		return x[ 0 ];
 	}
-	v1 = x[ offset ];
-	v2 = x[ offset + ((N-1)*stride) ];
+	v1 = x[ offsetX ];
+	v2 = x[ offsetX + ( ( N - 1 ) * strideX ) ];
 	if ( isnan( v1 ) || isnan( v2 ) ) {
 		return NaN;
 	}
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/lib/ndarray.native.js
index b2867599a5af..de4c3cf23616 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/lib/ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/lib/ndarray.native.js
@@ -20,8 +20,7 @@
 
 // MODULES //
 
-var Float64Array = require( '@stdlib/array/float64' );
-var addon = require( './dmaxabssorted.native.js' );
+var addon = require( './../src/addon.node' );
 
 
 // MAIN //
@@ -31,27 +30,20 @@ var addon = require( './dmaxabssorted.native.js' );
 *
 * @param {PositiveInteger} N - number of indexed elements
 * @param {Float64Array} x - sorted input array
-* @param {integer} stride - stride length
-* @param {NonNegativeInteger} offset - starting index
+* @param {integer} strideX - stride length
+* @param {NonNegativeInteger} offsetX - starting index
 * @returns {number} maximum absolute value
 *
 * @example
 * var Float64Array = require( '@stdlib/array/float64' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 *
 * var x = new Float64Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
-* var N = floor( x.length / 2 );
 *
-* var v = dmaxabssorted( N, x, 2, 1 );
+* var v = dmaxabssorted( 4, x, 2, 1 );
 * // returns 4.0
 */
-function dmaxabssorted( N, x, stride, offset ) {
-	var view;
-	if ( stride < 0 ) {
-		offset += (N-1) * stride;
-	}
-	view = new Float64Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len
-	return addon( N, view, stride );
+function dmaxabssorted( N, x, strideX, offsetX ) {
+	return addon.ndarray( N, x, strideX, offsetX );
 }
 
 
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/manifest.json b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/manifest.json
index 5bea2ec4b6a7..f20b3f18864a 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/manifest.json
+++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/manifest.json
@@ -1,6 +1,7 @@
 {
   "options": {
-    "task": "build"
+    "task": "build",
+    "wasm": false
   },
   "fields": [
     {
@@ -27,18 +28,20 @@
   "confs": [
     {
       "task": "build",
+      "wasm": false,
       "src": [
-        "./src/dmaxabssorted.c"
+        "./src/main.c"
       ],
       "include": [
         "./include"
       ],
-      "libraries": [
-        "-lm"
-      ],
+      "libraries": [],
       "libpath": [],
       "dependencies": [
         "@stdlib/math/base/assert/is-nan",
+        "@stdlib/math/base/special/abs",
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset",
         "@stdlib/napi/export",
         "@stdlib/napi/argv",
         "@stdlib/napi/argv-int64",
@@ -48,34 +51,56 @@
     },
     {
       "task": "benchmark",
+      "wasm": false,
       "src": [
-        "./src/dmaxabssorted.c"
+        "./src/main.c"
       ],
       "include": [
         "./include"
       ],
-      "libraries": [
-        "-lm"
-      ],
+      "libraries": [],
       "libpath": [],
       "dependencies": [
-        "@stdlib/math/base/assert/is-nan"
+        "@stdlib/math/base/assert/is-nan",
+        "@stdlib/math/base/special/abs",
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset"
       ]
     },
     {
       "task": "examples",
+      "wasm": false,
       "src": [
-        "./src/dmaxabssorted.c"
+        "./src/main.c"
       ],
       "include": [
         "./include"
       ],
-      "libraries": [
-        "-lm"
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/math/base/assert/is-nan",
+        "@stdlib/math/base/special/abs",
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset"
+      ]
+    },
+    {
+      "task": "",
+      "wasm": true,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
       ],
+      "libraries": [],
       "libpath": [],
       "dependencies": [
-        "@stdlib/math/base/assert/is-nan"
+        "@stdlib/math/base/assert/is-nan",
+        "@stdlib/math/base/special/abs",
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset"
       ]
     }
   ]
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/src/addon.c b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/src/addon.c
index 2d997a02fcf4..868cda7b11aa 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/src/addon.c
+++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/src/addon.c
@@ -34,10 +34,27 @@
 static napi_value addon( napi_env env, napi_callback_info info ) {
 	STDLIB_NAPI_ARGV( env, info, argv, argc, 3 );
 	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
-	STDLIB_NAPI_ARGV_INT64( env, stride, argv, 2 );
-	STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, stride, argv, 1 );
-	STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dmaxabssorted( N, X, stride ), v );
+	STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dmaxabssorted( N, X, strideX ), v );
 	return v;
 }
 
-STDLIB_NAPI_MODULE_EXPORT_FCN( addon )
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon_method( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 4 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 );
+	STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dmaxabssorted_ndarray( N, X, strideX, offsetX ), v );
+	return v;
+}
+
+STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method )
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/src/dmaxabssorted.c b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/src/dmaxabssorted.c
deleted file mode 100644
index d26827cb8e88..000000000000
--- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/src/dmaxabssorted.c
+++ /dev/null
@@ -1,58 +0,0 @@
-/**
-* @license Apache-2.0
-*
-* Copyright (c) 2020 The Stdlib Authors.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-*    http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-
-#include "stdlib/stats/base/dmaxabssorted.h"
-#include "stdlib/math/base/assert/is_nan.h"
-#include <stdint.h>
-#include <math.h>
-
-/**
-* Computes the maximum absolute value of a sorted double-precision floating-point strided array.
-*
-* @param N       number of indexed elements
-* @param X       sorted input array
-* @param stride  stride length
-* @return        output value
-*/
-double stdlib_strided_dmaxabssorted( const int64_t N, const double *X, const int64_t stride ) {
-	double v1;
-	double v2;
-
-	if ( N <= 0 ) {
-		return 0.0 / 0.0; // NaN
-	}
-	if ( N == 1 || stride == 0 ) {
-		return X[ 0 ];
-	}
-	if ( stride < 0 ) {
-		v1 = X[ (1-N) * stride ];
-		v2 = X[ 0 ];
-	} else {
-		v1 = X[ 0 ];
-		v2 = X[ (N-1) * stride ];
-	}
-	if ( stdlib_base_is_nan( v1 ) || stdlib_base_is_nan( v2 ) ) {
-		return 0.0 / 0.0; // NaN
-	}
-	v1 = fabs( v1 );
-	v2 = fabs( v2 );
-	if ( v1 > v2 ) {
-		return v1;
-	}
-	return v2;
-}
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/src/main.c b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/src/main.c
new file mode 100644
index 000000000000..396f6a63a34d
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/src/main.c
@@ -0,0 +1,68 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/dmaxabssorted.h"
+#include "stdlib/math/base/assert/is_nan.h"
+#include "stdlib/math/base/special/abs.h"
+#include "stdlib/blas/base/shared.h"
+#include "stdlib/strided/base/stride2offset.h"
+
+/**
+* Computes the maximum absolute value of a sorted double-precision floating-point strided array.
+*
+* @param N        number of indexed elements
+* @param X        sorted input array
+* @param strideX  stride length
+* @return         output value
+*/
+double API_SUFFIX(stdlib_strided_dmaxabssorted)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ) {
+	const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX );
+	return API_SUFFIX(stdlib_strided_dmaxabssorted_ndarray)( N, X, strideX, ox );
+}
+
+/**
+* Computes the maximum absolute value of a sorted double-precision floating-point strided array using alternative indexing semantics.
+*
+* @param N        number of indexed elements
+* @param X        sorted input array
+* @param strideX  stride length
+* @param offsetX  starting index for X
+* @return         output value
+*/
+double API_SUFFIX(stdlib_strided_dmaxabssorted_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) {
+	double v1;
+	double v2;
+
+	if ( N <= 0 ) {
+		return 0.0 / 0.0; // NaN
+	}
+	if ( N == 1 || strideX == 0 ) {
+		return X[ 0 ];
+	}
+	v1 = X[ offsetX ];
+	v2 = X[ ( ( N - 1 ) * strideX ) + offsetX ];
+	if ( stdlib_base_is_nan( v1 ) || stdlib_base_is_nan( v2 ) ) {
+		return 0.0 / 0.0; // NaN
+	}
+	v1 = stdlib_base_abs( v1 );
+	v2 = stdlib_base_abs( v2 );
+	if ( v1 > v2 ) {
+		return v1;
+	}
+	return v2;
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/test/test.dmaxabssorted.js b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/test/test.dmaxabssorted.js
index 85710b088c45..994dec1ec029 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/test/test.dmaxabssorted.js
+++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/test/test.dmaxabssorted.js
@@ -21,7 +21,6 @@
 // MODULES //
 
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' );
 var Float64Array = require( '@stdlib/array/float64' );
@@ -116,7 +115,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 });
 
 tape( 'the function supports a `stride` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -131,15 +129,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) {
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = dmaxabssorted( N, x, 2 );
+	v = dmaxabssorted( 4, x, 2 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
 });
 
 tape( 'the function supports a negative `stride` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -154,8 +150,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t )
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = dmaxabssorted( N, x, -2 );
+	v = dmaxabssorted( 4, x, -2 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
@@ -176,7 +171,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f
 tape( 'the function supports view offsets', function test( t ) {
 	var x0;
 	var x1;
-	var N;
 	var v;
 
 	x0 = new Float64Array([
@@ -192,9 +186,8 @@ tape( 'the function supports view offsets', function test( t ) {
 	]);
 
 	x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
-	N = floor(x1.length / 2);
 
-	v = dmaxabssorted( N, x1, 2 );
+	v = dmaxabssorted( 4, x1, 2 );
 	t.strictEqual( v, 4.0, 'returns expected value' );
 
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/test/test.dmaxabssorted.native.js b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/test/test.dmaxabssorted.native.js
index cc2276961163..61261f63439e 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/test/test.dmaxabssorted.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/test/test.dmaxabssorted.native.js
@@ -22,7 +22,6 @@
 
 var resolve = require( 'path' ).resolve;
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' );
 var Float64Array = require( '@stdlib/array/float64' );
@@ -125,7 +124,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 });
 
 tape( 'the function supports a `stride` parameter', opts, function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -140,15 +138,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) {
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = dmaxabssorted( N, x, 2 );
+	v = dmaxabssorted( 4, x, 2 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
 });
 
 tape( 'the function supports a negative `stride` parameter', opts, function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -163,8 +159,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = dmaxabssorted( N, x, -2 );
+	v = dmaxabssorted( 4, x, -2 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
@@ -185,7 +180,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f
 tape( 'the function supports view offsets', opts, function test( t ) {
 	var x0;
 	var x1;
-	var N;
 	var v;
 
 	x0 = new Float64Array([
@@ -201,9 +195,8 @@ tape( 'the function supports view offsets', opts, function test( t ) {
 	]);
 
 	x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
-	N = floor(x1.length / 2);
 
-	v = dmaxabssorted( N, x1, 2 );
+	v = dmaxabssorted( 4, x1, 2 );
 	t.strictEqual( v, 4.0, 'returns expected value' );
 
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/test/test.ndarray.js
index 070a3e9810db..b00f94f068c3 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/test/test.ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/test/test.ndarray.js
@@ -21,7 +21,6 @@
 // MODULES //
 
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' );
 var Float64Array = require( '@stdlib/array/float64' );
@@ -116,7 +115,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 });
 
 tape( 'the function supports a `stride` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -131,15 +129,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) {
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = dmaxabssorted( N, x, 2, 0 );
+	v = dmaxabssorted( 4, x, 2, 0 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
 });
 
 tape( 'the function supports a negative `stride` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -154,8 +150,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t )
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = dmaxabssorted( N, x, -2, 6 );
+	v = dmaxabssorted( 4, x, -2, 6 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
@@ -174,7 +169,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f
 });
 
 tape( 'the function supports an `offset` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -188,9 +182,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) {
 		3.0,
 		4.0   // 3
 	]);
-	N = floor( x.length / 2 );
 
-	v = dmaxabssorted( N, x, 2, 1 );
+	v = dmaxabssorted( 4, x, 2, 1 );
 	t.strictEqual( v, 4.0, 'returns expected value' );
 
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/test/test.ndarray.native.js
index 348454887153..347b35dec2fc 100644
--- a/lib/node_modules/@stdlib/stats/base/dmaxabssorted/test/test.ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dmaxabssorted/test/test.ndarray.native.js
@@ -22,7 +22,6 @@
 
 var resolve = require( 'path' ).resolve;
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' );
 var Float64Array = require( '@stdlib/array/float64' );
@@ -125,7 +124,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 });
 
 tape( 'the function supports a `stride` parameter', opts, function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -140,15 +138,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) {
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = dmaxabssorted( N, x, 2, 0 );
+	v = dmaxabssorted( 4, x, 2, 0 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
 });
 
 tape( 'the function supports a negative `stride` parameter', opts, function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -163,8 +159,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = dmaxabssorted( N, x, -2, 6 );
+	v = dmaxabssorted( 4, x, -2, 6 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
@@ -183,7 +178,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f
 });
 
 tape( 'the function supports an `offset` parameter', opts, function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -197,9 +191,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) {
 		3.0,
 		4.0   // 3
 	]);
-	N = floor( x.length / 2 );
 
-	v = dmaxabssorted( N, x, 2, 1 );
+	v = dmaxabssorted( 4, x, 2, 1 );
 	t.strictEqual( v, 4.0, 'returns expected value' );
 
 	t.end();

From d0d3ae740af35589071dd11884fc69d21160defe Mon Sep 17 00:00:00 2001
From: Aayush Khanna <96649223+aayush0325@users.noreply.github.com>
Date: Fri, 3 Jan 2025 03:44:19 +0530
Subject: [PATCH 25/87] feat: add C ndarray interface and refactor
 implementation for `stats/base/smaxabssorted`

PR-URL: https://github.com/stdlib-js/stdlib/pull/4479
Reviewed-by: Athan Reines <kgryte@gmail.com>
Co-authored-by: stdlib-bot <82920195+stdlib-bot@users.noreply.github.com>
---
 .../stats/base/smaxabssorted/README.md        | 155 +++++++++++++++---
 .../base/smaxabssorted/benchmark/benchmark.js |  17 +-
 .../benchmark/benchmark.native.js             |  13 +-
 .../benchmark/benchmark.ndarray.js            |  17 +-
 .../benchmark/benchmark.ndarray.native.js     |  13 +-
 .../benchmark/c/benchmark.length.c            |  50 +++++-
 .../stats/base/smaxabssorted/docs/repl.txt    |  32 ++--
 .../base/smaxabssorted/docs/types/index.d.ts  |  10 +-
 .../base/smaxabssorted/examples/c/example.c   |   9 +-
 .../base/smaxabssorted/examples/index.js      |  13 +-
 .../stats/base/smaxabssorted/include.gypi     |   2 +-
 .../include/stdlib/stats/base/smaxabssorted.h |   9 +-
 .../stats/base/smaxabssorted/lib/index.js     |   7 +-
 .../stats/base/smaxabssorted/lib/ndarray.js   |  22 ++-
 .../base/smaxabssorted/lib/ndarray.native.js  |  20 +--
 .../base/smaxabssorted/lib/smaxabssorted.js   |  37 +----
 .../smaxabssorted/lib/smaxabssorted.native.js |   9 +-
 .../stats/base/smaxabssorted/manifest.json    |  75 ++++++++-
 .../stats/base/smaxabssorted/src/addon.c      |  60 +++++++
 .../stats/base/smaxabssorted/src/addon.cpp    | 117 -------------
 .../stats/base/smaxabssorted/src/main.c       |  68 ++++++++
 .../base/smaxabssorted/src/smaxabssorted.c    |  58 -------
 .../base/smaxabssorted/test/test.ndarray.js   |  15 +-
 .../smaxabssorted/test/test.ndarray.native.js |  15 +-
 .../smaxabssorted/test/test.smaxabssorted.js  |  13 +-
 .../test/test.smaxabssorted.native.js         |  13 +-
 26 files changed, 483 insertions(+), 386 deletions(-)
 create mode 100644 lib/node_modules/@stdlib/stats/base/smaxabssorted/src/addon.c
 delete mode 100644 lib/node_modules/@stdlib/stats/base/smaxabssorted/src/addon.cpp
 create mode 100644 lib/node_modules/@stdlib/stats/base/smaxabssorted/src/main.c
 delete mode 100644 lib/node_modules/@stdlib/stats/base/smaxabssorted/src/smaxabssorted.c

diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/README.md b/lib/node_modules/@stdlib/stats/base/smaxabssorted/README.md
index 2d3b6fa7e7b6..7f59ecdb503e 100644
--- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/README.md
+++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/README.md
@@ -36,7 +36,7 @@ limitations under the License.
 var smaxabssorted = require( '@stdlib/stats/base/smaxabssorted' );
 ```
 
-#### smaxabssorted( N, x, stride )
+#### smaxabssorted( N, x, strideX )
 
 Computes the maximum absolute value of a sorted single-precision floating-point strided array `x`.
 
@@ -56,18 +56,16 @@ The function has the following parameters:
 
 -   **N**: number of indexed elements.
 -   **x**: sorted input [`Float32Array`][@stdlib/array/float32].
--   **stride**: index increment for `x`.
+-   **strideX**: index increment for `x`.
 
-The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the maximum absolute value of every other element in `x`,
+The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the maximum absolute value of every other element in `x`,
 
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x = new Float32Array( [ 1.0, 2.0, 2.0, -7.0, 3.0, 3.0, 4.0, 2.0 ] );
-var N = floor( x.length / 2 );
 
-var v = smaxabssorted( N, x, 2 );
+var v = smaxabssorted( 4, x, 2 );
 // returns 4.0
 ```
 
@@ -77,18 +75,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [
 
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x0 = new Float32Array( [ 2.0, 1.0, 2.0, 2.0, -2.0, 2.0, 3.0, 4.0 ] );
 var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
 
-var N = floor( x0.length / 2 );
-
-var v = smaxabssorted( N, x1, 2 );
+var v = smaxabssorted( 4, x1, 2 );
 // returns 4.0
 ```
 
-#### smaxabssorted.ndarray( N, x, stride, offset )
+#### smaxabssorted.ndarray( N, x, strideX, offsetX )
 
 Computes the maximum absolute value of a sorted single-precision floating-point strided array using alternative indexing semantics.
 
@@ -102,18 +97,16 @@ var v = smaxabssorted.ndarray( x.length, x, 1, 0 );
 
 The function has the following additional parameters:
 
--   **offset**: starting index for `x`.
+-   **offsetX**: starting index for `x`.
 
-While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the maximum absolute value for every other value in `x` starting from the second value
+While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the maximum absolute value for every other element in `x` starting from the second element
 
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x = new Float32Array( [ 2.0, 1.0, 2.0, 2.0, -2.0, 2.0, 3.0, 4.0 ] );
-var N = floor( x.length / 2 );
 
-var v = smaxabssorted.ndarray( N, x, 2, 1 );
+var v = smaxabssorted.ndarray( 4, x, 2, 1 );
 // returns 4.0
 ```
 
@@ -139,16 +132,13 @@ var v = smaxabssorted.ndarray( N, x, 2, 1 );
 <!-- eslint no-undef: "error" -->
 
 ```javascript
-var Float32Array = require( '@stdlib/array/float32' );
+var linspace = require( '@stdlib/array/linspace' );
 var smaxabssorted = require( '@stdlib/stats/base/smaxabssorted' );
 
-var x;
-var i;
-
-x = new Float32Array( 10 );
-for ( i = 0; i < x.length; i++ ) {
-    x[ i ] = i - 5.0;
-}
+var options = {
+    'dtype': 'float32'
+};
+var x = linspace( -5.0, 5.0, 10, options );
 console.log( x );
 
 var v = smaxabssorted( x.length, x, 1 );
@@ -159,6 +149,123 @@ console.log( v );
 
 <!-- /.examples -->
 
+<!-- C interface documentation. -->
+
+* * *
+
+<section class="c">
+
+## C APIs
+
+<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<!-- C usage documentation. -->
+
+<section class="usage">
+
+### Usage
+
+```c
+#include "stdlib/stats/base/smaxabssorted.h"
+```
+
+#### stdlib_strided_smaxabssorted( N, \*X, strideX )
+
+Computes the maximum absolute value of a sorted single-precision floating-point strided array.
+
+```c
+const float x[] = { -1.0f, -2.0f, -3.0f, -4.0f, -5.0f, -6.0f, -7.0f, -8.0f };
+
+float v = stdlib_strided_smaxabssorted( 4, x, 2 );
+// returns 7.0f
+```
+
+The function accepts the following arguments:
+
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **X**: `[in] float*` input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+
+```c
+float stdlib_strided_smaxabssorted( const CBLAS_INT N, const float *X, const CBLAS_INT strideX );
+```
+
+#### stdlib_strided_smaxabssorted_ndarray( N, \*X, strideX, offsetX )
+
+Computes the maximum absolute value of a sorted single-precision floating-point strided array using alternative indexing semantics.
+
+```c
+const float x[] = { -1.0f, -2.0f, -3.0f, -4.0f, -5.0f, -6.0f, -7.0f, -8.0f };
+
+float v = stdlib_strided_smaxabssorted_ndarray( 4, x, 2, 0 );
+// returns 7.0f
+```
+
+The function accepts the following arguments:
+
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **X**: `[in] float*` input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+-   **offsetX**: `[in] CBLAS_INT` starting index for `X`.
+
+```c
+float stdlib_strided_smaxabssorted_ndarray( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX );
+```
+
+</section>
+
+<!-- /.usage -->
+
+<!-- C API usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="notes">
+
+</section>
+
+<!-- /.notes -->
+
+<!-- C API usage examples. -->
+
+<section class="examples">
+
+### Examples
+
+```c
+#include "stdlib/stats/base/smaxabssorted.h"
+#include <stdio.h>
+
+int main( void ) {
+    // Create a strided array:
+    const float x[] = { -1.0f, -2.0f, -3.0f, -4.0f, -5.0f, -6.0f, -7.0f, -8.0f };
+
+    // Specify the number of elements:
+    const int N = 4;
+
+    // Specify the stride length:
+    const int strideX = 2;
+
+    // Compute the maximum absolute value:
+    float v = stdlib_strided_smaxabssorted( N, x, strideX );
+
+    // Print the result:
+    printf( "maxabs: %f\n", v );
+}
+```
+
+</section>
+
+<!-- /.examples -->
+
+</section>
+
+<!-- /.c -->
+
 <!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
 
 <section class="related">
diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/smaxabssorted/benchmark/benchmark.js
index 2ac183eec251..de2b563e9575 100644
--- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/benchmark/benchmark.js
+++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/benchmark/benchmark.js
@@ -22,12 +22,19 @@
 
 var bench = require( '@stdlib/bench' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
+var linspace = require( '@stdlib/array/linspace' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float32Array = require( '@stdlib/array/float32' );
 var pkg = require( './../package.json' ).name;
 var smaxabssorted = require( './../lib/smaxabssorted.js' );
 
 
+// VARIABLES //
+
+var options = {
+	'dtype': 'float32'
+};
+
+
 // FUNCTIONS //
 
 /**
@@ -38,13 +45,7 @@ var smaxabssorted = require( './../lib/smaxabssorted.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float32Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = i - (len/2);
-	}
+	var x = linspace( -len/2, len/2, len, options );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/smaxabssorted/benchmark/benchmark.native.js
index e078637b4a9f..5eb7b502b0eb 100644
--- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/benchmark/benchmark.native.js
+++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/benchmark/benchmark.native.js
@@ -23,8 +23,8 @@
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
+var linspace = require( '@stdlib/array/linspace' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float32Array = require( '@stdlib/array/float32' );
 var tryRequire = require( '@stdlib/utils/try-require' );
 var pkg = require( './../package.json' ).name;
 
@@ -35,6 +35,9 @@ var smaxabssorted = tryRequire( resolve( __dirname, './../lib/smaxabssorted.nati
 var opts = {
 	'skip': ( smaxabssorted instanceof Error )
 };
+var options = {
+	'dtype': 'float32'
+};
 
 
 // FUNCTIONS //
@@ -47,13 +50,7 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float32Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = i - (len/2);
-	}
+	var x = linspace( -len/2, len/2, len, options );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/smaxabssorted/benchmark/benchmark.ndarray.js
index da66e78de0f3..16c697f6cb4f 100644
--- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/benchmark/benchmark.ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/benchmark/benchmark.ndarray.js
@@ -22,12 +22,19 @@
 
 var bench = require( '@stdlib/bench' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
+var linspace = require( '@stdlib/array/linspace' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float32Array = require( '@stdlib/array/float32' );
 var pkg = require( './../package.json' ).name;
 var smaxabssorted = require( './../lib/ndarray.js' );
 
 
+// VARIABLES //
+
+var options = {
+	'dtype': 'float32'
+};
+
+
 // FUNCTIONS //
 
 /**
@@ -38,13 +45,7 @@ var smaxabssorted = require( './../lib/ndarray.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float32Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = i - (len/2);
-	}
+	var x = linspace( -len/2, len/2, len, options );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/smaxabssorted/benchmark/benchmark.ndarray.native.js
index 50677703e5d6..021d542282dc 100644
--- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/benchmark/benchmark.ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/benchmark/benchmark.ndarray.native.js
@@ -23,8 +23,8 @@
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
+var linspace = require( '@stdlib/array/linspace' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float32Array = require( '@stdlib/array/float32' );
 var tryRequire = require( '@stdlib/utils/try-require' );
 var pkg = require( './../package.json' ).name;
 
@@ -35,6 +35,9 @@ var smaxabssorted = tryRequire( resolve( __dirname, './../lib/ndarray.native.js'
 var opts = {
 	'skip': ( smaxabssorted instanceof Error )
 };
+var options = {
+	'dtype': 'float32'
+};
 
 
 // FUNCTIONS //
@@ -47,13 +50,7 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float32Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = i - (len/2);
-	}
+	var x = linspace( -len/2, len/2, len, options );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/smaxabssorted/benchmark/c/benchmark.length.c
index 4adecd1ce942..22f0fed7d4de 100644
--- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/benchmark/c/benchmark.length.c
+++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/benchmark/c/benchmark.length.c
@@ -94,7 +94,7 @@ static float rand_float( void ) {
 * @param len          array length
 * @return             elapsed time in seconds
 */
-static double benchmark( int iterations, int len ) {
+static double benchmark1( int iterations, int len ) {
 	double elapsed;
 	float x[ len ];
 	float v;
@@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) {
 	v = 0.0f;
 	t = tic();
 	for ( i = 0; i < iterations; i++ ) {
+		// cppcheck-suppress uninitvar
 		v = stdlib_strided_smaxabssorted( len, x, 1 );
 		if ( v != v ) {
 			printf( "should not return NaN\n" );
@@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) {
 	return elapsed;
 }
 
+/**
+* Runs a benchmark.
+*
+* @param iterations   number of iterations
+* @param len          array length
+* @return             elapsed time in seconds
+*/
+static double benchmark2( int iterations, int len ) {
+	double elapsed;
+	float x[ len ];
+	float v;
+	double t;
+	int i;
+
+	for ( i = 0; i < len; i++ ) {
+		x[ i ] = i - (len/2);
+	}
+	v = 0.0f;
+	t = tic();
+	for ( i = 0; i < iterations; i++ ) {
+		// cppcheck-suppress uninitvar
+		v = stdlib_strided_smaxabssorted_ndarray( len, x, 1, 0 );
+		if ( v != v ) {
+			printf( "should not return NaN\n" );
+			break;
+		}
+	}
+	elapsed = tic() - t;
+	if ( v != v ) {
+		printf( "should not return NaN\n" );
+	}
+	return elapsed;
+}
+
 /**
 * Main execution sequence.
 */
@@ -142,7 +177,18 @@ int main( void ) {
 		for ( j = 0; j < REPEATS; j++ ) {
 			count += 1;
 			printf( "# c::%s:len=%d\n", NAME, len );
-			elapsed = benchmark( iter, len );
+			elapsed = benchmark1( iter, len );
+			print_results( iter, elapsed );
+			printf( "ok %d benchmark finished\n", count );
+		}
+	}
+	for ( i = MIN; i <= MAX; i++ ) {
+		len = pow( 10, i );
+		iter = ITERATIONS;
+		for ( j = 0; j < REPEATS; j++ ) {
+			count += 1;
+			printf( "# c::%s:ndarray:len=%d\n", NAME, len );
+			elapsed = benchmark2( iter, len );
 			print_results( iter, elapsed );
 			printf( "ok %d benchmark finished\n", count );
 		}
diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/smaxabssorted/docs/repl.txt
index d8eb24b2245d..c95dd3923d9f 100644
--- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/docs/repl.txt
+++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/docs/repl.txt
@@ -1,13 +1,13 @@
 
-{{alias}}( N, x, stride )
+{{alias}}( N, x, strideX )
     Computes the maximum absolute value of a sorted single-precision floating-
     point strided array.
 
     The input strided array must be sorted in either strictly ascending or
     descending order.
 
-    The `N` and `stride` parameters determine which elements in `x` are accessed
-    at runtime.
+    The `N` and stride parameters determine which elements in the strided array
+    are accessed at runtime.
 
     Indexing is relative to the first index. To introduce an offset, use a typed
     array view.
@@ -22,8 +22,8 @@
     x: Float32Array
         Sorted input array.
 
-    stride: integer
-        Index increment.
+    strideX: integer
+        Stride Length.
 
     Returns
     -------
@@ -37,22 +37,19 @@
     > {{alias}}( x.length, x, 1 )
     3.0
 
-    // Using `N` and `stride` parameters:
+    // Using `N` and stride parameters:
     > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > var stride = 2;
-    > {{alias}}( N, x, stride )
+    > {{alias}}( 3, x, 2 )
     2.0
 
     // Using view offsets:
     > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );
     > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );
-    > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );
-    > stride = 2;
-    > {{alias}}( N, x1, stride )
+    > {{alias}}( 3, x1, 2 )
     3.0
 
-{{alias}}.ndarray( N, x, stride, offset )
+
+{{alias}}.ndarray( N, x, strideX, offsetX )
     Computes the maximum absolute value of a sorted single-precision floating-
     point strided array using alternative indexing semantics.
 
@@ -68,10 +65,10 @@
     x: Float32Array
         Sorted input array.
 
-    stride: integer
-        Index increment.
+    strideX: integer
+        Stride Length.
 
-    offset: integer
+    offsetX: integer
         Starting index.
 
     Returns
@@ -88,8 +85,7 @@
 
     // Using offset parameter:
     > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > {{alias}}.ndarray( N, x, 2, 1 )
+    > {{alias}}.ndarray( 3, x, 2, 1 )
     3.0
 
     See Also
diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/smaxabssorted/docs/types/index.d.ts
index 20111c7d9230..bebe407fc252 100644
--- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/docs/types/index.d.ts
@@ -27,7 +27,7 @@ interface Routine {
 	*
 	* @param N - number of indexed elements
 	* @param x - sorted input array
-	* @param stride - stride length
+	* @param strideX - stride length
 	* @returns maximum absolute value
 	*
 	* @example
@@ -38,15 +38,15 @@ interface Routine {
 	* var v = smaxabssorted( x.length, x, 1 );
 	* // returns 3.0
 	*/
-	( N: number, x: Float32Array, stride: number ): number;
+	( N: number, x: Float32Array, strideX: number ): number;
 
 	/**
 	* Computes the maximum absolute value of a sorted single-precision floating-point strided array using alternative indexing semantics.
 	*
 	* @param N - number of indexed elements
 	* @param x - sorted input array
-	* @param stride - stride length
-	* @param offset - starting index
+	* @param strideX - stride length
+	* @param offsetX - starting index
 	* @returns maximum absolute value
 	*
 	* @example
@@ -57,7 +57,7 @@ interface Routine {
 	* var v = smaxabssorted.ndarray( x.length, x, 1, 0 );
 	* // returns 3.0
 	*/
-	ndarray( N: number, x: Float32Array, stride: number, offset: number ): number;
+	ndarray( N: number, x: Float32Array, strideX: number, offsetX: number ): number;
 }
 
 /**
diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/smaxabssorted/examples/c/example.c
index abbe77270ced..5defd829bff7 100644
--- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/examples/c/example.c
+++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/examples/c/example.c
@@ -17,21 +17,20 @@
 */
 
 #include "stdlib/stats/base/smaxabssorted.h"
-#include <stdint.h>
 #include <stdio.h>
 
 int main( void ) {
 	// Create a strided array:
-	float x[] = { -1.0, -2.0, -3.0, -4.0, -5.0, -6.0, -7.0, -8.0 };
+	const float x[] = { -1.0f, -2.0f, -3.0f, -4.0f, -5.0f, -6.0f, -7.0f, -8.0f };
 
 	// Specify the number of elements:
-	int64_t N = 4;
+	const int N = 4;
 
 	// Specify the stride length:
-	int64_t stride = 2;
+	const int strideX = 2;
 
 	// Compute the maximum absolute value:
-	float v = stdlib_strided_smaxabssorted( N, x, stride );
+	float v = stdlib_strided_smaxabssorted( N, x, strideX );
 
 	// Print the result:
 	printf( "maxabs: %f\n", v );
diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/examples/index.js b/lib/node_modules/@stdlib/stats/base/smaxabssorted/examples/index.js
index 36fc67912ee4..7907b227a919 100644
--- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/examples/index.js
+++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/examples/index.js
@@ -18,16 +18,13 @@
 
 'use strict';
 
-var Float32Array = require( '@stdlib/array/float32' );
+var linspace = require( '@stdlib/array/linspace' );
 var smaxabssorted = require( './../lib' );
 
-var x;
-var i;
-
-x = new Float32Array( 10 );
-for ( i = 0; i < x.length; i++ ) {
-	x[ i ] = i - x.length;
-}
+var options = {
+	'dtype': 'float32'
+};
+var x = linspace( -5.0, 5.0, 10, options );
 console.log( x );
 
 var v = smaxabssorted( x.length, x, 1 );
diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/include.gypi b/lib/node_modules/@stdlib/stats/base/smaxabssorted/include.gypi
index 868c5c12e852..26476a8c2655 100644
--- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/include.gypi
+++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/include.gypi
@@ -36,7 +36,7 @@
 
     # Source files:
     'src_files': [
-      '<(src_dir)/addon.cpp',
+      '<(src_dir)/addon.c',
       '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).src; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
     ],
 
diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/include/stdlib/stats/base/smaxabssorted.h b/lib/node_modules/@stdlib/stats/base/smaxabssorted/include/stdlib/stats/base/smaxabssorted.h
index b96378d4169f..08fad6370531 100644
--- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/include/stdlib/stats/base/smaxabssorted.h
+++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/include/stdlib/stats/base/smaxabssorted.h
@@ -19,7 +19,7 @@
 #ifndef STDLIB_STATS_BASE_SMAXABSSORTED_H
 #define STDLIB_STATS_BASE_SMAXABSSORTED_H
 
-#include <stdint.h>
+#include "stdlib/blas/base/shared.h"
 
 /*
 * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler.
@@ -31,7 +31,12 @@ extern "C" {
 /**
 * Computes the maximum absolute value of a sorted single-precision floating-point strided array.
 */
-float stdlib_strided_smaxabssorted( const int64_t N, const float *X, const int64_t stride );
+float API_SUFFIX(stdlib_strided_smaxabssorted)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX );
+
+/**
+* Computes the maximum absolute value of a sorted single-precision floating-point strided array using alternative indexing semantics.
+*/
+float API_SUFFIX(stdlib_strided_smaxabssorted_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX );
 
 #ifdef __cplusplus
 }
diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/lib/index.js b/lib/node_modules/@stdlib/stats/base/smaxabssorted/lib/index.js
index 6c2bf70858db..2d0a5fe8bfdf 100644
--- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/lib/index.js
+++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/lib/index.js
@@ -28,20 +28,17 @@
 * var smaxabssorted = require( '@stdlib/stats/base/smaxabssorted' );
 *
 * var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );
-* var N = x.length;
 *
-* var v = smaxabssorted( N, x, 1 );
+* var v = smaxabssorted( x.length, x, 1 );
 * // returns 3.0
 *
 * @example
 * var Float32Array = require( '@stdlib/array/float32' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 * var smaxabssorted = require( '@stdlib/stats/base/smaxabssorted' );
 *
 * var x = new Float32Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
-* var N = floor( x.length / 2 );
 *
-* var v = smaxabssorted.ndarray( N, x, 2, 1 );
+* var v = smaxabssorted.ndarray( 4, x, 2, 1 );
 * // returns 4.0
 */
 
diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/smaxabssorted/lib/ndarray.js
index f75720ed3aeb..ac460c8c0a06 100644
--- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/lib/ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/lib/ndarray.js
@@ -21,7 +21,7 @@
 // MODULES //
 
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
-var abs = require( '@stdlib/math/base/special/abs' );
+var absf = require( '@stdlib/math/base/special/absf' );
 
 
 // MAIN //
@@ -31,37 +31,35 @@ var abs = require( '@stdlib/math/base/special/abs' );
 *
 * @param {PositiveInteger} N - number of indexed elements
 * @param {Float32Array} x - sorted input array
-* @param {integer} stride - stride length
-* @param {NonNegativeInteger} offset - starting index
+* @param {integer} strideX - stride length
+* @param {NonNegativeInteger} offsetX - starting index
 * @returns {number} maximum absolute value
 *
 * @example
 * var Float32Array = require( '@stdlib/array/float32' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 *
 * var x = new Float32Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
-* var N = floor( x.length / 2 );
 *
-* var v = smaxabssorted( N, x, 2, 1 );
+* var v = smaxabssorted( 4, x, 2, 1 );
 * // returns 4.0
 */
-function smaxabssorted( N, x, stride, offset ) {
+function smaxabssorted( N, x, strideX, offsetX ) {
 	var v1;
 	var v2;
 
 	if ( N <= 0 ) {
 		return NaN;
 	}
-	if ( N === 1 || stride === 0 ) {
+	if ( N === 1 || strideX === 0 ) {
 		return x[ 0 ];
 	}
-	v1 = x[ offset ];
-	v2 = x[ offset + ((N-1)*stride) ];
+	v1 = x[ offsetX ];
+	v2 = x[ offsetX + ((N-1)*strideX) ];
 	if ( isnanf( v1 ) || isnanf( v2 ) ) {
 		return NaN;
 	}
-	v1 = abs( v1 );
-	v2 = abs( v2 );
+	v1 = absf( v1 );
+	v2 = absf( v2 );
 	if ( v1 > v2 ) {
 		return v1;
 	}
diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/smaxabssorted/lib/ndarray.native.js
index 6c118eb57a89..70fb049038b9 100644
--- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/lib/ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/lib/ndarray.native.js
@@ -20,8 +20,7 @@
 
 // MODULES //
 
-var Float32Array = require( '@stdlib/array/float32' );
-var addon = require( './smaxabssorted.native.js' );
+var addon = require( './../src/addon.node' );
 
 
 // MAIN //
@@ -31,27 +30,20 @@ var addon = require( './smaxabssorted.native.js' );
 *
 * @param {PositiveInteger} N - number of indexed elements
 * @param {Float32Array} x - sorted input array
-* @param {integer} stride - stride length
-* @param {NonNegativeInteger} offset - starting index
+* @param {integer} strideX - stride length
+* @param {NonNegativeInteger} offsetX - starting index
 * @returns {number} maximum absolute value
 *
 * @example
 * var Float32Array = require( '@stdlib/array/float32' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 *
 * var x = new Float32Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
-* var N = floor( x.length / 2 );
 *
-* var v = smaxabssorted( N, x, 2, 1 );
+* var v = smaxabssorted( 4, x, 2, 1 );
 * // returns 4.0
 */
-function smaxabssorted( N, x, stride, offset ) {
-	var view;
-	if ( stride < 0 ) {
-		offset += (N-1) * stride;
-	}
-	view = new Float32Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len
-	return addon( N, view, stride );
+function smaxabssorted( N, x, strideX, offsetX ) {
+	return addon.ndarray( N, x, strideX, offsetX );
 }
 
 
diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/lib/smaxabssorted.js b/lib/node_modules/@stdlib/stats/base/smaxabssorted/lib/smaxabssorted.js
index 601547599380..58d223b34851 100644
--- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/lib/smaxabssorted.js
+++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/lib/smaxabssorted.js
@@ -20,8 +20,8 @@
 
 // MODULES //
 
-var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
-var abs = require( '@stdlib/math/base/special/abs' );
+var stride2offset = require( '@stdlib/strided/base/stride2offset' );
+var ndarray = require( './ndarray.js' );
 
 
 // MAIN //
@@ -31,44 +31,19 @@ var abs = require( '@stdlib/math/base/special/abs' );
 *
 * @param {PositiveInteger} N - number of indexed elements
 * @param {Float32Array} x - sorted input array
-* @param {integer} stride - stride length
+* @param {integer} strideX - stride length
 * @returns {number} maximum absolute value
 *
 * @example
 * var Float32Array = require( '@stdlib/array/float32' );
 *
 * var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );
-* var N = x.length;
 *
-* var v = smaxabssorted( N, x, 1 );
+* var v = smaxabssorted( x.length, x, 1 );
 * // returns 3.0
 */
-function smaxabssorted( N, x, stride ) {
-	var v1;
-	var v2;
-
-	if ( N <= 0 ) {
-		return NaN;
-	}
-	if ( N === 1 || stride === 0 ) {
-		return x[ 0 ];
-	}
-	if ( stride < 0 ) {
-		v1 = x[ (1-N) * stride ];
-		v2 = x[ 0 ];
-	} else {
-		v1 = x[ 0 ];
-		v2 = x[ (N-1) * stride ];
-	}
-	if ( isnanf( v1 ) || isnanf( v2 ) ) {
-		return NaN;
-	}
-	v1 = abs( v1 );
-	v2 = abs( v2 );
-	if ( v1 > v2 ) {
-		return v1;
-	}
-	return v2;
+function smaxabssorted( N, x, strideX ) {
+	return ndarray( N, x, strideX, stride2offset( N, strideX ) );
 }
 
 
diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/lib/smaxabssorted.native.js b/lib/node_modules/@stdlib/stats/base/smaxabssorted/lib/smaxabssorted.native.js
index f9a71bc2c9c7..ac6d9b262d87 100644
--- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/lib/smaxabssorted.native.js
+++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/lib/smaxabssorted.native.js
@@ -30,20 +30,19 @@ var addon = require( './../src/addon.node' );
 *
 * @param {PositiveInteger} N - number of indexed elements
 * @param {Float32Array} x - sorted input array
-* @param {integer} stride - stride length
+* @param {integer} strideX - stride length
 * @returns {number} maximum absolute value
 *
 * @example
 * var Float32Array = require( '@stdlib/array/float32' );
 *
 * var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );
-* var N = x.length;
 *
-* var v = smaxabssorted( N, x, 1 );
+* var v = smaxabssorted( x.length, x, 1 );
 * // returns 3.0
 */
-function smaxabssorted( N, x, stride ) {
-	return addon( N, x, stride );
+function smaxabssorted( N, x, strideX ) {
+	return addon( N, x, strideX );
 }
 
 
diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/manifest.json b/lib/node_modules/@stdlib/stats/base/smaxabssorted/manifest.json
index 70db545e29cd..c5f79a39adbb 100644
--- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/manifest.json
+++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/manifest.json
@@ -1,5 +1,8 @@
 {
-  "options": {},
+  "options": {
+    "task": "build",
+    "wasm": false
+  },
   "fields": [
     {
       "field": "src",
@@ -24,18 +27,80 @@
   ],
   "confs": [
     {
+      "task": "build",
+      "wasm": false,
       "src": [
-        "./src/smaxabssorted.c"
+        "./src/main.c"
       ],
       "include": [
         "./include"
       ],
-      "libraries": [
-        "-lm"
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/math/base/assert/is-nanf",
+        "@stdlib/math/base/special/absf",
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset",
+        "@stdlib/napi/export",
+        "@stdlib/napi/argv",
+        "@stdlib/napi/argv-int64",
+        "@stdlib/napi/argv-strided-float32array",
+        "@stdlib/napi/create-double"
+      ]
+    },
+    {
+      "task": "benchmark",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/math/base/assert/is-nanf",
+        "@stdlib/math/base/special/absf",
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset"
+      ]
+    },
+    {
+      "task": "examples",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/math/base/assert/is-nanf",
+        "@stdlib/math/base/special/absf",
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset"
+      ]
+    },
+    {
+      "task": "",
+      "wasm": true,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
       ],
+      "libraries": [],
       "libpath": [],
       "dependencies": [
-        "@stdlib/math/base/assert/is-nanf"
+        "@stdlib/math/base/assert/is-nanf",
+        "@stdlib/math/base/special/absf",
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset"
       ]
     }
   ]
diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/src/addon.c b/lib/node_modules/@stdlib/stats/base/smaxabssorted/src/addon.c
new file mode 100644
index 000000000000..351e50d9b3dd
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/src/addon.c
@@ -0,0 +1,60 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/smaxabssorted.h"
+#include "stdlib/napi/export.h"
+#include "stdlib/napi/argv.h"
+#include "stdlib/napi/argv_int64.h"
+#include "stdlib/napi/argv_strided_float32array.h"
+#include "stdlib/napi/create_double.h"
+#include <node_api.h>
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 3 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_smaxabssorted( N, X, strideX ), v );
+	return v;
+}
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon_method( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 4 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 );
+	STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_smaxabssorted_ndarray( N, X, strideX, offsetX ), v );
+	return v;
+}
+
+STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method )
diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/smaxabssorted/src/addon.cpp
deleted file mode 100644
index 247ca07d6599..000000000000
--- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/src/addon.cpp
+++ /dev/null
@@ -1,117 +0,0 @@
-/**
-* @license Apache-2.0
-*
-* Copyright (c) 2020 The Stdlib Authors.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-*    http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-
-#include "stdlib/stats/base/smaxabssorted.h"
-#include <node_api.h>
-#include <stdint.h>
-#include <stdlib.h>
-#include <stdbool.h>
-#include <assert.h>
-
-/**
-* Add-on namespace.
-*/
-namespace stdlib_stats_base_smaxabssorted {
-
-	/**
-	* Computes the maximum absolute value of a sorted single-precision floating-point strided array.
-	*
-	* ## Notes
-	*
-	* -   When called from JavaScript, the function expects three arguments:
-	*
-	*     -   `N`: number of indexed elements
-	*     -   `X`: sorted input array
-	*     -   `stride`: stride length
-	*/
-	napi_value node_smaxabssorted( napi_env env, napi_callback_info info ) {
-		napi_status status;
-
-		size_t argc = 3;
-		napi_value argv[ 3 ];
-		status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr );
-		assert( status == napi_ok );
-
-		if ( argc < 3 ) {
-			napi_throw_error( env, nullptr, "invalid invocation. Must provide 3 arguments." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype0;
-		status = napi_typeof( env, argv[ 0 ], &vtype0 );
-		assert( status == napi_ok );
-		if ( vtype0 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." );
-			return nullptr;
-		}
-
-		bool res;
-		status = napi_is_typedarray( env, argv[ 1 ], &res );
-		assert( status == napi_ok );
-		if ( res == false ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype2;
-		status = napi_typeof( env, argv[ 2 ], &vtype2 );
-		assert( status == napi_ok );
-		if ( vtype2 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." );
-			return nullptr;
-		}
-
-		int64_t N;
-		status = napi_get_value_int64( env, argv[ 0 ], &N );
-		assert( status == napi_ok );
-
-		int64_t stride;
-		status = napi_get_value_int64( env, argv[ 2 ], &stride );
-		assert( status == napi_ok );
-
-		napi_typedarray_type vtype1;
-		size_t xlen;
-		void *X;
-		status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr );
-		assert( status == napi_ok );
-		if ( vtype1 != napi_float32_array ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." );
-			return nullptr;
-		}
-		if ( (N-1)*llabs(stride) >= (int64_t)xlen ) {
-			napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." );
-			return nullptr;
-		}
-
-		napi_value v;
-		status = napi_create_double( env, (double)stdlib_strided_smaxabssorted( N, (float *)X, stride ), &v );
-		assert( status == napi_ok );
-
-		return v;
-	}
-
-	napi_value Init( napi_env env, napi_value exports ) {
-		napi_status status;
-		napi_value fcn;
-		status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_smaxabssorted, NULL, &fcn );
-		assert( status == napi_ok );
-		return fcn;
-	}
-
-	NAPI_MODULE( NODE_GYP_MODULE_NAME, Init )
-} // end namespace stdlib_stats_base_smaxabssorted
diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/src/main.c b/lib/node_modules/@stdlib/stats/base/smaxabssorted/src/main.c
new file mode 100644
index 000000000000..64a899661429
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/src/main.c
@@ -0,0 +1,68 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/smaxabssorted.h"
+#include "stdlib/math/base/assert/is_nanf.h"
+#include "stdlib/math/base/special/absf.h"
+#include "stdlib/blas/base/shared.h"
+#include "stdlib/strided/base/stride2offset.h"
+
+/**
+* Computes the maximum absolute value of a sorted single-precision floating-point strided array.
+*
+* @param N        number of indexed elements
+* @param X        sorted input array
+* @param strideX  stride length
+* @return         output value
+*/
+float API_SUFFIX(stdlib_strided_smaxabssorted)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX ) {
+	const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX );
+	return API_SUFFIX(stdlib_strided_smaxabssorted_ndarray)( N, X, strideX, ox );
+}
+
+/**
+* Computes the maximum absolute value of a sorted single-precision floating-point strided array using alternative indexing semantics.
+*
+* @param N        number of indexed elements
+* @param X        sorted input array
+* @param strideX  stride length
+* @param offsetX  starting index for X
+* @return         output value
+*/
+float API_SUFFIX(stdlib_strided_smaxabssorted_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) {
+	float v1;
+	float v2;
+
+	if ( N <= 0 ) {
+		return 0.0f / 0.0f; // NaN
+	}
+	if ( N == 1 || strideX == 0 ) {
+		return X[ 0 ];
+	}
+	v1 = X[ offsetX ];
+	v2 = X[ ( ( N - 1 ) * strideX ) + offsetX ];
+	if ( stdlib_base_is_nanf( v1 ) || stdlib_base_is_nanf( v2 ) ) {
+		return 0.0f / 0.0f; // NaN
+	}
+	v1 = stdlib_base_absf( v1 );
+	v2 = stdlib_base_absf( v2 );
+	if ( v1 > v2 ) {
+		return v1;
+	}
+	return v2;
+}
diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/src/smaxabssorted.c b/lib/node_modules/@stdlib/stats/base/smaxabssorted/src/smaxabssorted.c
deleted file mode 100644
index d91eccfab7f7..000000000000
--- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/src/smaxabssorted.c
+++ /dev/null
@@ -1,58 +0,0 @@
-/**
-* @license Apache-2.0
-*
-* Copyright (c) 2020 The Stdlib Authors.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-*    http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-
-#include "stdlib/stats/base/smaxabssorted.h"
-#include "stdlib/math/base/assert/is_nanf.h"
-#include <stdint.h>
-#include <math.h>
-
-/**
-* Computes the maximum absolute value of a sorted single-precision floating-point strided array.
-*
-* @param N       number of indexed elements
-* @param X       sorted input array
-* @param stride  stride length
-* @return        output value
-*/
-float stdlib_strided_smaxabssorted( const int64_t N, const float *X, const int64_t stride ) {
-	float v1;
-	float v2;
-
-	if ( N <= 0 ) {
-		return 0.0f / 0.0f; // NaN
-	}
-	if ( N == 1 || stride == 0 ) {
-		return X[ 0 ];
-	}
-	if ( stride < 0 ) {
-		v1 = X[ (1-N) * stride ];
-		v2 = X[ 0 ];
-	} else {
-		v1 = X[ 0 ];
-		v2 = X[ (N-1) * stride ];
-	}
-	if ( stdlib_base_is_nanf( v1 ) || stdlib_base_is_nanf( v2 ) ) {
-		return 0.0f / 0.0f; // NaN
-	}
-	v1 = fabsf( v1 );
-	v2 = fabsf( v2 );
-	if ( v1 > v2 ) {
-		return v1;
-	}
-	return v2;
-}
diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/smaxabssorted/test/test.ndarray.js
index 3222cdfd1981..c2f5e9a961e7 100644
--- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/test/test.ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/test/test.ndarray.js
@@ -21,7 +21,6 @@
 // MODULES //
 
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
 var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' );
 var Float32Array = require( '@stdlib/array/float32' );
@@ -116,7 +115,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 });
 
 tape( 'the function supports a `stride` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -125,21 +123,19 @@ tape( 'the function supports a `stride` parameter', function test( t ) {
 		2.0,
 		2.0,  // 1
 		-7.0,
-		3.0, // 2
+		3.0,  // 2
 		3.0,
 		4.0,  // 3
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = smaxabssorted( N, x, 2, 0 );
+	v = smaxabssorted( 4, x, 2, 0 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
 });
 
 tape( 'the function supports a negative `stride` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -154,8 +150,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t )
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = smaxabssorted( N, x, -2, 6 );
+	v = smaxabssorted( 4, x, -2, 6 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
@@ -174,7 +169,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f
 });
 
 tape( 'the function supports an `offset` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -188,9 +182,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) {
 		3.0,
 		4.0   // 3
 	]);
-	N = floor( x.length / 2 );
 
-	v = smaxabssorted( N, x, 2, 1 );
+	v = smaxabssorted( 4, x, 2, 1 );
 	t.strictEqual( v, 4.0, 'returns expected value' );
 
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/smaxabssorted/test/test.ndarray.native.js
index 8e0a25335ab7..c3379e3993de 100644
--- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/test/test.ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/test/test.ndarray.native.js
@@ -22,7 +22,6 @@
 
 var resolve = require( 'path' ).resolve;
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
 var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' );
 var Float32Array = require( '@stdlib/array/float32' );
@@ -125,7 +124,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 });
 
 tape( 'the function supports a `stride` parameter', opts, function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -134,21 +132,19 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) {
 		2.0,
 		2.0,  // 1
 		-7.0,
-		3.0, // 2
+		3.0,  // 2
 		3.0,
 		4.0,  // 3
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = smaxabssorted( N, x, 2, 0 );
+	v = smaxabssorted( 4, x, 2, 0 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
 });
 
 tape( 'the function supports a negative `stride` parameter', opts, function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -163,8 +159,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = smaxabssorted( N, x, -2, 6 );
+	v = smaxabssorted( 4, x, -2, 6 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
@@ -183,7 +178,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f
 });
 
 tape( 'the function supports an `offset` parameter', opts, function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -197,9 +191,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) {
 		3.0,
 		4.0   // 3
 	]);
-	N = floor( x.length / 2 );
 
-	v = smaxabssorted( N, x, 2, 1 );
+	v = smaxabssorted( 4, x, 2, 1 );
 	t.strictEqual( v, 4.0, 'returns expected value' );
 
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/test/test.smaxabssorted.js b/lib/node_modules/@stdlib/stats/base/smaxabssorted/test/test.smaxabssorted.js
index f654ff6f9525..e8f32a828003 100644
--- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/test/test.smaxabssorted.js
+++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/test/test.smaxabssorted.js
@@ -21,7 +21,6 @@
 // MODULES //
 
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
 var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' );
 var Float32Array = require( '@stdlib/array/float32' );
@@ -116,7 +115,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 });
 
 tape( 'the function supports a `stride` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -131,15 +129,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) {
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = smaxabssorted( N, x, 2 );
+	v = smaxabssorted( 4, x, 2 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
 });
 
 tape( 'the function supports a negative `stride` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -154,8 +150,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t )
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = smaxabssorted( N, x, -2 );
+	v = smaxabssorted( 4, x, -2 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
@@ -176,7 +171,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f
 tape( 'the function supports view offsets', function test( t ) {
 	var x0;
 	var x1;
-	var N;
 	var v;
 
 	x0 = new Float32Array([
@@ -192,9 +186,8 @@ tape( 'the function supports view offsets', function test( t ) {
 	]);
 
 	x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
-	N = floor(x1.length / 2);
 
-	v = smaxabssorted( N, x1, 2 );
+	v = smaxabssorted( 4, x1, 2 );
 	t.strictEqual( v, 4.0, 'returns expected value' );
 
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/smaxabssorted/test/test.smaxabssorted.native.js b/lib/node_modules/@stdlib/stats/base/smaxabssorted/test/test.smaxabssorted.native.js
index a7203cfdd25e..8b3a74a94dde 100644
--- a/lib/node_modules/@stdlib/stats/base/smaxabssorted/test/test.smaxabssorted.native.js
+++ b/lib/node_modules/@stdlib/stats/base/smaxabssorted/test/test.smaxabssorted.native.js
@@ -22,7 +22,6 @@
 
 var resolve = require( 'path' ).resolve;
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
 var isPositiveZerof = require( '@stdlib/math/base/assert/is-positive-zerof' );
 var Float32Array = require( '@stdlib/array/float32' );
@@ -125,7 +124,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 });
 
 tape( 'the function supports a `stride` parameter', opts, function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -140,15 +138,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) {
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = smaxabssorted( N, x, 2 );
+	v = smaxabssorted( 4, x, 2 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
 });
 
 tape( 'the function supports a negative `stride` parameter', opts, function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -163,8 +159,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = smaxabssorted( N, x, -2 );
+	v = smaxabssorted( 4, x, -2 );
 
 	t.strictEqual( v, 4.0, 'returns expected value' );
 	t.end();
@@ -185,7 +180,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f
 tape( 'the function supports view offsets', opts, function test( t ) {
 	var x0;
 	var x1;
-	var N;
 	var v;
 
 	x0 = new Float32Array([
@@ -201,9 +195,8 @@ tape( 'the function supports view offsets', opts, function test( t ) {
 	]);
 
 	x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
-	N = floor(x1.length / 2);
 
-	v = smaxabssorted( N, x1, 2 );
+	v = smaxabssorted( 4, x1, 2 );
 	t.strictEqual( v, 4.0, 'returns expected value' );
 
 	t.end();

From 4fbccddc5546de84ef3f6dff32178e8c1e98eedb Mon Sep 17 00:00:00 2001
From: Dhruv/ <154677013+DhruvArvindSingh@users.noreply.github.com>
Date: Fri, 3 Jan 2025 04:04:01 +0530
Subject: [PATCH 26/87] refactor: update `stats/base/sstdevtk` native addon
 from C++ to C

PR-URL: https://github.com/stdlib-js/stdlib/pull/4484
Reviewed-by: Athan Reines <kgryte@gmail.com>
---
 .../@stdlib/stats/base/sstdevtk/include.gypi  |   2 +-
 .../@stdlib/stats/base/sstdevtk/manifest.json |  43 +++++-
 .../@stdlib/stats/base/sstdevtk/src/addon.c   |  45 ++++++
 .../@stdlib/stats/base/sstdevtk/src/addon.cpp | 130 ------------------
 4 files changed, 88 insertions(+), 132 deletions(-)
 create mode 100644 lib/node_modules/@stdlib/stats/base/sstdevtk/src/addon.c
 delete mode 100644 lib/node_modules/@stdlib/stats/base/sstdevtk/src/addon.cpp

diff --git a/lib/node_modules/@stdlib/stats/base/sstdevtk/include.gypi b/lib/node_modules/@stdlib/stats/base/sstdevtk/include.gypi
index 868c5c12e852..26476a8c2655 100644
--- a/lib/node_modules/@stdlib/stats/base/sstdevtk/include.gypi
+++ b/lib/node_modules/@stdlib/stats/base/sstdevtk/include.gypi
@@ -36,7 +36,7 @@
 
     # Source files:
     'src_files': [
-      '<(src_dir)/addon.cpp',
+      '<(src_dir)/addon.c',
       '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).src; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
     ],
 
diff --git a/lib/node_modules/@stdlib/stats/base/sstdevtk/manifest.json b/lib/node_modules/@stdlib/stats/base/sstdevtk/manifest.json
index 52ce8a7859a2..1358a6561b45 100644
--- a/lib/node_modules/@stdlib/stats/base/sstdevtk/manifest.json
+++ b/lib/node_modules/@stdlib/stats/base/sstdevtk/manifest.json
@@ -1,5 +1,7 @@
 {
-  "options": {},
+  "options": {
+    "task": "build"
+  },
   "fields": [
     {
       "field": "src",
@@ -24,6 +26,45 @@
   ],
   "confs": [
     {
+      "task": "build",
+      "src": [
+        "./src/sstdevtk.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [
+        "-lm"
+      ],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/napi/export",
+        "@stdlib/napi/argv",
+        "@stdlib/napi/argv-int64",
+        "@stdlib/napi/argv-float",
+        "@stdlib/napi/argv-strided-float32array",
+        "@stdlib/stats/base/svariancetk",
+        "@stdlib/napi/create-double"
+      ]
+    },
+    {
+      "task": "benchmark",
+      "src": [
+        "./src/sstdevtk.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [
+        "-lm"
+      ],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/stats/base/svariancetk"
+      ]
+    },
+    {
+      "task": "examples",
       "src": [
         "./src/sstdevtk.c"
       ],
diff --git a/lib/node_modules/@stdlib/stats/base/sstdevtk/src/addon.c b/lib/node_modules/@stdlib/stats/base/sstdevtk/src/addon.c
new file mode 100644
index 000000000000..73b792006d36
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/sstdevtk/src/addon.c
@@ -0,0 +1,45 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/sstdevtk.h"
+#include "stdlib/napi/export.h"
+#include "stdlib/napi/argv.h"
+#include "stdlib/napi/argv_int64.h"
+#include "stdlib/napi/argv_float.h"
+#include "stdlib/napi/argv_strided_float32array.h"
+#include "stdlib/napi/create_double.h"
+#include <node_api.h>
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 4 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_FLOAT( env, correction, argv, 1 );
+	STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 2 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_sstdevtk( N, correction, X, stride ), v );
+	return v;
+}
+
+STDLIB_NAPI_MODULE_EXPORT_FCN( addon )
diff --git a/lib/node_modules/@stdlib/stats/base/sstdevtk/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/sstdevtk/src/addon.cpp
deleted file mode 100644
index e5cf7ae08a37..000000000000
--- a/lib/node_modules/@stdlib/stats/base/sstdevtk/src/addon.cpp
+++ /dev/null
@@ -1,130 +0,0 @@
-/**
-* @license Apache-2.0
-*
-* Copyright (c) 2020 The Stdlib Authors.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-*    http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-
-#include "stdlib/stats/base/sstdevtk.h"
-#include <node_api.h>
-#include <stdint.h>
-#include <stdlib.h>
-#include <stdbool.h>
-#include <assert.h>
-
-/**
-* Add-on namespace.
-*/
-namespace stdlib_stats_base_sstdevtk {
-
-	/**
-	* Computes the standard deviation of a single-precision floating-point strided array using a one-pass textbook algorithm.
-	*
-	* ## Notes
-	*
-	* -   When called from JavaScript, the function expects four arguments:
-	*
-	*     -   `N`: number of indexed elements
-	*     -   `correction`: degrees of freedom adjustment
-	*     -   `X`: input array
-	*     -   `stride`: stride length
-	*/
-	napi_value node_sstdevtk( napi_env env, napi_callback_info info ) {
-		napi_status status;
-
-		size_t argc = 4;
-		napi_value argv[ 4 ];
-		status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr );
-		assert( status == napi_ok );
-
-		if ( argc < 4 ) {
-			napi_throw_error( env, nullptr, "invalid invocation. Must provide 4 arguments." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype0;
-		status = napi_typeof( env, argv[ 0 ], &vtype0 );
-		assert( status == napi_ok );
-		if ( vtype0 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype1;
-		status = napi_typeof( env, argv[ 1 ], &vtype1 );
-		assert( status == napi_ok );
-		if ( vtype1 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." );
-			return nullptr;
-		}
-
-		bool res;
-		status = napi_is_typedarray( env, argv[ 2 ], &res );
-		assert( status == napi_ok );
-		if ( res == false ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype3;
-		status = napi_typeof( env, argv[ 3 ], &vtype3 );
-		assert( status == napi_ok );
-		if ( vtype3 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." );
-			return nullptr;
-		}
-
-		int64_t N;
-		status = napi_get_value_int64( env, argv[ 0 ], &N );
-		assert( status == napi_ok );
-
-		double correction;
-		status = napi_get_value_double( env, argv[ 1 ], &correction );
-		assert( status == napi_ok );
-
-		int64_t stride;
-		status = napi_get_value_int64( env, argv[ 3 ], &stride );
-		assert( status == napi_ok );
-
-		napi_typedarray_type vtype2;
-		size_t xlen;
-		void *X;
-		status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr );
-		assert( status == napi_ok );
-		if ( vtype2 != napi_float32_array ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." );
-			return nullptr;
-		}
-		if ( (N-1)*llabs(stride) >= (int64_t)xlen ) {
-			napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." );
-			return nullptr;
-		}
-
-		napi_value v;
-		status = napi_create_double( env, (double)stdlib_strided_sstdevtk( N, (float)correction, (float *)X, stride ), &v );
-		assert( status == napi_ok );
-
-		return v;
-	}
-
-	napi_value Init( napi_env env, napi_value exports ) {
-		napi_status status;
-		napi_value fcn;
-		status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_sstdevtk, NULL, &fcn );
-		assert( status == napi_ok );
-		return fcn;
-	}
-
-	NAPI_MODULE( NODE_GYP_MODULE_NAME, Init )
-} // end namespace stdlib_stats_base_sstdevtk

From 104495a9d8793023f9fc88b0a9f52851ad39854e Mon Sep 17 00:00:00 2001
From: Dhruv/ <154677013+DhruvArvindSingh@users.noreply.github.com>
Date: Fri, 3 Jan 2025 04:09:59 +0530
Subject: [PATCH 27/87] refactor: update `stats/base/snanstdevtk` native addon
 from C++ to C

PR-URL: https://github.com/stdlib-js/stdlib/pull/4474
Reviewed-by: Athan Reines <kgryte@gmail.com>
---
 .../stats/base/snanstdevtk/include.gypi       |   2 +-
 .../stats/base/snanstdevtk/manifest.json      |  43 +++++-
 .../stats/base/snanstdevtk/src/addon.c        |  45 ++++++
 .../stats/base/snanstdevtk/src/addon.cpp      | 130 ------------------
 4 files changed, 88 insertions(+), 132 deletions(-)
 create mode 100644 lib/node_modules/@stdlib/stats/base/snanstdevtk/src/addon.c
 delete mode 100644 lib/node_modules/@stdlib/stats/base/snanstdevtk/src/addon.cpp

diff --git a/lib/node_modules/@stdlib/stats/base/snanstdevtk/include.gypi b/lib/node_modules/@stdlib/stats/base/snanstdevtk/include.gypi
index 868c5c12e852..26476a8c2655 100644
--- a/lib/node_modules/@stdlib/stats/base/snanstdevtk/include.gypi
+++ b/lib/node_modules/@stdlib/stats/base/snanstdevtk/include.gypi
@@ -36,7 +36,7 @@
 
     # Source files:
     'src_files': [
-      '<(src_dir)/addon.cpp',
+      '<(src_dir)/addon.c',
       '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).src; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
     ],
 
diff --git a/lib/node_modules/@stdlib/stats/base/snanstdevtk/manifest.json b/lib/node_modules/@stdlib/stats/base/snanstdevtk/manifest.json
index 680e056bc510..54815a89aff3 100644
--- a/lib/node_modules/@stdlib/stats/base/snanstdevtk/manifest.json
+++ b/lib/node_modules/@stdlib/stats/base/snanstdevtk/manifest.json
@@ -1,5 +1,7 @@
 {
-  "options": {},
+  "options": {
+    "task": "build"
+  },
   "fields": [
     {
       "field": "src",
@@ -24,6 +26,45 @@
   ],
   "confs": [
     {
+      "task": "build",
+      "src": [
+        "./src/snanstdevtk.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [
+        "-lm"
+      ],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/napi/export",
+        "@stdlib/napi/argv",
+        "@stdlib/napi/argv-int64",
+        "@stdlib/napi/argv-float",
+        "@stdlib/napi/argv-strided-float32array",
+        "@stdlib/stats/base/snanvariancetk",
+        "@stdlib/napi/create-double"
+      ]
+    },
+    {
+      "task": "benchmark",
+      "src": [
+        "./src/snanstdevtk.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [
+        "-lm"
+      ],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/stats/base/snanvariancetk"
+      ]
+    },
+    {
+      "task": "examples",
       "src": [
         "./src/snanstdevtk.c"
       ],
diff --git a/lib/node_modules/@stdlib/stats/base/snanstdevtk/src/addon.c b/lib/node_modules/@stdlib/stats/base/snanstdevtk/src/addon.c
new file mode 100644
index 000000000000..f84960d49db4
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/snanstdevtk/src/addon.c
@@ -0,0 +1,45 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/snanstdevtk.h"
+#include "stdlib/napi/export.h"
+#include "stdlib/napi/argv.h"
+#include "stdlib/napi/argv_int64.h"
+#include "stdlib/napi/argv_float.h"
+#include "stdlib/napi/argv_strided_float32array.h"
+#include "stdlib/napi/create_double.h"
+#include <node_api.h>
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 4 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_FLOAT( env, correction, argv, 1 );
+	STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 2 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_snanstdevtk( N, correction, X, stride ), v );
+	return v;
+}
+
+STDLIB_NAPI_MODULE_EXPORT_FCN( addon )
diff --git a/lib/node_modules/@stdlib/stats/base/snanstdevtk/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/snanstdevtk/src/addon.cpp
deleted file mode 100644
index 0b8b81775319..000000000000
--- a/lib/node_modules/@stdlib/stats/base/snanstdevtk/src/addon.cpp
+++ /dev/null
@@ -1,130 +0,0 @@
-/**
-* @license Apache-2.0
-*
-* Copyright (c) 2020 The Stdlib Authors.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-*    http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-
-#include "stdlib/stats/base/snanstdevtk.h"
-#include <node_api.h>
-#include <stdint.h>
-#include <stdlib.h>
-#include <stdbool.h>
-#include <assert.h>
-
-/**
-* Add-on namespace.
-*/
-namespace stdlib_stats_base_snanstdevtk {
-
-	/**
-	* Computes the standard deviation of a single-precision floating-point strided array ignoring `NaN` values and using a one-pass textbook algorithm.
-	*
-	* ## Notes
-	*
-	* -   When called from JavaScript, the function expects four arguments:
-	*
-	*     -   `N`: number of indexed elements
-	*     -   `correction`: degrees of freedom adjustment
-	*     -   `X`: input array
-	*     -   `stride`: stride length
-	*/
-	napi_value node_snanstdevtk( napi_env env, napi_callback_info info ) {
-		napi_status status;
-
-		size_t argc = 4;
-		napi_value argv[ 4 ];
-		status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr );
-		assert( status == napi_ok );
-
-		if ( argc < 4 ) {
-			napi_throw_error( env, nullptr, "invalid invocation. Must provide 4 arguments." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype0;
-		status = napi_typeof( env, argv[ 0 ], &vtype0 );
-		assert( status == napi_ok );
-		if ( vtype0 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype1;
-		status = napi_typeof( env, argv[ 1 ], &vtype1 );
-		assert( status == napi_ok );
-		if ( vtype1 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." );
-			return nullptr;
-		}
-
-		bool res;
-		status = napi_is_typedarray( env, argv[ 2 ], &res );
-		assert( status == napi_ok );
-		if ( res == false ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype3;
-		status = napi_typeof( env, argv[ 3 ], &vtype3 );
-		assert( status == napi_ok );
-		if ( vtype3 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." );
-			return nullptr;
-		}
-
-		int64_t N;
-		status = napi_get_value_int64( env, argv[ 0 ], &N );
-		assert( status == napi_ok );
-
-		double correction;
-		status = napi_get_value_double( env, argv[ 1 ], &correction );
-		assert( status == napi_ok );
-
-		int64_t stride;
-		status = napi_get_value_int64( env, argv[ 3 ], &stride );
-		assert( status == napi_ok );
-
-		napi_typedarray_type vtype2;
-		size_t xlen;
-		void *X;
-		status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr );
-		assert( status == napi_ok );
-		if ( vtype2 != napi_float32_array ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." );
-			return nullptr;
-		}
-		if ( (N-1)*llabs(stride) >= (int64_t)xlen ) {
-			napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." );
-			return nullptr;
-		}
-
-		napi_value v;
-		status = napi_create_double( env, (double)stdlib_strided_snanstdevtk( N, (float)correction, (float *)X, stride ), &v );
-		assert( status == napi_ok );
-
-		return v;
-	}
-
-	napi_value Init( napi_env env, napi_value exports ) {
-		napi_status status;
-		napi_value fcn;
-		status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_snanstdevtk, NULL, &fcn );
-		assert( status == napi_ok );
-		return fcn;
-	}
-
-	NAPI_MODULE( NODE_GYP_MODULE_NAME, Init )
-} // end namespace stdlib_stats_base_snanstdevtk

From c76131857bbd5531cce6da70b44c18ffec7cb8d6 Mon Sep 17 00:00:00 2001
From: Dhruv/ <154677013+DhruvArvindSingh@users.noreply.github.com>
Date: Fri, 3 Jan 2025 04:13:44 +0530
Subject: [PATCH 28/87] refactor: update  `stats/base/snanstdevpn` native addon
 from C++ to C

PR-URL: https://github.com/stdlib-js/stdlib/pull/4475
Reviewed-by: Athan Reines <kgryte@gmail.com>
---
 .../stats/base/snanstdevpn/include.gypi       |   2 +-
 .../stats/base/snanstdevpn/manifest.json      |  43 +++++-
 .../stats/base/snanstdevpn/src/addon.c        |  45 ++++++
 .../stats/base/snanstdevpn/src/addon.cpp      | 130 ------------------
 4 files changed, 88 insertions(+), 132 deletions(-)
 create mode 100644 lib/node_modules/@stdlib/stats/base/snanstdevpn/src/addon.c
 delete mode 100644 lib/node_modules/@stdlib/stats/base/snanstdevpn/src/addon.cpp

diff --git a/lib/node_modules/@stdlib/stats/base/snanstdevpn/include.gypi b/lib/node_modules/@stdlib/stats/base/snanstdevpn/include.gypi
index 868c5c12e852..26476a8c2655 100644
--- a/lib/node_modules/@stdlib/stats/base/snanstdevpn/include.gypi
+++ b/lib/node_modules/@stdlib/stats/base/snanstdevpn/include.gypi
@@ -36,7 +36,7 @@
 
     # Source files:
     'src_files': [
-      '<(src_dir)/addon.cpp',
+      '<(src_dir)/addon.c',
       '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).src; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
     ],
 
diff --git a/lib/node_modules/@stdlib/stats/base/snanstdevpn/manifest.json b/lib/node_modules/@stdlib/stats/base/snanstdevpn/manifest.json
index 59f1de07b4c8..1b07aff82ef9 100644
--- a/lib/node_modules/@stdlib/stats/base/snanstdevpn/manifest.json
+++ b/lib/node_modules/@stdlib/stats/base/snanstdevpn/manifest.json
@@ -1,5 +1,7 @@
 {
-  "options": {},
+  "options": {
+    "task": "build"
+  },
   "fields": [
     {
       "field": "src",
@@ -24,6 +26,45 @@
   ],
   "confs": [
     {
+      "task": "build",
+      "src": [
+        "./src/snanstdevpn.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [
+        "-lm"
+      ],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/napi/export",
+        "@stdlib/napi/argv",
+        "@stdlib/napi/argv-int64",
+        "@stdlib/napi/argv-float",
+        "@stdlib/napi/argv-strided-float32array",
+        "@stdlib/stats/base/snanvariancepn",
+        "@stdlib/napi/create-double"
+      ]
+    },
+    {
+      "task": "benchmark",
+      "src": [
+        "./src/snanstdevpn.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [
+        "-lm"
+      ],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/stats/base/snanvariancepn"
+      ]
+    },
+    {
+      "task": "examples",
       "src": [
         "./src/snanstdevpn.c"
       ],
diff --git a/lib/node_modules/@stdlib/stats/base/snanstdevpn/src/addon.c b/lib/node_modules/@stdlib/stats/base/snanstdevpn/src/addon.c
new file mode 100644
index 000000000000..f8aa0f5c0a26
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/snanstdevpn/src/addon.c
@@ -0,0 +1,45 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/snanstdevpn.h"
+#include "stdlib/napi/export.h"
+#include "stdlib/napi/argv.h"
+#include "stdlib/napi/argv_int64.h"
+#include "stdlib/napi/argv_float.h"
+#include "stdlib/napi/argv_strided_float32array.h"
+#include "stdlib/napi/create_double.h"
+#include <node_api.h>
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 4 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_FLOAT( env, correction, argv, 1 );
+	STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 2 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_snanstdevpn( N, correction, X, stride ), v );
+	return v;
+}
+
+STDLIB_NAPI_MODULE_EXPORT_FCN( addon )
diff --git a/lib/node_modules/@stdlib/stats/base/snanstdevpn/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/snanstdevpn/src/addon.cpp
deleted file mode 100644
index 19a75e25bb53..000000000000
--- a/lib/node_modules/@stdlib/stats/base/snanstdevpn/src/addon.cpp
+++ /dev/null
@@ -1,130 +0,0 @@
-/**
-* @license Apache-2.0
-*
-* Copyright (c) 2020 The Stdlib Authors.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-*    http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-
-#include "stdlib/stats/base/snanstdevpn.h"
-#include <node_api.h>
-#include <stdint.h>
-#include <stdlib.h>
-#include <stdbool.h>
-#include <assert.h>
-
-/**
-* Add-on namespace.
-*/
-namespace stdlib_stats_base_snanstdevpn {
-
-	/**
-	* Computes the standard deviation of a single-precision floating-point strided array ignoring `NaN` values and using a two-pass algorithm.
-	*
-	* ## Notes
-	*
-	* -   When called from JavaScript, the function expects four arguments:
-	*
-	*     -   `N`: number of indexed elements
-	*     -   `correction`: degrees of freedom adjustment
-	*     -   `X`: input array
-	*     -   `stride`: stride length
-	*/
-	napi_value node_snanstdevpn( napi_env env, napi_callback_info info ) {
-		napi_status status;
-
-		size_t argc = 4;
-		napi_value argv[ 4 ];
-		status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr );
-		assert( status == napi_ok );
-
-		if ( argc < 4 ) {
-			napi_throw_error( env, nullptr, "invalid invocation. Must provide 4 arguments." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype0;
-		status = napi_typeof( env, argv[ 0 ], &vtype0 );
-		assert( status == napi_ok );
-		if ( vtype0 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype1;
-		status = napi_typeof( env, argv[ 1 ], &vtype1 );
-		assert( status == napi_ok );
-		if ( vtype1 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." );
-			return nullptr;
-		}
-
-		bool res;
-		status = napi_is_typedarray( env, argv[ 2 ], &res );
-		assert( status == napi_ok );
-		if ( res == false ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype3;
-		status = napi_typeof( env, argv[ 3 ], &vtype3 );
-		assert( status == napi_ok );
-		if ( vtype3 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." );
-			return nullptr;
-		}
-
-		int64_t N;
-		status = napi_get_value_int64( env, argv[ 0 ], &N );
-		assert( status == napi_ok );
-
-		double correction;
-		status = napi_get_value_double( env, argv[ 1 ], &correction );
-		assert( status == napi_ok );
-
-		int64_t stride;
-		status = napi_get_value_int64( env, argv[ 3 ], &stride );
-		assert( status == napi_ok );
-
-		napi_typedarray_type vtype2;
-		size_t xlen;
-		void *X;
-		status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr );
-		assert( status == napi_ok );
-		if ( vtype2 != napi_float32_array ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." );
-			return nullptr;
-		}
-		if ( (N-1)*llabs(stride) >= (int64_t)xlen ) {
-			napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." );
-			return nullptr;
-		}
-
-		napi_value v;
-		status = napi_create_double( env, (double)stdlib_strided_snanstdevpn( N, (float)correction, (float *)X, stride ), &v );
-		assert( status == napi_ok );
-
-		return v;
-	}
-
-	napi_value Init( napi_env env, napi_value exports ) {
-		napi_status status;
-		napi_value fcn;
-		status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_snanstdevpn, NULL, &fcn );
-		assert( status == napi_ok );
-		return fcn;
-	}
-
-	NAPI_MODULE( NODE_GYP_MODULE_NAME, Init )
-} // end namespace stdlib_stats_base_snanstdevpn

From 0ec7b9b962c5014c0e7ad5908100af3736f940d0 Mon Sep 17 00:00:00 2001
From: Dhruv/ <154677013+DhruvArvindSingh@users.noreply.github.com>
Date: Fri, 3 Jan 2025 04:15:17 +0530
Subject: [PATCH 29/87] refactor: update `stats/base/snanstdevyc` native addon
 from C++ to C

PR-URL: https://github.com/stdlib-js/stdlib/pull/4472
Reviewed-by: Athan Reines <kgryte@gmail.com>
---
 .../stats/base/snanstdevyc/include.gypi       |   2 +-
 .../stats/base/snanstdevyc/manifest.json      |  43 +++++-
 .../stats/base/snanstdevyc/src/addon.c        |  45 ++++++
 .../stats/base/snanstdevyc/src/addon.cpp      | 130 ------------------
 4 files changed, 88 insertions(+), 132 deletions(-)
 create mode 100644 lib/node_modules/@stdlib/stats/base/snanstdevyc/src/addon.c
 delete mode 100644 lib/node_modules/@stdlib/stats/base/snanstdevyc/src/addon.cpp

diff --git a/lib/node_modules/@stdlib/stats/base/snanstdevyc/include.gypi b/lib/node_modules/@stdlib/stats/base/snanstdevyc/include.gypi
index 868c5c12e852..26476a8c2655 100644
--- a/lib/node_modules/@stdlib/stats/base/snanstdevyc/include.gypi
+++ b/lib/node_modules/@stdlib/stats/base/snanstdevyc/include.gypi
@@ -36,7 +36,7 @@
 
     # Source files:
     'src_files': [
-      '<(src_dir)/addon.cpp',
+      '<(src_dir)/addon.c',
       '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).src; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
     ],
 
diff --git a/lib/node_modules/@stdlib/stats/base/snanstdevyc/manifest.json b/lib/node_modules/@stdlib/stats/base/snanstdevyc/manifest.json
index aaa633ca7b1d..ccd693a96a58 100644
--- a/lib/node_modules/@stdlib/stats/base/snanstdevyc/manifest.json
+++ b/lib/node_modules/@stdlib/stats/base/snanstdevyc/manifest.json
@@ -1,5 +1,7 @@
 {
-  "options": {},
+  "options": {
+    "task": "build"
+  },
   "fields": [
     {
       "field": "src",
@@ -24,6 +26,45 @@
   ],
   "confs": [
     {
+      "task": "build",
+      "src": [
+        "./src/snanstdevyc.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [
+        "-lm"
+      ],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/napi/export",
+        "@stdlib/napi/argv",
+        "@stdlib/napi/argv-int64",
+        "@stdlib/napi/argv-float",
+        "@stdlib/napi/argv-strided-float32array",
+        "@stdlib/stats/base/snanvarianceyc",
+        "@stdlib/napi/create-double"
+      ]
+    },
+    {
+      "task": "benchmark",
+      "src": [
+        "./src/snanstdevyc.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [
+        "-lm"
+      ],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/stats/base/snanvarianceyc"
+      ]
+    },
+    {
+      "task": "examples",
       "src": [
         "./src/snanstdevyc.c"
       ],
diff --git a/lib/node_modules/@stdlib/stats/base/snanstdevyc/src/addon.c b/lib/node_modules/@stdlib/stats/base/snanstdevyc/src/addon.c
new file mode 100644
index 000000000000..e35b098687ff
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/snanstdevyc/src/addon.c
@@ -0,0 +1,45 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/snanstdevyc.h"
+#include "stdlib/napi/export.h"
+#include "stdlib/napi/argv.h"
+#include "stdlib/napi/argv_int64.h"
+#include "stdlib/napi/argv_float.h"
+#include "stdlib/napi/argv_strided_float32array.h"
+#include "stdlib/napi/create_double.h"
+#include <node_api.h>
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 4 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_FLOAT( env, correction, argv, 1 );
+	STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 2 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_snanstdevyc( N, correction, X, stride ), v );
+	return v;
+}
+
+STDLIB_NAPI_MODULE_EXPORT_FCN( addon )
diff --git a/lib/node_modules/@stdlib/stats/base/snanstdevyc/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/snanstdevyc/src/addon.cpp
deleted file mode 100644
index ecaf47683a53..000000000000
--- a/lib/node_modules/@stdlib/stats/base/snanstdevyc/src/addon.cpp
+++ /dev/null
@@ -1,130 +0,0 @@
-/**
-* @license Apache-2.0
-*
-* Copyright (c) 2020 The Stdlib Authors.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-*    http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-
-#include "stdlib/stats/base/snanstdevyc.h"
-#include <node_api.h>
-#include <stdint.h>
-#include <stdlib.h>
-#include <stdbool.h>
-#include <assert.h>
-
-/**
-* Add-on namespace.
-*/
-namespace stdlib_stats_base_snanstdevyc {
-
-	/**
-	* Computes the standard deviation of a single-precision floating-point strided array ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and Cramer.
-	*
-	* ## Notes
-	*
-	* -   When called from JavaScript, the function expects four arguments:
-	*
-	*     -   `N`: number of indexed elements
-	*     -   `correction`: degrees of freedom adjustment
-	*     -   `X`: input array
-	*     -   `stride`: stride length
-	*/
-	napi_value node_snanstdevyc( napi_env env, napi_callback_info info ) {
-		napi_status status;
-
-		size_t argc = 4;
-		napi_value argv[ 4 ];
-		status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr );
-		assert( status == napi_ok );
-
-		if ( argc < 4 ) {
-			napi_throw_error( env, nullptr, "invalid invocation. Must provide 4 arguments." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype0;
-		status = napi_typeof( env, argv[ 0 ], &vtype0 );
-		assert( status == napi_ok );
-		if ( vtype0 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype1;
-		status = napi_typeof( env, argv[ 1 ], &vtype1 );
-		assert( status == napi_ok );
-		if ( vtype1 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." );
-			return nullptr;
-		}
-
-		bool res;
-		status = napi_is_typedarray( env, argv[ 2 ], &res );
-		assert( status == napi_ok );
-		if ( res == false ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype3;
-		status = napi_typeof( env, argv[ 3 ], &vtype3 );
-		assert( status == napi_ok );
-		if ( vtype3 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." );
-			return nullptr;
-		}
-
-		int64_t N;
-		status = napi_get_value_int64( env, argv[ 0 ], &N );
-		assert( status == napi_ok );
-
-		double correction;
-		status = napi_get_value_double( env, argv[ 1 ], &correction );
-		assert( status == napi_ok );
-
-		int64_t stride;
-		status = napi_get_value_int64( env, argv[ 3 ], &stride );
-		assert( status == napi_ok );
-
-		napi_typedarray_type vtype2;
-		size_t xlen;
-		void *X;
-		status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr );
-		assert( status == napi_ok );
-		if ( vtype2 != napi_float32_array ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." );
-			return nullptr;
-		}
-		if ( (N-1)*llabs(stride) >= (int64_t)xlen ) {
-			napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." );
-			return nullptr;
-		}
-
-		napi_value v;
-		status = napi_create_double( env, (double)stdlib_strided_snanstdevyc( N, (float)correction, (float *)X, stride ), &v );
-		assert( status == napi_ok );
-
-		return v;
-	}
-
-	napi_value Init( napi_env env, napi_value exports ) {
-		napi_status status;
-		napi_value fcn;
-		status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_snanstdevyc, NULL, &fcn );
-		assert( status == napi_ok );
-		return fcn;
-	}
-
-	NAPI_MODULE( NODE_GYP_MODULE_NAME, Init )
-} // end namespace stdlib_stats_base_snanstdevyc

From 156bc2f100ff204c4e61f8e1884b116c8fee7c52 Mon Sep 17 00:00:00 2001
From: Dhruv/ <154677013+DhruvArvindSingh@users.noreply.github.com>
Date: Fri, 3 Jan 2025 04:18:03 +0530
Subject: [PATCH 30/87] refactor: update `stats/base/snanvariancech` native
 addon from C++ to C

PR-URL: https://github.com/stdlib-js/stdlib/pull/4483
Co-authored-by: Athan Reines <kgryte@gmail.com>
Reviewed-by: Athan Reines <kgryte@gmail.com>
---
 .../stats/base/snanvariancech/include.gypi    |   2 +-
 .../stats/base/snanvariancech/manifest.json   |  40 +++++-
 .../stats/base/snanvariancech/src/addon.c     |  45 ++++++
 .../stats/base/snanvariancech/src/addon.cpp   | 130 ------------------
 4 files changed, 85 insertions(+), 132 deletions(-)
 create mode 100644 lib/node_modules/@stdlib/stats/base/snanvariancech/src/addon.c
 delete mode 100644 lib/node_modules/@stdlib/stats/base/snanvariancech/src/addon.cpp

diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancech/include.gypi b/lib/node_modules/@stdlib/stats/base/snanvariancech/include.gypi
index 868c5c12e852..26476a8c2655 100644
--- a/lib/node_modules/@stdlib/stats/base/snanvariancech/include.gypi
+++ b/lib/node_modules/@stdlib/stats/base/snanvariancech/include.gypi
@@ -36,7 +36,7 @@
 
     # Source files:
     'src_files': [
-      '<(src_dir)/addon.cpp',
+      '<(src_dir)/addon.c',
       '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).src; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
     ],
 
diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancech/manifest.json b/lib/node_modules/@stdlib/stats/base/snanvariancech/manifest.json
index d61e6247e082..63c353bfcf26 100644
--- a/lib/node_modules/@stdlib/stats/base/snanvariancech/manifest.json
+++ b/lib/node_modules/@stdlib/stats/base/snanvariancech/manifest.json
@@ -1,5 +1,7 @@
 {
-  "options": {},
+  "options": {
+    "task": "build"
+  },
   "fields": [
     {
       "field": "src",
@@ -24,6 +26,42 @@
   ],
   "confs": [
     {
+      "task": "build",
+      "src": [
+        "./src/snanvariancech.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [
+        "-lm"
+      ],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/napi/export",
+        "@stdlib/napi/argv",
+        "@stdlib/napi/argv-int64",
+        "@stdlib/napi/argv-float",
+        "@stdlib/napi/argv-strided-float32array",
+        "@stdlib/napi/create-double"
+      ]
+    },
+    {
+      "task": "benchmark",
+      "src": [
+        "./src/snanvariancech.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [
+        "-lm"
+      ],
+      "libpath": [],
+      "dependencies": []
+    },
+    {
+      "task": "examples",
       "src": [
         "./src/snanvariancech.c"
       ],
diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancech/src/addon.c b/lib/node_modules/@stdlib/stats/base/snanvariancech/src/addon.c
new file mode 100644
index 000000000000..2f7d51a8be74
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/snanvariancech/src/addon.c
@@ -0,0 +1,45 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/snanvariancech.h"
+#include "stdlib/napi/export.h"
+#include "stdlib/napi/argv.h"
+#include "stdlib/napi/argv_int64.h"
+#include "stdlib/napi/argv_float.h"
+#include "stdlib/napi/argv_strided_float32array.h"
+#include "stdlib/napi/create_double.h"
+#include <node_api.h>
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 4 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_FLOAT( env, correction, argv, 1 );
+	STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 2 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_snanvariancech( N, correction, X, stride ), v );
+	return v;
+}
+
+STDLIB_NAPI_MODULE_EXPORT_FCN( addon )
diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancech/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/snanvariancech/src/addon.cpp
deleted file mode 100644
index 9a88d0e0c69f..000000000000
--- a/lib/node_modules/@stdlib/stats/base/snanvariancech/src/addon.cpp
+++ /dev/null
@@ -1,130 +0,0 @@
-/**
-* @license Apache-2.0
-*
-* Copyright (c) 2020 The Stdlib Authors.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-*    http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-
-#include "stdlib/stats/base/snanvariancech.h"
-#include <node_api.h>
-#include <stdint.h>
-#include <stdlib.h>
-#include <stdbool.h>
-#include <assert.h>
-
-/**
-* Add-on namespace.
-*/
-namespace stdlib_stats_base_snanvariancech {
-
-	/**
-	* Computes the variance of a single-precision floating-point strided array ignoring `NaN` values and using a one-pass trial mean algorithm.
-	*
-	* ## Notes
-	*
-	* -   When called from JavaScript, the function expects four arguments:
-	*
-	*     -   `N`: number of indexed elements
-	*     -   `correction`: degrees of freedom adjustment
-	*     -   `X`: input array
-	*     -   `stride`: stride length
-	*/
-	napi_value node_snanvariancech( napi_env env, napi_callback_info info ) {
-		napi_status status;
-
-		size_t argc = 4;
-		napi_value argv[ 4 ];
-		status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr );
-		assert( status == napi_ok );
-
-		if ( argc < 4 ) {
-			napi_throw_error( env, nullptr, "invalid invocation. Must provide 4 arguments." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype0;
-		status = napi_typeof( env, argv[ 0 ], &vtype0 );
-		assert( status == napi_ok );
-		if ( vtype0 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype1;
-		status = napi_typeof( env, argv[ 1 ], &vtype1 );
-		assert( status == napi_ok );
-		if ( vtype1 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." );
-			return nullptr;
-		}
-
-		bool res;
-		status = napi_is_typedarray( env, argv[ 2 ], &res );
-		assert( status == napi_ok );
-		if ( res == false ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype3;
-		status = napi_typeof( env, argv[ 3 ], &vtype3 );
-		assert( status == napi_ok );
-		if ( vtype3 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." );
-			return nullptr;
-		}
-
-		int64_t N;
-		status = napi_get_value_int64( env, argv[ 0 ], &N );
-		assert( status == napi_ok );
-
-		double correction;
-		status = napi_get_value_double( env, argv[ 1 ], &correction );
-		assert( status == napi_ok );
-
-		int64_t stride;
-		status = napi_get_value_int64( env, argv[ 3 ], &stride );
-		assert( status == napi_ok );
-
-		napi_typedarray_type vtype2;
-		size_t xlen;
-		void *X;
-		status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr );
-		assert( status == napi_ok );
-		if ( vtype2 != napi_float32_array ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." );
-			return nullptr;
-		}
-		if ( (N-1)*llabs(stride) >= (int64_t)xlen ) {
-			napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." );
-			return nullptr;
-		}
-
-		napi_value v;
-		status = napi_create_double( env, (double)stdlib_strided_snanvariancech( N, (float)correction, (float *)X, stride ), &v );
-		assert( status == napi_ok );
-
-		return v;
-	}
-
-	napi_value Init( napi_env env, napi_value exports ) {
-		napi_status status;
-		napi_value fcn;
-		status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_snanvariancech, NULL, &fcn );
-		assert( status == napi_ok );
-		return fcn;
-	}
-
-	NAPI_MODULE( NODE_GYP_MODULE_NAME, Init )
-} // end namespace stdlib_stats_base_snanvariancech

From f1070e3303d3a09e127ce0c431858b042ccf5576 Mon Sep 17 00:00:00 2001
From: Aayush Khanna <96649223+aayush0325@users.noreply.github.com>
Date: Fri, 3 Jan 2025 05:33:37 +0530
Subject: [PATCH 31/87] feat: add C ndarray interface and refactor
 implementation for `stats/base/dcumin`

PR-URL: https://github.com/stdlib-js/stdlib/pull/4144
Co-authored-by: Athan Reines <kgryte@gmail.com>
Reviewed-by: Athan Reines <kgryte@gmail.com>
---
 .../@stdlib/stats/base/dcumin/README.md       | 151 ++++++++++++++++--
 .../stats/base/dcumin/benchmark/benchmark.js  |  20 +--
 .../base/dcumin/benchmark/benchmark.native.js |  16 +-
 .../dcumin/benchmark/benchmark.ndarray.js     |  20 +--
 .../benchmark/benchmark.ndarray.native.js     |  16 +-
 .../dcumin/benchmark/c/benchmark.length.c     |  49 +++++-
 .../@stdlib/stats/base/dcumin/docs/repl.txt   |  22 ++-
 .../stats/base/dcumin/examples/c/example.c    |  14 +-
 .../stats/base/dcumin/examples/index.js       |  17 +-
 .../dcumin/include/stdlib/stats/base/dcumin.h |   9 +-
 .../@stdlib/stats/base/dcumin/lib/dcumin.js   |  56 +------
 .../stats/base/dcumin/lib/dcumin.native.js    |   3 +-
 .../@stdlib/stats/base/dcumin/lib/index.js    |   7 +-
 .../@stdlib/stats/base/dcumin/lib/ndarray.js  |   4 +-
 .../stats/base/dcumin/lib/ndarray.native.js   |  19 +--
 .../@stdlib/stats/base/dcumin/manifest.json   |  46 ++++--
 .../@stdlib/stats/base/dcumin/src/addon.c     |  22 ++-
 .../base/dcumin/src/{dcumin.c => main.c}      |  41 +++--
 .../stats/base/dcumin/test/test.dcumin.js     |  22 +--
 .../base/dcumin/test/test.dcumin.native.js    |  22 +--
 .../stats/base/dcumin/test/test.ndarray.js    |  25 +--
 .../base/dcumin/test/test.ndarray.native.js   |  25 +--
 22 files changed, 360 insertions(+), 266 deletions(-)
 rename lib/node_modules/@stdlib/stats/base/dcumin/src/{dcumin.c => main.c} (58%)

diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/README.md b/lib/node_modules/@stdlib/stats/base/dcumin/README.md
index 3439c8de3e3f..09feee29d6da 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumin/README.md
+++ b/lib/node_modules/@stdlib/stats/base/dcumin/README.md
@@ -54,11 +54,11 @@ The function has the following parameters:
 
 -   **N**: number of indexed elements.
 -   **x**: input [`Float64Array`][@stdlib/array/float64].
--   **strideX**: index increment for `x`.
+-   **strideX**: stride length for `x`.
 -   **y**: output [`Float64Array`][@stdlib/array/float64].
--   **strideY**: index increment for `y`.
+-   **strideY**: stride length for `y`.
 
-The `N` and `stride` parameters determine which elements in `x` and `y` are accessed at runtime. For example, to compute the cumulative minimum of every other element in `x`,
+The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the cumulative minimum of every other element in `x`,
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
@@ -108,7 +108,7 @@ The function has the following additional parameters:
 -   **offsetX**: starting index for `x`.
 -   **offsetY**: starting index for `y`.
 
-While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, `offsetX` and `offsetY` parameters support indexing semantics based on a starting indices. For example, to calculate the cumulative minimum of every other value in `x` starting from the second value and to store in the last `N` elements of `y` starting from the last element
+While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on a starting indices. For example, to calculate the cumulative minimum of every other element in `x` starting from the second element and to store in the last `N` elements of `y` starting from the last element
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
@@ -141,21 +141,16 @@ dcumin.ndarray( 4, x, 2, 1, y, -1, y.length-1 );
 <!-- eslint no-undef: "error" -->
 
 ```javascript
-var randu = require( '@stdlib/random/base/randu' );
-var round = require( '@stdlib/math/base/special/round' );
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
 var Float64Array = require( '@stdlib/array/float64' );
 var dcumin = require( '@stdlib/stats/base/dcumin' );
 
-var y;
-var x;
-var i;
-
-x = new Float64Array( 10 );
-y = new Float64Array( x.length );
-for ( i = 0; i < x.length; i++ ) {
-    x[ i ] = round( randu()*100.0 );
-}
+var x = discreteUniform( 10, -50, 50, {
+    'dtype': 'float64'
+});
 console.log( x );
+
+var y = new Float64Array( x.length );
 console.log( y );
 
 dcumin( x.length, x, 1, y, -1 );
@@ -166,6 +161,132 @@ console.log( y );
 
 <!-- /.examples -->
 
+<!-- C interface documentation. -->
+
+* * *
+
+<section class="c">
+
+## C APIs
+
+<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<!-- C usage documentation. -->
+
+<section class="usage">
+
+### Usage
+
+```c
+#include "stdlib/stats/base/dcumin.h"
+```
+
+#### stdlib_strided_dcumin( N, \*X, strideX, \*Y, strideY )
+
+Computes the cumulative minimum of double-precision floating-point strided array elements.
+
+```c
+const double x[] = { 1.0, 2.0, -3.0, 4.0, -5.0, 6.0, 7.0, 8.0 };
+double y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 };
+
+stdlib_strided_dcumin( 4, x, 2, y, -2 );
+```
+
+The function accepts the following arguments:
+
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **X**: `[in] double*` input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+-   **Y**: `[out] double*` output array.
+-   **strideY**: `[in] CBLAS_INT` stride length for `Y`.
+
+```c
+void stdlib_strided_dcumin( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, double *Y, const CBLAS_INT strideY );
+```
+
+#### stdlib_strided_dcumin_ndarray(N, \*X, strideX, offsetX, \*Y, strideY, offsetY )
+
+Computes the cumulative minimum of double-precision floating-point strided array elements using alternative indexing semantics.
+
+```c
+const double x[] = { 1.0, 2.0, -3.0, 4.0, -5.0, 6.0, 7.0, 8.0 };
+double y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 };
+
+stdlib_strided_dcumin_ndarray( 4, x, 2, 0, y, -2, 0 );
+```
+
+The function accepts the following arguments:
+
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **X**: `[in] double*` input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+-   **offsetX**: `[in] CBLAS_INT` starting index for `X`.
+-   **Y**: `[out] double*` output array.
+-   **strideY**: `[in] CBLAS_INT` stride length for `Y`.
+-   **offsetY**: `[in] CBLAS_INT` starting index for `Y`.
+
+```c
+void stdlib_strided_dcumin_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, double *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY );
+```
+
+</section>
+
+<!-- /.usage -->
+
+<!-- C API usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="notes">
+
+</section>
+
+<!-- /.notes -->
+
+<!-- C API usage examples. -->
+
+<section class="examples">
+
+### Examples
+
+```c
+#include "stdlib/stats/base/dcumin.h"
+#include <stdio.h>
+
+int main( void ) {
+    // Create strided arrays:
+    const double x[] = { 1.0, 2.0, -3.0, 4.0, -5.0, 6.0, 7.0, 8.0 };
+    double y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 };
+
+    // Specify the number of elements:
+    const int N = 4;
+
+    // Specify stride lengths:
+    const int strideX = 2;
+    const int strideY = -2;
+
+    // Compute the cumulative minimum:
+    stdlib_strided_dcumin( N, x, strideX, y, strideY );
+
+    // Print the result:
+    for ( int i = 0; i < 8; i++ ) {
+        printf( "y[ %d ] = %lf\n", i, y[ i ] );
+    }
+}
+```
+
+</section>
+
+<!-- /.examples -->
+
+</section>
+
+<!-- /.c -->
+
 <section class="references">
 
 </section>
diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dcumin/benchmark/benchmark.js
index 1dcde9f45060..334eca929bf8 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumin/benchmark/benchmark.js
+++ b/lib/node_modules/@stdlib/stats/base/dcumin/benchmark/benchmark.js
@@ -21,7 +21,7 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/array/uniform' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
 var Float64Array = require( '@stdlib/array/float64' );
@@ -29,6 +29,13 @@ var pkg = require( './../package.json' ).name;
 var dcumin = require( './../lib/dcumin.js' );
 
 
+// VARIABLES //
+
+var options = {
+	'dtype': 'float64'
+};
+
+
 // FUNCTIONS //
 
 /**
@@ -39,15 +46,8 @@ var dcumin = require( './../lib/dcumin.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var y;
-	var x;
-	var i;
-
-	x = new Float64Array( len );
-	y = new Float64Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
+	var x = uniform( len, -10.0, 10.0, options );
+	var y = new Float64Array( len );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dcumin/benchmark/benchmark.native.js
index f63416764679..1e32c2356cde 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumin/benchmark/benchmark.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dcumin/benchmark/benchmark.native.js
@@ -22,7 +22,7 @@
 
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/array/uniform' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
 var Float64Array = require( '@stdlib/array/float64' );
@@ -36,6 +36,9 @@ var dcumin = tryRequire( resolve( __dirname, './../lib/dcumin.native.js' ) );
 var opts = {
 	'skip': ( dcumin instanceof Error )
 };
+var options = {
+	'dtype': 'float64'
+};
 
 
 // FUNCTIONS //
@@ -48,15 +51,8 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var y;
-	var i;
-
-	x = new Float64Array( len );
-	y = new Float64Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
+	var x = uniform( len, -10.0, 10.0, options );
+	var y = new Float64Array( len );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/dcumin/benchmark/benchmark.ndarray.js
index edb7e32a3470..3f097ae0f0c3 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumin/benchmark/benchmark.ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/dcumin/benchmark/benchmark.ndarray.js
@@ -21,7 +21,7 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/array/uniform' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
 var Float64Array = require( '@stdlib/array/float64' );
@@ -29,6 +29,13 @@ var pkg = require( './../package.json' ).name;
 var dcumin = require( './../lib/ndarray.js' );
 
 
+// VARIABLES //
+
+var options = {
+	'dtype': 'float64'
+};
+
+
 // FUNCTIONS //
 
 /**
@@ -39,15 +46,8 @@ var dcumin = require( './../lib/ndarray.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var y;
-	var i;
-
-	x = new Float64Array( len );
-	y = new Float64Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
+	var x = uniform( len, -10.0, 10.0, options );
+	var y = new Float64Array( len );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dcumin/benchmark/benchmark.ndarray.native.js
index 6045616a009f..954d6b0c8e9c 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumin/benchmark/benchmark.ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dcumin/benchmark/benchmark.ndarray.native.js
@@ -22,7 +22,7 @@
 
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/array/uniform' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
 var Float64Array = require( '@stdlib/array/float64' );
@@ -36,6 +36,9 @@ var dcumin = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) );
 var opts = {
 	'skip': ( dcumin instanceof Error )
 };
+var options = {
+	'dtype': 'float64'
+};
 
 
 // FUNCTIONS //
@@ -48,15 +51,8 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var y;
-	var i;
-
-	x = new Float64Array( len );
-	y = new Float64Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
+	var x = uniform( len, -10.0, 10.0, options );
+	var y = new Float64Array( len );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dcumin/benchmark/c/benchmark.length.c
index f890722d543c..542f7963e291 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumin/benchmark/c/benchmark.length.c
+++ b/lib/node_modules/@stdlib/stats/base/dcumin/benchmark/c/benchmark.length.c
@@ -94,7 +94,7 @@ static double rand_double( void ) {
 * @param len          array length
 * @return             elapsed time in seconds
 */
-static double benchmark( int iterations, int len ) {
+static double benchmark1( int iterations, int len ) {
 	double elapsed;
 	double x[ len ];
 	double y[ len ];
@@ -121,6 +121,40 @@ static double benchmark( int iterations, int len ) {
 	return elapsed;
 }
 
+/**
+* Runs a benchmark.
+*
+* @param iterations   number of iterations
+* @param len          array length
+* @return             elapsed time in seconds
+*/
+static double benchmark2( int iterations, int len ) {
+	double elapsed;
+	double x[ len ];
+	double y[ len ];
+	double t;
+	int i;
+
+	for ( i = 0; i < len; i++ ) {
+		x[ i ] = ( rand_double() * 20000.0 ) - 10000.0;
+		y[ i ] = 0.0;
+	}
+	t = tic();
+	for ( i = 0; i < iterations; i++ ) {
+		x[ 0 ] += 1.0;
+		stdlib_strided_dcumin_ndarray( len, x, 1, 0, y, 1, 0 );
+		if ( y[ 0 ] != y[ 0 ] ) {
+			printf( "should not return NaN\n" );
+			break;
+		}
+	}
+	elapsed = tic() - t;
+	if ( y[ len-1 ] != y[ len-1 ] ) {
+		printf( "should not return NaN\n" );
+	}
+	return elapsed;
+}
+
 /**
 * Main execution sequence.
 */
@@ -143,7 +177,18 @@ int main( void ) {
 		for ( j = 0; j < REPEATS; j++ ) {
 			count += 1;
 			printf( "# c::%s:len=%d\n", NAME, len );
-			elapsed = benchmark( iter, len );
+			elapsed = benchmark1( iter, len );
+			print_results( iter, elapsed );
+			printf( "ok %d benchmark finished\n", count );
+		}
+	}
+	for ( i = MIN; i <= MAX; i++ ) {
+		len = pow( 10, i );
+		iter = ITERATIONS / pow( 10, i-1 );
+		for ( j = 0; j < REPEATS; j++ ) {
+			count += 1;
+			printf( "# c::%s:ndarray:len=%d\n", NAME, len );
+			elapsed = benchmark2( iter, len );
 			print_results( iter, elapsed );
 			printf( "ok %d benchmark finished\n", count );
 		}
diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dcumin/docs/repl.txt
index 23e69025e980..11e8fade60df 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumin/docs/repl.txt
+++ b/lib/node_modules/@stdlib/stats/base/dcumin/docs/repl.txt
@@ -3,8 +3,8 @@
     Computes the cumulative minimum of double-precision floating-point strided
     array elements.
 
-    The `N` and `stride` parameters determine which elements in `x` and `y` are
-    accessed at runtime.
+    The `N` and stride parameters determine which elements in the strided arrays
+    are accessed at runtime.
 
     Indexing is relative to the first index. To introduce an offset, use a typed
     array view.
@@ -20,13 +20,13 @@
         Input array.
 
     strideX: integer
-        Index increment for `x`.
+        Stride Length for `x`.
 
     y: Float64Array
         Output array.
 
     strideY: integer
-        Index increment for `y`.
+        Stride Length for `y`.
 
     Returns
     -------
@@ -44,8 +44,7 @@
     // Using `N` and `stride` parameters:
     > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );
     > y = new {{alias:@stdlib/array/float64}}( x.length );
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > {{alias}}( N, x, 2, y, 2 )
+    > {{alias}}( 3, x, 2, y, 2 )
     <Float64Array>[ -2.0, 0.0, -2.0, 0.0, -2.0, 0.0 ]
 
     // Using view offsets:
@@ -53,12 +52,12 @@
     > var y0 = new {{alias:@stdlib/array/float64}}( x0.length );
     > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );
     > var y1 = new {{alias:@stdlib/array/float64}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 );
-    > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );
-    > {{alias}}( N, x1, 2, y1, 1 )
+    > {{alias}}( 3, x1, 2, y1, 1 )
     <Float64Array>[ -2.0, -2.0, -2.0 ]
     > y0
     <Float64Array>[ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]
 
+
 {{alias}}.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )
     Computes the cumulative minimum of double-precision floating-point strided
     array elements using alternative indexing semantics.
@@ -76,7 +75,7 @@
         Input array.
 
     strideX: integer
-        Index increment for `x`.
+        Stride Length for `x`.
 
     offsetX: integer
         Starting index for `x`.
@@ -85,7 +84,7 @@
         Output array.
 
     strideY: integer
-        Index increment for `y`.
+        Stride Length for `y`.
 
     offsetY: integer
         Starting index for `y`.
@@ -106,8 +105,7 @@
     // Advanced indexing:
     > x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );
     > y = new {{alias:@stdlib/array/float64}}( x.length );
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > {{alias}}.ndarray( N, x, 2, 1, y, -1, y.length-1 )
+    > {{alias}}.ndarray( 3, x, 2, 1, y, -1, y.length-1 )
     <Float64Array>[ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]
 
     See Also
diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dcumin/examples/c/example.c
index 68aceb555659..ed1876ec1c2e 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumin/examples/c/example.c
+++ b/lib/node_modules/@stdlib/stats/base/dcumin/examples/c/example.c
@@ -17,27 +17,25 @@
 */
 
 #include "stdlib/stats/base/dcumin.h"
-#include <stdint.h>
 #include <stdio.h>
-#include <inttypes.h>
 
 int main( void ) {
 	// Create strided arrays:
-	double x[] = { 1.0, 2.0, -3.0, 4.0, -5.0, 6.0, 7.0, 8.0 };
+	const double x[] = { 1.0, 2.0, -3.0, 4.0, -5.0, 6.0, 7.0, 8.0 };
 	double y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 };
 
 	// Specify the number of elements:
-	int64_t N = 4;
+	const int N = 4;
 
 	// Specify stride lengths:
-	int64_t strideX = 2;
-	int64_t strideY = -2;
+	const int strideX = 2;
+	const int strideY = -2;
 
 	// Compute the cumulative minimum:
 	stdlib_strided_dcumin( N, x, strideX, y, strideY );
 
 	// Print the result:
-	for ( int64_t i = 0; i < 8; i++ ) {
-		printf( "y[ %"PRId64" ] = %lf\n", i, y[ i ] );
+	for ( int i = 0; i < 8; i++ ) {
+		printf( "y[ %d ] = %lf\n", i, y[ i ] );
 	}
 }
diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/examples/index.js b/lib/node_modules/@stdlib/stats/base/dcumin/examples/index.js
index 5674c935f426..089eab0aa2b7 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumin/examples/index.js
+++ b/lib/node_modules/@stdlib/stats/base/dcumin/examples/index.js
@@ -18,21 +18,16 @@
 
 'use strict';
 
-var randu = require( '@stdlib/random/base/randu' );
-var round = require( '@stdlib/math/base/special/round' );
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
 var Float64Array = require( '@stdlib/array/float64' );
 var dcumin = require( './../lib' );
 
-var y;
-var x;
-var i;
-
-x = new Float64Array( 10 );
-y = new Float64Array( x.length );
-for ( i = 0; i < x.length; i++ ) {
-	x[ i ] = round( randu()*100.0 );
-}
+var x = discreteUniform( 10, -50, 50, {
+	'dtype': 'float64'
+});
 console.log( x );
+
+var y = new Float64Array( x.length );
 console.log( y );
 
 dcumin( x.length, x, 1, y, -1 );
diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/include/stdlib/stats/base/dcumin.h b/lib/node_modules/@stdlib/stats/base/dcumin/include/stdlib/stats/base/dcumin.h
index bdf7b4f03623..2072e32aabfb 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumin/include/stdlib/stats/base/dcumin.h
+++ b/lib/node_modules/@stdlib/stats/base/dcumin/include/stdlib/stats/base/dcumin.h
@@ -19,7 +19,7 @@
 #ifndef STDLIB_STATS_BASE_DCUMIN_H
 #define STDLIB_STATS_BASE_DCUMIN_H
 
-#include <stdint.h>
+#include "stdlib/blas/base/shared.h"
 
 /*
 * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler.
@@ -31,7 +31,12 @@ extern "C" {
 /**
 * Computes the cumulative minimum of double-precision floating-point strided array elements.
 */
-void stdlib_strided_dcumin( const int64_t N, const double *X, const int64_t strideX, double *Y, const int64_t strideY );
+void API_SUFFIX(stdlib_strided_dcumin)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, double *Y, const CBLAS_INT strideY );
+
+/**
+* Computes the cumulative minimum of double-precision floating-point strided array elements using alternative indexing semantics.
+*/
+void API_SUFFIX(stdlib_strided_dcumin_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, double *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY );
 
 #ifdef __cplusplus
 }
diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/lib/dcumin.js b/lib/node_modules/@stdlib/stats/base/dcumin/lib/dcumin.js
index 903fcb23e34c..301a08001fa5 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumin/lib/dcumin.js
+++ b/lib/node_modules/@stdlib/stats/base/dcumin/lib/dcumin.js
@@ -20,8 +20,8 @@
 
 // MODULES //
 
-var isnan = require( '@stdlib/math/base/assert/is-nan' );
-var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' );
+var stride2offset = require( '@stdlib/strided/base/stride2offset' );
+var ndarray = require( './ndarray.js' );
 
 
 // MAIN //
@@ -41,58 +41,14 @@ var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' );
 *
 * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );
 * var y = new Float64Array( x.length );
-* var N = x.length;
 *
-* var v = dcumin( N, x, 1, y, 1 );
+* var v = dcumin( x.length, x, 1, y, 1 );
 * // returns <Float64Array>[ 1.0, -2.0, -2.0 ]
 */
 function dcumin( N, x, strideX, y, strideY ) {
-	var min;
-	var ix;
-	var iy;
-	var v;
-	var i;
-
-	if ( N <= 0 ) {
-		return y;
-	}
-	if ( strideX < 0 ) {
-		ix = (1-N) * strideX;
-	} else {
-		ix = 0;
-	}
-	if ( strideY < 0 ) {
-		iy = (1-N) * strideY;
-	} else {
-		iy = 0;
-	}
-	min = x[ ix ];
-	y[ iy ] = min;
-
-	iy += strideY;
-	i = 1;
-	if ( isnan( min ) === false ) {
-		for ( i; i < N; i++ ) {
-			ix += strideX;
-			v = x[ ix ];
-			if ( isnan( v ) ) {
-				min = v;
-				break;
-			}
-			if ( v < min || ( v === min && isNegativeZero( v ) ) ) {
-				min = v;
-			}
-			y[ iy ] = min;
-			iy += strideY;
-		}
-	}
-	if ( isnan( min ) ) {
-		for ( i; i < N; i++ ) {
-			y[ iy ] = min;
-			iy += strideY;
-		}
-	}
-	return y;
+	var ox = stride2offset( N, strideX );
+	var oy = stride2offset( N, strideY );
+	return ndarray( N, x, strideX, ox, y, strideY, oy );
 }
 
 
diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/lib/dcumin.native.js b/lib/node_modules/@stdlib/stats/base/dcumin/lib/dcumin.native.js
index 7d8f37a83a13..0700b4a5fd84 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumin/lib/dcumin.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dcumin/lib/dcumin.native.js
@@ -40,9 +40,8 @@ var addon = require( './../src/addon.node' );
 *
 * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );
 * var y = new Float64Array( x.length );
-* var N = x.length;
 *
-* var v = dcumin( N, x, 1, y, 1 );
+* var v = dcumin( x.length, x, 1, y, 1 );
 * // returns <Float64Array>[ 1.0, -2.0, -2.0 ]
 */
 function dcumin( N, x, strideX, y, strideY ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/lib/index.js b/lib/node_modules/@stdlib/stats/base/dcumin/lib/index.js
index 6b07d0f2a275..94872e121c51 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumin/lib/index.js
+++ b/lib/node_modules/@stdlib/stats/base/dcumin/lib/index.js
@@ -29,21 +29,18 @@
 *
 * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );
 * var y = new Float64Array( x.length );
-* var N = x.length;
 *
-* dcumin( N, x, 1, y, 1 );
+* dcumin( x.length, x, 1, y, 1 );
 * // y => <Float64Array>[ 1.0, -2.0, -2.0 ]
 *
 * @example
 * var Float64Array = require( '@stdlib/array/float64' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 * var dcumin = require( '@stdlib/stats/base/dcumin' );
 *
 * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
 * var y = new Float64Array( x.length );
-* var N = floor( x.length / 2 );
 *
-* dcumin.ndarray( N, x, 2, 1, y, 1, 0 );
+* dcumin.ndarray( 4, x, 2, 1, y, 1, 0 );
 * // y => <Float64Array>[ 1.0, -2.0, -2.0, -2.0, 0.0, 0.0, 0.0, 0.0 ]
 */
 
diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/dcumin/lib/ndarray.js
index db660dea12f5..49e575254e95 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumin/lib/ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/dcumin/lib/ndarray.js
@@ -40,13 +40,11 @@ var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' );
 *
 * @example
 * var Float64Array = require( '@stdlib/array/float64' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 *
 * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
 * var y = new Float64Array( x.length );
-* var N = floor( x.length / 2 );
 *
-* var v = dcumin( N, x, 2, 1, y, 1, 0 );
+* var v = dcumin( 4, x, 2, 1, y, 1, 0 );
 * // returns <Float64Array>[ 1.0, -2.0, -2.0, -2.0, 0.0, 0.0, 0.0, 0.0 ]
 */
 function dcumin( N, x, strideX, offsetX, y, strideY, offsetY ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dcumin/lib/ndarray.native.js
index c55627c62cf6..99498beff430 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumin/lib/ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dcumin/lib/ndarray.native.js
@@ -20,8 +20,7 @@
 
 // MODULES //
 
-var Float64Array = require( '@stdlib/array/float64' );
-var addon = require( './dcumin.native.js' );
+var addon = require( './../src/addon.node' );
 
 
 // MAIN //
@@ -40,27 +39,15 @@ var addon = require( './dcumin.native.js' );
 *
 * @example
 * var Float64Array = require( '@stdlib/array/float64' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 *
 * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
 * var y = new Float64Array( x.length );
-* var N = floor( x.length / 2 );
 *
-* var v = dcumin( N, x, 2, 1, y, 1, 0 );
+* var v = dcumin( 4, x, 2, 1, y, 1, 0 );
 * // returns <Float64Array>[ 1.0, -2.0, -2.0, -2.0, 0.0, 0.0, 0.0, 0.0 ]
 */
 function dcumin( N, x, strideX, offsetX, y, strideY, offsetY ) {
-	var viewX;
-	var viewY;
-	if ( strideX < 0 ) {
-		offsetX += (N-1) * strideX;
-	}
-	if ( strideY < 0 ) {
-		offsetY += (N-1) * strideY;
-	}
-	viewX = new Float64Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offsetX), x.length-offsetX ); // eslint-disable-line max-len
-	viewY = new Float64Array( y.buffer, y.byteOffset+(y.BYTES_PER_ELEMENT*offsetY), y.length-offsetY ); // eslint-disable-line max-len
-	addon( N, viewX, strideX, viewY, strideY );
+	addon.ndarray( N, x, strideX, offsetX, y, strideY, offsetY );
 	return y;
 }
 
diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/manifest.json b/lib/node_modules/@stdlib/stats/base/dcumin/manifest.json
index 35026eba7713..09770f614dd4 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumin/manifest.json
+++ b/lib/node_modules/@stdlib/stats/base/dcumin/manifest.json
@@ -1,6 +1,7 @@
 {
   "options": {
-    "task": "build"
+    "task": "build",
+    "wasm": false
   },
   "fields": [
     {
@@ -27,17 +28,18 @@
   "confs": [
     {
       "task": "build",
+      "wasm": false,
       "src": [
-        "./src/dcumin.c"
+        "./src/main.c"
       ],
       "include": [
         "./include"
       ],
-      "libraries": [
-        "-lm"
-      ],
+      "libraries": [],
       "libpath": [],
       "dependencies": [
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset",
         "@stdlib/math/base/assert/is-negative-zero",
         "@stdlib/math/base/assert/is-nan",
         "@stdlib/napi/export",
@@ -48,34 +50,54 @@
     },
     {
       "task": "benchmark",
+      "wasm": false,
       "src": [
-        "./src/dcumin.c"
+        "./src/main.c"
       ],
       "include": [
         "./include"
       ],
-      "libraries": [
-        "-lm"
-      ],
+      "libraries": [],
       "libpath": [],
       "dependencies": [
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset",
         "@stdlib/math/base/assert/is-negative-zero",
         "@stdlib/math/base/assert/is-nan"
       ]
     },
     {
       "task": "examples",
+      "wasm": false,
       "src": [
-        "./src/dcumin.c"
+        "./src/main.c"
       ],
       "include": [
         "./include"
       ],
-      "libraries": [
-        "-lm"
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset",
+        "@stdlib/math/base/assert/is-nan",
+        "@stdlib/math/base/assert/is-negative-zero"
+      ]
+    },
+    {
+      "task": "",
+      "wasm": true,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
       ],
+      "libraries": [],
       "libpath": [],
       "dependencies": [
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset",
         "@stdlib/math/base/assert/is-nan",
         "@stdlib/math/base/assert/is-negative-zero"
       ]
diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/src/addon.c b/lib/node_modules/@stdlib/stats/base/dcumin/src/addon.c
index 9613a6c56f24..65e88425602d 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumin/src/addon.c
+++ b/lib/node_modules/@stdlib/stats/base/dcumin/src/addon.c
@@ -41,4 +41,24 @@ static napi_value addon( napi_env env, napi_callback_info info ) {
 	return NULL;
 }
 
-STDLIB_NAPI_MODULE_EXPORT_FCN( addon )
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon_method( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 7 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 );
+	STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 5 );
+	STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 );
+	STDLIB_NAPI_ARGV_INT64( env, offsetY, argv, 6 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, Y, N, strideY, argv, 4 );
+	stdlib_strided_dcumin_ndarray( N, X, strideX, offsetX, Y, strideY, offsetY );
+	return NULL;
+}
+
+STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method )
diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/src/dcumin.c b/lib/node_modules/@stdlib/stats/base/dcumin/src/main.c
similarity index 58%
rename from lib/node_modules/@stdlib/stats/base/dcumin/src/dcumin.c
rename to lib/node_modules/@stdlib/stats/base/dcumin/src/main.c
index 9dacb42a60d7..28d84fa6d19a 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumin/src/dcumin.c
+++ b/lib/node_modules/@stdlib/stats/base/dcumin/src/main.c
@@ -19,7 +19,8 @@
 #include "stdlib/stats/base/dcumin.h"
 #include "stdlib/math/base/assert/is_nan.h"
 #include "stdlib/math/base/assert/is_negative_zero.h"
-#include <stdint.h>
+#include "stdlib/blas/base/shared.h"
+#include "stdlib/strided/base/stride2offset.h"
 
 /**
 * Computes the cumulative minimum of double-precision floating-point strided array elements.
@@ -30,26 +31,36 @@
 * @param Y        output array
 * @param strideY  Y stride length
 */
-void stdlib_strided_dcumin( const int64_t N, const double *X, const int64_t strideX, double *Y, const int64_t strideY ) {
+void API_SUFFIX(stdlib_strided_dcumin)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, double *Y, const CBLAS_INT strideY ) {
+	const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX );
+	const CBLAS_INT oy = stdlib_strided_stride2offset( N, strideY );
+	API_SUFFIX(stdlib_strided_dcumin_ndarray)( N, X, strideX, ox, Y, strideY, oy );
+	return;
+}
+
+/**
+* Computes the cumulative minimum of double-precision floating-point strided array elements using alternative indexing semantics.
+*
+* @param N        number of indexed elements
+* @param X        input array
+* @param strideX  X stride length
+* @param offsetX  starting index for X
+* @param Y        output array
+* @param strideY  Y stride length
+* @param offsetY  starting index for Y
+*/
+void API_SUFFIX(stdlib_strided_dcumin_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, double *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ) {
+	CBLAS_INT ix;
+	CBLAS_INT iy;
+	CBLAS_INT i;
 	double min;
-	int64_t ix;
-	int64_t iy;
-	int64_t i;
 	double v;
 
 	if ( N <= 0 ) {
 		return;
 	}
-	if ( strideX < 0 ) {
-		ix = (1-N) * strideX;
-	} else {
-		ix = 0;
-	}
-	if ( strideY < 0 ) {
-		iy = (1-N) * strideY;
-	} else {
-		iy = 0;
-	}
+	ix = offsetX;
+	iy = offsetY;
 	min = X[ ix ];
 	Y[ iy ] = min;
 
diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/test/test.dcumin.js b/lib/node_modules/@stdlib/stats/base/dcumin/test/test.dcumin.js
index dd37e5768088..4bebc4892aa3 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumin/test/test.dcumin.js
+++ b/lib/node_modules/@stdlib/stats/base/dcumin/test/test.dcumin.js
@@ -21,7 +21,6 @@
 // MODULES //
 
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' );
 var Float64Array = require( '@stdlib/array/float64' );
@@ -150,7 +149,6 @@ tape( 'the function supports an `x` stride', function test( t ) {
 	var expected;
 	var x;
 	var y;
-	var N;
 
 	x = new Float64Array([
 		1.0,  // 0
@@ -166,9 +164,8 @@ tape( 'the function supports an `x` stride', function test( t ) {
 		0.0,
 		0.0
 	]);
-	N = 3;
 
-	dcumin( N, x, 2, y, 1 );
+	dcumin( 3, x, 2, y, 1 );
 
 	expected = new Float64Array( [ 1.0, 1.0, -5.0, 0.0, 0.0 ] );
 	t.deepEqual( y, expected, 'returns expected value' );
@@ -180,7 +177,6 @@ tape( 'the function supports a `y` stride', function test( t ) {
 	var expected;
 	var x;
 	var y;
-	var N;
 
 	x = new Float64Array([
 		1.0,  // 0
@@ -196,9 +192,8 @@ tape( 'the function supports a `y` stride', function test( t ) {
 		0.0,
 		0.0  // 2
 	]);
-	N = 3;
 
-	dcumin( N, x, 1, y, 2 );
+	dcumin( 3, x, 1, y, 2 );
 
 	expected = new Float64Array( [ 1.0, 0.0, -2.0, 0.0, -2.0 ] );
 	t.deepEqual( y, expected, 'returns expected value' );
@@ -210,7 +205,6 @@ tape( 'the function supports negative strides', function test( t ) {
 	var expected;
 	var x;
 	var y;
-	var N;
 
 	x = new Float64Array([
 		1.0,  // 2
@@ -226,9 +220,8 @@ tape( 'the function supports negative strides', function test( t ) {
 		0.0,
 		0.0
 	]);
-	N = 3;
 
-	dcumin( N, x, -2, y, -1 );
+	dcumin( 3, x, -2, y, -1 );
 
 	expected = new Float64Array( [ -5.0, -5.0, -5.0, 0.0, 0.0 ] );
 	t.deepEqual( y, expected, 'returns expected value' );
@@ -240,7 +233,6 @@ tape( 'the function supports complex access patterns', function test( t ) {
 	var expected;
 	var x;
 	var y;
-	var N;
 
 	x = new Float64Array([
 		1.0,  // 0
@@ -258,9 +250,8 @@ tape( 'the function supports complex access patterns', function test( t ) {
 		0.0,
 		0.0
 	]);
-	N = 3;
 
-	dcumin( N, x, 2, y, -1 );
+	dcumin( 3, x, 2, y, -1 );
 
 	expected = new Float64Array( [ -3.0, -3.0, 1.0, 0.0, 0.0, 0.0 ] );
 	t.deepEqual( y, expected, 'returns expected value' );
@@ -274,7 +265,6 @@ tape( 'the function supports view offsets', function test( t ) {
 	var y0;
 	var x1;
 	var y1;
-	var N;
 
 	// Initial arrays...
 	x0 = new Float64Array([
@@ -298,9 +288,7 @@ tape( 'the function supports view offsets', function test( t ) {
 	x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element
 	y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // begin at the 4th element
 
-	N = floor( x0.length / 2 );
-
-	dcumin( N, x1, -2, y1, 1 );
+	dcumin( 3, x1, -2, y1, 1 );
 	expected = new Float64Array( [ 0.0, 0.0, 0.0, 6.0, 4.0, 2.0 ] );
 
 	t.deepEqual( y0, expected, 'returns expected value' );
diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/test/test.dcumin.native.js b/lib/node_modules/@stdlib/stats/base/dcumin/test/test.dcumin.native.js
index 48b29100dfe4..e4b27dff4459 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumin/test/test.dcumin.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dcumin/test/test.dcumin.native.js
@@ -22,7 +22,6 @@
 
 var resolve = require( 'path' ).resolve;
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' );
 var Float64Array = require( '@stdlib/array/float64' );
@@ -159,7 +158,6 @@ tape( 'the function supports an `x` stride', opts, function test( t ) {
 	var expected;
 	var x;
 	var y;
-	var N;
 
 	x = new Float64Array([
 		1.0,  // 0
@@ -175,9 +173,8 @@ tape( 'the function supports an `x` stride', opts, function test( t ) {
 		0.0,
 		0.0
 	]);
-	N = 3;
 
-	dcumin( N, x, 2, y, 1 );
+	dcumin( 3, x, 2, y, 1 );
 
 	expected = new Float64Array( [ 1.0, 1.0, -5.0, 0.0, 0.0 ] );
 	t.deepEqual( y, expected, 'returns expected value' );
@@ -189,7 +186,6 @@ tape( 'the function supports a `y` stride', opts, function test( t ) {
 	var expected;
 	var x;
 	var y;
-	var N;
 
 	x = new Float64Array([
 		1.0,  // 0
@@ -205,9 +201,8 @@ tape( 'the function supports a `y` stride', opts, function test( t ) {
 		0.0,
 		0.0  // 2
 	]);
-	N = 3;
 
-	dcumin( N, x, 1, y, 2 );
+	dcumin( 3, x, 1, y, 2 );
 
 	expected = new Float64Array( [ 1.0, 0.0, -2.0, 0.0, -2.0 ] );
 	t.deepEqual( y, expected, 'returns expected value' );
@@ -219,7 +214,6 @@ tape( 'the function supports negative strides', opts, function test( t ) {
 	var expected;
 	var x;
 	var y;
-	var N;
 
 	x = new Float64Array([
 		1.0,  // 2
@@ -235,9 +229,8 @@ tape( 'the function supports negative strides', opts, function test( t ) {
 		0.0,
 		0.0
 	]);
-	N = 3;
 
-	dcumin( N, x, -2, y, -1 );
+	dcumin( 3, x, -2, y, -1 );
 
 	expected = new Float64Array( [ -5.0, -5.0, -5.0, 0.0, 0.0 ] );
 	t.deepEqual( y, expected, 'returns expected value' );
@@ -249,7 +242,6 @@ tape( 'the function supports complex access patterns', opts, function test( t )
 	var expected;
 	var x;
 	var y;
-	var N;
 
 	x = new Float64Array([
 		1.0,  // 0
@@ -267,9 +259,8 @@ tape( 'the function supports complex access patterns', opts, function test( t )
 		0.0,
 		0.0
 	]);
-	N = 3;
 
-	dcumin( N, x, 2, y, -1 );
+	dcumin( 3, x, 2, y, -1 );
 
 	expected = new Float64Array( [ -3.0, -3.0, 1.0, 0.0, 0.0, 0.0 ] );
 	t.deepEqual( y, expected, 'returns expected value' );
@@ -283,7 +274,6 @@ tape( 'the function supports view offsets', opts, function test( t ) {
 	var y0;
 	var x1;
 	var y1;
-	var N;
 
 	// Initial arrays...
 	x0 = new Float64Array([
@@ -307,9 +297,7 @@ tape( 'the function supports view offsets', opts, function test( t ) {
 	x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element
 	y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // begin at the 4th element
 
-	N = floor( x0.length / 2 );
-
-	dcumin( N, x1, -2, y1, 1 );
+	dcumin( 3, x1, -2, y1, 1 );
 	expected = new Float64Array( [ 0.0, 0.0, 0.0, 6.0, 4.0, 2.0 ] );
 
 	t.deepEqual( y0, expected, 'returns expected value' );
diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dcumin/test/test.ndarray.js
index 7ffcf66cc955..efff7548dc8d 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumin/test/test.ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/dcumin/test/test.ndarray.js
@@ -21,7 +21,6 @@
 // MODULES //
 
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' );
 var Float64Array = require( '@stdlib/array/float64' );
@@ -150,7 +149,6 @@ tape( 'the function supports an `x` stride', function test( t ) {
 	var expected;
 	var x;
 	var y;
-	var N;
 
 	x = new Float64Array([
 		1.0,  // 0
@@ -166,9 +164,8 @@ tape( 'the function supports an `x` stride', function test( t ) {
 		0.0,
 		0.0
 	]);
-	N = 3;
 
-	dcumin( N, x, 2, 0, y, 1, 0 );
+	dcumin( 3, x, 2, 0, y, 1, 0 );
 
 	expected = new Float64Array( [ 1.0, 1.0, -5.0, 0.0, 0.0 ] );
 	t.deepEqual( y, expected, 'returns expected value' );
@@ -180,7 +177,6 @@ tape( 'the function supports a `y` stride', function test( t ) {
 	var expected;
 	var x;
 	var y;
-	var N;
 
 	x = new Float64Array([
 		1.0,  // 0
@@ -196,9 +192,8 @@ tape( 'the function supports a `y` stride', function test( t ) {
 		0.0,
 		0.0  // 2
 	]);
-	N = 3;
 
-	dcumin( N, x, 1, 0, y, 2, 0 );
+	dcumin( 3, x, 1, 0, y, 2, 0 );
 
 	expected = new Float64Array( [ 1.0, 0.0, -2.0, 0.0, -2.0 ] );
 	t.deepEqual( y, expected, 'returns expected value' );
@@ -210,7 +205,6 @@ tape( 'the function supports negative strides', function test( t ) {
 	var expected;
 	var x;
 	var y;
-	var N;
 
 	x = new Float64Array([
 		1.0,  // 2
@@ -226,9 +220,8 @@ tape( 'the function supports negative strides', function test( t ) {
 		0.0,
 		0.0
 	]);
-	N = 3;
 
-	dcumin( N, x, -2, x.length-1, y, -1, 2 );
+	dcumin( 3, x, -2, x.length-1, y, -1, 2 );
 
 	expected = new Float64Array( [ -5.0, -5.0, -5.0, 0.0, 0.0 ] );
 	t.deepEqual( y, expected, 'returns expected value' );
@@ -238,7 +231,6 @@ tape( 'the function supports negative strides', function test( t ) {
 
 tape( 'the function supports an `x` offset', function test( t ) {
 	var expected;
-	var N;
 	var x;
 	var y;
 
@@ -262,9 +254,8 @@ tape( 'the function supports an `x` offset', function test( t ) {
 		0.0,
 		0.0
 	]);
-	N = floor( x.length / 2 );
 
-	dcumin( N, x, 2, 1, y, 1, 0 );
+	dcumin( 4, x, 2, 1, y, 1, 0 );
 
 	expected = new Float64Array( [ 1.0, -2.0, -2.0, -2.0, 0.0, 0.0, 0.0, 0.0 ] ); // eslint-disable-line max-len
 	t.deepEqual( y, expected, 'returns expected value' );
@@ -274,7 +265,6 @@ tape( 'the function supports an `x` offset', function test( t ) {
 
 tape( 'the function supports a `y` offset', function test( t ) {
 	var expected;
-	var N;
 	var x;
 	var y;
 
@@ -298,9 +288,8 @@ tape( 'the function supports a `y` offset', function test( t ) {
 		0.0,
 		0.0  // 3
 	]);
-	N = floor( x.length / 2 );
 
-	dcumin( N, x, 1, 0, y, 2, 1 );
+	dcumin( 4, x, 1, 0, y, 2, 1 );
 
 	expected = new Float64Array( [ 0.0, 2.0, 0.0, 1.0, 0.0, 1.0, 0.0, -2.0 ] );
 	t.deepEqual( y, expected, 'returns expected value' );
@@ -312,7 +301,6 @@ tape( 'the function supports complex access patterns', function test( t ) {
 	var expected;
 	var x;
 	var y;
-	var N;
 
 	x = new Float64Array([
 		1.0,  // 0
@@ -330,9 +318,8 @@ tape( 'the function supports complex access patterns', function test( t ) {
 		0.0,
 		0.0
 	]);
-	N = 3;
 
-	dcumin( N, x, 2, 0, y, -1, 2 );
+	dcumin( 3, x, 2, 0, y, -1, 2 );
 
 	expected = new Float64Array( [ -3.0, -3.0, 1.0, 0.0, 0.0, 0.0 ] );
 	t.deepEqual( y, expected, 'returns expected value' );
diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dcumin/test/test.ndarray.native.js
index 15b46090035c..5a1ac760c683 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumin/test/test.ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dcumin/test/test.ndarray.native.js
@@ -22,7 +22,6 @@
 
 var resolve = require( 'path' ).resolve;
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var isNegativeZero = require( '@stdlib/math/base/assert/is-negative-zero' );
 var Float64Array = require( '@stdlib/array/float64' );
@@ -159,7 +158,6 @@ tape( 'the function supports an `x` stride', opts, function test( t ) {
 	var expected;
 	var x;
 	var y;
-	var N;
 
 	x = new Float64Array([
 		1.0,  // 0
@@ -175,9 +173,8 @@ tape( 'the function supports an `x` stride', opts, function test( t ) {
 		0.0,
 		0.0
 	]);
-	N = 3;
 
-	dcumin( N, x, 2, 0, y, 1, 0 );
+	dcumin( 3, x, 2, 0, y, 1, 0 );
 
 	expected = new Float64Array( [ 1.0, 1.0, -5.0, 0.0, 0.0 ] );
 	t.deepEqual( y, expected, 'returns expected value' );
@@ -189,7 +186,6 @@ tape( 'the function supports a `y` stride', opts, function test( t ) {
 	var expected;
 	var x;
 	var y;
-	var N;
 
 	x = new Float64Array([
 		1.0,  // 0
@@ -205,9 +201,8 @@ tape( 'the function supports a `y` stride', opts, function test( t ) {
 		0.0,
 		0.0  // 2
 	]);
-	N = 3;
 
-	dcumin( N, x, 1, 0, y, 2, 0 );
+	dcumin( 3, x, 1, 0, y, 2, 0 );
 
 	expected = new Float64Array( [ 1.0, 0.0, -2.0, 0.0, -2.0 ] );
 	t.deepEqual( y, expected, 'returns expected value' );
@@ -219,7 +214,6 @@ tape( 'the function supports negative strides', opts, function test( t ) {
 	var expected;
 	var x;
 	var y;
-	var N;
 
 	x = new Float64Array([
 		1.0,  // 2
@@ -235,9 +229,8 @@ tape( 'the function supports negative strides', opts, function test( t ) {
 		0.0,
 		0.0
 	]);
-	N = 3;
 
-	dcumin( N, x, -2, x.length-1, y, -1, 2 );
+	dcumin( 3, x, -2, x.length-1, y, -1, 2 );
 
 	expected = new Float64Array( [ -5.0, -5.0, -5.0, 0.0, 0.0 ] );
 	t.deepEqual( y, expected, 'returns expected value' );
@@ -247,7 +240,6 @@ tape( 'the function supports negative strides', opts, function test( t ) {
 
 tape( 'the function supports an `x` offset', opts, function test( t ) {
 	var expected;
-	var N;
 	var x;
 	var y;
 
@@ -271,9 +263,8 @@ tape( 'the function supports an `x` offset', opts, function test( t ) {
 		0.0,
 		0.0
 	]);
-	N = floor( x.length / 2 );
 
-	dcumin( N, x, 2, 1, y, 1, 0 );
+	dcumin( 4, x, 2, 1, y, 1, 0 );
 
 	expected = new Float64Array( [ 1.0, -2.0, -2.0, -2.0, 0.0, 0.0, 0.0, 0.0 ] ); // eslint-disable-line max-len
 	t.deepEqual( y, expected, 'returns expected value' );
@@ -283,7 +274,6 @@ tape( 'the function supports an `x` offset', opts, function test( t ) {
 
 tape( 'the function supports a `y` offset', opts, function test( t ) {
 	var expected;
-	var N;
 	var x;
 	var y;
 
@@ -307,9 +297,8 @@ tape( 'the function supports a `y` offset', opts, function test( t ) {
 		0.0,
 		0.0  // 3
 	]);
-	N = floor( x.length / 2 );
 
-	dcumin( N, x, 1, 0, y, 2, 1 );
+	dcumin( 4, x, 1, 0, y, 2, 1 );
 
 	expected = new Float64Array( [ 0.0, 2.0, 0.0, 1.0, 0.0, 1.0, 0.0, -2.0 ] );
 	t.deepEqual( y, expected, 'returns expected value' );
@@ -321,7 +310,6 @@ tape( 'the function supports complex access patterns', opts, function test( t )
 	var expected;
 	var x;
 	var y;
-	var N;
 
 	x = new Float64Array([
 		1.0,  // 0
@@ -339,9 +327,8 @@ tape( 'the function supports complex access patterns', opts, function test( t )
 		0.0,
 		0.0
 	]);
-	N = 3;
 
-	dcumin( N, x, 2, 0, y, -1, 2 );
+	dcumin( 3, x, 2, 0, y, -1, 2 );
 
 	expected = new Float64Array( [ -3.0, -3.0, 1.0, 0.0, 0.0, 0.0 ] );
 	t.deepEqual( y, expected, 'returns expected value' );

From 47d93377b1da50c8a93865ca60547b1914b529b4 Mon Sep 17 00:00:00 2001
From: Aayush Khanna <96649223+aayush0325@users.noreply.github.com>
Date: Fri, 3 Jan 2025 05:36:00 +0530
Subject: [PATCH 32/87] feat: add C ndarray interface and refactor
 implementation for `stats/base/dcumaxabs`

PR-URL: https://github.com/stdlib-js/stdlib/pull/4139
Co-authored-by: Athan Reines <kgryte@gmail.com>
Reviewed-by: Athan Reines <kgryte@gmail.com>
---
 .../@stdlib/stats/base/dcumaxabs/README.md    | 151 ++++++++++++++++--
 .../base/dcumaxabs/benchmark/benchmark.js     |  20 +--
 .../dcumaxabs/benchmark/benchmark.native.js   |  16 +-
 .../dcumaxabs/benchmark/benchmark.ndarray.js  |  20 +--
 .../benchmark/benchmark.ndarray.native.js     |  16 +-
 .../dcumaxabs/benchmark/c/benchmark.length.c  |  49 +++++-
 .../stats/base/dcumaxabs/docs/repl.txt        |  24 ++-
 .../stats/base/dcumaxabs/examples/c/example.c |  14 +-
 .../stats/base/dcumaxabs/examples/index.js    |  17 +-
 .../include/stdlib/stats/base/dcumaxabs.h     |   9 +-
 .../stats/base/dcumaxabs/lib/dcumaxabs.js     |  53 +-----
 .../base/dcumaxabs/lib/dcumaxabs.native.js    |   3 +-
 .../@stdlib/stats/base/dcumaxabs/lib/index.js |   7 +-
 .../stats/base/dcumaxabs/lib/ndarray.js       |   4 +-
 .../base/dcumaxabs/lib/ndarray.native.js      |  19 +--
 .../stats/base/dcumaxabs/manifest.json        |  53 ++++--
 .../@stdlib/stats/base/dcumaxabs/src/addon.c  |  22 ++-
 .../dcumaxabs/src/{dcumaxabs.c => main.c}     |  47 +++---
 .../base/dcumaxabs/test/test.dcumaxabs.js     |  22 +--
 .../dcumaxabs/test/test.dcumaxabs.native.js   |  22 +--
 .../stats/base/dcumaxabs/test/test.ndarray.js |  25 +--
 .../dcumaxabs/test/test.ndarray.native.js     |  21 +--
 22 files changed, 367 insertions(+), 267 deletions(-)
 rename lib/node_modules/@stdlib/stats/base/dcumaxabs/src/{dcumaxabs.c => main.c} (53%)

diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/README.md b/lib/node_modules/@stdlib/stats/base/dcumaxabs/README.md
index 68619273f235..a8a279cf07dd 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/README.md
+++ b/lib/node_modules/@stdlib/stats/base/dcumaxabs/README.md
@@ -54,11 +54,11 @@ The function has the following parameters:
 
 -   **N**: number of indexed elements.
 -   **x**: input [`Float64Array`][@stdlib/array/float64].
--   **strideX**: index increment for `x`.
+-   **strideX**: stride length for `x`.
 -   **y**: output [`Float64Array`][@stdlib/array/float64].
--   **strideY**: index increment for `y`.
+-   **strideY**: stride length for `y`.
 
-The `N` and `stride` parameters determine which elements in `x` and `y` are accessed at runtime. For example, to compute the cumulative maximum absolute value of every other element in `x`,
+The `N` and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the cumulative maximum absolute value of every other element in `x`,
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
@@ -108,7 +108,7 @@ The function has the following additional parameters:
 -   **offsetX**: starting index for `x`.
 -   **offsetY**: starting index for `y`.
 
-While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, `offsetX` and `offsetY` parameters support indexing semantics based on a starting indices. For example, to calculate the cumulative maximum absolute value of every other value in `x` starting from the second value and to store in the last `N` elements of `y` starting from the last element
+While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on a starting indices. For example, to calculate the cumulative maximum absolute value of every other element in `x` starting from the second element and to store in the last `N` elements of `y` starting from the last element
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
@@ -141,21 +141,16 @@ dcumaxabs.ndarray( 4, x, 2, 1, y, -1, y.length-1 );
 <!-- eslint no-undef: "error" -->
 
 ```javascript
-var randu = require( '@stdlib/random/base/randu' );
-var round = require( '@stdlib/math/base/special/round' );
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
 var Float64Array = require( '@stdlib/array/float64' );
 var dcumaxabs = require( '@stdlib/stats/base/dcumaxabs' );
 
-var y;
-var x;
-var i;
-
-x = new Float64Array( 10 );
-y = new Float64Array( x.length );
-for ( i = 0; i < x.length; i++ ) {
-    x[ i ] = round( (randu()*100.0) - 50.0 );
-}
+var x = discreteUniform( 10, -50, 50, {
+    'dtype': 'float64'
+});
 console.log( x );
+
+var y = new Float64Array( x.length );
 console.log( y );
 
 dcumaxabs( x.length, x, 1, y, -1 );
@@ -166,6 +161,132 @@ console.log( y );
 
 <!-- /.examples -->
 
+<!-- C interface documentation. -->
+
+* * *
+
+<section class="c">
+
+## C APIs
+
+<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<!-- C usage documentation. -->
+
+<section class="usage">
+
+### Usage
+
+```c
+#include "stdlib/stats/base/dcumaxabs.h"
+```
+
+#### stdlib_strided_dcumaxabs( N, \*X, strideX, \*Y, strideY )
+
+Computes the cumulative maximum absolute value of double-precision floating-point strided array elements.
+
+```c
+const double x[] = { 1.0, 2.0, -3.0, 4.0, -5.0, 6.0, 7.0, 8.0 };
+double y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 };
+
+stdlib_strided_dcumaxabs( 4, x, 2, y, -2 );
+```
+
+The function accepts the following arguments:
+
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **X**: `[in] double*` input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+-   **Y**: `[out] double*` output array.
+-   **strideY**: `[in] CBLAS_INT` stride length for `Y`.
+
+```c
+void stdlib_strided_dcumaxabs( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, double *Y, const CBLAS_INT strideY );
+```
+
+#### stdlib_strided_dcumaxabs_ndarray(N, \*X, strideX, offsetX, \*Y, strideY, offsetY )
+
+Computes the cumulative maximum absolute value of double-precision floating-point strided array elements using alternative indexing semantics.
+
+```c
+const double x[] = { 1.0, 2.0, -3.0, 4.0, -5.0, 6.0, 7.0, 8.0 };
+double y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 };
+
+stdlib_strided_dcumaxabs_ndarray( 4, x, 2, 0, y, -2, 0 );
+```
+
+The function accepts the following arguments:
+
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **X**: `[in] double*` input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+-   **offsetX**: `[in] CBLAS_INT` starting index for `X`.
+-   **Y**: `[out] double*` output array.
+-   **strideY**: `[in] CBLAS_INT` stride length for `Y`.
+-   **offsetY**: `[in] CBLAS_INT` starting index for `Y`.
+
+```c
+void stdlib_strided_dcumaxabs_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, double *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY );
+```
+
+</section>
+
+<!-- /.usage -->
+
+<!-- C API usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="notes">
+
+</section>
+
+<!-- /.notes -->
+
+<!-- C API usage examples. -->
+
+<section class="examples">
+
+### Examples
+
+```c
+#include "stdlib/stats/base/dcumaxabs.h"
+#include <stdio.h>
+
+int main( void ) {
+    // Create strided arrays:
+    const double x[] = { 1.0, 2.0, -3.0, 4.0, -5.0, 6.0, 7.0, 8.0 };
+    double y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 };
+
+    // Specify the number of elements:
+    const int N = 4;
+
+    // Specify stride lengths:
+    const int strideX = 2;
+    const int strideY = -2;
+
+    // Compute the cumulative maximum absolute value:
+    stdlib_strided_dcumaxabs( N, x, strideX, y, strideY );
+
+    // Print the result:
+    for ( int i = 0; i < 8; i++ ) {
+        printf( "y[ %d ] = %lf\n", i, y[ i ] );
+    }
+}
+```
+
+</section>
+
+<!-- /.examples -->
+
+</section>
+
+<!-- /.c -->
+
 <section class="references">
 
 </section>
diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dcumaxabs/benchmark/benchmark.js
index 76350238b628..de4111f74aa8 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/benchmark/benchmark.js
+++ b/lib/node_modules/@stdlib/stats/base/dcumaxabs/benchmark/benchmark.js
@@ -21,7 +21,7 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/array/uniform' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
 var Float64Array = require( '@stdlib/array/float64' );
@@ -29,6 +29,13 @@ var pkg = require( './../package.json' ).name;
 var dcumaxabs = require( './../lib/dcumaxabs.js' );
 
 
+// VARIABLES //
+
+var options = {
+	'dtype': 'float64'
+};
+
+
 // FUNCTIONS //
 
 /**
@@ -39,15 +46,8 @@ var dcumaxabs = require( './../lib/dcumaxabs.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var y;
-	var x;
-	var i;
-
-	x = new Float64Array( len );
-	y = new Float64Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
+	var x = uniform( len, -10.0, 10.0, options );
+	var y = new Float64Array( len );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dcumaxabs/benchmark/benchmark.native.js
index eb4a06ac6037..7c534ac99c4d 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/benchmark/benchmark.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dcumaxabs/benchmark/benchmark.native.js
@@ -22,7 +22,7 @@
 
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/array/uniform' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
 var Float64Array = require( '@stdlib/array/float64' );
@@ -36,6 +36,9 @@ var dcumaxabs = tryRequire( resolve( __dirname, './../lib/dcumaxabs.native.js' )
 var opts = {
 	'skip': ( dcumaxabs instanceof Error )
 };
+var options = {
+	'dtype': 'float64'
+};
 
 
 // FUNCTIONS //
@@ -48,15 +51,8 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var y;
-	var i;
-
-	x = new Float64Array( len );
-	y = new Float64Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
+	var x = uniform( len, -10.0, 10.0, options );
+	var y = new Float64Array( len );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/dcumaxabs/benchmark/benchmark.ndarray.js
index 480d986ef97d..68e51184c963 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/benchmark/benchmark.ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/dcumaxabs/benchmark/benchmark.ndarray.js
@@ -21,7 +21,7 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/array/uniform' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
 var Float64Array = require( '@stdlib/array/float64' );
@@ -29,6 +29,13 @@ var pkg = require( './../package.json' ).name;
 var dcumaxabs = require( './../lib/ndarray.js' );
 
 
+// VARIABLES //
+
+var options = {
+	'dtype': 'float64'
+};
+
+
 // FUNCTIONS //
 
 /**
@@ -39,15 +46,8 @@ var dcumaxabs = require( './../lib/ndarray.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var y;
-	var i;
-
-	x = new Float64Array( len );
-	y = new Float64Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
+	var x = uniform( len, -10.0, 10.0, options );
+	var y = new Float64Array( len );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dcumaxabs/benchmark/benchmark.ndarray.native.js
index ce5d0c2b83d3..6941181db116 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/benchmark/benchmark.ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dcumaxabs/benchmark/benchmark.ndarray.native.js
@@ -22,7 +22,7 @@
 
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/array/uniform' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
 var Float64Array = require( '@stdlib/array/float64' );
@@ -36,6 +36,9 @@ var dcumaxabs = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' ) )
 var opts = {
 	'skip': ( dcumaxabs instanceof Error )
 };
+var options = {
+	'dtype': 'float64'
+};
 
 
 // FUNCTIONS //
@@ -48,15 +51,8 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var y;
-	var i;
-
-	x = new Float64Array( len );
-	y = new Float64Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = ( randu()*20.0 ) - 10.0;
-	}
+	var x = uniform( len, -10.0, 10.0, options );
+	var y = new Float64Array( len );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dcumaxabs/benchmark/c/benchmark.length.c
index a0b0a030c0ff..450fe7c72c10 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/benchmark/c/benchmark.length.c
+++ b/lib/node_modules/@stdlib/stats/base/dcumaxabs/benchmark/c/benchmark.length.c
@@ -94,7 +94,7 @@ static double rand_double( void ) {
 * @param len          array length
 * @return             elapsed time in seconds
 */
-static double benchmark( int iterations, int len ) {
+static double benchmark1( int iterations, int len ) {
 	double elapsed;
 	double x[ len ];
 	double y[ len ];
@@ -121,6 +121,40 @@ static double benchmark( int iterations, int len ) {
 	return elapsed;
 }
 
+/**
+* Runs a benchmark.
+*
+* @param iterations   number of iterations
+* @param len          array length
+* @return             elapsed time in seconds
+*/
+static double benchmark2( int iterations, int len ) {
+	double elapsed;
+	double x[ len ];
+	double y[ len ];
+	double t;
+	int i;
+
+	for ( i = 0; i < len; i++ ) {
+		x[ i ] = ( rand_double() * 20000.0 ) - 10000.0;
+		y[ i ] = 0.0;
+	}
+	t = tic();
+	for ( i = 0; i < iterations; i++ ) {
+		x[ 0 ] += 1.0;
+		stdlib_strided_dcumaxabs_ndarray( len, x, 1, 0, y, 1, 0 );
+		if ( y[ 0 ] != y[ 0 ] ) {
+			printf( "should not return NaN\n" );
+			break;
+		}
+	}
+	elapsed = tic() - t;
+	if ( y[ len-1 ] != y[ len-1 ] ) {
+		printf( "should not return NaN\n" );
+	}
+	return elapsed;
+}
+
 /**
 * Main execution sequence.
 */
@@ -143,7 +177,18 @@ int main( void ) {
 		for ( j = 0; j < REPEATS; j++ ) {
 			count += 1;
 			printf( "# c::%s:len=%d\n", NAME, len );
-			elapsed = benchmark( iter, len );
+			elapsed = benchmark1( iter, len );
+			print_results( iter, elapsed );
+			printf( "ok %d benchmark finished\n", count );
+		}
+	}
+	for ( i = MIN; i <= MAX; i++ ) {
+		len = pow( 10, i );
+		iter = ITERATIONS / pow( 10, i-1 );
+		for ( j = 0; j < REPEATS; j++ ) {
+			count += 1;
+			printf( "# c::%s:ndarray:len=%d\n", NAME, len );
+			elapsed = benchmark2( iter, len );
 			print_results( iter, elapsed );
 			printf( "ok %d benchmark finished\n", count );
 		}
diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dcumaxabs/docs/repl.txt
index a636769b4644..96d32d6dce5b 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/docs/repl.txt
+++ b/lib/node_modules/@stdlib/stats/base/dcumaxabs/docs/repl.txt
@@ -3,8 +3,8 @@
     Computes the cumulative maximum absolute value of double-precision floating-
     point strided array elements.
 
-    The `N` and `stride` parameters determine which elements in `x` and `y` are
-    accessed at runtime.
+    The `N` and stride parameters determine which elements in the strided arrays
+    are accessed at runtime.
 
     Indexing is relative to the first index. To introduce an offset, use a typed
     array view.
@@ -20,13 +20,13 @@
         Input array.
 
     strideX: integer
-        Index increment for `x`.
+        Stride Length for `x`.
 
     y: Float64Array
         Output array.
 
     strideY: integer
-        Index increment for `y`.
+        Stride Length for `y`.
 
     Returns
     -------
@@ -41,11 +41,10 @@
     > {{alias}}( x.length, x, 1, y, 1 )
     <Float64Array>[ 1.0, 2.0, 2.0 ]
 
-    // Using `N` and `stride` parameters:
+    // Using `N` and stride parameters:
     > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );
     > y = new {{alias:@stdlib/array/float64}}( x.length );
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > {{alias}}( N, x, 2, y, 2 )
+    > {{alias}}( 3, x, 2, y, 2 )
     <Float64Array>[ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ]
 
     // Using view offsets:
@@ -53,12 +52,12 @@
     > var y0 = new {{alias:@stdlib/array/float64}}( x0.length );
     > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );
     > var y1 = new {{alias:@stdlib/array/float64}}( y0.buffer, y0.BYTES_PER_ELEMENT*3 );
-    > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );
-    > {{alias}}( N, x1, 2, y1, 1 )
+    > {{alias}}( 3, x1, 2, y1, 1 )
     <Float64Array>[ 2.0, 2.0, 2.0 ]
     > y0
     <Float64Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]
 
+
 {{alias}}.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )
     Computes the cumulative maximum absolute value of double-precision floating-
     point strided array elements using alternative indexing semantics.
@@ -76,7 +75,7 @@
         Input array.
 
     strideX: integer
-        Index increment for `x`.
+        Stride Length for `x`.
 
     offsetX: integer
         Starting index for `x`.
@@ -85,7 +84,7 @@
         Output array.
 
     strideY: integer
-        Index increment for `y`.
+        Stride Length for `y`.
 
     offsetY: integer
         Starting index for `y`.
@@ -106,8 +105,7 @@
     // Advanced indexing:
     > x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );
     > y = new {{alias:@stdlib/array/float64}}( x.length );
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > {{alias}}.ndarray( N, x, 2, 1, y, -1, y.length-1 )
+    > {{alias}}.ndarray( 3, x, 2, 1, y, -1, y.length-1 )
     <Float64Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]
 
     See Also
diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dcumaxabs/examples/c/example.c
index 08a88e6495eb..64f4496175c8 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/examples/c/example.c
+++ b/lib/node_modules/@stdlib/stats/base/dcumaxabs/examples/c/example.c
@@ -17,27 +17,25 @@
 */
 
 #include "stdlib/stats/base/dcumaxabs.h"
-#include <stdint.h>
 #include <stdio.h>
-#include <inttypes.h>
 
 int main( void ) {
 	// Create strided arrays:
-	double x[] = { 1.0, 2.0, -3.0, 4.0, -5.0, 6.0, 7.0, 8.0 };
+	const double x[] = { 1.0, 2.0, -3.0, 4.0, -5.0, 6.0, 7.0, 8.0 };
 	double y[] = { 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 };
 
 	// Specify the number of elements:
-	int64_t N = 4;
+	const int N = 4;
 
 	// Specify stride lengths:
-	int64_t strideX = 2;
-	int64_t strideY = -2;
+	const int strideX = 2;
+	const int strideY = -2;
 
 	// Compute the cumulative maximum absolute value:
 	stdlib_strided_dcumaxabs( N, x, strideX, y, strideY );
 
 	// Print the result:
-	for ( int64_t i = 0; i < 8; i++ ) {
-		printf( "y[ %"PRId64" ] = %lf\n", i, y[ i ] );
+	for ( int i = 0; i < 8; i++ ) {
+		printf( "y[ %d ] = %lf\n", i, y[ i ] );
 	}
 }
diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/examples/index.js b/lib/node_modules/@stdlib/stats/base/dcumaxabs/examples/index.js
index b256fa90068d..112096e25a9e 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/examples/index.js
+++ b/lib/node_modules/@stdlib/stats/base/dcumaxabs/examples/index.js
@@ -18,21 +18,16 @@
 
 'use strict';
 
-var randu = require( '@stdlib/random/base/randu' );
-var round = require( '@stdlib/math/base/special/round' );
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
 var Float64Array = require( '@stdlib/array/float64' );
 var dcumaxabs = require( './../lib' );
 
-var y;
-var x;
-var i;
-
-x = new Float64Array( 10 );
-y = new Float64Array( x.length );
-for ( i = 0; i < x.length; i++ ) {
-	x[ i ] = round( (randu()*100.0) - 50.0 );
-}
+var x = discreteUniform( 10, -50, 50, {
+	'dtype': 'float64'
+});
 console.log( x );
+
+var y = new Float64Array( x.length );
 console.log( y );
 
 dcumaxabs( x.length, x, 1, y, -1 );
diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/include/stdlib/stats/base/dcumaxabs.h b/lib/node_modules/@stdlib/stats/base/dcumaxabs/include/stdlib/stats/base/dcumaxabs.h
index 2d243d91c3ac..4eccd4d7b119 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/include/stdlib/stats/base/dcumaxabs.h
+++ b/lib/node_modules/@stdlib/stats/base/dcumaxabs/include/stdlib/stats/base/dcumaxabs.h
@@ -19,7 +19,7 @@
 #ifndef STDLIB_STATS_BASE_DCUMAXABS_H
 #define STDLIB_STATS_BASE_DCUMAXABS_H
 
-#include <stdint.h>
+#include "stdlib/blas/base/shared.h"
 
 /*
 * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler.
@@ -31,7 +31,12 @@ extern "C" {
 /**
 * Computes the cumulative maximum absolute value of double-precision floating-point strided array elements.
 */
-void stdlib_strided_dcumaxabs( const int64_t N, const double *X, const int64_t strideX, double *Y, const int64_t strideY );
+void API_SUFFIX(stdlib_strided_dcumaxabs)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, double *Y, const CBLAS_INT strideY );
+
+/**
+* Computes the cumulative maximum absolute value of double-precision floating-point strided array elements using alternative indexing semantics.
+*/
+void API_SUFFIX(stdlib_strided_dcumaxabs_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, double *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY );
 
 #ifdef __cplusplus
 }
diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/lib/dcumaxabs.js b/lib/node_modules/@stdlib/stats/base/dcumaxabs/lib/dcumaxabs.js
index 68600c13c717..01fc61f72912 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/lib/dcumaxabs.js
+++ b/lib/node_modules/@stdlib/stats/base/dcumaxabs/lib/dcumaxabs.js
@@ -20,8 +20,8 @@
 
 // MODULES //
 
-var isnan = require( '@stdlib/math/base/assert/is-nan' );
-var abs = require( '@stdlib/math/base/special/abs' );
+var stride2offset = require( '@stdlib/strided/base/stride2offset' );
+var ndarray = require( './ndarray.js' );
 
 
 // MAIN //
@@ -47,52 +47,9 @@ var abs = require( '@stdlib/math/base/special/abs' );
 * // returns <Float64Array>[ 1.0, 2.0, 2.0 ]
 */
 function dcumaxabs( N, x, strideX, y, strideY ) {
-	var max;
-	var ix;
-	var iy;
-	var v;
-	var i;
-
-	if ( N <= 0 ) {
-		return y;
-	}
-	if ( strideX < 0 ) {
-		ix = (1-N) * strideX;
-	} else {
-		ix = 0;
-	}
-	if ( strideY < 0 ) {
-		iy = (1-N) * strideY;
-	} else {
-		iy = 0;
-	}
-	max = abs( x[ ix ] );
-	y[ iy ] = max;
-
-	iy += strideY;
-	i = 1;
-	if ( isnan( max ) === false ) {
-		for ( i; i < N; i++ ) {
-			ix += strideX;
-			v = abs( x[ ix ] );
-			if ( isnan( v ) ) {
-				max = v;
-				break;
-			}
-			if ( v > max ) {
-				max = v;
-			}
-			y[ iy ] = max;
-			iy += strideY;
-		}
-	}
-	if ( isnan( max ) ) {
-		for ( i; i < N; i++ ) {
-			y[ iy ] = max;
-			iy += strideY;
-		}
-	}
-	return y;
+	var ox = stride2offset( N, strideX );
+	var oy = stride2offset( N, strideY );
+	return ndarray( N, x, strideX, ox, y, strideY, oy );
 }
 
 
diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/lib/dcumaxabs.native.js b/lib/node_modules/@stdlib/stats/base/dcumaxabs/lib/dcumaxabs.native.js
index d5b5bd45a3b4..6948472d98a5 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/lib/dcumaxabs.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dcumaxabs/lib/dcumaxabs.native.js
@@ -40,9 +40,8 @@ var addon = require( './../src/addon.node' );
 *
 * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );
 * var y = new Float64Array( x.length );
-* var N = x.length;
 *
-* var v = dcumaxabs( N, x, 1, y, 1 );
+* var v = dcumaxabs( x.length, x, 1, y, 1 );
 * // returns <Float64Array>[ 1.0, 2.0, 2.0 ]
 */
 function dcumaxabs( N, x, strideX, y, strideY ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/lib/index.js b/lib/node_modules/@stdlib/stats/base/dcumaxabs/lib/index.js
index c58d8b9ff1f5..d789be726cb3 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/lib/index.js
+++ b/lib/node_modules/@stdlib/stats/base/dcumaxabs/lib/index.js
@@ -29,21 +29,18 @@
 *
 * var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );
 * var y = new Float64Array( x.length );
-* var N = x.length;
 *
-* dcumaxabs( N, x, 1, y, 1 );
+* dcumaxabs( x.length, x, 1, y, 1 );
 * // y => <Float64Array>[ 1.0, 2.0, 2.0 ]
 *
 * @example
 * var Float64Array = require( '@stdlib/array/float64' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 * var dcumaxabs = require( '@stdlib/stats/base/dcumaxabs' );
 *
 * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
 * var y = new Float64Array( x.length );
-* var N = floor( x.length / 2 );
 *
-* dcumaxabs.ndarray( N, x, 2, 1, y, 1, 0 );
+* dcumaxabs.ndarray( 4, x, 2, 1, y, 1, 0 );
 * // y => <Float64Array>[ 1.0, 2.0, 2.0, 4.0, 0.0, 0.0, 0.0, 0.0 ]
 */
 
diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/dcumaxabs/lib/ndarray.js
index c3199145be6d..3aa253e7995b 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/lib/ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/dcumaxabs/lib/ndarray.js
@@ -40,13 +40,11 @@ var abs = require( '@stdlib/math/base/special/abs' );
 *
 * @example
 * var Float64Array = require( '@stdlib/array/float64' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 *
 * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
 * var y = new Float64Array( x.length );
-* var N = floor( x.length / 2 );
 *
-* var v = dcumaxabs( N, x, 2, 1, y, 1, 0 );
+* var v = dcumaxabs( 4, x, 2, 1, y, 1, 0 );
 * // returns <Float64Array>[ 1.0, 2.0, 2.0, 4.0, 0.0, 0.0, 0.0, 0.0 ]
 */
 function dcumaxabs( N, x, strideX, offsetX, y, strideY, offsetY ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dcumaxabs/lib/ndarray.native.js
index c2fe95eb62bd..960146df5f94 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/lib/ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dcumaxabs/lib/ndarray.native.js
@@ -20,8 +20,7 @@
 
 // MODULES //
 
-var Float64Array = require( '@stdlib/array/float64' );
-var addon = require( './dcumaxabs.native.js' );
+var addon = require( './../src/addon.node' );
 
 
 // MAIN //
@@ -40,27 +39,15 @@ var addon = require( './dcumaxabs.native.js' );
 *
 * @example
 * var Float64Array = require( '@stdlib/array/float64' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 *
 * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
 * var y = new Float64Array( x.length );
-* var N = floor( x.length / 2 );
 *
-* var v = dcumaxabs( N, x, 2, 1, y, 1, 0 );
+* var v = dcumaxabs( 4, x, 2, 1, y, 1, 0 );
 * // returns <Float64Array>[ 1.0, 2.0, 2.0, 4.0, 0.0, 0.0, 0.0, 0.0 ]
 */
 function dcumaxabs( N, x, strideX, offsetX, y, strideY, offsetY ) {
-	var viewX;
-	var viewY;
-	if ( strideX < 0 ) {
-		offsetX += (N-1) * strideX;
-	}
-	if ( strideY < 0 ) {
-		offsetY += (N-1) * strideY;
-	}
-	viewX = new Float64Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offsetX), x.length-offsetX ); // eslint-disable-line max-len
-	viewY = new Float64Array( y.buffer, y.byteOffset+(y.BYTES_PER_ELEMENT*offsetY), y.length-offsetY ); // eslint-disable-line max-len
-	addon( N, viewX, strideX, viewY, strideY );
+	addon.ndarray( N, x, strideX, offsetX, y, strideY, offsetY );
 	return y;
 }
 
diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/manifest.json b/lib/node_modules/@stdlib/stats/base/dcumaxabs/manifest.json
index 25901c023456..39b3db80d9d8 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/manifest.json
+++ b/lib/node_modules/@stdlib/stats/base/dcumaxabs/manifest.json
@@ -1,6 +1,7 @@
 {
   "options": {
-    "task": "build"
+    "task": "build",
+    "wasm": false
   },
   "fields": [
     {
@@ -27,18 +28,20 @@
   "confs": [
     {
       "task": "build",
+      "wasm": false,
       "src": [
-        "./src/dcumaxabs.c"
+        "./src/main.c"
       ],
       "include": [
         "./include"
       ],
-      "libraries": [
-        "-lm"
-      ],
+      "libraries": [],
       "libpath": [],
       "dependencies": [
         "@stdlib/math/base/assert/is-nan",
+        "@stdlib/blas/base/shared",
+        "@stdlib/math/base/special/abs",
+        "@stdlib/strided/base/stride2offset",
         "@stdlib/napi/export",
         "@stdlib/napi/argv",
         "@stdlib/napi/argv-int64",
@@ -47,34 +50,56 @@
     },
     {
       "task": "benchmark",
+      "wasm": false,
       "src": [
-        "./src/dcumaxabs.c"
+        "./src/main.c"
       ],
       "include": [
         "./include"
       ],
-      "libraries": [
-        "-lm"
-      ],
+      "libraries": [],
       "libpath": [],
       "dependencies": [
-        "@stdlib/math/base/assert/is-nan"
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset",
+        "@stdlib/math/base/assert/is-nan",
+        "@stdlib/math/base/special/abs"
       ]
     },
     {
       "task": "examples",
+      "wasm": false,
       "src": [
-        "./src/dcumaxabs.c"
+        "./src/main.c"
       ],
       "include": [
         "./include"
       ],
-      "libraries": [
-        "-lm"
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset",
+        "@stdlib/math/base/assert/is-nan",
+        "@stdlib/math/base/special/abs"
+      ]
+    },
+    {
+      "task": "",
+      "wasm": true,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
       ],
+      "libraries": [],
       "libpath": [],
       "dependencies": [
-        "@stdlib/math/base/assert/is-nan"
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset",
+        "@stdlib/math/base/assert/is-nan",
+        "@stdlib/math/base/special/abs"
       ]
     }
   ]
diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/src/addon.c b/lib/node_modules/@stdlib/stats/base/dcumaxabs/src/addon.c
index 7d4b140b720d..15a6c35932dc 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/src/addon.c
+++ b/lib/node_modules/@stdlib/stats/base/dcumaxabs/src/addon.c
@@ -41,4 +41,24 @@ static napi_value addon( napi_env env, napi_callback_info info ) {
 	return NULL;
 }
 
-STDLIB_NAPI_MODULE_EXPORT_FCN( addon )
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon_method( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 7 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 );
+	STDLIB_NAPI_ARGV_INT64( env, strideY, argv, 5 );
+	STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 );
+	STDLIB_NAPI_ARGV_INT64( env, offsetY, argv, 6 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, Y, N, strideY, argv, 4 );
+	stdlib_strided_dcumaxabs_ndarray( N, X, strideX, offsetX, Y, strideY, offsetY );
+	return NULL;
+}
+
+STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method )
diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/src/dcumaxabs.c b/lib/node_modules/@stdlib/stats/base/dcumaxabs/src/main.c
similarity index 53%
rename from lib/node_modules/@stdlib/stats/base/dcumaxabs/src/dcumaxabs.c
rename to lib/node_modules/@stdlib/stats/base/dcumaxabs/src/main.c
index ea4beb7588d7..a42df2832336 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/src/dcumaxabs.c
+++ b/lib/node_modules/@stdlib/stats/base/dcumaxabs/src/main.c
@@ -18,8 +18,9 @@
 
 #include "stdlib/stats/base/dcumaxabs.h"
 #include "stdlib/math/base/assert/is_nan.h"
-#include <stdint.h>
-#include <math.h>
+#include "stdlib/math/base/special/abs.h"
+#include "stdlib/blas/base/shared.h"
+#include "stdlib/strided/base/stride2offset.h"
 
 /**
 * Computes the cumulative maximum absolute value of double-precision floating-point strided array elements.
@@ -30,27 +31,37 @@
 * @param Y        output array
 * @param strideY  Y stride length
 */
-void stdlib_strided_dcumaxabs( const int64_t N, const double *X, const int64_t strideX, double *Y, const int64_t strideY ) {
+void API_SUFFIX(stdlib_strided_dcumaxabs)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, double *Y, const CBLAS_INT strideY ) {
+	const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX );
+	const CBLAS_INT oy = stdlib_strided_stride2offset( N, strideY );
+	API_SUFFIX(stdlib_strided_dcumaxabs_ndarray)( N, X, strideX, ox, Y, strideY, oy );
+	return;
+}
+
+/**
+* Computes the cumulative maximum absolute value of double-precision floating-point strided array elements using alternative indexing semantics.
+*
+* @param N        number of indexed elements
+* @param X        input array
+* @param strideX  X stride length
+* @param offsetX  starting index for X
+* @param Y        output array
+* @param strideY  Y stride length
+* @param offsetY  starting index for Y
+*/
+void API_SUFFIX(stdlib_strided_dcumaxabs_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, double *Y, const CBLAS_INT strideY, const CBLAS_INT offsetY ) {
+	CBLAS_INT ix;
+	CBLAS_INT iy;
+	CBLAS_INT i;
 	double max;
-	int64_t ix;
-	int64_t iy;
-	int64_t i;
 	double v;
 
 	if ( N <= 0 ) {
 		return;
 	}
-	if ( strideX < 0 ) {
-		ix = (1-N) * strideX;
-	} else {
-		ix = 0;
-	}
-	if ( strideY < 0 ) {
-		iy = (1-N) * strideY;
-	} else {
-		iy = 0;
-	}
-	max = fabs( X[ ix ] );
+	ix = offsetX;
+	iy = offsetY;
+	max = stdlib_base_abs( X[ ix ] );
 	Y[ iy ] = max;
 
 	iy += strideY;
@@ -58,7 +69,7 @@ void stdlib_strided_dcumaxabs( const int64_t N, const double *X, const int64_t s
 	if ( !stdlib_base_is_nan( max ) ) {
 		for (; i < N; i++ ) {
 			ix += strideX;
-			v = fabs( X[ ix ] );
+			v = stdlib_base_abs( X[ ix ] );
 			if ( stdlib_base_is_nan( v ) ) {
 				max = v;
 				break;
diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/test/test.dcumaxabs.js b/lib/node_modules/@stdlib/stats/base/dcumaxabs/test/test.dcumaxabs.js
index a34eec63dc72..dfcf306b1349 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/test/test.dcumaxabs.js
+++ b/lib/node_modules/@stdlib/stats/base/dcumaxabs/test/test.dcumaxabs.js
@@ -21,7 +21,6 @@
 // MODULES //
 
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' );
 var Float64Array = require( '@stdlib/array/float64' );
@@ -150,7 +149,6 @@ tape( 'the function supports an `x` stride', function test( t ) {
 	var expected;
 	var x;
 	var y;
-	var N;
 
 	x = new Float64Array([
 		1.0,  // 0
@@ -166,9 +164,8 @@ tape( 'the function supports an `x` stride', function test( t ) {
 		0.0,
 		0.0
 	]);
-	N = 3;
 
-	dcumaxabs( N, x, 2, y, 1 );
+	dcumaxabs( 3, x, 2, y, 1 );
 
 	expected = new Float64Array( [ 1.0, 3.0, 5.0, 0.0, 0.0 ] );
 	t.deepEqual( y, expected, 'returns expected value' );
@@ -180,7 +177,6 @@ tape( 'the function supports a `y` stride', function test( t ) {
 	var expected;
 	var x;
 	var y;
-	var N;
 
 	x = new Float64Array([
 		1.0,  // 0
@@ -196,9 +192,8 @@ tape( 'the function supports a `y` stride', function test( t ) {
 		0.0,
 		0.0  // 2
 	]);
-	N = 3;
 
-	dcumaxabs( N, x, 1, y, 2 );
+	dcumaxabs( 3, x, 1, y, 2 );
 
 	expected = new Float64Array( [ 1.0, 0.0, 2.0, 0.0, 3.0 ] );
 	t.deepEqual( y, expected, 'returns expected value' );
@@ -210,7 +205,6 @@ tape( 'the function supports negative strides', function test( t ) {
 	var expected;
 	var x;
 	var y;
-	var N;
 
 	x = new Float64Array([
 		1.0,  // 2
@@ -226,9 +220,8 @@ tape( 'the function supports negative strides', function test( t ) {
 		0.0,
 		0.0
 	]);
-	N = 3;
 
-	dcumaxabs( N, x, -2, y, -1 );
+	dcumaxabs( 3, x, -2, y, -1 );
 
 	expected = new Float64Array( [ 5.0, 5.0, 5.0, 0.0, 0.0 ] );
 	t.deepEqual( y, expected, 'returns expected value' );
@@ -240,7 +233,6 @@ tape( 'the function supports complex access patterns', function test( t ) {
 	var expected;
 	var x;
 	var y;
-	var N;
 
 	x = new Float64Array([
 		1.0,  // 0
@@ -258,9 +250,8 @@ tape( 'the function supports complex access patterns', function test( t ) {
 		0.0,
 		0.0
 	]);
-	N = 3;
 
-	dcumaxabs( N, x, 2, y, -1 );
+	dcumaxabs( 3, x, 2, y, -1 );
 
 	expected = new Float64Array( [ 5.0, 3.0, 1.0, 0.0, 0.0, 0.0 ] );
 	t.deepEqual( y, expected, 'returns expected value' );
@@ -274,7 +265,6 @@ tape( 'the function supports view offsets', function test( t ) {
 	var y0;
 	var x1;
 	var y1;
-	var N;
 
 	// Initial arrays...
 	x0 = new Float64Array([
@@ -298,9 +288,7 @@ tape( 'the function supports view offsets', function test( t ) {
 	x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element
 	y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // begin at the 4th element
 
-	N = floor( x0.length / 2 );
-
-	dcumaxabs( N, x1, -2, y1, 1 );
+	dcumaxabs( 3, x1, -2, y1, 1 );
 	expected = new Float64Array( [ 0.0, 0.0, 0.0, 6.0, 6.0, 6.0 ] );
 
 	t.deepEqual( y0, expected, 'returns expected value' );
diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/test/test.dcumaxabs.native.js b/lib/node_modules/@stdlib/stats/base/dcumaxabs/test/test.dcumaxabs.native.js
index b51b3dcbc763..89eddb305f9d 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/test/test.dcumaxabs.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dcumaxabs/test/test.dcumaxabs.native.js
@@ -22,7 +22,6 @@
 
 var resolve = require( 'path' ).resolve;
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' );
 var Float64Array = require( '@stdlib/array/float64' );
@@ -159,7 +158,6 @@ tape( 'the function supports an `x` stride', opts, function test( t ) {
 	var expected;
 	var x;
 	var y;
-	var N;
 
 	x = new Float64Array([
 		1.0,  // 0
@@ -175,9 +173,8 @@ tape( 'the function supports an `x` stride', opts, function test( t ) {
 		0.0,
 		0.0
 	]);
-	N = 3;
 
-	dcumaxabs( N, x, 2, y, 1 );
+	dcumaxabs( 3, x, 2, y, 1 );
 
 	expected = new Float64Array( [ 1.0, 3.0, 5.0, 0.0, 0.0 ] );
 	t.deepEqual( y, expected, 'returns expected value' );
@@ -189,7 +186,6 @@ tape( 'the function supports a `y` stride', opts, function test( t ) {
 	var expected;
 	var x;
 	var y;
-	var N;
 
 	x = new Float64Array([
 		1.0,  // 0
@@ -205,9 +201,8 @@ tape( 'the function supports a `y` stride', opts, function test( t ) {
 		0.0,
 		0.0  // 2
 	]);
-	N = 3;
 
-	dcumaxabs( N, x, 1, y, 2 );
+	dcumaxabs( 3, x, 1, y, 2 );
 
 	expected = new Float64Array( [ 1.0, 0.0, 2.0, 0.0, 3.0 ] );
 	t.deepEqual( y, expected, 'returns expected value' );
@@ -219,7 +214,6 @@ tape( 'the function supports negative strides', opts, function test( t ) {
 	var expected;
 	var x;
 	var y;
-	var N;
 
 	x = new Float64Array([
 		1.0,  // 2
@@ -235,9 +229,8 @@ tape( 'the function supports negative strides', opts, function test( t ) {
 		0.0,
 		0.0
 	]);
-	N = 3;
 
-	dcumaxabs( N, x, -2, y, -1 );
+	dcumaxabs( 3, x, -2, y, -1 );
 
 	expected = new Float64Array( [ 5.0, 5.0, 5.0, 0.0, 0.0 ] );
 	t.deepEqual( y, expected, 'returns expected value' );
@@ -249,7 +242,6 @@ tape( 'the function supports complex access patterns', opts, function test( t )
 	var expected;
 	var x;
 	var y;
-	var N;
 
 	x = new Float64Array([
 		1.0,  // 0
@@ -267,9 +259,8 @@ tape( 'the function supports complex access patterns', opts, function test( t )
 		0.0,
 		0.0
 	]);
-	N = 3;
 
-	dcumaxabs( N, x, 2, y, -1 );
+	dcumaxabs( 3, x, 2, y, -1 );
 
 	expected = new Float64Array( [ 5.0, 3.0, 1.0, 0.0, 0.0, 0.0 ] );
 	t.deepEqual( y, expected, 'returns expected value' );
@@ -283,7 +274,6 @@ tape( 'the function supports view offsets', opts, function test( t ) {
 	var y0;
 	var x1;
 	var y1;
-	var N;
 
 	// Initial arrays...
 	x0 = new Float64Array([
@@ -307,9 +297,7 @@ tape( 'the function supports view offsets', opts, function test( t ) {
 	x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // begin at 2nd element
 	y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // begin at the 4th element
 
-	N = floor( x0.length / 2 );
-
-	dcumaxabs( N, x1, -2, y1, 1 );
+	dcumaxabs( 3, x1, -2, y1, 1 );
 	expected = new Float64Array( [ 0.0, 0.0, 0.0, 6.0, 6.0, 6.0 ] );
 
 	t.deepEqual( y0, expected, 'returns expected value' );
diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dcumaxabs/test/test.ndarray.js
index 64557c688973..9ad6bb70ddca 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/test/test.ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/dcumaxabs/test/test.ndarray.js
@@ -21,7 +21,6 @@
 // MODULES //
 
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' );
 var Float64Array = require( '@stdlib/array/float64' );
@@ -150,7 +149,6 @@ tape( 'the function supports an `x` stride', function test( t ) {
 	var expected;
 	var x;
 	var y;
-	var N;
 
 	x = new Float64Array([
 		1.0,  // 0
@@ -166,9 +164,8 @@ tape( 'the function supports an `x` stride', function test( t ) {
 		0.0,
 		0.0
 	]);
-	N = 3;
 
-	dcumaxabs( N, x, 2, 0, y, 1, 0 );
+	dcumaxabs( 3, x, 2, 0, y, 1, 0 );
 
 	expected = new Float64Array( [ 1.0, 3.0, 5.0, 0.0, 0.0 ] );
 	t.deepEqual( y, expected, 'returns expected value' );
@@ -180,7 +177,6 @@ tape( 'the function supports a `y` stride', function test( t ) {
 	var expected;
 	var x;
 	var y;
-	var N;
 
 	x = new Float64Array([
 		1.0,  // 0
@@ -196,9 +192,8 @@ tape( 'the function supports a `y` stride', function test( t ) {
 		0.0,
 		0.0  // 2
 	]);
-	N = 3;
 
-	dcumaxabs( N, x, 1, 0, y, 2, 0 );
+	dcumaxabs( 3, x, 1, 0, y, 2, 0 );
 
 	expected = new Float64Array( [ 1.0, 0.0, 2.0, 0.0, 3.0 ] );
 	t.deepEqual( y, expected, 'returns expected value' );
@@ -210,7 +205,6 @@ tape( 'the function supports negative strides', function test( t ) {
 	var expected;
 	var x;
 	var y;
-	var N;
 
 	x = new Float64Array([
 		1.0,  // 2
@@ -226,9 +220,8 @@ tape( 'the function supports negative strides', function test( t ) {
 		0.0,
 		0.0
 	]);
-	N = 3;
 
-	dcumaxabs( N, x, -2, x.length-1, y, -1, 2 );
+	dcumaxabs( 3, x, -2, x.length-1, y, -1, 2 );
 
 	expected = new Float64Array( [ 5.0, 5.0, 5.0, 0.0, 0.0 ] );
 	t.deepEqual( y, expected, 'returns expected value' );
@@ -238,7 +231,6 @@ tape( 'the function supports negative strides', function test( t ) {
 
 tape( 'the function supports an `x` offset', function test( t ) {
 	var expected;
-	var N;
 	var x;
 	var y;
 
@@ -262,9 +254,8 @@ tape( 'the function supports an `x` offset', function test( t ) {
 		0.0,
 		0.0
 	]);
-	N = floor( x.length / 2 );
 
-	dcumaxabs( N, x, 2, 1, y, 1, 0 );
+	dcumaxabs( 4, x, 2, 1, y, 1, 0 );
 
 	expected = new Float64Array( [ 1.0, 2.0, 2.0, 4.0, 0.0, 0.0, 0.0, 0.0 ] );
 	t.deepEqual( y, expected, 'returns expected value' );
@@ -274,7 +265,6 @@ tape( 'the function supports an `x` offset', function test( t ) {
 
 tape( 'the function supports a `y` offset', function test( t ) {
 	var expected;
-	var N;
 	var x;
 	var y;
 
@@ -298,9 +288,8 @@ tape( 'the function supports a `y` offset', function test( t ) {
 		0.0,
 		0.0  // 3
 	]);
-	N = floor( x.length / 2 );
 
-	dcumaxabs( N, x, 1, 0, y, 2, 1 );
+	dcumaxabs( 4, x, 1, 0, y, 2, 1 );
 
 	expected = new Float64Array( [ 0.0, 2.0, 0.0, 2.0, 0.0, 2.0, 0.0, 2.0 ] );
 	t.deepEqual( y, expected, 'returns expected value' );
@@ -312,7 +301,6 @@ tape( 'the function supports complex access patterns', function test( t ) {
 	var expected;
 	var x;
 	var y;
-	var N;
 
 	x = new Float64Array([
 		1.0,  // 0
@@ -330,9 +318,8 @@ tape( 'the function supports complex access patterns', function test( t ) {
 		0.0,
 		0.0
 	]);
-	N = 3;
 
-	dcumaxabs( N, x, 2, 0, y, -1, 2 );
+	dcumaxabs( 3, x, 2, 0, y, -1, 2 );
 
 	expected = new Float64Array( [ 5.0, 3.0, 1.0, 0.0, 0.0, 0.0 ] );
 	t.deepEqual( y, expected, 'returns expected value' );
diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dcumaxabs/test/test.ndarray.native.js
index 0d41b8102f5c..bed988d18cc8 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/test/test.ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dcumaxabs/test/test.ndarray.native.js
@@ -22,7 +22,6 @@
 
 var resolve = require( 'path' ).resolve;
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var isPositiveZero = require( '@stdlib/math/base/assert/is-positive-zero' );
 var Float64Array = require( '@stdlib/array/float64' );
@@ -159,7 +158,6 @@ tape( 'the function supports an `x` stride', opts, function test( t ) {
 	var expected;
 	var x;
 	var y;
-	var N;
 
 	x = new Float64Array([
 		1.0,  // 0
@@ -175,9 +173,8 @@ tape( 'the function supports an `x` stride', opts, function test( t ) {
 		0.0,
 		0.0
 	]);
-	N = 3;
 
-	dcumaxabs( N, x, 2, 0, y, 1, 0 );
+	dcumaxabs( 3, x, 2, 0, y, 1, 0 );
 
 	expected = new Float64Array( [ 1.0, 3.0, 5.0, 0.0, 0.0 ] );
 	t.deepEqual( y, expected, 'returns expected value' );
@@ -189,7 +186,6 @@ tape( 'the function supports a `y` stride', opts, function test( t ) {
 	var expected;
 	var x;
 	var y;
-	var N;
 
 	x = new Float64Array([
 		1.0,  // 0
@@ -205,9 +201,8 @@ tape( 'the function supports a `y` stride', opts, function test( t ) {
 		0.0,
 		0.0  // 2
 	]);
-	N = 3;
 
-	dcumaxabs( N, x, 1, 0, y, 2, 0 );
+	dcumaxabs( 3, x, 1, 0, y, 2, 0 );
 
 	expected = new Float64Array( [ 1.0, 0.0, 2.0, 0.0, 3.0 ] );
 	t.deepEqual( y, expected, 'returns expected value' );
@@ -219,7 +214,6 @@ tape( 'the function supports negative strides', opts, function test( t ) {
 	var expected;
 	var x;
 	var y;
-	var N;
 
 	x = new Float64Array([
 		1.0,  // 2
@@ -235,9 +229,8 @@ tape( 'the function supports negative strides', opts, function test( t ) {
 		0.0,
 		0.0
 	]);
-	N = 3;
 
-	dcumaxabs( N, x, -2, x.length-1, y, -1, 2 );
+	dcumaxabs( 3, x, -2, x.length-1, y, -1, 2 );
 
 	expected = new Float64Array( [ 5.0, 5.0, 5.0, 0.0, 0.0 ] );
 	t.deepEqual( y, expected, 'returns expected value' );
@@ -247,7 +240,6 @@ tape( 'the function supports negative strides', opts, function test( t ) {
 
 tape( 'the function supports an `x` offset', opts, function test( t ) {
 	var expected;
-	var N;
 	var x;
 	var y;
 
@@ -271,9 +263,8 @@ tape( 'the function supports an `x` offset', opts, function test( t ) {
 		0.0,
 		0.0
 	]);
-	N = floor( x.length / 2 );
 
-	dcumaxabs( N, x, 2, 1, y, 1, 0 );
+	dcumaxabs( 4, x, 2, 1, y, 1, 0 );
 
 	expected = new Float64Array( [ 1.0, 2.0, 2.0, 4.0, 0.0, 0.0, 0.0, 0.0 ] );
 	t.deepEqual( y, expected, 'returns expected value' );
@@ -283,7 +274,6 @@ tape( 'the function supports an `x` offset', opts, function test( t ) {
 
 tape( 'the function supports a `y` offset', opts, function test( t ) {
 	var expected;
-	var N;
 	var x;
 	var y;
 
@@ -307,9 +297,8 @@ tape( 'the function supports a `y` offset', opts, function test( t ) {
 		0.0,
 		0.0  // 3
 	]);
-	N = floor( x.length / 2 );
 
-	dcumaxabs( N, x, 1, 0, y, 2, 1 );
+	dcumaxabs( 4, x, 1, 0, y, 2, 1 );
 
 	expected = new Float64Array( [ 0.0, 2.0, 0.0, 2.0, 0.0, 2.0, 0.0, 2.0 ] );
 	t.deepEqual( y, expected, 'returns expected value' );

From 7d53e6dbba0aa699e03b945ecfeb837d46eaa754 Mon Sep 17 00:00:00 2001
From: Philipp Burckhardt <pburckhardt@outlook.com>
Date: Thu, 2 Jan 2025 19:52:39 -0500
Subject: [PATCH 33/87] build: do not set custom GitHub token

---
type: pre_commit_static_analysis_report
description: Results of running static analysis checks when committing changes.
report:
  - task: lint_filenames
    status: passed
  - task: lint_editorconfig
    status: passed
  - task: lint_markdown
    status: na
  - task: lint_package_json
    status: na
  - task: lint_repl_help
    status: na
  - task: lint_javascript_src
    status: na
  - task: lint_javascript_cli
    status: na
  - task: lint_javascript_examples
    status: na
  - task: lint_javascript_tests
    status: na
  - task: lint_javascript_benchmarks
    status: na
  - task: lint_python
    status: na
  - task: lint_r
    status: na
  - task: lint_c_src
    status: na
  - task: lint_c_examples
    status: na
  - task: lint_c_benchmarks
    status: na
  - task: lint_c_tests_fixtures
    status: na
  - task: lint_shell
    status: na
  - task: lint_typescript_declarations
    status: na
  - task: lint_typescript_tests
    status: na
  - task: lint_license_headers
    status: passed
---
---
 .github/workflows/labeler_needs_changes.yml | 1 -
 1 file changed, 1 deletion(-)

diff --git a/.github/workflows/labeler_needs_changes.yml b/.github/workflows/labeler_needs_changes.yml
index f9d1f055af0f..5f92960a9441 100644
--- a/.github/workflows/labeler_needs_changes.yml
+++ b/.github/workflows/labeler_needs_changes.yml
@@ -52,7 +52,6 @@ jobs:
         # Pin action to a known commit SHA for reproducibility:
         uses: actions/github-script@60a0d83039c74a4aee543508d2ffcb1c3799cdea # v7.0.1
         with:
-          github-token: ${{ secrets.CHATBOT_GITHUB_TOKEN }}
           script: |
             await github.rest.issues.addLabels({
               'owner': context.repo.owner,

From b0858add9933b1317daed58eda23c18c914db5bd Mon Sep 17 00:00:00 2001
From: Philipp Burckhardt <pburckhardt@outlook.com>
Date: Thu, 2 Jan 2025 20:01:43 -0500
Subject: [PATCH 34/87] docs: add missing spaces

---
type: pre_push_report
description: Results of running various checks prior to pushing changes.
report:
  - task: run_javascript_examples
    status: na
  - task: run_c_examples
    status: na
  - task: run_cpp_examples
    status: na
  - task: run_javascript_readme_examples
    status: failed
---
---
 lib/node_modules/@stdlib/stats/base/dcumaxabs/README.md | 2 +-
 lib/node_modules/@stdlib/stats/base/dcumin/README.md    | 2 +-
 lib/node_modules/@stdlib/stats/base/dcuminabs/README.md | 2 +-
 lib/node_modules/@stdlib/stats/base/scumax/README.md    | 2 +-
 4 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/README.md b/lib/node_modules/@stdlib/stats/base/dcumaxabs/README.md
index a8a279cf07dd..19c1b234d41d 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/README.md
+++ b/lib/node_modules/@stdlib/stats/base/dcumaxabs/README.md
@@ -210,7 +210,7 @@ The function accepts the following arguments:
 void stdlib_strided_dcumaxabs( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, double *Y, const CBLAS_INT strideY );
 ```
 
-#### stdlib_strided_dcumaxabs_ndarray(N, \*X, strideX, offsetX, \*Y, strideY, offsetY )
+#### stdlib_strided_dcumaxabs_ndarray( N, \*X, strideX, offsetX, \*Y, strideY, offsetY )
 
 Computes the cumulative maximum absolute value of double-precision floating-point strided array elements using alternative indexing semantics.
 
diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/README.md b/lib/node_modules/@stdlib/stats/base/dcumin/README.md
index 09feee29d6da..258fa0c21395 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumin/README.md
+++ b/lib/node_modules/@stdlib/stats/base/dcumin/README.md
@@ -210,7 +210,7 @@ The function accepts the following arguments:
 void stdlib_strided_dcumin( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, double *Y, const CBLAS_INT strideY );
 ```
 
-#### stdlib_strided_dcumin_ndarray(N, \*X, strideX, offsetX, \*Y, strideY, offsetY )
+#### stdlib_strided_dcumin_ndarray( N, \*X, strideX, offsetX, \*Y, strideY, offsetY )
 
 Computes the cumulative minimum of double-precision floating-point strided array elements using alternative indexing semantics.
 
diff --git a/lib/node_modules/@stdlib/stats/base/dcuminabs/README.md b/lib/node_modules/@stdlib/stats/base/dcuminabs/README.md
index ff669586b30e..064468679078 100644
--- a/lib/node_modules/@stdlib/stats/base/dcuminabs/README.md
+++ b/lib/node_modules/@stdlib/stats/base/dcuminabs/README.md
@@ -210,7 +210,7 @@ The function accepts the following arguments:
 void stdlib_strided_dcuminabs( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, double *Y, const CBLAS_INT strideY );
 ```
 
-#### stdlib_strided_dcuminabs_ndarray(N, \*X, strideX, offsetX, \*Y, strideY, offsetY)
+#### stdlib_strided_dcuminabs_ndarray( N, \*X, strideX, offsetX, \*Y, strideY, offsetY )
 
 Computes the cumulative minumum absolute value of double-precision floating-point strided array elements using alternative indexing semantics.
 
diff --git a/lib/node_modules/@stdlib/stats/base/scumax/README.md b/lib/node_modules/@stdlib/stats/base/scumax/README.md
index eb5b8c3c6687..dc2b120de152 100644
--- a/lib/node_modules/@stdlib/stats/base/scumax/README.md
+++ b/lib/node_modules/@stdlib/stats/base/scumax/README.md
@@ -210,7 +210,7 @@ The function accepts the following arguments:
 void stdlib_strided_scumax( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, float *Y, const CBLAS_INT strideY );
 ```
 
-#### stdlib_strided_scumax_ndarray(N, \*X, strideX, offsetX, \*Y, strideY, offsetY)
+#### stdlib_strided_scumax_ndarray( N, \*X, strideX, offsetX, \*Y, strideY, offsetY )
 
 Computes the cumulative maximum of single-precision floating-point strided array elements using alternative indexing semantics.
 

From 176eef861a14a73805cb88c125cdedd08cde9cff Mon Sep 17 00:00:00 2001
From: Philipp Burckhardt <pburckhardt@outlook.com>
Date: Thu, 2 Jan 2025 20:24:55 -0500
Subject: [PATCH 35/87] chore: disable lint rule

---
type: pre_commit_static_analysis_report
description: Results of running static analysis checks when committing changes.
report:
  - task: lint_filenames
    status: passed
  - task: lint_editorconfig
    status: passed
  - task: lint_markdown
    status: passed
  - task: lint_package_json
    status: na
  - task: lint_repl_help
    status: na
  - task: lint_javascript_src
    status: na
  - task: lint_javascript_cli
    status: na
  - task: lint_javascript_examples
    status: na
  - task: lint_javascript_tests
    status: na
  - task: lint_javascript_benchmarks
    status: na
  - task: lint_python
    status: na
  - task: lint_r
    status: na
  - task: lint_c_src
    status: na
  - task: lint_c_examples
    status: na
  - task: lint_c_benchmarks
    status: na
  - task: lint_c_tests_fixtures
    status: na
  - task: lint_shell
    status: na
  - task: lint_typescript_declarations
    status: na
  - task: lint_typescript_tests
    status: na
  - task: lint_license_headers
    status: passed
---

---
type: pre_push_report
description: Results of running various checks prior to pushing changes.
report:
  - task: run_javascript_examples
    status: na
  - task: run_c_examples
    status: na
  - task: run_cpp_examples
    status: na
  - task: run_javascript_readme_examples
    status: passed
  - task: run_c_benchmarks
    status: na
  - task: run_cpp_benchmarks
    status: na
  - task: run_fortran_benchmarks
    status: na
  - task: run_javascript_benchmarks
    status: na
  - task: run_julia_benchmarks
    status: na
  - task: run_python_benchmarks
    status: na
  - task: run_r_benchmarks
    status: na
  - task: run_javascript_tests
    status: na
---
---
 lib/node_modules/@stdlib/stats/base/dcumaxabs/README.md | 2 ++
 lib/node_modules/@stdlib/stats/base/dcumin/README.md    | 2 ++
 lib/node_modules/@stdlib/stats/base/dcuminabs/README.md | 2 ++
 lib/node_modules/@stdlib/stats/base/scumax/README.md    | 2 ++
 4 files changed, 8 insertions(+)

diff --git a/lib/node_modules/@stdlib/stats/base/dcumaxabs/README.md b/lib/node_modules/@stdlib/stats/base/dcumaxabs/README.md
index 19c1b234d41d..c4edd68ad3f3 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumaxabs/README.md
+++ b/lib/node_modules/@stdlib/stats/base/dcumaxabs/README.md
@@ -18,6 +18,8 @@ limitations under the License.
 
 -->
 
+<!-- lint disable maximum-heading-length -->
+
 # dcumaxabs
 
 > Calculate the cumulative maximum absolute value of double-precision floating-point strided array elements.
diff --git a/lib/node_modules/@stdlib/stats/base/dcumin/README.md b/lib/node_modules/@stdlib/stats/base/dcumin/README.md
index 258fa0c21395..80054c163b0b 100644
--- a/lib/node_modules/@stdlib/stats/base/dcumin/README.md
+++ b/lib/node_modules/@stdlib/stats/base/dcumin/README.md
@@ -18,6 +18,8 @@ limitations under the License.
 
 -->
 
+<!-- lint disable maximum-heading-length -->
+
 # dcumin
 
 > Calculate the cumulative minimum of double-precision floating-point strided array elements.
diff --git a/lib/node_modules/@stdlib/stats/base/dcuminabs/README.md b/lib/node_modules/@stdlib/stats/base/dcuminabs/README.md
index 064468679078..83fd29340cd4 100644
--- a/lib/node_modules/@stdlib/stats/base/dcuminabs/README.md
+++ b/lib/node_modules/@stdlib/stats/base/dcuminabs/README.md
@@ -18,6 +18,8 @@ limitations under the License.
 
 -->
 
+<!-- lint disable maximum-heading-length -->
+
 # dcuminabs
 
 > Calculate the cumulative minimum absolute value of double-precision floating-point strided array elements.
diff --git a/lib/node_modules/@stdlib/stats/base/scumax/README.md b/lib/node_modules/@stdlib/stats/base/scumax/README.md
index dc2b120de152..9780e0b7fa31 100644
--- a/lib/node_modules/@stdlib/stats/base/scumax/README.md
+++ b/lib/node_modules/@stdlib/stats/base/scumax/README.md
@@ -18,6 +18,8 @@ limitations under the License.
 
 -->
 
+<!-- lint disable maximum-heading-length -->
+
 # scumax
 
 > Calculate the cumulative maximum of single-precision floating-point strided array elements.

From 783088c02981f45e390bf10baab56575f33669e8 Mon Sep 17 00:00:00 2001
From: Philipp Burckhardt <pburckhardt@outlook.com>
Date: Thu, 2 Jan 2025 20:45:27 -0500
Subject: [PATCH 36/87] refactor: explicitly return zero for non-integer x

---
type: pre_commit_static_analysis_report
description: Results of running static analysis checks when committing changes.
report:
  - task: lint_filenames
    status: passed
  - task: lint_editorconfig
    status: passed
  - task: lint_markdown
    status: na
  - task: lint_package_json
    status: na
  - task: lint_repl_help
    status: na
  - task: lint_javascript_src
    status: passed
  - task: lint_javascript_cli
    status: na
  - task: lint_javascript_examples
    status: na
  - task: lint_javascript_tests
    status: passed
  - task: lint_javascript_benchmarks
    status: na
  - task: lint_python
    status: na
  - task: lint_r
    status: na
  - task: lint_c_src
    status: na
  - task: lint_c_examples
    status: na
  - task: lint_c_benchmarks
    status: na
  - task: lint_c_tests_fixtures
    status: na
  - task: lint_shell
    status: na
  - task: lint_typescript_declarations
    status: na
  - task: lint_typescript_tests
    status: na
  - task: lint_license_headers
    status: passed
---

---
type: pre_push_report
description: Results of running various checks prior to pushing changes.
report:
  - task: run_javascript_examples
    status: na
  - task: run_c_examples
    status: na
  - task: run_cpp_examples
    status: na
  - task: run_javascript_readme_examples
    status: na
  - task: run_c_benchmarks
    status: na
  - task: run_cpp_benchmarks
    status: na
  - task: run_fortran_benchmarks
    status: na
  - task: run_javascript_benchmarks
    status: na
  - task: run_julia_benchmarks
    status: na
  - task: run_python_benchmarks
    status: na
  - task: run_r_benchmarks
    status: na
  - task: run_javascript_tests
    status: passed
---
---
 .../stats/base/dists/signrank/pdf/lib/factory.js   |  4 ++++
 .../stats/base/dists/signrank/pdf/lib/main.js      |  4 ++++
 .../base/dists/signrank/pdf/test/test.factory.js   | 14 ++++++++++++++
 .../stats/base/dists/signrank/pdf/test/test.pdf.js | 12 ++++++++++++
 4 files changed, 34 insertions(+)

diff --git a/lib/node_modules/@stdlib/stats/base/dists/signrank/pdf/lib/factory.js b/lib/node_modules/@stdlib/stats/base/dists/signrank/pdf/lib/factory.js
index 98fe94e9a7a4..abe6cf55cdaa 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/signrank/pdf/lib/factory.js
+++ b/lib/node_modules/@stdlib/stats/base/dists/signrank/pdf/lib/factory.js
@@ -22,6 +22,7 @@
 
 var isPositiveInteger = require( '@stdlib/math/base/assert/is-positive-integer' );
 var constantFunction = require( '@stdlib/utils/constant-function' );
+var isInteger = require( '@stdlib/math/base/assert/is-integer' );
 var isfinite = require( '@stdlib/math/base/assert/is-finite' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var exp = require( '@stdlib/math/base/special/exp' );
@@ -69,6 +70,9 @@ function factory( n ) {
 		if ( isnan( x ) ) {
 			return NaN;
 		}
+		if ( !isInteger( x ) ) {
+			return 0.0;
+		}
 		if ( x < 0.0 || x > mlim ) {
 			return 0.0;
 		}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/signrank/pdf/lib/main.js b/lib/node_modules/@stdlib/stats/base/dists/signrank/pdf/lib/main.js
index 6bec2b634149..e945064d1d48 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/signrank/pdf/lib/main.js
+++ b/lib/node_modules/@stdlib/stats/base/dists/signrank/pdf/lib/main.js
@@ -21,6 +21,7 @@
 // MODULES //
 
 var isPositiveInteger = require( '@stdlib/math/base/assert/is-positive-integer' );
+var isInteger = require( '@stdlib/math/base/assert/is-integer' );
 var isfinite = require( '@stdlib/math/base/assert/is-finite' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var exp = require( '@stdlib/math/base/special/exp' );
@@ -75,6 +76,9 @@ function pdf( x, n ) {
 	) {
 		return NaN;
 	}
+	if ( !isInteger( x ) ) {
+		return 0.0;
+	}
 	mlim = ( n * ( n + 1 ) ) / 2;
 	if ( x < 0.0 || x > mlim ) {
 		return 0.0;
diff --git a/lib/node_modules/@stdlib/stats/base/dists/signrank/pdf/test/test.factory.js b/lib/node_modules/@stdlib/stats/base/dists/signrank/pdf/test/test.factory.js
index 3d4276aaa769..1515b1d0c946 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/signrank/pdf/test/test.factory.js
+++ b/lib/node_modules/@stdlib/stats/base/dists/signrank/pdf/test/test.factory.js
@@ -107,6 +107,20 @@ tape( 'if not provided a positive integer for `n`, the created function always r
 	t.end();
 });
 
+tape( 'the created function returns `0` if provided a non-integer for `x`', function test( t ) {
+	var pdf = factory( 8 );
+	var y = pdf( 1.5 );
+	t.equal( y, 0.0, 'returns expected value' );
+
+	y = pdf( 2.5 );
+	t.equal( y, 0.0, 'returns expected value' );
+
+	y = pdf( 0.1 );
+	t.equal( y, 0.0, 'returns expected value' );
+
+	t.end();
+});
+
 tape( 'the created function evaluates the PDF for `x` given `n` observations', function test( t ) {
 	var expected;
 	var delta;
diff --git a/lib/node_modules/@stdlib/stats/base/dists/signrank/pdf/test/test.pdf.js b/lib/node_modules/@stdlib/stats/base/dists/signrank/pdf/test/test.pdf.js
index 287553c021eb..a851772a5ed2 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/signrank/pdf/test/test.pdf.js
+++ b/lib/node_modules/@stdlib/stats/base/dists/signrank/pdf/test/test.pdf.js
@@ -80,6 +80,18 @@ tape( 'if not provided a positive integer for `n`, the function returns `NaN`',
 	t.end();
 });
 
+tape( 'the function returns `0` if provided a non-integer for `x`', function test( t ) {
+	var y = pdf( 1.5, 8 );
+	t.equal( y, 0.0, 'returns expected value' );
+	t.end();
+
+	y = pdf( 2.5, 8 );
+	t.equal( y, 0.0, 'returns expected value' );
+
+	y = pdf( 0.1, 4 );
+	t.equal( y, 0.0, 'returns expected value' );
+});
+
 tape( 'the function evaluates the PDF for `x` given `n` observations', function test( t ) {
 	var expected;
 	var delta;

From 60d37804ff67d223af691698e92872564ce5c133 Mon Sep 17 00:00:00 2001
From: JoyBoy <144602492+0PrashantYadav0@users.noreply.github.com>
Date: Fri, 3 Jan 2025 07:48:01 +0530
Subject: [PATCH 37/87] feat: add C implementation for
 `stats/base/dists/cosine/skewness`

PR-URL: https://github.com/stdlib-js/stdlib/pull/4469
Closes: https://github.com/stdlib-js/stdlib/issues/3524

Co-authored-by: Philipp Burckhardt <pburckhardt@outlook.com>
Reviewed-by: Philipp Burckhardt <pburckhardt@outlook.com>
Signed-off-by: Philipp Burckhardt <pburckhardt@outlook.com>
---
 .../base/dists/cosine/skewness/README.md      |  96 ++++++++++
 .../cosine/skewness/benchmark/benchmark.js    |  14 +-
 .../skewness/benchmark/benchmark.native.js    |  71 ++++++++
 .../cosine/skewness/benchmark/c/Makefile      | 146 +++++++++++++++
 .../cosine/skewness/benchmark/c/benchmark.c   | 141 +++++++++++++++
 .../base/dists/cosine/skewness/binding.gyp    | 170 ++++++++++++++++++
 .../dists/cosine/skewness/examples/c/Makefile | 146 +++++++++++++++
 .../cosine/skewness/examples/c/example.c      |  41 +++++
 .../base/dists/cosine/skewness/include.gypi   |  53 ++++++
 .../stdlib/stats/base/dists/cosine/skewness.h |  37 ++++
 .../base/dists/cosine/skewness/lib/native.js  |  63 +++++++
 .../base/dists/cosine/skewness/manifest.json  |  79 ++++++++
 .../base/dists/cosine/skewness/package.json   |   3 +
 .../base/dists/cosine/skewness/src/Makefile   |  70 ++++++++
 .../base/dists/cosine/skewness/src/addon.c    |  23 +++
 .../base/dists/cosine/skewness/src/main.c     |  42 +++++
 .../dists/cosine/skewness/test/test.native.js | 114 ++++++++++++
 17 files changed, 1306 insertions(+), 3 deletions(-)
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/benchmark/benchmark.native.js
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/benchmark/c/Makefile
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/benchmark/c/benchmark.c
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/binding.gyp
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/examples/c/Makefile
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/examples/c/example.c
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/include.gypi
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/include/stdlib/stats/base/dists/cosine/skewness.h
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/lib/native.js
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/manifest.json
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/src/Makefile
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/src/addon.c
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/src/main.c
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/test/test.native.js

diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/README.md b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/README.md
index b6b352571c29..e6da03e1ceb5 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/README.md
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/README.md
@@ -131,6 +131,102 @@ for ( i = 0; i < 10; i++ ) {
 
 <!-- /.examples -->
 
+<!-- C interface documentation. -->
+
+<section class="c">
+
+## C APIs
+
+<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<!-- C usage documentation. -->
+
+<section class="usage">
+
+### Usage
+
+```c
+#include "stdlib/stats/base/dists/cosine/skewness.h"
+```
+
+#### stdlib_base_dists_cosine_skewness( mu, s )
+
+Returns the [skewness][skewness] for a [raised cosine][cosine-distribution] distribution with location parameter `mu` and scale parameter `s`.
+
+```c
+double out = stdlib_base_dists_cosine_skewness( 0.0, 1.0 );
+// returns 0.0
+```
+
+The function accepts the following arguments:
+
+-   **mu**: `[in] double` location parameter.
+-   **s**: `[in] double` scale parameter.
+
+```c
+double stdlib_base_dists_cosine_skewness( const double mu, const double s );
+```
+
+</section>
+
+<!-- /.usage -->
+
+<!-- C API usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="notes">
+
+</section>
+
+<!-- /.notes -->
+
+<!-- C API usage examples. -->
+
+<section class="examples">
+
+### Examples
+
+```c
+#include "stdlib/stats/base/dists/cosine/skewness.h"
+#include "stdlib/constants/float64/eps.h"
+#include <stdlib.h>
+#include <stdio.h>
+
+static double random_uniform( const double min, const double max ) {
+    double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
+    return min + ( v * (max - min) );
+}
+
+int main( void ) {
+    double mu;
+    double s;
+    double y;
+    int i;
+
+    for ( i = 0; i < 10; i++ ) {
+        mu = random_uniform( -50.0, 50.0 );
+        s = random_uniform( 0.0, 20.0 ) + STDLIB_CONSTANT_FLOAT64_EPS;
+        y = stdlib_base_dists_cosine_skewness( mu, s );
+        printf( "µ: %lf, s: %lf, Skew(X;µ,s): %lf\n", mu, s , y );
+    }
+
+    return 0;
+}
+```
+
+</section>
+
+<!-- /.examples -->
+
+</section>
+
+<!-- /.c -->
+
 <!-- Section to include cited references. If references are included, add a horizontal rule *before* the section. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
 
 <section class="references">
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/benchmark/benchmark.js
index e4313c4a4210..2f3b8471a648 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/benchmark/benchmark.js
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/benchmark/benchmark.js
@@ -21,6 +21,7 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
+var Float64Array = require( '@stdlib/array/float64' );
 var randu = require( '@stdlib/random/base/randu' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var EPS = require( '@stdlib/constants/float64/eps' );
@@ -31,16 +32,23 @@ var skewness = require( './../lib' );
 // MAIN //
 
 bench( pkg, function benchmark( b ) {
+	var len;
 	var mu;
 	var s;
 	var y;
 	var i;
 
+	len = 100;
+	mu = new Float64Array( len );
+	s = new Float64Array( len );
+	for ( i = 0; i < len; i++ ) {
+		mu[ i ] = ( randu()*100.0 ) - 50.0;
+		s[ i ] = ( randu()*20.0 ) + EPS;
+	}
+
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		mu = ( randu()*100.0 ) - 50.0;
-		s = ( randu()*20.0 ) + EPS;
-		y = skewness( mu, s );
+		y = skewness( mu[ i % len ], s[ i % len ] );
 		if ( isnan( y ) ) {
 			b.fail( 'should not return NaN' );
 		}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/benchmark/benchmark.native.js
new file mode 100644
index 000000000000..87a8210b7071
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/benchmark/benchmark.native.js
@@ -0,0 +1,71 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var resolve = require( 'path' ).resolve;
+var bench = require( '@stdlib/bench' );
+var Float64Array = require( '@stdlib/array/float64' );
+var randu = require( '@stdlib/random/base/randu' );
+var EPS = require( '@stdlib/constants/float64/eps' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var tryRequire = require( '@stdlib/utils/try-require' );
+var pkg = require( './../package.json' ).name;
+
+
+// VARIABLES //
+
+var skewness = tryRequire( resolve( __dirname, './../lib/native.js' ) );
+var opts = {
+	'skip': ( skewness instanceof Error )
+};
+
+
+// MAIN //
+
+bench( pkg+'::native', opts, function benchmark( b ) {
+	var len;
+	var mu;
+	var s;
+	var y;
+	var i;
+
+	len = 100;
+	mu = new Float64Array( len );
+	s = new Float64Array( len );
+	for ( i = 0; i < len; i++ ) {
+		mu[ i ] = ( randu()*100.0 ) - 50.0;
+		s[ i ] = ( randu()*20.0 ) + EPS;
+	}
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		y = skewness( mu[ i % len ], s[ i % len ] );
+		if ( isnan( y ) ) {
+			b.fail( 'should not return NaN' );
+		}
+	}
+	b.toc();
+	if ( isnan( y ) ) {
+		b.fail( 'should not return NaN' );
+	}
+	b.pass( 'benchmark finished' );
+	b.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/benchmark/c/Makefile
new file mode 100644
index 000000000000..a4bd7b38fd74
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/benchmark/c/Makefile
@@ -0,0 +1,146 @@
+#/
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#/
+
+# VARIABLES #
+
+ifndef VERBOSE
+	QUIET := @
+else
+	QUIET :=
+endif
+
+# Determine the OS ([1][1], [2][2]).
+#
+# [1]: https://en.wikipedia.org/wiki/Uname#Examples
+# [2]: http://stackoverflow.com/a/27776822/2225624
+OS ?= $(shell uname)
+ifneq (, $(findstring MINGW,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring MSYS,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring CYGWIN,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring Windows_NT,$(OS)))
+	OS := WINNT
+endif
+endif
+endif
+endif
+
+# Define the program used for compiling C source files:
+ifdef C_COMPILER
+	CC := $(C_COMPILER)
+else
+	CC := gcc
+endif
+
+# Define the command-line options when compiling C files:
+CFLAGS ?= \
+	-std=c99 \
+	-O3 \
+	-Wall \
+	-pedantic
+
+# Determine whether to generate position independent code ([1][1], [2][2]).
+#
+# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options
+# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option
+ifeq ($(OS), WINNT)
+	fPIC ?=
+else
+	fPIC ?= -fPIC
+endif
+
+# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`):
+INCLUDE ?=
+
+# List of source files:
+SOURCE_FILES ?=
+
+# List of libraries (e.g., `-lopenblas -lpthread`):
+LIBRARIES ?=
+
+# List of library paths (e.g., `-L /foo/bar -L /beep/boop`):
+LIBPATH ?=
+
+# List of C targets:
+c_targets := benchmark.out
+
+
+# RULES #
+
+#/
+# Compiles source files.
+#
+# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`)
+# @param {string} [CFLAGS] - C compiler options
+# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`)
+# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`)
+# @param {string} [SOURCE_FILES] - list of source files
+# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`)
+# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`)
+#
+# @example
+# make
+#
+# @example
+# make all
+#/
+all: $(c_targets)
+
+.PHONY: all
+
+#/
+# Compiles C source files.
+#
+# @private
+# @param {string} CC - C compiler (e.g., `gcc`)
+# @param {string} CFLAGS - C compiler options
+# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`)
+# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`)
+# @param {string} SOURCE_FILES - list of source files
+# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`)
+# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`)
+#/
+$(c_targets): %.out: %.c
+	$(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES)
+
+#/
+# Runs compiled benchmarks.
+#
+# @example
+# make run
+#/
+run: $(c_targets)
+	$(QUIET) ./$<
+
+.PHONY: run
+
+#/
+# Removes generated files.
+#
+# @example
+# make clean
+#/
+clean:
+	$(QUIET) -rm -f *.o *.out
+
+.PHONY: clean
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/benchmark/c/benchmark.c
new file mode 100644
index 000000000000..cdc8b323b9f4
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/benchmark/c/benchmark.c
@@ -0,0 +1,141 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/dists/cosine/skewness.h"
+#include "stdlib/constants/float64/eps.h"
+#include <stdlib.h>
+#include <stdio.h>
+#include <math.h>
+#include <time.h>
+#include <sys/time.h>
+
+#define NAME "cosine-skewness"
+#define ITERATIONS 1000000
+#define REPEATS 3
+
+/**
+* Prints the TAP version.
+*/
+static void print_version( void ) {
+	printf( "TAP version 13\n" );
+}
+
+/**
+* Prints the TAP summary.
+*
+* @param total     total number of tests
+* @param passing   total number of passing tests
+*/
+static void print_summary( int total, int passing ) {
+	printf( "#\n" );
+	printf( "1..%d\n", total ); // TAP plan
+	printf( "# total %d\n", total );
+	printf( "# pass  %d\n", passing );
+	printf( "#\n" );
+	printf( "# ok\n" );
+}
+
+/**
+* Prints benchmarks results.
+*
+* @param elapsed   elapsed time in seconds
+*/
+static void print_results( double elapsed ) {
+	double rate = (double)ITERATIONS / elapsed;
+	printf( "  ---\n" );
+	printf( "  iterations: %d\n", ITERATIONS );
+	printf( "  elapsed: %0.9f\n", elapsed );
+	printf( "  rate: %0.9f\n", rate );
+	printf( "  ...\n" );
+}
+
+/**
+* Returns a clock time.
+*
+* @return clock time
+*/
+static double tic( void ) {
+	struct timeval now;
+	gettimeofday( &now, NULL );
+	return (double)now.tv_sec + (double)now.tv_usec/1.0e6;
+}
+
+/**
+* Generates a random number on the interval [min,max).
+*
+* @param min    minimum value (inclusive)
+* @param max    maximum value (exclusive)
+* @return       random number
+*/
+static double random_uniform( const double min, const double max ) {
+	double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
+	return min + ( v*(max-min) );
+}
+
+/**
+* Runs a benchmark.
+*
+* @return elapsed time in seconds
+*/
+static double benchmark( void ) {
+	double elapsed;
+	double mu[ 100 ];
+	double s[ 100 ];
+	double y;
+	double t;
+	int i;
+
+	for ( i = 0; i < 100; i++ ) {
+		mu[ i ] = random_uniform( -50.0, 50.0 );
+		s[ i ] = random_uniform( 0.0, 20.0 ) + STDLIB_CONSTANT_FLOAT64_EPS;
+	}
+
+	t = tic();
+	for ( i = 0; i < ITERATIONS; i++ ) {
+		y = stdlib_base_dists_cosine_skewness( mu[ i%100 ], s[ i%100 ] );
+		if ( y != y ) {
+			printf( "should not return NaN\n" );
+			break;
+		}
+	}
+	elapsed = tic() - t;
+	if ( y != y ) {
+		printf( "should not return NaN\n" );
+	}
+	return elapsed;
+}
+
+/**
+* Main execution sequence.
+*/
+int main( void ) {
+	double elapsed;
+	int i;
+
+	// Use the current time to seed the random number generator:
+	srand( time( NULL ) );
+
+	print_version();
+	for ( i = 0; i < REPEATS; i++ ) {
+		printf( "# c::%s\n", NAME );
+		elapsed = benchmark();
+		print_results( elapsed );
+		printf( "ok %d benchmark finished\n", i+1 );
+	}
+	print_summary( REPEATS, REPEATS );
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/binding.gyp
new file mode 100644
index 000000000000..68a1ca11d160
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/binding.gyp
@@ -0,0 +1,170 @@
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# A `.gyp` file for building a Node.js native add-on.
+#
+# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md
+# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md
+{
+  # List of files to include in this file:
+  'includes': [
+    './include.gypi',
+  ],
+
+  # Define variables to be used throughout the configuration for all targets:
+  'variables': {
+    # Target name should match the add-on export name:
+    'addon_target_name%': 'addon',
+
+    # Set variables based on the host OS:
+    'conditions': [
+      [
+        'OS=="win"',
+        {
+          # Define the object file suffix:
+          'obj': 'obj',
+        },
+        {
+          # Define the object file suffix:
+          'obj': 'o',
+        }
+      ], # end condition (OS=="win")
+    ], # end conditions
+  }, # end variables
+
+  # Define compile targets:
+  'targets': [
+
+    # Target to generate an add-on:
+    {
+      # The target name should match the add-on export name:
+      'target_name': '<(addon_target_name)',
+
+      # Define dependencies:
+      'dependencies': [],
+
+      # Define directories which contain relevant include headers:
+      'include_dirs': [
+        # Local include directory:
+        '<@(include_dirs)',
+      ],
+
+      # List of source files:
+      'sources': [
+        '<@(src_files)',
+      ],
+
+      # Settings which should be applied when a target's object files are used as linker input:
+      'link_settings': {
+        # Define libraries:
+        'libraries': [
+          '<@(libraries)',
+        ],
+
+        # Define library directories:
+        'library_dirs': [
+          '<@(library_dirs)',
+        ],
+      },
+
+      # C/C++ compiler flags:
+      'cflags': [
+        # Enable commonly used warning options:
+        '-Wall',
+
+        # Aggressive optimization:
+        '-O3',
+      ],
+
+      # C specific compiler flags:
+      'cflags_c': [
+        # Specify the C standard to which a program is expected to conform:
+        '-std=c99',
+      ],
+
+      # C++ specific compiler flags:
+      'cflags_cpp': [
+        # Specify the C++ standard to which a program is expected to conform:
+        '-std=c++11',
+      ],
+
+      # Linker flags:
+      'ldflags': [],
+
+      # Apply conditions based on the host OS:
+      'conditions': [
+        [
+          'OS=="mac"',
+          {
+            # Linker flags:
+            'ldflags': [
+              '-undefined dynamic_lookup',
+              '-Wl,-no-pie',
+              '-Wl,-search_paths_first',
+            ],
+          },
+        ], # end condition (OS=="mac")
+        [
+          'OS!="win"',
+          {
+            # C/C++ flags:
+            'cflags': [
+              # Generate platform-independent code:
+              '-fPIC',
+            ],
+          },
+        ], # end condition (OS!="win")
+      ], # end conditions
+    }, # end target <(addon_target_name)
+
+    # Target to copy a generated add-on to a standard location:
+    {
+      'target_name': 'copy_addon',
+
+      # Declare that the output of this target is not linked:
+      'type': 'none',
+
+      # Define dependencies:
+      'dependencies': [
+        # Require that the add-on be generated before building this target:
+        '<(addon_target_name)',
+      ],
+
+      # Define a list of actions:
+      'actions': [
+        {
+          'action_name': 'copy_addon',
+          'message': 'Copying addon...',
+
+          # Explicitly list the inputs in the command-line invocation below:
+          'inputs': [],
+
+          # Declare the expected outputs:
+          'outputs': [
+            '<(addon_output_dir)/<(addon_target_name).node',
+          ],
+
+          # Define the command-line invocation:
+          'action': [
+            'cp',
+            '<(PRODUCT_DIR)/<(addon_target_name).node',
+            '<(addon_output_dir)/<(addon_target_name).node',
+          ],
+        },
+      ], # end actions
+    }, # end target copy_addon
+  ], # end targets
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/examples/c/Makefile
new file mode 100644
index 000000000000..25ced822f96a
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/examples/c/Makefile
@@ -0,0 +1,146 @@
+#/
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#/
+
+# VARIABLES #
+
+ifndef VERBOSE
+	QUIET := @
+else
+	QUIET :=
+endif
+
+# Determine the OS ([1][1], [2][2]).
+#
+# [1]: https://en.wikipedia.org/wiki/Uname#Examples
+# [2]: http://stackoverflow.com/a/27776822/2225624
+OS ?= $(shell uname)
+ifneq (, $(findstring MINGW,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring MSYS,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring CYGWIN,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring Windows_NT,$(OS)))
+	OS := WINNT
+endif
+endif
+endif
+endif
+
+# Define the program used for compiling C source files:
+ifdef C_COMPILER
+	CC := $(C_COMPILER)
+else
+	CC := gcc
+endif
+
+# Define the command-line options when compiling C files:
+CFLAGS ?= \
+	-std=c99 \
+	-O3 \
+	-Wall \
+	-pedantic
+
+# Determine whether to generate position independent code ([1][1], [2][2]).
+#
+# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options
+# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option
+ifeq ($(OS), WINNT)
+	fPIC ?=
+else
+	fPIC ?= -fPIC
+endif
+
+# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`):
+INCLUDE ?=
+
+# List of source files:
+SOURCE_FILES ?=
+
+# List of libraries (e.g., `-lopenblas -lpthread`):
+LIBRARIES ?=
+
+# List of library paths (e.g., `-L /foo/bar -L /beep/boop`):
+LIBPATH ?=
+
+# List of C targets:
+c_targets := example.out
+
+
+# RULES #
+
+#/
+# Compiles source files.
+#
+# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`)
+# @param {string} [CFLAGS] - C compiler options
+# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`)
+# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`)
+# @param {string} [SOURCE_FILES] - list of source files
+# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`)
+# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`)
+#
+# @example
+# make
+#
+# @example
+# make all
+#/
+all: $(c_targets)
+
+.PHONY: all
+
+#/
+# Compiles C source files.
+#
+# @private
+# @param {string} CC - C compiler (e.g., `gcc`)
+# @param {string} CFLAGS - C compiler options
+# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`)
+# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`)
+# @param {string} SOURCE_FILES - list of source files
+# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`)
+# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`)
+#/
+$(c_targets): %.out: %.c
+	$(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES)
+
+#/
+# Runs compiled examples.
+#
+# @example
+# make run
+#/
+run: $(c_targets)
+	$(QUIET) ./$<
+
+.PHONY: run
+
+#/
+# Removes generated files.
+#
+# @example
+# make clean
+#/
+clean:
+	$(QUIET) -rm -f *.o *.out
+
+.PHONY: clean
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/examples/c/example.c
new file mode 100644
index 000000000000..2ff8d6630a1e
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/examples/c/example.c
@@ -0,0 +1,41 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/dists/cosine/skewness.h"
+#include "stdlib/constants/float64/eps.h"
+#include <stdlib.h>
+#include <stdio.h>
+
+static double random_uniform( const double min, const double max ) {
+	double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
+	return min + ( v*(max-min) );
+}
+
+int main( void ) {
+	double mu;
+	double s;
+	double y;
+	int i;
+
+	for ( i = 0; i < 10; i++ ) {
+		mu = random_uniform( -50.0, 50.0 );
+		s = random_uniform( 0.0, 20.0 ) + STDLIB_CONSTANT_FLOAT64_EPS;
+		y = stdlib_base_dists_cosine_skewness( mu, s );
+		printf( "µ: %lf, s: %lf, SD(X;µ,s): %lf\n", mu, s , y );
+	}
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/include.gypi
new file mode 100644
index 000000000000..ecfaf82a3279
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/include.gypi
@@ -0,0 +1,53 @@
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# A GYP include file for building a Node.js native add-on.
+#
+# Main documentation:
+#
+# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md
+# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md
+{
+  # Define variables to be used throughout the configuration for all targets:
+  'variables': {
+    # Source directory:
+    'src_dir': './src',
+
+    # Include directories:
+    'include_dirs': [
+      '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).include; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
+    ],
+
+    # Add-on destination directory:
+    'addon_output_dir': './src',
+
+    # Source files:
+    'src_files': [
+      '<(src_dir)/addon.c',
+      '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).src; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
+    ],
+
+    # Library dependencies:
+    'libraries': [
+      '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).libraries; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
+    ],
+
+    # Library directories:
+    'library_dirs': [
+      '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).libpath; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
+    ],
+  }, # end variables
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/include/stdlib/stats/base/dists/cosine/skewness.h b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/include/stdlib/stats/base/dists/cosine/skewness.h
new file mode 100644
index 000000000000..98fe7b92f399
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/include/stdlib/stats/base/dists/cosine/skewness.h
@@ -0,0 +1,37 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#ifndef STDLIB_STATS_BASE_DISTS_COSINE_SKEWNESS_H
+#define STDLIB_STATS_BASE_DISTS_COSINE_SKEWNESS_H
+
+/*
+* If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler.
+*/
+#ifdef __cplusplus
+extern "C" {
+#endif
+/**
+* Returns the skewness for a raised cosine distribution with location `mu` and scale `s`.
+*/
+double stdlib_base_dists_cosine_skewness( const double mu, const double s );
+
+#ifdef __cplusplus
+}
+#endif
+
+#endif // !STDLIB_STATS_BASE_DISTS_COSINE_SKEWNESS_H
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/lib/native.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/lib/native.js
new file mode 100644
index 000000000000..10c957c25776
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/lib/native.js
@@ -0,0 +1,63 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var addon = require( './../src/addon.node' );
+
+
+// MAIN //
+
+/**
+* Returns the skewness for a raised cosine distribution with location `mu` and scale `s`.
+*
+* @private
+* @param {number} mu - location parameter
+* @param {PositiveNumber} s - scale parameter
+* @returns {number} skewness
+*
+* @example
+* var y = skewness( 0.0, 1.0 );
+* // returns 0.0
+*
+* @example
+* var y = skewness( 5.0, 2.0 );
+* // returns 0.0
+*
+* @example
+* var y = skewness( NaN, 1.0 );
+* // returns NaN
+*
+* @example
+* var y = skewness( 0.0, NaN );
+* // returns NaN
+*
+* @example
+* var y = skewness( 0.0, 0.0 );
+* // returns NaN
+*/
+function skewness( mu, s ) {
+	return addon( mu, s );
+}
+
+
+// EXPORTS //
+
+module.exports = skewness;
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/manifest.json b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/manifest.json
new file mode 100644
index 000000000000..93ccded754bf
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/manifest.json
@@ -0,0 +1,79 @@
+{
+  "options": {
+    "task": "build",
+    "wasm": false
+  },
+  "fields": [
+    {
+      "field": "src",
+      "resolve": true,
+      "relative": true
+    },
+    {
+      "field": "include",
+      "resolve": true,
+      "relative": true
+    },
+    {
+      "field": "libraries",
+      "resolve": false,
+      "relative": false
+    },
+    {
+      "field": "libpath",
+      "resolve": true,
+      "relative": false
+    }
+  ],
+  "confs": [
+    {
+      "task": "build",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/math/base/napi/binary",
+        "@stdlib/math/base/assert/is-nan",
+        "@stdlib/constants/float64/eps"
+      ]
+    },
+    {
+      "task": "benchmark",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/math/base/assert/is-nan",
+        "@stdlib/constants/float64/eps"
+      ]
+    },
+    {
+      "task": "examples",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/math/base/assert/is-nan",
+        "@stdlib/constants/float64/eps"
+      ]
+    }
+  ]
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/package.json b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/package.json
index e35f815a2f13..f2b0fcd6e032 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/package.json
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/package.json
@@ -14,11 +14,14 @@
     }
   ],
   "main": "./lib",
+  "gypfile": true,
   "directories": {
     "benchmark": "./benchmark",
     "doc": "./docs",
     "example": "./examples",
+    "include": "./include",
     "lib": "./lib",
+    "src": "./src",
     "test": "./test"
   },
   "types": "./docs/types",
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/src/Makefile b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/src/Makefile
new file mode 100644
index 000000000000..7733b6180cb4
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/src/Makefile
@@ -0,0 +1,70 @@
+#/
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#/
+
+# VARIABLES #
+
+ifndef VERBOSE
+	QUIET := @
+else
+	QUIET :=
+endif
+
+# Determine the OS ([1][1], [2][2]).
+#
+# [1]: https://en.wikipedia.org/wiki/Uname#Examples
+# [2]: http://stackoverflow.com/a/27776822/2225624
+OS ?= $(shell uname)
+ifneq (, $(findstring MINGW,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring MSYS,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring CYGWIN,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring Windows_NT,$(OS)))
+	OS := WINNT
+endif
+endif
+endif
+endif
+
+
+# RULES #
+
+#/
+# Removes generated files for building an add-on.
+#
+# @example
+# make clean-addon
+#/
+clean-addon:
+	$(QUIET) -rm -f *.o *.node
+
+.PHONY: clean-addon
+
+#/
+# Removes generated files.
+#
+# @example
+# make clean
+#/
+clean: clean-addon
+
+.PHONY: clean
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/src/addon.c b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/src/addon.c
new file mode 100644
index 000000000000..ba0e45f92380
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/src/addon.c
@@ -0,0 +1,23 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/dists/cosine/skewness.h"
+#include "stdlib/math/base/napi/binary.h"
+
+// cppcheck-suppress shadowFunction
+STDLIB_MATH_BASE_NAPI_MODULE_DD_D( stdlib_base_dists_cosine_skewness )
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/src/main.c
new file mode 100644
index 000000000000..9bcf2ea2eb68
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/src/main.c
@@ -0,0 +1,42 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/dists/cosine/skewness.h"
+#include "stdlib/math/base/assert/is_nan.h"
+
+/**
+* Returns the skewness for a raised cosine distribution with location `mu` and scale `s`.
+*
+* @param mu   location parameter
+* @param s    scale parameter
+* @return     skewness
+*
+* @example
+* double y = stdlib_base_dists_cosine_skewness( 0.0, 1.0 );
+* // returns 0.0
+*/
+double stdlib_base_dists_cosine_skewness( const double mu, const double s ) {
+	if ( 
+		stdlib_base_is_nan( mu ) ||
+		stdlib_base_is_nan( s ) ||
+		s <= 0.0
+	) {
+		return 0.0/0.0; // NaN
+	}
+	return 0.0;
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/test/test.native.js
new file mode 100644
index 000000000000..ac737e256fe2
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/skewness/test/test.native.js
@@ -0,0 +1,114 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var resolve = require( 'path' ).resolve;
+var tape = require( 'tape' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var abs = require( '@stdlib/math/base/special/abs' );
+var PINF = require( '@stdlib/constants/float64/pinf' );
+var NINF = require( '@stdlib/constants/float64/ninf' );
+var EPS = require( '@stdlib/constants/float64/eps' );
+var tryRequire = require( '@stdlib/utils/try-require' );
+
+
+// FIXTURES //
+
+var data = require( './fixtures/julia/data.json' );
+
+
+// VARIABLES //
+
+var stdev = tryRequire( resolve( __dirname, './../lib/native.js' ) );
+var opts = {
+	'skip': ( stdev instanceof Error )
+};
+
+
+// TESTS //
+
+tape( 'main export is a function', opts, function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof stdev, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'if provided `NaN` for any parameter, the function returns `NaN`', opts, function test( t ) {
+	var y = stdev( NaN, 1.0 );
+	t.equal( isnan( y ), true, 'returns NaN' );
+	y = stdev( 1.0, NaN );
+	t.equal( isnan( y ), true, 'returns NaN' );
+	t.end();
+});
+
+tape( 'if provided a nonpositive `s`, the function returns `NaN`', opts, function test( t ) {
+	var y;
+
+	y = stdev( 2.0, 0.0 );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	y = stdev( 2.0, -1.0 );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	y = stdev( 2.0, -1.0 );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	y = stdev( 1.0, NINF );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	y = stdev( PINF, NINF );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	y = stdev( NINF, NINF );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	y = stdev( NaN, NINF );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	t.end();
+});
+
+tape( 'the function returns the stdev of a raised cosine distribution', opts, function test( t ) {
+	var expected;
+	var delta;
+	var tol;
+	var mu;
+	var s;
+	var y;
+	var i;
+
+	expected = data.expected;
+	mu = data.mu;
+	s = data.s;
+	for ( i = 0; i < mu.length; i++ ) {
+		y = stdev( mu[i], s[i] );
+		if ( expected[i] !== null ) {
+			if ( y === expected[i] ) {
+				t.equal( y, expected[i], 'mu:'+mu[i]+', s: '+s[i]+', y: '+y+', expected: '+expected[i] );
+			} else {
+				delta = abs( y - expected[ i ] );
+				tol = 2.0 * EPS * abs( expected[ i ] );
+				t.ok( delta <= tol, 'within tolerance. mu: '+mu[i]+'. s: '+s[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
+			}
+		}
+	}
+	t.end();
+});

From d7eca9f4f8b265ff1261a716e1cd3cfbf1644d87 Mon Sep 17 00:00:00 2001
From: JoyBoy <144602492+0PrashantYadav0@users.noreply.github.com>
Date: Fri, 3 Jan 2025 07:48:27 +0530
Subject: [PATCH 38/87] feat: add C implementation for
 `stats/base/dists/cosine/median`

PR-URL: https://github.com/stdlib-js/stdlib/pull/4467
Closes: https://github.com/stdlib-js/stdlib/issues/3519

Co-authored-by: Philipp Burckhardt <pburckhardt@outlook.com>
Reviewed-by: Philipp Burckhardt <pburckhardt@outlook.com>
Signed-off-by: Philipp Burckhardt <pburckhardt@outlook.com>
---
 .../stats/base/dists/cosine/median/README.md  |  96 ++++++++++
 .../cosine/median/benchmark/benchmark.js      |  14 +-
 .../median/benchmark/benchmark.native.js      |  71 ++++++++
 .../dists/cosine/median/benchmark/c/Makefile  | 146 +++++++++++++++
 .../cosine/median/benchmark/c/benchmark.c     | 141 +++++++++++++++
 .../base/dists/cosine/median/binding.gyp      | 170 ++++++++++++++++++
 .../dists/cosine/median/examples/c/Makefile   | 146 +++++++++++++++
 .../dists/cosine/median/examples/c/example.c  |  41 +++++
 .../base/dists/cosine/median/include.gypi     |  53 ++++++
 .../stdlib/stats/base/dists/cosine/median.h   |  37 ++++
 .../base/dists/cosine/median/lib/native.js    |  63 +++++++
 .../base/dists/cosine/median/manifest.json    |  79 ++++++++
 .../base/dists/cosine/median/package.json     |   3 +
 .../base/dists/cosine/median/src/Makefile     |  70 ++++++++
 .../base/dists/cosine/median/src/addon.c      |  23 +++
 .../stats/base/dists/cosine/median/src/main.c |  42 +++++
 .../dists/cosine/median/test/test.native.js   | 114 ++++++++++++
 17 files changed, 1306 insertions(+), 3 deletions(-)
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/median/benchmark/benchmark.native.js
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/median/benchmark/c/Makefile
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/median/benchmark/c/benchmark.c
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/median/binding.gyp
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/median/examples/c/Makefile
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/median/examples/c/example.c
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/median/include.gypi
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/median/include/stdlib/stats/base/dists/cosine/median.h
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/median/lib/native.js
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/median/manifest.json
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/median/src/Makefile
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/median/src/addon.c
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/median/src/main.c
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/median/test/test.native.js

diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/median/README.md b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/README.md
index 01caa20e621e..134ec3eecec0 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/cosine/median/README.md
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/README.md
@@ -131,6 +131,102 @@ for ( i = 0; i < 10; i++ ) {
 
 <!-- /.examples -->
 
+<!-- C interface documentation. -->
+
+<section class="c">
+
+## C APIs
+
+<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<!-- C usage documentation. -->
+
+<section class="usage">
+
+### Usage
+
+```c
+#include "stdlib/stats/base/dists/cosine/median.h"
+```
+
+#### stdlib_base_dists_cosine_median( mu, s )
+
+Returns the [median][median] for a [raised cosine][cosine-distribution] distribution with location parameter `mu` and scale parameter `s`.
+
+```c
+double out = stdlib_base_dists_cosine_median( 0.0, 1.0 );
+// returns 0.0
+```
+
+The function accepts the following arguments:
+
+-   **mu**: `[in] double` location parameter.
+-   **s**: `[in] double` scale parameter.
+
+```c
+double stdlib_base_dists_cosine_median( const double mu, const double s );
+```
+
+</section>
+
+<!-- /.usage -->
+
+<!-- C API usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="notes">
+
+</section>
+
+<!-- /.notes -->
+
+<!-- C API usage examples. -->
+
+<section class="examples">
+
+### Examples
+
+```c
+#include "stdlib/stats/base/dists/cosine/median.h"
+#include "stdlib/constants/float64/eps.h"
+#include <stdlib.h>
+#include <stdio.h>
+
+static double random_uniform( const double min, const double max ) {
+    double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
+    return min + ( v * (max - min) );
+}
+
+int main( void ) {
+    double mu;
+    double s;
+    double y;
+    int i;
+
+    for ( i = 0; i < 10; i++ ) {
+        mu = random_uniform( -50.0, 50.0 );
+        s = random_uniform( 0.0, 20.0 ) + STDLIB_CONSTANT_FLOAT64_EPS;
+        y = stdlib_base_dists_cosine_median( mu, s );
+        printf( "µ: %lf, s: %lf, Median(X;µ,s): %lf\n", mu, s , y );
+    }
+
+    return 0;
+}
+```
+
+</section>
+
+<!-- /.examples -->
+
+</section>
+
+<!-- /.c -->
+
 <!-- Section to include cited references. If references are included, add a horizontal rule *before* the section. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
 
 <section class="references">
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/median/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/benchmark/benchmark.js
index 8e02177c21e0..0d6f60f7dd67 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/cosine/median/benchmark/benchmark.js
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/benchmark/benchmark.js
@@ -21,6 +21,7 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
+var Float64Array = require( '@stdlib/array/float64' );
 var randu = require( '@stdlib/random/base/randu' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var EPS = require( '@stdlib/constants/float64/eps' );
@@ -31,16 +32,23 @@ var median = require( './../lib' );
 // MAIN //
 
 bench( pkg, function benchmark( b ) {
+	var len;
 	var mu;
 	var s;
 	var y;
 	var i;
 
+	len = 100;
+	mu = new Float64Array( len );
+	s = new Float64Array( len );
+	for ( i = 0; i < len; i++ ) {
+		mu[ i ] = ( randu()*100.0 ) - 50.0;
+		s[ i ] = ( randu()*20.0 ) + EPS;
+	}
+
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		mu = ( randu()*100.0 ) - 50.0;
-		s = ( randu()*20.0 ) + EPS;
-		y = median( mu, s );
+		y = median( mu[ i % len ], s[ i % len ] );
 		if ( isnan( y ) ) {
 			b.fail( 'should not return NaN' );
 		}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/median/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/benchmark/benchmark.native.js
new file mode 100644
index 000000000000..d73d223ebdbc
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/benchmark/benchmark.native.js
@@ -0,0 +1,71 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var resolve = require( 'path' ).resolve;
+var bench = require( '@stdlib/bench' );
+var Float64Array = require( '@stdlib/array/float64' );
+var randu = require( '@stdlib/random/base/randu' );
+var EPS = require( '@stdlib/constants/float64/eps' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var tryRequire = require( '@stdlib/utils/try-require' );
+var pkg = require( './../package.json' ).name;
+
+
+// VARIABLES //
+
+var median = tryRequire( resolve( __dirname, './../lib/native.js' ) );
+var opts = {
+	'skip': ( median instanceof Error )
+};
+
+
+// MAIN //
+
+bench( pkg+'::native', opts, function benchmark( b ) {
+	var len;
+	var mu;
+	var s;
+	var y;
+	var i;
+
+	len = 100;
+	mu = new Float64Array( len );
+	s = new Float64Array( len );
+	for ( i = 0; i < len; i++ ) {
+		mu[ i ] = ( randu()*100.0 ) - 50.0;
+		s[ i ] = ( randu()*20.0 ) + EPS;
+	}
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		y = median( mu[ i % len ], s[ i % len ] );
+		if ( isnan( y ) ) {
+			b.fail( 'should not return NaN' );
+		}
+	}
+	b.toc();
+	if ( isnan( y ) ) {
+		b.fail( 'should not return NaN' );
+	}
+	b.pass( 'benchmark finished' );
+	b.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/median/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/benchmark/c/Makefile
new file mode 100644
index 000000000000..a4bd7b38fd74
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/benchmark/c/Makefile
@@ -0,0 +1,146 @@
+#/
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#/
+
+# VARIABLES #
+
+ifndef VERBOSE
+	QUIET := @
+else
+	QUIET :=
+endif
+
+# Determine the OS ([1][1], [2][2]).
+#
+# [1]: https://en.wikipedia.org/wiki/Uname#Examples
+# [2]: http://stackoverflow.com/a/27776822/2225624
+OS ?= $(shell uname)
+ifneq (, $(findstring MINGW,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring MSYS,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring CYGWIN,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring Windows_NT,$(OS)))
+	OS := WINNT
+endif
+endif
+endif
+endif
+
+# Define the program used for compiling C source files:
+ifdef C_COMPILER
+	CC := $(C_COMPILER)
+else
+	CC := gcc
+endif
+
+# Define the command-line options when compiling C files:
+CFLAGS ?= \
+	-std=c99 \
+	-O3 \
+	-Wall \
+	-pedantic
+
+# Determine whether to generate position independent code ([1][1], [2][2]).
+#
+# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options
+# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option
+ifeq ($(OS), WINNT)
+	fPIC ?=
+else
+	fPIC ?= -fPIC
+endif
+
+# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`):
+INCLUDE ?=
+
+# List of source files:
+SOURCE_FILES ?=
+
+# List of libraries (e.g., `-lopenblas -lpthread`):
+LIBRARIES ?=
+
+# List of library paths (e.g., `-L /foo/bar -L /beep/boop`):
+LIBPATH ?=
+
+# List of C targets:
+c_targets := benchmark.out
+
+
+# RULES #
+
+#/
+# Compiles source files.
+#
+# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`)
+# @param {string} [CFLAGS] - C compiler options
+# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`)
+# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`)
+# @param {string} [SOURCE_FILES] - list of source files
+# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`)
+# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`)
+#
+# @example
+# make
+#
+# @example
+# make all
+#/
+all: $(c_targets)
+
+.PHONY: all
+
+#/
+# Compiles C source files.
+#
+# @private
+# @param {string} CC - C compiler (e.g., `gcc`)
+# @param {string} CFLAGS - C compiler options
+# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`)
+# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`)
+# @param {string} SOURCE_FILES - list of source files
+# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`)
+# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`)
+#/
+$(c_targets): %.out: %.c
+	$(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES)
+
+#/
+# Runs compiled benchmarks.
+#
+# @example
+# make run
+#/
+run: $(c_targets)
+	$(QUIET) ./$<
+
+.PHONY: run
+
+#/
+# Removes generated files.
+#
+# @example
+# make clean
+#/
+clean:
+	$(QUIET) -rm -f *.o *.out
+
+.PHONY: clean
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/median/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/benchmark/c/benchmark.c
new file mode 100644
index 000000000000..1b842f902369
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/benchmark/c/benchmark.c
@@ -0,0 +1,141 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/dists/cosine/median.h"
+#include "stdlib/constants/float64/eps.h"
+#include <stdlib.h>
+#include <stdio.h>
+#include <math.h>
+#include <time.h>
+#include <sys/time.h>
+
+#define NAME "cosine-median"
+#define ITERATIONS 1000000
+#define REPEATS 3
+
+/**
+* Prints the TAP version.
+*/
+static void print_version( void ) {
+	printf( "TAP version 13\n" );
+}
+
+/**
+* Prints the TAP summary.
+*
+* @param total     total number of tests
+* @param passing   total number of passing tests
+*/
+static void print_summary( int total, int passing ) {
+	printf( "#\n" );
+	printf( "1..%d\n", total ); // TAP plan
+	printf( "# total %d\n", total );
+	printf( "# pass  %d\n", passing );
+	printf( "#\n" );
+	printf( "# ok\n" );
+}
+
+/**
+* Prints benchmarks results.
+*
+* @param elapsed   elapsed time in seconds
+*/
+static void print_results( double elapsed ) {
+	double rate = (double)ITERATIONS / elapsed;
+	printf( "  ---\n" );
+	printf( "  iterations: %d\n", ITERATIONS );
+	printf( "  elapsed: %0.9f\n", elapsed );
+	printf( "  rate: %0.9f\n", rate );
+	printf( "  ...\n" );
+}
+
+/**
+* Returns a clock time.
+*
+* @return clock time
+*/
+static double tic( void ) {
+	struct timeval now;
+	gettimeofday( &now, NULL );
+	return (double)now.tv_sec + (double)now.tv_usec/1.0e6;
+}
+
+/**
+* Generates a random number on the interval [min,max).
+*
+* @param min    minimum value (inclusive)
+* @param max    maximum value (exclusive)
+* @return       random number
+*/
+static double random_uniform( const double min, const double max ) {
+	double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
+	return min + ( v*(max-min) );
+}
+
+/**
+* Runs a benchmark.
+*
+* @return elapsed time in seconds
+*/
+static double benchmark( void ) {
+	double elapsed;
+	double mu[ 100 ];
+	double s[ 100 ];
+	double y;
+	double t;
+	int i;
+
+	for ( i = 0; i < 100; i++ ) {
+		mu[ i ] = random_uniform( -50.0, 50.0 );
+		s[ i ] = random_uniform( 0.0, 20.0 ) + STDLIB_CONSTANT_FLOAT64_EPS;
+	}
+
+	t = tic();
+	for ( i = 0; i < ITERATIONS; i++ ) {
+		y = stdlib_base_dists_cosine_median( mu[ i%100 ], s[ i%100 ] );
+		if ( y != y ) {
+			printf( "should not return NaN\n" );
+			break;
+		}
+	}
+	elapsed = tic() - t;
+	if ( y != y ) {
+		printf( "should not return NaN\n" );
+	}
+	return elapsed;
+}
+
+/**
+* Main execution sequence.
+*/
+int main( void ) {
+	double elapsed;
+	int i;
+
+	// Use the current time to seed the random number generator:
+	srand( time( NULL ) );
+
+	print_version();
+	for ( i = 0; i < REPEATS; i++ ) {
+		printf( "# c::%s\n", NAME );
+		elapsed = benchmark();
+		print_results( elapsed );
+		printf( "ok %d benchmark finished\n", i+1 );
+	}
+	print_summary( REPEATS, REPEATS );
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/median/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/binding.gyp
new file mode 100644
index 000000000000..68a1ca11d160
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/binding.gyp
@@ -0,0 +1,170 @@
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# A `.gyp` file for building a Node.js native add-on.
+#
+# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md
+# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md
+{
+  # List of files to include in this file:
+  'includes': [
+    './include.gypi',
+  ],
+
+  # Define variables to be used throughout the configuration for all targets:
+  'variables': {
+    # Target name should match the add-on export name:
+    'addon_target_name%': 'addon',
+
+    # Set variables based on the host OS:
+    'conditions': [
+      [
+        'OS=="win"',
+        {
+          # Define the object file suffix:
+          'obj': 'obj',
+        },
+        {
+          # Define the object file suffix:
+          'obj': 'o',
+        }
+      ], # end condition (OS=="win")
+    ], # end conditions
+  }, # end variables
+
+  # Define compile targets:
+  'targets': [
+
+    # Target to generate an add-on:
+    {
+      # The target name should match the add-on export name:
+      'target_name': '<(addon_target_name)',
+
+      # Define dependencies:
+      'dependencies': [],
+
+      # Define directories which contain relevant include headers:
+      'include_dirs': [
+        # Local include directory:
+        '<@(include_dirs)',
+      ],
+
+      # List of source files:
+      'sources': [
+        '<@(src_files)',
+      ],
+
+      # Settings which should be applied when a target's object files are used as linker input:
+      'link_settings': {
+        # Define libraries:
+        'libraries': [
+          '<@(libraries)',
+        ],
+
+        # Define library directories:
+        'library_dirs': [
+          '<@(library_dirs)',
+        ],
+      },
+
+      # C/C++ compiler flags:
+      'cflags': [
+        # Enable commonly used warning options:
+        '-Wall',
+
+        # Aggressive optimization:
+        '-O3',
+      ],
+
+      # C specific compiler flags:
+      'cflags_c': [
+        # Specify the C standard to which a program is expected to conform:
+        '-std=c99',
+      ],
+
+      # C++ specific compiler flags:
+      'cflags_cpp': [
+        # Specify the C++ standard to which a program is expected to conform:
+        '-std=c++11',
+      ],
+
+      # Linker flags:
+      'ldflags': [],
+
+      # Apply conditions based on the host OS:
+      'conditions': [
+        [
+          'OS=="mac"',
+          {
+            # Linker flags:
+            'ldflags': [
+              '-undefined dynamic_lookup',
+              '-Wl,-no-pie',
+              '-Wl,-search_paths_first',
+            ],
+          },
+        ], # end condition (OS=="mac")
+        [
+          'OS!="win"',
+          {
+            # C/C++ flags:
+            'cflags': [
+              # Generate platform-independent code:
+              '-fPIC',
+            ],
+          },
+        ], # end condition (OS!="win")
+      ], # end conditions
+    }, # end target <(addon_target_name)
+
+    # Target to copy a generated add-on to a standard location:
+    {
+      'target_name': 'copy_addon',
+
+      # Declare that the output of this target is not linked:
+      'type': 'none',
+
+      # Define dependencies:
+      'dependencies': [
+        # Require that the add-on be generated before building this target:
+        '<(addon_target_name)',
+      ],
+
+      # Define a list of actions:
+      'actions': [
+        {
+          'action_name': 'copy_addon',
+          'message': 'Copying addon...',
+
+          # Explicitly list the inputs in the command-line invocation below:
+          'inputs': [],
+
+          # Declare the expected outputs:
+          'outputs': [
+            '<(addon_output_dir)/<(addon_target_name).node',
+          ],
+
+          # Define the command-line invocation:
+          'action': [
+            'cp',
+            '<(PRODUCT_DIR)/<(addon_target_name).node',
+            '<(addon_output_dir)/<(addon_target_name).node',
+          ],
+        },
+      ], # end actions
+    }, # end target copy_addon
+  ], # end targets
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/median/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/examples/c/Makefile
new file mode 100644
index 000000000000..25ced822f96a
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/examples/c/Makefile
@@ -0,0 +1,146 @@
+#/
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#/
+
+# VARIABLES #
+
+ifndef VERBOSE
+	QUIET := @
+else
+	QUIET :=
+endif
+
+# Determine the OS ([1][1], [2][2]).
+#
+# [1]: https://en.wikipedia.org/wiki/Uname#Examples
+# [2]: http://stackoverflow.com/a/27776822/2225624
+OS ?= $(shell uname)
+ifneq (, $(findstring MINGW,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring MSYS,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring CYGWIN,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring Windows_NT,$(OS)))
+	OS := WINNT
+endif
+endif
+endif
+endif
+
+# Define the program used for compiling C source files:
+ifdef C_COMPILER
+	CC := $(C_COMPILER)
+else
+	CC := gcc
+endif
+
+# Define the command-line options when compiling C files:
+CFLAGS ?= \
+	-std=c99 \
+	-O3 \
+	-Wall \
+	-pedantic
+
+# Determine whether to generate position independent code ([1][1], [2][2]).
+#
+# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options
+# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option
+ifeq ($(OS), WINNT)
+	fPIC ?=
+else
+	fPIC ?= -fPIC
+endif
+
+# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`):
+INCLUDE ?=
+
+# List of source files:
+SOURCE_FILES ?=
+
+# List of libraries (e.g., `-lopenblas -lpthread`):
+LIBRARIES ?=
+
+# List of library paths (e.g., `-L /foo/bar -L /beep/boop`):
+LIBPATH ?=
+
+# List of C targets:
+c_targets := example.out
+
+
+# RULES #
+
+#/
+# Compiles source files.
+#
+# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`)
+# @param {string} [CFLAGS] - C compiler options
+# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`)
+# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`)
+# @param {string} [SOURCE_FILES] - list of source files
+# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`)
+# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`)
+#
+# @example
+# make
+#
+# @example
+# make all
+#/
+all: $(c_targets)
+
+.PHONY: all
+
+#/
+# Compiles C source files.
+#
+# @private
+# @param {string} CC - C compiler (e.g., `gcc`)
+# @param {string} CFLAGS - C compiler options
+# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`)
+# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`)
+# @param {string} SOURCE_FILES - list of source files
+# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`)
+# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`)
+#/
+$(c_targets): %.out: %.c
+	$(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES)
+
+#/
+# Runs compiled examples.
+#
+# @example
+# make run
+#/
+run: $(c_targets)
+	$(QUIET) ./$<
+
+.PHONY: run
+
+#/
+# Removes generated files.
+#
+# @example
+# make clean
+#/
+clean:
+	$(QUIET) -rm -f *.o *.out
+
+.PHONY: clean
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/median/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/examples/c/example.c
new file mode 100644
index 000000000000..5eaaabbf8c15
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/examples/c/example.c
@@ -0,0 +1,41 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/dists/cosine/median.h"
+#include "stdlib/constants/float64/eps.h"
+#include <stdlib.h>
+#include <stdio.h>
+
+static double random_uniform( const double min, const double max ) {
+	double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
+	return min + ( v*(max-min) );
+}
+
+int main( void ) {
+	double mu;
+	double s;
+	double y;
+	int i;
+
+	for ( i = 0; i < 10; i++ ) {
+		mu = random_uniform( -50.0, 50.0 );
+		s = random_uniform( 0.0, 20.0 ) + STDLIB_CONSTANT_FLOAT64_EPS;
+		y = stdlib_base_dists_cosine_median( mu, s );
+		printf( "µ: %lf, s: %lf, Median(X;µ,s): %lf\n", mu, s , y );
+	}
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/median/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/include.gypi
new file mode 100644
index 000000000000..ecfaf82a3279
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/include.gypi
@@ -0,0 +1,53 @@
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# A GYP include file for building a Node.js native add-on.
+#
+# Main documentation:
+#
+# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md
+# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md
+{
+  # Define variables to be used throughout the configuration for all targets:
+  'variables': {
+    # Source directory:
+    'src_dir': './src',
+
+    # Include directories:
+    'include_dirs': [
+      '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).include; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
+    ],
+
+    # Add-on destination directory:
+    'addon_output_dir': './src',
+
+    # Source files:
+    'src_files': [
+      '<(src_dir)/addon.c',
+      '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).src; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
+    ],
+
+    # Library dependencies:
+    'libraries': [
+      '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).libraries; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
+    ],
+
+    # Library directories:
+    'library_dirs': [
+      '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).libpath; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
+    ],
+  }, # end variables
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/median/include/stdlib/stats/base/dists/cosine/median.h b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/include/stdlib/stats/base/dists/cosine/median.h
new file mode 100644
index 000000000000..085282075f99
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/include/stdlib/stats/base/dists/cosine/median.h
@@ -0,0 +1,37 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#ifndef STDLIB_STATS_BASE_DISTS_COSINE_MEDIAN_H
+#define STDLIB_STATS_BASE_DISTS_COSINE_MEDIAN_H
+
+/*
+* If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler.
+*/
+#ifdef __cplusplus
+extern "C" {
+#endif
+/**
+* Returns the median for a raised cosine distribution with location `mu` and scale `s`.
+*/
+double stdlib_base_dists_cosine_median( const double mu, const double s );
+
+#ifdef __cplusplus
+}
+#endif
+
+#endif // !STDLIB_STATS_BASE_DISTS_COSINE_MEDIAN_H
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/median/lib/native.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/lib/native.js
new file mode 100644
index 000000000000..339bbf4c2ac5
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/lib/native.js
@@ -0,0 +1,63 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var addon = require( './../src/addon.node' );
+
+
+// MAIN //
+
+/**
+* Returns the median for a raised cosine distribution with location `mu` and scale `s`.
+*
+* @private
+* @param {number} mu - location parameter
+* @param {PositiveNumber} s - scale parameter
+* @returns {number} median
+*
+* @example
+* var y = median( 0.0, 1.0 );
+* // returns 0.0
+*
+* @example
+* var y = median( 5.0, 2.0 );
+* // returns 5.0
+*
+* @example
+* var y = median( NaN, 1.0 );
+* // returns NaN
+*
+* @example
+* var y = median( 0.0, NaN );
+* // returns NaN
+*
+* @example
+* var y = median( 0.0, 0.0 );
+* // returns NaN
+*/
+function median( mu, s ) {
+	return addon( mu, s );
+}
+
+
+// EXPORTS //
+
+module.exports = median;
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/median/manifest.json b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/manifest.json
new file mode 100644
index 000000000000..93ccded754bf
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/manifest.json
@@ -0,0 +1,79 @@
+{
+  "options": {
+    "task": "build",
+    "wasm": false
+  },
+  "fields": [
+    {
+      "field": "src",
+      "resolve": true,
+      "relative": true
+    },
+    {
+      "field": "include",
+      "resolve": true,
+      "relative": true
+    },
+    {
+      "field": "libraries",
+      "resolve": false,
+      "relative": false
+    },
+    {
+      "field": "libpath",
+      "resolve": true,
+      "relative": false
+    }
+  ],
+  "confs": [
+    {
+      "task": "build",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/math/base/napi/binary",
+        "@stdlib/math/base/assert/is-nan",
+        "@stdlib/constants/float64/eps"
+      ]
+    },
+    {
+      "task": "benchmark",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/math/base/assert/is-nan",
+        "@stdlib/constants/float64/eps"
+      ]
+    },
+    {
+      "task": "examples",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/math/base/assert/is-nan",
+        "@stdlib/constants/float64/eps"
+      ]
+    }
+  ]
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/median/package.json b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/package.json
index de604bac259d..2576ab1702a7 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/cosine/median/package.json
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/package.json
@@ -14,11 +14,14 @@
     }
   ],
   "main": "./lib",
+  "gypfile": true,
   "directories": {
     "benchmark": "./benchmark",
     "doc": "./docs",
     "example": "./examples",
+    "include": "./include",
     "lib": "./lib",
+    "src": "./src",
     "test": "./test"
   },
   "types": "./docs/types",
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/median/src/Makefile b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/src/Makefile
new file mode 100644
index 000000000000..7733b6180cb4
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/src/Makefile
@@ -0,0 +1,70 @@
+#/
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#/
+
+# VARIABLES #
+
+ifndef VERBOSE
+	QUIET := @
+else
+	QUIET :=
+endif
+
+# Determine the OS ([1][1], [2][2]).
+#
+# [1]: https://en.wikipedia.org/wiki/Uname#Examples
+# [2]: http://stackoverflow.com/a/27776822/2225624
+OS ?= $(shell uname)
+ifneq (, $(findstring MINGW,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring MSYS,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring CYGWIN,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring Windows_NT,$(OS)))
+	OS := WINNT
+endif
+endif
+endif
+endif
+
+
+# RULES #
+
+#/
+# Removes generated files for building an add-on.
+#
+# @example
+# make clean-addon
+#/
+clean-addon:
+	$(QUIET) -rm -f *.o *.node
+
+.PHONY: clean-addon
+
+#/
+# Removes generated files.
+#
+# @example
+# make clean
+#/
+clean: clean-addon
+
+.PHONY: clean
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/median/src/addon.c b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/src/addon.c
new file mode 100644
index 000000000000..5d7758ec9cff
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/src/addon.c
@@ -0,0 +1,23 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/dists/cosine/median.h"
+#include "stdlib/math/base/napi/binary.h"
+
+// cppcheck-suppress shadowFunction
+STDLIB_MATH_BASE_NAPI_MODULE_DD_D( stdlib_base_dists_cosine_median )
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/median/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/src/main.c
new file mode 100644
index 000000000000..4d120b55c9a7
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/src/main.c
@@ -0,0 +1,42 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/dists/cosine/median.h"
+#include "stdlib/math/base/assert/is_nan.h"
+
+/**
+* Returns the mode for a raised cosine distribution with location `mu` and scale `s`.
+*
+* @param mu   location parameter
+* @param s    scale parameter
+* @return     median
+*
+* @example
+* double y = stdlib_base_dists_cosine_median( 0.0, 1.0 );
+* // returns 0.0
+*/
+double stdlib_base_dists_cosine_median( const double mu, const double s ) {
+	if ( 
+		stdlib_base_is_nan( mu ) ||
+		stdlib_base_is_nan( s ) ||
+		s <= 0.0
+	) {
+		return 0.0/0.0; // NaN
+	}
+	return mu;
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/median/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/test/test.native.js
new file mode 100644
index 000000000000..f01cbd74cd4b
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/median/test/test.native.js
@@ -0,0 +1,114 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var resolve = require( 'path' ).resolve;
+var tape = require( 'tape' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var abs = require( '@stdlib/math/base/special/abs' );
+var PINF = require( '@stdlib/constants/float64/pinf' );
+var NINF = require( '@stdlib/constants/float64/ninf' );
+var EPS = require( '@stdlib/constants/float64/eps' );
+var tryRequire = require( '@stdlib/utils/try-require' );
+
+
+// FIXTURES //
+
+var data = require( './fixtures/julia/data.json' );
+
+
+// VARIABLES //
+
+var median = tryRequire( resolve( __dirname, './../lib/native.js' ) );
+var opts = {
+	'skip': ( median instanceof Error )
+};
+
+
+// TESTS //
+
+tape( 'main export is a function', opts, function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof median, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'if provided `NaN` for any parameter, the function returns `NaN`', opts, function test( t ) {
+	var y = median( NaN, 1.0 );
+	t.equal( isnan( y ), true, 'returns NaN' );
+	y = median( 1.0, NaN );
+	t.equal( isnan( y ), true, 'returns NaN' );
+	t.end();
+});
+
+tape( 'if provided a nonpositive `s`, the function returns `NaN`', opts, function test( t ) {
+	var y;
+
+	y = median( 2.0, 0.0 );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	y = median( 2.0, -1.0 );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	y = median( 2.0, -1.0 );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	y = median( 1.0, NINF );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	y = median( PINF, NINF );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	y = median( NINF, NINF );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	y = median( NaN, NINF );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	t.end();
+});
+
+tape( 'the function returns the median of a raised cosine distribution', opts, function test( t ) {
+	var expected;
+	var delta;
+	var tol;
+	var mu;
+	var s;
+	var y;
+	var i;
+
+	expected = data.expected;
+	mu = data.mu;
+	s = data.s;
+	for ( i = 0; i < mu.length; i++ ) {
+		y = median( mu[i], s[i] );
+		if ( expected[i] !== null ) {
+			if ( y === expected[i] ) {
+				t.equal( y, expected[i], 'mu:'+mu[i]+', s: '+s[i]+', y: '+y+', expected: '+expected[i] );
+			} else {
+				delta = abs( y - expected[ i ] );
+				tol = 1.0 * EPS * abs( expected[ i ] );
+				t.ok( delta <= tol, 'within tolerance. mu: '+mu[i]+'. s: '+s[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
+			}
+		}
+	}
+	t.end();
+});

From e1a040eee651940db7cb7e8070562c001c3bd1ec Mon Sep 17 00:00:00 2001
From: JoyBoy <144602492+0PrashantYadav0@users.noreply.github.com>
Date: Fri, 3 Jan 2025 07:49:11 +0530
Subject: [PATCH 39/87] feat: add C implementation for
 `stats/base/dists/cosine/stdev`

PR-URL: https://github.com/stdlib-js/stdlib/pull/4468
Closes: https://github.com/stdlib-js/stdlib/issues/3525

Co-authored-by: Philipp Burckhardt <pburckhardt@outlook.com>
Reviewed-by: Philipp Burckhardt <pburckhardt@outlook.com>
Signed-off-by: JoyBoy <144602492+0PrashantYadav0@users.noreply.github.com>
Signed-off-by: Philipp Burckhardt <pburckhardt@outlook.com>
---
 .../stats/base/dists/cosine/stdev/README.md   |  96 ++++++++++
 .../dists/cosine/stdev/benchmark/benchmark.js |  14 +-
 .../stdev/benchmark/benchmark.native.js       |  71 ++++++++
 .../dists/cosine/stdev/benchmark/c/Makefile   | 146 +++++++++++++++
 .../cosine/stdev/benchmark/c/benchmark.c      | 141 +++++++++++++++
 .../stats/base/dists/cosine/stdev/binding.gyp | 170 ++++++++++++++++++
 .../dists/cosine/stdev/examples/c/Makefile    | 146 +++++++++++++++
 .../dists/cosine/stdev/examples/c/example.c   |  41 +++++
 .../base/dists/cosine/stdev/include.gypi      |  53 ++++++
 .../stdlib/stats/base/dists/cosine/stdev.h    |  37 ++++
 .../base/dists/cosine/stdev/lib/native.js     |  63 +++++++
 .../base/dists/cosine/stdev/manifest.json     |  85 +++++++++
 .../base/dists/cosine/stdev/package.json      |   3 +
 .../base/dists/cosine/stdev/src/Makefile      |  70 ++++++++
 .../stats/base/dists/cosine/stdev/src/addon.c |  23 +++
 .../stats/base/dists/cosine/stdev/src/main.c  |  44 +++++
 .../dists/cosine/stdev/test/test.native.js    | 114 ++++++++++++
 17 files changed, 1314 insertions(+), 3 deletions(-)
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/benchmark/benchmark.native.js
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/benchmark/c/Makefile
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/benchmark/c/benchmark.c
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/binding.gyp
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/examples/c/Makefile
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/examples/c/example.c
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/include.gypi
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/include/stdlib/stats/base/dists/cosine/stdev.h
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/lib/native.js
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/manifest.json
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/src/Makefile
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/src/addon.c
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/src/main.c
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/test/test.native.js

diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/README.md b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/README.md
index 6b22b0b93e6a..295665a00a15 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/README.md
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/README.md
@@ -131,6 +131,102 @@ for ( i = 0; i < 10; i++ ) {
 
 <!-- /.examples -->
 
+<!-- C interface documentation. -->
+
+<section class="c">
+
+## C APIs
+
+<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<!-- C usage documentation. -->
+
+<section class="usage">
+
+### Usage
+
+```c
+#include "stdlib/stats/base/dists/cosine/stdev.h"
+```
+
+#### stdlib_base_dists_cosine_stdev( mu, s )
+
+Returns the [standard deviation][stdev] for a [raised cosine][cosine-distribution] distribution with location parameter `mu` and scale parameter `s`.
+
+```c
+double out = stdlib_base_dists_cosine_stdev( 0.0, 1.0 );
+// returns ~0.362
+```
+
+The function accepts the following arguments:
+
+-   **mu**: `[in] double` location parameter.
+-   **s**: `[in] double` scale parameter.
+
+```c
+double stdlib_base_dists_cosine_stdev( const double mu, const double s );
+```
+
+</section>
+
+<!-- /.usage -->
+
+<!-- C API usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="notes">
+
+</section>
+
+<!-- /.notes -->
+
+<!-- C API usage examples. -->
+
+<section class="examples">
+
+### Examples
+
+```c
+#include "stdlib/stats/base/dists/cosine/stdev.h"
+#include "stdlib/constants/float64/eps.h"
+#include <stdlib.h>
+#include <stdio.h>
+
+static double random_uniform( const double min, const double max ) {
+    double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
+    return min + ( v * (max - min) );
+}
+
+int main( void ) {
+    double mu;
+    double s;
+    double y;
+    int i;
+
+    for ( i = 0; i < 10; i++ ) {
+        mu = random_uniform( -50.0, 50.0 );
+        s = random_uniform( 0.0, 20.0 ) + STDLIB_CONSTANT_FLOAT64_EPS;
+        y = stdlib_base_dists_cosine_stdev( mu, s );
+        printf( "µ: %lf, s: %lf, SD(X;µ,s): %lf\n", mu, s , y );
+    }
+
+    return 0;
+}
+```
+
+</section>
+
+<!-- /.examples -->
+
+</section>
+
+<!-- /.c -->
+
 <!-- Section to include cited references. If references are included, add a horizontal rule *before* the section. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
 
 <section class="references">
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/benchmark/benchmark.js
index 5544fb29feee..8f9f84b7521e 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/benchmark/benchmark.js
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/benchmark/benchmark.js
@@ -21,6 +21,7 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
+var Float64Array = require( '@stdlib/array/float64' );
 var randu = require( '@stdlib/random/base/randu' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var EPS = require( '@stdlib/constants/float64/eps' );
@@ -31,16 +32,23 @@ var stdev = require( './../lib' );
 // MAIN //
 
 bench( pkg, function benchmark( b ) {
+	var len;
 	var mu;
 	var s;
 	var y;
 	var i;
 
+	len = 100;
+	mu = new Float64Array( len );
+	s = new Float64Array( len );
+	for ( i = 0; i < len; i++ ) {
+		mu[ i ] = ( randu()*100.0 ) - 50.0;
+		s[ i ] = ( randu()*20.0 ) + EPS;
+	}
+
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		mu = ( randu()*100.0 ) - 50.0;
-		s = ( randu()*20.0 ) + EPS;
-		y = stdev( mu, s );
+		y = stdev( mu[ i % len ], s[ i % len ] );
 		if ( isnan( y ) ) {
 			b.fail( 'should not return NaN' );
 		}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/benchmark/benchmark.native.js
new file mode 100644
index 000000000000..f929b13622f3
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/benchmark/benchmark.native.js
@@ -0,0 +1,71 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var resolve = require( 'path' ).resolve;
+var bench = require( '@stdlib/bench' );
+var Float64Array = require( '@stdlib/array/float64' );
+var randu = require( '@stdlib/random/base/randu' );
+var EPS = require( '@stdlib/constants/float64/eps' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var tryRequire = require( '@stdlib/utils/try-require' );
+var pkg = require( './../package.json' ).name;
+
+
+// VARIABLES //
+
+var stdev = tryRequire( resolve( __dirname, './../lib/native.js' ) );
+var opts = {
+	'skip': ( stdev instanceof Error )
+};
+
+
+// MAIN //
+
+bench( pkg+'::native', opts, function benchmark( b ) {
+	var len;
+	var mu;
+	var s;
+	var y;
+	var i;
+
+	len = 100;
+	mu = new Float64Array( len );
+	s = new Float64Array( len );
+	for ( i = 0; i < len; i++ ) {
+		mu[ i ] = ( randu()*100.0 ) - 50.0;
+		s[ i ] = ( randu()*20.0 ) + EPS;
+	}
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		y = stdev( mu[ i % len ], s[ i % len ] );
+		if ( isnan( y ) ) {
+			b.fail( 'should not return NaN' );
+		}
+	}
+	b.toc();
+	if ( isnan( y ) ) {
+		b.fail( 'should not return NaN' );
+	}
+	b.pass( 'benchmark finished' );
+	b.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/benchmark/c/Makefile
new file mode 100644
index 000000000000..a4bd7b38fd74
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/benchmark/c/Makefile
@@ -0,0 +1,146 @@
+#/
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#/
+
+# VARIABLES #
+
+ifndef VERBOSE
+	QUIET := @
+else
+	QUIET :=
+endif
+
+# Determine the OS ([1][1], [2][2]).
+#
+# [1]: https://en.wikipedia.org/wiki/Uname#Examples
+# [2]: http://stackoverflow.com/a/27776822/2225624
+OS ?= $(shell uname)
+ifneq (, $(findstring MINGW,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring MSYS,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring CYGWIN,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring Windows_NT,$(OS)))
+	OS := WINNT
+endif
+endif
+endif
+endif
+
+# Define the program used for compiling C source files:
+ifdef C_COMPILER
+	CC := $(C_COMPILER)
+else
+	CC := gcc
+endif
+
+# Define the command-line options when compiling C files:
+CFLAGS ?= \
+	-std=c99 \
+	-O3 \
+	-Wall \
+	-pedantic
+
+# Determine whether to generate position independent code ([1][1], [2][2]).
+#
+# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options
+# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option
+ifeq ($(OS), WINNT)
+	fPIC ?=
+else
+	fPIC ?= -fPIC
+endif
+
+# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`):
+INCLUDE ?=
+
+# List of source files:
+SOURCE_FILES ?=
+
+# List of libraries (e.g., `-lopenblas -lpthread`):
+LIBRARIES ?=
+
+# List of library paths (e.g., `-L /foo/bar -L /beep/boop`):
+LIBPATH ?=
+
+# List of C targets:
+c_targets := benchmark.out
+
+
+# RULES #
+
+#/
+# Compiles source files.
+#
+# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`)
+# @param {string} [CFLAGS] - C compiler options
+# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`)
+# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`)
+# @param {string} [SOURCE_FILES] - list of source files
+# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`)
+# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`)
+#
+# @example
+# make
+#
+# @example
+# make all
+#/
+all: $(c_targets)
+
+.PHONY: all
+
+#/
+# Compiles C source files.
+#
+# @private
+# @param {string} CC - C compiler (e.g., `gcc`)
+# @param {string} CFLAGS - C compiler options
+# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`)
+# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`)
+# @param {string} SOURCE_FILES - list of source files
+# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`)
+# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`)
+#/
+$(c_targets): %.out: %.c
+	$(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES)
+
+#/
+# Runs compiled benchmarks.
+#
+# @example
+# make run
+#/
+run: $(c_targets)
+	$(QUIET) ./$<
+
+.PHONY: run
+
+#/
+# Removes generated files.
+#
+# @example
+# make clean
+#/
+clean:
+	$(QUIET) -rm -f *.o *.out
+
+.PHONY: clean
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/benchmark/c/benchmark.c
new file mode 100644
index 000000000000..3424ba3c5c5c
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/benchmark/c/benchmark.c
@@ -0,0 +1,141 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/dists/cosine/stdev.h"
+#include "stdlib/constants/float64/eps.h"
+#include <stdlib.h>
+#include <stdio.h>
+#include <math.h>
+#include <time.h>
+#include <sys/time.h>
+
+#define NAME "cosine-stdev"
+#define ITERATIONS 1000000
+#define REPEATS 3
+
+/**
+* Prints the TAP version.
+*/
+static void print_version( void ) {
+	printf( "TAP version 13\n" );
+}
+
+/**
+* Prints the TAP summary.
+*
+* @param total     total number of tests
+* @param passing   total number of passing tests
+*/
+static void print_summary( int total, int passing ) {
+	printf( "#\n" );
+	printf( "1..%d\n", total ); // TAP plan
+	printf( "# total %d\n", total );
+	printf( "# pass  %d\n", passing );
+	printf( "#\n" );
+	printf( "# ok\n" );
+}
+
+/**
+* Prints benchmarks results.
+*
+* @param elapsed   elapsed time in seconds
+*/
+static void print_results( double elapsed ) {
+	double rate = (double)ITERATIONS / elapsed;
+	printf( "  ---\n" );
+	printf( "  iterations: %d\n", ITERATIONS );
+	printf( "  elapsed: %0.9f\n", elapsed );
+	printf( "  rate: %0.9f\n", rate );
+	printf( "  ...\n" );
+}
+
+/**
+* Returns a clock time.
+*
+* @return clock time
+*/
+static double tic( void ) {
+	struct timeval now;
+	gettimeofday( &now, NULL );
+	return (double)now.tv_sec + (double)now.tv_usec/1.0e6;
+}
+
+/**
+* Generates a random number on the interval [min,max).
+*
+* @param min    minimum value (inclusive)
+* @param max    maximum value (exclusive)
+* @return       random number
+*/
+static double random_uniform( const double min, const double max ) {
+	double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
+	return min + ( v*(max-min) );
+}
+
+/**
+* Runs a benchmark.
+*
+* @return elapsed time in seconds
+*/
+static double benchmark( void ) {
+	double elapsed;
+	double mu[ 100 ];
+	double s[ 100 ];
+	double y;
+	double t;
+	int i;
+
+	for ( i = 0; i < 100; i++ ) {
+		mu[ i ] = random_uniform( -50.0, 50.0 );
+		s[ i ] = random_uniform( 0.0, 20.0 ) + STDLIB_CONSTANT_FLOAT64_EPS;
+	}
+
+	t = tic();
+	for ( i = 0; i < ITERATIONS; i++ ) {
+		y = stdlib_base_dists_cosine_stdev( mu[ i%100 ], s[ i%100 ] );
+		if ( y != y ) {
+			printf( "should not return NaN\n" );
+			break;
+		}
+	}
+	elapsed = tic() - t;
+	if ( y != y ) {
+		printf( "should not return NaN\n" );
+	}
+	return elapsed;
+}
+
+/**
+* Main execution sequence.
+*/
+int main( void ) {
+	double elapsed;
+	int i;
+
+	// Use the current time to seed the random number generator:
+	srand( time( NULL ) );
+
+	print_version();
+	for ( i = 0; i < REPEATS; i++ ) {
+		printf( "# c::%s\n", NAME );
+		elapsed = benchmark();
+		print_results( elapsed );
+		printf( "ok %d benchmark finished\n", i+1 );
+	}
+	print_summary( REPEATS, REPEATS );
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/binding.gyp
new file mode 100644
index 000000000000..68a1ca11d160
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/binding.gyp
@@ -0,0 +1,170 @@
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# A `.gyp` file for building a Node.js native add-on.
+#
+# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md
+# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md
+{
+  # List of files to include in this file:
+  'includes': [
+    './include.gypi',
+  ],
+
+  # Define variables to be used throughout the configuration for all targets:
+  'variables': {
+    # Target name should match the add-on export name:
+    'addon_target_name%': 'addon',
+
+    # Set variables based on the host OS:
+    'conditions': [
+      [
+        'OS=="win"',
+        {
+          # Define the object file suffix:
+          'obj': 'obj',
+        },
+        {
+          # Define the object file suffix:
+          'obj': 'o',
+        }
+      ], # end condition (OS=="win")
+    ], # end conditions
+  }, # end variables
+
+  # Define compile targets:
+  'targets': [
+
+    # Target to generate an add-on:
+    {
+      # The target name should match the add-on export name:
+      'target_name': '<(addon_target_name)',
+
+      # Define dependencies:
+      'dependencies': [],
+
+      # Define directories which contain relevant include headers:
+      'include_dirs': [
+        # Local include directory:
+        '<@(include_dirs)',
+      ],
+
+      # List of source files:
+      'sources': [
+        '<@(src_files)',
+      ],
+
+      # Settings which should be applied when a target's object files are used as linker input:
+      'link_settings': {
+        # Define libraries:
+        'libraries': [
+          '<@(libraries)',
+        ],
+
+        # Define library directories:
+        'library_dirs': [
+          '<@(library_dirs)',
+        ],
+      },
+
+      # C/C++ compiler flags:
+      'cflags': [
+        # Enable commonly used warning options:
+        '-Wall',
+
+        # Aggressive optimization:
+        '-O3',
+      ],
+
+      # C specific compiler flags:
+      'cflags_c': [
+        # Specify the C standard to which a program is expected to conform:
+        '-std=c99',
+      ],
+
+      # C++ specific compiler flags:
+      'cflags_cpp': [
+        # Specify the C++ standard to which a program is expected to conform:
+        '-std=c++11',
+      ],
+
+      # Linker flags:
+      'ldflags': [],
+
+      # Apply conditions based on the host OS:
+      'conditions': [
+        [
+          'OS=="mac"',
+          {
+            # Linker flags:
+            'ldflags': [
+              '-undefined dynamic_lookup',
+              '-Wl,-no-pie',
+              '-Wl,-search_paths_first',
+            ],
+          },
+        ], # end condition (OS=="mac")
+        [
+          'OS!="win"',
+          {
+            # C/C++ flags:
+            'cflags': [
+              # Generate platform-independent code:
+              '-fPIC',
+            ],
+          },
+        ], # end condition (OS!="win")
+      ], # end conditions
+    }, # end target <(addon_target_name)
+
+    # Target to copy a generated add-on to a standard location:
+    {
+      'target_name': 'copy_addon',
+
+      # Declare that the output of this target is not linked:
+      'type': 'none',
+
+      # Define dependencies:
+      'dependencies': [
+        # Require that the add-on be generated before building this target:
+        '<(addon_target_name)',
+      ],
+
+      # Define a list of actions:
+      'actions': [
+        {
+          'action_name': 'copy_addon',
+          'message': 'Copying addon...',
+
+          # Explicitly list the inputs in the command-line invocation below:
+          'inputs': [],
+
+          # Declare the expected outputs:
+          'outputs': [
+            '<(addon_output_dir)/<(addon_target_name).node',
+          ],
+
+          # Define the command-line invocation:
+          'action': [
+            'cp',
+            '<(PRODUCT_DIR)/<(addon_target_name).node',
+            '<(addon_output_dir)/<(addon_target_name).node',
+          ],
+        },
+      ], # end actions
+    }, # end target copy_addon
+  ], # end targets
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/examples/c/Makefile
new file mode 100644
index 000000000000..25ced822f96a
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/examples/c/Makefile
@@ -0,0 +1,146 @@
+#/
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#/
+
+# VARIABLES #
+
+ifndef VERBOSE
+	QUIET := @
+else
+	QUIET :=
+endif
+
+# Determine the OS ([1][1], [2][2]).
+#
+# [1]: https://en.wikipedia.org/wiki/Uname#Examples
+# [2]: http://stackoverflow.com/a/27776822/2225624
+OS ?= $(shell uname)
+ifneq (, $(findstring MINGW,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring MSYS,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring CYGWIN,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring Windows_NT,$(OS)))
+	OS := WINNT
+endif
+endif
+endif
+endif
+
+# Define the program used for compiling C source files:
+ifdef C_COMPILER
+	CC := $(C_COMPILER)
+else
+	CC := gcc
+endif
+
+# Define the command-line options when compiling C files:
+CFLAGS ?= \
+	-std=c99 \
+	-O3 \
+	-Wall \
+	-pedantic
+
+# Determine whether to generate position independent code ([1][1], [2][2]).
+#
+# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options
+# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option
+ifeq ($(OS), WINNT)
+	fPIC ?=
+else
+	fPIC ?= -fPIC
+endif
+
+# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`):
+INCLUDE ?=
+
+# List of source files:
+SOURCE_FILES ?=
+
+# List of libraries (e.g., `-lopenblas -lpthread`):
+LIBRARIES ?=
+
+# List of library paths (e.g., `-L /foo/bar -L /beep/boop`):
+LIBPATH ?=
+
+# List of C targets:
+c_targets := example.out
+
+
+# RULES #
+
+#/
+# Compiles source files.
+#
+# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`)
+# @param {string} [CFLAGS] - C compiler options
+# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`)
+# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`)
+# @param {string} [SOURCE_FILES] - list of source files
+# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`)
+# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`)
+#
+# @example
+# make
+#
+# @example
+# make all
+#/
+all: $(c_targets)
+
+.PHONY: all
+
+#/
+# Compiles C source files.
+#
+# @private
+# @param {string} CC - C compiler (e.g., `gcc`)
+# @param {string} CFLAGS - C compiler options
+# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`)
+# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`)
+# @param {string} SOURCE_FILES - list of source files
+# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`)
+# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`)
+#/
+$(c_targets): %.out: %.c
+	$(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES)
+
+#/
+# Runs compiled examples.
+#
+# @example
+# make run
+#/
+run: $(c_targets)
+	$(QUIET) ./$<
+
+.PHONY: run
+
+#/
+# Removes generated files.
+#
+# @example
+# make clean
+#/
+clean:
+	$(QUIET) -rm -f *.o *.out
+
+.PHONY: clean
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/examples/c/example.c
new file mode 100644
index 000000000000..0f70743ca6ac
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/examples/c/example.c
@@ -0,0 +1,41 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/dists/cosine/stdev.h"
+#include "stdlib/constants/float64/eps.h"
+#include <stdlib.h>
+#include <stdio.h>
+
+static double random_uniform( const double min, const double max ) {
+	double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
+	return min + ( v*(max-min) );
+}
+
+int main( void ) {
+	double mu;
+	double s;
+	double y;
+	int i;
+
+	for ( i = 0; i < 10; i++ ) {
+		mu = random_uniform( -50.0, 50.0 );
+		s = random_uniform( 0.0, 20.0 ) + STDLIB_CONSTANT_FLOAT64_EPS;
+		y = stdlib_base_dists_cosine_stdev( mu, s );
+		printf( "µ: %lf, s: %lf, SD(X;µ,s): %lf\n", mu, s , y );
+	}
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/include.gypi
new file mode 100644
index 000000000000..ecfaf82a3279
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/include.gypi
@@ -0,0 +1,53 @@
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# A GYP include file for building a Node.js native add-on.
+#
+# Main documentation:
+#
+# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md
+# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md
+{
+  # Define variables to be used throughout the configuration for all targets:
+  'variables': {
+    # Source directory:
+    'src_dir': './src',
+
+    # Include directories:
+    'include_dirs': [
+      '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).include; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
+    ],
+
+    # Add-on destination directory:
+    'addon_output_dir': './src',
+
+    # Source files:
+    'src_files': [
+      '<(src_dir)/addon.c',
+      '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).src; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
+    ],
+
+    # Library dependencies:
+    'libraries': [
+      '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).libraries; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
+    ],
+
+    # Library directories:
+    'library_dirs': [
+      '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).libpath; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
+    ],
+  }, # end variables
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/include/stdlib/stats/base/dists/cosine/stdev.h b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/include/stdlib/stats/base/dists/cosine/stdev.h
new file mode 100644
index 000000000000..81212a05720a
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/include/stdlib/stats/base/dists/cosine/stdev.h
@@ -0,0 +1,37 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#ifndef STDLIB_STATS_BASE_DISTS_COSINE_STDEV_H
+#define STDLIB_STATS_BASE_DISTS_COSINE_STDEV_H
+
+/*
+* If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler.
+*/
+#ifdef __cplusplus
+extern "C" {
+#endif
+/**
+* Returns the standard deviation for a raised cosine distribution with location `mu` and scale `s`.
+*/
+double stdlib_base_dists_cosine_stdev( const double mu, const double s );
+
+#ifdef __cplusplus
+}
+#endif
+
+#endif // !STDLIB_STATS_BASE_DISTS_COSINE_STDEV_H
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/lib/native.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/lib/native.js
new file mode 100644
index 000000000000..587da41da45a
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/lib/native.js
@@ -0,0 +1,63 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var addon = require( './../src/addon.node' );
+
+
+// MAIN //
+
+/**
+* Returns the standard deviation for a raised cosine distribution with location `mu` and scale `s`.
+*
+* @private
+* @param {number} mu - location parameter
+* @param {PositiveNumber} s - scale parameter
+* @returns {number} standard deviation
+*
+* @example
+* var y = stdev( 0.0, 1.0 );
+* // returns ~0.362
+*
+* @example
+* var y = stdev( 5.0, 2.0 );
+* // returns ~0.723
+*
+* @example
+* var y = stdev( NaN, 1.0 );
+* // returns NaN
+*
+* @example
+* var y = stdev( 0.0, NaN );
+* // returns NaN
+*
+* @example
+* var y = stdev( 0.0, 0.0 );
+* // returns NaN
+*/
+function stdev( mu, s ) {
+	return addon( mu, s );
+}
+
+
+// EXPORTS //
+
+module.exports = stdev;
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/manifest.json b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/manifest.json
new file mode 100644
index 000000000000..ced20f49d4e9
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/manifest.json
@@ -0,0 +1,85 @@
+{
+  "options": {
+    "task": "build",
+    "wasm": false
+  },
+  "fields": [
+    {
+      "field": "src",
+      "resolve": true,
+      "relative": true
+    },
+    {
+      "field": "include",
+      "resolve": true,
+      "relative": true
+    },
+    {
+      "field": "libraries",
+      "resolve": false,
+      "relative": false
+    },
+    {
+      "field": "libpath",
+      "resolve": true,
+      "relative": false
+    }
+  ],
+  "confs": [
+    {
+      "task": "build",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/math/base/napi/binary",
+        "@stdlib/math/base/assert/is-nan",
+        "@stdlib/constants/float64/eps",
+        "@stdlib/math/base/special/sqrt",
+        "@stdlib/constants/float64/pi-squared"
+      ]
+    },
+    {
+      "task": "benchmark",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/math/base/assert/is-nan",
+        "@stdlib/constants/float64/eps",
+        "@stdlib/math/base/special/sqrt",
+        "@stdlib/constants/float64/pi-squared"
+      ]
+    },
+    {
+      "task": "examples",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/math/base/assert/is-nan",
+        "@stdlib/constants/float64/eps",
+        "@stdlib/math/base/special/sqrt",
+        "@stdlib/constants/float64/pi-squared"
+      ]
+    }
+  ]
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/package.json b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/package.json
index 2038428d76ef..b78cf7690b31 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/package.json
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/package.json
@@ -14,11 +14,14 @@
     }
   ],
   "main": "./lib",
+  "gypfile": true,
   "directories": {
     "benchmark": "./benchmark",
     "doc": "./docs",
     "example": "./examples",
+    "include": "./include",
     "lib": "./lib",
+    "src": "./src",
     "test": "./test"
   },
   "types": "./docs/types",
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/src/Makefile b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/src/Makefile
new file mode 100644
index 000000000000..7733b6180cb4
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/src/Makefile
@@ -0,0 +1,70 @@
+#/
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#/
+
+# VARIABLES #
+
+ifndef VERBOSE
+	QUIET := @
+else
+	QUIET :=
+endif
+
+# Determine the OS ([1][1], [2][2]).
+#
+# [1]: https://en.wikipedia.org/wiki/Uname#Examples
+# [2]: http://stackoverflow.com/a/27776822/2225624
+OS ?= $(shell uname)
+ifneq (, $(findstring MINGW,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring MSYS,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring CYGWIN,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring Windows_NT,$(OS)))
+	OS := WINNT
+endif
+endif
+endif
+endif
+
+
+# RULES #
+
+#/
+# Removes generated files for building an add-on.
+#
+# @example
+# make clean-addon
+#/
+clean-addon:
+	$(QUIET) -rm -f *.o *.node
+
+.PHONY: clean-addon
+
+#/
+# Removes generated files.
+#
+# @example
+# make clean
+#/
+clean: clean-addon
+
+.PHONY: clean
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/src/addon.c b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/src/addon.c
new file mode 100644
index 000000000000..7ffe487c9706
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/src/addon.c
@@ -0,0 +1,23 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/dists/cosine/stdev.h"
+#include "stdlib/math/base/napi/binary.h"
+
+// cppcheck-suppress shadowFunction
+STDLIB_MATH_BASE_NAPI_MODULE_DD_D( stdlib_base_dists_cosine_stdev )
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/src/main.c
new file mode 100644
index 000000000000..c31bcc074c7f
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/src/main.c
@@ -0,0 +1,44 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/dists/cosine/stdev.h"
+#include "stdlib/math/base/assert/is_nan.h"
+#include "stdlib/math/base/special/sqrt.h"
+#include "stdlib/constants/float64/pi_squared.h"
+
+/**
+* Returns the mode for a raised cosine distribution with location `mu` and scale `s`.
+*
+* @param mu   location parameter
+* @param s    scale parameter
+* @return     standard deviation
+*
+* @example
+* double y = stdlib_base_dists_cosine_stdev( 0.0, 1.0 );
+* // returns ~0.362
+*/
+double stdlib_base_dists_cosine_stdev( const double mu, const double s ) {
+	if ( 
+		stdlib_base_is_nan( mu ) ||
+		stdlib_base_is_nan( s ) ||
+		s <= 0.0
+	) {
+		return 0.0/0.0; // NaN
+	}
+	return s * stdlib_base_sqrt( ( 1.0/3.0 ) - ( 2/STDLIB_CONSTANT_FLOAT64_PI_SQUARED ) );
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/test/test.native.js
new file mode 100644
index 000000000000..ac737e256fe2
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/stdev/test/test.native.js
@@ -0,0 +1,114 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var resolve = require( 'path' ).resolve;
+var tape = require( 'tape' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var abs = require( '@stdlib/math/base/special/abs' );
+var PINF = require( '@stdlib/constants/float64/pinf' );
+var NINF = require( '@stdlib/constants/float64/ninf' );
+var EPS = require( '@stdlib/constants/float64/eps' );
+var tryRequire = require( '@stdlib/utils/try-require' );
+
+
+// FIXTURES //
+
+var data = require( './fixtures/julia/data.json' );
+
+
+// VARIABLES //
+
+var stdev = tryRequire( resolve( __dirname, './../lib/native.js' ) );
+var opts = {
+	'skip': ( stdev instanceof Error )
+};
+
+
+// TESTS //
+
+tape( 'main export is a function', opts, function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof stdev, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'if provided `NaN` for any parameter, the function returns `NaN`', opts, function test( t ) {
+	var y = stdev( NaN, 1.0 );
+	t.equal( isnan( y ), true, 'returns NaN' );
+	y = stdev( 1.0, NaN );
+	t.equal( isnan( y ), true, 'returns NaN' );
+	t.end();
+});
+
+tape( 'if provided a nonpositive `s`, the function returns `NaN`', opts, function test( t ) {
+	var y;
+
+	y = stdev( 2.0, 0.0 );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	y = stdev( 2.0, -1.0 );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	y = stdev( 2.0, -1.0 );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	y = stdev( 1.0, NINF );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	y = stdev( PINF, NINF );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	y = stdev( NINF, NINF );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	y = stdev( NaN, NINF );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	t.end();
+});
+
+tape( 'the function returns the stdev of a raised cosine distribution', opts, function test( t ) {
+	var expected;
+	var delta;
+	var tol;
+	var mu;
+	var s;
+	var y;
+	var i;
+
+	expected = data.expected;
+	mu = data.mu;
+	s = data.s;
+	for ( i = 0; i < mu.length; i++ ) {
+		y = stdev( mu[i], s[i] );
+		if ( expected[i] !== null ) {
+			if ( y === expected[i] ) {
+				t.equal( y, expected[i], 'mu:'+mu[i]+', s: '+s[i]+', y: '+y+', expected: '+expected[i] );
+			} else {
+				delta = abs( y - expected[ i ] );
+				tol = 2.0 * EPS * abs( expected[ i ] );
+				t.ok( delta <= tol, 'within tolerance. mu: '+mu[i]+'. s: '+s[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
+			}
+		}
+	}
+	t.end();
+});

From 87788fee5792e3dd23a1a3d9cc593496c29d2eda Mon Sep 17 00:00:00 2001
From: JoyBoy <144602492+0PrashantYadav0@users.noreply.github.com>
Date: Fri, 3 Jan 2025 07:50:29 +0530
Subject: [PATCH 40/87] feat: add C implementation for
 `stats/base/dists/cosine/mode`

PR-URL: https://github.com/stdlib-js/stdlib/pull/4476
Closes: https://github.com/stdlib-js/stdlib/issues/3521

Co-authored-by: Philipp Burckhardt <pburckhardt@outlook.com>
Reviewed-by: Philipp Burckhardt <pburckhardt@outlook.com>
Signed-off-by: Philipp Burckhardt <pburckhardt@outlook.com>
---
 .../stats/base/dists/cosine/mode/README.md    |  96 ++++++++++
 .../dists/cosine/mode/benchmark/benchmark.js  |  14 +-
 .../cosine/mode/benchmark/benchmark.native.js |  71 ++++++++
 .../dists/cosine/mode/benchmark/c/Makefile    | 146 +++++++++++++++
 .../dists/cosine/mode/benchmark/c/benchmark.c | 141 +++++++++++++++
 .../stats/base/dists/cosine/mode/binding.gyp  | 170 ++++++++++++++++++
 .../dists/cosine/mode/examples/c/Makefile     | 146 +++++++++++++++
 .../dists/cosine/mode/examples/c/example.c    |  41 +++++
 .../stats/base/dists/cosine/mode/include.gypi |  53 ++++++
 .../stdlib/stats/base/dists/cosine/mode.h     |  37 ++++
 .../base/dists/cosine/mode/lib/native.js      |  63 +++++++
 .../base/dists/cosine/mode/manifest.json      |  79 ++++++++
 .../stats/base/dists/cosine/mode/package.json |   3 +
 .../stats/base/dists/cosine/mode/src/Makefile |  70 ++++++++
 .../stats/base/dists/cosine/mode/src/addon.c  |  23 +++
 .../stats/base/dists/cosine/mode/src/main.c   |  42 +++++
 .../dists/cosine/mode/test/test.native.js     | 114 ++++++++++++
 17 files changed, 1306 insertions(+), 3 deletions(-)
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/mode/benchmark/benchmark.native.js
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/mode/benchmark/c/Makefile
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/mode/benchmark/c/benchmark.c
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/mode/binding.gyp
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/mode/examples/c/Makefile
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/mode/examples/c/example.c
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/mode/include.gypi
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/mode/include/stdlib/stats/base/dists/cosine/mode.h
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/mode/lib/native.js
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/mode/manifest.json
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/mode/src/Makefile
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/mode/src/addon.c
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/mode/src/main.c
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/cosine/mode/test/test.native.js

diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/README.md b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/README.md
index 6a2ef13c044b..228f50104247 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/README.md
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/README.md
@@ -131,6 +131,102 @@ for ( i = 0; i < 10; i++ ) {
 
 <!-- /.examples -->
 
+<!-- C interface documentation. -->
+
+<section class="c">
+
+## C APIs
+
+<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<!-- C usage documentation. -->
+
+<section class="usage">
+
+### Usage
+
+```c
+#include "stdlib/stats/base/dists/cosine/mode.h"
+```
+
+#### stdlib_base_dists_cosine_mode( mu, s )
+
+Returns the [mode][mode] for a [raised cosine][cosine-distribution] distribution with location parameter `mu` and scale parameter `s`.
+
+```c
+double out = stdlib_base_dists_cosine_mode( 0.0, 1.0 );
+// returns 0.0
+```
+
+The function accepts the following arguments:
+
+-   **mu**: `[in] double` location parameter.
+-   **s**: `[in] double` scale parameter.
+
+```c
+double stdlib_base_dists_cosine_mode( const double mu, const double s );
+```
+
+</section>
+
+<!-- /.usage -->
+
+<!-- C API usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="notes">
+
+</section>
+
+<!-- /.notes -->
+
+<!-- C API usage examples. -->
+
+<section class="examples">
+
+### Examples
+
+```c
+#include "stdlib/stats/base/dists/cosine/mode.h"
+#include "stdlib/constants/float64/eps.h"
+#include <stdlib.h>
+#include <stdio.h>
+
+static double random_uniform( const double min, const double max ) {
+    double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
+    return min + ( v * (max - min) );
+}
+
+int main( void ) {
+    double mu;
+    double s;
+    double y;
+    int i;
+
+    for ( i = 0; i < 10; i++ ) {
+        mu = random_uniform( -50.0, 50.0 );
+        s = random_uniform( 0.0, 20.0 ) + STDLIB_CONSTANT_FLOAT64_EPS;
+        y = stdlib_base_dists_cosine_mode( mu, s );
+        printf( "µ: %lf, s: %lf, mode(X;µ,s): %lf\n", mu, s , y );
+    }
+
+    return 0;
+}
+```
+
+</section>
+
+<!-- /.examples -->
+
+</section>
+
+<!-- /.c -->
+
 <!-- Section to include cited references. If references are included, add a horizontal rule *before* the section. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
 
 <section class="references">
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/benchmark/benchmark.js
index dec66e180c0f..5cf431a76211 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/benchmark/benchmark.js
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/benchmark/benchmark.js
@@ -21,6 +21,7 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
+var Float64Array = require( '@stdlib/array/float64' );
 var randu = require( '@stdlib/random/base/randu' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var EPS = require( '@stdlib/constants/float64/eps' );
@@ -31,16 +32,23 @@ var mode = require( './../lib' );
 // MAIN //
 
 bench( pkg, function benchmark( b ) {
+	var len;
 	var mu;
 	var s;
 	var y;
 	var i;
 
+	len = 100;
+	mu = new Float64Array( len );
+	s = new Float64Array( len );
+	for ( i = 0; i < len; i++ ) {
+		mu[ i ] = ( randu()*100.0 ) - 50.0;
+		s[ i ] = ( randu()*20.0 ) + EPS;
+	}
+
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		mu = ( randu()*100.0 ) - 50.0;
-		s = ( randu()*20.0 ) + EPS;
-		y = mode( mu, s );
+		y = mode( mu[ i % len ], s[ i % len ] );
 		if ( isnan( y ) ) {
 			b.fail( 'should not return NaN' );
 		}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/benchmark/benchmark.native.js
new file mode 100644
index 000000000000..7fa1ff79dd31
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/benchmark/benchmark.native.js
@@ -0,0 +1,71 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var resolve = require( 'path' ).resolve;
+var bench = require( '@stdlib/bench' );
+var Float64Array = require( '@stdlib/array/float64' );
+var randu = require( '@stdlib/random/base/randu' );
+var EPS = require( '@stdlib/constants/float64/eps' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var tryRequire = require( '@stdlib/utils/try-require' );
+var pkg = require( './../package.json' ).name;
+
+
+// VARIABLES //
+
+var mode = tryRequire( resolve( __dirname, './../lib/native.js' ) );
+var opts = {
+	'skip': ( mode instanceof Error )
+};
+
+
+// MAIN //
+
+bench( pkg+'::native', opts, function benchmark( b ) {
+	var len;
+	var mu;
+	var s;
+	var y;
+	var i;
+
+	len = 100;
+	mu = new Float64Array( len );
+	s = new Float64Array( len );
+	for ( i = 0; i < len; i++ ) {
+		mu[ i ] = ( randu()*100.0 ) - 50.0;
+		s[ i ] = ( randu()*20.0 ) + EPS;
+	}
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		y = mode( mu[ i % len ], s[ i % len ] );
+		if ( isnan( y ) ) {
+			b.fail( 'should not return NaN' );
+		}
+	}
+	b.toc();
+	if ( isnan( y ) ) {
+		b.fail( 'should not return NaN' );
+	}
+	b.pass( 'benchmark finished' );
+	b.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/benchmark/c/Makefile
new file mode 100644
index 000000000000..a4bd7b38fd74
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/benchmark/c/Makefile
@@ -0,0 +1,146 @@
+#/
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#/
+
+# VARIABLES #
+
+ifndef VERBOSE
+	QUIET := @
+else
+	QUIET :=
+endif
+
+# Determine the OS ([1][1], [2][2]).
+#
+# [1]: https://en.wikipedia.org/wiki/Uname#Examples
+# [2]: http://stackoverflow.com/a/27776822/2225624
+OS ?= $(shell uname)
+ifneq (, $(findstring MINGW,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring MSYS,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring CYGWIN,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring Windows_NT,$(OS)))
+	OS := WINNT
+endif
+endif
+endif
+endif
+
+# Define the program used for compiling C source files:
+ifdef C_COMPILER
+	CC := $(C_COMPILER)
+else
+	CC := gcc
+endif
+
+# Define the command-line options when compiling C files:
+CFLAGS ?= \
+	-std=c99 \
+	-O3 \
+	-Wall \
+	-pedantic
+
+# Determine whether to generate position independent code ([1][1], [2][2]).
+#
+# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options
+# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option
+ifeq ($(OS), WINNT)
+	fPIC ?=
+else
+	fPIC ?= -fPIC
+endif
+
+# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`):
+INCLUDE ?=
+
+# List of source files:
+SOURCE_FILES ?=
+
+# List of libraries (e.g., `-lopenblas -lpthread`):
+LIBRARIES ?=
+
+# List of library paths (e.g., `-L /foo/bar -L /beep/boop`):
+LIBPATH ?=
+
+# List of C targets:
+c_targets := benchmark.out
+
+
+# RULES #
+
+#/
+# Compiles source files.
+#
+# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`)
+# @param {string} [CFLAGS] - C compiler options
+# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`)
+# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`)
+# @param {string} [SOURCE_FILES] - list of source files
+# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`)
+# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`)
+#
+# @example
+# make
+#
+# @example
+# make all
+#/
+all: $(c_targets)
+
+.PHONY: all
+
+#/
+# Compiles C source files.
+#
+# @private
+# @param {string} CC - C compiler (e.g., `gcc`)
+# @param {string} CFLAGS - C compiler options
+# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`)
+# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`)
+# @param {string} SOURCE_FILES - list of source files
+# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`)
+# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`)
+#/
+$(c_targets): %.out: %.c
+	$(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES)
+
+#/
+# Runs compiled benchmarks.
+#
+# @example
+# make run
+#/
+run: $(c_targets)
+	$(QUIET) ./$<
+
+.PHONY: run
+
+#/
+# Removes generated files.
+#
+# @example
+# make clean
+#/
+clean:
+	$(QUIET) -rm -f *.o *.out
+
+.PHONY: clean
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/benchmark/c/benchmark.c
new file mode 100644
index 000000000000..59471bf31e27
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/benchmark/c/benchmark.c
@@ -0,0 +1,141 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/dists/cosine/mode.h"
+#include "stdlib/constants/float64/eps.h"
+#include <stdlib.h>
+#include <stdio.h>
+#include <math.h>
+#include <time.h>
+#include <sys/time.h>
+
+#define NAME "cosine-mode"
+#define ITERATIONS 1000000
+#define REPEATS 3
+
+/**
+* Prints the TAP version.
+*/
+static void print_version( void ) {
+	printf( "TAP version 13\n" );
+}
+
+/**
+* Prints the TAP summary.
+*
+* @param total     total number of tests
+* @param passing   total number of passing tests
+*/
+static void print_summary( int total, int passing ) {
+	printf( "#\n" );
+	printf( "1..%d\n", total ); // TAP plan
+	printf( "# total %d\n", total );
+	printf( "# pass  %d\n", passing );
+	printf( "#\n" );
+	printf( "# ok\n" );
+}
+
+/**
+* Prints benchmarks results.
+*
+* @param elapsed   elapsed time in seconds
+*/
+static void print_results( double elapsed ) {
+	double rate = (double)ITERATIONS / elapsed;
+	printf( "  ---\n" );
+	printf( "  iterations: %d\n", ITERATIONS );
+	printf( "  elapsed: %0.9f\n", elapsed );
+	printf( "  rate: %0.9f\n", rate );
+	printf( "  ...\n" );
+}
+
+/**
+* Returns a clock time.
+*
+* @return clock time
+*/
+static double tic( void ) {
+	struct timeval now;
+	gettimeofday( &now, NULL );
+	return (double)now.tv_sec + (double)now.tv_usec/1.0e6;
+}
+
+/**
+* Generates a random number on the interval [min,max).
+*
+* @param min    minimum value (inclusive)
+* @param max    maximum value (exclusive)
+* @return       random number
+*/
+static double random_uniform( const double min, const double max ) {
+	double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
+	return min + ( v*(max-min) );
+}
+
+/**
+* Runs a benchmark.
+*
+* @return elapsed time in seconds
+*/
+static double benchmark( void ) {
+	double elapsed;
+	double mu[ 100 ];
+	double s[ 100 ];
+	double y;
+	double t;
+	int i;
+
+	for ( i = 0; i < 100; i++ ) {
+		mu[ i ] = random_uniform( -50.0, 50.0 );
+		s[ i ] = random_uniform( 0.0, 20.0 ) + STDLIB_CONSTANT_FLOAT64_EPS;
+	}
+
+	t = tic();
+	for ( i = 0; i < ITERATIONS; i++ ) {
+		y = stdlib_base_dists_cosine_mode( mu[ i%100 ], s[ i%100 ] );
+		if ( y != y ) {
+			printf( "should not return NaN\n" );
+			break;
+		}
+	}
+	elapsed = tic() - t;
+	if ( y != y ) {
+		printf( "should not return NaN\n" );
+	}
+	return elapsed;
+}
+
+/**
+* Main execution sequence.
+*/
+int main( void ) {
+	double elapsed;
+	int i;
+
+	// Use the current time to seed the random number generator:
+	srand( time( NULL ) );
+
+	print_version();
+	for ( i = 0; i < REPEATS; i++ ) {
+		printf( "# c::%s\n", NAME );
+		elapsed = benchmark();
+		print_results( elapsed );
+		printf( "ok %d benchmark finished\n", i+1 );
+	}
+	print_summary( REPEATS, REPEATS );
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/binding.gyp
new file mode 100644
index 000000000000..68a1ca11d160
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/binding.gyp
@@ -0,0 +1,170 @@
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# A `.gyp` file for building a Node.js native add-on.
+#
+# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md
+# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md
+{
+  # List of files to include in this file:
+  'includes': [
+    './include.gypi',
+  ],
+
+  # Define variables to be used throughout the configuration for all targets:
+  'variables': {
+    # Target name should match the add-on export name:
+    'addon_target_name%': 'addon',
+
+    # Set variables based on the host OS:
+    'conditions': [
+      [
+        'OS=="win"',
+        {
+          # Define the object file suffix:
+          'obj': 'obj',
+        },
+        {
+          # Define the object file suffix:
+          'obj': 'o',
+        }
+      ], # end condition (OS=="win")
+    ], # end conditions
+  }, # end variables
+
+  # Define compile targets:
+  'targets': [
+
+    # Target to generate an add-on:
+    {
+      # The target name should match the add-on export name:
+      'target_name': '<(addon_target_name)',
+
+      # Define dependencies:
+      'dependencies': [],
+
+      # Define directories which contain relevant include headers:
+      'include_dirs': [
+        # Local include directory:
+        '<@(include_dirs)',
+      ],
+
+      # List of source files:
+      'sources': [
+        '<@(src_files)',
+      ],
+
+      # Settings which should be applied when a target's object files are used as linker input:
+      'link_settings': {
+        # Define libraries:
+        'libraries': [
+          '<@(libraries)',
+        ],
+
+        # Define library directories:
+        'library_dirs': [
+          '<@(library_dirs)',
+        ],
+      },
+
+      # C/C++ compiler flags:
+      'cflags': [
+        # Enable commonly used warning options:
+        '-Wall',
+
+        # Aggressive optimization:
+        '-O3',
+      ],
+
+      # C specific compiler flags:
+      'cflags_c': [
+        # Specify the C standard to which a program is expected to conform:
+        '-std=c99',
+      ],
+
+      # C++ specific compiler flags:
+      'cflags_cpp': [
+        # Specify the C++ standard to which a program is expected to conform:
+        '-std=c++11',
+      ],
+
+      # Linker flags:
+      'ldflags': [],
+
+      # Apply conditions based on the host OS:
+      'conditions': [
+        [
+          'OS=="mac"',
+          {
+            # Linker flags:
+            'ldflags': [
+              '-undefined dynamic_lookup',
+              '-Wl,-no-pie',
+              '-Wl,-search_paths_first',
+            ],
+          },
+        ], # end condition (OS=="mac")
+        [
+          'OS!="win"',
+          {
+            # C/C++ flags:
+            'cflags': [
+              # Generate platform-independent code:
+              '-fPIC',
+            ],
+          },
+        ], # end condition (OS!="win")
+      ], # end conditions
+    }, # end target <(addon_target_name)
+
+    # Target to copy a generated add-on to a standard location:
+    {
+      'target_name': 'copy_addon',
+
+      # Declare that the output of this target is not linked:
+      'type': 'none',
+
+      # Define dependencies:
+      'dependencies': [
+        # Require that the add-on be generated before building this target:
+        '<(addon_target_name)',
+      ],
+
+      # Define a list of actions:
+      'actions': [
+        {
+          'action_name': 'copy_addon',
+          'message': 'Copying addon...',
+
+          # Explicitly list the inputs in the command-line invocation below:
+          'inputs': [],
+
+          # Declare the expected outputs:
+          'outputs': [
+            '<(addon_output_dir)/<(addon_target_name).node',
+          ],
+
+          # Define the command-line invocation:
+          'action': [
+            'cp',
+            '<(PRODUCT_DIR)/<(addon_target_name).node',
+            '<(addon_output_dir)/<(addon_target_name).node',
+          ],
+        },
+      ], # end actions
+    }, # end target copy_addon
+  ], # end targets
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/examples/c/Makefile
new file mode 100644
index 000000000000..25ced822f96a
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/examples/c/Makefile
@@ -0,0 +1,146 @@
+#/
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#/
+
+# VARIABLES #
+
+ifndef VERBOSE
+	QUIET := @
+else
+	QUIET :=
+endif
+
+# Determine the OS ([1][1], [2][2]).
+#
+# [1]: https://en.wikipedia.org/wiki/Uname#Examples
+# [2]: http://stackoverflow.com/a/27776822/2225624
+OS ?= $(shell uname)
+ifneq (, $(findstring MINGW,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring MSYS,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring CYGWIN,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring Windows_NT,$(OS)))
+	OS := WINNT
+endif
+endif
+endif
+endif
+
+# Define the program used for compiling C source files:
+ifdef C_COMPILER
+	CC := $(C_COMPILER)
+else
+	CC := gcc
+endif
+
+# Define the command-line options when compiling C files:
+CFLAGS ?= \
+	-std=c99 \
+	-O3 \
+	-Wall \
+	-pedantic
+
+# Determine whether to generate position independent code ([1][1], [2][2]).
+#
+# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options
+# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option
+ifeq ($(OS), WINNT)
+	fPIC ?=
+else
+	fPIC ?= -fPIC
+endif
+
+# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`):
+INCLUDE ?=
+
+# List of source files:
+SOURCE_FILES ?=
+
+# List of libraries (e.g., `-lopenblas -lpthread`):
+LIBRARIES ?=
+
+# List of library paths (e.g., `-L /foo/bar -L /beep/boop`):
+LIBPATH ?=
+
+# List of C targets:
+c_targets := example.out
+
+
+# RULES #
+
+#/
+# Compiles source files.
+#
+# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`)
+# @param {string} [CFLAGS] - C compiler options
+# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`)
+# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`)
+# @param {string} [SOURCE_FILES] - list of source files
+# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`)
+# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`)
+#
+# @example
+# make
+#
+# @example
+# make all
+#/
+all: $(c_targets)
+
+.PHONY: all
+
+#/
+# Compiles C source files.
+#
+# @private
+# @param {string} CC - C compiler (e.g., `gcc`)
+# @param {string} CFLAGS - C compiler options
+# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`)
+# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`)
+# @param {string} SOURCE_FILES - list of source files
+# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`)
+# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`)
+#/
+$(c_targets): %.out: %.c
+	$(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES)
+
+#/
+# Runs compiled examples.
+#
+# @example
+# make run
+#/
+run: $(c_targets)
+	$(QUIET) ./$<
+
+.PHONY: run
+
+#/
+# Removes generated files.
+#
+# @example
+# make clean
+#/
+clean:
+	$(QUIET) -rm -f *.o *.out
+
+.PHONY: clean
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/examples/c/example.c
new file mode 100644
index 000000000000..8b1d1c072c12
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/examples/c/example.c
@@ -0,0 +1,41 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/dists/cosine/mode.h"
+#include "stdlib/constants/float64/eps.h"
+#include <stdlib.h>
+#include <stdio.h>
+
+static double random_uniform( const double min, const double max ) {
+	double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
+	return min + ( v*(max-min) );
+}
+
+int main( void ) {
+	double mu;
+	double s;
+	double y;
+	int i;
+
+	for ( i = 0; i < 10; i++ ) {
+		mu = random_uniform( -50.0, 50.0 );
+		s = random_uniform( 0.0, 20.0 ) + STDLIB_CONSTANT_FLOAT64_EPS;
+		y = stdlib_base_dists_cosine_mode( mu, s );
+		printf( "µ: %lf, s: %lf, mode(X;µ,s): %lf\n", mu, s , y );
+	}
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/include.gypi
new file mode 100644
index 000000000000..ecfaf82a3279
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/include.gypi
@@ -0,0 +1,53 @@
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# A GYP include file for building a Node.js native add-on.
+#
+# Main documentation:
+#
+# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md
+# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md
+{
+  # Define variables to be used throughout the configuration for all targets:
+  'variables': {
+    # Source directory:
+    'src_dir': './src',
+
+    # Include directories:
+    'include_dirs': [
+      '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).include; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
+    ],
+
+    # Add-on destination directory:
+    'addon_output_dir': './src',
+
+    # Source files:
+    'src_files': [
+      '<(src_dir)/addon.c',
+      '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).src; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
+    ],
+
+    # Library dependencies:
+    'libraries': [
+      '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).libraries; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
+    ],
+
+    # Library directories:
+    'library_dirs': [
+      '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).libpath; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
+    ],
+  }, # end variables
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/include/stdlib/stats/base/dists/cosine/mode.h b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/include/stdlib/stats/base/dists/cosine/mode.h
new file mode 100644
index 000000000000..7caa74a6674d
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/include/stdlib/stats/base/dists/cosine/mode.h
@@ -0,0 +1,37 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#ifndef STDLIB_STATS_BASE_DISTS_COSINE_MODE_H
+#define STDLIB_STATS_BASE_DISTS_COSINE_MODE_H
+
+/*
+* If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler.
+*/
+#ifdef __cplusplus
+extern "C" {
+#endif
+/**
+* Returns the mode for a raised cosine distribution with location `mu` and scale `s`.
+*/
+double stdlib_base_dists_cosine_mode( const double mu, const double s );
+
+#ifdef __cplusplus
+}
+#endif
+
+#endif // !STDLIB_STATS_BASE_DISTS_COSINE_MODE_H
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/lib/native.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/lib/native.js
new file mode 100644
index 000000000000..e7007d612d0a
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/lib/native.js
@@ -0,0 +1,63 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var addon = require( './../src/addon.node' );
+
+
+// MAIN //
+
+/**
+* Returns the mode for a raised cosine distribution with location `mu` and scale `s`.
+*
+* @private
+* @param {number} mu - location parameter
+* @param {PositiveNumber} s - scale parameter
+* @returns {number} mode
+*
+* @example
+* var y = mode( 0.0, 1.0 );
+* // returns 0.0
+*
+* @example
+* var y = mode( 5.0, 2.0 );
+* // returns 5.0
+*
+* @example
+* var y = mode( NaN, 1.0 );
+* // returns NaN
+*
+* @example
+* var y = mode( 0.0, NaN );
+* // returns NaN
+*
+* @example
+* var y = mode( 0.0, 0.0 );
+* // returns NaN
+*/
+function mode( mu, s ) {
+	return addon( mu, s );
+}
+
+
+// EXPORTS //
+
+module.exports = mode;
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/manifest.json b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/manifest.json
new file mode 100644
index 000000000000..93ccded754bf
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/manifest.json
@@ -0,0 +1,79 @@
+{
+  "options": {
+    "task": "build",
+    "wasm": false
+  },
+  "fields": [
+    {
+      "field": "src",
+      "resolve": true,
+      "relative": true
+    },
+    {
+      "field": "include",
+      "resolve": true,
+      "relative": true
+    },
+    {
+      "field": "libraries",
+      "resolve": false,
+      "relative": false
+    },
+    {
+      "field": "libpath",
+      "resolve": true,
+      "relative": false
+    }
+  ],
+  "confs": [
+    {
+      "task": "build",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/math/base/napi/binary",
+        "@stdlib/math/base/assert/is-nan",
+        "@stdlib/constants/float64/eps"
+      ]
+    },
+    {
+      "task": "benchmark",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/math/base/assert/is-nan",
+        "@stdlib/constants/float64/eps"
+      ]
+    },
+    {
+      "task": "examples",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/math/base/assert/is-nan",
+        "@stdlib/constants/float64/eps"
+      ]
+    }
+  ]
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/package.json b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/package.json
index 685d5cc2284f..8068ddd5583a 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/package.json
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/package.json
@@ -14,11 +14,14 @@
     }
   ],
   "main": "./lib",
+  "gypfile": true,
   "directories": {
     "benchmark": "./benchmark",
     "doc": "./docs",
     "example": "./examples",
+    "include": "./include",
     "lib": "./lib",
+    "src": "./src",
     "test": "./test"
   },
   "types": "./docs/types",
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/src/Makefile b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/src/Makefile
new file mode 100644
index 000000000000..7733b6180cb4
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/src/Makefile
@@ -0,0 +1,70 @@
+#/
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#/
+
+# VARIABLES #
+
+ifndef VERBOSE
+	QUIET := @
+else
+	QUIET :=
+endif
+
+# Determine the OS ([1][1], [2][2]).
+#
+# [1]: https://en.wikipedia.org/wiki/Uname#Examples
+# [2]: http://stackoverflow.com/a/27776822/2225624
+OS ?= $(shell uname)
+ifneq (, $(findstring MINGW,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring MSYS,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring CYGWIN,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring Windows_NT,$(OS)))
+	OS := WINNT
+endif
+endif
+endif
+endif
+
+
+# RULES #
+
+#/
+# Removes generated files for building an add-on.
+#
+# @example
+# make clean-addon
+#/
+clean-addon:
+	$(QUIET) -rm -f *.o *.node
+
+.PHONY: clean-addon
+
+#/
+# Removes generated files.
+#
+# @example
+# make clean
+#/
+clean: clean-addon
+
+.PHONY: clean
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/src/addon.c b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/src/addon.c
new file mode 100644
index 000000000000..771b8091c6f0
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/src/addon.c
@@ -0,0 +1,23 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/dists/cosine/mode.h"
+#include "stdlib/math/base/napi/binary.h"
+
+// cppcheck-suppress shadowFunction
+STDLIB_MATH_BASE_NAPI_MODULE_DD_D( stdlib_base_dists_cosine_mode )
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/src/main.c
new file mode 100644
index 000000000000..c879fbbf20de
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/src/main.c
@@ -0,0 +1,42 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/dists/cosine/mode.h"
+#include "stdlib/math/base/assert/is_nan.h"
+
+/**
+* Returns the mode for a raised cosine distribution with location `mu` and scale `s`.
+*
+* @param mu   location parameter
+* @param s    scale parameter
+* @return     mode
+*
+* @example
+* double y = stdlib_base_dists_cosine_mode( 0.0, 1.0 );
+* // returns 0.0
+*/
+double stdlib_base_dists_cosine_mode( const double mu, const double s ) {
+	if ( 
+		stdlib_base_is_nan( mu ) ||
+		stdlib_base_is_nan( s ) ||
+		s <= 0.0
+	) {
+		return 0.0/0.0; // NaN
+	}
+	return mu;
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/test/test.native.js
new file mode 100644
index 000000000000..2bf0223d7b7c
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/cosine/mode/test/test.native.js
@@ -0,0 +1,114 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var resolve = require( 'path' ).resolve;
+var tape = require( 'tape' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var abs = require( '@stdlib/math/base/special/abs' );
+var PINF = require( '@stdlib/constants/float64/pinf' );
+var NINF = require( '@stdlib/constants/float64/ninf' );
+var EPS = require( '@stdlib/constants/float64/eps' );
+var tryRequire = require( '@stdlib/utils/try-require' );
+
+
+// FIXTURES //
+
+var data = require( './fixtures/julia/data.json' );
+
+
+// VARIABLES //
+
+var mode = tryRequire( resolve( __dirname, './../lib/native.js' ) );
+var opts = {
+	'skip': ( mode instanceof Error )
+};
+
+
+// TESTS //
+
+tape( 'main export is a function', opts, function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof mode, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'if provided `NaN` for any parameter, the function returns `NaN`', opts, function test( t ) {
+	var y = mode( NaN, 1.0 );
+	t.equal( isnan( y ), true, 'returns NaN' );
+	y = mode( 1.0, NaN );
+	t.equal( isnan( y ), true, 'returns NaN' );
+	t.end();
+});
+
+tape( 'if provided a nonpositive `s`, the function returns `NaN`', opts, function test( t ) {
+	var y;
+
+	y = mode( 2.0, 0.0 );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	y = mode( 2.0, -1.0 );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	y = mode( 2.0, -1.0 );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	y = mode( 1.0, NINF );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	y = mode( PINF, NINF );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	y = mode( NINF, NINF );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	y = mode( NaN, NINF );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	t.end();
+});
+
+tape( 'the function returns the mode of a raised cosine distribution', opts, function test( t ) {
+	var expected;
+	var delta;
+	var tol;
+	var mu;
+	var s;
+	var y;
+	var i;
+
+	expected = data.expected;
+	mu = data.mu;
+	s = data.s;
+	for ( i = 0; i < mu.length; i++ ) {
+		y = mode( mu[i], s[i] );
+		if ( expected[i] !== null ) {
+			if ( y === expected[i] ) {
+				t.equal( y, expected[i], 'mu:'+mu[i]+', s: '+s[i]+', y: '+y+', expected: '+expected[i] );
+			} else {
+				delta = abs( y - expected[ i ] );
+				tol = 1.0 * EPS * abs( expected[ i ] );
+				t.ok( delta <= tol, 'within tolerance. mu: '+mu[i]+'. s: '+s[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
+			}
+		}
+	}
+	t.end();
+});

From 301c7db0fa8f030d82fe4bf941f2e62b8ee91d25 Mon Sep 17 00:00:00 2001
From: JoyBoy <144602492+0PrashantYadav0@users.noreply.github.com>
Date: Fri, 3 Jan 2025 07:52:24 +0530
Subject: [PATCH 41/87] feat: add C implementation for
 `stats/base/dists/triangular/pdf`

PR-URL: https://github.com/stdlib-js/stdlib/pull/4322
Closes: https://github.com/stdlib-js/stdlib/issues/3820

Co-authored-by: Philipp Burckhardt <pburckhardt@outlook.com>
Co-authored-by: stdlib-bot <noreply@stdlib.io>
Reviewed-by: Philipp Burckhardt <pburckhardt@outlook.com>
Signed-off-by: Philipp Burckhardt <pburckhardt@outlook.com>
---
 .../stats/base/dists/triangular/pdf/README.md | 103 +++++++++
 .../triangular/pdf/benchmark/benchmark.js     |  21 +-
 .../pdf/benchmark/benchmark.native.js         |  78 +++++++
 .../dists/triangular/pdf/benchmark/c/Makefile | 146 ++++++++++++
 .../triangular/pdf/benchmark/c/benchmark.c    | 145 ++++++++++++
 .../base/dists/triangular/pdf/binding.gyp     | 170 ++++++++++++++
 .../dists/triangular/pdf/examples/c/Makefile  | 146 ++++++++++++
 .../dists/triangular/pdf/examples/c/example.c |  46 ++++
 .../base/dists/triangular/pdf/include.gypi    |  53 +++++
 .../stdlib/stats/base/dists/triangular/pdf.h  |  38 ++++
 .../base/dists/triangular/pdf/lib/native.js   |  81 +++++++
 .../base/dists/triangular/pdf/manifest.json   |  78 +++++++
 .../base/dists/triangular/pdf/package.json    |   3 +
 .../base/dists/triangular/pdf/src/Makefile    |  70 ++++++
 .../base/dists/triangular/pdf/src/addon.c     |  23 ++
 .../base/dists/triangular/pdf/src/main.c      |  60 +++++
 .../dists/triangular/pdf/test/test.native.js  | 215 ++++++++++++++++++
 .../dists/triangular/pdf/test/test.pdf.js     |  12 +-
 18 files changed, 1480 insertions(+), 8 deletions(-)
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/benchmark/benchmark.native.js
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/benchmark/c/Makefile
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/benchmark/c/benchmark.c
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/binding.gyp
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/examples/c/Makefile
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/examples/c/example.c
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/include.gypi
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/include/stdlib/stats/base/dists/triangular/pdf.h
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/lib/native.js
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/manifest.json
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/src/Makefile
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/src/addon.c
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/src/main.c
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/test/test.native.js

diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/README.md b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/README.md
index bb5659703e59..8b6f4c0f66be 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/README.md
+++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/README.md
@@ -148,6 +148,109 @@ for ( i = 0; i < 25; i++ ) {
 
 <!-- /.examples -->
 
+<!-- Section to include cited references. If references are included, add a horizontal rule *before* the section. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="references">
+
+<!-- C interface documentation. -->
+
+* * *
+
+<section class="c">
+
+## C APIs
+
+<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<!-- C usage documentation. -->
+
+<section class="usage">
+
+### Usage
+
+```c
+#include "stdlib/stats/base/dists/triangular/pdf.h"
+```
+
+#### stdlib_base_dists_triangular_pdf( x, a, b, c )
+
+Evaluates the [probability density function][pdf] (PDF) of a [triangular][triangular-distribution] distribution with parameters `a` (lower limit), `b` (upper limit) and `c` (mode).
+
+```c
+double y = stdlib_base_dists_triangular_pdf( 0.5, -1.0, 1.0, 0.0 );
+// returns 0.5
+```
+
+The function accepts the following arguments:
+
+-   **x**: `[in] double` input value.
+-   **a**: `[in] double` lower limit.
+-   **b**: `[in] double` upper limit.
+-   **c**: `[in] double` mode.
+
+```c
+double stdlib_base_dists_triangular_pdf( const double x, const double a, const double b, const double c );
+```
+
+</section>
+
+<!-- /.usage -->
+
+<!-- C API usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="notes">
+
+</section>
+
+<!-- /.notes -->
+
+<!-- C API usage examples. -->
+
+<section class="examples">
+
+### Examples
+
+```c
+#include "stdlib/stats/base/dists/triangular/pdf.h"
+#include "stdlib/constants/float64/eps.h"
+#include <stdlib.h>
+#include <stdio.h>
+#include <math.h>
+
+static double random_uniform( const double min, const double max ) {
+    double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
+    return min + ( v*(max-min) );
+}
+
+int main( void ) {
+    double a;
+    double b;
+    double c;
+    double x;
+    double y;
+    int i;
+
+    for ( i = 0; i < 25; i++ ) {
+        x = random_uniform( 0.0, 30.0 );
+        a = random_uniform( 0.0, 10.0 );
+        b = random_uniform( a, 40.0 ) + STDLIB_CONSTANT_FLOAT64_EPS;
+        c = a + random_uniform( 0.0, b - a );
+        y = stdlib_base_dists_triangular_pdf( x, a, b, c );
+        printf( "x: %lf, a: %lf, b: %lf, c: %lf, f(x;a,b,c): %lf\n", x, a, b, c, y );
+    }
+}
+```
+
+</section>
+
+<!-- /.references -->
+
 <!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
 
 <section class="related">
diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/benchmark/benchmark.js
index adee58ea936a..2009ea83885a 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/benchmark/benchmark.js
+++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/benchmark/benchmark.js
@@ -23,6 +23,7 @@
 var bench = require( '@stdlib/bench' );
 var randu = require( '@stdlib/random/base/randu' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var Float64Array = require( '@stdlib/array/float64' );
 var EPS = require( '@stdlib/constants/float64/eps' );
 var pkg = require( './../package.json' ).name;
 var pdf = require( './../lib' );
@@ -34,17 +35,27 @@ bench( pkg, function benchmark( b ) {
 	var mode;
 	var min;
 	var max;
+	var len;
 	var x;
 	var y;
 	var i;
 
+	len = 100;
+	x = new Float64Array( len );
+	min = new Float64Array( len );
+	max = new Float64Array( len );
+	mode = new Float64Array( len );
+
+	for ( i = 0; i < len; i++ ) {
+		x[ i ] = randu() * 30.0;
+		min[ i ] = randu() * 10.0;
+		max[ i ] = min[ i ] + ( randu() * 40.0 ) + EPS;
+		mode[ i ] = min[ i ] + ( ( max[ i ] - min[ i ] ) * randu() );
+	}
+
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		x = randu() * 30.0;
-		min = randu() * 10.0;
-		max = min + ( randu() * 40.0 ) + EPS;
-		mode = min + ( ( max - min ) * randu() );
-		y = pdf( x, min, max, mode );
+		y = pdf( x[ i%len ], min[ i%len ], max[ i%len ], mode[ i%len ] );
 		if ( isnan( y ) ) {
 			b.fail( 'should not return NaN' );
 		}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/benchmark/benchmark.native.js
new file mode 100644
index 000000000000..4020e9d53bf7
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/benchmark/benchmark.native.js
@@ -0,0 +1,78 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var resolve = require( 'path' ).resolve;
+var bench = require( '@stdlib/bench' );
+var Float64Array = require( '@stdlib/array/float64' );
+var randu = require( '@stdlib/random/base/randu' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var tryRequire = require( '@stdlib/utils/try-require' );
+var EPS = require( '@stdlib/constants/float64/eps' );
+var pkg = require( './../package.json' ).name;
+
+
+// VARIABLES //
+
+var pdf = tryRequire( resolve( __dirname, './../lib/native.js' ) );
+var opts = {
+	'skip': ( pdf instanceof Error )
+};
+
+
+// MAIN //
+
+bench( pkg+'::native', opts, function benchmark( b ) {
+	var mode;
+	var min;
+	var max;
+	var len;
+	var x;
+	var y;
+	var i;
+
+	len = 100;
+	x = new Float64Array( len );
+	min = new Float64Array( len );
+	max = new Float64Array( len );
+	mode = new Float64Array( len );
+
+	for ( i = 0; i < len; i++ ) {
+		x[ i ] = randu() * 30.0;
+		min[ i ] = randu() * 10.0;
+		max[ i ] = min[ i ] + ( randu() * 40.0 ) + EPS;
+		mode[ i ] = min[ i ] + ( ( max[ i ] - min[ i ] ) * randu() );
+	}
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		y = pdf( x[ i%len ], min[ i%len ], max[ i%len ], mode[ i%len ] );
+		if ( isnan( y ) ) {
+			b.fail( 'should not return NaN' );
+		}
+	}
+	b.toc();
+	if ( isnan( y ) ) {
+		b.fail( 'should not return NaN' );
+	}
+	b.pass( 'benchmark finished' );
+	b.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/benchmark/c/Makefile
new file mode 100644
index 000000000000..a4bd7b38fd74
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/benchmark/c/Makefile
@@ -0,0 +1,146 @@
+#/
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#/
+
+# VARIABLES #
+
+ifndef VERBOSE
+	QUIET := @
+else
+	QUIET :=
+endif
+
+# Determine the OS ([1][1], [2][2]).
+#
+# [1]: https://en.wikipedia.org/wiki/Uname#Examples
+# [2]: http://stackoverflow.com/a/27776822/2225624
+OS ?= $(shell uname)
+ifneq (, $(findstring MINGW,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring MSYS,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring CYGWIN,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring Windows_NT,$(OS)))
+	OS := WINNT
+endif
+endif
+endif
+endif
+
+# Define the program used for compiling C source files:
+ifdef C_COMPILER
+	CC := $(C_COMPILER)
+else
+	CC := gcc
+endif
+
+# Define the command-line options when compiling C files:
+CFLAGS ?= \
+	-std=c99 \
+	-O3 \
+	-Wall \
+	-pedantic
+
+# Determine whether to generate position independent code ([1][1], [2][2]).
+#
+# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options
+# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option
+ifeq ($(OS), WINNT)
+	fPIC ?=
+else
+	fPIC ?= -fPIC
+endif
+
+# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`):
+INCLUDE ?=
+
+# List of source files:
+SOURCE_FILES ?=
+
+# List of libraries (e.g., `-lopenblas -lpthread`):
+LIBRARIES ?=
+
+# List of library paths (e.g., `-L /foo/bar -L /beep/boop`):
+LIBPATH ?=
+
+# List of C targets:
+c_targets := benchmark.out
+
+
+# RULES #
+
+#/
+# Compiles source files.
+#
+# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`)
+# @param {string} [CFLAGS] - C compiler options
+# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`)
+# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`)
+# @param {string} [SOURCE_FILES] - list of source files
+# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`)
+# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`)
+#
+# @example
+# make
+#
+# @example
+# make all
+#/
+all: $(c_targets)
+
+.PHONY: all
+
+#/
+# Compiles C source files.
+#
+# @private
+# @param {string} CC - C compiler (e.g., `gcc`)
+# @param {string} CFLAGS - C compiler options
+# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`)
+# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`)
+# @param {string} SOURCE_FILES - list of source files
+# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`)
+# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`)
+#/
+$(c_targets): %.out: %.c
+	$(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES)
+
+#/
+# Runs compiled benchmarks.
+#
+# @example
+# make run
+#/
+run: $(c_targets)
+	$(QUIET) ./$<
+
+.PHONY: run
+
+#/
+# Removes generated files.
+#
+# @example
+# make clean
+#/
+clean:
+	$(QUIET) -rm -f *.o *.out
+
+.PHONY: clean
diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/benchmark/c/benchmark.c
new file mode 100644
index 000000000000..ae1718904aeb
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/benchmark/c/benchmark.c
@@ -0,0 +1,145 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/dists/triangular/pdf.h"
+#include "stdlib/constants/float64/eps.h"
+#include <stdlib.h>
+#include <stdio.h>
+#include <math.h>
+#include <time.h>
+#include <sys/time.h>
+
+#define NAME "triangular-pdf"
+#define ITERATIONS 1000000
+#define REPEATS 3
+
+/**
+* Prints the TAP version.
+*/
+static void print_version( void ) {
+	printf( "TAP version 13\n" );
+}
+
+/**
+* Prints the TAP summary.
+*
+* @param total    total number of tests
+* @param passing  total number of passing tests
+*/
+static void print_summary( int total, int passing ) {
+	printf( "#\n" );
+	printf( "1..%d\n", total ); // TAP plan
+	printf( "# total %d\n", total );
+	printf( "# pass  %d\n", passing );
+	printf( "#\n" );
+	printf( "# ok\n" );
+}
+
+/**
+* Prints benchmarks results.
+*
+* @param elapsed   elapsed time in seconds
+*/
+static void print_results( double elapsed ) {
+	double rate = (double)ITERATIONS / elapsed;
+	printf( "  ---\n" );
+	printf( "  iterations: %d\n", ITERATIONS );
+	printf( "  elapsed: %0.9f\n", elapsed );
+	printf( "  rate: %0.9f\n", rate );
+	printf( "  ...\n" );
+}
+
+/**
+* Returns a clock time.
+*
+* @return clock time
+*/
+static double tic( void ) {
+	struct timeval now;
+	gettimeofday( &now, NULL );
+	return (double)now.tv_sec + (double)now.tv_usec/1.0e6;
+}
+
+/**
+* Generates a random number on the interval [min,max).
+*
+* @param min    minimum value (inclusive)
+* @param max    maximum value (exclusive)
+* @return       random number
+*/
+static double random_uniform( const double min, const double max ) {
+	double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
+	return min + ( v*(max-min) );
+}
+
+/**
+* Runs a benchmark.
+*
+* @return elapsed time in seconds
+*/
+static double benchmark( void ) {
+	double elapsed;
+	double a[ 100 ];
+	double b[ 100 ];
+	double c[ 100 ];
+	double x[ 100 ];
+	double y;
+	double t;
+	int i;
+
+	for ( i = 0; i < 100; i++ ) {
+		x[ i ] = random_uniform( 0.0, 30.0 );
+		a[ i ] = random_uniform( 0.0, 10.0 );
+		b[ i ] = random_uniform( a[ i ], 40.0 ) + STDLIB_CONSTANT_FLOAT64_EPS;
+		c[ i ] = random_uniform( a[ i ], b[ i ] );
+	}
+
+	t = tic();
+	for ( i = 0; i < ITERATIONS; i++ ) {
+		y = stdlib_base_dists_triangular_pdf( x[ i % 100 ], a[ i % 100 ], b[ i % 100 ], c[ i % 100 ] );
+		if ( y != y ) {
+			printf( "should not return NaN\n" );
+			break;
+		}
+	}
+	elapsed = tic() - t;
+	if ( y != y ) {
+		printf( "should not return NaN\n" );
+	}
+	return elapsed;
+}
+
+/**
+* Main execution sequence.
+*/
+int main( void ) {
+	double elapsed;
+	int i;
+
+	// Use the current time to seed the random number generator:
+	srand( time( NULL ) );
+
+	print_version();
+	for ( i = 0; i < REPEATS; i++ ) {
+		printf( "# c::%s\n", NAME );
+		elapsed = benchmark();
+		print_results( elapsed );
+		printf( "ok %d benchmark finished\n", i+1 );
+	}
+	print_summary( REPEATS, REPEATS );
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/binding.gyp
new file mode 100644
index 000000000000..009bb9da333a
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/binding.gyp
@@ -0,0 +1,170 @@
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# A `.gyp` file for building a Node.js native add-on.
+#
+# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md
+# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md
+{
+  # List of files to include in this file:
+  'includes': [
+    './include.gypi',
+  ],
+
+  # Define variables to be used throughout the configuration for all targets:
+  'variables': {
+    # Target name should match the add-on export name:
+    'addon_target_name%': 'addon',
+
+    # Set variables based on the host OS:
+    'conditions': [
+      [
+        'OS=="win"',
+        {
+          # Define the object file suffix:
+          'obj': 'obj',
+        },
+        {
+          # Define the object file suffix:
+          'obj': 'o',
+        }
+      ], # end condition (OS=="win")
+    ], # end conditions
+  }, # end variables
+
+  # Define compile targets:
+  'targets': [
+
+    # Target to generate an add-on:
+    {
+      # The target name should match the add-on export name:
+      'target_name': '<(addon_target_name)',
+
+      # Define dependencies:
+      'dependencies': [],
+
+      # Define directories which contain relevant include headers:
+      'include_dirs': [
+        # Local include directory:
+        '<@(include_dirs)',
+      ],
+
+      # List of source files:
+      'sources': [
+        '<@(src_files)',
+      ],
+
+      # Settings which should be applied when a target's object files are used as linker input:
+      'link_settings': {
+        # Define libraries:
+        'libraries': [
+          '<@(libraries)',
+        ],
+
+        # Define library directories:
+        'library_dirs': [
+          '<@(library_dirs)',
+        ],
+      },
+
+      # C/C++ compiler flags:
+      'cflags': [
+        # Enable commonly used warning options:
+        '-Wall',
+
+        # Aggressive optimization:
+        '-O3',
+      ],
+
+      # C specific compiler flags:
+      'cflags_c': [
+        # Specify the C standard to which a program is expected to conform:
+        '-std=c99',
+      ],
+
+      # C++ specific compiler flags:
+      'cflags_cpp': [
+        # Specify the C++ standard to which a program is expected to conform:
+        '-std=c++11',
+      ],
+
+      # Linker flags:
+      'ldflags': [],
+
+      # Apply conditions based on the host OS:
+      'conditions': [
+        [
+          'OS=="mac"',
+          {
+            # Linker flags:
+            'ldflags': [
+              '-undefined dynamic_lookup',
+              '-Wl,-no-pie',
+              '-Wl,-search_paths_first',
+            ],
+          },
+        ], # end condition (OS=="mac")
+        [
+          'OS!="win"',
+          {
+            # C/C++ flags:
+            'cflags': [
+              # Generate platform-independent code:
+              '-fPIC',
+            ],
+          },
+        ], # end condition (OS!="win")
+      ], # end conditions
+    }, # end target <(addon_target_name)
+
+    # Target to copy a generated add-on to a standard location:
+    {
+      'target_name': 'copy_addon',
+
+      # Declare that the output of this target is not linked:
+      'type': 'none',
+
+      # Define dependencies:
+      'dependencies': [
+        # Require that the add-on be generated before building this target:
+        '<(addon_target_name)',
+      ],
+
+      # Define a list of actions:
+      'actions': [
+        {
+          'action_name': 'copy_addon',
+          'message': 'Copying addon...',
+
+          # Explicitly list the inputs in the command-line invocation below:
+          'inputs': [],
+
+          # Declare the expected outputs:
+          'outputs': [
+            '<(addon_output_dir)/<(addon_target_name).node',
+          ],
+
+          # Define the command-line invocation:
+          'action': [
+            'cp',
+            '<(PRODUCT_DIR)/<(addon_target_name).node',
+            '<(addon_output_dir)/<(addon_target_name).node',
+          ],
+        },
+      ], # end actions
+    }, # end target copy_addon
+  ], # end targets
+}
\ No newline at end of file
diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/examples/c/Makefile
new file mode 100644
index 000000000000..25ced822f96a
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/examples/c/Makefile
@@ -0,0 +1,146 @@
+#/
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#/
+
+# VARIABLES #
+
+ifndef VERBOSE
+	QUIET := @
+else
+	QUIET :=
+endif
+
+# Determine the OS ([1][1], [2][2]).
+#
+# [1]: https://en.wikipedia.org/wiki/Uname#Examples
+# [2]: http://stackoverflow.com/a/27776822/2225624
+OS ?= $(shell uname)
+ifneq (, $(findstring MINGW,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring MSYS,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring CYGWIN,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring Windows_NT,$(OS)))
+	OS := WINNT
+endif
+endif
+endif
+endif
+
+# Define the program used for compiling C source files:
+ifdef C_COMPILER
+	CC := $(C_COMPILER)
+else
+	CC := gcc
+endif
+
+# Define the command-line options when compiling C files:
+CFLAGS ?= \
+	-std=c99 \
+	-O3 \
+	-Wall \
+	-pedantic
+
+# Determine whether to generate position independent code ([1][1], [2][2]).
+#
+# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options
+# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option
+ifeq ($(OS), WINNT)
+	fPIC ?=
+else
+	fPIC ?= -fPIC
+endif
+
+# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`):
+INCLUDE ?=
+
+# List of source files:
+SOURCE_FILES ?=
+
+# List of libraries (e.g., `-lopenblas -lpthread`):
+LIBRARIES ?=
+
+# List of library paths (e.g., `-L /foo/bar -L /beep/boop`):
+LIBPATH ?=
+
+# List of C targets:
+c_targets := example.out
+
+
+# RULES #
+
+#/
+# Compiles source files.
+#
+# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`)
+# @param {string} [CFLAGS] - C compiler options
+# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`)
+# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`)
+# @param {string} [SOURCE_FILES] - list of source files
+# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`)
+# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`)
+#
+# @example
+# make
+#
+# @example
+# make all
+#/
+all: $(c_targets)
+
+.PHONY: all
+
+#/
+# Compiles C source files.
+#
+# @private
+# @param {string} CC - C compiler (e.g., `gcc`)
+# @param {string} CFLAGS - C compiler options
+# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`)
+# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`)
+# @param {string} SOURCE_FILES - list of source files
+# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`)
+# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`)
+#/
+$(c_targets): %.out: %.c
+	$(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES)
+
+#/
+# Runs compiled examples.
+#
+# @example
+# make run
+#/
+run: $(c_targets)
+	$(QUIET) ./$<
+
+.PHONY: run
+
+#/
+# Removes generated files.
+#
+# @example
+# make clean
+#/
+clean:
+	$(QUIET) -rm -f *.o *.out
+
+.PHONY: clean
diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/examples/c/example.c
new file mode 100644
index 000000000000..5eb9ac1d215f
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/examples/c/example.c
@@ -0,0 +1,46 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/dists/triangular/pdf.h"
+#include "stdlib/constants/float64/eps.h"
+#include <stdlib.h>
+#include <stdio.h>
+#include <math.h>
+
+static double random_uniform( const double min, const double max ) {
+	double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
+	return min + ( v*(max-min) );
+}
+
+int main( void ) {
+	double a;
+	double b;
+	double c;
+	double x;
+	double y;
+	int i;
+
+	for ( i = 0; i < 25; i++ ) {
+		x = random_uniform( 0.0, 30.0 );
+		a = random_uniform( 0.0, 10.0 );
+		b = random_uniform( a, 40.0 ) + STDLIB_CONSTANT_FLOAT64_EPS;
+		c = a + random_uniform( 0.0, b - a );
+		y = stdlib_base_dists_triangular_pdf( x, a, b, c );
+		printf( "x: %lf, a: %lf, b: %lf, c: %lf, f(x;a,b,c): %lf\n", x, a, b, c, y );
+	}
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/include.gypi
new file mode 100644
index 000000000000..f6557ac1ab57
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/include.gypi
@@ -0,0 +1,53 @@
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# A GYP include file for building a Node.js native add-on.
+#
+# Main documentation:
+#
+# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md
+# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md
+{
+  # Define variables to be used throughout the configuration for all targets:
+  'variables': {
+    # Source directory:
+    'src_dir': './src',
+
+    # Include directories:
+    'include_dirs': [
+      '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).include; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
+    ],
+
+    # Add-on destination directory:
+    'addon_output_dir': './src',
+
+    # Source files:
+    'src_files': [
+      '<(src_dir)/addon.c',
+      '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).src; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
+    ],
+
+    # Library dependencies:
+    'libraries': [
+      '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).libraries; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
+    ],
+
+    # Library directories:
+    'library_dirs': [
+      '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).libpath; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
+    ],
+  }, # end variables
+}
\ No newline at end of file
diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/include/stdlib/stats/base/dists/triangular/pdf.h b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/include/stdlib/stats/base/dists/triangular/pdf.h
new file mode 100644
index 000000000000..e23ab5a2c366
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/include/stdlib/stats/base/dists/triangular/pdf.h
@@ -0,0 +1,38 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#ifndef STDLIB_STATS_BASE_DISTS_TRIANGULAR_PDF_H
+#define STDLIB_STATS_BASE_DISTS_TRIANGULAR_PDF_H
+
+/*
+* If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler.
+*/
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+/**
+* Evaluates the probability density function (PDF) for a triangular distribution with lower limit `a` and upper limit `b` and mode `c` at a value `x`.
+*/
+double stdlib_base_dists_triangular_pdf( const double x, const double a, const double b, const double c );
+
+#ifdef __cplusplus
+}
+#endif
+
+#endif // !STDLIB_STATS_BASE_DISTS_TRIANGULAR_PDF_H
diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/lib/native.js b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/lib/native.js
new file mode 100644
index 000000000000..e38c2a42d56b
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/lib/native.js
@@ -0,0 +1,81 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var addon = require( './../src/addon.node' );
+
+
+// MAIN //
+
+/**
+* Evaluates the probability density function (PDF) for a triangular distribution with lower limit `a` and upper limit `b` and mode `c` at a value `x`.
+*
+* @private
+* @param {number} x - input value
+* @param {number} a - lower limit
+* @param {number} b - upper limit
+* @param {number} c - mode
+* @returns {number} evaluated PDF
+*
+* @example
+* var y = pdf( 0.5, -1.0, 1.0, 0.0 );
+* // returns 0.5
+*
+* @example
+* var y = pdf( 0.5, -1.0, 1.0, 0.5 );
+* // returns 1.0
+*
+* @example
+* var y = pdf( -10.0, -20.0, 0.0, -2.0 );
+* // returns ~0.056
+*
+* @example
+* var y = pdf( -2.0, -1.0, 1.0, 0.0 );
+* // returns 0.0
+*
+* @example
+* var y = pdf( NaN, 0.0, 1.0, 0.5 );
+* // returns NaN
+*
+* @example
+* var y = pdf( 0.0, NaN, 1.0, 0.5 );
+* // returns NaN
+*
+* @example
+* var y = pdf( 0.0, 0.0, NaN, 0.5 );
+* // returns NaN
+*
+* @example
+* var y = pdf( 2.0, 1.0, 0.0, NaN );
+* // returns NaN
+*
+* @example
+* var y = pdf( 2.0, 1.0, 0.0, 1.5 );
+* // returns NaN
+*/
+function pdf( x, a, b, c ) {
+	return addon( x, a, b, c );
+}
+
+
+// EXPORTS //
+
+module.exports = pdf;
diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/manifest.json b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/manifest.json
new file mode 100644
index 000000000000..492769997bfc
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/manifest.json
@@ -0,0 +1,78 @@
+{
+    "options": {
+      "task": "build",
+      "wasm": false
+    },
+    "fields": [
+      {
+        "field": "src",
+        "resolve": true,
+        "relative": true
+      },
+      {
+        "field": "include",
+        "resolve": true,
+        "relative": true
+      },
+      {
+        "field": "libraries",
+        "resolve": false,
+        "relative": false
+      },
+      {
+        "field": "libpath",
+        "resolve": true,
+        "relative": false
+      }
+    ],
+    "confs": [
+      {
+        "task": "build",
+        "wasm": false,
+        "src": [
+          "./src/main.c"
+        ],
+        "include": [
+          "./include"
+        ],
+        "libraries": [],
+        "libpath": [],
+        "dependencies": [
+          "@stdlib/math/base/napi/quaternary",
+          "@stdlib/math/base/assert/is-nan"
+        ]
+      },
+      {
+        "task": "benchmark",
+        "wasm": false,
+        "src": [
+          "./src/main.c"
+        ],
+        "include": [
+          "./include"
+        ],
+        "libraries": [],
+        "libpath": [],
+        "dependencies": [
+          "@stdlib/math/base/assert/is-nan",
+          "@stdlib/constants/float64/eps"
+        ]
+      },
+      {
+        "task": "examples",
+        "wasm": false,
+        "src": [
+          "./src/main.c"
+        ],
+        "include": [
+          "./include"
+        ],
+        "libraries": [],
+        "libpath": [],
+        "dependencies": [
+          "@stdlib/math/base/assert/is-nan",
+          "@stdlib/constants/float64/eps"
+        ]
+      }
+    ]
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/package.json b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/package.json
index 01d446eadd9b..1c9d32bea456 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/package.json
+++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/package.json
@@ -14,11 +14,14 @@
     }
   ],
   "main": "./lib",
+  "gypfile": true,
   "directories": {
     "benchmark": "./benchmark",
     "doc": "./docs",
     "example": "./examples",
+    "include": "./include",
     "lib": "./lib",
+    "src": "./src",
     "test": "./test"
   },
   "types": "./docs/types",
diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/src/Makefile b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/src/Makefile
new file mode 100644
index 000000000000..7733b6180cb4
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/src/Makefile
@@ -0,0 +1,70 @@
+#/
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#/
+
+# VARIABLES #
+
+ifndef VERBOSE
+	QUIET := @
+else
+	QUIET :=
+endif
+
+# Determine the OS ([1][1], [2][2]).
+#
+# [1]: https://en.wikipedia.org/wiki/Uname#Examples
+# [2]: http://stackoverflow.com/a/27776822/2225624
+OS ?= $(shell uname)
+ifneq (, $(findstring MINGW,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring MSYS,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring CYGWIN,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring Windows_NT,$(OS)))
+	OS := WINNT
+endif
+endif
+endif
+endif
+
+
+# RULES #
+
+#/
+# Removes generated files for building an add-on.
+#
+# @example
+# make clean-addon
+#/
+clean-addon:
+	$(QUIET) -rm -f *.o *.node
+
+.PHONY: clean-addon
+
+#/
+# Removes generated files.
+#
+# @example
+# make clean
+#/
+clean: clean-addon
+
+.PHONY: clean
diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/src/addon.c b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/src/addon.c
new file mode 100644
index 000000000000..f22df9aae7fb
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/src/addon.c
@@ -0,0 +1,23 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/dists/triangular/pdf.h"
+#include "stdlib/math/base/napi/quaternary.h"
+
+// cppcheck-suppress shadowFunction
+STDLIB_MATH_BASE_NAPI_MODULE_DDDD_D( stdlib_base_dists_triangular_pdf )
diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/src/main.c
new file mode 100644
index 000000000000..d21af392acf8
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/src/main.c
@@ -0,0 +1,60 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/dists/triangular/pdf.h"
+#include "stdlib/math/base/assert/is_nan.h"
+#include <math.h>
+
+/**
+* Evaluates the probability density function (PDF) for a triangular distribution with lower limit `a` and upper limit `b` and mode `c` at a value `x`.
+*
+* @param x   input value
+* @param a   lower limit
+* @param b   upper limit
+* @param c   mode
+* @return    evaluated PDF
+*
+* @example
+* double y = stdlib_base_dists_triangular_pdf( 0.5, -1.0, 1.0, 0.0 );
+* // returns 0.5
+*/
+double stdlib_base_dists_triangular_pdf( const double x, const double a, const double b, const double c ) {
+	if (
+		stdlib_base_is_nan( x ) ||
+		stdlib_base_is_nan( a ) ||
+		stdlib_base_is_nan( b ) ||
+		stdlib_base_is_nan( c ) ||
+		a > c ||
+		c > b
+	) {
+		return 0.0/0.0; // NaN
+	}
+	if ( x < a ) {
+		return 0.0;
+	}
+	if ( x < c ) {
+		return ( 2.0 * (x - a) ) / ( (b - a) * (c - a) );
+	}
+	if ( x == c ) {
+		return ( 2.0 / ( b - a ) );
+	}
+	if( x <= b ){
+		return ( 2.0 * (b - x) ) / ( (b - a) * (b - c) );
+	}
+	return 0.0;
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/test/test.native.js
new file mode 100644
index 000000000000..4dffae744320
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/test/test.native.js
@@ -0,0 +1,215 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var resolve = require( 'path' ).resolve;
+var tape = require( 'tape' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var abs = require( '@stdlib/math/base/special/abs' );
+var PINF = require( '@stdlib/constants/float64/pinf' );
+var NINF = require( '@stdlib/constants/float64/ninf' );
+var EPS = require( '@stdlib/constants/float64/eps' );
+var tryRequire = require( '@stdlib/utils/try-require' );
+
+
+// FIXTURES //
+
+var smallRange = require( './fixtures/julia/small_range.json' );
+var mediumRange = require( './fixtures/julia/medium_range.json' );
+var largeRange = require( './fixtures/julia/large_range.json' );
+
+
+// VARIABLES //
+
+var pdf = tryRequire( resolve( __dirname, './../lib/native.js' ) );
+var opts = {
+	'skip': ( pdf instanceof Error )
+};
+
+
+// TESTS //
+
+tape( 'main export is a function', opts, function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof pdf, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'if provided `NaN` for any parameter, the function returns `NaN`', opts, function test( t ) {
+	var y = pdf( NaN, 0.0, 1.0, 0.5 );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	y = pdf( 0.0, NaN, 1.0, 0.5 );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	y = pdf( 0.0, 1.0, NaN, 0.5 );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	y = pdf( 0.0, 0.0, 1.0, NaN );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	t.end();
+});
+
+tape( 'if provided a number greater than `b` for `x` and valid parameters, the function returns `0`', opts, function test( t ) {
+	var y = pdf( PINF, 0.0, 1.0, 0.5 );
+	t.equal( y, 0.0, 'returns 0' );
+
+	y = pdf( 20.0, 0.0, 1.0, 0.5 );
+	t.equal( y, 0.0, 'returns 0' );
+
+	y = pdf( 2.0, 0.0, 1.0, 0.5 );
+	t.equal( y, 0.0, 'returns 0' );
+
+	y = pdf( 1.1, 0.0, 1.0, 0.5 );
+	t.equal( y, 0.0, 'returns 0' );
+
+	t.end();
+});
+
+tape( 'if provided a number smaller than `a` for `x` and valid parameters, the function returns `0`', opts, function test( t ) {
+	var y = pdf( NINF, 0.0, 1.0, 0.5 );
+	t.equal( y, 0.0, 'returns 0' );
+
+	y = pdf( -20.0, 0.0, 1.0, 0.5 );
+	t.equal( y, 0.0, 'returns 0' );
+
+	y = pdf( -2.0, 0.0, 1.0, 0.5 );
+	t.equal( y, 0.0, 'returns 0' );
+
+	y = pdf( -0.5, 0.0, 1.0, 0.5 );
+	t.equal( y, 0.0, 'returns 0' );
+
+	t.end();
+});
+
+tape( 'if provided parameters not satisfying `a <= c <= b`, the function returns `NaN`', opts, function test( t ) {
+	var y;
+
+	y = pdf( 2.0, 3.0, 2.0, 2.5 );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	y = pdf( 0.0, 2.0, 3.0, 4.0 );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	y = pdf( 2.0, 2.0, 3.0, 1.0 );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	y = pdf( 2.0, PINF, NINF, 0.0 );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	t.end();
+});
+
+tape( 'the function returns `2/(b-a)` if provided `x = c`', opts, function test( t ) {
+	var a = 0.0;
+	var b = 2.0;
+	var c = 1.5;
+	t.equal( pdf( c, a, b, c ), 2/(b-a), 'returns 2/(b-a)' );
+	t.end();
+});
+
+tape( 'the function evaluates the pdf for `x` given a small range `b - a`', opts, function test( t ) {
+	var expected;
+	var delta;
+	var tol;
+	var x;
+	var a;
+	var b;
+	var c;
+	var y;
+	var i;
+
+	expected = smallRange.expected;
+	x = smallRange.x;
+	a = smallRange.a;
+	b = smallRange.b;
+	c = smallRange.c;
+	for ( i = 0; i < x.length; i++ ) {
+		y = pdf( x[i], a[i], b[i], c[i] );
+		if ( y === expected[i] ) {
+			t.equal( y, expected[i], 'x: '+x[i]+', a: '+a[i]+', b: '+b[i]+', c: '+c[i]+', y: '+y+', expected: '+expected[i] );
+		} else {
+			delta = abs( y - expected[ i ] );
+			tol = 1.0 * EPS * abs( expected[ i ] );
+			t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. a: '+a[i]+'. b: '+b[i]+'. c: '+c[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
+		}
+	}
+	t.end();
+});
+
+tape( 'the function evaluates the pdf for `x` given a medium range `b - a`', opts, function test( t ) {
+	var expected;
+	var delta;
+	var tol;
+	var x;
+	var a;
+	var b;
+	var c;
+	var y;
+	var i;
+
+	expected = mediumRange.expected;
+	x = mediumRange.x;
+	a = mediumRange.a;
+	b = mediumRange.b;
+	c = mediumRange.c;
+	for ( i = 0; i < x.length; i++ ) {
+		y = pdf( x[i], a[i], b[i], c[i] );
+		if ( y === expected[i] ) {
+			t.equal( y, expected[i], 'x: '+x[i]+', a: '+a[i]+', b: '+b[i]+', c: '+c[i]+', y: '+y+', expected: '+expected[i] );
+		} else {
+			delta = abs( y - expected[ i ] );
+			tol = 1.0 * EPS * abs( expected[ i ] );
+			t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. a: '+a[i]+'. b: '+b[i]+'. c: '+c[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
+		}
+	}
+	t.end();
+});
+
+tape( 'the function evaluates the pdf for `x` given a large range `b - a`', opts, function test( t ) {
+	var expected;
+	var delta;
+	var tol;
+	var x;
+	var a;
+	var b;
+	var c;
+	var y;
+	var i;
+
+	expected = largeRange.expected;
+	x = largeRange.x;
+	a = largeRange.a;
+	b = largeRange.b;
+	c = largeRange.c;
+	for ( i = 0; i < x.length; i++ ) {
+		y = pdf( x[i], a[i], b[i], c[i] );
+		if ( y === expected[i] ) {
+			t.equal( y, expected[i], 'x: '+x[i]+', a: '+a[i]+', b: '+b[i]+', c: '+c[i]+', y: '+y+', expected: '+expected[i] );
+		} else {
+			delta = abs( y - expected[ i ] );
+			tol = 1.0 * EPS * abs( expected[ i ] );
+			t.ok( delta <= tol, 'within tolerance. x: '+x[ i ]+'. a: '+a[i]+'. b: '+b[i]+'. c: '+c[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
+		}
+	}
+	t.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/test/test.pdf.js b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/test/test.pdf.js
index 80aaeaff3dcd..9831df998685 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/test/test.pdf.js
+++ b/lib/node_modules/@stdlib/stats/base/dists/triangular/pdf/test/test.pdf.js
@@ -45,12 +45,18 @@ tape( 'main export is a function', function test( t ) {
 });
 
 tape( 'if provided `NaN` for any parameter, the function returns `NaN`', function test( t ) {
-	var y = pdf( NaN, 0.0, 1.0 );
+	var y = pdf( NaN, 0.0, 1.0, 0.5 );
 	t.equal( isnan( y ), true, 'returns NaN' );
-	y = pdf( 0.0, NaN, 1.0 );
+
+	y = pdf( 0.0, NaN, 1.0, 0.5 );
 	t.equal( isnan( y ), true, 'returns NaN' );
-	y = pdf( 0.0, 1.0, NaN );
+
+	y = pdf( 0.0, 1.0, NaN, 0.5 );
 	t.equal( isnan( y ), true, 'returns NaN' );
+
+	y = pdf( 0.0, 0.0, 1.0, NaN );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
 	t.end();
 });
 

From 0699aa748576a80450eae238d82e1c85902e5e64 Mon Sep 17 00:00:00 2001
From: JoyBoy <144602492+0PrashantYadav0@users.noreply.github.com>
Date: Fri, 3 Jan 2025 08:12:59 +0530
Subject: [PATCH 42/87] feat: add C implementation for
 `stats/base/dists/geometric/entropy`

PR-URL: https://github.com/stdlib-js/stdlib/pull/4180
Closes: https://github.com/stdlib-js/stdlib/issues/3631

Co-authored-by: Philipp Burckhardt <pburckhardt@outlook.com>
Co-authored-by: stdlib-bot <noreply@stdlib.io>
Reviewed-by: Philipp Burckhardt <pburckhardt@outlook.com>
Signed-off-by: Philipp Burckhardt <pburckhardt@outlook.com>
---
 .../base/dists/geometric/entropy/README.md    |  88 +++++++++
 .../geometric/entropy/benchmark/benchmark.js  |  12 +-
 .../entropy/benchmark/benchmark.native.js     |  67 +++++++
 .../geometric/entropy/benchmark/c/Makefile    | 146 +++++++++++++++
 .../geometric/entropy/benchmark/c/benchmark.c | 138 ++++++++++++++
 .../base/dists/geometric/entropy/binding.gyp  | 170 ++++++++++++++++++
 .../geometric/entropy/examples/c/Makefile     | 146 +++++++++++++++
 .../geometric/entropy/examples/c/example.c    |  38 ++++
 .../base/dists/geometric/entropy/include.gypi |  53 ++++++
 .../stats/base/dists/geometric/entropy.h      |  38 ++++
 .../dists/geometric/entropy/lib/native.js     |  62 +++++++
 .../dists/geometric/entropy/manifest.json     |  79 ++++++++
 .../base/dists/geometric/entropy/package.json |   3 +
 .../base/dists/geometric/entropy/src/Makefile |  70 ++++++++
 .../base/dists/geometric/entropy/src/addon.c  |  23 +++
 .../base/dists/geometric/entropy/src/main.c   |  44 +++++
 .../geometric/entropy/test/test.native.js     |  99 ++++++++++
 17 files changed, 1273 insertions(+), 3 deletions(-)
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/benchmark/benchmark.native.js
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/benchmark/c/Makefile
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/benchmark/c/benchmark.c
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/binding.gyp
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/examples/c/Makefile
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/examples/c/example.c
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/include.gypi
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/include/stdlib/stats/base/dists/geometric/entropy.h
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/lib/native.js
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/manifest.json
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/src/Makefile
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/src/addon.c
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/src/main.c
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/test/test.native.js

diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/README.md b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/README.md
index a617a8b9fe14..9c80855663cd 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/README.md
+++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/README.md
@@ -122,6 +122,94 @@ for ( i = 0; i < 10; i++ ) {
 
 <!-- /.examples -->
 
+<!-- C interface documentation. -->
+
+* * *
+
+<section class="c">
+
+## C APIs
+
+<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<!-- C usage documentation. -->
+
+<section class="usage">
+
+### Usage
+
+```c
+#include "stdlib/stats/base/dists/geometric/entropy.h"
+```
+
+#### stdlib_base_dists_geometric_entropy( p )
+
+Returns the entropy of a geometric distribution.
+
+```c
+double out = stdlib_base_dists_geometric_entropy( 0.5 );
+// returns ~1.386
+```
+
+The function accepts the following arguments:
+
+-   **p**: `[in] double` success probability.
+
+```c
+double stdlib_base_dists_geometric_entropy( const double p );
+```
+
+</section>
+
+<!-- /.usage -->
+
+<!-- C API usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="notes">
+
+</section>
+
+<!-- /.notes -->
+
+<!-- C API usage examples. -->
+
+<section class="examples">
+
+### Examples
+
+```c
+#include "stdlib/stats/base/dists/geometric/entropy.h"
+#include <stdlib.h>
+#include <stdio.h>
+
+static double random_uniform( const double min, const double max ) {
+    double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
+    return min + ( v*(max-min) );
+}
+
+int main( void ) {
+    double p;
+    double y;
+    int i;
+
+    for ( i = 0; i < 25; i++ ) {
+        p = random_uniform( 0.0, 1.0 );
+        y = stdlib_base_dists_geometric_entropy( p );
+        printf( "p: %lf, H(X;p): %lf\n", p, y );
+    }
+}
+```
+
+</section>
+
+<!-- /.examples -->
+
 <!-- Section to include cited references. If references are included, add a horizontal rule *before* the section. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
 
 <section class="references">
diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/benchmark/benchmark.js
index 72181a16582a..2b3dc56001c4 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/benchmark/benchmark.js
+++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/benchmark/benchmark.js
@@ -21,9 +21,9 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
+var Float64Array = require( '@stdlib/array/float64' );
 var randu = require( '@stdlib/random/base/randu' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
-var EPS = require( '@stdlib/constants/float64/eps' );
 var pkg = require( './../package.json' ).name;
 var entropy = require( './../lib' );
 
@@ -31,14 +31,20 @@ var entropy = require( './../lib' );
 // MAIN //
 
 bench( pkg, function benchmark( b ) {
+	var len;
 	var p;
 	var y;
 	var i;
 
+	len = 100;
+	p = new Float64Array( len );
+	for ( i = 0; i < len; i++ ) {
+		p[ i ] = ( randu() * 1.0 );
+	}
+
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		p = ( randu()*1.0 ) + EPS;
-		y = entropy( p );
+		y = entropy( p[ i % len ] );
 		if ( isnan( y ) ) {
 			b.fail( 'should not return NaN' );
 		}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/benchmark/benchmark.native.js
new file mode 100644
index 000000000000..69b57c0dc5a8
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/benchmark/benchmark.native.js
@@ -0,0 +1,67 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var resolve = require( 'path' ).resolve;
+var bench = require( '@stdlib/bench' );
+var Float64Array = require( '@stdlib/array/float64' );
+var tryRequire = require( '@stdlib/utils/try-require' );
+var randu = require( '@stdlib/random/base/randu' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pkg = require( './../package.json' ).name;
+
+
+// VARIABLES //
+
+var entropy = tryRequire( resolve( __dirname, './../lib/native.js' ) );
+var opts = {
+	'skip': ( entropy instanceof Error )
+};
+
+
+// MAIN //
+
+bench( pkg+'::native', opts, function benchmark( b ) {
+	var len;
+	var p;
+	var y;
+	var i;
+
+	len = 100;
+	p = new Float64Array( len );
+	for ( i = 0; i < len; i++ ) {
+		p[ i ] = ( randu() * 1.0 );
+	}
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		y = entropy( p[ i % 100 ] );
+		if ( isnan( y ) ) {
+			b.fail( 'should not return NaN' );
+		}
+	}
+	b.toc();
+	if ( isnan( y ) ) {
+		b.fail( 'should not return NaN' );
+	}
+	b.pass( 'benchmark finished' );
+	b.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/benchmark/c/Makefile
new file mode 100644
index 000000000000..a4bd7b38fd74
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/benchmark/c/Makefile
@@ -0,0 +1,146 @@
+#/
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#/
+
+# VARIABLES #
+
+ifndef VERBOSE
+	QUIET := @
+else
+	QUIET :=
+endif
+
+# Determine the OS ([1][1], [2][2]).
+#
+# [1]: https://en.wikipedia.org/wiki/Uname#Examples
+# [2]: http://stackoverflow.com/a/27776822/2225624
+OS ?= $(shell uname)
+ifneq (, $(findstring MINGW,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring MSYS,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring CYGWIN,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring Windows_NT,$(OS)))
+	OS := WINNT
+endif
+endif
+endif
+endif
+
+# Define the program used for compiling C source files:
+ifdef C_COMPILER
+	CC := $(C_COMPILER)
+else
+	CC := gcc
+endif
+
+# Define the command-line options when compiling C files:
+CFLAGS ?= \
+	-std=c99 \
+	-O3 \
+	-Wall \
+	-pedantic
+
+# Determine whether to generate position independent code ([1][1], [2][2]).
+#
+# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options
+# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option
+ifeq ($(OS), WINNT)
+	fPIC ?=
+else
+	fPIC ?= -fPIC
+endif
+
+# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`):
+INCLUDE ?=
+
+# List of source files:
+SOURCE_FILES ?=
+
+# List of libraries (e.g., `-lopenblas -lpthread`):
+LIBRARIES ?=
+
+# List of library paths (e.g., `-L /foo/bar -L /beep/boop`):
+LIBPATH ?=
+
+# List of C targets:
+c_targets := benchmark.out
+
+
+# RULES #
+
+#/
+# Compiles source files.
+#
+# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`)
+# @param {string} [CFLAGS] - C compiler options
+# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`)
+# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`)
+# @param {string} [SOURCE_FILES] - list of source files
+# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`)
+# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`)
+#
+# @example
+# make
+#
+# @example
+# make all
+#/
+all: $(c_targets)
+
+.PHONY: all
+
+#/
+# Compiles C source files.
+#
+# @private
+# @param {string} CC - C compiler (e.g., `gcc`)
+# @param {string} CFLAGS - C compiler options
+# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`)
+# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`)
+# @param {string} SOURCE_FILES - list of source files
+# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`)
+# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`)
+#/
+$(c_targets): %.out: %.c
+	$(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES)
+
+#/
+# Runs compiled benchmarks.
+#
+# @example
+# make run
+#/
+run: $(c_targets)
+	$(QUIET) ./$<
+
+.PHONY: run
+
+#/
+# Removes generated files.
+#
+# @example
+# make clean
+#/
+clean:
+	$(QUIET) -rm -f *.o *.out
+
+.PHONY: clean
diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/benchmark/c/benchmark.c
new file mode 100644
index 000000000000..65fca8fabbbb
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/benchmark/c/benchmark.c
@@ -0,0 +1,138 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/dists/geometric/entropy.h"
+#include <stdlib.h>
+#include <stdio.h>
+#include <math.h>
+#include <time.h>
+#include <sys/time.h>
+
+#define NAME "geometric-entropy"
+#define ITERATIONS 1000000
+#define REPEATS 3
+
+/**
+* Prints the TAP version.
+*/
+static void print_version( void ) {
+	printf( "TAP version 13\n" );
+}
+
+/**
+* Prints the TAP summary.
+*
+* @param total     total number of tests
+* @param passing   total number of passing tests
+*/
+static void print_summary( int total, int passing ) {
+	printf( "#\n" );
+	printf( "1..%d\n", total ); // TAP plan
+	printf( "# total %d\n", total );
+	printf( "# pass  %d\n", passing );
+	printf( "#\n" );
+	printf( "# ok\n" );
+}
+
+/**
+* Prints benchmarks results.
+*
+* @param elapsed   elapsed time in seconds
+*/
+static void print_results( double elapsed ) {
+	double rate = (double)ITERATIONS / elapsed;
+	printf( "  ---\n" );
+	printf( "  iterations: %d\n", ITERATIONS );
+	printf( "  elapsed: %0.9f\n", elapsed );
+	printf( "  rate: %0.9f\n", rate );
+	printf( "  ...\n" );
+}
+
+/**
+* Returns a clock time.
+*
+* @return clock time
+*/
+static double tic( void ) {
+	struct timeval now;
+	gettimeofday( &now, NULL );
+	return (double)now.tv_sec + (double)now.tv_usec/1.0e6;
+}
+
+/**
+* Generates a random number on the interval [min,max).
+*
+* @param min    minimum value (inclusive)
+* @param max    maximum value (exclusive)
+* @return       random number
+*/
+static double random_uniform( const double min, const double max ) {
+	double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
+	return min + ( v*(max-min) );
+}
+
+/**
+* Runs a benchmark.
+*
+* @return elapsed time in seconds
+*/
+static double benchmark( void ) {
+	double elapsed;
+	double p[ 100 ];
+	double y;
+	double t;
+	int i;
+
+	for ( i = 0; i < 100; i++ ) {
+		p[ i ] = random_uniform( 0.0, 1.0 );
+	}
+
+	t = tic();
+	for ( i = 0; i < ITERATIONS; i++ ) {
+		y = stdlib_base_dists_geometric_entropy( p[ i % 100 ] );
+		if ( y != y ) {
+			printf( "should not return NaN\n" );
+			break;
+		}
+	}
+	elapsed = tic() - t;
+	if ( y != y ) {
+		printf( "should not return NaN\n" );
+	}
+	return elapsed;
+}
+
+/**
+* Main execution sequence.
+*/
+int main( void ) {
+	double elapsed;
+	int i;
+
+	// Use the current time to seed the random number generator:
+	srand( time( NULL ) );
+
+	print_version();
+	for ( i = 0; i < REPEATS; i++ ) {
+		printf( "# c::%s\n", NAME );
+		elapsed = benchmark();
+		print_results( elapsed );
+		printf( "ok %d benchmark finished\n", i+1 );
+	}
+	print_summary( REPEATS, REPEATS );
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/binding.gyp
new file mode 100644
index 000000000000..68a1ca11d160
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/binding.gyp
@@ -0,0 +1,170 @@
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# A `.gyp` file for building a Node.js native add-on.
+#
+# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md
+# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md
+{
+  # List of files to include in this file:
+  'includes': [
+    './include.gypi',
+  ],
+
+  # Define variables to be used throughout the configuration for all targets:
+  'variables': {
+    # Target name should match the add-on export name:
+    'addon_target_name%': 'addon',
+
+    # Set variables based on the host OS:
+    'conditions': [
+      [
+        'OS=="win"',
+        {
+          # Define the object file suffix:
+          'obj': 'obj',
+        },
+        {
+          # Define the object file suffix:
+          'obj': 'o',
+        }
+      ], # end condition (OS=="win")
+    ], # end conditions
+  }, # end variables
+
+  # Define compile targets:
+  'targets': [
+
+    # Target to generate an add-on:
+    {
+      # The target name should match the add-on export name:
+      'target_name': '<(addon_target_name)',
+
+      # Define dependencies:
+      'dependencies': [],
+
+      # Define directories which contain relevant include headers:
+      'include_dirs': [
+        # Local include directory:
+        '<@(include_dirs)',
+      ],
+
+      # List of source files:
+      'sources': [
+        '<@(src_files)',
+      ],
+
+      # Settings which should be applied when a target's object files are used as linker input:
+      'link_settings': {
+        # Define libraries:
+        'libraries': [
+          '<@(libraries)',
+        ],
+
+        # Define library directories:
+        'library_dirs': [
+          '<@(library_dirs)',
+        ],
+      },
+
+      # C/C++ compiler flags:
+      'cflags': [
+        # Enable commonly used warning options:
+        '-Wall',
+
+        # Aggressive optimization:
+        '-O3',
+      ],
+
+      # C specific compiler flags:
+      'cflags_c': [
+        # Specify the C standard to which a program is expected to conform:
+        '-std=c99',
+      ],
+
+      # C++ specific compiler flags:
+      'cflags_cpp': [
+        # Specify the C++ standard to which a program is expected to conform:
+        '-std=c++11',
+      ],
+
+      # Linker flags:
+      'ldflags': [],
+
+      # Apply conditions based on the host OS:
+      'conditions': [
+        [
+          'OS=="mac"',
+          {
+            # Linker flags:
+            'ldflags': [
+              '-undefined dynamic_lookup',
+              '-Wl,-no-pie',
+              '-Wl,-search_paths_first',
+            ],
+          },
+        ], # end condition (OS=="mac")
+        [
+          'OS!="win"',
+          {
+            # C/C++ flags:
+            'cflags': [
+              # Generate platform-independent code:
+              '-fPIC',
+            ],
+          },
+        ], # end condition (OS!="win")
+      ], # end conditions
+    }, # end target <(addon_target_name)
+
+    # Target to copy a generated add-on to a standard location:
+    {
+      'target_name': 'copy_addon',
+
+      # Declare that the output of this target is not linked:
+      'type': 'none',
+
+      # Define dependencies:
+      'dependencies': [
+        # Require that the add-on be generated before building this target:
+        '<(addon_target_name)',
+      ],
+
+      # Define a list of actions:
+      'actions': [
+        {
+          'action_name': 'copy_addon',
+          'message': 'Copying addon...',
+
+          # Explicitly list the inputs in the command-line invocation below:
+          'inputs': [],
+
+          # Declare the expected outputs:
+          'outputs': [
+            '<(addon_output_dir)/<(addon_target_name).node',
+          ],
+
+          # Define the command-line invocation:
+          'action': [
+            'cp',
+            '<(PRODUCT_DIR)/<(addon_target_name).node',
+            '<(addon_output_dir)/<(addon_target_name).node',
+          ],
+        },
+      ], # end actions
+    }, # end target copy_addon
+  ], # end targets
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/examples/c/Makefile
new file mode 100644
index 000000000000..25ced822f96a
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/examples/c/Makefile
@@ -0,0 +1,146 @@
+#/
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#/
+
+# VARIABLES #
+
+ifndef VERBOSE
+	QUIET := @
+else
+	QUIET :=
+endif
+
+# Determine the OS ([1][1], [2][2]).
+#
+# [1]: https://en.wikipedia.org/wiki/Uname#Examples
+# [2]: http://stackoverflow.com/a/27776822/2225624
+OS ?= $(shell uname)
+ifneq (, $(findstring MINGW,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring MSYS,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring CYGWIN,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring Windows_NT,$(OS)))
+	OS := WINNT
+endif
+endif
+endif
+endif
+
+# Define the program used for compiling C source files:
+ifdef C_COMPILER
+	CC := $(C_COMPILER)
+else
+	CC := gcc
+endif
+
+# Define the command-line options when compiling C files:
+CFLAGS ?= \
+	-std=c99 \
+	-O3 \
+	-Wall \
+	-pedantic
+
+# Determine whether to generate position independent code ([1][1], [2][2]).
+#
+# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options
+# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option
+ifeq ($(OS), WINNT)
+	fPIC ?=
+else
+	fPIC ?= -fPIC
+endif
+
+# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`):
+INCLUDE ?=
+
+# List of source files:
+SOURCE_FILES ?=
+
+# List of libraries (e.g., `-lopenblas -lpthread`):
+LIBRARIES ?=
+
+# List of library paths (e.g., `-L /foo/bar -L /beep/boop`):
+LIBPATH ?=
+
+# List of C targets:
+c_targets := example.out
+
+
+# RULES #
+
+#/
+# Compiles source files.
+#
+# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`)
+# @param {string} [CFLAGS] - C compiler options
+# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`)
+# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`)
+# @param {string} [SOURCE_FILES] - list of source files
+# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`)
+# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`)
+#
+# @example
+# make
+#
+# @example
+# make all
+#/
+all: $(c_targets)
+
+.PHONY: all
+
+#/
+# Compiles C source files.
+#
+# @private
+# @param {string} CC - C compiler (e.g., `gcc`)
+# @param {string} CFLAGS - C compiler options
+# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`)
+# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`)
+# @param {string} SOURCE_FILES - list of source files
+# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`)
+# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`)
+#/
+$(c_targets): %.out: %.c
+	$(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES)
+
+#/
+# Runs compiled examples.
+#
+# @example
+# make run
+#/
+run: $(c_targets)
+	$(QUIET) ./$<
+
+.PHONY: run
+
+#/
+# Removes generated files.
+#
+# @example
+# make clean
+#/
+clean:
+	$(QUIET) -rm -f *.o *.out
+
+.PHONY: clean
diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/examples/c/example.c
new file mode 100644
index 000000000000..a80f5327b8b6
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/examples/c/example.c
@@ -0,0 +1,38 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/dists/geometric/entropy.h"
+#include <stdlib.h>
+#include <stdio.h>
+
+static double random_uniform( const double min, const double max ) {
+	double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
+	return min + ( v*(max-min) );
+}
+
+int main( void ) {
+	double p;
+	double y;
+	int i;
+
+	for ( i = 0; i < 25; i++ ) {
+		p = random_uniform( 0.0, 1.0 );
+		y = stdlib_base_dists_geometric_entropy( p );
+		printf( "p: %lf, H(X;p): %lf\n", p, y );
+	}
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/include.gypi
new file mode 100644
index 000000000000..ecfaf82a3279
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/include.gypi
@@ -0,0 +1,53 @@
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# A GYP include file for building a Node.js native add-on.
+#
+# Main documentation:
+#
+# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md
+# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md
+{
+  # Define variables to be used throughout the configuration for all targets:
+  'variables': {
+    # Source directory:
+    'src_dir': './src',
+
+    # Include directories:
+    'include_dirs': [
+      '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).include; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
+    ],
+
+    # Add-on destination directory:
+    'addon_output_dir': './src',
+
+    # Source files:
+    'src_files': [
+      '<(src_dir)/addon.c',
+      '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).src; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
+    ],
+
+    # Library dependencies:
+    'libraries': [
+      '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).libraries; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
+    ],
+
+    # Library directories:
+    'library_dirs': [
+      '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).libpath; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
+    ],
+  }, # end variables
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/include/stdlib/stats/base/dists/geometric/entropy.h b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/include/stdlib/stats/base/dists/geometric/entropy.h
new file mode 100644
index 000000000000..50136d907ed4
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/include/stdlib/stats/base/dists/geometric/entropy.h
@@ -0,0 +1,38 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#ifndef STDLIB_STATS_BASE_DISTS_GEOMETRIC_ENTROPY_H
+#define STDLIB_STATS_BASE_DISTS_GEOMETRIC_ENTROPY_H
+
+/*
+* If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler.
+*/
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+/**
+* Returns the entropy of a geometric distribution.
+*/
+double stdlib_base_dists_geometric_entropy( const double p );
+
+#ifdef __cplusplus
+}
+#endif
+
+#endif // !STDLIB_STATS_BASE_DISTS_GEOMETRIC_ENTROPY_H
diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/lib/native.js b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/lib/native.js
new file mode 100644
index 000000000000..2a094798c55b
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/lib/native.js
@@ -0,0 +1,62 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var addon = require( './../src/addon.node' );
+
+
+// MAIN //
+
+/**
+* Returns the entropy of a geometric distribution.
+*
+* @private
+* @param {Probability} p - success probability
+* @returns {PositiveNumber} entropy
+*
+* @example
+* var v = entropy( 0.1 );
+* // returns ~3.251
+*
+* @example
+* var v = entropy( 0.5 );
+* // returns ~1.386
+*
+* @example
+* var v = entropy( 0.9 );
+* // returns ~0.361
+*
+* @example
+* var v = entropy( 1.1 );
+* // returns NaN
+*
+* @example
+* var v = entropy( NaN );
+* // returns NaN
+*/
+function entropy( p ) {
+	return addon( p );
+}
+
+
+// EXPORTS //
+
+module.exports = entropy;
diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/manifest.json b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/manifest.json
new file mode 100644
index 000000000000..de112674bc8a
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/manifest.json
@@ -0,0 +1,79 @@
+{
+  "options": {
+    "task": "build",
+    "wasm": false
+  },
+  "fields": [
+    {
+      "field": "src",
+      "resolve": true,
+      "relative": true
+    },
+    {
+      "field": "include",
+      "resolve": true,
+      "relative": true
+    },
+    {
+      "field": "libraries",
+      "resolve": false,
+      "relative": false
+    },
+    {
+      "field": "libpath",
+      "resolve": true,
+      "relative": false
+    }
+  ],
+  "confs": [
+    {
+      "task": "build",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/math/base/napi/unary",
+        "@stdlib/math/base/assert/is-nan",
+        "@stdlib/math/base/special/ln"
+      ]
+    },
+    {
+      "task": "benchmark",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/math/base/assert/is-nan",
+        "@stdlib/math/base/special/ln"
+      ]
+    },
+    {
+      "task": "examples",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/math/base/assert/is-nan",
+        "@stdlib/math/base/special/ln"
+      ]
+    }
+  ]
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/package.json b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/package.json
index ef4c3983e4bb..6a0dd161907a 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/package.json
+++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/package.json
@@ -14,11 +14,14 @@
     }
   ],
   "main": "./lib",
+  "gypfile": true,
   "directories": {
     "benchmark": "./benchmark",
     "doc": "./docs",
     "example": "./examples",
+    "include": "./include",
     "lib": "./lib",
+    "src": "./src",
     "test": "./test"
   },
   "types": "./docs/types",
diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/src/Makefile b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/src/Makefile
new file mode 100644
index 000000000000..7733b6180cb4
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/src/Makefile
@@ -0,0 +1,70 @@
+#/
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#/
+
+# VARIABLES #
+
+ifndef VERBOSE
+	QUIET := @
+else
+	QUIET :=
+endif
+
+# Determine the OS ([1][1], [2][2]).
+#
+# [1]: https://en.wikipedia.org/wiki/Uname#Examples
+# [2]: http://stackoverflow.com/a/27776822/2225624
+OS ?= $(shell uname)
+ifneq (, $(findstring MINGW,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring MSYS,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring CYGWIN,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring Windows_NT,$(OS)))
+	OS := WINNT
+endif
+endif
+endif
+endif
+
+
+# RULES #
+
+#/
+# Removes generated files for building an add-on.
+#
+# @example
+# make clean-addon
+#/
+clean-addon:
+	$(QUIET) -rm -f *.o *.node
+
+.PHONY: clean-addon
+
+#/
+# Removes generated files.
+#
+# @example
+# make clean
+#/
+clean: clean-addon
+
+.PHONY: clean
diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/src/addon.c b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/src/addon.c
new file mode 100644
index 000000000000..f1e61e0664fe
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/src/addon.c
@@ -0,0 +1,23 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/dists/geometric/entropy.h"
+#include "stdlib/math/base/napi/unary.h"
+
+// cppcheck-suppress shadowFunction
+STDLIB_MATH_BASE_NAPI_MODULE_D_D( stdlib_base_dists_geometric_entropy )
diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/src/main.c
new file mode 100644
index 000000000000..9dc6ff846288
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/src/main.c
@@ -0,0 +1,44 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/dists/geometric/entropy.h"
+#include "stdlib/math/base/assert/is_nan.h"
+#include "stdlib/math/base/special/ln.h"
+
+/**
+* Returns the entropy of a geometric distribution.
+*
+* @param p    success probability
+* @return     entropy
+*
+* @example
+* double y = stdlib_base_dists_geometric_entropy( 0.1 );
+* // returns ~3.251
+*/
+double stdlib_base_dists_geometric_entropy( const double p ) {
+	double q;
+	if (
+		stdlib_base_is_nan( p ) ||
+		p <= 0.0 ||
+		p >= 1.0
+	) {
+		return 0.0 / 0.0; // NaN
+	}
+	q = 1.0 - p;
+	return ( -( p * stdlib_base_ln( p ) ) - ( q * stdlib_base_ln( q ) ) ) / p;
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/test/test.native.js
new file mode 100644
index 000000000000..235f7fe49b17
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/geometric/entropy/test/test.native.js
@@ -0,0 +1,99 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var resolve = require( 'path' ).resolve;
+var tape = require( 'tape' );
+var tryRequire = require( '@stdlib/utils/try-require' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var abs = require( '@stdlib/math/base/special/abs' );
+var PINF = require( '@stdlib/constants/float64/pinf' );
+var NINF = require( '@stdlib/constants/float64/ninf' );
+var EPS = require( '@stdlib/constants/float64/eps' );
+
+
+// VARIABLES //
+
+var entropy = tryRequire( resolve( __dirname, './../lib/native.js' ) );
+var opts = {
+	'skip': ( entropy instanceof Error )
+};
+
+
+// FIXTURES //
+
+var data = require( './fixtures/julia/data.json' );
+
+
+// TESTS //
+
+tape( 'main export is a function', opts, function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof entropy, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'if provided `NaN` for `p`, the function returns `NaN`', opts, function test( t ) {
+	var k = entropy( NaN );
+	t.equal( isnan( k ), true, 'returns NaN' );
+	t.end();
+});
+
+tape( 'if provided a success probability `p` outside of `[0,1]`, the function returns `NaN`', opts, function test( t ) {
+	var k;
+
+	k = entropy( -1.0 );
+	t.equal( isnan( k ), true, 'returns NaN' );
+
+	k = entropy( 1.5 );
+	t.equal( isnan( k ), true, 'returns NaN' );
+
+	k = entropy( NINF );
+	t.equal( isnan( k ), true, 'returns NaN' );
+
+	k = entropy( PINF );
+	t.equal( isnan( k ), true, 'returns NaN' );
+
+	t.end();
+});
+
+tape( 'the function returns the entropy of a geometric distribution', opts, function test( t ) {
+	var expected;
+	var delta;
+	var tol;
+	var i;
+	var p;
+	var y;
+
+	expected = data.expected;
+	p = data.p;
+	for ( i = 0; i < expected.length; i++ ) {
+		y = entropy( p[i] );
+		if ( y === expected[i] ) {
+			t.equal( y, expected[i], 'p: '+p[i]+', y: '+y+', expected: '+expected[i] );
+		} else {
+			delta = abs( y - expected[ i ] );
+			tol = 100.0 * EPS * abs( expected[ i ] );
+			t.ok( delta <= tol, 'within tolerance. p: '+p[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
+		}
+	}
+	t.end();
+});

From b15d6c5d74a00968023c732baac23271197ca052 Mon Sep 17 00:00:00 2001
From: Athan Reines <kgryte@gmail.com>
Date: Thu, 2 Jan 2025 19:00:25 -0800
Subject: [PATCH 43/87] fix: update include paths and reorder includes

---
type: pre_commit_static_analysis_report
description: Results of running static analysis checks when committing changes.
report:
  - task: lint_filenames
    status: passed
  - task: lint_editorconfig
    status: passed
  - task: lint_markdown
    status: na
  - task: lint_package_json
    status: na
  - task: lint_repl_help
    status: na
  - task: lint_javascript_src
    status: na
  - task: lint_javascript_cli
    status: na
  - task: lint_javascript_examples
    status: na
  - task: lint_javascript_tests
    status: na
  - task: lint_javascript_benchmarks
    status: na
  - task: lint_python
    status: na
  - task: lint_r
    status: na
  - task: lint_c_src
    status: passed
  - task: lint_c_examples
    status: na
  - task: lint_c_benchmarks
    status: passed
  - task: lint_c_tests_fixtures
    status: na
  - task: lint_shell
    status: na
  - task: lint_typescript_declarations
    status: na
  - task: lint_typescript_tests
    status: na
  - task: lint_license_headers
    status: passed
---
---
 .../@stdlib/random/base/minstd/benchmark/c/benchmark.c       | 4 ++--
 .../random/base/minstd/include/stdlib/random/base/minstd.h   | 3 +--
 lib/node_modules/@stdlib/random/base/minstd/src/main.c       | 5 ++---
 3 files changed, 5 insertions(+), 7 deletions(-)

diff --git a/lib/node_modules/@stdlib/random/base/minstd/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/random/base/minstd/benchmark/c/benchmark.c
index d2194c37c3cc..95854406f4e0 100644
--- a/lib/node_modules/@stdlib/random/base/minstd/benchmark/c/benchmark.c
+++ b/lib/node_modules/@stdlib/random/base/minstd/benchmark/c/benchmark.c
@@ -16,14 +16,14 @@
 * limitations under the License.
 */
 
+#include "stdlib/random/base/minstd.h"
+#include "stdlib/random/base/shared.h"
 #include <stdlib.h>
 #include <stdio.h>
 #include <stdint.h>
 #include <math.h>
 #include <time.h>
 #include <sys/time.h>
-#include "stdlib/random/base.h"
-#include "stdlib/random/base/minstd.h"
 
 #define NAME "base/minstd"
 #define ITERATIONS 1000000
diff --git a/lib/node_modules/@stdlib/random/base/minstd/include/stdlib/random/base/minstd.h b/lib/node_modules/@stdlib/random/base/minstd/include/stdlib/random/base/minstd.h
index 324e7ab02e19..d17ac50471d8 100644
--- a/lib/node_modules/@stdlib/random/base/minstd/include/stdlib/random/base/minstd.h
+++ b/lib/node_modules/@stdlib/random/base/minstd/include/stdlib/random/base/minstd.h
@@ -19,9 +19,8 @@
 #ifndef STDLIB_RANDOM_BASE_MINSTD_H
 #define STDLIB_RANDOM_BASE_MINSTD_H
 
-// Note: keep project includes in alphabetical order...
+#include "stdlib/random/base/shared.h"
 #include <stdint.h>
-#include "stdlib/random/base.h"
 
 /*
 * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler.
diff --git a/lib/node_modules/@stdlib/random/base/minstd/src/main.c b/lib/node_modules/@stdlib/random/base/minstd/src/main.c
index 6ae0f84e65e7..5431a5d823cf 100644
--- a/lib/node_modules/@stdlib/random/base/minstd/src/main.c
+++ b/lib/node_modules/@stdlib/random/base/minstd/src/main.c
@@ -16,12 +16,11 @@
 * limitations under the License.
 */
 
-// Note: keep project includes in alphabetical order...
+#include "stdlib/random/base/minstd.h"
+#include "stdlib/random/base/shared.h"
 #include <stdlib.h>
 #include <stdint.h>
 #include <string.h>
-#include "stdlib/random/base.h"
-#include "stdlib/random/base/minstd.h"
 
 // Forward declarations:
 static inline int8_t next( struct BasePRNGObject *obj, uint64_t *out );

From a41b10485a9dbdcc082fc0647fc8b82d5cd4ad8f Mon Sep 17 00:00:00 2001
From: Athan Reines <kgryte@gmail.com>
Date: Thu, 2 Jan 2025 19:01:00 -0800
Subject: [PATCH 44/87] fix: update include paths and reorder includes

---
type: pre_commit_static_analysis_report
description: Results of running static analysis checks when committing changes.
report:
  - task: lint_filenames
    status: passed
  - task: lint_editorconfig
    status: passed
  - task: lint_markdown
    status: na
  - task: lint_package_json
    status: na
  - task: lint_repl_help
    status: na
  - task: lint_javascript_src
    status: na
  - task: lint_javascript_cli
    status: na
  - task: lint_javascript_examples
    status: na
  - task: lint_javascript_tests
    status: na
  - task: lint_javascript_benchmarks
    status: na
  - task: lint_python
    status: na
  - task: lint_r
    status: na
  - task: lint_c_src
    status: passed
  - task: lint_c_examples
    status: na
  - task: lint_c_benchmarks
    status: passed
  - task: lint_c_tests_fixtures
    status: na
  - task: lint_shell
    status: na
  - task: lint_typescript_declarations
    status: na
  - task: lint_typescript_tests
    status: na
  - task: lint_license_headers
    status: passed
---
---
 .../random/base/minstd-shuffle/benchmark/c/benchmark.c     | 4 ++--
 .../include/stdlib/random/base/minstd_shuffle.h            | 3 +--
 .../@stdlib/random/base/minstd-shuffle/src/main.c          | 7 +++----
 3 files changed, 6 insertions(+), 8 deletions(-)

diff --git a/lib/node_modules/@stdlib/random/base/minstd-shuffle/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/random/base/minstd-shuffle/benchmark/c/benchmark.c
index 88d82b7da1d6..128f111ad035 100644
--- a/lib/node_modules/@stdlib/random/base/minstd-shuffle/benchmark/c/benchmark.c
+++ b/lib/node_modules/@stdlib/random/base/minstd-shuffle/benchmark/c/benchmark.c
@@ -16,14 +16,14 @@
 * limitations under the License.
 */
 
+#include "stdlib/random/base/minstd_shuffle.h"
+#include "stdlib/random/base/shared.h"
 #include <stdlib.h>
 #include <stdio.h>
 #include <stdint.h>
 #include <math.h>
 #include <time.h>
 #include <sys/time.h>
-#include "stdlib/random/base.h"
-#include "stdlib/random/base/minstd_shuffle.h"
 
 #define NAME "base/minstd-shuffle"
 #define ITERATIONS 1000000
diff --git a/lib/node_modules/@stdlib/random/base/minstd-shuffle/include/stdlib/random/base/minstd_shuffle.h b/lib/node_modules/@stdlib/random/base/minstd-shuffle/include/stdlib/random/base/minstd_shuffle.h
index e54c6aeb4fc4..c9b804743f4a 100644
--- a/lib/node_modules/@stdlib/random/base/minstd-shuffle/include/stdlib/random/base/minstd_shuffle.h
+++ b/lib/node_modules/@stdlib/random/base/minstd-shuffle/include/stdlib/random/base/minstd_shuffle.h
@@ -19,9 +19,8 @@
 #ifndef STDLIB_RANDOM_BASE_MINSTD_SHUFFLE_H
 #define STDLIB_RANDOM_BASE_MINSTD_SHUFFLE_H
 
-// Note: keep project includes in alphabetical order...
+#include "stdlib/random/base/shared.h"
 #include <stdint.h>
-#include "stdlib/random/base.h"
 
 /*
 * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler.
diff --git a/lib/node_modules/@stdlib/random/base/minstd-shuffle/src/main.c b/lib/node_modules/@stdlib/random/base/minstd-shuffle/src/main.c
index 62cf8ae78740..430bff8eff37 100644
--- a/lib/node_modules/@stdlib/random/base/minstd-shuffle/src/main.c
+++ b/lib/node_modules/@stdlib/random/base/minstd-shuffle/src/main.c
@@ -16,13 +16,12 @@
 * limitations under the License.
 */
 
-// Note: keep project includes in alphabetical order...
+#include "stdlib/random/base/minstd_shuffle.h"
+#include "stdlib/random/base/minstd.h"
+#include "stdlib/random/base/shared.h"
 #include <stdlib.h>
 #include <stdint.h>
 #include <string.h>
-#include "stdlib/random/base.h"
-#include "stdlib/random/base/minstd.h"
-#include "stdlib/random/base/minstd_shuffle.h"
 
 // Forward declarations:
 static inline int8_t next( struct BasePRNGObject *obj, uint64_t *out );

From 412728de57348771059c109648e1842d04406f9b Mon Sep 17 00:00:00 2001
From: Athan Reines <kgryte@gmail.com>
Date: Thu, 2 Jan 2025 19:05:24 -0800
Subject: [PATCH 45/87] docs: fix include paths in examples

---
type: pre_commit_static_analysis_report
description: Results of running static analysis checks when committing changes.
report:
  - task: lint_filenames
    status: passed
  - task: lint_editorconfig
    status: passed
  - task: lint_markdown
    status: na
  - task: lint_package_json
    status: na
  - task: lint_repl_help
    status: na
  - task: lint_javascript_src
    status: na
  - task: lint_javascript_cli
    status: na
  - task: lint_javascript_examples
    status: na
  - task: lint_javascript_tests
    status: na
  - task: lint_javascript_benchmarks
    status: na
  - task: lint_python
    status: na
  - task: lint_r
    status: na
  - task: lint_c_src
    status: passed
  - task: lint_c_examples
    status: passed
  - task: lint_c_benchmarks
    status: na
  - task: lint_c_tests_fixtures
    status: na
  - task: lint_shell
    status: na
  - task: lint_typescript_declarations
    status: na
  - task: lint_typescript_tests
    status: na
  - task: lint_license_headers
    status: passed
---
---
 .../random/base/minstd/examples/c/example.c   |  2 +-
 .../@stdlib/random/base/minstd/src/main.c     | 20 +++++++++----------
 2 files changed, 11 insertions(+), 11 deletions(-)

diff --git a/lib/node_modules/@stdlib/random/base/minstd/examples/c/example.c b/lib/node_modules/@stdlib/random/base/minstd/examples/c/example.c
index 5e1520c62e71..9a6aa701aced 100644
--- a/lib/node_modules/@stdlib/random/base/minstd/examples/c/example.c
+++ b/lib/node_modules/@stdlib/random/base/minstd/examples/c/example.c
@@ -17,7 +17,7 @@
 */
 
 #include "stdlib/random/base/minstd.h"
-#include "stdlib/random/base.h"
+#include "stdlib/random/base/shared.h"
 #include <stdlib.h>
 #include <stdio.h>
 #include <inttypes.h>
diff --git a/lib/node_modules/@stdlib/random/base/minstd/src/main.c b/lib/node_modules/@stdlib/random/base/minstd/src/main.c
index 5431a5d823cf..59c1acf5fbe5 100644
--- a/lib/node_modules/@stdlib/random/base/minstd/src/main.c
+++ b/lib/node_modules/@stdlib/random/base/minstd/src/main.c
@@ -133,11 +133,11 @@ static inline void minstd_free( struct BasePRNGObject *obj ) {
 * @return      pointer to a dynamically allocated PRNG or, if unable to allocate memory, a null pointer
 *
 * @example
+* #include "stdlib/random/base/minstd.h"
+* #include "stdlib/random/base/shared.h"
 * #include <stdlib.h>
 * #include <stdio.h>
 * #include <stdint.h>
-* #include "stdlib/random/base.h"
-* #include "stdlib/random/base/minstd.h"
 *
 * // Create a PRNG:
 * struct BasePRNGObject *obj = stdlib_base_random_minstd_allocate( 12345 );
@@ -203,11 +203,11 @@ struct BasePRNGObject * stdlib_base_random_minstd_allocate( const int32_t seed )
 * @param obj  PRNG object
 *
 * @example
+* #include "stdlib/random/base/minstd.h"
+* #include "stdlib/random/base/shared.h"
 * #include <stdlib.h>
 * #include <stdio.h>
 * #include <stdint.h>
-* #include "stdlib/random/base.h"
-* #include "stdlib/random/base/minstd.h"
 *
 * // Create a PRNG:
 * struct BasePRNGObject *obj = stdlib_base_random_minstd_allocate( 12345 );
@@ -255,11 +255,11 @@ void stdlib_base_random_minstd_free( struct BasePRNGObject *obj ) {
 * @return     status code
 *
 * @example
+* #include "stdlib/random/base/minstd.h"
+* #include "stdlib/random/base/shared.h"
 * #include <stdlib.h>
 * #include <stdio.h>
 * #include <stdint.h>
-* #include "stdlib/random/base.h"
-* #include "stdlib/random/base/minstd.h"
 *
 * // Create a PRNG:
 * struct BasePRNGObject *obj = stdlib_base_random_minstd_allocate( 12345 );
@@ -304,11 +304,11 @@ int8_t stdlib_base_random_minstd_seed( const struct BasePRNGObject *obj, int32_t
 * @return     pointer to a copy of the PRNG's internal state or, if unable to allocate memory, a null pointer
 *
 * @example
+* #include "stdlib/random/base/minstd.h"
+* #include "stdlib/random/base/shared.h"
 * #include <stdlib.h>
 * #include <stdio.h>
 * #include <stdint.h>
-* #include "stdlib/random/base.h"
-* #include "stdlib/random/base/minstd.h"
 *
 * // Create a PRNG:
 * struct BasePRNGObject *obj = stdlib_base_random_minstd_allocate( 12345 );
@@ -353,11 +353,11 @@ void * stdlib_base_random_minstd_state( const struct BasePRNGObject *obj ) {
 * @return       status code
 *
 * @example
+* #include "stdlib/random/base/minstd.h"
+* #include "stdlib/random/base/shared.h"
 * #include <stdlib.h>
 * #include <stdio.h>
 * #include <stdint.h>
-* #include "stdlib/random/base.h"
-* #include "stdlib/random/base/minstd.h"
 *
 * // Create a PRNG:
 * struct BasePRNGObject *obj = stdlib_base_random_minstd_allocate( 12345 );

From 5eac7da2e2ab87d13d1810663b2613b71b48638f Mon Sep 17 00:00:00 2001
From: Athan Reines <kgryte@gmail.com>
Date: Thu, 2 Jan 2025 19:07:11 -0800
Subject: [PATCH 46/87] docs: fix include paths in examples

---
type: pre_commit_static_analysis_report
description: Results of running static analysis checks when committing changes.
report:
  - task: lint_filenames
    status: passed
  - task: lint_editorconfig
    status: passed
  - task: lint_markdown
    status: na
  - task: lint_package_json
    status: na
  - task: lint_repl_help
    status: na
  - task: lint_javascript_src
    status: na
  - task: lint_javascript_cli
    status: na
  - task: lint_javascript_examples
    status: na
  - task: lint_javascript_tests
    status: na
  - task: lint_javascript_benchmarks
    status: na
  - task: lint_python
    status: na
  - task: lint_r
    status: na
  - task: lint_c_src
    status: passed
  - task: lint_c_examples
    status: passed
  - task: lint_c_benchmarks
    status: na
  - task: lint_c_tests_fixtures
    status: na
  - task: lint_shell
    status: na
  - task: lint_typescript_declarations
    status: na
  - task: lint_typescript_tests
    status: na
  - task: lint_license_headers
    status: passed
---
---
 .../base/minstd-shuffle/examples/c/example.c  |  2 +-
 .../random/base/minstd-shuffle/src/main.c     | 20 +++++++++----------
 2 files changed, 11 insertions(+), 11 deletions(-)

diff --git a/lib/node_modules/@stdlib/random/base/minstd-shuffle/examples/c/example.c b/lib/node_modules/@stdlib/random/base/minstd-shuffle/examples/c/example.c
index 549dc2cd2c35..95bfda7ebdf1 100644
--- a/lib/node_modules/@stdlib/random/base/minstd-shuffle/examples/c/example.c
+++ b/lib/node_modules/@stdlib/random/base/minstd-shuffle/examples/c/example.c
@@ -17,7 +17,7 @@
 */
 
 #include "stdlib/random/base/minstd_shuffle.h"
-#include "stdlib/random/base.h"
+#include "stdlib/random/base/shared.h"
 #include <stdlib.h>
 #include <stdio.h>
 #include <inttypes.h>
diff --git a/lib/node_modules/@stdlib/random/base/minstd-shuffle/src/main.c b/lib/node_modules/@stdlib/random/base/minstd-shuffle/src/main.c
index 430bff8eff37..d46bba61ed31 100644
--- a/lib/node_modules/@stdlib/random/base/minstd-shuffle/src/main.c
+++ b/lib/node_modules/@stdlib/random/base/minstd-shuffle/src/main.c
@@ -182,11 +182,11 @@ static inline int8_t create_table( struct BasePRNGObject *obj, uint32_t *table )
 * @return      pointer to a dynamically allocated PRNG or, if unable to allocate memory, a null pointer
 *
 * @example
+* #include "stdlib/random/base/minstd_shuffle.h"
+* #include "stdlib/random/base/shared.h"
 * #include <stdlib.h>
 * #include <stdio.h>
 * #include <stdint.h>
-* #include "stdlib/random/base.h"
-* #include "stdlib/random/base/minstd_shuffle.h"
 *
 * // Create a PRNG:
 * struct BasePRNGObject *obj = stdlib_base_random_minstd_shuffle_allocate( 12345 );
@@ -273,11 +273,11 @@ struct BasePRNGObject * stdlib_base_random_minstd_shuffle_allocate( const int32_
 * @param obj  PRNG object
 *
 * @example
+* #include "stdlib/random/base/minstd_shuffle.h"
+* #include "stdlib/random/base/shared.h"
 * #include <stdlib.h>
 * #include <stdio.h>
 * #include <stdint.h>
-* #include "stdlib/random/base.h"
-* #include "stdlib/random/base/minstd_shuffle.h"
 *
 * // Create a PRNG:
 * struct BasePRNGObject *obj = stdlib_base_random_minstd_shuffle_allocate( 12345 );
@@ -325,11 +325,11 @@ void stdlib_base_random_minstd_shuffle_free( struct BasePRNGObject *obj ) {
 * @return     status code
 *
 * @example
+* #include "stdlib/random/base/minstd_shuffle.h"
+* #include "stdlib/random/base/shared.h"
 * #include <stdlib.h>
 * #include <stdio.h>
 * #include <stdint.h>
-* #include "stdlib/random/base.h"
-* #include "stdlib/random/base/minstd_shuffle.h"
 *
 * // Create a PRNG:
 * struct BasePRNGObject *obj = stdlib_base_random_minstd_shuffle_allocate( 12345 );
@@ -374,11 +374,11 @@ int8_t stdlib_base_random_minstd_shuffle_seed( const struct BasePRNGObject *obj,
 * @return     pointer to a copy of the PRNG's internal state or, if unable to allocate memory, a null pointer
 *
 * @example
+* #include "stdlib/random/base/minstd_shuffle.h"
+* #include "stdlib/random/base/shared.h"
 * #include <stdlib.h>
 * #include <stdio.h>
 * #include <stdint.h>
-* #include "stdlib/random/base.h"
-* #include "stdlib/random/base/minstd_shuffle.h"
 *
 * // Create a PRNG:
 * struct BasePRNGObject *obj = stdlib_base_random_minstd_shuffle_allocate( 12345 );
@@ -423,11 +423,11 @@ void * stdlib_base_random_minstd_shuffle_state( const struct BasePRNGObject *obj
 * @return       status code
 *
 * @example
+* #include "stdlib/random/base/minstd_shuffle.h"
+* #include "stdlib/random/base/shared.h"
 * #include <stdlib.h>
 * #include <stdio.h>
 * #include <stdint.h>
-* #include "stdlib/random/base.h"
-* #include "stdlib/random/base/minstd_shuffle.h"
 *
 * // Create a PRNG:
 * struct BasePRNGObject *obj = stdlib_base_random_minstd_shuffle_allocate( 12345 );

From c5f27772bca3e718aca6a5933150e488e8f9071c Mon Sep 17 00:00:00 2001
From: Athan Reines <kgryte@gmail.com>
Date: Thu, 2 Jan 2025 19:10:57 -0800
Subject: [PATCH 47/87] fix: update include paths and reorder includes

---
type: pre_commit_static_analysis_report
description: Results of running static analysis checks when committing changes.
report:
  - task: lint_filenames
    status: passed
  - task: lint_editorconfig
    status: passed
  - task: lint_markdown
    status: na
  - task: lint_package_json
    status: na
  - task: lint_repl_help
    status: na
  - task: lint_javascript_src
    status: na
  - task: lint_javascript_cli
    status: na
  - task: lint_javascript_examples
    status: na
  - task: lint_javascript_tests
    status: na
  - task: lint_javascript_benchmarks
    status: na
  - task: lint_python
    status: na
  - task: lint_r
    status: na
  - task: lint_c_src
    status: passed
  - task: lint_c_examples
    status: passed
  - task: lint_c_benchmarks
    status: passed
  - task: lint_c_tests_fixtures
    status: na
  - task: lint_shell
    status: na
  - task: lint_typescript_declarations
    status: na
  - task: lint_typescript_tests
    status: na
  - task: lint_license_headers
    status: passed
---
---
 .../base/mt19937/benchmark/c/benchmark.c      |  4 +--
 .../random/base/mt19937/examples/c/example.c  |  2 +-
 .../include/stdlib/random/base/mt19937.h      |  3 +-
 .../@stdlib/random/base/mt19937/src/main.c    | 31 +++++++++----------
 4 files changed, 19 insertions(+), 21 deletions(-)

diff --git a/lib/node_modules/@stdlib/random/base/mt19937/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/random/base/mt19937/benchmark/c/benchmark.c
index 93312b8106a4..559955e7889c 100644
--- a/lib/node_modules/@stdlib/random/base/mt19937/benchmark/c/benchmark.c
+++ b/lib/node_modules/@stdlib/random/base/mt19937/benchmark/c/benchmark.c
@@ -16,14 +16,14 @@
 * limitations under the License.
 */
 
+#include "stdlib/random/base/mt19937.h"
+#include "stdlib/random/base/shared.h"
 #include <stdlib.h>
 #include <stdio.h>
 #include <stdint.h>
 #include <math.h>
 #include <time.h>
 #include <sys/time.h>
-#include "stdlib/random/base.h"
-#include "stdlib/random/base/mt19937.h"
 
 #define NAME "base/mt19937"
 #define ITERATIONS 1000000
diff --git a/lib/node_modules/@stdlib/random/base/mt19937/examples/c/example.c b/lib/node_modules/@stdlib/random/base/mt19937/examples/c/example.c
index 8292539debca..dc00d7046215 100644
--- a/lib/node_modules/@stdlib/random/base/mt19937/examples/c/example.c
+++ b/lib/node_modules/@stdlib/random/base/mt19937/examples/c/example.c
@@ -17,7 +17,7 @@
 */
 
 #include "stdlib/random/base/mt19937.h"
-#include "stdlib/random/base.h"
+#include "stdlib/random/base/shared.h"
 #include <stdlib.h>
 #include <stdio.h>
 #include <inttypes.h>
diff --git a/lib/node_modules/@stdlib/random/base/mt19937/include/stdlib/random/base/mt19937.h b/lib/node_modules/@stdlib/random/base/mt19937/include/stdlib/random/base/mt19937.h
index 274b04a341c6..a9e8381a1e23 100644
--- a/lib/node_modules/@stdlib/random/base/mt19937/include/stdlib/random/base/mt19937.h
+++ b/lib/node_modules/@stdlib/random/base/mt19937/include/stdlib/random/base/mt19937.h
@@ -19,9 +19,8 @@
 #ifndef STDLIB_RANDOM_BASE_MT19937_H
 #define STDLIB_RANDOM_BASE_MT19937_H
 
-// Note: keep project includes in alphabetical order...
+#include "stdlib/random/base/shared.h"
 #include <stdint.h>
-#include "stdlib/random/base.h"
 
 /*
 * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler.
diff --git a/lib/node_modules/@stdlib/random/base/mt19937/src/main.c b/lib/node_modules/@stdlib/random/base/mt19937/src/main.c
index 61d605b8c303..2e5afe98a572 100644
--- a/lib/node_modules/@stdlib/random/base/mt19937/src/main.c
+++ b/lib/node_modules/@stdlib/random/base/mt19937/src/main.c
@@ -55,12 +55,11 @@
 * [mt19937]: http://www.math.sci.hiroshima-u.ac.jp/~m-mat/MT/MT2002/CODES/mt19937ar.c
 */
 
-// Note: keep project includes in alphabetical order...
+#include "stdlib/random/base/mt19937.h"
+#include "stdlib/random/base/shared.h"
 #include <stdlib.h>
 #include <stdint.h>
 #include <string.h>
-#include "stdlib/random/base.h"
-#include "stdlib/random/base/mt19937.h"
 
 // Forward declarations:
 static inline int8_t next( struct BasePRNGObject *obj, uint64_t *out );
@@ -392,11 +391,11 @@ static inline void twist( uint32_t *state, const int32_t N ) {
 * @return      pointer to a dynamically allocated PRNG or, if unable to allocate memory, a null pointer
 *
 * @example
+* #include "stdlib/random/base/mt19937.h"
+* #include "stdlib/random/base/shared.h"
 * #include <stdlib.h>
 * #include <stdio.h>
 * #include <stdint.h>
-* #include "stdlib/random/base.h"
-* #include "stdlib/random/base/mt19937.h"
 *
 * // Define a PRNG seed:
 * uint32_t seed[] = { 12345 };
@@ -472,11 +471,11 @@ struct BasePRNGObject * stdlib_base_random_mt19937_allocate( const uint32_t *see
 * @param obj  PRNG object
 *
 * @example
+* #include "stdlib/random/base/mt19937.h"
+* #include "stdlib/random/base/shared.h"
 * #include <stdlib.h>
 * #include <stdio.h>
 * #include <stdint.h>
-* #include "stdlib/random/base.h"
-* #include "stdlib/random/base/mt19937.h"
 *
 * // Define a PRNG seed:
 * uint32_t seed[] = { 12345 };
@@ -527,11 +526,11 @@ void stdlib_base_random_mt19937_free( struct BasePRNGObject *obj ) {
 * @return      status code
 *
 * @example
+* #include "stdlib/random/base/mt19937.h"
+* #include "stdlib/random/base/shared.h"
 * #include <stdlib.h>
 * #include <stdio.h>
 * #include <stdint.h>
-* #include "stdlib/random/base.h"
-* #include "stdlib/random/base/mt19937.h"
 *
 * // Define a PRNG seed:
 * uint32_t seed1[] = { 12345 };
@@ -596,11 +595,11 @@ int8_t stdlib_base_random_mt19937_seed_length( const struct BasePRNGObject *obj,
 * @return      status code
 *
 * @example
+* #include "stdlib/random/base/mt19937.h"
+* #include "stdlib/random/base/shared.h"
 * #include <stdlib.h>
 * #include <stdio.h>
 * #include <stdint.h>
-* #include "stdlib/random/base.h"
-* #include "stdlib/random/base/mt19937.h"
 *
 * // Define a PRNG seed:
 * uint32_t seed1[] = { 12345 };
@@ -664,11 +663,11 @@ int8_t stdlib_base_random_mt19937_seed( const struct BasePRNGObject *obj, uint32
 * @return     pointer to a copy of the PRNG's internal state or, if unable to allocate memory, a null pointer
 *
 * @example
+* #include "stdlib/random/base/mt19937.h"
+* #include "stdlib/random/base/shared.h"
 * #include <stdlib.h>
 * #include <stdio.h>
 * #include <stdint.h>
-* #include "stdlib/random/base.h"
-* #include "stdlib/random/base/mt19937.h"
 *
 * // Define a PRNG seed:
 * uint32_t seed[] = { 12345 };
@@ -695,8 +694,8 @@ int8_t stdlib_base_random_mt19937_seed( const struct BasePRNGObject *obj, uint32
 * free( state );
 */
 void * stdlib_base_random_mt19937_state( const struct BasePRNGObject *obj ) {
+	const stdlib_base_random_mt19937_state_t *so;
 	stdlib_base_random_mt19937_state_t *state;
-	stdlib_base_random_mt19937_state_t *so;
 	uint64_t nbytes;
 	uint32_t *seed;
 	if ( obj == NULL || obj->prng != &mt19937_prng ) {
@@ -735,11 +734,11 @@ void * stdlib_base_random_mt19937_state( const struct BasePRNGObject *obj ) {
 * @return       status code
 *
 * @example
+* #include "stdlib/random/base/mt19937.h"
+* #include "stdlib/random/base/shared.h"
 * #include <stdlib.h>
 * #include <stdio.h>
 * #include <stdint.h>
-* #include "stdlib/random/base.h"
-* #include "stdlib/random/base/mt19937.h"
 *
 * // Define a PRNG seed:
 * uint32_t seed[] = { 12345 };

From f5da92586395a6e3734c18e446753e205a4d3bbe Mon Sep 17 00:00:00 2001
From: Athan Reines <kgryte@gmail.com>
Date: Thu, 2 Jan 2025 19:13:31 -0800
Subject: [PATCH 48/87] style: update include order

---
type: pre_commit_static_analysis_report
description: Results of running static analysis checks when committing changes.
report:
  - task: lint_filenames
    status: passed
  - task: lint_editorconfig
    status: passed
  - task: lint_markdown
    status: na
  - task: lint_package_json
    status: na
  - task: lint_repl_help
    status: na
  - task: lint_javascript_src
    status: na
  - task: lint_javascript_cli
    status: na
  - task: lint_javascript_examples
    status: na
  - task: lint_javascript_tests
    status: na
  - task: lint_javascript_benchmarks
    status: na
  - task: lint_python
    status: na
  - task: lint_r
    status: na
  - task: lint_c_src
    status: passed
  - task: lint_c_examples
    status: na
  - task: lint_c_benchmarks
    status: passed
  - task: lint_c_tests_fixtures
    status: na
  - task: lint_shell
    status: na
  - task: lint_typescript_declarations
    status: na
  - task: lint_typescript_tests
    status: na
  - task: lint_license_headers
    status: passed
---
---
 .../@stdlib/random/base/shared/benchmark/c/benchmark.c      | 2 +-
 lib/node_modules/@stdlib/random/base/shared/src/main.c      | 6 ++----
 2 files changed, 3 insertions(+), 5 deletions(-)

diff --git a/lib/node_modules/@stdlib/random/base/shared/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/random/base/shared/benchmark/c/benchmark.c
index a36dcf4a8b91..152eec0f3d34 100644
--- a/lib/node_modules/@stdlib/random/base/shared/benchmark/c/benchmark.c
+++ b/lib/node_modules/@stdlib/random/base/shared/benchmark/c/benchmark.c
@@ -16,13 +16,13 @@
 * limitations under the License.
 */
 
+#include "stdlib/random/base/shared.h"
 #include <stdlib.h>
 #include <stdio.h>
 #include <stdint.h>
 #include <math.h>
 #include <time.h>
 #include <sys/time.h>
-#include "stdlib/random/base/shared.h"
 
 #define NAME "random/base/shared"
 #define ITERATIONS 1000000
diff --git a/lib/node_modules/@stdlib/random/base/shared/src/main.c b/lib/node_modules/@stdlib/random/base/shared/src/main.c
index 2b22fcfbb173..2834549b33ad 100644
--- a/lib/node_modules/@stdlib/random/base/shared/src/main.c
+++ b/lib/node_modules/@stdlib/random/base/shared/src/main.c
@@ -16,12 +16,10 @@
 * limitations under the License.
 */
 
-// Note: keep project includes in alphabetical order...
+#include "stdlib/random/base/shared.h"
 #include <stdlib.h>
 #include <stdint.h>
 #include <string.h>
-#include <math.h>
-#include "stdlib/random/base/shared.h"
 
 /**
 * Frees a PRNG's allocated memory.
@@ -66,7 +64,7 @@ uint64_t stdlib_base_prng_next( struct BasePRNGObject *obj ) {
 */
 double stdlib_base_prng_normalized( struct BasePRNGObject *obj ) {
 	if ( obj == NULL ) {
-		return NAN;
+		return 0.0 / 0.0; // NaN
 	}
 	double v;
 	obj->prng->normalized( obj, &v );

From 4befa33ca24cd6c3aeb13bce35d96db6a94de3fd Mon Sep 17 00:00:00 2001
From: Athan Reines <kgryte@gmail.com>
Date: Thu, 2 Jan 2025 21:24:45 -0800
Subject: [PATCH 49/87] fix: update include paths and refactor branching logic

---
type: pre_commit_static_analysis_report
description: Results of running static analysis checks when committing changes.
report:
  - task: lint_filenames
    status: passed
  - task: lint_editorconfig
    status: passed
  - task: lint_markdown
    status: na
  - task: lint_package_json
    status: na
  - task: lint_repl_help
    status: na
  - task: lint_javascript_src
    status: na
  - task: lint_javascript_cli
    status: na
  - task: lint_javascript_examples
    status: na
  - task: lint_javascript_tests
    status: na
  - task: lint_javascript_benchmarks
    status: na
  - task: lint_python
    status: na
  - task: lint_r
    status: na
  - task: lint_c_src
    status: passed
  - task: lint_c_examples
    status: passed
  - task: lint_c_benchmarks
    status: passed
  - task: lint_c_tests_fixtures
    status: na
  - task: lint_shell
    status: na
  - task: lint_typescript_declarations
    status: na
  - task: lint_typescript_tests
    status: na
  - task: lint_license_headers
    status: passed
---
---
 .../random/base/randi/benchmark/c/benchmark.c |  2 +-
 .../random/base/randi/examples/c/example.c    |  2 +-
 .../randi/include/stdlib/random/base/randi.h  |  3 +-
 .../@stdlib/random/base/randi/src/main.c      | 53 ++++++++++---------
 4 files changed, 30 insertions(+), 30 deletions(-)

diff --git a/lib/node_modules/@stdlib/random/base/randi/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/random/base/randi/benchmark/c/benchmark.c
index 1bde620faee6..7d78157bdce7 100644
--- a/lib/node_modules/@stdlib/random/base/randi/benchmark/c/benchmark.c
+++ b/lib/node_modules/@stdlib/random/base/randi/benchmark/c/benchmark.c
@@ -17,7 +17,7 @@
 */
 
 #include "stdlib/random/base/randi.h"
-#include "stdlib/random/base.h"
+#include "stdlib/random/base/shared.h"
 #include <stdlib.h>
 #include <stdio.h>
 #include <stdint.h>
diff --git a/lib/node_modules/@stdlib/random/base/randi/examples/c/example.c b/lib/node_modules/@stdlib/random/base/randi/examples/c/example.c
index b2171d1dc6f8..3e12bab097d8 100644
--- a/lib/node_modules/@stdlib/random/base/randi/examples/c/example.c
+++ b/lib/node_modules/@stdlib/random/base/randi/examples/c/example.c
@@ -17,7 +17,7 @@
 */
 
 #include "stdlib/random/base/randi.h"
-#include "stdlib/random/base.h"
+#include "stdlib/random/base/shared.h"
 #include <stdlib.h>
 #include <stdio.h>
 #include <inttypes.h>
diff --git a/lib/node_modules/@stdlib/random/base/randi/include/stdlib/random/base/randi.h b/lib/node_modules/@stdlib/random/base/randi/include/stdlib/random/base/randi.h
index 574b15078f52..703a1dca8f76 100644
--- a/lib/node_modules/@stdlib/random/base/randi/include/stdlib/random/base/randi.h
+++ b/lib/node_modules/@stdlib/random/base/randi/include/stdlib/random/base/randi.h
@@ -19,9 +19,8 @@
 #ifndef STDLIB_RANDOM_BASE_RANDI_H
 #define STDLIB_RANDOM_BASE_RANDI_H
 
-// Note: keep project includes in alphabetical order...
+#include "stdlib/random/base/shared.h"
 #include <stdarg.h>
-#include "stdlib/random/base.h"
 
 /*
 * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler.
diff --git a/lib/node_modules/@stdlib/random/base/randi/src/main.c b/lib/node_modules/@stdlib/random/base/randi/src/main.c
index 4d1112156c42..a6ffceb2ea94 100644
--- a/lib/node_modules/@stdlib/random/base/randi/src/main.c
+++ b/lib/node_modules/@stdlib/random/base/randi/src/main.c
@@ -16,15 +16,14 @@
 * limitations under the License.
 */
 
-// Note: keep project includes in alphabetical order...
-#include <stdlib.h>
-#include <stdint.h>
-#include <stdarg.h>
-#include "stdlib/random/base.h"
+#include "stdlib/random/base/randi.h"
+#include "stdlib/random/base/shared.h"
 #include "stdlib/random/base/minstd.h"
 #include "stdlib/random/base/minstd_shuffle.h"
 #include "stdlib/random/base/mt19937.h"
-#include "stdlib/random/base/randi.h"
+#include <stdlib.h>
+#include <stdint.h>
+#include <stdarg.h>
 
 // Define the default PRNG:
 static const enum STDLIB_BASE_RANDOM_RANDI_PRNG STDLIB_BASE_RANDOM_RANDI_DEFAULT = STDLIB_BASE_RANDOM_RANDI_MT19937;
@@ -43,11 +42,11 @@ static const enum STDLIB_BASE_RANDOM_RANDI_PRNG STDLIB_BASE_RANDOM_RANDI_DEFAULT
 * @return        pointer to a dynamically allocated PRNG or, if unable to allocate memory, a null pointer
 *
 * @example
+* #include "stdlib/random/base/randi.h"
+* #include "stdlib/random/base/shared.h"
 * #include <stdlib.h>
 * #include <stdio.h>
 * #include <stdint.h>
-* #include "stdlib/random/base.h"
-* #include "stdlib/random/base/randi.h"
 *
 * // Create a PRNG:
 * struct BasePRNGObject *obj = stdlib_base_random_randi_allocate( 0 );
@@ -73,11 +72,9 @@ static const enum STDLIB_BASE_RANDOM_RANDI_PRNG STDLIB_BASE_RANDOM_RANDI_DEFAULT
 */
 struct BasePRNGObject * stdlib_base_random_randi_allocate( const int nargs, ... ) {
 	enum STDLIB_BASE_RANDOM_RANDI_PRNG prng;
-	struct BasePRNGObject *obj;
-
 	va_list args;
-	va_start( args, nargs );
 
+	va_start( args, nargs );
 	if ( nargs < 1 ) {
 		prng = STDLIB_BASE_RANDOM_RANDI_DEFAULT;
 	} else {
@@ -90,20 +87,25 @@ struct BasePRNGObject * stdlib_base_random_randi_allocate( const int nargs, ...
 		} else {
 			seed = rand();
 		}
-		obj = stdlib_base_random_minstd_allocate( seed );
-	} else if ( prng == STDLIB_BASE_RANDOM_RANDI_MINSTD_SHUFFLE ) {
+		va_end( args );
+		return stdlib_base_random_minstd_allocate( seed );
+	}
+	if ( prng == STDLIB_BASE_RANDOM_RANDI_MINSTD_SHUFFLE ) {
 		int32_t seed;
 		if ( nargs > 1 ) {
 			seed = va_arg( args, int32_t );
 		} else {
 			seed = rand();
 		}
-		obj = stdlib_base_random_minstd_shuffle_allocate( seed );
-	} else if ( prng == STDLIB_BASE_RANDOM_RANDI_MT19937 ) {
+		va_end( args );
+		return stdlib_base_random_minstd_shuffle_allocate( seed );
+	}
+	if ( prng == STDLIB_BASE_RANDOM_RANDI_MT19937 ) {
+		const uint32_t *seed;
 		int64_t seed_length;
-		uint32_t *seed;
+		uint32_t tseed[ 1 ];
 		if ( nargs < 2 ) {
-			uint32_t tseed[] = { (uint32_t)rand() };
+			tseed[ 0 ] = (uint32_t)rand();
 			seed = tseed;
 			seed_length = 1;
 		} else if ( nargs == 3 ) {
@@ -114,13 +116,12 @@ struct BasePRNGObject * stdlib_base_random_randi_allocate( const int nargs, ...
 			va_end( args );
 			return NULL;
 		}
-		obj = stdlib_base_random_mt19937_allocate( seed, seed_length );
-	} else {
-		// How did we get here? A non-implemented PRNG?
-		obj = NULL;
+		va_end( args );
+		return stdlib_base_random_mt19937_allocate( seed, seed_length );
 	}
+	// How did we get here? A non-implemented PRNG?
 	va_end( args );
-	return obj;
+	return NULL;
 }
 
 /**
@@ -134,11 +135,11 @@ struct BasePRNGObject * stdlib_base_random_randi_allocate( const int nargs, ...
 * @return     pseudorandom integer
 *
 * @example
+* #include "stdlib/random/base/randi.h"
+* #include "stdlib/random/base/shared.h"
 * #include <stdlib.h>
 * #include <stdio.h>
 * #include <stdint.h>
-* #include "stdlib/random/base.h"
-* #include "stdlib/random/base/randi.h"
 *
 * // Create a PRNG:
 * struct BasePRNGObject *obj = stdlib_base_random_randi_allocate( 0 );
@@ -172,11 +173,11 @@ uint64_t stdlib_base_random_randi( struct BasePRNGObject *obj ) {
 * @param obj  PRNG object
 *
 * @example
+* #include "stdlib/random/base/randi.h"
+* #include "stdlib/random/base/shared.h"
 * #include <stdlib.h>
 * #include <stdio.h>
 * #include <stdint.h>
-* #include "stdlib/random/base.h"
-* #include "stdlib/random/base/randi.h"
 *
 * // Create a PRNG:
 * struct BasePRNGObject *obj = stdlib_base_random_randi_allocate( 0 );

From a1757084e81ade6c7a5fc7dd31846daebe39ee91 Mon Sep 17 00:00:00 2001
From: Athan Reines <kgryte@gmail.com>
Date: Thu, 2 Jan 2025 21:27:42 -0800
Subject: [PATCH 50/87] fix: update include paths and refactor branching logic

---
type: pre_commit_static_analysis_report
description: Results of running static analysis checks when committing changes.
report:
  - task: lint_filenames
    status: passed
  - task: lint_editorconfig
    status: passed
  - task: lint_markdown
    status: na
  - task: lint_package_json
    status: na
  - task: lint_repl_help
    status: na
  - task: lint_javascript_src
    status: na
  - task: lint_javascript_cli
    status: na
  - task: lint_javascript_examples
    status: na
  - task: lint_javascript_tests
    status: na
  - task: lint_javascript_benchmarks
    status: na
  - task: lint_python
    status: na
  - task: lint_r
    status: na
  - task: lint_c_src
    status: passed
  - task: lint_c_examples
    status: passed
  - task: lint_c_benchmarks
    status: passed
  - task: lint_c_tests_fixtures
    status: na
  - task: lint_shell
    status: na
  - task: lint_typescript_declarations
    status: na
  - task: lint_typescript_tests
    status: na
  - task: lint_license_headers
    status: passed
---
---
 .../random/base/randu/benchmark/c/benchmark.c |  2 +-
 .../random/base/randu/examples/c/example.c    |  4 +-
 .../randu/include/stdlib/random/base/randu.h  |  3 +-
 .../@stdlib/random/base/randu/src/main.c      | 53 ++++++++++---------
 4 files changed, 31 insertions(+), 31 deletions(-)

diff --git a/lib/node_modules/@stdlib/random/base/randu/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/random/base/randu/benchmark/c/benchmark.c
index 6ad496fa3696..c5e6f11bf4af 100644
--- a/lib/node_modules/@stdlib/random/base/randu/benchmark/c/benchmark.c
+++ b/lib/node_modules/@stdlib/random/base/randu/benchmark/c/benchmark.c
@@ -17,7 +17,7 @@
 */
 
 #include "stdlib/random/base/randu.h"
-#include "stdlib/random/base.h"
+#include "stdlib/random/base/shared.h"
 #include <stdlib.h>
 #include <stdio.h>
 #include <stdint.h>
diff --git a/lib/node_modules/@stdlib/random/base/randu/examples/c/example.c b/lib/node_modules/@stdlib/random/base/randu/examples/c/example.c
index e8aae23828e1..7c4f178fb790 100644
--- a/lib/node_modules/@stdlib/random/base/randu/examples/c/example.c
+++ b/lib/node_modules/@stdlib/random/base/randu/examples/c/example.c
@@ -16,10 +16,10 @@
 * limitations under the License.
 */
 
+#include "stdlib/random/base/shared.h"
+#include "stdlib/random/base/randu.h"
 #include <stdlib.h>
 #include <stdio.h>
-#include "stdlib/random/base.h"
-#include "stdlib/random/base/randu.h"
 
 int main( void ) {
 	int32_t i;
diff --git a/lib/node_modules/@stdlib/random/base/randu/include/stdlib/random/base/randu.h b/lib/node_modules/@stdlib/random/base/randu/include/stdlib/random/base/randu.h
index 3b4670f0263a..56c451003553 100644
--- a/lib/node_modules/@stdlib/random/base/randu/include/stdlib/random/base/randu.h
+++ b/lib/node_modules/@stdlib/random/base/randu/include/stdlib/random/base/randu.h
@@ -19,9 +19,8 @@
 #ifndef STDLIB_RANDOM_BASE_RANDU_H
 #define STDLIB_RANDOM_BASE_RANDU_H
 
-// Note: keep project includes in alphabetical order...
+#include "stdlib/random/base/shared.h"
 #include <stdarg.h>
-#include "stdlib/random/base.h"
 
 /*
 * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler.
diff --git a/lib/node_modules/@stdlib/random/base/randu/src/main.c b/lib/node_modules/@stdlib/random/base/randu/src/main.c
index 4609e45c1ec5..379fb33308a7 100644
--- a/lib/node_modules/@stdlib/random/base/randu/src/main.c
+++ b/lib/node_modules/@stdlib/random/base/randu/src/main.c
@@ -16,15 +16,14 @@
 * limitations under the License.
 */
 
-// Note: keep project includes in alphabetical order...
-#include <stdlib.h>
-#include <stdint.h>
-#include <stdarg.h>
-#include "stdlib/random/base.h"
+#include "stdlib/random/base/randu.h"
+#include "stdlib/random/base/shared.h"
 #include "stdlib/random/base/minstd.h"
 #include "stdlib/random/base/minstd_shuffle.h"
 #include "stdlib/random/base/mt19937.h"
-#include "stdlib/random/base/randu.h"
+#include <stdlib.h>
+#include <stdint.h>
+#include <stdarg.h>
 
 // Define the default PRNG:
 static const enum STDLIB_BASE_RANDOM_RANDU_PRNG STDLIB_BASE_RANDOM_RANDU_DEFAULT = STDLIB_BASE_RANDOM_RANDU_MT19937;
@@ -43,11 +42,11 @@ static const enum STDLIB_BASE_RANDOM_RANDU_PRNG STDLIB_BASE_RANDOM_RANDU_DEFAULT
 * @return        pointer to a dynamically allocated PRNG or, if unable to allocate memory, a null pointer
 *
 * @example
+* #include "stdlib/random/base/randu.h"
+* #include "stdlib/random/base/shared.h"
 * #include <stdlib.h>
 * #include <stdio.h>
 * #include <stdint.h>
-* #include "stdlib/random/base.h"
-* #include "stdlib/random/base/randu.h"
 *
 * // Create a PRNG:
 * struct BasePRNGObject *obj = stdlib_base_random_randu_allocate( 0 );
@@ -73,11 +72,9 @@ static const enum STDLIB_BASE_RANDOM_RANDU_PRNG STDLIB_BASE_RANDOM_RANDU_DEFAULT
 */
 struct BasePRNGObject * stdlib_base_random_randu_allocate( const int nargs, ... ) {
 	enum STDLIB_BASE_RANDOM_RANDU_PRNG prng;
-	struct BasePRNGObject *obj;
-
 	va_list args;
-	va_start( args, nargs );
 
+	va_start( args, nargs );
 	if ( nargs < 1 ) {
 		prng = STDLIB_BASE_RANDOM_RANDU_DEFAULT;
 	} else {
@@ -90,20 +87,25 @@ struct BasePRNGObject * stdlib_base_random_randu_allocate( const int nargs, ...
 		} else {
 			seed = rand();
 		}
-		obj = stdlib_base_random_minstd_allocate( seed );
-	} else if ( prng == STDLIB_BASE_RANDOM_RANDU_MINSTD_SHUFFLE ) {
+		va_end( args );
+		return stdlib_base_random_minstd_allocate( seed );
+	}
+	if ( prng == STDLIB_BASE_RANDOM_RANDU_MINSTD_SHUFFLE ) {
 		int32_t seed;
 		if ( nargs > 1 ) {
 			seed = va_arg( args, int32_t );
 		} else {
 			seed = rand();
 		}
-		obj = stdlib_base_random_minstd_shuffle_allocate( seed );
-	} else if ( prng == STDLIB_BASE_RANDOM_RANDU_MT19937 ) {
+		va_end( args );
+		return stdlib_base_random_minstd_shuffle_allocate( seed );
+	}
+	if ( prng == STDLIB_BASE_RANDOM_RANDU_MT19937 ) {
+		const uint32_t *seed;
 		int64_t seed_length;
-		uint32_t *seed;
+		uint32_t tseed[ 1 ];
 		if ( nargs < 2 ) {
-			uint32_t tseed[] = { (uint32_t)rand() };
+			tseed[ 0 ] = (uint32_t)rand();
 			seed = tseed;
 			seed_length = 1;
 		} else if ( nargs == 3 ) {
@@ -114,13 +116,12 @@ struct BasePRNGObject * stdlib_base_random_randu_allocate( const int nargs, ...
 			va_end( args );
 			return NULL;
 		}
-		obj = stdlib_base_random_mt19937_allocate( seed, seed_length );
-	} else {
-		// How did we get here? A non-implemented PRNG?
-		obj = NULL;
+		va_end( args );
+		return stdlib_base_random_mt19937_allocate( seed, seed_length );
 	}
+	// How did we get here? A non-implemented PRNG?
 	va_end( args );
-	return obj;
+	return NULL;
 }
 
 /**
@@ -134,11 +135,11 @@ struct BasePRNGObject * stdlib_base_random_randu_allocate( const int nargs, ...
 * @return     pseudorandom number
 *
 * @example
+* #include "stdlib/random/base/randu.h"
+* #include "stdlib/random/base/shared.h"
 * #include <stdlib.h>
 * #include <stdio.h>
 * #include <stdint.h>
-* #include "stdlib/random/base.h"
-* #include "stdlib/random/base/randu.h"
 *
 * // Create a PRNG:
 * struct BasePRNGObject *obj = stdlib_base_random_randu_allocate( 0 );
@@ -172,11 +173,11 @@ double stdlib_base_random_randu( struct BasePRNGObject *obj ) {
 * @param obj  PRNG object
 *
 * @example
+* #include "stdlib/random/base/randu.h"
+* #include "stdlib/random/base/shared.h"
 * #include <stdlib.h>
 * #include <stdio.h>
 * #include <stdint.h>
-* #include "stdlib/random/base.h"
-* #include "stdlib/random/base/randu.h"
 *
 * // Create a PRNG:
 * struct BasePRNGObject *obj = stdlib_base_random_randu_allocate( 0 );

From 4f7065465f21e5eb9e0b6b123e6d5a0d4bc86a0c Mon Sep 17 00:00:00 2001
From: Athan Reines <kgryte@gmail.com>
Date: Thu, 2 Jan 2025 21:29:03 -0800
Subject: [PATCH 51/87] docs: update note

---
type: pre_commit_static_analysis_report
description: Results of running static analysis checks when committing changes.
report:
  - task: lint_filenames
    status: passed
  - task: lint_editorconfig
    status: passed
  - task: lint_markdown
    status: na
  - task: lint_package_json
    status: na
  - task: lint_repl_help
    status: na
  - task: lint_javascript_src
    status: na
  - task: lint_javascript_cli
    status: na
  - task: lint_javascript_examples
    status: na
  - task: lint_javascript_tests
    status: na
  - task: lint_javascript_benchmarks
    status: na
  - task: lint_python
    status: na
  - task: lint_r
    status: na
  - task: lint_c_src
    status: passed
  - task: lint_c_examples
    status: na
  - task: lint_c_benchmarks
    status: na
  - task: lint_c_tests_fixtures
    status: na
  - task: lint_shell
    status: na
  - task: lint_typescript_declarations
    status: na
  - task: lint_typescript_tests
    status: na
  - task: lint_license_headers
    status: passed
---
---
 lib/node_modules/@stdlib/random/base/randu/src/main.c | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/lib/node_modules/@stdlib/random/base/randu/src/main.c b/lib/node_modules/@stdlib/random/base/randu/src/main.c
index 379fb33308a7..1fa15690f338 100644
--- a/lib/node_modules/@stdlib/random/base/randu/src/main.c
+++ b/lib/node_modules/@stdlib/random/base/randu/src/main.c
@@ -129,7 +129,7 @@ struct BasePRNGObject * stdlib_base_random_randu_allocate( const int nargs, ...
 *
 * ## Notes
 *
-* -   The function returns `NAN` if provided a `NULL` pointer.
+* -   The function returns `NaN` if provided a `NULL` pointer.
 *
 * @param obj  PRNG object
 * @return     pseudorandom number

From 5ae1ada5488007be9d719b9141b46c96989a4142 Mon Sep 17 00:00:00 2001
From: Athan Reines <kgryte@gmail.com>
Date: Thu, 2 Jan 2025 21:29:33 -0800
Subject: [PATCH 52/87] docs: update note

---
type: pre_commit_static_analysis_report
description: Results of running static analysis checks when committing changes.
report:
  - task: lint_filenames
    status: passed
  - task: lint_editorconfig
    status: passed
  - task: lint_markdown
    status: na
  - task: lint_package_json
    status: na
  - task: lint_repl_help
    status: na
  - task: lint_javascript_src
    status: na
  - task: lint_javascript_cli
    status: na
  - task: lint_javascript_examples
    status: na
  - task: lint_javascript_tests
    status: na
  - task: lint_javascript_benchmarks
    status: na
  - task: lint_python
    status: na
  - task: lint_r
    status: na
  - task: lint_c_src
    status: passed
  - task: lint_c_examples
    status: na
  - task: lint_c_benchmarks
    status: na
  - task: lint_c_tests_fixtures
    status: na
  - task: lint_shell
    status: na
  - task: lint_typescript_declarations
    status: na
  - task: lint_typescript_tests
    status: na
  - task: lint_license_headers
    status: passed
---
---
 lib/node_modules/@stdlib/random/base/shared/src/main.c | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/lib/node_modules/@stdlib/random/base/shared/src/main.c b/lib/node_modules/@stdlib/random/base/shared/src/main.c
index 2834549b33ad..fb81eaf24cdb 100644
--- a/lib/node_modules/@stdlib/random/base/shared/src/main.c
+++ b/lib/node_modules/@stdlib/random/base/shared/src/main.c
@@ -57,7 +57,7 @@ uint64_t stdlib_base_prng_next( struct BasePRNGObject *obj ) {
 *
 * ## Notes
 *
-* -   The function returns `NAN` if provided a `NULL` pointer.
+* -   The function returns `NaN` if provided a `NULL` pointer.
 *
 * @param obj  PRNG object
 * @return     pseudorandom number

From 1df3d7c116158c0ab2cfcee7232853faf1390f8d Mon Sep 17 00:00:00 2001
From: Athan Reines <kgryte@gmail.com>
Date: Thu, 2 Jan 2025 21:29:56 -0800
Subject: [PATCH 53/87] fix: update include paths and reorder includes

---
type: pre_commit_static_analysis_report
description: Results of running static analysis checks when committing changes.
report:
  - task: lint_filenames
    status: passed
  - task: lint_editorconfig
    status: passed
  - task: lint_markdown
    status: na
  - task: lint_package_json
    status: na
  - task: lint_repl_help
    status: na
  - task: lint_javascript_src
    status: na
  - task: lint_javascript_cli
    status: na
  - task: lint_javascript_examples
    status: na
  - task: lint_javascript_tests
    status: na
  - task: lint_javascript_benchmarks
    status: na
  - task: lint_python
    status: na
  - task: lint_r
    status: na
  - task: lint_c_src
    status: passed
  - task: lint_c_examples
    status: passed
  - task: lint_c_benchmarks
    status: passed
  - task: lint_c_tests_fixtures
    status: na
  - task: lint_shell
    status: na
  - task: lint_typescript_declarations
    status: na
  - task: lint_typescript_tests
    status: na
  - task: lint_license_headers
    status: passed
---
---
 .../random/base/uniform/benchmark/c/benchmark.c  |  6 +++---
 .../random/base/uniform/examples/c/example.c     |  6 +++---
 .../uniform/include/stdlib/random/base/uniform.h |  4 +---
 .../@stdlib/random/base/uniform/src/main.c       | 16 +++++++---------
 4 files changed, 14 insertions(+), 18 deletions(-)

diff --git a/lib/node_modules/@stdlib/random/base/uniform/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/random/base/uniform/benchmark/c/benchmark.c
index b3299dbb67a0..608941cf9cee 100644
--- a/lib/node_modules/@stdlib/random/base/uniform/benchmark/c/benchmark.c
+++ b/lib/node_modules/@stdlib/random/base/uniform/benchmark/c/benchmark.c
@@ -16,15 +16,15 @@
 * limitations under the License.
 */
 
+#include "stdlib/random/base/uniform.h"
+#include "stdlib/random/base/randu.h"
+#include "stdlib/random/base/shared.h"
 #include <stdlib.h>
 #include <stdio.h>
 #include <stdint.h>
 #include <math.h>
 #include <time.h>
 #include <sys/time.h>
-#include "stdlib/random/base.h"
-#include "stdlib/random/base/randu.h"
-#include "stdlib/random/base/uniform.h"
 
 #define NAME "base/uniform"
 #define ITERATIONS 1000000
diff --git a/lib/node_modules/@stdlib/random/base/uniform/examples/c/example.c b/lib/node_modules/@stdlib/random/base/uniform/examples/c/example.c
index 7e1a92256f85..05d304230d55 100644
--- a/lib/node_modules/@stdlib/random/base/uniform/examples/c/example.c
+++ b/lib/node_modules/@stdlib/random/base/uniform/examples/c/example.c
@@ -16,11 +16,11 @@
 * limitations under the License.
 */
 
+#include "stdlib/random/base/uniform.h"
+#include "stdlib/random/base/randu.h"
+#include "stdlib/random/base/shared.h"
 #include <stdlib.h>
 #include <stdio.h>
-#include "stdlib/random/base.h"
-#include "stdlib/random/base/randu.h"
-#include "stdlib/random/base/uniform.h"
 
 int main( void ) {
 	int32_t i;
diff --git a/lib/node_modules/@stdlib/random/base/uniform/include/stdlib/random/base/uniform.h b/lib/node_modules/@stdlib/random/base/uniform/include/stdlib/random/base/uniform.h
index 3b2ea5551765..ef6711c26d2c 100644
--- a/lib/node_modules/@stdlib/random/base/uniform/include/stdlib/random/base/uniform.h
+++ b/lib/node_modules/@stdlib/random/base/uniform/include/stdlib/random/base/uniform.h
@@ -19,9 +19,7 @@
 #ifndef STDLIB_RANDOM_BASE_UNIFORM_H
 #define STDLIB_RANDOM_BASE_UNIFORM_H
 
-// Note: keep project includes in alphabetical order...
-#include <stdarg.h>
-#include "stdlib/random/base.h"
+#include "stdlib/random/base/shared.h"
 
 /*
 * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler.
diff --git a/lib/node_modules/@stdlib/random/base/uniform/src/main.c b/lib/node_modules/@stdlib/random/base/uniform/src/main.c
index ad6067c9a29e..5863ac6c95a4 100644
--- a/lib/node_modules/@stdlib/random/base/uniform/src/main.c
+++ b/lib/node_modules/@stdlib/random/base/uniform/src/main.c
@@ -16,18 +16,16 @@
 * limitations under the License.
 */
 
-// Note: keep project includes in alphabetical order...
-#include <stdlib.h>
-#include <math.h>
-#include "stdlib/random/base.h"
 #include "stdlib/random/base/uniform.h"
+#include "stdlib/random/base/shared.h"
+#include <stdlib.h>
 
 /**
 * Returns a pseudorandom number drawn from a continuous uniform distribution with parameters `a` (minimum support; inclusive) and `b` (maximum support; exclusive).
 *
 * ## Notes
 *
-* -   The function returns `NAN` if provided a `NULL` pointer.
+* -   The function returns `NaN` if provided a `NULL` pointer.
 *
 * @param randu  PRNG object which generates uniformly distributed pseudorandom numbers on the interval `[0,1)`
 * @param a      minimum support (inclusive)
@@ -35,11 +33,11 @@
 * @return       pseudorandom number
 *
 * @example
+* #include "stdlib/random/base/uniform.h"
+* #include "stdlib/random/base/randu.h"
+* #include "stdlib/random/base/shared.h"
 * #include <stdlib.h>
 * #include <stdio.h>
-* #include "stdlib/random/base.h"
-* #include "stdlib/random/base/randu.h"
-* #include "stdlib/random/base/uniform.h"
 *
 * // Create a PRNG:
 * struct BasePRNGObject *randu = stdlib_base_random_randu_allocate( 0 );
@@ -65,7 +63,7 @@
 */
 double stdlib_base_random_uniform( struct BasePRNGObject *randu, const double a, const double b ) {
 	if ( randu == NULL ) {
-		return NAN;
+		return 0.0 / 0.0; // NaN
 	}
 	double r;
 	randu->prng->normalized( randu, &r );

From 43782d3614f08408049f2add6977177094215b52 Mon Sep 17 00:00:00 2001
From: JoyBoy <144602492+0PrashantYadav0@users.noreply.github.com>
Date: Fri, 3 Jan 2025 08:32:29 +0530
Subject: [PATCH 54/87] feat: add C implementation for
 `stats/base/dists/logistic/kurtosis`

PR-URL: https://github.com/stdlib-js/stdlib/pull/4034
Closes: https://github.com/stdlib-js/stdlib/issues/3735

Co-authored-by: stdlib-bot <noreply@stdlib.io>
Reviewed-by: Philipp Burckhardt <pburckhardt@outlook.com>
---
 .../base/dists/logistic/kurtosis/README.md    |  91 ++++++++++
 .../logistic/kurtosis/benchmark/benchmark.js  |  14 +-
 .../kurtosis/benchmark/benchmark.native.js    |  71 ++++++++
 .../logistic/kurtosis/benchmark/c/Makefile    | 146 +++++++++++++++
 .../logistic/kurtosis/benchmark/c/benchmark.c | 141 +++++++++++++++
 .../base/dists/logistic/kurtosis/binding.gyp  | 170 ++++++++++++++++++
 .../logistic/kurtosis/examples/c/Makefile     | 146 +++++++++++++++
 .../logistic/kurtosis/examples/c/example.c    |  40 +++++
 .../base/dists/logistic/kurtosis/include.gypi |  53 ++++++
 .../stats/base/dists/logistic/kurtosis.h      |  38 ++++
 .../dists/logistic/kurtosis/lib/native.js     |  63 +++++++
 .../dists/logistic/kurtosis/manifest.json     |  77 ++++++++
 .../base/dists/logistic/kurtosis/package.json |   3 +
 .../base/dists/logistic/kurtosis/src/Makefile |  70 ++++++++
 .../base/dists/logistic/kurtosis/src/addon.c  |  23 +++
 .../base/dists/logistic/kurtosis/src/main.c   |  42 +++++
 .../logistic/kurtosis/test/test.native.js     | 101 +++++++++++
 17 files changed, 1286 insertions(+), 3 deletions(-)
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/benchmark/benchmark.native.js
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/benchmark/c/Makefile
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/benchmark/c/benchmark.c
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/binding.gyp
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/examples/c/Makefile
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/examples/c/example.c
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/include.gypi
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/include/stdlib/stats/base/dists/logistic/kurtosis.h
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/lib/native.js
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/manifest.json
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/src/Makefile
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/src/addon.c
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/src/main.c
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/test/test.native.js

diff --git a/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/README.md b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/README.md
index 1af169055855..4358be27c0bc 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/README.md
+++ b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/README.md
@@ -131,6 +131,97 @@ for ( i = 0; i < 10; i++ ) {
 
 <!-- /.examples -->
 
+<!-- C interface documentation. -->
+
+* * *
+
+<section class="c">
+
+## C APIs
+
+<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<!-- C usage documentation. -->
+
+<section class="usage">
+
+### Usage
+
+```c
+#include "stdlib/stats/base/dists/logistic/kurtosis.h"
+```
+
+#### stdlib_base_dists_logistic_kurtosis( mu, s )
+
+Returns the kurtosis for a logistic distribution with location `mu` and scale `s`.
+
+```c
+double out = stdlib_base_dists_logistic_kurtosis( 0.0, 1.0 );
+// returns 1.2
+```
+
+The function accepts the following arguments:
+
+-   **mu**: `[in] double` location parameter.
+-   **s**: `[in] double` scale parameter.
+
+```c
+double stdlib_base_dists_logistic_kurtosis( const double mu, const double s );
+```
+
+</section>
+
+<!-- /.usage -->
+
+<!-- C API usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="notes">
+
+</section>
+
+<!-- /.notes -->
+
+<!-- C API usage examples. -->
+
+<section class="examples">
+
+### Examples
+
+```c
+#include "stdlib/stats/base/dists/logistic/kurtosis.h"
+#include <stdlib.h>
+#include <stdio.h>
+
+static double random_uniform( const double min, const double max ) {
+    double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
+    return min + ( v * (max - min) );
+}
+
+int main( void ) {
+    double mu;
+    double s;
+    double y;
+    int i;
+
+    for ( i = 0; i < 25; i++ ) {
+        mu = random_uniform( 0.0, 10.0 ) - 5.0;
+        s = random_uniform( 0.0, 20.0 );
+        y = stdlib_base_dists_logistic_kurtosis( mu, s );
+        printf( "µ: %lf, s: %lf, Kurt(X;µ,s): %lf\n", mu, s, y );
+    }
+}
+```
+
+</section>
+
+<!-- /.examples -->
+
 <!-- Section to include cited references. If references are included, add a horizontal rule *before* the section. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
 
 <section class="references">
diff --git a/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/benchmark/benchmark.js
index 3506be1968fb..7f20c60e7411 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/benchmark/benchmark.js
+++ b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/benchmark/benchmark.js
@@ -21,6 +21,7 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
+var Float64Array = require( '@stdlib/array/float64' );
 var randu = require( '@stdlib/random/base/randu' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var EPS = require( '@stdlib/constants/float64/eps' );
@@ -31,16 +32,23 @@ var kurtosis = require( './../lib' );
 // MAIN //
 
 bench( pkg, function benchmark( b ) {
+	var len;
 	var mu;
 	var s;
 	var y;
 	var i;
 
+	len = 100;
+	mu = new Float64Array( len );
+	s = new Float64Array( len );
+	for ( i = 0; i < len; i++ ) {
+		mu[ i ] = ( randu() * 100.0 ) - 50.0;
+		s[ i ] = ( randu() * 20.0 ) + EPS;
+	}
+
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		mu = ( randu()*100.0 ) - 50.0;
-		s = ( randu()*20.0 ) + EPS;
-		y = kurtosis( mu, s );
+		y = kurtosis( mu[ i % len ], s[ i % len ] );
 		if ( isnan( y ) ) {
 			b.fail( 'should not return NaN' );
 		}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/benchmark/benchmark.native.js
new file mode 100644
index 000000000000..c3dc60ddecf5
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/benchmark/benchmark.native.js
@@ -0,0 +1,71 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var resolve = require( 'path' ).resolve;
+var bench = require( '@stdlib/bench' );
+var Float64Array = require( '@stdlib/array/float64' );
+var tryRequire = require( '@stdlib/utils/try-require' );
+var randu = require( '@stdlib/random/base/randu' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var EPS = require( '@stdlib/constants/float64/eps' );
+var pkg = require( './../package.json' ).name;
+
+
+// VARIABLES //
+
+var kurtosis = tryRequire( resolve( __dirname, './../lib/native.js' ) );
+var opts = {
+	'skip': ( kurtosis instanceof Error )
+};
+
+
+// MAIN //
+
+bench( pkg+'::native', opts, function benchmark( b ) {
+	var len;
+	var mu;
+	var s;
+	var y;
+	var i;
+
+	len = 100;
+	mu = new Float64Array( len );
+	s = new Float64Array( len );
+	for ( i = 0; i < len; i++ ) {
+		mu[ i ] = ( randu() * 100.0 ) - 50.0;
+		s[ i ] = ( randu() * 20.0 ) + EPS;
+	}
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		y = kurtosis( mu[ i % len ], s[ i % len ] );
+		if ( isnan( y ) ) {
+			b.fail( 'should not return NaN' );
+		}
+	}
+	b.toc();
+	if ( isnan( y ) ) {
+		b.fail( 'should not return NaN' );
+	}
+	b.pass( 'benchmark finished' );
+	b.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/benchmark/c/Makefile
new file mode 100644
index 000000000000..a4bd7b38fd74
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/benchmark/c/Makefile
@@ -0,0 +1,146 @@
+#/
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#/
+
+# VARIABLES #
+
+ifndef VERBOSE
+	QUIET := @
+else
+	QUIET :=
+endif
+
+# Determine the OS ([1][1], [2][2]).
+#
+# [1]: https://en.wikipedia.org/wiki/Uname#Examples
+# [2]: http://stackoverflow.com/a/27776822/2225624
+OS ?= $(shell uname)
+ifneq (, $(findstring MINGW,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring MSYS,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring CYGWIN,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring Windows_NT,$(OS)))
+	OS := WINNT
+endif
+endif
+endif
+endif
+
+# Define the program used for compiling C source files:
+ifdef C_COMPILER
+	CC := $(C_COMPILER)
+else
+	CC := gcc
+endif
+
+# Define the command-line options when compiling C files:
+CFLAGS ?= \
+	-std=c99 \
+	-O3 \
+	-Wall \
+	-pedantic
+
+# Determine whether to generate position independent code ([1][1], [2][2]).
+#
+# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options
+# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option
+ifeq ($(OS), WINNT)
+	fPIC ?=
+else
+	fPIC ?= -fPIC
+endif
+
+# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`):
+INCLUDE ?=
+
+# List of source files:
+SOURCE_FILES ?=
+
+# List of libraries (e.g., `-lopenblas -lpthread`):
+LIBRARIES ?=
+
+# List of library paths (e.g., `-L /foo/bar -L /beep/boop`):
+LIBPATH ?=
+
+# List of C targets:
+c_targets := benchmark.out
+
+
+# RULES #
+
+#/
+# Compiles source files.
+#
+# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`)
+# @param {string} [CFLAGS] - C compiler options
+# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`)
+# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`)
+# @param {string} [SOURCE_FILES] - list of source files
+# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`)
+# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`)
+#
+# @example
+# make
+#
+# @example
+# make all
+#/
+all: $(c_targets)
+
+.PHONY: all
+
+#/
+# Compiles C source files.
+#
+# @private
+# @param {string} CC - C compiler (e.g., `gcc`)
+# @param {string} CFLAGS - C compiler options
+# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`)
+# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`)
+# @param {string} SOURCE_FILES - list of source files
+# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`)
+# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`)
+#/
+$(c_targets): %.out: %.c
+	$(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES)
+
+#/
+# Runs compiled benchmarks.
+#
+# @example
+# make run
+#/
+run: $(c_targets)
+	$(QUIET) ./$<
+
+.PHONY: run
+
+#/
+# Removes generated files.
+#
+# @example
+# make clean
+#/
+clean:
+	$(QUIET) -rm -f *.o *.out
+
+.PHONY: clean
diff --git a/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/benchmark/c/benchmark.c
new file mode 100644
index 000000000000..9d9f15860ef5
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/benchmark/c/benchmark.c
@@ -0,0 +1,141 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/dists/logistic/kurtosis.h"
+#include "stdlib/constants/float64/eps.h"
+#include <stdlib.h>
+#include <stdio.h>
+#include <math.h>
+#include <time.h>
+#include <sys/time.h>
+
+#define NAME "logistic-kurtosis"
+#define ITERATIONS 1000000
+#define REPEATS 3
+
+/**
+* Prints the TAP version.
+*/
+static void print_version( void ) {
+	printf( "TAP version 13\n" );
+}
+
+/**
+* Prints the TAP summary.
+*
+* @param total     total number of tests
+* @param passing   total number of passing tests
+*/
+static void print_summary( int total, int passing ) {
+	printf( "#\n" );
+	printf( "1..%d\n", total ); // TAP plan
+	printf( "# total %d\n", total );
+	printf( "# pass  %d\n", passing );
+	printf( "#\n" );
+	printf( "# ok\n" );
+}
+
+/**
+* Prints benchmarks results.
+*
+* @param elapsed   elapsed time in seconds
+*/
+static void print_results( double elapsed ) {
+	double rate = (double)ITERATIONS / elapsed;
+	printf( "  ---\n" );
+	printf( "  iterations: %d\n", ITERATIONS );
+	printf( "  elapsed: %0.9f\n", elapsed );
+	printf( "  rate: %0.9f\n", rate );
+	printf( "  ...\n" );
+}
+
+/**
+* Returns a clock time.
+*
+* @return clock time
+*/
+static double tic( void ) {
+	struct timeval now;
+	gettimeofday( &now, NULL );
+	return (double)now.tv_sec + (double)now.tv_usec/1.0e6;
+}
+
+/**
+* Generates a random number on the interval [min,max).
+*
+* @param min    minimum value (inclusive)
+* @param max    maximum value (exclusive)
+* @return       random number
+*/
+static double random_uniform( const double min, const double max ) {
+	double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
+	return min + ( v*(max-min) );
+}
+
+/**
+* Runs a benchmark.
+*
+* @return elapsed time in seconds
+*/
+static double benchmark( void ) {
+	double elapsed;
+	double mu[ 100 ];
+	double s[ 100 ];
+	double y;
+	double t;
+	int i;
+
+	for ( i = 0; i < 100; i++ ) {
+		mu[ i ] = random_uniform( 0.0, 100.0 ) - 50.0;
+		s[ i ] = random_uniform( 0.0, 20.0 ) + STDLIB_CONSTANT_FLOAT64_EPS;
+	}
+
+	t = tic();
+	for ( i = 0; i < ITERATIONS; i++ ) {
+		y = stdlib_base_dists_logistic_kurtosis( mu[ i % 100 ], s[ i % 100 ] );
+		if ( y != y ) {
+			printf( "should not return NaN\n" );
+			break;
+		}
+	}
+	elapsed = tic() - t;
+	if ( y != y ) {
+		printf( "should not return NaN\n" );
+	}
+	return elapsed;
+}
+
+/**
+* Main execution sequence.
+*/
+int main( void ) {
+	double elapsed;
+	int i;
+
+	// Use the current time to seed the random number generator:
+	srand( time( NULL ) );
+
+	print_version();
+	for ( i = 0; i < REPEATS; i++ ) {
+		printf( "# c::%s\n", NAME );
+		elapsed = benchmark();
+		print_results( elapsed );
+		printf( "ok %d benchmark finished\n", i+1 );
+	}
+	print_summary( REPEATS, REPEATS );
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/binding.gyp
new file mode 100644
index 000000000000..68a1ca11d160
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/binding.gyp
@@ -0,0 +1,170 @@
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# A `.gyp` file for building a Node.js native add-on.
+#
+# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md
+# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md
+{
+  # List of files to include in this file:
+  'includes': [
+    './include.gypi',
+  ],
+
+  # Define variables to be used throughout the configuration for all targets:
+  'variables': {
+    # Target name should match the add-on export name:
+    'addon_target_name%': 'addon',
+
+    # Set variables based on the host OS:
+    'conditions': [
+      [
+        'OS=="win"',
+        {
+          # Define the object file suffix:
+          'obj': 'obj',
+        },
+        {
+          # Define the object file suffix:
+          'obj': 'o',
+        }
+      ], # end condition (OS=="win")
+    ], # end conditions
+  }, # end variables
+
+  # Define compile targets:
+  'targets': [
+
+    # Target to generate an add-on:
+    {
+      # The target name should match the add-on export name:
+      'target_name': '<(addon_target_name)',
+
+      # Define dependencies:
+      'dependencies': [],
+
+      # Define directories which contain relevant include headers:
+      'include_dirs': [
+        # Local include directory:
+        '<@(include_dirs)',
+      ],
+
+      # List of source files:
+      'sources': [
+        '<@(src_files)',
+      ],
+
+      # Settings which should be applied when a target's object files are used as linker input:
+      'link_settings': {
+        # Define libraries:
+        'libraries': [
+          '<@(libraries)',
+        ],
+
+        # Define library directories:
+        'library_dirs': [
+          '<@(library_dirs)',
+        ],
+      },
+
+      # C/C++ compiler flags:
+      'cflags': [
+        # Enable commonly used warning options:
+        '-Wall',
+
+        # Aggressive optimization:
+        '-O3',
+      ],
+
+      # C specific compiler flags:
+      'cflags_c': [
+        # Specify the C standard to which a program is expected to conform:
+        '-std=c99',
+      ],
+
+      # C++ specific compiler flags:
+      'cflags_cpp': [
+        # Specify the C++ standard to which a program is expected to conform:
+        '-std=c++11',
+      ],
+
+      # Linker flags:
+      'ldflags': [],
+
+      # Apply conditions based on the host OS:
+      'conditions': [
+        [
+          'OS=="mac"',
+          {
+            # Linker flags:
+            'ldflags': [
+              '-undefined dynamic_lookup',
+              '-Wl,-no-pie',
+              '-Wl,-search_paths_first',
+            ],
+          },
+        ], # end condition (OS=="mac")
+        [
+          'OS!="win"',
+          {
+            # C/C++ flags:
+            'cflags': [
+              # Generate platform-independent code:
+              '-fPIC',
+            ],
+          },
+        ], # end condition (OS!="win")
+      ], # end conditions
+    }, # end target <(addon_target_name)
+
+    # Target to copy a generated add-on to a standard location:
+    {
+      'target_name': 'copy_addon',
+
+      # Declare that the output of this target is not linked:
+      'type': 'none',
+
+      # Define dependencies:
+      'dependencies': [
+        # Require that the add-on be generated before building this target:
+        '<(addon_target_name)',
+      ],
+
+      # Define a list of actions:
+      'actions': [
+        {
+          'action_name': 'copy_addon',
+          'message': 'Copying addon...',
+
+          # Explicitly list the inputs in the command-line invocation below:
+          'inputs': [],
+
+          # Declare the expected outputs:
+          'outputs': [
+            '<(addon_output_dir)/<(addon_target_name).node',
+          ],
+
+          # Define the command-line invocation:
+          'action': [
+            'cp',
+            '<(PRODUCT_DIR)/<(addon_target_name).node',
+            '<(addon_output_dir)/<(addon_target_name).node',
+          ],
+        },
+      ], # end actions
+    }, # end target copy_addon
+  ], # end targets
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/examples/c/Makefile
new file mode 100644
index 000000000000..25ced822f96a
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/examples/c/Makefile
@@ -0,0 +1,146 @@
+#/
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#/
+
+# VARIABLES #
+
+ifndef VERBOSE
+	QUIET := @
+else
+	QUIET :=
+endif
+
+# Determine the OS ([1][1], [2][2]).
+#
+# [1]: https://en.wikipedia.org/wiki/Uname#Examples
+# [2]: http://stackoverflow.com/a/27776822/2225624
+OS ?= $(shell uname)
+ifneq (, $(findstring MINGW,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring MSYS,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring CYGWIN,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring Windows_NT,$(OS)))
+	OS := WINNT
+endif
+endif
+endif
+endif
+
+# Define the program used for compiling C source files:
+ifdef C_COMPILER
+	CC := $(C_COMPILER)
+else
+	CC := gcc
+endif
+
+# Define the command-line options when compiling C files:
+CFLAGS ?= \
+	-std=c99 \
+	-O3 \
+	-Wall \
+	-pedantic
+
+# Determine whether to generate position independent code ([1][1], [2][2]).
+#
+# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options
+# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option
+ifeq ($(OS), WINNT)
+	fPIC ?=
+else
+	fPIC ?= -fPIC
+endif
+
+# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`):
+INCLUDE ?=
+
+# List of source files:
+SOURCE_FILES ?=
+
+# List of libraries (e.g., `-lopenblas -lpthread`):
+LIBRARIES ?=
+
+# List of library paths (e.g., `-L /foo/bar -L /beep/boop`):
+LIBPATH ?=
+
+# List of C targets:
+c_targets := example.out
+
+
+# RULES #
+
+#/
+# Compiles source files.
+#
+# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`)
+# @param {string} [CFLAGS] - C compiler options
+# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`)
+# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`)
+# @param {string} [SOURCE_FILES] - list of source files
+# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`)
+# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`)
+#
+# @example
+# make
+#
+# @example
+# make all
+#/
+all: $(c_targets)
+
+.PHONY: all
+
+#/
+# Compiles C source files.
+#
+# @private
+# @param {string} CC - C compiler (e.g., `gcc`)
+# @param {string} CFLAGS - C compiler options
+# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`)
+# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`)
+# @param {string} SOURCE_FILES - list of source files
+# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`)
+# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`)
+#/
+$(c_targets): %.out: %.c
+	$(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES)
+
+#/
+# Runs compiled examples.
+#
+# @example
+# make run
+#/
+run: $(c_targets)
+	$(QUIET) ./$<
+
+.PHONY: run
+
+#/
+# Removes generated files.
+#
+# @example
+# make clean
+#/
+clean:
+	$(QUIET) -rm -f *.o *.out
+
+.PHONY: clean
diff --git a/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/examples/c/example.c
new file mode 100644
index 000000000000..9c3934910883
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/examples/c/example.c
@@ -0,0 +1,40 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/dists/logistic/kurtosis.h"
+#include <stdlib.h>
+#include <stdio.h>
+
+static double random_uniform( const double min, const double max ) {
+	double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
+	return min + ( v * (max - min) );
+}
+
+int main( void ) {
+	double mu;
+	double s;
+	double y;
+	int i;
+
+	for ( i = 0; i < 25; i++ ) {
+		mu = random_uniform( 0.0, 10.0 ) - 5.0;
+		s = random_uniform( 0.0, 20.0 );
+		y = stdlib_base_dists_logistic_kurtosis( mu, s );
+		printf( "µ: %lf, s: %lf, Kurt(X;µ,s): %lf\n", mu, s, y );
+	}
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/include.gypi
new file mode 100644
index 000000000000..ecfaf82a3279
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/include.gypi
@@ -0,0 +1,53 @@
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# A GYP include file for building a Node.js native add-on.
+#
+# Main documentation:
+#
+# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md
+# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md
+{
+  # Define variables to be used throughout the configuration for all targets:
+  'variables': {
+    # Source directory:
+    'src_dir': './src',
+
+    # Include directories:
+    'include_dirs': [
+      '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).include; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
+    ],
+
+    # Add-on destination directory:
+    'addon_output_dir': './src',
+
+    # Source files:
+    'src_files': [
+      '<(src_dir)/addon.c',
+      '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).src; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
+    ],
+
+    # Library dependencies:
+    'libraries': [
+      '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).libraries; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
+    ],
+
+    # Library directories:
+    'library_dirs': [
+      '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).libpath; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
+    ],
+  }, # end variables
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/include/stdlib/stats/base/dists/logistic/kurtosis.h b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/include/stdlib/stats/base/dists/logistic/kurtosis.h
new file mode 100644
index 000000000000..a7f0ac3b35cf
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/include/stdlib/stats/base/dists/logistic/kurtosis.h
@@ -0,0 +1,38 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#ifndef STDLIB_STATS_BASE_DISTS_LOGISTIC_KURTOSIS_H
+#define STDLIB_STATS_BASE_DISTS_LOGISTIC_KURTOSIS_H
+
+/*
+* If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler.
+*/
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+/**
+* Returns the kurtosis for a logistic distribution with location `mu` and scale `s`.
+*/
+double stdlib_base_dists_logistic_kurtosis( const double mu, const double s );
+
+#ifdef __cplusplus
+}
+#endif
+
+#endif // !STDLIB_STATS_BASE_DISTS_LOGISTIC_KURTOSIS_H
diff --git a/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/lib/native.js b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/lib/native.js
new file mode 100644
index 000000000000..84ae3b7fad1c
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/lib/native.js
@@ -0,0 +1,63 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var addon = require( './../src/addon.node' );
+
+
+// MAIN //
+
+/**
+* Returns the kurtosis for a logistic distribution with location `mu` and scale `s`.
+*
+* @private
+* @param {number} mu - location parameter
+* @param {PositiveNumber} s - scale parameter
+* @returns {number} kurtosis
+*
+* @example
+* var y = kurtosis( 0.0, 1.0 );
+* // returns 1.2
+*
+* @example
+* var y = kurtosis( 5.0, 2.0 );
+* // returns 1.2
+*
+* @example
+* var y = kurtosis( NaN, 1.0 );
+* // returns NaN
+*
+* @example
+* var y = kurtosis( 0.0, NaN );
+* // returns NaN
+*
+* @example
+* var y = kurtosis( 0.0, 0.0 );
+* // returns NaN
+*/
+function kurtosis( mu, s ) {
+	return addon( mu, s );
+}
+
+
+// EXPORTS //
+
+module.exports = kurtosis;
diff --git a/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/manifest.json b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/manifest.json
new file mode 100644
index 000000000000..5b8285e0bed8
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/manifest.json
@@ -0,0 +1,77 @@
+{
+  "options": {
+    "task": "build",
+    "wasm": false
+  },
+  "fields": [
+    {
+      "field": "src",
+      "resolve": true,
+      "relative": true
+    },
+    {
+      "field": "include",
+      "resolve": true,
+      "relative": true
+    },
+    {
+      "field": "libraries",
+      "resolve": false,
+      "relative": false
+    },
+    {
+      "field": "libpath",
+      "resolve": true,
+      "relative": false
+    }
+  ],
+  "confs": [
+    {
+      "task": "build",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/math/base/napi/binary",
+        "@stdlib/math/base/assert/is-nan"
+      ]
+    },
+    {
+      "task": "benchmark",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/math/base/assert/is-nan",
+        "@stdlib/constants/float64/eps"
+      ]
+    },
+    {
+      "task": "examples",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/math/base/assert/is-nan"
+      ]
+    }
+  ]
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/package.json b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/package.json
index a4da5b55ad2a..e0d69a767913 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/package.json
+++ b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/package.json
@@ -14,11 +14,14 @@
     }
   ],
   "main": "./lib",
+  "gypfile": true,
   "directories": {
     "benchmark": "./benchmark",
     "doc": "./docs",
     "example": "./examples",
+    "include": "./include",
     "lib": "./lib",
+    "src": "./src",
     "test": "./test"
   },
   "types": "./docs/types",
diff --git a/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/src/Makefile b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/src/Makefile
new file mode 100644
index 000000000000..7733b6180cb4
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/src/Makefile
@@ -0,0 +1,70 @@
+#/
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#/
+
+# VARIABLES #
+
+ifndef VERBOSE
+	QUIET := @
+else
+	QUIET :=
+endif
+
+# Determine the OS ([1][1], [2][2]).
+#
+# [1]: https://en.wikipedia.org/wiki/Uname#Examples
+# [2]: http://stackoverflow.com/a/27776822/2225624
+OS ?= $(shell uname)
+ifneq (, $(findstring MINGW,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring MSYS,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring CYGWIN,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring Windows_NT,$(OS)))
+	OS := WINNT
+endif
+endif
+endif
+endif
+
+
+# RULES #
+
+#/
+# Removes generated files for building an add-on.
+#
+# @example
+# make clean-addon
+#/
+clean-addon:
+	$(QUIET) -rm -f *.o *.node
+
+.PHONY: clean-addon
+
+#/
+# Removes generated files.
+#
+# @example
+# make clean
+#/
+clean: clean-addon
+
+.PHONY: clean
diff --git a/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/src/addon.c b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/src/addon.c
new file mode 100644
index 000000000000..784d54a1018c
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/src/addon.c
@@ -0,0 +1,23 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/dists/logistic/kurtosis.h"
+#include "stdlib/math/base/napi/binary.h"
+
+// cppcheck-suppress shadowFunction
+STDLIB_MATH_BASE_NAPI_MODULE_DD_D( stdlib_base_dists_logistic_kurtosis )
diff --git a/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/src/main.c
new file mode 100644
index 000000000000..28376b9732b5
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/src/main.c
@@ -0,0 +1,42 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/dists/logistic/kurtosis.h"
+#include "stdlib/math/base/assert/is_nan.h"
+
+/**
+* Returns the kurtosis for a logistic distribution with location `mu` and scale `s`.
+*
+* @param mu    location parameter
+* @param s     scale parameter
+* @return      kurtosis
+*
+* @example
+* double y = stdlib_base_dists_logistic_kurtosis( 0.0, 1.0 );
+* // returns 1.2
+*/
+double stdlib_base_dists_logistic_kurtosis( const double mu, const double s ) {
+	if (
+		stdlib_base_is_nan( mu ) ||
+		stdlib_base_is_nan( s ) ||
+		s <= 0.0
+	) {
+		return 0.0 / 0.0; // NaN
+	}
+	return 1.2;
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/test/test.native.js
new file mode 100644
index 000000000000..7fa6fc9a09b3
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/logistic/kurtosis/test/test.native.js
@@ -0,0 +1,101 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var resolve = require( 'path' ).resolve;
+var tape = require( 'tape' );
+var tryRequire = require( '@stdlib/utils/try-require' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var PINF = require( '@stdlib/constants/float64/pinf' );
+var NINF = require( '@stdlib/constants/float64/ninf' );
+
+
+// VARIABLES //
+
+var kurtosis = tryRequire( resolve( __dirname, './../lib/native.js' ) );
+var opts = {
+	'skip': ( kurtosis instanceof Error )
+};
+
+
+// FIXTURES //
+
+var data = require( './fixtures/julia/data.json' );
+
+
+// TESTS //
+
+tape( 'main export is a function', opts, function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof kurtosis, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'if provided `NaN` for any parameter, the function returns `NaN`', opts, function test( t ) {
+	var y = kurtosis( NaN, 1.0 );
+	t.equal( isnan( y ), true, 'returns NaN' );
+	y = kurtosis( 1.0, NaN );
+	t.equal( isnan( y ), true, 'returns NaN' );
+	t.end();
+});
+
+tape( 'if provided a nonpositive `s`, the function returns `NaN`', opts, function test( t ) {
+	var y;
+
+	y = kurtosis( 2.0, 0.0 );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	y = kurtosis( 2.0, -1.0 );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	y = kurtosis( 1.0, NINF );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	y = kurtosis( PINF, NINF );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	y = kurtosis( NINF, NINF );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	y = kurtosis( NaN, NINF );
+	t.equal( isnan( y ), true, 'returns NaN' );
+
+	t.end();
+});
+
+tape( 'the function returns the kurtosis of a logistic distribution', opts, function test( t ) {
+	var expected;
+	var mu;
+	var s;
+	var y;
+	var i;
+
+	expected = data.expected;
+	mu = data.mu;
+	s = data.s;
+	for ( i = 0; i < mu.length; i++ ) {
+		y = kurtosis( mu[i], s[i] );
+		if ( expected[i] !== null ) {
+			t.equal( y, 1.2, 'mu: ' + mu[i] + ', s: ' + s[i] + ', y: ' + y + ', expected: 1.2' );
+		}
+	}
+	t.end();
+});

From ab5adfb3c45d2eb3abce519034eba9be24eab288 Mon Sep 17 00:00:00 2001
From: stdlib-bot <82920195+stdlib-bot@users.noreply.github.com>
Date: Thu, 2 Jan 2025 19:03:12 -0800
Subject: [PATCH 55/87] docs: update related packages sections

PR-URL: https://github.com/stdlib-js/stdlib/pull/4485

Co-authored-by: Philipp Burckhardt <pburckhardt@outlook.com>
Reviewed-by: Philipp Burckhardt <pburckhardt@outlook.com>
---
 .../@stdlib/array/base/ones/README.md         | 27 +++++++++++++++++++
 .../@stdlib/array/base/zeros3d/README.md      | 27 +++++++++++++++++++
 .../constants/float32/sqrt-half-pi/README.md  |  6 +++--
 .../slice/base/seq2multislice/README.md       | 13 +++++++++
 .../base/reinterpret-complex/README.md        | 15 +++++++++++
 5 files changed, 86 insertions(+), 2 deletions(-)

diff --git a/lib/node_modules/@stdlib/array/base/ones/README.md b/lib/node_modules/@stdlib/array/base/ones/README.md
index 1fd7cb3eea27..be21bf154635 100644
--- a/lib/node_modules/@stdlib/array/base/ones/README.md
+++ b/lib/node_modules/@stdlib/array/base/ones/README.md
@@ -103,6 +103,17 @@ console.log( arr );
 
 <section class="related">
 
+* * *
+
+## See Also
+
+-   <span class="package-name">[`@stdlib/array/base/zeros`][@stdlib/array/base/zeros]</span><span class="delimiter">: </span><span class="description">create a zero-filled generic array.</span>
+-   <span class="package-name">[`@stdlib/array/base/ones2d`][@stdlib/array/base/ones2d]</span><span class="delimiter">: </span><span class="description">create a two-dimensional nested array filled with ones.</span>
+-   <span class="package-name">[`@stdlib/array/base/ones3d`][@stdlib/array/base/ones3d]</span><span class="delimiter">: </span><span class="description">create a three-dimensional nested array filled with ones.</span>
+-   <span class="package-name">[`@stdlib/array/base/ones4d`][@stdlib/array/base/ones4d]</span><span class="delimiter">: </span><span class="description">create a four-dimensional nested array filled with ones.</span>
+-   <span class="package-name">[`@stdlib/array/base/ones5d`][@stdlib/array/base/ones5d]</span><span class="delimiter">: </span><span class="description">create a five-dimensional nested array filled with ones.</span>
+-   <span class="package-name">[`@stdlib/array/base/onesnd`][@stdlib/array/base/onesnd]</span><span class="delimiter">: </span><span class="description">create an n-dimensional nested array filled with ones.</span>
+
 </section>
 
 <!-- /.related -->
@@ -111,6 +122,22 @@ console.log( arr );
 
 <section class="links">
 
+<!-- <related-links> -->
+
+[@stdlib/array/base/zeros]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/zeros
+
+[@stdlib/array/base/ones2d]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/ones2d
+
+[@stdlib/array/base/ones3d]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/ones3d
+
+[@stdlib/array/base/ones4d]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/ones4d
+
+[@stdlib/array/base/ones5d]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/ones5d
+
+[@stdlib/array/base/onesnd]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/onesnd
+
+<!-- </related-links> -->
+
 </section>
 
 <!-- /.links -->
diff --git a/lib/node_modules/@stdlib/array/base/zeros3d/README.md b/lib/node_modules/@stdlib/array/base/zeros3d/README.md
index c82e7c1ac869..b7b30ddee9fd 100644
--- a/lib/node_modules/@stdlib/array/base/zeros3d/README.md
+++ b/lib/node_modules/@stdlib/array/base/zeros3d/README.md
@@ -95,6 +95,17 @@ out = zeros3d( [ 1, 3, 1 ] );
 
 <section class="related">
 
+* * *
+
+## See Also
+
+-   <span class="package-name">[`@stdlib/array/base/zeros`][@stdlib/array/base/zeros]</span><span class="delimiter">: </span><span class="description">create a zero-filled generic array.</span>
+-   <span class="package-name">[`@stdlib/array/base/ones3d`][@stdlib/array/base/ones3d]</span><span class="delimiter">: </span><span class="description">create a three-dimensional nested array filled with ones.</span>
+-   <span class="package-name">[`@stdlib/array/base/zeros2d`][@stdlib/array/base/zeros2d]</span><span class="delimiter">: </span><span class="description">create a zero-filled two-dimensional nested array.</span>
+-   <span class="package-name">[`@stdlib/array/base/zeros4d`][@stdlib/array/base/zeros4d]</span><span class="delimiter">: </span><span class="description">create a zero-filled four-dimensional nested array.</span>
+-   <span class="package-name">[`@stdlib/array/base/zeros5d`][@stdlib/array/base/zeros5d]</span><span class="delimiter">: </span><span class="description">create a zero-filled five-dimensional nested array.</span>
+-   <span class="package-name">[`@stdlib/array/base/zerosnd`][@stdlib/array/base/zerosnd]</span><span class="delimiter">: </span><span class="description">create a zero-filled n-dimensional nested array.</span>
+
 </section>
 
 <!-- /.related -->
@@ -103,6 +114,22 @@ out = zeros3d( [ 1, 3, 1 ] );
 
 <section class="links">
 
+<!-- <related-links> -->
+
+[@stdlib/array/base/zeros]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/zeros
+
+[@stdlib/array/base/ones3d]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/ones3d
+
+[@stdlib/array/base/zeros2d]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/zeros2d
+
+[@stdlib/array/base/zeros4d]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/zeros4d
+
+[@stdlib/array/base/zeros5d]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/zeros5d
+
+[@stdlib/array/base/zerosnd]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/base/zerosnd
+
+<!-- </related-links> -->
+
 </section>
 
 <!-- /.links -->
diff --git a/lib/node_modules/@stdlib/constants/float32/sqrt-half-pi/README.md b/lib/node_modules/@stdlib/constants/float32/sqrt-half-pi/README.md
index 194bd769c40e..3944e0477b58 100644
--- a/lib/node_modules/@stdlib/constants/float32/sqrt-half-pi/README.md
+++ b/lib/node_modules/@stdlib/constants/float32/sqrt-half-pi/README.md
@@ -124,7 +124,7 @@ Macro for the square root of the mathematical constant [π][@stdlib/constants/fl
 
 ## See Also
 
--   <span class="package-name">[`@stdlib/constants/float32/pi`][@stdlib/constants/float32/pi]</span><span class="delimiter">: </span><span class="description">π.</span>
+-   <span class="package-name">[`@stdlib/constants/float64/sqrt-half-pi`][@stdlib/constants/float64/sqrt-half-pi]</span><span class="delimiter">: </span><span class="description">square root of 0.5π.</span>
 
 </section>
 
@@ -134,9 +134,11 @@ Macro for the square root of the mathematical constant [π][@stdlib/constants/fl
 
 <section class="links">
 
+[@stdlib/constants/float32/pi]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/constants/float32/pi
+
 <!-- <related-links> -->
 
-[@stdlib/constants/float32/pi]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/constants/float32/pi
+[@stdlib/constants/float64/sqrt-half-pi]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/constants/float64/sqrt-half-pi
 
 <!-- </related-links> -->
 
diff --git a/lib/node_modules/@stdlib/slice/base/seq2multislice/README.md b/lib/node_modules/@stdlib/slice/base/seq2multislice/README.md
index 484deaea2cb1..dd2ec965934b 100644
--- a/lib/node_modules/@stdlib/slice/base/seq2multislice/README.md
+++ b/lib/node_modules/@stdlib/slice/base/seq2multislice/README.md
@@ -174,6 +174,13 @@ s = seq2multislice( 'foo,bar', [ 10, 10 ], false );
 
 <section class="related">
 
+* * *
+
+## See Also
+
+-   <span class="package-name">[`@stdlib/slice/base/seq2slice`][@stdlib/slice/base/seq2slice]</span><span class="delimiter">: </span><span class="description">convert a subsequence string to a Slice object.</span>
+-   <span class="package-name">[`@stdlib/slice/base/sargs2multislice`][@stdlib/slice/base/sargs2multislice]</span><span class="delimiter">: </span><span class="description">create a MultiSlice object from a comma-separated list of string-serialized MultiSlice constructor arguments.</span>
+
 </section>
 
 <!-- /.related -->
@@ -186,6 +193,12 @@ s = seq2multislice( 'foo,bar', [ 10, 10 ], false );
 
 [@stdlib/slice/base/seq2slice]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/slice/base/seq2slice
 
+<!-- <related-links> -->
+
+[@stdlib/slice/base/sargs2multislice]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/slice/base/sargs2multislice
+
+<!-- </related-links> -->
+
 </section>
 
 <!-- /.links -->
diff --git a/lib/node_modules/@stdlib/strided/base/reinterpret-complex/README.md b/lib/node_modules/@stdlib/strided/base/reinterpret-complex/README.md
index 985f78ff384b..c3342e35c689 100644
--- a/lib/node_modules/@stdlib/strided/base/reinterpret-complex/README.md
+++ b/lib/node_modules/@stdlib/strided/base/reinterpret-complex/README.md
@@ -144,6 +144,13 @@ var im = imag( z );
 
 <section class="related">
 
+* * *
+
+## See Also
+
+-   <span class="package-name">[`@stdlib/strided/base/reinterpret-complex128`][@stdlib/strided/base/reinterpret-complex128]</span><span class="delimiter">: </span><span class="description">reinterpret a Complex128Array as a Float64Array.</span>
+-   <span class="package-name">[`@stdlib/strided/base/reinterpret-complex64`][@stdlib/strided/base/reinterpret-complex64]</span><span class="delimiter">: </span><span class="description">reinterpret a Complex64Array as a Float32Array.</span>
+
 </section>
 
 <!-- /.related -->
@@ -152,6 +159,14 @@ var im = imag( z );
 
 <section class="links">
 
+<!-- <related-links> -->
+
+[@stdlib/strided/base/reinterpret-complex128]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/strided/base/reinterpret-complex128
+
+[@stdlib/strided/base/reinterpret-complex64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/strided/base/reinterpret-complex64
+
+<!-- </related-links> -->
+
 </section>
 
 <!-- /.links -->

From 7b11c9016d785409887fe43722a5a04d524a4e68 Mon Sep 17 00:00:00 2001
From: stdlib-bot <82920195+stdlib-bot@users.noreply.github.com>
Date: Thu, 2 Jan 2025 19:25:46 -0800
Subject: [PATCH 56/87] docs: update REPL namespace documentation

PR-URL: https://github.com/stdlib-js/stdlib/pull/4488

Co-authored-by: Philipp Burckhardt <pburckhardt@outlook.com>
Reviewed-by: Philipp Burckhardt <pburckhardt@outlook.com>
Signed-off-by: stdlib-bot <82920195+stdlib-bot@users.noreply.github.com>
---
 .../@stdlib/repl/code-blocks/data/data.csv    | 64 ++++++++---------
 .../@stdlib/repl/code-blocks/data/data.json   |  2 +-
 .../@stdlib/repl/help/data/data.csv           | 68 +++++++++----------
 .../@stdlib/repl/help/data/data.json          |  2 +-
 .../@stdlib/repl/info/data/data.csv           | 36 +++++-----
 .../@stdlib/repl/info/data/data.json          |  2 +-
 .../@stdlib/repl/signature/data/data.csv      | 36 +++++-----
 .../@stdlib/repl/signature/data/data.json     |  2 +-
 .../repl/typed-signature/data/data.csv        | 36 +++++-----
 .../repl/typed-signature/data/data.json       |  2 +-
 10 files changed, 125 insertions(+), 125 deletions(-)

diff --git a/lib/node_modules/@stdlib/repl/code-blocks/data/data.csv b/lib/node_modules/@stdlib/repl/code-blocks/data/data.csv
index 92c14dd130dd..af85e78a0e0b 100644
--- a/lib/node_modules/@stdlib/repl/code-blocks/data/data.csv
+++ b/lib/node_modules/@stdlib/repl/code-blocks/data/data.csv
@@ -1700,10 +1700,10 @@ base.strided.dcopy,"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nva
 base.strided.dcopy.ndarray,"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n"
 base.strided.dcumax,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumax( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumax( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcumax( 3, x1, 2, y1, 1 )\ny0\n"
 base.strided.dcumax.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n"
-base.strided.dcumaxabs,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumaxabs( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcumaxabs( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.dcumaxabs( N, x1, 2, y1, 1 )\ny0\n"
-base.strided.dcumaxabs.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n"
-base.strided.dcumin,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumin( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcumin( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.dcumin( N, x1, 2, y1, 1 )\ny0\n"
-base.strided.dcumin.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n"
+base.strided.dcumaxabs,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumaxabs( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumaxabs( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcumaxabs( 3, x1, 2, y1, 1 )\ny0\n"
+base.strided.dcumaxabs.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n"
+base.strided.dcumin,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumin( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumin( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcumin( 3, x1, 2, y1, 1 )\ny0\n"
+base.strided.dcumin.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n"
 base.strided.dcuminabs,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcuminabs( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcuminabs( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcuminabs( 3, x1, 2, y1, 1 )\ny0\n"
 base.strided.dcuminabs.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n"
 base.strided.dcusum,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusum( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusum( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusum( 3, 0.0, x1, 2, y1, 1 )\ny0\n"
@@ -1734,10 +1734,10 @@ base.strided.dmax,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided
 base.strided.dmax.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmax.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmax.ndarray( 3, x, 2, 1 )\n"
 base.strided.dmaxabs,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmaxabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmaxabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmaxabs( 3, x1, 2 )\n"
 base.strided.dmaxabs.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmaxabs.ndarray( 3, x, 2, 1 )\n"
-base.strided.dmaxabssorted,"var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.dmaxabssorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmaxabssorted( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmaxabssorted( N, x1, stride )\n"
-base.strided.dmaxabssorted.ndarray,"var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.dmaxabssorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmaxabssorted.ndarray( N, x, 2, 1 )\n"
-base.strided.dmaxsorted,"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmaxsorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmaxsorted( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmaxsorted( N, x1, stride )\n"
-base.strided.dmaxsorted.ndarray,"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmaxsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmaxsorted.ndarray( N, x, 2, 1 )\n"
+base.strided.dmaxabssorted,"var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.dmaxabssorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmaxabssorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmaxabssorted( 3, x1, 2 )\n"
+base.strided.dmaxabssorted.ndarray,"var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.dmaxabssorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.dmaxabssorted.ndarray( 3, x, 2, 1 )\n"
+base.strided.dmaxsorted,"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmaxsorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmaxsorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmaxsorted( 3, x1, 2 )\n"
+base.strided.dmaxsorted.ndarray,"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmaxsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.dmaxsorted.ndarray( 3, x, 2, 1 )\n"
 base.strided.dmean,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmean( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmean( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmean( N, x1, stride )\n"
 base.strided.dmean.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmean.ndarray( N, x, 2, 1 )\n"
 base.strided.dmeankbn,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeankbn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeankbn( N, x1, stride )\n"
@@ -1764,16 +1764,16 @@ base.strided.dmeanvarpn,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar ou
 base.strided.dmeanvarpn.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvarpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanvarpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n"
 base.strided.dmeanwd,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanwd( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanwd( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanwd( N, x1, stride )\n"
 base.strided.dmeanwd.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanwd.ndarray( N, x, 2, 1 )\n"
-base.strided.dmediansorted,"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmediansorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmediansorted( N, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dmediansorted( N, x1, 2 )\n"
-base.strided.dmediansorted.ndarray,"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmediansorted.ndarray( N, x, 2, 1 )\n"
+base.strided.dmediansorted,"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmediansorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmediansorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmediansorted( 3, x1, 2 )\n"
+base.strided.dmediansorted.ndarray,"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.dmediansorted.ndarray( 3, x, 2, 1 )\n"
 base.strided.dmidrange,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmidrange( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmidrange( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmidrange( 3, x1, 2 )\n"
 base.strided.dmidrange.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmidrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmidrange.ndarray( 3, x, 2, 1 )\n"
 base.strided.dmin,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmin( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmin( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmin( N, x1, stride )\n"
 base.strided.dmin.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmin.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmin.ndarray( 3, x, 2, 1 )\n"
 base.strided.dminabs,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dminabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dminabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dminabs( 3, x1, 2 )\n"
 base.strided.dminabs.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dminabs.ndarray( 3, x, 2, 1 )\n"
-base.strided.dminsorted,"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dminsorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dminsorted( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dminsorted( N, x1, stride )\n"
-base.strided.dminsorted.ndarray,"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dminsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dminsorted.ndarray( N, x, 2, 1 )\n"
+base.strided.dminsorted,"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dminsorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dminsorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dminsorted( 3, x1, 2 )\n"
+base.strided.dminsorted.ndarray,"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dminsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.dminsorted.ndarray( 3, x, 2, 1 )\n"
 base.strided.dmskabs,"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskabs( 2, x1, -2, m1, -2, y1, 1 )\ny0\n"
 base.strided.dmskabs.ndarray,"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n"
 base.strided.dmskabs2,"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskabs2( 2, x1, -2, m1, -2, y1, 1 )\ny0\n"
@@ -1792,10 +1792,10 @@ base.strided.dmskmap,"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m
 base.strided.dmskmap.ndarray,"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n"
 base.strided.dmskmap2,"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.add )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.add )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.add )\nz0\n"
 base.strided.dmskmap2.ndarray,"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.add )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.add )\n"
-base.strided.dmskmax,"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmax( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmskmax( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dmskmax( N, x1, 2, mask1, 2 )\n"
-base.strided.dmskmax.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n"
-base.strided.dmskmin,"var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmin( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmskmin( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dmskmin( N, x1, 2, mask1, 2 )\n"
-base.strided.dmskmin.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n"
+base.strided.dmskmax,"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmax( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskmax( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmskmax( 3, x1, 2, mask1, 2 )\n"
+base.strided.dmskmax.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n"
+base.strided.dmskmin,"var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmin( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskmin( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmskmin( 3, x1, 2, mask1, 2 )\n"
+base.strided.dmskmin.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n"
 base.strided.dmskramp,"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskramp( 2, x1, -2, m1, -2, y1, 1 )\ny0\n"
 base.strided.dmskramp.ndarray,"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n"
 base.strided.dmskrange,"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskrange( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskrange( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmskrange( 3, x1, 2, mask1, 2 )\n"
@@ -1972,8 +1972,8 @@ base.strided.dsum,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided
 base.strided.dsum.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsum.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsum.ndarray( 3, x, 2, 1 )\n"
 base.strided.dsumkbn,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumkbn( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumkbn( 3, x1, 2 )\n"
 base.strided.dsumkbn.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsumkbn.ndarray( 3, x, 2, 1 )\n"
-base.strided.dsumkbn2,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsumkbn2( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsumkbn2( N, x1, stride )\n"
-base.strided.dsumkbn2.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsumkbn2.ndarray( N, x, 2, 1 )\n"
+base.strided.dsumkbn2,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumkbn2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumkbn2( 3, x1, 2 )\n"
+base.strided.dsumkbn2.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsumkbn2.ndarray( 3, x, 2, 1 )\n"
 base.strided.dsumors,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumors( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumors( 3, x1, 2 )\n"
 base.strided.dsumors.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsumors.ndarray( 3, x, 2, 1 )\n"
 base.strided.dsumpw,"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumpw( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumpw( 3, x1, 2 )\n"
@@ -2012,8 +2012,8 @@ base.strided.gapx,"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar alpha
 base.strided.gapx.ndarray,"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar alpha = 5.0;\nbase.strided.gapx.ndarray( x.length, alpha, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nalpha = 5.0;\nvar stride = 2;\nbase.strided.gapx.ndarray( N, alpha, x, stride, 1 )\n"
 base.strided.gapxsum,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsum( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gapxsum( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gapxsum( N, 5.0, x1, stride )\n"
 base.strided.gapxsum.ndarray,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gapxsum.ndarray( N, 5.0, x, 2, 1 )\n"
-base.strided.gapxsumkbn,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gapxsumkbn( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gapxsumkbn( N, 5.0, x1, stride )\n"
-base.strided.gapxsumkbn.ndarray,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gapxsumkbn.ndarray( N, 5.0, x, 2, 1 )\n"
+base.strided.gapxsumkbn,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gapxsumkbn( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gapxsumkbn( 3, 5.0, x1, 2 )\n"
+base.strided.gapxsumkbn.ndarray,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n"
 base.strided.gapxsumkbn2,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn2( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gapxsumkbn2( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gapxsumkbn2( N, 5.0, x1, stride )\n"
 base.strided.gapxsumkbn2.ndarray,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gapxsumkbn2.ndarray( N, 5.0, x, 2, 1 )\n"
 base.strided.gapxsumors,"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumors( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gapxsumors( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gapxsumors( N, 5.0, x1, stride )\n"
@@ -2030,8 +2030,8 @@ base.strided.gcopy,"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.
 base.strided.gcopy.ndarray,"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n"
 base.strided.gcusum,"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusum( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusum( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.gcusum( N, 0.0, x1, 2, y1, 1 )\ny0\n"
 base.strided.gcusum.ndarray,"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusum.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n"
-base.strided.gcusumkbn,"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumkbn( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.gcusumkbn( N, 0.0, x1, 2, y1, 1 )\ny0\n"
-base.strided.gcusumkbn.ndarray,"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumkbn.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n"
+base.strided.gcusumkbn,"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcusumkbn( 3, 0.0, x1, 2, y1, 1 )\ny0\n"
+base.strided.gcusumkbn.ndarray,"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n"
 base.strided.gcusumkbn2,"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn2( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumkbn2( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.gcusumkbn2( N, 0.0, x1, 2, y1, 1 )\ny0\n"
 base.strided.gcusumkbn2.ndarray,"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumkbn2.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n"
 base.strided.gcusumors,"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumors( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumors( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.gcusumors( N, 0.0, x1, 2, y1, 1 )\ny0\n"
@@ -2289,10 +2289,10 @@ base.strided.smax,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided
 base.strided.smax.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smax.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smax.ndarray( N, x, 2, 1 )\n"
 base.strided.smaxabs,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smaxabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smaxabs( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smaxabs( 3, x1, 2 )\n"
 base.strided.smaxabs.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smaxabs.ndarray( 3, x, 2, 1 )\n"
-base.strided.smaxabssorted,"var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.smaxabssorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smaxabssorted( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smaxabssorted( N, x1, stride )\n"
-base.strided.smaxabssorted.ndarray,"var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smaxabssorted.ndarray( N, x, 2, 1 )\n"
-base.strided.smaxsorted,"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smaxsorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smaxsorted( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smaxsorted( N, x1, stride )\n"
-base.strided.smaxsorted.ndarray,"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smaxsorted.ndarray( N, x, 2, 1 )\n"
+base.strided.smaxabssorted,"var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.smaxabssorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smaxabssorted( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smaxabssorted( 3, x1, 2 )\n"
+base.strided.smaxabssorted.ndarray,"var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.smaxabssorted.ndarray( 3, x, 2, 1 )\n"
+base.strided.smaxsorted,"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smaxsorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smaxsorted( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smaxsorted( 3, x1, 2 )\n"
+base.strided.smaxsorted.ndarray,"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.smaxsorted.ndarray( 3, x, 2, 1 )\n"
 base.strided.smean,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smean( N, x1, stride )\n"
 base.strided.smean.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smean.ndarray( N, x, 2, 1 )\n"
 base.strided.smeankbn,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeankbn( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeankbn( N, x1, stride )\n"
@@ -2339,14 +2339,14 @@ base.strided.smskmap,"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m
 base.strided.smskmap.ndarray,"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n"
 base.strided.smskmap2,"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.addf )\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.addf )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.addf )\nz0\n"
 base.strided.smskmap2.ndarray,"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.addf )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.addf )\n"
-base.strided.smskmax,"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmax( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smskmax( N, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.smskmax( N, x1, 2, mask1, 2 )\n"
-base.strided.smskmax.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n"
-base.strided.smskmin,"var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmin( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smskmin( N, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.smskmin( N, x1, 2, mask1, 2 )\n"
-base.strided.smskmin.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n"
+base.strided.smskmax,"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmax( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskmax( 3, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.smskmax( 3, x1, 2, mask1, 2 )\n"
+base.strided.smskmax.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n"
+base.strided.smskmin,"var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmin( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskmin( 3, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.smskmin( 3, x1, 2, mask1, 2 )\n"
+base.strided.smskmin.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n"
 base.strided.smskramp,"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskramp( 2, x1, -2, m1, -2, y1, 1 )\ny0\n"
 base.strided.smskramp.ndarray,"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n"
-base.strided.smskrange,"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskrange( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smskrange( N, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.smskrange( N, x1, 2, mask1, 2 )\n"
-base.strided.smskrange.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n"
+base.strided.smskrange,"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskrange( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskrange( 3, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.smskrange( 3, x1, 2, mask1, 2 )\n"
+base.strided.smskrange.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n"
 base.strided.smskrsqrt,"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n"
 base.strided.smskrsqrt.ndarray,"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n"
 base.strided.smsksqrt,"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smsksqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n"
diff --git a/lib/node_modules/@stdlib/repl/code-blocks/data/data.json b/lib/node_modules/@stdlib/repl/code-blocks/data/data.json
index f1917dabbef2..9ecb3be283bf 100644
--- a/lib/node_modules/@stdlib/repl/code-blocks/data/data.json
+++ b/lib/node_modules/@stdlib/repl/code-blocks/data/data.json
@@ -1 +1 @@
-{"abs":"var y = abs( -1.0 )\nvar x = new Float64Array( [ -1.0, -2.0 ] );\ny = abs( x )\nx = [ -1.0, -2.0 ];\ny = abs( x )\nx = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] );\ny = abs( x )\ny.get( 0, 1 )\n","abs.assign":"var x = new Float64Array( [ -1.0, -2.0 ] );\nvar y = new Float64Array( x.length );\nvar out = abs.assign( x, y )\nvar bool = ( out === y )\nx = [ -1.0, -2.0 ];\ny = [ 0.0, 0.0 ];\nout = abs.assign( x, y )\nbool = ( out === y )\nx = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] );\ny = array( [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ] );\nout = abs.assign( x, y )\nout.get( 0, 1 )\nbool = ( out === y )\n","acartesianPower":"var x = [ 1, 2 ];\nvar out = acartesianPower( x, 2 )\n","acartesianProduct":"var x1 = [ 1, 2 ];\nvar x2 = [ 3, 4 ];\nvar out = acartesianProduct( x1, x2 )\n","acartesianSquare":"var out = acartesianSquare( [ 1, 2 ] )\n","acronym":"var out = acronym( 'the quick brown fox' )\nout = acronym( 'Hard-boiled eggs' )\n","aempty":"var arr = aempty( 2 )\narr = aempty( 2, 'float32' )\n","aemptyLike":"var x = new Float64Array( 2 );\nvar arr = aemptyLike( x )\narr = aemptyLike( x, 'float32' )\n","AFINN_96":"var list = AFINN_96()\n","AFINN_111":"var list = AFINN_111()\n","afull":"var arr = afull( 2, 1.0 )\narr = afull( 2, 1.0, 'float32' )\n","afullLike":"var x = new Float64Array( 2 );\nvar y = afullLike( x, 1.0 )\ny = afullLike( x, 1.0, 'float32' )\n","alias2pkg":"var v = alias2pkg( 'base.sin' )\n","alias2related":"var v = alias2related( 'base.sin' )\n","alias2standalone":"var v = alias2standalone( 'base.sin' )\n","aliases":"var o = aliases()\no = aliases( '@stdlib/math/base/special' )\n","allocUnsafe":"var buf = allocUnsafe( 100 )\n","amskfilter":"var x = [ 1, 2, 3, 4 ];\nvar y = amskfilter( x, [ 0, 1, 0, 1 ] )\n","amskput":"var x = [ 1, 2, 3, 4 ];\nvar out = amskput( x, [ 1, 0, 1, 0 ], [ 20, 40 ] )\nvar bool = ( out === x )\n","amskreject":"var x = [ 1, 2, 3, 4 ];\nvar y = amskreject( x, [ 0, 1, 0, 1 ] )\n","anans":"var arr = anans( 2 )\narr = anans( 2, 'float32' )\n","anansLike":"var x = new Float64Array( 2 );\nvar y = anansLike( x )\ny = anansLike( x, 'float32' )\n","anova1":"var x = [1, 3, 5, 2, 4, 6, 8, 7, 10, 11, 12, 15];\nvar f = [\n 'control', 'treatA', 'treatB', 'treatC', 'control',\n 'treatA', 'treatB', 'treatC', 'control', 'treatA', 'treatB', 'treatC'\n ];\nvar out = anova1( x, f )\n","ANSCOMBES_QUARTET":"var d = ANSCOMBES_QUARTET()\n","any":"var arr = [ 0, 0, 0, 0, 1 ];\nvar bool = any( arr )\n","anyBy":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ 1, 2, 3, 4, -1 ];\nvar bool = anyBy( arr, negative )\n","anyByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nanyByAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nanyByAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nanyByAsync( arr, opts, predicate, done )\n","anyByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = anyByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","anyByRight":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ -1, 1, 2, 3, 4 ];\nvar bool = anyByRight( arr, negative )\n","anyByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nanyByRightAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nanyByRightAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nanyByRightAsync( arr, opts, predicate, done )\n","anyByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = anyByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","anyInBy":"function isNegative(value) { return value < 0 }\nvar obj = { a: 1, b: -2, c: 3, d: 4 }\nvar result = anyInBy(obj, isNegative)\n","anyOwnBy":"function positive( v ) { return ( v > 0 ); };\nvar obj = { 'a': -1, 'b': 2, 'c': -3 };\nvar bool = anyOwnBy( obj, positive )\n","aones":"var arr = aones( 2 )\narr = aones( 2, 'float32' )\n","aonesLike":"var x = new Float64Array( 2 );\nvar y = aonesLike( x )\ny = aonesLike( x, 'float32' )\n","aoneTo":"var arr = aoneTo( 2 )\narr = aoneTo( 2, 'float32' )\n","aoneToLike":"var arr = aoneToLike( [ 0, 0 ] )\narr = aoneToLike( [ 0, 0 ], 'float32' )\n","APERY":"APERY\n","aplace":"var x = [ 1, 2, 3, 4 ];\nvar out = aplace( x, [ 0, 1, 0, 1 ], [ 20, 40 ] )\nvar bool = ( out === x )\n","append":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = append( arr, [ 6.0, 7.0 ] )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = append( arr, [ 3.0, 4.0 ] )\narr = { 'length': 0 };\narr = append( arr, [ 1.0, 2.0 ] )\n","aput":"var x = [ 1, 2, 3, 4 ];\nvar out = aput( x, [ 1, 3 ], [ 20, 40 ] )\nvar bool = ( out === x )\n","ARCH":"ARCH\n","argumentFunction":"var argn = argumentFunction( 1 );\nvar v = argn( 3.14, -3.14, 0.0 )\nv = argn( -1.0, -0.0, 1.0 )\nv = argn( 'beep', 'boop', 'bop' )\nv = argn( 'beep' )\n","ARGV":"var execPath = ARGV[ 0 ]\n","array":"var arr = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","array2buffer":"var buf = array2buffer( [ 1, 2, 3, 4 ] )\n","array2fancy":"var y = array2fancy( [ 1, 2, 3, 4 ] );\ny[ '1::2' ]\ny[ '::-1' ]\n","array2fancy.factory":"var f = array2fancy.factory();\nvar y = f( [ 1, 2, 3, 4 ] );\ny[ '1::2' ]\ny[ '::-1' ]\n","array2fancy.idx":"var idx = array2fancy.idx( [ 1, 2, 3, 4 ] );\n","array2iterator":"var it = array2iterator( [ 1, 2, 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","array2iteratorRight":"var it = array2iteratorRight( [ 1, 2, 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","ArrayBuffer":"var buf = new ArrayBuffer( 5 )\n","ArrayBuffer.length":"ArrayBuffer.length\n","ArrayBuffer.isView":"var arr = new Float64Array( 10 );\nArrayBuffer.isView( arr )\n","ArrayBuffer.prototype.byteLength":"var buf = new ArrayBuffer( 5 );\nbuf.byteLength\n","ArrayBuffer.prototype.slice":"var b1 = new ArrayBuffer( 10 );\nvar b2 = b1.slice( 2, 6 );\nvar bool = ( b1 === b2 )\nb2.byteLength\n","arraybuffer2buffer":"var ab = new ArrayBuffer( 10 )\nvar buf = arraybuffer2buffer( ab )\nvar len = buf.length\nbuf = arraybuffer2buffer( ab, 2, 6 )\nlen = buf.length\n","arrayCtors":"var ctor = arrayCtors( 'float64' )\nctor = arrayCtors( 'float' )\n","arrayDataType":"var arr = new Float64Array( 10 );\nvar dt = arrayDataType( arr )\ndt = arrayDataType( 'beep' )\n","arrayDataTypes":"var out = arrayDataTypes()\nout = arrayDataTypes( 'floating_point' )\nout = arrayDataTypes( 'floating_point_and_generic' )\n","ArrayIndex":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n","ArrayIndex.free":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nArrayIndex.free( idx.id )\n","ArrayIndex.get":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nArrayIndex.get( idx.id )\n","ArrayIndex.prototype.data":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.data\n","ArrayIndex.prototype.dtype":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.dtype\n","ArrayIndex.prototype.id":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.id\n","ArrayIndex.prototype.isCached":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.isCached\n","ArrayIndex.prototype.type":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.type\n","ArrayIndex.prototype.toString":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.toString()\n","ArrayIndex.prototype.toJSON":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.toJSON()\n","arrayMinDataType":"var dt = arrayMinDataType( 3.141592653589793 )\ndt = arrayMinDataType( 3 )\ndt = arrayMinDataType( -3 )\ndt = arrayMinDataType( '-3' )\n","arrayMostlySafeCasts":"var out = arrayMostlySafeCasts( 'float32' )\n","arrayNextDataType":"var out = arrayNextDataType( 'float32' )\n","arrayPromotionRules":"var out = arrayPromotionRules( 'float32', 'int32' )\n","arraySafeCasts":"var out = arraySafeCasts( 'float32' )\n","arraySameKindCasts":"var out = arraySameKindCasts( 'float32' )\n","arrayShape":"var out = arrayShape( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n","arrayStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar s = arrayStream( [ 1, 2, 3 ] );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","arrayStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = arrayStream.factory( opts );\n","arrayStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar s = arrayStream.objectMode( [ 1, 2, 3 ] );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","arrayview2iterator":"var it = arrayview2iterator( [ 1, 2, 3, 4 ], 1, 3 );\nvar v = it.next().value\nv = it.next().value\n","arrayview2iteratorRight":"var it = arrayview2iteratorRight( [ 1, 2, 3, 4 ], 1, 3 );\nvar v = it.next().value\nv = it.next().value\n","aslice":"var out = aslice( [ 1, 2, 3, 4 ] )\nout = aslice( [ 1, 2, 3, 4 ], 1 )\nout = aslice( [ 1, 2, 3, 4 ], 1, 3 )\n","AsyncIteratorSymbol":"var s = AsyncIteratorSymbol\n","atake":"var x = [ 1, 2, 3, 4 ];\nvar y = atake( x, [ 1, 3 ] )\n","azeros":"var arr = azeros( 2 )\narr = azeros( 2, 'float32' )\n","azerosLike":"var x = new Float64Array( 2 );\nvar y = azerosLike( x )\ny = azerosLike( x, 'float32' )\n","azeroTo":"var arr = azeroTo( 2 )\narr = azeroTo( 2, 'float32' )\n","azeroToLike":"var arr = azeroToLike( [ 0, 0 ] )\narr = azeroToLike( [ 0, 0 ], 'float32' )\n","bartlettTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = bartlettTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = bartlettTest( arr, { 'groups': groups } )\n","base.abs":"var y = base.abs( -1.0 )\ny = base.abs( 2.0 )\ny = base.abs( 0.0 )\ny = base.abs( -0.0 )\ny = base.abs( NaN )\n","base.abs2":"var y = base.abs2( -1.0 )\ny = base.abs2( 2.0 )\ny = base.abs2( 0.0 )\ny = base.abs2( -0.0 )\ny = base.abs2( NaN )\n","base.abs2f":"var y = base.abs2f( -1.0 )\ny = base.abs2f( 2.0 )\ny = base.abs2f( 0.0 )\ny = base.abs2f( -0.0 )\ny = base.abs2f( NaN )\n","base.absdiff":"var d = base.absdiff( 2.0, 5.0 )\nd = base.absdiff( -1.0, 3.14 )\nd = base.absdiff( 10.1, -2.05 )\nd = base.absdiff( -0.0, 0.0 )\nd = base.absdiff( NaN, 5.0 )\nd = base.absdiff( PINF, NINF )\nd = base.absdiff( PINF, PINF )\n","base.absf":"var y = base.absf( -1.0 )\ny = base.absf( 2.0 )\ny = base.absf( 0.0 )\ny = base.absf( -0.0 )\ny = base.absf( NaN )\n","base.acartesianPower":"var x = [ 1, 2 ];\nvar out = base.acartesianPower( x, 2 )\n","base.acartesianProduct":"var x1 = [ 1, 2 ];\nvar x2 = [ 3, 4 ];\nvar out = base.acartesianProduct( x1, x2 )\n","base.acartesianSquare":"var x = [ 1, 2 ];\nvar out = base.acartesianSquare( x )\n","base.acos":"var y = base.acos( 1.0 )\ny = base.acos( 0.707 )\ny = base.acos( NaN )\n","base.acosd":"var y = base.acosd( 0.0 )\ny = base.acosd( PI/6.0 )\ny = base.acosd( NaN )\n","base.acosf":"var y = base.acosf( 1.0 )\ny = base.acosf( 0.707 )\ny = base.acosf( NaN )\n","base.acosh":"var y = base.acosh( 1.0 )\ny = base.acosh( 2.0 )\ny = base.acosh( NaN )\n","base.acot":"var y = base.acot( 2.0 )\ny = base.acot( 0.0 )\ny = base.acot( 0.5 )\ny = base.acot( 1.0 )\ny = base.acot( NaN )\n","base.acotd":"var y = base.acotd( 0.0 )\ny = base.acotd( PI/6.0 )\ny = base.acotd( NaN )\n","base.acotf":"var y = base.acotf( 2.0 )\ny = base.acotf( 0.0 )\ny = base.acotf( 0.5 )\ny = base.acotf( 1.0 )\ny = base.acotf( NaN )\n","base.acoth":"var y = base.acoth( 2.0 )\ny = base.acoth( 0.0 )\ny = base.acoth( 0.5 )\ny = base.acoth( 1.0 )\ny = base.acoth( NaN )\n","base.acovercos":"var y = base.acovercos( -1.5 )\ny = base.acovercos( -0.0 )\n","base.acoversin":"var y = base.acoversin( 1.5 )\ny = base.acoversin( 0.0 )\n","base.acsc":"var y = base.acsc( 1.0 )\ny = base.acsc( PI )\ny = base.acsc( -PI )\ny = base.acsc( NaN )\n","base.acscd":"var y = base.acscd( 0.0 )\ny = base.acscd( PI/6.0 )\ny = base.acscd( 1 )\ny = base.acscd( NaN )\n","base.acscdf":"var y = base.acscdf( 0.0 )\ny = base.acscdf( 3.1415927410125732 / 6.0 )\ny = base.acscdf( 1.0 )\ny = base.acscdf( NaN )\n","base.acscf":"var y = base.acscf( 1.0 )\ny = base.acscf( 3.141592653589793 )\ny = base.acscf( -3.141592653589793 )\ny = base.acscf( NaN )\n","base.acsch":"var y = base.acsch( 0.0 )\ny = base.acsch( -1.0 )\ny = base.acsch( NaN )\n","base.add":"var v = base.add( -1.0, 5.0 )\nv = base.add( 2.0, 5.0 )\nv = base.add( 0.0, 5.0 )\nv = base.add( -0.0, 0.0 )\nv = base.add( NaN, NaN )\n","base.add3":"var v = base.add3( -1.0, 5.0, 2.0 )\nv = base.add3( 2.0, 5.0, 2.0 )\nv = base.add3( 0.0, 5.0, 2.0 )\nv = base.add3( -0.0, 0.0, -0.0 )\nv = base.add3( NaN, NaN, NaN )\n","base.add4":"var v = base.add4( -1.0, 5.0, 2.0, -3.0 )\nv = base.add4( 2.0, 5.0, 2.0, -3.0 )\nv = base.add4( 0.0, 5.0, 2.0, -3.0 )\nv = base.add4( -0.0, 0.0, -0.0, -0.0 )\nv = base.add4( NaN, NaN, NaN, NaN )\n","base.add5":"var v = base.add5( -1.0, 5.0, 2.0, -3.0, 4.0 )\nv = base.add5( 2.0, 5.0, 2.0, -3.0, 4.0 )\nv = base.add5( 0.0, 5.0, 2.0, -3.0, 4.0 )\nv = base.add5( -0.0, 0.0, -0.0, -0.0, -0.0 )\nv = base.add5( NaN, NaN, NaN, NaN, NaN )\n","base.addf":"var v = base.addf( -1.0, 5.0 )\nv = base.addf( 2.0, 5.0 )\nv = base.addf( 0.0, 5.0 )\nv = base.addf( -0.0, 0.0 )\nv = base.addf( NaN, NaN )\n","base.afilled":"var out = base.afilled( 0.0, 3 )\n","base.afilled2d":"var out = base.afilled2d( 0.0, [ 1, 3 ] )\n","base.afilled2dBy":"function clbk() { return 1.0; };\nvar out = base.afilled2dBy( [ 1, 3 ], clbk )\n","base.afilled3d":"var out = base.afilled3d( 0.0, [ 1, 1, 3 ] )\n","base.afilled3dBy":"function clbk() { return 1.0; };\nvar out = base.afilled3dBy( [ 1, 1, 3 ], clbk )\n","base.afilled4d":"var out = base.afilled4d( 0.0, [ 1, 1, 1, 3 ] )\n","base.afilled4dBy":"function clbk() { return 1.0; };\nvar out = base.afilled4dBy( [ 1, 1, 1, 3 ], clbk )\n","base.afilled5d":"var out = base.afilled5d( 0.0, [ 1, 1, 1, 1, 3 ] )\n","base.afilled5dBy":"function clbk() { return 1.0; };\nvar out = base.afilled5dBy( [ 1, 1, 1, 1, 3 ], clbk )\n","base.afilledBy":"function clbk() { return 1.0; };\nvar out = base.afilledBy( 3, clbk )\n","base.afillednd":"var out = base.afillednd( 0.0, [ 1, 3 ] )\n","base.afilledndBy":"function clbk() { return 1.0; };\nvar out = base.afilledndBy( [ 1, 3 ], clbk )\n","base.afilter":"function f( v ) { return ( v > 0 ); };\nvar x = [ 1, -2, -3, 4 ];\nvar out = base.afilter( x, f )\n","base.afirst":"var out = base.afirst( [ 1, 2, 3 ] )\n","base.aflatten":"var x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = base.aflatten( x, [ 2, 2 ], false )\nout = base.aflatten( x, [ 2, 2 ], true )\n","base.aflatten.assign":"var x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten.assign( x, [ 2, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten.assign( x, [ 2, 2 ], true, out, 1, 0 );\nout\n","base.aflatten2d":"var x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = base.aflatten2d( x, [ 2, 2 ], false )\nout = base.aflatten2d( x, [ 2, 2 ], true )\n","base.aflatten2d.assign":"var x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten2d.assign( x, [ 2, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten2d.assign( x, [ 2, 2 ], true, out, 1, 0 );\nout\n","base.aflatten2dBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = base.aflatten2dBy( x, [ 2, 2 ], false, fcn )\nout = base.aflatten2dBy( x, [ 2, 2 ], true, fcn )\n","base.aflatten2dBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten2dBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten2dBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\nout\n","base.aflatten3d":"var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\nvar out = base.aflatten3d( x, [ 2, 1, 2 ], false )\nout = base.aflatten3d( x, [ 2, 1, 2 ], true )\n","base.aflatten3d.assign":"var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten3d.assign( x, [ 2, 1, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten3d.assign( x, [ 2, 1, 2 ], true, out, 1, 0 );\nout\n","base.aflatten3dBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\nvar out = base.aflatten3dBy( x, [ 2, 1, 2 ], false, fcn )\nout = base.aflatten3dBy( x, [ 2, 1, 2 ], true, fcn )\n","base.aflatten3dBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten3dBy.assign( x, [ 2, 1, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten3dBy.assign( x, [ 2, 1, 2 ], true, out, 1, 0, fcn );\nout\n","base.aflatten4d":"var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\nvar out = base.aflatten4d( x, [ 2, 1, 1, 2 ], false )\nout = base.aflatten4d( x, [ 2, 1, 1, 2 ], true )\n","base.aflatten4d.assign":"var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten4d.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0 );\nout\n","base.aflatten4dBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\nvar out = base.aflatten4dBy( x, [ 2, 1, 1, 2 ], false, fcn )\nout = base.aflatten4dBy( x, [ 2, 1, 1, 2 ], true, fcn )\n","base.aflatten4dBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0, fcn );\nout\n","base.aflatten5d":"var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\nvar out = base.aflatten5d( x, [ 2, 1, 1, 1, 2 ], false )\nout = base.aflatten5d( x, [ 2, 1, 1, 1, 2 ], true )\n","base.aflatten5d.assign":"var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0 );\nout\n","base.aflatten5dBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\nvar out = base.aflatten5dBy( x, [ 2, 1, 1, 1, 2 ], false, fcn )\nout = base.aflatten5dBy( x, [ 2, 1, 1, 1, 2 ], true, fcn )\n","base.aflatten5dBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0, fcn );\nout\n","base.aflattenBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = base.aflattenBy( x, [ 2, 2 ], false, fcn )\nout = base.aflattenBy( x, [ 2, 2 ], true, fcn )\n","base.aflattenBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflattenBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflattenBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\nout\n","base.afliplr2d":"var out = base.afliplr2d( [ [ 1, 2 ], [ 3, 4 ] ] )\n","base.afliplr3d":"var out = base.afliplr3d( [ [ [ 1, 2 ], [ 3, 4 ] ] ] )\n","base.afliplr4d":"var out = base.afliplr4d( [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] )\n","base.afliplr5d":"var out = base.afliplr5d( [ [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] ] )\n","base.aflipud2d":"var out = base.aflipud2d( [ [ 1, 2 ], [ 3, 4 ] ] )\n","base.aflipud3d":"var out = base.aflipud3d( [ [ [ 1, 2 ], [ 3, 4 ] ] ] )\n","base.aflipud4d":"var out = base.aflipud4d( [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] )\n","base.aflipud5d":"var out = base.aflipud5d( [ [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] ] )\n","base.ahavercos":"var y = base.ahavercos( 0.5 )\ny = base.ahavercos( 0.0 )\n","base.ahaversin":"var y = base.ahaversin( 0.5 )\ny = base.ahaversin( 0.0 )\n","base.altcase":"var out = base.altcase( 'Hello World!' )\nout = base.altcase( 'I am a tiny little teapot' )\n","base.aones":"var out = base.aones( 3 )\n","base.aones2d":"var out = base.aones2d( [ 1, 3 ] )\n","base.aones3d":"var out = base.aones3d( [ 1, 1, 3 ] )\n","base.aones4d":"var out = base.aones4d( [ 1, 1, 1, 3 ] )\n","base.aones5d":"var out = base.aones5d( [ 1, 1, 1, 1, 3 ] )\n","base.aonesnd":"var out = base.aonesnd( [ 1, 3 ] )\n","base.aoneTo":"var arr = base.aoneTo( 6 )\n","base.aoneTo.assign":"var out = [ 0, 0, 0, 0, 0, 0 ];\nbase.aoneTo.assign( out, -1, out.length-1 );\nout\n","base.args2multislice":"var args = [ null, null, null ];\nvar s = new base.args2multislice( args );\ns.data\nargs = [ 10, new Slice( 0, 10, 1 ), null ];\ns = new base.args2multislice( args );\ns.data\n","base.asec":"var y = base.asec( 1.0 )\ny = base.asec( 2.0 )\ny = base.asec( NaN )\n","base.asecd":"var y = base.asecd( 0.0 )\ny = base.asecd( 2 )\ny = base.asecd( NaN )\n","base.asecdf":"var y = base.asecdf( 2.0 )\ny = base.asecdf( 0.0 )\ny = base.asecdf( NaN )\n","base.asecf":"var y = base.asecf( 1.0 )\ny = base.asecf( 2.0 )\ny = base.asecf( NaN )\n","base.asech":"var y = base.asech( 1.0 )\ny = base.asech( 0.5 )\ny = base.asech( NaN )\n","base.asin":"var y = base.asin( 0.0 )\ny = base.asin( -PI/6.0 )\ny = base.asin( NaN )\n","base.asind":"var y = base.asind( 0.0 )\ny = base.asind( PI / 6.0 )\ny = base.asind( NaN )\n","base.asindf":"var y = base.asindf( 0.0 )\ny = base.asindf( 3.1415927410125732 / 6.0 )\ny = base.asindf( NaN )\n","base.asinf":"var y = base.asinf( 0.0 )\ny = base.asinf( -3.14/6.0 )\ny = base.asinf( NaN )\n","base.asinh":"var y = base.asinh( 0.0 )\ny = base.asinh( 2.0 )\ny = base.asinh( -2.0 )\ny = base.asinh( NaN )\ny = base.asinh( NINF )\ny = base.asinh( PINF )\n","base.atan":"var y = base.atan( 0.0 )\ny = base.atan( -PI/2.0 )\ny = base.atan( PI/2.0 )\ny = base.atan( NaN )\n","base.atan2":"var v = base.atan2( 2.0, 2.0 )\nv = base.atan2( 6.0, 2.0 )\nv = base.atan2( -1.0, -1.0 )\nv = base.atan2( 3.0, 0.0 )\nv = base.atan2( -2.0, 0.0 )\nv = base.atan2( 0.0, 0.0 )\nv = base.atan2( 3.0, NaN )\nv = base.atan2( NaN, 2.0 )\n","base.atand":"var y = base.atand( 0.0 )\ny = base.atand( PI/6.0 )\ny = base.atand( NaN )\n","base.atanf":"var y = base.atanf( 0.0 )\ny = base.atanf( -3.14/4.0 )\ny = base.atanf( 3.14/4.0 )\ny = base.atanf( NaN )\n","base.atanh":"var y = base.atanh( 0.0 )\ny = base.atanh( 0.9 )\ny = base.atanh( 1.0 )\ny = base.atanh( -1.0 )\ny = base.atanh( NaN )\n","base.avercos":"var y = base.avercos( -1.5 )\ny = base.avercos( -0.0 )\n","base.aversin":"var y = base.aversin( 1.5 )\ny = base.aversin( 0.0 )\n","base.azeros":"var out = base.azeros( 3 )\n","base.azeros2d":"var out = base.azeros2d( [ 1, 3 ] )\n","base.azeros3d":"var out = base.azeros3d( [ 1, 1, 3 ] )\n","base.azeros4d":"var out = base.azeros4d( [ 1, 1, 1, 3 ] )\n","base.azeros5d":"var out = base.azeros5d( [ 1, 1, 1, 1, 3 ] )\n","base.azerosnd":"var out = base.azerosnd( [ 1, 3 ] )\n","base.azeroTo":"var arr = base.azeroTo( 6 )\n","base.azeroTo.assign":"var out = [ 0, 0, 0, 0, 0, 0 ];\nbase.azeroTo.assign( out, -1, out.length-1 );\nout\n","base.bernoulli":"var y = base.bernoulli( 0 )\ny = base.bernoulli( 1 )\ny = base.bernoulli( 2 )\ny = base.bernoulli( 3 )\ny = base.bernoulli( 4 )\ny = base.bernoulli( 5 )\ny = base.bernoulli( 20 )\ny = base.bernoulli( 260 )\ny = base.bernoulli( 262 )\ny = base.bernoulli( NaN )\n","base.besselj0":"var y = base.besselj0( 0.0 )\ny = base.besselj0( 1.0 )\ny = base.besselj0( PINF )\ny = base.besselj0( NINF )\ny = base.besselj0( NaN )\n","base.besselj1":"var y = base.besselj1( 0.0 )\ny = base.besselj1( 1.0 )\ny = base.besselj1( PINF )\ny = base.besselj1( NINF )\ny = base.besselj1( NaN )\n","base.bessely0":"var y = base.bessely0( 0.0 )\ny = base.bessely0( 1.0 )\ny = base.bessely0( -1.0 )\ny = base.bessely0( PINF )\ny = base.bessely0( NINF )\ny = base.bessely0( NaN )\n","base.bessely1":"var y = base.bessely1( 0.0 )\ny = base.bessely1( 1.0 )\ny = base.bessely1( -1.0 )\ny = base.bessely1( PINF )\ny = base.bessely1( NINF )\ny = base.bessely1( NaN )\n","base.beta":"var v = base.beta( 0.0, 0.5 )\nv = base.beta( 1.0, 1.0 )\nv = base.beta( -1.0, 2.0 )\nv = base.beta( 5.0, 0.2 )\nv = base.beta( 4.0, 1.0 )\nv = base.beta( NaN, 2.0 )\n","base.betainc":"var y = base.betainc( 0.5, 2.0, 2.0 )\ny = base.betainc( 0.5, 2.0, 2.0, false )\ny = base.betainc( 0.2, 1.0, 2.0 )\ny = base.betainc( 0.2, 1.0, 2.0, true, true )\ny = base.betainc( NaN, 1.0, 1.0 )\ny = base.betainc( 0.8, NaN, 1.0 )\ny = base.betainc( 0.8, 1.0, NaN )\ny = base.betainc( 1.5, 1.0, 1.0 )\ny = base.betainc( -0.5, 1.0, 1.0 )\ny = base.betainc( 0.5, -2.0, 2.0 )\ny = base.betainc( 0.5, 2.0, -2.0 )\n","base.betaincinv":"var y = base.betaincinv( 0.2, 3.0, 3.0 )\ny = base.betaincinv( 0.4, 3.0, 3.0 )\ny = base.betaincinv( 0.4, 3.0, 3.0, true )\ny = base.betaincinv( 0.4, 1.0, 6.0 )\ny = base.betaincinv( 0.8, 1.0, 6.0 )\ny = base.betaincinv( NaN, 1.0, 1.0 )\ny = base.betaincinv( 0.5, NaN, 1.0 )\ny = base.betaincinv( 0.5, 1.0, NaN )\ny = base.betaincinv( 1.2, 1.0, 1.0 )\ny = base.betaincinv( -0.5, 1.0, 1.0 )\ny = base.betaincinv( 0.5, -2.0, 2.0 )\ny = base.betaincinv( 0.5, 0.0, 2.0 )\ny = base.betaincinv( 0.5, 2.0, -2.0 )\ny = base.betaincinv( 0.5, 2.0, 0.0 )\n","base.betaln":"var v = base.betaln( 0.0, 0.0 )\nv = base.betaln( 1.0, 1.0 )\nv = base.betaln( -1.0, 2.0 )\nv = base.betaln( 5.0, 0.2 )\nv = base.betaln( 4.0, 1.0 )\nv = base.betaln( NaN, 2.0 )\n","base.binet":"var y = base.binet( 0.0 )\ny = base.binet( 1.0 )\ny = base.binet( 2.0 )\ny = base.binet( 3.0 )\ny = base.binet( 4.0 )\ny = base.binet( 5.0 )\ny = base.binet( NaN )\n","base.binomcoef":"var v = base.binomcoef( 8, 2 )\nv = base.binomcoef( 0, 0 )\nv = base.binomcoef( -4, 2 )\nv = base.binomcoef( 5, 3 )\nv = base.binomcoef( NaN, 3 )\nv = base.binomcoef( 5, NaN )\nv = base.binomcoef( NaN, NaN )\n","base.binomcoefln":"var v = base.binomcoefln( 8, 2 )\nv = base.binomcoefln( 0, 0 )\nv = base.binomcoefln( -4, 2 )\nv = base.binomcoefln( 88, 3 )\nv = base.binomcoefln( NaN, 3 )\nv = base.binomcoefln( 5, NaN )\nv = base.binomcoefln( NaN, NaN )\n","base.boxcox":"var v = base.boxcox( 1.0, 2.5 )\nv = base.boxcox( 4.0, 2.5 )\nv = base.boxcox( 10.0, 2.5 )\nv = base.boxcox( 2.0, 0.0 )\nv = base.boxcox( -1.0, 2.5 )\nv = base.boxcox( 0.0, -1.0 )\n","base.boxcox1p":"var v =  base.boxcox1p( 1.0, 2.5 )\nv = base.boxcox1p( 4.0, 2.5 )\nv = base.boxcox1p( 10.0, 2.5 )\nv = base.boxcox1p( 2.0, 0.0 )\nv = base.boxcox1p( -1.0, 2.5 )\nv = base.boxcox1p( 0.0, -1.0 )\nv = base.boxcox1p( -1.0, -1.0 )\n","base.boxcox1pinv":"var v = base.boxcox1pinv( 1.0, 2.5 )\nv = base.boxcox1pinv( 4.0, 2.5 )\nv = base.boxcox1pinv( 10.0, 2.5 )\nv = base.boxcox1pinv( 2.0, 0.0 )\nv = base.boxcox1pinv( -1.0, 2.5 )\nv = base.boxcox1pinv( 0.0, -1.0 )\nv = base.boxcox1pinv( 1.0, NaN )\nv = base.boxcox1pinv( NaN, 3.1 )\n","base.boxcoxinv":"var v = base.boxcoxinv( 1.0, 2.5 )\nv = base.boxcoxinv( 4.0, 2.5 )\nv = base.boxcoxinv( 10.0, 2.5 )\nv = base.boxcoxinv( 2.0, 0.0 )\nv = base.boxcoxinv( -1.0, 2.5 )\nv = base.boxcoxinv( 0.0, -1.0 )\nv = base.boxcoxinv( 1.0, NaN )\nv = base.boxcoxinv( NaN, 3.1 )\n","base.cabs":"var y = base.cabs( new Complex128( 5.0, 3.0 ) )\n","base.cabs2":"var y = base.cabs2( new Complex128( 5.0, 3.0 ) )\n","base.cabs2f":"var y = base.cabs2f( new Complex64( 5.0, 3.0 ) )\n","base.cabsf":"var y = base.cabsf( new Complex64( 5.0, 3.0 ) )\n","base.cadd":"var z = new Complex128( 5.0, 3.0 )\nvar out = base.cadd( z, z )\nvar re = real( out )\nvar im = imag( out )\n","base.caddf":"var z = new Complex64( 5.0, 3.0 )\nvar out = base.caddf( z, z )\nvar re = realf( out )\nvar im = imagf( out )\n","base.camelcase":"var out = base.camelcase( 'Hello World!' )\nout = base.camelcase( 'beep boop' )\n","base.capitalize":"var out = base.capitalize( 'beep' )\nout = base.capitalize( 'Boop' )\n","base.cbrt":"var y = base.cbrt( 64.0 )\ny = base.cbrt( 27.0 )\ny = base.cbrt( 0.0 )\ny = base.cbrt( -0.0 )\ny = base.cbrt( -9.0 )\ny = base.cbrt( NaN )\n","base.cbrtf":"var y = base.cbrtf( 64.0 )\ny = base.cbrtf( 27.0 )\ny = base.cbrtf( 0.0 )\ny = base.cbrtf( -0.0 )\ny = base.cbrtf( -9.0 )\ny = base.cbrtf( NaN )\n","base.cceil":"var v = base.cceil( new Complex128( -1.5, 2.5 ) )\nvar re = real( v )\nvar im = imag( v )\n","base.cceilf":"var v = base.cceilf( new Complex64( -1.5, 2.5 ) )\nvar re = realf( v )\nvar im = imagf( v )\n","base.cceiln":"var out = base.cceiln( new Complex128( 5.555, -3.333 ), -2 )\nvar re = real( out )\nvar im = imag( out )\n","base.ccis":"var y = base.ccis( new Complex128( 0.0, 0.0 ) )\nvar re = real( y )\nvar im = imag( y )\ny = base.ccis( new Complex128( 1.0, 0.0 ) )\nre = real( y )\nim = imag( y )\n","base.cdiv":"var z1 = new Complex128( -13.0, -1.0 )\nvar z2 = new Complex128( -2.0, 1.0 )\nvar y = base.cdiv( z1, z2 )\nvar re = real( y )\nvar im = imag( y )\n","base.ceil":"var y = base.ceil( 3.14 )\ny = base.ceil( -4.2 )\ny = base.ceil( -4.6 )\ny = base.ceil( 9.5 )\ny = base.ceil( -0.0 )\n","base.ceil2":"var y = base.ceil2( 3.14 )\ny = base.ceil2( -4.2 )\ny = base.ceil2( -4.6 )\ny = base.ceil2( 9.5 )\ny = base.ceil2( 13.0 )\ny = base.ceil2( -13.0 )\ny = base.ceil2( -0.0 )\n","base.ceil10":"var y = base.ceil10( 3.14 )\ny = base.ceil10( -4.2 )\ny = base.ceil10( -4.6 )\ny = base.ceil10( 9.5 )\ny = base.ceil10( 13.0 )\ny = base.ceil10( -13.0 )\ny = base.ceil10( -0.0 )\n","base.ceilb":"var y = base.ceilb( 3.14159, -4, 10 )\ny = base.ceilb( 3.14159, 0, 2 )\ny = base.ceilb( 5.0, 1, 2 )\n","base.ceilf":"var y = base.ceilf( 3.14 )\ny = base.ceilf( -4.2 )\ny = base.ceilf( -4.6 )\ny = base.ceilf( 9.5 )\ny = base.ceilf( -0.0 )\n","base.ceiln":"var y = base.ceiln( 3.14159, -2 )\ny = base.ceiln( 3.14159, 0 )\ny = base.ceiln( 12368.0, 3 )\n","base.ceilsd":"var y = base.ceilsd( 3.14159, 5, 10 )\ny = base.ceilsd( 3.14159, 1, 10 )\ny = base.ceilsd( 12368.0, 2, 10 )\ny = base.ceilsd( 0.0313, 2, 2 )\n","base.cexp":"var y = base.cexp( new Complex128( 0.0, 0.0 ) )\nvar re = real( y )\nvar im = imag( y )\ny = base.cexp( new Complex128( 0.0, 1.0 ) )\nre = real( y )\nim = imag( y )\n","base.cflipsign":"var v = base.cflipsign( new Complex128( -4.2, 5.5 ), -9.0 )\nvar re = real( v )\nvar im = imag( v )\n","base.cflipsignf":"var v = base.cflipsignf( new Complex64( -4.0, 5.0 ), -9.0 )\nvar re = realf( v )\nvar im = imagf( v )\n","base.cfloor":"var v = base.cfloor( new Complex128( 5.5, 3.3 ) )\nvar re = real( v )\nvar im = imag( v )\n","base.cfloorn":"var v = base.cfloorn( new Complex128( 5.555, -3.333 ), -2 )\nvar re = real( v )\nvar im = imag( v )\n","base.cidentity":"var v = base.cidentity( new Complex128( -1.0, 2.0 ) )\nvar re = real( v )\nvar img = imag( v )\n","base.cidentityf":"var v = base.cidentityf( new Complex64( -1.0, 2.0 ) )\nvar re = realf( v )\nvar img = imagf( v )\n","base.cinv":"var v = base.cinv( new Complex128( 2.0, 4.0 ) )\nvar re = real( v )\nvar im = imag( v )\n","base.clamp":"var y = base.clamp( 3.14, 0.0, 5.0 )\ny = base.clamp( -3.14, 0.0, 5.0 )\ny = base.clamp( 3.14, 0.0, 3.0 )\ny = base.clamp( -0.0, 0.0, 5.0 )\ny = base.clamp( 0.0, -3.14, -0.0 )\ny = base.clamp( NaN, 0.0, 5.0 )\n","base.clampf":"var y = base.clampf( 3.14, 0.0, 5.0 )\ny = base.clampf( -3.14, 0.0, 5.0 )\ny = base.clampf( 3.14, 0.0, 3.0 )\ny = base.clampf( -0.0, 0.0, 5.0 )\ny = base.clampf( 0.0, -3.14, -0.0 )\ny = base.clampf( NaN, 0.0, 5.0 )\n","base.cmul":"var z1 = new Complex128( 5.0, 3.0 )\nvar z2 = new Complex128( -2.0, 1.0 )\nvar out = base.cmul( z1, z2 )\nvar re = real( out )\nvar im = imag( out )\n","base.cmulf":"var z1 = new Complex64( 5.0, 3.0 )\nvar z2 = new Complex64( -2.0, 1.0 )\nvar out = base.cmulf( z1, z2 )\nvar re = realf( out )\nvar im = imagf( out )\n","base.cneg":"var z = new Complex128( -4.2, 5.5 )\nvar v = base.cneg( z )\nvar re = real( v )\nvar im = imag( v )\n","base.cnegf":"var z = new Complex64( -4.0, 5.0 )\nvar v = base.cnegf( z )\nvar re = realf( v )\nvar im = imagf( v )\n","base.codePointAt":"var out = base.codePointAt( 'last man standing', 4, false )\nout = base.codePointAt( 'presidential election', 8, true )\nout = base.codePointAt( 'अनुच्छेद', 2, false )\nout = base.codePointAt( '🌷', 1, true )\n","base.constantcase":"var out = base.constantcase( 'Hello World!' )\nout = base.constantcase( 'I am a tiny little teapot' )\n","base.continuedFraction":"function closure() {\nvar i = 0;\nreturn function() {\n    i += 1;\n    return [ i, i ];\n};\n };\nvar gen = closure();\nvar out = base.continuedFraction( gen )\nfunction* generator() {\n var i = 0;\n while ( true ) {\n     i += 1;\n     yield [ i, i ];\n }\n };\ngen = generator();\nout = base.continuedFraction( gen )\nout = base.continuedFraction( generator(), { 'keep': true } )\nout = base.continuedFraction( generator(), { 'maxIter': 10 } )\nout = base.continuedFraction( generator(), { 'tolerance': 1e-1 } )\n","base.copysign":"var z = base.copysign( -3.14, 10.0 )\nz = base.copysign( 3.14, -1.0 )\nz = base.copysign( 1.0, -0.0 )\nz = base.copysign( -3.14, -0.0 )\nz = base.copysign( -0.0, 1.0 )\n","base.copysignf":"var z = base.copysignf( -3.0, 10.0 )\nz = base.copysignf( 3.0, -1.0 )\nz = base.copysignf( 1.0, -0.0 )\nz = base.copysignf( -3.0, -0.0 )\nz = base.copysignf( -0.0, 1.0 )\n","base.cos":"var y = base.cos( 0.0 )\ny = base.cos( PI/4.0 )\ny = base.cos( -PI/6.0 )\ny = base.cos( NaN )\n","base.cosd":"var y = base.cosd( 0.0 )\ny = base.cosd( 90.0 )\ny = base.cosd( 60.0 )\ny = base.cosd( NaN )\n","base.cosh":"var y = base.cosh( 0.0 )\ny = base.cosh( 2.0 )\ny = base.cosh( -2.0 )\ny = base.cosh( NaN )\n","base.cosm1":"var y = base.cosm1( 0.0 )\ny = base.cosm1( PI/4.0 )\ny = base.cosm1( -PI/6.0 )\ny = base.cosm1( NaN )\n","base.cospi":"var y = base.cospi( 0.0 )\ny = base.cospi( 0.5 )\ny = base.cospi( 0.1 )\ny = base.cospi( NaN )\n","base.cot":"var y = base.cot( 0.0 )\ny = base.cot( -PI/4.0 )\ny = base.cot( PI/4.0 )\ny = base.cot( NaN )\n","base.cotd":"var y = base.cotd( 0.0 )\ny = base.cotd( 90.0 )\ny = base.cotd( 60.0 )\ny = base.cotd( NaN )\n","base.coth":"var y = base.coth( 0.0 )\ny = base.coth( -0.0 )\ny = base.coth( 2.0 )\ny = base.coth( -2.0 )\ny = base.coth( +Infinity )\ny = base.coth( -Infinity )\ny = base.coth( NaN )\n","base.covercos":"var y = base.covercos( 3.14 )\ny = base.covercos( -4.2 )\ny = base.covercos( -4.6 )\ny = base.covercos( 9.5 )\ny = base.covercos( -0.0 )\n","base.coversin":"var y = base.coversin( 3.14 )\ny = base.coversin( -4.2 )\ny = base.coversin( -4.6 )\ny = base.coversin( 9.5 )\ny = base.coversin( -0.0 )\n","base.cphase":"var phi = base.cphase( new Complex128( 5.0, 3.0 ) )\n","base.cpolar":"var out = base.cpolar( new Complex128( 5.0, 3.0 ) )\n","base.cpolar.assign":"var out = new Float64Array( 2 );\nvar v = base.cpolar.assign( new Complex128( 5.0, 3.0 ), out, 1, 0 )\nvar bool = ( v === out )\n","base.cround":"var v = base.cround( new Complex128( 5.5, 3.3 ) )\nvar re = real( v )\nvar im = imag( v )\n","base.croundn":"var v = base.croundn( new Complex128( 5.555, -3.336 ), -2 )\nvar re = real( v )\nvar im = imag( v )\n","base.csc":"var y = base.csc( 0.0 )\ny = base.csc( PI/2.0 )\ny = base.csc( -PI/6.0 )\ny = base.csc( NaN )\n","base.cscd":"var y = base.cscd( 1.0 )\ny = base.cscd( PI )\ny = base.cscd( -PI )\ny = base.cscd( NaN )\n","base.csch":"var y = base.csch( +0.0 )\nvar y = base.csch( -0.0 )\nvar y = base.csch( +Infinity )\nvar y = base.csch( -Infinity )\ny = base.csch( 2.0 )\ny = base.csch( -2.0 )\ny = base.csch( NaN )\n","base.csignum":"var v = base.csignum( new Complex128( -4.2, 5.5 ) )\nvar re = real( v )\nvar im = imag( v )\n","base.csub":"var z1 = new Complex128( 5.0, 3.0 )\nvar z2 = new Complex128( -2.0, 1.0 )\nvar out = base.csub( z1, z2 )\nvar re = real( out )\nvar im = imag( out )\n","base.csubf":"var z1 = new Complex64( 5.0, 3.0 )\nvar z2 = new Complex64( -2.0, 1.0 )\nvar out = base.csubf( z1, z2 )\nvar re = realf( out )\nvar im = imagf( out )\n","base.deg2rad":"var r = base.deg2rad( 90.0 )\nr = base.deg2rad( -45.0 )\nr = base.deg2rad( NaN )\n","base.deg2radf":"var r = base.deg2radf( 90.0 )\nr = base.deg2radf( -45.0 )\nr = base.deg2radf( NaN )\n","base.digamma":"var y = base.digamma( -2.5 )\ny = base.digamma( 1.0 )\ny = base.digamma( 10.0 )\ny = base.digamma( NaN )\ny = base.digamma( -1.0 )\n","base.diracDelta":"var y = base.diracDelta( 3.14 )\ny = base.diracDelta( 0.0 )\n","base.div":"var v = base.div( -1.0, 5.0 )\nv = base.div( 2.0, 5.0 )\nv = base.div( 0.0, 5.0 )\nv = base.div( -0.0, 5.0 )\nv = base.div( NaN, NaN )\n","base.divf":"var v = base.divf( -1.0, 5.0 )\nv = base.divf( 2.0, 5.0 )\nv = base.divf( 0.0, 5.0 )\nv = base.divf( -0.0, 5.0 )\nv = base.divf( NaN, NaN )\n","base.dotcase":"var out = base.dotcase( 'Hello World!' )\nout = base.dotcase( 'I am a tiny little teapot' )\n","base.dists.arcsine.Arcsine":"var arcsine = base.dists.arcsine.Arcsine( 0.0, 1.0 );\narcsine.a\narcsine.b\narcsine.entropy\narcsine.kurtosis\narcsine.mean\narcsine.median\narcsine.mode\narcsine.skewness\narcsine.stdev\narcsine.variance\narcsine.cdf( 0.8 )\narcsine.logcdf( 0.8 )\narcsine.logpdf( 0.4 )\narcsine.pdf( 0.8 )\narcsine.quantile( 0.8 )\n","base.dists.arcsine.cdf":"var y = base.dists.arcsine.cdf( 9.0, 0.0, 10.0 )\ny = base.dists.arcsine.cdf( 0.5, 0.0, 2.0 )\ny = base.dists.arcsine.cdf( PINF, 2.0, 4.0 )\ny = base.dists.arcsine.cdf( NINF, 2.0, 4.0 )\ny = base.dists.arcsine.cdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.cdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.cdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.cdf( 2.0, 1.0, 0.0 )\n","base.dists.arcsine.cdf.factory":"var mycdf = base.dists.arcsine.cdf.factory( 0.0, 10.0 );\nvar y = mycdf( 0.5 )\ny = mycdf( 8.0 )\n","base.dists.arcsine.entropy":"var v = base.dists.arcsine.entropy( 0.0, 1.0 )\nv = base.dists.arcsine.entropy( 4.0, 12.0 )\nv = base.dists.arcsine.entropy( 2.0, 8.0 )\n","base.dists.arcsine.kurtosis":"var v = base.dists.arcsine.kurtosis( 0.0, 1.0 )\nv = base.dists.arcsine.kurtosis( 4.0, 12.0 )\nv = base.dists.arcsine.kurtosis( 2.0, 8.0 )\n","base.dists.arcsine.logcdf":"var y = base.dists.arcsine.logcdf( 9.0, 0.0, 10.0 )\ny = base.dists.arcsine.logcdf( 0.5, 0.0, 2.0 )\ny = base.dists.arcsine.logcdf( PINF, 2.0, 4.0 )\ny = base.dists.arcsine.logcdf( NINF, 2.0, 4.0 )\ny = base.dists.arcsine.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.logcdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.logcdf( 2.0, 1.0, 0.0 )\n","base.dists.arcsine.logcdf.factory":"var mylogcdf = base.dists.arcsine.logcdf.factory( 0.0, 10.0 );\nvar y = mylogcdf( 0.5 )\ny = mylogcdf( 8.0 )\n","base.dists.arcsine.logpdf":"var y = base.dists.arcsine.logpdf( 2.0, 0.0, 4.0 )\ny = base.dists.arcsine.logpdf( 5.0, 0.0, 4.0 )\ny = base.dists.arcsine.logpdf( 0.25, 0.0, 1.0 )\ny = base.dists.arcsine.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.logpdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.logpdf( 2.0, 3.0, 1.0 )\n","base.dists.arcsine.logpdf.factory":"var mylogPDF = base.dists.arcsine.logpdf.factory( 6.0, 7.0 );\nvar y = mylogPDF( 7.0 )\ny = mylogPDF( 5.0 )\n","base.dists.arcsine.mean":"var v = base.dists.arcsine.mean( 0.0, 1.0 )\nv = base.dists.arcsine.mean( 4.0, 12.0 )\nv = base.dists.arcsine.mean( 2.0, 8.0 )\n","base.dists.arcsine.median":"var v = base.dists.arcsine.median( 0.0, 1.0 )\nv = base.dists.arcsine.median( 4.0, 12.0 )\nv = base.dists.arcsine.median( 2.0, 8.0 )\n","base.dists.arcsine.mode":"var v = base.dists.arcsine.mode( 0.0, 1.0 )\nv = base.dists.arcsine.mode( 4.0, 12.0 )\nv = base.dists.arcsine.mode( 2.0, 8.0 )\n","base.dists.arcsine.pdf":"var y = base.dists.arcsine.pdf( 2.0, 0.0, 4.0 )\ny = base.dists.arcsine.pdf( 5.0, 0.0, 4.0 )\ny = base.dists.arcsine.pdf( 0.25, 0.0, 1.0 )\ny = base.dists.arcsine.pdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.pdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.pdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.pdf( 2.0, 3.0, 1.0 )\n","base.dists.arcsine.pdf.factory":"var myPDF = base.dists.arcsine.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 7.0 )\ny = myPDF( 5.0 )\n","base.dists.arcsine.quantile":"var y = base.dists.arcsine.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( 0.5, 0.0, 10.0 )\ny = base.dists.arcsine.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.quantile( 0.0, 0.0, NaN )\ny = base.dists.arcsine.quantile( 0.5, 2.0, 1.0 )\n","base.dists.arcsine.quantile.factory":"var myQuantile = base.dists.arcsine.quantile.factory( 0.0, 4.0 );\nvar y = myQuantile( 0.8 )\n","base.dists.arcsine.skewness":"var v = base.dists.arcsine.skewness( 0.0, 1.0 )\nv = base.dists.arcsine.skewness( 4.0, 12.0 )\nv = base.dists.arcsine.skewness( 2.0, 8.0 )\n","base.dists.arcsine.stdev":"var v = base.dists.arcsine.stdev( 0.0, 1.0 )\nv = base.dists.arcsine.stdev( 4.0, 12.0 )\nv = base.dists.arcsine.stdev( 2.0, 8.0 )\n","base.dists.arcsine.variance":"var v = base.dists.arcsine.variance( 0.0, 1.0 )\nv = base.dists.arcsine.variance( 4.0, 12.0 )\nv = base.dists.arcsine.variance( 2.0, 8.0 )\n","base.dists.bernoulli.Bernoulli":"var bernoulli = base.dists.bernoulli.Bernoulli( 0.6 );\nbernoulli.p\nbernoulli.entropy\nbernoulli.kurtosis\nbernoulli.mean\nbernoulli.median\nbernoulli.skewness\nbernoulli.stdev\nbernoulli.variance\nbernoulli.cdf( 0.5 )\nbernoulli.mgf( 3.0 )\nbernoulli.pmf( 0.0 )\nbernoulli.quantile( 0.7 )\n","base.dists.bernoulli.cdf":"var y = base.dists.bernoulli.cdf( 0.5, 0.5 )\ny = base.dists.bernoulli.cdf( 0.8, 0.1 )\ny = base.dists.bernoulli.cdf( -1.0, 0.4 )\ny = base.dists.bernoulli.cdf( 1.5, 0.4 )\ny = base.dists.bernoulli.cdf( NaN, 0.5 )\ny = base.dists.bernoulli.cdf( 0.0, NaN )\ny = base.dists.bernoulli.cdf( 2.0, 1.4 )\n","base.dists.bernoulli.cdf.factory":"var mycdf = base.dists.bernoulli.cdf.factory( 0.5 );\nvar y = mycdf( 3.0 )\ny = mycdf( 0.7 )\n","base.dists.bernoulli.entropy":"var v = base.dists.bernoulli.entropy( 0.1 )\nv = base.dists.bernoulli.entropy( 0.5 )\n","base.dists.bernoulli.kurtosis":"var v = base.dists.bernoulli.kurtosis( 0.1 )\nv = base.dists.bernoulli.kurtosis( 0.5 )\n","base.dists.bernoulli.mean":"var v = base.dists.bernoulli.mean( 0.1 )\nv = base.dists.bernoulli.mean( 0.5 )\n","base.dists.bernoulli.median":"var v = base.dists.bernoulli.median( 0.1 )\nv = base.dists.bernoulli.median( 0.8 )\n","base.dists.bernoulli.mgf":"var y = base.dists.bernoulli.mgf( 0.2, 0.5 )\ny = base.dists.bernoulli.mgf( 0.4, 0.5 )\ny = base.dists.bernoulli.mgf( NaN, 0.0 )\ny = base.dists.bernoulli.mgf( 0.0, NaN )\ny = base.dists.bernoulli.mgf( -2.0, -1.0 )\ny = base.dists.bernoulli.mgf( 0.2, 2.0 )\n","base.dists.bernoulli.mgf.factory":"var mymgf = base.dists.bernoulli.mgf.factory( 0.8 );\nvar y = mymgf( -0.2 )\n","base.dists.bernoulli.mode":"var v = base.dists.bernoulli.mode( 0.1 )\nv = base.dists.bernoulli.mode( 0.8 )\n","base.dists.bernoulli.pmf":"var y = base.dists.bernoulli.pmf( 1.0, 0.3 )\ny = base.dists.bernoulli.pmf( 0.0, 0.7 )\ny = base.dists.bernoulli.pmf( -1.0, 0.5 )\ny = base.dists.bernoulli.pmf( 0.0, NaN )\ny = base.dists.bernoulli.pmf( NaN, 0.5 )\ny = base.dists.bernoulli.pmf( 0.0, 1.5 )\n","base.dists.bernoulli.pmf.factory":"var mypmf = base.dists.bernoulli.pmf.factory( 0.5 );\nvar y = mypmf( 1.0 )\ny = mypmf( 0.0 )\n","base.dists.bernoulli.quantile":"var y = base.dists.bernoulli.quantile( 0.8, 0.4 )\ny = base.dists.bernoulli.quantile( 0.5, 0.4 )\ny = base.dists.bernoulli.quantile( 0.9, 0.1 )\ny = base.dists.bernoulli.quantile( -0.2, 0.1 )\ny = base.dists.bernoulli.quantile( NaN, 0.8 )\ny = base.dists.bernoulli.quantile( 0.4, NaN )\ny = base.dists.bernoulli.quantile( 0.5, -1.0 )\ny = base.dists.bernoulli.quantile( 0.5, 1.5 )\n","base.dists.bernoulli.quantile.factory":"var myquantile = base.dists.bernoulli.quantile.factory( 0.4 );\nvar y = myquantile( 0.4 )\ny = myquantile( 0.8 )\ny = myquantile( 1.0 )\n","base.dists.bernoulli.skewness":"var v = base.dists.bernoulli.skewness( 0.1 )\nv = base.dists.bernoulli.skewness( 0.5 )\n","base.dists.bernoulli.stdev":"var v = base.dists.bernoulli.stdev( 0.1 )\nv = base.dists.bernoulli.stdev( 0.5 )\n","base.dists.bernoulli.variance":"var v = base.dists.bernoulli.variance( 0.1 )\nv = base.dists.bernoulli.variance( 0.5 )\n","base.dists.beta.Beta":"var beta = base.dists.beta.Beta( 1.0, 1.0 );\nbeta.alpha\nbeta.beta\nbeta.entropy\nbeta.kurtosis\nbeta.mean\nbeta.median\nbeta.mode\nbeta.skewness\nbeta.stdev\nbeta.variance\nbeta.cdf( 0.8 )\nbeta.logcdf( 0.8 )\nbeta.logpdf( 1.0 )\nbeta.mgf( 3.14 )\nbeta.pdf( 1.0 )\nbeta.quantile( 0.8 )\n","base.dists.beta.cdf":"var y = base.dists.beta.cdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.cdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.cdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.cdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.cdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.cdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.beta.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.beta.cdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.cdf( 0.0, NaN, 1.0 )\ny = base.dists.beta.cdf( 0.0, 1.0, NaN )\n","base.dists.beta.cdf.factory":"var mycdf = base.dists.beta.cdf.factory( 0.5, 0.5 );\nvar y = mycdf( 0.8 )\ny = mycdf( 0.3 )\n","base.dists.beta.entropy":"var v = base.dists.beta.entropy( 1.0, 1.0 )\nv = base.dists.beta.entropy( 4.0, 12.0 )\nv = base.dists.beta.entropy( 8.0, 2.0 )\nv = base.dists.beta.entropy( 1.0, -0.1 )\nv = base.dists.beta.entropy( -0.1, 1.0 )\nv = base.dists.beta.entropy( 2.0, NaN )\nv = base.dists.beta.entropy( NaN, 2.0 )\n","base.dists.beta.kurtosis":"var v = base.dists.beta.kurtosis( 1.0, 1.0 )\nv = base.dists.beta.kurtosis( 4.0, 12.0 )\nv = base.dists.beta.kurtosis( 8.0, 2.0 )\nv = base.dists.beta.kurtosis( 1.0, -0.1 )\nv = base.dists.beta.kurtosis( -0.1, 1.0 )\nv = base.dists.beta.kurtosis( 2.0, NaN )\nv = base.dists.beta.kurtosis( NaN, 2.0 )\n","base.dists.beta.logcdf":"var y = base.dists.beta.logcdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.logcdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.logcdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.logcdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.logcdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.logcdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.beta.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.beta.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.beta.logcdf( 0.0, 1.0, NaN )\n","base.dists.beta.logcdf.factory":"var mylogcdf = base.dists.beta.logcdf.factory( 0.5, 0.5 );\nvar y = mylogcdf( 0.8 )\ny = mylogcdf( 0.3 )\n","base.dists.beta.logpdf":"var y = base.dists.beta.logpdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.logpdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.logpdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.logpdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.logpdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.logpdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.logpdf( 0.5, -1.0, 0.5 )\ny = base.dists.beta.logpdf( 0.5, 0.5, -1.0 )\ny = base.dists.beta.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.logpdf( 0.5, NaN, 1.0 )\ny = base.dists.beta.logpdf( 0.5, 1.0, NaN )\n","base.dists.beta.logpdf.factory":"var mylogpdf = base.dists.beta.logpdf.factory( 0.5, 0.5 );\nvar y = mylogpdf( 0.8 )\ny = mylogpdf( 0.3 )\n","base.dists.beta.mean":"var v = base.dists.beta.mean( 1.0, 1.0 )\nv = base.dists.beta.mean( 4.0, 12.0 )\nv = base.dists.beta.mean( 8.0, 2.0 )\n","base.dists.beta.median":"var v = base.dists.beta.median( 1.0, 1.0 )\nv = base.dists.beta.median( 4.0, 12.0 )\nv = base.dists.beta.median( 8.0, 2.0 )\nv = base.dists.beta.median( 1.0, -0.1 )\nv = base.dists.beta.median( -0.1, 1.0 )\nv = base.dists.beta.median( 2.0, NaN )\nv = base.dists.beta.median( NaN, 2.0 )\n","base.dists.beta.mgf":"var y = base.dists.beta.mgf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.mgf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.mgf( 3.0, 2.0, 2.0 )\ny = base.dists.beta.mgf( -0.8, 4.0, 4.0 )\ny = base.dists.beta.mgf( NaN, 1.0, 1.0 )\ny = base.dists.beta.mgf( 0.0, NaN, 1.0 )\ny = base.dists.beta.mgf( 0.0, 1.0, NaN )\ny = base.dists.beta.mgf( 2.0, -1.0, 0.5 )\ny = base.dists.beta.mgf( 2.0, 0.0, 0.5 )\ny = base.dists.beta.mgf( 2.0, 0.5, -1.0 )\ny = base.dists.beta.mgf( 2.0, 0.5, 0.0 )\n","base.dists.beta.mgf.factory":"var myMGF = base.dists.beta.mgf.factory( 0.5, 0.5 );\nvar y = myMGF( 0.8 )\ny = myMGF( 0.3 )\n","base.dists.beta.mode":"var v = base.dists.beta.mode( 4.0, 12.0 )\nv = base.dists.beta.mode( 8.0, 2.0 )\nv = base.dists.beta.mode( 1.0, 1.0 )\n","base.dists.beta.pdf":"var y = base.dists.beta.pdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.pdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.pdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.pdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.pdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.pdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.pdf( 0.5, -1.0, 0.5 )\ny = base.dists.beta.pdf( 0.5, 0.5, -1.0 )\ny = base.dists.beta.pdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.pdf( 0.5, NaN, 1.0 )\ny = base.dists.beta.pdf( 0.5, 1.0, NaN )\n","base.dists.beta.pdf.factory":"var mypdf = base.dists.beta.pdf.factory( 0.5, 0.5 );\nvar y = mypdf( 0.8 )\ny = mypdf( 0.3 )\n","base.dists.beta.quantile":"var y = base.dists.beta.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.beta.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.beta.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.beta.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.beta.quantile( NaN, 1.0, 1.0 )\ny = base.dists.beta.quantile( 0.5, NaN, 1.0 )\ny = base.dists.beta.quantile( 0.5, 1.0, NaN )\ny = base.dists.beta.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.beta.quantile( 0.5, 1.0, -1.0 )\n","base.dists.beta.quantile.factory":"var myquantile = base.dists.beta.quantile.factory( 2.0, 2.0 );\ny = myquantile( 0.8 )\ny = myquantile( 0.4 )\n","base.dists.beta.skewness":"var v = base.dists.beta.skewness( 1.0, 1.0 )\nv = base.dists.beta.skewness( 4.0, 12.0 )\nv = base.dists.beta.skewness( 8.0, 2.0 )\nv = base.dists.beta.skewness( 1.0, -0.1 )\nv = base.dists.beta.skewness( -0.1, 1.0 )\nv = base.dists.beta.skewness( 2.0, NaN )\nv = base.dists.beta.skewness( NaN, 2.0 )\n","base.dists.beta.stdev":"var v = base.dists.beta.stdev( 1.0, 1.0 )\nv = base.dists.beta.stdev( 4.0, 12.0 )\nv = base.dists.beta.stdev( 8.0, 2.0 )\nv = base.dists.beta.stdev( 1.0, -0.1 )\nv = base.dists.beta.stdev( -0.1, 1.0 )\nv = base.dists.beta.stdev( 2.0, NaN )\nv = base.dists.beta.stdev( NaN, 2.0 )\n","base.dists.beta.variance":"var v = base.dists.beta.variance( 1.0, 1.0 )\nv = base.dists.beta.variance( 4.0, 12.0 )\nv = base.dists.beta.variance( 8.0, 2.0 )\nv = base.dists.beta.variance( 1.0, -0.1 )\nv = base.dists.beta.variance( -0.1, 1.0 )\nv = base.dists.beta.variance( 2.0, NaN )\nv = base.dists.beta.variance( NaN, 2.0 )\n","base.dists.betaprime.BetaPrime":"var betaprime = base.dists.betaprime.BetaPrime( 6.0, 5.0 );\nbetaprime.alpha\nbetaprime.beta\nbetaprime.kurtosis\nbetaprime.mean\nbetaprime.mode\nbetaprime.skewness\nbetaprime.stdev\nbetaprime.variance\nbetaprime.cdf( 0.8 )\nbetaprime.logcdf( 0.8 )\nbetaprime.logpdf( 1.0 )\nbetaprime.pdf( 1.0 )\nbetaprime.quantile( 0.8 )\n","base.dists.betaprime.cdf":"var y = base.dists.betaprime.cdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.cdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.cdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.cdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.cdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.betaprime.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.betaprime.cdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.cdf( 0.0, NaN, 1.0 )\ny = base.dists.betaprime.cdf( 0.0, 1.0, NaN )\n","base.dists.betaprime.cdf.factory":"var mycdf = base.dists.betaprime.cdf.factory( 0.5, 0.5 );\nvar y = mycdf( 0.8 )\ny = mycdf( 0.3 )\n","base.dists.betaprime.kurtosis":"var v = base.dists.betaprime.kurtosis( 2.0, 6.0 )\nv = base.dists.betaprime.kurtosis( 4.0, 12.0 )\nv = base.dists.betaprime.kurtosis( 8.0, 6.0 )\nv = base.dists.betaprime.kurtosis( 1.0, 2.8 )\nv = base.dists.betaprime.kurtosis( 1.0, -0.1 )\nv = base.dists.betaprime.kurtosis( -0.1, 5.0 )\nv = base.dists.betaprime.kurtosis( 2.0, NaN )\nv = base.dists.betaprime.kurtosis( NaN, 6.0 )\n","base.dists.betaprime.logcdf":"var y = base.dists.betaprime.logcdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.logcdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.logcdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.logcdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.logcdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.betaprime.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.betaprime.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.betaprime.logcdf( 0.0, 1.0, NaN )\n","base.dists.betaprime.logcdf.factory":"var mylogcdf = base.dists.betaprime.logcdf.factory( 0.5, 0.5 );\nvar y = mylogcdf( 0.8 )\ny = mylogcdf( 0.3 )\n","base.dists.betaprime.logpdf":"var y = base.dists.betaprime.logpdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.logpdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.logpdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.logpdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.logpdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.logpdf( 0.5, -1.0, 0.5 )\ny = base.dists.betaprime.logpdf( 0.5, 0.5, -1.0 )\ny = base.dists.betaprime.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.logpdf( 0.5, NaN, 1.0 )\ny = base.dists.betaprime.logpdf( 0.5, 1.0, NaN )\n","base.dists.betaprime.logpdf.factory":"var mylogpdf = base.dists.betaprime.logpdf.factory( 0.5, 0.5 );\nvar y = mylogpdf( 0.8 )\ny = mylogpdf( 0.3 )\n","base.dists.betaprime.mean":"var v = base.dists.betaprime.mean( 1.0, 2.0 )\nv = base.dists.betaprime.mean( 4.0, 12.0 )\nv = base.dists.betaprime.mean( 8.0, 2.0 )\n","base.dists.betaprime.mode":"var v = base.dists.betaprime.mode( 1.0, 2.0 )\nv = base.dists.betaprime.mode( 4.0, 12.0 )\nv = base.dists.betaprime.mode( 8.0, 2.0 )\n","base.dists.betaprime.pdf":"var y = base.dists.betaprime.pdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.pdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.pdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.pdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.pdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.pdf( 0.5, -1.0, 0.5 )\ny = base.dists.betaprime.pdf( 0.5, 0.5, -1.0 )\ny = base.dists.betaprime.pdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.pdf( 0.5, NaN, 1.0 )\ny = base.dists.betaprime.pdf( 0.5, 1.0, NaN )\n","base.dists.betaprime.pdf.factory":"var mypdf = base.dists.betaprime.pdf.factory( 0.5, 0.5 );\nvar y = mypdf( 0.8 )\ny = mypdf( 0.3 )\n","base.dists.betaprime.quantile":"var y = base.dists.betaprime.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.betaprime.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.betaprime.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.betaprime.quantile( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, NaN, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, 1.0, NaN )\ny = base.dists.betaprime.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, 1.0, -1.0 )\n","base.dists.betaprime.quantile.factory":"var myQuantile = base.dists.betaprime.quantile.factory( 2.0, 2.0 );\ny = myQuantile( 0.8 )\ny = myQuantile( 0.4 )\n","base.dists.betaprime.skewness":"var v = base.dists.betaprime.skewness( 2.0, 4.0 )\nv = base.dists.betaprime.skewness( 4.0, 12.0 )\nv = base.dists.betaprime.skewness( 8.0, 4.0 )\nv = base.dists.betaprime.skewness( 1.0, 2.8 )\nv = base.dists.betaprime.skewness( 1.0, -0.1 )\nv = base.dists.betaprime.skewness( -0.1, 4.0 )\nv = base.dists.betaprime.skewness( 2.0, NaN )\nv = base.dists.betaprime.skewness( NaN, 4.0 )\n","base.dists.betaprime.stdev":"var v = base.dists.betaprime.stdev( 1.0, 2.5 )\nv = base.dists.betaprime.stdev( 4.0, 12.0 )\nv = base.dists.betaprime.stdev( 8.0, 2.5 )\nv = base.dists.betaprime.stdev( 8.0, 1.0 )\nv = base.dists.betaprime.stdev( 1.0, -0.1 )\nv = base.dists.betaprime.stdev( -0.1, 3.0 )\nv = base.dists.betaprime.stdev( 2.0, NaN )\nv = base.dists.betaprime.stdev( NaN, 3.0 )\n","base.dists.betaprime.variance":"var v = base.dists.betaprime.variance( 1.0, 2.5 )\nv = base.dists.betaprime.variance( 4.0, 12.0 )\nv = base.dists.betaprime.variance( 8.0, 2.5 )\nv = base.dists.betaprime.variance( 8.0, 1.0 )\nv = base.dists.betaprime.variance( 1.0, -0.1 )\nv = base.dists.betaprime.variance( -0.1, 3.0 )\nv = base.dists.betaprime.variance( 2.0, NaN )\nv = base.dists.betaprime.variance( NaN, 3.0 )\n","base.dists.binomial.Binomial":"var binomial = base.dists.binomial.Binomial( 8, 0.5 );\nbinomial.n\nbinomial.p\nbinomial.kurtosis\nbinomial.mean\nbinomial.median\nbinomial.mode\nbinomial.skewness\nbinomial.stdev\nbinomial.variance\nbinomial.cdf( 2.9 )\nbinomial.logpmf( 3.0 )\nbinomial.mgf( 0.2 )\nbinomial.pmf( 3.0 )\nbinomial.quantile( 0.8 )\n","base.dists.binomial.cdf":"var y = base.dists.binomial.cdf( 3.0, 20, 0.2 )\ny = base.dists.binomial.cdf( 21.0, 20, 0.2 )\ny = base.dists.binomial.cdf( 5.0, 10, 0.4 )\ny = base.dists.binomial.cdf( 0.0, 10, 0.4 )\ny = base.dists.binomial.cdf( NaN, 20, 0.5 )\ny = base.dists.binomial.cdf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.cdf( 0.0, 20, NaN )\ny = base.dists.binomial.cdf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.cdf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.cdf( 2.0, 20, -1.0 )\ny = base.dists.binomial.cdf( 2.0, 20, 1.5 )\n","base.dists.binomial.cdf.factory":"var mycdf = base.dists.binomial.cdf.factory( 10, 0.5 );\nvar y = mycdf( 3.0 )\ny = mycdf( 1.0 )\n","base.dists.binomial.entropy":"var v = base.dists.binomial.entropy( 100, 0.1 )\nv = base.dists.binomial.entropy( 20, 0.5 )\nv = base.dists.binomial.entropy( 10.3, 0.5 )\nv = base.dists.binomial.entropy( 20, 1.1 )\nv = base.dists.binomial.entropy( 20, NaN )\n","base.dists.binomial.kurtosis":"var v = base.dists.binomial.kurtosis( 100, 0.1 )\nv = base.dists.binomial.kurtosis( 20, 0.5 )\nv = base.dists.binomial.kurtosis( 10.3, 0.5 )\nv = base.dists.binomial.kurtosis( 20, 1.1 )\nv = base.dists.binomial.kurtosis( 20, NaN )\n","base.dists.binomial.logpmf":"var y = base.dists.binomial.logpmf( 3.0, 20, 0.2 )\ny = base.dists.binomial.logpmf( 21.0, 20, 0.2 )\ny = base.dists.binomial.logpmf( 5.0, 10, 0.4 )\ny = base.dists.binomial.logpmf( 0.0, 10, 0.4 )\ny = base.dists.binomial.logpmf( NaN, 20, 0.5 )\ny = base.dists.binomial.logpmf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.logpmf( 0.0, 20, NaN )\ny = base.dists.binomial.logpmf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.logpmf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.logpmf( 2.0, 20, -1.0 )\ny = base.dists.binomial.logpmf( 2.0, 20, 1.5 )\n","base.dists.binomial.logpmf.factory":"var mylogpmf = base.dists.binomial.logpmf.factory( 10, 0.5 );\nvar y = mylogpmf( 3.0 )\ny = mylogpmf( 5.0 )\n","base.dists.binomial.mean":"var v = base.dists.binomial.mean( 100, 0.1 )\nv = base.dists.binomial.mean( 20, 0.5 )\nv = base.dists.binomial.mean( 10.3, 0.5 )\nv = base.dists.binomial.mean( 20, 1.1 )\nv = base.dists.binomial.mean( 20, NaN )\n","base.dists.binomial.median":"var v = base.dists.binomial.median( 100, 0.1 )\nv = base.dists.binomial.median( 20, 0.5 )\nv = base.dists.binomial.median( 10.3, 0.5 )\nv = base.dists.binomial.median( 20, 1.1 )\nv = base.dists.binomial.median( 20, NaN )\n","base.dists.binomial.mgf":"var y = base.dists.binomial.mgf( 0.5, 20, 0.2 )\ny = base.dists.binomial.mgf( 5.0, 20, 0.2 )\ny = base.dists.binomial.mgf( 0.9, 10, 0.4 )\ny = base.dists.binomial.mgf( 0.0, 10, 0.4 )\ny = base.dists.binomial.mgf( NaN, 20, 0.5 )\ny = base.dists.binomial.mgf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.mgf( 0.0, 20, NaN )\ny = base.dists.binomial.mgf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.mgf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.mgf( 2.0, 20, -1.0 )\ny = base.dists.binomial.mgf( 2.0, 20, 1.5 )\n","base.dists.binomial.mgf.factory":"var myMGF = base.dists.binomial.mgf.factory( 10, 0.5 );\nvar y = myMGF( 0.3 )\n","base.dists.binomial.mode":"var v = base.dists.binomial.mode( 100, 0.1 )\nv = base.dists.binomial.mode( 20, 0.5 )\nv = base.dists.binomial.mode( 10.3, 0.5 )\nv = base.dists.binomial.mode( 20, 1.1 )\nv = base.dists.binomial.mode( 20, NaN )\n","base.dists.binomial.pmf":"var y = base.dists.binomial.pmf( 3.0, 20, 0.2 )\ny = base.dists.binomial.pmf( 21.0, 20, 0.2 )\ny = base.dists.binomial.pmf( 5.0, 10, 0.4 )\ny = base.dists.binomial.pmf( 0.0, 10, 0.4 )\ny = base.dists.binomial.pmf( NaN, 20, 0.5 )\ny = base.dists.binomial.pmf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.pmf( 0.0, 20, NaN )\ny = base.dists.binomial.pmf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.pmf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.pmf( 2.0, 20, -1.0 )\ny = base.dists.binomial.pmf( 2.0, 20, 1.5 )\n","base.dists.binomial.pmf.factory":"var mypmf = base.dists.binomial.pmf.factory( 10, 0.5 );\nvar y = mypmf( 3.0 )\ny = mypmf( 5.0 )\n","base.dists.binomial.quantile":"var y = base.dists.binomial.quantile( 0.4, 20, 0.2 )\ny = base.dists.binomial.quantile( 0.8, 20, 0.2 )\ny = base.dists.binomial.quantile( 0.5, 10, 0.4 )\ny = base.dists.binomial.quantile( 0.0, 10, 0.4 )\ny = base.dists.binomial.quantile( 1.0, 10, 0.4 )\ny = base.dists.binomial.quantile( NaN, 20, 0.5 )\ny = base.dists.binomial.quantile( 0.2, NaN, 0.5 )\ny = base.dists.binomial.quantile( 0.2, 20, NaN )\ny = base.dists.binomial.quantile( 0.5, 1.5, 0.5 )\ny = base.dists.binomial.quantile( 0.5, -2.0, 0.5 )\ny = base.dists.binomial.quantile( 0.5, 20, -1.0 )\ny = base.dists.binomial.quantile( 0.5, 20, 1.5 )\n","base.dists.binomial.quantile.factory":"var myquantile = base.dists.binomial.quantile.factory( 10, 0.5 );\nvar y = myquantile( 0.1 )\ny = myquantile( 0.9 )\n","base.dists.binomial.skewness":"var v = base.dists.binomial.skewness( 100, 0.1 )\nv = base.dists.binomial.skewness( 20, 0.5 )\nv = base.dists.binomial.skewness( 10.3, 0.5 )\nv = base.dists.binomial.skewness( 20, 1.1 )\nv = base.dists.binomial.skewness( 20, NaN )\n","base.dists.binomial.stdev":"var v = base.dists.binomial.stdev( 100, 0.1 )\nv = base.dists.binomial.stdev( 20, 0.5 )\nv = base.dists.binomial.stdev( 10.3, 0.5 )\nv = base.dists.binomial.stdev( 20, 1.1 )\nv = base.dists.binomial.stdev( 20, NaN )\n","base.dists.binomial.variance":"var v = base.dists.binomial.variance( 100, 0.1 )\nv = base.dists.binomial.variance( 20, 0.5 )\nv = base.dists.binomial.variance( 10.3, 0.5 )\nv = base.dists.binomial.variance( 20, 1.1 )\nv = base.dists.binomial.variance( 20, NaN )\n","base.dists.cauchy.Cauchy":"var cauchy = base.dists.cauchy.Cauchy( 0.0, 1.0 );\ncauchy.x0\ncauchy.gamma\ncauchy.entropy\ncauchy.median\ncauchy.mode\ncauchy.cdf( 0.8 )\ncauchy.logcdf( 1.0 )\ncauchy.logpdf( 1.0 )\ncauchy.pdf( 1.0 )\ncauchy.quantile( 0.8 )\n","base.dists.cauchy.cdf":"var y = base.dists.cauchy.cdf( 4.0, 0.0, 2.0 )\ny = base.dists.cauchy.cdf( 1.0, 0.0, 2.0 )\ny = base.dists.cauchy.cdf( 1.0, 3.0, 2.0 )\ny = base.dists.cauchy.cdf( NaN, 0.0, 2.0 )\ny = base.dists.cauchy.cdf( 1.0, 2.0, NaN )\ny = base.dists.cauchy.cdf( 1.0, NaN, 3.0 )\n","base.dists.cauchy.cdf.factory":"var myCDF = base.dists.cauchy.cdf.factory( 1.5, 3.0 );\nvar y = myCDF( 1.0 )\n","base.dists.cauchy.entropy":"var v = base.dists.cauchy.entropy( 10.0, 7.0 )\nv = base.dists.cauchy.entropy( 22.0, 0.5 )\nv = base.dists.cauchy.entropy( 10.3, -0.5 )\n","base.dists.cauchy.logcdf":"var y = base.dists.cauchy.logcdf( 4.0, 0.0, 2.0 )\ny = base.dists.cauchy.logcdf( 1.0, 0.0, 2.0 )\ny = base.dists.cauchy.logcdf( 1.0, 3.0, 2.0 )\ny = base.dists.cauchy.logcdf( NaN, 0.0, 2.0 )\ny = base.dists.cauchy.logcdf( 1.0, 2.0, NaN )\ny = base.dists.cauchy.logcdf( 1.0, NaN, 3.0 )\n","base.dists.cauchy.logcdf.factory":"var mylogCDF = base.dists.cauchy.logcdf.factory( 1.5, 3.0 );\nvar y = mylogCDF( 1.0 )\n","base.dists.cauchy.logpdf":"var y = base.dists.cauchy.logpdf( 2.0, 1.0, 1.0 )\ny = base.dists.cauchy.logpdf( 4.0, 3.0, 0.1 )\ny = base.dists.cauchy.logpdf( 4.0, 3.0, 3.0 )\ny = base.dists.cauchy.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.cauchy.logpdf( 2.0, NaN, 1.0 )\ny = base.dists.cauchy.logpdf( 2.0, 1.0, NaN )\ny = base.dists.cauchy.logpdf( 2.0, 1.0, -2.0 )\n","base.dists.cauchy.logpdf.factory":"var mylogPDF = base.dists.cauchy.logpdf.factory( 10.0, 2.0 );\nvar y = mylogPDF( 10.0 )\n","base.dists.cauchy.median":"var v = base.dists.cauchy.median( 10.0, 5.0 )\nv = base.dists.cauchy.median( 7.0, 0.5 )\nv = base.dists.cauchy.median( 10.3, -0.5 )\n","base.dists.cauchy.mode":"var v = base.dists.cauchy.mode( 10.0, 5.0 )\nv = base.dists.cauchy.mode( 7.0, 0.5 )\nv = base.dists.cauchy.mode( 10.3, -0.5 )\n","base.dists.cauchy.pdf":"var y = base.dists.cauchy.pdf( 2.0, 1.0, 1.0 )\ny = base.dists.cauchy.pdf( 4.0, 3.0, 0.1 )\ny = base.dists.cauchy.pdf( 4.0, 3.0, 3.0 )\ny = base.dists.cauchy.pdf( NaN, 1.0, 1.0 )\ny = base.dists.cauchy.pdf( 2.0, NaN, 1.0 )\ny = base.dists.cauchy.pdf( 2.0, 1.0, NaN )\ny = base.dists.cauchy.pdf( 2.0, 1.0, -2.0 )\n","base.dists.cauchy.pdf.factory":"var myPDF = base.dists.cauchy.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\n","base.dists.cauchy.quantile":"var y = base.dists.cauchy.quantile( 0.3, 2.0, 2.0 )\ny = base.dists.cauchy.quantile( 0.8, 10, 2.0 )\ny = base.dists.cauchy.quantile( 0.1, 10.0, 2.0 )\ny = base.dists.cauchy.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.cauchy.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.cauchy.quantile( NaN, 0.0, 1.0 )\ny = base.dists.cauchy.quantile( 0.0, NaN, 1.0 )\ny = base.dists.cauchy.quantile( 0.0, 0.0, NaN )\ny = base.dists.cauchy.quantile( 0.5, 0.0, -1.0 )\n","base.dists.cauchy.quantile.factory":"var myQuantile = base.dists.cauchy.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.chi.cdf":"var y = base.dists.chi.cdf( 2.0, 3.0 )\ny = base.dists.chi.cdf( 1.0, 0.5 )\ny = base.dists.chi.cdf( -1.0, 4.0 )\ny = base.dists.chi.cdf( NaN, 1.0 )\ny = base.dists.chi.cdf( 0.0, NaN )\ny = base.dists.chi.cdf( 2.0, -1.0 )\ny = base.dists.chi.cdf( 2.0, 0.0 )\ny = base.dists.chi.cdf( -2.0, 0.0 )\ny = base.dists.chi.cdf( 0.0, 0.0 )\n","base.dists.chi.cdf.factory":"var mycdf = base.dists.chi.cdf.factory( 1.0 );\nvar y = mycdf( 2.0 )\ny = mycdf( 1.2 )\n","base.dists.chi.Chi":"var chi = base.dists.chi.Chi( 6.0 );\nchi.k\nchi.entropy\nchi.kurtosis\nchi.mean\nchi.mode\nchi.skewness\nchi.stdev\nchi.variance\nchi.cdf( 1.0 )\nchi.logpdf( 1.5 )\nchi.pdf( 1.5 )\nchi.quantile( 0.5 )\n","base.dists.chi.entropy":"var v = base.dists.chi.entropy( 11.0 )\nv = base.dists.chi.entropy( 1.5 )\n","base.dists.chi.kurtosis":"var v = base.dists.chi.kurtosis( 9.0 )\nv = base.dists.chi.kurtosis( 1.5 )\n","base.dists.chi.logpdf":"var y = base.dists.chi.logpdf( 0.3, 4.0 )\ny = base.dists.chi.logpdf( 0.7, 0.7 )\ny = base.dists.chi.logpdf( -1.0, 0.5 )\ny = base.dists.chi.logpdf( 0.0, NaN )\ny = base.dists.chi.logpdf( NaN, 2.0 )\ny = base.dists.chi.logpdf( 2.0, -1.0 )\ny = base.dists.chi.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.chi.logpdf( 0.0, 0.0, 2.0 )\n","base.dists.chi.logpdf.factory":"var mylogPDF = base.dists.chi.logpdf.factory( 6.0 );\nvar y = mylogPDF( 3.0 )\n","base.dists.chi.mean":"var v = base.dists.chi.mean( 11.0 )\nv = base.dists.chi.mean( 4.5 )\n","base.dists.chi.mode":"var v = base.dists.chi.mode( 11.0 )\nv = base.dists.chi.mode( 1.5 )\n","base.dists.chi.pdf":"var y = base.dists.chi.pdf( 0.3, 4.0 )\ny = base.dists.chi.pdf( 0.7, 0.7 )\ny = base.dists.chi.pdf( -1.0, 0.5 )\ny = base.dists.chi.pdf( 0.0, NaN )\ny = base.dists.chi.pdf( NaN, 2.0 )\ny = base.dists.chi.pdf( 2.0, -1.0 )\ny = base.dists.chi.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.chi.pdf( 0.0, 0.0, 2.0 )\n","base.dists.chi.pdf.factory":"var myPDF = base.dists.chi.pdf.factory( 6.0 );\nvar y = myPDF( 3.0 )\n","base.dists.chi.quantile":"var y = base.dists.chi.quantile( 0.8, 1.0 )\ny = base.dists.chi.quantile( 0.5, 4.0 )\ny = base.dists.chi.quantile( 0.8, 0.1 )\ny = base.dists.chi.quantile( -0.2, 0.5 )\ny = base.dists.chi.quantile( 1.1, 0.5 )\ny = base.dists.chi.quantile( NaN, 1.0 )\ny = base.dists.chi.quantile( 0.0, NaN )\ny = base.dists.chi.quantile( 0.5, -1.0 )\ny = base.dists.chi.quantile( 0.3, 0.0 )\ny = base.dists.chi.quantile( 0.9, 0.0 )\n","base.dists.chi.quantile.factory":"var myquantile = base.dists.chi.quantile.factory( 2.0 );\nvar y = myquantile( 0.3 )\ny = myquantile( 0.7 )\n","base.dists.chi.skewness":"var v = base.dists.chi.skewness( 11.0 )\nv = base.dists.chi.skewness( 1.5 )\n","base.dists.chi.stdev":"var v = base.dists.chi.stdev( 11.0 )\nv = base.dists.chi.stdev( 1.5 )\n","base.dists.chi.variance":"var v = base.dists.chi.variance( 11.0 )\nv = base.dists.chi.variance( 1.5 )\n","base.dists.chisquare.cdf":"var y = base.dists.chisquare.cdf( 2.0, 3.0 )\ny = base.dists.chisquare.cdf( 1.0, 0.5 )\ny = base.dists.chisquare.cdf( -1.0, 4.0 )\ny = base.dists.chisquare.cdf( NaN, 1.0 )\ny = base.dists.chisquare.cdf( 0.0, NaN )\ny = base.dists.chisquare.cdf( 2.0, -1.0 )\ny = base.dists.chisquare.cdf( 2.0, 0.0 )\ny = base.dists.chisquare.cdf( -2.0, 0.0 )\ny = base.dists.chisquare.cdf( 0.0, 0.0 )\n","base.dists.chisquare.cdf.factory":"var mycdf = base.dists.chisquare.cdf.factory( 1.0 );\nvar y = mycdf( 2.0 )\ny = mycdf( 1.2 )\n","base.dists.chisquare.ChiSquare":"var chisquare = base.dists.chisquare.ChiSquare( 6.0 );\nchisquare.k\nchisquare.entropy\nchisquare.kurtosis\nchisquare.mean\nchisquare.median\nchisquare.mode\nchisquare.skewness\nchisquare.stdev\nchisquare.variance\nchisquare.cdf( 3.0 )\nchisquare.mgf( 0.2 )\nchisquare.pdf( 1.5 )\nchisquare.quantile( 0.5 )\n","base.dists.chisquare.entropy":"var v = base.dists.chisquare.entropy( 11.0 )\nv = base.dists.chisquare.entropy( 1.5 )\n","base.dists.chisquare.kurtosis":"var v = base.dists.chisquare.kurtosis( 9.0 )\nv = base.dists.chisquare.kurtosis( 1.5 )\n","base.dists.chisquare.logpdf":"var y = base.dists.chisquare.logpdf( 0.3, 4.0 )\ny = base.dists.chisquare.logpdf( 0.7, 0.7 )\ny = base.dists.chisquare.logpdf( -1.0, 0.5 )\ny = base.dists.chisquare.logpdf( 0.0, NaN )\ny = base.dists.chisquare.logpdf( NaN, 2.0 )\ny = base.dists.chisquare.logpdf( 2.0, -1.0 )\ny = base.dists.chisquare.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.chisquare.logpdf( 0.0, 0.0, 2.0 )\n","base.dists.chisquare.logpdf.factory":"var myLogPDF = base.dists.chisquare.logpdf.factory( 6.0 );\nvar y = myLogPDF( 3.0 )\n","base.dists.chisquare.mean":"var v = base.dists.chisquare.mean( 11.0 )\nv = base.dists.chisquare.mean( 4.5 )\n","base.dists.chisquare.median":"var k = base.dists.chisquare.median( 9.0 )\nk = base.dists.chisquare.median( 2.0 )\n","base.dists.chisquare.mgf":"var y = base.dists.chisquare.mgf( 0.4, 2 )\ny = base.dists.chisquare.mgf( -1.0, 5.0 )\ny = base.dists.chisquare.mgf( 0.0, 10.0 )\n","base.dists.chisquare.mgf.factory":"var mymgf = base.dists.chisquare.mgf.factory( 1.0 );\nvar y = mymgf( 0.2 )\ny = mymgf( 0.4 )\n","base.dists.chisquare.mode":"var v = base.dists.chisquare.mode( 11.0 )\nv = base.dists.chisquare.mode( 1.5 )\n","base.dists.chisquare.pdf":"var y = base.dists.chisquare.pdf( 0.3, 4.0 )\ny = base.dists.chisquare.pdf( 0.7, 0.7 )\ny = base.dists.chisquare.pdf( -1.0, 0.5 )\ny = base.dists.chisquare.pdf( 0.0, NaN )\ny = base.dists.chisquare.pdf( NaN, 2.0 )\ny = base.dists.chisquare.pdf( 2.0, -1.0 )\ny = base.dists.chisquare.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.chisquare.pdf( 0.0, 0.0, 2.0 )\n","base.dists.chisquare.pdf.factory":"var myPDF = base.dists.chisquare.pdf.factory( 6.0 );\nvar y = myPDF( 3.0 )\n","base.dists.chisquare.quantile":"var y = base.dists.chisquare.quantile( 0.8, 1.0 )\ny = base.dists.chisquare.quantile( 0.5, 4.0 )\ny = base.dists.chisquare.quantile( 0.8, 0.1 )\ny = base.dists.chisquare.quantile( -0.2, 0.5 )\ny = base.dists.chisquare.quantile( 1.1, 0.5 )\ny = base.dists.chisquare.quantile( NaN, 1.0 )\ny = base.dists.chisquare.quantile( 0.0, NaN )\ny = base.dists.chisquare.quantile( 0.5, -1.0 )\ny = base.dists.chisquare.quantile( 0.3, 0.0 )\ny = base.dists.chisquare.quantile( 0.9, 0.0 )\n","base.dists.chisquare.quantile.factory":"var myquantile = base.dists.chisquare.quantile.factory( 2.0 );\nvar y = myquantile( 0.3 )\ny = myquantile( 0.7 )\n","base.dists.chisquare.skewness":"var v = base.dists.chisquare.skewness( 11.0 )\nv = base.dists.chisquare.skewness( 1.5 )\n","base.dists.chisquare.stdev":"var v = base.dists.chisquare.stdev( 11.0 )\nv = base.dists.chisquare.stdev( 1.5 )\n","base.dists.chisquare.variance":"var v = base.dists.chisquare.variance( 11.0 )\nv = base.dists.chisquare.variance( 1.5 )\n","base.dists.cosine.cdf":"var y = base.dists.cosine.cdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.cdf( 9.0, 10.0, 3.0 )\ny = base.dists.cosine.cdf( 2.0, 0.0, NaN )\ny = base.dists.cosine.cdf( 2.0, NaN, 1.0 )\ny = base.dists.cosine.cdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.cdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.cdf( 8.0, 8.0, 0.0 )\ny = base.dists.cosine.cdf( 10.0, 8.0, 0.0 )\n","base.dists.cosine.cdf.factory":"var mycdf = base.dists.cosine.cdf.factory( 3.0, 1.5 );\nvar y = mycdf( 1.9 )\n","base.dists.cosine.Cosine":"var cosine = base.dists.cosine.Cosine( -2.0, 3.0 );\ncosine.mu\ncosine.s\ncosine.kurtosis\ncosine.mean\ncosine.median\ncosine.mode\ncosine.skewness\ncosine.stdev\ncosine.variance\ncosine.cdf( 0.5 )\ncosine.logcdf( 0.5 )\ncosine.logpdf( -1.0 )\ncosine.mgf( 0.2 )\ncosine.pdf( -2.0 )\ncosine.quantile( 0.9 )\n","base.dists.cosine.kurtosis":"var y = base.dists.cosine.kurtosis( 0.0, 1.0 )\ny = base.dists.cosine.kurtosis( 4.0, 2.0 )\ny = base.dists.cosine.kurtosis( NaN, 1.0 )\ny = base.dists.cosine.kurtosis( 0.0, NaN )\ny = base.dists.cosine.kurtosis( 0.0, 0.0 )\n","base.dists.cosine.logcdf":"var y = base.dists.cosine.logcdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.logcdf( 9.0, 10.0, 3.0 )\ny = base.dists.cosine.logcdf( 2.0, 0.0, NaN )\ny = base.dists.cosine.logcdf( 2.0, NaN, 1.0 )\ny = base.dists.cosine.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.logcdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.logcdf( 8.0, 8.0, 0.0 )\ny = base.dists.cosine.logcdf( 10.0, 8.0, 0.0 )\n","base.dists.cosine.logcdf.factory":"var mylogcdf = base.dists.cosine.logcdf.factory( 3.0, 1.5 );\nvar y = mylogcdf( 1.9 )\n","base.dists.cosine.logpdf":"var y = base.dists.cosine.logpdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.logpdf( -1.0, 2.0, 4.0 )\ny = base.dists.cosine.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.cosine.logpdf( 0.0, 0.0, NaN )\ny = base.dists.cosine.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.cosine.logpdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.logpdf( 8.0, 8.0, 0.0 )\n","base.dists.cosine.logpdf.factory":"var mylogpdf = base.dists.cosine.logpdf.factory( 10.0, 2.0 );\nvar y = mylogpdf( 10.0 )\n","base.dists.cosine.mean":"var y = base.dists.cosine.mean( 0.0, 1.0 )\ny = base.dists.cosine.mean( 4.0, 2.0 )\ny = base.dists.cosine.mean( NaN, 1.0 )\ny = base.dists.cosine.mean( 0.0, NaN )\ny = base.dists.cosine.mean( 0.0, 0.0 )\n","base.dists.cosine.median":"var y = base.dists.cosine.median( 0.0, 1.0 )\ny = base.dists.cosine.median( 4.0, 2.0 )\ny = base.dists.cosine.median( NaN, 1.0 )\ny = base.dists.cosine.median( 0.0, NaN )\ny = base.dists.cosine.median( 0.0, 0.0 )\n","base.dists.cosine.mgf":"var y = base.dists.cosine.mgf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.mgf( 9.0, 10.0, 3.0 )\ny = base.dists.cosine.mgf( 0.5, 0.0, NaN )\ny = base.dists.cosine.mgf( 0.5, NaN, 1.0 )\ny = base.dists.cosine.mgf( NaN, 0.0, 1.0 )\n","base.dists.cosine.mgf.factory":"var mymgf = base.dists.cosine.mgf.factory( 3.0, 1.5 );\nvar y = mymgf( 1.9 )\n","base.dists.cosine.mode":"var y = base.dists.cosine.mode( 0.0, 1.0 )\ny = base.dists.cosine.mode( 4.0, 2.0 )\ny = base.dists.cosine.mode( NaN, 1.0 )\ny = base.dists.cosine.mode( 0.0, NaN )\ny = base.dists.cosine.mode( 0.0, 0.0 )\n","base.dists.cosine.pdf":"var y = base.dists.cosine.pdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.pdf( 2.4, 4.0, 2.0 )\ny = base.dists.cosine.pdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.pdf( 0.0, NaN, 1.0 )\ny = base.dists.cosine.pdf( 0.0, 0.0, NaN )\ny = base.dists.cosine.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.cosine.pdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.pdf( 8.0, 8.0, 0.0 )\n","base.dists.cosine.pdf.factory":"var myPDF = base.dists.cosine.pdf.factory( 0.0, 3.0 );\nvar y = myPDF( 2.0 )\n","base.dists.cosine.quantile":"var y = base.dists.cosine.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.cosine.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.cosine.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.cosine.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.cosine.quantile( NaN, 0.0, 1.0 )\ny = base.dists.cosine.quantile( 0.0, NaN, 1.0 )\ny = base.dists.cosine.quantile( 0.0, 0.0, NaN )\ny = base.dists.cosine.quantile( 0.5, 0.0, -1.0 )\n","base.dists.cosine.quantile.factory":"var myQuantile = base.dists.cosine.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.3 )\n","base.dists.cosine.skewness":"var y = base.dists.cosine.skewness( 0.0, 1.0 )\ny = base.dists.cosine.skewness( 4.0, 2.0 )\ny = base.dists.cosine.skewness( NaN, 1.0 )\ny = base.dists.cosine.skewness( 0.0, NaN )\ny = base.dists.cosine.skewness( 0.0, 0.0 )\n","base.dists.cosine.stdev":"var y = base.dists.cosine.stdev( 0.0, 1.0 )\ny = base.dists.cosine.stdev( 4.0, 2.0 )\ny = base.dists.cosine.stdev( NaN, 1.0 )\ny = base.dists.cosine.stdev( 0.0, NaN )\ny = base.dists.cosine.stdev( 0.0, 0.0 )\n","base.dists.cosine.variance":"var y = base.dists.cosine.variance( 0.0, 1.0 )\ny = base.dists.cosine.variance( 4.0, 2.0 )\ny = base.dists.cosine.variance( NaN, 1.0 )\ny = base.dists.cosine.variance( 0.0, NaN )\ny = base.dists.cosine.variance( 0.0, 0.0 )\n","base.dists.degenerate.cdf":"var y = base.dists.degenerate.cdf( 2.0, 3.0 )\ny = base.dists.degenerate.cdf( 4.0, 3.0 )\ny = base.dists.degenerate.cdf( 3.0, 3.0 )\ny = base.dists.degenerate.cdf( NaN, 0.0 )\ny = base.dists.degenerate.cdf( 0.0, NaN )\n","base.dists.degenerate.cdf.factory":"var myCDF = base.dists.degenerate.cdf.factory( 5.0 );\nvar y = myCDF( 3.0 )\ny = myCDF( 6.0 )\n","base.dists.degenerate.Degenerate":"var degenerate = base.dists.degenerate.Degenerate( 2.0 );\ndegenerate.mu\ndegenerate.entropy\ndegenerate.mean\ndegenerate.mode\ndegenerate.median\ndegenerate.stdev\ndegenerate.variance\ndegenerate.cdf( 0.5 )\ndegenerate.logcdf( 2.5 )\ndegenerate.logpdf( 0.5 )\ndegenerate.logpmf( 2.5 )\ndegenerate.mgf( 0.2 )\ndegenerate.pdf( 2.0 )\ndegenerate.pmf( 2.0 )\ndegenerate.quantile( 0.7 )\n","base.dists.degenerate.entropy":"var v = base.dists.degenerate.entropy( 20.0 )\nv = base.dists.degenerate.entropy( -10.0 )\n","base.dists.degenerate.logcdf":"var y = base.dists.degenerate.logcdf( 2.0, 3.0 )\ny = base.dists.degenerate.logcdf( 4.0, 3.0 )\ny = base.dists.degenerate.logcdf( 3.0, 3.0 )\ny = base.dists.degenerate.logcdf( NaN, 0.0 )\ny = base.dists.degenerate.logcdf( 0.0, NaN )\n","base.dists.degenerate.logcdf.factory":"var mylogcdf = base.dists.degenerate.logcdf.factory( 5.0 );\nvar y = mylogcdf( 3.0 )\ny = mylogcdf( 6.0 )\n","base.dists.degenerate.logpdf":"var y = base.dists.degenerate.logpdf( 2.0, 3.0 )\ny = base.dists.degenerate.logpdf( 3.0, 3.0 )\ny = base.dists.degenerate.logpdf( NaN, 0.0 )\ny = base.dists.degenerate.logpdf( 0.0, NaN )\n","base.dists.degenerate.logpdf.factory":"var mylogPDF = base.dists.degenerate.logpdf.factory( 10.0 );\nvar y = mylogPDF( 10.0 )\n","base.dists.degenerate.logpmf":"var y = base.dists.degenerate.logpmf( 2.0, 3.0 )\ny = base.dists.degenerate.logpmf( 3.0, 3.0 )\ny = base.dists.degenerate.logpmf( NaN, 0.0 )\ny = base.dists.degenerate.logpmf( 0.0, NaN )\n","base.dists.degenerate.logpmf.factory":"var mylogPMF = base.dists.degenerate.logpmf.factory( 10.0 );\nvar y = mylogPMF( 10.0 )\n","base.dists.degenerate.mean":"var v = base.dists.degenerate.mean( 20.0 )\nv = base.dists.degenerate.mean( -10.0 )\n","base.dists.degenerate.median":"var v = base.dists.degenerate.median( 20.0 )\nv = base.dists.degenerate.median( -10.0 )\n","base.dists.degenerate.mgf":"var y = base.dists.degenerate.mgf( 1.0, 1.0 )\ny = base.dists.degenerate.mgf( 2.0, 3.0 )\ny = base.dists.degenerate.mgf( NaN, 0.0 )\ny = base.dists.degenerate.mgf( 0.0, NaN )\n","base.dists.degenerate.mgf.factory":"var myMGF = base.dists.degenerate.mgf.factory( 10.0 );\nvar y = myMGF( 0.1 )\n","base.dists.degenerate.mode":"var v = base.dists.degenerate.mode( 20.0 )\nv = base.dists.degenerate.mode( -10.0 )\n","base.dists.degenerate.pdf":"var y = base.dists.degenerate.pdf( 2.0, 3.0 )\ny = base.dists.degenerate.pdf( 3.0, 3.0 )\ny = base.dists.degenerate.pdf( NaN, 0.0 )\ny = base.dists.degenerate.pdf( 0.0, NaN )\n","base.dists.degenerate.pdf.factory":"var myPDF = base.dists.degenerate.pdf.factory( 10.0 );\nvar y = myPDF( 10.0 )\n","base.dists.degenerate.pmf":"var y = base.dists.degenerate.pmf( 2.0, 3.0 )\ny = base.dists.degenerate.pmf( 3.0, 3.0 )\ny = base.dists.degenerate.pmf( NaN, 0.0 )\ny = base.dists.degenerate.pmf( 0.0, NaN )\n","base.dists.degenerate.pmf.factory":"var myPMF = base.dists.degenerate.pmf.factory( 10.0 );\nvar y = myPMF( 10.0 )\n","base.dists.degenerate.quantile":"var y = base.dists.degenerate.quantile( 0.5, 2.0 )\ny = base.dists.degenerate.quantile( 0.9, 4.0 )\ny = base.dists.degenerate.quantile( 1.1, 0.0 )\ny = base.dists.degenerate.quantile( -0.2, 0.0 )\ny = base.dists.degenerate.quantile( NaN, 0.0 )\ny = base.dists.degenerate.quantile( 0.0, NaN )\n","base.dists.degenerate.quantile.factory":"var myQuantile = base.dists.degenerate.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.degenerate.stdev":"var v = base.dists.degenerate.stdev( 20.0 )\nv = base.dists.degenerate.stdev( -10.0 )\n","base.dists.degenerate.variance":"var v = base.dists.degenerate.variance( 20.0 )\nv = base.dists.degenerate.variance( -10.0 )\n","base.dists.discreteUniform.cdf":"var y = base.dists.discreteUniform.cdf( 9.0, 0, 10 )\ny = base.dists.discreteUniform.cdf( 0.5, 0, 2 )\ny = base.dists.discreteUniform.cdf( PINF, 2, 4 )\ny = base.dists.discreteUniform.cdf( NINF, 2, 4 )\ny = base.dists.discreteUniform.cdf( NaN, 0, 1 )\ny = base.dists.discreteUniform.cdf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.cdf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.cdf( 2.0, 1, 0 )\n","base.dists.discreteUniform.cdf.factory":"var mycdf = base.dists.discreteUniform.cdf.factory( 0, 10 );\nvar y = mycdf( 0.5 )\ny = mycdf( 8.0 )\n","base.dists.discreteUniform.DiscreteUniform":"var discreteUniform = base.dists.discreteUniform.DiscreteUniform( -2, 2 );\ndiscreteUniform.a\ndiscreteUniform.b\ndiscreteUniform.entropy\ndiscreteUniform.kurtosis\ndiscreteUniform.mean\ndiscreteUniform.median\ndiscreteUniform.skewness\ndiscreteUniform.stdev\ndiscreteUniform.variance\ndiscreteUniform.cdf( 0.8 )\ndiscreteUniform.logcdf( 0.5 )\ndiscreteUniform.logpmf( 1.0 )\ndiscreteUniform.mgf( 0.8 )\ndiscreteUniform.pmf( 0.0 )\ndiscreteUniform.quantile( 0.8 )\n","base.dists.discreteUniform.entropy":"var v = base.dists.discreteUniform.entropy( 0, 1 )\nv = base.dists.discreteUniform.entropy( 4, 12 )\nv = base.dists.discreteUniform.entropy( 2, 8 )\n","base.dists.discreteUniform.kurtosis":"var v = base.dists.discreteUniform.kurtosis( 0, 1 )\nv = base.dists.discreteUniform.kurtosis( 4, 12 )\nv = base.dists.discreteUniform.kurtosis( -4, 8 )\n","base.dists.discreteUniform.logcdf":"var y = base.dists.discreteUniform.logcdf( 9.0, 0, 10 )\ny = base.dists.discreteUniform.logcdf( 0.5, 0, 2 )\ny = base.dists.discreteUniform.logcdf( PINF, 2, 4 )\ny = base.dists.discreteUniform.logcdf( NINF, 2, 4 )\ny = base.dists.discreteUniform.logcdf( NaN, 0, 1 )\ny = base.dists.discreteUniform.logcdf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.logcdf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.logcdf( 2.0, 1, 0 )\n","base.dists.discreteUniform.logcdf.factory":"var myLogCDF = base.dists.discreteUniform.logcdf.factory( 0, 10 );\nvar y = myLogCDF( 0.5 )\ny = myLogCDF( 8.0 )\n","base.dists.discreteUniform.logpmf":"var y = base.dists.discreteUniform.logpmf( 2.0, 0, 4 )\ny = base.dists.discreteUniform.logpmf( 5.0, 0, 4 )\ny = base.dists.discreteUniform.logpmf( 3.0, -4, 4 )\ny = base.dists.discreteUniform.logpmf( NaN, 0, 1 )\ny = base.dists.discreteUniform.logpmf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.logpmf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.logpmf( 2.0, 3, 1 )\ny = base.dists.discreteUniform.logpmf( 2.0, 1, 2.4 )\n","base.dists.discreteUniform.logpmf.factory":"var myLogPMF = base.dists.discreteUniform.logpmf.factory( 6, 7 );\nvar y = myLogPMF( 7.0 )\ny = myLogPMF( 5.0 )\n","base.dists.discreteUniform.mean":"var v = base.dists.discreteUniform.mean( -2, 2 )\nv = base.dists.discreteUniform.mean( 4, 12 )\nv = base.dists.discreteUniform.mean( 2, 8 )\n","base.dists.discreteUniform.median":"var v = base.dists.discreteUniform.median( -2, 2 )\nv = base.dists.discreteUniform.median( 4, 12 )\nv = base.dists.discreteUniform.median( 2, 8 )\n","base.dists.discreteUniform.mgf":"var y = base.dists.discreteUniform.mgf( 2.0, 0, 4 )\ny = base.dists.discreteUniform.mgf( -0.2, 0, 4 )\ny = base.dists.discreteUniform.mgf( 2.0, 0, 1 )\ny = base.dists.discreteUniform.mgf( 0.5, 3, 2 )\ny = base.dists.discreteUniform.mgf( NaN, 0, 1  )\ny = base.dists.discreteUniform.mgf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.mgf( 0.0, 0, NaN )\n","base.dists.discreteUniform.mgf.factory":"var mymgf = base.dists.discreteUniform.mgf.factory( 6, 7 );\nvar y = mymgf( 0.1 )\ny = mymgf( 1.1 )\n","base.dists.discreteUniform.pmf":"var y = base.dists.discreteUniform.pmf( 2.0, 0, 4 )\ny = base.dists.discreteUniform.pmf( 5.0, 0, 4 )\ny = base.dists.discreteUniform.pmf( 3.0, -4, 4 )\ny = base.dists.discreteUniform.pmf( NaN, 0, 1 )\ny = base.dists.discreteUniform.pmf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.pmf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.pmf( 2.0, 3, 1 )\ny = base.dists.discreteUniform.pmf( 2.0, 1, 2.4 )\n","base.dists.discreteUniform.pmf.factory":"var myPMF = base.dists.discreteUniform.pmf.factory( 6, 7 );\nvar y = myPMF( 7.0 )\ny = myPMF( 5.0 )\n","base.dists.discreteUniform.quantile":"var y = base.dists.discreteUniform.quantile( 0.8, 0, 1 )\ny = base.dists.discreteUniform.quantile( 0.5, 0.0, 10.0 )\ny = base.dists.discreteUniform.quantile( 1.1, 0, 4 )\ny = base.dists.discreteUniform.quantile( -0.2, 0, 4 )\ny = base.dists.discreteUniform.quantile( NaN, -2, 2 )\ny = base.dists.discreteUniform.quantile( 0.1, NaN, 2 )\ny = base.dists.discreteUniform.quantile( 0.1, -2, NaN )\ny = base.dists.discreteUniform.quantile( 0.5, 2, 1 )\n","base.dists.discreteUniform.quantile.factory":"var myQuantile = base.dists.discreteUniform.quantile.factory( 0, 4 );\nvar y = myQuantile( 0.8 )\n","base.dists.discreteUniform.skewness":"var v = base.dists.discreteUniform.skewness( -2, 2 )\nv = base.dists.discreteUniform.skewness( 4, 12 )\nv = base.dists.discreteUniform.skewness( 2, 8 )\n","base.dists.discreteUniform.stdev":"var v = base.dists.discreteUniform.stdev( 0, 1 )\nv = base.dists.discreteUniform.stdev( 4, 12 )\nv = base.dists.discreteUniform.stdev( 2, 8 )\n","base.dists.discreteUniform.variance":"var v = base.dists.discreteUniform.variance( 0, 1 )\nv = base.dists.discreteUniform.variance( 4, 12 )\nv = base.dists.discreteUniform.variance( 2, 8 )\n","base.dists.erlang.cdf":"var y = base.dists.erlang.cdf( 2.0, 1, 1.0 )\ny = base.dists.erlang.cdf( 2.0, 3, 1.0 )\ny = base.dists.erlang.cdf( 2.0, 2.5, 1.0 )\ny = base.dists.erlang.cdf( -1.0, 2, 2.0 )\ny = base.dists.erlang.cdf( PINF, 4, 2.0 )\ny = base.dists.erlang.cdf( NINF, 4, 2.0 )\ny = base.dists.erlang.cdf( NaN, 0, 1.0 )\ny = base.dists.erlang.cdf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.cdf( 0.0, 0, NaN )\ny = base.dists.erlang.cdf( 2.0, -1, 1.0 )\ny = base.dists.erlang.cdf( 2.0, 1, -1.0 )\n","base.dists.erlang.cdf.factory":"var mycdf = base.dists.erlang.cdf.factory( 2, 0.5 );\nvar y = mycdf( 6.0 )\ny = mycdf( 2.0 )\n","base.dists.erlang.entropy":"var v = base.dists.erlang.entropy( 1, 1.0 )\nv = base.dists.erlang.entropy( 4, 12.0 )\nv = base.dists.erlang.entropy( 8, 2.0 )\n","base.dists.erlang.Erlang":"var erlang = base.dists.erlang.Erlang( 6, 5.0 );\nerlang.k\nerlang.lambda\nerlang.entropy\nerlang.kurtosis\nerlang.mean\nerlang.mode\nerlang.skewness\nerlang.stdev\nerlang.variance\nerlang.cdf( 3.0 )\nerlang.logpdf( 3.0 )\nerlang.mgf( -0.5 )\nerlang.pdf( 3.0 )\nerlang.quantile( 0.8 )\n","base.dists.erlang.kurtosis":"var v = base.dists.erlang.kurtosis( 1, 1.0 )\nv = base.dists.erlang.kurtosis( 4, 12.0 )\nv = base.dists.erlang.kurtosis( 8, 2.0 )\n","base.dists.erlang.logpdf":"var y = base.dists.erlang.logpdf( 0.1, 1, 1.0 )\ny = base.dists.erlang.logpdf( 0.5, 2, 2.5 )\ny = base.dists.erlang.logpdf( -1.0, 4, 2.0 )\ny = base.dists.erlang.logpdf( NaN, 1, 1.0 )\ny = base.dists.erlang.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.logpdf( 0.0, 1, NaN )\ny = base.dists.erlang.logpdf( 2.0, -2, 0.5 )\ny = base.dists.erlang.logpdf( 2.0, 0.5, 0.5 )\ny = base.dists.erlang.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.erlang.logpdf( 0.0, 0.0, 2.0 )\ny = base.dists.erlang.logpdf( 2.0, 1, 0.0 )\ny = base.dists.erlang.logpdf( 2.0, 1, -1.0 )\n","base.dists.erlang.logpdf.factory":"var myLogPDF = base.dists.erlang.logpdf.factory( 6.0, 7.0 );\ny = myLogPDF( 7.0 )\n","base.dists.erlang.mean":"var v = base.dists.erlang.mean( 1, 1.0 )\nv = base.dists.erlang.mean( 4, 12.0 )\nv = base.dists.erlang.mean( 8, 2.0 )\n","base.dists.erlang.mgf":"var y = base.dists.erlang.mgf( 0.3, 1, 1.0 )\ny = base.dists.erlang.mgf( 2.0, 2, 3.0 )\ny = base.dists.erlang.mgf( -1.0, 2, 2.0 )\ny = base.dists.erlang.mgf( NaN, 1, 1.0 )\ny = base.dists.erlang.mgf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.mgf( 0.0, 1, NaN )\ny = base.dists.erlang.mgf( 0.2, -2, 0.5 )\ny = base.dists.erlang.mgf( 0.2, 0.5, 0.5 )\ny = base.dists.erlang.mgf( 0.2, 1, 0.0 )\ny = base.dists.erlang.mgf( 0.2, 1, -5.0 )\n","base.dists.erlang.mgf.factory":"var myMGF = base.dists.erlang.mgf.factory( 2, 0.5 );\nvar y = myMGF( 0.2 )\ny = myMGF( -0.5 )\n","base.dists.erlang.mode":"var v = base.dists.erlang.mode( 1, 1.0 )\nv = base.dists.erlang.mode( 4, 12.0 )\nv = base.dists.erlang.mode( 8, 2.0 )\n","base.dists.erlang.pdf":"var y = base.dists.erlang.pdf( 0.1, 1, 1.0 )\ny = base.dists.erlang.pdf( 0.5, 2, 2.5 )\ny = base.dists.erlang.pdf( -1.0, 4, 2.0 )\ny = base.dists.erlang.pdf( NaN, 1, 1.0 )\ny = base.dists.erlang.pdf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.pdf( 0.0, 1, NaN )\ny = base.dists.erlang.pdf( 2.0, -2, 0.5 )\ny = base.dists.erlang.pdf( 2.0, 0.5, 0.5 )\ny = base.dists.erlang.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.erlang.pdf( 0.0, 0.0, 2.0 )\ny = base.dists.erlang.pdf( 2.0, 1, 0.0 )\ny = base.dists.erlang.pdf( 2.0, 1, -1.0 )\n","base.dists.erlang.pdf.factory":"var myPDF = base.dists.erlang.pdf.factory( 6.0, 7.0 );\ny = myPDF( 7.0 )\n","base.dists.erlang.quantile":"var y = base.dists.erlang.quantile( 0.8, 2, 1.0 )\ny = base.dists.erlang.quantile( 0.5, 4, 2.0 )\ny = base.dists.erlang.quantile( 1.1, 1, 1.0 )\ny = base.dists.erlang.quantile( -0.2, 1, 1.0 )\ny = base.dists.erlang.quantile( NaN, 1, 1.0 )\ny = base.dists.erlang.quantile( 0.0, NaN, 1.0 )\ny = base.dists.erlang.quantile( 0.0, 1, NaN )\ny = base.dists.erlang.quantile( 0.5, 0.5, 1.0 )\ny = base.dists.erlang.quantile( 0.5, -1, 1.0 )\ny = base.dists.erlang.quantile( 0.5, 1, -1.0 )\n","base.dists.erlang.quantile.factory":"var myQuantile = base.dists.erlang.quantile.factory( 10, 2.0 );\nvar y = myQuantile( 0.4 )\n","base.dists.erlang.skewness":"var v = base.dists.erlang.skewness( 1, 1.0 )\nv = base.dists.erlang.skewness( 4, 12.0 )\nv = base.dists.erlang.skewness( 8, 2.0 )\n","base.dists.erlang.stdev":"var v = base.dists.erlang.stdev( 1, 1.0 )\nv = base.dists.erlang.stdev( 4, 12.0 )\nv = base.dists.erlang.stdev( 8, 2.0 )\n","base.dists.erlang.variance":"var v = base.dists.erlang.variance( 1, 1.0 )\nv = base.dists.erlang.variance( 4, 12.0 )\nv = base.dists.erlang.variance( 8, 2.0 )\n","base.dists.exponential.cdf":"var y = base.dists.exponential.cdf( 2.0, 0.1 )\ny = base.dists.exponential.cdf( 1.0, 2.0 )\ny = base.dists.exponential.cdf( -1.0, 4.0 )\ny = base.dists.exponential.cdf( NaN, 1.0 )\ny = base.dists.exponential.cdf( 0.0, NaN )\ny = base.dists.exponential.cdf( 2.0, -1.0 )\n","base.dists.exponential.cdf.factory":"var myCDF = base.dists.exponential.cdf.factory( 0.5 );\nvar y = myCDF( 3.0 )\n","base.dists.exponential.entropy":"var v = base.dists.exponential.entropy( 11.0 )\nv = base.dists.exponential.entropy( 4.5 )\n","base.dists.exponential.Exponential":"var exponential = base.dists.exponential.Exponential( 6.0 );\nexponential.lambda\nexponential.entropy\nexponential.kurtosis\nexponential.mean\nexponential.median\nexponential.mode\nexponential.skewness\nexponential.stdev\nexponential.variance\nexponential.cdf( 1.0 )\nexponential.logcdf( 1.0 )\nexponential.logpdf( 1.5 )\nexponential.mgf( -0.5 )\nexponential.pdf( 1.5 )\nexponential.quantile( 0.5 )\n","base.dists.exponential.kurtosis":"var v = base.dists.exponential.kurtosis( 11.0 )\nv = base.dists.exponential.kurtosis( 4.5 )\n","base.dists.exponential.logcdf":"var y = base.dists.exponential.logcdf( 2.0, 0.1 )\ny = base.dists.exponential.logcdf( 1.0, 2.0 )\ny = base.dists.exponential.logcdf( -1.0, 4.0 )\ny = base.dists.exponential.logcdf( NaN, 1.0 )\ny = base.dists.exponential.logcdf( 0.0, NaN )\ny = base.dists.exponential.logcdf( 2.0, -1.0 )\n","base.dists.exponential.logcdf.factory":"var mylogCDF = base.dists.exponential.logcdf.factory( 0.5 );\nvar y = mylogCDF( 3.0 )\n","base.dists.exponential.logpdf":"var y = base.dists.exponential.logpdf( 0.3, 4.0 )\ny = base.dists.exponential.logpdf( 2.0, 0.7 )\ny = base.dists.exponential.logpdf( -1.0, 0.5 )\ny = base.dists.exponential.logpdf( 0, NaN )\ny = base.dists.exponential.logpdf( NaN, 2.0 )\ny = base.dists.exponential.logpdf( 2.0, -1.0 )\n","base.dists.exponential.logpdf.factory":"var mylogpdf = base.dists.exponential.logpdf.factory( 0.5 );\nvar y = mylogpdf( 3.0 )\n","base.dists.exponential.mean":"var v = base.dists.exponential.mean( 11.0 )\nv = base.dists.exponential.mean( 4.5 )\n","base.dists.exponential.median":"var v = base.dists.exponential.median( 11.0 )\nv = base.dists.exponential.median( 4.5 )\n","base.dists.exponential.mgf":"var v = base.dists.exponential.mgf( 2.0, 3.0 )\nv = base.dists.exponential.mgf( 0.4, 1.2 )\nv = base.dists.exponential.mgf( 0.8, 1.6 )\nv = base.dists.exponential.mgf( 4.0, 3.0 )\nv = base.dists.exponential.mgf( NaN, 3.0 )\nv = base.dists.exponential.mgf( 2.0, NaN )\n","base.dists.exponential.mgf.factory":"var myMGF = base.dists.exponential.mgf.factory( 4.0 );\nvar y = myMGF( 3.0 )\ny = myMGF( 0.5 )\n","base.dists.exponential.mode":"var v = base.dists.exponential.mode( 11.0 )\nv = base.dists.exponential.mode( 4.5 )\n","base.dists.exponential.pdf":"var y = base.dists.exponential.pdf( 0.3, 4.0 )\ny = base.dists.exponential.pdf( 2.0, 0.7 )\ny = base.dists.exponential.pdf( -1.0, 0.5 )\ny = base.dists.exponential.pdf( 0, NaN )\ny = base.dists.exponential.pdf( NaN, 2.0 )\ny = base.dists.exponential.pdf( 2.0, -1.0 )\n","base.dists.exponential.pdf.factory":"var myPDF = base.dists.exponential.pdf.factory( 0.5 );\nvar y = myPDF( 3.0 )\n","base.dists.exponential.quantile":"var y = base.dists.exponential.quantile( 0.8, 1.0 )\ny = base.dists.exponential.quantile( 0.5, 4.0 )\ny = base.dists.exponential.quantile( 0.5, 0.1 )\ny = base.dists.exponential.quantile( -0.2, 0.1 )\ny = base.dists.exponential.quantile( NaN, 1.0 )\ny = base.dists.exponential.quantile( 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= base.dists.f.pdf( 0.1, 1.0, 1.0 )\ny = base.dists.f.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.f.pdf( NaN, 1.0, 1.0 )\ny = base.dists.f.pdf( 0.0, NaN, 1.0 )\ny = base.dists.f.pdf( 0.0, 1.0, NaN )\ny = base.dists.f.pdf( 2.0, 1.0, -1.0 )\ny = base.dists.f.pdf( 2.0, -1.0, 1.0 )\n","base.dists.f.pdf.factory":"var myPDF = base.dists.f.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 7.0 )\ny = myPDF( 2.0 )\n","base.dists.f.quantile":"var y = base.dists.f.quantile( 0.8, 1.0, 1.0 )\ny = base.dists.f.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.f.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.f.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.f.quantile( NaN, 1.0, 1.0 )\ny = base.dists.f.quantile( 0.5, NaN, 1.0 )\ny = base.dists.f.quantile( 0.5, 1.0, NaN )\ny = base.dists.f.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.f.quantile( 0.5, 1.0, -1.0 )\n","base.dists.f.quantile.factory":"var myQuantile = base.dists.f.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.2 )\ny = myQuantile( 0.8 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base.dists.frechet.kurtosis( 1.0, NaN, 0.0 )\ny = base.dists.frechet.kurtosis( 1.0, 1.0, NaN )\n","base.dists.frechet.logcdf":"var y = base.dists.frechet.logcdf( 10.0, 2.0, 3.0, 0.0 )\ny = base.dists.frechet.logcdf( -1.0, 2.0, 3.0, -3.0 )\ny = base.dists.frechet.logcdf( 2.5, 2.0, 1.0, 2.0 )\ny = base.dists.frechet.logcdf( NaN, 1.0, 1.0, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, NaN, 1.0, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, 1.0, NaN, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, 1.0, 1.0, NaN )\ny = base.dists.frechet.logcdf( 0.0, -1.0, 1.0, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, 1.0, -1.0, 0.0 )\n","base.dists.frechet.logcdf.factory":"var mylogcdf = base.dists.frechet.logcdf.factory( 3.0, 3.0, 5.0 );\nvar y = mylogcdf( 10.0 )\ny = mylogcdf( 7.0 )\n","base.dists.frechet.logpdf":"var y = base.dists.frechet.logpdf( 10.0, 1.0, 3.0, 5.0 )\ny = base.dists.frechet.logpdf( -2.0, 1.0, 3.0, -3.0 )\ny = base.dists.frechet.logpdf( 0.0, 2.0, 1.0, -1.0 )\ny = base.dists.frechet.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.frechet.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.frechet.logpdf( 0.0, 0.0, NaN )\ny = base.dists.frechet.logpdf( 0.0, 0.0, -1.0 )\n","base.dists.frechet.logpdf.factory":"var mylogPDF = base.dists.frechet.logpdf.factory( 2.0, 3.0, 1.0 );\nvar y = mylogPDF( 10.0 )\ny = mylogPDF( 2.0 )\n","base.dists.frechet.mean":"var y = base.dists.frechet.mean( 4.0, 2.0, 1.0 )\ny = base.dists.frechet.mean( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.mean( NaN, 1.0, 0.0 )\ny = base.dists.frechet.mean( 1.0, NaN, 0.0 )\ny = base.dists.frechet.mean( 1.0, 1.0, NaN )\n","base.dists.frechet.median":"var y = base.dists.frechet.median( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.median( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.median( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.median( NaN, 1.0, 0.0 )\ny = base.dists.frechet.median( 1.0, NaN, 0.0 )\ny = base.dists.frechet.median( 1.0, 1.0, NaN )\n","base.dists.frechet.mode":"var y = base.dists.frechet.mode( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.mode( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.mode( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.mode( NaN, 1.0, 0.0 )\ny = base.dists.frechet.mode( 1.0, NaN, 0.0 )\ny = base.dists.frechet.mode( 1.0, 1.0, NaN )\n","base.dists.frechet.pdf":"var y = base.dists.frechet.pdf( 10.0, 0.0, 3.0 )\ny = base.dists.frechet.pdf( -2.0, 0.0, 3.0 )\ny = base.dists.frechet.pdf( 0.0, 0.0, 1.0 )\ny = base.dists.frechet.pdf( NaN, 0.0, 1.0 )\ny = base.dists.frechet.pdf( 0.0, NaN, 1.0 )\ny = base.dists.frechet.pdf( 0.0, 0.0, NaN )\ny = base.dists.frechet.pdf( 0.0, 0.0, -1.0 )\n","base.dists.frechet.pdf.factory":"var myPDF = base.dists.frechet.pdf.factory( 2.0, 3.0 );\nvar y = myPDF( 10.0 )\ny = myPDF( 2.0 )\n","base.dists.frechet.quantile":"var y = base.dists.frechet.quantile( 0.3, 10.0, 2.0, 3.0 )\ny = base.dists.frechet.quantile( 0.2, 3.0, 3.0, 3.0 )\ny = base.dists.frechet.quantile( 0.9, 1.0, 1.0, -3.0 )\ny = base.dists.frechet.quantile( NaN, 1.0, 1.0, 0.0 )\ny = base.dists.frechet.quantile( 0.0, NaN, 1.0, 0.0)\ny = base.dists.frechet.quantile( 0.0, 1.0, NaN, 0.0 )\ny = base.dists.frechet.quantile( 0.0, 1.0, 1.0, NaN )\ny = base.dists.frechet.quantile( 0.0, -1.0, 1.0, 0.0 )\ny = base.dists.frechet.quantile( 0.0, 1.0, -1.0, 0.0 )\n","base.dists.frechet.quantile.factory":"var myQuantile = base.dists.frechet.quantile.factory( 2.0, 2.0, 3.0 );\nvar y = myQuantile( 0.5 )\ny = myQuantile( 0.2 )\n","base.dists.frechet.skewness":"var y = base.dists.frechet.skewness( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.skewness( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.skewness( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.skewness( NaN, 1.0, 0.0 )\ny = base.dists.frechet.skewness( 1.0, NaN, 0.0 )\ny = base.dists.frechet.skewness( 1.0, 1.0, NaN )\n","base.dists.frechet.stdev":"var y = base.dists.frechet.stdev( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.stdev( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.stdev( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.stdev( NaN, 1.0, 0.0 )\ny = base.dists.frechet.stdev( 1.0, NaN, 0.0 )\ny = base.dists.frechet.stdev( 1.0, 1.0, NaN )\n","base.dists.frechet.variance":"var y = base.dists.frechet.variance( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.variance( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.variance( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.variance( NaN, 1.0, 0.0 )\ny = base.dists.frechet.variance( 1.0, NaN, 0.0 )\ny = base.dists.frechet.variance( 1.0, 1.0, NaN )\n","base.dists.gamma.cdf":"var y = base.dists.gamma.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.gamma.cdf( 2.0, 3.0, 1.0 )\ny = base.dists.gamma.cdf( -1.0, 2.0, 2.0 )\ny = base.dists.gamma.cdf( PINF, 4.0, 2.0 )\ny = base.dists.gamma.cdf( NINF, 4.0, 2.0 )\ny = base.dists.gamma.cdf( NaN, 0.0, 1.0 )\ny = base.dists.gamma.cdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.cdf( 0.0, 0.0, NaN )\ny = base.dists.gamma.cdf( 2.0, -1.0, 1.0 )\ny = base.dists.gamma.cdf( 2.0, 1.0, -1.0 )\ny = base.dists.gamma.cdf( 2.0, 0.0, 2.0 )\ny = base.dists.gamma.cdf( -2.0, 0.0, 2.0 )\ny = base.dists.gamma.cdf( 0.0, 0.0, 2.0 )\n","base.dists.gamma.cdf.factory":"var myCDF = base.dists.gamma.cdf.factory( 2.0, 0.5 );\nvar y = myCDF( 6.0 )\ny = myCDF( 2.0 )\n","base.dists.gamma.entropy":"var v = base.dists.gamma.entropy( 1.0, 1.0 )\nv = base.dists.gamma.entropy( 4.0, 12.0 )\nv = base.dists.gamma.entropy( 8.0, 2.0 )\n","base.dists.gamma.Gamma":"var gamma = base.dists.gamma.Gamma( 6.0, 5.0 );\ngamma.alpha\ngamma.beta\ngamma.entropy\ngamma.kurtosis\ngamma.mean\ngamma.mode\ngamma.skewness\ngamma.stdev\ngamma.variance\ngamma.cdf( 0.8 )\ngamma.logcdf( 0.8 )\ngamma.logpdf( 1.0 )\ngamma.mgf( -0.5 )\ngamma.pdf( 1.0 )\ngamma.quantile( 0.8 )\n","base.dists.gamma.kurtosis":"var v = base.dists.gamma.kurtosis( 1.0, 1.0 )\nv = base.dists.gamma.kurtosis( 4.0, 12.0 )\nv = base.dists.gamma.kurtosis( 8.0, 2.0 )\n","base.dists.gamma.logcdf":"var y = base.dists.gamma.logcdf( 2.0, 0.5, 1.0 )\ny = base.dists.gamma.logcdf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.logcdf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.logcdf( NaN, 0.6, 1.0 )\ny = base.dists.gamma.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.logcdf( 0.0, 1.0, NaN )\ny = base.dists.gamma.logcdf( 2.0, -1.0, 1.0 )\ny = base.dists.gamma.logcdf( 2.0, 1.0, -1.0 )\n","base.dists.gamma.logcdf.factory":"var mylogCDF = base.dists.gamma.logcdf.factory( 6.0, 7.0 );\nvar y = mylogCDF( 2.0 )\n","base.dists.gamma.logpdf":"var y = base.dists.gamma.logpdf( 2.0, 0.5, 1.0 )\ny = base.dists.gamma.logpdf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.logpdf( NaN, 0.6, 1.0 )\ny = base.dists.gamma.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.logpdf( 0.0, 1.0, NaN )\ny = base.dists.gamma.logpdf( 2.0, -1.0, 1.0 )\ny = base.dists.gamma.logpdf( 2.0, 1.0, -1.0 )\ny = base.dists.gamma.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.gamma.logpdf( 0.0, 0.0, 2.0 )\n","base.dists.gamma.logpdf.factory":"var mylogPDF = base.dists.gamma.logpdf.factory( 6.0, 7.0 );\nvar y = mylogPDF( 2.0 )\n","base.dists.gamma.mean":"var v = base.dists.gamma.mean( 1.0, 1.0 )\nv = base.dists.gamma.mean( 4.0, 12.0 )\nv = base.dists.gamma.mean( 8.0, 2.0 )\n","base.dists.gamma.mgf":"var y = base.dists.gamma.mgf( 0.5, 0.5, 1.0 )\ny = base.dists.gamma.mgf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.mgf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.mgf( NaN, 1.0, 1.0 )\ny = base.dists.gamma.mgf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.mgf( 0.0, 1.0, NaN )\ny = base.dists.gamma.mgf( 2.0, 4.0, 1.0 )\ny = base.dists.gamma.mgf( 2.0, -0.5, 1.0 )\ny = base.dists.gamma.mgf( 2.0, 1.0, 0.0 )\ny = base.dists.gamma.mgf( 2.0, 1.0, -1.0 )\n","base.dists.gamma.mgf.factory":"var myMGF = base.dists.gamma.mgf.factory( 3.0, 1.5 );\nvar y = myMGF( 1.0 )\ny = myMGF( 0.5 )\n","base.dists.gamma.mode":"var v = base.dists.gamma.mode( 1.0, 1.0 )\nv = base.dists.gamma.mode( 4.0, 12.0 )\nv = base.dists.gamma.mode( 8.0, 2.0 )\n","base.dists.gamma.pdf":"var y = base.dists.gamma.pdf( 2.0, 0.5, 1.0 )\ny = base.dists.gamma.pdf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.pdf( NaN, 0.6, 1.0 )\ny = base.dists.gamma.pdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.pdf( 0.0, 1.0, NaN )\ny = base.dists.gamma.pdf( 2.0, -1.0, 1.0 )\ny = base.dists.gamma.pdf( 2.0, 1.0, -1.0 )\ny = base.dists.gamma.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.gamma.pdf( 0.0, 0.0, 2.0 )\n","base.dists.gamma.pdf.factory":"var myPDF = base.dists.gamma.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 2.0 )\n","base.dists.gamma.quantile":"var y = base.dists.gamma.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.gamma.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.gamma.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.gamma.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.gamma.quantile( NaN, 1.0, 1.0 )\ny = base.dists.gamma.quantile( 0.0, NaN, 1.0 )\ny = base.dists.gamma.quantile( 0.0, 1.0, NaN )\ny = base.dists.gamma.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.gamma.quantile( 0.5, 1.0, -1.0 )\ny = base.dists.gamma.quantile( 0.3, 0.0, 2.0 )\ny = base.dists.gamma.quantile( 0.9, 0.0, 2.0 )\n","base.dists.gamma.quantile.factory":"var myQuantile = base.dists.gamma.quantile.factory( 2.0, 2.0 );\nvar y = myQuantile( 0.8 )\ny = myQuantile( 0.4 )\n","base.dists.gamma.skewness":"var v = base.dists.gamma.skewness( 1.0, 1.0 )\nv = base.dists.gamma.skewness( 4.0, 12.0 )\nv = base.dists.gamma.skewness( 8.0, 2.0 )\n","base.dists.gamma.stdev":"var v = base.dists.gamma.stdev( 1.0, 1.0 )\nv = base.dists.gamma.stdev( 4.0, 12.0 )\nv = base.dists.gamma.stdev( 8.0, 2.0 )\n","base.dists.gamma.variance":"var v = base.dists.gamma.variance( 1.0, 1.0 )\nv = base.dists.gamma.variance( 4.0, 12.0 )\nv = base.dists.gamma.variance( 8.0, 2.0 )\n","base.dists.geometric.cdf":"var y = base.dists.geometric.cdf( 2.0, 0.5 )\ny = base.dists.geometric.cdf( 2.0, 0.1 )\ny = base.dists.geometric.cdf( -1.0, 4.0 )\ny = base.dists.geometric.cdf( NaN, 0.5 )\ny = base.dists.geometric.cdf( 0.0, NaN )\ny = base.dists.geometric.cdf( 2.0, 1.4 )\n","base.dists.geometric.cdf.factory":"var mycdf = base.dists.geometric.cdf.factory( 0.5 );\nvar y = mycdf( 3.0 )\ny = mycdf( 1.0 )\n","base.dists.geometric.entropy":"var v = base.dists.geometric.entropy( 0.1 )\nv = base.dists.geometric.entropy( 0.5 )\n","base.dists.geometric.Geometric":"var geometric = base.dists.geometric.Geometric( 0.6 );\ngeometric.p\ngeometric.entropy\ngeometric.kurtosis\ngeometric.mean\ngeometric.median\ngeometric.mode\ngeometric.skewness\ngeometric.stdev\ngeometric.variance\ngeometric.cdf( 3.0 )\ngeometric.logcdf( 3.0 )\ngeometric.logpmf( 4.0 )\ngeometric.mgf( 0.5 )\ngeometric.pmf( 2.0 )\ngeometric.quantile( 0.7 )\n","base.dists.geometric.kurtosis":"var v = base.dists.geometric.kurtosis( 0.1 )\nv = base.dists.geometric.kurtosis( 0.5 )\n","base.dists.geometric.logcdf":"var y = base.dists.geometric.logcdf( 2.0, 0.5 )\ny = base.dists.geometric.logcdf( 2.0, 0.1 )\ny = base.dists.geometric.logcdf( -1.0, 4.0 )\ny = base.dists.geometric.logcdf( NaN, 0.5 )\ny = base.dists.geometric.logcdf( 0.0, NaN )\ny = base.dists.geometric.logcdf( 2.0, 1.4 )\n","base.dists.geometric.logcdf.factory":"var mylogcdf = base.dists.geometric.logcdf.factory( 0.5 );\nvar y = mylogcdf( 3.0 )\ny = mylogcdf( 1.0 )\n","base.dists.geometric.logpmf":"var y = base.dists.geometric.logpmf( 4.0, 0.3 )\ny = base.dists.geometric.logpmf( 2.0, 0.7 )\ny = base.dists.geometric.logpmf( -1.0, 0.5 )\ny = base.dists.geometric.logpmf( 0.0, NaN )\ny = base.dists.geometric.logpmf( NaN, 0.5 )\ny = base.dists.geometric.logpmf( 2.0, 1.5 )\n","base.dists.geometric.logpmf.factory":"var mylogpmf = base.dists.geometric.logpmf.factory( 0.5 );\nvar y = mylogpmf( 3.0 )\ny = mylogpmf( 1.0 )\n","base.dists.geometric.mean":"var v = base.dists.geometric.mean( 0.1 )\nv = base.dists.geometric.mean( 0.5 )\n","base.dists.geometric.median":"var v = base.dists.geometric.median( 0.1 )\nv = base.dists.geometric.median( 0.5 )\n","base.dists.geometric.mgf":"var y = base.dists.geometric.mgf( 0.2, 0.5 )\ny = base.dists.geometric.mgf( 0.4, 0.5 )\ny = base.dists.geometric.mgf( 0.8, 0.5 )\ny = base.dists.geometric.mgf( NaN, 0.0 )\ny = base.dists.geometric.mgf( 0.0, NaN )\ny = base.dists.geometric.mgf( -2.0, -1.0 )\ny = base.dists.geometric.mgf( 0.2, 2.0 )\n","base.dists.geometric.mgf.factory":"var mymgf = base.dists.geometric.mgf.factory( 0.8 );\nvar y = mymgf( -0.2 )\n","base.dists.geometric.mode":"var v = base.dists.geometric.mode( 0.1 )\nv = base.dists.geometric.mode( 0.5 )\n","base.dists.geometric.pmf":"var y = base.dists.geometric.pmf( 4.0, 0.3 )\ny = base.dists.geometric.pmf( 2.0, 0.7 )\ny = base.dists.geometric.pmf( -1.0, 0.5 )\ny = base.dists.geometric.pmf( 0.0, NaN )\ny = base.dists.geometric.pmf( NaN, 0.5 )\ny = base.dists.geometric.pmf( 2.0, 1.5 )\n","base.dists.geometric.pmf.factory":"var mypmf = base.dists.geometric.pmf.factory( 0.5 );\nvar y = mypmf( 3.0 )\ny = mypmf( 1.0 )\n","base.dists.geometric.quantile":"var y = base.dists.geometric.quantile( 0.8, 0.4 )\ny = base.dists.geometric.quantile( 0.5, 0.4 )\ny = base.dists.geometric.quantile( 0.9, 0.1 )\ny = base.dists.geometric.quantile( -0.2, 0.1 )\ny = base.dists.geometric.quantile( NaN, 0.8 )\ny = base.dists.geometric.quantile( 0.4, NaN )\ny = base.dists.geometric.quantile( 0.5, -1.0 )\ny = base.dists.geometric.quantile( 0.5, 1.5 )\n","base.dists.geometric.quantile.factory":"var myquantile = base.dists.geometric.quantile.factory( 0.4 );\nvar y = myquantile( 0.4 )\ny = myquantile( 0.8 )\ny = myquantile( 1.0 )\n","base.dists.geometric.skewness":"var v = base.dists.geometric.skewness( 0.1 )\nv = base.dists.geometric.skewness( 0.5 )\n","base.dists.geometric.stdev":"var v = base.dists.geometric.stdev( 0.1 )\nv = base.dists.geometric.stdev( 0.5 )\n","base.dists.geometric.variance":"var v = base.dists.geometric.variance( 0.1 )\nv = base.dists.geometric.variance( 0.5 )\n","base.dists.gumbel.cdf":"var y = base.dists.gumbel.cdf( 10.0, 0.0, 3.0 )\ny = base.dists.gumbel.cdf( -2.0, 0.0, 3.0 )\ny = base.dists.gumbel.cdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.cdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.cdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.cdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.cdf( 0.0, 0.0, -1.0 )\n","base.dists.gumbel.cdf.factory":"var myCDF = base.dists.gumbel.cdf.factory( 2.0, 3.0 );\nvar y = myCDF( 10.0 )\ny = myCDF( 2.0 )\n","base.dists.gumbel.entropy":"var y = base.dists.gumbel.entropy( 0.0, 1.0 )\ny = base.dists.gumbel.entropy( 4.0, 2.0 )\ny = base.dists.gumbel.entropy( NaN, 1.0 )\ny = base.dists.gumbel.entropy( 0.0, NaN )\ny = base.dists.gumbel.entropy( 0.0, 0.0 )\n","base.dists.gumbel.Gumbel":"var gumbel = base.dists.gumbel.Gumbel( -2.0, 3.0 );\ngumbel.mu\ngumbel.beta\ngumbel.entropy\ngumbel.kurtosis\ngumbel.mean\ngumbel.median\ngumbel.mode\ngumbel.skewness\ngumbel.stdev\ngumbel.variance\ngumbel.cdf( 0.8 )\ngumbel.logcdf( 0.8 )\ngumbel.logpdf( 1.0 )\ngumbel.mgf( 0.2 )\ngumbel.pdf( 1.0 )\ngumbel.quantile( 0.8 )\n","base.dists.gumbel.kurtosis":"var y = base.dists.gumbel.kurtosis( 0.0, 1.0 )\ny = base.dists.gumbel.kurtosis( 4.0, 2.0 )\ny = base.dists.gumbel.kurtosis( NaN, 1.0 )\ny = base.dists.gumbel.kurtosis( 0.0, NaN )\ny = base.dists.gumbel.kurtosis( 0.0, 0.0 )\n","base.dists.gumbel.logcdf":"var y = base.dists.gumbel.logcdf( 10.0, 0.0, 3.0 )\ny = base.dists.gumbel.logcdf( -2.0, 0.0, 3.0 )\ny = base.dists.gumbel.logcdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.logcdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.logcdf( 0.0, 0.0, -1.0 )\n","base.dists.gumbel.logcdf.factory":"var myLCDF = base.dists.gumbel.logcdf.factory( 2.0, 3.0 );\nvar y = myLCDF( 10.0 )\ny = myLCDF( 2.0 )\n","base.dists.gumbel.logpdf":"var y = base.dists.gumbel.logpdf( 0.0, 0.0, 2.0 )\ny = base.dists.gumbel.logpdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.logpdf( 1.0, 3.0, 2.0 )\ny = base.dists.gumbel.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.logpdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.logpdf( 2.0, 0.0, -1.0 )\n","base.dists.gumbel.logpdf.factory":"var mylogpdf = base.dists.gumbel.logpdf.factory( 10.0, 2.0 );\nvar y = mylogpdf( 10.0 )\ny = mylogpdf( 12.0 )\n","base.dists.gumbel.mean":"var y = base.dists.gumbel.mean( 0.0, 1.0 )\ny = base.dists.gumbel.mean( 4.0, 2.0 )\ny = base.dists.gumbel.mean( NaN, 1.0 )\ny = base.dists.gumbel.mean( 0.0, NaN )\ny = base.dists.gumbel.mean( 0.0, 0.0 )\n","base.dists.gumbel.median":"var y = base.dists.gumbel.median( 0.0, 1.0 )\ny = base.dists.gumbel.median( 4.0, 2.0 )\ny = base.dists.gumbel.median( NaN, 1.0 )\ny = base.dists.gumbel.median( 0.0, NaN )\ny = base.dists.gumbel.median( 0.0, 0.0 )\n","base.dists.gumbel.mgf":"var y = base.dists.gumbel.mgf( -1.0, 0.0, 3.0 )\ny = base.dists.gumbel.mgf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.mgf( 0.1, 0.0, 3.0 )\ny = base.dists.gumbel.mgf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.mgf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.mgf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.mgf( 0.8, 0.0, 2.0 )\ny = base.dists.gumbel.mgf( 0.0, 0.0, -1.0 )\n","base.dists.gumbel.mgf.factory":"var myMGF = base.dists.gumbel.mgf.factory( 0.0, 3.0 );\nvar y = myMGF( -1.5 )\ny = myMGF( -1.0 )\n","base.dists.gumbel.mode":"var y = base.dists.gumbel.mode( 0.0, 1.0 )\ny = base.dists.gumbel.mode( 4.0, 2.0 )\ny = base.dists.gumbel.mode( NaN, 1.0 )\ny = base.dists.gumbel.mode( 0.0, NaN )\ny = base.dists.gumbel.mode( 0.0, 0.0 )\n","base.dists.gumbel.pdf":"var y = base.dists.gumbel.pdf( 0.0, 0.0, 2.0 )\ny = base.dists.gumbel.pdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.pdf( 1.0, 3.0, 2.0 )\ny = base.dists.gumbel.pdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.pdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.pdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.pdf( 2.0, 0.0, -1.0 )\n","base.dists.gumbel.pdf.factory":"var myPDF = base.dists.gumbel.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\ny = myPDF( 12.0 )\n","base.dists.gumbel.quantile":"var y = base.dists.gumbel.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.gumbel.quantile( 0.5, 4.0, 4.0 )\ny = base.dists.gumbel.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.quantile( 0.0, 0.0, NaN )\ny = base.dists.gumbel.quantile( 0.5, 0.0, -1.0 )\n","base.dists.gumbel.quantile.factory":"var myQuantile = base.dists.gumbel.quantile.factory( 8.0, 2.0 );\nvar y = myQuantile( 0.5 )\ny = myQuantile( 0.7 )\n","base.dists.gumbel.skewness":"var y = base.dists.gumbel.skewness( 0.0, 1.0 )\ny = base.dists.gumbel.skewness( 4.0, 2.0 )\ny = base.dists.gumbel.skewness( NaN, 1.0 )\ny = base.dists.gumbel.skewness( 0.0, NaN )\ny = base.dists.gumbel.skewness( 0.0, 0.0 )\n","base.dists.gumbel.stdev":"var y = base.dists.gumbel.stdev( 0.0, 1.0 )\ny = base.dists.gumbel.stdev( 4.0, 2.0 )\ny = base.dists.gumbel.stdev( NaN, 1.0 )\ny = base.dists.gumbel.stdev( 0.0, NaN )\ny = base.dists.gumbel.stdev( 0.0, 0.0 )\n","base.dists.gumbel.variance":"var y = base.dists.gumbel.variance( 0.0, 1.0 )\ny = base.dists.gumbel.variance( 4.0, 2.0 )\ny = base.dists.gumbel.variance( NaN, 1.0 )\ny = base.dists.gumbel.variance( 0.0, NaN )\ny = base.dists.gumbel.variance( 0.0, 0.0 )\n","base.dists.hypergeometric.cdf":"var y = base.dists.hypergeometric.cdf( 1.0, 8, 4, 2 )\ny = base.dists.hypergeometric.cdf( 1.5, 8, 4, 2 )\ny = base.dists.hypergeometric.cdf( 2.0, 8, 4, 2 )\ny = base.dists.hypergeometric.cdf( 0, 8, 4, 2)\ny = base.dists.hypergeometric.cdf( NaN, 10, 5, 2 )\ny = base.dists.hypergeometric.cdf( 0.0, NaN, 5, 2 )\ny = base.dists.hypergeometric.cdf( 0.0, 10, NaN, 2 )\ny = base.dists.hypergeometric.cdf( 0.0, 10, 5, NaN )\ny = base.dists.hypergeometric.cdf( 2.0, 10.5, 5, 2 )\ny = base.dists.hypergeometric.cdf( 2.0, 10, 1.5, 2 )\ny = base.dists.hypergeometric.cdf( 2.0, 10, 5, -2.0 )\ny = base.dists.hypergeometric.cdf( 2.0, 10, 5, 12 )\ny = base.dists.hypergeometric.cdf( 2.0, 8, 3, 9 )\n","base.dists.hypergeometric.cdf.factory":"var myCDF = base.dists.hypergeometric.cdf.factory( 30, 20, 5 );\nvar y = myCDF( 4.0 )\ny = myCDF( 1.0 )\n","base.dists.hypergeometric.Hypergeometric":"var hypergeometric = base.dists.hypergeometric.Hypergeometric( 100, 70, 20 );\nhypergeometric.N\nhypergeometric.K\nhypergeometric.n\nhypergeometric.kurtosis\nhypergeometric.mean\nhypergeometric.mode\nhypergeometric.skewness\nhypergeometric.stdev\nhypergeometric.variance\nhypergeometric.cdf( 2.9 )\nhypergeometric.logpmf( 10 )\nhypergeometric.pmf( 10 )\nhypergeometric.quantile( 0.8 )\n","base.dists.hypergeometric.kurtosis":"var v = base.dists.hypergeometric.kurtosis( 16, 11, 4 )\nv = base.dists.hypergeometric.kurtosis( 4, 2, 2 )\nv = base.dists.hypergeometric.kurtosis( 10, 5, 12 )\nv = base.dists.hypergeometric.kurtosis( 10.3, 10, 4 )\nv = base.dists.hypergeometric.kurtosis( 10, 5.5, 4 )\nv = base.dists.hypergeometric.kurtosis( 10, 5, 4.5 )\nv = base.dists.hypergeometric.kurtosis( NaN, 10, 4 )\nv = base.dists.hypergeometric.kurtosis( 20, NaN, 4 )\nv = base.dists.hypergeometric.kurtosis( 20, 10, NaN )\n","base.dists.hypergeometric.logpmf":"var y = base.dists.hypergeometric.logpmf( 1.0, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( 2.0, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( 1.5, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( NaN, 10, 5, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, NaN, 5, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, 10, NaN, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, 10, 5, NaN )\ny = base.dists.hypergeometric.logpmf( 2.0, 10.5, 5, 2 )\ny = base.dists.hypergeometric.logpmf( 2.0, 5, 1.5, 2 )\ny = base.dists.hypergeometric.logpmf( 2.0, 10, 5, -2.0 )\ny = base.dists.hypergeometric.logpmf( 2.0, 10, 5, 12 )\ny = base.dists.hypergeometric.logpmf( 2.0, 8, 3, 9 )\n","base.dists.hypergeometric.logpmf.factory":"var mylogPMF = base.dists.hypergeometric.logpmf.factory( 30, 20, 5 );\nvar y = mylogPMF( 4.0 )\ny = mylogPMF( 1.0 )\n","base.dists.hypergeometric.mean":"var v = base.dists.hypergeometric.mean( 16, 11, 4 )\nv = base.dists.hypergeometric.mean( 2, 1, 1 )\nv = base.dists.hypergeometric.mean( 10, 5, 12 )\nv = base.dists.hypergeometric.mean( 10.3, 10, 4 )\nv = base.dists.hypergeometric.mean( 10, 5.5, 4 )\nv = base.dists.hypergeometric.mean( 10, 5, 4.5 )\nv = base.dists.hypergeometric.mean( NaN, 10, 4 )\nv = base.dists.hypergeometric.mean( 20, NaN, 4 )\nv = base.dists.hypergeometric.mean( 20, 10, NaN )\n","base.dists.hypergeometric.mode":"var v = base.dists.hypergeometric.mode( 16, 11, 4 )\nv = base.dists.hypergeometric.mode( 2, 1, 1 )\nv = base.dists.hypergeometric.mode( 10, 5, 12 )\nv = base.dists.hypergeometric.mode( 10.3, 10, 4 )\nv = base.dists.hypergeometric.mode( 10, 5.5, 4 )\nv = base.dists.hypergeometric.mode( 10, 5, 4.5 )\nv = base.dists.hypergeometric.mode( NaN, 10, 4 )\nv = base.dists.hypergeometric.mode( 20, NaN, 4 )\nv = base.dists.hypergeometric.mode( 20, 10, NaN )\n","base.dists.hypergeometric.pmf":"var y = base.dists.hypergeometric.pmf( 1.0, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( 2.0, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( 1.5, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( NaN, 10, 5, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, NaN, 5, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, 10, NaN, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, 10, 5, NaN )\ny = base.dists.hypergeometric.pmf( 2.0, 10.5, 5, 2 )\ny = base.dists.hypergeometric.pmf( 2.0, 5, 1.5, 2 )\ny = base.dists.hypergeometric.pmf( 2.0, 10, 5, -2.0 )\ny = base.dists.hypergeometric.pmf( 2.0, 10, 5, 12 )\ny = base.dists.hypergeometric.pmf( 2.0, 8, 3, 9 )\n","base.dists.hypergeometric.pmf.factory":"var myPMF = base.dists.hypergeometric.pmf.factory( 30, 20, 5 );\nvar y = myPMF( 4.0 )\ny = myPMF( 1.0 )\n","base.dists.hypergeometric.quantile":"var y = base.dists.hypergeometric.quantile( 0.4, 40, 20, 10 )\ny = base.dists.hypergeometric.quantile( 0.8, 60, 40, 20 )\ny = base.dists.hypergeometric.quantile( 0.5, 100, 10, 10 )\ny = base.dists.hypergeometric.quantile( 0.0, 100, 40, 20 )\ny = base.dists.hypergeometric.quantile( 1.0, 100, 40, 20 )\ny = base.dists.hypergeometric.quantile( NaN, 40, 20, 10 )\ny = base.dists.hypergeometric.quantile( 0.2, NaN, 20, 10 )\ny = base.dists.hypergeometric.quantile( 0.2, 40, NaN, 10 )\ny = base.dists.hypergeometric.quantile( 0.2, 40, 20, NaN )\n","base.dists.hypergeometric.quantile.factory":"var myQuantile = base.dists.hypergeometric.quantile.factory( 100, 20, 10 );\nvar y = myQuantile( 0.2 )\ny = myQuantile( 0.9 )\n","base.dists.hypergeometric.skewness":"var v = base.dists.hypergeometric.skewness( 16, 11, 4 )\nv = base.dists.hypergeometric.skewness( 4, 2, 2 )\nv = base.dists.hypergeometric.skewness( 10, 5, 12 )\nv = base.dists.hypergeometric.skewness( 10.3, 10, 4 )\nv = base.dists.hypergeometric.skewness( 10, 5.5, 4 )\nv = base.dists.hypergeometric.skewness( 10, 5, 4.5 )\nv = base.dists.hypergeometric.skewness( NaN, 10, 4 )\nv = base.dists.hypergeometric.skewness( 20, NaN, 4 )\nv = base.dists.hypergeometric.skewness( 20, 10, NaN )\n","base.dists.hypergeometric.stdev":"var v = base.dists.hypergeometric.stdev( 16, 11, 4 )\nv = base.dists.hypergeometric.stdev( 2, 1, 1 )\nv = base.dists.hypergeometric.stdev( 10, 5, 12 )\nv = base.dists.hypergeometric.stdev( 10.3, 10, 4 )\nv = base.dists.hypergeometric.stdev( 10, 5.5, 4 )\nv = base.dists.hypergeometric.stdev( 10, 5, 4.5 )\nv = base.dists.hypergeometric.stdev( NaN, 10, 4 )\nv = base.dists.hypergeometric.stdev( 20, NaN, 4 )\nv = base.dists.hypergeometric.stdev( 20, 10, NaN )\n","base.dists.hypergeometric.variance":"var v = base.dists.hypergeometric.variance( 16, 11, 4 )\nv = base.dists.hypergeometric.variance( 2, 1, 1 )\nv = base.dists.hypergeometric.variance( 10, 5, 12 )\nv = base.dists.hypergeometric.variance( 10.3, 10, 4 )\nv = base.dists.hypergeometric.variance( 10, 5.5, 4 )\nv = base.dists.hypergeometric.variance( 10, 5, 4.5 )\nv = base.dists.hypergeometric.variance( NaN, 10, 4 )\nv = base.dists.hypergeometric.variance( 20, NaN, 4 )\nv = base.dists.hypergeometric.variance( 20, 10, NaN )\n","base.dists.invgamma.cdf":"var y = base.dists.invgamma.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.invgamma.cdf( 2.0, 3.0, 1.0 )\ny = base.dists.invgamma.cdf( -1.0, 2.0, 2.0 )\ny = base.dists.invgamma.cdf( PINF, 4.0, 2.0 )\ny = base.dists.invgamma.cdf( NINF, 4.0, 2.0 )\ny = base.dists.invgamma.cdf( NaN, 0.0, 1.0 )\ny = base.dists.invgamma.cdf( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.cdf( 0.0, 0.0, NaN )\ny = base.dists.invgamma.cdf( 2.0, -1.0, 1.0 )\ny = base.dists.invgamma.cdf( 2.0, 1.0, -1.0 )\n","base.dists.invgamma.cdf.factory":"var myCDF = base.dists.invgamma.cdf.factory( 2.0, 0.5 );\nvar y = myCDF( 0.5 )\ny = myCDF( 2.0 )\n","base.dists.invgamma.entropy":"var v = base.dists.invgamma.entropy( 1.0, 1.0 )\nv = base.dists.invgamma.entropy( 4.0, 12.0 )\nv = base.dists.invgamma.entropy( 8.0, 2.0 )\n","base.dists.invgamma.InvGamma":"var invgamma = base.dists.invgamma.InvGamma( 6.0, 5.0 );\ninvgamma.alpha\ninvgamma.beta\ninvgamma.entropy\ninvgamma.kurtosis\ninvgamma.mean\ninvgamma.mode\ninvgamma.skewness\ninvgamma.stdev\ninvgamma.variance\ninvgamma.cdf( 0.8 )\ninvgamma.pdf( 1.0 )\ninvgamma.logpdf( 1.0 )\ninvgamma.quantile( 0.8 )\n","base.dists.invgamma.kurtosis":"var v = base.dists.invgamma.kurtosis( 7.0, 5.0 )\nv = base.dists.invgamma.kurtosis( 6.0, 12.0 )\nv = base.dists.invgamma.kurtosis( 8.0, 2.0 )\n","base.dists.invgamma.logpdf":"var y = base.dists.invgamma.logpdf( 2.0, 0.5, 1.0 )\ny = base.dists.invgamma.logpdf( 0.2, 1.0, 1.0 )\ny = base.dists.invgamma.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.invgamma.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.invgamma.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.logpdf( 0.0, 1.0, NaN )\ny = base.dists.invgamma.logpdf( 2.0, -1.0, 1.0 )\ny = base.dists.invgamma.logpdf( 2.0, 1.0, -1.0 )\n","base.dists.invgamma.logpdf.factory":"var mylogPDF = base.dists.invgamma.logpdf.factory( 6.0, 7.0 );\nvar y = mylogPDF( 2.0 )\n","base.dists.invgamma.mean":"var v = base.dists.invgamma.mean( 4.0, 12.0 )\nv = base.dists.invgamma.mean( 8.0, 2.0 )\n","base.dists.invgamma.mode":"var v = base.dists.invgamma.mode( 1.0, 1.0 )\nv = base.dists.invgamma.mode( 4.0, 12.0 )\nv = base.dists.invgamma.mode( 8.0, 2.0 )\n","base.dists.invgamma.pdf":"var y = base.dists.invgamma.pdf( 2.0, 0.5, 1.0 )\ny = base.dists.invgamma.pdf( 0.2, 1.0, 1.0 )\ny = base.dists.invgamma.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.invgamma.pdf( NaN, 1.0, 1.0 )\ny = base.dists.invgamma.pdf( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.pdf( 0.0, 1.0, NaN )\ny = base.dists.invgamma.pdf( 2.0, -1.0, 1.0 )\ny = base.dists.invgamma.pdf( 2.0, 1.0, -1.0 )\n","base.dists.invgamma.pdf.factory":"var myPDF = base.dists.invgamma.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 2.0 )\n","base.dists.invgamma.quantile":"var y = base.dists.invgamma.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.invgamma.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.invgamma.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.invgamma.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.invgamma.quantile( NaN, 1.0, 1.0 )\ny = base.dists.invgamma.quantile( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.quantile( 0.0, 1.0, NaN )\ny = base.dists.invgamma.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.invgamma.quantile( 0.5, 1.0, -1.0 )\n","base.dists.invgamma.quantile.factory":"var myQuantile = base.dists.invgamma.quantile.factory( 2.0, 2.0 );\nvar y = myQuantile( 0.8 )\ny = myQuantile( 0.4 )\n","base.dists.invgamma.skewness":"var v = base.dists.invgamma.skewness( 4.0, 12.0 )\nv = base.dists.invgamma.skewness( 8.0, 2.0 )\n","base.dists.invgamma.stdev":"var v = base.dists.invgamma.stdev( 5.0, 7.0 )\nv = base.dists.invgamma.stdev( 4.0, 12.0 )\nv = base.dists.invgamma.stdev( 8.0, 2.0 )\n","base.dists.invgamma.variance":"var v = base.dists.invgamma.variance( 5.0, 7.0 )\nv = base.dists.invgamma.variance( 4.0, 12.0 )\nv = base.dists.invgamma.variance( 8.0, 2.0 )\n","base.dists.kumaraswamy.cdf":"var y = base.dists.kumaraswamy.cdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.cdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.cdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.cdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.cdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.cdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.cdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.cdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.cdf( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.cdf.factory":"var mycdf = base.dists.kumaraswamy.cdf.factory( 0.5, 1.0 );\nvar y = mycdf( 0.8 )\ny = mycdf( 0.3 )\n","base.dists.kumaraswamy.Kumaraswamy":"var kumaraswamy = base.dists.kumaraswamy.Kumaraswamy( 6.0, 5.0 );\nkumaraswamy.a\nkumaraswamy.b\nkumaraswamy.kurtosis\nkumaraswamy.mean\nkumaraswamy.mode\nkumaraswamy.skewness\nkumaraswamy.stdev\nkumaraswamy.variance\nkumaraswamy.cdf( 0.8 )\nkumaraswamy.pdf( 1.0 )\nkumaraswamy.quantile( 0.8 )\n","base.dists.kumaraswamy.kurtosis":"var v = base.dists.kumaraswamy.kurtosis( 1.0, 1.0 )\nv = base.dists.kumaraswamy.kurtosis( 4.0, 12.0 )\nv = base.dists.kumaraswamy.kurtosis( 16.0, 8.0 )\n","base.dists.kumaraswamy.logcdf":"var y = base.dists.kumaraswamy.logcdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logcdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.logcdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.logcdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.logcdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logcdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.logcdf( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.logcdf.factory":"var mylogcdf = base.dists.kumaraswamy.logcdf.factory( 0.5, 1.0 );\nvar y = mylogcdf( 0.8 )\ny = mylogcdf( 0.3 )\n","base.dists.kumaraswamy.logpdf":"var y = base.dists.kumaraswamy.logpdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logpdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.logpdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.logpdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.logpdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logpdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logpdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.logpdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.logpdf( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.logpdf.factory":"var mylogpdf = base.dists.kumaraswamy.logpdf.factory( 0.5, 1.0 );\nvar y = mylogpdf( 0.8 )\ny = mylogpdf( 0.3 )\n","base.dists.kumaraswamy.mean":"var v = base.dists.kumaraswamy.mean( 1.5, 1.5 )\nv = base.dists.kumaraswamy.mean( 4.0, 12.0 )\nv = base.dists.kumaraswamy.mean( 16.0, 8.0 )\n","base.dists.kumaraswamy.median":"var v = base.dists.kumaraswamy.median( 1.0, 1.0 )\nv = base.dists.kumaraswamy.median( 4.0, 12.0 )\nv = base.dists.kumaraswamy.median( 16.0, 8.0 )\n","base.dists.kumaraswamy.mode":"var v = base.dists.kumaraswamy.mode( 1.5, 1.5 )\nv = base.dists.kumaraswamy.mode( 4.0, 12.0 )\nv = base.dists.kumaraswamy.mode( 16.0, 8.0 )\n","base.dists.kumaraswamy.pdf":"var y = base.dists.kumaraswamy.pdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.pdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.pdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.pdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.pdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.pdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.pdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.pdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.pdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.pdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.pdf( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.pdf.factory":"var mypdf = base.dists.kumaraswamy.pdf.factory( 0.5, 1.0 );\nvar y = mypdf( 0.8 )\ny = mypdf( 0.3 )\n","base.dists.kumaraswamy.quantile":"var y = base.dists.kumaraswamy.quantile( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.quantile( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.quantile( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.quantile( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.quantile( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.quantile( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.quantile( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.quantile( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.quantile( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.quantile( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.quantile( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.quantile.factory":"var myQuantile = base.dists.kumaraswamy.quantile.factory( 0.5, 1.0 );\nvar y = myQuantile( 0.8 )\ny = myQuantile( 0.3 )\n","base.dists.kumaraswamy.skewness":"var v = base.dists.kumaraswamy.skewness( 1.0, 1.0 )\nv = base.dists.kumaraswamy.skewness( 4.0, 12.0 )\nv = base.dists.kumaraswamy.skewness( 16.0, 8.0 )\n","base.dists.kumaraswamy.stdev":"var v = base.dists.kumaraswamy.stdev( 1.0, 1.0 )\nv = base.dists.kumaraswamy.stdev( 4.0, 12.0 )\nv = base.dists.kumaraswamy.stdev( 16.0, 8.0 )\n","base.dists.kumaraswamy.variance":"var v = base.dists.kumaraswamy.variance( 1.0, 1.0 )\nv = base.dists.kumaraswamy.variance( 4.0, 12.0 )\nv = base.dists.kumaraswamy.variance( 16.0, 8.0 )\n","base.dists.laplace.cdf":"var y = base.dists.laplace.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.cdf( 5.0, 10.0, 3.0 )\ny = base.dists.laplace.cdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.cdf( 2, NaN, 1.0 )\ny = base.dists.laplace.cdf( 2.0, 0.0, NaN )\ny = base.dists.laplace.cdf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.cdf.factory":"var myCDF = base.dists.laplace.cdf.factory( 2.0, 3.0 );\nvar y = myCDF( 10.0 )\ny = myCDF( 2.0 )\n","base.dists.laplace.entropy":"var y = base.dists.laplace.entropy( 0.0, 1.0 )\ny = base.dists.laplace.entropy( 4.0, 2.0 )\ny = base.dists.laplace.entropy( NaN, 1.0 )\ny = base.dists.laplace.entropy( 0.0, NaN )\ny = base.dists.laplace.entropy( 0.0, 0.0 )\n","base.dists.laplace.kurtosis":"var y = base.dists.laplace.kurtosis( 0.0, 1.0 )\ny = base.dists.laplace.kurtosis( 4.0, 2.0 )\ny = base.dists.laplace.kurtosis( NaN, 1.0 )\ny = base.dists.laplace.kurtosis( 0.0, NaN )\ny = base.dists.laplace.kurtosis( 0.0, 0.0 )\n","base.dists.laplace.Laplace":"var laplace = base.dists.laplace.Laplace( -2.0, 3.0 );\nlaplace.mu\nlaplace.b\nlaplace.entropy\nlaplace.kurtosis\nlaplace.mean\nlaplace.median\nlaplace.mode\nlaplace.skewness\nlaplace.stdev\nlaplace.variance\nlaplace.cdf( 0.8 )\nlaplace.logcdf( 0.8 )\nlaplace.logpdf( 1.0 )\nlaplace.mgf( 0.2 )\nlaplace.pdf( 2.0 )\nlaplace.quantile( 0.9 )\n","base.dists.laplace.logcdf":"var y = base.dists.laplace.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.logcdf( 5.0, 10.0, 3.0 )\ny = base.dists.laplace.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.logcdf( 2, NaN, 1.0 )\ny = base.dists.laplace.logcdf( 2.0, 0.0, NaN )\ny = base.dists.laplace.logcdf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.logcdf.factory":"var mylogcdf = base.dists.laplace.logcdf.factory( 2.0, 3.0 );\nvar y = mylogcdf( 10.0 )\ny = mylogcdf( 2.0 )\n","base.dists.laplace.logpdf":"var y = base.dists.laplace.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.logpdf( -1.0, 2.0, 3.0 )\ny = base.dists.laplace.logpdf( 2.5, 2.0, 3.0 )\ny = base.dists.laplace.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.laplace.logpdf( 0.0, 0.0, NaN )\ny = base.dists.laplace.logpdf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.logpdf.factory":"var mylogPDF = base.dists.laplace.logpdf.factory( 10.0, 2.0 );\nvar y = mylogPDF( 10.0 )\n","base.dists.laplace.mean":"var y = base.dists.laplace.mean( 0.0, 1.0 )\ny = base.dists.laplace.mean( 4.0, 2.0 )\ny = base.dists.laplace.mean( NaN, 1.0 )\ny = base.dists.laplace.mean( 0.0, NaN )\ny = base.dists.laplace.mean( 0.0, 0.0 )\n","base.dists.laplace.median":"var y = base.dists.laplace.median( 0.0, 1.0 )\ny = base.dists.laplace.median( 4.0, 2.0 )\ny = base.dists.laplace.median( NaN, 1.0 )\ny = base.dists.laplace.median( 0.0, NaN )\ny = base.dists.laplace.median( 0.0, 0.0 )\n","base.dists.laplace.mgf":"var y = base.dists.laplace.mgf( 0.5, 0.0, 1.0 )\ny = base.dists.laplace.mgf( 0.0, 0.0, 1.0 )\ny = base.dists.laplace.mgf( -1.0, 4.0, 0.2 )\ny = base.dists.laplace.mgf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.mgf( 0.0, NaN, 1.0 )\ny = base.dists.laplace.mgf( 0.0, 0.0, NaN )\ny = base.dists.laplace.mgf( 1.0, 0.0, 2.0 )\ny = base.dists.laplace.mgf( -0.5, 0.0, 4.0 )\ny = base.dists.laplace.mgf( 2.0, 0.0, 0.0 )\ny = base.dists.laplace.mgf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.mgf.factory":"var mymgf = base.dists.laplace.mgf.factory( 4.0, 2.0 );\nvar y = mymgf( 0.2 )\ny = mymgf( 0.4 )\n","base.dists.laplace.mode":"var y = base.dists.laplace.mode( 0.0, 1.0 )\ny = base.dists.laplace.mode( 4.0, 2.0 )\ny = base.dists.laplace.mode( NaN, 1.0 )\ny = base.dists.laplace.mode( 0.0, NaN )\ny = base.dists.laplace.mode( 0.0, 0.0 )\n","base.dists.laplace.pdf":"var y = base.dists.laplace.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.pdf( -1.0, 2.0, 3.0 )\ny = base.dists.laplace.pdf( 2.5, 2.0, 3.0 )\ny = base.dists.laplace.pdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.pdf( 0.0, NaN, 1.0 )\ny = base.dists.laplace.pdf( 0.0, 0.0, NaN )\ny = base.dists.laplace.pdf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.pdf.factory":"var myPDF = base.dists.laplace.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\n","base.dists.laplace.quantile":"var y = base.dists.laplace.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.laplace.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.laplace.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.laplace.quantile( -0.2, 0.0, 1.0 )\ny = 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base.dists.logistic.median( 0.0, 0.0 )\n","base.dists.logistic.mgf":"var y = base.dists.logistic.mgf( 0.9, 0.0, 1.0 )\ny = base.dists.logistic.mgf( 0.1, 4.0, 4.0 )\ny = base.dists.logistic.mgf( -0.2, 4.0, 4.0 )\ny = base.dists.logistic.mgf( 0.5, 0.0, -1.0 )\ny = base.dists.logistic.mgf( 0.5, 0.0, 4.0 )\ny = base.dists.logistic.mgf( NaN, 0.0, 1.0 )\ny = base.dists.logistic.mgf( 0.0, NaN, 1.0 )\ny = base.dists.logistic.mgf( 0.0, 0.0, NaN )\n","base.dists.logistic.mgf.factory":"var mymgf = base.dists.logistic.mgf.factory( 10.0, 0.5 );\nvar y = mymgf( 0.5 )\ny = mymgf( 2.0 )\n","base.dists.logistic.mode":"var y = base.dists.logistic.mode( 0.0, 1.0 )\ny = base.dists.logistic.mode( 4.0, 2.0 )\ny = base.dists.logistic.mode( NaN, 1.0 )\ny = base.dists.logistic.mode( 0.0, NaN )\ny = base.dists.logistic.mode( 0.0, 0.0 )\n","base.dists.logistic.pdf":"var y = base.dists.logistic.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.logistic.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.logistic.pdf( NaN, 0.0, 1.0 )\ny = base.dists.logistic.pdf( 0.0, NaN, 1.0 )\ny = base.dists.logistic.pdf( 0.0, 0.0, NaN )\ny = base.dists.logistic.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.logistic.pdf( 2.0, 8.0, 0.0 )\ny = base.dists.logistic.pdf( 8.0, 8.0, 0.0 )\n","base.dists.logistic.pdf.factory":"var myPDF = base.dists.logistic.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\n","base.dists.logistic.quantile":"var y = base.dists.logistic.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.logistic.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.logistic.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.logistic.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.logistic.quantile( NaN, 0.0, 1.0 )\ny = base.dists.logistic.quantile( 0.0, NaN, 1.0 )\ny = base.dists.logistic.quantile( 0.0, 0.0, NaN )\ny = base.dists.logistic.quantile( 0.5, 0.0, -1.0 )\n","base.dists.logistic.quantile.factory":"var myQuantile = base.dists.logistic.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.logistic.skewness":"var y = 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0.0, 1.0 )\ny = base.dists.lognormal.logpdf( 1.0, 3.0, 1.0 )\ny = base.dists.lognormal.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.lognormal.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.logpdf( 0.0, 0.0, NaN )\ny = base.dists.lognormal.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.logpdf( 2.0, 0.0, 0.0 )\n","base.dists.lognormal.logpdf.factory":"var mylogPDF = base.dists.lognormal.logpdf.factory( 4.0, 2.0 );\nvar y = mylogPDF( 10.0 )\ny = mylogPDF( 2.0 )\n","base.dists.lognormal.mean":"var y = base.dists.lognormal.mean( 0.0, 1.0 )\ny = base.dists.lognormal.mean( 4.0, 2.0 )\ny = base.dists.lognormal.mean( NaN, 1.0 )\ny = base.dists.lognormal.mean( 0.0, NaN )\ny = base.dists.lognormal.mean( 0.0, 0.0 )\n","base.dists.lognormal.median":"var y = base.dists.lognormal.median( 0.0, 1.0 )\ny = base.dists.lognormal.median( 5.0, 2.0 )\ny = base.dists.lognormal.median( NaN, 1.0 )\ny = base.dists.lognormal.median( 0.0, NaN )\ny = base.dists.lognormal.median( 0.0, 0.0 )\n","base.dists.lognormal.mode":"var y = base.dists.lognormal.mode( 0.0, 1.0 )\ny = base.dists.lognormal.mode( 5.0, 2.0 )\ny = base.dists.lognormal.mode( NaN, 1.0 )\ny = base.dists.lognormal.mode( 0.0, NaN )\ny = base.dists.lognormal.mode( 0.0, 0.0 )\n","base.dists.lognormal.pdf":"var y = base.dists.lognormal.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.pdf( 1.0, 0.0, 1.0 )\ny = base.dists.lognormal.pdf( 1.0, 3.0, 1.0 )\ny = base.dists.lognormal.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.lognormal.pdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.pdf( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.pdf( 0.0, 0.0, NaN )\ny = base.dists.lognormal.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.pdf( 2.0, 0.0, 0.0 )\n","base.dists.lognormal.pdf.factory":"var myPDF = base.dists.lognormal.pdf.factory( 4.0, 2.0 );\nvar y = myPDF( 10.0 )\ny = myPDF( 2.0 )\n","base.dists.lognormal.quantile":"var y = base.dists.lognormal.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.lognormal.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.quantile( 0.0, 0.0, NaN )\ny = base.dists.lognormal.quantile( 0.5, 0.0, -1.0 )\ny = base.dists.lognormal.quantile( 0.5, 0.0, 0.0 )\n","base.dists.lognormal.quantile.factory":"var myQuantile = base.dists.lognormal.quantile.factory( 4.0, 2.0 );\nvar y = myQuantile( 0.2 )\ny = myQuantile( 0.8 )\n","base.dists.lognormal.skewness":"var y = base.dists.lognormal.skewness( 0.0, 1.0 )\ny = base.dists.lognormal.skewness( 5.0, 2.0 )\ny = base.dists.lognormal.skewness( NaN, 1.0 )\ny = base.dists.lognormal.skewness( 0.0, NaN )\ny = base.dists.lognormal.skewness( 0.0, 0.0 )\n","base.dists.lognormal.stdev":"var y = base.dists.lognormal.stdev( 0.0, 1.0 )\ny = base.dists.lognormal.stdev( 4.0, 2.0 )\ny = base.dists.lognormal.stdev( NaN, 1.0 )\ny = base.dists.lognormal.stdev( 0.0, NaN )\ny = base.dists.lognormal.stdev( 0.0, 0.0 )\n","base.dists.lognormal.variance":"var y = base.dists.lognormal.variance( 0.0, 1.0 )\ny = base.dists.lognormal.variance( 4.0, 2.0 )\ny = base.dists.lognormal.variance( NaN, 1.0 )\ny = base.dists.lognormal.variance( 0.0, NaN )\ny = base.dists.lognormal.variance( 0.0, 0.0 )\n","base.dists.negativeBinomial.cdf":"var y = base.dists.negativeBinomial.cdf( 5.0, 20.0, 0.8 )\ny = base.dists.negativeBinomial.cdf( 21.0, 20.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( 5.0, 10.0, 0.4 )\ny = base.dists.negativeBinomial.cdf( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.cdf( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.cdf( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.cdf( 2.0, 0.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( 2.0, -2.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.cdf( 0.0, 20.0, NaN )\ny = base.dists.negativeBinomial.cdf( 2.0, 20, -1.0 )\ny = base.dists.negativeBinomial.cdf( 2.0, 20, 1.5 )\n","base.dists.negativeBinomial.cdf.factory":"var myCDF = base.dists.negativeBinomial.cdf.factory( 10, 0.5 );\nvar y = myCDF( 3.0 )\ny = myCDF( 11.0 )\n","base.dists.negativeBinomial.kurtosis":"var v = base.dists.negativeBinomial.kurtosis( 100, 0.2 )\nv = base.dists.negativeBinomial.kurtosis( 20, 0.5 )\n","base.dists.negativeBinomial.logpmf":"var y = base.dists.negativeBinomial.logpmf( 5.0, 20.0, 0.8 )\ny = base.dists.negativeBinomial.logpmf( 21.0, 20.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 5.0, 10.0, 0.4 )\ny = base.dists.negativeBinomial.logpmf( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.logpmf( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.logpmf( 2.0, 0.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 2.0, -2.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 2.0, 20, -1.0 )\ny = base.dists.negativeBinomial.logpmf( 2.0, 20, 1.5 )\ny = base.dists.negativeBinomial.logpmf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 0.0, 20.0, NaN )\n","base.dists.negativeBinomial.logpmf.factory":"var mylogPMF = base.dists.negativeBinomial.logpmf.factory( 10, 0.5 );\nvar y = mylogPMF( 3.0 )\ny = mylogPMF( 5.0 )\n","base.dists.negativeBinomial.mean":"var v = base.dists.negativeBinomial.mean( 100, 0.2 )\nv = base.dists.negativeBinomial.mean( 20, 0.5 )\n","base.dists.negativeBinomial.mgf":"var y = base.dists.negativeBinomial.mgf( 0.05, 20.0, 0.8 )\ny = base.dists.negativeBinomial.mgf( 0.1, 20.0, 0.1 )\ny = base.dists.negativeBinomial.mgf( 0.5, 10.0, 0.4 )\ny = base.dists.negativeBinomial.mgf( 0.1, 0.0, 0.5 )\ny = base.dists.negativeBinomial.mgf( 0.1, -2.0, 0.5 )\ny = base.dists.negativeBinomial.mgf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.mgf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.mgf( 0.0, 20.0, NaN )\ny = base.dists.negativeBinomial.mgf( 0.2, 20, -1.0 )\ny = base.dists.negativeBinomial.mgf( 0.2, 20, 1.5 )\n","base.dists.negativeBinomial.mgf.factory":"var myMGF = base.dists.negativeBinomial.mgf.factory( 4.3, 0.4 );\nvar y = myMGF( 0.2 )\ny = myMGF( 0.4 )\n","base.dists.negativeBinomial.mode":"var v = base.dists.negativeBinomial.mode( 100, 0.2 )\nv = base.dists.negativeBinomial.mode( 20, 0.5 )\n","base.dists.negativeBinomial.NegativeBinomial":"var nbinomial = base.dists.negativeBinomial.NegativeBinomial( 8.0, 0.5 );\nnbinomial.r\nnbinomial.p\nnbinomial.kurtosis\nnbinomial.mean\nnbinomial.mode\nnbinomial.skewness\nnbinomial.stdev\nnbinomial.variance\nnbinomial.cdf( 2.9 )\nnbinomial.logpmf( 3.0 )\nnbinomial.mgf( 0.2 )\nnbinomial.pmf( 3.0 )\nnbinomial.quantile( 0.8 )\n","base.dists.negativeBinomial.pmf":"var y = base.dists.negativeBinomial.pmf( 5.0, 20.0, 0.8 )\ny = base.dists.negativeBinomial.pmf( 21.0, 20.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 5.0, 10.0, 0.4 )\ny = base.dists.negativeBinomial.pmf( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.pmf( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.pmf( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.pmf( 2.0, 0.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 2.0, -2.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 2.0, 20, -1.0 )\ny = base.dists.negativeBinomial.pmf( 2.0, 20, 1.5 )\ny = base.dists.negativeBinomial.pmf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.pmf( 0.0, 20.0, NaN )\n","base.dists.negativeBinomial.pmf.factory":"var myPMF = base.dists.negativeBinomial.pmf.factory( 10, 0.5 );\nvar y = myPMF( 3.0 )\ny = myPMF( 5.0 )\n","base.dists.negativeBinomial.quantile":"var y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.2 )\ny = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.8 )\ny = base.dists.negativeBinomial.quantile( 0.5, 10.0, 0.4 )\ny = base.dists.negativeBinomial.quantile( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.quantile( 1.1, 20.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( -0.1, 20.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.quantile( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.quantile( 0.5, 0.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.5, -2.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.3, 20.0, -1.0 )\ny = base.dists.negativeBinomial.quantile( 0.3, 20.0, 1.5 )\ny = base.dists.negativeBinomial.quantile( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.3, NaN, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.3, 20.0, NaN )\n","base.dists.negativeBinomial.quantile.factory":"var myQuantile = base.dists.negativeBinomial.quantile.factory( 10.0, 0.5 );\nvar y = myQuantile( 0.1 )\ny = myQuantile( 0.9 )\n","base.dists.negativeBinomial.skewness":"var v = base.dists.negativeBinomial.skewness( 100, 0.2 )\nv = base.dists.negativeBinomial.skewness( 20, 0.5 )\n","base.dists.negativeBinomial.stdev":"var v = base.dists.negativeBinomial.stdev( 100, 0.2 )\nv = base.dists.negativeBinomial.stdev( 20, 0.5 )\n","base.dists.negativeBinomial.variance":"var v = base.dists.negativeBinomial.variance( 100, 0.2 )\nv = base.dists.negativeBinomial.variance( 20, 0.5 )\n","base.dists.normal.cdf":"var y = base.dists.normal.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.cdf( -1.0, -1.0, 2.0 )\ny = base.dists.normal.cdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.cdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.cdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.cdf( 0.0, 0.0, NaN )\ny = base.dists.normal.cdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.cdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.cdf( 8.0, 8.0, 0.0 )\ny = base.dists.normal.cdf( 10.0, 8.0, 0.0 )\n","base.dists.normal.cdf.factory":"var myCDF = base.dists.normal.cdf.factory( 10.0, 2.0 );\nvar y = myCDF( 10.0 )\n","base.dists.normal.entropy":"var y = base.dists.normal.entropy( 0.0, 1.0 )\ny = base.dists.normal.entropy( 4.0, 3.0 )\ny = base.dists.normal.entropy( NaN, 1.0 )\ny = base.dists.normal.entropy( 0.0, NaN )\ny = base.dists.normal.entropy( 0.0, 0.0 )\n","base.dists.normal.kurtosis":"var y = base.dists.normal.kurtosis( 0.0, 1.0 )\ny = base.dists.normal.kurtosis( 4.0, 3.0 )\ny = base.dists.normal.kurtosis( NaN, 1.0 )\ny = base.dists.normal.kurtosis( 0.0, NaN )\ny = base.dists.normal.kurtosis( 0.0, 0.0 )\n","base.dists.normal.logcdf":"var y = base.dists.normal.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.logcdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.logcdf( 0.0, 0.0, NaN )\ny = base.dists.normal.logcdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.logcdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.logcdf( 8.0, 8.0, 0.0 )\n","base.dists.normal.logcdf.factory":"var mylogcdf = base.dists.normal.logcdf.factory( 10.0, 2.0 );\nvar y = mylogcdf( 10.0 )\n","base.dists.normal.logpdf":"var y = base.dists.normal.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.logpdf( 0.0, 0.0, NaN )\ny = base.dists.normal.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.logpdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.logpdf( 8.0, 8.0, 0.0 )\n","base.dists.normal.logpdf.factory":"var myLogPDF = base.dists.normal.logpdf.factory( 10.0, 2.0 );\nvar y = myLogPDF( 10.0 )\n","base.dists.normal.mean":"var y = base.dists.normal.mean( 0.0, 1.0 )\ny = base.dists.normal.mean( 4.0, 2.0 )\ny = base.dists.normal.mean( NaN, 1.0 )\ny = base.dists.normal.mean( 0.0, NaN )\ny = base.dists.normal.mean( 0.0, 0.0 )\n","base.dists.normal.median":"var y = base.dists.normal.median( 0.0, 1.0 )\ny = base.dists.normal.median( 4.0, 2.0 )\ny = base.dists.normal.median( NaN, 1.0 )\ny = base.dists.normal.median( 0.0, NaN )\ny = base.dists.normal.median( 0.0, 0.0 )\n","base.dists.normal.mgf":"var y = base.dists.normal.mgf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.mgf( 0.0, 0.0, 1.0 )\ny = base.dists.normal.mgf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.mgf( NaN, 0.0, 1.0 )\ny = base.dists.normal.mgf( 0.0, NaN, 1.0 )\ny = base.dists.normal.mgf( 0.0, 0.0, NaN )\ny = base.dists.normal.mgf( 2.0, 0.0, 0.0 )\n","base.dists.normal.mgf.factory":"var myMGF = base.dists.normal.mgf.factory( 4.0, 2.0 );\nvar y = myMGF( 1.0 )\ny = myMGF( 0.5 )\n","base.dists.normal.mode":"var y = base.dists.normal.mode( 0.0, 1.0 )\ny = base.dists.normal.mode( 4.0, 2.0 )\ny = base.dists.normal.mode( NaN, 1.0 )\ny = base.dists.normal.mode( 0.0, NaN )\ny = base.dists.normal.mode( 0.0, 0.0 )\n","base.dists.normal.Normal":"var normal = base.dists.normal.Normal( -2.0, 3.0 );\nnormal.mu\nnormal.sigma\nnormal.entropy\nnormal.kurtosis\nnormal.mean\nnormal.median\nnormal.mode\nnormal.skewness\nnormal.stdev\nnormal.variance\nnormal.cdf( 0.8 )\nnormal.logcdf( 0.8 )\nnormal.logpdf( 2.0 )\nnormal.mgf( 0.2 )\nnormal.pdf( 2.0 )\nnormal.quantile( 0.9 )\n","base.dists.normal.pdf":"var y = base.dists.normal.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.pdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.pdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.pdf( 0.0, 0.0, NaN )\ny = base.dists.normal.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.pdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.pdf( 8.0, 8.0, 0.0 )\n","base.dists.normal.pdf.factory":"var myPDF = base.dists.normal.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\n","base.dists.normal.quantile":"var y = base.dists.normal.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.normal.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.normal.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.normal.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.normal.quantile( NaN, 0.0, 1.0 )\ny = base.dists.normal.quantile( 0.0, NaN, 1.0 )\ny = base.dists.normal.quantile( 0.0, 0.0, NaN )\ny = base.dists.normal.quantile( 0.5, 0.0, -1.0 )\ny = base.dists.normal.quantile( 0.3, 8.0, 0.0 )\ny = base.dists.normal.quantile( 0.9, 8.0, 0.0 )\n","base.dists.normal.quantile.factory":"var myQuantile = base.dists.normal.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.normal.skewness":"var y = base.dists.normal.skewness( 0.0, 1.0 )\ny = base.dists.normal.skewness( 4.0, 3.0 )\ny = base.dists.normal.skewness( NaN, 1.0 )\ny = base.dists.normal.skewness( 0.0, NaN )\ny = base.dists.normal.skewness( 0.0, 0.0 )\n","base.dists.normal.stdev":"var y = base.dists.normal.stdev( 0.0, 1.0 )\ny = base.dists.normal.stdev( 4.0, 3.0 )\ny = base.dists.normal.stdev( NaN, 1.0 )\ny = base.dists.normal.stdev( 0.0, NaN )\ny = base.dists.normal.stdev( 0.0, 0.0 )\n","base.dists.normal.variance":"var y = base.dists.normal.variance( 0.0, 1.0 )\ny = base.dists.normal.variance( 4.0, 3.0 )\ny = base.dists.normal.variance( NaN, 1.0 )\ny = base.dists.normal.variance( 0.0, NaN )\ny = base.dists.normal.variance( 0.0, 0.0 )\n","base.dists.pareto1.cdf":"var y = base.dists.pareto1.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.pareto1.cdf( 5.0, 2.0, 4.0 )\ny = base.dists.pareto1.cdf( 4.0, 2.0, 2.0 )\ny = base.dists.pareto1.cdf( 1.9, 2.0, 2.0 )\ny = base.dists.pareto1.cdf( PINF, 4.0, 2.0 )\ny = base.dists.pareto1.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.pareto1.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.pareto1.cdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.cdf( 0.0, NaN, 1.0 )\ny = base.dists.pareto1.cdf( 0.0, 1.0, NaN )\n","base.dists.pareto1.cdf.factory":"var myCDF = base.dists.pareto1.cdf.factory( 10.0, 2.0 );\nvar y = myCDF( 3.0 )\ny = myCDF( 2.5 )\n","base.dists.pareto1.entropy":"var v = base.dists.pareto1.entropy( 0.8, 1.0 )\nv = base.dists.pareto1.entropy( 4.0, 12.0 )\nv = base.dists.pareto1.entropy( 8.0, 2.0 )\n","base.dists.pareto1.kurtosis":"var v = base.dists.pareto1.kurtosis( 5.0, 1.0 )\nv = base.dists.pareto1.kurtosis( 4.5, 12.0 )\nv = base.dists.pareto1.kurtosis( 8.0, 2.0 )\n","base.dists.pareto1.logcdf":"var y = base.dists.pareto1.logcdf( 2.0, 1.0, 1.0 )\ny = base.dists.pareto1.logcdf( 5.0, 2.0, 4.0 )\ny = base.dists.pareto1.logcdf( 4.0, 2.0, 2.0 )\ny = base.dists.pareto1.logcdf( 1.9, 2.0, 2.0 )\ny = base.dists.pareto1.logcdf( PINF, 4.0, 2.0 )\ny = base.dists.pareto1.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.pareto1.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.pareto1.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.pareto1.logcdf( 0.0, 1.0, NaN )\n","base.dists.pareto1.logcdf.factory":"var mylogCDF = base.dists.pareto1.logcdf.factory( 10.0, 2.0 );\nvar y = mylogCDF( 3.0 )\ny = mylogCDF( 2.5 )\n","base.dists.pareto1.logpdf":"var y = base.dists.pareto1.logpdf( 4.0, 1.0, 1.0 )\ny = base.dists.pareto1.logpdf( 20.0, 1.0, 10.0 )\ny = base.dists.pareto1.logpdf( 7.0, 2.0, 6.0 )\ny = base.dists.pareto1.logpdf( 7.0, 6.0, 3.0 )\ny = base.dists.pareto1.logpdf( 1.0, 4.0, 2.0 )\ny = base.dists.pareto1.logpdf( 1.5, 4.0, 2.0 )\ny = base.dists.pareto1.logpdf( 0.5, -1.0, 0.5 )\ny = base.dists.pareto1.logpdf( 0.5, 0.5, -1.0 )\ny = base.dists.pareto1.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.logpdf( 0.5, NaN, 1.0 )\ny = base.dists.pareto1.logpdf( 0.5, 1.0, NaN )\n","base.dists.pareto1.logpdf.factory":"var mylogPDF = base.dists.pareto1.logpdf.factory( 0.5, 0.5 );\nvar y = mylogPDF( 0.8 )\ny = mylogPDF( 2.0 )\n","base.dists.pareto1.mean":"var v = base.dists.pareto1.mean( 0.8, 1.0 )\nv = base.dists.pareto1.mean( 4.0, 12.0 )\nv = base.dists.pareto1.mean( 8.0, 2.0 )\n","base.dists.pareto1.median":"var v = base.dists.pareto1.median( 0.8, 1.0 )\nv = base.dists.pareto1.median( 4.0, 12.0 )\nv = base.dists.pareto1.median( 8.0, 2.0 )\n","base.dists.pareto1.mode":"var v = base.dists.pareto1.mode( 0.8, 1.0 )\nv = base.dists.pareto1.mode( 4.0, 12.0 )\nv = base.dists.pareto1.mode( 8.0, 2.0 )\n","base.dists.pareto1.Pareto1":"var pareto1 = base.dists.pareto1.Pareto1( 6.0, 5.0 );\npareto1.alpha\npareto1.beta\npareto1.entropy\npareto1.kurtosis\npareto1.mean\npareto1.median\npareto1.mode\npareto1.skewness\npareto1.variance\npareto1.cdf( 7.0 )\npareto1.logcdf( 7.0 )\npareto1.logpdf( 5.0 )\npareto1.pdf( 5.0 )\npareto1.quantile( 0.8 )\n","base.dists.pareto1.pdf":"var y = base.dists.pareto1.pdf( 4.0, 1.0, 1.0 )\ny = base.dists.pareto1.pdf( 20.0, 1.0, 10.0 )\ny = base.dists.pareto1.pdf( 7.0, 2.0, 6.0 )\ny = base.dists.pareto1.pdf( 7.0, 6.0, 3.0 )\ny = base.dists.pareto1.pdf( 1.0, 4.0, 2.0 )\ny = base.dists.pareto1.pdf( 1.5, 4.0, 2.0 )\ny = base.dists.pareto1.pdf( 0.5, -1.0, 0.5 )\ny = base.dists.pareto1.pdf( 0.5, 0.5, -1.0 )\ny = base.dists.pareto1.pdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.pdf( 0.5, NaN, 1.0 )\ny = base.dists.pareto1.pdf( 0.5, 1.0, NaN )\n","base.dists.pareto1.pdf.factory":"var myPDF = base.dists.pareto1.pdf.factory( 0.5, 0.5 );\nvar y = myPDF( 0.8 )\ny = myPDF( 2.0 )\n","base.dists.pareto1.quantile":"var y = base.dists.pareto1.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.pareto1.quantile( 0.8, 1.0, 10.0 )\ny = base.dists.pareto1.quantile( 0.1, 1.0, 10.0 )\ny = base.dists.pareto1.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.pareto1.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.pareto1.quantile( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.quantile( 0.5, NaN, 1.0 )\ny = base.dists.pareto1.quantile( 0.5, 1.0, NaN )\ny = base.dists.pareto1.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.pareto1.quantile( 0.5, 1.0, -1.0 )\n","base.dists.pareto1.quantile.factory":"var myQuantile = base.dists.pareto1.quantile.factory( 2.5, 0.5 );\nvar y = myQuantile( 0.5 )\ny = myQuantile( 0.8 )\n","base.dists.pareto1.skewness":"var v = base.dists.pareto1.skewness( 3.5, 1.0 )\nv = base.dists.pareto1.skewness( 4.0, 12.0 )\nv = base.dists.pareto1.skewness( 8.0, 2.0 )\n","base.dists.pareto1.stdev":"var v = base.dists.pareto1.stdev( 0.8, 1.0 )\nv = base.dists.pareto1.stdev( 4.0, 12.0 )\nv = base.dists.pareto1.stdev( 8.0, 2.0 )\n","base.dists.pareto1.variance":"var v = base.dists.pareto1.variance( 0.8, 1.0 )\nv = base.dists.pareto1.variance( 4.0, 12.0 )\nv = base.dists.pareto1.variance( 8.0, 2.0 )\n","base.dists.poisson.cdf":"var y = base.dists.poisson.cdf( 2.0, 0.5 )\ny = base.dists.poisson.cdf( 2.0, 10.0 )\ny = base.dists.poisson.cdf( -1.0, 4.0 )\ny = base.dists.poisson.cdf( NaN, 1.0 )\ny = base.dists.poisson.cdf( 0.0, NaN )\ny = base.dists.poisson.cdf( 2.0, -1.0 )\ny = base.dists.poisson.cdf( -2.0, 0.0 )\ny = base.dists.poisson.cdf( 0.0, 0.0 )\ny = base.dists.poisson.cdf( 10.0, 0.0 )\n","base.dists.poisson.cdf.factory":"var mycdf = base.dists.poisson.cdf.factory( 5.0 );\nvar y = mycdf( 3.0 )\ny = mycdf( 8.0 )\n","base.dists.poisson.entropy":"var v = base.dists.poisson.entropy( 11.0 )\nv = base.dists.poisson.entropy( 4.5 )\n","base.dists.poisson.kurtosis":"var v = base.dists.poisson.kurtosis( 11.0 )\nv = base.dists.poisson.kurtosis( 4.5 )\n","base.dists.poisson.logpmf":"var y = base.dists.poisson.logpmf( 4.0, 3.0 )\ny = base.dists.poisson.logpmf( 1.0, 3.0 )\ny = base.dists.poisson.logpmf( -1.0, 2.0 )\ny = base.dists.poisson.logpmf( 0.0, NaN )\ny = base.dists.poisson.logpmf( NaN, 0.5 )\ny = base.dists.poisson.logpmf( 2.0, -0.5 )\ny = base.dists.poisson.logpmf( 2.0, 0.0 )\ny = base.dists.poisson.logpmf( 0.0, 0.0 )\n","base.dists.poisson.logpmf.factory":"var mylogpmf = base.dists.poisson.logpmf.factory( 1.0 );\nvar y = mylogpmf( 3.0 )\ny = mylogpmf( 1.0 )\n","base.dists.poisson.mean":"var v = base.dists.poisson.mean( 11.0 )\nv = base.dists.poisson.mean( 4.5 )\n","base.dists.poisson.median":"var v = base.dists.poisson.median( 11.0 )\nv = base.dists.poisson.median( 4.5 )\n","base.dists.poisson.mgf":"var y = base.dists.poisson.mgf( 1.0, 1.5 )\ny = base.dists.poisson.mgf( 0.5, 0.5 )\ny = base.dists.poisson.mgf( NaN, 0.5 )\ny = base.dists.poisson.mgf( 0.0, NaN )\ny = base.dists.poisson.mgf( -2.0, -1.0 )\n","base.dists.poisson.mgf.factory":"var myMGF = base.dists.poisson.mgf.factory( 2.0 );\nvar y = myMGF( 0.1 )\n","base.dists.poisson.mode":"var v = base.dists.poisson.mode( 11.0 )\nv = base.dists.poisson.mode( 4.5 )\n","base.dists.poisson.pmf":"var y = base.dists.poisson.pmf( 4.0, 3.0 )\ny = base.dists.poisson.pmf( 1.0, 3.0 )\ny = base.dists.poisson.pmf( -1.0, 2.0 )\ny = base.dists.poisson.pmf( 0.0, NaN )\ny = base.dists.poisson.pmf( NaN, 0.5 )\ny = base.dists.poisson.pmf( 2.0, -0.5 )\ny = base.dists.poisson.pmf( 2.0, 0.0 )\ny = base.dists.poisson.pmf( 0.0, 0.0 )\n","base.dists.poisson.pmf.factory":"var mypmf = base.dists.poisson.pmf.factory( 1.0 );\nvar y = mypmf( 3.0 )\ny = mypmf( 1.0 )\n","base.dists.poisson.Poisson":"var poisson = base.dists.poisson.Poisson( 6.0 );\npoisson.lambda\npoisson.entropy\npoisson.kurtosis\npoisson.mean\npoisson.median\npoisson.mode\npoisson.skewness\npoisson.stdev\npoisson.variance\npoisson.cdf( 4.0 )\npoisson.logpmf( 2.0 )\npoisson.mgf( 0.5 )\npoisson.pmf( 2.0 )\npoisson.quantile( 0.5 )\n","base.dists.poisson.quantile":"var y = base.dists.poisson.quantile( 0.5, 2.0 )\ny = base.dists.poisson.quantile( 0.9, 4.0 )\ny = base.dists.poisson.quantile( 0.1, 200.0 )\ny = base.dists.poisson.quantile( 1.1, 0.0 )\ny = base.dists.poisson.quantile( -0.2, 0.0 )\ny = base.dists.poisson.quantile( NaN, 0.5 )\ny = base.dists.poisson.quantile( 0.0, NaN )\ny = base.dists.poisson.quantile( 2.0, -1.0 )\ny = base.dists.poisson.quantile( 0.1, 0.0 )\ny = base.dists.poisson.quantile( 0.9, 0.0 )\n","base.dists.poisson.quantile.factory":"var myQuantile = base.dists.poisson.quantile.factory( 0.4 );\nvar y = myQuantile( 0.4 )\ny = myQuantile( 1.0 )\n","base.dists.poisson.skewness":"var v = base.dists.poisson.skewness( 11.0 )\nv = base.dists.poisson.skewness( 4.5 )\n","base.dists.poisson.stdev":"var v = base.dists.poisson.stdev( 11.0 )\nv = base.dists.poisson.stdev( 4.5 )\n","base.dists.poisson.variance":"var v = base.dists.poisson.variance( 11.0 )\nv = base.dists.poisson.variance( 4.5 )\n","base.dists.rayleigh.cdf":"var y = base.dists.rayleigh.cdf( 2.0, 3.0 )\ny = base.dists.rayleigh.cdf( 1.0, 2.0 )\ny = base.dists.rayleigh.cdf( -1.0, 4.0 )\ny = base.dists.rayleigh.cdf( NaN, 1.0 )\ny = base.dists.rayleigh.cdf( 0.0, NaN )\ny = base.dists.rayleigh.cdf( 2.0, -1.0 )\ny = base.dists.rayleigh.cdf( -2.0, 0.0 )\ny = base.dists.rayleigh.cdf( 0.0, 0.0 )\ny = base.dists.rayleigh.cdf( 2.0, 0.0 )\n","base.dists.rayleigh.cdf.factory":"var myCDF = base.dists.rayleigh.cdf.factory( 0.5 );\nvar y = myCDF( 1.0 )\ny = myCDF( 0.5 )\n","base.dists.rayleigh.entropy":"var v = base.dists.rayleigh.entropy( 11.0 )\nv = base.dists.rayleigh.entropy( 4.5 )\n","base.dists.rayleigh.kurtosis":"var v = base.dists.rayleigh.kurtosis( 11.0 )\nv = base.dists.rayleigh.kurtosis( 4.5 )\n","base.dists.rayleigh.logcdf":"var y = base.dists.rayleigh.logcdf( 2.0, 3.0 )\ny = base.dists.rayleigh.logcdf( 1.0, 2.0 )\ny = base.dists.rayleigh.logcdf( -1.0, 4.0 )\ny = base.dists.rayleigh.logcdf( NaN, 1.0 )\ny = base.dists.rayleigh.logcdf( 0.0, NaN )\ny = base.dists.rayleigh.logcdf( 2.0, -1.0 )\n","base.dists.rayleigh.logcdf.factory":"var mylogcdf = base.dists.rayleigh.logcdf.factory( 0.5 );\nvar y = mylogcdf( 1.0 )\ny = mylogcdf( 0.5 )\n","base.dists.rayleigh.logpdf":"var y = base.dists.rayleigh.logpdf( 0.3, 1.0 )\ny = base.dists.rayleigh.logpdf( 2.0, 0.8 )\ny = base.dists.rayleigh.logpdf( -1.0, 0.5 )\ny = base.dists.rayleigh.logpdf( 0.0, NaN )\ny = base.dists.rayleigh.logpdf( NaN, 2.0 )\ny = base.dists.rayleigh.logpdf( 2.0, -1.0 )\n","base.dists.rayleigh.logpdf.factory":"var mylogpdf = base.dists.rayleigh.logpdf.factory( 4.0 );\nvar y = mylogpdf( 6.0 )\ny = mylogpdf( 4.0 )\n","base.dists.rayleigh.mean":"var v = base.dists.rayleigh.mean( 11.0 )\nv = base.dists.rayleigh.mean( 4.5 )\n","base.dists.rayleigh.median":"var v = base.dists.rayleigh.median( 11.0 )\nv = base.dists.rayleigh.median( 4.5 )\n","base.dists.rayleigh.mgf":"var y = base.dists.rayleigh.mgf( 1.0, 3.0 )\ny = base.dists.rayleigh.mgf( 1.0, 2.0 )\ny = base.dists.rayleigh.mgf( -1.0, 4.0 )\ny = base.dists.rayleigh.mgf( NaN, 1.0 )\ny = base.dists.rayleigh.mgf( 0.0, NaN )\ny = base.dists.rayleigh.mgf( 0.5, -1.0 )\n","base.dists.rayleigh.mgf.factory":"var myMGF = base.dists.rayleigh.mgf.factory( 0.5 );\nvar y = myMGF( 1.0 )\ny = myMGF( 0.5 )\n","base.dists.rayleigh.mode":"var v = base.dists.rayleigh.mode( 11.0 )\nv = base.dists.rayleigh.mode( 4.5 )\n","base.dists.rayleigh.pdf":"var y = base.dists.rayleigh.pdf( 0.3, 1.0 )\ny = base.dists.rayleigh.pdf( 2.0, 0.8 )\ny = base.dists.rayleigh.pdf( -1.0, 0.5 )\ny = base.dists.rayleigh.pdf( 0.0, NaN )\ny = base.dists.rayleigh.pdf( NaN, 2.0 )\ny = base.dists.rayleigh.pdf( 2.0, -1.0 )\ny = base.dists.rayleigh.pdf( -2.0, 0.0 )\ny = base.dists.rayleigh.pdf( 0.0, 0.0 )\ny = base.dists.rayleigh.pdf( 2.0, 0.0 )\n","base.dists.rayleigh.pdf.factory":"var myPDF = base.dists.rayleigh.pdf.factory( 4.0 );\nvar y = myPDF( 6.0 )\ny = myPDF( 4.0 )\n","base.dists.rayleigh.quantile":"var y = base.dists.rayleigh.quantile( 0.8, 1.0 )\ny = base.dists.rayleigh.quantile( 0.5, 4.0 )\ny = base.dists.rayleigh.quantile( 1.1, 1.0 )\ny = base.dists.rayleigh.quantile( -0.2, 1.0 )\ny = base.dists.rayleigh.quantile( NaN, 1.0 )\ny = base.dists.rayleigh.quantile( 0.0, NaN )\ny = base.dists.rayleigh.quantile( 0.5, -1.0 )\n","base.dists.rayleigh.quantile.factory":"var myQuantile = base.dists.rayleigh.quantile.factory( 0.4 );\nvar y = myQuantile( 0.4 )\ny = myQuantile( 1.0 )\n","base.dists.rayleigh.Rayleigh":"var rayleigh = base.dists.rayleigh.Rayleigh( 6.0 );\nrayleigh.sigma\nrayleigh.entropy\nrayleigh.kurtosis\nrayleigh.mean\nrayleigh.median\nrayleigh.mode\nrayleigh.skewness\nrayleigh.stdev\nrayleigh.variance\nrayleigh.cdf( 1.0 )\nrayleigh.logcdf( 1.0 )\nrayleigh.logpdf( 1.5 )\nrayleigh.mgf( -0.5 )\nrayleigh.pdf( 1.5 )\nrayleigh.quantile( 0.5 )\n","base.dists.rayleigh.skewness":"var v = base.dists.rayleigh.skewness( 11.0 )\nv = base.dists.rayleigh.skewness( 4.5 )\n","base.dists.rayleigh.stdev":"var v = base.dists.rayleigh.stdev( 9.0 )\nv = base.dists.rayleigh.stdev( 4.5 )\n","base.dists.rayleigh.variance":"var v = base.dists.rayleigh.variance( 9.0 )\nv = base.dists.rayleigh.variance( 4.5 )\n","base.dists.signrank.cdf":"var y = base.dists.signrank.cdf( 3, 7 )\ny = base.dists.signrank.cdf( 1.8, 3 )\ny = base.dists.signrank.cdf( -1.0, 40 )\ny = base.dists.signrank.cdf( NaN, 10 )\ny = base.dists.signrank.cdf( 0.0, NaN )\n","base.dists.signrank.cdf.factory":"var myCDF = base.dists.signrank.cdf.factory( 8 );\nvar y = myCDF( 5.7 )\ny = myCDF( 2.2 )\n","base.dists.signrank.pdf":"var y = base.dists.signrank.pdf( 3, 7 )\ny = base.dists.signrank.pdf( 1.8, 3 )\ny = base.dists.signrank.pdf( -1.0, 40 )\ny = base.dists.signrank.pdf( NaN, 10 )\ny = base.dists.signrank.pdf( 0.0, NaN )\n","base.dists.signrank.pdf.factory":"var myPDF = base.dists.signrank.pdf.factory( 8 );\nvar y = myPDF( 6.0 )\ny = myPDF( 2.0 )\n","base.dists.signrank.quantile":"var y = base.dists.signrank.quantile( 0.8, 5 )\ny = base.dists.signrank.quantile( 0.5, 4 )\ny = base.dists.signrank.quantile( 1.1, 5 )\ny = base.dists.signrank.quantile( -0.2, 5 )\ny = base.dists.signrank.quantile( NaN, 5 )\ny = base.dists.signrank.quantile( 0.0, NaN )\n","base.dists.signrank.quantile.factory":"var myQuantile = base.dists.signrank.quantile.factory( 8 );\nvar y = myQuantile( 0.4 )\ny = myQuantile( 1.0 )\n","base.dists.studentizedRange.cdf":"var y = base.dists.studentizedRange.cdf( 0.5, 3.0, 2.0 )\ny = base.dists.studentizedRange.cdf( 12.1, 17.0, 2.0 )\n","base.dists.studentizedRange.cdf.factory":"var mycdf = base.dists.studentizedRange.cdf.factory( 3.0, 2.0 );\nvar y = mycdf( 3.0 )\ny = mycdf( 1.0 )\n","base.dists.studentizedRange.quantile":"var y = quantile( 0.5, 3.0, 2.0 )\ny = quantile( 0.9, 17.0, 2.0 )\ny = quantile( 0.5, 3.0, 2.0, 2 )\ny = base.dists.studentizedRange.quantile( -0.2, 3.0, 3.0 )\ny = base.dists.studentizedRange.quantile( NaN, 2.0, 2.0 )\ny = base.dists.studentizedRange.quantile( 0.0, NaN, 2.0 )\ny = base.dists.studentizedRange.quantile( 0.5, -1.0, 2.0 )\n","base.dists.studentizedRange.quantile.factory":"var myQuantile = quantile.factory( 3.0, 3.0 );\nvar y = myQuantile( 0.5 )\n   ~1.791\ny = myQuantile( 0.8 )\n   ~3.245\n","base.dists.t.cdf":"var y = base.dists.t.cdf( 2.0, 0.1 )\ny = base.dists.t.cdf( 1.0, 2.0 )\ny = base.dists.t.cdf( -1.0, 4.0 )\ny = base.dists.t.cdf( NaN, 1.0 )\ny = base.dists.t.cdf( 0.0, NaN )\ny = base.dists.t.cdf( 2.0, -1.0 )\n","base.dists.t.cdf.factory":"var mycdf = base.dists.t.cdf.factory( 0.5 );\nvar y = mycdf( 3.0 )\ny = mycdf( 1.0 )\n","base.dists.t.entropy":"var v = base.dists.t.entropy( 11.0 )\nv = base.dists.t.entropy( 4.5 )\n","base.dists.t.kurtosis":"var v = base.dists.t.kurtosis( 11.0 )\nv = base.dists.t.kurtosis( 4.5 )\n","base.dists.t.logcdf":"var y = base.dists.t.logcdf( 2.0, 0.1 )\ny = base.dists.t.logcdf( 1.0, 2.0 )\ny = base.dists.t.logcdf( -1.0, 4.0 )\ny = base.dists.t.logcdf( NaN, 1.0 )\ny = base.dists.t.logcdf( 0.0, NaN )\ny = base.dists.t.logcdf( 2.0, -1.0 )\n","base.dists.t.logcdf.factory":"var mylogcdf = base.dists.t.logcdf.factory( 0.5 );\nvar y = mylogcdf( 3.0 )\ny = mylogcdf( 1.0 )\n","base.dists.t.logpdf":"var y = base.dists.t.logpdf( 0.3, 4.0 )\ny = base.dists.t.logpdf( 2.0, 0.7 )\ny = base.dists.t.logpdf( -1.0, 0.5 )\ny = base.dists.t.logpdf( 0.0, NaN )\ny = base.dists.t.logpdf( NaN, 2.0 )\ny = base.dists.t.logpdf( 2.0, -1.0 )\n","base.dists.t.logpdf.factory":"var mylogPDF = base.dists.t.logpdf.factory( 3.0 );\nvar y = mylogPDF( 1.0 )\n","base.dists.t.mean":"var v = base.dists.t.mean( 11.0 )\nv = base.dists.t.mean( 4.5 )\n","base.dists.t.median":"var v = base.dists.t.median( 11.0 )\nv = base.dists.t.median( 4.5 )\n","base.dists.t.mode":"var v = base.dists.t.mode( 11.0 )\nv = base.dists.t.mode( 4.5 )\n","base.dists.t.pdf":"var y = base.dists.t.pdf( 0.3, 4.0 )\ny = base.dists.t.pdf( 2.0, 0.7 )\ny = base.dists.t.pdf( -1.0, 0.5 )\ny = base.dists.t.pdf( 0.0, NaN )\ny = base.dists.t.pdf( NaN, 2.0 )\ny = base.dists.t.pdf( 2.0, -1.0 )\n","base.dists.t.pdf.factory":"var myPDF = base.dists.t.pdf.factory( 3.0 );\nvar y = myPDF( 1.0 )\n","base.dists.t.quantile":"var y = base.dists.t.quantile( 0.8, 1.0 )\ny = base.dists.t.quantile( 0.1, 1.0 )\ny = base.dists.t.quantile( 0.5, 0.1 )\ny = base.dists.t.quantile( -0.2, 0.1 )\ny = base.dists.t.quantile( NaN, 1.0 )\ny = base.dists.t.quantile( 0.0, NaN )\ny = base.dists.t.quantile( 0.5, -1.0 )\n","base.dists.t.quantile.factory":"var myQuantile = base.dists.t.quantile.factory( 4.0 );\nvar y = myQuantile( 0.2 )\ny = myQuantile( 0.9 )\n","base.dists.t.skewness":"var v = base.dists.t.skewness( 11.0 )\nv = base.dists.t.skewness( 4.5 )\n","base.dists.t.stdev":"var v = base.dists.t.stdev( 9.0 )\nv = base.dists.t.stdev( 4.5 )\n","base.dists.t.T":"var t = base.dists.t.T( 6.0 );\nt.v\nt.entropy\nt.kurtosis\nt.mean\nt.median\nt.mode\nt.skewness\nt.stdev\nt.variance\nt.cdf( 1.0 )\nt.logcdf( 1.0 )\nt.logpdf( 1.5 )\nt.pdf( 1.5 )\nt.quantile( 0.8 )\n","base.dists.t.variance":"var v = base.dists.t.variance( 9.0 )\nv = base.dists.t.variance( 4.5 )\n","base.dists.triangular.cdf":"var y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.cdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.cdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.cdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.cdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.cdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.cdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.cdf( 2.0, 1.0, 0.0, 1.5 )\n","base.dists.triangular.cdf.factory":"var mycdf = base.dists.triangular.cdf.factory( 0.0, 10.0, 2.0 );\nvar y = mycdf( 0.5 )\ny = mycdf( 8.0 )\n","base.dists.triangular.entropy":"var v = base.dists.triangular.entropy( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.entropy( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.entropy( 2.0, 8.0, 5.0 )\n","base.dists.triangular.kurtosis":"var v = base.dists.triangular.kurtosis( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.kurtosis( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.kurtosis( 2.0, 8.0, 5.0 )\n","base.dists.triangular.logcdf":"var y = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.logcdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.logcdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logcdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.logcdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.logcdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, 1.5 )\n","base.dists.triangular.logcdf.factory":"var mylogcdf = base.dists.triangular.logcdf.factory( 0.0, 10.0, 2.0 );\nvar y = mylogcdf( 0.5 )\ny = mylogcdf( 8.0 )\n","base.dists.triangular.logpdf":"var y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.logpdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.logpdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logpdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.logpdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.logpdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, 1.5 )\n","base.dists.triangular.logpdf.factory":"var mylogpdf = base.dists.triangular.logpdf.factory( 0.0, 10.0, 5.0 );\nvar y = mylogpdf( 2.0 )\ny = mylogpdf( 12.0 )\n","base.dists.triangular.mean":"var v = base.dists.triangular.mean( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.mean( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.mean( 2.0, 8.0, 5.0 )\n","base.dists.triangular.median":"var v = base.dists.triangular.median( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.median( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.median( 2.0, 8.0, 5.0 )\n","base.dists.triangular.mgf":"var y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.mgf( -0.3, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.mgf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.mgf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.mgf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.mgf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.mgf( 0.5, 1.0, 0.0, NaN )\ny = base.dists.triangular.mgf( 0.5, 1.0, 0.0, 1.5 )\n","base.dists.triangular.mgf.factory":"var mymgf = base.dists.triangular.mgf.factory( 0.0, 2.0, 1.0 );\nvar y = mymgf( -1.0 )\ny = mymgf( 2.0 )\n","base.dists.triangular.mode":"var v = base.dists.triangular.mode( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.mode( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.mode( 2.0, 8.0, 5.0 )\n","base.dists.triangular.pdf":"var y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.pdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.pdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.pdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.pdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.pdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.pdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.pdf( 2.0, 1.0, 0.0, 1.5 )\n","base.dists.triangular.pdf.factory":"var mypdf = base.dists.triangular.pdf.factory( 0.0, 10.0, 5.0 );\nvar y = mypdf( 2.0 )\ny = mypdf( 12.0 )\n","base.dists.triangular.quantile":"var y = base.dists.triangular.quantile( 0.9, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.quantile( 0.1, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.quantile( 0.1, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.quantile( 0.8, 0.0, 20.0, 0.0 )\ny = base.dists.triangular.quantile( 1.1, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.quantile( -0.1, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.quantile( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.quantile( 0.3, NaN, 1.0, 0.5 )\ny = base.dists.triangular.quantile( 0.3, 0.0, NaN, 0.5 )\ny = base.dists.triangular.quantile( 0.3, 1.0, 0.0, NaN )\ny = base.dists.triangular.quantile( 0.3, 1.0, 0.0, 1.5 )\n","base.dists.triangular.quantile.factory":"var myquantile = base.dists.triangular.quantile.factory( 2.0, 4.0, 2.5 );\nvar y = myquantile( 0.4 )\ny = myquantile( 0.8 )\n","base.dists.triangular.skewness":"var v = base.dists.triangular.skewness( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.skewness( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.skewness( 2.0, 8.0, 5.0 )\n","base.dists.triangular.stdev":"var v = base.dists.triangular.stdev( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.stdev( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.stdev( 2.0, 8.0, 5.0 )\n","base.dists.triangular.Triangular":"var triangular = base.dists.triangular.Triangular( 0.0, 1.0, 0.5 );\ntriangular.a\ntriangular.b\ntriangular.c\ntriangular.entropy\ntriangular.kurtosis\ntriangular.mean\ntriangular.median\ntriangular.mode\ntriangular.skewness\ntriangular.stdev\ntriangular.variance\ntriangular.cdf( 0.8 )\ntriangular.logcdf( 0.8 )\ntriangular.logpdf( 0.8 )\ntriangular.mgf( 0.8 )\ntriangular.pdf( 0.8 )\ntriangular.quantile( 0.8 )\n","base.dists.triangular.variance":"var v = base.dists.triangular.variance( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.variance( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.variance( 2.0, 8.0, 5.0 )\n","base.dists.uniform.cdf":"var y = base.dists.uniform.cdf( 9.0, 0.0, 10.0 )\ny = base.dists.uniform.cdf( 0.5, 0.0, 2.0 )\ny = base.dists.uniform.cdf( PINF, 2.0, 4.0 )\ny = base.dists.uniform.cdf( NINF, 2.0, 4.0 )\ny = base.dists.uniform.cdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.cdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.cdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.cdf( 2.0, 1.0, 0.0 )\n","base.dists.uniform.cdf.factory":"var mycdf = base.dists.uniform.cdf.factory( 0.0, 10.0 );\nvar y = mycdf( 0.5 )\ny = mycdf( 8.0 )\n","base.dists.uniform.entropy":"var v = base.dists.uniform.entropy( 0.0, 1.0 )\nv = base.dists.uniform.entropy( 4.0, 12.0 )\nv = base.dists.uniform.entropy( 2.0, 8.0 )\n","base.dists.uniform.kurtosis":"var v = base.dists.uniform.kurtosis( 0.0, 1.0 )\nv = base.dists.uniform.kurtosis( 4.0, 12.0 )\nv = base.dists.uniform.kurtosis( 2.0, 8.0 )\n","base.dists.uniform.logcdf":"var y = base.dists.uniform.logcdf( 9.0, 0.0, 10.0 )\ny = base.dists.uniform.logcdf( 0.5, 0.0, 2.0 )\ny = base.dists.uniform.logcdf( PINF, 2.0, 4.0 )\ny = base.dists.uniform.logcdf( NINF, 2.0, 4.0 )\ny = base.dists.uniform.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.logcdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.logcdf( 2.0, 1.0, 0.0 )\n","base.dists.uniform.logcdf.factory":"var mylogcdf = base.dists.uniform.logcdf.factory( 0.0, 10.0 );\nvar y = mylogcdf( 0.5 )\ny = mylogcdf( 8.0 )\n","base.dists.uniform.logpdf":"var y = base.dists.uniform.logpdf( 2.0, 0.0, 4.0 )\ny = base.dists.uniform.logpdf( 5.0, 0.0, 4.0 )\ny = base.dists.uniform.logpdf( 0.25, 0.0, 1.0 )\ny = base.dists.uniform.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.logpdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.logpdf( 2.0, 3.0, 1.0 )\n","base.dists.uniform.logpdf.factory":"var mylogPDF = base.dists.uniform.logpdf.factory( 6.0, 7.0 );\nvar y = mylogPDF( 7.0 )\ny = mylogPDF( 5.0 )\n","base.dists.uniform.mean":"var v = base.dists.uniform.mean( 0.0, 1.0 )\nv = base.dists.uniform.mean( 4.0, 12.0 )\nv = base.dists.uniform.mean( 2.0, 8.0 )\n","base.dists.uniform.median":"var v = base.dists.uniform.median( 0.0, 1.0 )\nv = base.dists.uniform.median( 4.0, 12.0 )\nv = base.dists.uniform.median( 2.0, 8.0 )\n","base.dists.uniform.mgf":"var y = base.dists.uniform.mgf( 2.0, 0.0, 4.0 )\ny = base.dists.uniform.mgf( -0.2, 0.0, 4.0 )\ny = base.dists.uniform.mgf( 2.0, 0.0, 1.0 )\ny = base.dists.uniform.mgf( 0.5, 3.0, 2.0 )\ny = base.dists.uniform.mgf( 0.5, 3.0, 3.0 )\ny = base.dists.uniform.mgf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.mgf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.mgf( 0.0, 0.0, NaN )\n","base.dists.uniform.mgf.factory":"var mymgf = base.dists.uniform.mgf.factory( 6.0, 7.0 );\nvar y = mymgf( 0.1 )\ny = mymgf( 1.1 )\n","base.dists.uniform.pdf":"var y = base.dists.uniform.pdf( 2.0, 0.0, 4.0 )\ny = base.dists.uniform.pdf( 5.0, 0.0, 4.0 )\ny = base.dists.uniform.pdf( 0.25, 0.0, 1.0 )\ny = base.dists.uniform.pdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.pdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.pdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.pdf( 2.0, 3.0, 1.0 )\n","base.dists.uniform.pdf.factory":"var myPDF = base.dists.uniform.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 7.0 )\ny = myPDF( 5.0 )\n","base.dists.uniform.quantile":"var y = base.dists.uniform.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.uniform.quantile( 0.5, 0.0, 10.0 )\ny = base.dists.uniform.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.uniform.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.uniform.quantile( NaN, 0.0, 1.0 )\ny = base.dists.uniform.quantile( 0.0, NaN, 1.0 )\ny = base.dists.uniform.quantile( 0.0, 0.0, NaN )\ny = base.dists.uniform.quantile( 0.5, 2.0, 1.0 )\n","base.dists.uniform.quantile.factory":"var myQuantile = base.dists.uniform.quantile.factory( 0.0, 4.0 );\nvar y = myQuantile( 0.8 )\n","base.dists.uniform.skewness":"var v = base.dists.uniform.skewness( 0.0, 1.0 )\nv = base.dists.uniform.skewness( 4.0, 12.0 )\nv = base.dists.uniform.skewness( 2.0, 8.0 )\n","base.dists.uniform.stdev":"var v = base.dists.uniform.stdev( 0.0, 1.0 )\nv = base.dists.uniform.stdev( 4.0, 12.0 )\nv = base.dists.uniform.stdev( 2.0, 8.0 )\n","base.dists.uniform.Uniform":"var uniform = base.dists.uniform.Uniform( 0.0, 1.0 );\nuniform.a\nuniform.b\nuniform.entropy\nuniform.kurtosis\nuniform.mean\nuniform.median\nuniform.skewness\nuniform.stdev\nuniform.variance\nuniform.cdf( 0.8 )\nuniform.logcdf( 0.5 )\nuniform.logpdf( 1.0 )\nuniform.mgf( 0.8 )\nuniform.pdf( 0.8 )\nuniform.quantile( 0.8 )\n","base.dists.uniform.variance":"var v = base.dists.uniform.variance( 0.0, 1.0 )\nv = base.dists.uniform.variance( 4.0, 12.0 )\nv = base.dists.uniform.variance( 2.0, 8.0 )\n","base.dists.weibull.cdf":"var y = base.dists.weibull.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.weibull.cdf( -1.0, 2.0, 2.0 )\ny = base.dists.weibull.cdf( PINF, 4.0, 2.0 )\ny = base.dists.weibull.cdf( NINF, 4.0, 2.0 )\ny = base.dists.weibull.cdf( NaN, 0.0, 1.0 )\ny = base.dists.weibull.cdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.cdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.cdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.cdf.factory":"var myCDF = base.dists.weibull.cdf.factory( 2.0, 10.0 );\nvar y = myCDF( 12.0 )\n","base.dists.weibull.entropy":"var v = base.dists.weibull.entropy( 1.0, 1.0 )\nv = base.dists.weibull.entropy( 4.0, 12.0 )\nv = base.dists.weibull.entropy( 8.0, 2.0 )\n","base.dists.weibull.kurtosis":"var v = base.dists.weibull.kurtosis( 1.0, 1.0 )\nv = base.dists.weibull.kurtosis( 4.0, 12.0 )\nv = base.dists.weibull.kurtosis( 8.0, 2.0 )\n","base.dists.weibull.logcdf":"var y = base.dists.weibull.logcdf( 2.0, 1.0, 1.0 )\ny = base.dists.weibull.logcdf( -1.0, 2.0, 2.0 )\ny = base.dists.weibull.logcdf( PINF, 4.0, 2.0 )\ny = base.dists.weibull.logcdf( NINF, 4.0, 2.0 )\ny = base.dists.weibull.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.weibull.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.logcdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.logcdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.logcdf.factory":"var mylogcdf = base.dists.weibull.logcdf.factory( 2.0, 10.0 );\nvar y = mylogcdf( 12.0 )\n","base.dists.weibull.logpdf":"var y = base.dists.weibull.logpdf( 2.0, 1.0, 0.5 )\ny = base.dists.weibull.logpdf( 0.1, 1.0, 1.0 )\ny = base.dists.weibull.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.weibull.logpdf( NaN, 0.6, 1.0 )\ny = base.dists.weibull.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.logpdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.logpdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.logpdf.factory":"var mylofpdf = base.dists.weibull.logpdf.factory( 7.0, 6.0 );\ny = mylofpdf( 7.0 )\n","base.dists.weibull.mean":"var v = base.dists.weibull.mean( 1.0, 1.0 )\nv = base.dists.weibull.mean( 4.0, 12.0 )\nv = base.dists.weibull.mean( 8.0, 2.0 )\n","base.dists.weibull.median":"var v = base.dists.weibull.median( 1.0, 1.0 )\nv = base.dists.weibull.median( 4.0, 12.0 )\nv = base.dists.weibull.median( 8.0, 2.0 )\n","base.dists.weibull.mgf":"var y = base.dists.weibull.mgf( 1.0, 1.0, 0.5 )\ny = base.dists.weibull.mgf( -1.0, 4.0, 4.0 )\ny = base.dists.weibull.mgf( NaN, 1.0, 1.0 )\ny = base.dists.weibull.mgf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.mgf( 0.0, 1.0, NaN )\ny = base.dists.weibull.mgf( 0.2, -1.0, 0.5 )\ny = base.dists.weibull.mgf( 0.2, 0.0, 0.5 )\ny = base.dists.weibull.mgf( 0.2, 0.5, -1.0 )\ny = base.dists.weibull.mgf( 0.2, 0.5, 0.0 )\n","base.dists.weibull.mgf.factory":"var myMGF = base.dists.weibull.mgf.factory( 8.0, 10.0 );\nvar y = myMGF( 0.8 )\ny = myMGF( 0.08 )\n","base.dists.weibull.mode":"var v = base.dists.weibull.mode( 1.0, 1.0 )\nv = base.dists.weibull.mode( 4.0, 12.0 )\nv = base.dists.weibull.mode( 8.0, 2.0 )\n","base.dists.weibull.pdf":"var y = base.dists.weibull.pdf( 2.0, 1.0, 0.5 )\ny = base.dists.weibull.pdf( 0.1, 1.0, 1.0 )\ny = base.dists.weibull.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.weibull.pdf( NaN, 0.6, 1.0 )\ny = base.dists.weibull.pdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.pdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.pdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.pdf.factory":"var myPDF = base.dists.weibull.pdf.factory( 7.0, 6.0 );\nvar y = myPDF( 7.0 )\n","base.dists.weibull.quantile":"var y = base.dists.weibull.quantile( 0.8, 1.0, 1.0 )\ny = base.dists.weibull.quantile( 0.5, 2.0, 4.0 )\ny = base.dists.weibull.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.weibull.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.weibull.quantile( NaN, 0.0, 1.0 )\ny = base.dists.weibull.quantile( 0.0, NaN, 1.0 )\ny = base.dists.weibull.quantile( 0.0, 0.0, NaN )\ny = base.dists.weibull.quantile( 0.5, 1.0, -1.0 )\n","base.dists.weibull.quantile.factory":"var myQuantile = base.dists.weibull.quantile.factory( 2.0, 10.0 );\nvar y = myQuantile( 0.4 )\n","base.dists.weibull.skewness":"var v = base.dists.weibull.skewness( 1.0, 1.0 )\nv = base.dists.weibull.skewness( 4.0, 12.0 )\nv = base.dists.weibull.skewness( 8.0, 2.0 )\n","base.dists.weibull.stdev":"var v = base.dists.weibull.stdev( 1.0, 1.0 )\nv = base.dists.weibull.stdev( 4.0, 12.0 )\nv = base.dists.weibull.stdev( 8.0, 2.0 )\n","base.dists.weibull.variance":"var v = base.dists.weibull.variance( 1.0, 1.0 )\nv = base.dists.weibull.variance( 4.0, 12.0 )\nv = base.dists.weibull.variance( 8.0, 2.0 )\n","base.dists.weibull.Weibull":"var weibull = base.dists.weibull.Weibull( 6.0, 5.0 );\nweibull.k\nweibull.lambda\nweibull.entropy\nweibull.kurtosis\nweibull.mean\nweibull.median\nweibull.mode\nweibull.skewness\nweibull.stdev\nweibull.variance\nweibull.cdf( 3.0 )\nweibull.logcdf( 3.0 )\nweibull.logpdf( 1.0 )\nweibull.mgf( -0.5 )\nweibull.pdf( 3.0 )\nweibull.quantile( 0.8 )\n","base.ellipe":"var y = base.ellipe( 0.5 )\ny = base.ellipe( -1.0 )\ny = base.ellipe( 2.0 )\ny = base.ellipe( PINF )\ny = base.ellipe( NINF )\ny = base.ellipe( NaN )\n","base.ellipj":"var v = base.ellipj( 0.3, 0.5 )\nv = base.ellipj( 0.0, 0.0 )\nv = base.ellipj( Infinity, 1.0 )\nv = base.ellipj( 0.0, -2.0)\nv = base.ellipj( NaN, NaN )\n","base.ellipj.assign":"var out = new Float64Array( 4 );\nvar v = base.ellipj.assign( 0.3, 0.5, out, 1, 0 )\nvar bool = ( v === out )\n","base.ellipj.sn":"var v = base.ellipj.sn( 0.3, 0.5 )\n","base.ellipj.cn":"var v = base.ellipj.cn( 0.3, 0.5 )\n","base.ellipj.dn":"var v = base.ellipj.dn( 0.3, 0.5 )\n","base.ellipj.am":"var v = base.ellipj.am( 0.3, 0.5 )\n","base.ellipk":"var y = base.ellipk( 0.5 )\ny = base.ellipk( -1.0 )\ny = base.ellipk( 2.0 )\ny = base.ellipk( PINF )\ny = base.ellipk( NINF )\ny = base.ellipk( NaN )\n","base.endsWith":"var bool = base.endsWith( 'beep', 'ep', 4 )\nbool = base.endsWith( 'Beep', 'op', 4 )\nbool = base.endsWith( 'Beep', 'ee', 3 )\nbool = base.endsWith( 'Beep', 'ee', -1 )\nbool = base.endsWith( 'beep', '', 4 )\n","base.epsdiff":"var d = base.epsdiff( 12.15, 12.149999999999999 )\nd = base.epsdiff( 2.4341309458983933, 2.4341309458633909, 'mean-abs' )\nfunction scale( x, y ) { return ( x > y ) ? y : x; };\nd = base.epsdiff( 1.0000000000000002, 1.0000000000000100, scale )\n","base.erf":"var y = base.erf( 2.0 )\ny = base.erf( -1.0 )\ny = base.erf( -0.0 )\ny = base.erf( NaN )\n","base.erfc":"var y = base.erfc( 2.0 )\ny = base.erfc( -1.0 )\ny = base.erfc( 0.0 )\ny = base.erfc( PINF )\ny = base.erfc( NINF )\ny = base.erfc( NaN )\n","base.erfcinv":"var y = base.erfcinv( 0.5 )\ny = base.erfcinv( 0.8 )\ny = base.erfcinv( 0.0 )\ny = base.erfcinv( 2.0 )\ny = base.erfcinv( NaN )\n","base.erfcx":"var y = base.erfcx( 1.0 )\ny = base.erfcx( -1.0 )\ny = base.erfcx( 0.0 )\ny = base.erfcx( NaN )\n","base.erfinv":"var y = base.erfinv( 0.5 )\ny = base.erfinv( 0.8 )\ny = base.erfinv( 0.0 )\ny = base.erfinv( -0.0 )\ny = base.erfinv( -1.0 )\ny = base.erfinv( 1.0 )\ny = base.erfinv( NaN )\n","base.eta":"var y = base.eta( 0.0 )\ny = base.eta( -1.0 )\ny = base.eta( 1.0 )\ny = base.eta( 3.14 )\ny = base.eta( NaN )\n","base.evalpoly":"var arr = [ 3.0, 2.0, 1.0 ];\nvar v = base.evalpoly( arr, 10.0 )\n","base.evalpoly.factory":"var f = base.evalpoly.factory( [ 3.0, 2.0, 1.0 ] );\nvar v = f( 10.0 )\nv = f( 5.0 )\n","base.evalrational":"var P = [ -6.0, -5.0, 4.0, 2.0 ];\nvar Q = [ 3.0, 0.5, 0.0, 0.0 ]; // zero-padded\nvar v = base.evalrational( P, Q, 6.0 )\n","base.evalrational.factory":"var P = [ 20.0, 8.0, 3.0 ];\nvar Q = [ 10.0, 9.0, 1.0 ];\nvar f = base.evalrational.factory( P, Q );\nvar v = f( 10.0 )\nv = f( 2.0 )\n","base.exp":"var y = base.exp( 4.0 )\ny = base.exp( -9.0 )\ny = base.exp( 0.0 )\ny = base.exp( NaN )\n","base.exp2":"var y = base.exp2( 3.0 )\ny = base.exp2( -9.0 )\ny = base.exp2( 0.0 )\ny = base.exp2( NaN )\n","base.exp10":"var y = base.exp10( 3.0 )\ny = base.exp10( -9.0 )\ny = base.exp10( 0.0 )\ny = base.exp10( NaN )\n","base.expit":"var y = base.expit( 0.0 )\ny = base.expit( 1.0 )\ny = base.expit( -1.0 )\ny = base.expit( Infinity )\ny = base.expit( NaN )\n","base.expm1":"var y = base.expm1( 0.2 )\ny = base.expm1( -9.0 )\ny = base.expm1( 0.0 )\ny = base.expm1( NaN )\n","base.expm1rel":"var y = base.expm1rel( 0.0 )\ny = base.expm1rel( 1.0 )\ny = base.expm1rel( -1.0 )\ny = base.expm1rel( NaN )\n","base.exponent":"var exponent = base.exponent( 3.14e-307 )\nexponent = base.exponent( -3.14 )\nexponent = base.exponent( 0.0 )\nexponent = base.exponent( NaN )\n","base.exponentf":"var exponent = base.exponentf( base.float64ToFloat32( 3.14e34 ) )\nexponent = base.exponentf( base.float64ToFloat32( 3.14e-34 ) )\nexponent = base.exponentf( base.float64ToFloat32( -3.14 ) )\nexponent = base.exponentf( 0.0 )\nexponent = base.exponentf( NaN )\n","base.factorial":"var y = base.factorial( 3.0 )\ny = base.factorial( -1.5 )\ny = base.factorial( -0.5 )\ny = base.factorial( 0.5 )\ny = base.factorial( -10.0 )\ny = base.factorial( 171.0 )\ny = base.factorial( NaN )\n","base.factorial2":"var y = base.factorial2( 3 )\ny = base.factorial2( 5 )\ny = base.factorial2( 6 )\ny = base.factorial2( 301 )\ny = base.factorial2( NaN )\n","base.factorialln":"var y = base.factorialln( 3.0 )\ny = base.factorialln( 2.4 )\ny = base.factorialln( -1.0 )\ny = base.factorialln( -1.5 )\ny = base.factorialln( NaN )\n","base.fallingFactorial":"var v = base.fallingFactorial( 0.9, 5 )\nv = base.fallingFactorial( -9.0, 3 )\nv = base.fallingFactorial( 0.0, 2 )\nv = base.fallingFactorial( 3.0, -2 )\n","base.fibonacci":"var y = base.fibonacci( 0 )\ny = base.fibonacci( 1 )\ny = base.fibonacci( 2 )\ny = base.fibonacci( 3 )\ny = base.fibonacci( 4 )\ny = base.fibonacci( 79 )\ny = base.fibonacci( NaN )\n","base.fibonacciIndex":"var n = base.fibonacciIndex( 2 )\nn = base.fibonacciIndex( 3 )\nn = base.fibonacciIndex( 5 )\nn = base.fibonacciIndex( NaN )\nn = base.fibonacciIndex( 1 )\n","base.fibpoly":"var v = base.fibpoly( 5, 2.0 )\n","base.fibpoly.factory":"var polyval = base.fibpoly.factory( 5 );\nvar v = polyval( 1.0 )\nv = polyval( 2.0 )\n","base.firstCodePoint":"var out = base.firstCodePoint( 'beep', 1 )\nout = base.firstCodePoint( 'Boop', 1 )\nout = base.firstCodePoint( 'foo bar', 5 )\n","base.firstCodeUnit":"var out = base.firstCodeUnit( 'beep', 1 )\nout = base.firstCodeUnit( 'Boop', 1 )\nout = base.firstCodeUnit( 'foo bar', 5 )\n","base.firstGraphemeCluster":"var out = base.firstGraphemeCluster( 'beep', 1 )\nout = base.firstGraphemeCluster( 'Boop', 1 )\nout = base.firstGraphemeCluster( 'foo bar', 5 )\n","base.flipsign":"var z = base.flipsign( -3.0, 10.0 )\nz = base.flipsign( -3.0, -1.0 )\nz = base.flipsign( 1.0, -0.0 )\nz = base.flipsign( -3.0, -0.0 )\nz = base.flipsign( -0.0, 1.0 )\nz = base.flipsign( 0.0, -1.0 )\n","base.flipsignf":"var z = base.flipsignf( -3.0, 10.0 )\nz = base.flipsignf( -3.0, -1.0 )\nz = base.flipsignf( 1.0, -0.0 )\nz = base.flipsignf( -3.0, -0.0 )\nz = base.flipsignf( -0.0, 1.0 )\nz = base.flipsignf( 0.0, -1.0 )\n","base.float32ToInt32":"var y = base.float32ToInt32( base.float64ToFloat32( 4294967295.0 ) )\ny = base.float32ToInt32( base.float64ToFloat32( 3.14 ) )\ny = base.float32ToInt32( base.float64ToFloat32( -3.14 ) )\ny = base.float32ToInt32( base.float64ToFloat32( NaN ) )\ny = base.float32ToInt32( FLOAT32_PINF )\ny = base.float32ToInt32( FLOAT32_NINF )\n","base.float32ToUint32":"var y = base.float32ToUint32( base.float64ToFloat32( 4294967297.0 ) )\ny = base.float32ToUint32( base.float64ToFloat32( 3.14 ) )\ny = base.float32ToUint32( base.float64ToFloat32( -3.14 ) )\ny = base.float32ToUint32( base.float64ToFloat32( NaN ) )\ny = base.float32ToUint32( FLOAT32_PINF )\ny = base.float32ToUint32( FLOAT32_NINF )\n","base.float64ToFloat32":"var y = base.float64ToFloat32( 1.337 )\n","base.float64ToInt32":"var y = base.float64ToInt32( 4294967295.0 )\ny = base.float64ToInt32( 3.14 )\ny = base.float64ToInt32( -3.14 )\ny = base.float64ToInt32( NaN )\ny = base.float64ToInt32( PINF )\ny = base.float64ToInt32( NINF )\n","base.float64ToInt64Bytes":"var y = base.float64ToInt64Bytes( 4294967297.0 )\n","base.float64ToInt64Bytes.assign":"var out = new Uint8Array( 16 );\nvar y = base.float64ToInt64Bytes( 4294967297.0, out, 2, 1 )\n","base.float64ToUint32":"var y = base.float64ToUint32( 4294967297.0 )\ny = base.float64ToUint32( 3.14 )\ny = base.float64ToUint32( -3.14 )\ny = base.float64ToUint32( NaN )\ny = base.float64ToUint32( PINF )\ny = base.float64ToUint32( NINF )\n","base.floor":"var y = base.floor( 3.14 )\ny = base.floor( -4.2 )\ny = base.floor( -4.6 )\ny = base.floor( 9.5 )\ny = base.floor( -0.0 )\n","base.floor2":"var y = base.floor2( 3.14 )\ny = base.floor2( -4.2 )\ny = base.floor2( -4.6 )\ny = base.floor2( 9.5 )\ny = base.floor2( 13.0 )\ny = base.floor2( -13.0 )\ny = base.floor2( -0.0 )\n","base.floor10":"var y = base.floor10( 3.14 )\ny = base.floor10( -4.2 )\ny = base.floor10( -4.6 )\ny = base.floor10( 9.5 )\ny = base.floor10( 13.0 )\ny = base.floor10( -13.0 )\ny = base.floor10( -0.0 )\n","base.floorb":"var y = base.floorb( 3.14159, -4, 10 )\ny = base.floorb( 3.14159, 0, 2 )\ny = base.floorb( 5.0, 1, 2 )\n","base.floorf":"var y = base.floorf( 3.14 )\ny = base.floorf( -4.2 )\ny = base.floorf( -4.6 )\ny = base.floorf( 9.5 )\ny = base.floorf( -0.0 )\n","base.floorn":"var y = base.floorn( 3.14159, -4 )\ny = base.floorn( 3.14159, 0 )\ny = base.floorn( 12368.0, 3 )\n","base.floorsd":"var y = base.floorsd( 3.14159, 5, 10 )\ny = base.floorsd( 3.14159, 1, 10 )\ny = base.floorsd( 12368.0, 2, 10 )\ny = base.floorsd( 0.0313, 2, 2 )\n","base.forEachChar":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachChar( 'hello world!', fcn );\nn\n","base.forEachCodePoint":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachCodePoint( 'hello world!', fcn );\nn\n","base.forEachCodePointRight":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachCodePointRight( 'hello world!', fcn );\nn\n","base.forEachGraphemeCluster":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachGraphemeCluster( 'hello world!', fcn );\nn\n","base.forEachRight":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachRight( 'hello world!', fcn );\nn\n","base.formatInterpolate":"var out = base.formatInterpolate( [ 'beep ', { 'specifier': 's' } ], 'boop' )\nout = base.formatInterpolate( [ 'baz ', { 'specifier': 'd', 'precision': 2 } ], 1 )\nout = base.formatInterpolate( [ { 'specifier': 'u', 'width': 6 } ], 12 )\n","base.formatTokenize":"var out = base.formatTokenize( 'Hello %s!' )\nout = base.formatTokenize( '%s %s %d' )\nout = base.formatTokenize( 'Pi: %.2f' )\n","base.fresnel":"var y = base.fresnel( 0.0 )\ny = base.fresnel( 1.0 )\ny = base.fresnel( PINF )\ny = base.fresnel( NINF )\ny = base.fresnel( NaN )\n","base.fresnel.assign":"var out = new Float64Array( 2 );\nvar v = base.fresnel.assign( 0.0, out, 1, 0 )\nvar bool = ( v === out )\n","base.fresnelc":"var y = base.fresnelc( 0.0 )\ny = base.fresnelc( 1.0 )\ny = base.fresnelc( PINF )\ny = base.fresnelc( NINF )\ny = base.fresnelc( NaN )\n","base.fresnels":"var y = base.fresnels( 0.0 )\ny = base.fresnels( 1.0 )\ny = base.fresnels( PINF )\ny = base.fresnels( NINF )\ny = base.fresnels( NaN )\n","base.frexp":"var out = base.frexp( 4.0 )\nout = base.frexp( 0.0 )\nout = base.frexp( -0.0 )\nout = base.frexp( NaN )\nout = base.frexp( PINF )\nout = base.frexp( NINF )\n","base.frexp.assign":"var out = new Float64Array( 2 );\nvar y = base.frexp.assign( 4.0, out, 1, 0 )\nvar bool = ( y === out )\n","base.fromBinaryString":"var bstr;\nbstr = '0100000000010000000000000000000000000000000000000000000000000000';\nvar val = base.fromBinaryString( bstr )\nbstr = '0100000000001001001000011111101101010100010001000010110100011000';\nval = base.fromBinaryString( bstr )\nbstr = '1111111111100001110011001111001110000101111010111100100010100000';\nval = base.fromBinaryString( bstr )\nbstr = '1000000000000000000000000000000000000000000000000001100011010011';\nval = base.fromBinaryString( bstr )\nbstr = '0000000000000000000000000000000000000000000000000000000000000001';\nval = base.fromBinaryString( bstr )\nbstr = '0000000000000000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '1000000000000000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '0111111111111000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '0111111111110000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '1111111111110000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\n","base.fromBinaryStringf":"var bstr = '01000000100000000000000000000000';\nvar val = base.fromBinaryStringf( bstr )\nbstr = '01000000010010010000111111011011';\nval = base.fromBinaryStringf( bstr )\nbstr = '11111111011011000011101000110011';\nval = base.fromBinaryStringf( bstr )\nbstr = '10000000000000000000000000010110';\nval = base.fromBinaryStringf( bstr )\nbstr = '00000000000000000000000000000001';\nval = base.fromBinaryStringf( bstr )\nbstr = '00000000000000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '10000000000000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '01111111110000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '01111111100000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '11111111100000000000000000000000';\nval = base.fromBinaryStringf( bstr )\n","base.fromBinaryStringUint8":"var bstr = '01010101';\nvar val = base.fromBinaryStringUint8( bstr )\nbstr = '00000000';\nval = base.fromBinaryStringUint8( bstr )\nbstr = '00000010';\nval = base.fromBinaryStringUint8( bstr )\nbstr = '11111111';\nval = base.fromBinaryStringUint8( bstr )\n","base.fromBinaryStringUint16":"var bstr = '0101010101010101';\nvar val = base.fromBinaryStringUint16( bstr )\nbstr = '0000000000000000';\nval = base.fromBinaryStringUint16( bstr )\nbstr = '0000000000000010';\nval = base.fromBinaryStringUint16( bstr )\nbstr = '1111111111111111';\nval = base.fromBinaryStringUint16( bstr )\n","base.fromBinaryStringUint32":"var bstr = '01010101010101010101010101010101';\nvar val = base.fromBinaryStringUint32( bstr )\nbstr = '00000000000000000000000000000000';\nval = base.fromBinaryStringUint32( bstr )\nbstr = '00000000000000000000000000000010';\nval = base.fromBinaryStringUint32( bstr )\nbstr = '11111111111111111111111111111111';\nval = base.fromBinaryStringUint32( bstr )\n","base.fromInt64Bytes":"var bytes = new Uint8Array( [ 255, 255, 255, 255, 255, 255, 255, 255 ] );\nvar y = base.fromInt64Bytes( bytes, 1, 0 )\n","base.fromWordf":"var word = 1068180177; // => 0 01111111 01010110010001011010001\nvar f32 = base.fromWordf( word ) // when printed, promoted to float64\n","base.fromWords":"var v = base.fromWords( 1774486211, 2479577218 )\nv = base.fromWords( 3221823995, 1413754136 )\nv = base.fromWords( 0, 0 )\nv = base.fromWords( 2147483648, 0 )\nv = base.fromWords( 2146959360, 0 )\nv = base.fromWords( 2146435072, 0 )\nv = base.fromWords( 4293918720, 0 )\n","base.gamma":"var y = base.gamma( 4.0 )\ny = base.gamma( -1.5 )\ny = base.gamma( -0.5 )\ny = base.gamma( 0.5 )\ny = base.gamma( 0.0 )\ny = base.gamma( -0.0 )\ny = base.gamma( NaN )\n","base.gamma1pm1":"var y = base.gamma1pm1( 0.2 )\ny = base.gamma1pm1( -6.7 )\ny = base.gamma1pm1( 0.0 )\ny = base.gamma1pm1( NaN )\n","base.gammaDeltaRatio":"var y = base.gammaDeltaRatio( 2.0, 3.0 )\ny = base.gammaDeltaRatio( 4.0, 0.5 )\ny = base.gammaDeltaRatio( 100.0, 0.0 )\ny = base.gammaDeltaRatio( NaN, 3.0 )\ny = base.gammaDeltaRatio( 5.0, NaN )\ny = base.gammaDeltaRatio( NaN, NaN )\n","base.gammainc":"var y = base.gammainc( 6.0, 2.0 )\ny = base.gammainc( 1.0, 2.0, true, true )\ny = base.gammainc( 7.0, 5.0 )\ny = base.gammainc( 7.0, 5.0, false )\ny = base.gammainc( NaN, 2.0 )\ny = base.gammainc( 6.0, NaN )\n","base.gammaincinv":"var y = base.gammaincinv( 0.5, 2.0 )\ny = base.gammaincinv( 0.1, 10.0 )\ny = base.gammaincinv( 0.75, 3.0 )\ny = base.gammaincinv( 0.75, 3.0, true )\ny = base.gammaincinv( 0.75, NaN )\ny = base.gammaincinv( NaN, 3.0 )\n","base.gammaLanczosSum":"var y = base.gammaLanczosSum( 4.0 )\ny = base.gammaLanczosSum( -1.5 )\ny = base.gammaLanczosSum( -0.5 )\ny = base.gammaLanczosSum( 0.5 )\ny = base.gammaLanczosSum( 0.0 )\ny = base.gammaLanczosSum( NaN )\n","base.gammaLanczosSumExpGScaled":"var y = base.gammaLanczosSumExpGScaled( 4.0 )\ny = base.gammaLanczosSumExpGScaled( -1.5 )\ny = base.gammaLanczosSumExpGScaled( -0.5 )\ny = base.gammaLanczosSumExpGScaled( 0.5 )\ny = base.gammaLanczosSumExpGScaled( 0.0 )\ny = base.gammaLanczosSumExpGScaled( NaN )\n","base.gammaln":"var y = base.gammaln( 1.0 )\ny = base.gammaln( 2.0 )\ny = base.gammaln( 4.0 )\ny = base.gammaln( -0.5 )\ny = base.gammaln( 0.5 )\ny = base.gammaln( 0.0 )\ny = base.gammaln( NaN )\n","base.gammasgn":"var y = base.gammasgn( 1.0 )\ny = base.gammasgn( -2.5 )\ny = base.gammasgn( 0.0 )\ny = base.gammasgn( NaN )\n","base.gcd":"var v = base.gcd( 48, 18 )\n","base.getHighWord":"var w = base.getHighWord( 3.14e201 )\n","base.getLowWord":"var w = base.getLowWord( 3.14e201 )\n","base.hacovercos":"var y = base.hacovercos( 3.14 )\ny = base.hacovercos( -4.2 )\ny = base.hacovercos( -4.6 )\ny = base.hacovercos( 9.5 )\ny = base.hacovercos( -0.0 )\n","base.hacoversin":"var y = base.hacoversin( 3.14 )\ny = base.hacoversin( -4.2 )\ny = base.hacoversin( -4.6 )\ny = base.hacoversin( 9.5 )\ny = base.hacoversin( -0.0 )\n","base.havercos":"var y = base.havercos( 3.14 )\ny = base.havercos( -4.2 )\ny = base.havercos( -4.6 )\ny = base.havercos( 9.5 )\ny = base.havercos( -0.0 )\n","base.haversin":"var y = base.haversin( 3.14 )\ny = base.haversin( -4.2 )\ny = base.haversin( -4.6 )\ny = base.haversin( 9.5 )\ny = base.haversin( -0.0 )\n","base.headercase":"var out = base.headercase( 'Hello World!' )\nout = base.headercase( 'beep boop' )\n","base.heaviside":"var y = base.heaviside( 3.14 )\ny = base.heaviside( -3.14 )\ny = base.heaviside( 0.0 )\ny = base.heaviside( 0.0, 'half-maximum' )\ny = base.heaviside( 0.0, 'left-continuous' )\ny = base.heaviside( 0.0, 'right-continuous' )\n","base.hermitepoly":"var y = base.hermitepoly( 1, 0.5 )\ny = base.hermitepoly( -1, 0.5 )\ny = base.hermitepoly( 0, 0.5 )\ny = base.hermitepoly( 2, 0.5 )\n","base.hermitepoly.factory":"var polyval = base.hermitepoly.factory( 2 );\nvar v = polyval( 0.5 )\n","base.hypot":"var h = base.hypot( -5.0, 12.0 )\nh = base.hypot( NaN, 12.0 )\nh = base.hypot( -0.0, -0.0 )\n","base.hypotf":"var h = base.hypotf( -5.0, 12.0 )\nh = base.hypotf( NaN, 12.0 )\nh = base.hypotf( -0.0, -0.0 )\n","base.identity":"var y = base.identity( -1.0 )\ny = base.identity( 2.0 )\ny = base.identity( 0.0 )\ny = base.identity( -0.0 )\ny = base.identity( NaN )\n","base.identityf":"var y = base.identityf( -1.0 )\ny = base.identityf( 2.0 )\ny = base.identityf( 0.0 )\ny = base.identityf( -0.0 )\ny = base.identityf( NaN )\n","base.imul":"var v = base.imul( -10|0, 4|0 )\n","base.imuldw":"var v = base.imuldw( 1, 10 )\n","base.imuldw.assign":"var out = [ 0, 0 ];\nvar v = base.imuldw.assign( 1, 10, out, 1, 0 )\nvar bool = ( v === out )\n","base.int2slice":"var s = base.int2slice( -1, 5, false );\ns.start\ns.stop\ns.step\n","base.int32ToUint32":"var y = base.int32ToUint32( base.float64ToInt32( -32 ) )\ny = base.int32ToUint32( base.float64ToInt32( 3 ) )\n","base.inv":"var y = base.inv( -1.0 )\ny = base.inv( 2.0 )\ny = base.inv( 0.0 )\ny = base.inv( -0.0 )\ny = base.inv( NaN )\n","base.invcase":"var out = base.invcase( 'Hello World!' )\nout = base.invcase( 'I am A tiny LITTLE teapot' )\n","base.invf":"var y = base.invf( -1.0 )\ny = base.invf( 2.0 )\ny = base.invf( 0.0 )\ny = base.invf( -0.0 )\ny = base.invf( NaN )\n","base.isComposite":"var bool = base.isComposite( 10.0 )\nbool = base.isComposite( 11.0 )\n","base.isCoprime":"var bool = base.isCoprime( 14.0, 15.0 )\nbool = base.isCoprime( 14.0, 21.0 )\n","base.isEven":"var bool = base.isEven( 5.0 )\nbool = base.isEven( -2.0 )\nbool = base.isEven( 0.0 )\nbool = base.isEven( NaN )\n","base.isEvenInt32":"var bool = base.isEvenInt32( 5 )\nbool = base.isEvenInt32( -2 )\nbool = base.isEvenInt32( 0 )\n","base.isFinite":"var bool = base.isFinite( 5.0 )\nbool = base.isFinite( -2.0e64 )\nbool = base.isFinite( PINF )\nbool = base.isFinite( NINF )\n","base.isFinitef":"var bool = base.isFinitef( 5.0 )\nbool = base.isFinitef( -1.0e38 )\nbool = base.isFinitef( FLOAT32_PINF )\nbool = base.isFinitef( FLOAT32_NINF )\n","base.isInfinite":"var bool = base.isInfinite( PINF )\nbool = base.isInfinite( NINF )\nbool = base.isInfinite( 5.0 )\nbool = base.isInfinite( NaN )\n","base.isInfinitef":"var bool = base.isInfinitef( FLOAT32_PINF )\nbool = base.isInfinitef( FLOAT32_NINF )\nbool = base.isInfinitef( 5.0 )\nbool = base.isInfinitef( NaN )\n","base.isInteger":"var bool = base.isInteger( 1.0 )\nbool = base.isInteger( 3.14 )\n","base.isnan":"var bool = base.isnan( NaN )\nbool = base.isnan( 7.0 )\n","base.isnanf":"var bool = base.isnanf( NaN )\nbool = base.isnanf( 7.0 )\n","base.isNegativeFinite":"var bool = base.isNegativeFinite( -3.14 )\nbool = base.isNegativeFinite( -Infinity )\nbool = base.isNegativeFinite( 2.0 )\nbool = base.isNegativeFinite( NaN )\nbool = base.isNegativeFinite( -0.0 )\n","base.isNegativeInteger":"var bool = base.isNegativeInteger( -1.0 )\nbool = base.isNegativeInteger( 0.0 )\nbool = base.isNegativeInteger( 10.0 )\n","base.isNegativeZero":"var bool = base.isNegativeZero( -0.0 )\nbool = base.isNegativeZero( 0.0 )\n","base.isNegativeZerof":"var bool = base.isNegativeZerof( -0.0 )\nbool = base.isNegativeZerof( 0.0 )\n","base.isNonNegativeFinite":"var out = base.isNonNegativeFinite( 5.0 )\nout = base.isNonNegativeFinite( 3.14 )\nout = base.isNonNegativeFinite( 0.0 )\nout = base.isNonNegativeFinite( Infinity )\nout = base.isNonNegativeFinite( -3.14 )\nout = base.isNonNegativeFinite( NaN )\n","base.isNonNegativeInteger":"var bool = base.isNonNegativeInteger( 1.0 )\nbool = base.isNonNegativeInteger( 0.0 )\nbool = base.isNonNegativeInteger( -10.0 )\n","base.isNonPositiveFinite":"var bool = base.isNonPositiveFinite( -3.14 )\nvar bool = base.isNonPositiveFinite( 0.0 )\nvar bool = base.isNonPositiveFinite( -Infinity )\nvar bool = base.isNonPositiveFinite( 3.14 )\nvar bool = base.isNonPositiveFinite( NaN )\n","base.isNonPositiveInteger":"var bool = base.isNonPositiveInteger( -1.0 )\nbool = base.isNonPositiveInteger( 0.0 )\nbool = base.isNonPositiveInteger( 10.0 )\n","base.isOdd":"var bool = base.isOdd( 5.0 )\nbool = base.isOdd( -2.0 )\nbool = base.isOdd( 0.0 )\nbool = base.isOdd( NaN )\n","base.isOddInt32":"var bool = base.isOddInt32( 5 )\nbool = base.isOddInt32( -2 )\nbool = base.isOddInt32( 0 )\n","base.isPositiveFinite":"var bool = base.isPositiveFinite( 5.0 )\nbool = base.isPositiveFinite( 3.14 )\nbool = base.isPositiveFinite( 0.0 )\nbool = base.isPositiveFinite( Infinity )\nbool = base.isPositiveFinite( -3.14 )\nbool = base.isPositiveFinite( NaN )\n","base.isPositiveInteger":"var bool = base.isPositiveInteger( 1.0 )\nbool = base.isPositiveInteger( 0.0 )\nbool = base.isPositiveInteger( -10.0 )\n","base.isPositiveZero":"var bool = base.isPositiveZero( 0.0 )\nbool = base.isPositiveZero( -0.0 )\n","base.isPositiveZerof":"var bool = base.isPositiveZerof( 0.0 )\nbool = base.isPositiveZerof( -0.0 )\n","base.isPow2Uint32":"var bool = base.isPow2Uint32( 2 )\nbool = base.isPow2Uint32( 5 )\n","base.isPrime":"var bool = base.isPrime( 11.0 )\nbool = base.isPrime( 3.14 )\n","base.isProbability":"var bool = base.isProbability( 0.5 )\nbool = base.isProbability( 3.14 )\nbool = base.isProbability( NaN )\n","base.isSafeInteger":"var bool = base.isSafeInteger( 1.0 )\nbool = base.isSafeInteger( 2.0e200 )\nbool = base.isSafeInteger( 3.14 )\n","base.kebabcase":"var out = base.kebabcase( 'Hello World!' )\nout = base.kebabcase( 'I am a tiny little teapot' )\n","base.kernelBetainc":"var out = base.kernelBetainc( 0.8, 1.0, 0.3, false, false )\nout = base.kernelBetainc( 0.2, 1.0, 2.0, true, false )\n","base.kernelBetainc.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.kernelBetainc.assign( 0.2, 1.0, 2.0, true, true, out, 1, 0 )\nvar bool = ( v === out )\n","base.kernelBetaincinv":"var y = base.kernelBetaincinv( 3.0, 3.0, 0.2, 0.8 )\ny = base.kernelBetaincinv( 3.0, 3.0, 0.4, 0.6 )\ny = base.kernelBetaincinv( 1.0, 6.0, 0.4, 0.6 )\ny = base.kernelBetaincinv( 1.0, 6.0, 0.8, 0.2 )\n","base.kernelCos":"var out = base.kernelCos( 0.0, 0.0 )\nout = base.kernelCos( PI/6.0, 0.0 )\nout = base.kernelCos( 0.785, -1.144e-17 )\nout = base.kernelCos( NaN )\n","base.kernelLog1p":"var y = base.kernelLog1p( 1.0 )\ny = base.kernelLog1p( 1.4142135623730951 )\ny = base.kernelLog1p( NaN )\n","base.kernelSin":"var y = base.kernelSin( 0.0, 0.0 )\ny = base.kernelSin( PI/6.0, 0.0 )\ny = base.kernelSin( 0.619, 9.279e-18 )\ny = base.kernelSin( NaN, 0.0 )\ny = base.kernelSin( 2.0, NaN )\ny = base.kernelSin( NaN, NaN )\n","base.kernelTan":"var out = base.kernelTan( PI/4.0, 0.0, 1 )\nout = base.kernelTan( PI/4.0, 0.0, -1 )\nout = base.kernelTan( PI/6.0, 0.0, 1 )\nout = base.kernelTan( 0.664, 5.288e-17, 1 )\nout = base.kernelTan( NaN, 0.0, 1 )\nout = base.kernelTan( 3.0, NaN, 1 )\nout = base.kernelTan( 3.0, 0.0, NaN )\n","base.kroneckerDelta":"var y = base.kroneckerDelta( 3.14, 0.0 )\ny = base.kroneckerDelta( 3.14, 3.14 )\n","base.kroneckerDeltaf":"var y = base.kroneckerDeltaf( 3.14, 0.0 )\ny = base.kroneckerDeltaf( 3.14, 3.14 )\n","base.labs":"var v = base.labs( -1|0 )\nv = base.labs( 2|0 )\nv = base.labs( 0|0 )\n","base.last":"var out = base.last( 'hello', 1 )\nout = base.last( 'JavaScript', 6 )\nout = base.last( 'foo bar', 10 )\n","base.lastCodePoint":"var out = base.lastCodePoint( 'hello world', 1 )\nout = base.lastCodePoint( 'JavaScript', 6 )\nout = base.lastCodePoint( 'अनुच्छेद', 1 )\n","base.lastGraphemeCluster":"var out = base.lastGraphemeCluster( 'beep', 1 )\nout = base.lastGraphemeCluster( 'Boop', 2 )\nout = base.lastGraphemeCluster( 'JavaScript', 6 )\n","base.lcm":"var v = base.lcm( 21, 6 )\n","base.ldexp":"var x = base.ldexp( 0.5, 3 )\nx = base.ldexp( 4.0, -2 )\nx = base.ldexp( 0.0, 20 )\nx = base.ldexp( -0.0, 39 )\nx = base.ldexp( NaN, -101 )\nx = base.ldexp( PINF, 11 )\nx = base.ldexp( NINF, -118 )\n","base.leftPad":"var out = base.leftPad( 'a', 5, ' ' )\nout = base.leftPad( 'beep', 10, 'b' )\nout = base.leftPad( 'boop', 12, 'beep' )\n","base.leftTrim":"var out = base.leftTrim( ' \\r\\n\\t  Beep \\t\\t\\n  ' )\n","base.ln":"var y = base.ln( 4.0 )\ny = base.ln( 0.0 )\ny = base.ln( PINF )\ny = base.ln( NaN )\ny = base.ln( -4.0 )\n","base.log":"var y = base.log( 100.0, 10.0 )\ny = base.log( 16.0, 2.0 )\ny = base.log( 5.0, 1.0 )\ny = base.log( NaN, 2.0 )\ny = base.log( 1.0, NaN )\ny = base.log( -4.0, 2.0 )\ny = base.log( 4.0, -2.0 )\n","base.log1mexp":"var y = base.log1mexp( -10.0 )\ny = base.log1mexp( 0.0 )\ny = base.log1mexp( 5.0 )\ny = base.log1mexp( 10.0 )\ny = base.log1mexp( NaN )\n","base.log1p":"var y = base.log1p( 4.0 )\ny = base.log1p( -1.0 )\ny = base.log1p( 0.0 )\ny = base.log1p( -0.0 )\ny = base.log1p( -2.0 )\ny = base.log1p( NaN )\n","base.log1pexp":"var y = base.log1pexp( -10.0 )\ny = base.log1pexp( 0.0 )\ny = base.log1pexp( 5.0 )\ny = base.log1pexp( 34.0 )\ny = base.log1pexp( NaN )\n","base.log1pmx":"base.log1pmx( 1.1 )\nbase.log1pmx( 0.99 )\nbase.log1pmx( -0.99 )\nbase.log1pmx( -1.1 )\nbase.log1pmx( NaN )\n","base.log2":"var y = base.log2( 4.0 )\ny = base.log2( 8.0 )\ny = base.log2( 0.0 )\ny = base.log2( PINF )\ny = base.log2( NaN )\ny = base.log2( -4.0 )\n","base.log10":"var y = base.log10( 100.0 )\ny = base.log10( 8.0 )\ny = base.log10( 0.0 )\ny = base.log10( PINF )\ny = base.log10( NaN )\ny = base.log10( -4.0 )\n","base.logaddexp":"var v = base.logaddexp( 90.0, 90.0 )\nv = base.logaddexp( -20.0, 90.0 )\nv = base.logaddexp( 0.0, -100.0 )\nv = base.logaddexp( NaN, NaN )\n","base.logit":"var y = base.logit( 0.2 )\ny = base.logit( 0.9 )\ny = base.logit( -4.0 )\ny = base.logit( 1.5 )\ny = base.logit( NaN )\n","base.lowercase":"var out = base.lowercase( 'bEEp' )\n","base.lucas":"var y = base.lucas( 0 )\ny = base.lucas( 1 )\ny = base.lucas( 2 )\ny = base.lucas( 3 )\ny = base.lucas( 4 )\ny = base.lucas( 77 )\ny = base.lucas( NaN )\n","base.lucaspoly":"var v = base.lucaspoly( 5, 2.0 )\n","base.lucaspoly.factory":"var polyval = base.lucaspoly.factory( 5 );\nvar v = polyval( 1.0 )\nv = polyval( 2.0 )\n","base.max":"var v = base.max( 3.14, 4.2 )\nv = base.max( 3.14, NaN )\nv = base.max( +0.0, -0.0 )\n","base.maxabs":"var v = base.maxabs( 3.14, -4.2 )\nv = base.maxabs( 3.14, NaN )\nv = base.maxabs( +0.0, -0.0 )\n","base.maxabsn":"var v = base.maxabsn( 3.14, -4.2 )\nv = base.maxabsn( 5.9, 3.14, 4.2 )\nv = base.maxabsn( 3.14, NaN )\nv = base.maxabsn( +0.0, -0.0 )\n","base.maxn":"var v = base.maxn( 3.14, 4.2 )\nv = base.maxn( 5.9, 3.14, 4.2 )\nv = base.maxn( 3.14, NaN )\nv = base.maxn( +0.0, -0.0 )\n","base.min":"var v = base.min( 3.14, 4.2 )\nv = base.min( 3.14, NaN )\nv = base.min( +0.0, -0.0 )\n","base.minabs":"var v = base.minabs( 3.14, -4.2 )\nv = base.minabs( 3.14, NaN )\nv = base.minabs( +0.0, -0.0 )\n","base.minabsn":"var v = base.minabsn( 3.14, -4.2 )\nv = base.minabsn( 5.9, 3.14, 4.2 )\nv = base.minabsn( 3.14, NaN )\nv = base.minabsn( +0.0, -0.0 )\n","base.minmax":"var v = base.minmax( 3.14, 4.2 )\nv = base.minmax( 3.14, NaN )\nv = base.minmax( +0.0, -0.0 )\n","base.minmax.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.minmax.assign( 3.14, -1.5, out, 1, 0 )\nvar bool = ( v === out )\n","base.minmaxabs":"var v = base.minmaxabs( 3.14, 4.2 )\nv = base.minmaxabs( -5.9, 3.14)\nv = base.minmaxabs( 3.14, NaN )\nv = base.minmaxabs( +0.0, -0.0 )\n","base.minmaxabs.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.minmaxabs.assign( 3.14, -3.14, out, 1, 0 )\nvar bool = ( v === out )\n","base.minmaxabsn":"var v = base.minmaxabsn( 3.14, 4.2 )\nv = base.minmaxabsn( -5.9, 3.14, 4.2 )\nv = base.minmaxabsn( 3.14, NaN )\nv = base.minmaxabsn( +0.0, -0.0 )\nv = base.minmaxabsn( 3.14 )\n","base.minmaxabsn.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.minmaxabsn.assign( 3.14, out, 1, 0 )\nvar bool = ( v === out )\n","base.minmaxn":"var v = base.minmaxn( 3.14, 4.2 )\nv = base.minmaxn( 5.9, 3.14, 4.2 )\nv = base.minmaxn( 3.14, NaN )\nv = base.minmaxn( +0.0, -0.0 )\nv = base.minmaxn( 3.14 )\n","base.minmaxn.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.minmaxn.assign( 3.14, -1.5, out, 1, 0 )\nvar bool = ( v === out )\n","base.minn":"var v = base.minn( 3.14, 4.2 )\nv = base.minn( 5.9, 3.14, 4.2 )\nv = base.minn( 3.14, NaN )\nv = base.minn( +0.0, -0.0 )\n","base.modf":"var parts = base.modf( 3.14 )\nparts = base.modf( 3.14 )\nparts = base.modf( +0.0 )\nparts = base.modf( -0.0 )\nparts = base.modf( PINF )\nparts = base.modf( NINF )\nparts = base.modf( NaN )\n","base.modf.assign":"var out = new Float64Array( 2 );\nvar parts = base.modf.assign( 3.14, out, 1, 0 )\nvar bool = ( parts === out )\n","base.mul":"var v = base.mul( -1.0, 5.0 )\nv = base.mul( 2.0, 5.0 )\nv = base.mul( 0.0, 5.0 )\nv = base.mul( -0.0, 0.0 )\nv = base.mul( NaN, NaN )\n","base.mulf":"var v = base.mulf( -1.0, 5.0 )\nv = base.mulf( 2.0, 5.0 )\nv = base.mulf( 0.0, 5.0 )\nv = base.mulf( -0.0, 0.0 )\nv = base.mulf( NaN, NaN )\n","base.ndarray":"var b = [ 1, 2, 3, 4 ]; // underlying data buffer\nvar d = [ 2, 2 ]; // shape\nvar s = [ 2, 1 ]; // strides\nvar o = 0; // index offset\nvar arr = base.ndarray( 'generic', b, d, s, o, 'row-major' )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40 );\narr.get( 1, 1 )\narr.iset( 3, 99 );\narr.get( 1, 1 )\n","base.ndarray.prototype.byteLength":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.byteLength\n","base.ndarray.prototype.BYTES_PER_ELEMENT":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.BYTES_PER_ELEMENT\n","base.ndarray.prototype.data":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar buf = arr.data\n","base.ndarray.prototype.dtype":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar dt = arr.dtype\n","base.ndarray.prototype.flags":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar fl = arr.flags\n","base.ndarray.prototype.length":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar len = arr.length\n","base.ndarray.prototype.ndims":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar n = arr.ndims\n","base.ndarray.prototype.offset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.offset\n","base.ndarray.prototype.order: string":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar ord = arr.order\n","base.ndarray.prototype.shape":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sh = arr.shape\n","base.ndarray.prototype.strides":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar st = arr.strides\n","base.ndarray.prototype.get":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.get( 1, 1 )\n","base.ndarray.prototype.iget":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.iget( 3 )\n","base.ndarray.prototype.set":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\narr.set( 1, 1, -4.0 );\narr.get( 1, 1 )\n","base.ndarray.prototype.iset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\narr.iset( 3, -4.0 );\narr.iget( 3 )\n","base.ndarray.prototype.toString":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toString()\n","base.ndarray.prototype.toJSON":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toJSON()\n","base.ndarrayUnary":"var xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dtype = 'float64';\nvar shape = [ 2, 2 ];\nvar sx = [ 2, 1 ];\nvar sy = [ 2, 1 ];\nvar ox = 0;\nvar oy = 0;\nvar order = 'row-major';\nvar x = ndarray( dtype, xbuf, shape, sx, ox, order );\nvar y = ndarray( dtype, ybuf, shape, sy, oy, order );\nbase.ndarrayUnary( [ x, y ], base.abs );\ny.data\nx = {\n 'dtype': dtype,\n 'data': xbuf,\n 'shape': shape,\n 'strides': sx,\n 'offset': ox,\n 'order': order\n };\ny = {\n 'dtype': dtype,\n 'data': ybuf,\n 'shape': shape,\n 'strides': sy,\n 'offset': oy,\n 'order': order\n };\nbase.ndarrayUnary( [ x, y ], base.abs );\ny.data\n","base.ndzeros":"var arr = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\nvar sh = arr.shape\nvar dt = arr.dtype\n","base.ndzerosLike":"var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\nvar sh = x.shape\nvar dt = x.dtype\nvar y = base.ndzerosLike( x )\nsh = y.shape\ndt = y.dtype\n","base.negafibonacci":"var y = base.negafibonacci( 0 )\ny = base.negafibonacci( -1 )\ny = base.negafibonacci( -2 )\ny = base.negafibonacci( -3 )\ny = base.negafibonacci( -4 )\ny = base.negafibonacci( -79 )\ny = base.negafibonacci( -80 )\ny = base.negafibonacci( NaN )\n","base.negalucas":"var y = base.negalucas( 0 )\ny = base.negalucas( -1 )\ny = base.negalucas( -2 )\ny = base.negalucas( -3 )\ny = base.negalucas( -4 )\ny = base.negalucas( -77 )\ny = base.negalucas( -78 )\ny = base.negalucas( NaN )\n","base.nonfibonacci":"var v = base.nonfibonacci( 1 )\nv = base.nonfibonacci( 2 )\nv = base.nonfibonacci( 3 )\nv = base.nonfibonacci( NaN )\n","base.normalize":"var out = base.normalize( 3.14e-319 )\nvar y = out[ 0 ];\nvar exponent = out[ 1 ];\nvar bool = ( y*base.pow(2.0, exponent) === 3.14e-319 )\nout = base.normalize( 0.0 )\nout = base.normalize( PINF )\nout = base.normalize( NINF )\nout = base.normalize( NaN )\n","base.normalize.assign":"var out = new Float64Array( 2 )\nvar v = base.normalize.assign( 3.14e-319, out, 1, 0 )\nvar bool = ( v === out )\n","base.normalizef":"var out = base.normalizef( base.float64ToFloat32( 1.401e-45 ) )\nvar y = out[ 0 ];\nvar exp = out[ 1 ];\nvar bool = ( y*base.pow(2,exp) === base.float64ToFloat32(1.401e-45) )\nout = base.normalizef( FLOAT32_PINF )\nout = base.normalizef( FLOAT32_NINF )\nout = base.normalizef( NaN )\n","base.normalizef.assign":"out = new Float32Array( 2 );\nvar v = base.normalizef.assign( base.float64ToFloat32( 1.401e-45 ), out, 1, 0 )\nbool = ( v === out )\n","base.normalizeSlice":"var s1 = new Slice( 1, 10, 1 );\nvar s2 = base.normalizeSlice( s1, 5, false );\ns2.start\ns2.stop\ns2.step\ns1 = new Slice( -2, null, -1 );\ns2 = base.normalizeSlice( s1, 10, false );\ns2.start\ns2.stop\ns2.step\n","base.normhermitepoly":"var y = base.normhermitepoly( 1, 0.5 )\ny = base.normhermitepoly( -1, 0.5 )\ny = base.normhermitepoly( 0, 0.5 )\ny = base.normhermitepoly( 2, 0.5 )\n","base.normhermitepoly.factory":"var f = base.normhermitepoly.factory( 2 );\nvar v = f( 0.5 )\n","base.pascalcase":"var out = base.pascalcase( 'Hello World!' )\nout = base.pascalcase( 'beep boop' )\n","base.pdiff":"var v = base.pdiff( 5.9, 3.14 )\nv = base.pdiff( 3.14, 4.2 )\nv = base.pdiff( 3.14, NaN )\nv = base.pdiff( -0.0, +0.0 )\n","base.pdifff":"var v = base.pdifff( 5.9, 3.15 )\nv = base.pdifff( 3.14, 4.2 )\nv = base.pdifff( 3.14, NaN )\nv = base.pdifff( -0.0, +0.0 )\n","base.percentEncode":"var out = base.percentEncode( '☃' )\n","base.polygamma":"var v = base.polygamma( 3, 1.2 )\nv = base.polygamma( 5, 1.2 )\nv = base.polygamma( 3, -4.9 )\nv = base.polygamma( -1, 5.3 )\nv = base.polygamma( 2, -1.0 )\n","base.pow":"var y = base.pow( 2.0, 3.0 )\ny = base.pow( 4.0, 0.5 )\ny = base.pow( 100.0, 0.0 )\ny = base.pow( PI, 5.0 )\ny = base.pow( PI, -0.2 )\ny = base.pow( NaN, 3.0 )\ny = base.pow( 5.0, NaN )\ny = base.pow( NaN, NaN )\n","base.powm1":"var y = base.powm1( 2.0, 3.0 )\ny = base.powm1( 4.0, 0.5 )\ny = base.powm1( 0.0, 100.0 )\ny = base.powm1( 100.0, 0.0 )\ny = base.powm1( 0.0, 0.0 )\ny = base.powm1( PI, 5.0 )\ny = base.powm1( NaN, 3.0 )\ny = base.powm1( 5.0, NaN )\n","base.rad2deg":"var d = base.rad2deg( PI/2.0 )\nd = base.rad2deg( -PI/4.0 )\nd = base.rad2deg( NaN )\nd = base.rad2deg( PI/6.0 )\n","base.rad2degf":"var d = base.rad2degf( 3.141592653589793 / 2.0 )\nd = base.rad2degf( -3.141592653589793 / 4.0 )\nd = base.rad2degf( NaN )\nd = base.rad2degf( 3.141592653589793 / 6.0 )\n","base.ramp":"var y = base.ramp( 3.14 )\ny = base.ramp( -3.14 )\n","base.rampf":"var y = base.rampf( 3.14 )\ny = base.rampf( -3.14 )\n","base.random.arcsine":"var r = base.random.arcsine( 2.0, 5.0 )\n","base.random.arcsine.factory":"var rand = base.random.arcsine.factory();\nvar r = rand( 0.0, 1.0 )\nr = rand( -2.0, 2.0 )\nrand = base.random.arcsine.factory( 0.0, 1.0 );\nr = rand()\nr = rand()\n","base.random.arcsine.NAME":"var str = base.random.arcsine.NAME\n","base.random.arcsine.PRNG":"var prng = base.random.arcsine.PRNG;\n","base.random.arcsine.seed":"var seed = base.random.arcsine.seed;\n","base.random.arcsine.seedLength":"var len = base.random.arcsine.seedLength;\n","base.random.arcsine.state":"var r = base.random.arcsine( 2.0, 4.0 )\nr = base.random.arcsine( 2.0, 4.0 )\nr = base.random.arcsine( 2.0, 4.0 )\nvar state = base.random.arcsine.state\nr = base.random.arcsine( 2.0, 4.0 )\nr = base.random.arcsine( 2.0, 4.0 )\nbase.random.arcsine.state = state;\nr = base.random.arcsine( 2.0, 4.0 )\nr = base.random.arcsine( 2.0, 4.0 )\n","base.random.arcsine.stateLength":"var len = base.random.arcsine.stateLength;\n","base.random.arcsine.byteLength":"var sz = base.random.arcsine.byteLength;\n","base.random.arcsine.toJSON":"var o = base.random.arcsine.toJSON()\n","base.random.bernoulli":"var r = base.random.bernoulli( 0.8 );\n","base.random.bernoulli.factory":"var rand = base.random.bernoulli.factory();\nvar r = rand( 0.3 );\nr = rand( 0.59 );\nrand = base.random.bernoulli.factory( 0.3 );\nr = rand();\nr = rand();\n","base.random.bernoulli.NAME":"var str = base.random.bernoulli.NAME\n","base.random.bernoulli.PRNG":"var prng = base.random.bernoulli.PRNG;\n","base.random.bernoulli.seed":"var seed = base.random.bernoulli.seed;\n","base.random.bernoulli.seedLength":"var len = base.random.bernoulli.seedLength;\n","base.random.bernoulli.state":"var r = base.random.bernoulli( 0.3 )\nr = base.random.bernoulli( 0.3 )\nr = base.random.bernoulli( 0.3 )\nvar state = base.random.bernoulli.state\nr = base.random.bernoulli( 0.3 )\nr = base.random.bernoulli( 0.3 )\nbase.random.bernoulli.state = state;\nr = base.random.bernoulli( 0.3 )\nr = base.random.bernoulli( 0.3 )\n","base.random.bernoulli.stateLength":"var len = base.random.bernoulli.stateLength;\n","base.random.bernoulli.byteLength":"var sz = base.random.bernoulli.byteLength;\n","base.random.bernoulli.toJSON":"var o = base.random.bernoulli.toJSON()\n","base.random.beta":"var r = base.random.beta( 2.0, 5.0 );\n","base.random.beta.factory":"var rand = base.random.beta.factory();\nvar r = rand( 1.5, 1.5 );\nr = rand( 2.0, 3.14 );\nrand = base.random.beta.factory( 1.5, 1.5 );\nr = rand();\nr = rand();\n","base.random.beta.NAME":"var str = base.random.beta.NAME\n","base.random.beta.PRNG":"var prng = base.random.beta.PRNG;\n","base.random.beta.seed":"var seed = base.random.beta.seed;\n","base.random.beta.seedLength":"var len = base.random.beta.seedLength;\n","base.random.beta.state":"var r = base.random.beta( 2.0, 5.0 )\nr = base.random.beta( 2.0, 5.0 )\nr = base.random.beta( 2.0, 5.0 )\nvar state = base.random.beta.state\nr = base.random.beta( 2.0, 5.0 )\nr = base.random.beta( 2.0, 5.0 )\nbase.random.beta.state = state;\nr = base.random.beta( 2.0, 5.0 )\nr = base.random.beta( 2.0, 5.0 )\n","base.random.beta.stateLength":"var len = base.random.beta.stateLength;\n","base.random.beta.byteLength":"var sz = base.random.beta.byteLength;\n","base.random.beta.toJSON":"var o = base.random.beta.toJSON()\n","base.random.betaprime":"var r = base.random.betaprime( 2.0, 5.0 );\n","base.random.betaprime.factory":"var rand = base.random.betaprime.factory();\nvar r = rand( 1.5, 1.5 );\nr = rand( 2.0, 3.14 );\nrand = base.random.betaprime.factory( 1.5, 1.5 );\nr = rand();\nr = rand();\n","base.random.betaprime.NAME":"var str = base.random.betaprime.NAME\n","base.random.betaprime.PRNG":"var prng = base.random.betaprime.PRNG;\n","base.random.betaprime.seed":"var seed = base.random.betaprime.seed;\n","base.random.betaprime.seedLength":"var len = base.random.betaprime.seedLength;\n","base.random.betaprime.state":"var r = base.random.betaprime( 2.0, 5.0 )\nr = base.random.betaprime( 2.0, 5.0 )\nr = base.random.betaprime( 2.0, 5.0 )\nvar state = base.random.betaprime.state\nr = base.random.betaprime( 2.0, 5.0 )\nr = base.random.betaprime( 2.0, 5.0 )\nbase.random.betaprime.state = state;\nr = base.random.betaprime( 2.0, 5.0 )\nr = base.random.betaprime( 2.0, 5.0 )\n","base.random.betaprime.stateLength":"var len = base.random.betaprime.stateLength;\n","base.random.betaprime.byteLength":"var sz = base.random.betaprime.byteLength;\n","base.random.betaprime.toJSON":"var o = base.random.betaprime.toJSON()\n","base.random.binomial":"var r = base.random.binomial( 20, 0.8 );\n","base.random.binomial.factory":"var rand = base.random.binomial.factory();\nvar r = rand( 20, 0.3 );\nr = rand( 10, 0.77 );\nrand = base.random.binomial.factory( 10, 0.8 );\nr = rand();\nr = rand();\n","base.random.binomial.NAME":"var str = base.random.binomial.NAME\n","base.random.binomial.PRNG":"var prng = base.random.binomial.PRNG;\n","base.random.binomial.seed":"var seed = base.random.binomial.seed;\n","base.random.binomial.seedLength":"var len = base.random.binomial.seedLength;\n","base.random.binomial.state":"var r = base.random.binomial( 20, 0.8 )\nr = base.random.binomial( 20, 0.8 )\nr = base.random.binomial( 20, 0.8 )\nvar state = base.random.binomial.state\nr = base.random.binomial( 20, 0.8 )\nr = base.random.binomial( 20, 0.8 )\nbase.random.binomial.state = state;\nr = base.random.binomial( 20, 0.8 )\nr = base.random.binomial( 20, 0.8 )\n","base.random.binomial.stateLength":"var len = base.random.binomial.stateLength;\n","base.random.binomial.byteLength":"var sz = base.random.binomial.byteLength;\n","base.random.binomial.toJSON":"var o = base.random.binomial.toJSON()\n","base.random.boxMuller":"var r = base.random.boxMuller();\n","base.random.boxMuller.factory":"var rand = base.random.boxMuller.factory();\nr = rand();\nr = rand();\n","base.random.boxMuller.NAME":"var str = base.random.boxMuller.NAME\n","base.random.boxMuller.PRNG":"var prng = base.random.boxMuller.PRNG;\n","base.random.boxMuller.seed":"var seed = base.random.boxMuller.seed;\n","base.random.boxMuller.seedLength":"var len = base.random.boxMuller.seedLength;\n","base.random.boxMuller.state":"var r = base.random.boxMuller()\nr = base.random.boxMuller()\nr = base.random.boxMuller()\nvar state = base.random.boxMuller.state\nr = base.random.boxMuller()\nr = base.random.boxMuller()\nbase.random.boxMuller.state = state;\nr = base.random.boxMuller()\nr = base.random.boxMuller()\n","base.random.boxMuller.stateLength":"var len = base.random.boxMuller.stateLength;\n","base.random.boxMuller.byteLength":"var sz = base.random.boxMuller.byteLength;\n","base.random.boxMuller.toJSON":"var o = base.random.boxMuller.toJSON()\n","base.random.cauchy":"var r = base.random.cauchy( 2.0, 5.0 );\n","base.random.cauchy.factory":"var rand = base.random.cauchy.factory();\nvar r = rand( 0.0, 1.5 );\nr = rand( -2.0, 2.0 );\nrand = base.random.cauchy.factory( 0.0, 1.5 );\nr = rand();\nr = rand();\n","base.random.cauchy.NAME":"var str = base.random.cauchy.NAME\n","base.random.cauchy.PRNG":"var prng = base.random.cauchy.PRNG;\n","base.random.cauchy.seed":"var seed = base.random.cauchy.seed;\n","base.random.cauchy.seedLength":"var len = base.random.cauchy.seedLength;\n","base.random.cauchy.state":"var r = base.random.cauchy( 2.0, 5.0 )\nr 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base.random.randi.NAME\n","base.random.randi.PRNG":"var prng = base.random.randi.PRNG;\n","base.random.randi.MIN":"var v = base.random.randi.MIN;\n","base.random.randi.MAX":"var v = base.random.randi.MAX;\n","base.random.randi.seed":"var seed = base.random.randi.seed;\n","base.random.randi.seedLength":"var len = base.random.randi.seedLength;\n","base.random.randi.state":"var r = base.random.randi()\nr = base.random.randi()\nr = base.random.randi()\nvar state = base.random.randi.state;\nr = base.random.randi()\nr = base.random.randi()\nbase.random.randi.state = state;\nr = base.random.randi()\nr = base.random.randi()\n","base.random.randi.stateLength":"var len = base.random.randi.stateLength;\n","base.random.randi.byteLength":"var sz = base.random.randi.byteLength;\n","base.random.randi.toJSON":"var o = base.random.randi.toJSON()\n","base.random.randn":"var r = base.random.randn();\n","base.random.randn.factory":"var rand = base.random.randn.factory();\nvar r = rand();\nr = rand();\nvar rand = base.random.randn.factory({ 'name': 'box-muller' });\nr = rand();\nr = rand();\n","base.random.randn.NAME":"var str = base.random.randn.NAME\n","base.random.randn.PRNG":"var prng = base.random.randn.PRNG;\n","base.random.randn.seed":"var seed = base.random.randn.seed;\n","base.random.randn.seedLength":"var len = base.random.randn.seedLength;\n","base.random.randn.state":"var r = base.random.randn()\nr = base.random.randn()\nr = base.random.randn()\nvar state = base.random.randn.state;\nr = base.random.randn()\nr = base.random.randn()\nbase.random.randn.state = state;\nr = base.random.randn()\nr = base.random.randn()\n","base.random.randn.stateLength":"var len = base.random.randn.stateLength;\n","base.random.randn.byteLength":"var sz = base.random.randn.byteLength;\n","base.random.randn.toJSON":"var o = base.random.randn.toJSON()\n","base.random.randu":"var r = base.random.randu();\n","base.random.randu.factory":"var rand = base.random.randu.factory();\nvar r = rand();\nr = rand();\nvar rand = base.random.randu.factory({ 'name': 'minstd' });\nr = rand();\nr = rand();\n","base.random.randu.NAME":"var str = base.random.randu.NAME\n","base.random.randu.PRNG":"var prng = base.random.randu.PRNG;\n","base.random.randu.MIN":"var v = base.random.randu.MIN;\n","base.random.randu.MAX":"var v = base.random.randu.MAX;\n","base.random.randu.seed":"var seed = base.random.randu.seed;\n","base.random.randu.seedLength":"var len = base.random.randu.seedLength;\n","base.random.randu.state":"var r = base.random.randu()\nr = base.random.randu()\nr = base.random.randu()\nvar state = base.random.randu.state;\nr = base.random.randu()\nr = base.random.randu()\nbase.random.randu.state = state;\nr = base.random.randu()\nr = base.random.randu()\n","base.random.randu.stateLength":"var len = base.random.randu.stateLength;\n","base.random.randu.byteLength":"var sz = base.random.randu.byteLength;\n","base.random.randu.toJSON":"var o = base.random.randu.toJSON()\n","base.random.rayleigh":"var r = base.random.rayleigh( 2.5 );\n","base.random.rayleigh.factory":"var rand = base.random.rayleigh.factory();\nvar r = rand( 5.0 );\nr = rand( 10.0 );\nrand = base.random.rayleigh.factory( 5.0 );\nr = rand();\nr = rand();\n","base.random.rayleigh.NAME":"var str = base.random.rayleigh.NAME\n","base.random.rayleigh.PRNG":"var prng = base.random.rayleigh.PRNG;\n","base.random.rayleigh.seed":"var seed = base.random.rayleigh.seed;\n","base.random.rayleigh.seedLength":"var len = base.random.rayleigh.seedLength;\n","base.random.rayleigh.state":"var r = base.random.rayleigh( 5.0 )\nr = base.random.rayleigh( 5.0 )\nr = base.random.rayleigh( 5.0 )\nvar state = base.random.rayleigh.state\nr = base.random.rayleigh( 5.0 )\nr = base.random.rayleigh( 5.0 )\nbase.random.rayleigh.state = state;\nr = base.random.rayleigh( 5.0 )\nr = base.random.rayleigh( 5.0 )\n","base.random.rayleigh.stateLength":"var len = base.random.rayleigh.stateLength;\n","base.random.rayleigh.byteLength":"var sz = base.random.rayleigh.byteLength;\n","base.random.rayleigh.toJSON":"var o = base.random.rayleigh.toJSON()\n","base.random.t":"var r = base.random.t( 2.0 );\n","base.random.t.factory":"var rand = base.random.t.factory();\nvar r = rand( 5.0 );\nr = rand( 3.14 );\nrand = base.random.t.factory( 5.0 );\nr = rand();\nr = rand();\n","base.random.t.NAME":"var str = base.random.t.NAME\n","base.random.t.PRNG":"var prng = base.random.t.PRNG;\n","base.random.t.seed":"var seed = base.random.t.seed;\n","base.random.t.seedLength":"var len = base.random.t.seedLength;\n","base.random.t.state":"var r = base.random.t( 10.0 )\nr = base.random.t( 10.0 )\nr = base.random.t( 10.0 )\nvar state = base.random.t.state\nr = base.random.t( 10.0 )\nr = base.random.t( 10.0 )\nbase.random.t.state = state;\nr = base.random.t( 10.0 )\nr = base.random.t( 10.0 )\n","base.random.t.stateLength":"var len = 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base.random.triangular( 0.0, 1.0, 0.5 )\nr = base.random.triangular( 0.0, 1.0, 0.5 )\nbase.random.triangular.state = state;\nr = base.random.triangular( 0.0, 1.0, 0.5 )\nr = base.random.triangular( 0.0, 1.0, 0.5 )\n","base.random.triangular.stateLength":"var len = base.random.triangular.stateLength;\n","base.random.triangular.byteLength":"var sz = base.random.triangular.byteLength;\n","base.random.triangular.toJSON":"var o = base.random.triangular.toJSON()\n","base.random.uniform":"var r = base.random.uniform( 2.0, 5.0 );\n","base.random.uniform.factory":"var rand = base.random.uniform.factory();\nvar r = rand( 0.0, 1.0 );\nr = rand( -2.0, 2.0 );\nrand = base.random.uniform.factory( 0.0, 1.0 );\nr = rand();\nr = rand();\n","base.random.uniform.NAME":"var str = base.random.uniform.NAME\n","base.random.uniform.PRNG":"var prng = base.random.uniform.PRNG;\n","base.random.uniform.seed":"var seed = base.random.uniform.seed;\n","base.random.uniform.seedLength":"var len = base.random.uniform.seedLength;\n","base.random.uniform.state":"var r = base.random.uniform( 2.0, 5.0 )\nr = base.random.uniform( 2.0, 5.0 )\nr = base.random.uniform( 2.0, 5.0 )\nvar state = base.random.uniform.state\nr = base.random.uniform( 2.0, 5.0 )\nr = base.random.uniform( 2.0, 5.0 )\nbase.random.uniform.state = state;\nr = base.random.uniform( 2.0, 5.0 )\nr = base.random.uniform( 2.0, 5.0 )\n","base.random.uniform.stateLength":"var len = base.random.uniform.stateLength;\n","base.random.uniform.byteLength":"var sz = base.random.uniform.byteLength;\n","base.random.uniform.toJSON":"var o = base.random.uniform.toJSON()\n","base.random.weibull":"var r = base.random.weibull( 2.0, 5.0 );\n","base.random.weibull.factory":"var rand = base.random.weibull.factory();\nvar r = rand( 0.1, 1.5 );\nr = rand( 2.0, 3.14 );\nrand = base.random.weibull.factory( 0.1, 1.5 );\nr = rand();\nr = rand();\n","base.random.weibull.NAME":"var str = base.random.weibull.NAME\n","base.random.weibull.PRNG":"var prng = base.random.weibull.PRNG;\n","base.random.weibull.seed":"var seed = base.random.weibull.seed;\n","base.random.weibull.seedLength":"var len = base.random.weibull.seedLength;\n","base.random.weibull.state":"var r = base.random.weibull( 2.0, 5.0 )\nr = base.random.weibull( 2.0, 5.0 )\nr = base.random.weibull( 2.0, 5.0 )\nvar state = base.random.weibull.state\nr = base.random.weibull( 2.0, 5.0 )\nr = base.random.weibull( 2.0, 5.0 )\nbase.random.weibull.state = state;\nr = base.random.weibull( 2.0, 5.0 )\nr = base.random.weibull( 2.0, 5.0 )\n","base.random.weibull.stateLength":"var len = base.random.weibull.stateLength;\n","base.random.weibull.byteLength":"var sz = base.random.weibull.byteLength;\n","base.random.weibull.toJSON":"var o = base.random.weibull.toJSON()\n","base.rcbrt":"var y = base.rcbrt( 8.0 )\ny = base.rcbrt( 1000.0 )\ny = base.rcbrt( 0.0 )\ny = base.rcbrt( PINF )\ny = base.rcbrt( -8.0 )\ny = base.rcbrt( NaN )\n","base.rcbrtf":"var y = base.rcbrtf( 8.0 )\ny = base.rcbrtf( 1000.0 )\ny = base.rcbrtf( 0.0 )\ny = base.rcbrtf( PINF )\ny = base.rcbrtf( -8.0 )\ny = base.rcbrtf( NaN )\n","base.reldiff":"var d = base.reldiff( 2.0, 5.0 )\nd = base.reldiff( -1.0, 3.14 )\nd = base.reldiff( -2.0, 5.0, 'max-abs' )\nd = base.reldiff( -2.0, 5.0, 'max' )\nd = base.reldiff( -2.0, 5.0, 'min-abs' )\nd = base.reldiff( -2.0, 5.0, 'min' )\nd = base.reldiff( -2.0, 5.0, 'mean-abs' )\nd = base.reldiff( -2.0, 5.0, 'mean' )\nd = base.reldiff( -2.0, 5.0, 'x' )\nd = base.reldiff( 5.0, -2.0, 'x' )\nd = base.reldiff( -2.0, 5.0, 'y' )\nd = base.reldiff( 5.0, -2.0, 'y' )\nfunction scale( x, y ) {\n var s;\n\n x = base.abs( x );\n y = base.abs( y );\n\n // Maximum absolute value:\n s = (x < y ) ? y : x;\n\n // Scale in units of epsilon:\n return s * EPS;\n };\nd = base.reldiff( 12.15, 12.149999999999999, scale )\n","base.removeFirst":"var out = base.removeFirst( 'beep', 1 )\nout = base.removeFirst( 'Boop', 1 )\nout = base.removeFirst( 'foo bar', 5 )\n","base.removeFirstCodePoint":"var out = base.removeFirstCodePoint( 'beep', 1 )\nout = base.removeFirstCodePoint( 'Boop', 1 )\nout = base.removeFirstCodePoint( 'foo bar', 5 )\n","base.removeFirstGraphemeCluster":"var out = base.removeFirstGraphemeCluster( 'beep', 1 )\nout = base.removeFirstGraphemeCluster( 'Boop', 1 )\nout = base.removeFirstGraphemeCluster( 'foo bar', 5 )\n","base.removeLast":"var out = base.removeLast( 'beep', 1 )\nout = base.removeLast( 'Boop', 1 )\nout = base.removeLast( 'foo bar', 5 )\n","base.removeLastCodePoint":"var out = base.removeLastCodePoint( 'beep', 1 )\nout = base.removeLastCodePoint( 'Boop', 1 )\nout = base.removeLastCodePoint( 'foo bar', 5 )\n","base.removeLastGraphemeCluster":"var out = base.removeLastGraphemeCluster( 'beep', 1 )\nout = base.removeLastGraphemeCluster( 'Boop', 1 )\nout = base.removeLastGraphemeCluster( 'foo bar', 5 )\n","base.rempio2":"var y = [ 0.0, 0.0 ];\nvar n = base.rempio2( 128.0, y )\nvar y1 = y[ 0 ]\nvar y2 = y[ 1 ]\n","base.repeat":"var out = base.repeat( 'a', 5 )\nout = base.repeat( '', 100 )\nout = base.repeat( 'beep', 0 )\n","base.replace":"function replacer( match, p1 ) { return '/'+p1+'/'; };\nvar str = 'Oranges and lemons';\nvar out = base.replace( str, /([^\\s]+)/gi, replacer )\nout = base.replace( 'beep', /e/, 'o' )\n","base.replaceAfter":"var out = base.replaceAfter( 'beep boop', ' ', 'foo', 0 )\nout = base.replaceAfter( 'beep boop', 'o', 'foo', 0 )\nout = base.replaceAfter( 'Hello World!', 'o', 'foo', 5 )\nout = base.replaceAfter( 'beep boop beep baz', 'beep', 'foo', 5 )\n","base.replaceAfterLast":"var str = 'beep boop';\nvar out = base.replaceAfterLast( str, ' ', 'foo', str.length )\nout = base.replaceAfterLast( str, 'o', 'foo', str.length )\nout = base.replaceAfterLast( 'Hello World!', 'o', 'foo', 5 )\n","base.replaceBefore":"var out = base.replaceBefore( 'beep boop', ' ', 'foo', 0 )\nout = base.replaceBefore( 'beep boop', 'o', 'foo', 0 )\n","base.replaceBeforeLast":"var str = 'beep boop';\nvar out = base.replaceBeforeLast( str, ' ', 'foo', str.length )\nout = base.replaceBeforeLast( str, 'o', 'foo', str.length )\nout = base.replaceBeforeLast( 'Hello World!', 'o', 'foo', 5 )\n","base.reverse":"var out = base.reverse( 'beep' )\nout = base.reverse( 'Boop' )\nout = base.reverse( 'foo bar' )\n","base.reverseCodePoints":"var out = base.reverseCodePoints( 'beep' )\nout = base.reverseCodePoints( 'Boop' )\nout = base.reverseCodePoints( 'foo bar' )\n","base.reverseGraphemeClusters":"var out = base.reverseGraphemeClusters( 'beep' )\nout = base.reverseGraphemeClusters( 'Boop' )\nout = base.reverseGraphemeClusters( 'foo bar' )\n","base.rightPad":"var out = base.rightPad( 'a', 5, ' ' )\nout = base.rightPad( 'beep', 10, 'b' )\nout = base.rightPad( 'boop', 12, 'beep' )\n","base.rightTrim":"var out = base.rightTrim( ' \\t\\t\\n  Beep \\r\\n\\t  ' )\n","base.risingFactorial":"var v = base.risingFactorial( 0.9, 5 )\nv = base.risingFactorial( -9.0, 3 )\nv = base.risingFactorial( 0.0, 2 )\nv = base.risingFactorial( 3.0, -2 )\n","base.rotl32":"var x = 2147483649;\nvar bStr = base.toBinaryStringUint32( x )\nvar y = base.rotl32( x, 10 )\nbstr = base.toBinaryStringUint32( y )\n","base.rotr32":"var x = 1;\nvar bStr = base.toBinaryStringUint32( x )\nvar y = base.rotr32( x, 10 )\nbstr = base.toBinaryStringUint32( y )\n","base.round":"var y = base.round( 3.14 )\ny = base.round( -4.2 )\ny = base.round( -4.6 )\ny = base.round( 9.5 )\ny = base.round( -0.0 )\n","base.round2":"var y = base.round2( 3.14 )\ny = base.round2( -4.2 )\ny = base.round2( -4.6 )\ny = base.round2( 9.5 )\ny = base.round2( 13.0 )\ny = base.round2( -13.0 )\ny = base.round2( -0.0 )\n","base.round10":"var y = base.round10( 3.14 )\ny = base.round10( -4.2 )\ny = base.round10( -4.6 )\ny = base.round10( 9.5 )\ny = base.round10( 13.0 )\ny = base.round10( -13.0 )\ny = base.round10( -0.0 )\n","base.roundb":"var y = base.roundb( 3.14159, -2, 10 )\ny = base.roundb( 3.14159, 0, 2 )\ny = base.roundb( 5.0, 1, 2 )\n","base.roundn":"var y = base.roundn( 3.14159, -2 )\ny = base.roundn( 3.14159, 0 )\ny = base.roundn( 12368.0, 3 )\n","base.roundsd":"var y = base.roundsd( 3.14159, 3 )\ny = base.roundsd( 3.14159, 1 )\ny = base.roundsd( 12368.0, 2 )\ny = base.roundsd( 0.0313, 2, 2 )\n","base.rsqrt":"var y = base.rsqrt( 4.0 )\ny = base.rsqrt( 100.0 )\ny = base.rsqrt( 0.0 )\ny = base.rsqrt( Infinity )\ny = base.rsqrt( -4.0 )\ny = base.rsqrt( NaN )\n","base.rsqrtf":"var y = base.rsqrtf( 4.0 )\ny = base.rsqrtf( 0.0 )\ny = base.rsqrtf( Infinity )\ny = base.rsqrtf( -4.0 )\ny = base.rsqrtf( NaN )\n","base.sargs2multislice":"var s = new base.sargs2multislice( 'null,null,null' );\ns.data\ns = new base.sargs2multislice( '10,Slice(0,10,1),null' );\ns.data\n","base.scalar2ndarray":"var x = base.scalar2ndarray( 1.0, 'float64', 'row-major' )\nvar sh = x.shape\nvar dt = x.dtype\nvar v = x.get()\n","base.secd":"var y = base.secd( 1.0 )\ny = base.secd( PI )\ny = base.secd( -PI )\ny = base.secd( NaN )\n","base.seq2multislice":"var s = new base.seq2multislice( '1:10', [ 10 ], false );\ns.data\ns = new base.seq2multislice( '4,2:5:2,:', [ 10, 10, 10 ], false );\ns.data\n","base.seq2slice":"var s = new base.seq2slice( '1:10', 10, false );\ns.start\ns.stop\ns.step\ns = new base.seq2slice( '2:5:2', 10, false );\ns.start\ns.stop\ns.step\n","base.setHighWord":"var high = 1072693248 >>> 0;\nvar y = base.setHighWord( PINF, high )\n","base.setLowWord":"var low = 5 >>> 0;\nvar x = 3.14e201;\nvar y = base.setLowWord( x, low )\nvar low = 12345678;\nvar y = base.setLowWord( PINF, low )\ny = base.setLowWord( NINF, low )\ny = base.setLowWord( NaN, low )\n","base.sici":"var y = base.sici( 3.0 )\ny = base.sici( 0.0 )\ny = base.sici( -9.0 )\ny = base.sici( NaN )\n","base.sici.assign":"var out = new Float64Array( 2 );\nvar y = base.sici.assign( 3.0, out, 1, 0 )\nvar bool = ( y === out )\n","base.signbit":"var bool = base.signbit( 4.0 )\nbool = base.signbit( -9.14e-34 )\nbool = base.signbit( 0.0 )\nbool = base.signbit( -0.0 )\n","base.signbitf":"var bool = base.signbitf( base.float64ToFloat32( 4.0 ) )\nbool = base.signbitf( base.float64ToFloat32( -9.14e-34 ) )\nbool = base.signbitf( 0.0 )\nbool = base.signbitf( -0.0 )\n","base.significandf":"var s = base.significandf( base.float64ToFloat32( 3.14e34 ) )\ns = base.significandf( base.float64ToFloat32( 3.14e-34 ) )\ns = base.significandf( base.float64ToFloat32( -3.14 ) )\ns = base.significandf( 0.0 )\ns = base.significandf( NaN )\n","base.signum":"var sign = base.signum( -5.0 )\nsign = base.signum( 5.0 )\nsign = base.signum( -0.0 )\nsign = base.signum( 0.0 )\nsign = base.signum( NaN )\n","base.signumf":"var sign = base.signumf( -5.0 )\nsign = base.signumf( 5.0 )\nsign = base.signumf( -0.0 )\nsign = base.signumf( 0.0 )\nsign = base.signumf( NaN )\n","base.sin":"var y = base.sin( 0.0 )\ny = base.sin( PI/2.0 )\ny = base.sin( -PI/6.0 )\ny = base.sin( NaN )\n","base.sinc":"var y = base.sinc( 0.5 )\ny = base.sinc( -1.2 )\ny = base.sinc( 0.0 )\ny = base.sinc( NaN )\n","base.sincos":"var y = base.sincos( 0.0 )\ny = base.sincos( PI/2.0 )\ny = base.sincos( -PI/6.0 )\ny = base.sincos( NaN )\nvar out = new Float64Array( 2 );\nvar v = base.sincos.assign( 0.0, out, 1, 0 )\nvar bool = ( v === out )\n","base.sincospi":"var y = base.sincospi( 0.0 )\ny = base.sincospi( 0.5 )\ny = base.sincospi( 0.1 )\ny = base.sincospi( NaN )\n","base.sincospi.assign":"var out = new Float64Array( 2 );\nvar v = base.sincospi.assign( 0.0, out, 1, 0 )\nvar bool = ( v === out )\n","base.sinh":"var y = base.sinh( 0.0 )\ny = base.sinh( 2.0 )\ny = base.sinh( -2.0 )\ny = base.sinh( NaN )\n","base.sinpi":"var y = base.sinpi( 0.0 )\ny = base.sinpi( 0.5 )\ny = base.sinpi( 0.9 )\ny = base.sinpi( NaN )\n","base.slice2seq":"var out = base.slice2seq( new Slice( 1, 10, 1 ) )\nout = base.slice2seq( new Slice( null, 10 ) )\n","base.sliceLength":"var s = new Slice( 1, 10, 1 );\nbase.sliceLength( s )\n","base.sliceNonReducedDimensions":"var s = new MultiSlice( 1, 3, null );\nvar out = base.sliceNonReducedDimensions( s )\n","base.sliceReducedDimensions":"var s = new MultiSlice( 1, 3, null );\nvar out = base.sliceReducedDimensions( s )\n","base.sliceShape":"var s = new Slice( 1, 10, 1 );\nvar ms = new MultiSlice( s, s );\nbase.sliceShape( ms )\n","base.snakecase":"var out = base.snakecase( 'Hello World!' )\nout = base.snakecase( 'I am a tiny little teapot' )\n","base.spence":"var y = base.spence( 3.0 )\ny = base.spence( 0.0 )\ny = base.spence( -9.0 )\ny = base.spence( NaN )\n","base.sqrt":"var y = base.sqrt( 4.0 )\ny = base.sqrt( 9.0 )\ny = base.sqrt( 0.0 )\ny = base.sqrt( -4.0 )\ny = base.sqrt( NaN )\n","base.sqrt1pm1":"var y = base.sqrt1pm1( 3.0 )\ny = base.sqrt1pm1( 0.5 )\ny = base.sqrt1pm1( 0.02 )\ny = base.sqrt1pm1( -0.5 )\ny = base.sqrt1pm1( -1.1 )\ny = base.sqrt1pm1( NaN )\n","base.sqrtf":"var y = base.sqrtf( 4.0 )\ny = base.sqrtf( 9.0 )\ny = base.sqrtf( 0.0 )\ny = base.sqrtf( -4.0 )\ny = base.sqrtf( NaN )\n","base.sqrtpi":"var y = base.sqrtpi( 4.0 )\ny = base.sqrtpi( 10.0 )\ny = base.sqrtpi( 0.0 )\ny = base.sqrtpi( -4.0 )\ny = base.sqrtpi( NaN )\n","base.startcase":"var out = base.startcase( 'beep boop' )\n","base.startsWith":"var bool = base.startsWith( 'Beep', 'Be', 0 )\nbool = base.startsWith( 'Beep', 'ep', 0 )\nbool = base.startsWith( 'Beep', 'ee', 1 )\nbool = base.startsWith( 'Beep', 'ee', -3 )\nbool = base.startsWith( 'Beep', '', 0 )\n","base.stickycase":"var out = base.stickycase( 'Hello World!' )\nout = base.stickycase( 'I am a tiny little teapot' )\n","base.strided.binary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nfunction f( x, y ) { return x + y; };\nbase.strided.binary( [ x, y, z ], shape, strides, f );\nz\n","base.strided.binary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nvar offsets = [ 0, 0, 0 ];\nfunction f( x, y ) { return x + y; };\nbase.strided.binary.ndarray( [ x, y, z ], shape, strides, offsets, f );\nz\n","base.strided.binaryDtypeSignatures":"var dt = strided.dataTypes();\nvar out = base.strided.binaryDtypeSignatures( dt, dt, dt )\n","base.strided.binarySignatureCallbacks":"var dt = strided.dataTypes();\nvar sigs = base.strided.binaryDtypeSignatures( dt, dt, dt );\nvar t = {\n 'default': base.add,\n 'complex64': base.caddf,\n 'complex128': base.cadd\n };\nvar out = base.strided.binarySignatureCallbacks( t, sigs )\n","base.strided.ccopy":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.ccopy( x.length, x, 1, y, 1 );\nvar z = y.get( 0 );\nvar re = realf( z )\nvar im = imagf( z )\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ccopy( 2, x, -2, y, 1 );\nz = y.get( 0 );\nre = realf( z )\nim = imagf( z )\nvar x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\nvar y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.ccopy( 2, x1, -2, y1, 1 );\nz = y0.get( 2 );\nre = realf( z )\nim = imagf( z )\n","base.strided.ccopy.ndarray":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.ccopy.ndarray( x.length, x, 1, 0, y, 1, 0 );\nvar z = y.get( 0 );\nvar re = realf( z )\nvar im = imagf( z )\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ccopy.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\nz = y.get( y.length-1 );\nre = realf( z )\nim = imagf( z )\n","base.strided.cmap":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex64Array( xbuf );\nvar y = new Complex64Array( x.length );\nbase.strided.cmap( x.length, x, 1, y, 1, base.cidentityf );\nvar v = y.get( 0 )\nvar re = real( v )\nvar im = imag( v )\ny = new Complex64Array( x.length );\nbase.strided.cmap( 2, x, 2, y, -1, base.cidentityf );\nv = y.get( 0 )\nre = real( v )\nim = imag( v )\nvar x0 = new Complex64Array( xbuf );\nvar y0 = new Complex64Array( x0.length );\nvar x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.cmap( 2, x1, -2, y1, 1, base.cidentityf );\nv = y1.get( 0 )\nre = real( v )\nim = imag( v )\n","base.strided.cmap.ndarray":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex64Array( xbuf );\nvar y = new Complex64Array( x.length );\nbase.strided.cmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentityf );\nvar v = y.get( 0 )\nvar re = real( v )\nvar im = imag( v )\nx = new Complex64Array( xbuf );\ny = new Complex64Array( x.length );\nbase.strided.cmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentityf );\nv = y.get( y.length-1 )\nre = real( v )\nim = imag( v )\n","base.strided.cswap":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.cswap( x.length, x, 1, y, 1 );\nvar z = y.get( 0 );\nvar re = realf( z )\nvar im = imagf( z )\nz = x.get( 0 );\nre = realf( z )\nim = imagf( z )\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.cswap( 2, x, -2, y, 1 );\nz = y.get( 0 );\nre = realf( z )\nim = imagf( z )\nz = x.get( 0 );\nre = realf( z )\nim = imagf( z )\nvar x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\nvar y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.cswap( 2, x1, -2, y1, 1 );\nz = y0.get( 2 );\nre = realf( z )\nim = imagf( z )\nz = x0.get( 1 );\nre = realf( z )\nim = imagf( z )\n","base.strided.cswap.ndarray":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.cswap.ndarray( x.length, x, 1, 0, y, 1, 0 );\nvar z = y.get( 0 );\nvar re = realf( z )\nvar im = imagf( z )\nz = x.get( 0 );\nre = realf( z )\nim = imagf( z )\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.cswap.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\nz = y.get( y.length-1 );\nre = realf( z )\nim = imagf( z )\nz = x.get( 1 );\nre = realf( z )\nim = imagf( z )\n","base.strided.cumax":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumax( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumax( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.cumax( N, x1, 2, y1, 1 )\ny0\n","base.strided.cumax.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumax.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.cumaxabs":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumaxabs( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumaxabs( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.cumaxabs( N, x1, 2, y1, 1 )\ny0\n","base.strided.cumaxabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.cumin":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumin( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumin( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.cumin( N, x1, 2, y1, 1 )\ny0\n","base.strided.cumin.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.cuminabs":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cuminabs( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cuminabs( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.cuminabs( N, x1, 2, y1, 1 )\ny0\n","base.strided.cuminabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dabs":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dabs( N, x1, -2, y1, 1 )\ny0\n","base.strided.dabs.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dabs2":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs2( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs2( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dabs2( N, x1, -2, y1, 1 )\ny0\n","base.strided.dabs2.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dapx":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dapx( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dapx( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapx( 3, 5.0, x1, 2 )\nx0\n","base.strided.dapx.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dapx.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.dapx.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsum":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsum( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsum( 3, 5.0, x1, 2 )\n","base.strided.dapxsum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsumkbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsumkbn( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsumkbn( 3, 5.0, x1, 2)\n","base.strided.dapxsumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsumkbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn2( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsumkbn2( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsumkbn2( 3, 5.0, x1, 2 )\n","base.strided.dapxsumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsumors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumors( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsumors( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsumors( 3, 5.0, x1, 2 )\n","base.strided.dapxsumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumpw( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsumpw( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsumpw( 3, 5.0, x1, 2 )\n","base.strided.dapxsumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dasum":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.dasum( x.length, x, 1 )\ns = base.strided.dasum( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\ns = base.strided.dasum( 3, x1, 2 )\n","base.strided.dasum.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.dasum.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\ns = base.strided.dasum.ndarray( 3, x, -1, x.length-1 )\n","base.strided.dasumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dasumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar stride = 2;\nbase.strided.dasumpw( 3, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.dasumpw( 3, x1, stride )\n","base.strided.dasumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dasumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dasumpw.ndarray( 3, x, 2, 1 )\n","base.strided.daxpy":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.daxpy( x.length, alpha, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nbase.strided.daxpy( 3, alpha, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.daxpy( 3, 5.0, x1, -2, y1, 1 )\ny0\n","base.strided.daxpy.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.daxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.daxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcbrt":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dcbrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dcbrt( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dcbrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.dcbrt.ndarray":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dcbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dceil":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dceil( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dceil( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dceil( N, x1, -2, y1, 1 )\ny0\n","base.strided.dceil.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcopy":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dcopy( x.length, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dcopy( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcopy( 3, x1, -2, y1, 1 )\ny0\n","base.strided.dcopy.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcumax":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumax( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumax( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcumax( 3, x1, 2, y1, 1 )\ny0\n","base.strided.dcumax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcumaxabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumaxabs( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcumaxabs( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.dcumaxabs( N, x1, 2, y1, 1 )\ny0\n","base.strided.dcumaxabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcumin":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumin( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcumin( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.dcumin( N, x1, 2, y1, 1 )\ny0\n","base.strided.dcumin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcuminabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcuminabs( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcuminabs( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcuminabs( 3, x1, 2, y1, 1 )\ny0\n","base.strided.dcuminabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusum":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusum( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusum( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusum( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumkbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumkbn( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusumkbn( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumkbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn2( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumkbn2( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusumkbn2( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumors( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumors( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusumors( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumpw( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumpw( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusumpw( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.ddeg2rad":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ddeg2rad( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ddeg2rad( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.ddeg2rad( N, x1, -2, y1, 1 )\ny0\n","base.strided.ddeg2rad.ndarray":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ddeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ddeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.ddot":"var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.ddot( x.length, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.ddot( 3, x, 2, y, -1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.ddot( 3, x1, -2, y1, 1 )\n","base.strided.ddot.ndarray":"var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.ddot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.ddot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nout = base.strided.ddot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.dfill":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dfill( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dfill( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dfill( 3, 5.0, x1, 2 )\nx0\n","base.strided.dfill.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dfill.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.dfill.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dfloor":"var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dfloor( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dfloor( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dfloor( N, x1, -2, y1, 1 )\ny0\n","base.strided.dfloor.ndarray":"var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dinv":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dinv( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dinv( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dinv( N, x1, -2, y1, 1 )\ny0\n","base.strided.dinv.ndarray":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dmap":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap( x.length, x, 1, y, 1, base.identity )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap( 2, x, 2, y, -1, base.identity )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmap( 2, x1, -2, y1, 1, base.identity )\ny0\n","base.strided.dmap.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identity )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identity )\n","base.strided.dmap2":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2( x.length, x, 1, y, 1, z, 1, base.add )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2( 2, x, 2, y, -1, z, 1, base.add )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmap2( 2, x1, -2, y1, 1, z1, 1, base.add )\nz0\n","base.strided.dmap2.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.add )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.add )\n","base.strided.dmax":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmax( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmax( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmax( 3, x1, 2 )\n","base.strided.dmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmax.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmax.ndarray( 3, x, 2, 1 )\n","base.strided.dmaxabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmaxabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmaxabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmaxabs( 3, x1, 2 )\n","base.strided.dmaxabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmaxabs.ndarray( 3, x, 2, 1 )\n","base.strided.dmaxabssorted":"var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.dmaxabssorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmaxabssorted( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmaxabssorted( N, x1, stride )\n","base.strided.dmaxabssorted.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.dmaxabssorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmaxabssorted.ndarray( N, x, 2, 1 )\n","base.strided.dmaxsorted":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmaxsorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmaxsorted( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmaxsorted( N, x1, stride )\n","base.strided.dmaxsorted.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmaxsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmaxsorted.ndarray( N, x, 2, 1 )\n","base.strided.dmean":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmean( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmean( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmean( N, x1, stride )\n","base.strided.dmean.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmean.ndarray( N, x, 2, 1 )\n","base.strided.dmeankbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeankbn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeankbn( N, x1, stride )\n","base.strided.dmeankbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeankbn.ndarray( N, x, 2, 1 )\n","base.strided.dmeankbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeankbn2( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeankbn2( N, x1, stride )\n","base.strided.dmeankbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeankbn2.ndarray( N, x, 2, 1 )\n","base.strided.dmeanli":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanli( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanli( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanli( N, x1, stride )\n","base.strided.dmeanli.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanli.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanli.ndarray( N, x, 2, 1 )\n","base.strided.dmeanlipw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanlipw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanlipw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanlipw( N, x1, stride )\n","base.strided.dmeanlipw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanlipw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanlipw.ndarray( N, x, 2, 1 )\n","base.strided.dmeanors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanors( N, x1, stride )\n","base.strided.dmeanors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanors.ndarray( N, x, 2, 1 )\n","base.strided.dmeanpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanpn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanpn( N, x1, stride )\n","base.strided.dmeanpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.dmeanpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanpw( N, x1, stride )\n","base.strided.dmeanpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanpw.ndarray( N, x, 2, 1 )\n","base.strided.dmeanstdev":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdev( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanstdev( N, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdev( N, 1, x1, 2, out, 1 )\n","base.strided.dmeanstdev.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdev.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdev.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanstdevpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdevpn( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanstdevpn( N, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdevpn( N, 1, x1, 2, out, 1 )\n","base.strided.dmeanstdevpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdevpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdevpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanvar":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvar( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanvar( N, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanvar( N, 1, x1, 2, out, 1 )\n","base.strided.dmeanvar.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvar.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanvar.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanvarpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvarpn( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanvarpn( N, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanvarpn( N, 1, x1, 2, out, 1 )\n","base.strided.dmeanvarpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvarpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanvarpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanwd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanwd( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanwd( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanwd( N, x1, stride )\n","base.strided.dmeanwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanwd.ndarray( N, x, 2, 1 )\n","base.strided.dmediansorted":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmediansorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmediansorted( N, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dmediansorted( N, x1, 2 )\n","base.strided.dmediansorted.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmediansorted.ndarray( N, x, 2, 1 )\n","base.strided.dmidrange":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmidrange( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmidrange( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmidrange( 3, x1, 2 )\n","base.strided.dmidrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmidrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmidrange.ndarray( 3, x, 2, 1 )\n","base.strided.dmin":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmin( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmin( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmin( N, x1, stride )\n","base.strided.dmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmin.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmin.ndarray( 3, x, 2, 1 )\n","base.strided.dminabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dminabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dminabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dminabs( 3, x1, 2 )\n","base.strided.dminabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dminabs.ndarray( 3, x, 2, 1 )\n","base.strided.dminsorted":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dminsorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dminsorted( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dminsorted( N, x1, stride )\n","base.strided.dminsorted.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dminsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dminsorted.ndarray( N, x, 2, 1 )\n","base.strided.dmskabs":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskabs( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskabs.ndarray":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskabs2":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskabs2( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskabs2.ndarray":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskcbrt":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskcbrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskcbrt.ndarray":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskceil":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskceil( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskceil.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskdeg2rad":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskdeg2rad.ndarray":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskfloor":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskfloor( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskfloor.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskinv":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskinv( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskinv.ndarray":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskmap":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap( x.length, x, 1, m, 1, y, 1, base.identity )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap( 2, x, 2, m, 2, y, -1, base.identity )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\ny0\n","base.strided.dmskmap.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n","base.strided.dmskmap2":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.add )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.add )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.add )\nz0\n","base.strided.dmskmap2.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.add )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.add )\n","base.strided.dmskmax":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmax( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmskmax( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dmskmax( N, x1, 2, mask1, 2 )\n","base.strided.dmskmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.dmskmin":"var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmin( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmskmin( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dmskmin( N, x1, 2, mask1, 2 )\n","base.strided.dmskmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.dmskramp":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskramp( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskramp.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskrange":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskrange( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskrange( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmskrange( 3, x1, 2, mask1, 2 )\n","base.strided.dmskrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.dmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.dmskrsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskrsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmsksqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmsksqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmsksqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmsktrunc":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmsktrunc( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmsktrunc.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dnanasum":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasum( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanasum( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanasum( 4, x1, 2 )\n","base.strided.dnanasum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasum.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanasum.ndarray( 4, x, 2, 1 )\n","base.strided.dnanasumors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasumors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanasumors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanasumors( N, x1, stride )\n","base.strided.dnanasumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanasumors.ndarray( N, x, 2, 1 )\n","base.strided.dnanmax":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmax( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanmax( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmax( 3, x1, 2 )\n","base.strided.dnanmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanmax.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanmax.ndarray( 3, x, 2, 1 )\n","base.strided.dnanmaxabs":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmaxabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanmaxabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmaxabs( 3, x1, 2 )\n","base.strided.dnanmaxabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanmaxabs.ndarray( 3, x, 2, 1 )\n","base.strided.dnanmean":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmean( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmean( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmean( N, x1, stride )\n","base.strided.dnanmean.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmean.ndarray( N, x, 2, 1 )\n","base.strided.dnanmeanors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmeanors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmeanors( N, x1, stride )\n","base.strided.dnanmeanors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmeanors.ndarray( N, x, 2, 1 )\n","base.strided.dnanmeanpn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmeanpn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmeanpn( N, x1, stride )\n","base.strided.dnanmeanpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.dnanmeanpw":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmeanpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmeanpw( N, x1, stride )\n","base.strided.dnanmeanpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmeanpw.ndarray( N, x, 2, 1 )\n","base.strided.dnanmeanwd":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanwd( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmeanwd( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmeanwd( N, x1, stride )\n","base.strided.dnanmeanwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmeanwd.ndarray( N, x, 2, 1 )\n","base.strided.dnanmin":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmin( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanmin( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmin( 3, x1, 2 )\n","base.strided.dnanmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanmin.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanmin.ndarray( 3, x, 2, 1 )\n","base.strided.dnanminabs":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanminabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanminabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanminabs( 3, x1, 2 )\n","base.strided.dnanminabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanminabs.ndarray( 3, x, 2, 1 )\n","base.strided.dnanmskmax":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.dnanmskmax( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskmax( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dnanmskmax( N, x1, 2, mask1, 2 )\n","base.strided.dnanmskmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.dnanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.dnanmskmin":"var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.dnanmskmin( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskmin( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dnanmskmin( N, x1, 2, mask1, 2 )\n","base.strided.dnanmskmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.dnanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.dnanmskrange":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.dnanmskrange( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskrange( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dnanmskrange( N, x1, 2, mask1, 2 )\n","base.strided.dnanmskrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.dnanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.dnannsum":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsum( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsum( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsum( 4, x1, 2, out, 1 )\n","base.strided.dnannsum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsum.ndarray( x.length, x, 1, 0, out, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsum.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumkbn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn( 4, x1, 2, out, 1 )\n","base.strided.dnannsumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn.ndarray( 4, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumkbn2":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn2( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn2( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn2( 4, x1, 2, out, 1 )\n","base.strided.dnannsumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn2.ndarray( 4, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn2.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumors( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumors( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumors( 4, x1, 2, out, 1 )\n","base.strided.dnannsumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumpw":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumpw( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumpw( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumpw( 4, x1, 2, out, 1 )\n","base.strided.dnannsumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumpw.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumpw.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnanrange":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanrange( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanrange( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanrange( 3, x1, 2 )\n","base.strided.dnanrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanrange.ndarray( 3, x, 2, 1 )\n","base.strided.dnanstdev":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdev( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdev( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdev( N, 1, x1, stride )\n","base.strided.dnanstdev.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanstdevch":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevch( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdevch( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdevch( N, 1, x1, stride )\n","base.strided.dnanstdevch.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanstdevpn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevpn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdevpn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdevpn( N, 1, x1, stride )\n","base.strided.dnanstdevpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanstdevtk":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevtk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdevtk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdevtk( N, 1, x1, stride )\n","base.strided.dnanstdevtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanstdevwd":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevwd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdevwd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdevwd( N, 1, x1, stride )\n","base.strided.dnanstdevwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanstdevyc":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdevyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdevyc( N, 1, x1, stride )\n","base.strided.dnanstdevyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnansum":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansum( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansum( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansum( 4, x1, 2 )\n","base.strided.dnansum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansum.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansum.ndarray( 4, x, 2, 1 )\n","base.strided.dnansumkbn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumkbn( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansumkbn( 4, x1, 2 )\n","base.strided.dnansumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumkbn.ndarray( 4, x, 2, 1 )\n","base.strided.dnansumkbn2":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumkbn2( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansumkbn2( 4, x1, 2 )\n","base.strided.dnansumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumkbn2.ndarray( 4, x, 2, 1 )\n","base.strided.dnansumors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumors( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansumors( 4, x1, 2 )\n","base.strided.dnansumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumors.ndarray( 4, x, 2, 1 )\n","base.strided.dnansumpw":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumpw( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansumpw( 4, x1, 2 )\n","base.strided.dnansumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumpw.ndarray( 4, x, 2, 1 )\n","base.strided.dnanvariance":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariance( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvariance( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvariance( N, 1, x1, stride )\n","base.strided.dnanvariance.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanvariancech":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancech( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvariancech( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvariancech( N, 1, x1, stride )\n","base.strided.dnanvariancech.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvariancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanvariancepn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancepn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvariancepn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvariancepn( N, 1, x1, stride )\n","base.strided.dnanvariancepn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanvariancetk":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancetk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvariancetk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvariancetk( N, 1, x1, stride )\n","base.strided.dnanvariancetk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvariancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanvariancewd":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancewd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvariancewd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvariancewd( N, 1, x1, stride )\n","base.strided.dnanvariancewd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvariancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanvarianceyc":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvarianceyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvarianceyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvarianceyc( N, 1, x1, stride )\n","base.strided.dnanvarianceyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvarianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnrm2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dnrm2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dnrm2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnrm2( 3, x1, 2 )\n","base.strided.dnrm2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dnrm2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dnrm2.ndarray( 3, x, 2, 1 )\n","base.strided.dramp":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dramp( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dramp( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dramp( N, x1, -2, y1, 1 )\ny0\n","base.strided.dramp.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.drange":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.drange( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.drange( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.drange( 3, x1, 2 )\n","base.strided.drange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.drange.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.drange.ndarray( 3, x, 2, 1 )\n","base.strided.drev":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.drev( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.drev( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.drev( 3, x1, 2 )\nx0\n","base.strided.drev.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.drev.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.drev.ndarray( 3, x, 2, 1 )\n","base.strided.drsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.drsqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.drsqrt( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.drsqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.drsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.drsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.drsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dsapxsum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsum( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsapxsum( 3, 5.0, x1, 2 )\n","base.strided.dsapxsum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dsapxsumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsumpw( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsapxsumpw( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsapxsumpw( 3, 5.0, x1, 2 )\n","base.strided.dsapxsumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dscal":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dscal( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dscal( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dscal( 3, 5.0, x1, 2 )\nx0\n","base.strided.dscal.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dscal.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.dscal.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dsdot":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar dot = base.strided.dsdot( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\ndot = base.strided.dsdot( 3, x, 2, y, -1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\ndot = base.strided.dsdot( 3, x1, -2, y1, 1 )\n","base.strided.dsdot.ndarray":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar dot = base.strided.dsdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\ndot = base.strided.dsdot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\ndot = base.strided.dsdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.dsem":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsem( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsem( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsem( N, 1, x1, stride )\n","base.strided.dsem.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsem.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsem.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsemch":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemch( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsemch( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsemch( N, 1, x1, stride )\n","base.strided.dsemch.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsemch.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsempn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsempn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsempn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsempn( N, 1, x1, stride )\n","base.strided.dsempn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsempn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsempn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsemtk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemtk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsemtk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsemtk( N, 1, x1, stride )\n","base.strided.dsemtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsemtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsemwd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemwd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsemwd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsemwd( N, 1, x1, stride )\n","base.strided.dsemwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsemwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsemyc":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsemyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsemyc( N, 1, x1, stride )\n","base.strided.dsemyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsemyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsmean":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsmean( N, x1, stride )\n","base.strided.dsmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsmean.ndarray( N, x, 2, 1 )\n","base.strided.dsmeanors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsmeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsmeanors( N, x1, stride )\n","base.strided.dsmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsmeanors.ndarray( N, x, 2, 1 )\n","base.strided.dsmeanpn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsmeanpn( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsmeanpn( N, x1, stride )\n","base.strided.dsmeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.dsmeanpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsmeanpw( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsmeanpw( N, x1, stride )\n","base.strided.dsmeanpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsmeanpw.ndarray( N, x, 2, 1 )\n","base.strided.dsmeanwd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsmeanwd( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsmeanwd( N, x1, stride )\n","base.strided.dsmeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsmeanwd.ndarray( N, x, 2, 1 )\n","base.strided.dsnanmean":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsnanmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsnanmean( N, x1, stride )\n","base.strided.dsnanmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsnanmean.ndarray( N, x, 2, 1 )\n","base.strided.dsnanmeanors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsnanmeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsnanmeanors( N, x1, stride )\n","base.strided.dsnanmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsnanmeanors.ndarray( N, x, 2, 1 )\n","base.strided.dsnanmeanpn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsnanmeanpn( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsnanmeanpn( N, x1, stride )\n","base.strided.dsnanmeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsnanmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.dsnanmeanwd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsnanmeanwd( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsnanmeanwd( N, x1, stride )\n","base.strided.dsnanmeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsnanmeanwd.ndarray( N, x, 2, 1 )\n","base.strided.dsnannsumors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dsnannsumors( x.length, x, 1, out, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dsnannsumors( 4, x, 2, out, 1 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dsnannsumors( N, x1, 2, out, 1 )\n","base.strided.dsnannsumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dsnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dsnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dsnansum":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansum( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnansum( 4, x1, 2 )\n","base.strided.dsnansum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansum.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsnansum.ndarray( 3, x, 2, 1 )\n","base.strided.dsnansumors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansumors( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnansumors( 4, x1, 2 )\n","base.strided.dsnansumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansumors.ndarray( 4, x, 2, 1 )\n","base.strided.dsnansumpw":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansumpw( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnansumpw( 4, x1, 2 )\n","base.strided.dsnansumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansumpw.ndarray( 4, x, 2, 1 )\n","base.strided.dsort2hp":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2hp( x.length, 1, x, 1, y, 1 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2hp( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsort2hp( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.dsort2hp.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.dsort2ins":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2ins( x.length, 1, x, 1, y, 1 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2ins( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsort2ins( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.dsort2ins.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.dsort2sh":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2sh( x.length, 1, x, 1, y, 1 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2sh( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsort2sh( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.dsort2sh.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.dsorthp":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsorthp( x.length, 1, x, 1 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsorthp( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsorthp( N, 1, x1, 2 )\nx0\n","base.strided.dsorthp.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsorthp.ndarray( x.length, 1, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsorthp.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsortins":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortins( x.length, 1, x, 1 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsortins( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsortins( N, 1, x1, 2 )\nx0\n","base.strided.dsortins.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortins.ndarray( x.length, 1, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsortins.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsortsh":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortsh( x.length, 1, x, 1 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsortsh( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsortsh( N, 1, x1, 2 )\nx0\n","base.strided.dsortsh.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortsh.ndarray( x.length, 1, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsortsh.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dsqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dsqrt( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.dsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dssum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dssum( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dssum( 3, x1, 2 )\n","base.strided.dssum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssum.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dssum.ndarray(3, x, 2, 1 )\n","base.strided.dssumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dssumors( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dssumors( 3, x1, 2 )\n","base.strided.dssumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dssumors.ndarray( 3, x, 2, 1 )\n","base.strided.dssumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dssumpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dssumpw( 3, x1, 2 )\n","base.strided.dssumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dssumpw.ndarray( 3, x, 2, 1 )\n","base.strided.dstdev":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdev( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdev( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdev( N, 1, x1, stride )\n","base.strided.dstdev.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.dstdevch":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevch( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdevch( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdevch( N, 1, x1, stride )\n","base.strided.dstdevch.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.dstdevpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevpn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdevpn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdevpn( N, 1, x1, stride )\n","base.strided.dstdevpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dstdevtk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevtk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdevtk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdevtk( N, 1, x1, stride )\n","base.strided.dstdevtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.dstdevwd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevwd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdevwd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdevwd( N, 1, x1, stride )\n","base.strided.dstdevwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.dstdevyc":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdevyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdevyc( N, 1, x1, stride )\n","base.strided.dstdevyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsum":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsum( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsum( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsum( 3, x1, 2 )\n","base.strided.dsum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsum.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsum.ndarray( 3, x, 2, 1 )\n","base.strided.dsumkbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumkbn( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumkbn( 3, x1, 2 )\n","base.strided.dsumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsumkbn.ndarray( 3, x, 2, 1 )\n","base.strided.dsumkbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsumkbn2( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsumkbn2( N, x1, stride )\n","base.strided.dsumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsumkbn2.ndarray( N, x, 2, 1 )\n","base.strided.dsumors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumors( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumors( 3, x1, 2 )\n","base.strided.dsumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsumors.ndarray( 3, x, 2, 1 )\n","base.strided.dsumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumpw( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumpw( 3, x1, 2 )\n","base.strided.dsumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumpw.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsumpw.ndarray( 3, x, 2, 1 )\n","base.strided.dsvariance":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariance( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsvariance( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsvariance( N, 1, x1, stride )\n","base.strided.dsvariance.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsvariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsvariancepn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariancepn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsvariancepn( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsvariancepn( N, 1, x1, stride )\n","base.strided.dsvariancepn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsvariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dswap":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dswap( x.length, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dswap( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dswap( 3, x1, -2, y1, 1 )\ny0\n","base.strided.dswap.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dtrunc":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dtrunc( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dtrunc( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dtrunc( N, x1, -2, y1, 1 )\ny0\n","base.strided.dtrunc.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dtrunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dtrunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dtypeEnum2Str":"var out = base.strided.dtypeEnum2Str( base.strided.dtypeStr2Enum( 'float64' ) )\n","base.strided.dtypeResolveEnum":"var out = base.strided.dtypeResolveEnum( 'float64' )\nout = base.strided.dtypeResolveEnum( base.strided.dtypeStr2Enum( 'float64' ) )\n","base.strided.dtypeResolveStr":"var out = base.strided.dtypeResolveStr( 'float64' )\nout = base.strided.dtypeResolveStr( base.strided.dtypeStr2Enum( 'float64' ) )\n","base.strided.dtypeStr2Enum":"var out = base.strided.dtypeStr2Enum( 'float64' )\n","base.strided.dvariance":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariance( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvariance( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvariance( N, 1, x1, stride )\n","base.strided.dvariance.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.dvariancech":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancech( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvariancech( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvariancech( N, 1, x1, stride )\n","base.strided.dvariancech.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvariancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.dvariancepn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancepn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvariancepn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvariancepn( N, 1, x1, stride )\n","base.strided.dvariancepn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dvariancetk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancetk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvariancetk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvariancetk( N, 1, x1, stride )\n","base.strided.dvariancetk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvariancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.dvariancewd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancewd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvariancewd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvariancewd( N, 1, x1, stride )\n","base.strided.dvariancewd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvariancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.dvarianceyc":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarianceyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvarianceyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvarianceyc( N, 1, x1, stride )\n","base.strided.dvarianceyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.dvarm":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarm( x.length, 1.0/3.0, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarm( N, 1.0/3.0, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dvarm( N, 1.0/3.0, 1, x1, 2 )\n","base.strided.dvarm.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarm.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarm.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n","base.strided.dvarmpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmpn( x.length, 1.0/3.0, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarmpn( N, 1.0/3.0, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dvarmpn( N, 1.0/3.0, 1, x1, 2 )\n","base.strided.dvarmpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmpn.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarmpn.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n","base.strided.dvarmtk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmtk( x.length, 1.0/3.0, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarmtk( N, 1.0/3.0, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dvarmtk( N, 1.0/3.0, 1, x1, 2 )\n","base.strided.dvarmtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmtk.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarmtk.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n","base.strided.gapx":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar alpha = 5.0;\nbase.strided.gapx( x.length, alpha, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nalpha = 5.0;\nvar stride = 2;\nbase.strided.gapx( N, alpha, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nalpha = 5.0;\nstride = 2;\nbase.strided.gapx( N, alpha, x1, stride )\nx0\n","base.strided.gapx.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar alpha = 5.0;\nbase.strided.gapx.ndarray( x.length, alpha, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nalpha = 5.0;\nvar stride = 2;\nbase.strided.gapx.ndarray( N, alpha, x, stride, 1 )\n","base.strided.gapxsum":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsum( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gapxsum( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gapxsum( N, 5.0, x1, stride )\n","base.strided.gapxsum.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gapxsum.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.gapxsumkbn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gapxsumkbn( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gapxsumkbn( N, 5.0, x1, stride )\n","base.strided.gapxsumkbn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gapxsumkbn.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.gapxsumkbn2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn2( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gapxsumkbn2( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gapxsumkbn2( N, 5.0, x1, stride )\n","base.strided.gapxsumkbn2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gapxsumkbn2.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.gapxsumors":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumors( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gapxsumors( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gapxsumors( N, 5.0, x1, stride )\n","base.strided.gapxsumors.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gapxsumors.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.gapxsumpw":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumpw( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gapxsumpw( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gapxsumpw( N, 5.0, x1, stride )\n","base.strided.gapxsumpw.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.gasum":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nvar s = base.strided.gasum( x.length, x, 1 )\ns = base.strided.gasum( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\ns = base.strided.gasum( 3, x1, 2 )\n","base.strided.gasum.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nvar s = base.strided.gasum.ndarray( x.length, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\ns = base.strided.gasum.ndarray( 3, x, -1, x.length-1 )\n","base.strided.gasumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.gasumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gasumpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gasumpw( N, x1, stride )\n","base.strided.gasumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.gasumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.gasumpw.ndarray( N, x, 2, 1 )\n","base.strided.gaxpy":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\nbase.strided.gaxpy( x.length, 5.0, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\nbase.strided.gaxpy( 3, 5.0, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gaxpy( 3, 5.0, x1, -2, y1, 1 )\ny0\n","base.strided.gaxpy.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\nbase.strided.gaxpy.ndarray( x.length, 5.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gaxpy.ndarray( 3, 5.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcopy":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gcopy( x.length, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gcopy( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcopy( 3, x1, -2, y1, 1 )\ny0\n","base.strided.gcopy.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusum":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusum( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusum( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.gcusum( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusum.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusum.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumkbn":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumkbn( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.gcusumkbn( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumkbn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumkbn.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumkbn2":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn2( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumkbn2( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.gcusumkbn2( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumkbn2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumkbn2.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumors":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumors( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumors( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.gcusumors( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumors.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumors.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumpw":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumpw( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumpw( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.gcusumpw( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumpw.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumpw.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gdot":"var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\nvar y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\nvar out = base.strided.gdot( x.length, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\nout = base.strided.gdot( 3, x, 2, y, -1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.gdot( 3, x1, -2, y1, 1 )\n","base.strided.gdot.ndarray":"var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\nvar y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\nvar out = base.strided.gdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\nout = base.strided.gdot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nout = base.strided.gdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.gfill":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfill( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gfill( N, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gfill( N, 5.0, x1, 2 )\nx0\n","base.strided.gfill.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfill.ndarray( x.length, 5.0, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gfill.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.gfillBy":"function fill() { return 5.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfillBy( x.length, x, 1, fill )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gfillBy( N, x, 2, fill )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gfillBy( N, x1, 2, fill )\nx0\n","base.strided.gfillBy.ndarray":"function fill() { return 5.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfillBy.ndarray( x.length, x, 1, 0, fill )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gfillBy.ndarray( N, x, 2, 1, fill )\n","base.strided.gnannsumkbn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nvar out = [ 0.0, 0 ];\nbase.strided.gnannsumkbn( x.length, x, 1, out, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nout = [ 0.0, 0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnannsumkbn( N, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = [ 0.0, 0 ];\nbase.strided.gnannsumkbn( N, x1, 2, out, 1 )\n","base.strided.gnannsumkbn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nvar out = [ 0.0, 0 ];\nbase.strided.gnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nout = [ 0.0, 0 ];\nbase.strided.gnannsumkbn.ndarray( N, x, 2, 1, out, 1, 0 )\n","base.strided.gnansum":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansum( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gnansum( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gnansum( N, x1, stride )\n","base.strided.gnansum.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansum.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnansum.ndarray( N, x, 2, 1 )\n","base.strided.gnansumkbn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gnansumkbn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gnansumkbn( N, x1, stride )\n","base.strided.gnansumkbn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnansumkbn.ndarray( N, x, 2, 1 )\n","base.strided.gnansumkbn2":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gnansumkbn2( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gnansumkbn2( N, x1, stride )\n","base.strided.gnansumkbn2.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnansumkbn2.ndarray( N, x, 2, 1 )\n","base.strided.gnansumors":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gnansumors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gnansumors( N, x1, stride )\n","base.strided.gnansumors.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnansumors.ndarray( N, x, 2, 1 )\n","base.strided.gnansumpw":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumpw( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gnansumpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gnansumpw( N, x1, stride )\n","base.strided.gnansumpw.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnansumpw.ndarray( N, x, 2, 1 )\n","base.strided.gnrm2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gnrm2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gnrm2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gnrm2( 3, x1, 2 )\n","base.strided.gnrm2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gnrm2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gnrm2.ndarray( 3, x, 2, 1 )\n","base.strided.grev":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.grev( x.length, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.grev( N, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.grev( N, x1, 2 )\nx0\n","base.strided.grev.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.grev.ndarray( x.length, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.grev.ndarray( N, x, 2, 1 )\n","base.strided.gscal":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar alpha = 5.0;\nbase.strided.gscal( x.length, alpha, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gscal( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gscal( 3, 5.0, x1, 2 )\nx0\n","base.strided.gscal.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gscal.ndarray( x.length, 5.0, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.gscal.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gsort2hp":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2hp( x.length, 1, x, 1, y, 1 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2hp( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsort2hp( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.gsort2hp.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.gsort2ins":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2ins( x.length, 1, x, 1, y, 1 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2ins( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsort2ins( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.gsort2ins.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2ins.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.gsort2sh":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2sh( x.length, 1, x, 1, y, 1 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2sh( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsort2sh( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.gsort2sh.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.gsorthp":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsorthp( x.length, 1, x, 1 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsorthp( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsorthp( N, 1, x1, 2 )\nx0\n","base.strided.gsorthp.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsorthp.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsorthp.ndarray( N, 1, x, 2, 1 )\n","base.strided.gsortins":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortins( x.length, 1, x, 1 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsortins( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsortins( N, 1, x1, 2 )\nx0\n","base.strided.gsortins.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortins.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsortins.ndarray( N, 1, x, 2, 1 )\n","base.strided.gsortsh":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortsh( x.length, 1, x, 1 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsortsh( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsortsh( N, 1, x1, 2 )\nx0\n","base.strided.gsortsh.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortsh.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsortsh.ndarray( N, 1, x, 2, 1 )\n","base.strided.gsum":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsum( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gsum( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gsum( N, x1, stride )\n","base.strided.gsum.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsum.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsum.ndarray( N, x, 2, 1 )\n","base.strided.gsumkbn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gsumkbn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gsumkbn( N, x1, stride )\n","base.strided.gsumkbn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsumkbn.ndarray( N, x, 2, 1 )\n","base.strided.gsumkbn2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gsumkbn2( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gsumkbn2( N, x1, stride )\n","base.strided.gsumkbn2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsumkbn2.ndarray( N, x, 2, 1 )\n","base.strided.gsumors":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gsumors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gsumors( N, x1, stride )\n","base.strided.gsumors.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsumors.ndarray( N, x, 2, 1 )\n","base.strided.gsumpw":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumpw( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gsumpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gsumpw( N, x1, stride )\n","base.strided.gsumpw.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumpw.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsumpw.ndarray( N, x, 2, 1 )\n","base.strided.gswap":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gswap( x.length, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gswap( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gswap( 3, x1, -2, y1, 1 )\ny0\n","base.strided.gswap.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.mapBy":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.mapBy( x.length, x, 1, y, 1, base.abs, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy( 2, x, 2, y, -1, base.abs, clbk )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.mapBy( 2, x1, -2, y1, 1, base.abs, clbk )\ny0\n","base.strided.mapBy.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.mapBy.ndarray( x.length, x, 1, 0, y, 1, 0, base.abs, clbk )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.abs, clbk )\n","base.strided.mapBy2":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 1.0, 1.0, 2.0, 2.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\nbase.strided.mapBy2( x.length, x, 1, y, 1, z, 1, base.add, clbk )\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy2( 2, x, 2, y, -1, z, -1, base.add, clbk )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 1.0, 1.0, 2.0, 2.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nbase.strided.mapBy2( 2, x1, -2, y1, 1, z1, 1, base.add, clbk )\nz0\n","base.strided.mapBy2.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 1.0, 1.0, 2.0, 2.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\nbase.strided.mapBy2.ndarray( 4, x, 1, 0, y, 1, 0, z, 1, 0, base.add, clbk )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 1.0, 1.0, 2.0, 2.0 ];\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy2.ndarray( 2, x, 2, 1, y, -1, 3, z, 1, 0, base.add, clbk )\n","base.strided.max":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.max( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.max( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.max( N, x1, stride )\n","base.strided.max.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.max.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.max.ndarray( N, x, 2, 1 )\n","base.strided.maxabs":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.maxabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.maxabs( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.maxabs( N, x1, stride )\n","base.strided.maxabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.maxabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.maxabs.ndarray( N, x, 2, 1 )\n","base.strided.maxBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.maxBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.maxBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.maxBy( N, x1, 2, accessor )\n","base.strided.maxBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.maxBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.maxBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.maxsorted":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.maxsorted( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.maxsorted( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.maxsorted( N, x1, stride )\n","base.strided.maxsorted.ndarray":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.maxsorted.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.maxsorted.ndarray( N, x, 2, 1 )\n","base.strided.maxViewBufferIndex":"var idx = base.strided.maxViewBufferIndex( 3, 2, 10 )\n","base.strided.mean":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.mean( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.mean( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.mean( N, x1, stride )\n","base.strided.mean.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.mean.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mean.ndarray( N, x, 2, 1 )\n","base.strided.meankbn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meankbn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meankbn( N, x1, stride )\n","base.strided.meankbn.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meankbn.ndarray( N, x, 2, 1 )\n","base.strided.meankbn2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meankbn2( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meankbn2( N, x1, stride )\n","base.strided.meankbn2.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meankbn2.ndarray( N, x, 2, 1 )\n","base.strided.meanors":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meanors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meanors( N, x1, stride )\n","base.strided.meanors.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meanors.ndarray( N, x, 2, 1 )\n","base.strided.meanpn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanpn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meanpn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meanpn( N, x1, stride )\n","base.strided.meanpn.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanpn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meanpn.ndarray( N, x, 2, 1 )\n","base.strided.meanpw":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanpw( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meanpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meanpw( N, x1, stride )\n","base.strided.meanpw.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanpw.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meanpw.ndarray( N, x, 2, 1 )\n","base.strided.meanwd":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanwd( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meanwd( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meanwd( N, x1, stride )\n","base.strided.meanwd.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanwd.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meanwd.ndarray( N, x, 2, 1 )\n","base.strided.mediansorted":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.mediansorted( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mediansorted( N, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.mediansorted( N, x1, 2 )\n","base.strided.mediansorted.ndarray":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.mediansorted.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mediansorted.ndarray( N, x, 2, 1 )\n","base.strided.metaDataProps":"var meta = { 'nargs': 7, 'nin': 1, 'nout': 1 };\nvar dt = [ 'float64', 'float64' ];\nvar obj = {};\nbase.strided.metaDataProps( meta, dt, obj, false );\nobj.nargs\nobj.nin\nobj.nout\nobj.types\n","base.strided.min":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.min( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.min( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.min( N, x1, stride )\n","base.strided.min.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.min.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.min.ndarray( N, x, 2, 1 )\n","base.strided.minabs":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.minabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.minabs( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.minabs( N, x1, stride )\n","base.strided.minabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.minabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.minabs.ndarray( N, x, 2, 1 )\n","base.strided.minBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.minBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.minBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.minBy( N, x1, 2, accessor )\n","base.strided.minBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.minBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.minBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.minsorted":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.minsorted( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.minsorted( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.minsorted( N, x1, stride )\n","base.strided.minsorted.ndarray":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.minsorted.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.minsorted.ndarray( N, x, 2, 1 )\n","base.strided.minViewBufferIndex":"var idx = base.strided.minViewBufferIndex( 3, -2, 10 )\n","base.strided.mskmax":"var x = [ 1.0, -2.0, 4.0, 2.0 ];\nvar mask = [ 0, 0, 1, 0 ];\nbase.strided.mskmax( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskmax( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.mskmax( N, x1, 2, mask1, 2 )\n","base.strided.mskmax.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0 ];\nvar mask = [ 0, 0, 0, 1 ];\nbase.strided.mskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.mskmin":"var x = [ 1.0, -2.0, -4.0, 2.0 ];\nvar mask = [ 0, 0, 1, 0 ];\nbase.strided.mskmin( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskmin( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.mskmin( N, x1, 2, mask1, 2 )\n","base.strided.mskmin.ndarray":"var x = [ 1.0, -2.0, 2.0, -4.0 ];\nvar mask = [ 0, 0, 0, 1 ];\nbase.strided.mskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.mskrange":"var x = [ 1.0, -2.0, 4.0, 2.0 ];\nvar mask = [ 0, 0, 1, 0 ];\nbase.strided.mskrange( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskrange( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.mskrange( N, x1, 2, mask1, 2 )\n","base.strided.mskrange.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0 ];\nvar mask = [ 0, 0, 0, 1 ];\nbase.strided.mskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.mskunary":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nbase.strided.mskunary( [ x, m, y ], shape, strides, base.abs );\ny\n","base.strided.mskunary.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nvar offsets = [ 0, 0, 0 ];\nbase.strided.mskunary.ndarray( [ x, m, y ], shape, strides, offsets, base.abs );\ny\n","base.strided.mskunaryDtypeSignatures":"var dt = strided.dataTypes();\nvar out = base.strided.mskunaryDtypeSignatures( dt, dt )\n","base.strided.mskunarySignatureCallbacks":"var dt = strided.dataTypes();\nvar sigs = base.strided.mskunaryDtypeSignatures( dt, dt );\nvar t = {\n 'default': base.identity,\n 'complex64': base.cidentityf,\n 'complex128': base.cidentity\n };\nvar out = base.strided.mskunarySignatureCallbacks( t, sigs )\n","base.strided.nanmax":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmax( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmax( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmax( N, x1, stride )\n","base.strided.nanmax.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmax.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmax.ndarray( N, x, 2, 1 )\n","base.strided.nanmaxabs":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmaxabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmaxabs( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmaxabs( N, x1, stride )\n","base.strided.nanmaxabs.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmaxabs.ndarray( N, x, 2, 1 )\n","base.strided.nanmaxBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanmaxBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmaxBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanmaxBy( N, x1, 2, accessor )\n","base.strided.nanmaxBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanmaxBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmaxBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.nanmean":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmean( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmean( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmean( N, x1, stride )\n","base.strided.nanmean.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmean.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmean.ndarray( N, x, 2, 1 )\n","base.strided.nanmeanors":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmeanors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmeanors( N, x1, stride )\n","base.strided.nanmeanors.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmeanors.ndarray( N, x, 2, 1 )\n","base.strided.nanmeanpn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanpn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmeanpn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmeanpn( N, x1, stride )\n","base.strided.nanmeanpn.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.nanmeanwd":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanwd( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmeanwd( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmeanwd( N, x1, stride )\n","base.strided.nanmeanwd.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmeanwd.ndarray( N, x, 2, 1 )\n","base.strided.nanmin":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmin( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmin( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmin( N, x1, stride )\n","base.strided.nanmin.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmin.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmin.ndarray( N, x, 2, 1 )\n","base.strided.nanminabs":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanminabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanminabs( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanminabs( N, x1, stride )\n","base.strided.nanminabs.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanminabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanminabs.ndarray( N, x, 2, 1 )\n","base.strided.nanminBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanminBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, NaN, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanminBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanminBy( N, x1, 2, accessor )\n","base.strided.nanminBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanminBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanminBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.nanmskmax":"var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\nvar mask = [ 0, 0, 1, 0, 0 ];\nbase.strided.nanmskmax( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskmax( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanmskmax( N, x1, 2, mask1, 2 )\n","base.strided.nanmskmax.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\nvar mask = [ 0, 0, 0, 1, 0 ];\nbase.strided.nanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.nanmskmin":"var x = [ 1.0, -2.0, -4.0, 2.0, NaN ];\nvar mask = [ 0, 0, 1, 0, 0 ];\nbase.strided.nanmskmin( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskmin( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanmskmin( N, x1, 2, mask1, 2 )\n","base.strided.nanmskmin.ndarray":"var x = [ 1.0, -2.0, 2.0, -4.0, NaN ];\nvar mask = [ 0, 0, 0, 1, 0 ];\nbase.strided.nanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.nanmskrange":"var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\nvar mask = [ 0, 0, 1, 0, 0 ];\nbase.strided.nanmskrange( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskrange( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanmskrange( N, x1, 2, mask1, 2 )\n","base.strided.nanmskrange.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\nvar mask = [ 0, 0, 0, 1, 0 ];\nbase.strided.nanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.nanrange":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanrange( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanrange( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanrange( N, x1, stride )\n","base.strided.nanrange.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanrange.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanrange.ndarray( N, x, 2, 1 )\n","base.strided.nanrangeBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanrangeBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0, 1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanrangeBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanrangeBy( N, x1, 2, accessor )\n","base.strided.nanrangeBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanrangeBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanrangeBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.nanstdev":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdev( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdev( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdev( N, 1, x1, 2 )\n","base.strided.nanstdev.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanstdevch":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevch( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevch( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdevch( N, 1, x1, 2 )\n","base.strided.nanstdevch.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanstdevpn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevpn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevpn( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdevpn( N, 1, x1, 2 )\n","base.strided.nanstdevpn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanstdevtk":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevtk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevtk( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdevtk( N, 1, x1, 2 )\n","base.strided.nanstdevtk.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanstdevwd":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevwd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevwd( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdevwd( N, 1, x1, 2 )\n","base.strided.nanstdevwd.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanstdevyc":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevyc( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevyc( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdevyc( N, 1, x1, 2 )\n","base.strided.nanstdevyc.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvariance":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariance( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvariance( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvariance( N, 1, x1, stride )\n","base.strided.nanvariance.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvariancech":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancech( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvariancech( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvariancech( N, 1, x1, stride )\n","base.strided.nanvariancech.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvariancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvariancepn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancepn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvariancepn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvariancepn( N, 1, x1, stride )\n","base.strided.nanvariancepn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvariancetk":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancetk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvariancetk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvariancetk( N, 1, x1, stride )\n","base.strided.nanvariancetk.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvariancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvariancewd":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancewd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvariancewd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvariancewd( N, 1, x1, stride )\n","base.strided.nanvariancewd.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvariancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvarianceyc":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvarianceyc( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvarianceyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvarianceyc( N, 1, x1, stride )\n","base.strided.nanvarianceyc.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvarianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.nullary":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1 ];\nvar fcn = constantFunction( 3.0 );\nbase.strided.nullary( [ x ], shape, strides, fcn );\nx\n","base.strided.nullary.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1 ];\nvar offsets = [ 0 ];\nvar fcn = constantFunction( 3.0 );\nbase.strided.nullary.ndarray( [ x ], shape, strides, offsets, fcn );\nx\n","base.strided.offsetView":"var x = new Float64Array( 10 );\nvar out = base.strided.offsetView( x, 0 )\nvar bool = ( out.buffer === x.buffer )\n","base.strided.quaternary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1 ];\nfunction f( x, y, z, w ) { return x + y + z + w; };\nbase.strided.quaternary( [ x, y, z, w, u ], shape, strides, f );\nu\n","base.strided.quaternary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1 ];\nvar offsets = [ 0, 0, 0, 0, 0 ];\nfunction f( x, y, z, w ) { return x + y + z + w; };\nbase.strided.quaternary.ndarray( [ x, y, z, w, u ], shape, strides, offsets, f );\nu\n","base.strided.quinary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1, 1 ];\nfunction f( x, y, z, w, u ) { return x + y + z + w + u; };\nbase.strided.quinary( [ x, y, z, w, u, v ], shape, strides, f );\nv\n","base.strided.quinary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1, 1 ];\nvar offsets = [ 0, 0, 0, 0, 0, 0 ];\nfunction f( x, y, z, w, u ) { return x + y + z + w + u; };\nbase.strided.quinary.ndarray( [ x, y, z, w, u, v ], shape, strides, offsets, f );\nv\n","base.strided.range":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.range( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.range( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.range( N, x1, stride )\n","base.strided.range.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.range.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.range.ndarray( N, x, 2, 1 )\n","base.strided.rangeBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.rangeBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.rangeBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.rangeBy( N, x1, 2, accessor )\n","base.strided.rangeBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.rangeBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.rangeBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.reinterpretComplex":"var x = new Complex128Array( 10 );\nvar out = base.strided.reinterpretComplex( x, 0 )\nvar bool = ( out.buffer === x.buffer )\nx = new Complex64Array( 10 );\nout = base.strided.reinterpretComplex( x, 0 )\nbool = ( out.buffer === x.buffer )\n","base.strided.reinterpretComplex64":"var x = new Complex64Array( 10 );\nvar out = base.strided.reinterpretComplex64( x, 0 )\nvar bool = ( out.buffer === x.buffer )\n","base.strided.reinterpretComplex128":"var x = new Complex128Array( 10 );\nvar out = base.strided.reinterpretComplex128( x, 0 )\nvar bool = ( out.buffer === x.buffer )\n","base.strided.sabs":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sabs( N, x1, -2, y1, 1 )\ny0\n","base.strided.sabs.ndarray":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sabs2":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs2( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs2( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sabs2( N, x1, -2, y1, 1 )\ny0\n","base.strided.sabs2.ndarray":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sapx":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sapx( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sapx( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapx( 3, 5.0, x1, 2 )\nx0\n","base.strided.sapx.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sapx.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.sapx.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsum( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsum( 3, 5.0, x1, 2 )\n","base.strided.sapxsum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsumkbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsumkbn( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsumkbn( 3, 5.0, x1, 2 )\n","base.strided.sapxsumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsumkbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn2( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsumkbn2( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsumkbn2( 3, 5.0, x1, 2 )\n","base.strided.sapxsumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumors( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sapxsumors( N, 5.0, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sapxsumors( N, 5.0, x1, stride )\n","base.strided.sapxsumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sapxsumors.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.sapxsumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumpw( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar stride = 2;\nbase.strided.sapxsumpw( 3, 5.0, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.sapxsumpw( 3, 5.0, x1, stride )\n","base.strided.sapxsumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sasum":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.sasum( x.length, x, 1 )\ns = base.strided.sasum( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\ns = base.strided.sasum( 3, x1, 2 )\n","base.strided.sasum.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.sasum.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\ns = base.strided.sasum.ndarray( 3, x, -1, x.length-1 )\n","base.strided.sasumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sasumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sasumpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sasumpw( 3, x1, 2 )\n","base.strided.sasumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sasumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sasumpw.ndarray( 3, x, 2, 1 )\n","base.strided.saxpy":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.saxpy( x.length, alpha, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nbase.strided.saxpy( 3, alpha, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.saxpy( 3, 5.0, x1, -2, y1, 1 )\ny0\n","base.strided.saxpy.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.saxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.saxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scbrt":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.scbrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.scbrt( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.scbrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.scbrt.ndarray":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.scbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.scbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sceil":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sceil( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sceil( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sceil( N, x1, -2, y1, 1 )\ny0\n","base.strided.sceil.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scopy":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.scopy( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.scopy( 3, x, -2, y, 1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scopy( 3, x1, -2, y1, 1 )\ny0\n","base.strided.scopy.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.scopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scumax":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumax( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumax( 3, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scumax( 3, x1, 2, y1, 1 )\ny0\n","base.strided.scumax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scumaxabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumaxabs( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scumaxabs( N, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scumaxabs( N, x1, 2, y1, 1 )\ny0\n","base.strided.scumaxabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scumin":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumin( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scumin( N, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scumin( N, x1, 2, y1, 1 )\ny0\n","base.strided.scumin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scuminabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scuminabs( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scuminabs( N, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scuminabs( N, x1, 2, y1, 1 )\ny0\n","base.strided.scuminabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusum( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusum( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusum( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumkbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scusumkbn( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumkbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn2( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn2( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scusumkbn2( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumors( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumors( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusumors( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumpw( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumpw( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusumpw( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sdeg2rad":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sdeg2rad( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sdeg2rad( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sdeg2rad( N, x1, -2, y1, 1 )\ny0\n","base.strided.sdeg2rad.ndarray":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sdeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sdot":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdot( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdot( 3, x, 2, y, -1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.sdot( 3, x1, -2, y1, 1 )\n","base.strided.sdot.ndarray":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nout = base.strided.sdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.sdsapxsum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsum( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sdsapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsapxsum( 3, 5.0, x1, 2 )\n","base.strided.sdsapxsum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sdsapxsumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsumpw( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sdsapxsumpw( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsapxsumpw( 3, 5.0, x1, 2 )\n","base.strided.sdsapxsumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sdsdot":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdsdot( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdsdot( 3, 0.0, x, 2, y, -1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.sdsdot( 3, 0.0, x1, -2, y1, 1 )\n","base.strided.sdsdot.ndarray":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdsdot.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdsdot.ndarray( 3, 0.0, x, 2, 0, y, 2, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nout = base.strided.sdsdot.ndarray( 3, 0.0, x, -2, x.length-1, y, 1, 3 )\n","base.strided.sdsmean":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsmean( N, x1, stride )\n","base.strided.sdsmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsmean.ndarray( N, x, 2, 1 )\n","base.strided.sdsmeanors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsmeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsmeanors( N, x1, stride )\n","base.strided.sdsmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsmeanors.ndarray( N, x, 2, 1 )\n","base.strided.sdsnanmean":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsnanmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsnanmean( N, x1, stride )\n","base.strided.sdsnanmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsnanmean.ndarray( N, x, 2, 1 )\n","base.strided.sdsnanmeanors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsnanmeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsnanmeanors( N, x1, stride )\n","base.strided.sdsnanmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsnanmeanors.ndarray( N, x, 2, 1 )\n","base.strided.sdsnansum":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar stride = 2;\nbase.strided.sdsnansum( 4, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.sdsnansum( 4, x1, stride )\n","base.strided.sdsnansum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansum.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.sdsnansum.ndarray( 4, x, 2, 1 )\n","base.strided.sdsnansumpw":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.sdsnansumpw( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsnansumpw( 4, x1, 2 )\n","base.strided.sdsnansumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.sdsnansumpw.ndarray( 4, x, 2, 1 )\n","base.strided.sdssum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar stride = 2;\nbase.strided.sdssum( 3, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.sdssum( 3, x1, stride )\n","base.strided.sdssum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssum.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdssum.ndarray( 3, x, 2, 1 )\n","base.strided.sdssumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar stride = 2;\nbase.strided.sdssumpw( 3, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.sdssumpw( 3, x1, stride )\n","base.strided.sdssumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdssumpw.ndarray( 3, x, 2, 1 )\n","base.strided.sfill":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sfill( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sfill( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sfill( 3, 5.0, x1, 2 )\nx0\n","base.strided.sfill.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sfill.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.sfill.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sfloor":"var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sfloor( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sfloor( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sfloor( N, x1, -2, y1, 1 )\ny0\n","base.strided.sfloor.ndarray":"var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sinv":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sinv( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sinv( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sinv( N, x1, -2, y1, 1 )\ny0\n","base.strided.sinv.ndarray":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.smap":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap( x.length, x, 1, y, 1, base.identityf )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap( 2, x, 2, y, -1, base.identityf )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smap( 2, x1, -2, y1, 1, base.identityf )\ny0\n","base.strided.smap.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identityf )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identityf )\n","base.strided.smap2":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2( x.length, x, 1, y, 1, z, 1, base.addf )\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2( 2, x, 2, y, -1, z, 1, base.addf )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nbase.strided.smap2( 2, x1, -2, y1, 1, z1, 1, base.addf )\nz0\n","base.strided.smap2.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.addf )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.addf )\n","base.strided.smax":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smax( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smax( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smax( 3, x1, 2 )\n","base.strided.smax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smax.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smax.ndarray( N, x, 2, 1 )\n","base.strided.smaxabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smaxabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smaxabs( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smaxabs( 3, x1, 2 )\n","base.strided.smaxabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smaxabs.ndarray( 3, x, 2, 1 )\n","base.strided.smaxabssorted":"var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.smaxabssorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smaxabssorted( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smaxabssorted( N, x1, stride )\n","base.strided.smaxabssorted.ndarray":"var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smaxabssorted.ndarray( N, x, 2, 1 )\n","base.strided.smaxsorted":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smaxsorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smaxsorted( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smaxsorted( N, x1, stride )\n","base.strided.smaxsorted.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smaxsorted.ndarray( N, x, 2, 1 )\n","base.strided.smean":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smean( N, x1, stride )\n","base.strided.smean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smean.ndarray( N, x, 2, 1 )\n","base.strided.smeankbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeankbn( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeankbn( N, x1, stride )\n","base.strided.smeankbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeankbn.ndarray( N, x, 2, 1 )\n","base.strided.smeankbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeankbn2( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeankbn2( N, x1, stride )\n","base.strided.smeankbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeankbn2.ndarray( N, x, 2, 1 )\n","base.strided.smeanli":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanli( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanli( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanli( N, x1, stride )\n","base.strided.smeanli.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanli.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanli.ndarray( N, x, 2, 1 )\n","base.strided.smeanlipw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanlipw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanlipw( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanlipw( N, x1, stride )\n","base.strided.smeanlipw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanlipw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanlipw.ndarray( N, x, 2, 1 )\n","base.strided.smeanors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanors( N, x1, stride )\n","base.strided.smeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanors.ndarray( N, x, 2, 1 )\n","base.strided.smeanpn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanpn( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanpn( N, x1, stride )\n","base.strided.smeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanpn.ndarray( N, x, 2, 1 )\n","base.strided.smeanpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanpw( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanpw( N, x1, stride )\n","base.strided.smeanpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanpw.ndarray( N, x, 2, 1 )\n","base.strided.smeanwd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanwd( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanwd( N, x1, stride )\n","base.strided.smeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanwd.ndarray( N, x, 2, 1 )\n","base.strided.smediansorted":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smediansorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smediansorted( N, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.smediansorted( N, x1, 2 )\n","base.strided.smediansorted.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smediansorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smediansorted.ndarray( N, x, 2, 1 )\n","base.strided.smidrange":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smidrange( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smidrange( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smidrange( 3, x1, 2 )\n","base.strided.smidrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smidrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smidrange.ndarray( 3, x, 2, 1 )\n","base.strided.smin":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smin( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smin( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smin( 3, x1, 2 )\n","base.strided.smin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smin.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smin.ndarray( 3, x, 2, 1 )\n","base.strided.sminabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sminabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sminabs( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sminabs( 3, x1, 2 )\n","base.strided.sminabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sminabs.ndarray( 3, x, 2, 1 )\n","base.strided.sminsorted":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.sminsorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sminsorted( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sminsorted( N, x1, stride )\n","base.strided.sminsorted.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.sminsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sminsorted.ndarray( N, x, 2, 1 )\n","base.strided.smskabs":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskabs( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskabs.ndarray":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskabs2":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskabs2( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskabs2.ndarray":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskcbrt":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskcbrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskcbrt.ndarray":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskceil":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskceil( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskceil.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskdeg2rad":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskdeg2rad.ndarray":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskfloor":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskfloor( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskfloor.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskinv":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskinv( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskinv.ndarray":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskmap":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap( x.length, x, 1, m, 1, y, 1, base.identity )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap( 2, x, 2, m, 2, y, -1, base.identity )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\ny0\n","base.strided.smskmap.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n","base.strided.smskmap2":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.addf )\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.addf )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.addf )\nz0\n","base.strided.smskmap2.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.addf )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.addf )\n","base.strided.smskmax":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmax( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smskmax( N, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.smskmax( N, x1, 2, mask1, 2 )\n","base.strided.smskmax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.smskmin":"var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmin( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smskmin( N, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.smskmin( N, x1, 2, mask1, 2 )\n","base.strided.smskmin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.smskramp":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskramp( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskramp.ndarray":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskrange":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskrange( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smskrange( N, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.smskrange( N, x1, 2, mask1, 2 )\n","base.strided.smskrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.smskrsqrt":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskrsqrt.ndarray":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smsksqrt":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smsksqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smsksqrt.ndarray":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smsktrunc":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smsktrunc( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smsktrunc.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.snanmax":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmax( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanmax( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmax( 3, x1, 2 )\n","base.strided.snanmax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanmax.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanmax.ndarray( 3, x, 2, 1 )\n","base.strided.snanmaxabs":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmaxabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanmaxabs( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmaxabs( 3, x1, 2 )\n","base.strided.snanmaxabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanmaxabs.ndarray( 3, x, 2, 1 )\n","base.strided.snanmean":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanmean( N, x1, stride )\n","base.strided.snanmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmean.ndarray( N, x, 2, 1 )\n","base.strided.snanmeanors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanmeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanmeanors( N, x1, stride )\n","base.strided.snanmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmeanors.ndarray( N, x, 2, 1 )\n","base.strided.snanmeanpn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanmeanpn( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanmeanpn( N, x1, stride )\n","base.strided.snanmeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.snanmeanwd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanmeanwd( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanmeanwd( N, x1, stride )\n","base.strided.snanmeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmeanwd.ndarray( N, x, 2, 1 )\n","base.strided.snanmin":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmin( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanmin( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmin( 3, x1, 2 )\n","base.strided.snanmin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanmin.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanmin.ndarray( 3, x, 2, 1 )\n","base.strided.snanminabs":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanminabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanminabs( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanminabs( 3, x1, 2 )\n","base.strided.snanminabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanminabs.ndarray( 3, x, 2, 1 )\n","base.strided.snanmskmax":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.snanmskmax( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskmax( N, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanmskmax( N, x1, 2, mask1, 2 )\n","base.strided.snanmskmax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.snanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.snanmskmin":"var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.snanmskmin( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskmin( N, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanmskmin( N, x1, 2, mask1, 2 )\n","base.strided.snanmskmin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.snanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.snanmskrange":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.snanmskrange( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskrange( N, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanmskrange( N, x1, 2, mask1, 2 )\n","base.strided.snanmskrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.snanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.snanrange":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanrange( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanrange( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanrange( 3, x1, 2 )\n","base.strided.snanrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanrange.ndarray( 3, x, 2, 1 )\n","base.strided.snanstdev":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdev( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdev( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdev( N, 1, x1, stride )\n","base.strided.snanstdev.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevch":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevch( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevch( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevch( N, 1, x1, stride )\n","base.strided.snanstdevch.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevpn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevpn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevpn( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevpn( N, 1, x1, stride )\n","base.strided.snanstdevpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevtk":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevtk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevtk( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevtk( N, 1, x1, stride )\n","base.strided.snanstdevtk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevwd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevwd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevwd( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevwd( N, 1, x1, stride )\n","base.strided.snanstdevwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevyc":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevyc( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevyc( N, 1, x1, stride )\n","base.strided.snanstdevyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.snansum":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.snansum( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snansum( 4, x1, 2 )\n","base.strided.snansum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansum.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansum.ndarray( 4, x, 2, 1 )\n","base.strided.snansumkbn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar stride = 2;\nbase.strided.snansumkbn( 4, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.snansumkbn( 4, x1, stride )\n","base.strided.snansumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansumkbn.ndarray( 4, x, 2, 1 )\n","base.strided.snansumkbn2":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar stride = 2;\nbase.strided.snansumkbn2( 4, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.snansumkbn2( 4, x1, stride )\n","base.strided.snansumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansumkbn2.ndarray( 4, x, 2, 1 )\n","base.strided.snansumors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar stride = 2;\nbase.strided.snansumors( 4, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.snansumors( 4, x1, stride )\n","base.strided.snansumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansumors.ndarray( 4, x, 2, 1 )\n","base.strided.snansumpw":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.snansumpw( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snansumpw( 4, x1, 2 )\n","base.strided.snansumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansumpw.ndarray( 4, x, 2, 1 )\n","base.strided.snanvariance":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariance( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariance( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariance( N, 1, x1, 2 )\n","base.strided.snanvariance.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancech":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancech( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancech( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancech( N, 1, x1, 2 )\n","base.strided.snanvariancech.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancepn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancepn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancepn( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancepn( N, 1, x1, 2 )\n","base.strided.snanvariancepn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancetk":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancetk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancetk( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancetk( N, 1, x1, 2 )\n","base.strided.snanvariancetk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancewd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancewd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancewd( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancewd( N, 1, x1, 2 )\n","base.strided.snanvariancewd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvarianceyc":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvarianceyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvarianceyc( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvarianceyc( N, 1, x1, 2 )\n","base.strided.snanvarianceyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvarianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.snrm2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.snrm2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.snrm2( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snrm2( 3, x1, 2 )\n","base.strided.snrm2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.snrm2.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.snrm2.ndarray( 3, x, 2, 1 )\n","base.strided.sramp":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sramp( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sramp( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sramp( N, x1, -2, y1, 1 )\ny0\n","base.strided.sramp.ndarray":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.srange":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.srange( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.srange( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.srange( 3, x1, 2 )\n","base.strided.srange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.srange.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.srange.ndarray( 3, x, 2, 1 )\n","base.strided.srev":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.srev( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.srev( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.srev( 3, x1, 2 )\nx0\n","base.strided.srev.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.srev.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.srev.ndarray( 3, x, 2, 1 )\n","base.strided.srsqrt":"var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.srsqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.srsqrt( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.srsqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.srsqrt.ndarray":"var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.srsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.srsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sscal":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sscal( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sscal( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sscal( 3, 5.0, x1, 2 )\nx0\n","base.strided.sscal.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sscal.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.sscal.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.ssort2hp":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2hp( x.length, 1, x, 1, y, 1 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2hp( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssort2hp( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.ssort2hp.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2hp.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.ssort2ins":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2ins( x.length, 1, x, 1, y, 1 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2ins( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssort2ins( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.ssort2ins.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.ssort2sh":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2sh( x.length, 1, x, 1, y, 1 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2sh( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssort2sh( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.ssort2sh.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2sh.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.ssorthp":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssorthp( x.length, 1, x, 1 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssorthp( 2, -1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssorthp( 2, 1, x1, 2 )\nx0\n","base.strided.ssorthp.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssorthp.ndarray( x.length, 1, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssorthp.ndarray( 2, 1, x, 2, 1 )\n","base.strided.ssortins":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortins( x.length, 1, x, 1 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortins( 2, -1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssortins( 2, 1, x1, 2 )\nx0\n","base.strided.ssortins.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortins.ndarray( x.length, 1, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortins.ndarray( 2, 1, x, 2, 1 )\n","base.strided.ssortsh":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortsh( x.length, 1, x, 1 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortsh( 2, -1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssortsh( 2, 1, x1, 2 )\nx0\n","base.strided.ssortsh.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortsh.ndarray( x.length, 1, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortsh.ndarray( 2, 1, x, 2, 1 )\n","base.strided.ssqrt":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ssqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ssqrt( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.ssqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.ssqrt.ndarray":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ssqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ssqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sstdev":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdev( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdev( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdev( N, 1, x1, stride )\n","base.strided.sstdev.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.sstdevch":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevch( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdevch( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdevch( N, 1, x1, stride )\n","base.strided.sstdevch.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.sstdevpn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevpn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdevpn( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdevpn( N, 1, x1, stride )\n","base.strided.sstdevpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.sstdevtk":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevtk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdevtk( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdevtk( N, 1, x1, stride )\n","base.strided.sstdevtk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.sstdevwd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevwd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdevwd( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdevwd( N, 1, x1, stride )\n","base.strided.sstdevwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.sstdevyc":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdevyc( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdevyc( N, 1, x1, stride )\n","base.strided.sstdevyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.ssum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssum( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssum( 3, x1, 2 )\n","base.strided.ssum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssum.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssum.ndarray( 3, x, 2, 1 )\n","base.strided.ssumkbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumkbn( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumkbn( 3, x1, 2 )\n","base.strided.ssumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumkbn.ndarray( 3, x, 2, 1 )\n","base.strided.ssumkbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumkbn2( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumkbn2( 3, x1, 2 )\n","base.strided.ssumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn2.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumkbn2.ndarray( 3, x, 2, 1 )\n","base.strided.ssumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumors( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumors( 3, x1, 2 )\n","base.strided.ssumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumors.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumors.ndarray( 3, x, 2, 1 )\n","base.strided.ssumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumpw( 3, x1, 2 )\n","base.strided.ssumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumpw.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumpw.ndarray( 3, x, 2, 1 )\n","base.strided.sswap":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.sswap( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.sswap( 3, x, -2, y, 1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.sswap( 3, x1, -2, y1, 1 )\ny0\n","base.strided.sswap.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.sswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.sswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.stdev":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdev( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdev( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdev( N, 1, x1, stride )\n","base.strided.stdev.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.stdevch":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevch( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdevch( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdevch( N, 1, x1, stride )\n","base.strided.stdevch.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.stdevpn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevpn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdevpn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdevpn( N, 1, x1, stride )\n","base.strided.stdevpn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.stdevtk":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevtk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdevtk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdevtk( N, 1, x1, stride )\n","base.strided.stdevtk.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.stdevwd":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevwd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdevwd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdevwd( N, 1, x1, stride )\n","base.strided.stdevwd.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.stdevyc":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevyc( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdevyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdevyc( N, 1, x1, stride )\n","base.strided.stdevyc.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.strunc":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.strunc( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.strunc( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.strunc( N, x1, -2, y1, 1 )\ny0\n","base.strided.strunc.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.strunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.strunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.svariance":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariance( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svariance( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svariance( N, 1, x1, stride )\n","base.strided.svariance.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.svariancech":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancech( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svariancech( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svariancech( N, 1, x1, stride )\n","base.strided.svariancech.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svariancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.svariancepn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancepn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svariancepn( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svariancepn( N, 1, x1, stride )\n","base.strided.svariancepn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.svariancetk":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancetk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svariancetk( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svariancetk( N, 1, x1, stride )\n","base.strided.svariancetk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svariancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.svariancewd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancewd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svariancewd( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svariancewd( N, 1, x1, stride )\n","base.strided.svariancewd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svariancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.svarianceyc":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svarianceyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svarianceyc( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svarianceyc( N, 1, x1, stride )\n","base.strided.svarianceyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svarianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.ternary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1 ];\nfunction f( x, y, z ) { return x + y + z; };\nbase.strided.ternary( [ x, y, z, w ], shape, strides, f );\nw\n","base.strided.ternary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1 ];\nvar offsets = [ 0, 0, 0, 0 ];\nfunction f( x, y, z ) { return x + y + z; };\nbase.strided.ternary.ndarray( [ x, y, z, w ], shape, strides, offsets, f );\nw\n","base.strided.unary":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1 ];\nbase.strided.unary( [ x, y ], shape, strides, base.abs );\ny\n","base.strided.unary.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1 ];\nvar offsets = [ 0, 0 ];\nbase.strided.unary.ndarray( [ x, y ], shape, strides, offsets, base.abs );\ny\n","base.strided.unaryBy":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nvar sh = [ x.length ];\nvar st = [ 1, 1 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\ny\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nsh = [ 2 ];\nst = [ 2, -1 ];\nbase.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nsh = [ 2 ];\nst = [ -2, 1 ];\nbase.strided.unaryBy( [ x1, y1 ], sh, st, base.abs, clbk );\ny1\ny0\n","base.strided.unaryBy.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nvar sh = [ x.length ];\nvar st = [ 1, 1 ];\nvar o = [ 0, 0 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nsh = [ 2 ];\nst = [ 2, -1 ];\no = [ 1, y.length-1 ];\nbase.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\ny\n","base.strided.unaryDtypeSignatures":"var dt = strided.dataTypes();\nvar out = base.strided.unaryDtypeSignatures( dt, dt )\n","base.strided.unarySignatureCallbacks":"var dt = strided.dataTypes();\nvar sigs = base.strided.unaryDtypeSignatures( dt, dt );\nvar t = {\n 'default': base.identity,\n 'complex64': base.cidentityf,\n 'complex128': base.cidentity\n };\nvar out = base.strided.unarySignatureCallbacks( t, sigs )\n","base.strided.variance":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variance( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.variance( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.variance( N, 1, x1, stride )\n","base.strided.variance.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variance.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.variance.ndarray( N, 1, x, 2, 1 )\n","base.strided.variancech":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancech( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.variancech( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.variancech( N, 1, x1, stride )\n","base.strided.variancech.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.variancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.variancepn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancepn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.variancepn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.variancepn( N, 1, x1, stride )\n","base.strided.variancepn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.variancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.variancetk":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancetk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.variancetk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.variancetk( N, 1, x1, stride )\n","base.strided.variancetk.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.variancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.variancewd":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancewd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.variancewd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.variancewd( N, 1, x1, stride )\n","base.strided.variancewd.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.variancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.varianceyc":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.varianceyc( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.varianceyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.varianceyc( N, 1, x1, stride )\n","base.strided.varianceyc.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.varianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.varianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.zmap":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex128Array( xbuf );\nvar y = new Complex128Array( x.length );\nbase.strided.zmap( x.length, x, 1, y, 1, base.cidentity );\nvar v = y.get( 0 )\nvar re = real( v )\nvar im = imag( v )\ny = new Complex128Array( x.length );\nbase.strided.zmap( 2, x, 2, y, -1, base.cidentity );\nv = y.get( 0 )\nre = real( v )\nim = imag( v )\nvar x0 = new Complex128Array( xbuf );\nvar y0 = new Complex128Array( x0.length );\nvar x1 = new Complex128Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex128Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.zmap( 2, x1, -2, y1, 1, base.cidentity );\nv = y1.get( 0 )\nre = real( v )\nim = imag( v )\n","base.strided.zmap.ndarray":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex128Array( xbuf );\nvar y = new Complex128Array( x.length );\nbase.strided.zmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentity );\nvar v = y.get( 0 )\nvar re = real( v )\nvar im = imag( v )\nx = new Complex128Array( xbuf );\ny = new Complex128Array( x.length );\nbase.strided.zmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentity );\nv = y.get( y.length-1 )\nre = real( v )\nim = imag( v )\n","base.str2multislice":"var s = new base.str2multislice( 'MultiSlice(null,null,null)' );\ns.data\ns = new base.str2multislice( 'MultiSlice(10,Slice(0,10,1),null)' );\ns.data\n","base.str2slice":"var s = new base.str2slice( 'Slice(1,10,1)' );\ns.start\ns.stop\ns.step\ns = new base.str2slice( 'Slice(2,5,2)' );\ns.start\ns.stop\ns.step\n","base.sub":"var v = base.sub( -1.0, 5.0 )\nv = base.sub( 2.0, 5.0 )\nv = base.sub( 0.0, 5.0 )\nv = base.sub( -0.0, 0.0 )\nv = base.sub( NaN, NaN )\n","base.subf":"var v = base.subf( -1.0, 5.0 )\nv = base.subf( 2.0, 5.0 )\nv = base.subf( 0.0, 5.0 )\nv = base.subf( -0.0, 0.0 )\nv = base.subf( NaN, NaN )\n","base.sumSeries":"function* geometricSeriesGenerator( x ) {\n var exponent = 0;\n while ( true ) {\n     yield Math.pow( x, exponent );\n     exponent += 1;\n }\n };\nvar gen = geometricSeriesGenerator( 0.9 );\nvar out = base.sumSeries( gen )\nfunction geometricSeriesClosure( x ) {\n var exponent = -1;\n return function() {\n     exponent += 1;\n     return Math.pow( x, exponent );\n };\n };\ngen = geometricSeriesClosure( 0.9 );\nout = base.sumSeries( gen )\nout = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'initialValue': 1 } )\nout = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'maxTerms': 10 } )\nout = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'tolerance': 1e-3 } )\n","base.tan":"var y = base.tan( 0.0 )\ny = base.tan( -PI/4.0 )\ny = base.tan( PI/4.0 )\ny = base.tan( NaN )\n","base.tand":"var y = base.tand( 0.0 )\ny = base.tand( 90.0 )\ny = base.tand( 60.0 )\ny = base.tand( NaN )\n","base.tanh":"var y = base.tanh( 0.0 )\nvar y = base.tanh( -0.0 )\ny = base.tanh( 2.0 )\ny = base.tanh( -2.0 )\ny = base.tanh( NaN )\n","base.toBinaryString":"var str = base.toBinaryString( 4.0 )\nstr = base.toBinaryString( PI )\nstr = base.toBinaryString( -1.0e308 )\nstr = base.toBinaryString( -3.14e-320 )\nstr = base.toBinaryString( 5.0e-324 )\nstr = base.toBinaryString( 0.0 )\nstr = base.toBinaryString( -0.0 )\nstr = base.toBinaryString( NaN )\nstr = base.toBinaryString( PINF )\nstr = base.toBinaryString( NINF )\n","base.toBinaryStringf":"var str = base.toBinaryStringf( base.float64ToFloat32( 4.0 ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( PI ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( -1.0e38 ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( -3.14e-39 ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( 1.4e-45 ) )\nstr = base.toBinaryStringf( 0.0 )\nstr = base.toBinaryStringf( -0.0 )\nstr = base.toBinaryStringf( NaN )\nstr = base.toBinaryStringf( FLOAT32_PINF )\nstr = base.toBinaryStringf( FLOAT32_NINF )\n","base.toBinaryStringUint8":"var a = new Uint8Array( [ 1, 4, 9 ] );\nvar str = base.toBinaryStringUint8( a[ 0 ] )\nstr = base.toBinaryStringUint8( a[ 1 ] )\nstr = base.toBinaryStringUint8( a[ 2 ] )\n","base.toBinaryStringUint16":"var a = new Uint16Array( [ 1, 4, 9 ] );\nvar str = base.toBinaryStringUint16( a[ 0 ] )\nstr = base.toBinaryStringUint16( a[ 1 ] )\nstr = base.toBinaryStringUint16( a[ 2 ] )\n","base.toBinaryStringUint32":"var a = new Uint32Array( [ 1, 4, 9 ] );\nvar str = base.toBinaryStringUint32( a[ 0 ] )\nstr = base.toBinaryStringUint32( a[ 1 ] )\nstr = base.toBinaryStringUint32( a[ 2 ] )\n","base.toWordf":"var f32 = base.float64ToFloat32( 1.337 )\nvar w = base.toWordf( f32 )\n","base.toWords":"var w = base.toWords( 3.14e201 )\n","base.toWords.assign":"var out = new Uint32Array( 2 );\nvar w = base.toWords.assign( 3.14e201, out, 1, 0 )\nvar bool = ( w === out )\n","base.transpose":"var x = array( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\nvar sh = x.shape\nvar y = base.transpose( x )\nsh = y.shape\nvar bool = ( x.data === y.data )\nbool = ( x.get( 0, 1 ) === y.get( 1, 0 ) )\n","base.tribonacci":"var y = base.tribonacci( 0 )\ny = base.tribonacci( 1 )\ny = base.tribonacci( 2 )\ny = base.tribonacci( 3 )\ny = base.tribonacci( 4 )\ny = base.tribonacci( 64 )\ny = base.tribonacci( NaN )\n","base.trigamma":"var y = base.trigamma( -2.5 )\ny = base.trigamma( 1.0 )\ny = base.trigamma( 10.0 )\ny = base.trigamma( NaN )\ny = base.trigamma( -1.0 )\n","base.trim":"var out = base.trim( ' \\t\\t\\n  Beep \\r\\n\\t  ' )\n","base.trunc":"var y = base.trunc( 3.14 )\ny = base.trunc( -4.2 )\ny = base.trunc( -4.6 )\ny = base.trunc( 9.5 )\ny = base.trunc( -0.0 )\n","base.trunc2":"var y = base.trunc2( 3.14 )\ny = base.trunc2( -4.2 )\ny = base.trunc2( -4.6 )\ny = base.trunc2( 9.5 )\ny = base.trunc2( 13.0 )\ny = base.trunc2( -13.0 )\ny = base.trunc2( -0.0 )\n","base.trunc10":"var y = base.trunc10( 3.14 )\ny = base.trunc10( -4.2 )\ny = base.trunc10( -4.6 )\ny = base.trunc10( 9.5 )\ny = base.trunc10( 13.0 )\ny = base.trunc10( -13.0 )\ny = base.trunc10( -0.0 )\n","base.truncateMiddle":"var str = 'beep boop';\nvar out = base.truncateMiddle( str, 5, '...' )\nout = base.truncateMiddle( str, 5, '|' )\n","base.truncb":"var y = base.truncb( 3.14159, -4, 10 )\ny = base.truncb( 3.14159, 0, 2 )\ny = base.truncb( 5.0, 1, 2 )\n","base.truncf":"var y = base.truncf( 3.14 )\ny = base.truncf( -4.2 )\ny = base.truncf( -4.6 )\ny = base.truncf( 9.5 )\ny = base.truncf( -0.0 )\n","base.truncn":"var y = base.truncn( 3.14159, -4 )\ny = base.truncn( 3.14159, 0 )\ny = base.truncn( 12368.0, 3 )\n","base.truncsd":"var y = base.truncsd( 3.14159, 5, 10 )\ny = base.truncsd( 3.14159, 1, 10 )\ny = base.truncsd( 12368.0, 2, 10 )\ny = base.truncsd( 0.0313, 2, 2 )\n","base.uint32ToInt32":"var y = base.uint32ToInt32( base.float64ToUint32( 4294967295 ) )\ny = base.uint32ToInt32( base.float64ToUint32( 3 ) )\n","base.umul":"var v = base.umul( 10>>>0, 4>>>0 )\n","base.umuldw":"var v = base.umuldw( 1, 10 )\n","base.umuldw.assign":"var out = [ 0, 0 ];\nvar v = base.umuldw.assign( 1, 10, out, 1, 0 )\nvar bool = ( v === out )\n","base.uncapitalize":"var out = base.uncapitalize( 'Beep' )\nout = base.uncapitalize( 'bOOp' )\n","base.uppercase":"var out = base.uppercase( 'bEEp' )\n","base.vercos":"var y = base.vercos( 3.14 )\ny = base.vercos( -4.2 )\ny = base.vercos( -4.6 )\ny = base.vercos( 9.5 )\ny = base.vercos( -0.0 )\n","base.versin":"var y = base.versin( 3.14 )\ny = base.versin( -4.2 )\ny = base.versin( -4.6 )\ny = base.versin( 9.5 )\ny = base.versin( -0.0 )\n","base.wrap":"var y = base.wrap( 3.14, 0.0, 5.0 )\ny = base.wrap( -3.14, 0.0, 5.0 )\ny = base.wrap( 3.14, 0.0, 3.0 )\ny = base.wrap( -0.0, 0.0, 5.0 )\ny = base.wrap( 0.0, -3.14, -0.0 )\ny = base.wrap( NaN, 0.0, 5.0 )\n","base.xlog1py":"var out = base.xlog1py( 3.0, 2.0 )\nout = base.xlog1py( 1.5, 5.9 )\nout = base.xlog1py( 0.9, 1.0 )\nout = base.xlog1py( 1.0, 0.0 )\nout = base.xlog1py( 0.0, -2.0 )\nout = base.xlog1py( 1.5, NaN )\nout = base.xlog1py( 0.0, NaN )\nout = base.xlog1py( NaN, 2.3 )\n","base.xlogy":"var out = base.xlogy( 3.0, 2.0 )\nout = base.xlogy( 1.5, 5.9 )\nout = base.xlogy( 0.9, 1.0 )\nout = base.xlogy( 0.0, -2.0 )\nout = base.xlogy( 1.5, NaN )\nout = base.xlogy( 0.0, NaN )\nout = base.xlogy( NaN, 2.3 )\n","base.zeta":"var y = base.zeta( 1.1 )\ny = base.zeta( -4.0 )\ny = base.zeta( 70.0 )\ny = base.zeta( 0.5 )\ny = base.zeta( NaN )\ny = base.zeta( 1.0 )\n","BERNDT_CPS_WAGES_1985":"var data = BERNDT_CPS_WAGES_1985()\n","bifurcate":"var collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar f = [ true, true, false, true ];\nvar out = bifurcate( collection, f )\nf = [ 1, 1, 0, 1 ];\nout = bifurcate( collection, f )\nf = [ true, true, false, true ];\nvar opts = { 'returns': 'indices' };\nout = bifurcate( collection, opts, f )\nopts = { 'returns': '*' };\nout = bifurcate( collection, opts, f )\n","bifurcateBy":"function predicate( v ) { return v[ 0 ] === 'b'; };\nvar collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar out = bifurcateBy( collection, predicate )\nvar opts = { 'returns': 'indices' };\nout = bifurcateBy( collection, opts, predicate )\nopts = { 'returns': '*' };\nout = bifurcateBy( collection, opts, predicate )\n","bifurcateByAsync":"function predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nbifurcateByAsync( arr, predicate, done )\nvar opts = { 'returns': 'indices' };\nbifurcateByAsync( arr, opts, predicate, done )\nopts = { 'returns': '*' };\nbifurcateByAsync( arr, opts, predicate, done )\nfunction predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nbifurcateByAsync( arr, opts, predicate, done )\nfunction predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nbifurcateByAsync( arr, opts, predicate, done )\n","bifurcateByAsync.factory":"function predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) );\n }\n };\nvar opts = { 'series': true };\nvar f = bifurcateByAsync.factory( opts, predicate );\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","bifurcateIn":"function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\nFoo.prototype = Object.create( null );\nFoo.prototype.c = 'foo';\nFoo.prototype.d = 'bar';\nvar obj = new Foo();\nfunction predicate( v ) { return v[ 0 ] === 'b'; };\nvar out = bifurcateIn( obj, predicate )\nvar opts = { 'returns': 'keys' };\nout = bifurcateIn( obj, opts, predicate )\nopts = { 'returns': '*' };\nout = bifurcateIn( obj, opts, predicate )\n","bifurcateOwn":"function predicate( v ) { return v[ 0 ] === 'b'; };\nvar obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\nvar out = bifurcateOwn( obj, predicate )\nvar opts = { 'returns': 'keys' };\nout = bifurcateOwn( obj, opts, predicate )\nopts = { 'returns': '*' };\nout = bifurcateOwn( obj, opts, predicate )\n","BigInt":"var v = ( BigInt ) ? BigInt( '1' ) : null\n","binomialTest":"var out = binomialTest( 682, 925 )\nout = binomialTest( [ 682, 925 - 682 ] )\nout = binomialTest( 21, 40, {\n 'p': 0.4,\n 'alternative': 'greater'\n })\n","Boolean":"var b = new Boolean( null )\nb = Boolean( null )\nb = Boolean( [] )\n","Boolean.prototype.toString":"var b = new Boolean( true )\nb.toString()\n","Boolean.prototype.valueOf":"var b = new Boolean( true )\nb.valueOf()\n","BooleanArray":"var arr = new BooleanArray()\nvar arr = new BooleanArray( 10 )\nvar len = arr.length\nvar arr1 = new BooleanArray( [ true, false, false, true ] )\nvar arr2 = new BooleanArray( arr1 )\nvar len = arr2.length\nvar buf = new Uint8Array( [ 1, 0, 0, 1 ] )\nvar arr = new BooleanArray( buf )\nvar len = arr.length\nvar arr1 = new BooleanArray( [ true, false, false, true ] )\nvar len = arr1.length\nvar arr2 = new BooleanArray( [ {}, null, '', 4 ] );\nlen = arr2.length\nvar buf = new ArrayBuffer( 240 );\nvar arr1 = new BooleanArray( buf )\nvar len = arr1.length\nvar arr2 = new BooleanArray( buf, 8 )\nlen = arr2.length\nvar arr3 = new BooleanArray( buf, 8, 20 )\nlen = arr3.length\n","BooleanArray.from":"function map( v ) { return !v };\nvar src = [ true, false ];\nvar arr = BooleanArray.from( src, map )\nvar len = arr.length\nvar v = arr.get( 0 )\nv = arr.get( 1 )\n","BooleanArray.of":"var arr = BooleanArray.of( true, false, false, true )\nvar len = arr.length\n","BooleanArray.BYTES_PER_ELEMENT":"var nbytes = BooleanArray.BYTES_PER_ELEMENT\n","BooleanArray.name":"var str = BooleanArray.name\n","BooleanArray.prototype.buffer":"var arr = new BooleanArray( 2 )\nvar buf = arr.buffer\n","BooleanArray.prototype.byteLength":"var arr = new BooleanArray( 10 )\nvar nbytes = arr.byteLength\n","BooleanArray.prototype.byteOffset":"var arr = new BooleanArray( 10 )\nvar offset = arr.byteOffset\nvar buf = new ArrayBuffer( 240 );\narr = new BooleanArray( buf, 64 )\noffset = arr.byteOffset\n","BooleanArray.prototype.BYTES_PER_ELEMENT":"var arr = new BooleanArray( 10 )\narr.BYTES_PER_ELEMENT\n","BooleanArray.prototype.length":"var arr = new BooleanArray( 10 )\nvar len = arr.length\n","BooleanArray.prototype.at":"var arr = new BooleanArray( [ true, false, false, true ] )\nvar v = arr.at( 1 )\nv = arr.at( -1 )\n","BooleanArray.prototype.copyWithin":"var arr = new BooleanArray( [ true, false, false, true ] )\narr.copyWithin( 0, 2 )\nvar v = arr.get( 0 )\nv = arr.get( 1 )\n","BooleanArray.prototype.entries":"var arr = new BooleanArray( [ true, false, true ] )\nvar it = arr.entries();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","BooleanArray.prototype.every":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, true, true ] )\nvar bool = arr.every( predicate )\n","BooleanArray.prototype.fill":"var arr = new BooleanArray( 3 )\narr.fill( true );\nvar v = arr.get( 0 )\nv = arr.get( 1 )\nv = arr.get( 2 )\n","BooleanArray.prototype.filter":"function predicate( v ) { return ( v === true ); };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.filter( predicate )\nvar len = out.length\nvar v = out.get( 0 )\nv = out.get( 1 )\n","BooleanArray.prototype.find":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar v = arr.find( predicate )\n","BooleanArray.prototype.findIndex":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar idx = arr.findIndex( predicate )\n","BooleanArray.prototype.findLast":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar v = arr.findLast( predicate )\n","BooleanArray.prototype.findLastIndex":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar idx = arr.findLastIndex( predicate )\n","BooleanArray.prototype.forEach":"var str = '%';\nfunction clbk( v ) { str += v.toString() + '%'; };\nvar arr = new BooleanArray( [ true, false, false, true ] )\narr.forEach( clbk );\nstr\n","BooleanArray.prototype.get":"var arr = new BooleanArray( 10 )\narr.set( true, 0 );\nvar v = arr.get( 0 )\n","BooleanArray.prototype.includes":"var arr = new BooleanArray( [ true, false, true, true, true ] )\nvar bool = arr.includes( true )\nbool = arr.includes( false, 3 )\n","BooleanArray.prototype.indexOf":"var arr = new BooleanArray( [ true, false, true, true, true ] )\nvar idx = arr.indexOf( true )\nidx = arr.indexOf( false, 3 )\n","BooleanArray.prototype.join":"var arr = new BooleanArray( [ true, false, true ] )\nvar str = arr.join()\nstr = arr.join( '|' )\n","BooleanArray.prototype.keys":"var arr = new BooleanArray( [ true, false ] )\nvar it = arr.keys();\nvar v = it.next().value\nv = it.next().value\nv = it.next().done\n","BooleanArray.prototype.lastIndexOf":"var arr = new BooleanArray( [ true, true, true, false, true ] )\nvar idx = arr.lastIndexOf( false )\nidx = arr.lastIndexOf( false, 2 )\n","BooleanArray.prototype.map":"function invert( v ) { return !v; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.map( invert )\nvar v = out.get( 0 )\nv = out.get( 1 )\nv = out.get( 2 )\n","BooleanArray.prototype.reduce":"function reducer( acc, v ) { return ( acc && v ); };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.reduce( reducer )\n","BooleanArray.prototype.reduceRight":"function reducer( acc, v ) { return ( acc && v ); };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.reduceRight( reducer )\n","BooleanArray.prototype.reverse":"var arr = new BooleanArray( [ true, false, false ] )\narr.reverse();\nvar v = arr.get( 0 )\nv = arr.get( 1 )\nv = arr.get( 2 )\n","BooleanArray.prototype.set":"var arr = new BooleanArray( 2 )\narr.set( false );\nvar v = arr.get( 0 )\narr.set( true, 1 );\nv = arr.get( 1 )\n","BooleanArray.prototype.slice":"var arr = new BooleanArray( [ true, false, true, false, true ] )\nvar out = arr.slice( 1 )\nvar len = out.length\nvar v = out.get( 0 )\nv = out.get( 1 )\n","BooleanArray.prototype.some":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ false, true, false ] )\nvar bool = arr.some( predicate )\n","BooleanArray.prototype.sort":"function compare( a, b ) { return a === true ? -1 : 1; };\nvar arr = new BooleanArray( [ true, false, true ] )\narr.sort( compare );\nvar v = arr.get( 0 )\nv = arr.get( 1 )\nv = arr.get( 2 )\n","BooleanArray.prototype.subarray":"var arr = new BooleanArray( [ true, false, true, false, true ] )\nvar out = arr.subarray( 1, 3 )\nvar len = out.length\nvar v = out.get( 0 )\nv = out.get( 1 )\n","BooleanArray.prototype.toLocaleString":"var arr = new BooleanArray( [ true, false, true ] )\nvar str = arr.toLocaleString()\n","BooleanArray.prototype.toReversed":"var arr = new BooleanArray( [ true, false, false ] )\nvar out = arr.toReversed()\nvar v = out.get( 0 )\nv = out.get( 1 )\nv = out.get( 2 )\n","BooleanArray.prototype.toSorted":"function compare( a, b ) { return a === true ? -1 : 1; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.toSorted( compare );\nvar v = out.get( 0 )\nv = out.get( 1 )\nv = out.get( 2 )\n","BooleanArray.prototype.toString":"var arr = new BooleanArray( [ true, false, true ] )\nvar str = arr.toString()\n","BooleanArray.prototype.values":"var arr = new BooleanArray( [ true, false ] )\nvar it = arr.values();\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","BooleanArray.prototype.with":"var arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.with( 0, false )\nvar v = out.get( 0 )\n","broadcastArray":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = broadcastArray( x, [ 3, 2, 2 ] )\nsh = y.shape\nvar v = y.get( 0, 0, 0 )\nv = y.get( 0, 0, 1 )\nv = y.get( 0, 1, 0 )\nv = y.get( 0, 1, 1 )\nv = y.get( 1, 0, 0 )\nv = y.get( 1, 1, 0 )\nv = y.get( 2, 0, 0 )\nv = y.get( 2, 1, 1 )\n","broadcastArrays":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = ndzeros( [ 3, 2, 2 ] )\nvar out = broadcastArrays( [ x, y ] )\nvar bx = out[ 0 ]\nsh = bx.shape\nvar v = bx.get( 0, 0, 0 )\nv = bx.get( 0, 0, 1 )\nv = bx.get( 0, 1, 0 )\nv = bx.get( 0, 1, 1 )\nv = bx.get( 1, 0, 0 )\nv = bx.get( 1, 1, 0 )\nv = bx.get( 2, 0, 0 )\nv = bx.get( 2, 1, 1 )\n","Buffer":"var b = new Buffer( 4 )\nvar b1 = new Buffer( [ 1, 2, 3, 4 ] );\nvar b2 = new Buffer( b1 )\nvar b = new Buffer( [ 1, 2, 3, 4 ] )\nvar b = new Buffer( 'beep boop' )\n","buffer2json":"var buf = new allocUnsafe( 2 );\nbuf[ 0 ] = 1;\nbuf[ 1 ] = 2;\nvar json = buffer2json( buf )\n","BYTE_ORDER":"BYTE_ORDER\n","camelcase":"var out = camelcase( 'Hello World!' )\nout = camelcase( 'beep boop' )\n","capitalize":"var out = capitalize( 'beep' )\nout = capitalize( 'Boop' )\n","capitalizeKeys":"var obj = { 'aa': 1, 'bb': 2 };\nvar out = capitalizeKeys( obj )\n","CATALAN":"CATALAN\n","CBRT_EPS":"CBRT_EPS\n","CDC_NCHS_US_BIRTHS_1969_1988":"var data = CDC_NCHS_US_BIRTHS_1969_1988()\n","CDC_NCHS_US_BIRTHS_1994_2003":"var data = CDC_NCHS_US_BIRTHS_1994_2003()\n","CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013":"var data = CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n","chdir":"var err = chdir( '/path/to/current/working/directory' )\n","chi2gof":"var x = [ 89, 37, 30, 28, 2 ];\nvar p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\nvar out = chi2gof( x, p );\nvar o = out.toJSON()\nout.toString()\nvar opts = { 'alpha': 0.01 };\nout = chi2gof( x, p, opts );\nout.toString()\nx = [ 89, 37, 30, 28, 2 ];\np = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\nopts = { 'simulate': true, 'iterations': 1000 };\nout = chi2gof( x, p, opts );\nout.toString()\nvar lambda = 3.0;\nvar rpois = base.random.poisson.factory( lambda );\nvar len = 400;\nx = [];\nfor ( var i = 0; i < len; i++ ) { x.push( rpois() ); };\nvar freqs = new Int32Array( len );\nfor ( i = 0; i < len; i++ ) { freqs[ x[ i ] ] += 1; };\nout = chi2gof( freqs, 'poisson', lambda );\nout.toString()\n","chi2test":"var x = [ [ 20, 30 ], [ 30, 20 ] ];\nvar out = chi2test( x );\nvar o = out.toJSON()\nout.toString()\nvar opts = { 'alpha': 0.1 };\nout = chi2test( x, opts );\no = out.toJSON()\nout.toString()\nopts = { 'correct': false };\nout = chi2test( x, opts );\nout.toString()\n","circarray2iterator":"var it = circarray2iterator( [ 1, 2, 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","circularArrayStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 15 };\nvar s = circularArrayStream( [ 1, 2, 3 ], opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","circularArrayStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = circularArrayStream.factory( opts );\n","circularArrayStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 15 };\nvar s = circularArrayStream.objectMode( [ 1, 2, 3 ], opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","CircularBuffer":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.length\nb.count\nb.push( 'boop' )\n","CircularBuffer.prototype.clear":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.count\nb.clear();\nb.count\n","CircularBuffer.prototype.count":"var b = CircularBuffer( 3 );\nb.count\nb.push( 'foo' );\nb.count\nb.push( 'bar' );\nb.count\n","CircularBuffer.prototype.full":"var b = CircularBuffer( 3 );\nb.full\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.full\n","CircularBuffer.prototype.iterator":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.push( 'boop' );\nvar it = b.iterator( b.length );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","CircularBuffer.prototype.length":"var b = CircularBuffer( [ 0, 0, 0 ] );\nvar len = b.length\n","CircularBuffer.prototype.push":"var b = CircularBuffer( 3 );\nb.push( 'foo' )\nb.push( 'bar' )\nb.push( 'beep' )\nb.push( 'boop' )\n","CircularBuffer.prototype.toArray":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.push( 'boop' );\nvar vals = b.toArray()\n","CircularBuffer.prototype.toJSON":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.push( 'boop' );\nvar o = b.toJSON()\n","close":"function done( error ) {\n if ( error ) {\n     console.error( error.message );\n }\n };\nvar fd = open.sync( './beep/boop.js', 'r+' );\nif ( !isError( fd ) ) { close( fd, done ); };\n","close.sync":"var fd = open.sync( './beep/boop.js', 'r+' );\nif ( !isError( fd ) ) { close.sync( fd ); };\n","CMUDICT":"var data = CMUDICT();\nvar dict = data.dict\nvar phones = data.phones\nvar symbols = data.symbols\nvar vp = data.vp\n","codePointAt":"var out = codePointAt( 'last man standing', 4 )\nout = codePointAt( 'presidential election', 8, true )\nout = codePointAt( 'अनुच्छेद', 2 )\nout = codePointAt( '🌷', 1, true )\n","commonKeys":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\nvar keys = commonKeys( obj1, obj2 )\n","commonKeysIn":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\nvar keys = commonKeysIn( obj1, obj2 )\n","complex":"var z = complex( 5.0, 3.0, 'float64' )\nz = complex( 5.0, 3.0, 'float32' )\n","Complex64":"var z = new Complex64( 5.0, 3.0 )\nz.re\nz.im\n","Complex64.BYTES_PER_ELEMENT":"var s = Complex64.BYTES_PER_ELEMENT\n","Complex64.prototype.BYTES_PER_ELEMENT":"var z = new Complex64( 5.0, 3.0 )\nvar s = z.BYTES_PER_ELEMENT\n","Complex64.prototype.byteLength":"var z = new Complex64( 5.0, 3.0 )\nvar s = z.byteLength\n","COMPLEX64_NAN":"COMPLEX64_NAN\n","COMPLEX64_NUM_BYTES":"COMPLEX64_NUM_BYTES\n","COMPLEX64_ZERO":"COMPLEX64_ZERO\n","Complex64Array":"var arr = new Complex64Array()\nvar arr = new Complex64Array( 10 )\nvar len = arr.length\nvar arr1 = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar arr2 = new Complex64Array( arr1 )\nvar len = arr2.length\nvar buf = new Float32Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar arr = new Complex64Array( buf )\nvar len = arr.length\nvar arr1 = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar len = arr1.length\nvar buf = [ new Complex64( 1.0, -1.0 ), new Complex64( 2.0, -2.0 )];\nvar arr2 = new Complex64Array( buf )\nlen = arr2.length\nvar buf = new ArrayBuffer( 240 );\nvar arr1 = new Complex64Array( buf )\nvar len = arr1.length\nvar arr2 = new Complex64Array( buf, 8 )\nlen = arr2.length\nvar arr3 = new Complex64Array( buf, 8, 20 )\nlen = arr3.length\n","Complex64Array.from":"function clbkFcn( v ) { return v * 2.0 };\nvar arr = Complex64Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\nvar len = arr.length\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.of":"var arr = Complex64Array.of( 1.0, -1.0, 2.0, -2.0 )\nvar len = arr.length\nvar z1 = new Complex64( 1.0, -1.0 );\nvar z2 = new Complex64( 2.0, -2.0 );\narr = Complex64Array.of( z1, z2 )\nlen = arr.length\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.BYTES_PER_ELEMENT":"var nbytes = Complex64Array.BYTES_PER_ELEMENT\n","Complex64Array.name":"var str = Complex64Array.name\n","Complex64Array.prototype.buffer":"var arr = new Complex64Array( 2 )\nvar buf = arr.buffer\n","Complex64Array.prototype.byteLength":"var arr = new Complex64Array( 10 )\nvar nbytes = arr.byteLength\n","Complex64Array.prototype.byteOffset":"var arr = new Complex64Array( 5 )\nvar offset = arr.byteOffset\nvar buf = new ArrayBuffer( 240 );\narr = new Complex64Array( buf, 64 )\noffset = arr.byteOffset\n","Complex64Array.prototype.BYTES_PER_ELEMENT":"var arr = new Complex64Array( 10 )\narr.BYTES_PER_ELEMENT\n","Complex64Array.prototype.length":"var arr = new Complex64Array( 10 )\nvar len = arr.length\n","Complex64Array.prototype.at":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.at( 1 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.copyWithin":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\narr.copyWithin( 0, 2 )\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.entries":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\nvar it = arr.entries();\nvar v = it.next().value\nvar re = realf( v[ 1 ] )\nvar im = imagf( v[ 1 ] )\nv = it.next().value\nre = realf( v[ 1 ] )\nim = imagf( v[ 1 ] )\nv = it.next().value\nre = realf( v[ 1 ] )\nim = imagf( v[ 1 ] )\nvar bool = it.next().done\n","Complex64Array.prototype.every":"function predicate( v ) { return ( realf( v ) > 0.0 ); };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar bool = arr.every( predicate )\n","Complex64Array.prototype.fill":"var arr = new Complex64Array( 3 )\narr.fill( new Complex64( 1.0, 1.0 ) );\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = arr.get( 1 )\nre = realf( z )\nim = imagf( z )\nz = arr.get( 2 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.filter":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar out = arr.filter( predicate )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.find":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar z = arr.find( predicate )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.findIndex":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar idx = arr.findIndex( predicate )\n","Complex64Array.prototype.findLast":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar z = arr.findLast( predicate )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.findLastIndex":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar idx = arr.findLastIndex( predicate )\n","Complex64Array.prototype.forEach":"var str = '%';\nfunction clbk( v ) { str += v.toString() + '%'; };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\narr.forEach( clbk );\nstr\n","Complex64Array.prototype.get":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.get( 1 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.includes":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar bool = arr.includes( new Complex64( 3.0, -3.0 ) )\nbool = arr.includes( new Complex64( 3.0, -3.0 ), 3 )\n","Complex64Array.prototype.indexOf":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar idx = arr.indexOf( new Complex64( 3.0, -3.0 ) )\nidx = arr.indexOf( new Complex64( 3.0, -3.0 ), 3 )\n","Complex64Array.prototype.join":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar str = arr.join()\nstr = arr.join( '/' )\n","Complex64Array.prototype.keys":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar it = arr.keys();\nvar v = it.next().value\nv = it.next().value\nv = it.next().done\n","Complex64Array.prototype.lastIndexOf":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\nvar idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ) )\nidx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ), 2 )\n","Complex64Array.prototype.map":"function clbk( v ) { return v; };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar out = arr.map( clbk )\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = out.get( 1 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.reduce":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.reduce( base.caddf )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.reduceRight":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.reduceRight( base.caddf )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.reverse":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\narr.reverse();\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = arr.get( 1 )\nre = realf( z )\nim = imagf( z )\nz = arr.get( 2 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.set":"var arr = new Complex64Array( 2 )\narr.set( new Complex64( 1.0, -1.0 ) );\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\narr.set( new Complex64( 2.0, -2.0 ), 1 );\nz = arr.get( 1 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.slice":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\nvar out = arr.slice( 1 )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = out.get( 1 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.some":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar bool = arr.some( predicate )\n","Complex64Array.prototype.sort":"function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\nvar arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\narr.sort( compare );\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = arr.get( 1 )\nre = realf( z )\nim = imagf( z )\nz = arr.get( 2 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.subarray":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar out = arr.subarray( 1, 3 )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = out.get( 1 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.toLocaleString":"var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0 ] )\nvar str = arr.toLocaleString()\n","Complex64Array.prototype.toReversed":"var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\nvar out = arr.toReversed()\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = out.get( 1 )\nre = realf( z )\nim = imagf( z )\nz = out.get( 2 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.toSorted":"function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\nvar arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\nvar out = arr.toSorted( compare );\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = out.get( 1 )\nre = realf( z )\nim = imagf( z )\nz = out.get( 2 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.toString":"var arr = new Complex64Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\nvar str = arr.toString()\n","Complex64Array.prototype.values":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar it = arr.values();\nvar v = it.next().value\nvar re = realf( v )\nvar im = imagf( v )\nv = it.next().value\nre = realf( v )\nim = imagf( v )\nvar bool = it.next().done\n","Complex64Array.prototype.with":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\nvar z = out.get( 1 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex128.BYTES_PER_ELEMENT":"var s = Complex128.BYTES_PER_ELEMENT\n","Complex128.prototype.BYTES_PER_ELEMENT":"var z = new Complex128( 5.0, 3.0 )\nvar s = z.BYTES_PER_ELEMENT\n","Complex128.prototype.byteLength":"var z = new Complex128( 5.0, 3.0 )\nvar s = z.byteLength\n","COMPLEX128_NAN":"COMPLEX128_NAN\n","COMPLEX128_NUM_BYTES":"COMPLEX128_NUM_BYTES\n","COMPLEX128_ZERO":"COMPLEX128_ZERO\n","Complex128Array":"var arr = new Complex128Array()\nvar arr = new Complex128Array( 10 )\nvar len = arr.length\nvar arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar arr2 = new Complex128Array( arr1 )\nvar len = arr2.length\nvar buf = new Float64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar arr = new Complex128Array( buf )\nvar len = arr.length\nvar arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar len = arr1.length\nvar buf = [ new Complex128( 1.0, -1.0 ), new Complex128( 2.0, -2.0 ) ];\nvar arr2 = new Complex128Array( buf )\nlen = arr2.length\nvar buf = new ArrayBuffer( 480 );\nvar arr1 = new Complex128Array( buf )\nvar len = arr1.length\nvar arr2 = new Complex128Array( buf, 16 )\nlen = arr2.length\nvar arr3 = new Complex128Array( buf, 16, 20 )\nlen = arr3.length\n","Complex128Array.from":"function clbkFcn( v ) { return v * 2.0 };\nvar arr = Complex128Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\nvar len = arr.length\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.of":"var arr = Complex128Array.of( 1.0, -1.0, 2.0, -2.0 )\nvar len = arr.length\nvar z1 = new Complex128( 1.0, -1.0 );\nvar z2 = new Complex128( 2.0, -2.0 );\narr = Complex128Array.of( z1, z2 )\nlen = arr.length\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.BYTES_PER_ELEMENT":"var nbytes = Complex128Array.BYTES_PER_ELEMENT\n","Complex128Array.name":"var str = Complex128Array.name\n","Complex128Array.prototype.buffer":"var arr = new Complex128Array( 2 )\nvar buf = arr.buffer\n","Complex128Array.prototype.byteLength":"var arr = new Complex128Array( 10 )\nvar nbytes = arr.byteLength\n","Complex128Array.prototype.byteOffset":"var arr = new Complex128Array( 10 )\nvar offset = arr.byteOffset\nvar buf = new ArrayBuffer( 480 );\narr = new Complex128Array( buf, 128 )\noffset = arr.byteOffset\n","Complex128Array.prototype.BYTES_PER_ELEMENT":"var arr = new Complex128Array( 10 )\narr.BYTES_PER_ELEMENT\n","Complex128Array.prototype.length":"var arr = new Complex128Array( 10 )\nvar len = arr.length\n","Complex128Array.prototype.at":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.at( 1 )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.copyWithin":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\narr.copyWithin( 0, 2 )\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.entries":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\nvar it = arr.entries();\nvar v = it.next().value\nvar re = real( v[ 1 ] )\nvar im = imag( v[ 1 ] )\nv = it.next().value\nre = real( v[ 1 ] )\nim = imag( v[ 1 ] )\nv = it.next().value\nre = real( v[ 1 ] )\nim = imag( v[ 1 ] )\nvar bool = it.next().done\n","Complex128Array.prototype.every":"function predicate( v ) { return ( real( v ) > 0.0 ); };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar bool = arr.every( predicate )\n","Complex128Array.prototype.fill":"var arr = new Complex128Array( 3 )\narr.fill( new Complex128( 1.0, 1.0 ) );\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = arr.get( 1 )\nre = real( z )\nim = imag( z )\nz = arr.get( 2 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.filter":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar out = arr.filter( predicate )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.find":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar z = arr.find( predicate )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.findIndex":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar idx = arr.findIndex( predicate )\n","Complex128Array.prototype.findLast":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar z = arr.findLast( predicate )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.findLastIndex":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar idx = arr.findLastIndex( predicate )\n","Complex128Array.prototype.forEach":"var str = '%';\nfunction clbk( v ) { str += v.toString() + '%'; };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\narr.forEach( clbk );\nstr\n","Complex128Array.prototype.get":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.get( 1 )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.includes":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar bool = arr.includes( new Complex128( 3.0, -3.0 ) )\nbool = arr.includes( new Complex128( 3.0, -3.0 ), 3 )\n","Complex128Array.prototype.indexOf":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar idx = arr.indexOf( new Complex128( 3.0, -3.0 ) )\nidx = arr.indexOf( new Complex128( 3.0, -3.0 ), 3 )\n","Complex128Array.prototype.join":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar str = arr.join()\nstr = arr.join( '/' )\n","Complex128Array.prototype.keys":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar it = arr.keys();\nvar v = it.next().value\nv = it.next().value\nv = it.next().done\n","Complex128Array.prototype.lastIndexOf":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\nvar idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ) )\nidx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ), 2 )\n","Complex128Array.prototype.map":"function clbk( v ) { return v; };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar out = arr.map( clbk )\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = out.get( 1 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.reduce":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.reduce( base.cadd )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.reduceRight":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.reduceRight( base.cadd )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.reverse":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\narr.reverse();\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = arr.get( 1 )\nre = real( z )\nim = imag( z )\nz = arr.get( 2 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.set":"var arr = new Complex128Array( 2 )\narr.set( new Complex128( 1.0, -1.0 ) );\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\narr.set( new Complex128( 2.0, -2.0 ), 1 );\nz = arr.get( 1 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.slice":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\nvar out = arr.slice( 1 )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = out.get( 1 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.some":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar bool = arr.some( predicate )\n","Complex128Array.prototype.sort":"function compare( a, b ) { return ( real( a ) - real( b ) ); };\nvar arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\narr.sort( compare );\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = arr.get( 1 )\nre = real( z )\nim = imag( z )\nz = arr.get( 2 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.subarray":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar out = arr.subarray( 1, 3 )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = out.get( 1 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.toLocaleString":"var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0 ] )\nvar str = arr.toLocaleString()\n","Complex128Array.prototype.toReversed":"var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\nvar out = arr.toReversed()\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = out.get( 1 )\nre = real( z )\nim = imag( z )\nz = out.get( 2 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.toSorted":"function compare( a, b ) { return ( real( a ) - real( b ) ); };\nvar arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\nvar out = arr.toSorted( compare );\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = out.get( 1 )\nre = real( z )\nim = imag( z )\nz = out.get( 2 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.toString":"var arr = new Complex128Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\nvar str = arr.toString()\n","Complex128Array.prototype.values":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar it = arr.values();\nvar v = it.next().value\nvar re = real( v )\nvar im = imag( v )\nv = it.next().value\nre = real( v )\nim = imag( v )\nvar bool = it.next().done\n","Complex128Array.prototype.with":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\nvar z = out.get( 1 )\nvar re = real( z )\nvar im = imag( z )\n","complexarray":"var arr = complexarray()\narr = complexarray( 'complex64' )\nvar arr = complexarray( 5 )\narr = complexarray( 5, 'complex64' )\nvar arr1 = complexarray( [ 0.5, 0.5, 0.5, 0.5 ] );\nvar arr2 = complexarray( arr1, 'complex64' )\nvar arr1 = [ 0.5, 0.5, 0.5, 0.5 ];\nvar arr2 = complexarray( arr1, 'complex64' )\nvar buf = new ArrayBuffer( 64 );\nvar arr = complexarray( buf, 0, 8, 'complex64' )\n","complexarrayCtors":"var ctor = complexarrayCtors( 'complex64' )\nctor = complexarrayCtors( 'float32' )\n","complexarrayDataTypes":"var out = complexarrayDataTypes()\n","complexCtors":"var ctor = complexCtors( 'complex128' )\nctor = complexCtors( 'complex' )\n","complexDataType":"var v = new Complex128( 1.0, 2.0 );\nvar dt = complexDataType( v )\ndt = complexDataType( 'beep' )\n","complexDataTypes":"var out = complexDataTypes()\n","complexPromotionRules":"var out = complexPromotionRules( 'complex128', 'complex64' )\n","compose":"function a( x ) {\nreturn 2 * x;\n }\nfunction b( x ) {\nreturn x + 3;\n }\nfunction c( x ) {\nreturn x / 5;\n }\nvar f = compose( c, b, a );\nvar z = f( 6 )\n","composeAsync":"function a( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n    next( null, 2*x );\n}\n };\nfunction b( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n    next( null, x+3 );\n}\n };\nfunction c( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n    next( null, x/5 );\n}\n };\nvar f = composeAsync( c, b, a );\nfunction done( error, result ) {\nif ( error ) {\n    throw error;\n}\nconsole.log( result );\n };\nf( 6, done )\n","configdir":"var dir = configdir()\ndir = configdir( 'appname/config' )\n","conj":"var z = new Complex128( 5.0, 3.0 );\nz.toString()\nvar v = conj( z );\nv.toString()\n","conjf":"var z = new Complex64( 5.0, 3.0 );\nz.toString()\nvar v = conjf( z );\nv.toString()\n","constantcase":"var out = constantcase( 'Hello World!' )\nout = constantcase( 'I am a tiny little teapot' )\n","constantFunction":"var fcn = constantFunction( 3.14 );\nvar v = fcn()\nv = fcn()\nv = fcn()\n","constantStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = constantStream( 'beep', opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","constantStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = constantStream.factory( opts );\n","constantStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = constantStream.objectMode( 3.14, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","constructorName":"var v = constructorName( 'a' )\nv = constructorName( {} )\nv = constructorName( true )\n","contains":"var bool = contains( 'Hello World', 'World' )\nbool = contains( 'Hello World', 'world' )\nbool = contains( [ 1, 2, 3, 4 ], 2 )\nbool = contains( [ NaN, 2, 3, 4 ], NaN )\nbool = contains( 'Hello World', 'Hello', 6 )\nbool = contains( [ true, NaN, false ], true, 1 )\n","convertArray":"var arr = [ 1.0, 2.0, 3.0, 4.0 ];\nvar out = convertArray( arr, 'float32' )\n","convertArraySame":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = new Float32Array( 0 );\nvar out = convertArraySame( x, y )\n","convertPath":"var out = convertPath( '/c/foo/bar/beep.c', 'win32' )\nout = convertPath( '/c/foo/bar/beep.c', 'mixed' )\nout = convertPath( '/c/foo/bar/beep.c', 'posix' )\nout = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'win32' )\nout = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'mixed' )\nout = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'posix' )\n","copy":"var value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\nvar out = copy( value )\nvar bool = ( value[ 0 ].c === out[ 0 ].c )\nvalue = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\nout = copy( value, 1 );\nbool = ( value[ 0 ] === out[ 0 ] )\nbool = ( value[ 0 ].c === out[ 0 ].c )\n","copyBuffer":"var b1 = array2buffer( [ 1, 2, 3, 4 ] );\nvar b2 = copyBuffer( b1 )\n","countBy":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n     return 'b';\n }\n return 'other';\n };\nvar collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar out = countBy( collection, indicator )\n","countByAsync":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\ncountByAsync( arr, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\ncountByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\ncountByAsync( arr, opts, indicator, done )\n","countByAsync.factory":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nvar opts = { 'series': true };\nvar f = countByAsync.factory( opts, indicator );\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000, 500 ];\nf( arr, done )\n","currentYear":"var y = currentYear()\n","curry":"function add( x, y ) { return x + y; };\nvar f = curry( add );\nvar sum = f( 2 )( 3 )\nfunction add() { return arguments[ 0 ] + arguments[ 1 ]; };\nf = curry( add, 2 );\nsum = f( 2 )( 3 )\nvar obj = {\n 'name': 'Ada',\n 'greet': function greet( word1, word2 ) {\n    return word1 + ' ' + word2 + ', ' + this.name + '!'\n }\n };\nf = curry( obj.greet, obj );\nvar str = f( 'Hello' )( 'there' )\n","curryRight":"function add( x, y ) { return x + y; };\nvar f = curryRight( add );\nvar sum = f( 2 )( 3 )\nfunction add() { return arguments[ 0 ] + arguments[ 1 ]; };\nf = curryRight( add, 2 );\nsum = f( 2 )( 3 )\nvar obj = {\n 'name': 'Ada',\n 'greet': function greet( word1, word2 ) {\n     return word1 + ' ' + word2 + ', ' + this.name + '!'\n }\n };\nf = curryRight( obj.greet, obj );\nvar str = f( 'there' )( 'Hello' )\n","cwd":"var dir = cwd()\n","DALE_CHALL_NEW":"var list = DALE_CHALL_NEW()\n","datasets":"var out = datasets( 'MONTH_NAMES_EN' )\nvar opts = { 'data': 'cities' };\nout = datasets( 'MINARD_NAPOLEONS_MARCH', opts )\n","DataView":"var buf = new ArrayBuffer( 5 )\nvar dv = new DataView( buf )\n","DataView.prototype.buffer":"var buf1 = new ArrayBuffer( 5 );\nvar dv = new DataView( buf1 );\nvar buf2 = dv.buffer\nvar b = ( buf1 === buf2 )\n","DataView.prototype.byteLength":"var buf = new ArrayBuffer( 5 );\nvar dv = new DataView( buf );\ndv.byteLength\n","DataView.prototype.byteOffset":"var buf = new ArrayBuffer( 5 );\nvar dv = new DataView( buf, 2 );\ndv.byteLength\ndv.byteOffset\n","datespace":"var stop = '2014-12-02T07:00:54.973Z';\nvar start = new Date( stop ) - 60000;\nvar arr = datespace( start, stop, 6 )\nvar opts = { 'round': 'ceil' };\narr = datespace( 1417503655000, 1417503655001, 3, opts )\n","dayOfQuarter":"var day = dayOfQuarter()\nday = dayOfQuarter( new Date() )\nday = dayOfQuarter( 12, 31, 2017 )\nday = dayOfQuarter( 'dec', 31, 2017 )\nday = dayOfQuarter( 'december', 31, 2017 )\n","dayOfYear":"var day = dayOfYear()\nday = dayOfYear( new Date() )\nday = dayOfYear( 12, 31, 2016 )\nday = dayOfYear( 'dec', 31, 2016 )\nday = dayOfYear( 'december', 31, 2016 )\n","daysInMonth":"var num = daysInMonth()\nnum = daysInMonth( 2 )\nnum = daysInMonth( 2, 2016 )\nnum = daysInMonth( 2, 2017 )\nnum = daysInMonth( 'feb', 2016 )\nnum = daysInMonth( 'february', 2016 )\n","daysInYear":"var num = daysInYear()\nnum = daysInYear( 2016 )\nnum = daysInYear( 2017 )\n","ddot":"var xbuf = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar x = array( xbuf );\nvar ybuf = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar y = array( ybuf );\nvar z = ddot( x, y )\nz.get()\n","debugSinkStream":"var s = debugSinkStream( { 'name': 'foo' } );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","debugSinkStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = debugSinkStream.factory( opts );\n","debugSinkStream.objectMode":"var s = debugSinkStream.objectMode( { 'name': 'foo' } );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","debugStream":"var s = debugStream( { 'name': 'foo' } );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","debugStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = debugStream.factory( opts );\n","debugStream.objectMode":"var s = debugStream.objectMode( { 'name': 'foo' } );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","decorateAfter":"function f( v ) { return -v; };\nvar fcn = decorateAfter( base.abs, 1, f );\nvar v = fcn( -5 )\nv = fcn( 5 )\n","decorateAfter.factory":"function f( v ) { return -v; };\nvar fcn = decorateAfter.factory( base.abs, 1, f );\nvar v = fcn( -5 )\nv = fcn( 5 )\n","deepEqual":"var bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, 3 ] )\nbool = deepEqual( [ 1, 2, 3 ], [ 1, 2, '3' ] )\nbool = deepEqual( { 'a': 2 }, { 'a': [ 2 ] } )\n","deepGet":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar val = deepGet( obj, 'a.b.c' )\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar val = deepGet( obj, 'a/b/c', { 'sep': '/' } )\n","deepGet.factory":"var dget = deepGet.factory( 'a/b/c', { 'sep': '/' } );\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar val = dget( obj )\n","deepHasOwnProp":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = deepHasOwnProp( obj, 'a.b.c' )\nobj = { 'a': { 'b': { 'c': 'd' } } };\nbool = deepHasOwnProp( obj, 'a/b/c', { 'sep': '/' } )\n","deepHasOwnProp.factory":"var has = deepHasOwnProp.factory( 'a/b/c', { 'sep': '/' } );\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = has( obj )\n","deepHasProp":"function Foo() { return this; };\nFoo.prototype.b = { 'c': 'd' };\nvar obj = { 'a': new Foo() };\nvar bool = deepHasProp( obj, 'a.b.c' )\nbool = deepHasProp( obj, 'a/b/c', { 'sep': '/' } )\n","deepHasProp.factory":"function Foo() { return this; };\nFoo.prototype.b = { 'c': 'd' };\nvar has = deepHasProp.factory( 'a/b/c', { 'sep': '/' } );\nvar obj = { 'a': new Foo() };\nvar bool = has( obj )\n","deepPluck":"var arr = [\n { 'a': { 'b': { 'c': 1 } } },\n { 'a': { 'b': { 'c': 2 } } }\n ];\nvar out = deepPluck( arr, 'a.b.c' )\narr = [\n { 'a': [ 0, 1, 2 ] },\n { 'a': [ 3, 4, 5 ] }\n ];\nout = deepPluck( arr, [ 'a', 1 ] )\n","deepSet":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = deepSet( obj, 'a.b.c', 'beep' )\nobj = { 'a': { 'b': { 'c': 'd' } } };\nbool = deepSet( obj, 'a/b/c', 'beep', { 'sep': '/' } );\nobj\nbool = deepSet( obj, 'a.e.c', 'boop', { 'create': true } );\nobj\n","deepSet.factory":"var dset = deepSet.factory( 'a/b/c', {\n 'create': true,\n 'sep': '/'\n });\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = dset( obj, 'beep' )\nobj\n","defineMemoizedProperty":"var obj = {};\nfunction foo() {\n return 'bar';\n };\ndefineMemoizedProperty( obj, 'foo', {\n 'configurable': false,\n 'enumerable': true,\n 'writable': false,\n 'value': foo\n });\nobj.foo\n","defineProperties":"var obj = {};\ndefineProperties( obj, {\n 'foo': {\n     'value': 'bar',\n     'writable': false,\n     'configurable': false,\n     'enumerable': true\n },\n 'baz': {\n     'value': 13\n }\n });\nobj.foo\nobj.baz\n","defineProperty":"var obj = {};\ndefineProperty( obj, 'foo', {\n 'value': 'bar',\n 'enumerable': true,\n 'writable': false\n });\nobj.foo = 'boop';\nobj\n","dirname":"var dir = dirname( './foo/bar/index.js' )\n","dotcase":"var out = dotcase( 'Hello World!' )\nout = dotcase( 'beep boop' )\n","DoublyLinkedList":"var list = DoublyLinkedList();\nlist.push( 'foo' ).push( 'bar' );\nlist.length\nlist.pop()\nlist.length\nlist.pop()\nlist.length\n","doUntil":"function predicate( i ) { return ( i >= 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\ndoUntil( beep, predicate )\n","doUntilAsync":"function fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n     next( null, 'boop'+i );\n }\n };\nfunction predicate( i, clbk ) { clbk( null, i >= 5 ); };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\ndoUntilAsync( fcn, predicate, done )\n","doUntilEach":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\ndoUntilEach( arr, logger, predicate )\n","doUntilEachRight":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\ndoUntilEachRight( arr, logger, predicate )\n","doWhile":"function predicate( i ) { return ( i < 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\ndoWhile( beep, predicate )\n","doWhileAsync":"function fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n     next( null, 'boop'+i );\n }\n };\nfunction predicate( i, clbk ) { clbk( null, i < 5 ); };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\ndoWhileAsync( fcn, predicate, done )\n","doWhileEach":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\ndoWhileEach( arr, logger, predicate )\n","doWhileEachRight":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\ndoWhileEachRight( arr, logger, predicate )\n","dswap":"var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\ndswap( x, y );\nx.data\ny.data\n","E":"E\n","EMOJI":"var data = EMOJI()\n","EMOJI_CODE_PICTO":"var out = EMOJI_CODE_PICTO()\n","EMOJI_PICTO_CODE":"var out = EMOJI_PICTO_CODE()\n","emptyStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar s = emptyStream();\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","emptyStream.factory":"var opts = { 'objectMode': true };\nvar createStream = emptyStream.factory( opts );\n","emptyStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar s = emptyStream.objectMode();\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","endsWith":"var bool = endsWith( 'beep', 'ep' )\nbool = endsWith( 'Beep', 'op' )\nbool = endsWith( 'Beep', 'ee', 3 )\nbool = endsWith( 'Beep', 'ee', -1 )\nbool = endsWith( 'beep', '' )\n","enumerableProperties":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar props = enumerableProperties( obj )\n","enumerablePropertiesIn":"var props = enumerablePropertiesIn( [] )\n","enumerablePropertySymbols":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = enumerablePropertySymbols( obj )\n","enumerablePropertySymbolsIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = enumerablePropertySymbolsIn( obj )\n","ENV":"var user = ENV.USER\n","EPS":"EPS\n","error2json":"var err = new Error( 'beep' );\nvar json = error2json( err )\n","EULERGAMMA":"EULERGAMMA\n","every":"var arr = [ 1, 1, 1, 1, 1 ];\nvar bool = every( arr )\n","everyBy":"function positive( v ) { return ( v > 0 ); };\nvar arr = [ 1, 2, 3, 4 ];\nvar bool = everyBy( arr, positive )\n","everyByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\neveryByAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\neveryByAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\neveryByAsync( arr, opts, predicate, done )\n","everyByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, true );\n }\n };\nvar opts = { 'series': true };\nvar f = everyByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","everyByRight":"function positive( v ) { return ( v > 0 ); };\nvar arr = [ 1, 2, 3, 4 ];\nvar bool = everyByRight( arr, positive )\n","everyByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\neveryByRightAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\neveryByRightAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\neveryByRightAsync( arr, opts, predicate, done )\n","everyByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, true );\n }\n };\nvar opts = { 'series': true };\nvar f = everyByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","everyInBy":"function positive( v ) { return ( v > 0 ); };\nvar o = {a: 1, b: 2, c: 3};\nvar bool = everyInBy( o, positive )\n","everyOwnBy":"function positive( v ) { return ( v > 0 ); };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nvar bool = everyOwnBy( obj, positive )\n","evil":"var v = evil( '5*4*3*2*1' )\n","EXEC_PATH":"EXEC_PATH\n","exists":"function done( error, bool ) { console.log( bool ); };\nexists( './beep/boop', done );\n","exists.sync":"var bool = exists.sync( './beep/boop' )\n","expandAcronyms":"var str = 'LOL, this is fun. I am ROFL.';\nvar out = expandAcronyms( str )\nstr = 'brb, I need to check my mail. thx!';\nout = expandAcronyms( str )\n","expandContractions":"var str = 'I won\\'t be able to get y\\'all out of this one.';\nvar out = expandContractions( str )\nstr = 'It oughtn\\'t to be my fault, because, you know, I didn\\'t know';\nout = expandContractions( str )\n","extname":"var ext = extname( 'index.js' )\n","FancyArray":"var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\nvar d = [ 2, 2 ]; // shape\nvar s = [ 2, 1 ]; // strides\nvar o = 0; // index offset\nvar arr = FancyArray( 'generic', b, d, s, o, 'row-major' )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","FancyArray.prototype.byteLength":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.byteLength\n","FancyArray.prototype.BYTES_PER_ELEMENT":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.BYTES_PER_ELEMENT\n","FancyArray.prototype.data":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar buf = arr.data\n","FancyArray.prototype.dtype":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar dt = arr.dtype\n","FancyArray.prototype.flags":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar fl = arr.flags\n","FancyArray.prototype.length":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar len = arr.length\n","FancyArray.prototype.ndims":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar n = arr.ndims\n","FancyArray.prototype.offset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.offset\n","FancyArray.prototype.order":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar ord = arr.order\n","FancyArray.prototype.shape":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar sh = arr.shape\n","FancyArray.prototype.strides":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar st = arr.strides\n","FancyArray.prototype.get":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.get( 1, 1 )\n","FancyArray.prototype.iget":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.iget( 3 )\n","FancyArray.prototype.set":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\narr.set( 1, 1, -4.0 );\narr.get( 1, 1 )\n","FancyArray.prototype.iset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\narr.iset( 3, -4.0 );\narr.iget( 3 )\n","FancyArray.prototype.toString":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\narr.toString()\n","FancyArray.prototype.toJSON":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\narr.toJSON()\n","fastmath.abs":"var v = fastmath.abs( -1.0 )\nv = fastmath.abs( 2.0 )\nv = fastmath.abs( 0.0 )\nv = fastmath.abs( -0.0 )\nv = fastmath.abs( NaN )\n","fastmath.acosh":"var v = fastmath.acosh( 1.0 )\nv = fastmath.acosh( 2.0 )\nv = fastmath.acosh( NaN )\nv = fastmath.acosh( 1.0e308 )\n","fastmath.ampbm":"var h = fastmath.ampbm( 5.0, 12.0 )\n","fastmath.ampbm.factory":"var hypot = fastmath.ampbm.factory( 1.0, 0.5 )\n","fastmath.asinh":"var v = fastmath.asinh( 0.0 )\nv = fastmath.asinh( 2.0 )\nv = fastmath.asinh( -2.0 )\nv = fastmath.asinh( NaN )\nv = fastmath.asinh( 1.0e200 )\nv = fastmath.asinh( 1.0e-50 )\n","fastmath.atanh":"var v = fastmath.atanh( 0.0 )\nv = fastmath.atanh( 0.9 )\nv = fastmath.atanh( 1.0 )\nv = fastmath.atanh( -1.0 )\nv = fastmath.atanh( NaN )\nv = fastmath.atanh( 1.0e-17 )\n","fastmath.hypot":"var h = fastmath.hypot( -5.0, 12.0 )\nh = fastmath.hypot( 1.0e154, 1.0e154 )\nh = fastmath.hypot( 1e-200, 1.0e-200 )\n","fastmath.log2Uint32":"var v = fastmath.log2Uint32( 4 >>> 0 )\nv = fastmath.log2Uint32( 8 >>> 0 )\nv = fastmath.log2Uint32( 9 >>> 0 )\n","fastmath.max":"var v = fastmath.max( 3.14, 4.2 )\nv = fastmath.max( 3.14, NaN )\nv = fastmath.max( NaN, 3.14 )\nv = fastmath.max( -0.0, +0.0 )\nv = fastmath.max( +0.0, -0.0 )\n","fastmath.min":"var v = fastmath.min( 3.14, 4.2 )\nv = fastmath.min( 3.14, NaN )\nv = fastmath.min( NaN, 3.14 )\nv = fastmath.min( -0.0, +0.0 )\nv = fastmath.min( +0.0, -0.0 )\n","fastmath.powint":"var v = fastmath.powint( 2.0, 3 )\nv = fastmath.powint( 3.14, 0 )\nv = fastmath.powint( 2.0, -2 )\nv = fastmath.powint( 0.0, 0 )\nv = fastmath.powint( -3.14, 1 )\nv = fastmath.powint( NaN, 0 )\n","fastmath.sqrtUint32":"var v = fastmath.sqrtUint32( 9 >>> 0 )\nv = fastmath.sqrtUint32( 2 >>> 0 )\nv = fastmath.sqrtUint32( 3 >>> 0 )\nv = fastmath.sqrtUint32( 0 >>> 0 )\n","FEMALE_FIRST_NAMES_EN":"var list = FEMALE_FIRST_NAMES_EN()\n","FIFO":"var q = FIFO();\nq.push( 'foo' ).push( 'bar' );\nq.length\nq.pop()\nq.length\nq.pop()\nq.length\n","filledarray":"var arr = filledarray()\narr = filledarray( 'float32' )\nvar arr = filledarray( 1.0, 5 )\narr = filledarray( 1, 5, 'int32' )\nvar arr1 = filledarray( 2.0, [ 0.5, 0.5, 0.5 ] )\nvar arr2 = filledarray( 1.0, arr1, 'float32' )\nvar arr1 = iterConstant( 3.0, {'iter': 3} );\nvar arr2 = filledarray( 1.0, arr1, 'float32' )\nvar buf = new ArrayBuffer( 16 );\nvar arr = filledarray( 1.0, buf, 0, 4, 'float32' )\n","filledarrayBy":"var arr = filledarrayBy()\narr = filledarrayBy( 'float32' )\nfunction clbk() { return 1.0; };\nvar arr = filledarrayBy( 5, clbk )\narr = filledarrayBy( 5, 'int32', clbk )\nvar arr1 = filledarrayBy( [ 0.5, 0.5, 0.5 ], constantFunction( 2.0 ) )\nvar arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\nvar arr1 = iterConstant( 3.0, {'iter': 3} );\nvar arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\nvar buf = new ArrayBuffer( 16 );\nvar arr = filledarrayBy( buf, 0, 4, 'float32', constantFunction( 1.0 ) )\n","filterArguments":"function foo( a, b ) { return [ a, b ]; };\nfunction predicate( v ) { return ( v !== 2 ); };\nvar bar = filterArguments( foo, predicate );\nvar out = bar( 1, 2, 3 )\n","find":"var data = [ 30, 20, 50, 60, 10 ];\nfunction condition( val ) { return val > 20; };\nvar vals = find( data, condition )\ndata = [ 30, 20, 50, 60, 10 ];\nvar opts = { 'k': 2, 'returns': 'values' };\nvals = find( data, opts, condition )\ndata = [ 30, 20, 50, 60, 10 ];\nopts = { 'k': -2, 'returns': '*' };\nvals = find( data, opts, condition )\n","firstChar":"var out = firstChar( 'beep' )\nout = firstChar( 'Boop', 1 )\nout = firstChar( 'foo bar', 5 )\n","FIVETHIRTYEIGHT_FFQ":"var data = FIVETHIRTYEIGHT_FFQ()\n","flattenArray":"var arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\nvar out = flattenArray( arr )\narr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\nout = flattenArray( arr, { 'depth': 2 } )\nvar bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\narr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\nout = flattenArray( arr, { 'depth': 2, 'copy': true } )\nbool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n","flattenArray.factory":"var flatten = flattenArray.factory( [ 2, 2 ], {\n 'copy': false\n });\nvar out = flatten( [ [ 1, 2 ], [ 3, 4 ] ] )\nout = flatten( [ [ 5, 6 ], [ 7, 8 ] ] )\n","flattenObject":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar out = flattenObject( obj )\nobj = { 'a': { 'b': { 'c': 'd' } } };\nout = flattenObject( obj, { 'depth': 1 } )\nvar bool = ( obj.a.b === out[ 'a.b' ] )\nobj = { 'a': { 'b': { 'c': 'd' } } };\nout = flattenObject( obj, { 'delimiter': '-|-' } )\nobj = { 'a': { 'b': [ 1, 2, 3 ] } };\nout = flattenObject( obj, { 'flattenArrays': true } )\n","flattenObject.factory":"var flatten = flattenObject.factory({\n 'depth': 1,\n 'copy': true,\n 'delimiter': '|'\n });\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar out = flatten( obj )\n","flignerTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = flignerTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = flignerTest( arr, { 'groups': groups } )\n","FLOAT_WORD_ORDER":"FLOAT_WORD_ORDER\n","FLOAT16_CBRT_EPS":"FLOAT16_CBRT_EPS\n","FLOAT16_EPS":"FLOAT16_EPS\n","FLOAT16_EXPONENT_BIAS":"FLOAT16_EXPONENT_BIAS\n","FLOAT16_MAX":"FLOAT16_MAX\n","FLOAT16_MAX_SAFE_INTEGER":"FLOAT16_MAX_SAFE_INTEGER\n","FLOAT16_MIN_SAFE_INTEGER":"FLOAT16_MIN_SAFE_INTEGER\n","FLOAT16_NINF":"FLOAT16_NINF\n","FLOAT16_NUM_BYTES":"FLOAT16_NUM_BYTES\n","FLOAT16_PINF":"FLOAT16_PINF\n","FLOAT16_PRECISION":"FLOAT16_PRECISION\n","FLOAT16_SMALLEST_NORMAL":"FLOAT16_SMALLEST_NORMAL\n","FLOAT16_SMALLEST_SUBNORMAL":"FLOAT16_SMALLEST_SUBNORMAL\n","FLOAT16_SQRT_EPS":"FLOAT16_SQRT_EPS\n","FLOAT32_ABS_MASK":"FLOAT32_ABS_MASK\nbase.toBinaryStringUint32( FLOAT32_ABS_MASK )\n","FLOAT32_CBRT_EPS":"FLOAT32_CBRT_EPS\n","FLOAT32_E":"FLOAT32_E\n","FLOAT32_EPS":"FLOAT32_EPS\n","FLOAT32_EXPONENT_BIAS":"FLOAT32_EXPONENT_BIAS\n","FLOAT32_EXPONENT_MASK":"FLOAT32_EXPONENT_MASK\nbase.toBinaryStringUint32( FLOAT32_EXPONENT_MASK )\n","FLOAT32_FOURTH_PI":"FLOAT32_FOURTH_PI\n","FLOAT32_HALF_LN_TWO":"FLOAT32_HALF_LN_TWO\n","FLOAT32_HALF_PI":"FLOAT32_HALF_PI\n","FLOAT32_LN_HALF":"FLOAT32_LN_HALF\n","FLOAT32_LN_PI":"FLOAT32_LN_PI\n","FLOAT32_LN_TEN":"FLOAT32_LN_TEN\n","FLOAT32_LN_TWO":"FLOAT32_LN_TWO\n","FLOAT32_MAX":"FLOAT32_MAX\n","FLOAT32_MAX_BASE2_EXPONENT":"FLOAT32_MAX_BASE2_EXPONENT\n","FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL":"FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL\n","FLOAT32_MAX_BASE10_EXPONENT":"FLOAT32_MAX_BASE10_EXPONENT\n","FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL":"FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL\n","FLOAT32_MAX_SAFE_FIBONACCI":"FLOAT32_MAX_SAFE_FIBONACCI\n","FLOAT32_MAX_SAFE_INTEGER":"FLOAT32_MAX_SAFE_INTEGER\n","FLOAT32_MAX_SAFE_NTH_FACTORIAL":"FLOAT32_MAX_SAFE_NTH_FACTORIAL\n","FLOAT32_MAX_SAFE_NTH_FIBONACCI":"FLOAT32_MAX_SAFE_NTH_FIBONACCI\n","FLOAT32_MAX_SAFE_NTH_LUCAS":"FLOAT32_MAX_SAFE_NTH_LUCAS\n","FLOAT32_MIN_BASE2_EXPONENT":"FLOAT32_MIN_BASE2_EXPONENT\n","FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL":"FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT32_MIN_BASE10_EXPONENT":"FLOAT32_MIN_BASE10_EXPONENT\n","FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL":"FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT32_MIN_SAFE_INTEGER":"FLOAT32_MIN_SAFE_INTEGER\n","FLOAT32_NAN":"FLOAT32_NAN\n","FLOAT32_NINF":"FLOAT32_NINF\n","FLOAT32_NUM_BYTES":"FLOAT32_NUM_BYTES\n","FLOAT32_PHI":"FLOAT32_PHI\n","FLOAT32_PI":"FLOAT32_PI\n","FLOAT32_PINF":"FLOAT32_PINF\n","FLOAT32_PRECISION":"FLOAT32_PRECISION\n","FLOAT32_SIGN_MASK":"FLOAT32_SIGN_MASK\nbase.toBinaryStringUint32( FLOAT32_SIGN_MASK )\n","FLOAT32_SIGNIFICAND_MASK":"FLOAT32_SIGNIFICAND_MASK\nbase.toBinaryStringUint32( FLOAT32_SIGNIFICAND_MASK )\n","FLOAT32_SMALLEST_NORMAL":"FLOAT32_SMALLEST_NORMAL\n","FLOAT32_SMALLEST_SUBNORMAL":"FLOAT32_SMALLEST_SUBNORMAL\n","FLOAT32_SQRT_EPS":"FLOAT32_SQRT_EPS\n","FLOAT32_SQRT_HALF":"FLOAT32_SQRT_HALF\n","FLOAT32_SQRT_HALF_PI":"FLOAT32_SQRT_HALF_PI\n","FLOAT32_SQRT_PHI":"FLOAT32_SQRT_PHI\n","FLOAT32_SQRT_PI":"FLOAT32_SQRT_PI\n","FLOAT32_SQRT_THREE":"FLOAT32_SQRT_THREE\n","FLOAT32_SQRT_TWO":"FLOAT32_SQRT_TWO\n","FLOAT32_SQRT_TWO_PI":"FLOAT32_SQRT_TWO_PI\n","FLOAT32_TWO_PI":"FLOAT32_TWO_PI\n","Float32Array":"var arr = new Float32Array()\nvar arr = new Float32Array( 5 )\nvar arr1 = new Float64Array( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = new Float32Array( arr1 )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = new Float32Array( arr1 )\nvar buf = new ArrayBuffer( 16 );\nvar arr = new Float32Array( buf, 0, 4 )\n","Float32Array.from":"function mapFcn( v ) { return v * 2.0; };\nvar arr = Float32Array.from( [ 1.0, -1.0 ], mapFcn )\n","Float32Array.of":"var arr = Float32Array.of( 2.0, -2.0 )\n","Float32Array.BYTES_PER_ELEMENT":"Float32Array.BYTES_PER_ELEMENT\n","Float32Array.name":"Float32Array.name\n","Float32Array.prototype.buffer":"var arr = new Float32Array( 5 );\narr.buffer\n","Float32Array.prototype.byteLength":"var arr = new Float32Array( 5 );\narr.byteLength\n","Float32Array.prototype.byteOffset":"var arr = new Float32Array( 5 );\narr.byteOffset\n","Float32Array.prototype.BYTES_PER_ELEMENT":"var arr = new Float32Array( 5 );\narr.BYTES_PER_ELEMENT\n","Float32Array.prototype.length":"var arr = new Float32Array( 5 );\narr.length\n","Float32Array.prototype.copyWithin":"var arr = new Float32Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Float32Array.prototype.entries":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Float32Array.prototype.every":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\narr.every( predicate )\n","Float32Array.prototype.fill":"var arr = new Float32Array( [ 1.0, -1.0 ] );\narr.fill( 2.0 );\narr[ 0 ]\narr[ 1 ]\n","Float32Array.prototype.filter":"var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Float32Array.prototype.find":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar v = arr.find( predicate )\n","Float32Array.prototype.findIndex":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar idx = arr.findIndex( predicate )\n","Float32Array.prototype.forEach":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Float32Array.prototype.includes":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar bool = arr.includes( 2.0 )\nbool = arr.includes( -1.0 )\n","Float32Array.prototype.indexOf":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar idx = arr.indexOf( 2.0 )\nidx = arr.indexOf( -1.0 )\n","Float32Array.prototype.join":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\narr.join( '|' )\n","Float32Array.prototype.keys":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Float32Array.prototype.lastIndexOf":"var arr = new Float32Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\nvar idx = arr.lastIndexOf( 2.0 )\nidx = arr.lastIndexOf( 0.0 )\n","Float32Array.prototype.map":"var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( v ) { return v * 2.0; };\nvar arr2 = arr1.map( fcn )\n","Float32Array.prototype.reduce":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0.0 )\n","Float32Array.prototype.reduceRight":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0.0 )\n","Float32Array.prototype.reverse":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] )\narr.reverse()\n","Float32Array.prototype.set":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\narr.set( [ -2.0, 2.0 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Float32Array.prototype.slice":"var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Float32Array.prototype.some":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\narr.some( predicate )\n","Float32Array.prototype.sort":"var arr = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\narr.sort()\n","Float32Array.prototype.subarray":"var arr1 = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\nvar arr2 = arr1.subarray( 2 )\n","Float32Array.prototype.toLocaleString":"var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\narr.toLocaleString()\n","Float32Array.prototype.toString":"var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\narr.toString()\n","Float32Array.prototype.values":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","FLOAT64_EXPONENT_BIAS":"FLOAT64_EXPONENT_BIAS\n","FLOAT64_HIGH_WORD_ABS_MASK":"FLOAT64_HIGH_WORD_ABS_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_ABS_MASK )\n","FLOAT64_HIGH_WORD_EXPONENT_MASK":"FLOAT64_HIGH_WORD_EXPONENT_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_EXPONENT_MASK )\n","FLOAT64_HIGH_WORD_SIGN_MASK":"FLOAT64_HIGH_WORD_SIGN_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGN_MASK )\n","FLOAT64_HIGH_WORD_SIGNIFICAND_MASK":"FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGNIFICAND_MASK )\n","FLOAT64_MAX":"FLOAT64_MAX\n","FLOAT64_MAX_BASE2_EXPONENT":"FLOAT64_MAX_BASE2_EXPONENT\n","FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL":"FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_BASE10_EXPONENT":"FLOAT64_MAX_BASE10_EXPONENT\n","FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL":"FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_LN":"FLOAT64_MAX_LN\n","FLOAT64_MAX_SAFE_FIBONACCI":"FLOAT64_MAX_SAFE_FIBONACCI\n","FLOAT64_MAX_SAFE_INTEGER":"FLOAT64_MAX_SAFE_INTEGER\n","FLOAT64_MAX_SAFE_LUCAS":"FLOAT64_MAX_SAFE_LUCAS\n","FLOAT64_MAX_SAFE_NTH_FIBONACCI":"FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT64_MAX_SAFE_NTH_LUCAS":"FLOAT64_MAX_SAFE_NTH_LUCAS\n","FLOAT64_MIN_BASE2_EXPONENT":"FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL":"FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_BASE10_EXPONENT":"FLOAT64_MIN_BASE10_EXPONENT\n","FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL":"FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_LN":"FLOAT64_MIN_LN\n","FLOAT64_MIN_SAFE_INTEGER":"FLOAT64_MIN_SAFE_INTEGER\n","FLOAT64_NUM_BYTES":"FLOAT64_NUM_BYTES\n","FLOAT64_PRECISION":"FLOAT64_PRECISION\n","FLOAT64_SMALLEST_NORMAL":"FLOAT64_SMALLEST_NORMAL\n","FLOAT64_SMALLEST_SUBNORMAL":"FLOAT64_SMALLEST_SUBNORMAL\n","Float64Array":"var arr = new Float64Array()\nvar arr = new Float64Array( 5 )\nvar arr1 = new Float32Array( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = new Float64Array( arr1 )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = new Float64Array( arr1 )\nvar buf = new ArrayBuffer( 32 );\nvar arr = new Float64Array( buf, 0, 4 )\n","Float64Array.from":"function mapFcn( v ) { return v * 2.0; };\nvar arr = Float64Array.from( [ 1.0, -1.0 ], mapFcn )\n","Float64Array.of":"var arr = Float64Array.of( 2.0, -2.0 )\n","Float64Array.BYTES_PER_ELEMENT":"Float64Array.BYTES_PER_ELEMENT\n","Float64Array.name":"Float64Array.name\n","Float64Array.prototype.buffer":"var arr = new Float64Array( 5 );\narr.buffer\n","Float64Array.prototype.byteLength":"var arr = new Float64Array( 5 );\narr.byteLength\n","Float64Array.prototype.byteOffset":"var arr = new Float64Array( 5 );\narr.byteOffset\n","Float64Array.prototype.BYTES_PER_ELEMENT":"var arr = new Float64Array( 5 );\narr.BYTES_PER_ELEMENT\n","Float64Array.prototype.length":"var arr = new Float64Array( 5 );\narr.length\n","Float64Array.prototype.copyWithin":"var arr = new Float64Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Float64Array.prototype.entries":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Float64Array.prototype.every":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\narr.every( predicate )\n","Float64Array.prototype.fill":"var arr = new Float64Array( [ 1.0, -1.0 ] );\narr.fill( 2.0 );\narr[ 0 ]\narr[ 1 ]\n","Float64Array.prototype.filter":"var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Float64Array.prototype.find":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar v = arr.find( predicate )\n","Float64Array.prototype.findIndex":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar idx = arr.findIndex( predicate )\n","Float64Array.prototype.forEach":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Float64Array.prototype.includes":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar bool = arr.includes( 2.0 )\nbool = arr.includes( -1.0 )\n","Float64Array.prototype.indexOf":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar idx = arr.indexOf( 2.0 )\nidx = arr.indexOf( -1.0 )\n","Float64Array.prototype.join":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\narr.join( '|' )\n","Float64Array.prototype.keys":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Float64Array.prototype.lastIndexOf":"var arr = new Float64Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\nvar idx = arr.lastIndexOf( 2.0 )\nidx = arr.lastIndexOf( 0.0 )\n","Float64Array.prototype.map":"var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( v ) { return v * 2.0; };\nvar arr2 = arr1.map( fcn )\n","Float64Array.prototype.reduce":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0.0 )\n","Float64Array.prototype.reduceRight":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0.0 )\n","Float64Array.prototype.reverse":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] )\narr.reverse()\n","Float64Array.prototype.set":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\narr.set( [ -2.0, 2.0 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Float64Array.prototype.slice":"var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Float64Array.prototype.some":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\narr.some( predicate )\n","Float64Array.prototype.sort":"var arr = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\narr.sort()\n","Float64Array.prototype.subarray":"var arr1 = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\nvar arr2 = arr1.subarray( 2 )\n","Float64Array.prototype.toLocaleString":"var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\narr.toLocaleString()\n","Float64Array.prototype.toString":"var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\narr.toString()\n","Float64Array.prototype.values":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","forEach":"function logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4 ];\nforEach( arr, logger )\n","forEachAsync":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n     throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 3000, 2500, 1000 ];\nforEachAsync( arr, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n     throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nforEachAsync( arr, opts, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n     throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nforEachAsync( arr, opts, onDuration, done )\n","forEachAsync.factory":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next();\n }\n };\nvar opts = { 'series': true };\nvar f = forEachAsync.factory( opts, onDuration );\nfunction done( error ) {\n if ( error ) {\n     throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","forEachChar":"var n = 0;\nfunction fcn() { n += 1; };\nforEachChar( 'hello world!', fcn );\nn\n","forEachRight":"function logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4 ];\nforEachRight( arr, logger )\n","forEachRightAsync":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n     throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 1000, 2500, 3000 ];\nforEachRightAsync( arr, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n     throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nforEachRightAsync( arr, opts, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n     throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nforEachRightAsync( arr, opts, onDuration, done )\n","forEachRightAsync.factory":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next();\n }\n };\nvar opts = { 'series': true };\nvar f = forEachRightAsync.factory( opts, onDuration );\nfunction done( error ) {\n if ( error ) {\n     throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","forIn":"function logger( v, k ) { console.log( '%s: %d', k, v ); };\nfunction Foo() { return this; };\nFoo.prototype.beep = 'boop';\nvar obj = new Foo();\nforIn( obj, logger )\n","format":"var out = format( 'Hello, %s!', 'World' )\nout = format( '%s %s', 'Hello', 'World' )\nout = format( 'Pi: %.2f', PI )\n","forOwn":"function logger( v, k ) { console.log( '%s: %d', k, v ); };\nvar obj = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\nforOwn( obj, logger )\n","FOURTH_PI":"FOURTH_PI\n","FOURTH_ROOT_EPS":"FOURTH_ROOT_EPS\n","FRB_SF_WAGE_RIGIDITY":"var data = FRB_SF_WAGE_RIGIDITY()\n","fromCodePoint":"var out = fromCodePoint( 9731 )\nout = fromCodePoint( [ 9731 ] )\nout = fromCodePoint( 97, 98, 99 )\nout = fromCodePoint( [ 97, 98, 99 ] )\n","Function":"var f = new Function( 'x', 'y', 'return x + y' );\nf( 1, 2 )\n","Function.prototype.apply":"var f = new Function( 'x', 'y', 'return x + y' );\nf.apply( null, [ 1, 2 ] )\n","Function.prototype.call":"var f = new Function( 'x', 'y', 'return x + y' );\nf.call( null, 1, 2 )\n","Function.prototype.bind":"var f = new Function( 'x', 'y', 'return x + y' );\nvar g = f.bind( null, 1 );\ng( 2 )\n","Function.prototype.toString":"var f = new Function( 'x', 'y', 'return x + y' );\nf.toString()\n","Function.prototype.length":"var f = new Function( 'x', 'y', 'return x + y' );\nf.length\n","Function.prototype.name":"var f = new Function( 'x', 'y', 'return x + y' );\nf.name\nvar f = new Function( 'x', 'y', 'return x + y' );\nf.name = 'add';\nf.name\n","Function.prototype.prototype":"var f = new Function( 'x', 'y', 'return x + y' );\nf.prototype\n","function2string":"function2string( base.erf )\n","functionName":"var v = functionName( String )\nv = functionName( function foo(){} )\nv = functionName( function(){} )\n","functionSequence":"function a( x ) { return 2 * x; };\nfunction b( x ) { return x + 3; };\nfunction c( x ) { return x / 5; };\nvar f = functionSequence( a, b, c );\nvar z = f( 6 )\n","functionSequenceAsync":"function a( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n    next( null, 2*x );\n}\n };\nfunction b( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n    next( null, x+3 );\n}\n };\nfunction c( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n    next( null, x/5 );\n}\n };\nvar f = functionSequenceAsync( a, b, c );\nfunction done( error, result ) {\nif ( error ) {\n    throw error;\n}\nconsole.log( result );\n };\nf( 6, done )\n","GAMMA_LANCZOS_G":"GAMMA_LANCZOS_G\n","gdot":"var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\ngdot( x, y )\nx = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\ny = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\ngdot( x, y )\n","getegid":"var gid = getegid()\n","geteuid":"var uid = geteuid()\n","getgid":"var gid = getgid()\n","getGlobal":"var g = getGlobal()\n","getPrototypeOf":"var proto = getPrototypeOf( {} )\n","getuid":"var uid = getuid()\n","GLAISHER":"GLAISHER\n","graphemeClusters2iterator":"var it = graphemeClusters2iterator( '🌷🍕' );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","graphemeClusters2iteratorRight":"var it = graphemeClusters2iteratorRight( '🌷🍕' );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","group":"var collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar groups = [ 'b', 'b', 'f', 'b' ];\nvar out = group( collection, groups )\ngroups = [ 1, 1, 2, 1 ];\nout = group( collection, groups )\ngroups = [ 'b', 'b', 'f', 'b' ];\nvar opts = { 'returns': 'indices' };\nout = group( collection, opts, groups )\nopts = { 'returns': '*' };\nout = group( collection, opts, groups )\n","groupBy":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n     return 'b';\n }\n return 'other';\n };\nvar collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar out = groupBy( collection, indicator )\nvar opts = { 'returns': 'indices' };\nout = groupBy( collection, opts, indicator )\nopts = { 'returns': '*' };\nout = groupBy( collection, opts, indicator )\n","groupByAsync":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\ngroupByAsync( arr, indicator, done )\nvar opts = { 'returns': 'indices' };\ngroupByAsync( arr, opts, indicator, done )\nopts = { 'returns': '*' };\ngroupByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\ngroupByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\ngroupByAsync( arr, opts, indicator, done )\n","groupByAsync.factory":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) );\n }\n };\nvar opts = { 'series': true };\nvar f = groupByAsync.factory( opts, indicator );\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","groupIn":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n     return 'b';\n }\n return 'other';\n };\nfunction Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\nFoo.prototype = Object.create( null );\nFoo.prototype.c = 'foo';\nFoo.prototype.d = 'bar';\nvar obj = new Foo();\nvar out = groupIn( obj, indicator )\nvar opts = { 'returns': 'keys' };\nout = groupIn( obj, opts, indicator )\nopts = { 'returns': '*' };\nout = groupIn( obj, opts, indicator )\n","groupOwn":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n     return 'b';\n }\n return 'other';\n };\nvar obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\nvar out = groupOwn( obj, indicator )\nvar opts = { 'returns': 'keys' };\nout = groupOwn( obj, opts, indicator )\nopts = { 'returns': '*' };\nout = groupOwn( obj, opts, indicator )\n","gswap":"var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\ngswap( x, y );\nx.data\ny.data\nx = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\ny = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\ngswap( x, y );\nx\ny\n","HALF_LN2":"HALF_LN2\n","HALF_PI":"HALF_PI\n","HARRISON_BOSTON_HOUSE_PRICES":"var data = HARRISON_BOSTON_HOUSE_PRICES()\n","HARRISON_BOSTON_HOUSE_PRICES_CORRECTED":"var data = HARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n","hasArrayBufferSupport":"var bool = hasArrayBufferSupport()\n","hasArrowFunctionSupport":"var bool = hasArrowFunctionSupport()\n","hasAsyncAwaitSupport":"var bool = hasAsyncAwaitSupport()\n","hasAsyncIteratorSymbolSupport":"var bool = hasAsyncIteratorSymbolSupport()\n","hasAtobSupport":"var bool = hasAtobSupport()\n","hasBigInt64ArraySupport":"var bool = hasBigInt64ArraySupport()\n","hasBigIntSupport":"var bool = hasBigIntSupport()\n","hasBigUint64ArraySupport":"var bool = hasBigUint64ArraySupport()\n","hasBtoaSupport":"var bool = hasBtoaSupport()\n","hasClassSupport":"var bool = hasClassSupport()\n","hasDataViewSupport":"var bool = hasDataViewSupport()\n","hasDefinePropertiesSupport":"var bool = hasDefinePropertiesSupport()\n","hasDefinePropertySupport":"var bool = hasDefinePropertySupport()\n","hasFloat32ArraySupport":"var bool = hasFloat32ArraySupport()\n","hasFloat64ArraySupport":"var bool = hasFloat64ArraySupport()\n","hasFunctionNameSupport":"var bool = hasFunctionNameSupport()\n","hasGeneratorSupport":"var bool = hasGeneratorSupport()\n","hasGlobalThisSupport":"var bool = hasGlobalThisSupport()\n","hasInt8ArraySupport":"var bool = hasInt8ArraySupport()\n","hasInt16ArraySupport":"var bool = hasInt16ArraySupport()\n","hasInt32ArraySupport":"var bool = hasInt32ArraySupport()\n","hasIteratorSymbolSupport":"var bool = hasIteratorSymbolSupport()\n","hasMapSupport":"var bool = hasMapSupport()\n","hasNodeBufferSupport":"var bool = hasNodeBufferSupport()\n","hasOwnProp":"var beep = { 'boop': true };\nvar bool = hasOwnProp( beep, 'boop' )\nbool = hasOwnProp( beep, 'bop' )\n","hasProp":"var beep = { 'boop': true };\nvar bool = hasProp( beep, 'boop' )\nbool = hasProp( beep, 'toString' )\nbool = hasProp( beep, 'bop' )\n","hasProxySupport":"var bool = hasProxySupport()\n","hasSetSupport":"var bool = hasSetSupport()\n","hasSharedArrayBufferSupport":"var bool = hasSharedArrayBufferSupport()\n","hasSymbolSupport":"var bool = hasSymbolSupport()\n","hasToStringTagSupport":"var bool = hasToStringTagSupport()\n","hasUint8ArraySupport":"var bool = hasUint8ArraySupport()\n","hasUint8ClampedArraySupport":"var bool = hasUint8ClampedArraySupport()\n","hasUint16ArraySupport":"var bool = hasUint16ArraySupport()\n","hasUint32ArraySupport":"var bool = hasUint32ArraySupport()\n","hasUTF16SurrogatePairAt":"var out = hasUTF16SurrogatePairAt( '🌷', 0 )\nout = hasUTF16SurrogatePairAt( '🌷', 1 )\n","hasWeakMapSupport":"var bool = hasWeakMapSupport()\n","hasWeakSetSupport":"var bool = hasWeakSetSupport()\n","hasWebAssemblySupport":"var bool = hasWebAssemblySupport()\n","headercase":"var out = headercase( 'Hello World!' )\nout = headercase( 'beep boop' )\n","HERNDON_VENUS_SEMIDIAMETERS":"var d = HERNDON_VENUS_SEMIDIAMETERS()\n","homedir":"var home = homedir()\n","HOURS_IN_DAY":"var days = 3.14;\nvar hrs = days * HOURS_IN_DAY\n","HOURS_IN_WEEK":"var wks = 3.14;\nvar hrs = wks * HOURS_IN_WEEK\n","hoursInMonth":"var num = hoursInMonth()\nnum = hoursInMonth( 2 )\nnum = hoursInMonth( 2, 2016 )\nnum = hoursInMonth( 2, 2017 )\nnum = hoursInMonth( 'feb', 2016 )\nnum = hoursInMonth( 'february', 2016 )\n","hoursInYear":"var num = hoursInYear()\nnum = hoursInYear( 2016 )\nnum = hoursInYear( 2017 )\n","httpServer":"var createServer = httpServer()\nfunction onRequest( request, response ) {\nconsole.log( request.url );\nresponse.end( 'OK' );\n };\ncreateServer = httpServer( onRequest )\nvar opts = { 'port': 7331 };\ncreateServer = httpServer( opts )\n","identity":"var v = identity( 3.14 )\n","ifelse":"var z = ifelse( true, 1.0, -1.0 )\nz = ifelse( false, 1.0, -1.0 )\n","ifelseAsync":"function predicate( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n     clbk( null, true );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nifelseAsync( predicate, 'beep', 'boop', done )\n","ifthen":"function x() { return 1.0; };\nfunction y() { return -1.0; };\nvar z = ifthen( true, x, y )\nz = ifthen( false, x, y )\n","ifthenAsync":"function predicate( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n     clbk( null, false );\n }\n };\nfunction x( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n     clbk( null, 'beep' );\n }\n };\nfunction y( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n     clbk( null, 'boop' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nifthenAsync( predicate, x, y, done )\n","imag":"var z = new Complex128( 5.0, 3.0 );\nvar im = imag( z )\n","imagf":"var z = new Complex64( 5.0, 3.0 );\nvar im = imagf( z )\n","IMG_ACANTHUS_MOLLIS":"var img = IMG_ACANTHUS_MOLLIS()\n","IMG_AIRPLANE_FROM_ABOVE":"var img = IMG_AIRPLANE_FROM_ABOVE()\n","IMG_ALLIUM_OREOPHILUM":"var img = IMG_ALLIUM_OREOPHILUM()\n","IMG_BLACK_CANYON":"var img = IMG_BLACK_CANYON()\n","IMG_DUST_BOWL_HOME":"var img = IMG_DUST_BOWL_HOME()\n","IMG_FRENCH_ALPINE_LANDSCAPE":"var img = IMG_FRENCH_ALPINE_LANDSCAPE()\n","IMG_LOCOMOTION_HOUSE_CAT":"var img = IMG_LOCOMOTION_HOUSE_CAT()\n","IMG_LOCOMOTION_NUDE_MALE":"var img = IMG_LOCOMOTION_NUDE_MALE()\n","IMG_MARCH_PASTORAL":"var img = IMG_MARCH_PASTORAL()\n","IMG_NAGASAKI_BOATS":"var img = IMG_NAGASAKI_BOATS()\n","incrapcorr":"var accumulator = incrapcorr();\nvar ar = accumulator()\nar = accumulator( 2.0, 1.0 )\nar = accumulator( -5.0, 3.14 )\nar = accumulator()\n","incrBinaryClassification":"var opts = {};\nopts.intercept = true;\nopts.lambda = 1.0e-5;\nvar acc = incrBinaryClassification( 3, opts );\nvar buf = new Float64Array( [ 2.3, 1.0, 5.0 ] );\nvar x = array( buf );\nvar coefs = acc( x, 1 )\nbuf = new Float64Array( [ 2.3, 5.3, 8.6 ] );\nx = array( buf );\nvar yhat = acc.predict( x )\n","incrcount":"var accumulator = incrcount();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrcovariance":"var accumulator = incrcovariance();\nvar v = accumulator()\nv = accumulator( 2.0, 1.0 )\nv = accumulator( -5.0, 3.14 )\nv = accumulator()\n","incrcovmat":"var accumulator = incrcovmat( 2 );\nvar out = accumulator()\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v )\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v )\nout = accumulator()\n","incrcv":"var accumulator = incrcv();\nvar cv = accumulator()\ncv = accumulator( 2.0 )\ncv = accumulator( 1.0 )\ncv = accumulator()\n","increwmean":"var accumulator = increwmean( 0.5 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","increwstdev":"var accumulator = increwstdev( 0.5 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","increwvariance":"var accumulator = increwvariance( 0.5 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrgmean":"var accumulator = incrgmean();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrgrubbs":"var acc = incrgrubbs();\nvar res = acc()\nfor ( var i = 0; i < 200; i++ ) {\n res = acc( base.random.normal( 10.0, 5.0 ) );\n };\nres.print()\n","incrhmean":"var accumulator = incrhmean();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrkmeans":"var accumulator = incrkmeans( 5, 2 );\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v );\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v );\n","incrkurtosis":"var accumulator = incrkurtosis();\nvar v = accumulator( 2.0 )\nv = accumulator( 2.0 )\nv = accumulator( -4.0 )\nv = accumulator( -4.0 )\n","incrmaape":"var accumulator = incrmaape();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator()\n","incrmae":"var accumulator = incrmae();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator()\n","incrmapcorr":"var accumulator = incrmapcorr( 3 );\nvar ar = accumulator()\nar = accumulator( 2.0, 1.0 )\nar = accumulator( -5.0, 3.14 )\nar = accumulator( 3.0, -1.0 )\nar = accumulator( 5.0, -9.5 )\nar = accumulator()\n","incrmape":"var accumulator = incrmape();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator()\n","incrmax":"var accumulator = incrmax();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrmaxabs":"var accumulator = incrmaxabs();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrmcovariance":"var accumulator = incrmcovariance( 3 );\nvar v = accumulator()\nv = accumulator( 2.0, 1.0 )\nv = accumulator( -5.0, 3.14 )\nv = accumulator( 3.0, -1.0 )\nv = accumulator( 5.0, -9.5 )\nv = accumulator()\n","incrmcv":"var accumulator = incrmcv( 3 );\nvar cv = accumulator()\ncv = accumulator( 2.0 )\ncv = accumulator( 1.0 )\ncv = accumulator( 3.0 )\ncv = accumulator( 7.0 )\ncv = accumulator()\n","incrmda":"var accumulator = incrmda();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 4.0 )\nm = accumulator()\n","incrme":"var accumulator = incrme();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator()\n","incrmean":"var accumulator = incrmean();\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator()\n","incrmeanabs":"var accumulator = incrmeanabs();\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator()\n","incrmeanabs2":"var accumulator = incrmeanabs2();\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator()\n","incrmeanstdev":"var accumulator = incrmeanstdev();\nvar ms = accumulator()\nms = accumulator( 2.0 )\nms = accumulator( -5.0 )\nms = accumulator( 3.0 )\nms = accumulator( 5.0 )\nms = accumulator()\n","incrmeanvar":"var accumulator = incrmeanvar();\nvar mv = accumulator()\nmv = accumulator( 2.0 )\nmv = accumulator( -5.0 )\nmv = accumulator( 3.0 )\nmv = accumulator( 5.0 )\nmv = accumulator()\n","incrmgmean":"var accumulator = incrmgmean( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmgrubbs":"var acc = incrmgrubbs( 20 );\nvar res = acc()\nfor ( var i = 0; i < 200; i++ ) {\n res = acc( base.random.normal( 10.0, 5.0 ) );\n };\nres.print()\n","incrmhmean":"var accumulator = incrmhmean( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmidrange":"var accumulator = incrmidrange();\nvar v = accumulator()\nv = accumulator( 3.14 )\nv = accumulator( -5.0 )\nv = accumulator( 10.1 )\nv = accumulator()\n","incrmin":"var accumulator = incrmin();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrminabs":"var accumulator = incrminabs();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrminmax":"var accumulator = incrminmax();\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrminmaxabs":"var accumulator = incrminmaxabs();\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrmmaape":"var accumulator = incrmmaape( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 2.0, 5.0 )\nm = accumulator()\n","incrmmae":"var accumulator = incrmmae( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 5.0, -2.0 )\nm = accumulator()\n","incrmmape":"var accumulator = incrmmape( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 2.0, 5.0 )\nm = accumulator()\n","incrmmax":"var accumulator = incrmmax( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmmaxabs":"var accumulator = incrmmaxabs( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmmda":"var accumulator = incrmmda( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 4.0, 5.0 )\nm = accumulator()\n","incrmme":"var accumulator = incrmme( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 5.0, -2.0 )\nm = accumulator()\n","incrmmean":"var accumulator = incrmmean( 3 );\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator( 3.0 )\nmu = accumulator( 5.0 )\nmu = accumulator()\n","incrmmeanabs":"var accumulator = incrmmeanabs( 3 );\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator( 3.0 )\nmu = accumulator( 5.0 )\nmu = accumulator()\n","incrmmeanabs2":"var accumulator = incrmmeanabs2( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmmeanstdev":"var accumulator = incrmmeanstdev( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmmeanvar":"var accumulator = incrmmeanvar( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmmidrange":"var accumulator = incrmmidrange( 3 );\nvar mr = accumulator()\nmr = accumulator( 2.0 )\nmr = accumulator( -5.0 )\nmr = accumulator( 3.0 )\nmr = accumulator( 5.0 )\nmr = accumulator()\n","incrmmin":"var accumulator = incrmmin( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmminabs":"var accumulator = incrmminabs( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmminmax":"var accumulator = incrmminmax( 3 );\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrmminmaxabs":"var accumulator = incrmminmaxabs( 3 );\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrmmpe":"var accumulator = incrmmpe( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 2.0, 5.0 )\nm = accumulator()\n","incrmmse":"var accumulator = incrmmse( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 5.0, -2.0 )\nm = accumulator()\n","incrmpcorr":"var accumulator = incrmpcorr( 3 );\nvar r = accumulator()\nr = accumulator( 2.0, 1.0 )\nr = accumulator( -5.0, 3.14 )\nr = accumulator( 3.0, -1.0 )\nr = accumulator( 5.0, -9.5 )\nr = accumulator()\n","incrmpcorr2":"var accumulator = incrmpcorr2( 3 );\nvar r2 = accumulator()\nr2 = accumulator( 2.0, 1.0 )\nr2 = accumulator( -5.0, 3.14 )\nr2 = accumulator( 3.0, -1.0 )\nr2 = accumulator( 5.0, -9.5 )\nr2 = accumulator()\n","incrmpcorrdist":"var accumulator = incrmpcorrdist( 3 );\nvar d = accumulator()\nd = accumulator( 2.0, 1.0 )\nd = accumulator( -5.0, 3.14 )\nd = accumulator( 3.0, -1.0 )\nd = accumulator( 5.0, -9.5 )\nd = accumulator()\n","incrmpe":"var accumulator = incrmpe();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator()\n","incrmprod":"var accumulator = incrmprod( 3 );\nvar p = accumulator()\np = accumulator( 2.0 )\np = accumulator( -5.0 )\np = accumulator( 3.0 )\np = accumulator( 5.0 )\np = accumulator()\n","incrmrange":"var accumulator = incrmrange( 3 );\nvar r = accumulator()\nr = accumulator( 2.0 )\nr = accumulator( -5.0 )\nr = accumulator( 3.0 )\nr = accumulator( 5.0 )\nr = accumulator()\n","incrmrmse":"var accumulator = incrmrmse( 3 );\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator( 3.0, 2.0 )\nr = accumulator( 5.0, -2.0 )\nr = accumulator()\n","incrmrss":"var accumulator = incrmrss( 3 );\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator( 3.0, 2.0 )\nr = accumulator( 5.0, -2.0 )\nr = accumulator()\n","incrmse":"var accumulator = incrmse();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator()\n","incrmstdev":"var accumulator = incrmstdev( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( 5.0 )\ns = accumulator()\n","incrmsum":"var accumulator = incrmsum( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( 5.0 )\ns = accumulator()\n","incrmsumabs":"var accumulator = incrmsumabs( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrmsumabs2":"var accumulator = incrmsumabs2( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrmsummary":"var accumulator = incrmsummary( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrmsumprod":"var accumulator = incrmsumprod( 3 );\nvar s = accumulator()\ns = accumulator( 2.0, 3.0 )\ns = accumulator( -5.0, 2.0 )\ns = accumulator( 3.0, -2.0 )\ns = accumulator( 5.0, 3.0 )\ns = accumulator()\n","incrmvariance":"var accumulator = incrmvariance( 3 );\nvar s2 = accumulator()\ns2 = accumulator( 2.0 )\ns2 = accumulator( -5.0 )\ns2 = accumulator( 3.0 )\ns2 = accumulator( 5.0 )\ns2 = accumulator()\n","incrmvmr":"var accumulator = incrmvmr( 3 );\nvar F = accumulator()\nF = accumulator( 2.0 )\nF = accumulator( 1.0 )\nF = accumulator( 3.0 )\nF = accumulator( 7.0 )\nF = accumulator()\n","incrnancount":"var accumulator = incrnancount();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrnansum":"var accumulator = incrnansum();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( NaN )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrnansumabs":"var accumulator = incrnansumabs();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( NaN )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrnansumabs2":"var accumulator = incrnansumabs2();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( NaN )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrpcorr":"var accumulator = incrpcorr();\nvar r = accumulator()\nr = accumulator( 2.0, 1.0 )\nr = accumulator( -5.0, 3.14 )\nr = accumulator()\n","incrpcorr2":"var accumulator = incrpcorr2();\nvar r2 = accumulator()\nr2 = accumulator( 2.0, 1.0 )\nr2 = accumulator( -5.0, 3.14 )\nr2 = accumulator()\n","incrpcorrdist":"var accumulator = incrpcorrdist();\nvar d = accumulator()\nd = accumulator( 2.0, 1.0 )\nd = accumulator( -5.0, 3.14 )\nd = accumulator()\n","incrpcorrdistmat":"var accumulator = incrpcorrdistmat( 2 );\nvar out = accumulator()\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v )\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v )\nout = accumulator()\n","incrpcorrmat":"var accumulator = incrpcorrmat( 2 );\nvar out = accumulator()\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v )\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v )\nout = accumulator()\n","incrprod":"var accumulator = incrprod();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrrange":"var accumulator = incrrange();\nvar v = accumulator()\nv = accumulator( -2.0 )\nv = accumulator( 1.0 )\nv = accumulator( 3.0 )\nv = accumulator()\n","incrrmse":"var accumulator = incrrmse();\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator()\n","incrrss":"var accumulator = incrrss();\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator()\n","incrskewness":"var accumulator = incrskewness();\nvar v = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator( -10.0 )\nv = accumulator()\n","incrspace":"var arr = incrspace( 0, 11, 2 )\n","incrstdev":"var accumulator = incrstdev();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsum":"var accumulator = incrsum();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsumabs":"var accumulator = incrsumabs();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsumabs2":"var accumulator = incrsumabs2();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsummary":"var accumulator = incrsummary();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsumprod":"var accumulator = incrsumprod();\nvar s = accumulator()\ns = accumulator( 2.0, 3.0 )\ns = accumulator( -5.0, 2.0 )\ns = accumulator()\n","incrvariance":"var accumulator = incrvariance();\nvar s2 = accumulator()\ns2 = accumulator( 2.0 )\ns2 = accumulator( -5.0 )\ns2 = accumulator()\n","incrvmr":"var accumulator = incrvmr();\nvar D = accumulator()\nD = accumulator( 2.0 )\nD = accumulator( 1.0 )\nD = accumulator()\n","incrwmean":"var accumulator = incrwmean();\nvar mu = accumulator()\nmu = accumulator( 2.0, 1.0 )\nmu = accumulator( 2.0, 0.5 )\nmu = accumulator( 3.0, 1.5 )\nmu = accumulator()\n","ind2sub":"var d = [ 3, 3, 3 ];\nvar s = ind2sub( d, 17 )\n","ind2sub.assign":"var d = [ 3, 3, 3 ];\nvar out = [ 0, 0, 0 ];\nvar s = ind2sub.assign( d, 17, out )\nvar bool = ( s === out )\n","indexOf":"var arr = [ 4, 3, 2, 1 ];\nvar idx = indexOf( arr, 3 )\narr = [ 4, 3, 2, 1 ];\nidx = indexOf( arr, 5 )\narr = [ 1, 2, 3, 4, 5, 2, 6 ];\nidx = indexOf( arr, 2, 3 )\narr = [ 1, 2, 3, 4, 2, 5 ];\nidx = indexOf( arr, 2, 10 )\narr = [ 1, 2, 3, 4, 5, 2, 6, 2 ];\nidx = indexOf( arr, 2, -4 )\nidx = indexOf( arr, 2, -1 )\narr = [ 1, 2, 3, 4, 5, 2, 6 ];\nidx = indexOf( arr, 2, -10 )\nvar str = 'bebop';\nidx = indexOf( str, 'o' )\n","inherit":"function Foo() { return this; };\nFoo.prototype.beep = function beep() { return 'boop'; };\nfunction Bar() { Foo.call( this ); return this; };\ninherit( Bar, Foo );\nvar bar = new Bar();\nvar v = bar.beep()\n","inheritedEnumerableProperties":"var props = inheritedEnumerableProperties( {} )\n","inheritedEnumerablePropertySymbols":"var symbols = inheritedEnumerablePropertySymbols( [] )\n","inheritedKeys":"var keys = inheritedKeys( {} )\n","inheritedNonEnumerableProperties":"var props = inheritedNonEnumerableProperties( {} )\n","inheritedNonEnumerablePropertyNames":"var keys = inheritedNonEnumerablePropertyNames( {} )\n","inheritedNonEnumerablePropertySymbols":"var symbols = inheritedNonEnumerablePropertySymbols( [] )\n","inheritedProperties":"var symbols = inheritedProperties( [] )\n","inheritedPropertyDescriptor":"var desc = inheritedPropertyDescriptor( {}, 'toString' )\n","inheritedPropertyDescriptors":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar desc = inheritedPropertyDescriptors( obj )\n","inheritedPropertyNames":"var keys = inheritedPropertyNames( [] )\n","inheritedPropertySymbols":"var symbols = inheritedPropertySymbols( [] )\n","inheritedWritableProperties":"var props = inheritedWritableProperties( {} )\n","inheritedWritablePropertyNames":"var keys = inheritedWritablePropertyNames( {} )\n","inheritedWritablePropertySymbols":"var symbols = inheritedWritablePropertySymbols( [] )\n","inmap":"function foo( v, i ) { return v * i; };\nvar arr = [ 1.0, 2.0, 3.0 ];\nvar out = inmap( arr, foo )\nvar bool = ( out === arr )\n","inmapAsync":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n     throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 3000, 2500, 1000 ];\ninmapAsync( arr, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n     throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\ninmapAsync( arr, opts, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n     throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\ninmapAsync( arr, opts, fcn, done )\n","inmapAsync.factory":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, value*index );\n }\n };\nvar opts = { 'series': true };\nvar f = inmapAsync.factory( opts, fcn );\nfunction done( error, collection ) {\n if ( error ) {\n     throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","inmapRight":"function foo( v, i ) { console.log( '%s: %d', i, v ); return v * i; };\nvar arr = [ 1.0, 2.0, 3.0 ];\nvar out = inmapRight( arr, foo )\nvar bool = ( out === arr )\n","inmapRightAsync":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n     throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 1000, 2500, 3000 ];\ninmapRightAsync( arr, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n     throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\ninmapRightAsync( arr, opts, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n     throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\ninmapRightAsync( arr, opts, fcn, done )\n","inmapRightAsync.factory":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, value*index );\n }\n };\nvar opts = { 'series': true };\nvar f = inmapRightAsync.factory( opts, fcn );\nfunction done( error, collection ) {\n if ( error ) {\n     throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","inspectSinkStream":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectSinkStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectSinkStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = inspectSinkStream.factory( opts );\nfunction clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = createStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectSinkStream.objectMode":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectSinkStream.objectMode( clbk );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","inspectStream":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = inspectStream.factory( opts );\nfunction clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = createStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectStream.objectMode":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectStream.objectMode( clbk );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","instanceOf":"var bool = instanceOf( [], Array )\nbool = instanceOf( {}, Object )\nbool = instanceOf( null, Object )\n","INT8_MAX":"INT8_MAX\n","INT8_MIN":"INT8_MIN\n","INT8_NUM_BYTES":"INT8_NUM_BYTES\n","Int8Array":"var arr = new Int8Array()\nvar arr = new Int8Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Int8Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Int8Array( arr1 )\nvar buf = new ArrayBuffer( 4 );\nvar arr = new Int8Array( buf, 0, 4 )\n","Int8Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Int8Array.from( [ 1, 2 ], mapFcn )\n","Int8Array.of":"var arr = Int8Array.of( 1, 2 )\n","Int8Array.BYTES_PER_ELEMENT":"Int8Array.BYTES_PER_ELEMENT\n","Int8Array.name":"Int8Array.name\n","Int8Array.prototype.buffer":"var arr = new Int8Array( 5 );\narr.buffer\n","Int8Array.prototype.byteLength":"var arr = new Int8Array( 5 );\narr.byteLength\n","Int8Array.prototype.byteOffset":"var arr = new Int8Array( 5 );\narr.byteOffset\n","Int8Array.prototype.BYTES_PER_ELEMENT":"var arr = new Int8Array( 5 );\narr.BYTES_PER_ELEMENT\n","Int8Array.prototype.length":"var arr = new Int8Array( 5 );\narr.length\n","Int8Array.prototype.copyWithin":"var arr = new Int8Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Int8Array.prototype.entries":"var arr = new Int8Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Int8Array.prototype.every":"var arr = new Int8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Int8Array.prototype.fill":"var arr = new Int8Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Int8Array.prototype.filter":"var arr1 = new Int8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Int8Array.prototype.find":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Int8Array.prototype.findIndex":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Int8Array.prototype.forEach":"var arr = new Int8Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Int8Array.prototype.includes":"var arr = new Int8Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Int8Array.prototype.indexOf":"var arr = new Int8Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Int8Array.prototype.join":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Int8Array.prototype.keys":"var arr = new Int8Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Int8Array.prototype.lastIndexOf":"var arr = new Int8Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Int8Array.prototype.map":"var arr1 = new Int8Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Int8Array.prototype.reduce":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Int8Array.prototype.reduceRight":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Int8Array.prototype.reverse":"var arr = new Int8Array( [ 1, 2, 3 ] )\narr.reverse()\n","Int8Array.prototype.set":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Int8Array.prototype.slice":"var arr1 = new Int8Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Int8Array.prototype.some":"var arr = new Int8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Int8Array.prototype.sort":"var arr = new Int8Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Int8Array.prototype.subarray":"var arr1 = new Int8Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Int8Array.prototype.toLocaleString":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Int8Array.prototype.toString":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.toString()\n","Int8Array.prototype.values":"var arr = new Int8Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","INT16_MAX":"INT16_MAX\n","INT16_MIN":"INT16_MIN\n","INT16_NUM_BYTES":"INT16_NUM_BYTES\n","Int16Array":"var arr = new Int16Array()\nvar arr = new Int16Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Int16Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Int16Array( arr1 )\nvar buf = new ArrayBuffer( 8 );\nvar arr = new Int16Array( buf, 0, 4 )\n","Int16Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Int16Array.from( [ 1, 2 ], mapFcn )\n","Int16Array.of":"var arr = Int16Array.of( 1, 2 )\n","Int16Array.BYTES_PER_ELEMENT":"Int16Array.BYTES_PER_ELEMENT\n","Int16Array.name":"Int16Array.name\n","Int16Array.prototype.buffer":"var arr = new Int16Array( 5 );\narr.buffer\n","Int16Array.prototype.byteLength":"var arr = new Int16Array( 5 );\narr.byteLength\n","Int16Array.prototype.byteOffset":"var arr = new Int16Array( 5 );\narr.byteOffset\n","Int16Array.prototype.BYTES_PER_ELEMENT":"var arr = new Int16Array( 5 );\narr.BYTES_PER_ELEMENT\n","Int16Array.prototype.length":"var arr = new Int16Array( 5 );\narr.length\n","Int16Array.prototype.copyWithin":"var arr = new Int16Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Int16Array.prototype.entries":"var arr = new Int16Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Int16Array.prototype.every":"var arr = new Int16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Int16Array.prototype.fill":"var arr = new Int16Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Int16Array.prototype.filter":"var arr1 = new Int16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Int16Array.prototype.find":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Int16Array.prototype.findIndex":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Int16Array.prototype.forEach":"var arr = new Int16Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Int16Array.prototype.includes":"var arr = new Int16Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Int16Array.prototype.indexOf":"var arr = new Int16Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Int16Array.prototype.join":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Int16Array.prototype.keys":"var arr = new Int16Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Int16Array.prototype.lastIndexOf":"var arr = new Int16Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Int16Array.prototype.map":"var arr1 = new Int16Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Int16Array.prototype.reduce":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Int16Array.prototype.reduceRight":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Int16Array.prototype.reverse":"var arr = new Int16Array( [ 1, 2, 3 ] )\narr.reverse()\n","Int16Array.prototype.set":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Int16Array.prototype.slice":"var arr1 = new Int16Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Int16Array.prototype.some":"var arr = new Int16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Int16Array.prototype.sort":"var arr = new Int16Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Int16Array.prototype.subarray":"var arr1 = new Int16Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Int16Array.prototype.toLocaleString":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Int16Array.prototype.toString":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.toString()\n","Int16Array.prototype.values":"var arr = new Int16Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","INT32_MAX":"INT32_MAX\n","INT32_MIN":"INT32_MIN\n","INT32_NUM_BYTES":"INT32_NUM_BYTES\n","Int32Array":"var arr = new Int32Array()\nvar arr = new Int32Array( 5 )\nvar arr1 = new Int16Array( [ 5, 5, 5 ] );\nvar arr2 = new Int32Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Int32Array( arr1 )\nvar buf = new ArrayBuffer( 16 );\nvar arr = new Int32Array( buf, 0, 4 )\n","Int32Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Int32Array.from( [ 1, 2 ], mapFcn )\n","Int32Array.of":"var arr = Int32Array.of( 1, 2 )\n","Int32Array.BYTES_PER_ELEMENT":"Int32Array.BYTES_PER_ELEMENT\n","Int32Array.name":"Int32Array.name\n","Int32Array.prototype.buffer":"var arr = new Int32Array( 5 );\narr.buffer\n","Int32Array.prototype.byteLength":"var arr = new Int32Array( 5 );\narr.byteLength\n","Int32Array.prototype.byteOffset":"var arr = new Int32Array( 5 );\narr.byteOffset\n","Int32Array.prototype.BYTES_PER_ELEMENT":"var arr = new Int32Array( 5 );\narr.BYTES_PER_ELEMENT\n","Int32Array.prototype.length":"var arr = new Int32Array( 5 );\narr.length\n","Int32Array.prototype.copyWithin":"var arr = new Int32Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Int32Array.prototype.entries":"var arr = new Int32Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Int32Array.prototype.every":"var arr = new Int32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Int32Array.prototype.fill":"var arr = new Int32Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Int32Array.prototype.filter":"var arr1 = new Int32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Int32Array.prototype.find":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Int32Array.prototype.findIndex":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Int32Array.prototype.forEach":"var arr = new Int32Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Int32Array.prototype.includes":"var arr = new Int32Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Int32Array.prototype.indexOf":"var arr = new Int32Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Int32Array.prototype.join":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Int32Array.prototype.keys":"var arr = new Int32Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Int32Array.prototype.lastIndexOf":"var arr = new Int32Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Int32Array.prototype.map":"var arr1 = new Int32Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Int32Array.prototype.reduce":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Int32Array.prototype.reduceRight":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Int32Array.prototype.reverse":"var arr = new Int32Array( [ 1, 2, 3 ] )\narr.reverse()\n","Int32Array.prototype.set":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Int32Array.prototype.slice":"var arr1 = new Int32Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Int32Array.prototype.some":"var arr = new Int32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Int32Array.prototype.sort":"var arr = new Int32Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Int32Array.prototype.subarray":"var arr1 = new Int32Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Int32Array.prototype.toLocaleString":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Int32Array.prototype.toString":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.toString()\n","Int32Array.prototype.values":"var arr = new Int32Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","IS_BIG_ENDIAN":"IS_BIG_ENDIAN\n","IS_BROWSER":"IS_BROWSER\n","IS_DARWIN":"IS_DARWIN\n","IS_DOCKER":"IS_DOCKER\n","IS_ELECTRON":"IS_ELECTRON\n","IS_ELECTRON_MAIN":"IS_ELECTRON_MAIN\n","IS_ELECTRON_RENDERER":"IS_ELECTRON_RENDERER\n","IS_LITTLE_ENDIAN":"IS_LITTLE_ENDIAN\n","IS_MOBILE":"IS_MOBILE\n","IS_NODE":"IS_NODE\n","IS_TOUCH_DEVICE":"IS_TOUCH_DEVICE\n","IS_WEB_WORKER":"IS_WEB_WORKER\n","IS_WINDOWS":"IS_WINDOWS\n","isAbsoluteHttpURI":"var bool = isAbsoluteHttpURI( 'http://example.com/' )\nbool = isAbsoluteHttpURI( 'example.com' )\nbool = isAbsoluteHttpURI( 'foo@bar.com' )\n","isAbsolutePath":"var bool = isAbsolutePath( 'C:\\\\foo\\\\bar\\\\baz' )\nbool = isAbsolutePath( '/foo/bar/baz' )\n","isAbsolutePath.posix":"var bool = isAbsolutePath.posix( '/foo/bar/baz' )\nbool = isAbsolutePath.posix( 'foo/bar/baz' )\n","isAbsolutePath.win32":"var bool = isAbsolutePath.win32( 'C:\\\\foo\\\\bar\\\\baz' )\nbool = isAbsolutePath.win32( 'foo\\\\bar\\\\baz' )\n","isAbsoluteURI":"var bool = isAbsoluteURI( 'http://example.com/' )\nbool = isAbsoluteURI( 'example.com' )\nbool = isAbsoluteURI( 'foo@bar.com' )\n","isAccessorArray":"var bool = isAccessorArray( new Complex64Array( 10 ) )\nbool = isAccessorArray( [] )\nbool = isAccessorArray( { 'length': 0 } )\nbool = isAccessorArray( {} )\n","isAccessorProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isAccessorProperty( obj, 'boop' )\nbool = isAccessorProperty( obj, 'beep' )\n","isAccessorPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isAccessorPropertyIn( obj, 'boop' )\nbool = isAccessorPropertyIn( obj, 'beep' )\n","isAlphagram":"var out = isAlphagram( 'beep' )\nout = isAlphagram( 'zba' )\nout = isAlphagram( '' )\n","isAlphaNumeric":"var bool = isAlphaNumeric( 'abc0123456789' )\nbool = isAlphaNumeric( 'abcdef' )\nbool = isAlphaNumeric( '0xff' )\nbool = isAlphaNumeric( '' )\n","isAnagram":"var str1 = 'I am a weakish speller';\nvar str2 = 'William Shakespeare';\nvar bool = isAnagram( str1, str2 )\nbool = isAnagram( 'bat', 'tabba' )\n","isArguments":"function foo() { return arguments; };\nvar bool = isArguments( foo() )\nbool = isArguments( [] )\n","isArray":"var bool = isArray( [] )\nbool = isArray( {} )\n","isArrayArray":"var bool = isArrayArray( [ [], [] ] )\nbool = isArrayArray( [ {}, {} ] )\nbool = isArrayArray( [] )\n","isArrayBuffer":"var bool = isArrayBuffer( new ArrayBuffer( 10 ) )\nbool = isArrayBuffer( [] )\n","isArrayBufferView":"var bool = isArrayBufferView( new Int8Array() )\nbool = isArrayBufferView( [] )\n","isArrayLength":"var bool = isArrayLength( 5 )\nbool = isArrayLength( 2.0e200 )\nbool = isArrayLength( -3.14 )\nbool = isArrayLength( null )\n","isArrayLike":"var bool = isArrayLike( [] )\nbool = isArrayLike( { 'length': 10 } )\nbool = isArrayLike( 'beep' )\nbool = isArrayLike( null )\n","isArrayLikeObject":"var bool = isArrayLikeObject( [] )\nbool = isArrayLikeObject( { 'length': 10 } )\nbool = isArrayLikeObject( 'beep' )\n","isArrowFunction":"function beep() {};\nvar bool = isArrowFunction( beep )\nbool = isArrowFunction( {} )\n","isASCII":"var str = 'beep boop';\nvar bool = isASCII( str )\nbool = isASCII( fromCodePoint( 130 ) )\n","isBetween":"var bool = isBetween( 3.14, 3.0, 4.0 )\nbool = isBetween( 3.0, 3.0, 4.0 )\nbool = isBetween( 4.0, 3.0, 4.0 )\nbool = isBetween( 3.0, 3.14, 4.0 )\nbool = isBetween( 3.14, 3.14, 4.0, 'open', 'closed' )\nbool = isBetween( 3.14, 3.0, 3.14, 'closed', 'open' )\n","isBetweenArray":"var arr = [ 3.0, 3.14, 4.0 ];\nvar bool = isBetweenArray( arr, 3.0, 4.0 )\nbool = isBetweenArray( arr, 3.14, 4.0 )\nbool = isBetweenArray( arr, 3.0, 3.14 )\nbool = isBetweenArray( arr, 3.0, 4.0, 'open', 'closed' )\nbool = isBetweenArray( arr, 3.0, 4.0, 'closed', 'open' )\n","isBigInt":"var bool = isBigInt( BigInt( '1' ) )\nbool = isBigInt( Object( BigInt( '1' ) ) )\nbool = isBigInt( {} )\nbool = isBigInt( null )\nbool = isBigInt( true )\n","isBigInt64Array":"var bool = isBigInt64Array( new BigInt64Array( 10 ) )\nbool = isBigInt64Array( [] )\n","isBigUint64Array":"var bool = isBigUint64Array( new BigUint64Array( 10 ) )\nbool = isBigUint64Array( [] )\n","isBinaryString":"var bool = isBinaryString( '1000101' )\nbool = isBinaryString( 'beep' )\nbool = isBinaryString( '' )\n","isBlankString":"var bool = isBlankString( '   ' )\nbool = isBlankString( 'beep' )\nbool = isBlankString( null )\n","isBoolean":"var bool = isBoolean( false )\nbool = isBoolean( new Boolean( false ) )\n","isBoolean.isPrimitive":"var bool = isBoolean.isPrimitive( true )\nbool = isBoolean.isPrimitive( false )\nbool = isBoolean.isPrimitive( new Boolean( true ) )\n","isBoolean.isObject":"var bool = isBoolean.isObject( true )\nbool = isBoolean.isObject( new Boolean( false ) )\n","isBooleanArray":"var bool = isBooleanArray( [ true, false, true ] )\nbool = isBooleanArray( [ true, 'abc', false ] )\n","isBooleanArray.primitives":"var bool = isBooleanArray.primitives( [ true, false ] )\nbool = isBooleanArray.primitives( [ false, new Boolean( true ) ] )\n","isBooleanArray.objects":"var bool = isBooleanArray.objects( [ new Boolean( false ), true ] )\nbool = isBooleanArray.objects( [ new Boolean( false ), new Boolean( true ) ] )\n","isBoxedPrimitive":"var bool = isBoxedPrimitive( new Boolean( false ) )\nbool = isBoxedPrimitive( true )\n","isBuffer":"var bool = isBuffer( new Buffer( 'beep' ) )\nbool = isBuffer( new Buffer( [ 1, 2, 3, 4 ] ) )\nbool = isBuffer( {} )\nbool = isBuffer( [] )\n","isCamelcase":"var bool = isCamelcase( 'helloWorld' )\nbool = isCamelcase( 'hello world' )\n","isCapitalized":"var bool = isCapitalized( 'Hello' )\nbool = isCapitalized( 'world' )\n","isCentrosymmetricMatrix":"var buf = [ 2, 1, 1, 2 ];\nvar M = ndarray( 'generic', buf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\nvar bool = isCentrosymmetricMatrix( M )\nbool = isCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isCentrosymmetricMatrix( 3.14 )\nbool = isCentrosymmetricMatrix( {} )\n","isCircular":"var obj = { 'beep': 'boop' };\nobj.self = obj;\nvar bool = isCircular( obj )\nbool = isCircular( {} )\nbool = isCircular( null )\n","isCircularArray":"var arr = [ 1, 2, 3 ];\narr.push( arr );\nvar bool = isCircularArray( arr )\nbool = isCircularArray( [] )\nbool = isCircularArray( null )\n","isCircularPlainObject":"var obj = { 'beep': 'boop' };\nobj.self = obj;\nvar bool = isCircularPlainObject( obj )\nbool = isCircularPlainObject( {} )\nbool = isCircularPlainObject( null )\n","isClass":"var bool = isClass( class Person {} )\nbool = isClass( function Person() {} )\nbool = isClass( {} )\nbool = isClass( null )\nbool = isClass( true )\n","isCollection":"var bool = isCollection( [] )\nbool = isCollection( { 'length': 0 } )\nbool = isCollection( {} )\n","isComplex":"var bool = isComplex( new Complex64( 2.0, 2.0 ) )\nbool = isComplex( new Complex128( 3.0, 1.0 ) )\nbool = isComplex( 3.14 )\nbool = isComplex( {} )\n","isComplex64":"var bool = isComplex64( new Complex64( 2.0, 2.0 ) )\nbool = isComplex64( new Complex128( 3.0, 1.0 ) )\nbool = isComplex64( 3.14 )\nbool = isComplex64( {} )\n","isComplex64Array":"var bool = isComplex64Array( new Complex64Array( 10 ) )\nbool = isComplex64Array( [] )\n","isComplex64MatrixLike":"var M = {};\nM.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex64MatrixLike( M )\nbool = isComplex64MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isComplex64MatrixLike( 3.14 )\nbool = isComplex64MatrixLike( {} )\n","isComplex64ndarrayLike":"var M = {};\nM.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex64ndarrayLike( M )\nbool = isComplex64ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isComplex64ndarrayLike( 3.14 )\nbool = isComplex64ndarrayLike( {} )\n","isComplex64VectorLike":"var M = {};\nM.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex64VectorLike( M )\nbool = isComplex64VectorLike( [ 1, 2, 3, 4 ] )\nbool = isComplex64VectorLike( 3.14 )\nbool = isComplex64VectorLike( {} )\n","isComplex128":"var bool = isComplex128( new Complex128( 3.0, 1.0 ) )\nbool = isComplex128( new Complex64( 2.0, 2.0 ) )\nbool = isComplex128( 3.14 )\nbool = isComplex128( {} )\n","isComplex128Array":"var bool = isComplex128Array( new Complex128Array( 10 ) )\nbool = isComplex128Array( [] )\n","isComplex128MatrixLike":"var M = {};\nM.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex128';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex128MatrixLike( M )\nbool = isComplex128MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isComplex128MatrixLike( 3.14 )\nbool = isComplex128MatrixLike( {} )\n","isComplex128ndarrayLike":"var M = {};\nM.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex128';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex128ndarrayLike( M )\nbool = isComplex128ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isComplex128ndarrayLike( 3.14 )\nbool = isComplex128ndarrayLike( {} )\n","isComplex128VectorLike":"var M = {};\nM.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex128';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex128VectorLike( M )\nbool = isComplex128VectorLike( [ 1, 2, 3, 4 ] )\nbool = isComplex128VectorLike( 3.14 )\nbool = isComplex128VectorLike( {} )\n","isComplexLike":"var bool = isComplexLike( new Complex64( 2.0, 2.0 ) )\nbool = isComplexLike( new Complex128( 3.0, 1.0 ) )\nbool = isComplexLike( 3.14 )\nbool = isComplexLike( {} )\n","isComplexTypedArray":"var bool = isComplexTypedArray( new Complex64Array( 10 ) )\n","isComplexTypedArrayLike":"var bool = isComplexTypedArrayLike( new Complex128Array() )\nbool = isComplexTypedArrayLike({\n'length': 10,\n'byteOffset': 0,\n'byteLength': 10,\n'BYTES_PER_ELEMENT': 4,\n'get': function get() {},\n'set': function set() {}\n })\n","isComposite":"var bool = isComposite( 4.0 )\nbool = isComposite( new Number( 4.0 ) )\nbool = isComposite( 3.14 )\nbool = isComposite( -4.0 )\nbool = isComposite( null )\n","isComposite.isPrimitive":"var bool = isComposite.isPrimitive( 4.0 )\nbool = isComposite.isPrimitive( new Number( 4.0 ) )\n","isComposite.isObject":"var bool = isComposite.isObject( 4.0 )\nbool = isComposite.isObject( new Number( 4.0 ) )\n","isConfigurableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isConfigurableProperty( obj, 'boop' )\nbool = isConfigurableProperty( obj, 'beep' )\n","isConfigurablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isConfigurablePropertyIn( obj, 'boop' )\nbool = isConfigurablePropertyIn( obj, 'beep' )\n","isConstantcase":"var bool = isConstantcase( 'BEEP_BOOP' )\nbool = isConstantcase( 'BEEP and BOOP' )\n","isCubeNumber":"var bool = isCubeNumber( 8.0 )\nbool = isCubeNumber( new Number( 8.0 ) )\nbool = isCubeNumber( 3.14 )\nbool = isCubeNumber( -5.0 )\nbool = isCubeNumber( null )\n","isCubeNumber.isPrimitive":"var bool = isCubeNumber.isPrimitive( 8.0 )\nbool = isCubeNumber.isPrimitive( new Number( 8.0 ) )\n","isCubeNumber.isObject":"var bool = isCubeNumber.isObject( 8.0 )\nbool = isCubeNumber.isObject( new Number( 8.0 ) )\n","isCurrentYear":"var bool = isCurrentYear( new Date() )\nbool = isCurrentYear( currentYear() )\nbool = isCurrentYear( 2021 )\nbool = isCurrentYear( null )\n","isDataProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isDataProperty( obj, 'boop' )\nbool = isDataProperty( obj, 'beep' )\n","isDataPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isDataPropertyIn( obj, 'boop' )\nbool = isDataPropertyIn( obj, 'beep' )\n","isDataView":"var buf = new ArrayBuffer( 10 );\nvar bool = isDataView( new DataView( buf ) )\nbool = isDataView( [] )\n","isDateObject":"var bool = isDateObject( new Date() )\nbool = isDateObject( '2017-01-01' )\n","isDateObjectArray":"var bool = isDateObjectArray( [ new Date(), new Date() ] )\nbool = isDateObjectArray( [ {}, {} ] )\nbool = isDateObjectArray( [ new Date(), '2011-01-01' ] )\nbool = isDateObjectArray( [] )\n","isDigitString":"var bool = isDigitString( '0123456789' )\nbool = isDigitString( 'abcdef' )\nbool = isDigitString( '0xff' )\nbool = isDigitString( '' )\n","isDomainName":"var bool = isDomainName( 'example.com' )\nbool = isDomainName( 'foo@bar.com' )\n","isDurationString":"var bool = isDurationString( '1d' )\nbool = isDurationString( '1h' )\nbool = isDurationString( 'beep' )\n","isEmailAddress":"var bool = isEmailAddress( 'beep@boop.com' )\nbool = isEmailAddress( 'beep' )\nbool = isEmailAddress( null )\n","isEmptyArray":"var bool = isEmptyArray( [] )\nbool = isEmptyArray( [ 1, 2, 3 ] )\nbool = isEmptyArray( {} )\n","isEmptyArrayLikeObject":"var bool = isEmptyArrayLikeObject( [] )\nbool = isEmptyArrayLikeObject( { 'length': 0 } )\nbool = isEmptyArrayLikeObject( '' )\n","isEmptyCollection":"var bool = isEmptyCollection( [] )\nbool = isEmptyCollection( { 'length': 0 } )\nbool = isEmptyCollection( [ 1, 2, 3 ] )\nbool = isEmptyCollection( {} )\n","isEmptyObject":"var bool = isEmptyObject( {} )\nbool = isEmptyObject( { 'beep': 'boop' } )\nbool = isEmptyObject( [] )\n","isEmptyString":"var bool = isEmptyString( '' )\nbool = isEmptyString( new String( '' ) )\nbool = isEmptyString( 'beep' )\nbool = isEmptyString( [] )\n","isEmptyString.isPrimitive":"var bool = isEmptyString.isPrimitive( '' )\nbool = isEmptyString.isPrimitive( new String( '' ) )\n","isEmptyString.isObject":"var bool = isEmptyString.isObject( new String( '' ) )\nbool = isEmptyString.isObject( '' )\n","isEnumerableProperty":"var beep = { 'boop': true };\nvar bool = isEnumerableProperty( beep, 'boop' )\nbool = isEnumerableProperty( beep, 'hasOwnProperty' )\n","isEnumerablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = true;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isEnumerablePropertyIn( obj, 'boop' )\nbool = isEnumerablePropertyIn( obj, 'beep' )\n","isEqualArray":"var x = [ 1.0, 2.0, 3.0 ];\nvar y = [ 1.0, 2.0, 3.0 ];\nvar bool = isEqualArray( x, y )\nx = [ NaN, NaN, NaN ];\ny = [ NaN, NaN, NaN ];\nbool = isEqualArray( x, y )\n","isError":"var bool = isError( new Error( 'beep' ) )\nbool = isError( {} )\n","isEvalError":"var bool = isEvalError( new EvalError( 'beep' ) )\nbool = isEvalError( {} )\n","isEven":"var bool = isEven( 4.0 )\nbool = isEven( new Number( 4.0 ) )\nbool = isEven( 3.0 )\nbool = isEven( -3.14 )\nbool = isEven( null )\n","isEven.isPrimitive":"var bool = isEven.isPrimitive( -4.0 )\nbool = isEven.isPrimitive( new Number( -4.0 ) )\n","isEven.isObject":"var bool = isEven.isObject( 4.0 )\nbool = isEven.isObject( new Number( 4.0 ) )\n","isFalsy":"var bool = isFalsy( false )\nbool = isFalsy( '' )\nbool = isFalsy( 0 )\nbool = isFalsy( null )\nbool = isFalsy( void 0 )\nbool = isFalsy( NaN )\nbool = isFalsy( {} )\nbool = isFalsy( [] )\n","isFalsyArray":"var bool = isFalsyArray( [ null, '' ] )\nbool = isFalsyArray( [ {}, [] ] )\nbool = isFalsyArray( [] )\n","isFinite":"var bool = isFinite( 5.0 )\nbool = isFinite( new Number( 5.0 ) )\nbool = isFinite( 1.0/0.0 )\nbool = isFinite( null )\n","isFinite.isPrimitive":"var bool = isFinite.isPrimitive( -3.0 )\nbool = isFinite.isPrimitive( new Number( -3.0 ) )\n","isFinite.isObject":"var bool = isFinite.isObject( 3.0 )\nbool = isFinite.isObject( new Number( 3.0 ) )\n","isFiniteArray":"var bool = isFiniteArray( [ -3.0, new Number(0.0), 2.0 ] )\nbool = isFiniteArray( [ -3.0, 1.0/0.0 ] )\n","isFiniteArray.primitives":"var bool = isFiniteArray.primitives( [ -1.0, 10.0 ] )\nbool = isFiniteArray.primitives( [ -1.0, 0.0, 5.0 ] )\nbool = isFiniteArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isFiniteArray.objects":"var bool = isFiniteArray.objects( [ new Number(1.0), new Number(3.0) ] )\nbool = isFiniteArray.objects( [ -1.0, 0.0, 3.0 ] )\nbool = isFiniteArray.objects( [ 3.0, new Number(-1.0) ] )\n","isFloat32Array":"var bool = isFloat32Array( new Float32Array( 10 ) )\nbool = isFloat32Array( [] )\n","isFloat32MatrixLike":"var M = {};\nM.data = new Float32Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float32';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat32MatrixLike( M )\nbool = isFloat32MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isFloat32MatrixLike( 3.14 )\nbool = isFloat32MatrixLike( {} )\n","isFloat32ndarrayLike":"var M = {};\nM.data = new Float32Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float32';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat32ndarrayLike( M )\nbool = isFloat32ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isFloat32ndarrayLike( 3.14 )\nbool = isFloat32ndarrayLike( {} )\n","isFloat32VectorLike":"var M = {};\nM.data = new Float32Array( [ 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float32';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat32VectorLike( M )\nbool = isFloat32VectorLike( [ 1, 2, 3, 4 ] )\nbool = isFloat32VectorLike( 3.14 )\nbool = isFloat32VectorLike( {} )\n","isFloat64Array":"var bool = isFloat64Array( new Float64Array( 10 ) )\nbool = isFloat64Array( [] )\n","isFloat64MatrixLike":"var M = {};\nM.data = new Float64Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat64MatrixLike( M )\nbool = isFloat64MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isFloat64MatrixLike( 3.14 )\nbool = isFloat64MatrixLike( {} )\n","isFloat64ndarrayLike":"var M = {};\nM.data = new Float64Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat64ndarrayLike( M )\nbool = isFloat64ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isFloat64ndarrayLike( 3.14 )\nbool = isFloat64ndarrayLike( {} )\n","isFloat64VectorLike":"var M = {};\nM.data = new Float64Array( [ 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat64VectorLike( M )\nbool = isFloat64VectorLike( [ 1, 2, 3, 4 ] )\nbool = isFloat64VectorLike( 3.14 )\nbool = isFloat64VectorLike( {} )\n","isFunction":"function beep() {};\nvar bool = isFunction( beep )\nbool = isFunction( {} )\n","isFunctionArray":"function beep() {};\nfunction boop() {};\nvar bool = isFunctionArray( [ beep, boop ] )\nbool = isFunctionArray( [ {}, beep ] )\nbool = isFunctionArray( [] )\n","isGeneratorObject":"function* generateID() {\n var idx = 0;\n while ( idx < idx+1 ) {\n     yield idx;\n     idx += 1;\n }\n };\nvar bool = isGeneratorObject( generateID() )\nbool = isGeneratorObject( generateID )\nbool = isGeneratorObject( {} )\nbool = isGeneratorObject( null )\n","isGeneratorObjectLike":"var obj = {\n 'next': function noop() {},\n 'return': function noop() {},\n 'throw': function noop() {}\n };\nvar bool = isGeneratorObjectLike( obj )\nbool = isGeneratorObjectLike( {} )\nbool = isGeneratorObjectLike( null )\n","isgzipBuffer":"var buf = new Uint8Array( 20 );\nbuf[ 0 ] = 31;  // 0x1f => magic number\nbuf[ 1 ] = 139; // 0x8b\nbuf[ 2 ] = 8;   // 0x08 => compression method\nvar bool = isgzipBuffer( buf )\nbool = isgzipBuffer( [] )\n","isHexString":"var bool = isHexString( '0123456789abcdefABCDEF' )\nbool = isHexString( '0xffffff' )\nbool = isHexString( 'x' )\nbool = isHexString( '' )\n","isInfinite":"var bool = isInfinite( 1.0/0.0 )\nbool = isInfinite( new Number( -1.0/0.0 ) )\nbool = isInfinite( 5.0 )\nbool = isInfinite( '1.0/0.0' )\n","isInfinite.isPrimitive":"var bool = isInfinite.isPrimitive( -1.0/0.0 )\nbool = isInfinite.isPrimitive( new Number( -1.0/0.0 ) )\n","isInfinite.isObject":"var bool = isInfinite.isObject( 1.0/0.0 )\nbool = isInfinite.isObject( new Number( 1.0/0.0 ) )\n","isInheritedProperty":"var beep = { 'boop': true };\nvar bool = isInheritedProperty( beep, 'boop' )\nbool = isInheritedProperty( beep, 'toString' )\nbool = isInheritedProperty( beep, 'bop' )\n","isInt8Array":"var bool = isInt8Array( new Int8Array( 10 ) )\nbool = isInt8Array( [] )\n","isInt16Array":"var bool = isInt16Array( new Int16Array( 10 ) )\nbool = isInt16Array( [] )\n","isInt32Array":"var bool = isInt32Array( new Int32Array( 10 ) )\nbool = isInt32Array( [] )\n","isInteger":"var bool = isInteger( 5.0 )\nbool = isInteger( new Number( 5.0 ) )\nbool = isInteger( -3.14 )\nbool = isInteger( null )\n","isInteger.isPrimitive":"var bool = isInteger.isPrimitive( -3.0 )\nbool = isInteger.isPrimitive( new Number( -3.0 ) )\n","isInteger.isObject":"var bool = isInteger.isObject( 3.0 )\nbool = isInteger.isObject( new Number( 3.0 ) )\n","isIntegerArray":"var bool = isIntegerArray( [ -3.0, new Number(0.0), 2.0 ] )\nbool = isIntegerArray( [ -3.0, '3.0' ] )\n","isIntegerArray.primitives":"var bool = isIntegerArray.primitives( [ -1.0, 10.0 ] )\nbool = isIntegerArray.primitives( [ -1.0, 0.0, 5.0 ] )\nbool = isIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isIntegerArray.objects":"var bool = isIntegerArray.objects( [ new Number(1.0), new Number(3.0) ] )\nbool = isIntegerArray.objects( [ -1.0, 0.0, 3.0 ] )\nbool = isIntegerArray.objects( [ 3.0, new Number(-1.0) ] )\n","isIterableLike":"var bool = isIterableLike( [ 1, 2, 3 ] )\nbool = isIterableLike( {} )\nbool = isIterableLike( null )\n","isIteratorLike":"var obj = {\n 'next': function noop() {}\n };\nvar bool = isIteratorLike( obj )\nbool = isIteratorLike( {} )\nbool = isIteratorLike( null )\n","isJSON":"var bool = isJSON( '{\"a\":5}' )\nbool = isJSON( '{a\":5}' )\n","isKebabcase":"var bool = isKebabcase( 'beep-boop' )\nbool = isKebabcase( 'BEEP_BOOP' )\n","isLeapYear":"var bool = isLeapYear( new Date() )\nbool = isLeapYear( 1996 )\nbool = isLeapYear( 2001 )\n","isLocalhost":"var bool = isLocalhost( 'localhost' )\nbool = isLocalhost( '127.0.0.1' )\nbool = isLocalhost( 'stdlib.io' )\n","isLowercase":"var bool = isLowercase( 'hello' )\nbool = isLowercase( 'World' )\n","isMatrixLike":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isMatrixLike( M )\nbool = isMatrixLike( [ 1, 2, 3, 4 ] )\nbool = isMatrixLike( 3.14 )\nbool = isMatrixLike( {} )\n","isMethod":"var beep = { 'boop': function beep() { return 'beep'; } };\nvar bool = isMethod( beep, 'boop' )\nbool = isMethod( beep, 'toString' )\n","isMethodIn":"var beep = { 'boop': true };\nvar bool = isMethodIn( beep, 'toString' )\nbool = isMethodIn( beep, 'boop' )\nbool = isMethodIn( beep, 'bop' )\n","isMultiSlice":"var bool = isMultiSlice( new MultiSlice() )\nbool = isMultiSlice( 3.14 )\nbool = isMultiSlice( {} )\n","isNamedTypedTupleLike":"var Point = namedtypedtuple( [ 'x', 'y' ] );\nvar p = new Point();\nvar bool = isNamedTypedTupleLike( p )\nbool = isNamedTypedTupleLike( [ 1, 2, 3, 4 ] )\nbool = isNamedTypedTupleLike( 3.14 )\nbool = isNamedTypedTupleLike( {} )\n","isnan":"var bool = isnan( NaN )\nbool = isnan( new Number( NaN ) )\nbool = isnan( 3.14 )\nbool = isnan( null )\n","isnan.isPrimitive":"var bool = isnan.isPrimitive( NaN )\nbool = isnan.isPrimitive( 3.14 )\nbool = isnan.isPrimitive( new Number( NaN ) )\n","isnan.isObject":"var bool = isnan.isObject( NaN )\nbool = isnan.isObject( new Number( NaN ) )\n","isNaNArray":"var bool = isNaNArray( [ NaN, NaN, NaN ] )\nbool = isNaNArray( [ NaN, 2 ] )\n","isNaNArray.primitives":"var bool = isNaNArray.primitives( [ NaN, new Number( NaN ) ] )\nbool = isNaNArray.primitives( [ NaN, NaN, NaN ] )\n","isNaNArray.objects":"var bool = isNaNArray.objects( [ new Number( NaN ), new Number( NaN ) ] )\nbool = isNaNArray.objects( [ NaN, new Number( NaN ), new Number( NaN ) ] )\nbool = isNaNArray.objects( [ NaN, NaN, NaN ] )\n","isNativeFunction":"var bool = isNativeFunction( Date )\nfunction beep() {};\nbool = isNativeFunction( beep )\nbool = isNativeFunction( {} )\n","isndarrayLike":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isndarrayLike( M )\nbool = isndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isndarrayLike( 3.14 )\nbool = isndarrayLike( {} )\n","isndarrayLikeWithDataType":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isndarrayLikeWithDataType( M, 'generic' )\nbool = isndarrayLikeWithDataType( [ 1, 2, 3, 4 ], 'generic' )\nbool = isndarrayLikeWithDataType( 3.14, 'generic' )\nbool = isndarrayLikeWithDataType( {}, 'generic' )\n","isNegativeFinite":"var bool = isNegativeFinite( -5.0 )\nbool = isNegativeFinite( new Number( -5.0 ) )\nbool = isNegativeFinite( -3.14 )\nbool = isNegativeFinite( 5.0 )\nbool = isNegativeFinite( null )\nbool = isNegativeFinite( -1.0/0.0 )\nbool = isNegativeFinite( new Number( -1.0/0.0 ) )\n","isNegativeFinite.isPrimitive":"var bool = isNegativeFinite.isPrimitive( -3.0 )\nbool = isNegativeFinite.isPrimitive( new Number( -3.0 ) )\nvar bool = isNegativeFinite.isPrimitive( -1.0/0.0 )\nbool = isNegativeFinite.isPrimitive( new Number( -1.0/0.0 ) )\n","isNegativeFinite.isObject":"var bool = isNegativeFinite.isObject( -3.0 )\nbool = isNegativeFinite.isObject( new Number( -3.0 ) )\nbool = isNegativeFinite.isObject( -1.0/0.0 )\nbool = isNegativeFinite.isObject( new Number( -1.0/0.0 ) )\n","isNegativeInteger":"var bool = isNegativeInteger( -5.0 )\nbool = isNegativeInteger( new Number( -5.0 ) )\nbool = isNegativeInteger( 5.0 )\nbool = isNegativeInteger( -3.14 )\nbool = isNegativeInteger( null )\n","isNegativeInteger.isPrimitive":"var bool = isNegativeInteger.isPrimitive( -3.0 )\nbool = isNegativeInteger.isPrimitive( new Number( -3.0 ) )\n","isNegativeInteger.isObject":"var bool = isNegativeInteger.isObject( -3.0 )\nbool = isNegativeInteger.isObject( new Number( -3.0 ) )\n","isNegativeIntegerArray":"var bool = isNegativeIntegerArray( [ -3.0, new Number(-3.0) ] )\nbool = isNegativeIntegerArray( [ -3.0, '-3.0' ] )\n","isNegativeIntegerArray.primitives":"var bool = isNegativeIntegerArray.primitives( [ -1.0, -10.0 ] )\nbool = isNegativeIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNegativeIntegerArray.objects":"var bool = isNegativeIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNegativeIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNegativeNumber":"var bool = isNegativeNumber( -5.0 )\nbool = isNegativeNumber( new Number( -5.0 ) )\nbool = isNegativeNumber( -3.14 )\nbool = isNegativeNumber( 5.0 )\nbool = isNegativeNumber( null )\n","isNegativeNumber.isPrimitive":"var bool = isNegativeNumber.isPrimitive( -3.0 )\nbool = isNegativeNumber.isPrimitive( new Number( -3.0 ) )\n","isNegativeNumber.isObject":"var bool = isNegativeNumber.isObject( -3.0 )\nbool = isNegativeNumber.isObject( new Number( -3.0 ) )\n","isNegativeNumberArray":"var bool = isNegativeNumberArray( [ -3.0, new Number(-3.0) ] )\nbool = isNegativeNumberArray( [ -3.0, '-3.0' ] )\n","isNegativeNumberArray.primitives":"var bool = isNegativeNumberArray.primitives( [ -1.0, -10.0 ] )\nbool = isNegativeNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNegativeNumberArray.objects":"var bool = isNegativeNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNegativeNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNegativeZero":"var bool = isNegativeZero( -0.0 )\nbool = isNegativeZero( new Number( -0.0 ) )\nbool = isNegativeZero( -3.14 )\nbool = isNegativeZero( 0.0 )\nbool = isNegativeZero( null )\n","isNegativeZero.isPrimitive":"var bool = isNegativeZero.isPrimitive( -0.0 )\nbool = isNegativeZero.isPrimitive( new Number( -0.0 ) )\n","isNegativeZero.isObject":"var bool = isNegativeZero.isObject( -0.0 )\nbool = isNegativeZero.isObject( new Number( -0.0 ) )\n","isNodeBuiltin":"var bool = isNodeBuiltin( 'cluster' )\nbool = isNodeBuiltin( 'crypto' )\nbool = isNodeBuiltin( 'fs-extra' )\nbool = isNodeBuiltin( '' )\n","isNodeDuplexStreamLike":"var Stream = require( 'stream' ).Duplex;\ns = new Stream();\nvar bool = isNodeDuplexStreamLike( s )\nbool = isNodeDuplexStreamLike( {} )\n","isNodeReadableStreamLike":"var Stream = require( 'stream' ).Readable;\ns = new Stream();\nvar bool = isNodeReadableStreamLike( s )\nbool = isNodeReadableStreamLike( {} )\n","isNodeREPL":"var bool = isNodeREPL()\n","isNodeStreamLike":"var Stream = require( 'stream' ).Stream;\ns = new Stream();\nvar bool = isNodeStreamLike( s )\nbool = isNodeStreamLike( {} )\n","isNodeTransformStreamLike":"var Stream = require( 'stream' ).Transform;\ns = new Stream();\nvar bool = isNodeTransformStreamLike( s )\nbool = isNodeTransformStreamLike( {} )\n","isNodeWritableStreamLike":"var Stream = require( 'stream' ).Writable;\ns = new Stream();\nvar bool = isNodeWritableStreamLike( s )\nbool = isNodeWritableStreamLike( {} )\n","isNonConfigurableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonConfigurableProperty( obj, 'boop' )\nbool = isNonConfigurableProperty( obj, 'beep' )\n","isNonConfigurablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonConfigurablePropertyIn( obj, 'boop' )\nbool = isNonConfigurablePropertyIn( obj, 'beep' )\n","isNonEnumerableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonEnumerableProperty( obj, 'boop' )\nbool = isNonEnumerableProperty( obj, 'beep' )\n","isNonEnumerablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = true;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonEnumerablePropertyIn( obj, 'boop' )\nbool = isNonEnumerablePropertyIn( obj, 'beep' )\n","isNonNegativeFinite":"var bool = isNonNegativeFinite( 5.0 )\nbool = isNonNegativeFinite( new Number( 5.0 ) )\nbool = isNonNegativeFinite( 3.14 )\nbool = isNonNegativeFinite( -5.0 )\nbool = isNonNegativeFinite( null )\nbool = isNonNegativeFinite( PINF )\n","isNonNegativeFinite.isPrimitive":"var bool = isNonNegativeFinite.isPrimitive( 3.0 )\nbool = isNonNegativeFinite.isPrimitive( new Number( 3.0 ) )\n","isNonNegativeFinite.isObject":"var bool = isNonNegativeFinite.isObject( 3.0 )\nbool = isNonNegativeFinite.isObject( new Number( 3.0 ) )\n","isNonNegativeInteger":"var bool = isNonNegativeInteger( 5.0 )\nbool = isNonNegativeInteger( new Number( 5.0 ) )\nbool = isNonNegativeInteger( 3.14 )\nbool = isNonNegativeInteger( -5.0 )\nbool = isNonNegativeInteger( null )\n","isNonNegativeInteger.isPrimitive":"var bool = isNonNegativeInteger.isPrimitive( 3.0 )\nbool = isNonNegativeInteger.isPrimitive( new Number( 3.0 ) )\n","isNonNegativeInteger.isObject":"var bool = isNonNegativeInteger.isObject( 3.0 )\nbool = isNonNegativeInteger.isObject( new Number( 3.0 ) )\n","isNonNegativeIntegerArray":"var bool = isNonNegativeIntegerArray( [ 3.0, new Number(3.0) ] )\nbool = isNonNegativeIntegerArray( [ 3.0, '3.0' ] )\n","isNonNegativeIntegerArray.primitives":"var bool = isNonNegativeIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n","isNonNegativeIntegerArray.objects":"var bool = isNonNegativeIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isNonNegativeIntegerArray.objects( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n","isNonNegativeNumber":"var bool = isNonNegativeNumber( 5.0 )\nbool = isNonNegativeNumber( new Number( 5.0 ) )\nbool = isNonNegativeNumber( 3.14 )\nbool = isNonNegativeNumber( -5.0 )\nbool = isNonNegativeNumber( null )\n","isNonNegativeNumber.isPrimitive":"var bool = isNonNegativeNumber.isPrimitive( 3.0 )\nbool = isNonNegativeNumber.isPrimitive( new Number( 3.0 ) )\n","isNonNegativeNumber.isObject":"var bool = isNonNegativeNumber.isObject( 3.0 )\nbool = isNonNegativeNumber.isObject( new Number( 3.0 ) )\n","isNonNegativeNumberArray":"var bool = isNonNegativeNumberArray( [ 3.0, new Number(3.0) ] )\nbool = isNonNegativeNumberArray( [ 3.0, '3.0' ] )\n","isNonNegativeNumberArray.primitives":"var bool = isNonNegativeNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n","isNonNegativeNumberArray.objects":"var bool = isNonNegativeNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isNonNegativeNumberArray.objects( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeNumberArray.objects( [ 3.0, new Number(1.0) ] )\n","isNonPositiveFinite":"var bool = isNonPositiveFinite( -5.0 )\nbool = isNonPositiveFinite( new Number( -5.0 ) )\nbool = isNonPositiveFinite( -3.14 )\nbool = isNonPositiveFinite( 5.0 )\nbool = isNonPositiveFinite( null )\n","isNonPositiveFinite.isPrimitive":"var bool = isNonPositiveFinite.isPrimitive( -3.0 )\nbool = isNonPositiveFinite.isPrimitive( new Number( -3.0 ) )\n","isNonPositiveFinite.isObject":"var bool = isNonPositiveFinite.isObject( -3.0 )\nbool = isNonPositiveFinite.isObject( new Number( -3.0 ) )\n","isNonPositiveInteger":"var bool = isNonPositiveInteger( -5.0 )\nbool = isNonPositiveInteger( new Number( -5.0 ) )\nbool = isNonPositiveInteger( 5.0 )\nbool = isNonPositiveInteger( -3.14 )\nbool = isNonPositiveInteger( null )\n","isNonPositiveInteger.isPrimitive":"var bool = isNonPositiveInteger.isPrimitive( -3.0 )\nbool = isNonPositiveInteger.isPrimitive( new Number( -3.0 ) )\n","isNonPositiveInteger.isObject":"var bool = isNonPositiveInteger.isObject( -3.0 )\nbool = isNonPositiveInteger.isObject( new Number( -3.0 ) )\n","isNonPositiveIntegerArray":"var bool = isNonPositiveIntegerArray( [ -3.0, new Number(-3.0) ] )\nbool = isNonPositiveIntegerArray( [ -3.0, '-3.0' ] )\n","isNonPositiveIntegerArray.primitives":"var bool = isNonPositiveIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNonPositiveIntegerArray.objects":"var bool = isNonPositiveIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNonPositiveIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNonPositiveNumber":"var bool = isNonPositiveNumber( -5.0 )\nbool = isNonPositiveNumber( new Number( -5.0 ) )\nbool = isNonPositiveNumber( -3.14 )\nbool = isNonPositiveNumber( 5.0 )\nbool = isNonPositiveNumber( null )\n","isNonPositiveNumber.isPrimitive":"var bool = isNonPositiveNumber.isPrimitive( -3.0 )\nbool = isNonPositiveNumber.isPrimitive( new Number( -3.0 ) )\n","isNonPositiveNumber.isObject":"var bool = isNonPositiveNumber.isObject( -3.0 )\nbool = isNonPositiveNumber.isObject( new Number( -3.0 ) )\n","isNonPositiveNumberArray":"var bool = isNonPositiveNumberArray( [ -3.0, new Number(-3.0) ] )\nbool = isNonPositiveNumberArray( [ -3.0, '-3.0' ] )\n","isNonPositiveNumberArray.primitives":"var bool = isNonPositiveNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNonPositiveNumberArray.objects":"var bool = isNonPositiveNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNonPositiveNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNonSymmetricMatrix":"var buf = [ 1, 2, 3, 4 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isNonSymmetricMatrix( M )\nbool = isNonSymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isNonSymmetricMatrix( 3.14 )\nbool = isNonSymmetricMatrix( {} )\n","isNull":"var bool = isNull( null )\nbool = isNull( true )\n","isNullArray":"var bool = isNullArray( [ null, null, null ] )\nbool = isNullArray( [ NaN, 2, null ] )\n","isNumber":"var bool = isNumber( 3.14 )\nbool = isNumber( new Number( 3.14 ) )\nbool = isNumber( NaN )\nbool = isNumber( null )\n","isNumber.isPrimitive":"var bool = isNumber.isPrimitive( 3.14 )\nbool = isNumber.isPrimitive( NaN )\nbool = isNumber.isPrimitive( new Number( 3.14 ) )\n","isNumber.isObject":"var bool = isNumber.isObject( 3.14 )\nbool = isNumber.isObject( new Number( 3.14 ) )\n","isNumberArray":"var bool = isNumberArray( [ 1, 2, 3 ] )\nbool = isNumberArray( [ '1', 2, 3 ] )\n","isNumberArray.primitives":"var arr = [ 1, 2, 3 ];\nvar bool = isNumberArray.primitives( arr )\narr = [ 1, new Number( 2 ) ];\nbool = isNumberArray.primitives( arr )\n","isNumberArray.objects":"var arr = [ new Number( 1 ), new Number( 2 ) ];\nvar bool = isNumberArray.objects( arr )\narr = [ new Number( 1 ), 2 ];\nbool = isNumberArray.objects( arr )\n","isNumericArray":"var bool = isNumericArray( new Int8Array( 10 ) )\nbool = isNumericArray( [ 1, 2, 3 ] )\nbool = isNumericArray( [ '1', '2', '3' ] )\n","isObject":"var bool = isObject( {} )\nbool = isObject( true )\n","isObjectArray":"var bool = isObjectArray( [ {}, new Number(3.0) ] )\nbool = isObjectArray( [ {}, { 'beep': 'boop' } ] )\nbool = isObjectArray( [ {}, '3.0' ] )\n","isObjectLike":"var bool = isObjectLike( {} )\nbool = isObjectLike( [] )\nbool = isObjectLike( null )\n","isOdd":"var bool = isOdd( 5.0 )\nbool = isOdd( new Number( 5.0 ) )\nbool = isOdd( 4.0 )\nbool = isOdd( new Number( 4.0 ) )\nbool = isOdd( -3.14 )\nbool = isOdd( null )\n","isOdd.isPrimitive":"var bool = isOdd.isPrimitive( -5.0 )\nbool = isOdd.isPrimitive( new Number( -5.0 ) )\n","isOdd.isObject":"var bool = isOdd.isObject( 5.0 )\nbool = isOdd.isObject( new Number( 5.0 ) )\n","isoWeeksInYear":"var num = isoWeeksInYear()\nnum = isoWeeksInYear( 2015 )\nnum = isoWeeksInYear( 2017 )\n","isPascalcase":"var bool = isPascalcase( 'HelloWorld' )\nbool = isPascalcase( 'hello-world' )\n","isPersymmetricMatrix":"var buf = [ 1, 2, 3, 1 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isPersymmetricMatrix( M )\nbool = isPersymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isPersymmetricMatrix( 3.14 )\nbool = isPersymmetricMatrix( {} )\n","isPlainObject":"var bool = isPlainObject( {} )\nbool = isPlainObject( null )\n","isPlainObjectArray":"var bool = isPlainObjectArray( [ {}, { 'beep': 'boop' } ] )\nbool = isPlainObjectArray( [ {}, new Number(3.0) ] )\nbool = isPlainObjectArray( [ {}, '3.0' ] )\n","isPositiveFinite":"var bool = isPositiveFinite( 5.0 )\nbool = isPositiveFinite( new Number( 5.0 ) )\nbool = isPositiveFinite( 3.14 )\nbool = isPositiveFinite( -5.0 )\nvar bool = isPositiveFinite( 1.0/0.0 )\nbool = isPositiveFinite( new Number( 1.0/0.0 ) )\nbool = isPositiveFinite( null )\n","isPositiveFinite.isPrimitive":"var bool = isPositiveFinite.isPrimitive( 3.0 )\nvar bool = isPositiveFinite.isPrimitive( 1.0/0.0 )\nbool = isPositiveFinite.isPrimitive( new Number( 3.0 ) )\n","isPositiveFinite.isObject":"var bool = isPositiveFinite.isObject( 3.0 )\nbool = isPositiveFinite.isObject( new Number( 3.0 ) )\nbool = isPositiveFinite.isObject( new Number( 1.0/0.0 ) )\n","isPositiveInteger":"var bool = isPositiveInteger( 5.0 )\nbool = isPositiveInteger( new Number( 5.0 ) )\nbool = isPositiveInteger( 3.14 )\nbool = isPositiveInteger( -5.0 )\nbool = isPositiveInteger( null )\n","isPositiveInteger.isPrimitive":"var bool = isPositiveInteger.isPrimitive( 3.0 )\nbool = isPositiveInteger.isPrimitive( new Number( 3.0 ) )\n","isPositiveInteger.isObject":"var bool = isPositiveInteger.isObject( 3.0 )\nbool = isPositiveInteger.isObject( new Number( 3.0 ) )\n","isPositiveIntegerArray":"var bool = isPositiveIntegerArray( [ 3.0, new Number(3.0) ] )\nbool = isPositiveIntegerArray( [ 3.0, '3.0' ] )\n","isPositiveIntegerArray.primitives":"var bool = isPositiveIntegerArray.primitives( [ 1.0, 10.0 ] )\nbool = isPositiveIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isPositiveIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n","isPositiveIntegerArray.objects":"var bool = isPositiveIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isPositiveIntegerArray.objects( [ 1.0, 2.0, 10.0 ] )\nbool = isPositiveIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n","isPositiveNumber":"var bool = isPositiveNumber( 5.0 )\nbool = isPositiveNumber( new Number( 5.0 ) )\nbool = isPositiveNumber( 3.14 )\nbool = isPositiveNumber( -5.0 )\nbool = isPositiveNumber( null )\n","isPositiveNumber.isPrimitive":"var bool = isPositiveNumber.isPrimitive( 3.0 )\nbool = isPositiveNumber.isPrimitive( new Number( 3.0 ) )\n","isPositiveNumber.isObject":"var bool = isPositiveNumber.isObject( 3.0 )\nbool = isPositiveNumber.isObject( new Number( 3.0 ) )\n","isPositiveNumberArray":"var bool = isPositiveNumberArray( [ 3.0, new Number(3.0) ] )\nbool = isPositiveNumberArray( [ 3.0, '3.0' ] )\n","isPositiveNumberArray.primitives":"var bool = isPositiveNumberArray.primitives( [ 1.0, 10.0 ] )\nbool = isPositiveNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isPositiveNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n","isPositiveNumberArray.objects":"var bool = isPositiveNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isPositiveNumberArray.objects( [ 1.0, 2.0, 10.0 ] )\nbool = isPositiveNumberArray.objects( [ 3.0, new Number(1.0) ] )\n","isPositiveZero":"var bool = isPositiveZero( 0.0 )\nbool = isPositiveZero( new Number( 0.0 ) )\nbool = isPositiveZero( -3.14 )\nbool = isPositiveZero( -0.0 )\nbool = isPositiveZero( null )\n","isPositiveZero.isPrimitive":"var bool = isPositiveZero.isPrimitive( 0.0 )\nbool = isPositiveZero.isPrimitive( new Number( 0.0 ) )\n","isPositiveZero.isObject":"var bool = isPositiveZero.isObject( 0.0 )\nbool = isPositiveZero.isObject( new Number( 0.0 ) )\n","isPrime":"var bool = isPrime( 5.0 )\nbool = isPrime( new Number( 5.0 ) )\nbool = isPrime( 3.14 )\nbool = isPrime( -5.0 )\nbool = isPrime( null )\n","isPrime.isPrimitive":"var bool = isPrime.isPrimitive( 5.0 )\nbool = isPrime.isPrimitive( new Number( 5.0 ) )\n","isPrime.isObject":"var bool = isPrime.isObject( 5.0 )\nbool = isPrime.isObject( new Number( 5.0 ) )\n","isPrimitive":"var bool = isPrimitive( true )\nbool = isPrimitive( {} )\n","isPrimitiveArray":"var bool = isPrimitiveArray( [ '3', 2, null ] )\nbool = isPrimitiveArray( [ {}, 2, 1 ] )\nbool = isPrimitiveArray( [ new String('abc'), '3.0' ] )\n","isPRNGLike":"var bool = isPRNGLike( base.random.randu )\nbool = isPRNGLike( [ 1, 2, 3, 4 ] )\nbool = isPRNGLike( 3.14 )\nbool = isPRNGLike( {} )\n","isProbability":"var bool = isProbability( 0.5 )\nbool = isProbability( new Number( 0.5 ) )\nbool = isProbability( 3.14 )\nbool = isProbability( -5.0 )\nbool = isProbability( null )\n","isProbability.isPrimitive":"var bool = isProbability.isPrimitive( 0.3 )\nbool = isProbability.isPrimitive( new Number( 0.3 ) )\n","isProbability.isObject":"var bool = isProbability.isObject( 0.77 )\nbool = isProbability.isObject( new Number( 0.77 ) )\n","isProbabilityArray":"var bool = isProbabilityArray( [ 0.5, new Number(0.8) ] )\nbool = isProbabilityArray( [ 0.8, 1.2 ] )\nbool = isProbabilityArray( [ 0.8, '0.2' ] )\n","isProbabilityArray.primitives":"var bool = isProbabilityArray.primitives( [ 1.0, 0.0, 0.5 ] )\nbool = isProbabilityArray.primitives( [ 0.3, new Number(0.4) ] )\n","isProbabilityArray.objects":"var bool = isProbabilityArray.objects( [ new Number(0.7), new Number(1.0) ] )\nbool = isProbabilityArray.objects( [ 1.0, 0.0, new Number(0.7) ] )\n","isPropertyKey":"var out = isPropertyKey( 'foo' )\nout = isPropertyKey( 1 )\nout = isPropertyKey( true )\n","isPrototypeOf":"function Foo() { return this; };\nfunction Bar() { return this; };\ninherit( Bar, Foo );\nvar bar = new Bar();\nvar bool = isPrototypeOf( bar, Foo.prototype )\n","isRaggedNestedArray":"var bool = isRaggedNestedArray( [ [ 1, 2, 3 ], [ 4, 5 ] ] )\nbool = isRaggedNestedArray( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\nbool = isRaggedNestedArray( 'beep' )\n","isRangeError":"var bool = isRangeError( new RangeError( 'beep' ) )\nbool = isRangeError( {} )\n","isReadableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadableProperty( obj, 'boop' )\nbool = isReadableProperty( obj, 'beep' )\n","isReadablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadablePropertyIn( obj, 'boop' )\nbool = isReadablePropertyIn( obj, 'beep' )\n","isReadOnlyProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadOnlyProperty( obj, 'boop' )\nbool = isReadOnlyProperty( obj, 'beep' )\n","isReadOnlyPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadOnlyPropertyIn( obj, 'boop' )\nbool = isReadOnlyPropertyIn( obj, 'beep' )\n","isReadWriteProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadWriteProperty( obj, 'boop' )\nbool = isReadWriteProperty( obj, 'beep' )\n","isReadWritePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadWritePropertyIn( obj, 'boop' )\nbool = isReadWritePropertyIn( obj, 'beep' )\n","isReferenceError":"var bool = isReferenceError( new ReferenceError( 'beep' ) )\nbool = isReferenceError( {} )\n","isRegExp":"var bool = isRegExp( /\\.+/ )\nbool = isRegExp( {} )\n","isRegExpString":"var bool = isRegExpString( '/beep/' )\nbool = isRegExpString( 'beep' )\nbool = isRegExpString( '' )\nbool = isRegExpString( null )\n","isRelativePath":"var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\nbool = isRelativePath( './foo/bar/baz' )\n","isRelativePath.posix":"var bool = isRelativePath.posix( './foo/bar/baz' )\nbool = isRelativePath.posix( '/foo/../bar/baz' )\n","isRelativePath.win32":"var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\nbool = isRelativePath( 'C:\\\\foo\\\\..\\\\bar\\\\baz' )\n","isRelativeURI":"var bool = isRelativeURI( '/images/example.png' )\nbool = isRelativeURI( 'http://www.example.com' )\nbool = isRelativeURI( null )\n","isSafeInteger":"var bool = isSafeInteger( 5.0 )\nbool = isSafeInteger( new Number( 5.0 ) )\nbool = isSafeInteger( 2.0e200 )\nbool = isSafeInteger( -3.14 )\nbool = isSafeInteger( null )\n","isSafeInteger.isPrimitive":"var bool = isSafeInteger.isPrimitive( -3.0 )\nbool = isSafeInteger.isPrimitive( new Number( -3.0 ) )\n","isSafeInteger.isObject":"var bool = isSafeInteger.isObject( 3.0 )\nbool = isSafeInteger.isObject( new Number( 3.0 ) )\n","isSafeIntegerArray":"var arr = [ -3.0, new Number(0.0), 2.0 ];\nvar bool = isSafeIntegerArray( arr )\narr = [ -3.0, '3.0' ];\nbool = isSafeIntegerArray( arr )\n","isSafeIntegerArray.primitives":"var arr = [ -1.0, 10.0 ];\nvar bool = isSafeIntegerArray.primitives( arr )\narr = [ -1.0, 0.0, 5.0 ];\nbool = isSafeIntegerArray.primitives( arr )\narr = [ -3.0, new Number(-1.0) ];\nbool = isSafeIntegerArray.primitives( arr )\n","isSafeIntegerArray.objects":"var arr = [ new Number(1.0), new Number(3.0) ];\nvar bool = isSafeIntegerArray.objects( arr )\narr = [ -1.0, 0.0, 3.0 ];\nbool = isSafeIntegerArray.objects( arr )\narr = [ 3.0, new Number(-1.0) ];\nbool = isSafeIntegerArray.objects( arr )\n","isSameArray":"var x = [ 1.0, 2.0, 3.0 ];\nvar y = [ 1.0, 2.0, 3.0 ];\nvar bool = isSameArray( x, y )\nx = [ NaN, NaN, NaN ];\ny = [ NaN, NaN, NaN ];\nbool = isSameArray( x, y )\n","isSameArrayLike":"var x = [ 1.0, 2.0, 3.0 ];\nvar y = [ 1.0, 2.0, 3.0 ];\nvar bool = isSameArrayLike( x, y )\nx = [ NaN, NaN, NaN ];\ny = [ NaN, NaN, NaN ];\nbool = isSameArrayLike( x, y )\n","isSameComplex64":"var x = new Complex64( 1.0, 2.0 );\nvar y = new Complex64( 1.0, 2.0 );\nvar bool = isSameComplex64( x, y )\nx = new Complex64( NaN, NaN );\ny = new Complex64( NaN, NaN );\nbool = isSameComplex64( x, y )\n","isSameComplex64Array":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar bool = isSameComplex64Array( x, y )\nx = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\ny = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\nbool = isSameComplex64Array( x, y )\n","isSameComplex128":"var x = new Complex128( 1.0, 2.0 );\nvar y = new Complex128( 1.0, 2.0 );\nvar bool = isSameComplex128( x, y )\nx = new Complex128( NaN, NaN );\ny = new Complex128( NaN, NaN );\nbool = isSameComplex128( x, y )\n","isSameComplex128Array":"var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar bool = isSameComplex128Array( x, y )\nx = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\ny = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\nbool = isSameComplex128Array( x, y )\n","isSameDateObject":"var d1 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\nvar d2 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\nvar bool = isSameDateObject( d1, d2 )\nvar d1 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\nvar d2 = new Date( 2024, 11, 31, 23, 59, 59, 78 );\nvar bool = isSameDateObject( d1, d2 )\n","isSameFloat32Array":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nvar bool = isSameFloat32Array( x, y )\nx = new Float32Array( [ NaN, NaN, NaN ] );\ny = new Float32Array( [ NaN, NaN, NaN ] );\nbool = isSameFloat32Array( x, y )\n","isSameFloat64Array":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nvar bool = isSameFloat64Array( x, y )\nx = new Float64Array( [ NaN, NaN, NaN ] );\ny = new Float64Array( [ NaN, NaN, NaN ] );\nbool = isSameFloat64Array( x, y )\n","isSameNativeClass":"var bool = isSameNativeClass( 3.14, new Number( 3.14 ) )\nbool = isSameNativeClass( 'beep', 'boop' )\nbool = isSameNativeClass( {}, [] )\n","isSameType":"var bool = isSameType( true, true )\nbool = isSameType( {}, [] )\nbool = isSameType( 3.12, -3.12 )\nbool = isSameType( 0.0, '0.0' )\n","isSameValue":"var bool = isSameValue( true, true )\nbool = isSameValue( {}, {} )\nbool = isSameValue( -0.0, -0.0 )\nbool = isSameValue( -0.0, 0.0 )\nbool = isSameValue( NaN, NaN )\n","isSameValueZero":"var bool = isSameValueZero( true, true )\nbool = isSameValueZero( {}, {} )\nbool = isSameValueZero( -0.0, -0.0 )\nbool = isSameValueZero( -0.0, 0.0 )\nbool = isSameValueZero( NaN, NaN )\n","isSemVer":"var bool = isSemVer( '1.0.0' )\nbool = isSemVer( '1.0.0-alpha.1' )\nbool = isSemVer( '0.1' )\nbool = isSemVer( null )\n","isSharedArrayBuffer":"var bool = isSharedArrayBuffer( new SharedArrayBuffer( 10 ) )\nbool = isSharedArrayBuffer( [] )\n","isSkewCentrosymmetricMatrix":"var buf = [ 2, 1, -1, -2 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSkewCentrosymmetricMatrix( M )\nbool = isSkewCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSkewCentrosymmetricMatrix( 3.14 )\nbool = isSkewCentrosymmetricMatrix( {} )\n","isSkewPersymmetricMatrix":"var buf = [ 1, 0, 0, -1 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSkewPersymmetricMatrix( M )\nbool = isSkewPersymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSkewPersymmetricMatrix( 3.14 )\nbool = isSkewPersymmetricMatrix( {} )\n","isSkewSymmetricMatrix":"var buf = [ 0, -1, 1, 0 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSkewSymmetricMatrix( M )\nbool = isSkewSymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSkewSymmetricMatrix( 3.14 )\nbool = isSkewSymmetricMatrix( {} )\n","isSlice":"var bool = isSlice( new Slice( 10 ) )\nbool = isSlice( 3.14 )\nbool = isSlice( {} )\n","isSnakecase":"var bool = isSnakecase( 'hello_world' )\nbool = isSnakecase( 'Hello World' )\n","isSquareMatrix":"var buf = [ 0, 0, 0, 0 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSquareMatrix( M )\nbool = isSquareMatrix( [ 1, 2, 3, 4 ] )\nbool = isSquareMatrix( 3.14 )\nbool = isSquareMatrix( {} )\n","isSquareNumber":"var bool = isSquareNumber( 4.0 )\nbool = isSquareNumber( new Number( 4.0 ) )\nbool = isSquareNumber( 3.14 )\nbool = isSquareNumber( -5.0 )\nbool = isSquareNumber( null )\n","isSquareNumber.isPrimitive":"var bool = isSquareNumber.isPrimitive( 4.0 )\nbool = isSquareNumber.isPrimitive( new Number( 4.0 ) )\n","isSquareNumber.isObject":"var bool = isSquareNumber.isObject( 4.0 )\nbool = isSquareNumber.isObject( new Number( 4.0 ) )\n","isSquareTriangularNumber":"var bool = isSquareTriangularNumber( 36.0 )\nbool = isSquareTriangularNumber( new Number( 36.0 ) )\nbool = isSquareTriangularNumber( 3.14 )\nbool = isSquareTriangularNumber( -5.0 )\nbool = isSquareTriangularNumber( null )\n","isSquareTriangularNumber.isPrimitive":"var bool = isSquareTriangularNumber.isPrimitive( 36.0 )\nbool = isSquareTriangularNumber.isPrimitive( new Number( 36.0 ) )\n","isSquareTriangularNumber.isObject":"var bool = isSquareTriangularNumber.isObject( 36.0 )\nbool = isSquareTriangularNumber.isObject( new Number( 36.0 ) )\n","isStartcase":"var bool = isStartcase( 'Beep Boop' )\nbool = isStartcase( 'Beep and Boop' )\n","isStrictEqual":"var bool = isStrictEqual( true, true )\nbool = isStrictEqual( {}, {} )\nbool = isStrictEqual( -0.0, -0.0 )\nbool = isStrictEqual( -0.0, 0.0 )\nbool = isStrictEqual( NaN, NaN )\n","isString":"var bool = isString( 'beep' )\nbool = isString( new String( 'beep' ) )\nbool = isString( 5 )\n","isString.isPrimitive":"var bool = isString.isPrimitive( 'beep' )\nbool = isString.isPrimitive( new String( 'beep' ) )\n","isString.isObject":"var bool = isString.isObject( new String( 'beep' ) )\nbool = isString.isObject( 'beep' )\n","isStringArray":"var bool = isStringArray( [ 'abc', 'def' ] )\nbool = isStringArray( [ 'abc', 123 ] )\n","isStringArray.primitives":"var arr = [ 'abc', 'def' ];\nvar bool = isStringArray.primitives( arr )\narr = [ 'abc', new String( 'def' ) ];\nbool = isStringArray.primitives( arr )\n","isStringArray.objects":"var arr = [ new String( 'ab' ), new String( 'cd' ) ];\nvar bool = isStringArray.objects( arr )\narr = [ new String( 'abc' ), 'def' ];\nbool = isStringArray.objects( arr )\n","isSymbol":"var bool = isSymbol( Symbol( 'beep' ) )\nbool = isSymbol( Object( Symbol( 'beep' ) ) )\nbool = isSymbol( {} )\nbool = isSymbol( null )\nbool = isSymbol( true )\n","isSymbolArray":"var bool = isSymbolArray( [ Symbol( 'beep' ), Symbol( 'boop' ) ] )\nbool = isSymbolArray( Symbol( 'beep' ) )\nbool = isSymbolArray( [] )\nbool = isSymbolArray( {} )\nbool = isSymbolArray( null )\nbool = isSymbolArray( true )\n","isSymbolArray.primitives":"var bool = isSymbolArray.primitives( [ Symbol( 'beep' ) ] )\nbool = isSymbolArray.primitives( [ Object( Symbol( 'beep' ) ) ] )\nbool = isSymbolArray.primitives( [] )\nbool = isSymbolArray.primitives( {} )\nbool = isSymbolArray.primitives( null )\nbool = isSymbolArray.primitives( true )\n","isSymbolArray.objects":"var bool = isSymbolArray.objects( [ Object( Symbol( 'beep' ) ) ] )\nbool = isSymbolArray.objects( [ Symbol( 'beep' ) ] )\nbool = isSymbolArray.objects( [] )\nbool = isSymbolArray.objects( {} )\nbool = isSymbolArray.objects( null )\nbool = isSymbolArray.objects( true )\n","isSymmetricMatrix":"var buf = [ 0, 1, 1, 2 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSymmetricMatrix( M )\nbool = isSymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSymmetricMatrix( 3.14 )\nbool = isSymmetricMatrix( {} )\n","isSyntaxError":"var bool = isSyntaxError( new SyntaxError( 'beep' ) )\nbool = isSyntaxError( {} )\n","isTriangularNumber":"var bool = isTriangularNumber( 36.0 )\nbool = isTriangularNumber( new Number( 36.0 ) )\nbool = isTriangularNumber( 3.14 )\nbool = isTriangularNumber( -5.0 )\nbool = isTriangularNumber( null )\n","isTriangularNumber.isPrimitive":"var bool = isTriangularNumber.isPrimitive( 36.0 )\nbool = isTriangularNumber.isPrimitive( new Number( 36.0 ) )\n","isTriangularNumber.isObject":"var bool = isTriangularNumber.isObject( 36.0 )\nbool = isTriangularNumber.isObject( new Number( 36.0 ) )\n","isTruthy":"var bool = isTruthy( true )\nbool = isTruthy( {} )\nbool = isTruthy( [] )\nbool = isTruthy( false )\nbool = isTruthy( '' )\nbool = isTruthy( 0 )\nbool = isTruthy( null )\nbool = isTruthy( void 0 )\nbool = isTruthy( NaN )\n","isTruthyArray":"var bool = isTruthyArray( [ {}, [] ] )\nbool = isTruthyArray( [ null, '' ] )\nbool = isTruthyArray( [] )\n","isTypedArray":"var bool = isTypedArray( new Int8Array( 10 ) )\n","isTypedArrayLength":"var bool = isTypedArrayLength( 5 )\nbool = isTypedArrayLength( 2.0e200 )\nbool = isTypedArrayLength( -3.14 )\nbool = isTypedArrayLength( null )\n","isTypedArrayLike":"var bool = isTypedArrayLike( new Int16Array() )\nbool = isTypedArrayLike({\n'length': 10,\n'byteOffset': 0,\n'byteLength': 10,\n'BYTES_PER_ELEMENT': 4\n })\n","isTypeError":"var bool = isTypeError( new TypeError( 'beep' ) )\nbool = isTypeError( {} )\n","isUint8Array":"var bool = isUint8Array( new Uint8Array( 10 ) )\nbool = isUint8Array( [] )\n","isUint8ClampedArray":"var bool = isUint8ClampedArray( new Uint8ClampedArray( 10 ) )\nbool = isUint8ClampedArray( [] )\n","isUint16Array":"var bool = isUint16Array( new Uint16Array( 10 ) )\nbool = isUint16Array( [] )\n","isUint32Array":"var bool = isUint32Array( new Uint32Array( 10 ) )\nbool = isUint32Array( [] )\n","isUNCPath":"var bool = isUNCPath( '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz' )\nbool = isUNCPath( '/foo/bar/baz' )\n","isUndefined":"var bool = isUndefined( void 0 )\nbool = isUndefined( null )\n","isUndefinedOrNull":"var bool = isUndefinedOrNull( void 0 )\nbool = isUndefinedOrNull( null )\nbool = isUndefinedOrNull( false )\n","isUnityProbabilityArray":"var bool = isUnityProbabilityArray( [ 0.25, 0.5, 0.25 ] )\nbool = isUnityProbabilityArray( new Uint8Array( [ 0, 1 ] ) )\nbool = isUnityProbabilityArray( [ 0.4, 0.4, 0.4 ] )\nbool = isUnityProbabilityArray( [ 3.14, 0.0 ] )\n","isUppercase":"var bool = isUppercase( 'HELLO' )\nbool = isUppercase( 'World' )\n","isURI":"var bool = isURI( 'http://google.com' )\nbool = isURI( 'http://localhost/' )\nbool = isURI( 'http://example.w3.org/path%20with%20spaces.html' )\nbool = isURI( 'ftp://ftp.is.co.za/rfc/rfc1808.txt' )\nbool = isURI( '' )\nbool = isURI( 'foo@bar' )\nbool = isURI( '://foo/' )\nbool = isURI( 'http://<foo>' )\nbool = isURI( 'http:////foo.html' )\nbool = isURI( 'http://example.w3.org/%a' )\n","isURIError":"var bool = isURIError( new URIError( 'beep' ) )\nbool = isURIError( {} )\n","isVectorLike":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isVectorLike( M )\nbool = isVectorLike( [ 1, 2, 3, 4 ] )\nbool = isVectorLike( 3.14 )\nbool = isVectorLike( {} )\n","isWebAssemblyMemory":"var bool = isWebAssemblyMemory( {} )\n","isWellFormedString":"var bool = isWellFormedString( '' )\nbool = isWellFormedString( new String( '' ) )\nbool = isWellFormedString( '\\uDBFF' )\nbool = isWellFormedString( '\\uDBFFFF\\uDBFF' )\nbool = isWellFormedString( [] )\nbool = isWellFormedString( '-5' )\nbool = isWellFormedString( null )\n","isWellFormedString.isPrimitive":"var bool = isWellFormedString.isPrimitive( '' )\nbool = isWellFormedString.isPrimitive( new String( '' ) )\n","isWellFormedString.isObject":"var bool = isWellFormedString.isObject( '' )\nbool = isWellFormedString.isObject( new String( '' ) )\n","isWhitespace":"var bool = isWhitespace( '       ' )\nbool = isWhitespace( 'abcdef' )\nbool = isWhitespace( '' )\n","isWritableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = false;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isWritableProperty( obj, 'boop' )\nbool = isWritableProperty( obj, 'beep' )\n","isWritablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = false;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isWritablePropertyIn( obj, 'boop' )\nbool = isWritablePropertyIn( obj, 'beep' )\n","isWriteOnlyProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isWriteOnlyProperty( obj, 'boop' )\nbool = isWriteOnlyProperty( obj, 'beep' )\n","isWriteOnlyPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isWriteOnlyPropertyIn( obj, 'boop' )\nbool = isWriteOnlyPropertyIn( obj, 'beep' )\n","iterAbs":"var it = iterAbs( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterAbs2":"var it = iterAbs2( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterAcos":"var it = iterAcos( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcosh":"var it = iterAcosh( random.iterators.uniform( 1.0, 10.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcot":"var it = iterAcot( random.iterators.uniform( -5.0, 5.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcoth":"var it = iterAcoth( random.iterators.uniform( 1.0, 10.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcovercos":"var it = iterAcovercos( random.iterators.uniform( -2.0, 0.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcoversin":"var it = iterAcoversin( random.iterators.uniform( 0.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAdd":"var it1 = array2iterator( [ 1.0, 2.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nvar it = iterAdd( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterAdvance":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar it = iterAdvance( arr, 4 );\nvar v = it.next().value\nvar bool = it.next().done\n","iterAhavercos":"var it = iterAhavercos( random.iterators.uniform( 0.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAhaversin":"var it = iterAhaversin( random.iterators.uniform( 0.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAny":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar bool = iterAny( arr )\n","iterAnyBy":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nfunction fcn( v ) { return ( v === 1 ); };\nvar bool = iterAnyBy( arr, fcn )\n","iterAsin":"var it = iterAsin( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAsinh":"var it = iterAsinh( random.iterators.uniform( -2.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAtan":"var it = iterAtan( random.iterators.uniform( -2.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAtan2":"var x = random.iterators.uniform( -2.0, 2.0 );\nvar y = random.iterators.uniform( -2.0, 2.0 );\nvar it = iterAtan2( y, x );\nvar r = it.next().value\nr = it.next().value\n","iterAtanh":"var it = iterAtanh( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterator2array":"var opts = { 'iter': 10 };\nvar arr = iterator2array( random.iterators.randu( opts ) )\n","iterator2arrayview":"var it = random.iterators.randu({ 'iter': 10 });\nvar out = new Float64Array( 20 );\nvar arr = iterator2arrayview( it, out, 5, 15 )\n","iterator2arrayviewRight":"var it = random.iterators.randu({ 'iter': 10 });\nvar out = new Float64Array( 20 );\nvar arr = iterator2arrayviewRight( it, out, 5, 15 )\n","iteratorStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar it = random.iterators.randu( opts );\nvar s = iteratorStream( it );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","iteratorStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = iteratorStream.factory( opts );\n","iteratorStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar it = random.iterators.randu( opts );\nvar s = iteratorStream.objectMode( it );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","IteratorSymbol":"var s = IteratorSymbol\n","iterAvercos":"var it = iterAvercos( random.iterators.uniform( -2.0, 0.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAversin":"var it = iterAversin( random.iterators.uniform( 0.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterawgn":"var src = iterSineWave();\nvar it = iterawgn( src, 0.5 );\nvar v = it.next().value\nv = it.next().value\n","iterawln":"var src = iterSineWave();\nvar it = iterawln( src, 0.5 );\nvar v = it.next().value\nv = it.next().value\n","iterawun":"var src = iterSineWave();\nvar it = iterawun( src, 0.5 );\nvar v = it.next().value\nv = it.next().value\n","iterBartlettHannPulse":"var it = iterBartlettHannPulse();\nvar v = it.next().value\nv = it.next().value\n","iterBartlettPulse":"var it = iterBartlettPulse();\nvar v = it.next().value\nv = it.next().value\n","iterBesselj0":"var it = iterBesselj0( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBesselj1":"var it = iterBesselj1( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBessely0":"var it = iterBessely0( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBessely1":"var it = iterBessely1( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBeta":"var x = random.iterators.uniform( 0.0, 2.0 );\nvar y = random.iterators.uniform( 0.0, 2.0 );\nvar it = iterBeta( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterBetaln":"var x = random.iterators.uniform( 0.0, 2.0 );\nvar y = random.iterators.uniform( 0.0, 2.0 );\nvar it = iterBetaln( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterBinet":"var it = iterBinet( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCbrt":"var it = iterCbrt( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCeil":"var it = iterCeil( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCeil2":"var it = iterCeil2( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCeil10":"var it = iterCeil10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterCompositesSeq":"var it = iterCompositesSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterConcat":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = array2iterator( [ 3, 4 ] );\nvar it = iterConcat( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterConstant":"var it = iterConstant( 3.14 );\nvar v = it.next().value\nv = it.next().value\n","iterContinuedFraction":"var terms = array2iterator( [ 3, 4, 12, 4 ] );\nvar v = iterContinuedFraction( terms )\n","iterContinuedFractionSeq":"var it = iterContinuedFractionSeq( 3.245 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\nit = iterContinuedFractionSeq( 3.245, { 'returns': 'convergents' } );\nv = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nbool = it.next().done\n","iterCos":"var it = iterCos( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCosh":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterCosh( r );\nvar v = it.next().value\nv = it.next().value\n","iterCosineWave":"var it = iterCosineWave();\nvar v = it.next().value\nv = it.next().value\n","iterCosm1":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterCosm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterCospi":"var it = iterCospi( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCounter":"var it = iterCounter( random.iterators.randu() );\nvar v = it.next().value\nv = it.next().value\n","iterCovercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterCovercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterCoversin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterCoversin( r );\nvar v = it.next().value\nv = it.next().value\n","iterCubesSeq":"var it = iterCubesSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","itercugmean":"var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\nvar it = itercugmean( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itercuhmean":"var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\nvar it = itercuhmean( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itercumax":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumax( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumaxabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumaxabs( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumean":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumean( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumeanabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumeanabs( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumeanabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumeanabs2( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumidrange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumidrange( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itercumin":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumin( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercuminabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercuminabs( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercuprod":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercuprod( arr );\nvar p = it.next().value\np = it.next().value\np = it.next().value\np = it.next().value\n","itercurange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercurange( arr );\nvar r = it.next().value\nr = it.next().value\nr = it.next().value\nr = it.next().value\n","itercusum":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercusum( arr );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itercusumabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercusumabs( arr );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itercusumabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercusumabs2( arr );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","iterDatespace":"var t1 = new Date();\nvar it = iterDatespace( t1, new Date( t1.getTime()+86400000 ) );\nvar v = it.next().value\nv = it.next().value\n","iterDedupe":"var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\nvar it = iterDedupe( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterDedupeBy":"var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\nfunction fcn( v ) { return v; };\nvar it = iterDedupeBy( arr, fcn );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterDeg2rad":"var r = random.iterators.uniform( -360.0, 360.0 );\nvar it = iterDeg2rad( r );\nvar v = it.next().value\nv = it.next().value\n","iterDigamma":"var r = random.iterators.uniform( 0.01, 5.0 );\nvar it = iterDigamma( r );\nvar v = it.next().value\nv = it.next().value\n","iterDiracComb":"var it = iterDiracComb();\nvar v = it.next().value\nv = it.next().value\n","iterDiracDelta":"var it = iterDiracDelta( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterDivide":"var it1 = array2iterator( [ 3.0, 2.0 ] );\nvar it2 = array2iterator( [ 1.0, 4.0 ] );\nvar it = iterDivide( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterDoWhileEach":"function predicate( v ) { return v === v };\nfunction f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterDoWhileEach( random.iterators.randu(), predicate, f );\nvar r = it.next().value\nr = it.next().value\n","iterEllipe":"var r = random.iterators.uniform( -1.0, 1.0 );\nvar it = iterEllipe( r );\nvar v = it.next().value\nv = it.next().value\n","iterEllipk":"var r = random.iterators.uniform( -1.0, 1.0 );\nvar it = iterEllipk( r );\nvar v = it.next().value\nv = it.next().value\n","iterEmpty":"var it = iterEmpty();\nvar bool = it.next().done\n","iterErf":"var it = iterErf( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterErfc":"var it = iterErfc( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterErfcinv":"var it = iterErfcinv( random.iterators.uniform( 0.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterErfinv":"var it = iterErfinv( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterEta":"var it = iterEta( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterEvenIntegersSeq":"var it = iterEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterEvery":"var arr = array2iterator( [ 1, 1, 1, 1, 0 ] );\nvar bool = iterEvery( arr )\n","iterEveryBy":"var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\nfunction fcn( v ) { return ( v > 0 ); };\nvar bool = iterEveryBy( arr, fcn )\n","iterExp":"var it = iterExp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterExp2":"var r = random.iterators.uniform( -50.0, 50.0 );\nvar it = iterExp2( r );\nvar v = it.next().value\nv = it.next().value\n","iterExp10":"var r = random.iterators.uniform( -50.0, 50.0 );\nvar it = iterExp10( r );\nvar v = it.next().value\nv = it.next().value\n","iterExpit":"var r = random.iterators.uniform( 0.0, 1.0 );\nvar it = iterExpit( r );\nvar v = it.next().value\nv = it.next().value\n","iterExpm1":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterExpm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterExpm1rel":"var r = random.iterators.uniform( -50.0, 50.0 );\nvar it = iterExpm1rel( r );\nvar v = it.next().value\nv = it.next().value\n","iterFactorial":"var it = iterFactorial( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterFactorialln":"var it = iterFactorialln( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterFactorialsSeq":"var it = iterFactorialsSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterFibonacciSeq":"var it = iterFibonacciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterFifthPowersSeq":"var it = iterFifthPowersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterFill":"var it = iterFill( random.iterators.randu(), 3.14, 0, 2 );\nvar r = it.next().value\nr = it.next().value\nr = it.next().value\n","iterFilter":"function f( v ) { return ( v > 2 ); };\nvar it1 = array2iterator( [ 1, 3, 2, 4 ] );\nvar it2 = iterFilter( it1, f );\nvar v = it2.next().value\nv = it2.next().value\n","iterFilterMap":"function f( v ) { if ( v > 2 ) { return v * 10 }; };\nvar it1 = array2iterator( [ 1, 3, 2, 4 ] );\nvar it2 = iterFilterMap( it1, f );\nvar v = it2.next().value\nv = it2.next().value\n","iterFirst":"var arr = array2iterator( [ 1, 0, 0, 0, 0 ] );\nvar v = iterFirst( arr )\n","iterFlatTopPulse":"var it = iterFlatTopPulse();\nvar v = it.next().value\nv = it.next().value\n","iterFloor":"var it = iterFloor( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterFloor2":"var it = iterFloor2( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterFloor10":"var it = iterFloor10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterFlow":"var o = {};\no.head = iterHead;\no.some = iterSome;\nvar fiter = iterFlow( o )\n","iterForEach":"function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterForEach( random.iterators.randu(), f );\nvar r = it.next().value\nr = it.next().value\n","iterFourthPowersSeq":"var it = iterFourthPowersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterFresnelc":"var r = random.iterators.uniform( 0.0, 10.0 );\nvar it = iterFresnelc( r );\nvar v = it.next().value\nv = it.next().value\n","iterFresnels":"var r = random.iterators.uniform( 0.0, 10.0 );\nvar it = iterFresnels( r );\nvar v = it.next().value\nv = it.next().value\n","iterGamma":"var it = iterGamma( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterGamma1pm1":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterGamma1pm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterGammaln":"var it = iterGammaln( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterHacovercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHacovercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterHacoversin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHacoversin( r );\nvar v = it.next().value\nv = it.next().value\n","iterHannPulse":"var it = iterHannPulse();\nvar v = it.next().value\nv = it.next().value\n","iterHavercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHavercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterHaversin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHaversin( r );\nvar v = it.next().value\nv = it.next().value\n","iterHead":"var it = iterHead( random.iterators.randu(), 5 );\nvar r = it.next().value\nr = it.next().value\n","iterIncrspace":"var it = iterIncrspace( 0, 101, 2 );\nvar v = it.next().value\nv = it.next().value\n","iterIntegersSeq":"var it = iterIntegersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterIntersection":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\nvar it = iterIntersection( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterIntersectionByHash":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\nfunction f( v ) { return v.toString(); };\nvar it = iterIntersectionByHash( it1, it2, f );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterInv":"var it = iterInv( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLanczosPulse":"var it = iterLanczosPulse();\nvar v = it.next().value\nv = it.next().value\n","iterLast":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar v = iterLast( arr )\n","iterLength":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar len = iterLength( arr )\n","iterLinspace":"var it = iterLinspace( 0, 99, 100 );\nvar v = it.next().value\nv = it.next().value\n","iterLn":"var it = iterLn( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog":"var x = random.iterators.uniform( 0.0, 100.0 );\nvar y = random.iterators.uniform( 0.0, 10.0 );\nvar it = iterLog( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterLog1mexp":"var it = iterLog1mexp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog1p":"var it = iterLog1p( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog1pexp":"var it = iterLog1pexp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog2":"var it = iterLog2( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog10":"var it = iterLog10( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLogit":"var r = random.iterators.uniform( 0.0, 1.0 );\nvar it = iterLogit( r );\nvar v = it.next().value\nv = it.next().value\n","iterLogspace":"var it = iterLogspace( 0, 3, 4 );\nvar v = it.next().value\nv = it.next().value\n","iterLucasSeq":"var it = iterLucasSeq();\nvar v = it.next().value\nv = it.next().value\n","iterMap":"function f( v ) { return v * 10.0; };\nvar it = iterMap( random.iterators.randu(), f );\nvar r = it.next().value\nr = it.next().value\n","iterMapN":"var it1 = array2iterator( [ 1.0, 2.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nfunction fcn( x, y ) { return x + y; };\nvar it = iterMapN( it1, it2, fcn );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","itermax":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar m = itermax( arr )\n","itermaxabs":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar m = itermaxabs( arr )\n","itermean":"var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = itermean( arr )\n","itermeanabs":"var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\nvar m = itermeanabs( arr )\n","itermeanabs2":"var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\nvar m = itermeanabs2( arr )\n","itermidrange":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar v = itermidrange( arr )\n","itermin":"var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\nvar m = itermin( arr )\n","iterminabs":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar m = iterminabs( arr )\n","itermmax":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmax( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmaxabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmaxabs( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmean":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmean( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmeanabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmeanabs( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmeanabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmeanabs2( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmidrange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmidrange( arr, 3 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itermmin":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmin( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermminabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermminabs( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","iterMod":"var it1 = array2iterator( [ 3.0, 2.0 ] );\nvar it2 = array2iterator( [ 1.0, 4.0 ] );\nvar it = iterMod( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","itermprod":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermprod( arr, 3 );\nvar p = it.next().value\np = it.next().value\np = it.next().value\np = it.next().value\n","itermrange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermrange( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermsum":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermsum( arr, 3 );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itermsumabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermsumabs( arr, 3 );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itermsumabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermsumabs2( arr, 3 );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","iterMultiply":"var it1 = array2iterator( [ 1.0, 2.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nvar it = iterMultiply( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterNegaFibonacciSeq":"var it = iterNegaFibonacciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegaLucasSeq":"var it = iterNegaLucasSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegativeEvenIntegersSeq":"var it = iterNegativeEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegativeIntegersSeq":"var it = iterNegativeIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegativeOddIntegersSeq":"var it = iterNegativeOddIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNone":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar bool = iterNone( arr )\n","iterNoneBy":"var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\nfunction fcn( v ) { return ( v <= 0 ); };\nvar bool = iterNoneBy( arr, fcn )\n","iterNonFibonacciSeq":"var it = iterNonFibonacciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonNegativeEvenIntegersSeq":"var it = iterNonNegativeEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonNegativeIntegersSeq":"var it = iterNonNegativeIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonPositiveEvenIntegersSeq":"var it = iterNonPositiveEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonPositiveIntegersSeq":"var it = iterNonPositiveIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonSquaresSeq":"var it = iterNonSquaresSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterNth":"var arr = array2iterator( [ 0, 0, 1, 0, 0 ] );\nvar v = iterNth( arr, 3 )\n","iterOddIntegersSeq":"var it = iterOddIntegersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterPeriodicSinc":"var it = iterPeriodicSinc( 7 );\nvar v = it.next().value\nv = it.next().value\n","iterPipeline":"var it1 = iterThunk( iterHead, 100 );\nfunction f( r ) { return ( r > 0.95 ); };\nvar it2 = iterThunk( iterSomeBy, 5, f );\nvar p = iterPipeline( it1, it2 );\nvar bool = p( random.iterators.randu() )\n","iterPop":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterPop( it1 );\nvar v = it2.next().value\nvar bool = it2.next().done\n","iterPositiveEvenIntegersSeq":"var it = iterPositiveEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterPositiveIntegersSeq":"var it = iterPositiveIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterPositiveOddIntegersSeq":"var it = iterPositiveOddIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterPow":"var x = random.iterators.uniform( 0.0, 2.0 );\nvar y = random.iterators.uniform( -2.0, 2.0 );\nvar it = iterPow( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterPrimesSeq":"var it = iterPrimesSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterprod":"var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar s = iterprod( arr )\n","iterPulse":"var it = iterPulse();\nvar v = it.next().value\nv = it.next().value\n","iterPush":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterPush( it1, 3, 4 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterRad2deg":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterRad2deg( r );\nvar v = it.next().value\nv = it.next().value\n","iterRamp":"var it = iterRamp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterrange":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar v = iterrange( arr )\n","iterReject":"function f( v ) { return ( v > 2 ); };\nvar it1 = array2iterator( [ 1, 3, 2, 4 ] );\nvar it2 = iterReject( it1, f );\nvar v = it2.next().value\nv = it2.next().value\n","iterReplicate":"var it1 = array2iterator( [ 1, 2, 3, 4 ] );\nvar it2 = iterReplicate( it1, 2 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\n","iterReplicateBy":"var it1 = array2iterator( [ 1, 2, 3, 4 ] );\nfunction f( v, i ) { return i + 1; };\nvar it2 = iterReplicateBy( it1, f );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\n","iterRound":"var it = iterRound( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterRound2":"var it = iterRound2( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterRound10":"var it = iterRound10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterRsqrt":"var it = iterRsqrt( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSawtoothWave":"var it = iterSawtoothWave();\nvar v = it.next().value\nv = it.next().value\n","iterShift":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterShift( it1 );\nvar v = it2.next().value\nvar bool = it2.next().done\n","iterSignum":"var it = iterSignum( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSin":"var it = iterSin( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSinc":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterSinc( r );\nvar v = it.next().value\nv = it.next().value\n","iterSineWave":"var it = iterSineWave();\nvar v = it.next().value\nv = it.next().value\n","iterSinh":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterSinh( r );\nvar v = it.next().value\nv = it.next().value\n","iterSinpi":"var it = iterSinpi( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSlice":"var it = iterSlice( random.iterators.randu(), 5, 10 );\nvar r = it.next().value\nr = it.next().value\n","iterSome":"var arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\nvar bool = iterSome( arr, 3 )\n","iterSomeBy":"var arr = array2iterator( [ 1, 1, 0, 0, 1 ] );\nfunction fcn( v ) { return ( v > 0 ); };\nvar bool = iterSomeBy( arr, 3, fcn )\n","iterSpence":"var r = random.iterators.uniform( 0.0, 100.0 );\nvar it = iterSpence( r );\nvar v = it.next().value\nv = it.next().value\n","iterSqrt":"var it = iterSqrt( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSqrt1pm1":"var r = random.iterators.uniform( 0.0, 100.0 );\nvar it = iterSqrt1pm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterSquaredTriangularSeq":"var it = iterSquaredTriangularSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterSquaresSeq":"var it = iterSquaresSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterSquareWave":"var it = iterSquareWave();\nvar v = it.next().value\nv = it.next().value\n","iterstdev":"var arr = array2iterator( [ 2.0, -5.0 ] );\nvar m = iterstdev( arr )\n","iterStep":"var it = iterStep( 0, 2, 10 );\nvar v = it.next().value\nv = it.next().value\n","iterStrided":"var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\nvar it = iterStrided( arr, 2, 1 );\nvar r = it.next().value\nr = it.next().value\n","iterStridedBy":"var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\nfunction stride( v, i ) { return (i % 10)+1; };\nvar it = iterStridedBy( arr, stride );\nvar r = it.next().value\nr = it.next().value\nr = it.next().value\n","iterSubtract":"var it1 = array2iterator( [ 1.0, 5.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nvar it = iterSubtract( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","itersum":"var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar s = itersum( arr )\n","itersumabs":"var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\nvar s = itersumabs( arr )\n","itersumabs2":"var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\nvar s = itersumabs2( arr )\n","iterTan":"var r = random.iterators.uniform( -1.57, 1.57 );\nvar it = iterTan( r );\nvar v = it.next().value\nv = it.next().value\n","iterTanh":"var r = random.iterators.uniform( -4.0, 4.0 );\nvar it = iterTanh( r );\nvar v = it.next().value\nv = it.next().value\n","iterThunk":"var fcn = iterThunk( iterSome, 3 );\nvar arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\nvar bool = fcn( arr )\n","iterTriangleWave":"var it = iterTriangleWave();\nvar v = it.next().value\nv = it.next().value\n","iterTriangularSeq":"var it = iterTriangularSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterTribonnaciSeq":"var it = iterTribonnaciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterTrigamma":"var r = random.iterators.uniform( 0.01, 50.0 );\nvar it = iterTrigamma( r );\nvar v = it.next().value\nv = it.next().value\n","iterTrunc":"var it = iterTrunc( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterTrunc2":"var it = iterTrunc2( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterTrunc10":"var it = iterTrunc10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterUnion":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\nvar it = iterUnion( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterUnique":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = iterUnique( it1 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUniqueBy":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nfunction f( a, b ) { return ( a !== b ); };\nvar it2 = iterUniqueBy( it1, f );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUniqueByHash":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nfunction f( v ) { return v.toString(); };\nvar it2 = iterUniqueByHash( it1, f );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUnitspace":"var it = iterUnitspace( 0, 99 );\nvar v = it.next().value\nv = it.next().value\n","iterUnshift":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterUnshift( it1, 3, 4 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUntilEach":"function predicate( v ) { return v !== v };\nfunction f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterUntilEach( random.iterators.randu(), predicate, f );\nvar r = it.next().value\nr = it.next().value\n","itervariance":"var arr = array2iterator( [ 2.0, -5.0 ] );\nvar s2 = itervariance( arr )\n","iterVercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterVercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterVersin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterVersin( r );\nvar v = it.next().value\nv = it.next().value\n","iterWhileEach":"function predicate( v ) { return v === v };\nfunction f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterWhileEach( random.iterators.randu(), predicate, f );\nvar r = it.next().value\nr = it.next().value\n","iterZeta":"var r = random.iterators.uniform( 1.1, 50.0 );\nvar it = iterZeta( r );\nvar v = it.next().value\nv = it.next().value\n","joinStream":"var s = joinStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","joinStream.factory":"var opts = { 'highWaterMark': 64 };\nvar createStream = joinStream.factory( opts );\nvar s = createStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","joinStream.objectMode":"var s = joinStream.objectMode();\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","kde2d":"var x = [ 1, 3, 5, 6, 21, 23, 16, 17, 20, 10 ];\nvar y = [ 0.40, 0.20, 0.20, 0.15, 0.05, 0.55, 0.6, 0.33, 0.8, 0.41 ];\nvar out = kde2d( x, y )\n","kebabcase":"var out = kebabcase( 'Hello World!' )\nout = kebabcase( 'I am a tiny little teapot' )\n","keyBy":"function toKey( v ) { return v.a; };\nvar arr = [ { 'a': 1 }, { 'a': 2 } ];\nkeyBy( arr, toKey )\n","keyByRight":"function toKey( v ) { return v.a; };\nvar arr = [ { 'a': 1 }, { 'a': 2 } ];\nkeyByRight( arr, toKey )\n","keysIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = keysIn( obj )\n","kruskalTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = kruskalTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = kruskalTest( arr, { 'groups': groups } )\n","kstest":"var rnorm = base.random.normal.factory({ 'seed': 4839 } );\nvar x = new Array( 100 );\nfor ( var i = 0; i < 100; i++ ) { x[ i ] = rnorm( 3.0, 1.0 ); }\nvar out = kstest( x, 'normal', 0.0, 1.0 )\nout = kstest( x, 'normal', 3.0, 1.0 )\nrunif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } )\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\nout = kstest( x, 'uniform', 0.0, 1.0 )\nout.print()\nout = kstest( x, 'uniform', 0.0, 1.0, { 'alpha': 0.1 } )\nrunif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } );\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\nout = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'less' } )\nout = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'greater' } )\nx = [ 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 ];\nout = kstest( x, 'uniform', 0.0, 1.0, { 'sorted': true } )\n","last":"var out = last( 'beep' )\nout = last( 'Boop', 2 )\nout = last( 'foo bar', 3 )\n","leveneTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = leveneTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = leveneTest( arr, { 'groups': groups } )\n","LinkedList":"var list = LinkedList();\nlist.push( 'foo' ).push( 'bar' );\nlist.length\nlist.pop()\nlist.length\nlist.pop()\nlist.length\n","linspace":"var arr = linspace( 0.0, 100.0, 6 )\narr = linspace( 0.0, 100.0, 5, { 'endpoint': false } )\narr = linspace( 0.0, 100.0, 6, { 'dtype': 'generic' } )\n","linspace.assign":"var arr = [ 0, 0, 0, 0, 0, 0 ];\nvar out = linspace.assign( 0, 100, arr )\nvar bool = ( arr === out )\narr = [ 0, 0, 0, 0, 0 ];\nout = linspace.assign( 0, 100, arr, { 'endpoint': false } )\n","LIU_NEGATIVE_OPINION_WORDS_EN":"var list = LIU_NEGATIVE_OPINION_WORDS_EN()\n","LIU_POSITIVE_OPINION_WORDS_EN":"var list = LIU_POSITIVE_OPINION_WORDS_EN()\n","LN_HALF":"LN_HALF\n","LN_PI":"LN_PI\n","LN_SQRT_TWO_PI":"LN_SQRT_TWO_PI\n","LN_TWO_PI":"LN_TWO_PI\n","LN2":"LN2\n","LN10":"LN10\n","LOG2E":"LOG2E\n","LOG10E":"LOG10E\n","logspace":"var arr = logspace( 0, 2, 6 )\n","lowercase":"var out = lowercase( 'bEEp' )\n","lowercaseKeys":"var obj = { 'A': 1, 'B': 2 };\nvar out = lowercaseKeys( obj )\n","lowess":"var x = new Float64Array( 100 );\nvar y = new Float64Array( x.length );\nfor ( var i = 0; i < x.length; i++ ) {\n x[ i ] = i;\n y[ i ] = ( 0.5*i ) + ( 10.0*base.random.randn() );\n }\nvar out = lowess( x, y );\nvar yhat = out.y;\nvar h = Plot( [ x, x ], [ y, yhat ] );\nh.lineStyle = [ 'none', '-' ];\nh.symbols = [ 'closed-circle', 'none' ];\nh.view( 'window' );\n","lpad":"var out = lpad( 'a', 5 )\nout = lpad( 'beep', 10, 'b' )\nout = lpad( 'boop', 12, 'beep' )\n","ltrim":"var out = ltrim( ' \\r\\n\\t  Beep \\t\\t\\n  ' )\n","ltrimN":"var out = ltrimN( '  abc  ', 2 )\nvar out = ltrimN( '!!!abc!!!', 2, '!' )\n","MALE_FIRST_NAMES_EN":"var list = MALE_FIRST_NAMES_EN()\n","map":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = map( arr, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = map( arr, f );\nvar v = out.get( 1, 1 )\n","map.assign":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmap.assign( arr, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\narr = array( arr, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmap.assign( arr, out, f );\nvar v = out.get( 1, 1 )\n","map2":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = map2( x, y, f )\nx = array( x, { 'shape': [ 2, 3 ] } );\ny = array( y, { 'shape': [ 2, 3 ] } );\nout = map2( x, y, f );\nvar v = out.get( 1, 1 )\n","map2.assign":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmap2.assign( x, y, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\nx = array( x, opts );\ny = array( y, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmap2.assign( x, y, out, f );\nvar v = out.get( 1, 1 )\n","map2d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ -1, -2, -3 ], [ -4, -5, -6 ] ];\nvar out = map2d( arr, f );\nout[ 0 ]\nout[ 1 ]\n","map2Right":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = map2Right( x, y, f )\nx = array( x, { 'shape': [ 2, 3 ] } );\ny = array( y, { 'shape': [ 2, 3 ] } );\nout = map2Right( x, y, f );\nvar v = out.get( 1, 1 )\n","map2Right.assign":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmap2Right.assign( x, y, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\nx = array( x, opts );\ny = array( y, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmap2Right.assign( x, y, out, f );\nvar v = out.get( 1, 1 )\n","map3d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ [ -1, -2, -3 ] ], [ [ -4, -5, -6 ] ] ];\nvar out = map3d( arr, f );\nout[ 0 ][ 0 ]\nout[ 1 ][ 0 ]\n","map4d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ [ [ -1, -2, -3 ] ] ], [ [ [ -4, -5, -6 ] ] ] ];\nvar out = map4d( arr, f );\nout[ 0 ][ 0 ][ 0 ]\nout[ 1 ][ 0 ][ 0 ]\n","map5d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ [ [ [ -1, -2, -3 ] ] ] ], [ [ [ [ -4, -5, -6 ] ] ] ] ];\nvar out = map5d( arr, f );\nout[ 0 ][ 0 ][ 0 ][ 0 ]\nout[ 1 ][ 0 ][ 0 ][ 0 ]\n","mapArguments":"function foo( a, b, c ) { return [ a, b, c ]; };\nfunction clbk( v ) { return v * 2; };\nvar bar = mapArguments( foo, clbk );\nvar out = bar( 1, 2, 3 )\n","mapFun":"function fcn( i ) { return i; };\nvar arr = mapFun( fcn, 5 )\n","mapFunAsync":"function fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n     next( null, i );\n }\n };\nfunction done( error, arr ) {\n if ( error ) {\n     throw error;\n }\n console.log( arr );\n };\nmapFunAsync( fcn, 10, done )\nfunction fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n     next( null, i );\n }\n };\nfunction done( error, arr ) {\n if ( error ) {\n     throw error;\n }\n console.log( arr );\n };\nvar opts = { 'limit': 2 };\nmapFunAsync( fcn, 10, opts, done )\nfunction fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n     next( null, i );\n }\n };\nfunction done( error, arr ) {\n if ( error ) {\n     throw error;\n }\n console.log( arr );\n };\nvar opts = { 'series': true };\nmapFunAsync( fcn, 10, opts, done )\n","mapFunAsync.factory":"function fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n     next( null, i );\n }\n };\nvar opts = { 'series': true };\nvar f = mapFunAsync.factory( opts, fcn );\nfunction done( error, arr ) {\n if ( error ) {\n     throw error;\n }\n console.log( arr );\n };\nf( 10, done )\n","mapKeys":"function transform( key, value ) { return key + value; };\nvar obj = { 'a': 1, 'b': 2 };\nvar out = mapKeys( obj, transform )\n","mapKeysAsync":"function transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n     throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2 };\nmapKeysAsync( obj, transform, done )\nfunction transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n     throw error;\n }\n console.log( out );\n };\nvar opts = { 'limit': 2 };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapKeysAsync( obj, opts, transform, done )\nfunction transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n     throw error;\n }\n console.log( out );\n };\nvar opts = { 'series': true };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapKeysAsync( obj, opts, transform, done )\n","mapKeysAsync.factory":"function transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     next( null, key+':'+value );\n }\n };\nvar opts = { 'series': true };\nvar f = mapKeysAsync.factory( opts, transform );\nfunction done( error, out ) {\n if ( error ) {\n     throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nf( obj, done )\nobj = { 'beep': 'boop' };\nf( obj, done )\n","mapReduce":"var f1 = naryFunction( base.abs, 1 );\nvar f2 = naryFunction( base.add, 2 );\nvar arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\nvar out = mapReduce( arr, 0.0, f1, f2 )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = mapReduce( arr, 0.0, f1, f2 )\n","mapReduceRight":"var f1 = naryFunction( base.abs, 1 );\nvar f2 = naryFunction( base.add, 2 );\nvar arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\nvar out = mapReduceRight( arr, 0.0, f1, f2 )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = mapReduceRight( arr, 0.0, f1, f2 )\n","mapRight":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = mapRight( arr, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = mapRight( arr, f );\nvar v = out.get( 1, 1 )\n","mapRight.assign":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmapRight.assign( arr, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\narr = array( arr, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmapRight.assign( arr, out, f );\nvar v = out.get( 1, 1 )\n","mapValues":"function transform( value, key ) { return key + value; };\nvar obj = { 'a': 1, 'b': 2 };\nvar out = mapValues( obj, transform )\n","mapValuesAsync":"function transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n     throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2 };\nmapValuesAsync( obj, transform, done )\nfunction transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n     throw error;\n }\n console.log( out );\n };\nvar opts = { 'limit': 2 };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapValuesAsync( obj, opts, transform, done )\nfunction transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n     throw error;\n }\n console.log( out );\n };\nvar opts = { 'series': true };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapValuesAsync( obj, opts, transform, done )\n","mapValuesAsync.factory":"function transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     next( null, key+':'+value );\n }\n };\nvar opts = { 'series': true };\nvar f = mapValuesAsync.factory( opts, transform );\nfunction done( error, out ) {\n if ( error ) {\n     throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nf( obj, done )\nobj = { 'beep': 'boop' };\nf( obj, done )\n","maskArguments":"function foo( a, b ) { return [ a, b ]; };\nvar bar = maskArguments( foo, [ 1, 0, 1 ] );\nvar out = bar( 1, 2, 3 )\n","MAX_ARRAY_LENGTH":"MAX_ARRAY_LENGTH\n","MAX_TYPED_ARRAY_LENGTH":"MAX_TYPED_ARRAY_LENGTH\n","maybeBroadcastArray":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = maybeBroadcastArray( x, [ 3, 2, 2 ] )\nsh = y.shape\nvar v = y.get( 0, 0, 0 )\nv = y.get( 0, 0, 1 )\nv = y.get( 0, 1, 0 )\nv = y.get( 0, 1, 1 )\nv = y.get( 1, 0, 0 )\nv = y.get( 1, 1, 0 )\nv = y.get( 2, 0, 0 )\nv = y.get( 2, 1, 1 )\n","maybeBroadcastArrays":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = ndzeros( [ 3, 2, 2 ] )\nvar out = maybeBroadcastArrays( [ x, y ] )\nvar bx = out[ 0 ]\nsh = bx.shape\nvar v = bx.get( 0, 0, 0 )\nv = bx.get( 0, 0, 1 )\nv = bx.get( 0, 1, 0 )\nv = bx.get( 0, 1, 1 )\nv = bx.get( 1, 0, 0 )\nv = bx.get( 1, 1, 0 )\nv = bx.get( 2, 0, 0 )\nv = bx.get( 2, 1, 1 )\n","memoize":"function factorial( n ) {\n var prod;\n var i;\n prod = 1;\n for ( i = n; i > 1; i-- ) {\n     prod *= i;\n }\n return prod;\n };\nvar memoized = memoize( factorial );\nvar v = memoized( 5 )\nv = memoized( 5 )\n","merge":"var target = { 'a': 'beep' };\nvar source = { 'a': 'boop', 'b': 'bap' };\nvar out = merge( target, source )\nvar bool = ( out === target )\n","merge.factory":"var opts = {\n 'level': 100,\n 'copy': true,\n 'override': true,\n 'extend': true\n };\nvar merge = merge.factory( opts )\nmerge = merge.factory( { 'level': 2 } );\nvar target = {\n '1': { 'a': 'beep', '2': { '3': null, 'b': [ 5, 6, 7 ] } }\n };\nvar source = {\n '1': { 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } }\n };\nvar out = merge( target, source )\nmerge = merge.factory( { 'copy': false } );\ntarget = {};\nsource = { 'a': [ 1, 2, 3 ] };\nout = merge( target, source );\nvar bool = ( out.a === source.a )\nmerge = merge.factory( { 'override': false } );\ntarget = { 'a': 'beep', 'b': 'boop' };\nsource = { 'a': null, 'c': 'bop' };\nout = merge( target, source )\nfunction strategy( a, b, key ) {\n // a => target value\n // b => source value\n // key => object key\n if ( key === 'a' ) {\n     return b;\n }\n if ( key === 'b' ) {\n     return a;\n }\n return 'bebop';\n };\nmerge = merge.factory( { 'override': strategy } );\ntarget = { 'a': 'beep', 'b': 'boop', 'c': 1234 };\nsource = { 'a': null, 'b': {}, 'c': 'bop' };\nout = merge( target, source )\nmerge = merge.factory( { 'extend': false } );\ntarget = { 'a': 'beep', 'b': 'boop' };\nsource = { 'b': 'hello', 'c': 'world' };\nout = merge( target, source )\n","MILLISECONDS_IN_DAY":"var days = 3.14;\nvar ms = days * MILLISECONDS_IN_DAY\n","MILLISECONDS_IN_HOUR":"var hrs = 3.14;\nvar ms = hrs * MILLISECONDS_IN_HOUR\n","MILLISECONDS_IN_MINUTE":"var mins = 3.14;\nvar ms = mins * MILLISECONDS_IN_MINUTE\n","MILLISECONDS_IN_SECOND":"var secs = 3.14;\nvar ms = secs * MILLISECONDS_IN_SECOND\n","MILLISECONDS_IN_WEEK":"var weeks = 3.14;\nvar ms = weeks * MILLISECONDS_IN_WEEK\n","MINARD_NAPOLEONS_MARCH":"var data = MINARD_NAPOLEONS_MARCH();\nvar army = data.army\nvar cities = data.cities\nvar labels = data.labels\nvar river = data.river\nvar t = data.temperature\n","MINUTES_IN_DAY":"var days = 3.14;\nvar mins = days * MINUTES_IN_DAY\n","MINUTES_IN_HOUR":"var hrs = 3.14;\nvar mins = hrs * MINUTES_IN_HOUR\n","MINUTES_IN_WEEK":"var wks = 3.14;\nvar mins = wks * MINUTES_IN_WEEK\n","minutesInMonth":"var num = minutesInMonth()\nnum = minutesInMonth( 2 )\nnum = minutesInMonth( 2, 2016 )\nnum = minutesInMonth( 2, 2017 )\nnum = minutesInMonth( 'feb', 2016 )\nnum = minutesInMonth( 'february', 2016 )\n","minutesInYear":"var num = minutesInYear()\nnum = minutesInYear( 2016 )\nnum = minutesInYear( 2017 )\n","MOBY_DICK":"var data = MOBY_DICK()\n","MONTH_NAMES_EN":"var list = MONTH_NAMES_EN()\n","MONTHS_IN_YEAR":"var yrs = 3.14;\nvar mons = yrs * MONTHS_IN_YEAR\n","moveProperty":"var obj1 = { 'a': 'b' };\nvar obj2 = {};\nvar bool = moveProperty( obj1, 'a', obj2 )\nbool = moveProperty( obj1, 'c', obj2 )\n","MultiSlice":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\n","MultiSlice.prototype.ndims":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\nms.ndims\n","MultiSlice.prototype.data":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\nms.data\n","MultiSlice.prototype.toString":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\nms.toString()\n","MultiSlice.prototype.toJSON":"var s = new Slice( 2, 10, 1 );\nvar ms = new MultiSlice( 2, s );\nms.toJSON()\n","namedtypedtuple":"var opts = {};\nopts.name = 'Point';\nvar factory = namedtypedtuple( [ 'x', 'y' ], opts );\nvar tuple = factory();\n","NAN":"NAN\n","naryFunction":"function foo( a, b, c ) { return [ a, b, c ]; };\nvar bar = naryFunction( foo, 2 );\nvar out = bar( 1, 2, 3 )\n","nativeClass":"var str = nativeClass( 'a' )\nstr = nativeClass( 5 )\nfunction Beep(){};\nstr = nativeClass( new Beep() )\n","ndarray":"var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\nvar d = [ 2, 2 ]; // shape\nvar s = [ 2, 1 ]; // strides\nvar o = 0; // index offset\nvar arr = ndarray( 'generic', b, d, s, o, 'row-major' )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","ndarray.prototype.byteLength":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.byteLength\n","ndarray.prototype.BYTES_PER_ELEMENT":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.BYTES_PER_ELEMENT\n","ndarray.prototype.data":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar buf = arr.data\n","ndarray.prototype.dtype":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar dt = arr.dtype\n","ndarray.prototype.flags":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar fl = arr.flags\n","ndarray.prototype.length":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar len = arr.length\n","ndarray.prototype.ndims":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar n = arr.ndims\n","ndarray.prototype.offset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.offset\n","ndarray.prototype.order":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar ord = arr.order\n","ndarray.prototype.shape":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sh = arr.shape\n","ndarray.prototype.strides":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar st = arr.strides\n","ndarray.prototype.get":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.get( 1, 1 )\n","ndarray.prototype.iget":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.iget( 3 )\n","ndarray.prototype.set":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\narr.set( 1, 1, -4.0 );\narr.get( 1, 1 )\n","ndarray.prototype.iset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\narr.iset( 3, -4.0 );\narr.iget( 3 )\n","ndarray.prototype.toString":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toString()\n","ndarray.prototype.toJSON":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toJSON()\n","ndarray2array":"var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar out = ndarray2array( arr )\n","ndarray2fancy":"var b = [ 1.0, 2.0, 3.0, 4.0 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar x = ndarray( 'generic', b, d, s, o, 'row-major' );\nvar arr = ndarray2fancy( x );\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","ndarray2fancy.factory":"var b = [ 1.0, 2.0, 3.0, 4.0 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar x = ndarray( 'generic', b, d, s, o, 'row-major' );\nvar f = ndarray2fancy.factory();\nvar y = f( x );\n","ndarray2fancy.idx":"var opts = { 'dtype': 'int32' };\nvar buf = new Int32Array( [ 1, 2, 3, 4 ] );\nvar arr = array( buf, opts );\nvar idx = ndarray2fancy.idx( arr );\n","ndarray2json":"var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar out = ndarray2json( arr )\n","ndarrayCastingModes":"var out = ndarrayCastingModes()\n","ndarrayDataBuffer":"var opts = { 'dtype': 'float64' };\nvar out = ndarrayDataBuffer( ndzeros( [ 3, 3, 3 ], opts ) )\n","ndarrayDataType":"var opts = { 'dtype': 'float64' };\nvar dt = ndarrayDataType( ndzeros( [ 3, 3, 3 ], opts ) )\n","ndarrayDataTypes":"var out = ndarrayDataTypes()\nout = ndarrayDataTypes( 'floating_point' )\nout = ndarrayDataTypes( 'floating_point_and_generic' )\n","ndarrayDispatch":"var t = [ 'float64', 'float64', 'float32', 'float32' ];\nvar d = [ base.abs, base.absf ];\nvar f = ndarrayDispatch( base.ndarrayUnary, t, d, 2, 1, 1 );\nvar xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar x = ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );\nvar ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar y = ndarray( 'float64', ybuf, [ 4 ], [ 1 ], 0, 'row-major' );\nf( x, y );\nybuf\n","ndarrayFlag":"var out = ndarrayFlag( ndzeros( [ 3, 3, 3 ] ), 'READONLY' )\n","ndarrayFlags":"var out = ndarrayFlags( ndzeros( [ 3, 3, 3 ] ) )\n","ndarrayIndexModes":"var out = ndarrayIndexModes()\n","ndarraylike2ndarray":"var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar out = ndarraylike2ndarray( arr )\n","ndarrayMinDataType":"var dt = ndarrayMinDataType( 3.141592653589793 )\ndt = ndarrayMinDataType( 3 )\ndt = ndarrayMinDataType( -3 )\ndt = ndarrayMinDataType( '-3' )\n","ndarrayMostlySafeCasts":"var out = ndarrayMostlySafeCasts( 'float32' )\n","ndarrayNextDataType":"var out = ndarrayNextDataType( 'float32' )\n","ndarrayOffset":"var n = ndarrayOffset( ndzeros( [ 3, 3, 3 ] ) )\n","ndarrayOrder":"var opts = { 'order': 'row-major' };\nvar dt = ndarrayOrder( ndzeros( [ 3, 3, 3 ], opts ) )\n","ndarrayOrders":"var out = ndarrayOrders()\n","ndarrayPromotionRules":"var out = ndarrayPromotionRules( 'float32', 'int32' )\n","ndarraySafeCasts":"var out = ndarraySafeCasts( 'float32' )\n","ndarraySameKindCasts":"var out = ndarraySameKindCasts( 'float32' )\n","ndarrayShape":"var out = ndarrayShape( ndzeros( [ 3, 3, 3 ] ) )\n","ndarrayStride":"var out = ndarrayStride( ndzeros( [ 3, 3, 3 ] ), 0 )\n","ndarrayStrides":"var out = ndarrayStrides( ndzeros( [ 3, 3, 3 ] ) )\n","ndat":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nndat( x, 0, 1 )\nndat( x, 1, 0 )\n","ndempty":"var arr = ndempty( [ 2, 2 ] )\nvar sh = arr.shape\nvar dt = arr.dtype\n","ndemptyLike":"var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\nvar sh = x.shape\nvar dt = x.dtype\nvar y = ndemptyLike( x )\nsh = y.shape\ndt = y.dtype\n","ndfilter":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { return v > 2.0; };\nvar y = ndfilter( x, f );\nndarray2array( y )\n","ndfilterMap":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { if ( v > 2.0 ) { return v * 10.0; } };\nvar y = ndfilterMap( x, f );\nndarray2array( y )\n","ndforEach":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { if ( v !== v ) { throw new Error( '...' ); } };\nndforEach( x, f );\n","ndims":"var n = ndims( ndzeros( [ 3, 3, 3 ] ) )\n","ndindex":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\n","ndindex.free":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nndindex.free( idx.id )\n","ndindex.get":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nndindex.get( idx.id )\n","ndindex.cartesianIndex":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = ndindex.cartesianIndex( x );\n","ndindex.linearIndex":"var x = ndempty( [ 5 ], { 'dtype': 'int32' } );\nvar idx = ndindex.linearIndex( x );\n","ndindex.prototype.data":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.data\n","ndindex.prototype.dtype":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.dtype\n","ndindex.prototype.id":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.id\n","ndindex.prototype.isCached":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.isCached\n","ndindex.prototype.kind":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x, { 'kind': 'cartesian' } );\nidx.kind\n","ndindex.prototype.type":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.type\n","ndindex.prototype.toString":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.toString()\n","ndindex.prototype.toJSON":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.toJSON()\n","nditerColumnEntries":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerColumnEntries( x );\nvar v = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\nv = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\n","nditerColumns":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerColumns( x );\nvar v = it.next().value;\nndarray2array( v )\nv = it.next().value;\nndarray2array( v )\n","nditerEntries":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerEntries( x );\nvar v = it.next().value\nv = it.next().value\n","nditerIndices":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerIndices( x.shape );\nvar v = it.next().value\nv = it.next().value\n","nditerInterleaveSubarrays":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerInterleaveSubarrays( [ x, x ], 2 );\nvar v = it.next().value;\nndarray2array( v )\n","nditerMatrices":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerMatrices( x );\nvar v = it.next().value;\nndarray2array( v )\n","nditerMatrixEntries":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerMatrixEntries( x );\nvar v = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\n","nditerRowEntries":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerRowEntries( x );\nvar v = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\nv = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\n","nditerRows":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerRows( x );\nvar v = it.next().value;\nndarray2array( v )\nv = it.next().value;\nndarray2array( v )\n","nditerSelectDimension":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerSelectDimension( x, 0 );\nvar v = it.next().value;\nndarray2array( v )\n","nditerStacks":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerStacks( x, [ 1, 2 ] );\nvar v = it.next().value;\nndarray2array( v )\n","nditerSubarrays":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerSubarrays( x, 2 );\nvar v = it.next().value;\nndarray2array( v )\n","nditerValues":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerValues( x );\nvar v = it.next().value\nv = it.next().value\n","ndmap":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { return v*10.0; };\nvar y = ndmap( x, f );\nndarray2array( y )\n","ndreject":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { return v <= 2.0; };\nvar y = ndreject( x, f );\nndarray2array( y )\n","ndslice":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar s = new MultiSlice( null, 1 )\nvar y = ndslice( x, s )\ny.shape\nndarray2array( y )\n","ndsliceAssign":"var y = ndzeros( [ 2, 2 ] )\nvar x = scalar2ndarray( 3.0 )\nvar s = new MultiSlice( null, 1 )\nvar out = ndsliceAssign( x, y, s )\nvar bool = ( out === y )\nndarray2array( y )\n","ndsliceDimension":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceDimension( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndsliceDimensionFrom":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceDimensionFrom( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndsliceDimensionTo":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceDimensionTo( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndsliceFrom":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceFrom( x, 0, 1 )\ny.shape\nndarray2array( y )\n","ndsliceTo":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceTo( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndzeros":"var arr = ndzeros( [ 2, 2 ] )\nvar sh = arr.shape\nvar dt = arr.dtype\n","ndzerosLike":"var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\nvar sh = x.shape\nvar dt = x.dtype\nvar y = ndzerosLike( x )\nsh = y.shape\ndt = y.dtype\n","nextGraphemeClusterBreak":"var out = nextGraphemeClusterBreak( 'last man standing', 4 )\nout = nextGraphemeClusterBreak( 'presidential election', 8 )\nout = nextGraphemeClusterBreak( 'अनुच्छेद', 1 )\nout = nextGraphemeClusterBreak( '🌷' )\n","nextTick":"function f() { console.log( 'beep' ); };\nnextTick( f )\n","NIGHTINGALES_ROSE":"var data = NIGHTINGALES_ROSE()\n","NINF":"NINF\n","NODE_VERSION":"NODE_VERSION\n","none":"var arr = [ 0, 0, 0, 0, 0 ];\nvar bool = none( arr )\n","noneBy":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ 1, 2, 3, 4 ];\nvar bool = noneBy( arr, negative )\n","noneByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nnoneByAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nnoneByAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nnoneByAsync( arr, opts, predicate, done )\n","noneByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = noneByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","noneByRight":"function positive( v ) { return ( v > 0 ); };\nvar arr = [ -1, -2, -3, -4 ];\nvar bool = noneByRight( arr, positive )\n","noneByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nnoneByRightAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nnoneByRightAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nnoneByRightAsync( arr, opts, predicate, done )\n","noneByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = noneByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","noneInBy":"function negative( v ) { return ( v < 0 ); };\nvar obj = { 'a': 1, 'b': 2, 'c': 4 };\nvar bool = noneInBy( obj, negative )\n","nonEnumerableProperties":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = false;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar props = nonEnumerableProperties( obj )\n","nonEnumerablePropertiesIn":"var props = nonEnumerablePropertiesIn( [] )\n","nonEnumerablePropertyNames":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = nonEnumerablePropertyNames( obj )\n","nonEnumerablePropertyNamesIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = nonEnumerablePropertyNamesIn( obj )\n","nonEnumerablePropertySymbols":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = nonEnumerablePropertySymbols( obj )\n","nonEnumerablePropertySymbolsIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? 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Object.assign( {}, { 'a': 1 }, { 'b': 2 } )\n","Object.create":"var o = Object.create( {}, { 'a': { 'value': 1 } } )\n","Object.defineProperties":"var o = Object.defineProperties( {}, { 'a': { 'value': 1 } } )\n","Object.defineProperty":"var o = Object.defineProperty( {}, 'a', {\n","Object.entries":"var o = Object.entries( { 'a': 1, 'b': 2 } )\n","Object.freeze":"var o = Object.freeze( { 'a': 1 } )\n","Object.getOwnPropertyDescriptor":"var o = Object.getOwnPropertyDescriptor( { 'a': 1 }, 'a' )\n","Object.getOwnPropertyDescriptors":"var o = Object.getOwnPropertyDescriptors( { 'a': 1, 'b': 2 } )\n","Object.getOwnPropertyNames":"var o = Object.getOwnPropertyNames( { 'a': 1, 'b': 2 } )\n","Object.getOwnPropertySymbols":"var o = Object.getOwnPropertySymbols( { 'a': 1, 'b': 2 } )\n","Object.getPrototypeOf":"var o = Object.getPrototypeOf( { 'a': 1, 'b': 2 } )\n","Object.hasOwn":"var o = Object.hasOwn( { 'a': 1, 'b': 2 }, 'a' )\n","Object.is":"var o = Object.is( 1, 1 )\nvar o = Object.is( 1, '1' )\n","Object.isExtensible":"var o = Object.isExtensible( { 'a': 1 } )\n","Object.isFrozen":"var o = Object.isFrozen( { 'a': 1 } )\nvar o = Object.isFrozen( Object.freeze( { 'a': 1 } ) )\n","Object.isSealed":"var o = Object.isSealed( { 'a': 1 } )\nvar o = Object.isSealed( Object.seal( { 'a': 1 } ) )\n","Object.keys":"var o = Object.keys( { 'a': 1, 'b': 2 } )\n","Object.preventExtensions":"var o = Object.preventExtensions( { 'a': 1 } )\no.b = 2;\no\n","Object.seal":"var o = Object.seal( { 'a': 1 } )\no.b = 2;\no\ndelete o.a;\no\n","Object.setPrototypeOf":"var o = Object.setPrototypeOf( { 'a': 1 }, { 'b': 2 } )\no.b\n","Object.values":"var o = Object.values( { 'a': 1, 'b': 2 } )\n","Object.prototype.toLocaleString":"var o = Object.prototype.toLocaleString.call( { 'a': 1, 'b': 2 } )\n","Object.prototype.toString":"var o = Object.prototype.toString.call( { 'a': 1, 'b': 2 } )\n","Object.prototype.valueOf":"var o = Object.prototype.valueOf.call( { 'a': 1, 'b': 2 } )\n","Object.prototype.hasOwnProperty":"var o = Object.prototype.hasOwnProperty.call( { 'a': 1, 'b': 2 }, 'a' )\n","Object.prototype.isPrototypeOf":"var p = { 'a': 1 };\nvar o = { '__proto__': p };\nvar b = o.isPrototypeOf( p );\n","Object.prototype.propertyIsEnumerable":"var o = { 'a': 1, 'b': 2 };\nvar bool = Object.prototype.propertyIsEnumerable.call( o, 'a' )\n","Object.prototype.constructor":"var o = new Object( null );\nvar ctr = o.constructor;\n","objectEntries":"var obj = { 'beep': 'boop', 'foo': 'bar' };\nvar entries = objectEntries( obj )\n","objectEntriesIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar entries = objectEntriesIn( obj )\n","objectFromEntries":"var entries = [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ];\nvar obj = objectFromEntries( entries )\n","objectInverse":"var obj = { 'a': 'beep', 'b': 'boop' };\nvar out = objectInverse( obj )\nobj = { 'a': 'beep', 'b': 'beep' };\nout = objectInverse( obj )\nobj = {};\nobj.a = 'beep';\nobj.b = 'boop';\nobj.c = 'beep';\nout = objectInverse( obj, { 'duplicates': false } )\n","objectInverseBy":"function transform( key, value ) { return key + value; };\nvar obj = { 'a': 'beep', 'b': 'boop' };\nvar out = objectInverseBy( obj, transform )\nfunction transform( key, value ) { return value; };\nobj = { 'a': 'beep', 'b': 'beep' };\nout = objectInverseBy( obj, transform )\nobj = {};\nobj.a = 'beep';\nobj.b = 'boop';\nobj.c = 'beep';\nout = objectInverseBy( obj, { 'duplicates': false }, transform )\n","objectKeys":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = objectKeys( obj )\n","objectValues":"var obj = { 'beep': 'boop', 'foo': 'bar' };\nvar vals = objectValues( obj )\n","objectValuesIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar values = objectValuesIn( obj )\n","omit":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = omit( obj1, 'b' )\n","omitBy":"function predicate( key, value ) { return ( value > 1 ); };\nvar obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = omitBy( obj1, predicate )\n","open":"function onOpen( error, fd ) {\n if ( error ) {\n     console.error( error.message );\n } else {\n     close.sync( fd );\n }\n };\nopen( './beep/boop.txt', onOpen );\n","open.sync":"var fd = open.sync( './beep/boop.txt' );\nif ( !isError( fd ) ) { close.sync( fd ); };\n","openURL":"var out = openURL( 'https://google.com' );\n","ordinalize":"var out = ordinalize( '1' )\nout = ordinalize( 2, { 'suffixOnly': true } )\nout = ordinalize( '3', { 'lang': 'es' } )\n","PACE_BOSTON_HOUSE_PRICES":"var data = PACE_BOSTON_HOUSE_PRICES()\n","pad":"var out = pad( 'a', 5 )\nout = pad( 'a', 10, { 'lpad': 'b' } )\nout = pad( 'a', 12, { 'rpad': 'b' } )\nvar opts = { 'lpad': 'a', 'rpad': 'c' };\nout = pad( 'b', 11, opts )\nopts.centerRight = false;\nout = pad( 'b', 10, opts )\nopts.centerRight = true;\nout = pad( 'b', 10, opts )\nopts = { 'lpad': 'boop', 'rpad': 'woot' };\nout = pad( 'beep', 10, opts )\nout = pad( 'beep', 2 )\nopts = { 'lpad': 'b' };\nout = pad( 'beep', 2, opts )\nopts = { 'lpad': '@', 'rpad': '!' };\nout = pad( 'beep', 2, opts )\nout = pad( 'abcdef', 3, opts )\nopts.centerRight = true;\nout = pad( 'abcdef', 3, opts )\n","padjust":"var pvalues = [ 0.008, 0.03, 0.123, 0.6, 0.2 ];\nvar out = padjust( pvalues, 'bh' )\nout = padjust( pvalues, 'bonferroni' )\nout = padjust( pvalues, 'by' )\nout = padjust( pvalues, 'holm' )\nout = padjust( pvalues, 'hommel' )\n","papply":"function add( x, y ) { return x + y; };\nvar add2 = papply( add, 2 );\nvar sum = add2( 3 )\n","papplyRight":"function say( text, name ) { return text + ', ' + name + '.'; };\nvar toGrace = papplyRight( say, 'Grace Hopper' );\nvar str = toGrace( 'Hello' )\nstr = toGrace( 'Thank you' )\n","parallel":"function done( error ) { if ( error ) { throw error; } };\nvar files = [ './a.js', './b.js' ];\nparallel( files, done );\nvar opts = { 'workers': 8 };\nparallel( files, opts, done );\n","parseJSON":"var obj = parseJSON( '{\"beep\":\"boop\"}' )\nfunction reviver( key, value ) {\n if ( key === '' ) { return value; }\n if ( key === 'beep' ) { return value; }\n };\nvar str = '{\"beep\":\"boop\",\"a\":\"b\"}';\nvar out = parseJSON( str, reviver )\n","pascalcase":"var out = pascalcase( 'Hello World!' )\nout = pascalcase( 'beep boop' )\n","PATH_DELIMITER":"PATH_DELIMITER\nvar path = '/usr/bin:/bin:/usr/sbin';\nvar parts = path.split( PATH_DELIMITER )\npath = 'C:\\\\Windows\\\\system32;C:\\\\Windows';\nparts = path.split( PATH_DELIMITER )\n","PATH_DELIMITER_POSIX":"PATH_DELIMITER_POSIX\nvar PATH = '/usr/bin:/bin:/usr/sbin:/sbin:/usr/local/bin';\nvar paths = PATH.split( PATH_DELIMITER_POSIX )\n","PATH_DELIMITER_WIN32":"PATH_DELIMITER_WIN32\nvar PATH = 'C:\\\\Windows\\\\system32;C:\\\\Windows;C:\\\\Program Files\\\\node\\\\';\nvar paths = PATH.split( PATH_DELIMITER_WIN32 )\n","PATH_SEP":"PATH_SEP\nvar parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP )\nparts = 'foo/bar/baz'.split( PATH_SEP )\n","PATH_SEP_POSIX":"PATH_SEP_POSIX\nvar parts = 'foo/bar/baz'.split( PATH_SEP_POSIX )\n","PATH_SEP_WIN32":"PATH_SEP_WIN32\nvar parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP_WIN32 )\n","pcorrtest":"var rho = 0.5;\nvar x = new Array( 300 );\nvar y = new Array( 300 );\nfor ( var i = 0; i < 300; i++ ) {\nx[ i ] = base.random.normal( 0.0, 1.0 );\ny[ i ] = ( rho * x[ i ] ) + base.random.normal( 0.0,\nbase.sqrt( 1.0 - (rho*rho) ) );\n }\nvar out = pcorrtest( x, y )\nvar table = out.print()\n","percentEncode":"var out = percentEncode( '☃' )\n","PHI":"PHI\n","PI":"PI\n","PI_SQUARED":"PI_SQUARED\n","pick":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = pick( obj1, 'b' )\n","pickArguments":"function foo( a, b ) { return [ a, b ]; };\nvar bar = pickArguments( foo, [ 0, 2 ] );\nvar out = bar( 1, 2, 3 )\n","pickBy":"function predicate( key, value ) {\n return ( value > 1 );\n };\nvar obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = pickBy( obj1, predicate )\n","PINF":"PINF\n","pkg2alias":"var v = pkg2alias( '@stdlib/math/base/special/sin' )\nv = pkg2alias( '@stdlib/math-base-special-sin' )\n","pkg2related":"var v = pkg2related( '@stdlib/math/base/special/sin' )\nv = pkg2related( '@stdlib/math-base-special-sin' )\n","pkg2standalone":"var v = pkg2standalone( '@stdlib/math/base/special/sin' )\n","PLATFORM":"PLATFORM\n","plot":"var plot = plot()\nvar x = [[0.10, 0.20, 0.30]];\nvar y = [[0.52, 0.79, 0.64]];\nplot = plot( x, y )\n","Plot":"var plot = Plot()\nvar x = [[0.10, 0.20, 0.30]];\nvar y = [[0.52, 0.79, 0.64]];\nplot = Plot( x, y )\n","pluck":"var arr = [\n { 'a': 1, 'b': 2 },\n { 'a': 0.5, 'b': 3 }\n ];\nvar out = pluck( arr, 'a' )\narr = [\n { 'a': 1, 'b': 2 },\n { 'a': 0.5, 'b': 3 }\n ];\nout = pluck( arr, 'a', { 'copy': false } )\nvar bool = ( arr[ 0 ] === out[ 0 ] )\n","pop":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar out = pop( arr )\narr = new Float64Array( [ 1.0, 2.0 ] );\nout = pop( arr )\narr = { 'length': 2, '0': 1.0, '1': 2.0 };\nout = pop( arr )\n","porterStemmer":"var out = porterStemmer( 'walking' )\nout = porterStemmer( 'walked' )\nout = porterStemmer( 'walks' )\nout = porterStemmer( '' )\n","prepend":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = prepend( arr, [ 6.0, 7.0 ] )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = prepend( arr, [ 3.0, 4.0 ] )\narr = { 'length': 1, '0': 1.0 };\narr = prepend( arr, [ 2.0, 3.0 ] )\n","prevGraphemeClusterBreak":"var out = prevGraphemeClusterBreak( 'last man standing', 4 )\nout = prevGraphemeClusterBreak( 'presidential election', 8 )\nout = prevGraphemeClusterBreak( 'अनुच्छेद', 2 )\nout = prevGraphemeClusterBreak( '🌷', 1 )\n","PRIMES_100K":"var list = PRIMES_100K()\n","properties":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar props = properties( obj )\n","propertiesIn":"var props = propertiesIn( [] )\n","propertyDescriptor":"var obj = { 'a': 'b' };\nvar desc = propertyDescriptor( obj, 'a' )\n","propertyDescriptorIn":"var obj = { 'a': 'b' };\nvar desc = propertyDescriptorIn( obj, 'a' )\n","propertyDescriptors":"var obj = { 'a': 'b' };\nvar desc = propertyDescriptors( obj )\n","propertyDescriptorsIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar desc = propertyDescriptorsIn( obj )\n","propertyNames":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = propertyNames( obj )\n","propertyNamesIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = propertyNamesIn( obj )\n","propertySymbols":"var s = propertySymbols( {} )\n","propertySymbolsIn":"var s = propertySymbolsIn( [] )\n","Proxy":"function get( obj, prop ) { return obj[ prop ] * 2.0 };\nvar h = { 'get': get };\nvar p = new Proxy( {}, h );\np.a = 3.14;\np.a\n","Proxy.revocable":"function get( obj, prop ) { return obj[ prop ] * 2.0 };\nvar h = { 'get': get };\nvar p = Proxy.revocable( {}, h );\np.proxy.a = 3.14;\np.proxy.a\np.revoke();\n","push":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = push( arr, 6.0, 7.0 )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = push( arr, 3.0, 4.0 )\narr = { 'length': 0 };\narr = push( arr, 1.0, 2.0 )\n","quarterOfYear":"var q = quarterOfYear( new Date() )\nq = quarterOfYear( 4 )\nq = quarterOfYear( 'June' )\nq = quarterOfYear( 'April' )\nq = quarterOfYear( 'apr' )\n","random.array.arcsine":"var out = random.array.arcsine( 3, 2.0, 5.0 )\n","random.array.arcsine.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.arcsine.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.arcsine.factory":"var fcn = random.array.arcsine.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.arcsine.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.arcsine.PRNG":"var prng = random.array.arcsine.PRNG;\n","random.array.arcsine.seed":"var seed = random.array.arcsine.seed;\n","random.array.arcsine.seedLength":"var len = random.array.arcsine.seedLength;\n","random.array.arcsine.state":"var out = random.array.arcsine( 3, 2.0, 5.0 )\nvar state = random.array.arcsine.state\nout = random.array.arcsine( 3, 2.0, 5.0 )\nout = random.array.arcsine( 3, 2.0, 5.0 )\nrandom.array.arcsine.state = state;\nout = random.array.arcsine( 3, 2.0, 5.0 )\n","random.array.arcsine.stateLength":"var len = random.array.arcsine.stateLength;\n","random.array.arcsine.byteLength":"var sz = random.array.arcsine.byteLength;\n","random.array.bernoulli":"var out = random.array.bernoulli( 3, 0.5 )\n","random.array.bernoulli.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.bernoulli.assign( 0.5, x )\nvar bool = ( out === x )\n","random.array.bernoulli.factory":"var fcn = random.array.bernoulli.factory();\nvar out = fcn( 3, 0.5 )\nfcn = random.array.bernoulli.factory( 0.5 );\nout = fcn( 3 )\n","random.array.bernoulli.PRNG":"var prng = random.array.bernoulli.PRNG;\n","random.array.bernoulli.seed":"var seed = random.array.bernoulli.seed;\n","random.array.bernoulli.seedLength":"var len = random.array.bernoulli.seedLength;\n","random.array.bernoulli.state":"var out = random.array.bernoulli( 3, 0.5 )\nvar state = random.array.bernoulli.state\nout = random.array.bernoulli( 3, 0.5 )\nout = random.array.bernoulli( 3, 0.5 )\nrandom.array.bernoulli.state = state;\nout = random.array.bernoulli( 3, 0.5 )\n","random.array.bernoulli.stateLength":"var len = random.array.bernoulli.stateLength;\n","random.array.bernoulli.byteLength":"var sz = random.array.bernoulli.byteLength;\n","random.array.beta":"var out = random.array.beta( 3, 2.0, 5.0 )\n","random.array.beta.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.beta.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.beta.factory":"var fcn = random.array.beta.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.beta.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.beta.PRNG":"var prng = random.array.beta.PRNG;\n","random.array.beta.seed":"var seed = random.array.beta.seed;\n","random.array.beta.seedLength":"var len = random.array.beta.seedLength;\n","random.array.beta.state":"var out = random.array.beta( 3, 2.0, 5.0 )\nvar state = random.array.beta.state\nout = random.array.beta( 3, 2.0, 5.0 )\nout = random.array.beta( 3, 2.0, 5.0 )\nrandom.array.beta.state = state;\nout = random.array.beta( 3, 2.0, 5.0 )\n","random.array.beta.stateLength":"var len = random.array.beta.stateLength;\n","random.array.beta.byteLength":"var sz = random.array.beta.byteLength;\n","random.array.betaprime":"var out = random.array.betaprime( 3, 2.0, 5.0 )\n","random.array.betaprime.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.betaprime.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.betaprime.factory":"var fcn = random.array.betaprime.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.betaprime.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.betaprime.PRNG":"var prng = random.array.betaprime.PRNG;\n","random.array.betaprime.seed":"var seed = random.array.betaprime.seed;\n","random.array.betaprime.seedLength":"var len = random.array.betaprime.seedLength;\n","random.array.betaprime.state":"var out = random.array.betaprime( 3, 2.0, 5.0 )\nvar state = random.array.betaprime.state\nout = random.array.betaprime( 3, 2.0, 5.0 )\nout = random.array.betaprime( 3, 2.0, 5.0 )\nrandom.array.betaprime.state = state;\nout = random.array.betaprime( 3, 2.0, 5.0 )\n","random.array.betaprime.stateLength":"var len = random.array.betaprime.stateLength;\n","random.array.betaprime.byteLength":"var sz = random.array.betaprime.byteLength;\n","random.array.binomial":"var out = random.array.binomial( 3, 17, 0.5 )\n","random.array.binomial.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.binomial.assign( 17, 0.5, x )\nvar bool = ( out === x )\n","random.array.binomial.factory":"var fcn = random.array.binomial.factory();\nvar out = fcn( 3, 17, 0.5 )\nfcn = random.array.binomial.factory( 17, 0.5 );\nout = fcn( 3 )\n","random.array.binomial.PRNG":"var prng = random.array.binomial.PRNG;\n","random.array.binomial.seed":"var seed = random.array.binomial.seed;\n","random.array.binomial.seedLength":"var len = random.array.binomial.seedLength;\n","random.array.binomial.state":"var out = random.array.binomial( 3, 17, 0.5 )\nvar state = random.array.binomial.state\nout = random.array.binomial( 3, 17, 0.5 )\nout = random.array.binomial( 3, 17, 0.5 )\nrandom.array.binomial.state = state;\nout = random.array.binomial( 3, 17, 0.5 )\n","random.array.binomial.stateLength":"var len = random.array.binomial.stateLength;\n","random.array.binomial.byteLength":"var sz = random.array.binomial.byteLength;\n","random.array.cauchy":"var out = random.array.cauchy( 3, 2.0, 5.0 )\n","random.array.cauchy.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.cauchy.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.cauchy.factory":"var fcn = random.array.cauchy.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.cauchy.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.cauchy.PRNG":"var prng = random.array.cauchy.PRNG;\n","random.array.cauchy.seed":"var seed = random.array.cauchy.seed;\n","random.array.cauchy.seedLength":"var len = random.array.cauchy.seedLength;\n","random.array.cauchy.state":"var out = random.array.cauchy( 3, 2.0, 5.0 )\nvar state = random.array.cauchy.state\nout = random.array.cauchy( 3, 2.0, 5.0 )\nout = random.array.cauchy( 3, 2.0, 5.0 )\nrandom.array.cauchy.state = state;\nout = random.array.cauchy( 3, 2.0, 5.0 )\n","random.array.cauchy.stateLength":"var len = random.array.cauchy.stateLength;\n","random.array.cauchy.byteLength":"var sz = random.array.cauchy.byteLength;\n","random.array.chi":"var out = random.array.chi( 3, 2.0 )\n","random.array.chi.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.chi.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.chi.factory":"var fcn = random.array.chi.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.chi.factory( 2.0 );\nout = fcn( 3 )\n","random.array.chi.PRNG":"var prng = random.array.chi.PRNG;\n","random.array.chi.seed":"var seed = random.array.chi.seed;\n","random.array.chi.seedLength":"var len = random.array.chi.seedLength;\n","random.array.chi.state":"var out = random.array.chi( 3, 2.0 )\nvar state = random.array.chi.state\nout = random.array.chi( 3, 2.0 )\nout = random.array.chi( 3, 2.0 )\nrandom.array.chi.state = state;\nout = random.array.chi( 3, 2.0 )\n","random.array.chi.stateLength":"var len = random.array.chi.stateLength;\n","random.array.chi.byteLength":"var sz = random.array.chi.byteLength;\n","random.array.chisquare":"var out = random.array.chisquare( 3, 2.0 )\n","random.array.chisquare.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.chisquare.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.chisquare.factory":"var fcn = random.array.chisquare.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.chisquare.factory( 2.0 );\nout = fcn( 3 )\n","random.array.chisquare.PRNG":"var prng = random.array.chisquare.PRNG;\n","random.array.chisquare.seed":"var seed = random.array.chisquare.seed;\n","random.array.chisquare.seedLength":"var len = random.array.chisquare.seedLength;\n","random.array.chisquare.state":"var out = random.array.chisquare( 3, 2.0 )\nvar state = random.array.chisquare.state\nout = random.array.chisquare( 3, 2.0 )\nout = random.array.chisquare( 3, 2.0 )\nrandom.array.chisquare.state = state;\nout = random.array.chisquare( 3, 2.0 )\n","random.array.chisquare.stateLength":"var len = random.array.chisquare.stateLength;\n","random.array.chisquare.byteLength":"var sz = random.array.chisquare.byteLength;\n","random.array.cosine":"var out = random.array.cosine( 3, 2.0, 5.0 )\n","random.array.cosine.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.cosine.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.cosine.factory":"var fcn = random.array.cosine.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.cosine.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.cosine.PRNG":"var prng = random.array.cosine.PRNG;\n","random.array.cosine.seed":"var seed = random.array.cosine.seed;\n","random.array.cosine.seedLength":"var len = random.array.cosine.seedLength;\n","random.array.cosine.state":"var out = random.array.cosine( 3, 2.0, 5.0 )\nvar state = random.array.cosine.state\nout = random.array.cosine( 3, 2.0, 5.0 )\nout = random.array.cosine( 3, 2.0, 5.0 )\nrandom.array.cosine.state = state;\nout = random.array.cosine( 3, 2.0, 5.0 )\n","random.array.cosine.stateLength":"var len = random.array.cosine.stateLength;\n","random.array.cosine.byteLength":"var sz = random.array.cosine.byteLength;\n","random.array.discreteUniform":"var out = random.array.discreteUniform( 3, -10, 10 )\n","random.array.discreteUniform.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.discreteUniform.assign( -10, 10, x )\nvar bool = ( out === x )\n","random.array.discreteUniform.factory":"var fcn = random.array.discreteUniform.factory();\nvar out = fcn( 3, -10, 10 )\nfcn = random.array.discreteUniform.factory( -10, 10 );\nout = fcn( 3 )\n","random.array.discreteUniform.PRNG":"var prng = random.array.discreteUniform.PRNG;\n","random.array.discreteUniform.seed":"var seed = random.array.discreteUniform.seed;\n","random.array.discreteUniform.seedLength":"var len = random.array.discreteUniform.seedLength;\n","random.array.discreteUniform.state":"var out = random.array.discreteUniform( 3, -10, 10 )\nvar state = random.array.discreteUniform.state\nout = random.array.discreteUniform( 3, -10, 10 )\nout = random.array.discreteUniform( 3, -10, 10 )\nrandom.array.discreteUniform.state = state;\nout = random.array.discreteUniform( 3, -10, 10 )\n","random.array.discreteUniform.stateLength":"var len = random.array.discreteUniform.stateLength;\n","random.array.discreteUniform.byteLength":"var sz = random.array.discreteUniform.byteLength;\n","random.array.erlang":"var out = random.array.erlang( 3, 2, 5.0 )\n","random.array.erlang.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.erlang.assign( 2, 5.0, x )\nvar bool = ( out === x )\n","random.array.erlang.factory":"var fcn = random.array.erlang.factory();\nvar out = fcn( 3, 2, 5.0 )\nfcn = random.array.erlang.factory( 2, 5.0 );\nout = fcn( 3 )\n","random.array.erlang.PRNG":"var prng = random.array.erlang.PRNG;\n","random.array.erlang.seed":"var seed = random.array.erlang.seed;\n","random.array.erlang.seedLength":"var len = random.array.erlang.seedLength;\n","random.array.erlang.state":"var out = random.array.erlang( 3, 2, 5.0 )\nvar state = random.array.erlang.state\nout = random.array.erlang( 3, 2, 5.0 )\nout = random.array.erlang( 3, 2, 5.0 )\nrandom.array.erlang.state = state;\nout = random.array.erlang( 3, 2, 5.0 )\n","random.array.erlang.stateLength":"var len = random.array.erlang.stateLength;\n","random.array.erlang.byteLength":"var sz = random.array.erlang.byteLength;\n","random.array.exponential":"var out = random.array.exponential( 3, 2.0 )\n","random.array.exponential.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.exponential.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.exponential.factory":"var fcn = random.array.exponential.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.exponential.factory( 2.0 );\nout = fcn( 3 )\n","random.array.exponential.PRNG":"var prng = random.array.exponential.PRNG;\n","random.array.exponential.seed":"var seed = random.array.exponential.seed;\n","random.array.exponential.seedLength":"var len = random.array.exponential.seedLength;\n","random.array.exponential.state":"var out = random.array.exponential( 3, 2.0 )\nvar state = random.array.exponential.state\nout = random.array.exponential( 3, 2.0 )\nout = random.array.exponential( 3, 2.0 )\nrandom.array.exponential.state = state;\nout = random.array.exponential( 3, 2.0 )\n","random.array.exponential.stateLength":"var len = random.array.exponential.stateLength;\n","random.array.exponential.byteLength":"var sz = random.array.exponential.byteLength;\n","random.array.f":"var out = random.array.f( 3, 2.0, 5.0 )\n","random.array.f.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.f.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.f.factory":"var fcn = random.array.f.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.f.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.f.PRNG":"var prng = random.array.f.PRNG;\n","random.array.f.seed":"var seed = random.array.f.seed;\n","random.array.f.seedLength":"var len = random.array.f.seedLength;\n","random.array.f.state":"var out = random.array.f( 3, 2.0, 5.0 )\nvar state = random.array.f.state\nout = random.array.f( 3, 2.0, 5.0 )\nout = random.array.f( 3, 2.0, 5.0 )\nrandom.array.f.state = state;\nout = random.array.f( 3, 2.0, 5.0 )\n","random.array.f.stateLength":"var len = random.array.f.stateLength;\n","random.array.f.byteLength":"var sz = random.array.f.byteLength;\n","random.array.frechet":"var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n","random.array.frechet.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.frechet.assign( 2.0, 5.0, 3.0, x )\nvar bool = ( out === x )\n","random.array.frechet.factory":"var fcn = random.array.frechet.factory();\nvar out = fcn( 3, 2.0, 5.0, 3.0 )\nfcn = random.array.frechet.factory( 2.0, 5.0, 3.0 );\nout = fcn( 3 )\n","random.array.frechet.PRNG":"var prng = random.array.frechet.PRNG;\n","random.array.frechet.seed":"var seed = random.array.frechet.seed;\n","random.array.frechet.seedLength":"var len = random.array.frechet.seedLength;\n","random.array.frechet.state":"var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\nvar state = random.array.frechet.state\nout = random.array.frechet( 3, 2.0, 5.0, 3.0 )\nout = random.array.frechet( 3, 2.0, 5.0, 3.0 )\nrandom.array.frechet.state = state;\nout = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n","random.array.frechet.stateLength":"var len = random.array.frechet.stateLength;\n","random.array.frechet.byteLength":"var sz = random.array.frechet.byteLength;\n","random.array.gamma":"var out = random.array.gamma( 3, 2.0, 5.0 )\n","random.array.gamma.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.gamma.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.gamma.factory":"var fcn = random.array.gamma.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.gamma.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.gamma.PRNG":"var prng = random.array.gamma.PRNG;\n","random.array.gamma.seed":"var seed = random.array.gamma.seed;\n","random.array.gamma.seedLength":"var len = random.array.gamma.seedLength;\n","random.array.gamma.state":"var out = random.array.gamma( 3, 2.0, 5.0 )\nvar state = random.array.gamma.state\nout = random.array.gamma( 3, 2.0, 5.0 )\nout = random.array.gamma( 3, 2.0, 5.0 )\nrandom.array.gamma.state = state;\nout = random.array.gamma( 3, 2.0, 5.0 )\n","random.array.gamma.stateLength":"var len = random.array.gamma.stateLength;\n","random.array.gamma.byteLength":"var sz = random.array.gamma.byteLength;\n","random.array.geometric":"var out = random.array.geometric( 3, 0.01 )\n","random.array.geometric.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.geometric.assign( 0.01, x )\nvar bool = ( out === x )\n","random.array.geometric.factory":"var fcn = random.array.geometric.factory();\nvar out = fcn( 3, 0.01 )\nfcn = random.array.geometric.factory( 0.01 );\nout = fcn( 3 )\n","random.array.geometric.PRNG":"var prng = random.array.geometric.PRNG;\n","random.array.geometric.seed":"var seed = random.array.geometric.seed;\n","random.array.geometric.seedLength":"var len = random.array.geometric.seedLength;\n","random.array.geometric.state":"var out = random.array.geometric( 3, 0.01 )\nvar state = random.array.geometric.state\nout = random.array.geometric( 3, 0.01 )\nout = random.array.geometric( 3, 0.01 )\nrandom.array.geometric.state = state;\nout = random.array.geometric( 3, 0.01 )\n","random.array.geometric.stateLength":"var len = random.array.geometric.stateLength;\n","random.array.geometric.byteLength":"var sz = random.array.geometric.byteLength;\n","random.array.gumbel":"var out = random.array.gumbel( 3, 2.0, 5.0 )\n","random.array.gumbel.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.gumbel.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.gumbel.factory":"var fcn = random.array.gumbel.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.gumbel.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.gumbel.PRNG":"var prng = random.array.gumbel.PRNG;\n","random.array.gumbel.seed":"var seed = random.array.gumbel.seed;\n","random.array.gumbel.seedLength":"var len = random.array.gumbel.seedLength;\n","random.array.gumbel.state":"var out = random.array.gumbel( 3, 2.0, 5.0 )\nvar state = random.array.gumbel.state\nout = random.array.gumbel( 3, 2.0, 5.0 )\nout = random.array.gumbel( 3, 2.0, 5.0 )\nrandom.array.gumbel.state = state;\nout = random.array.gumbel( 3, 2.0, 5.0 )\n","random.array.gumbel.stateLength":"var len = random.array.gumbel.stateLength;\n","random.array.gumbel.byteLength":"var sz = random.array.gumbel.byteLength;\n","random.array.hypergeometric":"var out = random.array.hypergeometric( 3, 20, 10, 7 )\n","random.array.hypergeometric.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.hypergeometric.assign( 20, 10, 7, x )\nvar bool = ( out === x )\n","random.array.hypergeometric.factory":"var fcn = random.array.hypergeometric.factory();\nvar out = fcn( 3, 20, 10, 7 )\nfcn = random.array.hypergeometric.factory( 20, 10, 7 );\nout = fcn( 3 )\n","random.array.hypergeometric.PRNG":"var prng = random.array.hypergeometric.PRNG;\n","random.array.hypergeometric.seed":"var seed = random.array.hypergeometric.seed;\n","random.array.hypergeometric.seedLength":"var len = random.array.hypergeometric.seedLength;\n","random.array.hypergeometric.state":"var out = random.array.hypergeometric( 3, 20, 10, 7 )\nvar state = random.array.hypergeometric.state\nout = random.array.hypergeometric( 3, 20, 10, 7 )\nout = random.array.hypergeometric( 3, 20, 10, 7 )\nrandom.array.hypergeometric.state = state;\nout = random.array.hypergeometric( 3, 20, 10, 7 )\n","random.array.hypergeometric.stateLength":"var len = random.array.hypergeometric.stateLength;\n","random.array.hypergeometric.byteLength":"var sz = random.array.hypergeometric.byteLength;\n","random.array.invgamma":"var out = random.array.invgamma( 3, 2.0, 5.0 )\n","random.array.invgamma.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.invgamma.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.invgamma.factory":"var fcn = random.array.invgamma.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.invgamma.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.invgamma.PRNG":"var prng = random.array.invgamma.PRNG;\n","random.array.invgamma.seed":"var seed = random.array.invgamma.seed;\n","random.array.invgamma.seedLength":"var len = random.array.invgamma.seedLength;\n","random.array.invgamma.state":"var out = random.array.invgamma( 3, 2.0, 5.0 )\nvar state = random.array.invgamma.state\nout = random.array.invgamma( 3, 2.0, 5.0 )\nout = random.array.invgamma( 3, 2.0, 5.0 )\nrandom.array.invgamma.state = state;\nout = random.array.invgamma( 3, 2.0, 5.0 )\n","random.array.invgamma.stateLength":"var len = random.array.invgamma.stateLength;\n","random.array.invgamma.byteLength":"var sz = random.array.invgamma.byteLength;\n","random.array.kumaraswamy":"var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n","random.array.kumaraswamy.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.kumaraswamy.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.kumaraswamy.factory":"var fcn = random.array.kumaraswamy.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.kumaraswamy.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.kumaraswamy.PRNG":"var prng = random.array.kumaraswamy.PRNG;\n","random.array.kumaraswamy.seed":"var seed = random.array.kumaraswamy.seed;\n","random.array.kumaraswamy.seedLength":"var len = random.array.kumaraswamy.seedLength;\n","random.array.kumaraswamy.state":"var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\nvar state = random.array.kumaraswamy.state\nout = random.array.kumaraswamy( 3, 2.0, 5.0 )\nout = random.array.kumaraswamy( 3, 2.0, 5.0 )\nrandom.array.kumaraswamy.state = state;\nout = random.array.kumaraswamy( 3, 2.0, 5.0 )\n","random.array.kumaraswamy.stateLength":"var len = random.array.kumaraswamy.stateLength;\n","random.array.kumaraswamy.byteLength":"var sz = random.array.kumaraswamy.byteLength;\n","random.array.laplace":"var out = random.array.laplace( 3, 2.0, 5.0 )\n","random.array.laplace.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.laplace.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.laplace.factory":"var fcn = random.array.laplace.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.laplace.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.laplace.PRNG":"var prng = random.array.laplace.PRNG;\n","random.array.laplace.seed":"var seed = random.array.laplace.seed;\n","random.array.laplace.seedLength":"var len = random.array.laplace.seedLength;\n","random.array.laplace.state":"var out = random.array.laplace( 3, 2.0, 5.0 )\nvar state = random.array.laplace.state\nout = random.array.laplace( 3, 2.0, 5.0 )\nout = random.array.laplace( 3, 2.0, 5.0 )\nrandom.array.laplace.state = state;\nout = random.array.laplace( 3, 2.0, 5.0 )\n","random.array.laplace.stateLength":"var len = random.array.laplace.stateLength;\n","random.array.laplace.byteLength":"var sz = random.array.laplace.byteLength;\n","random.array.levy":"var out = random.array.levy( 3, 2.0, 5.0 )\n","random.array.levy.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.levy.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.levy.factory":"var fcn = random.array.levy.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.levy.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.levy.PRNG":"var prng = random.array.levy.PRNG;\n","random.array.levy.seed":"var seed = random.array.levy.seed;\n","random.array.levy.seedLength":"var len = random.array.levy.seedLength;\n","random.array.levy.state":"var out = random.array.levy( 3, 2.0, 5.0 )\nvar state = random.array.levy.state\nout = random.array.levy( 3, 2.0, 5.0 )\nout = random.array.levy( 3, 2.0, 5.0 )\nrandom.array.levy.state = state;\nout = random.array.levy( 3, 2.0, 5.0 )\n","random.array.levy.stateLength":"var len = random.array.levy.stateLength;\n","random.array.levy.byteLength":"var sz = random.array.levy.byteLength;\n","random.array.logistic":"var out = random.array.logistic( 3, 2.0, 5.0 )\n","random.array.logistic.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.logistic.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.logistic.factory":"var fcn = random.array.logistic.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.logistic.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.logistic.PRNG":"var prng = random.array.logistic.PRNG;\n","random.array.logistic.seed":"var seed = random.array.logistic.seed;\n","random.array.logistic.seedLength":"var len = random.array.logistic.seedLength;\n","random.array.logistic.state":"var out = random.array.logistic( 3, 2.0, 5.0 )\nvar state = random.array.logistic.state\nout = random.array.logistic( 3, 2.0, 5.0 )\nout = random.array.logistic( 3, 2.0, 5.0 )\nrandom.array.logistic.state = state;\nout = random.array.logistic( 3, 2.0, 5.0 )\n","random.array.logistic.stateLength":"var len = random.array.logistic.stateLength;\n","random.array.logistic.byteLength":"var sz = random.array.logistic.byteLength;\n","random.array.lognormal":"var out = random.array.lognormal( 3, 2.0, 5.0 )\n","random.array.lognormal.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.lognormal.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.lognormal.factory":"var fcn = random.array.lognormal.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.lognormal.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.lognormal.PRNG":"var prng = random.array.lognormal.PRNG;\n","random.array.lognormal.seed":"var seed = random.array.lognormal.seed;\n","random.array.lognormal.seedLength":"var len = random.array.lognormal.seedLength;\n","random.array.lognormal.state":"var out = random.array.lognormal( 3, 2.0, 5.0 )\nvar state = random.array.lognormal.state\nout = random.array.lognormal( 3, 2.0, 5.0 )\nout = random.array.lognormal( 3, 2.0, 5.0 )\nrandom.array.lognormal.state = state;\nout = random.array.lognormal( 3, 2.0, 5.0 )\n","random.array.lognormal.stateLength":"var len = random.array.lognormal.stateLength;\n","random.array.lognormal.byteLength":"var sz = random.array.lognormal.byteLength;\n","random.array.minstd":"var out = random.array.minstd( 3 )\n","random.array.minstd.normalized":"var out = random.array.minstd.normalized( 3 )\n","random.array.minstd.factory":"var fcn = random.array.minstd.factory();\nvar out = fcn( 3 )\n","random.array.minstd.PRNG":"var prng = random.array.minstd.PRNG;\n","random.array.minstd.seed":"var seed = random.array.minstd.seed;\n","random.array.minstd.seedLength":"var len = random.array.minstd.seedLength;\n","random.array.minstd.state":"var out = random.array.minstd( 3 )\nvar state = random.array.minstd.state;\nout = random.array.minstd( 3 )\nout = random.array.minstd( 3 )\nrandom.array.minstd.state = state;\nout = random.array.minstd( 3 )\n","random.array.minstd.stateLength":"var len = random.array.minstd.stateLength;\n","random.array.minstd.byteLength":"var sz = random.array.minstd.byteLength;\n","random.array.minstdShuffle":"var out = random.array.minstdShuffle( 3 )\n","random.array.minstdShuffle.normalized":"var out = random.array.minstdShuffle.normalized( 3 )\n","random.array.minstdShuffle.factory":"var fcn = random.array.minstdShuffle.factory();\nvar out = fcn( 3 )\n","random.array.minstdShuffle.PRNG":"var prng = random.array.minstdShuffle.PRNG;\n","random.array.minstdShuffle.seed":"var seed = random.array.minstdShuffle.seed;\n","random.array.minstdShuffle.seedLength":"var len = random.array.minstdShuffle.seedLength;\n","random.array.minstdShuffle.state":"var out = random.array.minstdShuffle( 3 )\nvar state = random.array.minstdShuffle.state;\nout = random.array.minstdShuffle( 3 )\nout = random.array.minstdShuffle( 3 )\nrandom.array.minstdShuffle.state = state;\nout = random.array.minstdShuffle( 3 )\n","random.array.minstdShuffle.stateLength":"var len = random.array.minstdShuffle.stateLength;\n","random.array.minstdShuffle.byteLength":"var sz = random.array.minstdShuffle.byteLength;\n","random.array.mt19937":"var out = random.array.mt19937( 3 )\n","random.array.mt19937.normalized":"var out = random.array.mt19937.normalized( 3 )\n","random.array.mt19937.factory":"var fcn = random.array.mt19937.factory();\nvar out = fcn( 3 )\n","random.array.mt19937.PRNG":"var prng = random.array.mt19937.PRNG;\n","random.array.mt19937.seed":"var seed = random.array.mt19937.seed;\n","random.array.mt19937.seedLength":"var len = random.array.mt19937.seedLength;\n","random.array.mt19937.state":"var out = random.array.mt19937( 3 )\nvar state = random.array.mt19937.state;\nout = random.array.mt19937( 3 )\nout = random.array.mt19937( 3 )\nrandom.array.mt19937.state = state;\nout = random.array.mt19937( 3 )\n","random.array.mt19937.stateLength":"var len = random.array.mt19937.stateLength;\n","random.array.mt19937.byteLength":"var sz = random.array.mt19937.byteLength;\n","random.array.negativeBinomial":"var out = random.array.negativeBinomial( 3, 10, 0.5 )\n","random.array.negativeBinomial.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.negativeBinomial.assign( 10, 0.5, x )\nvar bool = ( out === x )\n","random.array.negativeBinomial.factory":"var fcn = random.array.negativeBinomial.factory();\nvar out = fcn( 3, 10, 0.5 )\nfcn = random.array.negativeBinomial.factory( 10, 0.5 );\nout = fcn( 3 )\n","random.array.negativeBinomial.PRNG":"var prng = random.array.negativeBinomial.PRNG;\n","random.array.negativeBinomial.seed":"var seed = random.array.negativeBinomial.seed;\n","random.array.negativeBinomial.seedLength":"var len = random.array.negativeBinomial.seedLength;\n","random.array.negativeBinomial.state":"var out = random.array.negativeBinomial( 3, 10, 0.5 )\nvar state = random.array.negativeBinomial.state\nout = random.array.negativeBinomial( 3, 10, 0.5 )\nout = random.array.negativeBinomial( 3, 10, 0.5 )\nrandom.array.negativeBinomial.state = state;\nout = random.array.negativeBinomial( 3, 10, 0.5 )\n","random.array.negativeBinomial.stateLength":"var len = random.array.negativeBinomial.stateLength;\n","random.array.negativeBinomial.byteLength":"var sz = random.array.negativeBinomial.byteLength;\n","random.array.normal":"var out = random.array.normal( 3, 2.0, 5.0 )\n","random.array.normal.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.normal.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.normal.factory":"var fcn = random.array.normal.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.normal.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.normal.PRNG":"var prng = random.array.normal.PRNG;\n","random.array.normal.seed":"var seed = random.array.normal.seed;\n","random.array.normal.seedLength":"var len = random.array.normal.seedLength;\n","random.array.normal.state":"var out = random.array.normal( 3, 2.0, 5.0 )\nvar state = random.array.normal.state\nout = random.array.normal( 3, 2.0, 5.0 )\nout = random.array.normal( 3, 2.0, 5.0 )\nrandom.array.normal.state = state;\nout = random.array.normal( 3, 2.0, 5.0 )\n","random.array.normal.stateLength":"var len = random.array.normal.stateLength;\n","random.array.normal.byteLength":"var sz = random.array.normal.byteLength;\n","random.array.pareto1":"var out = random.array.pareto1( 3, 2.0, 5.0 )\n","random.array.pareto1.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.pareto1.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.pareto1.factory":"var fcn = random.array.pareto1.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.pareto1.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.pareto1.PRNG":"var prng = random.array.pareto1.PRNG;\n","random.array.pareto1.seed":"var seed = random.array.pareto1.seed;\n","random.array.pareto1.seedLength":"var len = random.array.pareto1.seedLength;\n","random.array.pareto1.state":"var out = random.array.pareto1( 3, 2.0, 5.0 )\nvar state = random.array.pareto1.state\nout = random.array.pareto1( 3, 2.0, 5.0 )\nout = random.array.pareto1( 3, 2.0, 5.0 )\nrandom.array.pareto1.state = state;\nout = random.array.pareto1( 3, 2.0, 5.0 )\n","random.array.pareto1.stateLength":"var len = random.array.pareto1.stateLength;\n","random.array.pareto1.byteLength":"var sz = random.array.pareto1.byteLength;\n","random.array.poisson":"var out = random.array.poisson( 3, 2.0 )\n","random.array.poisson.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.poisson.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.poisson.factory":"var fcn = random.array.poisson.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.poisson.factory( 2.0 );\nout = fcn( 3 )\n","random.array.poisson.PRNG":"var prng = random.array.poisson.PRNG;\n","random.array.poisson.seed":"var seed = random.array.poisson.seed;\n","random.array.poisson.seedLength":"var len = random.array.poisson.seedLength;\n","random.array.poisson.state":"var out = random.array.poisson( 3, 2.0 )\nvar state = random.array.poisson.state\nout = random.array.poisson( 3, 2.0 )\nout = random.array.poisson( 3, 2.0 )\nrandom.array.poisson.state = state;\nout = random.array.poisson( 3, 2.0 )\n","random.array.poisson.stateLength":"var len = random.array.poisson.stateLength;\n","random.array.poisson.byteLength":"var sz = random.array.poisson.byteLength;\n","random.array.randu":"var out = random.array.randu( 3 )\n","random.array.randu.factory":"var fcn = random.array.randu.factory();\nvar out = fcn( 3 )\n","random.array.randu.PRNG":"var prng = random.array.randu.PRNG;\n","random.array.randu.seed":"var seed = random.array.randu.seed;\n","random.array.randu.seedLength":"var len = random.array.randu.seedLength;\n","random.array.randu.state":"var out = random.array.randu( 3 )\nvar state = random.array.randu.state;\nout = random.array.randu( 3 )\nout = random.array.randu( 3 )\nrandom.array.randu.state = state;\nout = random.array.randu( 3 )\n","random.array.randu.stateLength":"var len = random.array.randu.stateLength;\n","random.array.randu.byteLength":"var sz = random.array.randu.byteLength;\n","random.array.rayleigh":"var out = random.array.rayleigh( 3, 2.0 )\n","random.array.rayleigh.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.rayleigh.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.rayleigh.factory":"var fcn = random.array.rayleigh.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.rayleigh.factory( 2.0 );\nout = fcn( 3 )\n","random.array.rayleigh.PRNG":"var prng = random.array.rayleigh.PRNG;\n","random.array.rayleigh.seed":"var seed = random.array.rayleigh.seed;\n","random.array.rayleigh.seedLength":"var len = random.array.rayleigh.seedLength;\n","random.array.rayleigh.state":"var out = random.array.rayleigh( 3, 2.0 )\nvar state = random.array.rayleigh.state\nout = random.array.rayleigh( 3, 2.0 )\nout = random.array.rayleigh( 3, 2.0 )\nrandom.array.rayleigh.state = state;\nout = random.array.rayleigh( 3, 2.0 )\n","random.array.rayleigh.stateLength":"var len = random.array.rayleigh.stateLength;\n","random.array.rayleigh.byteLength":"var sz = random.array.rayleigh.byteLength;\n","random.array.t":"var out = random.array.t( 3, 2.0 )\n","random.array.t.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.t.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.t.factory":"var fcn = random.array.t.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.t.factory( 2.0 );\nout = fcn( 3 )\n","random.array.t.PRNG":"var prng = random.array.t.PRNG;\n","random.array.t.seed":"var seed = random.array.t.seed;\n","random.array.t.seedLength":"var len = random.array.t.seedLength;\n","random.array.t.state":"var out = random.array.t( 3, 2.0 )\nvar state = random.array.t.state\nout = random.array.t( 3, 2.0 )\nout = random.array.t( 3, 2.0 )\nrandom.array.t.state = state;\nout = random.array.t( 3, 2.0 )\n","random.array.t.stateLength":"var len = random.array.t.stateLength;\n","random.array.t.byteLength":"var sz = random.array.t.byteLength;\n","random.array.triangular":"var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n","random.array.triangular.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.triangular.assign( 2.0, 5.0, 3.0, x )\nvar bool = ( out === x )\n","random.array.triangular.factory":"var fcn = random.array.triangular.factory();\nvar out = fcn( 3, 2.0, 5.0, 3.0 )\nfcn = random.array.triangular.factory( 2.0, 5.0, 3.0 );\nout = fcn( 3 )\n","random.array.triangular.PRNG":"var prng = random.array.triangular.PRNG;\n","random.array.triangular.seed":"var seed = random.array.triangular.seed;\n","random.array.triangular.seedLength":"var len = random.array.triangular.seedLength;\n","random.array.triangular.state":"var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\nvar state = random.array.triangular.state\nout = random.array.triangular( 3, 2.0, 5.0, 3.0 )\nout = random.array.triangular( 3, 2.0, 5.0, 3.0 )\nrandom.array.triangular.state = state;\nout = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n","random.array.triangular.stateLength":"var len = random.array.triangular.stateLength;\n","random.array.triangular.byteLength":"var sz = random.array.triangular.byteLength;\n","random.array.uniform":"var out = random.array.uniform( 3, 2.0, 5.0 )\n","random.array.uniform.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.uniform.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.uniform.factory":"var fcn = random.array.uniform.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.uniform.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.uniform.PRNG":"var prng = random.array.uniform.PRNG;\n","random.array.uniform.seed":"var seed = random.array.uniform.seed;\n","random.array.uniform.seedLength":"var len = random.array.uniform.seedLength;\n","random.array.uniform.state":"var out = random.array.uniform( 3, 2.0, 5.0 )\nvar state = random.array.uniform.state\nout = random.array.uniform( 3, 2.0, 5.0 )\nout = random.array.uniform( 3, 2.0, 5.0 )\nrandom.array.uniform.state = state;\nout = random.array.uniform( 3, 2.0, 5.0 )\n","random.array.uniform.stateLength":"var len = random.array.uniform.stateLength;\n","random.array.uniform.byteLength":"var sz = random.array.uniform.byteLength;\n","random.array.weibull":"var out = random.array.weibull( 3, 2.0, 5.0 )\n","random.array.weibull.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.weibull.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.weibull.factory":"var fcn = random.array.weibull.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.weibull.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.weibull.PRNG":"var prng = random.array.weibull.PRNG;\n","random.array.weibull.seed":"var seed = random.array.weibull.seed;\n","random.array.weibull.seedLength":"var len = random.array.weibull.seedLength;\n","random.array.weibull.state":"var out = random.array.weibull( 3, 2.0, 5.0 )\nvar state = random.array.weibull.state\nout = random.array.weibull( 3, 2.0, 5.0 )\nout = random.array.weibull( 3, 2.0, 5.0 )\nrandom.array.weibull.state = state;\nout = random.array.weibull( 3, 2.0, 5.0 )\n","random.array.weibull.stateLength":"var len = random.array.weibull.stateLength;\n","random.array.weibull.byteLength":"var sz = random.array.weibull.byteLength;\n","random.iterators.arcsine":"var it = random.iterators.arcsine( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.bernoulli":"var it = random.iterators.bernoulli( 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.beta":"var it = random.iterators.beta( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.betaprime":"var it = random.iterators.betaprime( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.binomial":"var it = random.iterators.binomial( 10, 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.boxMuller":"var it = random.iterators.boxMuller();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.cauchy":"var it = random.iterators.cauchy( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.chi":"var it = random.iterators.chi( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.chisquare":"var it = random.iterators.chisquare( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.cosine":"var it = random.iterators.cosine( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.discreteUniform":"var it = random.iterators.discreteUniform( 0, 3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.erlang":"var it = random.iterators.erlang( 1, 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.exponential":"var it = random.iterators.exponential( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.f":"var it = random.iterators.f( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.frechet":"var it = random.iterators.frechet( 1.0, 1.0, 0.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.gamma":"var it = random.iterators.gamma( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.geometric":"var it = random.iterators.geometric( 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.gumbel":"var it = random.iterators.gumbel( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.hypergeometric":"var it = random.iterators.hypergeometric( 20, 10, 7 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.improvedZiggurat":"var it = random.iterators.improvedZiggurat();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.invgamma":"var it = random.iterators.invgamma( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.kumaraswamy":"var it = random.iterators.kumaraswamy( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.laplace":"var it = random.iterators.laplace( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.levy":"var it = random.iterators.levy( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.logistic":"var it = random.iterators.logistic( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.lognormal":"var it = random.iterators.lognormal( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.minstd":"var it = random.iterators.minstd();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.minstdShuffle":"var it = random.iterators.minstdShuffle();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.mt19937":"var it = random.iterators.mt19937();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.negativeBinomial":"var it = random.iterators.negativeBinomial( 10, 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.normal":"var it = random.iterators.normal( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.pareto1":"var it = random.iterators.pareto1( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.poisson":"var it = random.iterators.poisson( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.randi":"var it = random.iterators.randi();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.randn":"var it = random.iterators.randn();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.randu":"var it = random.iterators.randu();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.rayleigh":"var it = random.iterators.rayleigh( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.t":"var it = random.iterators.t( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.triangular":"var it = random.iterators.triangular( 0.0, 1.0, 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.uniform":"var it = random.iterators.uniform( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.weibull":"var it = random.iterators.weibull( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.streams.arcsine":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.arcsine( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.arcsine.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.arcsine.factory( opts );\n","random.streams.arcsine.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.arcsine.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.bernoulli":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.bernoulli( 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.bernoulli.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.bernoulli.factory( opts );\n","random.streams.bernoulli.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.bernoulli.objectMode( 0.3, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.beta":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.beta( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.beta.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.beta.factory( opts );\n","random.streams.beta.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.beta.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.betaprime":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.betaprime( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.betaprime.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.betaprime.factory( opts );\n","random.streams.betaprime.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.betaprime.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.binomial":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.binomial( 20, 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.binomial.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.binomial.factory( opts );\n","random.streams.binomial.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.binomial.objectMode( 20, 0.5, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.boxMuller":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.boxMuller( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.boxMuller.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.boxMuller.factory( opts );\n","random.streams.boxMuller.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.boxMuller.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.cauchy":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cauchy( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.cauchy.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.cauchy.factory( opts );\n","random.streams.cauchy.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cauchy.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.chi":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chi( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.chi.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.chi.factory( opts );\n","random.streams.chi.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chi.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.chisquare":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chisquare( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.chisquare.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.chisquare.factory( opts );\n","random.streams.chisquare.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chisquare.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.cosine":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cosine( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.cosine.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.cosine.factory( opts );\n","random.streams.cosine.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cosine.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.discreteUniform":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.discreteUniform( 2, 5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.discreteUniform.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.discreteUniform.factory( opts );\n","random.streams.discreteUniform.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.discreteUniform.objectMode( 2, 5, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.erlang":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.erlang( 2, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.erlang.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.erlang.factory( opts );\n","random.streams.erlang.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.erlang.objectMode( 2, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.exponential":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.exponential( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.exponential.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.exponential.factory( opts );\n","random.streams.exponential.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.exponential.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.f":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.f( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.f.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.f.factory( opts );\n","random.streams.f.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.f.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.frechet":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.frechet( 2.0, 5.0, 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.frechet.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.frechet.factory( opts );\n","random.streams.frechet.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.frechet.objectMode( 2.0, 5.0, 3.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.gamma":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gamma( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.gamma.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.gamma.factory( opts );\n","random.streams.gamma.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gamma.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.geometric":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.geometric( 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.geometric.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.geometric.factory( opts );\n","random.streams.geometric.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.geometric.objectMode( 0.3, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.gumbel":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gumbel( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.gumbel.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.gumbel.factory( opts );\n","random.streams.gumbel.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gumbel.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.hypergeometric":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.hypergeometric( 5, 3, 2, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.hypergeometric.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.hypergeometric.factory( opts );\n","random.streams.hypergeometric.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.hypergeometric.objectMode( 5, 3, 2, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.improvedZiggurat":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.improvedZiggurat( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.improvedZiggurat.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.improvedZiggurat.factory( opts );\n","random.streams.improvedZiggurat.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.improvedZiggurat.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.invgamma":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.invgamma( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.invgamma.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.invgamma.factory( opts );\n","random.streams.invgamma.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.invgamma.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.kumaraswamy":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.kumaraswamy( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.kumaraswamy.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.kumaraswamy.factory( opts );\n","random.streams.kumaraswamy.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.kumaraswamy.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.laplace":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.laplace( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.laplace.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.laplace.factory( opts );\n","random.streams.laplace.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.laplace.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.levy":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.levy( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.levy.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.levy.factory( opts );\n","random.streams.levy.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.levy.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.logistic":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.logistic( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.logistic.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.logistic.factory( opts );\n","random.streams.logistic.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.logistic.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.lognormal":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.lognormal( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.lognormal.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.lognormal.factory( opts );\n","random.streams.lognormal.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.lognormal.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.minstd":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstd( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.minstd.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.minstd.factory( opts );\n","random.streams.minstd.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstd.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.minstdShuffle":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstdShuffle( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.minstdShuffle.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.minstdShuffle.factory( opts );\n","random.streams.minstdShuffle.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstdShuffle.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.mt19937":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.mt19937( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.mt19937.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.mt19937.factory( opts );\n","random.streams.mt19937.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.mt19937.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.negativeBinomial":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.negativeBinomial( 20.0, 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.negativeBinomial.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.negativeBinomial.factory( opts );\n","random.streams.negativeBinomial.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.negativeBinomial.objectMode( 20.0, 0.5, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.normal":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.normal( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.normal.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.normal.factory( opts );\n","random.streams.normal.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.normal.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.pareto1":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.pareto1( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.pareto1.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.pareto1.factory( opts );\n","random.streams.pareto1.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.pareto1.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.poisson":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.poisson( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.poisson.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.poisson.factory( opts );\n","random.streams.poisson.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.poisson.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.randi":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randi( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.randi.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.randi.factory( opts );\n","random.streams.randi.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randi.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.randn":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randn( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.randn.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.randn.factory( opts );\n","random.streams.randn.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randn.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.randu":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randu( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.randu.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.randu.factory( opts );\n","random.streams.randu.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randu.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.rayleigh":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.rayleigh( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.rayleigh.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.rayleigh.factory( opts );\n","random.streams.rayleigh.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.rayleigh.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.t":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.t( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.t.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.t.factory( opts );\n","random.streams.t.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.t.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.triangular":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.triangular( 2.0, 5.0, 4.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.triangular.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.triangular.factory( opts );\n","random.streams.triangular.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.triangular.objectMode( 2.0, 5.0, 4.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.uniform":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.uniform( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.uniform.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.uniform.factory( opts );\n","random.streams.uniform.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.uniform.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.weibull":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.weibull( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.weibull.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.weibull.factory( opts );\n","random.streams.weibull.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.weibull.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.strided.arcsine":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.arcsine( out.length, a, 1, b, 1, out, 1 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.arcsine( 3, a, -2, b, 1, out, 1 )\n","random.strided.arcsine.ndarray":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.arcsine.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.arcsine.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.bernoulli":"var out = azeros( 5, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n","random.strided.bernoulli.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.bernoulli.ndarray( out.length, [ 0.5 ], 0, 0, out, 1, 0 )\n","random.strided.bernoulli.factory":"var fcn = random.strided.bernoulli.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 0.5 ], 0, out, 1 )\n","random.strided.bernoulli.PRNG":"var prng = random.strided.bernoulli.PRNG;\n","random.strided.bernoulli.seed":"var seed = random.strided.bernoulli.seed;\n","random.strided.bernoulli.seedLength":"var len = random.strided.bernoulli.seedLength;\n","random.strided.bernoulli.state":"var out = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\nvar state = random.strided.bernoulli.state\nout = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\nrandom.strided.bernoulli.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n","random.strided.bernoulli.stateLength":"var len = random.strided.bernoulli.stateLength;\n","random.strided.bernoulli.byteLength":"var sz = random.strided.bernoulli.byteLength;\n","random.strided.beta":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.beta( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.beta( 3, a, -2, b, 1, out, 1 )\n","random.strided.beta.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.beta.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.beta.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.betaprime":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.betaprime( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.betaprime( 3, a, -2, b, 1, out, 1 )\n","random.strided.betaprime.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.betaprime.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.betaprime.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.chi":"var out = azeros( 5, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chi.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.chi.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.chi.factory":"var fcn = random.strided.chi.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chi.PRNG":"var prng = random.strided.chi.PRNG;\n","random.strided.chi.seed":"var seed = random.strided.chi.seed;\n","random.strided.chi.seedLength":"var len = random.strided.chi.seedLength;\n","random.strided.chi.state":"var out = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.chi.state\nout = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.chi.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chi.stateLength":"var len = random.strided.chi.stateLength;\n","random.strided.chi.byteLength":"var sz = random.strided.chi.byteLength;\n","random.strided.chisquare":"var out = azeros( 5, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chisquare.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.chisquare.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.chisquare.factory":"var fcn = random.strided.chisquare.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chisquare.PRNG":"var prng = random.strided.chisquare.PRNG;\n","random.strided.chisquare.seed":"var seed = random.strided.chisquare.seed;\n","random.strided.chisquare.seedLength":"var len = random.strided.chisquare.seedLength;\n","random.strided.chisquare.state":"var out = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.chisquare.state\nout = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.chisquare.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chisquare.stateLength":"var len = random.strided.chisquare.stateLength;\n","random.strided.chisquare.byteLength":"var sz = random.strided.chisquare.byteLength;\n","random.strided.cosine":"var mu = linspace( 0.0, 1.0, 5 );\nvar s = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.cosine( out.length, mu, 1, s, 1, out, 1 )\nmu = linspace( 0.0, 1.0, 6 );\ns = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.cosine( 3, mu, -2, s, 1, out, 1 )\n","random.strided.cosine.ndarray":"var mu = linspace( 0.0, 1.0, 5 );\nvar s = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.cosine.ndarray( out.length, mu, 1, 0, s, 1, 0, out, 1, 0 )\nmu = linspace( 0.0, 1.0, 6 );\ns = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.cosine.ndarray( 3, mu, 2, 1, s, -1, s.length-1, out, 1, 0 )\n","random.strided.discreteUniform":"var a = [ -10, -5, 0, 5, 10 ];\nvar b = [ 20, 20, 20, 20, 20 ];\nvar out = azeros( 5, 'generic' );\nrandom.strided.discreteUniform( out.length, a, 1, b, 1, out, 1 )\na = [ -10, -5, 0, 5, 10, 15 ];\nb = [ 20, 20, 20, 20, 20, 20 ];\nout = azeros( 6, 'generic' );\nrandom.strided.discreteUniform( 3, a, -2, b, 1, out, 1 )\n","random.strided.discreteUniform.ndarray":"var a = [ -10, -5, 0, 5, 10 ];\nvar b = [ 20, 20, 20, 20, 20 ];\nvar out = azeros( 5, 'generic' );\nrandom.strided.discreteUniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = [ -10, -5, 0, 5, 10, 15 ];\nb = [ 20, 20, 20, 20, 20, 20 ];\nout = azeros( 6, 'generic' );\nrandom.strided.discreteUniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.exponential":"var out = azeros( 5, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.exponential.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.exponential.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.exponential.factory":"var fcn = random.strided.exponential.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.exponential.PRNG":"var prng = random.strided.exponential.PRNG;\n","random.strided.exponential.seed":"var seed = random.strided.exponential.seed;\n","random.strided.exponential.seedLength":"var len = random.strided.exponential.seedLength;\n","random.strided.exponential.state":"var out = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.exponential.state\nout = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.exponential.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.exponential.stateLength":"var len = random.strided.exponential.stateLength;\n","random.strided.exponential.byteLength":"var sz = random.strided.exponential.byteLength;\n","random.strided.gamma":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.gamma( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.gamma( 3, a, -2, b, 1, out, 1 )\n","random.strided.gamma.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.gamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.gamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.geometric":"var out = azeros( 5, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n","random.strided.geometric.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.geometric.ndarray( out.length, [ 0.01 ], 0, 0, out, 1, 0 )\n","random.strided.geometric.factory":"var fcn = random.strided.geometric.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 0.01 ], 0, out, 1 )\n","random.strided.geometric.PRNG":"var prng = random.strided.geometric.PRNG;\n","random.strided.geometric.seed":"var seed = random.strided.geometric.seed;\n","random.strided.geometric.seedLength":"var len = random.strided.geometric.seedLength;\n","random.strided.geometric.state":"var out = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\nvar state = random.strided.geometric.state\nout = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\nrandom.strided.geometric.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n","random.strided.geometric.stateLength":"var len = random.strided.geometric.stateLength;\n","random.strided.geometric.byteLength":"var sz = random.strided.geometric.byteLength;\n","random.strided.invgamma":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.invgamma( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.invgamma( 3, a, -2, b, 1, out, 1 )\n","random.strided.invgamma.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.invgamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.invgamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.lognormal":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.lognormal( out.length, mu, 1, sigma, 1, out, 1 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.lognormal( 3, mu, -2, sigma, 1, out, 1 )\n","random.strided.lognormal.ndarray":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.lognormal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.lognormal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n","random.strided.minstd":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd( out.length, out, 1 )\n","random.strided.minstd.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd.ndarray( out.length, out, 1, 0 )\n","random.strided.minstd.normalized":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd.normalized( out.length, out, 1 )\n","random.strided.minstd.normalized.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd.normalized.ndarray( out.length, out, 1, 0 )\n","random.strided.minstdShuffle":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle( out.length, out, 1 )\n","random.strided.minstdShuffle.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle.ndarray( out.length, out, 1, 0 )\n","random.strided.minstdShuffle.normalized":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle.normalized( out.length, out, 1 )\n","random.strided.minstdShuffle.normalized.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle.normalized.ndarray( out.length, out, 1, 0 )\n","random.strided.mt19937":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937( out.length, out, 1 )\n","random.strided.mt19937.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937.ndarray( out.length, out, 1, 0 )\n","random.strided.mt19937.normalized":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937.normalized( out.length, out, 1 )\n","random.strided.mt19937.normalized.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937.normalized.ndarray( out.length, out, 1, 0 )\n","random.strided.normal":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.normal( out.length, mu, 1, sigma, 1, out, 1 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.normal( 3, mu, -2, sigma, 1, out, 1 )\n","random.strided.normal.ndarray":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.normal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.normal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n","random.strided.poisson":"var out = azeros( 5, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.poisson.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.poisson.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.poisson.factory":"var fcn = random.strided.poisson.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.poisson.PRNG":"var prng = random.strided.poisson.PRNG;\n","random.strided.poisson.seed":"var seed = random.strided.poisson.seed;\n","random.strided.poisson.seedLength":"var len = random.strided.poisson.seedLength;\n","random.strided.poisson.state":"var out = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.poisson.state\nout = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.poisson.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.poisson.stateLength":"var len = random.strided.poisson.stateLength;\n","random.strided.poisson.byteLength":"var sz = random.strided.poisson.byteLength;\n","random.strided.randu":"var out = azeros( 5, 'generic' );\nrandom.strided.randu( out.length, out, 1 )\n","random.strided.randu.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.randu.ndarray( out.length, out, 1, 0 )\n","random.strided.rayleigh":"var out = azeros( 5, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.rayleigh.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.rayleigh.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.rayleigh.factory":"var fcn = random.strided.rayleigh.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.rayleigh.PRNG":"var prng = random.strided.rayleigh.PRNG;\n","random.strided.rayleigh.seed":"var seed = random.strided.rayleigh.seed;\n","random.strided.rayleigh.seedLength":"var len = random.strided.rayleigh.seedLength;\n","random.strided.rayleigh.state":"var out = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.rayleigh.state\nout = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.rayleigh.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.rayleigh.stateLength":"var len = random.strided.rayleigh.stateLength;\n","random.strided.rayleigh.byteLength":"var sz = random.strided.rayleigh.byteLength;\n","random.strided.t":"var out = azeros( 5, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.t.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.t.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.t.factory":"var fcn = random.strided.t.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.t.PRNG":"var prng = random.strided.t.PRNG;\n","random.strided.t.seed":"var seed = random.strided.t.seed;\n","random.strided.t.seedLength":"var len = random.strided.t.seedLength;\n","random.strided.t.state":"var out = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.t.state\nout = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.t.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.t.stateLength":"var len = random.strided.t.stateLength;\n","random.strided.t.byteLength":"var sz = random.strided.t.byteLength;\n","random.strided.uniform":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.uniform( out.length, a, 1, b, 1, out, 1 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.uniform( 3, a, -2, b, 1, out, 1 )\n","random.strided.uniform.ndarray":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.uniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.uniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.weibull":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.weibull( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.weibull( 3, a, -2, b, 1, out, 1 )\n","random.strided.weibull.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.weibull.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.weibull.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","ranks":"var arr = [ 1.1, 2.0, 3.5, 0.0, 2.4 ] ;\nvar out = ranks( arr )\narr =  [ 2, 2, 1, 4, 3 ];\nout = ranks( arr )\narr = [ null, 2, 2, 1, 4, 3, NaN, NaN ];\nout = ranks( arr )\n","readDir":"function onRead( error, data ) {\n if ( error ) {\n     console.error( error.message );\n } else {\n     console.log( data );\n }\n };\nreadDir( './beep/boop', onRead );\n","readDir.sync":"var out = readDir.sync( './beep/boop' );\n","readFile":"function onRead( error, data ) {\n if ( error ) {\n     console.error( error.message );\n } else {\n     console.log( data );\n }\n };\nreadFile( './beep/boop.js', onRead );\n","readFile.sync":"var out = readFile.sync( './beep/boop.js' );\n","readFileList":"function onRead( error, data ) {\n if ( error ) {\n     console.error( error.message );\n } else {\n     console.log( data );\n }\n };\nvar filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\nreadFileList( filepaths, onRead );\n","readFileList.sync":"var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\nvar out = readFileList.sync( filepaths );\n","readJSON":"function onRead( error, data ) {\n if ( error ) {\n     console.error( error.message );\n } else {\n     console.log( data );\n }\n };\nreadJSON( './beep/boop.json', onRead );\n","readJSON.sync":"var out = readJSON.sync( './beep/boop.json' );\n","readWASM":"function onRead( error, data ) {\n if ( error ) {\n     console.error( error.message );\n } else {\n     console.log( data );\n }\n };\nreadWASM( './beep/boop.wasm', onRead );\n","readWASM.sync":"var out = readWASM.sync( './beep/boop.wasm' );\n","real":"var z = new Complex128( 5.0, 3.0 );\nvar re = real( z )\n","realarray":"var arr = realarray()\narr = realarray( 'float32' )\nvar arr = realarray( 5 )\narr = realarray( 5, 'int32' )\nvar arr1 = realarray( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = realarray( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = realarray( arr1, 'float32' )\nvar buf = new ArrayBuffer( 16 );\nvar arr = realarray( buf, 0, 4, 'float32' )\n","realarrayCtors":"var ctor = realarrayCtors( 'float64' )\nctor = realarrayCtors( 'float' )\n","realarrayDataTypes":"var out = realarrayDataTypes()\n","realf":"var z = new Complex64( 5.0, 3.0 );\nvar re = realf( z )\n","realmax":"var m = realmax( 'float16' )\nm = realmax( 'float32' )\n","realmin":"var m = realmin( 'float16' )\nm = realmin( 'float32' )\n","reBasename":"var RE = reBasename()\nvar RE_POSIX = reBasename( 'posix' );\nvar RE_WIN32 = reBasename( 'win32' );\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reBasename.REGEXP":"var RE = reBasename.REGEXP\n","reBasename.REGEXP_POSIX":"var base = reBasename.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n","reBasename.REGEXP_WIN32":"var base = reBasename.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reBasenamePosix":"var RE_BASENAME_POSIX = reBasenamePosix();\nvar base = RE_BASENAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( 'index.js' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( '.' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( './' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( '' )[ 1 ]\n","reBasenamePosix.REGEXP":"var base = reBasenamePosix.REGEXP.exec( 'foo/bar/index.js' )[ 1 ]\n","reBasenameWindows":"var RE_BASENAME_WINDOWS = reBasenameWindows();\nvar base = RE_BASENAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\index.js' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'foo\\\\file.pdf' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'foo\\\\bar\\\\file' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'index.js' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( '.' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( '' )[ 1 ]\n","reBasenameWindows.REGEXP":"var match = reBasenameWindows.REGEXP.exec( 'foo\\\\file.pdf' )[ 1 ]\n","reColorHexadecimal":"var RE = reColorHexadecimal();\nvar bool = RE.test( 'ffffff' )\nbool = RE.test( '000' )\nbool = RE.test( 'beep' )\n","reColorHexadecimal.REGEXP":"var bool = reColorHexadecimal.REGEXP.test( 'ffffff' )\nbool = reColorHexadecimal.REGEXP.test( '000' )\nbool = reColorHexadecimal.REGEXP.test( 'beep' )\n","reColorHexadecimal.REGEXP_SHORTHAND":"var bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'ffffff' )\nbool = reColorHexadecimal.REGEXP_SHORTHAND.test( '000' )\nbool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'beep' )\n","reColorHexadecimal.REGEXP_EITHER":"var bool = reColorHexadecimal.REGEXP_EITHER.test( 'ffffff' )\nbool = reColorHexadecimal.REGEXP_EITHER.test( '000' )\nbool = reColorHexadecimal.REGEXP_EITHER.test( 'beep' )\n","reDecimalNumber":"var RE = reDecimalNumber();\nvar bool = RE.test( '1.234' )\nbool = RE.test( '-1.234' )\nbool = RE.test( '0.0' )\nbool = RE.test( '.0' )\nbool = RE.test( '0' )\nbool = RE.test( 'beep' )\nvar re = reDecimalNumber({ 'flags': 'g' });\nvar str = '1.234 5.6, 7.8';\nvar out = str.match( re )\n","reDecimalNumber.REGEXP":"var RE = reDecimalNumber.REGEXP;\nvar bool = RE.test( '1.234' )\nbool = RE.test( '-1.234' )\n","reDecimalNumber.REGEXP_CAPTURE":"var RE = reDecimalNumber.REGEXP_CAPTURE;\nvar str = '1.02';\nvar out = replace( str, RE, '$1 x $1' )\n","reDirname":"var RE = reDirname()\nvar RE_POSIX = reDirname( 'posix' );\nvar dir = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\nvar RE_WIN32 = reDirname( 'win32' );\ndir = RE_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reDirname.REGEXP":"var RE = reDirname.REGEXP\n","reDirname.REGEXP_POSIX":"var dir = reDirname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n","reDirname.REGEXP_WIN32":"var dir = reDirname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reDirnamePosix":"var RE = reDirnamePosix();\nvar dir = RE.exec( '/foo/bar/index.js' )[ 1 ]\ndir = RE.exec( './foo/bar/.gitignore' )[ 1 ]\ndir = RE.exec( 'foo/file.pdf' )[ 1 ]\ndir = RE.exec( '/foo/bar/file' )[ 1 ]\ndir = RE.exec( 'index.js' )[ 1 ]\ndir = RE.exec( '.' )[ 1 ]\ndir = RE.exec( './' )[ 1 ]\ndir = RE.exec( '' )[ 1 ]\n","reDirnamePosix.REGEXP":"var ext = reDirnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n","reDirnameWindows":"var RE = reDirnameWindows();\nvar dir = RE.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\ndir = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\ndir = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\ndir = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\ndir = RE.exec( 'index.js' )[ 1 ]\ndir = RE.exec( '' )[ 1 ]\n","reDirnameWindows.REGEXP":"var dir = reDirnameWindows.REGEXP.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n","reduce":"var f = naryFunction( base.add, 2 );\nvar arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\nvar out = reduce( arr, 0.0, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = reduce( arr, 0.0, f )\n","reduce2d":"var f = naryFunction( base.add, 2 );\nvar arr = [ [ 1, 2, 3 ], [ 4, 5, 6 ] ];\nvar out = reduce2d( arr, [ 0, 0 ], f )\n","reduceAsync":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     acc.sum += value;\n     next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n     throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nreduceAsync( arr, acc, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     acc.sum += value;\n     next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n     throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nreduceAsync( arr, acc, opts, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     acc.sum += value;\n     next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n     throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'series': false };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nreduceAsync( arr, acc, opts, fcn, done )\n","reduceAsync.factory":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     acc.sum += value;\n     next( null, acc );\n }\n };\nvar opts = { 'series': false };\nvar f = reduceAsync.factory( opts, fcn );\nfunction done( error, acc ) {\n if ( error ) {\n     throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nf( arr, acc, done )\nacc = { 'sum': 0 };\narr = [ 2000, 1500, 1000 ];\nf( arr, acc, done )\n","reduceRight":"var f = naryFunction( base.add, 2 );\nvar arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\nvar out = reduceRight( arr, 0.0, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = reduceRight( arr, 0.0, f )\n","reduceRightAsync":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     acc.sum += value;\n     next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n     throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nreduceRightAsync( arr, acc, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     acc.sum += value;\n     next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n     throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nreduceRightAsync( arr, acc, opts, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     acc.sum += value;\n     next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n     throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'series': false };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nreduceRightAsync( arr, acc, opts, fcn, done )\n","reduceRightAsync.factory":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     acc.sum += value;\n     next( null, acc );\n }\n };\nvar opts = { 'series': false };\nvar f = reduceRightAsync.factory( opts, fcn );\nfunction done( error, acc ) {\n if ( error ) {\n     throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nf( arr, acc, done )\nacc = { 'sum': 0 };\narr = [ 1000, 1500, 2000 ];\nf( arr, acc, done )\n","reDurationString":"var RE = reDurationString();\nvar parts = RE.exec( '3d2ms' )\nparts = RE.exec( '4h3m20s' )\n","reDurationString.REGEXP":"var bool = reDurationString.REGEXP.test( '3d2ms' )\nbool = reDurationString.REGEXP.test( 'foo' )\n","reEOL":"var RE_EOL = reEOL();\nvar bool = RE_EOL.test( '\\n' )\nbool = RE_EOL.test( '\\r\\n' )\nbool = RE_EOL.test( '\\\\r\\\\n' )\n","reEOL.REGEXP":"var bool = reEOL.REGEXP.test( 'abc' )\n","reEOL.REGEXP_CAPTURE":"var parts = reEOL.REGEXP_CAPTURE.exec( '\\n' )\n","reExtendedLengthPath":"var RE = reExtendedLengthPath();\nvar path = '\\\\\\\\?\\\\C:\\\\foo\\\\bar';\nvar bool = RE.test( path )\npath = '\\\\\\\\?\\\\UNC\\\\server\\\\share';\nbool = RE.test( path )\npath = 'C:\\\\foo\\\\bar';\nbool = RE.test( path )\npath = '/c/foo/bar';\nbool = RE.test( path )\npath = '/foo/bar';\nbool = RE.test( path )\n","reExtendedLengthPath.REGEXP":"var bool = reExtendedLengthPath.REGEXP.test( 'C:\\\\foo\\\\bar' )\n","reExtname":"var RE = reExtname()\nvar RE_POSIX = reExtname( 'posix' );\nvar ext = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\nvar RE_WIN32 = reExtname( 'win32' );\next = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reExtname.REGEXP":"var RE = reExtname.REGEXP\n","reExtname.REGEXP_POSIX":"var ext = reExtname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n","reExtname.REGEXP_WIN32":"var ext = reExtname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reExtnamePosix":"var RE = reExtnamePosix();\nvar ext = RE.exec( '/foo/bar/index.js' )[ 1 ]\next = RE.exec( './foo/bar/.gitignore' )[ 1 ]\next = RE.exec( 'foo/file.pdf' )[ 1 ]\next = RE.exec( '/foo/bar/file' )[ 1 ]\next = RE.exec( 'index.js' )[ 1 ]\next = RE.exec( '.' )[ 1 ]\next = RE.exec( './' )[ 1 ]\next = RE.exec( '' )[ 1 ]\n","reExtnamePosix.REGEXP":"var ext = reExtnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n","reExtnameWindows":"var RE = reExtnameWindows();\nvar ext = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\next = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\next = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\next = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\next = RE.exec( 'beep\\\\boop.' )[ 1 ]\next = RE.exec( 'index.js' )[ 1 ]\next = RE.exec( '' )[ 1 ]\n","reExtnameWindows.REGEXP":"var ext = reExtnameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reFilename":"var RE = reFilename()\nvar RE_POSIX = reFilename( 'posix' );\nvar parts = RE_POSIX.exec( '/foo/bar/index.js' ).slice()\nvar RE_WIN32 = reFilename( 'win32' );\nparts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reFilename.REGEXP":"var RE = reFilename.REGEXP\n","reFilename.REGEXP_POSIX":"var f = '/foo/bar/index.js';\nvar parts = reFilename.REGEXP_POSIX.exec( f ).slice()\n","reFilename.REGEXP_WIN32":"var f = 'C:\\\\foo\\\\bar\\\\index.js';\nvar parts = reFilename.REGEXP_WIN32.exec( f ).slice()\n","reFilenamePosix":"var RE = reFilenamePosix();\nvar parts = RE.exec( '/foo/bar/index.js' ).slice()\nparts = RE.exec( './foo/bar/.gitignore' ).slice()\nparts = RE.exec( 'foo/file.pdf' ).slice()\nparts = RE.exec( '/foo/bar/file' ).slice()\nparts = RE.exec( 'index.js' ).slice()\nparts = RE.exec( '.' ).slice()\nparts = RE.exec( './' ).slice()\nparts = RE.exec( '' ).slice()\n","reFilenamePosix.REGEXP":"var parts = reFilenamePosix.REGEXP.exec( '/foo/bar/index.js' ).slice()\n","reFilenameWindows":"var RE = reFilenameWindows();\nvar parts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\nparts = RE.exec( '\\\\foo\\\\bar\\\\.gitignore' ).slice()\nparts = RE.exec( 'foo\\\\file.pdf' ).slice()\nparts = RE.exec( '\\\\foo\\\\bar\\\\file' ).slice()\nparts = RE.exec( 'index.js' ).slice()\nparts = RE.exec( '.' ).slice()\nparts = RE.exec( './' ).slice()\nparts = RE.exec( '' ).slice()\n","reFilenameWindows.REGEXP":"var parts = reFilenameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n","reFromString":"var re = reFromString( '/beep/' )\nre = reFromString( '/beep' )\n","reFunctionName":"var RE_FUNCTION_NAME = reFunctionName();\nfunction beep() { return 'boop'; };\nvar name = RE_FUNCTION_NAME.exec( beep.toString() )[ 1 ]\nname = RE_FUNCTION_NAME.exec( function () {} )[ 1 ]\n","reFunctionName.REGEXP":"var str = reFunctionName.REGEXP.exec( Math.sqrt.toString() )[ 1 ]\n","regexp2json":"var json = regexp2json( /ab+c/ )\n","reim":"var z = new Complex128( 5.0, 3.0 );\nvar out = reim( z )\n","reimf":"var z = new Complex64( 5.0, 3.0 );\nvar out = reimf( z )\n","rejectArguments":"function foo( a, b ) { return [ a, b ]; };\nfunction predicate( v ) { return ( v === 2 ); };\nvar bar = rejectArguments( foo, predicate );\nvar out = bar( 1, 2, 3 )\n","removeFirst":"var out = removeFirst( 'beep' )\nout = removeFirst( 'Boop' )\nout = removeFirst( 'foo bar', 4 )\n","removeLast":"var out = removeLast( 'beep' )\nout = removeLast( 'Boop' )\nout = removeLast( 'foo bar', 4 )\n","removePunctuation":"var str = 'Sun Tzu said: \"A leader leads by example not by force.\"';\nvar out = removePunctuation( str )\nstr = 'This function removes these characters: `{}[]:,!/<>().;~|?\\'\"';\nout = removePunctuation( str )\n","removeUTF8BOM":"var out = removeUTF8BOM( '\\ufeffbeep' )\n","removeWords":"var out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ] )\nout = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ], true )\n","rename":"function done( error ) {\n if ( error ) {\n     console.error( error.message );\n }\n };\nrename( './beep/boop.txt', './beep/foo.txt', done );\n","rename.sync":"var err = rename.sync( './beep/boop.txt', './beep/foo.txt' );\n","reNativeFunction":"var RE = reNativeFunction();\nvar bool = RE.test( Date.toString() )\nbool = RE.test( (function noop() {}).toString() )\n","reNativeFunction.REGEXP":"var bool = reNativeFunction.REGEXP.test( Date.toString() )\nbool = reNativeFunction.REGEXP.test( (function noop() {}).toString() )\n","reorderArguments":"function foo( a, b, c ) { return [ a, b, c ]; };\nvar bar = reorderArguments( foo, [ 2, 0, 1 ] );\nvar out = bar( 1, 2, 3 )\n","repeat":"var out = repeat( 'a', 5 )\nout = repeat( '', 100 )\nout = repeat( 'beep', 0 )\n","replace":"var out = replace( 'beep', 'e', 'o' )\nfunction replacer( match, p1 ) { return '/'+p1+'/'; };\nvar str = 'Oranges and lemons';\nout = replace( str, /([^\\s]+)/gi, replacer )\nout = replace( 'beep', /e/, 'o' )\n","replaceBefore":"var str = 'beep boop';\nvar out = replaceBefore( str, ' ', 'foo' )\nout = replaceBefore( str, 'o', 'foo' )\n","reRegExp":"var RE = reRegExp();\nvar bool = RE.test( '/^beep$/' )\nbool = RE.test( '/boop' )\nbool = RE.test( '/^\\/([^\\/]+)\\/(.*)$/' )\nbool = RE.test( '/^\\\\/([^\\\\/]+)\\\\/(.*)$/' )\n","reRegExp.REGEXP":"var bool = reRegExp.REGEXP.test( '/^beep$/' )\nbool = reRegExp.REGEXP.test( '/boop' )\n","rescape":"var str = rescape( '[A-Z]*' )\n","reSemVer":"var RE_SEMVER = reSemVer()\nvar bool = RE_SEMVER.test( '1.0.0' )\nbool = RE_SEMVER.test( '1.0.0-alpha.1' )\nbool = RE_SEMVER.test( 'abc' )\nbool = RE_SEMVER.test( '1.0.0-alpha.1+build.1' )\n","reSemVer.REGEXP":"var bool = reSemVer.REGEXP.test( '1.0.0' )\nbool = reSemVer.REGEXP.test( '-1.0.0-alpha.1' )\n","resolveParentPath":"function onPath( error, path ) {\n if ( error ) {\n     console.error( error.message );\n } else {\n     console.log( path );\n }\n };\nresolveParentPath( 'package.json', onPath );\n","resolveParentPath.sync":"var out = resolveParentPath.sync( 'package.json' );\n","resolveParentPathBy":"function predicate( path, next ) {\n setTimeout( onTimeout, path );\n function onTimeout() {\n     console.log( path );\n     next( null, false );\n }\n };\nfunction onPath( error, path ) {\n if ( error ) {\n     console.error( error.message );\n } else {\n     console.log( path );\n }\n };\nresolveParentPathBy( 'package.json', predicate, onPath );\n","resolveParentPathBy.sync":"function predicate() { return false; };\nvar out = resolveParentPathBy.sync( 'package.json', predicate );\n","reUncPath":"var RE = reUncPath();\nvar path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\nvar bool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\\\\\share';\nbool = RE.test( path )\npath = '\\\\\\\\\\\\\\\\server\\\\share';\nbool = RE.test( path )\npath = 'beep boop \\\\\\\\server\\\\share';\nbool = RE.test( path )\npath = '\\\\\\\\server';\nbool = RE.test( path )\npath = '\\\\';\nbool = RE.test( path )\npath = '';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b:c';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\';\nbool = RE.test( path )\npath = '//server/share';\nbool = RE.test( path )\npath = '/foo/bar';\nbool = RE.test( path )\npath = 'foo/bar';\nbool = RE.test( path )\npath = './foo/bar';\nbool = RE.test( path )\npath = '/foo/../bar';\nbool = RE.test( path )\n","reUncPath.REGEXP":"var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\nvar bool = reUncPath.REGEXP.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\nbool = reUncPath.REGEXP.test( path )\n","reUtf16SurrogatePair":"var RE = reUtf16SurrogatePair();\nvar bool = RE.test( 'abc\\uD800\\uDC00def' )\nbool = RE.test( 'abcdef' )\n","reUtf16SurrogatePair.REGEXP":"var RE = reUtf16SurrogatePair.REGEXP;\nvar bool = RE.test( 'abc\\uD800\\uDC00def' )\nbool = RE.test( 'abcdef' )\n","reUtf16UnpairedSurrogate":"var RE = reUtf16UnpairedSurrogate();\nvar bool = RE.test( 'abc' )\nbool = RE.test( '\\uD800' )\n","reUtf16UnpairedSurrogate.REGEXP":"var RE = reUtf16UnpairedSurrogate.REGEXP;\nvar bool = RE.test( 'abc' )\nbool = RE.test( '\\uD800' )\n","reverseArguments":"function foo( a, b, c ) { return [ a, b, c ]; };\nvar bar = reverseArguments( foo );\nvar out = bar( 1, 2, 3 )\n","reverseString":"var out = reverseString( 'foo' )\nout = reverseString( 'abcdef' )\n","reviveBasePRNG":"var str = JSON.stringify( base.random.mt19937 );\nvar r = parseJSON( str, reviveBasePRNG )\n","reviveBuffer":"var str = '{\"type\":\"Buffer\",\"data\":[5,3]}';\nvar buf = parseJSON( str, reviveBuffer )\n","reviveComplex":"var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\nvar z = parseJSON( str, reviveComplex )\n","reviveComplex64":"var str = '{\"type\":\"Complex64\",\"re\":5,\"im\":3}';\nvar z = parseJSON( str, reviveComplex64 )\n","reviveComplex128":"var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\nvar z = parseJSON( str, reviveComplex128 )\n","reviveError":"var str = '{\"type\":\"TypeError\",\"message\":\"beep\"}';\nvar err = JSON.parse( str, reviveError )\n","reviveRegExp":"var str = '{\"type\":\"RegExp\",\"pattern\":\"ab+c\",\"flags\":\"\"}';\nvar v = parseJSON( str, reviveRegExp )\n","reviveTypedArray":"var str = '{\"type\":\"Float64Array\",\"data\":[5,3]}';\nvar arr = parseJSON( str, reviveTypedArray )\n","reWhitespace":"var RE = reWhitespace();\nvar bool = RE.test( '\\n' )\nbool = RE.test( ' ' )\nbool = RE.test( 'a' )\n","reWhitespace.REGEXP":"var RE = reWhitespace.REGEXP;\nvar bool = RE.test( '\\n' )\nbool = RE.test( ' ' )\nbool = RE.test( 'a' )\n","reWhitespace.REGEXP_CAPTURE":"var RE = reWhitespace.REGEXP_CAPTURE;\nvar str = 'Duplicate capture';\nvar out = replace( str, RE, '$1$1' )\n","rpad":"var out = rpad( 'a', 5 )\nout = rpad( 'beep', 10, 'p' )\nout = rpad( 'beep', 12, 'boop' )\n","rtrim":"var out = rtrim( ' \\t\\t\\n  Beep \\r\\n\\t  ' )\n","rtrimN":"var out = rtrimN( '  abc  ', 2 )\nvar out = rtrimN( '!!!abc!!!', 2, '!' )\n","safeintmax":"var m = safeintmax( 'float16' )\nm = safeintmax( 'float32' )\n","safeintmin":"var m = safeintmin( 'float16' )\nm = safeintmin( 'float32' )\n","sample":"var out = sample( 'abc' )\nout = sample( [ 3, 6, 9 ] )\nvar bool = ( out.length === 3 )\nout = sample( [ 3, null, NaN, 'abc', function(){} ] )\nout = sample( [ 3, 6, 9 ], { 'size': 10 } )\nout = sample( [ 0, 1 ], { 'size': 20 } )\nout = sample( [ 1, 2, 3, 4, 5, 6 ], { 'replace': false, 'size': 3 } )\nout = sample( [ 0, 1 ], { 'replace': false } )\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar probs = [ 0.1, 0.1, 0.1, 0.1, 0.1, 0.5 ];\nout = sample( x, { 'probs': probs } )\nout = sample( x, { 'probs': probs, 'size': 3, 'replace': false } )\n","sample.factory":"var mysample = sample.factory({ 'seed': 232 } );\nvar out = mysample( 'abcdefg' )\nvar pool = [ 1, 2, 3, 4, 5, 6 ];\nmysample = sample.factory( pool, { 'seed': 232, 'size': 2 } );\nout = mysample()\nout = mysample()\nvar opts = { 'seed': 474, 'size': 3, 'mutate': true, 'replace': false };\npool = [ 1, 2, 3, 4, 5, 6 ];\nmysample = sample.factory( pool, opts );\nout = mysample()\nout = mysample()\nout = mysample()\nmysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\nout = mysample()\nout = mysample({ 'size': 10 })\nmysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\nout = mysample()\nout = mysample({ 'replace': false })\nout = mysample()\n","SAVOY_STOPWORDS_FIN":"var list = SAVOY_STOPWORDS_FIN()\n","SAVOY_STOPWORDS_FR":"var list = SAVOY_STOPWORDS_FR()\n","SAVOY_STOPWORDS_GER":"var list = SAVOY_STOPWORDS_GER()\n","SAVOY_STOPWORDS_IT":"var list = SAVOY_STOPWORDS_IT()\n","SAVOY_STOPWORDS_POR":"var list = SAVOY_STOPWORDS_POR()\n","SAVOY_STOPWORDS_SP":"var list = SAVOY_STOPWORDS_SP()\n","SAVOY_STOPWORDS_SWE":"var list = SAVOY_STOPWORDS_SWE()\n","scalar2array":"var x = scalar2array( 1.0 )\n","scalar2ndarray":"var x = scalar2ndarray( 1.0 )\nvar sh = x.shape\nvar dt = x.dtype\nvar v = x.get()\n","sdot":"var xbuf = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar x = array( xbuf );\nvar ybuf = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar y = array( ybuf );\nvar z = sdot( x, y )\nz.get()\n","SECONDS_IN_DAY":"var days = 3.14;\nvar secs = days * SECONDS_IN_DAY\n","SECONDS_IN_HOUR":"var hrs = 3.14;\nvar secs = hrs * SECONDS_IN_HOUR\n","SECONDS_IN_MINUTE":"var mins = 3.14;\nvar secs = mins * SECONDS_IN_MINUTE\n","SECONDS_IN_WEEK":"var wks = 3.14;\nvar secs = wks * SECONDS_IN_WEEK\n","secondsInMonth":"var num = secondsInMonth()\nnum = secondsInMonth( 2 )\nnum = secondsInMonth( 2, 2016 )\nnum = secondsInMonth( 2, 2017 )\nnum = secondsInMonth( 'feb', 2016 )\nnum = secondsInMonth( 'february', 2016 )\n","secondsInYear":"var num = secondsInYear()\nnum = secondsInYear( 2016 )\nnum = secondsInYear( 2017 )\n","sentencize":"var out = sentencize( 'Hello Mrs. Maple, could you call me back?' )\nout = sentencize( 'Hello World! How are you?' )\n","seq2slice":"var s = new seq2slice( '1:10', 10, false );\ns.start\ns.stop\ns.step\ns = new seq2slice( '2:5:2', 10, false );\ns.start\ns.stop\ns.step\n","setConfigurableReadOnly":"var obj = {};\nsetConfigurableReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n","setConfigurableReadOnlyAccessor":"var obj = {};\nfunction getter() { return 'bar'; };\nsetConfigurableReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n","setConfigurableReadWriteAccessor":"var obj = {};\nvar name = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetConfigurableReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n","setConfigurableWriteOnlyAccessor":"var obj = {};\nvar val = '';\nfunction setter( v ) { val = v; };\nsetConfigurableWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n","setMemoizedConfigurableReadOnly":"var obj = {};\nfunction foo() { return 'bar'; };\nsetMemoizedConfigurableReadOnly( obj, 'foo', foo );\nobj.foo\n","setMemoizedReadOnly":"var obj = {};\nfunction foo() { return 'bar'; };\nsetMemoizedReadOnly( obj, 'foo', foo );\nobj.foo\n","setNonEnumerableProperty":"var obj = {};\nsetNonEnumerableProperty( obj, 'foo', 'bar' );\nobj.foo\nobjectKeys( obj )\n","setNonEnumerableReadOnly":"var obj = {};\nsetNonEnumerableReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n","setNonEnumerableReadOnlyAccessor":"var obj = {};\nfunction getter() { return 'bar'; };\nsetNonEnumerableReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n","setNonEnumerableReadWriteAccessor":"var obj = {};\nvar name = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetNonEnumerableReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n","setNonEnumerableWriteOnlyAccessor":"var obj = {};\nvar val = '';\nfunction setter( v ) { val = v; };\nsetNonEnumerableWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n","setReadOnly":"var obj = {};\nsetReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n","setReadOnlyAccessor":"var obj = {};\nfunction getter() { return 'bar'; };\nsetReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n","setReadWriteAccessor":"var obj = {};\nvar name = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n","setWriteOnlyAccessor":"var obj = {};\nvar val = '';\nfunction setter( v ) { val = v; };\nsetWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n","SharedArrayBuffer":"var buf = new SharedArrayBuffer( 5 )\n","SharedArrayBuffer.length":"SharedArrayBuffer.length\n","SharedArrayBuffer.prototype.byteLength":"var buf = new SharedArrayBuffer( 5 );\nbuf.byteLength\n","SharedArrayBuffer.prototype.slice":"var b1 = new SharedArrayBuffer( 10 );\nvar b2 = b1.slice( 2, 6 );\nvar bool = ( b1 === b2 )\nb2.byteLength\n","shift":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar out = shift( arr )\narr = new Float64Array( [ 1.0, 2.0 ] );\nout = shift( arr )\narr = { 'length': 2, '0': 1.0, '1': 2.0 };\nout = shift( arr )\n","shuffle":"var data = [ 1, 2, 3 ];\nvar out = shuffle( data )\nout = shuffle( data, { 'copy': 'none' } );\nvar bool = ( data === out )\n","shuffle.factory":"var myshuffle = shuffle.factory();\nmyshuffle = shuffle.factory({ 'seed': 239 });\nvar arr = [ 0, 1, 2, 3, 4 ];\nvar out = myshuffle( arr )\nmyshuffle = shuffle.factory({ 'copy': 'none', 'seed': 867 });\narr = [ 1, 2, 3, 4, 5, 6 ];\nout = myshuffle( arr );\nvar bool = ( arr === out )\narr = [ 1, 2, 3, 4 ];\nout = myshuffle( arr, { 'copy': 'shallow' } );\nbool = ( arr === out )\n","sizeOf":"var s = sizeOf( 'int8' )\ns = sizeOf( 'uint32' )\n","Slice":"var s = new Slice();\ns = new Slice( 10 );\nvar s = new Slice( 2, 10 );\ns = new Slice( 2, 10, 1 );\n","Slice.prototype.start":"var s = new Slice( 10 );\ns.start\ns = new Slice( 2, 10 );\ns.start\n","Slice.prototype.stop":"var s = new Slice( 10 );\ns.stop\ns = new Slice( 2, 10 );\ns.stop\n","Slice.prototype.step":"var s = new Slice( 10 );\ns.step\ns = new Slice( 2, 10 );\ns.step\ns = new Slice( 2, 10, 1 );\ns.step\n","Slice.prototype.toString":"var s = new Slice( 10 );\ns.toString()\ns = new Slice( 2, 10, 1 );\ns.toString()\n","Slice.prototype.toJSON":"var s = new Slice( 10 );\ns.toJSON()\ns = new Slice( 2, 10, 1 );\ns.toJSON()\n","snakecase":"var out = snakecase( 'Hello World!' )\nout = snakecase( 'I am a tiny little teapot' )\n","some":"var arr = [ 0, 0, 1, 2, 3 ];\nvar bool = some( arr, 3 )\n","someBy":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ 1, 2, -3, 4, -1 ];\nvar bool = someBy( arr, 2, negative )\n","someByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nsomeByAsync( arr, 2, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nsomeByAsync( arr, 2, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nsomeByAsync( arr, 2, opts, predicate, done )\n","someByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = someByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, 2, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, 2, done )\n","someByRight":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ -1, 1, -2, 3, 4 ];\nvar bool = someByRight( arr, 2, negative )\n","someByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nsomeByRightAsync( arr, 2, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nsomeByRightAsync( arr, 2, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nsomeByRightAsync( arr, 2, opts, predicate, done )\n","someByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = someByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, 2, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, 2, done )\n","someInBy":"function negative( v ) { return ( v < 0 ); };\nvar obj = { 'a': 1, 'b': 2, 'c': -3, 'd': 4, 'e': -1 };\nvar bool = someInBy( obj, 2, negative )\n","someOwnBy":"function negative( v ) { return ( v < 0 ); };\nvar obj = { a: 1, b: 2, c: -3, d: 4, e: -1 };\nvar bool = someOwnBy( obj, 2, negative )\n","SOTU":"var out = SOTU()\nvar opts = { 'name': 'Barack Obama' };\nout = SOTU( opts )\nopts = { 'party': [ 'Democratic', 'Federalist' ] };\nout = SOTU( opts )\nopts = { 'year': [ 2008, 2009, 2011 ] };\nout = SOTU( opts )\nopts = { 'range': [ 2008, 2016 ] }\nout = SOTU( opts )\n","SPACHE_REVISED":"var list = SPACHE_REVISED()\n","SPAM_ASSASSIN":"var data = SPAM_ASSASSIN()\n","SparklineBase":"var sparkline = new SparklineBase()\nvar data = [ 1, 2, 3 ];\nsparkline = new SparklineBase( data )\n","sparsearray2iterator":"var it = sparsearray2iterator( [ 1, , 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","sparsearray2iteratorRight":"var it = sparsearray2iteratorRight( [ 1, 2, , 4 ] );\nvar v = it.next().value\nv = it.next().value\n","splitStream":"var s = splitStream();\ns.write( 'a\\nb\\nc' );\ns.end();\n","splitStream.factory":"var opts = { 'highWaterMark': 64 };\nvar createStream = splitStream.factory( opts );\nvar s = createStream();\ns.write( 'a\\nb\\nc' );\ns.end();\n","splitStream.objectMode":"var s = splitStream.objectMode();\ns.write( 'a\\nb\\c' );\ns.end();\n","SQRT_EPS":"SQRT_EPS\n","SQRT_HALF":"SQRT_HALF\n","SQRT_HALF_PI":"SQRT_HALF_PI\n","SQRT_PHI":"SQRT_PHI\n","SQRT_PI":"SQRT_PI\n","SQRT_THREE":"SQRT_THREE\n","SQRT_TWO":"SQRT_TWO\n","SQRT_TWO_PI":"SQRT_TWO_PI\n","SSA_US_BIRTHS_2000_2014":"var data = SSA_US_BIRTHS_2000_2014()\n","sswap":"var x = array( new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\nsswap( x, y );\nx.data\ny.data\n","Stack":"var s = Stack();\ns.push( 'foo' ).push( 'bar' );\ns.length\ns.pop()\ns.length\ns.pop()\ns.length\n","standalone2pkg":"var v = standalone2pkg( '@stdlib/math-base-special-sin' )\n","STANDARD_CARD_DECK":"var list = STANDARD_CARD_DECK()\n","startcase":"var out = startcase( 'beep boop' )\n","startsWith":"var bool = startsWith( 'Beep', 'Be' )\nbool = startsWith( 'Beep', 'ep' )\nbool = startsWith( 'Beep', 'ee', 1 )\nbool = startsWith( 'Beep', 'ee', -3 )\nbool = startsWith( 'Beep', '' )\n","STOPWORDS_EN":"var list = STOPWORDS_EN()\n","strided.abs":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs( 2, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.abs( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.abs.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.abs2":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.abs2( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.abs2.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.abs2By":"var x = [ -1.0, -2.0, -3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.abs2By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.abs2By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.abs2By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.abs2By.ndarray":"var x = [ -1.0, -2.0, -3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.abs2By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ -1.0, -2.0, -3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.abs2By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.absBy":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nstrided.absBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.absBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.absBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.absBy.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nstrided.absBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.absBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acosBy":"var x = [ 1.0, 0.707, 0.866, -0.707 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, 0.707, 0.866, -0.707 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acosBy.ndarray":"var x = [ 1.0, 0.707, 0.866, -0.707 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 1.0, 0.707, 0.866, -0.707 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acoshBy":"var x = [ 1.0, 1.5, 2.0, 2.5 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acoshBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acoshBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, 1.5, 2.0, 2.5 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acoshBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acoshBy.ndarray":"var x = [ 1.0, 1.5, 2.0, 2.5 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acoshBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 1.0, 1.5, 2.0, 2.5 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acoshBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acotBy":"var x = [ -2.5, -1.5, -0.5, 0.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acotBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acotBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ -2.5, -1.5, -0.5, 0.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acotBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acotBy.ndarray":"var x = [ -2.5, -1.5, -0.5, 0.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acotBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ -2.5, -1.5, -0.5, 0.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acotBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acothBy":"var x = [ -5.0, -4.0, -3.0, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acothBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acothBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ -5.0, -4.0, -3.0, -1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acothBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acothBy.ndarray":"var x = [ -5.0, -4.0, -3.0, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acothBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ -5.0, -4.0, -3.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acothBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acovercosBy":"var x = [ 0.0, -1.57, -0.5, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acovercosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acovercosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -1.57, -0.5, -1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acovercosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acovercosBy.ndarray":"var x = [ 0.0, -1.57, -0.5, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acovercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -1.57, -0.5, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acovercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acoversinBy":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acoversinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acoversinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acoversinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acoversinBy.ndarray":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acoversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.57, 0.5, 1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acoversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.add":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.add( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.add( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.add( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\nz0\n","strided.add.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.add.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.add.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n","strided.addBy":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = [ 11.0, 12.0, 13.0, 14.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.addBy( x.length, x, 1, y, 1, z, 1, clbk )\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.addBy( 2, x, 2, y, -1, z, 1, clbk )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.addBy( 2, x1, -2, y1, 1, z1, 1, clbk )\nz0\n","strided.addBy.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = [ 11.0, 12.0, 13.0, 14.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.addBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\nx = [ 1.0, 2.0, 3.0, 4.0 ];\ny = [ 11.0, 12.0, 13.0, 14.0 ];\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nvar oy = y.length - 1;\nvar oz = z.length - 1;\nstrided.addBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n","strided.ahavercosBy":"var x = [ 0.0, 0.5, 1.0, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.ahavercosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.ahavercosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 0.5, 1.0, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.ahavercosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.ahavercosBy.ndarray":"var x = [ 0.0, 0.5, 1.0, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.ahavercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 0.5, 1.0, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.ahavercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.ahaversinBy":"var x = [ 0.0, 0.5, 1.0, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.ahaversinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.ahaversinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 0.5, 1.0, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.ahaversinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.ahaversinBy.ndarray":"var x = [ 0.0, 0.5, 1.0, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.ahaversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 0.5, 1.0, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.ahaversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.asinBy":"var x = [ 0.0, -0.5, 1.0, -0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.asinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.asinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -0.5, 1.0, -0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.asinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.asinBy.ndarray":"var x = [ 0.0, -0.5, 1.0, -0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.asinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -0.5, 1.0, -0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.asinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.asinhBy":"var x = [ 0.0, -0.0, 2.0, -2.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.asinhBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.asinhBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -0.0, 2.0, -2.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.asinhBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.asinhBy.ndarray":"var x = [ 0.0, -0.0, 2.0, -2.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.asinhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -0.0, 2.0, -2.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.asinhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.atanBy":"var x = [ 0.0, -0.5, 1.0, -1.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.atanBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.atanBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -0.5, 1.0, -1.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.atanBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.atanBy.ndarray":"var x = [ 0.0, -0.5, 1.0, -1.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.atanBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -0.5, 1.0, -1.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.atanBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.atanhBy":"var x = [ 0.0, -0.5, 1.0, -0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.atanhBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.atanhBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -0.5, 1.0, -0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.atanhBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.atanhBy.ndarray":"var x = [ 0.0, -0.5, 1.0, -0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.atanhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -0.5, 1.0, -0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.atanhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.avercosBy":"var x = [ 0.0, -1.57, -0.5, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.avercosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.avercosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -1.57, -0.5, -1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.avercosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.avercosBy.ndarray":"var x = [ 0.0, -1.57, -0.5, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.avercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -1.57, -0.5, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.avercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.aversinBy":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.aversinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.aversinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.aversinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.aversinBy.ndarray":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.aversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.57, 0.5, 1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.aversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.besselj0By":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.besselj0By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.besselj0By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.besselj0By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.besselj0By.ndarray":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.besselj0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 0.1, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.besselj0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.besselj1By":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.besselj1By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.besselj1By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.besselj1By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.besselj1By.ndarray":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.besselj1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 0.1, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.besselj1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.bessely0By":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.bessely0By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.bessely0By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.bessely0By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.bessely0By.ndarray":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.bessely0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 0.1, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.bessely0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.bessely1By":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.bessely1By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.bessely1By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.bessely1By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.bessely1By.ndarray":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.bessely1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 0.1, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.bessely1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.binetBy":"var x = [ 0.0, 1.0, 2.0, 3.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.binetBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.binetBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.binetBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.binetBy.ndarray":"var x = [ 0.0, 1.0, 2.0, 3.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.binetBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 2.0, 3.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.binetBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.cbrt":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.cbrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.cbrt.ndarray":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.cbrtBy":"var x = [ 1.0, 9.0, -27.0, 81.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.cbrtBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.cbrtBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.cbrtBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.cbrtBy.ndarray":"var x = [ 1.0, 9.0, -27.0, 81.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.cbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 1.0, 9.0, -27.0, 81.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.cbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.ceil":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.ceil( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.ceil.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.cosBy":"var x = [ 0.0, 3.14, -3.14, 10.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.cosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.cosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 3.14, -3.14, 10.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.cosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.cosBy.ndarray":"var x = [ 0.0, 3.14, -3.14, 10.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.cosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 3.14, -3.14, 10.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.cosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.deg2rad":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.deg2rad( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.deg2rad.ndarray":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.dataTypes":"var out = strided.dataTypes()\n","strided.dcbrtBy":"var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nfunction clbk( v ) { return v; };\nstrided.dcbrtBy( x.length, x, 1, y, 1, clbk )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.dcbrtBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.dcbrtBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.dcbrtBy.ndarray":"var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nfunction clbk( v ) { return v; };\nstrided.dcbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.dcbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.dispatch":"var t = [ 'float64', 'float64', 'float32', 'float32' ];\nvar d = [ base.abs, base.absf ];\nvar f = strided.dispatch( base.strided.unary, t, d, 7, 1, 1 );\nvar x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( x.length, 'float64', x, 1, 'float64', y, 1 );\ny\nf = strided.dispatch( base.strided.unary.ndarray, t, d, 9, 1, 1 );\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( 2, 'float64', x, 1, 2, 'float64', y, 1, 2 );\ny\n","strided.dispatchBy":"var t = [ 'float64', 'float64', 'float32', 'float32' ];\nvar d = [ base.abs, base.absf ];\nvar f = strided.dispatchBy( base.strided.unaryBy, t, d, 8, 1, 1 );\nvar x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( x.length, 'float64', x, 1, 'float64', y, 1, base.identity );\ny\nf = strided.dispatchBy( base.strided.unary.ndarray, t, d, 10, 1, 1 );\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( 2, 'float64', x, 1, 2, 'float64', y, 1, 2, base.identity );\ny\n","strided.floor":"var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.floor( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.floor.ndarray":"var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.inv":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.inv( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.inv.ndarray":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.mul":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.mul( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.mul( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.mul( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\nz0\n","strided.mul.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.mul.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.mul.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n","strided.mulBy":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = [ 11.0, 12.0, 13.0, 14.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.mulBy( x.length, x, 1, y, 1, z, 1, clbk )\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.mulBy( 2, x, 2, y, -1, z, 1, clbk )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.mulBy( 2, x1, -2, y1, 1, z1, 1, clbk )\nz0\n","strided.mulBy.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = [ 11.0, 12.0, 13.0, 14.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.mulBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\nx = [ 1.0, 2.0, 3.0, 4.0 ];\ny = [ 11.0, 12.0, 13.0, 14.0 ];\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nvar oy = y.length - 1;\nvar oz = z.length - 1;\nstrided.mulBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n","strided.ramp":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.ramp( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.ramp.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.rsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.rsqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.rsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.sinBy":"var x = [ 0.0, 3.14, -3.14, 10.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.sinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.sinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 3.14, -3.14, 10.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.sinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.sinBy.ndarray":"var x = [ 0.0, 3.14, -3.14, 10.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.sinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 3.14, -3.14, 10.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.sinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.sqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.sqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.sqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.sqrtBy":"var x = [ 0.0, 1.0, 122.0, 50.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.sqrtBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.sqrtBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 122.0, 50.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.sqrtBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.sqrtBy.ndarray":"var x = [ 0.0, 1.0, 122.0, 50.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.sqrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 122.0, 50.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.sqrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.sub":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.sub( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sub( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.sub( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\nz0\n","strided.sub.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.sub.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sub.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n","strided.subBy":"var x = [ 11.0, 12.0, 13.0, 14.0 ];\nvar y = [ 8.0, 7.0, 6.0, 5.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.subBy( x.length, x, 1, y, 1, z, 1, clbk )\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.subBy( 2, x, 2, y, -1, z, 1, clbk )\nvar x0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\nvar y0 = new Float64Array( [ 8.0, 7.0, 6.0, 5.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.subBy( 2, x1, -2, y1, 1, z1, 1, clbk )\nz0\n","strided.subBy.ndarray":"var x = [ 11.0, 12.0, 13.0, 14.0 ];\nvar y = [ 8.0, 7.0, 6.0, 5.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.subBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\nx = [ 11.0, 12.0, 13.0, 14.0 ];\ny = [ 8.0, 7.0, 6.0, 5.0 ];\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nvar oy = y.length - 1;\nvar oz = z.length - 1;\nstrided.subBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n","strided.trunc":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.trunc( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.trunc.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","stridedarray2iterator":"var it = stridedarray2iterator( 2, [ 1, 2, 3, 4 ], -2, 3 );\nvar v = it.next().value\nv = it.next().value\n","stridedArrayStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar s = stridedArrayStream( 3, [ 1, 2, 3 ], 1, 0 );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","stridedArrayStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = stridedArrayStream.factory( opts );\n","stridedArrayStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar s = stridedArrayStream.objectMode( 3, [ 1, 2, 3 ], 1, 0 );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","string2buffer":"var b = string2buffer( 'beep boop' )\nb = string2buffer( '7468697320697320612074c3a97374', 'hex' );\nb.toString()\n","sub2ind":"var d = [ 3, 3, 3 ];\nvar idx = sub2ind( d, 1, 2, 2 )\n","substringAfter":"var out = substringAfter( 'Hello World!', 'World' )\nout = substringAfter( 'Hello World!', 'Hello ' )\nout = substringAfter( 'Hello World!', 'l', 5 )\n","substringAfterLast":"var out = substringAfterLast( 'beep boop beep baz', 'beep' )\nout = substringAfterLast( 'Hello World!', 'Hello ' )\nout = substringAfterLast( 'Hello World!', 'o', 5 )\n","substringBefore":"var str = 'beep boop';\nvar out = substringBefore( str, ' ' )\nout = substringBefore( str, 'o' )\n","substringBeforeLast":"var str = 'Beep Boop Beep';\nvar out = substringBeforeLast( str, 'Beep' )\nout = substringBeforeLast( str, 'Boop' )\n","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"var data = SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"var data = SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n","Symbol":"var s = ( Symbol ) ? Symbol( 'beep' ) : null\n","tabulate":"var collection = [ 'beep', 'boop', 'foo', 'beep' ];\nvar out = tabulate( collection )\n","tabulateBy":"function indicator( value ) { return value[ 0 ]; };\nvar collection = [ 'beep', 'boop', 'foo', 'beep' ];\nvar out = tabulateBy( collection, indicator )\n","tabulateByAsync":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000, 750 ];\ntabulateByAsync( arr, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000, 750 ];\ntabulateByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000, 750 ];\ntabulateByAsync( arr, opts, indicator, done )\n","tabulateByAsync.factory":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nvar opts = { 'series': true };\nvar f = tabulateByAsync.factory( opts, indicator );\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000, 750 ];\nf( arr, done )\narr = [ 2000, 1500, 1000, 750 ];\nf( arr, done )\n","thunk":"var fcn = thunk( base.add, 2, 3 );\nvar v = fcn()\nv = fcn()\n","tic":"var t = tic()\n","timeit":"var code = 'var x = Math.pow( Math.random(), 3 );';\ncode += 'if ( x !== x ) {';\ncode += 'throw new Error( \\'Something went wrong.\\' );';\ncode += '}';\nfunction done( error, results ) {\n if ( error ) {\n     throw error;\n }\n console.dir( results );\n };\ntimeit( code, done )\n","tmpdir":"var dir = tmpdir()\n","toc":"var start = tic();\nvar delta = toc( start )\n","tokenize":"var out = tokenize( 'Hello Mrs. Maple, could you call me back?' )\nout = tokenize( 'Hello World!', true )\n","transformStream":"var s = transformStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","transformStream.factory":"var opts = { 'highWaterMark': 64 };\nvar createStream = transformStream.factory( opts );\nfunction fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\nvar s = createStream( fcn );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","transformStream.objectMode":"var s = transformStream.objectMode();\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","transformStream.ctor":"function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\nvar opts = { 'highWaterMark': 64, 'transform': fcn };\nvar customStream = transformStream.ctor( opts );\nvar s = customStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","trim":"var out = trim( ' \\t\\t\\n  Beep \\r\\n\\t  ' )\n","truncate":"var str = 'beep boop';\nvar out = truncate( str, 5 )\nout = truncate( str, 5, '|' )\n","truncateMiddle":"var str = 'beep boop';\nvar out = truncateMiddle( str, 5 )\nout = truncateMiddle( str, 5, '|' )\n","trycatch":"function x() {\n if ( base.random.randu() < 0.5 ) {\n     throw new Error( 'beep' );\n }\n return 1.0;\n };\nvar z = trycatch( x, -1.0 )\n","trycatchAsync":"function x( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n     clbk( new Error( 'beep' ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     // process error...\n }\n console.log( result );\n };\ntrycatchAsync( x, 'boop', done )\n","tryFunction":"function fcn() { throw new Error( 'beep boop' ); };\nvar f = tryFunction( fcn );\nvar out = f();\nout.message\n","tryRequire":"var out = tryRequire( '_unknown_module_id_' )\n","trythen":"function x() {\n if ( base.random.randu() < 0.5 ) {\n     throw new Error( 'beep' );\n }\n return 1.0;\n };\nfunction y() {\n return -1.0;\n };\nvar z = trythen( x, y )\n","trythenAsync":"function x( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n     clbk( new Error( 'beep' ) );\n }\n };\nfunction y( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n     clbk( null, 'boop' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\ntrythenAsync( x, y, done )\n","ttest":"var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 5776 } );\nvar x = new Array( 100 );\nfor ( var i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm();\n }\nvar out = ttest( x )\nrnorm = base.random.normal.factory( 1.0, 2.0, { 'seed': 786 } );\nx = new Array( 100 );\nvar y = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm();\n y[ i ] = rnorm();\n }\nout = ttest( x, y )\nvar table = out.print()\nvar arr = [ 2, 4, 3, 1, 0 ];\nout = ttest( arr, { 'alpha': 0.01 } );\ntable = out.print()\narr = [ 4, 4, 6, 6, 5 ];\nout = ttest( arr, { 'mu': 5 } )\narr = [ 4, 4, 6, 6, 5 ];\nout = ttest( arr, { 'alternative': 'less' } );\ntable = out.print()\nout = ttest( arr, { 'alternative': 'greater' } );\ntable = out.print()\n","ttest2":"var x = [ 0.7, -1.6, -0.2, -1.2, -0.1, 3.4, 3.7, 0.8, 0.0, 2.0 ];\nvar y = [ 1.9, 0.8, 1.1, 0.1, -0.1, 4.4, 5.5, 1.6, 4.6, 3.4 ];\nvar out = ttest2( x, y )\nvar table = out.print()\nout = ttest2( x, y, { 'alpha': 0.1 } );\ntable = out.print()\nout = ttest2( x, y, { 'alternative': 'less' } );\ntable = out.print()\nout = ttest2( x, y, { 'alternative': 'greater' } );\ntable = out.print()\nx = [ 2, 3, 1, 4 ];\ny = [ 1, 2, 3, 1, 2, 5, 3, 4 ];\nout = ttest2( x, y, { 'variance': 'equal' } );\ntable = out.print()\nvar rnorm = base.random.normal.factory({ 'seed': 372 } );\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm( 2.0, 3.0 );\n }\ny = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n y[ i ] = rnorm( 1.0, 3.0 );\n }\nout = ttest2( x, y, { 'difference': 1.0, 'variance': 'equal' } )\n","TWO_PI":"TWO_PI\n","typedarray":"var arr = typedarray()\narr = typedarray( 'float32' )\nvar arr = typedarray( 5 )\narr = typedarray( 5, 'int32' )\nvar arr1 = typedarray( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = typedarray( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = typedarray( arr1, 'float32' )\nvar buf = new ArrayBuffer( 16 );\nvar arr = typedarray( buf, 0, 4, 'float32' )\n","typedarray2json":"var arr = new Float64Array( 2 );\narr[ 0 ] = 5.0;\narr[ 1 ] = 3.0;\nvar json = typedarray2json( arr )\n","typedarrayCtors":"var ctor = typedarrayCtors( 'float64' )\nctor = typedarrayCtors( 'float' )\n","typedarrayDataTypes":"var out = typedarrayDataTypes()\n","typedarraypool":"var arr = typedarraypool()\narr = typedarraypool( 'float32' )\nvar arr = typedarraypool( 5 )\narr = typedarraypool( 5, 'int32' )\nvar arr1 = typedarraypool( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = typedarraypool( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = typedarraypool( arr1, 'float32' )\n","typedarraypool.malloc":"var arr = typedarraypool.malloc()\narr = typedarraypool.malloc( 'float32' )\nvar arr = typedarraypool.malloc( 5 )\narr = typedarraypool.malloc( 5, 'int32' )\nvar arr1 = typedarraypool.malloc( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = typedarraypool.malloc( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = typedarraypool.malloc( arr1, 'float32' )\n","typedarraypool.calloc":"var arr = typedarraypool.calloc()\narr = typedarraypool.calloc( 'float32' )\nvar arr = typedarraypool.calloc( 5 )\narr = typedarraypool.calloc( 5, 'int32' )\n","typedarraypool.free":"var arr = typedarraypool( 5 )\ntypedarraypool.free( arr );\n","typedarraypool.clear":"var arr = typedarraypool( 5 )\ntypedarraypool.free( arr );\ntypedarraypool.clear();\n","typedarraypool.highWaterMark":"typedarraypool.highWaterMark\n","typedarraypool.nbytes":"var arr = typedarraypool( 5 )\ntypedarraypool.nbytes\n","typedarraypool.factory":"var pool = typedarraypool.factory();\nvar arr1 = pool( 3, 'float64' )\n","typemax":"var m = typemax( 'int8' )\nm = typemax( 'uint32' )\n","typemin":"var m = typemin( 'int8' )\nm = typemin( 'uint32' )\n","typeOf":"var t = typeOf( 'a' )\nt = typeOf( 5 )\nt = typeOf( NaN )\nt = typeOf( true )\nt = typeOf( false )\nt = typeOf( null )\nt = typeOf( undefined )\nt = typeOf( [] )\nt = typeOf( {} )\nt = typeOf( function noop() {} )\nt = typeOf( Symbol( 'beep' ) )\nt = typeOf( /.+/ )\nt = typeOf( new String( 'beep' ) )\nt = typeOf( new Number( 5 ) )\nt = typeOf( new Boolean( false ) )\nt = typeOf( new Array() )\nt = typeOf( new Object() )\nt = typeOf( new Int8Array( 10 ) )\nt = typeOf( new Uint8Array( 10 ) )\nt = typeOf( new Uint8ClampedArray( 10 ) )\nt = typeOf( new Int16Array( 10 ) )\nt = typeOf( new Uint16Array( 10 ) )\nt = typeOf( new Int32Array( 10 ) )\nt = typeOf( new Uint32Array( 10 ) )\nt = typeOf( new Float32Array( 10 ) )\nt = typeOf( new Float64Array( 10 ) )\nt = typeOf( new ArrayBuffer( 10 ) )\nt = typeOf( new Date() )\nt = typeOf( new RegExp( '.+' ) )\nt = typeOf( new Map() )\nt = typeOf( new Set() )\nt = typeOf( new WeakMap() )\nt = typeOf( new WeakSet() )\nt = typeOf( new Error( 'beep' ) )\nt = typeOf( new TypeError( 'beep' ) )\nt = typeOf( new SyntaxError( 'beep' ) )\nt = typeOf( new ReferenceError( 'beep' ) )\nt = typeOf( new URIError( 'beep' ) )\nt = typeOf( new RangeError( 'beep' ) )\nt = typeOf( new EvalError( 'beep' ) )\nt = typeOf( Math )\nt = typeOf( JSON )\nfunction beep() { return arguments; };\nt = typeOf( beep() )\nt = typeOf( new Buffer( 10 ) )\nfunction Person() { return this };\nt = typeOf( new Person() )\nvar Foo = function () { return this; };\nt = typeOf( new Foo() )\n","UINT8_MAX":"UINT8_MAX\n","UINT8_NUM_BYTES":"UINT8_NUM_BYTES\n","Uint8Array":"var arr = new Uint8Array()\nvar arr = new Uint8Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint8Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint8Array( arr1 )\nvar buf = new ArrayBuffer( 4 );\nvar arr = new Uint8Array( buf, 0, 4 )\n","Uint8Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint8Array.from( [ 1, 2 ], mapFcn )\n","Uint8Array.of":"var arr = Uint8Array.of( 1, 2 )\n","Uint8Array.BYTES_PER_ELEMENT":"Uint8Array.BYTES_PER_ELEMENT\n","Uint8Array.name":"Uint8Array.name\n","Uint8Array.prototype.buffer":"var arr = new Uint8Array( 5 );\narr.buffer\n","Uint8Array.prototype.byteLength":"var arr = new Uint8Array( 5 );\narr.byteLength\n","Uint8Array.prototype.byteOffset":"var arr = new Uint8Array( 5 );\narr.byteOffset\n","Uint8Array.prototype.BYTES_PER_ELEMENT":"var arr = new Uint8Array( 5 );\narr.BYTES_PER_ELEMENT\n","Uint8Array.prototype.length":"var arr = new Uint8Array( 5 );\narr.length\n","Uint8Array.prototype.copyWithin":"var arr = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint8Array.prototype.entries":"var arr = new Uint8Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint8Array.prototype.every":"var arr = new Uint8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint8Array.prototype.fill":"var arr = new Uint8Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint8Array.prototype.filter":"var arr1 = new Uint8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint8Array.prototype.find":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint8Array.prototype.findIndex":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint8Array.prototype.forEach":"var arr = new Uint8Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint8Array.prototype.includes":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint8Array.prototype.indexOf":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint8Array.prototype.join":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint8Array.prototype.keys":"var arr = new Uint8Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint8Array.prototype.lastIndexOf":"var arr = new Uint8Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint8Array.prototype.map":"var arr1 = new Uint8Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Uint8Array.prototype.reduce":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint8Array.prototype.reduceRight":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint8Array.prototype.reverse":"var arr = new Uint8Array( [ 1, 2, 3 ] )\narr.reverse()\n","Uint8Array.prototype.set":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint8Array.prototype.slice":"var arr1 = new Uint8Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint8Array.prototype.some":"var arr = new Uint8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint8Array.prototype.sort":"var arr = new Uint8Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint8Array.prototype.subarray":"var arr1 = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint8Array.prototype.toLocaleString":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint8Array.prototype.toString":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.toString()\n","Uint8Array.prototype.values":"var arr = new Uint8Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","Uint8ClampedArray":"var arr = new Uint8ClampedArray()\nvar arr = new Uint8ClampedArray( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint8ClampedArray( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint8ClampedArray( arr1 )\nvar buf = new ArrayBuffer( 4 );\nvar arr = new Uint8ClampedArray( buf, 0, 4 )\n","Uint8ClampedArray.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint8ClampedArray.from( [ 1, 2 ], mapFcn )\n","Uint8ClampedArray.of":"var arr = Uint8ClampedArray.of( 1, 2 )\n","Uint8ClampedArray.BYTES_PER_ELEMENT":"Uint8ClampedArray.BYTES_PER_ELEMENT\n","Uint8ClampedArray.name":"Uint8ClampedArray.name\n","Uint8ClampedArray.prototype.buffer":"var arr = new Uint8ClampedArray( 5 );\narr.buffer\n","Uint8ClampedArray.prototype.byteLength":"var arr = new Uint8ClampedArray( 5 );\narr.byteLength\n","Uint8ClampedArray.prototype.byteOffset":"var arr = new Uint8ClampedArray( 5 );\narr.byteOffset\n","Uint8ClampedArray.prototype.BYTES_PER_ELEMENT":"var arr = new Uint8ClampedArray( 5 );\narr.BYTES_PER_ELEMENT\n","Uint8ClampedArray.prototype.length":"var arr = new Uint8ClampedArray( 5 );\narr.length\n","Uint8ClampedArray.prototype.copyWithin":"var arr = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint8ClampedArray.prototype.entries":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint8ClampedArray.prototype.every":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint8ClampedArray.prototype.fill":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint8ClampedArray.prototype.filter":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint8ClampedArray.prototype.find":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint8ClampedArray.prototype.findIndex":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint8ClampedArray.prototype.forEach":"var arr = new Uint8ClampedArray( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint8ClampedArray.prototype.includes":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint8ClampedArray.prototype.indexOf":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint8ClampedArray.prototype.join":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint8ClampedArray.prototype.keys":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint8ClampedArray.prototype.lastIndexOf":"var arr = new Uint8ClampedArray( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint8ClampedArray.prototype.map":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Uint8ClampedArray.prototype.reduce":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint8ClampedArray.prototype.reduceRight":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint8ClampedArray.prototype.reverse":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] )\narr.reverse()\n","Uint8ClampedArray.prototype.set":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint8ClampedArray.prototype.slice":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint8ClampedArray.prototype.some":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint8ClampedArray.prototype.sort":"var arr = new Uint8ClampedArray( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint8ClampedArray.prototype.subarray":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint8ClampedArray.prototype.toLocaleString":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint8ClampedArray.prototype.toString":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.toString()\n","Uint8ClampedArray.prototype.values":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","UINT16_MAX":"UINT16_MAX\n","UINT16_NUM_BYTES":"UINT16_NUM_BYTES\n","Uint16Array":"var arr = new Uint16Array()\nvar arr = new Uint16Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint16Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint16Array( arr1 )\nvar buf = new ArrayBuffer( 8 );\nvar arr = new Uint16Array( buf, 0, 4 )\n","Uint16Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint16Array.from( [ 1, 2 ], mapFcn )\n","Uint16Array.of":"var arr = Uint16Array.of( 1, 2 )\n","Uint16Array.BYTES_PER_ELEMENT":"Uint16Array.BYTES_PER_ELEMENT\n","Uint16Array.name":"Uint16Array.name\n","Uint16Array.prototype.buffer":"var arr = new Uint16Array( 5 );\narr.buffer\n","Uint16Array.prototype.byteLength":"var arr = new Uint16Array( 5 );\narr.byteLength\n","Uint16Array.prototype.byteOffset":"var arr = new Uint16Array( 5 );\narr.byteOffset\n","Uint16Array.prototype.BYTES_PER_ELEMENT":"var arr = new Uint16Array( 5 );\narr.BYTES_PER_ELEMENT\n","Uint16Array.prototype.length":"var arr = new Uint16Array( 5 );\narr.length\n","Uint16Array.prototype.copyWithin":"var arr = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint16Array.prototype.entries":"var arr = new Uint16Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint16Array.prototype.every":"var arr = new Uint16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint16Array.prototype.fill":"var arr = new Uint16Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint16Array.prototype.filter":"var arr1 = new Uint16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint16Array.prototype.find":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint16Array.prototype.findIndex":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint16Array.prototype.forEach":"var arr = new Uint16Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint16Array.prototype.includes":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint16Array.prototype.indexOf":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint16Array.prototype.join":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint16Array.prototype.keys":"var arr = new Uint16Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint16Array.prototype.lastIndexOf":"var arr = new Uint16Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint16Array.prototype.map":"var arr1 = new Uint16Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Uint16Array.prototype.reduce":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint16Array.prototype.reduceRight":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint16Array.prototype.reverse":"var arr = new Uint16Array( [ 1, 2, 3 ] )\narr.reverse()\n","Uint16Array.prototype.set":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint16Array.prototype.slice":"var arr1 = new Uint16Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint16Array.prototype.some":"var arr = new Uint16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint16Array.prototype.sort":"var arr = new Uint16Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint16Array.prototype.subarray":"var arr1 = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint16Array.prototype.toLocaleString":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint16Array.prototype.toString":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.toString()\n","Uint16Array.prototype.values":"var arr = new Uint16Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","UINT32_MAX":"UINT32_MAX\n","UINT32_NUM_BYTES":"UINT32_NUM_BYTES\n","Uint32Array":"var arr = new Uint32Array()\nvar arr = new Uint32Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint32Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint32Array( arr1 )\nvar buf = new ArrayBuffer( 16 );\nvar arr = new Uint32Array( buf, 0, 4 )\n","Uint32Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint32Array.from( [ 1, 2 ], mapFcn )\n","Uint32Array.of":"var arr = Uint32Array.of( 1, 2 )\n","Uint32Array.BYTES_PER_ELEMENT":"Uint32Array.BYTES_PER_ELEMENT\n","Uint32Array.name":"Uint32Array.name\n","Uint32Array.prototype.buffer":"var arr = new Uint32Array( 5 );\narr.buffer\n","Uint32Array.prototype.byteLength":"var arr = new Uint32Array( 5 );\narr.byteLength\n","Uint32Array.prototype.byteOffset":"var arr = new Uint32Array( 5 );\narr.byteOffset\n","Uint32Array.prototype.BYTES_PER_ELEMENT":"var arr = new Uint32Array( 5 );\narr.BYTES_PER_ELEMENT\n","Uint32Array.prototype.length":"var arr = new Uint32Array( 5 );\narr.length\n","Uint32Array.prototype.copyWithin":"var arr = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint32Array.prototype.entries":"var arr = new Uint32Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint32Array.prototype.every":"var arr = new Uint32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint32Array.prototype.fill":"var arr = new Uint32Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint32Array.prototype.filter":"var arr1 = new Uint32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint32Array.prototype.find":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint32Array.prototype.findIndex":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint32Array.prototype.forEach":"var arr = new Uint32Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint32Array.prototype.includes":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint32Array.prototype.indexOf":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint32Array.prototype.join":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint32Array.prototype.keys":"var arr = new Uint32Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint32Array.prototype.lastIndexOf":"var arr = new Uint32Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint32Array.prototype.map":"var arr1 = new Uint32Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Uint32Array.prototype.reduce":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint32Array.prototype.reduceRight":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint32Array.prototype.reverse":"var arr = new Uint32Array( [ 1, 2, 3 ] )\narr.reverse()\n","Uint32Array.prototype.set":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint32Array.prototype.slice":"var arr1 = new Uint32Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint32Array.prototype.some":"var arr = new Uint32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint32Array.prototype.sort":"var arr = new Uint32Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint32Array.prototype.subarray":"var arr1 = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint32Array.prototype.toLocaleString":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint32Array.prototype.toString":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.toString()\n","Uint32Array.prototype.values":"var arr = new Uint32Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","umask":"var mask = umask()\nmask = umask( { 'symbolic': true } )\n","uncapitalize":"var out = uncapitalize( 'Beep' )\nout = uncapitalize( 'bOOp' )\n","uncapitalizeKeys":"var obj = { 'AA': 1, 'BB': 2 };\nvar out = uncapitalizeKeys( obj )\n","uncurry":"function addX( x ) {\n return function addY( y ) {\n     return x + y;\n };\n };\nvar fcn = uncurry( addX );\nvar sum = fcn( 2, 3 )\nfunction add( x ) {\n return function add( y ) {\n     return x + y;\n };\n };\nfcn = uncurry( add, 2 );\nsum = fcn( 9 )\nfunction addX( x ) {\n this.x = x;\n return addY;\n };\nfunction addY( y ) {\n return this.x + y;\n };\nfcn = uncurry( addX, {} );\nsum = fcn( 2, 3 )\n","uncurryRight":"function addX( x ) {\n return function addY( y ) {\n     return x + y;\n };\n };\nvar fcn = uncurryRight( addX );\nvar sum = fcn( 3, 2 )\nfunction add( y ) {\n return function add( x ) {\n     return x + y;\n };\n };\nfcn = uncurryRight( add, 2 );\nsum = fcn( 9 )\nfunction addY( y ) {\n this.y = y;\n return addX;\n };\nfunction addX( x ) {\n return x + this.y;\n };\nfcn = uncurryRight( addY, {} );\nsum = fcn( 3, 2 )\n","UNICODE_MAX":"UNICODE_MAX\n","UNICODE_MAX_BMP":"UNICODE_MAX_BMP\n","UnicodeColumnChartSparkline":"var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\nvar chart = new UnicodeColumnChartSparkline( data );\nchart.render()\n","UnicodeLineChartSparkline":"var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\nvar chart = new UnicodeLineChartSparkline( data );\nchart.render()\n","UnicodeSparkline":"var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\nvar chart = new UnicodeSparkline( data );\nchart.render()\nchart.type = 'line';\nchart.render()\n","UnicodeTristateChartSparkline":"var data = [ -1, 1, 0, 0, 1, -1, -1, 1 ];\nvar chart = new UnicodeTristateChartSparkline( data );\nchart.render()\n","UnicodeUpDownChartSparkline":"var data = [ -1, 1, 1, 1, 1, -1, -1, 1 ];\nvar chart = new UnicodeUpDownChartSparkline( data );\nchart.render()\n","UnicodeWinLossChartSparkline":"var data = [ -2, 1, 2, 2, 1, -1, -1, 1 ];\nvar chart = new UnicodeWinLossChartSparkline( data );\nchart.render()\n","unlink":"function done( error ) {\n if ( error ) {\n     console.error( error.message );\n }\n };\nunlink( './beep/boop.txt', done );\n","unlink.sync":"var out = unlink.sync( './beep/boop.txt' );\n","unshift":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = unshift( arr, 6.0, 7.0 )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = unshift( arr, 3.0, 4.0 )\narr = { 'length': 1, '0': 1.0 };\narr = unshift( arr, 2.0, 3.0 )\n","until":"function predicate( i ) { return ( i >= 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\nuntil( predicate, beep )\n","untilAsync":"function predicate( i, clbk ) { clbk( null, i >= 5 ); };\nfunction fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n     next( null, 'boop'+i );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nuntilAsync( predicate, fcn, done )\n","untilEach":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\nuntilEach( arr, predicate, logger )\n","untilEachRight":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\nuntilEachRight( arr, predicate, logger )\n","unzip":"var arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\nvar out = unzip( arr )\narr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\nout = unzip( arr, [ 0, 2 ] )\n","uppercase":"var out = uppercase( 'bEEp' )\n","uppercaseKeys":"var obj = { 'a': 1, 'b': 2 };\nvar out = uppercaseKeys( obj )\n","US_STATES_ABBR":"var list = US_STATES_ABBR()\n","US_STATES_CAPITALS":"var list = US_STATES_CAPITALS()\n","US_STATES_CAPITALS_NAMES":"var out = US_STATES_CAPITALS_NAMES()\n","US_STATES_NAMES":"var list = US_STATES_NAMES()\n","US_STATES_NAMES_CAPITALS":"var out = US_STATES_NAMES_CAPITALS()\n","utf16ToUTF8Array":"var str = '☃';\nvar out = utf16ToUTF8Array( str )\n","vartest":"var x = [ 610, 610, 550, 590, 565, 570 ];\nvar y = [ 560, 550, 580, 550, 560, 590, 550, 590 ];\nvar out = vartest( x, y )\nvar table = out.print()\n","waterfall":"function foo( next ) { next( null, 'beep' ); };\nfunction bar( str, next ) { console.log( str ); next(); };\nfunction done( error ) { if ( error ) { throw error; } };\nvar fcns = [ foo, bar ];\nwaterfall( fcns, done );\n","waterfall.factory":"function foo( next ) { next( null, 'beep' ); };\nfunction bar( str, next ) { console.log( str ); next(); };\nfunction done( error ) { if ( error ) { throw error; } };\nvar fcns = [ foo, bar ];\nvar waterfall = waterfall.factory( fcns, done );\nwaterfall();\nwaterfall();\nwaterfall();\n","WebAssemblyMemory":"var mem = new WebAssemblyMemory( { 'initial': 0 } )\n","WebAssemblyMemory.prototype.buffer":"var mem = new WebAssemblyMemory( { 'initial': 0 } );\nmem.buffer\n","WebAssemblyMemory.prototype.grow":"var mem = new WebAssemblyMemory( { 'initial': 0 } );\nmem.grow( 1 )\n","whileAsync":"function predicate( i, clbk ) { clbk( null, i < 5 ); };\nfunction fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n     next( null, 'boop'+i );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nwhileAsync( predicate, fcn, done )\n","whileEach":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\nwhileEach( arr, predicate, logger )\n","whileEachRight":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\nwhileEachRight( arr, predicate, logger )\n","whilst":"function predicate( i ) { return ( i < 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\nwhilst( predicate, beep )\n","wilcoxon":"var arr = [ 6, 8, 14, 16, 23, 24, 28, 29, 41, -48, 49, 56, 60, -67, 75 ];\nvar out = wilcoxon( x )\nrunif = base.random.discreteUniform.factory( 1, 5, { 'seed': 786 });\nvar x = new Array( 100 );\nvar y = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = runif();\n y[ i ] = runif();\n }\nout = wilcoxon( x, y )\nvar table = out.print()\nout = wilcoxon( arr, { 'alpha': 0.01 });\ntable = out.print()\nout = wilcoxon( arr, { 'mu': 10 })\nout = wilcoxon( arr, { 'alternative': 'less' });\ntable = out.print()\nout = wilcoxon( arr, { 'alternative': 'greater' });\ntable = out.print()\n","writableProperties":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar props = writableProperties( obj )\n","writablePropertiesIn":"var props = writablePropertiesIn( [] )\n","writablePropertyNames":"var obj = { 'a': 'b' };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = writablePropertyNames( obj )\n","writablePropertyNamesIn":"var obj = { 'a': 'b' };\nvar desc = {};\ndesc.configurable = true;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = writablePropertyNamesIn( obj )\n","writablePropertySymbols":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = writablePropertySymbols( obj )\n","writablePropertySymbolsIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = writablePropertySymbolsIn( obj )\n","writeFile":"function onWrite( error ) {\n if ( error ) {\n     console.error( error.message );\n }\n };\nwriteFile( './beep/boop.txt', 'beep boop', onWrite );\n","writeFile.sync":"var err = writeFile.sync( './beep/boop.txt', 'beep boop' );\n","zip":"var out = zip( [ 1, 2 ], [ 'a', 'b' ] )\nvar opts = { 'trunc': false };\nout = zip( [ 1, 2, 3 ], [ 'a', 'b' ], opts )\n","ztest":"var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 212 } );\nvar x = new Array( 100 );\nfor ( var i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm();\n }\nvar out = ztest( x, 2.0 )\narr = [ 2, 4, 3, 1, 0 ];\nout = ztest( arr, 2.0, { 'alpha': 0.01 } );\ntable = out.print()\nvar arr = [ 4, 4, 6, 6, 5 ];\nout = ztest( arr, 1.0, { 'mu': 5 } )\narr = [ 4, 4, 6, 6, 5 ];\nout = ztest( arr, 1.0, { 'alternative': 'less' } )\nout = ztest( arr, 1.0, { 'alternative': 'greater' } )\n","ztest2":"var x = [ -0.21, 0.14, 1.65, 2.11, -1.86, -0.29, 1.48, 0.81, 0.86, 1.04 ];\nvar y = [ -1.53, -2.93, 2.34, -1.15, 2.7, -0.12, 4.22, 1.66, 3.43, 4.66 ];\nvar out = ztest2( x, y, 2.0, 2.0 )\nvar table = out.print()\nout = ztest2( x, y, 2.0, 2.0, { 'alpha': 0.4 } );\ntable = out.print()\nout = ztest2( x, y, 2.0, 2.0, { 'alternative': 'less' } );\ntable = out.print()\nout = ztest2( x, y, 2.0, 2.0, { 'alternative': 'greater' } );\ntable = out.print()\nvar rnorm = base.random.normal.factory({ 'seed': 372 } );\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm( 2.0, 1.0 );\n }\ny = new Array( 100 );\n for ( i = 0; i < x.length; i++ ) {\n y[ i ] = rnorm( 0.0, 2.0 );\n }\nout = ztest2( x, y, 1.0, 2.0, { 'difference': 2.0 } )\n"}
+{"abs":"var y = abs( -1.0 )\nvar x = new Float64Array( [ -1.0, -2.0 ] );\ny = abs( x )\nx = [ -1.0, -2.0 ];\ny = abs( x )\nx = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] );\ny = abs( x )\ny.get( 0, 1 )\n","abs.assign":"var x = new Float64Array( [ -1.0, -2.0 ] );\nvar y = new Float64Array( x.length );\nvar out = abs.assign( x, y )\nvar bool = ( out === y )\nx = [ -1.0, -2.0 ];\ny = [ 0.0, 0.0 ];\nout = abs.assign( x, y )\nbool = ( out === y )\nx = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] );\ny = array( [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ] );\nout = abs.assign( x, y )\nout.get( 0, 1 )\nbool = ( out === y )\n","acartesianPower":"var x = [ 1, 2 ];\nvar out = acartesianPower( x, 2 )\n","acartesianProduct":"var x1 = [ 1, 2 ];\nvar x2 = [ 3, 4 ];\nvar out = acartesianProduct( x1, x2 )\n","acartesianSquare":"var out = acartesianSquare( [ 1, 2 ] )\n","acronym":"var out = acronym( 'the quick brown fox' )\nout = acronym( 'Hard-boiled eggs' )\n","aempty":"var arr = aempty( 2 )\narr = aempty( 2, 'float32' )\n","aemptyLike":"var x = new Float64Array( 2 );\nvar arr = aemptyLike( x )\narr = aemptyLike( x, 'float32' )\n","AFINN_96":"var list = AFINN_96()\n","AFINN_111":"var list = AFINN_111()\n","afull":"var arr = afull( 2, 1.0 )\narr = afull( 2, 1.0, 'float32' )\n","afullLike":"var x = new Float64Array( 2 );\nvar y = afullLike( x, 1.0 )\ny = afullLike( x, 1.0, 'float32' )\n","alias2pkg":"var v = alias2pkg( 'base.sin' )\n","alias2related":"var v = alias2related( 'base.sin' )\n","alias2standalone":"var v = alias2standalone( 'base.sin' )\n","aliases":"var o = aliases()\no = aliases( '@stdlib/math/base/special' )\n","allocUnsafe":"var buf = allocUnsafe( 100 )\n","amskfilter":"var x = [ 1, 2, 3, 4 ];\nvar y = amskfilter( x, [ 0, 1, 0, 1 ] )\n","amskput":"var x = [ 1, 2, 3, 4 ];\nvar out = amskput( x, [ 1, 0, 1, 0 ], [ 20, 40 ] )\nvar bool = ( out === x )\n","amskreject":"var x = [ 1, 2, 3, 4 ];\nvar y = amskreject( x, [ 0, 1, 0, 1 ] )\n","anans":"var arr = anans( 2 )\narr = anans( 2, 'float32' )\n","anansLike":"var x = new Float64Array( 2 );\nvar y = anansLike( x )\ny = anansLike( x, 'float32' )\n","anova1":"var x = [1, 3, 5, 2, 4, 6, 8, 7, 10, 11, 12, 15];\nvar f = [\n 'control', 'treatA', 'treatB', 'treatC', 'control',\n 'treatA', 'treatB', 'treatC', 'control', 'treatA', 'treatB', 'treatC'\n ];\nvar out = anova1( x, f )\n","ANSCOMBES_QUARTET":"var d = ANSCOMBES_QUARTET()\n","any":"var arr = [ 0, 0, 0, 0, 1 ];\nvar bool = any( arr )\n","anyBy":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ 1, 2, 3, 4, -1 ];\nvar bool = anyBy( arr, negative )\n","anyByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nanyByAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nanyByAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nanyByAsync( arr, opts, predicate, done )\n","anyByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = anyByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","anyByRight":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ -1, 1, 2, 3, 4 ];\nvar bool = anyByRight( arr, negative )\n","anyByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nanyByRightAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nanyByRightAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nanyByRightAsync( arr, opts, predicate, done )\n","anyByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = anyByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","anyInBy":"function isNegative(value) { return value < 0 }\nvar obj = { a: 1, b: -2, c: 3, d: 4 }\nvar result = anyInBy(obj, isNegative)\n","anyOwnBy":"function positive( v ) { return ( v > 0 ); };\nvar obj = { 'a': -1, 'b': 2, 'c': -3 };\nvar bool = anyOwnBy( obj, positive )\n","aones":"var arr = aones( 2 )\narr = aones( 2, 'float32' )\n","aonesLike":"var x = new Float64Array( 2 );\nvar y = aonesLike( x )\ny = aonesLike( x, 'float32' )\n","aoneTo":"var arr = aoneTo( 2 )\narr = aoneTo( 2, 'float32' )\n","aoneToLike":"var arr = aoneToLike( [ 0, 0 ] )\narr = aoneToLike( [ 0, 0 ], 'float32' )\n","APERY":"APERY\n","aplace":"var x = [ 1, 2, 3, 4 ];\nvar out = aplace( x, [ 0, 1, 0, 1 ], [ 20, 40 ] )\nvar bool = ( out === x )\n","append":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = append( arr, [ 6.0, 7.0 ] )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = append( arr, [ 3.0, 4.0 ] )\narr = { 'length': 0 };\narr = append( arr, [ 1.0, 2.0 ] )\n","aput":"var x = [ 1, 2, 3, 4 ];\nvar out = aput( x, [ 1, 3 ], [ 20, 40 ] )\nvar bool = ( out === x )\n","ARCH":"ARCH\n","argumentFunction":"var argn = argumentFunction( 1 );\nvar v = argn( 3.14, -3.14, 0.0 )\nv = argn( -1.0, -0.0, 1.0 )\nv = argn( 'beep', 'boop', 'bop' )\nv = argn( 'beep' )\n","ARGV":"var execPath = ARGV[ 0 ]\n","array":"var arr = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","array2buffer":"var buf = array2buffer( [ 1, 2, 3, 4 ] )\n","array2fancy":"var y = array2fancy( [ 1, 2, 3, 4 ] );\ny[ '1::2' ]\ny[ '::-1' ]\n","array2fancy.factory":"var f = array2fancy.factory();\nvar y = f( [ 1, 2, 3, 4 ] );\ny[ '1::2' ]\ny[ '::-1' ]\n","array2fancy.idx":"var idx = array2fancy.idx( [ 1, 2, 3, 4 ] );\n","array2iterator":"var it = array2iterator( [ 1, 2, 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","array2iteratorRight":"var it = array2iteratorRight( [ 1, 2, 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","ArrayBuffer":"var buf = new ArrayBuffer( 5 )\n","ArrayBuffer.length":"ArrayBuffer.length\n","ArrayBuffer.isView":"var arr = new Float64Array( 10 );\nArrayBuffer.isView( arr )\n","ArrayBuffer.prototype.byteLength":"var buf = new ArrayBuffer( 5 );\nbuf.byteLength\n","ArrayBuffer.prototype.slice":"var b1 = new ArrayBuffer( 10 );\nvar b2 = b1.slice( 2, 6 );\nvar bool = ( b1 === b2 )\nb2.byteLength\n","arraybuffer2buffer":"var ab = new ArrayBuffer( 10 )\nvar buf = arraybuffer2buffer( ab )\nvar len = buf.length\nbuf = arraybuffer2buffer( ab, 2, 6 )\nlen = buf.length\n","arrayCtors":"var ctor = arrayCtors( 'float64' )\nctor = arrayCtors( 'float' )\n","arrayDataType":"var arr = new Float64Array( 10 );\nvar dt = arrayDataType( arr )\ndt = arrayDataType( 'beep' )\n","arrayDataTypes":"var out = arrayDataTypes()\nout = arrayDataTypes( 'floating_point' )\nout = arrayDataTypes( 'floating_point_and_generic' )\n","ArrayIndex":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n","ArrayIndex.free":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nArrayIndex.free( idx.id )\n","ArrayIndex.get":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nArrayIndex.get( idx.id )\n","ArrayIndex.prototype.data":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.data\n","ArrayIndex.prototype.dtype":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.dtype\n","ArrayIndex.prototype.id":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.id\n","ArrayIndex.prototype.isCached":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.isCached\n","ArrayIndex.prototype.type":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.type\n","ArrayIndex.prototype.toString":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.toString()\n","ArrayIndex.prototype.toJSON":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.toJSON()\n","arrayMinDataType":"var dt = arrayMinDataType( 3.141592653589793 )\ndt = arrayMinDataType( 3 )\ndt = arrayMinDataType( -3 )\ndt = arrayMinDataType( '-3' )\n","arrayMostlySafeCasts":"var out = arrayMostlySafeCasts( 'float32' )\n","arrayNextDataType":"var out = arrayNextDataType( 'float32' )\n","arrayPromotionRules":"var out = arrayPromotionRules( 'float32', 'int32' )\n","arraySafeCasts":"var out = arraySafeCasts( 'float32' )\n","arraySameKindCasts":"var out = arraySameKindCasts( 'float32' )\n","arrayShape":"var out = arrayShape( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n","arrayStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar s = arrayStream( [ 1, 2, 3 ] );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","arrayStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = arrayStream.factory( opts );\n","arrayStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar s = arrayStream.objectMode( [ 1, 2, 3 ] );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","arrayview2iterator":"var it = arrayview2iterator( [ 1, 2, 3, 4 ], 1, 3 );\nvar v = it.next().value\nv = it.next().value\n","arrayview2iteratorRight":"var it = arrayview2iteratorRight( [ 1, 2, 3, 4 ], 1, 3 );\nvar v = it.next().value\nv = it.next().value\n","aslice":"var out = aslice( [ 1, 2, 3, 4 ] )\nout = aslice( [ 1, 2, 3, 4 ], 1 )\nout = aslice( [ 1, 2, 3, 4 ], 1, 3 )\n","AsyncIteratorSymbol":"var s = AsyncIteratorSymbol\n","atake":"var x = [ 1, 2, 3, 4 ];\nvar y = atake( x, [ 1, 3 ] )\n","azeros":"var arr = azeros( 2 )\narr = azeros( 2, 'float32' )\n","azerosLike":"var x = new Float64Array( 2 );\nvar y = azerosLike( x )\ny = azerosLike( x, 'float32' )\n","azeroTo":"var arr = azeroTo( 2 )\narr = azeroTo( 2, 'float32' )\n","azeroToLike":"var arr = azeroToLike( [ 0, 0 ] )\narr = azeroToLike( [ 0, 0 ], 'float32' )\n","bartlettTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = bartlettTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = bartlettTest( arr, { 'groups': groups } )\n","base.abs":"var y = base.abs( -1.0 )\ny = base.abs( 2.0 )\ny = base.abs( 0.0 )\ny = base.abs( -0.0 )\ny = base.abs( NaN )\n","base.abs2":"var y = base.abs2( -1.0 )\ny = base.abs2( 2.0 )\ny = base.abs2( 0.0 )\ny = base.abs2( -0.0 )\ny = base.abs2( NaN )\n","base.abs2f":"var y = base.abs2f( -1.0 )\ny = base.abs2f( 2.0 )\ny = base.abs2f( 0.0 )\ny = base.abs2f( -0.0 )\ny = base.abs2f( NaN )\n","base.absdiff":"var d = base.absdiff( 2.0, 5.0 )\nd = base.absdiff( -1.0, 3.14 )\nd = base.absdiff( 10.1, -2.05 )\nd = base.absdiff( -0.0, 0.0 )\nd = base.absdiff( NaN, 5.0 )\nd = base.absdiff( PINF, NINF )\nd = base.absdiff( PINF, PINF )\n","base.absf":"var y = base.absf( -1.0 )\ny = base.absf( 2.0 )\ny = base.absf( 0.0 )\ny = base.absf( -0.0 )\ny = base.absf( NaN )\n","base.acartesianPower":"var x = [ 1, 2 ];\nvar out = base.acartesianPower( x, 2 )\n","base.acartesianProduct":"var x1 = [ 1, 2 ];\nvar x2 = [ 3, 4 ];\nvar out = base.acartesianProduct( x1, x2 )\n","base.acartesianSquare":"var x = [ 1, 2 ];\nvar out = base.acartesianSquare( x )\n","base.acos":"var y = base.acos( 1.0 )\ny = base.acos( 0.707 )\ny = base.acos( NaN )\n","base.acosd":"var y = base.acosd( 0.0 )\ny = base.acosd( PI/6.0 )\ny = base.acosd( NaN )\n","base.acosf":"var y = base.acosf( 1.0 )\ny = base.acosf( 0.707 )\ny = base.acosf( NaN )\n","base.acosh":"var y = base.acosh( 1.0 )\ny = base.acosh( 2.0 )\ny = base.acosh( NaN )\n","base.acot":"var y = base.acot( 2.0 )\ny = base.acot( 0.0 )\ny = base.acot( 0.5 )\ny = base.acot( 1.0 )\ny = base.acot( NaN )\n","base.acotd":"var y = base.acotd( 0.0 )\ny = base.acotd( PI/6.0 )\ny = base.acotd( NaN )\n","base.acotf":"var y = base.acotf( 2.0 )\ny = base.acotf( 0.0 )\ny = base.acotf( 0.5 )\ny = base.acotf( 1.0 )\ny = base.acotf( NaN )\n","base.acoth":"var y = base.acoth( 2.0 )\ny = base.acoth( 0.0 )\ny = base.acoth( 0.5 )\ny = base.acoth( 1.0 )\ny = base.acoth( NaN )\n","base.acovercos":"var y = base.acovercos( -1.5 )\ny = base.acovercos( -0.0 )\n","base.acoversin":"var y = base.acoversin( 1.5 )\ny = base.acoversin( 0.0 )\n","base.acsc":"var y = base.acsc( 1.0 )\ny = base.acsc( PI )\ny = base.acsc( -PI )\ny = base.acsc( NaN )\n","base.acscd":"var y = base.acscd( 0.0 )\ny = base.acscd( PI/6.0 )\ny = base.acscd( 1 )\ny = base.acscd( NaN )\n","base.acscdf":"var y = base.acscdf( 0.0 )\ny = base.acscdf( 3.1415927410125732 / 6.0 )\ny = base.acscdf( 1.0 )\ny = base.acscdf( NaN )\n","base.acscf":"var y = base.acscf( 1.0 )\ny = base.acscf( 3.141592653589793 )\ny = base.acscf( -3.141592653589793 )\ny = base.acscf( NaN )\n","base.acsch":"var y = base.acsch( 0.0 )\ny = base.acsch( -1.0 )\ny = base.acsch( NaN )\n","base.add":"var v = base.add( -1.0, 5.0 )\nv = base.add( 2.0, 5.0 )\nv = base.add( 0.0, 5.0 )\nv = base.add( -0.0, 0.0 )\nv = base.add( NaN, NaN )\n","base.add3":"var v = base.add3( -1.0, 5.0, 2.0 )\nv = base.add3( 2.0, 5.0, 2.0 )\nv = base.add3( 0.0, 5.0, 2.0 )\nv = base.add3( -0.0, 0.0, -0.0 )\nv = base.add3( NaN, NaN, NaN )\n","base.add4":"var v = base.add4( -1.0, 5.0, 2.0, -3.0 )\nv = base.add4( 2.0, 5.0, 2.0, -3.0 )\nv = base.add4( 0.0, 5.0, 2.0, -3.0 )\nv = base.add4( -0.0, 0.0, -0.0, -0.0 )\nv = base.add4( NaN, NaN, NaN, NaN )\n","base.add5":"var v = base.add5( -1.0, 5.0, 2.0, -3.0, 4.0 )\nv = base.add5( 2.0, 5.0, 2.0, -3.0, 4.0 )\nv = base.add5( 0.0, 5.0, 2.0, -3.0, 4.0 )\nv = base.add5( -0.0, 0.0, -0.0, -0.0, -0.0 )\nv = base.add5( NaN, NaN, NaN, NaN, NaN )\n","base.addf":"var v = base.addf( -1.0, 5.0 )\nv = base.addf( 2.0, 5.0 )\nv = base.addf( 0.0, 5.0 )\nv = base.addf( -0.0, 0.0 )\nv = base.addf( NaN, NaN )\n","base.afilled":"var out = base.afilled( 0.0, 3 )\n","base.afilled2d":"var out = base.afilled2d( 0.0, [ 1, 3 ] )\n","base.afilled2dBy":"function clbk() { return 1.0; };\nvar out = base.afilled2dBy( [ 1, 3 ], clbk )\n","base.afilled3d":"var out = base.afilled3d( 0.0, [ 1, 1, 3 ] )\n","base.afilled3dBy":"function clbk() { return 1.0; };\nvar out = base.afilled3dBy( [ 1, 1, 3 ], clbk )\n","base.afilled4d":"var out = base.afilled4d( 0.0, [ 1, 1, 1, 3 ] )\n","base.afilled4dBy":"function clbk() { return 1.0; };\nvar out = base.afilled4dBy( [ 1, 1, 1, 3 ], clbk )\n","base.afilled5d":"var out = base.afilled5d( 0.0, [ 1, 1, 1, 1, 3 ] )\n","base.afilled5dBy":"function clbk() { return 1.0; };\nvar out = base.afilled5dBy( [ 1, 1, 1, 1, 3 ], clbk )\n","base.afilledBy":"function clbk() { return 1.0; };\nvar out = base.afilledBy( 3, clbk )\n","base.afillednd":"var out = base.afillednd( 0.0, [ 1, 3 ] )\n","base.afilledndBy":"function clbk() { return 1.0; };\nvar out = base.afilledndBy( [ 1, 3 ], clbk )\n","base.afilter":"function f( v ) { return ( v > 0 ); };\nvar x = [ 1, -2, -3, 4 ];\nvar out = base.afilter( x, f )\n","base.afirst":"var out = base.afirst( [ 1, 2, 3 ] )\n","base.aflatten":"var x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = base.aflatten( x, [ 2, 2 ], false )\nout = base.aflatten( x, [ 2, 2 ], true )\n","base.aflatten.assign":"var x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten.assign( x, [ 2, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten.assign( x, [ 2, 2 ], true, out, 1, 0 );\nout\n","base.aflatten2d":"var x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = base.aflatten2d( x, [ 2, 2 ], false )\nout = base.aflatten2d( x, [ 2, 2 ], true )\n","base.aflatten2d.assign":"var x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten2d.assign( x, [ 2, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten2d.assign( x, [ 2, 2 ], true, out, 1, 0 );\nout\n","base.aflatten2dBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = base.aflatten2dBy( x, [ 2, 2 ], false, fcn )\nout = base.aflatten2dBy( x, [ 2, 2 ], true, fcn )\n","base.aflatten2dBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten2dBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten2dBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\nout\n","base.aflatten3d":"var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\nvar out = base.aflatten3d( x, [ 2, 1, 2 ], false )\nout = base.aflatten3d( x, [ 2, 1, 2 ], true )\n","base.aflatten3d.assign":"var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten3d.assign( x, [ 2, 1, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten3d.assign( x, [ 2, 1, 2 ], true, out, 1, 0 );\nout\n","base.aflatten3dBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\nvar out = base.aflatten3dBy( x, [ 2, 1, 2 ], false, fcn )\nout = base.aflatten3dBy( x, [ 2, 1, 2 ], true, fcn )\n","base.aflatten3dBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten3dBy.assign( x, [ 2, 1, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten3dBy.assign( x, [ 2, 1, 2 ], true, out, 1, 0, fcn );\nout\n","base.aflatten4d":"var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\nvar out = base.aflatten4d( x, [ 2, 1, 1, 2 ], false )\nout = base.aflatten4d( x, [ 2, 1, 1, 2 ], true )\n","base.aflatten4d.assign":"var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten4d.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0 );\nout\n","base.aflatten4dBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\nvar out = base.aflatten4dBy( x, [ 2, 1, 1, 2 ], false, fcn )\nout = base.aflatten4dBy( x, [ 2, 1, 1, 2 ], true, fcn )\n","base.aflatten4dBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0, fcn );\nout\n","base.aflatten5d":"var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\nvar out = base.aflatten5d( x, [ 2, 1, 1, 1, 2 ], false )\nout = base.aflatten5d( x, [ 2, 1, 1, 1, 2 ], true )\n","base.aflatten5d.assign":"var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0 );\nout\n","base.aflatten5dBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\nvar out = base.aflatten5dBy( x, [ 2, 1, 1, 1, 2 ], false, fcn )\nout = base.aflatten5dBy( x, [ 2, 1, 1, 1, 2 ], true, fcn )\n","base.aflatten5dBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0, fcn );\nout\n","base.aflattenBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = base.aflattenBy( x, [ 2, 2 ], false, fcn )\nout = base.aflattenBy( x, [ 2, 2 ], true, fcn )\n","base.aflattenBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflattenBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflattenBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\nout\n","base.afliplr2d":"var out = base.afliplr2d( [ [ 1, 2 ], [ 3, 4 ] ] )\n","base.afliplr3d":"var out = base.afliplr3d( [ [ [ 1, 2 ], [ 3, 4 ] ] ] )\n","base.afliplr4d":"var out = base.afliplr4d( [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] )\n","base.afliplr5d":"var out = base.afliplr5d( [ [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] ] )\n","base.aflipud2d":"var out = base.aflipud2d( [ [ 1, 2 ], [ 3, 4 ] ] )\n","base.aflipud3d":"var out = base.aflipud3d( [ [ [ 1, 2 ], [ 3, 4 ] ] ] )\n","base.aflipud4d":"var out = base.aflipud4d( [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] )\n","base.aflipud5d":"var out = base.aflipud5d( [ [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] ] )\n","base.ahavercos":"var y = base.ahavercos( 0.5 )\ny = base.ahavercos( 0.0 )\n","base.ahaversin":"var y = base.ahaversin( 0.5 )\ny = base.ahaversin( 0.0 )\n","base.altcase":"var out = base.altcase( 'Hello World!' )\nout = base.altcase( 'I am a tiny little teapot' )\n","base.aones":"var out = base.aones( 3 )\n","base.aones2d":"var out = base.aones2d( [ 1, 3 ] )\n","base.aones3d":"var out = base.aones3d( [ 1, 1, 3 ] )\n","base.aones4d":"var out = base.aones4d( [ 1, 1, 1, 3 ] )\n","base.aones5d":"var out = base.aones5d( [ 1, 1, 1, 1, 3 ] )\n","base.aonesnd":"var out = base.aonesnd( [ 1, 3 ] )\n","base.aoneTo":"var arr = base.aoneTo( 6 )\n","base.aoneTo.assign":"var out = [ 0, 0, 0, 0, 0, 0 ];\nbase.aoneTo.assign( out, -1, out.length-1 );\nout\n","base.args2multislice":"var args = [ null, null, null ];\nvar s = new base.args2multislice( args );\ns.data\nargs = [ 10, new Slice( 0, 10, 1 ), null ];\ns = new base.args2multislice( args );\ns.data\n","base.asec":"var y = base.asec( 1.0 )\ny = base.asec( 2.0 )\ny = base.asec( NaN )\n","base.asecd":"var y = base.asecd( 0.0 )\ny = base.asecd( 2 )\ny = base.asecd( NaN )\n","base.asecdf":"var y = base.asecdf( 2.0 )\ny = base.asecdf( 0.0 )\ny = base.asecdf( NaN )\n","base.asecf":"var y = base.asecf( 1.0 )\ny = base.asecf( 2.0 )\ny = base.asecf( NaN )\n","base.asech":"var y = base.asech( 1.0 )\ny = base.asech( 0.5 )\ny = base.asech( NaN )\n","base.asin":"var y = base.asin( 0.0 )\ny = base.asin( -PI/6.0 )\ny = base.asin( NaN )\n","base.asind":"var y = base.asind( 0.0 )\ny = base.asind( PI / 6.0 )\ny = base.asind( NaN )\n","base.asindf":"var y = base.asindf( 0.0 )\ny = base.asindf( 3.1415927410125732 / 6.0 )\ny = base.asindf( NaN )\n","base.asinf":"var y = base.asinf( 0.0 )\ny = base.asinf( -3.14/6.0 )\ny = base.asinf( NaN )\n","base.asinh":"var y = base.asinh( 0.0 )\ny = base.asinh( 2.0 )\ny = base.asinh( -2.0 )\ny = base.asinh( NaN )\ny = base.asinh( NINF )\ny = base.asinh( PINF )\n","base.atan":"var y = base.atan( 0.0 )\ny = base.atan( -PI/2.0 )\ny = base.atan( PI/2.0 )\ny = base.atan( NaN )\n","base.atan2":"var v = base.atan2( 2.0, 2.0 )\nv = base.atan2( 6.0, 2.0 )\nv = base.atan2( -1.0, -1.0 )\nv = base.atan2( 3.0, 0.0 )\nv = base.atan2( -2.0, 0.0 )\nv = base.atan2( 0.0, 0.0 )\nv = base.atan2( 3.0, NaN )\nv = base.atan2( NaN, 2.0 )\n","base.atand":"var y = base.atand( 0.0 )\ny = base.atand( PI/6.0 )\ny = base.atand( NaN )\n","base.atanf":"var y = base.atanf( 0.0 )\ny = base.atanf( -3.14/4.0 )\ny = base.atanf( 3.14/4.0 )\ny = base.atanf( NaN )\n","base.atanh":"var y = base.atanh( 0.0 )\ny = base.atanh( 0.9 )\ny = base.atanh( 1.0 )\ny = base.atanh( -1.0 )\ny = base.atanh( NaN 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1.0 )\ny = base.besselj0( PINF )\ny = base.besselj0( NINF )\ny = base.besselj0( NaN )\n","base.besselj1":"var y = base.besselj1( 0.0 )\ny = base.besselj1( 1.0 )\ny = base.besselj1( PINF )\ny = base.besselj1( NINF )\ny = base.besselj1( NaN )\n","base.bessely0":"var y = base.bessely0( 0.0 )\ny = base.bessely0( 1.0 )\ny = base.bessely0( -1.0 )\ny = base.bessely0( PINF )\ny = base.bessely0( NINF )\ny = base.bessely0( NaN )\n","base.bessely1":"var y = base.bessely1( 0.0 )\ny = base.bessely1( 1.0 )\ny = base.bessely1( -1.0 )\ny = base.bessely1( PINF )\ny = base.bessely1( NINF )\ny = base.bessely1( NaN )\n","base.beta":"var v = base.beta( 0.0, 0.5 )\nv = base.beta( 1.0, 1.0 )\nv = base.beta( -1.0, 2.0 )\nv = base.beta( 5.0, 0.2 )\nv = base.beta( 4.0, 1.0 )\nv = base.beta( NaN, 2.0 )\n","base.betainc":"var y = base.betainc( 0.5, 2.0, 2.0 )\ny = base.betainc( 0.5, 2.0, 2.0, false )\ny = base.betainc( 0.2, 1.0, 2.0 )\ny = base.betainc( 0.2, 1.0, 2.0, true, true )\ny = base.betainc( NaN, 1.0, 1.0 )\ny = base.betainc( 0.8, NaN, 1.0 )\ny = base.betainc( 0.8, 1.0, NaN )\ny = base.betainc( 1.5, 1.0, 1.0 )\ny = base.betainc( -0.5, 1.0, 1.0 )\ny = base.betainc( 0.5, -2.0, 2.0 )\ny = base.betainc( 0.5, 2.0, -2.0 )\n","base.betaincinv":"var y = base.betaincinv( 0.2, 3.0, 3.0 )\ny = base.betaincinv( 0.4, 3.0, 3.0 )\ny = base.betaincinv( 0.4, 3.0, 3.0, true )\ny = base.betaincinv( 0.4, 1.0, 6.0 )\ny = base.betaincinv( 0.8, 1.0, 6.0 )\ny = base.betaincinv( NaN, 1.0, 1.0 )\ny = base.betaincinv( 0.5, NaN, 1.0 )\ny = base.betaincinv( 0.5, 1.0, NaN )\ny = base.betaincinv( 1.2, 1.0, 1.0 )\ny = base.betaincinv( -0.5, 1.0, 1.0 )\ny = base.betaincinv( 0.5, -2.0, 2.0 )\ny = base.betaincinv( 0.5, 0.0, 2.0 )\ny = base.betaincinv( 0.5, 2.0, -2.0 )\ny = base.betaincinv( 0.5, 2.0, 0.0 )\n","base.betaln":"var v = base.betaln( 0.0, 0.0 )\nv = base.betaln( 1.0, 1.0 )\nv = base.betaln( -1.0, 2.0 )\nv = base.betaln( 5.0, 0.2 )\nv = base.betaln( 4.0, 1.0 )\nv = base.betaln( NaN, 2.0 )\n","base.binet":"var y = base.binet( 0.0 )\ny = base.binet( 1.0 )\ny = base.binet( 2.0 )\ny = base.binet( 3.0 )\ny = base.binet( 4.0 )\ny = base.binet( 5.0 )\ny = base.binet( NaN )\n","base.binomcoef":"var v = base.binomcoef( 8, 2 )\nv = base.binomcoef( 0, 0 )\nv = base.binomcoef( -4, 2 )\nv = base.binomcoef( 5, 3 )\nv = base.binomcoef( NaN, 3 )\nv = base.binomcoef( 5, NaN )\nv = base.binomcoef( NaN, NaN )\n","base.binomcoefln":"var v = base.binomcoefln( 8, 2 )\nv = base.binomcoefln( 0, 0 )\nv = base.binomcoefln( -4, 2 )\nv = base.binomcoefln( 88, 3 )\nv = base.binomcoefln( NaN, 3 )\nv = base.binomcoefln( 5, NaN )\nv = base.binomcoefln( NaN, NaN )\n","base.boxcox":"var v = base.boxcox( 1.0, 2.5 )\nv = base.boxcox( 4.0, 2.5 )\nv = base.boxcox( 10.0, 2.5 )\nv = base.boxcox( 2.0, 0.0 )\nv = base.boxcox( -1.0, 2.5 )\nv = base.boxcox( 0.0, -1.0 )\n","base.boxcox1p":"var v =  base.boxcox1p( 1.0, 2.5 )\nv = base.boxcox1p( 4.0, 2.5 )\nv = base.boxcox1p( 10.0, 2.5 )\nv = base.boxcox1p( 2.0, 0.0 )\nv = base.boxcox1p( -1.0, 2.5 )\nv = base.boxcox1p( 0.0, -1.0 )\nv = base.boxcox1p( -1.0, -1.0 )\n","base.boxcox1pinv":"var v = base.boxcox1pinv( 1.0, 2.5 )\nv = base.boxcox1pinv( 4.0, 2.5 )\nv = base.boxcox1pinv( 10.0, 2.5 )\nv = base.boxcox1pinv( 2.0, 0.0 )\nv = base.boxcox1pinv( -1.0, 2.5 )\nv = base.boxcox1pinv( 0.0, -1.0 )\nv = base.boxcox1pinv( 1.0, NaN )\nv = base.boxcox1pinv( NaN, 3.1 )\n","base.boxcoxinv":"var v = base.boxcoxinv( 1.0, 2.5 )\nv = base.boxcoxinv( 4.0, 2.5 )\nv = base.boxcoxinv( 10.0, 2.5 )\nv = base.boxcoxinv( 2.0, 0.0 )\nv = base.boxcoxinv( -1.0, 2.5 )\nv = base.boxcoxinv( 0.0, -1.0 )\nv = base.boxcoxinv( 1.0, NaN )\nv = base.boxcoxinv( NaN, 3.1 )\n","base.cabs":"var y = base.cabs( new Complex128( 5.0, 3.0 ) )\n","base.cabs2":"var y = base.cabs2( new Complex128( 5.0, 3.0 ) )\n","base.cabs2f":"var y = base.cabs2f( new Complex64( 5.0, 3.0 ) )\n","base.cabsf":"var y = base.cabsf( new Complex64( 5.0, 3.0 ) )\n","base.cadd":"var z = new Complex128( 5.0, 3.0 )\nvar out = base.cadd( z, z )\nvar re = real( out )\nvar im = imag( out )\n","base.caddf":"var z = new Complex64( 5.0, 3.0 )\nvar out = base.caddf( z, z )\nvar re = realf( out )\nvar im = imagf( out )\n","base.camelcase":"var out = base.camelcase( 'Hello World!' )\nout = base.camelcase( 'beep boop' )\n","base.capitalize":"var out = base.capitalize( 'beep' )\nout = base.capitalize( 'Boop' )\n","base.cbrt":"var y = base.cbrt( 64.0 )\ny = base.cbrt( 27.0 )\ny = base.cbrt( 0.0 )\ny = base.cbrt( -0.0 )\ny = base.cbrt( -9.0 )\ny = base.cbrt( NaN )\n","base.cbrtf":"var y = base.cbrtf( 64.0 )\ny = base.cbrtf( 27.0 )\ny = base.cbrtf( 0.0 )\ny = base.cbrtf( -0.0 )\ny = base.cbrtf( -9.0 )\ny = base.cbrtf( NaN )\n","base.cceil":"var v = base.cceil( new Complex128( -1.5, 2.5 ) )\nvar re = real( v )\nvar im = imag( v )\n","base.cceilf":"var v = base.cceilf( new Complex64( -1.5, 2.5 ) )\nvar re = realf( v )\nvar im = imagf( v )\n","base.cceiln":"var out = base.cceiln( new Complex128( 5.555, -3.333 ), -2 )\nvar re = real( out )\nvar im = imag( out )\n","base.ccis":"var y = base.ccis( new Complex128( 0.0, 0.0 ) )\nvar re = real( y )\nvar im = imag( y )\ny = base.ccis( new Complex128( 1.0, 0.0 ) )\nre = real( y )\nim = imag( y )\n","base.cdiv":"var z1 = new Complex128( -13.0, -1.0 )\nvar z2 = new Complex128( -2.0, 1.0 )\nvar y = base.cdiv( z1, z2 )\nvar re = real( y )\nvar im = imag( y )\n","base.ceil":"var y = base.ceil( 3.14 )\ny = base.ceil( -4.2 )\ny = base.ceil( -4.6 )\ny = base.ceil( 9.5 )\ny = base.ceil( -0.0 )\n","base.ceil2":"var y = base.ceil2( 3.14 )\ny = base.ceil2( -4.2 )\ny = base.ceil2( -4.6 )\ny = base.ceil2( 9.5 )\ny = base.ceil2( 13.0 )\ny = base.ceil2( -13.0 )\ny = base.ceil2( -0.0 )\n","base.ceil10":"var y = base.ceil10( 3.14 )\ny = base.ceil10( -4.2 )\ny = base.ceil10( -4.6 )\ny = base.ceil10( 9.5 )\ny = base.ceil10( 13.0 )\ny = base.ceil10( -13.0 )\ny = base.ceil10( -0.0 )\n","base.ceilb":"var y = base.ceilb( 3.14159, -4, 10 )\ny = base.ceilb( 3.14159, 0, 2 )\ny = base.ceilb( 5.0, 1, 2 )\n","base.ceilf":"var y = base.ceilf( 3.14 )\ny = base.ceilf( -4.2 )\ny = base.ceilf( -4.6 )\ny = base.ceilf( 9.5 )\ny = base.ceilf( -0.0 )\n","base.ceiln":"var y = base.ceiln( 3.14159, -2 )\ny = base.ceiln( 3.14159, 0 )\ny = base.ceiln( 12368.0, 3 )\n","base.ceilsd":"var y = base.ceilsd( 3.14159, 5, 10 )\ny = base.ceilsd( 3.14159, 1, 10 )\ny = base.ceilsd( 12368.0, 2, 10 )\ny = base.ceilsd( 0.0313, 2, 2 )\n","base.cexp":"var y = base.cexp( new Complex128( 0.0, 0.0 ) )\nvar re = real( y )\nvar im = imag( y )\ny = base.cexp( new Complex128( 0.0, 1.0 ) )\nre = real( y )\nim = imag( y )\n","base.cflipsign":"var v = base.cflipsign( new Complex128( -4.2, 5.5 ), -9.0 )\nvar re = real( v )\nvar im = imag( v )\n","base.cflipsignf":"var v = base.cflipsignf( new Complex64( -4.0, 5.0 ), -9.0 )\nvar re = realf( v )\nvar im = imagf( v )\n","base.cfloor":"var v = base.cfloor( new Complex128( 5.5, 3.3 ) )\nvar re = real( v )\nvar im = imag( v )\n","base.cfloorn":"var v = base.cfloorn( new Complex128( 5.555, -3.333 ), -2 )\nvar re = real( v )\nvar im = imag( v )\n","base.cidentity":"var v = base.cidentity( new Complex128( -1.0, 2.0 ) )\nvar re = real( v )\nvar img = imag( v )\n","base.cidentityf":"var v = base.cidentityf( new Complex64( -1.0, 2.0 ) )\nvar re = realf( v )\nvar img = imagf( v )\n","base.cinv":"var v = base.cinv( new Complex128( 2.0, 4.0 ) )\nvar re = real( v )\nvar im = imag( v )\n","base.clamp":"var y = base.clamp( 3.14, 0.0, 5.0 )\ny = base.clamp( -3.14, 0.0, 5.0 )\ny = base.clamp( 3.14, 0.0, 3.0 )\ny = base.clamp( -0.0, 0.0, 5.0 )\ny = base.clamp( 0.0, -3.14, -0.0 )\ny = base.clamp( NaN, 0.0, 5.0 )\n","base.clampf":"var y = base.clampf( 3.14, 0.0, 5.0 )\ny = base.clampf( -3.14, 0.0, 5.0 )\ny = base.clampf( 3.14, 0.0, 3.0 )\ny = base.clampf( -0.0, 0.0, 5.0 )\ny = base.clampf( 0.0, -3.14, -0.0 )\ny = base.clampf( NaN, 0.0, 5.0 )\n","base.cmul":"var z1 = new Complex128( 5.0, 3.0 )\nvar z2 = new Complex128( -2.0, 1.0 )\nvar out = base.cmul( z1, z2 )\nvar re = real( out )\nvar im = imag( out )\n","base.cmulf":"var z1 = new Complex64( 5.0, 3.0 )\nvar z2 = new Complex64( -2.0, 1.0 )\nvar out = base.cmulf( z1, z2 )\nvar re = realf( out )\nvar im = imagf( out )\n","base.cneg":"var z = new Complex128( -4.2, 5.5 )\nvar v = base.cneg( z )\nvar re = real( v )\nvar im = imag( v )\n","base.cnegf":"var z = new Complex64( -4.0, 5.0 )\nvar v = base.cnegf( z )\nvar re = realf( v )\nvar im = imagf( v )\n","base.codePointAt":"var out = base.codePointAt( 'last man standing', 4, false )\nout = base.codePointAt( 'presidential election', 8, true )\nout = base.codePointAt( 'अनुच्छेद', 2, false )\nout = base.codePointAt( '🌷', 1, true )\n","base.constantcase":"var out = base.constantcase( 'Hello World!' )\nout = base.constantcase( 'I am a tiny little teapot' )\n","base.continuedFraction":"function closure() {\nvar i = 0;\nreturn function() {\n    i += 1;\n    return [ i, i ];\n};\n };\nvar gen = closure();\nvar out = base.continuedFraction( gen )\nfunction* generator() {\n var i = 0;\n while ( true ) {\n     i += 1;\n     yield [ i, i ];\n }\n };\ngen = generator();\nout = base.continuedFraction( gen )\nout = base.continuedFraction( generator(), { 'keep': true } )\nout = base.continuedFraction( generator(), { 'maxIter': 10 } )\nout = base.continuedFraction( generator(), { 'tolerance': 1e-1 } )\n","base.copysign":"var z = base.copysign( -3.14, 10.0 )\nz = base.copysign( 3.14, -1.0 )\nz = base.copysign( 1.0, -0.0 )\nz = base.copysign( -3.14, -0.0 )\nz = base.copysign( -0.0, 1.0 )\n","base.copysignf":"var z = base.copysignf( -3.0, 10.0 )\nz = base.copysignf( 3.0, -1.0 )\nz = base.copysignf( 1.0, -0.0 )\nz = base.copysignf( -3.0, -0.0 )\nz = base.copysignf( -0.0, 1.0 )\n","base.cos":"var y = base.cos( 0.0 )\ny = base.cos( PI/4.0 )\ny = base.cos( -PI/6.0 )\ny = base.cos( NaN )\n","base.cosd":"var y = base.cosd( 0.0 )\ny = base.cosd( 90.0 )\ny = base.cosd( 60.0 )\ny = base.cosd( NaN )\n","base.cosh":"var y = base.cosh( 0.0 )\ny = base.cosh( 2.0 )\ny = base.cosh( -2.0 )\ny = base.cosh( NaN )\n","base.cosm1":"var y = base.cosm1( 0.0 )\ny = base.cosm1( PI/4.0 )\ny = base.cosm1( -PI/6.0 )\ny = base.cosm1( NaN )\n","base.cospi":"var y = base.cospi( 0.0 )\ny = base.cospi( 0.5 )\ny = base.cospi( 0.1 )\ny = base.cospi( NaN )\n","base.cot":"var y = base.cot( 0.0 )\ny = base.cot( -PI/4.0 )\ny = base.cot( PI/4.0 )\ny = base.cot( NaN )\n","base.cotd":"var y = base.cotd( 0.0 )\ny = base.cotd( 90.0 )\ny = base.cotd( 60.0 )\ny = base.cotd( NaN )\n","base.coth":"var y = base.coth( 0.0 )\ny = base.coth( -0.0 )\ny = base.coth( 2.0 )\ny = base.coth( -2.0 )\ny = base.coth( +Infinity )\ny = base.coth( -Infinity )\ny = base.coth( NaN )\n","base.covercos":"var y = base.covercos( 3.14 )\ny = base.covercos( -4.2 )\ny = base.covercos( -4.6 )\ny = base.covercos( 9.5 )\ny = base.covercos( -0.0 )\n","base.coversin":"var y = base.coversin( 3.14 )\ny = base.coversin( -4.2 )\ny = base.coversin( -4.6 )\ny = base.coversin( 9.5 )\ny = base.coversin( -0.0 )\n","base.cphase":"var phi = base.cphase( new Complex128( 5.0, 3.0 ) )\n","base.cpolar":"var out = base.cpolar( new Complex128( 5.0, 3.0 ) )\n","base.cpolar.assign":"var out = new Float64Array( 2 );\nvar v = base.cpolar.assign( new Complex128( 5.0, 3.0 ), out, 1, 0 )\nvar bool = ( v === out )\n","base.cround":"var v = base.cround( new Complex128( 5.5, 3.3 ) )\nvar re = real( v )\nvar im = imag( v )\n","base.croundn":"var v = base.croundn( new Complex128( 5.555, -3.336 ), -2 )\nvar re = real( v )\nvar im = imag( v )\n","base.csc":"var y = base.csc( 0.0 )\ny = base.csc( PI/2.0 )\ny = base.csc( -PI/6.0 )\ny = base.csc( NaN )\n","base.cscd":"var y = base.cscd( 1.0 )\ny = base.cscd( PI )\ny = base.cscd( -PI )\ny = base.cscd( NaN )\n","base.csch":"var y = base.csch( +0.0 )\nvar y = base.csch( -0.0 )\nvar y = base.csch( +Infinity )\nvar y = base.csch( -Infinity )\ny = base.csch( 2.0 )\ny = base.csch( -2.0 )\ny = base.csch( NaN )\n","base.csignum":"var v = base.csignum( new Complex128( -4.2, 5.5 ) )\nvar re = real( v )\nvar im = imag( v )\n","base.csub":"var z1 = new Complex128( 5.0, 3.0 )\nvar z2 = new Complex128( -2.0, 1.0 )\nvar out = base.csub( z1, z2 )\nvar re = real( out )\nvar im = imag( out )\n","base.csubf":"var z1 = new Complex64( 5.0, 3.0 )\nvar z2 = new Complex64( -2.0, 1.0 )\nvar out = base.csubf( z1, z2 )\nvar re = realf( out )\nvar im = imagf( out )\n","base.deg2rad":"var r = base.deg2rad( 90.0 )\nr = base.deg2rad( -45.0 )\nr = base.deg2rad( NaN )\n","base.deg2radf":"var r = base.deg2radf( 90.0 )\nr = base.deg2radf( -45.0 )\nr = base.deg2radf( NaN )\n","base.digamma":"var y = base.digamma( -2.5 )\ny = base.digamma( 1.0 )\ny = base.digamma( 10.0 )\ny = base.digamma( NaN )\ny = base.digamma( -1.0 )\n","base.diracDelta":"var y = base.diracDelta( 3.14 )\ny = base.diracDelta( 0.0 )\n","base.div":"var v = base.div( -1.0, 5.0 )\nv = base.div( 2.0, 5.0 )\nv = base.div( 0.0, 5.0 )\nv = base.div( -0.0, 5.0 )\nv = base.div( NaN, NaN )\n","base.divf":"var v = base.divf( 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)\n","base.dists.arcsine.cdf.factory":"var mycdf = base.dists.arcsine.cdf.factory( 0.0, 10.0 );\nvar y = mycdf( 0.5 )\ny = mycdf( 8.0 )\n","base.dists.arcsine.entropy":"var v = base.dists.arcsine.entropy( 0.0, 1.0 )\nv = base.dists.arcsine.entropy( 4.0, 12.0 )\nv = base.dists.arcsine.entropy( 2.0, 8.0 )\n","base.dists.arcsine.kurtosis":"var v = base.dists.arcsine.kurtosis( 0.0, 1.0 )\nv = base.dists.arcsine.kurtosis( 4.0, 12.0 )\nv = base.dists.arcsine.kurtosis( 2.0, 8.0 )\n","base.dists.arcsine.logcdf":"var y = base.dists.arcsine.logcdf( 9.0, 0.0, 10.0 )\ny = base.dists.arcsine.logcdf( 0.5, 0.0, 2.0 )\ny = base.dists.arcsine.logcdf( PINF, 2.0, 4.0 )\ny = base.dists.arcsine.logcdf( NINF, 2.0, 4.0 )\ny = base.dists.arcsine.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.logcdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.logcdf( 2.0, 1.0, 0.0 )\n","base.dists.arcsine.logcdf.factory":"var mylogcdf = base.dists.arcsine.logcdf.factory( 0.0, 10.0 );\nvar y = mylogcdf( 0.5 )\ny = mylogcdf( 8.0 )\n","base.dists.arcsine.logpdf":"var y = base.dists.arcsine.logpdf( 2.0, 0.0, 4.0 )\ny = base.dists.arcsine.logpdf( 5.0, 0.0, 4.0 )\ny = base.dists.arcsine.logpdf( 0.25, 0.0, 1.0 )\ny = base.dists.arcsine.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.logpdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.logpdf( 2.0, 3.0, 1.0 )\n","base.dists.arcsine.logpdf.factory":"var mylogPDF = base.dists.arcsine.logpdf.factory( 6.0, 7.0 );\nvar y = mylogPDF( 7.0 )\ny = mylogPDF( 5.0 )\n","base.dists.arcsine.mean":"var v = base.dists.arcsine.mean( 0.0, 1.0 )\nv = base.dists.arcsine.mean( 4.0, 12.0 )\nv = base.dists.arcsine.mean( 2.0, 8.0 )\n","base.dists.arcsine.median":"var v = base.dists.arcsine.median( 0.0, 1.0 )\nv = base.dists.arcsine.median( 4.0, 12.0 )\nv = base.dists.arcsine.median( 2.0, 8.0 )\n","base.dists.arcsine.mode":"var v = base.dists.arcsine.mode( 0.0, 1.0 )\nv = base.dists.arcsine.mode( 4.0, 12.0 )\nv = base.dists.arcsine.mode( 2.0, 8.0 )\n","base.dists.arcsine.pdf":"var y = base.dists.arcsine.pdf( 2.0, 0.0, 4.0 )\ny = base.dists.arcsine.pdf( 5.0, 0.0, 4.0 )\ny = base.dists.arcsine.pdf( 0.25, 0.0, 1.0 )\ny = base.dists.arcsine.pdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.pdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.pdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.pdf( 2.0, 3.0, 1.0 )\n","base.dists.arcsine.pdf.factory":"var myPDF = base.dists.arcsine.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 7.0 )\ny = myPDF( 5.0 )\n","base.dists.arcsine.quantile":"var y = base.dists.arcsine.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( 0.5, 0.0, 10.0 )\ny = base.dists.arcsine.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.quantile( 0.0, 0.0, NaN )\ny = base.dists.arcsine.quantile( 0.5, 2.0, 1.0 )\n","base.dists.arcsine.quantile.factory":"var myQuantile = base.dists.arcsine.quantile.factory( 0.0, 4.0 );\nvar y = myQuantile( 0.8 )\n","base.dists.arcsine.skewness":"var v = base.dists.arcsine.skewness( 0.0, 1.0 )\nv = base.dists.arcsine.skewness( 4.0, 12.0 )\nv = base.dists.arcsine.skewness( 2.0, 8.0 )\n","base.dists.arcsine.stdev":"var v = base.dists.arcsine.stdev( 0.0, 1.0 )\nv = base.dists.arcsine.stdev( 4.0, 12.0 )\nv = base.dists.arcsine.stdev( 2.0, 8.0 )\n","base.dists.arcsine.variance":"var v = base.dists.arcsine.variance( 0.0, 1.0 )\nv = base.dists.arcsine.variance( 4.0, 12.0 )\nv = base.dists.arcsine.variance( 2.0, 8.0 )\n","base.dists.bernoulli.Bernoulli":"var bernoulli = base.dists.bernoulli.Bernoulli( 0.6 );\nbernoulli.p\nbernoulli.entropy\nbernoulli.kurtosis\nbernoulli.mean\nbernoulli.median\nbernoulli.skewness\nbernoulli.stdev\nbernoulli.variance\nbernoulli.cdf( 0.5 )\nbernoulli.mgf( 3.0 )\nbernoulli.pmf( 0.0 )\nbernoulli.quantile( 0.7 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0.2, 0.5 )\ny = base.dists.bernoulli.mgf( 0.4, 0.5 )\ny = base.dists.bernoulli.mgf( NaN, 0.0 )\ny = base.dists.bernoulli.mgf( 0.0, NaN )\ny = base.dists.bernoulli.mgf( -2.0, -1.0 )\ny = base.dists.bernoulli.mgf( 0.2, 2.0 )\n","base.dists.bernoulli.mgf.factory":"var mymgf = base.dists.bernoulli.mgf.factory( 0.8 );\nvar y = mymgf( -0.2 )\n","base.dists.bernoulli.mode":"var v = base.dists.bernoulli.mode( 0.1 )\nv = base.dists.bernoulli.mode( 0.8 )\n","base.dists.bernoulli.pmf":"var y = base.dists.bernoulli.pmf( 1.0, 0.3 )\ny = base.dists.bernoulli.pmf( 0.0, 0.7 )\ny = base.dists.bernoulli.pmf( -1.0, 0.5 )\ny = base.dists.bernoulli.pmf( 0.0, NaN )\ny = base.dists.bernoulli.pmf( NaN, 0.5 )\ny = base.dists.bernoulli.pmf( 0.0, 1.5 )\n","base.dists.bernoulli.pmf.factory":"var mypmf = base.dists.bernoulli.pmf.factory( 0.5 );\nvar y = mypmf( 1.0 )\ny = mypmf( 0.0 )\n","base.dists.bernoulli.quantile":"var y = base.dists.bernoulli.quantile( 0.8, 0.4 )\ny = base.dists.bernoulli.quantile( 0.5, 0.4 )\ny = base.dists.bernoulli.quantile( 0.9, 0.1 )\ny = base.dists.bernoulli.quantile( -0.2, 0.1 )\ny = base.dists.bernoulli.quantile( NaN, 0.8 )\ny = base.dists.bernoulli.quantile( 0.4, NaN )\ny = base.dists.bernoulli.quantile( 0.5, -1.0 )\ny = base.dists.bernoulli.quantile( 0.5, 1.5 )\n","base.dists.bernoulli.quantile.factory":"var myquantile = base.dists.bernoulli.quantile.factory( 0.4 );\nvar y = myquantile( 0.4 )\ny = myquantile( 0.8 )\ny = myquantile( 1.0 )\n","base.dists.bernoulli.skewness":"var v = base.dists.bernoulli.skewness( 0.1 )\nv = base.dists.bernoulli.skewness( 0.5 )\n","base.dists.bernoulli.stdev":"var v = base.dists.bernoulli.stdev( 0.1 )\nv = base.dists.bernoulli.stdev( 0.5 )\n","base.dists.bernoulli.variance":"var v = base.dists.bernoulli.variance( 0.1 )\nv = base.dists.bernoulli.variance( 0.5 )\n","base.dists.beta.Beta":"var beta = base.dists.beta.Beta( 1.0, 1.0 );\nbeta.alpha\nbeta.beta\nbeta.entropy\nbeta.kurtosis\nbeta.mean\nbeta.median\nbeta.mode\nbeta.skewness\nbeta.stdev\nbeta.variance\nbeta.cdf( 0.8 )\nbeta.logcdf( 0.8 )\nbeta.logpdf( 1.0 )\nbeta.mgf( 3.14 )\nbeta.pdf( 1.0 )\nbeta.quantile( 0.8 )\n","base.dists.beta.cdf":"var y = base.dists.beta.cdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.cdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.cdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.cdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.cdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.cdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.beta.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.beta.cdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.cdf( 0.0, NaN, 1.0 )\ny = base.dists.beta.cdf( 0.0, 1.0, NaN )\n","base.dists.beta.cdf.factory":"var mycdf = base.dists.beta.cdf.factory( 0.5, 0.5 );\nvar y = mycdf( 0.8 )\ny = mycdf( 0.3 )\n","base.dists.beta.entropy":"var v = base.dists.beta.entropy( 1.0, 1.0 )\nv = base.dists.beta.entropy( 4.0, 12.0 )\nv = base.dists.beta.entropy( 8.0, 2.0 )\nv = base.dists.beta.entropy( 1.0, -0.1 )\nv = base.dists.beta.entropy( -0.1, 1.0 )\nv = base.dists.beta.entropy( 2.0, NaN )\nv = base.dists.beta.entropy( NaN, 2.0 )\n","base.dists.beta.kurtosis":"var v = base.dists.beta.kurtosis( 1.0, 1.0 )\nv = base.dists.beta.kurtosis( 4.0, 12.0 )\nv = base.dists.beta.kurtosis( 8.0, 2.0 )\nv = base.dists.beta.kurtosis( 1.0, -0.1 )\nv = base.dists.beta.kurtosis( -0.1, 1.0 )\nv = base.dists.beta.kurtosis( 2.0, NaN )\nv = base.dists.beta.kurtosis( NaN, 2.0 )\n","base.dists.beta.logcdf":"var y = base.dists.beta.logcdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.logcdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.logcdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.logcdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.logcdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.logcdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.beta.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.beta.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.beta.logcdf( 0.0, 1.0, NaN )\n","base.dists.beta.logcdf.factory":"var mylogcdf = base.dists.beta.logcdf.factory( 0.5, 0.5 );\nvar y = mylogcdf( 0.8 )\ny = mylogcdf( 0.3 )\n","base.dists.beta.logpdf":"var y = base.dists.beta.logpdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.logpdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.logpdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.logpdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.logpdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.logpdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.logpdf( 0.5, -1.0, 0.5 )\ny = base.dists.beta.logpdf( 0.5, 0.5, -1.0 )\ny = base.dists.beta.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.logpdf( 0.5, NaN, 1.0 )\ny = base.dists.beta.logpdf( 0.5, 1.0, NaN )\n","base.dists.beta.logpdf.factory":"var mylogpdf = base.dists.beta.logpdf.factory( 0.5, 0.5 );\nvar y = mylogpdf( 0.8 )\ny = mylogpdf( 0.3 )\n","base.dists.beta.mean":"var v = base.dists.beta.mean( 1.0, 1.0 )\nv = base.dists.beta.mean( 4.0, 12.0 )\nv = base.dists.beta.mean( 8.0, 2.0 )\n","base.dists.beta.median":"var v = base.dists.beta.median( 1.0, 1.0 )\nv = base.dists.beta.median( 4.0, 12.0 )\nv = base.dists.beta.median( 8.0, 2.0 )\nv = base.dists.beta.median( 1.0, -0.1 )\nv = base.dists.beta.median( -0.1, 1.0 )\nv = base.dists.beta.median( 2.0, NaN )\nv = base.dists.beta.median( NaN, 2.0 )\n","base.dists.beta.mgf":"var y = base.dists.beta.mgf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.mgf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.mgf( 3.0, 2.0, 2.0 )\ny = base.dists.beta.mgf( -0.8, 4.0, 4.0 )\ny = base.dists.beta.mgf( NaN, 1.0, 1.0 )\ny = base.dists.beta.mgf( 0.0, NaN, 1.0 )\ny = base.dists.beta.mgf( 0.0, 1.0, NaN )\ny = base.dists.beta.mgf( 2.0, -1.0, 0.5 )\ny = base.dists.beta.mgf( 2.0, 0.0, 0.5 )\ny = base.dists.beta.mgf( 2.0, 0.5, -1.0 )\ny = base.dists.beta.mgf( 2.0, 0.5, 0.0 )\n","base.dists.beta.mgf.factory":"var myMGF = base.dists.beta.mgf.factory( 0.5, 0.5 );\nvar y = myMGF( 0.8 )\ny = myMGF( 0.3 )\n","base.dists.beta.mode":"var v = base.dists.beta.mode( 4.0, 12.0 )\nv = base.dists.beta.mode( 8.0, 2.0 )\nv = base.dists.beta.mode( 1.0, 1.0 )\n","base.dists.beta.pdf":"var y = base.dists.beta.pdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.pdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.pdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.pdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.pdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.pdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.pdf( 0.5, -1.0, 0.5 )\ny = base.dists.beta.pdf( 0.5, 0.5, -1.0 )\ny = base.dists.beta.pdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.pdf( 0.5, NaN, 1.0 )\ny = base.dists.beta.pdf( 0.5, 1.0, NaN )\n","base.dists.beta.pdf.factory":"var mypdf = base.dists.beta.pdf.factory( 0.5, 0.5 );\nvar y = mypdf( 0.8 )\ny = mypdf( 0.3 )\n","base.dists.beta.quantile":"var y = base.dists.beta.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.beta.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.beta.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.beta.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.beta.quantile( NaN, 1.0, 1.0 )\ny = base.dists.beta.quantile( 0.5, NaN, 1.0 )\ny = base.dists.beta.quantile( 0.5, 1.0, NaN )\ny = base.dists.beta.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.beta.quantile( 0.5, 1.0, -1.0 )\n","base.dists.beta.quantile.factory":"var myquantile = base.dists.beta.quantile.factory( 2.0, 2.0 );\ny = myquantile( 0.8 )\ny = myquantile( 0.4 )\n","base.dists.beta.skewness":"var v = base.dists.beta.skewness( 1.0, 1.0 )\nv = base.dists.beta.skewness( 4.0, 12.0 )\nv = base.dists.beta.skewness( 8.0, 2.0 )\nv = base.dists.beta.skewness( 1.0, -0.1 )\nv = base.dists.beta.skewness( -0.1, 1.0 )\nv = base.dists.beta.skewness( 2.0, NaN )\nv = base.dists.beta.skewness( NaN, 2.0 )\n","base.dists.beta.stdev":"var v = base.dists.beta.stdev( 1.0, 1.0 )\nv = base.dists.beta.stdev( 4.0, 12.0 )\nv = base.dists.beta.stdev( 8.0, 2.0 )\nv = base.dists.beta.stdev( 1.0, -0.1 )\nv = base.dists.beta.stdev( -0.1, 1.0 )\nv = base.dists.beta.stdev( 2.0, NaN )\nv = base.dists.beta.stdev( NaN, 2.0 )\n","base.dists.beta.variance":"var v = base.dists.beta.variance( 1.0, 1.0 )\nv = base.dists.beta.variance( 4.0, 12.0 )\nv = base.dists.beta.variance( 8.0, 2.0 )\nv = base.dists.beta.variance( 1.0, -0.1 )\nv = base.dists.beta.variance( -0.1, 1.0 )\nv = base.dists.beta.variance( 2.0, NaN )\nv = base.dists.beta.variance( NaN, 2.0 )\n","base.dists.betaprime.BetaPrime":"var betaprime = base.dists.betaprime.BetaPrime( 6.0, 5.0 );\nbetaprime.alpha\nbetaprime.beta\nbetaprime.kurtosis\nbetaprime.mean\nbetaprime.mode\nbetaprime.skewness\nbetaprime.stdev\nbetaprime.variance\nbetaprime.cdf( 0.8 )\nbetaprime.logcdf( 0.8 )\nbetaprime.logpdf( 1.0 )\nbetaprime.pdf( 1.0 )\nbetaprime.quantile( 0.8 )\n","base.dists.betaprime.cdf":"var y = base.dists.betaprime.cdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.cdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.cdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.cdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.cdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.betaprime.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.betaprime.cdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.cdf( 0.0, NaN, 1.0 )\ny = base.dists.betaprime.cdf( 0.0, 1.0, NaN )\n","base.dists.betaprime.cdf.factory":"var mycdf = base.dists.betaprime.cdf.factory( 0.5, 0.5 );\nvar y = mycdf( 0.8 )\ny = mycdf( 0.3 )\n","base.dists.betaprime.kurtosis":"var v = base.dists.betaprime.kurtosis( 2.0, 6.0 )\nv = base.dists.betaprime.kurtosis( 4.0, 12.0 )\nv = base.dists.betaprime.kurtosis( 8.0, 6.0 )\nv = base.dists.betaprime.kurtosis( 1.0, 2.8 )\nv = base.dists.betaprime.kurtosis( 1.0, -0.1 )\nv = base.dists.betaprime.kurtosis( -0.1, 5.0 )\nv = base.dists.betaprime.kurtosis( 2.0, NaN )\nv = base.dists.betaprime.kurtosis( NaN, 6.0 )\n","base.dists.betaprime.logcdf":"var y = base.dists.betaprime.logcdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.logcdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.logcdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.logcdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.logcdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.betaprime.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.betaprime.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.betaprime.logcdf( 0.0, 1.0, NaN )\n","base.dists.betaprime.logcdf.factory":"var mylogcdf = base.dists.betaprime.logcdf.factory( 0.5, 0.5 );\nvar y = mylogcdf( 0.8 )\ny = mylogcdf( 0.3 )\n","base.dists.betaprime.logpdf":"var y = base.dists.betaprime.logpdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.logpdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.logpdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.logpdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.logpdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.logpdf( 0.5, -1.0, 0.5 )\ny = base.dists.betaprime.logpdf( 0.5, 0.5, -1.0 )\ny = base.dists.betaprime.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.logpdf( 0.5, NaN, 1.0 )\ny = base.dists.betaprime.logpdf( 0.5, 1.0, NaN )\n","base.dists.betaprime.logpdf.factory":"var mylogpdf = base.dists.betaprime.logpdf.factory( 0.5, 0.5 );\nvar y = mylogpdf( 0.8 )\ny = mylogpdf( 0.3 )\n","base.dists.betaprime.mean":"var v = base.dists.betaprime.mean( 1.0, 2.0 )\nv = base.dists.betaprime.mean( 4.0, 12.0 )\nv = base.dists.betaprime.mean( 8.0, 2.0 )\n","base.dists.betaprime.mode":"var v = base.dists.betaprime.mode( 1.0, 2.0 )\nv = base.dists.betaprime.mode( 4.0, 12.0 )\nv = base.dists.betaprime.mode( 8.0, 2.0 )\n","base.dists.betaprime.pdf":"var y = base.dists.betaprime.pdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.pdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.pdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.pdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.pdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.pdf( 0.5, -1.0, 0.5 )\ny = base.dists.betaprime.pdf( 0.5, 0.5, -1.0 )\ny = base.dists.betaprime.pdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.pdf( 0.5, NaN, 1.0 )\ny = base.dists.betaprime.pdf( 0.5, 1.0, NaN )\n","base.dists.betaprime.pdf.factory":"var mypdf = base.dists.betaprime.pdf.factory( 0.5, 0.5 );\nvar y = mypdf( 0.8 )\ny = mypdf( 0.3 )\n","base.dists.betaprime.quantile":"var y = base.dists.betaprime.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.betaprime.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.betaprime.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.betaprime.quantile( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, NaN, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, 1.0, NaN )\ny = base.dists.betaprime.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, 1.0, -1.0 )\n","base.dists.betaprime.quantile.factory":"var myQuantile = base.dists.betaprime.quantile.factory( 2.0, 2.0 );\ny = myQuantile( 0.8 )\ny = myQuantile( 0.4 )\n","base.dists.betaprime.skewness":"var v = base.dists.betaprime.skewness( 2.0, 4.0 )\nv = base.dists.betaprime.skewness( 4.0, 12.0 )\nv = base.dists.betaprime.skewness( 8.0, 4.0 )\nv = base.dists.betaprime.skewness( 1.0, 2.8 )\nv = base.dists.betaprime.skewness( 1.0, -0.1 )\nv = base.dists.betaprime.skewness( -0.1, 4.0 )\nv = base.dists.betaprime.skewness( 2.0, NaN )\nv = base.dists.betaprime.skewness( NaN, 4.0 )\n","base.dists.betaprime.stdev":"var v = base.dists.betaprime.stdev( 1.0, 2.5 )\nv = base.dists.betaprime.stdev( 4.0, 12.0 )\nv = base.dists.betaprime.stdev( 8.0, 2.5 )\nv = base.dists.betaprime.stdev( 8.0, 1.0 )\nv = base.dists.betaprime.stdev( 1.0, -0.1 )\nv = base.dists.betaprime.stdev( -0.1, 3.0 )\nv = base.dists.betaprime.stdev( 2.0, NaN )\nv = base.dists.betaprime.stdev( NaN, 3.0 )\n","base.dists.betaprime.variance":"var v = base.dists.betaprime.variance( 1.0, 2.5 )\nv = base.dists.betaprime.variance( 4.0, 12.0 )\nv = base.dists.betaprime.variance( 8.0, 2.5 )\nv = base.dists.betaprime.variance( 8.0, 1.0 )\nv = base.dists.betaprime.variance( 1.0, -0.1 )\nv = base.dists.betaprime.variance( -0.1, 3.0 )\nv = base.dists.betaprime.variance( 2.0, NaN )\nv = base.dists.betaprime.variance( NaN, 3.0 )\n","base.dists.binomial.Binomial":"var binomial = base.dists.binomial.Binomial( 8, 0.5 );\nbinomial.n\nbinomial.p\nbinomial.kurtosis\nbinomial.mean\nbinomial.median\nbinomial.mode\nbinomial.skewness\nbinomial.stdev\nbinomial.variance\nbinomial.cdf( 2.9 )\nbinomial.logpmf( 3.0 )\nbinomial.mgf( 0.2 )\nbinomial.pmf( 3.0 )\nbinomial.quantile( 0.8 )\n","base.dists.binomial.cdf":"var y = base.dists.binomial.cdf( 3.0, 20, 0.2 )\ny = base.dists.binomial.cdf( 21.0, 20, 0.2 )\ny = base.dists.binomial.cdf( 5.0, 10, 0.4 )\ny = base.dists.binomial.cdf( 0.0, 10, 0.4 )\ny = base.dists.binomial.cdf( NaN, 20, 0.5 )\ny = base.dists.binomial.cdf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.cdf( 0.0, 20, NaN )\ny = base.dists.binomial.cdf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.cdf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.cdf( 2.0, 20, -1.0 )\ny = base.dists.binomial.cdf( 2.0, 20, 1.5 )\n","base.dists.binomial.cdf.factory":"var mycdf = base.dists.binomial.cdf.factory( 10, 0.5 );\nvar y = mycdf( 3.0 )\ny = mycdf( 1.0 )\n","base.dists.binomial.entropy":"var v = base.dists.binomial.entropy( 100, 0.1 )\nv = base.dists.binomial.entropy( 20, 0.5 )\nv = base.dists.binomial.entropy( 10.3, 0.5 )\nv = base.dists.binomial.entropy( 20, 1.1 )\nv = base.dists.binomial.entropy( 20, NaN )\n","base.dists.binomial.kurtosis":"var v = base.dists.binomial.kurtosis( 100, 0.1 )\nv = base.dists.binomial.kurtosis( 20, 0.5 )\nv = base.dists.binomial.kurtosis( 10.3, 0.5 )\nv = base.dists.binomial.kurtosis( 20, 1.1 )\nv = base.dists.binomial.kurtosis( 20, NaN )\n","base.dists.binomial.logpmf":"var y = base.dists.binomial.logpmf( 3.0, 20, 0.2 )\ny = base.dists.binomial.logpmf( 21.0, 20, 0.2 )\ny = base.dists.binomial.logpmf( 5.0, 10, 0.4 )\ny = base.dists.binomial.logpmf( 0.0, 10, 0.4 )\ny = base.dists.binomial.logpmf( NaN, 20, 0.5 )\ny = base.dists.binomial.logpmf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.logpmf( 0.0, 20, NaN )\ny = base.dists.binomial.logpmf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.logpmf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.logpmf( 2.0, 20, -1.0 )\ny = base.dists.binomial.logpmf( 2.0, 20, 1.5 )\n","base.dists.binomial.logpmf.factory":"var mylogpmf = base.dists.binomial.logpmf.factory( 10, 0.5 );\nvar y = mylogpmf( 3.0 )\ny = mylogpmf( 5.0 )\n","base.dists.binomial.mean":"var v = base.dists.binomial.mean( 100, 0.1 )\nv = base.dists.binomial.mean( 20, 0.5 )\nv = base.dists.binomial.mean( 10.3, 0.5 )\nv = base.dists.binomial.mean( 20, 1.1 )\nv = base.dists.binomial.mean( 20, NaN )\n","base.dists.binomial.median":"var v = base.dists.binomial.median( 100, 0.1 )\nv = base.dists.binomial.median( 20, 0.5 )\nv = base.dists.binomial.median( 10.3, 0.5 )\nv = base.dists.binomial.median( 20, 1.1 )\nv = base.dists.binomial.median( 20, NaN )\n","base.dists.binomial.mgf":"var y = base.dists.binomial.mgf( 0.5, 20, 0.2 )\ny = base.dists.binomial.mgf( 5.0, 20, 0.2 )\ny = base.dists.binomial.mgf( 0.9, 10, 0.4 )\ny = base.dists.binomial.mgf( 0.0, 10, 0.4 )\ny = base.dists.binomial.mgf( NaN, 20, 0.5 )\ny = base.dists.binomial.mgf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.mgf( 0.0, 20, NaN )\ny = base.dists.binomial.mgf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.mgf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.mgf( 2.0, 20, -1.0 )\ny = base.dists.binomial.mgf( 2.0, 20, 1.5 )\n","base.dists.binomial.mgf.factory":"var myMGF = base.dists.binomial.mgf.factory( 10, 0.5 );\nvar y = myMGF( 0.3 )\n","base.dists.binomial.mode":"var v = base.dists.binomial.mode( 100, 0.1 )\nv = base.dists.binomial.mode( 20, 0.5 )\nv = base.dists.binomial.mode( 10.3, 0.5 )\nv = base.dists.binomial.mode( 20, 1.1 )\nv = base.dists.binomial.mode( 20, NaN )\n","base.dists.binomial.pmf":"var y = base.dists.binomial.pmf( 3.0, 20, 0.2 )\ny = base.dists.binomial.pmf( 21.0, 20, 0.2 )\ny = base.dists.binomial.pmf( 5.0, 10, 0.4 )\ny = base.dists.binomial.pmf( 0.0, 10, 0.4 )\ny = base.dists.binomial.pmf( NaN, 20, 0.5 )\ny = base.dists.binomial.pmf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.pmf( 0.0, 20, NaN )\ny = base.dists.binomial.pmf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.pmf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.pmf( 2.0, 20, -1.0 )\ny = base.dists.binomial.pmf( 2.0, 20, 1.5 )\n","base.dists.binomial.pmf.factory":"var mypmf = base.dists.binomial.pmf.factory( 10, 0.5 );\nvar y = mypmf( 3.0 )\ny = mypmf( 5.0 )\n","base.dists.binomial.quantile":"var y = base.dists.binomial.quantile( 0.4, 20, 0.2 )\ny = base.dists.binomial.quantile( 0.8, 20, 0.2 )\ny = base.dists.binomial.quantile( 0.5, 10, 0.4 )\ny = base.dists.binomial.quantile( 0.0, 10, 0.4 )\ny = base.dists.binomial.quantile( 1.0, 10, 0.4 )\ny = base.dists.binomial.quantile( NaN, 20, 0.5 )\ny = base.dists.binomial.quantile( 0.2, NaN, 0.5 )\ny = base.dists.binomial.quantile( 0.2, 20, NaN )\ny = base.dists.binomial.quantile( 0.5, 1.5, 0.5 )\ny = base.dists.binomial.quantile( 0.5, -2.0, 0.5 )\ny = base.dists.binomial.quantile( 0.5, 20, -1.0 )\ny = base.dists.binomial.quantile( 0.5, 20, 1.5 )\n","base.dists.binomial.quantile.factory":"var myquantile = base.dists.binomial.quantile.factory( 10, 0.5 );\nvar y = myquantile( 0.1 )\ny = myquantile( 0.9 )\n","base.dists.binomial.skewness":"var v = base.dists.binomial.skewness( 100, 0.1 )\nv = base.dists.binomial.skewness( 20, 0.5 )\nv = base.dists.binomial.skewness( 10.3, 0.5 )\nv = base.dists.binomial.skewness( 20, 1.1 )\nv = base.dists.binomial.skewness( 20, NaN )\n","base.dists.binomial.stdev":"var v = base.dists.binomial.stdev( 100, 0.1 )\nv = base.dists.binomial.stdev( 20, 0.5 )\nv = base.dists.binomial.stdev( 10.3, 0.5 )\nv = base.dists.binomial.stdev( 20, 1.1 )\nv = base.dists.binomial.stdev( 20, NaN )\n","base.dists.binomial.variance":"var v = base.dists.binomial.variance( 100, 0.1 )\nv = base.dists.binomial.variance( 20, 0.5 )\nv = base.dists.binomial.variance( 10.3, 0.5 )\nv = base.dists.binomial.variance( 20, 1.1 )\nv = base.dists.binomial.variance( 20, NaN )\n","base.dists.cauchy.Cauchy":"var cauchy = base.dists.cauchy.Cauchy( 0.0, 1.0 );\ncauchy.x0\ncauchy.gamma\ncauchy.entropy\ncauchy.median\ncauchy.mode\ncauchy.cdf( 0.8 )\ncauchy.logcdf( 1.0 )\ncauchy.logpdf( 1.0 )\ncauchy.pdf( 1.0 )\ncauchy.quantile( 0.8 )\n","base.dists.cauchy.cdf":"var y = base.dists.cauchy.cdf( 4.0, 0.0, 2.0 )\ny = base.dists.cauchy.cdf( 1.0, 0.0, 2.0 )\ny = base.dists.cauchy.cdf( 1.0, 3.0, 2.0 )\ny = base.dists.cauchy.cdf( NaN, 0.0, 2.0 )\ny = base.dists.cauchy.cdf( 1.0, 2.0, NaN )\ny = base.dists.cauchy.cdf( 1.0, NaN, 3.0 )\n","base.dists.cauchy.cdf.factory":"var myCDF = base.dists.cauchy.cdf.factory( 1.5, 3.0 );\nvar y = myCDF( 1.0 )\n","base.dists.cauchy.entropy":"var v = base.dists.cauchy.entropy( 10.0, 7.0 )\nv = base.dists.cauchy.entropy( 22.0, 0.5 )\nv = base.dists.cauchy.entropy( 10.3, -0.5 )\n","base.dists.cauchy.logcdf":"var y = base.dists.cauchy.logcdf( 4.0, 0.0, 2.0 )\ny = base.dists.cauchy.logcdf( 1.0, 0.0, 2.0 )\ny = base.dists.cauchy.logcdf( 1.0, 3.0, 2.0 )\ny = base.dists.cauchy.logcdf( NaN, 0.0, 2.0 )\ny = base.dists.cauchy.logcdf( 1.0, 2.0, NaN )\ny = base.dists.cauchy.logcdf( 1.0, NaN, 3.0 )\n","base.dists.cauchy.logcdf.factory":"var mylogCDF = base.dists.cauchy.logcdf.factory( 1.5, 3.0 );\nvar y = mylogCDF( 1.0 )\n","base.dists.cauchy.logpdf":"var y = base.dists.cauchy.logpdf( 2.0, 1.0, 1.0 )\ny = base.dists.cauchy.logpdf( 4.0, 3.0, 0.1 )\ny = base.dists.cauchy.logpdf( 4.0, 3.0, 3.0 )\ny = base.dists.cauchy.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.cauchy.logpdf( 2.0, NaN, 1.0 )\ny = base.dists.cauchy.logpdf( 2.0, 1.0, NaN )\ny = base.dists.cauchy.logpdf( 2.0, 1.0, -2.0 )\n","base.dists.cauchy.logpdf.factory":"var mylogPDF = base.dists.cauchy.logpdf.factory( 10.0, 2.0 );\nvar y = mylogPDF( 10.0 )\n","base.dists.cauchy.median":"var v = base.dists.cauchy.median( 10.0, 5.0 )\nv = base.dists.cauchy.median( 7.0, 0.5 )\nv = base.dists.cauchy.median( 10.3, -0.5 )\n","base.dists.cauchy.mode":"var v = base.dists.cauchy.mode( 10.0, 5.0 )\nv = base.dists.cauchy.mode( 7.0, 0.5 )\nv = base.dists.cauchy.mode( 10.3, -0.5 )\n","base.dists.cauchy.pdf":"var y = base.dists.cauchy.pdf( 2.0, 1.0, 1.0 )\ny = base.dists.cauchy.pdf( 4.0, 3.0, 0.1 )\ny = base.dists.cauchy.pdf( 4.0, 3.0, 3.0 )\ny = base.dists.cauchy.pdf( NaN, 1.0, 1.0 )\ny = base.dists.cauchy.pdf( 2.0, NaN, 1.0 )\ny = base.dists.cauchy.pdf( 2.0, 1.0, NaN )\ny = base.dists.cauchy.pdf( 2.0, 1.0, -2.0 )\n","base.dists.cauchy.pdf.factory":"var myPDF = base.dists.cauchy.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\n","base.dists.cauchy.quantile":"var y = base.dists.cauchy.quantile( 0.3, 2.0, 2.0 )\ny = base.dists.cauchy.quantile( 0.8, 10, 2.0 )\ny = base.dists.cauchy.quantile( 0.1, 10.0, 2.0 )\ny = base.dists.cauchy.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.cauchy.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.cauchy.quantile( NaN, 0.0, 1.0 )\ny = base.dists.cauchy.quantile( 0.0, NaN, 1.0 )\ny = base.dists.cauchy.quantile( 0.0, 0.0, NaN )\ny = base.dists.cauchy.quantile( 0.5, 0.0, -1.0 )\n","base.dists.cauchy.quantile.factory":"var myQuantile = base.dists.cauchy.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.chi.cdf":"var y = base.dists.chi.cdf( 2.0, 3.0 )\ny = base.dists.chi.cdf( 1.0, 0.5 )\ny = base.dists.chi.cdf( -1.0, 4.0 )\ny = base.dists.chi.cdf( NaN, 1.0 )\ny = base.dists.chi.cdf( 0.0, NaN )\ny = base.dists.chi.cdf( 2.0, -1.0 )\ny = base.dists.chi.cdf( 2.0, 0.0 )\ny = base.dists.chi.cdf( -2.0, 0.0 )\ny = base.dists.chi.cdf( 0.0, 0.0 )\n","base.dists.chi.cdf.factory":"var mycdf = base.dists.chi.cdf.factory( 1.0 );\nvar y = mycdf( 2.0 )\ny = mycdf( 1.2 )\n","base.dists.chi.Chi":"var chi = base.dists.chi.Chi( 6.0 );\nchi.k\nchi.entropy\nchi.kurtosis\nchi.mean\nchi.mode\nchi.skewness\nchi.stdev\nchi.variance\nchi.cdf( 1.0 )\nchi.logpdf( 1.5 )\nchi.pdf( 1.5 )\nchi.quantile( 0.5 )\n","base.dists.chi.entropy":"var v = base.dists.chi.entropy( 11.0 )\nv = base.dists.chi.entropy( 1.5 )\n","base.dists.chi.kurtosis":"var v = base.dists.chi.kurtosis( 9.0 )\nv = base.dists.chi.kurtosis( 1.5 )\n","base.dists.chi.logpdf":"var y = base.dists.chi.logpdf( 0.3, 4.0 )\ny = base.dists.chi.logpdf( 0.7, 0.7 )\ny = base.dists.chi.logpdf( -1.0, 0.5 )\ny = base.dists.chi.logpdf( 0.0, NaN )\ny = base.dists.chi.logpdf( NaN, 2.0 )\ny = base.dists.chi.logpdf( 2.0, -1.0 )\ny = base.dists.chi.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.chi.logpdf( 0.0, 0.0, 2.0 )\n","base.dists.chi.logpdf.factory":"var mylogPDF = base.dists.chi.logpdf.factory( 6.0 );\nvar y = mylogPDF( 3.0 )\n","base.dists.chi.mean":"var v = base.dists.chi.mean( 11.0 )\nv = base.dists.chi.mean( 4.5 )\n","base.dists.chi.mode":"var v = base.dists.chi.mode( 11.0 )\nv = base.dists.chi.mode( 1.5 )\n","base.dists.chi.pdf":"var y = base.dists.chi.pdf( 0.3, 4.0 )\ny = base.dists.chi.pdf( 0.7, 0.7 )\ny = base.dists.chi.pdf( -1.0, 0.5 )\ny = base.dists.chi.pdf( 0.0, NaN )\ny = base.dists.chi.pdf( NaN, 2.0 )\ny = base.dists.chi.pdf( 2.0, -1.0 )\ny = base.dists.chi.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.chi.pdf( 0.0, 0.0, 2.0 )\n","base.dists.chi.pdf.factory":"var myPDF = base.dists.chi.pdf.factory( 6.0 );\nvar y = myPDF( 3.0 )\n","base.dists.chi.quantile":"var y = base.dists.chi.quantile( 0.8, 1.0 )\ny = base.dists.chi.quantile( 0.5, 4.0 )\ny = base.dists.chi.quantile( 0.8, 0.1 )\ny = base.dists.chi.quantile( -0.2, 0.5 )\ny = base.dists.chi.quantile( 1.1, 0.5 )\ny = base.dists.chi.quantile( NaN, 1.0 )\ny = base.dists.chi.quantile( 0.0, NaN )\ny = base.dists.chi.quantile( 0.5, -1.0 )\ny = base.dists.chi.quantile( 0.3, 0.0 )\ny = base.dists.chi.quantile( 0.9, 0.0 )\n","base.dists.chi.quantile.factory":"var myquantile = base.dists.chi.quantile.factory( 2.0 );\nvar y = myquantile( 0.3 )\ny = myquantile( 0.7 )\n","base.dists.chi.skewness":"var v = base.dists.chi.skewness( 11.0 )\nv = base.dists.chi.skewness( 1.5 )\n","base.dists.chi.stdev":"var v = base.dists.chi.stdev( 11.0 )\nv = base.dists.chi.stdev( 1.5 )\n","base.dists.chi.variance":"var v = base.dists.chi.variance( 11.0 )\nv = base.dists.chi.variance( 1.5 )\n","base.dists.chisquare.cdf":"var y = base.dists.chisquare.cdf( 2.0, 3.0 )\ny = base.dists.chisquare.cdf( 1.0, 0.5 )\ny = base.dists.chisquare.cdf( -1.0, 4.0 )\ny = base.dists.chisquare.cdf( NaN, 1.0 )\ny = base.dists.chisquare.cdf( 0.0, NaN )\ny = base.dists.chisquare.cdf( 2.0, -1.0 )\ny = base.dists.chisquare.cdf( 2.0, 0.0 )\ny = base.dists.chisquare.cdf( -2.0, 0.0 )\ny = base.dists.chisquare.cdf( 0.0, 0.0 )\n","base.dists.chisquare.cdf.factory":"var mycdf = base.dists.chisquare.cdf.factory( 1.0 );\nvar y = mycdf( 2.0 )\ny = mycdf( 1.2 )\n","base.dists.chisquare.ChiSquare":"var chisquare = base.dists.chisquare.ChiSquare( 6.0 );\nchisquare.k\nchisquare.entropy\nchisquare.kurtosis\nchisquare.mean\nchisquare.median\nchisquare.mode\nchisquare.skewness\nchisquare.stdev\nchisquare.variance\nchisquare.cdf( 3.0 )\nchisquare.mgf( 0.2 )\nchisquare.pdf( 1.5 )\nchisquare.quantile( 0.5 )\n","base.dists.chisquare.entropy":"var v = base.dists.chisquare.entropy( 11.0 )\nv = base.dists.chisquare.entropy( 1.5 )\n","base.dists.chisquare.kurtosis":"var v = base.dists.chisquare.kurtosis( 9.0 )\nv = base.dists.chisquare.kurtosis( 1.5 )\n","base.dists.chisquare.logpdf":"var y = base.dists.chisquare.logpdf( 0.3, 4.0 )\ny = base.dists.chisquare.logpdf( 0.7, 0.7 )\ny = base.dists.chisquare.logpdf( -1.0, 0.5 )\ny = base.dists.chisquare.logpdf( 0.0, NaN )\ny = base.dists.chisquare.logpdf( NaN, 2.0 )\ny = base.dists.chisquare.logpdf( 2.0, -1.0 )\ny = base.dists.chisquare.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.chisquare.logpdf( 0.0, 0.0, 2.0 )\n","base.dists.chisquare.logpdf.factory":"var myLogPDF = base.dists.chisquare.logpdf.factory( 6.0 );\nvar y = myLogPDF( 3.0 )\n","base.dists.chisquare.mean":"var v = base.dists.chisquare.mean( 11.0 )\nv = base.dists.chisquare.mean( 4.5 )\n","base.dists.chisquare.median":"var k = base.dists.chisquare.median( 9.0 )\nk = base.dists.chisquare.median( 2.0 )\n","base.dists.chisquare.mgf":"var y = base.dists.chisquare.mgf( 0.4, 2 )\ny = base.dists.chisquare.mgf( -1.0, 5.0 )\ny = base.dists.chisquare.mgf( 0.0, 10.0 )\n","base.dists.chisquare.mgf.factory":"var mymgf = base.dists.chisquare.mgf.factory( 1.0 );\nvar y = mymgf( 0.2 )\ny = mymgf( 0.4 )\n","base.dists.chisquare.mode":"var v = base.dists.chisquare.mode( 11.0 )\nv = base.dists.chisquare.mode( 1.5 )\n","base.dists.chisquare.pdf":"var y = base.dists.chisquare.pdf( 0.3, 4.0 )\ny = base.dists.chisquare.pdf( 0.7, 0.7 )\ny = base.dists.chisquare.pdf( -1.0, 0.5 )\ny = base.dists.chisquare.pdf( 0.0, NaN )\ny = base.dists.chisquare.pdf( NaN, 2.0 )\ny = base.dists.chisquare.pdf( 2.0, -1.0 )\ny = base.dists.chisquare.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.chisquare.pdf( 0.0, 0.0, 2.0 )\n","base.dists.chisquare.pdf.factory":"var myPDF = base.dists.chisquare.pdf.factory( 6.0 );\nvar y = myPDF( 3.0 )\n","base.dists.chisquare.quantile":"var y = base.dists.chisquare.quantile( 0.8, 1.0 )\ny = base.dists.chisquare.quantile( 0.5, 4.0 )\ny = base.dists.chisquare.quantile( 0.8, 0.1 )\ny = base.dists.chisquare.quantile( -0.2, 0.5 )\ny = base.dists.chisquare.quantile( 1.1, 0.5 )\ny = base.dists.chisquare.quantile( NaN, 1.0 )\ny = base.dists.chisquare.quantile( 0.0, NaN )\ny = base.dists.chisquare.quantile( 0.5, -1.0 )\ny = base.dists.chisquare.quantile( 0.3, 0.0 )\ny = base.dists.chisquare.quantile( 0.9, 0.0 )\n","base.dists.chisquare.quantile.factory":"var myquantile = base.dists.chisquare.quantile.factory( 2.0 );\nvar y = myquantile( 0.3 )\ny = myquantile( 0.7 )\n","base.dists.chisquare.skewness":"var v = base.dists.chisquare.skewness( 11.0 )\nv = base.dists.chisquare.skewness( 1.5 )\n","base.dists.chisquare.stdev":"var v = base.dists.chisquare.stdev( 11.0 )\nv = base.dists.chisquare.stdev( 1.5 )\n","base.dists.chisquare.variance":"var v = base.dists.chisquare.variance( 11.0 )\nv = base.dists.chisquare.variance( 1.5 )\n","base.dists.cosine.cdf":"var y = base.dists.cosine.cdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.cdf( 9.0, 10.0, 3.0 )\ny = base.dists.cosine.cdf( 2.0, 0.0, NaN )\ny = base.dists.cosine.cdf( 2.0, NaN, 1.0 )\ny = base.dists.cosine.cdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.cdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.cdf( 8.0, 8.0, 0.0 )\ny = base.dists.cosine.cdf( 10.0, 8.0, 0.0 )\n","base.dists.cosine.cdf.factory":"var mycdf = base.dists.cosine.cdf.factory( 3.0, 1.5 );\nvar y = mycdf( 1.9 )\n","base.dists.cosine.Cosine":"var cosine = base.dists.cosine.Cosine( -2.0, 3.0 );\ncosine.mu\ncosine.s\ncosine.kurtosis\ncosine.mean\ncosine.median\ncosine.mode\ncosine.skewness\ncosine.stdev\ncosine.variance\ncosine.cdf( 0.5 )\ncosine.logcdf( 0.5 )\ncosine.logpdf( -1.0 )\ncosine.mgf( 0.2 )\ncosine.pdf( -2.0 )\ncosine.quantile( 0.9 )\n","base.dists.cosine.kurtosis":"var y = base.dists.cosine.kurtosis( 0.0, 1.0 )\ny = base.dists.cosine.kurtosis( 4.0, 2.0 )\ny = base.dists.cosine.kurtosis( NaN, 1.0 )\ny = base.dists.cosine.kurtosis( 0.0, NaN )\ny = base.dists.cosine.kurtosis( 0.0, 0.0 )\n","base.dists.cosine.logcdf":"var y = base.dists.cosine.logcdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.logcdf( 9.0, 10.0, 3.0 )\ny = base.dists.cosine.logcdf( 2.0, 0.0, NaN )\ny = base.dists.cosine.logcdf( 2.0, NaN, 1.0 )\ny = base.dists.cosine.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.logcdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.logcdf( 8.0, 8.0, 0.0 )\ny = base.dists.cosine.logcdf( 10.0, 8.0, 0.0 )\n","base.dists.cosine.logcdf.factory":"var mylogcdf = base.dists.cosine.logcdf.factory( 3.0, 1.5 );\nvar y = mylogcdf( 1.9 )\n","base.dists.cosine.logpdf":"var y = base.dists.cosine.logpdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.logpdf( -1.0, 2.0, 4.0 )\ny = base.dists.cosine.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.cosine.logpdf( 0.0, 0.0, NaN )\ny = base.dists.cosine.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.cosine.logpdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.logpdf( 8.0, 8.0, 0.0 )\n","base.dists.cosine.logpdf.factory":"var mylogpdf = base.dists.cosine.logpdf.factory( 10.0, 2.0 );\nvar y = mylogpdf( 10.0 )\n","base.dists.cosine.mean":"var y = base.dists.cosine.mean( 0.0, 1.0 )\ny = base.dists.cosine.mean( 4.0, 2.0 )\ny = base.dists.cosine.mean( NaN, 1.0 )\ny = base.dists.cosine.mean( 0.0, NaN )\ny = base.dists.cosine.mean( 0.0, 0.0 )\n","base.dists.cosine.median":"var y = base.dists.cosine.median( 0.0, 1.0 )\ny = base.dists.cosine.median( 4.0, 2.0 )\ny = base.dists.cosine.median( NaN, 1.0 )\ny = base.dists.cosine.median( 0.0, NaN )\ny = base.dists.cosine.median( 0.0, 0.0 )\n","base.dists.cosine.mgf":"var y = base.dists.cosine.mgf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.mgf( 9.0, 10.0, 3.0 )\ny = base.dists.cosine.mgf( 0.5, 0.0, NaN )\ny = base.dists.cosine.mgf( 0.5, NaN, 1.0 )\ny = base.dists.cosine.mgf( NaN, 0.0, 1.0 )\n","base.dists.cosine.mgf.factory":"var mymgf = base.dists.cosine.mgf.factory( 3.0, 1.5 );\nvar y = mymgf( 1.9 )\n","base.dists.cosine.mode":"var y = base.dists.cosine.mode( 0.0, 1.0 )\ny = base.dists.cosine.mode( 4.0, 2.0 )\ny = base.dists.cosine.mode( NaN, 1.0 )\ny = base.dists.cosine.mode( 0.0, NaN )\ny = base.dists.cosine.mode( 0.0, 0.0 )\n","base.dists.cosine.pdf":"var y = base.dists.cosine.pdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.pdf( 2.4, 4.0, 2.0 )\ny = base.dists.cosine.pdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.pdf( 0.0, NaN, 1.0 )\ny = base.dists.cosine.pdf( 0.0, 0.0, NaN )\ny = base.dists.cosine.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.cosine.pdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.pdf( 8.0, 8.0, 0.0 )\n","base.dists.cosine.pdf.factory":"var myPDF = base.dists.cosine.pdf.factory( 0.0, 3.0 );\nvar y = myPDF( 2.0 )\n","base.dists.cosine.quantile":"var y = base.dists.cosine.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.cosine.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.cosine.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.cosine.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.cosine.quantile( NaN, 0.0, 1.0 )\ny = base.dists.cosine.quantile( 0.0, NaN, 1.0 )\ny = base.dists.cosine.quantile( 0.0, 0.0, NaN )\ny = base.dists.cosine.quantile( 0.5, 0.0, -1.0 )\n","base.dists.cosine.quantile.factory":"var myQuantile = base.dists.cosine.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.3 )\n","base.dists.cosine.skewness":"var y = base.dists.cosine.skewness( 0.0, 1.0 )\ny = base.dists.cosine.skewness( 4.0, 2.0 )\ny = base.dists.cosine.skewness( NaN, 1.0 )\ny = base.dists.cosine.skewness( 0.0, NaN )\ny = base.dists.cosine.skewness( 0.0, 0.0 )\n","base.dists.cosine.stdev":"var y = base.dists.cosine.stdev( 0.0, 1.0 )\ny = base.dists.cosine.stdev( 4.0, 2.0 )\ny = base.dists.cosine.stdev( NaN, 1.0 )\ny = base.dists.cosine.stdev( 0.0, NaN )\ny = base.dists.cosine.stdev( 0.0, 0.0 )\n","base.dists.cosine.variance":"var y = base.dists.cosine.variance( 0.0, 1.0 )\ny = base.dists.cosine.variance( 4.0, 2.0 )\ny = base.dists.cosine.variance( NaN, 1.0 )\ny = base.dists.cosine.variance( 0.0, NaN )\ny = base.dists.cosine.variance( 0.0, 0.0 )\n","base.dists.degenerate.cdf":"var y = base.dists.degenerate.cdf( 2.0, 3.0 )\ny = base.dists.degenerate.cdf( 4.0, 3.0 )\ny = base.dists.degenerate.cdf( 3.0, 3.0 )\ny = base.dists.degenerate.cdf( NaN, 0.0 )\ny = base.dists.degenerate.cdf( 0.0, NaN )\n","base.dists.degenerate.cdf.factory":"var myCDF = base.dists.degenerate.cdf.factory( 5.0 );\nvar y = myCDF( 3.0 )\ny = myCDF( 6.0 )\n","base.dists.degenerate.Degenerate":"var degenerate = base.dists.degenerate.Degenerate( 2.0 );\ndegenerate.mu\ndegenerate.entropy\ndegenerate.mean\ndegenerate.mode\ndegenerate.median\ndegenerate.stdev\ndegenerate.variance\ndegenerate.cdf( 0.5 )\ndegenerate.logcdf( 2.5 )\ndegenerate.logpdf( 0.5 )\ndegenerate.logpmf( 2.5 )\ndegenerate.mgf( 0.2 )\ndegenerate.pdf( 2.0 )\ndegenerate.pmf( 2.0 )\ndegenerate.quantile( 0.7 )\n","base.dists.degenerate.entropy":"var v = base.dists.degenerate.entropy( 20.0 )\nv = base.dists.degenerate.entropy( -10.0 )\n","base.dists.degenerate.logcdf":"var y = base.dists.degenerate.logcdf( 2.0, 3.0 )\ny = base.dists.degenerate.logcdf( 4.0, 3.0 )\ny = base.dists.degenerate.logcdf( 3.0, 3.0 )\ny = base.dists.degenerate.logcdf( NaN, 0.0 )\ny = base.dists.degenerate.logcdf( 0.0, NaN )\n","base.dists.degenerate.logcdf.factory":"var mylogcdf = base.dists.degenerate.logcdf.factory( 5.0 );\nvar y = mylogcdf( 3.0 )\ny = mylogcdf( 6.0 )\n","base.dists.degenerate.logpdf":"var y = base.dists.degenerate.logpdf( 2.0, 3.0 )\ny = base.dists.degenerate.logpdf( 3.0, 3.0 )\ny = base.dists.degenerate.logpdf( NaN, 0.0 )\ny = base.dists.degenerate.logpdf( 0.0, NaN )\n","base.dists.degenerate.logpdf.factory":"var mylogPDF = base.dists.degenerate.logpdf.factory( 10.0 );\nvar y = mylogPDF( 10.0 )\n","base.dists.degenerate.logpmf":"var y = base.dists.degenerate.logpmf( 2.0, 3.0 )\ny = base.dists.degenerate.logpmf( 3.0, 3.0 )\ny = base.dists.degenerate.logpmf( NaN, 0.0 )\ny = base.dists.degenerate.logpmf( 0.0, NaN )\n","base.dists.degenerate.logpmf.factory":"var mylogPMF = base.dists.degenerate.logpmf.factory( 10.0 );\nvar y = mylogPMF( 10.0 )\n","base.dists.degenerate.mean":"var v = base.dists.degenerate.mean( 20.0 )\nv = base.dists.degenerate.mean( -10.0 )\n","base.dists.degenerate.median":"var v = base.dists.degenerate.median( 20.0 )\nv = base.dists.degenerate.median( -10.0 )\n","base.dists.degenerate.mgf":"var y = base.dists.degenerate.mgf( 1.0, 1.0 )\ny = base.dists.degenerate.mgf( 2.0, 3.0 )\ny = base.dists.degenerate.mgf( NaN, 0.0 )\ny = base.dists.degenerate.mgf( 0.0, NaN )\n","base.dists.degenerate.mgf.factory":"var myMGF = base.dists.degenerate.mgf.factory( 10.0 );\nvar y = myMGF( 0.1 )\n","base.dists.degenerate.mode":"var v = base.dists.degenerate.mode( 20.0 )\nv = base.dists.degenerate.mode( -10.0 )\n","base.dists.degenerate.pdf":"var y = base.dists.degenerate.pdf( 2.0, 3.0 )\ny = base.dists.degenerate.pdf( 3.0, 3.0 )\ny = base.dists.degenerate.pdf( NaN, 0.0 )\ny = base.dists.degenerate.pdf( 0.0, NaN )\n","base.dists.degenerate.pdf.factory":"var myPDF = base.dists.degenerate.pdf.factory( 10.0 );\nvar y = myPDF( 10.0 )\n","base.dists.degenerate.pmf":"var y = base.dists.degenerate.pmf( 2.0, 3.0 )\ny = base.dists.degenerate.pmf( 3.0, 3.0 )\ny = base.dists.degenerate.pmf( NaN, 0.0 )\ny = base.dists.degenerate.pmf( 0.0, NaN )\n","base.dists.degenerate.pmf.factory":"var myPMF = base.dists.degenerate.pmf.factory( 10.0 );\nvar y = myPMF( 10.0 )\n","base.dists.degenerate.quantile":"var y = base.dists.degenerate.quantile( 0.5, 2.0 )\ny = base.dists.degenerate.quantile( 0.9, 4.0 )\ny = base.dists.degenerate.quantile( 1.1, 0.0 )\ny = base.dists.degenerate.quantile( -0.2, 0.0 )\ny = base.dists.degenerate.quantile( NaN, 0.0 )\ny = base.dists.degenerate.quantile( 0.0, NaN )\n","base.dists.degenerate.quantile.factory":"var myQuantile = base.dists.degenerate.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 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);\nvar y = myLogPMF( 7.0 )\ny = myLogPMF( 5.0 )\n","base.dists.discreteUniform.mean":"var v = base.dists.discreteUniform.mean( -2, 2 )\nv = base.dists.discreteUniform.mean( 4, 12 )\nv = base.dists.discreteUniform.mean( 2, 8 )\n","base.dists.discreteUniform.median":"var v = base.dists.discreteUniform.median( -2, 2 )\nv = base.dists.discreteUniform.median( 4, 12 )\nv = base.dists.discreteUniform.median( 2, 8 )\n","base.dists.discreteUniform.mgf":"var y = base.dists.discreteUniform.mgf( 2.0, 0, 4 )\ny = base.dists.discreteUniform.mgf( -0.2, 0, 4 )\ny = base.dists.discreteUniform.mgf( 2.0, 0, 1 )\ny = base.dists.discreteUniform.mgf( 0.5, 3, 2 )\ny = base.dists.discreteUniform.mgf( NaN, 0, 1  )\ny = base.dists.discreteUniform.mgf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.mgf( 0.0, 0, NaN )\n","base.dists.discreteUniform.mgf.factory":"var mymgf = base.dists.discreteUniform.mgf.factory( 6, 7 );\nvar y = mymgf( 0.1 )\ny = mymgf( 1.1 )\n","base.dists.discreteUniform.pmf":"var y = base.dists.discreteUniform.pmf( 2.0, 0, 4 )\ny = base.dists.discreteUniform.pmf( 5.0, 0, 4 )\ny = base.dists.discreteUniform.pmf( 3.0, -4, 4 )\ny = base.dists.discreteUniform.pmf( NaN, 0, 1 )\ny = base.dists.discreteUniform.pmf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.pmf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.pmf( 2.0, 3, 1 )\ny = base.dists.discreteUniform.pmf( 2.0, 1, 2.4 )\n","base.dists.discreteUniform.pmf.factory":"var myPMF = base.dists.discreteUniform.pmf.factory( 6, 7 );\nvar y = myPMF( 7.0 )\ny = myPMF( 5.0 )\n","base.dists.discreteUniform.quantile":"var y = base.dists.discreteUniform.quantile( 0.8, 0, 1 )\ny = base.dists.discreteUniform.quantile( 0.5, 0.0, 10.0 )\ny = base.dists.discreteUniform.quantile( 1.1, 0, 4 )\ny = base.dists.discreteUniform.quantile( -0.2, 0, 4 )\ny = base.dists.discreteUniform.quantile( NaN, -2, 2 )\ny = base.dists.discreteUniform.quantile( 0.1, NaN, 2 )\ny = base.dists.discreteUniform.quantile( 0.1, -2, NaN )\ny = base.dists.discreteUniform.quantile( 0.5, 2, 1 )\n","base.dists.discreteUniform.quantile.factory":"var myQuantile = base.dists.discreteUniform.quantile.factory( 0, 4 );\nvar y = myQuantile( 0.8 )\n","base.dists.discreteUniform.skewness":"var v = base.dists.discreteUniform.skewness( -2, 2 )\nv = base.dists.discreteUniform.skewness( 4, 12 )\nv = base.dists.discreteUniform.skewness( 2, 8 )\n","base.dists.discreteUniform.stdev":"var v = base.dists.discreteUniform.stdev( 0, 1 )\nv = base.dists.discreteUniform.stdev( 4, 12 )\nv = base.dists.discreteUniform.stdev( 2, 8 )\n","base.dists.discreteUniform.variance":"var v = base.dists.discreteUniform.variance( 0, 1 )\nv = base.dists.discreteUniform.variance( 4, 12 )\nv = base.dists.discreteUniform.variance( 2, 8 )\n","base.dists.erlang.cdf":"var y = base.dists.erlang.cdf( 2.0, 1, 1.0 )\ny = base.dists.erlang.cdf( 2.0, 3, 1.0 )\ny = base.dists.erlang.cdf( 2.0, 2.5, 1.0 )\ny = base.dists.erlang.cdf( -1.0, 2, 2.0 )\ny = base.dists.erlang.cdf( PINF, 4, 2.0 )\ny = base.dists.erlang.cdf( NINF, 4, 2.0 )\ny = base.dists.erlang.cdf( NaN, 0, 1.0 )\ny = base.dists.erlang.cdf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.cdf( 0.0, 0, NaN )\ny = base.dists.erlang.cdf( 2.0, -1, 1.0 )\ny = base.dists.erlang.cdf( 2.0, 1, -1.0 )\n","base.dists.erlang.cdf.factory":"var mycdf = base.dists.erlang.cdf.factory( 2, 0.5 );\nvar y = mycdf( 6.0 )\ny = mycdf( 2.0 )\n","base.dists.erlang.entropy":"var v = base.dists.erlang.entropy( 1, 1.0 )\nv = base.dists.erlang.entropy( 4, 12.0 )\nv = base.dists.erlang.entropy( 8, 2.0 )\n","base.dists.erlang.Erlang":"var erlang = base.dists.erlang.Erlang( 6, 5.0 );\nerlang.k\nerlang.lambda\nerlang.entropy\nerlang.kurtosis\nerlang.mean\nerlang.mode\nerlang.skewness\nerlang.stdev\nerlang.variance\nerlang.cdf( 3.0 )\nerlang.logpdf( 3.0 )\nerlang.mgf( -0.5 )\nerlang.pdf( 3.0 )\nerlang.quantile( 0.8 )\n","base.dists.erlang.kurtosis":"var v = base.dists.erlang.kurtosis( 1, 1.0 )\nv = base.dists.erlang.kurtosis( 4, 12.0 )\nv = base.dists.erlang.kurtosis( 8, 2.0 )\n","base.dists.erlang.logpdf":"var y = base.dists.erlang.logpdf( 0.1, 1, 1.0 )\ny = base.dists.erlang.logpdf( 0.5, 2, 2.5 )\ny = base.dists.erlang.logpdf( -1.0, 4, 2.0 )\ny = base.dists.erlang.logpdf( NaN, 1, 1.0 )\ny = base.dists.erlang.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.logpdf( 0.0, 1, NaN )\ny = base.dists.erlang.logpdf( 2.0, -2, 0.5 )\ny = base.dists.erlang.logpdf( 2.0, 0.5, 0.5 )\ny = base.dists.erlang.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.erlang.logpdf( 0.0, 0.0, 2.0 )\ny = base.dists.erlang.logpdf( 2.0, 1, 0.0 )\ny = base.dists.erlang.logpdf( 2.0, 1, -1.0 )\n","base.dists.erlang.logpdf.factory":"var myLogPDF = base.dists.erlang.logpdf.factory( 6.0, 7.0 );\ny = myLogPDF( 7.0 )\n","base.dists.erlang.mean":"var v = base.dists.erlang.mean( 1, 1.0 )\nv = base.dists.erlang.mean( 4, 12.0 )\nv = base.dists.erlang.mean( 8, 2.0 )\n","base.dists.erlang.mgf":"var y = base.dists.erlang.mgf( 0.3, 1, 1.0 )\ny = base.dists.erlang.mgf( 2.0, 2, 3.0 )\ny = base.dists.erlang.mgf( -1.0, 2, 2.0 )\ny = base.dists.erlang.mgf( NaN, 1, 1.0 )\ny = base.dists.erlang.mgf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.mgf( 0.0, 1, NaN )\ny = base.dists.erlang.mgf( 0.2, -2, 0.5 )\ny = base.dists.erlang.mgf( 0.2, 0.5, 0.5 )\ny = base.dists.erlang.mgf( 0.2, 1, 0.0 )\ny = base.dists.erlang.mgf( 0.2, 1, -5.0 )\n","base.dists.erlang.mgf.factory":"var myMGF = base.dists.erlang.mgf.factory( 2, 0.5 );\nvar y = myMGF( 0.2 )\ny = myMGF( -0.5 )\n","base.dists.erlang.mode":"var v = base.dists.erlang.mode( 1, 1.0 )\nv = base.dists.erlang.mode( 4, 12.0 )\nv = base.dists.erlang.mode( 8, 2.0 )\n","base.dists.erlang.pdf":"var y = base.dists.erlang.pdf( 0.1, 1, 1.0 )\ny = base.dists.erlang.pdf( 0.5, 2, 2.5 )\ny = base.dists.erlang.pdf( -1.0, 4, 2.0 )\ny = base.dists.erlang.pdf( NaN, 1, 1.0 )\ny = base.dists.erlang.pdf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.pdf( 0.0, 1, NaN )\ny = base.dists.erlang.pdf( 2.0, -2, 0.5 )\ny = base.dists.erlang.pdf( 2.0, 0.5, 0.5 )\ny = base.dists.erlang.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.erlang.pdf( 0.0, 0.0, 2.0 )\ny = base.dists.erlang.pdf( 2.0, 1, 0.0 )\ny = base.dists.erlang.pdf( 2.0, 1, -1.0 )\n","base.dists.erlang.pdf.factory":"var myPDF = base.dists.erlang.pdf.factory( 6.0, 7.0 );\ny = myPDF( 7.0 )\n","base.dists.erlang.quantile":"var y = base.dists.erlang.quantile( 0.8, 2, 1.0 )\ny = base.dists.erlang.quantile( 0.5, 4, 2.0 )\ny = base.dists.erlang.quantile( 1.1, 1, 1.0 )\ny = base.dists.erlang.quantile( -0.2, 1, 1.0 )\ny = base.dists.erlang.quantile( NaN, 1, 1.0 )\ny = base.dists.erlang.quantile( 0.0, NaN, 1.0 )\ny = base.dists.erlang.quantile( 0.0, 1, NaN )\ny = base.dists.erlang.quantile( 0.5, 0.5, 1.0 )\ny = base.dists.erlang.quantile( 0.5, -1, 1.0 )\ny = base.dists.erlang.quantile( 0.5, 1, -1.0 )\n","base.dists.erlang.quantile.factory":"var myQuantile = base.dists.erlang.quantile.factory( 10, 2.0 );\nvar y = myQuantile( 0.4 )\n","base.dists.erlang.skewness":"var v = base.dists.erlang.skewness( 1, 1.0 )\nv = base.dists.erlang.skewness( 4, 12.0 )\nv = base.dists.erlang.skewness( 8, 2.0 )\n","base.dists.erlang.stdev":"var v = base.dists.erlang.stdev( 1, 1.0 )\nv = base.dists.erlang.stdev( 4, 12.0 )\nv = base.dists.erlang.stdev( 8, 2.0 )\n","base.dists.erlang.variance":"var v = base.dists.erlang.variance( 1, 1.0 )\nv = base.dists.erlang.variance( 4, 12.0 )\nv = base.dists.erlang.variance( 8, 2.0 )\n","base.dists.exponential.cdf":"var y = base.dists.exponential.cdf( 2.0, 0.1 )\ny = base.dists.exponential.cdf( 1.0, 2.0 )\ny = base.dists.exponential.cdf( -1.0, 4.0 )\ny = base.dists.exponential.cdf( NaN, 1.0 )\ny = base.dists.exponential.cdf( 0.0, NaN )\ny = base.dists.exponential.cdf( 2.0, -1.0 )\n","base.dists.exponential.cdf.factory":"var myCDF = base.dists.exponential.cdf.factory( 0.5 );\nvar y = myCDF( 3.0 )\n","base.dists.exponential.entropy":"var v = base.dists.exponential.entropy( 11.0 )\nv = base.dists.exponential.entropy( 4.5 )\n","base.dists.exponential.Exponential":"var exponential = base.dists.exponential.Exponential( 6.0 );\nexponential.lambda\nexponential.entropy\nexponential.kurtosis\nexponential.mean\nexponential.median\nexponential.mode\nexponential.skewness\nexponential.stdev\nexponential.variance\nexponential.cdf( 1.0 )\nexponential.logcdf( 1.0 )\nexponential.logpdf( 1.5 )\nexponential.mgf( -0.5 )\nexponential.pdf( 1.5 )\nexponential.quantile( 0.5 )\n","base.dists.exponential.kurtosis":"var v = base.dists.exponential.kurtosis( 11.0 )\nv = base.dists.exponential.kurtosis( 4.5 )\n","base.dists.exponential.logcdf":"var y = base.dists.exponential.logcdf( 2.0, 0.1 )\ny = base.dists.exponential.logcdf( 1.0, 2.0 )\ny = base.dists.exponential.logcdf( -1.0, 4.0 )\ny = base.dists.exponential.logcdf( NaN, 1.0 )\ny = base.dists.exponential.logcdf( 0.0, NaN )\ny = base.dists.exponential.logcdf( 2.0, -1.0 )\n","base.dists.exponential.logcdf.factory":"var mylogCDF = base.dists.exponential.logcdf.factory( 0.5 );\nvar y = mylogCDF( 3.0 )\n","base.dists.exponential.logpdf":"var y = base.dists.exponential.logpdf( 0.3, 4.0 )\ny = base.dists.exponential.logpdf( 2.0, 0.7 )\ny = base.dists.exponential.logpdf( -1.0, 0.5 )\ny = base.dists.exponential.logpdf( 0, NaN )\ny = base.dists.exponential.logpdf( NaN, 2.0 )\ny = base.dists.exponential.logpdf( 2.0, -1.0 )\n","base.dists.exponential.logpdf.factory":"var mylogpdf = base.dists.exponential.logpdf.factory( 0.5 );\nvar y = mylogpdf( 3.0 )\n","base.dists.exponential.mean":"var v = base.dists.exponential.mean( 11.0 )\nv = base.dists.exponential.mean( 4.5 )\n","base.dists.exponential.median":"var v = base.dists.exponential.median( 11.0 )\nv = base.dists.exponential.median( 4.5 )\n","base.dists.exponential.mgf":"var v = base.dists.exponential.mgf( 2.0, 3.0 )\nv = base.dists.exponential.mgf( 0.4, 1.2 )\nv = base.dists.exponential.mgf( 0.8, 1.6 )\nv = base.dists.exponential.mgf( 4.0, 3.0 )\nv = base.dists.exponential.mgf( NaN, 3.0 )\nv = base.dists.exponential.mgf( 2.0, NaN )\n","base.dists.exponential.mgf.factory":"var myMGF = base.dists.exponential.mgf.factory( 4.0 );\nvar y = myMGF( 3.0 )\ny = myMGF( 0.5 )\n","base.dists.exponential.mode":"var v = base.dists.exponential.mode( 11.0 )\nv = base.dists.exponential.mode( 4.5 )\n","base.dists.exponential.pdf":"var y = base.dists.exponential.pdf( 0.3, 4.0 )\ny = base.dists.exponential.pdf( 2.0, 0.7 )\ny = base.dists.exponential.pdf( -1.0, 0.5 )\ny = base.dists.exponential.pdf( 0, NaN )\ny = base.dists.exponential.pdf( NaN, 2.0 )\ny = base.dists.exponential.pdf( 2.0, -1.0 )\n","base.dists.exponential.pdf.factory":"var myPDF = base.dists.exponential.pdf.factory( 0.5 );\nvar y = myPDF( 3.0 )\n","base.dists.exponential.quantile":"var y = base.dists.exponential.quantile( 0.8, 1.0 )\ny = base.dists.exponential.quantile( 0.5, 4.0 )\ny = base.dists.exponential.quantile( 0.5, 0.1 )\ny = base.dists.exponential.quantile( -0.2, 0.1 )\ny = base.dists.exponential.quantile( NaN, 1.0 )\ny = base.dists.exponential.quantile( 0.0, NaN )\ny = base.dists.exponential.quantile( 0.5, -1.0 )\n","base.dists.exponential.quantile.factory":"var myQuantile = base.dists.exponential.quantile.factory( 0.4 );\nvar y = myQuantile( 0.4 )\ny = myQuantile( 1.0 )\n","base.dists.exponential.skewness":"var v = base.dists.exponential.skewness( 11.0 )\nv = base.dists.exponential.skewness( 4.5 )\n","base.dists.exponential.stdev":"var v = base.dists.exponential.stdev( 9.0 )\nv = base.dists.exponential.stdev( 1.0 )\n","base.dists.exponential.variance":"var v = base.dists.exponential.variance( 9.0 )\nv = base.dists.exponential.variance( 1.0 )\n","base.dists.f.cdf":"var y = base.dists.f.cdf( 2.0, 1.0, 1.0 )\nvar y = base.dists.f.cdf( 2.0, 8.0, 4.0 )\nvar y = base.dists.f.cdf( -1.0, 2.0, 2.0 )\nvar y = base.dists.f.cdf( PINF, 4.0, 2.0 )\nvar y = base.dists.f.cdf( NINF, 4.0, 2.0 )\nvar y = base.dists.f.cdf( NaN, 1.0, 1.0 )\nvar y = base.dists.f.cdf( 0.0, NaN, 1.0 )\nvar y = base.dists.f.cdf( 0.0, 1.0, NaN )\nvar y = base.dists.f.cdf( 2.0, 1.0, -1.0 )\nvar y = base.dists.f.cdf( 2.0, -1.0, 1.0 )\n","base.dists.f.cdf.factory":"var myCDF = base.dists.f.cdf.factory( 10.0, 2.0 );\nvar y = myCDF( 10.0 )\ny = myCDF( 8.0 )\n","base.dists.f.entropy":"var v = base.dists.f.entropy( 3.0, 7.0 )\nv = base.dists.f.entropy( 4.0, 12.0 )\nv = base.dists.f.entropy( 8.0, 2.0 )\n","base.dists.f.F":"var f = base.dists.f.F( 6.0, 9.0 );\nf.d1\nf.d2\nf.entropy\nf.kurtosis\nf.mean\nf.mode\nf.skewness\nf.stdev\nf.variance\nf.cdf( 3.0 )\nf.pdf( 2.5 )\nf.quantile( 0.8 )\n","base.dists.f.kurtosis":"var v = base.dists.f.kurtosis( 3.0, 9.0 )\nv = base.dists.f.kurtosis( 4.0, 12.0 )\nv = base.dists.f.kurtosis( 8.0, 9.0 )\n","base.dists.f.mean":"var v = base.dists.f.mean( 3.0, 5.0 )\nv = base.dists.f.mean( 4.0, 12.0 )\nv = base.dists.f.mean( 8.0, 4.0 )\n","base.dists.f.mode":"var v = base.dists.f.mode( 3.0, 5.0 )\nv = base.dists.f.mode( 4.0, 12.0 )\nv = base.dists.f.mode( 8.0, 4.0 )\n","base.dists.f.pdf":"var y = base.dists.f.pdf( 2.0, 0.5, 1.0 )\ny = base.dists.f.pdf( 0.1, 1.0, 1.0 )\ny = base.dists.f.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.f.pdf( NaN, 1.0, 1.0 )\ny = base.dists.f.pdf( 0.0, NaN, 1.0 )\ny = base.dists.f.pdf( 0.0, 1.0, NaN )\ny = base.dists.f.pdf( 2.0, 1.0, -1.0 )\ny = base.dists.f.pdf( 2.0, -1.0, 1.0 )\n","base.dists.f.pdf.factory":"var myPDF = base.dists.f.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 7.0 )\ny = myPDF( 2.0 )\n","base.dists.f.quantile":"var y = base.dists.f.quantile( 0.8, 1.0, 1.0 )\ny = base.dists.f.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.f.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.f.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.f.quantile( NaN, 1.0, 1.0 )\ny = base.dists.f.quantile( 0.5, NaN, 1.0 )\ny = base.dists.f.quantile( 0.5, 1.0, NaN )\ny = base.dists.f.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.f.quantile( 0.5, 1.0, -1.0 )\n","base.dists.f.quantile.factory":"var myQuantile = base.dists.f.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.2 )\ny = myQuantile( 0.8 )\n","base.dists.f.skewness":"var v = base.dists.f.skewness( 3.0, 7.0 )\nv = base.dists.f.skewness( 4.0, 12.0 )\nv = base.dists.f.skewness( 8.0, 7.0 )\n","base.dists.f.stdev":"var v = base.dists.f.stdev( 3.0, 5.0 )\nv = base.dists.f.stdev( 4.0, 12.0 )\nv = base.dists.f.stdev( 8.0, 5.0 )\n","base.dists.f.variance":"var v = base.dists.f.variance( 3.0, 5.0 )\nv = base.dists.f.variance( 4.0, 12.0 )\nv = base.dists.f.variance( 8.0, 5.0 )\n","base.dists.frechet.cdf":"var y = base.dists.frechet.cdf( 10.0, 2.0, 3.0, 0.0 )\ny = base.dists.frechet.cdf( -1.0, 2.0, 3.0, -3.0 )\ny = base.dists.frechet.cdf( 2.5, 2.0, 1.0, 2.0 )\ny = base.dists.frechet.cdf( NaN, 1.0, 1.0, 0.0 )\ny = base.dists.frechet.cdf( 0.0, NaN, 1.0, 0.0 )\ny = base.dists.frechet.cdf( 0.0, 1.0, NaN, 0.0 )\ny = base.dists.frechet.cdf( 0.0, 1.0, 1.0, NaN )\ny = base.dists.frechet.cdf( 0.0, -1.0, 1.0, 0.0 )\ny = base.dists.frechet.cdf( 0.0, 1.0, -1.0, 0.0 )\n","base.dists.frechet.cdf.factory":"var myCDF = base.dists.frechet.cdf.factory( 3.0, 3.0, 5.0 );\nvar y = myCDF( 10.0 )\ny = myCDF( 7.0 )\n","base.dists.frechet.entropy":"var y = base.dists.frechet.entropy( 1.0, 1.0, 1.0 )\ny = base.dists.frechet.entropy( 4.0, 2.0, 1.0 )\ny = base.dists.frechet.entropy( NaN, 1.0, 0.0 )\ny = base.dists.frechet.entropy( 1.0, NaN, 0.0 )\ny = base.dists.frechet.entropy( 1.0, 1.0, NaN )\n","base.dists.frechet.Frechet":"var frechet = base.dists.frechet.Frechet( 1.0, 1.0, 0.0 );\nfrechet.alpha\nfrechet.s\nfrechet.m\nfrechet.entropy\nfrechet.kurtosis\nfrechet.mean\nfrechet.median\nfrechet.mode\nfrechet.skewness\nfrechet.stdev\nfrechet.variance\nfrechet.cdf( 0.8 )\nfrechet.logcdf( 0.8 )\nfrechet.logpdf( 0.8 )\nfrechet.pdf( 0.8 )\nfrechet.quantile( 0.8 )\n","base.dists.frechet.kurtosis":"var y = base.dists.frechet.kurtosis( 5.0, 2.0, 1.0 )\nvar y = base.dists.frechet.kurtosis( 5.0, 10.0, -3.0 )\ny = base.dists.frechet.kurtosis( 3.5, 2.0, 1.0 )\ny = base.dists.frechet.kurtosis( NaN, 1.0, 0.0 )\ny = base.dists.frechet.kurtosis( 1.0, NaN, 0.0 )\ny = base.dists.frechet.kurtosis( 1.0, 1.0, NaN )\n","base.dists.frechet.logcdf":"var y = base.dists.frechet.logcdf( 10.0, 2.0, 3.0, 0.0 )\ny = base.dists.frechet.logcdf( -1.0, 2.0, 3.0, -3.0 )\ny = base.dists.frechet.logcdf( 2.5, 2.0, 1.0, 2.0 )\ny = base.dists.frechet.logcdf( NaN, 1.0, 1.0, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, NaN, 1.0, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, 1.0, NaN, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, 1.0, 1.0, NaN )\ny = base.dists.frechet.logcdf( 0.0, -1.0, 1.0, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, 1.0, -1.0, 0.0 )\n","base.dists.frechet.logcdf.factory":"var mylogcdf = base.dists.frechet.logcdf.factory( 3.0, 3.0, 5.0 );\nvar y = mylogcdf( 10.0 )\ny = mylogcdf( 7.0 )\n","base.dists.frechet.logpdf":"var y = base.dists.frechet.logpdf( 10.0, 1.0, 3.0, 5.0 )\ny = base.dists.frechet.logpdf( -2.0, 1.0, 3.0, -3.0 )\ny = base.dists.frechet.logpdf( 0.0, 2.0, 1.0, -1.0 )\ny = base.dists.frechet.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.frechet.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.frechet.logpdf( 0.0, 0.0, NaN )\ny = base.dists.frechet.logpdf( 0.0, 0.0, -1.0 )\n","base.dists.frechet.logpdf.factory":"var mylogPDF = base.dists.frechet.logpdf.factory( 2.0, 3.0, 1.0 );\nvar y = mylogPDF( 10.0 )\ny = mylogPDF( 2.0 )\n","base.dists.frechet.mean":"var y = base.dists.frechet.mean( 4.0, 2.0, 1.0 )\ny = base.dists.frechet.mean( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.mean( NaN, 1.0, 0.0 )\ny = base.dists.frechet.mean( 1.0, NaN, 0.0 )\ny = base.dists.frechet.mean( 1.0, 1.0, NaN )\n","base.dists.frechet.median":"var y = base.dists.frechet.median( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.median( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.median( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.median( NaN, 1.0, 0.0 )\ny = base.dists.frechet.median( 1.0, NaN, 0.0 )\ny = base.dists.frechet.median( 1.0, 1.0, NaN )\n","base.dists.frechet.mode":"var y = base.dists.frechet.mode( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.mode( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.mode( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.mode( NaN, 1.0, 0.0 )\ny = base.dists.frechet.mode( 1.0, NaN, 0.0 )\ny = base.dists.frechet.mode( 1.0, 1.0, NaN )\n","base.dists.frechet.pdf":"var y = base.dists.frechet.pdf( 10.0, 0.0, 3.0 )\ny = base.dists.frechet.pdf( -2.0, 0.0, 3.0 )\ny = base.dists.frechet.pdf( 0.0, 0.0, 1.0 )\ny = base.dists.frechet.pdf( NaN, 0.0, 1.0 )\ny = base.dists.frechet.pdf( 0.0, NaN, 1.0 )\ny = base.dists.frechet.pdf( 0.0, 0.0, NaN )\ny = base.dists.frechet.pdf( 0.0, 0.0, -1.0 )\n","base.dists.frechet.pdf.factory":"var myPDF = base.dists.frechet.pdf.factory( 2.0, 3.0 );\nvar y = myPDF( 10.0 )\ny = myPDF( 2.0 )\n","base.dists.frechet.quantile":"var y = base.dists.frechet.quantile( 0.3, 10.0, 2.0, 3.0 )\ny = base.dists.frechet.quantile( 0.2, 3.0, 3.0, 3.0 )\ny = base.dists.frechet.quantile( 0.9, 1.0, 1.0, -3.0 )\ny = base.dists.frechet.quantile( NaN, 1.0, 1.0, 0.0 )\ny = base.dists.frechet.quantile( 0.0, NaN, 1.0, 0.0)\ny = base.dists.frechet.quantile( 0.0, 1.0, NaN, 0.0 )\ny = base.dists.frechet.quantile( 0.0, 1.0, 1.0, NaN )\ny = base.dists.frechet.quantile( 0.0, -1.0, 1.0, 0.0 )\ny = base.dists.frechet.quantile( 0.0, 1.0, -1.0, 0.0 )\n","base.dists.frechet.quantile.factory":"var myQuantile = base.dists.frechet.quantile.factory( 2.0, 2.0, 3.0 );\nvar y = myQuantile( 0.5 )\ny = myQuantile( 0.2 )\n","base.dists.frechet.skewness":"var y = base.dists.frechet.skewness( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.skewness( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.skewness( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.skewness( NaN, 1.0, 0.0 )\ny = base.dists.frechet.skewness( 1.0, NaN, 0.0 )\ny = base.dists.frechet.skewness( 1.0, 1.0, NaN )\n","base.dists.frechet.stdev":"var y = base.dists.frechet.stdev( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.stdev( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.stdev( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.stdev( NaN, 1.0, 0.0 )\ny = base.dists.frechet.stdev( 1.0, NaN, 0.0 )\ny = base.dists.frechet.stdev( 1.0, 1.0, NaN )\n","base.dists.frechet.variance":"var y = base.dists.frechet.variance( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.variance( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.variance( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.variance( NaN, 1.0, 0.0 )\ny = base.dists.frechet.variance( 1.0, NaN, 0.0 )\ny = base.dists.frechet.variance( 1.0, 1.0, NaN )\n","base.dists.gamma.cdf":"var y = base.dists.gamma.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.gamma.cdf( 2.0, 3.0, 1.0 )\ny = base.dists.gamma.cdf( -1.0, 2.0, 2.0 )\ny = base.dists.gamma.cdf( PINF, 4.0, 2.0 )\ny = base.dists.gamma.cdf( NINF, 4.0, 2.0 )\ny = base.dists.gamma.cdf( NaN, 0.0, 1.0 )\ny = base.dists.gamma.cdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.cdf( 0.0, 0.0, NaN )\ny = base.dists.gamma.cdf( 2.0, -1.0, 1.0 )\ny = base.dists.gamma.cdf( 2.0, 1.0, -1.0 )\ny = base.dists.gamma.cdf( 2.0, 0.0, 2.0 )\ny = base.dists.gamma.cdf( -2.0, 0.0, 2.0 )\ny = base.dists.gamma.cdf( 0.0, 0.0, 2.0 )\n","base.dists.gamma.cdf.factory":"var myCDF = base.dists.gamma.cdf.factory( 2.0, 0.5 );\nvar y = myCDF( 6.0 )\ny = myCDF( 2.0 )\n","base.dists.gamma.entropy":"var v = base.dists.gamma.entropy( 1.0, 1.0 )\nv = base.dists.gamma.entropy( 4.0, 12.0 )\nv = base.dists.gamma.entropy( 8.0, 2.0 )\n","base.dists.gamma.Gamma":"var gamma = base.dists.gamma.Gamma( 6.0, 5.0 );\ngamma.alpha\ngamma.beta\ngamma.entropy\ngamma.kurtosis\ngamma.mean\ngamma.mode\ngamma.skewness\ngamma.stdev\ngamma.variance\ngamma.cdf( 0.8 )\ngamma.logcdf( 0.8 )\ngamma.logpdf( 1.0 )\ngamma.mgf( -0.5 )\ngamma.pdf( 1.0 )\ngamma.quantile( 0.8 )\n","base.dists.gamma.kurtosis":"var v = base.dists.gamma.kurtosis( 1.0, 1.0 )\nv = base.dists.gamma.kurtosis( 4.0, 12.0 )\nv = base.dists.gamma.kurtosis( 8.0, 2.0 )\n","base.dists.gamma.logcdf":"var y = base.dists.gamma.logcdf( 2.0, 0.5, 1.0 )\ny = base.dists.gamma.logcdf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.logcdf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.logcdf( NaN, 0.6, 1.0 )\ny = base.dists.gamma.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.logcdf( 0.0, 1.0, NaN )\ny = base.dists.gamma.logcdf( 2.0, -1.0, 1.0 )\ny = base.dists.gamma.logcdf( 2.0, 1.0, -1.0 )\n","base.dists.gamma.logcdf.factory":"var mylogCDF = base.dists.gamma.logcdf.factory( 6.0, 7.0 );\nvar y = mylogCDF( 2.0 )\n","base.dists.gamma.logpdf":"var y = base.dists.gamma.logpdf( 2.0, 0.5, 1.0 )\ny = base.dists.gamma.logpdf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.logpdf( NaN, 0.6, 1.0 )\ny = base.dists.gamma.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.logpdf( 0.0, 1.0, NaN )\ny = base.dists.gamma.logpdf( 2.0, -1.0, 1.0 )\ny = base.dists.gamma.logpdf( 2.0, 1.0, -1.0 )\ny = base.dists.gamma.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.gamma.logpdf( 0.0, 0.0, 2.0 )\n","base.dists.gamma.logpdf.factory":"var mylogPDF = base.dists.gamma.logpdf.factory( 6.0, 7.0 );\nvar y = mylogPDF( 2.0 )\n","base.dists.gamma.mean":"var v = base.dists.gamma.mean( 1.0, 1.0 )\nv = base.dists.gamma.mean( 4.0, 12.0 )\nv = base.dists.gamma.mean( 8.0, 2.0 )\n","base.dists.gamma.mgf":"var y = base.dists.gamma.mgf( 0.5, 0.5, 1.0 )\ny = base.dists.gamma.mgf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.mgf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.mgf( NaN, 1.0, 1.0 )\ny = base.dists.gamma.mgf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.mgf( 0.0, 1.0, NaN )\ny = base.dists.gamma.mgf( 2.0, 4.0, 1.0 )\ny = base.dists.gamma.mgf( 2.0, -0.5, 1.0 )\ny = base.dists.gamma.mgf( 2.0, 1.0, 0.0 )\ny = base.dists.gamma.mgf( 2.0, 1.0, -1.0 )\n","base.dists.gamma.mgf.factory":"var myMGF = base.dists.gamma.mgf.factory( 3.0, 1.5 );\nvar y = myMGF( 1.0 )\ny = myMGF( 0.5 )\n","base.dists.gamma.mode":"var v = base.dists.gamma.mode( 1.0, 1.0 )\nv = base.dists.gamma.mode( 4.0, 12.0 )\nv = base.dists.gamma.mode( 8.0, 2.0 )\n","base.dists.gamma.pdf":"var y = base.dists.gamma.pdf( 2.0, 0.5, 1.0 )\ny = base.dists.gamma.pdf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.pdf( NaN, 0.6, 1.0 )\ny = base.dists.gamma.pdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.pdf( 0.0, 1.0, NaN )\ny = base.dists.gamma.pdf( 2.0, -1.0, 1.0 )\ny = base.dists.gamma.pdf( 2.0, 1.0, -1.0 )\ny = base.dists.gamma.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.gamma.pdf( 0.0, 0.0, 2.0 )\n","base.dists.gamma.pdf.factory":"var myPDF = base.dists.gamma.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 2.0 )\n","base.dists.gamma.quantile":"var y = base.dists.gamma.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.gamma.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.gamma.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.gamma.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.gamma.quantile( NaN, 1.0, 1.0 )\ny = base.dists.gamma.quantile( 0.0, NaN, 1.0 )\ny = base.dists.gamma.quantile( 0.0, 1.0, NaN )\ny = base.dists.gamma.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.gamma.quantile( 0.5, 1.0, -1.0 )\ny = base.dists.gamma.quantile( 0.3, 0.0, 2.0 )\ny = base.dists.gamma.quantile( 0.9, 0.0, 2.0 )\n","base.dists.gamma.quantile.factory":"var myQuantile = base.dists.gamma.quantile.factory( 2.0, 2.0 );\nvar y = myQuantile( 0.8 )\ny = myQuantile( 0.4 )\n","base.dists.gamma.skewness":"var v = base.dists.gamma.skewness( 1.0, 1.0 )\nv = base.dists.gamma.skewness( 4.0, 12.0 )\nv = base.dists.gamma.skewness( 8.0, 2.0 )\n","base.dists.gamma.stdev":"var v = base.dists.gamma.stdev( 1.0, 1.0 )\nv = base.dists.gamma.stdev( 4.0, 12.0 )\nv = base.dists.gamma.stdev( 8.0, 2.0 )\n","base.dists.gamma.variance":"var v = base.dists.gamma.variance( 1.0, 1.0 )\nv = base.dists.gamma.variance( 4.0, 12.0 )\nv = base.dists.gamma.variance( 8.0, 2.0 )\n","base.dists.geometric.cdf":"var y = base.dists.geometric.cdf( 2.0, 0.5 )\ny = base.dists.geometric.cdf( 2.0, 0.1 )\ny = base.dists.geometric.cdf( -1.0, 4.0 )\ny = base.dists.geometric.cdf( NaN, 0.5 )\ny = base.dists.geometric.cdf( 0.0, NaN )\ny = base.dists.geometric.cdf( 2.0, 1.4 )\n","base.dists.geometric.cdf.factory":"var mycdf = base.dists.geometric.cdf.factory( 0.5 );\nvar y = mycdf( 3.0 )\ny = mycdf( 1.0 )\n","base.dists.geometric.entropy":"var v = base.dists.geometric.entropy( 0.1 )\nv = base.dists.geometric.entropy( 0.5 )\n","base.dists.geometric.Geometric":"var geometric = base.dists.geometric.Geometric( 0.6 );\ngeometric.p\ngeometric.entropy\ngeometric.kurtosis\ngeometric.mean\ngeometric.median\ngeometric.mode\ngeometric.skewness\ngeometric.stdev\ngeometric.variance\ngeometric.cdf( 3.0 )\ngeometric.logcdf( 3.0 )\ngeometric.logpmf( 4.0 )\ngeometric.mgf( 0.5 )\ngeometric.pmf( 2.0 )\ngeometric.quantile( 0.7 )\n","base.dists.geometric.kurtosis":"var v = base.dists.geometric.kurtosis( 0.1 )\nv = base.dists.geometric.kurtosis( 0.5 )\n","base.dists.geometric.logcdf":"var y = base.dists.geometric.logcdf( 2.0, 0.5 )\ny = base.dists.geometric.logcdf( 2.0, 0.1 )\ny = base.dists.geometric.logcdf( -1.0, 4.0 )\ny = base.dists.geometric.logcdf( NaN, 0.5 )\ny = base.dists.geometric.logcdf( 0.0, NaN )\ny = base.dists.geometric.logcdf( 2.0, 1.4 )\n","base.dists.geometric.logcdf.factory":"var mylogcdf = base.dists.geometric.logcdf.factory( 0.5 );\nvar y = mylogcdf( 3.0 )\ny = mylogcdf( 1.0 )\n","base.dists.geometric.logpmf":"var y = base.dists.geometric.logpmf( 4.0, 0.3 )\ny = base.dists.geometric.logpmf( 2.0, 0.7 )\ny = base.dists.geometric.logpmf( -1.0, 0.5 )\ny = base.dists.geometric.logpmf( 0.0, NaN )\ny = base.dists.geometric.logpmf( NaN, 0.5 )\ny = base.dists.geometric.logpmf( 2.0, 1.5 )\n","base.dists.geometric.logpmf.factory":"var mylogpmf = base.dists.geometric.logpmf.factory( 0.5 );\nvar y = mylogpmf( 3.0 )\ny = mylogpmf( 1.0 )\n","base.dists.geometric.mean":"var v = base.dists.geometric.mean( 0.1 )\nv = base.dists.geometric.mean( 0.5 )\n","base.dists.geometric.median":"var v = base.dists.geometric.median( 0.1 )\nv = base.dists.geometric.median( 0.5 )\n","base.dists.geometric.mgf":"var y = base.dists.geometric.mgf( 0.2, 0.5 )\ny = base.dists.geometric.mgf( 0.4, 0.5 )\ny = base.dists.geometric.mgf( 0.8, 0.5 )\ny = base.dists.geometric.mgf( NaN, 0.0 )\ny = base.dists.geometric.mgf( 0.0, NaN )\ny = base.dists.geometric.mgf( -2.0, -1.0 )\ny = base.dists.geometric.mgf( 0.2, 2.0 )\n","base.dists.geometric.mgf.factory":"var mymgf = base.dists.geometric.mgf.factory( 0.8 );\nvar y = mymgf( -0.2 )\n","base.dists.geometric.mode":"var v = base.dists.geometric.mode( 0.1 )\nv = base.dists.geometric.mode( 0.5 )\n","base.dists.geometric.pmf":"var y = base.dists.geometric.pmf( 4.0, 0.3 )\ny = base.dists.geometric.pmf( 2.0, 0.7 )\ny = base.dists.geometric.pmf( -1.0, 0.5 )\ny = base.dists.geometric.pmf( 0.0, NaN )\ny = base.dists.geometric.pmf( NaN, 0.5 )\ny = base.dists.geometric.pmf( 2.0, 1.5 )\n","base.dists.geometric.pmf.factory":"var mypmf = base.dists.geometric.pmf.factory( 0.5 );\nvar y = mypmf( 3.0 )\ny = mypmf( 1.0 )\n","base.dists.geometric.quantile":"var y = base.dists.geometric.quantile( 0.8, 0.4 )\ny = base.dists.geometric.quantile( 0.5, 0.4 )\ny = base.dists.geometric.quantile( 0.9, 0.1 )\ny = base.dists.geometric.quantile( -0.2, 0.1 )\ny = base.dists.geometric.quantile( NaN, 0.8 )\ny = base.dists.geometric.quantile( 0.4, NaN )\ny = base.dists.geometric.quantile( 0.5, -1.0 )\ny = base.dists.geometric.quantile( 0.5, 1.5 )\n","base.dists.geometric.quantile.factory":"var myquantile = base.dists.geometric.quantile.factory( 0.4 );\nvar y = myquantile( 0.4 )\ny = myquantile( 0.8 )\ny = myquantile( 1.0 )\n","base.dists.geometric.skewness":"var v = base.dists.geometric.skewness( 0.1 )\nv = base.dists.geometric.skewness( 0.5 )\n","base.dists.geometric.stdev":"var v = base.dists.geometric.stdev( 0.1 )\nv = base.dists.geometric.stdev( 0.5 )\n","base.dists.geometric.variance":"var v = base.dists.geometric.variance( 0.1 )\nv = base.dists.geometric.variance( 0.5 )\n","base.dists.gumbel.cdf":"var y = base.dists.gumbel.cdf( 10.0, 0.0, 3.0 )\ny = base.dists.gumbel.cdf( -2.0, 0.0, 3.0 )\ny = base.dists.gumbel.cdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.cdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.cdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.cdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.cdf( 0.0, 0.0, -1.0 )\n","base.dists.gumbel.cdf.factory":"var myCDF = base.dists.gumbel.cdf.factory( 2.0, 3.0 );\nvar y = myCDF( 10.0 )\ny = myCDF( 2.0 )\n","base.dists.gumbel.entropy":"var y = base.dists.gumbel.entropy( 0.0, 1.0 )\ny = base.dists.gumbel.entropy( 4.0, 2.0 )\ny = base.dists.gumbel.entropy( NaN, 1.0 )\ny = base.dists.gumbel.entropy( 0.0, NaN )\ny = base.dists.gumbel.entropy( 0.0, 0.0 )\n","base.dists.gumbel.Gumbel":"var gumbel = base.dists.gumbel.Gumbel( -2.0, 3.0 );\ngumbel.mu\ngumbel.beta\ngumbel.entropy\ngumbel.kurtosis\ngumbel.mean\ngumbel.median\ngumbel.mode\ngumbel.skewness\ngumbel.stdev\ngumbel.variance\ngumbel.cdf( 0.8 )\ngumbel.logcdf( 0.8 )\ngumbel.logpdf( 1.0 )\ngumbel.mgf( 0.2 )\ngumbel.pdf( 1.0 )\ngumbel.quantile( 0.8 )\n","base.dists.gumbel.kurtosis":"var y = base.dists.gumbel.kurtosis( 0.0, 1.0 )\ny = base.dists.gumbel.kurtosis( 4.0, 2.0 )\ny = base.dists.gumbel.kurtosis( NaN, 1.0 )\ny = base.dists.gumbel.kurtosis( 0.0, NaN )\ny = base.dists.gumbel.kurtosis( 0.0, 0.0 )\n","base.dists.gumbel.logcdf":"var y = base.dists.gumbel.logcdf( 10.0, 0.0, 3.0 )\ny = base.dists.gumbel.logcdf( -2.0, 0.0, 3.0 )\ny = base.dists.gumbel.logcdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.logcdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.logcdf( 0.0, 0.0, -1.0 )\n","base.dists.gumbel.logcdf.factory":"var myLCDF = base.dists.gumbel.logcdf.factory( 2.0, 3.0 );\nvar y = myLCDF( 10.0 )\ny = myLCDF( 2.0 )\n","base.dists.gumbel.logpdf":"var y = base.dists.gumbel.logpdf( 0.0, 0.0, 2.0 )\ny = base.dists.gumbel.logpdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.logpdf( 1.0, 3.0, 2.0 )\ny = base.dists.gumbel.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.logpdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.logpdf( 2.0, 0.0, -1.0 )\n","base.dists.gumbel.logpdf.factory":"var mylogpdf = base.dists.gumbel.logpdf.factory( 10.0, 2.0 );\nvar y = mylogpdf( 10.0 )\ny = mylogpdf( 12.0 )\n","base.dists.gumbel.mean":"var y = base.dists.gumbel.mean( 0.0, 1.0 )\ny = base.dists.gumbel.mean( 4.0, 2.0 )\ny = base.dists.gumbel.mean( NaN, 1.0 )\ny = base.dists.gumbel.mean( 0.0, NaN )\ny = base.dists.gumbel.mean( 0.0, 0.0 )\n","base.dists.gumbel.median":"var y = base.dists.gumbel.median( 0.0, 1.0 )\ny = base.dists.gumbel.median( 4.0, 2.0 )\ny = base.dists.gumbel.median( NaN, 1.0 )\ny = base.dists.gumbel.median( 0.0, NaN )\ny = base.dists.gumbel.median( 0.0, 0.0 )\n","base.dists.gumbel.mgf":"var y = base.dists.gumbel.mgf( -1.0, 0.0, 3.0 )\ny = base.dists.gumbel.mgf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.mgf( 0.1, 0.0, 3.0 )\ny = base.dists.gumbel.mgf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.mgf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.mgf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.mgf( 0.8, 0.0, 2.0 )\ny = base.dists.gumbel.mgf( 0.0, 0.0, -1.0 )\n","base.dists.gumbel.mgf.factory":"var myMGF = base.dists.gumbel.mgf.factory( 0.0, 3.0 );\nvar y = myMGF( -1.5 )\ny = myMGF( -1.0 )\n","base.dists.gumbel.mode":"var y = base.dists.gumbel.mode( 0.0, 1.0 )\ny = base.dists.gumbel.mode( 4.0, 2.0 )\ny = base.dists.gumbel.mode( NaN, 1.0 )\ny = base.dists.gumbel.mode( 0.0, NaN )\ny = base.dists.gumbel.mode( 0.0, 0.0 )\n","base.dists.gumbel.pdf":"var y = base.dists.gumbel.pdf( 0.0, 0.0, 2.0 )\ny = base.dists.gumbel.pdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.pdf( 1.0, 3.0, 2.0 )\ny = base.dists.gumbel.pdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.pdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.pdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.pdf( 2.0, 0.0, -1.0 )\n","base.dists.gumbel.pdf.factory":"var myPDF = base.dists.gumbel.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\ny = myPDF( 12.0 )\n","base.dists.gumbel.quantile":"var y = base.dists.gumbel.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.gumbel.quantile( 0.5, 4.0, 4.0 )\ny = base.dists.gumbel.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.quantile( 0.0, 0.0, NaN )\ny = base.dists.gumbel.quantile( 0.5, 0.0, -1.0 )\n","base.dists.gumbel.quantile.factory":"var myQuantile = base.dists.gumbel.quantile.factory( 8.0, 2.0 );\nvar y = myQuantile( 0.5 )\ny = myQuantile( 0.7 )\n","base.dists.gumbel.skewness":"var y = base.dists.gumbel.skewness( 0.0, 1.0 )\ny = base.dists.gumbel.skewness( 4.0, 2.0 )\ny = base.dists.gumbel.skewness( NaN, 1.0 )\ny = base.dists.gumbel.skewness( 0.0, NaN )\ny = base.dists.gumbel.skewness( 0.0, 0.0 )\n","base.dists.gumbel.stdev":"var y = base.dists.gumbel.stdev( 0.0, 1.0 )\ny = base.dists.gumbel.stdev( 4.0, 2.0 )\ny = base.dists.gumbel.stdev( NaN, 1.0 )\ny = base.dists.gumbel.stdev( 0.0, NaN )\ny = base.dists.gumbel.stdev( 0.0, 0.0 )\n","base.dists.gumbel.variance":"var y = base.dists.gumbel.variance( 0.0, 1.0 )\ny = base.dists.gumbel.variance( 4.0, 2.0 )\ny = base.dists.gumbel.variance( NaN, 1.0 )\ny = base.dists.gumbel.variance( 0.0, NaN )\ny = base.dists.gumbel.variance( 0.0, 0.0 )\n","base.dists.hypergeometric.cdf":"var y = base.dists.hypergeometric.cdf( 1.0, 8, 4, 2 )\ny = base.dists.hypergeometric.cdf( 1.5, 8, 4, 2 )\ny = base.dists.hypergeometric.cdf( 2.0, 8, 4, 2 )\ny = base.dists.hypergeometric.cdf( 0, 8, 4, 2)\ny = base.dists.hypergeometric.cdf( NaN, 10, 5, 2 )\ny = base.dists.hypergeometric.cdf( 0.0, NaN, 5, 2 )\ny = base.dists.hypergeometric.cdf( 0.0, 10, NaN, 2 )\ny = base.dists.hypergeometric.cdf( 0.0, 10, 5, NaN )\ny = base.dists.hypergeometric.cdf( 2.0, 10.5, 5, 2 )\ny = base.dists.hypergeometric.cdf( 2.0, 10, 1.5, 2 )\ny = base.dists.hypergeometric.cdf( 2.0, 10, 5, -2.0 )\ny = base.dists.hypergeometric.cdf( 2.0, 10, 5, 12 )\ny = base.dists.hypergeometric.cdf( 2.0, 8, 3, 9 )\n","base.dists.hypergeometric.cdf.factory":"var myCDF = base.dists.hypergeometric.cdf.factory( 30, 20, 5 );\nvar y = myCDF( 4.0 )\ny = myCDF( 1.0 )\n","base.dists.hypergeometric.Hypergeometric":"var hypergeometric = base.dists.hypergeometric.Hypergeometric( 100, 70, 20 );\nhypergeometric.N\nhypergeometric.K\nhypergeometric.n\nhypergeometric.kurtosis\nhypergeometric.mean\nhypergeometric.mode\nhypergeometric.skewness\nhypergeometric.stdev\nhypergeometric.variance\nhypergeometric.cdf( 2.9 )\nhypergeometric.logpmf( 10 )\nhypergeometric.pmf( 10 )\nhypergeometric.quantile( 0.8 )\n","base.dists.hypergeometric.kurtosis":"var v = base.dists.hypergeometric.kurtosis( 16, 11, 4 )\nv = base.dists.hypergeometric.kurtosis( 4, 2, 2 )\nv = base.dists.hypergeometric.kurtosis( 10, 5, 12 )\nv = base.dists.hypergeometric.kurtosis( 10.3, 10, 4 )\nv = base.dists.hypergeometric.kurtosis( 10, 5.5, 4 )\nv = base.dists.hypergeometric.kurtosis( 10, 5, 4.5 )\nv = base.dists.hypergeometric.kurtosis( NaN, 10, 4 )\nv = base.dists.hypergeometric.kurtosis( 20, NaN, 4 )\nv = base.dists.hypergeometric.kurtosis( 20, 10, NaN )\n","base.dists.hypergeometric.logpmf":"var y = base.dists.hypergeometric.logpmf( 1.0, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( 2.0, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( 1.5, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( NaN, 10, 5, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, NaN, 5, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, 10, NaN, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, 10, 5, NaN )\ny = base.dists.hypergeometric.logpmf( 2.0, 10.5, 5, 2 )\ny = base.dists.hypergeometric.logpmf( 2.0, 5, 1.5, 2 )\ny = base.dists.hypergeometric.logpmf( 2.0, 10, 5, -2.0 )\ny = base.dists.hypergeometric.logpmf( 2.0, 10, 5, 12 )\ny = base.dists.hypergeometric.logpmf( 2.0, 8, 3, 9 )\n","base.dists.hypergeometric.logpmf.factory":"var mylogPMF = base.dists.hypergeometric.logpmf.factory( 30, 20, 5 );\nvar y = mylogPMF( 4.0 )\ny = mylogPMF( 1.0 )\n","base.dists.hypergeometric.mean":"var v = base.dists.hypergeometric.mean( 16, 11, 4 )\nv = base.dists.hypergeometric.mean( 2, 1, 1 )\nv = base.dists.hypergeometric.mean( 10, 5, 12 )\nv = base.dists.hypergeometric.mean( 10.3, 10, 4 )\nv = base.dists.hypergeometric.mean( 10, 5.5, 4 )\nv = base.dists.hypergeometric.mean( 10, 5, 4.5 )\nv = base.dists.hypergeometric.mean( NaN, 10, 4 )\nv = base.dists.hypergeometric.mean( 20, NaN, 4 )\nv = base.dists.hypergeometric.mean( 20, 10, NaN )\n","base.dists.hypergeometric.mode":"var v = base.dists.hypergeometric.mode( 16, 11, 4 )\nv = base.dists.hypergeometric.mode( 2, 1, 1 )\nv = base.dists.hypergeometric.mode( 10, 5, 12 )\nv = base.dists.hypergeometric.mode( 10.3, 10, 4 )\nv = base.dists.hypergeometric.mode( 10, 5.5, 4 )\nv = base.dists.hypergeometric.mode( 10, 5, 4.5 )\nv = base.dists.hypergeometric.mode( NaN, 10, 4 )\nv = base.dists.hypergeometric.mode( 20, NaN, 4 )\nv = base.dists.hypergeometric.mode( 20, 10, NaN )\n","base.dists.hypergeometric.pmf":"var y = base.dists.hypergeometric.pmf( 1.0, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( 2.0, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( 1.5, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( NaN, 10, 5, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, NaN, 5, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, 10, NaN, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, 10, 5, NaN )\ny = base.dists.hypergeometric.pmf( 2.0, 10.5, 5, 2 )\ny = base.dists.hypergeometric.pmf( 2.0, 5, 1.5, 2 )\ny = base.dists.hypergeometric.pmf( 2.0, 10, 5, -2.0 )\ny = base.dists.hypergeometric.pmf( 2.0, 10, 5, 12 )\ny = base.dists.hypergeometric.pmf( 2.0, 8, 3, 9 )\n","base.dists.hypergeometric.pmf.factory":"var myPMF = base.dists.hypergeometric.pmf.factory( 30, 20, 5 );\nvar y = myPMF( 4.0 )\ny = myPMF( 1.0 )\n","base.dists.hypergeometric.quantile":"var y = base.dists.hypergeometric.quantile( 0.4, 40, 20, 10 )\ny = base.dists.hypergeometric.quantile( 0.8, 60, 40, 20 )\ny = base.dists.hypergeometric.quantile( 0.5, 100, 10, 10 )\ny = base.dists.hypergeometric.quantile( 0.0, 100, 40, 20 )\ny = base.dists.hypergeometric.quantile( 1.0, 100, 40, 20 )\ny = base.dists.hypergeometric.quantile( NaN, 40, 20, 10 )\ny = base.dists.hypergeometric.quantile( 0.2, NaN, 20, 10 )\ny = base.dists.hypergeometric.quantile( 0.2, 40, NaN, 10 )\ny = base.dists.hypergeometric.quantile( 0.2, 40, 20, NaN )\n","base.dists.hypergeometric.quantile.factory":"var myQuantile = base.dists.hypergeometric.quantile.factory( 100, 20, 10 );\nvar y = myQuantile( 0.2 )\ny = myQuantile( 0.9 )\n","base.dists.hypergeometric.skewness":"var v = base.dists.hypergeometric.skewness( 16, 11, 4 )\nv = base.dists.hypergeometric.skewness( 4, 2, 2 )\nv = base.dists.hypergeometric.skewness( 10, 5, 12 )\nv = base.dists.hypergeometric.skewness( 10.3, 10, 4 )\nv = base.dists.hypergeometric.skewness( 10, 5.5, 4 )\nv = base.dists.hypergeometric.skewness( 10, 5, 4.5 )\nv = base.dists.hypergeometric.skewness( NaN, 10, 4 )\nv = base.dists.hypergeometric.skewness( 20, NaN, 4 )\nv = base.dists.hypergeometric.skewness( 20, 10, NaN )\n","base.dists.hypergeometric.stdev":"var v = base.dists.hypergeometric.stdev( 16, 11, 4 )\nv = base.dists.hypergeometric.stdev( 2, 1, 1 )\nv = base.dists.hypergeometric.stdev( 10, 5, 12 )\nv = base.dists.hypergeometric.stdev( 10.3, 10, 4 )\nv = base.dists.hypergeometric.stdev( 10, 5.5, 4 )\nv = base.dists.hypergeometric.stdev( 10, 5, 4.5 )\nv = base.dists.hypergeometric.stdev( NaN, 10, 4 )\nv = base.dists.hypergeometric.stdev( 20, NaN, 4 )\nv = base.dists.hypergeometric.stdev( 20, 10, NaN )\n","base.dists.hypergeometric.variance":"var v = base.dists.hypergeometric.variance( 16, 11, 4 )\nv = base.dists.hypergeometric.variance( 2, 1, 1 )\nv = base.dists.hypergeometric.variance( 10, 5, 12 )\nv = base.dists.hypergeometric.variance( 10.3, 10, 4 )\nv = base.dists.hypergeometric.variance( 10, 5.5, 4 )\nv = base.dists.hypergeometric.variance( 10, 5, 4.5 )\nv = base.dists.hypergeometric.variance( NaN, 10, 4 )\nv = base.dists.hypergeometric.variance( 20, NaN, 4 )\nv = base.dists.hypergeometric.variance( 20, 10, NaN )\n","base.dists.invgamma.cdf":"var y = base.dists.invgamma.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.invgamma.cdf( 2.0, 3.0, 1.0 )\ny = base.dists.invgamma.cdf( -1.0, 2.0, 2.0 )\ny = base.dists.invgamma.cdf( PINF, 4.0, 2.0 )\ny = base.dists.invgamma.cdf( NINF, 4.0, 2.0 )\ny = base.dists.invgamma.cdf( NaN, 0.0, 1.0 )\ny = base.dists.invgamma.cdf( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.cdf( 0.0, 0.0, NaN )\ny = base.dists.invgamma.cdf( 2.0, -1.0, 1.0 )\ny = base.dists.invgamma.cdf( 2.0, 1.0, -1.0 )\n","base.dists.invgamma.cdf.factory":"var myCDF = base.dists.invgamma.cdf.factory( 2.0, 0.5 );\nvar y = myCDF( 0.5 )\ny = myCDF( 2.0 )\n","base.dists.invgamma.entropy":"var v = base.dists.invgamma.entropy( 1.0, 1.0 )\nv = base.dists.invgamma.entropy( 4.0, 12.0 )\nv = base.dists.invgamma.entropy( 8.0, 2.0 )\n","base.dists.invgamma.InvGamma":"var invgamma = base.dists.invgamma.InvGamma( 6.0, 5.0 );\ninvgamma.alpha\ninvgamma.beta\ninvgamma.entropy\ninvgamma.kurtosis\ninvgamma.mean\ninvgamma.mode\ninvgamma.skewness\ninvgamma.stdev\ninvgamma.variance\ninvgamma.cdf( 0.8 )\ninvgamma.pdf( 1.0 )\ninvgamma.logpdf( 1.0 )\ninvgamma.quantile( 0.8 )\n","base.dists.invgamma.kurtosis":"var v = base.dists.invgamma.kurtosis( 7.0, 5.0 )\nv = base.dists.invgamma.kurtosis( 6.0, 12.0 )\nv = base.dists.invgamma.kurtosis( 8.0, 2.0 )\n","base.dists.invgamma.logpdf":"var y = base.dists.invgamma.logpdf( 2.0, 0.5, 1.0 )\ny = base.dists.invgamma.logpdf( 0.2, 1.0, 1.0 )\ny = base.dists.invgamma.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.invgamma.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.invgamma.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.logpdf( 0.0, 1.0, NaN )\ny = base.dists.invgamma.logpdf( 2.0, -1.0, 1.0 )\ny = base.dists.invgamma.logpdf( 2.0, 1.0, -1.0 )\n","base.dists.invgamma.logpdf.factory":"var mylogPDF = base.dists.invgamma.logpdf.factory( 6.0, 7.0 );\nvar y = mylogPDF( 2.0 )\n","base.dists.invgamma.mean":"var v = base.dists.invgamma.mean( 4.0, 12.0 )\nv = base.dists.invgamma.mean( 8.0, 2.0 )\n","base.dists.invgamma.mode":"var v = base.dists.invgamma.mode( 1.0, 1.0 )\nv = base.dists.invgamma.mode( 4.0, 12.0 )\nv = base.dists.invgamma.mode( 8.0, 2.0 )\n","base.dists.invgamma.pdf":"var y = base.dists.invgamma.pdf( 2.0, 0.5, 1.0 )\ny = base.dists.invgamma.pdf( 0.2, 1.0, 1.0 )\ny = base.dists.invgamma.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.invgamma.pdf( NaN, 1.0, 1.0 )\ny = base.dists.invgamma.pdf( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.pdf( 0.0, 1.0, NaN )\ny = base.dists.invgamma.pdf( 2.0, -1.0, 1.0 )\ny = base.dists.invgamma.pdf( 2.0, 1.0, -1.0 )\n","base.dists.invgamma.pdf.factory":"var myPDF = base.dists.invgamma.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 2.0 )\n","base.dists.invgamma.quantile":"var y = base.dists.invgamma.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.invgamma.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.invgamma.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.invgamma.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.invgamma.quantile( NaN, 1.0, 1.0 )\ny = base.dists.invgamma.quantile( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.quantile( 0.0, 1.0, NaN )\ny = base.dists.invgamma.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.invgamma.quantile( 0.5, 1.0, -1.0 )\n","base.dists.invgamma.quantile.factory":"var myQuantile = base.dists.invgamma.quantile.factory( 2.0, 2.0 );\nvar y = myQuantile( 0.8 )\ny = myQuantile( 0.4 )\n","base.dists.invgamma.skewness":"var v = base.dists.invgamma.skewness( 4.0, 12.0 )\nv = base.dists.invgamma.skewness( 8.0, 2.0 )\n","base.dists.invgamma.stdev":"var v = base.dists.invgamma.stdev( 5.0, 7.0 )\nv = base.dists.invgamma.stdev( 4.0, 12.0 )\nv = base.dists.invgamma.stdev( 8.0, 2.0 )\n","base.dists.invgamma.variance":"var v = base.dists.invgamma.variance( 5.0, 7.0 )\nv = base.dists.invgamma.variance( 4.0, 12.0 )\nv = base.dists.invgamma.variance( 8.0, 2.0 )\n","base.dists.kumaraswamy.cdf":"var y = base.dists.kumaraswamy.cdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.cdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.cdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.cdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.cdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.cdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.cdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.cdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.cdf( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.cdf.factory":"var mycdf = base.dists.kumaraswamy.cdf.factory( 0.5, 1.0 );\nvar y = mycdf( 0.8 )\ny = mycdf( 0.3 )\n","base.dists.kumaraswamy.Kumaraswamy":"var kumaraswamy = base.dists.kumaraswamy.Kumaraswamy( 6.0, 5.0 );\nkumaraswamy.a\nkumaraswamy.b\nkumaraswamy.kurtosis\nkumaraswamy.mean\nkumaraswamy.mode\nkumaraswamy.skewness\nkumaraswamy.stdev\nkumaraswamy.variance\nkumaraswamy.cdf( 0.8 )\nkumaraswamy.pdf( 1.0 )\nkumaraswamy.quantile( 0.8 )\n","base.dists.kumaraswamy.kurtosis":"var v = base.dists.kumaraswamy.kurtosis( 1.0, 1.0 )\nv = base.dists.kumaraswamy.kurtosis( 4.0, 12.0 )\nv = base.dists.kumaraswamy.kurtosis( 16.0, 8.0 )\n","base.dists.kumaraswamy.logcdf":"var y = base.dists.kumaraswamy.logcdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logcdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.logcdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.logcdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.logcdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logcdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.logcdf( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.logcdf.factory":"var mylogcdf = base.dists.kumaraswamy.logcdf.factory( 0.5, 1.0 );\nvar y = mylogcdf( 0.8 )\ny = mylogcdf( 0.3 )\n","base.dists.kumaraswamy.logpdf":"var y = base.dists.kumaraswamy.logpdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logpdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.logpdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.logpdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.logpdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logpdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logpdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.logpdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.logpdf( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.logpdf.factory":"var mylogpdf = base.dists.kumaraswamy.logpdf.factory( 0.5, 1.0 );\nvar y = mylogpdf( 0.8 )\ny = mylogpdf( 0.3 )\n","base.dists.kumaraswamy.mean":"var v = base.dists.kumaraswamy.mean( 1.5, 1.5 )\nv = base.dists.kumaraswamy.mean( 4.0, 12.0 )\nv = base.dists.kumaraswamy.mean( 16.0, 8.0 )\n","base.dists.kumaraswamy.median":"var v = base.dists.kumaraswamy.median( 1.0, 1.0 )\nv = base.dists.kumaraswamy.median( 4.0, 12.0 )\nv = base.dists.kumaraswamy.median( 16.0, 8.0 )\n","base.dists.kumaraswamy.mode":"var v = base.dists.kumaraswamy.mode( 1.5, 1.5 )\nv = base.dists.kumaraswamy.mode( 4.0, 12.0 )\nv = base.dists.kumaraswamy.mode( 16.0, 8.0 )\n","base.dists.kumaraswamy.pdf":"var y = base.dists.kumaraswamy.pdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.pdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.pdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.pdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.pdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.pdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.pdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.pdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.pdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.pdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.pdf( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.pdf.factory":"var mypdf = base.dists.kumaraswamy.pdf.factory( 0.5, 1.0 );\nvar y = mypdf( 0.8 )\ny = mypdf( 0.3 )\n","base.dists.kumaraswamy.quantile":"var y = base.dists.kumaraswamy.quantile( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.quantile( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.quantile( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.quantile( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.quantile( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.quantile( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.quantile( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.quantile( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.quantile( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.quantile( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.quantile( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.quantile.factory":"var myQuantile = base.dists.kumaraswamy.quantile.factory( 0.5, 1.0 );\nvar y = myQuantile( 0.8 )\ny = myQuantile( 0.3 )\n","base.dists.kumaraswamy.skewness":"var v = base.dists.kumaraswamy.skewness( 1.0, 1.0 )\nv = base.dists.kumaraswamy.skewness( 4.0, 12.0 )\nv = base.dists.kumaraswamy.skewness( 16.0, 8.0 )\n","base.dists.kumaraswamy.stdev":"var v = base.dists.kumaraswamy.stdev( 1.0, 1.0 )\nv = base.dists.kumaraswamy.stdev( 4.0, 12.0 )\nv = base.dists.kumaraswamy.stdev( 16.0, 8.0 )\n","base.dists.kumaraswamy.variance":"var v = base.dists.kumaraswamy.variance( 1.0, 1.0 )\nv = base.dists.kumaraswamy.variance( 4.0, 12.0 )\nv = base.dists.kumaraswamy.variance( 16.0, 8.0 )\n","base.dists.laplace.cdf":"var y = base.dists.laplace.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.cdf( 5.0, 10.0, 3.0 )\ny = base.dists.laplace.cdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.cdf( 2, NaN, 1.0 )\ny = base.dists.laplace.cdf( 2.0, 0.0, NaN )\ny = base.dists.laplace.cdf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.cdf.factory":"var myCDF = base.dists.laplace.cdf.factory( 2.0, 3.0 );\nvar y = myCDF( 10.0 )\ny = myCDF( 2.0 )\n","base.dists.laplace.entropy":"var y = base.dists.laplace.entropy( 0.0, 1.0 )\ny = base.dists.laplace.entropy( 4.0, 2.0 )\ny = base.dists.laplace.entropy( NaN, 1.0 )\ny = base.dists.laplace.entropy( 0.0, NaN )\ny = base.dists.laplace.entropy( 0.0, 0.0 )\n","base.dists.laplace.kurtosis":"var y = base.dists.laplace.kurtosis( 0.0, 1.0 )\ny = base.dists.laplace.kurtosis( 4.0, 2.0 )\ny = base.dists.laplace.kurtosis( NaN, 1.0 )\ny = base.dists.laplace.kurtosis( 0.0, NaN )\ny = base.dists.laplace.kurtosis( 0.0, 0.0 )\n","base.dists.laplace.Laplace":"var laplace = base.dists.laplace.Laplace( -2.0, 3.0 );\nlaplace.mu\nlaplace.b\nlaplace.entropy\nlaplace.kurtosis\nlaplace.mean\nlaplace.median\nlaplace.mode\nlaplace.skewness\nlaplace.stdev\nlaplace.variance\nlaplace.cdf( 0.8 )\nlaplace.logcdf( 0.8 )\nlaplace.logpdf( 1.0 )\nlaplace.mgf( 0.2 )\nlaplace.pdf( 2.0 )\nlaplace.quantile( 0.9 )\n","base.dists.laplace.logcdf":"var y = base.dists.laplace.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.logcdf( 5.0, 10.0, 3.0 )\ny = base.dists.laplace.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.logcdf( 2, NaN, 1.0 )\ny = base.dists.laplace.logcdf( 2.0, 0.0, NaN )\ny = base.dists.laplace.logcdf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.logcdf.factory":"var mylogcdf = base.dists.laplace.logcdf.factory( 2.0, 3.0 );\nvar y = mylogcdf( 10.0 )\ny = mylogcdf( 2.0 )\n","base.dists.laplace.logpdf":"var y = base.dists.laplace.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.logpdf( -1.0, 2.0, 3.0 )\ny = base.dists.laplace.logpdf( 2.5, 2.0, 3.0 )\ny = base.dists.laplace.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.laplace.logpdf( 0.0, 0.0, NaN )\ny = base.dists.laplace.logpdf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.logpdf.factory":"var mylogPDF = base.dists.laplace.logpdf.factory( 10.0, 2.0 );\nvar y = mylogPDF( 10.0 )\n","base.dists.laplace.mean":"var y = base.dists.laplace.mean( 0.0, 1.0 )\ny = base.dists.laplace.mean( 4.0, 2.0 )\ny = base.dists.laplace.mean( NaN, 1.0 )\ny = base.dists.laplace.mean( 0.0, NaN )\ny = base.dists.laplace.mean( 0.0, 0.0 )\n","base.dists.laplace.median":"var y = base.dists.laplace.median( 0.0, 1.0 )\ny = base.dists.laplace.median( 4.0, 2.0 )\ny = base.dists.laplace.median( NaN, 1.0 )\ny = base.dists.laplace.median( 0.0, NaN )\ny = base.dists.laplace.median( 0.0, 0.0 )\n","base.dists.laplace.mgf":"var y = base.dists.laplace.mgf( 0.5, 0.0, 1.0 )\ny = base.dists.laplace.mgf( 0.0, 0.0, 1.0 )\ny = base.dists.laplace.mgf( -1.0, 4.0, 0.2 )\ny = base.dists.laplace.mgf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.mgf( 0.0, NaN, 1.0 )\ny = base.dists.laplace.mgf( 0.0, 0.0, NaN )\ny = base.dists.laplace.mgf( 1.0, 0.0, 2.0 )\ny = base.dists.laplace.mgf( -0.5, 0.0, 4.0 )\ny = base.dists.laplace.mgf( 2.0, 0.0, 0.0 )\ny = base.dists.laplace.mgf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.mgf.factory":"var mymgf = base.dists.laplace.mgf.factory( 4.0, 2.0 );\nvar y = mymgf( 0.2 )\ny = mymgf( 0.4 )\n","base.dists.laplace.mode":"var y = base.dists.laplace.mode( 0.0, 1.0 )\ny = base.dists.laplace.mode( 4.0, 2.0 )\ny = base.dists.laplace.mode( NaN, 1.0 )\ny = base.dists.laplace.mode( 0.0, NaN )\ny = base.dists.laplace.mode( 0.0, 0.0 )\n","base.dists.laplace.pdf":"var y = base.dists.laplace.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.pdf( -1.0, 2.0, 3.0 )\ny = base.dists.laplace.pdf( 2.5, 2.0, 3.0 )\ny = base.dists.laplace.pdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.pdf( 0.0, NaN, 1.0 )\ny = base.dists.laplace.pdf( 0.0, 0.0, NaN )\ny = base.dists.laplace.pdf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.pdf.factory":"var myPDF = base.dists.laplace.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\n","base.dists.laplace.quantile":"var y = base.dists.laplace.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.laplace.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.laplace.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.laplace.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.laplace.quantile( NaN, 0.0, 1.0 )\ny = base.dists.laplace.quantile( 0.0, NaN, 1.0 )\ny = base.dists.laplace.quantile( 0.0, 0.0, NaN )\ny = base.dists.laplace.quantile( 0.5, 0.0, -1.0 )\n","base.dists.laplace.quantile.factory":"var myQuantile = base.dists.laplace.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\ny = myQuantile( 0.8 )\n","base.dists.laplace.skewness":"var y = base.dists.laplace.skewness( 0.0, 1.0 )\ny = base.dists.laplace.skewness( 4.0, 2.0 )\ny = base.dists.laplace.skewness( NaN, 1.0 )\ny = base.dists.laplace.skewness( 0.0, NaN )\ny = base.dists.laplace.skewness( 0.0, 0.0 )\n","base.dists.laplace.stdev":"var y = base.dists.laplace.stdev( 0.0, 1.0 )\ny = base.dists.laplace.stdev( 4.0, 2.0 )\ny = base.dists.laplace.stdev( NaN, 1.0 )\ny = base.dists.laplace.stdev( 0.0, NaN )\ny = base.dists.laplace.stdev( 0.0, 0.0 )\n","base.dists.laplace.variance":"var y = base.dists.laplace.variance( 0.0, 1.0 )\ny = base.dists.laplace.variance( 4.0, 2.0 )\ny = base.dists.laplace.variance( NaN, 1.0 )\ny = base.dists.laplace.variance( 0.0, NaN )\ny = base.dists.laplace.variance( 0.0, 0.0 )\n","base.dists.levy.cdf":"var y = base.dists.levy.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.levy.cdf( 12.0, 10.0, 3.0 )\ny = base.dists.levy.cdf( 9.0, 10.0, 3.0 )\ny = base.dists.levy.cdf( NaN, 0.0, 1.0 )\ny = base.dists.levy.cdf( 2, NaN, 1.0 )\ny = base.dists.levy.cdf( 2.0, 0.0, NaN )\ny = base.dists.levy.cdf( 2.0, 0.0, -1.0 )\n","base.dists.levy.cdf.factory":"var myCDF = base.dists.levy.cdf.factory( 2.0, 3.0 );\nvar y = myCDF( 10.0 )\ny = myCDF( 2.0 )\n","base.dists.levy.entropy":"var y = base.dists.levy.entropy( 0.0, 1.0 )\ny = base.dists.levy.entropy( 4.0, 2.0 )\ny = base.dists.levy.entropy( NaN, 1.0 )\ny = base.dists.levy.entropy( 0.0, NaN )\ny = base.dists.levy.entropy( 0.0, 0.0 )\n","base.dists.levy.Levy":"var levy = base.dists.levy.Levy( -2.0, 3.0 );\nlevy.mu\nlevy.c\nlevy.entropy\nlevy.mean\nlevy.median\nlevy.mode\nlevy.stdev\nlevy.variance\nlevy.cdf( 0.8 )\nlevy.logcdf( 0.8 )\nlevy.logpdf( 1.0 )\nlevy.pdf( 1.0 )\nlevy.quantile( 0.8 )\n","base.dists.levy.logcdf":"var y = base.dists.levy.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.levy.logcdf( 12.0, 10.0, 3.0 )\ny = base.dists.levy.logcdf( 9.0, 10.0, 3.0 )\ny = base.dists.levy.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.levy.logcdf( 2, NaN, 1.0 )\ny = base.dists.levy.logcdf( 2.0, 0.0, NaN )\ny = base.dists.levy.logcdf( 2.0, 0.0, -1.0 )\n","base.dists.levy.logcdf.factory":"var mylogcdf = base.dists.levy.logcdf.factory( 2.0, 3.0 );\nvar y = mylogcdf( 10.0 )\ny = mylogcdf( 2.0 )\n","base.dists.levy.logpdf":"var y = base.dists.levy.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.levy.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.levy.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.levy.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.levy.logpdf( 0.0, 0.0, NaN )\ny = base.dists.levy.logpdf( 2.0, 0.0, -1.0 )\n","base.dists.levy.logpdf.factory":"var mylogPDF = base.dists.levy.logpdf.factory( 10.0, 2.0 );\nvar y = mylogPDF( 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myPDF = base.dists.levy.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 11.0 )\n","base.dists.levy.quantile":"var y = base.dists.levy.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.levy.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.levy.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.levy.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.levy.quantile( NaN, 0.0, 1.0 )\ny = base.dists.levy.quantile( 0.0, NaN, 1.0 )\ny = base.dists.levy.quantile( 0.0, 0.0, NaN )\ny = base.dists.levy.quantile( 0.5, 0.0, -1.0 )\n","base.dists.levy.quantile.factory":"var myQuantile = base.dists.levy.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.levy.stdev":"var y = base.dists.levy.stdev( 0.0, 1.0 )\ny = base.dists.levy.stdev( 4.0, 3.0 )\ny = base.dists.levy.stdev( NaN, 1.0 )\ny = base.dists.levy.stdev( 0.0, NaN )\ny = base.dists.levy.stdev( 0.0, 0.0 )\n","base.dists.levy.variance":"var y = base.dists.levy.variance( 0.0, 1.0 )\ny = base.dists.levy.variance( 4.0, 3.0 )\ny = base.dists.levy.variance( NaN, 1.0 )\ny = base.dists.levy.variance( 0.0, NaN )\ny = base.dists.levy.variance( 0.0, 0.0 )\n","base.dists.logistic.cdf":"var y = base.dists.logistic.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.logistic.cdf( 5.0, 10.0, 3.0 )\ny = base.dists.logistic.cdf( 2.0, 0.0, NaN )\ny = base.dists.logistic.cdf( 2.0, NaN, 1.0 )\ny = base.dists.logistic.cdf( NaN, 0.0, 1.0 )\ny = base.dists.logistic.cdf( 2.0, 8.0, 0.0 )\ny = base.dists.logistic.cdf( 8.0, 8.0, 0.0 )\ny = base.dists.logistic.cdf( 10.0, 8.0, 0.0 )\n","base.dists.logistic.cdf.factory":"var mycdf = base.dists.logistic.cdf.factory( 3.0, 1.5 );\nvar y = mycdf( 1.0 )\n","base.dists.logistic.entropy":"var y = base.dists.logistic.entropy( 0.0, 1.0 )\ny = base.dists.logistic.entropy( 4.0, 2.0 )\ny = base.dists.logistic.entropy( NaN, 1.0 )\ny = base.dists.logistic.entropy( 0.0, NaN )\ny = base.dists.logistic.entropy( 0.0, 0.0 )\n","base.dists.logistic.kurtosis":"var y = base.dists.logistic.kurtosis( 0.0, 1.0 )\ny = base.dists.logistic.kurtosis( 4.0, 2.0 )\ny = base.dists.logistic.kurtosis( NaN, 1.0 )\ny = base.dists.logistic.kurtosis( 0.0, NaN )\ny = base.dists.logistic.kurtosis( 0.0, 0.0 )\n","base.dists.logistic.logcdf":"var y = base.dists.logistic.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.logistic.logcdf( 5.0, 10.0, 3.0 )\ny = base.dists.logistic.logcdf( 2.0, 0.0, NaN )\ny = base.dists.logistic.logcdf( 2, NaN, 1.0 )\ny = base.dists.logistic.logcdf( NaN, 0.0, 1.0 )\n","base.dists.logistic.logcdf.factory":"var mylogcdf = base.dists.logistic.logcdf.factory( 3.0, 1.5 );\nvar y = mylogcdf( 1.0 )\n","base.dists.logistic.Logistic":"var logistic = base.dists.logistic.Logistic( -2.0, 3.0 );\nlogistic.mu\nlogistic.s\nlogistic.entropy\nlogistic.kurtosis\nlogistic.mean\nlogistic.median\nlogistic.mode\nlogistic.skewness\nlogistic.stdev\nlogistic.variance\nlogistic.cdf( 0.8 )\nlogistic.logcdf( 0.8 )\nlogistic.logpdf( 2.0 )\nlogistic.mgf( 0.2 )\nlogistic.pdf( 2.0 )\nlogistic.quantile( 0.9 )\n","base.dists.logistic.logpdf":"var y = base.dists.logistic.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.logistic.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.logistic.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.logistic.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.logistic.logpdf( 0.0, 0.0, NaN )\ny = base.dists.logistic.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.logistic.logpdf( 2.0, 8.0, 0.0 )\ny = base.dists.logistic.logpdf( 8.0, 8.0, 0.0 )\n","base.dists.logistic.logpdf.factory":"var mylogpdf = base.dists.logistic.logpdf.factory( 10.0, 2.0 );\nvar y = mylogpdf( 10.0 )\n","base.dists.logistic.mean":"var y = base.dists.logistic.mean( 0.0, 1.0 )\ny = base.dists.logistic.mean( 4.0, 2.0 )\ny = base.dists.logistic.mean( NaN, 1.0 )\ny = base.dists.logistic.mean( 0.0, NaN )\ny = base.dists.logistic.mean( 0.0, 0.0 )\n","base.dists.logistic.median":"var y = base.dists.logistic.median( 0.0, 1.0 )\ny = base.dists.logistic.median( 4.0, 2.0 )\ny = base.dists.logistic.median( NaN, 1.0 )\ny = base.dists.logistic.median( 0.0, NaN )\ny = base.dists.logistic.median( 0.0, 0.0 )\n","base.dists.logistic.mgf":"var y = base.dists.logistic.mgf( 0.9, 0.0, 1.0 )\ny = base.dists.logistic.mgf( 0.1, 4.0, 4.0 )\ny = base.dists.logistic.mgf( -0.2, 4.0, 4.0 )\ny = base.dists.logistic.mgf( 0.5, 0.0, -1.0 )\ny = base.dists.logistic.mgf( 0.5, 0.0, 4.0 )\ny = base.dists.logistic.mgf( NaN, 0.0, 1.0 )\ny = base.dists.logistic.mgf( 0.0, NaN, 1.0 )\ny = base.dists.logistic.mgf( 0.0, 0.0, NaN )\n","base.dists.logistic.mgf.factory":"var mymgf = base.dists.logistic.mgf.factory( 10.0, 0.5 );\nvar y = mymgf( 0.5 )\ny = mymgf( 2.0 )\n","base.dists.logistic.mode":"var y = base.dists.logistic.mode( 0.0, 1.0 )\ny = base.dists.logistic.mode( 4.0, 2.0 )\ny = base.dists.logistic.mode( NaN, 1.0 )\ny = base.dists.logistic.mode( 0.0, NaN )\ny = base.dists.logistic.mode( 0.0, 0.0 )\n","base.dists.logistic.pdf":"var y = base.dists.logistic.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.logistic.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.logistic.pdf( NaN, 0.0, 1.0 )\ny = base.dists.logistic.pdf( 0.0, NaN, 1.0 )\ny = base.dists.logistic.pdf( 0.0, 0.0, NaN )\ny = base.dists.logistic.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.logistic.pdf( 2.0, 8.0, 0.0 )\ny = base.dists.logistic.pdf( 8.0, 8.0, 0.0 )\n","base.dists.logistic.pdf.factory":"var myPDF = base.dists.logistic.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\n","base.dists.logistic.quantile":"var y = base.dists.logistic.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.logistic.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.logistic.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.logistic.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.logistic.quantile( NaN, 0.0, 1.0 )\ny = base.dists.logistic.quantile( 0.0, NaN, 1.0 )\ny = base.dists.logistic.quantile( 0.0, 0.0, NaN )\ny = base.dists.logistic.quantile( 0.5, 0.0, -1.0 )\n","base.dists.logistic.quantile.factory":"var myQuantile = base.dists.logistic.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.logistic.skewness":"var y = base.dists.logistic.skewness( 0.0, 1.0 )\ny = base.dists.logistic.skewness( 4.0, 2.0 )\ny = base.dists.logistic.skewness( NaN, 1.0 )\ny = base.dists.logistic.skewness( 0.0, NaN )\ny = base.dists.logistic.skewness( 0.0, 0.0 )\n","base.dists.logistic.stdev":"var y = base.dists.logistic.stdev( 0.0, 1.0 )\ny = base.dists.logistic.stdev( 4.0, 2.0 )\ny = base.dists.logistic.stdev( NaN, 1.0 )\ny = base.dists.logistic.stdev( 0.0, NaN )\ny = base.dists.logistic.stdev( 0.0, 0.0 )\n","base.dists.logistic.variance":"var y = base.dists.logistic.variance( 0.0, 1.0 )\ny = base.dists.logistic.variance( 4.0, 2.0 )\ny = base.dists.logistic.variance( NaN, 1.0 )\ny = base.dists.logistic.variance( 0.0, NaN )\ny = base.dists.logistic.variance( 0.0, 0.0 )\n","base.dists.lognormal.cdf":"var y = base.dists.lognormal.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.cdf( 5.0, 10.0, 3.0 )\ny = base.dists.lognormal.cdf( 2.0, 0.0, NaN )\ny = base.dists.lognormal.cdf( 2.0, NaN, 1.0 )\ny = base.dists.lognormal.cdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.cdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.cdf( 2.0, 0.0, 0.0 )\n","base.dists.lognormal.cdf.factory":"var myCDF = base.dists.lognormal.cdf.factory( 3.0, 1.5 );\nvar y = myCDF( 1.0 )\ny = myCDF( 4.0 )\n","base.dists.lognormal.entropy":"var y = base.dists.lognormal.entropy( 0.0, 1.0 )\ny = base.dists.lognormal.entropy( 5.0, 2.0 )\ny = base.dists.lognormal.entropy( NaN, 1.0 )\ny = base.dists.lognormal.entropy( 0.0, NaN )\ny = base.dists.lognormal.entropy( 0.0, 0.0 )\n","base.dists.lognormal.kurtosis":"var y = base.dists.lognormal.kurtosis( 0.0, 1.0 )\ny = base.dists.lognormal.kurtosis( 5.0, 2.0 )\ny = base.dists.lognormal.kurtosis( NaN, 1.0 )\ny = base.dists.lognormal.kurtosis( 0.0, NaN )\ny = base.dists.lognormal.kurtosis( 0.0, 0.0 )\n","base.dists.lognormal.LogNormal":"var lognormal = base.dists.lognormal.LogNormal( -2.0, 3.0 );\nlognormal.mu\nlognormal.sigma\nlognormal.entropy\nlognormal.kurtosis\nlognormal.mean\nlognormal.median\nlognormal.mode\nlognormal.skewness\nlognormal.stdev\nlognormal.variance\nlognormal.cdf( 0.8 )\nlognormal.logcdf( 0.8 )\nlognormal.logpdf( 2.0 )\nlognormal.pdf( 2.0 )\nlognormal.quantile( 0.9 )\n","base.dists.lognormal.logcdf":"var y = base.dists.lognormal.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.logcdf( 13.0, 4.0, 2.0 )\ny = base.dists.lognormal.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.logcdf( 0.0, 0.0, NaN )\ny = base.dists.lognormal.logcdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.logcdf( 2.0, 8.0, 0.0 )\ny = base.dists.lognormal.logcdf( 8.0, 8.0, 0.0 )\n","base.dists.lognormal.logcdf.factory":"var mylogcdf = base.dists.lognormal.logcdf.factory( 10.0, 2.0 );\nvar y = mylogcdf( 10.0 )\n","base.dists.lognormal.logpdf":"var y = base.dists.lognormal.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.logpdf( 1.0, 0.0, 1.0 )\ny = base.dists.lognormal.logpdf( 1.0, 3.0, 1.0 )\ny = base.dists.lognormal.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.lognormal.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.logpdf( 0.0, 0.0, NaN )\ny = base.dists.lognormal.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.logpdf( 2.0, 0.0, 0.0 )\n","base.dists.lognormal.logpdf.factory":"var mylogPDF = base.dists.lognormal.logpdf.factory( 4.0, 2.0 );\nvar y = mylogPDF( 10.0 )\ny = mylogPDF( 2.0 )\n","base.dists.lognormal.mean":"var y = base.dists.lognormal.mean( 0.0, 1.0 )\ny = base.dists.lognormal.mean( 4.0, 2.0 )\ny = base.dists.lognormal.mean( NaN, 1.0 )\ny = base.dists.lognormal.mean( 0.0, NaN )\ny = base.dists.lognormal.mean( 0.0, 0.0 )\n","base.dists.lognormal.median":"var y = base.dists.lognormal.median( 0.0, 1.0 )\ny = base.dists.lognormal.median( 5.0, 2.0 )\ny = base.dists.lognormal.median( NaN, 1.0 )\ny = base.dists.lognormal.median( 0.0, NaN )\ny = base.dists.lognormal.median( 0.0, 0.0 )\n","base.dists.lognormal.mode":"var y = base.dists.lognormal.mode( 0.0, 1.0 )\ny = base.dists.lognormal.mode( 5.0, 2.0 )\ny = base.dists.lognormal.mode( NaN, 1.0 )\ny = base.dists.lognormal.mode( 0.0, NaN )\ny = base.dists.lognormal.mode( 0.0, 0.0 )\n","base.dists.lognormal.pdf":"var y = base.dists.lognormal.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.pdf( 1.0, 0.0, 1.0 )\ny = base.dists.lognormal.pdf( 1.0, 3.0, 1.0 )\ny = base.dists.lognormal.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.lognormal.pdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.pdf( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.pdf( 0.0, 0.0, NaN )\ny = base.dists.lognormal.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.pdf( 2.0, 0.0, 0.0 )\n","base.dists.lognormal.pdf.factory":"var myPDF = base.dists.lognormal.pdf.factory( 4.0, 2.0 );\nvar y = myPDF( 10.0 )\ny = myPDF( 2.0 )\n","base.dists.lognormal.quantile":"var y = base.dists.lognormal.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.lognormal.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.quantile( 0.0, 0.0, NaN )\ny = base.dists.lognormal.quantile( 0.5, 0.0, -1.0 )\ny = base.dists.lognormal.quantile( 0.5, 0.0, 0.0 )\n","base.dists.lognormal.quantile.factory":"var myQuantile = base.dists.lognormal.quantile.factory( 4.0, 2.0 );\nvar y = myQuantile( 0.2 )\ny = myQuantile( 0.8 )\n","base.dists.lognormal.skewness":"var y = base.dists.lognormal.skewness( 0.0, 1.0 )\ny = base.dists.lognormal.skewness( 5.0, 2.0 )\ny = base.dists.lognormal.skewness( NaN, 1.0 )\ny = base.dists.lognormal.skewness( 0.0, NaN )\ny = base.dists.lognormal.skewness( 0.0, 0.0 )\n","base.dists.lognormal.stdev":"var y = base.dists.lognormal.stdev( 0.0, 1.0 )\ny = base.dists.lognormal.stdev( 4.0, 2.0 )\ny = base.dists.lognormal.stdev( NaN, 1.0 )\ny = base.dists.lognormal.stdev( 0.0, NaN )\ny = base.dists.lognormal.stdev( 0.0, 0.0 )\n","base.dists.lognormal.variance":"var y = base.dists.lognormal.variance( 0.0, 1.0 )\ny = base.dists.lognormal.variance( 4.0, 2.0 )\ny = base.dists.lognormal.variance( NaN, 1.0 )\ny = base.dists.lognormal.variance( 0.0, NaN )\ny = base.dists.lognormal.variance( 0.0, 0.0 )\n","base.dists.negativeBinomial.cdf":"var y = base.dists.negativeBinomial.cdf( 5.0, 20.0, 0.8 )\ny = base.dists.negativeBinomial.cdf( 21.0, 20.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( 5.0, 10.0, 0.4 )\ny = base.dists.negativeBinomial.cdf( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.cdf( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.cdf( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.cdf( 2.0, 0.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( 2.0, -2.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.cdf( 0.0, 20.0, NaN )\ny = base.dists.negativeBinomial.cdf( 2.0, 20, -1.0 )\ny = base.dists.negativeBinomial.cdf( 2.0, 20, 1.5 )\n","base.dists.negativeBinomial.cdf.factory":"var myCDF = base.dists.negativeBinomial.cdf.factory( 10, 0.5 );\nvar y = myCDF( 3.0 )\ny = myCDF( 11.0 )\n","base.dists.negativeBinomial.kurtosis":"var v = base.dists.negativeBinomial.kurtosis( 100, 0.2 )\nv = base.dists.negativeBinomial.kurtosis( 20, 0.5 )\n","base.dists.negativeBinomial.logpmf":"var y = base.dists.negativeBinomial.logpmf( 5.0, 20.0, 0.8 )\ny = base.dists.negativeBinomial.logpmf( 21.0, 20.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 5.0, 10.0, 0.4 )\ny = base.dists.negativeBinomial.logpmf( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.logpmf( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.logpmf( 2.0, 0.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 2.0, -2.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 2.0, 20, -1.0 )\ny = base.dists.negativeBinomial.logpmf( 2.0, 20, 1.5 )\ny = base.dists.negativeBinomial.logpmf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 0.0, 20.0, NaN )\n","base.dists.negativeBinomial.logpmf.factory":"var mylogPMF = base.dists.negativeBinomial.logpmf.factory( 10, 0.5 );\nvar y = mylogPMF( 3.0 )\ny = mylogPMF( 5.0 )\n","base.dists.negativeBinomial.mean":"var v = base.dists.negativeBinomial.mean( 100, 0.2 )\nv = base.dists.negativeBinomial.mean( 20, 0.5 )\n","base.dists.negativeBinomial.mgf":"var y = base.dists.negativeBinomial.mgf( 0.05, 20.0, 0.8 )\ny = base.dists.negativeBinomial.mgf( 0.1, 20.0, 0.1 )\ny = base.dists.negativeBinomial.mgf( 0.5, 10.0, 0.4 )\ny = base.dists.negativeBinomial.mgf( 0.1, 0.0, 0.5 )\ny = base.dists.negativeBinomial.mgf( 0.1, -2.0, 0.5 )\ny = base.dists.negativeBinomial.mgf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.mgf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.mgf( 0.0, 20.0, NaN )\ny = base.dists.negativeBinomial.mgf( 0.2, 20, -1.0 )\ny = base.dists.negativeBinomial.mgf( 0.2, 20, 1.5 )\n","base.dists.negativeBinomial.mgf.factory":"var myMGF = base.dists.negativeBinomial.mgf.factory( 4.3, 0.4 );\nvar y = myMGF( 0.2 )\ny = myMGF( 0.4 )\n","base.dists.negativeBinomial.mode":"var v = base.dists.negativeBinomial.mode( 100, 0.2 )\nv = base.dists.negativeBinomial.mode( 20, 0.5 )\n","base.dists.negativeBinomial.NegativeBinomial":"var nbinomial = base.dists.negativeBinomial.NegativeBinomial( 8.0, 0.5 );\nnbinomial.r\nnbinomial.p\nnbinomial.kurtosis\nnbinomial.mean\nnbinomial.mode\nnbinomial.skewness\nnbinomial.stdev\nnbinomial.variance\nnbinomial.cdf( 2.9 )\nnbinomial.logpmf( 3.0 )\nnbinomial.mgf( 0.2 )\nnbinomial.pmf( 3.0 )\nnbinomial.quantile( 0.8 )\n","base.dists.negativeBinomial.pmf":"var y = base.dists.negativeBinomial.pmf( 5.0, 20.0, 0.8 )\ny = base.dists.negativeBinomial.pmf( 21.0, 20.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 5.0, 10.0, 0.4 )\ny = base.dists.negativeBinomial.pmf( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.pmf( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.pmf( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.pmf( 2.0, 0.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 2.0, -2.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 2.0, 20, -1.0 )\ny = base.dists.negativeBinomial.pmf( 2.0, 20, 1.5 )\ny = base.dists.negativeBinomial.pmf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.pmf( 0.0, 20.0, NaN )\n","base.dists.negativeBinomial.pmf.factory":"var myPMF = base.dists.negativeBinomial.pmf.factory( 10, 0.5 );\nvar y = myPMF( 3.0 )\ny = myPMF( 5.0 )\n","base.dists.negativeBinomial.quantile":"var y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.2 )\ny = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.8 )\ny = base.dists.negativeBinomial.quantile( 0.5, 10.0, 0.4 )\ny = base.dists.negativeBinomial.quantile( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.quantile( 1.1, 20.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( -0.1, 20.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.quantile( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.quantile( 0.5, 0.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.5, -2.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.3, 20.0, -1.0 )\ny = base.dists.negativeBinomial.quantile( 0.3, 20.0, 1.5 )\ny = base.dists.negativeBinomial.quantile( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.3, NaN, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.3, 20.0, NaN )\n","base.dists.negativeBinomial.quantile.factory":"var myQuantile = base.dists.negativeBinomial.quantile.factory( 10.0, 0.5 );\nvar y = myQuantile( 0.1 )\ny = myQuantile( 0.9 )\n","base.dists.negativeBinomial.skewness":"var v = base.dists.negativeBinomial.skewness( 100, 0.2 )\nv = base.dists.negativeBinomial.skewness( 20, 0.5 )\n","base.dists.negativeBinomial.stdev":"var v = base.dists.negativeBinomial.stdev( 100, 0.2 )\nv = base.dists.negativeBinomial.stdev( 20, 0.5 )\n","base.dists.negativeBinomial.variance":"var v = base.dists.negativeBinomial.variance( 100, 0.2 )\nv = base.dists.negativeBinomial.variance( 20, 0.5 )\n","base.dists.normal.cdf":"var y = base.dists.normal.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.cdf( -1.0, -1.0, 2.0 )\ny = base.dists.normal.cdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.cdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.cdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.cdf( 0.0, 0.0, NaN )\ny = base.dists.normal.cdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.cdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.cdf( 8.0, 8.0, 0.0 )\ny = base.dists.normal.cdf( 10.0, 8.0, 0.0 )\n","base.dists.normal.cdf.factory":"var myCDF = base.dists.normal.cdf.factory( 10.0, 2.0 );\nvar y = myCDF( 10.0 )\n","base.dists.normal.entropy":"var y = base.dists.normal.entropy( 0.0, 1.0 )\ny = base.dists.normal.entropy( 4.0, 3.0 )\ny = base.dists.normal.entropy( NaN, 1.0 )\ny = base.dists.normal.entropy( 0.0, NaN )\ny = base.dists.normal.entropy( 0.0, 0.0 )\n","base.dists.normal.kurtosis":"var y = base.dists.normal.kurtosis( 0.0, 1.0 )\ny = base.dists.normal.kurtosis( 4.0, 3.0 )\ny = base.dists.normal.kurtosis( NaN, 1.0 )\ny = base.dists.normal.kurtosis( 0.0, NaN )\ny = base.dists.normal.kurtosis( 0.0, 0.0 )\n","base.dists.normal.logcdf":"var y = base.dists.normal.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.logcdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.logcdf( 0.0, 0.0, NaN )\ny = base.dists.normal.logcdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.logcdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.logcdf( 8.0, 8.0, 0.0 )\n","base.dists.normal.logcdf.factory":"var mylogcdf = base.dists.normal.logcdf.factory( 10.0, 2.0 );\nvar y = mylogcdf( 10.0 )\n","base.dists.normal.logpdf":"var y = base.dists.normal.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.logpdf( 0.0, 0.0, NaN )\ny = base.dists.normal.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.logpdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.logpdf( 8.0, 8.0, 0.0 )\n","base.dists.normal.logpdf.factory":"var myLogPDF = base.dists.normal.logpdf.factory( 10.0, 2.0 );\nvar y = myLogPDF( 10.0 )\n","base.dists.normal.mean":"var y = base.dists.normal.mean( 0.0, 1.0 )\ny = base.dists.normal.mean( 4.0, 2.0 )\ny = base.dists.normal.mean( NaN, 1.0 )\ny = base.dists.normal.mean( 0.0, NaN )\ny = base.dists.normal.mean( 0.0, 0.0 )\n","base.dists.normal.median":"var y = base.dists.normal.median( 0.0, 1.0 )\ny = base.dists.normal.median( 4.0, 2.0 )\ny = base.dists.normal.median( NaN, 1.0 )\ny = base.dists.normal.median( 0.0, NaN )\ny = base.dists.normal.median( 0.0, 0.0 )\n","base.dists.normal.mgf":"var y = base.dists.normal.mgf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.mgf( 0.0, 0.0, 1.0 )\ny = base.dists.normal.mgf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.mgf( NaN, 0.0, 1.0 )\ny = base.dists.normal.mgf( 0.0, NaN, 1.0 )\ny = base.dists.normal.mgf( 0.0, 0.0, NaN )\ny = base.dists.normal.mgf( 2.0, 0.0, 0.0 )\n","base.dists.normal.mgf.factory":"var myMGF = base.dists.normal.mgf.factory( 4.0, 2.0 );\nvar y = myMGF( 1.0 )\ny = myMGF( 0.5 )\n","base.dists.normal.mode":"var y = base.dists.normal.mode( 0.0, 1.0 )\ny = base.dists.normal.mode( 4.0, 2.0 )\ny = base.dists.normal.mode( NaN, 1.0 )\ny = base.dists.normal.mode( 0.0, NaN )\ny = base.dists.normal.mode( 0.0, 0.0 )\n","base.dists.normal.Normal":"var normal = base.dists.normal.Normal( -2.0, 3.0 );\nnormal.mu\nnormal.sigma\nnormal.entropy\nnormal.kurtosis\nnormal.mean\nnormal.median\nnormal.mode\nnormal.skewness\nnormal.stdev\nnormal.variance\nnormal.cdf( 0.8 )\nnormal.logcdf( 0.8 )\nnormal.logpdf( 2.0 )\nnormal.mgf( 0.2 )\nnormal.pdf( 2.0 )\nnormal.quantile( 0.9 )\n","base.dists.normal.pdf":"var y = base.dists.normal.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.pdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.pdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.pdf( 0.0, 0.0, NaN )\ny = base.dists.normal.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.pdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.pdf( 8.0, 8.0, 0.0 )\n","base.dists.normal.pdf.factory":"var myPDF = base.dists.normal.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\n","base.dists.normal.quantile":"var y = base.dists.normal.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.normal.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.normal.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.normal.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.normal.quantile( NaN, 0.0, 1.0 )\ny = base.dists.normal.quantile( 0.0, NaN, 1.0 )\ny = base.dists.normal.quantile( 0.0, 0.0, NaN )\ny = base.dists.normal.quantile( 0.5, 0.0, -1.0 )\ny = base.dists.normal.quantile( 0.3, 8.0, 0.0 )\ny = base.dists.normal.quantile( 0.9, 8.0, 0.0 )\n","base.dists.normal.quantile.factory":"var myQuantile = base.dists.normal.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.normal.skewness":"var y = base.dists.normal.skewness( 0.0, 1.0 )\ny = base.dists.normal.skewness( 4.0, 3.0 )\ny = base.dists.normal.skewness( NaN, 1.0 )\ny = base.dists.normal.skewness( 0.0, NaN )\ny = base.dists.normal.skewness( 0.0, 0.0 )\n","base.dists.normal.stdev":"var y = base.dists.normal.stdev( 0.0, 1.0 )\ny = base.dists.normal.stdev( 4.0, 3.0 )\ny = base.dists.normal.stdev( NaN, 1.0 )\ny = base.dists.normal.stdev( 0.0, NaN )\ny = base.dists.normal.stdev( 0.0, 0.0 )\n","base.dists.normal.variance":"var y = base.dists.normal.variance( 0.0, 1.0 )\ny = base.dists.normal.variance( 4.0, 3.0 )\ny = base.dists.normal.variance( NaN, 1.0 )\ny = base.dists.normal.variance( 0.0, NaN )\ny = base.dists.normal.variance( 0.0, 0.0 )\n","base.dists.pareto1.cdf":"var y = base.dists.pareto1.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.pareto1.cdf( 5.0, 2.0, 4.0 )\ny = base.dists.pareto1.cdf( 4.0, 2.0, 2.0 )\ny = base.dists.pareto1.cdf( 1.9, 2.0, 2.0 )\ny = base.dists.pareto1.cdf( PINF, 4.0, 2.0 )\ny = base.dists.pareto1.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.pareto1.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.pareto1.cdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.cdf( 0.0, NaN, 1.0 )\ny = base.dists.pareto1.cdf( 0.0, 1.0, NaN )\n","base.dists.pareto1.cdf.factory":"var myCDF = base.dists.pareto1.cdf.factory( 10.0, 2.0 );\nvar y = myCDF( 3.0 )\ny = myCDF( 2.5 )\n","base.dists.pareto1.entropy":"var v = base.dists.pareto1.entropy( 0.8, 1.0 )\nv = base.dists.pareto1.entropy( 4.0, 12.0 )\nv = base.dists.pareto1.entropy( 8.0, 2.0 )\n","base.dists.pareto1.kurtosis":"var v = base.dists.pareto1.kurtosis( 5.0, 1.0 )\nv = base.dists.pareto1.kurtosis( 4.5, 12.0 )\nv = base.dists.pareto1.kurtosis( 8.0, 2.0 )\n","base.dists.pareto1.logcdf":"var y = base.dists.pareto1.logcdf( 2.0, 1.0, 1.0 )\ny = base.dists.pareto1.logcdf( 5.0, 2.0, 4.0 )\ny = base.dists.pareto1.logcdf( 4.0, 2.0, 2.0 )\ny = base.dists.pareto1.logcdf( 1.9, 2.0, 2.0 )\ny = base.dists.pareto1.logcdf( PINF, 4.0, 2.0 )\ny = base.dists.pareto1.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.pareto1.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.pareto1.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.pareto1.logcdf( 0.0, 1.0, NaN )\n","base.dists.pareto1.logcdf.factory":"var mylogCDF = base.dists.pareto1.logcdf.factory( 10.0, 2.0 );\nvar y = mylogCDF( 3.0 )\ny = mylogCDF( 2.5 )\n","base.dists.pareto1.logpdf":"var y = base.dists.pareto1.logpdf( 4.0, 1.0, 1.0 )\ny = base.dists.pareto1.logpdf( 20.0, 1.0, 10.0 )\ny = base.dists.pareto1.logpdf( 7.0, 2.0, 6.0 )\ny = base.dists.pareto1.logpdf( 7.0, 6.0, 3.0 )\ny = base.dists.pareto1.logpdf( 1.0, 4.0, 2.0 )\ny = base.dists.pareto1.logpdf( 1.5, 4.0, 2.0 )\ny = base.dists.pareto1.logpdf( 0.5, -1.0, 0.5 )\ny = base.dists.pareto1.logpdf( 0.5, 0.5, -1.0 )\ny = base.dists.pareto1.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.logpdf( 0.5, NaN, 1.0 )\ny = base.dists.pareto1.logpdf( 0.5, 1.0, NaN )\n","base.dists.pareto1.logpdf.factory":"var mylogPDF = base.dists.pareto1.logpdf.factory( 0.5, 0.5 );\nvar y = mylogPDF( 0.8 )\ny = mylogPDF( 2.0 )\n","base.dists.pareto1.mean":"var v = base.dists.pareto1.mean( 0.8, 1.0 )\nv = base.dists.pareto1.mean( 4.0, 12.0 )\nv = base.dists.pareto1.mean( 8.0, 2.0 )\n","base.dists.pareto1.median":"var v = base.dists.pareto1.median( 0.8, 1.0 )\nv = base.dists.pareto1.median( 4.0, 12.0 )\nv = base.dists.pareto1.median( 8.0, 2.0 )\n","base.dists.pareto1.mode":"var v = base.dists.pareto1.mode( 0.8, 1.0 )\nv = base.dists.pareto1.mode( 4.0, 12.0 )\nv = base.dists.pareto1.mode( 8.0, 2.0 )\n","base.dists.pareto1.Pareto1":"var pareto1 = base.dists.pareto1.Pareto1( 6.0, 5.0 );\npareto1.alpha\npareto1.beta\npareto1.entropy\npareto1.kurtosis\npareto1.mean\npareto1.median\npareto1.mode\npareto1.skewness\npareto1.variance\npareto1.cdf( 7.0 )\npareto1.logcdf( 7.0 )\npareto1.logpdf( 5.0 )\npareto1.pdf( 5.0 )\npareto1.quantile( 0.8 )\n","base.dists.pareto1.pdf":"var y = base.dists.pareto1.pdf( 4.0, 1.0, 1.0 )\ny = base.dists.pareto1.pdf( 20.0, 1.0, 10.0 )\ny = base.dists.pareto1.pdf( 7.0, 2.0, 6.0 )\ny = base.dists.pareto1.pdf( 7.0, 6.0, 3.0 )\ny = base.dists.pareto1.pdf( 1.0, 4.0, 2.0 )\ny = base.dists.pareto1.pdf( 1.5, 4.0, 2.0 )\ny = base.dists.pareto1.pdf( 0.5, -1.0, 0.5 )\ny = base.dists.pareto1.pdf( 0.5, 0.5, -1.0 )\ny = base.dists.pareto1.pdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.pdf( 0.5, NaN, 1.0 )\ny = base.dists.pareto1.pdf( 0.5, 1.0, NaN )\n","base.dists.pareto1.pdf.factory":"var myPDF = base.dists.pareto1.pdf.factory( 0.5, 0.5 );\nvar y = myPDF( 0.8 )\ny = myPDF( 2.0 )\n","base.dists.pareto1.quantile":"var y = base.dists.pareto1.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.pareto1.quantile( 0.8, 1.0, 10.0 )\ny = base.dists.pareto1.quantile( 0.1, 1.0, 10.0 )\ny = base.dists.pareto1.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.pareto1.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.pareto1.quantile( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.quantile( 0.5, NaN, 1.0 )\ny = base.dists.pareto1.quantile( 0.5, 1.0, NaN )\ny = base.dists.pareto1.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.pareto1.quantile( 0.5, 1.0, -1.0 )\n","base.dists.pareto1.quantile.factory":"var myQuantile = base.dists.pareto1.quantile.factory( 2.5, 0.5 );\nvar y = myQuantile( 0.5 )\ny = myQuantile( 0.8 )\n","base.dists.pareto1.skewness":"var v = base.dists.pareto1.skewness( 3.5, 1.0 )\nv = base.dists.pareto1.skewness( 4.0, 12.0 )\nv = base.dists.pareto1.skewness( 8.0, 2.0 )\n","base.dists.pareto1.stdev":"var v = base.dists.pareto1.stdev( 0.8, 1.0 )\nv = base.dists.pareto1.stdev( 4.0, 12.0 )\nv = base.dists.pareto1.stdev( 8.0, 2.0 )\n","base.dists.pareto1.variance":"var v = base.dists.pareto1.variance( 0.8, 1.0 )\nv = base.dists.pareto1.variance( 4.0, 12.0 )\nv = base.dists.pareto1.variance( 8.0, 2.0 )\n","base.dists.poisson.cdf":"var y = base.dists.poisson.cdf( 2.0, 0.5 )\ny = base.dists.poisson.cdf( 2.0, 10.0 )\ny = base.dists.poisson.cdf( -1.0, 4.0 )\ny = base.dists.poisson.cdf( NaN, 1.0 )\ny = base.dists.poisson.cdf( 0.0, NaN )\ny = base.dists.poisson.cdf( 2.0, -1.0 )\ny = base.dists.poisson.cdf( -2.0, 0.0 )\ny = base.dists.poisson.cdf( 0.0, 0.0 )\ny = base.dists.poisson.cdf( 10.0, 0.0 )\n","base.dists.poisson.cdf.factory":"var mycdf = base.dists.poisson.cdf.factory( 5.0 );\nvar y = mycdf( 3.0 )\ny = mycdf( 8.0 )\n","base.dists.poisson.entropy":"var v = base.dists.poisson.entropy( 11.0 )\nv = base.dists.poisson.entropy( 4.5 )\n","base.dists.poisson.kurtosis":"var v = base.dists.poisson.kurtosis( 11.0 )\nv = base.dists.poisson.kurtosis( 4.5 )\n","base.dists.poisson.logpmf":"var y = base.dists.poisson.logpmf( 4.0, 3.0 )\ny = base.dists.poisson.logpmf( 1.0, 3.0 )\ny = base.dists.poisson.logpmf( -1.0, 2.0 )\ny = base.dists.poisson.logpmf( 0.0, NaN )\ny = base.dists.poisson.logpmf( NaN, 0.5 )\ny = base.dists.poisson.logpmf( 2.0, -0.5 )\ny = base.dists.poisson.logpmf( 2.0, 0.0 )\ny = base.dists.poisson.logpmf( 0.0, 0.0 )\n","base.dists.poisson.logpmf.factory":"var mylogpmf = base.dists.poisson.logpmf.factory( 1.0 );\nvar y = mylogpmf( 3.0 )\ny = mylogpmf( 1.0 )\n","base.dists.poisson.mean":"var v = base.dists.poisson.mean( 11.0 )\nv = base.dists.poisson.mean( 4.5 )\n","base.dists.poisson.median":"var v = base.dists.poisson.median( 11.0 )\nv = base.dists.poisson.median( 4.5 )\n","base.dists.poisson.mgf":"var y = base.dists.poisson.mgf( 1.0, 1.5 )\ny = base.dists.poisson.mgf( 0.5, 0.5 )\ny = base.dists.poisson.mgf( NaN, 0.5 )\ny = base.dists.poisson.mgf( 0.0, NaN )\ny = base.dists.poisson.mgf( -2.0, -1.0 )\n","base.dists.poisson.mgf.factory":"var myMGF = base.dists.poisson.mgf.factory( 2.0 );\nvar y = myMGF( 0.1 )\n","base.dists.poisson.mode":"var v = base.dists.poisson.mode( 11.0 )\nv = base.dists.poisson.mode( 4.5 )\n","base.dists.poisson.pmf":"var y = base.dists.poisson.pmf( 4.0, 3.0 )\ny = base.dists.poisson.pmf( 1.0, 3.0 )\ny = base.dists.poisson.pmf( -1.0, 2.0 )\ny = base.dists.poisson.pmf( 0.0, NaN )\ny = base.dists.poisson.pmf( NaN, 0.5 )\ny = base.dists.poisson.pmf( 2.0, -0.5 )\ny = base.dists.poisson.pmf( 2.0, 0.0 )\ny = base.dists.poisson.pmf( 0.0, 0.0 )\n","base.dists.poisson.pmf.factory":"var mypmf = base.dists.poisson.pmf.factory( 1.0 );\nvar y = mypmf( 3.0 )\ny = mypmf( 1.0 )\n","base.dists.poisson.Poisson":"var poisson = base.dists.poisson.Poisson( 6.0 );\npoisson.lambda\npoisson.entropy\npoisson.kurtosis\npoisson.mean\npoisson.median\npoisson.mode\npoisson.skewness\npoisson.stdev\npoisson.variance\npoisson.cdf( 4.0 )\npoisson.logpmf( 2.0 )\npoisson.mgf( 0.5 )\npoisson.pmf( 2.0 )\npoisson.quantile( 0.5 )\n","base.dists.poisson.quantile":"var y = base.dists.poisson.quantile( 0.5, 2.0 )\ny = base.dists.poisson.quantile( 0.9, 4.0 )\ny = base.dists.poisson.quantile( 0.1, 200.0 )\ny = base.dists.poisson.quantile( 1.1, 0.0 )\ny = base.dists.poisson.quantile( -0.2, 0.0 )\ny = base.dists.poisson.quantile( NaN, 0.5 )\ny = base.dists.poisson.quantile( 0.0, NaN )\ny = base.dists.poisson.quantile( 2.0, -1.0 )\ny = base.dists.poisson.quantile( 0.1, 0.0 )\ny = base.dists.poisson.quantile( 0.9, 0.0 )\n","base.dists.poisson.quantile.factory":"var myQuantile = base.dists.poisson.quantile.factory( 0.4 );\nvar y = myQuantile( 0.4 )\ny = myQuantile( 1.0 )\n","base.dists.poisson.skewness":"var v = base.dists.poisson.skewness( 11.0 )\nv = base.dists.poisson.skewness( 4.5 )\n","base.dists.poisson.stdev":"var v = base.dists.poisson.stdev( 11.0 )\nv = base.dists.poisson.stdev( 4.5 )\n","base.dists.poisson.variance":"var v = base.dists.poisson.variance( 11.0 )\nv = base.dists.poisson.variance( 4.5 )\n","base.dists.rayleigh.cdf":"var y = base.dists.rayleigh.cdf( 2.0, 3.0 )\ny = base.dists.rayleigh.cdf( 1.0, 2.0 )\ny = base.dists.rayleigh.cdf( -1.0, 4.0 )\ny = base.dists.rayleigh.cdf( NaN, 1.0 )\ny = base.dists.rayleigh.cdf( 0.0, NaN )\ny = base.dists.rayleigh.cdf( 2.0, -1.0 )\ny = base.dists.rayleigh.cdf( -2.0, 0.0 )\ny = base.dists.rayleigh.cdf( 0.0, 0.0 )\ny = base.dists.rayleigh.cdf( 2.0, 0.0 )\n","base.dists.rayleigh.cdf.factory":"var myCDF = base.dists.rayleigh.cdf.factory( 0.5 );\nvar y = myCDF( 1.0 )\ny = myCDF( 0.5 )\n","base.dists.rayleigh.entropy":"var v = base.dists.rayleigh.entropy( 11.0 )\nv = base.dists.rayleigh.entropy( 4.5 )\n","base.dists.rayleigh.kurtosis":"var v = base.dists.rayleigh.kurtosis( 11.0 )\nv = base.dists.rayleigh.kurtosis( 4.5 )\n","base.dists.rayleigh.logcdf":"var y = base.dists.rayleigh.logcdf( 2.0, 3.0 )\ny = base.dists.rayleigh.logcdf( 1.0, 2.0 )\ny = base.dists.rayleigh.logcdf( -1.0, 4.0 )\ny = base.dists.rayleigh.logcdf( NaN, 1.0 )\ny = base.dists.rayleigh.logcdf( 0.0, NaN )\ny = base.dists.rayleigh.logcdf( 2.0, -1.0 )\n","base.dists.rayleigh.logcdf.factory":"var mylogcdf = base.dists.rayleigh.logcdf.factory( 0.5 );\nvar y = mylogcdf( 1.0 )\ny = mylogcdf( 0.5 )\n","base.dists.rayleigh.logpdf":"var y = base.dists.rayleigh.logpdf( 0.3, 1.0 )\ny = base.dists.rayleigh.logpdf( 2.0, 0.8 )\ny = base.dists.rayleigh.logpdf( -1.0, 0.5 )\ny = base.dists.rayleigh.logpdf( 0.0, NaN )\ny = base.dists.rayleigh.logpdf( NaN, 2.0 )\ny = base.dists.rayleigh.logpdf( 2.0, -1.0 )\n","base.dists.rayleigh.logpdf.factory":"var mylogpdf = base.dists.rayleigh.logpdf.factory( 4.0 );\nvar y = mylogpdf( 6.0 )\ny = mylogpdf( 4.0 )\n","base.dists.rayleigh.mean":"var v = base.dists.rayleigh.mean( 11.0 )\nv = base.dists.rayleigh.mean( 4.5 )\n","base.dists.rayleigh.median":"var v = base.dists.rayleigh.median( 11.0 )\nv = base.dists.rayleigh.median( 4.5 )\n","base.dists.rayleigh.mgf":"var y = base.dists.rayleigh.mgf( 1.0, 3.0 )\ny = base.dists.rayleigh.mgf( 1.0, 2.0 )\ny = base.dists.rayleigh.mgf( -1.0, 4.0 )\ny = base.dists.rayleigh.mgf( NaN, 1.0 )\ny = base.dists.rayleigh.mgf( 0.0, NaN )\ny = base.dists.rayleigh.mgf( 0.5, -1.0 )\n","base.dists.rayleigh.mgf.factory":"var myMGF = base.dists.rayleigh.mgf.factory( 0.5 );\nvar y = myMGF( 1.0 )\ny = myMGF( 0.5 )\n","base.dists.rayleigh.mode":"var v = base.dists.rayleigh.mode( 11.0 )\nv = base.dists.rayleigh.mode( 4.5 )\n","base.dists.rayleigh.pdf":"var y = base.dists.rayleigh.pdf( 0.3, 1.0 )\ny = base.dists.rayleigh.pdf( 2.0, 0.8 )\ny = base.dists.rayleigh.pdf( -1.0, 0.5 )\ny = base.dists.rayleigh.pdf( 0.0, NaN )\ny = base.dists.rayleigh.pdf( NaN, 2.0 )\ny = base.dists.rayleigh.pdf( 2.0, -1.0 )\ny = base.dists.rayleigh.pdf( -2.0, 0.0 )\ny = base.dists.rayleigh.pdf( 0.0, 0.0 )\ny = base.dists.rayleigh.pdf( 2.0, 0.0 )\n","base.dists.rayleigh.pdf.factory":"var myPDF = base.dists.rayleigh.pdf.factory( 4.0 );\nvar y = myPDF( 6.0 )\ny = myPDF( 4.0 )\n","base.dists.rayleigh.quantile":"var y = base.dists.rayleigh.quantile( 0.8, 1.0 )\ny = base.dists.rayleigh.quantile( 0.5, 4.0 )\ny = base.dists.rayleigh.quantile( 1.1, 1.0 )\ny = base.dists.rayleigh.quantile( -0.2, 1.0 )\ny = base.dists.rayleigh.quantile( NaN, 1.0 )\ny = base.dists.rayleigh.quantile( 0.0, NaN )\ny = base.dists.rayleigh.quantile( 0.5, -1.0 )\n","base.dists.rayleigh.quantile.factory":"var myQuantile = base.dists.rayleigh.quantile.factory( 0.4 );\nvar y = myQuantile( 0.4 )\ny = myQuantile( 1.0 )\n","base.dists.rayleigh.Rayleigh":"var rayleigh = base.dists.rayleigh.Rayleigh( 6.0 );\nrayleigh.sigma\nrayleigh.entropy\nrayleigh.kurtosis\nrayleigh.mean\nrayleigh.median\nrayleigh.mode\nrayleigh.skewness\nrayleigh.stdev\nrayleigh.variance\nrayleigh.cdf( 1.0 )\nrayleigh.logcdf( 1.0 )\nrayleigh.logpdf( 1.5 )\nrayleigh.mgf( -0.5 )\nrayleigh.pdf( 1.5 )\nrayleigh.quantile( 0.5 )\n","base.dists.rayleigh.skewness":"var v = base.dists.rayleigh.skewness( 11.0 )\nv = base.dists.rayleigh.skewness( 4.5 )\n","base.dists.rayleigh.stdev":"var v = base.dists.rayleigh.stdev( 9.0 )\nv = base.dists.rayleigh.stdev( 4.5 )\n","base.dists.rayleigh.variance":"var v = base.dists.rayleigh.variance( 9.0 )\nv = base.dists.rayleigh.variance( 4.5 )\n","base.dists.signrank.cdf":"var y = base.dists.signrank.cdf( 3, 7 )\ny = base.dists.signrank.cdf( 1.8, 3 )\ny = base.dists.signrank.cdf( -1.0, 40 )\ny = base.dists.signrank.cdf( NaN, 10 )\ny = base.dists.signrank.cdf( 0.0, NaN )\n","base.dists.signrank.cdf.factory":"var myCDF = base.dists.signrank.cdf.factory( 8 );\nvar y = myCDF( 5.7 )\ny = myCDF( 2.2 )\n","base.dists.signrank.pdf":"var y = base.dists.signrank.pdf( 3, 7 )\ny = base.dists.signrank.pdf( 1.8, 3 )\ny = base.dists.signrank.pdf( -1.0, 40 )\ny = base.dists.signrank.pdf( NaN, 10 )\ny = base.dists.signrank.pdf( 0.0, NaN )\n","base.dists.signrank.pdf.factory":"var myPDF = base.dists.signrank.pdf.factory( 8 );\nvar y = myPDF( 6.0 )\ny = myPDF( 2.0 )\n","base.dists.signrank.quantile":"var y = base.dists.signrank.quantile( 0.8, 5 )\ny = base.dists.signrank.quantile( 0.5, 4 )\ny = base.dists.signrank.quantile( 1.1, 5 )\ny = base.dists.signrank.quantile( -0.2, 5 )\ny = base.dists.signrank.quantile( NaN, 5 )\ny = base.dists.signrank.quantile( 0.0, NaN )\n","base.dists.signrank.quantile.factory":"var myQuantile = base.dists.signrank.quantile.factory( 8 );\nvar y = myQuantile( 0.4 )\ny = myQuantile( 1.0 )\n","base.dists.studentizedRange.cdf":"var y = base.dists.studentizedRange.cdf( 0.5, 3.0, 2.0 )\ny = base.dists.studentizedRange.cdf( 12.1, 17.0, 2.0 )\n","base.dists.studentizedRange.cdf.factory":"var mycdf = base.dists.studentizedRange.cdf.factory( 3.0, 2.0 );\nvar y = mycdf( 3.0 )\ny = mycdf( 1.0 )\n","base.dists.studentizedRange.quantile":"var y = quantile( 0.5, 3.0, 2.0 )\ny = quantile( 0.9, 17.0, 2.0 )\ny = quantile( 0.5, 3.0, 2.0, 2 )\ny = base.dists.studentizedRange.quantile( -0.2, 3.0, 3.0 )\ny = base.dists.studentizedRange.quantile( NaN, 2.0, 2.0 )\ny = base.dists.studentizedRange.quantile( 0.0, NaN, 2.0 )\ny = base.dists.studentizedRange.quantile( 0.5, -1.0, 2.0 )\n","base.dists.studentizedRange.quantile.factory":"var myQuantile = quantile.factory( 3.0, 3.0 );\nvar y = myQuantile( 0.5 )\n   ~1.791\ny = myQuantile( 0.8 )\n   ~3.245\n","base.dists.t.cdf":"var y = base.dists.t.cdf( 2.0, 0.1 )\ny = base.dists.t.cdf( 1.0, 2.0 )\ny = base.dists.t.cdf( -1.0, 4.0 )\ny = base.dists.t.cdf( NaN, 1.0 )\ny = base.dists.t.cdf( 0.0, NaN )\ny = base.dists.t.cdf( 2.0, -1.0 )\n","base.dists.t.cdf.factory":"var mycdf = base.dists.t.cdf.factory( 0.5 );\nvar y = mycdf( 3.0 )\ny = mycdf( 1.0 )\n","base.dists.t.entropy":"var v = base.dists.t.entropy( 11.0 )\nv = base.dists.t.entropy( 4.5 )\n","base.dists.t.kurtosis":"var v = base.dists.t.kurtosis( 11.0 )\nv = base.dists.t.kurtosis( 4.5 )\n","base.dists.t.logcdf":"var y = base.dists.t.logcdf( 2.0, 0.1 )\ny = base.dists.t.logcdf( 1.0, 2.0 )\ny = base.dists.t.logcdf( -1.0, 4.0 )\ny = base.dists.t.logcdf( NaN, 1.0 )\ny = base.dists.t.logcdf( 0.0, NaN )\ny = base.dists.t.logcdf( 2.0, -1.0 )\n","base.dists.t.logcdf.factory":"var mylogcdf = base.dists.t.logcdf.factory( 0.5 );\nvar y = mylogcdf( 3.0 )\ny = mylogcdf( 1.0 )\n","base.dists.t.logpdf":"var y = base.dists.t.logpdf( 0.3, 4.0 )\ny = base.dists.t.logpdf( 2.0, 0.7 )\ny = base.dists.t.logpdf( -1.0, 0.5 )\ny = base.dists.t.logpdf( 0.0, NaN )\ny = base.dists.t.logpdf( NaN, 2.0 )\ny = base.dists.t.logpdf( 2.0, -1.0 )\n","base.dists.t.logpdf.factory":"var mylogPDF = base.dists.t.logpdf.factory( 3.0 );\nvar y = mylogPDF( 1.0 )\n","base.dists.t.mean":"var v = base.dists.t.mean( 11.0 )\nv = base.dists.t.mean( 4.5 )\n","base.dists.t.median":"var v = base.dists.t.median( 11.0 )\nv = base.dists.t.median( 4.5 )\n","base.dists.t.mode":"var v = base.dists.t.mode( 11.0 )\nv = base.dists.t.mode( 4.5 )\n","base.dists.t.pdf":"var y = base.dists.t.pdf( 0.3, 4.0 )\ny = base.dists.t.pdf( 2.0, 0.7 )\ny = base.dists.t.pdf( -1.0, 0.5 )\ny = base.dists.t.pdf( 0.0, NaN )\ny = base.dists.t.pdf( NaN, 2.0 )\ny = base.dists.t.pdf( 2.0, -1.0 )\n","base.dists.t.pdf.factory":"var myPDF = base.dists.t.pdf.factory( 3.0 );\nvar y = myPDF( 1.0 )\n","base.dists.t.quantile":"var y = base.dists.t.quantile( 0.8, 1.0 )\ny = base.dists.t.quantile( 0.1, 1.0 )\ny = base.dists.t.quantile( 0.5, 0.1 )\ny = base.dists.t.quantile( -0.2, 0.1 )\ny = base.dists.t.quantile( NaN, 1.0 )\ny = base.dists.t.quantile( 0.0, NaN )\ny = base.dists.t.quantile( 0.5, -1.0 )\n","base.dists.t.quantile.factory":"var myQuantile = base.dists.t.quantile.factory( 4.0 );\nvar y = myQuantile( 0.2 )\ny = myQuantile( 0.9 )\n","base.dists.t.skewness":"var v = base.dists.t.skewness( 11.0 )\nv = base.dists.t.skewness( 4.5 )\n","base.dists.t.stdev":"var v = base.dists.t.stdev( 9.0 )\nv = base.dists.t.stdev( 4.5 )\n","base.dists.t.T":"var t = base.dists.t.T( 6.0 );\nt.v\nt.entropy\nt.kurtosis\nt.mean\nt.median\nt.mode\nt.skewness\nt.stdev\nt.variance\nt.cdf( 1.0 )\nt.logcdf( 1.0 )\nt.logpdf( 1.5 )\nt.pdf( 1.5 )\nt.quantile( 0.8 )\n","base.dists.t.variance":"var v = base.dists.t.variance( 9.0 )\nv = base.dists.t.variance( 4.5 )\n","base.dists.triangular.cdf":"var y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.cdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.cdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.cdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.cdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.cdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.cdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.cdf( 2.0, 1.0, 0.0, 1.5 )\n","base.dists.triangular.cdf.factory":"var mycdf = base.dists.triangular.cdf.factory( 0.0, 10.0, 2.0 );\nvar y = mycdf( 0.5 )\ny = mycdf( 8.0 )\n","base.dists.triangular.entropy":"var v = base.dists.triangular.entropy( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.entropy( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.entropy( 2.0, 8.0, 5.0 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5.0 )\n","base.dists.triangular.mgf":"var y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.mgf( -0.3, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.mgf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.mgf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.mgf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.mgf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.mgf( 0.5, 1.0, 0.0, NaN )\ny = base.dists.triangular.mgf( 0.5, 1.0, 0.0, 1.5 )\n","base.dists.triangular.mgf.factory":"var mymgf = base.dists.triangular.mgf.factory( 0.0, 2.0, 1.0 );\nvar y = mymgf( -1.0 )\ny = mymgf( 2.0 )\n","base.dists.triangular.mode":"var v = base.dists.triangular.mode( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.mode( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.mode( 2.0, 8.0, 5.0 )\n","base.dists.triangular.pdf":"var y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.5 )\ny 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base.dists.triangular.quantile( 0.3, NaN, 1.0, 0.5 )\ny = base.dists.triangular.quantile( 0.3, 0.0, NaN, 0.5 )\ny = base.dists.triangular.quantile( 0.3, 1.0, 0.0, NaN )\ny = base.dists.triangular.quantile( 0.3, 1.0, 0.0, 1.5 )\n","base.dists.triangular.quantile.factory":"var myquantile = base.dists.triangular.quantile.factory( 2.0, 4.0, 2.5 );\nvar y = myquantile( 0.4 )\ny = myquantile( 0.8 )\n","base.dists.triangular.skewness":"var v = base.dists.triangular.skewness( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.skewness( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.skewness( 2.0, 8.0, 5.0 )\n","base.dists.triangular.stdev":"var v = base.dists.triangular.stdev( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.stdev( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.stdev( 2.0, 8.0, 5.0 )\n","base.dists.triangular.Triangular":"var triangular = base.dists.triangular.Triangular( 0.0, 1.0, 0.5 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base.dists.uniform.cdf.factory( 0.0, 10.0 );\nvar y = mycdf( 0.5 )\ny = mycdf( 8.0 )\n","base.dists.uniform.entropy":"var v = base.dists.uniform.entropy( 0.0, 1.0 )\nv = base.dists.uniform.entropy( 4.0, 12.0 )\nv = base.dists.uniform.entropy( 2.0, 8.0 )\n","base.dists.uniform.kurtosis":"var v = base.dists.uniform.kurtosis( 0.0, 1.0 )\nv = base.dists.uniform.kurtosis( 4.0, 12.0 )\nv = base.dists.uniform.kurtosis( 2.0, 8.0 )\n","base.dists.uniform.logcdf":"var y = base.dists.uniform.logcdf( 9.0, 0.0, 10.0 )\ny = base.dists.uniform.logcdf( 0.5, 0.0, 2.0 )\ny = base.dists.uniform.logcdf( PINF, 2.0, 4.0 )\ny = base.dists.uniform.logcdf( NINF, 2.0, 4.0 )\ny = base.dists.uniform.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.logcdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.logcdf( 2.0, 1.0, 0.0 )\n","base.dists.uniform.logcdf.factory":"var mylogcdf = base.dists.uniform.logcdf.factory( 0.0, 10.0 );\nvar y = mylogcdf( 0.5 )\ny = mylogcdf( 8.0 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0.0, 1.0 )\ny = base.dists.uniform.mgf( 0.5, 3.0, 2.0 )\ny = base.dists.uniform.mgf( 0.5, 3.0, 3.0 )\ny = base.dists.uniform.mgf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.mgf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.mgf( 0.0, 0.0, NaN )\n","base.dists.uniform.mgf.factory":"var mymgf = base.dists.uniform.mgf.factory( 6.0, 7.0 );\nvar y = mymgf( 0.1 )\ny = mymgf( 1.1 )\n","base.dists.uniform.pdf":"var y = base.dists.uniform.pdf( 2.0, 0.0, 4.0 )\ny = base.dists.uniform.pdf( 5.0, 0.0, 4.0 )\ny = base.dists.uniform.pdf( 0.25, 0.0, 1.0 )\ny = base.dists.uniform.pdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.pdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.pdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.pdf( 2.0, 3.0, 1.0 )\n","base.dists.uniform.pdf.factory":"var myPDF = base.dists.uniform.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 7.0 )\ny = myPDF( 5.0 )\n","base.dists.uniform.quantile":"var y = base.dists.uniform.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.uniform.quantile( 0.5, 0.0, 10.0 )\ny = base.dists.uniform.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.uniform.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.uniform.quantile( NaN, 0.0, 1.0 )\ny = base.dists.uniform.quantile( 0.0, NaN, 1.0 )\ny = base.dists.uniform.quantile( 0.0, 0.0, NaN )\ny = base.dists.uniform.quantile( 0.5, 2.0, 1.0 )\n","base.dists.uniform.quantile.factory":"var myQuantile = base.dists.uniform.quantile.factory( 0.0, 4.0 );\nvar y = myQuantile( 0.8 )\n","base.dists.uniform.skewness":"var v = base.dists.uniform.skewness( 0.0, 1.0 )\nv = base.dists.uniform.skewness( 4.0, 12.0 )\nv = base.dists.uniform.skewness( 2.0, 8.0 )\n","base.dists.uniform.stdev":"var v = base.dists.uniform.stdev( 0.0, 1.0 )\nv = base.dists.uniform.stdev( 4.0, 12.0 )\nv = base.dists.uniform.stdev( 2.0, 8.0 )\n","base.dists.uniform.Uniform":"var uniform = base.dists.uniform.Uniform( 0.0, 1.0 );\nuniform.a\nuniform.b\nuniform.entropy\nuniform.kurtosis\nuniform.mean\nuniform.median\nuniform.skewness\nuniform.stdev\nuniform.variance\nuniform.cdf( 0.8 )\nuniform.logcdf( 0.5 )\nuniform.logpdf( 1.0 )\nuniform.mgf( 0.8 )\nuniform.pdf( 0.8 )\nuniform.quantile( 0.8 )\n","base.dists.uniform.variance":"var v = base.dists.uniform.variance( 0.0, 1.0 )\nv = base.dists.uniform.variance( 4.0, 12.0 )\nv = base.dists.uniform.variance( 2.0, 8.0 )\n","base.dists.weibull.cdf":"var y = base.dists.weibull.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.weibull.cdf( -1.0, 2.0, 2.0 )\ny = base.dists.weibull.cdf( PINF, 4.0, 2.0 )\ny = base.dists.weibull.cdf( NINF, 4.0, 2.0 )\ny = base.dists.weibull.cdf( NaN, 0.0, 1.0 )\ny = base.dists.weibull.cdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.cdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.cdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.cdf.factory":"var myCDF = base.dists.weibull.cdf.factory( 2.0, 10.0 );\nvar y = myCDF( 12.0 )\n","base.dists.weibull.entropy":"var v = base.dists.weibull.entropy( 1.0, 1.0 )\nv = base.dists.weibull.entropy( 4.0, 12.0 )\nv = base.dists.weibull.entropy( 8.0, 2.0 )\n","base.dists.weibull.kurtosis":"var v = base.dists.weibull.kurtosis( 1.0, 1.0 )\nv = base.dists.weibull.kurtosis( 4.0, 12.0 )\nv = base.dists.weibull.kurtosis( 8.0, 2.0 )\n","base.dists.weibull.logcdf":"var y = base.dists.weibull.logcdf( 2.0, 1.0, 1.0 )\ny = base.dists.weibull.logcdf( -1.0, 2.0, 2.0 )\ny = base.dists.weibull.logcdf( PINF, 4.0, 2.0 )\ny = base.dists.weibull.logcdf( NINF, 4.0, 2.0 )\ny = base.dists.weibull.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.weibull.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.logcdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.logcdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.logcdf.factory":"var mylogcdf = base.dists.weibull.logcdf.factory( 2.0, 10.0 );\nvar y = mylogcdf( 12.0 )\n","base.dists.weibull.logpdf":"var y = base.dists.weibull.logpdf( 2.0, 1.0, 0.5 )\ny = base.dists.weibull.logpdf( 0.1, 1.0, 1.0 )\ny = base.dists.weibull.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.weibull.logpdf( NaN, 0.6, 1.0 )\ny = base.dists.weibull.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.logpdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.logpdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.logpdf.factory":"var mylofpdf = base.dists.weibull.logpdf.factory( 7.0, 6.0 );\ny = mylofpdf( 7.0 )\n","base.dists.weibull.mean":"var v = base.dists.weibull.mean( 1.0, 1.0 )\nv = base.dists.weibull.mean( 4.0, 12.0 )\nv = base.dists.weibull.mean( 8.0, 2.0 )\n","base.dists.weibull.median":"var v = base.dists.weibull.median( 1.0, 1.0 )\nv = base.dists.weibull.median( 4.0, 12.0 )\nv = base.dists.weibull.median( 8.0, 2.0 )\n","base.dists.weibull.mgf":"var y = base.dists.weibull.mgf( 1.0, 1.0, 0.5 )\ny = base.dists.weibull.mgf( -1.0, 4.0, 4.0 )\ny = base.dists.weibull.mgf( NaN, 1.0, 1.0 )\ny = base.dists.weibull.mgf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.mgf( 0.0, 1.0, NaN )\ny = base.dists.weibull.mgf( 0.2, -1.0, 0.5 )\ny = base.dists.weibull.mgf( 0.2, 0.0, 0.5 )\ny = base.dists.weibull.mgf( 0.2, 0.5, -1.0 )\ny = base.dists.weibull.mgf( 0.2, 0.5, 0.0 )\n","base.dists.weibull.mgf.factory":"var myMGF = base.dists.weibull.mgf.factory( 8.0, 10.0 );\nvar y = myMGF( 0.8 )\ny = myMGF( 0.08 )\n","base.dists.weibull.mode":"var v = base.dists.weibull.mode( 1.0, 1.0 )\nv = base.dists.weibull.mode( 4.0, 12.0 )\nv = base.dists.weibull.mode( 8.0, 2.0 )\n","base.dists.weibull.pdf":"var y = base.dists.weibull.pdf( 2.0, 1.0, 0.5 )\ny = base.dists.weibull.pdf( 0.1, 1.0, 1.0 )\ny = base.dists.weibull.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.weibull.pdf( NaN, 0.6, 1.0 )\ny = base.dists.weibull.pdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.pdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.pdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.pdf.factory":"var myPDF = base.dists.weibull.pdf.factory( 7.0, 6.0 );\nvar y = myPDF( 7.0 )\n","base.dists.weibull.quantile":"var y = base.dists.weibull.quantile( 0.8, 1.0, 1.0 )\ny = base.dists.weibull.quantile( 0.5, 2.0, 4.0 )\ny = base.dists.weibull.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.weibull.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.weibull.quantile( NaN, 0.0, 1.0 )\ny = base.dists.weibull.quantile( 0.0, NaN, 1.0 )\ny = base.dists.weibull.quantile( 0.0, 0.0, NaN )\ny = base.dists.weibull.quantile( 0.5, 1.0, -1.0 )\n","base.dists.weibull.quantile.factory":"var myQuantile = base.dists.weibull.quantile.factory( 2.0, 10.0 );\nvar y = myQuantile( 0.4 )\n","base.dists.weibull.skewness":"var v = base.dists.weibull.skewness( 1.0, 1.0 )\nv = base.dists.weibull.skewness( 4.0, 12.0 )\nv = base.dists.weibull.skewness( 8.0, 2.0 )\n","base.dists.weibull.stdev":"var v = base.dists.weibull.stdev( 1.0, 1.0 )\nv = base.dists.weibull.stdev( 4.0, 12.0 )\nv = base.dists.weibull.stdev( 8.0, 2.0 )\n","base.dists.weibull.variance":"var v = base.dists.weibull.variance( 1.0, 1.0 )\nv = base.dists.weibull.variance( 4.0, 12.0 )\nv = base.dists.weibull.variance( 8.0, 2.0 )\n","base.dists.weibull.Weibull":"var weibull = base.dists.weibull.Weibull( 6.0, 5.0 );\nweibull.k\nweibull.lambda\nweibull.entropy\nweibull.kurtosis\nweibull.mean\nweibull.median\nweibull.mode\nweibull.skewness\nweibull.stdev\nweibull.variance\nweibull.cdf( 3.0 )\nweibull.logcdf( 3.0 )\nweibull.logpdf( 1.0 )\nweibull.mgf( -0.5 )\nweibull.pdf( 3.0 )\nweibull.quantile( 0.8 )\n","base.ellipe":"var y = base.ellipe( 0.5 )\ny = base.ellipe( -1.0 )\ny = base.ellipe( 2.0 )\ny = base.ellipe( PINF )\ny = base.ellipe( NINF )\ny = base.ellipe( NaN )\n","base.ellipj":"var v = base.ellipj( 0.3, 0.5 )\nv = base.ellipj( 0.0, 0.0 )\nv = base.ellipj( Infinity, 1.0 )\nv = base.ellipj( 0.0, -2.0)\nv = base.ellipj( NaN, NaN )\n","base.ellipj.assign":"var out = new Float64Array( 4 );\nvar v = base.ellipj.assign( 0.3, 0.5, out, 1, 0 )\nvar bool = ( v === out )\n","base.ellipj.sn":"var v = base.ellipj.sn( 0.3, 0.5 )\n","base.ellipj.cn":"var v = base.ellipj.cn( 0.3, 0.5 )\n","base.ellipj.dn":"var v = base.ellipj.dn( 0.3, 0.5 )\n","base.ellipj.am":"var v = base.ellipj.am( 0.3, 0.5 )\n","base.ellipk":"var y = base.ellipk( 0.5 )\ny = base.ellipk( -1.0 )\ny = base.ellipk( 2.0 )\ny = base.ellipk( PINF )\ny = base.ellipk( NINF )\ny = base.ellipk( NaN )\n","base.endsWith":"var bool = base.endsWith( 'beep', 'ep', 4 )\nbool = base.endsWith( 'Beep', 'op', 4 )\nbool = base.endsWith( 'Beep', 'ee', 3 )\nbool = base.endsWith( 'Beep', 'ee', -1 )\nbool = base.endsWith( 'beep', '', 4 )\n","base.epsdiff":"var d = base.epsdiff( 12.15, 12.149999999999999 )\nd = base.epsdiff( 2.4341309458983933, 2.4341309458633909, 'mean-abs' )\nfunction scale( x, y ) { return ( x > y ) ? y : x; };\nd = base.epsdiff( 1.0000000000000002, 1.0000000000000100, scale )\n","base.erf":"var y = base.erf( 2.0 )\ny = base.erf( -1.0 )\ny = base.erf( -0.0 )\ny = base.erf( NaN )\n","base.erfc":"var y = base.erfc( 2.0 )\ny = base.erfc( -1.0 )\ny = base.erfc( 0.0 )\ny = base.erfc( PINF )\ny = base.erfc( NINF )\ny = base.erfc( NaN )\n","base.erfcinv":"var y = base.erfcinv( 0.5 )\ny = base.erfcinv( 0.8 )\ny = base.erfcinv( 0.0 )\ny = base.erfcinv( 2.0 )\ny = base.erfcinv( NaN )\n","base.erfcx":"var y = base.erfcx( 1.0 )\ny = base.erfcx( -1.0 )\ny = base.erfcx( 0.0 )\ny = base.erfcx( NaN )\n","base.erfinv":"var y = base.erfinv( 0.5 )\ny = base.erfinv( 0.8 )\ny = base.erfinv( 0.0 )\ny = base.erfinv( -0.0 )\ny = base.erfinv( -1.0 )\ny = base.erfinv( 1.0 )\ny = base.erfinv( NaN )\n","base.eta":"var y = base.eta( 0.0 )\ny = base.eta( -1.0 )\ny = base.eta( 1.0 )\ny = base.eta( 3.14 )\ny = base.eta( NaN )\n","base.evalpoly":"var arr = [ 3.0, 2.0, 1.0 ];\nvar v = base.evalpoly( arr, 10.0 )\n","base.evalpoly.factory":"var f = base.evalpoly.factory( [ 3.0, 2.0, 1.0 ] );\nvar v = f( 10.0 )\nv = f( 5.0 )\n","base.evalrational":"var P = [ -6.0, -5.0, 4.0, 2.0 ];\nvar Q = [ 3.0, 0.5, 0.0, 0.0 ]; // zero-padded\nvar v = base.evalrational( P, Q, 6.0 )\n","base.evalrational.factory":"var P = [ 20.0, 8.0, 3.0 ];\nvar Q = [ 10.0, 9.0, 1.0 ];\nvar f = base.evalrational.factory( P, Q );\nvar v = f( 10.0 )\nv = f( 2.0 )\n","base.exp":"var y = base.exp( 4.0 )\ny = base.exp( -9.0 )\ny = base.exp( 0.0 )\ny = base.exp( NaN )\n","base.exp2":"var y = base.exp2( 3.0 )\ny = base.exp2( -9.0 )\ny = base.exp2( 0.0 )\ny = base.exp2( NaN )\n","base.exp10":"var y = base.exp10( 3.0 )\ny = base.exp10( -9.0 )\ny = base.exp10( 0.0 )\ny = base.exp10( NaN )\n","base.expit":"var y = base.expit( 0.0 )\ny = base.expit( 1.0 )\ny = base.expit( -1.0 )\ny = base.expit( Infinity )\ny = base.expit( NaN )\n","base.expm1":"var y = base.expm1( 0.2 )\ny = base.expm1( -9.0 )\ny = base.expm1( 0.0 )\ny = base.expm1( NaN )\n","base.expm1rel":"var y = base.expm1rel( 0.0 )\ny = base.expm1rel( 1.0 )\ny = base.expm1rel( -1.0 )\ny = base.expm1rel( NaN )\n","base.exponent":"var exponent = base.exponent( 3.14e-307 )\nexponent = base.exponent( -3.14 )\nexponent = base.exponent( 0.0 )\nexponent = base.exponent( NaN )\n","base.exponentf":"var exponent = base.exponentf( base.float64ToFloat32( 3.14e34 ) )\nexponent = base.exponentf( base.float64ToFloat32( 3.14e-34 ) )\nexponent = base.exponentf( base.float64ToFloat32( -3.14 ) )\nexponent = base.exponentf( 0.0 )\nexponent = base.exponentf( NaN )\n","base.factorial":"var y = base.factorial( 3.0 )\ny = base.factorial( -1.5 )\ny = base.factorial( -0.5 )\ny = base.factorial( 0.5 )\ny = base.factorial( -10.0 )\ny = base.factorial( 171.0 )\ny = base.factorial( NaN )\n","base.factorial2":"var y = base.factorial2( 3 )\ny = base.factorial2( 5 )\ny = base.factorial2( 6 )\ny = base.factorial2( 301 )\ny = base.factorial2( NaN )\n","base.factorialln":"var y = base.factorialln( 3.0 )\ny = base.factorialln( 2.4 )\ny = base.factorialln( -1.0 )\ny = base.factorialln( -1.5 )\ny = base.factorialln( NaN )\n","base.fallingFactorial":"var v = base.fallingFactorial( 0.9, 5 )\nv = base.fallingFactorial( -9.0, 3 )\nv = base.fallingFactorial( 0.0, 2 )\nv = base.fallingFactorial( 3.0, -2 )\n","base.fibonacci":"var y = base.fibonacci( 0 )\ny = base.fibonacci( 1 )\ny = base.fibonacci( 2 )\ny = base.fibonacci( 3 )\ny = base.fibonacci( 4 )\ny = base.fibonacci( 79 )\ny = base.fibonacci( NaN )\n","base.fibonacciIndex":"var n = base.fibonacciIndex( 2 )\nn = base.fibonacciIndex( 3 )\nn = base.fibonacciIndex( 5 )\nn = base.fibonacciIndex( NaN )\nn = base.fibonacciIndex( 1 )\n","base.fibpoly":"var v = base.fibpoly( 5, 2.0 )\n","base.fibpoly.factory":"var polyval = base.fibpoly.factory( 5 );\nvar v = polyval( 1.0 )\nv = polyval( 2.0 )\n","base.firstCodePoint":"var out = base.firstCodePoint( 'beep', 1 )\nout = base.firstCodePoint( 'Boop', 1 )\nout = base.firstCodePoint( 'foo bar', 5 )\n","base.firstCodeUnit":"var out = base.firstCodeUnit( 'beep', 1 )\nout = base.firstCodeUnit( 'Boop', 1 )\nout = base.firstCodeUnit( 'foo bar', 5 )\n","base.firstGraphemeCluster":"var out = base.firstGraphemeCluster( 'beep', 1 )\nout = base.firstGraphemeCluster( 'Boop', 1 )\nout = base.firstGraphemeCluster( 'foo bar', 5 )\n","base.flipsign":"var z = base.flipsign( -3.0, 10.0 )\nz = base.flipsign( -3.0, -1.0 )\nz = base.flipsign( 1.0, -0.0 )\nz = base.flipsign( -3.0, -0.0 )\nz = base.flipsign( -0.0, 1.0 )\nz = base.flipsign( 0.0, -1.0 )\n","base.flipsignf":"var z = base.flipsignf( -3.0, 10.0 )\nz = base.flipsignf( -3.0, -1.0 )\nz = base.flipsignf( 1.0, -0.0 )\nz = base.flipsignf( -3.0, -0.0 )\nz = base.flipsignf( -0.0, 1.0 )\nz = base.flipsignf( 0.0, -1.0 )\n","base.float32ToInt32":"var y = base.float32ToInt32( base.float64ToFloat32( 4294967295.0 ) )\ny = base.float32ToInt32( base.float64ToFloat32( 3.14 ) )\ny = base.float32ToInt32( base.float64ToFloat32( -3.14 ) )\ny = base.float32ToInt32( base.float64ToFloat32( NaN ) )\ny = base.float32ToInt32( FLOAT32_PINF )\ny = base.float32ToInt32( FLOAT32_NINF )\n","base.float32ToUint32":"var y = base.float32ToUint32( base.float64ToFloat32( 4294967297.0 ) )\ny = base.float32ToUint32( base.float64ToFloat32( 3.14 ) )\ny = base.float32ToUint32( base.float64ToFloat32( -3.14 ) )\ny = base.float32ToUint32( base.float64ToFloat32( NaN ) )\ny = base.float32ToUint32( FLOAT32_PINF )\ny = base.float32ToUint32( FLOAT32_NINF )\n","base.float64ToFloat32":"var y = base.float64ToFloat32( 1.337 )\n","base.float64ToInt32":"var y = base.float64ToInt32( 4294967295.0 )\ny = base.float64ToInt32( 3.14 )\ny = base.float64ToInt32( -3.14 )\ny = base.float64ToInt32( NaN )\ny = base.float64ToInt32( PINF )\ny = base.float64ToInt32( NINF )\n","base.float64ToInt64Bytes":"var y = base.float64ToInt64Bytes( 4294967297.0 )\n","base.float64ToInt64Bytes.assign":"var out = new Uint8Array( 16 );\nvar y = base.float64ToInt64Bytes( 4294967297.0, out, 2, 1 )\n","base.float64ToUint32":"var y = base.float64ToUint32( 4294967297.0 )\ny = base.float64ToUint32( 3.14 )\ny = base.float64ToUint32( -3.14 )\ny = base.float64ToUint32( NaN )\ny = base.float64ToUint32( PINF )\ny = base.float64ToUint32( NINF )\n","base.floor":"var y = base.floor( 3.14 )\ny = base.floor( -4.2 )\ny = base.floor( -4.6 )\ny = base.floor( 9.5 )\ny = base.floor( -0.0 )\n","base.floor2":"var y = base.floor2( 3.14 )\ny = base.floor2( -4.2 )\ny = base.floor2( -4.6 )\ny = base.floor2( 9.5 )\ny = base.floor2( 13.0 )\ny = base.floor2( -13.0 )\ny = base.floor2( -0.0 )\n","base.floor10":"var y = base.floor10( 3.14 )\ny = base.floor10( -4.2 )\ny = base.floor10( -4.6 )\ny = base.floor10( 9.5 )\ny = base.floor10( 13.0 )\ny = base.floor10( -13.0 )\ny = base.floor10( -0.0 )\n","base.floorb":"var y = base.floorb( 3.14159, -4, 10 )\ny = base.floorb( 3.14159, 0, 2 )\ny = base.floorb( 5.0, 1, 2 )\n","base.floorf":"var y = base.floorf( 3.14 )\ny = base.floorf( -4.2 )\ny = base.floorf( -4.6 )\ny = base.floorf( 9.5 )\ny = base.floorf( -0.0 )\n","base.floorn":"var y = base.floorn( 3.14159, -4 )\ny = base.floorn( 3.14159, 0 )\ny = base.floorn( 12368.0, 3 )\n","base.floorsd":"var y = base.floorsd( 3.14159, 5, 10 )\ny = base.floorsd( 3.14159, 1, 10 )\ny = base.floorsd( 12368.0, 2, 10 )\ny = base.floorsd( 0.0313, 2, 2 )\n","base.forEachChar":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachChar( 'hello world!', fcn );\nn\n","base.forEachCodePoint":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachCodePoint( 'hello world!', fcn );\nn\n","base.forEachCodePointRight":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachCodePointRight( 'hello world!', fcn );\nn\n","base.forEachGraphemeCluster":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachGraphemeCluster( 'hello world!', fcn );\nn\n","base.forEachRight":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachRight( 'hello world!', fcn );\nn\n","base.formatInterpolate":"var out = base.formatInterpolate( [ 'beep ', { 'specifier': 's' } ], 'boop' )\nout = base.formatInterpolate( [ 'baz ', { 'specifier': 'd', 'precision': 2 } ], 1 )\nout = base.formatInterpolate( [ { 'specifier': 'u', 'width': 6 } ], 12 )\n","base.formatTokenize":"var out = base.formatTokenize( 'Hello %s!' )\nout = base.formatTokenize( '%s %s %d' )\nout = base.formatTokenize( 'Pi: %.2f' )\n","base.fresnel":"var y = base.fresnel( 0.0 )\ny = base.fresnel( 1.0 )\ny = base.fresnel( PINF )\ny = base.fresnel( NINF )\ny = base.fresnel( NaN )\n","base.fresnel.assign":"var out = new Float64Array( 2 );\nvar v = base.fresnel.assign( 0.0, out, 1, 0 )\nvar bool = ( v === out )\n","base.fresnelc":"var y = base.fresnelc( 0.0 )\ny = base.fresnelc( 1.0 )\ny = base.fresnelc( PINF )\ny = base.fresnelc( NINF )\ny = base.fresnelc( NaN )\n","base.fresnels":"var y = base.fresnels( 0.0 )\ny = base.fresnels( 1.0 )\ny = base.fresnels( PINF )\ny = base.fresnels( NINF )\ny = base.fresnels( NaN )\n","base.frexp":"var out = base.frexp( 4.0 )\nout = base.frexp( 0.0 )\nout = base.frexp( -0.0 )\nout = base.frexp( NaN )\nout = base.frexp( PINF )\nout = base.frexp( NINF )\n","base.frexp.assign":"var out = new Float64Array( 2 );\nvar y = base.frexp.assign( 4.0, out, 1, 0 )\nvar bool = ( y === out )\n","base.fromBinaryString":"var bstr;\nbstr = '0100000000010000000000000000000000000000000000000000000000000000';\nvar val = base.fromBinaryString( bstr )\nbstr = '0100000000001001001000011111101101010100010001000010110100011000';\nval = base.fromBinaryString( bstr )\nbstr = '1111111111100001110011001111001110000101111010111100100010100000';\nval = base.fromBinaryString( bstr )\nbstr = '1000000000000000000000000000000000000000000000000001100011010011';\nval = base.fromBinaryString( bstr )\nbstr = '0000000000000000000000000000000000000000000000000000000000000001';\nval = base.fromBinaryString( bstr )\nbstr = '0000000000000000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '1000000000000000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '0111111111111000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '0111111111110000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '1111111111110000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\n","base.fromBinaryStringf":"var bstr = '01000000100000000000000000000000';\nvar val = base.fromBinaryStringf( bstr )\nbstr = '01000000010010010000111111011011';\nval = base.fromBinaryStringf( bstr )\nbstr = '11111111011011000011101000110011';\nval = base.fromBinaryStringf( bstr )\nbstr = '10000000000000000000000000010110';\nval = base.fromBinaryStringf( bstr )\nbstr = '00000000000000000000000000000001';\nval = base.fromBinaryStringf( bstr )\nbstr = '00000000000000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '10000000000000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '01111111110000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '01111111100000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '11111111100000000000000000000000';\nval = base.fromBinaryStringf( bstr )\n","base.fromBinaryStringUint8":"var bstr = '01010101';\nvar val = base.fromBinaryStringUint8( bstr )\nbstr = '00000000';\nval = base.fromBinaryStringUint8( bstr )\nbstr = '00000010';\nval = base.fromBinaryStringUint8( bstr )\nbstr = '11111111';\nval = base.fromBinaryStringUint8( bstr )\n","base.fromBinaryStringUint16":"var bstr = '0101010101010101';\nvar val = base.fromBinaryStringUint16( bstr )\nbstr = '0000000000000000';\nval = base.fromBinaryStringUint16( bstr )\nbstr = '0000000000000010';\nval = base.fromBinaryStringUint16( bstr )\nbstr = '1111111111111111';\nval = base.fromBinaryStringUint16( bstr )\n","base.fromBinaryStringUint32":"var bstr = '01010101010101010101010101010101';\nvar val = base.fromBinaryStringUint32( bstr )\nbstr = '00000000000000000000000000000000';\nval = base.fromBinaryStringUint32( bstr )\nbstr = '00000000000000000000000000000010';\nval = base.fromBinaryStringUint32( bstr )\nbstr = '11111111111111111111111111111111';\nval = base.fromBinaryStringUint32( bstr )\n","base.fromInt64Bytes":"var bytes = new Uint8Array( [ 255, 255, 255, 255, 255, 255, 255, 255 ] );\nvar y = base.fromInt64Bytes( bytes, 1, 0 )\n","base.fromWordf":"var word = 1068180177; // => 0 01111111 01010110010001011010001\nvar f32 = base.fromWordf( word ) // when printed, promoted to float64\n","base.fromWords":"var v = base.fromWords( 1774486211, 2479577218 )\nv = base.fromWords( 3221823995, 1413754136 )\nv = base.fromWords( 0, 0 )\nv = base.fromWords( 2147483648, 0 )\nv = base.fromWords( 2146959360, 0 )\nv = base.fromWords( 2146435072, 0 )\nv = base.fromWords( 4293918720, 0 )\n","base.gamma":"var y = base.gamma( 4.0 )\ny = base.gamma( -1.5 )\ny = base.gamma( -0.5 )\ny = base.gamma( 0.5 )\ny = base.gamma( 0.0 )\ny = base.gamma( -0.0 )\ny = base.gamma( NaN )\n","base.gamma1pm1":"var y = base.gamma1pm1( 0.2 )\ny = base.gamma1pm1( -6.7 )\ny = base.gamma1pm1( 0.0 )\ny = base.gamma1pm1( NaN )\n","base.gammaDeltaRatio":"var y = base.gammaDeltaRatio( 2.0, 3.0 )\ny = base.gammaDeltaRatio( 4.0, 0.5 )\ny = base.gammaDeltaRatio( 100.0, 0.0 )\ny = base.gammaDeltaRatio( NaN, 3.0 )\ny = base.gammaDeltaRatio( 5.0, NaN )\ny = base.gammaDeltaRatio( NaN, NaN )\n","base.gammainc":"var y = base.gammainc( 6.0, 2.0 )\ny = base.gammainc( 1.0, 2.0, true, true )\ny = base.gammainc( 7.0, 5.0 )\ny = base.gammainc( 7.0, 5.0, false )\ny = base.gammainc( NaN, 2.0 )\ny = base.gammainc( 6.0, NaN )\n","base.gammaincinv":"var y = base.gammaincinv( 0.5, 2.0 )\ny = base.gammaincinv( 0.1, 10.0 )\ny = base.gammaincinv( 0.75, 3.0 )\ny = base.gammaincinv( 0.75, 3.0, true )\ny = base.gammaincinv( 0.75, NaN )\ny = base.gammaincinv( NaN, 3.0 )\n","base.gammaLanczosSum":"var y = base.gammaLanczosSum( 4.0 )\ny = base.gammaLanczosSum( -1.5 )\ny = base.gammaLanczosSum( -0.5 )\ny = base.gammaLanczosSum( 0.5 )\ny = base.gammaLanczosSum( 0.0 )\ny = base.gammaLanczosSum( NaN )\n","base.gammaLanczosSumExpGScaled":"var y = base.gammaLanczosSumExpGScaled( 4.0 )\ny = base.gammaLanczosSumExpGScaled( -1.5 )\ny = base.gammaLanczosSumExpGScaled( -0.5 )\ny = base.gammaLanczosSumExpGScaled( 0.5 )\ny = base.gammaLanczosSumExpGScaled( 0.0 )\ny = base.gammaLanczosSumExpGScaled( NaN )\n","base.gammaln":"var y = base.gammaln( 1.0 )\ny = base.gammaln( 2.0 )\ny = base.gammaln( 4.0 )\ny = base.gammaln( -0.5 )\ny = base.gammaln( 0.5 )\ny = base.gammaln( 0.0 )\ny = base.gammaln( NaN )\n","base.gammasgn":"var y = base.gammasgn( 1.0 )\ny = base.gammasgn( -2.5 )\ny = base.gammasgn( 0.0 )\ny = base.gammasgn( NaN )\n","base.gcd":"var v = base.gcd( 48, 18 )\n","base.getHighWord":"var w = base.getHighWord( 3.14e201 )\n","base.getLowWord":"var w = base.getLowWord( 3.14e201 )\n","base.hacovercos":"var y = base.hacovercos( 3.14 )\ny = base.hacovercos( -4.2 )\ny = base.hacovercos( -4.6 )\ny = base.hacovercos( 9.5 )\ny = base.hacovercos( -0.0 )\n","base.hacoversin":"var y = base.hacoversin( 3.14 )\ny = base.hacoversin( -4.2 )\ny = base.hacoversin( -4.6 )\ny = base.hacoversin( 9.5 )\ny = base.hacoversin( -0.0 )\n","base.havercos":"var y = base.havercos( 3.14 )\ny = base.havercos( -4.2 )\ny = base.havercos( -4.6 )\ny = base.havercos( 9.5 )\ny = base.havercos( -0.0 )\n","base.haversin":"var y = base.haversin( 3.14 )\ny = base.haversin( -4.2 )\ny = base.haversin( -4.6 )\ny = base.haversin( 9.5 )\ny = base.haversin( -0.0 )\n","base.headercase":"var out = base.headercase( 'Hello World!' )\nout = base.headercase( 'beep boop' )\n","base.heaviside":"var y = base.heaviside( 3.14 )\ny = base.heaviside( -3.14 )\ny = base.heaviside( 0.0 )\ny = base.heaviside( 0.0, 'half-maximum' )\ny = base.heaviside( 0.0, 'left-continuous' )\ny = base.heaviside( 0.0, 'right-continuous' )\n","base.hermitepoly":"var y = base.hermitepoly( 1, 0.5 )\ny = base.hermitepoly( -1, 0.5 )\ny = base.hermitepoly( 0, 0.5 )\ny = base.hermitepoly( 2, 0.5 )\n","base.hermitepoly.factory":"var polyval = base.hermitepoly.factory( 2 );\nvar v = polyval( 0.5 )\n","base.hypot":"var h = base.hypot( -5.0, 12.0 )\nh = base.hypot( NaN, 12.0 )\nh = base.hypot( -0.0, -0.0 )\n","base.hypotf":"var h = base.hypotf( -5.0, 12.0 )\nh = base.hypotf( NaN, 12.0 )\nh = base.hypotf( -0.0, -0.0 )\n","base.identity":"var y = base.identity( -1.0 )\ny = base.identity( 2.0 )\ny = base.identity( 0.0 )\ny = base.identity( -0.0 )\ny = base.identity( NaN )\n","base.identityf":"var y = base.identityf( -1.0 )\ny = base.identityf( 2.0 )\ny = base.identityf( 0.0 )\ny = base.identityf( -0.0 )\ny = base.identityf( NaN )\n","base.imul":"var v = base.imul( -10|0, 4|0 )\n","base.imuldw":"var v = base.imuldw( 1, 10 )\n","base.imuldw.assign":"var out = [ 0, 0 ];\nvar v = base.imuldw.assign( 1, 10, out, 1, 0 )\nvar bool = ( v === out )\n","base.int2slice":"var s = base.int2slice( -1, 5, false );\ns.start\ns.stop\ns.step\n","base.int32ToUint32":"var y = base.int32ToUint32( base.float64ToInt32( -32 ) )\ny = base.int32ToUint32( base.float64ToInt32( 3 ) )\n","base.inv":"var y = base.inv( -1.0 )\ny = base.inv( 2.0 )\ny = base.inv( 0.0 )\ny = base.inv( -0.0 )\ny = base.inv( NaN )\n","base.invcase":"var out = base.invcase( 'Hello World!' )\nout = base.invcase( 'I am A tiny LITTLE teapot' )\n","base.invf":"var y = base.invf( -1.0 )\ny = base.invf( 2.0 )\ny = base.invf( 0.0 )\ny = base.invf( -0.0 )\ny = base.invf( NaN )\n","base.isComposite":"var bool = base.isComposite( 10.0 )\nbool = base.isComposite( 11.0 )\n","base.isCoprime":"var bool = base.isCoprime( 14.0, 15.0 )\nbool = base.isCoprime( 14.0, 21.0 )\n","base.isEven":"var bool = base.isEven( 5.0 )\nbool = base.isEven( -2.0 )\nbool = base.isEven( 0.0 )\nbool = base.isEven( NaN )\n","base.isEvenInt32":"var bool = base.isEvenInt32( 5 )\nbool = base.isEvenInt32( -2 )\nbool = base.isEvenInt32( 0 )\n","base.isFinite":"var bool = base.isFinite( 5.0 )\nbool = base.isFinite( -2.0e64 )\nbool = base.isFinite( PINF )\nbool = base.isFinite( NINF )\n","base.isFinitef":"var bool = base.isFinitef( 5.0 )\nbool = base.isFinitef( -1.0e38 )\nbool = base.isFinitef( FLOAT32_PINF )\nbool = base.isFinitef( FLOAT32_NINF )\n","base.isInfinite":"var bool = base.isInfinite( PINF )\nbool = base.isInfinite( NINF )\nbool = base.isInfinite( 5.0 )\nbool = base.isInfinite( NaN )\n","base.isInfinitef":"var bool = base.isInfinitef( FLOAT32_PINF )\nbool = base.isInfinitef( FLOAT32_NINF )\nbool = base.isInfinitef( 5.0 )\nbool = base.isInfinitef( NaN )\n","base.isInteger":"var bool = base.isInteger( 1.0 )\nbool = base.isInteger( 3.14 )\n","base.isnan":"var bool = base.isnan( NaN )\nbool = base.isnan( 7.0 )\n","base.isnanf":"var bool = base.isnanf( NaN )\nbool = base.isnanf( 7.0 )\n","base.isNegativeFinite":"var bool = base.isNegativeFinite( -3.14 )\nbool = base.isNegativeFinite( -Infinity )\nbool = base.isNegativeFinite( 2.0 )\nbool = base.isNegativeFinite( NaN )\nbool = base.isNegativeFinite( -0.0 )\n","base.isNegativeInteger":"var bool = base.isNegativeInteger( -1.0 )\nbool = base.isNegativeInteger( 0.0 )\nbool = base.isNegativeInteger( 10.0 )\n","base.isNegativeZero":"var bool = base.isNegativeZero( -0.0 )\nbool = base.isNegativeZero( 0.0 )\n","base.isNegativeZerof":"var bool = base.isNegativeZerof( -0.0 )\nbool = base.isNegativeZerof( 0.0 )\n","base.isNonNegativeFinite":"var out = base.isNonNegativeFinite( 5.0 )\nout = base.isNonNegativeFinite( 3.14 )\nout = base.isNonNegativeFinite( 0.0 )\nout = base.isNonNegativeFinite( Infinity )\nout = base.isNonNegativeFinite( -3.14 )\nout = base.isNonNegativeFinite( NaN )\n","base.isNonNegativeInteger":"var bool = base.isNonNegativeInteger( 1.0 )\nbool = base.isNonNegativeInteger( 0.0 )\nbool = base.isNonNegativeInteger( -10.0 )\n","base.isNonPositiveFinite":"var bool = base.isNonPositiveFinite( -3.14 )\nvar bool = base.isNonPositiveFinite( 0.0 )\nvar bool = base.isNonPositiveFinite( -Infinity )\nvar bool = base.isNonPositiveFinite( 3.14 )\nvar bool = base.isNonPositiveFinite( NaN )\n","base.isNonPositiveInteger":"var bool = base.isNonPositiveInteger( -1.0 )\nbool = base.isNonPositiveInteger( 0.0 )\nbool = base.isNonPositiveInteger( 10.0 )\n","base.isOdd":"var bool = base.isOdd( 5.0 )\nbool = base.isOdd( -2.0 )\nbool = base.isOdd( 0.0 )\nbool = base.isOdd( NaN )\n","base.isOddInt32":"var bool = base.isOddInt32( 5 )\nbool = base.isOddInt32( -2 )\nbool = base.isOddInt32( 0 )\n","base.isPositiveFinite":"var bool = base.isPositiveFinite( 5.0 )\nbool = base.isPositiveFinite( 3.14 )\nbool = base.isPositiveFinite( 0.0 )\nbool = base.isPositiveFinite( Infinity )\nbool = base.isPositiveFinite( -3.14 )\nbool = base.isPositiveFinite( NaN )\n","base.isPositiveInteger":"var bool = base.isPositiveInteger( 1.0 )\nbool = base.isPositiveInteger( 0.0 )\nbool = base.isPositiveInteger( -10.0 )\n","base.isPositiveZero":"var bool = base.isPositiveZero( 0.0 )\nbool = base.isPositiveZero( -0.0 )\n","base.isPositiveZerof":"var bool = base.isPositiveZerof( 0.0 )\nbool = base.isPositiveZerof( -0.0 )\n","base.isPow2Uint32":"var bool = base.isPow2Uint32( 2 )\nbool = base.isPow2Uint32( 5 )\n","base.isPrime":"var bool = base.isPrime( 11.0 )\nbool = base.isPrime( 3.14 )\n","base.isProbability":"var bool = base.isProbability( 0.5 )\nbool = base.isProbability( 3.14 )\nbool = base.isProbability( NaN )\n","base.isSafeInteger":"var bool = base.isSafeInteger( 1.0 )\nbool = base.isSafeInteger( 2.0e200 )\nbool = base.isSafeInteger( 3.14 )\n","base.kebabcase":"var out = base.kebabcase( 'Hello World!' )\nout = base.kebabcase( 'I am a tiny little teapot' )\n","base.kernelBetainc":"var out = base.kernelBetainc( 0.8, 1.0, 0.3, false, false )\nout = base.kernelBetainc( 0.2, 1.0, 2.0, true, false )\n","base.kernelBetainc.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.kernelBetainc.assign( 0.2, 1.0, 2.0, true, true, out, 1, 0 )\nvar bool = ( v === out )\n","base.kernelBetaincinv":"var y = base.kernelBetaincinv( 3.0, 3.0, 0.2, 0.8 )\ny = base.kernelBetaincinv( 3.0, 3.0, 0.4, 0.6 )\ny = base.kernelBetaincinv( 1.0, 6.0, 0.4, 0.6 )\ny = base.kernelBetaincinv( 1.0, 6.0, 0.8, 0.2 )\n","base.kernelCos":"var out = base.kernelCos( 0.0, 0.0 )\nout = base.kernelCos( PI/6.0, 0.0 )\nout = base.kernelCos( 0.785, -1.144e-17 )\nout = base.kernelCos( NaN )\n","base.kernelLog1p":"var y = base.kernelLog1p( 1.0 )\ny = base.kernelLog1p( 1.4142135623730951 )\ny = base.kernelLog1p( NaN )\n","base.kernelSin":"var y = base.kernelSin( 0.0, 0.0 )\ny = base.kernelSin( PI/6.0, 0.0 )\ny = base.kernelSin( 0.619, 9.279e-18 )\ny = base.kernelSin( NaN, 0.0 )\ny = base.kernelSin( 2.0, NaN )\ny = base.kernelSin( NaN, NaN )\n","base.kernelTan":"var out = base.kernelTan( PI/4.0, 0.0, 1 )\nout = base.kernelTan( PI/4.0, 0.0, -1 )\nout = base.kernelTan( PI/6.0, 0.0, 1 )\nout = base.kernelTan( 0.664, 5.288e-17, 1 )\nout = base.kernelTan( NaN, 0.0, 1 )\nout = base.kernelTan( 3.0, NaN, 1 )\nout = base.kernelTan( 3.0, 0.0, NaN )\n","base.kroneckerDelta":"var y = base.kroneckerDelta( 3.14, 0.0 )\ny = base.kroneckerDelta( 3.14, 3.14 )\n","base.kroneckerDeltaf":"var y = base.kroneckerDeltaf( 3.14, 0.0 )\ny = base.kroneckerDeltaf( 3.14, 3.14 )\n","base.labs":"var v = base.labs( -1|0 )\nv = base.labs( 2|0 )\nv = base.labs( 0|0 )\n","base.last":"var out = base.last( 'hello', 1 )\nout = base.last( 'JavaScript', 6 )\nout = base.last( 'foo bar', 10 )\n","base.lastCodePoint":"var out = base.lastCodePoint( 'hello world', 1 )\nout = base.lastCodePoint( 'JavaScript', 6 )\nout = base.lastCodePoint( 'अनुच्छेद', 1 )\n","base.lastGraphemeCluster":"var out = base.lastGraphemeCluster( 'beep', 1 )\nout = base.lastGraphemeCluster( 'Boop', 2 )\nout = base.lastGraphemeCluster( 'JavaScript', 6 )\n","base.lcm":"var v = base.lcm( 21, 6 )\n","base.ldexp":"var x = base.ldexp( 0.5, 3 )\nx = base.ldexp( 4.0, -2 )\nx = base.ldexp( 0.0, 20 )\nx = base.ldexp( -0.0, 39 )\nx = base.ldexp( NaN, -101 )\nx = base.ldexp( PINF, 11 )\nx = base.ldexp( NINF, -118 )\n","base.leftPad":"var out = base.leftPad( 'a', 5, ' ' )\nout = base.leftPad( 'beep', 10, 'b' )\nout = base.leftPad( 'boop', 12, 'beep' )\n","base.leftTrim":"var out = base.leftTrim( ' \\r\\n\\t  Beep \\t\\t\\n  ' )\n","base.ln":"var y = base.ln( 4.0 )\ny = base.ln( 0.0 )\ny = base.ln( PINF )\ny = base.ln( NaN )\ny = base.ln( -4.0 )\n","base.log":"var y = base.log( 100.0, 10.0 )\ny = base.log( 16.0, 2.0 )\ny = base.log( 5.0, 1.0 )\ny = base.log( NaN, 2.0 )\ny = base.log( 1.0, NaN )\ny = base.log( -4.0, 2.0 )\ny = base.log( 4.0, -2.0 )\n","base.log1mexp":"var y = base.log1mexp( -10.0 )\ny = base.log1mexp( 0.0 )\ny = base.log1mexp( 5.0 )\ny = base.log1mexp( 10.0 )\ny = base.log1mexp( NaN )\n","base.log1p":"var y = base.log1p( 4.0 )\ny = base.log1p( -1.0 )\ny = base.log1p( 0.0 )\ny = base.log1p( -0.0 )\ny = base.log1p( -2.0 )\ny = base.log1p( NaN )\n","base.log1pexp":"var y = base.log1pexp( -10.0 )\ny = base.log1pexp( 0.0 )\ny = base.log1pexp( 5.0 )\ny = base.log1pexp( 34.0 )\ny = base.log1pexp( NaN )\n","base.log1pmx":"base.log1pmx( 1.1 )\nbase.log1pmx( 0.99 )\nbase.log1pmx( -0.99 )\nbase.log1pmx( -1.1 )\nbase.log1pmx( NaN )\n","base.log2":"var y = base.log2( 4.0 )\ny = base.log2( 8.0 )\ny = base.log2( 0.0 )\ny = base.log2( PINF )\ny = base.log2( NaN )\ny = base.log2( -4.0 )\n","base.log10":"var y = base.log10( 100.0 )\ny = base.log10( 8.0 )\ny = base.log10( 0.0 )\ny = base.log10( PINF )\ny = base.log10( NaN )\ny = base.log10( -4.0 )\n","base.logaddexp":"var v = base.logaddexp( 90.0, 90.0 )\nv = base.logaddexp( -20.0, 90.0 )\nv = base.logaddexp( 0.0, -100.0 )\nv = base.logaddexp( NaN, NaN )\n","base.logit":"var y = base.logit( 0.2 )\ny = base.logit( 0.9 )\ny = base.logit( -4.0 )\ny = base.logit( 1.5 )\ny = base.logit( NaN )\n","base.lowercase":"var out = base.lowercase( 'bEEp' )\n","base.lucas":"var y = base.lucas( 0 )\ny = base.lucas( 1 )\ny = base.lucas( 2 )\ny = base.lucas( 3 )\ny = base.lucas( 4 )\ny = base.lucas( 77 )\ny = base.lucas( NaN )\n","base.lucaspoly":"var v = base.lucaspoly( 5, 2.0 )\n","base.lucaspoly.factory":"var polyval = base.lucaspoly.factory( 5 );\nvar v = polyval( 1.0 )\nv = polyval( 2.0 )\n","base.max":"var v = base.max( 3.14, 4.2 )\nv = base.max( 3.14, NaN )\nv = base.max( +0.0, -0.0 )\n","base.maxabs":"var v = base.maxabs( 3.14, -4.2 )\nv = base.maxabs( 3.14, NaN )\nv = base.maxabs( +0.0, -0.0 )\n","base.maxabsn":"var v = base.maxabsn( 3.14, -4.2 )\nv = base.maxabsn( 5.9, 3.14, 4.2 )\nv = base.maxabsn( 3.14, NaN )\nv = base.maxabsn( +0.0, -0.0 )\n","base.maxn":"var v = base.maxn( 3.14, 4.2 )\nv = base.maxn( 5.9, 3.14, 4.2 )\nv = base.maxn( 3.14, NaN )\nv = base.maxn( +0.0, -0.0 )\n","base.min":"var v = base.min( 3.14, 4.2 )\nv = base.min( 3.14, NaN )\nv = base.min( +0.0, -0.0 )\n","base.minabs":"var v = base.minabs( 3.14, -4.2 )\nv = base.minabs( 3.14, NaN )\nv = base.minabs( +0.0, -0.0 )\n","base.minabsn":"var v = base.minabsn( 3.14, -4.2 )\nv = base.minabsn( 5.9, 3.14, 4.2 )\nv = base.minabsn( 3.14, NaN )\nv = base.minabsn( +0.0, -0.0 )\n","base.minmax":"var v = base.minmax( 3.14, 4.2 )\nv = base.minmax( 3.14, NaN )\nv = base.minmax( +0.0, -0.0 )\n","base.minmax.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.minmax.assign( 3.14, -1.5, out, 1, 0 )\nvar bool = ( v === out )\n","base.minmaxabs":"var v = base.minmaxabs( 3.14, 4.2 )\nv = base.minmaxabs( -5.9, 3.14)\nv = base.minmaxabs( 3.14, NaN )\nv = base.minmaxabs( +0.0, -0.0 )\n","base.minmaxabs.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.minmaxabs.assign( 3.14, -3.14, out, 1, 0 )\nvar bool = ( v === out )\n","base.minmaxabsn":"var v = base.minmaxabsn( 3.14, 4.2 )\nv = base.minmaxabsn( -5.9, 3.14, 4.2 )\nv = base.minmaxabsn( 3.14, NaN )\nv = base.minmaxabsn( +0.0, -0.0 )\nv = base.minmaxabsn( 3.14 )\n","base.minmaxabsn.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.minmaxabsn.assign( 3.14, out, 1, 0 )\nvar bool = ( v === out )\n","base.minmaxn":"var v = base.minmaxn( 3.14, 4.2 )\nv = base.minmaxn( 5.9, 3.14, 4.2 )\nv = base.minmaxn( 3.14, NaN )\nv = base.minmaxn( +0.0, -0.0 )\nv = base.minmaxn( 3.14 )\n","base.minmaxn.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.minmaxn.assign( 3.14, -1.5, out, 1, 0 )\nvar bool = ( v === out )\n","base.minn":"var v = base.minn( 3.14, 4.2 )\nv = base.minn( 5.9, 3.14, 4.2 )\nv = base.minn( 3.14, NaN )\nv = base.minn( +0.0, -0.0 )\n","base.modf":"var parts = base.modf( 3.14 )\nparts = base.modf( 3.14 )\nparts = base.modf( +0.0 )\nparts = base.modf( -0.0 )\nparts = base.modf( PINF )\nparts = base.modf( NINF )\nparts = base.modf( NaN )\n","base.modf.assign":"var out = new Float64Array( 2 );\nvar parts = base.modf.assign( 3.14, out, 1, 0 )\nvar bool = ( parts === out )\n","base.mul":"var v = base.mul( -1.0, 5.0 )\nv = base.mul( 2.0, 5.0 )\nv = base.mul( 0.0, 5.0 )\nv = base.mul( -0.0, 0.0 )\nv = base.mul( NaN, NaN )\n","base.mulf":"var v = base.mulf( -1.0, 5.0 )\nv = base.mulf( 2.0, 5.0 )\nv = base.mulf( 0.0, 5.0 )\nv = base.mulf( -0.0, 0.0 )\nv = base.mulf( NaN, NaN )\n","base.ndarray":"var b = [ 1, 2, 3, 4 ]; // underlying data buffer\nvar d = [ 2, 2 ]; // shape\nvar s = [ 2, 1 ]; // strides\nvar o = 0; // index offset\nvar arr = base.ndarray( 'generic', b, d, s, o, 'row-major' )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40 );\narr.get( 1, 1 )\narr.iset( 3, 99 );\narr.get( 1, 1 )\n","base.ndarray.prototype.byteLength":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.byteLength\n","base.ndarray.prototype.BYTES_PER_ELEMENT":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.BYTES_PER_ELEMENT\n","base.ndarray.prototype.data":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar buf = arr.data\n","base.ndarray.prototype.dtype":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar dt = arr.dtype\n","base.ndarray.prototype.flags":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar fl = arr.flags\n","base.ndarray.prototype.length":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar len = arr.length\n","base.ndarray.prototype.ndims":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar n = arr.ndims\n","base.ndarray.prototype.offset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.offset\n","base.ndarray.prototype.order: string":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar ord = arr.order\n","base.ndarray.prototype.shape":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sh = arr.shape\n","base.ndarray.prototype.strides":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar st = arr.strides\n","base.ndarray.prototype.get":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.get( 1, 1 )\n","base.ndarray.prototype.iget":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.iget( 3 )\n","base.ndarray.prototype.set":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\narr.set( 1, 1, -4.0 );\narr.get( 1, 1 )\n","base.ndarray.prototype.iset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\narr.iset( 3, -4.0 );\narr.iget( 3 )\n","base.ndarray.prototype.toString":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toString()\n","base.ndarray.prototype.toJSON":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toJSON()\n","base.ndarrayUnary":"var xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dtype = 'float64';\nvar shape = [ 2, 2 ];\nvar sx = [ 2, 1 ];\nvar sy = [ 2, 1 ];\nvar ox = 0;\nvar oy = 0;\nvar order = 'row-major';\nvar x = ndarray( dtype, xbuf, shape, sx, ox, order );\nvar y = ndarray( dtype, ybuf, shape, sy, oy, order );\nbase.ndarrayUnary( [ x, y ], base.abs );\ny.data\nx = {\n 'dtype': dtype,\n 'data': xbuf,\n 'shape': shape,\n 'strides': sx,\n 'offset': ox,\n 'order': order\n };\ny = {\n 'dtype': dtype,\n 'data': ybuf,\n 'shape': shape,\n 'strides': sy,\n 'offset': oy,\n 'order': order\n };\nbase.ndarrayUnary( [ x, y ], base.abs );\ny.data\n","base.ndzeros":"var arr = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\nvar sh = arr.shape\nvar dt = arr.dtype\n","base.ndzerosLike":"var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\nvar sh = x.shape\nvar dt = x.dtype\nvar y = base.ndzerosLike( x )\nsh = y.shape\ndt = y.dtype\n","base.negafibonacci":"var y = base.negafibonacci( 0 )\ny = base.negafibonacci( -1 )\ny = base.negafibonacci( -2 )\ny = base.negafibonacci( -3 )\ny = base.negafibonacci( -4 )\ny = base.negafibonacci( -79 )\ny = base.negafibonacci( -80 )\ny = base.negafibonacci( NaN )\n","base.negalucas":"var y = base.negalucas( 0 )\ny = base.negalucas( -1 )\ny = base.negalucas( -2 )\ny = base.negalucas( -3 )\ny = base.negalucas( -4 )\ny = base.negalucas( -77 )\ny = base.negalucas( -78 )\ny = base.negalucas( NaN )\n","base.nonfibonacci":"var v = base.nonfibonacci( 1 )\nv = base.nonfibonacci( 2 )\nv = base.nonfibonacci( 3 )\nv = base.nonfibonacci( NaN )\n","base.normalize":"var out = base.normalize( 3.14e-319 )\nvar y = out[ 0 ];\nvar exponent = out[ 1 ];\nvar bool = ( y*base.pow(2.0, exponent) === 3.14e-319 )\nout = base.normalize( 0.0 )\nout = base.normalize( PINF )\nout = base.normalize( NINF )\nout = base.normalize( NaN )\n","base.normalize.assign":"var out = new Float64Array( 2 )\nvar v = base.normalize.assign( 3.14e-319, out, 1, 0 )\nvar bool = ( v === out )\n","base.normalizef":"var out = base.normalizef( base.float64ToFloat32( 1.401e-45 ) )\nvar y = out[ 0 ];\nvar exp = out[ 1 ];\nvar bool = ( y*base.pow(2,exp) === base.float64ToFloat32(1.401e-45) )\nout = base.normalizef( FLOAT32_PINF )\nout = base.normalizef( FLOAT32_NINF )\nout = base.normalizef( NaN )\n","base.normalizef.assign":"out = new Float32Array( 2 );\nvar v = base.normalizef.assign( base.float64ToFloat32( 1.401e-45 ), out, 1, 0 )\nbool = ( v === out )\n","base.normalizeSlice":"var s1 = new Slice( 1, 10, 1 );\nvar s2 = base.normalizeSlice( s1, 5, false );\ns2.start\ns2.stop\ns2.step\ns1 = new Slice( -2, null, -1 );\ns2 = base.normalizeSlice( s1, 10, false );\ns2.start\ns2.stop\ns2.step\n","base.normhermitepoly":"var y = base.normhermitepoly( 1, 0.5 )\ny = base.normhermitepoly( -1, 0.5 )\ny = base.normhermitepoly( 0, 0.5 )\ny = base.normhermitepoly( 2, 0.5 )\n","base.normhermitepoly.factory":"var f = base.normhermitepoly.factory( 2 );\nvar v = f( 0.5 )\n","base.pascalcase":"var out = base.pascalcase( 'Hello World!' )\nout = base.pascalcase( 'beep boop' )\n","base.pdiff":"var v = base.pdiff( 5.9, 3.14 )\nv = base.pdiff( 3.14, 4.2 )\nv = base.pdiff( 3.14, NaN )\nv = base.pdiff( -0.0, +0.0 )\n","base.pdifff":"var v = base.pdifff( 5.9, 3.15 )\nv = base.pdifff( 3.14, 4.2 )\nv = base.pdifff( 3.14, NaN )\nv = base.pdifff( -0.0, +0.0 )\n","base.percentEncode":"var out = base.percentEncode( '☃' )\n","base.polygamma":"var v = base.polygamma( 3, 1.2 )\nv = base.polygamma( 5, 1.2 )\nv = base.polygamma( 3, -4.9 )\nv = base.polygamma( -1, 5.3 )\nv = base.polygamma( 2, -1.0 )\n","base.pow":"var y = base.pow( 2.0, 3.0 )\ny = base.pow( 4.0, 0.5 )\ny = base.pow( 100.0, 0.0 )\ny = base.pow( PI, 5.0 )\ny = base.pow( PI, -0.2 )\ny = base.pow( NaN, 3.0 )\ny = base.pow( 5.0, NaN )\ny = base.pow( NaN, NaN )\n","base.powm1":"var y = base.powm1( 2.0, 3.0 )\ny = base.powm1( 4.0, 0.5 )\ny = base.powm1( 0.0, 100.0 )\ny = base.powm1( 100.0, 0.0 )\ny = base.powm1( 0.0, 0.0 )\ny = base.powm1( PI, 5.0 )\ny = base.powm1( NaN, 3.0 )\ny = base.powm1( 5.0, NaN )\n","base.rad2deg":"var d = base.rad2deg( PI/2.0 )\nd = base.rad2deg( -PI/4.0 )\nd = base.rad2deg( NaN )\nd = base.rad2deg( PI/6.0 )\n","base.rad2degf":"var d = base.rad2degf( 3.141592653589793 / 2.0 )\nd = base.rad2degf( -3.141592653589793 / 4.0 )\nd = base.rad2degf( NaN )\nd = base.rad2degf( 3.141592653589793 / 6.0 )\n","base.ramp":"var y = base.ramp( 3.14 )\ny = base.ramp( -3.14 )\n","base.rampf":"var y = base.rampf( 3.14 )\ny = base.rampf( -3.14 )\n","base.random.arcsine":"var r = base.random.arcsine( 2.0, 5.0 )\n","base.random.arcsine.factory":"var rand = base.random.arcsine.factory();\nvar r = rand( 0.0, 1.0 )\nr = rand( -2.0, 2.0 )\nrand = base.random.arcsine.factory( 0.0, 1.0 );\nr = rand()\nr = rand()\n","base.random.arcsine.NAME":"var str = base.random.arcsine.NAME\n","base.random.arcsine.PRNG":"var prng = base.random.arcsine.PRNG;\n","base.random.arcsine.seed":"var seed = base.random.arcsine.seed;\n","base.random.arcsine.seedLength":"var len = base.random.arcsine.seedLength;\n","base.random.arcsine.state":"var r = base.random.arcsine( 2.0, 4.0 )\nr = base.random.arcsine( 2.0, 4.0 )\nr = base.random.arcsine( 2.0, 4.0 )\nvar state = base.random.arcsine.state\nr = base.random.arcsine( 2.0, 4.0 )\nr = base.random.arcsine( 2.0, 4.0 )\nbase.random.arcsine.state = state;\nr = base.random.arcsine( 2.0, 4.0 )\nr = base.random.arcsine( 2.0, 4.0 )\n","base.random.arcsine.stateLength":"var len = base.random.arcsine.stateLength;\n","base.random.arcsine.byteLength":"var sz = base.random.arcsine.byteLength;\n","base.random.arcsine.toJSON":"var o = base.random.arcsine.toJSON()\n","base.random.bernoulli":"var r = base.random.bernoulli( 0.8 );\n","base.random.bernoulli.factory":"var rand = base.random.bernoulli.factory();\nvar r = rand( 0.3 );\nr = rand( 0.59 );\nrand = base.random.bernoulli.factory( 0.3 );\nr = rand();\nr = rand();\n","base.random.bernoulli.NAME":"var str = base.random.bernoulli.NAME\n","base.random.bernoulli.PRNG":"var prng = base.random.bernoulli.PRNG;\n","base.random.bernoulli.seed":"var seed = base.random.bernoulli.seed;\n","base.random.bernoulli.seedLength":"var len = base.random.bernoulli.seedLength;\n","base.random.bernoulli.state":"var r = base.random.bernoulli( 0.3 )\nr = base.random.bernoulli( 0.3 )\nr = base.random.bernoulli( 0.3 )\nvar state = base.random.bernoulli.state\nr = base.random.bernoulli( 0.3 )\nr = base.random.bernoulli( 0.3 )\nbase.random.bernoulli.state = state;\nr = base.random.bernoulli( 0.3 )\nr = base.random.bernoulli( 0.3 )\n","base.random.bernoulli.stateLength":"var len = base.random.bernoulli.stateLength;\n","base.random.bernoulli.byteLength":"var sz = base.random.bernoulli.byteLength;\n","base.random.bernoulli.toJSON":"var o = base.random.bernoulli.toJSON()\n","base.random.beta":"var r = base.random.beta( 2.0, 5.0 );\n","base.random.beta.factory":"var rand = base.random.beta.factory();\nvar r = rand( 1.5, 1.5 );\nr = rand( 2.0, 3.14 );\nrand = base.random.beta.factory( 1.5, 1.5 );\nr = rand();\nr = rand();\n","base.random.beta.NAME":"var str = base.random.beta.NAME\n","base.random.beta.PRNG":"var prng = base.random.beta.PRNG;\n","base.random.beta.seed":"var seed = base.random.beta.seed;\n","base.random.beta.seedLength":"var len = base.random.beta.seedLength;\n","base.random.beta.state":"var r = base.random.beta( 2.0, 5.0 )\nr = base.random.beta( 2.0, 5.0 )\nr = base.random.beta( 2.0, 5.0 )\nvar state = base.random.beta.state\nr = base.random.beta( 2.0, 5.0 )\nr = base.random.beta( 2.0, 5.0 )\nbase.random.beta.state = state;\nr = base.random.beta( 2.0, 5.0 )\nr = base.random.beta( 2.0, 5.0 )\n","base.random.beta.stateLength":"var len = base.random.beta.stateLength;\n","base.random.beta.byteLength":"var sz = base.random.beta.byteLength;\n","base.random.beta.toJSON":"var o = base.random.beta.toJSON()\n","base.random.betaprime":"var r = base.random.betaprime( 2.0, 5.0 );\n","base.random.betaprime.factory":"var rand = base.random.betaprime.factory();\nvar r = rand( 1.5, 1.5 );\nr = rand( 2.0, 3.14 );\nrand = base.random.betaprime.factory( 1.5, 1.5 );\nr = rand();\nr = rand();\n","base.random.betaprime.NAME":"var str = base.random.betaprime.NAME\n","base.random.betaprime.PRNG":"var prng = base.random.betaprime.PRNG;\n","base.random.betaprime.seed":"var seed = base.random.betaprime.seed;\n","base.random.betaprime.seedLength":"var len = base.random.betaprime.seedLength;\n","base.random.betaprime.state":"var r = base.random.betaprime( 2.0, 5.0 )\nr = base.random.betaprime( 2.0, 5.0 )\nr = base.random.betaprime( 2.0, 5.0 )\nvar state = base.random.betaprime.state\nr = base.random.betaprime( 2.0, 5.0 )\nr = base.random.betaprime( 2.0, 5.0 )\nbase.random.betaprime.state = state;\nr = base.random.betaprime( 2.0, 5.0 )\nr = base.random.betaprime( 2.0, 5.0 )\n","base.random.betaprime.stateLength":"var len = base.random.betaprime.stateLength;\n","base.random.betaprime.byteLength":"var sz = base.random.betaprime.byteLength;\n","base.random.betaprime.toJSON":"var o = base.random.betaprime.toJSON()\n","base.random.binomial":"var r = base.random.binomial( 20, 0.8 );\n","base.random.binomial.factory":"var rand = base.random.binomial.factory();\nvar r = rand( 20, 0.3 );\nr = rand( 10, 0.77 );\nrand = base.random.binomial.factory( 10, 0.8 );\nr = rand();\nr = rand();\n","base.random.binomial.NAME":"var str = base.random.binomial.NAME\n","base.random.binomial.PRNG":"var prng = base.random.binomial.PRNG;\n","base.random.binomial.seed":"var seed = base.random.binomial.seed;\n","base.random.binomial.seedLength":"var len = base.random.binomial.seedLength;\n","base.random.binomial.state":"var r = base.random.binomial( 20, 0.8 )\nr = base.random.binomial( 20, 0.8 )\nr = base.random.binomial( 20, 0.8 )\nvar state = base.random.binomial.state\nr = base.random.binomial( 20, 0.8 )\nr = base.random.binomial( 20, 0.8 )\nbase.random.binomial.state = state;\nr = base.random.binomial( 20, 0.8 )\nr = base.random.binomial( 20, 0.8 )\n","base.random.binomial.stateLength":"var len = base.random.binomial.stateLength;\n","base.random.binomial.byteLength":"var sz = base.random.binomial.byteLength;\n","base.random.binomial.toJSON":"var o = base.random.binomial.toJSON()\n","base.random.boxMuller":"var r = base.random.boxMuller();\n","base.random.boxMuller.factory":"var rand = base.random.boxMuller.factory();\nr = rand();\nr = rand();\n","base.random.boxMuller.NAME":"var str = base.random.boxMuller.NAME\n","base.random.boxMuller.PRNG":"var prng = base.random.boxMuller.PRNG;\n","base.random.boxMuller.seed":"var seed = base.random.boxMuller.seed;\n","base.random.boxMuller.seedLength":"var len = base.random.boxMuller.seedLength;\n","base.random.boxMuller.state":"var r = base.random.boxMuller()\nr = base.random.boxMuller()\nr = base.random.boxMuller()\nvar state = base.random.boxMuller.state\nr = base.random.boxMuller()\nr = base.random.boxMuller()\nbase.random.boxMuller.state = state;\nr = base.random.boxMuller()\nr = base.random.boxMuller()\n","base.random.boxMuller.stateLength":"var len = base.random.boxMuller.stateLength;\n","base.random.boxMuller.byteLength":"var sz = base.random.boxMuller.byteLength;\n","base.random.boxMuller.toJSON":"var o = base.random.boxMuller.toJSON()\n","base.random.cauchy":"var r = base.random.cauchy( 2.0, 5.0 );\n","base.random.cauchy.factory":"var rand = base.random.cauchy.factory();\nvar r = rand( 0.0, 1.5 );\nr = rand( -2.0, 2.0 );\nrand = base.random.cauchy.factory( 0.0, 1.5 );\nr = rand();\nr = rand();\n","base.random.cauchy.NAME":"var str = base.random.cauchy.NAME\n","base.random.cauchy.PRNG":"var prng = base.random.cauchy.PRNG;\n","base.random.cauchy.seed":"var seed = base.random.cauchy.seed;\n","base.random.cauchy.seedLength":"var len = base.random.cauchy.seedLength;\n","base.random.cauchy.state":"var r = base.random.cauchy( 2.0, 5.0 )\nr = base.random.cauchy( 2.0, 5.0 )\nr = base.random.cauchy( 2.0, 5.0 )\nvar state = base.random.cauchy.state\nr = base.random.cauchy( 2.0, 5.0 )\nr = base.random.cauchy( 2.0, 5.0 )\nbase.random.cauchy.state = state;\nr = base.random.cauchy( 2.0, 5.0 )\nr = base.random.cauchy( 2.0, 5.0 )\n","base.random.cauchy.stateLength":"var len = base.random.cauchy.stateLength;\n","base.random.cauchy.byteLength":"var sz = base.random.cauchy.byteLength;\n","base.random.cauchy.toJSON":"var o = base.random.cauchy.toJSON()\n","base.random.chi":"var r = base.random.chi( 2 );\n","base.random.chi.factory":"var rand = base.random.chi.factory();\nvar r = rand( 5 );\nr = rand( 3.14 );\nrand = base.random.chi.factory( 3 );\nr = rand();\nr = rand();\n","base.random.chi.NAME":"var str = base.random.chi.NAME\n","base.random.chi.PRNG":"var prng = base.random.chi.PRNG;\n","base.random.chi.seed":"var seed = base.random.chi.seed;\n","base.random.chi.seedLength":"var len = base.random.chi.seedLength;\n","base.random.chi.state":"var r = base.random.chi( 2 )\nr = base.random.chi( 2 )\nr = base.random.chi( 2 )\nvar state = base.random.chi.state\nr = base.random.chi( 2 )\nr = base.random.chi( 2 )\nbase.random.chi.state = state;\nr = base.random.chi( 2 )\nr = base.random.chi( 2 )\n","base.random.chi.stateLength":"var len = base.random.chi.stateLength;\n","base.random.chi.byteLength":"var sz = base.random.chi.byteLength;\n","base.random.chi.toJSON":"var o = base.random.chi.toJSON()\n","base.random.chisquare":"var r = base.random.chisquare( 2 );\n","base.random.chisquare.factory":"var rand = base.random.chisquare.factory();\nvar r = rand( 5 );\nr = rand( 3.14 );\nrand = base.random.chisquare.factory( 3 );\nr = rand();\nr = rand();\n","base.random.chisquare.NAME":"var str = base.random.chisquare.NAME\n","base.random.chisquare.PRNG":"var prng = base.random.chisquare.PRNG;\n","base.random.chisquare.seed":"var seed = 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rand = base.random.randn.factory({ 'name': 'box-muller' });\nr = rand();\nr = rand();\n","base.random.randn.NAME":"var str = base.random.randn.NAME\n","base.random.randn.PRNG":"var prng = base.random.randn.PRNG;\n","base.random.randn.seed":"var seed = base.random.randn.seed;\n","base.random.randn.seedLength":"var len = base.random.randn.seedLength;\n","base.random.randn.state":"var r = base.random.randn()\nr = base.random.randn()\nr = base.random.randn()\nvar state = base.random.randn.state;\nr = base.random.randn()\nr = base.random.randn()\nbase.random.randn.state = state;\nr = base.random.randn()\nr = base.random.randn()\n","base.random.randn.stateLength":"var len = base.random.randn.stateLength;\n","base.random.randn.byteLength":"var sz = base.random.randn.byteLength;\n","base.random.randn.toJSON":"var o = base.random.randn.toJSON()\n","base.random.randu":"var r = base.random.randu();\n","base.random.randu.factory":"var rand = base.random.randu.factory();\nvar r = rand();\nr = 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base.random.triangular( 0.0, 1.0, 0.5 )\nr = base.random.triangular( 0.0, 1.0, 0.5 )\nbase.random.triangular.state = state;\nr = base.random.triangular( 0.0, 1.0, 0.5 )\nr = base.random.triangular( 0.0, 1.0, 0.5 )\n","base.random.triangular.stateLength":"var len = base.random.triangular.stateLength;\n","base.random.triangular.byteLength":"var sz = base.random.triangular.byteLength;\n","base.random.triangular.toJSON":"var o = base.random.triangular.toJSON()\n","base.random.uniform":"var r = base.random.uniform( 2.0, 5.0 );\n","base.random.uniform.factory":"var rand = base.random.uniform.factory();\nvar r = rand( 0.0, 1.0 );\nr = rand( -2.0, 2.0 );\nrand = base.random.uniform.factory( 0.0, 1.0 );\nr = rand();\nr = rand();\n","base.random.uniform.NAME":"var str = base.random.uniform.NAME\n","base.random.uniform.PRNG":"var prng = base.random.uniform.PRNG;\n","base.random.uniform.seed":"var seed = base.random.uniform.seed;\n","base.random.uniform.seedLength":"var len = base.random.uniform.seedLength;\n","base.random.uniform.state":"var r = base.random.uniform( 2.0, 5.0 )\nr = base.random.uniform( 2.0, 5.0 )\nr = base.random.uniform( 2.0, 5.0 )\nvar state = base.random.uniform.state\nr = base.random.uniform( 2.0, 5.0 )\nr = base.random.uniform( 2.0, 5.0 )\nbase.random.uniform.state = state;\nr = base.random.uniform( 2.0, 5.0 )\nr = base.random.uniform( 2.0, 5.0 )\n","base.random.uniform.stateLength":"var len = base.random.uniform.stateLength;\n","base.random.uniform.byteLength":"var sz = base.random.uniform.byteLength;\n","base.random.uniform.toJSON":"var o = base.random.uniform.toJSON()\n","base.random.weibull":"var r = base.random.weibull( 2.0, 5.0 );\n","base.random.weibull.factory":"var rand = base.random.weibull.factory();\nvar r = rand( 0.1, 1.5 );\nr = rand( 2.0, 3.14 );\nrand = base.random.weibull.factory( 0.1, 1.5 );\nr = rand();\nr = rand();\n","base.random.weibull.NAME":"var str = base.random.weibull.NAME\n","base.random.weibull.PRNG":"var 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base.rcbrtf( 1000.0 )\ny = base.rcbrtf( 0.0 )\ny = base.rcbrtf( PINF )\ny = base.rcbrtf( -8.0 )\ny = base.rcbrtf( NaN )\n","base.reldiff":"var d = base.reldiff( 2.0, 5.0 )\nd = base.reldiff( -1.0, 3.14 )\nd = base.reldiff( -2.0, 5.0, 'max-abs' )\nd = base.reldiff( -2.0, 5.0, 'max' )\nd = base.reldiff( -2.0, 5.0, 'min-abs' )\nd = base.reldiff( -2.0, 5.0, 'min' )\nd = base.reldiff( -2.0, 5.0, 'mean-abs' )\nd = base.reldiff( -2.0, 5.0, 'mean' )\nd = base.reldiff( -2.0, 5.0, 'x' )\nd = base.reldiff( 5.0, -2.0, 'x' )\nd = base.reldiff( -2.0, 5.0, 'y' )\nd = base.reldiff( 5.0, -2.0, 'y' )\nfunction scale( x, y ) {\n var s;\n\n x = base.abs( x );\n y = base.abs( y );\n\n // Maximum absolute value:\n s = (x < y ) ? y : x;\n\n // Scale in units of epsilon:\n return s * EPS;\n };\nd = base.reldiff( 12.15, 12.149999999999999, scale )\n","base.removeFirst":"var out = base.removeFirst( 'beep', 1 )\nout = base.removeFirst( 'Boop', 1 )\nout = base.removeFirst( 'foo bar', 5 )\n","base.removeFirstCodePoint":"var out = base.removeFirstCodePoint( 'beep', 1 )\nout = base.removeFirstCodePoint( 'Boop', 1 )\nout = base.removeFirstCodePoint( 'foo bar', 5 )\n","base.removeFirstGraphemeCluster":"var out = base.removeFirstGraphemeCluster( 'beep', 1 )\nout = base.removeFirstGraphemeCluster( 'Boop', 1 )\nout = base.removeFirstGraphemeCluster( 'foo bar', 5 )\n","base.removeLast":"var out = base.removeLast( 'beep', 1 )\nout = base.removeLast( 'Boop', 1 )\nout = base.removeLast( 'foo bar', 5 )\n","base.removeLastCodePoint":"var out = base.removeLastCodePoint( 'beep', 1 )\nout = base.removeLastCodePoint( 'Boop', 1 )\nout = base.removeLastCodePoint( 'foo bar', 5 )\n","base.removeLastGraphemeCluster":"var out = base.removeLastGraphemeCluster( 'beep', 1 )\nout = base.removeLastGraphemeCluster( 'Boop', 1 )\nout = base.removeLastGraphemeCluster( 'foo bar', 5 )\n","base.rempio2":"var y = [ 0.0, 0.0 ];\nvar n = base.rempio2( 128.0, y )\nvar y1 = y[ 0 ]\nvar y2 = y[ 1 ]\n","base.repeat":"var out = base.repeat( 'a', 5 )\nout = base.repeat( '', 100 )\nout = base.repeat( 'beep', 0 )\n","base.replace":"function replacer( match, p1 ) { return '/'+p1+'/'; };\nvar str = 'Oranges and lemons';\nvar out = base.replace( str, /([^\\s]+)/gi, replacer )\nout = base.replace( 'beep', /e/, 'o' )\n","base.replaceAfter":"var out = base.replaceAfter( 'beep boop', ' ', 'foo', 0 )\nout = base.replaceAfter( 'beep boop', 'o', 'foo', 0 )\nout = base.replaceAfter( 'Hello World!', 'o', 'foo', 5 )\nout = base.replaceAfter( 'beep boop beep baz', 'beep', 'foo', 5 )\n","base.replaceAfterLast":"var str = 'beep boop';\nvar out = base.replaceAfterLast( str, ' ', 'foo', str.length )\nout = base.replaceAfterLast( str, 'o', 'foo', str.length )\nout = base.replaceAfterLast( 'Hello World!', 'o', 'foo', 5 )\n","base.replaceBefore":"var out = base.replaceBefore( 'beep boop', ' ', 'foo', 0 )\nout = base.replaceBefore( 'beep boop', 'o', 'foo', 0 )\n","base.replaceBeforeLast":"var str = 'beep boop';\nvar out = base.replaceBeforeLast( str, ' ', 'foo', str.length )\nout = base.replaceBeforeLast( str, 'o', 'foo', str.length )\nout = base.replaceBeforeLast( 'Hello World!', 'o', 'foo', 5 )\n","base.reverse":"var out = base.reverse( 'beep' )\nout = base.reverse( 'Boop' )\nout = base.reverse( 'foo bar' )\n","base.reverseCodePoints":"var out = base.reverseCodePoints( 'beep' )\nout = base.reverseCodePoints( 'Boop' )\nout = base.reverseCodePoints( 'foo bar' )\n","base.reverseGraphemeClusters":"var out = base.reverseGraphemeClusters( 'beep' )\nout = base.reverseGraphemeClusters( 'Boop' )\nout = base.reverseGraphemeClusters( 'foo bar' )\n","base.rightPad":"var out = base.rightPad( 'a', 5, ' ' )\nout = base.rightPad( 'beep', 10, 'b' )\nout = base.rightPad( 'boop', 12, 'beep' )\n","base.rightTrim":"var out = base.rightTrim( ' \\t\\t\\n  Beep \\r\\n\\t  ' )\n","base.risingFactorial":"var v = base.risingFactorial( 0.9, 5 )\nv = base.risingFactorial( -9.0, 3 )\nv = base.risingFactorial( 0.0, 2 )\nv = base.risingFactorial( 3.0, -2 )\n","base.rotl32":"var x = 2147483649;\nvar bStr = base.toBinaryStringUint32( x )\nvar y = base.rotl32( x, 10 )\nbstr = base.toBinaryStringUint32( y )\n","base.rotr32":"var x = 1;\nvar bStr = base.toBinaryStringUint32( x )\nvar y = base.rotr32( x, 10 )\nbstr = base.toBinaryStringUint32( y )\n","base.round":"var y = base.round( 3.14 )\ny = base.round( -4.2 )\ny = base.round( -4.6 )\ny = base.round( 9.5 )\ny = base.round( -0.0 )\n","base.round2":"var y = base.round2( 3.14 )\ny = base.round2( -4.2 )\ny = base.round2( -4.6 )\ny = base.round2( 9.5 )\ny = base.round2( 13.0 )\ny = base.round2( -13.0 )\ny = base.round2( -0.0 )\n","base.round10":"var y = base.round10( 3.14 )\ny = base.round10( -4.2 )\ny = base.round10( -4.6 )\ny = base.round10( 9.5 )\ny = base.round10( 13.0 )\ny = base.round10( -13.0 )\ny = base.round10( -0.0 )\n","base.roundb":"var y = base.roundb( 3.14159, -2, 10 )\ny = base.roundb( 3.14159, 0, 2 )\ny = base.roundb( 5.0, 1, 2 )\n","base.roundn":"var y = base.roundn( 3.14159, -2 )\ny = base.roundn( 3.14159, 0 )\ny = base.roundn( 12368.0, 3 )\n","base.roundsd":"var y = base.roundsd( 3.14159, 3 )\ny = base.roundsd( 3.14159, 1 )\ny = base.roundsd( 12368.0, 2 )\ny = base.roundsd( 0.0313, 2, 2 )\n","base.rsqrt":"var y = base.rsqrt( 4.0 )\ny = base.rsqrt( 100.0 )\ny = base.rsqrt( 0.0 )\ny = base.rsqrt( Infinity )\ny = base.rsqrt( -4.0 )\ny = base.rsqrt( NaN )\n","base.rsqrtf":"var y = base.rsqrtf( 4.0 )\ny = base.rsqrtf( 0.0 )\ny = base.rsqrtf( Infinity )\ny = base.rsqrtf( -4.0 )\ny = base.rsqrtf( NaN )\n","base.sargs2multislice":"var s = new base.sargs2multislice( 'null,null,null' );\ns.data\ns = new base.sargs2multislice( '10,Slice(0,10,1),null' );\ns.data\n","base.scalar2ndarray":"var x = base.scalar2ndarray( 1.0, 'float64', 'row-major' )\nvar sh = x.shape\nvar dt = x.dtype\nvar v = x.get()\n","base.secd":"var y = base.secd( 1.0 )\ny = base.secd( PI )\ny = base.secd( -PI )\ny = base.secd( NaN )\n","base.seq2multislice":"var s = new base.seq2multislice( '1:10', [ 10 ], false );\ns.data\ns = new base.seq2multislice( '4,2:5:2,:', [ 10, 10, 10 ], false );\ns.data\n","base.seq2slice":"var s = new base.seq2slice( '1:10', 10, false );\ns.start\ns.stop\ns.step\ns = new base.seq2slice( '2:5:2', 10, false );\ns.start\ns.stop\ns.step\n","base.setHighWord":"var high = 1072693248 >>> 0;\nvar y = base.setHighWord( PINF, high )\n","base.setLowWord":"var low = 5 >>> 0;\nvar x = 3.14e201;\nvar y = base.setLowWord( x, low )\nvar low = 12345678;\nvar y = base.setLowWord( PINF, low )\ny = base.setLowWord( NINF, low )\ny = base.setLowWord( NaN, low )\n","base.sici":"var y = base.sici( 3.0 )\ny = base.sici( 0.0 )\ny = base.sici( -9.0 )\ny = base.sici( NaN )\n","base.sici.assign":"var out = new Float64Array( 2 );\nvar y = base.sici.assign( 3.0, out, 1, 0 )\nvar bool = ( y === out )\n","base.signbit":"var bool = base.signbit( 4.0 )\nbool = base.signbit( -9.14e-34 )\nbool = base.signbit( 0.0 )\nbool = base.signbit( -0.0 )\n","base.signbitf":"var bool = base.signbitf( base.float64ToFloat32( 4.0 ) )\nbool = base.signbitf( base.float64ToFloat32( -9.14e-34 ) )\nbool = base.signbitf( 0.0 )\nbool = base.signbitf( -0.0 )\n","base.significandf":"var s = base.significandf( base.float64ToFloat32( 3.14e34 ) )\ns = base.significandf( base.float64ToFloat32( 3.14e-34 ) )\ns = base.significandf( base.float64ToFloat32( -3.14 ) )\ns = base.significandf( 0.0 )\ns = base.significandf( NaN )\n","base.signum":"var sign = base.signum( -5.0 )\nsign = base.signum( 5.0 )\nsign = base.signum( -0.0 )\nsign = base.signum( 0.0 )\nsign = base.signum( NaN )\n","base.signumf":"var sign = base.signumf( -5.0 )\nsign = base.signumf( 5.0 )\nsign = base.signumf( -0.0 )\nsign = base.signumf( 0.0 )\nsign = base.signumf( NaN )\n","base.sin":"var y = base.sin( 0.0 )\ny = base.sin( PI/2.0 )\ny = base.sin( -PI/6.0 )\ny = base.sin( NaN )\n","base.sinc":"var y = base.sinc( 0.5 )\ny = base.sinc( -1.2 )\ny = base.sinc( 0.0 )\ny = base.sinc( NaN )\n","base.sincos":"var y = base.sincos( 0.0 )\ny = base.sincos( PI/2.0 )\ny = base.sincos( -PI/6.0 )\ny = base.sincos( NaN )\nvar out = new Float64Array( 2 );\nvar v = base.sincos.assign( 0.0, out, 1, 0 )\nvar bool = ( v === out )\n","base.sincospi":"var y = base.sincospi( 0.0 )\ny = base.sincospi( 0.5 )\ny = base.sincospi( 0.1 )\ny = base.sincospi( NaN )\n","base.sincospi.assign":"var out = new Float64Array( 2 );\nvar v = base.sincospi.assign( 0.0, out, 1, 0 )\nvar bool = ( v === out )\n","base.sinh":"var y = base.sinh( 0.0 )\ny = base.sinh( 2.0 )\ny = base.sinh( -2.0 )\ny = base.sinh( NaN )\n","base.sinpi":"var y = base.sinpi( 0.0 )\ny = base.sinpi( 0.5 )\ny = base.sinpi( 0.9 )\ny = base.sinpi( NaN )\n","base.slice2seq":"var out = base.slice2seq( new Slice( 1, 10, 1 ) )\nout = base.slice2seq( new Slice( null, 10 ) )\n","base.sliceLength":"var s = new Slice( 1, 10, 1 );\nbase.sliceLength( s )\n","base.sliceNonReducedDimensions":"var s = new MultiSlice( 1, 3, null );\nvar out = base.sliceNonReducedDimensions( s )\n","base.sliceReducedDimensions":"var s = new MultiSlice( 1, 3, null );\nvar out = base.sliceReducedDimensions( s )\n","base.sliceShape":"var s = new Slice( 1, 10, 1 );\nvar ms = new MultiSlice( s, s );\nbase.sliceShape( ms )\n","base.snakecase":"var out = base.snakecase( 'Hello World!' )\nout = base.snakecase( 'I am a tiny little teapot' )\n","base.spence":"var y = base.spence( 3.0 )\ny = base.spence( 0.0 )\ny = base.spence( -9.0 )\ny = base.spence( NaN )\n","base.sqrt":"var y = base.sqrt( 4.0 )\ny = base.sqrt( 9.0 )\ny = base.sqrt( 0.0 )\ny = base.sqrt( -4.0 )\ny = base.sqrt( NaN )\n","base.sqrt1pm1":"var y = base.sqrt1pm1( 3.0 )\ny = base.sqrt1pm1( 0.5 )\ny = base.sqrt1pm1( 0.02 )\ny = base.sqrt1pm1( -0.5 )\ny = base.sqrt1pm1( -1.1 )\ny = base.sqrt1pm1( NaN )\n","base.sqrtf":"var y = base.sqrtf( 4.0 )\ny = base.sqrtf( 9.0 )\ny = base.sqrtf( 0.0 )\ny = base.sqrtf( -4.0 )\ny = base.sqrtf( NaN )\n","base.sqrtpi":"var y = base.sqrtpi( 4.0 )\ny = base.sqrtpi( 10.0 )\ny = base.sqrtpi( 0.0 )\ny = base.sqrtpi( -4.0 )\ny = base.sqrtpi( NaN )\n","base.startcase":"var out = base.startcase( 'beep boop' )\n","base.startsWith":"var bool = base.startsWith( 'Beep', 'Be', 0 )\nbool = base.startsWith( 'Beep', 'ep', 0 )\nbool = base.startsWith( 'Beep', 'ee', 1 )\nbool = base.startsWith( 'Beep', 'ee', -3 )\nbool = base.startsWith( 'Beep', '', 0 )\n","base.stickycase":"var out = base.stickycase( 'Hello World!' )\nout = base.stickycase( 'I am a tiny little teapot' )\n","base.strided.binary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nfunction f( x, y ) { return x + y; };\nbase.strided.binary( [ x, y, z ], shape, strides, f );\nz\n","base.strided.binary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nvar offsets = [ 0, 0, 0 ];\nfunction f( x, y ) { return x + y; };\nbase.strided.binary.ndarray( [ x, y, z ], shape, strides, offsets, f );\nz\n","base.strided.binaryDtypeSignatures":"var dt = strided.dataTypes();\nvar out = base.strided.binaryDtypeSignatures( dt, dt, dt )\n","base.strided.binarySignatureCallbacks":"var dt = strided.dataTypes();\nvar sigs = base.strided.binaryDtypeSignatures( dt, dt, dt );\nvar t = {\n 'default': base.add,\n 'complex64': base.caddf,\n 'complex128': base.cadd\n };\nvar out = base.strided.binarySignatureCallbacks( t, sigs )\n","base.strided.ccopy":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.ccopy( x.length, x, 1, y, 1 );\nvar z = y.get( 0 );\nvar re = realf( z )\nvar im = imagf( z )\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ccopy( 2, x, -2, y, 1 );\nz = y.get( 0 );\nre = realf( z )\nim = imagf( z )\nvar x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\nvar y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.ccopy( 2, x1, -2, y1, 1 );\nz = y0.get( 2 );\nre = realf( z )\nim = imagf( z )\n","base.strided.ccopy.ndarray":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.ccopy.ndarray( x.length, x, 1, 0, y, 1, 0 );\nvar z = y.get( 0 );\nvar re = realf( z )\nvar im = imagf( z )\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ccopy.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\nz = y.get( y.length-1 );\nre = realf( z )\nim = imagf( z )\n","base.strided.cmap":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex64Array( xbuf );\nvar y = new Complex64Array( x.length );\nbase.strided.cmap( x.length, x, 1, y, 1, base.cidentityf );\nvar v = y.get( 0 )\nvar re = real( v )\nvar im = imag( v )\ny = new Complex64Array( x.length );\nbase.strided.cmap( 2, x, 2, y, -1, base.cidentityf );\nv = y.get( 0 )\nre = real( v )\nim = imag( v )\nvar x0 = new Complex64Array( xbuf );\nvar y0 = new Complex64Array( x0.length );\nvar x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.cmap( 2, x1, -2, y1, 1, base.cidentityf );\nv = y1.get( 0 )\nre = real( v )\nim = imag( v )\n","base.strided.cmap.ndarray":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex64Array( xbuf );\nvar y = new Complex64Array( x.length );\nbase.strided.cmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentityf );\nvar v = y.get( 0 )\nvar re = real( v )\nvar im = imag( v )\nx = new Complex64Array( xbuf );\ny = new Complex64Array( x.length );\nbase.strided.cmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentityf );\nv = y.get( y.length-1 )\nre = real( v )\nim = imag( v )\n","base.strided.cswap":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.cswap( x.length, x, 1, y, 1 );\nvar z = y.get( 0 );\nvar re = realf( z )\nvar im = imagf( z )\nz = x.get( 0 );\nre = realf( z )\nim = imagf( z )\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.cswap( 2, x, -2, y, 1 );\nz = y.get( 0 );\nre = realf( z )\nim = imagf( z )\nz = x.get( 0 );\nre = realf( z )\nim = imagf( z )\nvar x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\nvar y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.cswap( 2, x1, -2, y1, 1 );\nz = y0.get( 2 );\nre = realf( z )\nim = imagf( z )\nz = x0.get( 1 );\nre = realf( z )\nim = imagf( z )\n","base.strided.cswap.ndarray":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.cswap.ndarray( x.length, x, 1, 0, y, 1, 0 );\nvar z = y.get( 0 );\nvar re = realf( z )\nvar im = imagf( z )\nz = x.get( 0 );\nre = realf( z )\nim = imagf( z )\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.cswap.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\nz = y.get( y.length-1 );\nre = realf( z )\nim = imagf( z )\nz = x.get( 1 );\nre = realf( z )\nim = imagf( z )\n","base.strided.cumax":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumax( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumax( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.cumax( N, x1, 2, y1, 1 )\ny0\n","base.strided.cumax.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumax.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.cumaxabs":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumaxabs( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumaxabs( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.cumaxabs( N, x1, 2, y1, 1 )\ny0\n","base.strided.cumaxabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.cumin":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumin( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumin( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.cumin( N, x1, 2, y1, 1 )\ny0\n","base.strided.cumin.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.cuminabs":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cuminabs( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cuminabs( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.cuminabs( N, x1, 2, y1, 1 )\ny0\n","base.strided.cuminabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dabs":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dabs( N, x1, -2, y1, 1 )\ny0\n","base.strided.dabs.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dabs2":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs2( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs2( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dabs2( N, x1, -2, y1, 1 )\ny0\n","base.strided.dabs2.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dapx":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dapx( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dapx( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapx( 3, 5.0, x1, 2 )\nx0\n","base.strided.dapx.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dapx.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.dapx.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsum":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsum( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsum( 3, 5.0, x1, 2 )\n","base.strided.dapxsum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsumkbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsumkbn( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsumkbn( 3, 5.0, x1, 2)\n","base.strided.dapxsumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsumkbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn2( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsumkbn2( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsumkbn2( 3, 5.0, x1, 2 )\n","base.strided.dapxsumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsumors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumors( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsumors( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsumors( 3, 5.0, x1, 2 )\n","base.strided.dapxsumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumpw( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsumpw( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsumpw( 3, 5.0, x1, 2 )\n","base.strided.dapxsumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dasum":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.dasum( x.length, x, 1 )\ns = base.strided.dasum( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\ns = base.strided.dasum( 3, x1, 2 )\n","base.strided.dasum.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.dasum.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\ns = base.strided.dasum.ndarray( 3, x, -1, x.length-1 )\n","base.strided.dasumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dasumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar stride = 2;\nbase.strided.dasumpw( 3, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.dasumpw( 3, x1, stride )\n","base.strided.dasumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dasumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dasumpw.ndarray( 3, x, 2, 1 )\n","base.strided.daxpy":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.daxpy( x.length, alpha, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nbase.strided.daxpy( 3, alpha, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.daxpy( 3, 5.0, x1, -2, y1, 1 )\ny0\n","base.strided.daxpy.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.daxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.daxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcbrt":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dcbrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dcbrt( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dcbrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.dcbrt.ndarray":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dcbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dceil":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dceil( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dceil( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dceil( N, x1, -2, y1, 1 )\ny0\n","base.strided.dceil.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcopy":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dcopy( x.length, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dcopy( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcopy( 3, x1, -2, y1, 1 )\ny0\n","base.strided.dcopy.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcumax":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumax( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumax( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcumax( 3, x1, 2, y1, 1 )\ny0\n","base.strided.dcumax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcumaxabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumaxabs( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumaxabs( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcumaxabs( 3, x1, 2, y1, 1 )\ny0\n","base.strided.dcumaxabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcumin":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumin( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumin( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcumin( 3, x1, 2, y1, 1 )\ny0\n","base.strided.dcumin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcuminabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcuminabs( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcuminabs( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcuminabs( 3, x1, 2, y1, 1 )\ny0\n","base.strided.dcuminabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusum":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusum( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusum( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusum( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumkbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumkbn( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusumkbn( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumkbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn2( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumkbn2( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusumkbn2( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumors( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumors( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusumors( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumpw( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumpw( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusumpw( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.ddeg2rad":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ddeg2rad( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ddeg2rad( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.ddeg2rad( N, x1, -2, y1, 1 )\ny0\n","base.strided.ddeg2rad.ndarray":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ddeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ddeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.ddot":"var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.ddot( x.length, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.ddot( 3, x, 2, y, -1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.ddot( 3, x1, -2, y1, 1 )\n","base.strided.ddot.ndarray":"var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.ddot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.ddot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nout = base.strided.ddot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.dfill":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dfill( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dfill( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dfill( 3, 5.0, x1, 2 )\nx0\n","base.strided.dfill.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dfill.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.dfill.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dfloor":"var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dfloor( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dfloor( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dfloor( N, x1, -2, y1, 1 )\ny0\n","base.strided.dfloor.ndarray":"var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dinv":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dinv( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dinv( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dinv( N, x1, -2, y1, 1 )\ny0\n","base.strided.dinv.ndarray":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dmap":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap( x.length, x, 1, y, 1, base.identity )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap( 2, x, 2, y, -1, base.identity )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmap( 2, x1, -2, y1, 1, base.identity )\ny0\n","base.strided.dmap.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identity )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identity )\n","base.strided.dmap2":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2( x.length, x, 1, y, 1, z, 1, base.add )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2( 2, x, 2, y, -1, z, 1, base.add )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmap2( 2, x1, -2, y1, 1, z1, 1, base.add )\nz0\n","base.strided.dmap2.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.add )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.add )\n","base.strided.dmax":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmax( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmax( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmax( 3, x1, 2 )\n","base.strided.dmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmax.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmax.ndarray( 3, x, 2, 1 )\n","base.strided.dmaxabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmaxabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmaxabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmaxabs( 3, x1, 2 )\n","base.strided.dmaxabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmaxabs.ndarray( 3, x, 2, 1 )\n","base.strided.dmaxabssorted":"var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.dmaxabssorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmaxabssorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmaxabssorted( 3, x1, 2 )\n","base.strided.dmaxabssorted.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.dmaxabssorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.dmaxabssorted.ndarray( 3, x, 2, 1 )\n","base.strided.dmaxsorted":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmaxsorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmaxsorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmaxsorted( 3, x1, 2 )\n","base.strided.dmaxsorted.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmaxsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.dmaxsorted.ndarray( 3, x, 2, 1 )\n","base.strided.dmean":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmean( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmean( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmean( N, x1, stride )\n","base.strided.dmean.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmean.ndarray( N, x, 2, 1 )\n","base.strided.dmeankbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeankbn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeankbn( N, x1, stride )\n","base.strided.dmeankbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeankbn.ndarray( N, x, 2, 1 )\n","base.strided.dmeankbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeankbn2( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeankbn2( N, x1, stride )\n","base.strided.dmeankbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeankbn2.ndarray( N, x, 2, 1 )\n","base.strided.dmeanli":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanli( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanli( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanli( N, x1, stride )\n","base.strided.dmeanli.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanli.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanli.ndarray( N, x, 2, 1 )\n","base.strided.dmeanlipw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanlipw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanlipw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanlipw( N, x1, stride )\n","base.strided.dmeanlipw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanlipw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanlipw.ndarray( N, x, 2, 1 )\n","base.strided.dmeanors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanors( N, x1, stride )\n","base.strided.dmeanors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanors.ndarray( N, x, 2, 1 )\n","base.strided.dmeanpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanpn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanpn( N, x1, stride )\n","base.strided.dmeanpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.dmeanpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanpw( N, x1, stride )\n","base.strided.dmeanpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanpw.ndarray( N, x, 2, 1 )\n","base.strided.dmeanstdev":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdev( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanstdev( N, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdev( N, 1, x1, 2, out, 1 )\n","base.strided.dmeanstdev.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdev.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdev.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanstdevpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdevpn( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanstdevpn( N, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdevpn( N, 1, x1, 2, out, 1 )\n","base.strided.dmeanstdevpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdevpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdevpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanvar":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvar( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanvar( N, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanvar( N, 1, x1, 2, out, 1 )\n","base.strided.dmeanvar.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvar.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanvar.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanvarpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvarpn( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanvarpn( N, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanvarpn( N, 1, x1, 2, out, 1 )\n","base.strided.dmeanvarpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvarpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanvarpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanwd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanwd( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanwd( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanwd( N, x1, stride )\n","base.strided.dmeanwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanwd.ndarray( N, x, 2, 1 )\n","base.strided.dmediansorted":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmediansorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmediansorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmediansorted( 3, x1, 2 )\n","base.strided.dmediansorted.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.dmediansorted.ndarray( 3, x, 2, 1 )\n","base.strided.dmidrange":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmidrange( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmidrange( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmidrange( 3, x1, 2 )\n","base.strided.dmidrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmidrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmidrange.ndarray( 3, x, 2, 1 )\n","base.strided.dmin":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmin( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmin( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmin( N, x1, stride )\n","base.strided.dmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmin.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmin.ndarray( 3, x, 2, 1 )\n","base.strided.dminabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dminabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dminabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dminabs( 3, x1, 2 )\n","base.strided.dminabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dminabs.ndarray( 3, x, 2, 1 )\n","base.strided.dminsorted":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dminsorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dminsorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dminsorted( 3, x1, 2 )\n","base.strided.dminsorted.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dminsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.dminsorted.ndarray( 3, x, 2, 1 )\n","base.strided.dmskabs":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskabs( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskabs.ndarray":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskabs2":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskabs2( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskabs2.ndarray":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskcbrt":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskcbrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskcbrt.ndarray":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskceil":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskceil( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskceil.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskdeg2rad":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskdeg2rad.ndarray":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskfloor":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskfloor( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskfloor.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskinv":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskinv( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskinv.ndarray":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskmap":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap( x.length, x, 1, m, 1, y, 1, base.identity )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap( 2, x, 2, m, 2, y, -1, base.identity )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\ny0\n","base.strided.dmskmap.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n","base.strided.dmskmap2":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.add )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.add )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.add )\nz0\n","base.strided.dmskmap2.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.add )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.add )\n","base.strided.dmskmax":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmax( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskmax( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmskmax( 3, x1, 2, mask1, 2 )\n","base.strided.dmskmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.dmskmin":"var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmin( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskmin( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmskmin( 3, x1, 2, mask1, 2 )\n","base.strided.dmskmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.dmskramp":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskramp( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskramp.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskrange":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskrange( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskrange( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmskrange( 3, x1, 2, mask1, 2 )\n","base.strided.dmskrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.dmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.dmskrsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskrsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmsksqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmsksqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmsksqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmsktrunc":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmsktrunc( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmsktrunc.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dnanasum":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasum( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanasum( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanasum( 4, x1, 2 )\n","base.strided.dnanasum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasum.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanasum.ndarray( 4, x, 2, 1 )\n","base.strided.dnanasumors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasumors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanasumors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanasumors( N, x1, stride )\n","base.strided.dnanasumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanasumors.ndarray( N, x, 2, 1 )\n","base.strided.dnanmax":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmax( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanmax( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmax( 3, x1, 2 )\n","base.strided.dnanmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanmax.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanmax.ndarray( 3, x, 2, 1 )\n","base.strided.dnanmaxabs":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmaxabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanmaxabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmaxabs( 3, x1, 2 )\n","base.strided.dnanmaxabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanmaxabs.ndarray( 3, x, 2, 1 )\n","base.strided.dnanmean":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmean( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmean( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmean( N, x1, stride )\n","base.strided.dnanmean.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmean.ndarray( N, x, 2, 1 )\n","base.strided.dnanmeanors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmeanors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmeanors( N, x1, stride )\n","base.strided.dnanmeanors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmeanors.ndarray( N, x, 2, 1 )\n","base.strided.dnanmeanpn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmeanpn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmeanpn( N, x1, stride )\n","base.strided.dnanmeanpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.dnanmeanpw":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmeanpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmeanpw( N, x1, stride )\n","base.strided.dnanmeanpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmeanpw.ndarray( N, x, 2, 1 )\n","base.strided.dnanmeanwd":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanwd( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmeanwd( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmeanwd( N, x1, stride )\n","base.strided.dnanmeanwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmeanwd.ndarray( N, x, 2, 1 )\n","base.strided.dnanmin":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmin( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanmin( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmin( 3, x1, 2 )\n","base.strided.dnanmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanmin.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanmin.ndarray( 3, x, 2, 1 )\n","base.strided.dnanminabs":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanminabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanminabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanminabs( 3, x1, 2 )\n","base.strided.dnanminabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanminabs.ndarray( 3, x, 2, 1 )\n","base.strided.dnanmskmax":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.dnanmskmax( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskmax( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dnanmskmax( N, x1, 2, mask1, 2 )\n","base.strided.dnanmskmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.dnanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.dnanmskmin":"var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.dnanmskmin( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskmin( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dnanmskmin( N, x1, 2, mask1, 2 )\n","base.strided.dnanmskmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.dnanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.dnanmskrange":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.dnanmskrange( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskrange( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dnanmskrange( N, x1, 2, mask1, 2 )\n","base.strided.dnanmskrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.dnanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.dnannsum":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsum( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsum( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsum( 4, x1, 2, out, 1 )\n","base.strided.dnannsum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsum.ndarray( x.length, x, 1, 0, out, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsum.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumkbn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn( 4, x1, 2, out, 1 )\n","base.strided.dnannsumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn.ndarray( 4, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumkbn2":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn2( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn2( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn2( 4, x1, 2, out, 1 )\n","base.strided.dnannsumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn2.ndarray( 4, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn2.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumors( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumors( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumors( 4, x1, 2, out, 1 )\n","base.strided.dnannsumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumpw":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumpw( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumpw( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumpw( 4, x1, 2, out, 1 )\n","base.strided.dnannsumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumpw.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumpw.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnanrange":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanrange( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanrange( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanrange( 3, x1, 2 )\n","base.strided.dnanrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanrange.ndarray( 3, x, 2, 1 )\n","base.strided.dnanstdev":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdev( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdev( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdev( N, 1, x1, stride )\n","base.strided.dnanstdev.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanstdevch":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevch( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdevch( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdevch( N, 1, x1, stride )\n","base.strided.dnanstdevch.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanstdevpn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevpn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdevpn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdevpn( N, 1, x1, stride )\n","base.strided.dnanstdevpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanstdevtk":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevtk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdevtk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdevtk( N, 1, x1, stride )\n","base.strided.dnanstdevtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanstdevwd":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevwd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdevwd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdevwd( N, 1, x1, stride )\n","base.strided.dnanstdevwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanstdevyc":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdevyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdevyc( N, 1, x1, stride )\n","base.strided.dnanstdevyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnansum":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansum( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansum( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansum( 4, x1, 2 )\n","base.strided.dnansum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansum.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansum.ndarray( 4, x, 2, 1 )\n","base.strided.dnansumkbn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumkbn( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansumkbn( 4, x1, 2 )\n","base.strided.dnansumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumkbn.ndarray( 4, x, 2, 1 )\n","base.strided.dnansumkbn2":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumkbn2( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansumkbn2( 4, x1, 2 )\n","base.strided.dnansumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumkbn2.ndarray( 4, x, 2, 1 )\n","base.strided.dnansumors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumors( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansumors( 4, x1, 2 )\n","base.strided.dnansumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumors.ndarray( 4, x, 2, 1 )\n","base.strided.dnansumpw":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumpw( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansumpw( 4, x1, 2 )\n","base.strided.dnansumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumpw.ndarray( 4, x, 2, 1 )\n","base.strided.dnanvariance":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariance( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvariance( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvariance( N, 1, x1, stride )\n","base.strided.dnanvariance.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanvariancech":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancech( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvariancech( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvariancech( N, 1, x1, stride )\n","base.strided.dnanvariancech.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvariancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanvariancepn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancepn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvariancepn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvariancepn( N, 1, x1, stride )\n","base.strided.dnanvariancepn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanvariancetk":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancetk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvariancetk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvariancetk( N, 1, x1, stride )\n","base.strided.dnanvariancetk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvariancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanvariancewd":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancewd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvariancewd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvariancewd( N, 1, x1, stride )\n","base.strided.dnanvariancewd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvariancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanvarianceyc":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvarianceyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvarianceyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvarianceyc( N, 1, x1, stride )\n","base.strided.dnanvarianceyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvarianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnrm2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dnrm2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dnrm2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnrm2( 3, x1, 2 )\n","base.strided.dnrm2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dnrm2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dnrm2.ndarray( 3, x, 2, 1 )\n","base.strided.dramp":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dramp( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dramp( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dramp( N, x1, -2, y1, 1 )\ny0\n","base.strided.dramp.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.drange":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.drange( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.drange( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.drange( 3, x1, 2 )\n","base.strided.drange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.drange.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.drange.ndarray( 3, x, 2, 1 )\n","base.strided.drev":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.drev( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.drev( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.drev( 3, x1, 2 )\nx0\n","base.strided.drev.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.drev.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.drev.ndarray( 3, x, 2, 1 )\n","base.strided.drsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.drsqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.drsqrt( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.drsqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.drsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.drsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.drsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dsapxsum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsum( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsapxsum( 3, 5.0, x1, 2 )\n","base.strided.dsapxsum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dsapxsumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsumpw( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsapxsumpw( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsapxsumpw( 3, 5.0, x1, 2 )\n","base.strided.dsapxsumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dscal":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dscal( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dscal( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dscal( 3, 5.0, x1, 2 )\nx0\n","base.strided.dscal.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dscal.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.dscal.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dsdot":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar dot = base.strided.dsdot( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\ndot = base.strided.dsdot( 3, x, 2, y, -1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\ndot = base.strided.dsdot( 3, x1, -2, y1, 1 )\n","base.strided.dsdot.ndarray":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar dot = base.strided.dsdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\ndot = base.strided.dsdot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\ndot = base.strided.dsdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.dsem":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsem( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsem( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsem( N, 1, x1, stride )\n","base.strided.dsem.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsem.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsem.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsemch":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemch( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsemch( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsemch( N, 1, x1, stride )\n","base.strided.dsemch.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsemch.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsempn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsempn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsempn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsempn( N, 1, x1, stride )\n","base.strided.dsempn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsempn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsempn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsemtk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemtk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsemtk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsemtk( N, 1, x1, stride )\n","base.strided.dsemtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsemtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsemwd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemwd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsemwd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsemwd( N, 1, x1, stride )\n","base.strided.dsemwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsemwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsemyc":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsemyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsemyc( N, 1, x1, stride )\n","base.strided.dsemyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsemyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsmean":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsmean( N, x1, stride )\n","base.strided.dsmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsmean.ndarray( N, x, 2, 1 )\n","base.strided.dsmeanors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsmeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsmeanors( N, x1, stride )\n","base.strided.dsmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsmeanors.ndarray( N, x, 2, 1 )\n","base.strided.dsmeanpn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsmeanpn( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsmeanpn( N, x1, stride )\n","base.strided.dsmeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.dsmeanpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsmeanpw( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsmeanpw( N, x1, stride )\n","base.strided.dsmeanpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsmeanpw.ndarray( N, x, 2, 1 )\n","base.strided.dsmeanwd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsmeanwd( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsmeanwd( N, x1, stride )\n","base.strided.dsmeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsmeanwd.ndarray( N, x, 2, 1 )\n","base.strided.dsnanmean":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsnanmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsnanmean( N, x1, stride )\n","base.strided.dsnanmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsnanmean.ndarray( N, x, 2, 1 )\n","base.strided.dsnanmeanors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsnanmeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsnanmeanors( N, x1, stride )\n","base.strided.dsnanmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsnanmeanors.ndarray( N, x, 2, 1 )\n","base.strided.dsnanmeanpn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsnanmeanpn( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsnanmeanpn( N, x1, stride )\n","base.strided.dsnanmeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsnanmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.dsnanmeanwd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsnanmeanwd( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsnanmeanwd( N, x1, stride )\n","base.strided.dsnanmeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsnanmeanwd.ndarray( N, x, 2, 1 )\n","base.strided.dsnannsumors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dsnannsumors( x.length, x, 1, out, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dsnannsumors( 4, x, 2, out, 1 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dsnannsumors( N, x1, 2, out, 1 )\n","base.strided.dsnannsumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dsnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dsnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dsnansum":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansum( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnansum( 4, x1, 2 )\n","base.strided.dsnansum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansum.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsnansum.ndarray( 3, x, 2, 1 )\n","base.strided.dsnansumors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansumors( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnansumors( 4, x1, 2 )\n","base.strided.dsnansumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansumors.ndarray( 4, x, 2, 1 )\n","base.strided.dsnansumpw":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansumpw( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnansumpw( 4, x1, 2 )\n","base.strided.dsnansumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansumpw.ndarray( 4, x, 2, 1 )\n","base.strided.dsort2hp":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2hp( x.length, 1, x, 1, y, 1 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2hp( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsort2hp( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.dsort2hp.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.dsort2ins":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2ins( x.length, 1, x, 1, y, 1 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2ins( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsort2ins( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.dsort2ins.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.dsort2sh":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2sh( x.length, 1, x, 1, y, 1 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2sh( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsort2sh( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.dsort2sh.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.dsorthp":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsorthp( x.length, 1, x, 1 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsorthp( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsorthp( N, 1, x1, 2 )\nx0\n","base.strided.dsorthp.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsorthp.ndarray( x.length, 1, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsorthp.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsortins":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortins( x.length, 1, x, 1 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsortins( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsortins( N, 1, x1, 2 )\nx0\n","base.strided.dsortins.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortins.ndarray( x.length, 1, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsortins.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsortsh":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortsh( x.length, 1, x, 1 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsortsh( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsortsh( N, 1, x1, 2 )\nx0\n","base.strided.dsortsh.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortsh.ndarray( x.length, 1, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsortsh.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dsqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dsqrt( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.dsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dssum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dssum( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dssum( 3, x1, 2 )\n","base.strided.dssum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssum.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dssum.ndarray(3, x, 2, 1 )\n","base.strided.dssumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dssumors( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dssumors( 3, x1, 2 )\n","base.strided.dssumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dssumors.ndarray( 3, x, 2, 1 )\n","base.strided.dssumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dssumpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dssumpw( 3, x1, 2 )\n","base.strided.dssumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dssumpw.ndarray( 3, x, 2, 1 )\n","base.strided.dstdev":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdev( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdev( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdev( N, 1, x1, stride )\n","base.strided.dstdev.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.dstdevch":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevch( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdevch( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdevch( N, 1, x1, stride )\n","base.strided.dstdevch.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.dstdevpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevpn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdevpn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdevpn( N, 1, x1, stride )\n","base.strided.dstdevpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dstdevtk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevtk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdevtk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdevtk( N, 1, x1, stride )\n","base.strided.dstdevtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.dstdevwd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevwd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdevwd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdevwd( N, 1, x1, stride )\n","base.strided.dstdevwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.dstdevyc":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdevyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdevyc( N, 1, x1, stride )\n","base.strided.dstdevyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsum":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsum( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsum( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsum( 3, x1, 2 )\n","base.strided.dsum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsum.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsum.ndarray( 3, x, 2, 1 )\n","base.strided.dsumkbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumkbn( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumkbn( 3, x1, 2 )\n","base.strided.dsumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsumkbn.ndarray( 3, x, 2, 1 )\n","base.strided.dsumkbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumkbn2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumkbn2( 3, x1, 2 )\n","base.strided.dsumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsumkbn2.ndarray( 3, x, 2, 1 )\n","base.strided.dsumors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumors( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumors( 3, x1, 2 )\n","base.strided.dsumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsumors.ndarray( 3, x, 2, 1 )\n","base.strided.dsumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumpw( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumpw( 3, x1, 2 )\n","base.strided.dsumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumpw.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsumpw.ndarray( 3, x, 2, 1 )\n","base.strided.dsvariance":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariance( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsvariance( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsvariance( N, 1, x1, stride )\n","base.strided.dsvariance.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsvariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsvariancepn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariancepn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsvariancepn( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsvariancepn( N, 1, x1, stride )\n","base.strided.dsvariancepn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsvariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dswap":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dswap( x.length, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dswap( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dswap( 3, x1, -2, y1, 1 )\ny0\n","base.strided.dswap.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dtrunc":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dtrunc( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dtrunc( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dtrunc( N, x1, -2, y1, 1 )\ny0\n","base.strided.dtrunc.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dtrunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dtrunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dtypeEnum2Str":"var out = base.strided.dtypeEnum2Str( base.strided.dtypeStr2Enum( 'float64' ) )\n","base.strided.dtypeResolveEnum":"var out = base.strided.dtypeResolveEnum( 'float64' )\nout = base.strided.dtypeResolveEnum( base.strided.dtypeStr2Enum( 'float64' ) )\n","base.strided.dtypeResolveStr":"var out = base.strided.dtypeResolveStr( 'float64' )\nout = base.strided.dtypeResolveStr( base.strided.dtypeStr2Enum( 'float64' ) )\n","base.strided.dtypeStr2Enum":"var out = base.strided.dtypeStr2Enum( 'float64' )\n","base.strided.dvariance":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariance( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvariance( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvariance( N, 1, x1, stride )\n","base.strided.dvariance.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.dvariancech":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancech( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvariancech( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvariancech( N, 1, x1, stride )\n","base.strided.dvariancech.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvariancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.dvariancepn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancepn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvariancepn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvariancepn( N, 1, x1, stride )\n","base.strided.dvariancepn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dvariancetk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancetk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvariancetk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvariancetk( N, 1, x1, stride )\n","base.strided.dvariancetk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvariancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.dvariancewd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancewd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvariancewd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvariancewd( N, 1, x1, stride )\n","base.strided.dvariancewd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvariancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.dvarianceyc":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarianceyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvarianceyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvarianceyc( N, 1, x1, stride )\n","base.strided.dvarianceyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.dvarm":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarm( x.length, 1.0/3.0, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarm( N, 1.0/3.0, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dvarm( N, 1.0/3.0, 1, x1, 2 )\n","base.strided.dvarm.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarm.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarm.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n","base.strided.dvarmpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmpn( x.length, 1.0/3.0, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarmpn( N, 1.0/3.0, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dvarmpn( N, 1.0/3.0, 1, x1, 2 )\n","base.strided.dvarmpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmpn.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarmpn.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n","base.strided.dvarmtk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmtk( x.length, 1.0/3.0, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarmtk( N, 1.0/3.0, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dvarmtk( N, 1.0/3.0, 1, x1, 2 )\n","base.strided.dvarmtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmtk.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarmtk.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n","base.strided.gapx":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar alpha = 5.0;\nbase.strided.gapx( x.length, alpha, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nalpha = 5.0;\nvar stride = 2;\nbase.strided.gapx( N, alpha, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nalpha = 5.0;\nstride = 2;\nbase.strided.gapx( N, alpha, x1, stride )\nx0\n","base.strided.gapx.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar alpha = 5.0;\nbase.strided.gapx.ndarray( x.length, alpha, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nalpha = 5.0;\nvar stride = 2;\nbase.strided.gapx.ndarray( N, alpha, x, stride, 1 )\n","base.strided.gapxsum":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsum( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gapxsum( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gapxsum( N, 5.0, x1, stride )\n","base.strided.gapxsum.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gapxsum.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.gapxsumkbn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gapxsumkbn( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gapxsumkbn( 3, 5.0, x1, 2 )\n","base.strided.gapxsumkbn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gapxsumkbn2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn2( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gapxsumkbn2( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gapxsumkbn2( N, 5.0, x1, stride )\n","base.strided.gapxsumkbn2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gapxsumkbn2.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.gapxsumors":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumors( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gapxsumors( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gapxsumors( N, 5.0, x1, stride )\n","base.strided.gapxsumors.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gapxsumors.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.gapxsumpw":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumpw( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gapxsumpw( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gapxsumpw( N, 5.0, x1, stride )\n","base.strided.gapxsumpw.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.gasum":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nvar s = base.strided.gasum( x.length, x, 1 )\ns = base.strided.gasum( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\ns = base.strided.gasum( 3, x1, 2 )\n","base.strided.gasum.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nvar s = base.strided.gasum.ndarray( x.length, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\ns = base.strided.gasum.ndarray( 3, x, -1, x.length-1 )\n","base.strided.gasumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.gasumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gasumpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gasumpw( N, x1, stride )\n","base.strided.gasumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.gasumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.gasumpw.ndarray( N, x, 2, 1 )\n","base.strided.gaxpy":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\nbase.strided.gaxpy( x.length, 5.0, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\nbase.strided.gaxpy( 3, 5.0, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gaxpy( 3, 5.0, x1, -2, y1, 1 )\ny0\n","base.strided.gaxpy.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\nbase.strided.gaxpy.ndarray( x.length, 5.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gaxpy.ndarray( 3, 5.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcopy":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gcopy( x.length, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gcopy( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcopy( 3, x1, -2, y1, 1 )\ny0\n","base.strided.gcopy.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusum":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusum( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusum( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.gcusum( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusum.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusum.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumkbn":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcusumkbn( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumkbn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumkbn2":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn2( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumkbn2( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.gcusumkbn2( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumkbn2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumkbn2.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumors":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumors( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumors( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.gcusumors( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumors.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumors.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumpw":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumpw( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumpw( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.gcusumpw( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumpw.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumpw.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gdot":"var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\nvar y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\nvar out = base.strided.gdot( x.length, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\nout = base.strided.gdot( 3, x, 2, y, -1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.gdot( 3, x1, -2, y1, 1 )\n","base.strided.gdot.ndarray":"var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\nvar y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\nvar out = base.strided.gdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\nout = base.strided.gdot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nout = base.strided.gdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.gfill":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfill( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gfill( N, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gfill( N, 5.0, x1, 2 )\nx0\n","base.strided.gfill.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfill.ndarray( x.length, 5.0, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gfill.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.gfillBy":"function fill() { return 5.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfillBy( x.length, x, 1, fill )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gfillBy( N, x, 2, fill )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gfillBy( N, x1, 2, fill )\nx0\n","base.strided.gfillBy.ndarray":"function fill() { return 5.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfillBy.ndarray( x.length, x, 1, 0, fill )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gfillBy.ndarray( N, x, 2, 1, fill )\n","base.strided.gnannsumkbn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nvar out = [ 0.0, 0 ];\nbase.strided.gnannsumkbn( x.length, x, 1, out, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nout = [ 0.0, 0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnannsumkbn( N, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = [ 0.0, 0 ];\nbase.strided.gnannsumkbn( N, x1, 2, out, 1 )\n","base.strided.gnannsumkbn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nvar out = [ 0.0, 0 ];\nbase.strided.gnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nout = [ 0.0, 0 ];\nbase.strided.gnannsumkbn.ndarray( N, x, 2, 1, out, 1, 0 )\n","base.strided.gnansum":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansum( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gnansum( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gnansum( N, x1, stride )\n","base.strided.gnansum.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansum.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnansum.ndarray( N, x, 2, 1 )\n","base.strided.gnansumkbn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gnansumkbn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gnansumkbn( N, x1, stride )\n","base.strided.gnansumkbn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnansumkbn.ndarray( N, x, 2, 1 )\n","base.strided.gnansumkbn2":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gnansumkbn2( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gnansumkbn2( N, x1, stride )\n","base.strided.gnansumkbn2.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnansumkbn2.ndarray( N, x, 2, 1 )\n","base.strided.gnansumors":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gnansumors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gnansumors( N, x1, stride )\n","base.strided.gnansumors.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnansumors.ndarray( N, x, 2, 1 )\n","base.strided.gnansumpw":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumpw( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gnansumpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gnansumpw( N, x1, stride )\n","base.strided.gnansumpw.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnansumpw.ndarray( N, x, 2, 1 )\n","base.strided.gnrm2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gnrm2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gnrm2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gnrm2( 3, x1, 2 )\n","base.strided.gnrm2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gnrm2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gnrm2.ndarray( 3, x, 2, 1 )\n","base.strided.grev":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.grev( x.length, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.grev( N, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.grev( N, x1, 2 )\nx0\n","base.strided.grev.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.grev.ndarray( x.length, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.grev.ndarray( N, x, 2, 1 )\n","base.strided.gscal":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar alpha = 5.0;\nbase.strided.gscal( x.length, alpha, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gscal( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gscal( 3, 5.0, x1, 2 )\nx0\n","base.strided.gscal.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gscal.ndarray( x.length, 5.0, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.gscal.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gsort2hp":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2hp( x.length, 1, x, 1, y, 1 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2hp( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsort2hp( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.gsort2hp.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.gsort2ins":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2ins( x.length, 1, x, 1, y, 1 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2ins( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsort2ins( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.gsort2ins.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2ins.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.gsort2sh":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2sh( x.length, 1, x, 1, y, 1 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2sh( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsort2sh( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.gsort2sh.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.gsorthp":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsorthp( x.length, 1, x, 1 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsorthp( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsorthp( N, 1, x1, 2 )\nx0\n","base.strided.gsorthp.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsorthp.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsorthp.ndarray( N, 1, x, 2, 1 )\n","base.strided.gsortins":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortins( x.length, 1, x, 1 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsortins( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsortins( N, 1, x1, 2 )\nx0\n","base.strided.gsortins.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortins.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsortins.ndarray( N, 1, x, 2, 1 )\n","base.strided.gsortsh":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortsh( x.length, 1, x, 1 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsortsh( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsortsh( N, 1, x1, 2 )\nx0\n","base.strided.gsortsh.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortsh.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsortsh.ndarray( N, 1, x, 2, 1 )\n","base.strided.gsum":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsum( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gsum( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gsum( N, x1, stride )\n","base.strided.gsum.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsum.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsum.ndarray( N, x, 2, 1 )\n","base.strided.gsumkbn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gsumkbn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gsumkbn( N, x1, stride )\n","base.strided.gsumkbn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsumkbn.ndarray( N, x, 2, 1 )\n","base.strided.gsumkbn2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gsumkbn2( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gsumkbn2( N, x1, stride )\n","base.strided.gsumkbn2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsumkbn2.ndarray( N, x, 2, 1 )\n","base.strided.gsumors":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gsumors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gsumors( N, x1, stride )\n","base.strided.gsumors.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsumors.ndarray( N, x, 2, 1 )\n","base.strided.gsumpw":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumpw( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gsumpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gsumpw( N, x1, stride )\n","base.strided.gsumpw.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumpw.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsumpw.ndarray( N, x, 2, 1 )\n","base.strided.gswap":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gswap( x.length, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gswap( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gswap( 3, x1, -2, y1, 1 )\ny0\n","base.strided.gswap.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.mapBy":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.mapBy( x.length, x, 1, y, 1, base.abs, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy( 2, x, 2, y, -1, base.abs, clbk )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.mapBy( 2, x1, -2, y1, 1, base.abs, clbk )\ny0\n","base.strided.mapBy.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.mapBy.ndarray( x.length, x, 1, 0, y, 1, 0, base.abs, clbk )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.abs, clbk )\n","base.strided.mapBy2":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 1.0, 1.0, 2.0, 2.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\nbase.strided.mapBy2( x.length, x, 1, y, 1, z, 1, base.add, clbk )\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy2( 2, x, 2, y, -1, z, -1, base.add, clbk )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 1.0, 1.0, 2.0, 2.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nbase.strided.mapBy2( 2, x1, -2, y1, 1, z1, 1, base.add, clbk )\nz0\n","base.strided.mapBy2.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 1.0, 1.0, 2.0, 2.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\nbase.strided.mapBy2.ndarray( 4, x, 1, 0, y, 1, 0, z, 1, 0, base.add, clbk )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 1.0, 1.0, 2.0, 2.0 ];\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy2.ndarray( 2, x, 2, 1, y, -1, 3, z, 1, 0, base.add, clbk )\n","base.strided.max":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.max( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.max( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.max( N, x1, stride )\n","base.strided.max.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.max.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.max.ndarray( N, x, 2, 1 )\n","base.strided.maxabs":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.maxabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.maxabs( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.maxabs( N, x1, stride )\n","base.strided.maxabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.maxabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.maxabs.ndarray( N, x, 2, 1 )\n","base.strided.maxBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.maxBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.maxBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.maxBy( N, x1, 2, accessor )\n","base.strided.maxBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.maxBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.maxBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.maxsorted":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.maxsorted( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.maxsorted( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.maxsorted( N, x1, stride )\n","base.strided.maxsorted.ndarray":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.maxsorted.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.maxsorted.ndarray( N, x, 2, 1 )\n","base.strided.maxViewBufferIndex":"var idx = base.strided.maxViewBufferIndex( 3, 2, 10 )\n","base.strided.mean":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.mean( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.mean( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.mean( N, x1, stride )\n","base.strided.mean.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.mean.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mean.ndarray( N, x, 2, 1 )\n","base.strided.meankbn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meankbn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meankbn( N, x1, stride )\n","base.strided.meankbn.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meankbn.ndarray( N, x, 2, 1 )\n","base.strided.meankbn2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meankbn2( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meankbn2( N, x1, stride )\n","base.strided.meankbn2.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meankbn2.ndarray( N, x, 2, 1 )\n","base.strided.meanors":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meanors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meanors( N, x1, stride )\n","base.strided.meanors.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meanors.ndarray( N, x, 2, 1 )\n","base.strided.meanpn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanpn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meanpn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meanpn( N, x1, stride )\n","base.strided.meanpn.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanpn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meanpn.ndarray( N, x, 2, 1 )\n","base.strided.meanpw":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanpw( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meanpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meanpw( N, x1, stride )\n","base.strided.meanpw.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanpw.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meanpw.ndarray( N, x, 2, 1 )\n","base.strided.meanwd":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanwd( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meanwd( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meanwd( N, x1, stride )\n","base.strided.meanwd.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanwd.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meanwd.ndarray( N, x, 2, 1 )\n","base.strided.mediansorted":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.mediansorted( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mediansorted( N, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.mediansorted( N, x1, 2 )\n","base.strided.mediansorted.ndarray":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.mediansorted.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mediansorted.ndarray( N, x, 2, 1 )\n","base.strided.metaDataProps":"var meta = { 'nargs': 7, 'nin': 1, 'nout': 1 };\nvar dt = [ 'float64', 'float64' ];\nvar obj = {};\nbase.strided.metaDataProps( meta, dt, obj, false );\nobj.nargs\nobj.nin\nobj.nout\nobj.types\n","base.strided.min":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.min( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.min( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.min( N, x1, stride )\n","base.strided.min.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.min.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.min.ndarray( N, x, 2, 1 )\n","base.strided.minabs":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.minabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.minabs( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.minabs( N, x1, stride )\n","base.strided.minabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.minabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.minabs.ndarray( N, x, 2, 1 )\n","base.strided.minBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.minBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.minBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.minBy( N, x1, 2, accessor )\n","base.strided.minBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.minBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.minBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.minsorted":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.minsorted( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.minsorted( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.minsorted( N, x1, stride )\n","base.strided.minsorted.ndarray":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.minsorted.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.minsorted.ndarray( N, x, 2, 1 )\n","base.strided.minViewBufferIndex":"var idx = base.strided.minViewBufferIndex( 3, -2, 10 )\n","base.strided.mskmax":"var x = [ 1.0, -2.0, 4.0, 2.0 ];\nvar mask = [ 0, 0, 1, 0 ];\nbase.strided.mskmax( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskmax( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.mskmax( N, x1, 2, mask1, 2 )\n","base.strided.mskmax.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0 ];\nvar mask = [ 0, 0, 0, 1 ];\nbase.strided.mskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.mskmin":"var x = [ 1.0, -2.0, -4.0, 2.0 ];\nvar mask = [ 0, 0, 1, 0 ];\nbase.strided.mskmin( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskmin( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.mskmin( N, x1, 2, mask1, 2 )\n","base.strided.mskmin.ndarray":"var x = [ 1.0, -2.0, 2.0, -4.0 ];\nvar mask = [ 0, 0, 0, 1 ];\nbase.strided.mskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.mskrange":"var x = [ 1.0, -2.0, 4.0, 2.0 ];\nvar mask = [ 0, 0, 1, 0 ];\nbase.strided.mskrange( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskrange( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.mskrange( N, x1, 2, mask1, 2 )\n","base.strided.mskrange.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0 ];\nvar mask = [ 0, 0, 0, 1 ];\nbase.strided.mskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.mskunary":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nbase.strided.mskunary( [ x, m, y ], shape, strides, base.abs );\ny\n","base.strided.mskunary.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nvar offsets = [ 0, 0, 0 ];\nbase.strided.mskunary.ndarray( [ x, m, y ], shape, strides, offsets, base.abs );\ny\n","base.strided.mskunaryDtypeSignatures":"var dt = strided.dataTypes();\nvar out = base.strided.mskunaryDtypeSignatures( dt, dt )\n","base.strided.mskunarySignatureCallbacks":"var dt = strided.dataTypes();\nvar sigs = base.strided.mskunaryDtypeSignatures( dt, dt );\nvar t = {\n 'default': base.identity,\n 'complex64': base.cidentityf,\n 'complex128': base.cidentity\n };\nvar out = base.strided.mskunarySignatureCallbacks( t, sigs )\n","base.strided.nanmax":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmax( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmax( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmax( N, x1, stride )\n","base.strided.nanmax.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmax.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmax.ndarray( N, x, 2, 1 )\n","base.strided.nanmaxabs":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmaxabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmaxabs( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmaxabs( N, x1, stride )\n","base.strided.nanmaxabs.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmaxabs.ndarray( N, x, 2, 1 )\n","base.strided.nanmaxBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanmaxBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmaxBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanmaxBy( N, x1, 2, accessor )\n","base.strided.nanmaxBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanmaxBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmaxBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.nanmean":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmean( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmean( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmean( N, x1, stride )\n","base.strided.nanmean.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmean.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmean.ndarray( N, x, 2, 1 )\n","base.strided.nanmeanors":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmeanors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmeanors( N, x1, stride )\n","base.strided.nanmeanors.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmeanors.ndarray( N, x, 2, 1 )\n","base.strided.nanmeanpn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanpn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmeanpn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmeanpn( N, x1, stride )\n","base.strided.nanmeanpn.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.nanmeanwd":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanwd( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmeanwd( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmeanwd( N, x1, stride )\n","base.strided.nanmeanwd.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmeanwd.ndarray( N, x, 2, 1 )\n","base.strided.nanmin":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmin( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmin( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmin( N, x1, stride )\n","base.strided.nanmin.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmin.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmin.ndarray( N, x, 2, 1 )\n","base.strided.nanminabs":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanminabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanminabs( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanminabs( N, x1, stride )\n","base.strided.nanminabs.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanminabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanminabs.ndarray( N, x, 2, 1 )\n","base.strided.nanminBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanminBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, NaN, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanminBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanminBy( N, x1, 2, accessor )\n","base.strided.nanminBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanminBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanminBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.nanmskmax":"var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\nvar mask = [ 0, 0, 1, 0, 0 ];\nbase.strided.nanmskmax( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskmax( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanmskmax( N, x1, 2, mask1, 2 )\n","base.strided.nanmskmax.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\nvar mask = [ 0, 0, 0, 1, 0 ];\nbase.strided.nanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.nanmskmin":"var x = [ 1.0, -2.0, -4.0, 2.0, NaN ];\nvar mask = [ 0, 0, 1, 0, 0 ];\nbase.strided.nanmskmin( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskmin( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanmskmin( N, x1, 2, mask1, 2 )\n","base.strided.nanmskmin.ndarray":"var x = [ 1.0, -2.0, 2.0, -4.0, NaN ];\nvar mask = [ 0, 0, 0, 1, 0 ];\nbase.strided.nanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.nanmskrange":"var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\nvar mask = [ 0, 0, 1, 0, 0 ];\nbase.strided.nanmskrange( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskrange( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanmskrange( N, x1, 2, mask1, 2 )\n","base.strided.nanmskrange.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\nvar mask = [ 0, 0, 0, 1, 0 ];\nbase.strided.nanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.nanrange":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanrange( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanrange( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanrange( N, x1, stride )\n","base.strided.nanrange.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanrange.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanrange.ndarray( N, x, 2, 1 )\n","base.strided.nanrangeBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanrangeBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0, 1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanrangeBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanrangeBy( N, x1, 2, accessor )\n","base.strided.nanrangeBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanrangeBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanrangeBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.nanstdev":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdev( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdev( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdev( N, 1, x1, 2 )\n","base.strided.nanstdev.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanstdevch":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevch( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevch( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdevch( N, 1, x1, 2 )\n","base.strided.nanstdevch.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanstdevpn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevpn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevpn( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdevpn( N, 1, x1, 2 )\n","base.strided.nanstdevpn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanstdevtk":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevtk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevtk( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdevtk( N, 1, x1, 2 )\n","base.strided.nanstdevtk.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanstdevwd":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevwd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevwd( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdevwd( N, 1, x1, 2 )\n","base.strided.nanstdevwd.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanstdevyc":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevyc( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevyc( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdevyc( N, 1, x1, 2 )\n","base.strided.nanstdevyc.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvariance":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariance( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvariance( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvariance( N, 1, x1, stride )\n","base.strided.nanvariance.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvariancech":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancech( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvariancech( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvariancech( N, 1, x1, stride )\n","base.strided.nanvariancech.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvariancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvariancepn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancepn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvariancepn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvariancepn( N, 1, x1, stride )\n","base.strided.nanvariancepn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvariancetk":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancetk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvariancetk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvariancetk( N, 1, x1, stride )\n","base.strided.nanvariancetk.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvariancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvariancewd":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancewd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvariancewd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvariancewd( N, 1, x1, stride )\n","base.strided.nanvariancewd.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvariancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvarianceyc":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvarianceyc( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvarianceyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvarianceyc( N, 1, x1, stride )\n","base.strided.nanvarianceyc.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvarianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.nullary":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1 ];\nvar fcn = constantFunction( 3.0 );\nbase.strided.nullary( [ x ], shape, strides, fcn );\nx\n","base.strided.nullary.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1 ];\nvar offsets = [ 0 ];\nvar fcn = constantFunction( 3.0 );\nbase.strided.nullary.ndarray( [ x ], shape, strides, offsets, fcn );\nx\n","base.strided.offsetView":"var x = new Float64Array( 10 );\nvar out = base.strided.offsetView( x, 0 )\nvar bool = ( out.buffer === x.buffer )\n","base.strided.quaternary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1 ];\nfunction f( x, y, z, w ) { return x + y + z + w; };\nbase.strided.quaternary( [ x, y, z, w, u ], shape, strides, f );\nu\n","base.strided.quaternary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1 ];\nvar offsets = [ 0, 0, 0, 0, 0 ];\nfunction f( x, y, z, w ) { return x + y + z + w; };\nbase.strided.quaternary.ndarray( [ x, y, z, w, u ], shape, strides, offsets, f );\nu\n","base.strided.quinary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1, 1 ];\nfunction f( x, y, z, w, u ) { return x + y + z + w + u; };\nbase.strided.quinary( [ x, y, z, w, u, v ], shape, strides, f );\nv\n","base.strided.quinary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1, 1 ];\nvar offsets = [ 0, 0, 0, 0, 0, 0 ];\nfunction f( x, y, z, w, u ) { return x + y + z + w + u; };\nbase.strided.quinary.ndarray( [ x, y, z, w, u, v ], shape, strides, offsets, f );\nv\n","base.strided.range":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.range( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.range( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.range( N, x1, stride )\n","base.strided.range.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.range.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.range.ndarray( N, x, 2, 1 )\n","base.strided.rangeBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.rangeBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.rangeBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.rangeBy( N, x1, 2, accessor )\n","base.strided.rangeBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.rangeBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.rangeBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.reinterpretComplex":"var x = new Complex128Array( 10 );\nvar out = base.strided.reinterpretComplex( x, 0 )\nvar bool = ( out.buffer === x.buffer )\nx = new Complex64Array( 10 );\nout = base.strided.reinterpretComplex( x, 0 )\nbool = ( out.buffer === x.buffer )\n","base.strided.reinterpretComplex64":"var x = new Complex64Array( 10 );\nvar out = base.strided.reinterpretComplex64( x, 0 )\nvar bool = ( out.buffer === x.buffer )\n","base.strided.reinterpretComplex128":"var x = new Complex128Array( 10 );\nvar out = base.strided.reinterpretComplex128( x, 0 )\nvar bool = ( out.buffer === x.buffer )\n","base.strided.sabs":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sabs( N, x1, -2, y1, 1 )\ny0\n","base.strided.sabs.ndarray":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sabs2":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs2( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs2( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sabs2( N, x1, -2, y1, 1 )\ny0\n","base.strided.sabs2.ndarray":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sapx":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sapx( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sapx( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapx( 3, 5.0, x1, 2 )\nx0\n","base.strided.sapx.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sapx.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.sapx.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsum( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsum( 3, 5.0, x1, 2 )\n","base.strided.sapxsum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsumkbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsumkbn( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsumkbn( 3, 5.0, x1, 2 )\n","base.strided.sapxsumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsumkbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn2( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsumkbn2( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsumkbn2( 3, 5.0, x1, 2 )\n","base.strided.sapxsumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumors( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sapxsumors( N, 5.0, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sapxsumors( N, 5.0, x1, stride )\n","base.strided.sapxsumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sapxsumors.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.sapxsumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumpw( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar stride = 2;\nbase.strided.sapxsumpw( 3, 5.0, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.sapxsumpw( 3, 5.0, x1, stride )\n","base.strided.sapxsumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sasum":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.sasum( x.length, x, 1 )\ns = base.strided.sasum( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\ns = base.strided.sasum( 3, x1, 2 )\n","base.strided.sasum.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.sasum.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\ns = base.strided.sasum.ndarray( 3, x, -1, x.length-1 )\n","base.strided.sasumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sasumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sasumpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sasumpw( 3, x1, 2 )\n","base.strided.sasumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sasumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sasumpw.ndarray( 3, x, 2, 1 )\n","base.strided.saxpy":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.saxpy( x.length, alpha, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nbase.strided.saxpy( 3, alpha, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.saxpy( 3, 5.0, x1, -2, y1, 1 )\ny0\n","base.strided.saxpy.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.saxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.saxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scbrt":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.scbrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.scbrt( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.scbrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.scbrt.ndarray":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.scbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.scbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sceil":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sceil( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sceil( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sceil( N, x1, -2, y1, 1 )\ny0\n","base.strided.sceil.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scopy":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.scopy( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.scopy( 3, x, -2, y, 1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scopy( 3, x1, -2, y1, 1 )\ny0\n","base.strided.scopy.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.scopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scumax":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumax( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumax( 3, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scumax( 3, x1, 2, y1, 1 )\ny0\n","base.strided.scumax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scumaxabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumaxabs( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scumaxabs( N, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scumaxabs( N, x1, 2, y1, 1 )\ny0\n","base.strided.scumaxabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scumin":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumin( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scumin( N, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scumin( N, x1, 2, y1, 1 )\ny0\n","base.strided.scumin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scuminabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scuminabs( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scuminabs( N, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scuminabs( N, x1, 2, y1, 1 )\ny0\n","base.strided.scuminabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusum( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusum( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusum( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumkbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scusumkbn( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumkbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn2( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn2( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scusumkbn2( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumors( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumors( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusumors( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumpw( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumpw( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusumpw( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sdeg2rad":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sdeg2rad( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sdeg2rad( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sdeg2rad( N, x1, -2, y1, 1 )\ny0\n","base.strided.sdeg2rad.ndarray":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sdeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sdot":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdot( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdot( 3, x, 2, y, -1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.sdot( 3, x1, -2, y1, 1 )\n","base.strided.sdot.ndarray":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nout = base.strided.sdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.sdsapxsum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsum( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sdsapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsapxsum( 3, 5.0, x1, 2 )\n","base.strided.sdsapxsum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sdsapxsumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsumpw( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sdsapxsumpw( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsapxsumpw( 3, 5.0, x1, 2 )\n","base.strided.sdsapxsumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sdsdot":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdsdot( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdsdot( 3, 0.0, x, 2, y, -1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.sdsdot( 3, 0.0, x1, -2, y1, 1 )\n","base.strided.sdsdot.ndarray":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdsdot.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdsdot.ndarray( 3, 0.0, x, 2, 0, y, 2, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nout = base.strided.sdsdot.ndarray( 3, 0.0, x, -2, x.length-1, y, 1, 3 )\n","base.strided.sdsmean":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsmean( N, x1, stride )\n","base.strided.sdsmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsmean.ndarray( N, x, 2, 1 )\n","base.strided.sdsmeanors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsmeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsmeanors( N, x1, stride )\n","base.strided.sdsmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsmeanors.ndarray( N, x, 2, 1 )\n","base.strided.sdsnanmean":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsnanmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsnanmean( N, x1, stride )\n","base.strided.sdsnanmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsnanmean.ndarray( N, x, 2, 1 )\n","base.strided.sdsnanmeanors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsnanmeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsnanmeanors( N, x1, stride )\n","base.strided.sdsnanmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsnanmeanors.ndarray( N, x, 2, 1 )\n","base.strided.sdsnansum":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar stride = 2;\nbase.strided.sdsnansum( 4, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.sdsnansum( 4, x1, stride )\n","base.strided.sdsnansum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansum.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.sdsnansum.ndarray( 4, x, 2, 1 )\n","base.strided.sdsnansumpw":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.sdsnansumpw( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsnansumpw( 4, x1, 2 )\n","base.strided.sdsnansumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.sdsnansumpw.ndarray( 4, x, 2, 1 )\n","base.strided.sdssum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar stride = 2;\nbase.strided.sdssum( 3, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.sdssum( 3, x1, stride )\n","base.strided.sdssum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssum.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdssum.ndarray( 3, x, 2, 1 )\n","base.strided.sdssumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar stride = 2;\nbase.strided.sdssumpw( 3, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.sdssumpw( 3, x1, stride )\n","base.strided.sdssumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdssumpw.ndarray( 3, x, 2, 1 )\n","base.strided.sfill":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sfill( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sfill( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sfill( 3, 5.0, x1, 2 )\nx0\n","base.strided.sfill.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sfill.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.sfill.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sfloor":"var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sfloor( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sfloor( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sfloor( N, x1, -2, y1, 1 )\ny0\n","base.strided.sfloor.ndarray":"var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sinv":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sinv( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sinv( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sinv( N, x1, -2, y1, 1 )\ny0\n","base.strided.sinv.ndarray":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.smap":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap( x.length, x, 1, y, 1, base.identityf )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap( 2, x, 2, y, -1, base.identityf )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smap( 2, x1, -2, y1, 1, base.identityf )\ny0\n","base.strided.smap.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identityf )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identityf )\n","base.strided.smap2":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2( x.length, x, 1, y, 1, z, 1, base.addf )\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2( 2, x, 2, y, -1, z, 1, base.addf )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nbase.strided.smap2( 2, x1, -2, y1, 1, z1, 1, base.addf )\nz0\n","base.strided.smap2.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.addf )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.addf )\n","base.strided.smax":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smax( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smax( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smax( 3, x1, 2 )\n","base.strided.smax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smax.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smax.ndarray( N, x, 2, 1 )\n","base.strided.smaxabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smaxabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smaxabs( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smaxabs( 3, x1, 2 )\n","base.strided.smaxabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smaxabs.ndarray( 3, x, 2, 1 )\n","base.strided.smaxabssorted":"var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.smaxabssorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smaxabssorted( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smaxabssorted( 3, x1, 2 )\n","base.strided.smaxabssorted.ndarray":"var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.smaxabssorted.ndarray( 3, x, 2, 1 )\n","base.strided.smaxsorted":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smaxsorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smaxsorted( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smaxsorted( 3, x1, 2 )\n","base.strided.smaxsorted.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.smaxsorted.ndarray( 3, x, 2, 1 )\n","base.strided.smean":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smean( N, x1, stride )\n","base.strided.smean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smean.ndarray( N, x, 2, 1 )\n","base.strided.smeankbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeankbn( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeankbn( N, x1, stride )\n","base.strided.smeankbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeankbn.ndarray( N, x, 2, 1 )\n","base.strided.smeankbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeankbn2( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeankbn2( N, x1, stride )\n","base.strided.smeankbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeankbn2.ndarray( N, x, 2, 1 )\n","base.strided.smeanli":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanli( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanli( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanli( N, x1, stride )\n","base.strided.smeanli.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanli.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanli.ndarray( N, x, 2, 1 )\n","base.strided.smeanlipw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanlipw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanlipw( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanlipw( N, x1, stride )\n","base.strided.smeanlipw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanlipw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanlipw.ndarray( N, x, 2, 1 )\n","base.strided.smeanors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanors( N, x1, stride )\n","base.strided.smeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanors.ndarray( N, x, 2, 1 )\n","base.strided.smeanpn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanpn( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanpn( N, x1, stride )\n","base.strided.smeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanpn.ndarray( N, x, 2, 1 )\n","base.strided.smeanpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanpw( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanpw( N, x1, stride )\n","base.strided.smeanpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanpw.ndarray( N, x, 2, 1 )\n","base.strided.smeanwd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanwd( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanwd( N, x1, stride )\n","base.strided.smeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanwd.ndarray( N, x, 2, 1 )\n","base.strided.smediansorted":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smediansorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smediansorted( N, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.smediansorted( N, x1, 2 )\n","base.strided.smediansorted.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smediansorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smediansorted.ndarray( N, x, 2, 1 )\n","base.strided.smidrange":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smidrange( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smidrange( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smidrange( 3, x1, 2 )\n","base.strided.smidrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smidrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smidrange.ndarray( 3, x, 2, 1 )\n","base.strided.smin":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smin( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smin( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smin( 3, x1, 2 )\n","base.strided.smin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smin.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smin.ndarray( 3, x, 2, 1 )\n","base.strided.sminabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sminabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sminabs( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sminabs( 3, x1, 2 )\n","base.strided.sminabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sminabs.ndarray( 3, x, 2, 1 )\n","base.strided.sminsorted":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.sminsorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sminsorted( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sminsorted( N, x1, stride )\n","base.strided.sminsorted.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.sminsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sminsorted.ndarray( N, x, 2, 1 )\n","base.strided.smskabs":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskabs( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskabs.ndarray":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskabs2":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskabs2( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskabs2.ndarray":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskcbrt":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskcbrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskcbrt.ndarray":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskceil":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskceil( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskceil.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskdeg2rad":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskdeg2rad.ndarray":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskfloor":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskfloor( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskfloor.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskinv":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskinv( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskinv.ndarray":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskmap":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap( x.length, x, 1, m, 1, y, 1, base.identity )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap( 2, x, 2, m, 2, y, -1, base.identity )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\ny0\n","base.strided.smskmap.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n","base.strided.smskmap2":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.addf )\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.addf )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.addf )\nz0\n","base.strided.smskmap2.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.addf )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.addf )\n","base.strided.smskmax":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmax( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskmax( 3, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.smskmax( 3, x1, 2, mask1, 2 )\n","base.strided.smskmax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.smskmin":"var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmin( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskmin( 3, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.smskmin( 3, x1, 2, mask1, 2 )\n","base.strided.smskmin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.smskramp":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskramp( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskramp.ndarray":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskrange":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskrange( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskrange( 3, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.smskrange( 3, x1, 2, mask1, 2 )\n","base.strided.smskrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.smskrsqrt":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskrsqrt.ndarray":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smsksqrt":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smsksqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smsksqrt.ndarray":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smsktrunc":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smsktrunc( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smsktrunc.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.snanmax":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmax( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanmax( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmax( 3, x1, 2 )\n","base.strided.snanmax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanmax.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanmax.ndarray( 3, x, 2, 1 )\n","base.strided.snanmaxabs":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmaxabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanmaxabs( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmaxabs( 3, x1, 2 )\n","base.strided.snanmaxabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanmaxabs.ndarray( 3, x, 2, 1 )\n","base.strided.snanmean":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanmean( N, x1, stride )\n","base.strided.snanmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmean.ndarray( N, x, 2, 1 )\n","base.strided.snanmeanors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanmeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanmeanors( N, x1, stride )\n","base.strided.snanmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmeanors.ndarray( N, x, 2, 1 )\n","base.strided.snanmeanpn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanmeanpn( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanmeanpn( N, x1, stride )\n","base.strided.snanmeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.snanmeanwd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanmeanwd( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanmeanwd( N, x1, stride )\n","base.strided.snanmeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmeanwd.ndarray( N, x, 2, 1 )\n","base.strided.snanmin":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmin( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanmin( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmin( 3, x1, 2 )\n","base.strided.snanmin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanmin.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanmin.ndarray( 3, x, 2, 1 )\n","base.strided.snanminabs":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanminabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanminabs( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanminabs( 3, x1, 2 )\n","base.strided.snanminabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanminabs.ndarray( 3, x, 2, 1 )\n","base.strided.snanmskmax":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.snanmskmax( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskmax( N, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanmskmax( N, x1, 2, mask1, 2 )\n","base.strided.snanmskmax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.snanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.snanmskmin":"var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.snanmskmin( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskmin( N, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanmskmin( N, x1, 2, mask1, 2 )\n","base.strided.snanmskmin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.snanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.snanmskrange":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.snanmskrange( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskrange( N, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanmskrange( N, x1, 2, mask1, 2 )\n","base.strided.snanmskrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.snanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.snanrange":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanrange( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanrange( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanrange( 3, x1, 2 )\n","base.strided.snanrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanrange.ndarray( 3, x, 2, 1 )\n","base.strided.snanstdev":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdev( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdev( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdev( N, 1, x1, stride )\n","base.strided.snanstdev.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevch":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevch( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevch( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevch( N, 1, x1, stride )\n","base.strided.snanstdevch.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevpn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevpn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevpn( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevpn( N, 1, x1, stride )\n","base.strided.snanstdevpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevtk":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevtk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevtk( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevtk( N, 1, x1, stride )\n","base.strided.snanstdevtk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevwd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevwd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevwd( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevwd( N, 1, x1, stride )\n","base.strided.snanstdevwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevyc":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevyc( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevyc( N, 1, x1, stride )\n","base.strided.snanstdevyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.snansum":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.snansum( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snansum( 4, x1, 2 )\n","base.strided.snansum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansum.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansum.ndarray( 4, x, 2, 1 )\n","base.strided.snansumkbn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar stride = 2;\nbase.strided.snansumkbn( 4, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.snansumkbn( 4, x1, stride )\n","base.strided.snansumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansumkbn.ndarray( 4, x, 2, 1 )\n","base.strided.snansumkbn2":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar stride = 2;\nbase.strided.snansumkbn2( 4, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.snansumkbn2( 4, x1, stride )\n","base.strided.snansumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansumkbn2.ndarray( 4, x, 2, 1 )\n","base.strided.snansumors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar stride = 2;\nbase.strided.snansumors( 4, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.snansumors( 4, x1, stride )\n","base.strided.snansumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansumors.ndarray( 4, x, 2, 1 )\n","base.strided.snansumpw":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.snansumpw( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snansumpw( 4, x1, 2 )\n","base.strided.snansumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansumpw.ndarray( 4, x, 2, 1 )\n","base.strided.snanvariance":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariance( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariance( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariance( N, 1, x1, 2 )\n","base.strided.snanvariance.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancech":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancech( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancech( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancech( N, 1, x1, 2 )\n","base.strided.snanvariancech.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancepn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancepn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancepn( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancepn( N, 1, x1, 2 )\n","base.strided.snanvariancepn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancetk":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancetk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancetk( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancetk( N, 1, x1, 2 )\n","base.strided.snanvariancetk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancewd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancewd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancewd( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancewd( N, 1, x1, 2 )\n","base.strided.snanvariancewd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvarianceyc":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvarianceyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvarianceyc( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvarianceyc( N, 1, x1, 2 )\n","base.strided.snanvarianceyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvarianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.snrm2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.snrm2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.snrm2( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snrm2( 3, x1, 2 )\n","base.strided.snrm2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.snrm2.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.snrm2.ndarray( 3, x, 2, 1 )\n","base.strided.sramp":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sramp( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sramp( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sramp( N, x1, -2, y1, 1 )\ny0\n","base.strided.sramp.ndarray":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.srange":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.srange( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.srange( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.srange( 3, x1, 2 )\n","base.strided.srange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.srange.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.srange.ndarray( 3, x, 2, 1 )\n","base.strided.srev":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.srev( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.srev( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.srev( 3, x1, 2 )\nx0\n","base.strided.srev.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.srev.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.srev.ndarray( 3, x, 2, 1 )\n","base.strided.srsqrt":"var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.srsqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.srsqrt( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.srsqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.srsqrt.ndarray":"var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.srsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.srsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sscal":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sscal( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sscal( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sscal( 3, 5.0, x1, 2 )\nx0\n","base.strided.sscal.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sscal.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.sscal.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.ssort2hp":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2hp( x.length, 1, x, 1, y, 1 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2hp( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssort2hp( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.ssort2hp.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2hp.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.ssort2ins":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2ins( x.length, 1, x, 1, y, 1 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2ins( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssort2ins( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.ssort2ins.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.ssort2sh":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2sh( x.length, 1, x, 1, y, 1 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2sh( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssort2sh( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.ssort2sh.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2sh.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.ssorthp":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssorthp( x.length, 1, x, 1 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssorthp( 2, -1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssorthp( 2, 1, x1, 2 )\nx0\n","base.strided.ssorthp.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssorthp.ndarray( x.length, 1, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssorthp.ndarray( 2, 1, x, 2, 1 )\n","base.strided.ssortins":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortins( x.length, 1, x, 1 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortins( 2, -1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssortins( 2, 1, x1, 2 )\nx0\n","base.strided.ssortins.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortins.ndarray( x.length, 1, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortins.ndarray( 2, 1, x, 2, 1 )\n","base.strided.ssortsh":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortsh( x.length, 1, x, 1 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortsh( 2, -1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssortsh( 2, 1, x1, 2 )\nx0\n","base.strided.ssortsh.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortsh.ndarray( x.length, 1, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortsh.ndarray( 2, 1, x, 2, 1 )\n","base.strided.ssqrt":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ssqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ssqrt( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.ssqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.ssqrt.ndarray":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ssqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ssqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sstdev":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdev( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdev( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdev( N, 1, x1, stride )\n","base.strided.sstdev.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.sstdevch":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevch( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdevch( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdevch( N, 1, x1, stride )\n","base.strided.sstdevch.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.sstdevpn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevpn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdevpn( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdevpn( N, 1, x1, stride )\n","base.strided.sstdevpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.sstdevtk":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevtk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdevtk( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdevtk( N, 1, x1, stride )\n","base.strided.sstdevtk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.sstdevwd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevwd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdevwd( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdevwd( N, 1, x1, stride )\n","base.strided.sstdevwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.sstdevyc":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdevyc( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdevyc( N, 1, x1, stride )\n","base.strided.sstdevyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.ssum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssum( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssum( 3, x1, 2 )\n","base.strided.ssum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssum.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssum.ndarray( 3, x, 2, 1 )\n","base.strided.ssumkbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumkbn( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumkbn( 3, x1, 2 )\n","base.strided.ssumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumkbn.ndarray( 3, x, 2, 1 )\n","base.strided.ssumkbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumkbn2( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumkbn2( 3, x1, 2 )\n","base.strided.ssumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn2.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumkbn2.ndarray( 3, x, 2, 1 )\n","base.strided.ssumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumors( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumors( 3, x1, 2 )\n","base.strided.ssumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumors.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumors.ndarray( 3, x, 2, 1 )\n","base.strided.ssumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumpw( 3, x1, 2 )\n","base.strided.ssumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumpw.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumpw.ndarray( 3, x, 2, 1 )\n","base.strided.sswap":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.sswap( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.sswap( 3, x, -2, y, 1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.sswap( 3, x1, -2, y1, 1 )\ny0\n","base.strided.sswap.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.sswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.sswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.stdev":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdev( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdev( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdev( N, 1, x1, stride )\n","base.strided.stdev.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.stdevch":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevch( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdevch( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdevch( N, 1, x1, stride )\n","base.strided.stdevch.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.stdevpn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevpn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdevpn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdevpn( N, 1, x1, stride )\n","base.strided.stdevpn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.stdevtk":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevtk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdevtk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdevtk( N, 1, x1, stride )\n","base.strided.stdevtk.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.stdevwd":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevwd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdevwd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdevwd( N, 1, x1, stride )\n","base.strided.stdevwd.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.stdevyc":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevyc( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdevyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdevyc( N, 1, x1, stride )\n","base.strided.stdevyc.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.strunc":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.strunc( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.strunc( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.strunc( N, x1, -2, y1, 1 )\ny0\n","base.strided.strunc.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.strunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.strunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.svariance":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariance( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svariance( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svariance( N, 1, x1, stride )\n","base.strided.svariance.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.svariancech":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancech( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svariancech( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svariancech( N, 1, x1, stride )\n","base.strided.svariancech.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svariancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.svariancepn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancepn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svariancepn( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svariancepn( N, 1, x1, stride )\n","base.strided.svariancepn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.svariancetk":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancetk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svariancetk( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svariancetk( N, 1, x1, stride )\n","base.strided.svariancetk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svariancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.svariancewd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancewd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svariancewd( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svariancewd( N, 1, x1, stride )\n","base.strided.svariancewd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svariancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.svarianceyc":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svarianceyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svarianceyc( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svarianceyc( N, 1, x1, stride )\n","base.strided.svarianceyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svarianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.ternary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1 ];\nfunction f( x, y, z ) { return x + y + z; };\nbase.strided.ternary( [ x, y, z, w ], shape, strides, f );\nw\n","base.strided.ternary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1 ];\nvar offsets = [ 0, 0, 0, 0 ];\nfunction f( x, y, z ) { return x + y + z; };\nbase.strided.ternary.ndarray( [ x, y, z, w ], shape, strides, offsets, f );\nw\n","base.strided.unary":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1 ];\nbase.strided.unary( [ x, y ], shape, strides, base.abs );\ny\n","base.strided.unary.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1 ];\nvar offsets = [ 0, 0 ];\nbase.strided.unary.ndarray( [ x, y ], shape, strides, offsets, base.abs );\ny\n","base.strided.unaryBy":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nvar sh = [ x.length ];\nvar st = [ 1, 1 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\ny\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nsh = [ 2 ];\nst = [ 2, -1 ];\nbase.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nsh = [ 2 ];\nst = [ -2, 1 ];\nbase.strided.unaryBy( [ x1, y1 ], sh, st, base.abs, clbk );\ny1\ny0\n","base.strided.unaryBy.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nvar sh = [ x.length ];\nvar st = [ 1, 1 ];\nvar o = [ 0, 0 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nsh = [ 2 ];\nst = [ 2, -1 ];\no = [ 1, y.length-1 ];\nbase.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\ny\n","base.strided.unaryDtypeSignatures":"var dt = strided.dataTypes();\nvar out = base.strided.unaryDtypeSignatures( dt, dt )\n","base.strided.unarySignatureCallbacks":"var dt = strided.dataTypes();\nvar sigs = base.strided.unaryDtypeSignatures( dt, dt );\nvar t = {\n 'default': base.identity,\n 'complex64': base.cidentityf,\n 'complex128': base.cidentity\n };\nvar out = base.strided.unarySignatureCallbacks( t, sigs )\n","base.strided.variance":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variance( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.variance( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.variance( N, 1, x1, stride )\n","base.strided.variance.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variance.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.variance.ndarray( N, 1, x, 2, 1 )\n","base.strided.variancech":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancech( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.variancech( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.variancech( N, 1, x1, stride )\n","base.strided.variancech.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.variancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.variancepn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancepn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.variancepn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.variancepn( N, 1, x1, stride )\n","base.strided.variancepn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.variancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.variancetk":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancetk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.variancetk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.variancetk( N, 1, x1, stride )\n","base.strided.variancetk.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.variancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.variancewd":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancewd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.variancewd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.variancewd( N, 1, x1, stride )\n","base.strided.variancewd.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.variancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.varianceyc":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.varianceyc( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.varianceyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.varianceyc( N, 1, x1, stride )\n","base.strided.varianceyc.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.varianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.varianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.zmap":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex128Array( xbuf );\nvar y = new Complex128Array( x.length );\nbase.strided.zmap( x.length, x, 1, y, 1, base.cidentity );\nvar v = y.get( 0 )\nvar re = real( v )\nvar im = imag( v )\ny = new Complex128Array( x.length );\nbase.strided.zmap( 2, x, 2, y, -1, base.cidentity );\nv = y.get( 0 )\nre = real( v )\nim = imag( v )\nvar x0 = new Complex128Array( xbuf );\nvar y0 = new Complex128Array( x0.length );\nvar x1 = new Complex128Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex128Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.zmap( 2, x1, -2, y1, 1, base.cidentity );\nv = y1.get( 0 )\nre = real( v )\nim = imag( v )\n","base.strided.zmap.ndarray":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex128Array( xbuf );\nvar y = new Complex128Array( x.length );\nbase.strided.zmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentity );\nvar v = y.get( 0 )\nvar re = real( v )\nvar im = imag( v )\nx = new Complex128Array( xbuf );\ny = new Complex128Array( x.length );\nbase.strided.zmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentity );\nv = y.get( y.length-1 )\nre = real( v )\nim = imag( v )\n","base.str2multislice":"var s = new base.str2multislice( 'MultiSlice(null,null,null)' );\ns.data\ns = new base.str2multislice( 'MultiSlice(10,Slice(0,10,1),null)' );\ns.data\n","base.str2slice":"var s = new base.str2slice( 'Slice(1,10,1)' );\ns.start\ns.stop\ns.step\ns = new base.str2slice( 'Slice(2,5,2)' );\ns.start\ns.stop\ns.step\n","base.sub":"var v = base.sub( -1.0, 5.0 )\nv = base.sub( 2.0, 5.0 )\nv = base.sub( 0.0, 5.0 )\nv = base.sub( -0.0, 0.0 )\nv = base.sub( NaN, NaN )\n","base.subf":"var v = base.subf( -1.0, 5.0 )\nv = base.subf( 2.0, 5.0 )\nv = base.subf( 0.0, 5.0 )\nv = base.subf( -0.0, 0.0 )\nv = base.subf( NaN, NaN )\n","base.sumSeries":"function* geometricSeriesGenerator( x ) {\n var exponent = 0;\n while ( true ) {\n     yield Math.pow( x, exponent );\n     exponent += 1;\n }\n };\nvar gen = geometricSeriesGenerator( 0.9 );\nvar out = base.sumSeries( gen )\nfunction geometricSeriesClosure( x ) {\n var exponent = -1;\n return function() {\n     exponent += 1;\n     return Math.pow( x, exponent );\n };\n };\ngen = geometricSeriesClosure( 0.9 );\nout = base.sumSeries( gen )\nout = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'initialValue': 1 } )\nout = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'maxTerms': 10 } )\nout = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'tolerance': 1e-3 } )\n","base.tan":"var y = base.tan( 0.0 )\ny = base.tan( -PI/4.0 )\ny = base.tan( PI/4.0 )\ny = base.tan( NaN )\n","base.tand":"var y = base.tand( 0.0 )\ny = base.tand( 90.0 )\ny = base.tand( 60.0 )\ny = base.tand( NaN )\n","base.tanh":"var y = base.tanh( 0.0 )\nvar y = base.tanh( -0.0 )\ny = base.tanh( 2.0 )\ny = base.tanh( -2.0 )\ny = base.tanh( NaN )\n","base.toBinaryString":"var str = base.toBinaryString( 4.0 )\nstr = base.toBinaryString( PI )\nstr = base.toBinaryString( -1.0e308 )\nstr = base.toBinaryString( -3.14e-320 )\nstr = base.toBinaryString( 5.0e-324 )\nstr = base.toBinaryString( 0.0 )\nstr = base.toBinaryString( -0.0 )\nstr = base.toBinaryString( NaN )\nstr = base.toBinaryString( PINF )\nstr = base.toBinaryString( NINF )\n","base.toBinaryStringf":"var str = base.toBinaryStringf( base.float64ToFloat32( 4.0 ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( PI ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( -1.0e38 ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( -3.14e-39 ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( 1.4e-45 ) )\nstr = base.toBinaryStringf( 0.0 )\nstr = base.toBinaryStringf( -0.0 )\nstr = base.toBinaryStringf( NaN )\nstr = base.toBinaryStringf( FLOAT32_PINF )\nstr = base.toBinaryStringf( FLOAT32_NINF )\n","base.toBinaryStringUint8":"var a = new Uint8Array( [ 1, 4, 9 ] );\nvar str = base.toBinaryStringUint8( a[ 0 ] )\nstr = base.toBinaryStringUint8( a[ 1 ] )\nstr = base.toBinaryStringUint8( a[ 2 ] )\n","base.toBinaryStringUint16":"var a = new Uint16Array( [ 1, 4, 9 ] );\nvar str = base.toBinaryStringUint16( a[ 0 ] )\nstr = base.toBinaryStringUint16( a[ 1 ] )\nstr = base.toBinaryStringUint16( a[ 2 ] )\n","base.toBinaryStringUint32":"var a = new Uint32Array( [ 1, 4, 9 ] );\nvar str = base.toBinaryStringUint32( a[ 0 ] )\nstr = base.toBinaryStringUint32( a[ 1 ] )\nstr = base.toBinaryStringUint32( a[ 2 ] )\n","base.toWordf":"var f32 = base.float64ToFloat32( 1.337 )\nvar w = base.toWordf( f32 )\n","base.toWords":"var w = base.toWords( 3.14e201 )\n","base.toWords.assign":"var out = new Uint32Array( 2 );\nvar w = base.toWords.assign( 3.14e201, out, 1, 0 )\nvar bool = ( w === out )\n","base.transpose":"var x = array( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\nvar sh = x.shape\nvar y = base.transpose( x )\nsh = y.shape\nvar bool = ( x.data === y.data )\nbool = ( x.get( 0, 1 ) === y.get( 1, 0 ) )\n","base.tribonacci":"var y = base.tribonacci( 0 )\ny = base.tribonacci( 1 )\ny = base.tribonacci( 2 )\ny = base.tribonacci( 3 )\ny = base.tribonacci( 4 )\ny = base.tribonacci( 64 )\ny = base.tribonacci( NaN )\n","base.trigamma":"var y = base.trigamma( -2.5 )\ny = base.trigamma( 1.0 )\ny = base.trigamma( 10.0 )\ny = base.trigamma( NaN )\ny = base.trigamma( -1.0 )\n","base.trim":"var out = base.trim( ' \\t\\t\\n  Beep \\r\\n\\t  ' )\n","base.trunc":"var y = base.trunc( 3.14 )\ny = base.trunc( -4.2 )\ny = base.trunc( -4.6 )\ny = base.trunc( 9.5 )\ny = base.trunc( -0.0 )\n","base.trunc2":"var y = base.trunc2( 3.14 )\ny = base.trunc2( -4.2 )\ny = base.trunc2( -4.6 )\ny = base.trunc2( 9.5 )\ny = base.trunc2( 13.0 )\ny = base.trunc2( -13.0 )\ny = base.trunc2( -0.0 )\n","base.trunc10":"var y = base.trunc10( 3.14 )\ny = base.trunc10( -4.2 )\ny = base.trunc10( -4.6 )\ny = base.trunc10( 9.5 )\ny = base.trunc10( 13.0 )\ny = base.trunc10( -13.0 )\ny = base.trunc10( -0.0 )\n","base.truncateMiddle":"var str = 'beep boop';\nvar out = base.truncateMiddle( str, 5, '...' )\nout = base.truncateMiddle( str, 5, '|' )\n","base.truncb":"var y = base.truncb( 3.14159, -4, 10 )\ny = base.truncb( 3.14159, 0, 2 )\ny = base.truncb( 5.0, 1, 2 )\n","base.truncf":"var y = base.truncf( 3.14 )\ny = base.truncf( -4.2 )\ny = base.truncf( -4.6 )\ny = base.truncf( 9.5 )\ny = base.truncf( -0.0 )\n","base.truncn":"var y = base.truncn( 3.14159, -4 )\ny = base.truncn( 3.14159, 0 )\ny = base.truncn( 12368.0, 3 )\n","base.truncsd":"var y = base.truncsd( 3.14159, 5, 10 )\ny = base.truncsd( 3.14159, 1, 10 )\ny = base.truncsd( 12368.0, 2, 10 )\ny = base.truncsd( 0.0313, 2, 2 )\n","base.uint32ToInt32":"var y = base.uint32ToInt32( base.float64ToUint32( 4294967295 ) )\ny = base.uint32ToInt32( base.float64ToUint32( 3 ) )\n","base.umul":"var v = base.umul( 10>>>0, 4>>>0 )\n","base.umuldw":"var v = base.umuldw( 1, 10 )\n","base.umuldw.assign":"var out = [ 0, 0 ];\nvar v = base.umuldw.assign( 1, 10, out, 1, 0 )\nvar bool = ( v === out )\n","base.uncapitalize":"var out = base.uncapitalize( 'Beep' )\nout = base.uncapitalize( 'bOOp' )\n","base.uppercase":"var out = base.uppercase( 'bEEp' )\n","base.vercos":"var y = base.vercos( 3.14 )\ny = base.vercos( -4.2 )\ny = base.vercos( -4.6 )\ny = base.vercos( 9.5 )\ny = base.vercos( -0.0 )\n","base.versin":"var y = base.versin( 3.14 )\ny = base.versin( -4.2 )\ny = base.versin( -4.6 )\ny = base.versin( 9.5 )\ny = base.versin( -0.0 )\n","base.wrap":"var y = base.wrap( 3.14, 0.0, 5.0 )\ny = base.wrap( -3.14, 0.0, 5.0 )\ny = base.wrap( 3.14, 0.0, 3.0 )\ny = base.wrap( -0.0, 0.0, 5.0 )\ny = base.wrap( 0.0, -3.14, -0.0 )\ny = base.wrap( NaN, 0.0, 5.0 )\n","base.xlog1py":"var out = base.xlog1py( 3.0, 2.0 )\nout = base.xlog1py( 1.5, 5.9 )\nout = base.xlog1py( 0.9, 1.0 )\nout = base.xlog1py( 1.0, 0.0 )\nout = base.xlog1py( 0.0, -2.0 )\nout = base.xlog1py( 1.5, NaN )\nout = base.xlog1py( 0.0, NaN )\nout = base.xlog1py( NaN, 2.3 )\n","base.xlogy":"var out = base.xlogy( 3.0, 2.0 )\nout = base.xlogy( 1.5, 5.9 )\nout = base.xlogy( 0.9, 1.0 )\nout = base.xlogy( 0.0, -2.0 )\nout = base.xlogy( 1.5, NaN )\nout = base.xlogy( 0.0, NaN )\nout = base.xlogy( NaN, 2.3 )\n","base.zeta":"var y = base.zeta( 1.1 )\ny = base.zeta( -4.0 )\ny = base.zeta( 70.0 )\ny = base.zeta( 0.5 )\ny = base.zeta( NaN )\ny = base.zeta( 1.0 )\n","BERNDT_CPS_WAGES_1985":"var data = BERNDT_CPS_WAGES_1985()\n","bifurcate":"var collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar f = [ true, true, false, true ];\nvar out = bifurcate( collection, f )\nf = [ 1, 1, 0, 1 ];\nout = bifurcate( collection, f )\nf = [ true, true, false, true ];\nvar opts = { 'returns': 'indices' };\nout = bifurcate( collection, opts, f )\nopts = { 'returns': '*' };\nout = bifurcate( collection, opts, f )\n","bifurcateBy":"function predicate( v ) { return v[ 0 ] === 'b'; };\nvar collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar out = bifurcateBy( collection, predicate )\nvar opts = { 'returns': 'indices' };\nout = bifurcateBy( collection, opts, predicate )\nopts = { 'returns': '*' };\nout = bifurcateBy( collection, opts, predicate )\n","bifurcateByAsync":"function predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nbifurcateByAsync( arr, predicate, done )\nvar opts = { 'returns': 'indices' };\nbifurcateByAsync( arr, opts, predicate, done )\nopts = { 'returns': '*' };\nbifurcateByAsync( arr, opts, predicate, done )\nfunction predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nbifurcateByAsync( arr, opts, predicate, done )\nfunction predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nbifurcateByAsync( arr, opts, predicate, done )\n","bifurcateByAsync.factory":"function predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) );\n }\n };\nvar opts = { 'series': true };\nvar f = bifurcateByAsync.factory( opts, predicate );\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","bifurcateIn":"function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\nFoo.prototype = Object.create( null );\nFoo.prototype.c = 'foo';\nFoo.prototype.d = 'bar';\nvar obj = new Foo();\nfunction predicate( v ) { return v[ 0 ] === 'b'; };\nvar out = bifurcateIn( obj, predicate )\nvar opts = { 'returns': 'keys' };\nout = bifurcateIn( obj, opts, predicate )\nopts = { 'returns': '*' };\nout = bifurcateIn( obj, opts, predicate )\n","bifurcateOwn":"function predicate( v ) { return v[ 0 ] === 'b'; };\nvar obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\nvar out = bifurcateOwn( obj, predicate )\nvar opts = { 'returns': 'keys' };\nout = bifurcateOwn( obj, opts, predicate )\nopts = { 'returns': '*' };\nout = bifurcateOwn( obj, opts, predicate )\n","BigInt":"var v = ( BigInt ) ? BigInt( '1' ) : null\n","binomialTest":"var out = binomialTest( 682, 925 )\nout = binomialTest( [ 682, 925 - 682 ] )\nout = binomialTest( 21, 40, {\n 'p': 0.4,\n 'alternative': 'greater'\n })\n","Boolean":"var b = new Boolean( null )\nb = Boolean( null )\nb = Boolean( [] )\n","Boolean.prototype.toString":"var b = new Boolean( true )\nb.toString()\n","Boolean.prototype.valueOf":"var b = new Boolean( true )\nb.valueOf()\n","BooleanArray":"var arr = new BooleanArray()\nvar arr = new BooleanArray( 10 )\nvar len = arr.length\nvar arr1 = new BooleanArray( [ true, false, false, true ] )\nvar arr2 = new BooleanArray( arr1 )\nvar len = arr2.length\nvar buf = new Uint8Array( [ 1, 0, 0, 1 ] )\nvar arr = new BooleanArray( buf )\nvar len = arr.length\nvar arr1 = new BooleanArray( [ true, false, false, true ] )\nvar len = arr1.length\nvar arr2 = new BooleanArray( [ {}, null, '', 4 ] );\nlen = arr2.length\nvar buf = new ArrayBuffer( 240 );\nvar arr1 = new BooleanArray( buf )\nvar len = arr1.length\nvar arr2 = new BooleanArray( buf, 8 )\nlen = arr2.length\nvar arr3 = new BooleanArray( buf, 8, 20 )\nlen = arr3.length\n","BooleanArray.from":"function map( v ) { return !v };\nvar src = [ true, false ];\nvar arr = BooleanArray.from( src, map )\nvar len = arr.length\nvar v = arr.get( 0 )\nv = arr.get( 1 )\n","BooleanArray.of":"var arr = BooleanArray.of( true, false, false, true )\nvar len = arr.length\n","BooleanArray.BYTES_PER_ELEMENT":"var nbytes = BooleanArray.BYTES_PER_ELEMENT\n","BooleanArray.name":"var str = BooleanArray.name\n","BooleanArray.prototype.buffer":"var arr = new BooleanArray( 2 )\nvar buf = arr.buffer\n","BooleanArray.prototype.byteLength":"var arr = new BooleanArray( 10 )\nvar nbytes = arr.byteLength\n","BooleanArray.prototype.byteOffset":"var arr = new BooleanArray( 10 )\nvar offset = arr.byteOffset\nvar buf = new ArrayBuffer( 240 );\narr = new BooleanArray( buf, 64 )\noffset = arr.byteOffset\n","BooleanArray.prototype.BYTES_PER_ELEMENT":"var arr = new BooleanArray( 10 )\narr.BYTES_PER_ELEMENT\n","BooleanArray.prototype.length":"var arr = new BooleanArray( 10 )\nvar len = arr.length\n","BooleanArray.prototype.at":"var arr = new BooleanArray( [ true, false, false, true ] )\nvar v = arr.at( 1 )\nv = arr.at( -1 )\n","BooleanArray.prototype.copyWithin":"var arr = new BooleanArray( [ true, false, false, true ] )\narr.copyWithin( 0, 2 )\nvar v = arr.get( 0 )\nv = arr.get( 1 )\n","BooleanArray.prototype.entries":"var arr = new BooleanArray( [ true, false, true ] )\nvar it = arr.entries();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","BooleanArray.prototype.every":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, true, true ] )\nvar bool = arr.every( predicate )\n","BooleanArray.prototype.fill":"var arr = new BooleanArray( 3 )\narr.fill( true );\nvar v = arr.get( 0 )\nv = arr.get( 1 )\nv = arr.get( 2 )\n","BooleanArray.prototype.filter":"function predicate( v ) { return ( v === true ); };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.filter( predicate )\nvar len = out.length\nvar v = out.get( 0 )\nv = out.get( 1 )\n","BooleanArray.prototype.find":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar v = arr.find( predicate )\n","BooleanArray.prototype.findIndex":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar idx = arr.findIndex( predicate )\n","BooleanArray.prototype.findLast":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar v = arr.findLast( predicate )\n","BooleanArray.prototype.findLastIndex":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar idx = arr.findLastIndex( predicate )\n","BooleanArray.prototype.forEach":"var str = '%';\nfunction clbk( v ) { str += v.toString() + '%'; };\nvar arr = new BooleanArray( [ true, false, false, true ] )\narr.forEach( clbk );\nstr\n","BooleanArray.prototype.get":"var arr = new BooleanArray( 10 )\narr.set( true, 0 );\nvar v = arr.get( 0 )\n","BooleanArray.prototype.includes":"var arr = new BooleanArray( [ true, false, true, true, true ] )\nvar bool = arr.includes( true )\nbool = arr.includes( false, 3 )\n","BooleanArray.prototype.indexOf":"var arr = new BooleanArray( [ true, false, true, true, true ] )\nvar idx = arr.indexOf( true )\nidx = arr.indexOf( false, 3 )\n","BooleanArray.prototype.join":"var arr = new BooleanArray( [ true, false, true ] )\nvar str = arr.join()\nstr = arr.join( '|' )\n","BooleanArray.prototype.keys":"var arr = new BooleanArray( [ true, false ] )\nvar it = arr.keys();\nvar v = it.next().value\nv = it.next().value\nv = it.next().done\n","BooleanArray.prototype.lastIndexOf":"var arr = new BooleanArray( [ true, true, true, false, true ] )\nvar idx = arr.lastIndexOf( false )\nidx = arr.lastIndexOf( false, 2 )\n","BooleanArray.prototype.map":"function invert( v ) { return !v; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.map( invert )\nvar v = out.get( 0 )\nv = out.get( 1 )\nv = out.get( 2 )\n","BooleanArray.prototype.reduce":"function reducer( acc, v ) { return ( acc && v ); };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.reduce( reducer )\n","BooleanArray.prototype.reduceRight":"function reducer( acc, v ) { return ( acc && v ); };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.reduceRight( reducer )\n","BooleanArray.prototype.reverse":"var arr = new BooleanArray( [ true, false, false ] )\narr.reverse();\nvar v = arr.get( 0 )\nv = arr.get( 1 )\nv = arr.get( 2 )\n","BooleanArray.prototype.set":"var arr = new BooleanArray( 2 )\narr.set( false );\nvar v = arr.get( 0 )\narr.set( true, 1 );\nv = arr.get( 1 )\n","BooleanArray.prototype.slice":"var arr = new BooleanArray( [ true, false, true, false, true ] )\nvar out = arr.slice( 1 )\nvar len = out.length\nvar v = out.get( 0 )\nv = out.get( 1 )\n","BooleanArray.prototype.some":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ false, true, false ] )\nvar bool = arr.some( predicate )\n","BooleanArray.prototype.sort":"function compare( a, b ) { return a === true ? -1 : 1; };\nvar arr = new BooleanArray( [ true, false, true ] )\narr.sort( compare );\nvar v = arr.get( 0 )\nv = arr.get( 1 )\nv = arr.get( 2 )\n","BooleanArray.prototype.subarray":"var arr = new BooleanArray( [ true, false, true, false, true ] )\nvar out = arr.subarray( 1, 3 )\nvar len = out.length\nvar v = out.get( 0 )\nv = out.get( 1 )\n","BooleanArray.prototype.toLocaleString":"var arr = new BooleanArray( [ true, false, true ] )\nvar str = arr.toLocaleString()\n","BooleanArray.prototype.toReversed":"var arr = new BooleanArray( [ true, false, false ] )\nvar out = arr.toReversed()\nvar v = out.get( 0 )\nv = out.get( 1 )\nv = out.get( 2 )\n","BooleanArray.prototype.toSorted":"function compare( a, b ) { return a === true ? -1 : 1; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.toSorted( compare );\nvar v = out.get( 0 )\nv = out.get( 1 )\nv = out.get( 2 )\n","BooleanArray.prototype.toString":"var arr = new BooleanArray( [ true, false, true ] )\nvar str = arr.toString()\n","BooleanArray.prototype.values":"var arr = new BooleanArray( [ true, false ] )\nvar it = arr.values();\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","BooleanArray.prototype.with":"var arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.with( 0, false )\nvar v = out.get( 0 )\n","broadcastArray":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = broadcastArray( x, [ 3, 2, 2 ] )\nsh = y.shape\nvar v = y.get( 0, 0, 0 )\nv = y.get( 0, 0, 1 )\nv = y.get( 0, 1, 0 )\nv = y.get( 0, 1, 1 )\nv = y.get( 1, 0, 0 )\nv = y.get( 1, 1, 0 )\nv = y.get( 2, 0, 0 )\nv = y.get( 2, 1, 1 )\n","broadcastArrays":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = ndzeros( [ 3, 2, 2 ] )\nvar out = broadcastArrays( [ x, y ] )\nvar bx = out[ 0 ]\nsh = bx.shape\nvar v = bx.get( 0, 0, 0 )\nv = bx.get( 0, 0, 1 )\nv = bx.get( 0, 1, 0 )\nv = bx.get( 0, 1, 1 )\nv = bx.get( 1, 0, 0 )\nv = bx.get( 1, 1, 0 )\nv = bx.get( 2, 0, 0 )\nv = bx.get( 2, 1, 1 )\n","Buffer":"var b = new Buffer( 4 )\nvar b1 = new Buffer( [ 1, 2, 3, 4 ] );\nvar b2 = new Buffer( b1 )\nvar b = new Buffer( [ 1, 2, 3, 4 ] )\nvar b = new Buffer( 'beep boop' )\n","buffer2json":"var buf = new allocUnsafe( 2 );\nbuf[ 0 ] = 1;\nbuf[ 1 ] = 2;\nvar json = buffer2json( buf )\n","BYTE_ORDER":"BYTE_ORDER\n","camelcase":"var out = camelcase( 'Hello World!' )\nout = camelcase( 'beep boop' )\n","capitalize":"var out = capitalize( 'beep' )\nout = capitalize( 'Boop' )\n","capitalizeKeys":"var obj = { 'aa': 1, 'bb': 2 };\nvar out = capitalizeKeys( obj )\n","CATALAN":"CATALAN\n","CBRT_EPS":"CBRT_EPS\n","CDC_NCHS_US_BIRTHS_1969_1988":"var data = CDC_NCHS_US_BIRTHS_1969_1988()\n","CDC_NCHS_US_BIRTHS_1994_2003":"var data = CDC_NCHS_US_BIRTHS_1994_2003()\n","CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013":"var data = CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n","chdir":"var err = chdir( '/path/to/current/working/directory' )\n","chi2gof":"var x = [ 89, 37, 30, 28, 2 ];\nvar p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\nvar out = chi2gof( x, p );\nvar o = out.toJSON()\nout.toString()\nvar opts = { 'alpha': 0.01 };\nout = chi2gof( x, p, opts );\nout.toString()\nx = [ 89, 37, 30, 28, 2 ];\np = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\nopts = { 'simulate': true, 'iterations': 1000 };\nout = chi2gof( x, p, opts );\nout.toString()\nvar lambda = 3.0;\nvar rpois = base.random.poisson.factory( lambda );\nvar len = 400;\nx = [];\nfor ( var i = 0; i < len; i++ ) { x.push( rpois() ); };\nvar freqs = new Int32Array( len );\nfor ( i = 0; i < len; i++ ) { freqs[ x[ i ] ] += 1; };\nout = chi2gof( freqs, 'poisson', lambda );\nout.toString()\n","chi2test":"var x = [ [ 20, 30 ], [ 30, 20 ] ];\nvar out = chi2test( x );\nvar o = out.toJSON()\nout.toString()\nvar opts = { 'alpha': 0.1 };\nout = chi2test( x, opts );\no = out.toJSON()\nout.toString()\nopts = { 'correct': false };\nout = chi2test( x, opts );\nout.toString()\n","circarray2iterator":"var it = circarray2iterator( [ 1, 2, 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","circularArrayStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 15 };\nvar s = circularArrayStream( [ 1, 2, 3 ], opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","circularArrayStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = circularArrayStream.factory( opts );\n","circularArrayStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 15 };\nvar s = circularArrayStream.objectMode( [ 1, 2, 3 ], opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","CircularBuffer":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.length\nb.count\nb.push( 'boop' )\n","CircularBuffer.prototype.clear":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.count\nb.clear();\nb.count\n","CircularBuffer.prototype.count":"var b = CircularBuffer( 3 );\nb.count\nb.push( 'foo' );\nb.count\nb.push( 'bar' );\nb.count\n","CircularBuffer.prototype.full":"var b = CircularBuffer( 3 );\nb.full\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.full\n","CircularBuffer.prototype.iterator":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.push( 'boop' );\nvar it = b.iterator( b.length );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","CircularBuffer.prototype.length":"var b = CircularBuffer( [ 0, 0, 0 ] );\nvar len = b.length\n","CircularBuffer.prototype.push":"var b = CircularBuffer( 3 );\nb.push( 'foo' )\nb.push( 'bar' )\nb.push( 'beep' )\nb.push( 'boop' )\n","CircularBuffer.prototype.toArray":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.push( 'boop' );\nvar vals = b.toArray()\n","CircularBuffer.prototype.toJSON":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.push( 'boop' );\nvar o = b.toJSON()\n","close":"function done( error ) {\n if ( error ) {\n     console.error( error.message );\n }\n };\nvar fd = open.sync( './beep/boop.js', 'r+' );\nif ( !isError( fd ) ) { close( fd, done ); };\n","close.sync":"var fd = open.sync( './beep/boop.js', 'r+' );\nif ( !isError( fd ) ) { close.sync( fd ); };\n","CMUDICT":"var data = CMUDICT();\nvar dict = data.dict\nvar phones = data.phones\nvar symbols = data.symbols\nvar vp = data.vp\n","codePointAt":"var out = codePointAt( 'last man standing', 4 )\nout = codePointAt( 'presidential election', 8, true )\nout = codePointAt( 'अनुच्छेद', 2 )\nout = codePointAt( '🌷', 1, true )\n","commonKeys":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\nvar keys = commonKeys( obj1, obj2 )\n","commonKeysIn":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\nvar keys = commonKeysIn( obj1, obj2 )\n","complex":"var z = complex( 5.0, 3.0, 'float64' )\nz = complex( 5.0, 3.0, 'float32' )\n","Complex64":"var z = new Complex64( 5.0, 3.0 )\nz.re\nz.im\n","Complex64.BYTES_PER_ELEMENT":"var s = Complex64.BYTES_PER_ELEMENT\n","Complex64.prototype.BYTES_PER_ELEMENT":"var z = new Complex64( 5.0, 3.0 )\nvar s = z.BYTES_PER_ELEMENT\n","Complex64.prototype.byteLength":"var z = new Complex64( 5.0, 3.0 )\nvar s = z.byteLength\n","COMPLEX64_NAN":"COMPLEX64_NAN\n","COMPLEX64_NUM_BYTES":"COMPLEX64_NUM_BYTES\n","COMPLEX64_ZERO":"COMPLEX64_ZERO\n","Complex64Array":"var arr = new Complex64Array()\nvar arr = new Complex64Array( 10 )\nvar len = arr.length\nvar arr1 = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar arr2 = new Complex64Array( arr1 )\nvar len = arr2.length\nvar buf = new Float32Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar arr = new Complex64Array( buf )\nvar len = arr.length\nvar arr1 = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar len = arr1.length\nvar buf = [ new Complex64( 1.0, -1.0 ), new Complex64( 2.0, -2.0 )];\nvar arr2 = new Complex64Array( buf )\nlen = arr2.length\nvar buf = new ArrayBuffer( 240 );\nvar arr1 = new Complex64Array( buf )\nvar len = arr1.length\nvar arr2 = new Complex64Array( buf, 8 )\nlen = arr2.length\nvar arr3 = new Complex64Array( buf, 8, 20 )\nlen = arr3.length\n","Complex64Array.from":"function clbkFcn( v ) { return v * 2.0 };\nvar arr = Complex64Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\nvar len = arr.length\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.of":"var arr = Complex64Array.of( 1.0, -1.0, 2.0, -2.0 )\nvar len = arr.length\nvar z1 = new Complex64( 1.0, -1.0 );\nvar z2 = new Complex64( 2.0, -2.0 );\narr = Complex64Array.of( z1, z2 )\nlen = arr.length\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.BYTES_PER_ELEMENT":"var nbytes = Complex64Array.BYTES_PER_ELEMENT\n","Complex64Array.name":"var str = Complex64Array.name\n","Complex64Array.prototype.buffer":"var arr = new Complex64Array( 2 )\nvar buf = arr.buffer\n","Complex64Array.prototype.byteLength":"var arr = new Complex64Array( 10 )\nvar nbytes = arr.byteLength\n","Complex64Array.prototype.byteOffset":"var arr = new Complex64Array( 5 )\nvar offset = arr.byteOffset\nvar buf = new ArrayBuffer( 240 );\narr = new Complex64Array( buf, 64 )\noffset = arr.byteOffset\n","Complex64Array.prototype.BYTES_PER_ELEMENT":"var arr = new Complex64Array( 10 )\narr.BYTES_PER_ELEMENT\n","Complex64Array.prototype.length":"var arr = new Complex64Array( 10 )\nvar len = arr.length\n","Complex64Array.prototype.at":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.at( 1 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.copyWithin":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\narr.copyWithin( 0, 2 )\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.entries":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\nvar it = arr.entries();\nvar v = it.next().value\nvar re = realf( v[ 1 ] )\nvar im = imagf( v[ 1 ] )\nv = it.next().value\nre = realf( v[ 1 ] )\nim = imagf( v[ 1 ] )\nv = it.next().value\nre = realf( v[ 1 ] )\nim = imagf( v[ 1 ] )\nvar bool = it.next().done\n","Complex64Array.prototype.every":"function predicate( v ) { return ( realf( v ) > 0.0 ); };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar bool = arr.every( predicate )\n","Complex64Array.prototype.fill":"var arr = new Complex64Array( 3 )\narr.fill( new Complex64( 1.0, 1.0 ) );\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = arr.get( 1 )\nre = realf( z )\nim = imagf( z )\nz = arr.get( 2 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.filter":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar out = arr.filter( predicate )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.find":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar z = arr.find( predicate )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.findIndex":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar idx = arr.findIndex( predicate )\n","Complex64Array.prototype.findLast":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar z = arr.findLast( predicate )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.findLastIndex":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar idx = arr.findLastIndex( predicate )\n","Complex64Array.prototype.forEach":"var str = '%';\nfunction clbk( v ) { str += v.toString() + '%'; };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\narr.forEach( clbk );\nstr\n","Complex64Array.prototype.get":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.get( 1 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.includes":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar bool = arr.includes( new Complex64( 3.0, -3.0 ) )\nbool = arr.includes( new Complex64( 3.0, -3.0 ), 3 )\n","Complex64Array.prototype.indexOf":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar idx = arr.indexOf( new Complex64( 3.0, -3.0 ) )\nidx = arr.indexOf( new Complex64( 3.0, -3.0 ), 3 )\n","Complex64Array.prototype.join":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar str = arr.join()\nstr = arr.join( '/' )\n","Complex64Array.prototype.keys":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar it = arr.keys();\nvar v = it.next().value\nv = it.next().value\nv = it.next().done\n","Complex64Array.prototype.lastIndexOf":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\nvar idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ) )\nidx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ), 2 )\n","Complex64Array.prototype.map":"function clbk( v ) { return v; };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar out = arr.map( clbk )\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = out.get( 1 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.reduce":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.reduce( base.caddf )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.reduceRight":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.reduceRight( base.caddf )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.reverse":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\narr.reverse();\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = arr.get( 1 )\nre = realf( z )\nim = imagf( z )\nz = arr.get( 2 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.set":"var arr = new Complex64Array( 2 )\narr.set( new Complex64( 1.0, -1.0 ) );\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\narr.set( new Complex64( 2.0, -2.0 ), 1 );\nz = arr.get( 1 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.slice":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\nvar out = arr.slice( 1 )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = out.get( 1 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.some":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar bool = arr.some( predicate )\n","Complex64Array.prototype.sort":"function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\nvar arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\narr.sort( compare );\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = arr.get( 1 )\nre = realf( z )\nim = imagf( z )\nz = arr.get( 2 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.subarray":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar out = arr.subarray( 1, 3 )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = out.get( 1 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.toLocaleString":"var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0 ] )\nvar str = arr.toLocaleString()\n","Complex64Array.prototype.toReversed":"var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\nvar out = arr.toReversed()\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = out.get( 1 )\nre = realf( z )\nim = imagf( z )\nz = out.get( 2 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.toSorted":"function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\nvar arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\nvar out = arr.toSorted( compare );\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = out.get( 1 )\nre = realf( z )\nim = imagf( z )\nz = out.get( 2 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.toString":"var arr = new Complex64Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\nvar str = arr.toString()\n","Complex64Array.prototype.values":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar it = arr.values();\nvar v = it.next().value\nvar re = realf( v )\nvar im = imagf( v )\nv = it.next().value\nre = realf( v )\nim = imagf( v )\nvar bool = it.next().done\n","Complex64Array.prototype.with":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\nvar z = out.get( 1 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex128.BYTES_PER_ELEMENT":"var s = Complex128.BYTES_PER_ELEMENT\n","Complex128.prototype.BYTES_PER_ELEMENT":"var z = new Complex128( 5.0, 3.0 )\nvar s = z.BYTES_PER_ELEMENT\n","Complex128.prototype.byteLength":"var z = new Complex128( 5.0, 3.0 )\nvar s = z.byteLength\n","COMPLEX128_NAN":"COMPLEX128_NAN\n","COMPLEX128_NUM_BYTES":"COMPLEX128_NUM_BYTES\n","COMPLEX128_ZERO":"COMPLEX128_ZERO\n","Complex128Array":"var arr = new Complex128Array()\nvar arr = new Complex128Array( 10 )\nvar len = arr.length\nvar arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar arr2 = new Complex128Array( arr1 )\nvar len = arr2.length\nvar buf = new Float64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar arr = new Complex128Array( buf )\nvar len = arr.length\nvar arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar len = arr1.length\nvar buf = [ new Complex128( 1.0, -1.0 ), new Complex128( 2.0, -2.0 ) ];\nvar arr2 = new Complex128Array( buf )\nlen = arr2.length\nvar buf = new ArrayBuffer( 480 );\nvar arr1 = new Complex128Array( buf )\nvar len = arr1.length\nvar arr2 = new Complex128Array( buf, 16 )\nlen = arr2.length\nvar arr3 = new Complex128Array( buf, 16, 20 )\nlen = arr3.length\n","Complex128Array.from":"function clbkFcn( v ) { return v * 2.0 };\nvar arr = Complex128Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\nvar len = arr.length\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.of":"var arr = Complex128Array.of( 1.0, -1.0, 2.0, -2.0 )\nvar len = arr.length\nvar z1 = new Complex128( 1.0, -1.0 );\nvar z2 = new Complex128( 2.0, -2.0 );\narr = Complex128Array.of( z1, z2 )\nlen = arr.length\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.BYTES_PER_ELEMENT":"var nbytes = Complex128Array.BYTES_PER_ELEMENT\n","Complex128Array.name":"var str = Complex128Array.name\n","Complex128Array.prototype.buffer":"var arr = new Complex128Array( 2 )\nvar buf = arr.buffer\n","Complex128Array.prototype.byteLength":"var arr = new Complex128Array( 10 )\nvar nbytes = arr.byteLength\n","Complex128Array.prototype.byteOffset":"var arr = new Complex128Array( 10 )\nvar offset = arr.byteOffset\nvar buf = new ArrayBuffer( 480 );\narr = new Complex128Array( buf, 128 )\noffset = arr.byteOffset\n","Complex128Array.prototype.BYTES_PER_ELEMENT":"var arr = new Complex128Array( 10 )\narr.BYTES_PER_ELEMENT\n","Complex128Array.prototype.length":"var arr = new Complex128Array( 10 )\nvar len = arr.length\n","Complex128Array.prototype.at":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.at( 1 )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.copyWithin":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\narr.copyWithin( 0, 2 )\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.entries":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\nvar it = arr.entries();\nvar v = it.next().value\nvar re = real( v[ 1 ] )\nvar im = imag( v[ 1 ] )\nv = it.next().value\nre = real( v[ 1 ] )\nim = imag( v[ 1 ] )\nv = it.next().value\nre = real( v[ 1 ] )\nim = imag( v[ 1 ] )\nvar bool = it.next().done\n","Complex128Array.prototype.every":"function predicate( v ) { return ( real( v ) > 0.0 ); };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar bool = arr.every( predicate )\n","Complex128Array.prototype.fill":"var arr = new Complex128Array( 3 )\narr.fill( new Complex128( 1.0, 1.0 ) );\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = arr.get( 1 )\nre = real( z )\nim = imag( z )\nz = arr.get( 2 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.filter":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar out = arr.filter( predicate )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.find":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar z = arr.find( predicate )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.findIndex":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar idx = arr.findIndex( predicate )\n","Complex128Array.prototype.findLast":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar z = arr.findLast( predicate )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.findLastIndex":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar idx = arr.findLastIndex( predicate )\n","Complex128Array.prototype.forEach":"var str = '%';\nfunction clbk( v ) { str += v.toString() + '%'; };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\narr.forEach( clbk );\nstr\n","Complex128Array.prototype.get":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.get( 1 )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.includes":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar bool = arr.includes( new Complex128( 3.0, -3.0 ) )\nbool = arr.includes( new Complex128( 3.0, -3.0 ), 3 )\n","Complex128Array.prototype.indexOf":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar idx = arr.indexOf( new Complex128( 3.0, -3.0 ) )\nidx = arr.indexOf( new Complex128( 3.0, -3.0 ), 3 )\n","Complex128Array.prototype.join":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar str = arr.join()\nstr = arr.join( '/' )\n","Complex128Array.prototype.keys":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar it = arr.keys();\nvar v = it.next().value\nv = it.next().value\nv = it.next().done\n","Complex128Array.prototype.lastIndexOf":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\nvar idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ) )\nidx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ), 2 )\n","Complex128Array.prototype.map":"function clbk( v ) { return v; };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar out = arr.map( clbk )\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = out.get( 1 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.reduce":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.reduce( base.cadd )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.reduceRight":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.reduceRight( base.cadd )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.reverse":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\narr.reverse();\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = arr.get( 1 )\nre = real( z )\nim = imag( z )\nz = arr.get( 2 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.set":"var arr = new Complex128Array( 2 )\narr.set( new Complex128( 1.0, -1.0 ) );\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\narr.set( new Complex128( 2.0, -2.0 ), 1 );\nz = arr.get( 1 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.slice":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\nvar out = arr.slice( 1 )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = out.get( 1 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.some":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar bool = arr.some( predicate )\n","Complex128Array.prototype.sort":"function compare( a, b ) { return ( real( a ) - real( b ) ); };\nvar arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\narr.sort( compare );\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = arr.get( 1 )\nre = real( z )\nim = imag( z )\nz = arr.get( 2 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.subarray":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar out = arr.subarray( 1, 3 )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = out.get( 1 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.toLocaleString":"var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0 ] )\nvar str = arr.toLocaleString()\n","Complex128Array.prototype.toReversed":"var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\nvar out = arr.toReversed()\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = out.get( 1 )\nre = real( z )\nim = imag( z )\nz = out.get( 2 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.toSorted":"function compare( a, b ) { return ( real( a ) - real( b ) ); };\nvar arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\nvar out = arr.toSorted( compare );\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = out.get( 1 )\nre = real( z )\nim = imag( z )\nz = out.get( 2 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.toString":"var arr = new Complex128Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\nvar str = arr.toString()\n","Complex128Array.prototype.values":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar it = arr.values();\nvar v = it.next().value\nvar re = real( v )\nvar im = imag( v )\nv = it.next().value\nre = real( v )\nim = imag( v )\nvar bool = it.next().done\n","Complex128Array.prototype.with":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\nvar z = out.get( 1 )\nvar re = real( z )\nvar im = imag( z )\n","complexarray":"var arr = complexarray()\narr = complexarray( 'complex64' )\nvar arr = complexarray( 5 )\narr = complexarray( 5, 'complex64' )\nvar arr1 = complexarray( [ 0.5, 0.5, 0.5, 0.5 ] );\nvar arr2 = complexarray( arr1, 'complex64' )\nvar arr1 = [ 0.5, 0.5, 0.5, 0.5 ];\nvar arr2 = complexarray( arr1, 'complex64' )\nvar buf = new ArrayBuffer( 64 );\nvar arr = complexarray( buf, 0, 8, 'complex64' )\n","complexarrayCtors":"var ctor = complexarrayCtors( 'complex64' )\nctor = complexarrayCtors( 'float32' )\n","complexarrayDataTypes":"var out = complexarrayDataTypes()\n","complexCtors":"var ctor = complexCtors( 'complex128' )\nctor = complexCtors( 'complex' )\n","complexDataType":"var v = new Complex128( 1.0, 2.0 );\nvar dt = complexDataType( v )\ndt = complexDataType( 'beep' )\n","complexDataTypes":"var out = complexDataTypes()\n","complexPromotionRules":"var out = complexPromotionRules( 'complex128', 'complex64' )\n","compose":"function a( x ) {\nreturn 2 * x;\n }\nfunction b( x ) {\nreturn x + 3;\n }\nfunction c( x ) {\nreturn x / 5;\n }\nvar f = compose( c, b, a );\nvar z = f( 6 )\n","composeAsync":"function a( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n    next( null, 2*x );\n}\n };\nfunction b( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n    next( null, x+3 );\n}\n };\nfunction c( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n    next( null, x/5 );\n}\n };\nvar f = composeAsync( c, b, a );\nfunction done( error, result ) {\nif ( error ) {\n    throw error;\n}\nconsole.log( result );\n };\nf( 6, done )\n","configdir":"var dir = configdir()\ndir = configdir( 'appname/config' )\n","conj":"var z = new Complex128( 5.0, 3.0 );\nz.toString()\nvar v = conj( z );\nv.toString()\n","conjf":"var z = new Complex64( 5.0, 3.0 );\nz.toString()\nvar v = conjf( z );\nv.toString()\n","constantcase":"var out = constantcase( 'Hello World!' )\nout = constantcase( 'I am a tiny little teapot' )\n","constantFunction":"var fcn = constantFunction( 3.14 );\nvar v = fcn()\nv = fcn()\nv = fcn()\n","constantStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = constantStream( 'beep', opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","constantStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = constantStream.factory( opts );\n","constantStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = constantStream.objectMode( 3.14, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","constructorName":"var v = constructorName( 'a' )\nv = constructorName( {} )\nv = constructorName( true )\n","contains":"var bool = contains( 'Hello World', 'World' )\nbool = contains( 'Hello World', 'world' )\nbool = contains( [ 1, 2, 3, 4 ], 2 )\nbool = contains( [ NaN, 2, 3, 4 ], NaN )\nbool = contains( 'Hello World', 'Hello', 6 )\nbool = contains( [ true, NaN, false ], true, 1 )\n","convertArray":"var arr = [ 1.0, 2.0, 3.0, 4.0 ];\nvar out = convertArray( arr, 'float32' )\n","convertArraySame":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = new Float32Array( 0 );\nvar out = convertArraySame( x, y )\n","convertPath":"var out = convertPath( '/c/foo/bar/beep.c', 'win32' )\nout = convertPath( '/c/foo/bar/beep.c', 'mixed' )\nout = convertPath( '/c/foo/bar/beep.c', 'posix' )\nout = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'win32' )\nout = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'mixed' )\nout = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'posix' )\n","copy":"var value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\nvar out = copy( value )\nvar bool = ( value[ 0 ].c === out[ 0 ].c )\nvalue = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\nout = copy( value, 1 );\nbool = ( value[ 0 ] === out[ 0 ] )\nbool = ( value[ 0 ].c === out[ 0 ].c )\n","copyBuffer":"var b1 = array2buffer( [ 1, 2, 3, 4 ] );\nvar b2 = copyBuffer( b1 )\n","countBy":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n     return 'b';\n }\n return 'other';\n };\nvar collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar out = countBy( collection, indicator )\n","countByAsync":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\ncountByAsync( arr, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\ncountByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\ncountByAsync( arr, opts, indicator, done )\n","countByAsync.factory":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nvar opts = { 'series': true };\nvar f = countByAsync.factory( opts, indicator );\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000, 500 ];\nf( arr, done )\n","currentYear":"var y = currentYear()\n","curry":"function add( x, y ) { return x + y; };\nvar f = curry( add );\nvar sum = f( 2 )( 3 )\nfunction add() { return arguments[ 0 ] + arguments[ 1 ]; };\nf = curry( add, 2 );\nsum = f( 2 )( 3 )\nvar obj = {\n 'name': 'Ada',\n 'greet': function greet( word1, word2 ) {\n    return word1 + ' ' + word2 + ', ' + this.name + '!'\n }\n };\nf = curry( obj.greet, obj );\nvar str = f( 'Hello' )( 'there' )\n","curryRight":"function add( x, y ) { return x + y; };\nvar f = curryRight( add );\nvar sum = f( 2 )( 3 )\nfunction add() { return arguments[ 0 ] + arguments[ 1 ]; };\nf = curryRight( add, 2 );\nsum = f( 2 )( 3 )\nvar obj = {\n 'name': 'Ada',\n 'greet': function greet( word1, word2 ) {\n     return word1 + ' ' + word2 + ', ' + this.name + '!'\n }\n };\nf = curryRight( obj.greet, obj );\nvar str = f( 'there' )( 'Hello' )\n","cwd":"var dir = cwd()\n","DALE_CHALL_NEW":"var list = DALE_CHALL_NEW()\n","datasets":"var out = datasets( 'MONTH_NAMES_EN' )\nvar opts = { 'data': 'cities' };\nout = datasets( 'MINARD_NAPOLEONS_MARCH', opts )\n","DataView":"var buf = new ArrayBuffer( 5 )\nvar dv = new DataView( buf )\n","DataView.prototype.buffer":"var buf1 = new ArrayBuffer( 5 );\nvar dv = new DataView( buf1 );\nvar buf2 = dv.buffer\nvar b = ( buf1 === buf2 )\n","DataView.prototype.byteLength":"var buf = new ArrayBuffer( 5 );\nvar dv = new DataView( buf );\ndv.byteLength\n","DataView.prototype.byteOffset":"var buf = new ArrayBuffer( 5 );\nvar dv = new DataView( buf, 2 );\ndv.byteLength\ndv.byteOffset\n","datespace":"var stop = '2014-12-02T07:00:54.973Z';\nvar start = new Date( stop ) - 60000;\nvar arr = datespace( start, stop, 6 )\nvar opts = { 'round': 'ceil' };\narr = datespace( 1417503655000, 1417503655001, 3, opts )\n","dayOfQuarter":"var day = dayOfQuarter()\nday = dayOfQuarter( new Date() )\nday = dayOfQuarter( 12, 31, 2017 )\nday = dayOfQuarter( 'dec', 31, 2017 )\nday = dayOfQuarter( 'december', 31, 2017 )\n","dayOfYear":"var day = dayOfYear()\nday = dayOfYear( new Date() )\nday = dayOfYear( 12, 31, 2016 )\nday = dayOfYear( 'dec', 31, 2016 )\nday = dayOfYear( 'december', 31, 2016 )\n","daysInMonth":"var num = daysInMonth()\nnum = daysInMonth( 2 )\nnum = daysInMonth( 2, 2016 )\nnum = daysInMonth( 2, 2017 )\nnum = daysInMonth( 'feb', 2016 )\nnum = daysInMonth( 'february', 2016 )\n","daysInYear":"var num = daysInYear()\nnum = daysInYear( 2016 )\nnum = daysInYear( 2017 )\n","ddot":"var xbuf = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar x = array( xbuf );\nvar ybuf = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar y = array( ybuf );\nvar z = ddot( x, y )\nz.get()\n","debugSinkStream":"var s = debugSinkStream( { 'name': 'foo' } );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","debugSinkStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = debugSinkStream.factory( opts );\n","debugSinkStream.objectMode":"var s = debugSinkStream.objectMode( { 'name': 'foo' } );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","debugStream":"var s = debugStream( { 'name': 'foo' } );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","debugStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = debugStream.factory( opts );\n","debugStream.objectMode":"var s = debugStream.objectMode( { 'name': 'foo' } );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","decorateAfter":"function f( v ) { return -v; };\nvar fcn = decorateAfter( base.abs, 1, f );\nvar v = fcn( -5 )\nv = fcn( 5 )\n","decorateAfter.factory":"function f( v ) { return -v; };\nvar fcn = decorateAfter.factory( base.abs, 1, f );\nvar v = fcn( -5 )\nv = fcn( 5 )\n","deepEqual":"var bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, 3 ] )\nbool = deepEqual( [ 1, 2, 3 ], [ 1, 2, '3' ] )\nbool = deepEqual( { 'a': 2 }, { 'a': [ 2 ] } )\n","deepGet":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar val = deepGet( obj, 'a.b.c' )\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar val = deepGet( obj, 'a/b/c', { 'sep': '/' } )\n","deepGet.factory":"var dget = deepGet.factory( 'a/b/c', { 'sep': '/' } );\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar val = dget( obj )\n","deepHasOwnProp":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = deepHasOwnProp( obj, 'a.b.c' )\nobj = { 'a': { 'b': { 'c': 'd' } } };\nbool = deepHasOwnProp( obj, 'a/b/c', { 'sep': '/' } )\n","deepHasOwnProp.factory":"var has = deepHasOwnProp.factory( 'a/b/c', { 'sep': '/' } );\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = has( obj )\n","deepHasProp":"function Foo() { return this; };\nFoo.prototype.b = { 'c': 'd' };\nvar obj = { 'a': new Foo() };\nvar bool = deepHasProp( obj, 'a.b.c' )\nbool = deepHasProp( obj, 'a/b/c', { 'sep': '/' } )\n","deepHasProp.factory":"function Foo() { return this; };\nFoo.prototype.b = { 'c': 'd' };\nvar has = deepHasProp.factory( 'a/b/c', { 'sep': '/' } );\nvar obj = { 'a': new Foo() };\nvar bool = has( obj )\n","deepPluck":"var arr = [\n { 'a': { 'b': { 'c': 1 } } },\n { 'a': { 'b': { 'c': 2 } } }\n ];\nvar out = deepPluck( arr, 'a.b.c' )\narr = [\n { 'a': [ 0, 1, 2 ] },\n { 'a': [ 3, 4, 5 ] }\n ];\nout = deepPluck( arr, [ 'a', 1 ] )\n","deepSet":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = deepSet( obj, 'a.b.c', 'beep' )\nobj = { 'a': { 'b': { 'c': 'd' } } };\nbool = deepSet( obj, 'a/b/c', 'beep', { 'sep': '/' } );\nobj\nbool = deepSet( obj, 'a.e.c', 'boop', { 'create': true } );\nobj\n","deepSet.factory":"var dset = deepSet.factory( 'a/b/c', {\n 'create': true,\n 'sep': '/'\n });\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = dset( obj, 'beep' )\nobj\n","defineMemoizedProperty":"var obj = {};\nfunction foo() {\n return 'bar';\n };\ndefineMemoizedProperty( obj, 'foo', {\n 'configurable': false,\n 'enumerable': true,\n 'writable': false,\n 'value': foo\n });\nobj.foo\n","defineProperties":"var obj = {};\ndefineProperties( obj, {\n 'foo': {\n     'value': 'bar',\n     'writable': false,\n     'configurable': false,\n     'enumerable': true\n },\n 'baz': {\n     'value': 13\n }\n });\nobj.foo\nobj.baz\n","defineProperty":"var obj = {};\ndefineProperty( obj, 'foo', {\n 'value': 'bar',\n 'enumerable': true,\n 'writable': false\n });\nobj.foo = 'boop';\nobj\n","dirname":"var dir = dirname( './foo/bar/index.js' )\n","dotcase":"var out = dotcase( 'Hello World!' )\nout = dotcase( 'beep boop' )\n","DoublyLinkedList":"var list = DoublyLinkedList();\nlist.push( 'foo' ).push( 'bar' );\nlist.length\nlist.pop()\nlist.length\nlist.pop()\nlist.length\n","doUntil":"function predicate( i ) { return ( i >= 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\ndoUntil( beep, predicate )\n","doUntilAsync":"function fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n     next( null, 'boop'+i );\n }\n };\nfunction predicate( i, clbk ) { clbk( null, i >= 5 ); };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\ndoUntilAsync( fcn, predicate, done )\n","doUntilEach":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\ndoUntilEach( arr, logger, predicate )\n","doUntilEachRight":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\ndoUntilEachRight( arr, logger, predicate )\n","doWhile":"function predicate( i ) { return ( i < 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\ndoWhile( beep, predicate )\n","doWhileAsync":"function fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n     next( null, 'boop'+i );\n }\n };\nfunction predicate( i, clbk ) { clbk( null, i < 5 ); };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\ndoWhileAsync( fcn, predicate, done )\n","doWhileEach":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\ndoWhileEach( arr, logger, predicate )\n","doWhileEachRight":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\ndoWhileEachRight( arr, logger, predicate )\n","dswap":"var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\ndswap( x, y );\nx.data\ny.data\n","E":"E\n","EMOJI":"var data = EMOJI()\n","EMOJI_CODE_PICTO":"var out = EMOJI_CODE_PICTO()\n","EMOJI_PICTO_CODE":"var out = EMOJI_PICTO_CODE()\n","emptyStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar s = emptyStream();\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","emptyStream.factory":"var opts = { 'objectMode': true };\nvar createStream = emptyStream.factory( opts );\n","emptyStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar s = emptyStream.objectMode();\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","endsWith":"var bool = endsWith( 'beep', 'ep' )\nbool = endsWith( 'Beep', 'op' )\nbool = endsWith( 'Beep', 'ee', 3 )\nbool = endsWith( 'Beep', 'ee', -1 )\nbool = endsWith( 'beep', '' )\n","enumerableProperties":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar props = enumerableProperties( obj )\n","enumerablePropertiesIn":"var props = enumerablePropertiesIn( [] )\n","enumerablePropertySymbols":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = enumerablePropertySymbols( obj )\n","enumerablePropertySymbolsIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = enumerablePropertySymbolsIn( obj )\n","ENV":"var user = ENV.USER\n","EPS":"EPS\n","error2json":"var err = new Error( 'beep' );\nvar json = error2json( err )\n","EULERGAMMA":"EULERGAMMA\n","every":"var arr = [ 1, 1, 1, 1, 1 ];\nvar bool = every( arr )\n","everyBy":"function positive( v ) { return ( v > 0 ); };\nvar arr = [ 1, 2, 3, 4 ];\nvar bool = everyBy( arr, positive )\n","everyByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\neveryByAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\neveryByAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\neveryByAsync( arr, opts, predicate, done )\n","everyByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, true );\n }\n };\nvar opts = { 'series': true };\nvar f = everyByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","everyByRight":"function positive( v ) { return ( v > 0 ); };\nvar arr = [ 1, 2, 3, 4 ];\nvar bool = everyByRight( arr, positive )\n","everyByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\neveryByRightAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\neveryByRightAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\neveryByRightAsync( arr, opts, predicate, done )\n","everyByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, true );\n }\n };\nvar opts = { 'series': true };\nvar f = everyByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","everyInBy":"function positive( v ) { return ( v > 0 ); };\nvar o = {a: 1, b: 2, c: 3};\nvar bool = everyInBy( o, positive )\n","everyOwnBy":"function positive( v ) { return ( v > 0 ); };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nvar bool = everyOwnBy( obj, positive )\n","evil":"var v = evil( '5*4*3*2*1' )\n","EXEC_PATH":"EXEC_PATH\n","exists":"function done( error, bool ) { console.log( bool ); };\nexists( './beep/boop', done );\n","exists.sync":"var bool = exists.sync( './beep/boop' )\n","expandAcronyms":"var str = 'LOL, this is fun. I am ROFL.';\nvar out = expandAcronyms( str )\nstr = 'brb, I need to check my mail. thx!';\nout = expandAcronyms( str )\n","expandContractions":"var str = 'I won\\'t be able to get y\\'all out of this one.';\nvar out = expandContractions( str )\nstr = 'It oughtn\\'t to be my fault, because, you know, I didn\\'t know';\nout = expandContractions( str )\n","extname":"var ext = extname( 'index.js' )\n","FancyArray":"var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\nvar d = [ 2, 2 ]; // shape\nvar s = [ 2, 1 ]; // strides\nvar o = 0; // index offset\nvar arr = FancyArray( 'generic', b, d, s, o, 'row-major' )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","FancyArray.prototype.byteLength":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.byteLength\n","FancyArray.prototype.BYTES_PER_ELEMENT":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.BYTES_PER_ELEMENT\n","FancyArray.prototype.data":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar buf = arr.data\n","FancyArray.prototype.dtype":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar dt = arr.dtype\n","FancyArray.prototype.flags":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar fl = arr.flags\n","FancyArray.prototype.length":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar len = arr.length\n","FancyArray.prototype.ndims":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar n = arr.ndims\n","FancyArray.prototype.offset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.offset\n","FancyArray.prototype.order":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar ord = arr.order\n","FancyArray.prototype.shape":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar sh = arr.shape\n","FancyArray.prototype.strides":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar st = arr.strides\n","FancyArray.prototype.get":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.get( 1, 1 )\n","FancyArray.prototype.iget":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.iget( 3 )\n","FancyArray.prototype.set":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\narr.set( 1, 1, -4.0 );\narr.get( 1, 1 )\n","FancyArray.prototype.iset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\narr.iset( 3, -4.0 );\narr.iget( 3 )\n","FancyArray.prototype.toString":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\narr.toString()\n","FancyArray.prototype.toJSON":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\narr.toJSON()\n","fastmath.abs":"var v = fastmath.abs( -1.0 )\nv = fastmath.abs( 2.0 )\nv = fastmath.abs( 0.0 )\nv = fastmath.abs( -0.0 )\nv = fastmath.abs( NaN )\n","fastmath.acosh":"var v = fastmath.acosh( 1.0 )\nv = fastmath.acosh( 2.0 )\nv = fastmath.acosh( NaN )\nv = fastmath.acosh( 1.0e308 )\n","fastmath.ampbm":"var h = fastmath.ampbm( 5.0, 12.0 )\n","fastmath.ampbm.factory":"var hypot = fastmath.ampbm.factory( 1.0, 0.5 )\n","fastmath.asinh":"var v = fastmath.asinh( 0.0 )\nv = fastmath.asinh( 2.0 )\nv = fastmath.asinh( -2.0 )\nv = fastmath.asinh( NaN )\nv = fastmath.asinh( 1.0e200 )\nv = fastmath.asinh( 1.0e-50 )\n","fastmath.atanh":"var v = fastmath.atanh( 0.0 )\nv = fastmath.atanh( 0.9 )\nv = fastmath.atanh( 1.0 )\nv = fastmath.atanh( -1.0 )\nv = fastmath.atanh( NaN )\nv = fastmath.atanh( 1.0e-17 )\n","fastmath.hypot":"var h = fastmath.hypot( -5.0, 12.0 )\nh = fastmath.hypot( 1.0e154, 1.0e154 )\nh = fastmath.hypot( 1e-200, 1.0e-200 )\n","fastmath.log2Uint32":"var v = fastmath.log2Uint32( 4 >>> 0 )\nv = fastmath.log2Uint32( 8 >>> 0 )\nv = fastmath.log2Uint32( 9 >>> 0 )\n","fastmath.max":"var v = fastmath.max( 3.14, 4.2 )\nv = fastmath.max( 3.14, NaN )\nv = fastmath.max( NaN, 3.14 )\nv = fastmath.max( -0.0, +0.0 )\nv = fastmath.max( +0.0, -0.0 )\n","fastmath.min":"var v = fastmath.min( 3.14, 4.2 )\nv = fastmath.min( 3.14, NaN )\nv = fastmath.min( NaN, 3.14 )\nv = fastmath.min( -0.0, +0.0 )\nv = fastmath.min( +0.0, -0.0 )\n","fastmath.powint":"var v = fastmath.powint( 2.0, 3 )\nv = fastmath.powint( 3.14, 0 )\nv = fastmath.powint( 2.0, -2 )\nv = fastmath.powint( 0.0, 0 )\nv = fastmath.powint( -3.14, 1 )\nv = fastmath.powint( NaN, 0 )\n","fastmath.sqrtUint32":"var v = fastmath.sqrtUint32( 9 >>> 0 )\nv = fastmath.sqrtUint32( 2 >>> 0 )\nv = fastmath.sqrtUint32( 3 >>> 0 )\nv = fastmath.sqrtUint32( 0 >>> 0 )\n","FEMALE_FIRST_NAMES_EN":"var list = FEMALE_FIRST_NAMES_EN()\n","FIFO":"var q = FIFO();\nq.push( 'foo' ).push( 'bar' );\nq.length\nq.pop()\nq.length\nq.pop()\nq.length\n","filledarray":"var arr = filledarray()\narr = filledarray( 'float32' )\nvar arr = filledarray( 1.0, 5 )\narr = filledarray( 1, 5, 'int32' )\nvar arr1 = filledarray( 2.0, [ 0.5, 0.5, 0.5 ] )\nvar arr2 = filledarray( 1.0, arr1, 'float32' )\nvar arr1 = iterConstant( 3.0, {'iter': 3} );\nvar arr2 = filledarray( 1.0, arr1, 'float32' )\nvar buf = new ArrayBuffer( 16 );\nvar arr = filledarray( 1.0, buf, 0, 4, 'float32' )\n","filledarrayBy":"var arr = filledarrayBy()\narr = filledarrayBy( 'float32' )\nfunction clbk() { return 1.0; };\nvar arr = filledarrayBy( 5, clbk )\narr = filledarrayBy( 5, 'int32', clbk )\nvar arr1 = filledarrayBy( [ 0.5, 0.5, 0.5 ], constantFunction( 2.0 ) )\nvar arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\nvar arr1 = iterConstant( 3.0, {'iter': 3} );\nvar arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\nvar buf = new ArrayBuffer( 16 );\nvar arr = filledarrayBy( buf, 0, 4, 'float32', constantFunction( 1.0 ) )\n","filterArguments":"function foo( a, b ) { return [ a, b ]; };\nfunction predicate( v ) { return ( v !== 2 ); };\nvar bar = filterArguments( foo, predicate );\nvar out = bar( 1, 2, 3 )\n","find":"var data = [ 30, 20, 50, 60, 10 ];\nfunction condition( val ) { return val > 20; };\nvar vals = find( data, condition )\ndata = [ 30, 20, 50, 60, 10 ];\nvar opts = { 'k': 2, 'returns': 'values' };\nvals = find( data, opts, condition )\ndata = [ 30, 20, 50, 60, 10 ];\nopts = { 'k': -2, 'returns': '*' };\nvals = find( data, opts, condition )\n","firstChar":"var out = firstChar( 'beep' )\nout = firstChar( 'Boop', 1 )\nout = firstChar( 'foo bar', 5 )\n","FIVETHIRTYEIGHT_FFQ":"var data = FIVETHIRTYEIGHT_FFQ()\n","flattenArray":"var arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\nvar out = flattenArray( arr )\narr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\nout = flattenArray( arr, { 'depth': 2 } )\nvar bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\narr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\nout = flattenArray( arr, { 'depth': 2, 'copy': true } )\nbool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n","flattenArray.factory":"var flatten = flattenArray.factory( [ 2, 2 ], {\n 'copy': false\n });\nvar out = flatten( [ [ 1, 2 ], [ 3, 4 ] ] )\nout = flatten( [ [ 5, 6 ], [ 7, 8 ] ] )\n","flattenObject":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar out = flattenObject( obj )\nobj = { 'a': { 'b': { 'c': 'd' } } };\nout = flattenObject( obj, { 'depth': 1 } )\nvar bool = ( obj.a.b === out[ 'a.b' ] )\nobj = { 'a': { 'b': { 'c': 'd' } } };\nout = flattenObject( obj, { 'delimiter': '-|-' } )\nobj = { 'a': { 'b': [ 1, 2, 3 ] } };\nout = flattenObject( obj, { 'flattenArrays': true } )\n","flattenObject.factory":"var flatten = flattenObject.factory({\n 'depth': 1,\n 'copy': true,\n 'delimiter': '|'\n });\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar out = flatten( obj )\n","flignerTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = flignerTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = flignerTest( arr, { 'groups': groups } )\n","FLOAT_WORD_ORDER":"FLOAT_WORD_ORDER\n","FLOAT16_CBRT_EPS":"FLOAT16_CBRT_EPS\n","FLOAT16_EPS":"FLOAT16_EPS\n","FLOAT16_EXPONENT_BIAS":"FLOAT16_EXPONENT_BIAS\n","FLOAT16_MAX":"FLOAT16_MAX\n","FLOAT16_MAX_SAFE_INTEGER":"FLOAT16_MAX_SAFE_INTEGER\n","FLOAT16_MIN_SAFE_INTEGER":"FLOAT16_MIN_SAFE_INTEGER\n","FLOAT16_NINF":"FLOAT16_NINF\n","FLOAT16_NUM_BYTES":"FLOAT16_NUM_BYTES\n","FLOAT16_PINF":"FLOAT16_PINF\n","FLOAT16_PRECISION":"FLOAT16_PRECISION\n","FLOAT16_SMALLEST_NORMAL":"FLOAT16_SMALLEST_NORMAL\n","FLOAT16_SMALLEST_SUBNORMAL":"FLOAT16_SMALLEST_SUBNORMAL\n","FLOAT16_SQRT_EPS":"FLOAT16_SQRT_EPS\n","FLOAT32_ABS_MASK":"FLOAT32_ABS_MASK\nbase.toBinaryStringUint32( FLOAT32_ABS_MASK )\n","FLOAT32_CBRT_EPS":"FLOAT32_CBRT_EPS\n","FLOAT32_E":"FLOAT32_E\n","FLOAT32_EPS":"FLOAT32_EPS\n","FLOAT32_EXPONENT_BIAS":"FLOAT32_EXPONENT_BIAS\n","FLOAT32_EXPONENT_MASK":"FLOAT32_EXPONENT_MASK\nbase.toBinaryStringUint32( FLOAT32_EXPONENT_MASK )\n","FLOAT32_FOURTH_PI":"FLOAT32_FOURTH_PI\n","FLOAT32_HALF_LN_TWO":"FLOAT32_HALF_LN_TWO\n","FLOAT32_HALF_PI":"FLOAT32_HALF_PI\n","FLOAT32_LN_HALF":"FLOAT32_LN_HALF\n","FLOAT32_LN_PI":"FLOAT32_LN_PI\n","FLOAT32_LN_TEN":"FLOAT32_LN_TEN\n","FLOAT32_LN_TWO":"FLOAT32_LN_TWO\n","FLOAT32_MAX":"FLOAT32_MAX\n","FLOAT32_MAX_BASE2_EXPONENT":"FLOAT32_MAX_BASE2_EXPONENT\n","FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL":"FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL\n","FLOAT32_MAX_BASE10_EXPONENT":"FLOAT32_MAX_BASE10_EXPONENT\n","FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL":"FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL\n","FLOAT32_MAX_SAFE_FIBONACCI":"FLOAT32_MAX_SAFE_FIBONACCI\n","FLOAT32_MAX_SAFE_INTEGER":"FLOAT32_MAX_SAFE_INTEGER\n","FLOAT32_MAX_SAFE_NTH_FACTORIAL":"FLOAT32_MAX_SAFE_NTH_FACTORIAL\n","FLOAT32_MAX_SAFE_NTH_FIBONACCI":"FLOAT32_MAX_SAFE_NTH_FIBONACCI\n","FLOAT32_MAX_SAFE_NTH_LUCAS":"FLOAT32_MAX_SAFE_NTH_LUCAS\n","FLOAT32_MIN_BASE2_EXPONENT":"FLOAT32_MIN_BASE2_EXPONENT\n","FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL":"FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT32_MIN_BASE10_EXPONENT":"FLOAT32_MIN_BASE10_EXPONENT\n","FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL":"FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT32_MIN_SAFE_INTEGER":"FLOAT32_MIN_SAFE_INTEGER\n","FLOAT32_NAN":"FLOAT32_NAN\n","FLOAT32_NINF":"FLOAT32_NINF\n","FLOAT32_NUM_BYTES":"FLOAT32_NUM_BYTES\n","FLOAT32_PHI":"FLOAT32_PHI\n","FLOAT32_PI":"FLOAT32_PI\n","FLOAT32_PINF":"FLOAT32_PINF\n","FLOAT32_PRECISION":"FLOAT32_PRECISION\n","FLOAT32_SIGN_MASK":"FLOAT32_SIGN_MASK\nbase.toBinaryStringUint32( FLOAT32_SIGN_MASK )\n","FLOAT32_SIGNIFICAND_MASK":"FLOAT32_SIGNIFICAND_MASK\nbase.toBinaryStringUint32( FLOAT32_SIGNIFICAND_MASK )\n","FLOAT32_SMALLEST_NORMAL":"FLOAT32_SMALLEST_NORMAL\n","FLOAT32_SMALLEST_SUBNORMAL":"FLOAT32_SMALLEST_SUBNORMAL\n","FLOAT32_SQRT_EPS":"FLOAT32_SQRT_EPS\n","FLOAT32_SQRT_HALF":"FLOAT32_SQRT_HALF\n","FLOAT32_SQRT_HALF_PI":"FLOAT32_SQRT_HALF_PI\n","FLOAT32_SQRT_PHI":"FLOAT32_SQRT_PHI\n","FLOAT32_SQRT_PI":"FLOAT32_SQRT_PI\n","FLOAT32_SQRT_THREE":"FLOAT32_SQRT_THREE\n","FLOAT32_SQRT_TWO":"FLOAT32_SQRT_TWO\n","FLOAT32_SQRT_TWO_PI":"FLOAT32_SQRT_TWO_PI\n","FLOAT32_TWO_PI":"FLOAT32_TWO_PI\n","Float32Array":"var arr = new Float32Array()\nvar arr = new Float32Array( 5 )\nvar arr1 = new Float64Array( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = new Float32Array( arr1 )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = new Float32Array( arr1 )\nvar buf = new ArrayBuffer( 16 );\nvar arr = new Float32Array( buf, 0, 4 )\n","Float32Array.from":"function mapFcn( v ) { return v * 2.0; };\nvar arr = Float32Array.from( [ 1.0, -1.0 ], mapFcn )\n","Float32Array.of":"var arr = Float32Array.of( 2.0, -2.0 )\n","Float32Array.BYTES_PER_ELEMENT":"Float32Array.BYTES_PER_ELEMENT\n","Float32Array.name":"Float32Array.name\n","Float32Array.prototype.buffer":"var arr = new Float32Array( 5 );\narr.buffer\n","Float32Array.prototype.byteLength":"var arr = new Float32Array( 5 );\narr.byteLength\n","Float32Array.prototype.byteOffset":"var arr = new Float32Array( 5 );\narr.byteOffset\n","Float32Array.prototype.BYTES_PER_ELEMENT":"var arr = new Float32Array( 5 );\narr.BYTES_PER_ELEMENT\n","Float32Array.prototype.length":"var arr = new Float32Array( 5 );\narr.length\n","Float32Array.prototype.copyWithin":"var arr = new Float32Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Float32Array.prototype.entries":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Float32Array.prototype.every":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\narr.every( predicate )\n","Float32Array.prototype.fill":"var arr = new Float32Array( [ 1.0, -1.0 ] );\narr.fill( 2.0 );\narr[ 0 ]\narr[ 1 ]\n","Float32Array.prototype.filter":"var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Float32Array.prototype.find":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar v = arr.find( predicate )\n","Float32Array.prototype.findIndex":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar idx = arr.findIndex( predicate )\n","Float32Array.prototype.forEach":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Float32Array.prototype.includes":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar bool = arr.includes( 2.0 )\nbool = arr.includes( -1.0 )\n","Float32Array.prototype.indexOf":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar idx = arr.indexOf( 2.0 )\nidx = arr.indexOf( -1.0 )\n","Float32Array.prototype.join":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\narr.join( '|' )\n","Float32Array.prototype.keys":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Float32Array.prototype.lastIndexOf":"var arr = new Float32Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\nvar idx = arr.lastIndexOf( 2.0 )\nidx = arr.lastIndexOf( 0.0 )\n","Float32Array.prototype.map":"var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( v ) { return v * 2.0; };\nvar arr2 = arr1.map( fcn )\n","Float32Array.prototype.reduce":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0.0 )\n","Float32Array.prototype.reduceRight":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0.0 )\n","Float32Array.prototype.reverse":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] )\narr.reverse()\n","Float32Array.prototype.set":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\narr.set( [ -2.0, 2.0 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Float32Array.prototype.slice":"var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Float32Array.prototype.some":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\narr.some( predicate )\n","Float32Array.prototype.sort":"var arr = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\narr.sort()\n","Float32Array.prototype.subarray":"var arr1 = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\nvar arr2 = arr1.subarray( 2 )\n","Float32Array.prototype.toLocaleString":"var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\narr.toLocaleString()\n","Float32Array.prototype.toString":"var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\narr.toString()\n","Float32Array.prototype.values":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","FLOAT64_EXPONENT_BIAS":"FLOAT64_EXPONENT_BIAS\n","FLOAT64_HIGH_WORD_ABS_MASK":"FLOAT64_HIGH_WORD_ABS_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_ABS_MASK )\n","FLOAT64_HIGH_WORD_EXPONENT_MASK":"FLOAT64_HIGH_WORD_EXPONENT_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_EXPONENT_MASK )\n","FLOAT64_HIGH_WORD_SIGN_MASK":"FLOAT64_HIGH_WORD_SIGN_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGN_MASK )\n","FLOAT64_HIGH_WORD_SIGNIFICAND_MASK":"FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGNIFICAND_MASK )\n","FLOAT64_MAX":"FLOAT64_MAX\n","FLOAT64_MAX_BASE2_EXPONENT":"FLOAT64_MAX_BASE2_EXPONENT\n","FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL":"FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_BASE10_EXPONENT":"FLOAT64_MAX_BASE10_EXPONENT\n","FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL":"FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_LN":"FLOAT64_MAX_LN\n","FLOAT64_MAX_SAFE_FIBONACCI":"FLOAT64_MAX_SAFE_FIBONACCI\n","FLOAT64_MAX_SAFE_INTEGER":"FLOAT64_MAX_SAFE_INTEGER\n","FLOAT64_MAX_SAFE_LUCAS":"FLOAT64_MAX_SAFE_LUCAS\n","FLOAT64_MAX_SAFE_NTH_FIBONACCI":"FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT64_MAX_SAFE_NTH_LUCAS":"FLOAT64_MAX_SAFE_NTH_LUCAS\n","FLOAT64_MIN_BASE2_EXPONENT":"FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL":"FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_BASE10_EXPONENT":"FLOAT64_MIN_BASE10_EXPONENT\n","FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL":"FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_LN":"FLOAT64_MIN_LN\n","FLOAT64_MIN_SAFE_INTEGER":"FLOAT64_MIN_SAFE_INTEGER\n","FLOAT64_NUM_BYTES":"FLOAT64_NUM_BYTES\n","FLOAT64_PRECISION":"FLOAT64_PRECISION\n","FLOAT64_SMALLEST_NORMAL":"FLOAT64_SMALLEST_NORMAL\n","FLOAT64_SMALLEST_SUBNORMAL":"FLOAT64_SMALLEST_SUBNORMAL\n","Float64Array":"var arr = new Float64Array()\nvar arr = new Float64Array( 5 )\nvar arr1 = new Float32Array( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = new Float64Array( arr1 )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = new Float64Array( arr1 )\nvar buf = new ArrayBuffer( 32 );\nvar arr = new Float64Array( buf, 0, 4 )\n","Float64Array.from":"function mapFcn( v ) { return v * 2.0; };\nvar arr = Float64Array.from( [ 1.0, -1.0 ], mapFcn )\n","Float64Array.of":"var arr = Float64Array.of( 2.0, -2.0 )\n","Float64Array.BYTES_PER_ELEMENT":"Float64Array.BYTES_PER_ELEMENT\n","Float64Array.name":"Float64Array.name\n","Float64Array.prototype.buffer":"var arr = new Float64Array( 5 );\narr.buffer\n","Float64Array.prototype.byteLength":"var arr = new Float64Array( 5 );\narr.byteLength\n","Float64Array.prototype.byteOffset":"var arr = new Float64Array( 5 );\narr.byteOffset\n","Float64Array.prototype.BYTES_PER_ELEMENT":"var arr = new Float64Array( 5 );\narr.BYTES_PER_ELEMENT\n","Float64Array.prototype.length":"var arr = new Float64Array( 5 );\narr.length\n","Float64Array.prototype.copyWithin":"var arr = new Float64Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Float64Array.prototype.entries":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Float64Array.prototype.every":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\narr.every( predicate )\n","Float64Array.prototype.fill":"var arr = new Float64Array( [ 1.0, -1.0 ] );\narr.fill( 2.0 );\narr[ 0 ]\narr[ 1 ]\n","Float64Array.prototype.filter":"var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Float64Array.prototype.find":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar v = arr.find( predicate )\n","Float64Array.prototype.findIndex":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar idx = arr.findIndex( predicate )\n","Float64Array.prototype.forEach":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Float64Array.prototype.includes":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar bool = arr.includes( 2.0 )\nbool = arr.includes( -1.0 )\n","Float64Array.prototype.indexOf":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar idx = arr.indexOf( 2.0 )\nidx = arr.indexOf( -1.0 )\n","Float64Array.prototype.join":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\narr.join( '|' )\n","Float64Array.prototype.keys":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Float64Array.prototype.lastIndexOf":"var arr = new Float64Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\nvar idx = arr.lastIndexOf( 2.0 )\nidx = arr.lastIndexOf( 0.0 )\n","Float64Array.prototype.map":"var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( v ) { return v * 2.0; };\nvar arr2 = arr1.map( fcn )\n","Float64Array.prototype.reduce":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0.0 )\n","Float64Array.prototype.reduceRight":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0.0 )\n","Float64Array.prototype.reverse":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] )\narr.reverse()\n","Float64Array.prototype.set":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\narr.set( [ -2.0, 2.0 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Float64Array.prototype.slice":"var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Float64Array.prototype.some":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\narr.some( predicate )\n","Float64Array.prototype.sort":"var arr = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\narr.sort()\n","Float64Array.prototype.subarray":"var arr1 = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\nvar arr2 = arr1.subarray( 2 )\n","Float64Array.prototype.toLocaleString":"var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\narr.toLocaleString()\n","Float64Array.prototype.toString":"var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\narr.toString()\n","Float64Array.prototype.values":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","forEach":"function logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4 ];\nforEach( arr, logger )\n","forEachAsync":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n     throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 3000, 2500, 1000 ];\nforEachAsync( arr, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n     throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nforEachAsync( arr, opts, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n     throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nforEachAsync( arr, opts, onDuration, done )\n","forEachAsync.factory":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next();\n }\n };\nvar opts = { 'series': true };\nvar f = forEachAsync.factory( opts, onDuration );\nfunction done( error ) {\n if ( error ) {\n     throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","forEachChar":"var n = 0;\nfunction fcn() { n += 1; };\nforEachChar( 'hello world!', fcn );\nn\n","forEachRight":"function logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4 ];\nforEachRight( arr, logger )\n","forEachRightAsync":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n     throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 1000, 2500, 3000 ];\nforEachRightAsync( arr, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n     throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nforEachRightAsync( arr, opts, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n     throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nforEachRightAsync( arr, opts, onDuration, done )\n","forEachRightAsync.factory":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next();\n }\n };\nvar opts = { 'series': true };\nvar f = forEachRightAsync.factory( opts, onDuration );\nfunction done( error ) {\n if ( error ) {\n     throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","forIn":"function logger( v, k ) { console.log( '%s: %d', k, v ); };\nfunction Foo() { return this; };\nFoo.prototype.beep = 'boop';\nvar obj = new Foo();\nforIn( obj, logger )\n","format":"var out = format( 'Hello, %s!', 'World' )\nout = format( '%s %s', 'Hello', 'World' )\nout = format( 'Pi: %.2f', PI )\n","forOwn":"function logger( v, k ) { console.log( '%s: %d', k, v ); };\nvar obj = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\nforOwn( obj, logger )\n","FOURTH_PI":"FOURTH_PI\n","FOURTH_ROOT_EPS":"FOURTH_ROOT_EPS\n","FRB_SF_WAGE_RIGIDITY":"var data = FRB_SF_WAGE_RIGIDITY()\n","fromCodePoint":"var out = fromCodePoint( 9731 )\nout = fromCodePoint( [ 9731 ] )\nout = fromCodePoint( 97, 98, 99 )\nout = fromCodePoint( [ 97, 98, 99 ] )\n","Function":"var f = new Function( 'x', 'y', 'return x + y' );\nf( 1, 2 )\n","Function.prototype.apply":"var f = new Function( 'x', 'y', 'return x + y' );\nf.apply( null, [ 1, 2 ] )\n","Function.prototype.call":"var f = new Function( 'x', 'y', 'return x + y' );\nf.call( null, 1, 2 )\n","Function.prototype.bind":"var f = new Function( 'x', 'y', 'return x + y' );\nvar g = f.bind( null, 1 );\ng( 2 )\n","Function.prototype.toString":"var f = new Function( 'x', 'y', 'return x + y' );\nf.toString()\n","Function.prototype.length":"var f = new Function( 'x', 'y', 'return x + y' );\nf.length\n","Function.prototype.name":"var f = new Function( 'x', 'y', 'return x + y' );\nf.name\nvar f = new Function( 'x', 'y', 'return x + y' );\nf.name = 'add';\nf.name\n","Function.prototype.prototype":"var f = new Function( 'x', 'y', 'return x + y' );\nf.prototype\n","function2string":"function2string( base.erf )\n","functionName":"var v = functionName( String )\nv = functionName( function foo(){} )\nv = functionName( function(){} )\n","functionSequence":"function a( x ) { return 2 * x; };\nfunction b( x ) { return x + 3; };\nfunction c( x ) { return x / 5; };\nvar f = functionSequence( a, b, c );\nvar z = f( 6 )\n","functionSequenceAsync":"function a( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n    next( null, 2*x );\n}\n };\nfunction b( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n    next( null, x+3 );\n}\n };\nfunction c( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n    next( null, x/5 );\n}\n };\nvar f = functionSequenceAsync( a, b, c );\nfunction done( error, result ) {\nif ( error ) {\n    throw error;\n}\nconsole.log( result );\n };\nf( 6, done )\n","GAMMA_LANCZOS_G":"GAMMA_LANCZOS_G\n","gdot":"var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\ngdot( x, y )\nx = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\ny = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\ngdot( x, y )\n","getegid":"var gid = getegid()\n","geteuid":"var uid = geteuid()\n","getgid":"var gid = getgid()\n","getGlobal":"var g = getGlobal()\n","getPrototypeOf":"var proto = getPrototypeOf( {} )\n","getuid":"var uid = getuid()\n","GLAISHER":"GLAISHER\n","graphemeClusters2iterator":"var it = graphemeClusters2iterator( '🌷🍕' );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","graphemeClusters2iteratorRight":"var it = graphemeClusters2iteratorRight( '🌷🍕' );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","group":"var collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar groups = [ 'b', 'b', 'f', 'b' ];\nvar out = group( collection, groups )\ngroups = [ 1, 1, 2, 1 ];\nout = group( collection, groups )\ngroups = [ 'b', 'b', 'f', 'b' ];\nvar opts = { 'returns': 'indices' };\nout = group( collection, opts, groups )\nopts = { 'returns': '*' };\nout = group( collection, opts, groups )\n","groupBy":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n     return 'b';\n }\n return 'other';\n };\nvar collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar out = groupBy( collection, indicator )\nvar opts = { 'returns': 'indices' };\nout = groupBy( collection, opts, indicator )\nopts = { 'returns': '*' };\nout = groupBy( collection, opts, indicator )\n","groupByAsync":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\ngroupByAsync( arr, indicator, done )\nvar opts = { 'returns': 'indices' };\ngroupByAsync( arr, opts, indicator, done )\nopts = { 'returns': '*' };\ngroupByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\ngroupByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\ngroupByAsync( arr, opts, indicator, done )\n","groupByAsync.factory":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) );\n }\n };\nvar opts = { 'series': true };\nvar f = groupByAsync.factory( opts, indicator );\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","groupIn":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n     return 'b';\n }\n return 'other';\n };\nfunction Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\nFoo.prototype = Object.create( null );\nFoo.prototype.c = 'foo';\nFoo.prototype.d = 'bar';\nvar obj = new Foo();\nvar out = groupIn( obj, indicator )\nvar opts = { 'returns': 'keys' };\nout = groupIn( obj, opts, indicator )\nopts = { 'returns': '*' };\nout = groupIn( obj, opts, indicator )\n","groupOwn":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n     return 'b';\n }\n return 'other';\n };\nvar obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\nvar out = groupOwn( obj, indicator )\nvar opts = { 'returns': 'keys' };\nout = groupOwn( obj, opts, indicator )\nopts = { 'returns': '*' };\nout = groupOwn( obj, opts, indicator )\n","gswap":"var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\ngswap( x, y );\nx.data\ny.data\nx = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\ny = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\ngswap( x, y );\nx\ny\n","HALF_LN2":"HALF_LN2\n","HALF_PI":"HALF_PI\n","HARRISON_BOSTON_HOUSE_PRICES":"var data = HARRISON_BOSTON_HOUSE_PRICES()\n","HARRISON_BOSTON_HOUSE_PRICES_CORRECTED":"var data = HARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n","hasArrayBufferSupport":"var bool = hasArrayBufferSupport()\n","hasArrowFunctionSupport":"var bool = hasArrowFunctionSupport()\n","hasAsyncAwaitSupport":"var bool = hasAsyncAwaitSupport()\n","hasAsyncIteratorSymbolSupport":"var bool = hasAsyncIteratorSymbolSupport()\n","hasAtobSupport":"var bool = hasAtobSupport()\n","hasBigInt64ArraySupport":"var bool = hasBigInt64ArraySupport()\n","hasBigIntSupport":"var bool = hasBigIntSupport()\n","hasBigUint64ArraySupport":"var bool = hasBigUint64ArraySupport()\n","hasBtoaSupport":"var bool = hasBtoaSupport()\n","hasClassSupport":"var bool = hasClassSupport()\n","hasDataViewSupport":"var bool = hasDataViewSupport()\n","hasDefinePropertiesSupport":"var bool = hasDefinePropertiesSupport()\n","hasDefinePropertySupport":"var bool = hasDefinePropertySupport()\n","hasFloat32ArraySupport":"var bool = hasFloat32ArraySupport()\n","hasFloat64ArraySupport":"var bool = hasFloat64ArraySupport()\n","hasFunctionNameSupport":"var bool = hasFunctionNameSupport()\n","hasGeneratorSupport":"var bool = hasGeneratorSupport()\n","hasGlobalThisSupport":"var bool = hasGlobalThisSupport()\n","hasInt8ArraySupport":"var bool = hasInt8ArraySupport()\n","hasInt16ArraySupport":"var bool = hasInt16ArraySupport()\n","hasInt32ArraySupport":"var bool = hasInt32ArraySupport()\n","hasIteratorSymbolSupport":"var bool = hasIteratorSymbolSupport()\n","hasMapSupport":"var bool = hasMapSupport()\n","hasNodeBufferSupport":"var bool = hasNodeBufferSupport()\n","hasOwnProp":"var beep = { 'boop': true };\nvar bool = hasOwnProp( beep, 'boop' )\nbool = hasOwnProp( beep, 'bop' )\n","hasProp":"var beep = { 'boop': true };\nvar bool = hasProp( beep, 'boop' )\nbool = hasProp( beep, 'toString' )\nbool = hasProp( beep, 'bop' )\n","hasProxySupport":"var bool = hasProxySupport()\n","hasSetSupport":"var bool = hasSetSupport()\n","hasSharedArrayBufferSupport":"var bool = hasSharedArrayBufferSupport()\n","hasSymbolSupport":"var bool = hasSymbolSupport()\n","hasToStringTagSupport":"var bool = hasToStringTagSupport()\n","hasUint8ArraySupport":"var bool = hasUint8ArraySupport()\n","hasUint8ClampedArraySupport":"var bool = hasUint8ClampedArraySupport()\n","hasUint16ArraySupport":"var bool = hasUint16ArraySupport()\n","hasUint32ArraySupport":"var bool = hasUint32ArraySupport()\n","hasUTF16SurrogatePairAt":"var out = hasUTF16SurrogatePairAt( '🌷', 0 )\nout = hasUTF16SurrogatePairAt( '🌷', 1 )\n","hasWeakMapSupport":"var bool = hasWeakMapSupport()\n","hasWeakSetSupport":"var bool = hasWeakSetSupport()\n","hasWebAssemblySupport":"var bool = hasWebAssemblySupport()\n","headercase":"var out = headercase( 'Hello World!' )\nout = headercase( 'beep boop' )\n","HERNDON_VENUS_SEMIDIAMETERS":"var d = HERNDON_VENUS_SEMIDIAMETERS()\n","homedir":"var home = homedir()\n","HOURS_IN_DAY":"var days = 3.14;\nvar hrs = days * HOURS_IN_DAY\n","HOURS_IN_WEEK":"var wks = 3.14;\nvar hrs = wks * HOURS_IN_WEEK\n","hoursInMonth":"var num = hoursInMonth()\nnum = hoursInMonth( 2 )\nnum = hoursInMonth( 2, 2016 )\nnum = hoursInMonth( 2, 2017 )\nnum = hoursInMonth( 'feb', 2016 )\nnum = hoursInMonth( 'february', 2016 )\n","hoursInYear":"var num = hoursInYear()\nnum = hoursInYear( 2016 )\nnum = hoursInYear( 2017 )\n","httpServer":"var createServer = httpServer()\nfunction onRequest( request, response ) {\nconsole.log( request.url );\nresponse.end( 'OK' );\n };\ncreateServer = httpServer( onRequest )\nvar opts = { 'port': 7331 };\ncreateServer = httpServer( opts )\n","identity":"var v = identity( 3.14 )\n","ifelse":"var z = ifelse( true, 1.0, -1.0 )\nz = ifelse( false, 1.0, -1.0 )\n","ifelseAsync":"function predicate( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n     clbk( null, true );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nifelseAsync( predicate, 'beep', 'boop', done )\n","ifthen":"function x() { return 1.0; };\nfunction y() { return -1.0; };\nvar z = ifthen( true, x, y )\nz = ifthen( false, x, y )\n","ifthenAsync":"function predicate( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n     clbk( null, false );\n }\n };\nfunction x( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n     clbk( null, 'beep' );\n }\n };\nfunction y( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n     clbk( null, 'boop' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nifthenAsync( predicate, x, y, done )\n","imag":"var z = new Complex128( 5.0, 3.0 );\nvar im = imag( z )\n","imagf":"var z = new Complex64( 5.0, 3.0 );\nvar im = imagf( z )\n","IMG_ACANTHUS_MOLLIS":"var img = IMG_ACANTHUS_MOLLIS()\n","IMG_AIRPLANE_FROM_ABOVE":"var img = IMG_AIRPLANE_FROM_ABOVE()\n","IMG_ALLIUM_OREOPHILUM":"var img = IMG_ALLIUM_OREOPHILUM()\n","IMG_BLACK_CANYON":"var img = IMG_BLACK_CANYON()\n","IMG_DUST_BOWL_HOME":"var img = IMG_DUST_BOWL_HOME()\n","IMG_FRENCH_ALPINE_LANDSCAPE":"var img = IMG_FRENCH_ALPINE_LANDSCAPE()\n","IMG_LOCOMOTION_HOUSE_CAT":"var img = IMG_LOCOMOTION_HOUSE_CAT()\n","IMG_LOCOMOTION_NUDE_MALE":"var img = IMG_LOCOMOTION_NUDE_MALE()\n","IMG_MARCH_PASTORAL":"var img = IMG_MARCH_PASTORAL()\n","IMG_NAGASAKI_BOATS":"var img = IMG_NAGASAKI_BOATS()\n","incrapcorr":"var accumulator = incrapcorr();\nvar ar = accumulator()\nar = accumulator( 2.0, 1.0 )\nar = accumulator( -5.0, 3.14 )\nar = accumulator()\n","incrBinaryClassification":"var opts = {};\nopts.intercept = true;\nopts.lambda = 1.0e-5;\nvar acc = incrBinaryClassification( 3, opts );\nvar buf = new Float64Array( [ 2.3, 1.0, 5.0 ] );\nvar x = array( buf );\nvar coefs = acc( x, 1 )\nbuf = new Float64Array( [ 2.3, 5.3, 8.6 ] );\nx = array( buf );\nvar yhat = acc.predict( x )\n","incrcount":"var accumulator = incrcount();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrcovariance":"var accumulator = incrcovariance();\nvar v = accumulator()\nv = accumulator( 2.0, 1.0 )\nv = accumulator( -5.0, 3.14 )\nv = accumulator()\n","incrcovmat":"var accumulator = incrcovmat( 2 );\nvar out = accumulator()\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v )\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v )\nout = accumulator()\n","incrcv":"var accumulator = incrcv();\nvar cv = accumulator()\ncv = accumulator( 2.0 )\ncv = accumulator( 1.0 )\ncv = accumulator()\n","increwmean":"var accumulator = increwmean( 0.5 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","increwstdev":"var accumulator = increwstdev( 0.5 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","increwvariance":"var accumulator = increwvariance( 0.5 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrgmean":"var accumulator = incrgmean();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrgrubbs":"var acc = incrgrubbs();\nvar res = acc()\nfor ( var i = 0; i < 200; i++ ) {\n res = acc( base.random.normal( 10.0, 5.0 ) );\n };\nres.print()\n","incrhmean":"var accumulator = incrhmean();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrkmeans":"var accumulator = incrkmeans( 5, 2 );\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v );\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v );\n","incrkurtosis":"var accumulator = incrkurtosis();\nvar v = accumulator( 2.0 )\nv = accumulator( 2.0 )\nv = accumulator( -4.0 )\nv = accumulator( -4.0 )\n","incrmaape":"var accumulator = incrmaape();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator()\n","incrmae":"var accumulator = incrmae();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator()\n","incrmapcorr":"var accumulator = incrmapcorr( 3 );\nvar ar = accumulator()\nar = accumulator( 2.0, 1.0 )\nar = accumulator( -5.0, 3.14 )\nar = accumulator( 3.0, -1.0 )\nar = accumulator( 5.0, -9.5 )\nar = accumulator()\n","incrmape":"var accumulator = incrmape();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator()\n","incrmax":"var accumulator = incrmax();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrmaxabs":"var accumulator = incrmaxabs();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrmcovariance":"var accumulator = incrmcovariance( 3 );\nvar v = accumulator()\nv = accumulator( 2.0, 1.0 )\nv = accumulator( -5.0, 3.14 )\nv = accumulator( 3.0, -1.0 )\nv = accumulator( 5.0, -9.5 )\nv = accumulator()\n","incrmcv":"var accumulator = incrmcv( 3 );\nvar cv = accumulator()\ncv = accumulator( 2.0 )\ncv = accumulator( 1.0 )\ncv = accumulator( 3.0 )\ncv = accumulator( 7.0 )\ncv = accumulator()\n","incrmda":"var accumulator = incrmda();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 4.0 )\nm = accumulator()\n","incrme":"var accumulator = incrme();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator()\n","incrmean":"var accumulator = incrmean();\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator()\n","incrmeanabs":"var accumulator = incrmeanabs();\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator()\n","incrmeanabs2":"var accumulator = incrmeanabs2();\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator()\n","incrmeanstdev":"var accumulator = incrmeanstdev();\nvar ms = accumulator()\nms = accumulator( 2.0 )\nms = accumulator( -5.0 )\nms = accumulator( 3.0 )\nms = accumulator( 5.0 )\nms = accumulator()\n","incrmeanvar":"var accumulator = incrmeanvar();\nvar mv = accumulator()\nmv = accumulator( 2.0 )\nmv = accumulator( -5.0 )\nmv = accumulator( 3.0 )\nmv = accumulator( 5.0 )\nmv = accumulator()\n","incrmgmean":"var accumulator = incrmgmean( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmgrubbs":"var acc = incrmgrubbs( 20 );\nvar res = acc()\nfor ( var i = 0; i < 200; i++ ) {\n res = acc( base.random.normal( 10.0, 5.0 ) );\n };\nres.print()\n","incrmhmean":"var accumulator = incrmhmean( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmidrange":"var accumulator = incrmidrange();\nvar v = accumulator()\nv = accumulator( 3.14 )\nv = accumulator( -5.0 )\nv = accumulator( 10.1 )\nv = accumulator()\n","incrmin":"var accumulator = incrmin();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrminabs":"var accumulator = incrminabs();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrminmax":"var accumulator = incrminmax();\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrminmaxabs":"var accumulator = incrminmaxabs();\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrmmaape":"var accumulator = incrmmaape( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 2.0, 5.0 )\nm = accumulator()\n","incrmmae":"var accumulator = incrmmae( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 5.0, -2.0 )\nm = accumulator()\n","incrmmape":"var accumulator = incrmmape( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 2.0, 5.0 )\nm = accumulator()\n","incrmmax":"var accumulator = incrmmax( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmmaxabs":"var accumulator = incrmmaxabs( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmmda":"var accumulator = incrmmda( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 4.0, 5.0 )\nm = accumulator()\n","incrmme":"var accumulator = incrmme( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 5.0, -2.0 )\nm = accumulator()\n","incrmmean":"var accumulator = incrmmean( 3 );\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator( 3.0 )\nmu = accumulator( 5.0 )\nmu = accumulator()\n","incrmmeanabs":"var accumulator = incrmmeanabs( 3 );\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator( 3.0 )\nmu = accumulator( 5.0 )\nmu = accumulator()\n","incrmmeanabs2":"var accumulator = incrmmeanabs2( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmmeanstdev":"var accumulator = incrmmeanstdev( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmmeanvar":"var accumulator = incrmmeanvar( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmmidrange":"var accumulator = incrmmidrange( 3 );\nvar mr = accumulator()\nmr = accumulator( 2.0 )\nmr = accumulator( -5.0 )\nmr = accumulator( 3.0 )\nmr = accumulator( 5.0 )\nmr = accumulator()\n","incrmmin":"var accumulator = incrmmin( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmminabs":"var accumulator = incrmminabs( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmminmax":"var accumulator = incrmminmax( 3 );\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrmminmaxabs":"var accumulator = incrmminmaxabs( 3 );\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrmmpe":"var accumulator = incrmmpe( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 2.0, 5.0 )\nm = accumulator()\n","incrmmse":"var accumulator = incrmmse( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 5.0, -2.0 )\nm = accumulator()\n","incrmpcorr":"var accumulator = incrmpcorr( 3 );\nvar r = accumulator()\nr = accumulator( 2.0, 1.0 )\nr = accumulator( -5.0, 3.14 )\nr = accumulator( 3.0, -1.0 )\nr = accumulator( 5.0, -9.5 )\nr = accumulator()\n","incrmpcorr2":"var accumulator = incrmpcorr2( 3 );\nvar r2 = accumulator()\nr2 = accumulator( 2.0, 1.0 )\nr2 = accumulator( -5.0, 3.14 )\nr2 = accumulator( 3.0, -1.0 )\nr2 = accumulator( 5.0, -9.5 )\nr2 = accumulator()\n","incrmpcorrdist":"var accumulator = incrmpcorrdist( 3 );\nvar d = accumulator()\nd = accumulator( 2.0, 1.0 )\nd = accumulator( -5.0, 3.14 )\nd = accumulator( 3.0, -1.0 )\nd = accumulator( 5.0, -9.5 )\nd = accumulator()\n","incrmpe":"var accumulator = incrmpe();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator()\n","incrmprod":"var accumulator = incrmprod( 3 );\nvar p = accumulator()\np = accumulator( 2.0 )\np = accumulator( -5.0 )\np = accumulator( 3.0 )\np = accumulator( 5.0 )\np = accumulator()\n","incrmrange":"var accumulator = incrmrange( 3 );\nvar r = accumulator()\nr = accumulator( 2.0 )\nr = accumulator( -5.0 )\nr = accumulator( 3.0 )\nr = accumulator( 5.0 )\nr = accumulator()\n","incrmrmse":"var accumulator = incrmrmse( 3 );\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator( 3.0, 2.0 )\nr = accumulator( 5.0, -2.0 )\nr = accumulator()\n","incrmrss":"var accumulator = incrmrss( 3 );\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator( 3.0, 2.0 )\nr = accumulator( 5.0, -2.0 )\nr = accumulator()\n","incrmse":"var accumulator = incrmse();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator()\n","incrmstdev":"var accumulator = incrmstdev( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( 5.0 )\ns = accumulator()\n","incrmsum":"var accumulator = incrmsum( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( 5.0 )\ns = accumulator()\n","incrmsumabs":"var accumulator = incrmsumabs( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrmsumabs2":"var accumulator = incrmsumabs2( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrmsummary":"var accumulator = incrmsummary( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrmsumprod":"var accumulator = incrmsumprod( 3 );\nvar s = accumulator()\ns = accumulator( 2.0, 3.0 )\ns = accumulator( -5.0, 2.0 )\ns = accumulator( 3.0, -2.0 )\ns = accumulator( 5.0, 3.0 )\ns = accumulator()\n","incrmvariance":"var accumulator = incrmvariance( 3 );\nvar s2 = accumulator()\ns2 = accumulator( 2.0 )\ns2 = accumulator( -5.0 )\ns2 = accumulator( 3.0 )\ns2 = accumulator( 5.0 )\ns2 = accumulator()\n","incrmvmr":"var accumulator = incrmvmr( 3 );\nvar F = accumulator()\nF = accumulator( 2.0 )\nF = accumulator( 1.0 )\nF = accumulator( 3.0 )\nF = accumulator( 7.0 )\nF = accumulator()\n","incrnancount":"var accumulator = incrnancount();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrnansum":"var accumulator = incrnansum();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( NaN )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrnansumabs":"var accumulator = incrnansumabs();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( NaN )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrnansumabs2":"var accumulator = incrnansumabs2();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( NaN )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrpcorr":"var accumulator = incrpcorr();\nvar r = accumulator()\nr = accumulator( 2.0, 1.0 )\nr = accumulator( -5.0, 3.14 )\nr = accumulator()\n","incrpcorr2":"var accumulator = incrpcorr2();\nvar r2 = accumulator()\nr2 = accumulator( 2.0, 1.0 )\nr2 = accumulator( -5.0, 3.14 )\nr2 = accumulator()\n","incrpcorrdist":"var accumulator = incrpcorrdist();\nvar d = accumulator()\nd = accumulator( 2.0, 1.0 )\nd = accumulator( -5.0, 3.14 )\nd = accumulator()\n","incrpcorrdistmat":"var accumulator = incrpcorrdistmat( 2 );\nvar out = accumulator()\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v )\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v )\nout = accumulator()\n","incrpcorrmat":"var accumulator = incrpcorrmat( 2 );\nvar out = accumulator()\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v )\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v )\nout = accumulator()\n","incrprod":"var accumulator = incrprod();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrrange":"var accumulator = incrrange();\nvar v = accumulator()\nv = accumulator( -2.0 )\nv = accumulator( 1.0 )\nv = accumulator( 3.0 )\nv = accumulator()\n","incrrmse":"var accumulator = incrrmse();\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator()\n","incrrss":"var accumulator = incrrss();\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator()\n","incrskewness":"var accumulator = incrskewness();\nvar v = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator( -10.0 )\nv = accumulator()\n","incrspace":"var arr = incrspace( 0, 11, 2 )\n","incrstdev":"var accumulator = incrstdev();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsum":"var accumulator = incrsum();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsumabs":"var accumulator = incrsumabs();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsumabs2":"var accumulator = incrsumabs2();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsummary":"var accumulator = incrsummary();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsumprod":"var accumulator = incrsumprod();\nvar s = accumulator()\ns = accumulator( 2.0, 3.0 )\ns = accumulator( -5.0, 2.0 )\ns = accumulator()\n","incrvariance":"var accumulator = incrvariance();\nvar s2 = accumulator()\ns2 = accumulator( 2.0 )\ns2 = accumulator( -5.0 )\ns2 = accumulator()\n","incrvmr":"var accumulator = incrvmr();\nvar D = accumulator()\nD = accumulator( 2.0 )\nD = accumulator( 1.0 )\nD = accumulator()\n","incrwmean":"var accumulator = incrwmean();\nvar mu = accumulator()\nmu = accumulator( 2.0, 1.0 )\nmu = accumulator( 2.0, 0.5 )\nmu = accumulator( 3.0, 1.5 )\nmu = accumulator()\n","ind2sub":"var d = [ 3, 3, 3 ];\nvar s = ind2sub( d, 17 )\n","ind2sub.assign":"var d = [ 3, 3, 3 ];\nvar out = [ 0, 0, 0 ];\nvar s = ind2sub.assign( d, 17, out )\nvar bool = ( s === out )\n","indexOf":"var arr = [ 4, 3, 2, 1 ];\nvar idx = indexOf( arr, 3 )\narr = [ 4, 3, 2, 1 ];\nidx = indexOf( arr, 5 )\narr = [ 1, 2, 3, 4, 5, 2, 6 ];\nidx = indexOf( arr, 2, 3 )\narr = [ 1, 2, 3, 4, 2, 5 ];\nidx = indexOf( arr, 2, 10 )\narr = [ 1, 2, 3, 4, 5, 2, 6, 2 ];\nidx = indexOf( arr, 2, -4 )\nidx = indexOf( arr, 2, -1 )\narr = [ 1, 2, 3, 4, 5, 2, 6 ];\nidx = indexOf( arr, 2, -10 )\nvar str = 'bebop';\nidx = indexOf( str, 'o' )\n","inherit":"function Foo() { return this; };\nFoo.prototype.beep = function beep() { return 'boop'; };\nfunction Bar() { Foo.call( this ); return this; };\ninherit( Bar, Foo );\nvar bar = new Bar();\nvar v = bar.beep()\n","inheritedEnumerableProperties":"var props = inheritedEnumerableProperties( {} )\n","inheritedEnumerablePropertySymbols":"var symbols = inheritedEnumerablePropertySymbols( [] )\n","inheritedKeys":"var keys = inheritedKeys( {} )\n","inheritedNonEnumerableProperties":"var props = inheritedNonEnumerableProperties( {} )\n","inheritedNonEnumerablePropertyNames":"var keys = inheritedNonEnumerablePropertyNames( {} )\n","inheritedNonEnumerablePropertySymbols":"var symbols = inheritedNonEnumerablePropertySymbols( [] )\n","inheritedProperties":"var symbols = inheritedProperties( [] )\n","inheritedPropertyDescriptor":"var desc = inheritedPropertyDescriptor( {}, 'toString' )\n","inheritedPropertyDescriptors":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar desc = inheritedPropertyDescriptors( obj )\n","inheritedPropertyNames":"var keys = inheritedPropertyNames( [] )\n","inheritedPropertySymbols":"var symbols = inheritedPropertySymbols( [] )\n","inheritedWritableProperties":"var props = inheritedWritableProperties( {} )\n","inheritedWritablePropertyNames":"var keys = inheritedWritablePropertyNames( {} )\n","inheritedWritablePropertySymbols":"var symbols = inheritedWritablePropertySymbols( [] )\n","inmap":"function foo( v, i ) { return v * i; };\nvar arr = [ 1.0, 2.0, 3.0 ];\nvar out = inmap( arr, foo )\nvar bool = ( out === arr )\n","inmapAsync":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n     throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 3000, 2500, 1000 ];\ninmapAsync( arr, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n     throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\ninmapAsync( arr, opts, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n     throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\ninmapAsync( arr, opts, fcn, done )\n","inmapAsync.factory":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, value*index );\n }\n };\nvar opts = { 'series': true };\nvar f = inmapAsync.factory( opts, fcn );\nfunction done( error, collection ) {\n if ( error ) {\n     throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","inmapRight":"function foo( v, i ) { console.log( '%s: %d', i, v ); return v * i; };\nvar arr = [ 1.0, 2.0, 3.0 ];\nvar out = inmapRight( arr, foo )\nvar bool = ( out === arr )\n","inmapRightAsync":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n     throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 1000, 2500, 3000 ];\ninmapRightAsync( arr, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n     throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\ninmapRightAsync( arr, opts, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n     throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\ninmapRightAsync( arr, opts, fcn, done )\n","inmapRightAsync.factory":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, value*index );\n }\n };\nvar opts = { 'series': true };\nvar f = inmapRightAsync.factory( opts, fcn );\nfunction done( error, collection ) {\n if ( error ) {\n     throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","inspectSinkStream":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectSinkStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectSinkStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = inspectSinkStream.factory( opts );\nfunction clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = createStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectSinkStream.objectMode":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectSinkStream.objectMode( clbk );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","inspectStream":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = inspectStream.factory( opts );\nfunction clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = createStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectStream.objectMode":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectStream.objectMode( clbk );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","instanceOf":"var bool = instanceOf( [], Array )\nbool = instanceOf( {}, Object )\nbool = instanceOf( null, Object )\n","INT8_MAX":"INT8_MAX\n","INT8_MIN":"INT8_MIN\n","INT8_NUM_BYTES":"INT8_NUM_BYTES\n","Int8Array":"var arr = new Int8Array()\nvar arr = new Int8Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Int8Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Int8Array( arr1 )\nvar buf = new ArrayBuffer( 4 );\nvar arr = new Int8Array( buf, 0, 4 )\n","Int8Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Int8Array.from( [ 1, 2 ], mapFcn )\n","Int8Array.of":"var arr = Int8Array.of( 1, 2 )\n","Int8Array.BYTES_PER_ELEMENT":"Int8Array.BYTES_PER_ELEMENT\n","Int8Array.name":"Int8Array.name\n","Int8Array.prototype.buffer":"var arr = new Int8Array( 5 );\narr.buffer\n","Int8Array.prototype.byteLength":"var arr = new Int8Array( 5 );\narr.byteLength\n","Int8Array.prototype.byteOffset":"var arr = new Int8Array( 5 );\narr.byteOffset\n","Int8Array.prototype.BYTES_PER_ELEMENT":"var arr = new Int8Array( 5 );\narr.BYTES_PER_ELEMENT\n","Int8Array.prototype.length":"var arr = new Int8Array( 5 );\narr.length\n","Int8Array.prototype.copyWithin":"var arr = new Int8Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Int8Array.prototype.entries":"var arr = new Int8Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Int8Array.prototype.every":"var arr = new Int8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Int8Array.prototype.fill":"var arr = new Int8Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Int8Array.prototype.filter":"var arr1 = new Int8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Int8Array.prototype.find":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Int8Array.prototype.findIndex":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Int8Array.prototype.forEach":"var arr = new Int8Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Int8Array.prototype.includes":"var arr = new Int8Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Int8Array.prototype.indexOf":"var arr = new Int8Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Int8Array.prototype.join":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Int8Array.prototype.keys":"var arr = new Int8Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Int8Array.prototype.lastIndexOf":"var arr = new Int8Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Int8Array.prototype.map":"var arr1 = new Int8Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Int8Array.prototype.reduce":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Int8Array.prototype.reduceRight":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Int8Array.prototype.reverse":"var arr = new Int8Array( [ 1, 2, 3 ] )\narr.reverse()\n","Int8Array.prototype.set":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Int8Array.prototype.slice":"var arr1 = new Int8Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Int8Array.prototype.some":"var arr = new Int8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Int8Array.prototype.sort":"var arr = new Int8Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Int8Array.prototype.subarray":"var arr1 = new Int8Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Int8Array.prototype.toLocaleString":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Int8Array.prototype.toString":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.toString()\n","Int8Array.prototype.values":"var arr = new Int8Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","INT16_MAX":"INT16_MAX\n","INT16_MIN":"INT16_MIN\n","INT16_NUM_BYTES":"INT16_NUM_BYTES\n","Int16Array":"var arr = new Int16Array()\nvar arr = new Int16Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Int16Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Int16Array( arr1 )\nvar buf = new ArrayBuffer( 8 );\nvar arr = new Int16Array( buf, 0, 4 )\n","Int16Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Int16Array.from( [ 1, 2 ], mapFcn )\n","Int16Array.of":"var arr = Int16Array.of( 1, 2 )\n","Int16Array.BYTES_PER_ELEMENT":"Int16Array.BYTES_PER_ELEMENT\n","Int16Array.name":"Int16Array.name\n","Int16Array.prototype.buffer":"var arr = new Int16Array( 5 );\narr.buffer\n","Int16Array.prototype.byteLength":"var arr = new Int16Array( 5 );\narr.byteLength\n","Int16Array.prototype.byteOffset":"var arr = new Int16Array( 5 );\narr.byteOffset\n","Int16Array.prototype.BYTES_PER_ELEMENT":"var arr = new Int16Array( 5 );\narr.BYTES_PER_ELEMENT\n","Int16Array.prototype.length":"var arr = new Int16Array( 5 );\narr.length\n","Int16Array.prototype.copyWithin":"var arr = new Int16Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Int16Array.prototype.entries":"var arr = new Int16Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Int16Array.prototype.every":"var arr = new Int16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Int16Array.prototype.fill":"var arr = new Int16Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Int16Array.prototype.filter":"var arr1 = new Int16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Int16Array.prototype.find":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Int16Array.prototype.findIndex":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Int16Array.prototype.forEach":"var arr = new Int16Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Int16Array.prototype.includes":"var arr = new Int16Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Int16Array.prototype.indexOf":"var arr = new Int16Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Int16Array.prototype.join":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Int16Array.prototype.keys":"var arr = new Int16Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Int16Array.prototype.lastIndexOf":"var arr = new Int16Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Int16Array.prototype.map":"var arr1 = new Int16Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Int16Array.prototype.reduce":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Int16Array.prototype.reduceRight":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Int16Array.prototype.reverse":"var arr = new Int16Array( [ 1, 2, 3 ] )\narr.reverse()\n","Int16Array.prototype.set":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Int16Array.prototype.slice":"var arr1 = new Int16Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Int16Array.prototype.some":"var arr = new Int16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Int16Array.prototype.sort":"var arr = new Int16Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Int16Array.prototype.subarray":"var arr1 = new Int16Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Int16Array.prototype.toLocaleString":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Int16Array.prototype.toString":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.toString()\n","Int16Array.prototype.values":"var arr = new Int16Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","INT32_MAX":"INT32_MAX\n","INT32_MIN":"INT32_MIN\n","INT32_NUM_BYTES":"INT32_NUM_BYTES\n","Int32Array":"var arr = new Int32Array()\nvar arr = new Int32Array( 5 )\nvar arr1 = new Int16Array( [ 5, 5, 5 ] );\nvar arr2 = new Int32Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Int32Array( arr1 )\nvar buf = new ArrayBuffer( 16 );\nvar arr = new Int32Array( buf, 0, 4 )\n","Int32Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Int32Array.from( [ 1, 2 ], mapFcn )\n","Int32Array.of":"var arr = Int32Array.of( 1, 2 )\n","Int32Array.BYTES_PER_ELEMENT":"Int32Array.BYTES_PER_ELEMENT\n","Int32Array.name":"Int32Array.name\n","Int32Array.prototype.buffer":"var arr = new Int32Array( 5 );\narr.buffer\n","Int32Array.prototype.byteLength":"var arr = new Int32Array( 5 );\narr.byteLength\n","Int32Array.prototype.byteOffset":"var arr = new Int32Array( 5 );\narr.byteOffset\n","Int32Array.prototype.BYTES_PER_ELEMENT":"var arr = new Int32Array( 5 );\narr.BYTES_PER_ELEMENT\n","Int32Array.prototype.length":"var arr = new Int32Array( 5 );\narr.length\n","Int32Array.prototype.copyWithin":"var arr = new Int32Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Int32Array.prototype.entries":"var arr = new Int32Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Int32Array.prototype.every":"var arr = new Int32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Int32Array.prototype.fill":"var arr = new Int32Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Int32Array.prototype.filter":"var arr1 = new Int32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Int32Array.prototype.find":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Int32Array.prototype.findIndex":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Int32Array.prototype.forEach":"var arr = new Int32Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Int32Array.prototype.includes":"var arr = new Int32Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Int32Array.prototype.indexOf":"var arr = new Int32Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Int32Array.prototype.join":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Int32Array.prototype.keys":"var arr = new Int32Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Int32Array.prototype.lastIndexOf":"var arr = new Int32Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Int32Array.prototype.map":"var arr1 = new Int32Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Int32Array.prototype.reduce":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Int32Array.prototype.reduceRight":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Int32Array.prototype.reverse":"var arr = new Int32Array( [ 1, 2, 3 ] )\narr.reverse()\n","Int32Array.prototype.set":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Int32Array.prototype.slice":"var arr1 = new Int32Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Int32Array.prototype.some":"var arr = new Int32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Int32Array.prototype.sort":"var arr = new Int32Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Int32Array.prototype.subarray":"var arr1 = new Int32Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Int32Array.prototype.toLocaleString":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Int32Array.prototype.toString":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.toString()\n","Int32Array.prototype.values":"var arr = new Int32Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","IS_BIG_ENDIAN":"IS_BIG_ENDIAN\n","IS_BROWSER":"IS_BROWSER\n","IS_DARWIN":"IS_DARWIN\n","IS_DOCKER":"IS_DOCKER\n","IS_ELECTRON":"IS_ELECTRON\n","IS_ELECTRON_MAIN":"IS_ELECTRON_MAIN\n","IS_ELECTRON_RENDERER":"IS_ELECTRON_RENDERER\n","IS_LITTLE_ENDIAN":"IS_LITTLE_ENDIAN\n","IS_MOBILE":"IS_MOBILE\n","IS_NODE":"IS_NODE\n","IS_TOUCH_DEVICE":"IS_TOUCH_DEVICE\n","IS_WEB_WORKER":"IS_WEB_WORKER\n","IS_WINDOWS":"IS_WINDOWS\n","isAbsoluteHttpURI":"var bool = isAbsoluteHttpURI( 'http://example.com/' )\nbool = isAbsoluteHttpURI( 'example.com' )\nbool = isAbsoluteHttpURI( 'foo@bar.com' )\n","isAbsolutePath":"var bool = isAbsolutePath( 'C:\\\\foo\\\\bar\\\\baz' )\nbool = isAbsolutePath( '/foo/bar/baz' )\n","isAbsolutePath.posix":"var bool = isAbsolutePath.posix( '/foo/bar/baz' )\nbool = isAbsolutePath.posix( 'foo/bar/baz' )\n","isAbsolutePath.win32":"var bool = isAbsolutePath.win32( 'C:\\\\foo\\\\bar\\\\baz' )\nbool = isAbsolutePath.win32( 'foo\\\\bar\\\\baz' )\n","isAbsoluteURI":"var bool = isAbsoluteURI( 'http://example.com/' )\nbool = isAbsoluteURI( 'example.com' )\nbool = isAbsoluteURI( 'foo@bar.com' )\n","isAccessorArray":"var bool = isAccessorArray( new Complex64Array( 10 ) )\nbool = isAccessorArray( [] )\nbool = isAccessorArray( { 'length': 0 } )\nbool = isAccessorArray( {} )\n","isAccessorProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isAccessorProperty( obj, 'boop' )\nbool = isAccessorProperty( obj, 'beep' )\n","isAccessorPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isAccessorPropertyIn( obj, 'boop' )\nbool = isAccessorPropertyIn( obj, 'beep' )\n","isAlphagram":"var out = isAlphagram( 'beep' )\nout = isAlphagram( 'zba' )\nout = isAlphagram( '' )\n","isAlphaNumeric":"var bool = isAlphaNumeric( 'abc0123456789' )\nbool = isAlphaNumeric( 'abcdef' )\nbool = isAlphaNumeric( '0xff' )\nbool = isAlphaNumeric( '' )\n","isAnagram":"var str1 = 'I am a weakish speller';\nvar str2 = 'William Shakespeare';\nvar bool = isAnagram( str1, str2 )\nbool = isAnagram( 'bat', 'tabba' )\n","isArguments":"function foo() { return arguments; };\nvar bool = isArguments( foo() )\nbool = isArguments( [] )\n","isArray":"var bool = isArray( [] )\nbool = isArray( {} )\n","isArrayArray":"var bool = isArrayArray( [ [], [] ] )\nbool = isArrayArray( [ {}, {} ] )\nbool = isArrayArray( [] )\n","isArrayBuffer":"var bool = isArrayBuffer( new ArrayBuffer( 10 ) )\nbool = isArrayBuffer( [] )\n","isArrayBufferView":"var bool = isArrayBufferView( new Int8Array() )\nbool = isArrayBufferView( [] )\n","isArrayLength":"var bool = isArrayLength( 5 )\nbool = isArrayLength( 2.0e200 )\nbool = isArrayLength( -3.14 )\nbool = isArrayLength( null )\n","isArrayLike":"var bool = isArrayLike( [] )\nbool = isArrayLike( { 'length': 10 } )\nbool = isArrayLike( 'beep' )\nbool = isArrayLike( null )\n","isArrayLikeObject":"var bool = isArrayLikeObject( [] )\nbool = isArrayLikeObject( { 'length': 10 } )\nbool = isArrayLikeObject( 'beep' )\n","isArrowFunction":"function beep() {};\nvar bool = isArrowFunction( beep )\nbool = isArrowFunction( {} )\n","isASCII":"var str = 'beep boop';\nvar bool = isASCII( str )\nbool = isASCII( fromCodePoint( 130 ) )\n","isBetween":"var bool = isBetween( 3.14, 3.0, 4.0 )\nbool = isBetween( 3.0, 3.0, 4.0 )\nbool = isBetween( 4.0, 3.0, 4.0 )\nbool = isBetween( 3.0, 3.14, 4.0 )\nbool = isBetween( 3.14, 3.14, 4.0, 'open', 'closed' )\nbool = isBetween( 3.14, 3.0, 3.14, 'closed', 'open' )\n","isBetweenArray":"var arr = [ 3.0, 3.14, 4.0 ];\nvar bool = isBetweenArray( arr, 3.0, 4.0 )\nbool = isBetweenArray( arr, 3.14, 4.0 )\nbool = isBetweenArray( arr, 3.0, 3.14 )\nbool = isBetweenArray( arr, 3.0, 4.0, 'open', 'closed' )\nbool = isBetweenArray( arr, 3.0, 4.0, 'closed', 'open' )\n","isBigInt":"var bool = isBigInt( BigInt( '1' ) )\nbool = isBigInt( Object( BigInt( '1' ) ) )\nbool = isBigInt( {} )\nbool = isBigInt( null )\nbool = isBigInt( true )\n","isBigInt64Array":"var bool = isBigInt64Array( new BigInt64Array( 10 ) )\nbool = isBigInt64Array( [] )\n","isBigUint64Array":"var bool = isBigUint64Array( new BigUint64Array( 10 ) )\nbool = isBigUint64Array( [] )\n","isBinaryString":"var bool = isBinaryString( '1000101' )\nbool = isBinaryString( 'beep' )\nbool = isBinaryString( '' )\n","isBlankString":"var bool = isBlankString( '   ' )\nbool = isBlankString( 'beep' )\nbool = isBlankString( null )\n","isBoolean":"var bool = isBoolean( false )\nbool = isBoolean( new Boolean( false ) )\n","isBoolean.isPrimitive":"var bool = isBoolean.isPrimitive( true )\nbool = isBoolean.isPrimitive( false )\nbool = isBoolean.isPrimitive( new Boolean( true ) )\n","isBoolean.isObject":"var bool = isBoolean.isObject( true )\nbool = isBoolean.isObject( new Boolean( false ) )\n","isBooleanArray":"var bool = isBooleanArray( [ true, false, true ] )\nbool = isBooleanArray( [ true, 'abc', false ] )\n","isBooleanArray.primitives":"var bool = isBooleanArray.primitives( [ true, false ] )\nbool = isBooleanArray.primitives( [ false, new Boolean( true ) ] )\n","isBooleanArray.objects":"var bool = isBooleanArray.objects( [ new Boolean( false ), true ] )\nbool = isBooleanArray.objects( [ new Boolean( false ), new Boolean( true ) ] )\n","isBoxedPrimitive":"var bool = isBoxedPrimitive( new Boolean( false ) )\nbool = isBoxedPrimitive( true )\n","isBuffer":"var bool = isBuffer( new Buffer( 'beep' ) )\nbool = isBuffer( new Buffer( [ 1, 2, 3, 4 ] ) )\nbool = isBuffer( {} )\nbool = isBuffer( [] )\n","isCamelcase":"var bool = isCamelcase( 'helloWorld' )\nbool = isCamelcase( 'hello world' )\n","isCapitalized":"var bool = isCapitalized( 'Hello' )\nbool = isCapitalized( 'world' )\n","isCentrosymmetricMatrix":"var buf = [ 2, 1, 1, 2 ];\nvar M = ndarray( 'generic', buf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\nvar bool = isCentrosymmetricMatrix( M )\nbool = isCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isCentrosymmetricMatrix( 3.14 )\nbool = isCentrosymmetricMatrix( {} )\n","isCircular":"var obj = { 'beep': 'boop' };\nobj.self = obj;\nvar bool = isCircular( obj )\nbool = isCircular( {} )\nbool = isCircular( null )\n","isCircularArray":"var arr = [ 1, 2, 3 ];\narr.push( arr );\nvar bool = isCircularArray( arr )\nbool = isCircularArray( [] )\nbool = isCircularArray( null )\n","isCircularPlainObject":"var obj = { 'beep': 'boop' };\nobj.self = obj;\nvar bool = isCircularPlainObject( obj )\nbool = isCircularPlainObject( {} )\nbool = isCircularPlainObject( null )\n","isClass":"var bool = isClass( class Person {} )\nbool = isClass( function Person() {} )\nbool = isClass( {} )\nbool = isClass( null )\nbool = isClass( true )\n","isCollection":"var bool = isCollection( [] )\nbool = isCollection( { 'length': 0 } )\nbool = isCollection( {} )\n","isComplex":"var bool = isComplex( new Complex64( 2.0, 2.0 ) )\nbool = isComplex( new Complex128( 3.0, 1.0 ) )\nbool = isComplex( 3.14 )\nbool = isComplex( {} )\n","isComplex64":"var bool = isComplex64( new Complex64( 2.0, 2.0 ) )\nbool = isComplex64( new Complex128( 3.0, 1.0 ) )\nbool = isComplex64( 3.14 )\nbool = isComplex64( {} )\n","isComplex64Array":"var bool = isComplex64Array( new Complex64Array( 10 ) )\nbool = isComplex64Array( [] )\n","isComplex64MatrixLike":"var M = {};\nM.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex64MatrixLike( M )\nbool = isComplex64MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isComplex64MatrixLike( 3.14 )\nbool = isComplex64MatrixLike( {} )\n","isComplex64ndarrayLike":"var M = {};\nM.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex64ndarrayLike( M )\nbool = isComplex64ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isComplex64ndarrayLike( 3.14 )\nbool = isComplex64ndarrayLike( {} )\n","isComplex64VectorLike":"var M = {};\nM.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex64VectorLike( M )\nbool = isComplex64VectorLike( [ 1, 2, 3, 4 ] )\nbool = isComplex64VectorLike( 3.14 )\nbool = isComplex64VectorLike( {} )\n","isComplex128":"var bool = isComplex128( new Complex128( 3.0, 1.0 ) )\nbool = isComplex128( new Complex64( 2.0, 2.0 ) )\nbool = isComplex128( 3.14 )\nbool = isComplex128( {} )\n","isComplex128Array":"var bool = isComplex128Array( new Complex128Array( 10 ) )\nbool = isComplex128Array( [] )\n","isComplex128MatrixLike":"var M = {};\nM.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex128';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex128MatrixLike( M )\nbool = isComplex128MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isComplex128MatrixLike( 3.14 )\nbool = isComplex128MatrixLike( {} )\n","isComplex128ndarrayLike":"var M = {};\nM.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex128';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex128ndarrayLike( M )\nbool = isComplex128ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isComplex128ndarrayLike( 3.14 )\nbool = isComplex128ndarrayLike( {} )\n","isComplex128VectorLike":"var M = {};\nM.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex128';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex128VectorLike( M )\nbool = isComplex128VectorLike( [ 1, 2, 3, 4 ] )\nbool = isComplex128VectorLike( 3.14 )\nbool = isComplex128VectorLike( {} )\n","isComplexLike":"var bool = isComplexLike( new Complex64( 2.0, 2.0 ) )\nbool = isComplexLike( new Complex128( 3.0, 1.0 ) )\nbool = isComplexLike( 3.14 )\nbool = isComplexLike( {} )\n","isComplexTypedArray":"var bool = isComplexTypedArray( new Complex64Array( 10 ) )\n","isComplexTypedArrayLike":"var bool = isComplexTypedArrayLike( new Complex128Array() )\nbool = isComplexTypedArrayLike({\n'length': 10,\n'byteOffset': 0,\n'byteLength': 10,\n'BYTES_PER_ELEMENT': 4,\n'get': function get() {},\n'set': function set() {}\n })\n","isComposite":"var bool = isComposite( 4.0 )\nbool = isComposite( new Number( 4.0 ) )\nbool = isComposite( 3.14 )\nbool = isComposite( -4.0 )\nbool = isComposite( null )\n","isComposite.isPrimitive":"var bool = isComposite.isPrimitive( 4.0 )\nbool = isComposite.isPrimitive( new Number( 4.0 ) )\n","isComposite.isObject":"var bool = isComposite.isObject( 4.0 )\nbool = isComposite.isObject( new Number( 4.0 ) )\n","isConfigurableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isConfigurableProperty( obj, 'boop' )\nbool = isConfigurableProperty( obj, 'beep' )\n","isConfigurablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isConfigurablePropertyIn( obj, 'boop' )\nbool = isConfigurablePropertyIn( obj, 'beep' )\n","isConstantcase":"var bool = isConstantcase( 'BEEP_BOOP' )\nbool = isConstantcase( 'BEEP and BOOP' )\n","isCubeNumber":"var bool = isCubeNumber( 8.0 )\nbool = isCubeNumber( new Number( 8.0 ) )\nbool = isCubeNumber( 3.14 )\nbool = isCubeNumber( -5.0 )\nbool = isCubeNumber( null )\n","isCubeNumber.isPrimitive":"var bool = isCubeNumber.isPrimitive( 8.0 )\nbool = isCubeNumber.isPrimitive( new Number( 8.0 ) )\n","isCubeNumber.isObject":"var bool = isCubeNumber.isObject( 8.0 )\nbool = isCubeNumber.isObject( new Number( 8.0 ) )\n","isCurrentYear":"var bool = isCurrentYear( new Date() )\nbool = isCurrentYear( currentYear() )\nbool = isCurrentYear( 2021 )\nbool = isCurrentYear( null )\n","isDataProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isDataProperty( obj, 'boop' )\nbool = isDataProperty( obj, 'beep' )\n","isDataPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isDataPropertyIn( obj, 'boop' )\nbool = isDataPropertyIn( obj, 'beep' )\n","isDataView":"var buf = new ArrayBuffer( 10 );\nvar bool = isDataView( new DataView( buf ) )\nbool = isDataView( [] )\n","isDateObject":"var bool = isDateObject( new Date() )\nbool = isDateObject( '2017-01-01' )\n","isDateObjectArray":"var bool = isDateObjectArray( [ new Date(), new Date() ] )\nbool = isDateObjectArray( [ {}, {} ] )\nbool = isDateObjectArray( [ new Date(), '2011-01-01' ] )\nbool = isDateObjectArray( [] )\n","isDigitString":"var bool = isDigitString( '0123456789' )\nbool = isDigitString( 'abcdef' )\nbool = isDigitString( '0xff' )\nbool = isDigitString( '' )\n","isDomainName":"var bool = isDomainName( 'example.com' )\nbool = isDomainName( 'foo@bar.com' )\n","isDurationString":"var bool = isDurationString( '1d' )\nbool = isDurationString( '1h' )\nbool = isDurationString( 'beep' )\n","isEmailAddress":"var bool = isEmailAddress( 'beep@boop.com' )\nbool = isEmailAddress( 'beep' )\nbool = isEmailAddress( null )\n","isEmptyArray":"var bool = isEmptyArray( [] )\nbool = isEmptyArray( [ 1, 2, 3 ] )\nbool = isEmptyArray( {} )\n","isEmptyArrayLikeObject":"var bool = isEmptyArrayLikeObject( [] )\nbool = isEmptyArrayLikeObject( { 'length': 0 } )\nbool = isEmptyArrayLikeObject( '' )\n","isEmptyCollection":"var bool = isEmptyCollection( [] )\nbool = isEmptyCollection( { 'length': 0 } )\nbool = isEmptyCollection( [ 1, 2, 3 ] )\nbool = isEmptyCollection( {} )\n","isEmptyObject":"var bool = isEmptyObject( {} )\nbool = isEmptyObject( { 'beep': 'boop' } )\nbool = isEmptyObject( [] )\n","isEmptyString":"var bool = isEmptyString( '' )\nbool = isEmptyString( new String( '' ) )\nbool = isEmptyString( 'beep' )\nbool = isEmptyString( [] )\n","isEmptyString.isPrimitive":"var bool = isEmptyString.isPrimitive( '' )\nbool = isEmptyString.isPrimitive( new String( '' ) )\n","isEmptyString.isObject":"var bool = isEmptyString.isObject( new String( '' ) )\nbool = isEmptyString.isObject( '' )\n","isEnumerableProperty":"var beep = { 'boop': true };\nvar bool = isEnumerableProperty( beep, 'boop' )\nbool = isEnumerableProperty( beep, 'hasOwnProperty' )\n","isEnumerablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = true;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isEnumerablePropertyIn( obj, 'boop' )\nbool = isEnumerablePropertyIn( obj, 'beep' )\n","isEqualArray":"var x = [ 1.0, 2.0, 3.0 ];\nvar y = [ 1.0, 2.0, 3.0 ];\nvar bool = isEqualArray( x, y )\nx = [ NaN, NaN, NaN ];\ny = [ NaN, NaN, NaN ];\nbool = isEqualArray( x, y )\n","isError":"var bool = isError( new Error( 'beep' ) )\nbool = isError( {} )\n","isEvalError":"var bool = isEvalError( new EvalError( 'beep' ) )\nbool = isEvalError( {} )\n","isEven":"var bool = isEven( 4.0 )\nbool = isEven( new Number( 4.0 ) )\nbool = isEven( 3.0 )\nbool = isEven( -3.14 )\nbool = isEven( null )\n","isEven.isPrimitive":"var bool = isEven.isPrimitive( -4.0 )\nbool = isEven.isPrimitive( new Number( -4.0 ) )\n","isEven.isObject":"var bool = isEven.isObject( 4.0 )\nbool = isEven.isObject( new Number( 4.0 ) )\n","isFalsy":"var bool = isFalsy( false )\nbool = isFalsy( '' )\nbool = isFalsy( 0 )\nbool = isFalsy( null )\nbool = isFalsy( void 0 )\nbool = isFalsy( NaN )\nbool = isFalsy( {} )\nbool = isFalsy( [] )\n","isFalsyArray":"var bool = isFalsyArray( [ null, '' ] )\nbool = isFalsyArray( [ {}, [] ] )\nbool = isFalsyArray( [] )\n","isFinite":"var bool = isFinite( 5.0 )\nbool = isFinite( new Number( 5.0 ) )\nbool = isFinite( 1.0/0.0 )\nbool = isFinite( null )\n","isFinite.isPrimitive":"var bool = isFinite.isPrimitive( -3.0 )\nbool = isFinite.isPrimitive( new Number( -3.0 ) )\n","isFinite.isObject":"var bool = isFinite.isObject( 3.0 )\nbool = isFinite.isObject( new Number( 3.0 ) )\n","isFiniteArray":"var bool = isFiniteArray( [ -3.0, new Number(0.0), 2.0 ] )\nbool = isFiniteArray( [ -3.0, 1.0/0.0 ] )\n","isFiniteArray.primitives":"var bool = isFiniteArray.primitives( [ -1.0, 10.0 ] )\nbool = isFiniteArray.primitives( [ -1.0, 0.0, 5.0 ] )\nbool = isFiniteArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isFiniteArray.objects":"var bool = isFiniteArray.objects( [ new Number(1.0), new Number(3.0) ] )\nbool = isFiniteArray.objects( [ -1.0, 0.0, 3.0 ] )\nbool = isFiniteArray.objects( [ 3.0, new Number(-1.0) ] )\n","isFloat32Array":"var bool = isFloat32Array( new Float32Array( 10 ) )\nbool = isFloat32Array( [] )\n","isFloat32MatrixLike":"var M = {};\nM.data = new Float32Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float32';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat32MatrixLike( M )\nbool = isFloat32MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isFloat32MatrixLike( 3.14 )\nbool = isFloat32MatrixLike( {} )\n","isFloat32ndarrayLike":"var M = {};\nM.data = new Float32Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float32';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat32ndarrayLike( M )\nbool = isFloat32ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isFloat32ndarrayLike( 3.14 )\nbool = isFloat32ndarrayLike( {} )\n","isFloat32VectorLike":"var M = {};\nM.data = new Float32Array( [ 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float32';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat32VectorLike( M )\nbool = isFloat32VectorLike( [ 1, 2, 3, 4 ] )\nbool = isFloat32VectorLike( 3.14 )\nbool = isFloat32VectorLike( {} )\n","isFloat64Array":"var bool = isFloat64Array( new Float64Array( 10 ) )\nbool = isFloat64Array( [] )\n","isFloat64MatrixLike":"var M = {};\nM.data = new Float64Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat64MatrixLike( M )\nbool = isFloat64MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isFloat64MatrixLike( 3.14 )\nbool = isFloat64MatrixLike( {} )\n","isFloat64ndarrayLike":"var M = {};\nM.data = new Float64Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat64ndarrayLike( M )\nbool = isFloat64ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isFloat64ndarrayLike( 3.14 )\nbool = isFloat64ndarrayLike( {} )\n","isFloat64VectorLike":"var M = {};\nM.data = new Float64Array( [ 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat64VectorLike( M )\nbool = isFloat64VectorLike( [ 1, 2, 3, 4 ] )\nbool = isFloat64VectorLike( 3.14 )\nbool = isFloat64VectorLike( {} )\n","isFunction":"function beep() {};\nvar bool = isFunction( beep )\nbool = isFunction( {} )\n","isFunctionArray":"function beep() {};\nfunction boop() {};\nvar bool = isFunctionArray( [ beep, boop ] )\nbool = isFunctionArray( [ {}, beep ] )\nbool = isFunctionArray( [] )\n","isGeneratorObject":"function* generateID() {\n var idx = 0;\n while ( idx < idx+1 ) {\n     yield idx;\n     idx += 1;\n }\n };\nvar bool = isGeneratorObject( generateID() )\nbool = isGeneratorObject( generateID )\nbool = isGeneratorObject( {} )\nbool = isGeneratorObject( null )\n","isGeneratorObjectLike":"var obj = {\n 'next': function noop() {},\n 'return': function noop() {},\n 'throw': function noop() {}\n };\nvar bool = isGeneratorObjectLike( obj )\nbool = isGeneratorObjectLike( {} )\nbool = isGeneratorObjectLike( null )\n","isgzipBuffer":"var buf = new Uint8Array( 20 );\nbuf[ 0 ] = 31;  // 0x1f => magic number\nbuf[ 1 ] = 139; // 0x8b\nbuf[ 2 ] = 8;   // 0x08 => compression method\nvar bool = isgzipBuffer( buf )\nbool = isgzipBuffer( [] )\n","isHexString":"var bool = isHexString( '0123456789abcdefABCDEF' )\nbool = isHexString( '0xffffff' )\nbool = isHexString( 'x' )\nbool = isHexString( '' )\n","isInfinite":"var bool = isInfinite( 1.0/0.0 )\nbool = isInfinite( new Number( -1.0/0.0 ) )\nbool = isInfinite( 5.0 )\nbool = isInfinite( '1.0/0.0' )\n","isInfinite.isPrimitive":"var bool = isInfinite.isPrimitive( -1.0/0.0 )\nbool = isInfinite.isPrimitive( new Number( -1.0/0.0 ) )\n","isInfinite.isObject":"var bool = isInfinite.isObject( 1.0/0.0 )\nbool = isInfinite.isObject( new Number( 1.0/0.0 ) )\n","isInheritedProperty":"var beep = { 'boop': true };\nvar bool = isInheritedProperty( beep, 'boop' )\nbool = isInheritedProperty( beep, 'toString' )\nbool = isInheritedProperty( beep, 'bop' )\n","isInt8Array":"var bool = isInt8Array( new Int8Array( 10 ) )\nbool = isInt8Array( [] )\n","isInt16Array":"var bool = isInt16Array( new Int16Array( 10 ) )\nbool = isInt16Array( [] )\n","isInt32Array":"var bool = isInt32Array( new Int32Array( 10 ) )\nbool = isInt32Array( [] )\n","isInteger":"var bool = isInteger( 5.0 )\nbool = isInteger( new Number( 5.0 ) )\nbool = isInteger( -3.14 )\nbool = isInteger( null )\n","isInteger.isPrimitive":"var bool = isInteger.isPrimitive( -3.0 )\nbool = isInteger.isPrimitive( new Number( -3.0 ) )\n","isInteger.isObject":"var bool = isInteger.isObject( 3.0 )\nbool = isInteger.isObject( new Number( 3.0 ) )\n","isIntegerArray":"var bool = isIntegerArray( [ -3.0, new Number(0.0), 2.0 ] )\nbool = isIntegerArray( [ -3.0, '3.0' ] )\n","isIntegerArray.primitives":"var bool = isIntegerArray.primitives( [ -1.0, 10.0 ] )\nbool = isIntegerArray.primitives( [ -1.0, 0.0, 5.0 ] )\nbool = isIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isIntegerArray.objects":"var bool = isIntegerArray.objects( [ new Number(1.0), new Number(3.0) ] )\nbool = isIntegerArray.objects( [ -1.0, 0.0, 3.0 ] )\nbool = isIntegerArray.objects( [ 3.0, new Number(-1.0) ] )\n","isIterableLike":"var bool = isIterableLike( [ 1, 2, 3 ] )\nbool = isIterableLike( {} )\nbool = isIterableLike( null )\n","isIteratorLike":"var obj = {\n 'next': function noop() {}\n };\nvar bool = isIteratorLike( obj )\nbool = isIteratorLike( {} )\nbool = isIteratorLike( null )\n","isJSON":"var bool = isJSON( '{\"a\":5}' )\nbool = isJSON( '{a\":5}' )\n","isKebabcase":"var bool = isKebabcase( 'beep-boop' )\nbool = isKebabcase( 'BEEP_BOOP' )\n","isLeapYear":"var bool = isLeapYear( new Date() )\nbool = isLeapYear( 1996 )\nbool = isLeapYear( 2001 )\n","isLocalhost":"var bool = isLocalhost( 'localhost' )\nbool = isLocalhost( '127.0.0.1' )\nbool = isLocalhost( 'stdlib.io' )\n","isLowercase":"var bool = isLowercase( 'hello' )\nbool = isLowercase( 'World' )\n","isMatrixLike":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isMatrixLike( M )\nbool = isMatrixLike( [ 1, 2, 3, 4 ] )\nbool = isMatrixLike( 3.14 )\nbool = isMatrixLike( {} )\n","isMethod":"var beep = { 'boop': function beep() { return 'beep'; } };\nvar bool = isMethod( beep, 'boop' )\nbool = isMethod( beep, 'toString' )\n","isMethodIn":"var beep = { 'boop': true };\nvar bool = isMethodIn( beep, 'toString' )\nbool = isMethodIn( beep, 'boop' )\nbool = isMethodIn( beep, 'bop' )\n","isMultiSlice":"var bool = isMultiSlice( new MultiSlice() )\nbool = isMultiSlice( 3.14 )\nbool = isMultiSlice( {} )\n","isNamedTypedTupleLike":"var Point = namedtypedtuple( [ 'x', 'y' ] );\nvar p = new Point();\nvar bool = isNamedTypedTupleLike( p )\nbool = isNamedTypedTupleLike( [ 1, 2, 3, 4 ] )\nbool = isNamedTypedTupleLike( 3.14 )\nbool = isNamedTypedTupleLike( {} )\n","isnan":"var bool = isnan( NaN )\nbool = isnan( new Number( NaN ) )\nbool = isnan( 3.14 )\nbool = isnan( null )\n","isnan.isPrimitive":"var bool = isnan.isPrimitive( NaN )\nbool = isnan.isPrimitive( 3.14 )\nbool = isnan.isPrimitive( new Number( NaN ) )\n","isnan.isObject":"var bool = isnan.isObject( NaN )\nbool = isnan.isObject( new Number( NaN ) )\n","isNaNArray":"var bool = isNaNArray( [ NaN, NaN, NaN ] )\nbool = isNaNArray( [ NaN, 2 ] )\n","isNaNArray.primitives":"var bool = isNaNArray.primitives( [ NaN, new Number( NaN ) ] )\nbool = isNaNArray.primitives( [ NaN, NaN, NaN ] )\n","isNaNArray.objects":"var bool = isNaNArray.objects( [ new Number( NaN ), new Number( NaN ) ] )\nbool = isNaNArray.objects( [ NaN, new Number( NaN ), new Number( NaN ) ] )\nbool = isNaNArray.objects( [ NaN, NaN, NaN ] )\n","isNativeFunction":"var bool = isNativeFunction( Date )\nfunction beep() {};\nbool = isNativeFunction( beep )\nbool = isNativeFunction( {} )\n","isndarrayLike":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isndarrayLike( M )\nbool = isndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isndarrayLike( 3.14 )\nbool = isndarrayLike( {} )\n","isndarrayLikeWithDataType":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isndarrayLikeWithDataType( M, 'generic' )\nbool = isndarrayLikeWithDataType( [ 1, 2, 3, 4 ], 'generic' )\nbool = isndarrayLikeWithDataType( 3.14, 'generic' )\nbool = isndarrayLikeWithDataType( {}, 'generic' )\n","isNegativeFinite":"var bool = isNegativeFinite( -5.0 )\nbool = isNegativeFinite( new Number( -5.0 ) )\nbool = isNegativeFinite( -3.14 )\nbool = isNegativeFinite( 5.0 )\nbool = isNegativeFinite( null )\nbool = isNegativeFinite( -1.0/0.0 )\nbool = isNegativeFinite( new Number( -1.0/0.0 ) )\n","isNegativeFinite.isPrimitive":"var bool = isNegativeFinite.isPrimitive( -3.0 )\nbool = isNegativeFinite.isPrimitive( new Number( -3.0 ) )\nvar bool = isNegativeFinite.isPrimitive( -1.0/0.0 )\nbool = isNegativeFinite.isPrimitive( new Number( -1.0/0.0 ) )\n","isNegativeFinite.isObject":"var bool = isNegativeFinite.isObject( -3.0 )\nbool = isNegativeFinite.isObject( new Number( -3.0 ) )\nbool = isNegativeFinite.isObject( -1.0/0.0 )\nbool = isNegativeFinite.isObject( new Number( -1.0/0.0 ) )\n","isNegativeInteger":"var bool = isNegativeInteger( -5.0 )\nbool = isNegativeInteger( new Number( -5.0 ) )\nbool = isNegativeInteger( 5.0 )\nbool = isNegativeInteger( -3.14 )\nbool = isNegativeInteger( null )\n","isNegativeInteger.isPrimitive":"var bool = isNegativeInteger.isPrimitive( -3.0 )\nbool = isNegativeInteger.isPrimitive( new Number( -3.0 ) )\n","isNegativeInteger.isObject":"var bool = isNegativeInteger.isObject( -3.0 )\nbool = isNegativeInteger.isObject( new Number( -3.0 ) )\n","isNegativeIntegerArray":"var bool = isNegativeIntegerArray( [ -3.0, new Number(-3.0) ] )\nbool = isNegativeIntegerArray( [ -3.0, '-3.0' ] )\n","isNegativeIntegerArray.primitives":"var bool = isNegativeIntegerArray.primitives( [ -1.0, -10.0 ] )\nbool = isNegativeIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNegativeIntegerArray.objects":"var bool = isNegativeIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNegativeIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNegativeNumber":"var bool = isNegativeNumber( -5.0 )\nbool = isNegativeNumber( new Number( -5.0 ) )\nbool = isNegativeNumber( -3.14 )\nbool = isNegativeNumber( 5.0 )\nbool = isNegativeNumber( null )\n","isNegativeNumber.isPrimitive":"var bool = isNegativeNumber.isPrimitive( -3.0 )\nbool = isNegativeNumber.isPrimitive( new Number( -3.0 ) )\n","isNegativeNumber.isObject":"var bool = isNegativeNumber.isObject( -3.0 )\nbool = isNegativeNumber.isObject( new Number( -3.0 ) )\n","isNegativeNumberArray":"var bool = isNegativeNumberArray( [ -3.0, new Number(-3.0) ] )\nbool = isNegativeNumberArray( [ -3.0, '-3.0' ] )\n","isNegativeNumberArray.primitives":"var bool = isNegativeNumberArray.primitives( [ -1.0, -10.0 ] )\nbool = isNegativeNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNegativeNumberArray.objects":"var bool = isNegativeNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNegativeNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNegativeZero":"var bool = isNegativeZero( -0.0 )\nbool = isNegativeZero( new Number( -0.0 ) )\nbool = isNegativeZero( -3.14 )\nbool = isNegativeZero( 0.0 )\nbool = isNegativeZero( null )\n","isNegativeZero.isPrimitive":"var bool = isNegativeZero.isPrimitive( -0.0 )\nbool = isNegativeZero.isPrimitive( new Number( -0.0 ) )\n","isNegativeZero.isObject":"var bool = isNegativeZero.isObject( -0.0 )\nbool = isNegativeZero.isObject( new Number( -0.0 ) )\n","isNodeBuiltin":"var bool = isNodeBuiltin( 'cluster' )\nbool = isNodeBuiltin( 'crypto' )\nbool = isNodeBuiltin( 'fs-extra' )\nbool = isNodeBuiltin( '' )\n","isNodeDuplexStreamLike":"var Stream = require( 'stream' ).Duplex;\ns = new Stream();\nvar bool = isNodeDuplexStreamLike( s )\nbool = isNodeDuplexStreamLike( {} )\n","isNodeReadableStreamLike":"var Stream = require( 'stream' ).Readable;\ns = new Stream();\nvar bool = isNodeReadableStreamLike( s )\nbool = isNodeReadableStreamLike( {} )\n","isNodeREPL":"var bool = isNodeREPL()\n","isNodeStreamLike":"var Stream = require( 'stream' ).Stream;\ns = new Stream();\nvar bool = isNodeStreamLike( s )\nbool = isNodeStreamLike( {} )\n","isNodeTransformStreamLike":"var Stream = require( 'stream' ).Transform;\ns = new Stream();\nvar bool = isNodeTransformStreamLike( s )\nbool = isNodeTransformStreamLike( {} )\n","isNodeWritableStreamLike":"var Stream = require( 'stream' ).Writable;\ns = new Stream();\nvar bool = isNodeWritableStreamLike( s )\nbool = isNodeWritableStreamLike( {} )\n","isNonConfigurableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonConfigurableProperty( obj, 'boop' )\nbool = isNonConfigurableProperty( obj, 'beep' )\n","isNonConfigurablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonConfigurablePropertyIn( obj, 'boop' )\nbool = isNonConfigurablePropertyIn( obj, 'beep' )\n","isNonEnumerableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonEnumerableProperty( obj, 'boop' )\nbool = isNonEnumerableProperty( obj, 'beep' )\n","isNonEnumerablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = true;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonEnumerablePropertyIn( obj, 'boop' )\nbool = isNonEnumerablePropertyIn( obj, 'beep' )\n","isNonNegativeFinite":"var bool = isNonNegativeFinite( 5.0 )\nbool = isNonNegativeFinite( new Number( 5.0 ) )\nbool = isNonNegativeFinite( 3.14 )\nbool = isNonNegativeFinite( -5.0 )\nbool = isNonNegativeFinite( null )\nbool = isNonNegativeFinite( PINF )\n","isNonNegativeFinite.isPrimitive":"var bool = isNonNegativeFinite.isPrimitive( 3.0 )\nbool = isNonNegativeFinite.isPrimitive( new Number( 3.0 ) )\n","isNonNegativeFinite.isObject":"var bool = isNonNegativeFinite.isObject( 3.0 )\nbool = isNonNegativeFinite.isObject( new Number( 3.0 ) )\n","isNonNegativeInteger":"var bool = isNonNegativeInteger( 5.0 )\nbool = isNonNegativeInteger( new Number( 5.0 ) )\nbool = isNonNegativeInteger( 3.14 )\nbool = isNonNegativeInteger( -5.0 )\nbool = isNonNegativeInteger( null )\n","isNonNegativeInteger.isPrimitive":"var bool = isNonNegativeInteger.isPrimitive( 3.0 )\nbool = isNonNegativeInteger.isPrimitive( new Number( 3.0 ) )\n","isNonNegativeInteger.isObject":"var bool = isNonNegativeInteger.isObject( 3.0 )\nbool = isNonNegativeInteger.isObject( new Number( 3.0 ) )\n","isNonNegativeIntegerArray":"var bool = isNonNegativeIntegerArray( [ 3.0, new Number(3.0) ] )\nbool = isNonNegativeIntegerArray( [ 3.0, '3.0' ] )\n","isNonNegativeIntegerArray.primitives":"var bool = isNonNegativeIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n","isNonNegativeIntegerArray.objects":"var bool = isNonNegativeIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isNonNegativeIntegerArray.objects( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n","isNonNegativeNumber":"var bool = isNonNegativeNumber( 5.0 )\nbool = isNonNegativeNumber( new Number( 5.0 ) )\nbool = isNonNegativeNumber( 3.14 )\nbool = isNonNegativeNumber( -5.0 )\nbool = isNonNegativeNumber( null )\n","isNonNegativeNumber.isPrimitive":"var bool = isNonNegativeNumber.isPrimitive( 3.0 )\nbool = isNonNegativeNumber.isPrimitive( new Number( 3.0 ) )\n","isNonNegativeNumber.isObject":"var bool = isNonNegativeNumber.isObject( 3.0 )\nbool = isNonNegativeNumber.isObject( new Number( 3.0 ) )\n","isNonNegativeNumberArray":"var bool = isNonNegativeNumberArray( [ 3.0, new Number(3.0) ] )\nbool = isNonNegativeNumberArray( [ 3.0, '3.0' ] )\n","isNonNegativeNumberArray.primitives":"var bool = isNonNegativeNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n","isNonNegativeNumberArray.objects":"var bool = isNonNegativeNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isNonNegativeNumberArray.objects( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeNumberArray.objects( [ 3.0, new Number(1.0) ] )\n","isNonPositiveFinite":"var bool = isNonPositiveFinite( -5.0 )\nbool = isNonPositiveFinite( new Number( -5.0 ) )\nbool = isNonPositiveFinite( -3.14 )\nbool = isNonPositiveFinite( 5.0 )\nbool = isNonPositiveFinite( null )\n","isNonPositiveFinite.isPrimitive":"var bool = isNonPositiveFinite.isPrimitive( -3.0 )\nbool = isNonPositiveFinite.isPrimitive( new Number( -3.0 ) )\n","isNonPositiveFinite.isObject":"var bool = isNonPositiveFinite.isObject( -3.0 )\nbool = isNonPositiveFinite.isObject( new Number( -3.0 ) )\n","isNonPositiveInteger":"var bool = isNonPositiveInteger( -5.0 )\nbool = isNonPositiveInteger( new Number( -5.0 ) )\nbool = isNonPositiveInteger( 5.0 )\nbool = isNonPositiveInteger( -3.14 )\nbool = isNonPositiveInteger( null )\n","isNonPositiveInteger.isPrimitive":"var bool = isNonPositiveInteger.isPrimitive( -3.0 )\nbool = isNonPositiveInteger.isPrimitive( new Number( -3.0 ) )\n","isNonPositiveInteger.isObject":"var bool = isNonPositiveInteger.isObject( -3.0 )\nbool = isNonPositiveInteger.isObject( new Number( -3.0 ) )\n","isNonPositiveIntegerArray":"var bool = isNonPositiveIntegerArray( [ -3.0, new Number(-3.0) ] )\nbool = isNonPositiveIntegerArray( [ -3.0, '-3.0' ] )\n","isNonPositiveIntegerArray.primitives":"var bool = isNonPositiveIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNonPositiveIntegerArray.objects":"var bool = isNonPositiveIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNonPositiveIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNonPositiveNumber":"var bool = isNonPositiveNumber( -5.0 )\nbool = isNonPositiveNumber( new Number( -5.0 ) )\nbool = isNonPositiveNumber( -3.14 )\nbool = isNonPositiveNumber( 5.0 )\nbool = isNonPositiveNumber( null )\n","isNonPositiveNumber.isPrimitive":"var bool = isNonPositiveNumber.isPrimitive( -3.0 )\nbool = isNonPositiveNumber.isPrimitive( new Number( -3.0 ) )\n","isNonPositiveNumber.isObject":"var bool = isNonPositiveNumber.isObject( -3.0 )\nbool = isNonPositiveNumber.isObject( new Number( -3.0 ) )\n","isNonPositiveNumberArray":"var bool = isNonPositiveNumberArray( [ -3.0, new Number(-3.0) ] )\nbool = isNonPositiveNumberArray( [ -3.0, '-3.0' ] )\n","isNonPositiveNumberArray.primitives":"var bool = isNonPositiveNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNonPositiveNumberArray.objects":"var bool = isNonPositiveNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNonPositiveNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNonSymmetricMatrix":"var buf = [ 1, 2, 3, 4 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isNonSymmetricMatrix( M )\nbool = isNonSymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isNonSymmetricMatrix( 3.14 )\nbool = isNonSymmetricMatrix( {} )\n","isNull":"var bool = isNull( null )\nbool = isNull( true )\n","isNullArray":"var bool = isNullArray( [ null, null, null ] )\nbool = isNullArray( [ NaN, 2, null ] )\n","isNumber":"var bool = isNumber( 3.14 )\nbool = isNumber( new Number( 3.14 ) )\nbool = isNumber( NaN )\nbool = isNumber( null )\n","isNumber.isPrimitive":"var bool = isNumber.isPrimitive( 3.14 )\nbool = isNumber.isPrimitive( NaN )\nbool = isNumber.isPrimitive( new Number( 3.14 ) )\n","isNumber.isObject":"var bool = isNumber.isObject( 3.14 )\nbool = isNumber.isObject( new Number( 3.14 ) )\n","isNumberArray":"var bool = isNumberArray( [ 1, 2, 3 ] )\nbool = isNumberArray( [ '1', 2, 3 ] )\n","isNumberArray.primitives":"var arr = [ 1, 2, 3 ];\nvar bool = isNumberArray.primitives( arr )\narr = [ 1, new Number( 2 ) ];\nbool = isNumberArray.primitives( arr )\n","isNumberArray.objects":"var arr = [ new Number( 1 ), new Number( 2 ) ];\nvar bool = isNumberArray.objects( arr )\narr = [ new Number( 1 ), 2 ];\nbool = isNumberArray.objects( arr )\n","isNumericArray":"var bool = isNumericArray( new Int8Array( 10 ) )\nbool = isNumericArray( [ 1, 2, 3 ] )\nbool = isNumericArray( [ '1', '2', '3' ] )\n","isObject":"var bool = isObject( {} )\nbool = isObject( true )\n","isObjectArray":"var bool = isObjectArray( [ {}, new Number(3.0) ] )\nbool = isObjectArray( [ {}, { 'beep': 'boop' } ] )\nbool = isObjectArray( [ {}, '3.0' ] )\n","isObjectLike":"var bool = isObjectLike( {} )\nbool = isObjectLike( [] )\nbool = isObjectLike( null )\n","isOdd":"var bool = isOdd( 5.0 )\nbool = isOdd( new Number( 5.0 ) )\nbool = isOdd( 4.0 )\nbool = isOdd( new Number( 4.0 ) )\nbool = isOdd( -3.14 )\nbool = isOdd( null )\n","isOdd.isPrimitive":"var bool = isOdd.isPrimitive( -5.0 )\nbool = isOdd.isPrimitive( new Number( -5.0 ) )\n","isOdd.isObject":"var bool = isOdd.isObject( 5.0 )\nbool = isOdd.isObject( new Number( 5.0 ) )\n","isoWeeksInYear":"var num = isoWeeksInYear()\nnum = isoWeeksInYear( 2015 )\nnum = isoWeeksInYear( 2017 )\n","isPascalcase":"var bool = isPascalcase( 'HelloWorld' )\nbool = isPascalcase( 'hello-world' )\n","isPersymmetricMatrix":"var buf = [ 1, 2, 3, 1 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isPersymmetricMatrix( M )\nbool = isPersymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isPersymmetricMatrix( 3.14 )\nbool = isPersymmetricMatrix( {} )\n","isPlainObject":"var bool = isPlainObject( {} )\nbool = isPlainObject( null )\n","isPlainObjectArray":"var bool = isPlainObjectArray( [ {}, { 'beep': 'boop' } ] )\nbool = isPlainObjectArray( [ {}, new Number(3.0) ] )\nbool = isPlainObjectArray( [ {}, '3.0' ] )\n","isPositiveFinite":"var bool = isPositiveFinite( 5.0 )\nbool = isPositiveFinite( new Number( 5.0 ) )\nbool = isPositiveFinite( 3.14 )\nbool = isPositiveFinite( -5.0 )\nvar bool = isPositiveFinite( 1.0/0.0 )\nbool = isPositiveFinite( new Number( 1.0/0.0 ) )\nbool = isPositiveFinite( null )\n","isPositiveFinite.isPrimitive":"var bool = isPositiveFinite.isPrimitive( 3.0 )\nvar bool = isPositiveFinite.isPrimitive( 1.0/0.0 )\nbool = isPositiveFinite.isPrimitive( new Number( 3.0 ) )\n","isPositiveFinite.isObject":"var bool = isPositiveFinite.isObject( 3.0 )\nbool = isPositiveFinite.isObject( new Number( 3.0 ) )\nbool = isPositiveFinite.isObject( new Number( 1.0/0.0 ) )\n","isPositiveInteger":"var bool = isPositiveInteger( 5.0 )\nbool = isPositiveInteger( new Number( 5.0 ) )\nbool = isPositiveInteger( 3.14 )\nbool = isPositiveInteger( -5.0 )\nbool = isPositiveInteger( null )\n","isPositiveInteger.isPrimitive":"var bool = isPositiveInteger.isPrimitive( 3.0 )\nbool = isPositiveInteger.isPrimitive( new Number( 3.0 ) )\n","isPositiveInteger.isObject":"var bool = isPositiveInteger.isObject( 3.0 )\nbool = isPositiveInteger.isObject( new Number( 3.0 ) )\n","isPositiveIntegerArray":"var bool = isPositiveIntegerArray( [ 3.0, new Number(3.0) ] )\nbool = isPositiveIntegerArray( [ 3.0, '3.0' ] )\n","isPositiveIntegerArray.primitives":"var bool = isPositiveIntegerArray.primitives( [ 1.0, 10.0 ] )\nbool = isPositiveIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isPositiveIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n","isPositiveIntegerArray.objects":"var bool = isPositiveIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isPositiveIntegerArray.objects( [ 1.0, 2.0, 10.0 ] )\nbool = isPositiveIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n","isPositiveNumber":"var bool = isPositiveNumber( 5.0 )\nbool = isPositiveNumber( new Number( 5.0 ) )\nbool = isPositiveNumber( 3.14 )\nbool = isPositiveNumber( -5.0 )\nbool = isPositiveNumber( null )\n","isPositiveNumber.isPrimitive":"var bool = isPositiveNumber.isPrimitive( 3.0 )\nbool = isPositiveNumber.isPrimitive( new Number( 3.0 ) )\n","isPositiveNumber.isObject":"var bool = isPositiveNumber.isObject( 3.0 )\nbool = isPositiveNumber.isObject( new Number( 3.0 ) )\n","isPositiveNumberArray":"var bool = isPositiveNumberArray( [ 3.0, new Number(3.0) ] )\nbool = isPositiveNumberArray( [ 3.0, '3.0' ] )\n","isPositiveNumberArray.primitives":"var bool = isPositiveNumberArray.primitives( [ 1.0, 10.0 ] )\nbool = isPositiveNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isPositiveNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n","isPositiveNumberArray.objects":"var bool = isPositiveNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isPositiveNumberArray.objects( [ 1.0, 2.0, 10.0 ] )\nbool = isPositiveNumberArray.objects( [ 3.0, new Number(1.0) ] )\n","isPositiveZero":"var bool = isPositiveZero( 0.0 )\nbool = isPositiveZero( new Number( 0.0 ) )\nbool = isPositiveZero( -3.14 )\nbool = isPositiveZero( -0.0 )\nbool = isPositiveZero( null )\n","isPositiveZero.isPrimitive":"var bool = isPositiveZero.isPrimitive( 0.0 )\nbool = isPositiveZero.isPrimitive( new Number( 0.0 ) )\n","isPositiveZero.isObject":"var bool = isPositiveZero.isObject( 0.0 )\nbool = isPositiveZero.isObject( new Number( 0.0 ) )\n","isPrime":"var bool = isPrime( 5.0 )\nbool = isPrime( new Number( 5.0 ) )\nbool = isPrime( 3.14 )\nbool = isPrime( -5.0 )\nbool = isPrime( null )\n","isPrime.isPrimitive":"var bool = isPrime.isPrimitive( 5.0 )\nbool = isPrime.isPrimitive( new Number( 5.0 ) )\n","isPrime.isObject":"var bool = isPrime.isObject( 5.0 )\nbool = isPrime.isObject( new Number( 5.0 ) )\n","isPrimitive":"var bool = isPrimitive( true )\nbool = isPrimitive( {} )\n","isPrimitiveArray":"var bool = isPrimitiveArray( [ '3', 2, null ] )\nbool = isPrimitiveArray( [ {}, 2, 1 ] )\nbool = isPrimitiveArray( [ new String('abc'), '3.0' ] )\n","isPRNGLike":"var bool = isPRNGLike( base.random.randu )\nbool = isPRNGLike( [ 1, 2, 3, 4 ] )\nbool = isPRNGLike( 3.14 )\nbool = isPRNGLike( {} )\n","isProbability":"var bool = isProbability( 0.5 )\nbool = isProbability( new Number( 0.5 ) )\nbool = isProbability( 3.14 )\nbool = isProbability( -5.0 )\nbool = isProbability( null )\n","isProbability.isPrimitive":"var bool = isProbability.isPrimitive( 0.3 )\nbool = isProbability.isPrimitive( new Number( 0.3 ) )\n","isProbability.isObject":"var bool = isProbability.isObject( 0.77 )\nbool = isProbability.isObject( new Number( 0.77 ) )\n","isProbabilityArray":"var bool = isProbabilityArray( [ 0.5, new Number(0.8) ] )\nbool = isProbabilityArray( [ 0.8, 1.2 ] )\nbool = isProbabilityArray( [ 0.8, '0.2' ] )\n","isProbabilityArray.primitives":"var bool = isProbabilityArray.primitives( [ 1.0, 0.0, 0.5 ] )\nbool = isProbabilityArray.primitives( [ 0.3, new Number(0.4) ] )\n","isProbabilityArray.objects":"var bool = isProbabilityArray.objects( [ new Number(0.7), new Number(1.0) ] )\nbool = isProbabilityArray.objects( [ 1.0, 0.0, new Number(0.7) ] )\n","isPropertyKey":"var out = isPropertyKey( 'foo' )\nout = isPropertyKey( 1 )\nout = isPropertyKey( true )\n","isPrototypeOf":"function Foo() { return this; };\nfunction Bar() { return this; };\ninherit( Bar, Foo );\nvar bar = new Bar();\nvar bool = isPrototypeOf( bar, Foo.prototype )\n","isRaggedNestedArray":"var bool = isRaggedNestedArray( [ [ 1, 2, 3 ], [ 4, 5 ] ] )\nbool = isRaggedNestedArray( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\nbool = isRaggedNestedArray( 'beep' )\n","isRangeError":"var bool = isRangeError( new RangeError( 'beep' ) )\nbool = isRangeError( {} )\n","isReadableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadableProperty( obj, 'boop' )\nbool = isReadableProperty( obj, 'beep' )\n","isReadablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadablePropertyIn( obj, 'boop' )\nbool = isReadablePropertyIn( obj, 'beep' )\n","isReadOnlyProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadOnlyProperty( obj, 'boop' )\nbool = isReadOnlyProperty( obj, 'beep' )\n","isReadOnlyPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadOnlyPropertyIn( obj, 'boop' )\nbool = isReadOnlyPropertyIn( obj, 'beep' )\n","isReadWriteProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadWriteProperty( obj, 'boop' )\nbool = isReadWriteProperty( obj, 'beep' )\n","isReadWritePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadWritePropertyIn( obj, 'boop' )\nbool = isReadWritePropertyIn( obj, 'beep' )\n","isReferenceError":"var bool = isReferenceError( new ReferenceError( 'beep' ) )\nbool = isReferenceError( {} )\n","isRegExp":"var bool = isRegExp( /\\.+/ )\nbool = isRegExp( {} )\n","isRegExpString":"var bool = isRegExpString( '/beep/' )\nbool = isRegExpString( 'beep' )\nbool = isRegExpString( '' )\nbool = isRegExpString( null )\n","isRelativePath":"var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\nbool = isRelativePath( './foo/bar/baz' )\n","isRelativePath.posix":"var bool = isRelativePath.posix( './foo/bar/baz' )\nbool = isRelativePath.posix( '/foo/../bar/baz' )\n","isRelativePath.win32":"var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\nbool = isRelativePath( 'C:\\\\foo\\\\..\\\\bar\\\\baz' )\n","isRelativeURI":"var bool = isRelativeURI( '/images/example.png' )\nbool = isRelativeURI( 'http://www.example.com' )\nbool = isRelativeURI( null )\n","isSafeInteger":"var bool = isSafeInteger( 5.0 )\nbool = isSafeInteger( new Number( 5.0 ) )\nbool = isSafeInteger( 2.0e200 )\nbool = isSafeInteger( -3.14 )\nbool = isSafeInteger( null )\n","isSafeInteger.isPrimitive":"var bool = isSafeInteger.isPrimitive( -3.0 )\nbool = isSafeInteger.isPrimitive( new Number( -3.0 ) )\n","isSafeInteger.isObject":"var bool = isSafeInteger.isObject( 3.0 )\nbool = isSafeInteger.isObject( new Number( 3.0 ) )\n","isSafeIntegerArray":"var arr = [ -3.0, new Number(0.0), 2.0 ];\nvar bool = isSafeIntegerArray( arr )\narr = [ -3.0, '3.0' ];\nbool = isSafeIntegerArray( arr )\n","isSafeIntegerArray.primitives":"var arr = [ -1.0, 10.0 ];\nvar bool = isSafeIntegerArray.primitives( arr )\narr = [ -1.0, 0.0, 5.0 ];\nbool = isSafeIntegerArray.primitives( arr )\narr = [ -3.0, new Number(-1.0) ];\nbool = isSafeIntegerArray.primitives( arr )\n","isSafeIntegerArray.objects":"var arr = [ new Number(1.0), new Number(3.0) ];\nvar bool = isSafeIntegerArray.objects( arr )\narr = [ -1.0, 0.0, 3.0 ];\nbool = isSafeIntegerArray.objects( arr )\narr = [ 3.0, new Number(-1.0) ];\nbool = isSafeIntegerArray.objects( arr )\n","isSameArray":"var x = [ 1.0, 2.0, 3.0 ];\nvar y = [ 1.0, 2.0, 3.0 ];\nvar bool = isSameArray( x, y )\nx = [ NaN, NaN, NaN ];\ny = [ NaN, NaN, NaN ];\nbool = isSameArray( x, y )\n","isSameArrayLike":"var x = [ 1.0, 2.0, 3.0 ];\nvar y = [ 1.0, 2.0, 3.0 ];\nvar bool = isSameArrayLike( x, y )\nx = [ NaN, NaN, NaN ];\ny = [ NaN, NaN, NaN ];\nbool = isSameArrayLike( x, y )\n","isSameComplex64":"var x = new Complex64( 1.0, 2.0 );\nvar y = new Complex64( 1.0, 2.0 );\nvar bool = isSameComplex64( x, y )\nx = new Complex64( NaN, NaN );\ny = new Complex64( NaN, NaN );\nbool = isSameComplex64( x, y )\n","isSameComplex64Array":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar bool = isSameComplex64Array( x, y )\nx = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\ny = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\nbool = isSameComplex64Array( x, y )\n","isSameComplex128":"var x = new Complex128( 1.0, 2.0 );\nvar y = new Complex128( 1.0, 2.0 );\nvar bool = isSameComplex128( x, y )\nx = new Complex128( NaN, NaN );\ny = new Complex128( NaN, NaN );\nbool = isSameComplex128( x, y )\n","isSameComplex128Array":"var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar bool = isSameComplex128Array( x, y )\nx = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\ny = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\nbool = isSameComplex128Array( x, y )\n","isSameDateObject":"var d1 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\nvar d2 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\nvar bool = isSameDateObject( d1, d2 )\nvar d1 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\nvar d2 = new Date( 2024, 11, 31, 23, 59, 59, 78 );\nvar bool = isSameDateObject( d1, d2 )\n","isSameFloat32Array":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nvar bool = isSameFloat32Array( x, y )\nx = new Float32Array( [ NaN, NaN, NaN ] );\ny = new Float32Array( [ NaN, NaN, NaN ] );\nbool = isSameFloat32Array( x, y )\n","isSameFloat64Array":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nvar bool = isSameFloat64Array( x, y )\nx = new Float64Array( [ NaN, NaN, NaN ] );\ny = new Float64Array( [ NaN, NaN, NaN ] );\nbool = isSameFloat64Array( x, y )\n","isSameNativeClass":"var bool = isSameNativeClass( 3.14, new Number( 3.14 ) )\nbool = isSameNativeClass( 'beep', 'boop' )\nbool = isSameNativeClass( {}, [] )\n","isSameType":"var bool = isSameType( true, true )\nbool = isSameType( {}, [] )\nbool = isSameType( 3.12, -3.12 )\nbool = isSameType( 0.0, '0.0' )\n","isSameValue":"var bool = isSameValue( true, true )\nbool = isSameValue( {}, {} )\nbool = isSameValue( -0.0, -0.0 )\nbool = isSameValue( -0.0, 0.0 )\nbool = isSameValue( NaN, NaN )\n","isSameValueZero":"var bool = isSameValueZero( true, true )\nbool = isSameValueZero( {}, {} )\nbool = isSameValueZero( -0.0, -0.0 )\nbool = isSameValueZero( -0.0, 0.0 )\nbool = isSameValueZero( NaN, NaN )\n","isSemVer":"var bool = isSemVer( '1.0.0' )\nbool = isSemVer( '1.0.0-alpha.1' )\nbool = isSemVer( '0.1' )\nbool = isSemVer( null )\n","isSharedArrayBuffer":"var bool = isSharedArrayBuffer( new SharedArrayBuffer( 10 ) )\nbool = isSharedArrayBuffer( [] )\n","isSkewCentrosymmetricMatrix":"var buf = [ 2, 1, -1, -2 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSkewCentrosymmetricMatrix( M )\nbool = isSkewCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSkewCentrosymmetricMatrix( 3.14 )\nbool = isSkewCentrosymmetricMatrix( {} )\n","isSkewPersymmetricMatrix":"var buf = [ 1, 0, 0, -1 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSkewPersymmetricMatrix( M )\nbool = isSkewPersymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSkewPersymmetricMatrix( 3.14 )\nbool = isSkewPersymmetricMatrix( {} )\n","isSkewSymmetricMatrix":"var buf = [ 0, -1, 1, 0 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSkewSymmetricMatrix( M )\nbool = isSkewSymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSkewSymmetricMatrix( 3.14 )\nbool = isSkewSymmetricMatrix( {} )\n","isSlice":"var bool = isSlice( new Slice( 10 ) )\nbool = isSlice( 3.14 )\nbool = isSlice( {} )\n","isSnakecase":"var bool = isSnakecase( 'hello_world' )\nbool = isSnakecase( 'Hello World' )\n","isSquareMatrix":"var buf = [ 0, 0, 0, 0 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSquareMatrix( M )\nbool = isSquareMatrix( [ 1, 2, 3, 4 ] )\nbool = isSquareMatrix( 3.14 )\nbool = isSquareMatrix( {} )\n","isSquareNumber":"var bool = isSquareNumber( 4.0 )\nbool = isSquareNumber( new Number( 4.0 ) )\nbool = isSquareNumber( 3.14 )\nbool = isSquareNumber( -5.0 )\nbool = isSquareNumber( null )\n","isSquareNumber.isPrimitive":"var bool = isSquareNumber.isPrimitive( 4.0 )\nbool = isSquareNumber.isPrimitive( new Number( 4.0 ) )\n","isSquareNumber.isObject":"var bool = isSquareNumber.isObject( 4.0 )\nbool = isSquareNumber.isObject( new Number( 4.0 ) )\n","isSquareTriangularNumber":"var bool = isSquareTriangularNumber( 36.0 )\nbool = isSquareTriangularNumber( new Number( 36.0 ) )\nbool = isSquareTriangularNumber( 3.14 )\nbool = isSquareTriangularNumber( -5.0 )\nbool = isSquareTriangularNumber( null )\n","isSquareTriangularNumber.isPrimitive":"var bool = isSquareTriangularNumber.isPrimitive( 36.0 )\nbool = isSquareTriangularNumber.isPrimitive( new Number( 36.0 ) )\n","isSquareTriangularNumber.isObject":"var bool = isSquareTriangularNumber.isObject( 36.0 )\nbool = isSquareTriangularNumber.isObject( new Number( 36.0 ) )\n","isStartcase":"var bool = isStartcase( 'Beep Boop' )\nbool = isStartcase( 'Beep and Boop' )\n","isStrictEqual":"var bool = isStrictEqual( true, true )\nbool = isStrictEqual( {}, {} )\nbool = isStrictEqual( -0.0, -0.0 )\nbool = isStrictEqual( -0.0, 0.0 )\nbool = isStrictEqual( NaN, NaN )\n","isString":"var bool = isString( 'beep' )\nbool = isString( new String( 'beep' ) )\nbool = isString( 5 )\n","isString.isPrimitive":"var bool = isString.isPrimitive( 'beep' )\nbool = isString.isPrimitive( new String( 'beep' ) )\n","isString.isObject":"var bool = isString.isObject( new String( 'beep' ) )\nbool = isString.isObject( 'beep' )\n","isStringArray":"var bool = isStringArray( [ 'abc', 'def' ] )\nbool = isStringArray( [ 'abc', 123 ] )\n","isStringArray.primitives":"var arr = [ 'abc', 'def' ];\nvar bool = isStringArray.primitives( arr )\narr = [ 'abc', new String( 'def' ) ];\nbool = isStringArray.primitives( arr )\n","isStringArray.objects":"var arr = [ new String( 'ab' ), new String( 'cd' ) ];\nvar bool = isStringArray.objects( arr )\narr = [ new String( 'abc' ), 'def' ];\nbool = isStringArray.objects( arr )\n","isSymbol":"var bool = isSymbol( Symbol( 'beep' ) )\nbool = isSymbol( Object( Symbol( 'beep' ) ) )\nbool = isSymbol( {} )\nbool = isSymbol( null )\nbool = isSymbol( true )\n","isSymbolArray":"var bool = isSymbolArray( [ Symbol( 'beep' ), Symbol( 'boop' ) ] )\nbool = isSymbolArray( Symbol( 'beep' ) )\nbool = isSymbolArray( [] )\nbool = isSymbolArray( {} )\nbool = isSymbolArray( null )\nbool = isSymbolArray( true )\n","isSymbolArray.primitives":"var bool = isSymbolArray.primitives( [ Symbol( 'beep' ) ] )\nbool = isSymbolArray.primitives( [ Object( Symbol( 'beep' ) ) ] )\nbool = isSymbolArray.primitives( [] )\nbool = isSymbolArray.primitives( {} )\nbool = isSymbolArray.primitives( null )\nbool = isSymbolArray.primitives( true )\n","isSymbolArray.objects":"var bool = isSymbolArray.objects( [ Object( Symbol( 'beep' ) ) ] )\nbool = isSymbolArray.objects( [ Symbol( 'beep' ) ] )\nbool = isSymbolArray.objects( [] )\nbool = isSymbolArray.objects( {} )\nbool = isSymbolArray.objects( null )\nbool = isSymbolArray.objects( true )\n","isSymmetricMatrix":"var buf = [ 0, 1, 1, 2 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSymmetricMatrix( M )\nbool = isSymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSymmetricMatrix( 3.14 )\nbool = isSymmetricMatrix( {} )\n","isSyntaxError":"var bool = isSyntaxError( new SyntaxError( 'beep' ) )\nbool = isSyntaxError( {} )\n","isTriangularNumber":"var bool = isTriangularNumber( 36.0 )\nbool = isTriangularNumber( new Number( 36.0 ) )\nbool = isTriangularNumber( 3.14 )\nbool = isTriangularNumber( -5.0 )\nbool = isTriangularNumber( null )\n","isTriangularNumber.isPrimitive":"var bool = isTriangularNumber.isPrimitive( 36.0 )\nbool = isTriangularNumber.isPrimitive( new Number( 36.0 ) )\n","isTriangularNumber.isObject":"var bool = isTriangularNumber.isObject( 36.0 )\nbool = isTriangularNumber.isObject( new Number( 36.0 ) )\n","isTruthy":"var bool = isTruthy( true )\nbool = isTruthy( {} )\nbool = isTruthy( [] )\nbool = isTruthy( false )\nbool = isTruthy( '' )\nbool = isTruthy( 0 )\nbool = isTruthy( null )\nbool = isTruthy( void 0 )\nbool = isTruthy( NaN )\n","isTruthyArray":"var bool = isTruthyArray( [ {}, [] ] )\nbool = isTruthyArray( [ null, '' ] )\nbool = isTruthyArray( [] )\n","isTypedArray":"var bool = isTypedArray( new Int8Array( 10 ) )\n","isTypedArrayLength":"var bool = isTypedArrayLength( 5 )\nbool = isTypedArrayLength( 2.0e200 )\nbool = isTypedArrayLength( -3.14 )\nbool = isTypedArrayLength( null )\n","isTypedArrayLike":"var bool = isTypedArrayLike( new Int16Array() )\nbool = isTypedArrayLike({\n'length': 10,\n'byteOffset': 0,\n'byteLength': 10,\n'BYTES_PER_ELEMENT': 4\n })\n","isTypeError":"var bool = isTypeError( new TypeError( 'beep' ) )\nbool = isTypeError( {} )\n","isUint8Array":"var bool = isUint8Array( new Uint8Array( 10 ) )\nbool = isUint8Array( [] )\n","isUint8ClampedArray":"var bool = isUint8ClampedArray( new Uint8ClampedArray( 10 ) )\nbool = isUint8ClampedArray( [] )\n","isUint16Array":"var bool = isUint16Array( new Uint16Array( 10 ) )\nbool = isUint16Array( [] )\n","isUint32Array":"var bool = isUint32Array( new Uint32Array( 10 ) )\nbool = isUint32Array( [] )\n","isUNCPath":"var bool = isUNCPath( '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz' )\nbool = isUNCPath( '/foo/bar/baz' )\n","isUndefined":"var bool = isUndefined( void 0 )\nbool = isUndefined( null )\n","isUndefinedOrNull":"var bool = isUndefinedOrNull( void 0 )\nbool = isUndefinedOrNull( null )\nbool = isUndefinedOrNull( false )\n","isUnityProbabilityArray":"var bool = isUnityProbabilityArray( [ 0.25, 0.5, 0.25 ] )\nbool = isUnityProbabilityArray( new Uint8Array( [ 0, 1 ] ) )\nbool = isUnityProbabilityArray( [ 0.4, 0.4, 0.4 ] )\nbool = isUnityProbabilityArray( [ 3.14, 0.0 ] )\n","isUppercase":"var bool = isUppercase( 'HELLO' )\nbool = isUppercase( 'World' )\n","isURI":"var bool = isURI( 'http://google.com' )\nbool = isURI( 'http://localhost/' )\nbool = isURI( 'http://example.w3.org/path%20with%20spaces.html' )\nbool = isURI( 'ftp://ftp.is.co.za/rfc/rfc1808.txt' )\nbool = isURI( '' )\nbool = isURI( 'foo@bar' )\nbool = isURI( '://foo/' )\nbool = isURI( 'http://<foo>' )\nbool = isURI( 'http:////foo.html' )\nbool = isURI( 'http://example.w3.org/%a' )\n","isURIError":"var bool = isURIError( new URIError( 'beep' ) )\nbool = isURIError( {} )\n","isVectorLike":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isVectorLike( M )\nbool = isVectorLike( [ 1, 2, 3, 4 ] )\nbool = isVectorLike( 3.14 )\nbool = isVectorLike( {} )\n","isWebAssemblyMemory":"var bool = isWebAssemblyMemory( {} )\n","isWellFormedString":"var bool = isWellFormedString( '' )\nbool = isWellFormedString( new String( '' ) )\nbool = isWellFormedString( '\\uDBFF' )\nbool = isWellFormedString( '\\uDBFFFF\\uDBFF' )\nbool = isWellFormedString( [] )\nbool = isWellFormedString( '-5' )\nbool = isWellFormedString( null )\n","isWellFormedString.isPrimitive":"var bool = isWellFormedString.isPrimitive( '' )\nbool = isWellFormedString.isPrimitive( new String( '' ) )\n","isWellFormedString.isObject":"var bool = isWellFormedString.isObject( '' )\nbool = isWellFormedString.isObject( new String( '' ) )\n","isWhitespace":"var bool = isWhitespace( '       ' )\nbool = isWhitespace( 'abcdef' )\nbool = isWhitespace( '' )\n","isWritableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = false;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isWritableProperty( obj, 'boop' )\nbool = isWritableProperty( obj, 'beep' )\n","isWritablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = false;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isWritablePropertyIn( obj, 'boop' )\nbool = isWritablePropertyIn( obj, 'beep' )\n","isWriteOnlyProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isWriteOnlyProperty( obj, 'boop' )\nbool = isWriteOnlyProperty( obj, 'beep' )\n","isWriteOnlyPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isWriteOnlyPropertyIn( obj, 'boop' )\nbool = isWriteOnlyPropertyIn( obj, 'beep' )\n","iterAbs":"var it = iterAbs( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterAbs2":"var it = iterAbs2( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterAcos":"var it = iterAcos( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcosh":"var it = iterAcosh( random.iterators.uniform( 1.0, 10.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcot":"var it = iterAcot( random.iterators.uniform( -5.0, 5.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcoth":"var it = iterAcoth( random.iterators.uniform( 1.0, 10.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcovercos":"var it = iterAcovercos( random.iterators.uniform( -2.0, 0.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcoversin":"var it = iterAcoversin( random.iterators.uniform( 0.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAdd":"var it1 = array2iterator( [ 1.0, 2.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nvar it = iterAdd( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterAdvance":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar it = iterAdvance( arr, 4 );\nvar v = it.next().value\nvar bool = it.next().done\n","iterAhavercos":"var it = iterAhavercos( random.iterators.uniform( 0.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAhaversin":"var it = iterAhaversin( random.iterators.uniform( 0.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAny":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar bool = iterAny( arr )\n","iterAnyBy":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nfunction fcn( v ) { return ( v === 1 ); };\nvar bool = iterAnyBy( arr, fcn )\n","iterAsin":"var it = iterAsin( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAsinh":"var it = iterAsinh( random.iterators.uniform( -2.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAtan":"var it = iterAtan( random.iterators.uniform( -2.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAtan2":"var x = random.iterators.uniform( -2.0, 2.0 );\nvar y = random.iterators.uniform( -2.0, 2.0 );\nvar it = iterAtan2( y, x );\nvar r = it.next().value\nr = it.next().value\n","iterAtanh":"var it = iterAtanh( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterator2array":"var opts = { 'iter': 10 };\nvar arr = iterator2array( random.iterators.randu( opts ) )\n","iterator2arrayview":"var it = random.iterators.randu({ 'iter': 10 });\nvar out = new Float64Array( 20 );\nvar arr = iterator2arrayview( it, out, 5, 15 )\n","iterator2arrayviewRight":"var it = random.iterators.randu({ 'iter': 10 });\nvar out = new Float64Array( 20 );\nvar arr = iterator2arrayviewRight( it, out, 5, 15 )\n","iteratorStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar it = random.iterators.randu( opts );\nvar s = iteratorStream( it );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","iteratorStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = iteratorStream.factory( opts );\n","iteratorStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar it = random.iterators.randu( opts );\nvar s = iteratorStream.objectMode( it );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","IteratorSymbol":"var s = IteratorSymbol\n","iterAvercos":"var it = iterAvercos( random.iterators.uniform( -2.0, 0.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAversin":"var it = iterAversin( random.iterators.uniform( 0.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterawgn":"var src = iterSineWave();\nvar it = iterawgn( src, 0.5 );\nvar v = it.next().value\nv = it.next().value\n","iterawln":"var src = iterSineWave();\nvar it = iterawln( src, 0.5 );\nvar v = it.next().value\nv = it.next().value\n","iterawun":"var src = iterSineWave();\nvar it = iterawun( src, 0.5 );\nvar v = it.next().value\nv = it.next().value\n","iterBartlettHannPulse":"var it = iterBartlettHannPulse();\nvar v = it.next().value\nv = it.next().value\n","iterBartlettPulse":"var it = iterBartlettPulse();\nvar v = it.next().value\nv = it.next().value\n","iterBesselj0":"var it = iterBesselj0( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBesselj1":"var it = iterBesselj1( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBessely0":"var it = iterBessely0( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBessely1":"var it = iterBessely1( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBeta":"var x = random.iterators.uniform( 0.0, 2.0 );\nvar y = random.iterators.uniform( 0.0, 2.0 );\nvar it = iterBeta( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterBetaln":"var x = random.iterators.uniform( 0.0, 2.0 );\nvar y = random.iterators.uniform( 0.0, 2.0 );\nvar it = iterBetaln( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterBinet":"var it = iterBinet( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCbrt":"var it = iterCbrt( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCeil":"var it = iterCeil( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCeil2":"var it = iterCeil2( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCeil10":"var it = iterCeil10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterCompositesSeq":"var it = iterCompositesSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterConcat":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = array2iterator( [ 3, 4 ] );\nvar it = iterConcat( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterConstant":"var it = iterConstant( 3.14 );\nvar v = it.next().value\nv = it.next().value\n","iterContinuedFraction":"var terms = array2iterator( [ 3, 4, 12, 4 ] );\nvar v = iterContinuedFraction( terms )\n","iterContinuedFractionSeq":"var it = iterContinuedFractionSeq( 3.245 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\nit = iterContinuedFractionSeq( 3.245, { 'returns': 'convergents' } );\nv = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nbool = it.next().done\n","iterCos":"var it = iterCos( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCosh":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterCosh( r );\nvar v = it.next().value\nv = it.next().value\n","iterCosineWave":"var it = iterCosineWave();\nvar v = it.next().value\nv = it.next().value\n","iterCosm1":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterCosm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterCospi":"var it = iterCospi( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCounter":"var it = iterCounter( random.iterators.randu() );\nvar v = it.next().value\nv = it.next().value\n","iterCovercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterCovercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterCoversin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterCoversin( r );\nvar v = it.next().value\nv = it.next().value\n","iterCubesSeq":"var it = iterCubesSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","itercugmean":"var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\nvar it = itercugmean( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itercuhmean":"var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\nvar it = itercuhmean( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itercumax":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumax( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumaxabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumaxabs( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumean":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumean( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumeanabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumeanabs( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumeanabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumeanabs2( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumidrange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumidrange( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itercumin":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumin( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercuminabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercuminabs( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercuprod":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercuprod( arr );\nvar p = it.next().value\np = it.next().value\np = it.next().value\np = it.next().value\n","itercurange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercurange( arr );\nvar r = it.next().value\nr = it.next().value\nr = it.next().value\nr = it.next().value\n","itercusum":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercusum( arr );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itercusumabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercusumabs( arr );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itercusumabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercusumabs2( arr );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","iterDatespace":"var t1 = new Date();\nvar it = iterDatespace( t1, new Date( t1.getTime()+86400000 ) );\nvar v = it.next().value\nv = it.next().value\n","iterDedupe":"var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\nvar it = iterDedupe( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterDedupeBy":"var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\nfunction fcn( v ) { return v; };\nvar it = iterDedupeBy( arr, fcn );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterDeg2rad":"var r = random.iterators.uniform( -360.0, 360.0 );\nvar it = iterDeg2rad( r );\nvar v = it.next().value\nv = it.next().value\n","iterDigamma":"var r = random.iterators.uniform( 0.01, 5.0 );\nvar it = iterDigamma( r );\nvar v = it.next().value\nv = it.next().value\n","iterDiracComb":"var it = iterDiracComb();\nvar v = it.next().value\nv = it.next().value\n","iterDiracDelta":"var it = iterDiracDelta( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterDivide":"var it1 = array2iterator( [ 3.0, 2.0 ] );\nvar it2 = array2iterator( [ 1.0, 4.0 ] );\nvar it = iterDivide( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterDoWhileEach":"function predicate( v ) { return v === v };\nfunction f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterDoWhileEach( random.iterators.randu(), predicate, f );\nvar r = it.next().value\nr = it.next().value\n","iterEllipe":"var r = random.iterators.uniform( -1.0, 1.0 );\nvar it = iterEllipe( r );\nvar v = it.next().value\nv = it.next().value\n","iterEllipk":"var r = random.iterators.uniform( -1.0, 1.0 );\nvar it = iterEllipk( r );\nvar v = it.next().value\nv = it.next().value\n","iterEmpty":"var it = iterEmpty();\nvar bool = it.next().done\n","iterErf":"var it = iterErf( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterErfc":"var it = iterErfc( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterErfcinv":"var it = iterErfcinv( random.iterators.uniform( 0.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterErfinv":"var it = iterErfinv( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterEta":"var it = iterEta( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterEvenIntegersSeq":"var it = iterEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterEvery":"var arr = array2iterator( [ 1, 1, 1, 1, 0 ] );\nvar bool = iterEvery( arr )\n","iterEveryBy":"var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\nfunction fcn( v ) { return ( v > 0 ); };\nvar bool = iterEveryBy( arr, fcn )\n","iterExp":"var it = iterExp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterExp2":"var r = random.iterators.uniform( -50.0, 50.0 );\nvar it = iterExp2( r );\nvar v = it.next().value\nv = it.next().value\n","iterExp10":"var r = random.iterators.uniform( -50.0, 50.0 );\nvar it = iterExp10( r );\nvar v = it.next().value\nv = it.next().value\n","iterExpit":"var r = random.iterators.uniform( 0.0, 1.0 );\nvar it = iterExpit( r );\nvar v = it.next().value\nv = it.next().value\n","iterExpm1":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterExpm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterExpm1rel":"var r = random.iterators.uniform( -50.0, 50.0 );\nvar it = iterExpm1rel( r );\nvar v = it.next().value\nv = it.next().value\n","iterFactorial":"var it = iterFactorial( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterFactorialln":"var it = iterFactorialln( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterFactorialsSeq":"var it = iterFactorialsSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterFibonacciSeq":"var it = iterFibonacciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterFifthPowersSeq":"var it = iterFifthPowersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterFill":"var it = iterFill( random.iterators.randu(), 3.14, 0, 2 );\nvar r = it.next().value\nr = it.next().value\nr = it.next().value\n","iterFilter":"function f( v ) { return ( v > 2 ); };\nvar it1 = array2iterator( [ 1, 3, 2, 4 ] );\nvar it2 = iterFilter( it1, f );\nvar v = it2.next().value\nv = it2.next().value\n","iterFilterMap":"function f( v ) { if ( v > 2 ) { return v * 10 }; };\nvar it1 = array2iterator( [ 1, 3, 2, 4 ] );\nvar it2 = iterFilterMap( it1, f );\nvar v = it2.next().value\nv = it2.next().value\n","iterFirst":"var arr = array2iterator( [ 1, 0, 0, 0, 0 ] );\nvar v = iterFirst( arr )\n","iterFlatTopPulse":"var it = iterFlatTopPulse();\nvar v = it.next().value\nv = it.next().value\n","iterFloor":"var it = iterFloor( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterFloor2":"var it = iterFloor2( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterFloor10":"var it = iterFloor10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterFlow":"var o = {};\no.head = iterHead;\no.some = iterSome;\nvar fiter = iterFlow( o )\n","iterForEach":"function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterForEach( random.iterators.randu(), f );\nvar r = it.next().value\nr = it.next().value\n","iterFourthPowersSeq":"var it = iterFourthPowersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterFresnelc":"var r = random.iterators.uniform( 0.0, 10.0 );\nvar it = iterFresnelc( r );\nvar v = it.next().value\nv = it.next().value\n","iterFresnels":"var r = random.iterators.uniform( 0.0, 10.0 );\nvar it = iterFresnels( r );\nvar v = it.next().value\nv = it.next().value\n","iterGamma":"var it = iterGamma( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterGamma1pm1":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterGamma1pm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterGammaln":"var it = iterGammaln( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterHacovercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHacovercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterHacoversin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHacoversin( r );\nvar v = it.next().value\nv = it.next().value\n","iterHannPulse":"var it = iterHannPulse();\nvar v = it.next().value\nv = it.next().value\n","iterHavercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHavercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterHaversin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHaversin( r );\nvar v = it.next().value\nv = it.next().value\n","iterHead":"var it = iterHead( random.iterators.randu(), 5 );\nvar r = it.next().value\nr = it.next().value\n","iterIncrspace":"var it = iterIncrspace( 0, 101, 2 );\nvar v = it.next().value\nv = it.next().value\n","iterIntegersSeq":"var it = iterIntegersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterIntersection":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\nvar it = iterIntersection( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterIntersectionByHash":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\nfunction f( v ) { return v.toString(); };\nvar it = iterIntersectionByHash( it1, it2, f );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterInv":"var it = iterInv( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLanczosPulse":"var it = iterLanczosPulse();\nvar v = it.next().value\nv = it.next().value\n","iterLast":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar v = iterLast( arr )\n","iterLength":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar len = iterLength( arr )\n","iterLinspace":"var it = iterLinspace( 0, 99, 100 );\nvar v = it.next().value\nv = it.next().value\n","iterLn":"var it = iterLn( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog":"var x = random.iterators.uniform( 0.0, 100.0 );\nvar y = random.iterators.uniform( 0.0, 10.0 );\nvar it = iterLog( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterLog1mexp":"var it = iterLog1mexp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog1p":"var it = iterLog1p( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog1pexp":"var it = iterLog1pexp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog2":"var it = iterLog2( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog10":"var it = iterLog10( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLogit":"var r = random.iterators.uniform( 0.0, 1.0 );\nvar it = iterLogit( r );\nvar v = it.next().value\nv = it.next().value\n","iterLogspace":"var it = iterLogspace( 0, 3, 4 );\nvar v = it.next().value\nv = it.next().value\n","iterLucasSeq":"var it = iterLucasSeq();\nvar v = it.next().value\nv = it.next().value\n","iterMap":"function f( v ) { return v * 10.0; };\nvar it = iterMap( random.iterators.randu(), f );\nvar r = it.next().value\nr = it.next().value\n","iterMapN":"var it1 = array2iterator( [ 1.0, 2.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nfunction fcn( x, y ) { return x + y; };\nvar it = iterMapN( it1, it2, fcn );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","itermax":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar m = itermax( arr )\n","itermaxabs":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar m = itermaxabs( arr )\n","itermean":"var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = itermean( arr )\n","itermeanabs":"var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\nvar m = itermeanabs( arr )\n","itermeanabs2":"var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\nvar m = itermeanabs2( arr )\n","itermidrange":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar v = itermidrange( arr )\n","itermin":"var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\nvar m = itermin( arr )\n","iterminabs":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar m = iterminabs( arr )\n","itermmax":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmax( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmaxabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmaxabs( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmean":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmean( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmeanabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmeanabs( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmeanabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmeanabs2( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmidrange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmidrange( arr, 3 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itermmin":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmin( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermminabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermminabs( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","iterMod":"var it1 = array2iterator( [ 3.0, 2.0 ] );\nvar it2 = array2iterator( [ 1.0, 4.0 ] );\nvar it = iterMod( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","itermprod":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermprod( arr, 3 );\nvar p = it.next().value\np = it.next().value\np = it.next().value\np = it.next().value\n","itermrange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermrange( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermsum":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermsum( arr, 3 );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itermsumabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermsumabs( arr, 3 );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itermsumabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermsumabs2( arr, 3 );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","iterMultiply":"var it1 = array2iterator( [ 1.0, 2.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nvar it = iterMultiply( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterNegaFibonacciSeq":"var it = iterNegaFibonacciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegaLucasSeq":"var it = iterNegaLucasSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegativeEvenIntegersSeq":"var it = iterNegativeEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegativeIntegersSeq":"var it = iterNegativeIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegativeOddIntegersSeq":"var it = iterNegativeOddIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNone":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar bool = iterNone( arr )\n","iterNoneBy":"var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\nfunction fcn( v ) { return ( v <= 0 ); };\nvar bool = iterNoneBy( arr, fcn )\n","iterNonFibonacciSeq":"var it = iterNonFibonacciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonNegativeEvenIntegersSeq":"var it = iterNonNegativeEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonNegativeIntegersSeq":"var it = iterNonNegativeIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonPositiveEvenIntegersSeq":"var it = iterNonPositiveEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonPositiveIntegersSeq":"var it = iterNonPositiveIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonSquaresSeq":"var it = iterNonSquaresSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterNth":"var arr = array2iterator( [ 0, 0, 1, 0, 0 ] );\nvar v = iterNth( arr, 3 )\n","iterOddIntegersSeq":"var it = iterOddIntegersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterPeriodicSinc":"var it = iterPeriodicSinc( 7 );\nvar v = it.next().value\nv = it.next().value\n","iterPipeline":"var it1 = iterThunk( iterHead, 100 );\nfunction f( r ) { return ( r > 0.95 ); };\nvar it2 = iterThunk( iterSomeBy, 5, f );\nvar p = iterPipeline( it1, it2 );\nvar bool = p( random.iterators.randu() )\n","iterPop":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterPop( it1 );\nvar v = it2.next().value\nvar bool = it2.next().done\n","iterPositiveEvenIntegersSeq":"var it = iterPositiveEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterPositiveIntegersSeq":"var it = iterPositiveIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterPositiveOddIntegersSeq":"var it = iterPositiveOddIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterPow":"var x = random.iterators.uniform( 0.0, 2.0 );\nvar y = random.iterators.uniform( -2.0, 2.0 );\nvar it = iterPow( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterPrimesSeq":"var it = iterPrimesSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterprod":"var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar s = iterprod( arr )\n","iterPulse":"var it = iterPulse();\nvar v = it.next().value\nv = it.next().value\n","iterPush":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterPush( it1, 3, 4 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterRad2deg":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterRad2deg( r );\nvar v = it.next().value\nv = it.next().value\n","iterRamp":"var it = iterRamp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterrange":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar v = iterrange( arr )\n","iterReject":"function f( v ) { return ( v > 2 ); };\nvar it1 = array2iterator( [ 1, 3, 2, 4 ] );\nvar it2 = iterReject( it1, f );\nvar v = it2.next().value\nv = it2.next().value\n","iterReplicate":"var it1 = array2iterator( [ 1, 2, 3, 4 ] );\nvar it2 = iterReplicate( it1, 2 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\n","iterReplicateBy":"var it1 = array2iterator( [ 1, 2, 3, 4 ] );\nfunction f( v, i ) { return i + 1; };\nvar it2 = iterReplicateBy( it1, f );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\n","iterRound":"var it = iterRound( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterRound2":"var it = iterRound2( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterRound10":"var it = iterRound10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterRsqrt":"var it = iterRsqrt( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSawtoothWave":"var it = iterSawtoothWave();\nvar v = it.next().value\nv = it.next().value\n","iterShift":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterShift( it1 );\nvar v = it2.next().value\nvar bool = it2.next().done\n","iterSignum":"var it = iterSignum( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSin":"var it = iterSin( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSinc":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterSinc( r );\nvar v = it.next().value\nv = it.next().value\n","iterSineWave":"var it = iterSineWave();\nvar v = it.next().value\nv = it.next().value\n","iterSinh":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterSinh( r );\nvar v = it.next().value\nv = it.next().value\n","iterSinpi":"var it = iterSinpi( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSlice":"var it = iterSlice( random.iterators.randu(), 5, 10 );\nvar r = it.next().value\nr = it.next().value\n","iterSome":"var arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\nvar bool = iterSome( arr, 3 )\n","iterSomeBy":"var arr = array2iterator( [ 1, 1, 0, 0, 1 ] );\nfunction fcn( v ) { return ( v > 0 ); };\nvar bool = iterSomeBy( arr, 3, fcn )\n","iterSpence":"var r = random.iterators.uniform( 0.0, 100.0 );\nvar it = iterSpence( r );\nvar v = it.next().value\nv = it.next().value\n","iterSqrt":"var it = iterSqrt( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSqrt1pm1":"var r = random.iterators.uniform( 0.0, 100.0 );\nvar it = iterSqrt1pm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterSquaredTriangularSeq":"var it = iterSquaredTriangularSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterSquaresSeq":"var it = iterSquaresSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterSquareWave":"var it = iterSquareWave();\nvar v = it.next().value\nv = it.next().value\n","iterstdev":"var arr = array2iterator( [ 2.0, -5.0 ] );\nvar m = iterstdev( arr )\n","iterStep":"var it = iterStep( 0, 2, 10 );\nvar v = it.next().value\nv = it.next().value\n","iterStrided":"var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\nvar it = iterStrided( arr, 2, 1 );\nvar r = it.next().value\nr = it.next().value\n","iterStridedBy":"var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\nfunction stride( v, i ) { return (i % 10)+1; };\nvar it = iterStridedBy( arr, stride );\nvar r = it.next().value\nr = it.next().value\nr = it.next().value\n","iterSubtract":"var it1 = array2iterator( [ 1.0, 5.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nvar it = iterSubtract( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","itersum":"var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar s = itersum( arr )\n","itersumabs":"var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\nvar s = itersumabs( arr )\n","itersumabs2":"var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\nvar s = itersumabs2( arr )\n","iterTan":"var r = random.iterators.uniform( -1.57, 1.57 );\nvar it = iterTan( r );\nvar v = it.next().value\nv = it.next().value\n","iterTanh":"var r = random.iterators.uniform( -4.0, 4.0 );\nvar it = iterTanh( r );\nvar v = it.next().value\nv = it.next().value\n","iterThunk":"var fcn = iterThunk( iterSome, 3 );\nvar arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\nvar bool = fcn( arr )\n","iterTriangleWave":"var it = iterTriangleWave();\nvar v = it.next().value\nv = it.next().value\n","iterTriangularSeq":"var it = iterTriangularSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterTribonnaciSeq":"var it = iterTribonnaciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterTrigamma":"var r = random.iterators.uniform( 0.01, 50.0 );\nvar it = iterTrigamma( r );\nvar v = it.next().value\nv = it.next().value\n","iterTrunc":"var it = iterTrunc( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterTrunc2":"var it = iterTrunc2( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterTrunc10":"var it = iterTrunc10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterUnion":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\nvar it = iterUnion( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterUnique":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = iterUnique( it1 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUniqueBy":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nfunction f( a, b ) { return ( a !== b ); };\nvar it2 = iterUniqueBy( it1, f );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUniqueByHash":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nfunction f( v ) { return v.toString(); };\nvar it2 = iterUniqueByHash( it1, f );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUnitspace":"var it = iterUnitspace( 0, 99 );\nvar v = it.next().value\nv = it.next().value\n","iterUnshift":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterUnshift( it1, 3, 4 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUntilEach":"function predicate( v ) { return v !== v };\nfunction f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterUntilEach( random.iterators.randu(), predicate, f );\nvar r = it.next().value\nr = it.next().value\n","itervariance":"var arr = array2iterator( [ 2.0, -5.0 ] );\nvar s2 = itervariance( arr )\n","iterVercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterVercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterVersin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterVersin( r );\nvar v = it.next().value\nv = it.next().value\n","iterWhileEach":"function predicate( v ) { return v === v };\nfunction f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterWhileEach( random.iterators.randu(), predicate, f );\nvar r = it.next().value\nr = it.next().value\n","iterZeta":"var r = random.iterators.uniform( 1.1, 50.0 );\nvar it = iterZeta( r );\nvar v = it.next().value\nv = it.next().value\n","joinStream":"var s = joinStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","joinStream.factory":"var opts = { 'highWaterMark': 64 };\nvar createStream = joinStream.factory( opts );\nvar s = createStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","joinStream.objectMode":"var s = joinStream.objectMode();\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","kde2d":"var x = [ 1, 3, 5, 6, 21, 23, 16, 17, 20, 10 ];\nvar y = [ 0.40, 0.20, 0.20, 0.15, 0.05, 0.55, 0.6, 0.33, 0.8, 0.41 ];\nvar out = kde2d( x, y )\n","kebabcase":"var out = kebabcase( 'Hello World!' )\nout = kebabcase( 'I am a tiny little teapot' )\n","keyBy":"function toKey( v ) { return v.a; };\nvar arr = [ { 'a': 1 }, { 'a': 2 } ];\nkeyBy( arr, toKey )\n","keyByRight":"function toKey( v ) { return v.a; };\nvar arr = [ { 'a': 1 }, { 'a': 2 } ];\nkeyByRight( arr, toKey )\n","keysIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = keysIn( obj )\n","kruskalTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = kruskalTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = kruskalTest( arr, { 'groups': groups } )\n","kstest":"var rnorm = base.random.normal.factory({ 'seed': 4839 } );\nvar x = new Array( 100 );\nfor ( var i = 0; i < 100; i++ ) { x[ i ] = rnorm( 3.0, 1.0 ); }\nvar out = kstest( x, 'normal', 0.0, 1.0 )\nout = kstest( x, 'normal', 3.0, 1.0 )\nrunif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } )\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\nout = kstest( x, 'uniform', 0.0, 1.0 )\nout.print()\nout = kstest( x, 'uniform', 0.0, 1.0, { 'alpha': 0.1 } )\nrunif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } );\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\nout = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'less' } )\nout = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'greater' } )\nx = [ 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 ];\nout = kstest( x, 'uniform', 0.0, 1.0, { 'sorted': true } )\n","last":"var out = last( 'beep' )\nout = last( 'Boop', 2 )\nout = last( 'foo bar', 3 )\n","leveneTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = leveneTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = leveneTest( arr, { 'groups': groups } )\n","LinkedList":"var list = LinkedList();\nlist.push( 'foo' ).push( 'bar' );\nlist.length\nlist.pop()\nlist.length\nlist.pop()\nlist.length\n","linspace":"var arr = linspace( 0.0, 100.0, 6 )\narr = linspace( 0.0, 100.0, 5, { 'endpoint': false } )\narr = linspace( 0.0, 100.0, 6, { 'dtype': 'generic' } )\n","linspace.assign":"var arr = [ 0, 0, 0, 0, 0, 0 ];\nvar out = linspace.assign( 0, 100, arr )\nvar bool = ( arr === out )\narr = [ 0, 0, 0, 0, 0 ];\nout = linspace.assign( 0, 100, arr, { 'endpoint': false } )\n","LIU_NEGATIVE_OPINION_WORDS_EN":"var list = LIU_NEGATIVE_OPINION_WORDS_EN()\n","LIU_POSITIVE_OPINION_WORDS_EN":"var list = LIU_POSITIVE_OPINION_WORDS_EN()\n","LN_HALF":"LN_HALF\n","LN_PI":"LN_PI\n","LN_SQRT_TWO_PI":"LN_SQRT_TWO_PI\n","LN_TWO_PI":"LN_TWO_PI\n","LN2":"LN2\n","LN10":"LN10\n","LOG2E":"LOG2E\n","LOG10E":"LOG10E\n","logspace":"var arr = logspace( 0, 2, 6 )\n","lowercase":"var out = lowercase( 'bEEp' )\n","lowercaseKeys":"var obj = { 'A': 1, 'B': 2 };\nvar out = lowercaseKeys( obj )\n","lowess":"var x = new Float64Array( 100 );\nvar y = new Float64Array( x.length );\nfor ( var i = 0; i < x.length; i++ ) {\n x[ i ] = i;\n y[ i ] = ( 0.5*i ) + ( 10.0*base.random.randn() );\n }\nvar out = lowess( x, y );\nvar yhat = out.y;\nvar h = Plot( [ x, x ], [ y, yhat ] );\nh.lineStyle = [ 'none', '-' ];\nh.symbols = [ 'closed-circle', 'none' ];\nh.view( 'window' );\n","lpad":"var out = lpad( 'a', 5 )\nout = lpad( 'beep', 10, 'b' )\nout = lpad( 'boop', 12, 'beep' )\n","ltrim":"var out = ltrim( ' \\r\\n\\t  Beep \\t\\t\\n  ' )\n","ltrimN":"var out = ltrimN( '  abc  ', 2 )\nvar out = ltrimN( '!!!abc!!!', 2, '!' )\n","MALE_FIRST_NAMES_EN":"var list = MALE_FIRST_NAMES_EN()\n","map":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = map( arr, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = map( arr, f );\nvar v = out.get( 1, 1 )\n","map.assign":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmap.assign( arr, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\narr = array( arr, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmap.assign( arr, out, f );\nvar v = out.get( 1, 1 )\n","map2":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = map2( x, y, f )\nx = array( x, { 'shape': [ 2, 3 ] } );\ny = array( y, { 'shape': [ 2, 3 ] } );\nout = map2( x, y, f );\nvar v = out.get( 1, 1 )\n","map2.assign":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmap2.assign( x, y, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\nx = array( x, opts );\ny = array( y, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmap2.assign( x, y, out, f );\nvar v = out.get( 1, 1 )\n","map2d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ -1, -2, -3 ], [ -4, -5, -6 ] ];\nvar out = map2d( arr, f );\nout[ 0 ]\nout[ 1 ]\n","map2Right":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = map2Right( x, y, f )\nx = array( x, { 'shape': [ 2, 3 ] } );\ny = array( y, { 'shape': [ 2, 3 ] } );\nout = map2Right( x, y, f );\nvar v = out.get( 1, 1 )\n","map2Right.assign":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmap2Right.assign( x, y, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\nx = array( x, opts );\ny = array( y, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmap2Right.assign( x, y, out, f );\nvar v = out.get( 1, 1 )\n","map3d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ [ -1, -2, -3 ] ], [ [ -4, -5, -6 ] ] ];\nvar out = map3d( arr, f );\nout[ 0 ][ 0 ]\nout[ 1 ][ 0 ]\n","map4d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ [ [ -1, -2, -3 ] ] ], [ [ [ -4, -5, -6 ] ] ] ];\nvar out = map4d( arr, f );\nout[ 0 ][ 0 ][ 0 ]\nout[ 1 ][ 0 ][ 0 ]\n","map5d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ [ [ [ -1, -2, -3 ] ] ] ], [ [ [ [ -4, -5, -6 ] ] ] ] ];\nvar out = map5d( arr, f );\nout[ 0 ][ 0 ][ 0 ][ 0 ]\nout[ 1 ][ 0 ][ 0 ][ 0 ]\n","mapArguments":"function foo( a, b, c ) { return [ a, b, c ]; };\nfunction clbk( v ) { return v * 2; };\nvar bar = mapArguments( foo, clbk );\nvar out = bar( 1, 2, 3 )\n","mapFun":"function fcn( i ) { return i; };\nvar arr = mapFun( fcn, 5 )\n","mapFunAsync":"function fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n     next( null, i );\n }\n };\nfunction done( error, arr ) {\n if ( error ) {\n     throw error;\n }\n console.log( arr );\n };\nmapFunAsync( fcn, 10, done )\nfunction fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n     next( null, i );\n }\n };\nfunction done( error, arr ) {\n if ( error ) {\n     throw error;\n }\n console.log( arr );\n };\nvar opts = { 'limit': 2 };\nmapFunAsync( fcn, 10, opts, done )\nfunction fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n     next( null, i );\n }\n };\nfunction done( error, arr ) {\n if ( error ) {\n     throw error;\n }\n console.log( arr );\n };\nvar opts = { 'series': true };\nmapFunAsync( fcn, 10, opts, done )\n","mapFunAsync.factory":"function fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n     next( null, i );\n }\n };\nvar opts = { 'series': true };\nvar f = mapFunAsync.factory( opts, fcn );\nfunction done( error, arr ) {\n if ( error ) {\n     throw error;\n }\n console.log( arr );\n };\nf( 10, done )\n","mapKeys":"function transform( key, value ) { return key + value; };\nvar obj = { 'a': 1, 'b': 2 };\nvar out = mapKeys( obj, transform )\n","mapKeysAsync":"function transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n     throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2 };\nmapKeysAsync( obj, transform, done )\nfunction transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n     throw error;\n }\n console.log( out );\n };\nvar opts = { 'limit': 2 };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapKeysAsync( obj, opts, transform, done )\nfunction transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n     throw error;\n }\n console.log( out );\n };\nvar opts = { 'series': true };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapKeysAsync( obj, opts, transform, done )\n","mapKeysAsync.factory":"function transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     next( null, key+':'+value );\n }\n };\nvar opts = { 'series': true };\nvar f = mapKeysAsync.factory( opts, transform );\nfunction done( error, out ) {\n if ( error ) {\n     throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nf( obj, done )\nobj = { 'beep': 'boop' };\nf( obj, done )\n","mapReduce":"var f1 = naryFunction( base.abs, 1 );\nvar f2 = naryFunction( base.add, 2 );\nvar arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\nvar out = mapReduce( arr, 0.0, f1, f2 )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = mapReduce( arr, 0.0, f1, f2 )\n","mapReduceRight":"var f1 = naryFunction( base.abs, 1 );\nvar f2 = naryFunction( base.add, 2 );\nvar arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\nvar out = mapReduceRight( arr, 0.0, f1, f2 )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = mapReduceRight( arr, 0.0, f1, f2 )\n","mapRight":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = mapRight( arr, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = mapRight( arr, f );\nvar v = out.get( 1, 1 )\n","mapRight.assign":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmapRight.assign( arr, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\narr = array( arr, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmapRight.assign( arr, out, f );\nvar v = out.get( 1, 1 )\n","mapValues":"function transform( value, key ) { return key + value; };\nvar obj = { 'a': 1, 'b': 2 };\nvar out = mapValues( obj, transform )\n","mapValuesAsync":"function transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n     throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2 };\nmapValuesAsync( obj, transform, done )\nfunction transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n     throw error;\n }\n console.log( out );\n };\nvar opts = { 'limit': 2 };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapValuesAsync( obj, opts, transform, done )\nfunction transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n     throw error;\n }\n console.log( out );\n };\nvar opts = { 'series': true };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapValuesAsync( obj, opts, transform, done )\n","mapValuesAsync.factory":"function transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     next( null, key+':'+value );\n }\n };\nvar opts = { 'series': true };\nvar f = mapValuesAsync.factory( opts, transform );\nfunction done( error, out ) {\n if ( error ) {\n     throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nf( obj, done )\nobj = { 'beep': 'boop' };\nf( obj, done )\n","maskArguments":"function foo( a, b ) { return [ a, b ]; };\nvar bar = maskArguments( foo, [ 1, 0, 1 ] );\nvar out = bar( 1, 2, 3 )\n","MAX_ARRAY_LENGTH":"MAX_ARRAY_LENGTH\n","MAX_TYPED_ARRAY_LENGTH":"MAX_TYPED_ARRAY_LENGTH\n","maybeBroadcastArray":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = maybeBroadcastArray( x, [ 3, 2, 2 ] )\nsh = y.shape\nvar v = y.get( 0, 0, 0 )\nv = y.get( 0, 0, 1 )\nv = y.get( 0, 1, 0 )\nv = y.get( 0, 1, 1 )\nv = y.get( 1, 0, 0 )\nv = y.get( 1, 1, 0 )\nv = y.get( 2, 0, 0 )\nv = y.get( 2, 1, 1 )\n","maybeBroadcastArrays":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = ndzeros( [ 3, 2, 2 ] )\nvar out = maybeBroadcastArrays( [ x, y ] )\nvar bx = out[ 0 ]\nsh = bx.shape\nvar v = bx.get( 0, 0, 0 )\nv = bx.get( 0, 0, 1 )\nv = bx.get( 0, 1, 0 )\nv = bx.get( 0, 1, 1 )\nv = bx.get( 1, 0, 0 )\nv = bx.get( 1, 1, 0 )\nv = bx.get( 2, 0, 0 )\nv = bx.get( 2, 1, 1 )\n","memoize":"function factorial( n ) {\n var prod;\n var i;\n prod = 1;\n for ( i = n; i > 1; i-- ) {\n     prod *= i;\n }\n return prod;\n };\nvar memoized = memoize( factorial );\nvar v = memoized( 5 )\nv = memoized( 5 )\n","merge":"var target = { 'a': 'beep' };\nvar source = { 'a': 'boop', 'b': 'bap' };\nvar out = merge( target, source )\nvar bool = ( out === target )\n","merge.factory":"var opts = {\n 'level': 100,\n 'copy': true,\n 'override': true,\n 'extend': true\n };\nvar merge = merge.factory( opts )\nmerge = merge.factory( { 'level': 2 } );\nvar target = {\n '1': { 'a': 'beep', '2': { '3': null, 'b': [ 5, 6, 7 ] } }\n };\nvar source = {\n '1': { 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } }\n };\nvar out = merge( target, source )\nmerge = merge.factory( { 'copy': false } );\ntarget = {};\nsource = { 'a': [ 1, 2, 3 ] };\nout = merge( target, source );\nvar bool = ( out.a === source.a )\nmerge = merge.factory( { 'override': false } );\ntarget = { 'a': 'beep', 'b': 'boop' };\nsource = { 'a': null, 'c': 'bop' };\nout = merge( target, source )\nfunction strategy( a, b, key ) {\n // a => target value\n // b => source value\n // key => object key\n if ( key === 'a' ) {\n     return b;\n }\n if ( key === 'b' ) {\n     return a;\n }\n return 'bebop';\n };\nmerge = merge.factory( { 'override': strategy } );\ntarget = { 'a': 'beep', 'b': 'boop', 'c': 1234 };\nsource = { 'a': null, 'b': {}, 'c': 'bop' };\nout = merge( target, source )\nmerge = merge.factory( { 'extend': false } );\ntarget = { 'a': 'beep', 'b': 'boop' };\nsource = { 'b': 'hello', 'c': 'world' };\nout = merge( target, source )\n","MILLISECONDS_IN_DAY":"var days = 3.14;\nvar ms = days * MILLISECONDS_IN_DAY\n","MILLISECONDS_IN_HOUR":"var hrs = 3.14;\nvar ms = hrs * MILLISECONDS_IN_HOUR\n","MILLISECONDS_IN_MINUTE":"var mins = 3.14;\nvar ms = mins * MILLISECONDS_IN_MINUTE\n","MILLISECONDS_IN_SECOND":"var secs = 3.14;\nvar ms = secs * MILLISECONDS_IN_SECOND\n","MILLISECONDS_IN_WEEK":"var weeks = 3.14;\nvar ms = weeks * MILLISECONDS_IN_WEEK\n","MINARD_NAPOLEONS_MARCH":"var data = MINARD_NAPOLEONS_MARCH();\nvar army = data.army\nvar cities = data.cities\nvar labels = data.labels\nvar river = data.river\nvar t = data.temperature\n","MINUTES_IN_DAY":"var days = 3.14;\nvar mins = days * MINUTES_IN_DAY\n","MINUTES_IN_HOUR":"var hrs = 3.14;\nvar mins = hrs * MINUTES_IN_HOUR\n","MINUTES_IN_WEEK":"var wks = 3.14;\nvar mins = wks * MINUTES_IN_WEEK\n","minutesInMonth":"var num = minutesInMonth()\nnum = minutesInMonth( 2 )\nnum = minutesInMonth( 2, 2016 )\nnum = minutesInMonth( 2, 2017 )\nnum = minutesInMonth( 'feb', 2016 )\nnum = minutesInMonth( 'february', 2016 )\n","minutesInYear":"var num = minutesInYear()\nnum = minutesInYear( 2016 )\nnum = minutesInYear( 2017 )\n","MOBY_DICK":"var data = MOBY_DICK()\n","MONTH_NAMES_EN":"var list = MONTH_NAMES_EN()\n","MONTHS_IN_YEAR":"var yrs = 3.14;\nvar mons = yrs * MONTHS_IN_YEAR\n","moveProperty":"var obj1 = { 'a': 'b' };\nvar obj2 = {};\nvar bool = moveProperty( obj1, 'a', obj2 )\nbool = moveProperty( obj1, 'c', obj2 )\n","MultiSlice":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\n","MultiSlice.prototype.ndims":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\nms.ndims\n","MultiSlice.prototype.data":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\nms.data\n","MultiSlice.prototype.toString":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\nms.toString()\n","MultiSlice.prototype.toJSON":"var s = new Slice( 2, 10, 1 );\nvar ms = new MultiSlice( 2, s );\nms.toJSON()\n","namedtypedtuple":"var opts = {};\nopts.name = 'Point';\nvar factory = namedtypedtuple( [ 'x', 'y' ], opts );\nvar tuple = factory();\n","NAN":"NAN\n","naryFunction":"function foo( a, b, c ) { return [ a, b, c ]; };\nvar bar = naryFunction( foo, 2 );\nvar out = bar( 1, 2, 3 )\n","nativeClass":"var str = nativeClass( 'a' )\nstr = nativeClass( 5 )\nfunction Beep(){};\nstr = nativeClass( new Beep() )\n","ndarray":"var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\nvar d = [ 2, 2 ]; // shape\nvar s = [ 2, 1 ]; // strides\nvar o = 0; // index offset\nvar arr = ndarray( 'generic', b, d, s, o, 'row-major' )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","ndarray.prototype.byteLength":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.byteLength\n","ndarray.prototype.BYTES_PER_ELEMENT":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.BYTES_PER_ELEMENT\n","ndarray.prototype.data":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar buf = arr.data\n","ndarray.prototype.dtype":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar dt = arr.dtype\n","ndarray.prototype.flags":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar fl = arr.flags\n","ndarray.prototype.length":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar len = arr.length\n","ndarray.prototype.ndims":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar n = arr.ndims\n","ndarray.prototype.offset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.offset\n","ndarray.prototype.order":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar ord = arr.order\n","ndarray.prototype.shape":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sh = arr.shape\n","ndarray.prototype.strides":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar st = arr.strides\n","ndarray.prototype.get":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.get( 1, 1 )\n","ndarray.prototype.iget":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.iget( 3 )\n","ndarray.prototype.set":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\narr.set( 1, 1, -4.0 );\narr.get( 1, 1 )\n","ndarray.prototype.iset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\narr.iset( 3, -4.0 );\narr.iget( 3 )\n","ndarray.prototype.toString":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toString()\n","ndarray.prototype.toJSON":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toJSON()\n","ndarray2array":"var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar out = ndarray2array( arr )\n","ndarray2fancy":"var b = [ 1.0, 2.0, 3.0, 4.0 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar x = ndarray( 'generic', b, d, s, o, 'row-major' );\nvar arr = ndarray2fancy( x );\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","ndarray2fancy.factory":"var b = [ 1.0, 2.0, 3.0, 4.0 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar x = ndarray( 'generic', b, d, s, o, 'row-major' );\nvar f = ndarray2fancy.factory();\nvar y = f( x );\n","ndarray2fancy.idx":"var opts = { 'dtype': 'int32' };\nvar buf = new Int32Array( [ 1, 2, 3, 4 ] );\nvar arr = array( buf, opts );\nvar idx = ndarray2fancy.idx( arr );\n","ndarray2json":"var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar out = ndarray2json( arr )\n","ndarrayCastingModes":"var out = ndarrayCastingModes()\n","ndarrayDataBuffer":"var opts = { 'dtype': 'float64' };\nvar out = ndarrayDataBuffer( ndzeros( [ 3, 3, 3 ], opts ) )\n","ndarrayDataType":"var opts = { 'dtype': 'float64' };\nvar dt = ndarrayDataType( ndzeros( [ 3, 3, 3 ], opts ) )\n","ndarrayDataTypes":"var out = ndarrayDataTypes()\nout = ndarrayDataTypes( 'floating_point' )\nout = ndarrayDataTypes( 'floating_point_and_generic' )\n","ndarrayDispatch":"var t = [ 'float64', 'float64', 'float32', 'float32' ];\nvar d = [ base.abs, base.absf ];\nvar f = ndarrayDispatch( base.ndarrayUnary, t, d, 2, 1, 1 );\nvar xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar x = ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );\nvar ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar y = ndarray( 'float64', ybuf, [ 4 ], [ 1 ], 0, 'row-major' );\nf( x, y );\nybuf\n","ndarrayFlag":"var out = ndarrayFlag( ndzeros( [ 3, 3, 3 ] ), 'READONLY' )\n","ndarrayFlags":"var out = ndarrayFlags( ndzeros( [ 3, 3, 3 ] ) )\n","ndarrayIndexModes":"var out = ndarrayIndexModes()\n","ndarraylike2ndarray":"var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar out = ndarraylike2ndarray( arr )\n","ndarrayMinDataType":"var dt = ndarrayMinDataType( 3.141592653589793 )\ndt = ndarrayMinDataType( 3 )\ndt = ndarrayMinDataType( -3 )\ndt = ndarrayMinDataType( '-3' )\n","ndarrayMostlySafeCasts":"var out = ndarrayMostlySafeCasts( 'float32' )\n","ndarrayNextDataType":"var out = ndarrayNextDataType( 'float32' )\n","ndarrayOffset":"var n = ndarrayOffset( ndzeros( [ 3, 3, 3 ] ) )\n","ndarrayOrder":"var opts = { 'order': 'row-major' };\nvar dt = ndarrayOrder( ndzeros( [ 3, 3, 3 ], opts ) )\n","ndarrayOrders":"var out = ndarrayOrders()\n","ndarrayPromotionRules":"var out = ndarrayPromotionRules( 'float32', 'int32' )\n","ndarraySafeCasts":"var out = ndarraySafeCasts( 'float32' )\n","ndarraySameKindCasts":"var out = ndarraySameKindCasts( 'float32' )\n","ndarrayShape":"var out = ndarrayShape( ndzeros( [ 3, 3, 3 ] ) )\n","ndarrayStride":"var out = ndarrayStride( ndzeros( [ 3, 3, 3 ] ), 0 )\n","ndarrayStrides":"var out = ndarrayStrides( ndzeros( [ 3, 3, 3 ] ) )\n","ndat":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nndat( x, 0, 1 )\nndat( x, 1, 0 )\n","ndempty":"var arr = ndempty( [ 2, 2 ] )\nvar sh = arr.shape\nvar dt = arr.dtype\n","ndemptyLike":"var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\nvar sh = x.shape\nvar dt = x.dtype\nvar y = ndemptyLike( x )\nsh = y.shape\ndt = y.dtype\n","ndfilter":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { return v > 2.0; };\nvar y = ndfilter( x, f );\nndarray2array( y )\n","ndfilterMap":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { if ( v > 2.0 ) { return v * 10.0; } };\nvar y = ndfilterMap( x, f );\nndarray2array( y )\n","ndforEach":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { if ( v !== v ) { throw new Error( '...' ); } };\nndforEach( x, f );\n","ndims":"var n = ndims( ndzeros( [ 3, 3, 3 ] ) )\n","ndindex":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\n","ndindex.free":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nndindex.free( idx.id )\n","ndindex.get":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nndindex.get( idx.id )\n","ndindex.cartesianIndex":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = ndindex.cartesianIndex( x );\n","ndindex.linearIndex":"var x = ndempty( [ 5 ], { 'dtype': 'int32' } );\nvar idx = ndindex.linearIndex( x );\n","ndindex.prototype.data":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.data\n","ndindex.prototype.dtype":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.dtype\n","ndindex.prototype.id":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.id\n","ndindex.prototype.isCached":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.isCached\n","ndindex.prototype.kind":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x, { 'kind': 'cartesian' } );\nidx.kind\n","ndindex.prototype.type":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.type\n","ndindex.prototype.toString":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.toString()\n","ndindex.prototype.toJSON":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.toJSON()\n","nditerColumnEntries":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerColumnEntries( x );\nvar v = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\nv = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\n","nditerColumns":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerColumns( x );\nvar v = it.next().value;\nndarray2array( v )\nv = it.next().value;\nndarray2array( v )\n","nditerEntries":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerEntries( x );\nvar v = it.next().value\nv = it.next().value\n","nditerIndices":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerIndices( x.shape );\nvar v = it.next().value\nv = it.next().value\n","nditerInterleaveSubarrays":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerInterleaveSubarrays( [ x, x ], 2 );\nvar v = it.next().value;\nndarray2array( v )\n","nditerMatrices":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerMatrices( x );\nvar v = it.next().value;\nndarray2array( v )\n","nditerMatrixEntries":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerMatrixEntries( x );\nvar v = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\n","nditerRowEntries":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerRowEntries( x );\nvar v = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\nv = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\n","nditerRows":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerRows( x );\nvar v = it.next().value;\nndarray2array( v )\nv = it.next().value;\nndarray2array( v )\n","nditerSelectDimension":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerSelectDimension( x, 0 );\nvar v = it.next().value;\nndarray2array( v )\n","nditerStacks":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerStacks( x, [ 1, 2 ] );\nvar v = it.next().value;\nndarray2array( v )\n","nditerSubarrays":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerSubarrays( x, 2 );\nvar v = it.next().value;\nndarray2array( v )\n","nditerValues":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerValues( x );\nvar v = it.next().value\nv = it.next().value\n","ndmap":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { return v*10.0; };\nvar y = ndmap( x, f );\nndarray2array( y )\n","ndreject":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { return v <= 2.0; };\nvar y = ndreject( x, f );\nndarray2array( y )\n","ndslice":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar s = new MultiSlice( null, 1 )\nvar y = ndslice( x, s )\ny.shape\nndarray2array( y )\n","ndsliceAssign":"var y = ndzeros( [ 2, 2 ] )\nvar x = scalar2ndarray( 3.0 )\nvar s = new MultiSlice( null, 1 )\nvar out = ndsliceAssign( x, y, s )\nvar bool = ( out === y )\nndarray2array( y )\n","ndsliceDimension":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceDimension( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndsliceDimensionFrom":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceDimensionFrom( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndsliceDimensionTo":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceDimensionTo( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndsliceFrom":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceFrom( x, 0, 1 )\ny.shape\nndarray2array( y )\n","ndsliceTo":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceTo( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndzeros":"var arr = ndzeros( [ 2, 2 ] )\nvar sh = arr.shape\nvar dt = arr.dtype\n","ndzerosLike":"var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\nvar sh = x.shape\nvar dt = x.dtype\nvar y = ndzerosLike( x )\nsh = y.shape\ndt = y.dtype\n","nextGraphemeClusterBreak":"var out = nextGraphemeClusterBreak( 'last man standing', 4 )\nout = nextGraphemeClusterBreak( 'presidential election', 8 )\nout = nextGraphemeClusterBreak( 'अनुच्छेद', 1 )\nout = nextGraphemeClusterBreak( '🌷' )\n","nextTick":"function f() { console.log( 'beep' ); };\nnextTick( f )\n","NIGHTINGALES_ROSE":"var data = NIGHTINGALES_ROSE()\n","NINF":"NINF\n","NODE_VERSION":"NODE_VERSION\n","none":"var arr = [ 0, 0, 0, 0, 0 ];\nvar bool = none( arr )\n","noneBy":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ 1, 2, 3, 4 ];\nvar bool = noneBy( arr, negative )\n","noneByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nnoneByAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nnoneByAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nnoneByAsync( arr, opts, predicate, done )\n","noneByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = noneByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","noneByRight":"function positive( v ) { return ( v > 0 ); };\nvar arr = [ -1, -2, -3, -4 ];\nvar bool = noneByRight( arr, positive )\n","noneByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nnoneByRightAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nnoneByRightAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nnoneByRightAsync( arr, opts, predicate, done )\n","noneByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = noneByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","noneInBy":"function negative( v ) { return ( v < 0 ); };\nvar obj = { 'a': 1, 'b': 2, 'c': 4 };\nvar bool = noneInBy( obj, negative )\n","nonEnumerableProperties":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = false;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar props = nonEnumerableProperties( obj )\n","nonEnumerablePropertiesIn":"var props = nonEnumerablePropertiesIn( [] )\n","nonEnumerablePropertyNames":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = nonEnumerablePropertyNames( obj )\n","nonEnumerablePropertyNamesIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = nonEnumerablePropertyNamesIn( obj )\n","nonEnumerablePropertySymbols":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = nonEnumerablePropertySymbols( obj )\n","nonEnumerablePropertySymbolsIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? 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Object.assign( {}, { 'a': 1 }, { 'b': 2 } )\n","Object.create":"var o = Object.create( {}, { 'a': { 'value': 1 } } )\n","Object.defineProperties":"var o = Object.defineProperties( {}, { 'a': { 'value': 1 } } )\n","Object.defineProperty":"var o = Object.defineProperty( {}, 'a', {\n","Object.entries":"var o = Object.entries( { 'a': 1, 'b': 2 } )\n","Object.freeze":"var o = Object.freeze( { 'a': 1 } )\n","Object.getOwnPropertyDescriptor":"var o = Object.getOwnPropertyDescriptor( { 'a': 1 }, 'a' )\n","Object.getOwnPropertyDescriptors":"var o = Object.getOwnPropertyDescriptors( { 'a': 1, 'b': 2 } )\n","Object.getOwnPropertyNames":"var o = Object.getOwnPropertyNames( { 'a': 1, 'b': 2 } )\n","Object.getOwnPropertySymbols":"var o = Object.getOwnPropertySymbols( { 'a': 1, 'b': 2 } )\n","Object.getPrototypeOf":"var o = Object.getPrototypeOf( { 'a': 1, 'b': 2 } )\n","Object.hasOwn":"var o = Object.hasOwn( { 'a': 1, 'b': 2 }, 'a' )\n","Object.is":"var o = Object.is( 1, 1 )\nvar o = Object.is( 1, '1' )\n","Object.isExtensible":"var o = Object.isExtensible( { 'a': 1 } )\n","Object.isFrozen":"var o = Object.isFrozen( { 'a': 1 } )\nvar o = Object.isFrozen( Object.freeze( { 'a': 1 } ) )\n","Object.isSealed":"var o = Object.isSealed( { 'a': 1 } )\nvar o = Object.isSealed( Object.seal( { 'a': 1 } ) )\n","Object.keys":"var o = Object.keys( { 'a': 1, 'b': 2 } )\n","Object.preventExtensions":"var o = Object.preventExtensions( { 'a': 1 } )\no.b = 2;\no\n","Object.seal":"var o = Object.seal( { 'a': 1 } )\no.b = 2;\no\ndelete o.a;\no\n","Object.setPrototypeOf":"var o = Object.setPrototypeOf( { 'a': 1 }, { 'b': 2 } )\no.b\n","Object.values":"var o = Object.values( { 'a': 1, 'b': 2 } )\n","Object.prototype.toLocaleString":"var o = Object.prototype.toLocaleString.call( { 'a': 1, 'b': 2 } )\n","Object.prototype.toString":"var o = Object.prototype.toString.call( { 'a': 1, 'b': 2 } )\n","Object.prototype.valueOf":"var o = Object.prototype.valueOf.call( { 'a': 1, 'b': 2 } )\n","Object.prototype.hasOwnProperty":"var o = Object.prototype.hasOwnProperty.call( { 'a': 1, 'b': 2 }, 'a' )\n","Object.prototype.isPrototypeOf":"var p = { 'a': 1 };\nvar o = { '__proto__': p };\nvar b = o.isPrototypeOf( p );\n","Object.prototype.propertyIsEnumerable":"var o = { 'a': 1, 'b': 2 };\nvar bool = Object.prototype.propertyIsEnumerable.call( o, 'a' )\n","Object.prototype.constructor":"var o = new Object( null );\nvar ctr = o.constructor;\n","objectEntries":"var obj = { 'beep': 'boop', 'foo': 'bar' };\nvar entries = objectEntries( obj )\n","objectEntriesIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar entries = objectEntriesIn( obj )\n","objectFromEntries":"var entries = [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ];\nvar obj = objectFromEntries( entries )\n","objectInverse":"var obj = { 'a': 'beep', 'b': 'boop' };\nvar out = objectInverse( obj )\nobj = { 'a': 'beep', 'b': 'beep' };\nout = objectInverse( obj )\nobj = {};\nobj.a = 'beep';\nobj.b = 'boop';\nobj.c = 'beep';\nout = objectInverse( obj, { 'duplicates': false } )\n","objectInverseBy":"function transform( key, value ) { return key + value; };\nvar obj = { 'a': 'beep', 'b': 'boop' };\nvar out = objectInverseBy( obj, transform )\nfunction transform( key, value ) { return value; };\nobj = { 'a': 'beep', 'b': 'beep' };\nout = objectInverseBy( obj, transform )\nobj = {};\nobj.a = 'beep';\nobj.b = 'boop';\nobj.c = 'beep';\nout = objectInverseBy( obj, { 'duplicates': false }, transform )\n","objectKeys":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = objectKeys( obj )\n","objectValues":"var obj = { 'beep': 'boop', 'foo': 'bar' };\nvar vals = objectValues( obj )\n","objectValuesIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar values = objectValuesIn( obj )\n","omit":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = omit( obj1, 'b' )\n","omitBy":"function predicate( key, value ) { return ( value > 1 ); };\nvar obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = omitBy( obj1, predicate )\n","open":"function onOpen( error, fd ) {\n if ( error ) {\n     console.error( error.message );\n } else {\n     close.sync( fd );\n }\n };\nopen( './beep/boop.txt', onOpen );\n","open.sync":"var fd = open.sync( './beep/boop.txt' );\nif ( !isError( fd ) ) { close.sync( fd ); };\n","openURL":"var out = openURL( 'https://google.com' );\n","ordinalize":"var out = ordinalize( '1' )\nout = ordinalize( 2, { 'suffixOnly': true } )\nout = ordinalize( '3', { 'lang': 'es' } )\n","PACE_BOSTON_HOUSE_PRICES":"var data = PACE_BOSTON_HOUSE_PRICES()\n","pad":"var out = pad( 'a', 5 )\nout = pad( 'a', 10, { 'lpad': 'b' } )\nout = pad( 'a', 12, { 'rpad': 'b' } )\nvar opts = { 'lpad': 'a', 'rpad': 'c' };\nout = pad( 'b', 11, opts )\nopts.centerRight = false;\nout = pad( 'b', 10, opts )\nopts.centerRight = true;\nout = pad( 'b', 10, opts )\nopts = { 'lpad': 'boop', 'rpad': 'woot' };\nout = pad( 'beep', 10, opts )\nout = pad( 'beep', 2 )\nopts = { 'lpad': 'b' };\nout = pad( 'beep', 2, opts )\nopts = { 'lpad': '@', 'rpad': '!' };\nout = pad( 'beep', 2, opts )\nout = pad( 'abcdef', 3, opts )\nopts.centerRight = true;\nout = pad( 'abcdef', 3, opts )\n","padjust":"var pvalues = [ 0.008, 0.03, 0.123, 0.6, 0.2 ];\nvar out = padjust( pvalues, 'bh' )\nout = padjust( pvalues, 'bonferroni' )\nout = padjust( pvalues, 'by' )\nout = padjust( pvalues, 'holm' )\nout = padjust( pvalues, 'hommel' )\n","papply":"function add( x, y ) { return x + y; };\nvar add2 = papply( add, 2 );\nvar sum = add2( 3 )\n","papplyRight":"function say( text, name ) { return text + ', ' + name + '.'; };\nvar toGrace = papplyRight( say, 'Grace Hopper' );\nvar str = toGrace( 'Hello' )\nstr = toGrace( 'Thank you' )\n","parallel":"function done( error ) { if ( error ) { throw error; } };\nvar files = [ './a.js', './b.js' ];\nparallel( files, done );\nvar opts = { 'workers': 8 };\nparallel( files, opts, done );\n","parseJSON":"var obj = parseJSON( '{\"beep\":\"boop\"}' )\nfunction reviver( key, value ) {\n if ( key === '' ) { return value; }\n if ( key === 'beep' ) { return value; }\n };\nvar str = '{\"beep\":\"boop\",\"a\":\"b\"}';\nvar out = parseJSON( str, reviver )\n","pascalcase":"var out = pascalcase( 'Hello World!' )\nout = pascalcase( 'beep boop' )\n","PATH_DELIMITER":"PATH_DELIMITER\nvar path = '/usr/bin:/bin:/usr/sbin';\nvar parts = path.split( PATH_DELIMITER )\npath = 'C:\\\\Windows\\\\system32;C:\\\\Windows';\nparts = path.split( PATH_DELIMITER )\n","PATH_DELIMITER_POSIX":"PATH_DELIMITER_POSIX\nvar PATH = '/usr/bin:/bin:/usr/sbin:/sbin:/usr/local/bin';\nvar paths = PATH.split( PATH_DELIMITER_POSIX )\n","PATH_DELIMITER_WIN32":"PATH_DELIMITER_WIN32\nvar PATH = 'C:\\\\Windows\\\\system32;C:\\\\Windows;C:\\\\Program Files\\\\node\\\\';\nvar paths = PATH.split( PATH_DELIMITER_WIN32 )\n","PATH_SEP":"PATH_SEP\nvar parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP )\nparts = 'foo/bar/baz'.split( PATH_SEP )\n","PATH_SEP_POSIX":"PATH_SEP_POSIX\nvar parts = 'foo/bar/baz'.split( PATH_SEP_POSIX )\n","PATH_SEP_WIN32":"PATH_SEP_WIN32\nvar parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP_WIN32 )\n","pcorrtest":"var rho = 0.5;\nvar x = new Array( 300 );\nvar y = new Array( 300 );\nfor ( var i = 0; i < 300; i++ ) {\nx[ i ] = base.random.normal( 0.0, 1.0 );\ny[ i ] = ( rho * x[ i ] ) + base.random.normal( 0.0,\nbase.sqrt( 1.0 - (rho*rho) ) );\n }\nvar out = pcorrtest( x, y )\nvar table = out.print()\n","percentEncode":"var out = percentEncode( '☃' )\n","PHI":"PHI\n","PI":"PI\n","PI_SQUARED":"PI_SQUARED\n","pick":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = pick( obj1, 'b' )\n","pickArguments":"function foo( a, b ) { return [ a, b ]; };\nvar bar = pickArguments( foo, [ 0, 2 ] );\nvar out = bar( 1, 2, 3 )\n","pickBy":"function predicate( key, value ) {\n return ( value > 1 );\n };\nvar obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = pickBy( obj1, predicate )\n","PINF":"PINF\n","pkg2alias":"var v = pkg2alias( '@stdlib/math/base/special/sin' )\nv = pkg2alias( '@stdlib/math-base-special-sin' )\n","pkg2related":"var v = pkg2related( '@stdlib/math/base/special/sin' )\nv = pkg2related( '@stdlib/math-base-special-sin' )\n","pkg2standalone":"var v = pkg2standalone( '@stdlib/math/base/special/sin' )\n","PLATFORM":"PLATFORM\n","plot":"var plot = plot()\nvar x = [[0.10, 0.20, 0.30]];\nvar y = [[0.52, 0.79, 0.64]];\nplot = plot( x, y )\n","Plot":"var plot = Plot()\nvar x = [[0.10, 0.20, 0.30]];\nvar y = [[0.52, 0.79, 0.64]];\nplot = Plot( x, y )\n","pluck":"var arr = [\n { 'a': 1, 'b': 2 },\n { 'a': 0.5, 'b': 3 }\n ];\nvar out = pluck( arr, 'a' )\narr = [\n { 'a': 1, 'b': 2 },\n { 'a': 0.5, 'b': 3 }\n ];\nout = pluck( arr, 'a', { 'copy': false } )\nvar bool = ( arr[ 0 ] === out[ 0 ] )\n","pop":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar out = pop( arr )\narr = new Float64Array( [ 1.0, 2.0 ] );\nout = pop( arr )\narr = { 'length': 2, '0': 1.0, '1': 2.0 };\nout = pop( arr )\n","porterStemmer":"var out = porterStemmer( 'walking' )\nout = porterStemmer( 'walked' )\nout = porterStemmer( 'walks' )\nout = porterStemmer( '' )\n","prepend":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = prepend( arr, [ 6.0, 7.0 ] )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = prepend( arr, [ 3.0, 4.0 ] )\narr = { 'length': 1, '0': 1.0 };\narr = prepend( arr, [ 2.0, 3.0 ] )\n","prevGraphemeClusterBreak":"var out = prevGraphemeClusterBreak( 'last man standing', 4 )\nout = prevGraphemeClusterBreak( 'presidential election', 8 )\nout = prevGraphemeClusterBreak( 'अनुच्छेद', 2 )\nout = prevGraphemeClusterBreak( '🌷', 1 )\n","PRIMES_100K":"var list = PRIMES_100K()\n","properties":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar props = properties( obj )\n","propertiesIn":"var props = propertiesIn( [] )\n","propertyDescriptor":"var obj = { 'a': 'b' };\nvar desc = propertyDescriptor( obj, 'a' )\n","propertyDescriptorIn":"var obj = { 'a': 'b' };\nvar desc = propertyDescriptorIn( obj, 'a' )\n","propertyDescriptors":"var obj = { 'a': 'b' };\nvar desc = propertyDescriptors( obj )\n","propertyDescriptorsIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar desc = propertyDescriptorsIn( obj )\n","propertyNames":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = propertyNames( obj )\n","propertyNamesIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = propertyNamesIn( obj )\n","propertySymbols":"var s = propertySymbols( {} )\n","propertySymbolsIn":"var s = propertySymbolsIn( [] )\n","Proxy":"function get( obj, prop ) { return obj[ prop ] * 2.0 };\nvar h = { 'get': get };\nvar p = new Proxy( {}, h );\np.a = 3.14;\np.a\n","Proxy.revocable":"function get( obj, prop ) { return obj[ prop ] * 2.0 };\nvar h = { 'get': get };\nvar p = Proxy.revocable( {}, h );\np.proxy.a = 3.14;\np.proxy.a\np.revoke();\n","push":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = push( arr, 6.0, 7.0 )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = push( arr, 3.0, 4.0 )\narr = { 'length': 0 };\narr = push( arr, 1.0, 2.0 )\n","quarterOfYear":"var q = quarterOfYear( new Date() )\nq = quarterOfYear( 4 )\nq = quarterOfYear( 'June' )\nq = quarterOfYear( 'April' )\nq = quarterOfYear( 'apr' )\n","random.array.arcsine":"var out = random.array.arcsine( 3, 2.0, 5.0 )\n","random.array.arcsine.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.arcsine.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.arcsine.factory":"var fcn = random.array.arcsine.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.arcsine.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.arcsine.PRNG":"var prng = random.array.arcsine.PRNG;\n","random.array.arcsine.seed":"var seed = random.array.arcsine.seed;\n","random.array.arcsine.seedLength":"var len = random.array.arcsine.seedLength;\n","random.array.arcsine.state":"var out = random.array.arcsine( 3, 2.0, 5.0 )\nvar state = random.array.arcsine.state\nout = random.array.arcsine( 3, 2.0, 5.0 )\nout = random.array.arcsine( 3, 2.0, 5.0 )\nrandom.array.arcsine.state = state;\nout = random.array.arcsine( 3, 2.0, 5.0 )\n","random.array.arcsine.stateLength":"var len = random.array.arcsine.stateLength;\n","random.array.arcsine.byteLength":"var sz = random.array.arcsine.byteLength;\n","random.array.bernoulli":"var out = random.array.bernoulli( 3, 0.5 )\n","random.array.bernoulli.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.bernoulli.assign( 0.5, x )\nvar bool = ( out === x )\n","random.array.bernoulli.factory":"var fcn = random.array.bernoulli.factory();\nvar out = fcn( 3, 0.5 )\nfcn = random.array.bernoulli.factory( 0.5 );\nout = fcn( 3 )\n","random.array.bernoulli.PRNG":"var prng = random.array.bernoulli.PRNG;\n","random.array.bernoulli.seed":"var seed = random.array.bernoulli.seed;\n","random.array.bernoulli.seedLength":"var len = random.array.bernoulli.seedLength;\n","random.array.bernoulli.state":"var out = random.array.bernoulli( 3, 0.5 )\nvar state = random.array.bernoulli.state\nout = random.array.bernoulli( 3, 0.5 )\nout = random.array.bernoulli( 3, 0.5 )\nrandom.array.bernoulli.state = state;\nout = random.array.bernoulli( 3, 0.5 )\n","random.array.bernoulli.stateLength":"var len = random.array.bernoulli.stateLength;\n","random.array.bernoulli.byteLength":"var sz = random.array.bernoulli.byteLength;\n","random.array.beta":"var out = random.array.beta( 3, 2.0, 5.0 )\n","random.array.beta.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.beta.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.beta.factory":"var fcn = random.array.beta.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.beta.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.beta.PRNG":"var prng = random.array.beta.PRNG;\n","random.array.beta.seed":"var seed = random.array.beta.seed;\n","random.array.beta.seedLength":"var len = random.array.beta.seedLength;\n","random.array.beta.state":"var out = random.array.beta( 3, 2.0, 5.0 )\nvar state = random.array.beta.state\nout = random.array.beta( 3, 2.0, 5.0 )\nout = random.array.beta( 3, 2.0, 5.0 )\nrandom.array.beta.state = state;\nout = random.array.beta( 3, 2.0, 5.0 )\n","random.array.beta.stateLength":"var len = random.array.beta.stateLength;\n","random.array.beta.byteLength":"var sz = random.array.beta.byteLength;\n","random.array.betaprime":"var out = random.array.betaprime( 3, 2.0, 5.0 )\n","random.array.betaprime.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.betaprime.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.betaprime.factory":"var fcn = random.array.betaprime.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.betaprime.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.betaprime.PRNG":"var prng = random.array.betaprime.PRNG;\n","random.array.betaprime.seed":"var seed = random.array.betaprime.seed;\n","random.array.betaprime.seedLength":"var len = random.array.betaprime.seedLength;\n","random.array.betaprime.state":"var out = random.array.betaprime( 3, 2.0, 5.0 )\nvar state = random.array.betaprime.state\nout = random.array.betaprime( 3, 2.0, 5.0 )\nout = random.array.betaprime( 3, 2.0, 5.0 )\nrandom.array.betaprime.state = state;\nout = random.array.betaprime( 3, 2.0, 5.0 )\n","random.array.betaprime.stateLength":"var len = random.array.betaprime.stateLength;\n","random.array.betaprime.byteLength":"var sz = random.array.betaprime.byteLength;\n","random.array.binomial":"var out = random.array.binomial( 3, 17, 0.5 )\n","random.array.binomial.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.binomial.assign( 17, 0.5, x )\nvar bool = ( out === x )\n","random.array.binomial.factory":"var fcn = random.array.binomial.factory();\nvar out = fcn( 3, 17, 0.5 )\nfcn = random.array.binomial.factory( 17, 0.5 );\nout = fcn( 3 )\n","random.array.binomial.PRNG":"var prng = random.array.binomial.PRNG;\n","random.array.binomial.seed":"var seed = random.array.binomial.seed;\n","random.array.binomial.seedLength":"var len = random.array.binomial.seedLength;\n","random.array.binomial.state":"var out = random.array.binomial( 3, 17, 0.5 )\nvar state = random.array.binomial.state\nout = random.array.binomial( 3, 17, 0.5 )\nout = random.array.binomial( 3, 17, 0.5 )\nrandom.array.binomial.state = state;\nout = random.array.binomial( 3, 17, 0.5 )\n","random.array.binomial.stateLength":"var len = random.array.binomial.stateLength;\n","random.array.binomial.byteLength":"var sz = random.array.binomial.byteLength;\n","random.array.cauchy":"var out = random.array.cauchy( 3, 2.0, 5.0 )\n","random.array.cauchy.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.cauchy.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.cauchy.factory":"var fcn = random.array.cauchy.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.cauchy.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.cauchy.PRNG":"var prng = random.array.cauchy.PRNG;\n","random.array.cauchy.seed":"var seed = random.array.cauchy.seed;\n","random.array.cauchy.seedLength":"var len = random.array.cauchy.seedLength;\n","random.array.cauchy.state":"var out = random.array.cauchy( 3, 2.0, 5.0 )\nvar state = random.array.cauchy.state\nout = random.array.cauchy( 3, 2.0, 5.0 )\nout = random.array.cauchy( 3, 2.0, 5.0 )\nrandom.array.cauchy.state = state;\nout = random.array.cauchy( 3, 2.0, 5.0 )\n","random.array.cauchy.stateLength":"var len = random.array.cauchy.stateLength;\n","random.array.cauchy.byteLength":"var sz = random.array.cauchy.byteLength;\n","random.array.chi":"var out = random.array.chi( 3, 2.0 )\n","random.array.chi.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.chi.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.chi.factory":"var fcn = random.array.chi.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.chi.factory( 2.0 );\nout = fcn( 3 )\n","random.array.chi.PRNG":"var prng = random.array.chi.PRNG;\n","random.array.chi.seed":"var seed = random.array.chi.seed;\n","random.array.chi.seedLength":"var len = random.array.chi.seedLength;\n","random.array.chi.state":"var out = random.array.chi( 3, 2.0 )\nvar state = random.array.chi.state\nout = random.array.chi( 3, 2.0 )\nout = random.array.chi( 3, 2.0 )\nrandom.array.chi.state = state;\nout = random.array.chi( 3, 2.0 )\n","random.array.chi.stateLength":"var len = random.array.chi.stateLength;\n","random.array.chi.byteLength":"var sz = random.array.chi.byteLength;\n","random.array.chisquare":"var out = random.array.chisquare( 3, 2.0 )\n","random.array.chisquare.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.chisquare.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.chisquare.factory":"var fcn = random.array.chisquare.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.chisquare.factory( 2.0 );\nout = fcn( 3 )\n","random.array.chisquare.PRNG":"var prng = random.array.chisquare.PRNG;\n","random.array.chisquare.seed":"var seed = random.array.chisquare.seed;\n","random.array.chisquare.seedLength":"var len = random.array.chisquare.seedLength;\n","random.array.chisquare.state":"var out = random.array.chisquare( 3, 2.0 )\nvar state = random.array.chisquare.state\nout = random.array.chisquare( 3, 2.0 )\nout = random.array.chisquare( 3, 2.0 )\nrandom.array.chisquare.state = state;\nout = random.array.chisquare( 3, 2.0 )\n","random.array.chisquare.stateLength":"var len = random.array.chisquare.stateLength;\n","random.array.chisquare.byteLength":"var sz = random.array.chisquare.byteLength;\n","random.array.cosine":"var out = random.array.cosine( 3, 2.0, 5.0 )\n","random.array.cosine.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.cosine.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.cosine.factory":"var fcn = random.array.cosine.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.cosine.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.cosine.PRNG":"var prng = random.array.cosine.PRNG;\n","random.array.cosine.seed":"var seed = random.array.cosine.seed;\n","random.array.cosine.seedLength":"var len = random.array.cosine.seedLength;\n","random.array.cosine.state":"var out = random.array.cosine( 3, 2.0, 5.0 )\nvar state = random.array.cosine.state\nout = random.array.cosine( 3, 2.0, 5.0 )\nout = random.array.cosine( 3, 2.0, 5.0 )\nrandom.array.cosine.state = state;\nout = random.array.cosine( 3, 2.0, 5.0 )\n","random.array.cosine.stateLength":"var len = random.array.cosine.stateLength;\n","random.array.cosine.byteLength":"var sz = random.array.cosine.byteLength;\n","random.array.discreteUniform":"var out = random.array.discreteUniform( 3, -10, 10 )\n","random.array.discreteUniform.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.discreteUniform.assign( -10, 10, x )\nvar bool = ( out === x )\n","random.array.discreteUniform.factory":"var fcn = random.array.discreteUniform.factory();\nvar out = fcn( 3, -10, 10 )\nfcn = random.array.discreteUniform.factory( -10, 10 );\nout = fcn( 3 )\n","random.array.discreteUniform.PRNG":"var prng = random.array.discreteUniform.PRNG;\n","random.array.discreteUniform.seed":"var seed = random.array.discreteUniform.seed;\n","random.array.discreteUniform.seedLength":"var len = random.array.discreteUniform.seedLength;\n","random.array.discreteUniform.state":"var out = random.array.discreteUniform( 3, -10, 10 )\nvar state = random.array.discreteUniform.state\nout = random.array.discreteUniform( 3, -10, 10 )\nout = random.array.discreteUniform( 3, -10, 10 )\nrandom.array.discreteUniform.state = state;\nout = random.array.discreteUniform( 3, -10, 10 )\n","random.array.discreteUniform.stateLength":"var len = random.array.discreteUniform.stateLength;\n","random.array.discreteUniform.byteLength":"var sz = random.array.discreteUniform.byteLength;\n","random.array.erlang":"var out = random.array.erlang( 3, 2, 5.0 )\n","random.array.erlang.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.erlang.assign( 2, 5.0, x )\nvar bool = ( out === x )\n","random.array.erlang.factory":"var fcn = random.array.erlang.factory();\nvar out = fcn( 3, 2, 5.0 )\nfcn = random.array.erlang.factory( 2, 5.0 );\nout = fcn( 3 )\n","random.array.erlang.PRNG":"var prng = random.array.erlang.PRNG;\n","random.array.erlang.seed":"var seed = random.array.erlang.seed;\n","random.array.erlang.seedLength":"var len = random.array.erlang.seedLength;\n","random.array.erlang.state":"var out = random.array.erlang( 3, 2, 5.0 )\nvar state = random.array.erlang.state\nout = random.array.erlang( 3, 2, 5.0 )\nout = random.array.erlang( 3, 2, 5.0 )\nrandom.array.erlang.state = state;\nout = random.array.erlang( 3, 2, 5.0 )\n","random.array.erlang.stateLength":"var len = random.array.erlang.stateLength;\n","random.array.erlang.byteLength":"var sz = random.array.erlang.byteLength;\n","random.array.exponential":"var out = random.array.exponential( 3, 2.0 )\n","random.array.exponential.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.exponential.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.exponential.factory":"var fcn = random.array.exponential.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.exponential.factory( 2.0 );\nout = fcn( 3 )\n","random.array.exponential.PRNG":"var prng = random.array.exponential.PRNG;\n","random.array.exponential.seed":"var seed = random.array.exponential.seed;\n","random.array.exponential.seedLength":"var len = random.array.exponential.seedLength;\n","random.array.exponential.state":"var out = random.array.exponential( 3, 2.0 )\nvar state = random.array.exponential.state\nout = random.array.exponential( 3, 2.0 )\nout = random.array.exponential( 3, 2.0 )\nrandom.array.exponential.state = state;\nout = random.array.exponential( 3, 2.0 )\n","random.array.exponential.stateLength":"var len = random.array.exponential.stateLength;\n","random.array.exponential.byteLength":"var sz = random.array.exponential.byteLength;\n","random.array.f":"var out = random.array.f( 3, 2.0, 5.0 )\n","random.array.f.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.f.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.f.factory":"var fcn = random.array.f.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.f.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.f.PRNG":"var prng = random.array.f.PRNG;\n","random.array.f.seed":"var seed = random.array.f.seed;\n","random.array.f.seedLength":"var len = random.array.f.seedLength;\n","random.array.f.state":"var out = random.array.f( 3, 2.0, 5.0 )\nvar state = random.array.f.state\nout = random.array.f( 3, 2.0, 5.0 )\nout = random.array.f( 3, 2.0, 5.0 )\nrandom.array.f.state = state;\nout = random.array.f( 3, 2.0, 5.0 )\n","random.array.f.stateLength":"var len = random.array.f.stateLength;\n","random.array.f.byteLength":"var sz = random.array.f.byteLength;\n","random.array.frechet":"var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n","random.array.frechet.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.frechet.assign( 2.0, 5.0, 3.0, x )\nvar bool = ( out === x )\n","random.array.frechet.factory":"var fcn = random.array.frechet.factory();\nvar out = fcn( 3, 2.0, 5.0, 3.0 )\nfcn = random.array.frechet.factory( 2.0, 5.0, 3.0 );\nout = fcn( 3 )\n","random.array.frechet.PRNG":"var prng = random.array.frechet.PRNG;\n","random.array.frechet.seed":"var seed = random.array.frechet.seed;\n","random.array.frechet.seedLength":"var len = random.array.frechet.seedLength;\n","random.array.frechet.state":"var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\nvar state = random.array.frechet.state\nout = random.array.frechet( 3, 2.0, 5.0, 3.0 )\nout = random.array.frechet( 3, 2.0, 5.0, 3.0 )\nrandom.array.frechet.state = state;\nout = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n","random.array.frechet.stateLength":"var len = random.array.frechet.stateLength;\n","random.array.frechet.byteLength":"var sz = random.array.frechet.byteLength;\n","random.array.gamma":"var out = random.array.gamma( 3, 2.0, 5.0 )\n","random.array.gamma.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.gamma.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.gamma.factory":"var fcn = random.array.gamma.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.gamma.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.gamma.PRNG":"var prng = random.array.gamma.PRNG;\n","random.array.gamma.seed":"var seed = random.array.gamma.seed;\n","random.array.gamma.seedLength":"var len = random.array.gamma.seedLength;\n","random.array.gamma.state":"var out = random.array.gamma( 3, 2.0, 5.0 )\nvar state = random.array.gamma.state\nout = random.array.gamma( 3, 2.0, 5.0 )\nout = random.array.gamma( 3, 2.0, 5.0 )\nrandom.array.gamma.state = state;\nout = random.array.gamma( 3, 2.0, 5.0 )\n","random.array.gamma.stateLength":"var len = random.array.gamma.stateLength;\n","random.array.gamma.byteLength":"var sz = random.array.gamma.byteLength;\n","random.array.geometric":"var out = random.array.geometric( 3, 0.01 )\n","random.array.geometric.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.geometric.assign( 0.01, x )\nvar bool = ( out === x )\n","random.array.geometric.factory":"var fcn = random.array.geometric.factory();\nvar out = fcn( 3, 0.01 )\nfcn = random.array.geometric.factory( 0.01 );\nout = fcn( 3 )\n","random.array.geometric.PRNG":"var prng = random.array.geometric.PRNG;\n","random.array.geometric.seed":"var seed = random.array.geometric.seed;\n","random.array.geometric.seedLength":"var len = random.array.geometric.seedLength;\n","random.array.geometric.state":"var out = random.array.geometric( 3, 0.01 )\nvar state = random.array.geometric.state\nout = random.array.geometric( 3, 0.01 )\nout = random.array.geometric( 3, 0.01 )\nrandom.array.geometric.state = state;\nout = random.array.geometric( 3, 0.01 )\n","random.array.geometric.stateLength":"var len = random.array.geometric.stateLength;\n","random.array.geometric.byteLength":"var sz = random.array.geometric.byteLength;\n","random.array.gumbel":"var out = random.array.gumbel( 3, 2.0, 5.0 )\n","random.array.gumbel.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.gumbel.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.gumbel.factory":"var fcn = random.array.gumbel.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.gumbel.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.gumbel.PRNG":"var prng = random.array.gumbel.PRNG;\n","random.array.gumbel.seed":"var seed = random.array.gumbel.seed;\n","random.array.gumbel.seedLength":"var len = random.array.gumbel.seedLength;\n","random.array.gumbel.state":"var out = random.array.gumbel( 3, 2.0, 5.0 )\nvar state = random.array.gumbel.state\nout = random.array.gumbel( 3, 2.0, 5.0 )\nout = random.array.gumbel( 3, 2.0, 5.0 )\nrandom.array.gumbel.state = state;\nout = random.array.gumbel( 3, 2.0, 5.0 )\n","random.array.gumbel.stateLength":"var len = random.array.gumbel.stateLength;\n","random.array.gumbel.byteLength":"var sz = random.array.gumbel.byteLength;\n","random.array.hypergeometric":"var out = random.array.hypergeometric( 3, 20, 10, 7 )\n","random.array.hypergeometric.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.hypergeometric.assign( 20, 10, 7, x )\nvar bool = ( out === x )\n","random.array.hypergeometric.factory":"var fcn = random.array.hypergeometric.factory();\nvar out = fcn( 3, 20, 10, 7 )\nfcn = random.array.hypergeometric.factory( 20, 10, 7 );\nout = fcn( 3 )\n","random.array.hypergeometric.PRNG":"var prng = random.array.hypergeometric.PRNG;\n","random.array.hypergeometric.seed":"var seed = random.array.hypergeometric.seed;\n","random.array.hypergeometric.seedLength":"var len = random.array.hypergeometric.seedLength;\n","random.array.hypergeometric.state":"var out = random.array.hypergeometric( 3, 20, 10, 7 )\nvar state = random.array.hypergeometric.state\nout = random.array.hypergeometric( 3, 20, 10, 7 )\nout = random.array.hypergeometric( 3, 20, 10, 7 )\nrandom.array.hypergeometric.state = state;\nout = random.array.hypergeometric( 3, 20, 10, 7 )\n","random.array.hypergeometric.stateLength":"var len = random.array.hypergeometric.stateLength;\n","random.array.hypergeometric.byteLength":"var sz = random.array.hypergeometric.byteLength;\n","random.array.invgamma":"var out = random.array.invgamma( 3, 2.0, 5.0 )\n","random.array.invgamma.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.invgamma.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.invgamma.factory":"var fcn = random.array.invgamma.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.invgamma.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.invgamma.PRNG":"var prng = random.array.invgamma.PRNG;\n","random.array.invgamma.seed":"var seed = random.array.invgamma.seed;\n","random.array.invgamma.seedLength":"var len = random.array.invgamma.seedLength;\n","random.array.invgamma.state":"var out = random.array.invgamma( 3, 2.0, 5.0 )\nvar state = random.array.invgamma.state\nout = random.array.invgamma( 3, 2.0, 5.0 )\nout = random.array.invgamma( 3, 2.0, 5.0 )\nrandom.array.invgamma.state = state;\nout = random.array.invgamma( 3, 2.0, 5.0 )\n","random.array.invgamma.stateLength":"var len = random.array.invgamma.stateLength;\n","random.array.invgamma.byteLength":"var sz = random.array.invgamma.byteLength;\n","random.array.kumaraswamy":"var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n","random.array.kumaraswamy.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.kumaraswamy.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.kumaraswamy.factory":"var fcn = random.array.kumaraswamy.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.kumaraswamy.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.kumaraswamy.PRNG":"var prng = random.array.kumaraswamy.PRNG;\n","random.array.kumaraswamy.seed":"var seed = random.array.kumaraswamy.seed;\n","random.array.kumaraswamy.seedLength":"var len = random.array.kumaraswamy.seedLength;\n","random.array.kumaraswamy.state":"var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\nvar state = random.array.kumaraswamy.state\nout = random.array.kumaraswamy( 3, 2.0, 5.0 )\nout = random.array.kumaraswamy( 3, 2.0, 5.0 )\nrandom.array.kumaraswamy.state = state;\nout = random.array.kumaraswamy( 3, 2.0, 5.0 )\n","random.array.kumaraswamy.stateLength":"var len = random.array.kumaraswamy.stateLength;\n","random.array.kumaraswamy.byteLength":"var sz = random.array.kumaraswamy.byteLength;\n","random.array.laplace":"var out = random.array.laplace( 3, 2.0, 5.0 )\n","random.array.laplace.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.laplace.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.laplace.factory":"var fcn = random.array.laplace.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.laplace.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.laplace.PRNG":"var prng = random.array.laplace.PRNG;\n","random.array.laplace.seed":"var seed = random.array.laplace.seed;\n","random.array.laplace.seedLength":"var len = random.array.laplace.seedLength;\n","random.array.laplace.state":"var out = random.array.laplace( 3, 2.0, 5.0 )\nvar state = random.array.laplace.state\nout = random.array.laplace( 3, 2.0, 5.0 )\nout = random.array.laplace( 3, 2.0, 5.0 )\nrandom.array.laplace.state = state;\nout = random.array.laplace( 3, 2.0, 5.0 )\n","random.array.laplace.stateLength":"var len = random.array.laplace.stateLength;\n","random.array.laplace.byteLength":"var sz = random.array.laplace.byteLength;\n","random.array.levy":"var out = random.array.levy( 3, 2.0, 5.0 )\n","random.array.levy.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.levy.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.levy.factory":"var fcn = random.array.levy.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.levy.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.levy.PRNG":"var prng = random.array.levy.PRNG;\n","random.array.levy.seed":"var seed = random.array.levy.seed;\n","random.array.levy.seedLength":"var len = random.array.levy.seedLength;\n","random.array.levy.state":"var out = random.array.levy( 3, 2.0, 5.0 )\nvar state = random.array.levy.state\nout = random.array.levy( 3, 2.0, 5.0 )\nout = random.array.levy( 3, 2.0, 5.0 )\nrandom.array.levy.state = state;\nout = random.array.levy( 3, 2.0, 5.0 )\n","random.array.levy.stateLength":"var len = random.array.levy.stateLength;\n","random.array.levy.byteLength":"var sz = random.array.levy.byteLength;\n","random.array.logistic":"var out = random.array.logistic( 3, 2.0, 5.0 )\n","random.array.logistic.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.logistic.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.logistic.factory":"var fcn = random.array.logistic.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.logistic.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.logistic.PRNG":"var prng = random.array.logistic.PRNG;\n","random.array.logistic.seed":"var seed = random.array.logistic.seed;\n","random.array.logistic.seedLength":"var len = random.array.logistic.seedLength;\n","random.array.logistic.state":"var out = random.array.logistic( 3, 2.0, 5.0 )\nvar state = random.array.logistic.state\nout = random.array.logistic( 3, 2.0, 5.0 )\nout = random.array.logistic( 3, 2.0, 5.0 )\nrandom.array.logistic.state = state;\nout = random.array.logistic( 3, 2.0, 5.0 )\n","random.array.logistic.stateLength":"var len = random.array.logistic.stateLength;\n","random.array.logistic.byteLength":"var sz = random.array.logistic.byteLength;\n","random.array.lognormal":"var out = random.array.lognormal( 3, 2.0, 5.0 )\n","random.array.lognormal.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.lognormal.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.lognormal.factory":"var fcn = random.array.lognormal.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.lognormal.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.lognormal.PRNG":"var prng = random.array.lognormal.PRNG;\n","random.array.lognormal.seed":"var seed = random.array.lognormal.seed;\n","random.array.lognormal.seedLength":"var len = random.array.lognormal.seedLength;\n","random.array.lognormal.state":"var out = random.array.lognormal( 3, 2.0, 5.0 )\nvar state = random.array.lognormal.state\nout = random.array.lognormal( 3, 2.0, 5.0 )\nout = random.array.lognormal( 3, 2.0, 5.0 )\nrandom.array.lognormal.state = state;\nout = random.array.lognormal( 3, 2.0, 5.0 )\n","random.array.lognormal.stateLength":"var len = random.array.lognormal.stateLength;\n","random.array.lognormal.byteLength":"var sz = random.array.lognormal.byteLength;\n","random.array.minstd":"var out = random.array.minstd( 3 )\n","random.array.minstd.normalized":"var out = random.array.minstd.normalized( 3 )\n","random.array.minstd.factory":"var fcn = random.array.minstd.factory();\nvar out = fcn( 3 )\n","random.array.minstd.PRNG":"var prng = random.array.minstd.PRNG;\n","random.array.minstd.seed":"var seed = random.array.minstd.seed;\n","random.array.minstd.seedLength":"var len = random.array.minstd.seedLength;\n","random.array.minstd.state":"var out = random.array.minstd( 3 )\nvar state = random.array.minstd.state;\nout = random.array.minstd( 3 )\nout = random.array.minstd( 3 )\nrandom.array.minstd.state = state;\nout = random.array.minstd( 3 )\n","random.array.minstd.stateLength":"var len = random.array.minstd.stateLength;\n","random.array.minstd.byteLength":"var sz = random.array.minstd.byteLength;\n","random.array.minstdShuffle":"var out = random.array.minstdShuffle( 3 )\n","random.array.minstdShuffle.normalized":"var out = random.array.minstdShuffle.normalized( 3 )\n","random.array.minstdShuffle.factory":"var fcn = random.array.minstdShuffle.factory();\nvar out = fcn( 3 )\n","random.array.minstdShuffle.PRNG":"var prng = random.array.minstdShuffle.PRNG;\n","random.array.minstdShuffle.seed":"var seed = random.array.minstdShuffle.seed;\n","random.array.minstdShuffle.seedLength":"var len = random.array.minstdShuffle.seedLength;\n","random.array.minstdShuffle.state":"var out = random.array.minstdShuffle( 3 )\nvar state = random.array.minstdShuffle.state;\nout = random.array.minstdShuffle( 3 )\nout = random.array.minstdShuffle( 3 )\nrandom.array.minstdShuffle.state = state;\nout = random.array.minstdShuffle( 3 )\n","random.array.minstdShuffle.stateLength":"var len = random.array.minstdShuffle.stateLength;\n","random.array.minstdShuffle.byteLength":"var sz = random.array.minstdShuffle.byteLength;\n","random.array.mt19937":"var out = random.array.mt19937( 3 )\n","random.array.mt19937.normalized":"var out = random.array.mt19937.normalized( 3 )\n","random.array.mt19937.factory":"var fcn = random.array.mt19937.factory();\nvar out = fcn( 3 )\n","random.array.mt19937.PRNG":"var prng = random.array.mt19937.PRNG;\n","random.array.mt19937.seed":"var seed = random.array.mt19937.seed;\n","random.array.mt19937.seedLength":"var len = random.array.mt19937.seedLength;\n","random.array.mt19937.state":"var out = random.array.mt19937( 3 )\nvar state = random.array.mt19937.state;\nout = random.array.mt19937( 3 )\nout = random.array.mt19937( 3 )\nrandom.array.mt19937.state = state;\nout = random.array.mt19937( 3 )\n","random.array.mt19937.stateLength":"var len = random.array.mt19937.stateLength;\n","random.array.mt19937.byteLength":"var sz = random.array.mt19937.byteLength;\n","random.array.negativeBinomial":"var out = random.array.negativeBinomial( 3, 10, 0.5 )\n","random.array.negativeBinomial.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.negativeBinomial.assign( 10, 0.5, x )\nvar bool = ( out === x )\n","random.array.negativeBinomial.factory":"var fcn = random.array.negativeBinomial.factory();\nvar out = fcn( 3, 10, 0.5 )\nfcn = random.array.negativeBinomial.factory( 10, 0.5 );\nout = fcn( 3 )\n","random.array.negativeBinomial.PRNG":"var prng = random.array.negativeBinomial.PRNG;\n","random.array.negativeBinomial.seed":"var seed = random.array.negativeBinomial.seed;\n","random.array.negativeBinomial.seedLength":"var len = random.array.negativeBinomial.seedLength;\n","random.array.negativeBinomial.state":"var out = random.array.negativeBinomial( 3, 10, 0.5 )\nvar state = random.array.negativeBinomial.state\nout = random.array.negativeBinomial( 3, 10, 0.5 )\nout = random.array.negativeBinomial( 3, 10, 0.5 )\nrandom.array.negativeBinomial.state = state;\nout = random.array.negativeBinomial( 3, 10, 0.5 )\n","random.array.negativeBinomial.stateLength":"var len = random.array.negativeBinomial.stateLength;\n","random.array.negativeBinomial.byteLength":"var sz = random.array.negativeBinomial.byteLength;\n","random.array.normal":"var out = random.array.normal( 3, 2.0, 5.0 )\n","random.array.normal.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.normal.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.normal.factory":"var fcn = random.array.normal.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.normal.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.normal.PRNG":"var prng = random.array.normal.PRNG;\n","random.array.normal.seed":"var seed = random.array.normal.seed;\n","random.array.normal.seedLength":"var len = random.array.normal.seedLength;\n","random.array.normal.state":"var out = random.array.normal( 3, 2.0, 5.0 )\nvar state = random.array.normal.state\nout = random.array.normal( 3, 2.0, 5.0 )\nout = random.array.normal( 3, 2.0, 5.0 )\nrandom.array.normal.state = state;\nout = random.array.normal( 3, 2.0, 5.0 )\n","random.array.normal.stateLength":"var len = random.array.normal.stateLength;\n","random.array.normal.byteLength":"var sz = random.array.normal.byteLength;\n","random.array.pareto1":"var out = random.array.pareto1( 3, 2.0, 5.0 )\n","random.array.pareto1.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.pareto1.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.pareto1.factory":"var fcn = random.array.pareto1.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.pareto1.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.pareto1.PRNG":"var prng = random.array.pareto1.PRNG;\n","random.array.pareto1.seed":"var seed = random.array.pareto1.seed;\n","random.array.pareto1.seedLength":"var len = random.array.pareto1.seedLength;\n","random.array.pareto1.state":"var out = random.array.pareto1( 3, 2.0, 5.0 )\nvar state = random.array.pareto1.state\nout = random.array.pareto1( 3, 2.0, 5.0 )\nout = random.array.pareto1( 3, 2.0, 5.0 )\nrandom.array.pareto1.state = state;\nout = random.array.pareto1( 3, 2.0, 5.0 )\n","random.array.pareto1.stateLength":"var len = random.array.pareto1.stateLength;\n","random.array.pareto1.byteLength":"var sz = random.array.pareto1.byteLength;\n","random.array.poisson":"var out = random.array.poisson( 3, 2.0 )\n","random.array.poisson.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.poisson.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.poisson.factory":"var fcn = random.array.poisson.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.poisson.factory( 2.0 );\nout = fcn( 3 )\n","random.array.poisson.PRNG":"var prng = random.array.poisson.PRNG;\n","random.array.poisson.seed":"var seed = random.array.poisson.seed;\n","random.array.poisson.seedLength":"var len = random.array.poisson.seedLength;\n","random.array.poisson.state":"var out = random.array.poisson( 3, 2.0 )\nvar state = random.array.poisson.state\nout = random.array.poisson( 3, 2.0 )\nout = random.array.poisson( 3, 2.0 )\nrandom.array.poisson.state = state;\nout = random.array.poisson( 3, 2.0 )\n","random.array.poisson.stateLength":"var len = random.array.poisson.stateLength;\n","random.array.poisson.byteLength":"var sz = random.array.poisson.byteLength;\n","random.array.randu":"var out = random.array.randu( 3 )\n","random.array.randu.factory":"var fcn = random.array.randu.factory();\nvar out = fcn( 3 )\n","random.array.randu.PRNG":"var prng = random.array.randu.PRNG;\n","random.array.randu.seed":"var seed = random.array.randu.seed;\n","random.array.randu.seedLength":"var len = random.array.randu.seedLength;\n","random.array.randu.state":"var out = random.array.randu( 3 )\nvar state = random.array.randu.state;\nout = random.array.randu( 3 )\nout = random.array.randu( 3 )\nrandom.array.randu.state = state;\nout = random.array.randu( 3 )\n","random.array.randu.stateLength":"var len = random.array.randu.stateLength;\n","random.array.randu.byteLength":"var sz = random.array.randu.byteLength;\n","random.array.rayleigh":"var out = random.array.rayleigh( 3, 2.0 )\n","random.array.rayleigh.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.rayleigh.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.rayleigh.factory":"var fcn = random.array.rayleigh.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.rayleigh.factory( 2.0 );\nout = fcn( 3 )\n","random.array.rayleigh.PRNG":"var prng = random.array.rayleigh.PRNG;\n","random.array.rayleigh.seed":"var seed = random.array.rayleigh.seed;\n","random.array.rayleigh.seedLength":"var len = random.array.rayleigh.seedLength;\n","random.array.rayleigh.state":"var out = random.array.rayleigh( 3, 2.0 )\nvar state = random.array.rayleigh.state\nout = random.array.rayleigh( 3, 2.0 )\nout = random.array.rayleigh( 3, 2.0 )\nrandom.array.rayleigh.state = state;\nout = random.array.rayleigh( 3, 2.0 )\n","random.array.rayleigh.stateLength":"var len = random.array.rayleigh.stateLength;\n","random.array.rayleigh.byteLength":"var sz = random.array.rayleigh.byteLength;\n","random.array.t":"var out = random.array.t( 3, 2.0 )\n","random.array.t.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.t.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.t.factory":"var fcn = random.array.t.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.t.factory( 2.0 );\nout = fcn( 3 )\n","random.array.t.PRNG":"var prng = random.array.t.PRNG;\n","random.array.t.seed":"var seed = random.array.t.seed;\n","random.array.t.seedLength":"var len = random.array.t.seedLength;\n","random.array.t.state":"var out = random.array.t( 3, 2.0 )\nvar state = random.array.t.state\nout = random.array.t( 3, 2.0 )\nout = random.array.t( 3, 2.0 )\nrandom.array.t.state = state;\nout = random.array.t( 3, 2.0 )\n","random.array.t.stateLength":"var len = random.array.t.stateLength;\n","random.array.t.byteLength":"var sz = random.array.t.byteLength;\n","random.array.triangular":"var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n","random.array.triangular.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.triangular.assign( 2.0, 5.0, 3.0, x )\nvar bool = ( out === x )\n","random.array.triangular.factory":"var fcn = random.array.triangular.factory();\nvar out = fcn( 3, 2.0, 5.0, 3.0 )\nfcn = random.array.triangular.factory( 2.0, 5.0, 3.0 );\nout = fcn( 3 )\n","random.array.triangular.PRNG":"var prng = random.array.triangular.PRNG;\n","random.array.triangular.seed":"var seed = random.array.triangular.seed;\n","random.array.triangular.seedLength":"var len = random.array.triangular.seedLength;\n","random.array.triangular.state":"var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\nvar state = random.array.triangular.state\nout = random.array.triangular( 3, 2.0, 5.0, 3.0 )\nout = random.array.triangular( 3, 2.0, 5.0, 3.0 )\nrandom.array.triangular.state = state;\nout = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n","random.array.triangular.stateLength":"var len = random.array.triangular.stateLength;\n","random.array.triangular.byteLength":"var sz = random.array.triangular.byteLength;\n","random.array.uniform":"var out = random.array.uniform( 3, 2.0, 5.0 )\n","random.array.uniform.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.uniform.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.uniform.factory":"var fcn = random.array.uniform.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.uniform.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.uniform.PRNG":"var prng = random.array.uniform.PRNG;\n","random.array.uniform.seed":"var seed = random.array.uniform.seed;\n","random.array.uniform.seedLength":"var len = random.array.uniform.seedLength;\n","random.array.uniform.state":"var out = random.array.uniform( 3, 2.0, 5.0 )\nvar state = random.array.uniform.state\nout = random.array.uniform( 3, 2.0, 5.0 )\nout = random.array.uniform( 3, 2.0, 5.0 )\nrandom.array.uniform.state = state;\nout = random.array.uniform( 3, 2.0, 5.0 )\n","random.array.uniform.stateLength":"var len = random.array.uniform.stateLength;\n","random.array.uniform.byteLength":"var sz = random.array.uniform.byteLength;\n","random.array.weibull":"var out = random.array.weibull( 3, 2.0, 5.0 )\n","random.array.weibull.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.weibull.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.weibull.factory":"var fcn = random.array.weibull.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.weibull.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.weibull.PRNG":"var prng = random.array.weibull.PRNG;\n","random.array.weibull.seed":"var seed = random.array.weibull.seed;\n","random.array.weibull.seedLength":"var len = random.array.weibull.seedLength;\n","random.array.weibull.state":"var out = random.array.weibull( 3, 2.0, 5.0 )\nvar state = random.array.weibull.state\nout = random.array.weibull( 3, 2.0, 5.0 )\nout = random.array.weibull( 3, 2.0, 5.0 )\nrandom.array.weibull.state = state;\nout = random.array.weibull( 3, 2.0, 5.0 )\n","random.array.weibull.stateLength":"var len = random.array.weibull.stateLength;\n","random.array.weibull.byteLength":"var sz = random.array.weibull.byteLength;\n","random.iterators.arcsine":"var it = random.iterators.arcsine( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.bernoulli":"var it = random.iterators.bernoulli( 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.beta":"var it = random.iterators.beta( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.betaprime":"var it = random.iterators.betaprime( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.binomial":"var it = random.iterators.binomial( 10, 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.boxMuller":"var it = random.iterators.boxMuller();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.cauchy":"var it = random.iterators.cauchy( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.chi":"var it = random.iterators.chi( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.chisquare":"var it = random.iterators.chisquare( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.cosine":"var it = random.iterators.cosine( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.discreteUniform":"var it = random.iterators.discreteUniform( 0, 3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.erlang":"var it = random.iterators.erlang( 1, 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.exponential":"var it = random.iterators.exponential( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.f":"var it = random.iterators.f( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.frechet":"var it = random.iterators.frechet( 1.0, 1.0, 0.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.gamma":"var it = random.iterators.gamma( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.geometric":"var it = random.iterators.geometric( 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.gumbel":"var it = random.iterators.gumbel( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.hypergeometric":"var it = random.iterators.hypergeometric( 20, 10, 7 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.improvedZiggurat":"var it = random.iterators.improvedZiggurat();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.invgamma":"var it = random.iterators.invgamma( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.kumaraswamy":"var it = random.iterators.kumaraswamy( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.laplace":"var it = random.iterators.laplace( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.levy":"var it = random.iterators.levy( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.logistic":"var it = random.iterators.logistic( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.lognormal":"var it = random.iterators.lognormal( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.minstd":"var it = random.iterators.minstd();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.minstdShuffle":"var it = random.iterators.minstdShuffle();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.mt19937":"var it = random.iterators.mt19937();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.negativeBinomial":"var it = random.iterators.negativeBinomial( 10, 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.normal":"var it = random.iterators.normal( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.pareto1":"var it = random.iterators.pareto1( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.poisson":"var it = random.iterators.poisson( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.randi":"var it = random.iterators.randi();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.randn":"var it = random.iterators.randn();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.randu":"var it = random.iterators.randu();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.rayleigh":"var it = random.iterators.rayleigh( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.t":"var it = random.iterators.t( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.triangular":"var it = random.iterators.triangular( 0.0, 1.0, 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.uniform":"var it = random.iterators.uniform( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.weibull":"var it = random.iterators.weibull( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.streams.arcsine":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.arcsine( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.arcsine.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.arcsine.factory( opts );\n","random.streams.arcsine.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.arcsine.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.bernoulli":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.bernoulli( 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.bernoulli.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.bernoulli.factory( opts );\n","random.streams.bernoulli.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.bernoulli.objectMode( 0.3, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.beta":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.beta( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.beta.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.beta.factory( opts );\n","random.streams.beta.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.beta.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.betaprime":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.betaprime( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.betaprime.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.betaprime.factory( opts );\n","random.streams.betaprime.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.betaprime.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.binomial":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.binomial( 20, 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.binomial.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.binomial.factory( opts );\n","random.streams.binomial.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.binomial.objectMode( 20, 0.5, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.boxMuller":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.boxMuller( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.boxMuller.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.boxMuller.factory( opts );\n","random.streams.boxMuller.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.boxMuller.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.cauchy":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cauchy( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.cauchy.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.cauchy.factory( opts );\n","random.streams.cauchy.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cauchy.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.chi":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chi( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.chi.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.chi.factory( opts );\n","random.streams.chi.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chi.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.chisquare":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chisquare( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.chisquare.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.chisquare.factory( opts );\n","random.streams.chisquare.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chisquare.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.cosine":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cosine( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.cosine.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.cosine.factory( opts );\n","random.streams.cosine.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cosine.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.discreteUniform":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.discreteUniform( 2, 5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.discreteUniform.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.discreteUniform.factory( opts );\n","random.streams.discreteUniform.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.discreteUniform.objectMode( 2, 5, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.erlang":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.erlang( 2, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.erlang.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.erlang.factory( opts );\n","random.streams.erlang.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.erlang.objectMode( 2, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.exponential":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.exponential( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.exponential.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.exponential.factory( opts );\n","random.streams.exponential.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.exponential.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.f":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.f( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.f.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.f.factory( opts );\n","random.streams.f.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.f.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.frechet":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.frechet( 2.0, 5.0, 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.frechet.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.frechet.factory( opts );\n","random.streams.frechet.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.frechet.objectMode( 2.0, 5.0, 3.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.gamma":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gamma( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.gamma.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.gamma.factory( opts );\n","random.streams.gamma.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gamma.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.geometric":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.geometric( 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.geometric.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.geometric.factory( opts );\n","random.streams.geometric.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.geometric.objectMode( 0.3, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.gumbel":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gumbel( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.gumbel.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.gumbel.factory( opts );\n","random.streams.gumbel.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gumbel.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.hypergeometric":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.hypergeometric( 5, 3, 2, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.hypergeometric.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.hypergeometric.factory( opts );\n","random.streams.hypergeometric.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.hypergeometric.objectMode( 5, 3, 2, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.improvedZiggurat":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.improvedZiggurat( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.improvedZiggurat.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.improvedZiggurat.factory( opts );\n","random.streams.improvedZiggurat.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.improvedZiggurat.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.invgamma":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.invgamma( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.invgamma.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.invgamma.factory( opts );\n","random.streams.invgamma.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.invgamma.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.kumaraswamy":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.kumaraswamy( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.kumaraswamy.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.kumaraswamy.factory( opts );\n","random.streams.kumaraswamy.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.kumaraswamy.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.laplace":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.laplace( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.laplace.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.laplace.factory( opts );\n","random.streams.laplace.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.laplace.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.levy":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.levy( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.levy.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.levy.factory( opts );\n","random.streams.levy.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.levy.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.logistic":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.logistic( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.logistic.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.logistic.factory( opts );\n","random.streams.logistic.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.logistic.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.lognormal":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.lognormal( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.lognormal.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.lognormal.factory( opts );\n","random.streams.lognormal.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.lognormal.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.minstd":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstd( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.minstd.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.minstd.factory( opts );\n","random.streams.minstd.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstd.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.minstdShuffle":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstdShuffle( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.minstdShuffle.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.minstdShuffle.factory( opts );\n","random.streams.minstdShuffle.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstdShuffle.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.mt19937":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.mt19937( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.mt19937.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.mt19937.factory( opts );\n","random.streams.mt19937.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.mt19937.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.negativeBinomial":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.negativeBinomial( 20.0, 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.negativeBinomial.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.negativeBinomial.factory( opts );\n","random.streams.negativeBinomial.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.negativeBinomial.objectMode( 20.0, 0.5, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.normal":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.normal( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.normal.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.normal.factory( opts );\n","random.streams.normal.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.normal.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.pareto1":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.pareto1( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.pareto1.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.pareto1.factory( opts );\n","random.streams.pareto1.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.pareto1.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.poisson":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.poisson( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.poisson.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.poisson.factory( opts );\n","random.streams.poisson.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.poisson.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.randi":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randi( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.randi.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.randi.factory( opts );\n","random.streams.randi.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randi.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.randn":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randn( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.randn.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.randn.factory( opts );\n","random.streams.randn.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randn.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.randu":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randu( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.randu.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.randu.factory( opts );\n","random.streams.randu.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randu.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.rayleigh":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.rayleigh( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.rayleigh.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.rayleigh.factory( opts );\n","random.streams.rayleigh.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.rayleigh.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.t":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.t( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.t.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.t.factory( opts );\n","random.streams.t.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.t.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.triangular":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.triangular( 2.0, 5.0, 4.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.triangular.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.triangular.factory( opts );\n","random.streams.triangular.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.triangular.objectMode( 2.0, 5.0, 4.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.uniform":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.uniform( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.uniform.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.uniform.factory( opts );\n","random.streams.uniform.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.uniform.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.weibull":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.weibull( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.weibull.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.weibull.factory( opts );\n","random.streams.weibull.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.weibull.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.strided.arcsine":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.arcsine( out.length, a, 1, b, 1, out, 1 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.arcsine( 3, a, -2, b, 1, out, 1 )\n","random.strided.arcsine.ndarray":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.arcsine.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.arcsine.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.bernoulli":"var out = azeros( 5, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n","random.strided.bernoulli.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.bernoulli.ndarray( out.length, [ 0.5 ], 0, 0, out, 1, 0 )\n","random.strided.bernoulli.factory":"var fcn = random.strided.bernoulli.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 0.5 ], 0, out, 1 )\n","random.strided.bernoulli.PRNG":"var prng = random.strided.bernoulli.PRNG;\n","random.strided.bernoulli.seed":"var seed = random.strided.bernoulli.seed;\n","random.strided.bernoulli.seedLength":"var len = random.strided.bernoulli.seedLength;\n","random.strided.bernoulli.state":"var out = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\nvar state = random.strided.bernoulli.state\nout = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\nrandom.strided.bernoulli.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n","random.strided.bernoulli.stateLength":"var len = random.strided.bernoulli.stateLength;\n","random.strided.bernoulli.byteLength":"var sz = random.strided.bernoulli.byteLength;\n","random.strided.beta":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.beta( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.beta( 3, a, -2, b, 1, out, 1 )\n","random.strided.beta.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.beta.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.beta.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.betaprime":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.betaprime( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.betaprime( 3, a, -2, b, 1, out, 1 )\n","random.strided.betaprime.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.betaprime.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.betaprime.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.chi":"var out = azeros( 5, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chi.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.chi.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.chi.factory":"var fcn = random.strided.chi.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chi.PRNG":"var prng = random.strided.chi.PRNG;\n","random.strided.chi.seed":"var seed = random.strided.chi.seed;\n","random.strided.chi.seedLength":"var len = random.strided.chi.seedLength;\n","random.strided.chi.state":"var out = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.chi.state\nout = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.chi.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chi.stateLength":"var len = random.strided.chi.stateLength;\n","random.strided.chi.byteLength":"var sz = random.strided.chi.byteLength;\n","random.strided.chisquare":"var out = azeros( 5, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chisquare.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.chisquare.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.chisquare.factory":"var fcn = random.strided.chisquare.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chisquare.PRNG":"var prng = random.strided.chisquare.PRNG;\n","random.strided.chisquare.seed":"var seed = random.strided.chisquare.seed;\n","random.strided.chisquare.seedLength":"var len = random.strided.chisquare.seedLength;\n","random.strided.chisquare.state":"var out = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.chisquare.state\nout = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.chisquare.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chisquare.stateLength":"var len = random.strided.chisquare.stateLength;\n","random.strided.chisquare.byteLength":"var sz = random.strided.chisquare.byteLength;\n","random.strided.cosine":"var mu = linspace( 0.0, 1.0, 5 );\nvar s = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.cosine( out.length, mu, 1, s, 1, out, 1 )\nmu = linspace( 0.0, 1.0, 6 );\ns = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.cosine( 3, mu, -2, s, 1, out, 1 )\n","random.strided.cosine.ndarray":"var mu = linspace( 0.0, 1.0, 5 );\nvar s = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.cosine.ndarray( out.length, mu, 1, 0, s, 1, 0, out, 1, 0 )\nmu = linspace( 0.0, 1.0, 6 );\ns = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.cosine.ndarray( 3, mu, 2, 1, s, -1, s.length-1, out, 1, 0 )\n","random.strided.discreteUniform":"var a = [ -10, -5, 0, 5, 10 ];\nvar b = [ 20, 20, 20, 20, 20 ];\nvar out = azeros( 5, 'generic' );\nrandom.strided.discreteUniform( out.length, a, 1, b, 1, out, 1 )\na = [ -10, -5, 0, 5, 10, 15 ];\nb = [ 20, 20, 20, 20, 20, 20 ];\nout = azeros( 6, 'generic' );\nrandom.strided.discreteUniform( 3, a, -2, b, 1, out, 1 )\n","random.strided.discreteUniform.ndarray":"var a = [ -10, -5, 0, 5, 10 ];\nvar b = [ 20, 20, 20, 20, 20 ];\nvar out = azeros( 5, 'generic' );\nrandom.strided.discreteUniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = [ -10, -5, 0, 5, 10, 15 ];\nb = [ 20, 20, 20, 20, 20, 20 ];\nout = azeros( 6, 'generic' );\nrandom.strided.discreteUniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.exponential":"var out = azeros( 5, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.exponential.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.exponential.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.exponential.factory":"var fcn = random.strided.exponential.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.exponential.PRNG":"var prng = random.strided.exponential.PRNG;\n","random.strided.exponential.seed":"var seed = random.strided.exponential.seed;\n","random.strided.exponential.seedLength":"var len = random.strided.exponential.seedLength;\n","random.strided.exponential.state":"var out = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.exponential.state\nout = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.exponential.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.exponential.stateLength":"var len = random.strided.exponential.stateLength;\n","random.strided.exponential.byteLength":"var sz = random.strided.exponential.byteLength;\n","random.strided.gamma":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.gamma( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.gamma( 3, a, -2, b, 1, out, 1 )\n","random.strided.gamma.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.gamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.gamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.geometric":"var out = azeros( 5, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n","random.strided.geometric.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.geometric.ndarray( out.length, [ 0.01 ], 0, 0, out, 1, 0 )\n","random.strided.geometric.factory":"var fcn = random.strided.geometric.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 0.01 ], 0, out, 1 )\n","random.strided.geometric.PRNG":"var prng = random.strided.geometric.PRNG;\n","random.strided.geometric.seed":"var seed = random.strided.geometric.seed;\n","random.strided.geometric.seedLength":"var len = random.strided.geometric.seedLength;\n","random.strided.geometric.state":"var out = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\nvar state = random.strided.geometric.state\nout = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\nrandom.strided.geometric.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n","random.strided.geometric.stateLength":"var len = random.strided.geometric.stateLength;\n","random.strided.geometric.byteLength":"var sz = random.strided.geometric.byteLength;\n","random.strided.invgamma":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.invgamma( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.invgamma( 3, a, -2, b, 1, out, 1 )\n","random.strided.invgamma.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.invgamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.invgamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.lognormal":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.lognormal( out.length, mu, 1, sigma, 1, out, 1 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.lognormal( 3, mu, -2, sigma, 1, out, 1 )\n","random.strided.lognormal.ndarray":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.lognormal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.lognormal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n","random.strided.minstd":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd( out.length, out, 1 )\n","random.strided.minstd.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd.ndarray( out.length, out, 1, 0 )\n","random.strided.minstd.normalized":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd.normalized( out.length, out, 1 )\n","random.strided.minstd.normalized.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd.normalized.ndarray( out.length, out, 1, 0 )\n","random.strided.minstdShuffle":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle( out.length, out, 1 )\n","random.strided.minstdShuffle.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle.ndarray( out.length, out, 1, 0 )\n","random.strided.minstdShuffle.normalized":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle.normalized( out.length, out, 1 )\n","random.strided.minstdShuffle.normalized.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle.normalized.ndarray( out.length, out, 1, 0 )\n","random.strided.mt19937":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937( out.length, out, 1 )\n","random.strided.mt19937.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937.ndarray( out.length, out, 1, 0 )\n","random.strided.mt19937.normalized":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937.normalized( out.length, out, 1 )\n","random.strided.mt19937.normalized.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937.normalized.ndarray( out.length, out, 1, 0 )\n","random.strided.normal":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.normal( out.length, mu, 1, sigma, 1, out, 1 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.normal( 3, mu, -2, sigma, 1, out, 1 )\n","random.strided.normal.ndarray":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.normal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.normal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n","random.strided.poisson":"var out = azeros( 5, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.poisson.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.poisson.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.poisson.factory":"var fcn = random.strided.poisson.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.poisson.PRNG":"var prng = random.strided.poisson.PRNG;\n","random.strided.poisson.seed":"var seed = random.strided.poisson.seed;\n","random.strided.poisson.seedLength":"var len = random.strided.poisson.seedLength;\n","random.strided.poisson.state":"var out = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.poisson.state\nout = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.poisson.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.poisson.stateLength":"var len = random.strided.poisson.stateLength;\n","random.strided.poisson.byteLength":"var sz = random.strided.poisson.byteLength;\n","random.strided.randu":"var out = azeros( 5, 'generic' );\nrandom.strided.randu( out.length, out, 1 )\n","random.strided.randu.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.randu.ndarray( out.length, out, 1, 0 )\n","random.strided.rayleigh":"var out = azeros( 5, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.rayleigh.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.rayleigh.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.rayleigh.factory":"var fcn = random.strided.rayleigh.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.rayleigh.PRNG":"var prng = random.strided.rayleigh.PRNG;\n","random.strided.rayleigh.seed":"var seed = random.strided.rayleigh.seed;\n","random.strided.rayleigh.seedLength":"var len = random.strided.rayleigh.seedLength;\n","random.strided.rayleigh.state":"var out = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.rayleigh.state\nout = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.rayleigh.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.rayleigh.stateLength":"var len = random.strided.rayleigh.stateLength;\n","random.strided.rayleigh.byteLength":"var sz = random.strided.rayleigh.byteLength;\n","random.strided.t":"var out = azeros( 5, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.t.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.t.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.t.factory":"var fcn = random.strided.t.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.t.PRNG":"var prng = random.strided.t.PRNG;\n","random.strided.t.seed":"var seed = random.strided.t.seed;\n","random.strided.t.seedLength":"var len = random.strided.t.seedLength;\n","random.strided.t.state":"var out = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.t.state\nout = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.t.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.t.stateLength":"var len = random.strided.t.stateLength;\n","random.strided.t.byteLength":"var sz = random.strided.t.byteLength;\n","random.strided.uniform":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.uniform( out.length, a, 1, b, 1, out, 1 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.uniform( 3, a, -2, b, 1, out, 1 )\n","random.strided.uniform.ndarray":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.uniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.uniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.weibull":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.weibull( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.weibull( 3, a, -2, b, 1, out, 1 )\n","random.strided.weibull.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.weibull.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.weibull.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","ranks":"var arr = [ 1.1, 2.0, 3.5, 0.0, 2.4 ] ;\nvar out = ranks( arr )\narr =  [ 2, 2, 1, 4, 3 ];\nout = ranks( arr )\narr = [ null, 2, 2, 1, 4, 3, NaN, NaN ];\nout = ranks( arr )\n","readDir":"function onRead( error, data ) {\n if ( error ) {\n     console.error( error.message );\n } else {\n     console.log( data );\n }\n };\nreadDir( './beep/boop', onRead );\n","readDir.sync":"var out = readDir.sync( './beep/boop' );\n","readFile":"function onRead( error, data ) {\n if ( error ) {\n     console.error( error.message );\n } else {\n     console.log( data );\n }\n };\nreadFile( './beep/boop.js', onRead );\n","readFile.sync":"var out = readFile.sync( './beep/boop.js' );\n","readFileList":"function onRead( error, data ) {\n if ( error ) {\n     console.error( error.message );\n } else {\n     console.log( data );\n }\n };\nvar filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\nreadFileList( filepaths, onRead );\n","readFileList.sync":"var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\nvar out = readFileList.sync( filepaths );\n","readJSON":"function onRead( error, data ) {\n if ( error ) {\n     console.error( error.message );\n } else {\n     console.log( data );\n }\n };\nreadJSON( './beep/boop.json', onRead );\n","readJSON.sync":"var out = readJSON.sync( './beep/boop.json' );\n","readWASM":"function onRead( error, data ) {\n if ( error ) {\n     console.error( error.message );\n } else {\n     console.log( data );\n }\n };\nreadWASM( './beep/boop.wasm', onRead );\n","readWASM.sync":"var out = readWASM.sync( './beep/boop.wasm' );\n","real":"var z = new Complex128( 5.0, 3.0 );\nvar re = real( z )\n","realarray":"var arr = realarray()\narr = realarray( 'float32' )\nvar arr = realarray( 5 )\narr = realarray( 5, 'int32' )\nvar arr1 = realarray( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = realarray( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = realarray( arr1, 'float32' )\nvar buf = new ArrayBuffer( 16 );\nvar arr = realarray( buf, 0, 4, 'float32' )\n","realarrayCtors":"var ctor = realarrayCtors( 'float64' )\nctor = realarrayCtors( 'float' )\n","realarrayDataTypes":"var out = realarrayDataTypes()\n","realf":"var z = new Complex64( 5.0, 3.0 );\nvar re = realf( z )\n","realmax":"var m = realmax( 'float16' )\nm = realmax( 'float32' )\n","realmin":"var m = realmin( 'float16' )\nm = realmin( 'float32' )\n","reBasename":"var RE = reBasename()\nvar RE_POSIX = reBasename( 'posix' );\nvar RE_WIN32 = reBasename( 'win32' );\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reBasename.REGEXP":"var RE = reBasename.REGEXP\n","reBasename.REGEXP_POSIX":"var base = reBasename.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n","reBasename.REGEXP_WIN32":"var base = reBasename.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reBasenamePosix":"var RE_BASENAME_POSIX = reBasenamePosix();\nvar base = RE_BASENAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( 'index.js' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( '.' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( './' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( '' )[ 1 ]\n","reBasenamePosix.REGEXP":"var base = reBasenamePosix.REGEXP.exec( 'foo/bar/index.js' )[ 1 ]\n","reBasenameWindows":"var RE_BASENAME_WINDOWS = reBasenameWindows();\nvar base = RE_BASENAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\index.js' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'foo\\\\file.pdf' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'foo\\\\bar\\\\file' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'index.js' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( '.' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( '' )[ 1 ]\n","reBasenameWindows.REGEXP":"var match = reBasenameWindows.REGEXP.exec( 'foo\\\\file.pdf' )[ 1 ]\n","reColorHexadecimal":"var RE = reColorHexadecimal();\nvar bool = RE.test( 'ffffff' )\nbool = RE.test( '000' )\nbool = RE.test( 'beep' )\n","reColorHexadecimal.REGEXP":"var bool = reColorHexadecimal.REGEXP.test( 'ffffff' )\nbool = reColorHexadecimal.REGEXP.test( '000' )\nbool = reColorHexadecimal.REGEXP.test( 'beep' )\n","reColorHexadecimal.REGEXP_SHORTHAND":"var bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'ffffff' )\nbool = reColorHexadecimal.REGEXP_SHORTHAND.test( '000' )\nbool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'beep' )\n","reColorHexadecimal.REGEXP_EITHER":"var bool = reColorHexadecimal.REGEXP_EITHER.test( 'ffffff' )\nbool = reColorHexadecimal.REGEXP_EITHER.test( '000' )\nbool = reColorHexadecimal.REGEXP_EITHER.test( 'beep' )\n","reDecimalNumber":"var RE = reDecimalNumber();\nvar bool = RE.test( '1.234' )\nbool = RE.test( '-1.234' )\nbool = RE.test( '0.0' )\nbool = RE.test( '.0' )\nbool = RE.test( '0' )\nbool = RE.test( 'beep' )\nvar re = reDecimalNumber({ 'flags': 'g' });\nvar str = '1.234 5.6, 7.8';\nvar out = str.match( re )\n","reDecimalNumber.REGEXP":"var RE = reDecimalNumber.REGEXP;\nvar bool = RE.test( '1.234' )\nbool = RE.test( '-1.234' )\n","reDecimalNumber.REGEXP_CAPTURE":"var RE = reDecimalNumber.REGEXP_CAPTURE;\nvar str = '1.02';\nvar out = replace( str, RE, '$1 x $1' )\n","reDirname":"var RE = reDirname()\nvar RE_POSIX = reDirname( 'posix' );\nvar dir = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\nvar RE_WIN32 = reDirname( 'win32' );\ndir = RE_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reDirname.REGEXP":"var RE = reDirname.REGEXP\n","reDirname.REGEXP_POSIX":"var dir = reDirname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n","reDirname.REGEXP_WIN32":"var dir = reDirname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reDirnamePosix":"var RE = reDirnamePosix();\nvar dir = RE.exec( '/foo/bar/index.js' )[ 1 ]\ndir = RE.exec( './foo/bar/.gitignore' )[ 1 ]\ndir = RE.exec( 'foo/file.pdf' )[ 1 ]\ndir = RE.exec( '/foo/bar/file' )[ 1 ]\ndir = RE.exec( 'index.js' )[ 1 ]\ndir = RE.exec( '.' )[ 1 ]\ndir = RE.exec( './' )[ 1 ]\ndir = RE.exec( '' )[ 1 ]\n","reDirnamePosix.REGEXP":"var ext = reDirnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n","reDirnameWindows":"var RE = reDirnameWindows();\nvar dir = RE.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\ndir = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\ndir = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\ndir = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\ndir = RE.exec( 'index.js' )[ 1 ]\ndir = RE.exec( '' )[ 1 ]\n","reDirnameWindows.REGEXP":"var dir = reDirnameWindows.REGEXP.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n","reduce":"var f = naryFunction( base.add, 2 );\nvar arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\nvar out = reduce( arr, 0.0, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = reduce( arr, 0.0, f )\n","reduce2d":"var f = naryFunction( base.add, 2 );\nvar arr = [ [ 1, 2, 3 ], [ 4, 5, 6 ] ];\nvar out = reduce2d( arr, [ 0, 0 ], f )\n","reduceAsync":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     acc.sum += value;\n     next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n     throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nreduceAsync( arr, acc, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     acc.sum += value;\n     next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n     throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nreduceAsync( arr, acc, opts, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     acc.sum += value;\n     next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n     throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'series': false };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nreduceAsync( arr, acc, opts, fcn, done )\n","reduceAsync.factory":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     acc.sum += value;\n     next( null, acc );\n }\n };\nvar opts = { 'series': false };\nvar f = reduceAsync.factory( opts, fcn );\nfunction done( error, acc ) {\n if ( error ) {\n     throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nf( arr, acc, done )\nacc = { 'sum': 0 };\narr = [ 2000, 1500, 1000 ];\nf( arr, acc, done )\n","reduceRight":"var f = naryFunction( base.add, 2 );\nvar arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\nvar out = reduceRight( arr, 0.0, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = reduceRight( arr, 0.0, f )\n","reduceRightAsync":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     acc.sum += value;\n     next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n     throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nreduceRightAsync( arr, acc, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     acc.sum += value;\n     next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n     throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nreduceRightAsync( arr, acc, opts, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     acc.sum += value;\n     next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n     throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'series': false };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nreduceRightAsync( arr, acc, opts, fcn, done )\n","reduceRightAsync.factory":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     acc.sum += value;\n     next( null, acc );\n }\n };\nvar opts = { 'series': false };\nvar f = reduceRightAsync.factory( opts, fcn );\nfunction done( error, acc ) {\n if ( error ) {\n     throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nf( arr, acc, done )\nacc = { 'sum': 0 };\narr = [ 1000, 1500, 2000 ];\nf( arr, acc, done )\n","reDurationString":"var RE = reDurationString();\nvar parts = RE.exec( '3d2ms' )\nparts = RE.exec( '4h3m20s' )\n","reDurationString.REGEXP":"var bool = reDurationString.REGEXP.test( '3d2ms' )\nbool = reDurationString.REGEXP.test( 'foo' )\n","reEOL":"var RE_EOL = reEOL();\nvar bool = RE_EOL.test( '\\n' )\nbool = RE_EOL.test( '\\r\\n' )\nbool = RE_EOL.test( '\\\\r\\\\n' )\n","reEOL.REGEXP":"var bool = reEOL.REGEXP.test( 'abc' )\n","reEOL.REGEXP_CAPTURE":"var parts = reEOL.REGEXP_CAPTURE.exec( '\\n' )\n","reExtendedLengthPath":"var RE = reExtendedLengthPath();\nvar path = '\\\\\\\\?\\\\C:\\\\foo\\\\bar';\nvar bool = RE.test( path )\npath = '\\\\\\\\?\\\\UNC\\\\server\\\\share';\nbool = RE.test( path )\npath = 'C:\\\\foo\\\\bar';\nbool = RE.test( path )\npath = '/c/foo/bar';\nbool = RE.test( path )\npath = '/foo/bar';\nbool = RE.test( path )\n","reExtendedLengthPath.REGEXP":"var bool = reExtendedLengthPath.REGEXP.test( 'C:\\\\foo\\\\bar' )\n","reExtname":"var RE = reExtname()\nvar RE_POSIX = reExtname( 'posix' );\nvar ext = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\nvar RE_WIN32 = reExtname( 'win32' );\next = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reExtname.REGEXP":"var RE = reExtname.REGEXP\n","reExtname.REGEXP_POSIX":"var ext = reExtname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n","reExtname.REGEXP_WIN32":"var ext = reExtname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reExtnamePosix":"var RE = reExtnamePosix();\nvar ext = RE.exec( '/foo/bar/index.js' )[ 1 ]\next = RE.exec( './foo/bar/.gitignore' )[ 1 ]\next = RE.exec( 'foo/file.pdf' )[ 1 ]\next = RE.exec( '/foo/bar/file' )[ 1 ]\next = RE.exec( 'index.js' )[ 1 ]\next = RE.exec( '.' )[ 1 ]\next = RE.exec( './' )[ 1 ]\next = RE.exec( '' )[ 1 ]\n","reExtnamePosix.REGEXP":"var ext = reExtnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n","reExtnameWindows":"var RE = reExtnameWindows();\nvar ext = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\next = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\next = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\next = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\next = RE.exec( 'beep\\\\boop.' )[ 1 ]\next = RE.exec( 'index.js' )[ 1 ]\next = RE.exec( '' )[ 1 ]\n","reExtnameWindows.REGEXP":"var ext = reExtnameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reFilename":"var RE = reFilename()\nvar RE_POSIX = reFilename( 'posix' );\nvar parts = RE_POSIX.exec( '/foo/bar/index.js' ).slice()\nvar RE_WIN32 = reFilename( 'win32' );\nparts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reFilename.REGEXP":"var RE = reFilename.REGEXP\n","reFilename.REGEXP_POSIX":"var f = '/foo/bar/index.js';\nvar parts = reFilename.REGEXP_POSIX.exec( f ).slice()\n","reFilename.REGEXP_WIN32":"var f = 'C:\\\\foo\\\\bar\\\\index.js';\nvar parts = reFilename.REGEXP_WIN32.exec( f ).slice()\n","reFilenamePosix":"var RE = reFilenamePosix();\nvar parts = RE.exec( '/foo/bar/index.js' ).slice()\nparts = RE.exec( './foo/bar/.gitignore' ).slice()\nparts = RE.exec( 'foo/file.pdf' ).slice()\nparts = RE.exec( '/foo/bar/file' ).slice()\nparts = RE.exec( 'index.js' ).slice()\nparts = RE.exec( '.' ).slice()\nparts = RE.exec( './' ).slice()\nparts = RE.exec( '' ).slice()\n","reFilenamePosix.REGEXP":"var parts = reFilenamePosix.REGEXP.exec( '/foo/bar/index.js' ).slice()\n","reFilenameWindows":"var RE = reFilenameWindows();\nvar parts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\nparts = RE.exec( '\\\\foo\\\\bar\\\\.gitignore' ).slice()\nparts = RE.exec( 'foo\\\\file.pdf' ).slice()\nparts = RE.exec( '\\\\foo\\\\bar\\\\file' ).slice()\nparts = RE.exec( 'index.js' ).slice()\nparts = RE.exec( '.' ).slice()\nparts = RE.exec( './' ).slice()\nparts = RE.exec( '' ).slice()\n","reFilenameWindows.REGEXP":"var parts = reFilenameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n","reFromString":"var re = reFromString( '/beep/' )\nre = reFromString( '/beep' )\n","reFunctionName":"var RE_FUNCTION_NAME = reFunctionName();\nfunction beep() { return 'boop'; };\nvar name = RE_FUNCTION_NAME.exec( beep.toString() )[ 1 ]\nname = RE_FUNCTION_NAME.exec( function () {} )[ 1 ]\n","reFunctionName.REGEXP":"var str = reFunctionName.REGEXP.exec( Math.sqrt.toString() )[ 1 ]\n","regexp2json":"var json = regexp2json( /ab+c/ )\n","reim":"var z = new Complex128( 5.0, 3.0 );\nvar out = reim( z )\n","reimf":"var z = new Complex64( 5.0, 3.0 );\nvar out = reimf( z )\n","rejectArguments":"function foo( a, b ) { return [ a, b ]; };\nfunction predicate( v ) { return ( v === 2 ); };\nvar bar = rejectArguments( foo, predicate );\nvar out = bar( 1, 2, 3 )\n","removeFirst":"var out = removeFirst( 'beep' )\nout = removeFirst( 'Boop' )\nout = removeFirst( 'foo bar', 4 )\n","removeLast":"var out = removeLast( 'beep' )\nout = removeLast( 'Boop' )\nout = removeLast( 'foo bar', 4 )\n","removePunctuation":"var str = 'Sun Tzu said: \"A leader leads by example not by force.\"';\nvar out = removePunctuation( str )\nstr = 'This function removes these characters: `{}[]:,!/<>().;~|?\\'\"';\nout = removePunctuation( str )\n","removeUTF8BOM":"var out = removeUTF8BOM( '\\ufeffbeep' )\n","removeWords":"var out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ] )\nout = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ], true )\n","rename":"function done( error ) {\n if ( error ) {\n     console.error( error.message );\n }\n };\nrename( './beep/boop.txt', './beep/foo.txt', done );\n","rename.sync":"var err = rename.sync( './beep/boop.txt', './beep/foo.txt' );\n","reNativeFunction":"var RE = reNativeFunction();\nvar bool = RE.test( Date.toString() )\nbool = RE.test( (function noop() {}).toString() )\n","reNativeFunction.REGEXP":"var bool = reNativeFunction.REGEXP.test( Date.toString() )\nbool = reNativeFunction.REGEXP.test( (function noop() {}).toString() )\n","reorderArguments":"function foo( a, b, c ) { return [ a, b, c ]; };\nvar bar = reorderArguments( foo, [ 2, 0, 1 ] );\nvar out = bar( 1, 2, 3 )\n","repeat":"var out = repeat( 'a', 5 )\nout = repeat( '', 100 )\nout = repeat( 'beep', 0 )\n","replace":"var out = replace( 'beep', 'e', 'o' )\nfunction replacer( match, p1 ) { return '/'+p1+'/'; };\nvar str = 'Oranges and lemons';\nout = replace( str, /([^\\s]+)/gi, replacer )\nout = replace( 'beep', /e/, 'o' )\n","replaceBefore":"var str = 'beep boop';\nvar out = replaceBefore( str, ' ', 'foo' )\nout = replaceBefore( str, 'o', 'foo' )\n","reRegExp":"var RE = reRegExp();\nvar bool = RE.test( '/^beep$/' )\nbool = RE.test( '/boop' )\nbool = RE.test( '/^\\/([^\\/]+)\\/(.*)$/' )\nbool = RE.test( '/^\\\\/([^\\\\/]+)\\\\/(.*)$/' )\n","reRegExp.REGEXP":"var bool = reRegExp.REGEXP.test( '/^beep$/' )\nbool = reRegExp.REGEXP.test( '/boop' )\n","rescape":"var str = rescape( '[A-Z]*' )\n","reSemVer":"var RE_SEMVER = reSemVer()\nvar bool = RE_SEMVER.test( '1.0.0' )\nbool = RE_SEMVER.test( '1.0.0-alpha.1' )\nbool = RE_SEMVER.test( 'abc' )\nbool = RE_SEMVER.test( '1.0.0-alpha.1+build.1' )\n","reSemVer.REGEXP":"var bool = reSemVer.REGEXP.test( '1.0.0' )\nbool = reSemVer.REGEXP.test( '-1.0.0-alpha.1' )\n","resolveParentPath":"function onPath( error, path ) {\n if ( error ) {\n     console.error( error.message );\n } else {\n     console.log( path );\n }\n };\nresolveParentPath( 'package.json', onPath );\n","resolveParentPath.sync":"var out = resolveParentPath.sync( 'package.json' );\n","resolveParentPathBy":"function predicate( path, next ) {\n setTimeout( onTimeout, path );\n function onTimeout() {\n     console.log( path );\n     next( null, false );\n }\n };\nfunction onPath( error, path ) {\n if ( error ) {\n     console.error( error.message );\n } else {\n     console.log( path );\n }\n };\nresolveParentPathBy( 'package.json', predicate, onPath );\n","resolveParentPathBy.sync":"function predicate() { return false; };\nvar out = resolveParentPathBy.sync( 'package.json', predicate );\n","reUncPath":"var RE = reUncPath();\nvar path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\nvar bool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\\\\\share';\nbool = RE.test( path )\npath = '\\\\\\\\\\\\\\\\server\\\\share';\nbool = RE.test( path )\npath = 'beep boop \\\\\\\\server\\\\share';\nbool = RE.test( path )\npath = '\\\\\\\\server';\nbool = RE.test( path )\npath = '\\\\';\nbool = RE.test( path )\npath = '';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b:c';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\';\nbool = RE.test( path )\npath = '//server/share';\nbool = RE.test( path )\npath = '/foo/bar';\nbool = RE.test( path )\npath = 'foo/bar';\nbool = RE.test( path )\npath = './foo/bar';\nbool = RE.test( path )\npath = '/foo/../bar';\nbool = RE.test( path )\n","reUncPath.REGEXP":"var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\nvar bool = reUncPath.REGEXP.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\nbool = reUncPath.REGEXP.test( path )\n","reUtf16SurrogatePair":"var RE = reUtf16SurrogatePair();\nvar bool = RE.test( 'abc\\uD800\\uDC00def' )\nbool = RE.test( 'abcdef' )\n","reUtf16SurrogatePair.REGEXP":"var RE = reUtf16SurrogatePair.REGEXP;\nvar bool = RE.test( 'abc\\uD800\\uDC00def' )\nbool = RE.test( 'abcdef' )\n","reUtf16UnpairedSurrogate":"var RE = reUtf16UnpairedSurrogate();\nvar bool = RE.test( 'abc' )\nbool = RE.test( '\\uD800' )\n","reUtf16UnpairedSurrogate.REGEXP":"var RE = reUtf16UnpairedSurrogate.REGEXP;\nvar bool = RE.test( 'abc' )\nbool = RE.test( '\\uD800' )\n","reverseArguments":"function foo( a, b, c ) { return [ a, b, c ]; };\nvar bar = reverseArguments( foo );\nvar out = bar( 1, 2, 3 )\n","reverseString":"var out = reverseString( 'foo' )\nout = reverseString( 'abcdef' )\n","reviveBasePRNG":"var str = JSON.stringify( base.random.mt19937 );\nvar r = parseJSON( str, reviveBasePRNG )\n","reviveBuffer":"var str = '{\"type\":\"Buffer\",\"data\":[5,3]}';\nvar buf = parseJSON( str, reviveBuffer )\n","reviveComplex":"var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\nvar z = parseJSON( str, reviveComplex )\n","reviveComplex64":"var str = '{\"type\":\"Complex64\",\"re\":5,\"im\":3}';\nvar z = parseJSON( str, reviveComplex64 )\n","reviveComplex128":"var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\nvar z = parseJSON( str, reviveComplex128 )\n","reviveError":"var str = '{\"type\":\"TypeError\",\"message\":\"beep\"}';\nvar err = JSON.parse( str, reviveError )\n","reviveRegExp":"var str = '{\"type\":\"RegExp\",\"pattern\":\"ab+c\",\"flags\":\"\"}';\nvar v = parseJSON( str, reviveRegExp )\n","reviveTypedArray":"var str = '{\"type\":\"Float64Array\",\"data\":[5,3]}';\nvar arr = parseJSON( str, reviveTypedArray )\n","reWhitespace":"var RE = reWhitespace();\nvar bool = RE.test( '\\n' )\nbool = RE.test( ' ' )\nbool = RE.test( 'a' )\n","reWhitespace.REGEXP":"var RE = reWhitespace.REGEXP;\nvar bool = RE.test( '\\n' )\nbool = RE.test( ' ' )\nbool = RE.test( 'a' )\n","reWhitespace.REGEXP_CAPTURE":"var RE = reWhitespace.REGEXP_CAPTURE;\nvar str = 'Duplicate capture';\nvar out = replace( str, RE, '$1$1' )\n","rpad":"var out = rpad( 'a', 5 )\nout = rpad( 'beep', 10, 'p' )\nout = rpad( 'beep', 12, 'boop' )\n","rtrim":"var out = rtrim( ' \\t\\t\\n  Beep \\r\\n\\t  ' )\n","rtrimN":"var out = rtrimN( '  abc  ', 2 )\nvar out = rtrimN( '!!!abc!!!', 2, '!' )\n","safeintmax":"var m = safeintmax( 'float16' )\nm = safeintmax( 'float32' )\n","safeintmin":"var m = safeintmin( 'float16' )\nm = safeintmin( 'float32' )\n","sample":"var out = sample( 'abc' )\nout = sample( [ 3, 6, 9 ] )\nvar bool = ( out.length === 3 )\nout = sample( [ 3, null, NaN, 'abc', function(){} ] )\nout = sample( [ 3, 6, 9 ], { 'size': 10 } )\nout = sample( [ 0, 1 ], { 'size': 20 } )\nout = sample( [ 1, 2, 3, 4, 5, 6 ], { 'replace': false, 'size': 3 } )\nout = sample( [ 0, 1 ], { 'replace': false } )\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar probs = [ 0.1, 0.1, 0.1, 0.1, 0.1, 0.5 ];\nout = sample( x, { 'probs': probs } )\nout = sample( x, { 'probs': probs, 'size': 3, 'replace': false } )\n","sample.factory":"var mysample = sample.factory({ 'seed': 232 } );\nvar out = mysample( 'abcdefg' )\nvar pool = [ 1, 2, 3, 4, 5, 6 ];\nmysample = sample.factory( pool, { 'seed': 232, 'size': 2 } );\nout = mysample()\nout = mysample()\nvar opts = { 'seed': 474, 'size': 3, 'mutate': true, 'replace': false };\npool = [ 1, 2, 3, 4, 5, 6 ];\nmysample = sample.factory( pool, opts );\nout = mysample()\nout = mysample()\nout = mysample()\nmysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\nout = mysample()\nout = mysample({ 'size': 10 })\nmysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\nout = mysample()\nout = mysample({ 'replace': false })\nout = mysample()\n","SAVOY_STOPWORDS_FIN":"var list = SAVOY_STOPWORDS_FIN()\n","SAVOY_STOPWORDS_FR":"var list = SAVOY_STOPWORDS_FR()\n","SAVOY_STOPWORDS_GER":"var list = SAVOY_STOPWORDS_GER()\n","SAVOY_STOPWORDS_IT":"var list = SAVOY_STOPWORDS_IT()\n","SAVOY_STOPWORDS_POR":"var list = SAVOY_STOPWORDS_POR()\n","SAVOY_STOPWORDS_SP":"var list = SAVOY_STOPWORDS_SP()\n","SAVOY_STOPWORDS_SWE":"var list = SAVOY_STOPWORDS_SWE()\n","scalar2array":"var x = scalar2array( 1.0 )\n","scalar2ndarray":"var x = scalar2ndarray( 1.0 )\nvar sh = x.shape\nvar dt = x.dtype\nvar v = x.get()\n","sdot":"var xbuf = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar x = array( xbuf );\nvar ybuf = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar y = array( ybuf );\nvar z = sdot( x, y )\nz.get()\n","SECONDS_IN_DAY":"var days = 3.14;\nvar secs = days * SECONDS_IN_DAY\n","SECONDS_IN_HOUR":"var hrs = 3.14;\nvar secs = hrs * SECONDS_IN_HOUR\n","SECONDS_IN_MINUTE":"var mins = 3.14;\nvar secs = mins * SECONDS_IN_MINUTE\n","SECONDS_IN_WEEK":"var wks = 3.14;\nvar secs = wks * SECONDS_IN_WEEK\n","secondsInMonth":"var num = secondsInMonth()\nnum = secondsInMonth( 2 )\nnum = secondsInMonth( 2, 2016 )\nnum = secondsInMonth( 2, 2017 )\nnum = secondsInMonth( 'feb', 2016 )\nnum = secondsInMonth( 'february', 2016 )\n","secondsInYear":"var num = secondsInYear()\nnum = secondsInYear( 2016 )\nnum = secondsInYear( 2017 )\n","sentencize":"var out = sentencize( 'Hello Mrs. Maple, could you call me back?' )\nout = sentencize( 'Hello World! How are you?' )\n","seq2slice":"var s = new seq2slice( '1:10', 10, false );\ns.start\ns.stop\ns.step\ns = new seq2slice( '2:5:2', 10, false );\ns.start\ns.stop\ns.step\n","setConfigurableReadOnly":"var obj = {};\nsetConfigurableReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n","setConfigurableReadOnlyAccessor":"var obj = {};\nfunction getter() { return 'bar'; };\nsetConfigurableReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n","setConfigurableReadWriteAccessor":"var obj = {};\nvar name = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetConfigurableReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n","setConfigurableWriteOnlyAccessor":"var obj = {};\nvar val = '';\nfunction setter( v ) { val = v; };\nsetConfigurableWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n","setMemoizedConfigurableReadOnly":"var obj = {};\nfunction foo() { return 'bar'; };\nsetMemoizedConfigurableReadOnly( obj, 'foo', foo );\nobj.foo\n","setMemoizedReadOnly":"var obj = {};\nfunction foo() { return 'bar'; };\nsetMemoizedReadOnly( obj, 'foo', foo );\nobj.foo\n","setNonEnumerableProperty":"var obj = {};\nsetNonEnumerableProperty( obj, 'foo', 'bar' );\nobj.foo\nobjectKeys( obj )\n","setNonEnumerableReadOnly":"var obj = {};\nsetNonEnumerableReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n","setNonEnumerableReadOnlyAccessor":"var obj = {};\nfunction getter() { return 'bar'; };\nsetNonEnumerableReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n","setNonEnumerableReadWriteAccessor":"var obj = {};\nvar name = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetNonEnumerableReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n","setNonEnumerableWriteOnlyAccessor":"var obj = {};\nvar val = '';\nfunction setter( v ) { val = v; };\nsetNonEnumerableWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n","setReadOnly":"var obj = {};\nsetReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n","setReadOnlyAccessor":"var obj = {};\nfunction getter() { return 'bar'; };\nsetReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n","setReadWriteAccessor":"var obj = {};\nvar name = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n","setWriteOnlyAccessor":"var obj = {};\nvar val = '';\nfunction setter( v ) { val = v; };\nsetWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n","SharedArrayBuffer":"var buf = new SharedArrayBuffer( 5 )\n","SharedArrayBuffer.length":"SharedArrayBuffer.length\n","SharedArrayBuffer.prototype.byteLength":"var buf = new SharedArrayBuffer( 5 );\nbuf.byteLength\n","SharedArrayBuffer.prototype.slice":"var b1 = new SharedArrayBuffer( 10 );\nvar b2 = b1.slice( 2, 6 );\nvar bool = ( b1 === b2 )\nb2.byteLength\n","shift":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar out = shift( arr )\narr = new Float64Array( [ 1.0, 2.0 ] );\nout = shift( arr )\narr = { 'length': 2, '0': 1.0, '1': 2.0 };\nout = shift( arr )\n","shuffle":"var data = [ 1, 2, 3 ];\nvar out = shuffle( data )\nout = shuffle( data, { 'copy': 'none' } );\nvar bool = ( data === out )\n","shuffle.factory":"var myshuffle = shuffle.factory();\nmyshuffle = shuffle.factory({ 'seed': 239 });\nvar arr = [ 0, 1, 2, 3, 4 ];\nvar out = myshuffle( arr )\nmyshuffle = shuffle.factory({ 'copy': 'none', 'seed': 867 });\narr = [ 1, 2, 3, 4, 5, 6 ];\nout = myshuffle( arr );\nvar bool = ( arr === out )\narr = [ 1, 2, 3, 4 ];\nout = myshuffle( arr, { 'copy': 'shallow' } );\nbool = ( arr === out )\n","sizeOf":"var s = sizeOf( 'int8' )\ns = sizeOf( 'uint32' )\n","Slice":"var s = new Slice();\ns = new Slice( 10 );\nvar s = new Slice( 2, 10 );\ns = new Slice( 2, 10, 1 );\n","Slice.prototype.start":"var s = new Slice( 10 );\ns.start\ns = new Slice( 2, 10 );\ns.start\n","Slice.prototype.stop":"var s = new Slice( 10 );\ns.stop\ns = new Slice( 2, 10 );\ns.stop\n","Slice.prototype.step":"var s = new Slice( 10 );\ns.step\ns = new Slice( 2, 10 );\ns.step\ns = new Slice( 2, 10, 1 );\ns.step\n","Slice.prototype.toString":"var s = new Slice( 10 );\ns.toString()\ns = new Slice( 2, 10, 1 );\ns.toString()\n","Slice.prototype.toJSON":"var s = new Slice( 10 );\ns.toJSON()\ns = new Slice( 2, 10, 1 );\ns.toJSON()\n","snakecase":"var out = snakecase( 'Hello World!' )\nout = snakecase( 'I am a tiny little teapot' )\n","some":"var arr = [ 0, 0, 1, 2, 3 ];\nvar bool = some( arr, 3 )\n","someBy":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ 1, 2, -3, 4, -1 ];\nvar bool = someBy( arr, 2, negative )\n","someByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nsomeByAsync( arr, 2, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nsomeByAsync( arr, 2, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nsomeByAsync( arr, 2, opts, predicate, done )\n","someByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = someByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, 2, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, 2, done )\n","someByRight":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ -1, 1, -2, 3, 4 ];\nvar bool = someByRight( arr, 2, negative )\n","someByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nsomeByRightAsync( arr, 2, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nsomeByRightAsync( arr, 2, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nsomeByRightAsync( arr, 2, opts, predicate, done )\n","someByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = someByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, 2, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, 2, done )\n","someInBy":"function negative( v ) { return ( v < 0 ); };\nvar obj = { 'a': 1, 'b': 2, 'c': -3, 'd': 4, 'e': -1 };\nvar bool = someInBy( obj, 2, negative )\n","someOwnBy":"function negative( v ) { return ( v < 0 ); };\nvar obj = { a: 1, b: 2, c: -3, d: 4, e: -1 };\nvar bool = someOwnBy( obj, 2, negative )\n","SOTU":"var out = SOTU()\nvar opts = { 'name': 'Barack Obama' };\nout = SOTU( opts )\nopts = { 'party': [ 'Democratic', 'Federalist' ] };\nout = SOTU( opts )\nopts = { 'year': [ 2008, 2009, 2011 ] };\nout = SOTU( opts )\nopts = { 'range': [ 2008, 2016 ] }\nout = SOTU( opts )\n","SPACHE_REVISED":"var list = SPACHE_REVISED()\n","SPAM_ASSASSIN":"var data = SPAM_ASSASSIN()\n","SparklineBase":"var sparkline = new SparklineBase()\nvar data = [ 1, 2, 3 ];\nsparkline = new SparklineBase( data )\n","sparsearray2iterator":"var it = sparsearray2iterator( [ 1, , 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","sparsearray2iteratorRight":"var it = sparsearray2iteratorRight( [ 1, 2, , 4 ] );\nvar v = it.next().value\nv = it.next().value\n","splitStream":"var s = splitStream();\ns.write( 'a\\nb\\nc' );\ns.end();\n","splitStream.factory":"var opts = { 'highWaterMark': 64 };\nvar createStream = splitStream.factory( opts );\nvar s = createStream();\ns.write( 'a\\nb\\nc' );\ns.end();\n","splitStream.objectMode":"var s = splitStream.objectMode();\ns.write( 'a\\nb\\c' );\ns.end();\n","SQRT_EPS":"SQRT_EPS\n","SQRT_HALF":"SQRT_HALF\n","SQRT_HALF_PI":"SQRT_HALF_PI\n","SQRT_PHI":"SQRT_PHI\n","SQRT_PI":"SQRT_PI\n","SQRT_THREE":"SQRT_THREE\n","SQRT_TWO":"SQRT_TWO\n","SQRT_TWO_PI":"SQRT_TWO_PI\n","SSA_US_BIRTHS_2000_2014":"var data = SSA_US_BIRTHS_2000_2014()\n","sswap":"var x = array( new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\nsswap( x, y );\nx.data\ny.data\n","Stack":"var s = Stack();\ns.push( 'foo' ).push( 'bar' );\ns.length\ns.pop()\ns.length\ns.pop()\ns.length\n","standalone2pkg":"var v = standalone2pkg( '@stdlib/math-base-special-sin' )\n","STANDARD_CARD_DECK":"var list = STANDARD_CARD_DECK()\n","startcase":"var out = startcase( 'beep boop' )\n","startsWith":"var bool = startsWith( 'Beep', 'Be' )\nbool = startsWith( 'Beep', 'ep' )\nbool = startsWith( 'Beep', 'ee', 1 )\nbool = startsWith( 'Beep', 'ee', -3 )\nbool = startsWith( 'Beep', '' )\n","STOPWORDS_EN":"var list = STOPWORDS_EN()\n","strided.abs":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs( 2, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.abs( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.abs.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.abs2":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.abs2( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.abs2.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.abs2By":"var x = [ -1.0, -2.0, -3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.abs2By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.abs2By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.abs2By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.abs2By.ndarray":"var x = [ -1.0, -2.0, -3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.abs2By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ -1.0, -2.0, -3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.abs2By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.absBy":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nstrided.absBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.absBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.absBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.absBy.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nstrided.absBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.absBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acosBy":"var x = [ 1.0, 0.707, 0.866, -0.707 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, 0.707, 0.866, -0.707 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acosBy.ndarray":"var x = [ 1.0, 0.707, 0.866, -0.707 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 1.0, 0.707, 0.866, -0.707 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acoshBy":"var x = [ 1.0, 1.5, 2.0, 2.5 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acoshBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acoshBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, 1.5, 2.0, 2.5 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acoshBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acoshBy.ndarray":"var x = [ 1.0, 1.5, 2.0, 2.5 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acoshBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 1.0, 1.5, 2.0, 2.5 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acoshBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acotBy":"var x = [ -2.5, -1.5, -0.5, 0.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acotBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acotBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ -2.5, -1.5, -0.5, 0.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acotBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acotBy.ndarray":"var x = [ -2.5, -1.5, -0.5, 0.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acotBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ -2.5, -1.5, -0.5, 0.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acotBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acothBy":"var x = [ -5.0, -4.0, -3.0, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acothBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acothBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ -5.0, -4.0, -3.0, -1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acothBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acothBy.ndarray":"var x = [ -5.0, -4.0, -3.0, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acothBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ -5.0, -4.0, -3.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acothBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acovercosBy":"var x = [ 0.0, -1.57, -0.5, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acovercosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acovercosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -1.57, -0.5, -1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acovercosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acovercosBy.ndarray":"var x = [ 0.0, -1.57, -0.5, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acovercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -1.57, -0.5, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acovercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acoversinBy":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acoversinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acoversinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acoversinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acoversinBy.ndarray":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acoversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.57, 0.5, 1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acoversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.add":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.add( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.add( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.add( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\nz0\n","strided.add.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.add.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.add.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n","strided.addBy":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = [ 11.0, 12.0, 13.0, 14.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.addBy( x.length, x, 1, y, 1, z, 1, clbk )\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.addBy( 2, x, 2, y, -1, z, 1, clbk )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.addBy( 2, x1, -2, y1, 1, z1, 1, clbk )\nz0\n","strided.addBy.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = [ 11.0, 12.0, 13.0, 14.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.addBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\nx = [ 1.0, 2.0, 3.0, 4.0 ];\ny = [ 11.0, 12.0, 13.0, 14.0 ];\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nvar oy = y.length - 1;\nvar oz = z.length - 1;\nstrided.addBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n","strided.ahavercosBy":"var x = [ 0.0, 0.5, 1.0, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.ahavercosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.ahavercosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 0.5, 1.0, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.ahavercosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.ahavercosBy.ndarray":"var x = [ 0.0, 0.5, 1.0, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.ahavercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 0.5, 1.0, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.ahavercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.ahaversinBy":"var x = [ 0.0, 0.5, 1.0, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.ahaversinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.ahaversinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 0.5, 1.0, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.ahaversinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.ahaversinBy.ndarray":"var x = [ 0.0, 0.5, 1.0, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.ahaversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 0.5, 1.0, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.ahaversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.asinBy":"var x = [ 0.0, -0.5, 1.0, -0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.asinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.asinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -0.5, 1.0, -0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.asinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.asinBy.ndarray":"var x = [ 0.0, -0.5, 1.0, -0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.asinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -0.5, 1.0, -0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.asinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.asinhBy":"var x = [ 0.0, -0.0, 2.0, -2.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.asinhBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.asinhBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -0.0, 2.0, -2.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.asinhBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.asinhBy.ndarray":"var x = [ 0.0, -0.0, 2.0, -2.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.asinhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -0.0, 2.0, -2.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.asinhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.atanBy":"var x = [ 0.0, -0.5, 1.0, -1.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.atanBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.atanBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -0.5, 1.0, -1.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.atanBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.atanBy.ndarray":"var x = [ 0.0, -0.5, 1.0, -1.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.atanBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -0.5, 1.0, -1.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.atanBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.atanhBy":"var x = [ 0.0, -0.5, 1.0, -0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.atanhBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.atanhBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -0.5, 1.0, -0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.atanhBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.atanhBy.ndarray":"var x = [ 0.0, -0.5, 1.0, -0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.atanhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -0.5, 1.0, -0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.atanhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.avercosBy":"var x = [ 0.0, -1.57, -0.5, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.avercosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.avercosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -1.57, -0.5, -1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.avercosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.avercosBy.ndarray":"var x = [ 0.0, -1.57, -0.5, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.avercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -1.57, -0.5, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.avercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.aversinBy":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.aversinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.aversinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.aversinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.aversinBy.ndarray":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.aversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.57, 0.5, 1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.aversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.besselj0By":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.besselj0By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.besselj0By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.besselj0By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.besselj0By.ndarray":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.besselj0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 0.1, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.besselj0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.besselj1By":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.besselj1By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.besselj1By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.besselj1By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.besselj1By.ndarray":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.besselj1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 0.1, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.besselj1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.bessely0By":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.bessely0By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.bessely0By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.bessely0By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.bessely0By.ndarray":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.bessely0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 0.1, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.bessely0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.bessely1By":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.bessely1By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.bessely1By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.bessely1By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.bessely1By.ndarray":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.bessely1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 0.1, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.bessely1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.binetBy":"var x = [ 0.0, 1.0, 2.0, 3.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.binetBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.binetBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.binetBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.binetBy.ndarray":"var x = [ 0.0, 1.0, 2.0, 3.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.binetBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 2.0, 3.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.binetBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.cbrt":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.cbrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.cbrt.ndarray":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.cbrtBy":"var x = [ 1.0, 9.0, -27.0, 81.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.cbrtBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.cbrtBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.cbrtBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.cbrtBy.ndarray":"var x = [ 1.0, 9.0, -27.0, 81.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.cbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 1.0, 9.0, -27.0, 81.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.cbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.ceil":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.ceil( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.ceil.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.cosBy":"var x = [ 0.0, 3.14, -3.14, 10.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.cosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.cosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 3.14, -3.14, 10.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.cosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.cosBy.ndarray":"var x = [ 0.0, 3.14, -3.14, 10.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.cosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 3.14, -3.14, 10.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.cosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.deg2rad":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.deg2rad( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.deg2rad.ndarray":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.dataTypes":"var out = strided.dataTypes()\n","strided.dcbrtBy":"var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nfunction clbk( v ) { return v; };\nstrided.dcbrtBy( x.length, x, 1, y, 1, clbk )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.dcbrtBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.dcbrtBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.dcbrtBy.ndarray":"var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nfunction clbk( v ) { return v; };\nstrided.dcbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.dcbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.dispatch":"var t = [ 'float64', 'float64', 'float32', 'float32' ];\nvar d = [ base.abs, base.absf ];\nvar f = strided.dispatch( base.strided.unary, t, d, 7, 1, 1 );\nvar x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( x.length, 'float64', x, 1, 'float64', y, 1 );\ny\nf = strided.dispatch( base.strided.unary.ndarray, t, d, 9, 1, 1 );\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( 2, 'float64', x, 1, 2, 'float64', y, 1, 2 );\ny\n","strided.dispatchBy":"var t = [ 'float64', 'float64', 'float32', 'float32' ];\nvar d = [ base.abs, base.absf ];\nvar f = strided.dispatchBy( base.strided.unaryBy, t, d, 8, 1, 1 );\nvar x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( x.length, 'float64', x, 1, 'float64', y, 1, base.identity );\ny\nf = strided.dispatchBy( base.strided.unary.ndarray, t, d, 10, 1, 1 );\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( 2, 'float64', x, 1, 2, 'float64', y, 1, 2, base.identity );\ny\n","strided.floor":"var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.floor( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.floor.ndarray":"var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.inv":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.inv( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.inv.ndarray":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.mul":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.mul( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.mul( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.mul( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\nz0\n","strided.mul.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.mul.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.mul.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n","strided.mulBy":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = [ 11.0, 12.0, 13.0, 14.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.mulBy( x.length, x, 1, y, 1, z, 1, clbk )\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.mulBy( 2, x, 2, y, -1, z, 1, clbk )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.mulBy( 2, x1, -2, y1, 1, z1, 1, clbk )\nz0\n","strided.mulBy.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = [ 11.0, 12.0, 13.0, 14.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.mulBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\nx = [ 1.0, 2.0, 3.0, 4.0 ];\ny = [ 11.0, 12.0, 13.0, 14.0 ];\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nvar oy = y.length - 1;\nvar oz = z.length - 1;\nstrided.mulBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n","strided.ramp":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.ramp( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.ramp.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.rsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.rsqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.rsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.sinBy":"var x = [ 0.0, 3.14, -3.14, 10.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.sinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.sinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 3.14, -3.14, 10.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.sinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.sinBy.ndarray":"var x = [ 0.0, 3.14, -3.14, 10.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.sinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 3.14, -3.14, 10.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.sinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.sqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.sqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.sqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.sqrtBy":"var x = [ 0.0, 1.0, 122.0, 50.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.sqrtBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.sqrtBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 122.0, 50.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.sqrtBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.sqrtBy.ndarray":"var x = [ 0.0, 1.0, 122.0, 50.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.sqrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 122.0, 50.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.sqrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.sub":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.sub( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sub( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.sub( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\nz0\n","strided.sub.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.sub.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sub.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n","strided.subBy":"var x = [ 11.0, 12.0, 13.0, 14.0 ];\nvar y = [ 8.0, 7.0, 6.0, 5.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.subBy( x.length, x, 1, y, 1, z, 1, clbk )\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.subBy( 2, x, 2, y, -1, z, 1, clbk )\nvar x0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\nvar y0 = new Float64Array( [ 8.0, 7.0, 6.0, 5.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.subBy( 2, x1, -2, y1, 1, z1, 1, clbk )\nz0\n","strided.subBy.ndarray":"var x = [ 11.0, 12.0, 13.0, 14.0 ];\nvar y = [ 8.0, 7.0, 6.0, 5.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.subBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\nx = [ 11.0, 12.0, 13.0, 14.0 ];\ny = [ 8.0, 7.0, 6.0, 5.0 ];\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nvar oy = y.length - 1;\nvar oz = z.length - 1;\nstrided.subBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n","strided.trunc":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.trunc( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.trunc.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","stridedarray2iterator":"var it = stridedarray2iterator( 2, [ 1, 2, 3, 4 ], -2, 3 );\nvar v = it.next().value\nv = it.next().value\n","stridedArrayStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar s = stridedArrayStream( 3, [ 1, 2, 3 ], 1, 0 );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","stridedArrayStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = stridedArrayStream.factory( opts );\n","stridedArrayStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar s = stridedArrayStream.objectMode( 3, [ 1, 2, 3 ], 1, 0 );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","string2buffer":"var b = string2buffer( 'beep boop' )\nb = string2buffer( '7468697320697320612074c3a97374', 'hex' );\nb.toString()\n","sub2ind":"var d = [ 3, 3, 3 ];\nvar idx = sub2ind( d, 1, 2, 2 )\n","substringAfter":"var out = substringAfter( 'Hello World!', 'World' )\nout = substringAfter( 'Hello World!', 'Hello ' )\nout = substringAfter( 'Hello World!', 'l', 5 )\n","substringAfterLast":"var out = substringAfterLast( 'beep boop beep baz', 'beep' )\nout = substringAfterLast( 'Hello World!', 'Hello ' )\nout = substringAfterLast( 'Hello World!', 'o', 5 )\n","substringBefore":"var str = 'beep boop';\nvar out = substringBefore( str, ' ' )\nout = substringBefore( str, 'o' )\n","substringBeforeLast":"var str = 'Beep Boop Beep';\nvar out = substringBeforeLast( str, 'Beep' )\nout = substringBeforeLast( str, 'Boop' )\n","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"var data = SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"var data = SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n","Symbol":"var s = ( Symbol ) ? Symbol( 'beep' ) : null\n","tabulate":"var collection = [ 'beep', 'boop', 'foo', 'beep' ];\nvar out = tabulate( collection )\n","tabulateBy":"function indicator( value ) { return value[ 0 ]; };\nvar collection = [ 'beep', 'boop', 'foo', 'beep' ];\nvar out = tabulateBy( collection, indicator )\n","tabulateByAsync":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000, 750 ];\ntabulateByAsync( arr, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000, 750 ];\ntabulateByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000, 750 ];\ntabulateByAsync( arr, opts, indicator, done )\n","tabulateByAsync.factory":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nvar opts = { 'series': true };\nvar f = tabulateByAsync.factory( opts, indicator );\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000, 750 ];\nf( arr, done )\narr = [ 2000, 1500, 1000, 750 ];\nf( arr, done )\n","thunk":"var fcn = thunk( base.add, 2, 3 );\nvar v = fcn()\nv = fcn()\n","tic":"var t = tic()\n","timeit":"var code = 'var x = Math.pow( Math.random(), 3 );';\ncode += 'if ( x !== x ) {';\ncode += 'throw new Error( \\'Something went wrong.\\' );';\ncode += '}';\nfunction done( error, results ) {\n if ( error ) {\n     throw error;\n }\n console.dir( results );\n };\ntimeit( code, done )\n","tmpdir":"var dir = tmpdir()\n","toc":"var start = tic();\nvar delta = toc( start )\n","tokenize":"var out = tokenize( 'Hello Mrs. Maple, could you call me back?' )\nout = tokenize( 'Hello World!', true )\n","transformStream":"var s = transformStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","transformStream.factory":"var opts = { 'highWaterMark': 64 };\nvar createStream = transformStream.factory( opts );\nfunction fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\nvar s = createStream( fcn );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","transformStream.objectMode":"var s = transformStream.objectMode();\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","transformStream.ctor":"function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\nvar opts = { 'highWaterMark': 64, 'transform': fcn };\nvar customStream = transformStream.ctor( opts );\nvar s = customStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","trim":"var out = trim( ' \\t\\t\\n  Beep \\r\\n\\t  ' )\n","truncate":"var str = 'beep boop';\nvar out = truncate( str, 5 )\nout = truncate( str, 5, '|' )\n","truncateMiddle":"var str = 'beep boop';\nvar out = truncateMiddle( str, 5 )\nout = truncateMiddle( str, 5, '|' )\n","trycatch":"function x() {\n if ( base.random.randu() < 0.5 ) {\n     throw new Error( 'beep' );\n }\n return 1.0;\n };\nvar z = trycatch( x, -1.0 )\n","trycatchAsync":"function x( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n     clbk( new Error( 'beep' ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     // process error...\n }\n console.log( result );\n };\ntrycatchAsync( x, 'boop', done )\n","tryFunction":"function fcn() { throw new Error( 'beep boop' ); };\nvar f = tryFunction( fcn );\nvar out = f();\nout.message\n","tryRequire":"var out = tryRequire( '_unknown_module_id_' )\n","trythen":"function x() {\n if ( base.random.randu() < 0.5 ) {\n     throw new Error( 'beep' );\n }\n return 1.0;\n };\nfunction y() {\n return -1.0;\n };\nvar z = trythen( x, y )\n","trythenAsync":"function x( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n     clbk( new Error( 'beep' ) );\n }\n };\nfunction y( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n     clbk( null, 'boop' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\ntrythenAsync( x, y, done )\n","ttest":"var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 5776 } );\nvar x = new Array( 100 );\nfor ( var i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm();\n }\nvar out = ttest( x )\nrnorm = base.random.normal.factory( 1.0, 2.0, { 'seed': 786 } );\nx = new Array( 100 );\nvar y = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm();\n y[ i ] = rnorm();\n }\nout = ttest( x, y )\nvar table = out.print()\nvar arr = [ 2, 4, 3, 1, 0 ];\nout = ttest( arr, { 'alpha': 0.01 } );\ntable = out.print()\narr = [ 4, 4, 6, 6, 5 ];\nout = ttest( arr, { 'mu': 5 } )\narr = [ 4, 4, 6, 6, 5 ];\nout = ttest( arr, { 'alternative': 'less' } );\ntable = out.print()\nout = ttest( arr, { 'alternative': 'greater' } );\ntable = out.print()\n","ttest2":"var x = [ 0.7, -1.6, -0.2, -1.2, -0.1, 3.4, 3.7, 0.8, 0.0, 2.0 ];\nvar y = [ 1.9, 0.8, 1.1, 0.1, -0.1, 4.4, 5.5, 1.6, 4.6, 3.4 ];\nvar out = ttest2( x, y )\nvar table = out.print()\nout = ttest2( x, y, { 'alpha': 0.1 } );\ntable = out.print()\nout = ttest2( x, y, { 'alternative': 'less' } );\ntable = out.print()\nout = ttest2( x, y, { 'alternative': 'greater' } );\ntable = out.print()\nx = [ 2, 3, 1, 4 ];\ny = [ 1, 2, 3, 1, 2, 5, 3, 4 ];\nout = ttest2( x, y, { 'variance': 'equal' } );\ntable = out.print()\nvar rnorm = base.random.normal.factory({ 'seed': 372 } );\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm( 2.0, 3.0 );\n }\ny = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n y[ i ] = rnorm( 1.0, 3.0 );\n }\nout = ttest2( x, y, { 'difference': 1.0, 'variance': 'equal' } )\n","TWO_PI":"TWO_PI\n","typedarray":"var arr = typedarray()\narr = typedarray( 'float32' )\nvar arr = typedarray( 5 )\narr = typedarray( 5, 'int32' )\nvar arr1 = typedarray( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = typedarray( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = typedarray( arr1, 'float32' )\nvar buf = new ArrayBuffer( 16 );\nvar arr = typedarray( buf, 0, 4, 'float32' )\n","typedarray2json":"var arr = new Float64Array( 2 );\narr[ 0 ] = 5.0;\narr[ 1 ] = 3.0;\nvar json = typedarray2json( arr )\n","typedarrayCtors":"var ctor = typedarrayCtors( 'float64' )\nctor = typedarrayCtors( 'float' )\n","typedarrayDataTypes":"var out = typedarrayDataTypes()\n","typedarraypool":"var arr = typedarraypool()\narr = typedarraypool( 'float32' )\nvar arr = typedarraypool( 5 )\narr = typedarraypool( 5, 'int32' )\nvar arr1 = typedarraypool( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = typedarraypool( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = typedarraypool( arr1, 'float32' )\n","typedarraypool.malloc":"var arr = typedarraypool.malloc()\narr = typedarraypool.malloc( 'float32' )\nvar arr = typedarraypool.malloc( 5 )\narr = typedarraypool.malloc( 5, 'int32' )\nvar arr1 = typedarraypool.malloc( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = typedarraypool.malloc( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = typedarraypool.malloc( arr1, 'float32' )\n","typedarraypool.calloc":"var arr = typedarraypool.calloc()\narr = typedarraypool.calloc( 'float32' )\nvar arr = typedarraypool.calloc( 5 )\narr = typedarraypool.calloc( 5, 'int32' )\n","typedarraypool.free":"var arr = typedarraypool( 5 )\ntypedarraypool.free( arr );\n","typedarraypool.clear":"var arr = typedarraypool( 5 )\ntypedarraypool.free( arr );\ntypedarraypool.clear();\n","typedarraypool.highWaterMark":"typedarraypool.highWaterMark\n","typedarraypool.nbytes":"var arr = typedarraypool( 5 )\ntypedarraypool.nbytes\n","typedarraypool.factory":"var pool = typedarraypool.factory();\nvar arr1 = pool( 3, 'float64' )\n","typemax":"var m = typemax( 'int8' )\nm = typemax( 'uint32' )\n","typemin":"var m = typemin( 'int8' )\nm = typemin( 'uint32' )\n","typeOf":"var t = typeOf( 'a' )\nt = typeOf( 5 )\nt = typeOf( NaN )\nt = typeOf( true )\nt = typeOf( false )\nt = typeOf( null )\nt = typeOf( undefined )\nt = typeOf( [] )\nt = typeOf( {} )\nt = typeOf( function noop() {} )\nt = typeOf( Symbol( 'beep' ) )\nt = typeOf( /.+/ )\nt = typeOf( new String( 'beep' ) )\nt = typeOf( new Number( 5 ) )\nt = typeOf( new Boolean( false ) )\nt = typeOf( new Array() )\nt = typeOf( new Object() )\nt = typeOf( new Int8Array( 10 ) )\nt = typeOf( new Uint8Array( 10 ) )\nt = typeOf( new Uint8ClampedArray( 10 ) )\nt = typeOf( new Int16Array( 10 ) )\nt = typeOf( new Uint16Array( 10 ) )\nt = typeOf( new Int32Array( 10 ) )\nt = typeOf( new Uint32Array( 10 ) )\nt = typeOf( new Float32Array( 10 ) )\nt = typeOf( new Float64Array( 10 ) )\nt = typeOf( new ArrayBuffer( 10 ) )\nt = typeOf( new Date() )\nt = typeOf( new RegExp( '.+' ) )\nt = typeOf( new Map() )\nt = typeOf( new Set() )\nt = typeOf( new WeakMap() )\nt = typeOf( new WeakSet() )\nt = typeOf( new Error( 'beep' ) )\nt = typeOf( new TypeError( 'beep' ) )\nt = typeOf( new SyntaxError( 'beep' ) )\nt = typeOf( new ReferenceError( 'beep' ) )\nt = typeOf( new URIError( 'beep' ) )\nt = typeOf( new RangeError( 'beep' ) )\nt = typeOf( new EvalError( 'beep' ) )\nt = typeOf( Math )\nt = typeOf( JSON )\nfunction beep() { return arguments; };\nt = typeOf( beep() )\nt = typeOf( new Buffer( 10 ) )\nfunction Person() { return this };\nt = typeOf( new Person() )\nvar Foo = function () { return this; };\nt = typeOf( new Foo() )\n","UINT8_MAX":"UINT8_MAX\n","UINT8_NUM_BYTES":"UINT8_NUM_BYTES\n","Uint8Array":"var arr = new Uint8Array()\nvar arr = new Uint8Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint8Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint8Array( arr1 )\nvar buf = new ArrayBuffer( 4 );\nvar arr = new Uint8Array( buf, 0, 4 )\n","Uint8Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint8Array.from( [ 1, 2 ], mapFcn )\n","Uint8Array.of":"var arr = Uint8Array.of( 1, 2 )\n","Uint8Array.BYTES_PER_ELEMENT":"Uint8Array.BYTES_PER_ELEMENT\n","Uint8Array.name":"Uint8Array.name\n","Uint8Array.prototype.buffer":"var arr = new Uint8Array( 5 );\narr.buffer\n","Uint8Array.prototype.byteLength":"var arr = new Uint8Array( 5 );\narr.byteLength\n","Uint8Array.prototype.byteOffset":"var arr = new Uint8Array( 5 );\narr.byteOffset\n","Uint8Array.prototype.BYTES_PER_ELEMENT":"var arr = new Uint8Array( 5 );\narr.BYTES_PER_ELEMENT\n","Uint8Array.prototype.length":"var arr = new Uint8Array( 5 );\narr.length\n","Uint8Array.prototype.copyWithin":"var arr = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint8Array.prototype.entries":"var arr = new Uint8Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint8Array.prototype.every":"var arr = new Uint8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint8Array.prototype.fill":"var arr = new Uint8Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint8Array.prototype.filter":"var arr1 = new Uint8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint8Array.prototype.find":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint8Array.prototype.findIndex":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint8Array.prototype.forEach":"var arr = new Uint8Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint8Array.prototype.includes":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint8Array.prototype.indexOf":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint8Array.prototype.join":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint8Array.prototype.keys":"var arr = new Uint8Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint8Array.prototype.lastIndexOf":"var arr = new Uint8Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint8Array.prototype.map":"var arr1 = new Uint8Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Uint8Array.prototype.reduce":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint8Array.prototype.reduceRight":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint8Array.prototype.reverse":"var arr = new Uint8Array( [ 1, 2, 3 ] )\narr.reverse()\n","Uint8Array.prototype.set":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint8Array.prototype.slice":"var arr1 = new Uint8Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint8Array.prototype.some":"var arr = new Uint8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint8Array.prototype.sort":"var arr = new Uint8Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint8Array.prototype.subarray":"var arr1 = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint8Array.prototype.toLocaleString":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint8Array.prototype.toString":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.toString()\n","Uint8Array.prototype.values":"var arr = new Uint8Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","Uint8ClampedArray":"var arr = new Uint8ClampedArray()\nvar arr = new Uint8ClampedArray( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint8ClampedArray( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint8ClampedArray( arr1 )\nvar buf = new ArrayBuffer( 4 );\nvar arr = new Uint8ClampedArray( buf, 0, 4 )\n","Uint8ClampedArray.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint8ClampedArray.from( [ 1, 2 ], mapFcn )\n","Uint8ClampedArray.of":"var arr = Uint8ClampedArray.of( 1, 2 )\n","Uint8ClampedArray.BYTES_PER_ELEMENT":"Uint8ClampedArray.BYTES_PER_ELEMENT\n","Uint8ClampedArray.name":"Uint8ClampedArray.name\n","Uint8ClampedArray.prototype.buffer":"var arr = new Uint8ClampedArray( 5 );\narr.buffer\n","Uint8ClampedArray.prototype.byteLength":"var arr = new Uint8ClampedArray( 5 );\narr.byteLength\n","Uint8ClampedArray.prototype.byteOffset":"var arr = new Uint8ClampedArray( 5 );\narr.byteOffset\n","Uint8ClampedArray.prototype.BYTES_PER_ELEMENT":"var arr = new Uint8ClampedArray( 5 );\narr.BYTES_PER_ELEMENT\n","Uint8ClampedArray.prototype.length":"var arr = new Uint8ClampedArray( 5 );\narr.length\n","Uint8ClampedArray.prototype.copyWithin":"var arr = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint8ClampedArray.prototype.entries":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint8ClampedArray.prototype.every":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint8ClampedArray.prototype.fill":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint8ClampedArray.prototype.filter":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint8ClampedArray.prototype.find":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint8ClampedArray.prototype.findIndex":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint8ClampedArray.prototype.forEach":"var arr = new Uint8ClampedArray( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint8ClampedArray.prototype.includes":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint8ClampedArray.prototype.indexOf":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint8ClampedArray.prototype.join":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint8ClampedArray.prototype.keys":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint8ClampedArray.prototype.lastIndexOf":"var arr = new Uint8ClampedArray( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint8ClampedArray.prototype.map":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Uint8ClampedArray.prototype.reduce":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint8ClampedArray.prototype.reduceRight":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint8ClampedArray.prototype.reverse":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] )\narr.reverse()\n","Uint8ClampedArray.prototype.set":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint8ClampedArray.prototype.slice":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint8ClampedArray.prototype.some":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint8ClampedArray.prototype.sort":"var arr = new Uint8ClampedArray( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint8ClampedArray.prototype.subarray":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint8ClampedArray.prototype.toLocaleString":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint8ClampedArray.prototype.toString":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.toString()\n","Uint8ClampedArray.prototype.values":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","UINT16_MAX":"UINT16_MAX\n","UINT16_NUM_BYTES":"UINT16_NUM_BYTES\n","Uint16Array":"var arr = new Uint16Array()\nvar arr = new Uint16Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint16Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint16Array( arr1 )\nvar buf = new ArrayBuffer( 8 );\nvar arr = new Uint16Array( buf, 0, 4 )\n","Uint16Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint16Array.from( [ 1, 2 ], mapFcn )\n","Uint16Array.of":"var arr = Uint16Array.of( 1, 2 )\n","Uint16Array.BYTES_PER_ELEMENT":"Uint16Array.BYTES_PER_ELEMENT\n","Uint16Array.name":"Uint16Array.name\n","Uint16Array.prototype.buffer":"var arr = new Uint16Array( 5 );\narr.buffer\n","Uint16Array.prototype.byteLength":"var arr = new Uint16Array( 5 );\narr.byteLength\n","Uint16Array.prototype.byteOffset":"var arr = new Uint16Array( 5 );\narr.byteOffset\n","Uint16Array.prototype.BYTES_PER_ELEMENT":"var arr = new Uint16Array( 5 );\narr.BYTES_PER_ELEMENT\n","Uint16Array.prototype.length":"var arr = new Uint16Array( 5 );\narr.length\n","Uint16Array.prototype.copyWithin":"var arr = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint16Array.prototype.entries":"var arr = new Uint16Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint16Array.prototype.every":"var arr = new Uint16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint16Array.prototype.fill":"var arr = new Uint16Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint16Array.prototype.filter":"var arr1 = new Uint16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint16Array.prototype.find":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint16Array.prototype.findIndex":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint16Array.prototype.forEach":"var arr = new Uint16Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint16Array.prototype.includes":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint16Array.prototype.indexOf":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint16Array.prototype.join":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint16Array.prototype.keys":"var arr = new Uint16Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint16Array.prototype.lastIndexOf":"var arr = new Uint16Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint16Array.prototype.map":"var arr1 = new Uint16Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Uint16Array.prototype.reduce":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint16Array.prototype.reduceRight":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint16Array.prototype.reverse":"var arr = new Uint16Array( [ 1, 2, 3 ] )\narr.reverse()\n","Uint16Array.prototype.set":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint16Array.prototype.slice":"var arr1 = new Uint16Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint16Array.prototype.some":"var arr = new Uint16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint16Array.prototype.sort":"var arr = new Uint16Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint16Array.prototype.subarray":"var arr1 = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint16Array.prototype.toLocaleString":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint16Array.prototype.toString":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.toString()\n","Uint16Array.prototype.values":"var arr = new Uint16Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","UINT32_MAX":"UINT32_MAX\n","UINT32_NUM_BYTES":"UINT32_NUM_BYTES\n","Uint32Array":"var arr = new Uint32Array()\nvar arr = new Uint32Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint32Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint32Array( arr1 )\nvar buf = new ArrayBuffer( 16 );\nvar arr = new Uint32Array( buf, 0, 4 )\n","Uint32Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint32Array.from( [ 1, 2 ], mapFcn )\n","Uint32Array.of":"var arr = Uint32Array.of( 1, 2 )\n","Uint32Array.BYTES_PER_ELEMENT":"Uint32Array.BYTES_PER_ELEMENT\n","Uint32Array.name":"Uint32Array.name\n","Uint32Array.prototype.buffer":"var arr = new Uint32Array( 5 );\narr.buffer\n","Uint32Array.prototype.byteLength":"var arr = new Uint32Array( 5 );\narr.byteLength\n","Uint32Array.prototype.byteOffset":"var arr = new Uint32Array( 5 );\narr.byteOffset\n","Uint32Array.prototype.BYTES_PER_ELEMENT":"var arr = new Uint32Array( 5 );\narr.BYTES_PER_ELEMENT\n","Uint32Array.prototype.length":"var arr = new Uint32Array( 5 );\narr.length\n","Uint32Array.prototype.copyWithin":"var arr = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint32Array.prototype.entries":"var arr = new Uint32Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint32Array.prototype.every":"var arr = new Uint32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint32Array.prototype.fill":"var arr = new Uint32Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint32Array.prototype.filter":"var arr1 = new Uint32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint32Array.prototype.find":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint32Array.prototype.findIndex":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint32Array.prototype.forEach":"var arr = new Uint32Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint32Array.prototype.includes":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint32Array.prototype.indexOf":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint32Array.prototype.join":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint32Array.prototype.keys":"var arr = new Uint32Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint32Array.prototype.lastIndexOf":"var arr = new Uint32Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint32Array.prototype.map":"var arr1 = new Uint32Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Uint32Array.prototype.reduce":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint32Array.prototype.reduceRight":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint32Array.prototype.reverse":"var arr = new Uint32Array( [ 1, 2, 3 ] )\narr.reverse()\n","Uint32Array.prototype.set":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint32Array.prototype.slice":"var arr1 = new Uint32Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint32Array.prototype.some":"var arr = new Uint32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint32Array.prototype.sort":"var arr = new Uint32Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint32Array.prototype.subarray":"var arr1 = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint32Array.prototype.toLocaleString":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint32Array.prototype.toString":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.toString()\n","Uint32Array.prototype.values":"var arr = new Uint32Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","umask":"var mask = umask()\nmask = umask( { 'symbolic': true } )\n","uncapitalize":"var out = uncapitalize( 'Beep' )\nout = uncapitalize( 'bOOp' )\n","uncapitalizeKeys":"var obj = { 'AA': 1, 'BB': 2 };\nvar out = uncapitalizeKeys( obj )\n","uncurry":"function addX( x ) {\n return function addY( y ) {\n     return x + y;\n };\n };\nvar fcn = uncurry( addX );\nvar sum = fcn( 2, 3 )\nfunction add( x ) {\n return function add( y ) {\n     return x + y;\n };\n };\nfcn = uncurry( add, 2 );\nsum = fcn( 9 )\nfunction addX( x ) {\n this.x = x;\n return addY;\n };\nfunction addY( y ) {\n return this.x + y;\n };\nfcn = uncurry( addX, {} );\nsum = fcn( 2, 3 )\n","uncurryRight":"function addX( x ) {\n return function addY( y ) {\n     return x + y;\n };\n };\nvar fcn = uncurryRight( addX );\nvar sum = fcn( 3, 2 )\nfunction add( y ) {\n return function add( x ) {\n     return x + y;\n };\n };\nfcn = uncurryRight( add, 2 );\nsum = fcn( 9 )\nfunction addY( y ) {\n this.y = y;\n return addX;\n };\nfunction addX( x ) {\n return x + this.y;\n };\nfcn = uncurryRight( addY, {} );\nsum = fcn( 3, 2 )\n","UNICODE_MAX":"UNICODE_MAX\n","UNICODE_MAX_BMP":"UNICODE_MAX_BMP\n","UnicodeColumnChartSparkline":"var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\nvar chart = new UnicodeColumnChartSparkline( data );\nchart.render()\n","UnicodeLineChartSparkline":"var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\nvar chart = new UnicodeLineChartSparkline( data );\nchart.render()\n","UnicodeSparkline":"var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\nvar chart = new UnicodeSparkline( data );\nchart.render()\nchart.type = 'line';\nchart.render()\n","UnicodeTristateChartSparkline":"var data = [ -1, 1, 0, 0, 1, -1, -1, 1 ];\nvar chart = new UnicodeTristateChartSparkline( data );\nchart.render()\n","UnicodeUpDownChartSparkline":"var data = [ -1, 1, 1, 1, 1, -1, -1, 1 ];\nvar chart = new UnicodeUpDownChartSparkline( data );\nchart.render()\n","UnicodeWinLossChartSparkline":"var data = [ -2, 1, 2, 2, 1, -1, -1, 1 ];\nvar chart = new UnicodeWinLossChartSparkline( data );\nchart.render()\n","unlink":"function done( error ) {\n if ( error ) {\n     console.error( error.message );\n }\n };\nunlink( './beep/boop.txt', done );\n","unlink.sync":"var out = unlink.sync( './beep/boop.txt' );\n","unshift":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = unshift( arr, 6.0, 7.0 )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = unshift( arr, 3.0, 4.0 )\narr = { 'length': 1, '0': 1.0 };\narr = unshift( arr, 2.0, 3.0 )\n","until":"function predicate( i ) { return ( i >= 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\nuntil( predicate, beep )\n","untilAsync":"function predicate( i, clbk ) { clbk( null, i >= 5 ); };\nfunction fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n     next( null, 'boop'+i );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nuntilAsync( predicate, fcn, done )\n","untilEach":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\nuntilEach( arr, predicate, logger )\n","untilEachRight":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\nuntilEachRight( arr, predicate, logger )\n","unzip":"var arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\nvar out = unzip( arr )\narr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\nout = unzip( arr, [ 0, 2 ] )\n","uppercase":"var out = uppercase( 'bEEp' )\n","uppercaseKeys":"var obj = { 'a': 1, 'b': 2 };\nvar out = uppercaseKeys( obj )\n","US_STATES_ABBR":"var list = US_STATES_ABBR()\n","US_STATES_CAPITALS":"var list = US_STATES_CAPITALS()\n","US_STATES_CAPITALS_NAMES":"var out = US_STATES_CAPITALS_NAMES()\n","US_STATES_NAMES":"var list = US_STATES_NAMES()\n","US_STATES_NAMES_CAPITALS":"var out = US_STATES_NAMES_CAPITALS()\n","utf16ToUTF8Array":"var str = '☃';\nvar out = utf16ToUTF8Array( str )\n","vartest":"var x = [ 610, 610, 550, 590, 565, 570 ];\nvar y = [ 560, 550, 580, 550, 560, 590, 550, 590 ];\nvar out = vartest( x, y )\nvar table = out.print()\n","waterfall":"function foo( next ) { next( null, 'beep' ); };\nfunction bar( str, next ) { console.log( str ); next(); };\nfunction done( error ) { if ( error ) { throw error; } };\nvar fcns = [ foo, bar ];\nwaterfall( fcns, done );\n","waterfall.factory":"function foo( next ) { next( null, 'beep' ); };\nfunction bar( str, next ) { console.log( str ); next(); };\nfunction done( error ) { if ( error ) { throw error; } };\nvar fcns = [ foo, bar ];\nvar waterfall = waterfall.factory( fcns, done );\nwaterfall();\nwaterfall();\nwaterfall();\n","WebAssemblyMemory":"var mem = new WebAssemblyMemory( { 'initial': 0 } )\n","WebAssemblyMemory.prototype.buffer":"var mem = new WebAssemblyMemory( { 'initial': 0 } );\nmem.buffer\n","WebAssemblyMemory.prototype.grow":"var mem = new WebAssemblyMemory( { 'initial': 0 } );\nmem.grow( 1 )\n","whileAsync":"function predicate( i, clbk ) { clbk( null, i < 5 ); };\nfunction fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n     next( null, 'boop'+i );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nwhileAsync( predicate, fcn, done )\n","whileEach":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\nwhileEach( arr, predicate, logger )\n","whileEachRight":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\nwhileEachRight( arr, predicate, logger )\n","whilst":"function predicate( i ) { return ( i < 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\nwhilst( predicate, beep )\n","wilcoxon":"var arr = [ 6, 8, 14, 16, 23, 24, 28, 29, 41, -48, 49, 56, 60, -67, 75 ];\nvar out = wilcoxon( x )\nrunif = base.random.discreteUniform.factory( 1, 5, { 'seed': 786 });\nvar x = new Array( 100 );\nvar y = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = runif();\n y[ i ] = runif();\n }\nout = wilcoxon( x, y )\nvar table = out.print()\nout = wilcoxon( arr, { 'alpha': 0.01 });\ntable = out.print()\nout = wilcoxon( arr, { 'mu': 10 })\nout = wilcoxon( arr, { 'alternative': 'less' });\ntable = out.print()\nout = wilcoxon( arr, { 'alternative': 'greater' });\ntable = out.print()\n","writableProperties":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar props = writableProperties( obj )\n","writablePropertiesIn":"var props = writablePropertiesIn( [] )\n","writablePropertyNames":"var obj = { 'a': 'b' };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = writablePropertyNames( obj )\n","writablePropertyNamesIn":"var obj = { 'a': 'b' };\nvar desc = {};\ndesc.configurable = true;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = writablePropertyNamesIn( obj )\n","writablePropertySymbols":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = writablePropertySymbols( obj )\n","writablePropertySymbolsIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = writablePropertySymbolsIn( obj )\n","writeFile":"function onWrite( error ) {\n if ( error ) {\n     console.error( error.message );\n }\n };\nwriteFile( './beep/boop.txt', 'beep boop', onWrite );\n","writeFile.sync":"var err = writeFile.sync( './beep/boop.txt', 'beep boop' );\n","zip":"var out = zip( [ 1, 2 ], [ 'a', 'b' ] )\nvar opts = { 'trunc': false };\nout = zip( [ 1, 2, 3 ], [ 'a', 'b' ], opts )\n","ztest":"var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 212 } );\nvar x = new Array( 100 );\nfor ( var i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm();\n }\nvar out = ztest( x, 2.0 )\narr = [ 2, 4, 3, 1, 0 ];\nout = ztest( arr, 2.0, { 'alpha': 0.01 } );\ntable = out.print()\nvar arr = [ 4, 4, 6, 6, 5 ];\nout = ztest( arr, 1.0, { 'mu': 5 } )\narr = [ 4, 4, 6, 6, 5 ];\nout = ztest( arr, 1.0, { 'alternative': 'less' } )\nout = ztest( arr, 1.0, { 'alternative': 'greater' } )\n","ztest2":"var x = [ -0.21, 0.14, 1.65, 2.11, -1.86, -0.29, 1.48, 0.81, 0.86, 1.04 ];\nvar y = [ -1.53, -2.93, 2.34, -1.15, 2.7, -0.12, 4.22, 1.66, 3.43, 4.66 ];\nvar out = ztest2( x, y, 2.0, 2.0 )\nvar table = out.print()\nout = ztest2( x, y, 2.0, 2.0, { 'alpha': 0.4 } );\ntable = out.print()\nout = ztest2( x, y, 2.0, 2.0, { 'alternative': 'less' } );\ntable = out.print()\nout = ztest2( x, y, 2.0, 2.0, { 'alternative': 'greater' } );\ntable = out.print()\nvar rnorm = base.random.normal.factory({ 'seed': 372 } );\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm( 2.0, 1.0 );\n }\ny = new Array( 100 );\n for ( i = 0; i < x.length; i++ ) {\n y[ i ] = rnorm( 0.0, 2.0 );\n }\nout = ztest2( x, y, 1.0, 2.0, { 'difference': 2.0 } )\n"}
diff --git a/lib/node_modules/@stdlib/repl/help/data/data.csv b/lib/node_modules/@stdlib/repl/help/data/data.csv
index 106f2252260e..de78fff5fc4f 100644
--- a/lib/node_modules/@stdlib/repl/help/data/data.csv
+++ b/lib/node_modules/@stdlib/repl/help/data/data.csv
@@ -1700,10 +1700,10 @@ base.strided.dcopy,"\nbase.strided.dcopy( N, x, strideX, y, strideY )\n    Copie
 base.strided.dcopy.ndarray,"\nbase.strided.dcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Copies values from `x` into `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.dcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dswap, base.strided.gcopy, base.strided.scopy"
 base.strided.dcumax,"\nbase.strided.dcumax( N, x, strideX, y, strideY )\n    Computes the cumulative maximum of double-precision floating-point strided\n    array elements.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumax( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.0, 1.0, 2.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcumax( 3, x, 2, y, 2 )\n    <Float64Array>[ -2.0, 0.0, 1.0, 0.0, 2.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dcumax( 3, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 2.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 2.0, 2.0 ]\n\n\nbase.strided.dcumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum of double-precision floating-point strided\n    array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 1.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumax, base.strided.dcumin, base.strided.scumax\n"
 base.strided.dcumax.ndarray,"\nbase.strided.dcumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum of double-precision floating-point strided\n    array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 1.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumax, base.strided.dcumin, base.strided.scumax"
-base.strided.dcumaxabs,"\nbase.strided.dcumaxabs( N, x, strideX, y, strideY )\n    Computes the cumulative maximum absolute value of double-precision floating-\n    point strided array elements.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumaxabs( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.0, 2.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dcumaxabs( N, x, 2, y, 2 )\n    <Float64Array>[ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dcumaxabs( N, x1, 2, y1, 1 )\n    <Float64Array>[ 2.0, 2.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\nbase.strided.dcumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum absolute value of double-precision floating-\n    point strided array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dcumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cumaxabs, base.strided.dcumax, base.strided.dcuminabs, base.strided.scumaxabs\n"
-base.strided.dcumaxabs.ndarray,"\nbase.strided.dcumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum absolute value of double-precision floating-\n    point strided array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dcumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cumaxabs, base.strided.dcumax, base.strided.dcuminabs, base.strided.scumaxabs"
-base.strided.dcumin,"\nbase.strided.dcumin( N, x, strideX, y, strideY )\n    Computes the cumulative minimum of double-precision floating-point strided\n    array elements.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumin( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.0, -2.0, -2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dcumin( N, x, 2, y, 2 )\n    <Float64Array>[ -2.0, 0.0, -2.0, 0.0, -2.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dcumin( N, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, -2.0, -2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\nbase.strided.dcumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum of double-precision floating-point strided\n    array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -2.0, -2.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dcumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumin, base.strided.dcumax, base.strided.scumin\n"
-base.strided.dcumin.ndarray,"\nbase.strided.dcumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum of double-precision floating-point strided\n    array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -2.0, -2.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dcumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumin, base.strided.dcumax, base.strided.scumin"
+base.strided.dcumaxabs,"\nbase.strided.dcumaxabs( N, x, strideX, y, strideY )\n    Computes the cumulative maximum absolute value of double-precision floating-\n    point strided array elements.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumaxabs( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.0, 2.0, 2.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcumaxabs( 3, x, 2, y, 2 )\n    <Float64Array>[ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dcumaxabs( 3, x1, 2, y1, 1 )\n    <Float64Array>[ 2.0, 2.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n\nbase.strided.dcumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum absolute value of double-precision floating-\n    point strided array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cumaxabs, base.strided.dcumax, base.strided.dcuminabs, base.strided.scumaxabs\n"
+base.strided.dcumaxabs.ndarray,"\nbase.strided.dcumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum absolute value of double-precision floating-\n    point strided array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cumaxabs, base.strided.dcumax, base.strided.dcuminabs, base.strided.scumaxabs"
+base.strided.dcumin,"\nbase.strided.dcumin( N, x, strideX, y, strideY )\n    Computes the cumulative minimum of double-precision floating-point strided\n    array elements.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumin( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.0, -2.0, -2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcumin( 3, x, 2, y, 2 )\n    <Float64Array>[ -2.0, 0.0, -2.0, 0.0, -2.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dcumin( 3, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, -2.0, -2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n\nbase.strided.dcumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum of double-precision floating-point strided\n    array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -2.0, -2.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumin, base.strided.dcumax, base.strided.scumin\n"
+base.strided.dcumin.ndarray,"\nbase.strided.dcumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum of double-precision floating-point strided\n    array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -2.0, -2.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumin, base.strided.dcumax, base.strided.scumin"
 base.strided.dcuminabs,"\nbase.strided.dcuminabs( N, x, strideX, y, strideY )\n    Computes the cumulative minimum absolute value of double-precision floating-\n    point strided array elements.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcuminabs( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.0, 1.0, 1.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcuminabs( 3, x, 2, y, 2 )\n    <Float64Array>[ 2.0, 0.0, 1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dcuminabs( 3, x1, 2, y1, 1 )\n    <Float64Array>[ 2.0, 2.0, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 1.0 ]\n\n\nbase.strided.dcuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum absolute value of double-precision floating-\n    point strided array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cuminabs, base.strided.dcumaxabs, base.strided.dcumin, base.strided.scuminabs\n"
 base.strided.dcuminabs.ndarray,"\nbase.strided.dcuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum absolute value of double-precision floating-\n    point strided array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cuminabs, base.strided.dcumaxabs, base.strided.dcumin, base.strided.scuminabs"
 base.strided.dcusum,"\nbase.strided.dcusum( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements.\n\n    The `N` and stride parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusum( x.length, 0.0, x, 1, y, 1 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusum( 3, 0.0, x, 2, y, 2 )\n    <Float64Array>[ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dcusum( 3, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumpw, base.strided.gcusum, base.strided.scusum\n"
@@ -1734,10 +1734,10 @@ base.strided.dmax,"\nbase.strided.dmax( N, x, strideX )\n    Computes the maximu
 base.strided.dmax.ndarray,"\nbase.strided.dmax.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a double-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmax.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dmax.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dnanmax, base.strided.max, base.strided.smax"
 base.strided.dmaxabs,"\nbase.strided.dmaxabs( N, x, strideX )\n    Computes the maximum absolute value of a double-precision floating-point\n    strided array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmaxabs( x.length, x, 1 )\n    2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dmaxabs( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dmaxabs( 3, x1, 2 )\n    2.0\n\n\nbase.strided.dmaxabs.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmaxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dmaxabs.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dminabs, base.strided.dnanmaxabs, base.strided.maxabs, base.strided.smaxabs\n"
 base.strided.dmaxabs.ndarray,"\nbase.strided.dmaxabs.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmaxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dmaxabs.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dminabs, base.strided.dnanmaxabs, base.strided.maxabs, base.strided.smaxabs"
-base.strided.dmaxabssorted,"\nbase.strided.dmaxabssorted( N, x, stride )\n    Computes the maximum absolute value of a sorted double-precision floating-\n    point strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n    > base.strided.dmaxabssorted( x.length, x, 1 )\n    3.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dmaxabssorted( N, x, stride )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmaxabssorted( N, x1, stride )\n    3.0\n\nbase.strided.dmaxabssorted.ndarray( N, x, stride, offset )\n    Computes the maximum absolute value of a sorted double-precision floating-\n    point strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n    > base.strided.dmaxabssorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmaxabssorted.ndarray( N, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmaxabs, base.strided.dmaxsorted, base.strided.smaxabssorted\n"
-base.strided.dmaxabssorted.ndarray,"\nbase.strided.dmaxabssorted.ndarray( N, x, stride, offset )\n    Computes the maximum absolute value of a sorted double-precision floating-\n    point strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n    > base.strided.dmaxabssorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmaxabssorted.ndarray( N, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmaxabs, base.strided.dmaxsorted, base.strided.smaxabssorted"
-base.strided.dmaxsorted,"\nbase.strided.dmaxsorted( N, x, stride )\n    Computes the maximum value of a sorted double-precision floating-point\n    strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dmaxsorted( x.length, x, 1 )\n    3.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dmaxsorted( N, x, stride )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmaxsorted( N, x1, stride )\n    3.0\n\nbase.strided.dmaxsorted.ndarray( N, x, stride, offset )\n    Computes the maximum value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dmaxsorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmaxsorted.ndarray( N, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dminsorted, base.strided.maxsorted, base.strided.smaxsorted\n"
-base.strided.dmaxsorted.ndarray,"\nbase.strided.dmaxsorted.ndarray( N, x, stride, offset )\n    Computes the maximum value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dmaxsorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmaxsorted.ndarray( N, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dminsorted, base.strided.maxsorted, base.strided.smaxsorted"
+base.strided.dmaxabssorted,"\nbase.strided.dmaxabssorted( N, x, strideX )\n    Computes the maximum absolute value of a sorted double-precision floating-\n    point strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n    > base.strided.dmaxabssorted( x.length, x, 1 )\n    3.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dmaxabssorted( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dmaxabssorted( 3, x1, 2 )\n    3.0\n\n\nbase.strided.dmaxabssorted.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a sorted double-precision floating-\n    point strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n    > base.strided.dmaxabssorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.dmaxabssorted.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmaxabs, base.strided.dmaxsorted, base.strided.smaxabssorted\n"
+base.strided.dmaxabssorted.ndarray,"\nbase.strided.dmaxabssorted.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a sorted double-precision floating-\n    point strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n    > base.strided.dmaxabssorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.dmaxabssorted.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmaxabs, base.strided.dmaxsorted, base.strided.smaxabssorted"
+base.strided.dmaxsorted,"\nbase.strided.dmaxsorted( N, x, strideX )\n    Computes the maximum value of a sorted double-precision floating-point\n    strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dmaxsorted( x.length, x, 1 )\n    3.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dmaxsorted( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dmaxsorted( 3, x1, 2 )\n    3.0\n\n\nbase.strided.dmaxsorted.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dmaxsorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.dmaxsorted.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dminsorted, base.strided.maxsorted, base.strided.smaxsorted\n"
+base.strided.dmaxsorted.ndarray,"\nbase.strided.dmaxsorted.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dmaxsorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.dmaxsorted.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dminsorted, base.strided.maxsorted, base.strided.smaxsorted"
 base.strided.dmean,"\nbase.strided.dmean( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmean( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dmean( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmean( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.mean, base.strided.smean\n"
 base.strided.dmean.ndarray,"\nbase.strided.dmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.mean, base.strided.smean"
 base.strided.dmeankbn,"\nbase.strided.dmeankbn( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeankbn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dmeankbn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmeankbn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dmeankbn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeankbn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeankbn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.meankbn, base.strided.smeankbn\n"
@@ -1764,16 +1764,16 @@ base.strided.dmeanvarpn,"\nbase.strided.dmeanvarpn( N, c, x, strideX, out, strid
 base.strided.dmeanvarpn.ndarray,"\nbase.strided.dmeanvarpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the mean and variance of a double-precision floating-point strided\n    array using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanvarpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanvarpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.dmeanstdevpn, base.strided.dmeanvar, base.strided.dvariancepn"
 base.strided.dmeanwd,"\nbase.strided.dmeanwd( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanwd( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dmeanwd( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmeanwd( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dnanmeanwd, base.strided.meanwd, base.strided.smeanwd\n"
 base.strided.dmeanwd.ndarray,"\nbase.strided.dmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dnanmeanwd, base.strided.meanwd, base.strided.smeanwd"
-base.strided.dmediansorted,"\nbase.strided.dmediansorted( N, x, stride )\n    Computes the median value of a sorted double-precision floating-point\n    strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dmediansorted( x.length, x, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmediansorted( N, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dmediansorted( N, x1, 2 )\n    2.0\n\nbase.strided.dmediansorted.ndarray( N, x, stride, offset )\n    Computes the median value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmediansorted.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.mediansorted, base.strided.smediansorted\n"
-base.strided.dmediansorted.ndarray,"\nbase.strided.dmediansorted.ndarray( N, x, stride, offset )\n    Computes the median value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmediansorted.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.mediansorted, base.strided.smediansorted"
+base.strided.dmediansorted,"\nbase.strided.dmediansorted( N, x, strideX )\n    Computes the median value of a sorted double-precision floating-point\n    strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dmediansorted( x.length, x, 1 )\n    2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dmediansorted( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dmediansorted( 3, x1, 2 )\n    2.0\n\n\nbase.strided.dmediansorted.ndarray( N, x, strideX, offsetX )\n    Computes the median value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.dmediansorted.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.mediansorted, base.strided.smediansorted\n"
+base.strided.dmediansorted.ndarray,"\nbase.strided.dmediansorted.ndarray( N, x, strideX, offsetX )\n    Computes the median value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.dmediansorted.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.mediansorted, base.strided.smediansorted"
 base.strided.dmidrange,"\nbase.strided.dmidrange( N, x, strideX )\n    Computes the mid-range of a double-precision floating-point strided array.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Mid-range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmidrange( x.length, x, 1 )\n    0.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dmidrange( 3, x, 2 )\n    0.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dmidrange( 3, x1, 2 )\n    0.0\n\n\nbase.strided.dmidrange.ndarray( N, x, strideX, offsetX )\n    Computes the mid-range of a double-precision floating-point strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Mid-range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmidrange.ndarray( x.length, x, 1, 0 )\n    0.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dmidrange.ndarray( 3, x, 2, 1 )\n    0.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dmean, base.strided.dmin, base.strided.drange, base.strided.smidrange\n"
 base.strided.dmidrange.ndarray,"\nbase.strided.dmidrange.ndarray( N, x, strideX, offsetX )\n    Computes the mid-range of a double-precision floating-point strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Mid-range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmidrange.ndarray( x.length, x, 1, 0 )\n    0.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dmidrange.ndarray( 3, x, 2, 1 )\n    0.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dmean, base.strided.dmin, base.strided.drange, base.strided.smidrange"
 base.strided.dmin,"\nbase.strided.dmin( N, x, strideX )\n    Computes the minimum value of a double-precision floating-point strided\n    array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmin( x.length, x, 1 )\n    -2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dmin( 3, x, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmin( N, x1, stride )\n    -2.0\n\n\nbase.strided.dmin.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a double-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dmin.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dnanmin, base.strided.min, base.strided.smin\n"
 base.strided.dmin.ndarray,"\nbase.strided.dmin.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a double-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dmin.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dnanmin, base.strided.min, base.strided.smin"
 base.strided.dminabs,"\nbase.strided.dminabs( N, x, strideX )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dminabs( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dminabs( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dminabs( 3, x1, 2 )\n    1.0\n\n\nbase.strided.dminabs.ndarray( N, x, strideX, offsetX )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dminabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dminabs.ndarray( 3, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dmaxabs, base.strided.dnanminabs, base.strided.minabs, base.strided.sminabs\n"
 base.strided.dminabs.ndarray,"\nbase.strided.dminabs.ndarray( N, x, strideX, offsetX )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dminabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dminabs.ndarray( 3, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dmaxabs, base.strided.dnanminabs, base.strided.minabs, base.strided.sminabs"
-base.strided.dminsorted,"\nbase.strided.dminsorted( N, x, stride )\n    Computes the minimum value of a sorted double-precision floating-point\n    strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dminsorted( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dminsorted( N, x, stride )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dminsorted( N, x1, stride )\n    -2.0\n\nbase.strided.dminsorted.ndarray( N, x, stride, offset )\n    Computes the minimum value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dminsorted.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dminsorted.ndarray( N, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dmaxsorted, base.strided.minsorted, base.strided.sminsorted\n"
-base.strided.dminsorted.ndarray,"\nbase.strided.dminsorted.ndarray( N, x, stride, offset )\n    Computes the minimum value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dminsorted.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dminsorted.ndarray( N, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dmaxsorted, base.strided.minsorted, base.strided.sminsorted"
+base.strided.dminsorted,"\nbase.strided.dminsorted( N, x, strideX )\n    Computes the minimum value of a sorted double-precision floating-point\n    strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dminsorted( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dminsorted( 3, x, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dminsorted( 3, x1, 2 )\n    -2.0\n\n\nbase.strided.dminsorted.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dminsorted.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.dminsorted.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dmaxsorted, base.strided.minsorted, base.strided.sminsorted\n"
+base.strided.dminsorted.ndarray,"\nbase.strided.dminsorted.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dminsorted.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.dminsorted.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dmaxsorted, base.strided.minsorted, base.strided.sminsorted"
 base.strided.dmskabs,"\nbase.strided.dmskabs( N, x, sx, m, sm, y, sy )\n    Computes the absolute value for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ 2.0, 1.0, 0.0, 5.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskabs( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ 5.0, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 5.0, 1.0 ]\n\n\nbase.strided.dmskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the absolute value for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 2.0, 1.0, 0.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 5.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dabs, base.strided.dmskabs2, base.strided.smskabs\n"
 base.strided.dmskabs.ndarray,"\nbase.strided.dmskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the absolute value for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 2.0, 1.0, 0.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 5.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dabs, base.strided.dmskabs2, base.strided.smskabs"
 base.strided.dmskabs2,"\nbase.strided.dmskabs2( N, x, sx, m, sm, y, sy )\n    Computes the squared absolute value for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point\n    strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs2( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ 4.0, 1.0, 0.0, 25.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs2( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, 4.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskabs2( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ 25.0, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 25.0, 1.0 ]\n\n\nbase.strided.dmskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the squared absolute value for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point\n    strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 4.0, 1.0, 0.0, 25.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 25.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dabs2, base.strided.dmskabs, base.strided.smskabs2\n"
@@ -1792,10 +1792,10 @@ base.strided.dmskmap,"\nbase.strided.dmskmap( N, x, sx, m, sm, y, sy, fcn )\n
 base.strided.dmskmap.ndarray,"\nbase.strided.dmskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n    Applies a unary function to a double-precision floating-point strided input\n    array according to a strided mask array and assigns results to a double-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n    <Float64Array>[ 0.0, 0.0, 4.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmap, base.strided.dmskmap2, base.strided.mskunary, base.strided.smskmap"
 base.strided.dmskmap2,"\nbase.strided.dmskmap2( N, x, sx, y, sy, m, sm, z, sz, fcn )\n    Applies a binary function to double-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a double-\n    precision floating-point strided output array.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    z: Float64Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float64Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.dmskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.add )\n    <Float64Array>[ 2.0, 4.0, 0.0, 8.0 ]\n\n    // Using `N` and stride parameters:\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.add )\n    <Float64Array>[ 0.0, 3.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.add )\n    <Float64Array>[ 0.0, 6.0 ]\n    > z0\n    <Float64Array>[ 0.0, 0.0, 0.0, 6.0 ]\n\n\nbase.strided.dmskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n    Applies a binary function to double-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a double-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    z: Float64Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float64Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.dmskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.add )\n    <Float64Array>[ 2.0, 4.0, 0.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.dmskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.add )\n    <Float64Array>[ 0.0, 0.0, 7.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmap2, base.strided.dmskmap, base.strided.smskmap2\n"
 base.strided.dmskmap2.ndarray,"\nbase.strided.dmskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n    Applies a binary function to double-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a double-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    z: Float64Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float64Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.dmskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.add )\n    <Float64Array>[ 2.0, 4.0, 0.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.dmskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.add )\n    <Float64Array>[ 0.0, 0.0, 7.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmap2, base.strided.dmskmap, base.strided.smskmap2"
-base.strided.dmskmax,"\nbase.strided.dmskmax( N, x, strideX, mask, strideMask )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.dmskmax( x.length, x, 1, mask, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmskmax( N, x, 2, mask, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dmskmax( N, x1, 2, mask1, 2 )\n    2.0\n\nbase.strided.dmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dmskmin, base.strided.dnanmax, base.strided.dnanmskmax, base.strided.mskmax, base.strided.smskmax\n"
-base.strided.dmskmax.ndarray,"\nbase.strided.dmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dmskmin, base.strided.dnanmax, base.strided.dnanmskmax, base.strided.mskmax, base.strided.smskmax"
-base.strided.dmskmin,"\nbase.strided.dmskmin( N, x, strideX, mask, strideMask )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.dmskmin( x.length, x, 1, mask, 1 )\n    -2.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmskmin( N, x, 2, mask, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dmskmin( N, x1, 2, mask1, 2 )\n    -2.0\n\nbase.strided.dmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dmskmax, base.strided.dnanmin, base.strided.dnanmskmin, base.strided.mskmin, base.strided.smskmin\n"
-base.strided.dmskmin.ndarray,"\nbase.strided.dmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dmskmax, base.strided.dnanmin, base.strided.dnanmskmin, base.strided.mskmin, base.strided.smskmin"
+base.strided.dmskmax,"\nbase.strided.dmskmax( N, x, strideX, mask, strideMask )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask.\n\n    The `N` and stride parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.dmskmax( x.length, x, 1, mask, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.dmskmax( 3, x, 2, mask, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dmskmax( 3, x1, 2, mask1, 2 )\n    2.0\n\n\nbase.strided.dmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.dmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dmskmin, base.strided.dnanmax, base.strided.dnanmskmax, base.strided.mskmax, base.strided.smskmax\n"
+base.strided.dmskmax.ndarray,"\nbase.strided.dmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.dmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dmskmin, base.strided.dnanmax, base.strided.dnanmskmax, base.strided.mskmax, base.strided.smskmax"
+base.strided.dmskmin,"\nbase.strided.dmskmin( N, x, strideX, mask, strideMask )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.dmskmin( x.length, x, 1, mask, 1 )\n    -2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.dmskmin( 3, x, 2, mask, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dmskmin( 3, x1, 2, mask1, 2 )\n    -2.0\n\n\nbase.strided.dmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.dmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dmskmax, base.strided.dnanmin, base.strided.dnanmskmin, base.strided.mskmin, base.strided.smskmin\n"
+base.strided.dmskmin.ndarray,"\nbase.strided.dmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.dmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dmskmax, base.strided.dnanmin, base.strided.dnanmskmin, base.strided.mskmin, base.strided.smskmin"
 base.strided.dmskramp,"\nbase.strided.dmskramp( N, x, sx, m, sm, y, sy )\n    Evaluates the ramp function for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskramp( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ 1.1, 2.5, 0.0, 4.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskramp( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, 1.1, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskramp( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ 4.0, 2.5 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.5 ]\n\n\nbase.strided.dmskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Evaluates the ramp function for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.1, 2.5, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.5 ]\n\n    See Also\n    --------\n    base.strided.dramp, base.strided.smskramp\n"
 base.strided.dmskramp.ndarray,"\nbase.strided.dmskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Evaluates the ramp function for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.1, 2.5, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.5 ]\n\n    See Also\n    --------\n    base.strided.dramp, base.strided.smskramp"
 base.strided.dmskrange,"\nbase.strided.dmskrange( N, x, strideX, mask, strideMask )\n    Computes the range of a double-precision floating-point strided array\n    according to a mask.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.dmskrange( x.length, x, 1, mask, 1 )\n    4.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.dmskrange( 3, x, 2, mask, 2 )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dmskrange( 3, x1, 2, mask1, 2 )\n    4.0\n\n\nbase.strided.dmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a double-precision floating-point strided array\n    according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.dmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.dmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dmskmax, base.strided.dmskmin, base.strided.dnanrange, base.strided.drange, base.strided.mskrange, base.strided.smskrange\n"
@@ -1968,12 +1968,12 @@ base.strided.dstdevwd,"\nbase.strided.dstdevwd( N, correction, x, stride )\n
 base.strided.dstdevwd.ndarray,"\nbase.strided.dstdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevwd, base.strided.dstdev, base.strided.dvariancewd, base.strided.sstdevwd, base.strided.stdevwd"
 base.strided.dstdevyc,"\nbase.strided.dstdevyc( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevyc( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dstdevyc( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dstdevyc( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dstdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevyc, base.strided.dstdev, base.strided.dvarianceyc, base.strided.sstdevyc, base.strided.stdevyc\n"
 base.strided.dstdevyc.ndarray,"\nbase.strided.dstdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevyc, base.strided.dstdev, base.strided.dvarianceyc, base.strided.sstdevyc, base.strided.stdevyc"
-base.strided.dsum,"\nbase.strided.dsum( N, x, stride )\n    Computes the sum of double-precision floating-point strided array elements.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsum( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dsum( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsum( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.dsum.ndarray( N, x, stride, offset )\n    Computes the sum of double-precision floating-point strided array elements\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsum.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.dmean, base.strided.dnansum, base.strided.ssum, base.strided.gsum\n"
-base.strided.dsum.ndarray,"\nbase.strided.dsum.ndarray( N, x, stride, offset )\n    Computes the sum of double-precision floating-point strided array elements\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsum.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.dmean, base.strided.dnansum, base.strided.ssum, base.strided.gsum"
+base.strided.dsum,"\nbase.strided.dsum( N, x, strideX )\n    Computes the sum of double-precision floating-point strided array elements.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsum( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dsum( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsum( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.dsum.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsum.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.dmean, base.strided.dnansum, base.strided.ssum, base.strided.gsum\n"
+base.strided.dsum.ndarray,"\nbase.strided.dsum.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsum.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.dmean, base.strided.dnansum, base.strided.ssum, base.strided.gsum"
 base.strided.dsumkbn,"\nbase.strided.dsumkbn( N, x, strideX )\n    Computes the sum of double-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumkbn( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dsumkbn( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsumkbn( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.dsumkbn.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsumkbn.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn, base.strided.ssumkbn\n"
 base.strided.dsumkbn.ndarray,"\nbase.strided.dsumkbn.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsumkbn.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn, base.strided.ssumkbn"
-base.strided.dsumkbn2,"\nbase.strided.dsumkbn2( N, x, stride )\n    Computes the sum of double-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumkbn2( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsumkbn2( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsumkbn2( N, x1, stride )\n    -1.0\n\nbase.strided.dsumkbn2.ndarray( N, x, stride, offset )\n    Computes the sum of double-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsumkbn2.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn2, base.strided.dsum, base.strided.dsumkbn, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn2, base.strided.ssumkbn2\n"
-base.strided.dsumkbn2.ndarray,"\nbase.strided.dsumkbn2.ndarray( N, x, stride, offset )\n    Computes the sum of double-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsumkbn2.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn2, base.strided.dsum, base.strided.dsumkbn, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn2, base.strided.ssumkbn2"
+base.strided.dsumkbn2,"\nbase.strided.dsumkbn2( N, x, strideX )\n    Computes the sum of double-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumkbn2( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dsumkbn2( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsumkbn2( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.dsumkbn2.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsumkbn2.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn2, base.strided.dsum, base.strided.dsumkbn, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn2, base.strided.ssumkbn2\n"
+base.strided.dsumkbn2.ndarray,"\nbase.strided.dsumkbn2.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsumkbn2.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn2, base.strided.dsum, base.strided.dsumkbn, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn2, base.strided.ssumkbn2"
 base.strided.dsumors,"\nbase.strided.dsumors( N, x, stride )\n    Computes the sum of double-precision floating-point strided array elements\n    using ordinary recursive summation.\n\n    The `N` and `stride` parameters determine which elements in \n    the strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumors( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dsumors( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsumors( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.dsumors.ndarray( N, x, stride, offset )\n    Computes the sum of double-precision floating-point strided array elements\n    using ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsumors.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumors, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumpw, base.strided.gsumors, base.strided.ssumors\n"
 base.strided.dsumors.ndarray,"\nbase.strided.dsumors.ndarray( N, x, stride, offset )\n    Computes the sum of double-precision floating-point strided array elements\n    using ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsumors.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumors, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumpw, base.strided.gsumors, base.strided.ssumors"
 base.strided.dsumpw,"\nbase.strided.dsumpw( N, x, stride )\n    Computes the sum of double-precision floating-point strided array elements\n    using pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumpw( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dsumpw( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsumpw( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.dsumpw.ndarray( N, x, stride, offset )\n    Computes the sum of double-precision floating-point strided array elements\n    using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsumpw.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumpw, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.gsumpw, base.strided.ssumpw\n"
@@ -2012,8 +2012,8 @@ base.strided.gapx,"\nbase.strided.gapx( N, alpha, x, stride )\n    Adds a consta
 base.strided.gapx.ndarray,"\nbase.strided.gapx.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each element in a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > var alpha = 5.0;\n    > base.strided.gapx.ndarray( x.length, alpha, x, 1, 0 )\n    [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > alpha = 5.0;\n    > var stride = 2;\n    > base.strided.gapx.ndarray( N, alpha, x, stride, 1 )\n    [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dapx, base.strided.sapx"
 base.strided.gapxsum,"\nbase.strided.gapxsum( N, alpha, x, stride )\n    Adds a constant to each strided array element and computes the sum.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsum( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gapxsum( N, 5.0, x, stride )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gapxsum( N, 5.0, x1, stride )\n    14.0\n\nbase.strided.gapxsum.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each strided array element and computes the sum using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gapxsum.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.gapxsumpw, base.strided.gsum, base.strided.sapxsum\n"
 base.strided.gapxsum.ndarray,"\nbase.strided.gapxsum.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each strided array element and computes the sum using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gapxsum.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.gapxsumpw, base.strided.gsum, base.strided.sapxsum"
-base.strided.gapxsumkbn,"\nbase.strided.gapxsumkbn( N, alpha, x, stride )\n    Adds a constant to each strided array element and computes the sum using an\n    improved Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumkbn( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gapxsumkbn( N, 5.0, x, stride )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gapxsumkbn( N, 5.0, x1, stride )\n    14.0\n\nbase.strided.gapxsumkbn.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each strided array element and computes the sum using an\n    improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gapxsumkbn.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumkbn, base.strided.gapxsum, base.strided.gsumkbn, base.strided.sapxsumkbn\n"
-base.strided.gapxsumkbn.ndarray,"\nbase.strided.gapxsumkbn.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each strided array element and computes the sum using an\n    improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gapxsumkbn.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumkbn, base.strided.gapxsum, base.strided.gsumkbn, base.strided.sapxsumkbn"
+base.strided.gapxsumkbn,"\nbase.strided.gapxsumkbn( N, alpha, x, strideX )\n    Adds a scalar constant to each strided array element and computes the sum\n    using an improved Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumkbn( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and stride parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > base.strided.gapxsumkbn( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.gapxsumkbn( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.gapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each strided array element and computes the sum\n    using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > base.strided.gapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumkbn, base.strided.gapxsum, base.strided.gsumkbn, base.strided.sapxsumkbn\n"
+base.strided.gapxsumkbn.ndarray,"\nbase.strided.gapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each strided array element and computes the sum\n    using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > base.strided.gapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumkbn, base.strided.gapxsum, base.strided.gsumkbn, base.strided.sapxsumkbn"
 base.strided.gapxsumkbn2,"\nbase.strided.gapxsumkbn2( N, alpha, x, stride )\n    Adds a constant to each strided array element and computes the sum using a\n    second-order iterative Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumkbn2( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gapxsumkbn2( N, 5.0, x, stride )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gapxsumkbn2( N, 5.0, x1, stride )\n    14.0\n\nbase.strided.gapxsumkbn2.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each strided array element and computes the sum using a\n    second-order iterative Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gapxsumkbn2.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumkbn2, base.strided.gapxsum, base.strided.gsumkbn2, base.strided.sapxsumkbn2\n"
 base.strided.gapxsumkbn2.ndarray,"\nbase.strided.gapxsumkbn2.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each strided array element and computes the sum using a\n    second-order iterative Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gapxsumkbn2.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumkbn2, base.strided.gapxsum, base.strided.gsumkbn2, base.strided.sapxsumkbn2"
 base.strided.gapxsumors,"\nbase.strided.gapxsumors( N, alpha, x, stride )\n    Adds a constant to each strided array element and computes the sum using\n    ordinary recursive summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumors( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gapxsumors( N, 5.0, x, stride )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gapxsumors( N, 5.0, x1, stride )\n    14.0\n\nbase.strided.gapxsumors.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each strided array element and computes the sum using\n    ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gapxsumors.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumors, base.strided.gapxsum, base.strided.gsumors, base.strided.sapxsumors\n"
@@ -2030,8 +2030,8 @@ base.strided.gcopy,"\nbase.strided.gcopy( N, x, strideX, y, strideY )\n    Copie
 base.strided.gcopy.ndarray,"\nbase.strided.gcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Copies values from `x` into `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: ArrayLikeObject\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n    > base.strided.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n    > base.strided.gcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dcopy, base.strided.scopy"
 base.strided.gcusum,"\nbase.strided.gcusum( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of strided array elements.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusum( x.length, 0.0, x, 1, y, 1 )\n    [ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusum( N, 0.0, x, 2, y, 2 )\n    [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gcusum( N, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.gcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusum.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusumpw, base.strided.scusum\n"
 base.strided.gcusum.ndarray,"\nbase.strided.gcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusum.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusumpw, base.strided.scusum"
-base.strided.gcusumkbn,"\nbase.strided.gcusumkbn( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of strided array elements using an improved\n    Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumkbn( x.length, 0.0, x, 1, y, 1 )\n    [ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumkbn( N, 0.0, x, 2, y, 2 )\n    [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gcusumkbn( N, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.gcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using an improved\n    Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumkbn.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumkbn, base.strided.gcusum, base.strided.gcusumkbn2, base.strided.scusumkbn\n"
-base.strided.gcusumkbn.ndarray,"\nbase.strided.gcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using an improved\n    Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumkbn.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumkbn, base.strided.gcusum, base.strided.gcusumkbn2, base.strided.scusumkbn"
+base.strided.gcusumkbn,"\nbase.strided.gcusumkbn( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of strided array elements using an improved\n    Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Stride length for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumkbn( x.length, 0.0, x, 1, y, 1 )\n    [ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and stride parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumkbn( 3, 0.0, x, 2, y, 2 )\n    [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.gcusumkbn( 3, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.gcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using an improved\n    Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Stride length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumkbn, base.strided.gcusum, base.strided.gcusumkbn2, base.strided.scusumkbn\n"
+base.strided.gcusumkbn.ndarray,"\nbase.strided.gcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using an improved\n    Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Stride length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumkbn, base.strided.gcusum, base.strided.gcusumkbn2, base.strided.scusumkbn"
 base.strided.gcusumkbn2,"\nbase.strided.gcusumkbn2( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of strided array elements using a second-order\n    iterative Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumkbn2( x.length, 0.0, x, 1, y, 1 )\n    [ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumkbn2( N, 0.0, x, 2, y, 2 )\n    [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gcusumkbn2( N, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.gcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using a second-order\n    iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumkbn2.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumkbn2, base.strided.gcusum, base.strided.gcusumkbn, base.strided.scusumkbn2\n"
 base.strided.gcusumkbn2.ndarray,"\nbase.strided.gcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using a second-order\n    iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumkbn2.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumkbn2, base.strided.gcusum, base.strided.gcusumkbn, base.strided.scusumkbn2"
 base.strided.gcusumors,"\nbase.strided.gcusumors( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of strided array elements using ordinary\n    recursive summation.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumors( x.length, 0.0, x, 1, y, 1 )\n    [ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumors( N, 0.0, x, 2, y, 2 )\n    [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gcusumors( N, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.gcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using ordinary\n    recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumors.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumors, base.strided.gcusum, base.strided.gcusumpw, base.strided.scusumors\n"
@@ -2289,10 +2289,10 @@ base.strided.smax,"\nbase.strided.smax( N, x, strideX )\n    Computes the maximu
 base.strided.smax.ndarray,"\nbase.strided.smax.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a single-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smax.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smax.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.max, base.strided.smin, base.strided.snanmax"
 base.strided.smaxabs,"\nbase.strided.smaxabs( N, x, strideX )\n    Computes the maximum absolute value of a single-precision floating-point\n    strided array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smaxabs( x.length, x, 1 )\n    2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.smaxabs( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.smaxabs( 3, x1, 2 )\n    2.0\n\n\nbase.strided.smaxabs.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smaxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.smaxabs.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmaxabs, base.strided.maxabs, base.strided.smax, base.strided.sminabs, base.strided.snanmaxabs\n"
 base.strided.smaxabs.ndarray,"\nbase.strided.smaxabs.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smaxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.smaxabs.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmaxabs, base.strided.maxabs, base.strided.smax, base.strided.sminabs, base.strided.snanmaxabs"
-base.strided.smaxabssorted,"\nbase.strided.smaxabssorted( N, x, stride )\n    Computes the maximum absolute value of a sorted single-precision floating-\n    point strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n    > base.strided.smaxabssorted( x.length, x, 1 )\n    3.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.smaxabssorted( N, x, stride )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.smaxabssorted( N, x1, stride )\n    3.0\n\nbase.strided.smaxabssorted.ndarray( N, x, stride, offset )\n    Computes the maximum absolute value of a sorted single-precision floating-\n    point strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n    > base.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smaxabssorted.ndarray( N, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmaxabssorted, base.strided.smaxabs, base.strided.smaxsorted\n"
-base.strided.smaxabssorted.ndarray,"\nbase.strided.smaxabssorted.ndarray( N, x, stride, offset )\n    Computes the maximum absolute value of a sorted single-precision floating-\n    point strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n    > base.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smaxabssorted.ndarray( N, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmaxabssorted, base.strided.smaxabs, base.strided.smaxsorted"
-base.strided.smaxsorted,"\nbase.strided.smaxsorted( N, x, stride )\n    Computes the maximum value of a sorted single-precision floating-point\n    strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.smaxsorted( x.length, x, 1 )\n    3.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.smaxsorted( N, x, stride )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.smaxsorted( N, x1, stride )\n    3.0\n\nbase.strided.smaxsorted.ndarray( N, x, stride, offset )\n    Computes the maximum value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smaxsorted.ndarray( N, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmaxsorted, base.strided.maxsorted, base.strided.smax, base.strided.sminsorted\n"
-base.strided.smaxsorted.ndarray,"\nbase.strided.smaxsorted.ndarray( N, x, stride, offset )\n    Computes the maximum value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smaxsorted.ndarray( N, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmaxsorted, base.strided.maxsorted, base.strided.smax, base.strided.sminsorted"
+base.strided.smaxabssorted,"\nbase.strided.smaxabssorted( N, x, strideX )\n    Computes the maximum absolute value of a sorted single-precision floating-\n    point strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n    > base.strided.smaxabssorted( x.length, x, 1 )\n    3.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.smaxabssorted( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.smaxabssorted( 3, x1, 2 )\n    3.0\n\n\nbase.strided.smaxabssorted.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a sorted single-precision floating-\n    point strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n    > base.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.smaxabssorted.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmaxabssorted, base.strided.smaxabs, base.strided.smaxsorted\n"
+base.strided.smaxabssorted.ndarray,"\nbase.strided.smaxabssorted.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a sorted single-precision floating-\n    point strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n    > base.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.smaxabssorted.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmaxabssorted, base.strided.smaxabs, base.strided.smaxsorted"
+base.strided.smaxsorted,"\nbase.strided.smaxsorted( N, x, strideX )\n    Computes the maximum value of a sorted single-precision floating-point\n    strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.smaxsorted( x.length, x, 1 )\n    3.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.smaxsorted( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.smaxsorted( 3, x1, 2 )\n    3.0\n\n\nbase.strided.smaxsorted.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.smaxsorted.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmaxsorted, base.strided.maxsorted, base.strided.smax, base.strided.sminsorted\n"
+base.strided.smaxsorted.ndarray,"\nbase.strided.smaxsorted.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.smaxsorted.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmaxsorted, base.strided.maxsorted, base.strided.smax, base.strided.sminsorted"
 base.strided.smean,"\nbase.strided.smean( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smean( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.smean( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.smean( N, x1, stride )\n    ~-0.3333\n\nbase.strided.smean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsmean, base.strided.snanmean\n"
 base.strided.smean.ndarray,"\nbase.strided.smean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsmean, base.strided.snanmean"
 base.strided.smeankbn,"\nbase.strided.smeankbn( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeankbn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.smeankbn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.smeankbn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.smeankbn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeankbn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeankbn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeankbn, base.strided.meankbn, base.strided.smean\n"
@@ -2339,14 +2339,14 @@ base.strided.smskmap,"\nbase.strided.smskmap( N, x, sx, m, sm, y, sy, fcn )\n
 base.strided.smskmap.ndarray,"\nbase.strided.smskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n    Applies a unary function to a single-precision floating-point strided input\n    array according to a strided mask array and assigns results to a single-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n    <Float32Array>[ 0.0, 0.0, 4.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmskmap, base.strided.mskunary, base.strided.smap, base.strided.smskmap2"
 base.strided.smskmap2,"\nbase.strided.smskmap2( N, x, sx, y, sy, m, sm, z, sz, fcn )\n    Applies a binary function to single-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a single-\n    precision floating-point strided output array.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    z: Float32Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float32Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.smskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.addf )\n    <Float32Array>[ 2.0, 4.0, 0.0, 8.0 ]\n\n    // Using `N` and stride parameters:\n    > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.addf )\n    <Float32Array>[ 0.0, 3.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.addf )\n    <Float32Array>[ 0.0, 6.0 ]\n    > z0\n    <Float32Array>[ 0.0, 0.0, 0.0, 6.0 ]\n\n\nbase.strided.smskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n    Applies a binary function to single-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a single-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    z: Float32Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float32Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.smskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.addf )\n    <Float32Array>[ 2.0, 4.0, 0.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.smskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.addf )\n    <Float32Array>[ 0.0, 0.0, 7.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmskmap2, base.strided.smap2, base.strided.smskmap\n"
 base.strided.smskmap2.ndarray,"\nbase.strided.smskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n    Applies a binary function to single-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a single-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    z: Float32Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float32Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.smskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.addf )\n    <Float32Array>[ 2.0, 4.0, 0.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.smskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.addf )\n    <Float32Array>[ 0.0, 0.0, 7.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmskmap2, base.strided.smap2, base.strided.smskmap"
-base.strided.smskmax,"\nbase.strided.smskmax( N, x, strideX, mask, strideMask )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.smskmax( x.length, x, 1, mask, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smskmax( N, x, 2, mask, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.smskmax( N, x1, 2, mask1, 2 )\n    2.0\n\nbase.strided.smskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmskmax, base.strided.mskmax, base.strided.smax, base.strided.smskmin, base.strided.snanmax, base.strided.snanmskmax\n"
-base.strided.smskmax.ndarray,"\nbase.strided.smskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmskmax, base.strided.mskmax, base.strided.smax, base.strided.smskmin, base.strided.snanmax, base.strided.snanmskmax"
-base.strided.smskmin,"\nbase.strided.smskmin( N, x, strideX, mask, strideMask )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.smskmin( x.length, x, 1, mask, 1 )\n    -2.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smskmin( N, x, 2, mask, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.smskmin( N, x1, 2, mask1, 2 )\n    -2.0\n\nbase.strided.smskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmskmin, base.strided.mskmin, base.strided.smin, base.strided.smskmax, base.strided.snanmin, base.strided.snanmskmin\n"
-base.strided.smskmin.ndarray,"\nbase.strided.smskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmskmin, base.strided.mskmin, base.strided.smin, base.strided.smskmax, base.strided.snanmin, base.strided.snanmskmin"
+base.strided.smskmax,"\nbase.strided.smskmax( N, x, strideX, mask, strideMask )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.smskmax( x.length, x, 1, mask, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.smskmax( 3, x, 2, mask, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > base.strided.smskmax( 3, x1, 2, mask1, 2 )\n    2.0\n\n\nbase.strided.smskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.smskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmskmax, base.strided.mskmax, base.strided.smax, base.strided.smskmin, base.strided.snanmax, base.strided.snanmskmax\n"
+base.strided.smskmax.ndarray,"\nbase.strided.smskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.smskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmskmax, base.strided.mskmax, base.strided.smax, base.strided.smskmin, base.strided.snanmax, base.strided.snanmskmax"
+base.strided.smskmin,"\nbase.strided.smskmin( N, x, strideX, mask, strideMask )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.smskmin( x.length, x, 1, mask, 1 )\n    -2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.smskmin( 3, x, 2, mask, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > base.strided.smskmin( 3, x1, 2, mask1, 2 )\n    -2.0\n\n\nbase.strided.smskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.smskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmskmin, base.strided.mskmin, base.strided.smin, base.strided.smskmax, base.strided.snanmin, base.strided.snanmskmin\n"
+base.strided.smskmin.ndarray,"\nbase.strided.smskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.smskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmskmin, base.strided.mskmin, base.strided.smin, base.strided.smskmax, base.strided.snanmin, base.strided.snanmskmin"
 base.strided.smskramp,"\nbase.strided.smskramp( N, x, sx, m, sm, y, sy )\n    Evaluates the ramp function for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskramp( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskramp( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskramp( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ 4.0, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Evaluates the ramp function for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmskramp, base.strided.sramp\n"
 base.strided.smskramp.ndarray,"\nbase.strided.smskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Evaluates the ramp function for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmskramp, base.strided.sramp"
-base.strided.smskrange,"\nbase.strided.smskrange( N, x, strideX, mask, strideMask )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.smskrange( x.length, x, 1, mask, 1 )\n    4.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smskrange( N, x, 2, mask, 2 )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.smskrange( N, x1, 2, mask1, 2 )\n    4.0\n\nbase.strided.smskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dmskrange, base.strided.mskrange, base.strided.smskmax, base.strided.smskmin, base.strided.snanrange, base.strided.srange\n"
-base.strided.smskrange.ndarray,"\nbase.strided.smskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dmskrange, base.strided.mskrange, base.strided.smskmax, base.strided.smskmin, base.strided.snanrange, base.strided.srange"
+base.strided.smskrange,"\nbase.strided.smskrange( N, x, strideX, mask, strideMask )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.smskrange( x.length, x, 1, mask, 1 )\n    4.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.smskrange( 3, x, 2, mask, 2 )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > base.strided.smskrange( 3, x1, 2, mask1, 2 )\n    4.0\n\n\nbase.strided.smskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.smskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dmskrange, base.strided.mskrange, base.strided.smskmax, base.strided.smskmin, base.strided.snanrange, base.strided.srange\n"
+base.strided.smskrange.ndarray,"\nbase.strided.smskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.smskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dmskrange, base.strided.mskrange, base.strided.smskmax, base.strided.smskmin, base.strided.snanrange, base.strided.srange"
 base.strided.smskrsqrt,"\nbase.strided.smskrsqrt( N, x, sx, m, sm, y, sy )\n    Computes the reciprocal square root for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskrsqrt( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ Infinity, 0.5, 0.0, ~0.289 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskrsqrt( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, Infinity, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ ~0.289, 0.5 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.smskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the reciprocal square root for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ Infinity, 0.5, 0.0, ~0.289 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n    See Also\n    --------\n    base.strided.dmskrsqrt, base.strided.smsksqrt, base.strided.srsqrt\n"
 base.strided.smskrsqrt.ndarray,"\nbase.strided.smskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the reciprocal square root for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ Infinity, 0.5, 0.0, ~0.289 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n    See Also\n    --------\n    base.strided.dmskrsqrt, base.strided.smsksqrt, base.strided.srsqrt"
 base.strided.smsksqrt,"\nbase.strided.smsksqrt( N, x, sx, m, sm, y, sy )\n    Computes the principal square root for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsksqrt( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ 0.0, 2.0, 0.0, ~3.464 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsksqrt( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smsksqrt( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ ~3.464, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.smsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the principal square root for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, 2.0, 0.0, ~3.464 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmsksqrt, base.strided.smskcbrt, base.strided.smskrsqrt, base.strided.srsqrt\n"
diff --git a/lib/node_modules/@stdlib/repl/help/data/data.json b/lib/node_modules/@stdlib/repl/help/data/data.json
index 7ca5d0d2d500..03a7de903de9 100644
--- a/lib/node_modules/@stdlib/repl/help/data/data.json
+++ b/lib/node_modules/@stdlib/repl/help/data/data.json
@@ -1 +1 @@
-{"abs":"\nabs( x[, options] )\n    Computes the absolute value.\n\n    If provided a number, the function returns a number.\n\n    If provided an ndarray or array-like object, the function performs element-\n    wise computation.\n\n    If provided an array-like object, the function returns an array-like object\n    having the same length and data type as `x`.\n\n    If provided an ndarray, the function returns an ndarray having the same\n    shape and data type as `x`.\n\n    Parameters\n    ----------\n    x: ndarray|ArrayLikeObject|number\n        Input value.\n\n    options: Object (optional)\n        Options.\n\n    options.order: string (optional)\n        Output array order (either row-major (C-style) or column-major (Fortran-\n        style)). Only applicable when the input array is an ndarray. By default,\n        the output array order is inferred from the input array.\n\n    options.dtype: string (optional)\n        Output array data type. Only applicable when the input array is either\n        an ndarray or array-like object. By default, the output array data type\n        is inferred from the input array.\n\n    Returns\n    -------\n    y: ndarray|ArrayLikeObject|number\n        Results.\n\n    Examples\n    --------\n    // Provide a number:\n    > var y = abs( -1.0 )\n    1.0\n\n    // Provide an array-like object:\n    > var x = new Float64Array( [ -1.0, -2.0 ] );\n    > y = abs( x )\n    <Float64Array>[ 1.0, 2.0 ]\n\n    > x = [ -1.0, -2.0 ];\n    > y = abs( x )\n    [ 1.0, 2.0 ]\n\n    // Provide an ndarray:\n    > x = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] );\n    > y = abs( x )\n    <ndarray>\n    > y.get( 0, 1 )\n    2.0\n\n\nabs.assign( x, y )\n    Computes the absolute value and assigns results to a provided output array.\n\n    Parameters\n    ----------\n    x: ndarray|ArrayLikeObject\n        Input array.\n\n    y: ndarray|ArrayLikeObject\n        Output array. Must be the same data \"kind\" (i.e., ndarray or array-like\n        object) as the input array.\n\n    Returns\n    -------\n    y: ndarray|ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Provide an array-like object:\n    > var x = new Float64Array( [ -1.0, -2.0 ] );\n    > var y = new Float64Array( x.length );\n    > var out = abs.assign( x, y )\n    <Float64Array>[ 1.0, 2.0 ]\n    > var bool = ( out === y )\n    true\n\n    > x = [ -1.0, -2.0 ];\n    > y = [ 0.0, 0.0 ];\n    > out = abs.assign( x, y )\n    [ 1.0, 2.0 ]\n    > bool = ( out === y )\n    true\n\n    // Provide an ndarray:\n    > x = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] );\n    > y = array( [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ] );\n    > out = abs.assign( x, y )\n    <ndarray>\n    > out.get( 0, 1 )\n    2.0\n    > bool = ( out === y )\n    true\n\n","abs.assign":"\nabs.assign( x, y )\n    Computes the absolute value and assigns results to a provided output array.\n\n    Parameters\n    ----------\n    x: ndarray|ArrayLikeObject\n        Input array.\n\n    y: ndarray|ArrayLikeObject\n        Output array. Must be the same data \"kind\" (i.e., ndarray or array-like\n        object) as the input array.\n\n    Returns\n    -------\n    y: ndarray|ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Provide an array-like object:\n    > var x = new Float64Array( [ -1.0, -2.0 ] );\n    > var y = new Float64Array( x.length );\n    > var out = abs.assign( x, y )\n    <Float64Array>[ 1.0, 2.0 ]\n    > var bool = ( out === y )\n    true\n\n    > x = [ -1.0, -2.0 ];\n    > y = [ 0.0, 0.0 ];\n    > out = abs.assign( x, y )\n    [ 1.0, 2.0 ]\n    > bool = ( out === y )\n    true\n\n    // Provide an ndarray:\n    > x = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] );\n    > y = array( [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ] );\n    > out = abs.assign( x, y )\n    <ndarray>\n    > out.get( 0, 1 )\n    2.0\n    > bool = ( out === y )\n    true","acartesianPower":"\nacartesianPower( x, n )\n    Returns the Cartesian power.\n\n    If provided an empty array, the function returns an empty array.\n\n    If `n` is less than or equal to zero, the function returns an empty array.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    n: integer\n        Power.\n\n    Returns\n    -------\n    out: Array<Array>\n        Cartesian product.\n\n    Examples\n    --------\n    > var x = [ 1, 2 ];\n    > var out = acartesianPower( x, 2 )\n    [ [ 1, 1 ], [ 1, 2 ], [ 2, 1 ], [ 2, 2 ] ]\n\n    See Also\n    --------\n    acartesianProduct, acartesianSquare\n","acartesianProduct":"\nacartesianProduct( x1, x2 )\n    Returns the Cartesian product.\n\n    If provided one or more empty arrays, the function returns an empty array.\n\n    Parameters\n    ----------\n    x1: ArrayLikeObject\n        First input array.\n\n    x2: ArrayLikeObject\n        Second input array.\n\n    Returns\n    -------\n    out: Array<Array>\n        Cartesian product.\n\n    Examples\n    --------\n    > var x1 = [ 1, 2 ];\n    > var x2 = [ 3, 4 ];\n    > var out = acartesianProduct( x1, x2 )\n    [ [ 1, 3 ], [ 1, 4 ], [ 2, 3 ], [ 2, 4 ] ]\n\n    See Also\n    --------\n    acartesianPower, acartesianSquare\n","acartesianSquare":"\nacartesianSquare( x )\n    Returns the Cartesian square.\n\n    If provided an empty array, the function returns an empty array.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    Returns\n    -------\n    out: Array<Array>\n        Cartesian product.\n\n    Examples\n    --------\n    > var out = acartesianSquare( [ 1, 2 ] )\n    [ [ 1, 1 ], [ 1, 2 ], [ 2, 1 ], [ 2, 2 ] ]\n\n    See Also\n    --------\n    acartesianPower, acartesianProduct\n","acronym":"\nacronym( str[, options] )\n    Generates an acronym for a given string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    options: Object (optional)\n        Options.\n\n    options.stopwords: Array<string> (optional)\n        Array of custom stop words.\n\n    Returns\n    -------\n    out: string\n        Acronym for the given string.\n\n    Examples\n    --------\n    > var out = acronym( 'the quick brown fox' )\n    'QBF'\n    > out = acronym( 'Hard-boiled eggs' )\n    'HBE'\n","aempty":"\naempty( length[, dtype] )\n    Creates an uninitialized array having a specified length.\n\n    In browser environments, the function always returns zero-filled arrays.\n\n    If `dtype` is 'generic', the function always returns a zero-filled array.\n\n    In Node.js versions >=3.0.0, the underlying memory of returned typed arrays\n    is *not* initialized. Memory contents are unknown and may contain\n    *sensitive* data.\n\n    Parameters\n    ----------\n    length: integer\n        Array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = aempty( 2 )\n    <Float64Array>\n    > arr = aempty( 2, 'float32' )\n    <Float32Array>\n\n    See Also\n    --------\n    aemptyLike, afull, aones, azeros, ndempty\n","aemptyLike":"\naemptyLike( x[, dtype] )\n    Creates an uninitialized array having the same length and data type as a\n    provided input array.\n\n    In browser environments, the function always returns zero-filled arrays.\n\n    If `dtype` is 'generic', the function always returns a zero-filled array.\n\n    In Node.js versions >=3.0.0, the underlying memory of returned typed arrays\n    is *not* initialized. Memory contents are unknown and may contain\n    *sensitive* data.\n\n    Parameters\n    ----------\n    x: TypedArray|Array\n        Input array.\n\n    dtype: string (optional)\n        Data type. If not provided, the output array data type is inferred from\n        the input array.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var x = new Float64Array( 2 );\n    > var arr = aemptyLike( x )\n    <Float64Array>\n    > arr = aemptyLike( x, 'float32' )\n    <Float32Array>\n\n    See Also\n    --------\n    aempty, afullLike, aonesLike, azerosLike, ndemptyLike\n","AFINN_96":"\nAFINN_96()\n    Returns a list of English words rated for valence.\n\n    The returned list contains 1468 English words (and phrases) rated for\n    valence. Negative words have a negative valence [-5,0). Positive words have\n    a positive valence (0,5]. Neutral words have a valence of 0.\n\n    A few notes:\n\n    - The list is an earlier version of AFINN-111.\n    - The list includes misspelled words. Their presence is intentional, as such\n      misspellings frequently occur in social media content.\n    - All words are lowercase.\n    - Some \"words\" are phrases; e.g., \"cashing in\", \"cool stuff\".\n    - Words may contain apostrophes; e.g., \"can't stand\".\n    - Words may contain dashes; e.g., \"cover-up\", \"made-up\".\n\n    Returns\n    -------\n    out: Array<Array>\n        List of English words and their valence.\n\n    Examples\n    --------\n    > var list = AFINN_96()\n    [ [ 'abandon', -2 ], [ 'abandons', -2 ], [ 'abandoned', -2 ], ... ]\n\n    References\n    ----------\n    - Nielsen, Finn Årup. 2011. \"A new ANEW: Evaluation of a word list for\n    sentiment analysis in microblogs.\" In *Proceedings of the ESWC2011 Workshop\n    on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n    718:93–98. CEUR Workshop Proceedings. <http://ceur-ws.org/Vol-718/paper_16.\n    pdf>.\n\n    * If you use the list for publication or third party consumption, please\n    cite the listed reference.\n\n    See Also\n    --------\n    AFINN_111\n","AFINN_111":"\nAFINN_111()\n    Returns a list of English words rated for valence.\n\n    The returned list contains 2477 English words (and phrases) rated for\n    valence. Negative words have a negative valence [-5,0). Positive words have\n    a positive valence (0,5]. Neutral words have a valence of 0.\n\n    A few notes:\n\n    - The list includes misspelled words. Their presence is intentional, as such\n      misspellings frequently occur in social media content.\n    - All words are lowercase.\n    - Words may contain numbers; e.g., \"n00b\".\n    - Some \"words\" are phrases; e.g., \"cool stuff\", \"not good\".\n    - Words may contain apostrophes; e.g., \"can't stand\".\n    - Words may contain diaeresis; e.g., \"naïve\".\n    - Words may contain dashes; e.g., \"self-deluded\", \"self-confident\".\n\n    Returns\n    -------\n    out: Array<Array>\n        List of English words and their valence.\n\n    Examples\n    --------\n    > var list = AFINN_111()\n    [ [ 'abandon', -2 ], [ 'abandoned', -2 ], [ 'abandons', -2 ], ... ]\n\n    References\n    ----------\n    - Nielsen, Finn Årup. 2011. \"A new ANEW: Evaluation of a word list for\n    sentiment analysis in microblogs.\" In *Proceedings of the ESWC2011 Workshop\n    on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n    718:93–98. CEUR Workshop Proceedings. <http://ceur-ws.org/Vol-718/paper_16.\n    pdf>.\n\n    * If you use the list for publication or third party consumption, please\n    cite the listed reference.\n\n    See Also\n    --------\n    AFINN_96\n","afull":"\nafull( length, value[, dtype] )\n    Returns a filled array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Array length.\n\n    value: any\n        Fill value.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = afull( 2, 1.0 )\n    <Float64Array>[ 1.0, 1.0 ]\n    > arr = afull( 2, 1.0, 'float32' )\n    <Float32Array>[ 1.0, 1.0 ]\n\n    See Also\n    --------\n    afullLike, aones, azeros\n","afullLike":"\nafullLike( x[, dtype] )\n    Returns a filled array having the same length and data type as a provided\n    input array.\n\n    Parameters\n    ----------\n    x: TypedArray|Array\n        Input array.\n\n    dtype: string (optional)\n        Data type. If not provided, the output array data type is inferred from\n        the input array.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var x = new Float64Array( 2 );\n    > var y = afullLike( x, 1.0 )\n    <Float64Array>[ 1.0, 1.0 ]\n    > y = afullLike( x, 1.0, 'float32' )\n    <Float32Array>[ 1.0, 1.0 ]\n\n    See Also\n    --------\n    afull, aonesLike, azerosLike\n","alias2pkg":"\nalias2pkg( alias )\n    Returns the package name associated with a provided alias.\n\n    Parameters\n    ----------\n    alias: string\n        Alias.\n\n    Returns\n    -------\n    out: string|null\n        Package name.\n\n    Examples\n    --------\n    > var v = alias2pkg( 'base.sin' )\n    '@stdlib/math/base/special/sin'\n\n    See Also\n    --------\n    alias2related, aliases, pkg2alias\n","alias2related":"\nalias2related( alias )\n    Returns aliases related to a specified alias.\n\n    Parameters\n    ----------\n    alias: string\n        Alias.\n\n    Returns\n    -------\n    out: Array|null\n        Related aliases.\n\n    Examples\n    --------\n    > var v = alias2related( 'base.sin' )\n    [...]\n\n    See Also\n    --------\n    alias2pkg, aliases, pkg2related\n","alias2standalone":"\nalias2standalone( alias )\n    Returns the standalone package name associated with a provided alias.\n\n    Parameters\n    ----------\n    alias: string\n        Alias.\n\n    Returns\n    -------\n    out: string|null\n        Standalone package name.\n\n    Examples\n    --------\n    > var v = alias2standalone( 'base.sin' )\n    '@stdlib/math-base-special-sin'\n\n    See Also\n    --------\n    alias2pkg, alias2related, aliases, pkg2alias, pkg2standalone\n","aliases":"\naliases( [namespace] )\n    Returns a list of standard library aliases.\n\n    Parameters\n    ----------\n    namespace: string (optional)\n        Namespace filter.\n\n    Returns\n    -------\n    out: Array\n        List of aliases.\n\n    Examples\n    --------\n    > var o = aliases()\n    [...]\n    > o = aliases( '@stdlib/math/base/special' )\n    [...]\n\n    See Also\n    --------\n    alias2pkg, alias2related, pkg2alias\n","allocUnsafe":"\nallocUnsafe( size )\n    Allocates a buffer having a specified number of bytes.\n\n    The underlying memory of returned buffers is not initialized. Memory\n    contents are unknown and may contain sensitive data.\n\n    When the size is less than half a buffer pool size, memory is allocated from\n    the buffer pool for faster allocation of Buffer instances.\n\n    Parameters\n    ----------\n    size: integer\n        Number of bytes to allocate.\n\n    Returns\n    -------\n    out: Buffer\n        Buffer instance.\n\n    Examples\n    --------\n    > var buf = allocUnsafe( 100 )\n    <Buffer>\n\n    See Also\n    --------\n    Buffer, array2buffer, arraybuffer2buffer, copyBuffer, string2buffer\n","amskfilter":"\namskfilter( x, mask )\n    Returns a new array by applying a mask to a provided input array.\n\n    If a mask array element is truthy, the corresponding element in `x` is\n    included in the output array; otherwise, the corresponding element in `x` is\n    \"masked\" and thus excluded from the output array.\n\n    Parameters\n    ----------\n    x: Array|TypedArray|Object\n        Input array.\n\n    mask: Array|TypedArray|Object\n        Mask array.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Output array.\n\n    Examples\n    --------\n    > var x = [ 1, 2, 3, 4 ];\n    > var y = amskfilter( x, [ 0, 1, 0, 1 ] )\n    [ 2, 4 ]\n\n    See Also\n    --------\n    amskreject\n","amskput":"\namskput( x, mask, values[, options] )\n    Replaces elements of an array with provided values according to a provided\n    mask array.\n\n    In broadcasting modes, the function supports broadcasting a values array\n    containing a single element against the number of falsy values in the mask\n    array.\n\n    In repeat mode, the function supports recycling elements in a values array\n    to satisfy the number of falsy values in the mask array.\n\n    The function mutates the input array.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    mask: ArrayLikeObject\n        Mask array. If a mask array element is falsy, the corresponding element\n        in `x` is *replaced*; otherwise, the corresponding element in `x` is\n        \"masked\" and thus left unchanged.\n\n    values: ArrayLikeObject\n        Values to set.\n\n    options: Object (optional)\n        Function options.\n\n    options.mode: string (optional)\n        String specifying behavior when the number of values to set does not\n        equal the number of falsy mask values. The function supports the\n        following modes:\n\n        - 'strict': specifies that the function must raise an exception when the\n        number of values does not *exactly* equal the number of falsy mask\n        values.\n        - 'non_strict': specifies that the function must raise an exception when\n        the function is provided insufficient values to satisfy the mask array.\n        - 'strict_broadcast': specifies that the function must broadcast a\n        single-element values array and otherwise raise an exception when the\n        number of values does not **exactly** equal the number of falsy mask\n        values.\n        - 'broadcast': specifies that the function must broadcast a single-\n        element values array and otherwise raise an exception when the function\n        is provided insufficient values to satisfy the mask array.\n        - 'repeat': specifies that the function must reuse provided values when\n        replacing elements in `x` in order to satisfy the mask array.\n\n        Default: 'repeat'.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Input array.\n\n    Examples\n    --------\n    > var x = [ 1, 2, 3, 4 ];\n    > var out = amskput( x, [ 1, 0, 1, 0 ], [ 20, 40 ] )\n    [ 1, 20, 3, 40 ]\n    > var bool = ( out === x )\n    true\n\n    See Also\n    --------\n    aplace, aput, atake\n","amskreject":"\namskreject( x, mask )\n    Returns a new array by applying a mask to a provided input array.\n\n    If a mask array element is falsy, the corresponding element in `x` is\n    included in the output array; otherwise, the corresponding element in `x` is\n    \"masked\" and thus excluded from the output array.\n\n    Parameters\n    ----------\n    x: Array|TypedArray|Object\n        Input array.\n\n    mask: Array|TypedArray|Object\n        Mask array.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Output array.\n\n    Examples\n    --------\n    > var x = [ 1, 2, 3, 4 ];\n    > var y = amskreject( x, [ 0, 1, 0, 1 ] )\n    [ 1, 3 ]\n\n    See Also\n    --------\n    amskfilter\n","anans":"\nanans( length[, dtype] )\n    Returns an array filled with NaNs and having a specified length.\n\n    The function supports the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754)\n    - float32: single-precision floating-point numbers (IEEE 754)\n    - complex128: double-precision complex floating-point numbers\n    - complex64: single-precision complex floating-point numbers\n    - generic: generic JavaScript values\n\n    The default array data type is `float64`.\n\n    Parameters\n    ----------\n    length: integer\n        Array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = anans( 2 )\n    <Float64Array>[ NaN, NaN ]\n    > arr = anans( 2, 'float32' )\n    <Float32Array>[ NaN, NaN ]\n\n    See Also\n    --------\n    afull, anansLike, aones, azeros\n","anansLike":"\nanansLike( x[, dtype] )\n    Returns an array filled with NaNs and having the same length and data type\n    as a provided input array.\n\n    The function supports the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754).\n    - float32: single-precision floating-point numbers (IEEE 754).\n    - complex128: double-precision complex floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - generic: generic JavaScript values.\n\n    Parameters\n    ----------\n    x: TypedArray|Array\n        Input array.\n\n    dtype: string (optional)\n        Data type. If not provided, the output array data type is inferred from\n        the input array.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var x = new Float64Array( 2 );\n    > var y = anansLike( x )\n    <Float64Array>[ NaN, NaN ]\n    > y = anansLike( x, 'float32' )\n    <Float32Array>[ NaN, NaN ]\n\n    See Also\n    --------\n    afullLike, anans, aonesLike, azerosLike\n","anova1":"\nanova1( x, factor[, options] )\n    Performs a one-way analysis of variance.\n\n    Parameters\n    ----------\n    x: Array<number>\n        Measured values.\n\n    factor: Array\n        Array of treatments.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.method: string\n        Name of test.\n\n    out.means: Object\n        Group means alongside sample sizes and standard errors.\n\n    out.treatment: Object\n        Treatment results.\n\n    out.treatment.df: number\n        Treatment degrees of freedom.\n\n    out.treatment.ss: number\n        Treatment sum of squares.\n\n    out.treatment.ms: number\n        Treatment mean sum of squares.\n\n    out.error: Object\n        Error results.\n\n    out.error.df: number\n        Error degrees of freedom.\n\n    out.error.ss: number\n        Error sum of squares.\n\n    out.error.ms: number\n        Error mean sum of squares.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    > var x = [1, 3, 5, 2, 4, 6, 8, 7, 10, 11, 12, 15];\n    > var f = [\n    ... 'control', 'treatA', 'treatB', 'treatC', 'control',\n    ... 'treatA', 'treatB', 'treatC', 'control', 'treatA', 'treatB', 'treatC'\n    ... ];\n    > var out = anova1( x, f )\n    {...}\n\n","ANSCOMBES_QUARTET":"\nANSCOMBES_QUARTET()\n    Returns Anscombe's quartet.\n\n    Anscombe's quartet is a set of 4 datasets which all have nearly identical\n    simple statistical properties but vary considerably when graphed. Anscombe\n    created the datasets to demonstrate why graphical data exploration should\n    precede statistical data analysis and to show the effect of outliers on\n    statistical properties.\n\n    Returns\n    -------\n    out: Array<Array>\n        Anscombe's quartet.\n\n    Examples\n    --------\n    > var d = ANSCOMBES_QUARTET()\n    [[[10,8.04],...],[[10,9.14],...],[[10,7.46],...],[[8,6.58],...]]\n\n    References\n    ----------\n    - Anscombe, Francis J. 1973. \"Graphs in Statistical Analysis.\" *The American\n    Statistician* 27 (1). [American Statistical Association, Taylor & Francis,\n    Ltd.]: 17–21. <http://www.jstor.org/stable/2682899>.\n\n","any":"\nany( collection )\n    Tests whether at least one element in a collection is truthy.\n\n    The function immediately returns upon encountering a truthy value.\n\n    If provided an empty collection, the function returns `false`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if an element is truthy; otherwise, the\n        function returns `false`.\n\n    Examples\n    --------\n    > var arr = [ 0, 0, 0, 0, 1 ];\n    > var bool = any( arr )\n    true\n\n    See Also\n    --------\n    anyBy, every, forEach, none, some\n","anyBy":"\nanyBy( collection, predicate[, thisArg ] )\n    Tests whether at least one element in a collection passes a test implemented\n    by a predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    The function immediately returns upon encountering a truthy return value.\n\n    If provided an empty collection, the function returns `false`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns `true` for\n        any element; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function negative( v ) { return ( v < 0 ); };\n    > var arr = [ 1, 2, 3, 4, -1 ];\n    > var bool = anyBy( arr, negative )\n    true\n\n    See Also\n    --------\n    anyByAsync, anyByRight, everyBy, forEach, noneBy, someBy\n","anyByAsync":"\nanyByAsync( collection, [options,] predicate, done )\n    Tests whether at least one element in a collection passes a test implemented\n    by a predicate function.\n\n    When invoked, the predicate function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If the\n    predicate function accepts two arguments, the predicate function is\n    provided:\n\n    - value\n    - next\n\n    If the predicate function accepts three arguments, the predicate function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other predicate function signature, the predicate function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - result: test result.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    The function immediately returns upon encountering a non-falsy `result`\n    value and calls the `done` callback with `null` as the first argument and\n    `true` as the second argument.\n\n    If all elements fail, the function calls the `done` callback with `null`\n    as the first argument and `false` as the second argument.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > anyByAsync( arr, predicate, done )\n    1000\n    2500\n    3000\n    false\n\n    // Limit number of concurrent invocations:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 3000, 2500, 1000 ];\n    > anyByAsync( arr, opts, predicate, done )\n    2500\n    3000\n    1000\n    false\n\n    // Process sequentially:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 3000, 2500, 1000 ];\n    > anyByAsync( arr, opts, predicate, done )\n    3000\n    2500\n    1000\n    false\n\n\nanyByAsync.factory( [options,] predicate )\n    Returns a function which tests whether at least one element in a collection\n    passes a test implemented by a predicate function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = anyByAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    false\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    false\n\n    See Also\n    --------\n    anyBy, anyByRightAsync, everyByAsync, forEachAsync, noneByAsync, someByAsync\n","anyByAsync.factory":"\nanyByAsync.factory( [options,] predicate )\n    Returns a function which tests whether at least one element in a collection\n    passes a test implemented by a predicate function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = anyByAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    false\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    false\n\n    See Also\n    --------\n    anyBy, anyByRightAsync, everyByAsync, forEachAsync, noneByAsync, someByAsync","anyByRight":"\nanyByRight( collection, predicate[, thisArg ] )\n    Tests whether at least one element in a collection passes a test implemented\n    by a predicate function, iterating from right to left.\n\n    The predicate function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    The function immediately returns upon encountering a truthy return value.\n\n    If provided an empty collection, the function returns `false`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns `true` for\n        any element; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function negative( v ) { return ( v < 0 ); };\n    > var arr = [ -1, 1, 2, 3, 4 ];\n    > var bool = anyByRight( arr, negative )\n    true\n\n    See Also\n    --------\n    anyBy, anyByRightAsync, everyByRight, forEachRight, noneByRight, someByRight\n","anyByRightAsync":"\nanyByRightAsync( collection, [options,] predicate, done )\n    Tests whether at least one element in a collection passes a test implemented\n    by a predicate function, iterating from right to left.\n\n    When invoked, the predicate function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If the\n    predicate function accepts two arguments, the predicate function is\n    provided:\n\n    - value\n    - next\n\n    If the predicate function accepts three arguments, the predicate function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other predicate function signature, the predicate function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - result: test result.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    The function immediately returns upon encountering a non-falsy `result`\n    value and calls the `done` callback with `null` as the first argument and\n    `true` as the second argument.\n\n    If all elements fail, the function calls the `done` callback with `null`\n    as the first argument and `false` as the second argument.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > anyByRightAsync( arr, predicate, done )\n    1000\n    2500\n    3000\n    false\n\n    // Limit number of concurrent invocations:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 1000, 2500, 3000 ];\n    > anyByRightAsync( arr, opts, predicate, done )\n    2500\n    3000\n    1000\n    false\n\n    // Process sequentially:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 1000, 2500, 3000 ];\n    > anyByRightAsync( arr, opts, predicate, done )\n    3000\n    2500\n    1000\n    false\n\n\nanyByRightAsync.factory( [options,] predicate )\n    Returns a function which tests whether at least one element in a collection\n    passes a test implemented by a predicate function, iterating from right to\n    left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = anyByRightAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    false\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    false\n\n    See Also\n    --------\n    anyByAsync, anyByRight, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByRightAsync\n","anyByRightAsync.factory":"\nanyByRightAsync.factory( [options,] predicate )\n    Returns a function which tests whether at least one element in a collection\n    passes a test implemented by a predicate function, iterating from right to\n    left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = anyByRightAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    false\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    false\n\n    See Also\n    --------\n    anyByAsync, anyByRight, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByRightAsync","anyInBy":"\nanyInBy( object, predicate[, thisArg ] )\n    Tests whether at least one value in an object passes a test implemented by\n    a predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: the value of the current property being processed in the object\n    - key: the key of the current property being processed in the object\n    - object: the input object\n\n    The function immediately returns upon encountering a truthy return value.\n\n    If provided an empty object, the function returns `false`.\n\n    Parameters\n    ----------\n    object: Object\n        Input object over which to iterate. It must be non-null.\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns `true` for\n        any value; otherwise, it returns `false`.\n\n    Examples\n    --------\n    > function isNegative(value) { return value < 0 }\n    > var obj = { a: 1, b: -2, c: 3, d: 4 }\n    > var result = anyInBy(obj, isNegative)\n    true\n\n    See Also\n    --------\n    anyBy, anyOwnBy, everyInBy, someInBy","anyOwnBy":"\nanyOwnBy( object, predicate[, thisArg ] )\n    Tests whether at least one own property of an object passes a\n    test implemented by a predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: property value.\n    - index: property key.\n    - object: the input object.\n\n    The function immediately returns upon encountering a truthy return\n    value.\n\n    If provided an empty object, the function returns `false`.\n\n    Parameters\n    ----------\n    object: Object\n        Input object.\n\n    predicate: Function\n        Test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns a truthy\n        value for one own property; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function positive( v ) { return ( v > 0 ); };\n    > var obj = { 'a': -1, 'b': 2, 'c': -3 };\n    > var bool = anyOwnBy( obj, positive )\n    true\n\n    See Also\n    --------\n    anyBy, anyInBy, everyOwnBy, someOwnBy\n","aones":"\naones( length[, dtype] )\n    Returns an array filled with ones and having a specified length.\n\n    The function supports the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754).\n    - float32: single-precision floating-point numbers (IEEE 754).\n    - complex128: double-precision complex floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n    - generic: generic JavaScript values.\n\n    The default array data type is `float64`.\n\n    Parameters\n    ----------\n    length: integer\n        Array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = aones( 2 )\n    <Float64Array>[ 1.0, 1.0 ]\n    > arr = aones( 2, 'float32' )\n    <Float32Array>[ 1.0, 1.0 ]\n\n    See Also\n    --------\n    afull, anans, aonesLike, azeros\n","aonesLike":"\naonesLike( x[, dtype] )\n    Returns an array filled with ones and having the same length and data type\n    as a provided input array.\n\n    The function supports the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754).\n    - float32: single-precision floating-point numbers (IEEE 754).\n    - complex128: double-precision complex floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n    - generic: generic JavaScript values.\n\n    Parameters\n    ----------\n    x: TypedArray|Array\n        Input array.\n\n    dtype: string (optional)\n        Data type. If not provided, the output array data type is inferred from\n        the input array.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var x = new Float64Array( 2 );\n    > var y = aonesLike( x )\n    <Float64Array>[ 1.0, 1.0 ]\n    > y = aonesLike( x, 'float32' )\n    <Float32Array>[ 1.0, 1.0 ]\n\n    See Also\n    --------\n    afullLike, anansLike, aones, azerosLike\n","aoneTo":"\naoneTo( n[, dtype] )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from one.\n\n    The function supports the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754).\n    - float32: single-precision floating-point numbers (IEEE 754).\n    - complex128: double-precision complex floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n    - generic: generic JavaScript values.\n\n    The default array data type is `float64`.\n\n    If `n` is equal to zero, the function returns an empty array.\n\n    Parameters\n    ----------\n    n: integer\n        Number of elements.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = aoneTo( 2 )\n    <Float64Array>[ 1.0, 2.0 ]\n    > arr = aoneTo( 2, 'float32' )\n    <Float32Array>[ 1.0, 2.0 ]\n\n    See Also\n    --------\n    afull, aones, aoneToLike, azeroTo\n","aoneToLike":"\naoneToLike( x[, dtype] )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from one and having the same length and data type as a provided\n    input array.\n\n    The function supports the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754).\n    - float32: single-precision floating-point numbers (IEEE 754).\n    - complex128: double-precision complex floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n    - generic: generic JavaScript values.\n\n    Parameters\n    ----------\n    x: TypedArray|Array\n        Input array.\n\n    dtype: string (optional)\n        Data type. If not provided, the output array data type is inferred from\n        the input array.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = aoneToLike( [ 0, 0 ] )\n    [ 1, 2 ]\n    > arr = aoneToLike( [ 0, 0 ], 'float32' )\n    <Float32Array>[ 1.0, 2.0 ]\n\n    See Also\n    --------\n    afullLike, aonesLike, aoneTo, azeroToLike\n","APERY":"\nAPERY\n    Apéry's constant.\n\n    Examples\n    --------\n    > APERY\n    1.2020569031595942\n\n","aplace":"\naplace( x, mask, values[, options] )\n    Replaces elements of an array with provided values according to a provided\n    mask array.\n\n    In broadcasting modes, the function supports broadcasting a values array\n    containing a single element against the number of truthy values in the mask\n    array.\n\n    In repeat mode, the function supports recycling elements in a values array\n    to satisfy the number of truthy values in the mask array.\n\n    The function mutates the input array.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    mask: ArrayLikeObject\n        Mask array. If a mask array element is truthy, the corresponding element\n        in `x` is *replaced*; otherwise, the corresponding element in `x` is\n        \"masked\" and thus left unchanged.\n\n    values: ArrayLikeObject\n        Values to set.\n\n    options: Object (optional)\n        Function options.\n\n    options.mode: string (optional)\n        String specifying behavior when the number of values to set does not\n        equal the number of truthy mask values. The function supports the\n        following modes:\n\n        - 'strict': specifies that the function must raise an exception when the\n        number of values does not *exactly* equal the number of truthy mask\n        values.\n        - 'non_strict': specifies that the function must raise an exception when\n        the function is provided insufficient values to satisfy the mask array.\n        - 'strict_broadcast': specifies that the function must broadcast a\n        single-element values array and otherwise raise an exception when the\n        number of values does not **exactly** equal the number of truthy mask\n        values.\n        - 'broadcast': specifies that the function must broadcast a single-\n        element values array and otherwise raise an exception when the function\n        is provided insufficient values to satisfy the mask array.\n        - 'repeat': specifies that the function must reuse provided values when\n        replacing elements in `x` in order to satisfy the mask array.\n\n        Default: 'repeat'.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Input array.\n\n    Examples\n    --------\n    > var x = [ 1, 2, 3, 4 ];\n    > var out = aplace( x, [ 0, 1, 0, 1 ], [ 20, 40 ] )\n    [ 1, 20, 3, 40 ]\n    > var bool = ( out === x )\n    true\n\n    See Also\n    --------\n    amskput, aput, atake\n","append":"\nappend( collection1, collection2 )\n    Adds the elements of one collection to the end of another collection.\n\n    If the input collection is a typed array, the output value does not equal\n    the input reference and the underlying `ArrayBuffer` may *not* be the same\n    as the `ArrayBuffer` belonging to the input view.\n\n    For purposes of generality, always treat the output collection as distinct\n    from the input collection.\n\n    Parameters\n    ----------\n    collection1: Array|TypedArray|Object\n        A collection. If the collection is an `Object`, the collection should be\n        array-like.\n\n    collection2: Array|TypedArray|Object\n        A collection containing the elements to add. If the collection is an\n        `Object`, the collection should be array-like.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Updated collection.\n\n    Examples\n    --------\n    // Arrays:\n    > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > arr = append( arr, [ 6.0, 7.0 ] )\n    [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]\n\n    // Typed arrays:\n    > arr = new Float64Array( [ 1.0, 2.0 ] );\n    > arr = append( arr, [ 3.0, 4.0 ] )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Array-like object:\n    > arr = { 'length': 0 };\n    > arr = append( arr, [ 1.0, 2.0 ] )\n    { 'length': 2, '0': 1.0, '1': 2.0 }\n\n    See Also\n    --------\n    prepend, push\n","aput":"\naput( x, indices, values[, options] )\n    Replaces specified elements of an array with provided values.\n\n    The function supports broadcasting a `values` array containing a single\n    element against an `indices` array containing one or more elements.\n\n    The function mutates the input array.\n\n    Because each index is only validated at the time of replacing a particular\n    element, mutation may occur even when one or more indices are out-of-bounds,\n    including when the index mode indicates to raise an exception.\n\n    If `indices` is an empty array, the function returns the input array\n    unchanged.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    indices: ArrayLikeObject<integer>\n        List of element indices.\n\n    values: ArrayLikeObject\n        Values to set. When `indices` contains one or more elements, `values`\n        must be broadcast compatible with `indices` (i.e., must have either one\n        element or the same number of elements as `indices`).\n\n    options: Object (optional)\n        Function options.\n\n    options.mode: string (optional)\n        Specifies how to handle an index outside the interval [0, max], where\n        `max` is the maximum possible array index. If equal to 'throw', the\n        function throws an error. If equal to 'normalize', the function throws\n        an error if provided an out-of-bounds normalized index. If equal to\n        'wrap', the function wraps around an index using modulo arithmetic. If\n        equal to 'clamp', the function sets an index to either 0 (minimum index)\n        or the maximum index. Default: 'normalize'.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Input array.\n\n    Examples\n    --------\n    > var x = [ 1, 2, 3, 4 ];\n    > var out = aput( x, [ 1, 3 ], [ 20, 40 ] )\n    [ 1, 20, 3, 40 ]\n    > var bool = ( out === x )\n    true\n\n    See Also\n    --------\n    amskput, aplace, atake\n","ARCH":"\nARCH\n    Operating system CPU architecture for which the JavaScript runtime binary\n    was compiled.\n\n    Current possible values:\n\n    - arm\n    - arm64\n    - ia32\n    - mips\n    - mipsel\n    - ppc\n    - ppc64\n    - s390\n    - s390x\n    - x32\n    - x64\n\n    Examples\n    --------\n    > ARCH\n    <string>\n\n    See Also\n    --------\n    PLATFORM\n","argumentFunction":"\nargumentFunction( idx )\n    Returns a function which always returns a specified argument.\n\n    The input argument corresponds to the zero-based index of the argument to\n    return.\n\n    Parameters\n    ----------\n    idx: integer\n        Argument index to return (zero-based).\n\n    Returns\n    -------\n    out: Function\n        Argument function.\n\n    Examples\n    --------\n    > var argn = argumentFunction( 1 );\n    > var v = argn( 3.14, -3.14, 0.0 )\n    -3.14\n    > v = argn( -1.0, -0.0, 1.0 )\n    -0.0\n    > v = argn( 'beep', 'boop', 'bop' )\n    'boop'\n    > v = argn( 'beep' )\n    undefined\n\n    See Also\n    --------\n    constantFunction, identity\n","ARGV":"\nARGV\n    An array containing command-line arguments passed when launching the calling\n    process.\n\n    The first element is the absolute pathname of the executable that started\n    the calling process.\n\n    The second element is the path of the executed file.\n\n    Any additional elements are additional command-line arguments.\n\n    In browser environments, the array is empty.\n\n    Examples\n    --------\n    > var execPath = ARGV[ 0 ]\n    e.g., /usr/local/bin/node\n\n    See Also\n    --------\n    ENV\n","array":"\narray( [buffer,] [options] )\n    Returns a multidimensional array.\n\n    Parameters\n    ----------\n    buffer: Array|TypedArray|Buffer|ndarray (optional)\n        Data source.\n\n    options: Object (optional)\n        Options.\n\n    options.buffer: Array|TypedArray|Buffer|ndarray (optional)\n        Data source. If provided along with a `buffer` argument, the argument\n        takes precedence.\n\n    options.dtype: string (optional)\n        Underlying storage data type. If not specified and a data source is\n        provided, the data type is inferred from the provided data source. If an\n        input data source is not of the same type, this option specifies the\n        data type to which to cast the input data. For non-ndarray generic array\n        data sources, the function casts generic array data elements to the\n        default data type. In order to prevent this cast, the `dtype` option\n        must be explicitly set to `'generic'`. Any time a cast is required, the\n        `copy` option is set to `true`, as memory must be copied from the data\n        source to an output data buffer. Default: 'float64'.\n\n    options.order: string (optional)\n        Specifies the memory layout of the data source as either row-major (C-\n        style) or column-major (Fortran-style). The option may be one of the\n        following values:\n\n        - 'row-major': the order of the returned array is row-major.\n        - 'column-major': the order of the returned array is column-major.\n        - 'any': if a data source is column-major and not row-major, the order\n          of the returned array is column-major; otherwise, the order of the\n          returned array is row-major.\n        - 'same': the order of the returned array matches the order of an input\n          data source.\n\n        Note that specifying an order which differs from the order of a\n        provided data source does *not* entail a conversion from one memory\n        layout to another. In short, this option is descriptive, not\n        prescriptive. Default: 'row-major'.\n\n    options.shape: Array<integer> (optional)\n        Array shape (dimensions). If a shape is not specified, the function\n        attempts to infer a shape based on a provided data source. For example,\n        if provided a nested array, the function resolves nested array\n        dimensions. If provided a multidimensional array data source, the\n        function uses the array's associated shape. For most use cases, such\n        inference suffices. For the remaining use cases, specifying a shape is\n        necessary. For example, provide a shape to create a multidimensional\n        array view over a linear data buffer, ignoring any existing shape meta\n        data associated with a provided data source.\n\n    options.flatten: boolean (optional)\n        Boolean indicating whether to automatically flatten generic array data\n        sources. If an array shape is not specified, the shape is inferred from\n        the dimensions of nested arrays prior to flattening. If a use case\n        requires partial flattening, partially flatten prior to invoking this\n        function and set the option value to `false` to prevent further\n        flattening during invocation. Default: true.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to (shallow) copy source data to a new data\n        buffer. The function does *not* perform a deep copy. To prevent\n        undesired shared changes in state for generic arrays containing objects,\n        perform a deep copy prior to invoking this function. Default: false.\n\n    options.ndmin: integer (optional)\n        Specifies the minimum number of dimensions. If an array shape has fewer\n        dimensions than required by `ndmin`, the function prepends singleton\n        dimensions to the array shape in order to satisfy the dimensions\n        requirement. Default: 0.\n\n    options.casting: string (optional)\n        Specifies the casting rule used to determine acceptable casts. The\n        option may be one of the following values:\n\n        - 'none': only allow casting between identical types.\n        - 'equiv': allow casting between identical and byte swapped types.\n        - 'safe': only allow \"safe\" casts.\n        - 'mostly-safe': allow \"safe casts\" and, for floating-point data types,\n          downcasts.\n        - 'same-kind': allow \"safe\" casts and casts within the same kind (e.g.,\n          between signed integers or between floats).\n        - 'unsafe': allow casting between all types (including between integers\n          and floats).\n\n        Default: 'safe'.\n\n    options.codegen: boolean (optional)\n        Boolean indicating whether to use code generation. Code generation can\n        boost performance, but may be problematic in browser contexts enforcing\n        a strict content security policy (CSP). Default: true.\n\n    options.mode: string (optional)\n        Specifies how to handle indices which exceed array dimensions. The\n        option may be one of the following values:\n\n        - 'throw': an ndarray instance throws an error when an index exceeds\n          array dimensions.\n        - 'normalize': an ndarray instance normalizes negative indices and\n          throws an error when an index exceeds array dimensions.\n        - 'wrap': an ndarray instance wraps around indices exceeding array\n          dimensions using modulo arithmetic.\n        - 'clamp', an ndarray instance sets an index exceeding array dimensions\n          to either `0` (minimum index) or the maximum index.\n\n        Default: 'throw'.\n\n    options.submode: Array<string> (optional)\n        Specifies how to handle subscripts which exceed array dimensions. If a\n        mode for a corresponding dimension is equal to\n\n        - 'throw': an ndarray instance throws an error when a subscript exceeds\n          array dimensions.\n        - 'normalize': an ndarray instance normalizes negative subscripts and\n          throws an error when a subscript exceeds array dimensions.\n        - 'wrap': an ndarray instance wraps around subscripts exceeding array\n          dimensions using modulo arithmetic.\n        - 'clamp': an ndarray instance sets a subscript exceeding array\n          dimensions to either `0` (minimum index) or the maximum index.\n\n        If the number of modes is fewer than the number of dimensions, the\n        function recycles modes using modulo arithmetic.\n\n        Default: [ options.mode ].\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether an array should be read-only. Default: false.\n\n    Returns\n    -------\n    out: ndarray\n        Multidimensional array.\n\n    Examples\n    --------\n    // Create a 2x2 matrix:\n    > var arr = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] )\n    <ndarray>\n\n    // Get an element using subscripts:\n    > var v = arr.get( 1, 1 )\n    4.0\n\n    // Get an element using a linear index:\n    > v = arr.iget( 3 )\n    4.0\n\n    // Set an element using subscripts:\n    > arr.set( 1, 1, 40.0 );\n    > arr.get( 1, 1 )\n    40.0\n\n    // Set an element using a linear index:\n    > arr.iset( 3, 99.0 );\n    > arr.get( 1, 1 )\n    99.0\n\n    See Also\n    --------\n    ndarray\n","array2buffer":"\narray2buffer( arr )\n    Allocates a buffer using an octet array.\n\n    Parameters\n    ----------\n    arr: Array<integer>\n        Array (or array-like object) of octets from which to copy.\n\n    Returns\n    -------\n    out: Buffer\n        Buffer instance.\n\n    Examples\n    --------\n    > var buf = array2buffer( [ 1, 2, 3, 4 ] )\n    <Buffer>[ 1, 2, 3, 4 ]\n\n    See Also\n    --------\n    Buffer, arraybuffer2buffer, copyBuffer, string2buffer\n","array2fancy":"\narray2fancy( x[, options] )\n    Converts an array to an object supporting fancy indexing.\n\n    An array supporting fancy indexing is an array which supports slicing via\n    indexing expressions for both retrieval and assignment.\n\n    A fancy array shares the *same* data as the provided input array. Hence, any\n    mutations to the returned array will affect the underlying input array and\n    vice versa.\n\n    For operations returning a new array (e.g., when slicing or invoking an\n    instance method), a fancy array returns a new fancy array having the same\n    configuration as specified by provided options.\n\n    A fancy array supports indexing using positive and negative integers (both\n    numeric literals and strings), Slice instances, subsequence expressions,\n    mask arrays, boolean arrays, and integer arrays.\n\n    A fancy array supports all properties and methods of the input array, and,\n    thus, a fancy array can be consumed by any API which supports array-like\n    objects.\n\n    Indexing expressions provide a convenient and powerful means for creating\n    and operating on array views; however, their use does entail a performance\n    cost. Indexing expressions are best suited for interactive use (e.g., in the\n    REPL) and scripting. For performance critical applications, prefer\n    equivalent functional APIs supporting array-like objects.\n\n    Fancy arrays support broadcasting in which assigned scalars and single-\n    element arrays are repeated (without additional memory allocation) to match\n    the length of a target array instance.\n\n    Fancy array broadcasting follows the same rules as for ndarrays.\n\n    Consequently, when assigning arrays to slices, the array on the right-hand-\n    side must be broadcast-compatible with number of elements in the slice.\n\n    Fancy arrays support (mostly) safe casts (i.e., any cast which can be\n    performed without overflow or loss of precision, with the exception of\n    floating-point arrays which are also allowed to downcast from higher\n    precision to lower precision).\n\n    When attempting to perform an unsafe cast, fancy arrays will raise an\n    exception.\n\n    When assigning a real-valued scalar to a complex number array (e.g.,\n    Complex128Array or Complex64Array), a fancy array will cast the real-valued\n    scalar to a complex number argument having an imaginary component equal to\n    zero.\n\n    In older JavaScript environments which do not support Proxy objects, the use\n    of indexing expressions is not supported.\n\n    Parameters\n    ----------\n    x: Array|TypedArray|Object\n        Input array.\n\n    options: Object (optional)\n        Function options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking. Default:\n        false.\n\n    options.cache: Object (optional)\n        Cache for resolving array index objects. Must have a 'get' method which\n        accepts a single argument: a string identifier associated with an array\n        index. If an array index associated with a provided identifier exists,\n        the 'get' method should return an object having the following\n        properties:\n\n        - data: the underlying index array.\n        - type: the index type. Must be either 'mask', 'bool', or 'int'.\n        - dtype: the data type of the underlying array.\n\n        If an array index is not associated with a provided identifier, the\n        'get' method should return `null`.\n\n        Default: `ArrayIndex`.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Output array supporting fancy indexing.\n\n    Examples\n    --------\n    > var y = array2fancy( [ 1, 2, 3, 4 ] );\n    > y[ '1::2' ]\n    [ 2, 4 ]\n    > y[ '::-1' ]\n    [ 4, 3, 2, 1 ]\n\n\narray2fancy.factory( [options] )\n    Returns a function for converting an array to an object supporting fancy\n    indexing.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking by default.\n        Default: false.\n\n    options.cache: Object (optional)\n        Cache for resolving array index objects. Must have a 'get' method which\n        accepts a single argument: a string identifier associated with an array\n        index. If an array index associated with a provided identifier exists,\n        the 'get' method should return an object having the following\n        properties:\n\n        - data: the underlying index array.\n        - type: the index type. Must be either 'mask', 'bool', or 'int'.\n        - dtype: the data type of the underlying array.\n\n        If an array index is not associated with a provided identifier, the\n        'get' method should return `null`.\n\n        Default: `ArrayIndex`.\n\n    Returns\n    -------\n    fcn: Function\n        Function for converting an array to an object supporting fancy indexing.\n\n    Examples\n    --------\n    > var f = array2fancy.factory();\n    > var y = f( [ 1, 2, 3, 4 ] );\n    > y[ '1::2' ]\n    [ 2, 4 ]\n    > y[ '::-1' ]\n    [ 4, 3, 2, 1 ]\n\n\narray2fancy.idx( x[, options] )\n    Wraps a provided array as an array index object.\n\n    For documentation and usage, see `ArrayIndex`.\n\n    Parameters\n    ----------\n    x: Array|TypedArray|Object\n        Input array.\n\n    options: Object (optional)\n        Function options.\n\n    options.persist: boolean (optional)\n        Boolean indicating whether to continue persisting an index object after\n        first usage. Default: false.\n\n    Returns\n    -------\n    out: ArrayIndex\n        ArrayIndex instance.\n\n    Examples\n    --------\n    > var idx = array2fancy.idx( [ 1, 2, 3, 4 ] );\n\n    See Also\n    --------\n    aslice, FancyArray\n","array2fancy.factory":"\narray2fancy.factory( [options] )\n    Returns a function for converting an array to an object supporting fancy\n    indexing.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking by default.\n        Default: false.\n\n    options.cache: Object (optional)\n        Cache for resolving array index objects. Must have a 'get' method which\n        accepts a single argument: a string identifier associated with an array\n        index. If an array index associated with a provided identifier exists,\n        the 'get' method should return an object having the following\n        properties:\n\n        - data: the underlying index array.\n        - type: the index type. Must be either 'mask', 'bool', or 'int'.\n        - dtype: the data type of the underlying array.\n\n        If an array index is not associated with a provided identifier, the\n        'get' method should return `null`.\n\n        Default: `ArrayIndex`.\n\n    Returns\n    -------\n    fcn: Function\n        Function for converting an array to an object supporting fancy indexing.\n\n    Examples\n    --------\n    > var f = array2fancy.factory();\n    > var y = f( [ 1, 2, 3, 4 ] );\n    > y[ '1::2' ]\n    [ 2, 4 ]\n    > y[ '::-1' ]\n    [ 4, 3, 2, 1 ]","array2fancy.idx":"\narray2fancy.idx( x[, options] )\n    Wraps a provided array as an array index object.\n\n    For documentation and usage, see `ArrayIndex`.\n\n    Parameters\n    ----------\n    x: Array|TypedArray|Object\n        Input array.\n\n    options: Object (optional)\n        Function options.\n\n    options.persist: boolean (optional)\n        Boolean indicating whether to continue persisting an index object after\n        first usage. Default: false.\n\n    Returns\n    -------\n    out: ArrayIndex\n        ArrayIndex instance.\n\n    Examples\n    --------\n    > var idx = array2fancy.idx( [ 1, 2, 3, 4 ] );\n\n    See Also\n    --------\n    aslice, FancyArray","array2iterator":"\narray2iterator( src[, mapFcn[, thisArg]] )\n    Returns an iterator which iterates over the elements of an array-like\n    object.\n\n    When invoked, an input function is provided three arguments:\n\n    - value: iterated value.\n    - index: iterated value index.\n    - src: source array-like object.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an array's `@@iterator` method, regardless of whether this method is\n    defined. To convert an array to an implementation defined iterator, invoke\n    this method directly.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Array-like object from which to create the iterator.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = array2iterator( [ 1, 2, 3, 4 ] );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    iterator2array, circarray2iterator, array2iteratorRight, stridedarray2iterator\n","array2iteratorRight":"\narray2iteratorRight( src[, mapFcn[, thisArg]] )\n    Returns an iterator which iterates from right to left over the elements of\n    an array-like object.\n\n    When invoked, an input function is provided three arguments:\n\n    - value: iterated value.\n    - index: iterated value index.\n    - src: source array-like object.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an array's `@@iterator` method, regardless of whether this method is\n    defined. To convert an array to an implementation defined iterator, invoke\n    this method directly.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Array-like object from which to create the iterator.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = array2iteratorRight( [ 1, 2, 3, 4 ] );\n    > var v = it.next().value\n    4\n    > v = it.next().value\n    3\n\n    See Also\n    --------\n    iterator2array, array2iterator\n","ArrayBuffer":"\nArrayBuffer( size )\n    Returns an array buffer having a specified number of bytes.\n\n    Buffer contents are initialized to 0.\n\n    Parameters\n    ----------\n    size: integer\n        Number of bytes.\n\n    Returns\n    -------\n    out: ArrayBuffer\n        An array buffer.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 5 )\n    <ArrayBuffer>\n\n\nArrayBuffer.length\n    Number of input arguments the constructor accepts.\n\n    Examples\n    --------\n    > ArrayBuffer.length\n    1\n\n\nArrayBuffer.isView( arr )\n    Returns a boolean indicating if provided an array buffer view.\n\n    Parameters\n    ----------\n    arr: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an input argument is a buffer view.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 10 );\n    > ArrayBuffer.isView( arr )\n    true\n\n\nArrayBuffer.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the array buffer.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 5 );\n    > buf.byteLength\n    5\n\n\nArrayBuffer.prototype.slice( [start[, end]] )\n    Copies the bytes of an array buffer to a new array buffer.\n\n    Parameters\n    ----------\n    start: integer (optional)\n        Index at which to start copying buffer contents (inclusive). If\n        negative, the index is relative to the end of the buffer.\n\n    end: integer (optional)\n        Index at which to stop copying buffer contents (exclusive). If negative,\n        the index is relative to the end of the buffer.\n\n    Returns\n    -------\n    out: ArrayBuffer\n        A new array buffer whose contents have been copied from the calling\n        array buffer.\n\n    Examples\n    --------\n    > var b1 = new ArrayBuffer( 10 );\n    > var b2 = b1.slice( 2, 6 );\n    > var bool = ( b1 === b2 )\n    false\n    > b2.byteLength\n    4\n\n    See Also\n    --------\n    Buffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, SharedArrayBuffer, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","ArrayBuffer.length":"\nArrayBuffer.length\n    Number of input arguments the constructor accepts.\n\n    Examples\n    --------\n    > ArrayBuffer.length\n    1","ArrayBuffer.isView":"\nArrayBuffer.isView( arr )\n    Returns a boolean indicating if provided an array buffer view.\n\n    Parameters\n    ----------\n    arr: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an input argument is a buffer view.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 10 );\n    > ArrayBuffer.isView( arr )\n    true","ArrayBuffer.prototype.byteLength":"\nArrayBuffer.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the array buffer.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 5 );\n    > buf.byteLength\n    5","ArrayBuffer.prototype.slice":"\nArrayBuffer.prototype.slice( [start[, end]] )\n    Copies the bytes of an array buffer to a new array buffer.\n\n    Parameters\n    ----------\n    start: integer (optional)\n        Index at which to start copying buffer contents (inclusive). If\n        negative, the index is relative to the end of the buffer.\n\n    end: integer (optional)\n        Index at which to stop copying buffer contents (exclusive). If negative,\n        the index is relative to the end of the buffer.\n\n    Returns\n    -------\n    out: ArrayBuffer\n        A new array buffer whose contents have been copied from the calling\n        array buffer.\n\n    Examples\n    --------\n    > var b1 = new ArrayBuffer( 10 );\n    > var b2 = b1.slice( 2, 6 );\n    > var bool = ( b1 === b2 )\n    false\n    > b2.byteLength\n    4\n\n    See Also\n    --------\n    Buffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, SharedArrayBuffer, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","arraybuffer2buffer":"\narraybuffer2buffer( buf[, byteOffset[, length]] )\n    Allocates a buffer from an ArrayBuffer.\n\n    The behavior of this function varies across Node.js versions due to changes\n    in the underlying Node.js APIs:\n\n    - <3.0.0: the function copies ArrayBuffer bytes to a new Buffer instance.\n    - >=3.0.0 and <5.10.0: if provided a byte offset, the function copies\n      ArrayBuffer bytes to a new Buffer instance; otherwise, the function\n      returns a view of an ArrayBuffer without copying the underlying memory.\n    - <6.0.0: if provided an empty ArrayBuffer, the function returns an empty\n      Buffer which is not an ArrayBuffer view.\n    - >=6.0.0: the function returns a view of an ArrayBuffer without copying\n      the underlying memory.\n\n    Parameters\n    ----------\n    buf: ArrayBuffer\n        Input array buffer.\n\n    byteOffset: integer (optional)\n        Index offset specifying the location of the first byte.\n\n    length: integer (optional)\n        Number of bytes to expose from the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Buffer\n        Buffer instance.\n\n    Examples\n    --------\n    > var ab = new ArrayBuffer( 10 )\n    <ArrayBuffer>\n    > var buf = arraybuffer2buffer( ab )\n    <Buffer>\n    > var len = buf.length\n    10\n    > buf = arraybuffer2buffer( ab, 2, 6 )\n    <Buffer>\n    > len = buf.length\n    6\n\n    See Also\n    --------\n    Buffer, array2buffer, copyBuffer, string2buffer\n","arrayCtors":"\narrayCtors( dtype )\n    Returns an array constructor.\n\n    The function returns constructors for the following data types:\n\n    - float32: single-precision floating-point numbers.\n    - float64: double-precision floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - complex128: double-precision complex floating-point numbers.\n    - bool: boolean values.\n    - generic: values of any type.\n    - int16: signed 16-bit integers.\n    - int32: signed 32-bit integers.\n    - int8: signed 8-bit integers.\n    - uint16: unsigned 16-bit integers.\n    - uint32: unsigned 32-bit integers.\n    - uint8: unsigned 8-bit integers.\n    - uint8c: unsigned clamped 8-bit integers.\n\n    Parameters\n    ----------\n    dtype: string\n        Data type.\n\n    Returns\n    -------\n    out: Function|null\n        Constructor.\n\n    Examples\n    --------\n    > var ctor = arrayCtors( 'float64' )\n    <Function>\n    > ctor = arrayCtors( 'float' )\n    null\n\n    See Also\n    --------\n    typedarrayCtors\n","arrayDataType":"\narrayDataType( array )\n    Returns the data type of an array.\n\n    If provided an argument having an unknown or unsupported type, the function\n    returns `null`.\n\n    Parameters\n    ----------\n    array: any\n        Input value.\n\n    Returns\n    -------\n    out: string|null\n        Data type.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 10 );\n    > var dt = arrayDataType( arr )\n    'float64'\n    > dt = arrayDataType( 'beep' )\n    null\n\n    See Also\n    --------\n    arrayDataTypes\n","arrayDataTypes":"\narrayDataTypes( [kind] )\n    Returns a list of array data types.\n\n    When not provided a data type \"kind\", the function returns an array\n    containing the following data types:\n\n    - float32: single-precision floating-point numbers.\n    - float64: double-precision floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - complex128: double-precision complex floating-point numbers.\n    - bool: boolean values.\n    - generic: values of any type.\n    - int16: signed 16-bit integers.\n    - int32: signed 32-bit integers.\n    - int8: signed 8-bit integers.\n    - uint16: unsigned 16-bit integers.\n    - uint32: unsigned 32-bit integers.\n    - uint8: unsigned 8-bit integers.\n    - uint8c: unsigned clamped 8-bit integers.\n\n    The function supports the following data type \"kinds\":\n\n    - floating_point: floating-point data types.\n    - real_floating_point: real-valued floating-point data types.\n    - complex_floating_point: complex-valued floating-point data types.\n    - boolean: boolean data types.\n    - integer: integer data types.\n    - signed_integer: signed integer data types.\n    - unsigned_integer: unsigned integer data types.\n    - real: real-valued data types.\n    - numeric: numeric data types.\n    - typed: \"typed\" data types.\n    - all: all data types.\n\n    Additionally, the function supports extending the \"kinds\" listed above by\n    appending a '_and_generic' suffix to the kind name (e.g., real_and_generic).\n\n    Parameters\n    ----------\n    kind: string (optional)\n        Data type kind.\n\n    Returns\n    -------\n    out: Array<string>\n        List of array data types.\n\n    Examples\n    --------\n    > var out = arrayDataTypes()\n    [...]\n    > out = arrayDataTypes( 'floating_point' )\n    [...]\n    > out = arrayDataTypes( 'floating_point_and_generic' )\n    [...]\n\n    See Also\n    --------\n    typedarrayDataTypes, ndarrayDataTypes\n","ArrayIndex":"\nArrayIndex( x[, options] )\n    Wraps a provided array as an array index object.\n\n    Array index instances have no explicit functionality; however, they are used\n    by \"fancy\" arrays for element retrieval and assignment.\n\n    By default, an instance is invalidated and removed from an internal cache\n    immediately after a consumer resolves the underlying data associated with an\n    instance using the `get` static method. Immediate invalidation and cache\n    removal ensures that references to the underlying array are not the source\n    of memory leaks.\n\n    Because instances leverage an internal cache implementing the Singleton\n    pattern, one must be sure to use the same constructor as consumers. If one\n    uses a different constructor, the consumer will *not* be able to resolve the\n    original wrapped array, as the consumer will attempt to resolve an instance\n    in the wrong internal cache.\n\n    Because non-persisted instances are freed after first use, in order to avoid\n    holding onto memory and to allow garbage collection, one should avoid\n    scenarios in which an instance is never used.\n\n    Parameters\n    ----------\n    x: Array|TypedArray|Object\n        Input array.\n\n    options: Object (optional)\n        Function options.\n\n    options.persist: boolean (optional)\n        Boolean indicating whether to continue persisting an index object after\n        first usage. Default: false.\n\n    Returns\n    -------\n    out: ArrayIndex\n        ArrayIndex instance.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n\n\nArrayIndex.free( id )\n    Frees the instance associated with a provided identifier.\n\n    Parameters\n    ----------\n    id: string\n        Instance identifier.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an instance was successfully freed.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > ArrayIndex.free( idx.id )\n    <boolean>\n\n\nArrayIndex.get( id )\n    Returns the array associated with the instance having a provided identifier.\n\n    Parameters\n    ----------\n    id: string\n        Instance identifier.\n\n    Returns\n    -------\n    out: Object\n        Object containing array data.\n\n    out.data: Array|TypedArray|Object\n        The underlying array associated with the provided identifier.\n\n    out.type: string\n        The type of array index.\n\n    out.dtype: string\n        The data type of the underlying array.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > ArrayIndex.get( idx.id )\n    {...}\n\n\nArrayIndex.prototype.data\n    Read-only property returning the underlying index array.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Array data.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.data\n    [ 1, 2, 3, 4 ]\n\n\nArrayIndex.prototype.dtype\n    Read-only property returning the underlying data type of the index array.\n\n    Returns\n    -------\n    out: string\n        Array data type.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.dtype\n    'generic'\n\n\nArrayIndex.prototype.id\n    Read-only property returning the unique identifier associated with an\n    instance.\n\n    Returns\n    -------\n    out: string\n        String identifier.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.id\n    <string>\n\n\nArrayIndex.prototype.isCached\n    Read-only property returning a boolean indicating whether an array index is\n    actively cached.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an array index is actively cached.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.isCached\n    true\n\n\nArrayIndex.prototype.type\n    Read-only property returning the array index type.\n\n    Returns\n    -------\n    out: string\n        Array index type.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.type\n    <string>\n\n\nArrayIndex.prototype.toString()\n    Serializes an instance as a string.\n\n    Returns\n    -------\n    str: string\n        Serialized string.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.toString()\n    <string>\n\n\nArrayIndex.prototype.toJSON()\n    Serializes an instance as a JSON object.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.toJSON()\n    { 'type': 'ArrayIndex', 'data': [ 1, 2, 3, 4 ] }\n\n    See Also\n    --------\n    array2fancy\n","ArrayIndex.free":"\nArrayIndex.free( id )\n    Frees the instance associated with a provided identifier.\n\n    Parameters\n    ----------\n    id: string\n        Instance identifier.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an instance was successfully freed.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > ArrayIndex.free( idx.id )\n    <boolean>","ArrayIndex.get":"\nArrayIndex.get( id )\n    Returns the array associated with the instance having a provided identifier.\n\n    Parameters\n    ----------\n    id: string\n        Instance identifier.\n\n    Returns\n    -------\n    out: Object\n        Object containing array data.\n\n    out.data: Array|TypedArray|Object\n        The underlying array associated with the provided identifier.\n\n    out.type: string\n        The type of array index.\n\n    out.dtype: string\n        The data type of the underlying array.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > ArrayIndex.get( idx.id )\n    {...}","ArrayIndex.prototype.data":"\nArrayIndex.prototype.data\n    Read-only property returning the underlying index array.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Array data.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.data\n    [ 1, 2, 3, 4 ]","ArrayIndex.prototype.dtype":"\nArrayIndex.prototype.dtype\n    Read-only property returning the underlying data type of the index array.\n\n    Returns\n    -------\n    out: string\n        Array data type.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.dtype\n    'generic'","ArrayIndex.prototype.id":"\nArrayIndex.prototype.id\n    Read-only property returning the unique identifier associated with an\n    instance.\n\n    Returns\n    -------\n    out: string\n        String identifier.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.id\n    <string>","ArrayIndex.prototype.isCached":"\nArrayIndex.prototype.isCached\n    Read-only property returning a boolean indicating whether an array index is\n    actively cached.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an array index is actively cached.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.isCached\n    true","ArrayIndex.prototype.type":"\nArrayIndex.prototype.type\n    Read-only property returning the array index type.\n\n    Returns\n    -------\n    out: string\n        Array index type.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.type\n    <string>","ArrayIndex.prototype.toString":"\nArrayIndex.prototype.toString()\n    Serializes an instance as a string.\n\n    Returns\n    -------\n    str: string\n        Serialized string.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.toString()\n    <string>","ArrayIndex.prototype.toJSON":"\nArrayIndex.prototype.toJSON()\n    Serializes an instance as a JSON object.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.toJSON()\n    { 'type': 'ArrayIndex', 'data': [ 1, 2, 3, 4 ] }\n\n    See Also\n    --------\n    array2fancy","arrayMinDataType":"\narrayMinDataType( value )\n    Returns the minimum array data type of the closest \"kind\" necessary for\n    storing a provided scalar value.\n\n    The function does *not* provide precision guarantees for non-integer-valued\n    numbers. In other words, the function returns the smallest possible\n    floating-point (i.e., inexact) data type for storing numbers having\n    decimals.\n\n    Parameters\n    ----------\n    value: any\n        Scalar value.\n\n    Returns\n    -------\n    dt: string\n        Array data type.\n\n    Examples\n    --------\n    > var dt = arrayMinDataType( 3.141592653589793 )\n    'float32'\n    > dt = arrayMinDataType( 3 )\n    'uint8'\n    > dt = arrayMinDataType( -3 )\n    'int8'\n    > dt = arrayMinDataType( '-3' )\n    'generic'\n\n    See Also\n    --------\n    arrayDataTypes, arrayPromotionRules, arraySafeCasts\n","arrayMostlySafeCasts":"\narrayMostlySafeCasts( [dtype] )\n    Returns a list of array data types to which a provided array data type can\n    be safely cast and, for floating-point data types, can be downcast.\n\n    If not provided an array data type, the function returns a casting table.\n\n    If provided an unrecognized array data type, the function returns `null`.\n\n    Parameters\n    ----------\n    dtype: any (optional)\n        Array data type value.\n\n    Returns\n    -------\n    out: Object|Array<string>|null\n        Array data types to which a data type can be cast.\n\n    Examples\n    --------\n    > var out = arrayMostlySafeCasts( 'float32' )\n    <Array>\n\n    See Also\n    --------\n    convertArray, convertArraySame, arrayDataTypes, arraySafeCasts, arraySameKindCasts, ndarrayMostlySafeCasts\n","arrayNextDataType":"\narrayNextDataType( [dtype] )\n    Returns the next larger array data type of the same kind.\n\n    If not provided a data type, the function returns a table.\n\n    If a data type does not have a next larger data type or the next larger type\n    is not supported, the function returns `-1`.\n\n    If provided an unrecognized data type, the function returns `null`.\n\n    Parameters\n    ----------\n    dtype: string (optional)\n        Array data type.\n\n    Returns\n    -------\n    out: Object|string|integer|null\n        Next larger type(s).\n\n    Examples\n    --------\n    > var out = arrayNextDataType( 'float32' )\n    'float64'\n\n    See Also\n    --------\n    arrayDataType, arrayDataTypes\n","arrayPromotionRules":"\narrayPromotionRules( [dtype1, dtype2] )\n    Returns the array data type with the smallest size and closest \"kind\" to\n    which array data types can be safely cast.\n\n    If not provided data types, the function returns a type promotion table.\n\n    If a data type to which data types can be safely cast does *not* exist (or\n    is not supported), the function returns `-1`.\n\n    If provided an unrecognized data type, the function returns `null`.\n\n    Parameters\n    ----------\n    dtype1: any (optional)\n        Array data type.\n\n    dtype2: any (optional)\n        Array data type.\n\n    Returns\n    -------\n    out: Object|string|integer|null\n        Promotion rule(s).\n\n    Examples\n    --------\n    > var out = arrayPromotionRules( 'float32', 'int32' )\n    'float64'\n\n    See Also\n    --------\n    arrayDataTypes, arraySafeCasts, ndarrayPromotionRules\n","arraySafeCasts":"\narraySafeCasts( [dtype] )\n    Returns a list of array data types to which a provided array data type can\n    be safely cast.\n\n    If not provided an array data type, the function returns a casting table.\n\n    If provided an unrecognized array data type, the function returns `null`.\n\n    Parameters\n    ----------\n    dtype: any (optional)\n        Array data type.\n\n    Returns\n    -------\n    out: Object|Array<string>|null\n        Array data types to which a data type can be safely cast.\n\n    Examples\n    --------\n    > var out = arraySafeCasts( 'float32' )\n    <Array>\n\n    See Also\n    --------\n    convertArray, convertArraySame, arrayDataTypes, arrayMostlySafeCasts, arraySameKindCasts, ndarraySafeCasts\n","arraySameKindCasts":"\narraySameKindCasts( [dtype] )\n    Returns a list of array data types to which a provided array data type can\n    be safely cast or cast within the same \"kind\".\n\n    If not provided an array data type, the function returns a casting table.\n\n    If provided an unrecognized array data type, the function returns `null`.\n\n    Parameters\n    ----------\n    dtype: any (optional)\n        Array data type.\n\n    Returns\n    -------\n    out: Object|Array<string>|null\n        Array data types to which a data type can be safely cast or cast within\n        the same \"kind\".\n\n    Examples\n    --------\n    > var out = arraySameKindCasts( 'float32' )\n    <Array>\n\n    See Also\n    --------\n    convertArray, convertArraySame, arrayDataTypes, arraySafeCasts, ndarraySameKindCasts\n","arrayShape":"\narrayShape( arr )\n    Determines array dimensions.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject\n        Input array.\n\n    Returns\n    -------\n    out: Array\n        Array shape.\n\n    Examples\n    --------\n    > var out = arrayShape( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n    [ 2, 3 ]\n\n    See Also\n    --------\n    ndarray\n","arrayStream":"\narrayStream( src[, options] )\n    Creates a readable stream from an array-like object.\n\n    In object mode, `null` is a reserved value. If an array contains `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or filter `null` values\n    prior to invocation.\n\n    In binary mode, if an array contains `undefined` values, the stream will\n    emit an error. Consider providing a custom serialization function or\n    filtering `undefined` values prior to invocation.\n\n    If a serialization function fails to return a string or Buffer, the stream\n    emits an error.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Source value.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing the stream.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize streamed\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    options.dir: integer (optional)\n        Iteration direction. If set to `-1`, a stream iterates over elements\n        from right-to-left. Default: 1.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var s = arrayStream( [ 1, 2, 3 ] );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\narrayStream.factory( [options] )\n    Returns a function for creating readable streams from array-like objects.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing streaming.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize streamed\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    options.dir: integer (optional)\n        Iteration direction. If set to `-1`, a stream iterates over elements\n        from right-to-left. Default: 1.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = arrayStream.factory( opts );\n\n\narrayStream.objectMode( src[, options] )\n    Returns an \"objectMode\" readable stream from an array-like object.\n\n    In object mode, `null` is a reserved value. If an array contains `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or filter `null` values\n    prior to invocation.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Source value.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before pausing streaming.\n\n    options.dir: integer (optional)\n        Iteration direction. If set to `-1`, a stream iterates over elements\n        from right-to-left. Default: 1.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var s = arrayStream.objectMode( [ 1, 2, 3 ] );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    circularArrayStream, iteratorStream, stridedArrayStream\n","arrayStream.factory":"\narrayStream.factory( [options] )\n    Returns a function for creating readable streams from array-like objects.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing streaming.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize streamed\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    options.dir: integer (optional)\n        Iteration direction. If set to `-1`, a stream iterates over elements\n        from right-to-left. Default: 1.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = arrayStream.factory( opts );","arrayStream.objectMode":"\narrayStream.objectMode( src[, options] )\n    Returns an \"objectMode\" readable stream from an array-like object.\n\n    In object mode, `null` is a reserved value. If an array contains `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or filter `null` values\n    prior to invocation.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Source value.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before pausing streaming.\n\n    options.dir: integer (optional)\n        Iteration direction. If set to `-1`, a stream iterates over elements\n        from right-to-left. Default: 1.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var s = arrayStream.objectMode( [ 1, 2, 3 ] );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    circularArrayStream, iteratorStream, stridedArrayStream","arrayview2iterator":"\narrayview2iterator( src[, begin[, end]][, mapFcn[, thisArg]] )\n    Returns an iterator which iterates over the elements of an array-like object\n    view.\n\n    When invoked, an input function is provided four arguments:\n\n    - value: iterated value.\n    - index: iterated value index.\n    - n: iteration count (zero-based).\n    - src: source array-like object.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an array's `@@iterator` method, regardless of whether this method is\n    defined. To convert an array to an implementation defined iterator, invoke\n    this method directly.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Array-like object from which to create the iterator.\n\n    begin: integer (optional)\n        Starting index (inclusive). When negative, determined relative to the\n        last element. Default: 0.\n\n    end: integer (optional)\n        Ending index (non-inclusive). When negative, determined relative to the\n        last element. Default: src.length.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = arrayview2iterator( [ 1, 2, 3, 4 ], 1, 3 );\n    > var v = it.next().value\n    2\n    > v = it.next().value\n    3\n\n    See Also\n    --------\n    iterator2array, array2iterator, stridedarray2iterator, arrayview2iteratorRight\n","arrayview2iteratorRight":"\narrayview2iteratorRight( src[, begin[, end]][, mapFcn[, thisArg]] )\n    Returns an iterator which iterates from right to left over the elements of\n    an array-like object view.\n\n    When invoked, an input function is provided four arguments:\n\n    - value: iterated value.\n    - index: iterated value index.\n    - n: iteration count (zero-based).\n    - src: source array-like object.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an array's `@@iterator` method, regardless of whether this method is\n    defined. To convert an array to an implementation defined iterator, invoke\n    this method directly.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Array-like object from which to create the iterator.\n\n    begin: integer (optional)\n        Starting index (inclusive). When negative, determined relative to the\n        last element. Default: 0.\n\n    end: integer (optional)\n        Ending index (non-inclusive). When negative, determined relative to the\n        last element. Default: src.length.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = arrayview2iteratorRight( [ 1, 2, 3, 4 ], 1, 3 );\n    > var v = it.next().value\n    3\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    iterator2array, array2iteratorRight, stridedarray2iterator, arrayview2iterator\n","aslice":"\naslice( x[, start[, end]] )\n    Returns a shallow copy of a portion of an array.\n\n    If provided an array-like object having a `slice` method, the function\n    defers execution to that method and assumes that the method has the\n    following signature:\n\n      x.slice( start, end )\n\n    If provided an array-like object without a `slice` method, the function\n    copies input array elements to a new generic array.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    start: integer (optional)\n        Starting index (inclusive). Default: 0.\n\n    end: integer (optional)\n        Ending index (exclusive). Default: x.length.\n\n    Returns\n    -------\n    out: Array|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var out = aslice( [ 1, 2, 3, 4 ] )\n    [ 1, 2, 3, 4 ]\n    > out = aslice( [ 1, 2, 3, 4 ], 1 )\n    [ 2, 3, 4 ]\n    > out = aslice( [ 1, 2, 3, 4 ], 1, 3 )\n    [ 2, 3 ]\n\n    See Also\n    --------\n    atake\n","AsyncIteratorSymbol":"\nAsyncIteratorSymbol\n    Async iterator symbol.\n\n    This symbol specifies the default async iterator for an object.\n\n    The symbol is only supported in ES2018+ environments. For non-supporting\n    environments, the value is `null`.\n\n    Examples\n    --------\n    > var s = AsyncIteratorSymbol\n\n    See Also\n    --------\n    Symbol, IteratorSymbol\n","atake":"\natake( x, indices[, options] )\n    Takes elements from an array.\n\n    If `indices` is an empty array, the function returns an empty array.\n\n    Parameters\n    ----------\n    x: Array|TypedArray|Object\n        Input array.\n\n    indices: ArrayLikeObject<integer>\n        List of element indices.\n\n    options: Object (optional)\n        Function options.\n\n    options.mode: string (optional)\n        Specifies how to handle an index outside the interval [0, max], where\n        `max` is the maximum possible array index. If equal to 'throw', the\n        function throws an error. If equal to 'normalize', the function throws\n        an error if provided an out-of-bounds normalized index. If equal to\n        'wrap', the function wraps around an index using modulo arithmetic. If\n        equal to 'clamp', the function sets an index to either 0 (minimum index)\n        or the maximum index. Default: 'normalize'.\n\n    Returns\n    -------\n    out: Array|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = [ 1, 2, 3, 4 ];\n    > var y = atake( x, [ 1, 3 ] )\n    [ 2, 4 ]\n\n    See Also\n    --------\n    aput, aslice\n","azeros":"\nazeros( length[, dtype] )\n    Returns a zero-filled array having a specified length.\n\n    The function supports the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754).\n    - float32: single-precision floating-point numbers (IEEE 754).\n    - complex128: double-precision complex floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n    - generic: generic JavaScript values.\n\n    The default array data type is `float64`.\n\n    Parameters\n    ----------\n    length: integer\n        Array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = azeros( 2 )\n    <Float64Array>[ 0.0, 0.0 ]\n    > arr = azeros( 2, 'float32' )\n    <Float32Array>[ 0.0, 0.0 ]\n\n    See Also\n    --------\n    aempty, afull, anans, aones, azerosLike, ndzeros\n","azerosLike":"\nazerosLike( x[, dtype] )\n    Returns a zero-filled array having the same length and data type as a\n    provided input array.\n\n    The function supports the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754).\n    - float32: single-precision floating-point numbers (IEEE 754).\n    - complex128: double-precision complex floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n    - generic: generic JavaScript values.\n\n    Parameters\n    ----------\n    x: TypedArray|Array\n        Input array.\n\n    dtype: string (optional)\n        Data type. If not provided, the output array data type is inferred from\n        the input array.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var x = new Float64Array( 2 );\n    > var y = azerosLike( x )\n    <Float64Array>[ 0.0, 0.0 ]\n    > y = azerosLike( x, 'float32' )\n    <Float32Array>[ 0.0, 0.0 ]\n\n    See Also\n    --------\n    aemptyLike, afullLike, anansLike, aonesLike, azeros, ndzerosLike\n","azeroTo":"\nazeroTo( n[, dtype] )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from zero.\n\n    The function supports the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754).\n    - float32: single-precision floating-point numbers (IEEE 754).\n    - complex128: double-precision complex floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n    - generic: generic JavaScript values.\n\n    The default array data type is `float64`.\n\n    If `n` is equal to zero, the function returns an empty array.\n\n    Parameters\n    ----------\n    n: integer\n        Number of elements.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = azeroTo( 2 )\n    <Float64Array>[ 0.0, 1.0 ]\n    > arr = azeroTo( 2, 'float32' )\n    <Float32Array>[ 0.0, 1.0 ]\n\n    See Also\n    --------\n    aempty, afull, aoneTo, azeroToLike, azeros\n","azeroToLike":"\nazeroToLike( x[, dtype] )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from zero and having the same length and data type as a provided\n    input array.\n\n    The function supports the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754).\n    - float32: single-precision floating-point numbers (IEEE 754).\n    - complex128: double-precision complex floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n    - generic: generic JavaScript values.\n\n    Parameters\n    ----------\n    x: TypedArray|Array\n        Input array.\n\n    dtype: string (optional)\n        Data type. If not provided, the output array data type is inferred from\n        the input array.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = azeroToLike( [ 0, 0 ] )\n    [ 0, 1 ]\n    > arr = azeroToLike( [ 0, 0 ], 'float32' )\n    <Float32Array>[ 0.0, 1.0 ]\n\n    See Also\n    --------\n    aemptyLike, afullLike, anansLike, aoneToLike, aonesLike, azeroTo, azerosLike\n","bartlettTest":"\nbartlettTest( ...x[, options] )\n    Computes Bartlett’s test for equal variances.\n\n    Parameters\n    ----------\n    x: ...Array\n        Measured values.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.groups: Array (optional)\n        Array of group indicators.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.method: string\n        Name of test.\n\n    out.df: Object\n        Degrees of freedom.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    // Data from Hollander & Wolfe (1973), p. 116:\n    > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n    > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n    > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n    > var out = bartlettTest( x, y, z )\n\n    > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n    ...     3.8, 2.7, 4.0, 2.4,\n    ...     2.8, 3.4, 3.7, 2.2, 2.0\n    ... ];\n    > var groups = [\n    ...     'a', 'a', 'a', 'a', 'a',\n    ...     'b', 'b', 'b', 'b',\n    ...     'c', 'c', 'c', 'c', 'c'\n    ... ];\n    > out = bartlettTest( arr, { 'groups': groups } )\n\n    See Also\n    --------\n    vartest, leveneTest\n","base.abs":"\nbase.abs( x )\n    Computes the absolute value of a double-precision floating-point number `x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Absolute value.\n\n    Examples\n    --------\n    > var y = base.abs( -1.0 )\n    1.0\n    > y = base.abs( 2.0 )\n    2.0\n    > y = base.abs( 0.0 )\n    0.0\n    > y = base.abs( -0.0 )\n    0.0\n    > y = base.abs( NaN )\n    NaN\n\n    See Also\n    --------\n    base.abs2, base.absf, base.labs\n","base.abs2":"\nbase.abs2( x )\n    Computes the squared absolute value of a double-precision floating-point\n    `x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Squared absolute value.\n\n    Examples\n    --------\n    > var y = base.abs2( -1.0 )\n    1.0\n    > y = base.abs2( 2.0 )\n    4.0\n    > y = base.abs2( 0.0 )\n    0.0\n    > y = base.abs2( -0.0 )\n    0.0\n    > y = base.abs2( NaN )\n    NaN\n\n    See Also\n    --------\n    base.abs, base.abs2f\n","base.abs2f":"\nbase.abs2f( x )\n    Computes the squared absolute value of a single-precision floating-point\n    `x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Squared absolute value.\n\n    Examples\n    --------\n    > var y = base.abs2f( -1.0 )\n    1.0\n    > y = base.abs2f( 2.0 )\n    4.0\n    > y = base.abs2f( 0.0 )\n    0.0\n    > y = base.abs2f( -0.0 )\n    0.0\n    > y = base.abs2f( NaN )\n    NaN\n\n    See Also\n    --------\n    base.abs2, base.absf\n","base.absdiff":"\nbase.absdiff( x, y )\n    Computes the absolute difference.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Absolute difference.\n\n    Examples\n    --------\n    > var d = base.absdiff( 2.0, 5.0 )\n    3.0\n    > d = base.absdiff( -1.0, 3.14 )\n    ~4.14\n    > d = base.absdiff( 10.1, -2.05 )\n    ~12.15\n    > d = base.absdiff( -0.0, 0.0 )\n    +0.0\n    > d = base.absdiff( NaN, 5.0 )\n    NaN\n    > d = base.absdiff( PINF, NINF )\n    Infinity\n    > d = base.absdiff( PINF, PINF )\n    NaN\n\n    See Also\n    --------\n    base.reldiff, base.epsdiff\n","base.absf":"\nbase.absf( x )\n    Computes the absolute value of a single-precision floating-point number `x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Absolute value.\n\n    Examples\n    --------\n    > var y = base.absf( -1.0 )\n    1.0\n    > y = base.absf( 2.0 )\n    2.0\n    > y = base.absf( 0.0 )\n    0.0\n    > y = base.absf( -0.0 )\n    0.0\n    > y = base.absf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.abs, base.abs2f, base.labs\n","base.acartesianPower":"\nbase.acartesianPower( x, n )\n    Returns the Cartesian power.\n\n    If provided an empty array, the function returns an empty array.\n\n    If `n` is less than or equal to zero, the function returns an empty array.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    n: integer\n        Power.\n\n    Returns\n    -------\n    out: Array<Array>\n        Cartesian product.\n\n    Examples\n    --------\n    > var x = [ 1, 2 ];\n    > var out = base.acartesianPower( x, 2 )\n    [ [ 1, 1 ], [ 1, 2 ], [ 2, 1 ], [ 2, 2 ] ]\n\n    See Also\n    --------\n    acartesianPower, base.acartesianProduct, base.acartesianSquare\n","base.acartesianProduct":"\nbase.acartesianProduct( x1, x2 )\n    Returns the Cartesian product.\n\n    If provided one or more empty arrays, the function returns an empty array.\n\n    Parameters\n    ----------\n    x1: ArrayLikeObject\n        First input array.\n\n    x2: ArrayLikeObject\n        Second input array.\n\n    Returns\n    -------\n    out: Array<Array>\n        Cartesian product.\n\n    Examples\n    --------\n    > var x1 = [ 1, 2 ];\n    > var x2 = [ 3, 4 ];\n    > var out = base.acartesianProduct( x1, x2 )\n    [ [ 1, 3 ], [ 1, 4 ], [ 2, 3 ], [ 2, 4 ] ]\n\n    See Also\n    --------\n    acartesianProduct, base.acartesianPower, base.acartesianSquare\n","base.acartesianSquare":"\nbase.acartesianSquare( x )\n    Returns the Cartesian square.\n\n    If provided an empty array, the function returns an empty array.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    Returns\n    -------\n    out: Array<Array>\n        Cartesian product.\n\n    Examples\n    --------\n    > var x = [ 1, 2 ];\n    > var out = base.acartesianSquare( x )\n    [ [ 1, 1 ], [ 1, 2 ], [ 2, 1 ], [ 2, 2 ] ]\n\n    See Also\n    --------\n    acartesianSquare, base.acartesianPower, base.acartesianProduct\n","base.acos":"\nbase.acos( x )\n    Compute the arccosine of a double-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arccosine (in radians).\n\n    Examples\n    --------\n    > var y = base.acos( 1.0 )\n    0.0\n    > y = base.acos( 0.707 )\n    ~0.7855\n    > y = base.acos( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acosh, base.asin, base.atan\n","base.acosd":"\nbase.acosd( x )\n    Computes the arccosine (in degrees) of a double-precision floating-point \n    number.\n\n    If `|x| > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arccosine (in degrees).\n\n    Examples\n    --------\n    > var y = base.acosd( 0.0 )\n    90.0\n    > y = base.acosd( PI/6.0 )\n    ~58.43\n    > y = base.acosd( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acos, base.acosh, base.asind, base.atand\n","base.acosf":"\nbase.acosf( x )\n    Computes the arccosine of a single-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arccosine (in radians).\n\n    Examples\n    --------\n    > var y = base.acosf( 1.0 )\n    0.0\n    > y = base.acosf( 0.707 )\n    ~0.7855\n    > y = base.acosf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acos, base.acosh, base.asinf, base.atanf\n","base.acosh":"\nbase.acosh( x )\n    Computes the hyperbolic arccosine of a double-precision floating-point\n    number.\n\n    If `x < 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Hyperbolic arccosine.\n\n    Examples\n    --------\n    > var y = base.acosh( 1.0 )\n    0.0\n    > y = base.acosh( 2.0 )\n    ~1.317\n    > y = base.acosh( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acos, base.asinh, base.atanh\n","base.acot":"\nbase.acot( x )\n    Computes the inverse cotangent of a double-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Inverse cotangent (in radians).\n\n    Examples\n    --------\n    > var y = base.acot( 2.0 )\n    ~0.4636\n    > y = base.acot( 0.0 )\n    ~1.5708\n    > y = base.acot( 0.5 )\n    ~1.1071\n    > y = base.acot( 1.0 )\n    ~0.7854\n    > y = base.acot( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acoth, base.atan, base.cot\n","base.acotd":"\nbase.acotd( x )\n    Computes the arccotangent (in degrees) of a double-precision floating-point\n    number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arccotangent (in degrees).\n\n    Examples\n    --------\n    > var y = base.acotd( 0.0 )\n    90.0\n    > y = base.acotd( PI/6.0 )\n    ~62.36\n    > y = base.acotd( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acot, base.acoth, base.atand, base.cotd\n","base.acotf":"\nbase.acotf( x )\n    Computes the inverse cotangent of a single-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Inverse cotangent (in radians).\n\n    Examples\n    --------\n    > var y = base.acotf( 2.0 )\n    ~0.4636\n    > y = base.acotf( 0.0 )\n    ~1.5708\n    > y = base.acotf( 0.5 )\n    ~1.1071\n    > y = base.acotf( 1.0 )\n    ~0.7854\n    > y = base.acotf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acot, base.acoth, base.atanf\n","base.acoth":"\nbase.acoth( x )\n    Computes the inverse hyperbolic cotangent of a double-precision floating-\n    point number.\n\n    The domain of the inverse hyperbolic cotangent is the union of the intervals\n    (-inf,-1] and [1,inf).\n\n    If provided a value on the open interval (-1,1), the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Inverse hyperbolic cotangent.\n\n    Examples\n    --------\n    > var y = base.acoth( 2.0 )\n    ~0.5493\n    > y = base.acoth( 0.0 )\n    NaN\n    > y = base.acoth( 0.5 )\n    NaN\n    > y = base.acoth( 1.0 )\n    Infinity\n    > y = base.acoth( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acosh, base.acot, base.asinh, base.atanh\n","base.acovercos":"\nbase.acovercos( x )\n    Computes the inverse coversed cosine.\n\n    The inverse coversed cosine is defined as `asin(1+x)`.\n\n    If `x < -2`, `x > 0`, or `x` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Inverse coversed cosine.\n\n    Examples\n    --------\n    > var y = base.acovercos( -1.5 )\n    ~-0.5236\n    > y = base.acovercos( -0.0 )\n    ~1.5708\n\n    See Also\n    --------\n    base.acoversin, base.avercos, base.covercos, base.vercos\n","base.acoversin":"\nbase.acoversin( x )\n    Computes the inverse coversed sine.\n\n    The inverse coversed sine is defined as `asin(1-x)`.\n\n    If `x < 0`, `x > 2`, or `x` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Inverse coversed sine.\n\n    Examples\n    --------\n    > var y = base.acoversin( 1.5 )\n    ~-0.5236\n    > y = base.acoversin( 0.0 )\n    ~1.5708\n\n    See Also\n    --------\n    base.acovercos, base.aversin, base.coversin, base.versin\n","base.acsc":"\nbase.acsc( x )\n    Computes the arccosecant of a number.\n\n    If `|x| < 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arccosecant (in radians).\n\n    Examples\n    --------\n    > var y = base.acsc( 1.0 )\n    ~1.57\n    > y = base.acsc( PI )\n    ~0.32\n    > y = base.acsc( -PI )\n    ~-0.32\n    > y = base.acsc( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acot, base.acsch, base.asec, base.asin, base.csc\n","base.acscd":"\nbase.acscd( x )\n    Computes the arccosecant of (in degrees) a double-precision floating-point\n    number.\n\n    If `x` does not satisy `x >= 1` or `x <= -1`, the function returns NaN.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arccosecant (in degrees).\n\n    Examples\n    --------\n    > var y = base.acscd( 0.0 )\n    NaN\n    > y = base.acscd( PI/6.0 )\n    NaN\n    > y = base.acscd( 1 )\n    90.0\n    > y = base.acscd( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acsc, base.acsch, base.asecd, base.asind, base.cscd\n","base.acscdf":"\nbase.acscdf( x )\n    Computes the arccosecant (in degrees) of a single-precision floating-point\n    number.\n\n    If `x` does not satisy `x >= 1` or `x <= -1`, the function returns NaN.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arccosecant (in degrees).\n\n    Examples\n    --------\n    > var y = base.acscdf( 0.0 )\n    NaN\n    > y = base.acscdf( 3.1415927410125732 / 6.0 )\n    NaN\n    > y = base.acscdf( 1.0 )\n    90.0\n    > y = base.acscdf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acsc, base.acsch, base.asecdf, base.asindf\n","base.acscf":"\nbase.acscf( x )\n    Computes the arccosecant of a single-precision floating-point number.\n\n    If `|x| < 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arccosecant (in radians).\n\n    Examples\n    --------\n    > var y = base.acscf( 1.0 )\n    ~1.57\n    > y = base.acscf( 3.141592653589793 )\n    ~0.32\n    > y = base.acscf( -3.141592653589793 )\n    ~-0.32\n    > y = base.acscf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acsc, base.acsch, base.asecf, base.asinf\n","base.acsch":"\nbase.acsch( x )\n    Computes the hyperbolic arccosecant of a number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Hyperbolic arccosecant.\n\n    Examples\n    --------\n    > var y = base.acsch( 0.0 )\n    Infinity\n    > y = base.acsch( -1.0 )\n    ~-0.881\n    > y = base.acsch( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acoth, base.acsc, base.asech, base.asinh, base.csc, base.csch\n","base.add":"\nbase.add( x, y )\n    Computes the sum of two double-precision floating-point numbers `x` and `y`.\n\n    Parameters\n    ----------\n    x: number\n        First input value.\n\n    y: number\n        Second input value.\n\n    Returns\n    -------\n    z: number\n        Sum.\n\n    Examples\n    --------\n    > var v = base.add( -1.0, 5.0 )\n    4.0\n    > v = base.add( 2.0, 5.0 )\n    7.0\n    > v = base.add( 0.0, 5.0 )\n    5.0\n    > v = base.add( -0.0, 0.0 )\n    0.0\n    > v = base.add( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.div, base.mul, base.sub\n","base.add3":"\nbase.add3( x, y, z )\n    Computes the sum of three double-precision floating-point numbers.\n\n    Parameters\n    ----------\n    x: number\n        First input value.\n\n    y: number\n        Second input value.\n\n    z: number\n        Third input value.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    > var v = base.add3( -1.0, 5.0, 2.0 )\n    6.0\n    > v = base.add3( 2.0, 5.0, 2.0 )\n    9.0\n    > v = base.add3( 0.0, 5.0, 2.0 )\n    7.0\n    > v = base.add3( -0.0, 0.0, -0.0 )\n    0.0\n    > v = base.add3( NaN, NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.add\n","base.add4":"\nbase.add4( x, y, z, w )\n    Computes the sum of four double-precision floating-point numbers.\n\n    Parameters\n    ----------\n    x: number\n        First input value.\n\n    y: number\n        Second input value.\n\n    z: number\n        Third input value.\n\n    w: number\n        Fourth input value.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    > var v = base.add4( -1.0, 5.0, 2.0, -3.0 )\n    3.0\n    > v = base.add4( 2.0, 5.0, 2.0, -3.0 )\n    6.0\n    > v = base.add4( 0.0, 5.0, 2.0, -3.0 )\n    4.0\n    > v = base.add4( -0.0, 0.0, -0.0, -0.0 )\n    0.0\n    > v = base.add4( NaN, NaN, NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.add\n","base.add5":"\nbase.add5( x, y, z, w, u )\n    Computes the sum of five double-precision floating-point numbers.\n\n    Parameters\n    ----------\n    x: number\n        First input value.\n\n    y: number\n        Second input value.\n\n    z: number\n        Third input value.\n\n    w: number\n        Fourth input value.\n\n    u: number\n        Fifth input value.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    > var v = base.add5( -1.0, 5.0, 2.0, -3.0, 4.0 )\n    7.0\n    > v = base.add5( 2.0, 5.0, 2.0, -3.0, 4.0 )\n    10.0\n    > v = base.add5( 0.0, 5.0, 2.0, -3.0, 4.0 )\n    8.0\n    > v = base.add5( -0.0, 0.0, -0.0, -0.0, -0.0 )\n    0.0\n    > v = base.add5( NaN, NaN, NaN, NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.add\n","base.addf":"\nbase.addf( x, y )\n    Computes the sum of two single-precision floating-point numbers `x` and `y`.\n\n    Parameters\n    ----------\n    x: number\n        First input value.\n\n    y: number\n        Second input value.\n\n    Returns\n    -------\n    z: number\n        Sum.\n\n    Examples\n    --------\n    > var v = base.addf( -1.0, 5.0 )\n    4.0\n    > v = base.addf( 2.0, 5.0 )\n    7.0\n    > v = base.addf( 0.0, 5.0 )\n    5.0\n    > v = base.addf( -0.0, 0.0 )\n    0.0\n    > v = base.addf( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.add, base.divf, base.mulf, base.subf\n","base.afilled":"\nbase.afilled( value, len )\n    Returns a filled \"generic\" array.\n\n    Parameters\n    ----------\n    value: any\n        Fill value.\n\n    len: integer\n        Array length.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.afilled( 0.0, 3 )\n    [ 0.0, 0.0, 0.0 ]\n\n","base.afilled2d":"\nbase.afilled2d( value, shape )\n    Returns a filled two-dimensional nested array.\n\n    Parameters\n    ----------\n    value: any\n        Fill value.\n\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.afilled2d( 0.0, [ 1, 3 ] )\n    [ [ 0.0, 0.0, 0.0 ] ]\n\n","base.afilled2dBy":"\nbase.afilled2dBy( shape, clbk[, thisArg] )\n    Returns a filled two-dimensional nested array according to a provided\n    callback function.\n\n    The callback function is provided one argument:\n\n    - indices: current array element indices.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function clbk() { return 1.0; };\n    > var out = base.afilled2dBy( [ 1, 3 ], clbk )\n    [ [ 1.0, 1.0, 1.0 ] ]\n\n    See Also\n    --------\n    base.afilled2d\n","base.afilled3d":"\nbase.afilled3d( value, shape )\n    Returns a filled three-dimensional nested array.\n\n    Parameters\n    ----------\n    value: any\n        Fill value.\n\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.afilled3d( 0.0, [ 1, 1, 3 ] )\n    [ [ [ 0.0, 0.0, 0.0 ] ] ]\n\n","base.afilled3dBy":"\nbase.afilled3dBy( shape, clbk[, thisArg] )\n    Returns a filled three-dimensional nested array according to a provided\n    callback function.\n\n    The callback function is provided one argument:\n\n    - indices: current array element indices.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function clbk() { return 1.0; };\n    > var out = base.afilled3dBy( [ 1, 1, 3 ], clbk )\n    [ [ [ 1.0, 1.0, 1.0 ] ] ]\n\n    See Also\n    --------\n    base.afilled3d\n","base.afilled4d":"\nbase.afilled4d( value, shape )\n    Returns a filled four-dimensional nested array.\n\n    Parameters\n    ----------\n    value: any\n        Fill value.\n\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.afilled4d( 0.0, [ 1, 1, 1, 3 ] )\n    [ [ [ [ 0.0, 0.0, 0.0 ] ] ] ]\n\n","base.afilled4dBy":"\nbase.afilled4dBy( shape, clbk[, thisArg] )\n    Returns a filled four-dimensional nested array according to a provided\n    callback function.\n\n    The callback function is provided one argument:\n\n    - indices: current array element indices.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function clbk() { return 1.0; };\n    > var out = base.afilled4dBy( [ 1, 1, 1, 3 ], clbk )\n    [ [ [ [ 1.0, 1.0, 1.0 ] ] ] ]\n\n    See Also\n    --------\n    base.afilled4d\n","base.afilled5d":"\nbase.afilled5d( value, shape )\n    Returns a filled five-dimensional nested array.\n\n    Parameters\n    ----------\n    value: any\n        Fill value.\n\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.afilled5d( 0.0, [ 1, 1, 1, 1, 3 ] )\n    [ [ [ [ [ 0.0, 0.0, 0.0 ] ] ] ] ]\n\n","base.afilled5dBy":"\nbase.afilled5dBy( shape, clbk[, thisArg] )\n    Returns a filled five-dimensional nested array according to a provided\n    callback function.\n\n    The callback function is provided one argument:\n\n    - indices: current array element indices.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function clbk() { return 1.0; };\n    > var out = base.afilled5dBy( [ 1, 1, 1, 1, 3 ], clbk )\n    [ [ [ [ [ 1.0, 1.0, 1.0 ] ] ] ] ]\n\n    See Also\n    --------\n    base.afilled5d\n","base.afilledBy":"\nbase.afilledBy( len, clbk[, thisArg] )\n    Returns a filled \"generic\" array according to a provided callback function.\n\n    Parameters\n    ----------\n    len: integer\n        Array length.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function clbk() { return 1.0; };\n    > var out = base.afilledBy( 3, clbk )\n    [ 1.0, 1.0, 1.0 ]\n\n    See Also\n    --------\n    base.afilled\n","base.afillednd":"\nbase.afillednd( value, shape )\n    Returns a filled n-dimensional nested array.\n\n    Parameters\n    ----------\n    value: any\n        Fill value.\n\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.afillednd( 0.0, [ 1, 3 ] )\n    [ [ 0.0, 0.0, 0.0 ] ]\n\n","base.afilledndBy":"\nbase.afilledndBy( shape, clbk[, thisArg] )\n    Returns a filled n-dimensional nested array according to a callback\n    function.\n\n    The callback function is provided one argument:\n\n    - indices: current array element indices.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function clbk() { return 1.0; };\n    > var out = base.afilledndBy( [ 1, 3 ], clbk )\n    [ [ 1.0, 1.0, 1.0 ] ]\n\n    See Also\n    --------\n    base.afillednd\n","base.afilter":"\nbase.afilter( x, predicate[, thisArg] )\n    Returns a shallow copy of an array containing only those elements which pass\n    a test implemented by a predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the input array.\n\n    If provided an array-like object having a `filter` method , the function\n    defers execution to that method and assumes that the method has the\n    following signature:\n\n      x.filter( predicate, thisArg )\n\n    If provided an array-like object without a `filter` method, the function\n    performs a linear scan and always returns a generic array.\n\n    Parameters\n    ----------\n    x: Array|TypedArray|Object\n        Input array.\n\n    predicate: Function\n        Predicate function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Output array.\n\n    Examples\n    --------\n    > function f( v ) { return ( v > 0 ); };\n    > var x = [ 1, -2, -3, 4 ];\n    > var out = base.afilter( x, f )\n    [ 1, 4 ]\n\n","base.afirst":"\nbase.afirst( arr )\n    Returns the first element of an array-like object.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject\n        Input array.\n\n    Returns\n    -------\n    out: any\n        First element.\n\n    Examples\n    --------\n    > var out = base.afirst( [ 1, 2, 3 ] )\n    1\n\n","base.aflatten":"\nbase.aflatten( x, shape, colexicographic )\n    Flattens an n-dimensional nested array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    Returns\n    -------\n    out: Array\n        Flattened array.\n\n    Examples\n    --------\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = base.aflatten( x, [ 2, 2 ], false )\n    [ 1, 2, 3, 4 ]\n    > out = base.aflatten( x, [ 2, 2 ], true )\n    [ 1, 3, 2, 4 ]\n\n\nbase.aflatten.assign( x, shape, colexicographic, out, stride, offset )\n    Flattens an n-dimensional nested array and assigns elements to a provided\n    output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten.assign( x, [ 2, 2 ], false, out, 1, 0 )\n    [ 1, 2, 3, 4 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten.assign( x, [ 2, 2 ], true, out, 1, 0 );\n    > out\n    [ 1, 3, 2, 4 ]\n\n    See Also\n    --------\n    base.aflattenBy\n","base.aflatten.assign":"\nbase.aflatten.assign( x, shape, colexicographic, out, stride, offset )\n    Flattens an n-dimensional nested array and assigns elements to a provided\n    output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten.assign( x, [ 2, 2 ], false, out, 1, 0 )\n    [ 1, 2, 3, 4 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten.assign( x, [ 2, 2 ], true, out, 1, 0 );\n    > out\n    [ 1, 3, 2, 4 ]\n\n    See Also\n    --------\n    base.aflattenBy","base.aflatten2d":"\nbase.aflatten2d( x, shape, colexicographic )\n    Flattens a two-dimensional nested array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    Returns\n    -------\n    out: Array\n        Flattened array.\n\n    Examples\n    --------\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = base.aflatten2d( x, [ 2, 2 ], false )\n    [ 1, 2, 3, 4 ]\n    > out = base.aflatten2d( x, [ 2, 2 ], true )\n    [ 1, 3, 2, 4 ]\n\n\nbase.aflatten2d.assign( x, shape, colexicographic, out, stride, offset )\n    Flattens a two-dimensional nested array and assigns elements to a provided\n    output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten2d.assign( x, [ 2, 2 ], false, out, 1, 0 )\n    [ 1, 2, 3, 4 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten2d.assign( x, [ 2, 2 ], true, out, 1, 0 );\n    > out\n    [ 1, 3, 2, 4 ]\n\n    See Also\n    --------\n    base.aflatten2dBy\n","base.aflatten2d.assign":"\nbase.aflatten2d.assign( x, shape, colexicographic, out, stride, offset )\n    Flattens a two-dimensional nested array and assigns elements to a provided\n    output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten2d.assign( x, [ 2, 2 ], false, out, 1, 0 )\n    [ 1, 2, 3, 4 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten2d.assign( x, [ 2, 2 ], true, out, 1, 0 );\n    > out\n    [ 1, 3, 2, 4 ]\n\n    See Also\n    --------\n    base.aflatten2dBy","base.aflatten2dBy":"\nbase.aflatten2dBy( x, shape, colex, clbk[, thisArg] )\n    Flattens a two-dimensional nested array according to a callback function.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Flattened array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = base.aflatten2dBy( x, [ 2, 2 ], false, fcn )\n    [ 2, 4, 6, 8 ]\n    > out = base.aflatten2dBy( x, [ 2, 2 ], true, fcn )\n    [ 2, 6, 4, 8 ]\n\n\nbase.aflatten2dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n    Flattens a two-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten2dBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\n    [ 2, 4, 6, 8 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten2dBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\n    > out\n    [ 2, 6, 4, 8 ]\n\n    See Also\n    --------\n    base.aflatten2d\n","base.aflatten2dBy.assign":"\nbase.aflatten2dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n    Flattens a two-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten2dBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\n    [ 2, 4, 6, 8 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten2dBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\n    > out\n    [ 2, 6, 4, 8 ]\n\n    See Also\n    --------\n    base.aflatten2d","base.aflatten3d":"\nbase.aflatten3d( x, shape, colexicographic )\n    Flattens a three-dimensional nested array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    Returns\n    -------\n    out: Array\n        Flattened array.\n\n    Examples\n    --------\n    > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n    > var out = base.aflatten3d( x, [ 2, 1, 2 ], false )\n    [ 1, 2, 3, 4 ]\n    > out = base.aflatten3d( x, [ 2, 1, 2 ], true )\n    [ 1, 3, 2, 4 ]\n\n\nbase.aflatten3d.assign( x, shape, colexicographic, out, stride, offset )\n    Flattens a three-dimensional nested array and assigns elements to a provided\n    output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten3d.assign( x, [ 2, 1, 2 ], false, out, 1, 0 )\n    [ 1, 2, 3, 4 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten3d.assign( x, [ 2, 1, 2 ], true, out, 1, 0 );\n    > out\n    [ 1, 3, 2, 4 ]\n\n    See Also\n    --------\n    base.aflatten3dBy\n","base.aflatten3d.assign":"\nbase.aflatten3d.assign( x, shape, colexicographic, out, stride, offset )\n    Flattens a three-dimensional nested array and assigns elements to a provided\n    output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten3d.assign( x, [ 2, 1, 2 ], false, out, 1, 0 )\n    [ 1, 2, 3, 4 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten3d.assign( x, [ 2, 1, 2 ], true, out, 1, 0 );\n    > out\n    [ 1, 3, 2, 4 ]\n\n    See Also\n    --------\n    base.aflatten3dBy","base.aflatten3dBy":"\nbase.aflatten3dBy( x, shape, colex, clbk[, thisArg] )\n    Flattens a three-dimensional nested array according to a callback function.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Flattened array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n    > var out = base.aflatten3dBy( x, [ 2, 1, 2 ], false, fcn )\n    [ 2, 4, 6, 8 ]\n    > out = base.aflatten3dBy( x, [ 2, 1, 2 ], true, fcn )\n    [ 2, 6, 4, 8 ]\n\n\nbase.aflatten3dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n    Flattens a three-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten3dBy.assign( x, [ 2, 1, 2 ], false, out, 1, 0, fcn )\n    [ 2, 4, 6, 8 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten3dBy.assign( x, [ 2, 1, 2 ], true, out, 1, 0, fcn );\n    > out\n    [ 2, 6, 4, 8 ]\n\n    See Also\n    --------\n    base.aflatten3d\n","base.aflatten3dBy.assign":"\nbase.aflatten3dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n    Flattens a three-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten3dBy.assign( x, [ 2, 1, 2 ], false, out, 1, 0, fcn )\n    [ 2, 4, 6, 8 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten3dBy.assign( x, [ 2, 1, 2 ], true, out, 1, 0, fcn );\n    > out\n    [ 2, 6, 4, 8 ]\n\n    See Also\n    --------\n    base.aflatten3d","base.aflatten4d":"\nbase.aflatten4d( x, shape, colexicographic )\n    Flattens a four-dimensional nested array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    Returns\n    -------\n    out: Array\n        Flattened array.\n\n    Examples\n    --------\n    > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n    > var out = base.aflatten4d( x, [ 2, 1, 1, 2 ], false )\n    [ 1, 2, 3, 4 ]\n    > out = base.aflatten4d( x, [ 2, 1, 1, 2 ], true )\n    [ 1, 3, 2, 4 ]\n\n\nbase.aflatten4d.assign( x, shape, colexicographic, out, stride, offset )\n    Flattens a four-dimensional nested array and assigns elements to a provided\n    output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0 )\n    [ 1, 2, 3, 4 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0 );\n    > out\n    [ 1, 3, 2, 4 ]\n\n    See Also\n    --------\n    base.aflatten4dBy\n","base.aflatten4d.assign":"\nbase.aflatten4d.assign( x, shape, colexicographic, out, stride, offset )\n    Flattens a four-dimensional nested array and assigns elements to a provided\n    output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0 )\n    [ 1, 2, 3, 4 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0 );\n    > out\n    [ 1, 3, 2, 4 ]\n\n    See Also\n    --------\n    base.aflatten4dBy","base.aflatten4dBy":"\nbase.aflatten4dBy( x, shape, colex, clbk[, thisArg] )\n    Flattens a four-dimensional nested array according to a callback function.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Flattened array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n    > var out = base.aflatten4dBy( x, [ 2, 1, 1, 2 ], false, fcn )\n    [ 2, 4, 6, 8 ]\n    > out = base.aflatten4dBy( x, [ 2, 1, 1, 2 ], true, fcn )\n    [ 2, 6, 4, 8 ]\n\n\nbase.aflatten4dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n    Flattens a four-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0, fcn )\n    [ 2, 4, 6, 8 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0, fcn );\n    > out\n    [ 2, 6, 4, 8 ]\n\n    See Also\n    --------\n    base.aflatten4d\n","base.aflatten4dBy.assign":"\nbase.aflatten4dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n    Flattens a four-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0, fcn )\n    [ 2, 4, 6, 8 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0, fcn );\n    > out\n    [ 2, 6, 4, 8 ]\n\n    See Also\n    --------\n    base.aflatten4d","base.aflatten5d":"\nbase.aflatten5d( x, shape, colexicographic )\n    Flattens a five-dimensional nested array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    Returns\n    -------\n    out: Array\n        Flattened array.\n\n    Examples\n    --------\n    > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n    > var out = base.aflatten5d( x, [ 2, 1, 1, 1, 2 ], false )\n    [ 1, 2, 3, 4 ]\n    > out = base.aflatten5d( x, [ 2, 1, 1, 1, 2 ], true )\n    [ 1, 3, 2, 4 ]\n\n\nbase.aflatten5d.assign( x, shape, colexicographic, out, stride, offset )\n    Flattens a five-dimensional nested array and assigns elements to a provided\n    output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0 )\n    [ 1, 2, 3, 4 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0 );\n    > out\n    [ 1, 3, 2, 4 ]\n\n    See Also\n    --------\n    base.aflatten5dBy\n","base.aflatten5d.assign":"\nbase.aflatten5d.assign( x, shape, colexicographic, out, stride, offset )\n    Flattens a five-dimensional nested array and assigns elements to a provided\n    output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0 )\n    [ 1, 2, 3, 4 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0 );\n    > out\n    [ 1, 3, 2, 4 ]\n\n    See Also\n    --------\n    base.aflatten5dBy","base.aflatten5dBy":"\nbase.aflatten5dBy( x, shape, colex, clbk[, thisArg] )\n    Flattens a five-dimensional nested array according to a callback function.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Flattened array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n    > var out = base.aflatten5dBy( x, [ 2, 1, 1, 1, 2 ], false, fcn )\n    [ 2, 4, 6, 8 ]\n    > out = base.aflatten5dBy( x, [ 2, 1, 1, 1, 2 ], true, fcn )\n    [ 2, 6, 4, 8 ]\n\n\nbase.aflatten5dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n    Flattens a five-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0, fcn )\n    [ 2, 4, 6, 8 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0, fcn );\n    > out\n    [ 2, 6, 4, 8 ]\n\n    See Also\n    --------\n    base.aflatten5d\n","base.aflatten5dBy.assign":"\nbase.aflatten5dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n    Flattens a five-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0, fcn )\n    [ 2, 4, 6, 8 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0, fcn );\n    > out\n    [ 2, 6, 4, 8 ]\n\n    See Also\n    --------\n    base.aflatten5d","base.aflattenBy":"\nbase.aflattenBy( x, shape, colex, clbk[, thisArg] )\n    Flattens an n-dimensional nested array according to a callback function.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Flattened array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = base.aflattenBy( x, [ 2, 2 ], false, fcn )\n    [ 2, 4, 6, 8 ]\n    > out = base.aflattenBy( x, [ 2, 2 ], true, fcn )\n    [ 2, 6, 4, 8 ]\n\n\nbase.aflattenBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n    Flattens an n-dimensional nested array according to a callback function and\n    assigns elements to a provided output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflattenBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\n    [ 2, 4, 6, 8 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflattenBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\n    > out\n    [ 2, 6, 4, 8 ]\n\n    See Also\n    --------\n    base.aflatten\n","base.aflattenBy.assign":"\nbase.aflattenBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n    Flattens an n-dimensional nested array according to a callback function and\n    assigns elements to a provided output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflattenBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\n    [ 2, 4, 6, 8 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflattenBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\n    > out\n    [ 2, 6, 4, 8 ]\n\n    See Also\n    --------\n    base.aflatten","base.afliplr2d":"\nbase.afliplr2d( x )\n    Reverses the order of elements along the last dimension of a two-dimensional\n    nested input array.\n\n    The function does *not* perform a deep copy of nested array elements.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input nested array.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.afliplr2d( [ [ 1, 2 ], [ 3, 4 ] ] )\n    [ [ 2, 1 ], [ 4, 3 ] ]\n\n    See Also\n    --------\n    base.afliplr3d, base.afliplr4d, base.afliplr5d\n","base.afliplr3d":"\nbase.afliplr3d( x )\n    Reverses the order of elements along the last dimension of a three-\n    dimensional nested input array.\n\n    The function does *not* perform a deep copy of nested array elements.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input nested array.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.afliplr3d( [ [ [ 1, 2 ], [ 3, 4 ] ] ] )\n    [ [ [ 2, 1 ], [ 4, 3 ] ] ]\n\n    See Also\n    --------\n    base.afliplr2d, base.afliplr4d, base.afliplr5d\n","base.afliplr4d":"\nbase.afliplr4d( x )\n    Reverses the order of elements along the last dimension of a four-\n    dimensional nested input array.\n\n    The function does *not* perform a deep copy of nested array elements.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input nested array.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.afliplr4d( [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] )\n    [ [ [ [ 2, 1 ], [ 4, 3 ] ] ] ]\n\n    See Also\n    --------\n    base.afliplr2d, base.afliplr3d, base.afliplr5d\n","base.afliplr5d":"\nbase.afliplr5d( x )\n    Reverses the order of elements along the last dimension of a five-\n    dimensional nested input array.\n\n    The function does *not* perform a deep copy of nested array elements.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input nested array.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.afliplr5d( [ [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] ] )\n    [ [ [ [ [ 2, 1 ], [ 4, 3 ] ] ] ] ]\n\n    See Also\n    --------\n    base.afliplr2d, base.afliplr3d, base.afliplr4d\n","base.aflipud2d":"\nbase.aflipud2d( x )\n    Reverses the order of elements along the first dimension of a two-\n    dimensional nested input array.\n\n    The function does *not* perform a deep copy of nested array elements.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input nested array.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.aflipud2d( [ [ 1, 2 ], [ 3, 4 ] ] )\n    [ [ 3, 4 ], [ 1, 2 ] ]\n\n    See Also\n    --------\n    base.aflipud3d, base.aflipud4d, base.aflipud5d\n","base.aflipud3d":"\nbase.aflipud3d( x )\n    Reverses the order of elements along the second-to-last dimension of a\n    three-dimensional nested input array.\n\n    The function does *not* perform a deep copy of nested array elements.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input nested array.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.aflipud3d( [ [ [ 1, 2 ], [ 3, 4 ] ] ] )\n    [ [ [ 3, 4 ], [ 1, 2 ] ] ]\n\n    See Also\n    --------\n    base.aflipud2d, base.aflipud4d, base.aflipud5d\n","base.aflipud4d":"\nbase.aflipud4d( x )\n    Reverses the order of elements along the second-to-last dimension of a four-\n    dimensional nested input array.\n\n    The function does *not* perform a deep copy of nested array elements.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input nested array.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.aflipud4d( [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] )\n    [ [ [ [ 3, 4 ], [ 1, 2 ] ] ] ]\n\n    See Also\n    --------\n    base.aflipud2d, base.aflipud3d, base.aflipud5d\n","base.aflipud5d":"\nbase.aflipud5d( x )\n    Reverses the order of elements along the second-to-last dimension of a five-\n    dimensional nested input array.\n\n    The function does *not* perform a deep copy of nested array elements.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input nested array.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.aflipud5d( [ [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] ] )\n    [ [ [ [ [ 3, 4 ], [ 1, 2 ] ] ] ] ]\n\n    See Also\n    --------\n    base.aflipud2d, base.aflipud3d, base.aflipud4d\n","base.ahavercos":"\nbase.ahavercos( x )\n    Computes the inverse half-value versed cosine.\n\n    The inverse half-value versed cosine is defined as `2*acos(sqrt(x))`.\n\n    If `x < 0`, `x > 1`, or `x` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Inverse half-value versed cosine.\n\n    Examples\n    --------\n    > var y = base.ahavercos( 0.5 )\n    ~1.5708\n    > y = base.ahavercos( 0.0 )\n    ~3.1416\n\n    See Also\n    --------\n    base.ahaversin, base.havercos, base.vercos\n","base.ahaversin":"\nbase.ahaversin( x )\n    Computes the inverse half-value versed sine.\n\n    The inverse half-value versed sine is defined as `2*asin(sqrt(x))`.\n\n    If `x < 0`, `x > 1`, or `x` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Inverse half-value versed sine.\n\n    Examples\n    --------\n    > var y = base.ahaversin( 0.5 )\n    ~1.5708\n    > y = base.ahaversin( 0.0 )\n    0.0\n\n    See Also\n    --------\n    base.ahavercos, base.haversin, base.versin\n","base.altcase":"\nbase.altcase( str )\n    Converts a string to alternate case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Alternate-cased string.\n\n    Examples\n    --------\n    > var out = base.altcase( 'Hello World!' )\n    'hElLo wOrLd!'\n    > out = base.altcase( 'I am a tiny little teapot' )\n    'i aM A TiNy lItTlE TeApOt'\n\n    See Also\n    --------\n    base.lowercase, base.uppercase","base.aones":"\nbase.aones( len )\n    Returns a \"generic\" array filled with ones.\n\n    Parameters\n    ----------\n    len: integer\n        Array length.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.aones( 3 )\n    [ 1.0, 1.0, 1.0 ]\n\n    See Also\n    --------\n    base.azeros, base.aones2d, base.aones3d, base.aones4d, base.aones5d, base.aonesnd\n","base.aones2d":"\nbase.aones2d( shape )\n    Returns a two-dimensional nested array filled with ones.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.aones2d( [ 1, 3 ] )\n    [ [ 1.0, 1.0, 1.0 ] ]\n\n    See Also\n    --------\n    base.azeros2d, base.aones, base.aones3d, base.aones4d, base.aones5d, base.aonesnd\n","base.aones3d":"\nbase.aones3d( shape )\n    Returns a three-dimensional nested array filled with ones.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.aones3d( [ 1, 1, 3 ] )\n    [ [ [ 1.0, 1.0, 1.0 ] ] ]\n\n    See Also\n    --------\n    base.azeros3d, base.aones, base.aones2d, base.aones4d, base.aones5d, base.aonesnd\n","base.aones4d":"\nbase.aones4d( shape )\n    Returns a four-dimensional nested array filled with ones.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.aones4d( [ 1, 1, 1, 3 ] )\n    [ [ [ [ 1.0, 1.0, 1.0 ] ] ] ]\n\n    See Also\n    --------\n    base.azeros4d, base.aones, base.aones2d, base.aones3d, base.aones5d, base.aonesnd\n","base.aones5d":"\nbase.aones5d( shape )\n    Returns a five-dimensional nested array filled with ones.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.aones5d( [ 1, 1, 1, 1, 3 ] )\n    [ [ [ [ [ 1.0, 1.0, 1.0 ] ] ] ] ]\n\n    See Also\n    --------\n    base.azeros5d, base.aones, base.aones2d, base.aones3d, base.aones4d, base.aonesnd\n","base.aonesnd":"\nbase.aonesnd( shape )\n    Returns an n-dimensional nested array filled with ones.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.aonesnd( [ 1, 3 ] )\n    [ [ 1.0, 1.0, 1.0 ] ]\n\n    See Also\n    --------\n    base.azerosnd, base.aones, base.aones2d, base.aones3d, base.aones4d, base.aones5d\n","base.aoneTo":"\nbase.aoneTo( n )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from one.\n\n    If `n` is a non-integer value greater than zero, the function returns an\n    array having `ceil(n)` elements.\n\n    If `n` is less than or equal to zero, the function returns an empty array.\n\n    Parameters\n    ----------\n    n: number\n        Number of elements.\n\n    Returns\n    -------\n    out: Array\n        Linearly spaced numeric array.\n\n    Examples\n    --------\n    > var arr = base.aoneTo( 6 )\n    [ 1, 2, 3, 4, 5, 6 ]\n\n\nbase.aoneTo.assign( out, stride, offset )\n    Fills an array with linearly spaced numeric elements which increment by 1\n    starting from one.\n\n    Parameters\n    ----------\n    out: ArrayLikeObject\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > base.aoneTo.assign( out, -1, out.length-1 );\n    > out\n    [ 6, 5, 4, 3, 2, 1 ]\n\n    See Also\n    --------\n    base.azeroTo, base.aones\n","base.aoneTo.assign":"\nbase.aoneTo.assign( out, stride, offset )\n    Fills an array with linearly spaced numeric elements which increment by 1\n    starting from one.\n\n    Parameters\n    ----------\n    out: ArrayLikeObject\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > base.aoneTo.assign( out, -1, out.length-1 );\n    > out\n    [ 6, 5, 4, 3, 2, 1 ]\n\n    See Also\n    --------\n    base.azeroTo, base.aones","base.args2multislice":"\nbase.args2multislice( args )\n    Creates a MultiSlice object from a list of MultiSlice constructor arguments.\n\n    Parameters\n    ----------\n    args: Array<Slice|integer|null|undefined>\n        Constructor arguments.\n\n    Returns\n    -------\n    s: MultiSlice\n        MultiSlice instance.\n\n    Examples\n    --------\n    > var args = [ null, null, null ];\n    > var s = new base.args2multislice( args );\n    > s.data\n    [ null, null, null ]\n    > args = [ 10, new Slice( 0, 10, 1 ), null ];\n    > s = new base.args2multislice( args );\n    > s.data\n    [ 10, <Slice>, null ]\n\n","base.asec":"\nbase.asec( x )\n    Computes the inverse (arc) secant of a number.\n\n    If `x > -1` and `x < 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Inverse (arc) secant.\n\n    Examples\n    --------\n    > var y = base.asec( 1.0 )\n    0.0\n    > y = base.asec( 2.0 )\n    ~1.0472\n    > y = base.asec( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acot, base.acsc, base.asech, base.acos\n","base.asecd":"\nbase.asecd( x )\n    Computes the arcsecant (in degrees) of a double-precision floating-point\n    number.\n\n    If `x` does not satisy `x >= 1` or `x <= -1`, the function returns NaN.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arcsecant (in degrees).\n\n    Examples\n    --------\n    > var y = base.asecd( 0.0 )\n    NaN\n    > y = base.asecd( 2 )\n    ~60.0\n    > y = base.asecd( NaN )\n    NaN\n\n    See Also\n    --------\n    base.asec, base.asech, base.acosd, base.secd\n","base.asecdf":"\nbase.asecdf( x )\n    Computes the arcsecant (in degrees) of a single-precision floating-point\n    number.\n\n    If `x` does not satisy `x >= 1` or `x <= -1`, the function returns NaN.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arcsecant (in degrees).\n\n    Examples\n    --------\n    > var y = base.asecdf( 2.0 )\n    ~60.0\n    > y = base.asecdf( 0.0 )\n    NaN\n    > y = base.asecdf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.asec, base.asech\n","base.asecf":"\nbase.asecf( x )\n    Computes the inverse (arc) secant of a single-precision\n    floating-point number.\n\n    If `x > -1` and `x < 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Inverse (arc) secant.\n\n    Examples\n    --------\n    > var y = base.asecf( 1.0 )\n    0.0\n    > y = base.asecf( 2.0 )\n    ~1.0472\n    > y = base.asecf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.asec, base.asech, base.acosf\n","base.asech":"\nbase.asech( x )\n    Computes the hyperbolic arcsecant of a number.\n\n    If `x < 0` or `x > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Hyperbolic arcsecant.\n\n    Examples\n    --------\n    > var y = base.asech( 1.0 )\n    0.0\n    > y = base.asech( 0.5 )\n    ~1.317\n    > y = base.asech( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acosh, base.asec, base.asech, base.acoth\n","base.asin":"\nbase.asin( x )\n    Computes the arcsine of a double-precision floating-point number.\n\n    If `|x| > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arcsine (in radians).\n\n    Examples\n    --------\n    > var y = base.asin( 0.0 )\n    0.0\n    > y = base.asin( -PI/6.0 )\n    ~-0.551\n    > y = base.asin( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acos, base.asinh, base.atan\n","base.asind":"\nbase.asind( x )\n    Computes the arcsine (in degrees) of a double-precision floating-point\n    number.\n\n    If `|x| > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arcsine (in degrees).\n\n    Examples\n    --------\n    > var y = base.asind( 0.0 )\n    0.0\n    > y = base.asind( PI / 6.0 )\n    ~31.57\n    > y = base.asind( NaN )\n    NaN\n\n    See Also\n    --------\n    base.asin, base.asinh, base.atand\n","base.asindf":"\nbase.asindf( x )\n    Computes the arcsine (in degrees) of a single-precision floating-point\n    number.\n\n    If `|x| > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arcsine (in degrees).\n\n    Examples\n    --------\n    > var y = base.asindf( 0.0 )\n    0.0\n    > y = base.asindf( 3.1415927410125732 / 6.0 )\n    ~31.57\n    > y = base.asindf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.asinf, base.asind\n","base.asinf":"\nbase.asinf( x )\n    Computes the arcsine of a single-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arcsine (in radians).\n\n    Examples\n    --------\n    > var y = base.asinf( 0.0 )\n    0.0\n    > y = base.asinf( -3.14/6.0 )\n    ~-0.551\n    > y = base.asinf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.asin, base.asindf\n","base.asinh":"\nbase.asinh( x )\n    Computes the hyperbolic arcsine of a double-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Hyperbolic arcsine.\n\n    Examples\n    --------\n    > var y = base.asinh( 0.0 )\n    0.0\n    > y = base.asinh( 2.0 )\n    ~1.444\n    > y = base.asinh( -2.0 )\n    ~-1.444\n    > y = base.asinh( NaN )\n    NaN\n    > y = base.asinh( NINF )\n    -Infinity\n    > y = base.asinh( PINF )\n    Infinity\n\n    See Also\n    --------\n    base.acosh, base.asin, base.atanh\n","base.atan":"\nbase.atan( x )\n    Computes the arctangent of a double-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arctangent (in radians).\n\n    Examples\n    --------\n    > var y = base.atan( 0.0 )\n    ~0.0\n    > y = base.atan( -PI/2.0 )\n    ~-1.004\n    > y = base.atan( PI/2.0 )\n    ~1.004\n    > y = base.atan( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acos, base.asin, base.atanh\n","base.atan2":"\nbase.atan2( y, x )\n    Computes the angle in the plane (in radians) between the positive x-axis and\n    the ray from (0,0) to the point (x,y).\n\n    Parameters\n    ----------\n    y: number\n        Coordinate along y-axis.\n\n    x: number\n        Coordinate along x-axis.\n\n    Returns\n    -------\n    out: number\n        Angle (in radians).\n\n    Examples\n    --------\n    > var v = base.atan2( 2.0, 2.0 )\n    ~0.785\n    > v = base.atan2( 6.0, 2.0 )\n    ~1.249\n    > v = base.atan2( -1.0, -1.0 )\n    ~-2.356\n    > v = base.atan2( 3.0, 0.0 )\n    ~1.571\n    > v = base.atan2( -2.0, 0.0 )\n    ~-1.571\n    > v = base.atan2( 0.0, 0.0 )\n    0.0\n    > v = base.atan2( 3.0, NaN )\n    NaN\n    > v = base.atan2( NaN, 2.0 )\n    NaN\n\n    See Also\n    --------\n    base.atan\n","base.atand":"\nbase.atand( x )\n    Computes the arctangent (in degrees) of a double-precision floating-point\n    number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arctangent (in degrees).\n\n    Examples\n    --------\n    > var y = base.atand( 0.0 )\n    0.0\n    > y = base.atand( PI/6.0 )\n    ~27.64\n    > y = base.atand( NaN )\n    NaN\n\n    See Also\n    --------\n    base.atan, base.atanh, base.acosd\n","base.atanf":"\nbase.atanf( x )\n    Computes the arctangent of a single-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arctangent (in radians).\n\n    Examples\n    --------\n    > var y = base.atanf( 0.0 )\n    0.0\n    > y = base.atanf( -3.14/4.0 )\n    ~-0.666\n    > y = base.atanf( 3.14/4.0 )\n    ~0.666\n    > y = base.atanf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.atan, base.atanh, base.acosf\n","base.atanh":"\nbase.atanh( x )\n    Computes the hyperbolic arctangent of a double-precision floating-point\n    number.\n\n    If `|x| > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Hyperbolic arctangent.\n\n    Examples\n    --------\n    > var y = base.atanh( 0.0 )\n    0.0\n    > y = base.atanh( 0.9 )\n    ~1.472\n    > y = base.atanh( 1.0 )\n    Infinity\n    > y = base.atanh( -1.0 )\n    -Infinity\n    > y = base.atanh( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acosh, base.asinh, base.atan\n","base.avercos":"\nbase.avercos( x )\n    Computes the inverse versed cosine.\n\n    The inverse versed cosine is defined as `acos(1+x)`.\n\n    If `x < -2`, `x > 0`, or `x` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Inverse versed cosine.\n\n    Examples\n    --------\n    > var y = base.avercos( -1.5 )\n    ~2.0944\n    > y = base.avercos( -0.0 )\n    0.0\n\n    See Also\n    --------\n    base.aversin, base.versin\n","base.aversin":"\nbase.aversin( x )\n    Computes the inverse versed sine.\n\n    The inverse versed sine is defined as `acos(1-x)`.\n\n    If `x < 0`, `x > 2`, or `x` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Inverse versed sine.\n\n    Examples\n    --------\n    > var y = base.aversin( 1.5 )\n    ~2.0944\n    > y = base.aversin( 0.0 )\n    0.0\n\n    See Also\n    --------\n    base.avercos, base.vercos\n","base.azeros":"\nbase.azeros( len )\n    Returns a zero-filled \"generic\" array.\n\n    Parameters\n    ----------\n    len: integer\n        Array length.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.azeros( 3 )\n    [ 0.0, 0.0, 0.0 ]\n\n    See Also\n    --------\n    base.aones, base.azeros2d, base.azeros3d, base.azeros4d, base.azeros5d, base.azerosnd\n","base.azeros2d":"\nbase.azeros2d( shape )\n    Returns a zero-filled two-dimensional nested array.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.azeros2d( [ 1, 3 ] )\n    [ [ 0.0, 0.0, 0.0 ] ]\n\n    See Also\n    --------\n    base.azeros, base.aones2d, base.azeros3d, base.azeros4d, base.azeros5d, base.azerosnd\n","base.azeros3d":"\nbase.azeros3d( shape )\n    Returns a zero-filled three-dimensional nested array.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.azeros3d( [ 1, 1, 3 ] )\n    [ [ [ 0.0, 0.0, 0.0 ] ] ]\n\n    See Also\n    --------\n    base.azeros, base.aones3d, base.azeros2d, base.azeros4d, base.azeros5d, base.azerosnd\n","base.azeros4d":"\nbase.azeros4d( shape )\n    Returns a zero-filled four-dimensional nested array.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.azeros4d( [ 1, 1, 1, 3 ] )\n    [ [ [ [ 0.0, 0.0, 0.0 ] ] ] ]\n\n    See Also\n    --------\n    base.azeros, base.aones4d, base.azeros2d, base.azeros3d, base.azeros5d, base.azerosnd\n","base.azeros5d":"\nbase.azeros5d( shape )\n    Returns a zero-filled five-dimensional nested array.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.azeros5d( [ 1, 1, 1, 1, 3 ] )\n    [ [ [ [ [ 0.0, 0.0, 0.0 ] ] ] ] ]\n\n    See Also\n    --------\n    base.azeros, base.aones5d, base.azeros2d, base.azeros3d, base.azeros4d, base.azerosnd\n","base.azerosnd":"\nbase.azerosnd( shape )\n    Returns a zero-filled n-dimensional nested array.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.azerosnd( [ 1, 3 ] )\n    [ [ 0.0, 0.0, 0.0 ] ]\n\n    See Also\n    --------\n    base.azeros, base.aonesnd, base.azeros2d, base.azeros3d, base.azeros4d, base.azeros5d\n","base.azeroTo":"\nbase.azeroTo( n )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from zero.\n\n    If `n` is a non-integer value greater than zero, the function returns an\n    array having `ceil(n)` elements.\n\n    If `n` is less than or equal to zero, the function returns an empty array.\n\n    Parameters\n    ----------\n    n: number\n        Number of elements.\n\n    Returns\n    -------\n    out: Array\n        Linearly spaced numeric array.\n\n    Examples\n    --------\n    > var arr = base.azeroTo( 6 )\n    [ 0, 1, 2, 3, 4, 5 ]\n\n\nbase.azeroTo.assign( out, stride, offset )\n    Fills an array with linearly spaced numeric elements which increment by 1\n    starting from zero.\n\n    Parameters\n    ----------\n    out: ArrayLikeObject\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > base.azeroTo.assign( out, -1, out.length-1 );\n    > out\n    [ 5, 4, 3, 2, 1, 0 ]\n\n    See Also\n    --------\n    base.aoneTo\n","base.azeroTo.assign":"\nbase.azeroTo.assign( out, stride, offset )\n    Fills an array with linearly spaced numeric elements which increment by 1\n    starting from zero.\n\n    Parameters\n    ----------\n    out: ArrayLikeObject\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > base.azeroTo.assign( out, -1, out.length-1 );\n    > out\n    [ 5, 4, 3, 2, 1, 0 ]\n\n    See Also\n    --------\n    base.aoneTo","base.bernoulli":"\nbase.bernoulli( n )\n    Computes the nth Bernoulli number.\n\n    If not provided a nonnegative integer value, the function returns `NaN`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Bernoulli number.\n\n    Examples\n    --------\n    > var y = base.bernoulli( 0 )\n    1.0\n    > y = base.bernoulli( 1 )\n    0.5\n    > y = base.bernoulli( 2 )\n    ~0.167\n    > y = base.bernoulli( 3 )\n    0.0\n    > y = base.bernoulli( 4 )\n    ~-0.033\n    > y = base.bernoulli( 5 )\n    0.0\n    > y = base.bernoulli( 20 )\n    ~-529.124\n    > y = base.bernoulli( 260 )\n    -Infinity\n    > y = base.bernoulli( 262 )\n    Infinity\n    > y = base.bernoulli( NaN )\n    NaN\n\n","base.besselj0":"\nbase.besselj0( x )\n    Computes the Bessel function of the first kind of order zero.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.besselj0( 0.0 )\n    1.0\n    > y = base.besselj0( 1.0 )\n    ~0.765\n    > y = base.besselj0( PINF )\n    0.0\n    > y = base.besselj0( NINF )\n    0.0\n    > y = base.besselj0( NaN )\n    NaN\n\n    See Also\n    --------\n    base.besselj1, base.bessely0, base.bessely1\n","base.besselj1":"\nbase.besselj1( x )\n    Computes the Bessel function of the first kind of order one.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.besselj1( 0.0 )\n    0.0\n    > y = base.besselj1( 1.0 )\n    ~0.440\n    > y = base.besselj1( PINF )\n    0.0\n    > y = base.besselj1( NINF )\n    0.0\n    > y = base.besselj1( NaN )\n    NaN\n\n    See Also\n    --------\n    base.besselj0, base.bessely0, base.bessely1\n","base.bessely0":"\nbase.bessely0( x )\n    Computes the Bessel function of the second kind of order zero.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.bessely0( 0.0 )\n    -Infinity\n    > y = base.bessely0( 1.0 )\n    ~0.088\n    > y = base.bessely0( -1.0 )\n    NaN\n    > y = base.bessely0( PINF )\n    0.0\n    > y = base.bessely0( NINF )\n    NaN\n    > y = base.bessely0( NaN )\n    NaN\n\n    See Also\n    --------\n    base.besselj0, base.besselj1, base.bessely1\n","base.bessely1":"\nbase.bessely1( x )\n    Computes the Bessel function of the second kind of order one.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.bessely1( 0.0 )\n    -Infinity\n    > y = base.bessely1( 1.0 )\n    ~-0.781\n    > y = base.bessely1( -1.0 )\n    NaN\n    > y = base.bessely1( PINF )\n    0.0\n    > y = base.bessely1( NINF )\n    NaN\n    > y = base.bessely1( NaN )\n    NaN\n\n    See Also\n    --------\n    base.besselj0, base.besselj1, base.bessely0\n","base.beta":"\nbase.beta( x, y )\n    Evaluates the beta function.\n\n    Parameters\n    ----------\n    x: number\n        First function parameter (nonnegative).\n\n    y: number\n        Second function parameter (nonnegative).\n\n    Returns\n    -------\n    out: number\n        Evaluated beta function.\n\n    Examples\n    --------\n    > var v = base.beta( 0.0, 0.5 )\n    Infinity\n    > v = base.beta( 1.0, 1.0 )\n    1.0\n    > v = base.beta( -1.0, 2.0 )\n    NaN\n    > v = base.beta( 5.0, 0.2 )\n    ~3.382\n    > v = base.beta( 4.0, 1.0 )\n    0.25\n    > v = base.beta( NaN, 2.0 )\n    NaN\n\n    See Also\n    --------\n    base.betainc, base.betaincinv, base.betaln\n","base.betainc":"\nbase.betainc( x, a, b[, regularized[, upper]] )\n    Computes the regularized incomplete beta function.\n\n    The `regularized` and `upper` parameters specify whether to evaluate the\n    non-regularized and/or upper incomplete beta functions, respectively.\n\n    If provided `x < 0` or `x > 1`, the function returns `NaN`.\n\n    If provided `a < 0` or `b < 0`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        First function parameter.\n\n    a: number\n        Second function parameter.\n\n    b: number\n        Third function parameter.\n\n    regularized: boolean (optional)\n        Boolean indicating whether the function should evaluate the regularized\n        or non-regularized incomplete beta function. Default: `true`.\n\n    upper: boolean (optional)\n        Boolean indicating whether the function should return the upper tail of\n        the incomplete beta function. Default: `false`.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.betainc( 0.5, 2.0, 2.0 )\n    0.5\n    > y = base.betainc( 0.5, 2.0, 2.0, false )\n    ~0.083\n    > y = base.betainc( 0.2, 1.0, 2.0 )\n    0.36\n    > y = base.betainc( 0.2, 1.0, 2.0, true, true )\n    0.64\n    > y = base.betainc( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.betainc( 0.8, NaN, 1.0 )\n    NaN\n    > y = base.betainc( 0.8, 1.0, NaN )\n    NaN\n    > y = base.betainc( 1.5, 1.0, 1.0 )\n    NaN\n    > y = base.betainc( -0.5, 1.0, 1.0 )\n    NaN\n    > y = base.betainc( 0.5, -2.0, 2.0 )\n    NaN\n    > y = base.betainc( 0.5, 2.0, -2.0 )\n    NaN\n\n    See Also\n    --------\n    base.beta, base.betaincinv, base.betaln\n","base.betaincinv":"\nbase.betaincinv( p, a, b[, upper] )\n    Computes the inverse of the lower incomplete beta function.\n\n    In contrast to a more commonly used definition, the first argument is the\n    probability `p` and the second and third arguments are `a` and `b`,\n    respectively.\n\n    By default, the function inverts the lower regularized incomplete beta\n    function. To invert the upper function, set the `upper` argument to `true`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Probability.\n\n    a: number\n        Second function parameter.\n\n    b: number\n        Third function parameter.\n\n    upper: boolean (optional)\n        Boolean indicating if the function should invert the upper tail of the\n        incomplete beta function. Default: `false`.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.betaincinv( 0.2, 3.0, 3.0 )\n    ~0.327\n    > y = base.betaincinv( 0.4, 3.0, 3.0 )\n    ~0.446\n    > y = base.betaincinv( 0.4, 3.0, 3.0, true )\n    ~0.554\n    > y = base.betaincinv( 0.4, 1.0, 6.0 )\n    ~0.082\n    > y = base.betaincinv( 0.8, 1.0, 6.0 )\n    ~0.235\n    > y = base.betaincinv( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.betaincinv( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.betaincinv( 0.5, 1.0, NaN )\n    NaN\n    > y = base.betaincinv( 1.2, 1.0, 1.0 )\n    NaN\n    > y = base.betaincinv( -0.5, 1.0, 1.0 )\n    NaN\n    > y = base.betaincinv( 0.5, -2.0, 2.0 )\n    NaN\n    > y = base.betaincinv( 0.5, 0.0, 2.0 )\n    NaN\n    > y = base.betaincinv( 0.5, 2.0, -2.0 )\n    NaN\n    > y = base.betaincinv( 0.5, 2.0, 0.0 )\n    NaN\n\n    See Also\n    --------\n    base.beta, base.betainc, base.betaln\n","base.betaln":"\nbase.betaln( a, b )\n    Evaluates the natural logarithm of the beta function.\n\n    Parameters\n    ----------\n    a: number\n        First function parameter (nonnegative).\n\n    b: number\n        Second function parameter (nonnegative).\n\n    Returns\n    -------\n    out: number\n        Natural logarithm of the beta function.\n\n    Examples\n    --------\n    > var v = base.betaln( 0.0, 0.0 )\n    Infinity\n    > v = base.betaln( 1.0, 1.0 )\n    0.0\n    > v = base.betaln( -1.0, 2.0 )\n    NaN\n    > v = base.betaln( 5.0, 0.2 )\n    ~1.218\n    > v = base.betaln( 4.0, 1.0 )\n    ~-1.386\n    > v = base.betaln( NaN, 2.0 )\n    NaN\n\n    See Also\n    --------\n    base.beta, base.betainc, base.betaincinv\n","base.binet":"\nbase.binet( x )\n    Evaluates Binet's formula extended to real numbers.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function result.\n\n    Examples\n    --------\n    > var y = base.binet( 0.0 )\n    0.0\n    > y = base.binet( 1.0 )\n    1.0\n    > y = base.binet( 2.0 )\n    1.0\n    > y = base.binet( 3.0 )\n    2.0\n    > y = base.binet( 4.0 )\n    3.0\n    > y = base.binet( 5.0 )\n    ~5.0\n    > y = base.binet( NaN )\n    NaN\n\n    See Also\n    --------\n    base.fibonacci, base.negafibonacci\n","base.binomcoef":"\nbase.binomcoef( n, k )\n    Computes the binomial coefficient of two integers.\n\n    If `k < 0`, the function returns `0`.\n\n    The function returns `NaN` for non-integer `n` or `k`.\n\n    Parameters\n    ----------\n    n: integer\n        First input value.\n\n    k: integer\n        Second input value.\n\n    Returns\n    -------\n    out: number\n        Function value.\n\n    Examples\n    --------\n    > var v = base.binomcoef( 8, 2 )\n    28\n    > v = base.binomcoef( 0, 0 )\n    1\n    > v = base.binomcoef( -4, 2 )\n    10\n    > v = base.binomcoef( 5, 3 )\n    10\n    > v = base.binomcoef( NaN, 3 )\n    NaN\n    > v = base.binomcoef( 5, NaN )\n    NaN\n    > v = base.binomcoef( NaN, NaN )\n    NaN\n\n","base.binomcoefln":"\nbase.binomcoefln( n, k )\n    Computes the natural logarithm of the binomial coefficient of two integers.\n\n    If `k < 0`, the function returns negative infinity.\n\n    The function returns `NaN` for non-integer `n` or `k`.\n\n    Parameters\n    ----------\n    n: integer\n        First input value.\n\n    k: integer\n        Second input value.\n\n    Returns\n    -------\n    out: number\n        Natural logarithm of the binomial coefficient.\n\n    Examples\n    --------\n    > var v = base.binomcoefln( 8, 2 )\n    ~3.332\n    > v = base.binomcoefln( 0, 0 )\n    0.0\n    > v = base.binomcoefln( -4, 2 )\n    ~2.303\n    > v = base.binomcoefln( 88, 3 )\n    ~11.606\n    > v = base.binomcoefln( NaN, 3 )\n    NaN\n    > v = base.binomcoefln( 5, NaN )\n    NaN\n    > v = base.binomcoefln( NaN, NaN )\n    NaN\n\n","base.boxcox":"\nbase.boxcox( x, lambda )\n    Computes a one-parameter Box-Cox transformation.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    lambda: number\n        Power parameter.\n\n    Returns\n    -------\n    b: number\n        Function value.\n\n    Examples\n    --------\n    > var v = base.boxcox( 1.0, 2.5 )\n    0.0\n    > v = base.boxcox( 4.0, 2.5 )\n    12.4\n    > v = base.boxcox( 10.0, 2.5 )\n    ~126.0911\n    > v = base.boxcox( 2.0, 0.0 )\n    ~0.6931\n    > v = base.boxcox( -1.0, 2.5 )\n    NaN\n    > v = base.boxcox( 0.0, -1.0 )\n    -Infinity\n\n    See Also\n    --------\n    base.boxcoxinv, base.boxcox1p, base.boxcox1pinv","base.boxcox1p":"\nbase.boxcox1p( x, lambda )\n    Computes a one-parameter Box-Cox transformation of 1+x.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    lambda: number\n        Power parameter.\n\n    Returns\n    -------\n    b: number\n        Function value.\n\n    Examples\n    --------\n    > var v =  base.boxcox1p( 1.0, 2.5 )\n    ~1.8627\n    > v = base.boxcox1p( 4.0, 2.5 )\n    ~21.9607\n    > v = base.boxcox1p( 10.0, 2.5 )\n    ~160.1246\n    > v = base.boxcox1p( 2.0, 0.0 )\n    ~1.0986\n    > v = base.boxcox1p( -1.0, 2.5 )\n    -0.4\n    > v = base.boxcox1p( 0.0, -1.0 )\n    0.0\n    > v = base.boxcox1p( -1.0, -1.0 )\n    -Infinity\n\n    See Also\n    --------\n    base.boxcox, base.boxcox1pinv, base.boxcoxinv","base.boxcox1pinv":"\nbase.boxcox1pinv( y, lambda )\n    Computes the inverse of a one-parameter Box-Cox transformation for 1+x.\n\n    Parameters\n    ----------\n    y: number\n        Input value.\n\n    lambda: number\n        Power parameter.\n\n    Returns\n    -------\n    v: number\n        Function value.\n\n    Examples\n    --------\n    > var v = base.boxcox1pinv( 1.0, 2.5 )\n    ~0.6505\n    > v = base.boxcox1pinv( 4.0, 2.5 )\n    ~1.6095\n    > v = base.boxcox1pinv( 10.0, 2.5 )\n    ~2.6812\n    > v = base.boxcox1pinv( 2.0, 0.0 )\n    ~6.3891\n    > v = base.boxcox1pinv( -1.0, 2.5 )\n    NaN\n    > v = base.boxcox1pinv( 0.0, -1.0 )\n    0.0\n    > v = base.boxcox1pinv( 1.0, NaN )\n    NaN\n    > v = base.boxcox1pinv( NaN, 3.1 )\n    NaN\n\n    See Also\n    --------\n    base.boxcox, base.boxcox1p, base.boxcoxinv","base.boxcoxinv":"\nbase.boxcoxinv( y, lambda )\n    Computes the inverse of a one-parameter Box-Cox transformation.\n\n    Parameters\n    ----------\n    y: number\n        Input value.\n\n    lambda: number\n        Power parameter.\n\n    Returns\n    -------\n    b: number\n        Function value.\n\n    Examples\n    --------\n    > var v = base.boxcoxinv( 1.0, 2.5 )\n    ~1.6505\n    > v = base.boxcoxinv( 4.0, 2.5 )\n    ~2.6095\n    > v = base.boxcoxinv( 10.0, 2.5 )\n    ~3.6812\n    > v = base.boxcoxinv( 2.0, 0.0 )\n    ~7.3891\n    > v = base.boxcoxinv( -1.0, 2.5 )\n    NaN\n    > v = base.boxcoxinv( 0.0, -1.0 )\n    1.0\n    > v = base.boxcoxinv( 1.0, NaN )\n    NaN\n    > v = base.boxcoxinv( NaN, 3.1 )\n    NaN\n\n    See Also\n    --------\n    base.boxcox, base.boxcox1p, base.boxcox1pinv","base.cabs":"\nbase.cabs( z )\n    Computes the absolute value of a double-precision complex floating-point\n    number.\n\n    The absolute value of a complex number is its distance from zero.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    y: number\n        Absolute value.\n\n    Examples\n    --------\n    > var y = base.cabs( new Complex128( 5.0, 3.0 ) )\n    ~5.831\n\n    See Also\n    --------\n    base.cabs2, base.abs\n","base.cabs2":"\nbase.cabs2( z )\n    Computes the squared absolute value of a double-precision complex floating-\n    point number.\n\n    The absolute value of a complex number is its distance from zero.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    y: number\n        Squared absolute value.\n\n    Examples\n    --------\n    > var y = base.cabs2( new Complex128( 5.0, 3.0 ) )\n    34.0\n\n    See Also\n    --------\n    base.cabs, base.abs2\n","base.cabs2f":"\nbase.cabs2f( z )\n    Computes the squared absolute value of a single-precision complex floating-\n    point number.\n\n    The absolute value of a complex number is its distance from zero.\n\n    Parameters\n    ----------\n    z: Complex64\n        Complex number.\n\n    Returns\n    -------\n    y: number\n        Squared absolute value.\n\n    Examples\n    --------\n    > var y = base.cabs2f( new Complex64( 5.0, 3.0 ) )\n    34.0\n\n    See Also\n    --------\n    base.cabs2, base.cabsf, base.abs2f\n","base.cabsf":"\nbase.cabsf( z )\n    Computes the absolute value of a single-precision complex floating-point\n    number.\n\n    The absolute value of a complex number is its distance from zero.\n\n    Parameters\n    ----------\n    z: Complex64\n        Complex number.\n\n    Returns\n    -------\n    y: number\n        Absolute value.\n\n    Examples\n    --------\n    > var y = base.cabsf( new Complex64( 5.0, 3.0 ) )\n    ~5.831\n\n    See Also\n    --------\n    base.cabs, base.cabs2f, base.absf\n","base.cadd":"\nbase.cadd( z1, z2 )\n    Adds two double-precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    z1: Complex128\n        Complex number.\n\n    z2: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Result.\n\n    Examples\n    --------\n    > var z = new Complex128( 5.0, 3.0 )\n    <Complex128>\n    > var out = base.cadd( z, z )\n    <Complex128>\n    > var re = real( out )\n    10.0\n    > var im = imag( out )\n    6.0\n\n    See Also\n    --------\n    base.cdiv, base.cmul, base.csub\n","base.caddf":"\nbase.caddf( z1, z2 )\n    Adds two single-precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    z1: Complex64\n        Complex number.\n\n    z2: Complex64\n        Complex number.\n\n    Returns\n    -------\n    out: Complex64\n        Result.\n\n    Examples\n    --------\n    > var z = new Complex64( 5.0, 3.0 )\n    <Complex64>\n    > var out = base.caddf( z, z )\n    <Complex64>\n    > var re = realf( out )\n    10.0\n    > var im = imagf( out )\n    6.0\n\n    See Also\n    --------\n    base.cadd, base.cmulf, base.csubf\n","base.camelcase":"\nbase.camelcase( str )\n    Converts a string to camel case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Camel-cased string.\n\n    Examples\n    --------\n    > var out = base.camelcase( 'Hello World!' )\n    'helloWorld'\n    > out = base.camelcase( 'beep boop' )\n    'beepBoop'\n\n    See Also\n    --------\n    base.constantcase, base.lowercase, base.snakecase, base.uppercase","base.capitalize":"\nbase.capitalize( str )\n    Capitalizes the first character in a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Capitalized string.\n\n    Examples\n    --------\n    > var out = base.capitalize( 'beep' )\n    'Beep'\n    > out = base.capitalize( 'Boop' )\n    'Boop'\n\n    See Also\n    --------\n    base.lowercase, base.uppercase\n","base.cbrt":"\nbase.cbrt( x )\n    Computes the cube root of a double-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Cube root.\n\n    Examples\n    --------\n    > var y = base.cbrt( 64.0 )\n    4.0\n    > y = base.cbrt( 27.0 )\n    3.0\n    > y = base.cbrt( 0.0 )\n    0.0\n    > y = base.cbrt( -0.0 )\n    -0.0\n    > y = base.cbrt( -9.0 )\n    ~-2.08\n    > y = base.cbrt( NaN )\n    NaN\n\n    See Also\n    --------\n    base.pow, base.sqrt\n","base.cbrtf":"\nbase.cbrtf( x )\n    Computes the cube root of a single-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Cube root.\n\n    Examples\n    --------\n    > var y = base.cbrtf( 64.0 )\n    4.0\n    > y = base.cbrtf( 27.0 )\n    3.0\n    > y = base.cbrtf( 0.0 )\n    0.0\n    > y = base.cbrtf( -0.0 )\n    -0.0\n    > y = base.cbrtf( -9.0 )\n    ~-2.08\n    > y = base.cbrtf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cbrt, base.sqrtf\n","base.cceil":"\nbase.cceil( z )\n    Rounds each component of a double-precision complex floating-point number\n    toward positive infinity.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Result.\n\n    Examples\n    --------\n    > var v = base.cceil( new Complex128( -1.5, 2.5 ) )\n    <Complex128>\n    > var re = real( v )\n    -1.0\n    > var im = imag( v )\n    3.0\n\n    See Also\n    --------\n    base.cceiln, base.cfloor, base.cround\n","base.cceilf":"\nbase.cceilf( z )\n    Rounds a single-precision complex floating-point number toward positive\n    infinity.\n\n    Parameters\n    ----------\n    z: Complex64\n        Complex number.\n\n    Returns\n    -------\n    out: Complex64\n        Result.\n\n    Examples\n    --------\n    > var v = base.cceilf( new Complex64( -1.5, 2.5 ) )\n    <Complex64>\n    > var re = realf( v )\n    -1.0\n    > var im = imagf( v )\n    3.0\n\n    See Also\n    --------\n    base.cceil\n","base.cceiln":"\nbase.cceiln( z, n )\n    Rounds each component of a double-precision complex number to the nearest\n    multiple of `10^n` toward positive infinity.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    n: integer\n        Integer power of 10.\n\n    Returns\n    -------\n    out: Complex128\n        Real and imaginary components.\n\n    Examples\n    --------\n    > var out = base.cceiln( new Complex128( 5.555, -3.333 ), -2 )\n    <Complex128>\n    > var re = real( out )\n    5.56\n    > var im = imag( out )\n    -3.33\n\n    See Also\n    --------\n    base.cceil, base.cfloorn, base.croundn\n","base.ccis":"\nbase.ccis( z )\n    Evaluates the cis function for a double-precision complex floating-point\n    number.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Complex number.\n\n    Examples\n    --------\n    > var y = base.ccis( new Complex128( 0.0, 0.0 ) )\n    <Complex128>\n    > var re = real( y )\n    1.0\n    > var im = imag( y )\n    0.0\n    > y = base.ccis( new Complex128( 1.0, 0.0 ) )\n    <Complex128>\n    > re = real( y )\n    ~0.540\n    > im = imag( y )\n    ~0.841\n\n","base.cdiv":"\nbase.cdiv( z1, z2 )\n    Divides two double-precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    z1: Complex128\n        Complex number.\n\n    z2: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Result.\n\n    Examples\n    --------\n    > var z1 = new Complex128( -13.0, -1.0 )\n    <Complex128>\n    > var z2 = new Complex128( -2.0, 1.0 )\n    <Complex128>\n    > var y = base.cdiv( z1, z2 )\n    <Complex128>\n    > var re = real( y )\n    5.0\n    > var im = imag( y )\n    3.0\n\n    See Also\n    --------\n    base.cadd, base.cmul, base.csub\n","base.ceil":"\nbase.ceil( x )\n    Rounds a double-precision floating-point number toward positive infinity.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.ceil( 3.14 )\n    4.0\n    > y = base.ceil( -4.2 )\n    -4.0\n    > y = base.ceil( -4.6 )\n    -4.0\n    > y = base.ceil( 9.5 )\n    10.0\n    > y = base.ceil( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceiln, base.floor, base.round\n","base.ceil2":"\nbase.ceil2( x )\n    Rounds a numeric value to the nearest power of two toward positive infinity.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.ceil2( 3.14 )\n    4.0\n    > y = base.ceil2( -4.2 )\n    -4.0\n    > y = base.ceil2( -4.6 )\n    -4.0\n    > y = base.ceil2( 9.5 )\n    16.0\n    > y = base.ceil2( 13.0 )\n    16.0\n    > y = base.ceil2( -13.0 )\n    -8.0\n    > y = base.ceil2( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceil, base.ceil10, base.floor2, base.round2\n","base.ceil10":"\nbase.ceil10( x )\n    Rounds a numeric value to the nearest power of ten toward positive infinity.\n\n    The function may not return accurate results for subnormals due to a general\n    loss in precision.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.ceil10( 3.14 )\n    10.0\n    > y = base.ceil10( -4.2 )\n    -1.0\n    > y = base.ceil10( -4.6 )\n    -1.0\n    > y = base.ceil10( 9.5 )\n    10.0\n    > y = base.ceil10( 13.0 )\n    100.0\n    > y = base.ceil10( -13.0 )\n    -10.0\n    > y = base.ceil10( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceil, base.ceil2, base.floor10, base.round10\n","base.ceilb":"\nbase.ceilb( x, n, b )\n    Rounds a numeric value to the nearest multiple of `b^n` toward positive\n    infinity.\n\n    Due to floating-point rounding error, rounding may not be exact.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Integer power.\n\n    b: integer\n        Base.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    // Round to 4 decimal places:\n    > var y = base.ceilb( 3.14159, -4, 10 )\n    3.1416\n\n    // If `n = 0` or `b = 1`, standard round behavior:\n    > y = base.ceilb( 3.14159, 0, 2 )\n    4.0\n\n    // Round to nearest multiple of two toward positive infinity:\n    > y = base.ceilb( 5.0, 1, 2 )\n    6.0\n\n    See Also\n    --------\n    base.ceil, base.ceiln, base.floorb, base.roundb\n","base.ceilf":"\nbase.ceilf( x )\n    Rounds a single-precision floating-point number toward positive infinity.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.ceilf( 3.14 )\n    4.0\n    > y = base.ceilf( -4.2 )\n    -4.0\n    > y = base.ceilf( -4.6 )\n    -4.0\n    > y = base.ceilf( 9.5 )\n    10.0\n    > y = base.ceilf( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.floorf\n","base.ceiln":"\nbase.ceiln( x, n )\n    Rounds a numeric value to the nearest multiple of `10^n` toward positive\n    infinity.\n\n    When operating on floating-point numbers in bases other than `2`, rounding\n    to specified digits can be inexact.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Integer power of 10.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    // Round to 2 decimal places:\n    > var y = base.ceiln( 3.14159, -2 )\n    3.15\n\n    // If `n = 0`, standard round toward positive infinity behavior:\n    > y = base.ceiln( 3.14159, 0 )\n    4.0\n\n    // Round to nearest thousand:\n    > y = base.ceiln( 12368.0, 3 )\n    13000.0\n\n\n    See Also\n    --------\n    base.ceil, base.ceilb, base.floorn, base.roundn\n","base.ceilsd":"\nbase.ceilsd( x, n, b )\n    Rounds a numeric value to the nearest number toward positive infinity with\n    `n` significant figures.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Number of significant figures. Must be greater than 0.\n\n    b: integer\n        Base. Must be greater than 0.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.ceilsd( 3.14159, 5, 10 )\n    3.1416\n    > y = base.ceilsd( 3.14159, 1, 10 )\n    4.0\n    > y = base.ceilsd( 12368.0, 2, 10 )\n    13000.0\n    > y = base.ceilsd( 0.0313, 2, 2 )\n    0.046875\n\n    See Also\n    --------\n    base.ceil, base.floorsd, base.roundsd, base.truncsd\n","base.cexp":"\nbase.cexp( z )\n    Evaluates the exponential function for a double-precision complex floating-\n    point number.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Complex number.\n\n    Examples\n    --------\n    > var y = base.cexp( new Complex128( 0.0, 0.0 ) )\n    <Complex128>\n    > var re = real( y )\n    1.0\n    > var im = imag( y )\n    0.0\n    > y = base.cexp( new Complex128( 0.0, 1.0 ) )\n    <Complex128>\n    > re = real( y )\n    ~0.540\n    > im = imag( y )\n    ~0.841\n\n","base.cflipsign":"\nbase.cflipsign( z, y )\n    Returns a double-precision complex floating-point number with the same\n    magnitude as `z` and the sign of `y*z`.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    y: number\n        Number from which to derive the sign.\n\n    Returns\n    -------\n    out: Complex128\n        Result.\n\n    Examples\n    --------\n    > var v = base.cflipsign( new Complex128( -4.2, 5.5 ), -9.0 )\n    <Complex128>\n    > var re = real( v )\n    4.2\n    > var im = imag( v )\n    -5.5\n\n    See Also\n    --------\n    base.cneg, base.csignum\n","base.cflipsignf":"\nbase.cflipsignf( z, y )\n    Returns a single-precision complex floating-point number with the same\n    magnitude as `z` and the sign of `y*z`.\n\n    Parameters\n    ----------\n    z: Complex64\n        Complex number.\n\n    y: number\n        Number from which to derive the sign.\n\n    Returns\n    -------\n    out: Complex64\n        Result.\n\n    Examples\n    --------\n    > var v = base.cflipsignf( new Complex64( -4.0, 5.0 ), -9.0 )\n    <Complex64>\n    > var re = realf( v )\n    4.0\n    > var im = imagf( v )\n    -5.0\n\n    See Also\n    --------\n    base.cnegf, base.cflipsign\n","base.cfloor":"\nbase.cfloor( z )\n    Rounds a double-precision complex floating-point number toward negative\n    infinity.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Result.\n\n    Examples\n    --------\n    > var v = base.cfloor( new Complex128( 5.5, 3.3 ) )\n    <Complex128>\n    > var re = real( v )\n    5.0\n    > var im = imag( v )\n    3.0\n\n    See Also\n    --------\n    base.cceil, base.cfloorn, base.cround\n","base.cfloorn":"\nbase.cfloorn( z, n )\n    Rounds each component of a double-precision complex floating-point number\n    to the nearest multiple of `10^n` toward negative infinity.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    n: integer\n        Integer power of 10.\n\n    Returns\n    -------\n    z: Complex128\n        Result.\n\n    Examples\n    --------\n    > var v = base.cfloorn( new Complex128( 5.555, -3.333 ), -2 )\n    <Complex128>\n    > var re = real( v )\n    5.55\n    > var im = imag( v )\n    -3.34\n\n    See Also\n    --------\n    base.cceiln, base.cfloor, base.croundn\n","base.cidentity":"\nbase.cidentity( z )\n    Evaluates the identity function for a double-precision complex floating-\n    point number.\n\n    Parameters\n    ----------\n    z: Complex128\n        Input value.\n\n    Returns\n    -------\n    v: Complex128\n        Input value.\n\n    Examples\n    --------\n    > var v = base.cidentity( new Complex128( -1.0, 2.0 ) )\n    <Complex128>\n    > var re = real( v )\n    -1.0\n    > var img = imag( v )\n    2.0\n\n    See Also\n    --------\n    base.cidentityf, base.identity\n","base.cidentityf":"\nbase.cidentityf( z )\n    Evaluates the identity function for a single-precision complex floating-\n    point number.\n\n    Parameters\n    ----------\n    z: Complex64\n        Input value.\n\n    Returns\n    -------\n    v: Complex64\n        Input value.\n\n    Examples\n    --------\n    > var v = base.cidentityf( new Complex64( -1.0, 2.0 ) )\n    <Complex64>\n    > var re = realf( v )\n    -1.0\n    > var img = imagf( v )\n    2.0\n\n    See Also\n    --------\n    base.cidentity, base.identityf\n","base.cinv":"\nbase.cinv( z )\n    Computes the inverse of a double-precision complex floating-point number.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Result.\n\n    Examples\n    --------\n    > var v = base.cinv( new Complex128( 2.0, 4.0 ) )\n    <Complex128>\n    > var re = real( v )\n    0.1\n    > var im = imag( v )\n    -0.2\n\n    See Also\n    --------\n    base.cdiv\n","base.clamp":"\nbase.clamp( v, min, max )\n    Restricts a double-precision floating-point number to a specified range.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    v: number\n        Value to restrict.\n\n    min: number\n        Minimum value.\n\n    max: number\n        Maximum value.\n\n    Returns\n    -------\n    y: number\n        Restricted value.\n\n    Examples\n    --------\n    > var y = base.clamp( 3.14, 0.0, 5.0 )\n    3.14\n    > y = base.clamp( -3.14, 0.0, 5.0 )\n    0.0\n    > y = base.clamp( 3.14, 0.0, 3.0 )\n    3.0\n    > y = base.clamp( -0.0, 0.0, 5.0 )\n    0.0\n    > y = base.clamp( 0.0, -3.14, -0.0 )\n    -0.0\n    > y = base.clamp( NaN, 0.0, 5.0 )\n    NaN\n\n    See Also\n    --------\n    base.clampf, base.wrap\n","base.clampf":"\nbase.clampf( v, min, max )\n    Restricts a single-precision floating-point number to a specified range.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    v: number\n        Value to restrict.\n\n    min: number\n        Minimum value.\n\n    max: number\n        Maximum value.\n\n    Returns\n    -------\n    y: number\n        Restricted value.\n\n    Examples\n    --------\n    > var y = base.clampf( 3.14, 0.0, 5.0 )\n    3.14\n    > y = base.clampf( -3.14, 0.0, 5.0 )\n    0.0\n    > y = base.clampf( 3.14, 0.0, 3.0 )\n    3.0\n    > y = base.clampf( -0.0, 0.0, 5.0 )\n    0.0\n    > y = base.clampf( 0.0, -3.14, -0.0 )\n    -0.0\n    > y = base.clampf( NaN, 0.0, 5.0 )\n    NaN\n\n    See Also\n    --------\n    base.clamp\n","base.cmul":"\nbase.cmul( z1, z2 )\n    Multiplies two double-precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    z1: Complex128\n        Complex number.\n\n    z2: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Result.\n\n    Examples\n    --------\n    > var z1 = new Complex128( 5.0, 3.0 )\n    <Complex128>\n    > var z2 = new Complex128( -2.0, 1.0 )\n    <Complex128>\n    > var out = base.cmul( z1, z2 )\n    <Complex128>\n    > var re = real( out )\n    -13.0\n    > var im = imag( out )\n    -1.0\n\n    See Also\n    --------\n    base.cadd, base.cdiv, base.csub\n","base.cmulf":"\nbase.cmulf( z1, z2 )\n    Multiplies two single-precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    z1: Complex64\n        Complex number.\n\n    z2: Complex64\n        Complex number.\n\n    Returns\n    -------\n    out: Complex64\n        Result.\n\n    Examples\n    --------\n    > var z1 = new Complex64( 5.0, 3.0 )\n    <Complex64>\n    > var z2 = new Complex64( -2.0, 1.0 )\n    <Complex64>\n    > var out = base.cmulf( z1, z2 )\n    <Complex64>\n    > var re = realf( out )\n    -13.0\n    > var im = imagf( out )\n    -1.0\n\n    See Also\n    --------\n    base.caddf, base.cmul, base.csubf\n","base.cneg":"\nbase.cneg( z )\n    Negates a double-precision complex floating-point number.\n\n    Parameters\n    ----------\n    z: Complex128\n       Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Result.\n\n    Examples\n    --------\n    > var z = new Complex128( -4.2, 5.5 )\n    <Complex128>\n    > var v = base.cneg( z )\n    <Complex128>\n    > var re = real( v )\n    4.2\n    > var im = imag( v )\n    -5.5\n\n    See Also\n    --------\n    base.cabs\n","base.cnegf":"\nbase.cnegf( z )\n    Negates a single-precision complex floating-point number.\n\n    Parameters\n    ----------\n    z: Complex64\n       Complex number.\n\n    Returns\n    -------\n    out: Complex64\n        Result.\n\n    Examples\n    --------\n    > var z = new Complex64( -4.0, 5.0 )\n    <Complex64>\n    > var v = base.cnegf( z )\n    <Complex64>\n    > var re = realf( v )\n    4.0\n    > var im = imagf( v )\n    -5.0\n\n    See Also\n    --------\n    base.cneg, base.cabsf\n","base.codePointAt":"\nbase.codePointAt( str, idx, backward )\n    Returns a Unicode code point from a string at a specified position.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    idx: integer\n        Position. If less than `0`, the string position is determined relative\n        to the end of the input string.\n\n    backward: boolean\n        Backward iteration for low surrogates.\n\n    Returns\n    -------\n    out: integer\n        Unicode code point.\n\n    Examples\n    --------\n    > var out = base.codePointAt( 'last man standing', 4, false )\n    32\n    > out = base.codePointAt( 'presidential election', 8, true )\n    116\n    > out = base.codePointAt( 'अनुच्छेद', 2, false )\n    2369\n    > out = base.codePointAt( '🌷', 1, true )\n    127799\n","base.constantcase":"\nbase.constantcase( str )\n    Converts a string to constant case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Constant-cased string.\n\n    Examples\n    --------\n    > var out = base.constantcase( 'Hello World!' )\n    'HELLO_WORLD'\n    > out = base.constantcase( 'I am a tiny little teapot' )\n    'I_AM_A_TINY_LITTLE_TEAPOT'\n\n    See Also\n    --------\n    base.camelcase, base.lowercase, base.snakecase, base.uppercase","base.continuedFraction":"\nbase.continuedFraction( generator[, options] )\n    Evaluates the continued fraction approximation for the supplied series\n    generator using the modified Lentz algorithm.\n\n    `generator` can be either a function which returns an array with two\n    elements, the `a` and `b` terms of the fraction, or an ES6 Generator object.\n\n    By default, the function computes\n\n             a1\n        ---------------\n        b1 +     a2\n             ----------\n              b2 +   a3\n                  -----\n                  b3 + ...\n\n    To evaluate\n\n        b0 +\t a1\n        ---------------\n        b1 +\t a2\n             ----------\n             b2 +  a3\n                  -----\n                  b3 + ...\n\n    set the `keep` option to `true`.\n\n    Parameters\n    ----------\n    generator: Function\n        Function returning terms of continued fraction expansion.\n\n    options: Object (optional)\n        Options.\n\n    options.maxIter: integer (optional)\n         Maximum number of iterations. Default: `1000000`.\n\n    options.tolerance: number (optional)\n        Further terms are only added as long as the next term is greater than\n        current term times the tolerance. Default: `2.22e-16`.\n\n    options.keep: boolean (optional)\n        Boolean indicating whether to keep the `b0` term in the continued\n        fraction. Default: `false`.\n\n    Returns\n    -------\n    out: number\n       Value of continued fraction.\n\n    Examples\n    --------\n    // Continued fraction for (e-1)^(-1):\n    > function closure() {\n    ...    var i = 0;\n    ...    return function() {\n    ...        i += 1;\n    ...        return [ i, i ];\n    ...    };\n    ... };\n    > var gen = closure();\n    > var out = base.continuedFraction( gen )\n    ~0.582\n\n    // Using an ES6 generator:\n    > function* generator() {\n    ...     var i = 0;\n    ...     while ( true ) {\n    ...         i += 1;\n    ...         yield [ i, i ];\n    ...     }\n    ... };\n    > gen = generator();\n    > out = base.continuedFraction( gen )\n    ~0.582\n\n    // Set options:\n    > out = base.continuedFraction( generator(), { 'keep': true } )\n    ~1.718\n    > out = base.continuedFraction( generator(), { 'maxIter': 10 } )\n    ~0.582\n    > out = base.continuedFraction( generator(), { 'tolerance': 1e-1 } )\n    ~0.579\n\n","base.copysign":"\nbase.copysign( x, y )\n    Returns a double-precision floating-point number with the magnitude of `x`\n    and the sign of `y`.\n\n    Parameters\n    ----------\n    x: number\n        Number from which to derive a magnitude.\n\n    y: number\n        Number from which to derive a sign.\n\n    Returns\n    -------\n    z: number\n        Double-precision floating-point number.\n\n    Examples\n    --------\n    > var z = base.copysign( -3.14, 10.0 )\n    3.14\n    > z = base.copysign( 3.14, -1.0 )\n    -3.14\n    > z = base.copysign( 1.0, -0.0 )\n    -1.0\n    > z = base.copysign( -3.14, -0.0 )\n    -3.14\n    > z = base.copysign( -0.0, 1.0 )\n    0.0\n\n    See Also\n    --------\n    base.flipsign\n","base.copysignf":"\nbase.copysignf( x, y )\n    Returns a single-precision floating-point number with the magnitude of `x`\n    and the sign of `y`.\n\n    Parameters\n    ----------\n    x: number\n        Number from which to derive a magnitude.\n\n    y: number\n        Number from which to derive a sign.\n\n    Returns\n    -------\n    z: number\n        Single-precision floating-point number.\n\n    Examples\n    --------\n    > var z = base.copysignf( -3.0, 10.0 )\n    3.0\n    > z = base.copysignf( 3.0, -1.0 )\n    -3.0\n    > z = base.copysignf( 1.0, -0.0 )\n    -1.0\n    > z = base.copysignf( -3.0, -0.0 )\n    -3.0\n    > z = base.copysignf( -0.0, 1.0 )\n    0.0\n\n    See Also\n    --------\n    base.copysign, base.flipsignf\n","base.cos":"\nbase.cos( x )\n    Computes the cosine of a number.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Cosine.\n\n    Examples\n    --------\n    > var y = base.cos( 0.0 )\n    1.0\n    > y = base.cos( PI/4.0 )\n    ~0.707\n    > y = base.cos( -PI/6.0 )\n    ~0.866\n    > y = base.cos( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cospi, base.cosm1, base.sin, base.tan\n","base.cosd":"\nbase.cosd( x )\n    Computes the cosine of an angle measured in degrees.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in degrees).\n\n    Returns\n    -------\n    y: number\n        Cosine.\n\n    Examples\n    --------\n    > var y = base.cosd( 0.0 )\n    1.0\n    > y = base.cosd( 90.0 )\n    0.0\n    > y = base.cosd( 60.0 )\n    ~0.5\n    > y = base.cosd( NaN )\n    NaN\n\n    See Also\n    --------\n    base.tand\n","base.cosh":"\nbase.cosh( x )\n    Computes the hyperbolic cosine of a double-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Hyperbolic cosine.\n\n    Examples\n    --------\n    > var y = base.cosh( 0.0 )\n    1.0\n    > y = base.cosh( 2.0 )\n    ~3.762\n    > y = base.cosh( -2.0 )\n    ~3.762\n    > y = base.cosh( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cos, base.sinh, base.tanh\n","base.cosm1":"\nbase.cosm1( x )\n    Computes the cosine of a number minus one.\n\n    This function should be used instead of manually calculating `cos(x)-1` when\n    `x` is near unity.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Cosine minus one.\n\n    Examples\n    --------\n    > var y = base.cosm1( 0.0 )\n    0.0\n    > y = base.cosm1( PI/4.0 )\n    ~-0.293\n    > y = base.cosm1( -PI/6.0 )\n    ~-0.134\n    > y = base.cosm1( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cos\n","base.cospi":"\nbase.cospi( x )\n    Computes the value of `cos(πx)`.\n\n    This function computes `cos(πx)` more accurately than the obvious approach,\n    especially for large `x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.cospi( 0.0 )\n    1.0\n    > y = base.cospi( 0.5 )\n    0.0\n    > y = base.cospi( 0.1 )\n    ~0.951\n    > y = base.cospi( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cos\n","base.cot":"\nbase.cot( x )\n    Computes the cotangent of a number.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Cotangent.\n\n    Examples\n    --------\n    > var y = base.cot( 0.0 )\n    Infinity\n    > y = base.cot( -PI/4.0 )\n    ~-1.0\n    > y = base.cot( PI/4.0 )\n    ~1.0\n    > y = base.cot( NaN )\n    NaN\n\n    See Also\n    --------\n    base.csc, base.tan\n","base.cotd":"\nbase.cotd( x )\n    Computes the cotangent of an angle measured in degrees.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in degrees).\n\n    Returns\n    -------\n    y: number\n        Cotangent.\n\n    Examples\n    --------\n    > var y = base.cotd( 0.0 )\n    Infinity\n    > y = base.cotd( 90.0 )\n    0.0\n    > y = base.cotd( 60.0 )\n    ~0.58\n    > y = base.cotd( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cscd, base.secd, base.tand\n","base.coth":"\nbase.coth( x )\n    Computes the hyperbolic cotangent of a number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Hyperbolic cotangent.\n\n    Examples\n    --------\n    > var y = base.coth( 0.0 )\n    Infinity\n    > y = base.coth( -0.0 )\n    -Infinity\n    > y = base.coth( 2.0 )\n    ~1.0373\n    > y = base.coth( -2.0 )\n    ~-1.0373\n    > y = base.coth( +Infinity )\n    ~1\n    > y = base.coth( -Infinity )\n    ~-1\n    > y = base.coth( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acoth, base.cot, base.csch, base.tanh\n","base.covercos":"\nbase.covercos( x )\n    Computes the coversed cosine.\n\n    The coversed cosine is defined as `1 + sin(x)`.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Coversed cosine.\n\n    Examples\n    --------\n    > var y = base.covercos( 3.14 )\n    ~1.0016\n    > y = base.covercos( -4.2 )\n    ~1.8716\n    > y = base.covercos( -4.6 )\n    ~1.9937\n    > y = base.covercos( 9.5 )\n    ~0.9248\n    > y = base.covercos( -0.0 )\n    1.0\n\n    See Also\n    --------\n    base.coversin, base.vercos\n","base.coversin":"\nbase.coversin( x )\n    Computes the coversed sine.\n\n    The coversed sine is defined as `1 - sin(x)`.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Coversed sine.\n\n    Examples\n    --------\n    > var y = base.coversin( 3.14 )\n    ~0.9984\n    > y = base.coversin( -4.2 )\n    ~0.1284\n    > y = base.coversin( -4.6 )\n    ~0.0063\n    > y = base.coversin( 9.5 )\n    ~1.0752\n    > y = base.coversin( -0.0 )\n    1.0\n\n    See Also\n    --------\n    base.covercos, base.versin\n","base.cphase":"\nbase.cphase( z )\n    Computes the argument of a double-precision complex floating-point number\n    in radians.\n\n    The argument of a complex number, also known as the phase, is the angle of\n    the radius extending from the origin to the complex number plotted in the\n    complex plane and the positive real axis.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    phi: number\n        Argument.\n\n    Examples\n    --------\n    > var phi = base.cphase( new Complex128( 5.0, 3.0 ) )\n    ~0.5404\n\n    See Also\n    --------\n    base.cabs\n","base.cpolar":"\nbase.cpolar( z )\n    Returns the absolute value and phase of a double-precision complex\n    floating-point number.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Array<number>\n        Absolute value and phase, respectively.\n\n    Examples\n    --------\n    > var out = base.cpolar( new Complex128( 5.0, 3.0 ) )\n    [ ~5.83, ~0.5404 ]\n\n\nbase.cpolar.assign( z, out, stride, offset )\n    Returns the absolute value and phase of a double-precision complex\n    floating-point number and assigns results to a provided output array.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    out: Array|TypedArray|Object\n        Destination array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Absolute value and phase, respectively.\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var v = base.cpolar.assign( new Complex128( 5.0, 3.0 ), out, 1, 0 )\n    <Float64Array>[ ~5.83, ~0.5404 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.cabs, base.cphase","base.cpolar.assign":"\nbase.cpolar.assign( z, out, stride, offset )\n    Returns the absolute value and phase of a double-precision complex\n    floating-point number and assigns results to a provided output array.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    out: Array|TypedArray|Object\n        Destination array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Absolute value and phase, respectively.\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var v = base.cpolar.assign( new Complex128( 5.0, 3.0 ), out, 1, 0 )\n    <Float64Array>[ ~5.83, ~0.5404 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.cabs, base.cphase","base.cround":"\nbase.cround( z )\n    Rounds each component of a double-precision complex floating-point number\n    to the nearest integer.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Rounded complex number.\n\n    Examples\n    --------\n    > var v = base.cround( new Complex128( 5.5, 3.3 ) )\n    <Complex128>\n    > var re = real( v )\n    6.0\n    > var im = imag( v )\n    3.0\n\n    See Also\n    --------\n    base.cceil, base.cfloor, base.croundn\n","base.croundn":"\nbase.croundn( z, n )\n    Rounds each component of a double-precision complex floating-point number\n    to the nearest multiple of `10^n`.\n\n    When operating on floating-point numbers in bases other than `2`, rounding\n    to specified digits can be inexact.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    n: integer\n        Integer power of 10.\n\n    Returns\n    -------\n    out: Complex128\n        Result.\n\n    Examples\n    --------\n    > var v = base.croundn( new Complex128( 5.555, -3.336 ), -2 )\n    <Complex128>\n    > var re = real( v )\n    5.56\n    > var im = imag( v )\n    -3.34\n\n    See Also\n    --------\n    base.cceiln, base.cfloorn, base.cround\n","base.csc":"\nbase.csc( x )\n    Computes the cosecant of a number.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Cosecant.\n\n    Examples\n    --------\n    > var y = base.csc( 0.0 )\n    Infinity\n    > y = base.csc( PI/2.0 )\n    ~1.0\n    > y = base.csc( -PI/6.0 )\n    ~-2.0\n    > y = base.csc( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cot, base.sin","base.cscd":"\nbase.cscd( x )\n    Computes the cosecant of a degree.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in degrees).\n\n    Returns\n    -------\n    y: number\n        Cosecant.\n\n    Examples\n    --------\n    > var y = base.cscd( 1.0 )\n    ~57.30\n    > y = base.cscd( PI )\n    ~18.25\n    > y = base.cscd( -PI )\n    ~-18.25\n    > y = base.cscd( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cotd, base.secd\n","base.csch":"\nbase.csch( x )\n    Computes the hyperbolic cosecant of a number.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Hyperbolic cosecant.\n\n    Examples\n    --------\n    > var y = base.csch( +0.0 )\n    +Infinity\n    > var y = base.csch( -0.0 )\n    -Infinity\n    > var y = base.csch( +Infinity )\n    +0.0\n    > var y = base.csch( -Infinity )\n    -0.0\n    > y = base.csch( 2.0 )\n    ~0.2757\n    > y = base.csch( -2.0 )\n    ~-0.2757\n    > y = base.csch( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acsch, base.csc, base.coth, base.sinh\n","base.csignum":"\nbase.csignum( z )\n    Evaluates the signum function of a double-precision complex floating-point\n    number.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Result.\n\n    Examples\n    --------\n    > var v = base.csignum( new Complex128( -4.2, 5.5 ) )\n    <Complex128>\n    > var re = real( v )\n    -0.6069136033622302\n    > var im = imag( v )\n    0.79476781392673\n\n    See Also\n    --------\n    base.signum\n","base.csub":"\nbase.csub( z1, z2 )\n    Subtracts two double-precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    z1: Complex128\n        Complex number.\n\n    z2: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Result.\n\n    Examples\n    --------\n    > var z1 = new Complex128( 5.0, 3.0 )\n    <Complex128>\n    > var z2 = new Complex128( -2.0, 1.0 )\n    <Complex128>\n    > var out = base.csub( z1, z2 )\n    <Complex128>\n    > var re = real( out )\n    7.0\n    > var im = imag( out )\n    2.0\n\n    See Also\n    --------\n    base.cadd, base.cdiv, base.cmul\n","base.csubf":"\nbase.csubf( z1, z2 )\n    Subtracts two single-precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    z1: Complex64\n        Complex number.\n\n    z2: Complex64\n        Complex number.\n\n    Returns\n    -------\n    out: Complex64\n        Result.\n\n    Examples\n    --------\n    > var z1 = new Complex64( 5.0, 3.0 )\n    <Complex64>\n    > var z2 = new Complex64( -2.0, 1.0 )\n    <Complex64>\n    > var out = base.csubf( z1, z2 )\n    <Complex64>\n    > var re = realf( out )\n    7.0\n    > var im = imagf( out )\n    2.0\n\n    See Also\n    --------\n    base.caddf, base.cmulf, base.csub\n","base.deg2rad":"\nbase.deg2rad( x )\n    Converts an angle from degrees to radians.\n\n    Parameters\n    ----------\n    x: number\n        Angle in degrees.\n\n    Returns\n    -------\n    r: number\n        Angle in radians.\n\n    Examples\n    --------\n    > var r = base.deg2rad( 90.0 )\n    ~1.571\n    > r = base.deg2rad( -45.0 )\n    ~-0.785\n    > r = base.deg2rad( NaN )\n    NaN\n\n    See Also\n    --------\n    base.rad2deg\n","base.deg2radf":"\nbase.deg2radf( x )\n    Converts an angle from degrees to radians (single-precision).\n\n    Parameters\n    ----------\n    x: number\n        Angle in degrees.\n\n    Returns\n    -------\n    r: number\n        Angle in radians.\n\n    Examples\n    --------\n    > var r = base.deg2radf( 90.0 )\n    ~1.571\n    > r = base.deg2radf( -45.0 )\n    ~-0.785\n    > r = base.deg2radf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.deg2rad, base.rad2degf\n","base.digamma":"\nbase.digamma( x )\n    Evaluates the digamma function.\n\n    If `x` is zero or a negative integer, the function returns `NaN`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.digamma( -2.5 )\n    ~1.103\n    > y = base.digamma( 1.0 )\n    ~-0.577\n    > y = base.digamma( 10.0 )\n    ~2.252\n    > y = base.digamma( NaN )\n    NaN\n    > y = base.digamma( -1.0 )\n    NaN\n\n    See Also\n    --------\n    base.gamma, base.trigamma\n","base.diracDelta":"\nbase.diracDelta( x )\n    Evaluates the Dirac delta function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.diracDelta( 3.14 )\n    0.0\n    > y = base.diracDelta( 0.0 )\n    Infinity\n\n    See Also\n    --------\n    base.kroneckerDelta\n","base.div":"\nbase.div( x, y )\n    Divides two double-precision floating-point numbers `x` and `y`.\n\n    Parameters\n    ----------\n    x: number\n        First input value (dividend).\n\n    y: number\n        Second input value (divisor).\n\n    Returns\n    -------\n    z: number\n        Result.\n\n    Examples\n    --------\n    > var v = base.div( -1.0, 5.0 )\n    -0.2\n    > v = base.div( 2.0, 5.0 )\n    0.4\n    > v = base.div( 0.0, 5.0 )\n    0.0\n    > v = base.div( -0.0, 5.0 )\n    -0.0\n    > v = base.div( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.add, base.mul, base.sub\n","base.divf":"\nbase.divf( x, y )\n    Divides two single-precision floating-point numbers `x` and `y`.\n\n    Parameters\n    ----------\n    x: number\n        First input value (dividend).\n\n    y: number\n        Second input value (divisor).\n\n    Returns\n    -------\n    z: number\n        Result.\n\n    Examples\n    --------\n    > var v = base.divf( -1.0, 5.0 )\n    ~-0.2\n    > v = base.divf( 2.0, 5.0 )\n    ~0.4\n    > v = base.divf( 0.0, 5.0 )\n    0.0\n    > v = base.divf( -0.0, 5.0 )\n    -0.0\n    > v = base.divf( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.addf, base.div, base.mulf, base.subf\n","base.dotcase":"\nbase.dotcase( str )\n    Converts a string to dot case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Dot-cased string.\n\n    Examples\n    --------\n    > var out = base.dotcase( 'Hello World!' )\n    'hello.world'\n    > out = base.dotcase( 'I am a tiny little teapot' )\n    'i.am.a.tiny.little.teapot'\n\n    See Also\n    --------\n    base.camelcase, base.lowercase, base.snakecase, base.uppercase","base.dists.arcsine.Arcsine":"\nbase.dists.arcsine.Arcsine( [a, b] )\n    Returns an arcsine distribution object.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support. Must be less than `b`. Default: `0.0`.\n\n    b: number (optional)\n        Maximum support. Must be greater than `a`. Default: `1.0`.\n\n    Returns\n    -------\n    arcsine: Object\n        Distribution instance.\n\n    arcsine.a: number\n        Minimum support. If set, the value must be less than `b`.\n\n    arcsine.b: number\n        Maximum support. If set, the value must be greater than `a`.\n\n    arcsine.entropy: number\n        Read-only property which returns the differential entropy.\n\n    arcsine.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    arcsine.mean: number\n        Read-only property which returns the expected value.\n\n    arcsine.median: number\n        Read-only property which returns the median.\n\n    arcsine.mode: number\n        Read-only property which returns the mode.\n\n    arcsine.skewness: number\n        Read-only property which returns the skewness.\n\n    arcsine.stdev: number\n        Read-only property which returns the standard deviation.\n\n    arcsine.variance: number\n        Read-only property which returns the variance.\n\n    arcsine.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    arcsine.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    arcsine.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    arcsine.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    arcsine.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var arcsine = base.dists.arcsine.Arcsine( 0.0, 1.0 );\n    > arcsine.a\n    0.0\n    > arcsine.b\n    1.0\n    > arcsine.entropy\n    ~-0.242\n    > arcsine.kurtosis\n    -1.5\n    > arcsine.mean\n    0.5\n    > arcsine.median\n    0.5\n    > arcsine.mode\n    0.0\n    > arcsine.skewness\n    0.0\n    > arcsine.stdev\n    ~0.354\n    > arcsine.variance\n    0.125\n    > arcsine.cdf( 0.8 )\n    ~0.705\n    > arcsine.logcdf( 0.8 )\n    ~-0.35\n    > arcsine.logpdf( 0.4 )\n    ~-0.431\n    > arcsine.pdf( 0.8 )\n    ~0.796\n    > arcsine.quantile( 0.8 )\n    ~0.905\n\n","base.dists.arcsine.cdf":"\nbase.dists.arcsine.cdf( x, a, b )\n    Evaluates the cumulative distribution function (CDF) for an arcsine\n    distribution with minimum support `a` and maximum support `b` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.arcsine.cdf( 9.0, 0.0, 10.0 )\n    ~0.795\n    > y = base.dists.arcsine.cdf( 0.5, 0.0, 2.0 )\n    ~0.333\n    > y = base.dists.arcsine.cdf( PINF, 2.0, 4.0 )\n    1.0\n    > y = base.dists.arcsine.cdf( NINF, 2.0, 4.0 )\n    0.0\n    > y = base.dists.arcsine.cdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.arcsine.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.arcsine.cdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.arcsine.cdf( 2.0, 1.0, 0.0 )\n    NaN\n\n\nbase.dists.arcsine.cdf.factory( a, b )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an arcsine distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.arcsine.cdf.factory( 0.0, 10.0 );\n    > var y = mycdf( 0.5 )\n    ~0.144\n    > y = mycdf( 8.0 )\n    ~0.705\n\n","base.dists.arcsine.cdf.factory":"\nbase.dists.arcsine.cdf.factory( a, b )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an arcsine distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.arcsine.cdf.factory( 0.0, 10.0 );\n    > var y = mycdf( 0.5 )\n    ~0.144\n    > y = mycdf( 8.0 )\n    ~0.705","base.dists.arcsine.entropy":"\nbase.dists.arcsine.entropy( a, b )\n    Returns the differential entropy of an arcsine distribution (in nats).\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.arcsine.entropy( 0.0, 1.0 )\n    ~-0.242\n    > v = base.dists.arcsine.entropy( 4.0, 12.0 )\n    ~1.838\n    > v = base.dists.arcsine.entropy( 2.0, 8.0 )\n    ~1.55\n\n","base.dists.arcsine.kurtosis":"\nbase.dists.arcsine.kurtosis( a, b )\n    Returns the excess kurtosis of an arcsine distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.arcsine.kurtosis( 0.0, 1.0 )\n    -1.5\n    > v = base.dists.arcsine.kurtosis( 4.0, 12.0 )\n    -1.5\n    > v = base.dists.arcsine.kurtosis( 2.0, 8.0 )\n    -1.5\n\n","base.dists.arcsine.logcdf":"\nbase.dists.arcsine.logcdf( x, a, b )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for an\n    arcsine distribution with minimum support `a` and maximum support `b` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.arcsine.logcdf( 9.0, 0.0, 10.0 )\n    ~-0.229\n    > y = base.dists.arcsine.logcdf( 0.5, 0.0, 2.0 )\n    ~-1.1\n    > y = base.dists.arcsine.logcdf( PINF, 2.0, 4.0 )\n    0.0\n    > y = base.dists.arcsine.logcdf( NINF, 2.0, 4.0 )\n    -Infinity\n    > y = base.dists.arcsine.logcdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.arcsine.logcdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.arcsine.logcdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.arcsine.logcdf( 2.0, 1.0, 0.0 )\n    NaN\n\n\nbase.dists.arcsine.logcdf.factory( a, b )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of an arcsine distribution with minimum support\n    `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.arcsine.logcdf.factory( 0.0, 10.0 );\n    > var y = mylogcdf( 0.5 )\n    ~-1.941\n    > y = mylogcdf( 8.0 )\n    ~-0.35\n\n","base.dists.arcsine.logcdf.factory":"\nbase.dists.arcsine.logcdf.factory( a, b )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of an arcsine distribution with minimum support\n    `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.arcsine.logcdf.factory( 0.0, 10.0 );\n    > var y = mylogcdf( 0.5 )\n    ~-1.941\n    > y = mylogcdf( 8.0 )\n    ~-0.35","base.dists.arcsine.logpdf":"\nbase.dists.arcsine.logpdf( x, a, b )\n    Evaluates the logarithm of the probability density function (PDF) for an\n    arcsine distribution with minimum support `a` and maximum support `b` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.arcsine.logpdf( 2.0, 0.0, 4.0 )\n    ~-1.838\n    > y = base.dists.arcsine.logpdf( 5.0, 0.0, 4.0 )\n    -Infinity\n    > y = base.dists.arcsine.logpdf( 0.25, 0.0, 1.0 )\n    ~-0.308\n    > y = base.dists.arcsine.logpdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.arcsine.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.arcsine.logpdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.arcsine.logpdf( 2.0, 3.0, 1.0 )\n    NaN\n\n\nbase.dists.arcsine.logpdf.factory( a, b )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of an arcsine distribution with minimum support `a` and\n    maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.arcsine.logpdf.factory( 6.0, 7.0 );\n    > var y = mylogPDF( 7.0 )\n    Infinity\n    > y = mylogPDF( 5.0 )\n    -Infinity\n\n","base.dists.arcsine.logpdf.factory":"\nbase.dists.arcsine.logpdf.factory( a, b )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of an arcsine distribution with minimum support `a` and\n    maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.arcsine.logpdf.factory( 6.0, 7.0 );\n    > var y = mylogPDF( 7.0 )\n    Infinity\n    > y = mylogPDF( 5.0 )\n    -Infinity","base.dists.arcsine.mean":"\nbase.dists.arcsine.mean( a, b )\n    Returns the expected value of an arcsine distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.arcsine.mean( 0.0, 1.0 )\n    0.5\n    > v = base.dists.arcsine.mean( 4.0, 12.0 )\n    8.0\n    > v = base.dists.arcsine.mean( 2.0, 8.0 )\n    5.0\n\n","base.dists.arcsine.median":"\nbase.dists.arcsine.median( a, b )\n    Returns the median of an arcsine distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.arcsine.median( 0.0, 1.0 )\n    0.5\n    > v = base.dists.arcsine.median( 4.0, 12.0 )\n    8.0\n    > v = base.dists.arcsine.median( 2.0, 8.0 )\n    5.0\n\n","base.dists.arcsine.mode":"\nbase.dists.arcsine.mode( a, b )\n    Returns the mode of an arcsine distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.arcsine.mode( 0.0, 1.0 )\n    0.0\n    > v = base.dists.arcsine.mode( 4.0, 12.0 )\n    4.0\n    > v = base.dists.arcsine.mode( 2.0, 8.0 )\n    2.0\n\n","base.dists.arcsine.pdf":"\nbase.dists.arcsine.pdf( x, a, b )\n    Evaluates the probability density function (PDF) for an arcsine distribution\n    with minimum support `a` and maximum support `b` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.arcsine.pdf( 2.0, 0.0, 4.0 )\n    ~0.159\n    > y = base.dists.arcsine.pdf( 5.0, 0.0, 4.0 )\n    0.0\n    > y = base.dists.arcsine.pdf( 0.25, 0.0, 1.0 )\n    ~0.735\n    > y = base.dists.arcsine.pdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.arcsine.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.arcsine.pdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.arcsine.pdf( 2.0, 3.0, 1.0 )\n    NaN\n\n\nbase.dists.arcsine.pdf.factory( a, b )\n    Returns a function for evaluating the probability density function (PDF) of\n    an arcsine distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.arcsine.pdf.factory( 6.0, 7.0 );\n    > var y = myPDF( 7.0 )\n    Infinity\n    > y = myPDF( 5.0 )\n    0.0\n\n","base.dists.arcsine.pdf.factory":"\nbase.dists.arcsine.pdf.factory( a, b )\n    Returns a function for evaluating the probability density function (PDF) of\n    an arcsine distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.arcsine.pdf.factory( 6.0, 7.0 );\n    > var y = myPDF( 7.0 )\n    Infinity\n    > y = myPDF( 5.0 )\n    0.0","base.dists.arcsine.quantile":"\nbase.dists.arcsine.quantile( p, a, b )\n    Evaluates the quantile function for an arcsine distribution with minimum\n    support `a` and maximum support `b` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.arcsine.quantile( 0.8, 0.0, 1.0 )\n    ~0.905\n    > y = base.dists.arcsine.quantile( 0.5, 0.0, 10.0 )\n    ~5.0\n\n    > y = base.dists.arcsine.quantile( 1.1, 0.0, 1.0 )\n    NaN\n    > y = base.dists.arcsine.quantile( -0.2, 0.0, 1.0 )\n    NaN\n\n    > y = base.dists.arcsine.quantile( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.arcsine.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.arcsine.quantile( 0.0, 0.0, NaN )\n    NaN\n\n    > y = base.dists.arcsine.quantile( 0.5, 2.0, 1.0 )\n    NaN\n\n\nbase.dists.arcsine.quantile.factory( a, b )\n    Returns a function for evaluating the quantile function of an arcsine\n    distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.arcsine.quantile.factory( 0.0, 4.0 );\n    > var y = myQuantile( 0.8 )\n    ~3.618\n\n","base.dists.arcsine.quantile.factory":"\nbase.dists.arcsine.quantile.factory( a, b )\n    Returns a function for evaluating the quantile function of an arcsine\n    distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.arcsine.quantile.factory( 0.0, 4.0 );\n    > var y = myQuantile( 0.8 )\n    ~3.618","base.dists.arcsine.skewness":"\nbase.dists.arcsine.skewness( a, b )\n    Returns the skewness of an arcsine distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.arcsine.skewness( 0.0, 1.0 )\n    0.0\n    > v = base.dists.arcsine.skewness( 4.0, 12.0 )\n    0.0\n    > v = base.dists.arcsine.skewness( 2.0, 8.0 )\n    0.0\n\n","base.dists.arcsine.stdev":"\nbase.dists.arcsine.stdev( a, b )\n    Returns the standard deviation of an arcsine distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.arcsine.stdev( 0.0, 1.0 )\n    ~0.354\n    > v = base.dists.arcsine.stdev( 4.0, 12.0 )\n    ~2.828\n    > v = base.dists.arcsine.stdev( 2.0, 8.0 )\n    ~2.121\n\n","base.dists.arcsine.variance":"\nbase.dists.arcsine.variance( a, b )\n    Returns the variance of an arcsine distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.arcsine.variance( 0.0, 1.0 )\n    ~0.125\n    > v = base.dists.arcsine.variance( 4.0, 12.0 )\n    8.0\n    > v = base.dists.arcsine.variance( 2.0, 8.0 )\n    ~4.5\n\n","base.dists.bernoulli.Bernoulli":"\nbase.dists.bernoulli.Bernoulli( [p] )\n    Returns a Bernoulli distribution object.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability. Must be between `0` and `1`. Default: `0.5`.\n\n    Returns\n    -------\n    bernoulli: Object\n        Distribution instance.\n\n    bernoulli.p: number\n        Success probability. If set, the value must be between `0` and `1`.\n\n    bernoulli.entropy: number\n        Read-only property which returns the differential entropy.\n\n    bernoulli.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    bernoulli.mean: number\n        Read-only property which returns the expected value.\n\n    bernoulli.median: number\n        Read-only property which returns the median.\n\n    bernoulli.skewness: number\n        Read-only property which returns the skewness.\n\n    bernoulli.stdev: number\n        Read-only property which returns the standard deviation.\n\n    bernoulli.variance: number\n        Read-only property which returns the variance.\n\n    bernoulli.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    bernoulli.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    bernoulli.pmf: Function\n        Evaluates the probability mass function (PMF).\n\n    bernoulli.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var bernoulli = base.dists.bernoulli.Bernoulli( 0.6 );\n    > bernoulli.p\n    0.6\n    > bernoulli.entropy\n    ~0.673\n    > bernoulli.kurtosis\n    ~-1.833\n    > bernoulli.mean\n    0.6\n    > bernoulli.median\n    1.0\n    > bernoulli.skewness\n    ~-0.408\n    > bernoulli.stdev\n    ~0.49\n    > bernoulli.variance\n    ~0.24\n    > bernoulli.cdf( 0.5 )\n    0.4\n    > bernoulli.mgf( 3.0 )\n    ~12.451\n    > bernoulli.pmf( 0.0 )\n    0.4\n    > bernoulli.quantile( 0.7 )\n    1.0\n\n","base.dists.bernoulli.cdf":"\nbase.dists.bernoulli.cdf( x, p )\n    Evaluates the cumulative distribution function (CDF) for a Bernoulli\n    distribution with success probability `p` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.bernoulli.cdf( 0.5, 0.5 )\n    0.5\n    > y = base.dists.bernoulli.cdf( 0.8, 0.1 )\n    0.9\n    > y = base.dists.bernoulli.cdf( -1.0, 0.4 )\n    0.0\n    > y = base.dists.bernoulli.cdf( 1.5, 0.4 )\n    1.0\n    > y = base.dists.bernoulli.cdf( NaN, 0.5 )\n    NaN\n    > y = base.dists.bernoulli.cdf( 0.0, NaN )\n    NaN\n    // Invalid probability:\n    > y = base.dists.bernoulli.cdf( 2.0, 1.4 )\n    NaN\n\n\nbase.dists.bernoulli.cdf.factory( p )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Bernoulli distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.bernoulli.cdf.factory( 0.5 );\n    > var y = mycdf( 3.0 )\n    1.0\n    > y = mycdf( 0.7 )\n    0.5\n\n","base.dists.bernoulli.cdf.factory":"\nbase.dists.bernoulli.cdf.factory( p )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Bernoulli distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.bernoulli.cdf.factory( 0.5 );\n    > var y = mycdf( 3.0 )\n    1.0\n    > y = mycdf( 0.7 )\n    0.5","base.dists.bernoulli.entropy":"\nbase.dists.bernoulli.entropy( p )\n    Returns the entropy of a Bernoulli distribution with success probability\n    `p` (in nats).\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.bernoulli.entropy( 0.1 )\n    ~0.325\n    > v = base.dists.bernoulli.entropy( 0.5 )\n    ~0.693\n\n","base.dists.bernoulli.kurtosis":"\nbase.dists.bernoulli.kurtosis( p )\n    Returns the excess kurtosis of a Bernoulli distribution with success\n    probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.bernoulli.kurtosis( 0.1 )\n    ~5.111\n    > v = base.dists.bernoulli.kurtosis( 0.5 )\n    -2.0\n\n","base.dists.bernoulli.mean":"\nbase.dists.bernoulli.mean( p )\n    Returns the expected value of a Bernoulli distribution with success\n    probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.bernoulli.mean( 0.1 )\n    0.1\n    > v = base.dists.bernoulli.mean( 0.5 )\n    0.5\n\n","base.dists.bernoulli.median":"\nbase.dists.bernoulli.median( p )\n    Returns the median of a Bernoulli distribution with success probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: integer\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.bernoulli.median( 0.1 )\n    0\n    > v = base.dists.bernoulli.median( 0.8 )\n    1\n\n","base.dists.bernoulli.mgf":"\nbase.dists.bernoulli.mgf( t, p )\n    Evaluates the moment-generating function (MGF) for a Bernoulli\n    distribution with success probability `p` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.bernoulli.mgf( 0.2, 0.5 )\n    ~1.111\n    > y = base.dists.bernoulli.mgf( 0.4, 0.5 )\n    ~1.246\n    > y = base.dists.bernoulli.mgf( NaN, 0.0 )\n    NaN\n    > y = base.dists.bernoulli.mgf( 0.0, NaN )\n    NaN\n    > y = base.dists.bernoulli.mgf( -2.0, -1.0 )\n    NaN\n    > y = base.dists.bernoulli.mgf( 0.2, 2.0 )\n    NaN\n\n\nbase.dists.bernoulli.mgf.factory( p )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Bernoulli distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.bernoulli.mgf.factory( 0.8 );\n    > var y = mymgf( -0.2 )\n    ~0.855\n\n","base.dists.bernoulli.mgf.factory":"\nbase.dists.bernoulli.mgf.factory( p )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Bernoulli distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.bernoulli.mgf.factory( 0.8 );\n    > var y = mymgf( -0.2 )\n    ~0.855","base.dists.bernoulli.mode":"\nbase.dists.bernoulli.mode( p )\n    Returns the mode of a Bernoulli distribution with success probability `p`.\n\n    For `p = 0.5`, the mode is either `0` or `1`. This implementation returns\n    `0` for `p = 0.5`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: integer\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.bernoulli.mode( 0.1 )\n    0\n    > v = base.dists.bernoulli.mode( 0.8 )\n    1\n\n","base.dists.bernoulli.pmf":"\nbase.dists.bernoulli.pmf( x, p )\n    Evaluates the probability mass function (PMF) for a Bernoulli distribution\n    with success probability `p` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated PMF.\n\n    Examples\n    --------\n    > var y = base.dists.bernoulli.pmf( 1.0, 0.3 )\n    0.3\n    > y = base.dists.bernoulli.pmf( 0.0, 0.7 )\n    0.3\n    > y = base.dists.bernoulli.pmf( -1.0, 0.5 )\n    0.0\n    > y = base.dists.bernoulli.pmf( 0.0, NaN )\n    NaN\n    > y = base.dists.bernoulli.pmf( NaN, 0.5 )\n    NaN\n    // Invalid success probability:\n    > y = base.dists.bernoulli.pmf( 0.0, 1.5 )\n    NaN\n\n\nbase.dists.bernoulli.pmf.factory( p )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    Bernoulli distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var mypmf = base.dists.bernoulli.pmf.factory( 0.5 );\n    > var y = mypmf( 1.0 )\n    0.5\n    > y = mypmf( 0.0 )\n    0.5\n\n","base.dists.bernoulli.pmf.factory":"\nbase.dists.bernoulli.pmf.factory( p )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    Bernoulli distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var mypmf = base.dists.bernoulli.pmf.factory( 0.5 );\n    > var y = mypmf( 1.0 )\n    0.5\n    > y = mypmf( 0.0 )\n    0.5","base.dists.bernoulli.quantile":"\nbase.dists.bernoulli.quantile( r, p )\n    Evaluates the quantile function for a Bernoulli distribution with success\n    probability `p` at a probability `r`.\n\n    If `r < 0` or `r > 1`, the function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    r: number\n        Input probability.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.bernoulli.quantile( 0.8, 0.4 )\n    1\n    > y = base.dists.bernoulli.quantile( 0.5, 0.4 )\n    0\n    > y = base.dists.bernoulli.quantile( 0.9, 0.1 )\n    0\n\n    > y = base.dists.bernoulli.quantile( -0.2, 0.1 )\n    NaN\n\n    > y = base.dists.bernoulli.quantile( NaN, 0.8 )\n    NaN\n    > y = base.dists.bernoulli.quantile( 0.4, NaN )\n    NaN\n\n    > y = base.dists.bernoulli.quantile( 0.5, -1.0 )\n    NaN\n    > y = base.dists.bernoulli.quantile( 0.5, 1.5 )\n    NaN\n\n\nbase.dists.bernoulli.quantile.factory( p )\n    Returns a function for evaluating the quantile function of a Bernoulli\n    distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.bernoulli.quantile.factory( 0.4 );\n    > var y = myquantile( 0.4 )\n    0\n    > y = myquantile( 0.8 )\n    1\n    > y = myquantile( 1.0 )\n    1\n\n","base.dists.bernoulli.quantile.factory":"\nbase.dists.bernoulli.quantile.factory( p )\n    Returns a function for evaluating the quantile function of a Bernoulli\n    distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.bernoulli.quantile.factory( 0.4 );\n    > var y = myquantile( 0.4 )\n    0\n    > y = myquantile( 0.8 )\n    1\n    > y = myquantile( 1.0 )\n    1","base.dists.bernoulli.skewness":"\nbase.dists.bernoulli.skewness( p )\n    Returns the skewness of a Bernoulli distribution with success probability\n    `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.bernoulli.skewness( 0.1 )\n    ~2.667\n    > v = base.dists.bernoulli.skewness( 0.5 )\n    0.0\n\n","base.dists.bernoulli.stdev":"\nbase.dists.bernoulli.stdev( p )\n    Returns the standard deviation of a Bernoulli distribution with success\n    probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.bernoulli.stdev( 0.1 )\n    ~0.3\n    > v = base.dists.bernoulli.stdev( 0.5 )\n    0.5\n\n","base.dists.bernoulli.variance":"\nbase.dists.bernoulli.variance( p )\n    Returns the variance of a Bernoulli distribution with success probability\n    `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.bernoulli.variance( 0.1 )\n    ~0.09\n    > v = base.dists.bernoulli.variance( 0.5 )\n    0.25\n\n","base.dists.beta.Beta":"\nbase.dists.beta.Beta( [α, β] )\n    Returns a beta distribution object.\n\n    Parameters\n    ----------\n    α: number (optional)\n        First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n    β: number (optional)\n        Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    beta: Object\n        Distribution instance.\n\n    beta.alpha: number\n        First shape parameter. If set, the value must be greater than `0`.\n\n    beta.beta: number\n        Second shape parameter. If set, the value must be greater than `0`.\n\n    beta.entropy: number\n        Read-only property which returns the differential entropy.\n\n    beta.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    beta.mean: number\n        Read-only property which returns the expected value.\n\n    beta.median: number\n        Read-only property which returns the median.\n\n    beta.mode: number\n        Read-only property which returns the mode.\n\n    beta.skewness: number\n        Read-only property which returns the skewness.\n\n    beta.stdev: number\n        Read-only property which returns the standard deviation.\n\n    beta.variance: number\n        Read-only property which returns the variance.\n\n    beta.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    beta.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    beta.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    beta.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    beta.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    beta.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var beta = base.dists.beta.Beta( 1.0, 1.0 );\n    > beta.alpha\n    1.0\n    > beta.beta\n    1.0\n    > beta.entropy\n    0.0\n    > beta.kurtosis\n    -1.2\n    > beta.mean\n    0.5\n    > beta.median\n    0.5\n    > beta.mode\n    NaN\n    > beta.skewness\n    0.0\n    > beta.stdev\n    ~0.289\n    > beta.variance\n    ~0.0833\n    > beta.cdf( 0.8 )\n    0.8\n    > beta.logcdf( 0.8 )\n    ~-0.223\n    > beta.logpdf( 1.0 )\n    0.0\n    > beta.mgf( 3.14 )\n    ~7.0394\n    > beta.pdf( 1.0 )\n    1.0\n    > beta.quantile( 0.8 )\n    0.8\n\n","base.dists.beta.cdf":"\nbase.dists.beta.cdf( x, α, β )\n    Evaluates the cumulative distribution function (CDF) for a beta distribution\n    with first shape parameter `α` and second shape parameter `β` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.beta.cdf( 0.5, 1.0, 1.0 )\n    0.5\n    > y = base.dists.beta.cdf( 0.5, 2.0, 4.0 )\n    ~0.813\n    > y = base.dists.beta.cdf( 0.2, 2.0, 2.0 )\n    ~0.104\n    > y = base.dists.beta.cdf( 0.8, 4.0, 4.0 )\n    ~0.967\n    > y = base.dists.beta.cdf( -0.5, 4.0, 2.0 )\n    0.0\n    > y = base.dists.beta.cdf( 1.5, 4.0, 2.0 )\n    1.0\n\n    > y = base.dists.beta.cdf( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.beta.cdf( 2.0, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.beta.cdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.beta.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.beta.cdf( 0.0, 1.0, NaN )\n    NaN\n\n\nbase.dists.beta.cdf.factory( α, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a beta distribution with first shape parameter `α` and second shape\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.beta.cdf.factory( 0.5, 0.5 );\n    > var y = mycdf( 0.8 )\n    ~0.705\n    > y = mycdf( 0.3 )\n    ~0.369\n\n","base.dists.beta.cdf.factory":"\nbase.dists.beta.cdf.factory( α, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a beta distribution with first shape parameter `α` and second shape\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.beta.cdf.factory( 0.5, 0.5 );\n    > var y = mycdf( 0.8 )\n    ~0.705\n    > y = mycdf( 0.3 )\n    ~0.369","base.dists.beta.entropy":"\nbase.dists.beta.entropy( α, β )\n    Returns the differential entropy of a beta distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Differential entropy.\n\n    Examples\n    --------\n    > var v = base.dists.beta.entropy( 1.0, 1.0 )\n    0.0\n    > v = base.dists.beta.entropy( 4.0, 12.0 )\n    ~-0.869\n    > v = base.dists.beta.entropy( 8.0, 2.0 )\n    ~-0.795\n\n    > v = base.dists.beta.entropy( 1.0, -0.1 )\n    NaN\n    > v = base.dists.beta.entropy( -0.1, 1.0 )\n    NaN\n\n    > v = base.dists.beta.entropy( 2.0, NaN )\n    NaN\n    > v = base.dists.beta.entropy( NaN, 2.0 )\n    NaN\n\n","base.dists.beta.kurtosis":"\nbase.dists.beta.kurtosis( α, β )\n    Returns the excess kurtosis of a beta distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.beta.kurtosis( 1.0, 1.0 )\n    -1.2\n    > v = base.dists.beta.kurtosis( 4.0, 12.0 )\n    ~0.082\n    > v = base.dists.beta.kurtosis( 8.0, 2.0 )\n    ~0.490\n\n    > v = base.dists.beta.kurtosis( 1.0, -0.1 )\n    NaN\n    > v = base.dists.beta.kurtosis( -0.1, 1.0 )\n    NaN\n\n    > v = base.dists.beta.kurtosis( 2.0, NaN )\n    NaN\n    > v = base.dists.beta.kurtosis( NaN, 2.0 )\n    NaN\n\n","base.dists.beta.logcdf":"\nbase.dists.beta.logcdf( x, α, β )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a beta distribution with first shape parameter `α` and second\n    shape parameter `β` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.beta.logcdf( 0.5, 1.0, 1.0 )\n    ~-0.693\n    > y = base.dists.beta.logcdf( 0.5, 2.0, 4.0 )\n    ~-0.208\n    > y = base.dists.beta.logcdf( 0.2, 2.0, 2.0 )\n    ~-2.263\n    > y = base.dists.beta.logcdf( 0.8, 4.0, 4.0 )\n    ~-0.034\n    > y = base.dists.beta.logcdf( -0.5, 4.0, 2.0 )\n    -Infinity\n    > y = base.dists.beta.logcdf( 1.5, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.beta.logcdf( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.beta.logcdf( 2.0, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.beta.logcdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.beta.logcdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.beta.logcdf( 0.0, 1.0, NaN )\n    NaN\n\n\nbase.dists.beta.logcdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a beta distribution with first shape\n    parameter `α` and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.beta.logcdf.factory( 0.5, 0.5 );\n    > var y = mylogcdf( 0.8 )\n    ~-0.35\n    > y = mylogcdf( 0.3 )\n    ~-0.997\n\n","base.dists.beta.logcdf.factory":"\nbase.dists.beta.logcdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a beta distribution with first shape\n    parameter `α` and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.beta.logcdf.factory( 0.5, 0.5 );\n    > var y = mylogcdf( 0.8 )\n    ~-0.35\n    > y = mylogcdf( 0.3 )\n    ~-0.997","base.dists.beta.logpdf":"\nbase.dists.beta.logpdf( x, α, β )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a beta distribution with first shape parameter `α` and second shape\n    parameter `β` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Natural logarithm of the PDF.\n\n    Examples\n    --------\n    > var y = base.dists.beta.logpdf( 0.5, 1.0, 1.0 )\n    0.0\n    > y = base.dists.beta.logpdf( 0.5, 2.0, 4.0 )\n    ~0.223\n    > y = base.dists.beta.logpdf( 0.2, 2.0, 2.0 )\n    ~-0.041\n    > y = base.dists.beta.logpdf( 0.8, 4.0, 4.0 )\n    ~-0.556\n    > y = base.dists.beta.logpdf( -0.5, 4.0, 2.0 )\n    -Infinity\n    > y = base.dists.beta.logpdf( 1.5, 4.0, 2.0 )\n    -Infinity\n\n    > y = base.dists.beta.logpdf( 0.5, -1.0, 0.5 )\n    NaN\n    > y = base.dists.beta.logpdf( 0.5, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.beta.logpdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.beta.logpdf( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.dists.beta.logpdf( 0.5, 1.0, NaN )\n    NaN\n\n\nbase.dists.beta.logpdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a beta distribution with first shape parameter `α`\n    and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    fcn: Function\n        Function to evaluate the natural logarithm of the PDF.\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.beta.logpdf.factory( 0.5, 0.5 );\n    > var y = mylogpdf( 0.8 )\n    ~-0.228\n    > y = mylogpdf( 0.3 )\n    ~-0.364\n\n","base.dists.beta.logpdf.factory":"\nbase.dists.beta.logpdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a beta distribution with first shape parameter `α`\n    and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    fcn: Function\n        Function to evaluate the natural logarithm of the PDF.\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.beta.logpdf.factory( 0.5, 0.5 );\n    > var y = mylogpdf( 0.8 )\n    ~-0.228\n    > y = mylogpdf( 0.3 )\n    ~-0.364","base.dists.beta.mean":"\nbase.dists.beta.mean( α, β )\n    Returns the expected value of a beta distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.beta.mean( 1.0, 1.0 )\n    0.5\n    > v = base.dists.beta.mean( 4.0, 12.0 )\n    0.25\n    > v = base.dists.beta.mean( 8.0, 2.0 )\n    0.8\n\n","base.dists.beta.median":"\nbase.dists.beta.median( α, β )\n    Returns the median of a beta distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.beta.median( 1.0, 1.0 )\n    0.5\n    > v = base.dists.beta.median( 4.0, 12.0 )\n    ~0.239\n    > v = base.dists.beta.median( 8.0, 2.0 )\n    ~0.820\n\n    > v = base.dists.beta.median( 1.0, -0.1 )\n    NaN\n    > v = base.dists.beta.median( -0.1, 1.0 )\n    NaN\n\n    > v = base.dists.beta.median( 2.0, NaN )\n    NaN\n    > v = base.dists.beta.median( NaN, 2.0 )\n    NaN\n\n","base.dists.beta.mgf":"\nbase.dists.beta.mgf( t, α, β )\n    Evaluates the moment-generating function (MGF) for a beta distribution with\n    first shape parameter `α` and second shape parameter `β` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.beta.mgf( 0.5, 1.0, 1.0 )\n    ~1.297\n    > y = base.dists.beta.mgf( 0.5, 2.0, 4.0 )\n    ~1.186\n    > y = base.dists.beta.mgf( 3.0, 2.0, 2.0 )\n    ~5.575\n    > y = base.dists.beta.mgf( -0.8, 4.0, 4.0 )\n    ~0.676\n\n    > y = base.dists.beta.mgf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.beta.mgf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.beta.mgf( 0.0, 1.0, NaN )\n    NaN\n\n    > y = base.dists.beta.mgf( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.beta.mgf( 2.0, 0.0, 0.5 )\n    NaN\n\n    > y = base.dists.beta.mgf( 2.0, 0.5, -1.0 )\n    NaN\n    > y = base.dists.beta.mgf( 2.0, 0.5, 0.0 )\n    NaN\n\n\nbase.dists.beta.mgf.factory( α, β )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    beta distribution with first shape parameter `α` and second shape parameter\n    `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.beta.mgf.factory( 0.5, 0.5 );\n    > var y = myMGF( 0.8 )\n    ~1.552\n    > y = myMGF( 0.3 )\n    ~1.168\n\n","base.dists.beta.mgf.factory":"\nbase.dists.beta.mgf.factory( α, β )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    beta distribution with first shape parameter `α` and second shape parameter\n    `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.beta.mgf.factory( 0.5, 0.5 );\n    > var y = myMGF( 0.8 )\n    ~1.552\n    > y = myMGF( 0.3 )\n    ~1.168","base.dists.beta.mode":"\nbase.dists.beta.mode( α, β )\n    Returns the mode of a beta distribution.\n\n    If `α <= 1` or `β <= 1`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.beta.mode( 4.0, 12.0 )\n    ~0.214\n    > v = base.dists.beta.mode( 8.0, 2.0 )\n    ~0.875\n    > v = base.dists.beta.mode( 1.0, 1.0 )\n    NaN\n\n","base.dists.beta.pdf":"\nbase.dists.beta.pdf( x, α, β )\n    Evaluates the probability density function (PDF) for a beta distribution\n    with first shape parameter `α` and second shape parameter `β` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.beta.pdf( 0.5, 1.0, 1.0 )\n    1.0\n    > y = base.dists.beta.pdf( 0.5, 2.0, 4.0 )\n    1.25\n    > y = base.dists.beta.pdf( 0.2, 2.0, 2.0 )\n    ~0.96\n    > y = base.dists.beta.pdf( 0.8, 4.0, 4.0 )\n    ~0.573\n    > y = base.dists.beta.pdf( -0.5, 4.0, 2.0 )\n    0.0\n    > y = base.dists.beta.pdf( 1.5, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.beta.pdf( 0.5, -1.0, 0.5 )\n    NaN\n    > y = base.dists.beta.pdf( 0.5, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.beta.pdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.beta.pdf( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.dists.beta.pdf( 0.5, 1.0, NaN )\n    NaN\n\n\nbase.dists.beta.pdf.factory( α, β )\n    Returns a function for evaluating the probability density function (PDF) of\n    a beta distribution with first shape parameter `α` and second shape\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var mypdf = base.dists.beta.pdf.factory( 0.5, 0.5 );\n    > var y = mypdf( 0.8 )\n    ~0.796\n    > y = mypdf( 0.3 )\n    ~0.695\n\n","base.dists.beta.pdf.factory":"\nbase.dists.beta.pdf.factory( α, β )\n    Returns a function for evaluating the probability density function (PDF) of\n    a beta distribution with first shape parameter `α` and second shape\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var mypdf = base.dists.beta.pdf.factory( 0.5, 0.5 );\n    > var y = mypdf( 0.8 )\n    ~0.796\n    > y = mypdf( 0.3 )\n    ~0.695","base.dists.beta.quantile":"\nbase.dists.beta.quantile( p, α, β )\n    Evaluates the quantile function for a beta distribution with first shape\n    parameter `α` and second shape parameter `β` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input value (probability).\n\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.beta.quantile( 0.8, 2.0, 1.0 )\n    ~0.894\n    > y = base.dists.beta.quantile( 0.5, 4.0, 2.0 )\n    ~0.686\n    > y = base.dists.beta.quantile( 1.1, 1.0, 1.0 )\n    NaN\n    > y = base.dists.beta.quantile( -0.2, 1.0, 1.0 )\n    NaN\n\n    > y = base.dists.beta.quantile( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.beta.quantile( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.dists.beta.quantile( 0.5, 1.0, NaN )\n    NaN\n\n    > y = base.dists.beta.quantile( 0.5, -1.0, 1.0 )\n    NaN\n    > y = base.dists.beta.quantile( 0.5, 1.0, -1.0 )\n    NaN\n\n\nbase.dists.beta.quantile.factory( α, β )\n    Returns a function for evaluating the quantile function of a beta\n    distribution with first shape parameter `α` and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.beta.quantile.factory( 2.0, 2.0 );\n    > y = myquantile( 0.8 )\n    ~0.713\n    > y = myquantile( 0.4 )\n    ~0.433\n\n","base.dists.beta.quantile.factory":"\nbase.dists.beta.quantile.factory( α, β )\n    Returns a function for evaluating the quantile function of a beta\n    distribution with first shape parameter `α` and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.beta.quantile.factory( 2.0, 2.0 );\n    > y = myquantile( 0.8 )\n    ~0.713\n    > y = myquantile( 0.4 )\n    ~0.433","base.dists.beta.skewness":"\nbase.dists.beta.skewness( α, β )\n    Returns the skewness of a beta distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.beta.skewness( 1.0, 1.0 )\n    0.0\n    > v = base.dists.beta.skewness( 4.0, 12.0 )\n    ~0.529\n    > v = base.dists.beta.skewness( 8.0, 2.0 )\n    ~-0.829\n\n    > v = base.dists.beta.skewness( 1.0, -0.1 )\n    NaN\n    > v = base.dists.beta.skewness( -0.1, 1.0 )\n    NaN\n\n    > v = base.dists.beta.skewness( 2.0, NaN )\n    NaN\n    > v = base.dists.beta.skewness( NaN, 2.0 )\n    NaN\n\n","base.dists.beta.stdev":"\nbase.dists.beta.stdev( α, β )\n    Returns the standard deviation of a beta distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.beta.stdev( 1.0, 1.0 )\n    ~0.289\n    > v = base.dists.beta.stdev( 4.0, 12.0 )\n    ~0.105\n    > v = base.dists.beta.stdev( 8.0, 2.0 )\n    ~0.121\n\n    > v = base.dists.beta.stdev( 1.0, -0.1 )\n    NaN\n    > v = base.dists.beta.stdev( -0.1, 1.0 )\n    NaN\n\n    > v = base.dists.beta.stdev( 2.0, NaN )\n    NaN\n    > v = base.dists.beta.stdev( NaN, 2.0 )\n    NaN\n\n","base.dists.beta.variance":"\nbase.dists.beta.variance( α, β )\n    Returns the variance of a beta distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.beta.variance( 1.0, 1.0 )\n    ~0.083\n    > v = base.dists.beta.variance( 4.0, 12.0 )\n    ~0.011\n    > v = base.dists.beta.variance( 8.0, 2.0 )\n    ~0.015\n\n    > v = base.dists.beta.variance( 1.0, -0.1 )\n    NaN\n    > v = base.dists.beta.variance( -0.1, 1.0 )\n    NaN\n\n    > v = base.dists.beta.variance( 2.0, NaN )\n    NaN\n    > v = base.dists.beta.variance( NaN, 2.0 )\n    NaN\n\n","base.dists.betaprime.BetaPrime":"\nbase.dists.betaprime.BetaPrime( [α, β] )\n    Returns a beta prime distribution object.\n\n    Parameters\n    ----------\n    α: number (optional)\n        First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n    β: number (optional)\n        Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    betaprime: Object\n        Distribution instance.\n\n    betaprime.alpha: number\n        First shape parameter. If set, the value must be greater than `0`.\n\n    betaprime.beta: number\n        Second shape parameter. If set, the value must be greater than `0`.\n\n    betaprime.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    betaprime.mean: number\n        Read-only property which returns the expected value.\n\n    betaprime.mode: number\n        Read-only property which returns the mode.\n\n    betaprime.skewness: number\n        Read-only property which returns the skewness.\n\n    betaprime.stdev: number\n        Read-only property which returns the standard deviation.\n\n    betaprime.variance: number\n        Read-only property which returns the variance.\n\n    betaprime.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    betaprime.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    betaprime.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    betaprime.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    betaprime.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var betaprime = base.dists.betaprime.BetaPrime( 6.0, 5.0 );\n    > betaprime.alpha\n    6.0\n    > betaprime.beta\n    5.0\n    > betaprime.kurtosis\n    44.4\n    > betaprime.mean\n    1.5\n    > betaprime.mode\n    ~0.833\n    > betaprime.skewness\n    ~3.578\n    > betaprime.stdev\n    ~1.118\n    > betaprime.variance\n    1.25\n    > betaprime.cdf( 0.8 )\n    ~0.25\n    > betaprime.logcdf( 0.8 )\n    ~-1.387\n    > betaprime.logpdf( 1.0 )\n    ~-0.486\n    > betaprime.pdf( 1.0 )\n    ~0.615\n    > betaprime.quantile( 0.8 )\n    ~2.06\n\n","base.dists.betaprime.cdf":"\nbase.dists.betaprime.cdf( x, α, β )\n    Evaluates the cumulative distribution function (CDF) for a beta prime\n    distribution with first shape parameter `α` and second shape parameter `β`\n    at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.betaprime.cdf( 0.5, 1.0, 1.0 )\n    ~0.333\n    > y = base.dists.betaprime.cdf( 0.5, 2.0, 4.0 )\n    ~0.539\n    > y = base.dists.betaprime.cdf( 0.2, 2.0, 2.0 )\n    ~0.074\n    > y = base.dists.betaprime.cdf( 0.8, 4.0, 4.0 )\n    ~0.38\n    > y = base.dists.betaprime.cdf( -0.5, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.betaprime.cdf( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.betaprime.cdf( 2.0, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.betaprime.cdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.betaprime.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.betaprime.cdf( 0.0, 1.0, NaN )\n    NaN\n\n\nbase.dists.betaprime.cdf.factory( α, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a beta prime distribution with first shape parameter `α` and second shape\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.betaprime.cdf.factory( 0.5, 0.5 );\n    > var y = mycdf( 0.8 )\n    ~0.465\n    > y = mycdf( 0.3 )\n    ~0.319\n\n","base.dists.betaprime.cdf.factory":"\nbase.dists.betaprime.cdf.factory( α, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a beta prime distribution with first shape parameter `α` and second shape\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.betaprime.cdf.factory( 0.5, 0.5 );\n    > var y = mycdf( 0.8 )\n    ~0.465\n    > y = mycdf( 0.3 )\n    ~0.319","base.dists.betaprime.kurtosis":"\nbase.dists.betaprime.kurtosis( α, β )\n    Returns the excess kurtosis of a beta prime distribution.\n\n    If `α <= 0` or `β <= 4`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.betaprime.kurtosis( 2.0, 6.0 )\n    ~26.143\n    > v = base.dists.betaprime.kurtosis( 4.0, 12.0 )\n    ~5.764\n    > v = base.dists.betaprime.kurtosis( 8.0, 6.0 )\n    ~19.962\n\n    > v = base.dists.betaprime.kurtosis( 1.0, 2.8 )\n    NaN\n    > v = base.dists.betaprime.kurtosis( 1.0, -0.1 )\n    NaN\n    > v = base.dists.betaprime.kurtosis( -0.1, 5.0 )\n    NaN\n\n    > v = base.dists.betaprime.kurtosis( 2.0, NaN )\n    NaN\n    > v = base.dists.betaprime.kurtosis( NaN, 6.0 )\n    NaN\n\n","base.dists.betaprime.logcdf":"\nbase.dists.betaprime.logcdf( x, α, β )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a beta prime distribution with first shape parameter `α` and\n    second shape parameter `β` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.betaprime.logcdf( 0.5, 1.0, 1.0 )\n    ~-1.099\n    > y = base.dists.betaprime.logcdf( 0.5, 2.0, 4.0 )\n    ~-0.618\n    > y = base.dists.betaprime.logcdf( 0.2, 2.0, 2.0 )\n    ~-2.603\n    > y = base.dists.betaprime.logcdf( 0.8, 4.0, 4.0 )\n    ~-0.968\n    > y = base.dists.betaprime.logcdf( -0.5, 4.0, 2.0 )\n    -Infinity\n\n    > y = base.dists.betaprime.logcdf( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.betaprime.logcdf( 2.0, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.betaprime.logcdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.betaprime.logcdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.betaprime.logcdf( 0.0, 1.0, NaN )\n    NaN\n\n\nbase.dists.betaprime.logcdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a beta prime distribution with first shape\n    parameter `α` and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.betaprime.logcdf.factory( 0.5, 0.5 );\n    > var y = mylogcdf( 0.8 )\n    ~-0.767\n    > y = mylogcdf( 0.3 )\n    ~-1.143\n\n","base.dists.betaprime.logcdf.factory":"\nbase.dists.betaprime.logcdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a beta prime distribution with first shape\n    parameter `α` and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.betaprime.logcdf.factory( 0.5, 0.5 );\n    > var y = mylogcdf( 0.8 )\n    ~-0.767\n    > y = mylogcdf( 0.3 )\n    ~-1.143","base.dists.betaprime.logpdf":"\nbase.dists.betaprime.logpdf( x, α, β )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a beta prime distribution with first shape parameter `α` and second\n    shape parameter `β` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Natural logarithm of the PDF.\n\n    Examples\n    --------\n    > var y = base.dists.betaprime.logpdf( 0.5, 1.0, 1.0 )\n    ~-0.811\n    > y = base.dists.betaprime.logpdf( 0.5, 2.0, 4.0 )\n    ~-0.13\n    > y = base.dists.betaprime.logpdf( 0.2, 2.0, 2.0 )\n    ~-0.547\n    > y = base.dists.betaprime.logpdf( 0.8, 4.0, 4.0 )\n    ~-0.43\n    > y = base.dists.betaprime.logpdf( -0.5, 4.0, 2.0 )\n    -Infinity\n\n    > y = base.dists.betaprime.logpdf( 0.5, -1.0, 0.5 )\n    NaN\n    > y = base.dists.betaprime.logpdf( 0.5, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.betaprime.logpdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.betaprime.logpdf( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.dists.betaprime.logpdf( 0.5, 1.0, NaN )\n    NaN\n\n\nbase.dists.betaprime.logpdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a beta prime distribution with first shape\n    parameter `α` and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    fcn: Function\n        Function to evaluate the natural logarithm of the PDF.\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.betaprime.logpdf.factory( 0.5, 0.5 );\n    > var y = mylogpdf( 0.8 )\n    ~-1.62\n    > y = mylogpdf( 0.3 )\n    ~-0.805\n\n","base.dists.betaprime.logpdf.factory":"\nbase.dists.betaprime.logpdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a beta prime distribution with first shape\n    parameter `α` and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    fcn: Function\n        Function to evaluate the natural logarithm of the PDF.\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.betaprime.logpdf.factory( 0.5, 0.5 );\n    > var y = mylogpdf( 0.8 )\n    ~-1.62\n    > y = mylogpdf( 0.3 )\n    ~-0.805","base.dists.betaprime.mean":"\nbase.dists.betaprime.mean( α, β )\n    Returns the expected value of a beta prime distribution.\n\n    If `α <= 0` or `β <= 1`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.betaprime.mean( 1.0, 2.0 )\n    1.0\n    > v = base.dists.betaprime.mean( 4.0, 12.0 )\n    ~0.364\n    > v = base.dists.betaprime.mean( 8.0, 2.0 )\n    8.0\n\n","base.dists.betaprime.mode":"\nbase.dists.betaprime.mode( α, β )\n    Returns the mode of a beta prime distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.betaprime.mode( 1.0, 2.0 )\n    0.0\n    > v = base.dists.betaprime.mode( 4.0, 12.0 )\n    ~0.231\n    > v = base.dists.betaprime.mode( 8.0, 2.0 )\n    ~2.333\n\n","base.dists.betaprime.pdf":"\nbase.dists.betaprime.pdf( x, α, β )\n    Evaluates the probability density function (PDF) for a beta prime\n    distribution  with first shape parameter `α` and second shape parameter `β`\n    at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.betaprime.pdf( 0.5, 1.0, 1.0 )\n    ~0.444\n    > y = base.dists.betaprime.pdf( 0.5, 2.0, 4.0 )\n    ~0.878\n    > y = base.dists.betaprime.pdf( 0.2, 2.0, 2.0 )\n    ~0.579\n    > y = base.dists.betaprime.pdf( 0.8, 4.0, 4.0 )\n    ~0.65\n    > y = base.dists.betaprime.pdf( -0.5, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.betaprime.pdf( 0.5, -1.0, 0.5 )\n    NaN\n    > y = base.dists.betaprime.pdf( 0.5, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.betaprime.pdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.betaprime.pdf( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.dists.betaprime.pdf( 0.5, 1.0, NaN )\n    NaN\n\n\nbase.dists.betaprime.pdf.factory( α, β )\n    Returns a function for evaluating the probability density function (PDF) of\n    a beta prime distribution with first shape parameter `α` and second shape\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var mypdf = base.dists.betaprime.pdf.factory( 0.5, 0.5 );\n    > var y = mypdf( 0.8 )\n    ~0.198\n    > y = mypdf( 0.3 )\n    ~0.447\n\n","base.dists.betaprime.pdf.factory":"\nbase.dists.betaprime.pdf.factory( α, β )\n    Returns a function for evaluating the probability density function (PDF) of\n    a beta prime distribution with first shape parameter `α` and second shape\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var mypdf = base.dists.betaprime.pdf.factory( 0.5, 0.5 );\n    > var y = mypdf( 0.8 )\n    ~0.198\n    > y = mypdf( 0.3 )\n    ~0.447","base.dists.betaprime.quantile":"\nbase.dists.betaprime.quantile( p, α, β )\n    Evaluates the quantile function for a beta prime distribution with first\n    shape parameter `α` and second shape parameter `β` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input value (probability).\n\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.betaprime.quantile( 0.8, 2.0, 1.0 )\n    ~8.472\n    > y = base.dists.betaprime.quantile( 0.5, 4.0, 2.0 )\n    ~2.187\n    > y = base.dists.betaprime.quantile( 1.1, 1.0, 1.0 )\n    NaN\n    > y = base.dists.betaprime.quantile( -0.2, 1.0, 1.0 )\n    NaN\n\n    > y = base.dists.betaprime.quantile( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.betaprime.quantile( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.dists.betaprime.quantile( 0.5, 1.0, NaN )\n    NaN\n\n    > y = base.dists.betaprime.quantile( 0.5, -1.0, 1.0 )\n    NaN\n    > y = base.dists.betaprime.quantile( 0.5, 1.0, -1.0 )\n    NaN\n\n\nbase.dists.betaprime.quantile.factory( α, β )\n    Returns a function for evaluating the quantile function of a beta prime\n    distribution with first shape parameter `α` and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.betaprime.quantile.factory( 2.0, 2.0 );\n    > y = myQuantile( 0.8 )\n    ~2.483\n    > y = myQuantile( 0.4 )\n    ~0.763\n\n","base.dists.betaprime.quantile.factory":"\nbase.dists.betaprime.quantile.factory( α, β )\n    Returns a function for evaluating the quantile function of a beta prime\n    distribution with first shape parameter `α` and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.betaprime.quantile.factory( 2.0, 2.0 );\n    > y = myQuantile( 0.8 )\n    ~2.483\n    > y = myQuantile( 0.4 )\n    ~0.763","base.dists.betaprime.skewness":"\nbase.dists.betaprime.skewness( α, β )\n    Returns the skewness of a beta prime distribution.\n\n    If `α <= 0` or `β <= 3`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.betaprime.skewness( 2.0, 4.0 )\n    ~6.261\n    > v = base.dists.betaprime.skewness( 4.0, 12.0 )\n    ~1.724\n    > v = base.dists.betaprime.skewness( 8.0, 4.0 )\n    ~5.729\n\n    > v = base.dists.betaprime.skewness( 1.0, 2.8 )\n    NaN\n    > v = base.dists.betaprime.skewness( 1.0, -0.1 )\n    NaN\n    > v = base.dists.betaprime.skewness( -0.1, 4.0 )\n    NaN\n\n    > v = base.dists.betaprime.skewness( 2.0, NaN )\n    NaN\n    > v = base.dists.betaprime.skewness( NaN, 4.0 )\n    NaN\n\n","base.dists.betaprime.stdev":"\nbase.dists.betaprime.stdev( α, β )\n    Returns the standard deviation of a beta prime distribution.\n\n    If `α <= 0` or `β <= 2`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.betaprime.stdev( 1.0, 2.5 )\n    ~1.491\n    > v = base.dists.betaprime.stdev( 4.0, 12.0 )\n    ~0.223\n    > v = base.dists.betaprime.stdev( 8.0, 2.5 )\n    ~8.219\n\n    > v = base.dists.betaprime.stdev( 8.0, 1.0 )\n    NaN\n    > v = base.dists.betaprime.stdev( 1.0, -0.1 )\n    NaN\n    > v = base.dists.betaprime.stdev( -0.1, 3.0 )\n    NaN\n\n    > v = base.dists.betaprime.stdev( 2.0, NaN )\n    NaN\n    > v = base.dists.betaprime.stdev( NaN, 3.0 )\n    NaN\n\n","base.dists.betaprime.variance":"\nbase.dists.betaprime.variance( α, β )\n    Returns the variance of a beta prime distribution.\n\n    If `α <= 0` or `β <= 2`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.betaprime.variance( 1.0, 2.5 )\n    ~2.222\n    > v = base.dists.betaprime.variance( 4.0, 12.0 )\n    ~0.05\n    > v = base.dists.betaprime.variance( 8.0, 2.5 )\n    ~67.556\n\n    > v = base.dists.betaprime.variance( 8.0, 1.0 )\n    NaN\n    > v = base.dists.betaprime.variance( 1.0, -0.1 )\n    NaN\n    > v = base.dists.betaprime.variance( -0.1, 3.0 )\n    NaN\n\n    > v = base.dists.betaprime.variance( 2.0, NaN )\n    NaN\n    > v = base.dists.betaprime.variance( NaN, 3.0 )\n    NaN\n\n","base.dists.binomial.Binomial":"\nbase.dists.binomial.Binomial( [n, p] )\n    Returns a binomial distribution object.\n\n    Parameters\n    ----------\n    n: integer (optional)\n        Number of trials. Must be a positive integer. Default: `1`.\n\n    p: number (optional)\n        Success probability. Must be a number between `0` and `1`. Default:\n        `0.5`.\n\n    Returns\n    -------\n    binomial: Object\n        Distribution instance.\n\n    binomial.n: number\n        Number of trials. If set, the value must be a positive integer.\n\n    binomial.p: number\n        Success probability. If set, the value must be a number between `0` and\n        `1`.\n\n    binomial.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    binomial.mean: number\n        Read-only property which returns the expected value.\n\n    binomial.median: number\n        Read-only property which returns the median.\n\n    binomial.mode: number\n        Read-only property which returns the mode.\n\n    binomial.skewness: number\n        Read-only property which returns the skewness.\n\n    binomial.stdev: number\n        Read-only property which returns the standard deviation.\n\n    binomial.variance: number\n        Read-only property which returns the variance.\n\n    binomial.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    binomial.logpmf: Function\n        Evaluates the natural logarithm of the probability mass function (PMF).\n\n    binomial.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    binomial.pmf: Function\n        Evaluates the probability mass function (PMF).\n\n    binomial.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var binomial = base.dists.binomial.Binomial( 8, 0.5 );\n    > binomial.n\n    8.0\n    > binomial.p\n    0.5\n    > binomial.kurtosis\n    -0.25\n    > binomial.mean\n    4.0\n    > binomial.median\n    4.0\n    > binomial.mode\n    4.0\n    > binomial.skewness\n    0.0\n    > binomial.stdev\n    ~1.414\n    > binomial.variance\n    2.0\n    > binomial.cdf( 2.9 )\n    ~0.145\n    > binomial.logpmf( 3.0 )\n    ~-1.52\n    > binomial.mgf( 0.2 )\n    ~2.316\n    > binomial.pmf( 3.0 )\n    ~0.219\n    > binomial.quantile( 0.8 )\n    5.0\n\n","base.dists.binomial.cdf":"\nbase.dists.binomial.cdf( x, n, p )\n    Evaluates the cumulative distribution function (CDF) for a binomial\n    distribution with number of trials `n` and success probability `p` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.binomial.cdf( 3.0, 20, 0.2 )\n    ~0.411\n    > y = base.dists.binomial.cdf( 21.0, 20, 0.2 )\n    1.0\n    > y = base.dists.binomial.cdf( 5.0, 10, 0.4 )\n    ~0.834\n    > y = base.dists.binomial.cdf( 0.0, 10, 0.4 )\n    ~0.006\n    > y = base.dists.binomial.cdf( NaN, 20, 0.5 )\n    NaN\n    > y = base.dists.binomial.cdf( 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.binomial.cdf( 0.0, 20, NaN )\n    NaN\n    > y = base.dists.binomial.cdf( 2.0, 1.5, 0.5 )\n    NaN\n    > y = base.dists.binomial.cdf( 2.0, -2.0, 0.5 )\n    NaN\n    > y = base.dists.binomial.cdf( 2.0, 20, -1.0 )\n    NaN\n    > y = base.dists.binomial.cdf( 2.0, 20, 1.5 )\n    NaN\n\n\nbase.dists.binomial.cdf.factory( n, p )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a binomial distribution with number of trials `n` and success probability\n    `p`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.binomial.cdf.factory( 10, 0.5 );\n    > var y = mycdf( 3.0 )\n    ~0.172\n    > y = mycdf( 1.0 )\n    ~0.011\n\n","base.dists.binomial.cdf.factory":"\nbase.dists.binomial.cdf.factory( n, p )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a binomial distribution with number of trials `n` and success probability\n    `p`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.binomial.cdf.factory( 10, 0.5 );\n    > var y = mycdf( 3.0 )\n    ~0.172\n    > y = mycdf( 1.0 )\n    ~0.011","base.dists.binomial.entropy":"\nbase.dists.binomial.entropy( n, p )\n    Returns the entropy of a binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.binomial.entropy( 100, 0.1 )\n    ~2.511\n    > v = base.dists.binomial.entropy( 20, 0.5 )\n    ~2.223\n    > v = base.dists.binomial.entropy( 10.3, 0.5 )\n    NaN\n    > v = base.dists.binomial.entropy( 20, 1.1 )\n    NaN\n    > v = base.dists.binomial.entropy( 20, NaN )\n    NaN\n\n","base.dists.binomial.kurtosis":"\nbase.dists.binomial.kurtosis( n, p )\n    Returns the excess kurtosis of a binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.binomial.kurtosis( 100, 0.1 )\n    ~0.051\n    > v = base.dists.binomial.kurtosis( 20, 0.5 )\n    ~-0.1\n    > v = base.dists.binomial.kurtosis( 10.3, 0.5 )\n    NaN\n    > v = base.dists.binomial.kurtosis( 20, 1.1 )\n    NaN\n    > v = base.dists.binomial.kurtosis( 20, NaN )\n    NaN\n\n","base.dists.binomial.logpmf":"\nbase.dists.binomial.logpmf( x, n, p )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    binomial distribution with number of trials `n` and success probability `p`\n    at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPMF.\n\n    Examples\n    --------\n    > var y = base.dists.binomial.logpmf( 3.0, 20, 0.2 )\n    ~-1.583\n    > y = base.dists.binomial.logpmf( 21.0, 20, 0.2 )\n    -Infinity\n    > y = base.dists.binomial.logpmf( 5.0, 10, 0.4 )\n    ~-1.606\n    > y = base.dists.binomial.logpmf( 0.0, 10, 0.4 )\n    ~-5.108\n    > y = base.dists.binomial.logpmf( NaN, 20, 0.5 )\n    NaN\n    > y = base.dists.binomial.logpmf( 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.binomial.logpmf( 0.0, 20, NaN )\n    NaN\n    > y = base.dists.binomial.logpmf( 2.0, 1.5, 0.5 )\n    NaN\n    > y = base.dists.binomial.logpmf( 2.0, -2.0, 0.5 )\n    NaN\n    > y = base.dists.binomial.logpmf( 2.0, 20, -1.0 )\n    NaN\n    > y = base.dists.binomial.logpmf( 2.0, 20, 1.5 )\n    NaN\n\n\nbase.dists.binomial.logpmf.factory( n, p )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a binomial distribution with number of trials `n` and\n    success probability `p`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogpmf = base.dists.binomial.logpmf.factory( 10, 0.5 );\n    > var y = mylogpmf( 3.0 )\n    ~-2.144\n    > y = mylogpmf( 5.0 )\n    ~-1.402\n\n","base.dists.binomial.logpmf.factory":"\nbase.dists.binomial.logpmf.factory( n, p )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a binomial distribution with number of trials `n` and\n    success probability `p`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogpmf = base.dists.binomial.logpmf.factory( 10, 0.5 );\n    > var y = mylogpmf( 3.0 )\n    ~-2.144\n    > y = mylogpmf( 5.0 )\n    ~-1.402","base.dists.binomial.mean":"\nbase.dists.binomial.mean( n, p )\n    Returns the expected value of a binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.binomial.mean( 100, 0.1 )\n    10.0\n    > v = base.dists.binomial.mean( 20, 0.5 )\n    10.0\n    > v = base.dists.binomial.mean( 10.3, 0.5 )\n    NaN\n    > v = base.dists.binomial.mean( 20, 1.1 )\n    NaN\n    > v = base.dists.binomial.mean( 20, NaN )\n    NaN\n\n","base.dists.binomial.median":"\nbase.dists.binomial.median( n, p )\n    Returns the median of a binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.binomial.median( 100, 0.1 )\n    10\n    > v = base.dists.binomial.median( 20, 0.5 )\n    10\n    > v = base.dists.binomial.median( 10.3, 0.5 )\n    NaN\n    > v = base.dists.binomial.median( 20, 1.1 )\n    NaN\n    > v = base.dists.binomial.median( 20, NaN )\n    NaN\n\n","base.dists.binomial.mgf":"\nbase.dists.binomial.mgf( t, n, p )\n    Evaluates the moment-generating function (MGF) for a binomial distribution\n    with number of trials `n` and success probability `p` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.binomial.mgf( 0.5, 20, 0.2 )\n    ~11.471\n    > y = base.dists.binomial.mgf( 5.0, 20, 0.2 )\n    ~4.798e+29\n    > y = base.dists.binomial.mgf( 0.9, 10, 0.4 )\n    ~99.338\n    > y = base.dists.binomial.mgf( 0.0, 10, 0.4 )\n    1.0\n\n    > y = base.dists.binomial.mgf( NaN, 20, 0.5 )\n    NaN\n    > y = base.dists.binomial.mgf( 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.binomial.mgf( 0.0, 20, NaN )\n    NaN\n\n    > y = base.dists.binomial.mgf( 2.0, 1.5, 0.5 )\n    NaN\n    > y = base.dists.binomial.mgf( 2.0, -2.0, 0.5 )\n    NaN\n    > y = base.dists.binomial.mgf( 2.0, 20, -1.0 )\n    NaN\n    > y = base.dists.binomial.mgf( 2.0, 20, 1.5 )\n    NaN\n\n\nbase.dists.binomial.mgf.factory( n, p )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    binomial distribution with number of trials `n` and success probability `p`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.binomial.mgf.factory( 10, 0.5 );\n    > var y = myMGF( 0.3 )\n    ~5.013\n\n","base.dists.binomial.mgf.factory":"\nbase.dists.binomial.mgf.factory( n, p )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    binomial distribution with number of trials `n` and success probability `p`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.binomial.mgf.factory( 10, 0.5 );\n    > var y = myMGF( 0.3 )\n    ~5.013","base.dists.binomial.mode":"\nbase.dists.binomial.mode( n, p )\n    Returns the mode of a binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.binomial.mode( 100, 0.1 )\n    10\n    > v = base.dists.binomial.mode( 20, 0.5 )\n    10\n    > v = base.dists.binomial.mode( 10.3, 0.5 )\n    NaN\n    > v = base.dists.binomial.mode( 20, 1.1 )\n    NaN\n    > v = base.dists.binomial.mode( 20, NaN )\n    NaN\n\n","base.dists.binomial.pmf":"\nbase.dists.binomial.pmf( x, n, p )\n    Evaluates the probability mass function (PMF) for a binomial distribution\n    with number of trials `n` and success probability `p` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated PMF.\n\n    Examples\n    --------\n    > var y = base.dists.binomial.pmf( 3.0, 20, 0.2 )\n    ~0.205\n    > y = base.dists.binomial.pmf( 21.0, 20, 0.2 )\n    0.0\n    > y = base.dists.binomial.pmf( 5.0, 10, 0.4 )\n    ~0.201\n    > y = base.dists.binomial.pmf( 0.0, 10, 0.4 )\n    ~0.006\n    > y = base.dists.binomial.pmf( NaN, 20, 0.5 )\n    NaN\n    > y = base.dists.binomial.pmf( 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.binomial.pmf( 0.0, 20, NaN )\n    NaN\n    > y = base.dists.binomial.pmf( 2.0, 1.5, 0.5 )\n    NaN\n    > y = base.dists.binomial.pmf( 2.0, -2.0, 0.5 )\n    NaN\n    > y = base.dists.binomial.pmf( 2.0, 20, -1.0 )\n    NaN\n    > y = base.dists.binomial.pmf( 2.0, 20, 1.5 )\n    NaN\n\n\nbase.dists.binomial.pmf.factory( n, p )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    binomial distribution with number of trials `n` and success probability `p`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var mypmf = base.dists.binomial.pmf.factory( 10, 0.5 );\n    > var y = mypmf( 3.0 )\n    ~0.117\n    > y = mypmf( 5.0 )\n    ~0.246\n\n","base.dists.binomial.pmf.factory":"\nbase.dists.binomial.pmf.factory( n, p )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    binomial distribution with number of trials `n` and success probability `p`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var mypmf = base.dists.binomial.pmf.factory( 10, 0.5 );\n    > var y = mypmf( 3.0 )\n    ~0.117\n    > y = mypmf( 5.0 )\n    ~0.246","base.dists.binomial.quantile":"\nbase.dists.binomial.quantile( r, n, p )\n    Evaluates the quantile function for a binomial distribution with number of\n    trials `n` and success probability `p` at a probability `r`.\n\n    If `r < 0` or `r > 1`, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    r: number\n        Input probability.\n\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.binomial.quantile( 0.4, 20, 0.2 )\n    3\n    > y = base.dists.binomial.quantile( 0.8, 20, 0.2 )\n    5\n    > y = base.dists.binomial.quantile( 0.5, 10, 0.4 )\n    4\n    > y = base.dists.binomial.quantile( 0.0, 10, 0.4 )\n    0\n    > y = base.dists.binomial.quantile( 1.0, 10, 0.4 )\n    10\n\n    > y = base.dists.binomial.quantile( NaN, 20, 0.5 )\n    NaN\n    > y = base.dists.binomial.quantile( 0.2, NaN, 0.5 )\n    NaN\n    > y = base.dists.binomial.quantile( 0.2, 20, NaN )\n    NaN\n\n    > y = base.dists.binomial.quantile( 0.5, 1.5, 0.5 )\n    NaN\n    > y = base.dists.binomial.quantile( 0.5, -2.0, 0.5 )\n    NaN\n\n    > y = base.dists.binomial.quantile( 0.5, 20, -1.0 )\n    NaN\n    > y = base.dists.binomial.quantile( 0.5, 20, 1.5 )\n    NaN\n\n\nbase.dists.binomial.quantile.factory( n, p )\n    Returns a function for evaluating the quantile function of a binomial\n    distribution with number of trials `n` and success probability `p`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.binomial.quantile.factory( 10, 0.5 );\n    > var y = myquantile( 0.1 )\n    3\n    > y = myquantile( 0.9 )\n    7\n\n","base.dists.binomial.quantile.factory":"\nbase.dists.binomial.quantile.factory( n, p )\n    Returns a function for evaluating the quantile function of a binomial\n    distribution with number of trials `n` and success probability `p`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.binomial.quantile.factory( 10, 0.5 );\n    > var y = myquantile( 0.1 )\n    3\n    > y = myquantile( 0.9 )\n    7","base.dists.binomial.skewness":"\nbase.dists.binomial.skewness( n, p )\n    Returns the skewness of a binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.binomial.skewness( 100, 0.1 )\n    ~0.267\n    > v = base.dists.binomial.skewness( 20, 0.5 )\n    0.0\n    > v = base.dists.binomial.skewness( 10.3, 0.5 )\n    NaN\n    > v = base.dists.binomial.skewness( 20, 1.1 )\n    NaN\n    > v = base.dists.binomial.skewness( 20, NaN )\n    NaN\n\n","base.dists.binomial.stdev":"\nbase.dists.binomial.stdev( n, p )\n    Returns the standard deviation of a binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.binomial.stdev( 100, 0.1 )\n    3.0\n    > v = base.dists.binomial.stdev( 20, 0.5 )\n    ~2.236\n    > v = base.dists.binomial.stdev( 10.3, 0.5 )\n    NaN\n    > v = base.dists.binomial.stdev( 20, 1.1 )\n    NaN\n    > v = base.dists.binomial.stdev( 20, NaN )\n    NaN\n\n","base.dists.binomial.variance":"\nbase.dists.binomial.variance( n, p )\n    Returns the variance of a binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.binomial.variance( 100, 0.1 )\n    9\n    > v = base.dists.binomial.variance( 20, 0.5 )\n    5\n    > v = base.dists.binomial.variance( 10.3, 0.5 )\n    NaN\n    > v = base.dists.binomial.variance( 20, 1.1 )\n    NaN\n    > v = base.dists.binomial.variance( 20, NaN )\n    NaN\n\n","base.dists.cauchy.Cauchy":"\nbase.dists.cauchy.Cauchy( [x0, Ɣ] )\n    Returns a Cauchy distribution object.\n\n    Parameters\n    ----------\n    x0: number (optional)\n        Location parameter. Default: `0.0`.\n\n    Ɣ: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    cauchy: Object\n        Distribution instance.\n\n    cauchy.x0: number\n        Location parameter.\n\n    cauchy.gamma: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    cauchy.entropy: number\n        Read-only property which returns the differential entropy.\n\n    cauchy.median: number\n        Read-only property which returns the median.\n\n    cauchy.mode: number\n        Read-only property which returns the mode.\n\n    cauchy.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    cauchy.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    cauchy.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    cauchy.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    cauchy.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var cauchy = base.dists.cauchy.Cauchy( 0.0, 1.0 );\n    > cauchy.x0\n    0.0\n    > cauchy.gamma\n    1.0\n    > cauchy.entropy\n    ~2.531\n    > cauchy.median\n    0.0\n    > cauchy.mode\n    0.0\n    > cauchy.cdf( 0.8 )\n    ~0.715\n    > cauchy.logcdf( 1.0 )\n    ~-0.288\n    > cauchy.logpdf( 1.0 )\n    ~-1.838\n    > cauchy.pdf( 1.0 )\n    ~0.159\n    > cauchy.quantile( 0.8 )\n    ~1.376\n\n","base.dists.cauchy.cdf":"\nbase.dists.cauchy.cdf( x, x0, Ɣ )\n    Evaluates the cumulative distribution function (CDF) for a Cauchy\n    distribution with location parameter `x0` and scale parameter `Ɣ` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `Ɣ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.cauchy.cdf( 4.0, 0.0, 2.0 )\n    ~0.852\n    > y = base.dists.cauchy.cdf( 1.0, 0.0, 2.0 )\n    ~0.648\n    > y = base.dists.cauchy.cdf( 1.0, 3.0, 2.0 )\n    0.25\n    > y = base.dists.cauchy.cdf( NaN, 0.0, 2.0 )\n    NaN\n    > y = base.dists.cauchy.cdf( 1.0, 2.0, NaN )\n    NaN\n    > y = base.dists.cauchy.cdf( 1.0, NaN, 3.0 )\n    NaN\n\n\nbase.dists.cauchy.cdf.factory( x0, Ɣ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Cauchy distribution with location parameter `x0` and scale parameter\n    `Ɣ`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.cauchy.cdf.factory( 1.5, 3.0 );\n    > var y = myCDF( 1.0 )\n    ~0.447\n\n","base.dists.cauchy.cdf.factory":"\nbase.dists.cauchy.cdf.factory( x0, Ɣ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Cauchy distribution with location parameter `x0` and scale parameter\n    `Ɣ`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.cauchy.cdf.factory( 1.5, 3.0 );\n    > var y = myCDF( 1.0 )\n    ~0.447","base.dists.cauchy.entropy":"\nbase.dists.cauchy.entropy( x0, Ɣ )\n    Returns the differential entropy of a Cauchy distribution (in nats).\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `Ɣ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.cauchy.entropy( 10.0, 7.0 )\n    ~4.477\n    > v = base.dists.cauchy.entropy( 22.0, 0.5 )\n    ~1.838\n    > v = base.dists.cauchy.entropy( 10.3, -0.5 )\n    NaN\n\n","base.dists.cauchy.logcdf":"\nbase.dists.cauchy.logcdf( x, x0, Ɣ )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (logCDF) for a Cauchy distribution with location parameter `x0` and scale\n    parameter `Ɣ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `Ɣ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Natural logarithm of the CDF.\n\n    Examples\n    --------\n    > var y = base.dists.cauchy.logcdf( 4.0, 0.0, 2.0 )\n    ~-0.16\n    > y = base.dists.cauchy.logcdf( 1.0, 0.0, 2.0 )\n    ~-0.435\n    > y = base.dists.cauchy.logcdf( 1.0, 3.0, 2.0 )\n    ~-1.386\n    > y = base.dists.cauchy.logcdf( NaN, 0.0, 2.0 )\n    NaN\n    > y = base.dists.cauchy.logcdf( 1.0, 2.0, NaN )\n    NaN\n    > y = base.dists.cauchy.logcdf( 1.0, NaN, 3.0 )\n    NaN\n\n\nbase.dists.cauchy.logcdf.factory( x0, Ɣ )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (logCDF) of a Cauchy distribution with location\n    parameter `x0` and scale parameter `Ɣ`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Function to evaluate the natural logarithm of CDF.\n\n    Examples\n    --------\n    > var mylogCDF = base.dists.cauchy.logcdf.factory( 1.5, 3.0 );\n    > var y = mylogCDF( 1.0 )\n    ~-0.804\n\n","base.dists.cauchy.logcdf.factory":"\nbase.dists.cauchy.logcdf.factory( x0, Ɣ )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (logCDF) of a Cauchy distribution with location\n    parameter `x0` and scale parameter `Ɣ`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Function to evaluate the natural logarithm of CDF.\n\n    Examples\n    --------\n    > var mylogCDF = base.dists.cauchy.logcdf.factory( 1.5, 3.0 );\n    > var y = mylogCDF( 1.0 )\n    ~-0.804","base.dists.cauchy.logpdf":"\nbase.dists.cauchy.logpdf( x, x0, Ɣ )\n    Evaluates the natural logarithm of the probability density function (logPDF)\n    for a Cauchy distribution with location parameter `x0` and scale parameter\n    `Ɣ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `Ɣ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Natural logarithm of PDF.\n\n    Examples\n    --------\n    > var y = base.dists.cauchy.logpdf( 2.0, 1.0, 1.0 )\n    ~-1.838\n    > y = base.dists.cauchy.logpdf( 4.0, 3.0, 0.1 )\n    ~-3.457\n    > y = base.dists.cauchy.logpdf( 4.0, 3.0, 3.0 )\n    ~-2.349\n    > y = base.dists.cauchy.logpdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.cauchy.logpdf( 2.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.cauchy.logpdf( 2.0, 1.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.cauchy.logpdf( 2.0, 1.0, -2.0 )\n    NaN\n\n\nbase.dists.cauchy.logpdf.factory( x0, Ɣ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (logPDF) of a Cauchy distribution with location parameter\n    `x0` and scale parameter `Ɣ`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Function to evaluate the natural logarithm of the PDF.\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.cauchy.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogPDF( 10.0 )\n    ~-1.838\n\n","base.dists.cauchy.logpdf.factory":"\nbase.dists.cauchy.logpdf.factory( x0, Ɣ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (logPDF) of a Cauchy distribution with location parameter\n    `x0` and scale parameter `Ɣ`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Function to evaluate the natural logarithm of the PDF.\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.cauchy.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogPDF( 10.0 )\n    ~-1.838","base.dists.cauchy.median":"\nbase.dists.cauchy.median( x0, Ɣ )\n    Returns the median of a Cauchy distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `Ɣ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.cauchy.median( 10.0, 5.0 )\n    10.0\n    > v = base.dists.cauchy.median( 7.0, 0.5 )\n    7.0\n    > v = base.dists.cauchy.median( 10.3, -0.5 )\n    NaN\n\n","base.dists.cauchy.mode":"\nbase.dists.cauchy.mode( x0, Ɣ )\n    Returns the mode of a Cauchy distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `Ɣ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.cauchy.mode( 10.0, 5.0 )\n    10.0\n    > v = base.dists.cauchy.mode( 7.0, 0.5 )\n    7.0\n    > v = base.dists.cauchy.mode( 10.3, -0.5 )\n    NaN\n\n","base.dists.cauchy.pdf":"\nbase.dists.cauchy.pdf( x, x0, Ɣ )\n    Evaluates the probability density function (PDF) for a Cauchy distribution\n    with location parameter `x0` and scale parameter `Ɣ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `Ɣ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.cauchy.pdf( 2.0, 1.0, 1.0 )\n    ~0.159\n    > y = base.dists.cauchy.pdf( 4.0, 3.0, 0.1 )\n    ~0.0315\n    > y = base.dists.cauchy.pdf( 4.0, 3.0, 3.0 )\n    ~0.095\n    > y = base.dists.cauchy.pdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.cauchy.pdf( 2.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.cauchy.pdf( 2.0, 1.0, NaN )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.cauchy.pdf( 2.0, 1.0, -2.0 )\n    NaN\n\n\nbase.dists.cauchy.pdf.factory( x0, Ɣ )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Cauchy distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.cauchy.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    ~0.159\n\n","base.dists.cauchy.pdf.factory":"\nbase.dists.cauchy.pdf.factory( x0, Ɣ )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Cauchy distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.cauchy.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    ~0.159","base.dists.cauchy.quantile":"\nbase.dists.cauchy.quantile( p, x0, Ɣ )\n    Evaluates the quantile function for a Cauchy distribution with location\n    parameter `x0`  and scale parameter `Ɣ` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `Ɣ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.cauchy.quantile( 0.3, 2.0, 2.0 )\n    ~0.547\n    > y = base.dists.cauchy.quantile( 0.8, 10, 2.0 )\n    ~12.753\n    > y = base.dists.cauchy.quantile( 0.1, 10.0, 2.0 )\n    ~3.845\n\n    > y = base.dists.cauchy.quantile( 1.1, 0.0, 1.0 )\n    NaN\n    > y = base.dists.cauchy.quantile( -0.2, 0.0, 1.0 )\n    NaN\n\n    > y = base.dists.cauchy.quantile( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.cauchy.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.cauchy.quantile( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.cauchy.quantile( 0.5, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.cauchy.quantile.factory( x0, Ɣ )\n    Returns a function for evaluating the quantile function of a Cauchy\n    distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.cauchy.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    10.0\n\n","base.dists.cauchy.quantile.factory":"\nbase.dists.cauchy.quantile.factory( x0, Ɣ )\n    Returns a function for evaluating the quantile function of a Cauchy\n    distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.cauchy.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    10.0","base.dists.chi.cdf":"\nbase.dists.chi.cdf( x, k )\n    Evaluates the cumulative distribution function (CDF) for a chi distribution\n    with degrees of freedom `k` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.chi.cdf( 2.0, 3.0 )\n    ~0.739\n    > y = base.dists.chi.cdf( 1.0, 0.5 )\n    ~0.846\n    > y = base.dists.chi.cdf( -1.0, 4.0 )\n    0.0\n    > y = base.dists.chi.cdf( NaN, 1.0 )\n    NaN\n    > y = base.dists.chi.cdf( 0.0, NaN )\n    NaN\n\n    // Negative degrees of freedom:\n    > y = base.dists.chi.cdf( 2.0, -1.0 )\n    NaN\n\n    // Degenerate distribution when `k = 0`:\n    > y = base.dists.chi.cdf( 2.0, 0.0 )\n    1.0\n    > y = base.dists.chi.cdf( -2.0, 0.0 )\n    0.0\n    > y = base.dists.chi.cdf( 0.0, 0.0 )\n    0.0\n\nbase.dists.chi.cdf.factory( k )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a chi distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.chi.cdf.factory( 1.0 );\n    > var y = mycdf( 2.0 )\n    ~0.954\n    > y = mycdf( 1.2 )\n    ~0.77\n\n","base.dists.chi.cdf.factory":"\nbase.dists.chi.cdf.factory( k )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a chi distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.chi.cdf.factory( 1.0 );\n    > var y = mycdf( 2.0 )\n    ~0.954\n    > y = mycdf( 1.2 )\n    ~0.77","base.dists.chi.Chi":"\nbase.dists.chi.Chi( [k] )\n    Returns a chi distribution object.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    chi: Object\n        Distribution instance.\n\n    chi.k: number\n        Degrees of freedom. If set, the value must be greater than `0`.\n\n    chi.entropy: number\n        Read-only property which returns the differential entropy.\n\n    chi.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    chi.mean: number\n        Read-only property which returns the expected value.\n\n    chi.mode: number\n        Read-only property which returns the mode.\n\n    chi.skewness: number\n        Read-only property which returns the skewness.\n\n    chi.stdev: number\n        Read-only property which returns the standard deviation.\n\n    chi.variance: number\n        Read-only property which returns the variance.\n\n    chi.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    chi.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    chi.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    chi.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var chi = base.dists.chi.Chi( 6.0 );\n    > chi.k\n    6.0\n    > chi.entropy\n    ~1.04\n    > chi.kurtosis\n    ~0.025\n    > chi.mean\n    ~2.35\n    > chi.mode\n    ~2.236\n    > chi.skewness\n    ~0.318\n    > chi.stdev\n    ~0.691\n    > chi.variance\n    ~0.478\n    > chi.cdf( 1.0 )\n    ~0.014\n    > chi.logpdf( 1.5 )\n    ~-1.177\n    > chi.pdf( 1.5 )\n    ~0.308\n    > chi.quantile( 0.5 )\n    ~2.313\n\n","base.dists.chi.entropy":"\nbase.dists.chi.entropy( k )\n    Returns the differential entropy of a chi distribution (in nats).\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.chi.entropy( 11.0 )\n    ~1.056\n    > v = base.dists.chi.entropy( 1.5 )\n    ~0.878\n\n","base.dists.chi.kurtosis":"\nbase.dists.chi.kurtosis( k )\n    Returns the excess kurtosis of a chi distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.chi.kurtosis( 9.0 )\n    ~0.011\n    > v = base.dists.chi.kurtosis( 1.5 )\n    ~0.424\n\n","base.dists.chi.logpdf":"\nbase.dists.chi.logpdf( x, k )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a chi distribution with degrees of freedom `k` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.chi.logpdf( 0.3, 4.0 )\n    ~-4.35\n    > y = base.dists.chi.logpdf( 0.7, 0.7 )\n    ~-0.622\n    > y = base.dists.chi.logpdf( -1.0, 0.5 )\n    -Infinity\n    > y = base.dists.chi.logpdf( 0.0, NaN )\n    NaN\n    > y = base.dists.chi.logpdf( NaN, 2.0 )\n    NaN\n\n    // Negative degrees of freedom:\n    > y = base.dists.chi.logpdf( 2.0, -1.0 )\n    NaN\n\n    // Degenerate distribution when `k = 0`:\n    > y = base.dists.chi.logpdf( 2.0, 0.0, 2.0 )\n    -Infinity\n    > y = base.dists.chi.logpdf( 0.0, 0.0, 2.0 )\n    Infinity\n\n\nbase.dists.chi.logpdf.factory( k )\n    Returns a function for evaluating the natural logarithm of the  probability\n    density function (PDF) of a chi distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.chi.logpdf.factory( 6.0 );\n    > var y = mylogPDF( 3.0 )\n    ~-1.086\n\n","base.dists.chi.logpdf.factory":"\nbase.dists.chi.logpdf.factory( k )\n    Returns a function for evaluating the natural logarithm of the  probability\n    density function (PDF) of a chi distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.chi.logpdf.factory( 6.0 );\n    > var y = mylogPDF( 3.0 )\n    ~-1.086","base.dists.chi.mean":"\nbase.dists.chi.mean( k )\n    Returns the expected value of a chi distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.chi.mean( 11.0 )\n    ~3.242\n    > v = base.dists.chi.mean( 4.5 )\n    ~2.008\n\n","base.dists.chi.mode":"\nbase.dists.chi.mode( k )\n    Returns the mode of a chi distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.chi.mode( 11.0 )\n    ~3.162\n    > v = base.dists.chi.mode( 1.5 )\n    ~0.707\n\n","base.dists.chi.pdf":"\nbase.dists.chi.pdf( x, k )\n    Evaluates the probability density function (PDF) for a chi distribution with\n    degrees of freedom `k` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.chi.pdf( 0.3, 4.0 )\n    ~0.013\n    > y = base.dists.chi.pdf( 0.7, 0.7 )\n    ~0.537\n    > y = base.dists.chi.pdf( -1.0, 0.5 )\n    0.0\n    > y = base.dists.chi.pdf( 0.0, NaN )\n    NaN\n    > y = base.dists.chi.pdf( NaN, 2.0 )\n    NaN\n\n    // Negative degrees of freedom:\n    > y = base.dists.chi.pdf( 2.0, -1.0 )\n    NaN\n\n    // Degenerate distribution when `k = 0`:\n    > y = base.dists.chi.pdf( 2.0, 0.0, 2.0 )\n    0.0\n    > y = base.dists.chi.pdf( 0.0, 0.0, 2.0 )\n    Infinity\n\n\nbase.dists.chi.pdf.factory( k )\n    Returns a function for evaluating the probability density function (PDF) of\n    a chi distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.chi.pdf.factory( 6.0 );\n    > var y = myPDF( 3.0 )\n    ~0.337\n\n","base.dists.chi.pdf.factory":"\nbase.dists.chi.pdf.factory( k )\n    Returns a function for evaluating the probability density function (PDF) of\n    a chi distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.chi.pdf.factory( 6.0 );\n    > var y = myPDF( 3.0 )\n    ~0.337","base.dists.chi.quantile":"\nbase.dists.chi.quantile( p, k )\n    Evaluates the quantile function for a chi distribution with degrees of\n    freedom `k` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.chi.quantile( 0.8, 1.0 )\n    ~1.282\n    > y = base.dists.chi.quantile( 0.5, 4.0 )\n    ~1.832\n    > y = base.dists.chi.quantile( 0.8, 0.1 )\n    ~0.116\n    > y = base.dists.chi.quantile( -0.2, 0.5 )\n    NaN\n    > y = base.dists.chi.quantile( 1.1, 0.5 )\n    NaN\n    > y = base.dists.chi.quantile( NaN, 1.0 )\n    NaN\n    > y = base.dists.chi.quantile( 0.0, NaN )\n    NaN\n\n    // Negative degrees of freedom:\n    > y = base.dists.chi.quantile( 0.5, -1.0 )\n    NaN\n\n    // Degenerate distribution when `k = 0`:\n    > y = base.dists.chi.quantile( 0.3, 0.0 )\n    0.0\n    > y = base.dists.chi.quantile( 0.9, 0.0 )\n    0.0\n\n\nbase.dists.chi.quantile.factory( k )\n    Returns a function for evaluating the quantile function of a chi\n    distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.chi.quantile.factory( 2.0 );\n    > var y = myquantile( 0.3 )\n    ~0.845\n    > y = myquantile( 0.7 )\n    ~1.552\n\n","base.dists.chi.quantile.factory":"\nbase.dists.chi.quantile.factory( k )\n    Returns a function for evaluating the quantile function of a chi\n    distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.chi.quantile.factory( 2.0 );\n    > var y = myquantile( 0.3 )\n    ~0.845\n    > y = myquantile( 0.7 )\n    ~1.552","base.dists.chi.skewness":"\nbase.dists.chi.skewness( k )\n    Returns the skewness of a chi distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.chi.skewness( 11.0 )\n    ~0.225\n    > v = base.dists.chi.skewness( 1.5 )\n    ~0.763\n\n","base.dists.chi.stdev":"\nbase.dists.chi.stdev( k )\n    Returns the standard deviation of a chi distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.chi.stdev( 11.0 )\n    ~0.699\n    > v = base.dists.chi.stdev( 1.5 )\n    ~0.637\n\n","base.dists.chi.variance":"\nbase.dists.chi.variance( k )\n    Returns the variance of a chi distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.chi.variance( 11.0 )\n    ~0.488\n    > v = base.dists.chi.variance( 1.5 )\n    ~0.406\n\n","base.dists.chisquare.cdf":"\nbase.dists.chisquare.cdf( x, k )\n    Evaluates the cumulative distribution function (CDF) for a chi-squared\n    distribution with degrees of freedom `k` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.chisquare.cdf( 2.0, 3.0 )\n    ~0.428\n    > y = base.dists.chisquare.cdf( 1.0, 0.5 )\n    ~0.846\n    > y = base.dists.chisquare.cdf( -1.0, 4.0 )\n    0.0\n    > y = base.dists.chisquare.cdf( NaN, 1.0 )\n    NaN\n    > y = base.dists.chisquare.cdf( 0.0, NaN )\n    NaN\n\n    // Negative degrees of freedom:\n    > y = base.dists.chisquare.cdf( 2.0, -1.0 )\n    NaN\n\n    // Degenerate distribution when `k = 0`:\n    > y = base.dists.chisquare.cdf( 2.0, 0.0 )\n    1.0\n    > y = base.dists.chisquare.cdf( -2.0, 0.0 )\n    0.0\n    > y = base.dists.chisquare.cdf( 0.0, 0.0 )\n    0.0\n\nbase.dists.chisquare.cdf.factory( k )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a chi-squared distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.chisquare.cdf.factory( 1.0 );\n    > var y = mycdf( 2.0 )\n    ~0.843\n    > y = mycdf( 1.2 )\n    ~0.727\n\n","base.dists.chisquare.cdf.factory":"\nbase.dists.chisquare.cdf.factory( k )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a chi-squared distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.chisquare.cdf.factory( 1.0 );\n    > var y = mycdf( 2.0 )\n    ~0.843\n    > y = mycdf( 1.2 )\n    ~0.727","base.dists.chisquare.ChiSquare":"\nbase.dists.chisquare.ChiSquare( [k] )\n    Returns a  chi-squared distribution object.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    chisquare: Object\n        Distribution instance.\n\n    chisquare.k: number\n        Degrees of freedom. If set, the value must be greater than `0`.\n\n    chisquare.entropy: number\n        Read-only property which returns the differential entropy.\n\n    chisquare.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    chisquare.mean: number\n        Read-only property which returns the expected value.\n\n    chisquare.median: number\n        Read-only property which returns the median.\n\n    chisquare.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    chisquare.mode: number\n        Read-only property which returns the mode.\n\n    chisquare.skewness: number\n        Read-only property which returns the skewness.\n\n    chisquare.stdev: number\n        Read-only property which returns the standard deviation.\n\n    chisquare.variance: number\n        Read-only property which returns the variance.\n\n    chisquare.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    chisquare.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    chisquare.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var chisquare = base.dists.chisquare.ChiSquare( 6.0 );\n    > chisquare.k\n    6.0\n    > chisquare.entropy\n    ~2.541\n    > chisquare.kurtosis\n    2.0\n    > chisquare.mean\n    6.0\n    > chisquare.median\n    ~5.348\n    > chisquare.mode\n    4.0\n    > chisquare.skewness\n    ~1.155\n    > chisquare.stdev\n    ~3.464\n    > chisquare.variance\n    12.0\n    > chisquare.cdf( 3.0 )\n    ~0.191\n    > chisquare.mgf( 0.2 )\n    ~4.63\n    > chisquare.pdf( 1.5 )\n    ~0.066\n    > chisquare.quantile( 0.5 )\n    ~5.348\n\n","base.dists.chisquare.entropy":"\nbase.dists.chisquare.entropy( k )\n    Returns the differential entropy of a chi-squared distribution (in nats).\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.chisquare.entropy( 11.0 )\n    ~2.901\n    > v = base.dists.chisquare.entropy( 1.5 )\n    ~1.375\n\n","base.dists.chisquare.kurtosis":"\nbase.dists.chisquare.kurtosis( k )\n    Returns the excess kurtosis of a chi-squared distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.chisquare.kurtosis( 9.0 )\n    ~1.333\n    > v = base.dists.chisquare.kurtosis( 1.5 )\n    8.0\n\n","base.dists.chisquare.logpdf":"\nbase.dists.chisquare.logpdf( x, k )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a chi-squared distribution with degrees of freedom `k` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.chisquare.logpdf( 0.3, 4.0 )\n    ~-2.74\n    > y = base.dists.chisquare.logpdf( 0.7, 0.7 )\n    ~-1.295\n    > y = base.dists.chisquare.logpdf( -1.0, 0.5 )\n    -Infinity\n    > y = base.dists.chisquare.logpdf( 0.0, NaN )\n    NaN\n    > y = base.dists.chisquare.logpdf( NaN, 2.0 )\n    NaN\n\n    // Negative degrees of freedom:\n    > y = base.dists.chisquare.logpdf( 2.0, -1.0 )\n    NaN\n\n    // Degenerate distribution when `k = 0`:\n    > y = base.dists.chisquare.logpdf( 2.0, 0.0, 2.0 )\n    -Infinity\n    > y = base.dists.chisquare.logpdf( 0.0, 0.0, 2.0 )\n    Infinity\n\n\nbase.dists.chisquare.logpdf.factory( k )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a chi-squared distribution with degrees of freedom\n    `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var myLogPDF = base.dists.chisquare.logpdf.factory( 6.0 );\n    > var y = myLogPDF( 3.0 )\n    ~-2.075\n\n","base.dists.chisquare.logpdf.factory":"\nbase.dists.chisquare.logpdf.factory( k )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a chi-squared distribution with degrees of freedom\n    `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var myLogPDF = base.dists.chisquare.logpdf.factory( 6.0 );\n    > var y = myLogPDF( 3.0 )\n    ~-2.075","base.dists.chisquare.mean":"\nbase.dists.chisquare.mean( k )\n    Returns the expected value of a chi-squared distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.chisquare.mean( 11.0 )\n    11.0\n    > v = base.dists.chisquare.mean( 4.5 )\n    4.5\n\n","base.dists.chisquare.median":"\nbase.dists.chisquare.median( k )\n    Returns the median of a chi-squared distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var k = base.dists.chisquare.median( 9.0 )\n    ~8.343\n    > k = base.dists.chisquare.median( 2.0 )\n    ~1.386\n\n","base.dists.chisquare.mgf":"\nbase.dists.chisquare.mgf( t, k )\n    Evaluates the moment-generating function (MGF) for a chi-squared\n    distribution with degrees of freedom `k` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.chisquare.mgf( 0.4, 2 )\n    ~5.0\n    > y = base.dists.chisquare.mgf( -1.0, 5.0 )\n    ~0.0642\n    > y = base.dists.chisquare.mgf( 0.0, 10.0 )\n    1.0\n\n\nbase.dists.chisquare.mgf.factory( k )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    chi-squared distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.chisquare.mgf.factory( 1.0 );\n    > var y = mymgf( 0.2 )\n    ~1.291\n    > y = mymgf( 0.4 )\n    ~2.236\n\n","base.dists.chisquare.mgf.factory":"\nbase.dists.chisquare.mgf.factory( k )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    chi-squared distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.chisquare.mgf.factory( 1.0 );\n    > var y = mymgf( 0.2 )\n    ~1.291\n    > y = mymgf( 0.4 )\n    ~2.236","base.dists.chisquare.mode":"\nbase.dists.chisquare.mode( k )\n    Returns the mode of a chi-squared distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.chisquare.mode( 11.0 )\n    9.0\n    > v = base.dists.chisquare.mode( 1.5 )\n    0.0\n\n","base.dists.chisquare.pdf":"\nbase.dists.chisquare.pdf( x, k )\n    Evaluates the probability density function (PDF) for a chi-squared\n    distribution with degrees of freedom `k` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.chisquare.pdf( 0.3, 4.0 )\n    ~0.065\n    > y = base.dists.chisquare.pdf( 0.7, 0.7 )\n    ~0.274\n    > y = base.dists.chisquare.pdf( -1.0, 0.5 )\n    0.0\n    > y = base.dists.chisquare.pdf( 0.0, NaN )\n    NaN\n    > y = base.dists.chisquare.pdf( NaN, 2.0 )\n    NaN\n\n    // Negative degrees of freedom:\n    > y = base.dists.chisquare.pdf( 2.0, -1.0 )\n    NaN\n\n    // Degenerate distribution when `k = 0`:\n    > y = base.dists.chisquare.pdf( 2.0, 0.0, 2.0 )\n    0.0\n    > y = base.dists.chisquare.pdf( 0.0, 0.0, 2.0 )\n    Infinity\n\n\nbase.dists.chisquare.pdf.factory( k )\n    Returns a function for evaluating the probability density function (PDF) of\n    a chi-squared distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.chisquare.pdf.factory( 6.0 );\n    > var y = myPDF( 3.0 )\n    ~0.126\n\n","base.dists.chisquare.pdf.factory":"\nbase.dists.chisquare.pdf.factory( k )\n    Returns a function for evaluating the probability density function (PDF) of\n    a chi-squared distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.chisquare.pdf.factory( 6.0 );\n    > var y = myPDF( 3.0 )\n    ~0.126","base.dists.chisquare.quantile":"\nbase.dists.chisquare.quantile( p, k )\n    Evaluates the quantile function for a chi-squared distribution with degrees\n    of freedom `k` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.chisquare.quantile( 0.8, 1.0 )\n    ~1.642\n    > y = base.dists.chisquare.quantile( 0.5, 4.0 )\n    ~3.357\n    > y = base.dists.chisquare.quantile( 0.8, 0.1 )\n    ~0.014\n    > y = base.dists.chisquare.quantile( -0.2, 0.5 )\n    NaN\n    > y = base.dists.chisquare.quantile( 1.1, 0.5 )\n    NaN\n    > y = base.dists.chisquare.quantile( NaN, 1.0 )\n    NaN\n    > y = base.dists.chisquare.quantile( 0.0, NaN )\n    NaN\n\n    // Negative degrees of freedom:\n    > y = base.dists.chisquare.quantile( 0.5, -1.0 )\n    NaN\n\n    // Degenerate distribution when `k = 0`:\n    > y = base.dists.chisquare.quantile( 0.3, 0.0 )\n    0.0\n    > y = base.dists.chisquare.quantile( 0.9, 0.0 )\n    0.0\n\n\nbase.dists.chisquare.quantile.factory( k )\n    Returns a function for evaluating the quantile function of a chi-squared\n    distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.chisquare.quantile.factory( 2.0 );\n    > var y = myquantile( 0.3 )\n    ~0.713\n    > y = myquantile( 0.7 )\n    ~2.408\n\n","base.dists.chisquare.quantile.factory":"\nbase.dists.chisquare.quantile.factory( k )\n    Returns a function for evaluating the quantile function of a chi-squared\n    distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.chisquare.quantile.factory( 2.0 );\n    > var y = myquantile( 0.3 )\n    ~0.713\n    > y = myquantile( 0.7 )\n    ~2.408","base.dists.chisquare.skewness":"\nbase.dists.chisquare.skewness( k )\n    Returns the skewness of a chi-squared distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.chisquare.skewness( 11.0 )\n    ~0.853\n    > v = base.dists.chisquare.skewness( 1.5 )\n    ~2.309\n\n","base.dists.chisquare.stdev":"\nbase.dists.chisquare.stdev( k )\n    Returns the standard deviation of a chi-squared distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.chisquare.stdev( 11.0 )\n    ~4.69\n    > v = base.dists.chisquare.stdev( 1.5 )\n    ~1.732\n\n","base.dists.chisquare.variance":"\nbase.dists.chisquare.variance( k )\n    Returns the variance of a chi-squared distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.chisquare.variance( 11.0 )\n    22.0\n    > v = base.dists.chisquare.variance( 1.5 )\n    3.0\n\n","base.dists.cosine.cdf":"\nbase.dists.cosine.cdf( x, μ, s )\n    Evaluates the cumulative distribution function (CDF) for a raised cosine\n    distribution with location parameter `μ` and scale parameter `s` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.cdf( 2.0, 0.0, 3.0 )\n    ~0.971\n    > y = base.dists.cosine.cdf( 9.0, 10.0, 3.0 )\n    ~0.196\n\n    > y = base.dists.cosine.cdf( 2.0, 0.0, NaN )\n    NaN\n    > y = base.dists.cosine.cdf( 2.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.cdf( NaN, 0.0, 1.0 )\n    NaN\n\n    // Degenerate distribution centered at `μ` when `s = 0.0`:\n    > y = base.dists.cosine.cdf( 2.0, 8.0, 0.0 )\n    0.0\n    > y = base.dists.cosine.cdf( 8.0, 8.0, 0.0 )\n    1.0\n    > y = base.dists.cosine.cdf( 10.0, 8.0, 0.0 )\n    1.0\n\n\nbase.dists.cosine.cdf.factory( μ, s )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a raised cosine distribution with location parameter `μ` and scale\n    parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.cosine.cdf.factory( 3.0, 1.5 );\n    > var y = mycdf( 1.9 )\n    ~0.015\n\n","base.dists.cosine.cdf.factory":"\nbase.dists.cosine.cdf.factory( μ, s )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a raised cosine distribution with location parameter `μ` and scale\n    parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.cosine.cdf.factory( 3.0, 1.5 );\n    > var y = mycdf( 1.9 )\n    ~0.015","base.dists.cosine.Cosine":"\nbase.dists.cosine.Cosine( [μ, s] )\n    Returns a raised cosine distribution object.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter. Default: `0.0`.\n\n    s: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    cosine: Object\n        Distribution instance.\n\n    cosine.mu: number\n        Location parameter.\n\n    cosine.s: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    cosine.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    cosine.mean: number\n        Read-only property which returns the expected value.\n\n    cosine.median: number\n        Read-only property which returns the median.\n\n    cosine.mode: number\n        Read-only property which returns the mode.\n\n    cosine.skewness: number\n        Read-only property which returns the skewness.\n\n    cosine.stdev: number\n        Read-only property which returns the standard deviation.\n\n    cosine.variance: number\n        Read-only property which returns the variance.\n\n    cosine.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    cosine.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    cosine.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    cosine.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    cosine.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    cosine.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var cosine = base.dists.cosine.Cosine( -2.0, 3.0 );\n    > cosine.mu\n    -2.0\n    > cosine.s\n    3.0\n    > cosine.kurtosis\n    ~-0.594\n    > cosine.mean\n    -2.0\n    > cosine.median\n    -2.0\n    > cosine.mode\n    -2.0\n    > cosine.skewness\n    0.0\n    > cosine.stdev\n    ~1.085\n    > cosine.variance\n    ~1.176\n    > cosine.cdf( 0.5 )\n    ~0.996\n    > cosine.logcdf( 0.5 )\n    ~-0.004\n    > cosine.logpdf( -1.0 )\n    ~-1.386\n    > cosine.mgf( 0.2 )\n    ~0.686\n    > cosine.pdf( -2.0 )\n    ~0.333\n    > cosine.quantile( 0.9 )\n    ~-0.553\n\n","base.dists.cosine.kurtosis":"\nbase.dists.cosine.kurtosis( μ, s )\n    Returns the excess kurtosis of a raised cosine distribution with location\n    parameter `μ` and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.kurtosis( 0.0, 1.0 )\n    ~-0.594\n    > y = base.dists.cosine.kurtosis( 4.0, 2.0 )\n    ~-0.594\n    > y = base.dists.cosine.kurtosis( NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.kurtosis( 0.0, NaN )\n    NaN\n    > y = base.dists.cosine.kurtosis( 0.0, 0.0 )\n    NaN\n\n","base.dists.cosine.logcdf":"\nbase.dists.cosine.logcdf( x, μ, s )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a raised cosine distribution with location parameter `μ` and scale\n     parameter `s` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.logcdf( 2.0, 0.0, 3.0 )\n    ~-0.029\n    > y = base.dists.cosine.logcdf( 9.0, 10.0, 3.0 )\n    ~-1.632\n\n    > y = base.dists.cosine.logcdf( 2.0, 0.0, NaN )\n    NaN\n    > y = base.dists.cosine.logcdf( 2.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.logcdf( NaN, 0.0, 1.0 )\n    NaN\n\n    // Degenerate distribution centered at `μ` when `s = 0.0`:\n    > y = base.dists.cosine.logcdf( 2.0, 8.0, 0.0 )\n    -Infinity\n    > y = base.dists.cosine.logcdf( 8.0, 8.0, 0.0 )\n    0.0\n    > y = base.dists.cosine.logcdf( 10.0, 8.0, 0.0 )\n    0.0\n\n\nbase.dists.cosine.logcdf.factory( μ, s )\n    Returns a function for evaluating the natural logarithm of the  cumulative\n    distribution function (CDF) of a raised cosine distribution with location\n    parameter `μ` and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.cosine.logcdf.factory( 3.0, 1.5 );\n    > var y = mylogcdf( 1.9 )\n    ~-4.2\n\n","base.dists.cosine.logcdf.factory":"\nbase.dists.cosine.logcdf.factory( μ, s )\n    Returns a function for evaluating the natural logarithm of the  cumulative\n    distribution function (CDF) of a raised cosine distribution with location\n    parameter `μ` and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.cosine.logcdf.factory( 3.0, 1.5 );\n    > var y = mylogcdf( 1.9 )\n    ~-4.2","base.dists.cosine.logpdf":"\nbase.dists.cosine.logpdf( x, μ, s )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    raised cosine distribution with location parameter `μ` and scale parameter\n    `s` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.logpdf( 2.0, 0.0, 3.0 )\n    ~-2.485\n    > y = base.dists.cosine.logpdf( -1.0, 2.0, 4.0 )\n    ~-3.307\n    > y = base.dists.cosine.logpdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.cosine.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.logpdf( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.cosine.logpdf( 2.0, 0.0, -1.0 )\n    NaN\n\n    // Degenerate distribution at `s = 0.0`:\n    > y = base.dists.cosine.logpdf( 2.0, 8.0, 0.0 )\n    -Infinity\n    > y = base.dists.cosine.logpdf( 8.0, 8.0, 0.0 )\n    Infinity\n\n\nbase.dists.cosine.logpdf.factory( μ, s )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a raised cosine distribution with location parameter `μ`\n    and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.cosine.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogpdf( 10.0 )\n    ~-0.693\n\n","base.dists.cosine.logpdf.factory":"\nbase.dists.cosine.logpdf.factory( μ, s )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a raised cosine distribution with location parameter `μ`\n    and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.cosine.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogpdf( 10.0 )\n    ~-0.693","base.dists.cosine.mean":"\nbase.dists.cosine.mean( μ, s )\n    Returns the expected value of a raised cosine distribution with location\n    parameter `μ` and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.mean( 0.0, 1.0 )\n    0.0\n    > y = base.dists.cosine.mean( 4.0, 2.0 )\n    4.0\n    > y = base.dists.cosine.mean( NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.mean( 0.0, NaN )\n    NaN\n    > y = base.dists.cosine.mean( 0.0, 0.0 )\n    NaN\n\n","base.dists.cosine.median":"\nbase.dists.cosine.median( μ, s )\n    Returns the median of a raised cosine distribution with location parameter\n    `μ` and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.median( 0.0, 1.0 )\n    0.0\n    > y = base.dists.cosine.median( 4.0, 2.0 )\n    4.0\n    > y = base.dists.cosine.median( NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.median( 0.0, NaN )\n    NaN\n    > y = base.dists.cosine.median( 0.0, 0.0 )\n    NaN\n\n","base.dists.cosine.mgf":"\nbase.dists.cosine.mgf( t, μ, s )\n    Evaluates the moment-generating function (MGF) for a raised cosine\n    distribution with location parameter `μ` and scale parameter `s` at a value\n    `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.mgf( 2.0, 0.0, 3.0 )\n    ~7.234\n    > y = base.dists.cosine.mgf( 9.0, 10.0, 3.0 )\n    ~1.606e+47\n\n    > y = base.dists.cosine.mgf( 0.5, 0.0, NaN )\n    NaN\n    > y = base.dists.cosine.mgf( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.mgf( NaN, 0.0, 1.0 )\n    NaN\n\n\nbase.dists.cosine.mgf.factory( μ, s )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    raised cosine distribution with location parameter `μ` and scale parameter\n    `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.cosine.mgf.factory( 3.0, 1.5 );\n    > var y = mymgf( 1.9 )\n    ~495.57\n\n","base.dists.cosine.mgf.factory":"\nbase.dists.cosine.mgf.factory( μ, s )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    raised cosine distribution with location parameter `μ` and scale parameter\n    `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.cosine.mgf.factory( 3.0, 1.5 );\n    > var y = mymgf( 1.9 )\n    ~495.57","base.dists.cosine.mode":"\nbase.dists.cosine.mode( μ, s )\n    Returns the mode of a raised cosine distribution with location parameter `μ`\n    and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.mode( 0.0, 1.0 )\n    0.0\n    > y = base.dists.cosine.mode( 4.0, 2.0 )\n    4.0\n    > y = base.dists.cosine.mode( NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.mode( 0.0, NaN )\n    NaN\n    > y = base.dists.cosine.mode( 0.0, 0.0 )\n    NaN\n\n","base.dists.cosine.pdf":"\nbase.dists.cosine.pdf( x, μ, s )\n    Evaluates the probability density function (PDF) for a raised cosine\n    distribution with location parameter `μ` and scale parameter `s` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.pdf( 2.0, 0.0, 3.0 )\n    ~0.083\n    > y = base.dists.cosine.pdf( 2.4, 4.0, 2.0 )\n    ~0.048\n    > y = base.dists.cosine.pdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.cosine.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.pdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.cosine.pdf( 2.0, 0.0, -1.0 )\n    NaN\n    > y = base.dists.cosine.pdf( 2.0, 8.0, 0.0 )\n    0.0\n    > y = base.dists.cosine.pdf( 8.0, 8.0, 0.0 )\n    Infinity\n\n\nbase.dists.cosine.pdf.factory( μ, s )\n    Returns a function for evaluating the probability density function (PDF) of\n    a raised cosine distribution with location parameter `μ` and scale parameter\n    `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.cosine.pdf.factory( 0.0, 3.0 );\n    > var y = myPDF( 2.0 )\n    ~0.083\n\n","base.dists.cosine.pdf.factory":"\nbase.dists.cosine.pdf.factory( μ, s )\n    Returns a function for evaluating the probability density function (PDF) of\n    a raised cosine distribution with location parameter `μ` and scale parameter\n    `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.cosine.pdf.factory( 0.0, 3.0 );\n    > var y = myPDF( 2.0 )\n    ~0.083","base.dists.cosine.quantile":"\nbase.dists.cosine.quantile( p, μ, s )\n    Evaluates the quantile function for a raised cosine distribution with\n    location parameter `μ` and scale parameter `s` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.quantile( 0.8, 0.0, 1.0 )\n    ~0.327\n    > y = base.dists.cosine.quantile( 0.5, 4.0, 2.0 )\n    ~4.0\n\n    > y = base.dists.cosine.quantile( 1.1, 0.0, 1.0 )\n    NaN\n    > y = base.dists.cosine.quantile( -0.2, 0.0, 1.0 )\n    NaN\n\n    > y = base.dists.cosine.quantile( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.cosine.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.quantile( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.cosine.quantile( 0.5, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.cosine.quantile.factory( μ, s )\n    Returns a function for evaluating the quantile function of a raised cosine\n    distribution with location parameter `μ` and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.cosine.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.3 )\n    ~9.586\n\n","base.dists.cosine.quantile.factory":"\nbase.dists.cosine.quantile.factory( μ, s )\n    Returns a function for evaluating the quantile function of a raised cosine\n    distribution with location parameter `μ` and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.cosine.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.3 )\n    ~9.586","base.dists.cosine.skewness":"\nbase.dists.cosine.skewness( μ, s )\n    Returns the skewness of a raised cosine distribution with location parameter\n    `μ` and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.skewness( 0.0, 1.0 )\n    0.0\n    > y = base.dists.cosine.skewness( 4.0, 2.0 )\n    0.0\n    > y = base.dists.cosine.skewness( NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.skewness( 0.0, NaN )\n    NaN\n    > y = base.dists.cosine.skewness( 0.0, 0.0 )\n    NaN\n\n","base.dists.cosine.stdev":"\nbase.dists.cosine.stdev( μ, s )\n    Returns the standard deviation of a raised cosine distribution with location\n    parameter `μ` and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.stdev( 0.0, 1.0 )\n    ~0.362\n    > y = base.dists.cosine.stdev( 4.0, 2.0 )\n    ~0.723\n    > y = base.dists.cosine.stdev( NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.stdev( 0.0, NaN )\n    NaN\n    > y = base.dists.cosine.stdev( 0.0, 0.0 )\n    NaN\n\n","base.dists.cosine.variance":"\nbase.dists.cosine.variance( μ, s )\n    Returns the variance of a raised cosine distribution with location parameter\n    `μ` and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.variance( 0.0, 1.0 )\n    ~0.131\n    > y = base.dists.cosine.variance( 4.0, 2.0 )\n    ~0.523\n    > y = base.dists.cosine.variance( NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.variance( 0.0, NaN )\n    NaN\n    > y = base.dists.cosine.variance( 0.0, 0.0 )\n    NaN\n\n","base.dists.degenerate.cdf":"\nbase.dists.degenerate.cdf( x, μ )\n    Evaluates the cumulative distribution function (CDF) for a degenerate\n    distribution with mean value `μ`.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.degenerate.cdf( 2.0, 3.0 )\n    0.0\n    > y = base.dists.degenerate.cdf( 4.0, 3.0 )\n    1.0\n    > y = base.dists.degenerate.cdf( 3.0, 3.0 )\n    1.0\n    > y = base.dists.degenerate.cdf( NaN, 0.0 )\n    NaN\n    > y = base.dists.degenerate.cdf( 0.0, NaN )\n    NaN\n\n\nbase.dists.degenerate.cdf.factory( μ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a degenerate distribution centered at a provided mean value.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.degenerate.cdf.factory( 5.0 );\n    > var y = myCDF( 3.0 )\n    0.0\n    > y = myCDF( 6.0 )\n    1.0\n\n","base.dists.degenerate.cdf.factory":"\nbase.dists.degenerate.cdf.factory( μ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a degenerate distribution centered at a provided mean value.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.degenerate.cdf.factory( 5.0 );\n    > var y = myCDF( 3.0 )\n    0.0\n    > y = myCDF( 6.0 )\n    1.0","base.dists.degenerate.Degenerate":"\nbase.dists.degenerate.Degenerate( [μ] )\n    Returns a degenerate distribution object.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Constant value of distribution.\n\n    Returns\n    -------\n    degenerate: Object\n        Distribution instance.\n\n    degenerate.mu: number\n        Constant value of distribution.\n\n    degenerate.entropy: number\n        Read-only property which returns the differential entropy.\n\n    degenerate.mean: number\n        Read-only property which returns the expected value.\n\n    degenerate.median: number\n        Read-only property which returns the median.\n\n    degenerate.stdev: number\n        Read-only property which returns the standard deviation.\n\n    degenerate.variance: number\n        Read-only property which returns the variance.\n\n    degenerate.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    degenerate.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    degenerate.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    degenerate.logpmf: Function\n        Evaluates the natural logarithm of the probability mass function\n        (PMF).\n\n    degenerate.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    degenerate.pmf: Function\n        Evaluates the probability mass function (PMF).\n\n    degenerate.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    degenerate.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var degenerate = base.dists.degenerate.Degenerate( 2.0 );\n    > degenerate.mu\n    2.0\n    > degenerate.entropy\n    0.0\n    > degenerate.mean\n    2.0\n    > degenerate.mode\n    2.0\n    > degenerate.median\n    2.0\n    > degenerate.stdev\n    0.0\n    > degenerate.variance\n    0.0\n    > degenerate.cdf( 0.5 )\n    0.0\n    > degenerate.logcdf( 2.5 )\n    0.0\n    > degenerate.logpdf( 0.5 )\n    -Infinity\n    > degenerate.logpmf( 2.5 )\n    -Infinity\n    > degenerate.mgf( 0.2 )\n    ~1.492\n    > degenerate.pdf( 2.0 )\n    +Infinity\n    > degenerate.pmf( 2.0 )\n    1.0\n    > degenerate.quantile( 0.7 )\n    2.0\n\n","base.dists.degenerate.entropy":"\nbase.dists.degenerate.entropy( μ )\n    Returns the entropy of a degenerate distribution with constant value `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.degenerate.entropy( 20.0 )\n    0.0\n    > v = base.dists.degenerate.entropy( -10.0 )\n    0.0\n\n","base.dists.degenerate.logcdf":"\nbase.dists.degenerate.logcdf( x, μ )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (logCDF) for a degenerate distribution with mean `μ`.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Natural logarithm of the CDF.\n\n    Examples\n    --------\n    > var y = base.dists.degenerate.logcdf( 2.0, 3.0 )\n    -Infinity\n    > y = base.dists.degenerate.logcdf( 4.0, 3.0 )\n    0\n    > y = base.dists.degenerate.logcdf( 3.0, 3.0 )\n    0\n    > y = base.dists.degenerate.logcdf( NaN, 0.0 )\n    NaN\n    > y = base.dists.degenerate.logcdf( 0.0, NaN )\n    NaN\n\n\nbase.dists.degenerate.logcdf.factory( μ )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (logCDF) of a degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    logcdf: Function\n        Function to evaluate the natural logarithm of cumulative distribution\n        function (logCDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.degenerate.logcdf.factory( 5.0 );\n    > var y = mylogcdf( 3.0 )\n    -Infinity\n    > y = mylogcdf( 6.0 )\n    0\n\n","base.dists.degenerate.logcdf.factory":"\nbase.dists.degenerate.logcdf.factory( μ )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (logCDF) of a degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    logcdf: Function\n        Function to evaluate the natural logarithm of cumulative distribution\n        function (logCDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.degenerate.logcdf.factory( 5.0 );\n    > var y = mylogcdf( 3.0 )\n    -Infinity\n    > y = mylogcdf( 6.0 )\n    0","base.dists.degenerate.logpdf":"\nbase.dists.degenerate.logpdf( x, μ )\n    Evaluates the natural logarithm of the probability density function (logPDF)\n    for a degenerate distribution with mean `μ`.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Natural logarithm of the PDF.\n\n    Examples\n    --------\n    > var y = base.dists.degenerate.logpdf( 2.0, 3.0 )\n    -Infinity\n    > y = base.dists.degenerate.logpdf( 3.0, 3.0 )\n    Infinity\n    > y = base.dists.degenerate.logpdf( NaN, 0.0 )\n    NaN\n    > y = base.dists.degenerate.logpdf( 0.0, NaN )\n    NaN\n\n\nbase.dists.degenerate.logpdf.factory( μ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (logPDF) of a degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    logpdf: Function\n        Function to evaluate the natural logarithm of the PDF.\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.degenerate.logpdf.factory( 10.0 );\n    > var y = mylogPDF( 10.0 )\n    Infinity\n\n","base.dists.degenerate.logpdf.factory":"\nbase.dists.degenerate.logpdf.factory( μ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (logPDF) of a degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    logpdf: Function\n        Function to evaluate the natural logarithm of the PDF.\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.degenerate.logpdf.factory( 10.0 );\n    > var y = mylogPDF( 10.0 )\n    Infinity","base.dists.degenerate.logpmf":"\nbase.dists.degenerate.logpmf( x, μ )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    degenerate distribution with mean `μ`.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPMF.\n\n    Examples\n    --------\n    > var y = base.dists.degenerate.logpmf( 2.0, 3.0 )\n    -Infinity\n    > y = base.dists.degenerate.logpmf( 3.0, 3.0 )\n    0.0\n    > y = base.dists.degenerate.logpmf( NaN, 0.0 )\n    NaN\n    > y = base.dists.degenerate.logpmf( 0.0, NaN )\n    NaN\n\n\nbase.dists.degenerate.logpmf.factory( μ )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogPMF = base.dists.degenerate.logpmf.factory( 10.0 );\n    > var y = mylogPMF( 10.0 )\n    0.0\n\n","base.dists.degenerate.logpmf.factory":"\nbase.dists.degenerate.logpmf.factory( μ )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogPMF = base.dists.degenerate.logpmf.factory( 10.0 );\n    > var y = mylogPMF( 10.0 )\n    0.0","base.dists.degenerate.mean":"\nbase.dists.degenerate.mean( μ )\n    Returns the expected value of a degenerate distribution with constant value\n    `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.degenerate.mean( 20.0 )\n    20.0\n    > v = base.dists.degenerate.mean( -10.0 )\n    -10.0\n\n","base.dists.degenerate.median":"\nbase.dists.degenerate.median( μ )\n    Returns the median of a degenerate distribution with constant value `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.degenerate.median( 20.0 )\n    20.0\n    > v = base.dists.degenerate.median( -10.0 )\n    -10.0\n\n","base.dists.degenerate.mgf":"\nbase.dists.degenerate.mgf( x, μ )\n    Evaluates the moment-generating function (MGF) for a degenerate distribution\n    with mean `μ`.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.degenerate.mgf( 1.0, 1.0 )\n    ~2.718\n    > y = base.dists.degenerate.mgf( 2.0, 3.0 )\n    ~403.429\n    > y = base.dists.degenerate.mgf( NaN, 0.0 )\n    NaN\n    > y = base.dists.degenerate.mgf( 0.0, NaN )\n    NaN\n\n\nbase.dists.degenerate.mgf.factory( μ )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.degenerate.mgf.factory( 10.0 );\n    > var y = myMGF( 0.1 )\n    ~2.718\n\n","base.dists.degenerate.mgf.factory":"\nbase.dists.degenerate.mgf.factory( μ )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.degenerate.mgf.factory( 10.0 );\n    > var y = myMGF( 0.1 )\n    ~2.718","base.dists.degenerate.mode":"\nbase.dists.degenerate.mode( μ )\n    Returns the mode of a degenerate distribution with constant value `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.degenerate.mode( 20.0 )\n    20.0\n    > v = base.dists.degenerate.mode( -10.0 )\n    -10.0\n\n","base.dists.degenerate.pdf":"\nbase.dists.degenerate.pdf( x, μ )\n    Evaluates the probability density function (PDF) for a degenerate\n    distribution with mean `μ`.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.degenerate.pdf( 2.0, 3.0 )\n    0.0\n    > y = base.dists.degenerate.pdf( 3.0, 3.0 )\n    Infinity\n    > y = base.dists.degenerate.pdf( NaN, 0.0 )\n    NaN\n    > y = base.dists.degenerate.pdf( 0.0, NaN )\n    NaN\n\n\nbase.dists.degenerate.pdf.factory( μ )\n    Returns a function for evaluating the probability density function (PDF) of\n    a degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.degenerate.pdf.factory( 10.0 );\n    > var y = myPDF( 10.0 )\n    Infinity\n\n","base.dists.degenerate.pdf.factory":"\nbase.dists.degenerate.pdf.factory( μ )\n    Returns a function for evaluating the probability density function (PDF) of\n    a degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.degenerate.pdf.factory( 10.0 );\n    > var y = myPDF( 10.0 )\n    Infinity","base.dists.degenerate.pmf":"\nbase.dists.degenerate.pmf( x, μ )\n    Evaluates the probability mass function (PMF) for a degenerate distribution\n    with mean `μ`.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Evaluated PMF.\n\n    Examples\n    --------\n    > var y = base.dists.degenerate.pmf( 2.0, 3.0 )\n    0.0\n    > y = base.dists.degenerate.pmf( 3.0, 3.0 )\n    1.0\n    > y = base.dists.degenerate.pmf( NaN, 0.0 )\n    NaN\n    > y = base.dists.degenerate.pmf( 0.0, NaN )\n    NaN\n\n\nbase.dists.degenerate.pmf.factory( μ )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var myPMF = base.dists.degenerate.pmf.factory( 10.0 );\n    > var y = myPMF( 10.0 )\n    1.0\n\n","base.dists.degenerate.pmf.factory":"\nbase.dists.degenerate.pmf.factory( μ )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var myPMF = base.dists.degenerate.pmf.factory( 10.0 );\n    > var y = myPMF( 10.0 )\n    1.0","base.dists.degenerate.quantile":"\nbase.dists.degenerate.quantile( p, μ )\n    Evaluates the quantile function for a degenerate distribution with mean `μ`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.degenerate.quantile( 0.5, 2.0 )\n    2.0\n    > y = base.dists.degenerate.quantile( 0.9, 4.0 )\n    4.0\n    > y = base.dists.degenerate.quantile( 1.1, 0.0 )\n    NaN\n    > y = base.dists.degenerate.quantile( -0.2, 0.0 )\n    NaN\n    > y = base.dists.degenerate.quantile( NaN, 0.0 )\n    NaN\n    > y = base.dists.degenerate.quantile( 0.0, NaN )\n    NaN\n\n\nbase.dists.degenerate.quantile.factory( μ )\n    Returns a function for evaluating the quantile function of a degenerate\n    distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.degenerate.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    10.0\n\n","base.dists.degenerate.quantile.factory":"\nbase.dists.degenerate.quantile.factory( μ )\n    Returns a function for evaluating the quantile function of a degenerate\n    distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.degenerate.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    10.0","base.dists.degenerate.stdev":"\nbase.dists.degenerate.stdev( μ )\n    Returns the standard deviation of a degenerate distribution with constant\n    value `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.degenerate.stdev( 20.0 )\n    0.0\n    > v = base.dists.degenerate.stdev( -10.0 )\n    0.0\n\n","base.dists.degenerate.variance":"\nbase.dists.degenerate.variance( μ )\n    Returns the variance of a degenerate distribution with constant value `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.degenerate.variance( 20.0 )\n    0.0\n    > v = base.dists.degenerate.variance( -10.0 )\n    0.0\n\n","base.dists.discreteUniform.cdf":"\nbase.dists.discreteUniform.cdf( x, a, b )\n    Evaluates the cumulative distribution function (CDF) for a discrete uniform\n    distribution with minimum support `a` and maximum support `b` at a value\n    `x`.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.discreteUniform.cdf( 9.0, 0, 10 )\n    ~0.909\n    > y = base.dists.discreteUniform.cdf( 0.5, 0, 2 )\n    ~0.333\n    > y = base.dists.discreteUniform.cdf( PINF, 2, 4 )\n    1.0\n    > y = base.dists.discreteUniform.cdf( NINF, 2, 4 )\n    0.0\n    > y = base.dists.discreteUniform.cdf( NaN, 0, 1 )\n    NaN\n    > y = base.dists.discreteUniform.cdf( 0.0, NaN, 1 )\n    NaN\n    > y = base.dists.discreteUniform.cdf( 0.0, 0, NaN )\n    NaN\n    > y = base.dists.discreteUniform.cdf( 2.0, 1, 0 )\n    NaN\n\n\nbase.dists.discreteUniform.cdf.factory( a, b )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a discrete uniform distribution with minimum support `a` and maximum\n    support `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.discreteUniform.cdf.factory( 0, 10 );\n    > var y = mycdf( 0.5 )\n    ~0.091\n    > y = mycdf( 8.0 )\n    ~0.818\n\n","base.dists.discreteUniform.cdf.factory":"\nbase.dists.discreteUniform.cdf.factory( a, b )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a discrete uniform distribution with minimum support `a` and maximum\n    support `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.discreteUniform.cdf.factory( 0, 10 );\n    > var y = mycdf( 0.5 )\n    ~0.091\n    > y = mycdf( 8.0 )\n    ~0.818","base.dists.discreteUniform.DiscreteUniform":"\nbase.dists.discreteUniform.DiscreteUniform( [a, b] )\n    Returns a discrete uniform distribution object.\n\n    Parameters\n    ----------\n    a: integer (optional)\n        Minimum support. Must be an integer smaller than `b`. Default: `0`.\n\n    b: integer (optional)\n        Maximum support. Must be an integer greater than `a`. Default: `1`.\n\n    Returns\n    -------\n    discreteUniform: Object\n        Distribution instance.\n\n    discreteUniform.a: integer\n        Minimum support. If set, the value must be an integer smaller than or\n        equal to `b`.\n\n    discreteUniform.b: integer\n        Maximum support. If set, the value must be an integer greater than or\n        equal to `a`.\n\n    discreteUniform.entropy: number\n        Read-only property which returns the entropy.\n\n    discreteUniform.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    discreteUniform.mean: number\n        Read-only property which returns the expected value.\n\n    discreteUniform.median: number\n        Read-only property which returns the median.\n\n    discreteUniform.skewness: number\n        Read-only property which returns the skewness.\n\n    discreteUniform.stdev: number\n        Read-only property which returns the standard deviation.\n\n    discreteUniform.variance: number\n        Read-only property which returns the variance.\n\n    discreteUniform.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    discreteUniform.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    discreteUniform.logpmf: Function\n        Evaluates the natural logarithm of the probability mass function (PMF).\n\n    discreteUniform.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    discreteUniform.pmf: Function\n        Evaluates the probability mass function (PMF).\n\n    discreteUniform.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var discreteUniform = base.dists.discreteUniform.DiscreteUniform( -2, 2 );\n    > discreteUniform.a\n    -2\n    > discreteUniform.b\n    2\n    > discreteUniform.entropy\n    ~1.609\n    > discreteUniform.kurtosis\n    -1.3\n    > discreteUniform.mean\n    0.0\n    > discreteUniform.median\n    0.0\n    > discreteUniform.skewness\n    0.0\n    > discreteUniform.stdev\n    ~1.414\n    > discreteUniform.variance\n    2.0\n    > discreteUniform.cdf( 0.8 )\n    0.6\n    > discreteUniform.logcdf( 0.5 )\n    ~-0.511\n    > discreteUniform.logpmf( 1.0 )\n    ~-1.609\n    > discreteUniform.mgf( 0.8 )\n    ~1.766\n    > discreteUniform.pmf( 0.0 )\n    0.2\n    > discreteUniform.quantile( 0.8 )\n    2.0\n\n","base.dists.discreteUniform.entropy":"\nbase.dists.discreteUniform.entropy( a, b )\n    Returns the entropy of a discrete uniform distribution.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.discreteUniform.entropy( 0, 1 )\n    ~0.693\n    > v = base.dists.discreteUniform.entropy( 4, 12 )\n    ~2.197\n    > v = base.dists.discreteUniform.entropy( 2, 8 )\n    ~1.946\n\n","base.dists.discreteUniform.kurtosis":"\nbase.dists.discreteUniform.kurtosis( a, b )\n    Returns the excess kurtosis of a discrete uniform distribution.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.discreteUniform.kurtosis( 0, 1 )\n    -2.0\n    > v = base.dists.discreteUniform.kurtosis( 4, 12 )\n    ~-1.23\n    > v = base.dists.discreteUniform.kurtosis( -4, 8 )\n    ~-1.214\n\n","base.dists.discreteUniform.logcdf":"\nbase.dists.discreteUniform.logcdf( x, a, b )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a discrete uniform distribution with minimum support `a` and\n    maximum support `b` at a value `x`.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.discreteUniform.logcdf( 9.0, 0, 10 )\n    ~-0.095\n    > y = base.dists.discreteUniform.logcdf( 0.5, 0, 2 )\n    ~-1.099\n    > y = base.dists.discreteUniform.logcdf( PINF, 2, 4 )\n    0.0\n    > y = base.dists.discreteUniform.logcdf( NINF, 2, 4 )\n    -Infinity\n    > y = base.dists.discreteUniform.logcdf( NaN, 0, 1 )\n    NaN\n    > y = base.dists.discreteUniform.logcdf( 0.0, NaN, 1 )\n    NaN\n    > y = base.dists.discreteUniform.logcdf( 0.0, 0, NaN )\n    NaN\n    > y = base.dists.discreteUniform.logcdf( 2.0, 1, 0 )\n    NaN\n\n\nbase.dists.discreteUniform.logcdf.factory( a, b )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a discrete uniform distribution with minimum\n    support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myLogCDF = base.dists.discreteUniform.logcdf.factory( 0, 10 );\n    > var y = myLogCDF( 0.5 )\n    ~-2.398\n    > y = myLogCDF( 8.0 )\n    ~-0.201\n\n","base.dists.discreteUniform.logcdf.factory":"\nbase.dists.discreteUniform.logcdf.factory( a, b )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a discrete uniform distribution with minimum\n    support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myLogCDF = base.dists.discreteUniform.logcdf.factory( 0, 10 );\n    > var y = myLogCDF( 0.5 )\n    ~-2.398\n    > y = myLogCDF( 8.0 )\n    ~-0.201","base.dists.discreteUniform.logpmf":"\nbase.dists.discreteUniform.logpmf( x, a, b )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    discrete uniform distribution with minimum support `a` and maximum support\n    `b` at a value `x`.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPMF.\n\n    Examples\n    --------\n    > var y = base.dists.discreteUniform.logpmf( 2.0, 0, 4 )\n    ~-1.609\n    > y = base.dists.discreteUniform.logpmf( 5.0, 0, 4 )\n    -Infinity\n    > y = base.dists.discreteUniform.logpmf( 3.0, -4, 4 )\n    ~-2.197\n    > y = base.dists.discreteUniform.logpmf( NaN, 0, 1 )\n    NaN\n    > y = base.dists.discreteUniform.logpmf( 0.0, NaN, 1 )\n    NaN\n    > y = base.dists.discreteUniform.logpmf( 0.0, 0, NaN )\n    NaN\n    > y = base.dists.discreteUniform.logpmf( 2.0, 3, 1 )\n    NaN\n    > y = base.dists.discreteUniform.logpmf( 2.0, 1, 2.4 )\n    NaN\n\n\nbase.dists.discreteUniform.logpmf.factory( a, b )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a discrete uniform distribution with minimum support\n    `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var myLogPMF = base.dists.discreteUniform.logpmf.factory( 6, 7 );\n    > var y = myLogPMF( 7.0 )\n    ~-0.693\n    > y = myLogPMF( 5.0 )\n    -Infinity\n\n","base.dists.discreteUniform.logpmf.factory":"\nbase.dists.discreteUniform.logpmf.factory( a, b )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a discrete uniform distribution with minimum support\n    `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var myLogPMF = base.dists.discreteUniform.logpmf.factory( 6, 7 );\n    > var y = myLogPMF( 7.0 )\n    ~-0.693\n    > y = myLogPMF( 5.0 )\n    -Infinity","base.dists.discreteUniform.mean":"\nbase.dists.discreteUniform.mean( a, b )\n    Returns the expected value of a discrete uniform distribution.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.discreteUniform.mean( -2, 2 )\n    0.0\n    > v = base.dists.discreteUniform.mean( 4, 12 )\n    8.0\n    > v = base.dists.discreteUniform.mean( 2, 8 )\n    5.0\n\n","base.dists.discreteUniform.median":"\nbase.dists.discreteUniform.median( a, b )\n    Returns the median of a discrete uniform distribution.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.discreteUniform.median( -2, 2 )\n    0.0\n    > v = base.dists.discreteUniform.median( 4, 12 )\n    8.0\n    > v = base.dists.discreteUniform.median( 2, 8 )\n    5.0\n\n","base.dists.discreteUniform.mgf":"\nbase.dists.discreteUniform.mgf( t, a, b )\n    Evaluates the moment-generating function (MGF) for a discrete uniform\n    distribution with minimum support `a` and maximum support `b` at a value\n    `t`.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.discreteUniform.mgf( 2.0, 0, 4 )\n    ~689.475\n    > y = base.dists.discreteUniform.mgf( -0.2, 0, 4 )\n    ~0.697\n    > y = base.dists.discreteUniform.mgf( 2.0, 0, 1 )\n    ~4.195\n    > y = base.dists.discreteUniform.mgf( 0.5, 3, 2 )\n    NaN\n    > y = base.dists.discreteUniform.mgf( NaN, 0, 1  )\n    NaN\n    > y = base.dists.discreteUniform.mgf( 0.0, NaN, 1 )\n    NaN\n    > y = base.dists.discreteUniform.mgf( 0.0, 0, NaN )\n    NaN\n\n\nbase.dists.discreteUniform.mgf.factory( a, b )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a discrete uniform distribution with minimum support `a` and maximum\n    support `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.discreteUniform.mgf.factory( 6, 7 );\n    > var y = mymgf( 0.1 )\n    ~1.918\n    > y = mymgf( 1.1 )\n    ~1471.722\n\n","base.dists.discreteUniform.mgf.factory":"\nbase.dists.discreteUniform.mgf.factory( a, b )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a discrete uniform distribution with minimum support `a` and maximum\n    support `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.discreteUniform.mgf.factory( 6, 7 );\n    > var y = mymgf( 0.1 )\n    ~1.918\n    > y = mymgf( 1.1 )\n    ~1471.722","base.dists.discreteUniform.pmf":"\nbase.dists.discreteUniform.pmf( x, a, b )\n    Evaluates the probability mass function (PMF) for a discrete uniform\n    distribution with minimum support `a` and maximum support `b` at a value\n    `x`.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated PMF.\n\n    Examples\n    --------\n    > var y = base.dists.discreteUniform.pmf( 2.0, 0, 4 )\n    ~0.2\n    > y = base.dists.discreteUniform.pmf( 5.0, 0, 4 )\n    0.0\n    > y = base.dists.discreteUniform.pmf( 3.0, -4, 4 )\n    ~0.111\n    > y = base.dists.discreteUniform.pmf( NaN, 0, 1 )\n    NaN\n    > y = base.dists.discreteUniform.pmf( 0.0, NaN, 1 )\n    NaN\n    > y = base.dists.discreteUniform.pmf( 0.0, 0, NaN )\n    NaN\n    > y = base.dists.discreteUniform.pmf( 2.0, 3, 1 )\n    NaN\n    > y = base.dists.discreteUniform.pmf( 2.0, 1, 2.4 )\n    NaN\n\n\nbase.dists.discreteUniform.pmf.factory( a, b )\n    Returns a function for evaluating the probability mass function (PMF) of\n    a discrete uniform distribution with minimum support `a` and maximum support\n    `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var myPMF = base.dists.discreteUniform.pmf.factory( 6, 7 );\n    > var y = myPMF( 7.0 )\n    0.5\n    > y = myPMF( 5.0 )\n    0.0\n\n","base.dists.discreteUniform.pmf.factory":"\nbase.dists.discreteUniform.pmf.factory( a, b )\n    Returns a function for evaluating the probability mass function (PMF) of\n    a discrete uniform distribution with minimum support `a` and maximum support\n    `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var myPMF = base.dists.discreteUniform.pmf.factory( 6, 7 );\n    > var y = myPMF( 7.0 )\n    0.5\n    > y = myPMF( 5.0 )\n    0.0","base.dists.discreteUniform.quantile":"\nbase.dists.discreteUniform.quantile( p, a, b )\n    Evaluates the quantile function for a discrete uniform distribution with\n    minimum support `a` and maximum support `b` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    If provided `a > b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.discreteUniform.quantile( 0.8, 0, 1 )\n    1\n    > y = base.dists.discreteUniform.quantile( 0.5, 0.0, 10.0 )\n    5\n\n    > y = base.dists.discreteUniform.quantile( 1.1, 0, 4 )\n    NaN\n    > y = base.dists.discreteUniform.quantile( -0.2, 0, 4 )\n    NaN\n\n    > y = base.dists.discreteUniform.quantile( NaN, -2, 2 )\n    NaN\n    > y = base.dists.discreteUniform.quantile( 0.1, NaN, 2 )\n    NaN\n    > y = base.dists.discreteUniform.quantile( 0.1, -2, NaN )\n    NaN\n\n    > y = base.dists.discreteUniform.quantile( 0.5, 2, 1 )\n    NaN\n\n\nbase.dists.discreteUniform.quantile.factory( a, b )\n    Returns a function for evaluating the quantile function of a discrete\n    uniform distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.discreteUniform.quantile.factory( 0, 4 );\n    > var y = myQuantile( 0.8 )\n    4\n\n","base.dists.discreteUniform.quantile.factory":"\nbase.dists.discreteUniform.quantile.factory( a, b )\n    Returns a function for evaluating the quantile function of a discrete\n    uniform distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.discreteUniform.quantile.factory( 0, 4 );\n    > var y = myQuantile( 0.8 )\n    4","base.dists.discreteUniform.skewness":"\nbase.dists.discreteUniform.skewness( a, b )\n    Returns the skewness of a discrete uniform distribution.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.discreteUniform.skewness( -2, 2 )\n    0.0\n    > v = base.dists.discreteUniform.skewness( 4, 12 )\n    0.0\n    > v = base.dists.discreteUniform.skewness( 2, 8 )\n    0.0\n\n","base.dists.discreteUniform.stdev":"\nbase.dists.discreteUniform.stdev( a, b )\n    Returns the standard deviation of a discrete uniform distribution.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.discreteUniform.stdev( 0, 1 )\n    ~0.5\n    > v = base.dists.discreteUniform.stdev( 4, 12 )\n    ~2.582\n    > v = base.dists.discreteUniform.stdev( 2, 8 )\n    2.0\n\n","base.dists.discreteUniform.variance":"\nbase.dists.discreteUniform.variance( a, b )\n    Returns the variance of a discrete uniform distribution.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.discreteUniform.variance( 0, 1 )\n    ~0.25\n    > v = base.dists.discreteUniform.variance( 4, 12 )\n    ~6.667\n    > v = base.dists.discreteUniform.variance( 2, 8 )\n    4.0\n\n","base.dists.erlang.cdf":"\nbase.dists.erlang.cdf( x, k, λ )\n    Evaluates the cumulative distribution function (CDF) for an Erlang\n    distribution with shape parameter `k` and rate parameter `λ` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.erlang.cdf( 2.0, 1, 1.0 )\n    ~0.865\n    > y = base.dists.erlang.cdf( 2.0, 3, 1.0 )\n    ~0.323\n    > y = base.dists.erlang.cdf( 2.0, 2.5, 1.0 )\n    NaN\n    > y = base.dists.erlang.cdf( -1.0, 2, 2.0 )\n    0.0\n    > y = base.dists.erlang.cdf( PINF, 4, 2.0 )\n    1.0\n    > y = base.dists.erlang.cdf( NINF, 4, 2.0 )\n    0.0\n    > y = base.dists.erlang.cdf( NaN, 0, 1.0 )\n    NaN\n    > y = base.dists.erlang.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.erlang.cdf( 0.0, 0, NaN )\n    NaN\n    > y = base.dists.erlang.cdf( 2.0, -1, 1.0 )\n    NaN\n    > y = base.dists.erlang.cdf( 2.0, 1, -1.0 )\n    NaN\n\n\nbase.dists.erlang.cdf.factory( k, λ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.erlang.cdf.factory( 2, 0.5 );\n    > var y = mycdf( 6.0 )\n    ~0.801\n    > y = mycdf( 2.0 )\n    ~0.264\n\n","base.dists.erlang.cdf.factory":"\nbase.dists.erlang.cdf.factory( k, λ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.erlang.cdf.factory( 2, 0.5 );\n    > var y = mycdf( 6.0 )\n    ~0.801\n    > y = mycdf( 2.0 )\n    ~0.264","base.dists.erlang.entropy":"\nbase.dists.erlang.entropy( k, λ )\n    Returns the differential entropy of an Erlang distribution (in nats).\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a positive integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: integer\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.erlang.entropy( 1, 1.0 )\n    ~1.0\n    > v = base.dists.erlang.entropy( 4, 12.0 )\n    ~-0.462\n    > v = base.dists.erlang.entropy( 8, 2.0 )\n    ~1.723\n\n","base.dists.erlang.Erlang":"\nbase.dists.erlang.Erlang( [k, λ] )\n    Returns an Erlang distribution object.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Shape parameter. Must be a positive integer. Default: `1.0`.\n\n    λ: number (optional)\n        Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    erlang: Object\n        Distribution instance.\n\n    erlang.k: number\n        Shape parameter. If set, the value must be a positive integer.\n\n    erlang.lambda: number\n        Rate parameter. If set, the value must be greater than `0`.\n\n    erlang.entropy: number\n        Read-only property which returns the differential entropy.\n\n    erlang.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    erlang.mean: number\n        Read-only property which returns the expected value.\n\n    erlang.mode: number\n        Read-only property which returns the mode.\n\n    erlang.skewness: number\n        Read-only property which returns the skewness.\n\n    erlang.stdev: number\n        Read-only property which returns the standard deviation.\n\n    erlang.variance: number\n        Read-only property which returns the variance.\n\n    erlang.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    erlang.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    erlang.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    erlang.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    erlang.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var erlang = base.dists.erlang.Erlang( 6, 5.0 );\n    > erlang.k\n    6\n    > erlang.lambda\n    5.0\n    > erlang.entropy\n    ~0.647\n    > erlang.kurtosis\n    1.0\n    > erlang.mean\n    1.2\n    > erlang.mode\n    1.0\n    > erlang.skewness\n    ~0.816\n    > erlang.stdev\n    ~0.49\n    > erlang.variance\n    0.24\n    > erlang.cdf( 3.0 )\n    ~0.997\n    > erlang.logpdf( 3.0 )\n    ~-4.638\n    > erlang.mgf( -0.5 )\n    ~0.564\n    > erlang.pdf( 3.0 )\n    ~0.01\n    > erlang.quantile( 0.8 )\n    ~1.581\n\n","base.dists.erlang.kurtosis":"\nbase.dists.erlang.kurtosis( k, λ )\n    Returns the excess kurtosis of an Erlang distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a positive integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: integer\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.erlang.kurtosis( 1, 1.0 )\n    6.0\n    > v = base.dists.erlang.kurtosis( 4, 12.0 )\n    1.5\n    > v = base.dists.erlang.kurtosis( 8, 2.0 )\n    0.75\n\n","base.dists.erlang.logpdf":"\nbase.dists.erlang.logpdf( x, k, λ )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for an Erlang distribution with shape parameter `k` and rate parameter `λ`\n    at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.erlang.logpdf( 0.1, 1, 1.0 )\n    ~-0.1\n    > y = base.dists.erlang.logpdf( 0.5, 2, 2.5 )\n    ~-0.111\n    > y = base.dists.erlang.logpdf( -1.0, 4, 2.0 )\n    -Infinity\n    > y = base.dists.erlang.logpdf( NaN, 1, 1.0 )\n    NaN\n    > y = base.dists.erlang.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.erlang.logpdf( 0.0, 1, NaN )\n    NaN\n    > y = base.dists.erlang.logpdf( 2.0, -2, 0.5 )\n    NaN\n    > y = base.dists.erlang.logpdf( 2.0, 0.5, 0.5 )\n    NaN\n    > y = base.dists.erlang.logpdf( 2.0, 0.0, 2.0 )\n    -Infinity\n    > y = base.dists.erlang.logpdf( 0.0, 0.0, 2.0 )\n    Infinity\n    > y = base.dists.erlang.logpdf( 2.0, 1, 0.0 )\n    NaN\n    > y = base.dists.erlang.logpdf( 2.0, 1, -1.0 )\n    NaN\n\n\nbase.dists.erlang.logpdf.factory( k, λ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of an Erlang distribution with shape parameter `k`\n    and rate parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var myLogPDF = base.dists.erlang.logpdf.factory( 6.0, 7.0 );\n    > y = myLogPDF( 7.0 )\n    ~-32.382\n\n\n","base.dists.erlang.logpdf.factory":"\nbase.dists.erlang.logpdf.factory( k, λ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of an Erlang distribution with shape parameter `k`\n    and rate parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var myLogPDF = base.dists.erlang.logpdf.factory( 6.0, 7.0 );\n    > y = myLogPDF( 7.0 )\n    ~-32.382","base.dists.erlang.mean":"\nbase.dists.erlang.mean( k, λ )\n    Returns the expected value of an Erlang distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a positive integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: integer\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.erlang.mean( 1, 1.0 )\n    1.0\n    > v = base.dists.erlang.mean( 4, 12.0 )\n    ~0.333\n    > v = base.dists.erlang.mean( 8, 2.0 )\n    4.0\n\n","base.dists.erlang.mgf":"\nbase.dists.erlang.mgf( t, k, λ )\n    Evaluates the moment-generating function (MGF) for an Erlang distribution\n    with shape parameter `k` and rate parameter `λ` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.erlang.mgf( 0.3, 1, 1.0 )\n    ~1.429\n    > y = base.dists.erlang.mgf( 2.0, 2, 3.0 )\n    ~9.0\n    > y = base.dists.erlang.mgf( -1.0, 2, 2.0 )\n    ~0.444\n\n    > y = base.dists.erlang.mgf( NaN, 1, 1.0 )\n    NaN\n    > y = base.dists.erlang.mgf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.erlang.mgf( 0.0, 1, NaN )\n    NaN\n\n    > y = base.dists.erlang.mgf( 0.2, -2, 0.5 )\n    NaN\n    > y = base.dists.erlang.mgf( 0.2, 0.5, 0.5 )\n    NaN\n\n    > y = base.dists.erlang.mgf( 0.2, 1, 0.0 )\n    NaN\n    > y = base.dists.erlang.mgf( 0.2, 1, -5.0 )\n    NaN\n\n\nbase.dists.erlang.mgf.factory( k, λ )\n    Returns a function for evaluating the moment-generating function (MGF) of an\n    Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.erlang.mgf.factory( 2, 0.5 );\n    > var y = myMGF( 0.2 )\n    ~2.778\n    > y = myMGF( -0.5 )\n    0.25\n\n","base.dists.erlang.mgf.factory":"\nbase.dists.erlang.mgf.factory( k, λ )\n    Returns a function for evaluating the moment-generating function (MGF) of an\n    Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.erlang.mgf.factory( 2, 0.5 );\n    > var y = myMGF( 0.2 )\n    ~2.778\n    > y = myMGF( -0.5 )\n    0.25","base.dists.erlang.mode":"\nbase.dists.erlang.mode( k, λ )\n    Returns the mode of an Erlang distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a positive integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: integer\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.erlang.mode( 1, 1.0 )\n    0.0\n    > v = base.dists.erlang.mode( 4, 12.0 )\n    0.25\n    > v = base.dists.erlang.mode( 8, 2.0 )\n    3.5\n\n","base.dists.erlang.pdf":"\nbase.dists.erlang.pdf( x, k, λ )\n    Evaluates the probability density function (PDF) for an Erlang distribution\n    with shape parameter `k` and rate parameter `λ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.erlang.pdf( 0.1, 1, 1.0 )\n    ~0.905\n    > y = base.dists.erlang.pdf( 0.5, 2, 2.5 )\n    ~0.895\n    > y = base.dists.erlang.pdf( -1.0, 4, 2.0 )\n    0.0\n    > y = base.dists.erlang.pdf( NaN, 1, 1.0 )\n    NaN\n    > y = base.dists.erlang.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.erlang.pdf( 0.0, 1, NaN )\n    NaN\n    > y = base.dists.erlang.pdf( 2.0, -2, 0.5 )\n    NaN\n    > y = base.dists.erlang.pdf( 2.0, 0.5, 0.5 )\n    NaN\n    > y = base.dists.erlang.pdf( 2.0, 0.0, 2.0 )\n    0.0\n    > y = base.dists.erlang.pdf( 0.0, 0.0, 2.0 )\n    Infinity\n    > y = base.dists.erlang.pdf( 2.0, 1, 0.0 )\n    NaN\n    > y = base.dists.erlang.pdf( 2.0, 1, -1.0 )\n    NaN\n\n\nbase.dists.erlang.pdf.factory( k, λ )\n    Returns a function for evaluating the probability density function (PDF)\n    of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.erlang.pdf.factory( 6.0, 7.0 );\n    > y = myPDF( 7.0 )\n    ~8.639e-15\n\n\n","base.dists.erlang.pdf.factory":"\nbase.dists.erlang.pdf.factory( k, λ )\n    Returns a function for evaluating the probability density function (PDF)\n    of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.erlang.pdf.factory( 6.0, 7.0 );\n    > y = myPDF( 7.0 )\n    ~8.639e-15","base.dists.erlang.quantile":"\nbase.dists.erlang.quantile( p, k, λ )\n    Evaluates the quantile function for an Erlang distribution with shape\n    parameter `k` and rate parameter `λ` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive number for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.erlang.quantile( 0.8, 2, 1.0 )\n    ~2.994\n    > y = base.dists.erlang.quantile( 0.5, 4, 2.0 )\n    ~1.836\n\n    > y = base.dists.erlang.quantile( 1.1, 1, 1.0 )\n    NaN\n    > y = base.dists.erlang.quantile( -0.2, 1, 1.0 )\n    NaN\n\n    > y = base.dists.erlang.quantile( NaN, 1, 1.0 )\n    NaN\n    > y = base.dists.erlang.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.erlang.quantile( 0.0, 1, NaN )\n    NaN\n\n    // Non-integer shape parameter:\n    > y = base.dists.erlang.quantile( 0.5, 0.5, 1.0 )\n    NaN\n    // Non-positive shape parameter:\n    > y = base.dists.erlang.quantile( 0.5, -1, 1.0 )\n    NaN\n    // Non-positive rate parameter:\n    > y = base.dists.erlang.quantile( 0.5, 1, -1.0 )\n    NaN\n\n\nbase.dists.erlang.quantile.factory( k, λ )\n    Returns a function for evaluating the quantile function of an Erlang\n    distribution with shape parameter `k` and rate parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.erlang.quantile.factory( 10, 2.0 );\n    > var y = myQuantile( 0.4 )\n    ~4.452\n\n","base.dists.erlang.quantile.factory":"\nbase.dists.erlang.quantile.factory( k, λ )\n    Returns a function for evaluating the quantile function of an Erlang\n    distribution with shape parameter `k` and rate parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.erlang.quantile.factory( 10, 2.0 );\n    > var y = myQuantile( 0.4 )\n    ~4.452","base.dists.erlang.skewness":"\nbase.dists.erlang.skewness( k, λ )\n    Returns the skewness of an Erlang distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a positive integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: integer\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.erlang.skewness( 1, 1.0 )\n    2.0\n    > v = base.dists.erlang.skewness( 4, 12.0 )\n    1.0\n    > v = base.dists.erlang.skewness( 8, 2.0 )\n    ~0.707\n\n","base.dists.erlang.stdev":"\nbase.dists.erlang.stdev( k, λ )\n    Returns the standard deviation of an Erlang distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a positive integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: integer\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.erlang.stdev( 1, 1.0 )\n    1.0\n    > v = base.dists.erlang.stdev( 4, 12.0 )\n    ~0.167\n    > v = base.dists.erlang.stdev( 8, 2.0 )\n    ~1.414\n\n","base.dists.erlang.variance":"\nbase.dists.erlang.variance( k, λ )\n    Returns the variance of an Erlang distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a positive integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: integer\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.erlang.variance( 1, 1.0 )\n    1.0\n    > v = base.dists.erlang.variance( 4, 12.0 )\n    ~0.028\n    > v = base.dists.erlang.variance( 8, 2.0 )\n    2.0\n\n","base.dists.exponential.cdf":"\nbase.dists.exponential.cdf( x, λ )\n    Evaluates the cumulative distribution function (CDF) for an exponential\n    distribution with rate parameter `λ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.exponential.cdf( 2.0, 0.1 )\n    ~0.181\n    > y = base.dists.exponential.cdf( 1.0, 2.0 )\n    ~0.865\n    > y = base.dists.exponential.cdf( -1.0, 4.0 )\n    0.0\n    > y = base.dists.exponential.cdf( NaN, 1.0 )\n    NaN\n    > y = base.dists.exponential.cdf( 0.0, NaN )\n    NaN\n\n    // Negative rate parameter:\n    > y = base.dists.exponential.cdf( 2.0, -1.0 )\n    NaN\n\nbase.dists.exponential.cdf.factory( λ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    for an exponential distribution with rate parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.exponential.cdf.factory( 0.5 );\n    > var y = myCDF( 3.0 )\n    ~0.777\n\n","base.dists.exponential.cdf.factory":"\nbase.dists.exponential.cdf.factory( λ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    for an exponential distribution with rate parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.exponential.cdf.factory( 0.5 );\n    > var y = myCDF( 3.0 )\n    ~0.777","base.dists.exponential.entropy":"\nbase.dists.exponential.entropy( λ )\n    Returns the differential entropy of an exponential distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.exponential.entropy( 11.0 )\n    ~-1.398\n    > v = base.dists.exponential.entropy( 4.5 )\n    ~-0.504\n\n","base.dists.exponential.Exponential":"\nbase.dists.exponential.Exponential( [λ] )\n    Returns an exponential distribution object.\n\n    Parameters\n    ----------\n    λ: number (optional)\n        Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    exponential: Object\n        Distribution instance.\n\n    exponential.lambda: number\n        Rate parameter. If set, the value must be greater than `0`.\n\n    exponential.entropy: number\n        Read-only property which returns the differential entropy.\n\n    exponential.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    exponential.mean: number\n        Read-only property which returns the expected value.\n\n    exponential.median: number\n        Read-only property which returns the median.\n\n    exponential.mode: number\n        Read-only property which returns the mode.\n\n    exponential.skewness: number\n        Read-only property which returns the skewness.\n\n    exponential.stdev: number\n        Read-only property which returns the standard deviation.\n\n    exponential.variance: number\n        Read-only property which returns the variance.\n\n    exponential.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    exponential.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    exponential.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    exponential.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    exponential.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    exponential.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var exponential = base.dists.exponential.Exponential( 6.0 );\n    > exponential.lambda\n    6.0\n    > exponential.entropy\n    ~-0.792\n    > exponential.kurtosis\n    6.0\n    > exponential.mean\n    ~0.167\n    > exponential.median\n    ~0.116\n    > exponential.mode\n    0.0\n    > exponential.skewness\n    2.0\n    > exponential.stdev\n    ~0.167\n    > exponential.variance\n    ~0.028\n    > exponential.cdf( 1.0 )\n    ~0.998\n    > exponential.logcdf( 1.0 )\n    ~-0.002\n    > exponential.logpdf( 1.5 )\n    ~-7.208\n    > exponential.mgf( -0.5 )\n    ~0.923\n    > exponential.pdf( 1.5 )\n    ~0.001\n    > exponential.quantile( 0.5 )\n    ~0.116\n\n","base.dists.exponential.kurtosis":"\nbase.dists.exponential.kurtosis( λ )\n    Returns the excess kurtosis of an exponential distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.exponential.kurtosis( 11.0 )\n    6.0\n    > v = base.dists.exponential.kurtosis( 4.5 )\n    6.0\n\n","base.dists.exponential.logcdf":"\nbase.dists.exponential.logcdf( x, λ )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for an exponential distribution with rate parameter `λ` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.exponential.logcdf( 2.0, 0.1 )\n    ~-1.708\n    > y = base.dists.exponential.logcdf( 1.0, 2.0 )\n    ~-0.145\n    > y = base.dists.exponential.logcdf( -1.0, 4.0 )\n    -Infinity\n    > y = base.dists.exponential.logcdf( NaN, 1.0 )\n    NaN\n    > y = base.dists.exponential.logcdf( 0.0, NaN )\n    NaN\n\n    // Negative rate parameter:\n    > y = base.dists.exponential.logcdf( 2.0, -1.0 )\n    NaN\n\nbase.dists.exponential.logcdf.factory( λ )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) for an exponential distribution with rate\n    parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogCDF = base.dists.exponential.logcdf.factory( 0.5 );\n    > var y = mylogCDF( 3.0 )\n    ~-0.252\n\n","base.dists.exponential.logcdf.factory":"\nbase.dists.exponential.logcdf.factory( λ )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) for an exponential distribution with rate\n    parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogCDF = base.dists.exponential.logcdf.factory( 0.5 );\n    > var y = mylogCDF( 3.0 )\n    ~-0.252","base.dists.exponential.logpdf":"\nbase.dists.exponential.logpdf( x, λ )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for an exponential distribution with rate parameter `λ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.exponential.logpdf( 0.3, 4.0 )\n    ~0.186\n    > y = base.dists.exponential.logpdf( 2.0, 0.7 )\n    ~-1.757\n    > y = base.dists.exponential.logpdf( -1.0, 0.5 )\n    -Infinity\n    > y = base.dists.exponential.logpdf( 0, NaN )\n    NaN\n    > y = base.dists.exponential.logpdf( NaN, 2.0 )\n    NaN\n\n    // Negative rate:\n    > y = base.dists.exponential.logpdf( 2.0, -1.0 )\n    NaN\n\nbase.dists.exponential.logpdf.factory( λ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) for an exponential distribution with rate parameter\n    `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.exponential.logpdf.factory( 0.5 );\n    > var y = mylogpdf( 3.0 )\n    ~-2.193\n\n","base.dists.exponential.logpdf.factory":"\nbase.dists.exponential.logpdf.factory( λ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) for an exponential distribution with rate parameter\n    `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.exponential.logpdf.factory( 0.5 );\n    > var y = mylogpdf( 3.0 )\n    ~-2.193","base.dists.exponential.mean":"\nbase.dists.exponential.mean( λ )\n    Returns the expected value of an exponential distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.exponential.mean( 11.0 )\n    ~0.091\n    > v = base.dists.exponential.mean( 4.5 )\n    ~0.222\n\n","base.dists.exponential.median":"\nbase.dists.exponential.median( λ )\n    Returns the median of an exponential distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.exponential.median( 11.0 )\n    ~0.063\n    > v = base.dists.exponential.median( 4.5 )\n    ~0.154\n\n","base.dists.exponential.mgf":"\nbase.dists.exponential.mgf( t, λ )\n    Evaluates the moment-generating function (MGF) for an exponential\n    distribution with rate parameter `λ` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var v = base.dists.exponential.mgf( 2.0, 3.0 )\n    3.0\n    > v = base.dists.exponential.mgf( 0.4, 1.2 )\n    1.5\n    > v = base.dists.exponential.mgf( 0.8, 1.6 )\n    2.0\n    > v = base.dists.exponential.mgf( 4.0, 3.0 )\n    NaN\n    > v = base.dists.exponential.mgf( NaN, 3.0 )\n    NaN\n    > v = base.dists.exponential.mgf( 2.0, NaN )\n    NaN\n\n\nbase.dists.exponential.mgf.factory( λ )\n    Returns a function for evaluating the moment-generating function (MGF) for\n    an exponential distribution with rate parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    mg: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.exponential.mgf.factory( 4.0 );\n    > var y = myMGF( 3.0 )\n    4.0\n    > y = myMGF( 0.5 )\n    ~1.143\n\n","base.dists.exponential.mgf.factory":"\nbase.dists.exponential.mgf.factory( λ )\n    Returns a function for evaluating the moment-generating function (MGF) for\n    an exponential distribution with rate parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    mg: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.exponential.mgf.factory( 4.0 );\n    > var y = myMGF( 3.0 )\n    4.0\n    > y = myMGF( 0.5 )\n    ~1.143","base.dists.exponential.mode":"\nbase.dists.exponential.mode( λ )\n    Returns the mode of an exponential distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.exponential.mode( 11.0 )\n    0.0\n    > v = base.dists.exponential.mode( 4.5 )\n    0.0\n\n","base.dists.exponential.pdf":"\nbase.dists.exponential.pdf( x, λ )\n    Evaluates the probability density function (PDF) for an exponential\n    distribution with rate parameter `λ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.exponential.pdf( 0.3, 4.0 )\n    ~1.205\n    > y = base.dists.exponential.pdf( 2.0, 0.7 )\n    ~0.173\n    > y = base.dists.exponential.pdf( -1.0, 0.5 )\n    0.0\n    > y = base.dists.exponential.pdf( 0, NaN )\n    NaN\n    > y = base.dists.exponential.pdf( NaN, 2.0 )\n    NaN\n\n    // Negative rate:\n    > y = base.dists.exponential.pdf( 2.0, -1.0 )\n    NaN\n\nbase.dists.exponential.pdf.factory( λ )\n    Returns a function for evaluating the probability density function (PDF)\n    for an exponential distribution with rate parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.exponential.pdf.factory( 0.5 );\n    > var y = myPDF( 3.0 )\n    ~0.112\n\n","base.dists.exponential.pdf.factory":"\nbase.dists.exponential.pdf.factory( λ )\n    Returns a function for evaluating the probability density function (PDF)\n    for an exponential distribution with rate parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.exponential.pdf.factory( 0.5 );\n    > var y = myPDF( 3.0 )\n    ~0.112","base.dists.exponential.quantile":"\nbase.dists.exponential.quantile( p, λ )\n    Evaluates the quantile function for an exponential distribution with rate\n    parameter `λ` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.exponential.quantile( 0.8, 1.0 )\n    ~1.609\n    > y = base.dists.exponential.quantile( 0.5, 4.0 )\n    ~0.173\n    > y = base.dists.exponential.quantile( 0.5, 0.1 )\n    ~6.931\n\n    > y = base.dists.exponential.quantile( -0.2, 0.1 )\n    NaN\n\n    > y = base.dists.exponential.quantile( NaN, 1.0 )\n    NaN\n    > y = base.dists.exponential.quantile( 0.0, NaN )\n    NaN\n\n    // Negative rate parameter:\n    > y = base.dists.exponential.quantile( 0.5, -1.0 )\n    NaN\n\n\nbase.dists.exponential.quantile.factory( λ )\n    Returns a function for evaluating the quantile function for an exponential\n    distribution with rate parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.exponential.quantile.factory( 0.4 );\n    > var y = myQuantile( 0.4 )\n    ~1.277\n    > y = myQuantile( 1.0 )\n    Infinity\n\n","base.dists.exponential.quantile.factory":"\nbase.dists.exponential.quantile.factory( λ )\n    Returns a function for evaluating the quantile function for an exponential\n    distribution with rate parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.exponential.quantile.factory( 0.4 );\n    > var y = myQuantile( 0.4 )\n    ~1.277\n    > y = myQuantile( 1.0 )\n    Infinity","base.dists.exponential.skewness":"\nbase.dists.exponential.skewness( λ )\n    Returns the skewness of an exponential distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.exponential.skewness( 11.0 )\n    2.0\n    > v = base.dists.exponential.skewness( 4.5 )\n    2.0\n\n","base.dists.exponential.stdev":"\nbase.dists.exponential.stdev( λ )\n    Returns the standard deviation of an exponential distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.exponential.stdev( 9.0 )\n    ~0.11\n    > v = base.dists.exponential.stdev( 1.0 )\n    1.0\n\n","base.dists.exponential.variance":"\nbase.dists.exponential.variance( λ )\n    Returns the variance of an exponential distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.exponential.variance( 9.0 )\n    ~0.012\n    > v = base.dists.exponential.variance( 1.0 )\n    1.0\n\n","base.dists.f.cdf":"\nbase.dists.f.cdf( x, d1, d2 )\n    Evaluates the cumulative distribution function (CDF) for an F distribution\n    with numerator degrees of freedom `d1` and denominator degrees of freedom\n    `d2` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.f.cdf( 2.0, 1.0, 1.0 )\n    ~0.608\n    > var y = base.dists.f.cdf( 2.0, 8.0, 4.0 )\n    ~0.737\n    > var y = base.dists.f.cdf( -1.0, 2.0, 2.0 )\n    0.0\n    > var y = base.dists.f.cdf( PINF, 4.0, 2.0 )\n    1.0\n    > var y = base.dists.f.cdf( NINF, 4.0, 2.0 )\n    0.0\n\n    > var y = base.dists.f.cdf( NaN, 1.0, 1.0 )\n    NaN\n    > var y = base.dists.f.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > var y = base.dists.f.cdf( 0.0, 1.0, NaN )\n    NaN\n\n    > var y = base.dists.f.cdf( 2.0, 1.0, -1.0 )\n    NaN\n    > var y = base.dists.f.cdf( 2.0, -1.0, 1.0 )\n    NaN\n\n\nbase.dists.f.cdf.factory( d1, d2 )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an F distribution with numerator degrees of freedom `d1` and denominator\n    degrees of freedom `d2`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.f.cdf.factory( 10.0, 2.0 );\n    > var y = myCDF( 10.0 )\n    ~0.906\n    > y = myCDF( 8.0 )\n    ~0.884\n\n","base.dists.f.cdf.factory":"\nbase.dists.f.cdf.factory( d1, d2 )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an F distribution with numerator degrees of freedom `d1` and denominator\n    degrees of freedom `d2`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.f.cdf.factory( 10.0, 2.0 );\n    > var y = myCDF( 10.0 )\n    ~0.906\n    > y = myCDF( 8.0 )\n    ~0.884","base.dists.f.entropy":"\nbase.dists.f.entropy( d1, d2 )\n    Returns the differential entropy of an F distribution (in nats).\n\n    If `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n    If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.f.entropy( 3.0, 7.0 )\n    ~1.298\n    > v = base.dists.f.entropy( 4.0, 12.0 )\n    ~1.12\n    > v = base.dists.f.entropy( 8.0, 2.0 )\n    ~2.144\n\n","base.dists.f.F":"\nbase.dists.f.F( [d1, d2] )\n    Returns an F distribution object.\n\n    Parameters\n    ----------\n    d1: number (optional)\n        Numerator degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n    d2: number (optional)\n        Denominator degrees of freedom. Must be greater than `0`.\n        Default: `1.0`.\n\n    Returns\n    -------\n    f: Object\n        Distribution instance.\n\n    f.d1: number\n        Numerator degrees of freedom. If set, the value must be greater than\n        `0`.\n\n    f.d2: number\n        Denominator degrees of freedom. If set, the value must be greater than\n        `0`.\n\n    f.entropy: number\n        Read-only property which returns the differential entropy.\n\n    f.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    f.mean: number\n        Read-only property which returns the expected value.\n\n    f.mode: number\n        Read-only property which returns the mode.\n\n    f.skewness: number\n        Read-only property which returns the skewness.\n\n    f.stdev: number\n        Read-only property which returns the standard deviation.\n\n    f.variance: number\n        Read-only property which returns the variance.\n\n    f.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    f.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    f.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var f = base.dists.f.F( 6.0, 9.0 );\n    > f.d1\n    6.0\n    > f.d2\n    9.0\n    > f.entropy\n    ~1.134\n    > f.kurtosis\n    ~104.564\n    > f.mean\n    ~1.286\n    > f.mode\n    ~0.545\n    > f.skewness\n    ~4.535\n    > f.stdev\n    ~1.197\n    > f.variance\n    ~1.433\n    > f.cdf( 3.0 )\n    ~0.932\n    > f.pdf( 2.5 )\n    ~0.095\n    > f.quantile( 0.8 )\n    ~1.826\n\n","base.dists.f.kurtosis":"\nbase.dists.f.kurtosis( d1, d2 )\n    Returns the excess kurtosis of an F distribution.\n\n    If `d1 <= 0` or `d2 <= 8`, the function returns `NaN`.\n\n    If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.f.kurtosis( 3.0, 9.0 )\n    ~124.667\n    > v = base.dists.f.kurtosis( 4.0, 12.0 )\n    ~26.143\n    > v = base.dists.f.kurtosis( 8.0, 9.0 )\n    ~100.167\n\n","base.dists.f.mean":"\nbase.dists.f.mean( d1, d2 )\n    Returns the expected value of an F distribution.\n\n    If `d1 <= 0` or `d2 <= 2`, the function returns `NaN`.\n\n    If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.f.mean( 3.0, 5.0 )\n    ~1.667\n    > v = base.dists.f.mean( 4.0, 12.0 )\n    ~1.2\n    > v = base.dists.f.mean( 8.0, 4.0 )\n    2.0\n\n","base.dists.f.mode":"\nbase.dists.f.mode( d1, d2 )\n    Returns the mode of an F distribution.\n\n    If `d1 <= 2` or `d2 <= 0`, the function returns `NaN`.\n\n    If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.f.mode( 3.0, 5.0 )\n    ~0.238\n    > v = base.dists.f.mode( 4.0, 12.0 )\n    ~0.429\n    > v = base.dists.f.mode( 8.0, 4.0 )\n    0.5\n\n","base.dists.f.pdf":"\nbase.dists.f.pdf( x, d1, d2 )\n    Evaluates the probability density function (PDF) for an F distribution with\n    numerator degrees of freedom `d1` and denominator degrees of freedom `d2` at\n    a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.f.pdf( 2.0, 0.5, 1.0 )\n    ~0.057\n    > y = base.dists.f.pdf( 0.1, 1.0, 1.0 )\n    ~0.915\n    > y = base.dists.f.pdf( -1.0, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.f.pdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.f.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.f.pdf( 0.0, 1.0, NaN )\n    NaN\n\n    > y = base.dists.f.pdf( 2.0, 1.0, -1.0 )\n    NaN\n    > y = base.dists.f.pdf( 2.0, -1.0, 1.0 )\n    NaN\n\n\nbase.dists.f.pdf.factory( d1, d2 )\n    Returns a function for evaluating the probability density function (PDF) of\n    an F distribution with numerator degrees of freedom `d1` and denominator\n    degrees of freedom `d2`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.f.pdf.factory( 6.0, 7.0 );\n    > var y = myPDF( 7.0 )\n    ~0.004\n    > y = myPDF( 2.0 )\n    ~0.166\n\n","base.dists.f.pdf.factory":"\nbase.dists.f.pdf.factory( d1, d2 )\n    Returns a function for evaluating the probability density function (PDF) of\n    an F distribution with numerator degrees of freedom `d1` and denominator\n    degrees of freedom `d2`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.f.pdf.factory( 6.0, 7.0 );\n    > var y = myPDF( 7.0 )\n    ~0.004\n    > y = myPDF( 2.0 )\n    ~0.166","base.dists.f.quantile":"\nbase.dists.f.quantile( p, d1, d2 )\n    Evaluates the quantile function for an F distribution with numerator degrees\n    of freedom `d1` and denominator degrees of freedom `d2` at a probability\n    `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.f.quantile( 0.8, 1.0, 1.0 )\n    ~9.472\n    > y = base.dists.f.quantile( 0.5, 4.0, 2.0 )\n    ~1.207\n\n    > y = base.dists.f.quantile( 1.1, 1.0, 1.0 )\n    NaN\n    > y = base.dists.f.quantile( -0.2, 1.0, 1.0 )\n    NaN\n\n    > y = base.dists.f.quantile( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.f.quantile( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.dists.f.quantile( 0.5, 1.0, NaN )\n    NaN\n\n    > y = base.dists.f.quantile( 0.5, -1.0, 1.0 )\n    NaN\n    > y = base.dists.f.quantile( 0.5, 1.0, -1.0 )\n    NaN\n\n\nbase.dists.f.quantile.factory( d1, d2 )\n    Returns a function for evaluating the quantile function of an F distribution\n    with numerator degrees of freedom `d1` and denominator degrees of freedom\n    `d2`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.f.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.2 )\n    ~0.527\n    > y = myQuantile( 0.8 )\n    ~4.382\n\n","base.dists.f.quantile.factory":"\nbase.dists.f.quantile.factory( d1, d2 )\n    Returns a function for evaluating the quantile function of an F distribution\n    with numerator degrees of freedom `d1` and denominator degrees of freedom\n    `d2`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.f.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.2 )\n    ~0.527\n    > y = myQuantile( 0.8 )\n    ~4.382","base.dists.f.skewness":"\nbase.dists.f.skewness( d1, d2 )\n    Returns the skewness of an F distribution.\n\n    If `d1 <= 0` or `d2 <= 6`, the function returns `NaN`.\n\n    If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.f.skewness( 3.0, 7.0 )\n    11.0\n    > v = base.dists.f.skewness( 4.0, 12.0 )\n    ~3.207\n    > v = base.dists.f.skewness( 8.0, 7.0 )\n    ~10.088\n\n","base.dists.f.stdev":"\nbase.dists.f.stdev( d1, d2 )\n    Returns the standard deviation of an F distribution.\n\n    If `d1 <= 0` or `d2 <= 4`, the function returns `NaN`.\n\n    If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.f.stdev( 3.0, 5.0 )\n    ~3.333\n    > v = base.dists.f.stdev( 4.0, 12.0 )\n    ~1.122\n    > v = base.dists.f.stdev( 8.0, 5.0 )\n    ~2.764\n\n","base.dists.f.variance":"\nbase.dists.f.variance( d1, d2 )\n    Returns the variance of an F distribution.\n\n    If `d1 <= 0` or `d2 <= 4`, the function returns `NaN`.\n\n    If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.f.variance( 3.0, 5.0 )\n    ~11.111\n    > v = base.dists.f.variance( 4.0, 12.0 )\n    ~1.26\n    > v = base.dists.f.variance( 8.0, 5.0 )\n    ~7.639\n\n","base.dists.frechet.cdf":"\nbase.dists.frechet.cdf( x, α, s, m )\n    Evaluates the cumulative distribution function (CDF) for a Fréchet\n    distribution with shape parameter `α`, scale parameter `s`, and location\n    `m`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.cdf( 10.0, 2.0, 3.0, 0.0 )\n    ~0.914\n    > y = base.dists.frechet.cdf( -1.0, 2.0, 3.0, -3.0 )\n    ~0.105\n    > y = base.dists.frechet.cdf( 2.5, 2.0, 1.0, 2.0 )\n    ~0.018\n    > y = base.dists.frechet.cdf( NaN, 1.0, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.cdf( 0.0, NaN, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.cdf( 0.0, 1.0, NaN, 0.0 )\n    NaN\n    > y = base.dists.frechet.cdf( 0.0, 1.0, 1.0, NaN )\n    NaN\n    > y = base.dists.frechet.cdf( 0.0, -1.0, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.cdf( 0.0, 1.0, -1.0, 0.0 )\n    NaN\n\n\nbase.dists.frechet.cdf.factory( α, s, m )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n    location `m`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.frechet.cdf.factory( 3.0, 3.0, 5.0 );\n    > var y = myCDF( 10.0 )\n    ~0.806\n    > y = myCDF( 7.0 )\n    ~0.034\n\n","base.dists.frechet.cdf.factory":"\nbase.dists.frechet.cdf.factory( α, s, m )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n    location `m`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.frechet.cdf.factory( 3.0, 3.0, 5.0 );\n    > var y = myCDF( 10.0 )\n    ~0.806\n    > y = myCDF( 7.0 )\n    ~0.034","base.dists.frechet.entropy":"\nbase.dists.frechet.entropy( α, s, m )\n    Returns the differential entropy of a Fréchet distribution with shape\n    parameter `α`, scale parameter `s`, and location `m` (in nats).\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.entropy( 1.0, 1.0, 1.0 )\n    ~2.154\n    > y = base.dists.frechet.entropy( 4.0, 2.0, 1.0 )\n    ~1.028\n    > y = base.dists.frechet.entropy( NaN, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.entropy( 1.0, NaN, 0.0 )\n    NaN\n    > y = base.dists.frechet.entropy( 1.0, 1.0, NaN )\n    NaN\n\n","base.dists.frechet.Frechet":"\nbase.dists.frechet.Frechet( [α, s, m] )\n    Returns a Fréchet distribution object.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n    s: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    m: number (optional)\n        Location parameter. Default: `0.0`.\n\n    Returns\n    -------\n    frechet: Object\n        Distribution instance.\n\n    frechet.alpha: number\n        Shape parameter. If set, the value must be greater than `0`.\n\n    frechet.s: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    frechet.m: number\n        Location parameter.\n\n    frechet.entropy: number\n        Read-only property which returns the differential entropy.\n\n    frechet.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    frechet.mean: number\n        Read-only property which returns the expected value.\n\n    frechet.median: number\n        Read-only property which returns the median.\n\n    frechet.mode: number\n        Read-only property which returns the mode.\n\n    frechet.skewness: number\n        Read-only property which returns the skewness.\n\n    frechet.stdev: number\n        Read-only property which returns the standard deviation.\n\n    frechet.variance: number\n        Read-only property which returns the variance.\n\n    frechet.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    frechet.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    frechet.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    frechet.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    frechet.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var frechet = base.dists.frechet.Frechet( 1.0, 1.0, 0.0 );\n    > frechet.alpha\n    1.0\n    > frechet.s\n    1.0\n    > frechet.m\n    0.0\n    > frechet.entropy\n    ~2.154\n    > frechet.kurtosis\n    Infinity\n    > frechet.mean\n    Infinity\n    > frechet.median\n    ~1.443\n    > frechet.mode\n    0.5\n    > frechet.skewness\n    Infinity\n    > frechet.stdev\n    Infinity\n    > frechet.variance\n    Infinity\n    > frechet.cdf( 0.8 )\n    ~0.287\n    > frechet.logcdf( 0.8 )\n    -1.25\n    > frechet.logpdf( 0.8 )\n    ~-0.804\n    > frechet.pdf( 0.8 )\n    ~0.448\n    > frechet.quantile( 0.8 )\n    ~4.481\n\n","base.dists.frechet.kurtosis":"\nbase.dists.frechet.kurtosis( α, s, m )\n    Returns the excess kurtosis of a Fréchet distribution with shape parameter\n    `α`, scale parameter `s`, and location `m`.\n\n    If provided `0 < α <= 4` and `s > 0`, the function returns positive\n    infinity.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.kurtosis( 5.0, 2.0, 1.0 )\n    ~45.092\n    > var y = base.dists.frechet.kurtosis( 5.0, 10.0, -3.0 )\n    ~45.092\n    > y = base.dists.frechet.kurtosis( 3.5, 2.0, 1.0 )\n    Infinity\n    > y = base.dists.frechet.kurtosis( NaN, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.kurtosis( 1.0, NaN, 0.0 )\n    NaN\n    > y = base.dists.frechet.kurtosis( 1.0, 1.0, NaN )\n    NaN\n\n","base.dists.frechet.logcdf":"\nbase.dists.frechet.logcdf( x, α, s, m )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a Fréchet distribution with shape parameter `α`, scale parameter\n    `s`, and location `m`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.logcdf( 10.0, 2.0, 3.0, 0.0 )\n    ~-0.09\n    > y = base.dists.frechet.logcdf( -1.0, 2.0, 3.0, -3.0 )\n    ~-2.25\n    > y = base.dists.frechet.logcdf( 2.5, 2.0, 1.0, 2.0 )\n    -4.0\n    > y = base.dists.frechet.logcdf( NaN, 1.0, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.logcdf( 0.0, NaN, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.logcdf( 0.0, 1.0, NaN, 0.0 )\n    NaN\n    > y = base.dists.frechet.logcdf( 0.0, 1.0, 1.0, NaN )\n    NaN\n    > y = base.dists.frechet.logcdf( 0.0, -1.0, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.logcdf( 0.0, 1.0, -1.0, 0.0 )\n    NaN\n\n\nbase.dists.frechet.logcdf.factory( α, s, m )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Fréchet distribution with shape parameter\n    `α`, scale parameter `s`, and location `m`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.frechet.logcdf.factory( 3.0, 3.0, 5.0 );\n    > var y = mylogcdf( 10.0 )\n    ~-0.216\n    > y = mylogcdf( 7.0 )\n    ~-3.375\n\n","base.dists.frechet.logcdf.factory":"\nbase.dists.frechet.logcdf.factory( α, s, m )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Fréchet distribution with shape parameter\n    `α`, scale parameter `s`, and location `m`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.frechet.logcdf.factory( 3.0, 3.0, 5.0 );\n    > var y = mylogcdf( 10.0 )\n    ~-0.216\n    > y = mylogcdf( 7.0 )\n    ~-3.375","base.dists.frechet.logpdf":"\nbase.dists.frechet.logpdf( x, α, s, m )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n    location `m`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.logpdf( 10.0, 1.0, 3.0, 5.0 )\n    ~-2.72\n    > y = base.dists.frechet.logpdf( -2.0, 1.0, 3.0, -3.0 )\n    ~-1.901\n    > y = base.dists.frechet.logpdf( 0.0, 2.0, 1.0, -1.0 )\n    ~-0.307\n    > y = base.dists.frechet.logpdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.frechet.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.frechet.logpdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.frechet.logpdf( 0.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.frechet.logpdf.factory( α, s, m )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Fréchet distribution with shape parameter `α`, scale\n    parameter `s`, and location `m`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.frechet.logpdf.factory( 2.0, 3.0, 1.0 );\n    > var y = mylogPDF( 10.0 )\n    ~-3.812\n    > y = mylogPDF( 2.0 )\n    ~-6.11\n\n","base.dists.frechet.logpdf.factory":"\nbase.dists.frechet.logpdf.factory( α, s, m )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Fréchet distribution with shape parameter `α`, scale\n    parameter `s`, and location `m`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.frechet.logpdf.factory( 2.0, 3.0, 1.0 );\n    > var y = mylogPDF( 10.0 )\n    ~-3.812\n    > y = mylogPDF( 2.0 )\n    ~-6.11","base.dists.frechet.mean":"\nbase.dists.frechet.mean( α, s, m )\n    Returns the expected value of a Fréchet distribution with shape parameter\n    `α`, scale parameter `s`, and location `m`.\n\n    If provided `0 < α <= 1` and `s > 0`, the function returns positive\n    infinity.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Mean.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.mean( 4.0, 2.0, 1.0 )\n    ~3.451\n    > y = base.dists.frechet.mean( 0.5, 2.0, 1.0 )\n    Infinity\n    > y = base.dists.frechet.mean( NaN, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.mean( 1.0, NaN, 0.0 )\n    NaN\n    > y = base.dists.frechet.mean( 1.0, 1.0, NaN )\n    NaN\n\n","base.dists.frechet.median":"\nbase.dists.frechet.median( α, s, m )\n    Returns the median of a Fréchet distribution with shape parameter\n    `α`, scale parameter `s`, and location `m`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.median( 4.0, 2.0, 1.0 )\n    ~3.192\n    > var y = base.dists.frechet.median( 4.0, 2.0, -3.0 )\n    ~-0.808\n    > y = base.dists.frechet.median( 0.5, 2.0, 1.0 )\n    ~5.163\n    > y = base.dists.frechet.median( NaN, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.median( 1.0, NaN, 0.0 )\n    NaN\n    > y = base.dists.frechet.median( 1.0, 1.0, NaN )\n    NaN\n\n","base.dists.frechet.mode":"\nbase.dists.frechet.mode( α, s, m )\n    Returns the mode of a Fréchet distribution with shape parameter `α`, scale\n    parameter `s`, and location `m`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.mode( 4.0, 2.0, 1.0 )\n    ~2.891\n    > var y = base.dists.frechet.mode( 4.0, 2.0, -3.0 )\n    ~-1.109\n    > y = base.dists.frechet.mode( 0.5, 2.0, 1.0 )\n    ~1.222\n    > y = base.dists.frechet.mode( NaN, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.mode( 1.0, NaN, 0.0 )\n    NaN\n    > y = base.dists.frechet.mode( 1.0, 1.0, NaN )\n    NaN\n\n","base.dists.frechet.pdf":"\nbase.dists.frechet.pdf( x, α, s, m )\n    Evaluates the probability density function (PDF) for a Fréchet distribution\n    with shape parameter `α`, scale parameter `s`, and location `m`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.pdf( 10.0, 0.0, 3.0 )\n    ~0.965\n    > y = base.dists.frechet.pdf( -2.0, 0.0, 3.0 )\n    ~0.143\n    > y = base.dists.frechet.pdf( 0.0, 0.0, 1.0 )\n    ~0.368\n    > y = base.dists.frechet.pdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.frechet.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.frechet.pdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.frechet.pdf( 0.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.frechet.pdf.factory( α, s, m )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n    location `m`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.frechet.pdf.factory( 2.0, 3.0 );\n    > var y = myPDF( 10.0 )\n    ~0.933\n    > y = myPDF( 2.0 )\n    ~0.368\n\n","base.dists.frechet.pdf.factory":"\nbase.dists.frechet.pdf.factory( α, s, m )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n    location `m`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.frechet.pdf.factory( 2.0, 3.0 );\n    > var y = myPDF( 10.0 )\n    ~0.933\n    > y = myPDF( 2.0 )\n    ~0.368","base.dists.frechet.quantile":"\nbase.dists.frechet.quantile( p, α, s, m )\n    Evaluates the quantile function for a Fréchet distribution with shape\n    parameter `α`, scale parameter `s`, and location `m`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.quantile( 0.3, 10.0, 2.0, 3.0 )\n    ~4.963\n    > y = base.dists.frechet.quantile( 0.2, 3.0, 3.0, 3.0 )\n    ~5.56\n    > y = base.dists.frechet.quantile( 0.9, 1.0, 1.0, -3.0 )\n    ~6.491\n    > y = base.dists.frechet.quantile( NaN, 1.0, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.quantile( 0.0, NaN, 1.0, 0.0)\n    NaN\n    > y = base.dists.frechet.quantile( 0.0, 1.0, NaN, 0.0 )\n    NaN\n    > y = base.dists.frechet.quantile( 0.0, 1.0, 1.0, NaN )\n    NaN\n    > y = base.dists.frechet.quantile( 0.0, -1.0, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.quantile( 0.0, 1.0, -1.0, 0.0 )\n    NaN\n\n\nbase.dists.frechet.quantile.factory( α, s, m )\n    Returns a function for evaluating the quantile function of a Fréchet\n    distribution with shape parameter `α`, scale parameter `s`, and location\n    `m`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.frechet.quantile.factory( 2.0, 2.0, 3.0 );\n    > var y = myQuantile( 0.5 )\n    ~5.402\n    > y = myQuantile( 0.2 )\n    ~4.576\n\n","base.dists.frechet.quantile.factory":"\nbase.dists.frechet.quantile.factory( α, s, m )\n    Returns a function for evaluating the quantile function of a Fréchet\n    distribution with shape parameter `α`, scale parameter `s`, and location\n    `m`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.frechet.quantile.factory( 2.0, 2.0, 3.0 );\n    > var y = myQuantile( 0.5 )\n    ~5.402\n    > y = myQuantile( 0.2 )\n    ~4.576","base.dists.frechet.skewness":"\nbase.dists.frechet.skewness( α, s, m )\n    Returns the skewness of a Fréchet distribution with shape parameter `α`,\n    scale parameter `s`, and location `m`.\n\n    If provided `0 < α <= 3` and `s > 0`, the function returns positive\n    infinity.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.skewness( 4.0, 2.0, 1.0 )\n    ~5.605\n    > var y = base.dists.frechet.skewness( 4.0, 2.0, -3.0 )\n    ~5.605\n    > y = base.dists.frechet.skewness( 0.5, 2.0, 1.0 )\n    Infinity\n    > y = base.dists.frechet.skewness( NaN, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.skewness( 1.0, NaN, 0.0 )\n    NaN\n    > y = base.dists.frechet.skewness( 1.0, 1.0, NaN )\n    NaN\n\n","base.dists.frechet.stdev":"\nbase.dists.frechet.stdev( α, s, m )\n    Returns the standard deviation of a Fréchet distribution with shape\n    parameter `α`, scale parameter `s`, and location `m`.\n\n    If provided `0 < α <= 2` and `s > 0`, the function returns positive\n    infinity.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.stdev( 4.0, 2.0, 1.0 )\n    ~1.041\n    > var y = base.dists.frechet.stdev( 4.0, 2.0, -3.0 )\n    ~1.041\n    > y = base.dists.frechet.stdev( 0.5, 2.0, 1.0 )\n    Infinity\n    > y = base.dists.frechet.stdev( NaN, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.stdev( 1.0, NaN, 0.0 )\n    NaN\n    > y = base.dists.frechet.stdev( 1.0, 1.0, NaN )\n    NaN\n\n","base.dists.frechet.variance":"\nbase.dists.frechet.variance( α, s, m )\n    Returns the variance of a Fréchet distribution with shape parameter `α`,\n    scale parameter `s`, and location `m`.\n\n    If provided `0 < α <= 2` and `s > 0`, the function returns positive\n    infinity.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.variance( 4.0, 2.0, 1.0 )\n    ~1.083\n    > var y = base.dists.frechet.variance( 4.0, 2.0, -3.0 )\n    ~1.083\n    > y = base.dists.frechet.variance( 0.5, 2.0, 1.0 )\n    Infinity\n    > y = base.dists.frechet.variance( NaN, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.variance( 1.0, NaN, 0.0 )\n    NaN\n    > y = base.dists.frechet.variance( 1.0, 1.0, NaN )\n    NaN\n\n","base.dists.gamma.cdf":"\nbase.dists.gamma.cdf( x, α, β )\n    Evaluates the cumulative distribution function (CDF) for a gamma\n    distribution with shape parameter `α` and rate parameter `β` at a value `x`.\n\n    If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.gamma.cdf( 2.0, 1.0, 1.0 )\n    ~0.865\n    > y = base.dists.gamma.cdf( 2.0, 3.0, 1.0 )\n    ~0.323\n    > y = base.dists.gamma.cdf( -1.0, 2.0, 2.0 )\n    0.0\n    > y = base.dists.gamma.cdf( PINF, 4.0, 2.0 )\n    1.0\n    > y = base.dists.gamma.cdf( NINF, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.gamma.cdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.gamma.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gamma.cdf( 0.0, 0.0, NaN )\n    NaN\n\n    > y = base.dists.gamma.cdf( 2.0, -1.0, 1.0 )\n    NaN\n    > y = base.dists.gamma.cdf( 2.0, 1.0, -1.0 )\n    NaN\n\n    // Degenerate distribution centered at `0` when `α = 0.0`:\n    > y = base.dists.gamma.cdf( 2.0, 0.0, 2.0 )\n    1.0\n    > y = base.dists.gamma.cdf( -2.0, 0.0, 2.0 )\n    0.0\n    > y = base.dists.gamma.cdf( 0.0, 0.0, 2.0 )\n    0.0\n\n\nbase.dists.gamma.cdf.factory( α, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.gamma.cdf.factory( 2.0, 0.5 );\n    > var y = myCDF( 6.0 )\n    ~0.801\n    > y = myCDF( 2.0 )\n    ~0.264\n\n","base.dists.gamma.cdf.factory":"\nbase.dists.gamma.cdf.factory( α, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.gamma.cdf.factory( 2.0, 0.5 );\n    > var y = myCDF( 6.0 )\n    ~0.801\n    > y = myCDF( 2.0 )\n    ~0.264","base.dists.gamma.entropy":"\nbase.dists.gamma.entropy( α, β )\n    Returns the differential entropy of a gamma distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.gamma.entropy( 1.0, 1.0 )\n    1.0\n    > v = base.dists.gamma.entropy( 4.0, 12.0 )\n    ~-0.462\n    > v = base.dists.gamma.entropy( 8.0, 2.0 )\n    ~1.723\n\n","base.dists.gamma.Gamma":"\nbase.dists.gamma.Gamma( [α, β] )\n    Returns a gamma distribution object.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n    β: number (optional)\n        Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    gamma: Object\n        Distribution instance.\n\n    gamma.alpha: number\n        Shape parameter. If set, the value must be greater than `0`.\n\n    gamma.beta: number\n        Rate parameter. If set, the value must be greater than `0`.\n\n    gamma.entropy: number\n        Read-only property which returns the differential entropy.\n\n    gamma.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    gamma.mean: number\n        Read-only property which returns the expected value.\n\n    gamma.mode: number\n        Read-only property which returns the mode.\n\n    gamma.skewness: number\n        Read-only property which returns the skewness.\n\n    gamma.stdev: number\n        Read-only property which returns the standard deviation.\n\n    gamma.variance: number\n        Read-only property which returns the variance.\n\n    gamma.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    gamma.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    gamma.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    gamma.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    gamma.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    gamma.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var gamma = base.dists.gamma.Gamma( 6.0, 5.0 );\n    > gamma.alpha\n    6.0\n    > gamma.beta\n    5.0\n    > gamma.entropy\n    ~0.647\n    > gamma.kurtosis\n    1.0\n    > gamma.mean\n    1.2\n    > gamma.mode\n    1.0\n    > gamma.skewness\n    ~0.816\n    > gamma.stdev\n    ~0.49\n    > gamma.variance\n    0.24\n    > gamma.cdf( 0.8 )\n    ~0.215\n    > gamma.logcdf( 0.8 )\n    ~-1.538\n    > gamma.logpdf( 1.0 )\n    ~-0.131\n    > gamma.mgf( -0.5 )\n    ~0.564\n    > gamma.pdf( 1.0 )\n    ~0.877\n    > gamma.quantile( 0.8 )\n    ~1.581\n\n","base.dists.gamma.kurtosis":"\nbase.dists.gamma.kurtosis( α, β )\n    Returns the excess kurtosis of a gamma distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.gamma.kurtosis( 1.0, 1.0 )\n    6.0\n    > v = base.dists.gamma.kurtosis( 4.0, 12.0 )\n    1.5\n    > v = base.dists.gamma.kurtosis( 8.0, 2.0 )\n    0.75\n\n","base.dists.gamma.logcdf":"\nbase.dists.gamma.logcdf( x, α, β )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    gamma distribution with shape parameter `α` and rate parameter `β` at a\n    value `x`.\n\n    If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.gamma.logcdf( 2.0, 0.5, 1.0 )\n    ~-0.047\n    > y = base.dists.gamma.logcdf( 0.1, 1.0, 1.0 )\n    ~-2.352\n    > y = base.dists.gamma.logcdf( -1.0, 4.0, 2.0 )\n    -Infinity\n\n    > y = base.dists.gamma.logcdf( NaN, 0.6, 1.0 )\n    NaN\n    > y = base.dists.gamma.logcdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gamma.logcdf( 0.0, 1.0, NaN )\n    NaN\n\n    // Negative shape parameter:\n    > y = base.dists.gamma.logcdf( 2.0, -1.0, 1.0 )\n    NaN\n    // Non-positive rate parameter:\n    > y = base.dists.gamma.logcdf( 2.0, 1.0, -1.0 )\n    NaN\n\n\nbase.dists.gamma.logcdf.factory( α, β )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a gamma distribution with shape parameter `α`\n    and rate parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogCDF = base.dists.gamma.logcdf.factory( 6.0, 7.0 );\n    > var y = mylogCDF( 2.0 )\n    ~-0.006\n\n","base.dists.gamma.logcdf.factory":"\nbase.dists.gamma.logcdf.factory( α, β )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a gamma distribution with shape parameter `α`\n    and rate parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogCDF = base.dists.gamma.logcdf.factory( 6.0, 7.0 );\n    > var y = mylogCDF( 2.0 )\n    ~-0.006","base.dists.gamma.logpdf":"\nbase.dists.gamma.logpdf( x, α, β )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    gamma distribution with shape parameter `α` and rate parameter `β` at a\n    value `x`.\n\n    If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.gamma.logpdf( 2.0, 0.5, 1.0 )\n    ~-2.919\n    > y = base.dists.gamma.logpdf( 0.1, 1.0, 1.0 )\n    ~-0.1\n    > y = base.dists.gamma.logpdf( -1.0, 4.0, 2.0 )\n    -Infinity\n\n    > y = base.dists.gamma.logpdf( NaN, 0.6, 1.0 )\n    NaN\n    > y = base.dists.gamma.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gamma.logpdf( 0.0, 1.0, NaN )\n    NaN\n\n    // Negative shape parameter:\n    > y = base.dists.gamma.logpdf( 2.0, -1.0, 1.0 )\n    NaN\n    // Non-positive rate parameter:\n    > y = base.dists.gamma.logpdf( 2.0, 1.0, -1.0 )\n    NaN\n\n    // Degenerate distribution centered at `0.0` when `α = 0.0`:\n    > y = base.dists.gamma.logpdf( 2.0, 0.0, 2.0 )\n    -Infinity\n    > y = base.dists.gamma.logpdf( 0.0, 0.0, 2.0 )\n    Infinity\n\n\nbase.dists.gamma.logpdf.factory( α, β )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a gamma distribution with shape parameter `α` and rate\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.gamma.logpdf.factory( 6.0, 7.0 );\n    > var y = mylogPDF( 2.0 )\n    ~-3.646\n\n","base.dists.gamma.logpdf.factory":"\nbase.dists.gamma.logpdf.factory( α, β )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a gamma distribution with shape parameter `α` and rate\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.gamma.logpdf.factory( 6.0, 7.0 );\n    > var y = mylogPDF( 2.0 )\n    ~-3.646","base.dists.gamma.mean":"\nbase.dists.gamma.mean( α, β )\n    Returns the expected value of a gamma distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.gamma.mean( 1.0, 1.0 )\n    1.0\n    > v = base.dists.gamma.mean( 4.0, 12.0 )\n    ~0.333\n    > v = base.dists.gamma.mean( 8.0, 2.0 )\n    4.0\n\n","base.dists.gamma.mgf":"\nbase.dists.gamma.mgf( t, α, β )\n    Evaluates the moment-generating function (MGF) for a gamma distribution with\n    shape parameter `α` and rate parameter `β` at a value `t`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.gamma.mgf( 0.5, 0.5, 1.0 )\n    ~1.414\n    > y = base.dists.gamma.mgf( 0.1, 1.0, 1.0 )\n    ~1.111\n    > y = base.dists.gamma.mgf( -1.0, 4.0, 2.0 )\n    ~0.198\n\n    > y = base.dists.gamma.mgf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.gamma.mgf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gamma.mgf( 0.0, 1.0, NaN )\n    NaN\n\n    > y = base.dists.gamma.mgf( 2.0, 4.0, 1.0 )\n    NaN\n    > y = base.dists.gamma.mgf( 2.0, -0.5, 1.0 )\n    NaN\n    > y = base.dists.gamma.mgf( 2.0, 1.0, 0.0 )\n    NaN\n    > y = base.dists.gamma.mgf( 2.0, 1.0, -1.0 )\n    NaN\n\n\nbase.dists.gamma.mgf.factory( α, β )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    gamma distribution with shape parameter `α` and rate parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.gamma.mgf.factory( 3.0, 1.5 );\n    > var y = myMGF( 1.0 )\n    ~27.0\n    > y = myMGF( 0.5 )\n    ~3.375\n\n","base.dists.gamma.mgf.factory":"\nbase.dists.gamma.mgf.factory( α, β )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    gamma distribution with shape parameter `α` and rate parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.gamma.mgf.factory( 3.0, 1.5 );\n    > var y = myMGF( 1.0 )\n    ~27.0\n    > y = myMGF( 0.5 )\n    ~3.375","base.dists.gamma.mode":"\nbase.dists.gamma.mode( α, β )\n    Returns the mode of a gamma distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.gamma.mode( 1.0, 1.0 )\n    0.0\n    > v = base.dists.gamma.mode( 4.0, 12.0 )\n    0.25\n    > v = base.dists.gamma.mode( 8.0, 2.0 )\n    3.5\n\n","base.dists.gamma.pdf":"\nbase.dists.gamma.pdf( x, α, β )\n    Evaluates the probability density function (PDF) for a gamma distribution\n    with shape parameter `α` and rate parameter `β` at a value `x`.\n\n    If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.gamma.pdf( 2.0, 0.5, 1.0 )\n    ~0.054\n    > y = base.dists.gamma.pdf( 0.1, 1.0, 1.0 )\n    ~0.905\n    > y = base.dists.gamma.pdf( -1.0, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.gamma.pdf( NaN, 0.6, 1.0 )\n    NaN\n    > y = base.dists.gamma.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gamma.pdf( 0.0, 1.0, NaN )\n    NaN\n\n    // Negative shape parameter:\n    > y = base.dists.gamma.pdf( 2.0, -1.0, 1.0 )\n    NaN\n    // Non-positive rate parameter:\n    > y = base.dists.gamma.pdf( 2.0, 1.0, -1.0 )\n    NaN\n\n    // Degenerate distribution centered at `0.0` when `α = 0.0`:\n    > y = base.dists.gamma.pdf( 2.0, 0.0, 2.0 )\n    0.0\n    > y = base.dists.gamma.pdf( 0.0, 0.0, 2.0 )\n    Infinity\n\n\nbase.dists.gamma.pdf.factory( α, β )\n    Returns a function for evaluating the probability density function (PDF) of\n    a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.gamma.pdf.factory( 6.0, 7.0 );\n    > var y = myPDF( 2.0 )\n    ~0.026\n\n","base.dists.gamma.pdf.factory":"\nbase.dists.gamma.pdf.factory( α, β )\n    Returns a function for evaluating the probability density function (PDF) of\n    a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.gamma.pdf.factory( 6.0, 7.0 );\n    > var y = myPDF( 2.0 )\n    ~0.026","base.dists.gamma.quantile":"\nbase.dists.gamma.quantile( p, α, β )\n    Evaluates the quantile function for a gamma distribution with shape\n    parameter `α` and rate parameter `β` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.gamma.quantile( 0.8, 2.0, 1.0 )\n    ~2.994\n    > y = base.dists.gamma.quantile( 0.5, 4.0, 2.0 )\n    ~1.836\n\n    > y = base.dists.gamma.quantile( 1.1, 1.0, 1.0 )\n    NaN\n    > y = base.dists.gamma.quantile( -0.2, 1.0, 1.0 )\n    NaN\n\n    > y = base.dists.gamma.quantile( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.gamma.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gamma.quantile( 0.0, 1.0, NaN )\n    NaN\n\n    // Non-positive shape parameter:\n    > y = base.dists.gamma.quantile( 0.5, -1.0, 1.0 )\n    NaN\n    // Non-positive rate parameter:\n    > y = base.dists.gamma.quantile( 0.5, 1.0, -1.0 )\n    NaN\n\n    // Degenerate distribution centered at `0.0` when `α = 0.0`:\n    > y = base.dists.gamma.quantile( 0.3, 0.0, 2.0 )\n    0.0\n    > y = base.dists.gamma.quantile( 0.9, 0.0, 2.0 )\n    0.0\n\n\nbase.dists.gamma.quantile.factory( α, β )\n    Returns a function for evaluating the quantile function of a gamma\n    distribution with shape parameter `α` and rate parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.gamma.quantile.factory( 2.0, 2.0 );\n    > var y = myQuantile( 0.8 )\n    ~1.497\n    > y = myQuantile( 0.4 )\n    ~0.688\n\n","base.dists.gamma.quantile.factory":"\nbase.dists.gamma.quantile.factory( α, β )\n    Returns a function for evaluating the quantile function of a gamma\n    distribution with shape parameter `α` and rate parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.gamma.quantile.factory( 2.0, 2.0 );\n    > var y = myQuantile( 0.8 )\n    ~1.497\n    > y = myQuantile( 0.4 )\n    ~0.688","base.dists.gamma.skewness":"\nbase.dists.gamma.skewness( α, β )\n    Returns the skewness of a gamma distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.gamma.skewness( 1.0, 1.0 )\n    2.0\n    > v = base.dists.gamma.skewness( 4.0, 12.0 )\n    1.0\n    > v = base.dists.gamma.skewness( 8.0, 2.0 )\n    ~0.707\n\n","base.dists.gamma.stdev":"\nbase.dists.gamma.stdev( α, β )\n    Returns the standard deviation of a gamma distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.gamma.stdev( 1.0, 1.0 )\n    1.0\n    > v = base.dists.gamma.stdev( 4.0, 12.0 )\n    ~0.167\n    > v = base.dists.gamma.stdev( 8.0, 2.0 )\n    ~1.414\n\n","base.dists.gamma.variance":"\nbase.dists.gamma.variance( α, β )\n    Returns the variance of a gamma distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.gamma.variance( 1.0, 1.0 )\n    1.0\n    > v = base.dists.gamma.variance( 4.0, 12.0 )\n    ~0.028\n    > v = base.dists.gamma.variance( 8.0, 2.0 )\n    2.0\n\n","base.dists.geometric.cdf":"\nbase.dists.geometric.cdf( x, p )\n    Evaluates the cumulative distribution function (CDF) for a geometric\n    distribution with success probability `p` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.geometric.cdf( 2.0, 0.5 )\n    0.875\n    > y = base.dists.geometric.cdf( 2.0, 0.1 )\n    ~0.271\n    > y = base.dists.geometric.cdf( -1.0, 4.0 )\n    0.0\n    > y = base.dists.geometric.cdf( NaN, 0.5 )\n    NaN\n    > y = base.dists.geometric.cdf( 0.0, NaN )\n    NaN\n    // Invalid probability\n    > y = base.dists.geometric.cdf( 2.0, 1.4 )\n    NaN\n\n\nbase.dists.geometric.cdf.factory( p )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a geometric distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.geometric.cdf.factory( 0.5 );\n    > var y = mycdf( 3.0 )\n    0.9375\n    > y = mycdf( 1.0 )\n    0.75\n\n","base.dists.geometric.cdf.factory":"\nbase.dists.geometric.cdf.factory( p )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a geometric distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.geometric.cdf.factory( 0.5 );\n    > var y = mycdf( 3.0 )\n    0.9375\n    > y = mycdf( 1.0 )\n    0.75","base.dists.geometric.entropy":"\nbase.dists.geometric.entropy( p )\n    Returns the entropy of a geometric distribution with success probability\n    `p` (in nats).\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.geometric.entropy( 0.1 )\n    ~3.251\n    > v = base.dists.geometric.entropy( 0.5 )\n    ~1.386\n\n","base.dists.geometric.Geometric":"\nbase.dists.geometric.Geometric( [p] )\n    Returns a geometric distribution object.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability. Must be between `0` and `1`. Default: `0.5`.\n\n    Returns\n    -------\n    geometric: Object\n        Distribution instance.\n\n    geometric.p: number\n        Success probability. If set, the value must be between `0` and `1`.\n\n    geometric.entropy: number\n        Read-only property which returns the differential entropy.\n\n    geometric.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    geometric.mean: number\n        Read-only property which returns the expected value.\n\n    geometric.median: number\n        Read-only property which returns the median.\n\n    geometric.mode: number\n        Read-only property which returns the mode.\n\n    geometric.skewness: number\n        Read-only property which returns the skewness.\n\n    geometric.stdev: number\n        Read-only property which returns the standard deviation.\n\n    geometric.variance: number\n        Read-only property which returns the variance.\n\n    geometric.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    geometric.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    geometric.logpmf: Function\n        Evaluates the natural logarithm of the probability mass function (PMF).\n\n    geometric.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    geometric.pmf: Function\n        Evaluates the probability mass function (PMF).\n\n    geometric.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var geometric = base.dists.geometric.Geometric( 0.6 );\n    > geometric.p\n    0.6\n    > geometric.entropy\n    ~1.122\n    > geometric.kurtosis\n    ~6.9\n    > geometric.mean\n    ~0.667\n    > geometric.median\n    0.0\n    > geometric.mode\n    0.0\n    > geometric.skewness\n    ~2.214\n    > geometric.stdev\n    ~1.054\n    > geometric.variance\n    ~1.111\n    > geometric.cdf( 3.0 )\n    ~0.974\n    > geometric.logcdf( 3.0 )\n    ~-0.026\n    > geometric.logpmf( 4.0 )\n    ~-4.176\n    > geometric.mgf( 0.5 )\n    ~2.905\n    > geometric.pmf( 2.0 )\n    ~0.096\n    > geometric.quantile( 0.7 )\n    1.0\n\n","base.dists.geometric.kurtosis":"\nbase.dists.geometric.kurtosis( p )\n    Returns the excess kurtosis of a geometric distribution with success\n    probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.geometric.kurtosis( 0.1 )\n    ~6.011\n    > v = base.dists.geometric.kurtosis( 0.5 )\n    6.5\n\n","base.dists.geometric.logcdf":"\nbase.dists.geometric.logcdf( x, p )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    geometric distribution with success probability `p` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.geometric.logcdf( 2.0, 0.5 )\n    ~-0.134\n    > y = base.dists.geometric.logcdf( 2.0, 0.1 )\n    ~-1.306\n    > y = base.dists.geometric.logcdf( -1.0, 4.0 )\n    -Infinity\n    > y = base.dists.geometric.logcdf( NaN, 0.5 )\n    NaN\n    > y = base.dists.geometric.logcdf( 0.0, NaN )\n    NaN\n    // Invalid probability\n    > y = base.dists.geometric.logcdf( 2.0, 1.4 )\n    NaN\n\n\nbase.dists.geometric.logcdf.factory( p )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a geometric distribution with success\n    probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.geometric.logcdf.factory( 0.5 );\n    > var y = mylogcdf( 3.0 )\n    ~-0.065\n    > y = mylogcdf( 1.0 )\n    ~-0.288\n\n","base.dists.geometric.logcdf.factory":"\nbase.dists.geometric.logcdf.factory( p )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a geometric distribution with success\n    probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.geometric.logcdf.factory( 0.5 );\n    > var y = mylogcdf( 3.0 )\n    ~-0.065\n    > y = mylogcdf( 1.0 )\n    ~-0.288","base.dists.geometric.logpmf":"\nbase.dists.geometric.logpmf( x, p )\n    Evaluates the logarithm of the probability mass function (PMF) for a\n    geometric distribution with success probability `p` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPMF.\n\n    Examples\n    --------\n    > var y = base.dists.geometric.logpmf( 4.0, 0.3 )\n    ~-2.631\n    > y = base.dists.geometric.logpmf( 2.0, 0.7 )\n    ~-2.765\n    > y = base.dists.geometric.logpmf( -1.0, 0.5 )\n    -Infinity\n    > y = base.dists.geometric.logpmf( 0.0, NaN )\n    NaN\n    > y = base.dists.geometric.logpmf( NaN, 0.5 )\n    NaN\n    // Invalid success probability:\n    > y = base.dists.geometric.logpmf( 2.0, 1.5 )\n    NaN\n\n\nbase.dists.geometric.logpmf.factory( p )\n    Returns a function for evaluating the logarithm of the probability mass\n    function (PMF) of a geometric distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogpmf = base.dists.geometric.logpmf.factory( 0.5 );\n    > var y = mylogpmf( 3.0 )\n    ~-2.773\n    > y = mylogpmf( 1.0 )\n    ~-1.386\n\n","base.dists.geometric.logpmf.factory":"\nbase.dists.geometric.logpmf.factory( p )\n    Returns a function for evaluating the logarithm of the probability mass\n    function (PMF) of a geometric distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogpmf = base.dists.geometric.logpmf.factory( 0.5 );\n    > var y = mylogpmf( 3.0 )\n    ~-2.773\n    > y = mylogpmf( 1.0 )\n    ~-1.386","base.dists.geometric.mean":"\nbase.dists.geometric.mean( p )\n    Returns the expected value of a geometric distribution with success\n    probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.geometric.mean( 0.1 )\n    9.0\n    > v = base.dists.geometric.mean( 0.5 )\n    1.0\n\n","base.dists.geometric.median":"\nbase.dists.geometric.median( p )\n    Returns the median of a geometric distribution with success probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: integer\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.geometric.median( 0.1 )\n    6\n    > v = base.dists.geometric.median( 0.5 )\n    0\n\n","base.dists.geometric.mgf":"\nbase.dists.geometric.mgf( t, p )\n    Evaluates the moment-generating function (MGF) for a geometric\n    distribution with success probability `p` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If `t >= -ln(1-p)`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.geometric.mgf( 0.2, 0.5 )\n    ~1.569\n    > y = base.dists.geometric.mgf( 0.4, 0.5 )\n    ~2.936\n    // Case: t >= -ln(1-p)\n    > y = base.dists.geometric.mgf( 0.8, 0.5 )\n    NaN\n    > y = base.dists.geometric.mgf( NaN, 0.0 )\n    NaN\n    > y = base.dists.geometric.mgf( 0.0, NaN )\n    NaN\n    > y = base.dists.geometric.mgf( -2.0, -1.0 )\n    NaN\n    > y = base.dists.geometric.mgf( 0.2, 2.0 )\n    NaN\n\n\nbase.dists.geometric.mgf.factory( p )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    geometric distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.geometric.mgf.factory( 0.8 );\n    > var y = mymgf( -0.2 )\n    ~0.783\n\n","base.dists.geometric.mgf.factory":"\nbase.dists.geometric.mgf.factory( p )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    geometric distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.geometric.mgf.factory( 0.8 );\n    > var y = mymgf( -0.2 )\n    ~0.783","base.dists.geometric.mode":"\nbase.dists.geometric.mode( p )\n    Returns the mode of a geometric distribution with success probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: integer\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.geometric.mode( 0.1 )\n    0\n    > v = base.dists.geometric.mode( 0.5 )\n    0\n\n","base.dists.geometric.pmf":"\nbase.dists.geometric.pmf( x, p )\n    Evaluates the probability mass function (PMF) for a geometric distribution\n    with success probability `p` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated PMF.\n\n    Examples\n    --------\n    > var y = base.dists.geometric.pmf( 4.0, 0.3 )\n    ~0.072\n    > y = base.dists.geometric.pmf( 2.0, 0.7 )\n    ~0.063\n    > y = base.dists.geometric.pmf( -1.0, 0.5 )\n    0.0\n    > y = base.dists.geometric.pmf( 0.0, NaN )\n    NaN\n    > y = base.dists.geometric.pmf( NaN, 0.5 )\n    NaN\n    // Invalid success probability:\n    > y = base.dists.geometric.pmf( 2.0, 1.5 )\n    NaN\n\n\nbase.dists.geometric.pmf.factory( p )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    geometric distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var mypmf = base.dists.geometric.pmf.factory( 0.5 );\n    > var y = mypmf( 3.0 )\n    0.0625\n    > y = mypmf( 1.0 )\n    0.25\n\n","base.dists.geometric.pmf.factory":"\nbase.dists.geometric.pmf.factory( p )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    geometric distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var mypmf = base.dists.geometric.pmf.factory( 0.5 );\n    > var y = mypmf( 3.0 )\n    0.0625\n    > y = mypmf( 1.0 )\n    0.25","base.dists.geometric.quantile":"\nbase.dists.geometric.quantile( r, p )\n    Evaluates the quantile function for a geometric distribution with success\n    probability `p` at a probability `r`.\n\n    If `r < 0` or `r > 1`, the function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    r: number\n        Input probability.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.geometric.quantile( 0.8, 0.4 )\n    3\n    > y = base.dists.geometric.quantile( 0.5, 0.4 )\n    1\n    > y = base.dists.geometric.quantile( 0.9, 0.1 )\n    21\n\n    > y = base.dists.geometric.quantile( -0.2, 0.1 )\n    NaN\n\n    > y = base.dists.geometric.quantile( NaN, 0.8 )\n    NaN\n    > y = base.dists.geometric.quantile( 0.4, NaN )\n    NaN\n\n    > y = base.dists.geometric.quantile( 0.5, -1.0 )\n    NaN\n    > y = base.dists.geometric.quantile( 0.5, 1.5 )\n    NaN\n\n\nbase.dists.geometric.quantile.factory( p )\n    Returns a function for evaluating the quantile function of a geometric\n    distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.geometric.quantile.factory( 0.4 );\n    > var y = myquantile( 0.4 )\n    0\n    > y = myquantile( 0.8 )\n    3\n    > y = myquantile( 1.0 )\n    Infinity\n\n","base.dists.geometric.quantile.factory":"\nbase.dists.geometric.quantile.factory( p )\n    Returns a function for evaluating the quantile function of a geometric\n    distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.geometric.quantile.factory( 0.4 );\n    > var y = myquantile( 0.4 )\n    0\n    > y = myquantile( 0.8 )\n    3\n    > y = myquantile( 1.0 )\n    Infinity","base.dists.geometric.skewness":"\nbase.dists.geometric.skewness( p )\n    Returns the skewness of a geometric distribution with success probability\n    `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.geometric.skewness( 0.1 )\n    ~2.003\n    > v = base.dists.geometric.skewness( 0.5 )\n    ~2.121\n\n","base.dists.geometric.stdev":"\nbase.dists.geometric.stdev( p )\n    Returns the standard deviation of a geometric distribution with success\n    probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.geometric.stdev( 0.1 )\n    ~9.487\n    > v = base.dists.geometric.stdev( 0.5 )\n    ~1.414\n\n","base.dists.geometric.variance":"\nbase.dists.geometric.variance( p )\n    Returns the variance of a geometric distribution with success probability\n    `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.geometric.variance( 0.1 )\n    ~90.0\n    > v = base.dists.geometric.variance( 0.5 )\n    2.0\n\n","base.dists.gumbel.cdf":"\nbase.dists.gumbel.cdf( x, μ, β )\n    Evaluates the cumulative distribution function (CDF) for a Gumbel\n    distribution with location parameter `μ` and scale parameter `β` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.cdf( 10.0, 0.0, 3.0 )\n    ~0.965\n    > y = base.dists.gumbel.cdf( -2.0, 0.0, 3.0 )\n    ~0.143\n    > y = base.dists.gumbel.cdf( 0.0, 0.0, 1.0 )\n    ~0.368\n    > y = base.dists.gumbel.cdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.gumbel.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.cdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.gumbel.cdf( 0.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.gumbel.cdf.factory( μ, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Gumbel distribution with location parameter `μ` and scale parameter\n    `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.gumbel.cdf.factory( 2.0, 3.0 );\n    > var y = myCDF( 10.0 )\n    ~0.933\n    > y = myCDF( 2.0 )\n    ~0.368\n\n","base.dists.gumbel.cdf.factory":"\nbase.dists.gumbel.cdf.factory( μ, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Gumbel distribution with location parameter `μ` and scale parameter\n    `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.gumbel.cdf.factory( 2.0, 3.0 );\n    > var y = myCDF( 10.0 )\n    ~0.933\n    > y = myCDF( 2.0 )\n    ~0.368","base.dists.gumbel.entropy":"\nbase.dists.gumbel.entropy( μ, β )\n    Returns the differential entropy of a Gumbel distribution with location\n    parameter `μ` and scale parameter `β` (in nats).\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.entropy( 0.0, 1.0 )\n    ~1.577\n    > y = base.dists.gumbel.entropy( 4.0, 2.0 )\n    ~2.27\n    > y = base.dists.gumbel.entropy( NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.entropy( 0.0, NaN )\n    NaN\n    > y = base.dists.gumbel.entropy( 0.0, 0.0 )\n    NaN\n\n","base.dists.gumbel.Gumbel":"\nbase.dists.gumbel.Gumbel( [μ, β] )\n    Returns a Gumbel distribution object.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter. Default: `0.0`.\n\n    β: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    gumbel: Object\n        Distribution instance.\n\n    gumbel.mu: number\n        Location parameter.\n\n    gumbel.beta: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    gumbel.entropy: number\n        Read-only property which returns the differential entropy.\n\n    gumbel.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    gumbel.mean: number\n        Read-only property which returns the expected value.\n\n    gumbel.median: number\n        Read-only property which returns the median.\n\n    gumbel.mode: number\n        Read-only property which returns the mode.\n\n    gumbel.skewness: number\n        Read-only property which returns the skewness.\n\n    gumbel.stdev: number\n        Read-only property which returns the standard deviation.\n\n    gumbel.variance: number\n        Read-only property which returns the variance.\n\n    gumbel.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    gumbel.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    gumbel.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    gumbel.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    gumbel.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    gumbel.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var gumbel = base.dists.gumbel.Gumbel( -2.0, 3.0 );\n    > gumbel.mu\n    -2.0\n    > gumbel.beta\n    3.0\n    > gumbel.entropy\n    ~2.676\n    > gumbel.kurtosis\n    2.4\n    > gumbel.mean\n    ~-0.268\n    > gumbel.median\n    ~-0.9\n    > gumbel.mode\n    -2.0\n    > gumbel.skewness\n    ~1.14\n    > gumbel.stdev\n    ~3.848\n    > gumbel.variance\n    ~14.804\n    > gumbel.cdf( 0.8 )\n    ~0.675\n    > gumbel.logcdf( 0.8 )\n    ~-0.393\n    > gumbel.logpdf( 1.0 )\n    ~-2.466\n    > gumbel.mgf( 0.2 )\n    ~1.487\n    > gumbel.pdf( 1.0 )\n    ~0.085\n    > gumbel.quantile( 0.8 )\n    ~2.5\n\n","base.dists.gumbel.kurtosis":"\nbase.dists.gumbel.kurtosis( μ, β )\n    Returns the excess kurtosis of a Gumbel distribution with location parameter\n    `μ` and scale parameter `β`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.kurtosis( 0.0, 1.0 )\n    2.4\n    > y = base.dists.gumbel.kurtosis( 4.0, 2.0 )\n    2.4\n    > y = base.dists.gumbel.kurtosis( NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.kurtosis( 0.0, NaN )\n    NaN\n    > y = base.dists.gumbel.kurtosis( 0.0, 0.0 )\n    NaN\n\n","base.dists.gumbel.logcdf":"\nbase.dists.gumbel.logcdf( x, μ, β )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.logcdf( 10.0, 0.0, 3.0 )\n    ~-0.036\n    > y = base.dists.gumbel.logcdf( -2.0, 0.0, 3.0 )\n    ~-1.948\n    > y = base.dists.gumbel.logcdf( 0.0, 0.0, 1.0 )\n    ~-1.0\n    > y = base.dists.gumbel.logcdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.gumbel.logcdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.logcdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.gumbel.logcdf( 0.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.gumbel.logcdf.factory( μ, β )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Gumbel distribution with location parameter\n    `μ` and scale parameter `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myLCDF = base.dists.gumbel.logcdf.factory( 2.0, 3.0 );\n    > var y = myLCDF( 10.0 )\n    ~-0.069\n    > y = myLCDF( 2.0 )\n    ~-1.0\n\n","base.dists.gumbel.logcdf.factory":"\nbase.dists.gumbel.logcdf.factory( μ, β )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Gumbel distribution with location parameter\n    `μ` and scale parameter `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myLCDF = base.dists.gumbel.logcdf.factory( 2.0, 3.0 );\n    > var y = myLCDF( 10.0 )\n    ~-0.069\n    > y = myLCDF( 2.0 )\n    ~-1.0","base.dists.gumbel.logpdf":"\nbase.dists.gumbel.logpdf( x, μ, β )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.logpdf( 0.0, 0.0, 2.0 )\n    ~-1.693\n    > y = base.dists.gumbel.logpdf( 0.0, 0.0, 1.0 )\n    ~-1\n    > y = base.dists.gumbel.logpdf( 1.0, 3.0, 2.0 )\n    ~-2.411\n    > y = base.dists.gumbel.logpdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.gumbel.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.logpdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.gumbel.logpdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.gumbel.logpdf.factory( μ, β )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Gumbel distribution with location parameter `μ` and\n    scale parameter `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.gumbel.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogpdf( 10.0 )\n    ~-1.693\n    > y = mylogpdf( 12.0 )\n    ~-2.061\n\n","base.dists.gumbel.logpdf.factory":"\nbase.dists.gumbel.logpdf.factory( μ, β )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Gumbel distribution with location parameter `μ` and\n    scale parameter `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.gumbel.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogpdf( 10.0 )\n    ~-1.693\n    > y = mylogpdf( 12.0 )\n    ~-2.061","base.dists.gumbel.mean":"\nbase.dists.gumbel.mean( μ, β )\n    Returns the expected value of a Gumbel distribution with location parameter\n    `μ` and scale parameter `β`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.mean( 0.0, 1.0 )\n    ~0.577\n    > y = base.dists.gumbel.mean( 4.0, 2.0 )\n    ~5.154\n    > y = base.dists.gumbel.mean( NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.mean( 0.0, NaN )\n    NaN\n    > y = base.dists.gumbel.mean( 0.0, 0.0 )\n    NaN\n\n","base.dists.gumbel.median":"\nbase.dists.gumbel.median( μ, β )\n    Returns the median of a Gumbel distribution with location parameter `μ` and\n    scale parameter `β`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.median( 0.0, 1.0 )\n    ~0.367\n    > y = base.dists.gumbel.median( 4.0, 2.0 )\n    ~4.733\n    > y = base.dists.gumbel.median( NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.median( 0.0, NaN )\n    NaN\n    > y = base.dists.gumbel.median( 0.0, 0.0 )\n    NaN\n\n","base.dists.gumbel.mgf":"\nbase.dists.gumbel.mgf( t, μ, β )\n    Evaluates the moment-generating function (MGF) for a Gumbel distribution\n    with location parameter `μ` and scale parameter `β` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.mgf( -1.0, 0.0, 3.0 )\n    6.0\n    > y = base.dists.gumbel.mgf( 0.0, 0.0, 1.0 )\n    1.0\n    > y = base.dists.gumbel.mgf( 0.1, 0.0, 3.0 )\n    ~1.298\n\n    > y = base.dists.gumbel.mgf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.gumbel.mgf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.mgf( 0.0, 0.0, NaN )\n    NaN\n\n    // Case: `t >= 1/beta`\n    > y = base.dists.gumbel.mgf( 0.8, 0.0, 2.0 )\n    NaN\n\n    // Non-positive scale parameter:\n    > y = base.dists.gumbel.mgf( 0.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.gumbel.mgf.factory( μ, β )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Gumbel distribution with location parameter `μ` and scale parameter `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.gumbel.mgf.factory( 0.0, 3.0 );\n    > var y = myMGF( -1.5 )\n    ~52.343\n    > y = myMGF( -1.0 )\n    6.0\n\n","base.dists.gumbel.mgf.factory":"\nbase.dists.gumbel.mgf.factory( μ, β )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Gumbel distribution with location parameter `μ` and scale parameter `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.gumbel.mgf.factory( 0.0, 3.0 );\n    > var y = myMGF( -1.5 )\n    ~52.343\n    > y = myMGF( -1.0 )\n    6.0","base.dists.gumbel.mode":"\nbase.dists.gumbel.mode( μ, β )\n    Returns the mode of a Gumbel distribution with location parameter `μ` and\n    scale parameter `β`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.mode( 0.0, 1.0 )\n    0.0\n    > y = base.dists.gumbel.mode( 4.0, 2.0 )\n    4.0\n    > y = base.dists.gumbel.mode( NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.mode( 0.0, NaN )\n    NaN\n    > y = base.dists.gumbel.mode( 0.0, 0.0 )\n    NaN\n\n","base.dists.gumbel.pdf":"\nbase.dists.gumbel.pdf( x, μ, β )\n    Evaluates the probability density function (PDF) for a Gumbel distribution\n    with location parameter `μ` and scale parameter `β` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.pdf( 0.0, 0.0, 2.0 )\n    ~0.184\n    > y = base.dists.gumbel.pdf( 0.0, 0.0, 1.0 )\n    ~0.368\n    > y = base.dists.gumbel.pdf( 1.0, 3.0, 2.0 )\n    ~0.09\n    > y = base.dists.gumbel.pdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.gumbel.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.pdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.gumbel.pdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.gumbel.pdf.factory( μ, β )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Gumbel distribution with location parameter `μ` and scale parameter\n    `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.gumbel.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    ~0.184\n    > y = myPDF( 12.0 )\n    ~0.127\n\n","base.dists.gumbel.pdf.factory":"\nbase.dists.gumbel.pdf.factory( μ, β )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Gumbel distribution with location parameter `μ` and scale parameter\n    `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.gumbel.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    ~0.184\n    > y = myPDF( 12.0 )\n    ~0.127","base.dists.gumbel.quantile":"\nbase.dists.gumbel.quantile( p, μ, β )\n    Evaluates the quantile function for a Gumbel distribution with location\n    parameter `μ` and scale parameter `β` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.quantile( 0.8, 0.0, 1.0 )\n    ~1.5\n    > y = base.dists.gumbel.quantile( 0.5, 4.0, 2.0 )\n    ~4.733\n    > y = base.dists.gumbel.quantile( 0.5, 4.0, 4.0 )\n    ~5.466\n\n    > y = base.dists.gumbel.quantile( 1.1, 0.0, 1.0 )\n    NaN\n    > y = base.dists.gumbel.quantile( -0.2, 0.0, 1.0 )\n    NaN\n\n    > y = base.dists.gumbel.quantile( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.gumbel.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.quantile( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.gumbel.quantile( 0.5, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.gumbel.quantile.factory( μ, β )\n    Returns a function for evaluating the quantile function of a Gumbel\n    distribution with location parameter `μ` and scale parameter `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.gumbel.quantile.factory( 8.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    ~8.733\n    > y = myQuantile( 0.7 )\n    ~10.062\n\n","base.dists.gumbel.quantile.factory":"\nbase.dists.gumbel.quantile.factory( μ, β )\n    Returns a function for evaluating the quantile function of a Gumbel\n    distribution with location parameter `μ` and scale parameter `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.gumbel.quantile.factory( 8.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    ~8.733\n    > y = myQuantile( 0.7 )\n    ~10.062","base.dists.gumbel.skewness":"\nbase.dists.gumbel.skewness( μ, β )\n    Returns the skewness of a Gumbel distribution with location parameter `μ`\n    and scale parameter `β`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.skewness( 0.0, 1.0 )\n    ~1.14\n    > y = base.dists.gumbel.skewness( 4.0, 2.0 )\n    ~1.14\n    > y = base.dists.gumbel.skewness( NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.skewness( 0.0, NaN )\n    NaN\n    > y = base.dists.gumbel.skewness( 0.0, 0.0 )\n    NaN\n\n","base.dists.gumbel.stdev":"\nbase.dists.gumbel.stdev( μ, β )\n    Returns the standard deviation of a Gumbel distribution with location\n    parameter `μ` and scale parameter `β`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.stdev( 0.0, 1.0 )\n    ~1.283\n    > y = base.dists.gumbel.stdev( 4.0, 2.0 )\n    ~2.565\n    > y = base.dists.gumbel.stdev( NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.stdev( 0.0, NaN )\n    NaN\n    > y = base.dists.gumbel.stdev( 0.0, 0.0 )\n    NaN\n\n","base.dists.gumbel.variance":"\nbase.dists.gumbel.variance( μ, β )\n    Returns the variance of a Gumbel distribution with location parameter `μ`\n    and scale parameter `β`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.variance( 0.0, 1.0 )\n    ~1.645\n    > y = base.dists.gumbel.variance( 4.0, 2.0 )\n    ~6.58\n    > y = base.dists.gumbel.variance( NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.variance( 0.0, NaN )\n    NaN\n    > y = base.dists.gumbel.variance( 0.0, 0.0 )\n    NaN\n\n","base.dists.hypergeometric.cdf":"\nbase.dists.hypergeometric.cdf( x, N, K, n )\n    Evaluates the cumulative distribution function (CDF) for a hypergeometric\n    distribution with population size `N`, subpopulation size `K`, and number of\n    draws `n` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a population size `N`, subpopulation size `K` or draws `n` which\n    is not a nonnegative integer, the function returns `NaN`.\n\n    If the number of draws `n` or subpopulation size `K` exceeds population size\n     `N`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.hypergeometric.cdf( 1.0, 8, 4, 2 )\n    ~0.786\n    > y = base.dists.hypergeometric.cdf( 1.5, 8, 4, 2 )\n    ~0.786\n    > y = base.dists.hypergeometric.cdf( 2.0, 8, 4, 2 )\n    1.0\n    > y = base.dists.hypergeometric.cdf( 0, 8, 4, 2)\n    ~0.214\n\n    > y = base.dists.hypergeometric.cdf( NaN, 10, 5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.cdf( 0.0, NaN, 5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.cdf( 0.0, 10, NaN, 2 )\n    NaN\n    > y = base.dists.hypergeometric.cdf( 0.0, 10, 5, NaN )\n    NaN\n\n    > y = base.dists.hypergeometric.cdf( 2.0, 10.5, 5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.cdf( 2.0, 10, 1.5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.cdf( 2.0, 10, 5, -2.0 )\n    NaN\n    > y = base.dists.hypergeometric.cdf( 2.0, 10, 5, 12 )\n    NaN\n    > y = base.dists.hypergeometric.cdf( 2.0, 8, 3, 9 )\n    NaN\n\n\nbase.dists.hypergeometric.cdf.factory( N, K, n )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a hypergeometric distribution with population size `N`, subpopulation\n    size `K`, and number of draws `n`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.hypergeometric.cdf.factory( 30, 20, 5 );\n    > var y = myCDF( 4.0 )\n    ~0.891\n    > y = myCDF( 1.0 )\n    ~0.031\n\n","base.dists.hypergeometric.cdf.factory":"\nbase.dists.hypergeometric.cdf.factory( N, K, n )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a hypergeometric distribution with population size `N`, subpopulation\n    size `K`, and number of draws `n`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.hypergeometric.cdf.factory( 30, 20, 5 );\n    > var y = myCDF( 4.0 )\n    ~0.891\n    > y = myCDF( 1.0 )\n    ~0.031","base.dists.hypergeometric.Hypergeometric":"\nbase.dists.hypergeometric.Hypergeometric( [N, K, n] )\n    Returns a hypergeometric distribution object.\n\n    Parameters\n    ----------\n    N: integer (optional)\n        Population size. Must be a nonnegative integer larger than or equal to\n        `K` and `n`.\n\n    K: integer (optional)\n        Subpopulation size. Must be a nonnegative integer smaller than or equal\n        to `N`.\n\n    n: integer (optional)\n        Number of draws. Must be a nonnegative integer smaller than or equal to\n        `N`.\n\n    Returns\n    -------\n    hypergeometric: Object\n        Distribution instance.\n\n    hypergeometric.N: number\n        Population size. If set, the value must be a nonnegative integer larger\n        than or equal to `K` and `n`.\n\n    hypergeometric.K: number\n        Subpopulation size. If set, the value must be a nonnegative integer\n        smaller than or equal to `N`.\n\n    hypergeometric.n: number\n        Number of draws. If set, the value must be a nonnegative integer\n        smaller than or equal to `N`.\n\n    hypergeometric.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    hypergeometric.mean: number\n        Read-only property which returns the expected value.\n\n    hypergeometric.mode: number\n        Read-only property which returns the mode.\n\n    hypergeometric.skewness: number\n        Read-only property which returns the skewness.\n\n    hypergeometric.stdev: number\n        Read-only property which returns the standard deviation.\n\n    hypergeometric.variance: number\n        Read-only property which returns the variance.\n\n    hypergeometric.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    hypergeometric.logpmf: Function\n        Evaluates the natural logarithm of the probability mass function (PMF).\n\n    hypergeometric.pmf: Function\n        Evaluates the probability mass function (PMF).\n\n    hypergeometric.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var hypergeometric = base.dists.hypergeometric.Hypergeometric( 100, 70, 20 );\n    > hypergeometric.N\n    100.0\n    > hypergeometric.K\n    70.0\n    > hypergeometric.n\n    20.0\n    > hypergeometric.kurtosis\n    ~-0.063\n    > hypergeometric.mean\n    14.0\n    > hypergeometric.mode\n    14.0\n    > hypergeometric.skewness\n    ~-0.133\n    > hypergeometric.stdev\n    ~1.842\n    > hypergeometric.variance\n    ~3.394\n    > hypergeometric.cdf( 2.9 )\n    ~0.0\n    > hypergeometric.logpmf( 10 )\n    ~-3.806\n    > hypergeometric.pmf( 10 )\n    ~0.022\n    > hypergeometric.quantile( 0.8 )\n    16.0\n\n","base.dists.hypergeometric.kurtosis":"\nbase.dists.hypergeometric.kurtosis( N, K, n )\n    Returns the excess kurtosis of a hypergeometric distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a population size `N`, subpopulation size `K` or draws `n` which\n    is not a nonnegative integer, the function returns `NaN`.\n\n    If the number of draws `n` or subpopulation size `K` exceed population size\n    `N`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.hypergeometric.kurtosis( 16, 11, 4 )\n    ~-0.326\n    > v = base.dists.hypergeometric.kurtosis( 4, 2, 2 )\n    0.0\n\n    > v = base.dists.hypergeometric.kurtosis( 10, 5, 12 )\n    NaN\n    > v = base.dists.hypergeometric.kurtosis( 10.3, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.kurtosis( 10, 5.5, 4 )\n    NaN\n    > v = base.dists.hypergeometric.kurtosis( 10, 5, 4.5 )\n    NaN\n\n    > v = base.dists.hypergeometric.kurtosis( NaN, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.kurtosis( 20, NaN, 4 )\n    NaN\n    > v = base.dists.hypergeometric.kurtosis( 20, 10, NaN )\n    NaN\n\n","base.dists.hypergeometric.logpmf":"\nbase.dists.hypergeometric.logpmf( x, N, K, n )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    hypergeometric distribution with population size `N`, subpopulation size\n    `K`, and number of draws `n` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a population size `N`, subpopulation size `K`, or draws `n`\n    which is not a nonnegative integer, the function returns `NaN`.\n\n    If the number of draws `n` or the subpopulation size `K` exceed population\n    size `N`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPMF.\n\n    Examples\n    --------\n    > var y = base.dists.hypergeometric.logpmf( 1.0, 8, 4, 2 )\n    ~-0.56\n    > y = base.dists.hypergeometric.logpmf( 2.0, 8, 4, 2 )\n    ~-1.54\n    > y = base.dists.hypergeometric.logpmf( 0.0, 8, 4, 2 )\n    ~-1.54\n    > y = base.dists.hypergeometric.logpmf( 1.5, 8, 4, 2 )\n    -Infinity\n\n    > y = base.dists.hypergeometric.logpmf( NaN, 10, 5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.logpmf( 0.0, NaN, 5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.logpmf( 0.0, 10, NaN, 2 )\n    NaN\n    > y = base.dists.hypergeometric.logpmf( 0.0, 10, 5, NaN )\n    NaN\n\n    > y = base.dists.hypergeometric.logpmf( 2.0, 10.5, 5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.logpmf( 2.0, 5, 1.5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.logpmf( 2.0, 10, 5, -2.0 )\n    NaN\n    > y = base.dists.hypergeometric.logpmf( 2.0, 10, 5, 12 )\n    NaN\n    > y = base.dists.hypergeometric.logpmf( 2.0, 8, 3, 9 )\n    NaN\n\n\nbase.dists.hypergeometric.logpmf.factory( N, K, n )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a hypergeometric distribution with population size\n    `N`, subpopulation size `K`, and number of draws `n`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogPMF = base.dists.hypergeometric.logpmf.factory( 30, 20, 5 );\n    > var y = mylogPMF( 4.0 )\n    ~-1.079\n    > y = mylogPMF( 1.0 )\n    ~-3.524\n\n","base.dists.hypergeometric.logpmf.factory":"\nbase.dists.hypergeometric.logpmf.factory( N, K, n )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a hypergeometric distribution with population size\n    `N`, subpopulation size `K`, and number of draws `n`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogPMF = base.dists.hypergeometric.logpmf.factory( 30, 20, 5 );\n    > var y = mylogPMF( 4.0 )\n    ~-1.079\n    > y = mylogPMF( 1.0 )\n    ~-3.524","base.dists.hypergeometric.mean":"\nbase.dists.hypergeometric.mean( N, K, n )\n    Returns the expected value of a hypergeometric distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a population size `N`, subpopulation size `K` or draws `n` which\n    is not a nonnegative integer, the function returns `NaN`.\n\n    If the number of draws `n` or the subpopulation size `K` exceed population\n    size `N`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.hypergeometric.mean( 16, 11, 4 )\n    2.75\n    > v = base.dists.hypergeometric.mean( 2, 1, 1 )\n    0.5\n\n    > v = base.dists.hypergeometric.mean( 10, 5, 12 )\n    NaN\n    > v = base.dists.hypergeometric.mean( 10.3, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.mean( 10, 5.5, 4 )\n    NaN\n    > v = base.dists.hypergeometric.mean( 10, 5, 4.5 )\n    NaN\n\n    > v = base.dists.hypergeometric.mean( NaN, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.mean( 20, NaN, 4 )\n    NaN\n    > v = base.dists.hypergeometric.mean( 20, 10, NaN )\n    NaN\n\n","base.dists.hypergeometric.mode":"\nbase.dists.hypergeometric.mode( N, K, n )\n    Returns the mode of a hypergeometric distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a population size `N`, subpopulation size `K` or draws `n` which\n    is not a nonnegative integer, the function returns `NaN`.\n\n    If the number of draws `n` or the subpopulation size `K` exceed population\n    size `N`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.hypergeometric.mode( 16, 11, 4 )\n    3\n    > v = base.dists.hypergeometric.mode( 2, 1, 1 )\n    1\n\n    > v = base.dists.hypergeometric.mode( 10, 5, 12 )\n    NaN\n    > v = base.dists.hypergeometric.mode( 10.3, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.mode( 10, 5.5, 4 )\n    NaN\n    > v = base.dists.hypergeometric.mode( 10, 5, 4.5 )\n    NaN\n\n    > v = base.dists.hypergeometric.mode( NaN, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.mode( 20, NaN, 4 )\n    NaN\n    > v = base.dists.hypergeometric.mode( 20, 10, NaN )\n    NaN\n\n","base.dists.hypergeometric.pmf":"\nbase.dists.hypergeometric.pmf( x, N, K, n )\n    Evaluates the probability mass function (PMF) for a hypergeometric\n    distribution with population size `N`, subpopulation size `K`, and number of\n    draws `n` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a population size `N`, subpopulation size `K` or draws `n` which\n    is not a nonnegative integer, the function returns `NaN`.\n\n    If the number of draws `n` or the subpopulation size `K` exceed population\n    size `N`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    out: number\n        Evaluated PMF.\n\n    Examples\n    --------\n    > var y = base.dists.hypergeometric.pmf( 1.0, 8, 4, 2 )\n    ~0.571\n    > y = base.dists.hypergeometric.pmf( 2.0, 8, 4, 2 )\n    ~0.214\n    > y = base.dists.hypergeometric.pmf( 0.0, 8, 4, 2 )\n    ~0.214\n    > y = base.dists.hypergeometric.pmf( 1.5, 8, 4, 2 )\n    0.0\n\n    > y = base.dists.hypergeometric.pmf( NaN, 10, 5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.pmf( 0.0, NaN, 5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.pmf( 0.0, 10, NaN, 2 )\n    NaN\n    > y = base.dists.hypergeometric.pmf( 0.0, 10, 5, NaN )\n    NaN\n\n    > y = base.dists.hypergeometric.pmf( 2.0, 10.5, 5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.pmf( 2.0, 5, 1.5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.pmf( 2.0, 10, 5, -2.0 )\n    NaN\n    > y = base.dists.hypergeometric.pmf( 2.0, 10, 5, 12 )\n    NaN\n    > y = base.dists.hypergeometric.pmf( 2.0, 8, 3, 9 )\n    NaN\n\n\nbase.dists.hypergeometric.pmf.factory( N, K, n )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    hypergeometric distribution with population size `N`, subpopulation size\n    `K`, and number of draws `n`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var myPMF = base.dists.hypergeometric.pmf.factory( 30, 20, 5 );\n    > var y = myPMF( 4.0 )\n    ~0.34\n    > y = myPMF( 1.0 )\n    ~0.029\n\n","base.dists.hypergeometric.pmf.factory":"\nbase.dists.hypergeometric.pmf.factory( N, K, n )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    hypergeometric distribution with population size `N`, subpopulation size\n    `K`, and number of draws `n`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var myPMF = base.dists.hypergeometric.pmf.factory( 30, 20, 5 );\n    > var y = myPMF( 4.0 )\n    ~0.34\n    > y = myPMF( 1.0 )\n    ~0.029","base.dists.hypergeometric.quantile":"\nbase.dists.hypergeometric.quantile( p, N, K, n )\n    Evaluates the quantile function for a hypergeometric distribution with\n    population size `N`, subpopulation size `K`, and number of draws `n` at a\n    probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a population size `N`, subpopulation size `K` or draws `n` which\n    is not a nonnegative integer, the function returns `NaN`.\n\n    If the number of draws `n` or the subpopulation size `K` exceed population\n    size `N`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.hypergeometric.quantile( 0.4, 40, 20, 10 )\n    5\n    > y = base.dists.hypergeometric.quantile( 0.8, 60, 40, 20 )\n    15\n    > y = base.dists.hypergeometric.quantile( 0.5, 100, 10, 10 )\n    1\n    > y = base.dists.hypergeometric.quantile( 0.0, 100, 40, 20 )\n    0\n    > y = base.dists.hypergeometric.quantile( 1.0, 100, 40, 20 )\n    20\n\n    > y = base.dists.hypergeometric.quantile( NaN, 40, 20, 10 )\n    NaN\n    > y = base.dists.hypergeometric.quantile( 0.2, NaN, 20, 10 )\n    NaN\n    > y = base.dists.hypergeometric.quantile( 0.2, 40, NaN, 10 )\n    NaN\n    > y = base.dists.hypergeometric.quantile( 0.2, 40, 20, NaN )\n    NaN\n\n\nbase.dists.hypergeometric.quantile.factory( N, K, n )\n    Returns a function for evaluating the quantile function of a hypergeometric\n    distribution with population size `N`, subpopulation size `K`, and number of\n    draws `n`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.hypergeometric.quantile.factory( 100, 20, 10 );\n    > var y = myQuantile( 0.2 )\n    1\n    > y = myQuantile( 0.9 )\n    4\n\n","base.dists.hypergeometric.quantile.factory":"\nbase.dists.hypergeometric.quantile.factory( N, K, n )\n    Returns a function for evaluating the quantile function of a hypergeometric\n    distribution with population size `N`, subpopulation size `K`, and number of\n    draws `n`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.hypergeometric.quantile.factory( 100, 20, 10 );\n    > var y = myQuantile( 0.2 )\n    1\n    > y = myQuantile( 0.9 )\n    4","base.dists.hypergeometric.skewness":"\nbase.dists.hypergeometric.skewness( N, K, n )\n    Returns the skewness of a hypergeometric distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a population size `N`, subpopulation size `K` or draws `n` which\n    is not a nonnegative integer, the function returns `NaN`.\n\n    If the number of draws `n` or the subpopulation size `K` exceed population\n    size `N`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.hypergeometric.skewness( 16, 11, 4 )\n    ~-0.258\n    > v = base.dists.hypergeometric.skewness( 4, 2, 2 )\n    0.0\n\n    > v = base.dists.hypergeometric.skewness( 10, 5, 12 )\n    NaN\n    > v = base.dists.hypergeometric.skewness( 10.3, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.skewness( 10, 5.5, 4 )\n    NaN\n    > v = base.dists.hypergeometric.skewness( 10, 5, 4.5 )\n    NaN\n\n    > v = base.dists.hypergeometric.skewness( NaN, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.skewness( 20, NaN, 4 )\n    NaN\n    > v = base.dists.hypergeometric.skewness( 20, 10, NaN )\n    NaN\n\n","base.dists.hypergeometric.stdev":"\nbase.dists.hypergeometric.stdev( N, K, n )\n    Returns the standard deviation of a hypergeometric distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a population size `N`, subpopulation size `K` or draws `n` which\n    is not a nonnegative integer, the function returns `NaN`.\n\n    If the number of draws `n` or the subpopulation size `K` exceed population\n    size `N`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.hypergeometric.stdev( 16, 11, 4 )\n    ~0.829\n    > v = base.dists.hypergeometric.stdev( 2, 1, 1 )\n    0.5\n\n    > v = base.dists.hypergeometric.stdev( 10, 5, 12 )\n    NaN\n    > v = base.dists.hypergeometric.stdev( 10.3, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.stdev( 10, 5.5, 4 )\n    NaN\n    > v = base.dists.hypergeometric.stdev( 10, 5, 4.5 )\n    NaN\n\n    > v = base.dists.hypergeometric.stdev( NaN, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.stdev( 20, NaN, 4 )\n    NaN\n    > v = base.dists.hypergeometric.stdev( 20, 10, NaN )\n    NaN\n\n","base.dists.hypergeometric.variance":"\nbase.dists.hypergeometric.variance( N, K, n )\n    Returns the variance of a hypergeometric distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a population size `N`, subpopulation size `K` or draws `n` which\n    is not a nonnegative integer, the function returns `NaN`.\n\n    If the number of draws `n` or the subpopulation size `K` exceed population\n    size `N`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.hypergeometric.variance( 16, 11, 4 )\n    ~0.688\n    > v = base.dists.hypergeometric.variance( 2, 1, 1 )\n    0.25\n\n    > v = base.dists.hypergeometric.variance( 10, 5, 12 )\n    NaN\n    > v = base.dists.hypergeometric.variance( 10.3, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.variance( 10, 5.5, 4 )\n    NaN\n    > v = base.dists.hypergeometric.variance( 10, 5, 4.5 )\n    NaN\n\n    > v = base.dists.hypergeometric.variance( NaN, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.variance( 20, NaN, 4 )\n    NaN\n    > v = base.dists.hypergeometric.variance( 20, 10, NaN )\n    NaN\n\n","base.dists.invgamma.cdf":"\nbase.dists.invgamma.cdf( x, α, β )\n    Evaluates the cumulative distribution function (CDF) for an inverse gamma\n    distribution with shape parameter `α` and scale parameter `β` at a value\n    `x`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.invgamma.cdf( 2.0, 1.0, 1.0 )\n    ~0.607\n    > y = base.dists.invgamma.cdf( 2.0, 3.0, 1.0 )\n    ~0.986\n    > y = base.dists.invgamma.cdf( -1.0, 2.0, 2.0 )\n    0.0\n    > y = base.dists.invgamma.cdf( PINF, 4.0, 2.0 )\n    1.0\n    > y = base.dists.invgamma.cdf( NINF, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.invgamma.cdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.invgamma.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.invgamma.cdf( 0.0, 0.0, NaN )\n    NaN\n\n    > y = base.dists.invgamma.cdf( 2.0, -1.0, 1.0 )\n    NaN\n    > y = base.dists.invgamma.cdf( 2.0, 1.0, -1.0 )\n    NaN\n\n\nbase.dists.invgamma.cdf.factory( α, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an inverse gamma distribution with shape parameter `α` and scale\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.invgamma.cdf.factory( 2.0, 0.5 );\n    > var y = myCDF( 0.5 )\n    ~0.736\n    > y = myCDF( 2.0 )\n    ~0.974\n\n","base.dists.invgamma.cdf.factory":"\nbase.dists.invgamma.cdf.factory( α, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an inverse gamma distribution with shape parameter `α` and scale\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.invgamma.cdf.factory( 2.0, 0.5 );\n    > var y = myCDF( 0.5 )\n    ~0.736\n    > y = myCDF( 2.0 )\n    ~0.974","base.dists.invgamma.entropy":"\nbase.dists.invgamma.entropy( α, β )\n    Returns the differential entropy of an inverse gamma distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.invgamma.entropy( 1.0, 1.0 )\n    ~2.154\n    > v = base.dists.invgamma.entropy( 4.0, 12.0 )\n    ~1.996\n    > v = base.dists.invgamma.entropy( 8.0, 2.0 )\n    ~-0.922\n\n","base.dists.invgamma.InvGamma":"\nbase.dists.invgamma.InvGamma( [α, β] )\n    Returns an inverse gamma distribution object.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n    β: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    invgamma: Object\n        Distribution instance.\n\n    invgamma.alpha: number\n        Shape parameter. If set, the value must be greater than `0`.\n\n    invgamma.beta: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    invgamma.entropy: number\n        Read-only property which returns the differential entropy.\n\n    invgamma.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    invgamma.mean: number\n        Read-only property which returns the expected value.\n\n    invgamma.mode: number\n        Read-only property which returns the mode.\n\n    invgamma.skewness: number\n        Read-only property which returns the skewness.\n\n    invgamma.stdev: number\n        Read-only property which returns the standard deviation.\n\n    invgamma.variance: number\n        Read-only property which returns the variance.\n\n    invgamma.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    invgamma.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    invgamma.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    invgamma.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var invgamma = base.dists.invgamma.InvGamma( 6.0, 5.0 );\n    > invgamma.alpha\n    6.0\n    > invgamma.beta\n    5.0\n    > invgamma.entropy\n    ~0.454\n    > invgamma.kurtosis\n    19.0\n    > invgamma.mean\n    1.0\n    > invgamma.mode\n    ~0.714\n    > invgamma.skewness\n    ~2.667\n    > invgamma.stdev\n    0.5\n    > invgamma.variance\n    0.25\n    > invgamma.cdf( 0.8 )\n    ~0.406\n    > invgamma.pdf( 1.0 )\n    ~0.877\n    > invgamma.logpdf( 1.0 )\n    ~-0.131\n    > invgamma.quantile( 0.8 )\n    ~1.281\n\n","base.dists.invgamma.kurtosis":"\nbase.dists.invgamma.kurtosis( α, β )\n    Returns the excess kurtosis of an inverse gamma distribution.\n\n    If `α <= 4` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.invgamma.kurtosis( 7.0, 5.0 )\n    12.0\n    > v = base.dists.invgamma.kurtosis( 6.0, 12.0 )\n    19.0\n    > v = base.dists.invgamma.kurtosis( 8.0, 2.0 )\n    ~8.7\n\n","base.dists.invgamma.logpdf":"\nbase.dists.invgamma.logpdf( x, α, β )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for an inverse gamma distribution with shape parameter `α` and scale\n    parameter `β` at a value `x`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.invgamma.logpdf( 2.0, 0.5, 1.0 )\n    ~-2.112\n    > y = base.dists.invgamma.logpdf( 0.2, 1.0, 1.0 )\n    ~-1.781\n    > y = base.dists.invgamma.logpdf( -1.0, 4.0, 2.0 )\n    -Infinity\n\n    > y = base.dists.invgamma.logpdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.invgamma.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.invgamma.logpdf( 0.0, 1.0, NaN )\n    NaN\n\n    // Negative shape parameter:\n    > y = base.dists.invgamma.logpdf( 2.0, -1.0, 1.0 )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.invgamma.logpdf( 2.0, 1.0, -1.0 )\n    NaN\n\n\nbase.dists.invgamma.logpdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) for an inverse gamma distribution with shape\n    parameter `α` and scale parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.invgamma.logpdf.factory( 6.0, 7.0 );\n    > var y = mylogPDF( 2.0 )\n    ~-1.464\n\n","base.dists.invgamma.logpdf.factory":"\nbase.dists.invgamma.logpdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) for an inverse gamma distribution with shape\n    parameter `α` and scale parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.invgamma.logpdf.factory( 6.0, 7.0 );\n    > var y = mylogPDF( 2.0 )\n    ~-1.464","base.dists.invgamma.mean":"\nbase.dists.invgamma.mean( α, β )\n    Returns the expected value of an inverse gamma distribution.\n\n    If `α <= 1` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.invgamma.mean( 4.0, 12.0 )\n    4.0\n    > v = base.dists.invgamma.mean( 8.0, 2.0 )\n    ~0.286\n\n","base.dists.invgamma.mode":"\nbase.dists.invgamma.mode( α, β )\n    Returns the mode of an inverse gamma distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.invgamma.mode( 1.0, 1.0 )\n    0.5\n    > v = base.dists.invgamma.mode( 4.0, 12.0 )\n    2.4\n    > v = base.dists.invgamma.mode( 8.0, 2.0 )\n    ~0.222\n\n","base.dists.invgamma.pdf":"\nbase.dists.invgamma.pdf( x, α, β )\n    Evaluates the probability density function (PDF) for an inverse gamma\n    distribution with shape parameter `α` and scale parameter `β` at a value\n    `x`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.invgamma.pdf( 2.0, 0.5, 1.0 )\n    ~0.121\n    > y = base.dists.invgamma.pdf( 0.2, 1.0, 1.0 )\n    ~0.168\n    > y = base.dists.invgamma.pdf( -1.0, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.invgamma.pdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.invgamma.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.invgamma.pdf( 0.0, 1.0, NaN )\n    NaN\n\n    // Negative shape parameter:\n    > y = base.dists.invgamma.pdf( 2.0, -1.0, 1.0 )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.invgamma.pdf( 2.0, 1.0, -1.0 )\n    NaN\n\n\nbase.dists.invgamma.pdf.factory( α, β )\n    Returns a function for evaluating the probability density function (PDF)\n    of an inverse gamma distribution with shape parameter `α` and scale\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.invgamma.pdf.factory( 6.0, 7.0 );\n    > var y = myPDF( 2.0 )\n    ~0.231\n\n","base.dists.invgamma.pdf.factory":"\nbase.dists.invgamma.pdf.factory( α, β )\n    Returns a function for evaluating the probability density function (PDF)\n    of an inverse gamma distribution with shape parameter `α` and scale\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.invgamma.pdf.factory( 6.0, 7.0 );\n    > var y = myPDF( 2.0 )\n    ~0.231","base.dists.invgamma.quantile":"\nbase.dists.invgamma.quantile( p, α, β )\n    Evaluates the quantile function for an inverse gamma distribution with shape\n    parameter `α` and scale parameter `β` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.invgamma.quantile( 0.8, 2.0, 1.0 )\n    ~1.213\n    > y = base.dists.invgamma.quantile( 0.5, 4.0, 2.0 )\n    ~0.545\n    > y = base.dists.invgamma.quantile( 1.1, 1.0, 1.0 )\n    NaN\n    > y = base.dists.invgamma.quantile( -0.2, 1.0, 1.0 )\n    NaN\n\n    > y = base.dists.invgamma.quantile( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.invgamma.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.invgamma.quantile( 0.0, 1.0, NaN )\n    NaN\n\n    // Non-positive shape parameter:\n    > y = base.dists.invgamma.quantile( 0.5, -1.0, 1.0 )\n    NaN\n\n    // Non-positive rate parameter:\n    > y = base.dists.invgamma.quantile( 0.5, 1.0, -1.0 )\n    NaN\n\n\nbase.dists.invgamma.quantile.factory( α, β )\n    Returns a function for evaluating the quantile function of an inverse gamma\n    distribution with shape parameter `α` and scale parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.invgamma.quantile.factory( 2.0, 2.0 );\n    > var y = myQuantile( 0.8 )\n    ~2.426\n    > y = myQuantile( 0.4 )\n    ~0.989\n\n","base.dists.invgamma.quantile.factory":"\nbase.dists.invgamma.quantile.factory( α, β )\n    Returns a function for evaluating the quantile function of an inverse gamma\n    distribution with shape parameter `α` and scale parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.invgamma.quantile.factory( 2.0, 2.0 );\n    > var y = myQuantile( 0.8 )\n    ~2.426\n    > y = myQuantile( 0.4 )\n    ~0.989","base.dists.invgamma.skewness":"\nbase.dists.invgamma.skewness( α, β )\n    Returns the skewness of an inverse gamma distribution.\n\n    If `α <= 3` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.invgamma.skewness( 4.0, 12.0 )\n    ~5.657\n    > v = base.dists.invgamma.skewness( 8.0, 2.0 )\n    ~1.96\n\n","base.dists.invgamma.stdev":"\nbase.dists.invgamma.stdev( α, β )\n    Returns the standard deviation of an inverse gamma distribution.\n\n    If `α <= 2` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.invgamma.stdev( 5.0, 7.0 )\n    ~1.01\n    > v = base.dists.invgamma.stdev( 4.0, 12.0 )\n    ~2.828\n    > v = base.dists.invgamma.stdev( 8.0, 2.0 )\n    ~0.117\n\n","base.dists.invgamma.variance":"\nbase.dists.invgamma.variance( α, β )\n    Returns the variance of an inverse gamma distribution.\n\n    If `α <= 2` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.invgamma.variance( 5.0, 7.0 )\n    ~1.021\n    > v = base.dists.invgamma.variance( 4.0, 12.0 )\n    8.0\n    > v = base.dists.invgamma.variance( 8.0, 2.0 )\n    ~0.014\n\n","base.dists.kumaraswamy.cdf":"\nbase.dists.kumaraswamy.cdf( x, a, b )\n    Evaluates the cumulative distribution function (CDF) for Kumaraswamy's\n    double bounded distribution with first shape parameter `a` and second shape\n    parameter `b` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.kumaraswamy.cdf( 0.5, 1.0, 1.0 )\n    ~0.5\n    > y = base.dists.kumaraswamy.cdf( 0.5, 2.0, 4.0 )\n    ~0.684\n    > y = base.dists.kumaraswamy.cdf( 0.2, 2.0, 2.0 )\n    ~0.078\n    > y = base.dists.kumaraswamy.cdf( 0.8, 4.0, 4.0 )\n    ~0.878\n    > y = base.dists.kumaraswamy.cdf( -0.5, 4.0, 2.0 )\n    0.0\n    > y = base.dists.kumaraswamy.cdf( 1.5, 4.0, 2.0 )\n    1.0\n\n    > y = base.dists.kumaraswamy.cdf( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.kumaraswamy.cdf( 2.0, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.kumaraswamy.cdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.kumaraswamy.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.kumaraswamy.cdf( 0.0, 1.0, NaN )\n    NaN\n\n\nbase.dists.kumaraswamy.cdf.factory( a, b )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Kumaraswamy's double bounded distribution with first shape parameter\n    `a` and second shape parameter `b`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.kumaraswamy.cdf.factory( 0.5, 1.0 );\n    > var y = mycdf( 0.8 )\n    ~0.894\n    > y = mycdf( 0.3 )\n    ~0.548\n\n","base.dists.kumaraswamy.cdf.factory":"\nbase.dists.kumaraswamy.cdf.factory( a, b )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Kumaraswamy's double bounded distribution with first shape parameter\n    `a` and second shape parameter `b`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.kumaraswamy.cdf.factory( 0.5, 1.0 );\n    > var y = mycdf( 0.8 )\n    ~0.894\n    > y = mycdf( 0.3 )\n    ~0.548","base.dists.kumaraswamy.Kumaraswamy":"\nbase.dists.kumaraswamy.Kumaraswamy( [a, b] )\n    Returns a Kumaraswamy's double bounded distribution object.\n\n    Parameters\n    ----------\n    a: number (optional)\n        First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n    b: number (optional)\n        Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    kumaraswamy: Object\n        Distribution instance.\n\n    kumaraswamy.a: number\n        First shape parameter. If set, the value must be greater than `0`.\n\n    kumaraswamy.b: number\n        Second shape parameter. If set, the value must be greater than `0`.\n\n    kumaraswamy.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    kumaraswamy.mean: number\n        Read-only property which returns the expected value.\n\n    kumaraswamy.mode: number\n        Read-only property which returns the mode.\n\n    kumaraswamy.skewness: number\n        Read-only property which returns the skewness.\n\n    kumaraswamy.stdev: number\n        Read-only property which returns the standard deviation.\n\n    kumaraswamy.variance: number\n        Read-only property which returns the variance.\n\n    kumaraswamy.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    kumaraswamy.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    kumaraswamy.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var kumaraswamy = base.dists.kumaraswamy.Kumaraswamy( 6.0, 5.0 );\n    > kumaraswamy.a\n    6.0\n    > kumaraswamy.b\n    5.0\n    > kumaraswamy.kurtosis\n    ~3.194\n    > kumaraswamy.mean\n    ~0.696\n    > kumaraswamy.mode\n    ~0.746\n    > kumaraswamy.skewness\n    ~-0.605\n    > kumaraswamy.stdev\n    ~0.126\n    > kumaraswamy.variance\n    ~0.016\n    > kumaraswamy.cdf( 0.8 )\n    ~0.781\n    > kumaraswamy.pdf( 1.0 )\n    ~0.0\n    > kumaraswamy.quantile( 0.8 )\n    ~0.807\n\n","base.dists.kumaraswamy.kurtosis":"\nbase.dists.kumaraswamy.kurtosis( a, b )\n    Returns the excess kurtosis of a Kumaraswamy's double bounded distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.kumaraswamy.kurtosis( 1.0, 1.0 )\n    ~1.8\n    > v = base.dists.kumaraswamy.kurtosis( 4.0, 12.0 )\n    ~2.704\n    > v = base.dists.kumaraswamy.kurtosis( 16.0, 8.0 )\n    ~4.311\n\n","base.dists.kumaraswamy.logcdf":"\nbase.dists.kumaraswamy.logcdf( x, a, b )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for Kumaraswamy's double bounded distribution with first shape\n    parameter `a` and second shape parameter `b` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.kumaraswamy.logcdf( 0.5, 1.0, 1.0 )\n    ~-0.693\n    > y = base.dists.kumaraswamy.logcdf( 0.5, 2.0, 4.0 )\n    ~-0.38\n    > y = base.dists.kumaraswamy.logcdf( 0.2, 2.0, 2.0 )\n    ~-2.546\n    > y = base.dists.kumaraswamy.logcdf( 0.8, 4.0, 4.0 )\n    ~-0.13\n    > y = base.dists.kumaraswamy.logcdf( -0.5, 4.0, 2.0 )\n    -Infinity\n    > y = base.dists.kumaraswamy.logcdf( 1.5, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.kumaraswamy.logcdf( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.kumaraswamy.logcdf( 2.0, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.kumaraswamy.logcdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.kumaraswamy.logcdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.kumaraswamy.logcdf( 0.0, 1.0, NaN )\n    NaN\n\n\nbase.dists.kumaraswamy.logcdf.factory( a, b )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Kumaraswamy's double bounded distribution\n    with first shape parameter `a` and second shape parameter `b`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.kumaraswamy.logcdf.factory( 0.5, 1.0 );\n    > var y = mylogcdf( 0.8 )\n    ~-0.112\n    > y = mylogcdf( 0.3 )\n    ~-0.602\n\n","base.dists.kumaraswamy.logcdf.factory":"\nbase.dists.kumaraswamy.logcdf.factory( a, b )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Kumaraswamy's double bounded distribution\n    with first shape parameter `a` and second shape parameter `b`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.kumaraswamy.logcdf.factory( 0.5, 1.0 );\n    > var y = mylogcdf( 0.8 )\n    ~-0.112\n    > y = mylogcdf( 0.3 )\n    ~-0.602","base.dists.kumaraswamy.logpdf":"\nbase.dists.kumaraswamy.logpdf( x, a, b )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for Kumaraswamy's double bounded distribution with first shape parameter `a`\n    and second shape parameter `b` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.kumaraswamy.logpdf( 0.5, 1.0, 1.0 )\n    0.0\n    > y = base.dists.kumaraswamy.logpdf( 0.5, 2.0, 4.0 )\n    ~0.523\n    > y = base.dists.kumaraswamy.logpdf( 0.2, 2.0, 2.0 )\n    ~-0.264\n    > y = base.dists.kumaraswamy.logpdf( 0.8, 4.0, 4.0 )\n    ~0.522\n    > y = base.dists.kumaraswamy.logpdf( -0.5, 4.0, 2.0 )\n    -Infinity\n    > y = base.dists.kumaraswamy.logpdf( 1.5, 4.0, 2.0 )\n    -Infinity\n\n    > y = base.dists.kumaraswamy.logpdf( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.kumaraswamy.logpdf( 2.0, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.kumaraswamy.logpdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.kumaraswamy.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.kumaraswamy.logpdf( 0.0, 1.0, NaN )\n    NaN\n\n\nbase.dists.kumaraswamy.logpdf.factory( a, b )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a Kumaraswamy's double bounded distribution with\n    first shape parameter `a` and second shape parameter `b`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.kumaraswamy.logpdf.factory( 0.5, 1.0 );\n    > var y = mylogpdf( 0.8 )\n    ~-0.582\n    > y = mylogpdf( 0.3 )\n    ~-0.091\n\n","base.dists.kumaraswamy.logpdf.factory":"\nbase.dists.kumaraswamy.logpdf.factory( a, b )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a Kumaraswamy's double bounded distribution with\n    first shape parameter `a` and second shape parameter `b`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.kumaraswamy.logpdf.factory( 0.5, 1.0 );\n    > var y = mylogpdf( 0.8 )\n    ~-0.582\n    > y = mylogpdf( 0.3 )\n    ~-0.091","base.dists.kumaraswamy.mean":"\nbase.dists.kumaraswamy.mean( a, b )\n    Returns the mean of a Kumaraswamy's double bounded distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Mean.\n\n    Examples\n    --------\n    > var v = base.dists.kumaraswamy.mean( 1.5, 1.5 )\n    ~0.512\n    > v = base.dists.kumaraswamy.mean( 4.0, 12.0 )\n    ~0.481\n    > v = base.dists.kumaraswamy.mean( 16.0, 8.0 )\n    ~0.846\n\n","base.dists.kumaraswamy.median":"\nbase.dists.kumaraswamy.median( a, b )\n    Returns the median of a Kumaraswamy's double bounded distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.kumaraswamy.median( 1.0, 1.0 )\n    0.5\n    > v = base.dists.kumaraswamy.median( 4.0, 12.0 )\n    ~0.487\n    > v = base.dists.kumaraswamy.median( 16.0, 8.0 )\n    ~0.856\n\n","base.dists.kumaraswamy.mode":"\nbase.dists.kumaraswamy.mode( a, b )\n    Returns the mode of a Kumaraswamy's double bounded distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a < 1`, `b < 1`, or `a = b = 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.kumaraswamy.mode( 1.5, 1.5 )\n    ~0.543\n    > v = base.dists.kumaraswamy.mode( 4.0, 12.0 )\n    ~0.503\n    > v = base.dists.kumaraswamy.mode( 16.0, 8.0 )\n    ~0.875\n\n","base.dists.kumaraswamy.pdf":"\nbase.dists.kumaraswamy.pdf( x, a, b )\n    Evaluates the probability density function (PDF) for Kumaraswamy's double\n    bounded distribution with first shape parameter `a` and second shape\n    parameter `b` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.kumaraswamy.pdf( 0.5, 1.0, 1.0 )\n    1.0\n    > y = base.dists.kumaraswamy.pdf( 0.5, 2.0, 4.0 )\n    ~1.688\n    > y = base.dists.kumaraswamy.pdf( 0.2, 2.0, 2.0 )\n    ~0.768\n    > y = base.dists.kumaraswamy.pdf( 0.8, 4.0, 4.0 )\n    ~1.686\n    > y = base.dists.kumaraswamy.pdf( -0.5, 4.0, 2.0 )\n    0.0\n    > y = base.dists.kumaraswamy.pdf( 1.5, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.kumaraswamy.pdf( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.kumaraswamy.pdf( 2.0, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.kumaraswamy.pdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.kumaraswamy.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.kumaraswamy.pdf( 0.0, 1.0, NaN )\n    NaN\n\n\nbase.dists.kumaraswamy.pdf.factory( a, b )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Kumaraswamy's double bounded distribution with first shape parameter\n    `a` and second shape parameter `b`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var mypdf = base.dists.kumaraswamy.pdf.factory( 0.5, 1.0 );\n    > var y = mypdf( 0.8 )\n    ~0.559\n    > y = mypdf( 0.3 )\n    ~0.913\n\n","base.dists.kumaraswamy.pdf.factory":"\nbase.dists.kumaraswamy.pdf.factory( a, b )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Kumaraswamy's double bounded distribution with first shape parameter\n    `a` and second shape parameter `b`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var mypdf = base.dists.kumaraswamy.pdf.factory( 0.5, 1.0 );\n    > var y = mypdf( 0.8 )\n    ~0.559\n    > y = mypdf( 0.3 )\n    ~0.913","base.dists.kumaraswamy.quantile":"\nbase.dists.kumaraswamy.quantile( p, a, b )\n    Evaluates the quantile function for a Kumaraswamy's double bounded\n    distribution with first shape parameter `a` and second shape parameter `b`\n    at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.kumaraswamy.quantile( 0.5, 1.0, 1.0 )\n    0.5\n    > y = base.dists.kumaraswamy.quantile( 0.5, 2.0, 4.0 )\n    ~0.399\n    > y = base.dists.kumaraswamy.quantile( 0.2, 2.0, 2.0 )\n    ~0.325\n    > y = base.dists.kumaraswamy.quantile( 0.8, 4.0, 4.0 )\n    ~0.759\n\n    > y = base.dists.kumaraswamy.quantile( -0.5, 4.0, 2.0 )\n    NaN\n    > y = base.dists.kumaraswamy.quantile( 1.5, 4.0, 2.0 )\n    NaN\n\n    > y = base.dists.kumaraswamy.quantile( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.kumaraswamy.quantile( 2.0, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.kumaraswamy.quantile( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.kumaraswamy.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.kumaraswamy.quantile( 0.0, 1.0, NaN )\n    NaN\n\n\nbase.dists.kumaraswamy.quantile.factory( a, b )\n    Returns a function for evaluating the quantile function of a Kumaraswamy's\n    double bounded distribution with first shape parameter `a` and second shape\n    parameter `b`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.kumaraswamy.quantile.factory( 0.5, 1.0 );\n    > var y = myQuantile( 0.8 )\n    ~0.64\n    > y = myQuantile( 0.3 )\n    ~0.09\n\n","base.dists.kumaraswamy.quantile.factory":"\nbase.dists.kumaraswamy.quantile.factory( a, b )\n    Returns a function for evaluating the quantile function of a Kumaraswamy's\n    double bounded distribution with first shape parameter `a` and second shape\n    parameter `b`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.kumaraswamy.quantile.factory( 0.5, 1.0 );\n    > var y = myQuantile( 0.8 )\n    ~0.64\n    > y = myQuantile( 0.3 )\n    ~0.09","base.dists.kumaraswamy.skewness":"\nbase.dists.kumaraswamy.skewness( a, b )\n    Returns the skewness of a Kumaraswamy's double bounded distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.kumaraswamy.skewness( 1.0, 1.0 )\n    ~1.154e-15\n    > v = base.dists.kumaraswamy.skewness( 4.0, 12.0 )\n    ~-0.201\n    > v = base.dists.kumaraswamy.skewness( 16.0, 8.0 )\n    ~-0.94\n\n","base.dists.kumaraswamy.stdev":"\nbase.dists.kumaraswamy.stdev( a, b )\n    Returns the standard deviation of a Kumaraswamy's double bounded\n    distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.kumaraswamy.stdev( 1.0, 1.0 )\n    ~0.289\n    > v = base.dists.kumaraswamy.stdev( 4.0, 12.0 )\n    ~0.13\n    > v = base.dists.kumaraswamy.stdev( 16.0, 8.0 )\n    ~0.062\n\n","base.dists.kumaraswamy.variance":"\nbase.dists.kumaraswamy.variance( a, b )\n    Returns the variance of a Kumaraswamy's double bounded distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.kumaraswamy.variance( 1.0, 1.0 )\n    ~0.083\n    > v = base.dists.kumaraswamy.variance( 4.0, 12.0 )\n    ~0.017\n    > v = base.dists.kumaraswamy.variance( 16.0, 8.0 )\n    ~0.004\n\n","base.dists.laplace.cdf":"\nbase.dists.laplace.cdf( x, μ, b )\n    Evaluates the cumulative distribution function (CDF) for a Laplace\n    distribution with scale parameter `b` and location parameter `μ` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.cdf( 2.0, 0.0, 1.0 )\n    ~0.932\n    > y = base.dists.laplace.cdf( 5.0, 10.0, 3.0 )\n    ~0.094\n    > y = base.dists.laplace.cdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.laplace.cdf( 2, NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.cdf( 2.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.laplace.cdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.laplace.cdf.factory( μ, b )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Laplace distribution with scale parameter `b` and location parameter\n    `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.laplace.cdf.factory( 2.0, 3.0 );\n    > var y = myCDF( 10.0 )\n    ~0.965\n    > y = myCDF( 2.0 )\n    0.5\n\n","base.dists.laplace.cdf.factory":"\nbase.dists.laplace.cdf.factory( μ, b )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Laplace distribution with scale parameter `b` and location parameter\n    `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.laplace.cdf.factory( 2.0, 3.0 );\n    > var y = myCDF( 10.0 )\n    ~0.965\n    > y = myCDF( 2.0 )\n    0.5","base.dists.laplace.entropy":"\nbase.dists.laplace.entropy( μ, b )\n    Returns the differential entropy of a Laplace distribution with location\n    parameter `μ` and scale parameter `b`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Differential entropy.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.entropy( 0.0, 1.0 )\n    ~1.693\n    > y = base.dists.laplace.entropy( 4.0, 2.0 )\n    ~2.386\n    > y = base.dists.laplace.entropy( NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.entropy( 0.0, NaN )\n    NaN\n    > y = base.dists.laplace.entropy( 0.0, 0.0 )\n    NaN\n\n","base.dists.laplace.kurtosis":"\nbase.dists.laplace.kurtosis( μ, b )\n    Returns the excess kurtosis of a Laplace distribution with location\n    parameter `μ` and scale parameter `b`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.kurtosis( 0.0, 1.0 )\n    3.0\n    > y = base.dists.laplace.kurtosis( 4.0, 2.0 )\n    3.0\n    > y = base.dists.laplace.kurtosis( NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.kurtosis( 0.0, NaN )\n    NaN\n    > y = base.dists.laplace.kurtosis( 0.0, 0.0 )\n    NaN\n\n","base.dists.laplace.Laplace":"\nbase.dists.laplace.Laplace( [μ, b] )\n    Returns a Laplace distribution object.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter. Default: `0.0`.\n\n    b: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    laplace: Object\n        Distribution instance.\n\n    laplace.mu: number\n        Location parameter.\n\n    laplace.b: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    laplace.entropy: number\n        Read-only property which returns the differential entropy.\n\n    laplace.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    laplace.mean: number\n        Read-only property which returns the expected value.\n\n    laplace.median: number\n        Read-only property which returns the median.\n\n    laplace.mode: number\n        Read-only property which returns the mode.\n\n    laplace.skewness: number\n        Read-only property which returns the skewness.\n\n    laplace.stdev: number\n        Read-only property which returns the standard deviation.\n\n    laplace.variance: number\n        Read-only property which returns the variance.\n\n    laplace.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    laplace.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    laplace.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    laplace.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    laplace.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    laplace.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var laplace = base.dists.laplace.Laplace( -2.0, 3.0 );\n    > laplace.mu\n    -2.0\n    > laplace.b\n    3.0\n    > laplace.entropy\n    ~2.792\n    > laplace.kurtosis\n    3.0\n    > laplace.mean\n    -2.0\n    > laplace.median\n    -2.0\n    > laplace.mode\n    -2.0\n    > laplace.skewness\n    0.0\n    > laplace.stdev\n    ~4.243\n    > laplace.variance\n    18.0\n    > laplace.cdf( 0.8 )\n    ~0.803\n    > laplace.logcdf( 0.8 )\n    ~-0.219\n    > laplace.logpdf( 1.0 )\n    ~-2.792\n    > laplace.mgf( 0.2 )\n    ~1.047\n    > laplace.pdf( 2.0 )\n    ~0.044\n    > laplace.quantile( 0.9 )\n    ~2.828\n\n","base.dists.laplace.logcdf":"\nbase.dists.laplace.logcdf( x, μ, b )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    Laplace distribution with scale parameter `b` and location parameter `μ` at\n    a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.logcdf( 2.0, 0.0, 1.0 )\n    ~-0.07\n    > y = base.dists.laplace.logcdf( 5.0, 10.0, 3.0 )\n    ~-2.36\n    > y = base.dists.laplace.logcdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.laplace.logcdf( 2, NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.logcdf( 2.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.laplace.logcdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.laplace.logcdf.factory( μ, b )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Laplace distribution with scale parameter\n    `b` and location parameter `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.laplace.logcdf.factory( 2.0, 3.0 );\n    > var y = mylogcdf( 10.0 )\n    ~-0.035\n    > y = mylogcdf( 2.0 )\n    ~-0.693\n\n","base.dists.laplace.logcdf.factory":"\nbase.dists.laplace.logcdf.factory( μ, b )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Laplace distribution with scale parameter\n    `b` and location parameter `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.laplace.logcdf.factory( 2.0, 3.0 );\n    > var y = mylogcdf( 10.0 )\n    ~-0.035\n    > y = mylogcdf( 2.0 )\n    ~-0.693","base.dists.laplace.logpdf":"\nbase.dists.laplace.logpdf( x, μ, b )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    Laplace distribution with scale parameter `b` and location parameter `μ` at\n    a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.logpdf( 2.0, 0.0, 1.0 )\n    ~-2.693\n    > y = base.dists.laplace.logpdf( -1.0, 2.0, 3.0 )\n    ~-2.792\n    > y = base.dists.laplace.logpdf( 2.5, 2.0, 3.0 )\n    ~-1.958\n    > y = base.dists.laplace.logpdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.laplace.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.logpdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.laplace.logpdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.laplace.logpdf.factory( μ, b )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Laplace distribution with scale parameter `b` and\n    location parameter `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.laplace.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogPDF( 10.0 )\n    ~-1.386\n\n","base.dists.laplace.logpdf.factory":"\nbase.dists.laplace.logpdf.factory( μ, b )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Laplace distribution with scale parameter `b` and\n    location parameter `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.laplace.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogPDF( 10.0 )\n    ~-1.386","base.dists.laplace.mean":"\nbase.dists.laplace.mean( μ, b )\n    Returns the expected value of a Laplace distribution with location parameter\n    `μ` and scale parameter `b`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.mean( 0.0, 1.0 )\n    0.0\n    > y = base.dists.laplace.mean( 4.0, 2.0 )\n    4.0\n    > y = base.dists.laplace.mean( NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.mean( 0.0, NaN )\n    NaN\n    > y = base.dists.laplace.mean( 0.0, 0.0 )\n    NaN\n\n","base.dists.laplace.median":"\nbase.dists.laplace.median( μ, b )\n    Returns the median of a Laplace distribution with location parameter `μ` and\n    scale parameter `b`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.median( 0.0, 1.0 )\n    0.0\n    > y = base.dists.laplace.median( 4.0, 2.0 )\n    4.0\n    > y = base.dists.laplace.median( NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.median( 0.0, NaN )\n    NaN\n    > y = base.dists.laplace.median( 0.0, 0.0 )\n    NaN\n\n","base.dists.laplace.mgf":"\nbase.dists.laplace.mgf( t, μ, b )\n    Evaluates the moment-generating function (MGF) for a Laplace\n    distribution with scale parameter `b` and location parameter `μ` at a\n    value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.mgf( 0.5, 0.0, 1.0 )\n    ~1.333\n    > y = base.dists.laplace.mgf( 0.0, 0.0, 1.0 )\n    1.0\n    > y = base.dists.laplace.mgf( -1.0, 4.0, 0.2 )\n    ~0.019\n    > y = base.dists.laplace.mgf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.laplace.mgf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.mgf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.laplace.mgf( 1.0, 0.0, 2.0 )\n    NaN\n    > y = base.dists.laplace.mgf( -0.5, 0.0, 4.0 )\n    NaN\n    > y = base.dists.laplace.mgf( 2.0, 0.0, 0.0 )\n    NaN\n    > y = base.dists.laplace.mgf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.laplace.mgf.factory( μ, b )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a Laplace distribution with scale parameter `b` and location parameter\n    `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.laplace.mgf.factory( 4.0, 2.0 );\n    > var y = mymgf( 0.2 )\n    ~2.649\n    > y = mymgf( 0.4 )\n    ~13.758\n\n","base.dists.laplace.mgf.factory":"\nbase.dists.laplace.mgf.factory( μ, b )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a Laplace distribution with scale parameter `b` and location parameter\n    `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.laplace.mgf.factory( 4.0, 2.0 );\n    > var y = mymgf( 0.2 )\n    ~2.649\n    > y = mymgf( 0.4 )\n    ~13.758","base.dists.laplace.mode":"\nbase.dists.laplace.mode( μ, b )\n    Returns the mode of a Laplace distribution with location parameter `μ` and\n    scale parameter `b`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.mode( 0.0, 1.0 )\n    0.0\n    > y = base.dists.laplace.mode( 4.0, 2.0 )\n    4.0\n    > y = base.dists.laplace.mode( NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.mode( 0.0, NaN )\n    NaN\n    > y = base.dists.laplace.mode( 0.0, 0.0 )\n    NaN\n\n","base.dists.laplace.pdf":"\nbase.dists.laplace.pdf( x, μ, b )\n    Evaluates the probability density function (PDF) for a Laplace\n    distribution with scale parameter `b` and location parameter `μ` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.pdf( 2.0, 0.0, 1.0 )\n    ~0.068\n    > y = base.dists.laplace.pdf( -1.0, 2.0, 3.0 )\n    ~0.061\n    > y = base.dists.laplace.pdf( 2.5, 2.0, 3.0 )\n    ~0.141\n    > y = base.dists.laplace.pdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.laplace.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.pdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.laplace.pdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.laplace.pdf.factory( μ, b )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Laplace distribution with scale parameter `b` and location parameter\n    `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.laplace.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    0.25\n\n","base.dists.laplace.pdf.factory":"\nbase.dists.laplace.pdf.factory( μ, b )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Laplace distribution with scale parameter `b` and location parameter\n    `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.laplace.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    0.25","base.dists.laplace.quantile":"\nbase.dists.laplace.quantile( p, μ, b )\n    Evaluates the quantile function for a Laplace distribution with scale\n    parameter `b` and location parameter `μ` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.quantile( 0.8, 0.0, 1.0 )\n    ~0.916\n    > y = base.dists.laplace.quantile( 0.5, 4.0, 2.0 )\n    4.0\n\n    > y = base.dists.laplace.quantile( 1.1, 0.0, 1.0 )\n    NaN\n    > y = base.dists.laplace.quantile( -0.2, 0.0, 1.0 )\n    NaN\n\n    > y = base.dists.laplace.quantile( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.laplace.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.quantile( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.laplace.quantile( 0.5, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.laplace.quantile.factory( μ, b )\n    Returns a function for evaluating the quantile function of a Laplace\n    distribution with scale parameter `b` and location parameter `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.laplace.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    10.0\n    > y = myQuantile( 0.8 )\n    ~11.833\n\n","base.dists.laplace.quantile.factory":"\nbase.dists.laplace.quantile.factory( μ, b )\n    Returns a function for evaluating the quantile function of a Laplace\n    distribution with scale parameter `b` and location parameter `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.laplace.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    10.0\n    > y = myQuantile( 0.8 )\n    ~11.833","base.dists.laplace.skewness":"\nbase.dists.laplace.skewness( μ, b )\n    Returns the skewness of a Laplace distribution with location parameter `μ`\n    and scale parameter `b`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.skewness( 0.0, 1.0 )\n    0.0\n    > y = base.dists.laplace.skewness( 4.0, 2.0 )\n    0.0\n    > y = base.dists.laplace.skewness( NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.skewness( 0.0, NaN )\n    NaN\n    > y = base.dists.laplace.skewness( 0.0, 0.0 )\n    NaN\n\n","base.dists.laplace.stdev":"\nbase.dists.laplace.stdev( μ, b )\n    Returns the standard deviation of a Laplace distribution with location\n    parameter `μ` and scale parameter `b`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.stdev( 0.0, 1.0 )\n    ~1.414\n    > y = base.dists.laplace.stdev( 4.0, 2.0 )\n    ~2.828\n    > y = base.dists.laplace.stdev( NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.stdev( 0.0, NaN )\n    NaN\n    > y = base.dists.laplace.stdev( 0.0, 0.0 )\n    NaN\n\n","base.dists.laplace.variance":"\nbase.dists.laplace.variance( μ, b )\n    Returns the variance of a Laplace distribution with location parameter `μ`\n    and scale parameter `b`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.variance( 0.0, 1.0 )\n    2.0\n    > y = base.dists.laplace.variance( 4.0, 2.0 )\n    8.0\n    > y = base.dists.laplace.variance( NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.variance( 0.0, NaN )\n    NaN\n    > y = base.dists.laplace.variance( 0.0, 0.0 )\n    NaN\n\n","base.dists.levy.cdf":"\nbase.dists.levy.cdf( x, μ, c )\n    Evaluates the cumulative distribution function (CDF) for a Lévy distribution\n    with location parameter `μ` and scale parameter `c` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.levy.cdf( 2.0, 0.0, 1.0 )\n    ~0.48\n    > y = base.dists.levy.cdf( 12.0, 10.0, 3.0 )\n    ~0.221\n    > y = base.dists.levy.cdf( 9.0, 10.0, 3.0 )\n    0.0\n    > y = base.dists.levy.cdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.levy.cdf( 2, NaN, 1.0 )\n    NaN\n    > y = base.dists.levy.cdf( 2.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.levy.cdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.levy.cdf.factory( μ, c )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.levy.cdf.factory( 2.0, 3.0 );\n    > var y = myCDF( 10.0 )\n    ~0.54\n    > y = myCDF( 2.0 )\n    0.0\n\n","base.dists.levy.cdf.factory":"\nbase.dists.levy.cdf.factory( μ, c )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.levy.cdf.factory( 2.0, 3.0 );\n    > var y = myCDF( 10.0 )\n    ~0.54\n    > y = myCDF( 2.0 )\n    0.0","base.dists.levy.entropy":"\nbase.dists.levy.entropy( μ, c )\n    Returns the entropy of a Lévy distribution with location parameter `μ` and\n    scale parameter `c`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var y = base.dists.levy.entropy( 0.0, 1.0 )\n    ~3.324\n    > y = base.dists.levy.entropy( 4.0, 2.0 )\n    ~4.018\n    > y = base.dists.levy.entropy( NaN, 1.0 )\n    NaN\n    > y = base.dists.levy.entropy( 0.0, NaN )\n    NaN\n    > y = base.dists.levy.entropy( 0.0, 0.0 )\n    NaN\n\n","base.dists.levy.Levy":"\nbase.dists.levy.Levy( [μ, c] )\n    Returns a Lévy distribution object.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter. Default: `0.0`.\n\n    c: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    levy: Object\n        Distribution instance.\n\n    levy.mu: number\n        Location parameter.\n\n    levy.c: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    levy.entropy: number\n        Read-only property which returns the differential entropy.\n\n    levy.mean: number\n        Read-only property which returns the expected value.\n\n    levy.median: number\n        Read-only property which returns the median.\n\n    levy.mode: number\n        Read-only property which returns the mode.\n\n    levy.stdev: number\n        Read-only property which returns the standard deviation.\n\n    levy.variance: number\n        Read-only property which returns the variance.\n\n    levy.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    levy.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    levy.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    levy.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    levy.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var levy = base.dists.levy.Levy( -2.0, 3.0 );\n    > levy.mu\n    -2.0\n    > levy.c\n    3.0\n    > levy.entropy\n    ~4.423\n    > levy.mean\n    Infinity\n    > levy.median\n    ~4.594\n    > levy.mode\n    -1.0\n    > levy.stdev\n    Infinity\n    > levy.variance\n    Infinity\n    > levy.cdf( 0.8 )\n    ~0.3\n    > levy.logcdf( 0.8 )\n    ~-1.2\n    > levy.logpdf( 1.0 )\n    ~-2.518\n    > levy.pdf( 1.0 )\n    ~0.081\n    > levy.quantile( 0.8 )\n    ~44.74\n\n","base.dists.levy.logcdf":"\nbase.dists.levy.logcdf( x, μ, c )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    Lévy distribution with location parameter `μ` and scale parameter `c` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.levy.logcdf( 2.0, 0.0, 1.0 )\n    ~-0.735\n    > y = base.dists.levy.logcdf( 12.0, 10.0, 3.0 )\n    ~-1.51\n    > y = base.dists.levy.logcdf( 9.0, 10.0, 3.0 )\n    -Infinity\n    > y = base.dists.levy.logcdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.levy.logcdf( 2, NaN, 1.0 )\n    NaN\n    > y = base.dists.levy.logcdf( 2.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.levy.logcdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.levy.logcdf.factory( μ, c )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Lévy distribution with location parameter\n    `μ` and scale parameter `c`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.levy.logcdf.factory( 2.0, 3.0 );\n    > var y = mylogcdf( 10.0 )\n    ~-0.616\n    > y = mylogcdf( 2.0 )\n    -Infinity\n\n","base.dists.levy.logcdf.factory":"\nbase.dists.levy.logcdf.factory( μ, c )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Lévy distribution with location parameter\n    `μ` and scale parameter `c`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.levy.logcdf.factory( 2.0, 3.0 );\n    > var y = mylogcdf( 10.0 )\n    ~-0.616\n    > y = mylogcdf( 2.0 )\n    -Infinity","base.dists.levy.logpdf":"\nbase.dists.levy.logpdf( x, μ, c )\n    Evaluates the logarithm of the probability density function (PDF) for a Lévy\n    distribution with location parameter `μ` and scale parameter `c` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.levy.logpdf( 2.0, 0.0, 1.0 )\n    ~-2.209\n    > y = base.dists.levy.logpdf( -1.0, 4.0, 2.0 )\n    -Infinity\n    > y = base.dists.levy.logpdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.levy.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.levy.logpdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.levy.logpdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.levy.logpdf.factory( μ, c )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Lévy distribution with location parameter `μ` and scale\n    parameter `c`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.levy.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogPDF( 11.0 )\n    ~-1.572\n\n","base.dists.levy.logpdf.factory":"\nbase.dists.levy.logpdf.factory( μ, c )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Lévy distribution with location parameter `μ` and scale\n    parameter `c`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.levy.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogPDF( 11.0 )\n    ~-1.572","base.dists.levy.mean":"\nbase.dists.levy.mean( μ, c )\n    Returns the expected value of a Lévy distribution with location parameter\n    `μ` and scale parameter `c`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var y = base.dists.levy.mean( 0.0, 1.0 )\n    Infinity\n    > y = base.dists.levy.mean( 4.0, 3.0 )\n    Infinity\n    > y = base.dists.levy.mean( NaN, 1.0 )\n    NaN\n    > y = base.dists.levy.mean( 0.0, NaN )\n    NaN\n    > y = base.dists.levy.mean( 0.0, 0.0 )\n    NaN\n\n","base.dists.levy.median":"\nbase.dists.levy.median( μ, c )\n    Returns the median of a Lévy distribution with location parameter `μ` and\n    scale parameter `c`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var y = base.dists.levy.median( 0.0, 1.0 )\n    ~2.198\n    > y = base.dists.levy.median( 4.0, 3.0 )\n    ~10.594\n    > y = base.dists.levy.median( NaN, 1.0 )\n    NaN\n    > y = base.dists.levy.median( 0.0, NaN )\n    NaN\n    > y = base.dists.levy.median( 0.0, 0.0 )\n    NaN\n\n","base.dists.levy.mode":"\nbase.dists.levy.mode( μ, c )\n    Returns the mode of a Lévy distribution with location parameter `μ` and\n    scale parameter `c`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var y = base.dists.levy.mode( 0.0, 1.0 )\n    ~0.333\n    > y = base.dists.levy.mode( 4.0, 3.0 )\n    5.0\n    > y = base.dists.levy.mode( NaN, 1.0 )\n    NaN\n    > y = base.dists.levy.mode( 0.0, NaN )\n    NaN\n    > y = base.dists.levy.mode( 0.0, 0.0 )\n    NaN\n\n","base.dists.levy.pdf":"\nbase.dists.levy.pdf( x, μ, c )\n    Evaluates the probability density function (PDF) for a Lévy distribution\n    with location parameter `μ` and scale parameter `c` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.levy.pdf( 2.0, 0.0, 1.0 )\n    ~0.11\n    > y = base.dists.levy.pdf( -1.0, 4.0, 2.0 )\n    0.0\n    > y = base.dists.levy.pdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.levy.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.levy.pdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.levy.pdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.levy.pdf.factory( μ, c )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.levy.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 11.0 )\n    ~0.208\n\n","base.dists.levy.pdf.factory":"\nbase.dists.levy.pdf.factory( μ, c )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.levy.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 11.0 )\n    ~0.208","base.dists.levy.quantile":"\nbase.dists.levy.quantile( p, μ, c )\n    Evaluates the quantile function for a Lévy distribution with location\n    parameter `μ` and scale parameter `c` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.levy.quantile( 0.8, 0.0, 1.0 )\n    ~15.58\n    > y = base.dists.levy.quantile( 0.5, 4.0, 2.0 )\n    ~8.396\n\n    > y = base.dists.levy.quantile( 1.1, 0.0, 1.0 )\n    NaN\n    > y = base.dists.levy.quantile( -0.2, 0.0, 1.0 )\n    NaN\n\n    > y = base.dists.levy.quantile( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.levy.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.levy.quantile( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.levy.quantile( 0.5, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.levy.quantile.factory( μ, c )\n    Returns a function for evaluating the quantile function of a Lévy\n    distribution with location parameter `μ` and scale parameter `c`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.levy.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    ~14.396\n\n","base.dists.levy.quantile.factory":"\nbase.dists.levy.quantile.factory( μ, c )\n    Returns a function for evaluating the quantile function of a Lévy\n    distribution with location parameter `μ` and scale parameter `c`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.levy.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    ~14.396","base.dists.levy.stdev":"\nbase.dists.levy.stdev( μ, c )\n    Returns the standard deviation of a Lévy distribution with location\n    parameter `μ` and scale parameter `c`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var y = base.dists.levy.stdev( 0.0, 1.0 )\n    Infinity\n    > y = base.dists.levy.stdev( 4.0, 3.0 )\n    Infinity\n    > y = base.dists.levy.stdev( NaN, 1.0 )\n    NaN\n    > y = base.dists.levy.stdev( 0.0, NaN )\n    NaN\n    > y = base.dists.levy.stdev( 0.0, 0.0 )\n    NaN\n\n","base.dists.levy.variance":"\nbase.dists.levy.variance( μ, c )\n    Returns the variance of a Lévy distribution with location parameter `μ` and\n    scale parameter `c`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var y = base.dists.levy.variance( 0.0, 1.0 )\n    Infinity\n    > y = base.dists.levy.variance( 4.0, 3.0 )\n    Infinity\n    > y = base.dists.levy.variance( NaN, 1.0 )\n    NaN\n    > y = base.dists.levy.variance( 0.0, NaN )\n    NaN\n    > y = base.dists.levy.variance( 0.0, 0.0 )\n    NaN\n\n","base.dists.logistic.cdf":"\nbase.dists.logistic.cdf( x, μ, s )\n    Evaluates the cumulative distribution function (CDF) for a logistic\n    distribution with location parameter `μ` and scale parameter `s` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.cdf( 2.0, 0.0, 1.0 )\n    ~0.881\n    > y = base.dists.logistic.cdf( 5.0, 10.0, 3.0 )\n    ~0.159\n\n    > y = base.dists.logistic.cdf( 2.0, 0.0, NaN )\n    NaN\n    > y = base.dists.logistic.cdf( 2.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.cdf( NaN, 0.0, 1.0 )\n    NaN\n\n    // Degenerate distribution centered at `μ` when `s = 0.0`:\n    > y = base.dists.logistic.cdf( 2.0, 8.0, 0.0 )\n    0.0\n    > y = base.dists.logistic.cdf( 8.0, 8.0, 0.0 )\n    1.0\n    > y = base.dists.logistic.cdf( 10.0, 8.0, 0.0 )\n    1.0\n\n\nbase.dists.logistic.cdf.factory( μ, s )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a logistic distribution with location parameter `μ` and scale parameter\n    `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.logistic.cdf.factory( 3.0, 1.5 );\n    > var y = mycdf( 1.0 )\n    ~0.209\n\n","base.dists.logistic.cdf.factory":"\nbase.dists.logistic.cdf.factory( μ, s )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a logistic distribution with location parameter `μ` and scale parameter\n    `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.logistic.cdf.factory( 3.0, 1.5 );\n    > var y = mycdf( 1.0 )\n    ~0.209","base.dists.logistic.entropy":"\nbase.dists.logistic.entropy( μ, s )\n    Returns the entropy of a logistic distribution with location parameter `μ`\n    and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.entropy( 0.0, 1.0 )\n    2.0\n    > y = base.dists.logistic.entropy( 4.0, 2.0 )\n    ~2.693\n    > y = base.dists.logistic.entropy( NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.entropy( 0.0, NaN )\n    NaN\n    > y = base.dists.logistic.entropy( 0.0, 0.0 )\n    NaN\n\n","base.dists.logistic.kurtosis":"\nbase.dists.logistic.kurtosis( μ, s )\n    Returns the excess kurtosis of a logistic distribution with location\n    parameter `μ` and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.kurtosis( 0.0, 1.0 )\n    1.2\n    > y = base.dists.logistic.kurtosis( 4.0, 2.0 )\n    1.2\n    > y = base.dists.logistic.kurtosis( NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.kurtosis( 0.0, NaN )\n    NaN\n    > y = base.dists.logistic.kurtosis( 0.0, 0.0 )\n    NaN\n\n\n","base.dists.logistic.logcdf":"\nbase.dists.logistic.logcdf( x, μ, s )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    logistic distribution with location parameter `μ` and scale parameter `s` at\n    a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.logcdf( 2.0, 0.0, 1.0 )\n    ~-0.127\n    > y = base.dists.logistic.logcdf( 5.0, 10.0, 3.0 )\n    ~-1.84\n    > y = base.dists.logistic.logcdf( 2.0, 0.0, NaN )\n    NaN\n    > y = base.dists.logistic.logcdf( 2, NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.logcdf( NaN, 0.0, 1.0 )\n    NaN\n\n\nbase.dists.logistic.logcdf.factory( μ, s )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Logistic distribution with location\n    parameter `μ` and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.logistic.logcdf.factory( 3.0, 1.5 );\n    > var y = mylogcdf( 1.0 )\n    ~-1.567\n\n","base.dists.logistic.logcdf.factory":"\nbase.dists.logistic.logcdf.factory( μ, s )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Logistic distribution with location\n    parameter `μ` and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.logistic.logcdf.factory( 3.0, 1.5 );\n    > var y = mylogcdf( 1.0 )\n    ~-1.567","base.dists.logistic.Logistic":"\nbase.dists.logistic.Logistic( [μ, s] )\n    Returns a logistic distribution object.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter. Default: `0.0`.\n\n    s: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    logistic: Object\n        Distribution instance.\n\n    logistic.mu: number\n        Location parameter.\n\n    logistic.s: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    logistic.entropy: number\n        Read-only property which returns the differential entropy.\n\n    logistic.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    logistic.mean: number\n        Read-only property which returns the expected value.\n\n    logistic.median: number\n        Read-only property which returns the median.\n\n    logistic.mode: number\n        Read-only property which returns the mode.\n\n    logistic.skewness: number\n        Read-only property which returns the skewness.\n\n    logistic.stdev: number\n        Read-only property which returns the standard deviation.\n\n    logistic.variance: number\n        Read-only property which returns the variance.\n\n    logistic.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    logistic.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    logistic.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    logistic.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    logistic.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    logistic.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var logistic = base.dists.logistic.Logistic( -2.0, 3.0 );\n    > logistic.mu\n    -2.0\n    > logistic.s\n    3.0\n    > logistic.entropy\n    ~3.1\n    > logistic.kurtosis\n    1.2\n    > logistic.mean\n    -2.0\n    > logistic.median\n    -2.0\n    > logistic.mode\n    -2.0\n    > logistic.skewness\n    0.0\n    > logistic.stdev\n    ~5.441\n    > logistic.variance\n    ~29.609\n    > logistic.cdf( 0.8 )\n    ~0.718\n    > logistic.logcdf( 0.8 )\n    ~-0.332\n    > logistic.logpdf( 2.0 )\n    ~-2.9\n    > logistic.mgf( 0.2 )\n    ~1.329\n    > logistic.pdf( 2.0 )\n    ~0.055\n    > logistic.quantile( 0.9 )\n    ~4.592\n\n","base.dists.logistic.logpdf":"\nbase.dists.logistic.logpdf( x, μ, s )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    logistic distribution with location parameter `μ` and scale parameter `s` at\n    a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.logpdf( 2.0, 0.0, 1.0 )\n    ~-2.254\n    > y = base.dists.logistic.logpdf( -1.0, 4.0, 2.0 )\n    ~-3.351\n    > y = base.dists.logistic.logpdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.logistic.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.logpdf( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.logistic.logpdf( 2.0, 0.0, -1.0 )\n    NaN\n\n    // Degenerate distribution at `s = 0.0`:\n    > y = base.dists.logistic.logpdf( 2.0, 8.0, 0.0 )\n    -Infinity\n    > y = base.dists.logistic.logpdf( 8.0, 8.0, 0.0 )\n    Infinity\n\n\nbase.dists.logistic.logpdf.factory( μ, s )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Logistic distribution with location parameter `μ` and\n    scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.logistic.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogpdf( 10.0 )\n    ~-2.079\n\n","base.dists.logistic.logpdf.factory":"\nbase.dists.logistic.logpdf.factory( μ, s )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Logistic distribution with location parameter `μ` and\n    scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.logistic.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogpdf( 10.0 )\n    ~-2.079","base.dists.logistic.mean":"\nbase.dists.logistic.mean( μ, s )\n    Returns the expected value of a logistic distribution with location\n    parameter `μ` and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.mean( 0.0, 1.0 )\n    0.0\n    > y = base.dists.logistic.mean( 4.0, 2.0 )\n    4.0\n    > y = base.dists.logistic.mean( NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.mean( 0.0, NaN )\n    NaN\n    > y = base.dists.logistic.mean( 0.0, 0.0 )\n    NaN\n\n","base.dists.logistic.median":"\nbase.dists.logistic.median( μ, s )\n    Returns the median of a logistic distribution with location parameter `μ`\n    and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.median( 0.0, 1.0 )\n    0.0\n    > y = base.dists.logistic.median( 4.0, 2.0 )\n    4.0\n    > y = base.dists.logistic.median( NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.median( 0.0, NaN )\n    NaN\n    > y = base.dists.logistic.median( 0.0, 0.0 )\n    NaN\n\n","base.dists.logistic.mgf":"\nbase.dists.logistic.mgf( t, μ, s )\n    Evaluates the moment-generating function (MGF) for a logistic distribution\n    with location parameter `μ` and scale parameter `s` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.mgf( 0.9, 0.0, 1.0 )\n    ~9.15\n    > y = base.dists.logistic.mgf( 0.1, 4.0, 4.0 )\n    ~1.971\n    > y = base.dists.logistic.mgf( -0.2, 4.0, 4.0 )\n    ~1.921\n    > y = base.dists.logistic.mgf( 0.5, 0.0, -1.0 )\n    NaN\n    > y = base.dists.logistic.mgf( 0.5, 0.0, 4.0 )\n    Infinity\n    > y = base.dists.logistic.mgf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.logistic.mgf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.mgf( 0.0, 0.0, NaN )\n    NaN\n\n\nbase.dists.logistic.mgf.factory( μ, s )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a Logistic distribution with location parameter `μ` and scale parameter\n    `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.logistic.mgf.factory( 10.0, 0.5 );\n    > var y = mymgf( 0.5 )\n    ~164.846\n    > y = mymgf( 2.0 )\n    Infinity\n\n","base.dists.logistic.mgf.factory":"\nbase.dists.logistic.mgf.factory( μ, s )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a Logistic distribution with location parameter `μ` and scale parameter\n    `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.logistic.mgf.factory( 10.0, 0.5 );\n    > var y = mymgf( 0.5 )\n    ~164.846\n    > y = mymgf( 2.0 )\n    Infinity","base.dists.logistic.mode":"\nbase.dists.logistic.mode( μ, s )\n    Returns the mode of a logistic distribution with location parameter `μ` and\n    scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.mode( 0.0, 1.0 )\n    0.0\n    > y = base.dists.logistic.mode( 4.0, 2.0 )\n    4.0\n    > y = base.dists.logistic.mode( NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.mode( 0.0, NaN )\n    NaN\n    > y = base.dists.logistic.mode( 0.0, 0.0 )\n    NaN\n\n","base.dists.logistic.pdf":"\nbase.dists.logistic.pdf( x, μ, s )\n    Evaluates the probability density function (PDF) for a logistic distribution\n    with location parameter `μ` and scale parameter `s` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.pdf( 2.0, 0.0, 1.0 )\n    ~0.105\n    > y = base.dists.logistic.pdf( -1.0, 4.0, 2.0 )\n    ~0.035\n    > y = base.dists.logistic.pdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.logistic.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.pdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.logistic.pdf( 2.0, 0.0, -1.0 )\n    NaN\n    > y = base.dists.logistic.pdf( 2.0, 8.0, 0.0 )\n    0.0\n    > y = base.dists.logistic.pdf( 8.0, 8.0, 0.0 )\n    Infinity\n\n\nbase.dists.logistic.pdf.factory( μ, s )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Logistic distribution with location parameter `μ` and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.logistic.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    0.125\n\n","base.dists.logistic.pdf.factory":"\nbase.dists.logistic.pdf.factory( μ, s )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Logistic distribution with location parameter `μ` and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.logistic.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    0.125","base.dists.logistic.quantile":"\nbase.dists.logistic.quantile( p, μ, s )\n    Evaluates the quantile function for a logistic distribution with location\n    parameter `μ` and scale parameter `s` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.quantile( 0.8, 0.0, 1.0 )\n    ~1.386\n    > y = base.dists.logistic.quantile( 0.5, 4.0, 2.0 )\n    4\n\n    > y = base.dists.logistic.quantile( 1.1, 0.0, 1.0 )\n    NaN\n    > y = base.dists.logistic.quantile( -0.2, 0.0, 1.0 )\n    NaN\n\n    > y = base.dists.logistic.quantile( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.logistic.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.quantile( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.logistic.quantile( 0.5, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.logistic.quantile.factory( μ, s )\n    Returns a function for evaluating the quantile function of a logistic\n    distribution with location parameter `μ` and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.logistic.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    10.0\n\n","base.dists.logistic.quantile.factory":"\nbase.dists.logistic.quantile.factory( μ, s )\n    Returns a function for evaluating the quantile function of a logistic\n    distribution with location parameter `μ` and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.logistic.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    10.0","base.dists.logistic.skewness":"\nbase.dists.logistic.skewness( μ, s )\n    Returns the skewness of a logistic distribution with location parameter `μ`\n    and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.skewness( 0.0, 1.0 )\n    0.0\n    > y = base.dists.logistic.skewness( 4.0, 2.0 )\n    0.0\n    > y = base.dists.logistic.skewness( NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.skewness( 0.0, NaN )\n    NaN\n    > y = base.dists.logistic.skewness( 0.0, 0.0 )\n    NaN\n\n","base.dists.logistic.stdev":"\nbase.dists.logistic.stdev( μ, s )\n    Returns the standard deviation of a logistic distribution with location\n    parameter `μ` and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.stdev( 0.0, 1.0 )\n    ~1.814\n    > y = base.dists.logistic.stdev( 4.0, 2.0 )\n    ~3.628\n    > y = base.dists.logistic.stdev( NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.stdev( 0.0, NaN )\n    NaN\n    > y = base.dists.logistic.stdev( 0.0, 0.0 )\n    NaN\n\n","base.dists.logistic.variance":"\nbase.dists.logistic.variance( μ, s )\n    Returns the variance of a logistic distribution with location parameter `μ`\n    and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.variance( 0.0, 1.0 )\n    ~3.29\n    > y = base.dists.logistic.variance( 4.0, 2.0 )\n    ~13.159\n    > y = base.dists.logistic.variance( NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.variance( 0.0, NaN )\n    NaN\n    > y = base.dists.logistic.variance( 0.0, 0.0 )\n    NaN\n\n","base.dists.lognormal.cdf":"\nbase.dists.lognormal.cdf( x, μ, σ )\n    Evaluates the cumulative distribution function (CDF) for a lognormal\n    distribution with location parameter `μ` and scale parameter `σ` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.cdf( 2.0, 0.0, 1.0 )\n    ~0.756\n    > y = base.dists.lognormal.cdf( 5.0, 10.0, 3.0 )\n    ~0.003\n\n    > y = base.dists.lognormal.cdf( 2.0, 0.0, NaN )\n    NaN\n    > y = base.dists.lognormal.cdf( 2.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.cdf( NaN, 0.0, 1.0 )\n    NaN\n\n    // Non-positive scale parameter `σ`:\n    > y = base.dists.lognormal.cdf( 2.0, 0.0, -1.0 )\n    NaN\n    > y = base.dists.lognormal.cdf( 2.0, 0.0, 0.0 )\n    NaN\n\n\nbase.dists.lognormal.cdf.factory( μ, σ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a lognormal distribution with location parameter `μ` and scale parameter\n    `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.lognormal.cdf.factory( 3.0, 1.5 );\n    > var y = myCDF( 1.0 )\n    ~0.023\n    > y = myCDF( 4.0 )\n    ~0.141\n\n","base.dists.lognormal.cdf.factory":"\nbase.dists.lognormal.cdf.factory( μ, σ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a lognormal distribution with location parameter `μ` and scale parameter\n    `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.lognormal.cdf.factory( 3.0, 1.5 );\n    > var y = myCDF( 1.0 )\n    ~0.023\n    > y = myCDF( 4.0 )\n    ~0.141","base.dists.lognormal.entropy":"\nbase.dists.lognormal.entropy( μ, σ )\n    Returns the differential entropy of a lognormal distribution with location\n    `μ` and scale `σ` (in nats).\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.entropy( 0.0, 1.0 )\n    ~1.419\n    > y = base.dists.lognormal.entropy( 5.0, 2.0 )\n    ~7.112\n    > y = base.dists.lognormal.entropy( NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.entropy( 0.0, NaN )\n    NaN\n    > y = base.dists.lognormal.entropy( 0.0, 0.0 )\n    NaN\n\n","base.dists.lognormal.kurtosis":"\nbase.dists.lognormal.kurtosis( μ, σ )\n    Returns the excess kurtosis of a lognormal distribution with location `μ`\n    and scale `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Kurtosis.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.kurtosis( 0.0, 1.0 )\n    ~110.936\n    > y = base.dists.lognormal.kurtosis( 5.0, 2.0 )\n    ~9220556.977\n    > y = base.dists.lognormal.kurtosis( NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.kurtosis( 0.0, NaN )\n    NaN\n    > y = base.dists.lognormal.kurtosis( 0.0, 0.0 )\n    NaN\n\n","base.dists.lognormal.LogNormal":"\nbase.dists.lognormal.LogNormal( [μ, σ] )\n    Returns a lognormal distribution object.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter. Default: `0.0`.\n\n    σ: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    lognormal: Object\n        Distribution instance.\n\n    lognormal.mu: number\n        Location parameter.\n\n    lognormal.sigma: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    lognormal.entropy: number\n        Read-only property which returns the differential entropy.\n\n    lognormal.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    lognormal.mean: number\n        Read-only property which returns the expected value.\n\n    lognormal.median: number\n        Read-only property which returns the median.\n\n    lognormal.mode: number\n        Read-only property which returns the mode.\n\n    lognormal.skewness: number\n        Read-only property which returns the skewness.\n\n    lognormal.stdev: number\n        Read-only property which returns the standard deviation.\n\n    lognormal.variance: number\n        Read-only property which returns the variance.\n\n    lognormal.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    lognormal.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    lognormal.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    lognormal.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    lognormal.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var lognormal = base.dists.lognormal.LogNormal( -2.0, 3.0 );\n    > lognormal.mu\n    -2.0\n    > lognormal.sigma\n    3.0\n    > lognormal.entropy\n    ~0.518\n    > lognormal.kurtosis\n    4312295840576300\n    > lognormal.mean\n    ~12.182\n    > lognormal.median\n    ~0.135\n    > lognormal.mode\n    ~0.0\n    > lognormal.skewness\n    ~729551.383\n    > lognormal.stdev\n    ~1096.565\n    > lognormal.variance\n    ~1202455.871\n    > lognormal.cdf( 0.8 )\n    ~0.723\n    > lognormal.logcdf( 0.8 )\n    ~-4.334\n    > lognormal.logpdf( 2.0 )\n    ~-3.114\n    > lognormal.pdf( 2.0 )\n    ~0.044\n    > lognormal.quantile( 0.9 )\n    ~6.326\n\n","base.dists.lognormal.logcdf":"\nbase.dists.lognormal.logcdf( x, μ, σ )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a lognormal distribution with mean `μ` and standard deviation `σ`\n    at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Evaluated logcdf.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.logcdf( 2.0, 0.0, 1.0 )\n    ~-0.2799\n    > y = base.dists.lognormal.logcdf( 13.0, 4.0, 2.0 )\n    ~-1.442\n    > y = base.dists.lognormal.logcdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.lognormal.logcdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.logcdf( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative standard deviation:\n    > y = base.dists.lognormal.logcdf( 2.0, 0.0, -1.0 )\n    NaN\n\n    // Degenerate distribution centered at `μ` when `σ = 0.0`:\n    > y = base.dists.lognormal.logcdf( 2.0, 8.0, 0.0 )\n    -Infinity\n    > y = base.dists.lognormal.logcdf( 8.0, 8.0, 0.0 )\n    -Infinity\n\n\nbase.dists.lognormal.logcdf.factory( μ, σ )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a lognormal distribution with mean `μ` and\n    standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.lognormal.logcdf.factory( 10.0, 2.0 );\n    > var y = mylogcdf( 10.0 )\n    ~-9.732\n\n","base.dists.lognormal.logcdf.factory":"\nbase.dists.lognormal.logcdf.factory( μ, σ )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a lognormal distribution with mean `μ` and\n    standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.lognormal.logcdf.factory( 10.0, 2.0 );\n    > var y = mylogcdf( 10.0 )\n    ~-9.732","base.dists.lognormal.logpdf":"\nbase.dists.lognormal.logpdf( x, μ, σ )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a lognormal distribution with location parameter `μ` and scale parameter\n    `σ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.logpdf( 2.0, 0.0, 1.0 )\n    ~-1.852\n    > y = base.dists.lognormal.logpdf( 1.0, 0.0, 1.0 )\n    ~-0.919\n    > y = base.dists.lognormal.logpdf( 1.0, 3.0, 1.0 )\n    ~-5.419\n    > y = base.dists.lognormal.logpdf( -1.0, 4.0, 2.0 )\n    -Infinity\n\n    > y = base.dists.lognormal.logpdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.lognormal.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.logpdf( 0.0, 0.0, NaN )\n    NaN\n\n    // Non-positive scale parameter `σ`:\n    > y = base.dists.lognormal.logpdf( 2.0, 0.0, -1.0 )\n    NaN\n    > y = base.dists.lognormal.logpdf( 2.0, 0.0, 0.0 )\n    NaN\n\n\nbase.dists.lognormal.logpdf.factory( μ, σ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a lognormal distribution with location parameter\n    `μ` and scale parameter `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.lognormal.logpdf.factory( 4.0, 2.0 );\n    > var y = mylogPDF( 10.0 )\n    ~-4.275\n    > y = mylogPDF( 2.0 )\n    ~-3.672\n\n","base.dists.lognormal.logpdf.factory":"\nbase.dists.lognormal.logpdf.factory( μ, σ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a lognormal distribution with location parameter\n    `μ` and scale parameter `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.lognormal.logpdf.factory( 4.0, 2.0 );\n    > var y = mylogPDF( 10.0 )\n    ~-4.275\n    > y = mylogPDF( 2.0 )\n    ~-3.672","base.dists.lognormal.mean":"\nbase.dists.lognormal.mean( μ, σ )\n    Returns the expected value of a lognormal distribution with location `μ` and\n    scale `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.mean( 0.0, 1.0 )\n    ~1.649\n    > y = base.dists.lognormal.mean( 4.0, 2.0 )\n    ~403.429\n    > y = base.dists.lognormal.mean( NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.mean( 0.0, NaN )\n    NaN\n    > y = base.dists.lognormal.mean( 0.0, 0.0 )\n    NaN\n\n","base.dists.lognormal.median":"\nbase.dists.lognormal.median( μ, σ )\n    Returns the median of a lognormal distribution with location `μ` and scale\n    `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.median( 0.0, 1.0 )\n    1.0\n    > y = base.dists.lognormal.median( 5.0, 2.0 )\n    ~148.413\n    > y = base.dists.lognormal.median( NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.median( 0.0, NaN )\n    NaN\n    > y = base.dists.lognormal.median( 0.0, 0.0 )\n    NaN\n\n","base.dists.lognormal.mode":"\nbase.dists.lognormal.mode( μ, σ )\n    Returns the mode of a lognormal distribution with location `μ` and scale\n    `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.mode( 0.0, 1.0 )\n    ~0.368\n    > y = base.dists.lognormal.mode( 5.0, 2.0 )\n    ~2.718\n    > y = base.dists.lognormal.mode( NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.mode( 0.0, NaN )\n    NaN\n    > y = base.dists.lognormal.mode( 0.0, 0.0 )\n    NaN\n\n","base.dists.lognormal.pdf":"\nbase.dists.lognormal.pdf( x, μ, σ )\n    Evaluates the probability density function (PDF) for a lognormal\n    distribution with location parameter `μ` and scale parameter `σ` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.pdf( 2.0, 0.0, 1.0 )\n    ~0.157\n    > y = base.dists.lognormal.pdf( 1.0, 0.0, 1.0 )\n    ~0.399\n    > y = base.dists.lognormal.pdf( 1.0, 3.0, 1.0 )\n    ~0.004\n    > y = base.dists.lognormal.pdf( -1.0, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.lognormal.pdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.lognormal.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.pdf( 0.0, 0.0, NaN )\n    NaN\n\n    // Non-positive scale parameter `σ`:\n    > y = base.dists.lognormal.pdf( 2.0, 0.0, -1.0 )\n    NaN\n    > y = base.dists.lognormal.pdf( 2.0, 0.0, 0.0 )\n    NaN\n\n\nbase.dists.lognormal.pdf.factory( μ, σ )\n    Returns a function for evaluating the probability density function (PDF) of\n    a lognormal distribution with location parameter `μ` and scale parameter\n    `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.lognormal.pdf.factory( 4.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    ~0.014\n    > y = myPDF( 2.0 )\n    ~0.025\n\n","base.dists.lognormal.pdf.factory":"\nbase.dists.lognormal.pdf.factory( μ, σ )\n    Returns a function for evaluating the probability density function (PDF) of\n    a lognormal distribution with location parameter `μ` and scale parameter\n    `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.lognormal.pdf.factory( 4.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    ~0.014\n    > y = myPDF( 2.0 )\n    ~0.025","base.dists.lognormal.quantile":"\nbase.dists.lognormal.quantile( p, μ, σ )\n    Evaluates the quantile function for a lognormal distribution with location\n    parameter `μ` and scale parameter `σ` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.quantile( 0.8, 0.0, 1.0 )\n    ~2.32\n    > y = base.dists.lognormal.quantile( 0.5, 4.0, 2.0 )\n    ~54.598\n    > y = base.dists.lognormal.quantile( 1.1, 0.0, 1.0 )\n    NaN\n    > y = base.dists.lognormal.quantile( -0.2, 0.0, 1.0 )\n    NaN\n\n    > y = base.dists.lognormal.quantile( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.lognormal.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.quantile( 0.0, 0.0, NaN )\n    NaN\n\n    // Non-positive scale parameter `σ`:\n    > y = base.dists.lognormal.quantile( 0.5, 0.0, -1.0 )\n    NaN\n    > y = base.dists.lognormal.quantile( 0.5, 0.0, 0.0 )\n    NaN\n\n\nbase.dists.lognormal.quantile.factory( μ, σ )\n    Returns a function for evaluating the quantile function of a lognormal\n    distribution with location parameter `μ` and scale parameter `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.lognormal.quantile.factory( 4.0, 2.0 );\n    > var y = myQuantile( 0.2 )\n    ~10.143\n    > y = myQuantile( 0.8 )\n    ~293.901\n\n","base.dists.lognormal.quantile.factory":"\nbase.dists.lognormal.quantile.factory( μ, σ )\n    Returns a function for evaluating the quantile function of a lognormal\n    distribution with location parameter `μ` and scale parameter `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.lognormal.quantile.factory( 4.0, 2.0 );\n    > var y = myQuantile( 0.2 )\n    ~10.143\n    > y = myQuantile( 0.8 )\n    ~293.901","base.dists.lognormal.skewness":"\nbase.dists.lognormal.skewness( μ, σ )\n    Returns the skewness of a lognormal distribution with location `μ` and scale\n    `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.skewness( 0.0, 1.0 )\n    ~6.185\n    > y = base.dists.lognormal.skewness( 5.0, 2.0 )\n    ~414.359\n    > y = base.dists.lognormal.skewness( NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.skewness( 0.0, NaN )\n    NaN\n    > y = base.dists.lognormal.skewness( 0.0, 0.0 )\n    NaN\n\n","base.dists.lognormal.stdev":"\nbase.dists.lognormal.stdev( μ, σ )\n    Returns the standard deviation of a lognormal distribution with location `μ`\n    and scale `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.stdev( 0.0, 1.0 )\n    ~2.161\n    > y = base.dists.lognormal.stdev( 4.0, 2.0 )\n    ~2953.533\n    > y = base.dists.lognormal.stdev( NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.stdev( 0.0, NaN )\n    NaN\n    > y = base.dists.lognormal.stdev( 0.0, 0.0 )\n    NaN\n\n","base.dists.lognormal.variance":"\nbase.dists.lognormal.variance( μ, σ )\n    Returns the variance of a lognormal distribution with location `μ` and scale\n    `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.variance( 0.0, 1.0 )\n    ~4.671\n    > y = base.dists.lognormal.variance( 4.0, 2.0 )\n    ~8723355.729\n    > y = base.dists.lognormal.variance( NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.variance( 0.0, NaN )\n    NaN\n    > y = base.dists.lognormal.variance( 0.0, 0.0 )\n    NaN\n\n","base.dists.negativeBinomial.cdf":"\nbase.dists.negativeBinomial.cdf( x, r, p )\n    Evaluates the cumulative distribution function (CDF) for a negative binomial\n    distribution with number of successes until experiment is stopped `r` and\n    success probability `p` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a `r` which is not a positive number, the function returns\n    `NaN`.\n\n    If provided a success probability `p` outside of `[0,1]`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.negativeBinomial.cdf( 5.0, 20.0, 0.8 )\n    ~0.617\n    > y = base.dists.negativeBinomial.cdf( 21.0, 20.0, 0.5 )\n    ~0.622\n    > y = base.dists.negativeBinomial.cdf( 5.0, 10.0, 0.4 )\n    ~0.034\n    > y = base.dists.negativeBinomial.cdf( 0.0, 10.0, 0.9 )\n    ~0.349\n    > y = base.dists.negativeBinomial.cdf( 21.0, 15.5, 0.5 )\n    ~0.859\n    > y = base.dists.negativeBinomial.cdf( 5.0, 7.4, 0.4 )\n    ~0.131\n\n    > y = base.dists.negativeBinomial.cdf( 2.0, 0.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.cdf( 2.0, -2.0, 0.5 )\n    NaN\n\n    > y = base.dists.negativeBinomial.cdf( NaN, 20.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.cdf( 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.cdf( 0.0, 20.0, NaN )\n    NaN\n\n    > y = base.dists.negativeBinomial.cdf( 2.0, 20, -1.0 )\n    NaN\n    > y = base.dists.negativeBinomial.cdf( 2.0, 20, 1.5 )\n    NaN\n\n\nbase.dists.negativeBinomial.cdf.factory( r, p )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a negative binomial distribution with number of successes until\n    experiment is stopped `r` and success probability `p`.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.negativeBinomial.cdf.factory( 10, 0.5 );\n    > var y = myCDF( 3.0 )\n    ~0.046\n    > y = myCDF( 11.0 )\n    ~0.668\n\n","base.dists.negativeBinomial.cdf.factory":"\nbase.dists.negativeBinomial.cdf.factory( r, p )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a negative binomial distribution with number of successes until\n    experiment is stopped `r` and success probability `p`.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.negativeBinomial.cdf.factory( 10, 0.5 );\n    > var y = myCDF( 3.0 )\n    ~0.046\n    > y = myCDF( 11.0 )\n    ~0.668","base.dists.negativeBinomial.kurtosis":"\nbase.dists.negativeBinomial.kurtosis( r, p )\n    Returns the excess kurtosis of a negative binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a `r` which is not a positive number, the function returns\n    `NaN`.\n\n    If provided a success probability `p` outside of `[0,1]`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    r: integer\n        Number of failures until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.negativeBinomial.kurtosis( 100, 0.2 )\n    ~0.061\n    > v = base.dists.negativeBinomial.kurtosis( 20, 0.5 )\n    ~0.325\n\n","base.dists.negativeBinomial.logpmf":"\nbase.dists.negativeBinomial.logpmf( x, r, p )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    negative binomial distribution with number of successes until experiment is\n    stopped `r` and success probability `p` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a `r` which is not a positive number, the function returns\n    `NaN`.\n\n    If provided a success probability `p` outside of `[0,1]`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPMF.\n\n    Examples\n    --------\n    > var y = base.dists.negativeBinomial.logpmf( 5.0, 20.0, 0.8 )\n    ~-1.853\n    > y = base.dists.negativeBinomial.logpmf( 21.0, 20.0, 0.5 )\n    ~-2.818\n    > y = base.dists.negativeBinomial.logpmf( 5.0, 10.0, 0.4 )\n    ~-4.115\n    > y = base.dists.negativeBinomial.logpmf( 0.0, 10.0, 0.9 )\n    ~-1.054\n    > y = base.dists.negativeBinomial.logpmf( 21.0, 15.5, 0.5 )\n    ~-3.292\n    > y = base.dists.negativeBinomial.logpmf( 5.0, 7.4, 0.4 )\n    ~-2.976\n\n    > y = base.dists.negativeBinomial.logpmf( 2.0, 0.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.logpmf( 2.0, -2.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.logpmf( 2.0, 20, -1.0 )\n    NaN\n    > y = base.dists.negativeBinomial.logpmf( 2.0, 20, 1.5 )\n    NaN\n\n    > y = base.dists.negativeBinomial.logpmf( NaN, 20.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.logpmf( 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.logpmf( 0.0, 20.0, NaN )\n    NaN\n\n\nbase.dists.negativeBinomial.logpmf.factory( r, p )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a negative binomial distribution with number of\n    successes until experiment is stopped `r` and success probability `p`.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogPMF = base.dists.negativeBinomial.logpmf.factory( 10, 0.5 );\n    > var y = mylogPMF( 3.0 )\n    ~-3.617\n    > y = mylogPMF( 5.0 )\n    ~-2.795\n\n","base.dists.negativeBinomial.logpmf.factory":"\nbase.dists.negativeBinomial.logpmf.factory( r, p )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a negative binomial distribution with number of\n    successes until experiment is stopped `r` and success probability `p`.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogPMF = base.dists.negativeBinomial.logpmf.factory( 10, 0.5 );\n    > var y = mylogPMF( 3.0 )\n    ~-3.617\n    > y = mylogPMF( 5.0 )\n    ~-2.795","base.dists.negativeBinomial.mean":"\nbase.dists.negativeBinomial.mean( r, p )\n    Returns the expected value of a negative binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a `r` which is not a positive number, the function returns\n    `NaN`.\n\n    If provided a success probability `p` outside of `[0,1]`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    r: integer\n        Number of failures until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.negativeBinomial.mean( 100, 0.2 )\n    400\n    > v = base.dists.negativeBinomial.mean( 20, 0.5 )\n    20\n\n","base.dists.negativeBinomial.mgf":"\nbase.dists.negativeBinomial.mgf( x, r, p )\n    Evaluates the moment-generating function (MGF) for a negative binomial\n    distribution with number of successes until experiment is stopped `r` and\n    success probability `p` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a `r` which is not a positive number, the function returns\n    `NaN`.\n\n    If provided a success probability `p` outside of `[0,1]`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.negativeBinomial.mgf( 0.05, 20.0, 0.8 )\n    ~267.839\n    > y = base.dists.negativeBinomial.mgf( 0.1, 20.0, 0.1 )\n    ~9.347\n    > y = base.dists.negativeBinomial.mgf( 0.5, 10.0, 0.4 )\n    ~42822.023\n\n    > y = base.dists.negativeBinomial.mgf( 0.1, 0.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.mgf( 0.1, -2.0, 0.5 )\n    NaN\n\n    > y = base.dists.negativeBinomial.mgf( NaN, 20.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.mgf( 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.mgf( 0.0, 20.0, NaN )\n    NaN\n\n    > y = base.dists.negativeBinomial.mgf( 0.2, 20, -1.0 )\n    NaN\n    > y = base.dists.negativeBinomial.mgf( 0.2, 20, 1.5 )\n    NaN\n\n\nbase.dists.negativeBinomial.mgf.factory( r, p )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    negative binomial distribution with number of successes until experiment is\n    stopped `r` and success probability `p`.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.negativeBinomial.mgf.factory( 4.3, 0.4 );\n    > var y = myMGF( 0.2 )\n    ~4.696\n    > y = myMGF( 0.4 )\n    ~30.83\n\n","base.dists.negativeBinomial.mgf.factory":"\nbase.dists.negativeBinomial.mgf.factory( r, p )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    negative binomial distribution with number of successes until experiment is\n    stopped `r` and success probability `p`.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.negativeBinomial.mgf.factory( 4.3, 0.4 );\n    > var y = myMGF( 0.2 )\n    ~4.696\n    > y = myMGF( 0.4 )\n    ~30.83","base.dists.negativeBinomial.mode":"\nbase.dists.negativeBinomial.mode( r, p )\n    Returns the mode of a negative binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a `r` which is not a positive number, the function returns\n    `NaN`.\n\n    If provided a success probability `p` outside of `[0,1]`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    r: integer\n        Number of failures until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.negativeBinomial.mode( 100, 0.2 )\n    396\n    > v = base.dists.negativeBinomial.mode( 20, 0.5 )\n    19\n\n","base.dists.negativeBinomial.NegativeBinomial":"\nbase.dists.negativeBinomial.NegativeBinomial( [r, p] )\n    Returns a negative binomial distribution object.\n\n    Parameters\n    ----------\n    r: number (optional)\n        Number of successes until experiment is stopped. Must be a positive\n        number. Default: `1`.\n\n    p: number (optional)\n        Success probability. Must be a number between `0` and `1`. Default:\n        `0.5`.\n\n    Returns\n    -------\n    nbinomial: Object\n        Distribution instance.\n\n    nbinomial.r: number\n        Number of trials. If set, the value must be a positive number.\n\n    nbinomial.p: number\n        Success probability. If set, the value must be a number between `0` and\n        `1`.\n\n    nbinomial.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    nbinomial.mean: number\n        Read-only property which returns the expected value.\n\n    nbinomial.mode: number\n        Read-only property which returns the mode.\n\n    nbinomial.skewness: number\n        Read-only property which returns the skewness.\n\n    nbinomial.stdev: number\n        Read-only property which returns the standard deviation.\n\n    nbinomial.variance: number\n        Read-only property which returns the variance.\n\n    nbinomial.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    nbinomial.logpmf: Function\n        Evaluates the natural logarithm of the probability mass function (PMF).\n\n    nbinomial.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    nbinomial.pmf: Function\n        Evaluates the probability mass function (PMF).\n\n    nbinomial.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var nbinomial = base.dists.negativeBinomial.NegativeBinomial( 8.0, 0.5 );\n    > nbinomial.r\n    8.0\n    > nbinomial.p\n    0.5\n    > nbinomial.kurtosis\n    0.8125\n    > nbinomial.mean\n    8.0\n    > nbinomial.mode\n    7.0\n    > nbinomial.skewness\n    0.75\n    > nbinomial.stdev\n    4.0\n    > nbinomial.variance\n    16.0\n    > nbinomial.cdf( 2.9 )\n    ~0.055\n    > nbinomial.logpmf( 3.0 )\n    ~-2.837\n    > nbinomial.mgf( 0.2 )\n    ~36.675\n    > nbinomial.pmf( 3.0 )\n    ~0.059\n    > nbinomial.quantile( 0.8 )\n    11.0\n\n","base.dists.negativeBinomial.pmf":"\nbase.dists.negativeBinomial.pmf( x, r, p )\n    Evaluates the probability mass function (PMF) for a negative binomial\n    distribution with number of successes until experiment is stopped `r` and\n    success probability `p` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a `r` which is not a positive number, the function returns\n    `NaN`.\n\n    If provided a success probability `p` outside of `[0,1]`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated PMF.\n\n    Examples\n    --------\n    > var y = base.dists.negativeBinomial.pmf( 5.0, 20.0, 0.8 )\n    ~0.157\n    > y = base.dists.negativeBinomial.pmf( 21.0, 20.0, 0.5 )\n    ~0.06\n    > y = base.dists.negativeBinomial.pmf( 5.0, 10.0, 0.4 )\n    ~0.016\n    > y = base.dists.negativeBinomial.pmf( 0.0, 10.0, 0.9 )\n    ~0.349\n    > y = base.dists.negativeBinomial.pmf( 21.0, 15.5, 0.5 )\n    ~0.037\n    > y = base.dists.negativeBinomial.pmf( 5.0, 7.4, 0.4 )\n    ~0.051\n\n    > y = base.dists.negativeBinomial.pmf( 2.0, 0.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.pmf( 2.0, -2.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.pmf( 2.0, 20, -1.0 )\n    NaN\n    > y = base.dists.negativeBinomial.pmf( 2.0, 20, 1.5 )\n    NaN\n\n    > y = base.dists.negativeBinomial.pmf( NaN, 20.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.pmf( 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.pmf( 0.0, 20.0, NaN )\n    NaN\n\n\nbase.dists.negativeBinomial.pmf.factory( r, p )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    negative binomial distribution with number of successes until experiment is\n    stopped `r` and success probability `p`.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var myPMF = base.dists.negativeBinomial.pmf.factory( 10, 0.5 );\n    > var y = myPMF( 3.0 )\n    ~0.027\n    > y = myPMF( 5.0 )\n    ~0.061\n\n","base.dists.negativeBinomial.pmf.factory":"\nbase.dists.negativeBinomial.pmf.factory( r, p )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    negative binomial distribution with number of successes until experiment is\n    stopped `r` and success probability `p`.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var myPMF = base.dists.negativeBinomial.pmf.factory( 10, 0.5 );\n    > var y = myPMF( 3.0 )\n    ~0.027\n    > y = myPMF( 5.0 )\n    ~0.061","base.dists.negativeBinomial.quantile":"\nbase.dists.negativeBinomial.quantile( k, r, p )\n    Evaluates the quantile function for a negative binomial distribution with\n    number of successes until experiment is stopped `r` and success probability\n    `p` at a probability `k`.\n\n    If provided a `k` outside of `[0,1]`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a `r` which is not a positive number, the function returns\n    `NaN`.\n\n    If provided a success probability `p` outside of `[0,1]`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Input probability.\n\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.2 )\n    106\n    > y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.8 )\n    8\n    > y = base.dists.negativeBinomial.quantile( 0.5, 10.0, 0.4 )\n    14\n    > y = base.dists.negativeBinomial.quantile( 0.0, 10.0, 0.9 )\n    0\n\n    > y = base.dists.negativeBinomial.quantile( 1.1, 20.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.quantile( -0.1, 20.0, 0.5 )\n    NaN\n\n    > y = base.dists.negativeBinomial.quantile( 21.0, 15.5, 0.5 )\n    12\n    > y = base.dists.negativeBinomial.quantile( 5.0, 7.4, 0.4 )\n    10\n\n    > y = base.dists.negativeBinomial.quantile( 0.5, 0.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.quantile( 0.5, -2.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, -1.0 )\n    NaN\n    > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, 1.5 )\n    NaN\n\n    > y = base.dists.negativeBinomial.quantile( NaN, 20.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.quantile( 0.3, NaN, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, NaN )\n    NaN\n\n\nbase.dists.negativeBinomial.quantile.factory( r, p )\n    Returns a function for evaluating the quantile function of a negative\n    binomial distribution with number of successes until experiment is stopped\n    `r` and success probability `p`.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.negativeBinomial.quantile.factory( 10.0, 0.5 );\n    > var y = myQuantile( 0.1 )\n    5\n    > y = myQuantile( 0.9 )\n    16\n\n","base.dists.negativeBinomial.quantile.factory":"\nbase.dists.negativeBinomial.quantile.factory( r, p )\n    Returns a function for evaluating the quantile function of a negative\n    binomial distribution with number of successes until experiment is stopped\n    `r` and success probability `p`.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.negativeBinomial.quantile.factory( 10.0, 0.5 );\n    > var y = myQuantile( 0.1 )\n    5\n    > y = myQuantile( 0.9 )\n    16","base.dists.negativeBinomial.skewness":"\nbase.dists.negativeBinomial.skewness( r, p )\n    Returns the skewness of a negative binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a `r` which is not a positive number, the function returns\n    `NaN`.\n\n    If provided a success probability `p` outside of `[0,1]`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    r: integer\n        Number of failures until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.negativeBinomial.skewness( 100, 0.2 )\n    ~0.201\n    > v = base.dists.negativeBinomial.skewness( 20, 0.5 )\n    ~0.474\n\n","base.dists.negativeBinomial.stdev":"\nbase.dists.negativeBinomial.stdev( r, p )\n    Returns the standard deviation of a negative binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a `r` which is not a positive number, the function returns\n    `NaN`.\n\n    If provided a success probability `p` outside of `[0,1]`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    r: integer\n        Number of failures until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.negativeBinomial.stdev( 100, 0.2 )\n    ~44.721\n    > v = base.dists.negativeBinomial.stdev( 20, 0.5 )\n    ~6.325\n\n","base.dists.negativeBinomial.variance":"\nbase.dists.negativeBinomial.variance( r, p )\n    Returns the variance of a negative binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a `r` which is not a positive number, the function returns\n    `NaN`.\n\n    If provided a success probability `p` outside of `[0,1]`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    r: integer\n        Number of failures until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.negativeBinomial.variance( 100, 0.2 )\n    2000.0\n    > v = base.dists.negativeBinomial.variance( 20, 0.5 )\n    40.0\n\n","base.dists.normal.cdf":"\nbase.dists.normal.cdf( x, μ, σ )\n    Evaluates the cumulative distribution function (CDF) for a normal\n    distribution with mean `μ` and standard deviation `σ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.normal.cdf( 2.0, 0.0, 1.0 )\n    ~0.977\n    > y = base.dists.normal.cdf( -1.0, -1.0, 2.0 )\n    0.5\n    > y = base.dists.normal.cdf( -1.0, 4.0, 2.0 )\n    ~0.006\n    > y = base.dists.normal.cdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.normal.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.cdf( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative standard deviation:\n    > y = base.dists.normal.cdf( 2.0, 0.0, -1.0 )\n    NaN\n\n    // Degenerate distribution centered at `μ` when `σ = 0.0`:\n    > y = base.dists.normal.cdf( 2.0, 8.0, 0.0 )\n    0.0\n    > y = base.dists.normal.cdf( 8.0, 8.0, 0.0 )\n    1.0\n    > y = base.dists.normal.cdf( 10.0, 8.0, 0.0 )\n    1.0\n\n\nbase.dists.normal.cdf.factory( μ, σ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a normal distribution with mean `μ` and standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.normal.cdf.factory( 10.0, 2.0 );\n    > var y = myCDF( 10.0 )\n    0.5\n\n","base.dists.normal.cdf.factory":"\nbase.dists.normal.cdf.factory( μ, σ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a normal distribution with mean `μ` and standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.normal.cdf.factory( 10.0, 2.0 );\n    > var y = myCDF( 10.0 )\n    0.5","base.dists.normal.entropy":"\nbase.dists.normal.entropy( μ, σ )\n    Returns the differential entropy of a normal distribution with mean `μ` and\n    standard deviation `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var y = base.dists.normal.entropy( 0.0, 1.0 )\n    ~1.419\n    > y = base.dists.normal.entropy( 4.0, 3.0 )\n    ~2.518\n    > y = base.dists.normal.entropy( NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.entropy( 0.0, NaN )\n    NaN\n    > y = base.dists.normal.entropy( 0.0, 0.0 )\n    NaN\n\n","base.dists.normal.kurtosis":"\nbase.dists.normal.kurtosis( μ, σ )\n    Returns the excess kurtosis of a normal distribution with mean `μ` and\n    standard deviation `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var y = base.dists.normal.kurtosis( 0.0, 1.0 )\n    0.0\n    > y = base.dists.normal.kurtosis( 4.0, 3.0 )\n    0.0\n    > y = base.dists.normal.kurtosis( NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.kurtosis( 0.0, NaN )\n    NaN\n    > y = base.dists.normal.kurtosis( 0.0, 0.0 )\n    NaN\n\n","base.dists.normal.logcdf":"\nbase.dists.normal.logcdf( x, μ, σ )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a normal distribution with mean `μ` and standard deviation `σ` at\n    a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Evaluated logcdf.\n\n    Examples\n    --------\n    > var y = base.dists.normal.logcdf( 2.0, 0.0, 1.0 )\n    ~-0.023\n    > y = base.dists.normal.logcdf( -1.0, 4.0, 2.0 )\n    ~-5.082\n    > y = base.dists.normal.logcdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.normal.logcdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.logcdf( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative standard deviation:\n    > y = base.dists.normal.logcdf( 2.0, 0.0, -1.0 )\n    NaN\n\n    // Degenerate distribution centered at `μ` when `σ = 0.0`:\n    > y = base.dists.normal.logcdf( 2.0, 8.0, 0.0 )\n    -Infinity\n    > y = base.dists.normal.logcdf( 8.0, 8.0, 0.0 )\n    0.0\n\n\nbase.dists.normal.logcdf.factory( μ, σ )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a normal distribution with mean `μ` and\n    standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.normal.logcdf.factory( 10.0, 2.0 );\n    > var y = mylogcdf( 10.0 )\n    ~-0.693\n\n","base.dists.normal.logcdf.factory":"\nbase.dists.normal.logcdf.factory( μ, σ )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a normal distribution with mean `μ` and\n    standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.normal.logcdf.factory( 10.0, 2.0 );\n    > var y = mylogcdf( 10.0 )\n    ~-0.693","base.dists.normal.logpdf":"\nbase.dists.normal.logpdf( x, μ, σ )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a normal distribution with mean `μ` and standard deviation `σ` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.normal.logpdf( 2.0, 0.0, 1.0 )\n    ~-2.919\n    > y = base.dists.normal.logpdf( -1.0, 4.0, 2.0 )\n    ~-4.737\n    > y = base.dists.normal.logpdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.normal.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.logpdf( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative standard deviation:\n    > y = base.dists.normal.logpdf( 2.0, 0.0, -1.0 )\n    NaN\n\n    // Degenerate distribution centered at `μ` when `σ = 0.0`:\n    > y = base.dists.normal.logpdf( 2.0, 8.0, 0.0 )\n    -Infinity\n    > y = base.dists.normal.logpdf( 8.0, 8.0, 0.0 )\n    Infinity\n\n\nbase.dists.normal.logpdf.factory( μ, σ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a normal distribution with mean `μ` and standard\n    deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var myLogPDF = base.dists.normal.logpdf.factory( 10.0, 2.0 );\n    > var y = myLogPDF( 10.0 )\n    ~-1.612\n\n","base.dists.normal.logpdf.factory":"\nbase.dists.normal.logpdf.factory( μ, σ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a normal distribution with mean `μ` and standard\n    deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var myLogPDF = base.dists.normal.logpdf.factory( 10.0, 2.0 );\n    > var y = myLogPDF( 10.0 )\n    ~-1.612","base.dists.normal.mean":"\nbase.dists.normal.mean( μ, σ )\n    Returns the expected value of a normal distribution with mean `μ` and\n    standard deviation `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var y = base.dists.normal.mean( 0.0, 1.0 )\n    0.0\n    > y = base.dists.normal.mean( 4.0, 2.0 )\n    4.0\n    > y = base.dists.normal.mean( NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.mean( 0.0, NaN )\n    NaN\n    > y = base.dists.normal.mean( 0.0, 0.0 )\n    NaN\n\n","base.dists.normal.median":"\nbase.dists.normal.median( μ, σ )\n    Returns the median of a normal distribution with mean `μ` and standard\n    deviation `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var y = base.dists.normal.median( 0.0, 1.0 )\n    0.0\n    > y = base.dists.normal.median( 4.0, 2.0 )\n    4.0\n    > y = base.dists.normal.median( NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.median( 0.0, NaN )\n    NaN\n    > y = base.dists.normal.median( 0.0, 0.0 )\n    NaN\n\n","base.dists.normal.mgf":"\nbase.dists.normal.mgf( x, μ, σ )\n    Evaluates the moment-generating function (MGF) for a normal distribution\n    with mean `μ` and standard deviation `σ` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.normal.mgf( 2.0, 0.0, 1.0 )\n    ~7.389\n    > y = base.dists.normal.mgf( 0.0, 0.0, 1.0 )\n    1.0\n    > y = base.dists.normal.mgf( -1.0, 4.0, 2.0 )\n    ~0.1353\n    > y = base.dists.normal.mgf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.normal.mgf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.mgf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.normal.mgf( 2.0, 0.0, 0.0 )\n    NaN\n\n\nbase.dists.normal.mgf.factory( μ, σ )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    normal distribution with mean `μ` and standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.normal.mgf.factory( 4.0, 2.0 );\n    > var y = myMGF( 1.0 )\n    ~403.429\n    > y = myMGF( 0.5 )\n    ~12.182\n\n","base.dists.normal.mgf.factory":"\nbase.dists.normal.mgf.factory( μ, σ )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    normal distribution with mean `μ` and standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.normal.mgf.factory( 4.0, 2.0 );\n    > var y = myMGF( 1.0 )\n    ~403.429\n    > y = myMGF( 0.5 )\n    ~12.182","base.dists.normal.mode":"\nbase.dists.normal.mode( μ, σ )\n    Returns the mode of a normal distribution with mean `μ` and standard\n    deviation `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var y = base.dists.normal.mode( 0.0, 1.0 )\n    0.0\n    > y = base.dists.normal.mode( 4.0, 2.0 )\n    4.0\n    > y = base.dists.normal.mode( NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.mode( 0.0, NaN )\n    NaN\n    > y = base.dists.normal.mode( 0.0, 0.0 )\n    NaN\n\n","base.dists.normal.Normal":"\nbase.dists.normal.Normal( [μ, σ] )\n    Returns a normal distribution object.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean parameter. Default: `0.0`.\n\n    σ: number (optional)\n        Standard deviation. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    normal: Object\n        Distribution instance.\n\n    normal.mu: number\n        Mean parameter.\n\n    normal.sigma: number\n        Standard deviation. If set, the value must be greater than `0`.\n\n    normal.entropy: number\n        Read-only property which returns the differential entropy.\n\n    normal.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    normal.mean: number\n        Read-only property which returns the expected value.\n\n    normal.median: number\n        Read-only property which returns the median.\n\n    normal.mode: number\n        Read-only property which returns the mode.\n\n    normal.skewness: number\n        Read-only property which returns the skewness.\n\n    normal.stdev: number\n        Read-only property which returns the standard deviation.\n\n    normal.variance: number\n        Read-only property which returns the variance.\n\n    normal.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    normal.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    normal.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    normal.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    normal.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    normal.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var normal = base.dists.normal.Normal( -2.0, 3.0 );\n    > normal.mu\n    -2.0\n    > normal.sigma\n    3.0\n    > normal.entropy\n    ~2.518\n    > normal.kurtosis\n    0.0\n    > normal.mean\n    -2.0\n    > normal.median\n    -2.0\n    > normal.mode\n    -2.0\n    > normal.skewness\n    0.0\n    > normal.stdev\n    3.0\n    > normal.variance\n    9.0\n    > normal.cdf( 0.8 )\n    ~0.825\n    > normal.logcdf( 0.8 )\n    ~-0.193\n    > normal.logpdf( 2.0 )\n    ~-2.9\n    > normal.mgf( 0.2 )\n    ~0.803\n    > normal.pdf( 2.0 )\n    ~0.055\n    > normal.quantile( 0.9 )\n    ~1.845\n\n","base.dists.normal.pdf":"\nbase.dists.normal.pdf( x, μ, σ )\n    Evaluates the probability density function (PDF) for a normal distribution\n    with mean `μ` and standard deviation `σ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.normal.pdf( 2.0, 0.0, 1.0 )\n    ~0.054\n    > y = base.dists.normal.pdf( -1.0, 4.0, 2.0 )\n    ~0.009\n    > y = base.dists.normal.pdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.normal.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.pdf( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative standard deviation:\n    > y = base.dists.normal.pdf( 2.0, 0.0, -1.0 )\n    NaN\n\n    // Degenerate distribution centered at `μ` when `σ = 0.0`:\n    > y = base.dists.normal.pdf( 2.0, 8.0, 0.0 )\n    0.0\n    > y = base.dists.normal.pdf( 8.0, 8.0, 0.0 )\n    infinity\n\n\nbase.dists.normal.pdf.factory( μ, σ )\n    Returns a function for evaluating the probability density function (PDF) of\n    a normal distribution with mean `μ` and standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.normal.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    ~0.199\n\n","base.dists.normal.pdf.factory":"\nbase.dists.normal.pdf.factory( μ, σ )\n    Returns a function for evaluating the probability density function (PDF) of\n    a normal distribution with mean `μ` and standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.normal.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    ~0.199","base.dists.normal.quantile":"\nbase.dists.normal.quantile( p, μ, σ )\n    Evaluates the quantile function for a normal distribution with mean `μ` and\n    standard deviation `σ` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.normal.quantile( 0.8, 0.0, 1.0 )\n    ~0.842\n    > y = base.dists.normal.quantile( 0.5, 4.0, 2.0 )\n    4\n\n    > y = base.dists.normal.quantile( 1.1, 0.0, 1.0 )\n    NaN\n    > y = base.dists.normal.quantile( -0.2, 0.0, 1.0 )\n    NaN\n\n    > y = base.dists.normal.quantile( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.normal.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.quantile( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative standard deviation:\n    > y = base.dists.normal.quantile( 0.5, 0.0, -1.0 )\n    NaN\n\n    // Degenerate distribution centered at `μ` when `σ = 0.0`:\n    > y = base.dists.normal.quantile( 0.3, 8.0, 0.0 )\n    8.0\n    > y = base.dists.normal.quantile( 0.9, 8.0, 0.0 )\n    8.0\n\n\nbase.dists.normal.quantile.factory( μ, σ )\n    Returns a function for evaluating the quantile function\n    of a normal distribution with mean `μ` and standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.normal.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    10.0\n\n","base.dists.normal.quantile.factory":"\nbase.dists.normal.quantile.factory( μ, σ )\n    Returns a function for evaluating the quantile function\n    of a normal distribution with mean `μ` and standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.normal.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    10.0","base.dists.normal.skewness":"\nbase.dists.normal.skewness( μ, σ )\n    Returns the skewness of a normal distribution with mean `μ` and standard\n    deviation `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var y = base.dists.normal.skewness( 0.0, 1.0 )\n    0.0\n    > y = base.dists.normal.skewness( 4.0, 3.0 )\n    0.0\n    > y = base.dists.normal.skewness( NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.skewness( 0.0, NaN )\n    NaN\n    > y = base.dists.normal.skewness( 0.0, 0.0 )\n    NaN\n\n","base.dists.normal.stdev":"\nbase.dists.normal.stdev( μ, σ )\n    Returns the standard deviation of a normal distribution with mean `μ` and\n    standard deviation `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var y = base.dists.normal.stdev( 0.0, 1.0 )\n    1.0\n    > y = base.dists.normal.stdev( 4.0, 3.0 )\n    3.0\n    > y = base.dists.normal.stdev( NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.stdev( 0.0, NaN )\n    NaN\n    > y = base.dists.normal.stdev( 0.0, 0.0 )\n    NaN\n\n","base.dists.normal.variance":"\nbase.dists.normal.variance( μ, σ )\n    Returns the variance of a normal distribution with mean `μ` and standard\n    deviation `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var y = base.dists.normal.variance( 0.0, 1.0 )\n    1.0\n    > y = base.dists.normal.variance( 4.0, 3.0 )\n    9.0\n    > y = base.dists.normal.variance( NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.variance( 0.0, NaN )\n    NaN\n    > y = base.dists.normal.variance( 0.0, 0.0 )\n    NaN\n\n","base.dists.pareto1.cdf":"\nbase.dists.pareto1.cdf( x, α, β )\n    Evaluates the cumulative distribution function (CDF) for a Pareto (Type I)\n    distribution with shape parameter `α` and scale parameter `β` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.pareto1.cdf( 2.0, 1.0, 1.0 )\n    0.5\n    > y = base.dists.pareto1.cdf( 5.0, 2.0, 4.0 )\n    ~0.36\n    > y = base.dists.pareto1.cdf( 4.0, 2.0, 2.0 )\n    0.75\n    > y = base.dists.pareto1.cdf( 1.9, 2.0, 2.0 )\n    0.0\n    > y = base.dists.pareto1.cdf( PINF, 4.0, 2.0 )\n    1.0\n\n    > y = base.dists.pareto1.cdf( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.pareto1.cdf( 2.0, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.pareto1.cdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.pareto1.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.pareto1.cdf( 0.0, 1.0, NaN )\n    NaN\n\n\nbase.dists.pareto1.cdf.factory( α, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Pareto (Type I) distribution with shape parameter `α` and scale\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.pareto1.cdf.factory( 10.0, 2.0 );\n    > var y = myCDF( 3.0 )\n    ~0.983\n    > y = myCDF( 2.5 )\n    ~0.893\n\n","base.dists.pareto1.cdf.factory":"\nbase.dists.pareto1.cdf.factory( α, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Pareto (Type I) distribution with shape parameter `α` and scale\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.pareto1.cdf.factory( 10.0, 2.0 );\n    > var y = myCDF( 3.0 )\n    ~0.983\n    > y = myCDF( 2.5 )\n    ~0.893","base.dists.pareto1.entropy":"\nbase.dists.pareto1.entropy( α, β )\n    Returns the differential entropy of a Pareto (Type I) distribution\n    (in nats).\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Differential entropy.\n\n    Examples\n    --------\n    > var v = base.dists.pareto1.entropy( 0.8, 1.0 )\n    ~2.473\n    > v = base.dists.pareto1.entropy( 4.0, 12.0 )\n    ~2.349\n    > v = base.dists.pareto1.entropy( 8.0, 2.0 )\n    ~-0.261\n\n","base.dists.pareto1.kurtosis":"\nbase.dists.pareto1.kurtosis( α, β )\n    Returns the excess kurtosis of a Pareto (Type I) distribution.\n\n    If `α <= 4` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.pareto1.kurtosis( 5.0, 1.0 )\n    ~70.8\n    > v = base.dists.pareto1.kurtosis( 4.5, 12.0 )\n    ~146.444\n    > v = base.dists.pareto1.kurtosis( 8.0, 2.0 )\n    ~19.725\n\n","base.dists.pareto1.logcdf":"\nbase.dists.pareto1.logcdf( x, α, β )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a Pareto (Type I) distribution with shape parameter `α` and scale\n    parameter `β` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.pareto1.logcdf( 2.0, 1.0, 1.0 )\n    ~-0.693\n    > y = base.dists.pareto1.logcdf( 5.0, 2.0, 4.0 )\n    ~-1.022\n    > y = base.dists.pareto1.logcdf( 4.0, 2.0, 2.0 )\n    ~-0.288\n    > y = base.dists.pareto1.logcdf( 1.9, 2.0, 2.0 )\n    -Infinity\n    > y = base.dists.pareto1.logcdf( PINF, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.pareto1.logcdf( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.pareto1.logcdf( 2.0, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.pareto1.logcdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.pareto1.logcdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.pareto1.logcdf( 0.0, 1.0, NaN )\n    NaN\n\n\nbase.dists.pareto1.logcdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Pareto (Type I) distribution with shape\n    parameter `α` and scale parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogCDF = base.dists.pareto1.logcdf.factory( 10.0, 2.0 );\n    > var y = mylogCDF( 3.0 )\n    ~-0.017\n    > y = mylogCDF( 2.5 )\n    ~-0.114\n\n","base.dists.pareto1.logcdf.factory":"\nbase.dists.pareto1.logcdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Pareto (Type I) distribution with shape\n    parameter `α` and scale parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogCDF = base.dists.pareto1.logcdf.factory( 10.0, 2.0 );\n    > var y = mylogCDF( 3.0 )\n    ~-0.017\n    > y = mylogCDF( 2.5 )\n    ~-0.114","base.dists.pareto1.logpdf":"\nbase.dists.pareto1.logpdf( x, α, β )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a Pareto (Type I) distribution with shape parameter `α` and scale\n    parameter `β` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.pareto1.logpdf( 4.0, 1.0, 1.0 )\n    ~-2.773\n    > y = base.dists.pareto1.logpdf( 20.0, 1.0, 10.0 )\n    ~-3.689\n    > y = base.dists.pareto1.logpdf( 7.0, 2.0, 6.0 )\n    ~-1.561\n    > y = base.dists.pareto1.logpdf( 7.0, 6.0, 3.0 )\n    ~-5.238\n    > y = base.dists.pareto1.logpdf( 1.0, 4.0, 2.0 )\n    -Infinity\n    > y = base.dists.pareto1.logpdf( 1.5, 4.0, 2.0 )\n    -Infinity\n\n    > y = base.dists.pareto1.logpdf( 0.5, -1.0, 0.5 )\n    NaN\n    > y = base.dists.pareto1.logpdf( 0.5, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.pareto1.logpdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.pareto1.logpdf( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.dists.pareto1.logpdf( 0.5, 1.0, NaN )\n    NaN\n\n\nbase.dists.pareto1.logpdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a Pareto (Type I) distribution with shape\n    parameter `α` and scale parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.pareto1.logpdf.factory( 0.5, 0.5 );\n    > var y = mylogPDF( 0.8 )\n    ~-0.705\n    > y = mylogPDF( 2.0 )\n    ~-2.079\n\n","base.dists.pareto1.logpdf.factory":"\nbase.dists.pareto1.logpdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a Pareto (Type I) distribution with shape\n    parameter `α` and scale parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.pareto1.logpdf.factory( 0.5, 0.5 );\n    > var y = mylogPDF( 0.8 )\n    ~-0.705\n    > y = mylogPDF( 2.0 )\n    ~-2.079","base.dists.pareto1.mean":"\nbase.dists.pareto1.mean( α, β )\n    Returns the expected value of a Pareto (Type I) distribution.\n\n    If `0 < α <= 1`, the function returns `Infinity`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.pareto1.mean( 0.8, 1.0 )\n    Infinity\n    > v = base.dists.pareto1.mean( 4.0, 12.0 )\n    16.0\n    > v = base.dists.pareto1.mean( 8.0, 2.0 )\n    ~2.286\n\n","base.dists.pareto1.median":"\nbase.dists.pareto1.median( α, β )\n    Returns the median of a Pareto (Type I) distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.pareto1.median( 0.8, 1.0 )\n    ~2.378\n    > v = base.dists.pareto1.median( 4.0, 12.0 )\n    ~14.27\n    > v = base.dists.pareto1.median( 8.0, 2.0 )\n    ~2.181\n\n","base.dists.pareto1.mode":"\nbase.dists.pareto1.mode( α, β )\n    Returns the mode of a Pareto (Type I) distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.pareto1.mode( 0.8, 1.0 )\n    1.0\n    > v = base.dists.pareto1.mode( 4.0, 12.0 )\n    12.0\n    > v = base.dists.pareto1.mode( 8.0, 2.0 )\n    2.0\n\n","base.dists.pareto1.Pareto1":"\nbase.dists.pareto1.Pareto1( [α, β] )\n    Returns a Pareto (Type I) distribution object.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n    β: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    pareto1: Object\n        Distribution instance.\n\n    pareto1.alpha: number\n        Shape parameter. If set, the value must be greater than `0`.\n\n    pareto1.beta: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    pareto1.entropy: number\n        Read-only property which returns the differential entropy.\n\n    pareto1.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    pareto1.mean: number\n        Read-only property which returns the expected value.\n\n    pareto1.median: number\n        Read-only property which returns the median.\n\n    pareto1.mode: number\n        Read-only property which returns the mode.\n\n    pareto1.skewness: number\n        Read-only property which returns the skewness.\n\n    pareto1.variance: number\n        Read-only property which returns the variance.\n\n    pareto1.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    pareto1.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (logCDF).\n\n    pareto1.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (logPDF).\n\n    pareto1.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    pareto1.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var pareto1 = base.dists.pareto1.Pareto1( 6.0, 5.0 );\n    > pareto1.alpha\n    6.0\n    > pareto1.beta\n    5.0\n    > pareto1.entropy\n    ~0.984\n    > pareto1.kurtosis\n    ~35.667\n    > pareto1.mean\n    6.0\n    > pareto1.median\n    ~5.612\n    > pareto1.mode\n    5.0\n    > pareto1.skewness\n    ~3.81\n    > pareto1.variance\n    1.5\n    > pareto1.cdf( 7.0 )\n    ~0.867\n    > pareto1.logcdf( 7.0 )\n    ~-0.142\n    > pareto1.logpdf( 5.0 )\n    ~0.182\n    > pareto1.pdf( 5.0 )\n    1.2\n    > pareto1.quantile( 0.8 )\n    ~6.538\n\n","base.dists.pareto1.pdf":"\nbase.dists.pareto1.pdf( x, α, β )\n    Evaluates the probability density function (PDF) for a Pareto (Type I)\n    distribution with shape parameter `α` and scale parameter `β` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.pareto1.pdf( 4.0, 1.0, 1.0 )\n    ~0.063\n    > y = base.dists.pareto1.pdf( 20.0, 1.0, 10.0 )\n    0.025\n    > y = base.dists.pareto1.pdf( 7.0, 2.0, 6.0 )\n    ~0.21\n    > y = base.dists.pareto1.pdf( 7.0, 6.0, 3.0 )\n    ~0.005\n    > y = base.dists.pareto1.pdf( 1.0, 4.0, 2.0 )\n    0.0\n    > y = base.dists.pareto1.pdf( 1.5, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.pareto1.pdf( 0.5, -1.0, 0.5 )\n    NaN\n    > y = base.dists.pareto1.pdf( 0.5, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.pareto1.pdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.pareto1.pdf( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.dists.pareto1.pdf( 0.5, 1.0, NaN )\n    NaN\n\n\nbase.dists.pareto1.pdf.factory( α, β )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Pareto (Type I) distribution with shape parameter `α` and scale parameter\n    `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.pareto1.pdf.factory( 0.5, 0.5 );\n    > var y = myPDF( 0.8 )\n    ~0.494\n    > y = myPDF( 2.0 )\n    ~0.125\n\n","base.dists.pareto1.pdf.factory":"\nbase.dists.pareto1.pdf.factory( α, β )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Pareto (Type I) distribution with shape parameter `α` and scale parameter\n    `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.pareto1.pdf.factory( 0.5, 0.5 );\n    > var y = myPDF( 0.8 )\n    ~0.494\n    > y = myPDF( 2.0 )\n    ~0.125","base.dists.pareto1.quantile":"\nbase.dists.pareto1.quantile( p, α, β )\n    Evaluates the quantile function for a Pareto (Type I) distribution with\n    shape parameter `α` and scale parameter `β` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.pareto1.quantile( 0.8, 2.0, 1.0 )\n    ~2.236\n    > y = base.dists.pareto1.quantile( 0.8, 1.0, 10.0 )\n    ~50.0\n    > y = base.dists.pareto1.quantile( 0.1, 1.0, 10.0 )\n    ~11.111\n\n    > y = base.dists.pareto1.quantile( 1.1, 1.0, 1.0 )\n    NaN\n    > y = base.dists.pareto1.quantile( -0.2, 1.0, 1.0 )\n    NaN\n\n    > y = base.dists.pareto1.quantile( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.pareto1.quantile( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.dists.pareto1.quantile( 0.5, 1.0, NaN )\n    NaN\n\n    > y = base.dists.pareto1.quantile( 0.5, -1.0, 1.0 )\n    NaN\n    > y = base.dists.pareto1.quantile( 0.5, 1.0, -1.0 )\n    NaN\n\n\nbase.dists.pareto1.quantile.factory( α, β )\n    Returns a function for evaluating the quantile function of a Pareto (Type I)\n    distribution with shape parameter `α` and scale parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.pareto1.quantile.factory( 2.5, 0.5 );\n    > var y = myQuantile( 0.5 )\n    ~0.66\n    > y = myQuantile( 0.8 )\n    ~0.952\n\n","base.dists.pareto1.quantile.factory":"\nbase.dists.pareto1.quantile.factory( α, β )\n    Returns a function for evaluating the quantile function of a Pareto (Type I)\n    distribution with shape parameter `α` and scale parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.pareto1.quantile.factory( 2.5, 0.5 );\n    > var y = myQuantile( 0.5 )\n    ~0.66\n    > y = myQuantile( 0.8 )\n    ~0.952","base.dists.pareto1.skewness":"\nbase.dists.pareto1.skewness( α, β )\n    Returns the skewness of a Pareto (Type I) distribution.\n\n    If `α <= 3` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.pareto1.skewness( 3.5, 1.0 )\n    ~11.784\n    > v = base.dists.pareto1.skewness( 4.0, 12.0 )\n    ~7.071\n    > v = base.dists.pareto1.skewness( 8.0, 2.0 )\n    ~3.118\n\n","base.dists.pareto1.stdev":"\nbase.dists.pareto1.stdev( α, β )\n    Returns the standard deviation of a Pareto (Type I) distribution.\n\n    If `0 < α <= 2` and `β > 0`, the function returns positive infinity.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.pareto1.stdev( 0.8, 1.0 )\n    Infinity\n    > v = base.dists.pareto1.stdev( 4.0, 12.0 )\n    ~5.657\n    > v = base.dists.pareto1.stdev( 8.0, 2.0 )\n    ~0.33\n\n","base.dists.pareto1.variance":"\nbase.dists.pareto1.variance( α, β )\n    Returns the variance of a Pareto (Type I) distribution.\n\n    If `0 < α <= 2` and `β > 0`, the function returns positive infinity.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.pareto1.variance( 0.8, 1.0 )\n    Infinity\n    > v = base.dists.pareto1.variance( 4.0, 12.0 )\n    32.0\n    > v = base.dists.pareto1.variance( 8.0, 2.0 )\n    ~0.109\n\n","base.dists.poisson.cdf":"\nbase.dists.poisson.cdf( x, λ )\n    Evaluates the cumulative distribution function (CDF) for a Poisson\n    distribution with mean parameter `λ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.poisson.cdf( 2.0, 0.5 )\n    ~0.986\n    > y = base.dists.poisson.cdf( 2.0, 10.0 )\n    ~0.003\n    > y = base.dists.poisson.cdf( -1.0, 4.0 )\n    0.0\n    > y = base.dists.poisson.cdf( NaN, 1.0 )\n    NaN\n    > y = base.dists.poisson.cdf( 0.0, NaN )\n    NaN\n\n    // Negative mean parameter:\n    > y = base.dists.poisson.cdf( 2.0, -1.0 )\n    NaN\n\n    // Degenerate distribution at `λ = 0`:\n    > y = base.dists.poisson.cdf( -2.0, 0.0 )\n    0.0\n    > y = base.dists.poisson.cdf( 0.0, 0.0 )\n    1.0\n    > y = base.dists.poisson.cdf( 10.0, 0.0 )\n    1.0\n\n\nbase.dists.poisson.cdf.factory( λ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Poisson distribution with mean parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.poisson.cdf.factory( 5.0 );\n    > var y = mycdf( 3.0 )\n    ~0.265\n    > y = mycdf( 8.0 )\n    ~0.932\n\n","base.dists.poisson.cdf.factory":"\nbase.dists.poisson.cdf.factory( λ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Poisson distribution with mean parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.poisson.cdf.factory( 5.0 );\n    > var y = mycdf( 3.0 )\n    ~0.265\n    > y = mycdf( 8.0 )\n    ~0.932","base.dists.poisson.entropy":"\nbase.dists.poisson.entropy( λ )\n    Returns the entropy of a Poisson distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.poisson.entropy( 11.0 )\n    ~2.61\n    > v = base.dists.poisson.entropy( 4.5 )\n    ~2.149\n\n","base.dists.poisson.kurtosis":"\nbase.dists.poisson.kurtosis( λ )\n    Returns the excess kurtosis of a Poisson distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.poisson.kurtosis( 11.0 )\n    ~0.091\n    > v = base.dists.poisson.kurtosis( 4.5 )\n    ~0.222\n\n","base.dists.poisson.logpmf":"\nbase.dists.poisson.logpmf( x, λ )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    Poisson distribution with mean parameter `λ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPMF.\n\n    Examples\n    --------\n    > var y = base.dists.poisson.logpmf( 4.0, 3.0 )\n    ~-1.784\n    > y = base.dists.poisson.logpmf( 1.0, 3.0 )\n    ~-1.901\n    > y = base.dists.poisson.logpmf( -1.0, 2.0 )\n    -Infinity\n    > y = base.dists.poisson.logpmf( 0.0, NaN )\n    NaN\n    > y = base.dists.poisson.logpmf( NaN, 0.5 )\n    NaN\n\n    // Negative mean parameter:\n    > y = base.dists.poisson.logpmf( 2.0, -0.5 )\n    NaN\n\n    // Degenerate distribution at `λ = 0`:\n    > y = base.dists.poisson.logpmf( 2.0, 0.0 )\n    -Infinity\n    > y = base.dists.poisson.logpmf( 0.0, 0.0 )\n    0.0\n\n\nbase.dists.poisson.logpmf.factory( λ )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a Poisson distribution with mean parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogpmf = base.dists.poisson.logpmf.factory( 1.0 );\n    > var y = mylogpmf( 3.0 )\n    ~-2.792\n    > y = mylogpmf( 1.0 )\n    ~-1.0\n\n","base.dists.poisson.logpmf.factory":"\nbase.dists.poisson.logpmf.factory( λ )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a Poisson distribution with mean parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogpmf = base.dists.poisson.logpmf.factory( 1.0 );\n    > var y = mylogpmf( 3.0 )\n    ~-2.792\n    > y = mylogpmf( 1.0 )\n    ~-1.0","base.dists.poisson.mean":"\nbase.dists.poisson.mean( λ )\n    Returns the expected value of a Poisson distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.poisson.mean( 11.0 )\n    11.0\n    > v = base.dists.poisson.mean( 4.5 )\n    4.5\n\n","base.dists.poisson.median":"\nbase.dists.poisson.median( λ )\n    Returns the median of a Poisson distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: integer\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.poisson.median( 11.0 )\n    11\n    > v = base.dists.poisson.median( 4.5 )\n    4\n\n","base.dists.poisson.mgf":"\nbase.dists.poisson.mgf( x, λ )\n    Evaluates the moment-generating function (MGF) for a Poisson distribution\n    with mean parameter `λ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.poisson.mgf( 1.0, 1.5 )\n    ~13.163\n    > y = base.dists.poisson.mgf( 0.5, 0.5 )\n    ~1.383\n    > y = base.dists.poisson.mgf( NaN, 0.5 )\n    NaN\n    > y = base.dists.poisson.mgf( 0.0, NaN )\n    NaN\n    > y = base.dists.poisson.mgf( -2.0, -1.0 )\n    NaN\n\n\nbase.dists.poisson.mgf.factory( λ )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Poisson distribution with mean parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.poisson.mgf.factory( 2.0 );\n    > var y = myMGF( 0.1 )\n    ~1.234\n\n","base.dists.poisson.mgf.factory":"\nbase.dists.poisson.mgf.factory( λ )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Poisson distribution with mean parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.poisson.mgf.factory( 2.0 );\n    > var y = myMGF( 0.1 )\n    ~1.234","base.dists.poisson.mode":"\nbase.dists.poisson.mode( λ )\n    Returns the mode of a Poisson distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: integer\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.poisson.mode( 11.0 )\n    11\n    > v = base.dists.poisson.mode( 4.5 )\n    4\n\n","base.dists.poisson.pmf":"\nbase.dists.poisson.pmf( x, λ )\n    Evaluates the probability mass function (PMF) for a Poisson\n    distribution with mean parameter `λ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PMF.\n\n    Examples\n    --------\n    > var y = base.dists.poisson.pmf( 4.0, 3.0 )\n    ~0.168\n    > y = base.dists.poisson.pmf( 1.0, 3.0 )\n    ~0.149\n    > y = base.dists.poisson.pmf( -1.0, 2.0 )\n    0.0\n    > y = base.dists.poisson.pmf( 0.0, NaN )\n    NaN\n    > y = base.dists.poisson.pmf( NaN, 0.5 )\n    NaN\n\n    // Negative mean parameter:\n    > y = base.dists.poisson.pmf( 2.0, -0.5 )\n    NaN\n\n    // Degenerate distribution at `λ = 0`:\n    > y = base.dists.poisson.pmf( 2.0, 0.0 )\n    0.0\n    > y = base.dists.poisson.pmf( 0.0, 0.0 )\n    1.0\n\n\nbase.dists.poisson.pmf.factory( λ )\n    Returns a function for evaluating the probability mass function (PMF)\n    of a Poisson distribution with mean parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var mypmf = base.dists.poisson.pmf.factory( 1.0 );\n    > var y = mypmf( 3.0 )\n    ~0.061\n    > y = mypmf( 1.0 )\n    ~0.368\n\n","base.dists.poisson.pmf.factory":"\nbase.dists.poisson.pmf.factory( λ )\n    Returns a function for evaluating the probability mass function (PMF)\n    of a Poisson distribution with mean parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var mypmf = base.dists.poisson.pmf.factory( 1.0 );\n    > var y = mypmf( 3.0 )\n    ~0.061\n    > y = mypmf( 1.0 )\n    ~0.368","base.dists.poisson.Poisson":"\nbase.dists.poisson.Poisson( [λ] )\n    Returns a Poisson distribution object.\n\n    Parameters\n    ----------\n    λ: number (optional)\n        Mean parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    poisson: Object\n        Distribution instance.\n\n    poisson.lambda: number\n        Mean parameter. If set, the value must be greater than `0`.\n\n    poisson.entropy: number\n        Read-only property which returns the differential entropy.\n\n    poisson.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    poisson.mean: number\n        Read-only property which returns the expected value.\n\n    poisson.median: number\n        Read-only property which returns the median.\n\n    poisson.mode: number\n        Read-only property which returns the mode.\n\n    poisson.skewness: number\n        Read-only property which returns the skewness.\n\n    poisson.stdev: number\n        Read-only property which returns the standard deviation.\n\n    poisson.variance: number\n        Read-only property which returns the variance.\n\n    poisson.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    poisson.logpmf: Function\n        Evaluates the natural logarithm of the probability mass function (PMF).\n\n    poisson.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    poisson.pmf: Function\n        Evaluates the probability mass function (PMF).\n\n    poisson.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var poisson = base.dists.poisson.Poisson( 6.0 );\n    > poisson.lambda\n    6.0\n    > poisson.entropy\n    ~2.3\n    > poisson.kurtosis\n    ~0.167\n    > poisson.mean\n    6.0\n    > poisson.median\n    6.0\n    > poisson.mode\n    6.0\n    > poisson.skewness\n    ~0.408\n    > poisson.stdev\n    ~2.449\n    > poisson.variance\n    6.0\n    > poisson.cdf( 4.0 )\n    ~0.285\n    > poisson.logpmf( 2.0 )\n    ~-3.11\n    > poisson.mgf( 0.5 )\n    ~49.025\n    > poisson.pmf( 2.0 )\n    ~0.045\n    > poisson.quantile( 0.5 )\n    6.0\n\n","base.dists.poisson.quantile":"\nbase.dists.poisson.quantile( p, λ )\n    Evaluates the quantile function for a Poisson distribution with mean\n    parameter `λ` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.poisson.quantile( 0.5, 2.0 )\n    2\n    > y = base.dists.poisson.quantile( 0.9, 4.0 )\n    7\n    > y = base.dists.poisson.quantile( 0.1, 200.0 )\n    182\n\n    > y = base.dists.poisson.quantile( 1.1, 0.0 )\n    NaN\n    > y = base.dists.poisson.quantile( -0.2, 0.0 )\n    NaN\n\n    > y = base.dists.poisson.quantile( NaN, 0.5 )\n    NaN\n    > y = base.dists.poisson.quantile( 0.0, NaN )\n    NaN\n\n    // Negative mean parameter:\n    > y = base.dists.poisson.quantile( 2.0, -1.0 )\n    NaN\n\n    // Degenerate distribution at `λ = 0`:\n    > y = base.dists.poisson.quantile( 0.1, 0.0 )\n    0.0\n    > y = base.dists.poisson.quantile( 0.9, 0.0 )\n    0.0\n\n\nbase.dists.poisson.quantile.factory( λ )\n    Returns a function for evaluating the quantile function of a Poisson\n    distribution with mean parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.poisson.quantile.factory( 0.4 );\n    > var y = myQuantile( 0.4 )\n    0.0\n    > y = myQuantile( 1.0 )\n    Infinity\n\n","base.dists.poisson.quantile.factory":"\nbase.dists.poisson.quantile.factory( λ )\n    Returns a function for evaluating the quantile function of a Poisson\n    distribution with mean parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.poisson.quantile.factory( 0.4 );\n    > var y = myQuantile( 0.4 )\n    0.0\n    > y = myQuantile( 1.0 )\n    Infinity","base.dists.poisson.skewness":"\nbase.dists.poisson.skewness( λ )\n    Returns the skewness of a Poisson distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a nonpositive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.poisson.skewness( 11.0 )\n    ~0.302\n    > v = base.dists.poisson.skewness( 4.5 )\n    ~0.471\n\n","base.dists.poisson.stdev":"\nbase.dists.poisson.stdev( λ )\n    Returns the standard deviation of a Poisson distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.poisson.stdev( 11.0 )\n    ~3.317\n    > v = base.dists.poisson.stdev( 4.5 )\n    ~2.121\n\n","base.dists.poisson.variance":"\nbase.dists.poisson.variance( λ )\n    Returns the variance of a Poisson distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.poisson.variance( 11.0 )\n    11.0\n    > v = base.dists.poisson.variance( 4.5 )\n    4.5\n\n","base.dists.rayleigh.cdf":"\nbase.dists.rayleigh.cdf( x, sigma )\n    Evaluates the cumulative distribution function (CDF) for a Rayleigh\n    distribution with scale parameter `sigma` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `sigma`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.rayleigh.cdf( 2.0, 3.0 )\n    ~0.199\n    > y = base.dists.rayleigh.cdf( 1.0, 2.0 )\n    ~0.118\n    > y = base.dists.rayleigh.cdf( -1.0, 4.0 )\n    0.0\n    > y = base.dists.rayleigh.cdf( NaN, 1.0 )\n    NaN\n    > y = base.dists.rayleigh.cdf( 0.0, NaN )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.rayleigh.cdf( 2.0, -1.0 )\n    NaN\n\n    // Degenerate distribution when `sigma = 0.0`:\n    > y = base.dists.rayleigh.cdf( -2.0, 0.0 )\n    0.0\n    > y = base.dists.rayleigh.cdf( 0.0, 0.0 )\n    1.0\n    > y = base.dists.rayleigh.cdf( 2.0, 0.0 )\n    1.0\n\n\nbase.dists.rayleigh.cdf.factory( sigma )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Rayleigh distribution with scale parameter `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.rayleigh.cdf.factory( 0.5 );\n    > var y = myCDF( 1.0 )\n    ~0.865\n    > y = myCDF( 0.5 )\n    ~0.393\n\n","base.dists.rayleigh.cdf.factory":"\nbase.dists.rayleigh.cdf.factory( sigma )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Rayleigh distribution with scale parameter `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.rayleigh.cdf.factory( 0.5 );\n    > var y = myCDF( 1.0 )\n    ~0.865\n    > y = myCDF( 0.5 )\n    ~0.393","base.dists.rayleigh.entropy":"\nbase.dists.rayleigh.entropy( σ )\n    Returns the differential entropy of a Rayleigh distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.rayleigh.entropy( 11.0 )\n    ~3.34\n    > v = base.dists.rayleigh.entropy( 4.5 )\n    ~2.446\n\n","base.dists.rayleigh.kurtosis":"\nbase.dists.rayleigh.kurtosis( σ )\n    Returns the excess kurtosis of a Rayleigh distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.rayleigh.kurtosis( 11.0 )\n    ~0.245\n    > v = base.dists.rayleigh.kurtosis( 4.5 )\n    ~0.245\n\n","base.dists.rayleigh.logcdf":"\nbase.dists.rayleigh.logcdf( x, sigma )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    Rayleigh distribution with scale parameter `sigma` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `sigma`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.rayleigh.logcdf( 2.0, 3.0 )\n    ~-1.613\n    > y = base.dists.rayleigh.logcdf( 1.0, 2.0 )\n    ~-2.141\n    > y = base.dists.rayleigh.logcdf( -1.0, 4.0 )\n    -Infinity\n    > y = base.dists.rayleigh.logcdf( NaN, 1.0 )\n    NaN\n    > y = base.dists.rayleigh.logcdf( 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.rayleigh.logcdf( 2.0, -1.0 )\n    NaN\n\n\nbase.dists.rayleigh.logcdf.factory( sigma )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Rayleigh distribution with scale parameter\n    `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.rayleigh.logcdf.factory( 0.5 );\n    > var y = mylogcdf( 1.0 )\n    ~-0.145\n    > y = mylogcdf( 0.5 )\n    ~-0.933\n\n","base.dists.rayleigh.logcdf.factory":"\nbase.dists.rayleigh.logcdf.factory( sigma )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Rayleigh distribution with scale parameter\n    `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.rayleigh.logcdf.factory( 0.5 );\n    > var y = mylogcdf( 1.0 )\n    ~-0.145\n    > y = mylogcdf( 0.5 )\n    ~-0.933","base.dists.rayleigh.logpdf":"\nbase.dists.rayleigh.logpdf( x, sigma )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    Rayleigh distribution with scale parameter `sigma` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `sigma`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.rayleigh.logpdf( 0.3, 1.0 )\n    ~-1.249\n    > y = base.dists.rayleigh.logpdf( 2.0, 0.8 )\n    ~-1.986\n    > y = base.dists.rayleigh.logpdf( -1.0, 0.5 )\n    -Infinity\n    > y = base.dists.rayleigh.logpdf( 0.0, NaN )\n    NaN\n    > y = base.dists.rayleigh.logpdf( NaN, 2.0 )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.rayleigh.logpdf( 2.0, -1.0 )\n    NaN\n\n\nbase.dists.rayleigh.logpdf.factory( sigma )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Rayleigh distribution with scale parameter `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.rayleigh.logpdf.factory( 4.0 );\n    > var y = mylogpdf( 6.0 )\n    ~-2.106\n    > y = mylogpdf( 4.0 )\n    ~-1.886\n\n","base.dists.rayleigh.logpdf.factory":"\nbase.dists.rayleigh.logpdf.factory( sigma )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Rayleigh distribution with scale parameter `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.rayleigh.logpdf.factory( 4.0 );\n    > var y = mylogpdf( 6.0 )\n    ~-2.106\n    > y = mylogpdf( 4.0 )\n    ~-1.886","base.dists.rayleigh.mean":"\nbase.dists.rayleigh.mean( σ )\n    Returns the expected value of a Rayleigh distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.rayleigh.mean( 11.0 )\n    ~13.786\n    > v = base.dists.rayleigh.mean( 4.5 )\n    ~5.64\n\n","base.dists.rayleigh.median":"\nbase.dists.rayleigh.median( σ )\n    Returns the median of a Rayleigh distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.rayleigh.median( 11.0 )\n    ~12.952\n    > v = base.dists.rayleigh.median( 4.5 )\n    ~5.298\n\n","base.dists.rayleigh.mgf":"\nbase.dists.rayleigh.mgf( t, sigma )\n    Evaluates the moment-generating function (MGF) for a Rayleigh distribution\n    with scale parameter `sigma` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `sigma`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.rayleigh.mgf( 1.0, 3.0 )\n    ~678.508\n    > y = base.dists.rayleigh.mgf( 1.0, 2.0 )\n    ~38.65\n    > y = base.dists.rayleigh.mgf( -1.0, 4.0 )\n    ~-0.947\n    > y = base.dists.rayleigh.mgf( NaN, 1.0 )\n    NaN\n    > y = base.dists.rayleigh.mgf( 0.0, NaN )\n    NaN\n    > y = base.dists.rayleigh.mgf( 0.5, -1.0 )\n    NaN\n\n\nbase.dists.rayleigh.mgf.factory( sigma )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Rayleigh distribution with scale parameter `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.rayleigh.mgf.factory( 0.5 );\n    > var y = myMGF( 1.0 )\n    ~2.715\n    > y = myMGF( 0.5 )\n    ~1.888\n\n","base.dists.rayleigh.mgf.factory":"\nbase.dists.rayleigh.mgf.factory( sigma )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Rayleigh distribution with scale parameter `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.rayleigh.mgf.factory( 0.5 );\n    > var y = myMGF( 1.0 )\n    ~2.715\n    > y = myMGF( 0.5 )\n    ~1.888","base.dists.rayleigh.mode":"\nbase.dists.rayleigh.mode( σ )\n    Returns the mode of a Rayleigh distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.rayleigh.mode( 11.0 )\n    11.0\n    > v = base.dists.rayleigh.mode( 4.5 )\n    4.5\n\n","base.dists.rayleigh.pdf":"\nbase.dists.rayleigh.pdf( x, sigma )\n    Evaluates the probability density function (PDF) for a Rayleigh\n    distribution with scale parameter `sigma` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `sigma`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.rayleigh.pdf( 0.3, 1.0 )\n    ~0.287\n    > y = base.dists.rayleigh.pdf( 2.0, 0.8 )\n    ~0.137\n    > y = base.dists.rayleigh.pdf( -1.0, 0.5 )\n    0.0\n    > y = base.dists.rayleigh.pdf( 0.0, NaN )\n    NaN\n    > y = base.dists.rayleigh.pdf( NaN, 2.0 )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.rayleigh.pdf( 2.0, -1.0 )\n    NaN\n\n    // Degenerate distribution when `sigma = 0.0`:\n    > y = base.dists.rayleigh.pdf( -2.0, 0.0 )\n    0.0\n    > y = base.dists.rayleigh.pdf( 0.0, 0.0 )\n    Infinity\n    > y = base.dists.rayleigh.pdf( 2.0, 0.0 )\n    0.0\n\n\nbase.dists.rayleigh.pdf.factory( sigma )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Rayleigh distribution with scale parameter `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.rayleigh.pdf.factory( 4.0 );\n    > var y = myPDF( 6.0 )\n    ~0.122\n    > y = myPDF( 4.0 )\n    ~0.152\n\n","base.dists.rayleigh.pdf.factory":"\nbase.dists.rayleigh.pdf.factory( sigma )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Rayleigh distribution with scale parameter `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.rayleigh.pdf.factory( 4.0 );\n    > var y = myPDF( 6.0 )\n    ~0.122\n    > y = myPDF( 4.0 )\n    ~0.152","base.dists.rayleigh.quantile":"\nbase.dists.rayleigh.quantile( p, sigma )\n    Evaluates the quantile function for a Rayleigh distribution with scale\n    parameter `sigma` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative probability for `sigma`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.rayleigh.quantile( 0.8, 1.0 )\n    ~1.794\n    > y = base.dists.rayleigh.quantile( 0.5, 4.0 )\n    ~4.71\n\n    > y = base.dists.rayleigh.quantile( 1.1, 1.0 )\n    NaN\n    > y = base.dists.rayleigh.quantile( -0.2, 1.0 )\n    NaN\n\n    > y = base.dists.rayleigh.quantile( NaN, 1.0 )\n    NaN\n    > y = base.dists.rayleigh.quantile( 0.0, NaN )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.rayleigh.quantile( 0.5, -1.0 )\n    NaN\n\n\nbase.dists.rayleigh.quantile.factory( sigma )\n    Returns a function for evaluating the quantile function of a Rayleigh\n    distribution with scale parameter `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.rayleigh.quantile.factory( 0.4 );\n    > var y = myQuantile( 0.4 )\n    ~0.404\n    > y = myQuantile( 1.0 )\n    Infinity\n\n","base.dists.rayleigh.quantile.factory":"\nbase.dists.rayleigh.quantile.factory( sigma )\n    Returns a function for evaluating the quantile function of a Rayleigh\n    distribution with scale parameter `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.rayleigh.quantile.factory( 0.4 );\n    > var y = myQuantile( 0.4 )\n    ~0.404\n    > y = myQuantile( 1.0 )\n    Infinity","base.dists.rayleigh.Rayleigh":"\nbase.dists.rayleigh.Rayleigh( [σ] )\n    Returns a Rayleigh distribution object.\n\n    Parameters\n    ----------\n    σ: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    rayleigh: Object\n        Distribution instance.\n\n    rayleigh.sigma: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    rayleigh.entropy: number\n        Read-only property which returns the differential entropy.\n\n    rayleigh.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    rayleigh.mean: number\n        Read-only property which returns the expected value.\n\n    rayleigh.median: number\n        Read-only property which returns the median.\n\n    rayleigh.mode: number\n        Read-only property which returns the mode.\n\n    rayleigh.skewness: number\n        Read-only property which returns the skewness.\n\n    rayleigh.stdev: number\n        Read-only property which returns the standard deviation.\n\n    rayleigh.variance: number\n        Read-only property which returns the variance.\n\n    rayleigh.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    rayleigh.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    rayleigh.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    rayleigh.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    rayleigh.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    rayleigh.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var rayleigh = base.dists.rayleigh.Rayleigh( 6.0 );\n    > rayleigh.sigma\n    6.0\n    > rayleigh.entropy\n    ~2.734\n    > rayleigh.kurtosis\n    ~0.245\n    > rayleigh.mean\n    ~7.52\n    > rayleigh.median\n    ~7.064\n    > rayleigh.mode\n    6.0\n    > rayleigh.skewness\n    ~0.631\n    > rayleigh.stdev\n    ~3.931\n    > rayleigh.variance\n    ~15.451\n    > rayleigh.cdf( 1.0 )\n    ~0.014\n    > rayleigh.logcdf( 1.0 )\n    ~-4.284\n    > rayleigh.logpdf( 1.5 )\n    ~-3.209\n    > rayleigh.mgf( -0.5 )\n    ~-0.91\n    > rayleigh.pdf( 1.5 )\n    ~0.04\n    > rayleigh.quantile( 0.5 )\n    ~7.064\n\n","base.dists.rayleigh.skewness":"\nbase.dists.rayleigh.skewness( σ )\n    Returns the skewness of a Rayleigh distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.rayleigh.skewness( 11.0 )\n    ~0.631\n    > v = base.dists.rayleigh.skewness( 4.5 )\n    ~0.631\n\n","base.dists.rayleigh.stdev":"\nbase.dists.rayleigh.stdev( σ )\n    Returns the standard deviation of a Rayleigh distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.rayleigh.stdev( 9.0 )\n    ~5.896\n    > v = base.dists.rayleigh.stdev( 4.5 )\n    ~2.948\n\n","base.dists.rayleigh.variance":"\nbase.dists.rayleigh.variance( σ )\n    Returns the variance of a Rayleigh distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.rayleigh.variance( 9.0 )\n    ~34.765\n    > v = base.dists.rayleigh.variance( 4.5 )\n    ~8.691\n\n","base.dists.signrank.cdf":"\nbase.dists.signrank.cdf( x, n )\n    Evaluates the cumulative distribution function (CDF) for the distribution of\n    the Wilcoxon signed rank test statistic with `n` observations.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `x`, the function returns `NaN`.\n\n    If not provided a positive integer for `n`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Number of observations.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.signrank.cdf( 3, 7 )\n    ~0.039\n    > y = base.dists.signrank.cdf( 1.8, 3 )\n    ~0.375\n    > y = base.dists.signrank.cdf( -1.0, 40 )\n    0.0\n    > y = base.dists.signrank.cdf( NaN, 10 )\n    NaN\n    > y = base.dists.signrank.cdf( 0.0, NaN )\n    NaN\n\n\nbase.dists.signrank.cdf.factory( n )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of the distribution of the Wilcoxon signed rank test statistic.\n\n    Parameters\n    ----------\n    n: integer\n        Number of observations.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.signrank.cdf.factory( 8 );\n    > var y = myCDF( 5.7 )\n    ~0.055\n    > y = myCDF( 2.2 )\n    ~0.012\n\n","base.dists.signrank.cdf.factory":"\nbase.dists.signrank.cdf.factory( n )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of the distribution of the Wilcoxon signed rank test statistic.\n\n    Parameters\n    ----------\n    n: integer\n        Number of observations.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.signrank.cdf.factory( 8 );\n    > var y = myCDF( 5.7 )\n    ~0.055\n    > y = myCDF( 2.2 )\n    ~0.012","base.dists.signrank.pdf":"\nbase.dists.signrank.pdf( x, n )\n    Evaluates the probability density function (PDF) for the distribution of\n    the Wilcoxon signed rank test statistic with `n` observations.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `x`, the function returns `NaN`.\n\n    If not provided a positive integer for `n`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Number of observations.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.signrank.pdf( 3, 7 )\n    ~0.0156\n    > y = base.dists.signrank.pdf( 1.8, 3 )\n    0.0\n    > y = base.dists.signrank.pdf( -1.0, 40 )\n    0.0\n    > y = base.dists.signrank.pdf( NaN, 10 )\n    NaN\n    > y = base.dists.signrank.pdf( 0.0, NaN )\n    NaN\n\n\nbase.dists.signrank.pdf.factory( n )\n    Returns a function for evaluating the probability density function (PDF)\n    of the distribution of the Wilcoxon signed rank test statistic.\n\n    Parameters\n    ----------\n    n: integer\n        Number of observations.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.signrank.pdf.factory( 8 );\n    > var y = myPDF( 6.0 )\n    ~0.0156\n    > y = myPDF( 2.0 )\n    ~0.0039\n\n","base.dists.signrank.pdf.factory":"\nbase.dists.signrank.pdf.factory( n )\n    Returns a function for evaluating the probability density function (PDF)\n    of the distribution of the Wilcoxon signed rank test statistic.\n\n    Parameters\n    ----------\n    n: integer\n        Number of observations.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.signrank.pdf.factory( 8 );\n    > var y = myPDF( 6.0 )\n    ~0.0156\n    > y = myPDF( 2.0 )\n    ~0.0039","base.dists.signrank.quantile":"\nbase.dists.signrank.quantile( p, n )\n    Evaluates the quantile function for the Wilcoxon signed rank test statistic\n    with `n` observations at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a positive integer for `n`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    n: integer\n        Number of observations.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.signrank.quantile( 0.8, 5 )\n    11\n    > y = base.dists.signrank.quantile( 0.5, 4 )\n    5\n\n    > y = base.dists.signrank.quantile( 1.1, 5 )\n    NaN\n    > y = base.dists.signrank.quantile( -0.2, 5 )\n    NaN\n\n    > y = base.dists.signrank.quantile( NaN, 5 )\n    NaN\n    > y = base.dists.signrank.quantile( 0.0, NaN )\n    NaN\n\n\nbase.dists.signrank.quantile.factory( n )\n    Returns a function for evaluating the quantile function of the Wilcoxon\n    signed rank test statistic with `n` observations.\n\n    Parameters\n    ----------\n    n: integer\n        Number of observations.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.signrank.quantile.factory( 8 );\n    > var y = myQuantile( 0.4 )\n    16\n    > y = myQuantile( 1.0 )\n    36\n\n","base.dists.signrank.quantile.factory":"\nbase.dists.signrank.quantile.factory( n )\n    Returns a function for evaluating the quantile function of the Wilcoxon\n    signed rank test statistic with `n` observations.\n\n    Parameters\n    ----------\n    n: integer\n        Number of observations.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.signrank.quantile.factory( 8 );\n    > var y = myQuantile( 0.4 )\n    16\n    > y = myQuantile( 1.0 )\n    36","base.dists.studentizedRange.cdf":"\nbase.dists.studentizedRange.cdf( x, r, v[, nranges] )\n    Evaluates the cumulative distribution function (CDF) of a studentized range\n    distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `r < 2` or `v < 2`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    r: number\n        Sample size for range (same for each group).\n\n    v: number\n        Degrees of freedom.\n\n    nranges: integer\n        Number of groups whose maximum range is considered. Default: 1.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.studentizedRange.cdf( 0.5, 3.0, 2.0 )\n    ~0.0644\n\n    > y = base.dists.studentizedRange.cdf( 12.1, 17.0, 2.0 )\n    ~0.913\n\n\nbase.dists.studentizedRange.cdf.factory( r, v[, nranges] )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a studentized range distribution.\n\n    Parameters\n    ----------\n    r: number\n        Number of samples.\n\n    v: number\n        Degrees of freedom.\n\n    nranges: integer\n        Number of groups whose maximum range is considered. Default: 1.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.studentizedRange.cdf.factory( 3.0, 2.0 );\n    > var y = mycdf( 3.0 )\n    ~0.712\n    > y = mycdf( 1.0 )\n    ~0.216\n\n","base.dists.studentizedRange.cdf.factory":"\nbase.dists.studentizedRange.cdf.factory( r, v[, nranges] )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a studentized range distribution.\n\n    Parameters\n    ----------\n    r: number\n        Number of samples.\n\n    v: number\n        Degrees of freedom.\n\n    nranges: integer\n        Number of groups whose maximum range is considered. Default: 1.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.studentizedRange.cdf.factory( 3.0, 2.0 );\n    > var y = mycdf( 3.0 )\n    ~0.712\n    > y = mycdf( 1.0 )\n    ~0.216","base.dists.studentizedRange.quantile":"\nbase.dists.studentizedRange.quantile( p, r, v[, nranges] )\n    Evaluates the quantile function for a studentized range distribution.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `r < 2` or `v < 2`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    r: number\n        Sample size for range (same for each group).\n\n    v: number\n        Degrees of freedom.\n\n    nranges: integer\n        Number of groups whose maximum range is considered. Default: 1.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = quantile( 0.5, 3.0, 2.0 )\n     ~0.0644\n\n    > y = quantile( 0.9, 17.0, 2.0 )\n     ~0.913\n\n    > y = quantile( 0.5, 3.0, 2.0, 2 )\n     ~0.01\n\n    > y = base.dists.studentizedRange.quantile( -0.2, 3.0, 3.0 )\n    NaN\n\n    > y = base.dists.studentizedRange.quantile( NaN, 2.0, 2.0 )\n    NaN\n    > y = base.dists.studentizedRange.quantile( 0.0, NaN, 2.0 )\n    NaN\n\n    > y = base.dists.studentizedRange.quantile( 0.5, -1.0, 2.0 )\n    NaN\n\n\nbase.dists.studentizedRange.quantile.factory( r, v[, nranges] )\n    Returns a function for evaluating the quantile function of a studentized\n    range distribution.\n\n    Parameters\n    ----------\n    r: number\n        Sample size for range (same for each group).\n\n    v: number\n        Degrees of freedom.\n\n    nranges: integer\n        Number of groups whose maximum range is considered. Default: 1.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = quantile.factory( 3.0, 3.0 );\n    > var y = myQuantile( 0.5 )\n   ~1.791\n\n    > y = myQuantile( 0.8 )\n   ~3.245\n\n","base.dists.studentizedRange.quantile.factory":"\nbase.dists.studentizedRange.quantile.factory( r, v[, nranges] )\n    Returns a function for evaluating the quantile function of a studentized\n    range distribution.\n\n    Parameters\n    ----------\n    r: number\n        Sample size for range (same for each group).\n\n    v: number\n        Degrees of freedom.\n\n    nranges: integer\n        Number of groups whose maximum range is considered. Default: 1.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = quantile.factory( 3.0, 3.0 );\n    > var y = myQuantile( 0.5 )\n   ~1.791\n\n    > y = myQuantile( 0.8 )\n   ~3.245","base.dists.t.cdf":"\nbase.dists.t.cdf( x, v )\n    Evaluates the cumulative distribution function (CDF) for a Student's t\n    distribution with degrees of freedom `v` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a non-positive value for `v`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.t.cdf( 2.0, 0.1 )\n    ~0.611\n    > y = base.dists.t.cdf( 1.0, 2.0 )\n    ~0.789\n    > y = base.dists.t.cdf( -1.0, 4.0 )\n    ~0.187\n    > y = base.dists.t.cdf( NaN, 1.0 )\n    NaN\n    > y = base.dists.t.cdf( 0.0, NaN )\n    NaN\n    > y = base.dists.t.cdf( 2.0, -1.0 )\n    NaN\n\n\nbase.dists.t.cdf.factory( v )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Student's t distribution with degrees of freedom `v`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.t.cdf.factory( 0.5 );\n    > var y = mycdf( 3.0 )\n    ~0.816\n    > y = mycdf( 1.0 )\n    ~0.699\n\n","base.dists.t.cdf.factory":"\nbase.dists.t.cdf.factory( v )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Student's t distribution with degrees of freedom `v`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.t.cdf.factory( 0.5 );\n    > var y = mycdf( 3.0 )\n    ~0.816\n    > y = mycdf( 1.0 )\n    ~0.699","base.dists.t.entropy":"\nbase.dists.t.entropy( v )\n    Returns the differential entropy of a Student's t distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `v < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.t.entropy( 11.0 )\n    ~1.512\n    > v = base.dists.t.entropy( 4.5 )\n    ~1.652\n\n","base.dists.t.kurtosis":"\nbase.dists.t.kurtosis( v )\n    Returns the excess kurtosis of a Student's t distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `v <= 2`, the function returns `NaN`.\n\n    If provided `2 < v <= 4`, the function returns positive infinity.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.t.kurtosis( 11.0 )\n    ~0.857\n    > v = base.dists.t.kurtosis( 4.5 )\n    12.0\n\n","base.dists.t.logcdf":"\nbase.dists.t.logcdf( x, v )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a Student's t distribution with degrees of freedom `v` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a non-positive value for `v`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.t.logcdf( 2.0, 0.1 )\n    ~-0.493\n    > y = base.dists.t.logcdf( 1.0, 2.0 )\n    ~-0.237\n    > y = base.dists.t.logcdf( -1.0, 4.0 )\n    ~-1.677\n    > y = base.dists.t.logcdf( NaN, 1.0 )\n    NaN\n    > y = base.dists.t.logcdf( 0.0, NaN )\n    NaN\n    > y = base.dists.t.logcdf( 2.0, -1.0 )\n    NaN\n\n\nbase.dists.t.logcdf.factory( v )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Student's t distribution with degrees of\n    freedom `v`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.t.logcdf.factory( 0.5 );\n    > var y = mylogcdf( 3.0 )\n    ~-0.203\n    > y = mylogcdf( 1.0 )\n    ~-0.358\n\n","base.dists.t.logcdf.factory":"\nbase.dists.t.logcdf.factory( v )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Student's t distribution with degrees of\n    freedom `v`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.t.logcdf.factory( 0.5 );\n    > var y = mylogcdf( 3.0 )\n    ~-0.203\n    > y = mylogcdf( 1.0 )\n    ~-0.358","base.dists.t.logpdf":"\nbase.dists.t.logpdf( x, v )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a Student's t distribution with degrees of freedom `v` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a non-positive value for `v`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.t.logpdf( 0.3, 4.0 )\n    ~-1.036\n    > y = base.dists.t.logpdf( 2.0, 0.7 )\n    ~-2.841\n    > y = base.dists.t.logpdf( -1.0, 0.5 )\n    ~-2.134\n    > y = base.dists.t.logpdf( 0.0, NaN )\n    NaN\n    > y = base.dists.t.logpdf( NaN, 2.0 )\n    NaN\n    > y = base.dists.t.logpdf( 2.0, -1.0 )\n    NaN\n\n\nbase.dists.t.logpdf.factory( v )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a Student's t distribution with degrees of\n    freedom `v`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.t.logpdf.factory( 3.0 );\n    > var y = mylogPDF( 1.0 )\n    ~-1.576\n\n","base.dists.t.logpdf.factory":"\nbase.dists.t.logpdf.factory( v )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a Student's t distribution with degrees of\n    freedom `v`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.t.logpdf.factory( 3.0 );\n    > var y = mylogPDF( 1.0 )\n    ~-1.576","base.dists.t.mean":"\nbase.dists.t.mean( v )\n    Returns the expected value of a Student's t distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `v <= 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.t.mean( 11.0 )\n    0.0\n    > v = base.dists.t.mean( 4.5 )\n    0.0\n\n","base.dists.t.median":"\nbase.dists.t.median( v )\n    Returns the median of a Student's t distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `v < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.t.median( 11.0 )\n    0.0\n    > v = base.dists.t.median( 4.5 )\n    0.0\n\n","base.dists.t.mode":"\nbase.dists.t.mode( v )\n    Returns the mode of a Student's t distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `v < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.t.mode( 11.0 )\n    0.0\n    > v = base.dists.t.mode( 4.5 )\n    0.0\n\n","base.dists.t.pdf":"\nbase.dists.t.pdf( x, v )\n    Evaluates the probability density function (PDF) for a Student's t\n    distribution with degrees of freedom `v` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a non-positive value for `v`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.t.pdf( 0.3, 4.0 )\n    ~0.355\n    > y = base.dists.t.pdf( 2.0, 0.7 )\n    ~0.058\n    > y = base.dists.t.pdf( -1.0, 0.5 )\n    ~0.118\n    > y = base.dists.t.pdf( 0.0, NaN )\n    NaN\n    > y = base.dists.t.pdf( NaN, 2.0 )\n    NaN\n    > y = base.dists.t.pdf( 2.0, -1.0 )\n    NaN\n\n\nbase.dists.t.pdf.factory( v )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Student's t distribution with degrees of freedom `v`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.t.pdf.factory( 3.0 );\n    > var y = myPDF( 1.0 )\n    ~0.207\n\n","base.dists.t.pdf.factory":"\nbase.dists.t.pdf.factory( v )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Student's t distribution with degrees of freedom `v`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.t.pdf.factory( 3.0 );\n    > var y = myPDF( 1.0 )\n    ~0.207","base.dists.t.quantile":"\nbase.dists.t.quantile( p, v )\n    Evaluates the quantile function for a Student's t distribution with degrees\n    of freedom `v` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a non-positive value for `v`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.t.quantile( 0.8, 1.0 )\n    ~1.376\n    > y = base.dists.t.quantile( 0.1, 1.0 )\n    ~-3.078\n    > y = base.dists.t.quantile( 0.5, 0.1 )\n    0.0\n\n    > y = base.dists.t.quantile( -0.2, 0.1 )\n    NaN\n\n    > y = base.dists.t.quantile( NaN, 1.0 )\n    NaN\n    > y = base.dists.t.quantile( 0.0, NaN )\n    NaN\n\n    > y = base.dists.t.quantile( 0.5, -1.0 )\n    NaN\n\n\nbase.dists.t.quantile.factory( v )\n    Returns a function for evaluating the quantile function of a Student's t\n    distribution with degrees of freedom `v`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.t.quantile.factory( 4.0 );\n    > var y = myQuantile( 0.2 )\n    ~-0.941\n    > y = myQuantile( 0.9 )\n    ~1.533\n\n","base.dists.t.quantile.factory":"\nbase.dists.t.quantile.factory( v )\n    Returns a function for evaluating the quantile function of a Student's t\n    distribution with degrees of freedom `v`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.t.quantile.factory( 4.0 );\n    > var y = myQuantile( 0.2 )\n    ~-0.941\n    > y = myQuantile( 0.9 )\n    ~1.533","base.dists.t.skewness":"\nbase.dists.t.skewness( v )\n    Returns the skewness of a Student's t distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `v <= 3`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.t.skewness( 11.0 )\n    0.0\n    > v = base.dists.t.skewness( 4.5 )\n    0.0\n\n","base.dists.t.stdev":"\nbase.dists.t.stdev( v )\n    Returns the standard deviation of a Student's t distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `1 < v <= 2`, the function returns positive infinity.\n\n    If provided `v <= 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.t.stdev( 9.0 )\n    ~1.134\n    > v = base.dists.t.stdev( 4.5 )\n    ~1.342\n\n","base.dists.t.T":"\nbase.dists.t.T( [v] )\n    Returns a Student's t distribution object.\n\n    Parameters\n    ----------\n    v: number (optional)\n        Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    t: Object\n        Distribution instance.\n\n    t.v: number\n        Degrees of freedom. If set, the value must be greater than `0`.\n\n    t.entropy: number\n        Read-only property which returns the differential entropy.\n\n    t.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    t.mean: number\n        Read-only property which returns the expected value.\n\n    t.median: number\n        Read-only property which returns the median.\n\n    t.mode: number\n        Read-only property which returns the mode.\n\n    t.skewness: number\n        Read-only property which returns the skewness.\n\n    t.stdev: number\n        Read-only property which returns the standard deviation.\n\n    t.variance: number\n        Read-only property which returns the variance.\n\n    t.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    t.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    t.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    t.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    t.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var t = base.dists.t.T( 6.0 );\n    > t.v\n    6.0\n    > t.entropy\n    ~1.592\n    > t.kurtosis\n    3.0\n    > t.mean\n    0.0\n    > t.median\n    0.0\n    > t.mode\n    0.0\n    > t.skewness\n    0.0\n    > t.stdev\n    ~1.225\n    > t.variance\n    1.5\n    > t.cdf( 1.0 )\n    ~0.822\n    > t.logcdf( 1.0 )\n    ~-0.196\n    > t.logpdf( 1.5 )\n    ~-2.075\n    > t.pdf( 1.5 )\n    ~0.126\n    > t.quantile( 0.8 )\n    ~0.906\n\n","base.dists.t.variance":"\nbase.dists.t.variance( v )\n    Returns the variance of a Student's t distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `1 < v <= 2`, the function returns positive infinity.\n\n    If provided `v <= 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.t.variance( 9.0 )\n    ~1.286\n    > v = base.dists.t.variance( 4.5 )\n    ~1.8\n\n","base.dists.triangular.cdf":"\nbase.dists.triangular.cdf( x, a, b, c )\n    Evaluates the cumulative distribution function (CDF) for a triangular\n    distribution with minimum support `a`, maximum support `b`, and mode `c` at\n    a value `x`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.0 )\n    0.875\n    > y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.5 )\n    0.75\n    > y = base.dists.triangular.cdf( -10.0, -20.0, 0.0, -2.0 )\n    ~0.278\n    > y = base.dists.triangular.cdf( -2.0, -1.0, 1.0, 0.0 )\n    0.0\n    > y = base.dists.triangular.cdf( NaN, 0.0, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.cdf( 0.0, NaN, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.cdf( 0.0, 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.triangular.cdf( 2.0, 1.0, 0.0, NaN )\n    NaN\n    > y = base.dists.triangular.cdf( 2.0, 1.0, 0.0, 1.5 )\n    NaN\n\n\nbase.dists.triangular.cdf.factory( a, b, c )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a triangular distribution with minimum support `a`, maximum support `b`,\n    and mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.triangular.cdf.factory( 0.0, 10.0, 2.0 );\n    > var y = mycdf( 0.5 )\n    0.0125\n    > y = mycdf( 8.0 )\n    0.95\n\n\n","base.dists.triangular.cdf.factory":"\nbase.dists.triangular.cdf.factory( a, b, c )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a triangular distribution with minimum support `a`, maximum support `b`,\n    and mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.triangular.cdf.factory( 0.0, 10.0, 2.0 );\n    > var y = mycdf( 0.5 )\n    0.0125\n    > y = mycdf( 8.0 )\n    0.95","base.dists.triangular.entropy":"\nbase.dists.triangular.entropy( a, b, c )\n    Returns the differential entropy of a triangular distribution (in nats).\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.triangular.entropy( 0.0, 1.0, 0.8 )\n    ~-0.193\n    > v = base.dists.triangular.entropy( 4.0, 12.0, 5.0 )\n    ~1.886\n    > v = base.dists.triangular.entropy( 2.0, 8.0, 5.0 )\n    ~1.599\n\n","base.dists.triangular.kurtosis":"\nbase.dists.triangular.kurtosis( a, b, c )\n    Returns the excess kurtosis of a triangular distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.triangular.kurtosis( 0.0, 1.0, 0.8 )\n    -0.6\n    > v = base.dists.triangular.kurtosis( 4.0, 12.0, 5.0 )\n    -0.6\n    > v = base.dists.triangular.kurtosis( 2.0, 8.0, 5.0 )\n    -0.6\n\n","base.dists.triangular.logcdf":"\nbase.dists.triangular.logcdf( x, a, b, c )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a triangular distribution with minimum support `a`, maximum\n    support `b`, and mode `c` at a value `x`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.0 )\n    ~-0.134\n    > y = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.5 )\n    ~-0.288\n    > y = base.dists.triangular.logcdf( -10.0, -20.0, 0.0, -2.0 )\n    ~-1.281\n    > y = base.dists.triangular.logcdf( -2.0, -1.0, 1.0, 0.0 )\n    -Infinity\n    > y = base.dists.triangular.logcdf( NaN, 0.0, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.logcdf( 0.0, NaN, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.logcdf( 0.0, 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, NaN )\n    NaN\n    > y = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, 1.5 )\n    NaN\n\n\nbase.dists.triangular.logcdf.factory( a, b, c )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a triangular distribution with minimum\n    support `a`, maximum support `b`, and mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    cdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.triangular.logcdf.factory( 0.0, 10.0, 2.0 );\n    > var y = mylogcdf( 0.5 )\n    ~-4.382\n    > y = mylogcdf( 8.0 )\n    ~-0.051\n\n\n","base.dists.triangular.logcdf.factory":"\nbase.dists.triangular.logcdf.factory( a, b, c )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a triangular distribution with minimum\n    support `a`, maximum support `b`, and mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    cdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.triangular.logcdf.factory( 0.0, 10.0, 2.0 );\n    > var y = mylogcdf( 0.5 )\n    ~-4.382\n    > y = mylogcdf( 8.0 )\n    ~-0.051","base.dists.triangular.logpdf":"\nbase.dists.triangular.logpdf( x, a, b, c )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a triangular distribution with minimum support `a`, maximum support `b`,\n    and mode `c` at a value `x`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.0 )\n    ~-0.693\n    > y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.5 )\n    0.0\n    > y = base.dists.triangular.logpdf( -10.0, -20.0, 0.0, -2.0 )\n    ~-2.89\n    > y = base.dists.triangular.logpdf( -2.0, -1.0, 1.0, 0.0 )\n    -Infinity\n    > y = base.dists.triangular.logpdf( NaN, 0.0, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.logpdf( 0.0, NaN, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.logpdf( 0.0, 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, NaN )\n    NaN\n    > y = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, 1.5 )\n    NaN\n\n\nbase.dists.triangular.logpdf.factory( a, b, c )\n    Returns a function for evaluating the natural logarithm of the  probability\n    density function (PDF) of a triangular distribution with minimum support\n    `a`, maximum support `b`, and mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.triangular.logpdf.factory( 0.0, 10.0, 5.0 );\n    > var y = mylogpdf( 2.0 )\n    ~-2.526\n    > y = mylogpdf( 12.0 )\n    -Infinity\n\n\n","base.dists.triangular.logpdf.factory":"\nbase.dists.triangular.logpdf.factory( a, b, c )\n    Returns a function for evaluating the natural logarithm of the  probability\n    density function (PDF) of a triangular distribution with minimum support\n    `a`, maximum support `b`, and mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.triangular.logpdf.factory( 0.0, 10.0, 5.0 );\n    > var y = mylogpdf( 2.0 )\n    ~-2.526\n    > y = mylogpdf( 12.0 )\n    -Infinity","base.dists.triangular.mean":"\nbase.dists.triangular.mean( a, b, c )\n    Returns the expected value of a triangular distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.triangular.mean( 0.0, 1.0, 0.8 )\n    ~0.6\n    > v = base.dists.triangular.mean( 4.0, 12.0, 5.0 )\n    7.0\n    > v = base.dists.triangular.mean( 2.0, 8.0, 5.0 )\n    5.0\n\n","base.dists.triangular.median":"\nbase.dists.triangular.median( a, b, c )\n    Returns the median of a triangular distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.triangular.median( 0.0, 1.0, 0.8 )\n    ~0.632\n    > v = base.dists.triangular.median( 4.0, 12.0, 5.0 )\n    ~6.708\n    > v = base.dists.triangular.median( 2.0, 8.0, 5.0 )\n    5.0\n\n","base.dists.triangular.mgf":"\nbase.dists.triangular.mgf( t, a, b, c )\n    Evaluates the moment-generating function (MGF) for a triangular distribution\n    with minimum support `a`, maximum support `b`, and mode `c` at a value `t`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.0 )\n    ~1.021\n    > y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.5 )\n    ~1.111\n    > y = base.dists.triangular.mgf( -0.3, -20.0, 0.0, -2.0 )\n    ~24.334\n    > y = base.dists.triangular.mgf( -2.0, -1.0, 1.0, 0.0 )\n    ~1.381\n    > y = base.dists.triangular.mgf( NaN, 0.0, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.mgf( 0.0, NaN, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.mgf( 0.0, 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.triangular.mgf( 0.5, 1.0, 0.0, NaN )\n    NaN\n    > y = base.dists.triangular.mgf( 0.5, 1.0, 0.0, 1.5 )\n    NaN\n\n\nbase.dists.triangular.mgf.factory( a, b, c )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    triangular distribution with minimum support `a`, maximum support `b`, and\n    mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.triangular.mgf.factory( 0.0, 2.0, 1.0 );\n    > var y = mymgf( -1.0 )\n    ~0.3996\n    > y = mymgf( 2.0 )\n    ~10.205\n\n\n","base.dists.triangular.mgf.factory":"\nbase.dists.triangular.mgf.factory( a, b, c )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    triangular distribution with minimum support `a`, maximum support `b`, and\n    mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.triangular.mgf.factory( 0.0, 2.0, 1.0 );\n    > var y = mymgf( -1.0 )\n    ~0.3996\n    > y = mymgf( 2.0 )\n    ~10.205","base.dists.triangular.mode":"\nbase.dists.triangular.mode( a, b, c )\n    Returns the mode of a triangular distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.triangular.mode( 0.0, 1.0, 0.8 )\n    0.8\n    > v = base.dists.triangular.mode( 4.0, 12.0, 5.0 )\n    5.0\n    > v = base.dists.triangular.mode( 2.0, 8.0, 5.0 )\n    5.0\n\n","base.dists.triangular.pdf":"\nbase.dists.triangular.pdf( x, a, b, c )\n    Evaluates the probability density function (PDF) for a triangular\n    distribution with minimum support `a`, maximum support `b`, and mode `c` at\n    a value `x`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.0 )\n    0.5\n    > y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.5 )\n    1.0\n    > y = base.dists.triangular.pdf( -10.0, -20.0, 0.0, -2.0 )\n    ~0.056\n    > y = base.dists.triangular.pdf( -2.0, -1.0, 1.0, 0.0 )\n    0.0\n    > y = base.dists.triangular.pdf( NaN, 0.0, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.pdf( 0.0, NaN, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.pdf( 0.0, 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.triangular.pdf( 2.0, 1.0, 0.0, NaN )\n    NaN\n    > y = base.dists.triangular.pdf( 2.0, 1.0, 0.0, 1.5 )\n    NaN\n\n\nbase.dists.triangular.pdf.factory( a, b, c )\n    Returns a function for evaluating the probability density function (PDF) of\n    a triangular distribution with minimum support `a`, maximum support `b`, and\n    mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var mypdf = base.dists.triangular.pdf.factory( 0.0, 10.0, 5.0 );\n    > var y = mypdf( 2.0 )\n    0.08\n    > y = mypdf( 12.0 )\n    0.0\n\n\n","base.dists.triangular.pdf.factory":"\nbase.dists.triangular.pdf.factory( a, b, c )\n    Returns a function for evaluating the probability density function (PDF) of\n    a triangular distribution with minimum support `a`, maximum support `b`, and\n    mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var mypdf = base.dists.triangular.pdf.factory( 0.0, 10.0, 5.0 );\n    > var y = mypdf( 2.0 )\n    0.08\n    > y = mypdf( 12.0 )\n    0.0","base.dists.triangular.quantile":"\nbase.dists.triangular.quantile( p, a, b, c )\n    Evaluates the quantile function for a triangular distribution with minimum\n    support `a`, maximum support `b`, and mode `c` at a value `x`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.triangular.quantile( 0.9, -1.0, 1.0, 0.0 )\n    ~0.553\n    > y = base.dists.triangular.quantile( 0.1, -1.0, 1.0, 0.5 )\n    ~-0.452\n    > y = base.dists.triangular.quantile( 0.1, -20.0, 0.0, -2.0 )\n    -14.0\n    > y = base.dists.triangular.quantile( 0.8, 0.0, 20.0, 0.0 )\n    ~11.056\n\n    > y = base.dists.triangular.quantile( 1.1, -1.0, 1.0, 0.0 )\n    NaN\n    > y = base.dists.triangular.quantile( -0.1, -1.0, 1.0, 0.0 )\n    NaN\n\n    > y = base.dists.triangular.quantile( NaN, 0.0, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.quantile( 0.3, NaN, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.quantile( 0.3, 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.triangular.quantile( 0.3, 1.0, 0.0, NaN )\n    NaN\n\n    > y = base.dists.triangular.quantile( 0.3, 1.0, 0.0, 1.5 )\n    NaN\n\n\nbase.dists.triangular.quantile.factory( a, b, c )\n    Returns a function for evaluating the quantile function of a triangular\n    distribution with minimum support `a`, maximum support `b`, and mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.triangular.quantile.factory( 2.0, 4.0, 2.5 );\n    > var y = myquantile( 0.4 )\n    ~2.658\n    > y = myquantile( 0.8 )\n    ~3.225\n\n\n","base.dists.triangular.quantile.factory":"\nbase.dists.triangular.quantile.factory( a, b, c )\n    Returns a function for evaluating the quantile function of a triangular\n    distribution with minimum support `a`, maximum support `b`, and mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.triangular.quantile.factory( 2.0, 4.0, 2.5 );\n    > var y = myquantile( 0.4 )\n    ~2.658\n    > y = myquantile( 0.8 )\n    ~3.225","base.dists.triangular.skewness":"\nbase.dists.triangular.skewness( a, b, c )\n    Returns the skewness of a triangular distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.triangular.skewness( 0.0, 1.0, 0.8 )\n    ~-0.476\n    > v = base.dists.triangular.skewness( 4.0, 12.0, 5.0 )\n    ~0.532\n    > v = base.dists.triangular.skewness( 2.0, 8.0, 5.0 )\n    0.0\n\n","base.dists.triangular.stdev":"\nbase.dists.triangular.stdev( a, b, c )\n    Returns the standard deviation of a triangular distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.triangular.stdev( 0.0, 1.0, 0.8 )\n    ~0.216\n    > v = base.dists.triangular.stdev( 4.0, 12.0, 5.0 )\n    ~1.78\n    > v = base.dists.triangular.stdev( 2.0, 8.0, 5.0 )\n    ~1.225\n\n","base.dists.triangular.Triangular":"\nbase.dists.triangular.Triangular( [a, b, c] )\n    Returns a triangular distribution object.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support. Must be smaller than `b` and `c`. Default: `0.0`.\n\n    b: number (optional)\n        Maximum support. Must be greater than `a` and `c`. Default: `1.0`.\n\n    c: number (optional)\n        Mode. Must be greater than `a` and smaller than `b`. Default: `0.5`.\n\n    Returns\n    -------\n    triangular: Object\n        Distribution instance.\n\n    triangular.a: number\n        Minimum support. If set, the value must be smaller or equal to `b` and\n        `c`.\n\n    triangular.b: number\n        Maximum support. If set, the value must be greater than or equal to `a`\n        and `c`.\n\n    triangular.c: number\n        Mode. If set, the value must be greater than or equal to `a` and smaller\n        than or equal to `b`.\n\n    triangular.entropy: number\n        Read-only property which returns the differential entropy.\n\n    triangular.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    triangular.mean: number\n        Read-only property which returns the expected value.\n\n    triangular.median: number\n        Read-only property which returns the median.\n\n    triangular.mode: number\n        Read-only property which returns the mode.\n\n    triangular.skewness: number\n        Read-only property which returns the skewness.\n\n    triangular.stdev: number\n        Read-only property which returns the standard deviation.\n\n    triangular.variance: number\n        Read-only property which returns the variance.\n\n    triangular.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    triangular.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    triangular.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    triangular.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    triangular.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    triangular.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var triangular = base.dists.triangular.Triangular( 0.0, 1.0, 0.5 );\n    > triangular.a\n    0.0\n    > triangular.b\n    1.0\n    > triangular.c\n    0.5\n    > triangular.entropy\n    ~-0.193\n    > triangular.kurtosis\n    -0.6\n    > triangular.mean\n    0.5\n    > triangular.median\n    0.5\n    > triangular.mode\n    0.5\n    > triangular.skewness\n    0.0\n    > triangular.stdev\n    ~0.204\n    > triangular.variance\n    ~0.042\n    > triangular.cdf( 0.8 )\n    0.92\n    > triangular.logcdf( 0.8 )\n    ~-0.083\n    > triangular.logpdf( 0.8 )\n    ~-0.223\n    > triangular.mgf( 0.8 )\n    ~1.512\n    > triangular.pdf( 0.8 )\n    ~0.8\n    > triangular.quantile( 0.8 )\n    ~0.684\n\n","base.dists.triangular.variance":"\nbase.dists.triangular.variance( a, b, c )\n    Returns the variance of a triangular distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.triangular.variance( 0.0, 1.0, 0.8 )\n    ~0.047\n    > v = base.dists.triangular.variance( 4.0, 12.0, 5.0 )\n    ~3.167\n    > v = base.dists.triangular.variance( 2.0, 8.0, 5.0 )\n    ~1.5\n\n","base.dists.uniform.cdf":"\nbase.dists.uniform.cdf( x, a, b )\n    Evaluates the cumulative distribution function (CDF) for a uniform\n    distribution with minimum support `a` and maximum support `b` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.uniform.cdf( 9.0, 0.0, 10.0 )\n    0.9\n    > y = base.dists.uniform.cdf( 0.5, 0.0, 2.0 )\n    0.25\n    > y = base.dists.uniform.cdf( PINF, 2.0, 4.0 )\n    1.0\n    > y = base.dists.uniform.cdf( NINF, 2.0, 4.0 )\n    0.0\n    > y = base.dists.uniform.cdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.uniform.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.uniform.cdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.uniform.cdf( 2.0, 1.0, 0.0 )\n    NaN\n\n\nbase.dists.uniform.cdf.factory( a, b )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a uniform distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.uniform.cdf.factory( 0.0, 10.0 );\n    > var y = mycdf( 0.5 )\n    0.05\n    > y = mycdf( 8.0 )\n    0.8\n\n","base.dists.uniform.cdf.factory":"\nbase.dists.uniform.cdf.factory( a, b )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a uniform distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.uniform.cdf.factory( 0.0, 10.0 );\n    > var y = mycdf( 0.5 )\n    0.05\n    > y = mycdf( 8.0 )\n    0.8","base.dists.uniform.entropy":"\nbase.dists.uniform.entropy( a, b )\n    Returns the differential entropy of a uniform distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Differential entropy.\n\n    Examples\n    --------\n    > var v = base.dists.uniform.entropy( 0.0, 1.0 )\n    0.0\n    > v = base.dists.uniform.entropy( 4.0, 12.0 )\n    ~2.079\n    > v = base.dists.uniform.entropy( 2.0, 8.0 )\n    ~1.792\n\n","base.dists.uniform.kurtosis":"\nbase.dists.uniform.kurtosis( a, b )\n    Returns the excess kurtosis of a uniform distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.uniform.kurtosis( 0.0, 1.0 )\n    -1.2\n    > v = base.dists.uniform.kurtosis( 4.0, 12.0 )\n    -1.2\n    > v = base.dists.uniform.kurtosis( 2.0, 8.0 )\n    -1.2\n\n","base.dists.uniform.logcdf":"\nbase.dists.uniform.logcdf( x, a, b )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    uniform distribution with minimum support `a` and maximum support `b` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.uniform.logcdf( 9.0, 0.0, 10.0 )\n    ~-0.105\n    > y = base.dists.uniform.logcdf( 0.5, 0.0, 2.0 )\n    ~-1.386\n    > y = base.dists.uniform.logcdf( PINF, 2.0, 4.0 )\n    0.0\n    > y = base.dists.uniform.logcdf( NINF, 2.0, 4.0 )\n    -Infinity\n    > y = base.dists.uniform.logcdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.uniform.logcdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.uniform.logcdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.uniform.logcdf( 2.0, 1.0, 0.0 )\n    NaN\n\n\nbase.dists.uniform.logcdf.factory( a, b )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a uniform distribution with minimum support\n    `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.uniform.logcdf.factory( 0.0, 10.0 );\n    > var y = mylogcdf( 0.5 )\n    ~-2.996\n    > y = mylogcdf( 8.0 )\n    ~-0.223\n\n","base.dists.uniform.logcdf.factory":"\nbase.dists.uniform.logcdf.factory( a, b )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a uniform distribution with minimum support\n    `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.uniform.logcdf.factory( 0.0, 10.0 );\n    > var y = mylogcdf( 0.5 )\n    ~-2.996\n    > y = mylogcdf( 8.0 )\n    ~-0.223","base.dists.uniform.logpdf":"\nbase.dists.uniform.logpdf( x, a, b )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    uniform distribution with minimum support `a` and maximum support `b` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.uniform.logpdf( 2.0, 0.0, 4.0 )\n    ~-1.386\n    > y = base.dists.uniform.logpdf( 5.0, 0.0, 4.0 )\n    -infinity\n    > y = base.dists.uniform.logpdf( 0.25, 0.0, 1.0 )\n    0.0\n    > y = base.dists.uniform.logpdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.uniform.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.uniform.logpdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.uniform.logpdf( 2.0, 3.0, 1.0 )\n    NaN\n\n\nbase.dists.uniform.logpdf.factory( a, b )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a uniform distribution with minimum support `a` and\n    maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.uniform.logpdf.factory( 6.0, 7.0 );\n    > var y = mylogPDF( 7.0 )\n    0.0\n    > y = mylogPDF( 5.0 )\n    -infinity\n\n","base.dists.uniform.logpdf.factory":"\nbase.dists.uniform.logpdf.factory( a, b )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a uniform distribution with minimum support `a` and\n    maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.uniform.logpdf.factory( 6.0, 7.0 );\n    > var y = mylogPDF( 7.0 )\n    0.0\n    > y = mylogPDF( 5.0 )\n    -infinity","base.dists.uniform.mean":"\nbase.dists.uniform.mean( a, b )\n    Returns the expected value of a uniform distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.uniform.mean( 0.0, 1.0 )\n    0.5\n    > v = base.dists.uniform.mean( 4.0, 12.0 )\n    8.0\n    > v = base.dists.uniform.mean( 2.0, 8.0 )\n    5.0\n\n","base.dists.uniform.median":"\nbase.dists.uniform.median( a, b )\n    Returns the median of a uniform distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.uniform.median( 0.0, 1.0 )\n    0.5\n    > v = base.dists.uniform.median( 4.0, 12.0 )\n    8.0\n    > v = base.dists.uniform.median( 2.0, 8.0 )\n    5.0\n\n","base.dists.uniform.mgf":"\nbase.dists.uniform.mgf( t, a, b )\n    Evaluates the moment-generating function (MGF) for a uniform\n    distribution with minimum support `a` and maximum support `b` at a value\n    `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.uniform.mgf( 2.0, 0.0, 4.0 )\n    ~372.495\n    > y = base.dists.uniform.mgf( -0.2, 0.0, 4.0 )\n    ~0.688\n    > y = base.dists.uniform.mgf( 2.0, 0.0, 1.0 )\n    ~3.195\n    > y = base.dists.uniform.mgf( 0.5, 3.0, 2.0 )\n    NaN\n    > y = base.dists.uniform.mgf( 0.5, 3.0, 3.0 )\n    NaN\n    > y = base.dists.uniform.mgf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.uniform.mgf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.uniform.mgf( 0.0, 0.0, NaN )\n    NaN\n\n\nbase.dists.uniform.mgf.factory( a, b )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a uniform distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.uniform.mgf.factory( 6.0, 7.0 );\n    > var y = mymgf( 0.1 )\n    ~1.916\n    > y = mymgf( 1.1 )\n    ~1339.321\n\n","base.dists.uniform.mgf.factory":"\nbase.dists.uniform.mgf.factory( a, b )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a uniform distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.uniform.mgf.factory( 6.0, 7.0 );\n    > var y = mymgf( 0.1 )\n    ~1.916\n    > y = mymgf( 1.1 )\n    ~1339.321","base.dists.uniform.pdf":"\nbase.dists.uniform.pdf( x, a, b )\n    Evaluates the probability density function (PDF) for a uniform distribution\n    with minimum support `a` and maximum support `b` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.uniform.pdf( 2.0, 0.0, 4.0 )\n    0.25\n    > y = base.dists.uniform.pdf( 5.0, 0.0, 4.0 )\n    0.0\n    > y = base.dists.uniform.pdf( 0.25, 0.0, 1.0 )\n    1.0\n    > y = base.dists.uniform.pdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.uniform.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.uniform.pdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.uniform.pdf( 2.0, 3.0, 1.0 )\n    NaN\n\n\nbase.dists.uniform.pdf.factory( a, b )\n    Returns a function for evaluating the probability density function (PDF) of\n    a uniform distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.uniform.pdf.factory( 6.0, 7.0 );\n    > var y = myPDF( 7.0 )\n    1.0\n    > y = myPDF( 5.0 )\n    0.0\n\n","base.dists.uniform.pdf.factory":"\nbase.dists.uniform.pdf.factory( a, b )\n    Returns a function for evaluating the probability density function (PDF) of\n    a uniform distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.uniform.pdf.factory( 6.0, 7.0 );\n    > var y = myPDF( 7.0 )\n    1.0\n    > y = myPDF( 5.0 )\n    0.0","base.dists.uniform.quantile":"\nbase.dists.uniform.quantile( p, a, b )\n    Evaluates the quantile function for a uniform distribution with minimum\n    support `a` and maximum support `b` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.uniform.quantile( 0.8, 0.0, 1.0 )\n    0.8\n    > y = base.dists.uniform.quantile( 0.5, 0.0, 10.0 )\n    5.0\n\n    > y = base.dists.uniform.quantile( 1.1, 0.0, 1.0 )\n    NaN\n    > y = base.dists.uniform.quantile( -0.2, 0.0, 1.0 )\n    NaN\n\n    > y = base.dists.uniform.quantile( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.uniform.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.uniform.quantile( 0.0, 0.0, NaN )\n    NaN\n\n    > y = base.dists.uniform.quantile( 0.5, 2.0, 1.0 )\n    NaN\n\n\nbase.dists.uniform.quantile.factory( a, b )\n    Returns a function for evaluating the quantile function of a uniform\n    distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.uniform.quantile.factory( 0.0, 4.0 );\n    > var y = myQuantile( 0.8 )\n    3.2\n\n","base.dists.uniform.quantile.factory":"\nbase.dists.uniform.quantile.factory( a, b )\n    Returns a function for evaluating the quantile function of a uniform\n    distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.uniform.quantile.factory( 0.0, 4.0 );\n    > var y = myQuantile( 0.8 )\n    3.2","base.dists.uniform.skewness":"\nbase.dists.uniform.skewness( a, b )\n    Returns the skewness of a uniform distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.uniform.skewness( 0.0, 1.0 )\n    0.0\n    > v = base.dists.uniform.skewness( 4.0, 12.0 )\n    0.0\n    > v = base.dists.uniform.skewness( 2.0, 8.0 )\n    0.0\n\n","base.dists.uniform.stdev":"\nbase.dists.uniform.stdev( a, b )\n    Returns the standard deviation of a uniform distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.uniform.stdev( 0.0, 1.0 )\n    ~0.289\n    > v = base.dists.uniform.stdev( 4.0, 12.0 )\n    ~2.309\n    > v = base.dists.uniform.stdev( 2.0, 8.0 )\n    ~1.732\n\n","base.dists.uniform.Uniform":"\nbase.dists.uniform.Uniform( [a, b] )\n    Returns a uniform distribution object.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support. Must be smaller than `b`. Default: `0.0`.\n\n    b: number (optional)\n        Maximum support. Must be greater than `a`. Default: `1.0`.\n\n    Returns\n    -------\n    uniform: Object\n        Distribution instance.\n\n    uniform.a: number\n        Minimum support. If set, the value must be smaller than `b`.\n\n    uniform.b: number\n        Maximum support. If set, the value must be greater than `a`.\n\n    uniform.entropy: number\n        Read-only property which returns the differential entropy.\n\n    uniform.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    uniform.mean: number\n        Read-only property which returns the expected value.\n\n    uniform.median: number\n        Read-only property which returns the median.\n\n    uniform.skewness: number\n        Read-only property which returns the skewness.\n\n    uniform.stdev: number\n        Read-only property which returns the standard deviation.\n\n    uniform.variance: number\n        Read-only property which returns the variance.\n\n    uniform.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    uniform.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    uniform.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    uniform.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    uniform.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    uniform.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var uniform = base.dists.uniform.Uniform( 0.0, 1.0 );\n    > uniform.a\n    0.0\n    > uniform.b\n    1.0\n    > uniform.entropy\n    0.0\n    > uniform.kurtosis\n    -1.2\n    > uniform.mean\n    0.5\n    > uniform.median\n    0.5\n    > uniform.skewness\n    0.0\n    > uniform.stdev\n    ~0.289\n    > uniform.variance\n    ~0.083\n    > uniform.cdf( 0.8 )\n    0.8\n    > uniform.logcdf( 0.5 )\n    ~-0.693\n    > uniform.logpdf( 1.0 )\n    ~-0.0\n    > uniform.mgf( 0.8 )\n    ~1.532\n    > uniform.pdf( 0.8 )\n    1.0\n    > uniform.quantile( 0.8 )\n    0.8\n\n","base.dists.uniform.variance":"\nbase.dists.uniform.variance( a, b )\n    Returns the variance of a uniform distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.uniform.variance( 0.0, 1.0 )\n    ~0.083\n    > v = base.dists.uniform.variance( 4.0, 12.0 )\n    ~5.333\n    > v = base.dists.uniform.variance( 2.0, 8.0 )\n    3.0\n\n","base.dists.weibull.cdf":"\nbase.dists.weibull.cdf( x, k, λ )\n    Evaluates the cumulative distribution function (CDF) for a Weibull\n    distribution with shape parameter `k` and scale parameter `λ` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a non-positive value for `λ` or `k`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.weibull.cdf( 2.0, 1.0, 1.0 )\n    ~0.865\n    > y = base.dists.weibull.cdf( -1.0, 2.0, 2.0 )\n    0.0\n    > y = base.dists.weibull.cdf( PINF, 4.0, 2.0 )\n    1.0\n    > y = base.dists.weibull.cdf( NINF, 4.0, 2.0 )\n    0.0\n    > y = base.dists.weibull.cdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.weibull.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.weibull.cdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.weibull.cdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.weibull.cdf.factory( k, λ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.weibull.cdf.factory( 2.0, 10.0 );\n    > var y = myCDF( 12.0 )\n    ~0.763\n\n","base.dists.weibull.cdf.factory":"\nbase.dists.weibull.cdf.factory( k, λ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.weibull.cdf.factory( 2.0, 10.0 );\n    > var y = myCDF( 12.0 )\n    ~0.763","base.dists.weibull.entropy":"\nbase.dists.weibull.entropy( k, λ )\n    Returns the differential entropy of a Weibull distribution (in nats).\n\n    If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n    If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.weibull.entropy( 1.0, 1.0 )\n    1.0\n    > v = base.dists.weibull.entropy( 4.0, 12.0 )\n    ~2.532\n    > v = base.dists.weibull.entropy( 8.0, 2.0 )\n    ~0.119\n\n","base.dists.weibull.kurtosis":"\nbase.dists.weibull.kurtosis( k, λ )\n    Returns the excess kurtosis of a Weibull distribution.\n\n    If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n    If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.weibull.kurtosis( 1.0, 1.0 )\n    6.0\n    > v = base.dists.weibull.kurtosis( 4.0, 12.0 )\n    ~-0.252\n    > v = base.dists.weibull.kurtosis( 8.0, 2.0 )\n    ~0.328\n\n","base.dists.weibull.logcdf":"\nbase.dists.weibull.logcdf( x, k, λ )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.weibull.logcdf( 2.0, 1.0, 1.0 )\n    ~-0.145\n    > y = base.dists.weibull.logcdf( -1.0, 2.0, 2.0 )\n    -Infinity\n    > y = base.dists.weibull.logcdf( PINF, 4.0, 2.0 )\n    0.0\n    > y = base.dists.weibull.logcdf( NINF, 4.0, 2.0 )\n    -Infinity\n    > y = base.dists.weibull.logcdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.weibull.logcdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.weibull.logcdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.weibull.logcdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.weibull.logcdf.factory( k, λ)\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Weibull distribution with scale parameter\n    `λ` and shape parameter `k`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.weibull.logcdf.factory( 2.0, 10.0 );\n    > var y = mylogcdf( 12.0 )\n    ~-0.27\n\n","base.dists.weibull.logcdf.factory":"\nbase.dists.weibull.logcdf.factory( k, λ)\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Weibull distribution with scale parameter\n    `λ` and shape parameter `k`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.weibull.logcdf.factory( 2.0, 10.0 );\n    > var y = mylogcdf( 12.0 )\n    ~-0.27","base.dists.weibull.logpdf":"\nbase.dists.weibull.logpdf( x, k, λ )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.weibull.logpdf( 2.0, 1.0, 0.5 )\n    ~-3.307\n    > y = base.dists.weibull.logpdf( 0.1, 1.0, 1.0 )\n    ~-0.1\n    > y = base.dists.weibull.logpdf( -1.0, 4.0, 2.0 )\n    -Infinity\n    > y = base.dists.weibull.logpdf( NaN, 0.6, 1.0 )\n    NaN\n    > y = base.dists.weibull.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.weibull.logpdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.weibull.logpdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.weibull.logpdf.factory( k, λ )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Weibull distribution with shape parameter `k` and scale\n    parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylofpdf = base.dists.weibull.logpdf.factory( 7.0, 6.0 );\n    > y = mylofpdf( 7.0 )\n    ~-1.863\n\n","base.dists.weibull.logpdf.factory":"\nbase.dists.weibull.logpdf.factory( k, λ )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Weibull distribution with shape parameter `k` and scale\n    parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylofpdf = base.dists.weibull.logpdf.factory( 7.0, 6.0 );\n    > y = mylofpdf( 7.0 )\n    ~-1.863","base.dists.weibull.mean":"\nbase.dists.weibull.mean( k, λ )\n    Returns the expected value of a Weibull distribution.\n\n    If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n    If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.weibull.mean( 1.0, 1.0 )\n    1.0\n    > v = base.dists.weibull.mean( 4.0, 12.0 )\n    ~10.877\n    > v = base.dists.weibull.mean( 8.0, 2.0 )\n    ~1.883\n\n","base.dists.weibull.median":"\nbase.dists.weibull.median( k, λ )\n    Returns the median of a Weibull distribution.\n\n    If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n    If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.weibull.median( 1.0, 1.0 )\n    ~0.693\n    > v = base.dists.weibull.median( 4.0, 12.0 )\n    ~10.949\n    > v = base.dists.weibull.median( 8.0, 2.0 )\n    ~1.91\n\n","base.dists.weibull.mgf":"\nbase.dists.weibull.mgf( x, k, λ )\n    Evaluates the moment-generating function (MGF) for a Weibull distribution\n    with shape parameter `k` and scale parameter `λ` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a non-positive value for `λ` or `k`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.weibull.mgf( 1.0, 1.0, 0.5 )\n    ~2.0\n    > y = base.dists.weibull.mgf( -1.0, 4.0, 4.0 )\n    ~0.019\n\n    > y = base.dists.weibull.mgf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.weibull.mgf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.weibull.mgf( 0.0, 1.0, NaN )\n    NaN\n\n    > y = base.dists.weibull.mgf( 0.2, -1.0, 0.5 )\n    NaN\n    > y = base.dists.weibull.mgf( 0.2, 0.0, 0.5 )\n    NaN\n\n    > y = base.dists.weibull.mgf( 0.2, 0.5, -1.0 )\n    NaN\n    > y = base.dists.weibull.mgf( 0.2, 0.5, 0.0 )\n    NaN\n\n\nbase.dists.weibull.mgf.factory( k, λ )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.weibull.mgf.factory( 8.0, 10.0 );\n    > var y = myMGF( 0.8 )\n    ~3150.149\n    > y = myMGF( 0.08 )\n    ~2.137\n\n","base.dists.weibull.mgf.factory":"\nbase.dists.weibull.mgf.factory( k, λ )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.weibull.mgf.factory( 8.0, 10.0 );\n    > var y = myMGF( 0.8 )\n    ~3150.149\n    > y = myMGF( 0.08 )\n    ~2.137","base.dists.weibull.mode":"\nbase.dists.weibull.mode( k, λ )\n    Returns the mode of a Weibull distribution.\n\n    If `0 < k <= 1`, the function returns `0.0`.\n\n    If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n    If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.weibull.mode( 1.0, 1.0 )\n    0.0\n    > v = base.dists.weibull.mode( 4.0, 12.0 )\n    ~11.167\n    > v = base.dists.weibull.mode( 8.0, 2.0 )\n    ~1.967\n\n","base.dists.weibull.pdf":"\nbase.dists.weibull.pdf( x, k, λ )\n    Evaluates the probability density function (PDF) for a Weibull distribution\n    with shape parameter `k` and scale parameter `λ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.weibull.pdf( 2.0, 1.0, 0.5 )\n    ~0.037\n    > y = base.dists.weibull.pdf( 0.1, 1.0, 1.0 )\n    ~0.905\n    > y = base.dists.weibull.pdf( -1.0, 4.0, 2.0 )\n    0.0\n    > y = base.dists.weibull.pdf( NaN, 0.6, 1.0 )\n    NaN\n    > y = base.dists.weibull.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.weibull.pdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.weibull.pdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.weibull.pdf.factory( k, λ )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.weibull.pdf.factory( 7.0, 6.0 );\n    > var y = myPDF( 7.0 )\n    ~0.155\n\n","base.dists.weibull.pdf.factory":"\nbase.dists.weibull.pdf.factory( k, λ )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.weibull.pdf.factory( 7.0, 6.0 );\n    > var y = myPDF( 7.0 )\n    ~0.155","base.dists.weibull.quantile":"\nbase.dists.weibull.quantile( p, k, λ )\n    Evaluates the quantile function for a Weibull distribution with scale\n    parameter `k` and shape parameter `λ` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.weibull.quantile( 0.8, 1.0, 1.0 )\n    ~1.609\n    > y = base.dists.weibull.quantile( 0.5, 2.0, 4.0 )\n    ~3.33\n\n    > y = base.dists.weibull.quantile( 1.1, 1.0, 1.0 )\n    NaN\n    > y = base.dists.weibull.quantile( -0.2, 1.0, 1.0 )\n    NaN\n\n    > y = base.dists.weibull.quantile( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.weibull.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.weibull.quantile( 0.0, 0.0, NaN )\n    NaN\n\n    > y = base.dists.weibull.quantile( 0.5, 1.0, -1.0 )\n    NaN\n\n\nbase.dists.weibull.quantile.factory( k, λ )\n    Returns a function for evaluating the quantile function of a Weibull\n    distribution with scale parameter `k` and shape parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.weibull.quantile.factory( 2.0, 10.0 );\n    > var y = myQuantile( 0.4 )\n    ~7.147\n\n","base.dists.weibull.quantile.factory":"\nbase.dists.weibull.quantile.factory( k, λ )\n    Returns a function for evaluating the quantile function of a Weibull\n    distribution with scale parameter `k` and shape parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.weibull.quantile.factory( 2.0, 10.0 );\n    > var y = myQuantile( 0.4 )\n    ~7.147","base.dists.weibull.skewness":"\nbase.dists.weibull.skewness( k, λ )\n    Returns the skewness of a Weibull distribution.\n\n    If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n    If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.weibull.skewness( 1.0, 1.0 )\n    2.0\n    > v = base.dists.weibull.skewness( 4.0, 12.0 )\n    ~-0.087\n    > v = base.dists.weibull.skewness( 8.0, 2.0 )\n    ~-0.534\n\n","base.dists.weibull.stdev":"\nbase.dists.weibull.stdev( k, λ )\n    Returns the standard deviation of a Weibull distribution.\n\n    If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n    If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.weibull.stdev( 1.0, 1.0 )\n    1.0\n    > v = base.dists.weibull.stdev( 4.0, 12.0 )\n    ~3.051\n    > v = base.dists.weibull.stdev( 8.0, 2.0 )\n    ~0.279\n\n","base.dists.weibull.variance":"\nbase.dists.weibull.variance( k, λ )\n    Returns the variance of a Weibull distribution.\n\n    If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n    If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.weibull.variance( 1.0, 1.0 )\n    1.0\n    > v = base.dists.weibull.variance( 4.0, 12.0 )\n    ~9.311\n    > v = base.dists.weibull.variance( 8.0, 2.0 )\n    ~0.078\n\n","base.dists.weibull.Weibull":"\nbase.dists.weibull.Weibull( [k, λ] )\n    Returns a Weibull distribution object.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n    λ: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    weibull: Object\n        Distribution instance.\n\n    weibull.k: number\n        Shape parameter. If set, the value must be greater than `0`.\n\n    weibull.lambda: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    weibull.entropy: number\n        Read-only property which returns the differential entropy.\n\n    weibull.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    weibull.mean: number\n        Read-only property which returns the expected value.\n\n    weibull.median: number\n        Read-only property which returns the median.\n\n    weibull.mode: number\n        Read-only property which returns the mode.\n\n    weibull.skewness: number\n        Read-only property which returns the skewness.\n\n    weibull.stdev: number\n        Read-only property which returns the standard deviation.\n\n    weibull.variance: number\n        Read-only property which returns the variance.\n\n    weibull.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    weibull.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    weibull.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    weibull.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    weibull.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    weibull.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var weibull = base.dists.weibull.Weibull( 6.0, 5.0 );\n    > weibull.k\n    6.0\n    > weibull.lambda\n    5.0\n    > weibull.entropy\n    ~1.299\n    > weibull.kurtosis\n    ~0.035\n    > weibull.mean\n    ~4.639\n    > weibull.median\n    ~4.704\n    > weibull.mode\n    ~4.85\n    > weibull.skewness\n    ~-0.373\n    > weibull.stdev\n    ~0.899\n    > weibull.variance\n    ~0.808\n    > weibull.cdf( 3.0 )\n    ~0.046\n    > weibull.logcdf( 3.0 )\n    ~-3.088\n    > weibull.logpdf( 1.0 )\n    ~-7.865\n    > weibull.mgf( -0.5 )\n    ~0.075\n    > weibull.pdf( 3.0 )\n    ~0.089\n    > weibull.quantile( 0.8 )\n    ~5.413\n\n","base.ellipe":"\nbase.ellipe( m )\n    Computes the complete elliptic integral of the second kind.\n\n    Parameters\n    ----------\n    m: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.ellipe( 0.5 )\n    ~1.351\n    > y = base.ellipe( -1.0 )\n    ~1.910\n    > y = base.ellipe( 2.0 )\n    NaN\n    > y = base.ellipe( PINF )\n    NaN\n    > y = base.ellipe( NINF )\n    NaN\n    > y = base.ellipe( NaN )\n    NaN\n\n    See Also\n    --------\n    base.ellipj, base.ellipk\n","base.ellipj":"\nbase.ellipj( u, m )\n    Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n    amplitude am.\n\n    Parameters\n    ----------\n    u: number\n        Input value.\n\n    m: number\n        Modulus m, equivalent to k².\n\n    Returns\n    -------\n    out: Array\n        Jacobi elliptic functions and Jacobi amplitude.\n\n    Examples\n    --------\n    > var v = base.ellipj( 0.3, 0.5 )\n    [ ~0.293, ~0.956, ~0.978, ~0.298 ]\n    > v = base.ellipj( 0.0, 0.0 )\n    [ ~0.0, ~1.0, ~1.0, ~0.0 ]\n    > v = base.ellipj( Infinity, 1.0 )\n    [ ~1.0, ~0.0, ~0.0, ~1.571 ]\n    > v = base.ellipj( 0.0, -2.0)\n    [ ~0.0, ~1.0, ~1.0, NaN ]\n    > v = base.ellipj( NaN, NaN )\n    [ NaN, NaN, NaN, NaN ]\n\n\nbase.ellipj.assign( u, m, out, stride, offset )\n    Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n    amplitude am and assigns results to a provided output array.\n\n    Parameters\n    ----------\n    u: number\n        Input value.\n\n    m: number\n        Modulus m, equivalent to k².\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Jacobi elliptic functions and Jacobi amplitude.\n\n    Examples\n    --------\n    > var out = new Float64Array( 4 );\n    > var v = base.ellipj.assign( 0.3, 0.5, out, 1, 0 )\n    <Float64Array>[ ~0.293, ~0.956, ~0.978, ~0.298 ]\n    > var bool = ( v === out )\n    true\n\n\nbase.ellipj.sn( u, m )\n    Computes the Jacobi elliptic function sn.\n\n    Parameters\n    ----------\n    u: number\n        Input value.\n\n    m: number\n        Modulus m, equivalent to k².\n\n    Returns\n    -------\n    out: number\n        Jacobi elliptic function sn.\n\n    Examples\n    --------\n    > var v = base.ellipj.sn( 0.3, 0.5 )\n    ~0.293\n\n\nbase.ellipj.cn( u, m )\n    Computes the Jacobi elliptic functions cn.\n\n    Parameters\n    ----------\n    u: number\n        Input value.\n\n    m: number\n        Modulus m, equivalent to k².\n\n    Returns\n    -------\n    out: number\n        Jacobi elliptic function cn.\n\n    Examples\n    --------\n    > var v = base.ellipj.cn( 0.3, 0.5 )\n    ~0.956\n\n\nbase.ellipj.dn( u, m )\n    Computes the Jacobi elliptic function dn.\n\n    Parameters\n    ----------\n    u: number\n        Input value.\n\n    m: number\n        Modulus m, equivalent to k².\n\n    Returns\n    -------\n    out: number\n        Jacobi elliptic function dn.\n\n    Examples\n    --------\n    > var v = base.ellipj.dn( 0.3, 0.5 )\n    ~0.978\n\n\nbase.ellipj.am( u, m )\n    Computes the Jacobi amplitude am.\n\n    Parameters\n    ----------\n    u: number\n        Input value.\n\n    m: number\n        Modulus m, equivalent to k².\n\n    Returns\n    -------\n    out: number\n        Jacobi elliptic function am.\n\n    Examples\n    --------\n    > var v = base.ellipj.am( 0.3, 0.5 )\n    ~0.298\n\n    See Also\n    --------\n    base.ellipe, base.ellipk","base.ellipj.assign":"\nbase.ellipj.assign( u, m, out, stride, offset )\n    Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n    amplitude am and assigns results to a provided output array.\n\n    Parameters\n    ----------\n    u: number\n        Input value.\n\n    m: number\n        Modulus m, equivalent to k².\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Jacobi elliptic functions and Jacobi amplitude.\n\n    Examples\n    --------\n    > var out = new Float64Array( 4 );\n    > var v = base.ellipj.assign( 0.3, 0.5, out, 1, 0 )\n    <Float64Array>[ ~0.293, ~0.956, ~0.978, ~0.298 ]\n    > var bool = ( v === out )\n    true","base.ellipj.sn":"\nbase.ellipj.sn( u, m )\n    Computes the Jacobi elliptic function sn.\n\n    Parameters\n    ----------\n    u: number\n        Input value.\n\n    m: number\n        Modulus m, equivalent to k².\n\n    Returns\n    -------\n    out: number\n        Jacobi elliptic function sn.\n\n    Examples\n    --------\n    > var v = base.ellipj.sn( 0.3, 0.5 )\n    ~0.293","base.ellipj.cn":"\nbase.ellipj.cn( u, m )\n    Computes the Jacobi elliptic functions cn.\n\n    Parameters\n    ----------\n    u: number\n        Input value.\n\n    m: number\n        Modulus m, equivalent to k².\n\n    Returns\n    -------\n    out: number\n        Jacobi elliptic function cn.\n\n    Examples\n    --------\n    > var v = base.ellipj.cn( 0.3, 0.5 )\n    ~0.956","base.ellipj.dn":"\nbase.ellipj.dn( u, m )\n    Computes the Jacobi elliptic function dn.\n\n    Parameters\n    ----------\n    u: number\n        Input value.\n\n    m: number\n        Modulus m, equivalent to k².\n\n    Returns\n    -------\n    out: number\n        Jacobi elliptic function dn.\n\n    Examples\n    --------\n    > var v = base.ellipj.dn( 0.3, 0.5 )\n    ~0.978","base.ellipj.am":"\nbase.ellipj.am( u, m )\n    Computes the Jacobi amplitude am.\n\n    Parameters\n    ----------\n    u: number\n        Input value.\n\n    m: number\n        Modulus m, equivalent to k².\n\n    Returns\n    -------\n    out: number\n        Jacobi elliptic function am.\n\n    Examples\n    --------\n    > var v = base.ellipj.am( 0.3, 0.5 )\n    ~0.298\n\n    See Also\n    --------\n    base.ellipe, base.ellipk","base.ellipk":"\nbase.ellipk( m )\n    Computes the complete elliptic integral of the first kind.\n\n    Parameters\n    ----------\n    m: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.ellipk( 0.5 )\n    ~1.854\n    > y = base.ellipk( -1.0 )\n    ~1.311\n    > y = base.ellipk( 2.0 )\n    NaN\n    > y = base.ellipk( PINF )\n    NaN\n    > y = base.ellipk( NINF )\n    NaN\n    > y = base.ellipk( NaN )\n    NaN\n\n    See Also\n    --------\n    base.ellipe, base.ellipj\n","base.endsWith":"\nbase.endsWith( str, search, len )\n    Tests if a string ends with the characters of another string.\n\n    If provided an empty search string, the function always returns `true`.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search string.\n\n    len: integer\n        Substring length. Restricts the search to a substring within the input\n        string beginning from the leftmost character. If provided a negative\n        value, `len` indicates to ignore the last `len` characters, and is thus\n        equivalent to `str.length + len`. Default: str.length.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a string ends with the characters of another\n        string.\n\n    Examples\n    --------\n    > var bool = base.endsWith( 'beep', 'ep', 4 )\n    true\n    > bool = base.endsWith( 'Beep', 'op', 4 )\n    false\n    > bool = base.endsWith( 'Beep', 'ee', 3 )\n    true\n    > bool = base.endsWith( 'Beep', 'ee', -1 )\n    true\n    > bool = base.endsWith( 'beep', '', 4 )\n    true\n\n    See Also\n    --------\n    base.startsWith\n","base.epsdiff":"\nbase.epsdiff( x, y[, scale] )\n    Computes the relative difference of two real numbers in units of double-\n    precision floating-point epsilon.\n\n    By default, the function scales the absolute difference by dividing the\n    absolute difference by the maximum absolute value of `x` and `y`. To scale\n    by a different function, specify a scale function name.\n\n    The following `scale` functions are supported:\n\n    - 'max-abs': maximum absolute value of `x` and `y` (default).\n    - 'max': maximum value of `x` and `y`.\n    - 'min-abs': minimum absolute value of `x` and `y`.\n    - 'min': minimum value of `x` and `y`.\n    - 'mean-abs': arithmetic mean of the absolute values of `x` and `y`.\n    - 'mean': arithmetic mean of `x` and `y`.\n    - 'x': `x` (*noncommutative*).\n    - 'y': `y` (*noncommutative*).\n\n    To use a custom scale function, provide a function which accepts two numeric\n    arguments `x` and `y`.\n\n    If computing the relative difference in units of epsilon will result in\n    overflow, the function returns the maximum double-precision floating-point\n    number.\n\n    If the absolute difference of `x` and `y` is `0`, the relative difference is\n    always `0`.\n\n    If `|x| = |y| = infinity`, the function returns `NaN`.\n\n    If `|x| = |-y| = infinity`, the relative difference is `+infinity`.\n\n    If a `scale` function returns `0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    scale: string|Function (optional)\n        Scale function. Default: `'max-abs'`.\n\n    Returns\n    -------\n    out: number\n        Relative difference in units of double-precision floating-point epsilon.\n\n    Examples\n    --------\n    > var d = base.epsdiff( 12.15, 12.149999999999999 )\n    ~0.658\n    > d = base.epsdiff( 2.4341309458983933, 2.4341309458633909, 'mean-abs' )\n    ~64761.512\n\n    // Custom scale function:\n    > function scale( x, y ) { return ( x > y ) ? y : x; };\n    > d = base.epsdiff( 1.0000000000000002, 1.0000000000000100, scale )\n    ~44\n\n    See Also\n    --------\n    base.absdiff, base.reldiff\n","base.erf":"\nbase.erf( x )\n    Evaluates the error function.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    As the error function is an odd function (i.e., `erf(-x) == -erf(x)`), if\n    provided `-0`, the function returns `-0`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.erf( 2.0 )\n    ~0.9953\n    > y = base.erf( -1.0 )\n    ~-0.8427\n    > y = base.erf( -0.0 )\n    -0.0\n    > y = base.erf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.erfc, base.erfinv, base.erfcinv\n","base.erfc":"\nbase.erfc( x )\n    Evaluates the complementary error function.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.erfc( 2.0 )\n    ~0.0047\n    > y = base.erfc( -1.0 )\n    ~1.8427\n    > y = base.erfc( 0.0 )\n    1.0\n    > y = base.erfc( PINF )\n    0.0\n    > y = base.erfc( NINF )\n    2.0\n    > y = base.erfc( NaN )\n    NaN\n\n    See Also\n    --------\n    base.erf, base.erfinv, base.erfcinv, base.erfcx\n","base.erfcinv":"\nbase.erfcinv( x )\n    Evaluates the inverse complementary error function.\n\n    The domain of `x` is restricted to `[0,2]`. If `x` is outside this interval,\n    the function returns `NaN`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.erfcinv( 0.5 )\n    ~0.4769\n    > y = base.erfcinv( 0.8 )\n    ~0.1791\n    > y = base.erfcinv( 0.0 )\n    Infinity\n    > y = base.erfcinv( 2.0 )\n    -Infinity\n    > y = base.erfcinv( NaN )\n    NaN\n\n    See Also\n    --------\n    base.erf, base.erfc, base.erfinv, base.erfcx\n","base.erfcx":"\nbase.erfcx( x )\n    Evaluates the scaled complementary error function.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.erfcx( 1.0 )\n    ~0.4276\n    > y = base.erfcx( -1.0 )\n    ~5.01\n    > y = base.erfcx( 0.0 )\n    1.0\n    > y = base.erfcx( NaN )\n    NaN\n\n    See Also\n    --------\n    base.erfc, base.erfcinv, base.erf, base.erfinv","base.erfinv":"\nbase.erfinv( x )\n    Evaluates the inverse error function.\n\n    If `|x| > 1`, the function returns `NaN`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    As the inverse error function is an odd function (i.e., `erfinv(-x) ==\n    -erfinv(x)`), if provided `-0`, the function returns `-0`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.erfinv( 0.5 )\n    ~0.4769\n    > y = base.erfinv( 0.8 )\n    ~0.9062\n    > y = base.erfinv( 0.0 )\n    0.0\n    > y = base.erfinv( -0.0 )\n    -0.0\n    > y = base.erfinv( -1.0 )\n    -Infinity\n    > y = base.erfinv( 1.0 )\n    Infinity\n    > y = base.erfinv( NaN )\n    NaN\n\n    See Also\n    --------\n    base.erf, base.erfc, base.erfcinv\n","base.eta":"\nbase.eta( s )\n    Evaluates the Dirichlet eta function for a double-precision\n    floating-point number `s`.\n\n    Parameters\n    ----------\n    s: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.eta( 0.0 )\n    0.5\n    > y = base.eta( -1.0 )\n    0.25\n    > y = base.eta( 1.0 )\n    ~0.6931\n    > y = base.eta( 3.14 )\n    ~0.9096\n    > y = base.eta( NaN )\n    NaN\n\n","base.evalpoly":"\nbase.evalpoly( c, x )\n    Evaluates a polynomial using double-precision floating-point arithmetic.\n\n    Parameters\n    ----------\n    c: Array<number>\n        Polynomial coefficients sorted in ascending degree.\n\n    x: number\n        Value at which to evaluate the polynomial.\n\n    Returns\n    -------\n    out: number\n        Evaluated polynomial.\n\n    Examples\n    --------\n    > var arr = [ 3.0, 2.0, 1.0 ];\n\n    // 3*10^0 + 2*10^1 + 1*10^2\n    > var v = base.evalpoly( arr, 10.0 )\n    123.0\n\n\nbase.evalpoly.factory( c )\n    Returns a function for evaluating a polynomial using double-precision\n    floating-point arithmetic.\n\n    Parameters\n    ----------\n    c: Array<number>\n        Polynomial coefficients sorted in ascending degree.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a polynomial.\n\n    Examples\n    --------\n    > var f = base.evalpoly.factory( [ 3.0, 2.0, 1.0 ] );\n\n    // 3*10^0 + 2*10^1 + 1*10^2\n    > var v = f( 10.0 )\n    123.0\n\n    // 3*5^0 + 2*5^1 + 1*5^2\n    > v = f( 5.0 )\n    38.0\n\n    See Also\n    --------\n    base.evalrational\n","base.evalpoly.factory":"\nbase.evalpoly.factory( c )\n    Returns a function for evaluating a polynomial using double-precision\n    floating-point arithmetic.\n\n    Parameters\n    ----------\n    c: Array<number>\n        Polynomial coefficients sorted in ascending degree.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a polynomial.\n\n    Examples\n    --------\n    > var f = base.evalpoly.factory( [ 3.0, 2.0, 1.0 ] );\n\n    // 3*10^0 + 2*10^1 + 1*10^2\n    > var v = f( 10.0 )\n    123.0\n\n    // 3*5^0 + 2*5^1 + 1*5^2\n    > v = f( 5.0 )\n    38.0\n\n    See Also\n    --------\n    base.evalrational","base.evalrational":"\nbase.evalrational( P, Q, x )\n    Evaluates a rational function using double-precision floating-point\n    arithmetic.\n\n    A rational function `f(x)` is defined as\n\n               P(x)\n        f(x) = ----\n               Q(x)\n\n    where both `P(x)` and `Q(x)` are polynomials in `x`.\n\n    The coefficients for both `P` and `Q` should be sorted in ascending degree.\n\n    For polynomials of different degree, the coefficient array for the lower\n    degree polynomial should be padded with zeros.\n\n    Parameters\n    ----------\n    P: Array<number>\n        Numerator polynomial coefficients sorted in ascending degree.\n\n    Q: Array<number>\n        Denominator polynomial coefficients sorted in ascending degree.\n\n    x: number\n        Value at which to evaluate the rational function.\n\n    Returns\n    -------\n    out: number\n        Evaluated rational function.\n\n    Examples\n    --------\n    // 2x^3 + 4x^2 - 5x^1 - 6x^0\n    > var P = [ -6.0, -5.0, 4.0, 2.0 ];\n\n    // 0.5x^1 + 3x^0\n    > var Q = [ 3.0, 0.5, 0.0, 0.0 ]; // zero-padded\n\n    // Evaluate the rational function:\n    > var v = base.evalrational( P, Q, 6.0 )\n    90.0\n\n\nbase.evalrational.factory( P, Q )\n    Returns a function for evaluating a rational function using double-precision\n    floating-point arithmetic.\n\n    Parameters\n    ----------\n    P: Array<number>\n        Numerator polynomial coefficients sorted in ascending degree.\n\n    Q: Array<number>\n        Denominator polynomial coefficients sorted in ascending degree.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a rational function.\n\n    Examples\n    --------\n    > var P = [ 20.0, 8.0, 3.0 ];\n    > var Q = [ 10.0, 9.0, 1.0 ];\n    > var f = base.evalrational.factory( P, Q );\n\n    // (20*10^0 + 8*10^1 + 3*10^2) / (10*10^0 + 9*10^1 + 1*10^2):\n    > var v = f( 10.0 )\n    2.0\n\n    // (20*2^0 + 8*2^1 + 3*2^2) / (10*2^0 + 9*2^1 + 1*2^2):\n    > v = f( 2.0 )\n    1.5\n\n    See Also\n    --------\n    base.evalpoly\n","base.evalrational.factory":"\nbase.evalrational.factory( P, Q )\n    Returns a function for evaluating a rational function using double-precision\n    floating-point arithmetic.\n\n    Parameters\n    ----------\n    P: Array<number>\n        Numerator polynomial coefficients sorted in ascending degree.\n\n    Q: Array<number>\n        Denominator polynomial coefficients sorted in ascending degree.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a rational function.\n\n    Examples\n    --------\n    > var P = [ 20.0, 8.0, 3.0 ];\n    > var Q = [ 10.0, 9.0, 1.0 ];\n    > var f = base.evalrational.factory( P, Q );\n\n    // (20*10^0 + 8*10^1 + 3*10^2) / (10*10^0 + 9*10^1 + 1*10^2):\n    > var v = f( 10.0 )\n    2.0\n\n    // (20*2^0 + 8*2^1 + 3*2^2) / (10*2^0 + 9*2^1 + 1*2^2):\n    > v = f( 2.0 )\n    1.5\n\n    See Also\n    --------\n    base.evalpoly","base.exp":"\nbase.exp( x )\n    Evaluates the natural exponential function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.exp( 4.0 )\n    ~54.5982\n    > y = base.exp( -9.0 )\n    ~1.234e-4\n    > y = base.exp( 0.0 )\n    1.0\n    > y = base.exp( NaN )\n    NaN\n\n    See Also\n    --------\n    base.exp10, base.exp2, base.expm1, base.ln\n","base.exp2":"\nbase.exp2( x )\n    Evaluates the base 2 exponential function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.exp2( 3.0 )\n    8.0\n    > y = base.exp2( -9.0 )\n    ~0.002\n    > y = base.exp2( 0.0 )\n    1.0\n    > y = base.exp2( NaN )\n    NaN\n\n    See Also\n    --------\n    base.exp, base.exp10, base.log2\n","base.exp10":"\nbase.exp10( x )\n    Evaluates the base 10 exponential function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.exp10( 3.0 )\n    1000\n    > y = base.exp10( -9.0 )\n    1.0e-9\n    > y = base.exp10( 0.0 )\n    1.0\n    > y = base.exp10( NaN )\n    NaN\n\n    See Also\n    --------\n    base.exp, base.exp2, base.log10\n","base.expit":"\nbase.expit( x )\n    Evaluates the standard logistic function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.expit( 0.0 )\n    0.5\n    > y = base.expit( 1.0 )\n    ~0.731\n    > y = base.expit( -1.0 )\n    ~0.269\n    > y = base.expit( Infinity )\n    1.0\n    > y = base.expit( NaN )\n    NaN\n\n    See Also\n    --------\n    base.exp, base.logit","base.expm1":"\nbase.expm1( x )\n    Computes `exp(x)-1`, where `exp(x)` is the natural exponential function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.expm1( 0.2 )\n    ~0.221\n    > y = base.expm1( -9.0 )\n    ~-1.0\n    > y = base.expm1( 0.0 )\n    0.0\n    > y = base.expm1( NaN )\n    NaN\n\n    See Also\n    --------\n    base.exp, base.expm1rel\n","base.expm1rel":"\nbase.expm1rel( x )\n    Relative error exponential.\n\n    When `x` is near zero,\n\n        e^x - 1\n\n    can suffer catastrophic cancellation (i.e., significant loss of precision).\n    This function avoids the loss of precision when `x` is near zero.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.expm1rel( 0.0 )\n    1.0\n    > y = base.expm1rel( 1.0 )\n    ~1.718\n    > y = base.expm1rel( -1.0 )\n    ~0.632\n    > y = base.expm1rel( NaN )\n    NaN\n\t\n    See Also\n    --------\n    base.exp, base.expm1\n","base.exponent":"\nbase.exponent( x )\n    Returns an integer corresponding to the unbiased exponent of a double-\n    precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    Returns\n    -------\n    out: integer\n        Unbiased exponent.\n\n    Examples\n    --------\n    > var exponent = base.exponent( 3.14e-307 )\n    -1019\n    > exponent = base.exponent( -3.14 )\n    1\n    > exponent = base.exponent( 0.0 )\n    -1023\n    > exponent = base.exponent( NaN )\n    1024\n\n    See Also\n    --------\n    base.exponentf\n","base.exponentf":"\nbase.exponentf( x )\n    Returns an integer corresponding to the unbiased exponent of a single-\n    precision floating-point number.\n\n    Parameters\n    ----------\n    x: float\n        Single-precision floating-point number.\n\n    Returns\n    -------\n    out: integer\n        Unbiased exponent.\n\n    Examples\n    --------\n    > var exponent = base.exponentf( base.float64ToFloat32( 3.14e34 ) )\n    114\n    > exponent = base.exponentf( base.float64ToFloat32( 3.14e-34 ) )\n    -112\n    > exponent = base.exponentf( base.float64ToFloat32( -3.14 ) )\n    1\n    > exponent = base.exponentf( 0.0 )\n    -127\n    > exponent = base.exponentf( NaN )\n    128\n\n    See Also\n    --------\n    base.exponent\n","base.factorial":"\nbase.factorial( x )\n    Evaluates the factorial of `x`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Factorial.\n\n    Examples\n    --------\n    > var y = base.factorial( 3.0 )\n    6.0\n    > y = base.factorial( -1.5 )\n    ~-3.545\n    > y = base.factorial( -0.5 )\n    ~1.772\n    > y = base.factorial( 0.5 )\n    ~0.886\n    > y = base.factorial( -10.0 )\n    NaN\n    > y = base.factorial( 171.0 )\n    Infinity\n    > y = base.factorial( NaN )\n    NaN\n\n    See Also\n    --------\n    base.factorialln\n","base.factorial2":"\nbase.factorial2( n )\n    Evaluates the double factorial of `n`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Double factorial.\n\n    Examples\n    --------\n    > var y = base.factorial2( 3 )\n    3\n    > y = base.factorial2( 5 )\n    15\n    > y = base.factorial2( 6 )\n    48\n    > y = base.factorial2( 301 )\n    Infinity\n    > y = base.factorial2( NaN )\n    NaN\n\n    See Also\n    --------\n    base.factorial\n","base.factorialln":"\nbase.factorialln( x )\n    Evaluates the natural logarithm of the factorial of `x`.\n\n    For input values other than negative integers, the function returns\n\n      ln( x! ) = ln( Γ(x+1) )\n\n    where `Γ` is the Gamma function. For negative integers, the function returns\n    `NaN`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Natural logarithm of the factorial of `x`.\n\n    Examples\n    --------\n    > var y = base.factorialln( 3.0 )\n    ~1.792\n    > y = base.factorialln( 2.4 )\n    ~1.092\n    > y = base.factorialln( -1.0 )\n    NaN\n    > y = base.factorialln( -1.5 )\n    ~1.266\n    > y = base.factorialln( NaN )\n    NaN\n\n    See Also\n    --------\n    base.factorial\n","base.fallingFactorial":"\nbase.fallingFactorial( x, n )\n    Computes the falling factorial of `x` and `n`.\n\n    If not provided a nonnegative integer for `n`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        First function parameter.\n\n    n: integer\n        Second function parameter.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var v = base.fallingFactorial( 0.9, 5 )\n    ~0.644\n    > v = base.fallingFactorial( -9.0, 3 )\n    -990.0\n    > v = base.fallingFactorial( 0.0, 2 )\n    0.0\n    > v = base.fallingFactorial( 3.0, -2 )\n    NaN\n\n    See Also\n    --------\n    base.risingFactorial\n","base.fibonacci":"\nbase.fibonacci( n )\n    Computes the nth Fibonacci number.\n\n    Fibonacci numbers follow the recurrence relation\n\n      F_n = F_{n-1} + F_{n-2}\n\n    with seed values F_0 = 0 and F_1 = 1.\n\n    If `n` is greater than `78`, the function returns `NaN`, as larger Fibonacci\n    numbers cannot be accurately represented due to limitations of double-\n    precision floating-point format.\n\n    If not provided a nonnegative integer value, the function returns `NaN`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Input value.\n\n    Returns\n    -------\n    y: integer\n        Fibonacci number.\n\n    Examples\n    --------\n    > var y = base.fibonacci( 0 )\n    0\n    > y = base.fibonacci( 1 )\n    1\n    > y = base.fibonacci( 2 )\n    1\n    > y = base.fibonacci( 3 )\n    2\n    > y = base.fibonacci( 4 )\n    3\n    > y = base.fibonacci( 79 )\n    NaN\n    > y = base.fibonacci( NaN )\n    NaN\n\n    See Also\n    --------\n    base.binet, base.fibonacciIndex, base.lucas, base.negafibonacci\n","base.fibonacciIndex":"\nbase.fibonacciIndex( F )\n    Computes the Fibonacci number index.\n\n    If not provided a nonnegative integer value, the function returns `NaN`.\n\n    If provided `F <= 1` or `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    F: integer\n        Fibonacci number.\n\n    Returns\n    -------\n    n: number\n        Fibonacci number index.\n\n    Examples\n    --------\n    > var n = base.fibonacciIndex( 2 )\n    3\n    > n = base.fibonacciIndex( 3 )\n    4\n    > n = base.fibonacciIndex( 5 )\n    5\n    > n = base.fibonacciIndex( NaN )\n    NaN\n    > n = base.fibonacciIndex( 1 )\n    NaN\n\n    See Also\n    --------\n    base.fibonacci\n","base.fibpoly":"\nbase.fibpoly( n, x )\n    Evaluates a Fibonacci polynomial.\n\n    Parameters\n    ----------\n    n: integer\n        Fibonacci polynomial to evaluate.\n\n    x: number\n        Value at which to evaluate the Fibonacci polynomial.\n\n    Returns\n    -------\n    out: number\n        Evaluated Fibonacci polynomial.\n\n    Examples\n    --------\n    // 2^4 + 3*2^2 + 1\n    > var v = base.fibpoly( 5, 2.0 )\n    29.0\n\n\nbase.fibpoly.factory( n )\n    Returns a function for evaluating a Fibonacci polynomial.\n\n    Parameters\n    ----------\n    n: integer\n        Fibonacci polynomial to evaluate.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a Fibonacci polynomial.\n\n    Examples\n    --------\n    > var polyval = base.fibpoly.factory( 5 );\n\n    // 1^4 + 3*1^2 + 1\n    > var v = polyval( 1.0 )\n    5.0\n\n    // 2^4 + 3*2^2 + 1\n    > v = polyval( 2.0 )\n    29.0\n\n    See Also\n    --------\n    base.evalpoly, base.lucaspoly\n","base.fibpoly.factory":"\nbase.fibpoly.factory( n )\n    Returns a function for evaluating a Fibonacci polynomial.\n\n    Parameters\n    ----------\n    n: integer\n        Fibonacci polynomial to evaluate.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a Fibonacci polynomial.\n\n    Examples\n    --------\n    > var polyval = base.fibpoly.factory( 5 );\n\n    // 1^4 + 3*1^2 + 1\n    > var v = polyval( 1.0 )\n    5.0\n\n    // 2^4 + 3*2^2 + 1\n    > v = polyval( 2.0 )\n    29.0\n\n    See Also\n    --------\n    base.evalpoly, base.lucaspoly","base.firstCodePoint":"\nbase.firstCodePoint( str, n )\n    Returns the first `n` Unicode code points of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of Unicode code points to return.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.firstCodePoint( 'beep', 1 )\n    'b'\n    > out = base.firstCodePoint( 'Boop', 1 )\n    'B'\n    > out = base.firstCodePoint( 'foo bar', 5 )\n    'foo b'\n\n    See Also\n    --------\n    base.firstCodeUnit, base.firstGraphemeCluster, base.lastCodePoint, base.removeFirstCodePoint, firstChar\n","base.firstCodeUnit":"\nbase.firstCodeUnit( str, n )\n    Returns the first `n` UTF-16 code units of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of UTF-16 code units to return.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.firstCodeUnit( 'beep', 1 )\n    'b'\n    > out = base.firstCodeUnit( 'Boop', 1 )\n    'B'\n    > out = base.firstCodeUnit( 'foo bar', 5 )\n    'foo b'\n\n    See Also\n    --------\n    base.firstCodePoint, base.firstGraphemeCluster, base.last, base.removeFirst, firstChar\n","base.firstGraphemeCluster":"\nbase.firstGraphemeCluster( str, n )\n    Returns the first `n` grapheme clusters (i.e., user-perceived characters) of\n    a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of grapheme clusters to return.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.firstGraphemeCluster( 'beep', 1 )\n    'b'\n    > out = base.firstGraphemeCluster( 'Boop', 1 )\n    'B'\n    > out = base.firstGraphemeCluster( 'foo bar', 5 )\n    'foo b'\n\n    See Also\n    --------\n    base.firstCodeUnit, base.firstCodePoint, base.lastGraphemeCluster, base.removeFirstGraphemeCluster, firstChar\n","base.flipsign":"\nbase.flipsign( x, y )\n    Returns a double-precision floating-point number with the magnitude of `x`\n    and the sign of `x*y`.\n\n    The function only returns `-x` when `y` is a negative number.\n\n    According to the IEEE 754 standard, a `NaN` has a biased exponent equal to\n    `2047`, a significand greater than `0`, and a sign bit equal to either `1`\n    or `0`. In which case, `NaN` may not correspond to just one but many binary\n    representations. Accordingly, care should be taken to ensure that `y` is not\n    `NaN`; otherwise, behavior may be indeterminate.\n\n    Parameters\n    ----------\n    x: number\n        Number from which to derive a magnitude.\n\n    y: number\n        Number from which to derive a sign.\n\n    Returns\n    -------\n    z: number\n        Double-precision floating-point number.\n\n    Examples\n    --------\n    > var z = base.flipsign( -3.0, 10.0 )\n    -3.0\n    > z = base.flipsign( -3.0, -1.0 )\n    3.0\n    > z = base.flipsign( 1.0, -0.0 )\n    -1.0\n    > z = base.flipsign( -3.0, -0.0 )\n    3.0\n    > z = base.flipsign( -0.0, 1.0 )\n    -0.0\n    > z = base.flipsign( 0.0, -1.0 )\n    -0.0\n\n    See Also\n    --------\n    base.copysign\n","base.flipsignf":"\nbase.flipsignf( x, y )\n    Returns a single-precision floating-point number with the magnitude of `x`\n    and the sign of `x*y`.\n\n    The function only returns `-x` when `y` is a negative number.\n\n    According to the IEEE 754 standard, a `NaN` has a biased exponent equal to\n    `255`, a significand greater than `0`, and a sign bit equal to either `1` or\n    `0`. In which case, `NaN` may not correspond to just one but many binary\n    representations. Accordingly, care should be taken to ensure that `y` is not\n    `NaN`; otherwise, behavior may be indeterminate.\n\n    Parameters\n    ----------\n    x: number\n        Number from which to derive a magnitude.\n\n    y: number\n        Number from which to derive a sign.\n\n    Returns\n    -------\n    z: number\n        Single-precision floating-point number.\n\n    Examples\n    --------\n    > var z = base.flipsignf( -3.0, 10.0 )\n    -3.0\n    > z = base.flipsignf( -3.0, -1.0 )\n    3.0\n    > z = base.flipsignf( 1.0, -0.0 )\n    -1.0\n    > z = base.flipsignf( -3.0, -0.0 )\n    3.0\n    > z = base.flipsignf( -0.0, 1.0 )\n    -0.0\n    > z = base.flipsignf( 0.0, -1.0 )\n    -0.0\n\n    See Also\n    --------\n    base.copysignf, base.flipsign\n","base.float32ToInt32":"\nbase.float32ToInt32( x )\n    Converts a single-precision floating-point number to a signed 32-bit\n    integer.\n\n    Parameters\n    ----------\n    x: float\n        Single-precision floating-point number.\n\n    Returns\n    -------\n    out: integer\n        Signed 32-bit integer.\n\n    Examples\n    --------\n    > var y = base.float32ToInt32( base.float64ToFloat32( 4294967295.0 ) )\n    0\n    > y = base.float32ToInt32( base.float64ToFloat32( 3.14 ) )\n    3\n    > y = base.float32ToInt32( base.float64ToFloat32( -3.14 ) )\n    -3\n    > y = base.float32ToInt32( base.float64ToFloat32( NaN ) )\n    0\n    > y = base.float32ToInt32( FLOAT32_PINF )\n    0\n    > y = base.float32ToInt32( FLOAT32_NINF )\n    0\n\n    See Also\n    --------\n    base.float32ToUint32","base.float32ToUint32":"\nbase.float32ToUint32( x )\n    Converts a single-precision floating-point number to a unsigned 32-bit\n    integer.\n\n    Parameters\n    ----------\n    x: float\n        Single-precision floating-point number.\n\n    Returns\n    -------\n    out: integer\n        Unsigned 32-bit integer.\n\n    Examples\n    --------\n    > var y = base.float32ToUint32( base.float64ToFloat32( 4294967297.0 ) )\n    0\n    > y = base.float32ToUint32( base.float64ToFloat32( 3.14 ) )\n    3\n    > y = base.float32ToUint32( base.float64ToFloat32( -3.14 ) )\n    4294967293\n    > y = base.float32ToUint32( base.float64ToFloat32( NaN ) )\n    0\n    > y = base.float32ToUint32( FLOAT32_PINF )\n    0\n    > y = base.float32ToUint32( FLOAT32_NINF )\n    0\n\n    See Also\n    --------\n    base.float32ToInt32","base.float64ToFloat32":"\nbase.float64ToFloat32( x )\n    Converts a double-precision floating-point number to the nearest single-\n    precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    Returns\n    -------\n    out: float\n        Nearest single-precision floating-point number.\n\n    Examples\n    --------\n    > var y = base.float64ToFloat32( 1.337 )\n    1.3370000123977661\n","base.float64ToInt32":"\nbase.float64ToInt32( x )\n    Converts a double-precision floating-point number to a signed 32-bit\n    integer.\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    Returns\n    -------\n    out: integer\n        Signed 32-bit integer.\n\n    Examples\n    --------\n    > var y = base.float64ToInt32( 4294967295.0 )\n    -1\n    > y = base.float64ToInt32( 3.14 )\n    3\n    > y = base.float64ToInt32( -3.14 )\n    -3\n    > y = base.float64ToInt32( NaN )\n    0\n    > y = base.float64ToInt32( PINF )\n    0\n    > y = base.float64ToInt32( NINF )\n    0\n\n    See Also\n    --------\n    base.float64ToUint32","base.float64ToInt64Bytes":"\nbase.float64ToInt64Bytes( x )\n    Converts an integer-valued double-precision floating-point number to a\n    signed 64-bit integer byte array according to host byte order (endianness).\n\n    This function assumes that the input value is less than the maximum safe\n    double-precision floating-point integer plus one (i.e., `2**53`).\n\n    Parameters\n    ----------\n    x: integer\n        Integer-valued double-precision floating-point number.\n\n    Returns\n    -------\n    out: Uint8Array\n        Byte array.\n\n    Examples\n    --------\n    > var y = base.float64ToInt64Bytes( 4294967297.0 )\n    <Uint8Array>\n\n\nbase.float64ToInt64Bytes.assign( x, out, stride, offset )\n    Converts an integer-valued double-precision floating-point number to a\n    signed 64-bit integer byte array according to host byte order (endianness)\n    and assigns results to a provided output array.\n\n    This function assumes that the input value is less than the maximum safe\n    double-precision floating-point integer plus one (i.e., `2**53`).\n\n    Parameters\n    ----------\n    x: integer\n        Integer-valued double-precision floating-point number.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Output array.\n\n    Examples\n    --------\n    > var out = new Uint8Array( 16 );\n    > var y = base.float64ToInt64Bytes( 4294967297.0, out, 2, 1 )\n    <Uint8Array>\n\n    See Also\n    --------\n    base.float64ToInt32","base.float64ToInt64Bytes.assign":"\nbase.float64ToInt64Bytes.assign( x, out, stride, offset )\n    Converts an integer-valued double-precision floating-point number to a\n    signed 64-bit integer byte array according to host byte order (endianness)\n    and assigns results to a provided output array.\n\n    This function assumes that the input value is less than the maximum safe\n    double-precision floating-point integer plus one (i.e., `2**53`).\n\n    Parameters\n    ----------\n    x: integer\n        Integer-valued double-precision floating-point number.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Output array.\n\n    Examples\n    --------\n    > var out = new Uint8Array( 16 );\n    > var y = base.float64ToInt64Bytes( 4294967297.0, out, 2, 1 )\n    <Uint8Array>\n\n    See Also\n    --------\n    base.float64ToInt32","base.float64ToUint32":"\nbase.float64ToUint32( x )\n    Converts a double-precision floating-point number to a unsigned 32-bit\n    integer.\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    Returns\n    -------\n    out: integer\n        Unsigned 32-bit integer.\n\n    Examples\n    --------\n    > var y = base.float64ToUint32( 4294967297.0 )\n    1\n    > y = base.float64ToUint32( 3.14 )\n    3\n    > y = base.float64ToUint32( -3.14 )\n    4294967293\n    > y = base.float64ToUint32( NaN )\n    0\n    > y = base.float64ToUint32( PINF )\n    0\n    > y = base.float64ToUint32( NINF )\n    0\n\n    See Also\n    --------\n    base.float64ToInt32","base.floor":"\nbase.floor( x )\n    Rounds a double-precision floating-point number toward negative infinity.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.floor( 3.14 )\n    3.0\n    > y = base.floor( -4.2 )\n    -5.0\n    > y = base.floor( -4.6 )\n    -5.0\n    > y = base.floor( 9.5 )\n    9.0\n    > y = base.floor( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceil, base.round\n","base.floor2":"\nbase.floor2( x )\n    Rounds a numeric value to the nearest power of two toward negative infinity.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.floor2( 3.14 )\n    2.0\n    > y = base.floor2( -4.2 )\n    -8.0\n    > y = base.floor2( -4.6 )\n    -8.0\n    > y = base.floor2( 9.5 )\n    8.0\n    > y = base.floor2( 13.0 )\n    8.0\n    > y = base.floor2( -13.0 )\n    -16.0\n    > y = base.floor2( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceil2, base.floor, base.floor10, base.round2\n","base.floor10":"\nbase.floor10( x )\n    Rounds a numeric value to the nearest power of ten toward negative infinity.\n\n    The function may not return accurate results for subnormals due to a general\n    loss in precision.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.floor10( 3.14 )\n    1.0\n    > y = base.floor10( -4.2 )\n    -10.0\n    > y = base.floor10( -4.6 )\n    -10.0\n    > y = base.floor10( 9.5 )\n    1.0\n    > y = base.floor10( 13.0 )\n    10.0\n    > y = base.floor10( -13.0 )\n    -100.0\n    > y = base.floor10( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceil10, base.floor, base.floor2, base.round10\n","base.floorb":"\nbase.floorb( x, n, b )\n    Rounds a numeric value to the nearest multiple of `b^n` toward negative\n    infinity.\n\n    Due to floating-point rounding error, rounding may not be exact.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Integer power.\n\n    b: integer\n        Base.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    // Round to 4 decimal places:\n    > var y = base.floorb( 3.14159, -4, 10 )\n    3.1415\n\n    // If `n = 0` or `b = 1`, standard round behavior:\n    > y = base.floorb( 3.14159, 0, 2 )\n    3.0\n\n    // Round to nearest multiple of two toward negative infinity:\n    > y = base.floorb( 5.0, 1, 2 )\n    4.0\n\n    See Also\n    --------\n    base.ceilb, base.floor, base.floorn, base.roundb\n","base.floorf":"\nbase.floorf( x )\n    Rounds a single-precision floating-point number toward negative infinity.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.floorf( 3.14 )\n    3.0\n    > y = base.floorf( -4.2 )\n    -5.0\n    > y = base.floorf( -4.6 )\n    -5.0\n    > y = base.floorf( 9.5 )\n    9.0\n    > y = base.floorf( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceilf, base.floor\n","base.floorn":"\nbase.floorn( x, n )\n    Rounds a double-precision floating-point number to the nearest multiple of\n    `10^n` toward negative infinity.\n\n    When operating on floating-point numbers in bases other than `2`, rounding\n    to specified digits can be inexact.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Integer power of 10.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    // Round to 4 decimal places:\n    > var y = base.floorn( 3.14159, -4 )\n    3.1415\n\n    // If `n = 0`, standard round toward negative infinity behavior:\n    > y = base.floorn( 3.14159, 0 )\n    3.0\n\n    // Round to nearest thousand:\n    > y = base.floorn( 12368.0, 3 )\n    12000.0\n\n\n    See Also\n    --------\n    base.ceiln, base.floor, base.floorb, base.roundn\n","base.floorsd":"\nbase.floorsd( x, n, b )\n    Rounds a numeric value to the nearest number toward negative infinity with\n    `n` significant figures.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Number of significant figures. Must be greater than 0.\n\n    b: integer\n        Base. Must be greater than 0.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.floorsd( 3.14159, 5, 10 )\n    3.1415\n    > y = base.floorsd( 3.14159, 1, 10 )\n    3.0\n    > y = base.floorsd( 12368.0, 2, 10 )\n    12000.0\n    > y = base.floorsd( 0.0313, 2, 2 )\n    0.03125\n\n    See Also\n    --------\n    base.ceilsd, base.floor, base.roundsd, base.truncsd\n","base.forEachChar":"\nbase.forEachChar( str, clbk[, thisArg] )\n    Invokes a function for each UTF-16 code unit in a string.\n\n    When invoked, the provided function is provided three arguments:\n\n    - value: character.\n    - index: character index.\n    - str: input string.\n\n    Parameters\n    ----------\n    str: string\n        Input string over which to iterate.\n\n    clbk: Function\n        The function to invoke for each UTF-16 code unit in the input string.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: string\n        Input string.\n\n    Examples\n    --------\n    > var n = 0;\n    > function fcn() { n += 1; };\n    > base.forEachChar( 'hello world!', fcn );\n    > n\n    12\n\n    See Also\n    --------\n    base.forEachCodePoint, base.forEachGraphemeCluster, forEachChar\n","base.forEachCodePoint":"\nbase.forEachCodePoint( str, clbk[, thisArg] )\n    Invokes a function for each Unicode code point in a string.\n\n    When invoked, the provided function is provided three arguments:\n\n    - value: code point.\n    - index: starting code point index.\n    - str: input string.\n\n    Parameters\n    ----------\n    str: string\n        Input string over which to iterate.\n\n    clbk: Function\n        The function to invoke for each Unicode code point in the input string.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: string\n        Input string.\n\n    Examples\n    --------\n    > var n = 0;\n    > function fcn() { n += 1; };\n    > base.forEachCodePoint( 'hello world!', fcn );\n    > n\n    12\n\n    See Also\n    --------\n    base.forEachChar, base.forEachGraphemeCluster, forEachChar\n","base.forEachCodePointRight":"\nbase.forEachCodePointRight( str, clbk[, thisArg] )\n    Invokes a function for each Unicode code point in a string, iterating from\n    right to left.\n\n    When invoked, the provided function is provided three arguments:\n\n    - value: code point.\n    - index: starting code point index.\n    - str: input string.\n\n    Parameters\n    ----------\n    str: string\n        Input string over which to iterate.\n\n    clbk: Function\n        The function to invoke for each Unicode code point in the input string.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: string\n        Input string.\n\n    Examples\n    --------\n    > var n = 0;\n    > function fcn() { n += 1; };\n    > base.forEachCodePointRight( 'hello world!', fcn );\n    > n\n    12\n\n    See Also\n    --------\n    base.forEachCodePoint, base.forEachRight\n","base.forEachGraphemeCluster":"\nbase.forEachGraphemeCluster( str, clbk[, thisArg] )\n    Invokes a function for each grapheme cluster (i.e., user-perceived\n    character) in a string.\n\n    When invoked, the provided function is provided three arguments:\n\n    - value: grapheme cluster.\n    - index: starting grapheme cluster index.\n    - str: input string.\n\n    Parameters\n    ----------\n    str: string\n        Input string over which to iterate.\n\n    clbk: Function\n        The function to invoke for each grapheme cluster in the input string.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: string\n        Input string.\n\n    Examples\n    --------\n    > var n = 0;\n    > function fcn() { n += 1; };\n    > base.forEachGraphemeCluster( 'hello world!', fcn );\n    > n\n    12\n\n    See Also\n    --------\n    base.forEachChar, base.forEachCodePoint, forEachChar\n","base.forEachRight":"\nbase.forEachRight( str, clbk[, thisArg] )\n    Invokes a function for each UTF-16 code unit in a string, iterating from\n    right to left.\n\n    When invoked, the provided function is provided three arguments:\n\n    - value: character.\n    - index: character index.\n    - str: input string.\n\n    Parameters\n    ----------\n    str: string\n        Input string over which to iterate.\n\n    clbk: Function\n        Function to invoke for each UTF-16 code unit in the input string.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: string\n        Input string.\n\n    Examples\n    --------\n    > var n = 0;\n    > function fcn() { n += 1; };\n    > base.forEachRight( 'hello world!', fcn );\n    > n\n    12\n\n    See Also\n    --------\n    base.forEachChar, base.forEachCodePointRight\n","base.formatInterpolate":"\nbase.formatInterpolate( tokens, ...args )\n    Generate string from a token array by interpolating values.\n\n    Parameters\n    ----------\n    tokens: Array\n        Array of string parts and format identifier objects.\n\n    args: ...any\n        Variable values.\n\n    Returns\n    -------\n    out: string\n        Formatted string.\n\n    Examples\n    --------\n    > var out = base.formatInterpolate( [ 'beep ', { 'specifier': 's' } ], 'boop' )\n    'beep boop'\n    > out = base.formatInterpolate( [ 'baz ', { 'specifier': 'd', 'precision': 2 } ], 1 )\n    'baz 1.00'\n    > out = base.formatInterpolate( [ { 'specifier': 'u', 'width': 6 } ], 12 )\n    '    12'\n\n    See Also\n    --------\n    base.formatTokenize\n","base.formatTokenize":"\nbase.formatTokenize( str )\n    Tokenize a string into an array of string parts and format identifier\n    objects.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: Array\n        Array of string parts and format identifier objects.\n\n    Examples\n    --------\n    > var out = base.formatTokenize( 'Hello %s!' )\n    [ 'Hello ', {...}, '!' ]\n    > out = base.formatTokenize( '%s %s %d' )\n    [ {...}, ' ', {...}, ' ', {...}, ' ' ]\n    > out = base.formatTokenize( 'Pi: %.2f' )\n    [ 'Pi: ', {...} ]\n\n    See Also\n    --------\n    base.formatInterpolate\n","base.fresnel":"\nbase.fresnel( x )\n    Computes the Fresnel integrals S(x) and C(x).\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: Array<number>\n        S(x) and C(x).\n\n    Examples\n    --------\n    > var y = base.fresnel( 0.0 )\n    [ ~0.0, ~0.0 ]\n    > y = base.fresnel( 1.0 )\n    [ ~0.438, ~0.780 ]\n    > y = base.fresnel( PINF )\n    [ ~0.5, ~0.5 ]\n    > y = base.fresnel( NINF )\n    [ ~-0.5, ~-0.5 ]\n    > y = base.fresnel( NaN )\n    [ NaN, NaN ]\n\n\nbase.fresnel.assign( x, out, stride, offset )\n    Computes the Fresnel integrals S(x) and C(x) and assigns results to a\n    provided output array.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    out: Array<number>\n        Destination array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array<number>\n        S(x) and C(x).\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var v = base.fresnel.assign( 0.0, out, 1, 0 )\n    <Float64Array>[ ~0.0, ~0.0 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.fresnelc, base.fresnels","base.fresnel.assign":"\nbase.fresnel.assign( x, out, stride, offset )\n    Computes the Fresnel integrals S(x) and C(x) and assigns results to a\n    provided output array.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    out: Array<number>\n        Destination array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array<number>\n        S(x) and C(x).\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var v = base.fresnel.assign( 0.0, out, 1, 0 )\n    <Float64Array>[ ~0.0, ~0.0 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.fresnelc, base.fresnels","base.fresnelc":"\nbase.fresnelc( x )\n    Computes the Fresnel integral C(x).\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        C(x).\n\n    Examples\n    --------\n    > var y = base.fresnelc( 0.0 )\n    ~0.0\n    > y = base.fresnelc( 1.0 )\n    ~0.780\n    > y = base.fresnelc( PINF )\n    ~0.5\n    > y = base.fresnelc( NINF )\n    ~-0.5\n    > y = base.fresnelc( NaN )\n    NaN\n\n    See Also\n    --------\n    base.fresnel, base.fresnels\n","base.fresnels":"\nbase.fresnels( x )\n    Computes the Fresnel integral S(x).\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        S(x).\n\n    Examples\n    --------\n    > var y = base.fresnels( 0.0 )\n    ~0.0\n    > y = base.fresnels( 1.0 )\n    ~0.438\n    > y = base.fresnels( PINF )\n    ~0.5\n    > y = base.fresnels( NINF )\n    ~-0.5\n    > y = base.fresnels( NaN )\n    NaN\n\n    See Also\n    --------\n    base.fresnel, base.fresnelc\n","base.frexp":"\nbase.frexp( x )\n    Splits a double-precision floating-point number into a normalized fraction\n    and an integer power of two.\n\n    The first element of the returned array is the normalized fraction and the\n    second is the exponent. The normalized fraction and exponent satisfy the\n    relation\n\n      x = frac * 2^exp\n\n    If provided positive or negative zero, `NaN`, or positive or negative\n    infinity, the function returns a two-element array containing the input\n    value and an exponent equal to zero.\n\n    For all other numeric input values, the absolute value of the normalized\n    fraction resides on the interval [0.5,1).\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    out: Array<number>\n        A normalized fraction and an exponent.\n\n    Examples\n    --------\n    > var out = base.frexp( 4.0 )\n    [ 0.5, 3 ]\n    > out = base.frexp( 0.0 )\n    [ 0.0, 0 ]\n    > out = base.frexp( -0.0 )\n    [ -0.0, 0 ]\n    > out = base.frexp( NaN )\n    [ NaN, 0 ]\n    > out = base.frexp( PINF )\n    [ Infinity, 0 ]\n    > out = base.frexp( NINF )\n    [ -Infinity, 0 ]\n\n\nbase.frexp.assign( x, out, stride, offset )\n    Splits a double-precision floating-point number into a normalized fraction\n    and an integer power of two and assigns results to a provided output array.\n\n    The first element of the returned array is the normalized fraction and the\n    second is the exponent. The normalized fraction and exponent satisfy the\n    relation\n\n      x = frac * 2^exp\n\n    If provided positive or negative zero, `NaN`, or positive or negative\n    infinity, the function returns a two-element array containing the input\n    value and an exponent equal to zero.\n\n    For all other numeric input values, the absolute value of the normalized\n    fraction resides on the interval [0.5,1).\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    out: Array<number>\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array<number>\n        A normalized fraction and an exponent.\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var y = base.frexp.assign( 4.0, out, 1, 0 )\n    <Float64Array>[ 0.5, 3 ]\n    > var bool = ( y === out )\n    true\n\n    See Also\n    --------\n    base.ldexp\n","base.frexp.assign":"\nbase.frexp.assign( x, out, stride, offset )\n    Splits a double-precision floating-point number into a normalized fraction\n    and an integer power of two and assigns results to a provided output array.\n\n    The first element of the returned array is the normalized fraction and the\n    second is the exponent. The normalized fraction and exponent satisfy the\n    relation\n\n      x = frac * 2^exp\n\n    If provided positive or negative zero, `NaN`, or positive or negative\n    infinity, the function returns a two-element array containing the input\n    value and an exponent equal to zero.\n\n    For all other numeric input values, the absolute value of the normalized\n    fraction resides on the interval [0.5,1).\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    out: Array<number>\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array<number>\n        A normalized fraction and an exponent.\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var y = base.frexp.assign( 4.0, out, 1, 0 )\n    <Float64Array>[ 0.5, 3 ]\n    > var bool = ( y === out )\n    true\n\n    See Also\n    --------\n    base.ldexp","base.fromBinaryString":"\nbase.fromBinaryString( bstr )\n    Creates a double-precision floating-point number from a literal bit\n    representation.\n\n    Parameters\n    ----------\n    bstr: string\n        Literal bit representation.\n\n    Returns\n    -------\n    out: number\n        Double-precision floating-point number.\n\n    Examples\n    --------\n    > var bstr;\n    > bstr = '0100000000010000000000000000000000000000000000000000000000000000';\n    > var val = base.fromBinaryString( bstr )\n    4.0\n    > bstr = '0100000000001001001000011111101101010100010001000010110100011000';\n    > val = base.fromBinaryString( bstr )\n    3.141592653589793\n    > bstr = '1111111111100001110011001111001110000101111010111100100010100000';\n    > val = base.fromBinaryString( bstr )\n    -1.0e308\n\n    // The function handles subnormals:\n    > bstr = '1000000000000000000000000000000000000000000000000001100011010011';\n    > val = base.fromBinaryString( bstr )\n    -3.14e-320\n    > bstr = '0000000000000000000000000000000000000000000000000000000000000001';\n    > val = base.fromBinaryString( bstr )\n    5.0e-324\n\n    // The function handles special values:\n    > bstr = '0000000000000000000000000000000000000000000000000000000000000000';\n    > val = base.fromBinaryString( bstr )\n    0.0\n    > bstr = '1000000000000000000000000000000000000000000000000000000000000000';\n    > val = base.fromBinaryString( bstr )\n    -0.0\n    > bstr = '0111111111111000000000000000000000000000000000000000000000000000';\n    > val = base.fromBinaryString( bstr )\n    NaN\n    > bstr = '0111111111110000000000000000000000000000000000000000000000000000';\n    > val = base.fromBinaryString( bstr )\n    Infinity\n    > bstr = '1111111111110000000000000000000000000000000000000000000000000000';\n    > val = base.fromBinaryString( bstr )\n    -Infinity\n\n    See Also\n    --------\n    base.fromBinaryStringf, base.toBinaryString\n","base.fromBinaryStringf":"\nbase.fromBinaryStringf( bstr )\n    Creates a single-precision floating-point number from an IEEE 754 literal\n    bit representation.\n\n    Parameters\n    ----------\n    bstr: string\n        Literal bit representation.\n\n    Returns\n    -------\n    out: float\n        Single-precision floating-point number.\n\n    Examples\n    --------\n    > var bstr = '01000000100000000000000000000000';\n    > var val = base.fromBinaryStringf( bstr )\n    4.0\n    > bstr = '01000000010010010000111111011011';\n    > val = base.fromBinaryStringf( bstr )\n    ~3.14\n    > bstr = '11111111011011000011101000110011';\n    > val = base.fromBinaryStringf( bstr )\n    ~-3.14e+38\n\n    // The function handles subnormals:\n    > bstr = '10000000000000000000000000010110';\n    > val = base.fromBinaryStringf( bstr )\n    ~-3.08e-44\n    > bstr = '00000000000000000000000000000001';\n    > val = base.fromBinaryStringf( bstr )\n    ~1.40e-45\n\n    // The function handles special values:\n    > bstr = '00000000000000000000000000000000';\n    > val = base.fromBinaryStringf( bstr )\n    0.0\n    > bstr = '10000000000000000000000000000000';\n    > val = base.fromBinaryStringf( bstr )\n    -0.0\n    > bstr = '01111111110000000000000000000000';\n    > val = base.fromBinaryStringf( bstr )\n    NaN\n    > bstr = '01111111100000000000000000000000';\n    > val = base.fromBinaryStringf( bstr )\n    Infinity\n    > bstr = '11111111100000000000000000000000';\n    > val = base.fromBinaryStringf( bstr )\n    -Infinity\n\n    See Also\n    --------\n    base.toBinaryStringf, base.fromBinaryString\n","base.fromBinaryStringUint8":"\nbase.fromBinaryStringUint8( bstr )\n    Creates an unsigned 8-bit integer from a literal bit representation.\n\n    Parameters\n    ----------\n    bstr: string\n        Literal bit representation.\n\n    Returns\n    -------\n    out: integer\n        Unsigned 8-bit integer.\n\n    Examples\n    --------\n    > var bstr = '01010101';\n    > var val = base.fromBinaryStringUint8( bstr )\n    85\n    > bstr = '00000000';\n    > val = base.fromBinaryStringUint8( bstr )\n    0\n    > bstr = '00000010';\n    > val = base.fromBinaryStringUint8( bstr )\n    2\n    > bstr = '11111111';\n    > val = base.fromBinaryStringUint8( bstr )\n    255\n\n    See Also\n    --------\n    base.fromBinaryStringUint16, base.fromBinaryStringUint32, base.toBinaryStringUint8\n","base.fromBinaryStringUint16":"\nbase.fromBinaryStringUint16( bstr )\n    Creates an unsigned 16-bit integer from a literal bit representation.\n\n    Parameters\n    ----------\n    bstr: string\n        Literal bit representation.\n\n    Returns\n    -------\n    out: integer\n        Unsigned 16-bit integer.\n\n    Examples\n    --------\n    > var bstr = '0101010101010101';\n    > var val = base.fromBinaryStringUint16( bstr )\n    21845\n    > bstr = '0000000000000000';\n    > val = base.fromBinaryStringUint16( bstr )\n    0\n    > bstr = '0000000000000010';\n    > val = base.fromBinaryStringUint16( bstr )\n    2\n    > bstr = '1111111111111111';\n    > val = base.fromBinaryStringUint16( bstr )\n    65535\n\n    See Also\n    --------\n    base.toBinaryStringUint16, base.fromBinaryStringUint32, base.fromBinaryStringUint8\n","base.fromBinaryStringUint32":"\nbase.fromBinaryStringUint32( bstr )\n    Creates an unsigned 32-bit integer from a literal bit representation.\n\n    Parameters\n    ----------\n    bstr: string\n        Literal bit representation.\n\n    Returns\n    -------\n    out: integer\n        Unsigned 32-bit integer.\n\n    Examples\n    --------\n    > var bstr = '01010101010101010101010101010101';\n    > var val = base.fromBinaryStringUint32( bstr )\n    1431655765\n    > bstr = '00000000000000000000000000000000';\n    > val = base.fromBinaryStringUint32( bstr )\n    0\n    > bstr = '00000000000000000000000000000010';\n    > val = base.fromBinaryStringUint32( bstr )\n    2\n    > bstr = '11111111111111111111111111111111';\n    > val = base.fromBinaryStringUint32( bstr )\n    4294967295\n\n    See Also\n    --------\n    base.fromBinaryStringUint16, base.toBinaryStringUint32, base.fromBinaryStringUint8\n","base.fromInt64Bytes":"\nbase.fromInt64Bytes( bytes, stride, offset )\n    Converts a signed 64-bit integer byte array to a double-precision floating-\n    point number.\n\n    The function assumes host byte order (endianness).\n\n    Parameters\n    ----------\n    bytes: Array<number>|TypedArray|Object\n        Byte array.\n\n    stride: integer\n        Index stride.\n\n    offset: integer\n        Index offset.\n\n    Returns\n    -------\n    out: number\n        Number.\n\n    Examples\n    --------\n    > var bytes = new Uint8Array( [ 255, 255, 255, 255, 255, 255, 255, 255 ] );\n    > var y = base.fromInt64Bytes( bytes, 1, 0 )\n    -1.0\n\n    See Also\n    --------\n    base.float64ToInt64Bytes","base.fromWordf":"\nbase.fromWordf( word )\n    Creates a single-precision floating-point number from an unsigned integer\n    corresponding to an IEEE 754 binary representation.\n\n    Parameters\n    ----------\n    word: integer\n        Unsigned integer.\n\n    Returns\n    -------\n    out: float\n        Single-precision floating-point number.\n\n    Examples\n    --------\n    > var word = 1068180177; // => 0 01111111 01010110010001011010001\n    > var f32 = base.fromWordf( word ) // when printed, promoted to float64\n    1.3370000123977661\n\n    See Also\n    --------\n    base.fromWords\n","base.fromWords":"\nbase.fromWords( high, low )\n    Creates a double-precision floating-point number from a higher order word\n    (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n\n    Parameters\n    ----------\n    high: integer\n        Higher order word (unsigned 32-bit integer).\n\n    low: integer\n        Lower order word (unsigned 32-bit integer).\n\n    Returns\n    -------\n    out: number\n        Double-precision floating-point number.\n\n    Examples\n    --------\n    > var v = base.fromWords( 1774486211, 2479577218 )\n    3.14e201\n    > v = base.fromWords( 3221823995, 1413754136 )\n    -3.141592653589793\n    > v = base.fromWords( 0, 0 )\n    0.0\n    > v = base.fromWords( 2147483648, 0 )\n    -0.0\n    > v = base.fromWords( 2146959360, 0 )\n    NaN\n    > v = base.fromWords( 2146435072, 0 )\n    Infinity\n    > v = base.fromWords( 4293918720, 0 )\n    -Infinity\n\n    See Also\n    --------\n    base.fromWordf\n","base.gamma":"\nbase.gamma( x )\n    Evaluates the gamma function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.gamma( 4.0 )\n    6.0\n    > y = base.gamma( -1.5 )\n    ~2.363\n    > y = base.gamma( -0.5 )\n    ~-3.545\n    > y = base.gamma( 0.5 )\n    ~1.772\n    > y = base.gamma( 0.0 )\n    Infinity\n    > y = base.gamma( -0.0 )\n    -Infinity\n    > y = base.gamma( NaN )\n    NaN\n\n    See Also\n    --------\n    base.gamma1pm1, base.gammainc, base.gammaincinv, base.gammaln\n","base.gamma1pm1":"\nbase.gamma1pm1( x )\n    Computes `gamma(x+1) - 1` without cancellation errors, where `gamma(x)` is\n    the gamma function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.gamma1pm1( 0.2 )\n    ~-0.082\n    > y = base.gamma1pm1( -6.7 )\n    ~-0.991\n    > y = base.gamma1pm1( 0.0 )\n    0.0\n    > y = base.gamma1pm1( NaN )\n    NaN\n\n    See Also\n    --------\n    base.gamma, base.gammainc, base.gammaincinv, base.gammaln\n","base.gammaDeltaRatio":"\nbase.gammaDeltaRatio( z, delta )\n    Computes the ratio of two gamma functions.\n\n    The ratio is defined as: Γ(z) / Γ(z+Δ).\n\n    Parameters\n    ----------\n    z: number\n        First gamma parameter.\n\n    delta: number\n        Difference.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.gammaDeltaRatio( 2.0, 3.0 )\n    ~0.042\n    > y = base.gammaDeltaRatio( 4.0, 0.5 )\n    ~0.516\n    > y = base.gammaDeltaRatio( 100.0, 0.0 )\n    1.0\n    > y = base.gammaDeltaRatio( NaN, 3.0 )\n    NaN\n    > y = base.gammaDeltaRatio( 5.0, NaN )\n    NaN\n    > y = base.gammaDeltaRatio( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.gamma\n","base.gammainc":"\nbase.gammainc( x, s[, regularized[, upper]] )\n    Computes the regularized incomplete gamma function.\n\n    The `regularized` and `upper` parameters specify whether to evaluate the\n    non-regularized and/or upper incomplete gamma functions, respectively.\n\n    If provided `x < 0` or `s <= 0`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        First function parameter.\n\n    s: number\n        Second function parameter.\n\n    regularized: boolean (optional)\n        Boolean indicating whether the function should evaluate the regularized\n        or non-regularized incomplete gamma function. Default: `true`.\n\n    upper: boolean (optional)\n        Boolean indicating whether the function should return the upper tail of\n        the incomplete gamma function. Default: `false`.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.gammainc( 6.0, 2.0 )\n    ~0.9826\n    > y = base.gammainc( 1.0, 2.0, true, true )\n    ~0.7358\n    > y = base.gammainc( 7.0, 5.0 )\n    ~0.8270\n    > y = base.gammainc( 7.0, 5.0, false )\n    ~19.8482\n    > y = base.gammainc( NaN, 2.0 )\n    NaN\n    > y = base.gammainc( 6.0, NaN )\n    NaN\n\n    See Also\n    --------\n    base.gamma, base.gamma1pm1, base.gammaincinv, base.gammaln\n","base.gammaincinv":"\nbase.gammaincinv( p, a[, upper] )\n    Computes the inverse of the lower incomplete gamma function.\n\n    In contrast to a more commonly used definition, the first argument is the\n    probability `p` and the second argument is the scale factor `a`.\n\n    By default, the function inverts the lower regularized incomplete gamma\n    function, `P(x,a)`. To invert the upper function `Q(x,a)`, set the `upper`\n    argument to `true`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Probability.\n\n    a: number\n        Scale parameter.\n\n    upper: boolean (optional)\n        Boolean indicating if the function should invert the upper tail of the\n        incomplete gamma function; i.e., compute `xr` such that `Q(a,xr) = p`.\n        Default: `false`.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.gammaincinv( 0.5, 2.0 )\n    ~1.678\n    > y = base.gammaincinv( 0.1, 10.0 )\n    ~6.221\n    > y = base.gammaincinv( 0.75, 3.0 )\n    ~3.92\n    > y = base.gammaincinv( 0.75, 3.0, true )\n    ~1.727\n    > y = base.gammaincinv( 0.75, NaN )\n    NaN\n    > y = base.gammaincinv( NaN, 3.0 )\n    NaN\n\n    See Also\n    --------\n    base.gamma, base.gamma1pm1, base.gammainc, base.gammaln\n","base.gammaLanczosSum":"\nbase.gammaLanczosSum( x )\n    Calculates the Lanczos sum for the approximation of the gamma function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Lanczos sum.\n\n    Examples\n    --------\n    > var y = base.gammaLanczosSum( 4.0 )\n    ~950.366\n    > y = base.gammaLanczosSum( -1.5 )\n    ~1373366.245\n    > y = base.gammaLanczosSum( -0.5 )\n    ~-699841.735\n    > y = base.gammaLanczosSum( 0.5 )\n    ~96074.186\n    > y = base.gammaLanczosSum( 0.0 )\n    Infinity\n    > y = base.gammaLanczosSum( NaN )\n    NaN\n\n    See Also\n    --------\n    base.gamma, base.gammaLanczosSumExpGScaled\n","base.gammaLanczosSumExpGScaled":"\nbase.gammaLanczosSumExpGScaled( x )\n    Calculates the scaled Lanczos sum for the approximation of the gamma\n    function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Scaled Lanczos sum.\n\n    Examples\n    --------\n    > var y = base.gammaLanczosSumExpGScaled( 4.0 )\n    ~0.018\n    > y = base.gammaLanczosSumExpGScaled( -1.5 )\n    ~25.337\n    > y = base.gammaLanczosSumExpGScaled( -0.5 )\n    ~-12.911\n    > y = base.gammaLanczosSumExpGScaled( 0.5 )\n    ~1.772\n    > y = base.gammaLanczosSumExpGScaled( 0.0 )\n    Infinity\n    > y = base.gammaLanczosSumExpGScaled( NaN )\n    NaN\n\n    See Also\n    --------\n    base.gamma, base.gammaLanczosSum\n","base.gammaln":"\nbase.gammaln( x )\n    Evaluates the natural logarithm of the gamma function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Natural logarithm of the gamma function.\n\n    Examples\n    --------\n    > var y = base.gammaln( 1.0 )\n    0.0\n    > y = base.gammaln( 2.0 )\n    0.0\n    > y = base.gammaln( 4.0 )\n    ~1.792\n    > y = base.gammaln( -0.5 )\n    ~1.266\n    > y = base.gammaln( 0.5 )\n    ~0.572\n    > y = base.gammaln( 0.0 )\n    Infinity\n    > y = base.gammaln( NaN )\n    NaN\n\n    See Also\n    --------\n    base.gamma, base.gammainc, base.gammaincinv\n","base.gammasgn":"\nbase.gammasgn( x )\n    Computes the sign of the gamma function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Sign of the gamma function.\n\n    Examples\n    --------\n    > var y = base.gammasgn( 1.0 )\n    1.0\n    > y = base.gammasgn( -2.5 )\n    -1.0\n    > y = base.gammasgn( 0.0 )\n    0.0\n    > y = base.gammasgn( NaN )\n    NaN\n\n    See Also\n    --------\n    base.gamma","base.gcd":"\nbase.gcd( a, b )\n    Computes the greatest common divisor (gcd).\n\n    If both `a` and `b` are `0`, the function returns `0`.\n\n    Both `a` and `b` must have integer values; otherwise, the function returns\n    `NaN`.\n\n    Parameters\n    ----------\n    a: integer\n        First number.\n\n    b: integer\n        Second number.\n\n    Returns\n    -------\n    out: integer\n        Greatest common divisor.\n\n    Examples\n    --------\n    > var v = base.gcd( 48, 18 )\n    6\n\n    See Also\n    --------\n    base.lcm\n","base.getHighWord":"\nbase.getHighWord( x )\n    Returns an unsigned 32-bit integer corresponding to the more significant 32\n    bits of a double-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    out: integer\n        Higher order word (unsigned 32-bit integer).\n\n    Examples\n    --------\n    > var w = base.getHighWord( 3.14e201 )\n    1774486211\n\n    See Also\n    --------\n    base.getLowWord, base.setHighWord\n","base.getLowWord":"\nbase.getLowWord( x )\n    Returns an unsigned 32-bit integer corresponding to the less significant 32\n    bits of a double-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    out: integer\n        Lower order word (unsigned 32-bit integer).\n\n    Examples\n    --------\n    > var w = base.getLowWord( 3.14e201 )\n    2479577218\n\n    See Also\n    --------\n    base.getHighWord, base.setHighWord\n","base.hacovercos":"\nbase.hacovercos( x )\n    Computes the half-value coversed cosine.\n\n    The half-value coversed cosine is defined as `(1 + sin(x)) / 2`.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Half-value coversed cosine.\n\n    Examples\n    --------\n    > var y = base.hacovercos( 3.14 )\n    ~0.5008\n    > y = base.hacovercos( -4.2 )\n    ~0.9358\n    > y = base.hacovercos( -4.6 )\n    ~0.9968\n    > y = base.hacovercos( 9.5 )\n    ~0.4624\n    > y = base.hacovercos( -0.0 )\n    0.5\n\n    See Also\n    --------\n    base.hacoversin, base.havercos\n","base.hacoversin":"\nbase.hacoversin( x )\n    Computes the half-value coversed sine.\n\n    The half-value coversed sine is defined as `(1 - sin(x)) / 2`.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Half-value coversed sine.\n\n    Examples\n    --------\n    > var y = base.hacoversin( 3.14 )\n    ~0.4992\n    > y = base.hacoversin( -4.2 )\n    ~0.0642\n    > y = base.hacoversin( -4.6 )\n    ~0.0032\n    > y = base.hacoversin( 9.5 )\n    ~0.538\n    > y = base.hacoversin( -0.0 )\n    0.5\n\n    See Also\n    --------\n    base.hacovercos, base.haversin\n","base.havercos":"\nbase.havercos( x )\n    Computes the half-value versed cosine.\n\n    The half-value versed cosine is defined as `(1 + cos(x)) / 2`.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Half-value versed cosine.\n\n    Examples\n    --------\n    > var y = base.havercos( 3.14 )\n    ~0.0\n    > y = base.havercos( -4.2 )\n    ~0.2549\n    > y = base.havercos( -4.6 )\n    ~0.4439\n    > y = base.havercos( 9.5 )\n    ~0.0014\n    > y = base.havercos( -0.0 )\n    1.0\n\n    See Also\n    --------\n    base.haversin, base.vercos\n","base.haversin":"\nbase.haversin( x )\n    Computes the half-value versed sine.\n\n    The half-value versed sine is defined as `(1 - cos(x)) / 2`.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Half-value versed sine.\n\n    Examples\n    --------\n    > var y = base.haversin( 3.14 )\n    ~1.0\n    > y = base.haversin( -4.2 )\n    ~0.7451\n    > y = base.haversin( -4.6 )\n    ~0.5561\n    > y = base.haversin( 9.5 )\n    ~0.9986\n    > y = base.haversin( -0.0 )\n    0.0\n\n    See Also\n    --------\n    base.havercos, base.versin\n","base.headercase":"\nbase.headercase( str )\n    Converts a string to HTTP header case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        HTTP header-cased string.\n\n    Examples\n    --------\n    > var out = base.headercase( 'Hello World!' )\n    'Hello-World'\n    > out = base.headercase( 'beep boop' )\n    'Beep-Boop'\n\n    See Also\n    --------\n    base.camelcase, base.pascalcase, base.uppercase","base.heaviside":"\nbase.heaviside( x[, continuity] )\n    Evaluates the Heaviside function.\n\n    The `continuity` parameter may be one of the following:\n\n    - 'half-maximum': if `x == 0`, the function returns `0.5`.\n    - 'left-continuous': if `x == 0`, the function returns `0`.\n    - 'right-continuous': if `x == 0`, the function returns `1`.\n\n    By default, if `x == 0`, the function returns `NaN` (i.e., the function is\n    discontinuous).\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    continuity: string (optional)\n        Specifies how to handle `x == 0`. By default, if `x == 0`, the function\n        returns `NaN`.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.heaviside( 3.14 )\n    1.0\n    > y = base.heaviside( -3.14 )\n    0.0\n    > y = base.heaviside( 0.0 )\n    NaN\n    > y = base.heaviside( 0.0, 'half-maximum' )\n    0.5\n    > y = base.heaviside( 0.0, 'left-continuous' )\n    0.0\n    > y = base.heaviside( 0.0, 'right-continuous' )\n    1.0\n\n    See Also\n    --------\n    base.ramp\n","base.hermitepoly":"\nbase.hermitepoly( n, x )\n    Evaluates a physicist's Hermite polynomial.\n\n    Parameters\n    ----------\n    n: integer\n        Nonnegative polynomial degree.\n\n    x: number\n        Value at which to evaluate the polynomial.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.hermitepoly( 1, 0.5 )\n    1.0\n    > y = base.hermitepoly( -1, 0.5 )\n    NaN\n    > y = base.hermitepoly( 0, 0.5 )\n    1.0\n    > y = base.hermitepoly( 2, 0.5 )\n    -1.0\n\n\nbase.hermitepoly.factory( n )\n    Returns a function for evaluating a physicist's Hermite polynomial.\n\n    Parameters\n    ----------\n    n: integer\n        Nonnegative polynomial degree.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a physicist's Hermite polynomial.\n\n    Examples\n    --------\n    > var polyval = base.hermitepoly.factory( 2 );\n    > var v = polyval( 0.5 )\n    -1.0\n\n    See Also\n    --------\n    base.evalpoly, base.normhermitepoly\n","base.hermitepoly.factory":"\nbase.hermitepoly.factory( n )\n    Returns a function for evaluating a physicist's Hermite polynomial.\n\n    Parameters\n    ----------\n    n: integer\n        Nonnegative polynomial degree.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a physicist's Hermite polynomial.\n\n    Examples\n    --------\n    > var polyval = base.hermitepoly.factory( 2 );\n    > var v = polyval( 0.5 )\n    -1.0\n\n    See Also\n    --------\n    base.evalpoly, base.normhermitepoly","base.hypot":"\nbase.hypot( x, y )\n    Computes the hypotenuse avoiding overflow and underflow.\n\n    If either argument is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Hypotenuse.\n\n    Examples\n    --------\n    > var h = base.hypot( -5.0, 12.0 )\n    13.0\n    > h = base.hypot( NaN, 12.0 )\n    NaN\n    > h = base.hypot( -0.0, -0.0 )\n    0.0\n\n","base.hypotf":"\nbase.hypotf( x, y )\n    Computes the hypotenuse avoiding overflow and underflow (single-precision).\n\n    If either argument is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Hypotenuse.\n\n    Examples\n    --------\n    > var h = base.hypotf( -5.0, 12.0 )\n    13.0\n    > h = base.hypotf( NaN, 12.0 )\n    NaN\n    > h = base.hypotf( -0.0, -0.0 )\n    0.0\n\n    See Also\n    --------\n    base.hypot\n","base.identity":"\nbase.identity( x )\n    Evaluates the identity function for a double-precision floating-point number\n    `x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Input value.\n\n    Examples\n    --------\n    > var y = base.identity( -1.0 )\n    -1.0\n    > y = base.identity( 2.0 )\n    2.0\n    > y = base.identity( 0.0 )\n    0.0\n    > y = base.identity( -0.0 )\n    -0.0\n    > y = base.identity( NaN )\n    NaN\n\n","base.identityf":"\nbase.identityf( x )\n    Evaluates the identity function for a single-precision floating-point number\n    `x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Input value.\n\n    Examples\n    --------\n    > var y = base.identityf( -1.0 )\n    -1.0\n    > y = base.identityf( 2.0 )\n    2.0\n    > y = base.identityf( 0.0 )\n    0.0\n    > y = base.identityf( -0.0 )\n    -0.0\n    > y = base.identityf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.identityf\n","base.imul":"\nbase.imul( a, b )\n    Performs C-like multiplication of two signed 32-bit integers.\n\n    Parameters\n    ----------\n    a: integer\n        Signed 32-bit integer.\n\n    b: integer\n        Signed 32-bit integer.\n\n    Returns\n    -------\n    out: integer\n        Product.\n\n    Examples\n    --------\n    > var v = base.imul( -10|0, 4|0 )\n    -40\n\n    See Also\n    --------\n    base.imuldw\n","base.imuldw":"\nbase.imuldw( a, b )\n    Multiplies two signed 32-bit integers and returns an array of two signed 32-\n    bit integers which represents the signed 64-bit integer product.\n\n    When computing the product of 32-bit integer values in double-precision\n    floating-point format (the default JavaScript numeric data type), computing\n    the double word product is necessary in order to avoid exceeding the maximum\n    safe double-precision floating-point integer value.\n\n    Parameters\n    ----------\n    a: integer\n        Signed 32-bit integer.\n\n    b: integer\n        Signed 32-bit integer.\n\n    Returns\n    -------\n    out: Array<number>\n        Double word product (in big endian order; i.e., the first element\n        corresponds to the most significant bits and the second element to the\n        least significant bits).\n\n    Examples\n    --------\n    > var v = base.imuldw( 1, 10 )\n    [ 0, 10 ]\n\n\nbase.imuldw.assign( a, b, out, stride, offset )\n    Multiplies two signed 32-bit integers and assigns results representing the\n    signed 64-bit integer product to a provided output array.\n\n    When computing the product of 32-bit integer values in double-precision\n    floating-point format (the default JavaScript numeric data type), computing\n    the double word product is necessary in order to avoid exceeding the maximum\n    safe double-precision floating-point integer value.\n\n    Parameters\n    ----------\n    a: integer\n        Signed 32-bit integer.\n\n    b: integer\n        Signed 32-bit integer.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Double word product (in big endian order; i.e., the first element\n        corresponds to the most significant bits and the second element to the\n        least significant bits).\n\n    Examples\n    --------\n    > var out = [ 0, 0 ];\n    > var v = base.imuldw.assign( 1, 10, out, 1, 0 )\n    [ 0, 10 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.imul","base.imuldw.assign":"\nbase.imuldw.assign( a, b, out, stride, offset )\n    Multiplies two signed 32-bit integers and assigns results representing the\n    signed 64-bit integer product to a provided output array.\n\n    When computing the product of 32-bit integer values in double-precision\n    floating-point format (the default JavaScript numeric data type), computing\n    the double word product is necessary in order to avoid exceeding the maximum\n    safe double-precision floating-point integer value.\n\n    Parameters\n    ----------\n    a: integer\n        Signed 32-bit integer.\n\n    b: integer\n        Signed 32-bit integer.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Double word product (in big endian order; i.e., the first element\n        corresponds to the most significant bits and the second element to the\n        least significant bits).\n\n    Examples\n    --------\n    > var out = [ 0, 0 ];\n    > var v = base.imuldw.assign( 1, 10, out, 1, 0 )\n    [ 0, 10 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.imul","base.int2slice":"\nbase.int2slice( value, max, strict )\n    Converts an integer to a Slice object.\n\n    In strict mode, the function returns an error object if an input value\n    exceeds index bounds.\n\n    A returned error object is a plain object having the following properties:\n\n    - code: error code.\n\n    A returned error object may have one of the following error codes:\n\n    - ERR_SLICE_OUT_OF_BOUNDS: a slice exceeds index bounds.\n\n    Parameters\n    ----------\n    value: integer\n        Input value.\n\n    max: integer\n        Index upper bound (exclusive).\n\n    strict: boolean\n        Boolean indicating whether to enforce strict bounds checking.\n\n    Returns\n    -------\n    s: Slice|Object\n        Slice instance (or an error object).\n\n    Examples\n    --------\n    > var s = base.int2slice( -1, 5, false );\n    > s.start\n    4\n    > s.stop\n    5\n    > s.step\n    1\n\n    See Also\n    --------\n    base.seq2slice, base.str2slice\n","base.int32ToUint32":"\nbase.int32ToUint32( x )\n    Converts a signed 32-bit integer to an unsigned 32-bit integer.\n\n    Parameters\n    ----------\n    x: integer\n        Signed 32-bit integer.\n\n    Returns\n    -------\n    out: integer\n        Unsigned 32-bit integer.\n\n    Examples\n    --------\n    > var y = base.int32ToUint32( base.float64ToInt32( -32 ) )\n    4294967264\n    > y = base.int32ToUint32( base.float64ToInt32( 3 ) )\n    3\n\n    See Also\n    --------\n    base.uint32ToInt32\n","base.inv":"\nbase.inv( x )\n    Computes the multiplicative inverse of a double-precision floating-point\n    number `x`.\n\n    The multiplicative inverse is defined as `1/x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Multiplicative inverse.\n\n    Examples\n    --------\n    > var y = base.inv( -1.0 )\n    -1.0\n    > y = base.inv( 2.0 )\n    0.5\n    > y = base.inv( 0.0 )\n    Infinity\n    > y = base.inv( -0.0 )\n    -Infinity\n    > y = base.inv( NaN )\n    NaN\n\n    See Also\n    --------\n    base.pow\n","base.invcase":"\nbase.invcase( str )\n    Converts a string to inverse case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Inverse-cased string.\n\n    Examples\n    --------\n    > var out = base.invcase( 'Hello World!' )\n    'hELLO wORLD!'\n    > out = base.invcase( 'I am A tiny LITTLE teapot' )\n    'i AM a TINY little TEAPOT'\n\n    See Also\n    --------\n    base.lowercase, base.uppercase","base.invf":"\nbase.invf( x )\n    Computes the multiplicative inverse of a single-precision floating-point\n    number `x`.\n\n    The multiplicative inverse is defined as `1/x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Multiplicative inverse.\n\n    Examples\n    --------\n    > var y = base.invf( -1.0 )\n    -1.0\n    > y = base.invf( 2.0 )\n    0.5\n    > y = base.invf( 0.0 )\n    Infinity\n    > y = base.invf( -0.0 )\n    -Infinity\n    > y = base.invf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.inv\n","base.isComposite":"\nbase.isComposite( x )\n    Tests if a number is composite.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is a composite number.\n\n    Examples\n    --------\n    > var bool = base.isComposite( 10.0 )\n    true\n    > bool = base.isComposite( 11.0 )\n    false\n\n    See Also\n    --------\n    base.isInteger, base.isPrime\n","base.isCoprime":"\nbase.isCoprime( a, b )\n    Tests if two numbers are coprime.\n\n    Parameters\n    ----------\n    a: number\n        First value.\n\n    b: number\n        Second value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the values are coprime.\n\n    Examples\n    --------\n    > var bool = base.isCoprime( 14.0, 15.0 )\n    true\n    > bool = base.isCoprime( 14.0, 21.0 )\n    false\n\n    See Also\n    --------\n    base.isComposite, base.isPrime, base.gcd\n","base.isEven":"\nbase.isEven( x )\n    Tests if a finite numeric value is an even number.\n\n    The function assumes a finite number. If provided positive or negative\n    infinity, the function will return `true`, when, in fact, the result is\n    undefined.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is an even number.\n\n    Examples\n    --------\n    > var bool = base.isEven( 5.0 )\n    false\n    > bool = base.isEven( -2.0 )\n    true\n    > bool = base.isEven( 0.0 )\n    true\n    > bool = base.isEven( NaN )\n    false\n\n    See Also\n    --------\n    base.isOdd\n","base.isEvenInt32":"\nbase.isEvenInt32( x )\n    Tests if a 32-bit integer is even.\n\n    Parameters\n    ----------\n    x: integer\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is an even number.\n\n    Examples\n    --------\n    > var bool = base.isEvenInt32( 5 )\n    false\n    > bool = base.isEvenInt32( -2 )\n    true\n    > bool = base.isEvenInt32( 0 )\n    true\n\n    See Also\n    --------\n    base.isEven, base.isOddInt32\n","base.isFinite":"\nbase.isFinite( x )\n    Tests if a double-precision floating-point numeric value is finite.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is finite.\n\n    Examples\n    --------\n    > var bool = base.isFinite( 5.0 )\n    true\n    > bool = base.isFinite( -2.0e64 )\n    true\n    > bool = base.isFinite( PINF )\n    false\n    > bool = base.isFinite( NINF )\n    false\n\n    See Also\n    --------\n    base.isInfinite\n","base.isFinitef":"\nbase.isFinitef( x )\n    Tests if a single-precision floating-point numeric value is finite.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is finite.\n\n    Examples\n    --------\n    > var bool = base.isFinitef( 5.0 )\n    true\n    > bool = base.isFinitef( -1.0e38 )\n    true\n    > bool = base.isFinitef( FLOAT32_PINF )\n    false\n    > bool = base.isFinitef( FLOAT32_NINF )\n    false\n\n    See Also\n    --------\n    base.isInfinitef\n","base.isInfinite":"\nbase.isInfinite( x )\n    Tests if a double-precision floating-point numeric value is infinite.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is infinite.\n\n    Examples\n    --------\n    > var bool = base.isInfinite( PINF )\n    true\n    > bool = base.isInfinite( NINF )\n    true\n    > bool = base.isInfinite( 5.0 )\n    false\n    > bool = base.isInfinite( NaN )\n    false\n\n    See Also\n    --------\n    base.isFinite\n","base.isInfinitef":"\nbase.isInfinitef( x )\n    Tests if a single-precision floating-point numeric value is infinite.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is infinite.\n\n    Examples\n    --------\n    > var bool = base.isInfinitef( FLOAT32_PINF )\n    true\n    > bool = base.isInfinitef( FLOAT32_NINF )\n    true\n    > bool = base.isInfinitef( 5.0 )\n    false\n    > bool = base.isInfinitef( NaN )\n    false\n\n    See Also\n    --------\n    base.isFinitef\n","base.isInteger":"\nbase.isInteger( x )\n    Tests if a finite double-precision floating-point number is an integer.\n\n    The function assumes a finite number. If provided positive or negative\n    infinity, the function will return `true`, when, in fact, the result is\n    undefined.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is an integer.\n\n    Examples\n    --------\n    > var bool = base.isInteger( 1.0 )\n    true\n    > bool = base.isInteger( 3.14 )\n    false\n\n","base.isnan":"\nbase.isnan( x )\n     Tests if a double-precision floating-point numeric value is `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is `NaN`.\n\n    Examples\n    --------\n    > var bool = base.isnan( NaN )\n    true\n    > bool = base.isnan( 7.0 )\n    false\n\n    See Also\n    --------\n    base.isnanf\n","base.isnanf":"\nbase.isnanf( x )\n     Tests if a single-precision floating-point numeric value is `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is `NaN`.\n\n    Examples\n    --------\n    > var bool = base.isnanf( NaN )\n    true\n    > bool = base.isnanf( 7.0 )\n    false\n\n    See Also\n    --------\n    base.isnan\n","base.isNegativeFinite":"\nbase.isNegativeFinite( x )\n    Tests if a double-precision floating-point numeric value is a negative\n    finite number.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether the value is a negative finite number.\n\n    Examples\n    --------\n    > var bool = base.isNegativeFinite( -3.14 )\n    true\n    > bool = base.isNegativeFinite( -Infinity )\n    false\n    > bool = base.isNegativeFinite( 2.0 )\n    false\n    > bool = base.isNegativeFinite( NaN )\n    false\n    > bool = base.isNegativeFinite( -0.0 )\n    false\n\n    See Also\n    --------\n    base.isPositiveFinite, base.isNonNegativeFinite, base.isNonPositiveFinite\n","base.isNegativeInteger":"\nbase.isNegativeInteger( x )\n    Tests if a finite double-precision floating-point number is a negative\n    integer.\n\n    The function assumes a finite number. If provided negative infinity, the\n    function will return `true`, when, in fact, the result is undefined.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is a negative integer.\n\n    Examples\n    --------\n    > var bool = base.isNegativeInteger( -1.0 )\n    true\n    > bool = base.isNegativeInteger( 0.0 )\n    false\n    > bool = base.isNegativeInteger( 10.0 )\n    false\n\n    See Also\n    --------\n    base.isInteger, base.isNonNegativeInteger, base.isNonPositiveInteger, base.isPositiveInteger\n","base.isNegativeZero":"\nbase.isNegativeZero( x )\n    Tests if a double-precision floating-point numeric value is negative zero.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is negative zero.\n\n    Examples\n    --------\n    > var bool = base.isNegativeZero( -0.0 )\n    true\n    > bool = base.isNegativeZero( 0.0 )\n    false\n\n    See Also\n    --------\n    base.isPositiveZero\n","base.isNegativeZerof":"\nbase.isNegativeZerof( x )\n    Tests if a single-precision floating-point numeric value is negative zero.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is negative zero.\n\n    Examples\n    --------\n    > var bool = base.isNegativeZerof( -0.0 )\n    true\n    > bool = base.isNegativeZerof( 0.0 )\n    false\n\n    See Also\n    --------\n    base.isNegativeZero, base.isPositiveZerof\n","base.isNonNegativeFinite":"\nbase.isNonNegativeFinite( x )\n    Tests if a double-precision floating-point numeric value is a nonnegative\n    finite number.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is a nonnegative finite number.\n\n    Examples\n    --------\n    > var out = base.isNonNegativeFinite( 5.0 )\n    true\n    > out = base.isNonNegativeFinite( 3.14 )\n    true\n    > out = base.isNonNegativeFinite( 0.0 )\n    true\n    > out = base.isNonNegativeFinite( Infinity )\n    false\n    > out = base.isNonNegativeFinite( -3.14 )\n    false\n    > out = base.isNonNegativeFinite( NaN )\n    false\n\n    See Also\n    --------\n    base.isNegativeFinite, base.isPositiveFinite, base.isNonPositiveFinite\n","base.isNonNegativeInteger":"\nbase.isNonNegativeInteger( x )\n    Tests if a finite double-precision floating-point number is a nonnegative\n    integer.\n\n    The function assumes a finite number. If provided positive infinity, the\n    function will return `true`, when, in fact, the result is undefined.\n\n    The function does not distinguish between positive and negative zero.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is a nonnegative integer.\n\n    Examples\n    --------\n    > var bool = base.isNonNegativeInteger( 1.0 )\n    true\n    > bool = base.isNonNegativeInteger( 0.0 )\n    true\n    > bool = base.isNonNegativeInteger( -10.0 )\n    false\n\n    See Also\n    --------\n    base.isInteger, base.isNegativeInteger, base.isNonPositiveInteger, base.isPositiveInteger\n","base.isNonPositiveFinite":"\nbase.isNonPositiveFinite( x )\n    Tests if a double-precision floating-point numeric value is a nonpositive\n    finite number.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether the value is a nonpositive finite number.\n\n    Examples\n    --------\n    > var bool = base.isNonPositiveFinite( -3.14 )\n    true\n    > var bool = base.isNonPositiveFinite( 0.0 )\n    true\n    > var bool = base.isNonPositiveFinite( -Infinity )\n    false\n    > var bool = base.isNonPositiveFinite( 3.14 )\n    false\n    > var bool = base.isNonPositiveFinite( NaN )\n    false\n\n    See Also\n    --------\n    base.isNegativeFinite, base.isPositiveFinite, base.isNonNegativeFinite\n","base.isNonPositiveInteger":"\nbase.isNonPositiveInteger( x )\n    Tests if a finite double-precision floating-point number is a nonpositive\n    integer.\n\n    The function assumes a finite number. If provided negative infinity, the\n    function will return `true`, when, in fact, the result is undefined.\n\n    The function does not distinguish between positive and negative zero.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is a nonpositive integer.\n\n    Examples\n    --------\n    > var bool = base.isNonPositiveInteger( -1.0 )\n    true\n    > bool = base.isNonPositiveInteger( 0.0 )\n    true\n    > bool = base.isNonPositiveInteger( 10.0 )\n    false\n\n    See Also\n    --------\n    base.isInteger, base.isNegativeInteger, base.isNonNegativeInteger, base.isPositiveInteger\n","base.isOdd":"\nbase.isOdd( x )\n    Tests if a finite numeric value is an odd number.\n\n    The function assumes a finite number. If provided positive or negative\n    infinity, the function will return `true`, when, in fact, the result is\n    undefined.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is an odd number.\n\n    Examples\n    --------\n    > var bool = base.isOdd( 5.0 )\n    true\n    > bool = base.isOdd( -2.0 )\n    false\n    > bool = base.isOdd( 0.0 )\n    false\n    > bool = base.isOdd( NaN )\n    false\n\n    See Also\n    --------\n    base.isEven\n","base.isOddInt32":"\nbase.isOddInt32( x )\n    Tests if a 32-bit integer is odd.\n\n    Parameters\n    ----------\n    x: integer\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is an odd number.\n\n    Examples\n    --------\n    > var bool = base.isOddInt32( 5 )\n    true\n    > bool = base.isOddInt32( -2 )\n    false\n    > bool = base.isOddInt32( 0 )\n    false\n\n    See Also\n    --------\n    base.isEvenInt32, base.isOdd\n","base.isPositiveFinite":"\nbase.isPositiveFinite( x )\n    Tests if a double-precision floating-point numeric value is a positive\n    finite number.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is a positive finite number.\n\n    Examples\n    --------\n    > var bool = base.isPositiveFinite( 5.0 )\n    true\n    > bool = base.isPositiveFinite( 3.14 )\n    true\n    > bool = base.isPositiveFinite( 0.0 )\n    false\n    > bool = base.isPositiveFinite( Infinity )\n    false\n    > bool = base.isPositiveFinite( -3.14 )\n    false\n    > bool = base.isPositiveFinite( NaN )\n    false\n\n    See Also\n    --------\n    base.isNegativeFinite, base.isNonNegativeFinite, base.isNonPositiveFinite\n","base.isPositiveInteger":"\nbase.isPositiveInteger( x )\n    Tests if a finite double-precision floating-point number is a positive\n    integer.\n\n    The function assumes a finite number. If provided positive infinity, the\n    function will return `true`, when, in fact, the result is undefined.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is a positive integer.\n\n    Examples\n    --------\n    > var bool = base.isPositiveInteger( 1.0 )\n    true\n    > bool = base.isPositiveInteger( 0.0 )\n    false\n    > bool = base.isPositiveInteger( -10.0 )\n    false\n\n    See Also\n    --------\n    base.isInteger, base.isNegativeInteger, base.isNonNegativeInteger, base.isNonPositiveInteger\n","base.isPositiveZero":"\nbase.isPositiveZero( x )\n    Tests if a double-precision floating-point numeric value is positive zero.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is positive zero.\n\n    Examples\n    --------\n    > var bool = base.isPositiveZero( 0.0 )\n    true\n    > bool = base.isPositiveZero( -0.0 )\n    false\n\n    See Also\n    --------\n    base.isNegativeZero\n","base.isPositiveZerof":"\nbase.isPositiveZerof( x )\n    Tests if a single-precision floating-point numeric value is positive zero.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is positive zero.\n\n    Examples\n    --------\n    > var bool = base.isPositiveZerof( 0.0 )\n    true\n    > bool = base.isPositiveZerof( -0.0 )\n    false\n\n    See Also\n    --------\n    base.isNegativeZerof, base.isPositiveZero\n","base.isPow2Uint32":"\nbase.isPow2Uint32( x )\n    Tests whether an unsigned integer is a power of 2.\n\n    Parameters\n    ----------\n    x: integer\n        Unsigned integer.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is a power of 2.\n\n    Examples\n    --------\n    > var bool = base.isPow2Uint32( 2 )\n    true\n    > bool = base.isPow2Uint32( 5 )\n    false\n\n","base.isPrime":"\nbase.isPrime( x )\n    Tests if a number is prime.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is a prime number.\n\n    Examples\n    --------\n    > var bool = base.isPrime( 11.0 )\n    true\n    > bool = base.isPrime( 3.14 )\n    false\n\n    See Also\n    --------\n    base.isComposite, base.isInteger\n","base.isProbability":"\nbase.isProbability( x )\n    Tests if a double-precision floating-point number value is a probability.\n\n    A probability is defined as a number on the closed interval [0,1].\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is a probability.\n\n    Examples\n    --------\n    > var bool = base.isProbability( 0.5 )\n    true\n    > bool = base.isProbability( 3.14 )\n    false\n    > bool = base.isProbability( NaN )\n    false\n\n","base.isSafeInteger":"\nbase.isSafeInteger( x )\n    Tests if a finite double-precision floating-point number is a safe integer.\n\n    An integer valued number is \"safe\" when the number can be exactly\n    represented as a double-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is a safe integer.\n\n    Examples\n    --------\n    > var bool = base.isSafeInteger( 1.0 )\n    true\n    > bool = base.isSafeInteger( 2.0e200 )\n    false\n    > bool = base.isSafeInteger( 3.14 )\n    false\n\n","base.kebabcase":"\nbase.kebabcase( str )\n    Converts a string to kebab case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Kebab-cased string.\n\n    Examples\n    --------\n    > var out = base.kebabcase( 'Hello World!' )\n    'hello-world'\n    > out = base.kebabcase( 'I am a tiny little teapot' )\n    'i-am-a-tiny-little-teapot'\n\n    See Also\n    --------\n    base.camelcase, base.lowercase, base.pascalcase, base.snakecase, base.uppercase","base.kernelBetainc":"\nbase.kernelBetainc( x, a, b, regularized, upper )\n    Computes the kernel function for the regularized incomplete beta function.\n\n    The `regularized` and `upper` parameters specify whether to evaluate the\n    non-regularized and/or upper incomplete beta functions, respectively.\n\n    If provided `x < 0` or `x > 1`, the function returns `[ NaN, NaN ]`.\n\n    If provided `a < 0` or `b < 0`, the function returns `[ NaN, NaN ]`.\n\n    If provided `NaN` for `x`, `a`, or `b`, the function returns `[ NaN, NaN ]`.\n\n    Parameters\n    ----------\n    x: number\n        First function parameter.\n\n    a: number\n        Second function parameter.\n\n    b: number\n        Third function parameter.\n\n    regularized: boolean\n        Boolean indicating whether the function should evaluate the regularized\n        or non-regularized incomplete beta function.\n\n    upper: boolean\n        Boolean indicating whether the function should return the upper tail of\n        the incomplete beta function.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Function value and first derivative.\n\n    Examples\n    --------\n    > var out = base.kernelBetainc( 0.8, 1.0, 0.3, false, false )\n    [ ~1.277, ~0.926 ]\n    > out = base.kernelBetainc( 0.2, 1.0, 2.0, true, false )\n    [ 0.36, 1.6 ]\n\n\nbase.kernelBetainc.assign( x, a, b, regularized, upper, out, stride, offset )\n    Computes the kernel function for the regularized incomplete beta function.\n\n    The `regularized` and `upper` parameters specify whether to evaluate the\n    non-regularized and/or upper incomplete beta functions, respectively.\n\n    If provided `x < 0` or `x > 1`, the function returns `[ NaN, NaN ]`.\n\n    If provided `a < 0` or `b < 0`, the function returns `[ NaN, NaN ]`.\n\n    If provided `NaN` for `x`, `a`, or `b`, the function returns `[ NaN, NaN ]`.\n\n    Parameters\n    ----------\n    x: number\n        First function parameter.\n\n    a: number\n        Second function parameter.\n\n    b: number\n        Third function parameter.\n\n    regularized: boolean\n        Boolean indicating whether the function should evaluate the regularized\n        or non-regularized incomplete beta function.\n\n    upper: boolean\n        Boolean indicating whether the function should return the upper tail of\n        the incomplete beta function.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Function value and first derivative.\n\n    Examples\n    --------\n    > var out = [ 0.0, 0.0 ];\n    > var v = base.kernelBetainc.assign( 0.2, 1.0, 2.0, true, true, out, 1, 0 )\n    [ 0.64, 1.6 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.betainc\n","base.kernelBetainc.assign":"\nbase.kernelBetainc.assign( x, a, b, regularized, upper, out, stride, offset )\n    Computes the kernel function for the regularized incomplete beta function.\n\n    The `regularized` and `upper` parameters specify whether to evaluate the\n    non-regularized and/or upper incomplete beta functions, respectively.\n\n    If provided `x < 0` or `x > 1`, the function returns `[ NaN, NaN ]`.\n\n    If provided `a < 0` or `b < 0`, the function returns `[ NaN, NaN ]`.\n\n    If provided `NaN` for `x`, `a`, or `b`, the function returns `[ NaN, NaN ]`.\n\n    Parameters\n    ----------\n    x: number\n        First function parameter.\n\n    a: number\n        Second function parameter.\n\n    b: number\n        Third function parameter.\n\n    regularized: boolean\n        Boolean indicating whether the function should evaluate the regularized\n        or non-regularized incomplete beta function.\n\n    upper: boolean\n        Boolean indicating whether the function should return the upper tail of\n        the incomplete beta function.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Function value and first derivative.\n\n    Examples\n    --------\n    > var out = [ 0.0, 0.0 ];\n    > var v = base.kernelBetainc.assign( 0.2, 1.0, 2.0, true, true, out, 1, 0 )\n    [ 0.64, 1.6 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.betainc","base.kernelBetaincinv":"\nbase.kernelBetaincinv( a, b, p, q )\n    Computes the inverse of the lower incomplete beta function.\n\n    Probabilities `p` and `q` must satisfy `p = 1 - q`.\n\n    Parameters\n    ----------\n    a: number\n        First function parameter (a positive number).\n\n    b: number\n        Second function parameter (a positive number).\n\n    p: number\n        Probability.\n\n    q: number\n        Probability equal to `1-p`.\n\n    Returns\n    -------\n    out: Array\n        Two-element array holding function value `y` and `1-y`.\n\n    Examples\n    --------\n    > var y = base.kernelBetaincinv( 3.0, 3.0, 0.2, 0.8 )\n    [ ~0.327, ~0.673 ]\n    > y = base.kernelBetaincinv( 3.0, 3.0, 0.4, 0.6 )\n    [ ~0.446, ~0.554 ]\n    > y = base.kernelBetaincinv( 1.0, 6.0, 0.4, 0.6 )\n    [ ~0.082, ~0.918 ]\n    > y = base.kernelBetaincinv( 1.0, 6.0, 0.8, 0.2 )\n    [ ~0.235, ~0.765 ]\n\n    See Also\n    --------\n    base.betaincinv\n","base.kernelCos":"\nbase.kernelCos( x, y )\n    Computes the cosine of a double-precision floating-point number on the\n    interval [-π/4, π/4].\n\n    For increased accuracy, the number for which the cosine should be evaluated\n    can be supplied as a double-double number (i.e., a non-evaluated sum of two\n    double-precision floating-point numbers `x` and `y`).\n\n    The two numbers must satisfy `|y| < 0.5 * ulp( x )`.\n\n    If either argument is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    y: number\n        Tail of `x`.\n\n    Returns\n    -------\n    out: number\n        Cosine.\n\n    Examples\n    --------\n    > var out = base.kernelCos( 0.0, 0.0 )\n    ~1.0\n    > out = base.kernelCos( PI/6.0, 0.0 )\n    ~0.866\n    > out = base.kernelCos( 0.785, -1.144e-17 )\n    ~0.707\n    > out = base.kernelCos( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cos, base.kernelSin, base.kernelTan\n","base.kernelLog1p":"\nbase.kernelLog1p( f )\n    Computes `log(1+f) - f` for `1+f` in ~[sqrt(2)/2, sqrt(2)].\n\n    This function provides a common means for computing logarithms in base e.\n    Argument reduction and adding the final term of the polynomial must be done\n    by the caller for increased accuracy when different bases are used.\n\n    Parameters\n    ----------\n    f: number\n        Input value.\n\n    Returns\n    -------\n    out: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.kernelLog1p( 1.0 )\n    ~0.1931\n    > y = base.kernelLog1p( 1.4142135623730951 )\n    ~0.4672\n    > y = base.kernelLog1p( NaN )\n    NaN\n\n    See Also\n    --------\n    base.log1p\n","base.kernelSin":"\nbase.kernelSin( x, y )\n    Computes the sine of a double-precision floating-point number on [-π/4,π/4].\n\n    For increased accuracy, the number for which the cosine should be evaluated\n    can be supplied as a double-double number (i.e., a non-evaluated sum of two\n    double-precision floating-point numbers `x` and `y`).\n\n    The two numbers must satisfy `|y| < 0.5 * ulp( x )`.\n\n    If either argument is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    y: number\n        Tail of `x`.\n\n    Returns\n    -------\n    out: number\n        Sine.\n\n    Examples\n    --------\n    > var y = base.kernelSin( 0.0, 0.0 )\n    ~0.0\n    > y = base.kernelSin( PI/6.0, 0.0 )\n    ~0.5\n    > y = base.kernelSin( 0.619, 9.279e-18 )\n    ~0.58\n\n    > y = base.kernelSin( NaN, 0.0 )\n    NaN\n    > y = base.kernelSin( 2.0, NaN )\n    NaN\n    > y = base.kernelSin( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.kernelCos, base.kernelTan, base.sin\n","base.kernelTan":"\nbase.kernelTan( x, y, k )\n    Computes the tangent of a double-precision floating-point number on the\n    interval [-π/4, π/4].\n\n    For increased accuracy, the number for which the tangent should be evaluated\n    can be supplied as a double-double number (i.e., a non-evaluated sum of two\n    double-precision floating-point numbers `x` and `y`).\n\n    The numbers `x` and `y` must satisfy `|y| < 0.5 * ulp( x )`.\n\n    If either `x` or `y` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    y: number\n        Tail of `x`.\n\n    k: integer\n        If `k=1`, the function returns `tan(x+y)`. If `k=-1`, the function\n        returns the negative inverse `-1/tan(x+y)`.\n\n    Returns\n    -------\n    out: number\n        Tangent.\n\n    Examples\n    --------\n    > var out = base.kernelTan( PI/4.0, 0.0, 1 )\n    ~1.0\n    > out = base.kernelTan( PI/4.0, 0.0, -1 )\n    ~-1.0\n    > out = base.kernelTan( PI/6.0, 0.0, 1 )\n    ~0.577\n    > out = base.kernelTan( 0.664, 5.288e-17, 1 )\n    ~0.783\n\n    > out = base.kernelTan( NaN, 0.0, 1 )\n    NaN\n    > out = base.kernelTan( 3.0, NaN, 1 )\n    NaN\n    > out = base.kernelTan( 3.0, 0.0, NaN )\n    NaN\n\n    See Also\n    --------\n    base.kernelCos, base.kernelSin, base.tan\n","base.kroneckerDelta":"\nbase.kroneckerDelta( i, j )\n    Evaluates the Kronecker delta.\n\n    If `i == j`, the function returns `1`; otherwise, the function returns zero.\n\n    Parameters\n    ----------\n    i: number\n        Input value.\n\n    j: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.kroneckerDelta( 3.14, 0.0 )\n    0.0\n    > y = base.kroneckerDelta( 3.14, 3.14 )\n    1.0\n\n    See Also\n    --------\n    base.diracDelta\n","base.kroneckerDeltaf":"\nbase.kroneckerDeltaf( i, j )\n    Evaluates the Kronecker delta (single-precision).\n\n    If `i == j`, the function returns `1`; otherwise, the function returns zero.\n\n    Parameters\n    ----------\n    i: number\n        Input value.\n\n    j: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.kroneckerDeltaf( 3.14, 0.0 )\n    0.0\n    > y = base.kroneckerDeltaf( 3.14, 3.14 )\n    1.0\n\n    See Also\n    --------\n    base.kroneckerDelta\n","base.labs":"\nbase.labs( x )\n    Computes an absolute value of a signed 32-bit integer in two's complement\n    format.\n\n    Parameters\n    ----------\n    x: integer\n        Signed 32-bit integer.\n\n    Returns\n    -------\n    out: integer\n        Absolute value.\n\n    Examples\n    --------\n    > var v = base.labs( -1|0 )\n    1\n    > v = base.labs( 2|0 )\n    2\n    > v = base.labs( 0|0 )\n    0\n\n    See Also\n    --------\n    base.abs\n","base.last":"\nbase.last( str, n )\n    Returns the last `n` UTF-16 code units of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of UTF-16 code units to return.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.last( 'hello', 1 )\n    'o'\n    > out = base.last( 'JavaScript', 6 )\n    'Script'\n    > out = base.last( 'foo bar', 10 )\n    'foo bar'\n\n    See Also\n    --------\n    base.firstCodeUnit, base.lastCodePoint, base.lastGraphemeCluster\n","base.lastCodePoint":"\nbase.lastCodePoint( str, n )\n    Returns the last `n` Unicode code points of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of Unicode code points to return.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.lastCodePoint( 'hello world', 1 )\n    'd'\n    > out = base.lastCodePoint( 'JavaScript', 6 )\n    'Script'\n    > out = base.lastCodePoint( 'अनुच्छेद', 1 )\n    'द'\n\n    See Also\n    --------\n    base.firstCodePoint, base.lastGraphemeCluster, base.last\n","base.lastGraphemeCluster":"\nbase.lastGraphemeCluster( str, n )\n    Returns the last `n` grapheme clusters (i.e., user-perceived characters) of\n    a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of grapheme clusters to return.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.lastGraphemeCluster( 'beep', 1 )\n    'p'\n    > out = base.lastGraphemeCluster( 'Boop', 2 )\n    'op'\n    > out = base.lastGraphemeCluster( 'JavaScript', 6 )\n    'Script'\n\n    See Also\n    --------\n    base.firstGraphemeCluster, base.lastCodePoint, base.last\n","base.lcm":"\nbase.lcm( a, b )\n    Computes the least common multiple (lcm).\n\n    If either `a` or `b` is `0`, the function returns `0`.\n\n    Both `a` and `b` must have integer values; otherwise, the function returns\n    `NaN`.\n\n    Parameters\n    ----------\n    a: integer\n        First integer.\n\n    b: integer\n        Second integer.\n\n    Returns\n    -------\n    out: integer\n        Least common multiple.\n\n    Examples\n    --------\n    > var v = base.lcm( 21, 6 )\n    42\n\n    See Also\n    --------\n    base.gcd\n","base.ldexp":"\nbase.ldexp( frac, exp )\n    Multiplies a double-precision floating-point number by an integer power of\n    two; i.e., `x = frac * 2^exp`.\n\n    If `frac` equals positive or negative `zero`, `NaN`, or positive or negative\n    infinity, the function returns a value equal to `frac`.\n\n    Parameters\n    ----------\n    frac: number\n        Fraction.\n\n    exp: number\n        Exponent.\n\n    Returns\n    -------\n    out: number\n        Double-precision floating-point number equal to `frac * 2^exp`.\n\n    Examples\n    --------\n    > var x = base.ldexp( 0.5, 3 )\n    4.0\n    > x = base.ldexp( 4.0, -2 )\n    1.0\n    > x = base.ldexp( 0.0, 20 )\n    0.0\n    > x = base.ldexp( -0.0, 39 )\n    -0.0\n    > x = base.ldexp( NaN, -101 )\n    NaN\n    > x = base.ldexp( PINF, 11 )\n    Infinity\n    > x = base.ldexp( NINF, -118 )\n    -Infinity\n\n    See Also\n    --------\n    base.frexp\n","base.leftPad":"\nbase.leftPad( str, len, pad )\n    Left pads a string such that the padded string has a length of at least\n    `len`.\n\n    An output string is not guaranteed to have a length of exactly `len`, but to\n    have a length of at least `len`. To generate a padded string having a length\n    equal to `len`, post-process a padded string by trimming off excess\n    characters.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    len: integer\n        Minimum string length.\n\n    pad: string\n        String used to pad.\n\n    Returns\n    -------\n    out: string\n        Padded string.\n\n    Examples\n    --------\n    > var out = base.leftPad( 'a', 5, ' ' )\n    '    a'\n    > out = base.leftPad( 'beep', 10, 'b' )\n    'bbbbbbbeep'\n    > out = base.leftPad( 'boop', 12, 'beep' )\n    'beepbeepboop'\n\n    See Also\n    --------\n    base.rightPad\n","base.leftTrim":"\nbase.leftTrim( str )\n    Trims whitespace from the beginning of a string.\n\n    \"Whitespace\" is defined as the following characters:\n\n    - \\f\n    - \\n\n    - \\r\n    - \\t\n    - \\v\n    - \\u0020\n    - \\u00a0\n    - \\u1680\n    - \\u2000-\\u200a\n    - \\u2028\n    - \\u2029\n    - \\u202f\n    - \\u205f\n    - \\u3000\n    - \\ufeff\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Trimmed string.\n\n    Examples\n    --------\n    > var out = base.leftTrim( ' \\r\\n\\t  Beep \\t\\t\\n  ' )\n    'Beep \\t\\t\\n  '\n\n    See Also\n    --------\n    base.rightTrim, base.trim\n","base.ln":"\nbase.ln( x )\n    Evaluates the natural logarithm of a double-precision floating-point number.\n\n    For negative numbers, the natural logarithm is not defined.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.ln( 4.0 )\n    ~1.386\n    > y = base.ln( 0.0 )\n    -Infinity\n    > y = base.ln( PINF )\n    Infinity\n    > y = base.ln( NaN )\n    NaN\n    > y = base.ln( -4.0 )\n    NaN\n\n    See Also\n    --------\n    base.exp, base.log10, base.log1p, base.log2\n","base.log":"\nbase.log( x, b )\n    Computes the base `b` logarithm of a double-precision floating-point number.\n\n    For negative `b` or `x`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    b: number\n        Base.\n\n    Returns\n    -------\n    y: number\n        Logarithm (base `b`).\n\n    Examples\n    --------\n    > var y = base.log( 100.0, 10.0 )\n    2.0\n    > y = base.log( 16.0, 2.0 )\n    4.0\n    > y = base.log( 5.0, 1.0 )\n    Infinity\n    > y = base.log( NaN, 2.0 )\n    NaN\n    > y = base.log( 1.0, NaN )\n    NaN\n    > y = base.log( -4.0, 2.0 )\n    NaN\n    > y = base.log( 4.0, -2.0 )\n    NaN\n\n    See Also\n    --------\n    base.exp, base.ln, base.log10, base.log1p, base.log2\n","base.log1mexp":"\nbase.log1mexp( x )\n    Evaluates the natural logarithm of `1-exp(-|x|)`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.log1mexp( -10.0 )\n    ~-0.00005\n    > y = base.log1mexp( 0.0 )\n    -Infinity\n    > y = base.log1mexp( 5.0 )\n    ~-0.00676\n    > y = base.log1mexp( 10.0 )\n    ~-0.00005\n    > y = base.log1mexp( NaN )\n    NaN\n\n    See Also\n    --------\n    base.exp, base.ln, base.log1p, base.log1pexp","base.log1p":"\nbase.log1p( x )\n    Evaluates the natural logarithm of `1+x`.\n\n    For `x < -1`, the function returns `NaN`, as the natural logarithm is not\n    defined for negative numbers.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.log1p( 4.0 )\n    ~1.609\n    > y = base.log1p( -1.0 )\n    -Infinity\n    > y = base.log1p( 0.0 )\n    0.0\n    > y = base.log1p( -0.0 )\n    -0.0\n    > y = base.log1p( -2.0 )\n    NaN\n    > y = base.log1p( NaN )\n    NaN\n\n    See Also\n    --------\n    base.ln, base.log\n","base.log1pexp":"\nbase.log1pexp( x )\n    Evaluates the natural logarithm of `1+exp(x)`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.log1pexp( -10.0 )\n    ~0.000045\n    > y = base.log1pexp( 0.0 )\n    ~0.693147\n    > y = base.log1pexp( 5.0 )\n    ~5.006715\n    > y = base.log1pexp( 34.0 )\n    34.0\n    > y = base.log1pexp( NaN )\n    NaN\n\n    See Also\n    --------\n    base.exp, base.ln, base.log1mexp, base.log1p","base.log1pmx":"\nbase.log1pmx( x )\n    Evaluates `ln(1+x) - x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > base.log1pmx( 1.1 )\n    ~-0.358\n    > base.log1pmx( 0.99 )\n    ~-0.302\n    > base.log1pmx( -0.99 )\n    ~-3.615\n    > base.log1pmx( -1.1 )\n    NaN\n    > base.log1pmx( NaN )\n    NaN\n\n    See Also\n    --------\n    base.ln, base.log1p","base.log2":"\nbase.log2( x )\n    Evaluates the binary logarithm (base two).\n\n    For negative numbers, the binary logarithm is not defined.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.log2( 4.0 )\n    2.0\n    > y = base.log2( 8.0 )\n    3.0\n    > y = base.log2( 0.0 )\n    -Infinity\n    > y = base.log2( PINF )\n    Infinity\n    > y = base.log2( NaN )\n    NaN\n    > y = base.log2( -4.0 )\n    NaN\n\n    See Also\n    --------\n    base.exp2, base.ln, base.log\n","base.log10":"\nbase.log10( x )\n    Evaluates the common logarithm (base 10).\n\n    For negative numbers, the common logarithm is not defined.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.log10( 100.0 )\n    2.0\n    > y = base.log10( 8.0 )\n    ~0.903\n    > y = base.log10( 0.0 )\n    -Infinity\n    > y = base.log10( PINF )\n    Infinity\n    > y = base.log10( NaN )\n    NaN\n    > y = base.log10( -4.0 )\n    NaN\n\n    See Also\n    --------\n    base.exp10, base.ln, base.log\n","base.logaddexp":"\nbase.logaddexp( x, y )\n    Computes the natural logarithm of `exp(x) + exp(y)`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    y: number\n        Input value.\n\n    Returns\n    -------\n    v: number\n        Function value.\n\n    Examples\n    --------\n    > var v = base.logaddexp( 90.0, 90.0 )\n    ~90.6931\n    > v = base.logaddexp( -20.0, 90.0 )\n    90.0\n    > v = base.logaddexp( 0.0, -100.0 )\n    ~3.7201e-44\n    > v = base.logaddexp( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.exp, base.ln\n","base.logit":"\nbase.logit( p )\n    Evaluates the logit function.\n\n    Let `p` be the probability of some event. The logit function is defined as\n    the logarithm of the odds `p / (1-p)`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.logit( 0.2 )\n    ~-1.386\n    > y = base.logit( 0.9 )\n    ~2.197\n    > y = base.logit( -4.0 )\n    NaN\n    > y = base.logit( 1.5 )\n    NaN\n    > y = base.logit( NaN )\n    NaN\n\n","base.lowercase":"\nbase.lowercase( str )\n    Converts a string to lowercase.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Lowercase string.\n\n    Examples\n    --------\n    > var out = base.lowercase( 'bEEp' )\n    'beep'\n\n    See Also\n    --------\n    base.snakecase, base.uppercase\n","base.lucas":"\nbase.lucas( n )\n    Computes the nth Lucas number.\n\n    Lucas numbers follow the recurrence relation\n\n      L_n = L_{n-1} + L_{n-2}\n\n    with seed values L_0 = 2 and L_1 = 1.\n\n    If `n` is greater than `76`, the function returns `NaN`, as larger Lucas\n    numbers cannot be accurately represented due to limitations of double-\n    precision floating-point format.\n\n    If not provided a nonnegative integer value, the function returns `NaN`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Input value.\n\n    Returns\n    -------\n    y: integer\n        Lucas number.\n\n    Examples\n    --------\n    > var y = base.lucas( 0 )\n    2\n    > y = base.lucas( 1 )\n    1\n    > y = base.lucas( 2 )\n    3\n    > y = base.lucas( 3 )\n    4\n    > y = base.lucas( 4 )\n    7\n    > y = base.lucas( 77 )\n    NaN\n    > y = base.lucas( NaN )\n    NaN\n\n    See Also\n    --------\n    base.fibonacci, base.negalucas\n","base.lucaspoly":"\nbase.lucaspoly( n, x )\n    Evaluates a Lucas polynomial.\n\n    Parameters\n    ----------\n    n: integer\n        Lucas polynomial to evaluate.\n\n    x: number\n        Value at which to evaluate the Lucas polynomial.\n\n    Returns\n    -------\n    out: number\n        Evaluated Lucas polynomial.\n\n    Examples\n    --------\n    // 2^5 + 5*2^3 + 5*2\n    > var v = base.lucaspoly( 5, 2.0 )\n    82.0\n\n\nbase.lucaspoly.factory( n )\n    Returns a function for evaluating a Lucas polynomial.\n\n    Parameters\n    ----------\n    n: integer\n        Lucas polynomial to evaluate.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a Lucas polynomial.\n\n    Examples\n    --------\n    > var polyval = base.lucaspoly.factory( 5 );\n\n    // 1^5 + 5*1^2 + 5\n    > var v = polyval( 1.0 )\n    11.0\n\n    // 2^5 + 5*2^3 + 5*2\n    > v = polyval( 2.0 )\n    82.0\n\n    See Also\n    --------\n    base.evalpoly, base.fibpoly\n","base.lucaspoly.factory":"\nbase.lucaspoly.factory( n )\n    Returns a function for evaluating a Lucas polynomial.\n\n    Parameters\n    ----------\n    n: integer\n        Lucas polynomial to evaluate.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a Lucas polynomial.\n\n    Examples\n    --------\n    > var polyval = base.lucaspoly.factory( 5 );\n\n    // 1^5 + 5*1^2 + 5\n    > var v = polyval( 1.0 )\n    11.0\n\n    // 2^5 + 5*2^3 + 5*2\n    > v = polyval( 2.0 )\n    82.0\n\n    See Also\n    --------\n    base.evalpoly, base.fibpoly","base.max":"\nbase.max( x, y )\n    Returns the maximum value.\n\n    If any argument is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    > var v = base.max( 3.14, 4.2 )\n    4.2\n    > v = base.max( 3.14, NaN )\n    NaN\n    > v = base.max( +0.0, -0.0 )\n    +0.0\n\n    See Also\n    --------\n    base.maxabs, base.maxn, base.min\n","base.maxabs":"\nbase.maxabs( x, y )\n    Returns the maximum absolute value.\n\n    If any argument is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    > var v = base.maxabs( 3.14, -4.2 )\n    4.2\n    > v = base.maxabs( 3.14, NaN )\n    NaN\n    > v = base.maxabs( +0.0, -0.0 )\n    +0.0\n\n    See Also\n    --------\n    base.max, base.minabs\n","base.maxabsn":"\nbase.maxabsn( [x[, y[, ...args]]] )\n    Returns the maximum absolute value.\n\n    If any argument is `NaN`, the function returns `NaN`.\n\n    When an empty set is considered a subset of the extended reals (all real\n    numbers, including positive and negative infinity), negative infinity is the\n    least upper bound. Similar to zero being the identity element for the sum of\n    an empty set and to one being the identity element for the product of an\n    empty set, negative infinity is the identity element for the maximum, and\n    thus, if not provided any arguments, the function returns `+infinity` (i.e.,\n    the absolute value of `-infinity`).\n\n    Parameters\n    ----------\n    x: number (optional)\n        First number.\n\n    y: number (optional)\n        Second number.\n\n    args: ...number (optional)\n        Numbers.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    > var v = base.maxabsn( 3.14, -4.2 )\n    4.2\n    > v = base.maxabsn( 5.9, 3.14, 4.2 )\n    5.9\n    > v = base.maxabsn( 3.14, NaN )\n    NaN\n    > v = base.maxabsn( +0.0, -0.0 )\n    +0.0\n\n    See Also\n    --------\n    base.maxn, base.maxabs, base.minabsn\n","base.maxn":"\nbase.maxn( [x[, y[, ...args]]] )\n    Returns the maximum value.\n\n    If any argument is `NaN`, the function returns `NaN`.\n\n    When an empty set is considered a subset of the extended reals (all real\n    numbers, including positive and negative infinity), negative infinity is the\n    least upper bound. Similar to zero being the identity element for the sum of\n    an empty set and to one being the identity element for the product of an\n    empty set, negative infinity is the identity element for the maximum, and\n    thus, if not provided any arguments, the function returns negative infinity.\n\n    Parameters\n    ----------\n    x: number (optional)\n        First number.\n\n    y: number (optional)\n        Second number.\n\n    args: ...number (optional)\n        Numbers.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    > var v = base.maxn( 3.14, 4.2 )\n    4.2\n    > v = base.maxn( 5.9, 3.14, 4.2 )\n    5.9\n    > v = base.maxn( 3.14, NaN )\n    NaN\n    > v = base.maxn( +0.0, -0.0 )\n    +0.0\n\n    See Also\n    --------\n    base.max, base.maxabsn, base.minn\n","base.min":"\nbase.min( x, y )\n    Returns the minimum value.\n\n    If any argument is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    > var v = base.min( 3.14, 4.2 )\n    3.14\n    > v = base.min( 3.14, NaN )\n    NaN\n    > v = base.min( +0.0, -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.max, base.minabs, base.minn\n","base.minabs":"\nbase.minabs( x, y )\n    Returns the minimum absolute value.\n\n    If any argument is `NaN`, the function returns `NaN`.\n\n    When an empty set is considered a subset of the extended reals (all real\n    numbers, including positive and negative infinity), positive infinity is the\n    greatest upper bound. Similar to zero being the identity element for the sum\n    of an empty set and to one being the identity element for the product of an\n    empty set, positive infinity is the identity element for the minimum, and\n    thus, if not provided any arguments, the function returns positive infinity.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    > var v = base.minabs( 3.14, -4.2 )\n    3.14\n    > v = base.minabs( 3.14, NaN )\n    NaN\n    > v = base.minabs( +0.0, -0.0 )\n    +0.0\n\n    See Also\n    --------\n    base.maxabs, base.min\n","base.minabsn":"\nbase.minabsn( [x[, y[, ...args]]] )\n    Returns the minimum absolute value.\n\n    If any argument is `NaN`, the function returns `NaN`.\n\n    When an empty set is considered a subset of the extended reals (all real\n    numbers, including positive and negative infinity), positive infinity is the\n    greatest upper bound. Similar to zero being the identity element for the sum\n    of an empty set and to one being the identity element for the product of an\n    empty set, positive infinity is the identity element for the minimum, and\n    thus, if not provided any arguments, the function returns positive infinity.\n\n    Parameters\n    ----------\n    x: number (optional)\n        First number.\n\n    y: number (optional)\n        Second number.\n\n    args: ...number (optional)\n        Numbers.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    > var v = base.minabsn( 3.14, -4.2 )\n    3.14\n    > v = base.minabsn( 5.9, 3.14, 4.2 )\n    3.14\n    > v = base.minabsn( 3.14, NaN )\n    NaN\n    > v = base.minabsn( +0.0, -0.0 )\n    +0.0\n\n    See Also\n    --------\n    base.maxabsn, base.minn, base.minabs\n","base.minmax":"\nbase.minmax( x, y )\n    Returns the minimum and maximum values.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum values.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: Array<number>\n        Minimum and maximum values.\n\n    Examples\n    --------\n    > var v = base.minmax( 3.14, 4.2 )\n    [ 3.14, 4.2 ]\n    > v = base.minmax( 3.14, NaN )\n    [ NaN, NaN ]\n    > v = base.minmax( +0.0, -0.0 )\n    [ -0.0, +0.0 ]\n\n\nbase.minmax.assign( x, y, out, stride, offset )\n    Returns the minimum and maximum values and assigns results to a provided\n    output array.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum values.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    out: Array|TypedArray|Object\n        Output object.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Minimum and maximum values.\n\n    Examples\n    --------\n    > var out = [ 0.0, 0.0 ];\n    > var v = base.minmax.assign( 3.14, -1.5, out, 1, 0 )\n    [ -1.5, 3.14 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.max, base.min, base.minmaxabs","base.minmax.assign":"\nbase.minmax.assign( x, y, out, stride, offset )\n    Returns the minimum and maximum values and assigns results to a provided\n    output array.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum values.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    out: Array|TypedArray|Object\n        Output object.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Minimum and maximum values.\n\n    Examples\n    --------\n    > var out = [ 0.0, 0.0 ];\n    > var v = base.minmax.assign( 3.14, -1.5, out, 1, 0 )\n    [ -1.5, 3.14 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.max, base.min, base.minmaxabs","base.minmaxabs":"\nbase.minmaxabs( x, y )\n    Returns the minimum and maximum absolute values.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum absolute values.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: Array<number>\n        Minimum and maximum absolute values.\n\n    Examples\n    --------\n    > var v = base.minmaxabs( 3.14, 4.2 )\n    [ 3.14, 4.2 ]\n    > v = base.minmaxabs( -5.9, 3.14)\n    [ 3.14, 5.9 ]\n    > v = base.minmaxabs( 3.14, NaN )\n    [ NaN, NaN ]\n    > v = base.minmaxabs( +0.0, -0.0 )\n    [ 0.0, 0.0 ]\n\n\nbase.minmaxabs.assign( x, y, out, stride, offset )\n    Returns the minimum and maximum absolute values.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum absolute values.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    out: Array|TypedArray|Object\n        Output object.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Minimum and maximum absolute values.\n\n    Examples\n    --------\n    > var out = [ 0.0, 0.0 ];\n    > var v = base.minmaxabs.assign( 3.14, -3.14, out, 1, 0 )\n    [ 3.14, 3.14 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.maxabs, base.minabs, base.minmax\n","base.minmaxabs.assign":"\nbase.minmaxabs.assign( x, y, out, stride, offset )\n    Returns the minimum and maximum absolute values.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum absolute values.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    out: Array|TypedArray|Object\n        Output object.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Minimum and maximum absolute values.\n\n    Examples\n    --------\n    > var out = [ 0.0, 0.0 ];\n    > var v = base.minmaxabs.assign( 3.14, -3.14, out, 1, 0 )\n    [ 3.14, 3.14 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.maxabs, base.minabs, base.minmax","base.minmaxabsn":"\nbase.minmaxabsn( [x[, y[, ...args]]] )\n    Returns the minimum and maximum absolute values.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum absolute values.\n\n    When an empty set is considered a subset of the extended reals (all real\n    numbers, including positive and negative infinity), positive infinity is the\n    greatest lower bound and negative infinity is the least upper bound. Similar\n    to zero being the identity element for the sum of an empty set and to one\n    being the identity element for the product of an empty set, positive\n    infinity is the identity element for the minimum and negative infinity is\n    the identity element for the maximum, and thus, if not provided any\n    arguments, the function returns positive infinity for both the minimum and\n    maximum absolute values.\n\n    Parameters\n    ----------\n    x: number (optional)\n        First number.\n\n    y: number (optional)\n        Second number.\n\n    args: ...number (optional)\n        Numbers.\n\n    Returns\n    -------\n    out: Array<number>\n        Minimum and maximum absolute values.\n\n    Examples\n    --------\n    > var v = base.minmaxabsn( 3.14, 4.2 )\n    [ 3.14, 4.2 ]\n    > v = base.minmaxabsn( -5.9, 3.14, 4.2 )\n    [ 3.14, 5.9 ]\n    > v = base.minmaxabsn( 3.14, NaN )\n    [ NaN, NaN ]\n    > v = base.minmaxabsn( +0.0, -0.0 )\n    [ 0.0, 0.0 ]\n    > v = base.minmaxabsn( 3.14 )\n    [ 3.14, 3.14 ]\n\n\nbase.minmaxabsn.assign( [x[, y[, ...args]]], out, stride, offset )\n    Returns the minimum and maximum absolute values.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum absolute values.\n\n    Parameters\n    ----------\n    x: number (optional)\n        First number.\n\n    y: number (optional)\n        Second number.\n\n    args: ...number (optional)\n        Numbers.\n\n    out: Array|TypedArray|Object\n        Output object.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Minimum and maximum absolute values.\n\n    Examples\n    --------\n    > var out = [ 0.0, 0.0 ];\n    > var v = base.minmaxabsn.assign( 3.14, out, 1, 0 )\n    [ 3.14, 3.14 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.maxabsn, base.minabsn, base.minmaxn\n","base.minmaxabsn.assign":"\nbase.minmaxabsn.assign( [x[, y[, ...args]]], out, stride, offset )\n    Returns the minimum and maximum absolute values.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum absolute values.\n\n    Parameters\n    ----------\n    x: number (optional)\n        First number.\n\n    y: number (optional)\n        Second number.\n\n    args: ...number (optional)\n        Numbers.\n\n    out: Array|TypedArray|Object\n        Output object.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Minimum and maximum absolute values.\n\n    Examples\n    --------\n    > var out = [ 0.0, 0.0 ];\n    > var v = base.minmaxabsn.assign( 3.14, out, 1, 0 )\n    [ 3.14, 3.14 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.maxabsn, base.minabsn, base.minmaxn","base.minmaxn":"\nbase.minmaxn( [x[, y[, ...args]]] )\n    Returns the minimum and maximum values.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum values.\n\n    When an empty set is considered a subset of the extended reals (all real\n    numbers, including positive and negative infinity), positive infinity is the\n    greatest lower bound and negative infinity is the least upper bound. Similar\n    to zero being the identity element for the sum of an empty set and to one\n    being the identity element for the product of an empty set, positive\n    infinity is the identity element for the minimum and negative infinity is\n    the identity element for the maximum, and thus, if not provided any\n    arguments, the function returns positive infinity for the minimum value and\n    negative infinity for the maximum value.\n\n    Parameters\n    ----------\n    x: number (optional)\n        First number.\n\n    y: number (optional)\n        Second number.\n\n    args: ...number (optional)\n        Numbers.\n\n    Returns\n    -------\n    out: Array<number>\n        Minimum and maximum values.\n\n    Examples\n    --------\n    > var v = base.minmaxn( 3.14, 4.2 )\n    [ 3.14, 4.2 ]\n    > v = base.minmaxn( 5.9, 3.14, 4.2 )\n    [ 3.14, 5.9 ]\n    > v = base.minmaxn( 3.14, NaN )\n    [ NaN, NaN ]\n    > v = base.minmaxn( +0.0, -0.0 )\n    [ -0.0, +0.0 ]\n    > v = base.minmaxn( 3.14 )\n    [ 3.14, 3.14 ]\n\n\nbase.minmaxn.assign( [x[, y[, ...args]]], out, stride, offset )\n    Returns the minimum and maximum values and assigns results to a provided\n    output array.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum values.\n\n    Parameters\n    ----------\n    x: number (optional)\n        First number.\n\n    y: number (optional)\n        Second number.\n\n    args: ...number (optional)\n        Numbers.\n\n    out: Array|TypedArray|Object\n        Output object.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Minimum and maximum values.\n\n    Examples\n    --------\n    > var out = [ 0.0, 0.0 ];\n    > var v = base.minmaxn.assign( 3.14, -1.5, out, 1, 0 )\n    [ -1.5, 3.14 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.maxn, base.minn, base.minmaxabsn","base.minmaxn.assign":"\nbase.minmaxn.assign( [x[, y[, ...args]]], out, stride, offset )\n    Returns the minimum and maximum values and assigns results to a provided\n    output array.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum values.\n\n    Parameters\n    ----------\n    x: number (optional)\n        First number.\n\n    y: number (optional)\n        Second number.\n\n    args: ...number (optional)\n        Numbers.\n\n    out: Array|TypedArray|Object\n        Output object.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Minimum and maximum values.\n\n    Examples\n    --------\n    > var out = [ 0.0, 0.0 ];\n    > var v = base.minmaxn.assign( 3.14, -1.5, out, 1, 0 )\n    [ -1.5, 3.14 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.maxn, base.minn, base.minmaxabsn","base.minn":"\nbase.minn( [x[, y[, ...args]]] )\n    Returns the minimum value.\n\n    If any argument is `NaN`, the function returns `NaN`.\n\n    When an empty set is considered a subset of the extended reals (all real\n    numbers, including positive and negative infinity), positive infinity is the\n    greatest lower bound. Similar to zero being the identity element for the sum\n    of an empty set and to one being the identity element for the product of an\n    empty set, positive infinity is the identity element for the minimum, and\n    thus, if not provided any arguments, the function returns positive infinity.\n\n    Parameters\n    ----------\n    x: number (optional)\n        First number.\n\n    y: number (optional)\n        Second number.\n\n    args: ...number (optional)\n        Numbers.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    > var v = base.minn( 3.14, 4.2 )\n    3.14\n    > v = base.minn( 5.9, 3.14, 4.2 )\n    3.14\n    > v = base.minn( 3.14, NaN )\n    NaN\n    > v = base.minn( +0.0, -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.maxn, base.min, base.minabsn\n","base.modf":"\nbase.modf( x )\n    Decomposes a double-precision floating-point number into integral and\n    fractional parts, each having the same type and sign as the input value.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    out: Array<number>\n        Integral and fractional parts.\n\n    Examples\n    --------\n    > var parts = base.modf( 3.14 )\n    [ 3.0, 0.14000000000000012 ]\n    > parts = base.modf( 3.14 )\n    [ 3.0, 0.14000000000000012 ]\n    > parts = base.modf( +0.0 )\n    [ +0.0, +0.0 ]\n    > parts = base.modf( -0.0 )\n    [ -0.0, -0.0 ]\n    > parts = base.modf( PINF )\n    [ Infinity, +0.0 ]\n    > parts = base.modf( NINF )\n    [ -Infinity, -0.0 ]\n    > parts = base.modf( NaN )\n    [ NaN, NaN ]\n\n\nbase.modf.assign( x, out, stride, offset )\n    Decomposes a double-precision floating-point number into integral and\n    fractional parts, each having the same type and sign as the input value,\n    and assigns results to a provided output array.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Integral and fractional parts.\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var parts = base.modf.assign( 3.14, out, 1, 0 )\n    <Float64Array>[ 3.0, 0.14000000000000012 ]\n    > var bool = ( parts === out )\n    true\n","base.modf.assign":"\nbase.modf.assign( x, out, stride, offset )\n    Decomposes a double-precision floating-point number into integral and\n    fractional parts, each having the same type and sign as the input value,\n    and assigns results to a provided output array.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Integral and fractional parts.\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var parts = base.modf.assign( 3.14, out, 1, 0 )\n    <Float64Array>[ 3.0, 0.14000000000000012 ]\n    > var bool = ( parts === out )\n    true","base.mul":"\nbase.mul( x, y )\n    Multiplies two double-precision floating-point numbers `x` and `y`.\n\n    Parameters\n    ----------\n    x: number\n        First input value.\n\n    y: number\n        Second input value.\n\n    Returns\n    -------\n    z: number\n        Result.\n\n    Examples\n    --------\n    > var v = base.mul( -1.0, 5.0 )\n    -5.0\n    > v = base.mul( 2.0, 5.0 )\n    10.0\n    > v = base.mul( 0.0, 5.0 )\n    0.0\n    > v = base.mul( -0.0, 0.0 )\n    -0.0\n    > v = base.mul( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.add, base.div, base.sub\n","base.mulf":"\nbase.mulf( x, y )\n    Multiplies two single-precision floating-point numbers `x` and `y`.\n\n    Parameters\n    ----------\n    x: number\n        First input value.\n\n    y: number\n        Second input value.\n\n    Returns\n    -------\n    z: number\n        Result.\n\n    Examples\n    --------\n    > var v = base.mulf( -1.0, 5.0 )\n    -5.0\n    > v = base.mulf( 2.0, 5.0 )\n    10.0\n    > v = base.mulf( 0.0, 5.0 )\n    0.0\n    > v = base.mulf( -0.0, 0.0 )\n    -0.0\n    > v = base.mulf( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.addf, base.divf, base.mul, base.subf\n","base.ndarray":"\nbase.ndarray( dtype, buffer, shape, strides, offset, order )\n    Returns an ndarray.\n\n    Parameters\n    ----------\n    dtype: string\n        Underlying data type.\n\n    buffer: ArrayLikeObject|TypedArray|Buffer\n        Data buffer. A data buffer must be an array-like object (i.e., have a\n        `length` property). For data buffers which are not indexed collections\n        (i.e., collections which cannot support direct index access, such as\n        `buffer[ index ]`; e.g., Complex64Array, Complex128Array, etc), a data\n        buffer should provide `#.get( idx )` and `#.set( v[, idx] )` methods.\n        Note that, for `set` methods, the value to set should be the first\n        argument, followed by the linear index, similar to the native typed\n        array `set` method.\n\n    shape: ArrayLikeObject<integer>\n        Array shape.\n\n    strides: ArrayLikeObject<integer>\n        Array strides.\n\n    offset: integer\n        Index offset.\n\n    order: string\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran-style).\n\n    Returns\n    -------\n    ndarray: ndarray\n        ndarray instance.\n\n    Examples\n    --------\n    // Create a new instance...\n    > var b = [ 1, 2, 3, 4 ]; // underlying data buffer\n    > var d = [ 2, 2 ]; // shape\n    > var s = [ 2, 1 ]; // strides\n    > var o = 0; // index offset\n    > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' )\n    <ndarray>\n\n    // Get an element using subscripts:\n    > var v = arr.get( 1, 1 )\n    4\n\n    // Get an element using a linear index:\n    > v = arr.iget( 3 )\n    4\n\n    // Set an element using subscripts:\n    > arr.set( 1, 1, 40 );\n    > arr.get( 1, 1 )\n    40\n\n    // Set an element using a linear index:\n    > arr.iset( 3, 99 );\n    > arr.get( 1, 1 )\n    99\n\n\nbase.ndarray.prototype.byteLength\n    Size (in bytes) of the array (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of the array.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.byteLength\n    32\n\n\nbase.ndarray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.BYTES_PER_ELEMENT\n    8\n\n\nbase.ndarray.prototype.data\n    Pointer to the underlying data buffer.\n\n    Returns\n    -------\n    buf: ArrayLikeObject|TypedArray|Buffer\n        Underlying data buffer.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var buf = arr.data\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n\nbase.ndarray.prototype.dtype\n    Underlying data type.\n\n    Returns\n    -------\n    dtype: string\n        Underlying data type.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var dt = arr.dtype\n    'float64'\n\n\nbase.ndarray.prototype.flags\n    Meta information, such as information concerning the memory layout of the\n    array.\n\n    Returns\n    -------\n    flags: Object\n        Info object.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var fl = arr.flags\n    {...}\n\n\nbase.ndarray.prototype.length\n    Length of the array (i.e., number of elements).\n\n    Returns\n    -------\n    len: integer\n        Array length.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var len = arr.length\n    4\n\n\nbase.ndarray.prototype.ndims\n    Number of dimensions.\n\n    Returns\n    -------\n    ndims: integer\n        Number of dimensions.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var n = arr.ndims\n    2\n\n\nbase.ndarray.prototype.offset\n    Index offset which specifies the buffer index at which to start iterating\n    over array elements.\n\n    Returns\n    -------\n    offset: integer\n        Index offset.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.offset\n    0\n\n\nbase.ndarray.prototype.order: string\n    Array order.\n\n    The array order is either row-major (C-style) or column-major (Fortran-\n    style).\n\n    Returns\n    -------\n    order: string\n        Array order.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var ord = arr.order\n    'row-major'\n\n\nbase.ndarray.prototype.shape\n    Array shape.\n\n    Returns\n    -------\n    shape: Array\n        Array shape.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sh = arr.shape\n    [ 2, 2 ]\n\n\nbase.ndarray.prototype.strides\n    Index strides which specify how to access data along corresponding array\n    dimensions.\n\n    Returns\n    -------\n    strides: Array\n        Index strides.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var st = arr.strides\n    [ 2, 1 ]\n\n\nbase.ndarray.prototype.get( ...idx )\n    Returns an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.get( 1, 1 )\n    4.0\n\n\nbase.ndarray.prototype.iget( idx )\n    Returns an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the input argument is ignored and, for clarity,\n    should not be provided.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.iget( 3 )\n    4.0\n\n\nbase.ndarray.prototype.set( ...idx, v )\n    Sets an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: ndarray\n        ndarray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > arr.set( 1, 1, -4.0 );\n    > arr.get( 1, 1 )\n    -4.0\n\n\nbase.ndarray.prototype.iset( idx, v )\n    Sets an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the first, and only, argument should be the\n    value to set.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: ndarray\n        ndarray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > arr.iset( 3, -4.0 );\n    > arr.iget( 3 )\n    -4.0\n\n\nbase.ndarray.prototype.toString()\n    Serializes an ndarray as a string.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    str: string\n        Serialized ndarray string.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toString()\n    '...'\n\n\nbase.ndarray.prototype.toJSON()\n    Serializes an ndarray as a JSON object.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toJSON()\n    {...}\n\n    See Also\n    --------\n    array, ndarray\n","base.ndarray.prototype.byteLength":"\nbase.ndarray.prototype.byteLength\n    Size (in bytes) of the array (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of the array.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.byteLength\n    32","base.ndarray.prototype.BYTES_PER_ELEMENT":"\nbase.ndarray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.BYTES_PER_ELEMENT\n    8","base.ndarray.prototype.data":"\nbase.ndarray.prototype.data\n    Pointer to the underlying data buffer.\n\n    Returns\n    -------\n    buf: ArrayLikeObject|TypedArray|Buffer\n        Underlying data buffer.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var buf = arr.data\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]","base.ndarray.prototype.dtype":"\nbase.ndarray.prototype.dtype\n    Underlying data type.\n\n    Returns\n    -------\n    dtype: string\n        Underlying data type.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var dt = arr.dtype\n    'float64'","base.ndarray.prototype.flags":"\nbase.ndarray.prototype.flags\n    Meta information, such as information concerning the memory layout of the\n    array.\n\n    Returns\n    -------\n    flags: Object\n        Info object.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var fl = arr.flags\n    {...}","base.ndarray.prototype.length":"\nbase.ndarray.prototype.length\n    Length of the array (i.e., number of elements).\n\n    Returns\n    -------\n    len: integer\n        Array length.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var len = arr.length\n    4","base.ndarray.prototype.ndims":"\nbase.ndarray.prototype.ndims\n    Number of dimensions.\n\n    Returns\n    -------\n    ndims: integer\n        Number of dimensions.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var n = arr.ndims\n    2","base.ndarray.prototype.offset":"\nbase.ndarray.prototype.offset\n    Index offset which specifies the buffer index at which to start iterating\n    over array elements.\n\n    Returns\n    -------\n    offset: integer\n        Index offset.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.offset\n    0","base.ndarray.prototype.order: string":"\nbase.ndarray.prototype.order: string\n    Array order.\n\n    The array order is either row-major (C-style) or column-major (Fortran-\n    style).\n\n    Returns\n    -------\n    order: string\n        Array order.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var ord = arr.order\n    'row-major'","base.ndarray.prototype.shape":"\nbase.ndarray.prototype.shape\n    Array shape.\n\n    Returns\n    -------\n    shape: Array\n        Array shape.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sh = arr.shape\n    [ 2, 2 ]","base.ndarray.prototype.strides":"\nbase.ndarray.prototype.strides\n    Index strides which specify how to access data along corresponding array\n    dimensions.\n\n    Returns\n    -------\n    strides: Array\n        Index strides.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var st = arr.strides\n    [ 2, 1 ]","base.ndarray.prototype.get":"\nbase.ndarray.prototype.get( ...idx )\n    Returns an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.get( 1, 1 )\n    4.0","base.ndarray.prototype.iget":"\nbase.ndarray.prototype.iget( idx )\n    Returns an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the input argument is ignored and, for clarity,\n    should not be provided.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.iget( 3 )\n    4.0","base.ndarray.prototype.set":"\nbase.ndarray.prototype.set( ...idx, v )\n    Sets an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: ndarray\n        ndarray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > arr.set( 1, 1, -4.0 );\n    > arr.get( 1, 1 )\n    -4.0","base.ndarray.prototype.iset":"\nbase.ndarray.prototype.iset( idx, v )\n    Sets an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the first, and only, argument should be the\n    value to set.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: ndarray\n        ndarray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > arr.iset( 3, -4.0 );\n    > arr.iget( 3 )\n    -4.0","base.ndarray.prototype.toString":"\nbase.ndarray.prototype.toString()\n    Serializes an ndarray as a string.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    str: string\n        Serialized ndarray string.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toString()\n    '...'","base.ndarray.prototype.toJSON":"\nbase.ndarray.prototype.toJSON()\n    Serializes an ndarray as a JSON object.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toJSON()\n    {...}\n\n    See Also\n    --------\n    array, ndarray","base.ndarrayUnary":"\nbase.ndarrayUnary( arrays, fcn )\n    Applies a unary callback to elements in an input ndarray and assigns results\n    to elements in an output ndarray.\n\n    Each provided \"ndarray\" should be an object with the following properties:\n\n    - dtype: data type.\n    - data: data buffer.\n    - shape: dimensions.\n    - strides: stride lengths.\n    - offset: index offset.\n    - order: specifies whether an ndarray is row-major (C-style) or column-major\n    (Fortran-style).\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ndarray>\n        Array-like object containing one input ndarray and one output ndarray.\n\n    fcn: Function\n        Unary callback.\n\n    Examples\n    --------\n    // Define ndarray data and meta data...\n    > var xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var dtype = 'float64';\n    > var shape = [ 2, 2 ];\n    > var sx = [ 2, 1 ];\n    > var sy = [ 2, 1 ];\n    > var ox = 0;\n    > var oy = 0;\n    > var order = 'row-major';\n\n    // Using ndarrays...\n    > var x = ndarray( dtype, xbuf, shape, sx, ox, order );\n    > var y = ndarray( dtype, ybuf, shape, sy, oy, order );\n    > base.ndarrayUnary( [ x, y ], base.abs );\n    > y.data\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Using minimal ndarray-like objects...\n    > x = {\n    ...     'dtype': dtype,\n    ...     'data': xbuf,\n    ...     'shape': shape,\n    ...     'strides': sx,\n    ...     'offset': ox,\n    ...     'order': order\n    ... };\n    > y = {\n    ...     'dtype': dtype,\n    ...     'data': ybuf,\n    ...     'shape': shape,\n    ...     'strides': sy,\n    ...     'offset': oy,\n    ...     'order': order\n    ... };\n    > base.ndarrayUnary( [ x, y ], base.abs );\n    > y.data\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    See Also\n    --------\n    ndarrayDispatch\n","base.ndzeros":"\nbase.ndzeros( dtype, shape, order )\n    Returns a zero-filled ndarray having a specified shape and data type.\n\n    Parameters\n    ----------\n    dtype: string\n        Underlying data type. Must be a numeric data type or \"generic\".\n\n    shape: ArrayLikeObject<integer>\n        Array shape.\n\n    order: string\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran-style).\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var arr = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n    <ndarray>\n    > var sh = arr.shape\n    [ 2, 2 ]\n    > var dt = arr.dtype\n    'float64'\n\n    See Also\n    --------\n    base.ndarray, base.ndzerosLike\n","base.ndzerosLike":"\nbase.ndzerosLike( x )\n    Returns a zero-filled ndarray having the same shape and data type as a\n    provided input ndarray.\n\n    Along with data type, shape, and order, the function infers the \"class\" of\n    the returned ndarray from the provided ndarray. For example, if provided a\n    \"base\" ndarray, the function returns a base ndarray. If provided a non-base\n    ndarray, the function returns a non-base ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n    <ndarray>\n    > var sh = x.shape\n    [ 2, 2 ]\n    > var dt = x.dtype\n    'float64'\n    > var y = base.ndzerosLike( x )\n    <ndarray>\n    > sh = y.shape\n    [ 2, 2 ]\n    > dt = y.dtype\n    'float64'\n\n    See Also\n    --------\n    base.ndarray, base.ndzeros\n","base.negafibonacci":"\nbase.negafibonacci( n )\n    Computes the nth negaFibonacci number.\n\n    The negaFibonacci numbers follow the recurrence relation\n\n      F_{n-2} = F_{n} - F_{n-1}\n\n    with seed values F_0 = 0 and F_{-1} = 1.\n\n    If `|n|` is greater than `78`, the function returns `NaN` as larger\n    negaFibonacci numbers cannot be accurately represented due to limitations of\n    double-precision floating-point format.\n\n    If not provided a non-positive integer value, the function returns `NaN`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Input value.\n\n    Returns\n    -------\n    y: integer\n        NegaFibonacci number.\n\n    Examples\n    --------\n    > var y = base.negafibonacci( 0 )\n    0\n    > y = base.negafibonacci( -1 )\n    1\n    > y = base.negafibonacci( -2 )\n    -1\n    > y = base.negafibonacci( -3 )\n    2\n    > y = base.negafibonacci( -4 )\n    -3\n    > y = base.negafibonacci( -79 )\n    NaN\n    > y = base.negafibonacci( -80 )\n    NaN\n    > y = base.negafibonacci( NaN )\n    NaN\n\n    See Also\n    --------\n    base.fibonacci, base.negalucas\n","base.negalucas":"\nbase.negalucas( n )\n    Computes the nth negaLucas number.\n\n    The negaLucas numbers follow the recurrence relation\n\n      L_{n-2} = L_{n} - L_{n-1}\n\n    with seed values L_0 = 2 and L_{-1} = -1.\n\n    If `|n|` is greater than `76`, the function returns `NaN` as larger\n    negaLucas numbers cannot be accurately represented due to limitations of\n    double-precision floating-point format.\n\n    If not provided a non-positive integer value, the function returns `NaN`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Input value.\n\n    Returns\n    -------\n    y: integer\n        NegaLucas number.\n\n    Examples\n    --------\n    > var y = base.negalucas( 0 )\n    2\n    > y = base.negalucas( -1 )\n    -1\n    > y = base.negalucas( -2 )\n    3\n    > y = base.negalucas( -3 )\n    -4\n    > y = base.negalucas( -4 )\n    7\n    > y = base.negalucas( -77 )\n    NaN\n    > y = base.negalucas( -78 )\n    NaN\n    > y = base.negalucas( NaN )\n    NaN\n\n    See Also\n    --------\n    base.fibonacci, base.lucas, base.negafibonacci\n","base.nonfibonacci":"\nbase.nonfibonacci( n )\n    Computes the nth non-Fibonacci number.\n\n    If not provided a nonnegative integer value, the function returns `NaN`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Non-Fibonacci number.\n\n    Examples\n    --------\n    > var v = base.nonfibonacci( 1 )\n    4\n    > v = base.nonfibonacci( 2 )\n    6\n    > v = base.nonfibonacci( 3 )\n    7\n    > v = base.nonfibonacci( NaN )\n    NaN\n\n    See Also\n    --------\n    base.fibonacci\n","base.normalize":"\nbase.normalize( x )\n    Returns a normal number and exponent satisfying `x = y * 2^exp` as an array.\n\n    The first element of the returned array corresponds to `y` and the second to\n    `exp`.\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    Returns\n    -------\n    out: Array<number>\n        An array containing `y` and `exp`.\n\n    Examples\n    --------\n    > var out = base.normalize( 3.14e-319 )\n    [ 1.4141234400356668e-303, -52 ]\n    > var y = out[ 0 ];\n    > var exponent = out[ 1 ];\n    > var bool = ( y*base.pow(2.0, exponent) === 3.14e-319 )\n    true\n\n    // Special cases:\n    > out = base.normalize( 0.0 )\n    [ 0.0, 0 ];\n    > out = base.normalize( PINF )\n    [ Infinity, 0 ]\n    > out = base.normalize( NINF )\n    [ -Infinity, 0 ]\n    > out = base.normalize( NaN )\n    [ NaN, 0 ]\n\n\nbase.normalize.assign( x, out, stride, offset )\n    Returns a normal number and exponent satisfying `x = y * 2^exp` and assigns\n    results to a provided output array.\n\n    The first element of the returned array corresponds to `y` and the second to\n    `exp`.\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Output array.\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 )\n    > var v = base.normalize.assign( 3.14e-319, out, 1, 0 )\n    <Float64Array>[ 1.4141234400356668e-303, -52 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.normalizef\n","base.normalize.assign":"\nbase.normalize.assign( x, out, stride, offset )\n    Returns a normal number and exponent satisfying `x = y * 2^exp` and assigns\n    results to a provided output array.\n\n    The first element of the returned array corresponds to `y` and the second to\n    `exp`.\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Output array.\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 )\n    > var v = base.normalize.assign( 3.14e-319, out, 1, 0 )\n    <Float64Array>[ 1.4141234400356668e-303, -52 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.normalizef","base.normalizef":"\nbase.normalizef( x )\n    Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` as\n    an array.\n\n    The first element of the returned array corresponds to `y` and the second to\n    `exp`.\n\n    While the function accepts higher precision floating-point numbers, beware\n    that providing such numbers can be a source of subtle bugs as the relation\n    `x = y * 2^exp` may not hold.\n\n    Parameters\n    ----------\n    x: float\n        Single-precision floating-point number.\n\n    Returns\n    -------\n    out: Array<number>\n        An array containing `y` and `exp`.\n\n    Examples\n    --------\n    > var out = base.normalizef( base.float64ToFloat32( 1.401e-45 ) )\n    [ 1.1754943508222875e-38, -23 ]\n    > var y = out[ 0 ];\n    > var exp = out[ 1 ];\n    > var bool = ( y*base.pow(2,exp) === base.float64ToFloat32(1.401e-45) )\n    true\n\n    // Special cases:\n    > out = base.normalizef( FLOAT32_PINF )\n    [ Infinity, 0 ]\n    > out = base.normalizef( FLOAT32_NINF )\n    [ -Infinity, 0 ]\n    > out = base.normalizef( NaN )\n    [ NaN, 0 ]\n\n\nbase.normalizef.assign( x, out, stride, offset )\n    Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` and\n    assigns results to a provided output array.\n\n    The first element of the returned array corresponds to `y` and the second to\n    `exp`.\n\n    While the function accepts higher precision floating-point numbers, beware\n    that providing such numbers can be a source of subtle bugs as the relation\n    `x = y * 2^exp` may not hold.\n\n    Parameters\n    ----------\n    x: float\n        Single-precision floating-point number.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        An array containing `y` and `exp`.\n\n    Examples\n    --------\n    > out = new Float32Array( 2 );\n    > var v = base.normalizef.assign( base.float64ToFloat32( 1.401e-45 ), out, 1, 0 )\n    <Float32Array>[ 1.1754943508222875e-38, -23.0 ]\n    > bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.normalize","base.normalizef.assign":"\nbase.normalizef.assign( x, out, stride, offset )\n    Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` and\n    assigns results to a provided output array.\n\n    The first element of the returned array corresponds to `y` and the second to\n    `exp`.\n\n    While the function accepts higher precision floating-point numbers, beware\n    that providing such numbers can be a source of subtle bugs as the relation\n    `x = y * 2^exp` may not hold.\n\n    Parameters\n    ----------\n    x: float\n        Single-precision floating-point number.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        An array containing `y` and `exp`.\n\n    Examples\n    --------\n    > out = new Float32Array( 2 );\n    > var v = base.normalizef.assign( base.float64ToFloat32( 1.401e-45 ), out, 1, 0 )\n    <Float32Array>[ 1.1754943508222875e-38, -23.0 ]\n    > bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.normalize","base.normalizeSlice":"\nbase.normalizeSlice( slice, len, strict )\n    Returns a normalized Slice object.\n\n    In strict mode, the function returns an error object if an input slice\n    exceeds index bounds.\n\n    A returned error object is a plain object having the following properties:\n\n    - code: error code.\n\n    A returned error object may have one of the following error codes:\n\n    - ERR_SLICE_OUT_OF_BOUNDS: a slice exceeds index bounds.\n\n    Parameters\n    ----------\n    slice: Slice\n        Input slice object.\n\n    len: integer\n        Maximum number of elements allowed in the slice.\n\n    strict: boolean\n        Boolean indicating whether to enforce strict bounds checking.\n\n    Returns\n    -------\n    s: Slice|Object\n        Slice instance (or an error object).\n\n    Examples\n    --------\n    > var s1 = new Slice( 1, 10, 1 );\n    > var s2 = base.normalizeSlice( s1, 5, false );\n    > s2.start\n    1\n    > s2.stop\n    5\n    > s2.step\n    1\n    > s1 = new Slice( -2, null, -1 );\n    > s2 = base.normalizeSlice( s1, 10, false );\n    > s2.start\n    8\n    > s2.stop\n    null\n    > s2.step\n    -1\n\n    See Also\n    --------\n    base.normalizeMultiSlice\n","base.normhermitepoly":"\nbase.normhermitepoly( n, x )\n    Evaluates a normalized Hermite polynomial using double-precision floating-\n    point arithmetic.\n\n    Parameters\n    ----------\n    n: integer\n        Nonnegative polynomial degree.\n\n    x: number\n        Value at which to evaluate the polynomial.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.normhermitepoly( 1, 0.5 )\n    0.5\n    > y = base.normhermitepoly( -1, 0.5 )\n    NaN\n    > y = base.normhermitepoly( 0, 0.5 )\n    1.0\n    > y = base.normhermitepoly( 2, 0.5 )\n    -0.75\n\n\nbase.normhermitepoly.factory( n )\n    Returns a function for evaluating a normalized Hermite polynomial using\n    double-precision floating-point arithmetic.\n\n    Parameters\n    ----------\n    n: integer\n        Nonnegative polynomial degree.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a normalized Hermite polynomial.\n\n    Examples\n    --------\n    > var f = base.normhermitepoly.factory( 2 );\n    > var v = f( 0.5 )\n    -0.75\n\n    See Also\n    --------\n    base.evalpoly, base.hermitepoly\n","base.normhermitepoly.factory":"\nbase.normhermitepoly.factory( n )\n    Returns a function for evaluating a normalized Hermite polynomial using\n    double-precision floating-point arithmetic.\n\n    Parameters\n    ----------\n    n: integer\n        Nonnegative polynomial degree.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a normalized Hermite polynomial.\n\n    Examples\n    --------\n    > var f = base.normhermitepoly.factory( 2 );\n    > var v = f( 0.5 )\n    -0.75\n\n    See Also\n    --------\n    base.evalpoly, base.hermitepoly","base.pascalcase":"\nbase.pascalcase( str )\n    Converts a string to Pascal case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Pascal-cased string.\n\n    Examples\n    --------\n    > var out = base.pascalcase( 'Hello World!' )\n    'HelloWorld'\n    > out = base.pascalcase( 'beep boop' )\n    'BeepBoop'\n\n    See Also\n    --------\n    base.camelcase, base.lowercase, base.uppercase","base.pdiff":"\nbase.pdiff( x, y )\n    Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n    returns `0`.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Positive difference.\n\n    Examples\n    --------\n    > var v = base.pdiff( 5.9, 3.14 )\n    2.76\n    > v = base.pdiff( 3.14, 4.2 )\n    0.0\n    > v = base.pdiff( 3.14, NaN )\n    NaN\n    > v = base.pdiff( -0.0, +0.0 )\n    +0.0\n\n","base.pdifff":"\nbase.pdifff( x, y )\n    Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n    returns `0`.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Positive difference.\n\n    Examples\n    --------\n    > var v = base.pdifff( 5.9, 3.15 )\n    2.75\n    > v = base.pdifff( 3.14, 4.2 )\n    0.0\n    > v = base.pdifff( 3.14, NaN )\n    NaN\n    > v = base.pdifff( -0.0, +0.0 )\n    +0.0\n\n    See Also\n    --------\n    base.pdiff\n","base.percentEncode":"\nbase.percentEncode( str )\n    Percent-encodes a UTF-16 encoded string according to RFC 3986.\n\n    Parameters\n    ----------\n    str: string\n        UTF-16 encoded string.\n\n    Returns\n    -------\n    out: string\n        Percent-encoded string.\n\n    Examples\n    --------\n    > var out = base.percentEncode( '☃' )\n    '%E2%98%83'\n\n","base.polygamma":"\nbase.polygamma( n, x )\n    Evaluates the polygamma function of order `n`; i.e., the (n+1)th derivative\n    of the natural logarithm of the gamma function.\n\n    If `n` is not a nonnegative integer, the function returns `NaN`.\n\n    If `x` is zero or a negative integer, the function returns `NaN`.\n\n    If provided `NaN` as either parameter, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Derivative order.\n\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var v = base.polygamma( 3, 1.2 )\n    ~3.245\n    > v = base.polygamma( 5, 1.2 )\n    ~41.39\n    > v = base.polygamma( 3, -4.9 )\n    ~60014.239\n    > v = base.polygamma( -1, 5.3 )\n    NaN\n    > v = base.polygamma( 2, -1.0 )\n    Infinity\n\n    See Also\n    --------\n    base.trigamma, base.digamma, base.gamma\n","base.pow":"\nbase.pow( b, x )\n    Evaluates the exponential function `bˣ`.\n\n    Parameters\n    ----------\n    b: number\n        Base.\n\n    x: number\n        Exponent.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.pow( 2.0, 3.0 )\n    8.0\n    > y = base.pow( 4.0, 0.5 )\n    2.0\n    > y = base.pow( 100.0, 0.0 )\n    1.0\n    > y = base.pow( PI, 5.0 )\n    ~306.0197\n    > y = base.pow( PI, -0.2 )\n    ~0.7954\n    > y = base.pow( NaN, 3.0 )\n    NaN\n    > y = base.pow( 5.0, NaN )\n    NaN\n    > y = base.pow( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.exp, base.powm1\n","base.powm1":"\nbase.powm1( b, x )\n    Evaluates `bˣ - 1`.\n\n    When `b` is close to `1` and/or `x` is small, this function is more accurate\n    than naively computing `bˣ` and subtracting `1`.\n\n    Parameters\n    ----------\n    b: number\n        Base.\n\n    x: number\n        Exponent.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.powm1( 2.0, 3.0 )\n    7.0\n    > y = base.powm1( 4.0, 0.5 )\n    1.0\n    > y = base.powm1( 0.0, 100.0 )\n    -1.0\n    > y = base.powm1( 100.0, 0.0 )\n    0.0\n    > y = base.powm1( 0.0, 0.0 )\n    0.0\n    > y = base.powm1( PI, 5.0 )\n    ~305.0197\n    > y = base.powm1( NaN, 3.0 )\n    NaN\n    > y = base.powm1( 5.0, NaN )\n    NaN\n\n    See Also\n    --------\n    base.pow\n","base.rad2deg":"\nbase.rad2deg( x )\n    Converts an angle from radians to degrees.\n\n    Parameters\n    ----------\n    x: number\n        Angle in radians.\n\n    Returns\n    -------\n    d: number\n        Angle in degrees.\n\n    Examples\n    --------\n    > var d = base.rad2deg( PI/2.0 )\n    90.0\n    > d = base.rad2deg( -PI/4.0 )\n    -45.0\n    > d = base.rad2deg( NaN )\n    NaN\n\n    // Due to finite precision, canonical values may not be returned:\n    > d = base.rad2deg( PI/6.0 )\n    29.999999999999996\n\n    See Also\n    --------\n    base.deg2rad\n","base.rad2degf":"\nbase.rad2degf( x )\n    Converts an angle from radians to degrees (single-precision).\n\n    Parameters\n    ----------\n    x: number\n        Angle in radians.\n\n    Returns\n    -------\n    d: number\n        Angle in degrees.\n\n    Examples\n    --------\n    > var d = base.rad2degf( 3.141592653589793 / 2.0 )\n    90.0\n    > d = base.rad2degf( -3.141592653589793 / 4.0 )\n    -45.0\n    > d = base.rad2degf( NaN )\n    NaN\n\n    // Due to finite precision, canonical values may not be returned:\n    > d = base.rad2degf( 3.141592653589793 / 6.0 )\n    30.000001907348633\n\n    See Also\n    --------\n    base.rad2deg\n","base.ramp":"\nbase.ramp( x )\n    Evaluates the ramp function.\n\n    If `x >= 0`, the function returns `x`; otherwise, the function returns zero.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.ramp( 3.14 )\n    3.14\n    > y = base.ramp( -3.14 )\n    0.0\n\n    See Also\n    --------\n    base.heaviside\n","base.rampf":"\nbase.rampf( x )\n    Evaluates the ramp function (single-precision).\n\n    If `x >= 0`, the function returns `x`; otherwise, the function returns zero.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.rampf( 3.14 )\n    3.14\n    > y = base.rampf( -3.14 )\n    0.0\n\n    See Also\n    --------\n    base.ramp\n","base.random.arcsine":"\nbase.random.arcsine( a, b )\n    Returns a pseudorandom number drawn from an arcsine distribution.\n\n    If `a >= b`, the function returns `NaN`.\n\n    If `a` or `b` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.arcsine( 2.0, 5.0 )\n    <number>\n\n\nbase.random.arcsine.factory( [a, b, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an arcsine distribution.\n\n    If provided `a` and `b`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `a` and `b`, the returned PRNG requires that both `a` and\n    `b` be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.arcsine.factory();\n    > var r = rand( 0.0, 1.0 )\n    <number>\n    > r = rand( -2.0, 2.0 )\n    <number>\n\n    // Provide `a` and `b`:\n    > rand = base.random.arcsine.factory( 0.0, 1.0 );\n    > r = rand()\n    <number>\n    > r = rand()\n    <number>\n\n\nbase.random.arcsine.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.arcsine.NAME\n    'arcsine'\n\n\nbase.random.arcsine.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.arcsine.PRNG;\n\n\nbase.random.arcsine.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.arcsine.seed;\n\n\nbase.random.arcsine.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.arcsine.seedLength;\n\n\nbase.random.arcsine.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.arcsine.state\n    <Uint32Array>\n\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n\n    // Set the state:\n    > base.random.arcsine.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n\n\nbase.random.arcsine.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.arcsine.stateLength;\n\n\nbase.random.arcsine.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.arcsine.byteLength;\n\n\nbase.random.arcsine.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.arcsine.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.arcsine, random.iterators.arcsine, random.streams.arcsine, base.random.beta\n","base.random.arcsine.factory":"\nbase.random.arcsine.factory( [a, b, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an arcsine distribution.\n\n    If provided `a` and `b`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `a` and `b`, the returned PRNG requires that both `a` and\n    `b` be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.arcsine.factory();\n    > var r = rand( 0.0, 1.0 )\n    <number>\n    > r = rand( -2.0, 2.0 )\n    <number>\n\n    // Provide `a` and `b`:\n    > rand = base.random.arcsine.factory( 0.0, 1.0 );\n    > r = rand()\n    <number>\n    > r = rand()\n    <number>","base.random.arcsine.NAME":"\nbase.random.arcsine.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.arcsine.NAME\n    'arcsine'","base.random.arcsine.PRNG":"\nbase.random.arcsine.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.arcsine.PRNG;","base.random.arcsine.seed":"\nbase.random.arcsine.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.arcsine.seed;","base.random.arcsine.seedLength":"\nbase.random.arcsine.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.arcsine.seedLength;","base.random.arcsine.state":"\nbase.random.arcsine.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.arcsine.state\n    <Uint32Array>\n\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n\n    // Set the state:\n    > base.random.arcsine.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>","base.random.arcsine.stateLength":"\nbase.random.arcsine.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.arcsine.stateLength;","base.random.arcsine.byteLength":"\nbase.random.arcsine.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.arcsine.byteLength;","base.random.arcsine.toJSON":"\nbase.random.arcsine.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.arcsine.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.arcsine, random.iterators.arcsine, random.streams.arcsine, base.random.beta","base.random.bernoulli":"\nbase.random.bernoulli( p )\n    Returns a pseudorandom number drawn from a Bernoulli distribution.\n\n    If `p < 0` or `p > 1` or `p` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.bernoulli( 0.8 );\n\n\nbase.random.bernoulli.factory( [p, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Bernoulli distribution.\n\n    If provided `p`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `p`, the returned PRNG requires that `p` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.bernoulli.factory();\n    > var r = rand( 0.3 );\n    > r = rand( 0.59 );\n\n    // Provide `p`:\n    > rand = base.random.bernoulli.factory( 0.3 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.bernoulli.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.bernoulli.NAME\n    'bernoulli'\n\n\nbase.random.bernoulli.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.bernoulli.PRNG;\n\n\nbase.random.bernoulli.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.bernoulli.seed;\n\n\nbase.random.bernoulli.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.bernoulli.seedLength;\n\n\nbase.random.bernoulli.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.bernoulli( 0.3 )\n    <number>\n    > r = base.random.bernoulli( 0.3 )\n    <number>\n    > r = base.random.bernoulli( 0.3 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.bernoulli.state\n    <Uint32Array>\n\n    > r = base.random.bernoulli( 0.3 )\n    <number>\n    > r = base.random.bernoulli( 0.3 )\n    <number>\n\n    // Set the state:\n    > base.random.bernoulli.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.bernoulli( 0.3 )\n    <number>\n    > r = base.random.bernoulli( 0.3 )\n    <number>\n\n\nbase.random.bernoulli.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.bernoulli.stateLength;\n\n\nbase.random.bernoulli.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.bernoulli.byteLength;\n\n\nbase.random.bernoulli.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.bernoulli.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.bernoulli, random.iterators.bernoulli, random.streams.bernoulli, base.random.binomial\n","base.random.bernoulli.factory":"\nbase.random.bernoulli.factory( [p, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Bernoulli distribution.\n\n    If provided `p`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `p`, the returned PRNG requires that `p` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.bernoulli.factory();\n    > var r = rand( 0.3 );\n    > r = rand( 0.59 );\n\n    // Provide `p`:\n    > rand = base.random.bernoulli.factory( 0.3 );\n    > r = rand();\n    > r = rand();","base.random.bernoulli.NAME":"\nbase.random.bernoulli.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.bernoulli.NAME\n    'bernoulli'","base.random.bernoulli.PRNG":"\nbase.random.bernoulli.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.bernoulli.PRNG;","base.random.bernoulli.seed":"\nbase.random.bernoulli.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.bernoulli.seed;","base.random.bernoulli.seedLength":"\nbase.random.bernoulli.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.bernoulli.seedLength;","base.random.bernoulli.state":"\nbase.random.bernoulli.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.bernoulli( 0.3 )\n    <number>\n    > r = base.random.bernoulli( 0.3 )\n    <number>\n    > r = base.random.bernoulli( 0.3 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.bernoulli.state\n    <Uint32Array>\n\n    > r = base.random.bernoulli( 0.3 )\n    <number>\n    > r = base.random.bernoulli( 0.3 )\n    <number>\n\n    // Set the state:\n    > base.random.bernoulli.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.bernoulli( 0.3 )\n    <number>\n    > r = base.random.bernoulli( 0.3 )\n    <number>","base.random.bernoulli.stateLength":"\nbase.random.bernoulli.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.bernoulli.stateLength;","base.random.bernoulli.byteLength":"\nbase.random.bernoulli.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.bernoulli.byteLength;","base.random.bernoulli.toJSON":"\nbase.random.bernoulli.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.bernoulli.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.bernoulli, random.iterators.bernoulli, random.streams.bernoulli, base.random.binomial","base.random.beta":"\nbase.random.beta( α, β )\n    Returns a pseudorandom number drawn from a beta distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.beta( 2.0, 5.0 );\n\n\nbase.random.beta.factory( [α, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a beta distribution.\n\n    If provided `α` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `α` and `β`, the returned PRNG requires that both `α` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        First shape parameter.\n\n    β: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.beta.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `α` and `β`:\n    > rand = base.random.beta.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.beta.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.beta.NAME\n    'beta'\n\n\nbase.random.beta.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.beta.PRNG;\n\n\nbase.random.beta.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.beta.seed;\n\n\nbase.random.beta.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.beta.seedLength;\n\n\nbase.random.beta.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.beta( 2.0, 5.0 )\n    <number>\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.beta.state\n    <Uint32Array>\n\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.beta.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>\n\n\nbase.random.beta.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.beta.stateLength;\n\n\nbase.random.beta.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.beta.byteLength;\n\n\nbase.random.beta.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.beta.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.beta, random.iterators.beta, random.streams.beta\n","base.random.beta.factory":"\nbase.random.beta.factory( [α, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a beta distribution.\n\n    If provided `α` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `α` and `β`, the returned PRNG requires that both `α` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        First shape parameter.\n\n    β: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.beta.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `α` and `β`:\n    > rand = base.random.beta.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.beta.NAME":"\nbase.random.beta.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.beta.NAME\n    'beta'","base.random.beta.PRNG":"\nbase.random.beta.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.beta.PRNG;","base.random.beta.seed":"\nbase.random.beta.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.beta.seed;","base.random.beta.seedLength":"\nbase.random.beta.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.beta.seedLength;","base.random.beta.state":"\nbase.random.beta.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.beta( 2.0, 5.0 )\n    <number>\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.beta.state\n    <Uint32Array>\n\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.beta.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>","base.random.beta.stateLength":"\nbase.random.beta.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.beta.stateLength;","base.random.beta.byteLength":"\nbase.random.beta.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.beta.byteLength;","base.random.beta.toJSON":"\nbase.random.beta.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.beta.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.beta, random.iterators.beta, random.streams.beta","base.random.betaprime":"\nbase.random.betaprime( α, β )\n    Returns a pseudorandom number drawn from a beta prime distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.betaprime( 2.0, 5.0 );\n\n\nbase.random.betaprime.factory( [α, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a beta prime distribution.\n\n    If provided `α` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `α` and `β`, the returned PRNG requires that both `α` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        First shape parameter.\n\n    β: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.betaprime.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `α` and `β`:\n    > rand = base.random.betaprime.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.betaprime.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.betaprime.NAME\n    'betaprime'\n\n\nbase.random.betaprime.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.betaprime.PRNG;\n\n\nbase.random.betaprime.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.betaprime.seed;\n\n\nbase.random.betaprime.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.betaprime.seedLength;\n\n\nbase.random.betaprime.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.betaprime.state\n    <Uint32Array>\n\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.betaprime.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n\n\nbase.random.betaprime.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.betaprime.stateLength;\n\n\nbase.random.betaprime.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.betaprime.byteLength;\n\n\nbase.random.betaprime.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.betaprime.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.betaprime, random.iterators.betaprime, random.streams.betaprime\n","base.random.betaprime.factory":"\nbase.random.betaprime.factory( [α, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a beta prime distribution.\n\n    If provided `α` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `α` and `β`, the returned PRNG requires that both `α` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        First shape parameter.\n\n    β: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.betaprime.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `α` and `β`:\n    > rand = base.random.betaprime.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.betaprime.NAME":"\nbase.random.betaprime.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.betaprime.NAME\n    'betaprime'","base.random.betaprime.PRNG":"\nbase.random.betaprime.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.betaprime.PRNG;","base.random.betaprime.seed":"\nbase.random.betaprime.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.betaprime.seed;","base.random.betaprime.seedLength":"\nbase.random.betaprime.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.betaprime.seedLength;","base.random.betaprime.state":"\nbase.random.betaprime.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.betaprime.state\n    <Uint32Array>\n\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.betaprime.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>","base.random.betaprime.stateLength":"\nbase.random.betaprime.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.betaprime.stateLength;","base.random.betaprime.byteLength":"\nbase.random.betaprime.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.betaprime.byteLength;","base.random.betaprime.toJSON":"\nbase.random.betaprime.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.betaprime.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.betaprime, random.iterators.betaprime, random.streams.betaprime","base.random.binomial":"\nbase.random.binomial( n, p )\n    Returns a pseudorandom number drawn from a binomial distribution.\n\n    If `n` is not a positive integer or `p` is not a probability, the function\n    returns `NaN`.\n\n    If `n` or `p` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.binomial( 20, 0.8 );\n\n\nbase.random.binomial.factory( [n, p, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a binomial distribution.\n\n    If provided `n` and `p`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `n` and `p`, the returned PRNG requires that both `n` and\n    `p` be provided at each invocation.\n\n    Parameters\n    ----------\n    n: integer (optional)\n        Number of trials.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.binomial.factory();\n    > var r = rand( 20, 0.3 );\n    > r = rand( 10, 0.77 );\n\n    // Provide `n` and `p`:\n    > rand = base.random.binomial.factory( 10, 0.8 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.binomial.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.binomial.NAME\n    'binomial'\n\n\nbase.random.binomial.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.binomial.PRNG;\n\n\nbase.random.binomial.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.binomial.seed;\n\n\nbase.random.binomial.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.binomial.seedLength;\n\n\nbase.random.binomial.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.binomial( 20, 0.8 )\n    <number>\n    > r = base.random.binomial( 20, 0.8 )\n    <number>\n    > r = base.random.binomial( 20, 0.8 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.binomial.state\n    <Uint32Array>\n\n    > r = base.random.binomial( 20, 0.8 )\n    <number>\n    > r = base.random.binomial( 20, 0.8 )\n    <number>\n\n    // Set the state:\n    > base.random.binomial.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.binomial( 20, 0.8 )\n    <number>\n    > r = base.random.binomial( 20, 0.8 )\n    <number>\n\n\nbase.random.binomial.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.binomial.stateLength;\n\n\nbase.random.binomial.byteLength\n    Size of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.binomial.byteLength;\n\n\nbase.random.binomial.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.binomial.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.binomial, random.iterators.binomial, random.streams.binomial\n","base.random.binomial.factory":"\nbase.random.binomial.factory( [n, p, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a binomial distribution.\n\n    If provided `n` and `p`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `n` and `p`, the returned PRNG requires that both `n` and\n    `p` be provided at each invocation.\n\n    Parameters\n    ----------\n    n: integer (optional)\n        Number of trials.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.binomial.factory();\n    > var r = rand( 20, 0.3 );\n    > r = rand( 10, 0.77 );\n\n    // Provide `n` and `p`:\n    > rand = base.random.binomial.factory( 10, 0.8 );\n    > r = rand();\n    > r = rand();","base.random.binomial.NAME":"\nbase.random.binomial.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.binomial.NAME\n    'binomial'","base.random.binomial.PRNG":"\nbase.random.binomial.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.binomial.PRNG;","base.random.binomial.seed":"\nbase.random.binomial.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.binomial.seed;","base.random.binomial.seedLength":"\nbase.random.binomial.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.binomial.seedLength;","base.random.binomial.state":"\nbase.random.binomial.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.binomial( 20, 0.8 )\n    <number>\n    > r = base.random.binomial( 20, 0.8 )\n    <number>\n    > r = base.random.binomial( 20, 0.8 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.binomial.state\n    <Uint32Array>\n\n    > r = base.random.binomial( 20, 0.8 )\n    <number>\n    > r = base.random.binomial( 20, 0.8 )\n    <number>\n\n    // Set the state:\n    > base.random.binomial.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.binomial( 20, 0.8 )\n    <number>\n    > r = base.random.binomial( 20, 0.8 )\n    <number>","base.random.binomial.stateLength":"\nbase.random.binomial.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.binomial.stateLength;","base.random.binomial.byteLength":"\nbase.random.binomial.byteLength\n    Size of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.binomial.byteLength;","base.random.binomial.toJSON":"\nbase.random.binomial.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.binomial.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.binomial, random.iterators.binomial, random.streams.binomial","base.random.boxMuller":"\nbase.random.boxMuller()\n    Returns a pseudorandom number drawn from a standard normal distribution.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.boxMuller();\n\n\nbase.random.boxMuller.factory( [options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a standard normal distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.boxMuller.factory();\n    > r = rand();\n    > r = rand();\n\n\nbase.random.boxMuller.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.boxMuller.NAME\n    'box-muller'\n\n\nbase.random.boxMuller.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.boxMuller.PRNG;\n\n\nbase.random.boxMuller.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.boxMuller.seed;\n\n\nbase.random.boxMuller.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.boxMuller.seedLength;\n\n\nbase.random.boxMuller.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.boxMuller()\n    <number>\n    > r = base.random.boxMuller()\n    <number>\n    > r = base.random.boxMuller()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.boxMuller.state\n    <Uint32Array>\n\n    > r = base.random.boxMuller()\n    <number>\n    > r = base.random.boxMuller()\n    <number>\n\n    // Set the state:\n    > base.random.boxMuller.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.boxMuller()\n    <number>\n    > r = base.random.boxMuller()\n    <number>\n\n\nbase.random.boxMuller.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.boxMuller.stateLength;\n\n\nbase.random.boxMuller.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.boxMuller.byteLength;\n\n\nbase.random.boxMuller.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.boxMuller.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.iterators.boxMuller, random.streams.boxMuller\n","base.random.boxMuller.factory":"\nbase.random.boxMuller.factory( [options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a standard normal distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.boxMuller.factory();\n    > r = rand();\n    > r = rand();","base.random.boxMuller.NAME":"\nbase.random.boxMuller.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.boxMuller.NAME\n    'box-muller'","base.random.boxMuller.PRNG":"\nbase.random.boxMuller.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.boxMuller.PRNG;","base.random.boxMuller.seed":"\nbase.random.boxMuller.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.boxMuller.seed;","base.random.boxMuller.seedLength":"\nbase.random.boxMuller.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.boxMuller.seedLength;","base.random.boxMuller.state":"\nbase.random.boxMuller.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.boxMuller()\n    <number>\n    > r = base.random.boxMuller()\n    <number>\n    > r = base.random.boxMuller()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.boxMuller.state\n    <Uint32Array>\n\n    > r = base.random.boxMuller()\n    <number>\n    > r = base.random.boxMuller()\n    <number>\n\n    // Set the state:\n    > base.random.boxMuller.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.boxMuller()\n    <number>\n    > r = base.random.boxMuller()\n    <number>","base.random.boxMuller.stateLength":"\nbase.random.boxMuller.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.boxMuller.stateLength;","base.random.boxMuller.byteLength":"\nbase.random.boxMuller.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.boxMuller.byteLength;","base.random.boxMuller.toJSON":"\nbase.random.boxMuller.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.boxMuller.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.iterators.boxMuller, random.streams.boxMuller","base.random.cauchy":"\nbase.random.cauchy( x0, Ɣ )\n    Returns a pseudorandom number drawn from a Cauchy distribution.\n\n    If `x0` or `Ɣ` is `NaN` or `Ɣ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.cauchy( 2.0, 5.0 );\n\n\nbase.random.cauchy.factory( [x0, Ɣ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Cauchy distribution.\n\n    If provided `x0` and `Ɣ`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `x0` and `Ɣ`, the returned PRNG requires that both `x0` and\n    `Ɣ` be provided at each invocation.\n\n    Parameters\n    ----------\n    x0: number (optional)\n        Location parameter.\n\n    Ɣ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.cauchy.factory();\n    > var r = rand( 0.0, 1.5 );\n    > r = rand( -2.0, 2.0 );\n\n    // Provide `x0` and `Ɣ`:\n    > rand = base.random.cauchy.factory( 0.0, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.cauchy.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.cauchy.NAME\n    'cauchy'\n\n\nbase.random.cauchy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.cauchy.PRNG;\n\n\nbase.random.cauchy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.cauchy.seed;\n\n\nbase.random.cauchy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.cauchy.seedLength;\n\n\nbase.random.cauchy.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.cauchy.state\n    <Uint32Array>\n\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.cauchy.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n\n\nbase.random.cauchy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.cauchy.stateLength;\n\n\nbase.random.cauchy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.cauchy.byteLength;\n\n\nbase.random.cauchy.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.cauchy.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.cauchy, random.iterators.cauchy, random.streams.cauchy\n","base.random.cauchy.factory":"\nbase.random.cauchy.factory( [x0, Ɣ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Cauchy distribution.\n\n    If provided `x0` and `Ɣ`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `x0` and `Ɣ`, the returned PRNG requires that both `x0` and\n    `Ɣ` be provided at each invocation.\n\n    Parameters\n    ----------\n    x0: number (optional)\n        Location parameter.\n\n    Ɣ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.cauchy.factory();\n    > var r = rand( 0.0, 1.5 );\n    > r = rand( -2.0, 2.0 );\n\n    // Provide `x0` and `Ɣ`:\n    > rand = base.random.cauchy.factory( 0.0, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.cauchy.NAME":"\nbase.random.cauchy.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.cauchy.NAME\n    'cauchy'","base.random.cauchy.PRNG":"\nbase.random.cauchy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.cauchy.PRNG;","base.random.cauchy.seed":"\nbase.random.cauchy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.cauchy.seed;","base.random.cauchy.seedLength":"\nbase.random.cauchy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.cauchy.seedLength;","base.random.cauchy.state":"\nbase.random.cauchy.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.cauchy.state\n    <Uint32Array>\n\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.cauchy.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>","base.random.cauchy.stateLength":"\nbase.random.cauchy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.cauchy.stateLength;","base.random.cauchy.byteLength":"\nbase.random.cauchy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.cauchy.byteLength;","base.random.cauchy.toJSON":"\nbase.random.cauchy.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.cauchy.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.cauchy, random.iterators.cauchy, random.streams.cauchy","base.random.chi":"\nbase.random.chi( k )\n    Returns a pseudorandom number drawn from a chi distribution.\n\n    If `k <= 0` or `k` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.chi( 2 );\n\n\nbase.random.chi.factory( [k, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a chi distribution.\n\n    If provided `k`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `k`, the returned PRNG requires that `k` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.chi.factory();\n    > var r = rand( 5 );\n    > r = rand( 3.14 );\n\n    // Provide `k`:\n    > rand = base.random.chi.factory( 3 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.chi.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.chi.NAME\n    'chi'\n\n\nbase.random.chi.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.chi.PRNG;\n\n\nbase.random.chi.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.chi.seed;\n\n\nbase.random.chi.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.chi.seedLength;\n\n\nbase.random.chi.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.chi( 2 )\n    <number>\n    > r = base.random.chi( 2 )\n    <number>\n    > r = base.random.chi( 2 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.chi.state\n    <Uint32Array>\n\n    > r = base.random.chi( 2 )\n    <number>\n    > r = base.random.chi( 2 )\n    <number>\n\n    // Set the state:\n    > base.random.chi.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.chi( 2 )\n    <number>\n    > r = base.random.chi( 2 )\n    <number>\n\n\nbase.random.chi.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.chi.stateLength;\n\n\nbase.random.chi.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.chi.byteLength;\n\n\nbase.random.chi.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.chi.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.chi, random.iterators.chi, random.streams.chi\n","base.random.chi.factory":"\nbase.random.chi.factory( [k, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a chi distribution.\n\n    If provided `k`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `k`, the returned PRNG requires that `k` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.chi.factory();\n    > var r = rand( 5 );\n    > r = rand( 3.14 );\n\n    // Provide `k`:\n    > rand = base.random.chi.factory( 3 );\n    > r = rand();\n    > r = rand();","base.random.chi.NAME":"\nbase.random.chi.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.chi.NAME\n    'chi'","base.random.chi.PRNG":"\nbase.random.chi.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.chi.PRNG;","base.random.chi.seed":"\nbase.random.chi.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.chi.seed;","base.random.chi.seedLength":"\nbase.random.chi.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.chi.seedLength;","base.random.chi.state":"\nbase.random.chi.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.chi( 2 )\n    <number>\n    > r = base.random.chi( 2 )\n    <number>\n    > r = base.random.chi( 2 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.chi.state\n    <Uint32Array>\n\n    > r = base.random.chi( 2 )\n    <number>\n    > r = base.random.chi( 2 )\n    <number>\n\n    // Set the state:\n    > base.random.chi.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.chi( 2 )\n    <number>\n    > r = base.random.chi( 2 )\n    <number>","base.random.chi.stateLength":"\nbase.random.chi.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.chi.stateLength;","base.random.chi.byteLength":"\nbase.random.chi.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.chi.byteLength;","base.random.chi.toJSON":"\nbase.random.chi.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.chi.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.chi, random.iterators.chi, random.streams.chi","base.random.chisquare":"\nbase.random.chisquare( k )\n    Returns a pseudorandom number drawn from a chi-square distribution.\n\n    If `k <= 0` or `k` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.chisquare( 2 );\n\n\nbase.random.chisquare.factory( [k, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a chi-square distribution.\n\n    If provided `k`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `k`, the returned PRNG requires that `k` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.chisquare.factory();\n    > var r = rand( 5 );\n    > r = rand( 3.14 );\n\n    // Provide `k`:\n    > rand = base.random.chisquare.factory( 3 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.chisquare.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.chisquare.NAME\n    'chisquare'\n\n\nbase.random.chisquare.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.chisquare.PRNG;\n\n\nbase.random.chisquare.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.chisquare.seed;\n\n\nbase.random.chisquare.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.chisquare.seedLength;\n\n\nbase.random.chisquare.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.chisquare( 2 )\n    <number>\n    > r = base.random.chisquare( 2 )\n    <number>\n    > r = base.random.chisquare( 2 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.chisquare.state\n    <Uint32Array>\n\n    > r = base.random.chisquare( 2 )\n    <number>\n    > r = base.random.chisquare( 2 )\n    <number>\n\n    // Set the state:\n    > base.random.chisquare.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.chisquare( 2 )\n    <number>\n    > r = base.random.chisquare( 2 )\n    <number>\n\n\nbase.random.chisquare.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.chisquare.stateLength;\n\n\nbase.random.chisquare.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.chisquare.byteLength;\n\n\nbase.random.chisquare.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.chisquare.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.chisquare, random.iterators.chisquare, random.streams.chisquare\n","base.random.chisquare.factory":"\nbase.random.chisquare.factory( [k, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a chi-square distribution.\n\n    If provided `k`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `k`, the returned PRNG requires that `k` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.chisquare.factory();\n    > var r = rand( 5 );\n    > r = rand( 3.14 );\n\n    // Provide `k`:\n    > rand = base.random.chisquare.factory( 3 );\n    > r = rand();\n    > r = rand();","base.random.chisquare.NAME":"\nbase.random.chisquare.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.chisquare.NAME\n    'chisquare'","base.random.chisquare.PRNG":"\nbase.random.chisquare.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.chisquare.PRNG;","base.random.chisquare.seed":"\nbase.random.chisquare.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.chisquare.seed;","base.random.chisquare.seedLength":"\nbase.random.chisquare.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.chisquare.seedLength;","base.random.chisquare.state":"\nbase.random.chisquare.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.chisquare( 2 )\n    <number>\n    > r = base.random.chisquare( 2 )\n    <number>\n    > r = base.random.chisquare( 2 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.chisquare.state\n    <Uint32Array>\n\n    > r = base.random.chisquare( 2 )\n    <number>\n    > r = base.random.chisquare( 2 )\n    <number>\n\n    // Set the state:\n    > base.random.chisquare.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.chisquare( 2 )\n    <number>\n    > r = base.random.chisquare( 2 )\n    <number>","base.random.chisquare.stateLength":"\nbase.random.chisquare.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.chisquare.stateLength;","base.random.chisquare.byteLength":"\nbase.random.chisquare.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.chisquare.byteLength;","base.random.chisquare.toJSON":"\nbase.random.chisquare.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.chisquare.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.chisquare, random.iterators.chisquare, random.streams.chisquare","base.random.cosine":"\nbase.random.cosine( μ, s )\n    Returns a pseudorandom number drawn from a raised cosine distribution.\n\n    If `μ` or `s` is `NaN` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.cosine( 2.0, 5.0 );\n\n\nbase.random.cosine.factory( [μ, s, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a raised cosine distribution.\n\n    If provided `μ` and `s`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n    `s` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.cosine.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `s`:\n    > rand = base.random.cosine.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.cosine.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.cosine.NAME\n    'cosine'\n\n\nbase.random.cosine.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.cosine.PRNG;\n\n\nbase.random.cosine.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.cosine.seed;\n\n\nbase.random.cosine.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.cosine.seedLength;\n\n\nbase.random.cosine.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.cosine( 2.0, 5.0 )\n    <number>\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.cosine.state\n    <Uint32Array>\n\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.cosine.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>\n\n\nbase.random.cosine.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.cosine.stateLength;\n\n\nbase.random.cosine.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.cosine.byteLength;\n\n\nbase.random.cosine.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.cosine.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.cosine, random.iterators.cosine, random.streams.cosine\n","base.random.cosine.factory":"\nbase.random.cosine.factory( [μ, s, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a raised cosine distribution.\n\n    If provided `μ` and `s`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n    `s` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.cosine.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `s`:\n    > rand = base.random.cosine.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.cosine.NAME":"\nbase.random.cosine.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.cosine.NAME\n    'cosine'","base.random.cosine.PRNG":"\nbase.random.cosine.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.cosine.PRNG;","base.random.cosine.seed":"\nbase.random.cosine.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.cosine.seed;","base.random.cosine.seedLength":"\nbase.random.cosine.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.cosine.seedLength;","base.random.cosine.state":"\nbase.random.cosine.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.cosine( 2.0, 5.0 )\n    <number>\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.cosine.state\n    <Uint32Array>\n\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.cosine.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>","base.random.cosine.stateLength":"\nbase.random.cosine.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.cosine.stateLength;","base.random.cosine.byteLength":"\nbase.random.cosine.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.cosine.byteLength;","base.random.cosine.toJSON":"\nbase.random.cosine.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.cosine.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.cosine, random.iterators.cosine, random.streams.cosine","base.random.discreteUniform":"\nbase.random.discreteUniform( a, b )\n    Returns a pseudorandom number drawn from a discrete uniform distribution.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.discreteUniform( 2, 50 );\n\n\nbase.random.discreteUniform.factory( [a, b, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a discrete uniform distribution.\n\n    If provided `a` and `b`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `a` and `b`, the returned PRNG requires that both `a` and\n    `b` be provided at each invocation.\n\n    Parameters\n    ----------\n    a: integer (optional)\n        Minimum support.\n\n    b: integer (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom integers. If provided, the `state` and `seed`\n        options are ignored. In order to seed the returned pseudorandom number\n        generator, one must seed the provided `prng` (assuming the provided\n        `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n        properties specifying the minimum and maximum possible pseudorandom\n        integers.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.discreteUniform.factory();\n    > var r = rand( 0, 10 );\n    > r = rand( -20, 20 );\n\n    // Provide `a` and `b`:\n    > rand = base.random.discreteUniform.factory( 0, 10 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.discreteUniform.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.discreteUniform.NAME\n    'discrete-uniform'\n\n\nbase.random.discreteUniform.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.discreteUniform.PRNG;\n\n\nbase.random.discreteUniform.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.discreteUniform.seed;\n\n\nbase.random.discreteUniform.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.discreteUniform.seedLength;\n\n\nbase.random.discreteUniform.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.discreteUniform( 2, 50 )\n    <number>\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.discreteUniform.state\n    <Uint32Array>\n\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>\n\n    // Set the state:\n    > base.random.discreteUniform.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>\n\n\nbase.random.discreteUniform.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.discreteUniform.stateLength;\n\n\nbase.random.discreteUniform.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.discreteUniform.byteLength;\n\n\nbase.random.discreteUniform.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.discreteUniform.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.discreteUniform, random.iterators.discreteUniform, random.streams.discreteUniform\n","base.random.discreteUniform.factory":"\nbase.random.discreteUniform.factory( [a, b, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a discrete uniform distribution.\n\n    If provided `a` and `b`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `a` and `b`, the returned PRNG requires that both `a` and\n    `b` be provided at each invocation.\n\n    Parameters\n    ----------\n    a: integer (optional)\n        Minimum support.\n\n    b: integer (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom integers. If provided, the `state` and `seed`\n        options are ignored. In order to seed the returned pseudorandom number\n        generator, one must seed the provided `prng` (assuming the provided\n        `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n        properties specifying the minimum and maximum possible pseudorandom\n        integers.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.discreteUniform.factory();\n    > var r = rand( 0, 10 );\n    > r = rand( -20, 20 );\n\n    // Provide `a` and `b`:\n    > rand = base.random.discreteUniform.factory( 0, 10 );\n    > r = rand();\n    > r = rand();","base.random.discreteUniform.NAME":"\nbase.random.discreteUniform.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.discreteUniform.NAME\n    'discrete-uniform'","base.random.discreteUniform.PRNG":"\nbase.random.discreteUniform.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.discreteUniform.PRNG;","base.random.discreteUniform.seed":"\nbase.random.discreteUniform.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.discreteUniform.seed;","base.random.discreteUniform.seedLength":"\nbase.random.discreteUniform.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.discreteUniform.seedLength;","base.random.discreteUniform.state":"\nbase.random.discreteUniform.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.discreteUniform( 2, 50 )\n    <number>\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.discreteUniform.state\n    <Uint32Array>\n\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>\n\n    // Set the state:\n    > base.random.discreteUniform.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>","base.random.discreteUniform.stateLength":"\nbase.random.discreteUniform.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.discreteUniform.stateLength;","base.random.discreteUniform.byteLength":"\nbase.random.discreteUniform.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.discreteUniform.byteLength;","base.random.discreteUniform.toJSON":"\nbase.random.discreteUniform.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.discreteUniform.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.discreteUniform, random.iterators.discreteUniform, random.streams.discreteUniform","base.random.erlang":"\nbase.random.erlang( k, λ )\n    Returns a pseudorandom number drawn from an Erlang distribution.\n\n    If `k` is not a positive integer or `λ <= 0`, the function returns `NaN`.\n\n    If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: integer\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.erlang( 2, 5.0 );\n\n\nbase.random.erlang.factory( [k, λ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an Erlang distribution.\n\n    If provided `k` and `λ`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `k` and `λ`, the returned PRNG requires that both `k` and\n    `λ` be provided at each invocation.\n\n    Parameters\n    ----------\n    k: integer (optional)\n        Shape parameter.\n\n    λ: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.erlang.factory();\n    > var r = rand( 2, 1.0 );\n    > r = rand( 4, 3.14 );\n\n    // Provide `k` and `λ`:\n    > rand = base.random.erlang.factory( 2, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.erlang.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.erlang.NAME\n    'erlang'\n\n\nbase.random.erlang.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.erlang.PRNG;\n\n\nbase.random.erlang.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.erlang.seed;\n\n\nbase.random.erlang.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.erlang.seedLength;\n\n\nbase.random.erlang.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.erlang( 2, 5.0 )\n    <number>\n    > r = base.random.erlang( 2, 5.0 )\n    <number>\n    > r = base.random.erlang( 2, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.erlang.state\n    <Uint32Array>\n\n    > r = base.random.erlang( 2, 5.0 )\n    <number>\n    > r = base.random.erlang( 2, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.erlang.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.erlang( 2, 5.0 )\n    <number>\n    > r = base.random.erlang( 2, 5.0 )\n    <number>\n\n\nbase.random.erlang.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.erlang.stateLength;\n\n\nbase.random.erlang.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.erlang.byteLength;\n\n\nbase.random.erlang.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.erlang.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.erlang, random.iterators.erlang, random.streams.erlang\n","base.random.erlang.factory":"\nbase.random.erlang.factory( [k, λ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an Erlang distribution.\n\n    If provided `k` and `λ`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `k` and `λ`, the returned PRNG requires that both `k` and\n    `λ` be provided at each invocation.\n\n    Parameters\n    ----------\n    k: integer (optional)\n        Shape parameter.\n\n    λ: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.erlang.factory();\n    > var r = rand( 2, 1.0 );\n    > r = rand( 4, 3.14 );\n\n    // Provide `k` and `λ`:\n    > rand = base.random.erlang.factory( 2, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.erlang.NAME":"\nbase.random.erlang.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.erlang.NAME\n    'erlang'","base.random.erlang.PRNG":"\nbase.random.erlang.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.erlang.PRNG;","base.random.erlang.seed":"\nbase.random.erlang.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.erlang.seed;","base.random.erlang.seedLength":"\nbase.random.erlang.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.erlang.seedLength;","base.random.erlang.state":"\nbase.random.erlang.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.erlang( 2, 5.0 )\n    <number>\n    > r = base.random.erlang( 2, 5.0 )\n    <number>\n    > r = base.random.erlang( 2, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.erlang.state\n    <Uint32Array>\n\n    > r = base.random.erlang( 2, 5.0 )\n    <number>\n    > r = base.random.erlang( 2, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.erlang.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.erlang( 2, 5.0 )\n    <number>\n    > r = base.random.erlang( 2, 5.0 )\n    <number>","base.random.erlang.stateLength":"\nbase.random.erlang.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.erlang.stateLength;","base.random.erlang.byteLength":"\nbase.random.erlang.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.erlang.byteLength;","base.random.erlang.toJSON":"\nbase.random.erlang.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.erlang.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.erlang, random.iterators.erlang, random.streams.erlang","base.random.exponential":"\nbase.random.exponential( λ )\n    Returns a pseudorandom number drawn from an exponential distribution.\n\n    If `λ <= 0` or `λ` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.exponential( 7.9 );\n\n\nbase.random.exponential.factory( [λ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an exponential distribution.\n\n    If provided `λ`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    λ: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.exponential.factory();\n    > var r = rand( 5.0 );\n    > r = rand( 3.14 );\n\n    // Provide `λ`:\n    > rand = base.random.exponential.factory( 10.0 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.exponential.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.exponential.NAME\n    'exponential'\n\n\nbase.random.exponential.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.exponential.PRNG;\n\n\nbase.random.exponential.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.exponential.seed;\n\n\nbase.random.exponential.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.exponential.seedLength;\n\n\nbase.random.exponential.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.exponential( 7.9 )\n    <number>\n    > r = base.random.exponential( 7.9 )\n    <number>\n    > r = base.random.exponential( 7.9 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.exponential.state\n    <Uint32Array>\n\n    > r = base.random.exponential( 7.9 )\n    <number>\n    > r = base.random.exponential( 7.9 )\n    <number>\n\n    // Set the state:\n    > base.random.exponential.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.exponential( 7.9 )\n    <number>\n    > r = base.random.exponential( 7.9 )\n    <number>\n\n\nbase.random.exponential.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.exponential.stateLength;\n\n\nbase.random.exponential.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.exponential.byteLength;\n\n\nbase.random.exponential.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.exponential.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.exponential, random.iterators.exponential, random.streams.exponential\n","base.random.exponential.factory":"\nbase.random.exponential.factory( [λ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an exponential distribution.\n\n    If provided `λ`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    λ: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.exponential.factory();\n    > var r = rand( 5.0 );\n    > r = rand( 3.14 );\n\n    // Provide `λ`:\n    > rand = base.random.exponential.factory( 10.0 );\n    > r = rand();\n    > r = rand();","base.random.exponential.NAME":"\nbase.random.exponential.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.exponential.NAME\n    'exponential'","base.random.exponential.PRNG":"\nbase.random.exponential.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.exponential.PRNG;","base.random.exponential.seed":"\nbase.random.exponential.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.exponential.seed;","base.random.exponential.seedLength":"\nbase.random.exponential.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.exponential.seedLength;","base.random.exponential.state":"\nbase.random.exponential.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.exponential( 7.9 )\n    <number>\n    > r = base.random.exponential( 7.9 )\n    <number>\n    > r = base.random.exponential( 7.9 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.exponential.state\n    <Uint32Array>\n\n    > r = base.random.exponential( 7.9 )\n    <number>\n    > r = base.random.exponential( 7.9 )\n    <number>\n\n    // Set the state:\n    > base.random.exponential.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.exponential( 7.9 )\n    <number>\n    > r = base.random.exponential( 7.9 )\n    <number>","base.random.exponential.stateLength":"\nbase.random.exponential.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.exponential.stateLength;","base.random.exponential.byteLength":"\nbase.random.exponential.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.exponential.byteLength;","base.random.exponential.toJSON":"\nbase.random.exponential.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.exponential.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.exponential, random.iterators.exponential, random.streams.exponential","base.random.f":"\nbase.random.f( d1, d2 )\n    Returns a pseudorandom number drawn from an F distribution.\n\n    If `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n    If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    d1: number\n        Degrees of freedom.\n\n    d2: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.f( 2.0, 5.0 );\n\n\nbase.random.f.factory( [d1, d2, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an F distribution.\n\n    If provided `d1` and `d2`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `d1` and `d2`, the returned PRNG requires that both `d1` and\n    `d2` be provided at each invocation.\n\n    Parameters\n    ----------\n    d1: number (optional)\n        Degrees of freedom.\n\n    d2: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.f.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 3.0, 3.14 );\n\n    // Provide `d1` and `d2`:\n    > rand = base.random.f.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.f.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.f.NAME\n    'f'\n\n\nbase.random.f.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.f.PRNG;\n\n\nbase.random.f.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.f.seed;\n\n\nbase.random.f.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.f.seedLength;\n\n\nbase.random.f.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.f( 1.5, 1.5 )\n    <number>\n    > r = base.random.f( 1.5, 1.5 )\n    <number>\n    > r = base.random.f( 1.5, 1.5 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.f.state\n    <Uint32Array>\n\n    > r = base.random.f( 1.5, 1.5 )\n    <number>\n    > r = base.random.f( 1.5, 1.5 )\n    <number>\n\n    // Set the state:\n    > base.random.f.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.f( 1.5, 1.5 )\n    <number>\n    > r = base.random.f( 1.5, 1.5 )\n    <number>\n\n\nbase.random.f.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.f.stateLength;\n\n\nbase.random.f.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.f.byteLength;\n\n\nbase.random.f.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.f.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.f, random.iterators.f, random.streams.f\n","base.random.f.factory":"\nbase.random.f.factory( [d1, d2, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an F distribution.\n\n    If provided `d1` and `d2`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `d1` and `d2`, the returned PRNG requires that both `d1` and\n    `d2` be provided at each invocation.\n\n    Parameters\n    ----------\n    d1: number (optional)\n        Degrees of freedom.\n\n    d2: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.f.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 3.0, 3.14 );\n\n    // Provide `d1` and `d2`:\n    > rand = base.random.f.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.f.NAME":"\nbase.random.f.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.f.NAME\n    'f'","base.random.f.PRNG":"\nbase.random.f.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.f.PRNG;","base.random.f.seed":"\nbase.random.f.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.f.seed;","base.random.f.seedLength":"\nbase.random.f.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.f.seedLength;","base.random.f.state":"\nbase.random.f.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.f( 1.5, 1.5 )\n    <number>\n    > r = base.random.f( 1.5, 1.5 )\n    <number>\n    > r = base.random.f( 1.5, 1.5 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.f.state\n    <Uint32Array>\n\n    > r = base.random.f( 1.5, 1.5 )\n    <number>\n    > r = base.random.f( 1.5, 1.5 )\n    <number>\n\n    // Set the state:\n    > base.random.f.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.f( 1.5, 1.5 )\n    <number>\n    > r = base.random.f( 1.5, 1.5 )\n    <number>","base.random.f.stateLength":"\nbase.random.f.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.f.stateLength;","base.random.f.byteLength":"\nbase.random.f.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.f.byteLength;","base.random.f.toJSON":"\nbase.random.f.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.f.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.f, random.iterators.f, random.streams.f","base.random.frechet":"\nbase.random.frechet( α, s, m )\n    Returns a pseudorandom number drawn from a Fréchet distribution.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    If either `α`, `s`, or `m` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.frechet( 2.0, 5.0, 3.33 );\n\n\nbase.random.frechet.factory( [α, s, m, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a triangular distribution.\n\n    If provided `α`, `s`, and `m`, the returned PRNG returns random variates\n    drawn from the specified distribution.\n\n    If not provided `α`, `s`, and `m`, the returned PRNG requires that `α`, `s`,\n    and `m` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    m: number (optional)\n        Location parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.frechet.factory();\n    > var r = rand( 1.0, 1.0, 0.5 );\n    > r = rand( 2.0, 2.0, 1.0 );\n\n    // Provide `α`, `s`, and `m`:\n    > rand = base.random.frechet.factory( 1.0, 1.0, 0.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.frechet.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.frechet.NAME\n    'frechet'\n\n\nbase.random.frechet.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.frechet.PRNG;\n\n\nbase.random.frechet.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.frechet.seed;\n\n\nbase.random.frechet.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.frechet.seedLength;\n\n\nbase.random.frechet.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.frechet.state\n    <Uint32Array>\n\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n\n    // Set the state:\n    > base.random.frechet.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n\n\nbase.random.frechet.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.frechet.stateLength;\n\n\nbase.random.frechet.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.frechet.byteLength;\n\n\nbase.random.frechet.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.frechet.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.frechet, random.iterators.frechet, random.streams.frechet\n","base.random.frechet.factory":"\nbase.random.frechet.factory( [α, s, m, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a triangular distribution.\n\n    If provided `α`, `s`, and `m`, the returned PRNG returns random variates\n    drawn from the specified distribution.\n\n    If not provided `α`, `s`, and `m`, the returned PRNG requires that `α`, `s`,\n    and `m` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    m: number (optional)\n        Location parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.frechet.factory();\n    > var r = rand( 1.0, 1.0, 0.5 );\n    > r = rand( 2.0, 2.0, 1.0 );\n\n    // Provide `α`, `s`, and `m`:\n    > rand = base.random.frechet.factory( 1.0, 1.0, 0.5 );\n    > r = rand();\n    > r = rand();","base.random.frechet.NAME":"\nbase.random.frechet.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.frechet.NAME\n    'frechet'","base.random.frechet.PRNG":"\nbase.random.frechet.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.frechet.PRNG;","base.random.frechet.seed":"\nbase.random.frechet.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.frechet.seed;","base.random.frechet.seedLength":"\nbase.random.frechet.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.frechet.seedLength;","base.random.frechet.state":"\nbase.random.frechet.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.frechet.state\n    <Uint32Array>\n\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n\n    // Set the state:\n    > base.random.frechet.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>","base.random.frechet.stateLength":"\nbase.random.frechet.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.frechet.stateLength;","base.random.frechet.byteLength":"\nbase.random.frechet.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.frechet.byteLength;","base.random.frechet.toJSON":"\nbase.random.frechet.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.frechet.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.frechet, random.iterators.frechet, random.streams.frechet","base.random.gamma":"\nbase.random.gamma( α, β )\n    Returns a pseudorandom number drawn from a gamma distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.gamma( 2.0, 5.0 );\n\n\nbase.random.gamma.factory( [α, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a gamma distribution.\n\n    If provided `α` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `α` and `β`, the returned PRNG requires that both `α` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.gamma.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 3.14, 2.25 );\n\n    // Provide `α` and `β`:\n    > rand = base.random.gamma.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.gamma.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.gamma.NAME\n    'gamma'\n\n\nbase.random.gamma.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.gamma.PRNG;\n\n\nbase.random.gamma.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.gamma.seed;\n\n\nbase.random.gamma.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.gamma.seedLength;\n\n\nbase.random.gamma.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.gamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.gamma.state\n    <Uint32Array>\n\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.gamma.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>\n\n\nbase.random.gamma.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.gamma.stateLength;\n\n\nbase.random.gamma.byteLength\n    Size of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.gamma.byteLength;\n\n\nbase.random.gamma.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.gamma.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.gamma, random.iterators.gamma, random.streams.gamma\n","base.random.gamma.factory":"\nbase.random.gamma.factory( [α, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a gamma distribution.\n\n    If provided `α` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `α` and `β`, the returned PRNG requires that both `α` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.gamma.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 3.14, 2.25 );\n\n    // Provide `α` and `β`:\n    > rand = base.random.gamma.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.gamma.NAME":"\nbase.random.gamma.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.gamma.NAME\n    'gamma'","base.random.gamma.PRNG":"\nbase.random.gamma.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.gamma.PRNG;","base.random.gamma.seed":"\nbase.random.gamma.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.gamma.seed;","base.random.gamma.seedLength":"\nbase.random.gamma.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.gamma.seedLength;","base.random.gamma.state":"\nbase.random.gamma.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.gamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.gamma.state\n    <Uint32Array>\n\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.gamma.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>","base.random.gamma.stateLength":"\nbase.random.gamma.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.gamma.stateLength;","base.random.gamma.byteLength":"\nbase.random.gamma.byteLength\n    Size of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.gamma.byteLength;","base.random.gamma.toJSON":"\nbase.random.gamma.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.gamma.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.gamma, random.iterators.gamma, random.streams.gamma","base.random.geometric":"\nbase.random.geometric( p )\n    Returns a pseudorandom number drawn from a geometric distribution.\n\n    If `p < 0` or `p > 1` or `p` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.geometric( 0.8 );\n\n\nbase.random.geometric.factory( [p, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a geometric distribution.\n\n    If provided `p`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `p`, the returned PRNG requires that `p` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.geometric.factory();\n    > var r = rand( 0.3 );\n    > r = rand( 0.59 );\n\n    // Provide `p`:\n    > rand = base.random.geometric.factory( 0.3 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.geometric.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.geometric.NAME\n    'geometric'\n\n\nbase.random.geometric.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.geometric.PRNG;\n\n\nbase.random.geometric.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.geometric.seed;\n\n\nbase.random.geometric.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.geometric.seedLength;\n\n\nbase.random.geometric.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.geometric( 0.3 )\n    <number>\n    > r = base.random.geometric( 0.3 )\n    <number>\n    > r = base.random.geometric( 0.3 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.geometric.state\n    <Uint32Array>\n\n    > r = base.random.geometric( 0.3 )\n    <number>\n    > r = base.random.geometric( 0.3 )\n    <number>\n\n    // Set the state:\n    > base.random.geometric.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.geometric( 0.3 )\n    <number>\n    > r = base.random.geometric( 0.3 )\n    <number>\n\n\nbase.random.geometric.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.geometric.stateLength;\n\n\nbase.random.geometric.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.geometric.byteLength;\n\n\nbase.random.geometric.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.geometric.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.geometric, random.iterators.geometric, random.streams.geometric\n","base.random.geometric.factory":"\nbase.random.geometric.factory( [p, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a geometric distribution.\n\n    If provided `p`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `p`, the returned PRNG requires that `p` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.geometric.factory();\n    > var r = rand( 0.3 );\n    > r = rand( 0.59 );\n\n    // Provide `p`:\n    > rand = base.random.geometric.factory( 0.3 );\n    > r = rand();\n    > r = rand();","base.random.geometric.NAME":"\nbase.random.geometric.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.geometric.NAME\n    'geometric'","base.random.geometric.PRNG":"\nbase.random.geometric.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.geometric.PRNG;","base.random.geometric.seed":"\nbase.random.geometric.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.geometric.seed;","base.random.geometric.seedLength":"\nbase.random.geometric.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.geometric.seedLength;","base.random.geometric.state":"\nbase.random.geometric.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.geometric( 0.3 )\n    <number>\n    > r = base.random.geometric( 0.3 )\n    <number>\n    > r = base.random.geometric( 0.3 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.geometric.state\n    <Uint32Array>\n\n    > r = base.random.geometric( 0.3 )\n    <number>\n    > r = base.random.geometric( 0.3 )\n    <number>\n\n    // Set the state:\n    > base.random.geometric.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.geometric( 0.3 )\n    <number>\n    > r = base.random.geometric( 0.3 )\n    <number>","base.random.geometric.stateLength":"\nbase.random.geometric.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.geometric.stateLength;","base.random.geometric.byteLength":"\nbase.random.geometric.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.geometric.byteLength;","base.random.geometric.toJSON":"\nbase.random.geometric.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.geometric.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.geometric, random.iterators.geometric, random.streams.geometric","base.random.gumbel":"\nbase.random.gumbel( μ, β )\n    Returns a pseudorandom number drawn from a Gumbel distribution.\n\n    If `μ` or `β` is `NaN` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.gumbel( 2.0, 5.0 );\n\n\nbase.random.gumbel.factory( [μ, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Gumbel distribution.\n\n    If provided `μ` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `β`, the returned PRNG requires that both `μ` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.gumbel.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `β`:\n    > rand = base.random.gumbel.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.gumbel.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.gumbel.NAME\n    'gumbel'\n\n\nbase.random.gumbel.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.gumbel.PRNG;\n\n\nbase.random.gumbel.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.gumbel.seed;\n\n\nbase.random.gumbel.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.gumbel.seedLength;\n\n\nbase.random.gumbel.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.gumbel.state\n    <Uint32Array>\n\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.gumbel.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n\n\nbase.random.gumbel.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.gumbel.stateLength;\n\n\nbase.random.gumbel.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.gumbel.byteLength;\n\n\nbase.random.gumbel.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.gumbel.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.gumbel, random.iterators.gumbel, random.streams.gumbel\n","base.random.gumbel.factory":"\nbase.random.gumbel.factory( [μ, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Gumbel distribution.\n\n    If provided `μ` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `β`, the returned PRNG requires that both `μ` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.gumbel.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `β`:\n    > rand = base.random.gumbel.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.gumbel.NAME":"\nbase.random.gumbel.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.gumbel.NAME\n    'gumbel'","base.random.gumbel.PRNG":"\nbase.random.gumbel.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.gumbel.PRNG;","base.random.gumbel.seed":"\nbase.random.gumbel.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.gumbel.seed;","base.random.gumbel.seedLength":"\nbase.random.gumbel.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.gumbel.seedLength;","base.random.gumbel.state":"\nbase.random.gumbel.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.gumbel.state\n    <Uint32Array>\n\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.gumbel.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>","base.random.gumbel.stateLength":"\nbase.random.gumbel.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.gumbel.stateLength;","base.random.gumbel.byteLength":"\nbase.random.gumbel.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.gumbel.byteLength;","base.random.gumbel.toJSON":"\nbase.random.gumbel.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.gumbel.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.gumbel, random.iterators.gumbel, random.streams.gumbel","base.random.hypergeometric":"\nbase.random.hypergeometric( N, K, n )\n    Returns a pseudorandom number drawn from a hypergeometric distribution.\n\n    `N`, `K`, and `n` must all be nonnegative integers; otherwise, the function\n    returns `NaN`.\n\n    If `n > N` or `K > N`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.hypergeometric( 20, 10, 7 );\n\n\nbase.random.hypergeometric.factory( [N, K, n, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a hypergeometric distribution.\n\n    If provided `N`, `K`, and `n`, the returned PRNG returns random variates\n    drawn from the specified distribution.\n\n    If not provided `N`, `K`, and `n`, the returned PRNG requires that `N`, `K`,\n    and `n` be provided at each invocation.\n\n    Parameters\n    ----------\n    N: integer (optional)\n        Population size.\n\n    K: integer (optional)\n        Subpopulation size.\n\n    n: integer (optional)\n        Number of draws.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.hypergeometric.factory();\n    > var r = rand( 20, 10, 15 );\n    > r = rand( 20, 10, 7 );\n\n    // Provide `N`, `K`, and `n`:\n    > rand = base.random.hypergeometric.factory( 20, 10, 15 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.hypergeometric.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.hypergeometric.NAME\n    'hypergeometric'\n\n\nbase.random.hypergeometric.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.hypergeometric.PRNG;\n\n\nbase.random.hypergeometric.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.hypergeometric.seed;\n\n\nbase.random.hypergeometric.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.hypergeometric.seedLength;\n\n\nbase.random.hypergeometric.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.hypergeometric.state\n    <Uint32Array>\n\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n\n    // Set the state:\n    > base.random.hypergeometric.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n\n\nbase.random.hypergeometric.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.hypergeometric.stateLength;\n\n\nbase.random.hypergeometric.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.hypergeometric.byteLength;\n\n\nbase.random.hypergeometric.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.hypergeometric.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.hypergeometric, random.iterators.hypergeometric, random.streams.hypergeometric\n","base.random.hypergeometric.factory":"\nbase.random.hypergeometric.factory( [N, K, n, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a hypergeometric distribution.\n\n    If provided `N`, `K`, and `n`, the returned PRNG returns random variates\n    drawn from the specified distribution.\n\n    If not provided `N`, `K`, and `n`, the returned PRNG requires that `N`, `K`,\n    and `n` be provided at each invocation.\n\n    Parameters\n    ----------\n    N: integer (optional)\n        Population size.\n\n    K: integer (optional)\n        Subpopulation size.\n\n    n: integer (optional)\n        Number of draws.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.hypergeometric.factory();\n    > var r = rand( 20, 10, 15 );\n    > r = rand( 20, 10, 7 );\n\n    // Provide `N`, `K`, and `n`:\n    > rand = base.random.hypergeometric.factory( 20, 10, 15 );\n    > r = rand();\n    > r = rand();","base.random.hypergeometric.NAME":"\nbase.random.hypergeometric.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.hypergeometric.NAME\n    'hypergeometric'","base.random.hypergeometric.PRNG":"\nbase.random.hypergeometric.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.hypergeometric.PRNG;","base.random.hypergeometric.seed":"\nbase.random.hypergeometric.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.hypergeometric.seed;","base.random.hypergeometric.seedLength":"\nbase.random.hypergeometric.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.hypergeometric.seedLength;","base.random.hypergeometric.state":"\nbase.random.hypergeometric.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.hypergeometric.state\n    <Uint32Array>\n\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n\n    // Set the state:\n    > base.random.hypergeometric.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>","base.random.hypergeometric.stateLength":"\nbase.random.hypergeometric.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.hypergeometric.stateLength;","base.random.hypergeometric.byteLength":"\nbase.random.hypergeometric.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.hypergeometric.byteLength;","base.random.hypergeometric.toJSON":"\nbase.random.hypergeometric.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.hypergeometric.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.hypergeometric, random.iterators.hypergeometric, random.streams.hypergeometric","base.random.improvedZiggurat":"\nbase.random.improvedZiggurat()\n    Returns a pseudorandom number drawn from a standard normal distribution.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.improvedZiggurat();\n\n\nbase.random.improvedZiggurat.factory( [options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a standard normal distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.improvedZiggurat.factory();\n    > r = rand();\n    > r = rand();\n\n\nbase.random.improvedZiggurat.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.improvedZiggurat.NAME\n    'improved-ziggurat'\n\n\nbase.random.improvedZiggurat.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.improvedZiggurat.PRNG;\n\n\nbase.random.improvedZiggurat.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.improvedZiggurat.seed;\n\n\nbase.random.improvedZiggurat.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.improvedZiggurat.seedLength;\n\n\nbase.random.improvedZiggurat.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.improvedZiggurat()\n    <number>\n    > r = base.random.improvedZiggurat()\n    <number>\n    > r = base.random.improvedZiggurat()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.improvedZiggurat.state\n    <Uint32Array>\n\n    > r = base.random.improvedZiggurat()\n    <number>\n    > r = base.random.improvedZiggurat()\n    <number>\n\n    // Set the state:\n    > base.random.improvedZiggurat.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.improvedZiggurat()\n    <number>\n    > r = base.random.improvedZiggurat()\n    <number>\n\n\nbase.random.improvedZiggurat.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.improvedZiggurat.stateLength;\n\n\nbase.random.improvedZiggurat.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.improvedZiggurat.byteLength;\n\n\nbase.random.improvedZiggurat.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.improvedZiggurat.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.iterators.improvedZiggurat, random.streams.improvedZiggurat\n","base.random.improvedZiggurat.factory":"\nbase.random.improvedZiggurat.factory( [options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a standard normal distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.improvedZiggurat.factory();\n    > r = rand();\n    > r = rand();","base.random.improvedZiggurat.NAME":"\nbase.random.improvedZiggurat.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.improvedZiggurat.NAME\n    'improved-ziggurat'","base.random.improvedZiggurat.PRNG":"\nbase.random.improvedZiggurat.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.improvedZiggurat.PRNG;","base.random.improvedZiggurat.seed":"\nbase.random.improvedZiggurat.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.improvedZiggurat.seed;","base.random.improvedZiggurat.seedLength":"\nbase.random.improvedZiggurat.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.improvedZiggurat.seedLength;","base.random.improvedZiggurat.state":"\nbase.random.improvedZiggurat.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.improvedZiggurat()\n    <number>\n    > r = base.random.improvedZiggurat()\n    <number>\n    > r = base.random.improvedZiggurat()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.improvedZiggurat.state\n    <Uint32Array>\n\n    > r = base.random.improvedZiggurat()\n    <number>\n    > r = base.random.improvedZiggurat()\n    <number>\n\n    // Set the state:\n    > base.random.improvedZiggurat.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.improvedZiggurat()\n    <number>\n    > r = base.random.improvedZiggurat()\n    <number>","base.random.improvedZiggurat.stateLength":"\nbase.random.improvedZiggurat.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.improvedZiggurat.stateLength;","base.random.improvedZiggurat.byteLength":"\nbase.random.improvedZiggurat.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.improvedZiggurat.byteLength;","base.random.improvedZiggurat.toJSON":"\nbase.random.improvedZiggurat.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.improvedZiggurat.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.iterators.improvedZiggurat, random.streams.improvedZiggurat","base.random.invgamma":"\nbase.random.invgamma( α, β )\n    Returns a pseudorandom number drawn from an inverse gamma distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.invgamma( 2.0, 5.0 );\n\n\nbase.random.invgamma.factory( [α, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an inverse gamma distribution.\n\n    If provided `α` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `α` and `β`, the returned PRNG requires that both `α` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.invgamma.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 3.14, 2.25 );\n\n    // Provide `α` and `β`:\n    > rand = base.random.invgamma.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.invgamma.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.invgamma.NAME\n    'invgamma'\n\n\nbase.random.invgamma.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.invgamma.PRNG;\n\n\nbase.random.invgamma.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.invgamma.seed;\n\n\nbase.random.invgamma.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.invgamma.seedLength;\n\n\nbase.random.invgamma.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.invgamma.state\n    <Uint32Array>\n\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.invgamma.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n\n\nbase.random.invgamma.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.invgamma.stateLength;\n\n\nbase.random.invgamma.byteLength\n    Size of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.invgamma.byteLength;\n\n\nbase.random.invgamma.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.invgamma.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.invgamma, random.iterators.invgamma, random.streams.invgamma\n","base.random.invgamma.factory":"\nbase.random.invgamma.factory( [α, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an inverse gamma distribution.\n\n    If provided `α` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `α` and `β`, the returned PRNG requires that both `α` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.invgamma.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 3.14, 2.25 );\n\n    // Provide `α` and `β`:\n    > rand = base.random.invgamma.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.invgamma.NAME":"\nbase.random.invgamma.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.invgamma.NAME\n    'invgamma'","base.random.invgamma.PRNG":"\nbase.random.invgamma.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.invgamma.PRNG;","base.random.invgamma.seed":"\nbase.random.invgamma.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.invgamma.seed;","base.random.invgamma.seedLength":"\nbase.random.invgamma.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.invgamma.seedLength;","base.random.invgamma.state":"\nbase.random.invgamma.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.invgamma.state\n    <Uint32Array>\n\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.invgamma.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>","base.random.invgamma.stateLength":"\nbase.random.invgamma.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.invgamma.stateLength;","base.random.invgamma.byteLength":"\nbase.random.invgamma.byteLength\n    Size of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.invgamma.byteLength;","base.random.invgamma.toJSON":"\nbase.random.invgamma.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.invgamma.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.invgamma, random.iterators.invgamma, random.streams.invgamma","base.random.kumaraswamy":"\nbase.random.kumaraswamy( a, b )\n    Returns a pseudorandom number drawn from Kumaraswamy's double bounded\n    distribution.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    If `a` or `b` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.kumaraswamy( 2.0, 5.0 );\n\n\nbase.random.kumaraswamy.factory( [a, b, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from Kumaraswamy's double bounded distribution.\n\n    If provided `a` and `b`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `a` and `b`, the returned PRNG requires that both `a` and\n    `b` be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        First shape parameter.\n\n    b: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.kumaraswamy.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `a` and `b`:\n    > rand = base.random.kumaraswamy.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.kumaraswamy.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.kumaraswamy.NAME\n    'kumaraswamy'\n\n\nbase.random.kumaraswamy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.kumaraswamy.PRNG;\n\n\nbase.random.kumaraswamy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.kumaraswamy.seed;\n\n\nbase.random.kumaraswamy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.kumaraswamy.seedLength;\n\n\nbase.random.kumaraswamy.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.kumaraswamy.state\n    <Uint32Array>\n\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n\n    // Set the state:\n    > base.random.kumaraswamy.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n\n\nbase.random.kumaraswamy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.kumaraswamy.stateLength;\n\n\nbase.random.kumaraswamy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.kumaraswamy.byteLength;\n\n\nbase.random.kumaraswamy.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.kumaraswamy.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.kumaraswamy, random.iterators.kumaraswamy, random.streams.kumaraswamy\n","base.random.kumaraswamy.factory":"\nbase.random.kumaraswamy.factory( [a, b, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from Kumaraswamy's double bounded distribution.\n\n    If provided `a` and `b`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `a` and `b`, the returned PRNG requires that both `a` and\n    `b` be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        First shape parameter.\n\n    b: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.kumaraswamy.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `a` and `b`:\n    > rand = base.random.kumaraswamy.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.kumaraswamy.NAME":"\nbase.random.kumaraswamy.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.kumaraswamy.NAME\n    'kumaraswamy'","base.random.kumaraswamy.PRNG":"\nbase.random.kumaraswamy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.kumaraswamy.PRNG;","base.random.kumaraswamy.seed":"\nbase.random.kumaraswamy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.kumaraswamy.seed;","base.random.kumaraswamy.seedLength":"\nbase.random.kumaraswamy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.kumaraswamy.seedLength;","base.random.kumaraswamy.state":"\nbase.random.kumaraswamy.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.kumaraswamy.state\n    <Uint32Array>\n\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n\n    // Set the state:\n    > base.random.kumaraswamy.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>","base.random.kumaraswamy.stateLength":"\nbase.random.kumaraswamy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.kumaraswamy.stateLength;","base.random.kumaraswamy.byteLength":"\nbase.random.kumaraswamy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.kumaraswamy.byteLength;","base.random.kumaraswamy.toJSON":"\nbase.random.kumaraswamy.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.kumaraswamy.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.kumaraswamy, random.iterators.kumaraswamy, random.streams.kumaraswamy","base.random.laplace":"\nbase.random.laplace( μ, b )\n    Returns a pseudorandom number drawn from a Laplace distribution.\n\n    If `μ` or `b` is `NaN` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.laplace( 2.0, 5.0 );\n\n\nbase.random.laplace.factory( [μ, b, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Laplace distribution.\n\n    If provided `μ` and `b`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `b`, the returned PRNG requires that both `μ` and\n    `b` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    b: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.laplace.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `b`:\n    > rand = base.random.laplace.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.laplace.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.laplace.NAME\n    'laplace'\n\n\nbase.random.laplace.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.laplace.PRNG;\n\n\nbase.random.laplace.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.laplace.seed;\n\n\nbase.random.laplace.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.laplace.seedLength;\n\n\nbase.random.laplace.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.laplace( 2.0, 5.0 )\n    <number>\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.laplace.state\n    <Uint32Array>\n\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.laplace.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>\n\n\nbase.random.laplace.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.laplace.stateLength;\n\n\nbase.random.laplace.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.laplace.byteLength;\n\n\nbase.random.laplace.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.laplace.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.laplace, random.iterators.laplace, random.streams.laplace\n","base.random.laplace.factory":"\nbase.random.laplace.factory( [μ, b, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Laplace distribution.\n\n    If provided `μ` and `b`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `b`, the returned PRNG requires that both `μ` and\n    `b` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    b: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.laplace.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `b`:\n    > rand = base.random.laplace.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.laplace.NAME":"\nbase.random.laplace.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.laplace.NAME\n    'laplace'","base.random.laplace.PRNG":"\nbase.random.laplace.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.laplace.PRNG;","base.random.laplace.seed":"\nbase.random.laplace.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.laplace.seed;","base.random.laplace.seedLength":"\nbase.random.laplace.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.laplace.seedLength;","base.random.laplace.state":"\nbase.random.laplace.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.laplace( 2.0, 5.0 )\n    <number>\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.laplace.state\n    <Uint32Array>\n\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.laplace.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>","base.random.laplace.stateLength":"\nbase.random.laplace.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.laplace.stateLength;","base.random.laplace.byteLength":"\nbase.random.laplace.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.laplace.byteLength;","base.random.laplace.toJSON":"\nbase.random.laplace.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.laplace.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.laplace, random.iterators.laplace, random.streams.laplace","base.random.levy":"\nbase.random.levy( μ, c )\n    Returns a pseudorandom number drawn from a Lévy distribution.\n\n    If `μ` or `c` is `NaN` or `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.levy( 2.0, 5.0 );\n\n\nbase.random.levy.factory( [μ, c, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Lévy distribution.\n\n    If provided `μ` and `c`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `c`, the returned PRNG requires that both `μ` and\n    `c` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    c: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.levy.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `b`:\n    > rand = base.random.levy.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.levy.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.levy.NAME\n    'levy'\n\n\nbase.random.levy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.levy.PRNG;\n\n\nbase.random.levy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.levy.seed;\n\n\nbase.random.levy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.levy.seedLength;\n\n\nbase.random.levy.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.levy( 2.0, 5.0 )\n    <number>\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.levy.state\n    <Uint32Array>\n\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.levy.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>\n\n\nbase.random.levy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.levy.stateLength;\n\n\nbase.random.levy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.levy.byteLength;\n\n\nbase.random.levy.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.levy.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.levy, random.iterators.levy, random.streams.levy\n","base.random.levy.factory":"\nbase.random.levy.factory( [μ, c, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Lévy distribution.\n\n    If provided `μ` and `c`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `c`, the returned PRNG requires that both `μ` and\n    `c` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    c: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.levy.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `b`:\n    > rand = base.random.levy.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.levy.NAME":"\nbase.random.levy.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.levy.NAME\n    'levy'","base.random.levy.PRNG":"\nbase.random.levy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.levy.PRNG;","base.random.levy.seed":"\nbase.random.levy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.levy.seed;","base.random.levy.seedLength":"\nbase.random.levy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.levy.seedLength;","base.random.levy.state":"\nbase.random.levy.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.levy( 2.0, 5.0 )\n    <number>\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.levy.state\n    <Uint32Array>\n\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.levy.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>","base.random.levy.stateLength":"\nbase.random.levy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.levy.stateLength;","base.random.levy.byteLength":"\nbase.random.levy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.levy.byteLength;","base.random.levy.toJSON":"\nbase.random.levy.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.levy.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.levy, random.iterators.levy, random.streams.levy","base.random.logistic":"\nbase.random.logistic( μ, s )\n    Returns a pseudorandom number drawn from a logistic distribution.\n\n    If `μ` or `s` is `NaN` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.logistic( 2.0, 5.0 );\n\n\nbase.random.logistic.factory( [μ, s, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a logistic distribution.\n\n    If provided `μ` and `s`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n    `s` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.logistic.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `s`:\n    > rand = base.random.logistic.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.logistic.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.logistic.NAME\n    'logistic'\n\n\nbase.random.logistic.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.logistic.PRNG;\n\n\nbase.random.logistic.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.logistic.seed;\n\n\nbase.random.logistic.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.logistic.seedLength;\n\n\nbase.random.logistic.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.logistic( 2.0, 5.0 )\n    <number>\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.logistic.state\n    <Uint32Array>\n\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.logistic.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>\n\n\nbase.random.logistic.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.logistic.stateLength;\n\n\nbase.random.logistic.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.logistic.byteLength;\n\n\nbase.random.logistic.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.logistic.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.logistic, random.iterators.logistic, random.streams.logistic\n","base.random.logistic.factory":"\nbase.random.logistic.factory( [μ, s, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a logistic distribution.\n\n    If provided `μ` and `s`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n    `s` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.logistic.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `s`:\n    > rand = base.random.logistic.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.logistic.NAME":"\nbase.random.logistic.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.logistic.NAME\n    'logistic'","base.random.logistic.PRNG":"\nbase.random.logistic.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.logistic.PRNG;","base.random.logistic.seed":"\nbase.random.logistic.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.logistic.seed;","base.random.logistic.seedLength":"\nbase.random.logistic.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.logistic.seedLength;","base.random.logistic.state":"\nbase.random.logistic.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.logistic( 2.0, 5.0 )\n    <number>\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.logistic.state\n    <Uint32Array>\n\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.logistic.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>","base.random.logistic.stateLength":"\nbase.random.logistic.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.logistic.stateLength;","base.random.logistic.byteLength":"\nbase.random.logistic.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.logistic.byteLength;","base.random.logistic.toJSON":"\nbase.random.logistic.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.logistic.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.logistic, random.iterators.logistic, random.streams.logistic","base.random.lognormal":"\nbase.random.lognormal( μ, σ )\n    Returns a pseudorandom number drawn from a lognormal distribution.\n\n    If `μ` or `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.lognormal( 2.0, 5.0 );\n\n\nbase.random.lognormal.factory( [μ, σ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a lognormal distribution.\n\n    If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n    `σ` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter.\n\n    σ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.lognormal.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `σ`:\n    > rand = base.random.lognormal.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.lognormal.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.lognormal.NAME\n    'lognormal'\n\n\nbase.random.lognormal.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.lognormal.PRNG;\n\n\nbase.random.lognormal.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.lognormal.seed;\n\n\nbase.random.lognormal.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.lognormal.seedLength;\n\n\nbase.random.lognormal.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.lognormal.state\n    <Uint32Array>\n\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.lognormal.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n\n\nbase.random.lognormal.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.lognormal.stateLength;\n\n\nbase.random.lognormal.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.lognormal.byteLength;\n\n\nbase.random.lognormal.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.lognormal.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.lognormal, random.iterators.lognormal, random.streams.lognormal\n","base.random.lognormal.factory":"\nbase.random.lognormal.factory( [μ, σ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a lognormal distribution.\n\n    If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n    `σ` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter.\n\n    σ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.lognormal.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `σ`:\n    > rand = base.random.lognormal.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.lognormal.NAME":"\nbase.random.lognormal.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.lognormal.NAME\n    'lognormal'","base.random.lognormal.PRNG":"\nbase.random.lognormal.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.lognormal.PRNG;","base.random.lognormal.seed":"\nbase.random.lognormal.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.lognormal.seed;","base.random.lognormal.seedLength":"\nbase.random.lognormal.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.lognormal.seedLength;","base.random.lognormal.state":"\nbase.random.lognormal.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.lognormal.state\n    <Uint32Array>\n\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.lognormal.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>","base.random.lognormal.stateLength":"\nbase.random.lognormal.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.lognormal.stateLength;","base.random.lognormal.byteLength":"\nbase.random.lognormal.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.lognormal.byteLength;","base.random.lognormal.toJSON":"\nbase.random.lognormal.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.lognormal.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.lognormal, random.iterators.lognormal, random.streams.lognormal","base.random.minstd":"\nbase.random.minstd()\n    Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n\n    This pseudorandom number generator (PRNG) is a linear congruential\n    pseudorandom number generator (LCG) based on Park and Miller.\n\n    The generator has a period of approximately `2.1e9`.\n\n    An LCG is fast and uses little memory. On the other hand, because the\n    generator is a simple LCG, the generator has recognized shortcomings. By\n    today's PRNG standards, the generator's period is relatively short. More\n    importantly, the \"randomness quality\" of the generator's output is lacking.\n    These defects make the generator unsuitable, for example, in Monte Carlo\n    simulations and in cryptographic applications.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.minstd();\n\n\nbase.random.minstd.normalized()\n    Returns a pseudorandom number on the interval `[0,1)`.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.minstd.normalized();\n\n\nbase.random.minstd.factory( [options] )\n    Returns a linear congruential pseudorandom number generator (LCG).\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.minstd.factory();\n    > r = rand();\n    > r = rand();\n\n    // Provide a seed:\n    > rand = base.random.minstd.factory( { 'seed': 1234 } );\n    > r = rand()\n    20739838\n\n\nbase.random.minstd.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.minstd.NAME\n    'minstd'\n\n\nbase.random.minstd.MIN\n    Minimum possible value.\n\n    Examples\n    --------\n    > var v = base.random.minstd.MIN\n    1\n\n\nbase.random.minstd.MAX\n    Maximum possible value.\n\n    Examples\n    --------\n    > var v = base.random.minstd.MAX\n    2147483646\n\n\nbase.random.minstd.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.minstd.seed;\n\n\nbase.random.minstd.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.minstd.seedLength;\n\n\nbase.random.minstd.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.minstd()\n    <number>\n    > r = base.random.minstd()\n    <number>\n    > r = base.random.minstd()\n    <number>\n\n    // Get the current state:\n    > var state = base.random.minstd.state\n    <Int32Array>\n\n    > r = base.random.minstd()\n    <number>\n    > r = base.random.minstd()\n    <number>\n\n    // Set the state:\n    > base.random.minstd.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.minstd()\n    <number>\n    > r = base.random.minstd()\n    <number>\n\n\nbase.random.minstd.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.minstd.stateLength;\n\n\nbase.random.minstd.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.minstd.byteLength;\n\n\nbase.random.minstd.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.minstd.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.minstd, random.iterators.minstd, random.streams.minstd, base.random.minstdShuffle, base.random.mt19937, base.random.randi\n","base.random.minstd.normalized":"\nbase.random.minstd.normalized()\n    Returns a pseudorandom number on the interval `[0,1)`.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.minstd.normalized();","base.random.minstd.factory":"\nbase.random.minstd.factory( [options] )\n    Returns a linear congruential pseudorandom number generator (LCG).\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.minstd.factory();\n    > r = rand();\n    > r = rand();\n\n    // Provide a seed:\n    > rand = base.random.minstd.factory( { 'seed': 1234 } );\n    > r = rand()\n    20739838","base.random.minstd.NAME":"\nbase.random.minstd.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.minstd.NAME\n    'minstd'","base.random.minstd.MIN":"\nbase.random.minstd.MIN\n    Minimum possible value.\n\n    Examples\n    --------\n    > var v = base.random.minstd.MIN\n    1","base.random.minstd.MAX":"\nbase.random.minstd.MAX\n    Maximum possible value.\n\n    Examples\n    --------\n    > var v = base.random.minstd.MAX\n    2147483646","base.random.minstd.seed":"\nbase.random.minstd.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.minstd.seed;","base.random.minstd.seedLength":"\nbase.random.minstd.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.minstd.seedLength;","base.random.minstd.state":"\nbase.random.minstd.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.minstd()\n    <number>\n    > r = base.random.minstd()\n    <number>\n    > r = base.random.minstd()\n    <number>\n\n    // Get the current state:\n    > var state = base.random.minstd.state\n    <Int32Array>\n\n    > r = base.random.minstd()\n    <number>\n    > r = base.random.minstd()\n    <number>\n\n    // Set the state:\n    > base.random.minstd.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.minstd()\n    <number>\n    > r = base.random.minstd()\n    <number>","base.random.minstd.stateLength":"\nbase.random.minstd.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.minstd.stateLength;","base.random.minstd.byteLength":"\nbase.random.minstd.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.minstd.byteLength;","base.random.minstd.toJSON":"\nbase.random.minstd.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.minstd.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.minstd, random.iterators.minstd, random.streams.minstd, base.random.minstdShuffle, base.random.mt19937, base.random.randi","base.random.minstdShuffle":"\nbase.random.minstdShuffle()\n    Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n\n    This pseudorandom number generator (PRNG) is a linear congruential\n    pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n    Durham algorithm. The shuffle step considerably strengthens the \"randomness\n    quality\" of a simple LCG's output.\n\n    The generator has a period of approximately `2.1e9`.\n\n    An LCG is fast and uses little memory. On the other hand, because the\n    generator is a simple LCG, the generator has recognized shortcomings. By\n    today's PRNG standards, the generator's period is relatively short. In\n    general, this generator is unsuitable for Monte Carlo simulations and\n    cryptographic applications.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.minstdShuffle();\n\n\nbase.random.minstdShuffle.normalized()\n    Returns a pseudorandom number on the interval `[0,1)`.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.minstdShuffle.normalized();\n\n\nbase.random.minstdShuffle.factory( [options] )\n    Returns a linear congruential pseudorandom number generator (LCG) whose\n    output is shuffled.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.minstdShuffle.factory();\n    > r = rand();\n    > r = rand();\n\n    // Provide a seed:\n    > rand = base.random.minstdShuffle.factory( { 'seed': 1234 } );\n    > r = rand()\n    1421600654\n\n\nbase.random.minstdShuffle.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.minstdShuffle.NAME\n    'minstd-shuffle'\n\n\nbase.random.minstdShuffle.MIN\n    Minimum possible value.\n\n    Examples\n    --------\n    > var v = base.random.minstdShuffle.MIN\n    1\n\n\nbase.random.minstdShuffle.MAX\n    Maximum possible value.\n\n    Examples\n    --------\n    > var v = base.random.minstdShuffle.MAX\n    2147483646\n\n\nbase.random.minstdShuffle.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.minstdShuffle.seed;\n\n\nbase.random.minstdShuffle.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.minstdShuffle.seedLength;\n\n\nbase.random.minstdShuffle.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.minstdShuffle()\n    <number>\n    > r = base.random.minstdShuffle()\n    <number>\n    > r = base.random.minstdShuffle()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.minstdShuffle.state\n    <Int32Array>\n\n    > r = base.random.minstdShuffle()\n    <number>\n    > r = base.random.minstdShuffle()\n    <number>\n\n    // Set the state:\n    > base.random.minstdShuffle.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.minstdShuffle()\n    <number>\n    > r = base.random.minstdShuffle()\n    <number>\n\n\nbase.random.minstdShuffle.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.minstdShuffle.stateLength;\n\n\nbase.random.minstdShuffle.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.minstdShuffle.byteLength;\n\n\nbase.random.minstdShuffle.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.minstdShuffle.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstdShuffle, base.random.minstd, base.random.mt19937, base.random.randi\n","base.random.minstdShuffle.normalized":"\nbase.random.minstdShuffle.normalized()\n    Returns a pseudorandom number on the interval `[0,1)`.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.minstdShuffle.normalized();","base.random.minstdShuffle.factory":"\nbase.random.minstdShuffle.factory( [options] )\n    Returns a linear congruential pseudorandom number generator (LCG) whose\n    output is shuffled.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.minstdShuffle.factory();\n    > r = rand();\n    > r = rand();\n\n    // Provide a seed:\n    > rand = base.random.minstdShuffle.factory( { 'seed': 1234 } );\n    > r = rand()\n    1421600654","base.random.minstdShuffle.NAME":"\nbase.random.minstdShuffle.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.minstdShuffle.NAME\n    'minstd-shuffle'","base.random.minstdShuffle.MIN":"\nbase.random.minstdShuffle.MIN\n    Minimum possible value.\n\n    Examples\n    --------\n    > var v = base.random.minstdShuffle.MIN\n    1","base.random.minstdShuffle.MAX":"\nbase.random.minstdShuffle.MAX\n    Maximum possible value.\n\n    Examples\n    --------\n    > var v = base.random.minstdShuffle.MAX\n    2147483646","base.random.minstdShuffle.seed":"\nbase.random.minstdShuffle.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.minstdShuffle.seed;","base.random.minstdShuffle.seedLength":"\nbase.random.minstdShuffle.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.minstdShuffle.seedLength;","base.random.minstdShuffle.state":"\nbase.random.minstdShuffle.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.minstdShuffle()\n    <number>\n    > r = base.random.minstdShuffle()\n    <number>\n    > r = base.random.minstdShuffle()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.minstdShuffle.state\n    <Int32Array>\n\n    > r = base.random.minstdShuffle()\n    <number>\n    > r = base.random.minstdShuffle()\n    <number>\n\n    // Set the state:\n    > base.random.minstdShuffle.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.minstdShuffle()\n    <number>\n    > r = base.random.minstdShuffle()\n    <number>","base.random.minstdShuffle.stateLength":"\nbase.random.minstdShuffle.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.minstdShuffle.stateLength;","base.random.minstdShuffle.byteLength":"\nbase.random.minstdShuffle.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.minstdShuffle.byteLength;","base.random.minstdShuffle.toJSON":"\nbase.random.minstdShuffle.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.minstdShuffle.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstdShuffle, base.random.minstd, base.random.mt19937, base.random.randi","base.random.mt19937":"\nbase.random.mt19937()\n    Returns a pseudorandom integer on the interval `[0, 4294967295]`.\n\n    This pseudorandom number generator (PRNG) is a 32-bit Mersenne Twister\n    pseudorandom number generator.\n\n    The PRNG is *not* a cryptographically secure PRNG.\n\n    The PRNG has a period of 2^19937 - 1.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.mt19937();\n\n\nbase.random.mt19937.normalized()\n    Returns a pseudorandom number on the interval `[0,1)` with 53-bit precision.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.mt19937.normalized();\n\n\nbase.random.mt19937.factory( [options] )\n    Returns a 32-bit Mersenne Twister pseudorandom number generator.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.mt19937.factory();\n    > r = rand();\n    > r = rand();\n\n    // Provide a seed:\n    > rand = base.random.mt19937.factory( { 'seed': 1234 } );\n    > r = rand()\n    822569775\n\n\nbase.random.mt19937.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.mt19937.NAME\n    'mt19937'\n\n\nbase.random.mt19937.MIN\n    Minimum possible value.\n\n    Examples\n    --------\n    > var v = base.random.mt19937.MIN\n    0\n\n\nbase.random.mt19937.MAX\n    Maximum possible value.\n\n    Examples\n    --------\n    > var v = base.random.mt19937.MAX\n    4294967295\n\n\nbase.random.mt19937.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.mt19937.seed;\n\n\nbase.random.mt19937.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.mt19937.seedLength;\n\n\nbase.random.mt19937.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.mt19937()\n    <number>\n    > r = base.random.mt19937()\n    <number>\n    > r = base.random.mt19937()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.mt19937.state\n    <Uint32Array>\n\n    > r = base.random.mt19937()\n    <number>\n    > r = base.random.mt19937()\n    <number>\n\n    // Set the state:\n    > base.random.mt19937.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.mt19937()\n    <number>\n    > r = base.random.mt19937()\n    <number>\n\n\nbase.random.mt19937.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.mt19937.stateLength;\n\n\nbase.random.mt19937.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.mt19937.byteLength;\n\n\nbase.random.mt19937.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.mt19937.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.mt19937, random.iterators.mt19937, random.streams.mt19937, base.random.minstd, base.random.randi\n","base.random.mt19937.normalized":"\nbase.random.mt19937.normalized()\n    Returns a pseudorandom number on the interval `[0,1)` with 53-bit precision.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.mt19937.normalized();","base.random.mt19937.factory":"\nbase.random.mt19937.factory( [options] )\n    Returns a 32-bit Mersenne Twister pseudorandom number generator.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.mt19937.factory();\n    > r = rand();\n    > r = rand();\n\n    // Provide a seed:\n    > rand = base.random.mt19937.factory( { 'seed': 1234 } );\n    > r = rand()\n    822569775","base.random.mt19937.NAME":"\nbase.random.mt19937.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.mt19937.NAME\n    'mt19937'","base.random.mt19937.MIN":"\nbase.random.mt19937.MIN\n    Minimum possible value.\n\n    Examples\n    --------\n    > var v = base.random.mt19937.MIN\n    0","base.random.mt19937.MAX":"\nbase.random.mt19937.MAX\n    Maximum possible value.\n\n    Examples\n    --------\n    > var v = base.random.mt19937.MAX\n    4294967295","base.random.mt19937.seed":"\nbase.random.mt19937.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.mt19937.seed;","base.random.mt19937.seedLength":"\nbase.random.mt19937.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.mt19937.seedLength;","base.random.mt19937.state":"\nbase.random.mt19937.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.mt19937()\n    <number>\n    > r = base.random.mt19937()\n    <number>\n    > r = base.random.mt19937()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.mt19937.state\n    <Uint32Array>\n\n    > r = base.random.mt19937()\n    <number>\n    > r = base.random.mt19937()\n    <number>\n\n    // Set the state:\n    > base.random.mt19937.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.mt19937()\n    <number>\n    > r = base.random.mt19937()\n    <number>","base.random.mt19937.stateLength":"\nbase.random.mt19937.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.mt19937.stateLength;","base.random.mt19937.byteLength":"\nbase.random.mt19937.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.mt19937.byteLength;","base.random.mt19937.toJSON":"\nbase.random.mt19937.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.mt19937.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.mt19937, random.iterators.mt19937, random.streams.mt19937, base.random.minstd, base.random.randi","base.random.negativeBinomial":"\nbase.random.negativeBinomial( r, p )\n    Returns a pseudorandom number drawn from a negative binomial distribution.\n\n    If `p` is not in the interval `(0,1)`, the function returns `NaN`.\n\n    If `r` or `p` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.negativeBinomial( 20, 0.8 );\n\n\nbase.random.negativeBinomial.factory( [r, p, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a negative binomial distribution.\n\n    If provided `r` and `p`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `r` and `p`, the returned PRNG requires that both `r` and\n    `p` be provided at each invocation.\n\n    Parameters\n    ----------\n    r: number (optional)\n        Number of successes until experiment is stopped.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.negativeBinomial.factory();\n    > var r = rand( 20, 0.3 );\n    > r = rand( 10, 0.77 );\n\n    // Provide `r` and `p`:\n    > rand = base.random.negativeBinomial.factory( 10, 0.8 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.negativeBinomial.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.negativeBinomial.NAME\n    'negative-binomial'\n\n\nbase.random.negativeBinomial.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.negativeBinomial.PRNG;\n\n\nbase.random.negativeBinomial.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.negativeBinomial.seed;\n\n\nbase.random.negativeBinomial.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.negativeBinomial.seedLength;\n\n\nbase.random.negativeBinomial.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.negativeBinomial.state\n    <Uint32Array>\n\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n\n    // Set the state:\n    > base.random.negativeBinomial.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n\n\nbase.random.negativeBinomial.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.negativeBinomial.stateLength;\n\n\nbase.random.negativeBinomial.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.negativeBinomial.byteLength;\n\n\nbase.random.negativeBinomial.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.negativeBinomial.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.negativeBinomial, random.iterators.negativeBinomial, random.streams.negativeBinomial\n","base.random.negativeBinomial.factory":"\nbase.random.negativeBinomial.factory( [r, p, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a negative binomial distribution.\n\n    If provided `r` and `p`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `r` and `p`, the returned PRNG requires that both `r` and\n    `p` be provided at each invocation.\n\n    Parameters\n    ----------\n    r: number (optional)\n        Number of successes until experiment is stopped.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.negativeBinomial.factory();\n    > var r = rand( 20, 0.3 );\n    > r = rand( 10, 0.77 );\n\n    // Provide `r` and `p`:\n    > rand = base.random.negativeBinomial.factory( 10, 0.8 );\n    > r = rand();\n    > r = rand();","base.random.negativeBinomial.NAME":"\nbase.random.negativeBinomial.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.negativeBinomial.NAME\n    'negative-binomial'","base.random.negativeBinomial.PRNG":"\nbase.random.negativeBinomial.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.negativeBinomial.PRNG;","base.random.negativeBinomial.seed":"\nbase.random.negativeBinomial.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.negativeBinomial.seed;","base.random.negativeBinomial.seedLength":"\nbase.random.negativeBinomial.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.negativeBinomial.seedLength;","base.random.negativeBinomial.state":"\nbase.random.negativeBinomial.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.negativeBinomial.state\n    <Uint32Array>\n\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n\n    // Set the state:\n    > base.random.negativeBinomial.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>","base.random.negativeBinomial.stateLength":"\nbase.random.negativeBinomial.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.negativeBinomial.stateLength;","base.random.negativeBinomial.byteLength":"\nbase.random.negativeBinomial.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.negativeBinomial.byteLength;","base.random.negativeBinomial.toJSON":"\nbase.random.negativeBinomial.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.negativeBinomial.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.negativeBinomial, random.iterators.negativeBinomial, random.streams.negativeBinomial","base.random.normal":"\nbase.random.normal( μ, σ )\n    Returns a pseudorandom number drawn from a normal distribution.\n\n    If `μ` or `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.normal( 2.0, 5.0 );\n\n\nbase.random.normal.factory( [μ, σ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a normal distribution.\n\n    If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n    `σ` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    σ: number (optional)\n        Standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.normal.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `σ`:\n    > rand = base.random.normal.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.normal.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.normal.NAME\n    'normal'\n\n\nbase.random.normal.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.normal.PRNG;\n\n\nbase.random.normal.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.normal.seed;\n\n\nbase.random.normal.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.normal.seedLength;\n\n\nbase.random.normal.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.normal( 2.0, 5.0 )\n    <number>\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.normal.state\n    <Uint32Array>\n\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.normal.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>\n\n\nbase.random.normal.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.normal.stateLength;\n\n\nbase.random.normal.byteLength\n    Size of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.normal.byteLength;\n\n\nbase.random.normal.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.normal.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.normal, random.iterators.normal, random.streams.normal\n","base.random.normal.factory":"\nbase.random.normal.factory( [μ, σ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a normal distribution.\n\n    If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n    `σ` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    σ: number (optional)\n        Standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.normal.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `σ`:\n    > rand = base.random.normal.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.normal.NAME":"\nbase.random.normal.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.normal.NAME\n    'normal'","base.random.normal.PRNG":"\nbase.random.normal.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.normal.PRNG;","base.random.normal.seed":"\nbase.random.normal.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.normal.seed;","base.random.normal.seedLength":"\nbase.random.normal.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.normal.seedLength;","base.random.normal.state":"\nbase.random.normal.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.normal( 2.0, 5.0 )\n    <number>\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.normal.state\n    <Uint32Array>\n\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.normal.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>","base.random.normal.stateLength":"\nbase.random.normal.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.normal.stateLength;","base.random.normal.byteLength":"\nbase.random.normal.byteLength\n    Size of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.normal.byteLength;","base.random.normal.toJSON":"\nbase.random.normal.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.normal.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.normal, random.iterators.normal, random.streams.normal","base.random.pareto1":"\nbase.random.pareto1( α, β )\n    Returns a pseudorandom number drawn from a Pareto (Type I) distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.pareto1( 2.0, 5.0 );\n\n\nbase.random.pareto1.factory( [α, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Pareto (Type I) distribution.\n\n    If provided `α` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `α` and `β`, the returned PRNG requires that both `α` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.pareto1.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `α` and `β`:\n    > rand = base.random.pareto1.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.pareto1.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.pareto1.NAME\n    'pareto-type1'\n\n\nbase.random.pareto1.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.pareto1.PRNG;\n\n\nbase.random.pareto1.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.pareto1.seed;\n\n\nbase.random.pareto1.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.pareto1.seedLength;\n\n\nbase.random.pareto1.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.pareto1.state\n    <Uint32Array>\n\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.pareto1.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n\n\nbase.random.pareto1.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.pareto1.stateLength;\n\n\nbase.random.pareto1.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.pareto1.byteLength;\n\n\nbase.random.pareto1.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.pareto1.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.pareto1, random.iterators.pareto1, random.streams.pareto1\n","base.random.pareto1.factory":"\nbase.random.pareto1.factory( [α, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Pareto (Type I) distribution.\n\n    If provided `α` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `α` and `β`, the returned PRNG requires that both `α` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.pareto1.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `α` and `β`:\n    > rand = base.random.pareto1.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.pareto1.NAME":"\nbase.random.pareto1.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.pareto1.NAME\n    'pareto-type1'","base.random.pareto1.PRNG":"\nbase.random.pareto1.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.pareto1.PRNG;","base.random.pareto1.seed":"\nbase.random.pareto1.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.pareto1.seed;","base.random.pareto1.seedLength":"\nbase.random.pareto1.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.pareto1.seedLength;","base.random.pareto1.state":"\nbase.random.pareto1.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.pareto1.state\n    <Uint32Array>\n\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.pareto1.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>","base.random.pareto1.stateLength":"\nbase.random.pareto1.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.pareto1.stateLength;","base.random.pareto1.byteLength":"\nbase.random.pareto1.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.pareto1.byteLength;","base.random.pareto1.toJSON":"\nbase.random.pareto1.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.pareto1.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.pareto1, random.iterators.pareto1, random.streams.pareto1","base.random.poisson":"\nbase.random.poisson( λ )\n    Returns a pseudorandom number drawn from a Poisson distribution.\n\n    If `λ <= 0` or `λ` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.poisson( 7.9 );\n\n\nbase.random.poisson.factory( [λ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Poisson distribution.\n\n    If provided `λ`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    λ: number (optional)\n        Mean.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.poisson.factory();\n    > var r = rand( 4.0 );\n    > r = rand( 3.14 );\n\n    // Provide `λ`:\n    > rand = base.random.poisson.factory( 10.0 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.poisson.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.poisson.NAME\n    'poisson'\n\n\nbase.random.poisson.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.poisson.PRNG;\n\n\nbase.random.poisson.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.poisson.seed;\n\n\nbase.random.poisson.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.poisson.seedLength;\n\n\nbase.random.poisson.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.poisson( 10.0 )\n    <number>\n    > r = base.random.poisson( 10.0 )\n    <number>\n    > r = base.random.poisson( 10.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.poisson.state\n    <Uint32Array>\n\n    > r = base.random.poisson( 10.0 )\n    <number>\n    > r = base.random.poisson( 10.0 )\n    <number>\n\n    // Set the state:\n    > base.random.poisson.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.poisson( 10.0 )\n    <number>\n    > r = base.random.poisson( 10.0 )\n    <number>\n\n\nbase.random.poisson.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.poisson.stateLength;\n\n\nbase.random.poisson.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.poisson.byteLength;\n\n\nbase.random.poisson.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.poisson.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.poisson, random.iterators.poisson, random.streams.poisson\n","base.random.poisson.factory":"\nbase.random.poisson.factory( [λ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Poisson distribution.\n\n    If provided `λ`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    λ: number (optional)\n        Mean.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.poisson.factory();\n    > var r = rand( 4.0 );\n    > r = rand( 3.14 );\n\n    // Provide `λ`:\n    > rand = base.random.poisson.factory( 10.0 );\n    > r = rand();\n    > r = rand();","base.random.poisson.NAME":"\nbase.random.poisson.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.poisson.NAME\n    'poisson'","base.random.poisson.PRNG":"\nbase.random.poisson.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.poisson.PRNG;","base.random.poisson.seed":"\nbase.random.poisson.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.poisson.seed;","base.random.poisson.seedLength":"\nbase.random.poisson.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.poisson.seedLength;","base.random.poisson.state":"\nbase.random.poisson.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.poisson( 10.0 )\n    <number>\n    > r = base.random.poisson( 10.0 )\n    <number>\n    > r = base.random.poisson( 10.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.poisson.state\n    <Uint32Array>\n\n    > r = base.random.poisson( 10.0 )\n    <number>\n    > r = base.random.poisson( 10.0 )\n    <number>\n\n    // Set the state:\n    > base.random.poisson.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.poisson( 10.0 )\n    <number>\n    > r = base.random.poisson( 10.0 )\n    <number>","base.random.poisson.stateLength":"\nbase.random.poisson.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.poisson.stateLength;","base.random.poisson.byteLength":"\nbase.random.poisson.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.poisson.byteLength;","base.random.poisson.toJSON":"\nbase.random.poisson.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.poisson.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.poisson, random.iterators.poisson, random.streams.poisson","base.random.randi":"\nbase.random.randi()\n    Returns a pseudorandom number having an integer value.\n\n    The default underlying pseudorandom number generator (PRNG) *may* change in\n    the future. If exact reproducibility is required, either use the `factory`\n    method to explicitly specify a PRNG via the `name` option or use an\n    underlying PRNG directly.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.randi();\n\n\nbase.random.randi.factory( [options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers having integer values.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of the underlying pseudorandom number generator (PRNG). The\n        following PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underlying PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var randi = base.random.randi.factory();\n    > var r = randi();\n    > r = randi();\n\n    // Specify alternative PRNG:\n    > randi = base.random.randi.factory({ 'name': 'minstd' });\n    > r = randi();\n    > r = randi();\n\n\nbase.random.randi.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.randi.NAME\n    'randi'\n\n\nbase.random.randi.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.randi.PRNG;\n\n\nbase.random.randi.MIN\n    Minimum possible value (specific to underlying PRNG).\n\n    Examples\n    --------\n    > var v = base.random.randi.MIN;\n\n\nbase.random.randi.MAX\n    Maximum possible value (specific to underlying PRNG).\n\n    Examples\n    --------\n    > var v = base.random.randi.MAX;\n\n\nbase.random.randi.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.randi.seed;\n\n\nbase.random.randi.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.randi.seedLength;\n\n\nbase.random.randi.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.randi()\n    <number>\n    > r = base.random.randi()\n    <number>\n    > r = base.random.randi()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.randi.state;\n\n    > r = base.random.randi()\n    <number>\n    > r = base.random.randi()\n    <number>\n\n    // Set the state:\n    > base.random.randi.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.randi()\n    <number>\n    > r = base.random.randi()\n    <number>\n\n\nbase.random.randi.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.randi.stateLength;\n\n\nbase.random.randi.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.randi.byteLength;\n\n\nbase.random.randi.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.randi.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.iterators.randi, random.streams.randi, base.random.minstd, base.random.minstdShuffle, base.random.mt19937\n","base.random.randi.factory":"\nbase.random.randi.factory( [options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers having integer values.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of the underlying pseudorandom number generator (PRNG). The\n        following PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underlying PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var randi = base.random.randi.factory();\n    > var r = randi();\n    > r = randi();\n\n    // Specify alternative PRNG:\n    > randi = base.random.randi.factory({ 'name': 'minstd' });\n    > r = randi();\n    > r = randi();","base.random.randi.NAME":"\nbase.random.randi.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.randi.NAME\n    'randi'","base.random.randi.PRNG":"\nbase.random.randi.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.randi.PRNG;","base.random.randi.MIN":"\nbase.random.randi.MIN\n    Minimum possible value (specific to underlying PRNG).\n\n    Examples\n    --------\n    > var v = base.random.randi.MIN;","base.random.randi.MAX":"\nbase.random.randi.MAX\n    Maximum possible value (specific to underlying PRNG).\n\n    Examples\n    --------\n    > var v = base.random.randi.MAX;","base.random.randi.seed":"\nbase.random.randi.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.randi.seed;","base.random.randi.seedLength":"\nbase.random.randi.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.randi.seedLength;","base.random.randi.state":"\nbase.random.randi.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.randi()\n    <number>\n    > r = base.random.randi()\n    <number>\n    > r = base.random.randi()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.randi.state;\n\n    > r = base.random.randi()\n    <number>\n    > r = base.random.randi()\n    <number>\n\n    // Set the state:\n    > base.random.randi.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.randi()\n    <number>\n    > r = base.random.randi()\n    <number>","base.random.randi.stateLength":"\nbase.random.randi.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.randi.stateLength;","base.random.randi.byteLength":"\nbase.random.randi.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.randi.byteLength;","base.random.randi.toJSON":"\nbase.random.randi.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.randi.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.iterators.randi, random.streams.randi, base.random.minstd, base.random.minstdShuffle, base.random.mt19937","base.random.randn":"\nbase.random.randn()\n    Returns a pseudorandom number drawn from a standard normal distribution.\n\n    The default underlying pseudorandom number generator (PRNG) *may* change in\n    the future. If exact reproducibility is required, either use the `factory`\n    method to explicitly specify a PRNG via the `name` option or use an\n    underlying PRNG directly.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.randn();\n\n\nbase.random.randn.factory( [options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a standard normal distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of the underlying pseudorandom number generator (PRNG) that samples\n        from a standard normal distribution. The following PRNGs are supported:\n\n        - improved-ziggurat: improved ziggurat method.\n        - box-muller: Box-Muller transform.\n\n        Default: 'improved-ziggurat'.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underlying PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.randn.factory();\n    > var r = rand();\n    > r = rand();\n\n    // Specify alternative PRNG:\n    > var rand = base.random.randn.factory({ 'name': 'box-muller' });\n    > r = rand();\n    > r = rand();\n\n\nbase.random.randn.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.randn.NAME\n    'randn'\n\n\nbase.random.randn.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.randn.PRNG;\n\n\nbase.random.randn.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.randn.seed;\n\n\nbase.random.randn.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.randn.seedLength;\n\n\nbase.random.randn.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.randn()\n    <number>\n    > r = base.random.randn()\n    <number>\n    > r = base.random.randn()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.randn.state;\n\n    > r = base.random.randn()\n    <number>\n    > r = base.random.randn()\n    <number>\n\n    // Set the state:\n    > base.random.randn.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.randn()\n    <number>\n    > r = base.random.randn()\n    <number>\n\n\nbase.random.randn.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.randn.stateLength;\n\n\nbase.random.randn.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.randn.byteLength;\n\n\nbase.random.randn.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.randn.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.iterators.randn, random.streams.randn, base.random.improvedZiggurat, base.random.randu\n","base.random.randn.factory":"\nbase.random.randn.factory( [options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a standard normal distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of the underlying pseudorandom number generator (PRNG) that samples\n        from a standard normal distribution. The following PRNGs are supported:\n\n        - improved-ziggurat: improved ziggurat method.\n        - box-muller: Box-Muller transform.\n\n        Default: 'improved-ziggurat'.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underlying PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.randn.factory();\n    > var r = rand();\n    > r = rand();\n\n    // Specify alternative PRNG:\n    > var rand = base.random.randn.factory({ 'name': 'box-muller' });\n    > r = rand();\n    > r = rand();","base.random.randn.NAME":"\nbase.random.randn.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.randn.NAME\n    'randn'","base.random.randn.PRNG":"\nbase.random.randn.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.randn.PRNG;","base.random.randn.seed":"\nbase.random.randn.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.randn.seed;","base.random.randn.seedLength":"\nbase.random.randn.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.randn.seedLength;","base.random.randn.state":"\nbase.random.randn.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.randn()\n    <number>\n    > r = base.random.randn()\n    <number>\n    > r = base.random.randn()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.randn.state;\n\n    > r = base.random.randn()\n    <number>\n    > r = base.random.randn()\n    <number>\n\n    // Set the state:\n    > base.random.randn.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.randn()\n    <number>\n    > r = base.random.randn()\n    <number>","base.random.randn.stateLength":"\nbase.random.randn.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.randn.stateLength;","base.random.randn.byteLength":"\nbase.random.randn.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.randn.byteLength;","base.random.randn.toJSON":"\nbase.random.randn.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.randn.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.iterators.randn, random.streams.randn, base.random.improvedZiggurat, base.random.randu","base.random.randu":"\nbase.random.randu()\n    Returns a pseudorandom number drawn from a uniform distribution.\n\n    The default underlying pseudorandom number generator (PRNG) *may* change in\n    the future. If exact reproducibility is required, either use the `factory`\n    method to explicitly specify a PRNG via the `name` option or use an\n    underlying PRNG directly.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number on the interval `[0,1)`.\n\n    Examples\n    --------\n    > var r = base.random.randu();\n\n\nbase.random.randu.factory( [options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a uniform distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of the underlying pseudorandom number generator (PRNG). The\n        following PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underlying PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.randu.factory();\n    > var r = rand();\n    > r = rand();\n\n    // Specify alternative PRNG:\n    > var rand = base.random.randu.factory({ 'name': 'minstd' });\n    > r = rand();\n    > r = rand();\n\n\nbase.random.randu.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.randu.NAME\n    'randu'\n\n\nbase.random.randu.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.randu.PRNG;\n\n\nbase.random.randu.MIN\n    Minimum possible value (specific to underlying PRNG).\n\n    Examples\n    --------\n    > var v = base.random.randu.MIN;\n\n\nbase.random.randu.MAX\n    Maximum possible value (specific to underlying PRNG).\n\n    Examples\n    --------\n    > var v = base.random.randu.MAX;\n\n\nbase.random.randu.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.randu.seed;\n\n\nbase.random.randu.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.randu.seedLength;\n\n\nbase.random.randu.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.randu()\n    <number>\n    > r = base.random.randu()\n    <number>\n    > r = base.random.randu()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.randu.state;\n\n    > r = base.random.randu()\n    <number>\n    > r = base.random.randu()\n    <number>\n\n    // Set the state:\n    > base.random.randu.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.randu()\n    <number>\n    > r = base.random.randu()\n    <number>\n\n\nbase.random.randu.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.randu.stateLength;\n\n\nbase.random.randu.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.randu.byteLength;\n\n\nbase.random.randu.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.randu.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.randu, random.iterators.randu, random.streams.randu, base.random.discreteUniform, base.random.randn\n","base.random.randu.factory":"\nbase.random.randu.factory( [options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a uniform distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of the underlying pseudorandom number generator (PRNG). The\n        following PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underlying PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.randu.factory();\n    > var r = rand();\n    > r = rand();\n\n    // Specify alternative PRNG:\n    > var rand = base.random.randu.factory({ 'name': 'minstd' });\n    > r = rand();\n    > r = rand();","base.random.randu.NAME":"\nbase.random.randu.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.randu.NAME\n    'randu'","base.random.randu.PRNG":"\nbase.random.randu.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.randu.PRNG;","base.random.randu.MIN":"\nbase.random.randu.MIN\n    Minimum possible value (specific to underlying PRNG).\n\n    Examples\n    --------\n    > var v = base.random.randu.MIN;","base.random.randu.MAX":"\nbase.random.randu.MAX\n    Maximum possible value (specific to underlying PRNG).\n\n    Examples\n    --------\n    > var v = base.random.randu.MAX;","base.random.randu.seed":"\nbase.random.randu.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.randu.seed;","base.random.randu.seedLength":"\nbase.random.randu.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.randu.seedLength;","base.random.randu.state":"\nbase.random.randu.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.randu()\n    <number>\n    > r = base.random.randu()\n    <number>\n    > r = base.random.randu()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.randu.state;\n\n    > r = base.random.randu()\n    <number>\n    > r = base.random.randu()\n    <number>\n\n    // Set the state:\n    > base.random.randu.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.randu()\n    <number>\n    > r = base.random.randu()\n    <number>","base.random.randu.stateLength":"\nbase.random.randu.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.randu.stateLength;","base.random.randu.byteLength":"\nbase.random.randu.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.randu.byteLength;","base.random.randu.toJSON":"\nbase.random.randu.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.randu.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.randu, random.iterators.randu, random.streams.randu, base.random.discreteUniform, base.random.randn","base.random.rayleigh":"\nbase.random.rayleigh( σ )\n    Returns a pseudorandom number drawn from a Rayleigh distribution.\n\n    If `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.rayleigh( 2.5 );\n\n\nbase.random.rayleigh.factory( [σ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Rayleigh distribution.\n\n    If provided `σ`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `σ`, the returned PRNG requires that `σ` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    σ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.rayleigh.factory();\n    > var r = rand( 5.0 );\n    > r = rand( 10.0 );\n\n    // Provide `σ`:\n    > rand = base.random.rayleigh.factory( 5.0 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.rayleigh.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.rayleigh.NAME\n    'rayleigh'\n\n\nbase.random.rayleigh.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.rayleigh.PRNG;\n\n\nbase.random.rayleigh.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.rayleigh.seed;\n\n\nbase.random.rayleigh.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.rayleigh.seedLength;\n\n\nbase.random.rayleigh.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.rayleigh( 5.0 )\n    <number>\n    > r = base.random.rayleigh( 5.0 )\n    <number>\n    > r = base.random.rayleigh( 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.rayleigh.state\n    <Uint32Array>\n\n    > r = base.random.rayleigh( 5.0 )\n    <number>\n    > r = base.random.rayleigh( 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.rayleigh.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.rayleigh( 5.0 )\n    <number>\n    > r = base.random.rayleigh( 5.0 )\n    <number>\n\n\nbase.random.rayleigh.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.rayleigh.stateLength;\n\n\nbase.random.rayleigh.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.rayleigh.byteLength;\n\n\nbase.random.rayleigh.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.rayleigh.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.rayleigh, random.iterators.rayleigh, random.streams.rayleigh\n","base.random.rayleigh.factory":"\nbase.random.rayleigh.factory( [σ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Rayleigh distribution.\n\n    If provided `σ`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `σ`, the returned PRNG requires that `σ` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    σ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.rayleigh.factory();\n    > var r = rand( 5.0 );\n    > r = rand( 10.0 );\n\n    // Provide `σ`:\n    > rand = base.random.rayleigh.factory( 5.0 );\n    > r = rand();\n    > r = rand();","base.random.rayleigh.NAME":"\nbase.random.rayleigh.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.rayleigh.NAME\n    'rayleigh'","base.random.rayleigh.PRNG":"\nbase.random.rayleigh.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.rayleigh.PRNG;","base.random.rayleigh.seed":"\nbase.random.rayleigh.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.rayleigh.seed;","base.random.rayleigh.seedLength":"\nbase.random.rayleigh.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.rayleigh.seedLength;","base.random.rayleigh.state":"\nbase.random.rayleigh.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.rayleigh( 5.0 )\n    <number>\n    > r = base.random.rayleigh( 5.0 )\n    <number>\n    > r = base.random.rayleigh( 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.rayleigh.state\n    <Uint32Array>\n\n    > r = base.random.rayleigh( 5.0 )\n    <number>\n    > r = base.random.rayleigh( 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.rayleigh.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.rayleigh( 5.0 )\n    <number>\n    > r = base.random.rayleigh( 5.0 )\n    <number>","base.random.rayleigh.stateLength":"\nbase.random.rayleigh.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.rayleigh.stateLength;","base.random.rayleigh.byteLength":"\nbase.random.rayleigh.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.rayleigh.byteLength;","base.random.rayleigh.toJSON":"\nbase.random.rayleigh.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.rayleigh.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.rayleigh, random.iterators.rayleigh, random.streams.rayleigh","base.random.t":"\nbase.random.t( v )\n    Returns a pseudorandom number drawn from a Student's t distribution.\n\n    If `v <= 0` or `v` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.t( 2.0 );\n\n\nbase.random.t.factory( [v, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Student's t distribution.\n\n    If provided `v`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `v`, the returned PRNG requires that `v` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    v: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.t.factory();\n    > var r = rand( 5.0 );\n    > r = rand( 3.14 );\n\n    // Provide `v`:\n    > rand = base.random.t.factory( 5.0 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.t.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.t.NAME\n    't'\n\n\nbase.random.t.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.t.PRNG;\n\n\nbase.random.t.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.t.seed;\n\n\nbase.random.t.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.t.seedLength;\n\n\nbase.random.t.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.t( 10.0 )\n    <number>\n    > r = base.random.t( 10.0 )\n    <number>\n    > r = base.random.t( 10.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.t.state\n    <Uint32Array>\n\n    > r = base.random.t( 10.0 )\n    <number>\n    > r = base.random.t( 10.0 )\n    <number>\n\n    // Set the state:\n    > base.random.t.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.t( 10.0 )\n    <number>\n    > r = base.random.t( 10.0 )\n    <number>\n\n\nbase.random.t.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.t.stateLength;\n\n\nbase.random.t.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.t.byteLength;\n\n\nbase.random.t.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.t.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.t, random.iterators.t, random.streams.t\n","base.random.t.factory":"\nbase.random.t.factory( [v, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Student's t distribution.\n\n    If provided `v`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `v`, the returned PRNG requires that `v` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    v: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.t.factory();\n    > var r = rand( 5.0 );\n    > r = rand( 3.14 );\n\n    // Provide `v`:\n    > rand = base.random.t.factory( 5.0 );\n    > r = rand();\n    > r = rand();","base.random.t.NAME":"\nbase.random.t.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.t.NAME\n    't'","base.random.t.PRNG":"\nbase.random.t.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.t.PRNG;","base.random.t.seed":"\nbase.random.t.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.t.seed;","base.random.t.seedLength":"\nbase.random.t.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.t.seedLength;","base.random.t.state":"\nbase.random.t.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.t( 10.0 )\n    <number>\n    > r = base.random.t( 10.0 )\n    <number>\n    > r = base.random.t( 10.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.t.state\n    <Uint32Array>\n\n    > r = base.random.t( 10.0 )\n    <number>\n    > r = base.random.t( 10.0 )\n    <number>\n\n    // Set the state:\n    > base.random.t.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.t( 10.0 )\n    <number>\n    > r = base.random.t( 10.0 )\n    <number>","base.random.t.stateLength":"\nbase.random.t.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.t.stateLength;","base.random.t.byteLength":"\nbase.random.t.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.t.byteLength;","base.random.t.toJSON":"\nbase.random.t.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.t.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.t, random.iterators.t, random.streams.t","base.random.triangular":"\nbase.random.triangular( a, b, c )\n    Returns a pseudorandom number drawn from a triangular distribution.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.triangular( 2.0, 5.0, 3.33 );\n\n\nbase.random.triangular.factory( [a, b, c, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a triangular distribution.\n\n    If provided `a`, `b`, and `c`, the returned PRNG returns random variates\n    drawn from the specified distribution.\n\n    If not provided `a`, `b`, and `c`, the returned PRNG requires that `a`, `b`,\n    and `c` be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    c: number (optional)\n        Mode.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.triangular.factory();\n    > var r = rand( 0.0, 1.0, 0.5 );\n    > r = rand( -2.0, 2.0, 1.0 );\n\n    // Provide `a`, `b`, and `c`:\n    > rand = base.random.triangular.factory( 0.0, 1.0, 0.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.triangular.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.triangular.NAME\n    'triangular'\n\n\nbase.random.triangular.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.triangular.PRNG;\n\n\nbase.random.triangular.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.triangular.seed;\n\n\nbase.random.triangular.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.triangular.seedLength;\n\n\nbase.random.triangular.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.triangular.state\n    <Uint32Array>\n\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n\n    // Set the state:\n    > base.random.triangular.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n\n\nbase.random.triangular.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.triangular.stateLength;\n\n\nbase.random.triangular.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.triangular.byteLength;\n\n\nbase.random.triangular.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.triangular.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.triangular, random.iterators.triangular, random.streams.triangular\n","base.random.triangular.factory":"\nbase.random.triangular.factory( [a, b, c, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a triangular distribution.\n\n    If provided `a`, `b`, and `c`, the returned PRNG returns random variates\n    drawn from the specified distribution.\n\n    If not provided `a`, `b`, and `c`, the returned PRNG requires that `a`, `b`,\n    and `c` be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    c: number (optional)\n        Mode.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.triangular.factory();\n    > var r = rand( 0.0, 1.0, 0.5 );\n    > r = rand( -2.0, 2.0, 1.0 );\n\n    // Provide `a`, `b`, and `c`:\n    > rand = base.random.triangular.factory( 0.0, 1.0, 0.5 );\n    > r = rand();\n    > r = rand();","base.random.triangular.NAME":"\nbase.random.triangular.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.triangular.NAME\n    'triangular'","base.random.triangular.PRNG":"\nbase.random.triangular.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.triangular.PRNG;","base.random.triangular.seed":"\nbase.random.triangular.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.triangular.seed;","base.random.triangular.seedLength":"\nbase.random.triangular.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.triangular.seedLength;","base.random.triangular.state":"\nbase.random.triangular.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.triangular.state\n    <Uint32Array>\n\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n\n    // Set the state:\n    > base.random.triangular.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>","base.random.triangular.stateLength":"\nbase.random.triangular.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.triangular.stateLength;","base.random.triangular.byteLength":"\nbase.random.triangular.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.triangular.byteLength;","base.random.triangular.toJSON":"\nbase.random.triangular.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.triangular.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.triangular, random.iterators.triangular, random.streams.triangular","base.random.uniform":"\nbase.random.uniform( a, b )\n    Returns a pseudorandom number drawn from a continuous uniform distribution.\n\n    If `a >= b`, the function returns `NaN`.\n\n    If `a` or `b` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support (inclusive).\n\n    b: number\n        Maximum support (exclusive).\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.uniform( 2.0, 5.0 );\n\n\nbase.random.uniform.factory( [a, b, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a continuous uniform distribution.\n\n    If provided `a` and `b`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `a` and `b`, the returned PRNG requires that both `a` and\n    `b` be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support (inclusive).\n\n    b: number (optional)\n        Maximum support (exclusive).\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.uniform.factory();\n    > var r = rand( 0.0, 1.0 );\n    > r = rand( -2.0, 2.0 );\n\n    // Provide `a` and `b`:\n    > rand = base.random.uniform.factory( 0.0, 1.0 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.uniform.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.uniform.NAME\n    'uniform'\n\n\nbase.random.uniform.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.uniform.PRNG;\n\n\nbase.random.uniform.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.uniform.seed;\n\n\nbase.random.uniform.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.uniform.seedLength;\n\n\nbase.random.uniform.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.uniform( 2.0, 5.0 )\n    <number>\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.uniform.state\n    <Uint32Array>\n\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.uniform.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>\n\n\nbase.random.uniform.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.uniform.stateLength;\n\n\nbase.random.uniform.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.uniform.byteLength;\n\n\nbase.random.uniform.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.uniform.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.uniform, random.iterators.uniform, random.streams.uniform, base.random.discreteUniform, base.random.randu\n","base.random.uniform.factory":"\nbase.random.uniform.factory( [a, b, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a continuous uniform distribution.\n\n    If provided `a` and `b`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `a` and `b`, the returned PRNG requires that both `a` and\n    `b` be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support (inclusive).\n\n    b: number (optional)\n        Maximum support (exclusive).\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.uniform.factory();\n    > var r = rand( 0.0, 1.0 );\n    > r = rand( -2.0, 2.0 );\n\n    // Provide `a` and `b`:\n    > rand = base.random.uniform.factory( 0.0, 1.0 );\n    > r = rand();\n    > r = rand();","base.random.uniform.NAME":"\nbase.random.uniform.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.uniform.NAME\n    'uniform'","base.random.uniform.PRNG":"\nbase.random.uniform.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.uniform.PRNG;","base.random.uniform.seed":"\nbase.random.uniform.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.uniform.seed;","base.random.uniform.seedLength":"\nbase.random.uniform.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.uniform.seedLength;","base.random.uniform.state":"\nbase.random.uniform.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.uniform( 2.0, 5.0 )\n    <number>\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.uniform.state\n    <Uint32Array>\n\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.uniform.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>","base.random.uniform.stateLength":"\nbase.random.uniform.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.uniform.stateLength;","base.random.uniform.byteLength":"\nbase.random.uniform.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.uniform.byteLength;","base.random.uniform.toJSON":"\nbase.random.uniform.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.uniform.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.uniform, random.iterators.uniform, random.streams.uniform, base.random.discreteUniform, base.random.randu","base.random.weibull":"\nbase.random.weibull( k, λ )\n    Returns a pseudorandom number drawn from a Weibull distribution.\n\n    If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n    If either `λ` or `k` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Scale parameter.\n\n    λ: number\n        Shape parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.weibull( 2.0, 5.0 );\n\n\nbase.random.weibull.factory( [k, λ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Weibull distribution.\n\n    If provided `k` and `λ`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `k` and `λ`, the returned PRNG requires that both\n    `k` and `λ` be provided at each invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Scale parameter.\n\n    λ: number (optional)\n        Shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.weibull.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `λ` and `k`:\n    > rand = base.random.weibull.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.weibull.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.weibull.NAME\n    'weibull'\n\n\nbase.random.weibull.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.weibull.PRNG;\n\n\nbase.random.weibull.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.weibull.seed;\n\n\nbase.random.weibull.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.weibull.seedLength;\n\n\nbase.random.weibull.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.weibull( 2.0, 5.0 )\n    <number>\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.weibull.state\n    <Uint32Array>\n\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.weibull.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>\n\n\nbase.random.weibull.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.weibull.stateLength;\n\n\nbase.random.weibull.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.weibull.byteLength;\n\n\nbase.random.weibull.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.weibull.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.weibull, random.iterators.weibull, random.streams.weibull\n","base.random.weibull.factory":"\nbase.random.weibull.factory( [k, λ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Weibull distribution.\n\n    If provided `k` and `λ`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `k` and `λ`, the returned PRNG requires that both\n    `k` and `λ` be provided at each invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Scale parameter.\n\n    λ: number (optional)\n        Shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.weibull.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `λ` and `k`:\n    > rand = base.random.weibull.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.weibull.NAME":"\nbase.random.weibull.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.weibull.NAME\n    'weibull'","base.random.weibull.PRNG":"\nbase.random.weibull.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.weibull.PRNG;","base.random.weibull.seed":"\nbase.random.weibull.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.weibull.seed;","base.random.weibull.seedLength":"\nbase.random.weibull.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.weibull.seedLength;","base.random.weibull.state":"\nbase.random.weibull.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.weibull( 2.0, 5.0 )\n    <number>\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.weibull.state\n    <Uint32Array>\n\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.weibull.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>","base.random.weibull.stateLength":"\nbase.random.weibull.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.weibull.stateLength;","base.random.weibull.byteLength":"\nbase.random.weibull.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.weibull.byteLength;","base.random.weibull.toJSON":"\nbase.random.weibull.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.weibull.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.weibull, random.iterators.weibull, random.streams.weibull","base.rcbrt":"\nbase.rcbrt( x )\n    Computes the reciprocal cube root of a double-precision floating-point\n    number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Reciprocal cube root.\n\n    Examples\n    --------\n    > var y = base.rcbrt( 8.0 )\n    0.5\n    > y = base.rcbrt( 1000.0 )\n    0.1\n    > y = base.rcbrt( 0.0 )\n    Infinity\n    > y = base.rcbrt( PINF )\n    0.0\n    > y = base.rcbrt( -8.0 )\n    -0.5\n    > y = base.rcbrt( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cbrt\n","base.rcbrtf":"\nbase.rcbrtf( x )\n    Computes the reciprocal cube root of a single-precision floating-point\n    number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Reciprocal cube root.\n\n    Examples\n    --------\n    > var y = base.rcbrtf( 8.0 )\n    0.5\n    > y = base.rcbrtf( 1000.0 )\n    ~0.1\n    > y = base.rcbrtf( 0.0 )\n    Infinity\n    > y = base.rcbrtf( PINF )\n    0.0\n    > y = base.rcbrtf( -8.0 )\n    -0.5\n    > y = base.rcbrtf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.rcbrt, base.cbrtf\n","base.reldiff":"\nbase.reldiff( x, y[, scale] )\n    Computes the relative difference of two real numbers.\n\n    By default, the function scales the absolute difference by dividing the\n    absolute difference by the maximum absolute value of `x` and `y`. To scale\n    by a different function, specify a scale function name.\n\n    The following `scale` functions are supported:\n\n    - 'max-abs': maximum absolute value of `x` and `y` (default).\n    - 'max': maximum value of `x` and `y`.\n    - 'min-abs': minimum absolute value of `x` and `y`.\n    - 'min': minimum value of `x` and `y`.\n    - 'mean-abs': arithmetic mean of the absolute values of `x` and `y`.\n    - 'mean': arithmetic mean of `x` and `y`.\n    - 'x': `x` (*noncommutative*).\n    - 'y': `y` (*noncommutative*).\n\n    To use a custom scale function, provide a function which accepts two numeric\n    arguments `x` and `y`.\n\n    If the absolute difference of `x` and `y` is `0`, the relative difference is\n    always `0`.\n\n    If `|x| = |y| = infinity`, the function returns `NaN`.\n\n    If `|x| = |-y| = infinity`, the relative difference is `+infinity`.\n\n    If a `scale` function returns `0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    scale: string|Function (optional)\n        Scale function. Default: `'max-abs'`.\n\n    Returns\n    -------\n    out: number\n        Relative difference.\n\n    Examples\n    --------\n    > var d = base.reldiff( 2.0, 5.0 )\n    0.6\n    > d = base.reldiff( -1.0, 3.14 )\n    ~1.318\n    > d = base.reldiff( -2.0, 5.0, 'max-abs' )\n    1.4\n    > d = base.reldiff( -2.0, 5.0, 'max' )\n    1.4\n    > d = base.reldiff( -2.0, 5.0, 'min-abs' )\n    3.5\n    > d = base.reldiff( -2.0, 5.0, 'min' )\n    3.5\n    > d = base.reldiff( -2.0, 5.0, 'mean-abs' )\n    2.0\n    > d = base.reldiff( -2.0, 5.0, 'mean' )\n    ~4.667\n    > d = base.reldiff( -2.0, 5.0, 'x' )\n    3.5\n    > d = base.reldiff( 5.0, -2.0, 'x' )\n    1.4\n    > d = base.reldiff( -2.0, 5.0, 'y' )\n    1.4\n    > d = base.reldiff( 5.0, -2.0, 'y' )\n    3.5\n\n    // Custom scale function:\n    > function scale( x, y ) {\n    ...     var s;\n    ...\n    ...     x = base.abs( x );\n    ...     y = base.abs( y );\n    ...\n    ...     // Maximum absolute value:\n    ...     s = (x < y ) ? y : x;\n    ...\n    ...     // Scale in units of epsilon:\n    ...     return s * EPS;\n    ... };\n    > d = base.reldiff( 12.15, 12.149999999999999, scale )\n    ~0.658\n\n    See Also\n    --------\n    base.absdiff, base.epsdiff\n","base.removeFirst":"\nbase.removeFirst( str, n )\n    Removes the first `n` UTF-16 code units of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of UTF-16 code units to remove.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.removeFirst( 'beep', 1 )\n    'eep'\n    > out = base.removeFirst( 'Boop', 1 )\n    'oop'\n    > out = base.removeFirst( 'foo bar', 5 )\n    'ar'\n\n    See Also\n    --------\n    base.removeFirstCodePoint, base.removeFirstGraphemeCluster, base.removeLast\n","base.removeFirstCodePoint":"\nbase.removeFirstCodePoint( str, n )\n    Removes the first `n` Unicode code points of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of Unicode code points to remove.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.removeFirstCodePoint( 'beep', 1 )\n    'eep'\n    > out = base.removeFirstCodePoint( 'Boop', 1 )\n    'oop'\n    > out = base.removeFirstCodePoint( 'foo bar', 5 )\n    'ar'\n\n    See Also\n    --------\n    base.removeLastCodePoint, base.removeFirstGraphemeCluster, base.removeFirst\n","base.removeFirstGraphemeCluster":"\nbase.removeFirstGraphemeCluster( str, n )\n    Removes the first `n` grapheme clusters (i.e., user-perceived characters)\n    of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of grapheme clusters to remove.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.removeFirstGraphemeCluster( 'beep', 1 )\n    'eep'\n    > out = base.removeFirstGraphemeCluster( 'Boop', 1 )\n    'oop'\n    > out = base.removeFirstGraphemeCluster( 'foo bar', 5 )\n    'ar'\n\n    See Also\n    --------\n    base.removeFirstCodePoint, base.removeLastGraphemeCluster, base.removeFirst\n","base.removeLast":"\nbase.removeLast( str, n )\n    Removes the last `n` UTF-16 code units of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of UTF-16 code units to remove.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.removeLast( 'beep', 1 )\n    'bee'\n    > out = base.removeLast( 'Boop', 1 )\n    'Boo'\n    > out = base.removeLast( 'foo bar', 5 )\n    'fo'\n\n    See Also\n    --------\n    base.removeLastCodePoint, base.removeLastGraphemeCluster, base.removeFirst\n","base.removeLastCodePoint":"\nbase.removeLastCodePoint( str, n )\n    Removes the last `n` Unicode code points of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of Unicode code points to remove.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.removeLastCodePoint( 'beep', 1 )\n    'bee'\n    > out = base.removeLastCodePoint( 'Boop', 1 )\n    'Boo'\n    > out = base.removeLastCodePoint( 'foo bar', 5 )\n    'fo'\n\n    See Also\n    --------\n    base.removeFirstCodePoint, base.removeLastGraphemeCluster, base.removeLast\n","base.removeLastGraphemeCluster":"\nbase.removeLastGraphemeCluster( str, n )\n    Removes the last `n` grapheme clusters (i.e., user-perceived characters)\n    of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of grapheme clusters to remove.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.removeLastGraphemeCluster( 'beep', 1 )\n    'bee'\n    > out = base.removeLastGraphemeCluster( 'Boop', 1 )\n    'Boo'\n    > out = base.removeLastGraphemeCluster( 'foo bar', 5 )\n    'fo'\n\n    See Also\n    --------\n    base.removeFirstCodePoint, base.removeLastCodePoint, base.removeLast\n","base.rempio2":"\nbase.rempio2( x, y )\n    Computes `x - nπ/2 = r`.\n\n    The function returns `n` and stores the remainder `r` as the two numbers\n    `y[0]` and `y[1]`, such that `y[0] + y[1] = r`.\n\n    For input values larger than `2^20 * π/2` in magnitude, the function only\n    returns the last three binary digits of `n` and not the full result.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    y: Array|TypedArray|Object\n        Remainder elements.\n\n    Returns\n    -------\n    n: integer\n        Factor of `π/2`.\n\n    Examples\n    --------\n    > var y = [ 0.0, 0.0 ];\n    > var n = base.rempio2( 128.0, y )\n    81\n    > var y1 = y[ 0 ]\n    ~0.765\n    > var y2 = y[ 1 ]\n    ~3.618e-17\n\n\n","base.repeat":"\nbase.repeat( str, n )\n    Repeats a string `n` times and returns the concatenated result.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of repetitions.\n\n    Returns\n    -------\n    out: string\n        Repeated string.\n\n    Examples\n    --------\n    > var out = base.repeat( 'a', 5 )\n    'aaaaa'\n    > out = base.repeat( '', 100 )\n    ''\n    > out = base.repeat( 'beep', 0 )\n    ''\n\n","base.replace":"\nbase.replace( str, search, newval )\n    Replaces search occurrences with a replacement string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: RegExp\n        Search expression.\n\n    newval: string|Function\n        Replacement value or function.\n\n    Returns\n    -------\n    out: string\n        String containing replacement(s).\n\n    Examples\n    --------\n    > function replacer( match, p1 ) { return '/'+p1+'/'; };\n    > var str = 'Oranges and lemons';\n    > var out = base.replace( str, /([^\\s]+)/gi, replacer )\n    '/Oranges/ /and/ /lemons/'\n\n    // Replace only first match:\n    > out = base.replace( 'beep', /e/, 'o' )\n    'boep'\n\n    See Also\n    --------\n    base.replaceAfter, base.replaceBefore, base.replaceAfterLast, base.replaceBeforeLast\n","base.replaceAfter":"\nbase.replaceAfter( str, search, replacement, fromIndex )\n    Replaces the substring after the first occurrence of a specified search\n    string.\n\n    If unable to find a search string, the function returns the input string\n    unchanged.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search string.\n\n    replacement: string\n        Replacement string.\n\n    fromIndex: integer\n        Starting index (inclusive). If less than zero, the starting index is\n        resolved relative to the last string character, with the last string\n        character corresponding to `fromIndex = -1`.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.replaceAfter( 'beep boop', ' ', 'foo', 0 )\n    'beep foo'\n    > out = base.replaceAfter( 'beep boop', 'o', 'foo', 0 )\n    'beep bofoo'\n    > out = base.replaceAfter( 'Hello World!', 'o', 'foo', 5 )\n    'Hello Wofoo'\n    > out = base.replaceAfter( 'beep boop beep baz', 'beep', 'foo', 5 )\n    'beep boop beepfoo'\n\n    See Also\n    --------\n    base.replaceAfterLast, base.replaceBefore, base.replaceBeforeLast\n","base.replaceAfterLast":"\nbase.replaceAfterLast( str, search, replacement, fromIndex )\n    Replaces the substring after the last occurrence of a specified search\n    string.\n\n    If unable to find a search string, the function returns the input string\n    unchanged.\n\n    The function scans an input string from the starting index to the beginning\n    of the string (i.e., backward).\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search string.\n\n    replacement: string\n        Replacement string.\n\n    fromIndex: integer\n        Starting index (inclusive). If less than zero, the starting index is\n        resolved relative to the last string character, with the last string\n        character corresponding to `fromIndex = -1`.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var str = 'beep boop';\n    > var out = base.replaceAfterLast( str, ' ', 'foo', str.length )\n    'beep foo'\n    > out = base.replaceAfterLast( str, 'o', 'foo', str.length )\n    'beep boofoo'\n    > out = base.replaceAfterLast( 'Hello World!', 'o', 'foo', 5 )\n    'Hellofoo'\n\n    See Also\n    --------\n    base.replaceAfter, base.replaceBeforeLast, base.replaceBefore\n","base.replaceBefore":"\nbase.replaceBefore( str, search, replacement, fromIndex )\n    Replaces the substring before the first occurrence of a specified search\n    string.\n\n    If unable to find a search string, the function returns the input string\n    unchanged.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search string.\n\n    replacement: string\n        Replacement string.\n\n    fromIndex: integer\n        Starting index (inclusive). If less than zero, the starting index is\n        resolved relative to the last string character, with the last string\n        character corresponding to `fromIndex = -1`.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.replaceBefore( 'beep boop', ' ', 'foo', 0 )\n    'foo boop'\n    > out = base.replaceBefore( 'beep boop', 'o', 'foo', 0 )\n    'foooop'\n\n    See Also\n    --------\n    base.replaceAfter, base.replaceBeforeLast, base.replaceAfterLast\n","base.replaceBeforeLast":"\nbase.replaceBeforeLast( str, search, replacement, fromIndex )\n    Replaces the substring before the last occurrence of a specified search\n    string.\n\n    If unable to find a search string, the function returns the input string\n    unchanged.\n\n    The function scans an input string from the starting index to the beginning\n    of the string (i.e., backward).\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search string.\n\n    replacement: string\n        Replacement string.\n\n    fromIndex: integer\n        Starting index (inclusive). If less than zero, the starting index is\n        resolved relative to the last string character, with the last string\n        character corresponding to `fromIndex = -1`.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var str = 'beep boop';\n    > var out = base.replaceBeforeLast( str, ' ', 'foo', str.length )\n    'foo boop'\n    > out = base.replaceBeforeLast( str, 'o', 'foo', str.length )\n    'fooop'\n    > out = base.replaceBeforeLast( 'Hello World!', 'o', 'foo', 5 )\n    'fooo World!'\n\n    See Also\n    --------\n    base.replaceAfterLast, base.replaceAfter, base.replaceBefore\n","base.reverse":"\nbase.reverse( str )\n    Reverses the UTF-16 code units of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.reverse( 'beep' )\n    'peeb'\n    > out = base.reverse( 'Boop' )\n    'pooB'\n    > out = base.reverse( 'foo bar' )\n    'rab oof'\n\n    See Also\n    --------\n    base.reverseCodePoints, base.reverseGraphemeClusters\n","base.reverseCodePoints":"\nbase.reverseCodePoints( str )\n    Reverses the Unicode code points of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.reverseCodePoints( 'beep' )\n    'peeb'\n    > out = base.reverseCodePoints( 'Boop' )\n    'pooB'\n    > out = base.reverseCodePoints( 'foo bar' )\n    'rab oof'\n\n    See Also\n    --------\n    base.reverseGraphemeClusters, base.reverse\n","base.reverseGraphemeClusters":"\nbase.reverseGraphemeClusters( str )\n    Reverses the grapheme clusters (i.e., user-perceived characters) of a\n    string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.reverseGraphemeClusters( 'beep' )\n    'peeb'\n    > out = base.reverseGraphemeClusters( 'Boop' )\n    'pooB'\n    > out = base.reverseGraphemeClusters( 'foo bar' )\n    'rab oof'\n\n    See Also\n    --------\n    base.reverseCodePoints, base.reverse\n","base.rightPad":"\nbase.rightPad( str, len, pad )\n    Right pads a string such that the padded string has a length of at least\n    `len`.\n\n    An output string is not guaranteed to have a length of exactly `len`, but to\n    have a length of at least `len`. To generate a padded string having a length\n    equal to `len`, post-process a padded string by trimming off excess\n    characters.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    len: integer\n        Minimum string length.\n\n    pad: string\n        String used to pad.\n\n    Returns\n    -------\n    out: string\n        Padded string.\n\n    Examples\n    --------\n    > var out = base.rightPad( 'a', 5, ' ' )\n    'a    '\n    > out = base.rightPad( 'beep', 10, 'b' )\n    'beepbbbbbb'\n    > out = base.rightPad( 'boop', 12, 'beep' )\n    'boopbeepbeep'\n\n    See Also\n    --------\n    base.leftPad\n","base.rightTrim":"\nbase.rightTrim( str )\n    Trims whitespace from the end of a string.\n\n    \"Whitespace\" is defined as the following characters:\n\n    - \\f\n    - \\n\n    - \\r\n    - \\t\n    - \\v\n    - \\u0020\n    - \\u00a0\n    - \\u1680\n    - \\u2000-\\u200a\n    - \\u2028\n    - \\u2029\n    - \\u202f\n    - \\u205f\n    - \\u3000\n    - \\ufeff\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Trimmed string.\n\n    Examples\n    --------\n    > var out = base.rightTrim( ' \\t\\t\\n  Beep \\r\\n\\t  ' )\n    ' \\t\\t\\n  Beep'\n\n    See Also\n    --------\n    base.leftTrim\n","base.risingFactorial":"\nbase.risingFactorial( x, n )\n    Computes the rising factorial of `x` and `n`.\n\n    If provided a non-integer for `n`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        First function parameter.\n\n    n: integer\n        Second function parameter.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var v = base.risingFactorial( 0.9, 5 )\n    ~94.766\n    > v = base.risingFactorial( -9.0, 3 )\n    -504.0\n    > v = base.risingFactorial( 0.0, 2 )\n    0.0\n    > v = base.risingFactorial( 3.0, -2 )\n    0.5\n\n    See Also\n    --------\n    base.fallingFactorial\n","base.rotl32":"\nbase.rotl32( x, shift )\n    Performs a bitwise rotation to the left.\n\n    If `shift = 0`, the function returns `x`.\n\n    If `shift >= 32`, the function only considers the five least significant\n    bits of `shift` (i.e., `shift % 32`).\n\n    Parameters\n    ----------\n    x: integer\n        Unsigned 32-bit integer.\n\n    shift: integer\n        Number of bits to shift.\n\n    Returns\n    -------\n    out: integer\n        Unsigned 32-bit integer.\n\n    Examples\n    --------\n    > var x = 2147483649;\n    > var bStr = base.toBinaryStringUint32( x )\n    '10000000000000000000000000000001'\n    > var y = base.rotl32( x, 10 )\n    1536\n    > bstr = base.toBinaryStringUint32( y )\n    '00000000000000000000011000000000'\n\n    See Also\n    --------\n    base.rotr32\n","base.rotr32":"\nbase.rotr32( x, shift )\n    Performs a bitwise rotation to the right.\n\n    If `shift = 0`, the function returns `x`.\n\n    If `shift >= 32`, the function only considers the five least significant\n    bits of `shift` (i.e., `shift % 32`).\n\n    Parameters\n    ----------\n    x: integer\n        Unsigned 32-bit integer.\n\n    shift: integer\n        Number of bits to shift.\n\n    Returns\n    -------\n    out: integer\n        Unsigned 32-bit integer.\n\n    Examples\n    --------\n    > var x = 1;\n    > var bStr = base.toBinaryStringUint32( x )\n    '00000000000000000000000000000001'\n    > var y = base.rotr32( x, 10 )\n    4194304\n    > bstr = base.toBinaryStringUint32( y )\n    '00000000010000000000000000000000'\n\n    See Also\n    --------\n    base.rotl32\n","base.round":"\nbase.round( x )\n    Rounds a numeric value to the nearest integer.\n\n    Ties are rounded toward positive infinity.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.round( 3.14 )\n    3.0\n    > y = base.round( -4.2 )\n    -4.0\n    > y = base.round( -4.6 )\n    -5.0\n    > y = base.round( 9.5 )\n    10.0\n    > y = base.round( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceil, base.floor, base.roundn, base.trunc\n","base.round2":"\nbase.round2( x )\n    Rounds a numeric value to the nearest power of two on a linear scale.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.round2( 3.14 )\n    4.0\n    > y = base.round2( -4.2 )\n    -4.0\n    > y = base.round2( -4.6 )\n    -4.0\n    > y = base.round2( 9.5 )\n    8.0\n    > y = base.round2( 13.0 )\n    16.0\n    > y = base.round2( -13.0 )\n    -16.0\n    > y = base.round2( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceil2, base.floor2, base.round, base.round10\n","base.round10":"\nbase.round10( x )\n    Rounds a numeric value to the nearest power of ten on a linear scale.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.round10( 3.14 )\n    1.0\n    > y = base.round10( -4.2 )\n    -1.0\n    > y = base.round10( -4.6 )\n    -1.0\n    > y = base.round10( 9.5 )\n    10.0\n    > y = base.round10( 13.0 )\n    10.0\n    > y = base.round10( -13.0 )\n    -10.0\n    > y = base.round10( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceil10, base.floor10, base.round, base.round2\n","base.roundb":"\nbase.roundb( x, n, b )\n    Rounds a numeric value to the nearest multiple of `b^n` on a linear scale.\n\n    Due to floating-point rounding error, rounding may not be exact.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Integer power.\n\n    b: integer\n        Base.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    // Round to 2 decimal places:\n    > var y = base.roundb( 3.14159, -2, 10 )\n    3.14\n\n    // If `n = 0` or `b = 1`, standard round behavior:\n    > y = base.roundb( 3.14159, 0, 2 )\n    3.0\n\n    // Round to nearest multiple of two:\n    > y = base.roundb( 5.0, 1, 2 )\n    6.0\n\n    See Also\n    --------\n    base.ceilb, base.floorb, base.round, base.roundn\n","base.roundn":"\nbase.roundn( x, n )\n    Rounds a numeric value to the nearest multiple of `10^n`.\n\n    When operating on floating-point numbers in bases other than `2`, rounding\n    to specified digits can be inexact.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Integer power of 10.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    // Round to 2 decimal places:\n    > var y = base.roundn( 3.14159, -2 )\n    3.14\n\n    // If `n = 0`, standard round behavior:\n    > y = base.roundn( 3.14159, 0 )\n    3.0\n\n    // Round to nearest thousand:\n    > y = base.roundn( 12368.0, 3 )\n    12000.0\n\n\n    See Also\n    --------\n    base.ceiln, base.floorn, base.round, base.roundb\n","base.roundsd":"\nbase.roundsd( x, n[, b] )\n    Rounds a numeric value to the nearest number with `n` significant figures.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Number of significant figures. Must be greater than 0.\n\n    b: integer (optional)\n        Base. Must be greater than 0. Default: 10.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.roundsd( 3.14159, 3 )\n    3.14\n    > y = base.roundsd( 3.14159, 1 )\n    3.0\n    > y = base.roundsd( 12368.0, 2 )\n    12000.0\n    > y = base.roundsd( 0.0313, 2, 2 )\n    0.03125\n\n    See Also\n    --------\n    base.ceilsd, base.floorsd, base.round, base.truncsd\n","base.rsqrt":"\nbase.rsqrt( x )\n    Computes the reciprocal square root of a double-precision floating-point\n    number.\n\n    For `x < 0`, the reciprocal square root is not defined.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Reciprocal square root.\n\n    Examples\n    --------\n    > var y = base.rsqrt( 4.0 )\n    0.5\n    > y = base.rsqrt( 100.0 )\n    0.1\n    > y = base.rsqrt( 0.0 )\n    Infinity\n    > y = base.rsqrt( Infinity )\n    0.0\n    > y = base.rsqrt( -4.0 )\n    NaN\n    > y = base.rsqrt( NaN )\n    NaN\n\n    See Also\n    --------\n    base.sqrt\n","base.rsqrtf":"\nbase.rsqrtf( x )\n    Computes the reciprocal square root of a single-precision floating-point\n    number.\n\n    For `x < 0`, the reciprocal square root is not defined.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Reciprocal square root.\n\n    Examples\n    --------\n    > var y = base.rsqrtf( 4.0 )\n    0.5\n    > y = base.rsqrtf( 0.0 )\n    Infinity\n    > y = base.rsqrtf( Infinity )\n    0.0\n    > y = base.rsqrtf( -4.0 )\n    NaN\n    > y = base.rsqrtf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.rsqrt, base.sqrtf\n","base.sargs2multislice":"\nbase.sargs2multislice( str )\n    Creates a MultiSlice object from a comma-separated list of string-serialized\n    MultiSlice constructor arguments.\n\n    The function returns `null` if provided an invalid string.\n\n    Parameters\n    ----------\n    str: string\n        Input string containing constructor arguments.\n\n    Returns\n    -------\n    s: MultiSlice|null\n        MultiSlice instance (or null).\n\n    Examples\n    --------\n    > var s = new base.sargs2multislice( 'null,null,null' );\n    > s.data\n    [ null, null, null ]\n    > s = new base.sargs2multislice( '10,Slice(0,10,1),null' );\n    > s.data\n    [ 10, <Slice>, null ]\n\n    See Also\n    --------\n    base.args2multislice, base.seq2multislice\n","base.scalar2ndarray":"\nbase.scalar2ndarray( value, dtype, order )\n    Returns a zero-dimensional ndarray containing a provided scalar value.\n\n    If `value` is a number and `dtype` is a complex number data type, the\n    function returns a zero-dimensional ndarray containing a complex number\n    whose real component equals the provided scalar value and whose imaginary\n    component is zero.\n\n    Parameters\n    ----------\n    value: any\n        Scalar value.\n\n    dtype: string\n        Data type.\n\n    order: string\n        Memory layout (either 'row-major' or 'column-major').\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var x = base.scalar2ndarray( 1.0, 'float64', 'row-major' )\n    <ndarray>\n    > var sh = x.shape\n    []\n    > var dt = x.dtype\n    'float64'\n    > var v = x.get()\n    1.0\n\n    See Also\n    --------\n    array, base.ndarray, ndarray\n","base.secd":"\nbase.secd( x )\n    Computes the secant of an angle measured in degrees.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in degrees).\n\n    Returns\n    -------\n    y: number\n        Secant.\n\n    Examples\n    --------\n    > var y = base.secd( 1.0 )\n    ~1.0\n    > y = base.secd( PI )\n    ~1.0\n    > y = base.secd( -PI )\n    ~1.0\n    > y = base.secd( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cosd, base.cos\n","base.seq2multislice":"\nbase.seq2multislice( str, shape, strict )\n    Converts a multidimensional subsequence string to a MultiSlice object.\n\n    A multidimensional subsequence string is a comma-separated list of single-\n    dimension indexing expressions (i.e., integers and/or subsequence strings).\n\n    For example, the following\n\n      2\n      :\n      2:\n      :10\n      2:10\n      ::-1\n      10:2:-1\n      :2:\n      2:10:\n      2::2\n      :10:2\n      :, :, :\n      1, 2, 3\n      0:10, 1:20:2, ::-1\n      ...\n      :, ..., 2\n\n    are all valid multidimensional subsequence strings.\n\n    Providing a single nonnegative integer `i` as a single-dimension index\n    indexes the same elements as the subsequence `i:i+1`.\n\n    Providing a single negative integer `i` as a single-dimension index indexes\n    the same elements as the subsequence `n+i:n+i+i`, where `n` is the dimension\n    size.\n\n    While integers index the same elements as equivalent subsequences, providing\n    an integer as a single-dimension index indicates to reduce the number of\n    dimensions by one (e.g., if the provided shape corresponds to an array\n    having rank 2, then rank(A)-1 == rank(A['0,:'])).\n\n    In contrast, providing a subsequence indicates to retain a respective\n    dimension (e.g., if the provided shape corresponds to an array having rank\n    2, then rank(A) == rank(A[':,:'])).\n\n    A multidimensional subsequence string can only contain **one** ellipsis\n    ('...') operator. An ellipsis indicates to apply ':' to each dimension\n    necessary to index all dimensions (e.g., if A has rank 4, A['1:,...,2:5']\n    equals A['1:,:,:,2:5']).\n\n    Except in the case of providing a single ellipsis, the number of single-\n    dimension indexing expressions must equal the number of dimensions in the\n    input shape.\n\n    The function returns an error object if provided an invalid subsequence\n    string.\n\n    In strict mode, the function returns an error object if a single-dimension\n    index expression which exceeds index bounds.\n\n    A returned error object is a plain object having the following properties:\n\n    - code: error code.\n\n    A returned error object may have one of the following error codes:\n\n    - ERR_SLICE_INVALID_SUBSEQUENCE: a subsequence string is invalid.\n    - ERR_SLICE_INVALID_INCREMENT: a subsequence string must have a non-zero\n      increment.\n    - ERR_SLICE_OUT_OF_BOUNDS: a subsequence string resolves to a slice\n      exceeding index bounds.\n    - ERR_SLICE_TOO_MANY_DIMENSIONS: a subsequence string has more dimensions\n      than the provided shape.\n    - ERR_SLICE_INSUFFICIENT_DIMENSIONS: a subsequence string has too few\n      dimensions.\n    - ERR_SLICE_INVALID_ELLIPSIS: a subsequence string must only contain at most\n      one ellipsis.\n\n    Parameters\n    ----------\n    str: string\n        Subsequence string.\n\n    shape: Array<integer>\n        Maximum allowed slice shape.\n\n    strict: boolean\n        Boolean indicating whether to enforce strict bounds checking.\n\n    Returns\n    -------\n    s: MultiSlice|Object\n        MultiSlice instance or an error object.\n\n    Examples\n    --------\n    > var s = new base.seq2multislice( '1:10', [ 10 ], false );\n    > s.data\n    [ <Slice> ]\n    > s = new base.seq2multislice( '4,2:5:2,:', [ 10, 10, 10 ], false );\n    > s.data\n    [ 4, <Slice>, <Slice> ]\n\n    See Also\n    --------\n    base.seq2slice, base.sargs2multislice\n","base.seq2slice":"\nbase.seq2slice( str, len, strict )\n    Converts a subsequence string to a Slice object.\n\n    A subsequence string has the following format:\n\n      <start>:<stop>:<increment>\n\n    If an increment is not specified, the default increment is one. An increment\n    of zero is not allowed.\n\n    The start index is inclusive.\n\n    The stop index is exclusive.\n\n    Both start and stop indices are optional. If not provided, the start and\n    stop indices default to index extremes. Which extremes correspond to which\n    index depends on whether the increment is positive or negative.\n\n    Both start and stop indices can be negative; in which case, the\n    corresponding index is resolved by subtracting the respective value from the\n    provided length.\n\n    Both start and stop indices can use the 'end' keyword (e.g., 'end-2::2',\n    'end-3:', etc), which supports basic subtraction and division.\n\n    The 'end' keyword resolves to the provided length. Thus, ':-1' is equivalent\n    to ':end-1', ':-2' is equivalent to ':end-2', and so on and so forth. The\n    exception is when performing a division operation when the increment is less\n    than zero; in which case, 'end' is equal to 'len-1' in order to preserve\n    user expectations when 'end/d' equals a whole number and slicing from right-\n    to-left. The result from a division operation is rounded down to the nearest\n    integer value.\n\n    In non-strict mode, the resolved slice start is clamped to the slice index\n    bounds [0, len).\n\n    In non-strict mode, Tte resolved slice end is upper bound clamped to the\n    provided length (i.e., one greater than the last possible index).\n\n    When the increment is negative, the resolved slice end value may be `null`,\n    thus indicating that a non-empty slice should include the first index.\n\n    The function ensures that results satisfy the convention that ':n' combined\n    with 'n:' is equivalent to ':' (i.e., selecting all elements).\n\n    When the provided length is zero, the function always returns a slice object\n    equivalent to '0:0:<increment>'.\n\n    The function returns an error object if provided an invalid subsequence\n    string.\n\n    In strict mode, the function returns an error object if provided a\n    subsequence string which exceeds index bounds.\n\n    A returned error object is a plain object having the following properties:\n\n    - code: error code.\n\n    A returned error object may have one of the following error codes:\n\n    - ERR_SLICE_INVALID_SUBSEQUENCE: a subsequence string is invalid.\n    - ERR_SLICE_INVALID_INCREMENT: a subsequence string must have a non-zero\n      increment.\n    - ERR_SLICE_OUT_OF_BOUNDS: a subsequence string resolves to a slice\n      exceeding index bounds.\n\n    Parameters\n    ----------\n    str: string\n        Subsequence string.\n\n    len: integer\n        Maximum number of elements allowed in the slice.\n\n    strict: boolean\n        Boolean indicating whether to enforce strict bounds checking.\n\n    Returns\n    -------\n    s: Slice|Object\n        Slice instance or an error object.\n\n    Examples\n    --------\n    > var s = new base.seq2slice( '1:10', 10, false );\n    > s.start\n    1\n    > s.stop\n    10\n    > s.step\n    1\n    > s = new base.seq2slice( '2:5:2', 10, false );\n    > s.start\n    2\n    > s.stop\n    5\n    > s.step\n    2\n\n    See Also\n    --------\n    base.seq2multislice, base.slice2seq\n","base.setHighWord":"\nbase.setHighWord( x, high )\n    Sets the more significant 32 bits of a double-precision floating-point\n    number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    high: integer\n        Unsigned 32-bit integer to replace the higher order word of `x`.\n\n    Returns\n    -------\n    out: number\n        Double having the same lower order word as `x`.\n\n    Examples\n    --------\n    // Set the higher order bits of `+infinity` to return `1`:\n    > var high = 1072693248 >>> 0;\n    > var y = base.setHighWord( PINF, high )\n    1.0\n\n    See Also\n    --------\n    base.getHighWord, base.setLowWord\n","base.setLowWord":"\nbase.setLowWord( x, low )\n    Sets the less significant 32 bits of a double-precision floating-point\n    number.\n\n    Setting the lower order bits of `NaN` or positive or negative infinity will\n    return `NaN`, as `NaN` is defined as a double whose exponent bit sequence is\n    all ones and whose fraction can be any bit sequence except all zeros.\n    Positive and negative infinity are defined as doubles with an exponent bit\n    sequence equal to all ones and a fraction equal to all zeros. Hence,\n    changing the less significant bits of positive and negative infinity\n    converts each value to `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    low: integer\n        Unsigned 32-bit integer to replace the lower order word of `x`.\n\n    Returns\n    -------\n    out: number\n        Double having the same higher order word as `x`.\n\n    Examples\n    --------\n    > var low = 5 >>> 0;\n    > var x = 3.14e201;\n    > var y = base.setLowWord( x, low )\n    3.139998651394392e+201\n\n    // Special cases:\n    > var low = 12345678;\n    > var y = base.setLowWord( PINF, low )\n    NaN\n    > y = base.setLowWord( NINF, low )\n    NaN\n    > y = base.setLowWord( NaN, low )\n    NaN\n\n    See Also\n    --------\n    base.getLowWord, base.setHighWord\n","base.sici":"\nbase.sici( x )\n    Computes the sine and cosine integrals.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    out: Array<number>\n        Sine and cosine integrals.\n\n    Examples\n    --------\n    > var y = base.sici( 3.0 )\n    [ ~1.849, ~0.12 ]\n    > y = base.sici( 0.0 )\n    [ 0.0, -Infinity ]\n    > y = base.sici( -9.0 )\n    [ ~-1.665, ~0.055 ]\n    > y = base.sici( NaN )\n    [ NaN, NaN ]\n\n\nbase.sici.assign( x, out, stride, offset )\n    Computes the sine and cosine integrals and assigns results to a provided\n    output array.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Sine and cosine integrals.\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var y = base.sici.assign( 3.0, out, 1, 0 )\n    <Float64Array>[ ~1.849, ~0.12 ]\n    > var bool = ( y === out )\n    true\n","base.sici.assign":"\nbase.sici.assign( x, out, stride, offset )\n    Computes the sine and cosine integrals and assigns results to a provided\n    output array.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Sine and cosine integrals.\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var y = base.sici.assign( 3.0, out, 1, 0 )\n    <Float64Array>[ ~1.849, ~0.12 ]\n    > var bool = ( y === out )\n    true","base.signbit":"\nbase.signbit( x )\n    Returns a boolean indicating if the sign bit is on (true) or off (false).\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if sign bit is on or off.\n\n    Examples\n    --------\n    > var bool = base.signbit( 4.0 )\n    false\n    > bool = base.signbit( -9.14e-34 )\n    true\n    > bool = base.signbit( 0.0 )\n    false\n    > bool = base.signbit( -0.0 )\n    true\n\n    See Also\n    --------\n    base.signbitf\n","base.signbitf":"\nbase.signbitf( x )\n    Returns a boolean indicating if the sign bit is on (true) or off (false).\n\n    Parameters\n    ----------\n    x: float\n        Single-precision floating-point number.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if sign bit is on or off.\n\n    Examples\n    --------\n    > var bool = base.signbitf( base.float64ToFloat32( 4.0 ) )\n    false\n    > bool = base.signbitf( base.float64ToFloat32( -9.14e-34 ) )\n    true\n    > bool = base.signbitf( 0.0 )\n    false\n    > bool = base.signbitf( -0.0 )\n    true\n\n    See Also\n    --------\n    base.signbit\n","base.significandf":"\nbase.significandf( x )\n    Returns an integer corresponding to the significand of a single-precision\n    floating-point number.\n\n    Parameters\n    ----------\n    x: float\n        Single-precision floating-point number.\n\n    Returns\n    -------\n    out: integer\n        Significand.\n\n    Examples\n    --------\n    > var s = base.significandf( base.float64ToFloat32( 3.14e34 ) )\n    4293751\n    > s = base.significandf( base.float64ToFloat32( 3.14e-34 ) )\n    5288021\n    > s = base.significandf( base.float64ToFloat32( -3.14 ) )\n    4781507\n    > s = base.significandf( 0.0 )\n    0\n    > s = base.significandf( NaN )\n    4194304\n\n","base.signum":"\nbase.signum( x )\n    Evaluates the signum function for a double-precision floating-point number.\n\n    Value | Sign\n    ----- | -----\n    x > 0 |    +1\n    x < 0 |    -1\n        0 |     0\n       -0 |    -0\n      NaN |   NaN\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    sign: number\n        Function value.\n\n    Examples\n    --------\n    > var sign = base.signum( -5.0 )\n    -1.0\n    > sign = base.signum( 5.0 )\n    1.0\n    > sign = base.signum( -0.0 )\n    -0.0\n    > sign = base.signum( 0.0 )\n    0.0\n    > sign = base.signum( NaN )\n    NaN\n\n","base.signumf":"\nbase.signumf( x )\n    Evaluates the signum function for a single-precision floating-point number.\n\n    Value | Sign\n    ----- | -----\n    x > 0 |    +1\n    x < 0 |    -1\n        0 |     0\n       -0 |    -0\n      NaN |   NaN\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    sign: number\n        Function value.\n\n    Examples\n    --------\n    > var sign = base.signumf( -5.0 )\n    -1.0\n    > sign = base.signumf( 5.0 )\n    1.0\n    > sign = base.signumf( -0.0 )\n    -0.0\n    > sign = base.signumf( 0.0 )\n    0.0\n    > sign = base.signumf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.signum\n","base.sin":"\nbase.sin( x )\n    Computes the sine of a number.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Sine.\n\n    Examples\n    --------\n    > var y = base.sin( 0.0 )\n    ~0.0\n    > y = base.sin( PI/2.0 )\n    ~1.0\n    > y = base.sin( -PI/6.0 )\n    ~-0.5\n    > y = base.sin( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cos, base.sinpi, base.tan\n","base.sinc":"\nbase.sinc( x )\n    Computes the normalized cardinal sine of a number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Cardinal sine.\n\n    Examples\n    --------\n    > var y = base.sinc( 0.5 )\n    ~0.637\n    > y = base.sinc( -1.2 )\n    ~-0.156\n    > y = base.sinc( 0.0 )\n    1.0\n    > y = base.sinc( NaN )\n    NaN\n\n    See Also\n    --------\n    base.sin\n","base.sincos":"\nbase.sincos( x )\n    Simultaneously computes the sine and cosine of a number.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: Array<number>\n        Sine and cosine.\n\n    Examples\n    --------\n    > var y = base.sincos( 0.0 )\n    [ ~0.0, ~1.0 ]\n    > y = base.sincos( PI/2.0 )\n    [ ~1.0, ~0.0 ]\n    > y = base.sincos( -PI/6.0 )\n    [ ~-0.5, ~0.866 ]\n    > y = base.sincos( NaN )\n    [ NaN, NaN ]\n\n\nbase.sincos( x, out, stride, offset )\n    Simultaneously computes the sine and cosine of a number and assigns\n    results to a provided output array.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Sine and cosine.\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var v = base.sincos.assign( 0.0, out, 1, 0 )\n    <Float64Array>[ ~0.0, ~1.0 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.cos, base.sin, base.sincospi","base.sincospi":"\nbase.sincospi( x )\n    Simultaneously computes the sine and cosine of a number times π.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: Array<number>\n        Two-element array containing sin(πx) and cos(πx).\n\n    Examples\n    --------\n    > var y = base.sincospi( 0.0 )\n    [ 0.0, 1.0 ]\n    > y = base.sincospi( 0.5 )\n    [ 1.0, 0.0 ]\n    > y = base.sincospi( 0.1 )\n    [ ~0.309, ~0.951 ]\n    > y = base.sincospi( NaN )\n    [ NaN, NaN ]\n\n\nbase.sincospi.assign( x, out, stride, offset )\n    Simultaneously computes the sine and cosine of a number times π and\n    assigns results to a provided output array.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Two-element array containing sin(πx) and cos(πx).\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var v = base.sincospi.assign( 0.0, out, 1, 0 )\n    <Float64Array>[ 0.0, 1.0 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.cospi, base.sincos, base.sinpi","base.sincospi.assign":"\nbase.sincospi.assign( x, out, stride, offset )\n    Simultaneously computes the sine and cosine of a number times π and\n    assigns results to a provided output array.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Two-element array containing sin(πx) and cos(πx).\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var v = base.sincospi.assign( 0.0, out, 1, 0 )\n    <Float64Array>[ 0.0, 1.0 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.cospi, base.sincos, base.sinpi","base.sinh":"\nbase.sinh( x )\n    Computes the hyperbolic sine of a double-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Hyperbolic sine.\n\n    Examples\n    --------\n    > var y = base.sinh( 0.0 )\n    0.0\n    > y = base.sinh( 2.0 )\n    ~3.627\n    > y = base.sinh( -2.0 )\n    ~-3.627\n    > y = base.sinh( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cosh, base.sin, base.tanh\n","base.sinpi":"\nbase.sinpi( x )\n    Computes the value of `sin(πx)`.\n\n    The function computes `sin(πx)` more accurately than the obvious approach,\n    especially for large `x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.sinpi( 0.0 )\n    0.0\n    > y = base.sinpi( 0.5 )\n    1.0\n    > y = base.sinpi( 0.9 )\n    ~0.309\n    > y = base.sinpi( NaN )\n    NaN\n\n    See Also\n    --------\n    base.sin\n","base.slice2seq":"\nbase.slice2seq( slice )\n    Converts a Slice object to a subsequence string.\n\n    Parameters\n    ----------\n    slice: Slice\n        Input slice.\n\n    Returns\n    -------\n    out: string\n        Subsequence string.\n\n    Examples\n    --------\n    > var out = base.slice2seq( new Slice( 1, 10, 1 ) )\n    '1:10:1'\n    > out = base.slice2seq( new Slice( null, 10 ) )\n    ':10'\n\n    See Also\n    --------\n    base.seq2slice\n","base.sliceLength":"\nbase.sliceLength( slice )\n    Returns the number of elements in a normalized slice.\n\n    Parameters\n    ----------\n    slice: Slice\n        Input normalized slice object.\n\n    Returns\n    -------\n    len: integer\n        Number of elements.\n\n    Examples\n    --------\n    > var s = new Slice( 1, 10, 1 );\n    > base.sliceLength( s )\n    9\n\n    See Also\n    --------\n    base.sliceNonReducedDimensions, base.sliceReducedDimensions, base.sliceShape\n","base.sliceNonReducedDimensions":"\nbase.sliceNonReducedDimensions( slice )\n    Returns a list of non-reduced dimensions in an un-normalized multi-slice.\n\n    Parameters\n    ----------\n    slice: MultiSlice\n        Input slice object.\n\n    Returns\n    -------\n    out: Array<integer>\n        Dimension indices.\n\n    Examples\n    --------\n    > var s = new MultiSlice( 1, 3, null );\n    > var out = base.sliceNonReducedDimensions( s )\n    [ 2 ]\n\n    See Also\n    --------\n    base.sliceLength, base.sliceReducedDimensions, base.sliceShape\n","base.sliceReducedDimensions":"\nbase.sliceReducedDimensions( slice )\n    Returns a list of reduced dimensions in an un-normalized multi-slice.\n\n    Parameters\n    ----------\n    slice: MultiSlice\n        Input slice object.\n\n    Returns\n    -------\n    out: Array<integer>\n        Dimension indices.\n\n    Examples\n    --------\n    > var s = new MultiSlice( 1, 3, null );\n    > var out = base.sliceReducedDimensions( s )\n    [ 0, 1 ]\n\n    See Also\n    --------\n    base.sliceLength, base.sliceNonReducedDimensions, base.sliceShape\n","base.sliceShape":"\nbase.sliceShape( slice )\n    Returns the shape of a normalized multi-slice.\n\n    Parameters\n    ----------\n    slice: MultiSlice\n        Input normalized multi-slice object.\n\n    Returns\n    -------\n    sh: Array<integer>\n        Slice shape.\n\n    Examples\n    --------\n    > var s = new Slice( 1, 10, 1 );\n    > var ms = new MultiSlice( s, s );\n    > base.sliceShape( ms )\n    [ 9, 9 ]\n\n    See Also\n    --------\n    base.sliceLength, base.sliceNonReducedDimensions, base.sliceReducedDimensions\n","base.snakecase":"\nbase.snakecase( str )\n    Converts a string to snake case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Snake-cased string.\n\n    Examples\n    --------\n    > var out = base.snakecase( 'Hello World!' )\n    'hello_world'\n    > out = base.snakecase( 'I am a tiny little teapot' )\n    'i_am_a_tiny_little_teapot'\n\n    See Also\n    --------\n    base.camelcase, base.lowercase, base.stickycase, base.uppercase","base.spence":"\nbase.spence( x )\n    Evaluates Spence's function, which is also known as the dilogarithm.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.spence( 3.0 )\n    ~-1.437\n    > y = base.spence( 0.0 )\n    ~1.645\n    > y = base.spence( -9.0 )\n    NaN\n    > y = base.spence( NaN )\n    NaN\n\n","base.sqrt":"\nbase.sqrt( x )\n    Computes the principal square root of a double-precision floating-point\n    number.\n\n    For `x < 0`, the principal square root is not defined.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Principal square root.\n\n    Examples\n    --------\n    > var y = base.sqrt( 4.0 )\n    2.0\n    > y = base.sqrt( 9.0 )\n    3.0\n    > y = base.sqrt( 0.0 )\n    0.0\n    > y = base.sqrt( -4.0 )\n    NaN\n    > y = base.sqrt( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cbrt, base.rsqrt\n","base.sqrt1pm1":"\nbase.sqrt1pm1( x )\n    Computes the principal square root of `1+x` minus one.\n\n    This function is more accurate than the obvious approach for small `x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Square root of `1+x` minus one.\n\n    Examples\n    --------\n    > var y = base.sqrt1pm1( 3.0 )\n    1.0\n    > y = base.sqrt1pm1( 0.5 )\n    ~0.225\n    > y = base.sqrt1pm1( 0.02 )\n    ~0.01\n    > y = base.sqrt1pm1( -0.5 )\n    ~-0.293\n    > y = base.sqrt1pm1( -1.1 )\n    NaN\n    > y = base.sqrt1pm1( NaN )\n    NaN\n\n    See Also\n    --------\n    base.sqrt\n","base.sqrtf":"\nbase.sqrtf( x )\n    Computes the principal square root of a single-precision floating-point\n    number.\n\n    For `x < 0`, the principal square root is not defined.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Principal square root.\n\n    Examples\n    --------\n    > var y = base.sqrtf( 4.0 )\n    2.0\n    > y = base.sqrtf( 9.0 )\n    3.0\n    > y = base.sqrtf( 0.0 )\n    0.0\n    > y = base.sqrtf( -4.0 )\n    NaN\n    > y = base.sqrtf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cbrtf, base.rsqrtf, base.sqrt\n","base.sqrtpi":"\nbase.sqrtpi( x )\n    Computes the principal square root of the product of π and a positive\n    double-precision floating-point number.\n\n    For `x < 0`, the square root is not defined.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Principal square root of the product of π and the input value.\n\n    Examples\n    --------\n    > var y = base.sqrtpi( 4.0 )\n    ~3.5449\n    > y = base.sqrtpi( 10.0 )\n    ~5.60499\n    > y = base.sqrtpi( 0.0 )\n    0.0\n    > y = base.sqrtpi( -4.0 )\n    NaN\n    > y = base.sqrtpi( NaN )\n    NaN\n\n    See Also\n    --------\n    base.sqrt","base.startcase":"\nbase.startcase( str )\n    Capitalizes the first letter of each word in an input string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        String containing words where each first letter is capitalized.\n\n    Examples\n    --------\n    > var out = base.startcase( 'beep boop' )\n    'Beep Boop'\n\n    See Also\n    --------\n    base.capitalize, base.lowercase, base.uppercase\n","base.startsWith":"\nbase.startsWith( str, search, position )\n    Tests if a string starts with the characters of another string.\n\n    If provided an empty search string, the function always returns `true`.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search string.\n\n    position: integer\n        Position at which to start searching for `search`. If less than `0`, the\n        start position is determined relative to the end of the input string.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a string starts with the characters of\n        another string.\n\n    Examples\n    --------\n    > var bool = base.startsWith( 'Beep', 'Be', 0 )\n    true\n    > bool = base.startsWith( 'Beep', 'ep', 0 )\n    false\n    > bool = base.startsWith( 'Beep', 'ee', 1 )\n    true\n    > bool = base.startsWith( 'Beep', 'ee', -3 )\n    true\n    > bool = base.startsWith( 'Beep', '', 0 )\n    true\n\n    See Also\n    --------\n    base.endsWith\n","base.stickycase":"\nbase.stickycase( str[, p] )\n    Converts a string to sticky case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n \n    p: number\n        Probability of capitalization.\n\n    Returns\n    -------\n    out: string\n        Sticky-cased string.\n\n    Examples\n    --------\n    > var out = base.stickycase( 'Hello World!' )\n    <string>\n\n    > out = base.stickycase( 'I am a tiny little teapot' )\n    <string>\n    See Also\n    --------\n    base.camelcase, base.lowercase, base.snakecase, base.uppercase\n","base.strided.binary":"\nbase.strided.binary( arrays, shape, strides, fcn )\n    Applies a binary callback to strided input array elements and assigns\n    results to elements in a strided output array.\n\n    The `shape` and `strides` parameters determine which elements in the strided\n    input and output arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing two strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    fcn: Function\n        Binary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1 ];\n    > function f( x, y ) { return x + y; };\n    > base.strided.binary( [ x, y, z ], shape, strides, f );\n    > z\n    <Float64Array>[ 2.0, 4.0, 6.0, 8.0 ]\n\n\nbase.strided.binary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a binary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing two strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Binary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1 ];\n    > var offsets = [ 0, 0, 0 ];\n    > function f( x, y ) { return x + y; };\n    > base.strided.binary.ndarray( [ x, y, z ], shape, strides, offsets, f );\n    > z\n    <Float64Array>[ 2.0, 4.0, 6.0, 8.0 ]\n\n    See Also\n    --------\n    base.strided.dmap2, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap2, base.strided.ternary, base.strided.unary\n","base.strided.binary.ndarray":"\nbase.strided.binary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a binary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing two strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Binary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1 ];\n    > var offsets = [ 0, 0, 0 ];\n    > function f( x, y ) { return x + y; };\n    > base.strided.binary.ndarray( [ x, y, z ], shape, strides, offsets, f );\n    > z\n    <Float64Array>[ 2.0, 4.0, 6.0, 8.0 ]\n\n    See Also\n    --------\n    base.strided.dmap2, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap2, base.strided.ternary, base.strided.unary","base.strided.binaryDtypeSignatures":"\nbase.strided.binaryDtypeSignatures( dtypes1, dtypes2, dtypes3[, options] )\n    Generates a list of binary interface signatures from strided array data\n    types.\n\n    The function returns a strided array having a stride length of `3` (i.e.,\n    every `3` elements define a binary interface signature).\n\n    For each signature (i.e., set of three consecutive non-overlapping strided\n    array elements), the first two elements are the input data types and the\n    third element is the return data type.\n\n    All signatures follow type promotion rules.\n\n    Parameters\n    ----------\n    dtypes1: ArrayLike<any>\n        List of supported data types for the first input argument.\n\n    dtypes2: ArrayLike<any>\n        List of supported data types for the second input argument.\n\n    dtypes3: ArrayLike<any>\n        List of supported data types for the output value.\n\n    options: Object (optional)\n        Options.\n\n    options.enums: boolean (optional)\n        Boolean flag indicating whether to return signatures as a list of data\n        type enumeration constants. Default: false.\n\n    Returns\n    -------\n    out: Array\n        Strided array containing binary interface signatures.\n\n    Examples\n    --------\n    > var dt = strided.dataTypes();\n    > var out = base.strided.binaryDtypeSignatures( dt, dt, dt )\n    [...]\n\n    See Also\n    --------\n    base.strided.binarySignatureCallbacks\n","base.strided.binarySignatureCallbacks":"\nbase.strided.binarySignatureCallbacks( table, signatures )\n    Assigns callbacks to binary interfaces according to type promotion rules.\n\n    Parameters\n    ----------\n    table: Object\n        Object mapping callbacks to data types.\n\n    table.default: Function\n        Default callback.\n\n    table.complex64: Function\n        Callback to be invoked when input arrays promote to single-precision\n        complex floating-point numbers.\n\n    table.complex128: Function\n        Callback to be invoked when input arrays promote to double precision\n        complex floating-point numbers.\n\n    signatures: ArrayLike<any>\n        Strided array containing binary interface signatures.\n\n    Returns\n    -------\n    out: Array<Function>\n        List of callbacks, one per signature.\n\n    Examples\n    --------\n    > var dt = strided.dataTypes();\n    > var sigs = base.strided.binaryDtypeSignatures( dt, dt, dt );\n    > var t = {\n    ...     'default': base.add,\n    ...     'complex64': base.caddf,\n    ...     'complex128': base.cadd\n    ... };\n    > var out = base.strided.binarySignatureCallbacks( t, sigs )\n    [...]\n\n    See Also\n    --------\n    base.strided.binaryDtypeSignatures\n","base.strided.ccopy":"\nbase.strided.ccopy( N, x, strideX, y, strideY )\n    Copies values from one complex single-precision floating-point vector to\n    another complex single-precision floating-point vector.\n\n    The `N` and stride parameters determine how values from `x` are copied into\n    `y`.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Complex64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Complex64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n    > base.strided.ccopy( x.length, x, 1, y, 1 );\n    > var z = y.get( 0 );\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    2.0\n\n    // Advanced indexing:\n    > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n    > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.ccopy( 2, x, -2, y, 1 );\n    > z = y.get( 0 );\n    > re = realf( z )\n    5.0\n    > im = imagf( z )\n    6.0\n\n    // Using typed array views:\n    > var x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n    > var y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.ccopy( 2, x1, -2, y1, 1 );\n    > z = y0.get( 2 );\n    > re = realf( z )\n    7.0\n    > im = imagf( z )\n    8.0\n\n\nbase.strided.ccopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Copies values from one complex single-precision floating-point vector to\n    another complex single-precision floating-point vector using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Complex64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Complex64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n    > base.strided.ccopy.ndarray( x.length, x, 1, 0, y, 1, 0 );\n    > var z = y.get( 0 );\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    2.0\n\n    // Advanced indexing:\n    > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n    > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.ccopy.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\n    > z = y.get( y.length-1 );\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    4.0\n\n    See Also\n    --------\n    base.strided.cswap\n","base.strided.ccopy.ndarray":"\nbase.strided.ccopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Copies values from one complex single-precision floating-point vector to\n    another complex single-precision floating-point vector using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Complex64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Complex64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n    > base.strided.ccopy.ndarray( x.length, x, 1, 0, y, 1, 0 );\n    > var z = y.get( 0 );\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    2.0\n\n    // Advanced indexing:\n    > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n    > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.ccopy.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\n    > z = y.get( y.length-1 );\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    4.0\n\n    See Also\n    --------\n    base.strided.cswap","base.strided.cmap":"\nbase.strided.cmap( N, x, strideX, y, strideY, fcn )\n    Applies a unary function to a single-precision complex floating-point\n    strided input array and assigns results to a single-precision complex\n    floating-point strided output array.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Complex64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Complex64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n    > var x = new Complex64Array( xbuf );\n    > var y = new Complex64Array( x.length );\n    > base.strided.cmap( x.length, x, 1, y, 1, base.cidentityf );\n    > var v = y.get( 0 )\n    <Complex64>\n    > var re = real( v )\n    1.0\n    > var im = imag( v )\n    2.0\n\n    // Using `N` and stride parameters:\n    > y = new Complex64Array( x.length );\n    > base.strided.cmap( 2, x, 2, y, -1, base.cidentityf );\n    > v = y.get( 0 )\n    <Complex64>\n    > re = real( v )\n    5.0\n    > im = imag( v )\n    6.0\n\n    // Using view offsets:\n    > var x0 = new Complex64Array( xbuf );\n    > var y0 = new Complex64Array( x0.length );\n    > var x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.cmap( 2, x1, -2, y1, 1, base.cidentityf );\n    > v = y1.get( 0 )\n    <Complex64>\n    > re = real( v )\n    7.0\n    > im = imag( v )\n    8.0\n\n\nbase.strided.cmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n    Applies a unary function to a single-precision complex floating-point\n    strided input array and assigns results to a single-precision complex\n    floating-point strided output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Complex64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Complex64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n    > var x = new Complex64Array( xbuf );\n    > var y = new Complex64Array( x.length );\n    > base.strided.cmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentityf );\n    > var v = y.get( 0 )\n    <Complex64>\n    > var re = real( v )\n    1.0\n    > var im = imag( v )\n    2.0\n\n    // Advanced indexing:\n    > x = new Complex64Array( xbuf );\n    > y = new Complex64Array( x.length );\n    > base.strided.cmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentityf );\n    > v = y.get( y.length-1 )\n    <Complex64>\n    > re = real( v )\n    3.0\n    > im = imag( v )\n    4.0\n\n    See Also\n    --------\n    base.strided.zmap, base.strided.unary\n","base.strided.cmap.ndarray":"\nbase.strided.cmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n    Applies a unary function to a single-precision complex floating-point\n    strided input array and assigns results to a single-precision complex\n    floating-point strided output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Complex64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Complex64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n    > var x = new Complex64Array( xbuf );\n    > var y = new Complex64Array( x.length );\n    > base.strided.cmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentityf );\n    > var v = y.get( 0 )\n    <Complex64>\n    > var re = real( v )\n    1.0\n    > var im = imag( v )\n    2.0\n\n    // Advanced indexing:\n    > x = new Complex64Array( xbuf );\n    > y = new Complex64Array( x.length );\n    > base.strided.cmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentityf );\n    > v = y.get( y.length-1 )\n    <Complex64>\n    > re = real( v )\n    3.0\n    > im = imag( v )\n    4.0\n\n    See Also\n    --------\n    base.strided.zmap, base.strided.unary","base.strided.cswap":"\nbase.strided.cswap( N, x, strideX, y, strideY )\n    Interchanges two complex single-precision floating-point vectors.\n\n    The `N` and stride parameters determine how values from `x` are swapped with\n    values from `y`.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the vectors are unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Complex64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Complex64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n    > base.strided.cswap( x.length, x, 1, y, 1 );\n    > var z = y.get( 0 );\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    2.0\n    > z = x.get( 0 );\n    > re = realf( z )\n    6.0\n    > im = imagf( z )\n    7.0\n\n    // Advanced indexing:\n    > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n    > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.cswap( 2, x, -2, y, 1 );\n    > z = y.get( 0 );\n    > re = realf( z )\n    5.0\n    > im = imagf( z )\n    6.0\n    > z = x.get( 0 );\n    > re = realf( z )\n    0.0\n    > im = imagf( z )\n    0.0\n\n    // Using typed array views:\n    > var x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n    > var y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.cswap( 2, x1, -2, y1, 1 );\n    > z = y0.get( 2 );\n    > re = realf( z )\n    7.0\n    > im = imagf( z )\n    8.0\n    > z = x0.get( 1 );\n    > re = realf( z )\n    0.0\n    > im = imagf( z )\n    0.0\n\n\nbase.strided.cswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Interchanges two complex single-precision floating-point vectors using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Complex64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Complex64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n    > base.strided.cswap.ndarray( x.length, x, 1, 0, y, 1, 0 );\n    > var z = y.get( 0 );\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    2.0\n    > z = x.get( 0 );\n    > re = realf( z )\n    6.0\n    > im = imagf( z )\n    7.0\n\n    // Advanced indexing:\n    > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n    > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.cswap.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\n    > z = y.get( y.length-1 );\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    4.0\n    > z = x.get( 1 );\n    > re = realf( z )\n    0.0\n    > im = imagf( z )\n    0.0\n\n    See Also\n    --------\n    base.strided.ccopy\n","base.strided.cswap.ndarray":"\nbase.strided.cswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Interchanges two complex single-precision floating-point vectors using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Complex64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Complex64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n    > base.strided.cswap.ndarray( x.length, x, 1, 0, y, 1, 0 );\n    > var z = y.get( 0 );\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    2.0\n    > z = x.get( 0 );\n    > re = realf( z )\n    6.0\n    > im = imagf( z )\n    7.0\n\n    // Advanced indexing:\n    > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n    > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.cswap.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\n    > z = y.get( y.length-1 );\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    4.0\n    > z = x.get( 1 );\n    > re = realf( z )\n    0.0\n    > im = imagf( z )\n    0.0\n\n    See Also\n    --------\n    base.strided.ccopy","base.strided.cumax":"\nbase.strided.cumax( N, x, strideX, y, strideY )\n    Computes the cumulative maximum of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cumax( x.length, x, 1, y, 1 )\n    [ 1.0, 1.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cumax( N, x, 2, y, 2 )\n    [ -2.0, 0.0, 1.0, 0.0, 2.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.cumax( N, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 2.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 2.0, 2.0 ]\n\nbase.strided.cumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum of a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, 1.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cumax.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumin, base.strided.dcumax, base.strided.scumax\n","base.strided.cumax.ndarray":"\nbase.strided.cumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum of a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, 1.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cumax.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumin, base.strided.dcumax, base.strided.scumax","base.strided.cumaxabs":"\nbase.strided.cumaxabs( N, x, strideX, y, strideY )\n    Computes the cumulative maximum absolute value of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cumaxabs( x.length, x, 1, y, 1 )\n    [ 1.0, 2.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cumaxabs( N, x, 2, y, 2 )\n    [ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.cumaxabs( N, x1, 2, y1, 1 )\n    <Float64Array>[ 2.0, 2.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\nbase.strided.cumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum absolute value of a strided array using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, 2.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cumax, base.strided.cuminabs, base.strided.dcumaxabs, base.strided.scumaxabs\n","base.strided.cumaxabs.ndarray":"\nbase.strided.cumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum absolute value of a strided array using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, 2.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cumax, base.strided.cuminabs, base.strided.dcumaxabs, base.strided.scumaxabs","base.strided.cumin":"\nbase.strided.cumin( N, x, strideX, y, strideY )\n    Computes the cumulative minimum of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cumin( x.length, x, 1, y, 1 )\n    [ 1.0, -2.0, -2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cumin( N, x, 2, y, 2 )\n    [ -2.0, 0.0, -2.0, 0.0, -2.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.cumin( N, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, -2.0, -2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\nbase.strided.cumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum of a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, -2.0, -2.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumax, base.strided.dcumin, base.strided.scumin\n","base.strided.cumin.ndarray":"\nbase.strided.cumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum of a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, -2.0, -2.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumax, base.strided.dcumin, base.strided.scumin","base.strided.cuminabs":"\nbase.strided.cuminabs( N, x, strideX, y, strideY )\n    Computes the cumulative minimum absolute value of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cuminabs( x.length, x, 1, y, 1 )\n    [ 1.0, 1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cuminabs( N, x, 2, y, 2 )\n    [ 2.0, 0.0, 1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.cuminabs( N, x1, 2, y1, 1 )\n    <Float64Array>[ 2.0, 2.0, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 1.0 ]\n\nbase.strided.cuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum absolute value of a strided array using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, 1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cumaxabs, base.strided.cumin, base.strided.dcuminabs, base.strided.scuminabs\n","base.strided.cuminabs.ndarray":"\nbase.strided.cuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum absolute value of a strided array using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, 1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cumaxabs, base.strided.cumin, base.strided.dcuminabs, base.strided.scuminabs","base.strided.dabs":"\nbase.strided.dabs( N, x, strideX, y, strideY )\n    Computes the absolute value for each element in a double-precision floating-\n    point strided array `x` and assigns the results to elements in a double-\n    precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dabs( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dabs( N, x, 2, y, -1 )\n    <Float64Array>[ 3.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dabs( N, x1, -2, y1, 1 )\n    <Float64Array>[ 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the absolute value for each element in a double-precision floating-\n    point strided array `x` and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    strided.abs, base.strided.dabs2, base.strided.sabs\n","base.strided.dabs.ndarray":"\nbase.strided.dabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the absolute value for each element in a double-precision floating-\n    point strided array `x` and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    strided.abs, base.strided.dabs2, base.strided.sabs","base.strided.dabs2":"\nbase.strided.dabs2( N, x, strideX, y, strideY )\n    Computes the squared absolute value for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dabs2( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.0, 4.0, 9.0, 16.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dabs2( N, x, 2, y, -1 )\n    <Float64Array>[ 9.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dabs2( N, x1, -2, y1, 1 )\n    <Float64Array>[ 16.0, 4.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 16.0, 4.0 ]\n\n\nbase.strided.dabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the squared absolute value for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 4.0, 9.0, 16.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 16.0, 4.0 ]\n\n    See Also\n    --------\n    strided.abs2, base.strided.dabs, base.strided.sabs2\n","base.strided.dabs2.ndarray":"\nbase.strided.dabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the squared absolute value for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 4.0, 9.0, 16.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 16.0, 4.0 ]\n\n    See Also\n    --------\n    strided.abs2, base.strided.dabs, base.strided.sabs2","base.strided.dapx":"\nbase.strided.dapx( N, alpha, x, strideX )\n    Adds a scalar constant to each element in a double-precision floating-point\n    strided array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns the strided array unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dapx( x.length, 5.0, x, 1 )\n    <Float64Array>[ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dapx( 3, 5.0, x, 2 )\n    <Float64Array>[ 3.0, 1.0, 8.0, -5.0, 9.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dapx( 3, 5.0, x1, 2 )\n    <Float64Array>[ 3.0, 3.0, 1.0, 5.0, -1.0 ]\n    > x0\n    <Float64Array>[ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n\nbase.strided.dapx.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each element in a double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dapx.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float64Array>[ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.dapx.ndarray( 3, 5.0, x, 2, 1 )\n    <Float64Array>[ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n    See Also\n    --------\n    base.strided.gapx, base.strided.sapx\n","base.strided.dapx.ndarray":"\nbase.strided.dapx.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each element in a double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dapx.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float64Array>[ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.dapx.ndarray( 3, 5.0, x, 2, 1 )\n    <Float64Array>[ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n    See Also\n    --------\n    base.strided.gapx, base.strided.sapx","base.strided.dapxsum":"\nbase.strided.dapxsum( N, alpha, x, strideX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsum( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dapxsum( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dapxsum( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.dapxsum.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dapxsum.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumpw, base.strided.dsum, base.strided.gapxsum, base.strided.sapxsum\n","base.strided.dapxsum.ndarray":"\nbase.strided.dapxsum.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dapxsum.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumpw, base.strided.dsum, base.strided.gapxsum, base.strided.sapxsum","base.strided.dapxsumkbn":"\nbase.strided.dapxsumkbn( N, alpha, x, strideX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using an improved Kahan–Babuška\n    algorithm.\n\n    The `N` and stride parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumkbn( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dapxsumkbn( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dapxsumkbn( 3, 5.0, x1, 2)\n    14.0\n\n\nbase.strided.dapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using an improved Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.dsumkbn, base.strided.gapxsumkbn, base.strided.sapxsumkbn\n","base.strided.dapxsumkbn.ndarray":"\nbase.strided.dapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using an improved Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.dsumkbn, base.strided.gapxsumkbn, base.strided.sapxsumkbn","base.strided.dapxsumkbn2":"\nbase.strided.dapxsumkbn2( N, alpha, x, strideX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using a second-order iterative\n    Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumkbn2( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dapxsumkbn2( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dapxsumkbn2( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.dapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using a second-order iterative\n    Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.dsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsumkbn2\n","base.strided.dapxsumkbn2.ndarray":"\nbase.strided.dapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using a second-order iterative\n    Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.dsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsumkbn2","base.strided.dapxsumors":"\nbase.strided.dapxsumors( N, alpha, x, strideX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using ordinary recursive summation.\n\n    The `N` and stride parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumors( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dapxsumors( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dapxsumors( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.dapxsumors.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using ordinary recursive summation\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.dsumors, base.strided.gapxsumors, base.strided.sapxsumors\n","base.strided.dapxsumors.ndarray":"\nbase.strided.dapxsumors.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using ordinary recursive summation\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.dsumors, base.strided.gapxsumors, base.strided.sapxsumors","base.strided.dapxsumpw":"\nbase.strided.dapxsumpw( N, alpha, x, strideX )\n    Adds a scalar constant to each double-precision floating-point strided array\n    element and computes the sum using pairwise summation.\n\n    The `N` and stride parameters determine which elements in\n    the strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumpw( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dapxsumpw( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dapxsumpw( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.dapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a constant to each double-precision floating-point strided array\n    element and computes the sum using pairwise summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.dsumpw, base.strided.gapxsumpw, base.strided.sapxsumpw\n","base.strided.dapxsumpw.ndarray":"\nbase.strided.dapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a constant to each double-precision floating-point strided array\n    element and computes the sum using pairwise summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.dsumpw, base.strided.gapxsumpw, base.strided.sapxsumpw","base.strided.dasum":"\nbase.strided.dasum( N, x, stride )\n    Computes the sum of the absolute values.\n\n    The sum of absolute values corresponds to the *L1* norm.\n\n    The `N` and `stride` parameters determine which elements in `x` are used to\n    compute the sum.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the function returns `0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    sum: number\n        Sum of absolute values.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n    > var s = base.strided.dasum( x.length, x, 1 )\n    15.0\n\n    // Sum every other value:\n    > s = base.strided.dasum( 3, x, 2 )\n    9.0\n\n    // Use view offset; e.g., starting at 2nd element:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > s = base.strided.dasum( 3, x1, 2 )\n    12.0\n\n\nbase.strided.dasum.ndarray( N, x, stride, offset )\n    Computes the sum of absolute values using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    sum: number\n        Sum of absolute values.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n    > var s = base.strided.dasum.ndarray( x.length, x, 1, 0 )\n    15.0\n\n    // Sum the last three elements:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > s = base.strided.dasum.ndarray( 3, x, -1, x.length-1 )\n    15.0\n\n    See Also\n    --------\n    base.strided.daxpy, base.strided.gasum, base.strided.sasum, base.strided.dsum\n","base.strided.dasum.ndarray":"\nbase.strided.dasum.ndarray( N, x, stride, offset )\n    Computes the sum of absolute values using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    sum: number\n        Sum of absolute values.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n    > var s = base.strided.dasum.ndarray( x.length, x, 1, 0 )\n    15.0\n\n    // Sum the last three elements:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > s = base.strided.dasum.ndarray( 3, x, -1, x.length-1 )\n    15.0\n\n    See Also\n    --------\n    base.strided.daxpy, base.strided.gasum, base.strided.sasum, base.strided.dsum","base.strided.dasumpw":"\nbase.strided.dasumpw( N, x, strideX )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements using pairwise summation.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dasumpw( x.length, x, 1 )\n    5.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var stride = 2;\n    > base.strided.dasumpw( 3, x, stride )\n    5.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > stride = 2;\n    > base.strided.dasumpw( 3, x1, stride )\n    5.0\n\n\nbase.strided.dasumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements using pairwise summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dasumpw.ndarray( x.length, x, 1, 0 )\n    5.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dasumpw.ndarray( 3, x, 2, 1 )\n    5.0\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.dsumpw, base.strided.gasumpw, base.strided.sasumpw\n","base.strided.dasumpw.ndarray":"\nbase.strided.dasumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements using pairwise summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dasumpw.ndarray( x.length, x, 1, 0 )\n    5.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dasumpw.ndarray( 3, x, 2, 1 )\n    5.0\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.dsumpw, base.strided.gasumpw, base.strided.sasumpw","base.strided.daxpy":"\nbase.strided.daxpy( N, alpha, x, strideX, y, strideY )\n    Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > var alpha = 5.0;\n    > base.strided.daxpy( x.length, alpha, x, 1, y, 1 )\n    <Float64Array>[ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > base.strided.daxpy( 3, alpha, x, 2, y, -1 )\n    <Float64Array>[ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.daxpy( 3, 5.0, x1, -2, y1, 1 )\n    <Float64Array>[ 40.0, 31.0, 22.0 ]\n    > y0\n    <Float64Array>[ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.strided.daxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n    Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > var alpha = 5.0;\n    > base.strided.daxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.daxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.gaxpy, base.strided.saxpy\n","base.strided.daxpy.ndarray":"\nbase.strided.daxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n    Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > var alpha = 5.0;\n    > base.strided.daxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.daxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.gaxpy, base.strided.saxpy","base.strided.dcbrt":"\nbase.strided.dcbrt( N, x, strideX, y, strideY )\n    Computes the cube root of each element in a double-precision floating-point\n    strided array `x` and assigns the results to elements in a double-precision\n    floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dcbrt( x.length, x, 1, y, 1 )\n    <Float64Array>[ 0.0, 1.0, 2.0, 3.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dcbrt( N, x, 2, y, -1 )\n    <Float64Array>[ 2.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dcbrt( N, x1, -2, y1, 1 )\n    <Float64Array>[ 3.0, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.dcbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cube root of each element in a double-precision floating-point\n    strided array `x` and assigns the results to elements in a double-precision\n    floating-point strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dcbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, 1.0, 2.0, 3.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dcbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n    See Also\n    --------\n    strided.cbrt, base.strided.dsqrt, base.strided.scbrt\n","base.strided.dcbrt.ndarray":"\nbase.strided.dcbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cube root of each element in a double-precision floating-point\n    strided array `x` and assigns the results to elements in a double-precision\n    floating-point strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dcbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, 1.0, 2.0, 3.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dcbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n    See Also\n    --------\n    strided.cbrt, base.strided.dsqrt, base.strided.scbrt","base.strided.dceil":"\nbase.strided.dceil( N, x, strideX, y, strideY )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward positive infinity and assigns the results to elements in a double-\n    precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dceil( x.length, x, 1, y, 1 )\n    <Float64Array>[ 2.0, 3.0, -3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dceil( N, x, 2, y, -1 )\n    <Float64Array>[ -3.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dceil( N, x1, -2, y1, 1 )\n    <Float64Array>[ 4.0, 3.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.dceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward positive infinity and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 2.0, 3.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n    See Also\n    --------\n    strided.ceil, base.strided.dfloor, base.strided.dtrunc, base.strided.sceil\n","base.strided.dceil.ndarray":"\nbase.strided.dceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward positive infinity and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 2.0, 3.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n    See Also\n    --------\n    strided.ceil, base.strided.dfloor, base.strided.dtrunc, base.strided.sceil","base.strided.dcopy":"\nbase.strided.dcopy( N, x, strideX, y, strideY )\n    Copies values from `x` into `y`.\n\n    The `N` and stride parameters determine how values from `x` are copied into\n    `y`.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.dcopy( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.dcopy( 3, x, -2, y, 1 )\n    <Float64Array>[ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n    // Using typed array views:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dcopy( 3, x1, -2, y1, 1 )\n    <Float64Array>[ 6.0, 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.dcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Copies values from `x` into `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.dcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dswap, base.strided.gcopy, base.strided.scopy\n","base.strided.dcopy.ndarray":"\nbase.strided.dcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Copies values from `x` into `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.dcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dswap, base.strided.gcopy, base.strided.scopy","base.strided.dcumax":"\nbase.strided.dcumax( N, x, strideX, y, strideY )\n    Computes the cumulative maximum of double-precision floating-point strided\n    array elements.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumax( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.0, 1.0, 2.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcumax( 3, x, 2, y, 2 )\n    <Float64Array>[ -2.0, 0.0, 1.0, 0.0, 2.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dcumax( 3, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 2.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 2.0, 2.0 ]\n\n\nbase.strided.dcumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum of double-precision floating-point strided\n    array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 1.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumax, base.strided.dcumin, base.strided.scumax\n","base.strided.dcumax.ndarray":"\nbase.strided.dcumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum of double-precision floating-point strided\n    array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 1.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumax, base.strided.dcumin, base.strided.scumax","base.strided.dcumaxabs":"\nbase.strided.dcumaxabs( N, x, strideX, y, strideY )\n    Computes the cumulative maximum absolute value of double-precision floating-\n    point strided array elements.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumaxabs( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.0, 2.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dcumaxabs( N, x, 2, y, 2 )\n    <Float64Array>[ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dcumaxabs( N, x1, 2, y1, 1 )\n    <Float64Array>[ 2.0, 2.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\nbase.strided.dcumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum absolute value of double-precision floating-\n    point strided array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dcumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cumaxabs, base.strided.dcumax, base.strided.dcuminabs, base.strided.scumaxabs\n","base.strided.dcumaxabs.ndarray":"\nbase.strided.dcumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum absolute value of double-precision floating-\n    point strided array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dcumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cumaxabs, base.strided.dcumax, base.strided.dcuminabs, base.strided.scumaxabs","base.strided.dcumin":"\nbase.strided.dcumin( N, x, strideX, y, strideY )\n    Computes the cumulative minimum of double-precision floating-point strided\n    array elements.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumin( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.0, -2.0, -2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dcumin( N, x, 2, y, 2 )\n    <Float64Array>[ -2.0, 0.0, -2.0, 0.0, -2.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dcumin( N, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, -2.0, -2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\nbase.strided.dcumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum of double-precision floating-point strided\n    array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -2.0, -2.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dcumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumin, base.strided.dcumax, base.strided.scumin\n","base.strided.dcumin.ndarray":"\nbase.strided.dcumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum of double-precision floating-point strided\n    array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -2.0, -2.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dcumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumin, base.strided.dcumax, base.strided.scumin","base.strided.dcuminabs":"\nbase.strided.dcuminabs( N, x, strideX, y, strideY )\n    Computes the cumulative minimum absolute value of double-precision floating-\n    point strided array elements.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcuminabs( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.0, 1.0, 1.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcuminabs( 3, x, 2, y, 2 )\n    <Float64Array>[ 2.0, 0.0, 1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dcuminabs( 3, x1, 2, y1, 1 )\n    <Float64Array>[ 2.0, 2.0, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 1.0 ]\n\n\nbase.strided.dcuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum absolute value of double-precision floating-\n    point strided array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cuminabs, base.strided.dcumaxabs, base.strided.dcumin, base.strided.scuminabs\n","base.strided.dcuminabs.ndarray":"\nbase.strided.dcuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum absolute value of double-precision floating-\n    point strided array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cuminabs, base.strided.dcumaxabs, base.strided.dcumin, base.strided.scuminabs","base.strided.dcusum":"\nbase.strided.dcusum( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements.\n\n    The `N` and stride parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusum( x.length, 0.0, x, 1, y, 1 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusum( 3, 0.0, x, 2, y, 2 )\n    <Float64Array>[ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dcusum( 3, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumpw, base.strided.gcusum, base.strided.scusum\n","base.strided.dcusum.ndarray":"\nbase.strided.dcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumpw, base.strided.gcusum, base.strided.scusum","base.strided.dcusumkbn":"\nbase.strided.dcusumkbn( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using an improved Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumkbn( x.length, 0.0, x, 1, y, 1 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumkbn( 3, 0.0, x, 2, y, 2 )\n    <Float64Array>[ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dcusumkbn( 3, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusumkbn, base.strided.scusumkbn\n","base.strided.dcusumkbn.ndarray":"\nbase.strided.dcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusumkbn, base.strided.scusumkbn","base.strided.dcusumkbn2":"\nbase.strided.dcusumkbn2( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of double-precision floating-point strided\n    array elements using a second-order iterative Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumkbn2( x.length, 0.0, x, 1, y, 1 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumkbn2( 3, 0.0, x, 2, y, 2 )\n    <Float64Array>[ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dcusumkbn2( 3, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of double-precision floating-point strided\n    array elements using a second-order iterative Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusumkbn2, base.strided.scusumkbn2\n","base.strided.dcusumkbn2.ndarray":"\nbase.strided.dcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of double-precision floating-point strided\n    array elements using a second-order iterative Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusumkbn2, base.strided.scusumkbn2","base.strided.dcusumors":"\nbase.strided.dcusumors( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using ordinary recursive summation.\n\n    The `N` and stride parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumors( x.length, 0.0, x, 1, y, 1 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumors( 3, 0.0, x, 2, y, 2 )\n    <Float64Array>[ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dcusumors( 3, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using ordinary recursive summation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusumors, base.strided.scusumors\n","base.strided.dcusumors.ndarray":"\nbase.strided.dcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using ordinary recursive summation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusumors, base.strided.scusumors","base.strided.dcusumpw":"\nbase.strided.dcusumpw( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using pairwise summation.\n\n    The `N` and stride parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumpw( x.length, 0.0, x, 1, y, 1 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumpw( 3, 0.0, x, 2, y, 2 )\n    <Float64Array>[ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dcusumpw( 3, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusumpw, base.strided.scusumpw\n","base.strided.dcusumpw.ndarray":"\nbase.strided.dcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusumpw, base.strided.scusumpw","base.strided.ddeg2rad":"\nbase.strided.ddeg2rad( N, x, strideX, y, strideY )\n    Converts each element in a double-precision floating-point strided array `x`\n    from degrees to radians and assigns the results to elements in a double-\n    precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.ddeg2rad( x.length, x, 1, y, 1 )\n    <Float64Array>[ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.ddeg2rad( N, x, 2, y, -1 )\n    <Float64Array>[ ~0.785, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.ddeg2rad( N, x1, -2, y1, 1 )\n    <Float64Array>[ ~1.047, ~0.524 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.ddeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Converts each element in a double-precision floating-point strided array `x`\n    from degrees to radians and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.ddeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.ddeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n    See Also\n    --------\n    strided.deg2rad, base.strided.sdeg2rad\n","base.strided.ddeg2rad.ndarray":"\nbase.strided.ddeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Converts each element in a double-precision floating-point strided array `x`\n    from degrees to radians and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.ddeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.ddeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n    See Also\n    --------\n    strided.deg2rad, base.strided.sdeg2rad","base.strided.ddot":"\nbase.strided.ddot( N, x, strideX, y, strideY )\n    Computes the dot product of two double-precision floating-point vectors.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: number\n        Dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var out = base.strided.ddot( x.length, x, 1, y, 1 )\n    -5.0\n\n    // Strides:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > out = base.strided.ddot( 3, x, 2, y, -1 )\n    9.0\n\n    // Using view offsets:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n    > out = base.strided.ddot( 3, x1, -2, y1, 1 )\n    128.0\n\n\nbase.strided.ddot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the dot product of two double-precision floating-point vectors\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing based on a starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: number\n        Dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var out = base.strided.ddot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    -5.0\n\n    // Strides:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > out = base.strided.ddot.ndarray( 3, x, 2, 0, y, 2, 0 )\n    9.0\n\n    // Using offset indices:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > out = base.strided.ddot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n    128.0\n\n    See Also\n    --------\n    base.strided.dsdot, base.strided.gdot, base.strided.sdot, base.strided.sdsdot, ddot\n","base.strided.ddot.ndarray":"\nbase.strided.ddot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the dot product of two double-precision floating-point vectors\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing based on a starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: number\n        Dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var out = base.strided.ddot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    -5.0\n\n    // Strides:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > out = base.strided.ddot.ndarray( 3, x, 2, 0, y, 2, 0 )\n    9.0\n\n    // Using offset indices:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > out = base.strided.ddot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n    128.0\n\n    See Also\n    --------\n    base.strided.dsdot, base.strided.gdot, base.strided.sdot, base.strided.sdsdot, ddot","base.strided.dfill":"\nbase.strided.dfill( N, alpha, x, strideX )\n    Fills a double-precision floating-point strided array with a specified\n    scalar value.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dfill( x.length, 5.0, x, 1 )\n    <Float64Array>[ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dfill( 3, 5.0, x, 2 )\n    <Float64Array>[ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dfill( 3, 5.0, x1, 2 )\n    <Float64Array>[ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n    > x0\n    <Float64Array>[ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.dfill.ndarray( N, alpha, x, strideX, offsetX )\n    Fills a double-precision floating-point strided array with a specified\n    scalar value using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dfill.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float64Array>[ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.dfill.ndarray( 3, 5.0, x, 2, 1 )\n    <Float64Array>[ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n    See Also\n    --------\n    base.strided.gfill, base.strided.sfill\n","base.strided.dfill.ndarray":"\nbase.strided.dfill.ndarray( N, alpha, x, strideX, offsetX )\n    Fills a double-precision floating-point strided array with a specified\n    scalar value using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dfill.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float64Array>[ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.dfill.ndarray( 3, 5.0, x, 2, 1 )\n    <Float64Array>[ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n    See Also\n    --------\n    base.strided.gfill, base.strided.sfill","base.strided.dfloor":"\nbase.strided.dfloor( N, x, strideX, y, strideY )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward negative infinity and assigns the results to elements in a double-\n    precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dfloor( x.length, x, 1, y, 1 )\n    <Float64Array>[ -2.0, 1.0, 3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dfloor( N, x, 2, y, -1 )\n    <Float64Array>[ 3.0, -2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dfloor( N, x1, -2, y1, 1 )\n    <Float64Array>[ 4.0, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 1.0 ]\n\n\nbase.strided.dfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward negative infinity and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ -2.0, 1.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dceil, base.strided.dtrunc, strided.floor, base.strided.sfloor\n","base.strided.dfloor.ndarray":"\nbase.strided.dfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward negative infinity and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ -2.0, 1.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dceil, base.strided.dtrunc, strided.floor, base.strided.sfloor","base.strided.dinv":"\nbase.strided.dinv( N, x, strideX, y, strideY )\n    Computes the multiplicative inverse for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dinv( x.length, x, 1, y, 1 )\n    <Float64Array>[ -0.05, -1.0, 0.5, 0.25 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dinv( N, x, 2, y, -1 )\n    <Float64Array>[ 0.5, -0.05, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dinv( N, x1, -2, y1, 1 )\n    <Float64Array>[ 0.25, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.dinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the multiplicative inverse for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ -0.05, -1.0, 0.5, 0.25 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n    See Also\n    --------\n    strided.inv, base.strided.sinv\n","base.strided.dinv.ndarray":"\nbase.strided.dinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the multiplicative inverse for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ -0.05, -1.0, 0.5, 0.25 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n    See Also\n    --------\n    strided.inv, base.strided.sinv","base.strided.dmap":"\nbase.strided.dmap( N, x, strideX, y, strideY, fcn )\n    Applies a unary function to a double-precision floating-point strided input\n    array and assigns results to a double-precision floating-point strided\n    output array.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap( x.length, x, 1, y, 1, base.identity )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap( 2, x, 2, y, -1, base.identity )\n    <Float64Array>[ 3.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmap( 2, x1, -2, y1, 1, base.identity )\n    <Float64Array>[ 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n    Applies a unary function to a double-precision floating-point strided input\n    array and assigns results to a double-precision floating-point strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identity )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identity )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.smap, base.strided.unary\n","base.strided.dmap.ndarray":"\nbase.strided.dmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n    Applies a unary function to a double-precision floating-point strided input\n    array and assigns results to a double-precision floating-point strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identity )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identity )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.smap, base.strided.unary","base.strided.dmap2":"\nbase.strided.dmap2( N, x, sx, y, sy, z, sz, fcn )\n    Applies a binary function to double-precision floating-point strided input\n    arrays and assigns results to a double-precision floating-point strided\n    output array.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    z: Float64Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float64Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap2( x.length, x, 1, y, 1, z, 1, base.add )\n    <Float64Array>[ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Using `N` and stride parameters:\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap2( 2, x, 2, y, -1, z, 1, base.add )\n    <Float64Array>[ 3.0, 4.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmap2( 2, x1, -2, y1, 1, z1, 1, base.add )\n    <Float64Array>[ 7.0, 6.0 ]\n    > z0\n    <Float64Array>[ 0.0, 0.0, 7.0, 6.0 ]\n\n\nbase.strided.dmap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Float64Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float64Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.add )\n    <Float64Array>[ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.add )\n    <Float64Array>[ 0.0, 6.0, 7.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.smap2, base.strided.binary\n","base.strided.dmap2.ndarray":"\nbase.strided.dmap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Float64Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float64Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.add )\n    <Float64Array>[ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.add )\n    <Float64Array>[ 0.0, 6.0, 7.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.smap2, base.strided.binary","base.strided.dmax":"\nbase.strided.dmax( N, x, strideX )\n    Computes the maximum value of a double-precision floating-point strided\n    array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmax( x.length, x, 1 )\n    2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dmax( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dmax( 3, x1, 2 )\n    2.0\n\n\nbase.strided.dmax.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a double-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmax.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dmax.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dnanmax, base.strided.max, base.strided.smax\n","base.strided.dmax.ndarray":"\nbase.strided.dmax.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a double-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmax.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dmax.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dnanmax, base.strided.max, base.strided.smax","base.strided.dmaxabs":"\nbase.strided.dmaxabs( N, x, strideX )\n    Computes the maximum absolute value of a double-precision floating-point\n    strided array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmaxabs( x.length, x, 1 )\n    2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dmaxabs( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dmaxabs( 3, x1, 2 )\n    2.0\n\n\nbase.strided.dmaxabs.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmaxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dmaxabs.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dminabs, base.strided.dnanmaxabs, base.strided.maxabs, base.strided.smaxabs\n","base.strided.dmaxabs.ndarray":"\nbase.strided.dmaxabs.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmaxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dmaxabs.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dminabs, base.strided.dnanmaxabs, base.strided.maxabs, base.strided.smaxabs","base.strided.dmaxabssorted":"\nbase.strided.dmaxabssorted( N, x, stride )\n    Computes the maximum absolute value of a sorted double-precision floating-\n    point strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n    > base.strided.dmaxabssorted( x.length, x, 1 )\n    3.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dmaxabssorted( N, x, stride )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmaxabssorted( N, x1, stride )\n    3.0\n\nbase.strided.dmaxabssorted.ndarray( N, x, stride, offset )\n    Computes the maximum absolute value of a sorted double-precision floating-\n    point strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n    > base.strided.dmaxabssorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmaxabssorted.ndarray( N, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmaxabs, base.strided.dmaxsorted, base.strided.smaxabssorted\n","base.strided.dmaxabssorted.ndarray":"\nbase.strided.dmaxabssorted.ndarray( N, x, stride, offset )\n    Computes the maximum absolute value of a sorted double-precision floating-\n    point strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n    > base.strided.dmaxabssorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmaxabssorted.ndarray( N, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmaxabs, base.strided.dmaxsorted, base.strided.smaxabssorted","base.strided.dmaxsorted":"\nbase.strided.dmaxsorted( N, x, stride )\n    Computes the maximum value of a sorted double-precision floating-point\n    strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dmaxsorted( x.length, x, 1 )\n    3.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dmaxsorted( N, x, stride )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmaxsorted( N, x1, stride )\n    3.0\n\nbase.strided.dmaxsorted.ndarray( N, x, stride, offset )\n    Computes the maximum value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dmaxsorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmaxsorted.ndarray( N, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dminsorted, base.strided.maxsorted, base.strided.smaxsorted\n","base.strided.dmaxsorted.ndarray":"\nbase.strided.dmaxsorted.ndarray( N, x, stride, offset )\n    Computes the maximum value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dmaxsorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmaxsorted.ndarray( N, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dminsorted, base.strided.maxsorted, base.strided.smaxsorted","base.strided.dmean":"\nbase.strided.dmean( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmean( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dmean( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmean( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.mean, base.strided.smean\n","base.strided.dmean.ndarray":"\nbase.strided.dmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.mean, base.strided.smean","base.strided.dmeankbn":"\nbase.strided.dmeankbn( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeankbn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dmeankbn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmeankbn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dmeankbn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeankbn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeankbn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.meankbn, base.strided.smeankbn\n","base.strided.dmeankbn.ndarray":"\nbase.strided.dmeankbn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeankbn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeankbn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.meankbn, base.strided.smeankbn","base.strided.dmeankbn2":"\nbase.strided.dmeankbn2( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a second-order iterative Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeankbn2( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dmeankbn2( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmeankbn2( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dmeankbn2.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeankbn2.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeankbn2.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.meankbn2, base.strided.smeankbn2\n","base.strided.dmeankbn2.ndarray":"\nbase.strided.dmeankbn2.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeankbn2.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeankbn2.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.meankbn2, base.strided.smeankbn2","base.strided.dmeanli":"\nbase.strided.dmeanli( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanli( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dmeanli( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmeanli( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dmeanli.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanli.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanli.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dmeanlipw, base.strided.smeanli\n","base.strided.dmeanli.ndarray":"\nbase.strided.dmeanli.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanli.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanli.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dmeanlipw, base.strided.smeanli","base.strided.dmeanlipw":"\nbase.strided.dmeanlipw( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm with pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanlipw( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dmeanlipw( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmeanlipw( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dmeanlipw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm with pairwise summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanlipw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanlipw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dmeanli, base.strided.dmeanpw, base.strided.smeanlipw\n","base.strided.dmeanlipw.ndarray":"\nbase.strided.dmeanlipw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm with pairwise summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanlipw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanlipw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dmeanli, base.strided.dmeanpw, base.strided.smeanlipw","base.strided.dmeanors":"\nbase.strided.dmeanors( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using ordinary recursive summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanors( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dmeanors( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmeanors( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dnanmeanors, base.strided.meanors, base.strided.smeanors\n","base.strided.dmeanors.ndarray":"\nbase.strided.dmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dnanmeanors, base.strided.meanors, base.strided.smeanors","base.strided.dmeanpn":"\nbase.strided.dmeanpn( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a two-pass error correction algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanpn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dmeanpn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmeanpn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a two-pass error correction algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dnanmeanpn, base.strided.meanpn, base.strided.smeanpn\n","base.strided.dmeanpn.ndarray":"\nbase.strided.dmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a two-pass error correction algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dnanmeanpn, base.strided.meanpn, base.strided.smeanpn","base.strided.dmeanpw":"\nbase.strided.dmeanpw( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanpw( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dmeanpw( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmeanpw( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dmeanpw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanpw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanpw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dnanmeanpw, base.strided.meanpw, base.strided.smeanpw\n","base.strided.dmeanpw.ndarray":"\nbase.strided.dmeanpw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanpw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanpw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dnanmeanpw, base.strided.meanpw, base.strided.smeanpw","base.strided.dmeanstdev":"\nbase.strided.dmeanstdev( N, c, x, strideX, out, strideOut )\n    Computes the mean and standard deviation of a double-precision floating-\n    point strided array.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns a mean and standard deviation equal to\n    `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanstdev( x.length, 1, x, 1, out, 1 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > out = new Float64Array( 2 );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanstdev( N, 1, x, 2, out, 1 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanstdev( N, 1, x1, 2, out, 1 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\nbase.strided.dmeanstdev.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the mean and standard deviation of a double-precision floating-\n    point strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanstdev.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanstdev.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dmeanvar, base.strided.dstdev\n","base.strided.dmeanstdev.ndarray":"\nbase.strided.dmeanstdev.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the mean and standard deviation of a double-precision floating-\n    point strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanstdev.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanstdev.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dmeanvar, base.strided.dstdev","base.strided.dmeanstdevpn":"\nbase.strided.dmeanstdevpn( N, c, x, strideX, out, strideOut )\n    Computes the mean and standard deviation of a double-precision floating-\n    point strided array using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns a mean and standard deviation equal to\n    `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanstdevpn( x.length, 1, x, 1, out, 1 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > out = new Float64Array( 2 );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanstdevpn( N, 1, x, 2, out, 1 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanstdevpn( N, 1, x1, 2, out, 1 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\nbase.strided.dmeanstdevpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the mean and standard deviation of a double-precision floating-\n    point strided array using a two-pass algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanstdevpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanstdevpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.dmeanstdev, base.strided.dmeanvarpn, base.strided.dstdevpn\n","base.strided.dmeanstdevpn.ndarray":"\nbase.strided.dmeanstdevpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the mean and standard deviation of a double-precision floating-\n    point strided array using a two-pass algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanstdevpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanstdevpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.dmeanstdev, base.strided.dmeanvarpn, base.strided.dstdevpn","base.strided.dmeanvar":"\nbase.strided.dmeanvar( N, c, x, strideX, out, strideOut )\n    Computes the mean and variance of a double-precision floating-point strided\n    array.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns a mean and variance equal to `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanvar( x.length, 1, x, 1, out, 1 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > out = new Float64Array( 2 );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanvar( N, 1, x, 2, out, 1 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanvar( N, 1, x1, 2, out, 1 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\nbase.strided.dmeanvar.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the mean and variance of a double-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanvar.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanvar.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dvariance\n","base.strided.dmeanvar.ndarray":"\nbase.strided.dmeanvar.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the mean and variance of a double-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanvar.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanvar.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dvariance","base.strided.dmeanvarpn":"\nbase.strided.dmeanvarpn( N, c, x, strideX, out, strideOut )\n    Computes the mean and variance of a double-precision floating-point strided\n    array using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns a mean and variance equal to `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanvarpn( x.length, 1, x, 1, out, 1 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > out = new Float64Array( 2 );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanvarpn( N, 1, x, 2, out, 1 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanvarpn( N, 1, x1, 2, out, 1 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\nbase.strided.dmeanvarpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the mean and variance of a double-precision floating-point strided\n    array using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanvarpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanvarpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.dmeanstdevpn, base.strided.dmeanvar, base.strided.dvariancepn\n","base.strided.dmeanvarpn.ndarray":"\nbase.strided.dmeanvarpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the mean and variance of a double-precision floating-point strided\n    array using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanvarpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanvarpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.dmeanstdevpn, base.strided.dmeanvar, base.strided.dvariancepn","base.strided.dmeanwd":"\nbase.strided.dmeanwd( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanwd( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dmeanwd( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmeanwd( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dnanmeanwd, base.strided.meanwd, base.strided.smeanwd\n","base.strided.dmeanwd.ndarray":"\nbase.strided.dmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dnanmeanwd, base.strided.meanwd, base.strided.smeanwd","base.strided.dmediansorted":"\nbase.strided.dmediansorted( N, x, stride )\n    Computes the median value of a sorted double-precision floating-point\n    strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dmediansorted( x.length, x, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmediansorted( N, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dmediansorted( N, x1, 2 )\n    2.0\n\nbase.strided.dmediansorted.ndarray( N, x, stride, offset )\n    Computes the median value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmediansorted.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.mediansorted, base.strided.smediansorted\n","base.strided.dmediansorted.ndarray":"\nbase.strided.dmediansorted.ndarray( N, x, stride, offset )\n    Computes the median value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmediansorted.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.mediansorted, base.strided.smediansorted","base.strided.dmidrange":"\nbase.strided.dmidrange( N, x, strideX )\n    Computes the mid-range of a double-precision floating-point strided array.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Mid-range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmidrange( x.length, x, 1 )\n    0.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dmidrange( 3, x, 2 )\n    0.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dmidrange( 3, x1, 2 )\n    0.0\n\n\nbase.strided.dmidrange.ndarray( N, x, strideX, offsetX )\n    Computes the mid-range of a double-precision floating-point strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Mid-range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmidrange.ndarray( x.length, x, 1, 0 )\n    0.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dmidrange.ndarray( 3, x, 2, 1 )\n    0.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dmean, base.strided.dmin, base.strided.drange, base.strided.smidrange\n","base.strided.dmidrange.ndarray":"\nbase.strided.dmidrange.ndarray( N, x, strideX, offsetX )\n    Computes the mid-range of a double-precision floating-point strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Mid-range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmidrange.ndarray( x.length, x, 1, 0 )\n    0.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dmidrange.ndarray( 3, x, 2, 1 )\n    0.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dmean, base.strided.dmin, base.strided.drange, base.strided.smidrange","base.strided.dmin":"\nbase.strided.dmin( N, x, strideX )\n    Computes the minimum value of a double-precision floating-point strided\n    array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmin( x.length, x, 1 )\n    -2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dmin( 3, x, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmin( N, x1, stride )\n    -2.0\n\n\nbase.strided.dmin.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a double-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dmin.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dnanmin, base.strided.min, base.strided.smin\n","base.strided.dmin.ndarray":"\nbase.strided.dmin.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a double-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dmin.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dnanmin, base.strided.min, base.strided.smin","base.strided.dminabs":"\nbase.strided.dminabs( N, x, strideX )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dminabs( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dminabs( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dminabs( 3, x1, 2 )\n    1.0\n\n\nbase.strided.dminabs.ndarray( N, x, strideX, offsetX )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dminabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dminabs.ndarray( 3, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dmaxabs, base.strided.dnanminabs, base.strided.minabs, base.strided.sminabs\n","base.strided.dminabs.ndarray":"\nbase.strided.dminabs.ndarray( N, x, strideX, offsetX )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dminabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dminabs.ndarray( 3, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dmaxabs, base.strided.dnanminabs, base.strided.minabs, base.strided.sminabs","base.strided.dminsorted":"\nbase.strided.dminsorted( N, x, stride )\n    Computes the minimum value of a sorted double-precision floating-point\n    strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dminsorted( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dminsorted( N, x, stride )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dminsorted( N, x1, stride )\n    -2.0\n\nbase.strided.dminsorted.ndarray( N, x, stride, offset )\n    Computes the minimum value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dminsorted.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dminsorted.ndarray( N, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dmaxsorted, base.strided.minsorted, base.strided.sminsorted\n","base.strided.dminsorted.ndarray":"\nbase.strided.dminsorted.ndarray( N, x, stride, offset )\n    Computes the minimum value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dminsorted.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dminsorted.ndarray( N, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dmaxsorted, base.strided.minsorted, base.strided.sminsorted","base.strided.dmskabs":"\nbase.strided.dmskabs( N, x, sx, m, sm, y, sy )\n    Computes the absolute value for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ 2.0, 1.0, 0.0, 5.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskabs( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ 5.0, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 5.0, 1.0 ]\n\n\nbase.strided.dmskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the absolute value for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 2.0, 1.0, 0.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 5.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dabs, base.strided.dmskabs2, base.strided.smskabs\n","base.strided.dmskabs.ndarray":"\nbase.strided.dmskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the absolute value for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 2.0, 1.0, 0.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 5.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dabs, base.strided.dmskabs2, base.strided.smskabs","base.strided.dmskabs2":"\nbase.strided.dmskabs2( N, x, sx, m, sm, y, sy )\n    Computes the squared absolute value for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point\n    strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs2( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ 4.0, 1.0, 0.0, 25.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs2( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, 4.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskabs2( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ 25.0, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 25.0, 1.0 ]\n\n\nbase.strided.dmskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the squared absolute value for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point\n    strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 4.0, 1.0, 0.0, 25.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 25.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dabs2, base.strided.dmskabs, base.strided.smskabs2\n","base.strided.dmskabs2.ndarray":"\nbase.strided.dmskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the squared absolute value for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point\n    strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 4.0, 1.0, 0.0, 25.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 25.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dabs2, base.strided.dmskabs, base.strided.smskabs2","base.strided.dmskcbrt":"\nbase.strided.dmskcbrt( N, x, sx, m, sm, y, sy )\n    Computes the cube root for each element in a double-precision floating-point\n    strided array `x` according to a strided mask array and assigns the results\n    to elements in a double-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskcbrt( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ 0.0, 1.0, 0.0, 3.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskcbrt( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskcbrt( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ 3.0, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.dmskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the cube root for each element in a double-precision floating-point\n    strided array `x` according to a strided mask array and assigns the results\n    to elements in a double-precision floating-point strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, 1.0, 0.0, 3.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dcbrt, base.strided.dmsksqrt, base.strided.smskcbrt\n","base.strided.dmskcbrt.ndarray":"\nbase.strided.dmskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the cube root for each element in a double-precision floating-point\n    strided array `x` according to a strided mask array and assigns the results\n    to elements in a double-precision floating-point strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, 1.0, 0.0, 3.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dcbrt, base.strided.dmsksqrt, base.strided.smskcbrt","base.strided.dmskceil":"\nbase.strided.dmskceil( N, x, sx, m, sm, y, sy )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward positive infinity according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskceil( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ 2.0, 3.0, 0.0, 4.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskceil( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskceil( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ 4.0, 3.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.dmskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward positive infinity according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 2.0, 3.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n    See Also\n    --------\n    base.strided.dceil, base.strided.dmskfloor, base.strided.dmsktrunc, base.strided.smskceil\n","base.strided.dmskceil.ndarray":"\nbase.strided.dmskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward positive infinity according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 2.0, 3.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n    See Also\n    --------\n    base.strided.dceil, base.strided.dmskfloor, base.strided.dmsktrunc, base.strided.smskceil","base.strided.dmskdeg2rad":"\nbase.strided.dmskdeg2rad( N, x, sx, m, sm, y, sy )\n    Converts each element in a double-precision floating-point strided array `x`\n    from degrees to radians according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskdeg2rad( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ 0.0, ~0.524, 0.0, ~1.047 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskdeg2rad( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ ~1.047, ~0.524 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.dmskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Converts each element in a double-precision floating-point strided array `x`\n    from degrees to radians according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, ~0.524, 0.0, ~1.047 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n    See Also\n    --------\n    base.strided.ddeg2rad, base.strided.dmskdeg2rad, base.strided.smskdeg2rad\n","base.strided.dmskdeg2rad.ndarray":"\nbase.strided.dmskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Converts each element in a double-precision floating-point strided array `x`\n    from degrees to radians according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, ~0.524, 0.0, ~1.047 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n    See Also\n    --------\n    base.strided.ddeg2rad, base.strided.dmskdeg2rad, base.strided.smskdeg2rad","base.strided.dmskfloor":"\nbase.strided.dmskfloor( N, x, sx, m, sm, y, sy )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward negative infinity according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskfloor( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskfloor( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskfloor( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dmskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward negative infinity according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dfloor, base.strided.dmskceil, base.strided.dmsktrunc, base.strided.smskfloor\n","base.strided.dmskfloor.ndarray":"\nbase.strided.dmskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward negative infinity according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dfloor, base.strided.dmskceil, base.strided.dmsktrunc, base.strided.smskfloor","base.strided.dmskinv":"\nbase.strided.dmskinv( N, x, sx, m, sm, y, sy )\n    Computes the multiplicative inverse for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskinv( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ -0.05, -1.0, 0.0, 0.25 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskinv( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, -0.05, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskinv( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ 0.25, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.dmskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the multiplicative inverse for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ -0.05, -1.0, 0.0, 0.25 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dinv, base.strided.smskinv\n","base.strided.dmskinv.ndarray":"\nbase.strided.dmskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the multiplicative inverse for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ -0.05, -1.0, 0.0, 0.25 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dinv, base.strided.smskinv","base.strided.dmskmap":"\nbase.strided.dmskmap( N, x, sx, m, sm, y, sy, fcn )\n    Applies a unary function to a double-precision floating-point strided input\n    array according to a strided mask array and assigns results to a double-\n    precision floating-point strided output array.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskmap( x.length, x, 1, m, 1, y, 1, base.identity )\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskmap( 2, x, 2, m, 2, y, -1, base.identity )\n    <Float64Array>[ 0.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\n    <Float64Array>[ 0.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, 2.0 ]\n\n\nbase.strided.dmskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n    Applies a unary function to a double-precision floating-point strided input\n    array according to a strided mask array and assigns results to a double-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n    <Float64Array>[ 0.0, 0.0, 4.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmap, base.strided.dmskmap2, base.strided.mskunary, base.strided.smskmap\n","base.strided.dmskmap.ndarray":"\nbase.strided.dmskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n    Applies a unary function to a double-precision floating-point strided input\n    array according to a strided mask array and assigns results to a double-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n    <Float64Array>[ 0.0, 0.0, 4.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmap, base.strided.dmskmap2, base.strided.mskunary, base.strided.smskmap","base.strided.dmskmap2":"\nbase.strided.dmskmap2( N, x, sx, y, sy, m, sm, z, sz, fcn )\n    Applies a binary function to double-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a double-\n    precision floating-point strided output array.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    z: Float64Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float64Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.dmskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.add )\n    <Float64Array>[ 2.0, 4.0, 0.0, 8.0 ]\n\n    // Using `N` and stride parameters:\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.add )\n    <Float64Array>[ 0.0, 3.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.add )\n    <Float64Array>[ 0.0, 6.0 ]\n    > z0\n    <Float64Array>[ 0.0, 0.0, 0.0, 6.0 ]\n\n\nbase.strided.dmskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n    Applies a binary function to double-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a double-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    z: Float64Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float64Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.dmskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.add )\n    <Float64Array>[ 2.0, 4.0, 0.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.dmskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.add )\n    <Float64Array>[ 0.0, 0.0, 7.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmap2, base.strided.dmskmap, base.strided.smskmap2\n","base.strided.dmskmap2.ndarray":"\nbase.strided.dmskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n    Applies a binary function to double-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a double-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    z: Float64Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float64Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.dmskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.add )\n    <Float64Array>[ 2.0, 4.0, 0.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.dmskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.add )\n    <Float64Array>[ 0.0, 0.0, 7.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmap2, base.strided.dmskmap, base.strided.smskmap2","base.strided.dmskmax":"\nbase.strided.dmskmax( N, x, strideX, mask, strideMask )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.dmskmax( x.length, x, 1, mask, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmskmax( N, x, 2, mask, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dmskmax( N, x1, 2, mask1, 2 )\n    2.0\n\nbase.strided.dmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dmskmin, base.strided.dnanmax, base.strided.dnanmskmax, base.strided.mskmax, base.strided.smskmax\n","base.strided.dmskmax.ndarray":"\nbase.strided.dmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dmskmin, base.strided.dnanmax, base.strided.dnanmskmax, base.strided.mskmax, base.strided.smskmax","base.strided.dmskmin":"\nbase.strided.dmskmin( N, x, strideX, mask, strideMask )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.dmskmin( x.length, x, 1, mask, 1 )\n    -2.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmskmin( N, x, 2, mask, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dmskmin( N, x1, 2, mask1, 2 )\n    -2.0\n\nbase.strided.dmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dmskmax, base.strided.dnanmin, base.strided.dnanmskmin, base.strided.mskmin, base.strided.smskmin\n","base.strided.dmskmin.ndarray":"\nbase.strided.dmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dmskmax, base.strided.dnanmin, base.strided.dnanmskmin, base.strided.mskmin, base.strided.smskmin","base.strided.dmskramp":"\nbase.strided.dmskramp( N, x, sx, m, sm, y, sy )\n    Evaluates the ramp function for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskramp( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ 1.1, 2.5, 0.0, 4.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskramp( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, 1.1, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskramp( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ 4.0, 2.5 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.5 ]\n\n\nbase.strided.dmskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Evaluates the ramp function for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.1, 2.5, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.5 ]\n\n    See Also\n    --------\n    base.strided.dramp, base.strided.smskramp\n","base.strided.dmskramp.ndarray":"\nbase.strided.dmskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Evaluates the ramp function for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.1, 2.5, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.5 ]\n\n    See Also\n    --------\n    base.strided.dramp, base.strided.smskramp","base.strided.dmskrange":"\nbase.strided.dmskrange( N, x, strideX, mask, strideMask )\n    Computes the range of a double-precision floating-point strided array\n    according to a mask.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.dmskrange( x.length, x, 1, mask, 1 )\n    4.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.dmskrange( 3, x, 2, mask, 2 )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dmskrange( 3, x1, 2, mask1, 2 )\n    4.0\n\n\nbase.strided.dmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a double-precision floating-point strided array\n    according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.dmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.dmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dmskmax, base.strided.dmskmin, base.strided.dnanrange, base.strided.drange, base.strided.mskrange, base.strided.smskrange\n","base.strided.dmskrange.ndarray":"\nbase.strided.dmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a double-precision floating-point strided array\n    according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.dmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.dmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dmskmax, base.strided.dmskmin, base.strided.dnanrange, base.strided.drange, base.strided.mskrange, base.strided.smskrange","base.strided.dmskrsqrt":"\nbase.strided.dmskrsqrt( N, x, sx, m, sm, y, sy )\n    Computes the reciprocal square root for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskrsqrt( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ Infinity, 0.5, 0.0, ~0.289 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskrsqrt( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, Infinity, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ ~0.289, 0.5 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.dmskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the reciprocal square root for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ Infinity, 0.5, 0.0, ~0.289 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n    See Also\n    --------\n    base.strided.dmsksqrt, base.strided.dsqrt, base.strided.smskrsqrt\n","base.strided.dmskrsqrt.ndarray":"\nbase.strided.dmskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the reciprocal square root for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ Infinity, 0.5, 0.0, ~0.289 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n    See Also\n    --------\n    base.strided.dmsksqrt, base.strided.dsqrt, base.strided.smskrsqrt","base.strided.dmsksqrt":"\nbase.strided.dmsksqrt( N, x, sx, m, sm, y, sy )\n    Computes the principal square root for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsksqrt( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ 0.0, 2.0, 0.0, ~3.464 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsksqrt( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmsksqrt( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ ~3.464, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.dmsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the principal square root for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, 2.0, 0.0, ~3.464 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmskcbrt, base.strided.dmskrsqrt, base.strided.dsqrt, base.strided.smsksqrt\n","base.strided.dmsksqrt.ndarray":"\nbase.strided.dmsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the principal square root for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, 2.0, 0.0, ~3.464 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmskcbrt, base.strided.dmskrsqrt, base.strided.dsqrt, base.strided.smsksqrt","base.strided.dmsktrunc":"\nbase.strided.dmsktrunc( N, x, sx, m, sm, y, sy )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward zero according to a strided mask array and assigns the results to\n    elements in a double-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsktrunc( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsktrunc( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmsktrunc( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dmsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward zero according to a strided mask array and assigns the results to\n    elements in a double-precision floating-point strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmskceil, base.strided.dmskfloor, base.strided.dtrunc, base.strided.smsktrunc\n","base.strided.dmsktrunc.ndarray":"\nbase.strided.dmsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward zero according to a strided mask array and assigns the results to\n    elements in a double-precision floating-point strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmskceil, base.strided.dmskfloor, base.strided.dtrunc, base.strided.smsktrunc","base.strided.dnanasum":"\nbase.strided.dnanasum( N, x, strideX )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements, ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanasum( x.length, x, 1 )\n    5.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.dnanasum( 4, x, 2 )\n    5.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnanasum( 4, x1, 2 )\n    5.0\n\n\nbase.strided.dnanasum.ndarray( N, x, strideX, offsetX )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements, ignoring `NaN` values and using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanasum.ndarray( x.length, x, 1, 0 )\n    5.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnanasum.ndarray( 4, x, 2, 1 )\n    5.0\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.dasumpw","base.strided.dnanasum.ndarray":"\nbase.strided.dnanasum.ndarray( N, x, strideX, offsetX )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements, ignoring `NaN` values and using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanasum.ndarray( x.length, x, 1, 0 )\n    5.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnanasum.ndarray( 4, x, 2, 1 )\n    5.0\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.dasumpw","base.strided.dnanasumors":"\nbase.strided.dnanasumors( N, x, strideX )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements, ignoring `NaN` values and using ordinary\n    recursive summation.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanasumors( x.length, x, 1 )\n    5.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanasumors( N, x, stride )\n    5.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanasumors( N, x1, stride )\n    5.0\n\n\nbase.strided.dnanasumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements, ignoring `NaN` values and using ordinary\n    recursive summation alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanasumors.ndarray( x.length, x, 1, 0 )\n    5.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanasumors.ndarray( N, x, 2, 1 )\n    5.0\n\n    See Also\n    --------\n    base.strided.dnanasum\n","base.strided.dnanasumors.ndarray":"\nbase.strided.dnanasumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements, ignoring `NaN` values and using ordinary\n    recursive summation alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanasumors.ndarray( x.length, x, 1, 0 )\n    5.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanasumors.ndarray( N, x, 2, 1 )\n    5.0\n\n    See Also\n    --------\n    base.strided.dnanasum","base.strided.dnanmax":"\nbase.strided.dnanmax( N, x, strideX )\n    Computes the maximum value of a double-precision floating-point strided\n    array, ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmax( x.length, x, 1 )\n    2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > base.strided.dnanmax( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnanmax( 3, x1, 2 )\n    2.0\n\n\nbase.strided.dnanmax.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a double-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.dnanmax.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanmax.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dnanmin, base.strided.nanmax, base.strided.snanmax\n","base.strided.dnanmax.ndarray":"\nbase.strided.dnanmax.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a double-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.dnanmax.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanmax.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dnanmin, base.strided.nanmax, base.strided.snanmax","base.strided.dnanmaxabs":"\nbase.strided.dnanmaxabs( N, x, strideX )\n    Computes the maximum absolute value of a double-precision floating-point\n    strided array, ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmaxabs( x.length, x, 1 )\n    2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > base.strided.dnanmaxabs( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnanmaxabs( 3, x1, 2 )\n    2.0\n\n\nbase.strided.dnanmaxabs.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a double-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.dnanmaxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanmaxabs.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmaxabs, base.strided.dnanmax, base.strided.dnanminabs, base.strided.nanmaxabs, base.strided.snanmaxabs\n","base.strided.dnanmaxabs.ndarray":"\nbase.strided.dnanmaxabs.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a double-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.dnanmaxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanmaxabs.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmaxabs, base.strided.dnanmax, base.strided.dnanminabs, base.strided.nanmaxabs, base.strided.snanmaxabs","base.strided.dnanmean":"\nbase.strided.dnanmean( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmean( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanmean( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanmean( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dnanmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.nanmean, base.strided.snanmean\n","base.strided.dnanmean.ndarray":"\nbase.strided.dnanmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.nanmean, base.strided.snanmean","base.strided.dnanmeanors":"\nbase.strided.dnanmeanors( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanors( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanmeanors( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanmeanors( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dnanmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanors, base.strided.dnanmean, base.strided.nanmeanors, base.strided.snanmeanors\n","base.strided.dnanmeanors.ndarray":"\nbase.strided.dnanmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanors, base.strided.dnanmean, base.strided.nanmeanors, base.strided.snanmeanors","base.strided.dnanmeanpn":"\nbase.strided.dnanmeanpn( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction\n    algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanpn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanmeanpn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanmeanpn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dnanmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction algorithm\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.dnanmean, base.strided.nanmeanpn, base.strided.snanmeanpn\n","base.strided.dnanmeanpn.ndarray":"\nbase.strided.dnanmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction algorithm\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.dnanmean, base.strided.nanmeanpn, base.strided.snanmeanpn","base.strided.dnanmeanpw":"\nbase.strided.dnanmeanpw( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanpw( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanmeanpw( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanmeanpw( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dnanmeanpw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using pairwise summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanpw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmeanpw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpw, base.strided.dnanmean\n","base.strided.dnanmeanpw.ndarray":"\nbase.strided.dnanmeanpw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using pairwise summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanpw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmeanpw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpw, base.strided.dnanmean","base.strided.dnanmeanwd":"\nbase.strided.dnanmeanwd( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, using Welford's algorithm and ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanwd( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanmeanwd( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanmeanwd( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dnanmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanwd, base.strided.dnanmean, base.strided.nanmeanwd, base.strided.snanmeanwd\n","base.strided.dnanmeanwd.ndarray":"\nbase.strided.dnanmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanwd, base.strided.dnanmean, base.strided.nanmeanwd, base.strided.snanmeanwd","base.strided.dnanmin":"\nbase.strided.dnanmin( N, x, strideX )\n    Computes the minimum value of a double-precision floating-point strided\n    array, ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmin( x.length, x, 1 )\n    -2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > base.strided.dnanmin( 3, x, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnanmin( 3, x1, 2 )\n    -2.0\n\n\nbase.strided.dnanmin.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a double-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.dnanmin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanmin.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dnanmax, base.strided.nanmin, base.strided.snanmin\n","base.strided.dnanmin.ndarray":"\nbase.strided.dnanmin.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a double-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.dnanmin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanmin.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dnanmax, base.strided.nanmin, base.strided.snanmin","base.strided.dnanminabs":"\nbase.strided.dnanminabs( N, x, strideX )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array, ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanminabs( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > base.strided.dnanminabs( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnanminabs( 3, x1, 2 )\n    1.0\n\n\nbase.strided.dnanminabs.ndarray( N, x, strideX, offsetX )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.dnanminabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanminabs.ndarray( 3, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dminabs, base.strided.dnanmaxabs, base.strided.dnanmin, base.strided.nanminabs, base.strided.snanminabs\n","base.strided.dnanminabs.ndarray":"\nbase.strided.dnanminabs.ndarray( N, x, strideX, offsetX )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.dnanminabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanminabs.ndarray( 3, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dminabs, base.strided.dnanmaxabs, base.strided.dnanmin, base.strided.nanminabs, base.strided.snanminabs","base.strided.dnanmskmax":"\nbase.strided.dnanmskmax( N, x, strideX, mask, strideMask )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n    > base.strided.dnanmskmax( x.length, x, 1, mask, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmskmax( N, x, 2, mask, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dnanmskmax( N, x1, 2, mask1, 2 )\n    2.0\n\nbase.strided.dnanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.dnanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmskmax, base.strided.dnanmax, base.strided.dnanmskmin, base.strided.nanmskmax, base.strided.snanmskmax\n","base.strided.dnanmskmax.ndarray":"\nbase.strided.dnanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.dnanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmskmax, base.strided.dnanmax, base.strided.dnanmskmin, base.strided.nanmskmax, base.strided.snanmskmax","base.strided.dnanmskmin":"\nbase.strided.dnanmskmin( N, x, strideX, mask, strideMask )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n    > base.strided.dnanmskmin( x.length, x, 1, mask, 1 )\n    -2.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmskmin( N, x, 2, mask, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dnanmskmin( N, x1, 2, mask1, 2 )\n    -2.0\n\nbase.strided.dnanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.dnanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmskmin, base.strided.dnanmin, base.strided.dnanmskmax, base.strided.nanmskmin, base.strided.snanmskmin\n","base.strided.dnanmskmin.ndarray":"\nbase.strided.dnanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.dnanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmskmin, base.strided.dnanmin, base.strided.dnanmskmax, base.strided.nanmskmin, base.strided.snanmskmin","base.strided.dnanmskrange":"\nbase.strided.dnanmskrange( N, x, strideX, mask, strideMask )\n    Computes the range of a double-precision floating-point strided array\n    according to a mask, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n    > base.strided.dnanmskrange( x.length, x, 1, mask, 1 )\n    4.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmskrange( N, x, 2, mask, 2 )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dnanmskrange( N, x1, 2, mask1, 2 )\n    4.0\n\nbase.strided.dnanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a double-precision floating-point strided array\n    according to a mask, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.dnanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dmskrange, base.strided.dnanrange, base.strided.dnanmskmax, base.strided.dnanmskmin, base.strided.nanmskrange, base.strided.snanmskrange\n","base.strided.dnanmskrange.ndarray":"\nbase.strided.dnanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a double-precision floating-point strided array\n    according to a mask, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.dnanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dmskrange, base.strided.dnanrange, base.strided.dnanmskmax, base.strided.dnanmskmin, base.strided.nanmskrange, base.strided.snanmskrange","base.strided.dnannsum":"\nbase.strided.dnannsum( N, x, strideX, out, strideOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns a sum equal to `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsum( x.length, x, 1, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsum( 4, x, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsum( 4, x1, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n\nbase.strided.dnannsum.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsum.ndarray( x.length, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsum.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.dsum","base.strided.dnannsum.ndarray":"\nbase.strided.dnannsum.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsum.ndarray( x.length, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsum.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.dsum","base.strided.dnannsumkbn":"\nbase.strided.dnannsumkbn( N, x, strideX, out, strideOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns a sum equal to `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn( x.length, x, 1, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn( 4, x, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn( 4, x1, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n\nbase.strided.dnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn.ndarray( 4, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsum, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn, base.strided.gnannsumkbn\n","base.strided.dnannsumkbn.ndarray":"\nbase.strided.dnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn.ndarray( 4, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsum, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn, base.strided.gnannsumkbn","base.strided.dnannsumkbn2":"\nbase.strided.dnannsumkbn2( N, x, strideX, out, strideOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm.\n\n    The `N` and stride parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns a sum equal to `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn2( x.length, x, 1, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn2( 4, x, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn2( 4, x1, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n\nbase.strided.dnannsumkbn2.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn2.ndarray( 4, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn2.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn2\n","base.strided.dnannsumkbn2.ndarray":"\nbase.strided.dnannsumkbn2.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn2.ndarray( 4, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn2.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn2","base.strided.dnannsumors":"\nbase.strided.dnannsumors( N, x, strideX, out, strideOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation.\n\n    The `N` and stride parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns a sum equal to `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumors( x.length, x, 1, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumors( 4, x, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumors( 4, x1, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n\nbase.strided.dnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumpw, base.strided.dsumors\n","base.strided.dnannsumors.ndarray":"\nbase.strided.dnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumpw, base.strided.dsumors","base.strided.dnannsumpw":"\nbase.strided.dnannsumpw( N, x, strideX, out, strideOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation.\n\n    The `N` and stride parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns a sum equal to `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumpw( x.length, x, 1, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumpw( 4, x, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumpw( 4, x1, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n\nbase.strided.dnannsumpw.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for the strided array.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumpw.ndarray( x.length, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumpw.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dsumpw\n","base.strided.dnannsumpw.ndarray":"\nbase.strided.dnannsumpw.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for the strided array.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumpw.ndarray( x.length, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumpw.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dsumpw","base.strided.dnanrange":"\nbase.strided.dnanrange( N, x, strideX )\n    Computes the range of a double-precision floating-point strided array,\n    ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanrange( x.length, x, 1 )\n    4.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > base.strided.dnanrange( 3, x, 2 )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnanrange( 3, x1, 2 )\n    4.0\n\n\nbase.strided.dnanrange.ndarray( N, x, strideX, offsetX )\n    Computes the range of a double-precision floating-point strided array,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.dnanrange.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanrange.ndarray( 3, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dnanmax, base.strided.dnanmin, base.strided.drange, base.strided.nanrange, base.strided.snanrange\n","base.strided.dnanrange.ndarray":"\nbase.strided.dnanrange.ndarray( N, x, strideX, offsetX )\n    Computes the range of a double-precision floating-point strided array,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.dnanrange.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanrange.ndarray( 3, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dnanmax, base.strided.dnanmin, base.strided.drange, base.strided.nanrange, base.strided.snanrange","base.strided.dnanstdev":"\nbase.strided.dnanstdev( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdev( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanstdev( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanstdev( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dnanstdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanvariance, base.strided.dstdev, base.strided.nanstdev, base.strided.snanstdev\n","base.strided.dnanstdev.ndarray":"\nbase.strided.dnanstdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanvariance, base.strided.dstdev, base.strided.nanstdev, base.strided.snanstdev","base.strided.dnanstdevch":"\nbase.strided.dnanstdevch( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevch( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanstdevch( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanstdevch( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dnanstdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dnanvariancech, base.strided.dstdevch, base.strided.nanstdevch, base.strided.snanstdevch\n","base.strided.dnanstdevch.ndarray":"\nbase.strided.dnanstdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dnanvariancech, base.strided.dstdevch, base.strided.nanstdevch, base.strided.snanstdevch","base.strided.dnanstdevpn":"\nbase.strided.dnanstdevpn( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevpn( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanstdevpn( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanstdevpn( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dnanstdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.snanstdevpn\n","base.strided.dnanstdevpn.ndarray":"\nbase.strided.dnanstdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.snanstdevpn","base.strided.dnanstdevtk":"\nbase.strided.dnanstdevtk( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevtk( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanstdevtk( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanstdevtk( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dnanstdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.snanstdevtk\n","base.strided.dnanstdevtk.ndarray":"\nbase.strided.dnanstdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.snanstdevtk","base.strided.dnanstdevwd":"\nbase.strided.dnanstdevwd( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevwd( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanstdevwd( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanstdevwd( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dnanstdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.snanstdevwd\n","base.strided.dnanstdevwd.ndarray":"\nbase.strided.dnanstdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.snanstdevwd","base.strided.dnanstdevyc":"\nbase.strided.dnanstdevyc( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass algorithm proposed by\n    Youngs and Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevyc( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanstdevyc( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanstdevyc( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dnanstdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass algorithm proposed by\n    Youngs and Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.snanstdevyc\n","base.strided.dnanstdevyc.ndarray":"\nbase.strided.dnanstdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass algorithm proposed by\n    Youngs and Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.snanstdevyc","base.strided.dnansum":"\nbase.strided.dnansum( N, x, strideX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansum( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansum( 4, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnansum( 4, x1, 2 )\n    -1.0\n\n\nbase.strided.dnansum.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansum.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.dsum, base.strided.snansum, base.strided.gnansum\n","base.strided.dnansum.ndarray":"\nbase.strided.dnansum.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansum.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.dsum, base.strided.snansum, base.strided.gnansum","base.strided.dnansumkbn":"\nbase.strided.dnansumkbn( N, x, strideX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumkbn( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumkbn( 4, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnansumkbn( 4, x1, 2 )\n    -1.0\n\n\nbase.strided.dnansumkbn.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumkbn.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.snansumkbn\n","base.strided.dnansumkbn.ndarray":"\nbase.strided.dnansumkbn.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumkbn.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.snansumkbn","base.strided.dnansumkbn2":"\nbase.strided.dnansumkbn2( N, x, strideX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm.\n\n    The `N` and stride parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumkbn2( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumkbn2( 4, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnansumkbn2( 4, x1, 2 )\n    -1.0\n\n\nbase.strided.dnansumkbn2.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumkbn2.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.snansumkbn2\n","base.strided.dnansumkbn2.ndarray":"\nbase.strided.dnansumkbn2.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumkbn2.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.snansumkbn2","base.strided.dnansumors":"\nbase.strided.dnansumors( N, x, strideX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumors( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumors( 4, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnansumors( 4, x1, 2 )\n    -1.0\n\n\nbase.strided.dnansumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumors.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumpw, base.strided.dsumors, base.strided.gnansumors, base.strided.snansumors\n","base.strided.dnansumors.ndarray":"\nbase.strided.dnansumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumors.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumpw, base.strided.dsumors, base.strided.gnansumors, base.strided.snansumors","base.strided.dnansumpw":"\nbase.strided.dnansumpw( N, x, strideX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumpw( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumpw( 4, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnansumpw( 4, x1, 2 )\n    -1.0\n\n\nbase.strided.dnansumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumpw.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumors, base.strided.dsumpw, base.strided.gnansumpw, base.strided.snansumpw\n","base.strided.dnansumpw.ndarray":"\nbase.strided.dnansumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumpw.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumors, base.strided.dsumpw, base.strided.gnansumpw, base.strided.snansumpw","base.strided.dnanvariance":"\nbase.strided.dnanvariance( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariance( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanvariance( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanvariance( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dnanvariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dvariance, base.strided.nanvariance, base.strided.snanvariance\n","base.strided.dnanvariance.ndarray":"\nbase.strided.dnanvariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dvariance, base.strided.nanvariance, base.strided.snanvariance","base.strided.dnanvariancech":"\nbase.strided.dnanvariancech( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancech( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanvariancech( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanvariancech( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dnanvariancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvariancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancech, base.strided.dnanvariance, base.strided.nanvariancech, base.strided.snanvariancech\n","base.strided.dnanvariancech.ndarray":"\nbase.strided.dnanvariancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvariancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancech, base.strided.dnanvariance, base.strided.nanvariancech, base.strided.snanvariancech","base.strided.dnanvariancepn":"\nbase.strided.dnanvariancepn( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancepn( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanvariancepn( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanvariancepn( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dnanvariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancepn, base.strided.dnanvariance, base.strided.nanvariancepn, base.strided.snanvariancepn\n","base.strided.dnanvariancepn.ndarray":"\nbase.strided.dnanvariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancepn, base.strided.dnanvariance, base.strided.nanvariancepn, base.strided.snanvariancepn","base.strided.dnanvariancetk":"\nbase.strided.dnanvariancetk( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancetk( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanvariancetk( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanvariancetk( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dnanvariancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvariancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancetk, base.strided.dnanvariance, base.strided.nanvariancetk, base.strided.snanvariancetk\n","base.strided.dnanvariancetk.ndarray":"\nbase.strided.dnanvariancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvariancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancetk, base.strided.dnanvariance, base.strided.nanvariancetk, base.strided.snanvariancetk","base.strided.dnanvariancewd":"\nbase.strided.dnanvariancewd( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancewd( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanvariancewd( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanvariancewd( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dnanvariancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using Welford's algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvariancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancewd, base.strided.dnanvariance, base.strided.nanvariancewd, base.strided.snanvariancewd\n","base.strided.dnanvariancewd.ndarray":"\nbase.strided.dnanvariancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using Welford's algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvariancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancewd, base.strided.dnanvariance, base.strided.nanvariancewd, base.strided.snanvariancewd","base.strided.dnanvarianceyc":"\nbase.strided.dnanvarianceyc( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n    Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvarianceyc( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanvarianceyc( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanvarianceyc( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dnanvarianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n    Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvarianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvarianceyc, base.strided.dnanvariance, base.strided.nanvarianceyc, base.strided.snanvarianceyc\n","base.strided.dnanvarianceyc.ndarray":"\nbase.strided.dnanvarianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n    Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvarianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvarianceyc, base.strided.dnanvariance, base.strided.nanvarianceyc, base.strided.snanvarianceyc","base.strided.dnrm2":"\nbase.strided.dnrm2( N, x, stride )\n    Computes the L2-norm of a double-precision floating-point vector.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    nrm2: number\n        The L2-norm.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dnrm2( x.length, x, 1 )\n    3.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dnrm2( 3, x, 2 )\n    3.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnrm2( 3, x1, 2 )\n    3.0\n\n\nbase.strided.dnrm2.ndarray( N, x, stride, offset )\n    Computes the L2-norm of a double-precision floating-point vector using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    nrm2: number\n        The L2-norm.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dnrm2.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dnrm2.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.gnrm2, base.strided.snrm2\n","base.strided.dnrm2.ndarray":"\nbase.strided.dnrm2.ndarray( N, x, stride, offset )\n    Computes the L2-norm of a double-precision floating-point vector using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    nrm2: number\n        The L2-norm.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dnrm2.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dnrm2.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.gnrm2, base.strided.snrm2","base.strided.dramp":"\nbase.strided.dramp( N, x, strideX, y, strideY )\n    Evaluates the ramp function for each element in a double-precision floating-\n    point strided array `x` and assigns the results to elements in a double-\n    precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dramp( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.1, 2.5, 0.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dramp( N, x, 2, y, -1 )\n    <Float64Array>[ 0.0, 1.1, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dramp( N, x1, -2, y1, 1 )\n    <Float64Array>[ 4.0, 2.5 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.5 ]\n\n\nbase.strided.dramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Evaluates the ramp function for each element in a double-precision floating-\n    point strided array `x` and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.1, 2.5, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.5 ]\n\n    See Also\n    --------\n    strided.ramp, base.strided.sramp\n","base.strided.dramp.ndarray":"\nbase.strided.dramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Evaluates the ramp function for each element in a double-precision floating-\n    point strided array `x` and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.1, 2.5, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.5 ]\n\n    See Also\n    --------\n    strided.ramp, base.strided.sramp","base.strided.drange":"\nbase.strided.drange( N, x, strideX )\n    Computes the range of a double-precision floating-point strided array.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.drange( x.length, x, 1 )\n    4.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.drange( 3, x, 2 )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > stride = 2;\n    > base.strided.drange( 3, x1, 2 )\n    4.0\n\n\nbase.strided.drange.ndarray( N, x, strideX, offsetX )\n    Computes the range of a double-precision floating-point strided array using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.drange.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.drange.ndarray( 3, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dmin, base.strided.dnanrange, base.strided.range, base.strided.srange\n","base.strided.drange.ndarray":"\nbase.strided.drange.ndarray( N, x, strideX, offsetX )\n    Computes the range of a double-precision floating-point strided array using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.drange.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.drange.ndarray( 3, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dmin, base.strided.dnanrange, base.strided.range, base.strided.srange","base.strided.drev":"\nbase.strided.drev( N, x, strideX )\n    Reverses a double-precision floating-point strided array in-place.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.drev( x.length, x, 1 )\n    <Float64Array>[ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.drev( 3, x, 2 )\n    <Float64Array>[ 4.0, 1.0, 3.0, -5.0, -2.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.drev( 3, x1, 2 )\n    <Float64Array>[ -6.0, 3.0, -4.0, 5.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n\nbase.strided.drev.ndarray( N, x, strideX, offsetX )\n    Reverses a double-precision floating-point strided array in-place using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.drev.ndarray( x.length, x, 1, 0 )\n    <Float64Array>[ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.drev.ndarray( 3, x, 2, 1 )\n    <Float64Array>[ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.grev, base.strided.srev\n","base.strided.drev.ndarray":"\nbase.strided.drev.ndarray( N, x, strideX, offsetX )\n    Reverses a double-precision floating-point strided array in-place using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.drev.ndarray( x.length, x, 1, 0 )\n    <Float64Array>[ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.drev.ndarray( 3, x, 2, 1 )\n    <Float64Array>[ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.grev, base.strided.srev","base.strided.drsqrt":"\nbase.strided.drsqrt( N, x, strideX, y, strideY )\n    Computes the reciprocal square root for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.drsqrt( x.length, x, 1, y, 1 )\n    <Float64Array>[ Infinity, 0.5, ~0.333, ~0.289 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.drsqrt( N, x, 2, y, -1 )\n    <Float64Array>[ ~0.333, Infinity, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.drsqrt( N, x1, -2, y1, 1 )\n    <Float64Array>[ ~0.289, 0.5 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.drsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the reciprocal square root for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.drsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ Infinity, 0.5, ~0.333, ~0.289 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.drsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n    See Also\n    --------\n    base.strided.dsqrt, strided.rsqrt, base.strided.srsqrt\n","base.strided.drsqrt.ndarray":"\nbase.strided.drsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the reciprocal square root for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.drsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ Infinity, 0.5, ~0.333, ~0.289 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.drsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n    See Also\n    --------\n    base.strided.dsqrt, strided.rsqrt, base.strided.srsqrt","base.strided.dsapxsum":"\nbase.strided.dsapxsum( N, alpha, x, strideX )\n    Adds a scalar constant to each single-precision floating-point strided array\n    element, and computes the sum using extended accumulation and returning\n    an extended precision result.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsapxsum( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dsapxsum( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsapxsum( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.dsapxsum.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each single-precision floating-point strided array\n    element, and computes the sum using pairwise summation with extended\n    accumulation and alternative indexing semantics and returning an extended\n    precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.dssum, base.strided.sapxsum\n","base.strided.dsapxsum.ndarray":"\nbase.strided.dsapxsum.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each single-precision floating-point strided array\n    element, and computes the sum using pairwise summation with extended\n    accumulation and alternative indexing semantics and returning an extended\n    precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.dssum, base.strided.sapxsum","base.strided.dsapxsumpw":"\nbase.strided.dsapxsumpw( N, alpha, x, strideX )\n    Adds a constant to each single-precision floating-point strided array\n    element, and computes the sum using pairwise summation with extended\n    accumulation and returning an extended precision result.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsapxsumpw( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dsapxsumpw( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsapxsumpw( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.dsapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a constant to each single-precision floating-point strided array\n    element, and computes the sum using pairwise summation with extended\n    accumulation and alternative indexing semantics and returning an extended\n    precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumpw, base.strided.dsapxsum, base.strided.dssumpw, base.strided.sapxsumpw\n","base.strided.dsapxsumpw.ndarray":"\nbase.strided.dsapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a constant to each single-precision floating-point strided array\n    element, and computes the sum using pairwise summation with extended\n    accumulation and alternative indexing semantics and returning an extended\n    precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumpw, base.strided.dsapxsum, base.strided.dssumpw, base.strided.sapxsumpw","base.strided.dscal":"\nbase.strided.dscal( N, alpha, x, stride )\n    Multiplies a double-precision floating-point vector `x` by a constant\n    `alpha`.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dscal( x.length, 5.0, x, 1 )\n    <Float64Array>[ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dscal( 3, 5.0, x, 2 )\n    <Float64Array>[ -10.0, 1.0, 15.0, -5.0, 20.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dscal( 3, 5.0, x1, 2 )\n    <Float64Array>[ -10.0, 3.0, -20.0, 5.0, -30.0 ]\n    > x0\n    <Float64Array>[ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n\nbase.strided.dscal.ndarray( N, alpha, x, stride, offset )\n    Multiplies a double-precision floating-point vector `x` by a constant\n    `alpha` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dscal.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float64Array>[ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.dscal.ndarray( 3, 5.0, x, 2, 1 )\n    <Float64Array>[ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n    See Also\n    --------\n    base.strided.daxpy, base.strided.gscal, base.strided.sscal, base.strided.saxpy\n","base.strided.dscal.ndarray":"\nbase.strided.dscal.ndarray( N, alpha, x, stride, offset )\n    Multiplies a double-precision floating-point vector `x` by a constant\n    `alpha` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dscal.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float64Array>[ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.dscal.ndarray( 3, 5.0, x, 2, 1 )\n    <Float64Array>[ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n    See Also\n    --------\n    base.strided.daxpy, base.strided.gscal, base.strided.sscal, base.strided.saxpy","base.strided.dsdot":"\nbase.strided.dsdot( N, x, strideX, y, strideY )\n    Computes the dot product of two single-precision floating-point vectors with\n    extended accumulation and result.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0` the function returns `0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    dot: number\n        Dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var dot = base.strided.dsdot( x.length, x, 1, y, 1 )\n    -5.0\n\n    // Strides:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > dot = base.strided.dsdot( 3, x, 2, y, -1 )\n    9.0\n\n    // Using view offsets:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n    > dot = base.strided.dsdot( 3, x1, -2, y1, 1 )\n    128.0\n\n\nbase.strided.dsdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the dot product of two single-precision floating-point vectors\n    using alternative indexing semantics and with extended accumulation and\n    result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing based on a starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    dot: number\n        Dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var dot = base.strided.dsdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    -5.0\n\n    // Strides:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > dot = base.strided.dsdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n    9.0\n\n    // Using offset indices:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > dot = base.strided.dsdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n    128.0\n\n    References\n    ----------\n    - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n    Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n    Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n    NY, USA: Association for Computing Machinery: 324–25.\n    doi:10.1145/355841.355848.\n\n    See Also\n    --------\n    base.strided.ddot, base.strided.sdot, base.strided.sdsdot\n","base.strided.dsdot.ndarray":"\nbase.strided.dsdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the dot product of two single-precision floating-point vectors\n    using alternative indexing semantics and with extended accumulation and\n    result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing based on a starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    dot: number\n        Dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var dot = base.strided.dsdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    -5.0\n\n    // Strides:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > dot = base.strided.dsdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n    9.0\n\n    // Using offset indices:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > dot = base.strided.dsdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n    128.0\n\n    References\n    ----------\n    - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n    Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n    Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n    NY, USA: Association for Computing Machinery: 324–25.\n    doi:10.1145/355841.355848.\n\n    See Also\n    --------\n    base.strided.ddot, base.strided.sdot, base.strided.sdsdot","base.strided.dsem":"\nbase.strided.dsem( N, correction, x, stride )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsem( x.length, 1, x, 1 )\n    ~1.20185\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsem( N, 1, x, stride )\n    ~1.20185\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsem( N, 1, x1, stride )\n    ~1.20185\n\nbase.strided.dsem.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsem.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsem.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dstdev\n","base.strided.dsem.ndarray":"\nbase.strided.dsem.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsem.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsem.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dstdev","base.strided.dsemch":"\nbase.strided.dsemch( N, correction, x, stride )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemch( x.length, 1, x, 1 )\n    ~1.20185\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsemch( N, 1, x, stride )\n    ~1.20185\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsemch( N, 1, x1, stride )\n    ~1.20185\n\nbase.strided.dsemch.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass trial mean algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemch.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsemch.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dsem, base.strided.dstdevch\n","base.strided.dsemch.ndarray":"\nbase.strided.dsemch.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass trial mean algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemch.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsemch.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dsem, base.strided.dstdevch","base.strided.dsempn":"\nbase.strided.dsempn( N, correction, x, stride )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsempn( x.length, 1, x, 1 )\n    ~1.20185\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsempn( N, 1, x, stride )\n    ~1.20185\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsempn( N, 1, x1, stride )\n    ~1.20185\n\nbase.strided.dsempn.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a two-pass algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsempn.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsempn.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dsem, base.strided.dstdevpn\n","base.strided.dsempn.ndarray":"\nbase.strided.dsempn.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a two-pass algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsempn.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsempn.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dsem, base.strided.dstdevpn","base.strided.dsemtk":"\nbase.strided.dsemtk( N, correction, x, stride )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemtk( x.length, 1, x, 1 )\n    ~1.20185\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsemtk( N, 1, x, stride )\n    ~1.20185\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsemtk( N, 1, x1, stride )\n    ~1.20185\n\nbase.strided.dsemtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass textbook algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemtk.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsemtk.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dsem, base.strided.dstdevtk\n","base.strided.dsemtk.ndarray":"\nbase.strided.dsemtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass textbook algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemtk.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsemtk.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dsem, base.strided.dstdevtk","base.strided.dsemwd":"\nbase.strided.dsemwd( N, correction, x, stride )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemwd( x.length, 1, x, 1 )\n    ~1.20185\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsemwd( N, 1, x, stride )\n    ~1.20185\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsemwd( N, 1, x1, stride )\n    ~1.20185\n\nbase.strided.dsemwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using Welford's algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemwd.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsemwd.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dsem, base.strided.dstdevwd\n","base.strided.dsemwd.ndarray":"\nbase.strided.dsemwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using Welford's algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemwd.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsemwd.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dsem, base.strided.dstdevwd","base.strided.dsemyc":"\nbase.strided.dsemyc( N, correction, x, stride )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass algorithm proposed by Youngs and\n    Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemyc( x.length, 1, x, 1 )\n    ~1.20185\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsemyc( N, 1, x, stride )\n    ~1.20185\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsemyc( N, 1, x1, stride )\n    ~1.20185\n\nbase.strided.dsemyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass algorithm proposed by Youngs and Cramer\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemyc.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsemyc.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dsem, base.strided.dstdevyc\n","base.strided.dsemyc.ndarray":"\nbase.strided.dsemyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass algorithm proposed by Youngs and Cramer\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemyc.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsemyc.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dsem, base.strided.dstdevyc","base.strided.dsmean":"\nbase.strided.dsmean( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using extended accumulation and returning an extended precision\n    result.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmean( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsmean( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsmean( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dsmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using extended accumulation and alternative indexing semantics and\n    returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dsnanmean, base.strided.mean, base.strided.sdsmean, base.strided.smean\n","base.strided.dsmean.ndarray":"\nbase.strided.dsmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using extended accumulation and alternative indexing semantics and\n    returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dsnanmean, base.strided.mean, base.strided.sdsmean, base.strided.smean","base.strided.dsmeanors":"\nbase.strided.dsmeanors( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation with extended accumulation and\n    returning an extended precision result.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanors( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsmeanors( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsmeanors( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dsmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation with extended accumulation and\n    alternative indexing semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanors, base.strided.dsmean, base.strided.dsnanmeanors, base.strided.meanors, base.strided.smeanors\n","base.strided.dsmeanors.ndarray":"\nbase.strided.dsmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation with extended accumulation and\n    alternative indexing semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanors, base.strided.dsmean, base.strided.dsnanmeanors, base.strided.meanors, base.strided.smeanors","base.strided.dsmeanpn":"\nbase.strided.dsmeanpn( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a two-pass error correction algorithm with extended accumulation\n    and returning an extended precision result.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanpn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsmeanpn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsmeanpn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dsmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a two-pass error correction algorithm with extended accumulation\n    and alternative indexing semantics and returning an extended precision\n    result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.dsmean, base.strided.dsnanmeanpn, base.strided.meanpn, base.strided.smeanpn\n","base.strided.dsmeanpn.ndarray":"\nbase.strided.dsmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a two-pass error correction algorithm with extended accumulation\n    and alternative indexing semantics and returning an extended precision\n    result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.dsmean, base.strided.dsnanmeanpn, base.strided.meanpn, base.strided.smeanpn","base.strided.dsmeanpw":"\nbase.strided.dsmeanpw( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using pairwise summation with extended accumulation and returning an\n    extended precision result.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanpw( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsmeanpw( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsmeanpw( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dsmeanpw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using pairwise summation with extended accumulation and alternative\n    indexing semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanpw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsmeanpw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpw, base.strided.dsmean, base.strided.meanpw, base.strided.smeanpw\n","base.strided.dsmeanpw.ndarray":"\nbase.strided.dsmeanpw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using pairwise summation with extended accumulation and alternative\n    indexing semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanpw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsmeanpw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpw, base.strided.dsmean, base.strided.meanpw, base.strided.smeanpw","base.strided.dsmeanwd":"\nbase.strided.dsmeanwd( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using Welford's algorithm with extended accumulation and returning an\n    extended precision result.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanwd( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsmeanwd( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsmeanwd( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dsmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using Welford's algorithm with extended accumulation and alternative\n    indexing semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanwd, base.strided.dsmean, base.strided.dsnanmeanwd, base.strided.meanwd, base.strided.smeanwd\n","base.strided.dsmeanwd.ndarray":"\nbase.strided.dsmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using Welford's algorithm with extended accumulation and alternative\n    indexing semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanwd, base.strided.dsmean, base.strided.dsnanmeanwd, base.strided.meanwd, base.strided.smeanwd","base.strided.dsnanmean":"\nbase.strided.dsnanmean( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values, using extended accumulation, and returning an\n    extended precision result.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmean( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsnanmean( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsnanmean( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dsnanmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using extended accumulation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsnanmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.dsmean, base.strided.nanmean, base.strided.sdsnanmean, base.strided.snanmean\n","base.strided.dsnanmean.ndarray":"\nbase.strided.dsnanmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using extended accumulation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsnanmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.dsmean, base.strided.nanmean, base.strided.sdsnanmean, base.strided.snanmean","base.strided.dsnanmeanors":"\nbase.strided.dsnanmeanors( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values, using ordinary recursive summation with\n    extended accumulation, and returning an extended precision result.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmeanors( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsnanmeanors( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsnanmeanors( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dsnanmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation with\n    extended accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsnanmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanors, base.strided.dsmeanors, base.strided.dsnanmean, base.strided.nanmeanors, base.strided.sdsnanmean, base.strided.snanmeanors\n","base.strided.dsnanmeanors.ndarray":"\nbase.strided.dsnanmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation with\n    extended accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsnanmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanors, base.strided.dsmeanors, base.strided.dsnanmean, base.strided.nanmeanors, base.strided.sdsnanmean, base.strided.snanmeanors","base.strided.dsnanmeanpn":"\nbase.strided.dsnanmeanpn( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values, using a two-pass error correction algorithm\n    with extended accumulation, and returning an extended precision result.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmeanpn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsnanmeanpn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsnanmeanpn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dsnanmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction algorithm\n    with extended accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsnanmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanpn, base.strided.dsmeanpn, base.strided.dsnanmean, base.strided.nanmeanpn, base.strided.sdsnanmean, base.strided.snanmeanpn\n","base.strided.dsnanmeanpn.ndarray":"\nbase.strided.dsnanmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction algorithm\n    with extended accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsnanmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanpn, base.strided.dsmeanpn, base.strided.dsnanmean, base.strided.nanmeanpn, base.strided.sdsnanmean, base.strided.snanmeanpn","base.strided.dsnanmeanwd":"\nbase.strided.dsnanmeanwd( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values, using Welford's algorithm with extended\n    accumulation, and returning an extended precision result.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmeanwd( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsnanmeanwd( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsnanmeanwd( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dsnanmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm with extended\n    accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsnanmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanwd, base.strided.dsmeanwd, base.strided.dsnanmean, base.strided.nanmeanwd, base.strided.sdsnanmean, base.strided.snanmeanwd\n","base.strided.dsnanmeanwd.ndarray":"\nbase.strided.dsnanmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm with extended\n    accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsnanmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanwd, base.strided.dsmeanwd, base.strided.dsnanmean, base.strided.nanmeanwd, base.strided.sdsnanmean, base.strided.snanmeanwd","base.strided.dsnannsumors":"\nbase.strided.dsnannsumors( N, x, strideX, out, strideOut )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using ordinary recursive summation with extended\n    accumulation, and returning an extended precision result.\n\n    The `N` and stride parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns a sum equal to `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dsnannsumors( x.length, x, 1, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dsnannsumors( 4, x, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dsnannsumors( N, x1, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n\nbase.strided.dsnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using ordinary recursive summation with extended\n    accumulation and alternative indexing semantics, and returning an extended\n    precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dsnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dsnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsumors, base.strided.dsnansumors, base.strided.dssumors\n","base.strided.dsnannsumors.ndarray":"\nbase.strided.dsnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using ordinary recursive summation with extended\n    accumulation and alternative indexing semantics, and returning an extended\n    precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dsnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dsnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsumors, base.strided.dsnansumors, base.strided.dssumors","base.strided.dsnansum":"\nbase.strided.dsnansum( N, x, strideX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using extended accumulation, and returning an\n    extended precision result.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnansum( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.dsnansum( 4, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsnansum( 4, x1, 2 )\n    -1.0\n\n\nbase.strided.dsnansum.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using extended accumulation and alternative\n    indexing semantics, and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnansum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsnansum.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnanmean, base.strided.dssum, base.strided.sdsnansum, base.strided.snansum\n","base.strided.dsnansum.ndarray":"\nbase.strided.dsnansum.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using extended accumulation and alternative\n    indexing semantics, and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnansum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsnansum.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnanmean, base.strided.dssum, base.strided.sdsnansum, base.strided.snansum","base.strided.dsnansumors":"\nbase.strided.dsnansumors( N, x, strideX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using ordinary recursive summation with extended\n    accumulation, and returning an extended precision result.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnansumors( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.dsnansumors( 4, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsnansumors( 4, x1, 2 )\n    -1.0\n\n\nbase.strided.dsnansumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation with extended\n    accumulation and alternative indexing semantics, and returning an extended\n    precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnansumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dsnansumors.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnanmeanors, base.strided.dssum, base.strided.dssumors, base.strided.snansumors\n","base.strided.dsnansumors.ndarray":"\nbase.strided.dsnansumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation with extended\n    accumulation and alternative indexing semantics, and returning an extended\n    precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnansumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dsnansumors.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnanmeanors, base.strided.dssum, base.strided.dssumors, base.strided.snansumors","base.strided.dsnansumpw":"\nbase.strided.dsnansumpw( N, x, strideX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using pairwise summation with extended accumulation,\n    and returning an extended precision result.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnansumpw( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.dsnansumpw( 4, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsnansumpw( 4, x1, 2 )\n    -1.0\n\n\nbase.strided.dsnansumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using pairwise summation with extended accumulation\n    and alternative indexing semantics, and returning an extended precision\n    result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnansumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dsnansumpw.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumpw, base.strided.dssum, base.strided.dssumpw, base.strided.snansumpw\n","base.strided.dsnansumpw.ndarray":"\nbase.strided.dsnansumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using pairwise summation with extended accumulation\n    and alternative indexing semantics, and returning an extended precision\n    result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnansumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dsnansumpw.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumpw, base.strided.dssum, base.strided.dssumpw, base.strided.snansumpw","base.strided.dsort2hp":"\nbase.strided.dsort2hp( N, order, x, strideX, y, strideY )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using heapsort.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided arrays are sorted *in-place* (i.e., the input strided\n    arrays are *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2hp( x.length, 1, x, 1, y, 1 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float64Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsort2hp( N, -1, x, 2, y, 2 )\n    <Float64Array>[ 3.0, -2.0, 1.0, -4.0 ]\n    > y\n    <Float64Array>[ 2.0, 1.0, 0.0, 3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dsort2hp( N, 1, x1, 2, y1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.dsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using heapsort and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float64Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssort2hp\n","base.strided.dsort2hp.ndarray":"\nbase.strided.dsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using heapsort and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float64Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssort2hp","base.strided.dsort2ins":"\nbase.strided.dsort2ins( N, order, x, strideX, y, strideY )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using insertion sort.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^2).\n\n    The algorithm is efficient for *small* strided arrays (typically N <= 20)\n    and is particularly efficient for sorting strided arrays which are already\n    substantially sorted.\n\n    The algorithm is *stable*, meaning that the algorithm does *not* change the\n    order of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided arrays are sorted *in-place* (i.e., the input strided\n    arrays is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2ins( x.length, 1, x, 1, y, 1 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float64Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2ins( 2, -1, x, 2, y, 2 )\n    <Float64Array>[ 3.0, -2.0, 1.0, -4.0 ]\n    > y\n    <Float64Array>[ 2.0, 1.0, 0.0, 3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsort2ins( 2, 1, x1, 2, y1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.dsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using insertion sort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float64Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsortins, base.strided.gsort2ins, base.strided.ssort2ins\n","base.strided.dsort2ins.ndarray":"\nbase.strided.dsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using insertion sort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float64Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsortins, base.strided.gsort2ins, base.strided.ssort2ins","base.strided.dsort2sh":"\nbase.strided.dsort2sh( N, order, x, strideX, y, strideY )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using Shellsort.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^(4/3)).\n\n    The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided arrays are sorted *in-place* (i.e., the input strided\n    arrays are *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2sh( x.length, 1, x, 1, y, 1 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float64Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsort2sh( N, -1, x, 2, y, 2 )\n    <Float64Array>[ 3.0, -2.0, 1.0, -4.0 ]\n    > y\n    <Float64Array>[ 2.0, 1.0, 0.0, 3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dsort2sh( N, 1, x1, 2, y1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.dsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using Shellsort and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float64Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssort2sh\n","base.strided.dsort2sh.ndarray":"\nbase.strided.dsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using Shellsort and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float64Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssort2sh","base.strided.dsorthp":"\nbase.strided.dsorthp( N, order, x, stride )\n    Sorts a double-precision floating-point strided array using heapsort.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided array is sorted *in-place* (i.e., the input strided array\n    is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.dsorthp( x.length, 1, x, 1 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsorthp( N, -1, x, 2 )\n    <Float64Array>[ 3.0, -2.0, 1.0, -4.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dsorthp( N, 1, x1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.dsorthp.ndarray( N, order, x, stride, offset )\n    Sorts a double-precision floating-point strided array using heapsort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.dsorthp.ndarray( x.length, 1, x, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsorthp.ndarray( N, 1, x, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssorthp\n","base.strided.dsorthp.ndarray":"\nbase.strided.dsorthp.ndarray( N, order, x, stride, offset )\n    Sorts a double-precision floating-point strided array using heapsort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.dsorthp.ndarray( x.length, 1, x, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsorthp.ndarray( N, 1, x, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssorthp","base.strided.dsortins":"\nbase.strided.dsortins( N, order, x, stride )\n    Sorts a double-precision floating-point strided array using insertion sort.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^2).\n\n    The algorithm is efficient for *small* strided arrays (typically N <= 20)\n    and is particularly efficient for sorting strided arrays which are already\n    substantially sorted.\n\n    The algorithm is *stable*, meaning that the algorithm does *not* change the\n    order of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided array is sorted *in-place* (i.e., the input strided array\n    is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.dsortins( x.length, 1, x, 1 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsortins( N, -1, x, 2 )\n    <Float64Array>[ 3.0, -2.0, 1.0, -4.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dsortins( N, 1, x1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.dsortins.ndarray( N, order, x, stride, offset )\n    Sorts a double-precision floating-point strided array using insertion sort\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.dsortins.ndarray( x.length, 1, x, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsortins.ndarray( N, 1, x, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2ins, base.strided.gsortins, base.strided.ssortins\n","base.strided.dsortins.ndarray":"\nbase.strided.dsortins.ndarray( N, order, x, stride, offset )\n    Sorts a double-precision floating-point strided array using insertion sort\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.dsortins.ndarray( x.length, 1, x, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsortins.ndarray( N, 1, x, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2ins, base.strided.gsortins, base.strided.ssortins","base.strided.dsortsh":"\nbase.strided.dsortsh( N, order, x, stride )\n    Sorts a double-precision floating-point strided array using Shellsort.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^(4/3)).\n\n    The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided array is sorted *in-place* (i.e., the input strided array\n    is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.dsortsh( x.length, 1, x, 1 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsortsh( N, -1, x, 2 )\n    <Float64Array>[ 3.0, -2.0, 1.0, -4.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dsortsh( N, 1, x1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.dsortsh.ndarray( N, order, x, stride, offset )\n    Sorts a double-precision floating-point strided array using Shellsort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.dsortsh.ndarray( x.length, 1, x, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsortsh.ndarray( N, 1, x, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssortsh\n","base.strided.dsortsh.ndarray":"\nbase.strided.dsortsh.ndarray( N, order, x, stride, offset )\n    Sorts a double-precision floating-point strided array using Shellsort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.dsortsh.ndarray( x.length, 1, x, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsortsh.ndarray( N, 1, x, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssortsh","base.strided.dsqrt":"\nbase.strided.dsqrt( N, x, strideX, y, strideY )\n    Computes the principal square root for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dsqrt( x.length, x, 1, y, 1 )\n    <Float64Array>[ 0.0, 2.0, 3.0, ~3.464 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dsqrt( N, x, 2, y, -1 )\n    <Float64Array>[ 3.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dsqrt( N, x1, -2, y1, 1 )\n    <Float64Array>[ ~3.464, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.dsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the principal square root for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, 2.0, 3.0, ~3.464 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dcbrt, base.strided.drsqrt, strided.sqrt, base.strided.ssqrt\n","base.strided.dsqrt.ndarray":"\nbase.strided.dsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the principal square root for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, 2.0, 3.0, ~3.464 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dcbrt, base.strided.drsqrt, strided.sqrt, base.strided.ssqrt","base.strided.dssum":"\nbase.strided.dssum( N, x, strideX )\n    Computes the sum of single-precision floating-point strided array elements\n    using extended accumulation and returning an extended precision result.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dssum( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dssum( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dssum( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.dssum.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements\n    using extended accumulation and alternative indexing semantics and returning\n    an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dssum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dssum.ndarray(3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnansum, base.strided.sdssum, base.strided.ssum, base.strided.dsmean\n","base.strided.dssum.ndarray":"\nbase.strided.dssum.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements\n    using extended accumulation and alternative indexing semantics and returning\n    an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dssum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dssum.ndarray(3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnansum, base.strided.sdssum, base.strided.ssum, base.strided.dsmean","base.strided.dssumors":"\nbase.strided.dssumors( N, x, strideX )\n    Computes the sum of single-precision floating-point strided array elements\n    using ordinary recursive summation with extended accumulation and returning\n    an extended precision result.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dssumors( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dssumors( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dssumors( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.dssumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements\n    using ordinary recursive summation with extended accumulation and\n    alternative indexing semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dssumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dssumors.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnansumors, base.strided.dssum, base.strided.dsumors, base.strided.ssumors\n","base.strided.dssumors.ndarray":"\nbase.strided.dssumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements\n    using ordinary recursive summation with extended accumulation and\n    alternative indexing semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dssumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dssumors.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnansumors, base.strided.dssum, base.strided.dsumors, base.strided.ssumors","base.strided.dssumpw":"\nbase.strided.dssumpw( N, x, strideX )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation with extended accumulation and returning an\n    extended precision result.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dssumpw( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dssumpw( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dssumpw( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.dssumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation with extended accumulation and alternative indexing\n    semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dssumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dssumpw.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnansumpw, base.strided.dssum, base.strided.dsumpw, base.strided.ssumpw\n","base.strided.dssumpw.ndarray":"\nbase.strided.dssumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation with extended accumulation and alternative indexing\n    semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dssumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dssumpw.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnansumpw, base.strided.dssum, base.strided.dsumpw, base.strided.ssumpw","base.strided.dstdev":"\nbase.strided.dstdev( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdev( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dstdev( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dstdev( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dstdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dvariance, base.strided.sstdev, base.strided.stdev\n","base.strided.dstdev.ndarray":"\nbase.strided.dstdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dvariance, base.strided.sstdev, base.strided.stdev","base.strided.dstdevch":"\nbase.strided.dstdevch( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevch( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dstdevch( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dstdevch( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dstdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevch, base.strided.dstdev, base.strided.dvariancech, base.strided.sstdevch, base.strided.stdevch\n","base.strided.dstdevch.ndarray":"\nbase.strided.dstdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevch, base.strided.dstdev, base.strided.dvariancech, base.strided.sstdevch, base.strided.stdevch","base.strided.dstdevpn":"\nbase.strided.dstdevpn( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevpn( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dstdevpn( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dstdevpn( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dstdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevpn, base.strided.dstdev, base.strided.dvariancepn, base.strided.sstdevpn, base.strided.stdevpn\n","base.strided.dstdevpn.ndarray":"\nbase.strided.dstdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevpn, base.strided.dstdev, base.strided.dvariancepn, base.strided.sstdevpn, base.strided.stdevpn","base.strided.dstdevtk":"\nbase.strided.dstdevtk( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevtk( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dstdevtk( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dstdevtk( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dstdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass textbook algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevtk, base.strided.dstdev, base.strided.dvariancetk, base.strided.sstdevtk, base.strided.stdevtk\n","base.strided.dstdevtk.ndarray":"\nbase.strided.dstdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass textbook algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevtk, base.strided.dstdev, base.strided.dvariancetk, base.strided.sstdevtk, base.strided.stdevtk","base.strided.dstdevwd":"\nbase.strided.dstdevwd( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevwd( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dstdevwd( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dstdevwd( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dstdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevwd, base.strided.dstdev, base.strided.dvariancewd, base.strided.sstdevwd, base.strided.stdevwd\n","base.strided.dstdevwd.ndarray":"\nbase.strided.dstdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevwd, base.strided.dstdev, base.strided.dvariancewd, base.strided.sstdevwd, base.strided.stdevwd","base.strided.dstdevyc":"\nbase.strided.dstdevyc( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevyc( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dstdevyc( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dstdevyc( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dstdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevyc, base.strided.dstdev, base.strided.dvarianceyc, base.strided.sstdevyc, base.strided.stdevyc\n","base.strided.dstdevyc.ndarray":"\nbase.strided.dstdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevyc, base.strided.dstdev, base.strided.dvarianceyc, base.strided.sstdevyc, base.strided.stdevyc","base.strided.dsum":"\nbase.strided.dsum( N, x, stride )\n    Computes the sum of double-precision floating-point strided array elements.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsum( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dsum( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsum( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.dsum.ndarray( N, x, stride, offset )\n    Computes the sum of double-precision floating-point strided array elements\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsum.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.dmean, base.strided.dnansum, base.strided.ssum, base.strided.gsum\n","base.strided.dsum.ndarray":"\nbase.strided.dsum.ndarray( N, x, stride, offset )\n    Computes the sum of double-precision floating-point strided array elements\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsum.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.dmean, base.strided.dnansum, base.strided.ssum, base.strided.gsum","base.strided.dsumkbn":"\nbase.strided.dsumkbn( N, x, strideX )\n    Computes the sum of double-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumkbn( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dsumkbn( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsumkbn( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.dsumkbn.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsumkbn.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn, base.strided.ssumkbn\n","base.strided.dsumkbn.ndarray":"\nbase.strided.dsumkbn.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsumkbn.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn, base.strided.ssumkbn","base.strided.dsumkbn2":"\nbase.strided.dsumkbn2( N, x, stride )\n    Computes the sum of double-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumkbn2( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsumkbn2( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsumkbn2( N, x1, stride )\n    -1.0\n\nbase.strided.dsumkbn2.ndarray( N, x, stride, offset )\n    Computes the sum of double-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsumkbn2.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn2, base.strided.dsum, base.strided.dsumkbn, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn2, base.strided.ssumkbn2\n","base.strided.dsumkbn2.ndarray":"\nbase.strided.dsumkbn2.ndarray( N, x, stride, offset )\n    Computes the sum of double-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsumkbn2.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn2, base.strided.dsum, base.strided.dsumkbn, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn2, base.strided.ssumkbn2","base.strided.dsumors":"\nbase.strided.dsumors( N, x, stride )\n    Computes the sum of double-precision floating-point strided array elements\n    using ordinary recursive summation.\n\n    The `N` and `stride` parameters determine which elements in \n    the strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumors( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dsumors( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsumors( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.dsumors.ndarray( N, x, stride, offset )\n    Computes the sum of double-precision floating-point strided array elements\n    using ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsumors.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumors, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumpw, base.strided.gsumors, base.strided.ssumors\n","base.strided.dsumors.ndarray":"\nbase.strided.dsumors.ndarray( N, x, stride, offset )\n    Computes the sum of double-precision floating-point strided array elements\n    using ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsumors.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumors, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumpw, base.strided.gsumors, base.strided.ssumors","base.strided.dsumpw":"\nbase.strided.dsumpw( N, x, stride )\n    Computes the sum of double-precision floating-point strided array elements\n    using pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumpw( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dsumpw( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsumpw( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.dsumpw.ndarray( N, x, stride, offset )\n    Computes the sum of double-precision floating-point strided array elements\n    using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsumpw.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumpw, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.gsumpw, base.strided.ssumpw\n","base.strided.dsumpw.ndarray":"\nbase.strided.dsumpw.ndarray( N, x, stride, offset )\n    Computes the sum of double-precision floating-point strided array elements\n    using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsumpw.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumpw, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.gsumpw, base.strided.ssumpw","base.strided.dsvariance":"\nbase.strided.dsvariance( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    using extended accumulation and returning an extended precision result.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsvariance( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsvariance( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsvariance( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dsvariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using extended accumulation and alternative indexing semantics and\n    returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsvariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsvariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariance, base.strided.variance, base.strided.svariance\n","base.strided.dsvariance.ndarray":"\nbase.strided.dsvariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using extended accumulation and alternative indexing semantics and\n    returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsvariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsvariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariance, base.strided.variance, base.strided.svariance","base.strided.dsvariancepn":"\nbase.strided.dsvariancepn( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    using a two-pass algorithm with extended accumulation and returning an\n    extended precision result.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsvariancepn( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsvariancepn( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsvariancepn( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dsvariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using a two-pass algorithm with extended accumulation and alternative\n    indexing semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsvariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsvariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancepn, base.strided.dsvariance, base.strided.variancepn, base.strided.svariancepn\n","base.strided.dsvariancepn.ndarray":"\nbase.strided.dsvariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using a two-pass algorithm with extended accumulation and alternative\n    indexing semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsvariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsvariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancepn, base.strided.dsvariance, base.strided.variancepn, base.strided.svariancepn","base.strided.dswap":"\nbase.strided.dswap( N, x, strideX, y, strideY )\n    Interchanges two double-precision floating-point vectors.\n\n    The `N` and stride parameters determine how values from `x` are swapped\n    with values from `y`.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the vectors are unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Second input array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.dswap( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.dswap( 3, x, -2, y, 1 )\n    <Float64Array>[ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n    // Using typed array views:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dswap( 3, x1, -2, y1, 1 )\n    <Float64Array>[ 6.0, 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.dswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Interchanges two double-precision floating-point vectors using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Second input array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.dswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.dswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dcopy, base.strided.gswap, base.strided.sswap, dswap\n","base.strided.dswap.ndarray":"\nbase.strided.dswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Interchanges two double-precision floating-point vectors using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Second input array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.dswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.dswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dcopy, base.strided.gswap, base.strided.sswap, dswap","base.strided.dtrunc":"\nbase.strided.dtrunc( N, x, strideX, y, strideY )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward zero and assigns the results to elements in a double-precision\n    floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dtrunc( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.0, 2.0, -3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dtrunc( N, x, 2, y, -1 )\n    <Float64Array>[ -3.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dtrunc( N, x1, -2, y1, 1 )\n    <Float64Array>[ 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dtrunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward zero and assigns the results to elements in a double-precision\n    floating-point strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dtrunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dtrunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dceil, base.strided.dfloor, strided.trunc, base.strided.strunc\n","base.strided.dtrunc.ndarray":"\nbase.strided.dtrunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward zero and assigns the results to elements in a double-precision\n    floating-point strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dtrunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dtrunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dceil, base.strided.dfloor, strided.trunc, base.strided.strunc","base.strided.dtypeEnum2Str":"\nbase.strided.dtypeEnum2Str( dtype )\n    Returns the data type string associated with a strided array data type\n    enumeration constant.\n\n    Parameters\n    ----------\n    dtype: integer\n        Data type enumeration constant.\n\n    Returns\n    -------\n    out: string|null\n        Data type string.\n\n    Examples\n    --------\n    > var out = base.strided.dtypeEnum2Str( base.strided.dtypeStr2Enum( 'float64' ) )\n    'float64'\n\n    See Also\n    --------\n    base.strided.dtypeStr2Enum\n","base.strided.dtypeResolveEnum":"\nbase.strided.dtypeResolveEnum( dtype )\n    Returns the enumeration constant associated with a supported strided array\n    data type value.\n\n    Downstream consumers of this function should *not* rely on specific integer\n    values (e.g., `INT8 == 0`). Instead, the function should be used in an\n    opaque manner.\n\n    Parameters\n    ----------\n    dtype: any\n        Data type value.\n\n    Returns\n    -------\n    out: integer|null\n        Enumeration constant.\n\n    Examples\n    --------\n    > var out = base.strided.dtypeResolveEnum( 'float64' )\n    <number>\n    > out = base.strided.dtypeResolveEnum( base.strided.dtypeStr2Enum( 'float64' ) )\n    <number>\n\n    See Also\n    --------\n    base.strided.dtypeResolveStr\n","base.strided.dtypeResolveStr":"\nbase.strided.dtypeResolveStr( dtype )\n    Returns the data type string associated with a supported data type value.\n\n    Parameters\n    ----------\n    dtype: any\n        Data type value.\n\n    Returns\n    -------\n    out: string|null\n        Data type string.\n\n    Examples\n    --------\n    > var out = base.strided.dtypeResolveStr( 'float64' )\n    'float64'\n    > out = base.strided.dtypeResolveStr( base.strided.dtypeStr2Enum( 'float64' ) )\n    'float64'\n\n    See Also\n    --------\n    base.strided.dtypeResolveEnum\n","base.strided.dtypeStr2Enum":"\nbase.strided.dtypeStr2Enum( dtype )\n    Returns the enumeration constant associated with a strided array data type\n    string.\n\n    Downstream consumers of this function should *not* rely on specific integer\n    values (e.g., `INT8 == 0`). Instead, the function should be used in an\n    opaque manner.\n\n    Parameters\n    ----------\n    dtype: string\n        Data type string.\n\n    Returns\n    -------\n    out: integer|null\n        Enumeration constant.\n\n    Examples\n    --------\n    > var out = base.strided.dtypeStr2Enum( 'float64' )\n    <number>\n\n    See Also\n    --------\n    base.strided.dtypeEnum2Str\n","base.strided.dvariance":"\nbase.strided.dvariance( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariance( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dvariance( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dvariance( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dvariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariance, base.strided.dstdev, base.strided.dvarm, base.strided.svariance, base.strided.variance\n","base.strided.dvariance.ndarray":"\nbase.strided.dvariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariance, base.strided.dstdev, base.strided.dvarm, base.strided.svariance, base.strided.variance","base.strided.dvariancech":"\nbase.strided.dvariancech( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancech( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dvariancech( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dvariancech( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dvariancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass trial mean algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvariancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancech, base.strided.dstdevch, base.strided.dvariance, base.strided.svariancech, base.strided.variancech\n","base.strided.dvariancech.ndarray":"\nbase.strided.dvariancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass trial mean algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvariancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancech, base.strided.dstdevch, base.strided.dvariance, base.strided.svariancech, base.strided.variancech","base.strided.dvariancepn":"\nbase.strided.dvariancepn( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancepn( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dvariancepn( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dvariancepn( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dvariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.dvariance, base.strided.svariancepn, base.strided.variancepn\n","base.strided.dvariancepn.ndarray":"\nbase.strided.dvariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.dvariance, base.strided.svariancepn, base.strided.variancepn","base.strided.dvariancetk":"\nbase.strided.dvariancetk( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancetk( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dvariancetk( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dvariancetk( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dvariancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass textbook algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvariancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.dvariance, base.strided.svariancetk, base.strided.variancetk\n","base.strided.dvariancetk.ndarray":"\nbase.strided.dvariancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass textbook algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvariancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.dvariance, base.strided.svariancetk, base.strided.variancetk","base.strided.dvariancewd":"\nbase.strided.dvariancewd( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancewd( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dvariancewd( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dvariancewd( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dvariancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvariancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.dvariance, base.strided.svariancewd, base.strided.variancewd\n","base.strided.dvariancewd.ndarray":"\nbase.strided.dvariancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvariancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.dvariance, base.strided.svariancewd, base.strided.variancewd","base.strided.dvarianceyc":"\nbase.strided.dvarianceyc( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass algorithm proposed by Youngs and Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarianceyc( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dvarianceyc( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dvarianceyc( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dvarianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass algorithm proposed by Youngs and Cramer and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvarianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.dvariance, base.strided.svarianceyc, base.strided.varianceyc\n","base.strided.dvarianceyc.ndarray":"\nbase.strided.dvarianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass algorithm proposed by Youngs and Cramer and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvarianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.dvariance, base.strided.svarianceyc, base.strided.varianceyc","base.strided.dvarm":"\nbase.strided.dvarm( N, mean, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mean: number\n        Mean.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarm( x.length, 1.0/3.0, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvarm( N, 1.0/3.0, 1, x, 2 )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dvarm( N, 1.0/3.0, 1, x1, 2 )\n    ~4.3333\n\nbase.strided.dvarm.ndarray( N, mean, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mean: number\n        Mean.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarm.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvarm.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariance\n","base.strided.dvarm.ndarray":"\nbase.strided.dvarm.ndarray( N, mean, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mean: number\n        Mean.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarm.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvarm.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariance","base.strided.dvarmpn":"\nbase.strided.dvarmpn( N, mean, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using Neely's correction algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mean: number\n        Mean.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarmpn( x.length, 1.0/3.0, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvarmpn( N, 1.0/3.0, 1, x, 2 )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dvarmpn( N, 1.0/3.0, 1, x1, 2 )\n    ~4.3333\n\nbase.strided.dvarmpn.ndarray( N, mean, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using Neely's correction algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mean: number\n        Mean.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarmpn.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvarmpn.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvarm\n","base.strided.dvarmpn.ndarray":"\nbase.strided.dvarmpn.ndarray( N, mean, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using Neely's correction algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mean: number\n        Mean.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarmpn.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvarmpn.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvarm","base.strided.dvarmtk":"\nbase.strided.dvarmtk( N, mean, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using a one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mean: number\n        Mean.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarmtk( x.length, 1.0/3.0, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvarmtk( N, 1.0/3.0, 1, x, 2 )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dvarmtk( N, 1.0/3.0, 1, x1, 2 )\n    ~4.3333\n\nbase.strided.dvarmtk.ndarray( N, mean, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mean: number\n        Mean.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarmtk.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvarmtk.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvarm\n","base.strided.dvarmtk.ndarray":"\nbase.strided.dvarmtk.ndarray( N, mean, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mean: number\n        Mean.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarmtk.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvarmtk.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvarm","base.strided.gapx":"\nbase.strided.gapx( N, alpha, x, stride )\n    Adds a constant to each element in a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > var alpha = 5.0;\n    > base.strided.gapx( x.length, alpha, x, 1 )\n    [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > alpha = 5.0;\n    > var stride = 2;\n    > base.strided.gapx( N, alpha, x, stride )\n    [ 3.0, 1.0, 8.0, -5.0, 9.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > alpha = 5.0;\n    > stride = 2;\n    > base.strided.gapx( N, alpha, x1, stride )\n    <Float64Array>[ 3.0, 3.0, 1.0, 5.0, -1.0 ]\n    > x0\n    <Float64Array>[ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\nbase.strided.gapx.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each element in a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > var alpha = 5.0;\n    > base.strided.gapx.ndarray( x.length, alpha, x, 1, 0 )\n    [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > alpha = 5.0;\n    > var stride = 2;\n    > base.strided.gapx.ndarray( N, alpha, x, stride, 1 )\n    [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dapx, base.strided.sapx\n","base.strided.gapx.ndarray":"\nbase.strided.gapx.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each element in a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > var alpha = 5.0;\n    > base.strided.gapx.ndarray( x.length, alpha, x, 1, 0 )\n    [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > alpha = 5.0;\n    > var stride = 2;\n    > base.strided.gapx.ndarray( N, alpha, x, stride, 1 )\n    [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dapx, base.strided.sapx","base.strided.gapxsum":"\nbase.strided.gapxsum( N, alpha, x, stride )\n    Adds a constant to each strided array element and computes the sum.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsum( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gapxsum( N, 5.0, x, stride )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gapxsum( N, 5.0, x1, stride )\n    14.0\n\nbase.strided.gapxsum.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each strided array element and computes the sum using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gapxsum.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.gapxsumpw, base.strided.gsum, base.strided.sapxsum\n","base.strided.gapxsum.ndarray":"\nbase.strided.gapxsum.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each strided array element and computes the sum using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gapxsum.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.gapxsumpw, base.strided.gsum, base.strided.sapxsum","base.strided.gapxsumkbn":"\nbase.strided.gapxsumkbn( N, alpha, x, stride )\n    Adds a constant to each strided array element and computes the sum using an\n    improved Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumkbn( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gapxsumkbn( N, 5.0, x, stride )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gapxsumkbn( N, 5.0, x1, stride )\n    14.0\n\nbase.strided.gapxsumkbn.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each strided array element and computes the sum using an\n    improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gapxsumkbn.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumkbn, base.strided.gapxsum, base.strided.gsumkbn, base.strided.sapxsumkbn\n","base.strided.gapxsumkbn.ndarray":"\nbase.strided.gapxsumkbn.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each strided array element and computes the sum using an\n    improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gapxsumkbn.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumkbn, base.strided.gapxsum, base.strided.gsumkbn, base.strided.sapxsumkbn","base.strided.gapxsumkbn2":"\nbase.strided.gapxsumkbn2( N, alpha, x, stride )\n    Adds a constant to each strided array element and computes the sum using a\n    second-order iterative Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumkbn2( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gapxsumkbn2( N, 5.0, x, stride )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gapxsumkbn2( N, 5.0, x1, stride )\n    14.0\n\nbase.strided.gapxsumkbn2.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each strided array element and computes the sum using a\n    second-order iterative Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gapxsumkbn2.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumkbn2, base.strided.gapxsum, base.strided.gsumkbn2, base.strided.sapxsumkbn2\n","base.strided.gapxsumkbn2.ndarray":"\nbase.strided.gapxsumkbn2.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each strided array element and computes the sum using a\n    second-order iterative Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gapxsumkbn2.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumkbn2, base.strided.gapxsum, base.strided.gsumkbn2, base.strided.sapxsumkbn2","base.strided.gapxsumors":"\nbase.strided.gapxsumors( N, alpha, x, stride )\n    Adds a constant to each strided array element and computes the sum using\n    ordinary recursive summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumors( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gapxsumors( N, 5.0, x, stride )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gapxsumors( N, 5.0, x1, stride )\n    14.0\n\nbase.strided.gapxsumors.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each strided array element and computes the sum using\n    ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gapxsumors.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumors, base.strided.gapxsum, base.strided.gsumors, base.strided.sapxsumors\n","base.strided.gapxsumors.ndarray":"\nbase.strided.gapxsumors.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each strided array element and computes the sum using\n    ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gapxsumors.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumors, base.strided.gapxsum, base.strided.gsumors, base.strided.sapxsumors","base.strided.gapxsumpw":"\nbase.strided.gapxsumpw( N, alpha, x, stride )\n    Adds a constant to each strided array element and computes the sum using\n    pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumpw( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gapxsumpw( N, 5.0, x, stride )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gapxsumpw( N, 5.0, x1, stride )\n    14.0\n\nbase.strided.gapxsumpw.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each strided array element and computes the sum using\n    pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumpw, base.strided.gapxsum, base.strided.gsumpw, base.strided.sapxsumpw\n","base.strided.gapxsumpw.ndarray":"\nbase.strided.gapxsumpw.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each strided array element and computes the sum using\n    pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumpw, base.strided.gapxsum, base.strided.gsumpw, base.strided.sapxsumpw","base.strided.gasum":"\nbase.strided.gasum( N, x, stride )\n    Computes the sum of the absolute values.\n\n    The sum of absolute values corresponds to the *L1* norm.\n\n    The `N` and `stride` parameters determine which elements in `x` are used to\n    compute the sum.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` or `stride` is less than or equal to `0`, the function returns `0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    sum: number\n        Sum of absolute values.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n    > var s = base.strided.gasum( x.length, x, 1 )\n    19.0\n\n    // Sum every other value:\n    > s = base.strided.gasum( 3, x, 2 )\n    10.0\n\n    // Use view offset; e.g., starting at 2nd element:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > s = base.strided.gasum( 3, x1, 2 )\n    12.0\n\n\nbase.strided.gasum.ndarray( N, x, stride, offset )\n    Computes the sum of absolute values using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    sum: number\n        Sum of absolute values.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n    > var s = base.strided.gasum.ndarray( x.length, x, 1, 0 )\n    19.0\n\n    // Sum the last three elements:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > s = base.strided.gasum.ndarray( 3, x, -1, x.length-1 )\n    15.0\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.sasum\n","base.strided.gasum.ndarray":"\nbase.strided.gasum.ndarray( N, x, stride, offset )\n    Computes the sum of absolute values using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    sum: number\n        Sum of absolute values.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n    > var s = base.strided.gasum.ndarray( x.length, x, 1, 0 )\n    19.0\n\n    // Sum the last three elements:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > s = base.strided.gasum.ndarray( 3, x, -1, x.length-1 )\n    15.0\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.sasum","base.strided.gasumpw":"\nbase.strided.gasumpw( N, x, stride )\n    Computes the sum of absolute values (L1 norm) of strided array elements\n    using pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.gasumpw( x.length, x, 1 )\n    5.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gasumpw( N, x, stride )\n    5.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gasumpw( N, x1, stride )\n    5.0\n\nbase.strided.gasumpw.ndarray( N, x, stride, offset )\n    Computes the sum of absolute values (L1 norm) of strided array elements\n    using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.gasumpw.ndarray( x.length, x, 1, 0 )\n    5.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gasumpw.ndarray( N, x, 2, 1 )\n    5.0\n\n    See Also\n    --------\n    base.strided.gasum, base.strided.dasumpw, base.strided.gsumpw, base.strided.sasumpw\n","base.strided.gasumpw.ndarray":"\nbase.strided.gasumpw.ndarray( N, x, stride, offset )\n    Computes the sum of absolute values (L1 norm) of strided array elements\n    using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.gasumpw.ndarray( x.length, x, 1, 0 )\n    5.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gasumpw.ndarray( N, x, 2, 1 )\n    5.0\n\n    See Also\n    --------\n    base.strided.gasum, base.strided.dasumpw, base.strided.gsumpw, base.strided.sasumpw","base.strided.gaxpy":"\nbase.strided.gaxpy( N, alpha, x, strideX, y, strideY )\n    Multiplies `x` by a constant `alpha` and adds the result to `y`.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n    > base.strided.gaxpy( x.length, 5.0, x, 1, y, 1 )\n    [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n    // Using `N` and stride parameters:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n    > base.strided.gaxpy( 3, 5.0, x, 2, y, -1 )\n    [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.gaxpy( 3, 5.0, x1, -2, y1, 1 )\n    <Float64Array>[ 40.0, 31.0, 22.0 ]\n    > y0\n    <Float64Array>[ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.strided.gaxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n    Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n    > base.strided.gaxpy.ndarray( x.length, 5.0, x, 1, 0, y, 1, 0 )\n    [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n    > base.strided.gaxpy.ndarray( 3, 5.0, x, 2, 1, y, -1, y.length-1 )\n    [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n    See Also\n    --------\n    base.strided.daxpy, base.strided.saxpy\n","base.strided.gaxpy.ndarray":"\nbase.strided.gaxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n    Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n    > base.strided.gaxpy.ndarray( x.length, 5.0, x, 1, 0, y, 1, 0 )\n    [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n    > base.strided.gaxpy.ndarray( 3, 5.0, x, 2, 1, y, -1, y.length-1 )\n    [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n    See Also\n    --------\n    base.strided.daxpy, base.strided.saxpy","base.strided.gcopy":"\nbase.strided.gcopy( N, x, strideX, y, strideY )\n    Copies values from `x` into `y`.\n\n    The `N` and stride parameters determine how values from `x` are copied into\n    `y`.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: ArrayLikeObject\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n    > base.strided.gcopy( x.length, x, 1, y, 1 )\n    [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n    > base.strided.gcopy( 3, x, -2, y, 1 )\n    [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n    // Using typed array views:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.gcopy( 3, x1, -2, y1, 1 )\n    <Float64Array>[ 6.0, 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.gcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Copies values from `x` into `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: ArrayLikeObject\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n    > base.strided.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n    > base.strided.gcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dcopy, base.strided.scopy\n","base.strided.gcopy.ndarray":"\nbase.strided.gcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Copies values from `x` into `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: ArrayLikeObject\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n    > base.strided.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n    > base.strided.gcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dcopy, base.strided.scopy","base.strided.gcusum":"\nbase.strided.gcusum( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of strided array elements.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusum( x.length, 0.0, x, 1, y, 1 )\n    [ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusum( N, 0.0, x, 2, y, 2 )\n    [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gcusum( N, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.gcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusum.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusumpw, base.strided.scusum\n","base.strided.gcusum.ndarray":"\nbase.strided.gcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusum.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusumpw, base.strided.scusum","base.strided.gcusumkbn":"\nbase.strided.gcusumkbn( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of strided array elements using an improved\n    Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumkbn( x.length, 0.0, x, 1, y, 1 )\n    [ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumkbn( N, 0.0, x, 2, y, 2 )\n    [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gcusumkbn( N, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.gcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using an improved\n    Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumkbn.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumkbn, base.strided.gcusum, base.strided.gcusumkbn2, base.strided.scusumkbn\n","base.strided.gcusumkbn.ndarray":"\nbase.strided.gcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using an improved\n    Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumkbn.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumkbn, base.strided.gcusum, base.strided.gcusumkbn2, base.strided.scusumkbn","base.strided.gcusumkbn2":"\nbase.strided.gcusumkbn2( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of strided array elements using a second-order\n    iterative Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumkbn2( x.length, 0.0, x, 1, y, 1 )\n    [ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumkbn2( N, 0.0, x, 2, y, 2 )\n    [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gcusumkbn2( N, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.gcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using a second-order\n    iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumkbn2.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumkbn2, base.strided.gcusum, base.strided.gcusumkbn, base.strided.scusumkbn2\n","base.strided.gcusumkbn2.ndarray":"\nbase.strided.gcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using a second-order\n    iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumkbn2.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumkbn2, base.strided.gcusum, base.strided.gcusumkbn, base.strided.scusumkbn2","base.strided.gcusumors":"\nbase.strided.gcusumors( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of strided array elements using ordinary\n    recursive summation.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumors( x.length, 0.0, x, 1, y, 1 )\n    [ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumors( N, 0.0, x, 2, y, 2 )\n    [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gcusumors( N, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.gcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using ordinary\n    recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumors.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumors, base.strided.gcusum, base.strided.gcusumpw, base.strided.scusumors\n","base.strided.gcusumors.ndarray":"\nbase.strided.gcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using ordinary\n    recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumors.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumors, base.strided.gcusum, base.strided.gcusumpw, base.strided.scusumors","base.strided.gcusumpw":"\nbase.strided.gcusumpw( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of strided array elements using pairwise\n    summation.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumpw( x.length, 0.0, x, 1, y, 1 )\n    [ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumpw( N, 0.0, x, 2, y, 2 )\n    [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gcusumpw( N, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.gcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using pairwise\n    summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumpw.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumpw, base.strided.gcusum, base.strided.scusumpw\n","base.strided.gcusumpw.ndarray":"\nbase.strided.gcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using pairwise\n    summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumpw.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumpw, base.strided.gcusum, base.strided.scusumpw","base.strided.gdot":"\nbase.strided.gdot( N, x, strideX, y, strideY )\n    Computes the dot product of two vectors.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: number\n        The dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n    > var y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n    > var out = base.strided.gdot( x.length, x, 1, y, 1 )\n    -5.0\n\n    // Strides:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n    > out = base.strided.gdot( 3, x, 2, y, -1 )\n    9.0\n\n    // Using view offsets:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n    > out = base.strided.gdot( 3, x1, -2, y1, 1 )\n    128.0\n\n\nbase.strided.gdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the dot product of two vectors using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing based on a starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: number\n        The dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n    > var y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n    > var out = base.strided.gdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    -5.0\n\n    // Strides:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n    > out = base.strided.gdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n    9.0\n\n    // Using offset indices:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n    > out = base.strided.gdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n    128.0\n\n    See Also\n    --------\n    base.strided.ddot, base.strided.sdot, gdot\n","base.strided.gdot.ndarray":"\nbase.strided.gdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the dot product of two vectors using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing based on a starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: number\n        The dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n    > var y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n    > var out = base.strided.gdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    -5.0\n\n    // Strides:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n    > out = base.strided.gdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n    9.0\n\n    // Using offset indices:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n    > out = base.strided.gdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n    128.0\n\n    See Also\n    --------\n    base.strided.ddot, base.strided.sdot, gdot","base.strided.gfill":"\nbase.strided.gfill( N, alpha, x, stride )\n    Fills a strided array with a specified scalar value.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: any\n        Constant.\n\n    x: ArrayLikeObject\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: ArrayLikeObject\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.gfill( x.length, 5.0, x, 1 )\n    [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gfill( N, 5.0, x, 2 )\n    [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gfill( N, 5.0, x1, 2 )\n    <Float64Array>[ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n    > x0\n    <Float64Array>[ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.gfill.ndarray( N, alpha, x, stride, offset )\n    Fills a strided array with a specified scalar value using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: any\n        Constant.\n\n    x: ArrayLikeObject\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: ArrayLikeObject\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.gfill.ndarray( x.length, 5.0, x, 1, 0 )\n    [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gfill.ndarray( N, 5.0, x, 2, 1 )\n    [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n    See Also\n    --------\n    base.strided.dfill, base.strided.sfill\n","base.strided.gfill.ndarray":"\nbase.strided.gfill.ndarray( N, alpha, x, stride, offset )\n    Fills a strided array with a specified scalar value using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: any\n        Constant.\n\n    x: ArrayLikeObject\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: ArrayLikeObject\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.gfill.ndarray( x.length, 5.0, x, 1, 0 )\n    [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gfill.ndarray( N, 5.0, x, 2, 1 )\n    [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n    See Also\n    --------\n    base.strided.dfill, base.strided.sfill","base.strided.gfillBy":"\nbase.strided.gfillBy( N, x, stride, clbk[, thisArg] )\n    Fills a strided array according to a provided callback function.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - aidx: array index.\n    - sidx: strided index (offset + aidx*stride).\n    - array: the input array.\n\n    The callback return value is used as the fill value for the current array\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    x: ArrayLikeObject\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function fill() { return 5.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.gfillBy( x.length, x, 1, fill )\n    [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gfillBy( N, x, 2, fill )\n    [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gfillBy( N, x1, 2, fill )\n    <Float64Array>[ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n    > x0\n    <Float64Array>[ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.gfillBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Fills a strided array according to a provided callback function and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    x: ArrayLikeObject\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function fill() { return 5.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.gfillBy.ndarray( x.length, x, 1, 0, fill )\n    [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gfillBy.ndarray( N, x, 2, 1, fill )\n    [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n    See Also\n    --------\n    base.strided.gfill\n","base.strided.gfillBy.ndarray":"\nbase.strided.gfillBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Fills a strided array according to a provided callback function and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    x: ArrayLikeObject\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function fill() { return 5.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.gfillBy.ndarray( x.length, x, 1, 0, fill )\n    [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gfillBy.ndarray( N, x, 2, 1, fill )\n    [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n    See Also\n    --------\n    base.strided.gfill","base.strided.gnannsumkbn":"\nbase.strided.gnannsumkbn( N, x, strideX, out, strideOut )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    an improved Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns a sum equal to `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > var out = [ 0.0, 0 ];\n    > base.strided.gnannsumkbn( x.length, x, 1, out, 1 )\n    [ 1.0, 3 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n    > out = [ 0.0, 0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gnannsumkbn( N, x, 2, out, 1 )\n    [ 1.0, 3 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > out = [ 0.0, 0 ];\n    > base.strided.gnannsumkbn( N, x1, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\nbase.strided.gnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > var out = [ 0.0, 0 ];\n    > base.strided.gnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\n    [ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > out = [ 0.0, 0 ];\n    > base.strided.gnannsumkbn.ndarray( N, x, 2, 1, out, 1, 0 )\n    [ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsumkbn\n","base.strided.gnannsumkbn.ndarray":"\nbase.strided.gnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > var out = [ 0.0, 0 ];\n    > base.strided.gnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\n    [ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > out = [ 0.0, 0 ];\n    > base.strided.gnannsumkbn.ndarray( N, x, 2, 1, out, 1, 0 )\n    [ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsumkbn","base.strided.gnansum":"\nbase.strided.gnansum( N, x, stride )\n    Computes the sum of strided array elements, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansum( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gnansum( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gnansum( N, x1, stride )\n    -1.0\n\nbase.strided.gnansum.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gnansum.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.snansum, base.strided.gsum, base.strided.nanmean\n","base.strided.gnansum.ndarray":"\nbase.strided.gnansum.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gnansum.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.snansum, base.strided.gsum, base.strided.nanmean","base.strided.gnansumkbn":"\nbase.strided.gnansumkbn( N, x, stride )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    an improved Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumkbn( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gnansumkbn( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gnansumkbn( N, x1, stride )\n    -1.0\n\nbase.strided.gnansumkbn.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gnansumkbn.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn, base.strided.snansumkbn\n","base.strided.gnansumkbn.ndarray":"\nbase.strided.gnansumkbn.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gnansumkbn.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn, base.strided.snansumkbn","base.strided.gnansumkbn2":"\nbase.strided.gnansumkbn2( N, x, stride )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    a second-order iterative Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumkbn2( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gnansumkbn2( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gnansumkbn2( N, x1, stride )\n    -1.0\n\nbase.strided.gnansumkbn2.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    a second-order iterative Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gnansumkbn2.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn2, base.strided.gnansum, base.strided.gnansumkbn, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn2, base.strided.snansumkbn2\n","base.strided.gnansumkbn2.ndarray":"\nbase.strided.gnansumkbn2.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    a second-order iterative Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gnansumkbn2.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn2, base.strided.gnansum, base.strided.gnansumkbn, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn2, base.strided.snansumkbn2","base.strided.gnansumors":"\nbase.strided.gnansumors( N, x, stride )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    ordinary recursive summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumors( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gnansumors( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gnansumors( N, x1, stride )\n    -1.0\n\nbase.strided.gnansumors.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gnansumors.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumors, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumpw, base.strided.gsumors, base.strided.snansumors\n","base.strided.gnansumors.ndarray":"\nbase.strided.gnansumors.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gnansumors.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumors, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumpw, base.strided.gsumors, base.strided.snansumors","base.strided.gnansumpw":"\nbase.strided.gnansumpw( N, x, stride )\n    Computes the sum of strided array elements, ignoring `NaN` values and\n    pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumpw( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gnansumpw( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gnansumpw( N, x1, stride )\n    -1.0\n\nbase.strided.gnansumpw.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gnansumpw.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumpw, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gsumpw, base.strided.snansumpw\n","base.strided.gnansumpw.ndarray":"\nbase.strided.gnansumpw.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gnansumpw.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumpw, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gsumpw, base.strided.snansumpw","base.strided.gnrm2":"\nbase.strided.gnrm2( N, x, stride )\n    Computes the L2-norm of a vector.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0` or `stride <= 0`, the function returns `0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The L2-norm.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gnrm2( x.length, x, 1 )\n    3.0\n\n    // Using `N` and stride parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > base.strided.gnrm2( 3, x, 2 )\n    3.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.gnrm2( 3, x1, 2 )\n    3.0\n\n\nbase.strided.gnrm2.ndarray( N, x, stride, offset )\n    Computes the L2-norm of a vector using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    nrm2: number\n        The L2-norm.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gnrm2.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > base.strided.gnrm2.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dnrm2, base.strided.snrm2\n","base.strided.gnrm2.ndarray":"\nbase.strided.gnrm2.ndarray( N, x, stride, offset )\n    Computes the L2-norm of a vector using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    nrm2: number\n        The L2-norm.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gnrm2.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > base.strided.gnrm2.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dnrm2, base.strided.snrm2","base.strided.grev":"\nbase.strided.grev( N, x, stride )\n    Reverses a strided array in-place.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: ArrayLikeObject\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.grev( x.length, x, 1 )\n    [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.grev( N, x, 2 )\n    [ 4.0, 1.0, 3.0, -5.0, -2.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.grev( N, x1, 2 )\n    <Float64Array>[ -6.0, 3.0, -4.0, 5.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n\nbase.strided.grev.ndarray( N, x, stride, offset )\n    Reverses a strided array in-place using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: ArrayLikeObject\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.grev.ndarray( x.length, x, 1, 0 )\n    [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.grev.ndarray( N, x, 2, 1 )\n    [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.drev, base.strided.srev\n","base.strided.grev.ndarray":"\nbase.strided.grev.ndarray( N, x, stride, offset )\n    Reverses a strided array in-place using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: ArrayLikeObject\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.grev.ndarray( x.length, x, 1, 0 )\n    [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.grev.ndarray( N, x, 2, 1 )\n    [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.drev, base.strided.srev","base.strided.gscal":"\nbase.strided.gscal( N, alpha, x, stride )\n    Multiplies a vector `x` by a constant `alpha`.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `stride <= 0`, the function returns `x` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > var alpha = 5.0;\n    > base.strided.gscal( x.length, alpha, x, 1 )\n    [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.gscal( 3, 5.0, x, 2 )\n    [ -10.0, 1.0, 15.0, -5.0, 20.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.gscal( 3, 5.0, x1, 2 )\n    <Float64Array>[ -10.0, 3.0, -20.0, 5.0, -30.0 ]\n    > x0\n    <Float64Array>[ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n\nbase.strided.gscal.ndarray( N, alpha, x, stride, offset )\n    Multiplies `x` by a constant `alpha` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.gscal.ndarray( x.length, 5.0, x, 1, 0 )\n    [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > base.strided.gscal.ndarray( 3, 5.0, x, 2, 1 )\n    [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n    See Also\n    --------\n    base.strided.dscal, base.strided.gaxpy, base.strided.sscal\n","base.strided.gscal.ndarray":"\nbase.strided.gscal.ndarray( N, alpha, x, stride, offset )\n    Multiplies `x` by a constant `alpha` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.gscal.ndarray( x.length, 5.0, x, 1, 0 )\n    [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > base.strided.gscal.ndarray( 3, 5.0, x, 2, 1 )\n    [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n    See Also\n    --------\n    base.strided.dscal, base.strided.gaxpy, base.strided.sscal","base.strided.gsort2hp":"\nbase.strided.gsort2hp( N, order, x, strideX, y, strideY )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using heapsort.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided arrays are sorted *in-place* (i.e., the input strided\n    arrays is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > base.strided.gsort2hp( x.length, 1, x, 1, y, 1 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    [ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsort2hp( N, -1, x, 2, y, 2 )\n    [ 3.0, -2.0, 1.0, -4.0 ]\n    > y\n    [ 2.0, 1.0, 0.0, 3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gsort2hp( N, 1, x1, 2, y1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.gsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using heapsort and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > base.strided.gsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    [ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    [ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssort2hp\n","base.strided.gsort2hp.ndarray":"\nbase.strided.gsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using heapsort and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > base.strided.gsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    [ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    [ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssort2hp","base.strided.gsort2ins":"\nbase.strided.gsort2ins( N, order, x, strideX, y, strideY )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using insertion sort.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^2).\n\n    The algorithm is efficient for *small* strided arrays (typically N <= 20)\n    and is particularly efficient for sorting strided arrays which are already\n    substantially sorted.\n\n    The algorithm is *stable*, meaning that the algorithm does *not* change the\n    order of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided arrays are sorted *in-place* (i.e., the input strided\n    arrays is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > base.strided.gsort2ins( x.length, 1, x, 1, y, 1 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    [ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsort2ins( N, -1, x, 2, y, 2 )\n    [ 3.0, -2.0, 1.0, -4.0 ]\n    > y\n    [ 2.0, 1.0, 0.0, 3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gsort2ins( N, 1, x1, 2, y1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.gsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using insertion sort and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > base.strided.gsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    [ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsort2ins.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    [ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2ins, base.strided.gsortins, base.strided.ssort2ins\n","base.strided.gsort2ins.ndarray":"\nbase.strided.gsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using insertion sort and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > base.strided.gsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    [ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsort2ins.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    [ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2ins, base.strided.gsortins, base.strided.ssort2ins","base.strided.gsort2sh":"\nbase.strided.gsort2sh( N, order, x, strideX, y, strideY )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using Shellsort.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^(4/3)).\n\n    The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided arrays are sorted *in-place* (i.e., the input strided\n    arrays is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > base.strided.gsort2sh( x.length, 1, x, 1, y, 1 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    [ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsort2sh( N, -1, x, 2, y, 2 )\n    [ 3.0, -2.0, 1.0, -4.0 ]\n    > y\n    [ 2.0, 1.0, 0.0, 3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gsort2sh( N, 1, x1, 2, y1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.gsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using Shellsort and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > base.strided.gsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    [ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    [ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssort2sh\n","base.strided.gsort2sh.ndarray":"\nbase.strided.gsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using Shellsort and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > base.strided.gsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    [ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    [ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssort2sh","base.strided.gsorthp":"\nbase.strided.gsorthp( N, order, x, stride )\n    Sorts a strided array using heapsort.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided array is sorted *in-place* (i.e., the input strided array\n    is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > base.strided.gsorthp( x.length, 1, x, 1 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsorthp( N, -1, x, 2 )\n    [ 3.0, -2.0, 1.0, -4.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gsorthp( N, 1, x1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.gsorthp.ndarray( N, order, x, stride, offset )\n    Sorts a strided array using heapsort and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > base.strided.gsorthp.ndarray( x.length, 1, x, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsorthp.ndarray( N, 1, x, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssorthp\n","base.strided.gsorthp.ndarray":"\nbase.strided.gsorthp.ndarray( N, order, x, stride, offset )\n    Sorts a strided array using heapsort and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > base.strided.gsorthp.ndarray( x.length, 1, x, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsorthp.ndarray( N, 1, x, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssorthp","base.strided.gsortins":"\nbase.strided.gsortins( N, order, x, stride )\n    Sorts a strided array using insertion sort.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^2).\n\n    The algorithm is efficient for *small* strided arrays (typically N <= 20)\n    and is particularly efficient for sorting strided arrays which are already\n    substantially sorted.\n\n    The algorithm is *stable*, meaning that the algorithm does *not* change the\n    order of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided array is sorted *in-place* (i.e., the input strided array\n    is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > base.strided.gsortins( x.length, 1, x, 1 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsortins( N, -1, x, 2 )\n    [ 3.0, -2.0, 1.0, -4.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gsortins( N, 1, x1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.gsortins.ndarray( N, order, x, stride, offset )\n    Sorts a strided array using insertion sort and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > base.strided.gsortins.ndarray( x.length, 1, x, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsortins.ndarray( N, 1, x, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsortins, base.strided.gsort2ins, base.strided.ssortins\n","base.strided.gsortins.ndarray":"\nbase.strided.gsortins.ndarray( N, order, x, stride, offset )\n    Sorts a strided array using insertion sort and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > base.strided.gsortins.ndarray( x.length, 1, x, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsortins.ndarray( N, 1, x, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsortins, base.strided.gsort2ins, base.strided.ssortins","base.strided.gsortsh":"\nbase.strided.gsortsh( N, order, x, stride )\n    Sorts a strided array using Shellsort.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^(4/3)).\n\n    The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided array is sorted *in-place* (i.e., the input strided array\n    is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > base.strided.gsortsh( x.length, 1, x, 1 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsortsh( N, -1, x, 2 )\n    [ 3.0, -2.0, 1.0, -4.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gsortsh( N, 1, x1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.gsortsh.ndarray( N, order, x, stride, offset )\n    Sorts a strided array using Shellsort and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > base.strided.gsortsh.ndarray( x.length, 1, x, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsortsh.ndarray( N, 1, x, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssortsh\n","base.strided.gsortsh.ndarray":"\nbase.strided.gsortsh.ndarray( N, order, x, stride, offset )\n    Sorts a strided array using Shellsort and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > base.strided.gsortsh.ndarray( x.length, 1, x, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsortsh.ndarray( N, 1, x, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssortsh","base.strided.gsum":"\nbase.strided.gsum( N, x, stride )\n    Computes the sum of strided array elements.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsum( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gsum( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gsum( N, x1, stride )\n    -1.0\n\nbase.strided.gsum.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsum.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsum, base.strided.gnansum, base.strided.ssum, base.strided.mean\n","base.strided.gsum.ndarray":"\nbase.strided.gsum.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsum.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsum, base.strided.gnansum, base.strided.ssum, base.strided.mean","base.strided.gsumkbn":"\nbase.strided.gsumkbn( N, x, stride )\n    Computes the sum of strided array elements using an improved Kahan–Babuška\n    algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumkbn( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gsumkbn( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gsumkbn( N, x1, stride )\n    -1.0\n\nbase.strided.gsumkbn.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements using an improved Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsumkbn.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn\n","base.strided.gsumkbn.ndarray":"\nbase.strided.gsumkbn.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements using an improved Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsumkbn.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn","base.strided.gsumkbn2":"\nbase.strided.gsumkbn2( N, x, stride )\n    Computes the sum of strided array elements using a second-order iterative\n    Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumkbn2( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gsumkbn2( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gsumkbn2( N, x1, stride )\n    -1.0\n\nbase.strided.gsumkbn2.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements using a second-order iterative\n    Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsumkbn2.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.gsum, base.strided.gsumkbn, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn2\n","base.strided.gsumkbn2.ndarray":"\nbase.strided.gsumkbn2.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements using a second-order iterative\n    Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsumkbn2.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.gsum, base.strided.gsumkbn, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn2","base.strided.gsumors":"\nbase.strided.gsumors( N, x, stride )\n    Computes the sum of strided array elements using ordinary recursive\n    summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumors( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gsumors( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gsumors( N, x1, stride )\n    -1.0\n\nbase.strided.gsumors.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements using ordinary recursive\n    summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsumors.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumors, base.strided.gnansumors, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumpw, base.strided.ssumors\n","base.strided.gsumors.ndarray":"\nbase.strided.gsumors.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements using ordinary recursive\n    summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsumors.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumors, base.strided.gnansumors, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumpw, base.strided.ssumors","base.strided.gsumpw":"\nbase.strided.gsumpw( N, x, stride )\n    Computes the sum of strided array elements using pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumpw( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gsumpw( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gsumpw( N, x1, stride )\n    -1.0\n\nbase.strided.gsumpw.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements using pairwise summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsumpw.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumpw, base.strided.gnansumpw, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.ssumpw\n","base.strided.gsumpw.ndarray":"\nbase.strided.gsumpw.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements using pairwise summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsumpw.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumpw, base.strided.gnansumpw, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.ssumpw","base.strided.gswap":"\nbase.strided.gswap( N, x, strideX, y, strideY )\n    Interchanges vectors `x` and `y`.\n\n    The `N` and stride parameters determine how values from `x` are swapped with\n    values from `y`.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the vectors are unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: ArrayLikeObject\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n    > base.strided.gswap( x.length, x, 1, y, 1 )\n    [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n    > base.strided.gswap( 3, x, -2, y, 1 )\n    [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n    // Using typed array views:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.gswap( 3, x1, -2, y1, 1 )\n    <Float64Array>[ 6.0, 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.gswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Interchanges vectors `x` and `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: ArrayLikeObject\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n    > base.strided.gswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n    > base.strided.gswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dswap, base.strided.gcopy, base.strided.sswap, gswap\n","base.strided.gswap.ndarray":"\nbase.strided.gswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Interchanges vectors `x` and `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: ArrayLikeObject\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n    > base.strided.gswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n    > base.strided.gswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dswap, base.strided.gcopy, base.strided.sswap, gswap","base.strided.mapBy":"\nbase.strided.mapBy( N, x, sx, y, sy, fcn, clbk[, thisArg] )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - indices: strided indices (offset + idx*stride).\n    - arrays: input and output arrays.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    fcn: Function\n        Unary function to apply to callback return values.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v * 2.0; };\n    > base.strided.mapBy( x.length, x, 1, y, 1, base.abs, clbk )\n    [ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > base.strided.mapBy( 2, x, 2, y, -1, base.abs, clbk )\n    [ 6.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.mapBy( 2, x1, -2, y1, 1, base.abs, clbk )\n    <Float64Array>[ 8.0, 4.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 8.0, 4.0 ]\n\n\nbase.strided.mapBy.ndarray( N, x, sx, ox, y, sy, oy, fcn, clbk[, thisArg] )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offsest parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply to callback return values.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v * 2.0; };\n    > base.strided.mapBy.ndarray( x.length, x, 1, 0, y, 1, 0, base.abs, clbk )\n    [ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > base.strided.mapBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.abs, clbk )\n    [ 0.0, 0.0, 8.0, 4.0 ]\n\n    See Also\n    --------\n    base.strided.mapBy2, base.strided.unary\n","base.strided.mapBy.ndarray":"\nbase.strided.mapBy.ndarray( N, x, sx, ox, y, sy, oy, fcn, clbk[, thisArg] )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offsest parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply to callback return values.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v * 2.0; };\n    > base.strided.mapBy.ndarray( x.length, x, 1, 0, y, 1, 0, base.abs, clbk )\n    [ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > base.strided.mapBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.abs, clbk )\n    [ 0.0, 0.0, 8.0, 4.0 ]\n\n    See Also\n    --------\n    base.strided.mapBy2, base.strided.unary","base.strided.mapBy2":"\nbase.strided.mapBy2( N, x, sx, y, sy, z, sz, fcn, clbk[, thisArg] )\n    Applies a binary function to each pair of elements retrieved from strided\n    input arrays according to a callback function and assigns results to a\n    strided output array.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided four arguments:\n\n    - values: input array elements.\n    - idx: iteration index.\n    - indices: strided array indices (offset + idx*stride).\n    - arrays: input and output arrays.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    fcn: Function\n        Binary function to apply to callback return values.\n\n    clbk: Function\n        Callback function which returns an array-like object containing two\n        values.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 1.0, 1.0, 2.0, 2.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\n    > base.strided.mapBy2( x.length, x, 1, y, 1, z, 1, base.add, clbk )\n    [ 4.0, -2.0, 10.0, -4.0 ]\n\n    // Using `N` and stride parameters:\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > base.strided.mapBy2( 2, x, 2, y, -1, z, -1, base.add, clbk )\n    [ 8.0, 4.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y0 = new Float64Array( [ 1.0, 1.0, 2.0, 2.0 ] );\n    > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > base.strided.mapBy2( 2, x1, -2, y1, 1, z1, 1, base.add, clbk )\n    <Float64Array>[ -4.0, 0.0 ]\n    > z0\n    <Float64Array>[ 0.0, 0.0, -4.0, 0.0 ]\n\n\nbase.strided.mapBy2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn, clbk[, thisArg] )\n    Applies a binary function to each pair of elements retrieved from strided\n    input arrays according to a callback function and assigns results to a\n    strided output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offsest parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    fcn: Function\n        Binary function to apply to callback return values.\n\n    clbk: Function\n        Callback function which returns an array-like object containing two\n        values.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 1.0, 1.0, 2.0, 2.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\n    > base.strided.mapBy2.ndarray( 4, x, 1, 0, y, 1, 0, z, 1, 0, base.add, clbk )\n    [ 4.0, -2.0, 10.0, -4.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 1.0, 1.0, 2.0, 2.0 ];\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > base.strided.mapBy2.ndarray( 2, x, 2, 1, y, -1, 3, z, 1, 0, base.add, clbk )\n    [ 0.0, -4.0, 0.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.mapBy, base.strided.binary\n","base.strided.mapBy2.ndarray":"\nbase.strided.mapBy2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn, clbk[, thisArg] )\n    Applies a binary function to each pair of elements retrieved from strided\n    input arrays according to a callback function and assigns results to a\n    strided output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offsest parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    fcn: Function\n        Binary function to apply to callback return values.\n\n    clbk: Function\n        Callback function which returns an array-like object containing two\n        values.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 1.0, 1.0, 2.0, 2.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\n    > base.strided.mapBy2.ndarray( 4, x, 1, 0, y, 1, 0, z, 1, 0, base.add, clbk )\n    [ 4.0, -2.0, 10.0, -4.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 1.0, 1.0, 2.0, 2.0 ];\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > base.strided.mapBy2.ndarray( 2, x, 2, 1, y, -1, 3, z, 1, 0, base.add, clbk )\n    [ 0.0, -4.0, 0.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.mapBy, base.strided.binary","base.strided.max":"\nbase.strided.max( N, x, stride )\n    Computes the maximum value of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.max( x.length, x, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.max( N, x, stride )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.max( N, x1, stride )\n    2.0\n\nbase.strided.max.ndarray( N, x, stride, offset )\n    Computes the maximum value of a strided array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.max.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.max.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.min, base.strided.nanmax, base.strided.smax\n","base.strided.max.ndarray":"\nbase.strided.max.ndarray( N, x, stride, offset )\n    Computes the maximum value of a strided array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.max.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.max.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.min, base.strided.nanmax, base.strided.smax","base.strided.maxabs":"\nbase.strided.maxabs( N, x, stride )\n    Computes the maximum absolute value of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.maxabs( x.length, x, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.maxabs( N, x, stride )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.maxabs( N, x1, stride )\n    2.0\n\nbase.strided.maxabs.ndarray( N, x, stride, offset )\n    Computes the maximum absolute value of a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.maxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.maxabs.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmaxabs, base.strided.max, base.strided.minabs, base.strided.nanmaxabs, base.strided.smaxabs\n","base.strided.maxabs.ndarray":"\nbase.strided.maxabs.ndarray( N, x, stride, offset )\n    Computes the maximum absolute value of a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.maxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.maxabs.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmaxabs, base.strided.max, base.strided.minabs, base.strided.nanmaxabs, base.strided.smaxabs","base.strided.maxBy":"\nbase.strided.maxBy( N, x, stride, clbk[, thisArg] )\n    Calculates the maximum value of a strided array via a callback function.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - aidx: array index.\n    - sidx: strided index (offset + aidx*stride).\n    - array: the input array.\n\n    The callback function should return a numeric value.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.maxBy( x.length, x, 1, accessor )\n    8.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.maxBy( N, x, 2, accessor )\n    8.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.maxBy( N, x1, 2, accessor )\n    -4.0\n\nbase.strided.maxBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the maximum value of a strided array via a callback function and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.maxBy.ndarray( x.length, x, 1, 0, accessor )\n    8.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.maxBy.ndarray( N, x, 2, 1, accessor )\n    -4.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.max, base.strided.minBy, base.strided.nanmaxBy, base.strided.smax\n","base.strided.maxBy.ndarray":"\nbase.strided.maxBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the maximum value of a strided array via a callback function and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.maxBy.ndarray( x.length, x, 1, 0, accessor )\n    8.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.maxBy.ndarray( N, x, 2, 1, accessor )\n    -4.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.max, base.strided.minBy, base.strided.nanmaxBy, base.strided.smax","base.strided.maxsorted":"\nbase.strided.maxsorted( N, x, stride )\n    Computes the maximum value of a sorted strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > base.strided.maxsorted( x.length, x, 1 )\n    3.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.maxsorted( N, x, stride )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.maxsorted( N, x1, stride )\n    3.0\n\nbase.strided.maxsorted.ndarray( N, x, stride, offset )\n    Computes the maximum value of a sorted strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > base.strided.maxsorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.maxsorted.ndarray( N, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmaxsorted, base.strided.max, base.strided.minsorted, base.strided.smaxsorted\n","base.strided.maxsorted.ndarray":"\nbase.strided.maxsorted.ndarray( N, x, stride, offset )\n    Computes the maximum value of a sorted strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > base.strided.maxsorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.maxsorted.ndarray( N, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmaxsorted, base.strided.max, base.strided.minsorted, base.strided.smaxsorted","base.strided.maxViewBufferIndex":"\nbase.strided.maxViewBufferIndex( N, stride, offset )\n    Returns the maximum accessible index based on a set of provided strided\n    array parameters.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    stride: integer\n        Stride length.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    idx: integer\n        Minimum accessible index.\n\n    Examples\n    --------\n    > var idx = base.strided.maxViewBufferIndex( 3, 2, 10 )\n    14\n\n","base.strided.mean":"\nbase.strided.mean( N, x, stride )\n    Computes the arithmetic mean of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.mean( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.mean( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.mean( N, x1, stride )\n    ~-0.3333\n\nbase.strided.mean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.mean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.nanmean, base.strided.smean\n","base.strided.mean.ndarray":"\nbase.strided.mean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.mean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.nanmean, base.strided.smean","base.strided.meankbn":"\nbase.strided.meankbn( N, x, stride )\n    Computes the arithmetic mean of a strided array using an improved Kahan–\n    Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.meankbn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.meankbn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.meankbn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.meankbn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using an improved Kahan–\n    Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meankbn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meankbn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeankbn, base.strided.mean, base.strided.smeankbn\n","base.strided.meankbn.ndarray":"\nbase.strided.meankbn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using an improved Kahan–\n    Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meankbn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meankbn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeankbn, base.strided.mean, base.strided.smeankbn","base.strided.meankbn2":"\nbase.strided.meankbn2( N, x, stride )\n    Computes the arithmetic mean of a strided array using a second-order\n    iterative Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.meankbn2( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.meankbn2( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.meankbn2( N, x1, stride )\n    ~-0.3333\n\nbase.strided.meankbn2.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using a second-order\n    iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meankbn2.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meankbn2.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeankbn2, base.strided.mean, base.strided.smeankbn2\n","base.strided.meankbn2.ndarray":"\nbase.strided.meankbn2.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using a second-order\n    iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meankbn2.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meankbn2.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeankbn2, base.strided.mean, base.strided.smeankbn2","base.strided.meanors":"\nbase.strided.meanors( N, x, stride )\n    Computes the arithmetic mean of a strided array using ordinary recursive\n    summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.meanors( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.meanors( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.meanors( N, x1, stride )\n    ~-0.3333\n\nbase.strided.meanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using ordinary recursive\n    summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanors, base.strided.mean, base.strided.nanmeanors, base.strided.smeanors\n","base.strided.meanors.ndarray":"\nbase.strided.meanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using ordinary recursive\n    summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanors, base.strided.mean, base.strided.nanmeanors, base.strided.smeanors","base.strided.meanpn":"\nbase.strided.meanpn( N, x, stride )\n    Computes the arithmetic mean of a strided array using a two-pass error\n    correction algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.meanpn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.meanpn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.meanpn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.meanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using a two-pass error\n    correction algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.mean, base.strided.nanmeanpn, base.strided.smeanpn\n","base.strided.meanpn.ndarray":"\nbase.strided.meanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using a two-pass error\n    correction algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.mean, base.strided.nanmeanpn, base.strided.smeanpn","base.strided.meanpw":"\nbase.strided.meanpw( N, x, stride )\n    Computes the arithmetic mean of a strided array using pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.meanpw( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.meanpw( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.meanpw( N, x1, stride )\n    ~-0.3333\n\nbase.strided.meanpw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using pairwise summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meanpw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meanpw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpw, base.strided.mean, base.strided.smeanpw\n","base.strided.meanpw.ndarray":"\nbase.strided.meanpw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using pairwise summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meanpw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meanpw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpw, base.strided.mean, base.strided.smeanpw","base.strided.meanwd":"\nbase.strided.meanwd( N, x, stride )\n    Computes the arithmetic mean of a strided array using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.meanwd( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.meanwd( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.meanwd( N, x1, stride )\n    ~-0.3333\n\nbase.strided.meanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using Welford's algorithm\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanwd, base.strided.mean, base.strided.nanmeanwd, base.strided.smeanwd\n","base.strided.meanwd.ndarray":"\nbase.strided.meanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using Welford's algorithm\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanwd, base.strided.mean, base.strided.nanmeanwd, base.strided.smeanwd","base.strided.mediansorted":"\nbase.strided.mediansorted( N, x, stride )\n    Computes the median value of a sorted strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > base.strided.mediansorted( x.length, x, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mediansorted( N, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.mediansorted( N, x1, 2 )\n    2.0\n\nbase.strided.mediansorted.ndarray( N, x, stride, offset )\n    Computes the median value of a sorted strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > base.strided.mediansorted.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mediansorted.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmediansorted, base.strided.mean, base.strided.smediansorted\n","base.strided.mediansorted.ndarray":"\nbase.strided.mediansorted.ndarray( N, x, stride, offset )\n    Computes the median value of a sorted strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > base.strided.mediansorted.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mediansorted.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmediansorted, base.strided.mean, base.strided.smediansorted","base.strided.metaDataProps":"\nbase.strided.metaDataProps( meta, dtypes, obj, bool )\n    Defines non-enumerable read-only properties which expose strided array\n    function meta data.\n\n    Parameters\n    ----------\n    meta: Object\n        Function meta data.\n\n    meta.nargs: integer\n        Total number of arguments (excluding offsets).\n\n    meta.nin: integer\n        Total number of input arrays.\n\n    meta.nout: integer\n        Total number of output arrays.\n\n    dtypes: ArrayLikeObject\n        List of strided array data types.\n\n    obj: Object|Function\n        Object on which to define properties.\n\n    bool: boolean\n        Boolean indicating whether the provided object should describe an\n        \"ndarray\" function interface.\n\n    Returns\n    -------\n    out: Object|Function\n        Object on which properties were defined.\n\n    Examples\n    --------\n    > var meta = { 'nargs': 7, 'nin': 1, 'nout': 1 };\n    > var dt = [ 'float64', 'float64' ];\n    > var obj = {};\n    > base.strided.metaDataProps( meta, dt, obj, false );\n    > obj.nargs\n    7\n    > obj.nin\n    1\n    > obj.nout\n    1\n    > obj.types\n    [...]\n\n","base.strided.min":"\nbase.strided.min( N, x, stride )\n    Computes the minimum value of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.min( x.length, x, 1 )\n    -2.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.min( N, x, stride )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.min( N, x1, stride )\n    -2.0\n\nbase.strided.min.ndarray( N, x, stride, offset )\n    Computes the minimum value of a strided array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.min.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.min.ndarray( N, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.max, base.strided.nanmin, base.strided.smin\n","base.strided.min.ndarray":"\nbase.strided.min.ndarray( N, x, stride, offset )\n    Computes the minimum value of a strided array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.min.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.min.ndarray( N, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.max, base.strided.nanmin, base.strided.smin","base.strided.minabs":"\nbase.strided.minabs( N, x, stride )\n    Computes the minimum absolute value of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.minabs( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.minabs( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.minabs( N, x1, stride )\n    1.0\n\nbase.strided.minabs.ndarray( N, x, stride, offset )\n    Computes the minimum absolute value of a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.minabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.minabs.ndarray( N, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dminabs, base.strided.maxabs, base.strided.min, base.strided.nanminabs, base.strided.sminabs\n","base.strided.minabs.ndarray":"\nbase.strided.minabs.ndarray( N, x, stride, offset )\n    Computes the minimum absolute value of a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.minabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.minabs.ndarray( N, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dminabs, base.strided.maxabs, base.strided.min, base.strided.nanminabs, base.strided.sminabs","base.strided.minBy":"\nbase.strided.minBy( N, x, stride, clbk[, thisArg] )\n    Calculates the minimum value of a strided array via a callback function.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - aidx: array index.\n    - sidx: strided index (offset + aidx*stride).\n    - array: the input array.\n\n    The callback function should return a numeric value.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.minBy( x.length, x, 1, accessor )\n    -10.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.minBy( N, x, 2, accessor )\n    -4.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.minBy( N, x1, 2, accessor )\n    -12.0\n\nbase.strided.minBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the minimum value of a strided array via a callback function and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.minBy.ndarray( x.length, x, 1, 0, accessor )\n    -10.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.minBy.ndarray( N, x, 2, 1, accessor )\n    -12.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.maxBy, base.strided.min, base.strided.nanminBy, base.strided.smin\n","base.strided.minBy.ndarray":"\nbase.strided.minBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the minimum value of a strided array via a callback function and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.minBy.ndarray( x.length, x, 1, 0, accessor )\n    -10.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.minBy.ndarray( N, x, 2, 1, accessor )\n    -12.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.maxBy, base.strided.min, base.strided.nanminBy, base.strided.smin","base.strided.minsorted":"\nbase.strided.minsorted( N, x, stride )\n    Computes the minimum value of a sorted strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > base.strided.minsorted( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.minsorted( N, x, stride )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.minsorted( N, x1, stride )\n    -2.0\n\nbase.strided.minsorted.ndarray( N, x, stride, offset )\n    Computes the minimum value of a sorted strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > base.strided.minsorted.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.minsorted.ndarray( N, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dminsorted, base.strided.maxsorted, base.strided.min, base.strided.sminsorted\n","base.strided.minsorted.ndarray":"\nbase.strided.minsorted.ndarray( N, x, stride, offset )\n    Computes the minimum value of a sorted strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > base.strided.minsorted.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.minsorted.ndarray( N, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dminsorted, base.strided.maxsorted, base.strided.min, base.strided.sminsorted","base.strided.minViewBufferIndex":"\nbase.strided.minViewBufferIndex( N, stride, offset )\n    Returns the minimum accessible index based on a set of provided strided\n    array parameters.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    stride: integer\n        Stride length.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    idx: integer\n        Minimum accessible index.\n\n    Examples\n    --------\n    > var idx = base.strided.minViewBufferIndex( 3, -2, 10 )\n    6\n\n    See Also\n    --------\n    base.strided.offsetView\n","base.strided.mskmax":"\nbase.strided.mskmax( N, x, strideX, mask, strideMask )\n    Computes the maximum value of a strided array according to a mask.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 4.0, 2.0 ];\n    > var mask = [ 0, 0, 1, 0 ];\n    > base.strided.mskmax( x.length, x, 1, mask, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mskmax( N, x, 2, mask, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.mskmax( N, x1, 2, mask1, 2 )\n    2.0\n\nbase.strided.mskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a strided array according to a mask and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n    > var mask = [ 0, 0, 0, 1 ];\n    > base.strided.mskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmskmax, base.strided.max, base.strided.mskmin, base.strided.nanmax, base.strided.smskmax\n","base.strided.mskmax.ndarray":"\nbase.strided.mskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a strided array according to a mask and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n    > var mask = [ 0, 0, 0, 1 ];\n    > base.strided.mskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmskmax, base.strided.max, base.strided.mskmin, base.strided.nanmax, base.strided.smskmax","base.strided.mskmin":"\nbase.strided.mskmin( N, x, strideX, mask, strideMask )\n    Computes the minimum value of a strided array according to a mask.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, -4.0, 2.0 ];\n    > var mask = [ 0, 0, 1, 0 ];\n    > base.strided.mskmin( x.length, x, 1, mask, 1 )\n    -2.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mskmin( N, x, 2, mask, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.mskmin( N, x1, 2, mask1, 2 )\n    -2.0\n\nbase.strided.mskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a strided array according to a mask and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, -4.0 ];\n    > var mask = [ 0, 0, 0, 1 ];\n    > base.strided.mskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmskmin, base.strided.min, base.strided.mskmax, base.strided.nanmin, base.strided.smskmin\n","base.strided.mskmin.ndarray":"\nbase.strided.mskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a strided array according to a mask and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, -4.0 ];\n    > var mask = [ 0, 0, 0, 1 ];\n    > base.strided.mskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmskmin, base.strided.min, base.strided.mskmax, base.strided.nanmin, base.strided.smskmin","base.strided.mskrange":"\nbase.strided.mskrange( N, x, strideX, mask, strideMask )\n    Computes the range of a strided array according to a mask.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 4.0, 2.0 ];\n    > var mask = [ 0, 0, 1, 0 ];\n    > base.strided.mskrange( x.length, x, 1, mask, 1 )\n    4.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mskrange( N, x, 2, mask, 2 )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.mskrange( N, x1, 2, mask1, 2 )\n    4.0\n\nbase.strided.mskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a strided array according to a mask and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n    > var mask = [ 0, 0, 0, 1 ];\n    > base.strided.mskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dmskrange, base.strided.range, base.strided.mskmax, base.strided.mskmin, base.strided.nanrange, base.strided.smskrange\n","base.strided.mskrange.ndarray":"\nbase.strided.mskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a strided array according to a mask and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n    > var mask = [ 0, 0, 0, 1 ];\n    > base.strided.mskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dmskrange, base.strided.range, base.strided.mskmax, base.strided.mskmin, base.strided.nanrange, base.strided.smskrange","base.strided.mskunary":"\nbase.strided.mskunary( arrays, shape, strides, fcn )\n    Applies a unary callback to elements in a strided input array according to\n    elements in a strided mask array and assigns results to elements in a\n    strided output array.\n\n    The `shape` and `strides` parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided input array, a strided mask\n        array, and one strided output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided arrays.\n\n    fcn: Function\n        Unary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1 ];\n    > base.strided.mskunary( [ x, m, y ], shape, strides, base.abs );\n    > y\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n\nbase.strided.mskunary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a unary callback to elements in a strided input array according to\n    elements in a strided mask array, and assigns results to elements in a\n    strided output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided input array, a strided mask\n        array, and one strided output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided arrays.\n\n    fcn: Function\n        Unary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1 ];\n    > var offsets = [ 0, 0, 0 ];\n    > base.strided.mskunary.ndarray( [ x, m, y ], shape, strides, offsets, base.abs );\n    > y\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    See Also\n    --------\n    base.strided.dmskmap, base.strided.smskmap, base.strided.unary\n","base.strided.mskunary.ndarray":"\nbase.strided.mskunary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a unary callback to elements in a strided input array according to\n    elements in a strided mask array, and assigns results to elements in a\n    strided output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided input array, a strided mask\n        array, and one strided output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided arrays.\n\n    fcn: Function\n        Unary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1 ];\n    > var offsets = [ 0, 0, 0 ];\n    > base.strided.mskunary.ndarray( [ x, m, y ], shape, strides, offsets, base.abs );\n    > y\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    See Also\n    --------\n    base.strided.dmskmap, base.strided.smskmap, base.strided.unary","base.strided.mskunaryDtypeSignatures":"\nbase.strided.mskunaryDtypeSignatures( dtypes1, dtypes2[, options] )\n    Generates a list of masked unary interface signatures from strided array\n    data types.\n\n    The function returns a strided array having a stride length of three (i.e.,\n    every three elements define a masked unary interface signature).\n\n    For each signature (i.e., set of three consecutive non-overlapping strided\n    array elements), the first element is the input data type, the second\n    element is the mask data type, and the last element is the return data type.\n\n    All signatures follow type promotion rules.\n\n    The mask array data type is always `uint8`.\n\n    Parameters\n    ----------\n    dtypes1: ArrayLike<any>\n        List of supported data types for the input argument.\n\n    dtypes2: ArrayLike<any>\n        List of supported data types for the output argument.\n\n    options: Object (optional)\n        Options.\n\n    options.enums: boolean (optional)\n        Boolean flag indicating whether to return signatures as a list of data\n        type enumeration constants. Default: false.\n\n    Returns\n    -------\n    out: Array\n        Strided array containing masked unary interface signatures.\n\n    Examples\n    --------\n    > var dt = strided.dataTypes();\n    > var out = base.strided.mskunaryDtypeSignatures( dt, dt )\n    [...]\n\n    See Also\n    --------\n    base.strided.mskunarySignatureCallbacks\n","base.strided.mskunarySignatureCallbacks":"\nbase.strided.mskunarySignatureCallbacks( table, signatures )\n    Assigns callbacks to masked unary interfaces according to type promotion\n    rules.\n\n    Parameters\n    ----------\n    table: Object\n        Object mapping callbacks to data types.\n\n    table.default: Function\n        Default callback.\n\n    table.complex64: Function\n        Callback to be invoked when input arrays promote to single-precision\n        complex floating-point numbers.\n\n    table.complex128: Function\n        Callback to be invoked when input arrays promote to double precision\n        complex floating-point numbers.\n\n    signatures: ArrayLike<any>\n        Strided array containing masked unary interface signatures.\n\n    Returns\n    -------\n    out: Array<Function>\n        List of callbacks, one per signature.\n\n    Examples\n    --------\n    > var dt = strided.dataTypes();\n    > var sigs = base.strided.mskunaryDtypeSignatures( dt, dt );\n    > var t = {\n    ...     'default': base.identity,\n    ...     'complex64': base.cidentityf,\n    ...     'complex128': base.cidentity\n    ... };\n    > var out = base.strided.mskunarySignatureCallbacks( t, sigs )\n    [...]\n\n    See Also\n    --------\n    base.strided.mskunaryDtypeSignatures\n","base.strided.nanmax":"\nbase.strided.nanmax( N, x, stride )\n    Computes the maximum value of a strided array, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmax( x.length, x, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanmax( N, x, stride )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanmax( N, x1, stride )\n    2.0\n\nbase.strided.nanmax.ndarray( N, x, stride, offset )\n    Computes the maximum value of a strided array, ignoring `NaN` values and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmax.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmax.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmax, base.strided.max, base.strided.nanmin, base.strided.snanmax\n","base.strided.nanmax.ndarray":"\nbase.strided.nanmax.ndarray( N, x, stride, offset )\n    Computes the maximum value of a strided array, ignoring `NaN` values and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmax.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmax.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmax, base.strided.max, base.strided.nanmin, base.strided.snanmax","base.strided.nanmaxabs":"\nbase.strided.nanmaxabs( N, x, stride )\n    Computes the maximum absolute value of a strided array, ignoring `NaN`\n    values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmaxabs( x.length, x, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanmaxabs( N, x, stride )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanmaxabs( N, x1, stride )\n    2.0\n\nbase.strided.nanmaxabs.ndarray( N, x, stride, offset )\n    Computes the maximum absolute value of a strided array, ignoring `NaN`\n    values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmaxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmaxabs.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmaxabs, base.strided.maxabs, base.strided.nanmax, base.strided.nanminabs, base.strided.snanmaxabs\n","base.strided.nanmaxabs.ndarray":"\nbase.strided.nanmaxabs.ndarray( N, x, stride, offset )\n    Computes the maximum absolute value of a strided array, ignoring `NaN`\n    values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmaxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmaxabs.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmaxabs, base.strided.maxabs, base.strided.nanmax, base.strided.nanminabs, base.strided.snanmaxabs","base.strided.nanmaxBy":"\nbase.strided.nanmaxBy( N, x, stride, clbk[, thisArg] )\n    Calculates the maximum value of a strided array via a callback function,\n    ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - aidx: array index.\n    - sidx: strided index (offset + aidx*stride).\n    - array: the input array.\n\n    The callback function should return a numeric value.\n\n    If the callback function returns `NaN`, the value is ignored.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n    > base.strided.nanmaxBy( x.length, x, 1, accessor )\n    8.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmaxBy( N, x, 2, accessor )\n    8.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanmaxBy( N, x1, 2, accessor )\n    -4.0\n\nbase.strided.nanmaxBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the maximum value of a strided array via a callback function,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n    > base.strided.nanmaxBy.ndarray( x.length, x, 1, 0, accessor )\n    8.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmaxBy.ndarray( N, x, 2, 1, accessor )\n    -4.0\n\n    See Also\n    --------\n    base.strided.dnanmax, base.strided.maxBy, base.strided.nanmax, base.strided.nanminBy, base.strided.snanmax\n","base.strided.nanmaxBy.ndarray":"\nbase.strided.nanmaxBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the maximum value of a strided array via a callback function,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n    > base.strided.nanmaxBy.ndarray( x.length, x, 1, 0, accessor )\n    8.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmaxBy.ndarray( N, x, 2, 1, accessor )\n    -4.0\n\n    See Also\n    --------\n    base.strided.dnanmax, base.strided.maxBy, base.strided.nanmax, base.strided.nanminBy, base.strided.snanmax","base.strided.nanmean":"\nbase.strided.nanmean( N, x, stride )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmean( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanmean( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanmean( N, x1, stride )\n    ~-0.3333\n\nbase.strided.nanmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.mean, base.strided.snanmean\n","base.strided.nanmean.ndarray":"\nbase.strided.nanmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.mean, base.strided.snanmean","base.strided.nanmeanors":"\nbase.strided.nanmeanors( N, x, stride )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using ordinary recursive summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmeanors( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanmeanors( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanmeanors( N, x1, stride )\n    ~-0.3333\n\nbase.strided.nanmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanors, base.strided.meanors, base.strided.nanmean, base.strided.snanmeanors\n","base.strided.nanmeanors.ndarray":"\nbase.strided.nanmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanors, base.strided.meanors, base.strided.nanmean, base.strided.snanmeanors","base.strided.nanmeanpn":"\nbase.strided.nanmeanpn( N, x, stride )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using a two-pass error correction algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmeanpn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanmeanpn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanmeanpn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.nanmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using a two-pass error correction algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanpn, base.strided.meanpn, base.strided.nanmean, base.strided.snanmeanpn\n","base.strided.nanmeanpn.ndarray":"\nbase.strided.nanmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using a two-pass error correction algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanpn, base.strided.meanpn, base.strided.nanmean, base.strided.snanmeanpn","base.strided.nanmeanwd":"\nbase.strided.nanmeanwd( N, x, stride )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmeanwd( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanmeanwd( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanmeanwd( N, x1, stride )\n    ~-0.3333\n\nbase.strided.nanmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanwd, base.strided.meanwd, base.strided.nanmean, base.strided.snanmeanwd\n","base.strided.nanmeanwd.ndarray":"\nbase.strided.nanmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanwd, base.strided.meanwd, base.strided.nanmean, base.strided.snanmeanwd","base.strided.nanmin":"\nbase.strided.nanmin( N, x, stride )\n    Computes the minimum value of a strided array, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmin( x.length, x, 1 )\n    -2.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanmin( N, x, stride )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanmin( N, x1, stride )\n    -2.0\n\nbase.strided.nanmin.ndarray( N, x, stride, offset )\n    Computes the minimum value of a strided array, ignoring `NaN` values and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmin.ndarray( N, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dnanmin, base.strided.min, base.strided.nanmax, base.strided.snanmin\n","base.strided.nanmin.ndarray":"\nbase.strided.nanmin.ndarray( N, x, stride, offset )\n    Computes the minimum value of a strided array, ignoring `NaN` values and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmin.ndarray( N, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dnanmin, base.strided.min, base.strided.nanmax, base.strided.snanmin","base.strided.nanminabs":"\nbase.strided.nanminabs( N, x, stride )\n    Computes the minimum absolute value of a strided array, ignoring `NaN`\n    values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanminabs( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanminabs( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanminabs( N, x1, stride )\n    1.0\n\nbase.strided.nanminabs.ndarray( N, x, stride, offset )\n    Computes the minimum absolute value of a strided array, ignoring `NaN`\n    values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanminabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanminabs.ndarray( N, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dnanminabs, base.strided.minabs, base.strided.nanmaxabs, base.strided.nanmin, base.strided.snanminabs\n","base.strided.nanminabs.ndarray":"\nbase.strided.nanminabs.ndarray( N, x, stride, offset )\n    Computes the minimum absolute value of a strided array, ignoring `NaN`\n    values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanminabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanminabs.ndarray( N, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dnanminabs, base.strided.minabs, base.strided.nanmaxabs, base.strided.nanmin, base.strided.snanminabs","base.strided.nanminBy":"\nbase.strided.nanminBy( N, x, stride, clbk[, thisArg] )\n    Calculates the minimum value of a strided array via a callback function,\n    ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - aidx: array index.\n    - sidx: strided index (offset + aidx*stride).\n    - array: the input array.\n\n    The callback function should return a numeric value.\n\n    If the callback function returns `NaN`, the value is ignored.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n    > base.strided.nanminBy( x.length, x, 1, accessor )\n    -10.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, NaN, -3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanminBy( N, x, 2, accessor )\n    -4.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanminBy( N, x1, 2, accessor )\n    -12.0\n\nbase.strided.nanminBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the minimum value of a strided array via a callback function,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n    > base.strided.nanminBy.ndarray( x.length, x, 1, 0, accessor )\n    -10.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanminBy.ndarray( N, x, 2, 1, accessor )\n    -12.0\n\n    See Also\n    --------\n    base.strided.dnanmin, base.strided.minBy, base.strided.nanmaxBy, base.strided.nanmin, base.strided.snanmin\n","base.strided.nanminBy.ndarray":"\nbase.strided.nanminBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the minimum value of a strided array via a callback function,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n    > base.strided.nanminBy.ndarray( x.length, x, 1, 0, accessor )\n    -10.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanminBy.ndarray( N, x, 2, 1, accessor )\n    -12.0\n\n    See Also\n    --------\n    base.strided.dnanmin, base.strided.minBy, base.strided.nanmaxBy, base.strided.nanmin, base.strided.snanmin","base.strided.nanmskmax":"\nbase.strided.nanmskmax( N, x, strideX, mask, strideMask )\n    Computes the maximum value of a strided array according to a mask and\n    ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\n    > var mask = [ 0, 0, 1, 0, 0 ];\n    > base.strided.nanmskmax( x.length, x, 1, mask, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmskmax( N, x, 2, mask, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanmskmax( N, x1, 2, mask1, 2 )\n    2.0\n\nbase.strided.nanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a strided array according to a mask,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n    > var mask = [ 0, 0, 0, 1, 0 ];\n    > base.strided.nanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmskmax, base.strided.mskmax, base.strided.nanmax, base.strided.nanmskmin, base.strided.snanmskmax\n","base.strided.nanmskmax.ndarray":"\nbase.strided.nanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a strided array according to a mask,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n    > var mask = [ 0, 0, 0, 1, 0 ];\n    > base.strided.nanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmskmax, base.strided.mskmax, base.strided.nanmax, base.strided.nanmskmin, base.strided.snanmskmax","base.strided.nanmskmin":"\nbase.strided.nanmskmin( N, x, strideX, mask, strideMask )\n    Computes the minimum value of a strided array according to a mask and\n    ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, -4.0, 2.0, NaN ];\n    > var mask = [ 0, 0, 1, 0, 0 ];\n    > base.strided.nanmskmin( x.length, x, 1, mask, 1 )\n    -2.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmskmin( N, x, 2, mask, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanmskmin( N, x1, 2, mask1, 2 )\n    -2.0\n\nbase.strided.nanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a strided array according to a mask, ignoring\n    `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, -4.0, NaN ];\n    > var mask = [ 0, 0, 0, 1, 0 ];\n    > base.strided.nanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dnanmskmin, base.strided.mskmin, base.strided.nanmin, base.strided.nanmskmax, base.strided.snanmskmin\n","base.strided.nanmskmin.ndarray":"\nbase.strided.nanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a strided array according to a mask, ignoring\n    `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, -4.0, NaN ];\n    > var mask = [ 0, 0, 0, 1, 0 ];\n    > base.strided.nanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dnanmskmin, base.strided.mskmin, base.strided.nanmin, base.strided.nanmskmax, base.strided.snanmskmin","base.strided.nanmskrange":"\nbase.strided.nanmskrange( N, x, strideX, mask, strideMask )\n    Computes the range of a strided array according to a mask and ignoring `NaN`\n    values.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\n    > var mask = [ 0, 0, 1, 0, 0 ];\n    > base.strided.nanmskrange( x.length, x, 1, mask, 1 )\n    4.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmskrange( N, x, 2, mask, 2 )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanmskrange( N, x1, 2, mask1, 2 )\n    4.0\n\nbase.strided.nanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a strided array according to a mask, ignoring `NaN`\n    values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n    > var mask = [ 0, 0, 0, 1, 0 ];\n    > base.strided.nanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dnanmskrange, base.strided.mskrange, base.strided.nanrange, base.strided.nanmskmax, base.strided.nanmskmin, base.strided.snanmskrange\n","base.strided.nanmskrange.ndarray":"\nbase.strided.nanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a strided array according to a mask, ignoring `NaN`\n    values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n    > var mask = [ 0, 0, 0, 1, 0 ];\n    > base.strided.nanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dnanmskrange, base.strided.mskrange, base.strided.nanrange, base.strided.nanmskmax, base.strided.nanmskmin, base.strided.snanmskrange","base.strided.nanrange":"\nbase.strided.nanrange( N, x, stride )\n    Computes the range of a strided array, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanrange( x.length, x, 1 )\n    4.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanrange( N, x, stride )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanrange( N, x1, stride )\n    4.0\n\nbase.strided.nanrange.ndarray( N, x, stride, offset )\n    Computes the range of a strided array, ignoring `NaN` values and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanrange.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanrange.ndarray( N, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dnanrange, base.strided.nanmax, base.strided.nanmin, base.strided.range, base.strided.snanrange\n","base.strided.nanrange.ndarray":"\nbase.strided.nanrange.ndarray( N, x, stride, offset )\n    Computes the range of a strided array, ignoring `NaN` values and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanrange.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanrange.ndarray( N, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dnanrange, base.strided.nanmax, base.strided.nanmin, base.strided.range, base.strided.snanrange","base.strided.nanrangeBy":"\nbase.strided.nanrangeBy( N, x, stride, clbk[, thisArg] )\n    Calculates the range of a strided array via a callback function, ignoring\n    `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - aidx: array index.\n    - sidx: strided index (offset + aidx*stride).\n    - array: the input array.\n\n    The callback function should return a numeric value.\n\n    If the callback function returns `NaN`, the value is ignored.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n    > base.strided.nanrangeBy( x.length, x, 1, accessor )\n    18.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0, 1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanrangeBy( N, x, 2, accessor )\n    14.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanrangeBy( N, x1, 2, accessor )\n    8.0\n\nbase.strided.nanrangeBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the range of a strided array via a callback function, ignoring\n    `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n    > base.strided.nanrangeBy.ndarray( x.length, x, 1, 0, accessor )\n    18.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanrangeBy.ndarray( N, x, 2, 1, accessor )\n    8.0\n\n    See Also\n    --------\n    base.strided.dnanrange, base.strided.nanmaxBy, base.strided.nanminBy, base.strided.nanrange, base.strided.rangeBy, base.strided.snanrange\n","base.strided.nanrangeBy.ndarray":"\nbase.strided.nanrangeBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the range of a strided array via a callback function, ignoring\n    `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n    > base.strided.nanrangeBy.ndarray( x.length, x, 1, 0, accessor )\n    18.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanrangeBy.ndarray( N, x, 2, 1, accessor )\n    8.0\n\n    See Also\n    --------\n    base.strided.dnanrange, base.strided.nanmaxBy, base.strided.nanminBy, base.strided.nanrange, base.strided.rangeBy, base.strided.snanrange","base.strided.nanstdev":"\nbase.strided.nanstdev( N, correction, x, stride )\n    Computes the standard deviation of a strided array ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdev( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdev( N, 1, x, 2 )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanstdev( N, 1, x1, 2 )\n    ~2.0817\n\nbase.strided.nanstdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.nanvariance, base.strided.snanstdev, base.strided.stdev\n","base.strided.nanstdev.ndarray":"\nbase.strided.nanstdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.nanvariance, base.strided.snanstdev, base.strided.stdev","base.strided.nanstdevch":"\nbase.strided.nanstdevch( N, correction, x, stride )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevch( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevch( N, 1, x, 2 )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanstdevch( N, 1, x1, 2 )\n    ~2.0817\n\nbase.strided.nanstdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass trial mean algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevch, base.strided.nanvariancech, base.strided.nanstdev, base.strided.snanstdevch, base.strided.stdevch\n","base.strided.nanstdevch.ndarray":"\nbase.strided.nanstdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass trial mean algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevch, base.strided.nanvariancech, base.strided.nanstdev, base.strided.snanstdevch, base.strided.stdevch","base.strided.nanstdevpn":"\nbase.strided.nanstdevpn( N, correction, x, stride )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevpn( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevpn( N, 1, x, 2 )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanstdevpn( N, 1, x1, 2 )\n    ~2.0817\n\nbase.strided.nanstdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevpn, base.strided.nanvariancepn, base.strided.nanstdev, base.strided.snanstdevpn, base.strided.stdevpn\n","base.strided.nanstdevpn.ndarray":"\nbase.strided.nanstdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevpn, base.strided.nanvariancepn, base.strided.nanstdev, base.strided.snanstdevpn, base.strided.stdevpn","base.strided.nanstdevtk":"\nbase.strided.nanstdevtk( N, correction, x, stride )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevtk( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevtk( N, 1, x, 2 )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanstdevtk( N, 1, x1, 2 )\n    ~2.0817\n\nbase.strided.nanstdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass textbook algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevtk, base.strided.nanvariancetk, base.strided.nanstdev, base.strided.snanstdevtk, base.strided.stdevtk\n","base.strided.nanstdevtk.ndarray":"\nbase.strided.nanstdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass textbook algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevtk, base.strided.nanvariancetk, base.strided.nanstdev, base.strided.snanstdevtk, base.strided.stdevtk","base.strided.nanstdevwd":"\nbase.strided.nanstdevwd( N, correction, x, stride )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevwd( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevwd( N, 1, x, 2 )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanstdevwd( N, 1, x1, 2 )\n    ~2.0817\n\nbase.strided.nanstdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevwd, base.strided.nanvariancewd, base.strided.nanstdev, base.strided.snanstdevwd, base.strided.stdevwd\n","base.strided.nanstdevwd.ndarray":"\nbase.strided.nanstdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevwd, base.strided.nanvariancewd, base.strided.nanstdev, base.strided.snanstdevwd, base.strided.stdevwd","base.strided.nanstdevyc":"\nbase.strided.nanstdevyc( N, correction, x, stride )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass algorithm proposed by Youngs and Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevyc( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevyc( N, 1, x, 2 )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanstdevyc( N, 1, x1, 2 )\n    ~2.0817\n\nbase.strided.nanstdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass algorithm proposed by Youngs and Cramer and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevyc, base.strided.nanvarianceyc, base.strided.nanstdev, base.strided.snanstdevyc, base.strided.stdevyc\n","base.strided.nanstdevyc.ndarray":"\nbase.strided.nanstdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass algorithm proposed by Youngs and Cramer and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevyc, base.strided.nanvarianceyc, base.strided.nanstdev, base.strided.snanstdevyc, base.strided.stdevyc","base.strided.nanvariance":"\nbase.strided.nanvariance( N, correction, x, stride )\n    Computes the variance of a strided array ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariance( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanvariance( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanvariance( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.nanvariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariance, base.strided.nanstdev, base.strided.snanvariance, base.strided.variance\n","base.strided.nanvariance.ndarray":"\nbase.strided.nanvariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariance, base.strided.nanstdev, base.strided.snanvariance, base.strided.variance","base.strided.nanvariancech":"\nbase.strided.nanvariancech( N, correction, x, stride )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancech( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanvariancech( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanvariancech( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.nanvariancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass trial mean algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvariancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancech, base.strided.nanstdevch, base.strided.nanvariance, base.strided.snanvariancech, base.strided.variancech\n","base.strided.nanvariancech.ndarray":"\nbase.strided.nanvariancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass trial mean algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvariancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancech, base.strided.nanstdevch, base.strided.nanvariance, base.strided.snanvariancech, base.strided.variancech","base.strided.nanvariancepn":"\nbase.strided.nanvariancepn( N, correction, x, stride )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancepn( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanvariancepn( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanvariancepn( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.nanvariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancepn, base.strided.nanstdevpn, base.strided.nanvariance, base.strided.snanvariancepn, base.strided.variancepn\n","base.strided.nanvariancepn.ndarray":"\nbase.strided.nanvariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancepn, base.strided.nanstdevpn, base.strided.nanvariance, base.strided.snanvariancepn, base.strided.variancepn","base.strided.nanvariancetk":"\nbase.strided.nanvariancetk( N, correction, x, stride )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancetk( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanvariancetk( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanvariancetk( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.nanvariancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass textbook algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvariancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancetk, base.strided.nanstdevtk, base.strided.nanvariance, base.strided.snanvariancetk, base.strided.variancetk\n","base.strided.nanvariancetk.ndarray":"\nbase.strided.nanvariancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass textbook algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvariancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancetk, base.strided.nanstdevtk, base.strided.nanvariance, base.strided.snanvariancetk, base.strided.variancetk","base.strided.nanvariancewd":"\nbase.strided.nanvariancewd( N, correction, x, stride )\n    Computes the variance of a strided array ignoring `NaN` values and using\n    Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancewd( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanvariancewd( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanvariancewd( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.nanvariancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using\n    Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvariancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancewd, base.strided.nanstdevwd, base.strided.nanvariance, base.strided.snanvariancewd, base.strided.variancewd\n","base.strided.nanvariancewd.ndarray":"\nbase.strided.nanvariancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using\n    Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvariancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancewd, base.strided.nanstdevwd, base.strided.nanvariance, base.strided.snanvariancewd, base.strided.variancewd","base.strided.nanvarianceyc":"\nbase.strided.nanvarianceyc( N, correction, x, stride )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass algorithm proposed by Youngs and Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvarianceyc( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanvarianceyc( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanvarianceyc( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.nanvarianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass algorithm proposed by Youngs and Cramer and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvarianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvarianceyc, base.strided.nanstdevyc, base.strided.nanvariance, base.strided.snanvarianceyc, base.strided.varianceyc\n","base.strided.nanvarianceyc.ndarray":"\nbase.strided.nanvarianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass algorithm proposed by Youngs and Cramer and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvarianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvarianceyc, base.strided.nanstdevyc, base.strided.nanvariance, base.strided.snanvarianceyc, base.strided.varianceyc","base.strided.nullary":"\nbase.strided.nullary( arrays, shape, strides, fcn )\n    Applies a nullary callback and assigns results to elements in a strided\n    output array.\n\n    The `shape` and `strides` parameters determine which elements in the strided\n    output array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride length for the strided output\n        array.\n\n    fcn: Function\n        Nullary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1 ];\n    > var fcn = constantFunction( 3.0 );\n    > base.strided.nullary( [ x ], shape, strides, fcn );\n    > x\n    <Float64Array>[ 3.0, 3.0, 3.0, 3.0 ]\n\n\nbase.strided.nullary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a nullary callback and assigns results to elements in a strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride length for the strided output\n        array.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting index (i.e., index offset) for\n        the strided output array.\n\n    fcn: Function\n        Nullary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1 ];\n    > var offsets = [ 0 ];\n    > var fcn = constantFunction( 3.0 );\n    > base.strided.nullary.ndarray( [ x ], shape, strides, offsets, fcn );\n    > x\n    <Float64Array>[ 3.0, 3.0, 3.0, 3.0 ]\n\n    See Also\n    --------\n    base.strided.binary, base.strided.quaternary, base.strided.quinary, base.strided.ternary, base.strided.unary\n","base.strided.nullary.ndarray":"\nbase.strided.nullary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a nullary callback and assigns results to elements in a strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride length for the strided output\n        array.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting index (i.e., index offset) for\n        the strided output array.\n\n    fcn: Function\n        Nullary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1 ];\n    > var offsets = [ 0 ];\n    > var fcn = constantFunction( 3.0 );\n    > base.strided.nullary.ndarray( [ x ], shape, strides, offsets, fcn );\n    > x\n    <Float64Array>[ 3.0, 3.0, 3.0, 3.0 ]\n\n    See Also\n    --------\n    base.strided.binary, base.strided.quaternary, base.strided.quinary, base.strided.ternary, base.strided.unary","base.strided.offsetView":"\nbase.strided.offsetView( x, offset )\n    Returns a typed array view having the same data type as a provided input\n    typed array and starting at a specified index offset.\n\n    Parameters\n    ----------\n    x: TypedArray\n        Input array.\n\n    offset: integer\n        Starting index of the view relative to the input array.\n\n    Returns\n    -------\n    out: TypedArray\n        Typed array view having the same data type as the input array.\n\n    Examples\n    --------\n    > var x = new Float64Array( 10 );\n    > var out = base.strided.offsetView( x, 0 )\n    <Float64Array>\n    > var bool = ( out.buffer === x.buffer )\n    true\n\n    See Also\n    --------\n    base.strided.minViewBufferIndex\n","base.strided.quaternary":"\nbase.strided.quaternary( arrays, shape, strides, fcn )\n    Applies a quaternary callback to strided input array elements and assigns\n    results to elements in a strided output array.\n\n    The `shape` and `strides` parameters determine which elements in the strided\n    input and output arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing four strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    fcn: Function\n        Quaternary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1, 1, 1 ];\n    > function f( x, y, z, w ) { return x + y + z + w; };\n    > base.strided.quaternary( [ x, y, z, w, u ], shape, strides, f );\n    > u\n    <Float64Array>[ 4.0, 8.0, 12.0, 16.0 ]\n\n\nbase.strided.quaternary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a quaternary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing four strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Quaternary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1, 1, 1 ];\n    > var offsets = [ 0, 0, 0, 0, 0 ];\n    > function f( x, y, z, w ) { return x + y + z + w; };\n    > base.strided.quaternary.ndarray( [ x, y, z, w, u ], shape, strides, offsets, f );\n    > u\n    <Float64Array>[ 4.0, 8.0, 12.0, 16.0 ]\n\n    See Also\n    --------\n    base.strided.binary, base.strided.nullary, base.strided.quinary, base.strided.ternary, base.strided.unary\n","base.strided.quaternary.ndarray":"\nbase.strided.quaternary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a quaternary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing four strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Quaternary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1, 1, 1 ];\n    > var offsets = [ 0, 0, 0, 0, 0 ];\n    > function f( x, y, z, w ) { return x + y + z + w; };\n    > base.strided.quaternary.ndarray( [ x, y, z, w, u ], shape, strides, offsets, f );\n    > u\n    <Float64Array>[ 4.0, 8.0, 12.0, 16.0 ]\n\n    See Also\n    --------\n    base.strided.binary, base.strided.nullary, base.strided.quinary, base.strided.ternary, base.strided.unary","base.strided.quinary":"\nbase.strided.quinary( arrays, shape, strides, fcn )\n    Applies a quinary callback to strided input array elements and assigns\n    results to elements in a strided output array.\n\n    The `shape` and `strides` parameters determine which elements in the strided\n    input and output arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing five strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    fcn: Function\n        Quinary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1, 1, 1, 1 ];\n    > function f( x, y, z, w, u ) { return x + y + z + w + u; };\n    > base.strided.quinary( [ x, y, z, w, u, v ], shape, strides, f );\n    > v\n    <Float64Array>[ 5.0, 10.0, 15.0, 20.0 ]\n\n\nbase.strided.quinary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a quinary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing five strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Quinary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1, 1, 1, 1 ];\n    > var offsets = [ 0, 0, 0, 0, 0, 0 ];\n    > function f( x, y, z, w, u ) { return x + y + z + w + u; };\n    > base.strided.quinary.ndarray( [ x, y, z, w, u, v ], shape, strides, offsets, f );\n    > v\n    <Float64Array>[ 5.0, 10.0, 15.0, 20.0 ]\n\n    See Also\n    --------\n    base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.ternary, base.strided.unary\n","base.strided.quinary.ndarray":"\nbase.strided.quinary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a quinary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing five strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Quinary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1, 1, 1, 1 ];\n    > var offsets = [ 0, 0, 0, 0, 0, 0 ];\n    > function f( x, y, z, w, u ) { return x + y + z + w + u; };\n    > base.strided.quinary.ndarray( [ x, y, z, w, u, v ], shape, strides, offsets, f );\n    > v\n    <Float64Array>[ 5.0, 10.0, 15.0, 20.0 ]\n\n    See Also\n    --------\n    base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.ternary, base.strided.unary","base.strided.range":"\nbase.strided.range( N, x, stride )\n    Computes the range of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.range( x.length, x, 1 )\n    4.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.range( N, x, stride )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.range( N, x1, stride )\n    4.0\n\nbase.strided.range.ndarray( N, x, stride, offset )\n    Computes the range of a strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.range.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.range.ndarray( N, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.drange, base.strided.max, base.strided.min, base.strided.nanrange, base.strided.srange\n","base.strided.range.ndarray":"\nbase.strided.range.ndarray( N, x, stride, offset )\n    Computes the range of a strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.range.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.range.ndarray( N, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.drange, base.strided.max, base.strided.min, base.strided.nanrange, base.strided.srange","base.strided.rangeBy":"\nbase.strided.rangeBy( N, x, stride, clbk[, thisArg] )\n    Calculates the range of a strided array via a callback function.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - aidx: array index.\n    - sidx: strided index (offset + aidx*stride).\n    - array: the input array.\n\n    The callback function should return a numeric value.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.rangeBy( x.length, x, 1, accessor )\n    18.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.rangeBy( N, x, 2, accessor )\n    12.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.rangeBy( N, x1, 2, accessor )\n    8.0\n\nbase.strided.rangeBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the range of a strided array via a callback function and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.rangeBy.ndarray( x.length, x, 1, 0, accessor )\n    18.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.rangeBy.ndarray( N, x, 2, 1, accessor )\n    8.0\n\n    See Also\n    --------\n    base.strided.drange, base.strided.maxBy, base.strided.minBy, base.strided.nanrangeBy, base.strided.range, base.strided.srange\n","base.strided.rangeBy.ndarray":"\nbase.strided.rangeBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the range of a strided array via a callback function and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.rangeBy.ndarray( x.length, x, 1, 0, accessor )\n    18.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.rangeBy.ndarray( N, x, 2, 1, accessor )\n    8.0\n\n    See Also\n    --------\n    base.strided.drange, base.strided.maxBy, base.strided.minBy, base.strided.nanrangeBy, base.strided.range, base.strided.srange","base.strided.reinterpretComplex":"\nbase.strided.reinterpretComplex( x, offset )\n    Returns a real-valued floating-point array view of a complex-valued\n    floating-point array having the same precision.\n\n    Parameters\n    ----------\n    x: Complex128Array|Complex64Array\n        Input array.\n\n    offset: integer\n        Starting index of the view relative to the input array.\n\n    Returns\n    -------\n    out: Float64Array|Float32Array\n        Real-valued floating-point array view.\n\n    Examples\n    --------\n    > var x = new Complex128Array( 10 );\n    > var out = base.strided.reinterpretComplex( x, 0 )\n    <Float64Array>\n    > var bool = ( out.buffer === x.buffer )\n    true\n    > x = new Complex64Array( 10 );\n    > out = base.strided.reinterpretComplex( x, 0 )\n    <Float32Array>\n    > bool = ( out.buffer === x.buffer )\n    true\n\n    See Also\n    --------\n    base.strided.reinterpretComplex128, base.strided.reinterpretComplex64\n","base.strided.reinterpretComplex64":"\nbase.strided.reinterpretComplex64( x, offset )\n    Returns a Float32Array view of a Complex64Array.\n\n    Parameters\n    ----------\n    x: Complex64Array\n        Input array.\n\n    offset: integer\n        Starting index of the view relative to the Complex64Array.\n\n    Returns\n    -------\n    out: Float32Array\n        Float32Array view.\n\n    Examples\n    --------\n    > var x = new Complex64Array( 10 );\n    > var out = base.strided.reinterpretComplex64( x, 0 )\n    <Float32Array>\n    > var bool = ( out.buffer === x.buffer )\n    true\n\n    See Also\n    --------\n    base.strided.reinterpretComplex, base.strided.reinterpretComplex128\n","base.strided.reinterpretComplex128":"\nbase.strided.reinterpretComplex128( x, offset )\n    Returns a Float64Array view of a Complex128Array.\n\n    Parameters\n    ----------\n    x: Complex128Array\n        Input array.\n\n    offset: integer\n        Starting index of the view relative to the Complex128Array.\n\n    Returns\n    -------\n    out: Float64Array\n        Float64Array view.\n\n    Examples\n    --------\n    > var x = new Complex128Array( 10 );\n    > var out = base.strided.reinterpretComplex128( x, 0 )\n    <Float64Array>\n    > var bool = ( out.buffer === x.buffer )\n    true\n\n    See Also\n    --------\n    base.strided.reinterpretComplex, base.strided.reinterpretComplex64\n","base.strided.sabs":"\nbase.strided.sabs( N, x, strideX, y, strideY )\n    Computes the absolute value for each element in a single-precision floating-\n    point strided array `x` and assigns the results to elements in a single-\n    precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sabs( x.length, x, 1, y, 1 )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sabs( N, x, 2, y, -1 )\n    <Float32Array>[ 3.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.sabs( N, x1, -2, y1, 1 )\n    <Float32Array>[ 4.0, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.sabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the absolute value for each element in a single-precision floating-\n    point strided array `x` and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    strided.abs, base.strided.dabs, base.strided.sabs2\n","base.strided.sabs.ndarray":"\nbase.strided.sabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the absolute value for each element in a single-precision floating-\n    point strided array `x` and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    strided.abs, base.strided.dabs, base.strided.sabs2","base.strided.sabs2":"\nbase.strided.sabs2( N, x, strideX, y, strideY )\n    Computes the squared absolute value for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sabs2( x.length, x, 1, y, 1 )\n    <Float32Array>[ 1.0, 4.0, 9.0, 16.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sabs2( N, x, 2, y, -1 )\n    <Float32Array>[ 9.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.sabs2( N, x1, -2, y1, 1 )\n    <Float32Array>[ 16.0, 4.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 16.0, 4.0 ]\n\n\nbase.strided.sabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the squared absolute value for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 4.0, 9.0, 16.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 16.0, 4.0 ]\n\n    See Also\n    --------\n    strided.abs2, base.strided.dabs2, base.strided.sabs\n","base.strided.sabs2.ndarray":"\nbase.strided.sabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the squared absolute value for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 4.0, 9.0, 16.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 16.0, 4.0 ]\n\n    See Also\n    --------\n    strided.abs2, base.strided.dabs2, base.strided.sabs","base.strided.sapx":"\nbase.strided.sapx( N, alpha, x, stride )\n    Adds a constant to each element in a single-precision floating-point strided\n    array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns the strided array unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sapx( x.length, 5.0, x, 1 )\n    <Float32Array>[ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sapx( 3, 5.0, x, 2 )\n    <Float32Array>[ 3.0, 1.0, 8.0, -5.0, 9.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sapx( 3, 5.0, x1, 2 )\n    <Float32Array>[ 3.0, 3.0, 1.0, 5.0, -1.0 ]\n    > x0\n    <Float32Array>[ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n\nbase.strided.sapx.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each element in a single-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sapx.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float32Array>[ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.sapx.ndarray( 3, 5.0, x, 2, 1 )\n    <Float32Array>[ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dapx, base.strided.gapx\n","base.strided.sapx.ndarray":"\nbase.strided.sapx.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each element in a single-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sapx.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float32Array>[ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.sapx.ndarray( 3, 5.0, x, 2, 1 )\n    <Float32Array>[ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dapx, base.strided.gapx","base.strided.sapxsum":"\nbase.strided.sapxsum( N, alpha, x, stride )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum.\n\n    The `N` and stride parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsum( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.sapxsum( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sapxsum( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.sapxsum.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sapxsum.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.gapxsum, base.strided.sapxsumpw, base.strided.ssum\n","base.strided.sapxsum.ndarray":"\nbase.strided.sapxsum.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sapxsum.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.gapxsum, base.strided.sapxsumpw, base.strided.ssum","base.strided.sapxsumkbn":"\nbase.strided.sapxsumkbn( N, alpha, x, stride )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using an improved Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumkbn( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.sapxsumkbn( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sapxsumkbn( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.sapxsumkbn.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumkbn, base.strided.gapxsumkbn, base.strided.sapxsum, base.strided.ssumkbn\n","base.strided.sapxsumkbn.ndarray":"\nbase.strided.sapxsumkbn.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumkbn, base.strided.gapxsumkbn, base.strided.sapxsum, base.strided.ssumkbn","base.strided.sapxsumkbn2":"\nbase.strided.sapxsumkbn2( N, alpha, x, stride )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using a second-order iterative Kahan–Babuška\n    algorithm.\n\n    The `N` and `stride` parameters determine which elements in the \n    strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumkbn2( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.sapxsumkbn2( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sapxsumkbn2( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.sapxsumkbn2.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsum, base.strided.ssumkbn2\n","base.strided.sapxsumkbn2.ndarray":"\nbase.strided.sapxsumkbn2.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsum, base.strided.ssumkbn2","base.strided.sapxsumors":"\nbase.strided.sapxsumors( N, alpha, x, stride )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using ordinary recursive summation.\n\n    The `N` and `stride` parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumors( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sapxsumors( N, 5.0, x, stride )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sapxsumors( N, 5.0, x1, stride )\n    14.0\n\n\nbase.strided.sapxsumors.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using ordinary recursive summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sapxsumors.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumors, base.strided.gapxsumors, base.strided.sapxsum, base.strided.ssumors\n","base.strided.sapxsumors.ndarray":"\nbase.strided.sapxsumors.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using ordinary recursive summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sapxsumors.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumors, base.strided.gapxsumors, base.strided.sapxsum, base.strided.ssumors","base.strided.sapxsumpw":"\nbase.strided.sapxsumpw( N, alpha, x, stride )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using pairwise summation.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumpw( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var stride = 2;\n    > base.strided.sapxsumpw( 3, 5.0, x, stride )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > stride = 2;\n    > base.strided.sapxsumpw( 3, 5.0, x1, stride )\n    14.0\n\n\nbase.strided.sapxsumpw.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using pairwise summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumpw, base.strided.gapxsumpw, base.strided.sapxsum, base.strided.ssumpw\n","base.strided.sapxsumpw.ndarray":"\nbase.strided.sapxsumpw.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using pairwise summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumpw, base.strided.gapxsumpw, base.strided.sapxsum, base.strided.ssumpw","base.strided.sasum":"\nbase.strided.sasum( N, x, stride )\n    Computes the sum of the absolute values.\n\n    The sum of absolute values corresponds to the *L1* norm.\n\n    The `N` and stride parameters determine which elements in `x` are used to\n    compute the sum.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the function returns `0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    sum: float\n        Sum of absolute values.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n    > var s = base.strided.sasum( x.length, x, 1 )\n    15.0\n\n    // Sum every other value:\n    > s = base.strided.sasum( 3, x, 2 )\n    9.0\n\n    // Use view offset; e.g., starting at 2nd element:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > s = base.strided.sasum( 3, x1, 2 )\n    12.0\n\n\nbase.strided.sasum.ndarray( N, x, stride, offset )\n    Computes the sum of absolute values using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    sum: float\n        Sum of absolute values.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n    > var s = base.strided.sasum.ndarray( x.length, x, 1, 0 )\n    15.0\n\n    // Sum the last three elements:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > s = base.strided.sasum.ndarray( 3, x, -1, x.length-1 )\n    15.0\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.gasum\n","base.strided.sasum.ndarray":"\nbase.strided.sasum.ndarray( N, x, stride, offset )\n    Computes the sum of absolute values using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    sum: float\n        Sum of absolute values.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n    > var s = base.strided.sasum.ndarray( x.length, x, 1, 0 )\n    15.0\n\n    // Sum the last three elements:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > s = base.strided.sasum.ndarray( 3, x, -1, x.length-1 )\n    15.0\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.gasum","base.strided.sasumpw":"\nbase.strided.sasumpw( N, x, stride )\n    Computes the sum of absolute values (L1 norm) of single-precision floating-\n    point strided array elements using pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in the strided \n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sasumpw( x.length, x, 1 )\n    5.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.sasumpw( 3, x, 2 )\n    5.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sasumpw( 3, x1, 2 )\n    5.0\n\n\nbase.strided.sasumpw.ndarray( N, x, stride, offset )\n    Computes the sum of absolute values (L1 norm) of single-precision floating-\n    point strided array elements using pairwise summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sasumpw.ndarray( x.length, x, 1, 0 )\n    5.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sasumpw.ndarray( 3, x, 2, 1 )\n    5.0\n\n    See Also\n    --------\n    base.strided.sasum, base.strided.dasumpw, base.strided.gasumpw, base.strided.ssumpw\n","base.strided.sasumpw.ndarray":"\nbase.strided.sasumpw.ndarray( N, x, stride, offset )\n    Computes the sum of absolute values (L1 norm) of single-precision floating-\n    point strided array elements using pairwise summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sasumpw.ndarray( x.length, x, 1, 0 )\n    5.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sasumpw.ndarray( 3, x, 2, 1 )\n    5.0\n\n    See Also\n    --------\n    base.strided.sasum, base.strided.dasumpw, base.strided.gasumpw, base.strided.ssumpw","base.strided.saxpy":"\nbase.strided.saxpy( N, alpha, x, strideX, y, strideY )\n    Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > var alpha = 5.0;\n    > base.strided.saxpy( x.length, alpha, x, 1, y, 1 )\n    <Float32Array>[ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > base.strided.saxpy( 3, alpha, x, 2, y, -1 )\n    <Float32Array>[ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.saxpy( 3, 5.0, x1, -2, y1, 1 )\n    <Float32Array>[ 40.0, 31.0, 22.0 ]\n    > y0\n    <Float32Array>[ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.strided.saxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n    Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > var alpha = 5.0;\n    > base.strided.saxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.saxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n    See Also\n    --------\n    base.strided.daxpy, base.strided.gaxpy\n","base.strided.saxpy.ndarray":"\nbase.strided.saxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n    Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > var alpha = 5.0;\n    > base.strided.saxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.saxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n    See Also\n    --------\n    base.strided.daxpy, base.strided.gaxpy","base.strided.scbrt":"\nbase.strided.scbrt( N, x, strideX, y, strideY )\n    Computes the cube root of each element in a single-precision floating-point \n    strided array `x` and assigns the results to elements in a single-precision \n    floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.scbrt( x.length, x, 1, y, 1 )\n    <Float32Array>[ 0.0, 1.0, 2.0, 3.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.scbrt( N, x, 2, y, -1 )\n    <Float32Array>[ 2.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.scbrt( N, x1, -2, y1, 1 )\n    <Float32Array>[ 3.0, 1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.scbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cube root of each element in a single-precision floating-point \n    strided array `x` and assigns the results to elements in a single-precision \n    floating-point strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.scbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, 1.0, 2.0, 3.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.scbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dcbrt, strided.cbrt, base.strided.ssqrt\n","base.strided.scbrt.ndarray":"\nbase.strided.scbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cube root of each element in a single-precision floating-point \n    strided array `x` and assigns the results to elements in a single-precision \n    floating-point strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.scbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, 1.0, 2.0, 3.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.scbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dcbrt, strided.cbrt, base.strided.ssqrt","base.strided.sceil":"\nbase.strided.sceil( N, x, strideX, y, strideY )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward positive infinity and assigns the results to elements in a single-\n    precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sceil( x.length, x, 1, y, 1 )\n    <Float32Array>[ 2.0, 3.0, -3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sceil( N, x, 2, y, -1 )\n    <Float32Array>[ -3.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.sceil( N, x1, -2, y1, 1 )\n    <Float32Array>[ 4.0, 3.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.sceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward positive infinity and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 2.0, 3.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n    See Also\n    --------\n    strided.ceil, base.strided.dceil, base.strided.sfloor, base.strided.strunc\n","base.strided.sceil.ndarray":"\nbase.strided.sceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward positive infinity and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 2.0, 3.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n    See Also\n    --------\n    strided.ceil, base.strided.dceil, base.strided.sfloor, base.strided.strunc","base.strided.scopy":"\nbase.strided.scopy( N, x, strideX, y, strideY )\n    Copies values from `x` into `y`.\n\n    The `N` and stride parameters determine how values from `x` are copied\n    into `y`.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.scopy( x.length, x, 1, y, 1 )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.scopy( 3, x, -2, y, 1 )\n    <Float32Array>[ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n    // Using typed array views:\n    > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.scopy( 3, x1, -2, y1, 1 )\n    <Float32Array>[ 6.0, 4.0, 2.0 ]\n    > y0\n    <Float32Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.scopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Copies values from `x` into `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.scopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dcopy, base.strided.gcopy, base.strided.sswap\n","base.strided.scopy.ndarray":"\nbase.strided.scopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Copies values from `x` into `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.scopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dcopy, base.strided.gcopy, base.strided.sswap","base.strided.scumax":"\nbase.strided.scumax( N, x, strideX, y, strideY )\n    Computes the cumulative maximum of single-precision floating-point strided\n    array elements.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scumax( x.length, x, 1, y, 1 )\n    <Float32Array>[ 1.0, 1.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scumax( 3, x, 2, y, 2 )\n    <Float32Array>[ -2.0, 0.0, 1.0, 0.0, 2.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float32Array( x0.length );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.scumax( 3, x1, 2, y1, 1 )\n    <Float32Array>[ -2.0, 2.0, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.0, -2.0, 2.0, 2.0 ]\n\n\nbase.strided.scumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum of single-precision floating-point strided\n    array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 1.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumax, base.strided.dcumax, base.strided.scumin\n","base.strided.scumax.ndarray":"\nbase.strided.scumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum of single-precision floating-point strided\n    array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 1.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumax, base.strided.dcumax, base.strided.scumin","base.strided.scumaxabs":"\nbase.strided.scumaxabs( N, x, strideX, y, strideY )\n    Computes the cumulative maximum absolute value of single-precision floating-\n    point strided array elements.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scumaxabs( x.length, x, 1, y, 1 )\n    <Float32Array>[ 1.0, 2.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.scumaxabs( N, x, 2, y, 2 )\n    <Float32Array>[ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float32Array( x0.length );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.scumaxabs( N, x1, 2, y1, 1 )\n    <Float32Array>[ 2.0, 2.0, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\nbase.strided.scumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum absolute value of single-precision floating-\n    point strided array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.scumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cumaxabs, base.strided.dcumaxabs, base.strided.scumax, base.strided.scuminabs\n","base.strided.scumaxabs.ndarray":"\nbase.strided.scumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum absolute value of single-precision floating-\n    point strided array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.scumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cumaxabs, base.strided.dcumaxabs, base.strided.scumax, base.strided.scuminabs","base.strided.scumin":"\nbase.strided.scumin( N, x, strideX, y, strideY )\n    Computes the cumulative minimum of single-precision floating-point strided\n    array elements.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scumin( x.length, x, 1, y, 1 )\n    <Float32Array>[ 1.0, -2.0, -2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.scumin( N, x, 2, y, 2 )\n    <Float32Array>[ -2.0, 0.0, -2.0, 0.0, -2.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float32Array( x0.length );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.scumin( N, x1, 2, y1, 1 )\n    <Float32Array>[ -2.0, -2.0, -2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\nbase.strided.scumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum of single-precision floating-point strided\n    array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -2.0, -2.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.scumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumin, base.strided.dcumin, base.strided.scumax\n","base.strided.scumin.ndarray":"\nbase.strided.scumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum of single-precision floating-point strided\n    array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -2.0, -2.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.scumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumin, base.strided.dcumin, base.strided.scumax","base.strided.scuminabs":"\nbase.strided.scuminabs( N, x, strideX, y, strideY )\n    Computes the cumulative minimum absolute value of single-precision floating-\n    point strided array elements.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scuminabs( x.length, x, 1, y, 1 )\n    <Float32Array>[ 1.0, 1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.scuminabs( N, x, 2, y, 2 )\n    <Float32Array>[ 2.0, 0.0, 1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float32Array( x0.length );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.scuminabs( N, x1, 2, y1, 1 )\n    <Float32Array>[ 2.0, 2.0, 1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 1.0 ]\n\nbase.strided.scuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum absolute value of single-precision floating-\n    point strided array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.scuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cuminabs, base.strided.dcuminabs, base.strided.scumaxabs, base.strided.scumin\n","base.strided.scuminabs.ndarray":"\nbase.strided.scuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum absolute value of single-precision floating-\n    point strided array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.scuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cuminabs, base.strided.dcuminabs, base.strided.scumaxabs, base.strided.scumin","base.strided.scusum":"\nbase.strided.scusum( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements.\n\n    The `N` and `stride` parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusum( x.length, 0.0, x, 1, y, 1 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusum( 3, 0.0, x, 2, y, 2 )\n    <Float32Array>[ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float32Array( x0.length );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.scusum( 3, 0.0, x1, 2, y1, 1 )\n    <Float32Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusum, base.strided.scusumpw\n","base.strided.scusum.ndarray":"\nbase.strided.scusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusum, base.strided.scusumpw","base.strided.scusumkbn":"\nbase.strided.scusumkbn( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using an improved Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumkbn( x.length, 0.0, x, 1, y, 1 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumkbn( 3, 0.0, x, 2, y, 2 )\n    <Float32Array>[ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float32Array( x0.length );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.scusumkbn( N, 0.0, x1, 2, y1, 1 )\n    <Float32Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumkbn, base.strided.gcusumkbn, base.strided.scusum, base.strided.scusumkbn2\n","base.strided.scusumkbn.ndarray":"\nbase.strided.scusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumkbn, base.strided.gcusumkbn, base.strided.scusum, base.strided.scusumkbn2","base.strided.scusumkbn2":"\nbase.strided.scusumkbn2( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of single-precision floating-point strided \n    array elements using a second-order iterative Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use \n    a typed array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumkbn2( x.length, 0.0, x, 1, y, 1 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumkbn2( 3, 0.0, x, 2, y, 2 )\n    <Float32Array>[ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float32Array( x0.length );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.scusumkbn2( N, 0.0, x1, 2, y1, 1 )\n    <Float32Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of single-precision floating-point strided\n    array elements using a second-order iterative Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameter supports indexing semantics\n    based on starting indices.\n\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n\n    See Also\n    --------\n    base.strided.dcusumkbn2, base.strided.gcusumkbn2, base.strided.scusum, base.strided.scusumkbn\n","base.strided.scusumkbn2.ndarray":"\nbase.strided.scusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of single-precision floating-point strided\n    array elements using a second-order iterative Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameter supports indexing semantics\n    based on starting indices.\n\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n\n    See Also\n    --------\n    base.strided.dcusumkbn2, base.strided.gcusumkbn2, base.strided.scusum, base.strided.scusumkbn","base.strided.scusumors":"\nbase.strided.scusumors( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using ordinary recursive summation.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n     are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumors( x.length, 0.0, x, 1, y, 1 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumors( 3, 0.0, x, 2, y, 2 )\n    <Float32Array>[ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float32Array( x0.length );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.scusumors( 3, 0.0, x1, 2, y1, 1 )\n    <Float32Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using ordinary recursive summation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumors, base.strided.gcusumors, base.strided.scusum\n","base.strided.scusumors.ndarray":"\nbase.strided.scusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using ordinary recursive summation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumors, base.strided.gcusumors, base.strided.scusum","base.strided.scusumpw":"\nbase.strided.scusumpw( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using pairwise summation.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumpw( x.length, 0.0, x, 1, y, 1 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumpw( 3, 0.0, x, 2, y, 2 )\n    <Float32Array>[ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float32Array( x0.length );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.scusumpw( 3, 0.0, x1, 2, y1, 1 )\n    <Float32Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumpw, base.strided.gcusumpw, base.strided.scusum\n","base.strided.scusumpw.ndarray":"\nbase.strided.scusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumpw, base.strided.gcusumpw, base.strided.scusum","base.strided.sdeg2rad":"\nbase.strided.sdeg2rad( N, x, strideX, y, strideY )\n    Converts each element in a single-precision floating-point strided array `x`\n    from degrees to radians and assigns the results to elements in a single-\n    precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sdeg2rad( x.length, x, 1, y, 1 )\n    <Float32Array>[ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sdeg2rad( N, x, 2, y, -1 )\n    <Float32Array>[ ~0.785, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.sdeg2rad( N, x1, -2, y1, 1 )\n    <Float32Array>[ ~1.047, ~0.524 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.sdeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Converts each element in a single-precision floating-point strided array `x`\n    from degrees to radians and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sdeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sdeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n    See Also\n    --------\n    base.strided.ddeg2rad, strided.deg2rad\n","base.strided.sdeg2rad.ndarray":"\nbase.strided.sdeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Converts each element in a single-precision floating-point strided array `x`\n    from degrees to radians and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sdeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sdeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n    See Also\n    --------\n    base.strided.ddeg2rad, strided.deg2rad","base.strided.sdot":"\nbase.strided.sdot( N, x, strideX, y, strideY )\n    Computes the dot product of two single-precision floating-point vectors.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: float\n        The dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var out = base.strided.sdot( x.length, x, 1, y, 1 )\n    -5.0\n\n    // Strides:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > out = base.strided.sdot( 3, x, 2, y, -1 )\n    9.0\n\n    // Using view offsets:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n    > out = base.strided.sdot( 3, x1, -2, y1, 1 )\n    128.0\n\n\nbase.strided.sdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the dot product of two single-precision floating-point vectors\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing based on a starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: float\n        The dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var out = base.strided.sdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    -5.0\n\n    // Strides:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > out = base.strided.sdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n    9.0\n\n    // Using offset indices:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > out = base.strided.sdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n    128.0\n\n    See Also\n    --------\n    base.strided.ddot, base.strided.dsdot, base.strided.sdsdot, sdot\n","base.strided.sdot.ndarray":"\nbase.strided.sdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the dot product of two single-precision floating-point vectors\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing based on a starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: float\n        The dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var out = base.strided.sdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    -5.0\n\n    // Strides:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > out = base.strided.sdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n    9.0\n\n    // Using offset indices:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > out = base.strided.sdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n    128.0\n\n    See Also\n    --------\n    base.strided.ddot, base.strided.dsdot, base.strided.sdsdot, sdot","base.strided.sdsapxsum":"\nbase.strided.sdsapxsum( N, alpha, x, stride )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using extended accumulation.\n\n    The `N` and `stride` parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsapxsum( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.sdsapxsum( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sdsapxsum( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.sdsapxsum.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using extended accumulation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sdsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dsapxsum, base.strided.sapxsum, base.strided.sdssum\n","base.strided.sdsapxsum.ndarray":"\nbase.strided.sdsapxsum.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using extended accumulation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sdsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dsapxsum, base.strided.sapxsum, base.strided.sdssum","base.strided.sdsapxsumpw":"\nbase.strided.sdsapxsumpw( N, alpha, x, stride )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using pairwise summation with extended\n    accumulation.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsapxsumpw( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.sdsapxsumpw( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sdsapxsumpw( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.sdsapxsumpw.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using pairwise summation with extended\n    accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sdsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dsapxsumpw, base.strided.sapxsumpw, base.strided.sdsapxsum, base.strided.sdssumpw","base.strided.sdsapxsumpw.ndarray":"\nbase.strided.sdsapxsumpw.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using pairwise summation with extended\n    accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sdsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dsapxsumpw, base.strided.sapxsumpw, base.strided.sdsapxsum, base.strided.sdssumpw","base.strided.sdsdot":"\nbase.strided.sdsdot( N, scalar, x, strideX, y, strideY )\n    Computes the dot product of two single-precision floating-point vectors with\n    extended accumulation.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0` the function returns the provided scalar constant.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    scalar: number\n        Scalar constant added to dot product.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: number\n        The dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var out = base.strided.sdsdot( x.length, 0.0, x, 1, y, 1 )\n    -5.0\n\n    // Strides:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > out = base.strided.sdsdot( 3, 0.0, x, 2, y, -1 )\n    9.0\n\n    // Using view offsets:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n    > out = base.strided.sdsdot( 3, 0.0, x1, -2, y1, 1 )\n    128.0\n\n\nbase.strided.sdsdot.ndarray( N, scalar, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the dot product of two single-precision floating-point vectors\n    using alternative indexing semantics and with extended accumulation.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing based on a starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    scalar: number\n        Scalar constant added to dot product.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: number\n        The dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var out = base.strided.sdsdot.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    -5.0\n\n    // Strides:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > out = base.strided.sdsdot.ndarray( 3, 0.0, x, 2, 0, y, 2, 0 )\n    9.0\n\n    // Using offset indices:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > out = base.strided.sdsdot.ndarray( 3, 0.0, x, -2, x.length-1, y, 1, 3 )\n    128.0\n\n    References\n    ----------\n    - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n    Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n    Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n    NY, USA: Association for Computing Machinery: 324–25.\n    doi:10.1145/355841.355848.\n\n    See Also\n    --------\n    base.strided.ddot, base.strided.dsdot, base.strided.sdot\n","base.strided.sdsdot.ndarray":"\nbase.strided.sdsdot.ndarray( N, scalar, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the dot product of two single-precision floating-point vectors\n    using alternative indexing semantics and with extended accumulation.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing based on a starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    scalar: number\n        Scalar constant added to dot product.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: number\n        The dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var out = base.strided.sdsdot.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    -5.0\n\n    // Strides:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > out = base.strided.sdsdot.ndarray( 3, 0.0, x, 2, 0, y, 2, 0 )\n    9.0\n\n    // Using offset indices:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > out = base.strided.sdsdot.ndarray( 3, 0.0, x, -2, x.length-1, y, 1, 3 )\n    128.0\n\n    References\n    ----------\n    - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n    Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n    Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n    NY, USA: Association for Computing Machinery: 324–25.\n    doi:10.1145/355841.355848.\n\n    See Also\n    --------\n    base.strided.ddot, base.strided.dsdot, base.strided.sdot","base.strided.sdsmean":"\nbase.strided.sdsmean( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using extended accumulation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsmean( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sdsmean( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sdsmean( N, x1, stride )\n    ~-0.3333\n\nbase.strided.sdsmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using extended accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sdsmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsnanmean, base.strided.smean\n","base.strided.sdsmean.ndarray":"\nbase.strided.sdsmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using extended accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sdsmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsnanmean, base.strided.smean","base.strided.sdsmeanors":"\nbase.strided.sdsmeanors( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation with extended accumulation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsmeanors( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sdsmeanors( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sdsmeanors( N, x1, stride )\n    ~-0.3333\n\nbase.strided.sdsmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation with extended accumulation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sdsmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.sdsmean, base.strided.sdsnanmeanors\n","base.strided.sdsmeanors.ndarray":"\nbase.strided.sdsmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation with extended accumulation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sdsmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.sdsmean, base.strided.sdsnanmeanors","base.strided.sdsnanmean":"\nbase.strided.sdsnanmean( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using extended accumulation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnanmean( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sdsnanmean( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sdsnanmean( N, x1, stride )\n    ~-0.3333\n\nbase.strided.sdsnanmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using extended accumulation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnanmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sdsnanmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.dsnanmean, base.strided.nanmean, base.strided.sdsmean, base.strided.snanmean\n","base.strided.sdsnanmean.ndarray":"\nbase.strided.sdsnanmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using extended accumulation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnanmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sdsnanmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.dsnanmean, base.strided.nanmean, base.strided.sdsmean, base.strided.snanmean","base.strided.sdsnanmeanors":"\nbase.strided.sdsnanmeanors( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation with\n    extended accumulation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnanmeanors( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sdsnanmeanors( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sdsnanmeanors( N, x1, stride )\n    ~-0.3333\n\nbase.strided.sdsnanmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation with\n    extended accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnanmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sdsnanmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.sdsmeanors, base.strided.sdsnanmean\n","base.strided.sdsnanmeanors.ndarray":"\nbase.strided.sdsnanmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation with\n    extended accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnanmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sdsnanmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.sdsmeanors, base.strided.sdsnanmean","base.strided.sdsnansum":"\nbase.strided.sdsnansum( N, x, stride )\n    Computes the sum of single-precision floating-point strided array\n    elements, ignore `NaN` values and using extended accumulation.\n\n    The `N` and `stride` parameters determine which elements in the\n    strided array are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnansum( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > var stride = 2;\n    > base.strided.sdsnansum( 4, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > stride = 2;\n    > base.strided.sdsnansum( 4, x1, stride )\n    -1.0\n\n\nbase.strided.sdsnansum.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using extended accumulation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnansum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.sdsnansum.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnansum, base.strided.dnansum, base.strided.gnansum, base.strided.sdssum, base.strided.snansum\n","base.strided.sdsnansum.ndarray":"\nbase.strided.sdsnansum.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using extended accumulation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnansum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.sdsnansum.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnansum, base.strided.dnansum, base.strided.gnansum, base.strided.sdssum, base.strided.snansum","base.strided.sdsnansumpw":"\nbase.strided.sdsnansumpw( N, x, stride )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation with extended\n    accumulation.\n\n    The `N` and `stride` parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnansumpw( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.sdsnansumpw( 4, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sdsnansumpw( 4, x1, 2 )\n    -1.0\n\n\nbase.strided.sdsnansumpw.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation with extended\n    accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnansumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.sdsnansumpw.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnansumpw, base.strided.dnansumpw, base.strided.gnansumpw, base.strided.sdsnansum, base.strided.sdssumpw, base.strided.snansumpw\n","base.strided.sdsnansumpw.ndarray":"\nbase.strided.sdsnansumpw.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation with extended\n    accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnansumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.sdsnansumpw.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnansumpw, base.strided.dnansumpw, base.strided.gnansumpw, base.strided.sdsnansum, base.strided.sdssumpw, base.strided.snansumpw","base.strided.sdssum":"\nbase.strided.sdssum( N, x, stride )\n    Computes the sum of single-precision floating-point strided array elements\n    using extended accumulation.\n\n    The `N` and stride parameters determine which elements in \n    the strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdssum( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var stride = 2;\n    > base.strided.sdssum( 3, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > stride = 2;\n    > base.strided.sdssum( 3, x1, stride )\n    -1.0\n\n\nbase.strided.sdssum.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements\n    using extended accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdssum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sdssum.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dssum, base.strided.dsum, base.strided.sdsnansum, base.strided.ssum, base.strided.gsum\n","base.strided.sdssum.ndarray":"\nbase.strided.sdssum.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements\n    using extended accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdssum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sdssum.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dssum, base.strided.dsum, base.strided.sdsnansum, base.strided.ssum, base.strided.gsum","base.strided.sdssumpw":"\nbase.strided.sdssumpw( N, x, stride )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation with extended accumulation.\n\n    The `N` and stride parameters determine which elements in the strided\n    array are accessed are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset,\n    use a typed array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdssumpw( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var stride = 2;\n    > base.strided.sdssumpw( 3, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > stride = 2;\n    > base.strided.sdssumpw( 3, x1, stride )\n    -1.0\n\n\nbase.strided.sdssumpw.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation with extended accumulation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdssumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sdssumpw.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dssumpw, base.strided.dsumpw, base.strided.sdsnansumpw, base.strided.sdssum, base.strided.ssumpw, base.strided.gsumpw\n","base.strided.sdssumpw.ndarray":"\nbase.strided.sdssumpw.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation with extended accumulation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdssumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sdssumpw.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dssumpw, base.strided.dsumpw, base.strided.sdsnansumpw, base.strided.sdssum, base.strided.ssumpw, base.strided.gsumpw","base.strided.sfill":"\nbase.strided.sfill( N, alpha, x, strideX )\n    Fills a single-precision floating-point strided array with a specified\n    scalar value.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sfill( x.length, 5.0, x, 1 )\n    <Float32Array>[ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sfill( 3, 5.0, x, 2 )\n    <Float32Array>[ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sfill( 3, 5.0, x1, 2 )\n    <Float32Array>[ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n    > x0\n    <Float32Array>[ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.sfill.ndarray( N, alpha, x, strideX, offsetX )\n    Fills a single-precision floating-point strided array with a specified\n    scalar value using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sfill.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float32Array>[ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.sfill.ndarray( 3, 5.0, x, 2, 1 )\n    <Float32Array>[ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n    See Also\n    --------\n    base.strided.dfill, base.strided.gfill\n","base.strided.sfill.ndarray":"\nbase.strided.sfill.ndarray( N, alpha, x, strideX, offsetX )\n    Fills a single-precision floating-point strided array with a specified\n    scalar value using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sfill.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float32Array>[ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.sfill.ndarray( 3, 5.0, x, 2, 1 )\n    <Float32Array>[ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n    See Also\n    --------\n    base.strided.dfill, base.strided.gfill","base.strided.sfloor":"\nbase.strided.sfloor( N, x, strideX, y, strideY )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward negative infinity and assigns the results to elements in a single-\n    precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sfloor( x.length, x, 1, y, 1 )\n    <Float32Array>[ -2.0, 1.0, 3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sfloor( N, x, 2, y, -1 )\n    <Float32Array>[ 3.0, -2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.sfloor( N, x1, -2, y1, 1 )\n    <Float32Array>[ 4.0, 1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 4.0, 1.0 ]\n\n\nbase.strided.sfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward negative infinity and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ -2.0, 1.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dfloor, strided.floor, base.strided.sceil, base.strided.strunc\n","base.strided.sfloor.ndarray":"\nbase.strided.sfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward negative infinity and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ -2.0, 1.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dfloor, strided.floor, base.strided.sceil, base.strided.strunc","base.strided.sinv":"\nbase.strided.sinv( N, x, strideX, y, strideY )\n    Computes the multiplicative inverse for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sinv( x.length, x, 1, y, 1 )\n    <Float32Array>[ ~-0.05, -1.0, 0.5, 0.25 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sinv( N, x, 2, y, -1 )\n    <Float32Array>[ 0.5, ~-0.05, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.sinv( N, x1, -2, y1, 1 )\n    <Float32Array>[ 0.25, -1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.sinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the multiplicative inverse for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ ~-0.05, -1.0, 0.5, 0.25 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dinv, strided.inv\n","base.strided.sinv.ndarray":"\nbase.strided.sinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the multiplicative inverse for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ ~-0.05, -1.0, 0.5, 0.25 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dinv, strided.inv","base.strided.smap":"\nbase.strided.smap( N, x, strideX, y, strideY, fcn )\n    Applies a unary function to a single-precision floating-point strided input\n    array and assigns results to a single-precision floating-point strided\n    output array.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap( x.length, x, 1, y, 1, base.identityf )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap( 2, x, 2, y, -1, base.identityf )\n    <Float32Array>[ 3.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smap( 2, x1, -2, y1, 1, base.identityf )\n    <Float32Array>[ 4.0, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n    Applies a unary function to a single-precision floating-point strided input\n    array and assigns results to a single-precision floating-point strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identityf )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identityf )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmap, base.strided.unary\n","base.strided.smap.ndarray":"\nbase.strided.smap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n    Applies a unary function to a single-precision floating-point strided input\n    array and assigns results to a single-precision floating-point strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identityf )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identityf )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmap, base.strided.unary","base.strided.smap2":"\nbase.strided.smap2( N, x, sx, y, sy, z, sz, fcn )\n    Applies a binary function to single-precision floating-point strided input\n    arrays and assigns results to a single-precision floating-point strided\n    output array.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    z: Float32Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float32Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap2( x.length, x, 1, y, 1, z, 1, base.addf )\n    <Float32Array>[ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Using `N` and stride parameters:\n    > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap2( 2, x, 2, y, -1, z, 1, base.addf )\n    <Float32Array>[ 3.0, 4.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smap2( 2, x1, -2, y1, 1, z1, 1, base.addf )\n    <Float32Array>[ 7.0, 6.0 ]\n    > z0\n    <Float32Array>[ 0.0, 0.0, 7.0, 6.0 ]\n\n\nbase.strided.smap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n    Applies a binary function to single-precision floating-point strided input\n    arrays and assigns results to a single-precision floating-point strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Float32Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float32Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.addf )\n    <Float32Array>[ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.addf )\n    <Float32Array>[ 0.0, 6.0, 7.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmap2, base.strided.binary\n","base.strided.smap2.ndarray":"\nbase.strided.smap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n    Applies a binary function to single-precision floating-point strided input\n    arrays and assigns results to a single-precision floating-point strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Float32Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float32Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.addf )\n    <Float32Array>[ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.addf )\n    <Float32Array>[ 0.0, 6.0, 7.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmap2, base.strided.binary","base.strided.smax":"\nbase.strided.smax( N, x, strideX )\n    Computes the maximum value of a single-precision floating-point strided\n    array.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smax( x.length, x, 1 )\n    2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.smax( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.smax( 3, x1, 2 )\n    2.0\n\n\nbase.strided.smax.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a single-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smax.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smax.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.max, base.strided.smin, base.strided.snanmax\n","base.strided.smax.ndarray":"\nbase.strided.smax.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a single-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smax.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smax.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.max, base.strided.smin, base.strided.snanmax","base.strided.smaxabs":"\nbase.strided.smaxabs( N, x, strideX )\n    Computes the maximum absolute value of a single-precision floating-point\n    strided array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smaxabs( x.length, x, 1 )\n    2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.smaxabs( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.smaxabs( 3, x1, 2 )\n    2.0\n\n\nbase.strided.smaxabs.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smaxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.smaxabs.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmaxabs, base.strided.maxabs, base.strided.smax, base.strided.sminabs, base.strided.snanmaxabs\n","base.strided.smaxabs.ndarray":"\nbase.strided.smaxabs.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smaxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.smaxabs.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmaxabs, base.strided.maxabs, base.strided.smax, base.strided.sminabs, base.strided.snanmaxabs","base.strided.smaxabssorted":"\nbase.strided.smaxabssorted( N, x, stride )\n    Computes the maximum absolute value of a sorted single-precision floating-\n    point strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n    > base.strided.smaxabssorted( x.length, x, 1 )\n    3.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.smaxabssorted( N, x, stride )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.smaxabssorted( N, x1, stride )\n    3.0\n\nbase.strided.smaxabssorted.ndarray( N, x, stride, offset )\n    Computes the maximum absolute value of a sorted single-precision floating-\n    point strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n    > base.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smaxabssorted.ndarray( N, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmaxabssorted, base.strided.smaxabs, base.strided.smaxsorted\n","base.strided.smaxabssorted.ndarray":"\nbase.strided.smaxabssorted.ndarray( N, x, stride, offset )\n    Computes the maximum absolute value of a sorted single-precision floating-\n    point strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n    > base.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smaxabssorted.ndarray( N, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmaxabssorted, base.strided.smaxabs, base.strided.smaxsorted","base.strided.smaxsorted":"\nbase.strided.smaxsorted( N, x, stride )\n    Computes the maximum value of a sorted single-precision floating-point\n    strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.smaxsorted( x.length, x, 1 )\n    3.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.smaxsorted( N, x, stride )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.smaxsorted( N, x1, stride )\n    3.0\n\nbase.strided.smaxsorted.ndarray( N, x, stride, offset )\n    Computes the maximum value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smaxsorted.ndarray( N, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmaxsorted, base.strided.maxsorted, base.strided.smax, base.strided.sminsorted\n","base.strided.smaxsorted.ndarray":"\nbase.strided.smaxsorted.ndarray( N, x, stride, offset )\n    Computes the maximum value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smaxsorted.ndarray( N, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmaxsorted, base.strided.maxsorted, base.strided.smax, base.strided.sminsorted","base.strided.smean":"\nbase.strided.smean( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smean( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.smean( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.smean( N, x1, stride )\n    ~-0.3333\n\nbase.strided.smean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsmean, base.strided.snanmean\n","base.strided.smean.ndarray":"\nbase.strided.smean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsmean, base.strided.snanmean","base.strided.smeankbn":"\nbase.strided.smeankbn( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeankbn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.smeankbn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.smeankbn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.smeankbn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeankbn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeankbn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeankbn, base.strided.meankbn, base.strided.smean\n","base.strided.smeankbn.ndarray":"\nbase.strided.smeankbn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeankbn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeankbn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeankbn, base.strided.meankbn, base.strided.smean","base.strided.smeankbn2":"\nbase.strided.smeankbn2( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a second-order iterative Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeankbn2( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.smeankbn2( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.smeankbn2( N, x1, stride )\n    ~-0.3333\n\nbase.strided.smeankbn2.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeankbn2.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeankbn2.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeankbn2, base.strided.meankbn2, base.strided.smean\n","base.strided.smeankbn2.ndarray":"\nbase.strided.smeankbn2.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeankbn2.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeankbn2.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeankbn2, base.strided.meankbn2, base.strided.smean","base.strided.smeanli":"\nbase.strided.smeanli( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanli( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.smeanli( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.smeanli( N, x1, stride )\n    ~-0.3333\n\nbase.strided.smeanli.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanli.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanli.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanli, base.strided.smean, base.strided.smeanlipw\n","base.strided.smeanli.ndarray":"\nbase.strided.smeanli.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanli.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanli.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanli, base.strided.smean, base.strided.smeanlipw","base.strided.smeanlipw":"\nbase.strided.smeanlipw( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm with pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanlipw( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.smeanlipw( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.smeanlipw( N, x1, stride )\n    ~-0.3333\n\nbase.strided.smeanlipw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm with pairwise summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanlipw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanlipw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanlipw, base.strided.smean, base.strided.smeanli\n","base.strided.smeanlipw.ndarray":"\nbase.strided.smeanlipw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm with pairwise summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanlipw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanlipw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanlipw, base.strided.smean, base.strided.smeanli","base.strided.smeanors":"\nbase.strided.smeanors( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanors( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.smeanors( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.smeanors( N, x1, stride )\n    ~-0.3333\n\nbase.strided.smeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanors, base.strided.meanors, base.strided.smean, base.strided.snanmeanors\n","base.strided.smeanors.ndarray":"\nbase.strided.smeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanors, base.strided.meanors, base.strided.smean, base.strided.snanmeanors","base.strided.smeanpn":"\nbase.strided.smeanpn( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a two-pass error correction algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanpn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.smeanpn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.smeanpn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.smeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a two-pass error correction algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.meanpn, base.strided.smean, base.strided.snanmeanpn\n","base.strided.smeanpn.ndarray":"\nbase.strided.smeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a two-pass error correction algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.meanpn, base.strided.smean, base.strided.snanmeanpn","base.strided.smeanpw":"\nbase.strided.smeanpw( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanpw( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.smeanpw( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.smeanpw( N, x1, stride )\n    ~-0.3333\n\nbase.strided.smeanpw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanpw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanpw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpw, base.strided.meanpw, base.strided.smean\n","base.strided.smeanpw.ndarray":"\nbase.strided.smeanpw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanpw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanpw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpw, base.strided.meanpw, base.strided.smean","base.strided.smeanwd":"\nbase.strided.smeanwd( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanwd( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.smeanwd( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.smeanwd( N, x1, stride )\n    ~-0.3333\n\nbase.strided.smeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanwd, base.strided.meanwd, base.strided.smean, base.strided.snanmeanwd\n","base.strided.smeanwd.ndarray":"\nbase.strided.smeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanwd, base.strided.meanwd, base.strided.smean, base.strided.snanmeanwd","base.strided.smediansorted":"\nbase.strided.smediansorted( N, x, stride )\n    Computes the median value of a sorted single-precision floating-point\n    strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.smediansorted( x.length, x, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smediansorted( N, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.smediansorted( N, x1, 2 )\n    2.0\n\nbase.strided.smediansorted.ndarray( N, x, stride, offset )\n    Computes the median value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.smediansorted.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smediansorted.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmediansorted, base.strided.mediansorted, base.strided.smean\n","base.strided.smediansorted.ndarray":"\nbase.strided.smediansorted.ndarray( N, x, stride, offset )\n    Computes the median value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.smediansorted.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smediansorted.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmediansorted, base.strided.mediansorted, base.strided.smean","base.strided.smidrange":"\nbase.strided.smidrange( N, x, strideX )\n    Computes the mid-range of a single-precision floating-point strided array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Mid-range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smidrange( x.length, x, 1 )\n    0.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.smidrange( 3, x, 2 )\n    0.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.smidrange( 3, x1, 2 )\n    0.0\n\n\nbase.strided.smidrange.ndarray( N, x, strideX, offsetX )\n    Computes the mid-range of a single-precision floating-point strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Mid-range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smidrange.ndarray( x.length, x, 1, 0 )\n    0.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.smidrange.ndarray( 3, x, 2, 1 )\n    0.0\n\n    See Also\n    --------\n    base.strided.dmidrange, base.strided.smax, base.strided.smean, base.strided.smin, base.strided.srange\n","base.strided.smidrange.ndarray":"\nbase.strided.smidrange.ndarray( N, x, strideX, offsetX )\n    Computes the mid-range of a single-precision floating-point strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Mid-range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smidrange.ndarray( x.length, x, 1, 0 )\n    0.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.smidrange.ndarray( 3, x, 2, 1 )\n    0.0\n\n    See Also\n    --------\n    base.strided.dmidrange, base.strided.smax, base.strided.smean, base.strided.smin, base.strided.srange","base.strided.smin":"\nbase.strided.smin( N, x, strideX )\n    Computes the minimum value of a single-precision floating-point strided\n    array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smin( x.length, x, 1 )\n    -2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.smin( 3, x, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.smin( 3, x1, 2 )\n    -2.0\n\n\nbase.strided.smin.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a single-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.smin.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.min, base.strided.smax, base.strided.snanmin\n","base.strided.smin.ndarray":"\nbase.strided.smin.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a single-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.smin.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.min, base.strided.smax, base.strided.snanmin","base.strided.sminabs":"\nbase.strided.sminabs( N, x, strideX )\n    Computes the minimum absolute value of a single-precision floating-point\n    strided array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sminabs( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.sminabs( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sminabs( 3, x1, 2 )\n    1.0\n\n\nbase.strided.sminabs.ndarray( N, x, strideX, offsetX )\n    Computes the minimum absolute value of a single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sminabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sminabs.ndarray( 3, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dminabs, base.strided.minabs, base.strided.smaxabs, base.strided.smin, base.strided.snanminabs\n","base.strided.sminabs.ndarray":"\nbase.strided.sminabs.ndarray( N, x, strideX, offsetX )\n    Computes the minimum absolute value of a single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sminabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sminabs.ndarray( 3, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dminabs, base.strided.minabs, base.strided.smaxabs, base.strided.smin, base.strided.snanminabs","base.strided.sminsorted":"\nbase.strided.sminsorted( N, x, stride )\n    Computes the minimum value of a sorted single-precision floating-point\n    strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.sminsorted( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sminsorted( N, x, stride )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sminsorted( N, x1, stride )\n    -2.0\n\nbase.strided.sminsorted.ndarray( N, x, stride, offset )\n    Computes the minimum value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.sminsorted.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sminsorted.ndarray( N, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dminsorted, base.strided.minsorted, base.strided.smaxsorted, base.strided.smin\n","base.strided.sminsorted.ndarray":"\nbase.strided.sminsorted.ndarray( N, x, stride, offset )\n    Computes the minimum value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.sminsorted.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sminsorted.ndarray( N, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dminsorted, base.strided.minsorted, base.strided.smaxsorted, base.strided.smin","base.strided.smskabs":"\nbase.strided.smskabs( N, x, sx, m, sm, y, sy )\n    Computes the absolute value for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ 2.0, 1.0, 0.0, 5.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskabs( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ 5.0, 1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 5.0, 1.0 ]\n\n\nbase.strided.smskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the absolute value for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 2.0, 1.0, 0.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 5.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dmskabs, base.strided.sabs, base.strided.smskabs2\n","base.strided.smskabs.ndarray":"\nbase.strided.smskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the absolute value for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 2.0, 1.0, 0.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 5.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dmskabs, base.strided.sabs, base.strided.smskabs2","base.strided.smskabs2":"\nbase.strided.smskabs2( N, x, sx, m, sm, y, sy )\n    Computes the squared absolute value for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point\n    strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs2( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ 4.0, 1.0, 0.0, 25.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs2( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, 4.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskabs2( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ 25.0, 1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 25.0, 1.0 ]\n\n\nbase.strided.smskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the squared absolute value for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point\n    strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 4.0, 1.0, 0.0, 25.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 25.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dmskabs2, base.strided.sabs2, base.strided.smskabs\n","base.strided.smskabs2.ndarray":"\nbase.strided.smskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the squared absolute value for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point\n    strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 4.0, 1.0, 0.0, 25.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 25.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dmskabs2, base.strided.sabs2, base.strided.smskabs","base.strided.smskcbrt":"\nbase.strided.smskcbrt( N, x, sx, m, sm, y, sy )\n    Computes the cube root for each element in a single-precision floating-point\n    strided array `x` according to a strided mask array and assigns the results\n    to elements in a single-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskcbrt( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ 0.0, 1.0, 0.0, 3.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskcbrt( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskcbrt( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ 3.0, 1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.smskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the cube root for each element in a single-precision floating-point\n    strided array `x` according to a strided mask array and assigns the results\n    to elements in a single-precision floating-point strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, 1.0, 0.0, 3.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dmskcbrt, base.strided.scbrt, base.strided.ssqrt\n","base.strided.smskcbrt.ndarray":"\nbase.strided.smskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the cube root for each element in a single-precision floating-point\n    strided array `x` according to a strided mask array and assigns the results\n    to elements in a single-precision floating-point strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, 1.0, 0.0, 3.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dmskcbrt, base.strided.scbrt, base.strided.ssqrt","base.strided.smskceil":"\nbase.strided.smskceil( N, x, sx, m, sm, y, sy )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward positive infinity according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskceil( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ 2.0, 3.0, 0.0, 4.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskceil( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskceil( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ 4.0, 3.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.smskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward positive infinity according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 2.0, 3.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n    See Also\n    --------\n    base.strided.dmskceil, base.strided.sceil, base.strided.smskfloor, base.strided.smsktrunc\n","base.strided.smskceil.ndarray":"\nbase.strided.smskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward positive infinity according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 2.0, 3.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n    See Also\n    --------\n    base.strided.dmskceil, base.strided.sceil, base.strided.smskfloor, base.strided.smsktrunc","base.strided.smskdeg2rad":"\nbase.strided.smskdeg2rad( N, x, sx, m, sm, y, sy )\n    Converts each element in a single-precision floating-point strided array `x`\n    from degrees to radians according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskdeg2rad( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ 0.0, ~0.524, 0.0, ~1.047 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskdeg2rad( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ ~1.047, ~0.524 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.smskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Converts each element in a single-precision floating-point strided array `x`\n    from degrees to radians according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, ~0.524, 0.0, ~1.047 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n    See Also\n    --------\n    base.strided.dmskdeg2rad, base.strided.sdeg2rad\n","base.strided.smskdeg2rad.ndarray":"\nbase.strided.smskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Converts each element in a single-precision floating-point strided array `x`\n    from degrees to radians according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, ~0.524, 0.0, ~1.047 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n    See Also\n    --------\n    base.strided.dmskdeg2rad, base.strided.sdeg2rad","base.strided.smskfloor":"\nbase.strided.smskfloor( N, x, sx, m, sm, y, sy )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward negative infinity according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskfloor( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskfloor( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskfloor( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ 4.0, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward negative infinity according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmskfloor, base.strided.sfloor, base.strided.smskceil, base.strided.smsktrunc\n","base.strided.smskfloor.ndarray":"\nbase.strided.smskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward negative infinity according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmskfloor, base.strided.sfloor, base.strided.smskceil, base.strided.smsktrunc","base.strided.smskinv":"\nbase.strided.smskinv( N, x, sx, m, sm, y, sy )\n    Computes the multiplicative inverse for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskinv( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ ~-0.05, -1.0, 0.0, 0.25 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskinv( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, ~-0.05, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskinv( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ 0.25, -1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.smskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the multiplicative inverse for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ ~-0.05, -1.0, 0.0, 0.25 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dinv, base.strided.dmskinv\n","base.strided.smskinv.ndarray":"\nbase.strided.smskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the multiplicative inverse for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ ~-0.05, -1.0, 0.0, 0.25 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dinv, base.strided.dmskinv","base.strided.smskmap":"\nbase.strided.smskmap( N, x, sx, m, sm, y, sy, fcn )\n    Applies a unary function to a single-precision floating-point strided input\n    array according to a strided mask array and assigns results to a single-\n    precision floating-point strided output array.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskmap( x.length, x, 1, m, 1, y, 1, base.identity )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskmap( 2, x, 2, m, 2, y, -1, base.identity )\n    <Float32Array>[ 0.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\n    <Float32Array>[ 0.0, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.0, 2.0 ]\n\n\nbase.strided.smskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n    Applies a unary function to a single-precision floating-point strided input\n    array according to a strided mask array and assigns results to a single-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n    <Float32Array>[ 0.0, 0.0, 4.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmskmap, base.strided.mskunary, base.strided.smap, base.strided.smskmap2\n","base.strided.smskmap.ndarray":"\nbase.strided.smskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n    Applies a unary function to a single-precision floating-point strided input\n    array according to a strided mask array and assigns results to a single-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n    <Float32Array>[ 0.0, 0.0, 4.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmskmap, base.strided.mskunary, base.strided.smap, base.strided.smskmap2","base.strided.smskmap2":"\nbase.strided.smskmap2( N, x, sx, y, sy, m, sm, z, sz, fcn )\n    Applies a binary function to single-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a single-\n    precision floating-point strided output array.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    z: Float32Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float32Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.smskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.addf )\n    <Float32Array>[ 2.0, 4.0, 0.0, 8.0 ]\n\n    // Using `N` and stride parameters:\n    > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.addf )\n    <Float32Array>[ 0.0, 3.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.addf )\n    <Float32Array>[ 0.0, 6.0 ]\n    > z0\n    <Float32Array>[ 0.0, 0.0, 0.0, 6.0 ]\n\n\nbase.strided.smskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n    Applies a binary function to single-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a single-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    z: Float32Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float32Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.smskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.addf )\n    <Float32Array>[ 2.0, 4.0, 0.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.smskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.addf )\n    <Float32Array>[ 0.0, 0.0, 7.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmskmap2, base.strided.smap2, base.strided.smskmap\n","base.strided.smskmap2.ndarray":"\nbase.strided.smskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n    Applies a binary function to single-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a single-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    z: Float32Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float32Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.smskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.addf )\n    <Float32Array>[ 2.0, 4.0, 0.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.smskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.addf )\n    <Float32Array>[ 0.0, 0.0, 7.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmskmap2, base.strided.smap2, base.strided.smskmap","base.strided.smskmax":"\nbase.strided.smskmax( N, x, strideX, mask, strideMask )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.smskmax( x.length, x, 1, mask, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smskmax( N, x, 2, mask, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.smskmax( N, x1, 2, mask1, 2 )\n    2.0\n\nbase.strided.smskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmskmax, base.strided.mskmax, base.strided.smax, base.strided.smskmin, base.strided.snanmax, base.strided.snanmskmax\n","base.strided.smskmax.ndarray":"\nbase.strided.smskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmskmax, base.strided.mskmax, base.strided.smax, base.strided.smskmin, base.strided.snanmax, base.strided.snanmskmax","base.strided.smskmin":"\nbase.strided.smskmin( N, x, strideX, mask, strideMask )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.smskmin( x.length, x, 1, mask, 1 )\n    -2.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smskmin( N, x, 2, mask, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.smskmin( N, x1, 2, mask1, 2 )\n    -2.0\n\nbase.strided.smskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmskmin, base.strided.mskmin, base.strided.smin, base.strided.smskmax, base.strided.snanmin, base.strided.snanmskmin\n","base.strided.smskmin.ndarray":"\nbase.strided.smskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmskmin, base.strided.mskmin, base.strided.smin, base.strided.smskmax, base.strided.snanmin, base.strided.snanmskmin","base.strided.smskramp":"\nbase.strided.smskramp( N, x, sx, m, sm, y, sy )\n    Evaluates the ramp function for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskramp( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskramp( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskramp( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ 4.0, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Evaluates the ramp function for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmskramp, base.strided.sramp\n","base.strided.smskramp.ndarray":"\nbase.strided.smskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Evaluates the ramp function for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmskramp, base.strided.sramp","base.strided.smskrange":"\nbase.strided.smskrange( N, x, strideX, mask, strideMask )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.smskrange( x.length, x, 1, mask, 1 )\n    4.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smskrange( N, x, 2, mask, 2 )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.smskrange( N, x1, 2, mask1, 2 )\n    4.0\n\nbase.strided.smskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dmskrange, base.strided.mskrange, base.strided.smskmax, base.strided.smskmin, base.strided.snanrange, base.strided.srange\n","base.strided.smskrange.ndarray":"\nbase.strided.smskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dmskrange, base.strided.mskrange, base.strided.smskmax, base.strided.smskmin, base.strided.snanrange, base.strided.srange","base.strided.smskrsqrt":"\nbase.strided.smskrsqrt( N, x, sx, m, sm, y, sy )\n    Computes the reciprocal square root for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskrsqrt( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ Infinity, 0.5, 0.0, ~0.289 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskrsqrt( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, Infinity, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ ~0.289, 0.5 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.smskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the reciprocal square root for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ Infinity, 0.5, 0.0, ~0.289 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n    See Also\n    --------\n    base.strided.dmskrsqrt, base.strided.smsksqrt, base.strided.srsqrt\n","base.strided.smskrsqrt.ndarray":"\nbase.strided.smskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the reciprocal square root for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ Infinity, 0.5, 0.0, ~0.289 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n    See Also\n    --------\n    base.strided.dmskrsqrt, base.strided.smsksqrt, base.strided.srsqrt","base.strided.smsksqrt":"\nbase.strided.smsksqrt( N, x, sx, m, sm, y, sy )\n    Computes the principal square root for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsksqrt( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ 0.0, 2.0, 0.0, ~3.464 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsksqrt( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smsksqrt( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ ~3.464, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.smsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the principal square root for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, 2.0, 0.0, ~3.464 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmsksqrt, base.strided.smskcbrt, base.strided.smskrsqrt, base.strided.srsqrt\n","base.strided.smsksqrt.ndarray":"\nbase.strided.smsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the principal square root for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, 2.0, 0.0, ~3.464 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmsksqrt, base.strided.smskcbrt, base.strided.smskrsqrt, base.strided.srsqrt","base.strided.smsktrunc":"\nbase.strided.smsktrunc( N, x, sx, m, sm, y, sy )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward zero according to a strided mask array and assigns the results to\n    elements in a single-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsktrunc( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsktrunc( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smsktrunc( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ 4.0, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward zero according to a strided mask array and assigns the results to\n    elements in a single-precision floating-point strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmsktrunc, base.strided.smskceil, base.strided.smskfloor, base.strided.strunc\n","base.strided.smsktrunc.ndarray":"\nbase.strided.smsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward zero according to a strided mask array and assigns the results to\n    elements in a single-precision floating-point strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmsktrunc, base.strided.smskceil, base.strided.smskfloor, base.strided.strunc","base.strided.snanmax":"\nbase.strided.snanmax( N, x, strideX )\n    Computes the maximum value of a single-precision floating-point strided\n    array, ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmax( x.length, x, 1 )\n    2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > base.strided.snanmax( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.snanmax( 3, x1, 2 )\n    2.0\n\n\nbase.strided.snanmax.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a single-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.snanmax.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.snanmax.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmax, base.strided.nanmax, base.strided.smax, base.strided.snanmin\n","base.strided.snanmax.ndarray":"\nbase.strided.snanmax.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a single-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.snanmax.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.snanmax.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmax, base.strided.nanmax, base.strided.smax, base.strided.snanmin","base.strided.snanmaxabs":"\nbase.strided.snanmaxabs( N, x, strideX )\n    Computes the maximum absolute value of a single-precision floating-point\n    strided array, ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmaxabs( x.length, x, 1 )\n    2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > base.strided.snanmaxabs( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.snanmaxabs( 3, x1, 2 )\n    2.0\n\n\nbase.strided.snanmaxabs.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a single-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.snanmaxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.snanmaxabs.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmaxabs, base.strided.nanmaxabs, base.strided.smaxabs, base.strided.snanmax, base.strided.snanminabs\n","base.strided.snanmaxabs.ndarray":"\nbase.strided.snanmaxabs.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a single-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.snanmaxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.snanmaxabs.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmaxabs, base.strided.nanmaxabs, base.strided.smaxabs, base.strided.snanmax, base.strided.snanminabs","base.strided.snanmean":"\nbase.strided.snanmean( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmean( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.snanmean( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.snanmean( N, x1, stride )\n    ~-0.3333\n\nbase.strided.snanmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.smean, base.strided.nanmean\n","base.strided.snanmean.ndarray":"\nbase.strided.snanmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.smean, base.strided.nanmean","base.strided.snanmeanors":"\nbase.strided.snanmeanors( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmeanors( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.snanmeanors( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.snanmeanors( N, x1, stride )\n    ~-0.3333\n\nbase.strided.snanmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanors, base.strided.nanmeanors, base.strided.smeanors, base.strided.snanmean\n","base.strided.snanmeanors.ndarray":"\nbase.strided.snanmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanors, base.strided.nanmeanors, base.strided.smeanors, base.strided.snanmean","base.strided.snanmeanpn":"\nbase.strided.snanmeanpn( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction\n    algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmeanpn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.snanmeanpn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.snanmeanpn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.snanmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction algorithm\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanpn, base.strided.nanmeanpn, base.strided.smeanpn, base.strided.snanmean\n","base.strided.snanmeanpn.ndarray":"\nbase.strided.snanmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction algorithm\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanpn, base.strided.nanmeanpn, base.strided.smeanpn, base.strided.snanmean","base.strided.snanmeanwd":"\nbase.strided.snanmeanwd( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmeanwd( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.snanmeanwd( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.snanmeanwd( N, x1, stride )\n    ~-0.3333\n\nbase.strided.snanmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanwd, base.strided.nanmeanwd, base.strided.smeanwd, base.strided.snanmean\n","base.strided.snanmeanwd.ndarray":"\nbase.strided.snanmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanwd, base.strided.nanmeanwd, base.strided.smeanwd, base.strided.snanmean","base.strided.snanmin":"\nbase.strided.snanmin( N, x, strideX )\n    Computes the minimum value of a single-precision floating-point strided\n    array, ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmin( x.length, x, 1 )\n    -2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > base.strided.snanmin( 3, x, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.snanmin( 3, x1, 2 )\n    -2.0\n\n\nbase.strided.snanmin.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a single-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.snanmin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.snanmin.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dnanmin, base.strided.nanmin, base.strided.smin, base.strided.snanmax\n","base.strided.snanmin.ndarray":"\nbase.strided.snanmin.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a single-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.snanmin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.snanmin.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dnanmin, base.strided.nanmin, base.strided.smin, base.strided.snanmax","base.strided.snanminabs":"\nbase.strided.snanminabs( N, x, strideX )\n    Computes the minimum absolute value of a single-precision floating-point\n    strided array, ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanminabs( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > base.strided.snanminabs( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.snanminabs( 3, x1, 2 )\n    1.0\n\n\nbase.strided.snanminabs.ndarray( N, x, strideX, offsetX )\n    Computes the minimum absolute value of a single-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.snanminabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.snanminabs.ndarray( 3, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dnanminabs, base.strided.nanminabs, base.strided.sminabs, base.strided.snanmaxabs, base.strided.snanmin\n","base.strided.snanminabs.ndarray":"\nbase.strided.snanminabs.ndarray( N, x, strideX, offsetX )\n    Computes the minimum absolute value of a single-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.snanminabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.snanminabs.ndarray( 3, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dnanminabs, base.strided.nanminabs, base.strided.sminabs, base.strided.snanmaxabs, base.strided.snanmin","base.strided.snanmskmax":"\nbase.strided.snanmskmax( N, x, strideX, mask, strideMask )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n    > base.strided.snanmskmax( x.length, x, 1, mask, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmskmax( N, x, 2, mask, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.snanmskmax( N, x1, 2, mask1, 2 )\n    2.0\n\nbase.strided.snanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.snanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmskmax, base.strided.nanmskmax, base.strided.smskmax, base.strided.snanmax, base.strided.snanmskmin\n","base.strided.snanmskmax.ndarray":"\nbase.strided.snanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.snanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmskmax, base.strided.nanmskmax, base.strided.smskmax, base.strided.snanmax, base.strided.snanmskmin","base.strided.snanmskmin":"\nbase.strided.snanmskmin( N, x, strideX, mask, strideMask )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n    > base.strided.snanmskmin( x.length, x, 1, mask, 1 )\n    -2.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmskmin( N, x, 2, mask, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.snanmskmin( N, x1, 2, mask1, 2 )\n    -2.0\n\nbase.strided.snanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.snanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dnanmskmin, base.strided.nanmskmin, base.strided.smskmin, base.strided.snanmin, base.strided.snanmskmax\n","base.strided.snanmskmin.ndarray":"\nbase.strided.snanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.snanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dnanmskmin, base.strided.nanmskmin, base.strided.smskmin, base.strided.snanmin, base.strided.snanmskmax","base.strided.snanmskrange":"\nbase.strided.snanmskrange( N, x, strideX, mask, strideMask )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n    > base.strided.snanmskrange( x.length, x, 1, mask, 1 )\n    4.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmskrange( N, x, 2, mask, 2 )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.snanmskrange( N, x1, 2, mask1, 2 )\n    4.0\n\nbase.strided.snanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.snanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dnanmskrange, base.strided.nanmskrange, base.strided.smskrange, base.strided.snanrange, base.strided.snanmskmax, base.strided.snanmskmin\n","base.strided.snanmskrange.ndarray":"\nbase.strided.snanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.snanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dnanmskrange, base.strided.nanmskrange, base.strided.smskrange, base.strided.snanrange, base.strided.snanmskmax, base.strided.snanmskmin","base.strided.snanrange":"\nbase.strided.snanrange( N, x, strideX )\n    Computes the range of a single-precision floating-point strided array,\n    ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanrange( x.length, x, 1 )\n    4.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > base.strided.snanrange( 3, x, 2 )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.snanrange( 3, x1, 2 )\n    4.0\n\n\nbase.strided.snanrange.ndarray( N, x, strideX, offsetX )\n    Computes the range of a single-precision floating-point strided array,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.snanrange.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.snanrange.ndarray( 3, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dnanrange, base.strided.nanrange, base.strided.snanmax, base.strided.snanmin, base.strided.srange\n","base.strided.snanrange.ndarray":"\nbase.strided.snanrange.ndarray( N, x, strideX, offsetX )\n    Computes the range of a single-precision floating-point strided array,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.snanrange.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.snanrange.ndarray( 3, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dnanrange, base.strided.nanrange, base.strided.snanmax, base.strided.snanmin, base.strided.srange","base.strided.snanstdev":"\nbase.strided.snanstdev( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdev( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.snanstdev( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.snanstdev( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.snanstdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.nanstdev, base.strided.snanvariance, base.strided.sstdev\n","base.strided.snanstdev.ndarray":"\nbase.strided.snanstdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.nanstdev, base.strided.snanvariance, base.strided.sstdev","base.strided.snanstdevch":"\nbase.strided.snanstdevch( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevch( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.snanstdevch( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.snanstdevch( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.snanstdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevch, base.strided.nanstdevch, base.strided.snanstdev, base.strided.snanvariancech, base.strided.sstdevch\n","base.strided.snanstdevch.ndarray":"\nbase.strided.snanstdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevch, base.strided.nanstdevch, base.strided.snanstdev, base.strided.snanvariancech, base.strided.sstdevch","base.strided.snanstdevpn":"\nbase.strided.snanstdevpn( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevpn( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.snanstdevpn( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.snanstdevpn( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.snanstdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevpn, base.strided.nanstdevpn, base.strided.snanstdev, base.strided.snanvariancepn, base.strided.sstdevpn\n","base.strided.snanstdevpn.ndarray":"\nbase.strided.snanstdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevpn, base.strided.nanstdevpn, base.strided.snanstdev, base.strided.snanvariancepn, base.strided.sstdevpn","base.strided.snanstdevtk":"\nbase.strided.snanstdevtk( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevtk( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.snanstdevtk( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.snanstdevtk( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.snanstdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevtk, base.strided.nanstdevtk, base.strided.snanstdev, base.strided.snanvariancetk, base.strided.sstdevtk\n","base.strided.snanstdevtk.ndarray":"\nbase.strided.snanstdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevtk, base.strided.nanstdevtk, base.strided.snanstdev, base.strided.snanvariancetk, base.strided.sstdevtk","base.strided.snanstdevwd":"\nbase.strided.snanstdevwd( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevwd( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.snanstdevwd( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.snanstdevwd( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.snanstdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevwd, base.strided.nanstdevwd, base.strided.snanstdev, base.strided.snanvariancewd, base.strided.sstdevwd\n","base.strided.snanstdevwd.ndarray":"\nbase.strided.snanstdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevwd, base.strided.nanstdevwd, base.strided.snanstdev, base.strided.snanvariancewd, base.strided.sstdevwd","base.strided.snanstdevyc":"\nbase.strided.snanstdevyc( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass algorithm proposed by\n    Youngs and Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevyc( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.snanstdevyc( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.snanstdevyc( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.snanstdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass algorithm proposed by\n    Youngs and Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevyc, base.strided.nanstdevyc, base.strided.snanstdev, base.strided.snanvarianceyc, base.strided.sstdevyc\n","base.strided.snanstdevyc.ndarray":"\nbase.strided.snanstdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass algorithm proposed by\n    Youngs and Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevyc, base.strided.nanstdevyc, base.strided.snanstdev, base.strided.snanvarianceyc, base.strided.sstdevyc","base.strided.snansum":"\nbase.strided.snansum( N, x, stride )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansum( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.snansum( 4, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.snansum( 4, x1, 2 )\n    -1.0\n\n\nbase.strided.snansum.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.snansum.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.gnansum, base.strided.snanmean, base.strided.ssum\n","base.strided.snansum.ndarray":"\nbase.strided.snansum.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.snansum.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.gnansum, base.strided.snanmean, base.strided.ssum","base.strided.snansumkbn":"\nbase.strided.snansumkbn( N, x, stride )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in the strided \n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, \n    use a typed array view. \n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumkbn( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > var stride = 2;\n    > base.strided.snansumkbn( 4, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > stride = 2;\n    > base.strided.snansumkbn( 4, x1, stride )\n    -1.0\n\n\nbase.strided.snansumkbn.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.snansumkbn.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn, base.strided.gnansumkbn, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn\n","base.strided.snansumkbn.ndarray":"\nbase.strided.snansumkbn.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.snansumkbn.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn, base.strided.gnansumkbn, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn","base.strided.snansumkbn2":"\nbase.strided.snansumkbn2( N, x, stride )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset,\n    use a typed array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumkbn2( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > var stride = 2;\n    > base.strided.snansumkbn2( 4, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > stride = 2;\n    > base.strided.snansumkbn2( 4, x1, stride )\n    -1.0\n\n\nbase.strided.snansumkbn2.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.snansumkbn2.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn2, base.strided.gnansumkbn2, base.strided.snansum, base.strided.snansumkbn, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn2\n","base.strided.snansumkbn2.ndarray":"\nbase.strided.snansumkbn2.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.snansumkbn2.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn2, base.strided.gnansumkbn2, base.strided.snansum, base.strided.snansumkbn, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn2","base.strided.snansumors":"\nbase.strided.snansumors( N, x, strideX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumors( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > var stride = 2;\n    > base.strided.snansumors( 4, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > stride = 2;\n    > base.strided.snansumors( 4, x1, stride )\n    -1.0\n\n\nbase.strided.snansumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.snansumors.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumors, base.strided.gnansumors, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumpw, base.strided.ssumors\n","base.strided.snansumors.ndarray":"\nbase.strided.snansumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.snansumors.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumors, base.strided.gnansumors, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumpw, base.strided.ssumors","base.strided.snansumpw":"\nbase.strided.snansumpw( N, x, strideX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumpw( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.snansumpw( 4, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.snansumpw( 4, x1, 2 )\n    -1.0\n\n\nbase.strided.snansumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.snansumpw.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumpw, base.strided.gnansumpw, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.ssumpw\n","base.strided.snansumpw.ndarray":"\nbase.strided.snansumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.snansumpw.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumpw, base.strided.gnansumpw, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.ssumpw","base.strided.snanvariance":"\nbase.strided.snanvariance( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariance( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariance( N, 1, x, 2 )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.snanvariance( N, 1, x1, 2 )\n    ~4.3333\n\nbase.strided.snanvariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariance, base.strided.nanvariance, base.strided.snanstdev, base.strided.svariance\n","base.strided.snanvariance.ndarray":"\nbase.strided.snanvariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariance, base.strided.nanvariance, base.strided.snanstdev, base.strided.svariance","base.strided.snanvariancech":"\nbase.strided.snanvariancech( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancech( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancech( N, 1, x, 2 )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.snanvariancech( N, 1, x1, 2 )\n    ~4.3333\n\nbase.strided.snanvariancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancech, base.strided.nanvariancech, base.strided.snanstdevch, base.strided.snanvariance, base.strided.svariancech\n","base.strided.snanvariancech.ndarray":"\nbase.strided.snanvariancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancech, base.strided.nanvariancech, base.strided.snanstdevch, base.strided.snanvariance, base.strided.svariancech","base.strided.snanvariancepn":"\nbase.strided.snanvariancepn( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancepn( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancepn( N, 1, x, 2 )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.snanvariancepn( N, 1, x1, 2 )\n    ~4.3333\n\nbase.strided.snanvariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancepn, base.strided.nanvariancepn, base.strided.snanstdevpn, base.strided.snanvariance, base.strided.svariancepn\n","base.strided.snanvariancepn.ndarray":"\nbase.strided.snanvariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancepn, base.strided.nanvariancepn, base.strided.snanstdevpn, base.strided.snanvariance, base.strided.svariancepn","base.strided.snanvariancetk":"\nbase.strided.snanvariancetk( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancetk( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancetk( N, 1, x, 2 )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.snanvariancetk( N, 1, x1, 2 )\n    ~4.3333\n\nbase.strided.snanvariancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancetk, base.strided.nanvariancetk, base.strided.snanstdevtk, base.strided.snanvariance, base.strided.svariancetk\n","base.strided.snanvariancetk.ndarray":"\nbase.strided.snanvariancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancetk, base.strided.nanvariancetk, base.strided.snanstdevtk, base.strided.snanvariance, base.strided.svariancetk","base.strided.snanvariancewd":"\nbase.strided.snanvariancewd( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancewd( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancewd( N, 1, x, 2 )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.snanvariancewd( N, 1, x1, 2 )\n    ~4.3333\n\nbase.strided.snanvariancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using Welford's algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancewd, base.strided.nanvariancewd, base.strided.snanstdevwd, base.strided.snanvariance, base.strided.svariancewd\n","base.strided.snanvariancewd.ndarray":"\nbase.strided.snanvariancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using Welford's algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancewd, base.strided.nanvariancewd, base.strided.snanstdevwd, base.strided.snanvariance, base.strided.svariancewd","base.strided.snanvarianceyc":"\nbase.strided.snanvarianceyc( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n    Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvarianceyc( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvarianceyc( N, 1, x, 2 )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.snanvarianceyc( N, 1, x1, 2 )\n    ~4.3333\n\nbase.strided.snanvarianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n    Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvarianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvarianceyc, base.strided.nanvarianceyc, base.strided.snanstdevyc, base.strided.snanvariance, base.strided.svarianceyc\n","base.strided.snanvarianceyc.ndarray":"\nbase.strided.snanvarianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n    Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvarianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvarianceyc, base.strided.nanvarianceyc, base.strided.snanstdevyc, base.strided.snanvariance, base.strided.svarianceyc","base.strided.snrm2":"\nbase.strided.snrm2( N, x, stride )\n    Computes the L2-norm of a single-precision floating-point vector.\n\n    The `N` and `stride` parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0` the function returns `0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The L2-norm.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.snrm2( x.length, x, 1 )\n    3.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.snrm2( 3, x, 2 )\n    3.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.snrm2( 3, x1, 2 )\n    3.0\n\n\nbase.strided.snrm2.ndarray( N, x, stride, offset )\n    Computes the L2-norm of a single-precision floating-point vector using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The L2-norm.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.snrm2.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.snrm2.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dnrm2, base.strided.gnrm2\n","base.strided.snrm2.ndarray":"\nbase.strided.snrm2.ndarray( N, x, stride, offset )\n    Computes the L2-norm of a single-precision floating-point vector using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The L2-norm.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.snrm2.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.snrm2.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dnrm2, base.strided.gnrm2","base.strided.sramp":"\nbase.strided.sramp( N, x, strideX, y, strideY )\n    Evaluates the ramp function for each element in a single-precision floating-\n    point strided array `x` and assigns the results to elements in a single-\n    precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sramp( x.length, x, 1, y, 1 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sramp( N, x, 2, y, -1 )\n    <Float32Array>[ 0.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.sramp( N, x1, -2, y1, 1 )\n    <Float32Array>[ 4.0, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.sramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Evaluates the ramp function for each element in a single-precision floating-\n    point strided array `x` and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dramp, strided.ramp\n","base.strided.sramp.ndarray":"\nbase.strided.sramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Evaluates the ramp function for each element in a single-precision floating-\n    point strided array `x` and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dramp, strided.ramp","base.strided.srange":"\nbase.strided.srange( N, x, strideX )\n    Computes the range of a single-precision floating-point strided array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.srange( x.length, x, 1 )\n    4.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.srange( 3, x, 2 )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.srange( 3, x1, 2 )\n    4.0\n\n\nbase.strided.srange.ndarray( N, x, strideX, offsetX )\n    Computes the range of a single-precision floating-point strided array using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.srange.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.srange.ndarray( 3, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.drange, base.strided.smax, base.strided.smin, base.strided.snanrange, base.strided.range\n","base.strided.srange.ndarray":"\nbase.strided.srange.ndarray( N, x, strideX, offsetX )\n    Computes the range of a single-precision floating-point strided array using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.srange.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.srange.ndarray( 3, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.drange, base.strided.smax, base.strided.smin, base.strided.snanrange, base.strided.range","base.strided.srev":"\nbase.strided.srev( N, x, stride )\n    Reverses a single-precision floating-point strided array in-place.\n\n    The `N` and `stride` parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.srev( x.length, x, 1 )\n    <Float32Array>[ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.srev( 3, x, 2 )\n    <Float32Array>[ 4.0, 1.0, 3.0, -5.0, -2.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.srev( 3, x1, 2 )\n    <Float32Array>[ -6.0, 3.0, -4.0, 5.0, -2.0 ]\n    > x0\n    <Float32Array>[ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n\nbase.strided.srev.ndarray( N, x, stride, offset )\n    Reverses a single-precision floating-point strided array in-place using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.srev.ndarray( x.length, x, 1, 0 )\n    <Float32Array>[ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.srev.ndarray( 3, x, 2, 1 )\n    <Float32Array>[ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.drev, base.strided.grev\n","base.strided.srev.ndarray":"\nbase.strided.srev.ndarray( N, x, stride, offset )\n    Reverses a single-precision floating-point strided array in-place using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.srev.ndarray( x.length, x, 1, 0 )\n    <Float32Array>[ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.srev.ndarray( 3, x, 2, 1 )\n    <Float32Array>[ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.drev, base.strided.grev","base.strided.srsqrt":"\nbase.strided.srsqrt( N, x, strideX, y, strideY )\n    Computes the reciprocal square root for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.srsqrt( x.length, x, 1, y, 1 )\n    <Float32Array>[ 1.0, 0.5, ~0.333, ~0.289 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.srsqrt( N, x, 2, y, -1 )\n    <Float32Array>[ ~0.333, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.srsqrt( N, x1, -2, y1, 1 )\n    <Float32Array>[ ~0.289, 0.5 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.srsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the reciprocal square root for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.srsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 0.5, ~0.333, ~0.289 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.srsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n    See Also\n    --------\n    base.strided.drsqrt, strided.rsqrt, base.strided.ssqrt\n","base.strided.srsqrt.ndarray":"\nbase.strided.srsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the reciprocal square root for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.srsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 0.5, ~0.333, ~0.289 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.srsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n    See Also\n    --------\n    base.strided.drsqrt, strided.rsqrt, base.strided.ssqrt","base.strided.sscal":"\nbase.strided.sscal( N, alpha, x, stride )\n    Multiplies a single-precision floating-point vector `x` by a constant\n    `alpha`.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sscal( x.length, 5.0, x, 1 )\n    <Float32Array>[ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sscal( 3, 5.0, x, 2 )\n    <Float32Array>[ -10.0, 1.0, 15.0, -5.0, 20.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sscal( 3, 5.0, x1, 2 )\n    <Float32Array>[ -10.0, 3.0, -20.0, 5.0, -30.0 ]\n    > x0\n    <Float32Array>[ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n\nbase.strided.sscal.ndarray( N, alpha, x, stride, offset )\n    Multiplies a single-precision floating-point vector `x` by a constant\n    `alpha` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sscal.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float32Array>[ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.sscal.ndarray( 3, 5.0, x, 2, 1 )\n    <Float32Array>[ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n    See Also\n    --------\n    base.strided.daxpy, base.strided.dscal, base.strided.gscal, base.strided.saxpy\n","base.strided.sscal.ndarray":"\nbase.strided.sscal.ndarray( N, alpha, x, stride, offset )\n    Multiplies a single-precision floating-point vector `x` by a constant\n    `alpha` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sscal.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float32Array>[ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.sscal.ndarray( 3, 5.0, x, 2, 1 )\n    <Float32Array>[ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n    See Also\n    --------\n    base.strided.daxpy, base.strided.dscal, base.strided.gscal, base.strided.saxpy","base.strided.ssort2hp":"\nbase.strided.ssort2hp( N, order, x, strideX, y, strideY )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using heapsort.\n\n    The `N` and `stride` parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided arrays are sorted *in-place* (i.e., the input strided\n    arrays are *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2hp( x.length, 1, x, 1, y, 1 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float32Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2hp( 2, -1, x, 2, y, 2 )\n    <Float32Array>[ 3.0, -2.0, 1.0, -4.0 ]\n    > y\n    <Float32Array>[ 2.0, 1.0, 0.0, 3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n    > base.strided.ssort2hp( 2, 1, x1, 2, y1, 2 )\n    <Float32Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.ssort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using heapsort and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float32Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2hp.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float32Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2hp, base.strided.gsort2hp, base.strided.ssorthp\n","base.strided.ssort2hp.ndarray":"\nbase.strided.ssort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using heapsort and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float32Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2hp.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float32Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2hp, base.strided.gsort2hp, base.strided.ssorthp","base.strided.ssort2ins":"\nbase.strided.ssort2ins( N, order, x, strideX, y, strideY )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using insertion sort.\n\n    The `N` and stride parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function leaves the strided arrays\n    are unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^2).\n\n    The algorithm is efficient for *small* strided arrays (typically N <= 20)\n    and is particularly efficient for sorting strided arrays which are already\n    substantially sorted.\n\n    The algorithm is *stable*, meaning that the algorithm does *not* change the\n    order of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided arrays are sorted *in-place* (i.e., the input strided\n    arrays is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    x: Float32Array\n        First input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2ins( x.length, 1, x, 1, y, 1 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float32Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2ins( 2, -1, x, 2, y, 2 )\n    <Float32Array>[ 3.0, -2.0, 1.0, -4.0 ]\n    > y\n    <Float32Array>[ 2.0, 1.0, 0.0, 3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n    > base.strided.ssort2ins( 2, 1, x1, 2, y1, 2 )\n    <Float32Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.ssort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using insertion sort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float32Array\n        First input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float32Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float32Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2ins, base.strided.gsort2ins, base.strided.ssortins\n","base.strided.ssort2ins.ndarray":"\nbase.strided.ssort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using insertion sort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float32Array\n        First input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float32Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float32Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2ins, base.strided.gsort2ins, base.strided.ssortins","base.strided.ssort2sh":"\nbase.strided.ssort2sh( N, order, x, strideX, y, strideY )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using Shellsort.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^(4/3)).\n\n    The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided arrays are sorted *in-place* (i.e., the input strided\n    arrays are *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2sh( x.length, 1, x, 1, y, 1 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float32Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2sh( 2, -1, x, 2, y, 2 )\n    <Float32Array>[ 3.0, -2.0, 1.0, -4.0 ]\n    > y\n    <Float32Array>[ 2.0, 1.0, 0.0, 3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n    > base.strided.ssort2sh( 2, 1, x1, 2, y1, 2 )\n    <Float32Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.ssort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using Shellsort and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float32Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2sh.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float32Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2sh, base.strided.gsort2sh, base.strided.ssortsh\n","base.strided.ssort2sh.ndarray":"\nbase.strided.ssort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using Shellsort and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float32Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2sh.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float32Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2sh, base.strided.gsort2sh, base.strided.ssortsh","base.strided.ssorthp":"\nbase.strided.ssorthp( N, order, x, stride )\n    Sorts a single-precision floating-point strided array using heapsort.\n\n    The `N` and stride parameters determine which elements in the strided\n    array are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function returns the strided\n    array unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided array is sorted *in-place* (i.e., the input strided array\n    is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts the strided array in\n        decreasing order. If `order > 0`, the function sorts the strided array\n        in increasing order.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for the strided array.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array the strided array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssorthp( x.length, 1, x, 1 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssorthp( 2, -1, x, 2 )\n    <Float32Array>[ 3.0, -2.0, 1.0, -4.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.ssorthp( 2, 1, x1, 2 )\n    <Float32Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.ssorthp.ndarray( N, order, x, stride, offset )\n    Sorts a single-precision floating-point strided array using heapsort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts the strided array in\n        decreasing order. If `order > 0`, the function sorts the strided array\n        in increasing order.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for the strided array.\n\n    offset: integer\n        Starting index of the strided array.\n\n    Returns\n    -------\n    x: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssorthp.ndarray( x.length, 1, x, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssorthp.ndarray( 2, 1, x, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsorthp, base.strided.gsorthp, base.strided.ssort2hp\n","base.strided.ssorthp.ndarray":"\nbase.strided.ssorthp.ndarray( N, order, x, stride, offset )\n    Sorts a single-precision floating-point strided array using heapsort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts the strided array in\n        decreasing order. If `order > 0`, the function sorts the strided array\n        in increasing order.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for the strided array.\n\n    offset: integer\n        Starting index of the strided array.\n\n    Returns\n    -------\n    x: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssorthp.ndarray( x.length, 1, x, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssorthp.ndarray( 2, 1, x, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsorthp, base.strided.gsorthp, base.strided.ssort2hp","base.strided.ssortins":"\nbase.strided.ssortins( N, order, x, stride )\n    Sorts a single-precision floating-point strided array using insertion sort.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^2).\n\n    The algorithm is efficient for *small* strided arrays (typically N <= 20)\n    and is particularly efficient for sorting strided arrays which are already\n    substantially sorted.\n\n    The algorithm is *stable*, meaning that the algorithm does *not* change the\n    order of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided array is sorted *in-place* (i.e., the input strided array\n    is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortins( x.length, 1, x, 1 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortins( 2, -1, x, 2 )\n    <Float32Array>[ 3.0, -2.0, 1.0, -4.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.ssortins( 2, 1, x1, 2 )\n    <Float32Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.ssortins.ndarray( N, order, x, stride, offset )\n    Sorts a single-precision floating-point strided array using insertion sort\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortins.ndarray( x.length, 1, x, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortins.ndarray( 2, 1, x, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsortins, base.strided.gsortins, base.strided.ssort2ins\n","base.strided.ssortins.ndarray":"\nbase.strided.ssortins.ndarray( N, order, x, stride, offset )\n    Sorts a single-precision floating-point strided array using insertion sort\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortins.ndarray( x.length, 1, x, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortins.ndarray( 2, 1, x, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsortins, base.strided.gsortins, base.strided.ssort2ins","base.strided.ssortsh":"\nbase.strided.ssortsh( N, order, x, stride )\n    Sorts a single-precision floating-point strided array using Shellsort.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^(4/3)).\n\n    The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided array is sorted *in-place* (i.e., the input strided array\n    is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortsh( x.length, 1, x, 1 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortsh( 2, -1, x, 2 )\n    <Float32Array>[ 3.0, -2.0, 1.0, -4.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.ssortsh( 2, 1, x1, 2 )\n    <Float32Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.ssortsh.ndarray( N, order, x, stride, offset )\n    Sorts a single-precision floating-point strided array using Shellsort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortsh.ndarray( x.length, 1, x, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortsh.ndarray( 2, 1, x, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsortsh, base.strided.gsortsh, base.strided.ssort2sh\n","base.strided.ssortsh.ndarray":"\nbase.strided.ssortsh.ndarray( N, order, x, stride, offset )\n    Sorts a single-precision floating-point strided array using Shellsort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortsh.ndarray( x.length, 1, x, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortsh.ndarray( 2, 1, x, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsortsh, base.strided.gsortsh, base.strided.ssort2sh","base.strided.ssqrt":"\nbase.strided.ssqrt( N, x, strideX, y, strideY )\n    Computes the principal square root for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.ssqrt( x.length, x, 1, y, 1 )\n    <Float32Array>[ 0.0, 2.0, 3.0, ~3.464 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.ssqrt( N, x, 2, y, -1 )\n    <Float32Array>[ 3.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.ssqrt( N, x1, -2, y1, 1 )\n    <Float32Array>[ ~3.464, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.ssqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the principal square root for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.ssqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, 2.0, 3.0, ~3.464 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.ssqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dsqrt, base.strided.scbrt, strided.sqrt, base.strided.srsqrt\n","base.strided.ssqrt.ndarray":"\nbase.strided.ssqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the principal square root for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.ssqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, 2.0, 3.0, ~3.464 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.ssqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dsqrt, base.strided.scbrt, strided.sqrt, base.strided.srsqrt","base.strided.sstdev":"\nbase.strided.sstdev( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdev( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sstdev( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sstdev( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.sstdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdev, base.strided.snanstdev, base.strided.stdev, base.strided.svariance\n","base.strided.sstdev.ndarray":"\nbase.strided.sstdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdev, base.strided.snanstdev, base.strided.stdev, base.strided.svariance","base.strided.sstdevch":"\nbase.strided.sstdevch( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevch( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sstdevch( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sstdevch( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.sstdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevch, base.strided.snanstdevch, base.strided.sstdev, base.strided.stdevch, base.strided.svariancech\n","base.strided.sstdevch.ndarray":"\nbase.strided.sstdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevch, base.strided.snanstdevch, base.strided.sstdev, base.strided.stdevch, base.strided.svariancech","base.strided.sstdevpn":"\nbase.strided.sstdevpn( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevpn( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sstdevpn( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sstdevpn( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.sstdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevpn, base.strided.snanstdevpn, base.strided.sstdev, base.strided.stdevpn, base.strided.svariancepn\n","base.strided.sstdevpn.ndarray":"\nbase.strided.sstdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevpn, base.strided.snanstdevpn, base.strided.sstdev, base.strided.stdevpn, base.strided.svariancepn","base.strided.sstdevtk":"\nbase.strided.sstdevtk( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevtk( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sstdevtk( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sstdevtk( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.sstdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass textbook algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevtk, base.strided.snanstdevtk, base.strided.sstdev, base.strided.stdevtk, base.strided.svariancetk\n","base.strided.sstdevtk.ndarray":"\nbase.strided.sstdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass textbook algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevtk, base.strided.snanstdevtk, base.strided.sstdev, base.strided.stdevtk, base.strided.svariancetk","base.strided.sstdevwd":"\nbase.strided.sstdevwd( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevwd( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sstdevwd( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sstdevwd( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.sstdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevwd, base.strided.snanstdevwd, base.strided.sstdev, base.strided.stdevwd, base.strided.svariancewd\n","base.strided.sstdevwd.ndarray":"\nbase.strided.sstdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevwd, base.strided.snanstdevwd, base.strided.sstdev, base.strided.stdevwd, base.strided.svariancewd","base.strided.sstdevyc":"\nbase.strided.sstdevyc( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevyc( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sstdevyc( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sstdevyc( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.sstdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevyc, base.strided.snanstdevyc, base.strided.sstdev, base.strided.stdevyc, base.strided.svarianceyc\n","base.strided.sstdevyc.ndarray":"\nbase.strided.sstdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevyc, base.strided.snanstdevyc, base.strided.sstdev, base.strided.stdevyc, base.strided.svarianceyc","base.strided.ssum":"\nbase.strided.ssum( N, x, stride )\n    Computes the sum of single-precision floating-point strided array elements.\n\n    The `N` and `stride` parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssum( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.ssum( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.ssum( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.ssum.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.ssum.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsum, base.strided.smean, base.strided.snansum, base.strided.gsum\n","base.strided.ssum.ndarray":"\nbase.strided.ssum.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.ssum.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsum, base.strided.smean, base.strided.snansum, base.strided.gsum","base.strided.ssumkbn":"\nbase.strided.ssumkbn( N, x, stride )\n    Computes the sum of single-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumkbn( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.ssumkbn( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.ssumkbn( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.ssumkbn.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.ssumkbn.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumkbn, base.strided.gsumkbn, base.strided.snansumkbn, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors, base.strided.ssumpw\n","base.strided.ssumkbn.ndarray":"\nbase.strided.ssumkbn.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.ssumkbn.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumkbn, base.strided.gsumkbn, base.strided.snansumkbn, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors, base.strided.ssumpw","base.strided.ssumkbn2":"\nbase.strided.ssumkbn2( N, x, stride )\n    Computes the sum of single-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in  the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumkbn2( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.ssumkbn2( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.ssumkbn2( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.ssumkbn2.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.ssumkbn2.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumkbn2, base.strided.gsumkbn2, base.strided.snansumkbn2, base.strided.ssum, base.strided.ssumkbn, base.strided.ssumors, base.strided.ssumpw\n","base.strided.ssumkbn2.ndarray":"\nbase.strided.ssumkbn2.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.ssumkbn2.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumkbn2, base.strided.gsumkbn2, base.strided.snansumkbn2, base.strided.ssum, base.strided.ssumkbn, base.strided.ssumors, base.strided.ssumpw","base.strided.ssumors":"\nbase.strided.ssumors( N, x, strideX )\n    Computes the sum of single-precision floating-point strided array elements\n    using ordinary recursive summation.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumors( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.ssumors( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.ssumors( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.ssumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements\n    using ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.ssumors.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumors, base.strided.gsumors, base.strided.snansumors, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumpw\n","base.strided.ssumors.ndarray":"\nbase.strided.ssumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements\n    using ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.ssumors.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumors, base.strided.gsumors, base.strided.snansumors, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumpw","base.strided.ssumpw":"\nbase.strided.ssumpw( N, x, strideX )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumpw( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.ssumpw( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.ssumpw( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.ssumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.ssumpw.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumpw, base.strided.gsumpw, base.strided.snansumpw, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors\n","base.strided.ssumpw.ndarray":"\nbase.strided.ssumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.ssumpw.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumpw, base.strided.gsumpw, base.strided.snansumpw, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors","base.strided.sswap":"\nbase.strided.sswap( N, x, strideX, y, strideY )\n    Interchanges two single-precision floating-point vectors.\n\n    The `N` and stride parameters determine how values from `x` are swapped\n    with values from `y`.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the vectors are unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Second input array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.sswap( x.length, x, 1, y, 1 )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.sswap( 3, x, -2, y, 1 )\n    <Float32Array>[ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n    // Using typed array views:\n    > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.sswap( 3, x1, -2, y1, 1 )\n    <Float32Array>[ 6.0, 4.0, 2.0 ]\n    > y0\n    <Float32Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.sswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Interchanges two single-precision floating-point vectors using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Second input array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.sswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.sswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dswap, base.strided.gswap, base.strided.scopy, sswap\n","base.strided.sswap.ndarray":"\nbase.strided.sswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Interchanges two single-precision floating-point vectors using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Second input array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.sswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.sswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dswap, base.strided.gswap, base.strided.scopy, sswap","base.strided.stdev":"\nbase.strided.stdev( N, correction, x, stride )\n    Computes the standard deviation of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdev( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.stdev( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.stdev( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.stdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdev, base.strided.nanstdev, base.strided.sstdev, base.strided.variance\n","base.strided.stdev.ndarray":"\nbase.strided.stdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdev, base.strided.nanstdev, base.strided.sstdev, base.strided.variance","base.strided.stdevch":"\nbase.strided.stdevch( N, correction, x, stride )\n    Computes the standard deviation of a strided array using a one-pass trial\n    mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevch( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.stdevch( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.stdevch( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.stdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using a one-pass trial\n    mean algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevch, base.strided.nanstdevch, base.strided.sstdevch, base.strided.stdev, base.strided.variancech\n","base.strided.stdevch.ndarray":"\nbase.strided.stdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using a one-pass trial\n    mean algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevch, base.strided.nanstdevch, base.strided.sstdevch, base.strided.stdev, base.strided.variancech","base.strided.stdevpn":"\nbase.strided.stdevpn( N, correction, x, stride )\n    Computes the standard deviation of a strided array using a two-pass\n    algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevpn( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.stdevpn( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.stdevpn( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.stdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using a two-pass\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.sstdevpn, base.strided.stdev, base.strided.variancepn\n","base.strided.stdevpn.ndarray":"\nbase.strided.stdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using a two-pass\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.sstdevpn, base.strided.stdev, base.strided.variancepn","base.strided.stdevtk":"\nbase.strided.stdevtk( N, correction, x, stride )\n    Computes the standard deviation of a strided array using a one-pass textbook\n    algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevtk( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.stdevtk( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.stdevtk( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.stdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using a one-pass textbook\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.sstdevtk, base.strided.stdev, base.strided.variancetk\n","base.strided.stdevtk.ndarray":"\nbase.strided.stdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using a one-pass textbook\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.sstdevtk, base.strided.stdev, base.strided.variancetk","base.strided.stdevwd":"\nbase.strided.stdevwd( N, correction, x, stride )\n    Computes the standard deviation of a strided array using Welford's\n    algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevwd( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.stdevwd( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.stdevwd( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.stdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using Welford's algorithm\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.sstdevwd, base.strided.stdev, base.strided.variancewd\n","base.strided.stdevwd.ndarray":"\nbase.strided.stdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using Welford's algorithm\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.sstdevwd, base.strided.stdev, base.strided.variancewd","base.strided.stdevyc":"\nbase.strided.stdevyc( N, correction, x, stride )\n    Computes the standard deviation of a strided array using a one-pass\n    algorithm proposed by Youngs and Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevyc( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.stdevyc( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.stdevyc( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.stdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using a one-pass\n    algorithm proposed by Youngs and Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.sstdevyc, base.strided.stdev, base.strided.varianceyc\n","base.strided.stdevyc.ndarray":"\nbase.strided.stdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using a one-pass\n    algorithm proposed by Youngs and Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.sstdevyc, base.strided.stdev, base.strided.varianceyc","base.strided.strunc":"\nbase.strided.strunc( N, x, strideX, y, strideY )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward zero and assigns the results to elements in a single-precision\n    floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.strunc( x.length, x, 1, y, 1 )\n    <Float32Array>[ 1.0, 2.0, -3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.strunc( N, x, 2, y, -1 )\n    <Float32Array>[ -3.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.strunc( N, x1, -2, y1, 1 )\n    <Float32Array>[ 4.0, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.strunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward zero and assigns the results to elements in a single-precision\n    floating-point strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.strunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.strunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dtrunc, base.strided.sceil, base.strided.sfloor, strided.trunc\n","base.strided.strunc.ndarray":"\nbase.strided.strunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward zero and assigns the results to elements in a single-precision\n    floating-point strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.strunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.strunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dtrunc, base.strided.sceil, base.strided.sfloor, strided.trunc","base.strided.svariance":"\nbase.strided.svariance( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariance( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.svariance( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.svariance( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.svariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariance, base.strided.snanvariance, base.strided.sstdev, base.strided.variance\n","base.strided.svariance.ndarray":"\nbase.strided.svariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariance, base.strided.snanvariance, base.strided.sstdev, base.strided.variance","base.strided.svariancech":"\nbase.strided.svariancech( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancech( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.svariancech( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.svariancech( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.svariancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass trial mean algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svariancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancech, base.strided.snanvariancech, base.strided.sstdevch, base.strided.svariance, base.strided.variancech\n","base.strided.svariancech.ndarray":"\nbase.strided.svariancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass trial mean algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svariancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancech, base.strided.snanvariancech, base.strided.sstdevch, base.strided.svariance, base.strided.variancech","base.strided.svariancepn":"\nbase.strided.svariancepn( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancepn( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.svariancepn( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.svariancepn( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.svariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancepn, base.strided.snanvariancepn, base.strided.sstdevpn, base.strided.svariance, base.strided.variancepn\n","base.strided.svariancepn.ndarray":"\nbase.strided.svariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancepn, base.strided.snanvariancepn, base.strided.sstdevpn, base.strided.svariance, base.strided.variancepn","base.strided.svariancetk":"\nbase.strided.svariancetk( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancetk( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.svariancetk( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.svariancetk( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.svariancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass textbook algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svariancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancetk, base.strided.snanvariancetk, base.strided.sstdevtk, base.strided.svariance, base.strided.variancetk\n","base.strided.svariancetk.ndarray":"\nbase.strided.svariancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass textbook algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svariancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancetk, base.strided.snanvariancetk, base.strided.sstdevtk, base.strided.svariance, base.strided.variancetk","base.strided.svariancewd":"\nbase.strided.svariancewd( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancewd( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.svariancewd( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.svariancewd( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.svariancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svariancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancewd, base.strided.snanvariancewd, base.strided.sstdevwd, base.strided.svariance, base.strided.variancewd\n","base.strided.svariancewd.ndarray":"\nbase.strided.svariancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svariancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancewd, base.strided.snanvariancewd, base.strided.sstdevwd, base.strided.svariance, base.strided.variancewd","base.strided.svarianceyc":"\nbase.strided.svarianceyc( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass algorithm proposed by Youngs and Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svarianceyc( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.svarianceyc( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.svarianceyc( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.svarianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass algorithm proposed by Youngs and Cramer and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svarianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svarianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvarianceyc, base.strided.snanvarianceyc, base.strided.sstdevyc, base.strided.svariance, base.strided.varianceyc\n","base.strided.svarianceyc.ndarray":"\nbase.strided.svarianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass algorithm proposed by Youngs and Cramer and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svarianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svarianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvarianceyc, base.strided.snanvarianceyc, base.strided.sstdevyc, base.strided.svariance, base.strided.varianceyc","base.strided.ternary":"\nbase.strided.ternary( arrays, shape, strides, fcn )\n    Applies a ternary callback to strided input array elements and assigns\n    results to elements in a strided output array.\n\n    The `shape` and `strides` parameters determine which elements in the strided\n    input and output arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing three strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    fcn: Function\n        Ternary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1, 1 ];\n    > function f( x, y, z ) { return x + y + z; };\n    > base.strided.ternary( [ x, y, z, w ], shape, strides, f );\n    > w\n    <Float64Array>[ 3.0, 6.0, 9.0, 12.0 ]\n\n\nbase.strided.ternary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a ternary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing three strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Ternary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1, 1 ];\n    > var offsets = [ 0, 0, 0, 0 ];\n    > function f( x, y, z ) { return x + y + z; };\n    > base.strided.ternary.ndarray( [ x, y, z, w ], shape, strides, offsets, f );\n    > w\n    <Float64Array>[ 3.0, 6.0, 9.0, 12.0 ]\n\n    See Also\n    --------\n    base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.unary\n","base.strided.ternary.ndarray":"\nbase.strided.ternary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a ternary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing three strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Ternary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1, 1 ];\n    > var offsets = [ 0, 0, 0, 0 ];\n    > function f( x, y, z ) { return x + y + z; };\n    > base.strided.ternary.ndarray( [ x, y, z, w ], shape, strides, offsets, f );\n    > w\n    <Float64Array>[ 3.0, 6.0, 9.0, 12.0 ]\n\n    See Also\n    --------\n    base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.unary","base.strided.unary":"\nbase.strided.unary( arrays, shape, strides, fcn )\n    Applies a unary callback to elements in a strided input array and assigns\n    results to elements in a strided output array.\n\n    The `shape` and `strides` parameters determine which elements in the strided\n    input and output arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided input array and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    fcn: Function\n        Unary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1 ];\n    > base.strided.unary( [ x, y ], shape, strides, base.abs );\n    > y\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n\nbase.strided.unary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a unary callback to elements in a strided input array and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided input array and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Unary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1 ];\n    > var offsets = [ 0, 0 ];\n    > base.strided.unary.ndarray( [ x, y ], shape, strides, offsets, base.abs );\n    > y\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    See Also\n    --------\n    base.strided.unary, base.strided.dmap, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap, base.strided.ternary\n","base.strided.unary.ndarray":"\nbase.strided.unary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a unary callback to elements in a strided input array and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided input array and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Unary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1 ];\n    > var offsets = [ 0, 0 ];\n    > base.strided.unary.ndarray( [ x, y ], shape, strides, offsets, base.abs );\n    > y\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    See Also\n    --------\n    base.strided.unary, base.strided.dmap, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap, base.strided.ternary","base.strided.unaryBy":"\nbase.strided.unaryBy( arrays, shape, strides, fcn, clbk[, thisArg] )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array.\n\n    The shape and stride parameters determine which elements in the strided\n    input and output arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - indices: strided indices (offset + idx*stride).\n    - arrays: input and output arrays.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided input array and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    fcn: Function\n        Unary function to apply to callback return values.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > var sh = [ x.length ];\n    > var st = [ 1, 1 ];\n    > function clbk( v ) { return v * 2.0; };\n    > base.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\n    > y\n    [ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Using shape and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > sh = [ 2 ];\n    > st = [ 2, -1 ];\n    > base.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\n    > y\n    [ 6.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > sh = [ 2 ];\n    > st = [ -2, 1 ];\n    > base.strided.unaryBy( [ x1, y1 ], sh, st, base.abs, clbk );\n    > y1\n    <Float64Array>[ 8.0, 4.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 8.0, 4.0 ]\n\n\nbase.strided.unaryBy.ndarray( arrays, shape, strides, offsets, fcn, clbk[, thisArg] )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offsest parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided input array and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Unary function to apply to callback return values.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > var sh = [ x.length ];\n    > var st = [ 1, 1 ];\n    > var o = [ 0, 0 ];\n    > function clbk( v ) { return v * 2.0; };\n    > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n    > y\n    [ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > sh = [ 2 ];\n    > st = [ 2, -1 ];\n    > o = [ 1, y.length-1 ];\n    > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n    > y\n    [ 0.0, 0.0, 8.0, 4.0 ]\n\n    See Also\n    --------\n    base.strided.mapBy, base.strided.unary\n","base.strided.unaryBy.ndarray":"\nbase.strided.unaryBy.ndarray( arrays, shape, strides, offsets, fcn, clbk[, thisArg] )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offsest parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided input array and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Unary function to apply to callback return values.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > var sh = [ x.length ];\n    > var st = [ 1, 1 ];\n    > var o = [ 0, 0 ];\n    > function clbk( v ) { return v * 2.0; };\n    > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n    > y\n    [ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > sh = [ 2 ];\n    > st = [ 2, -1 ];\n    > o = [ 1, y.length-1 ];\n    > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n    > y\n    [ 0.0, 0.0, 8.0, 4.0 ]\n\n    See Also\n    --------\n    base.strided.mapBy, base.strided.unary","base.strided.unaryDtypeSignatures":"\nbase.strided.unaryDtypeSignatures( dtypes1, dtypes2[, options] )\n    Generates a list of unary interface signatures from strided array data\n    types.\n\n    The function returns a strided array having a stride length of two (i.e.,\n    every two elements define a unary interface signature).\n\n    For each signature (i.e., set of two consecutive non-overlapping strided\n    array elements), the first element is the input data type and the second\n    element is the return data type.\n\n    All signatures follow type promotion rules.\n\n    Parameters\n    ----------\n    dtypes1: ArrayLike<any>\n        List of supported data types for the input argument.\n\n    dtypes2: ArrayLike<any>\n        List of supported data types for the output argument.\n\n    options: Object (optional)\n        Options.\n\n    options.enums: boolean (optional)\n        Boolean flag indicating whether to return signatures as a list of data\n        type enumeration constants. Default: false.\n\n    Returns\n    -------\n    out: Array\n        Strided array containing unary interface signatures.\n\n    Examples\n    --------\n    > var dt = strided.dataTypes();\n    > var out = base.strided.unaryDtypeSignatures( dt, dt )\n    [...]\n\n    See Also\n    --------\n    base.strided.unarySignatureCallbacks\n","base.strided.unarySignatureCallbacks":"\nbase.strided.unarySignatureCallbacks( table, signatures )\n    Assigns callbacks to unary interfaces according to type promotion rules.\n\n    Parameters\n    ----------\n    table: Object\n        Object mapping callbacks to data types.\n\n    table.default: Function\n        Default callback.\n\n    table.complex64: Function\n        Callback to be invoked when input arrays promote to single-precision\n        complex floating-point numbers.\n\n    table.complex128: Function\n        Callback to be invoked when input arrays promote to double precision\n        complex floating-point numbers.\n\n    signatures: ArrayLike<any>\n        Strided array containing unary interface signatures.\n\n    Returns\n    -------\n    out: Array<Function>\n        List of callbacks, one per signature.\n\n    Examples\n    --------\n    > var dt = strided.dataTypes();\n    > var sigs = base.strided.unaryDtypeSignatures( dt, dt );\n    > var t = {\n    ...     'default': base.identity,\n    ...     'complex64': base.cidentityf,\n    ...     'complex128': base.cidentity\n    ... };\n    > var out = base.strided.unarySignatureCallbacks( t, sigs )\n    [...]\n\n    See Also\n    --------\n    base.strided.unaryDtypeSignatures\n","base.strided.variance":"\nbase.strided.variance( N, correction, x, stride )\n    Computes the variance of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variance( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.variance( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.variance( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.variance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.variance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariance, base.strided.nanvariance, base.strided.stdev, base.strided.svariance\n","base.strided.variance.ndarray":"\nbase.strided.variance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.variance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariance, base.strided.nanvariance, base.strided.stdev, base.strided.svariance","base.strided.variancech":"\nbase.strided.variancech( N, correction, x, stride )\n    Computes the variance of a strided array using a one-pass trial mean\n    algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancech( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.variancech( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.variancech( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.variancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using a one-pass trial mean\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.variancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancech, base.strided.nanvariancech, base.strided.stdevch, base.strided.variance\n","base.strided.variancech.ndarray":"\nbase.strided.variancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using a one-pass trial mean\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.variancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancech, base.strided.nanvariancech, base.strided.stdevch, base.strided.variance","base.strided.variancepn":"\nbase.strided.variancepn( N, correction, x, stride )\n    Computes the variance of a strided array using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancepn( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.variancepn( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.variancepn( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.variancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using a two-pass algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.variancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancepn, base.strided.nanvariancepn, base.strided.stdevpn, base.strided.variance\n","base.strided.variancepn.ndarray":"\nbase.strided.variancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using a two-pass algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.variancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancepn, base.strided.nanvariancepn, base.strided.stdevpn, base.strided.variance","base.strided.variancetk":"\nbase.strided.variancetk( N, correction, x, stride )\n    Computes the variance of a strided array using a one-pass textbook\n    algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancetk( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.variancetk( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.variancetk( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.variancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using a one-pass textbook algorithm\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.variancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancetk, base.strided.nanvariancetk, base.strided.stdevtk, base.strided.variance\n","base.strided.variancetk.ndarray":"\nbase.strided.variancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using a one-pass textbook algorithm\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.variancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancetk, base.strided.nanvariancetk, base.strided.stdevtk, base.strided.variance","base.strided.variancewd":"\nbase.strided.variancewd( N, correction, x, stride )\n    Computes the variance of a strided array using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancewd( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.variancewd( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.variancewd( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.variancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using Welford's algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.variancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancewd, base.strided.nanvariancewd, base.strided.stdevwd, base.strided.variance\n","base.strided.variancewd.ndarray":"\nbase.strided.variancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using Welford's algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.variancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancewd, base.strided.nanvariancewd, base.strided.stdevwd, base.strided.variance","base.strided.varianceyc":"\nbase.strided.varianceyc( N, correction, x, stride )\n    Computes the variance of a strided array using a one-pass algorithm proposed\n    by Youngs and Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.varianceyc( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.varianceyc( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.varianceyc( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.varianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using a one-pass algorithm proposed\n    by Youngs and Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.varianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.varianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvarianceyc, base.strided.nanvarianceyc, base.strided.stdevyc, base.strided.variance\n","base.strided.varianceyc.ndarray":"\nbase.strided.varianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using a one-pass algorithm proposed\n    by Youngs and Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.varianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.varianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvarianceyc, base.strided.nanvarianceyc, base.strided.stdevyc, base.strided.variance","base.strided.zmap":"\nbase.strided.zmap( N, x, strideX, y, strideY, fcn )\n    Applies a unary function to a double-precision complex floating-point\n    strided input array and assigns results to a double-precision complex\n    floating-point strided output array.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex128Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Complex128Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Complex128Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n    > var x = new Complex128Array( xbuf );\n    > var y = new Complex128Array( x.length );\n    > base.strided.zmap( x.length, x, 1, y, 1, base.cidentity );\n    > var v = y.get( 0 )\n    <Complex128>\n    > var re = real( v )\n    1.0\n    > var im = imag( v )\n    2.0\n\n    // Using `N` and stride parameters:\n    > y = new Complex128Array( x.length );\n    > base.strided.zmap( 2, x, 2, y, -1, base.cidentity );\n    > v = y.get( 0 )\n    <Complex128>\n    > re = real( v )\n    5.0\n    > im = imag( v )\n    6.0\n\n    // Using view offsets:\n    > var x0 = new Complex128Array( xbuf );\n    > var y0 = new Complex128Array( x0.length );\n    > var x1 = new Complex128Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Complex128Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.zmap( 2, x1, -2, y1, 1, base.cidentity );\n    > v = y1.get( 0 )\n    <Complex128>\n    > re = real( v )\n    7.0\n    > im = imag( v )\n    8.0\n\n\nbase.strided.zmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n    Applies a unary function to a double-precision complex floating-point\n    strided input array and assigns results to a double-precision complex\n    floating-point strided output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex128Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Complex128Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Complex128Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n    > var x = new Complex128Array( xbuf );\n    > var y = new Complex128Array( x.length );\n    > base.strided.zmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentity );\n    > var v = y.get( 0 )\n    <Complex128>\n    > var re = real( v )\n    1.0\n    > var im = imag( v )\n    2.0\n\n    // Advanced indexing:\n    > x = new Complex128Array( xbuf );\n    > y = new Complex128Array( x.length );\n    > base.strided.zmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentity );\n    > v = y.get( y.length-1 )\n    <Complex128>\n    > re = real( v )\n    3.0\n    > im = imag( v )\n    4.0\n\n    See Also\n    --------\n    base.strided.cmap, base.strided.unary\n","base.strided.zmap.ndarray":"\nbase.strided.zmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n    Applies a unary function to a double-precision complex floating-point\n    strided input array and assigns results to a double-precision complex\n    floating-point strided output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex128Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Complex128Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Complex128Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n    > var x = new Complex128Array( xbuf );\n    > var y = new Complex128Array( x.length );\n    > base.strided.zmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentity );\n    > var v = y.get( 0 )\n    <Complex128>\n    > var re = real( v )\n    1.0\n    > var im = imag( v )\n    2.0\n\n    // Advanced indexing:\n    > x = new Complex128Array( xbuf );\n    > y = new Complex128Array( x.length );\n    > base.strided.zmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentity );\n    > v = y.get( y.length-1 )\n    <Complex128>\n    > re = real( v )\n    3.0\n    > im = imag( v )\n    4.0\n\n    See Also\n    --------\n    base.strided.cmap, base.strided.unary","base.str2multislice":"\nbase.str2multislice( str )\n    Parses a string-serialized MultiSlice object.\n\n    The function returns `null` if provided an invalid string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    s: MultiSlice|null\n        MultiSlice instance (or null).\n\n    Examples\n    --------\n    > var s = new base.str2multislice( 'MultiSlice(null,null,null)' );\n    > s.data\n    [ null, null, null ]\n    > s = new base.str2multislice( 'MultiSlice(10,Slice(0,10,1),null)' );\n    > s.data\n    [ 10, <Slice>, null ]\n\n    See Also\n    --------\n    base.str2slice\n","base.str2slice":"\nbase.str2slice( str )\n    Parses a string-serialized Slice object.\n\n    The function returns `null` if provided an invalid string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    s: Slice|null\n        Slice instance (or null).\n\n    Examples\n    --------\n    > var s = new base.str2slice( 'Slice(1,10,1)' );\n    > s.start\n    1\n    > s.stop\n    10\n    > s.step\n    1\n    > s = new base.str2slice( 'Slice(2,5,2)' );\n    > s.start\n    2\n    > s.stop\n    5\n    > s.step\n    2\n\n    See Also\n    --------\n    base.str2multislice\n","base.sub":"\nbase.sub( x, y )\n    Subtracts two double-precision floating-point numbers `x` and `y`.\n\n    Parameters\n    ----------\n    x: number\n        First input value.\n\n    y: number\n        Second input value.\n\n    Returns\n    -------\n    z: number\n        Result.\n\n    Examples\n    --------\n    > var v = base.sub( -1.0, 5.0 )\n    -6.0\n    > v = base.sub( 2.0, 5.0 )\n    -3.0\n    > v = base.sub( 0.0, 5.0 )\n    -5.0\n    > v = base.sub( -0.0, 0.0 )\n    -0.0\n    > v = base.sub( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.add, base.div, base.mul\n","base.subf":"\nbase.subf( x, y )\n    Subtracts two single-precision floating-point numbers `x` and `y`.\n\n    Parameters\n    ----------\n    x: number\n        First input value.\n\n    y: number\n        Second input value.\n\n    Returns\n    -------\n    z: number\n        Result.\n\n    Examples\n    --------\n    > var v = base.subf( -1.0, 5.0 )\n    -6.0\n    > v = base.subf( 2.0, 5.0 )\n    -3.0\n    > v = base.subf( 0.0, 5.0 )\n    -5.0\n    > v = base.subf( -0.0, 0.0 )\n    -0.0\n    > v = base.subf( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.addf, base.divf, base.mulf, base.sub\n","base.sumSeries":"\nbase.sumSeries( generator[, options] )\n    Sum the elements of the series given by the supplied function.\n\n    Parameters\n    ----------\n    generator: Function\n        Series function.\n\n    options: Object (optional)\n        Options.\n\n    options.maxTerms: integer (optional)\n        Maximum number of terms to be added. Default: `1000000`.\n\n    options.tolerance: number (optional)\n        Further terms are only added as long as the next term is greater than\n        the current term times the tolerance. Default: `2.22e-16`.\n\n    options.initialValue: number (optional)\n        Initial value of the resulting sum. Default: `0`.\n\n    Returns\n    -------\n    out: number\n        Sum of series terms.\n\n    Examples\n    --------\n    // Using an ES6 generator function:\n    > function* geometricSeriesGenerator( x ) {\n    ...     var exponent = 0;\n    ...     while ( true ) {\n    ...         yield Math.pow( x, exponent );\n    ...         exponent += 1;\n    ...     }\n    ... };\n    > var gen = geometricSeriesGenerator( 0.9 );\n    > var out = base.sumSeries( gen )\n    10\n\n    // Using a closure:\n    > function geometricSeriesClosure( x ) {\n    ...     var exponent = -1;\n    ...     return function() {\n    ...         exponent += 1;\n    ...         return Math.pow( x, exponent );\n    ...     };\n    ... };\n    > gen = geometricSeriesClosure( 0.9 );\n    > out = base.sumSeries( gen )\n    10\n\n    // Setting an initial value for the sum:\n    > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'initialValue': 1 } )\n    3\n    // Changing the maximum number of terms to be summed:\n    > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'maxTerms': 10 } )\n    ~1.998 // Infinite sum is 2\n\n    // Adjusting the used tolerance:\n    > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'tolerance': 1e-3 } )\n    ~1.998\n\n","base.tan":"\nbase.tan( x )\n    Computes the tangent of a number.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Tangent.\n\n    Examples\n    --------\n    > var y = base.tan( 0.0 )\n    ~0.0\n    > y = base.tan( -PI/4.0 )\n    ~-1.0\n    > y = base.tan( PI/4.0 )\n    ~1.0\n    > y = base.tan( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cos, base.sin\n","base.tand":"\nbase.tand( x )\n    Computes the tangent of an angle measured in degrees.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in degrees).\n\n    Returns\n    -------\n    y: number\n        Tangent.\n\n    Examples\n    --------\n    > var y = base.tand( 0.0 )\n    0.0\n    > y = base.tand( 90.0 )\n    Infinity\n    > y = base.tand( 60.0 )\n    ~1.73\n    > y = base.tand( NaN )\n    NaN\n\n    See Also\n    --------\n    base.tan, base.cosd\n","base.tanh":"\nbase.tanh( x )\n    Computes the hyperbolic tangent of a double-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Hyperbolic tangent.\n\n    Examples\n    --------\n    > var y = base.tanh( 0.0 )\n    0.0\n    > var y = base.tanh( -0.0 )\n    -0.0\n    > y = base.tanh( 2.0 )\n    ~0.964\n    > y = base.tanh( -2.0 )\n    ~-0.964\n    > y = base.tanh( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cosh, base.sinh, base.tan\n","base.toBinaryString":"\nbase.toBinaryString( x )\n    Returns a string giving the literal bit representation of a double-precision\n    floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    Returns\n    -------\n    bstr: string\n        Bit representation.\n\n    Examples\n    --------\n    > var str = base.toBinaryString( 4.0 )\n    '0100000000010000000000000000000000000000000000000000000000000000'\n    > str = base.toBinaryString( PI )\n    '0100000000001001001000011111101101010100010001000010110100011000'\n    > str = base.toBinaryString( -1.0e308 )\n    '1111111111100001110011001111001110000101111010111100100010100000'\n    > str = base.toBinaryString( -3.14e-320 )\n    '1000000000000000000000000000000000000000000000000001100011010011'\n    > str = base.toBinaryString( 5.0e-324 )\n    '0000000000000000000000000000000000000000000000000000000000000001'\n    > str = base.toBinaryString( 0.0 )\n    '0000000000000000000000000000000000000000000000000000000000000000'\n    > str = base.toBinaryString( -0.0 )\n    '1000000000000000000000000000000000000000000000000000000000000000'\n    > str = base.toBinaryString( NaN )\n    '0111111111111000000000000000000000000000000000000000000000000000'\n    > str = base.toBinaryString( PINF )\n    '0111111111110000000000000000000000000000000000000000000000000000'\n    > str = base.toBinaryString( NINF )\n    '1111111111110000000000000000000000000000000000000000000000000000'\n\n    See Also\n    --------\n    base.fromBinaryString, base.toBinaryStringf\n","base.toBinaryStringf":"\nbase.toBinaryStringf( x )\n    Returns a string giving the literal bit representation of a single-precision\n    floating-point number.\n\n    Parameters\n    ----------\n    x: float\n        Single-precision floating-point number.\n\n    Returns\n    -------\n    str: string\n        Bit representation.\n\n    Examples\n    --------\n    > var str = base.toBinaryStringf( base.float64ToFloat32( 4.0 ) )\n    '01000000100000000000000000000000'\n    > str = base.toBinaryStringf( base.float64ToFloat32( PI ) )\n    '01000000010010010000111111011011'\n    > str = base.toBinaryStringf( base.float64ToFloat32( -1.0e38 ) )\n    '11111110100101100111011010011001'\n    > str = base.toBinaryStringf( base.float64ToFloat32( -3.14e-39 ) )\n    '10000000001000100011000100001011'\n    > str = base.toBinaryStringf( base.float64ToFloat32( 1.4e-45 ) )\n    '00000000000000000000000000000001'\n    > str = base.toBinaryStringf( 0.0 )\n    '00000000000000000000000000000000'\n    > str = base.toBinaryStringf( -0.0 )\n    '10000000000000000000000000000000'\n    > str = base.toBinaryStringf( NaN )\n    '01111111110000000000000000000000'\n    > str = base.toBinaryStringf( FLOAT32_PINF )\n    '01111111100000000000000000000000'\n    > str = base.toBinaryStringf( FLOAT32_NINF )\n    '11111111100000000000000000000000'\n\n    See Also\n    --------\n    base.fromBinaryStringf, base.toBinaryString\n","base.toBinaryStringUint8":"\nbase.toBinaryStringUint8( x )\n    Returns a string giving the literal bit representation of an unsigned 8-bit\n    integer.\n\n    Except for typed arrays, JavaScript does not provide native user support for\n    unsigned 8-bit integers. According to the ECMAScript standard, `number`\n    values correspond to double-precision floating-point numbers. While this\n    function is intended for unsigned 8-bit integers, the function will accept\n    floating-point values and represent the values as if they are unsigned 8-bit\n    integers. Accordingly, care should be taken to ensure that only nonnegative\n    integer values less than `256` (`2^8`) are provided.\n\n    Parameters\n    ----------\n    x: integer\n        Input value.\n\n    Returns\n    -------\n    str: string\n        Bit representation.\n\n    Examples\n    --------\n    > var a = new Uint8Array( [ 1, 4, 9 ] );\n    > var str = base.toBinaryStringUint8( a[ 0 ] )\n    '00000001'\n    > str = base.toBinaryStringUint8( a[ 1 ] )\n    '00000100'\n    > str = base.toBinaryStringUint8( a[ 2 ] )\n    '00001001'\n\n    See Also\n    --------\n    base.toBinaryString\n","base.toBinaryStringUint16":"\nbase.toBinaryStringUint16( x )\n    Returns a string giving the literal bit representation of an unsigned 16-bit\n    integer.\n\n    Except for typed arrays, JavaScript does not provide native user support for\n    unsigned 16-bit integers. According to the ECMAScript standard, `number`\n    values correspond to double-precision floating-point numbers. While this\n    function is intended for unsigned 16-bit integers, the function will accept\n    floating-point values and represent the values as if they are unsigned\n    16-bit integers. Accordingly, care should be taken to ensure that only\n    nonnegative integer values less than `65536` (`2^16`) are provided.\n\n    Parameters\n    ----------\n    x: integer\n        Input value.\n\n    Returns\n    -------\n    str: string\n        Bit representation.\n\n    Examples\n    --------\n    > var a = new Uint16Array( [ 1, 4, 9 ] );\n    > var str = base.toBinaryStringUint16( a[ 0 ] )\n    '0000000000000001'\n    > str = base.toBinaryStringUint16( a[ 1 ] )\n    '0000000000000100'\n    > str = base.toBinaryStringUint16( a[ 2 ] )\n    '0000000000001001'\n\n    See Also\n    --------\n    base.toBinaryString\n","base.toBinaryStringUint32":"\nbase.toBinaryStringUint32( x )\n    Returns a string giving the literal bit representation of an unsigned 32-bit\n    integer.\n\n    Except for typed arrays, JavaScript does not provide native user support for\n    unsigned 32-bit integers. According to the ECMAScript standard, `number`\n    values correspond to double-precision floating-point numbers. While this\n    function is intended for unsigned 32-bit integers, the function will accept\n    floating-point values and represent the values as if they are unsigned\n    32-bit integers. Accordingly, care should be taken to ensure that only\n    nonnegative integer values less than `4,294,967,296` (`2^32`) are provided.\n\n    Parameters\n    ----------\n    x: integer\n        Input value.\n\n    Returns\n    -------\n    str: string\n        Bit representation.\n\n    Examples\n    --------\n    > var a = new Uint32Array( [ 1, 4, 9 ] );\n    > var str = base.toBinaryStringUint32( a[ 0 ] )\n    '00000000000000000000000000000001'\n    > str = base.toBinaryStringUint32( a[ 1 ] )\n    '00000000000000000000000000000100'\n    > str = base.toBinaryStringUint32( a[ 2 ] )\n    '00000000000000000000000000001001'\n\n    See Also\n    --------\n    base.toBinaryString\n","base.toWordf":"\nbase.toWordf( x )\n    Returns an unsigned 32-bit integer corresponding to the IEEE 754 binary\n    representation of a single-precision floating-point number.\n\n    Parameters\n    ----------\n    x: float\n        Single-precision floating-point number.\n\n    Returns\n    -------\n    out: integer\n        Unsigned 32-bit integer.\n\n    Examples\n    --------\n    > var f32 = base.float64ToFloat32( 1.337 )\n    1.3370000123977661\n    > var w = base.toWordf( f32 )\n    1068180177\n\n    See Also\n    --------\n    base.fromWordf, base.toWords\n","base.toWords":"\nbase.toWords( x )\n    Splits a double-precision floating-point number into a higher order word\n    (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n\n    When provided a destination object, the function returns an array with two\n    elements: a higher order word and a lower order word, respectively. The\n    lower order word contains the less significant bits, while the higher order\n    word contains the more significant bits and includes the exponent and sign.\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    Returns\n    -------\n    out: Array<integer>\n        Higher and lower order words.\n\n    Examples\n    --------\n    > var w = base.toWords( 3.14e201 )\n    [ 1774486211, 2479577218 ]\n\n\nbase.toWords.assign( x, out, stride, offset )\n    Splits a double-precision floating-point number into a higher order word\n    (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer)\n    and assigns results to a provided output array.\n\n    When provided a destination object, the function returns an array with two\n    elements: a higher order word and a lower order word, respectively. The\n    lower order word contains the less significant bits, while the higher order\n    word contains the more significant bits and includes the exponent and sign.\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Higher and lower order words.\n\n    Examples\n    --------\n    > var out = new Uint32Array( 2 );\n    > var w = base.toWords.assign( 3.14e201, out, 1, 0 )\n    <Uint32Array>[ 1774486211, 2479577218 ]\n    > var bool = ( w === out )\n    true\n\n    See Also\n    --------\n    base.fromWords, base.toWordf","base.toWords.assign":"\nbase.toWords.assign( x, out, stride, offset )\n    Splits a double-precision floating-point number into a higher order word\n    (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer)\n    and assigns results to a provided output array.\n\n    When provided a destination object, the function returns an array with two\n    elements: a higher order word and a lower order word, respectively. The\n    lower order word contains the less significant bits, while the higher order\n    word contains the more significant bits and includes the exponent and sign.\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Higher and lower order words.\n\n    Examples\n    --------\n    > var out = new Uint32Array( 2 );\n    > var w = base.toWords.assign( 3.14e201, out, 1, 0 )\n    <Uint32Array>[ 1774486211, 2479577218 ]\n    > var bool = ( w === out )\n    true\n\n    See Also\n    --------\n    base.fromWords, base.toWordf","base.transpose":"\nbase.transpose( x )\n    Transposes a matrix (or a stack of matrices).\n\n    The returned ndarray is a *view* of the input ndarray. Accordingly, writing\n    to the original ndarray will mutate the returned ndarray and vice versa.\n    While powerful, this can lead to subtle bugs. In general, one should handle\n    the returned ndarray as read-only.\n\n    If provided an ndarray with fewer than two dimensions, the function raises\n    an exception.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n    <ndarray>\n    > var sh = x.shape\n    [ 2, 3 ]\n    > var y = base.transpose( x )\n    <ndarray>\n    > sh = y.shape\n    [ 3, 2 ]\n    > var bool = ( x.data === y.data )\n    true\n    > bool = ( x.get( 0, 1 ) === y.get( 1, 0 ) )\n    true\n\n    See Also\n    --------\n    ndarray\n","base.tribonacci":"\nbase.tribonacci( n )\n    Computes the nth Tribonacci number.\n\n    Tribonacci numbers follow the recurrence relation\n\n      F_n = F_{n-1} + F_{n-2} + F_{n-3}\n\n    with seed values F_0 = 0, F_1 = 0, and F_2 = 1.\n\n    If `n` is greater than `63`, the function returns `NaN`, as larger\n    Tribonacci numbers cannot be accurately represented due to limitations of\n    double-precision floating-point format.\n\n    If not provided a nonnegative integer value, the function returns `NaN`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Input value.\n\n    Returns\n    -------\n    y: integer\n        Tribonacci number.\n\n    Examples\n    --------\n    > var y = base.tribonacci( 0 )\n    0\n    > y = base.tribonacci( 1 )\n    0\n    > y = base.tribonacci( 2 )\n    1\n    > y = base.tribonacci( 3 )\n    1\n    > y = base.tribonacci( 4 )\n    2\n    > y = base.tribonacci( 64 )\n    NaN\n    > y = base.tribonacci( NaN )\n    NaN\n\n    See Also\n    --------\n    base.fibonacci\n","base.trigamma":"\nbase.trigamma( x )\n    Evaluates the trigamma function.\n\n    If `x` is `0` or a negative `integer`, the `function` returns `NaN`.\n\n    If provided `NaN`, the `function` returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.trigamma( -2.5 )\n    ~9.539\n    > y = base.trigamma( 1.0 )\n    ~1.645\n    > y = base.trigamma( 10.0 )\n    ~0.105\n    > y = base.trigamma( NaN )\n    NaN\n    > y = base.trigamma( -1.0 )\n    NaN\n\n    See Also\n    --------\n    base.digamma, base.gamma\n","base.trim":"\nbase.trim( str )\n    Trims whitespace from the beginning and end of a `string`.\n\n    \"Whitespace\" is defined as the following characters:\n\n    - \\f\n    - \\n\n    - \\r\n    - \\t\n    - \\v\n    - \\u0020\n    - \\u00a0\n    - \\u1680\n    - \\u2000-\\u200a\n    - \\u2028\n    - \\u2029\n    - \\u202f\n    - \\u205f\n    - \\u3000\n    - \\ufeff\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Trimmed string.\n\n    Examples\n    --------\n    > var out = base.trim( ' \\t\\t\\n  Beep \\r\\n\\t  ' )\n    'Beep'\n\n    See Also\n    --------\n    base.leftTrim, base.rightTrim\n","base.trunc":"\nbase.trunc( x )\n    Rounds a double-precision floating-point number toward zero.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.trunc( 3.14 )\n    3.0\n    > y = base.trunc( -4.2 )\n    -4.0\n    > y = base.trunc( -4.6 )\n    -4.0\n    > y = base.trunc( 9.5 )\n    9.0\n    > y = base.trunc( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceil, base.floor, base.round\n","base.trunc2":"\nbase.trunc2( x )\n    Rounds a numeric value to the nearest power of two toward zero.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.trunc2( 3.14 )\n    2.0\n    > y = base.trunc2( -4.2 )\n    -4.0\n    > y = base.trunc2( -4.6 )\n    -4.0\n    > y = base.trunc2( 9.5 )\n    8.0\n    > y = base.trunc2( 13.0 )\n    8.0\n    > y = base.trunc2( -13.0 )\n    -8.0\n    > y = base.trunc2( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceil2, base.floor2, base.round2, base.trunc, base.trunc10\n","base.trunc10":"\nbase.trunc10( x )\n    Rounds a numeric value to the nearest power of ten toward zero.\n\n    The function may not return accurate results for subnormals due to a general\n    loss in precision.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.trunc10( 3.14 )\n    1.0\n    > y = base.trunc10( -4.2 )\n    -1.0\n    > y = base.trunc10( -4.6 )\n    -1.0\n    > y = base.trunc10( 9.5 )\n    1.0\n    > y = base.trunc10( 13.0 )\n    10.0\n    > y = base.trunc10( -13.0 )\n    -10.0\n    > y = base.trunc10( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceil10, base.floor10, base.round10, base.trunc, base.trunc2\n","base.truncateMiddle":"\nbase.truncateMiddle( str, len, seq )\n    Truncates the middle UTF-16 code units of a string to return a string\n    having a specified length.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    len: integer\n        Output string length.\n\n    seq: string\n        Custom replacement sequence.\n\n    Returns\n    -------\n    out: string\n        Truncated string.\n\n    Examples\n    --------\n    > var str = 'beep boop';\n    > var out = base.truncateMiddle( str, 5, '...' )\n    'b...p'\n    > out = base.truncateMiddle( str, 5, '|' )\n    'be|op'\n","base.truncb":"\nbase.truncb( x, n, b )\n    Rounds a numeric value to the nearest multiple of `b^n` toward zero.\n\n    Due to floating-point rounding error, rounding may not be exact.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Integer power.\n\n    b: integer\n        Base.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    // Round to 4 decimal places:\n    > var y = base.truncb( 3.14159, -4, 10 )\n    3.1415\n\n    // If `n = 0` or `b = 1`, standard round behavior:\n    > y = base.truncb( 3.14159, 0, 2 )\n    3.0\n\n    // Round to nearest multiple of two toward zero:\n    > y = base.truncb( 5.0, 1, 2 )\n    4.0\n\n    See Also\n    --------\n    base.ceilb, base.floorb, base.roundb, base.trunc, base.truncn\n","base.truncf":"\nbase.truncf( x )\n    Rounds a single-precision floating-point number toward zero.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.truncf( 3.14 )\n    3.0\n    > y = base.truncf( -4.2 )\n    -4.0\n    > y = base.truncf( -4.6 )\n    -4.0\n    > y = base.truncf( 9.5 )\n    9.0\n    > y = base.truncf( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceilf, base.floorf, base.trunc\n","base.truncn":"\nbase.truncn( x, n )\n    Rounds a numeric value to the nearest multiple of `10^n` toward zero.\n\n    When operating on floating-point numbers in bases other than `2`, rounding\n    to specified digits can be inexact.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Integer power of 10.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    // Round to 4 decimal places:\n    > var y = base.truncn( 3.14159, -4 )\n    3.1415\n\n    // If `n = 0`, standard round behavior:\n    > y = base.truncn( 3.14159, 0 )\n    3.0\n\n    // Round to nearest thousand:\n    > y = base.truncn( 12368.0, 3 )\n    12000.0\n\n\n    See Also\n    --------\n    base.ceiln, base.floorn, base.roundn, base.trunc, base.truncb\n","base.truncsd":"\nbase.truncsd( x, n, b )\n    Rounds a numeric value to the nearest number toward zero with `n`\n    significant figures.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Number of significant figures. Must be greater than 0.\n\n    b: integer\n        Base. Must be greater than 0.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.truncsd( 3.14159, 5, 10 )\n    3.1415\n    > y = base.truncsd( 3.14159, 1, 10 )\n    3.0\n    > y = base.truncsd( 12368.0, 2, 10 )\n    12000.0\n    > y = base.truncsd( 0.0313, 2, 2 )\n    0.03125\n\n    See Also\n    --------\n    base.ceilsd, base.floorsd, base.roundsd, base.trunc\n","base.uint32ToInt32":"\nbase.uint32ToInt32( x )\n    Converts an unsigned 32-bit integer to a signed 32-bit integer.\n\n    Parameters\n    ----------\n    x: integer\n        Unsigned 32-bit integer.\n\n    Returns\n    -------\n    out: integer\n        Signed 32-bit integer.\n\n    Examples\n    --------\n    > var y = base.uint32ToInt32( base.float64ToUint32( 4294967295 ) )\n    -1\n    > y = base.uint32ToInt32( base.float64ToUint32( 3 ) )\n    3\n\n","base.umul":"\nbase.umul( a, b )\n    Performs C-like multiplication of two unsigned 32-bit integers.\n\n    Parameters\n    ----------\n    a: integer\n        Unsigned 32-bit integer.\n\n    b: integer\n        Unsigned 32-bit integer.\n\n    Returns\n    -------\n    out: integer\n        Product.\n\n    Examples\n    --------\n    > var v = base.umul( 10>>>0, 4>>>0 )\n    40\n\n    See Also\n    --------\n    base.imul\n","base.umuldw":"\nbase.umuldw( a, b )\n    Multiplies two unsigned 32-bit integers and returns an array of two unsigned\n    32-bit integers which represents the unsigned 64-bit integer product.\n\n    When computing the product of 32-bit integer values in double-precision\n    floating-point format (the default JavaScript numeric data type), computing\n    the double word product is necessary in order to avoid exceeding the maximum\n    safe double-precision floating-point integer value.\n\n    Parameters\n    ----------\n    a: integer\n        Unsigned 32-bit integer.\n\n    b: integer\n        Unsigned 32-bit integer.\n\n    Returns\n    -------\n    out: Array<number>\n        Double word product (in big endian order; i.e., the first element\n        corresponds to the most significant bits and the second element to the\n        least significant bits).\n\n    Examples\n    --------\n    > var v = base.umuldw( 1, 10 )\n    [ 0, 10 ]\n\n\nbase.umuldw.assign( a, b, out, stride, offset )\n    Multiplies two unsigned 32-bit integers and assigns results representing\n    the unsigned 64-bit integer product to a provided output array.\n\n    When computing the product of 32-bit integer values in double-precision\n    floating-point format (the default JavaScript numeric data type), computing\n    the double word product is necessary in order to avoid exceeding the maximum\n    safe double-precision floating-point integer value.\n\n    Parameters\n    ----------\n    a: integer\n        Unsigned 32-bit integer.\n\n    b: integer\n        Unsigned 32-bit integer.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Double word product (in big endian order; i.e., the first element\n        corresponds to the most significant bits and the second element to the\n        least significant bits).\n\n    Examples\n    --------\n    > var out = [ 0, 0 ];\n    > var v = base.umuldw.assign( 1, 10, out, 1, 0 )\n    [ 0, 10 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.imuldw, base.umul\n","base.umuldw.assign":"\nbase.umuldw.assign( a, b, out, stride, offset )\n    Multiplies two unsigned 32-bit integers and assigns results representing\n    the unsigned 64-bit integer product to a provided output array.\n\n    When computing the product of 32-bit integer values in double-precision\n    floating-point format (the default JavaScript numeric data type), computing\n    the double word product is necessary in order to avoid exceeding the maximum\n    safe double-precision floating-point integer value.\n\n    Parameters\n    ----------\n    a: integer\n        Unsigned 32-bit integer.\n\n    b: integer\n        Unsigned 32-bit integer.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Double word product (in big endian order; i.e., the first element\n        corresponds to the most significant bits and the second element to the\n        least significant bits).\n\n    Examples\n    --------\n    > var out = [ 0, 0 ];\n    > var v = base.umuldw.assign( 1, 10, out, 1, 0 )\n    [ 0, 10 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.imuldw, base.umul","base.uncapitalize":"\nbase.uncapitalize( str )\n    Lowercases the first character of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Uncapitalized string.\n\n    Examples\n    --------\n    > var out = base.uncapitalize( 'Beep' )\n    'beep'\n    > out = base.uncapitalize( 'bOOp' )\n    'bOOp'\n\n    See Also\n    --------\n    base.capitalize\n","base.uppercase":"\nbase.uppercase( str )\n    Converts a string to uppercase.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Uppercase string.\n\n    Examples\n    --------\n    > var out = base.uppercase( 'bEEp' )\n    'BEEP'\n\n    See Also\n    --------\n    base.lowercase\n","base.vercos":"\nbase.vercos( x )\n    Computes the versed cosine.\n\n    The versed cosine is defined as `1 + cos(x)`.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Versed cosine.\n\n    Examples\n    --------\n    > var y = base.vercos( 3.14 )\n    ~0.0\n    > y = base.vercos( -4.2 )\n    ~0.5097\n    > y = base.vercos( -4.6 )\n    ~0.8878\n    > y = base.vercos( 9.5 )\n    ~0.0028\n    > y = base.vercos( -0.0 )\n    2.0\n\n    See Also\n    --------\n    base.cos, base.versin\n","base.versin":"\nbase.versin( x )\n    Computes the versed sine.\n\n    The versed sine is defined as `1 - cos(x)`.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Versed sine.\n\n    Examples\n    --------\n    > var y = base.versin( 3.14 )\n    ~2.0\n    > y = base.versin( -4.2 )\n    ~1.490\n    > y = base.versin( -4.6 )\n    ~1.112\n    > y = base.versin( 9.5 )\n    ~1.997\n    > y = base.versin( -0.0 )\n    0.0\n\n    See Also\n    --------\n    base.cos, base.sin, base.vercos\n","base.wrap":"\nbase.wrap( v, min, max )\n    Wraps a value on the half-open interval `[min,max)`.\n\n    The function does not distinguish between positive and negative zero. Where\n    appropriate, the function returns positive zero.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    v: number\n        Value to wrap.\n\n    min: number\n        Minimum value.\n\n    max: number\n        Maximum value.\n\n    Returns\n    -------\n    y: number\n        Wrapped value.\n\n    Examples\n    --------\n    > var y = base.wrap( 3.14, 0.0, 5.0 )\n    3.14\n    > y = base.wrap( -3.14, 0.0, 5.0 )\n    ~1.86\n    > y = base.wrap( 3.14, 0.0, 3.0 )\n    ~0.14\n    > y = base.wrap( -0.0, 0.0, 5.0 )\n    0.0\n    > y = base.wrap( 0.0, -3.14, -0.0 )\n    -3.14\n    > y = base.wrap( NaN, 0.0, 5.0 )\n    NaN\n\n    See Also\n    --------\n    base.clamp\n","base.xlog1py":"\nbase.xlog1py( x, y )\n    Computes `x * ln(y+1)` so that the result is `0` if `x = 0`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    y: number\n        Input value.\n\n    Returns\n    -------\n    out: number\n        Function value.\n\n    Examples\n    --------\n    > var out = base.xlog1py( 3.0, 2.0 )\n    ~3.296\n    > out = base.xlog1py( 1.5, 5.9 )\n    ~2.897\n    > out = base.xlog1py( 0.9, 1.0 )\n    ~0.624\n    > out = base.xlog1py( 1.0, 0.0 )\n    0.0\n    > out = base.xlog1py( 0.0, -2.0 )\n    0.0\n    > out = base.xlog1py( 1.5, NaN )\n    NaN\n    > out = base.xlog1py( 0.0, NaN )\n    NaN\n    > out = base.xlog1py( NaN, 2.3 )\n    NaN\n\n    See Also\n    --------\n    base.log1p, base.xlogy\n","base.xlogy":"\nbase.xlogy( x, y )\n    Computes `x * ln(y)` so that the result is `0` if `x = 0`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    y: number\n        Input value.\n\n    Returns\n    -------\n    out: number\n        Function value.\n\n    Examples\n    --------\n    > var out = base.xlogy( 3.0, 2.0 )\n    ~2.079\n    > out = base.xlogy( 1.5, 5.9 )\n    ~2.662\n    > out = base.xlogy( 0.9, 1.0 )\n    0.0\n    > out = base.xlogy( 0.0, -2.0 )\n    0.0\n    > out = base.xlogy( 1.5, NaN )\n    NaN\n    > out = base.xlogy( 0.0, NaN )\n    NaN\n    > out = base.xlogy( NaN, 2.3 )\n    NaN\n\n    See Also\n    --------\n    base.ln, base.xlog1py\n","base.zeta":"\nbase.zeta( s )\n    Evaluates the Riemann zeta function as a function of a real variable `s`.\n\n    Parameters\n    ----------\n    s: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.zeta( 1.1 )\n    ~10.584\n    > y = base.zeta( -4.0 )\n    0.0\n    > y = base.zeta( 70.0 )\n    1.0\n    > y = base.zeta( 0.5 )\n    ~-1.46\n    > y = base.zeta( NaN )\n    NaN\n\n    // Evaluate at a pole:\n    > y = base.zeta( 1.0 )\n    NaN\n\n","BERNDT_CPS_WAGES_1985":"\nBERNDT_CPS_WAGES_1985()\n    Returns a random sample of 534 workers from the Current Population Survey\n    (CPS) from 1985, including their wages and and other characteristics.\n\n    Each array element has the following eleven fields:\n\n    - education: number of years of education.\n    - south: indicator variable for southern region (1 if a person lives in the\n    South; 0 if a person does not live in the South).\n    - gender: gender of the person.\n    - experience: number of years of work experience.\n    - union: indicator variable for union membership (1 if union member; 0 if\n    not a union member).\n    - wage: wage (in dollars per hour).\n    - age: age (in years).\n    - race: ethnicity/race (white, hispanic, and other).\n    - occupation: occupational category (management, sales, clerical, service,\n    professional, and other).\n    - sector: sector (other, manufacturing, or construction).\n    - married: marital status (0 if unmarried; 1 if married).\n\n    Based on residual plots, wages were log-transformed to stabilize the\n    variance.\n\n    Returns\n    -------\n    out: Array<Object>\n        CPS data.\n\n    Examples\n    --------\n    > var data = BERNDT_CPS_WAGES_1985()\n    [ {...}, {...}, ... ]\n\n    References\n    ----------\n    - Berndt, Ernst R. 1991. _The Practice of Econometrics_. Addison Wesley\n    Longman Publishing Co.\n\n","bifurcate":"\nbifurcate( collection, [options,] filter )\n    Splits values into two groups.\n\n    If an element in `filter` is truthy, then the corresponding element in the\n    input collection belongs to the first group; otherwise, the collection\n    element belongs to the second group.\n\n    If provided an empty collection, the function returns an empty array.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection to group. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Options.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `indices`, indices are returned; if\n        `*`, both indices and values are returned. Default: 'values'.\n\n    filter: Array|TypedArray|Object\n        A collection indicating which group an element in the input collection\n        belongs to. If an element in `filter` is truthy, the corresponding\n        element in `collection` belongs to the first group; otherwise, the\n        collection element belongs to the second group. If provided an object,\n        the object must be array-like (excluding strings and functions).\n\n    Returns\n    -------\n    out: Array<Array>|Array\n        Group results.\n\n    Examples\n    --------\n    > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n    > var f = [ true, true, false, true ];\n    > var out = bifurcate( collection, f )\n    [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n    > f = [ 1, 1, 0, 1 ];\n    > out = bifurcate( collection, f )\n    [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n    // Output group results as indices:\n    > f = [ true, true, false, true ];\n    > var opts = { 'returns': 'indices' };\n    > out = bifurcate( collection, opts, f )\n    [ [ 0, 1, 3 ], [ 2 ] ]\n\n    // Output group results as index-element pairs:\n    > opts = { 'returns': '*' };\n    > out = bifurcate( collection, opts, f )\n    [ [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], [ [2, 'foo'] ] ]\n\n    See Also\n    --------\n    bifurcateBy, bifurcateOwn, group\n","bifurcateBy":"\nbifurcateBy( collection, [options,] predicate )\n    Splits values into two groups according to a predicate function.\n\n    When invoked, the predicate function is provided two arguments:\n\n    - value: collection value.\n    - index: collection index.\n\n    If a predicate function returns a truthy value, a collection value is\n    placed in the first group; otherwise, a collection value is placed in the\n    second group.\n\n    If provided an empty collection, the function returns an empty array.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection to group. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Options.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `indices`, indices are returned; if\n        `*`, both indices and values are returned. Default: 'values'.\n\n    predicate: Function\n        Predicate function indicating which group an element in the input\n        collection belongs to.\n\n    Returns\n    -------\n    out: Array<Array>|Array\n        Group results.\n\n    Examples\n    --------\n    > function predicate( v ) { return v[ 0 ] === 'b'; };\n    > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n    > var out = bifurcateBy( collection, predicate )\n    [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n    // Output group results as indices:\n    > var opts = { 'returns': 'indices' };\n    > out = bifurcateBy( collection, opts, predicate )\n    [ [ 0, 1, 3 ], [ 2 ] ]\n\n    // Output group results as index-value pairs:\n    > opts = { 'returns': '*' };\n    > out = bifurcateBy( collection, opts, predicate )\n    [ [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], [ [2, 'foo' ] ] ]\n\n    See Also\n    --------\n    bifurcate, groupBy\n","bifurcateByAsync":"\nbifurcateByAsync( collection, [options,] predicate, done )\n    Splits values into two groups according to a predicate function.\n\n    When invoked, the predicate function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If the\n    predicate function accepts two arguments, the predicate function is\n    provided:\n\n    - value\n    - next\n\n    If the predicate function accepts three arguments, the predicate function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other predicate function signature, the predicate function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - group: value group.\n\n    If an predicate function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    If a predicate function calls the `next` callback with a truthy group value,\n    a collection value is placed in the first group; otherwise, a collection\n    value is placed in the second group.\n\n    If provided an empty collection, the function calls the `done` callback with\n    an empty array as the second argument.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `indices`, indices are returned; if\n        `*`, both indices and values are returned. Default: 'values'.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        Predicate function indicating which group an element in the input\n        collection belongs to.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function predicate( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > bifurcateByAsync( arr, predicate, done )\n    1000\n    2500\n    3000\n    [ [ 1000, 3000 ], [ 2500 ] ]\n\n    // Output group results as indices:\n    > var opts = { 'returns': 'indices' };\n    > bifurcateByAsync( arr, opts, predicate, done )\n    1000\n    2500\n    3000\n    [ [ 2, 0 ], [ 1 ] ]\n\n    // Output group results as index-value pairs:\n    > opts = { 'returns': '*' };\n    > bifurcateByAsync( arr, opts, predicate, done )\n    1000\n    2500\n    3000\n    [ [ [ 2, 1000 ], [ 0, 3000 ] ], [ [ 1, 2500 ] ] ]\n\n    // Limit number of concurrent invocations:\n    > function predicate( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 3000, 2500, 1000 ];\n    > bifurcateByAsync( arr, opts, predicate, done )\n    2500\n    3000\n    1000\n    [ [ 3000, 1000 ], [ 2500 ] ]\n\n    // Process sequentially:\n    > function predicate( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 3000, 2500, 1000 ];\n    > bifurcateByAsync( arr, opts, predicate, done )\n    3000\n    2500\n    1000\n    [ [ 3000, 1000 ], [ 2500 ] ]\n\n\nbifurcateByAsync.factory( [options,] predicate )\n    Returns a function which splits values into two groups according to an\n    predicate function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `indices`, indices are returned; if\n        `*`, both indices and values are returned. Default: 'values'.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        Predicate function indicating which group an element in the input\n        collection belongs to.\n\n    Returns\n    -------\n    out: Function\n        A function which splits values into two groups.\n\n    Examples\n    --------\n    > function predicate( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = bifurcateByAsync.factory( opts, predicate );\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    [ [ 3000, 1000 ], [ 2500 ] ]\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    [ [ 2000, 1000 ], [ 1500 ] ]\n\n    See Also\n    --------\n    bifurcateBy, groupByAsync\n","bifurcateByAsync.factory":"\nbifurcateByAsync.factory( [options,] predicate )\n    Returns a function which splits values into two groups according to an\n    predicate function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `indices`, indices are returned; if\n        `*`, both indices and values are returned. Default: 'values'.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        Predicate function indicating which group an element in the input\n        collection belongs to.\n\n    Returns\n    -------\n    out: Function\n        A function which splits values into two groups.\n\n    Examples\n    --------\n    > function predicate( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = bifurcateByAsync.factory( opts, predicate );\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    [ [ 3000, 1000 ], [ 2500 ] ]\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    [ [ 2000, 1000 ], [ 1500 ] ]\n\n    See Also\n    --------\n    bifurcateBy, groupByAsync","bifurcateIn":"\nbifurcateIn( obj, [options,] predicate )\n    Splits values into two groups according to a predicate function.\n\n    When invoked, the predicate function is provided two arguments:\n\n    - value: object value.\n    - key: object key.\n\n    If a predicate function returns a truthy value, a value is placed in the\n    first group; otherwise, a value is placed in the second group.\n\n    If provided an empty object with no prototype, the function returns an empty\n    array.\n\n    The function iterates over an object's own and inherited properties.\n\n    Key iteration order is *not* guaranteed, and, thus, result order is *not*\n    guaranteed.\n\n    Parameters\n    ----------\n    obj: Object|Array|TypedArray\n        Input object to group.\n\n    options: Object (optional)\n        Options.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `keys`, keys are returned; if `*`,\n        both keys and values are returned. Default: 'values'.\n\n    predicate: Function\n        Predicate function indicating which group a value in the input object\n        belongs to.\n\n    Returns\n    -------\n    out: Array<Array>|Array\n        Group results.\n\n    Examples\n    --------\n    > function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\n    > Foo.prototype = Object.create( null );\n    > Foo.prototype.c = 'foo';\n    > Foo.prototype.d = 'bar';\n    > var obj = new Foo();\n    > function predicate( v ) { return v[ 0 ] === 'b'; };\n    > var out = bifurcateIn( obj, predicate )\n    [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n    // Output group results as keys:\n    > var opts = { 'returns': 'keys' };\n    > out = bifurcateIn( obj, opts, predicate )\n    [ [ 'a', 'b', 'd' ], [ 'c' ] ]\n\n    // Output group results as key-value pairs:\n    > opts = { 'returns': '*' };\n    > out = bifurcateIn( obj, opts, predicate )\n    [ [ ['a', 'beep'], ['b', 'boop'], ['d', 'bar'] ], [ ['c', 'foo' ] ] ]\n\n    See Also\n    --------\n    bifurcate, bifurcateBy, bifurcateOwn, groupIn\n","bifurcateOwn":"\nbifurcateOwn( obj, [options,] predicate )\n    Splits values into two groups according to a predicate function.\n\n    When invoked, the predicate function is provided two arguments:\n\n    - value: object value.\n    - key: object key.\n\n    If a predicate function returns a truthy value, a value is placed in the\n    first group; otherwise, a value is placed in the second group.\n\n    If provided an empty object, the function returns an empty array.\n\n    The function iterates over an object's own properties.\n\n    Key iteration order is *not* guaranteed, and, thus, result order is *not*\n    guaranteed.\n\n    Parameters\n    ----------\n    obj: Object|Array|TypedArray\n        Input object to group.\n\n    options: Object (optional)\n        Options.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `keys`, keys are returned; if `*`,\n        both keys and values are returned. Default: 'values'.\n\n    predicate: Function\n        Predicate function indicating which group a value in the input object\n        belongs to.\n\n    Returns\n    -------\n    out: Array<Array>|Array\n        Group results.\n\n    Examples\n    --------\n    > function predicate( v ) { return v[ 0 ] === 'b'; };\n    > var obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\n    > var out = bifurcateOwn( obj, predicate )\n    [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n    // Output group results as keys:\n    > var opts = { 'returns': 'keys' };\n    > out = bifurcateOwn( obj, opts, predicate )\n    [ [ 'a', 'b', 'd' ], [ 'c' ] ]\n\n    // Output group results as key-value pairs:\n    > opts = { 'returns': '*' };\n    > out = bifurcateOwn( obj, opts, predicate )\n    [ [ ['a', 'beep'], ['b', 'boop'], ['d', 'bar'] ], [ ['c', 'foo' ] ] ]\n\n    See Also\n    --------\n    bifurcate, bifurcateBy, bifurcateIn, groupOwn\n","BigInt":"\nBigInt( value )\n    Returns a BigInt.\n\n    Unlike conventional constructors, this function does **not** support the\n    `new` keyword.\n\n    This function is only supported in environments which support BigInts.\n\n    Parameters\n    ----------\n    value: integer|string\n        Value of the BigInt.\n\n    Returns\n    -------\n    out: BigInt\n        BigInt.\n\n    Examples\n    --------\n    > var v = ( BigInt ) ? BigInt( '1' ) : null\n\n\nTODO: document properties/methods\n\n","binomialTest":"\nbinomialTest( x[, n][, options] )\n    Computes an exact test for the success probability in a Bernoulli\n    experiment.\n\n    The returned object comes with a `.print()` method which when invoked will\n    print a formatted output of the results of the hypothesis test.\n\n    Parameters\n    ----------\n    x: (number|Array<number>)\n        Number of successes or two-element array with successes and failures.\n\n    n: Array<number> (optional)\n        Total number of observations.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.alternative: string (optional)\n        Indicates whether the alternative hypothesis is that the mean of `x` is\n        larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n        `mu` (`two-sided`). Default: `'two-sided'`.\n\n    options.p: number (optional)\n        Hypothesized probability under the null hypothesis. Default: `0.5`.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Used significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Sample proportion.\n\n    out.ci: Array<number>\n        1-alpha confidence interval for the success probability.\n\n    out.nullValue: number\n        Assumed success probability under H0.\n\n    out.alternative: string\n        Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n    out.method: string\n        Name of test.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    > var out = binomialTest( 682, 925 )\n    {\n        'pValue': ~3.544e-49,\n        'statistic': ~0.737\n        // ...\n    }\n\n    > out = binomialTest( [ 682, 925 - 682 ] )\n    {\n        'pValue': ~3.544e-49,\n        'statistic': ~0.737\n        // ...\n    }\n\n    > out = binomialTest( 21, 40, {\n    ...     'p': 0.4,\n    ...     'alternative': 'greater'\n    ... })\n    {\n        'pValue': ~0.074,\n        'statistic': 0.525\n        // ...\n    }\n\n","Boolean":"\nBoolean( value )\n    Returns a boolean.\n\n    When invoked without `new`,\n\n    - if provided `false`, `null`, `undefined`, `-0`, `0`, `NaN`, or an empty\n      string, the function returns `false`.\n    - if provided any other value, including an empty object, an empty array,\n      the string `'false'`, or a `Boolean` object (including a `Boolean` object\n      whose value is `false`), the function returns `true`.\n\n    When invoked with `new`, the constructor returns a `Boolean` object, which\n    is an object wrapper for a primitive boolean value. The value of the\n    returned `Boolean` object follows the same conversion semantics as when the\n    constructor is invoked without `new`.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    out: boolean|Boolean\n        Boolean primitive or object.\n\n    Examples\n    --------\n    > var b = new Boolean( null )\n    <Boolean>\n    > b = Boolean( null )\n    false\n    > b = Boolean( [] )\n    true\n\nBoolean.prototype.toString()\n    Returns a string representing the `Boolean` object.\n\n    Returns\n    -------\n    out: string\n        String representation.\n\n    Examples\n    --------\n    > var b = new Boolean( true )\n    <Boolean>\n    > b.toString()\n    'true'\n\nBoolean.prototype.valueOf()\n    Returns the primitive value of a `Boolean` object.\n\n    Returns\n    -------\n    out: boolean\n        Boolean primitive.\n\n    Examples\n    --------\n    > var b = new Boolean( true )\n    <Boolean>\n    > b.valueOf()\n    true\n\n","Boolean.prototype.toString":"\nBoolean.prototype.toString()\n    Returns a string representing the `Boolean` object.\n\n    Returns\n    -------\n    out: string\n        String representation.\n\n    Examples\n    --------\n    > var b = new Boolean( true )\n    <Boolean>\n    > b.toString()\n    'true'","Boolean.prototype.valueOf":"\nBoolean.prototype.valueOf()\n    Returns the primitive value of a `Boolean` object.\n\n    Returns\n    -------\n    out: boolean\n        Boolean primitive.\n\n    Examples\n    --------\n    > var b = new Boolean( true )\n    <Boolean>\n    > b.valueOf()\n    true","BooleanArray":"\nBooleanArray()\n    A Boolean array.\n\n    Returns\n    -------\n    out: BooleanArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new BooleanArray()\n    <BooleanArray>\n\n\nBooleanArray( length )\n    Creates a boolean array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: BooleanArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 10 )\n    <BooleanArray>\n    > var len = arr.length\n    10\n\n\nBooleanArray( booleanarray )\n    Creates a boolean array from another boolean array.\n\n    Parameters\n    ----------\n    booleanarray: BooleanArray\n        Boolean array from which to generate another boolean array.\n\n    Returns\n    -------\n    out: BooleanArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new BooleanArray( [ true, false, false, true ] )\n    <BooleanArray>\n    > var arr2 = new BooleanArray( arr1 )\n    <BooleanArray>\n    > var len = arr2.length\n    4\n\n\nBooleanArray( typedarray )\n    Creates a boolean array from a typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate boolean array.\n\n    Returns\n    -------\n    out: BooleanArray\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new Uint8Array( [ 1, 0, 0, 1 ] )\n    <Uint8Array>\n    > var arr = new BooleanArray( buf )\n    <BooleanArray>\n    > var len = arr.length\n    4\n\n\nBooleanArray( obj )\n    Creates a boolean array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a boolean array.\n\n    Returns\n    -------\n    out: BooleanArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new BooleanArray( [ true, false, false, true ] )\n    <BooleanArray>\n    > var len = arr1.length\n    4\n    > var arr2 = new BooleanArray( [ {}, null, '', 4 ] );\n    > len = arr2.length\n    4\n\n\nBooleanArray( buffer[, byteOffset[, length]] )\n    Returns a boolean array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: BooleanArray\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 240 );\n    > var arr1 = new BooleanArray( buf )\n    <BooleanArray>\n    > var len = arr1.length\n    240\n    > var arr2 = new BooleanArray( buf, 8 )\n    <BooleanArray>\n    > len = arr2.length\n    232\n    > var arr3 = new BooleanArray( buf, 8, 20 )\n    <BooleanArray>\n    > len = arr3.length\n    20\n\n\nBooleanArray.from( src[, clbk[, thisArg]] )\n    Creates a new boolean array from an array-like object or an iterable.\n\n    A callback function is provided two arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    clbk: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: BooleanArray\n        A typed array.\n\n    Examples\n    --------\n    > function map( v ) { return !v };\n    > var src = [ true, false ];\n    > var arr = BooleanArray.from( src, map )\n    <BooleanArray>\n    > var len = arr.length\n    2\n    > var v = arr.get( 0 )\n    false\n    > v = arr.get( 1 )\n    true\n\n\nBooleanArray.of( element0[, element1[, ...elementN]] )\n    Creates a new boolean array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: bool\n        Array element.\n\n    element1: bool (optional)\n        Array element.\n\n    elementN: ...bool (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: BooleanArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = BooleanArray.of( true, false, false, true )\n    <BooleanArray>\n    > var len = arr.length\n    4\n\n\nBooleanArray.BYTES_PER_ELEMENT\n    The size of each array element in bytes.\n\n    Examples\n    --------\n    > var nbytes = BooleanArray.BYTES_PER_ELEMENT\n    1\n\n\nBooleanArray.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > var str = BooleanArray.name\n    'BooleanArray'\n\n\nBooleanArray.prototype.buffer\n    Pointer to the underlying data buffer.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 2 )\n    <BooleanArray>\n    > var buf = arr.buffer\n    <ArrayBuffer>\n\n\nBooleanArray.prototype.byteLength\n    Size of the array in bytes.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 10 )\n    <BooleanArray>\n    > var nbytes = arr.byteLength\n    10\n\n\nBooleanArray.prototype.byteOffset\n    Offset (in bytes) of the array from the start of its underlying\n    ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 10 )\n    <BooleanArray>\n    > var offset = arr.byteOffset\n    0\n    > var buf = new ArrayBuffer( 240 );\n    > arr = new BooleanArray( buf, 64 )\n    <BooleanArray>\n    > offset = arr.byteOffset\n    64\n\n\nBooleanArray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 10 )\n    <BooleanArray>\n    > arr.BYTES_PER_ELEMENT\n    1\n\n\nBooleanArray.prototype.length\n    The number of array elements.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 10 )\n    <BooleanArray>\n    > var len = arr.length\n    10\n\n\nBooleanArray.prototype.at( i )\n    Returns an array element located at integer position (index) `i`, with\n    support for noth nonnegative and negative integer positions.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n\n    Returns\n    -------\n    out: boolean|void\n        An array element.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, false, true ] )\n    <BooleanArray>\n    > var v = arr.at( 1 )\n    false\n    > v = arr.at( -1 )\n    true\n\n\nBooleanArray.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n    \n    start: integer\n        Source start index position.\n    \n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: BooleanArray\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, false, true ] )\n    <BooleanArray>\n    > arr.copyWithin( 0, 2 )\n    <BooleanArray>\n    > var v = arr.get( 0 )\n    false\n    > v = arr.get( 1 )\n    true\n\n\nBooleanArray.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var it = arr.entries();\n    > var v = it.next().value\n    [ 0, true ]\n    > v = it.next().value\n    [ 1, false ]\n    > v = it.next().value\n    [ 2, true ]\n    > var bool = it.next().done\n    true\n\n\nBooleanArray.prototype.every( predicate[, thisArg] )\n    Returns a boolean indicating whether all elements in the array pass a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all elements pass the test.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ true, true, true ] )\n    <BooleanArray>\n    > var bool = arr.every( predicate )\n    true\n\n\nBooleanArray.prototype.fill( value[, start[, end]] )\n    Returns a modified typed array filled with a fill value.\n\n    Parameters\n    ----------\n    value: boolean\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: BooleanArray\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new BooleanArray( 3 )\n    <BooleanArray>\n    > arr.fill( true );\n    > var v = arr.get( 0 )\n    true\n    > v = arr.get( 1 )\n    true\n    > v = arr.get( 2 )\n    true\n\n\nBooleanArray.prototype.filter( predicate[, thisArg] )\n    Returns a new array containing the elements of an array which pass a test\n    implemented by a predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: BooleanArray\n        A new typed array.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( v === true ); };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.filter( predicate )\n    <BooleanArray>\n    > var len = out.length\n    2\n    > var v = out.get( 0 )\n    true\n    > v = out.get( 1 )\n    true\n\n\nBooleanArray.prototype.find( predicate[, thisArg] )\n    Returns the first element in an array for which a predicate function returns\n    a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: boolean|void\n        Array element or `undefined`.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var v = arr.find( predicate )\n    true\n\n\nBooleanArray.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var idx = arr.findIndex( predicate )\n    0\n\n\nBooleanArray.prototype.findLast( predicate[, thisArg] )\n    Returns the last element in an array for which a predicate function returns\n    a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: boolean|void\n        Array element or `undefined`.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var v = arr.findLast( predicate )\n    true\n\n\nBooleanArray.prototype.findLastIndex( predicate[, thisArg] )\n    Returns the index of the last element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var idx = arr.findLastIndex( predicate )\n    2\n\n\nBooleanArray.prototype.forEach( clbk[, thisArg] )\n    Invokes a function once for each array element.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Examples\n    --------\n    > var str = '%';\n    > function clbk( v ) { str += v.toString() + '%'; };\n    > var arr = new BooleanArray( [ true, false, false, true ] )\n    <BooleanArray>\n    > arr.forEach( clbk );\n    > str\n    '%true%false%false%true%'\n\n\nBooleanArray.prototype.get( i )\n    Returns an array element located at integer position (index) `i`.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n\n    Returns\n    -------\n    out: boolean|void\n        Array element or `undefined`.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 10 )\n    <BooleanArray>\n    > arr.set( true, 0 );\n    > var v = arr.get( 0 )\n    true\n\n\nBooleanArray.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a provided value.\n\n    Parameters\n    ----------\n    searchElement: boolean\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true, true, true ] )\n    <BooleanArray>\n    > var bool = arr.includes( true )\n    true\n    > bool = arr.includes( false, 3 )\n    false\n\n\nBooleanArray.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the first index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: boolean\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true, true, true ] )\n    <BooleanArray>\n    > var idx = arr.indexOf( true )\n    0\n    > idx = arr.indexOf( false, 3 )\n    -1\n\n\nBooleanArray.prototype.join( [separator] )\n    Returns a new string by concatenating all array elements separated by a\n    separator string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        Separator string. Default: ','.\n\n    Returns\n    -------\n    out: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var str = arr.join()\n    'true,false,true'\n    > str = arr.join( '|' )\n    'true|false|true'\n\n\nBooleanArray.prototype.keys()\n    Returns an iterator for iterating over each index key in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array index keys.\n    \n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false ] )\n    <BooleanArray>\n    > var it = arr.keys();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().done\n    true\n\n\nBooleanArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the last index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: boolean\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: out.length-1.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, true, true, false, true ] )\n    <BooleanArray>\n    > var idx = arr.lastIndexOf( false )\n    3\n    > idx = arr.lastIndexOf( false, 2 )\n    -1\n\n\nBooleanArray.prototype.map( clbk[, thisArg] )\n    Returns a new array with each element being the result of a provided\n    callback function.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: BooleanArray\n        A new typed array.\n\n    Examples\n    --------\n    > function invert( v ) { return !v; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.map( invert )\n    <BooleanArray>\n    > var v = out.get( 0 )\n    false\n    > v = out.get( 1 )\n    true\n    > v = out.get( 2 )\n    false\n\n\nBooleanArray.prototype.reduce( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in order, passing\n    in the return value from the calculation on the preceding element and\n    returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.\n\n    initialValue: any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: any\n        Accumulated result.\n\n    Examples\n    --------\n    > function reducer( acc, v ) { return ( acc && v ); };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.reduce( reducer )\n    false\n\n\nBooleanArray.prototype.reduceRight( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in reverse order,\n    passing in the return value from the calculation on the preceding element\n    and returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.\n\n    initialValue: any (optional)\n        Initial accumulation value.\n    \n    Returns\n    -------\n    out: any\n        Accumulated result.\n    \n    Examples\n    --------\n    > function reducer( acc, v ) { return ( acc && v ); };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.reduceRight( reducer )\n    false\n\n\nBooleanArray.prototype.reverse()\n    Reverses the array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: BooleanArray\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, false ] )\n    <BooleanArray>\n    > arr.reverse();\n    > var v = arr.get( 0 )\n    false\n    > v = arr.get( 1 )\n    false\n    > v = arr.get( 2 )\n    true\n\n\nBooleanArray.prototype.set( v[, i] )\n    Sets one or more array elements.\n\n    If provided a single argument, the method sets array elements starting at\n    position (index) `i = 0`. To set elements starting elsewhere in the array,\n    provide an index argument `i`.\n\n    To set one or more array elements, provide an array-like object containing\n    truthy and falsy values.\n\n    Parameters\n    ----------\n    v: bool|BooleanArray|ArrayLikeObject\n        Boolean value or Boolean value array.\n\n    i: integer (optional)\n        Array index at which to start setting elements. Default: 0.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 2 )\n    <BooleanArray>\n    > arr.set( false );\n    > var v = arr.get( 0 )\n    false\n    > arr.set( true, 1 );\n    > v = arr.get( 1 )\n    true\n\n\nBooleanArray.prototype.slice( [start[, end]] )\n    Copies a portion of a typed array to a new typed array.\n\n    Parameters\n    ----------\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: BooleanArray\n        New typed array.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true, false, true ] )\n    <BooleanArray>\n    > var out = arr.slice( 1 )\n    <BooleanArray>\n    > var len = out.length\n    4\n    > var v = out.get( 0 )\n    false\n    > v = out.get( 1 )\n    true\n\n\nBooleanArray.prototype.some( predicate[, thisArg] )\n    Returns a boolean indicating whether at least one element passes a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one element passes the test.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ false, true, false ] )\n    <BooleanArray>\n    > var bool = arr.some( predicate )\n    true\n\n\nBooleanArray.prototype.sort( [compareFunction] )\n    Sorts an array in-place.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first boolean value for comparison.\n    - b: second boolean value for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Comparison function.\n\n    Returns\n    -------\n    out: BooleanArray\n        Modified array.\n\n    Examples\n    --------\n    > function compare( a, b ) { return a === true ? -1 : 1; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > arr.sort( compare );\n    > var v = arr.get( 0 )\n    true\n    > v = arr.get( 1 )\n    true\n    > v = arr.get( 2 )\n    false\n\n\nBooleanArray.prototype.subarray( [begin[, end]] )\n    Creates a new typed array view over the same underlying `ArrayBuffer` and\n    with the same underlying data type as the host array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: BooleanArray\n        New typed array view.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true, false, true ] )\n    <BooleanArray>\n    > var out = arr.subarray( 1, 3 )\n    <BooleanArray>\n    > var len = out.length\n    2\n    > var v = out.get( 0 )\n    false\n    > v = out.get( 1 )\n    true\n\n\nBooleanArray.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array (optional)\n        Locale identifier(s).\n    \n    options: Object (optional)\n        An object containing serialization options.\n    \n    Returns\n    -------\n    str: string\n        Local-specific string.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var str = arr.toLocaleString()\n    'true,false,true'\n\n\nBooleanArray.prototype.toReversed()\n    Returns a new typed array containing the elements in reversed order.\n\n    Returns\n    -------\n    out: BooleanArray\n        New typed array.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, false ] )\n    <BooleanArray>\n    > var out = arr.toReversed()\n    <BooleanArray>\n    > var v = out.get( 0 )\n    false\n    > v = out.get( 1 )\n    false\n    > v = out.get( 2 )\n    true\n\n\nBooleanArray.prototype.toSorted( [compareFunction] )\n    Returns a new typed array containing the elements in sorted order.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first boolean value for comparison.\n    - b: second boolean value for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Comparison function.\n\n    Returns\n    -------\n    out: BooleanArray\n        New typed array.\n\n    Examples\n    --------\n    > function compare( a, b ) { return a === true ? -1 : 1; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.toSorted( compare );\n    > var v = out.get( 0 )\n    true\n    > v = out.get( 1 )\n    true\n    > v = out.get( 2 )\n    false\n\n\nBooleanArray.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    out: string\n        String serialization of the array.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var str = arr.toString()\n    'true,false,true'\n\n\nBooleanArray.prototype.values()\n    Returns an iterator for iterating over each value in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array values.\n    \n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false ] )\n    <BooleanArray>\n    > var it = arr.values();\n    > var v = it.next().value\n    true\n    > v = it.next().value\n    false\n    > var bool = it.next().done\n    true\n\n\nBooleanArray.prototype.with( index, value )\n    Returns a new typed array with the element at a provided index replaced\n    with a provided value.\n\n    Parameters\n    ----------\n    index: integer\n        Element index.\n    \n    value: boolean\n        Element value.  \n\n    Returns\n    -------\n    out: BooleanArray\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.with( 0, false )\n    <BooleanArray>\n    > var v = out.get( 0 )\n    false\n\n\n    See Also\n    --------\n    ArrayBuffer","BooleanArray.from":"\nBooleanArray.from( src[, clbk[, thisArg]] )\n    Creates a new boolean array from an array-like object or an iterable.\n\n    A callback function is provided two arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    clbk: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: BooleanArray\n        A typed array.\n\n    Examples\n    --------\n    > function map( v ) { return !v };\n    > var src = [ true, false ];\n    > var arr = BooleanArray.from( src, map )\n    <BooleanArray>\n    > var len = arr.length\n    2\n    > var v = arr.get( 0 )\n    false\n    > v = arr.get( 1 )\n    true","BooleanArray.of":"\nBooleanArray.of( element0[, element1[, ...elementN]] )\n    Creates a new boolean array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: bool\n        Array element.\n\n    element1: bool (optional)\n        Array element.\n\n    elementN: ...bool (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: BooleanArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = BooleanArray.of( true, false, false, true )\n    <BooleanArray>\n    > var len = arr.length\n    4","BooleanArray.BYTES_PER_ELEMENT":"\nBooleanArray.BYTES_PER_ELEMENT\n    The size of each array element in bytes.\n\n    Examples\n    --------\n    > var nbytes = BooleanArray.BYTES_PER_ELEMENT\n    1","BooleanArray.name":"\nBooleanArray.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > var str = BooleanArray.name\n    'BooleanArray'","BooleanArray.prototype.buffer":"\nBooleanArray.prototype.buffer\n    Pointer to the underlying data buffer.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 2 )\n    <BooleanArray>\n    > var buf = arr.buffer\n    <ArrayBuffer>","BooleanArray.prototype.byteLength":"\nBooleanArray.prototype.byteLength\n    Size of the array in bytes.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 10 )\n    <BooleanArray>\n    > var nbytes = arr.byteLength\n    10","BooleanArray.prototype.byteOffset":"\nBooleanArray.prototype.byteOffset\n    Offset (in bytes) of the array from the start of its underlying\n    ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 10 )\n    <BooleanArray>\n    > var offset = arr.byteOffset\n    0\n    > var buf = new ArrayBuffer( 240 );\n    > arr = new BooleanArray( buf, 64 )\n    <BooleanArray>\n    > offset = arr.byteOffset\n    64","BooleanArray.prototype.BYTES_PER_ELEMENT":"\nBooleanArray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 10 )\n    <BooleanArray>\n    > arr.BYTES_PER_ELEMENT\n    1","BooleanArray.prototype.length":"\nBooleanArray.prototype.length\n    The number of array elements.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 10 )\n    <BooleanArray>\n    > var len = arr.length\n    10","BooleanArray.prototype.at":"\nBooleanArray.prototype.at( i )\n    Returns an array element located at integer position (index) `i`, with\n    support for noth nonnegative and negative integer positions.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n\n    Returns\n    -------\n    out: boolean|void\n        An array element.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, false, true ] )\n    <BooleanArray>\n    > var v = arr.at( 1 )\n    false\n    > v = arr.at( -1 )\n    true","BooleanArray.prototype.copyWithin":"\nBooleanArray.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n    \n    start: integer\n        Source start index position.\n    \n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: BooleanArray\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, false, true ] )\n    <BooleanArray>\n    > arr.copyWithin( 0, 2 )\n    <BooleanArray>\n    > var v = arr.get( 0 )\n    false\n    > v = arr.get( 1 )\n    true","BooleanArray.prototype.entries":"\nBooleanArray.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var it = arr.entries();\n    > var v = it.next().value\n    [ 0, true ]\n    > v = it.next().value\n    [ 1, false ]\n    > v = it.next().value\n    [ 2, true ]\n    > var bool = it.next().done\n    true","BooleanArray.prototype.every":"\nBooleanArray.prototype.every( predicate[, thisArg] )\n    Returns a boolean indicating whether all elements in the array pass a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all elements pass the test.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ true, true, true ] )\n    <BooleanArray>\n    > var bool = arr.every( predicate )\n    true","BooleanArray.prototype.fill":"\nBooleanArray.prototype.fill( value[, start[, end]] )\n    Returns a modified typed array filled with a fill value.\n\n    Parameters\n    ----------\n    value: boolean\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: BooleanArray\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new BooleanArray( 3 )\n    <BooleanArray>\n    > arr.fill( true );\n    > var v = arr.get( 0 )\n    true\n    > v = arr.get( 1 )\n    true\n    > v = arr.get( 2 )\n    true","BooleanArray.prototype.filter":"\nBooleanArray.prototype.filter( predicate[, thisArg] )\n    Returns a new array containing the elements of an array which pass a test\n    implemented by a predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: BooleanArray\n        A new typed array.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( v === true ); };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.filter( predicate )\n    <BooleanArray>\n    > var len = out.length\n    2\n    > var v = out.get( 0 )\n    true\n    > v = out.get( 1 )\n    true","BooleanArray.prototype.find":"\nBooleanArray.prototype.find( predicate[, thisArg] )\n    Returns the first element in an array for which a predicate function returns\n    a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: boolean|void\n        Array element or `undefined`.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var v = arr.find( predicate )\n    true","BooleanArray.prototype.findIndex":"\nBooleanArray.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var idx = arr.findIndex( predicate )\n    0","BooleanArray.prototype.findLast":"\nBooleanArray.prototype.findLast( predicate[, thisArg] )\n    Returns the last element in an array for which a predicate function returns\n    a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: boolean|void\n        Array element or `undefined`.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var v = arr.findLast( predicate )\n    true","BooleanArray.prototype.findLastIndex":"\nBooleanArray.prototype.findLastIndex( predicate[, thisArg] )\n    Returns the index of the last element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var idx = arr.findLastIndex( predicate )\n    2","BooleanArray.prototype.forEach":"\nBooleanArray.prototype.forEach( clbk[, thisArg] )\n    Invokes a function once for each array element.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Examples\n    --------\n    > var str = '%';\n    > function clbk( v ) { str += v.toString() + '%'; };\n    > var arr = new BooleanArray( [ true, false, false, true ] )\n    <BooleanArray>\n    > arr.forEach( clbk );\n    > str\n    '%true%false%false%true%'","BooleanArray.prototype.get":"\nBooleanArray.prototype.get( i )\n    Returns an array element located at integer position (index) `i`.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n\n    Returns\n    -------\n    out: boolean|void\n        Array element or `undefined`.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 10 )\n    <BooleanArray>\n    > arr.set( true, 0 );\n    > var v = arr.get( 0 )\n    true","BooleanArray.prototype.includes":"\nBooleanArray.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a provided value.\n\n    Parameters\n    ----------\n    searchElement: boolean\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true, true, true ] )\n    <BooleanArray>\n    > var bool = arr.includes( true )\n    true\n    > bool = arr.includes( false, 3 )\n    false","BooleanArray.prototype.indexOf":"\nBooleanArray.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the first index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: boolean\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true, true, true ] )\n    <BooleanArray>\n    > var idx = arr.indexOf( true )\n    0\n    > idx = arr.indexOf( false, 3 )\n    -1","BooleanArray.prototype.join":"\nBooleanArray.prototype.join( [separator] )\n    Returns a new string by concatenating all array elements separated by a\n    separator string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        Separator string. Default: ','.\n\n    Returns\n    -------\n    out: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var str = arr.join()\n    'true,false,true'\n    > str = arr.join( '|' )\n    'true|false|true'","BooleanArray.prototype.keys":"\nBooleanArray.prototype.keys()\n    Returns an iterator for iterating over each index key in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array index keys.\n    \n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false ] )\n    <BooleanArray>\n    > var it = arr.keys();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().done\n    true","BooleanArray.prototype.lastIndexOf":"\nBooleanArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the last index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: boolean\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: out.length-1.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, true, true, false, true ] )\n    <BooleanArray>\n    > var idx = arr.lastIndexOf( false )\n    3\n    > idx = arr.lastIndexOf( false, 2 )\n    -1","BooleanArray.prototype.map":"\nBooleanArray.prototype.map( clbk[, thisArg] )\n    Returns a new array with each element being the result of a provided\n    callback function.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: BooleanArray\n        A new typed array.\n\n    Examples\n    --------\n    > function invert( v ) { return !v; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.map( invert )\n    <BooleanArray>\n    > var v = out.get( 0 )\n    false\n    > v = out.get( 1 )\n    true\n    > v = out.get( 2 )\n    false","BooleanArray.prototype.reduce":"\nBooleanArray.prototype.reduce( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in order, passing\n    in the return value from the calculation on the preceding element and\n    returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.\n\n    initialValue: any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: any\n        Accumulated result.\n\n    Examples\n    --------\n    > function reducer( acc, v ) { return ( acc && v ); };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.reduce( reducer )\n    false","BooleanArray.prototype.reduceRight":"\nBooleanArray.prototype.reduceRight( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in reverse order,\n    passing in the return value from the calculation on the preceding element\n    and returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.\n\n    initialValue: any (optional)\n        Initial accumulation value.\n    \n    Returns\n    -------\n    out: any\n        Accumulated result.\n    \n    Examples\n    --------\n    > function reducer( acc, v ) { return ( acc && v ); };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.reduceRight( reducer )\n    false","BooleanArray.prototype.reverse":"\nBooleanArray.prototype.reverse()\n    Reverses the array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: BooleanArray\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, false ] )\n    <BooleanArray>\n    > arr.reverse();\n    > var v = arr.get( 0 )\n    false\n    > v = arr.get( 1 )\n    false\n    > v = arr.get( 2 )\n    true","BooleanArray.prototype.set":"\nBooleanArray.prototype.set( v[, i] )\n    Sets one or more array elements.\n\n    If provided a single argument, the method sets array elements starting at\n    position (index) `i = 0`. To set elements starting elsewhere in the array,\n    provide an index argument `i`.\n\n    To set one or more array elements, provide an array-like object containing\n    truthy and falsy values.\n\n    Parameters\n    ----------\n    v: bool|BooleanArray|ArrayLikeObject\n        Boolean value or Boolean value array.\n\n    i: integer (optional)\n        Array index at which to start setting elements. Default: 0.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 2 )\n    <BooleanArray>\n    > arr.set( false );\n    > var v = arr.get( 0 )\n    false\n    > arr.set( true, 1 );\n    > v = arr.get( 1 )\n    true","BooleanArray.prototype.slice":"\nBooleanArray.prototype.slice( [start[, end]] )\n    Copies a portion of a typed array to a new typed array.\n\n    Parameters\n    ----------\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: BooleanArray\n        New typed array.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true, false, true ] )\n    <BooleanArray>\n    > var out = arr.slice( 1 )\n    <BooleanArray>\n    > var len = out.length\n    4\n    > var v = out.get( 0 )\n    false\n    > v = out.get( 1 )\n    true","BooleanArray.prototype.some":"\nBooleanArray.prototype.some( predicate[, thisArg] )\n    Returns a boolean indicating whether at least one element passes a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one element passes the test.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ false, true, false ] )\n    <BooleanArray>\n    > var bool = arr.some( predicate )\n    true","BooleanArray.prototype.sort":"\nBooleanArray.prototype.sort( [compareFunction] )\n    Sorts an array in-place.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first boolean value for comparison.\n    - b: second boolean value for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Comparison function.\n\n    Returns\n    -------\n    out: BooleanArray\n        Modified array.\n\n    Examples\n    --------\n    > function compare( a, b ) { return a === true ? -1 : 1; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > arr.sort( compare );\n    > var v = arr.get( 0 )\n    true\n    > v = arr.get( 1 )\n    true\n    > v = arr.get( 2 )\n    false","BooleanArray.prototype.subarray":"\nBooleanArray.prototype.subarray( [begin[, end]] )\n    Creates a new typed array view over the same underlying `ArrayBuffer` and\n    with the same underlying data type as the host array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: BooleanArray\n        New typed array view.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true, false, true ] )\n    <BooleanArray>\n    > var out = arr.subarray( 1, 3 )\n    <BooleanArray>\n    > var len = out.length\n    2\n    > var v = out.get( 0 )\n    false\n    > v = out.get( 1 )\n    true","BooleanArray.prototype.toLocaleString":"\nBooleanArray.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array (optional)\n        Locale identifier(s).\n    \n    options: Object (optional)\n        An object containing serialization options.\n    \n    Returns\n    -------\n    str: string\n        Local-specific string.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var str = arr.toLocaleString()\n    'true,false,true'","BooleanArray.prototype.toReversed":"\nBooleanArray.prototype.toReversed()\n    Returns a new typed array containing the elements in reversed order.\n\n    Returns\n    -------\n    out: BooleanArray\n        New typed array.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, false ] )\n    <BooleanArray>\n    > var out = arr.toReversed()\n    <BooleanArray>\n    > var v = out.get( 0 )\n    false\n    > v = out.get( 1 )\n    false\n    > v = out.get( 2 )\n    true","BooleanArray.prototype.toSorted":"\nBooleanArray.prototype.toSorted( [compareFunction] )\n    Returns a new typed array containing the elements in sorted order.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first boolean value for comparison.\n    - b: second boolean value for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Comparison function.\n\n    Returns\n    -------\n    out: BooleanArray\n        New typed array.\n\n    Examples\n    --------\n    > function compare( a, b ) { return a === true ? -1 : 1; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.toSorted( compare );\n    > var v = out.get( 0 )\n    true\n    > v = out.get( 1 )\n    true\n    > v = out.get( 2 )\n    false","BooleanArray.prototype.toString":"\nBooleanArray.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    out: string\n        String serialization of the array.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var str = arr.toString()\n    'true,false,true'","BooleanArray.prototype.values":"\nBooleanArray.prototype.values()\n    Returns an iterator for iterating over each value in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array values.\n    \n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false ] )\n    <BooleanArray>\n    > var it = arr.values();\n    > var v = it.next().value\n    true\n    > v = it.next().value\n    false\n    > var bool = it.next().done\n    true","BooleanArray.prototype.with":"\nBooleanArray.prototype.with( index, value )\n    Returns a new typed array with the element at a provided index replaced\n    with a provided value.\n\n    Parameters\n    ----------\n    index: integer\n        Element index.\n    \n    value: boolean\n        Element value.  \n\n    Returns\n    -------\n    out: BooleanArray\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.with( 0, false )\n    <BooleanArray>\n    > var v = out.get( 0 )\n    false\n\n\n    See Also\n    --------\n    ArrayBuffer","broadcastArray":"\nbroadcastArray( x, shape )\n    Broadcasts an ndarray to a specified shape.\n\n    The returned array is a read-only view on the input array data buffer. The\n    view is typically *not* contiguous. As more than one element of a returned\n    view may refer to the same memory location, writing to the input array may\n    affect multiple elements. If you need to write to the input array, copy the\n    input array before broadcasting.\n\n    The function throws an error if a provided ndarray is incompatible with a\n    provided shape.\n\n    The function always returns a new ndarray instance even if the input ndarray\n    shape and the desired shape are the same.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    shape: ArrayLikeObject\n        Desired shape.\n\n    Returns\n    -------\n    out: ndarray\n        Broadcasted array.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n    <ndarray>\n    > var sh = x.shape\n    [ 2, 2 ]\n    > var y = broadcastArray( x, [ 3, 2, 2 ] )\n    <ndarray>\n    > sh = y.shape\n    [ 3, 2, 2 ]\n    > var v = y.get( 0, 0, 0 )\n    1\n    > v = y.get( 0, 0, 1 )\n    2\n    > v = y.get( 0, 1, 0 )\n    3\n    > v = y.get( 0, 1, 1 )\n    4\n    > v = y.get( 1, 0, 0 )\n    1\n    > v = y.get( 1, 1, 0 )\n    3\n    > v = y.get( 2, 0, 0 )\n    1\n    > v = y.get( 2, 1, 1 )\n    4\n\n    See Also\n    --------\n    array, broadcastArrays, ndarray, maybeBroadcastArray\n","broadcastArrays":"\nbroadcastArrays( ...arrays )\n    Broadcasts ndarrays to a common shape.\n\n    The function supports two (mutually exclusive) means of providing ndarray\n    arguments:\n\n    1. Providing a single array containing ndarray arguments.\n    2. Providing ndarray arguments as separate arguments.\n\n    The returned arrays are read-only views on their respective underlying\n    array data buffers. The views are typically **not** contiguous. As more\n    than one element of a returned view may refer to the same memory location,\n    writing to a view may affect multiple elements. If you need to write to an\n    input array, copy the array before broadcasting.\n\n    The function throws an error if provided broadcast-incompatible ndarrays.\n\n    The function always returns new ndarray instances even if an input ndarray\n    and the broadcasted shape are the same.\n\n    Parameters\n    ----------\n    arrays: ...ndarray|ArrayLikeObject<ndarray>\n        Array arguments.\n\n    Returns\n    -------\n    out: Array<ndarray>\n        Broadcasted arrays.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n    <ndarray>\n    > var sh = x.shape\n    [ 2, 2 ]\n    > var y = ndzeros( [ 3, 2, 2 ] )\n    <ndarray>\n    > var out = broadcastArrays( [ x, y ] )\n    [ <ndarray>, <ndarray> ]\n\n    // Retrieve the broadcasted \"x\" array:\n    > var bx = out[ 0 ]\n    <ndarray>\n    > sh = bx.shape\n    [ 3, 2, 2 ]\n\n    // Retrieve broadcasted elements...\n    > var v = bx.get( 0, 0, 0 )\n    1\n    > v = bx.get( 0, 0, 1 )\n    2\n    > v = bx.get( 0, 1, 0 )\n    3\n    > v = bx.get( 0, 1, 1 )\n    4\n    > v = bx.get( 1, 0, 0 )\n    1\n    > v = bx.get( 1, 1, 0 )\n    3\n    > v = bx.get( 2, 0, 0 )\n    1\n    > v = bx.get( 2, 1, 1 )\n    4\n\n    See Also\n    --------\n    array, broadcastArray, ndarray, maybeBroadcastArrays\n","Buffer":"\nBuffer\n    Buffer constructor.\n\n\nBuffer( size )\n    Allocates a buffer having a specified number of bytes.\n\n    Parameters\n    ----------\n    size: integer\n        Number of bytes to allocate.\n\n    Returns\n    -------\n    out: Buffer\n        Buffer instance.\n\n    Examples\n    --------\n    > var b = new Buffer( 4 )\n    <Buffer>\n\n\nBuffer( buffer )\n    Copies buffer data to a new Buffer instance.\n\n    Parameters\n    ----------\n    buffer: Buffer\n        Buffer to copy from.\n\n    Returns\n    -------\n    out: Buffer\n        Buffer instance.\n\n    Examples\n    --------\n    > var b1 = new Buffer( [ 1, 2, 3, 4 ] );\n    > var b2 = new Buffer( b1 )\n    <Buffer>[ 1, 2, 3, 4 ]\n\n\nBuffer( array )\n    Allocates a buffer using an array of octets.\n\n    Parameters\n    ----------\n    array: Array\n        Array of octets.\n\n    Returns\n    -------\n    out: Buffer\n        Buffer instance.\n\n    Examples\n    --------\n    > var b = new Buffer( [ 1, 2, 3, 4 ] )\n    <Buffer>[ 1, 2, 3, 4 ]\n\n\nBuffer( str[, encoding] )\n    Allocates a buffer containing a provided string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    encoding: string (optional)\n        Character encoding. Default: 'utf8'.\n\n    Returns\n    -------\n    out: Buffer\n        Buffer instance.\n\n    Examples\n    --------\n    > var b = new Buffer( 'beep boop' )\n    <Buffer>\n\n\nTODO: add methods and properties\n\n\n    See Also\n    --------\n    ArrayBuffer\n","buffer2json":"\nbuffer2json( buffer )\n    Returns a JSON representation of a buffer.\n\n    Parameters\n    ----------\n    buffer: Buffer\n        Buffer to serialize.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    out.type: string\n        Value type. The assigned value is always \"Buffer\".\n\n    out.data: Array\n        Buffer data.\n\n    Examples\n    --------\n    > var buf = new allocUnsafe( 2 );\n    > buf[ 0 ] = 1;\n    > buf[ 1 ] = 2;\n    > var json = buffer2json( buf )\n    { 'type': 'Buffer', 'data': [ 1, 2 ] }\n\n    See Also\n    --------\n    typedarray2json, reviveBuffer\n","BYTE_ORDER":"\nBYTE_ORDER\n    Platform byte order.\n\n    Possible values:\n\n    - 'little-endian'\n    - 'big-endian'\n    - 'mixed-endian'\n    - 'unknown'\n\n    Examples\n    --------\n    > BYTE_ORDER\n    <string>\n\n    See Also\n    --------\n    IS_BIG_ENDIAN, IS_LITTLE_ENDIAN\n","camelcase":"\ncamelcase( str )\n    Converts a string to camel case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Camel-cased string.\n\n    Examples\n    --------\n    > var out = camelcase( 'Hello World!' )\n    'helloWorld'\n    > out = camelcase( 'beep boop' )\n    'beepBoop'\n\n    See Also\n    --------\n    constantcase, kebabcase, pascalcase, snakecase","capitalize":"\ncapitalize( str )\n    Capitalizes the first character in a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Capitalized string.\n\n    Examples\n    --------\n    > var out = capitalize( 'beep' )\n    'Beep'\n    > out = capitalize( 'Boop' )\n    'Boop'\n\n    See Also\n    --------\n    uncapitalize, uppercase\n","capitalizeKeys":"\ncapitalizeKeys( obj )\n    Converts the first letter of each object key to uppercase.\n\n    The function only transforms own properties. Hence, the function does not\n    transform inherited properties.\n\n    The function shallow copies key values.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > var obj = { 'aa': 1, 'bb': 2 };\n    > var out = capitalizeKeys( obj )\n    { 'Aa': 1, 'Bb': 2 }\n\n    See Also\n    --------\n    uncapitalizeKeys, uppercaseKeys\n","CATALAN":"\nCATALAN\n    Catalan's constant.\n\n    Examples\n    --------\n    > CATALAN\n    0.915965594177219\n\n","CBRT_EPS":"\nCBRT_EPS\n    Cube root of double-precision floating-point epsilon.\n\n    Examples\n    --------\n    > CBRT_EPS\n    0.0000060554544523933395\n\n    See Also\n    --------\n    EPS, SQRT_EPS\n","CDC_NCHS_US_BIRTHS_1969_1988":"\nCDC_NCHS_US_BIRTHS_1969_1988()\n    Returns US birth data from 1969 to 1988, as provided by the Center for\n    Disease Control and Prevention's National Center for Health Statistics.\n\n    Returns\n    -------\n    out: Array<Object>\n        Birth data.\n\n    Examples\n    --------\n    > var data = CDC_NCHS_US_BIRTHS_1969_1988()\n    [ {...}, ... ]\n\n    See Also\n    --------\n    CDC_NCHS_US_BIRTHS_1994_2003, SSA_US_BIRTHS_2000_2014\n","CDC_NCHS_US_BIRTHS_1994_2003":"\nCDC_NCHS_US_BIRTHS_1994_2003()\n    Returns US birth data from 1994 to 2003, as provided by the Center for\n    Disease Control and Prevention's National Center for Health Statistics.\n\n    Returns\n    -------\n    out: Array<Object>\n        Birth data.\n\n    Examples\n    --------\n    > var data = CDC_NCHS_US_BIRTHS_1994_2003()\n    [ {...}, ... ]\n\n    See Also\n    --------\n    CDC_NCHS_US_BIRTHS_1969_1988, SSA_US_BIRTHS_2000_2014\n","CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013":"\nCDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n    Returns US infant mortality data, by race, from 1915 to 2013, as provided by\n    the Center for Disease Control and Prevention's National Center for Health\n    Statistics.\n\n    All birth data by race before 1980 are based on race of the child. Starting\n    in 1980, birth data by race are based on race of the mother. Birth data are\n    used to calculate infant mortality rate.\n\n    Returns\n    -------\n    out: Array<Object>\n        Infant mortality data.\n\n    Examples\n    --------\n    > var data = CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n    { 'black': [...], 'white': [...] }\n\n","chdir":"\nchdir( path )\n    Changes the current working directory.\n\n    If unable to set the current working directory (e.g., due to a non-existent\n    path), the function returns an error; otherwise, the function returns\n    `null`.\n\n    Parameters\n    ----------\n    path: string\n        Desired working directory.\n\n    Returns\n    -------\n    err: Error|null\n        Error object or null.\n\n    Examples\n    --------\n    > var err = chdir( '/path/to/current/working/directory' )\n\n    See Also\n    --------\n    cwd\n","chi2gof":"\nchi2gof( x, y[, ...args][, options] )\n    Performs a chi-square goodness-of-fit test.\n\n    A chi-square goodness-of-fit test is computed for the null hypothesis that\n    the values of `x` come from the discrete probability distribution specified\n    by `y`.\n\n    The second argument can either be expected frequencies, population\n    probabilities summing to one, or a discrete probability distribution name to\n    test against.\n\n    When providing a discrete probability distribution name, distribution\n    parameters *must* be supplied as additional arguments.\n\n    The function returns an object containing the test statistic, p-value, and\n    decision.\n\n    By default, the p-value is computed using a chi-square distribution with\n    `k-1` degrees of freedom, where `k` is the length of `x`.\n\n    If provided distribution arguments are estimated (e.g., via maximum\n    likelihood estimation), the degrees of freedom should be corrected. Set the\n    `ddof` option to use `k-1-n` degrees of freedom, where `n` is the degrees of\n    freedom adjustment.\n\n    The chi-square approximation may be incorrect if the observed or expected\n    frequencies in each category are too small. Common practice is to require\n    frequencies greater than five.\n\n    Instead of relying on chi-square approximation to calculate the p-value, one\n    can use Monte Carlo simulation. When the `simulate` option is `true`, the\n    simulation is performed by re-sampling from the discrete probability\n    distribution specified by `y`.\n\n    Parameters\n    ----------\n    x: ndarray|Array<number>|TypedArray\n        Observation frequencies.\n\n    y: ndarray|Array<number>|TypedArray|string\n        Expected frequencies, population probabilities, or a discrete\n        probability distribution name.\n\n    args: ...number (optional)\n        Distribution parameters. Distribution parameters will be passed to a\n        probability mass function (PMF) as arguments.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Significance level of the hypothesis test. Must be on the interval\n        [0,1]. Default: 0.05.\n\n    options.ddof: number (optional)\n        Delta degrees of freedom adjustment. Default: 0.\n\n    options.simulate: boolean (optional)\n        Boolean indicating whether to calculate p-values by Monte Carlo\n        simulation. The simulation is performed by re-sampling from the discrete\n        distribution specified by `y`. Default: false.\n\n    options.iterations: number (optional)\n        Number of Monte Carlo iterations. Default: 500.\n\n    Returns\n    -------\n    out: Object\n        Test results object.\n\n    out.alpha: number\n        Significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        Test p-value.\n\n    out.statistic: number\n        Test statistic.\n\n    out.df: number|null\n        Degrees of freedom.\n\n    out.method: string\n        Test name.\n\n    out.toString: Function\n        Serializes results as formatted output.\n\n    out.toJSON: Function\n        Serializes results as JSON.\n\n    Examples\n    --------\n    // Provide expected probabilities...\n    > var x = [ 89, 37, 30, 28, 2 ];\n    > var p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\n    > var out = chi2gof( x, p );\n    > var o = out.toJSON()\n    { 'pValue': ~0.0406, 'statistic': ~9.9901, ... }\n    > out.toString()\n\n    // Set significance level...\n    > var opts = { 'alpha': 0.01 };\n    > out = chi2gof( x, p, opts );\n    > out.toString()\n\n    // Calculate the test p-value via Monte Carlo simulation...\n    > x = [ 89, 37, 30, 28, 2 ];\n    > p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\n    > opts = { 'simulate': true, 'iterations': 1000 };\n    > out = chi2gof( x, p, opts );\n    > out.toString()\n\n    // Verify that data comes from Poisson distribution...\n    > var lambda = 3.0;\n    > var rpois = base.random.poisson.factory( lambda );\n    > var len = 400;\n    > x = [];\n    > for ( var i = 0; i < len; i++ ) { x.push( rpois() ); };\n\n    // Generate a frequency table...\n    > var freqs = new Int32Array( len );\n    > for ( i = 0; i < len; i++ ) { freqs[ x[ i ] ] += 1; };\n    > out = chi2gof( freqs, 'poisson', lambda );\n    > out.toString()\n\n","chi2test":"\nchi2test( x[, options] )\n    Performs a chi-square independence test.\n\n    For a two-way contingency table, the function computes a chi-square\n    independence test for the null hypothesis that the joint distribution of the\n    cell counts is the product of the row and column marginals (i.e. that the\n    row and column variables are independent).\n\n    The chi-square approximation may be incorrect if the observed or expected\n    frequencies in each category are too small. Common practice is to require\n    frequencies greater than five. The Yates' continuity correction is enabled\n    by default for 2x2 tables to account for this, although it tends to\n    over-correct.\n\n    The function returns an object containing the test statistic, p-value, and\n    decision.\n\n    Parameters\n    ----------\n    x: ndarray|Array<Collection<number>>\n        Two-way table of observed frequencies.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Significance level of the hypothesis test. Must be on the interval\n        [0,1]. Default: 0.05.\n\n    options.correct: boolean (optional)\n        Boolean indicating whether to use Yates' continuity correction when\n        provided a 2x2 contingency table. Default: true.\n\n    Returns\n    -------\n    out: Object\n        Test results object.\n\n    out.alpha: number\n        Significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        Test p-value.\n\n    out.statistic: number\n        Test statistic.\n\n    out.df: number\n        Degrees of freedom.\n\n    out.expected: ndarray\n        Expected frequencies.\n\n    out.method: string\n        Test name.\n\n    out.toString: Function\n        Serializes results as formatted output.\n\n    out.toJSON: Function\n        Serializes results as JSON.\n\n    Examples\n    --------\n    > var x = [ [ 20, 30 ], [ 30, 20 ] ];\n    > var out = chi2test( x );\n    > var o = out.toJSON()\n    { 'rejected': false, 'pValue': ~0.072, 'statistic': 3.24, ... }\n    > out.toString()\n\n    // Set significance level...\n    > var opts = { 'alpha': 0.1 };\n    > out = chi2test( x, opts );\n    > o = out.toJSON()\n    { 'rejected': true, 'pValue': ~0.072, 'statistic': 3.24, ... }\n    > out.toString()\n\n    // Disable Yates' continuity correction (primarily used with small counts):\n    > opts = { 'correct': false };\n    > out = chi2test( x, opts );\n    > out.toString()\n\n","circarray2iterator":"\ncircarray2iterator( src[, options][, mapFcn[, thisArg]] )\n    Returns an iterator which repeatedly iterates over the elements of an array-\n    like object.\n\n    When invoked, an input function is provided four arguments:\n\n    - value: iterated value.\n    - index: iterated value index.\n    - n: iteration count.\n    - src: source array-like object.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an array's `@@iterator` method, regardless of whether this method is\n    defined. To convert an array to an implementation defined iterator, invoke\n    this method directly.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Array-like object from which to create the iterator.\n\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    options.dir: integer (optional)\n        Iteration direction. If set to `-1`, an iterator iterates over elements\n        from right-to-left. Default: 1.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = circarray2iterator( [ 1, 2, 3, 4 ] );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    array2iterator, stridedarray2iterator\n","circularArrayStream":"\ncircularArrayStream( src[, options] )\n    Creates a readable stream from an array-like object which repeatedly\n    iterates over the provided value's elements.\n\n    In object mode, `null` is a reserved value. If an array contains `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or filter `null` values\n    prior to invocation.\n\n    In binary mode, if an array contains `undefined` values, the stream will\n    emit an error. Consider providing a custom serialization function or\n    filtering `undefined` values prior to invocation.\n\n    If a serialization function fails to return a string or Buffer, the stream\n    emits an error.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Source value.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing the stream.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize streamed\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    options.dir: integer (optional)\n        Iteration direction. If set to `-1`, a stream iterates over elements\n        from right-to-left. Default: 1.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 15 };\n    > var s = circularArrayStream( [ 1, 2, 3 ], opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\ncircularArrayStream.factory( [options] )\n    Returns a function for creating readable streams from array-like objects\n    which repeatedly iterate over the elements of provided values.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing streaming.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize streamed\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    options.dir: integer (optional)\n        Iteration direction. If set to `-1`, a stream iterates over elements\n        from right-to-left. Default: 1.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = circularArrayStream.factory( opts );\n\n\ncircularArrayStream.objectMode( src[, options] )\n    Returns an \"objectMode\" readable stream from an array-like object which\n    repeatedly iterates over a provided value's elements.\n\n    In object mode, `null` is a reserved value. If an array contains `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or filter `null` values\n    prior to invocation.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Source value.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before pausing streaming.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    options.dir: integer (optional)\n        Iteration direction. If set to `-1`, a stream iterates over elements\n        from right-to-left. Default: 1.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 15 };\n    > var s = circularArrayStream.objectMode( [ 1, 2, 3 ], opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    arrayStream, iteratorStream, stridedArrayStream\n","circularArrayStream.factory":"\ncircularArrayStream.factory( [options] )\n    Returns a function for creating readable streams from array-like objects\n    which repeatedly iterate over the elements of provided values.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing streaming.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize streamed\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    options.dir: integer (optional)\n        Iteration direction. If set to `-1`, a stream iterates over elements\n        from right-to-left. Default: 1.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = circularArrayStream.factory( opts );","circularArrayStream.objectMode":"\ncircularArrayStream.objectMode( src[, options] )\n    Returns an \"objectMode\" readable stream from an array-like object which\n    repeatedly iterates over a provided value's elements.\n\n    In object mode, `null` is a reserved value. If an array contains `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or filter `null` values\n    prior to invocation.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Source value.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before pausing streaming.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    options.dir: integer (optional)\n        Iteration direction. If set to `-1`, a stream iterates over elements\n        from right-to-left. Default: 1.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 15 };\n    > var s = circularArrayStream.objectMode( [ 1, 2, 3 ], opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    arrayStream, iteratorStream, stridedArrayStream","CircularBuffer":"\nCircularBuffer( buffer )\n    Circular buffer constructor.\n\n    Parameters\n    ----------\n    buffer: integer|ArrayLike\n        Buffer size or an array-like object to use as the underlying buffer.\n\n    Returns\n    -------\n    buf: Object\n        Circular buffer data structure.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.push( 'foo' );\n    > b.push( 'bar' );\n    > b.push( 'beep' );\n    > b.length\n    3\n    > b.count\n    3\n    > b.push( 'boop' )\n    'foo'\n\n\nCircularBuffer.prototype.clear()\n    Clears a buffer.\n\n    Returns\n    -------\n    out: Object\n        Circular buffer instance.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.push( 'foo' );\n    > b.push( 'bar' );\n    > b.push( 'beep' );\n    > b.count\n    3\n    > b.clear();\n    > b.count\n    0\n\n\nCircularBuffer.prototype.count\n    Read-only property returning the number of elements currently in the buffer.\n\n    Returns\n    -------\n    out: integer\n        Number of elements currently in the buffer.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.count\n    0\n    > b.push( 'foo' );\n    > b.count\n    1\n    > b.push( 'bar' );\n    > b.count\n    2\n\n\nCircularBuffer.prototype.full\n    Read-only property returning a boolean indicating whether a circular buffer\n    is full.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether a circular buffer is full.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.full\n    false\n    > b.push( 'foo' );\n    > b.push( 'bar' );\n    > b.push( 'beep' );\n    > b.full\n    true\n\n\nCircularBuffer.prototype.iterator( [niters] )\n    Returns an iterator for iterating over a circular buffer.\n\n    A returned iterator does not iterate over partially full buffers.\n\n    Parameters\n    ----------\n    niters: integer (optional)\n        Number of iterations. Default: infinity.\n\n    Returns\n    -------\n    out: Iterator\n        Iterator.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.push( 'foo' );\n    > b.push( 'bar' );\n    > b.push( 'beep' );\n    > b.push( 'boop' );\n    > var it = b.iterator( b.length );\n    > var v = it.next().value\n    'bar'\n    > v = it.next().value\n    'beep'\n    > v = it.next().value\n    'boop'\n    > var bool = it.next().done\n    true\n\n\nCircularBuffer.prototype.length\n    Read-only property returning the buffer length (i.e., capacity).\n\n    Returns\n    -------\n    out: integer\n        Buffer length.\n\n    Examples\n    --------\n    > var b = CircularBuffer( [ 0, 0, 0 ] );\n    > var len = b.length\n    3\n\n\nCircularBuffer.prototype.push( value )\n    Adds a value to a circular buffer.\n\n    Parameters\n    ----------\n    value: any\n        Value to add.\n\n    Returns\n    -------\n    out: any\n        Removed element (or undefined).\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.push( 'foo' )\n    undefined\n    > b.push( 'bar' )\n    undefined\n    > b.push( 'beep' )\n    undefined\n    > b.push( 'boop' )\n    'foo'\n\n\nCircularBuffer.prototype.toArray()\n    Returns an array of circular buffer values.\n\n    Returns\n    -------\n    out: Array\n        Circular buffer values.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.push( 'foo' );\n    > b.push( 'bar' );\n    > b.push( 'beep' );\n    > b.push( 'boop' );\n    > var vals = b.toArray()\n    [ 'bar', 'beep', 'boop' ]\n\n\nCircularBuffer.prototype.toJSON()\n    Serializes a circular buffer as JSON.\n\n    Returns\n    -------\n    out: Object\n        Serialized circular buffer.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.push( 'foo' );\n    > b.push( 'bar' );\n    > b.push( 'beep' );\n    > b.push( 'boop' );\n    > var o = b.toJSON()\n    {'type':'circular-buffer','length':3,'data':['bar','beep','boop']}\n\n    See Also\n    --------\n    FIFO, Stack\n","CircularBuffer.prototype.clear":"\nCircularBuffer.prototype.clear()\n    Clears a buffer.\n\n    Returns\n    -------\n    out: Object\n        Circular buffer instance.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.push( 'foo' );\n    > b.push( 'bar' );\n    > b.push( 'beep' );\n    > b.count\n    3\n    > b.clear();\n    > b.count\n    0","CircularBuffer.prototype.count":"\nCircularBuffer.prototype.count\n    Read-only property returning the number of elements currently in the buffer.\n\n    Returns\n    -------\n    out: integer\n        Number of elements currently in the buffer.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.count\n    0\n    > b.push( 'foo' );\n    > b.count\n    1\n    > b.push( 'bar' );\n    > b.count\n    2","CircularBuffer.prototype.full":"\nCircularBuffer.prototype.full\n    Read-only property returning a boolean indicating whether a circular buffer\n    is full.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether a circular buffer is full.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.full\n    false\n    > b.push( 'foo' );\n    > b.push( 'bar' );\n    > b.push( 'beep' );\n    > b.full\n    true","CircularBuffer.prototype.iterator":"\nCircularBuffer.prototype.iterator( [niters] )\n    Returns an iterator for iterating over a circular buffer.\n\n    A returned iterator does not iterate over partially full buffers.\n\n    Parameters\n    ----------\n    niters: integer (optional)\n        Number of iterations. Default: infinity.\n\n    Returns\n    -------\n    out: Iterator\n        Iterator.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.push( 'foo' );\n    > b.push( 'bar' );\n    > b.push( 'beep' );\n    > b.push( 'boop' );\n    > var it = b.iterator( b.length );\n    > var v = it.next().value\n    'bar'\n    > v = it.next().value\n    'beep'\n    > v = it.next().value\n    'boop'\n    > var bool = it.next().done\n    true","CircularBuffer.prototype.length":"\nCircularBuffer.prototype.length\n    Read-only property returning the buffer length (i.e., capacity).\n\n    Returns\n    -------\n    out: integer\n        Buffer length.\n\n    Examples\n    --------\n    > var b = CircularBuffer( [ 0, 0, 0 ] );\n    > var len = b.length\n    3","CircularBuffer.prototype.push":"\nCircularBuffer.prototype.push( value )\n    Adds a value to a circular buffer.\n\n    Parameters\n    ----------\n    value: any\n        Value to add.\n\n    Returns\n    -------\n    out: any\n        Removed element (or undefined).\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.push( 'foo' )\n    undefined\n    > b.push( 'bar' )\n    undefined\n    > b.push( 'beep' )\n    undefined\n    > b.push( 'boop' )\n    'foo'","CircularBuffer.prototype.toArray":"\nCircularBuffer.prototype.toArray()\n    Returns an array of circular buffer values.\n\n    Returns\n    -------\n    out: Array\n        Circular buffer values.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.push( 'foo' );\n    > b.push( 'bar' );\n    > b.push( 'beep' );\n    > b.push( 'boop' );\n    > var vals = b.toArray()\n    [ 'bar', 'beep', 'boop' ]","CircularBuffer.prototype.toJSON":"\nCircularBuffer.prototype.toJSON()\n    Serializes a circular buffer as JSON.\n\n    Returns\n    -------\n    out: Object\n        Serialized circular buffer.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.push( 'foo' );\n    > b.push( 'bar' );\n    > b.push( 'beep' );\n    > b.push( 'boop' );\n    > var o = b.toJSON()\n    {'type':'circular-buffer','length':3,'data':['bar','beep','boop']}\n\n    See Also\n    --------\n    FIFO, Stack","close":"\nclose( fd, clbk )\n    Asynchronously closes a file descriptor, so that the file descriptor no\n    longer refers to any file and may be reused.\n\n    Parameters\n    ----------\n    fd: integer\n        File descriptor.\n\n    clbk: Function\n        Callback to invoke upon closing a file descriptor.\n\n    Examples\n    --------\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     }\n    ... };\n    > var fd = open.sync( './beep/boop.js', 'r+' );\n    > if ( !isError( fd ) ) { close( fd, done ); };\n\n\nclose.sync( fd )\n    Synchronously closes a file descriptor.\n\n    Parameters\n    ----------\n    fd: integer\n        File descriptor.\n\n    Returns\n    -------\n    out: Error|void\n        If an error occurs, an error object; otherwise, undefined.\n\n    Examples\n    --------\n    > var fd = open.sync( './beep/boop.js', 'r+' );\n    > if ( !isError( fd ) ) { close.sync( fd ); };\n\n    See Also\n    --------\n    exists, open, readFile\n","close.sync":"\nclose.sync( fd )\n    Synchronously closes a file descriptor.\n\n    Parameters\n    ----------\n    fd: integer\n        File descriptor.\n\n    Returns\n    -------\n    out: Error|void\n        If an error occurs, an error object; otherwise, undefined.\n\n    Examples\n    --------\n    > var fd = open.sync( './beep/boop.js', 'r+' );\n    > if ( !isError( fd ) ) { close.sync( fd ); };\n\n    See Also\n    --------\n    exists, open, readFile","CMUDICT":"\nCMUDICT( [options] )\n    Returns datasets from the Carnegie Mellon Pronouncing Dictionary (CMUdict).\n\n    Data includes the following:\n\n    - dict: the main pronouncing dictionary.\n    - phones: manners of articulation for each sound.\n    - symbols: complete list of ARPABET symbols used by the dictionary.\n    - vp: verbal pronunciations of punctuation marks.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.data: string (optional)\n        Dataset name.\n\n    Returns\n    -------\n    out: Object|Array\n        CMUdict dataset.\n\n    Examples\n    --------\n    > var data = CMUDICT();\n    > var dict = data.dict\n    {...}\n    > var phones = data.phones\n    {...}\n    > var symbols = data.symbols\n    [...]\n    > var vp = data.vp\n    {...}\n\n","codePointAt":"\ncodePointAt( str, idx[, backward] )\n    Returns a Unicode code point from a string at a specified position.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    idx: integer\n        Position. If less than `0`, the string position is determined relative\n        to the end of the input string.\n\n    backward: boolean (optional)\n        Backward iteration for low surrogates. Default: false.\n\n    Returns\n    -------\n    out: integer\n        Unicode code point.\n\n    Examples\n    --------\n    > var out = codePointAt( 'last man standing', 4 )\n    32\n    > out = codePointAt( 'presidential election', 8, true )\n    116\n    > out = codePointAt( 'अनुच्छेद', 2 )\n    2369\n    > out = codePointAt( '🌷', 1, true )\n    127799\n\n    See Also\n    --------\n    fromCodePoint","commonKeys":"\ncommonKeys( obj1, obj2[, ...obj] )\n    Returns the common own property names of two or more objects.\n\n    Parameters\n    ----------\n    obj1: any\n        First object.\n\n    obj2: any\n        Second object.\n\n    obj: ...any (optional)\n        Additional objects.\n\n    Returns\n    -------\n    out: Array<string>\n        Common keys of objects.\n\n    Examples\n    --------\n    > var obj1 = { 'a': 1, 'b': 2 };\n    > var obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\n    > var keys = commonKeys( obj1, obj2 )\n    [ 'a', 'b' ]\n\n    See Also\n    --------\n    commonKeysIn, objectKeys","commonKeysIn":"\ncommonKeysIn( obj1, obj2[, ...obj] )\n    Returns the common own and inherited property names of two or more objects.\n\n    Parameters\n    ----------\n    obj1: any\n        First object.\n\n    obj2: any\n        Second object.\n\n    obj: ...any (optional)\n        Additional objects.\n\n    Returns\n    -------\n    out: Array<string>\n        Common keys.\n\n    Examples\n    --------\n    > var obj1 = { 'a': 1, 'b': 2 };\n    > var obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\n    > var keys = commonKeysIn( obj1, obj2 )\n    [ 'a', 'b' ]\n\n    See Also\n    --------\n    commonKeys, keysIn","complex":"\ncomplex( real, imag[, dtype] )\n    Creates a complex number.\n\n    The function supports the following data types:\n\n    - float64\n    - float32\n\n    Parameters\n    ----------\n    real: number\n        Real component.\n\n    imag: number\n        Imaginary component.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    z: Complex\n        Complex number.\n\n    Examples\n    --------\n    > var z = complex( 5.0, 3.0, 'float64' )\n    <Complex128>\n    > z = complex( 5.0, 3.0, 'float32' )\n    <Complex64>\n\n    See Also\n    --------\n    Complex128, Complex64\n","Complex64":"\nComplex64( real, imag )\n    64-bit complex number constructor.\n\n    Both the real and imaginary components are stored as single-precision\n    floating-point numbers.\n\n    Parameters\n    ----------\n    real: number\n        Real component.\n\n    imag: number\n        Imaginary component.\n\n    Returns\n    -------\n    z: Complex64\n        64-bit complex number.\n\n    z.re: number\n        Read-only property returning the real component.\n\n    z.im: number\n        Read-only property returning the imaginary component.\n\n    Examples\n    --------\n    > var z = new Complex64( 5.0, 3.0 )\n    <Complex64>\n    > z.re\n    5.0\n    > z.im\n    3.0\n\n\nComplex64.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n\n    Returns\n    -------\n    v: integer\n        Size (in bytes) of each component.\n\n    Examples\n    --------\n    > var s = Complex64.BYTES_PER_ELEMENT\n    4\n\n\nComplex64.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n\n    Returns\n    -------\n    s: integer\n        Size (in bytes) of each component.\n\n    Examples\n    --------\n    > var z = new Complex64( 5.0, 3.0 )\n    <Complex64>\n    > var s = z.BYTES_PER_ELEMENT\n    4\n\n\nComplex64.prototype.byteLength\n    Length (in bytes) of a complex number.\n\n    Returns\n    -------\n    len: integer\n        Length (in bytes) of a complex number.\n\n    Examples\n    --------\n    > var z = new Complex64( 5.0, 3.0 )\n    <Complex64>\n    > var s = z.byteLength\n    8\n\n    See Also\n    --------\n    complex, Complex128\n","Complex64.BYTES_PER_ELEMENT":"\nComplex64.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n\n    Returns\n    -------\n    v: integer\n        Size (in bytes) of each component.\n\n    Examples\n    --------\n    > var s = Complex64.BYTES_PER_ELEMENT\n    4","Complex64.prototype.BYTES_PER_ELEMENT":"\nComplex64.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n\n    Returns\n    -------\n    s: integer\n        Size (in bytes) of each component.\n\n    Examples\n    --------\n    > var z = new Complex64( 5.0, 3.0 )\n    <Complex64>\n    > var s = z.BYTES_PER_ELEMENT\n    4","Complex64.prototype.byteLength":"\nComplex64.prototype.byteLength\n    Length (in bytes) of a complex number.\n\n    Returns\n    -------\n    len: integer\n        Length (in bytes) of a complex number.\n\n    Examples\n    --------\n    > var z = new Complex64( 5.0, 3.0 )\n    <Complex64>\n    > var s = z.byteLength\n    8\n\n    See Also\n    --------\n    complex, Complex128","COMPLEX64_NAN":"\nCOMPLEX64_NAN\n    Canonical single-precision complex floating-point NaN.\n\n    Examples\n    --------\n    > COMPLEX64_NAN\n    <Complex64>\n\n    See Also\n    --------\n    COMPLEX128_NAN\n","COMPLEX64_NUM_BYTES":"\nCOMPLEX64_NUM_BYTES\n    Size (in bytes) of a 64-bit complex number.\n\n    Examples\n    --------\n    > COMPLEX64_NUM_BYTES\n    8\n\n    See Also\n    --------\n    COMPLEX128_NUM_BYTES, FLOAT32_NUM_BYTES\n","COMPLEX64_ZERO":"\nCOMPLEX64_ZERO\n    Single-precision complex floating-point zero.\n\n    Examples\n    --------\n    > COMPLEX64_ZERO\n    <Complex64>\n\n    See Also\n    --------\n    COMPLEX128_ZERO\n","Complex64Array":"\nComplex64Array()\n    A 64-bit complex number array.\n\n    Returns\n    -------\n    out: Complex64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Complex64Array()\n    <Complex64Array>\n\n\nComplex64Array( length )\n    Creates a 64-bit complex number array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: Complex64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 10 )\n    <Complex64Array>\n    > var len = arr.length\n    10\n\n\nComplex64Array( complexarray )\n    Creates a 64-bit complex number array from another complex number array.\n\n    Parameters\n    ----------\n    complexarray: Complex64Array\n        Complex array from which to generate another complex array.\n\n    Returns\n    -------\n    out: Complex64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var arr2 = new Complex64Array( arr1 )\n    <Complex64Array>\n    > var len = arr2.length\n    2\n\n\nComplex64Array( typedarray )\n    Creates a 64-bit complex number array from a typed array\n    containing interleaved real and imaginary components.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate complex array.\n\n    Returns\n    -------\n    out: Complex64Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new Float32Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Float32Array>\n    > var arr = new Complex64Array( buf )\n    <Complex64Array>\n    > var len = arr.length\n    2\n\n\nComplex64Array( obj )\n    Creates a 64-bit complex number array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a complex array.\n\n    Returns\n    -------\n    out: Complex64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var len = arr1.length\n    2\n    > var buf = [ new Complex64( 1.0, -1.0 ), new Complex64( 2.0, -2.0 )];\n    > var arr2 = new Complex64Array( buf )\n    <Complex64Array>\n    > len = arr2.length\n    2\n\n\nComplex64Array( buffer[, byteOffset[, length]] )\n    Returns a 64-bit complex number array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Complex64Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 240 );\n    > var arr1 = new Complex64Array( buf )\n    <Complex64Array>\n    > var len = arr1.length\n    30\n    > var arr2 = new Complex64Array( buf, 8 )\n    <Complex64Array>\n    > len = arr2.length\n    29\n    > var arr3 = new Complex64Array( buf, 8, 20 )\n    <Complex64Array>\n    > len = arr3.length\n    20\n\n\nComplex64Array.from( src[, clbk[, thisArg]] )\n    Creates a new 64-bit complex number array from an array-like object or an\n    iterable.\n\n    A callback function is provided two arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    clbk: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n    \n    Returns\n    -------\n    out: Complex64Array\n        A typed array.\n    \n    Examples\n    --------\n    > function clbkFcn( v ) { return v * 2.0 };\n    > var arr = Complex64Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\n    <Complex64Array>\n    > var len = arr.length\n    2\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    -2.0\n\n\nComplex64Array.of( element0[, element1[, ...elementN]] )\n    Creates a new 64-bit complex number array from a variable number of\n    arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Complex64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Complex64Array.of( 1.0, -1.0, 2.0, -2.0 )\n    <Complex64Array>\n    > var len = arr.length\n    2\n    > var z1 = new Complex64( 1.0, -1.0 );\n    > var z2 = new Complex64( 2.0, -2.0 );\n    > arr = Complex64Array.of( z1, z2 )\n    <Complex64Array>\n    > len = arr.length\n    2\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    -1.0\n\n\nComplex64Array.BYTES_PER_ELEMENT\n    The size of each array element in bytes.\n\n    Examples\n    --------\n    > var nbytes = Complex64Array.BYTES_PER_ELEMENT\n    8\n\n\nComplex64Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > var str = Complex64Array.name\n    'Complex64Array'\n\n\nComplex64Array.prototype.buffer\n    Pointer to the underlying data buffer.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 2 )\n    <Complex64Array>\n    > var buf = arr.buffer\n    <ArrayBuffer>\n\n\nComplex64Array.prototype.byteLength\n    Length of the array in bytes.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 10 )\n    <Complex64Array>\n    > var nbytes = arr.byteLength\n    80\n\n\nComplex64Array.prototype.byteOffset\n    Offset (in bytes) of the array from the start of its underlying\n    ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 5 )\n    <Complex64Array>\n    > var offset = arr.byteOffset\n    0\n    > var buf = new ArrayBuffer( 240 );\n    > arr = new Complex64Array( buf, 64 )\n    <Complex64Array>\n    > offset = arr.byteOffset\n    64\n\n\nComplex64Array.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 10 )\n    <Complex64Array>\n    > arr.BYTES_PER_ELEMENT\n    8\n\n\nComplex64Array.prototype.length\n    The number of array elements.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 10 )\n    <Complex64Array>\n    > var len = arr.length\n    10\n\n\nComplex64Array.prototype.at( i )\n    Returns an array element located at integer position (index) `i`, with\n    support for noth nonnegative and negative integer positions.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n\n    Returns\n    -------\n    out: Complex64|void\n        An array element.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var z = arr.at( 1 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    -2.0\n\n\nComplex64Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n    \n    start: integer\n        Source start index position.\n    \n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Complex64Array\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex64Array>\n    > arr.copyWithin( 0, 2 )\n    <Complex64Array>\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    -3.0\n\n\nComplex64Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var it = arr.entries();\n    > var v = it.next().value\n    [ 0, <Complex64> ]\n    > var re = realf( v[ 1 ] )\n    1.0\n    > var im = imagf( v[ 1 ] )\n    -1.0\n    > v = it.next().value\n    [ 1, <Complex64> ]\n    > re = realf( v[ 1 ] )\n    2.0\n    > im = imagf( v[ 1 ] )\n    -2.0\n    > v = it.next().value\n    [ 2, <Complex64> ]\n    > re = realf( v[ 1 ] )\n    3.0\n    > im = imagf( v[ 1 ] )\n    -3.0\n    > var bool = it.next().done\n    true\n\n\nComplex64Array.prototype.every( predicate[, thisArg] )\n    Returns a boolean indicating whether all elements in the array pass a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all elements pass the test.\n\n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) > 0.0 ); };\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var bool = arr.every( predicate )\n    true\n\n\nComplex64Array.prototype.fill( value[, start[, end]] )\n    Returns a modified typed array filled with a fill value.\n\n    Parameters\n    ----------\n    value: Complex64\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Complex64Array\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( 3 )\n    <Complex64Array>\n    > arr.fill( new Complex64( 1.0, 1.0 ) );\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    1.0\n    > z = arr.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    1.0\n    > im = imagf( z )\n    1.0\n    > z = arr.get( 2 )\n    <Complex64>\n    > re = realf( z )\n    1.0\n    > im = imagf( z )\n    1.0\n\n\nComplex64Array.prototype.filter( predicate[, thisArg] )\n    Returns a new array containing the elements of an array which pass a test\n    implemented by a predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Complex64Array\n        A new typed array.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var out = arr.filter( predicate )\n    <Complex64Array>\n    > var len = out.length\n    1\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    2.0\n\n\nComplex64Array.prototype.find( predicate[, thisArg] )\n    Returns the first element in an array for which a predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    out: Complex64|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var z = arr.find( predicate )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    1.0\n\n\nComplex64Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var idx = arr.findIndex( predicate )\n    0\n\n\nComplex64Array.prototype.findLast( predicate[, thisArg] )\n    Returns the last element in an array for which a predicate function returns\n    a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.  \n    \n    Returns\n    -------\n    out: Complex64|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var z = arr.findLast( predicate )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    2.0\n\n\nComplex64Array.prototype.findLastIndex( predicate[, thisArg] )\n    Returns the index of the last element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var idx = arr.findLastIndex( predicate )\n    1\n\n\nComplex64Array.prototype.forEach( clbk[, thisArg] )\n    Invokes a function once for each array element.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Examples\n    --------\n    > var str = '%';\n    > function clbk( v ) { str += v.toString() + '%'; };\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > arr.forEach( clbk );\n    > str\n    '%1 - 1i%2 - 2i%'\n\n\nComplex64Array.prototype.get( i )\n    Returns an array element located at integer position (index) `i`.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n    \n    Returns\n    -------\n    out: Complex64|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var z = arr.get( 1 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    -2.0\n\n\nComplex64Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a provided value.\n\n    Parameters\n    ----------\n    searchElement: Complex64\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n    \n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex64Array>\n    > var bool = arr.includes( new Complex64( 3.0, -3.0 ) )\n    true\n    > bool = arr.includes( new Complex64( 3.0, -3.0 ), 3 )\n    false\n\n\nComplex64Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the first index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: Complex64\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex64Array>\n    > var idx = arr.indexOf( new Complex64( 3.0, -3.0 ) )\n    2\n    > idx = arr.indexOf( new Complex64( 3.0, -3.0 ), 3 )\n    -1\n\n\nComplex64Array.prototype.join( [separator] )\n    Returns a new string by concatenating all array elements separated by a\n    separator string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        Separator string. Default: ','.\n    \n    Returns\n    -------\n    out: string\n        Array serialized as a string.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var str = arr.join()\n    '1 - 1i,2 - 2i'\n    > str = arr.join( '/' )\n    '1 - 1i/2 - 2i'\n\n\nComplex64Array.prototype.keys()\n    Returns an iterator for iterating over each index key in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array index keys.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var it = arr.keys();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().done\n    true\n\n\nComplex64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the last index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: Complex64\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: out.length-1.\n    \n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex64Array>\n    > var idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ) )\n    3\n    > idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ), 2 )\n    0\n\n\nComplex64Array.prototype.map( clbk[, thisArg] )\n    Returns a new array with each element being the result of a provided\n    callback function.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Complex64Array\n        A new typed array.\n    \n    Examples\n    --------\n    > function clbk( v ) { return v; };\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var out = arr.map( clbk )\n    <Complex64Array>\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    -1.0\n    > z = out.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    -2.0\n\n\nComplex64Array.prototype.reduce( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in order, passing\n    in the return value from the calculation on the preceding element and\n    returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.    \n\n    initialValue: any (optional)\n        Initial accumulation value.\n    \n    Returns\n    -------\n    out: any\n        Accumulated result.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var z = arr.reduce( base.caddf )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    -3.0\n\n\nComplex64Array.prototype.reduceRight( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in reverse order,\n    passing in the return value from the calculation on the preceding element\n    and returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.\n\n    initialValue: any (optional)\n        Initial accumulation value.\n    \n    Returns\n    -------\n    out: any\n        Accumulated result.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var z = arr.reduceRight( base.caddf )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    -3.0\n\n\nComplex64Array.prototype.reverse()\n    Reverses the array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Complex64Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > arr.reverse();\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    -3.0\n    > z = arr.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    -2.0\n    > z = arr.get( 2 )\n    <Complex64>\n    > re = realf( z )\n    1.0\n    > im = imagf( z )\n    -1.0\n\n\nComplex64Array.prototype.set( z[, i] )\n    Sets one or more array elements.\n\n    If provided a single argument, the method sets array elements starting at\n    position (index) `i = 0`. To set elements starting elsewhere in the array,\n    provide an index argument `i`.\n\n    To set one or more array elements, provide an array-like object containing\n    either complex numbers or interleaved real and imaginary components.\n\n    Parameters\n    ----------\n    z: Complex64|Complex64Array|ArrayLikeObject\n        Complex number or complex number array.\n\n    i: integer (optional)\n        Array index at which to start setting elements. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 2 )\n    <Complex64Array>\n    > arr.set( new Complex64( 1.0, -1.0 ) );\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    -1.0\n    > arr.set( new Complex64( 2.0, -2.0 ), 1 );\n    > z = arr.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    -2.0\n\n\nComplex64Array.prototype.slice( [start[, end]] )\n    Copies a portion of a typed array to a new typed array.\n\n    Parameters\n    ----------\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n    \n    Returns\n    -------\n    out: Complex64Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var out = arr.slice( 1 )\n    <Complex64Array>\n    > var len = out.length\n    2\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    -2.0\n    > z = out.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    -3.0\n\n\nComplex64Array.prototype.some( predicate[, thisArg] )\n    Returns a boolean indicating whether at least one element passes a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n    \n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one element passes the test.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var bool = arr.some( predicate )\n    true\n\n\nComplex64Array.prototype.sort( compareFunction )\n    Sorts an array in-place.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first element for comparison.\n    - b: second element for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFunction: Function\n        Comparison function.\n    \n    Returns\n    -------\n    out: Complex64Array\n        Modified array.\n    \n    Examples\n    --------\n    > function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\n    > var arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex64Array>\n    > arr.sort( compare );\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    -1.0\n    > z = arr.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    -2.0\n    > z = arr.get( 2 )\n    <Complex64>\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    -3.0\n\n\nComplex64Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array view over the same underlying `ArrayBuffer` and\n    with the same underlying data type as the host array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Complex64Array\n        New typed array view.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex64Array>\n    > var out = arr.subarray( 1, 3 )\n    <Complex64Array>\n    > var len = out.length\n    2\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    -2.0\n    > z = out.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    -3.0\n\n\nComplex64Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array (optional)\n        Locale identifier(s).\n    \n    options: Object (optional)\n        An object containing serialization options.\n    \n    Returns\n    -------\n    str: string\n        Local-specific string.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0 ] )\n    <Complex64Array>\n    > var str = arr.toLocaleString()\n    '1 + 1i,2 + 2i'\n\n\nComplex64Array.prototype.toReversed()\n    Returns a new typed array containing the elements in reversed order.\n\n    Returns\n    -------\n    out: Complex64Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\n    <Complex64Array>\n    > var out = arr.toReversed()\n    <Complex64Array>\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    3.0\n    > z = out.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    2.0\n    > z = out.get( 2 )\n    <Complex64>\n    > re = realf( z )\n    1.0\n    > im = imagf( z )\n    1.0\n\n\nComplex64Array.prototype.toSorted( compareFcn )\n    Returns a new typed array containing the elements in sorted order.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first element for comparison.\n    - b: second element for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFcn: Function\n        Comparison function.\n    \n    Returns\n    -------\n    out: Complex64Array\n        New typed array.\n    \n    Examples\n    --------\n    > function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\n    > var arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex64Array>\n    > var out = arr.toSorted( compare );\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    -1.0\n    > z = out.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    -2.0\n    > z = out.get( 2 )\n    <Complex64>\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    -3.0\n\n\nComplex64Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        String serialization of the array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\n    <Complex64Array>\n    > var str = arr.toString()\n    '1 + 1i,2 - 2i,3 + 3i'\n\n\nComplex64Array.prototype.values()\n    Returns an iterator for iterating over each value in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array values.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var it = arr.values();\n    > var v = it.next().value\n    <Complex64>\n    > var re = realf( v )\n    1.0\n    > var im = imagf( v )\n    -1.0\n    > v = it.next().value\n    <Complex64>\n    > re = realf( v )\n    2.0\n    > im = imagf( v )\n    -2.0\n    > var bool = it.next().done\n    true\n\n\nComplex64Array.prototype.with( index, value )\n    Returns a new typed array with the element at a provided index replaced\n    with a provided value.\n\n    Parameters\n    ----------\n    index: integer\n        Element index.\n    \n    value: Complex64\n        Element value.  \n\n    Returns\n    -------\n    out: Complex64Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n    <Complex64Array>\n    > var z = out.get( 1 )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    -3.0\n\n\n    See Also\n    --------\n    Complex128Array, complex, Complex64","Complex64Array.from":"\nComplex64Array.from( src[, clbk[, thisArg]] )\n    Creates a new 64-bit complex number array from an array-like object or an\n    iterable.\n\n    A callback function is provided two arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    clbk: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n    \n    Returns\n    -------\n    out: Complex64Array\n        A typed array.\n    \n    Examples\n    --------\n    > function clbkFcn( v ) { return v * 2.0 };\n    > var arr = Complex64Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\n    <Complex64Array>\n    > var len = arr.length\n    2\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    -2.0","Complex64Array.of":"\nComplex64Array.of( element0[, element1[, ...elementN]] )\n    Creates a new 64-bit complex number array from a variable number of\n    arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Complex64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Complex64Array.of( 1.0, -1.0, 2.0, -2.0 )\n    <Complex64Array>\n    > var len = arr.length\n    2\n    > var z1 = new Complex64( 1.0, -1.0 );\n    > var z2 = new Complex64( 2.0, -2.0 );\n    > arr = Complex64Array.of( z1, z2 )\n    <Complex64Array>\n    > len = arr.length\n    2\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    -1.0","Complex64Array.BYTES_PER_ELEMENT":"\nComplex64Array.BYTES_PER_ELEMENT\n    The size of each array element in bytes.\n\n    Examples\n    --------\n    > var nbytes = Complex64Array.BYTES_PER_ELEMENT\n    8","Complex64Array.name":"\nComplex64Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > var str = Complex64Array.name\n    'Complex64Array'","Complex64Array.prototype.buffer":"\nComplex64Array.prototype.buffer\n    Pointer to the underlying data buffer.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 2 )\n    <Complex64Array>\n    > var buf = arr.buffer\n    <ArrayBuffer>","Complex64Array.prototype.byteLength":"\nComplex64Array.prototype.byteLength\n    Length of the array in bytes.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 10 )\n    <Complex64Array>\n    > var nbytes = arr.byteLength\n    80","Complex64Array.prototype.byteOffset":"\nComplex64Array.prototype.byteOffset\n    Offset (in bytes) of the array from the start of its underlying\n    ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 5 )\n    <Complex64Array>\n    > var offset = arr.byteOffset\n    0\n    > var buf = new ArrayBuffer( 240 );\n    > arr = new Complex64Array( buf, 64 )\n    <Complex64Array>\n    > offset = arr.byteOffset\n    64","Complex64Array.prototype.BYTES_PER_ELEMENT":"\nComplex64Array.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 10 )\n    <Complex64Array>\n    > arr.BYTES_PER_ELEMENT\n    8","Complex64Array.prototype.length":"\nComplex64Array.prototype.length\n    The number of array elements.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 10 )\n    <Complex64Array>\n    > var len = arr.length\n    10","Complex64Array.prototype.at":"\nComplex64Array.prototype.at( i )\n    Returns an array element located at integer position (index) `i`, with\n    support for noth nonnegative and negative integer positions.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n\n    Returns\n    -------\n    out: Complex64|void\n        An array element.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var z = arr.at( 1 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    -2.0","Complex64Array.prototype.copyWithin":"\nComplex64Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n    \n    start: integer\n        Source start index position.\n    \n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Complex64Array\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex64Array>\n    > arr.copyWithin( 0, 2 )\n    <Complex64Array>\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    -3.0","Complex64Array.prototype.entries":"\nComplex64Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var it = arr.entries();\n    > var v = it.next().value\n    [ 0, <Complex64> ]\n    > var re = realf( v[ 1 ] )\n    1.0\n    > var im = imagf( v[ 1 ] )\n    -1.0\n    > v = it.next().value\n    [ 1, <Complex64> ]\n    > re = realf( v[ 1 ] )\n    2.0\n    > im = imagf( v[ 1 ] )\n    -2.0\n    > v = it.next().value\n    [ 2, <Complex64> ]\n    > re = realf( v[ 1 ] )\n    3.0\n    > im = imagf( v[ 1 ] )\n    -3.0\n    > var bool = it.next().done\n    true","Complex64Array.prototype.every":"\nComplex64Array.prototype.every( predicate[, thisArg] )\n    Returns a boolean indicating whether all elements in the array pass a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all elements pass the test.\n\n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) > 0.0 ); };\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var bool = arr.every( predicate )\n    true","Complex64Array.prototype.fill":"\nComplex64Array.prototype.fill( value[, start[, end]] )\n    Returns a modified typed array filled with a fill value.\n\n    Parameters\n    ----------\n    value: Complex64\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Complex64Array\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( 3 )\n    <Complex64Array>\n    > arr.fill( new Complex64( 1.0, 1.0 ) );\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    1.0\n    > z = arr.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    1.0\n    > im = imagf( z )\n    1.0\n    > z = arr.get( 2 )\n    <Complex64>\n    > re = realf( z )\n    1.0\n    > im = imagf( z )\n    1.0","Complex64Array.prototype.filter":"\nComplex64Array.prototype.filter( predicate[, thisArg] )\n    Returns a new array containing the elements of an array which pass a test\n    implemented by a predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Complex64Array\n        A new typed array.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var out = arr.filter( predicate )\n    <Complex64Array>\n    > var len = out.length\n    1\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    2.0","Complex64Array.prototype.find":"\nComplex64Array.prototype.find( predicate[, thisArg] )\n    Returns the first element in an array for which a predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    out: Complex64|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var z = arr.find( predicate )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    1.0","Complex64Array.prototype.findIndex":"\nComplex64Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var idx = arr.findIndex( predicate )\n    0","Complex64Array.prototype.findLast":"\nComplex64Array.prototype.findLast( predicate[, thisArg] )\n    Returns the last element in an array for which a predicate function returns\n    a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.  \n    \n    Returns\n    -------\n    out: Complex64|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var z = arr.findLast( predicate )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    2.0","Complex64Array.prototype.findLastIndex":"\nComplex64Array.prototype.findLastIndex( predicate[, thisArg] )\n    Returns the index of the last element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var idx = arr.findLastIndex( predicate )\n    1","Complex64Array.prototype.forEach":"\nComplex64Array.prototype.forEach( clbk[, thisArg] )\n    Invokes a function once for each array element.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Examples\n    --------\n    > var str = '%';\n    > function clbk( v ) { str += v.toString() + '%'; };\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > arr.forEach( clbk );\n    > str\n    '%1 - 1i%2 - 2i%'","Complex64Array.prototype.get":"\nComplex64Array.prototype.get( i )\n    Returns an array element located at integer position (index) `i`.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n    \n    Returns\n    -------\n    out: Complex64|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var z = arr.get( 1 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    -2.0","Complex64Array.prototype.includes":"\nComplex64Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a provided value.\n\n    Parameters\n    ----------\n    searchElement: Complex64\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n    \n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex64Array>\n    > var bool = arr.includes( new Complex64( 3.0, -3.0 ) )\n    true\n    > bool = arr.includes( new Complex64( 3.0, -3.0 ), 3 )\n    false","Complex64Array.prototype.indexOf":"\nComplex64Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the first index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: Complex64\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex64Array>\n    > var idx = arr.indexOf( new Complex64( 3.0, -3.0 ) )\n    2\n    > idx = arr.indexOf( new Complex64( 3.0, -3.0 ), 3 )\n    -1","Complex64Array.prototype.join":"\nComplex64Array.prototype.join( [separator] )\n    Returns a new string by concatenating all array elements separated by a\n    separator string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        Separator string. Default: ','.\n    \n    Returns\n    -------\n    out: string\n        Array serialized as a string.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var str = arr.join()\n    '1 - 1i,2 - 2i'\n    > str = arr.join( '/' )\n    '1 - 1i/2 - 2i'","Complex64Array.prototype.keys":"\nComplex64Array.prototype.keys()\n    Returns an iterator for iterating over each index key in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array index keys.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var it = arr.keys();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().done\n    true","Complex64Array.prototype.lastIndexOf":"\nComplex64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the last index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: Complex64\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: out.length-1.\n    \n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex64Array>\n    > var idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ) )\n    3\n    > idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ), 2 )\n    0","Complex64Array.prototype.map":"\nComplex64Array.prototype.map( clbk[, thisArg] )\n    Returns a new array with each element being the result of a provided\n    callback function.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Complex64Array\n        A new typed array.\n    \n    Examples\n    --------\n    > function clbk( v ) { return v; };\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var out = arr.map( clbk )\n    <Complex64Array>\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    -1.0\n    > z = out.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    -2.0","Complex64Array.prototype.reduce":"\nComplex64Array.prototype.reduce( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in order, passing\n    in the return value from the calculation on the preceding element and\n    returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.    \n\n    initialValue: any (optional)\n        Initial accumulation value.\n    \n    Returns\n    -------\n    out: any\n        Accumulated result.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var z = arr.reduce( base.caddf )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    -3.0","Complex64Array.prototype.reduceRight":"\nComplex64Array.prototype.reduceRight( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in reverse order,\n    passing in the return value from the calculation on the preceding element\n    and returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.\n\n    initialValue: any (optional)\n        Initial accumulation value.\n    \n    Returns\n    -------\n    out: any\n        Accumulated result.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var z = arr.reduceRight( base.caddf )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    -3.0","Complex64Array.prototype.reverse":"\nComplex64Array.prototype.reverse()\n    Reverses the array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Complex64Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > arr.reverse();\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    -3.0\n    > z = arr.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    -2.0\n    > z = arr.get( 2 )\n    <Complex64>\n    > re = realf( z )\n    1.0\n    > im = imagf( z )\n    -1.0","Complex64Array.prototype.set":"\nComplex64Array.prototype.set( z[, i] )\n    Sets one or more array elements.\n\n    If provided a single argument, the method sets array elements starting at\n    position (index) `i = 0`. To set elements starting elsewhere in the array,\n    provide an index argument `i`.\n\n    To set one or more array elements, provide an array-like object containing\n    either complex numbers or interleaved real and imaginary components.\n\n    Parameters\n    ----------\n    z: Complex64|Complex64Array|ArrayLikeObject\n        Complex number or complex number array.\n\n    i: integer (optional)\n        Array index at which to start setting elements. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 2 )\n    <Complex64Array>\n    > arr.set( new Complex64( 1.0, -1.0 ) );\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    -1.0\n    > arr.set( new Complex64( 2.0, -2.0 ), 1 );\n    > z = arr.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    -2.0","Complex64Array.prototype.slice":"\nComplex64Array.prototype.slice( [start[, end]] )\n    Copies a portion of a typed array to a new typed array.\n\n    Parameters\n    ----------\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n    \n    Returns\n    -------\n    out: Complex64Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var out = arr.slice( 1 )\n    <Complex64Array>\n    > var len = out.length\n    2\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    -2.0\n    > z = out.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    -3.0","Complex64Array.prototype.some":"\nComplex64Array.prototype.some( predicate[, thisArg] )\n    Returns a boolean indicating whether at least one element passes a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n    \n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one element passes the test.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var bool = arr.some( predicate )\n    true","Complex64Array.prototype.sort":"\nComplex64Array.prototype.sort( compareFunction )\n    Sorts an array in-place.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first element for comparison.\n    - b: second element for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFunction: Function\n        Comparison function.\n    \n    Returns\n    -------\n    out: Complex64Array\n        Modified array.\n    \n    Examples\n    --------\n    > function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\n    > var arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex64Array>\n    > arr.sort( compare );\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    -1.0\n    > z = arr.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    -2.0\n    > z = arr.get( 2 )\n    <Complex64>\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    -3.0","Complex64Array.prototype.subarray":"\nComplex64Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array view over the same underlying `ArrayBuffer` and\n    with the same underlying data type as the host array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Complex64Array\n        New typed array view.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex64Array>\n    > var out = arr.subarray( 1, 3 )\n    <Complex64Array>\n    > var len = out.length\n    2\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    -2.0\n    > z = out.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    -3.0","Complex64Array.prototype.toLocaleString":"\nComplex64Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array (optional)\n        Locale identifier(s).\n    \n    options: Object (optional)\n        An object containing serialization options.\n    \n    Returns\n    -------\n    str: string\n        Local-specific string.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0 ] )\n    <Complex64Array>\n    > var str = arr.toLocaleString()\n    '1 + 1i,2 + 2i'","Complex64Array.prototype.toReversed":"\nComplex64Array.prototype.toReversed()\n    Returns a new typed array containing the elements in reversed order.\n\n    Returns\n    -------\n    out: Complex64Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\n    <Complex64Array>\n    > var out = arr.toReversed()\n    <Complex64Array>\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    3.0\n    > z = out.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    2.0\n    > z = out.get( 2 )\n    <Complex64>\n    > re = realf( z )\n    1.0\n    > im = imagf( z )\n    1.0","Complex64Array.prototype.toSorted":"\nComplex64Array.prototype.toSorted( compareFcn )\n    Returns a new typed array containing the elements in sorted order.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first element for comparison.\n    - b: second element for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFcn: Function\n        Comparison function.\n    \n    Returns\n    -------\n    out: Complex64Array\n        New typed array.\n    \n    Examples\n    --------\n    > function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\n    > var arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex64Array>\n    > var out = arr.toSorted( compare );\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    -1.0\n    > z = out.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    -2.0\n    > z = out.get( 2 )\n    <Complex64>\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    -3.0","Complex64Array.prototype.toString":"\nComplex64Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        String serialization of the array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\n    <Complex64Array>\n    > var str = arr.toString()\n    '1 + 1i,2 - 2i,3 + 3i'","Complex64Array.prototype.values":"\nComplex64Array.prototype.values()\n    Returns an iterator for iterating over each value in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array values.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var it = arr.values();\n    > var v = it.next().value\n    <Complex64>\n    > var re = realf( v )\n    1.0\n    > var im = imagf( v )\n    -1.0\n    > v = it.next().value\n    <Complex64>\n    > re = realf( v )\n    2.0\n    > im = imagf( v )\n    -2.0\n    > var bool = it.next().done\n    true","Complex64Array.prototype.with":"\nComplex64Array.prototype.with( index, value )\n    Returns a new typed array with the element at a provided index replaced\n    with a provided value.\n\n    Parameters\n    ----------\n    index: integer\n        Element index.\n    \n    value: Complex64\n        Element value.  \n\n    Returns\n    -------\n    out: Complex64Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n    <Complex64Array>\n    > var z = out.get( 1 )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    -3.0\n\n\n    See Also\n    --------\n    Complex128Array, complex, Complex64","Complex128":"\nComplex128( real, imag )\n    128-bit complex number constructor.\n\n    Both the real and imaginary components are stored as double-precision\n    floating-point numbers.\n\n    Parameters\n    ----------\n    real: number\n        Real component.\n\n    imag: number\n        Imaginary component.\n\n    Returns\n    -------\n    z: Complex128\n        128-bit complex number.\n\n    z.re: number\n        Read-only property returning the real component.\n\n    z.im: number\n        Read-only property returning the imaginary component.\n\n\nComplex128.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n\n    Returns\n    -------\n    v: integer\n        Size (in bytes) of each component.\n\n    Examples\n    --------\n    > var s = Complex128.BYTES_PER_ELEMENT\n    8\n\n\nComplex128.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n\n    Returns\n    -------\n    s: integer\n        Size (in bytes) of each component.\n\n    Examples\n    --------\n    > var z = new Complex128( 5.0, 3.0 )\n    <Complex128>\n    > var s = z.BYTES_PER_ELEMENT\n    8\n\n\nComplex128.prototype.byteLength\n    Length (in bytes) of a complex number.\n\n    Returns\n    -------\n    len: integer\n        Length (in bytes) of a complex number.\n\n    Examples\n    --------\n    > var z = new Complex128( 5.0, 3.0 )\n    <Complex128>\n    > var s = z.byteLength\n    16\n\n    See Also\n    --------\n    complex, Complex64\n","Complex128.BYTES_PER_ELEMENT":"\nComplex128.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n\n    Returns\n    -------\n    v: integer\n        Size (in bytes) of each component.\n\n    Examples\n    --------\n    > var s = Complex128.BYTES_PER_ELEMENT\n    8","Complex128.prototype.BYTES_PER_ELEMENT":"\nComplex128.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n\n    Returns\n    -------\n    s: integer\n        Size (in bytes) of each component.\n\n    Examples\n    --------\n    > var z = new Complex128( 5.0, 3.0 )\n    <Complex128>\n    > var s = z.BYTES_PER_ELEMENT\n    8","Complex128.prototype.byteLength":"\nComplex128.prototype.byteLength\n    Length (in bytes) of a complex number.\n\n    Returns\n    -------\n    len: integer\n        Length (in bytes) of a complex number.\n\n    Examples\n    --------\n    > var z = new Complex128( 5.0, 3.0 )\n    <Complex128>\n    > var s = z.byteLength\n    16\n\n    See Also\n    --------\n    complex, Complex64","COMPLEX128_NAN":"\nCOMPLEX128_NAN\n    Canonical double-precision complex floating-point NaN.\n\n    Examples\n    --------\n    > COMPLEX128_NAN\n    <Complex128>\n\n    See Also\n    --------\n    COMPLEX64_NAN\n","COMPLEX128_NUM_BYTES":"\nCOMPLEX128_NUM_BYTES\n    Size (in bytes) of a 128-bit complex number.\n\n    Examples\n    --------\n    > COMPLEX128_NUM_BYTES\n    16\n\n    See Also\n    --------\n    COMPLEX64_NUM_BYTES, FLOAT64_NUM_BYTES\n","COMPLEX128_ZERO":"\nCOMPLEX128_ZERO\n    Double-precision complex floating-point zero.\n\n    Examples\n    --------\n    > COMPLEX128_ZERO\n    <Complex128>\n\n    See Also\n    --------\n    COMPLEX64_ZERO\n","Complex128Array":"\nComplex128Array()\n    A 128-bit complex number array.\n\n    Returns\n    -------\n    out: Complex128Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Complex128Array()\n    <Complex128Array>\n\n\nComplex128Array( length )\n    Creates a 128-bit complex number array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: Complex128Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 10 )\n    <Complex128Array>\n    > var len = arr.length\n    10\n\n\nComplex128Array( complexarray )\n    Creates a 64-bit complex number array from another complex number array.\n\n    Parameters\n    ----------\n    complexarray: Complex128Array\n        Complex array from which to generate another complex array.\n\n    Returns\n    -------\n    out: Complex128Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var arr2 = new Complex128Array( arr1 )\n    <Complex128Array>\n    > var len = arr2.length\n    2\n\n\nComplex128Array( typedarray )\n    Creates a 128-bit complex number array from a typed array\n    containing interleaved real and imaginary components.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate a complex array.\n\n    Returns\n    -------\n    out: Complex128Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new Float64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Float64Array>\n    > var arr = new Complex128Array( buf )\n    <Complex128Array>\n    > var len = arr.length\n    2\n\n\nComplex128Array( obj )\n    Creates a 128-bit complex number array from an array-like object or \n    iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a complex array.\n\n    Returns\n    -------\n    out: Complex128Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var len = arr1.length\n    2\n    > var buf = [ new Complex128( 1.0, -1.0 ), new Complex128( 2.0, -2.0 ) ];\n    > var arr2 = new Complex128Array( buf )\n    <Complex128Array>\n    > len = arr2.length\n    2\n\n\nComplex128Array( buffer[, byteOffset[, length]] )\n    Returns a 128-bit complex number array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Complex128Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 480 );\n    > var arr1 = new Complex128Array( buf )\n    <Complex128Array>\n    > var len = arr1.length\n    30\n    > var arr2 = new Complex128Array( buf, 16 )\n    <Complex128Array>\n    > len = arr2.length\n    29\n    > var arr3 = new Complex128Array( buf, 16, 20 )\n    <Complex128Array>\n    > len = arr3.length\n    20\n\n\nComplex128Array.from( src[, clbk[, thisArg]] )\n    Creates a new 128-bit complex number array from an array-like object or an\n    iterable.\n\n    A callback function is provided two arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    clbk: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n    \n    Returns\n    -------\n    out: Complex128Array\n        A typed array.\n    \n    Examples\n    --------\n    > function clbkFcn( v ) { return v * 2.0 };\n    > var arr = Complex128Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\n    <Complex128Array>\n    > var len = arr.length\n    2\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    -2.0\n\n\nComplex128Array.of( element0[, element1[, ...elementN]] )\n    Creates a new 128-bit complex number array from a variable number of\n    arguments.\n\n    Parameters\n    ----------\n    element0: number|ComplexLike\n        Array element.\n\n    element1: number |ComplexLike(optional)\n        Array element.\n\n    elementN: ...number|ComplexLike (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Complex128Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Complex128Array.of( 1.0, -1.0, 2.0, -2.0 )\n    <Complex128Array>\n    > var len = arr.length\n    2\n    > var z1 = new Complex128( 1.0, -1.0 );\n    > var z2 = new Complex128( 2.0, -2.0 );\n    > arr = Complex128Array.of( z1, z2 )\n    <Complex128Array>\n    > len = arr.length\n    2\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    -1.0\n\n\nComplex128Array.BYTES_PER_ELEMENT\n    The size of each array element in bytes.\n\n    Examples\n    --------\n    > var nbytes = Complex128Array.BYTES_PER_ELEMENT\n    16\n\n\nComplex128Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > var str = Complex128Array.name\n    'Complex128Array'\n\n\nComplex128Array.prototype.buffer\n    Pointer to the underlying data buffer.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 2 )\n    <Complex128Array>\n    > var buf = arr.buffer\n    <ArrayBuffer>\n\n\nComplex128Array.prototype.byteLength\n    Length of the array in bytes.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 10 )\n    <Complex128Array>\n    > var nbytes = arr.byteLength\n    160\n\n\nComplex128Array.prototype.byteOffset\n    Offset (in bytes) of the array from the start of its underlying\n    ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 10 )\n    <Complex128Array>\n    > var offset = arr.byteOffset\n    0\n    > var buf = new ArrayBuffer( 480 );\n    > arr = new Complex128Array( buf, 128 )\n    <Complex128Array>\n    > offset = arr.byteOffset\n    128\n\n\nComplex128Array.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 10 )\n    <Complex128Array>\n    > arr.BYTES_PER_ELEMENT\n    16\n\n\nComplex128Array.prototype.length\n    The number of array elements.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 10 )\n    <Complex128Array>\n    > var len = arr.length\n    10\n\n\nComplex128Array.prototype.at( i )\n    Returns an array element located at integer position (index) `i`, with\n    support for both nonnegative and negative integer positions.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n\n    Returns\n    -------\n    out: Complex128|void\n        An array element.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var z = arr.at( 1 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    -2.0\n\n\nComplex128Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n    \n    start: integer\n        Source start index position.\n    \n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Complex128Array\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex128Array>\n    > arr.copyWithin( 0, 2 )\n    <Complex128Array>\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    -3.0\n\n\nComplex128Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var it = arr.entries();\n    > var v = it.next().value\n    [ 0, <Complex128> ]\n    > var re = real( v[ 1 ] )\n    1.0\n    > var im = imag( v[ 1 ] )\n    -1.0\n    > v = it.next().value\n    [ 1, <Complex128> ]\n    > re = real( v[ 1 ] )\n    2.0\n    > im = imag( v[ 1 ] )\n    -2.0\n    > v = it.next().value\n    [ 2, <Complex128> ]\n    > re = real( v[ 1 ] )\n    3.0\n    > im = imag( v[ 1 ] )\n    -3.0\n    > var bool = it.next().done\n    true\n\n\nComplex128Array.prototype.every( predicate[, thisArg] )\n    Returns a boolean indicating whether all elements in the array pass a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all elements pass the test.\n\n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) > 0.0 ); };\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var bool = arr.every( predicate )\n    true\n\n\nComplex128Array.prototype.fill( value[, start[, end]] )\n    Returns a modified typed array filled with a fill value.\n\n    Parameters\n    ----------\n    value: Complex128\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Complex128Array\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( 3 )\n    <Complex128Array>\n    > arr.fill( new Complex128( 1.0, 1.0 ) );\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    1.0\n    > z = arr.get( 1 )\n    <Complex128>\n    > re = real( z )\n    1.0\n    > im = imag( z )\n    1.0\n    > z = arr.get( 2 )\n    <Complex128>\n    > re = real( z )\n    1.0\n    > im = imag( z )\n    1.0\n\n\nComplex128Array.prototype.filter( predicate[, thisArg] )\n    Returns a new array containing the elements of an array which pass a test\n    implemented by a predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Complex128Array\n        A new typed array.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var out = arr.filter( predicate )\n    <Complex128Array>\n    > var len = out.length\n    1\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    2.0\n\n\nComplex128Array.prototype.find( predicate[, thisArg] )\n    Returns the first element in an array for which a predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    out: Complex128|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var z = arr.find( predicate )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    1.0\n\n\nComplex128Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var idx = arr.findIndex( predicate )\n    0\n\n\nComplex128Array.prototype.findLast( predicate[, thisArg] )\n    Returns the last element in an array for which a predicate function returns\n    a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.  \n    \n    Returns\n    -------\n    out: Complex128|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var z = arr.findLast( predicate )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    2.0\n\n\nComplex128Array.prototype.findLastIndex( predicate[, thisArg] )\n    Returns the index of the last element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var idx = arr.findLastIndex( predicate )\n    1\n\n\nComplex128Array.prototype.forEach( clbk[, thisArg] )\n    Invokes a function once for each array element.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Examples\n    --------\n    > var str = '%';\n    > function clbk( v ) { str += v.toString() + '%'; };\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > arr.forEach( clbk );\n    > str\n    '%1 - 1i%2 - 2i%'\n\n\nComplex128Array.prototype.get( i )\n    Returns an array element located at integer position (index) `i`.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n    \n    Returns\n    -------\n    out: Complex128|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var z = arr.get( 1 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    -2.0\n\n\nComplex128Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a provided value.\n\n    Parameters\n    ----------\n    searchElement: Complex128\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n    \n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex128Array>\n    > var bool = arr.includes( new Complex128( 3.0, -3.0 ) )\n    true\n    > bool = arr.includes( new Complex128( 3.0, -3.0 ), 3 )\n    false\n\n\nComplex128Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the first index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: Complex128\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex128Array>\n    > var idx = arr.indexOf( new Complex128( 3.0, -3.0 ) )\n    2\n    > idx = arr.indexOf( new Complex128( 3.0, -3.0 ), 3 )\n    -1\n\n\nComplex128Array.prototype.join( [separator] )\n    Returns a new string by concatenating all array elements separated by a\n    separator string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        Separator string. Default: ','.\n    \n    Returns\n    -------\n    out: string\n        Array serialized as a string.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var str = arr.join()\n    '1 - 1i,2 - 2i'\n    > str = arr.join( '/' )\n    '1 - 1i/2 - 2i'\n\n\nComplex128Array.prototype.keys()\n    Returns an iterator for iterating over each index key in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array index keys.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var it = arr.keys();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().done\n    true\n\n\nComplex128Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the last index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: Complex128\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: out.length-1.\n    \n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex128Array>\n    > var idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ) )\n    3\n    > idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ), 2 )\n    0\n\n\nComplex128Array.prototype.map( clbk[, thisArg] )\n    Returns a new array with each element being the result of a provided\n    callback function.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Complex128Array\n        A new typed array.\n    \n    Examples\n    --------\n    > function clbk( v ) { return v; };\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var out = arr.map( clbk )\n    <Complex128Array>\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    -1.0\n    > z = out.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    -2.0\n\n\nComplex128Array.prototype.reduce( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in order, passing\n    in the return value from the calculation on the preceding element and\n    returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.    \n\n    initialValue: any (optional)\n        Initial accumulation value.\n    \n    Returns\n    -------\n    out: any\n        Accumulated result.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var z = arr.reduce( base.cadd )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    -3.0\n\n\nComplex128Array.prototype.reduceRight( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in reverse order,\n    passing in the return value from the calculation on the preceding element\n    and returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.\n\n    initialValue: any (optional)\n        Initial accumulation value.\n    \n    Returns\n    -------\n    out: any\n        Accumulated result.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var z = arr.reduceRight( base.cadd )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    -3.0\n\n\nComplex128Array.prototype.reverse()\n    Reverses the array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Complex128Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > arr.reverse();\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    -3.0\n    > z = arr.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    -2.0\n    > z = arr.get( 2 )\n    <Complex128>\n    > re = real( z )\n    1.0\n    > im = imag( z )\n    -1.0\n\n\nComplex128Array.prototype.set( z[, i] )\n    Sets one or more array elements.\n\n    If provided a single argument, the method sets array elements starting at\n    position (index) `i = 0`. To set elements starting elsewhere in the array,\n    provide an index argument `i`.\n\n    To set one or more array elements, provide an array-like object containing\n    either complex numbers or interleaved real and imaginary components.\n\n    Parameters\n    ----------\n    z: Complex128|Complex128Array|ArrayLikeObject\n        Complex number or complex number array.\n\n    i: integer (optional)\n        Array index at which to start setting elements. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 2 )\n    <Complex128Array>\n    > arr.set( new Complex128( 1.0, -1.0 ) );\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    -1.0\n    > arr.set( new Complex128( 2.0, -2.0 ), 1 );\n    > z = arr.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    -2.0\n\n\nComplex128Array.prototype.slice( [start[, end]] )\n    Copies a portion of a typed array to a new typed array.\n\n    Parameters\n    ----------\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n    \n    Returns\n    -------\n    out: Complex128Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var out = arr.slice( 1 )\n    <Complex128Array>\n    > var len = out.length\n    2\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    -2.0\n    > z = out.get( 1 )\n    <Complex128>\n    > re = real( z )\n    3.0\n    > im = imag( z )\n    -3.0\n\n\nComplex128Array.prototype.some( predicate[, thisArg] )\n    Returns a boolean indicating whether at least one element passes a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n    \n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one element passes the test.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var bool = arr.some( predicate )\n    true\n\n\nComplex128Array.prototype.sort( compareFunction )\n    Sorts an array in-place.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first element for comparison.\n    - b: second element for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFunction: Function\n        Comparison function.\n    \n    Returns\n    -------\n    out: Complex128Array\n        Modified array.\n    \n    Examples\n    --------\n    > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n    > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex128Array>\n    > arr.sort( compare );\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    -1.0\n    > z = arr.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    -2.0\n    > z = arr.get( 2 )\n    <Complex128>\n    > re = real( z )\n    3.0\n    > im = imag( z )\n    -3.0\n\n\nComplex128Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array view over the same underlying `ArrayBuffer` and\n    with the same underlying data type as the host array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Complex128Array\n        New typed array view.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex128Array>\n    > var out = arr.subarray( 1, 3 )\n    <Complex128Array>\n    > var len = out.length\n    2\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    -2.0\n    > z = out.get( 1 )\n    <Complex128>\n    > re = real( z )\n    3.0\n    > im = imag( z )\n    -3.0\n\n\nComplex128Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array (optional)\n        Locale identifier(s).\n    \n    options: Object (optional)\n        An object containing serialization options.\n    \n    Returns\n    -------\n    str: string\n        Local-specific string.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0 ] )\n    <Complex128Array>\n    > var str = arr.toLocaleString()\n    '1 + 1i,2 + 2i'\n\n\nComplex128Array.prototype.toReversed()\n    Returns a new typed array containing the elements in reversed order.\n\n    Returns\n    -------\n    out: Complex128Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\n    <Complex128Array>\n    > var out = arr.toReversed()\n    <Complex128Array>\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    3.0\n    > z = out.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    2.0\n    > z = out.get( 2 )\n    <Complex128>\n    > re = real( z )\n    1.0\n    > im = imag( z )\n    1.0\n\n\nComplex128Array.prototype.toSorted( compareFcn )\n    Returns a new typed array containing the elements in sorted order.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first element for comparison.\n    - b: second element for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFcn: Function\n        Comparison function.\n    \n    Returns\n    -------\n    out: Complex128Array\n        New typed array.\n    \n    Examples\n    --------\n    > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n    > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex128Array>\n    > var out = arr.toSorted( compare );\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    -1.0\n    > z = out.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    -2.0\n    > z = out.get( 2 )\n    <Complex128>\n    > re = real( z )\n    3.0\n    > im = imag( z )\n    -3.0\n\n\nComplex128Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        String serialization of the array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\n    <Complex128Array>\n    > var str = arr.toString()\n    '1 + 1i,2 - 2i,3 + 3i'\n\n\nComplex128Array.prototype.values()\n    Returns an iterator for iterating over each value in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array values.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var it = arr.values();\n    > var v = it.next().value\n    <Complex128>\n    > var re = real( v )\n    1.0\n    > var im = imag( v )\n    -1.0\n    > v = it.next().value\n    <Complex128>\n    > re = real( v )\n    2.0\n    > im = imag( v )\n    -2.0\n    > var bool = it.next().done\n    true\n\n\nComplex128Array.prototype.with( index, value )\n    Returns a new typed array with the element at a provided index replaced\n    with a provided value.\n\n    Parameters\n    ----------\n    index: integer\n        Element index.\n    \n    value: Complex128\n        Element value.  \n\n    Returns\n    -------\n    out: Complex128Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n    <Complex128Array>\n    > var z = out.get( 1 )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    -3.0\n\n\n    See Also\n    --------\n    Complex64Array, complex, Complex128","Complex128Array.from":"\nComplex128Array.from( src[, clbk[, thisArg]] )\n    Creates a new 128-bit complex number array from an array-like object or an\n    iterable.\n\n    A callback function is provided two arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    clbk: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n    \n    Returns\n    -------\n    out: Complex128Array\n        A typed array.\n    \n    Examples\n    --------\n    > function clbkFcn( v ) { return v * 2.0 };\n    > var arr = Complex128Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\n    <Complex128Array>\n    > var len = arr.length\n    2\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    -2.0","Complex128Array.of":"\nComplex128Array.of( element0[, element1[, ...elementN]] )\n    Creates a new 128-bit complex number array from a variable number of\n    arguments.\n\n    Parameters\n    ----------\n    element0: number|ComplexLike\n        Array element.\n\n    element1: number |ComplexLike(optional)\n        Array element.\n\n    elementN: ...number|ComplexLike (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Complex128Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Complex128Array.of( 1.0, -1.0, 2.0, -2.0 )\n    <Complex128Array>\n    > var len = arr.length\n    2\n    > var z1 = new Complex128( 1.0, -1.0 );\n    > var z2 = new Complex128( 2.0, -2.0 );\n    > arr = Complex128Array.of( z1, z2 )\n    <Complex128Array>\n    > len = arr.length\n    2\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    -1.0","Complex128Array.BYTES_PER_ELEMENT":"\nComplex128Array.BYTES_PER_ELEMENT\n    The size of each array element in bytes.\n\n    Examples\n    --------\n    > var nbytes = Complex128Array.BYTES_PER_ELEMENT\n    16","Complex128Array.name":"\nComplex128Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > var str = Complex128Array.name\n    'Complex128Array'","Complex128Array.prototype.buffer":"\nComplex128Array.prototype.buffer\n    Pointer to the underlying data buffer.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 2 )\n    <Complex128Array>\n    > var buf = arr.buffer\n    <ArrayBuffer>","Complex128Array.prototype.byteLength":"\nComplex128Array.prototype.byteLength\n    Length of the array in bytes.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 10 )\n    <Complex128Array>\n    > var nbytes = arr.byteLength\n    160","Complex128Array.prototype.byteOffset":"\nComplex128Array.prototype.byteOffset\n    Offset (in bytes) of the array from the start of its underlying\n    ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 10 )\n    <Complex128Array>\n    > var offset = arr.byteOffset\n    0\n    > var buf = new ArrayBuffer( 480 );\n    > arr = new Complex128Array( buf, 128 )\n    <Complex128Array>\n    > offset = arr.byteOffset\n    128","Complex128Array.prototype.BYTES_PER_ELEMENT":"\nComplex128Array.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 10 )\n    <Complex128Array>\n    > arr.BYTES_PER_ELEMENT\n    16","Complex128Array.prototype.length":"\nComplex128Array.prototype.length\n    The number of array elements.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 10 )\n    <Complex128Array>\n    > var len = arr.length\n    10","Complex128Array.prototype.at":"\nComplex128Array.prototype.at( i )\n    Returns an array element located at integer position (index) `i`, with\n    support for both nonnegative and negative integer positions.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n\n    Returns\n    -------\n    out: Complex128|void\n        An array element.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var z = arr.at( 1 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    -2.0","Complex128Array.prototype.copyWithin":"\nComplex128Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n    \n    start: integer\n        Source start index position.\n    \n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Complex128Array\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex128Array>\n    > arr.copyWithin( 0, 2 )\n    <Complex128Array>\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    -3.0","Complex128Array.prototype.entries":"\nComplex128Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var it = arr.entries();\n    > var v = it.next().value\n    [ 0, <Complex128> ]\n    > var re = real( v[ 1 ] )\n    1.0\n    > var im = imag( v[ 1 ] )\n    -1.0\n    > v = it.next().value\n    [ 1, <Complex128> ]\n    > re = real( v[ 1 ] )\n    2.0\n    > im = imag( v[ 1 ] )\n    -2.0\n    > v = it.next().value\n    [ 2, <Complex128> ]\n    > re = real( v[ 1 ] )\n    3.0\n    > im = imag( v[ 1 ] )\n    -3.0\n    > var bool = it.next().done\n    true","Complex128Array.prototype.every":"\nComplex128Array.prototype.every( predicate[, thisArg] )\n    Returns a boolean indicating whether all elements in the array pass a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all elements pass the test.\n\n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) > 0.0 ); };\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var bool = arr.every( predicate )\n    true","Complex128Array.prototype.fill":"\nComplex128Array.prototype.fill( value[, start[, end]] )\n    Returns a modified typed array filled with a fill value.\n\n    Parameters\n    ----------\n    value: Complex128\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Complex128Array\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( 3 )\n    <Complex128Array>\n    > arr.fill( new Complex128( 1.0, 1.0 ) );\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    1.0\n    > z = arr.get( 1 )\n    <Complex128>\n    > re = real( z )\n    1.0\n    > im = imag( z )\n    1.0\n    > z = arr.get( 2 )\n    <Complex128>\n    > re = real( z )\n    1.0\n    > im = imag( z )\n    1.0","Complex128Array.prototype.filter":"\nComplex128Array.prototype.filter( predicate[, thisArg] )\n    Returns a new array containing the elements of an array which pass a test\n    implemented by a predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Complex128Array\n        A new typed array.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var out = arr.filter( predicate )\n    <Complex128Array>\n    > var len = out.length\n    1\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    2.0","Complex128Array.prototype.find":"\nComplex128Array.prototype.find( predicate[, thisArg] )\n    Returns the first element in an array for which a predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    out: Complex128|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var z = arr.find( predicate )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    1.0","Complex128Array.prototype.findIndex":"\nComplex128Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var idx = arr.findIndex( predicate )\n    0","Complex128Array.prototype.findLast":"\nComplex128Array.prototype.findLast( predicate[, thisArg] )\n    Returns the last element in an array for which a predicate function returns\n    a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.  \n    \n    Returns\n    -------\n    out: Complex128|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var z = arr.findLast( predicate )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    2.0","Complex128Array.prototype.findLastIndex":"\nComplex128Array.prototype.findLastIndex( predicate[, thisArg] )\n    Returns the index of the last element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var idx = arr.findLastIndex( predicate )\n    1","Complex128Array.prototype.forEach":"\nComplex128Array.prototype.forEach( clbk[, thisArg] )\n    Invokes a function once for each array element.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Examples\n    --------\n    > var str = '%';\n    > function clbk( v ) { str += v.toString() + '%'; };\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > arr.forEach( clbk );\n    > str\n    '%1 - 1i%2 - 2i%'","Complex128Array.prototype.get":"\nComplex128Array.prototype.get( i )\n    Returns an array element located at integer position (index) `i`.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n    \n    Returns\n    -------\n    out: Complex128|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var z = arr.get( 1 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    -2.0","Complex128Array.prototype.includes":"\nComplex128Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a provided value.\n\n    Parameters\n    ----------\n    searchElement: Complex128\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n    \n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex128Array>\n    > var bool = arr.includes( new Complex128( 3.0, -3.0 ) )\n    true\n    > bool = arr.includes( new Complex128( 3.0, -3.0 ), 3 )\n    false","Complex128Array.prototype.indexOf":"\nComplex128Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the first index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: Complex128\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex128Array>\n    > var idx = arr.indexOf( new Complex128( 3.0, -3.0 ) )\n    2\n    > idx = arr.indexOf( new Complex128( 3.0, -3.0 ), 3 )\n    -1","Complex128Array.prototype.join":"\nComplex128Array.prototype.join( [separator] )\n    Returns a new string by concatenating all array elements separated by a\n    separator string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        Separator string. Default: ','.\n    \n    Returns\n    -------\n    out: string\n        Array serialized as a string.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var str = arr.join()\n    '1 - 1i,2 - 2i'\n    > str = arr.join( '/' )\n    '1 - 1i/2 - 2i'","Complex128Array.prototype.keys":"\nComplex128Array.prototype.keys()\n    Returns an iterator for iterating over each index key in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array index keys.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var it = arr.keys();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().done\n    true","Complex128Array.prototype.lastIndexOf":"\nComplex128Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the last index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: Complex128\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: out.length-1.\n    \n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex128Array>\n    > var idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ) )\n    3\n    > idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ), 2 )\n    0","Complex128Array.prototype.map":"\nComplex128Array.prototype.map( clbk[, thisArg] )\n    Returns a new array with each element being the result of a provided\n    callback function.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Complex128Array\n        A new typed array.\n    \n    Examples\n    --------\n    > function clbk( v ) { return v; };\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var out = arr.map( clbk )\n    <Complex128Array>\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    -1.0\n    > z = out.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    -2.0","Complex128Array.prototype.reduce":"\nComplex128Array.prototype.reduce( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in order, passing\n    in the return value from the calculation on the preceding element and\n    returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.    \n\n    initialValue: any (optional)\n        Initial accumulation value.\n    \n    Returns\n    -------\n    out: any\n        Accumulated result.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var z = arr.reduce( base.cadd )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    -3.0","Complex128Array.prototype.reduceRight":"\nComplex128Array.prototype.reduceRight( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in reverse order,\n    passing in the return value from the calculation on the preceding element\n    and returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.\n\n    initialValue: any (optional)\n        Initial accumulation value.\n    \n    Returns\n    -------\n    out: any\n        Accumulated result.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var z = arr.reduceRight( base.cadd )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    -3.0","Complex128Array.prototype.reverse":"\nComplex128Array.prototype.reverse()\n    Reverses the array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Complex128Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > arr.reverse();\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    -3.0\n    > z = arr.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    -2.0\n    > z = arr.get( 2 )\n    <Complex128>\n    > re = real( z )\n    1.0\n    > im = imag( z )\n    -1.0","Complex128Array.prototype.set":"\nComplex128Array.prototype.set( z[, i] )\n    Sets one or more array elements.\n\n    If provided a single argument, the method sets array elements starting at\n    position (index) `i = 0`. To set elements starting elsewhere in the array,\n    provide an index argument `i`.\n\n    To set one or more array elements, provide an array-like object containing\n    either complex numbers or interleaved real and imaginary components.\n\n    Parameters\n    ----------\n    z: Complex128|Complex128Array|ArrayLikeObject\n        Complex number or complex number array.\n\n    i: integer (optional)\n        Array index at which to start setting elements. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 2 )\n    <Complex128Array>\n    > arr.set( new Complex128( 1.0, -1.0 ) );\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    -1.0\n    > arr.set( new Complex128( 2.0, -2.0 ), 1 );\n    > z = arr.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    -2.0","Complex128Array.prototype.slice":"\nComplex128Array.prototype.slice( [start[, end]] )\n    Copies a portion of a typed array to a new typed array.\n\n    Parameters\n    ----------\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n    \n    Returns\n    -------\n    out: Complex128Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var out = arr.slice( 1 )\n    <Complex128Array>\n    > var len = out.length\n    2\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    -2.0\n    > z = out.get( 1 )\n    <Complex128>\n    > re = real( z )\n    3.0\n    > im = imag( z )\n    -3.0","Complex128Array.prototype.some":"\nComplex128Array.prototype.some( predicate[, thisArg] )\n    Returns a boolean indicating whether at least one element passes a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n    \n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one element passes the test.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var bool = arr.some( predicate )\n    true","Complex128Array.prototype.sort":"\nComplex128Array.prototype.sort( compareFunction )\n    Sorts an array in-place.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first element for comparison.\n    - b: second element for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFunction: Function\n        Comparison function.\n    \n    Returns\n    -------\n    out: Complex128Array\n        Modified array.\n    \n    Examples\n    --------\n    > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n    > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex128Array>\n    > arr.sort( compare );\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    -1.0\n    > z = arr.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    -2.0\n    > z = arr.get( 2 )\n    <Complex128>\n    > re = real( z )\n    3.0\n    > im = imag( z )\n    -3.0","Complex128Array.prototype.subarray":"\nComplex128Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array view over the same underlying `ArrayBuffer` and\n    with the same underlying data type as the host array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Complex128Array\n        New typed array view.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex128Array>\n    > var out = arr.subarray( 1, 3 )\n    <Complex128Array>\n    > var len = out.length\n    2\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    -2.0\n    > z = out.get( 1 )\n    <Complex128>\n    > re = real( z )\n    3.0\n    > im = imag( z )\n    -3.0","Complex128Array.prototype.toLocaleString":"\nComplex128Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array (optional)\n        Locale identifier(s).\n    \n    options: Object (optional)\n        An object containing serialization options.\n    \n    Returns\n    -------\n    str: string\n        Local-specific string.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0 ] )\n    <Complex128Array>\n    > var str = arr.toLocaleString()\n    '1 + 1i,2 + 2i'","Complex128Array.prototype.toReversed":"\nComplex128Array.prototype.toReversed()\n    Returns a new typed array containing the elements in reversed order.\n\n    Returns\n    -------\n    out: Complex128Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\n    <Complex128Array>\n    > var out = arr.toReversed()\n    <Complex128Array>\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    3.0\n    > z = out.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    2.0\n    > z = out.get( 2 )\n    <Complex128>\n    > re = real( z )\n    1.0\n    > im = imag( z )\n    1.0","Complex128Array.prototype.toSorted":"\nComplex128Array.prototype.toSorted( compareFcn )\n    Returns a new typed array containing the elements in sorted order.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first element for comparison.\n    - b: second element for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFcn: Function\n        Comparison function.\n    \n    Returns\n    -------\n    out: Complex128Array\n        New typed array.\n    \n    Examples\n    --------\n    > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n    > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex128Array>\n    > var out = arr.toSorted( compare );\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    -1.0\n    > z = out.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    -2.0\n    > z = out.get( 2 )\n    <Complex128>\n    > re = real( z )\n    3.0\n    > im = imag( z )\n    -3.0","Complex128Array.prototype.toString":"\nComplex128Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        String serialization of the array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\n    <Complex128Array>\n    > var str = arr.toString()\n    '1 + 1i,2 - 2i,3 + 3i'","Complex128Array.prototype.values":"\nComplex128Array.prototype.values()\n    Returns an iterator for iterating over each value in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array values.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var it = arr.values();\n    > var v = it.next().value\n    <Complex128>\n    > var re = real( v )\n    1.0\n    > var im = imag( v )\n    -1.0\n    > v = it.next().value\n    <Complex128>\n    > re = real( v )\n    2.0\n    > im = imag( v )\n    -2.0\n    > var bool = it.next().done\n    true","Complex128Array.prototype.with":"\nComplex128Array.prototype.with( index, value )\n    Returns a new typed array with the element at a provided index replaced\n    with a provided value.\n\n    Parameters\n    ----------\n    index: integer\n        Element index.\n    \n    value: Complex128\n        Element value.  \n\n    Returns\n    -------\n    out: Complex128Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n    <Complex128Array>\n    > var z = out.get( 1 )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    -3.0\n\n\n    See Also\n    --------\n    Complex64Array, complex, Complex128","complexarray":"\ncomplexarray( [dtype] )\n    Creates a complex typed array.\n\n    The function supports the following data types:\n\n    - complex128: double-precision complex floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n\n    The default typed array data type is `complex128`.\n\n    Parameters\n    ----------\n    dtype: string (optional)\n        Data type. Default: 'complex128'.\n\n    Returns\n    -------\n    out: ComplexArray\n        A complex number typed array.\n\n    Examples\n    --------\n    > var arr = complexarray()\n    <Complex128Array>\n    > arr = complexarray( 'complex64' )\n    <Complex64Array>\n\n\ncomplexarray( length[, dtype] )\n    Returns a complex number typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Array length.\n\n    dtype: string (optional)\n        Data type. Default: 'complex128'.\n\n    Returns\n    -------\n    out: ComplexArray\n        A complex number typed array.\n\n    Examples\n    --------\n    > var arr = complexarray( 5 )\n    <Complex128Array>\n    > arr = complexarray( 5, 'complex64' )\n    <Complex64Array>\n\n\ncomplexarray( complexarray[, dtype] )\n    Creates a complex number typed array from another complex number typed\n    array.\n\n    Parameters\n    ----------\n    complexarray: ComplexArray\n        Complex number typed array from which to generate another complex number\n        typed array.\n\n    dtype: string (optional)\n        Data type. Default: 'complex128'.\n\n    Returns\n    -------\n    out: ComplexArray\n        A complex number typed array.\n\n    Examples\n    --------\n    > var arr1 = complexarray( [ 0.5, 0.5, 0.5, 0.5 ] );\n    > var arr2 = complexarray( arr1, 'complex64' )\n    <Complex64Array>\n\n\ncomplexarray( obj[, dtype] )\n    Creates a complex number typed array from an array-like object or iterable.\n\n    If an array-like object contains interleaved real and imaginary components,\n    the array-like object must have a length which is a multiple of two.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate an array.\n\n    dtype: string (optional)\n        Data type. Default: 'complex128'.\n\n    Returns\n    -------\n    out: ComplexArray\n        A complex number typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 0.5, 0.5, 0.5, 0.5 ];\n    > var arr2 = complexarray( arr1, 'complex64' )\n    <Complex64Array>\n\n\ncomplexarray( buffer[, byteOffset[, length]][, dtype] )\n    Returns a complex number typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first array element.\n        Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    dtype: string (optional)\n        Data type. Default: 'complex128'.\n\n    Returns\n    -------\n    out: ComplexArray\n        A complex number typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 64 );\n    > var arr = complexarray( buf, 0, 8, 'complex64' )\n    <Complex64Array>\n\n    See Also\n    --------\n    typedarray, realarray\n","complexarrayCtors":"\ncomplexarrayCtors( dtype )\n    Returns a complex typed array constructor.\n\n    The function returns constructors for the following data types:\n\n    - complex64: single-precision floating-point complex numbers.\n    - complex128: double-precision floating-point complex numbers.\n\n    Parameters\n    ----------\n    dtype: string\n        Data type.\n\n    Returns\n    -------\n    out: Function|null\n        Complex typed array constructor.\n\n    Examples\n    --------\n    > var ctor = complexarrayCtors( 'complex64' )\n    <Function>\n    > ctor = complexarrayCtors( 'float32' )\n    null\n\n    See Also\n    --------\n    arrayCtors, typedarrayCtors, realarrayCtors\n","complexarrayDataTypes":"\ncomplexarrayDataTypes()\n    Returns a list of complex typed array data types.\n\n    Returns\n    -------\n    out: Array<string>\n        List of complex typed array data types.\n\n    Examples\n    --------\n    > var out = complexarrayDataTypes()\n    <Array>\n\n    See Also\n    --------\n    arrayDataTypes, typedarrayDataTypes, realarrayDataTypes, ndarrayDataTypes\n","complexCtors":"\ncomplexCtors( dtype )\n    Returns a complex number constructor.\n\n    The function returns constructors for the following data types:\n\n    - complex64: single-precision complex floating-point numbers.\n    - complex128: double-precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    dtype: string\n        Data type.\n\n    Returns\n    -------\n    out: Function|null\n        Constructor.\n\n    Examples\n    --------\n    > var ctor = complexCtors( 'complex128' )\n    <Function>\n    > ctor = complexCtors( 'complex' )\n    null\n\n    See Also\n    --------\n    complexarrayCtors\n","complexDataType":"\ncomplexDataType( value )\n    Returns the data type of a complex number object.\n\n    If provided an argument having an unknown or unsupported type, the function\n    returns `null`.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    out: string|null\n        Data type.\n\n    Examples\n    --------\n    > var v = new Complex128( 1.0, 2.0 );\n    > var dt = complexDataType( v )\n    'complex128'\n    > dt = complexDataType( 'beep' )\n    null\n\n    See Also\n    --------\n    arrayDataType\n","complexDataTypes":"\ncomplexDataTypes()\n    Returns a list of complex number data types.\n\n    The output array contains the following data types:\n\n    - complex64: single-precision complex floating-point numbers.\n    - complex128: double-precision complex floating-point numbers.\n\n    Returns\n    -------\n    out: Array<string>\n        List of complex number data types.\n\n    Examples\n    --------\n    > var out = complexDataTypes()\n    <Array>\n\n    See Also\n    --------\n    complexarrayDataTypes\n","complexPromotionRules":"\ncomplexPromotionRules( [dtype1, dtype2] )\n    Returns the complex number data type with the smallest size and closest\n    \"kind\" to which data types can be safely cast.\n\n    If not provided data types, the function returns a type promotion table.\n\n    If a data type to which data types can be safely cast does *not* exist (or\n    is not supported), the function returns `-1`.\n\n    If provided an unrecognized data type, the function returns `null`.\n\n    Parameters\n    ----------\n    dtype1: string (optional)\n        Data type.\n\n    dtype2: string (optional)\n        Data type.\n\n    Returns\n    -------\n    out: Object|string|integer|null\n        Promotion rule(s).\n\n    Examples\n    --------\n    > var out = complexPromotionRules( 'complex128', 'complex64' )\n    'complex128'\n\n    See Also\n    --------\n    arrayPromotionRules, ndarrayPromotionRules\n","compose":"\ncompose( ...f )\n    Function composition.\n\n    Returns a composite function. Starting from the right, the composite\n    function evaluates each function and passes the result as an argument\n    to the next function. The result of the leftmost function is the result\n    of the whole.\n\n    Notes:\n\n    - Only the rightmost function is explicitly permitted to accept multiple\n      arguments. All other functions are evaluated as unary functions.\n    - The function will throw if provided fewer than two input arguments.\n\n    Parameters\n    ----------\n    f: ...Function\n        Functions to compose.\n\n    Returns\n    -------\n    out: Function\n        Composite function.\n\n    Examples\n    --------\n    > function a( x ) {\n    ...    return 2 * x;\n    ... }\n    > function b( x ) {\n    ...    return x + 3;\n    ... }\n    > function c( x ) {\n    ...    return x / 5;\n    ... }\n    > var f = compose( c, b, a );\n    > var z = f( 6 )\n    3\n\n    See Also\n    --------\n    composeAsync\n","composeAsync":"\ncomposeAsync( ...f )\n    Function composition.\n\n    Returns a composite function. Starting from the right, the composite\n    function evaluates each function and passes the result as the first argument\n    of the next function. The result of the leftmost function is the result\n    of the whole.\n\n    The last argument for each provided function is a `next` callback which\n    should be invoked upon function completion. The callback accepts two\n    arguments:\n\n    - error: error argument.\n    - result: function result.\n\n    If a composed function calls the `next` callback with a truthy `error`\n    argument, the composite function suspends execution and immediately calls\n    the `done` callback for subsequent `error` handling.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Only the rightmost function is explicitly permitted to accept multiple\n    arguments. All other functions are evaluated as binary functions.\n\n    The function will throw if provided fewer than two input arguments.\n\n    Parameters\n    ----------\n    f: ...Function\n        Functions to compose.\n\n    Returns\n    -------\n    out: Function\n        Composite function.\n\n    Examples\n    --------\n    > function a( x, next ) {\n    ...    setTimeout( onTimeout, 0 );\n    ...    function onTimeout() {\n    ...        next( null, 2*x );\n    ...    }\n    ... };\n    > function b( x, next ) {\n    ...    setTimeout( onTimeout, 0 );\n    ...    function onTimeout() {\n    ...        next( null, x+3 );\n    ...    }\n    ... };\n    > function c( x, next ) {\n    ...    setTimeout( onTimeout, 0 );\n    ...    function onTimeout() {\n    ...        next( null, x/5 );\n    ...    }\n    ... };\n    > var f = composeAsync( c, b, a );\n    > function done( error, result ) {\n    ...    if ( error ) {\n    ...        throw error;\n    ...    }\n    ...    console.log( result );\n    ... };\n    > f( 6, done )\n    3\n\n    See Also\n    --------\n    compose\n","configdir":"\nconfigdir( [p] )\n    Returns a directory for user-specific configuration files.\n\n    On Windows platforms, the function first checks for a `LOCALAPPDATA`\n    environment variable before checking for an `APPDATA` environment variable.\n    This means that machine specific user configuration files have precedence\n    over roaming user configuration files.\n\n    On non-Windows platforms, if the function is unable to locate the current\n    user's `home` directory, the function returns `null`. Similarly, on Windows\n    platforms, if the function is unable to locate an application data\n    directory, the function also returns `null`.\n\n    Parameters\n    ----------\n    p: string (optional)\n        Path to append to a base directory.\n\n    Returns\n    -------\n    out: string|null\n        Directory.\n\n    Examples\n    --------\n    > var dir = configdir()\n    e.g., '/Users/<username>/Library/Preferences'\n    > dir = configdir( 'appname/config' )\n    e.g., '/Users/<username>/Library/Preferences/appname/config'\n\n    See Also\n    --------\n    homedir, tmpdir\n","conj":"\nconj( z )\n    Returns the complex conjugate of a double-precision complex floating-point\n    number.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Complex conjugate.\n\n    Examples\n    --------\n    > var z = new Complex128( 5.0, 3.0 );\n    > z.toString()\n    '5 + 3i'\n    > var v = conj( z );\n    > v.toString()\n    '5 - 3i'\n\n    See Also\n    --------\n    imag, real, reim\n","conjf":"\nconjf( z )\n    Returns the complex conjugate of a single-precision complex floating-point\n    number.\n\n    Parameters\n    ----------\n    z: Complex64\n        Complex number.\n\n    Returns\n    -------\n    out: Complex64\n        Complex conjugate.\n\n    Examples\n    --------\n    > var z = new Complex64( 5.0, 3.0 );\n    > z.toString()\n    '5 + 3i'\n    > var v = conjf( z );\n    > v.toString()\n    '5 - 3i'\n\n    See Also\n    --------\n    conj, imagf, realf, reimf\n","constantcase":"\nconstantcase( str )\n    Converts a string to constant case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Constant-cased string.\n\n    Examples\n    --------\n    > var out = constantcase( 'Hello World!' )\n    'HELLO_WORLD'\n    > out = constantcase( 'I am a tiny little teapot' )\n    'I_AM_A_TINY_LITTLE_TEAPOT'\n\n    See Also\n    --------\n    camelcase, kebabcase, pascalcase, snakecase","constantFunction":"\nconstantFunction( val )\n    Creates a function which always returns the same value.\n\n    Notes:\n\n    - When provided an object reference, the returned `function` always returns\n      the same reference.\n\n    Parameters\n    ----------\n    val: any\n        Value to always return.\n\n    Returns\n    -------\n    out: Function\n        Constant function.\n\n    Examples\n    --------\n    > var fcn = constantFunction( 3.14 );\n    > var v = fcn()\n    3.14\n    > v = fcn()\n    3.14\n    > v = fcn()\n    3.14\n\n    See Also\n    --------\n    argumentFunction, identity\n","constantStream":"\nconstantStream( value[, options] )\n    Returns a readable stream which always streams the same value.\n\n    In object mode, `null` is a reserved value. If provided `null`, the\n    returned stream will prematurely end.\n\n    Parameters\n    ----------\n    value: string|Buffer|Uint8Array|any\n        Value to stream.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing streaming.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = constantStream( 'beep', opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nconstantStream.factory( [value, ][options] )\n    Returns a function for creating readable streams which always stream the\n    same value.\n\n    If provided a value to stream, the returned function returns readable always\n    streams the provided value.\n\n    If not provided a value to stream, the returned function requires that a\n    value be provided at each invocation.\n\n    If provided only one argument and that argument is an object (either empty\n    or not containing any recognized options properties), the function treats\n    the argument as a value to be streamed, not as an options argument.\n\n    Parameters\n    ----------\n    value: string|Buffer|Uint8Array|any (optional)\n        Value to stream.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing streaming.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = constantStream.factory( opts );\n\n\nconstantStream.objectMode( value[, options] )\n    Returns an \"objectMode\" readable stream which always streams the same value.\n\n    In object mode, `null` is a reserved value. If provided `null`, the\n    returned stream will prematurely end.\n\n    Parameters\n    ----------\n    value: any\n        Value to stream.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before pausing streaming.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = constantStream.objectMode( 3.14, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    arrayStream, iteratorStream\n","constantStream.factory":"\nconstantStream.factory( [value, ][options] )\n    Returns a function for creating readable streams which always stream the\n    same value.\n\n    If provided a value to stream, the returned function returns readable always\n    streams the provided value.\n\n    If not provided a value to stream, the returned function requires that a\n    value be provided at each invocation.\n\n    If provided only one argument and that argument is an object (either empty\n    or not containing any recognized options properties), the function treats\n    the argument as a value to be streamed, not as an options argument.\n\n    Parameters\n    ----------\n    value: string|Buffer|Uint8Array|any (optional)\n        Value to stream.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing streaming.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = constantStream.factory( opts );","constantStream.objectMode":"\nconstantStream.objectMode( value[, options] )\n    Returns an \"objectMode\" readable stream which always streams the same value.\n\n    In object mode, `null` is a reserved value. If provided `null`, the\n    returned stream will prematurely end.\n\n    Parameters\n    ----------\n    value: any\n        Value to stream.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before pausing streaming.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = constantStream.objectMode( 3.14, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    arrayStream, iteratorStream","constructorName":"\nconstructorName( val )\n    Determines the name of a value's constructor.\n\n    Parameters\n    ----------\n    val: any\n        Input value.\n\n    Returns\n    -------\n    out: string\n        Name of a value's constructor.\n\n    Examples\n    --------\n    > var v = constructorName( 'a' )\n    'String'\n    > v = constructorName( {} )\n    'Object'\n    > v = constructorName( true )\n    'Boolean'\n\n    See Also\n    --------\n    functionName\n","contains":"\ncontains( val, searchValue[, position] )\n    Tests if an array-like value contains a search value.\n\n    When `val` is a string, the function checks whether the characters of the\n    search string are found in the input string. The search is case-sensitive.\n\n    When `val` is an array-like object, the function checks whether the input\n    array contains an element strictly equal to the specified search value.\n\n    For strings, this function is modeled after `String.prototype.includes`,\n    part of the ECMAScript 6 specification. This function is different from a\n    call to `String.prototype.includes.call` insofar as type-checking is\n    performed for all arguments.\n\n    The function does not distinguish between positive and negative zero.\n\n    If `position < 0`, the search is performed for the entire input array or\n    string.\n\n\n    Parameters\n    ----------\n    val: ArrayLike\n        Input value.\n\n    searchValue: any\n        Value to search for.\n\n    position: integer (optional)\n        Position at which to start searching for `searchValue`. Default: `0`.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an input value contains another value.\n\n    Examples\n    --------\n    > var bool = contains( 'Hello World', 'World' )\n    true\n    > bool = contains( 'Hello World', 'world' )\n    false\n    > bool = contains( [ 1, 2, 3, 4 ], 2 )\n    true\n    > bool = contains( [ NaN, 2, 3, 4 ], NaN )\n    true\n\n    // Supply a position:\n    > bool = contains( 'Hello World', 'Hello', 6 )\n    false\n    > bool = contains( [ true, NaN, false ], true, 1 )\n    false\n\n","convertArray":"\nconvertArray( arr, dtype )\n    Converts an input array to an array of a different data type.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject\n        Array to convert.\n\n    dtype: string\n        Output data type.\n\n    Returns\n    -------\n    out: Array|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var arr = [ 1.0, 2.0, 3.0, 4.0 ];\n    > var out = convertArray( arr, 'float32' )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    See Also\n    --------\n    convertArraySame\n","convertArraySame":"\nconvertArraySame( x, y )\n    Converts an input array to the same data type as a second input array.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Array to convert.\n\n    y: Array|TypedArray\n        Array having desired output data type.\n\n    Returns\n    -------\n    out: Array|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n    > var y = new Float32Array( 0 );\n    > var out = convertArraySame( x, y )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    See Also\n    --------\n    convertArray\n","convertPath":"\nconvertPath( from, to )\n    Converts between POSIX and Windows paths.\n\n    Parameters\n    ----------\n    from: string\n        Input path.\n\n    to: string\n        Output path convention: 'win32', 'mixed', or 'posix'.\n\n    Returns\n    -------\n    out: string\n        Converted path.\n\n    Examples\n    --------\n    > var out = convertPath( '/c/foo/bar/beep.c', 'win32' )\n    'c:\\\\foo\\\\bar\\\\beep.c'\n    > out = convertPath( '/c/foo/bar/beep.c', 'mixed' )\n    'c:/foo/bar/beep.c'\n    > out = convertPath( '/c/foo/bar/beep.c', 'posix' )\n    '/c/foo/bar/beep.c'\n    > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'win32' )\n    'C:\\\\\\\\foo\\\\bar\\\\beep.c'\n    > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'mixed' )\n    'C:/foo/bar/beep.c'\n    > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'posix' )\n    '/c/foo/bar/beep.c'\n\n","copy":"\ncopy( value[, level] )\n    Copy or deep clone a value to an arbitrary depth.\n\n    The implementation can handle circular references.\n\n    If a `Number`, `String`, or `Boolean` object is encountered, the value is\n    cloned as a primitive. This behavior is intentional.\n\n    For objects, the implementation only copies enumerable keys and their\n    associated property descriptors.\n\n    The implementation only checks whether basic `Objects`, `Arrays`, and class\n    instances are extensible, sealed, and/or frozen.\n\n    Functions are not cloned; their reference is copied.\n\n    The implementation supports custom error types which are `Error` instances\n    (e.g., ES2015 subclasses).\n\n    Support for copying class instances is inherently fragile. Any instances\n    with privileged access to variables (e.g., within closures) cannot be\n    cloned. This stated, basic copying of class instances is supported. Provided\n    an environment which supports ES5, the implementation is greedy and performs\n    a deep clone of any arbitrary class instance and its properties. The\n    implementation assumes that the concept of `level` applies only to the class\n    instance reference, but not to its internal state.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    level: integer (optional)\n         Copy depth. Default: Infinity.\n\n    Returns\n    -------\n    out: any\n        Value copy.\n\n    Examples\n    --------\n    > var value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\n    > var out = copy( value )\n    [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ]\n    > var bool = ( value[ 0 ].c === out[ 0 ].c )\n    false\n\n    // Set the `level` option to limit the copy depth:\n    > value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\n    > out = copy( value, 1 );\n    > bool = ( value[ 0 ] === out[ 0 ] )\n    true\n    > bool = ( value[ 0 ].c === out[ 0 ].c )\n    true\n\n\n    See Also\n    --------\n    merge\n","copyBuffer":"\ncopyBuffer( buffer )\n    Copies buffer data to a new Buffer instance.\n\n    Parameters\n    ----------\n    buffer: Buffer\n        Buffer to copy from.\n\n    Returns\n    -------\n    out: Buffer\n        Buffer instance.\n\n    Examples\n    --------\n    > var b1 = array2buffer( [ 1, 2, 3, 4 ] );\n    > var b2 = copyBuffer( b1 )\n    <Buffer>[ 1, 2, 3, 4 ]\n\n    See Also\n    --------\n    allocUnsafe, Buffer\n","countBy":"\ncountBy( collection, [options,] indicator )\n    Groups values according to an indicator function and returns group counts.\n\n    When invoked, the indicator function is provided two arguments:\n\n    - value: collection value.\n    - index: collection index.\n\n    The value returned by an indicator function should be a value which can be\n    serialized as an object key.\n\n    If provided an empty collection, the function returns an empty object.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection to group. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Options.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    indicator: Function\n        Indicator function specifying which group an element in the input\n        collection belongs to.\n\n    Returns\n    -------\n    out: Object\n        Group results.\n\n    Examples\n    --------\n    > function indicator( v ) {\n    ...     if ( v[ 0 ] === 'b' ) {\n    ...         return 'b';\n    ...     }\n    ...     return 'other';\n    ... };\n    > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n    > var out = countBy( collection, indicator )\n    { 'b': 3, 'other': 1 }\n\n    See Also\n    --------\n    group, groupBy\n","countByAsync":"\ncountByAsync( collection, [options,] indicator, done )\n    Groups values according to an indicator function and returns group counts.\n\n    When invoked, the indicator function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If the\n    indicator function accepts two arguments, the indicator function is\n    provided:\n\n    - value\n    - next\n\n    If the indicator function accepts three arguments, the indicator function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other indicator function signature, the indicator function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - group: value group.\n\n    If an indicator function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    If provided an empty collection, the function calls the `done` callback with\n    an empty object as the second argument.\n\n    The `group` returned by an indicator function should be a value which can be\n    serialized as an object key.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    indicator: Function\n        Indicator function specifying which group an element in the input\n        collection belongs to.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > countByAsync( arr, indicator, done )\n    1000\n    2500\n    3000\n    { \"even\": 2, \"odd\": 1 }\n\n    // Limit number of concurrent invocations:\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 3000, 2500, 1000 ];\n    > countByAsync( arr, opts, indicator, done )\n    2500\n    3000\n    1000\n    { \"even\": 2, \"odd\": 1 }\n\n    // Process sequentially:\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 3000, 2500, 1000 ];\n    > countByAsync( arr, opts, indicator, done )\n    3000\n    2500\n    1000\n    { \"even\": 2, \"odd\": 1 }\n\n\ncountByAsync.factory( [options,] indicator )\n    Returns a function which groups values according to an indicator function\n    and returns group counts.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    indicator: Function\n        Indicator function specifying which group an element in the input\n        collection belongs to.\n\n    Returns\n    -------\n    out: Function\n        A function which groups values and returns group counts.\n\n    Examples\n    --------\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = countByAsync.factory( opts, indicator );\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    { \"even\": 2, \"odd\": 1 }\n    > arr = [ 2000, 1500, 1000, 500 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    500\n    { \"even\": 2, \"odd\": 2 }\n\n    See Also\n    --------\n    countBy, groupByAsync, tabulateByAsync\n","countByAsync.factory":"\ncountByAsync.factory( [options,] indicator )\n    Returns a function which groups values according to an indicator function\n    and returns group counts.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    indicator: Function\n        Indicator function specifying which group an element in the input\n        collection belongs to.\n\n    Returns\n    -------\n    out: Function\n        A function which groups values and returns group counts.\n\n    Examples\n    --------\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = countByAsync.factory( opts, indicator );\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    { \"even\": 2, \"odd\": 1 }\n    > arr = [ 2000, 1500, 1000, 500 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    500\n    { \"even\": 2, \"odd\": 2 }\n\n    See Also\n    --------\n    countBy, groupByAsync, tabulateByAsync","currentYear":"\ncurrentYear()\n    Returns the current year.\n\n    Returns\n    -------\n    out: integer\n        Current year.\n\n    Examples\n    --------\n    > var y = currentYear()\n    <number>\n\n    See Also\n    --------\n    isCurrentYear\n","curry":"\ncurry( fcn[, arity][, thisArg] )\n    Transforms a function into a sequence of functions each accepting a single\n    argument.\n\n    Until return value resolution, each invocation returns a new partially\n    applied curry function.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to curry.\n\n    arity: integer (optional)\n        Number of parameters. Default: `fcn.length`.\n\n    thisArg: any (optional)\n        Evaluation context.\n\n    Returns\n    -------\n    out: Function\n        Curry function.\n\n    Examples\n    --------\n    > function add( x, y ) { return x + y; };\n    > var f = curry( add );\n    > var sum = f( 2 )( 3 )\n    5\n\n    // Supply arity:\n    > function add() { return arguments[ 0 ] + arguments[ 1 ]; };\n    > f = curry( add, 2 );\n    > sum = f( 2 )( 3 )\n    5\n\n    // Provide function context:\n    > var obj = {\n    ...     'name': 'Ada',\n    ...     'greet': function greet( word1, word2 ) {\n    ...        return word1 + ' ' + word2 + ', ' + this.name + '!'\n    ...     }\n    ... };\n    > f = curry( obj.greet, obj );\n    > var str = f( 'Hello' )( 'there' )\n    'Hello there, Ada!'\n\n    See Also\n    --------\n    curryRight, uncurry, uncurryRight\n","curryRight":"\ncurryRight( fcn[, arity][, thisArg] )\n    Transforms a function into a sequence of functions each accepting a single\n    argument.\n\n    Until return value resolution, each invocation returns a new partially\n    applied curry function.\n\n    This function applies arguments starting from the right.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to curry.\n\n    arity: integer (optional)\n        Number of parameters. Default: `fcn.length`.\n\n    thisArg: any (optional)\n        Evaluation context.\n\n    Returns\n    -------\n    out: Function\n        Curry function.\n\n    Examples\n    --------\n    > function add( x, y ) { return x + y; };\n    > var f = curryRight( add );\n    > var sum = f( 2 )( 3 )\n    5\n\n    // Supply arity:\n    > function add() { return arguments[ 0 ] + arguments[ 1 ]; };\n    > f = curryRight( add, 2 );\n    > sum = f( 2 )( 3 )\n    5\n\n    // Provide function context:\n    > var obj = {\n    ...     'name': 'Ada',\n    ...     'greet': function greet( word1, word2 ) {\n    ...         return word1 + ' ' + word2 + ', ' + this.name + '!'\n    ...     }\n    ... };\n    > f = curryRight( obj.greet, obj );\n    > var str = f( 'there' )( 'Hello' )\n    'Hello there, Ada!'\n\n    See Also\n    --------\n    curry, uncurry, uncurryRight\n","cwd":"\ncwd()\n    Returns the current working directory.\n\n    Returns\n    -------\n    path: string\n        Current working directory of the process.\n\n    Examples\n    --------\n    > var dir = cwd()\n    '/path/to/current/working/directory'\n\n    See Also\n    --------\n    chdir\n","DALE_CHALL_NEW":"\nDALE_CHALL_NEW()\n    Returns a list of familiar English words.\n\n    Returns\n    -------\n    out: Array<string>\n        List of familiar English words.\n\n    Examples\n    --------\n    > var list = DALE_CHALL_NEW()\n    [ 'a', 'able', 'aboard', 'about', 'above', ... ]\n\n    References\n    ----------\n    - Chall, Jeanne Sternlicht, and Edgar Dale. 1995. *Readability revisited:\n    the new Dale-Chall readability formula*. Brookline Books.\n    <https://books.google.com/books?id=2nbuAAAAMAAJ>.\n\n","datasets":"\ndatasets( name[, options] )\n    Returns a dataset.\n\n    The function forwards provided options to the dataset interface specified\n    by `name`.\n\n    Parameters\n    ----------\n    name: string\n        Dataset name.\n\n    options: Object (optional)\n        Function options.\n\n    Returns\n    -------\n    out: any\n        Dataset.\n\n    Examples\n    --------\n    > var out = datasets( 'MONTH_NAMES_EN' )\n    [ 'January', 'February', ... ]\n    > var opts = { 'data': 'cities' };\n    > out = datasets( 'MINARD_NAPOLEONS_MARCH', opts )\n    [ {...}, {...}, ... ]\n\n","DataView":"\nDataView( buffer[, byteOffset[, byteLength]] )\n    Returns a data view representing a provided array buffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer|SharedArrayBuffer\n        Array buffer.\n\n    byteOffset: integer (optional)\n        Offset (in bytes) to the first byte in the array buffer for the new view\n        to reference. Default: 0.\n\n    byteLength: integer (optional)\n        Number of elements in the byte array. If not provided, the view's length\n        will equal the buffer's length.\n\n    Returns\n    -------\n    out: DataView\n        A data view.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 5 )\n    <ArrayBuffer>\n    > var dv = new DataView( buf )\n    <DataView>\n\n\nDataView.prototype.buffer\n    Read-only property which returns the underyling array buffer.\n\n    Examples\n    --------\n    > var buf1 = new ArrayBuffer( 5 );\n    > var dv = new DataView( buf1 );\n    > var buf2 = dv.buffer\n    <ArrayBuffer>\n    > var b = ( buf1 === buf2 )\n    true\n\n\nDataView.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the view.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 5 );\n    > var dv = new DataView( buf );\n    > dv.byteLength\n    5\n\n\nDataView.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the view to the\n    start of the underlying array buffer.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 5 );\n    > var dv = new DataView( buf, 2 );\n    > dv.byteLength\n    3\n    > dv.byteOffset\n    2\n\n\nTODO: document properties/methods\n\n\n    See Also\n    --------\n    ArrayBuffer, typedarray\n","DataView.prototype.buffer":"\nDataView.prototype.buffer\n    Read-only property which returns the underyling array buffer.\n\n    Examples\n    --------\n    > var buf1 = new ArrayBuffer( 5 );\n    > var dv = new DataView( buf1 );\n    > var buf2 = dv.buffer\n    <ArrayBuffer>\n    > var b = ( buf1 === buf2 )\n    true","DataView.prototype.byteLength":"\nDataView.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the view.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 5 );\n    > var dv = new DataView( buf );\n    > dv.byteLength\n    5","DataView.prototype.byteOffset":"\nDataView.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the view to the\n    start of the underlying array buffer.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 5 );\n    > var dv = new DataView( buf, 2 );\n    > dv.byteLength\n    3\n    > dv.byteOffset\n    2","datespace":"\ndatespace( start, stop[, length][ , options] )\n    Generates an array of linearly spaced dates.\n\n    Parameters\n    ----------\n    start: number\n        Start time as either a `Date` object, Unix timestamp, JavaScript\n        timestamp, or date string.\n\n    stop: number\n        Stop time as either a `Date` object, Unix timestamp, JavaScript\n        timestamp, or date string.\n\n    length: integer (optional)\n        Length of output array. Default: `100`.\n\n    options: Object (optional)\n        Options.\n\n    options.round: string (optional)\n        Specifies how sub-millisecond times should be rounded:\n        [ 'floor', 'ceil', 'round' ]. Default: 'floor'.\n\n    Returns\n    -------\n    arr: Array\n        Array of dates.\n\n    Examples\n    --------\n    > var stop = '2014-12-02T07:00:54.973Z';\n    > var start = new Date( stop ) - 60000;\n    > var arr = datespace( start, stop, 6 )\n    [...]\n\n    // Equivalent of Math.ceil():\n    > var opts = { 'round': 'ceil' };\n    > arr = datespace( 1417503655000, 1417503655001, 3, opts )\n    [...]\n\n    See Also\n    --------\n    linspace, logspace\n","dayOfQuarter":"\ndayOfQuarter( [month[, day, year]] )\n    Returns the day of the quarter.\n\n    By default, the function returns the day of the quarter for the current date\n    (according to local time). To determine the day of the quarter for a\n    particular day, provide `month`, `day`, and `year` arguments.\n\n    A `month` may be either a month's integer value, three letter abbreviation,\n    or full name (case insensitive).\n\n    The function also accepts a `Date` object.\n\n    Parameters\n    ----------\n    month: string|integer|Date (optional)\n        Month (or `Date`).\n\n    day: integer (optional)\n        Day.\n\n    year: integer (optional)\n        Year.\n\n    Returns\n    -------\n    out: integer\n        Day of the quarter.\n\n    Examples\n    --------\n    > var day = dayOfQuarter()\n    <number>\n    > day = dayOfQuarter( new Date() )\n    <number>\n    > day = dayOfQuarter( 12, 31, 2017 )\n    92\n\n    // Other ways to supply month:\n    > day = dayOfQuarter( 'dec', 31, 2017 )\n    92\n    > day = dayOfQuarter( 'december', 31, 2017 )\n    92\n\n    See Also\n    --------\n    dayOfYear\n","dayOfYear":"\ndayOfYear( [month[, day, year]] )\n    Returns the day of the year.\n\n    By default, the function returns the day of the year for the current date\n    (according to local time). To determine the day of the year for a particular\n    day, provide `month`, `day`, and `year` arguments.\n\n    A `month` may be either a month's integer value, three letter abbreviation,\n    or full name (case insensitive).\n\n    The function also accepts a `Date` object.\n\n    Parameters\n    ----------\n    month: string|integer|Date (optional)\n        Month (or `Date`).\n\n    day: integer (optional)\n        Day.\n\n    year: integer (optional)\n        Year.\n\n    Returns\n    -------\n    out: integer\n        Day of the year.\n\n    Examples\n    --------\n    > var day = dayOfYear()\n    <number>\n    > day = dayOfYear( new Date() )\n    <number>\n    > day = dayOfYear( 12, 31, 2016 )\n    366\n\n    // Other ways to supply month:\n    > day = dayOfYear( 'dec', 31, 2016 )\n    366\n    > day = dayOfYear( 'december', 31, 2016 )\n    366\n\n    See Also\n    --------\n    dayOfQuarter\n","daysInMonth":"\ndaysInMonth( [month[, year]] )\n    Returns the number of days in a month.\n\n    By default, the function returns the number of days in the current month\n    of the current year (according to local time). To determine the number of\n    days for a particular month and year, provide `month` and `year` arguments.\n\n    A `month` may be either a month's integer value, three letter abbreviation,\n    or full name (case insensitive).\n\n    The function's return value is a generalization and does **not** take into\n    account inaccuracies due to daylight savings conventions, crossing\n    timezones, or other complications with time and dates.\n\n    Parameters\n    ----------\n    month: string|integer|Date (optional)\n        Month (or `Date`).\n\n    year: integer (optional)\n        Year.\n\n    Returns\n    -------\n    out: integer\n        Days in a month.\n\n    Examples\n    --------\n    > var num = daysInMonth()\n    <number>\n    > num = daysInMonth( 2 )\n    <number>\n    > num = daysInMonth( 2, 2016 )\n    29\n    > num = daysInMonth( 2, 2017 )\n    28\n\n    // Other ways to supply month:\n    > num = daysInMonth( 'feb', 2016 )\n    29\n    > num = daysInMonth( 'february', 2016 )\n    29\n\n    See Also\n    --------\n    daysInYear\n","daysInYear":"\ndaysInYear( [value] )\n    Returns the number of days in a year according to the Gregorian calendar.\n\n    By default, the function returns the number of days in the current year\n    (according to local time). To determine the number of days for a particular\n    year, provide either a year or a `Date` object.\n\n    The function's return value is a generalization and does **not** take into\n    account inaccuracies due to daylight savings conventions, crossing\n    timezones, or other complications with time and dates.\n\n    Parameters\n    ----------\n    value: integer|Date (optional)\n        Year or `Date` object.\n\n    Returns\n    -------\n    out: integer\n        Number of days in a year.\n\n    Examples\n    --------\n    > var num = daysInYear()\n    <number>\n    > num = daysInYear( 2016 )\n    366\n    > num = daysInYear( 2017 )\n    365\n\n    See Also\n    --------\n    daysInMonth\n","ddot":"\nddot( x, y[, dim] )\n    Computes the dot product of two double-precision floating-point vectors.\n\n    If provided at least one input array having more than one dimension, the\n    input arrays are broadcasted to a common shape.\n\n    For multi-dimensional input arrays, the function performs batched\n    computation, such that the function computes the dot product for each pair\n    of vectors in `x` and `y` according to the specified dimension index.\n\n    The size of the contracted dimension must be the same for both input arrays.\n\n    The function resolves the dimension index for which to compute the dot\n    product *before* broadcasting.\n\n    If provided empty vectors, the dot product is `0`.\n\n    Parameters\n    ----------\n    x: ndarray\n        First input array. Must have a 'float64' data type. Must have at least\n        one dimension and be broadcast-compatible with the second input array.\n\n    y: ndarray\n        Second input array. Must have a 'float64' data type. Must have at least\n        one dimension and be broadcast-compatible with the first input array.\n\n    dim: integer (optional)\n        Dimension index for which to compute the dot product. Must be a negative\n        integer. Negative indices are resolved relative to the last array\n        dimension, with the last dimension corresponding to `-1`. Default: -1.\n\n    Returns\n    -------\n    out: ndarray\n        The dot product. The output array has the same data type as the input\n        arrays and has a shape which is determined by broadcasting and excludes\n        the contracted dimension.\n\n    Examples\n    --------\n    > var xbuf = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var x = array( xbuf );\n    > var ybuf = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var y = array( ybuf );\n    > var z = ddot( x, y )\n    <ndarray>\n    > z.get()\n    -5.0\n\n    See Also\n    --------\n    base.strided.ddot, gdot, sdot\n","debugSinkStream":"\ndebugSinkStream( [options,] [clbk] )\n    Returns a writable stream for debugging stream pipelines.\n\n    If the `DEBUG` environment variable is not set, no data is logged.\n\n    Providing a `name` option is *strongly* encouraged, as the `DEBUG`\n    environment variable can be used to filter debuggers.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Debug namespace.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to encode strings as `Buffer` objects before writing\n        data to a returned stream. Default: true.\n\n    options.defaultEncoding: string (optional)\n        Default encoding when not explicitly specified when writing data.\n        Default: 'utf8'.\n\n    clbk: Function (optional)\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: WritableStream\n        Writable stream.\n\n    Examples\n    --------\n    > var s = debugSinkStream( { 'name': 'foo' } );\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();\n\n\ndebugSinkStream.factory( [options] )\n    Returns a function for creating writable streams for debugging stream\n    pipelines.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to encode strings as `Buffer` objects before writing\n        data to a returned stream. Default: true.\n\n    options.defaultEncoding: string (optional)\n        Default encoding when not explicitly specified when writing data.\n        Default: 'utf8'.\n\n    Returns\n    -------\n    createStream( name[, clbk] ): Function\n        Function for creating writable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = debugSinkStream.factory( opts );\n\n\ndebugSinkStream.objectMode( [options,] [clbk] )\n    Returns an \"objectMode\" writable stream for debugging stream pipelines.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Debug namespace.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to encode strings as `Buffer` objects before writing\n        data to a returned stream. Default: true.\n\n    options.defaultEncoding: string (optional)\n        Default encoding when not explicitly specified when writing data.\n        Default: 'utf8'.\n\n    clbk: Function (optional)\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: WritableStream\n        Writable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > var s = debugSinkStream.objectMode( { 'name': 'foo' } );\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();\n\n    See Also\n    --------\n    debugStream, inspectSinkStream\n","debugSinkStream.factory":"\ndebugSinkStream.factory( [options] )\n    Returns a function for creating writable streams for debugging stream\n    pipelines.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to encode strings as `Buffer` objects before writing\n        data to a returned stream. Default: true.\n\n    options.defaultEncoding: string (optional)\n        Default encoding when not explicitly specified when writing data.\n        Default: 'utf8'.\n\n    Returns\n    -------\n    createStream( name[, clbk] ): Function\n        Function for creating writable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = debugSinkStream.factory( opts );","debugSinkStream.objectMode":"\ndebugSinkStream.objectMode( [options,] [clbk] )\n    Returns an \"objectMode\" writable stream for debugging stream pipelines.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Debug namespace.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to encode strings as `Buffer` objects before writing\n        data to a returned stream. Default: true.\n\n    options.defaultEncoding: string (optional)\n        Default encoding when not explicitly specified when writing data.\n        Default: 'utf8'.\n\n    clbk: Function (optional)\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: WritableStream\n        Writable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > var s = debugSinkStream.objectMode( { 'name': 'foo' } );\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();\n\n    See Also\n    --------\n    debugStream, inspectSinkStream","debugStream":"\ndebugStream( [options,] [clbk] )\n    Returns a transform stream for debugging stream pipelines.\n\n    If the `DEBUG` environment variable is not set, no data is logged.\n\n    Providing a `name` option is *strongly* encouraged, as the `DEBUG`\n    environment variable can be used to filter debuggers.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Debug namespace.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    clbk: Function (optional)\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream.\n\n    Examples\n    --------\n    > var s = debugStream( { 'name': 'foo' } );\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();\n\n\ndebugStream.factory( [options] )\n    Returns a function for creating transform streams for debugging stream\n    pipelines.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    createStream( name[, clbk] ): Function\n        Function for creating transform streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = debugStream.factory( opts );\n\n\ndebugStream.objectMode( [options,] [clbk] )\n    Returns an \"objectMode\" transform stream for debugging stream pipelines.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Debug namespace.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    clbk: Function (optional)\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > var s = debugStream.objectMode( { 'name': 'foo' } );\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();\n\n    See Also\n    --------\n    debugSinkStream, inspectStream\n","debugStream.factory":"\ndebugStream.factory( [options] )\n    Returns a function for creating transform streams for debugging stream\n    pipelines.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    createStream( name[, clbk] ): Function\n        Function for creating transform streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = debugStream.factory( opts );","debugStream.objectMode":"\ndebugStream.objectMode( [options,] [clbk] )\n    Returns an \"objectMode\" transform stream for debugging stream pipelines.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Debug namespace.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    clbk: Function (optional)\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > var s = debugStream.objectMode( { 'name': 'foo' } );\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();\n\n    See Also\n    --------\n    debugSinkStream, inspectStream","decorateAfter":"\ndecorateAfter( fcn, arity, after[, thisArg] )\n    Decorates a provided function such that the function's return value is\n    provided as an argument to another function.\n\n    Decorators are intended to be transparent, meaning that, when interfacing\n    with an API, the decorated API should have the same signature (i.e., number\n    of parameters) as the decorated function.\n\n    Thus, a typical value for `arity` is `fcn.length`. This function does not\n    require equality, however, and the `arity` argument is allowed to diverge\n    from that of the decorated function. Specifying a differing `arity` does\n    *not* affect function evaluation behavior, as the returned function passes\n    all provided arguments to the decorated function.\n\n    If the `after` function returns `undefined`, the returned decorator returns\n    the return value of the decorated function `fcn`; otherwise, the returned\n    decorator returns the return value of `after`.\n\n    The returned decorator supports an `arity` less than or equal to `10` (i.e.,\n    the maximum arity of the returned function is `10`). For an arity greater\n    than `10`, the returned function has an arity equal to `0`. While this\n    violates strict notions of a decorator, for all practical purposes, this is\n    unlikely to be an issue, as the vast majority of functions have fewer than\n    `10` parameters and the need for explicitly checking function length is\n    relatively uncommon.\n\n    Common use cases for decorating a function with additional actions *after*\n    invocation include logging, capturing invocation statistics, and validating\n    return values.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to decorate.\n\n    arity: integer\n        Number of parameters.\n\n    after: Function\n        Function with which to invoke the return value of the decorated\n        function.\n\n    thisArg: any (optional)\n        Evaluation context for `after`.\n\n    Returns\n    -------\n    out: Function\n        Decorator function.\n\n    Examples\n    --------\n    > function f( v ) { return -v; };\n    > var fcn = decorateAfter( base.abs, 1, f );\n    > var v = fcn( -5 )\n    -5\n    > v = fcn( 5 )\n    -5\n\n\ndecorateAfter.factory( fcn, arity, after[, thisArg] )\n    Uses code generation to decorate a provided function such that the\n    function's return value is provided as an argument to another function.\n\n    Code generation may be problematic in browser contexts enforcing a strict\n    content security policy] (CSP). If running in or targeting an environment\n    with a CSP, avoid using code generation.\n\n    For non-native functions, the function supports returning a decorator whose\n    API exactly matches the API of the decorated function, including function\n    length and parameter names.\n\n    For native functions, due to how native functions serialize to strings, the\n    function generates placeholder parameter names, which are unlikely to match\n    the canonical parameter names. Using placeholder parameter names ensures\n    that the length of the decorator (i.e., number of parameters) matches the\n    decorated function and, except in scenarios involving function source code\n    inspection, will not affect runtime behavior.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to decorate.\n\n    arity: integer\n        Number of parameters.\n\n    after: Function\n        Function with which to invoke the return value of the decorated\n        function.\n\n    thisArg: any (optional)\n        Evaluation context for `after`.\n\n    Returns\n    -------\n    out: Function\n        Decorator function.\n\n    Examples\n    --------\n    > function f( v ) { return -v; };\n    > var fcn = decorateAfter.factory( base.abs, 1, f );\n    > var v = fcn( -5 )\n    -5\n    > v = fcn( 5 )\n    -5\n\n","decorateAfter.factory":"\ndecorateAfter.factory( fcn, arity, after[, thisArg] )\n    Uses code generation to decorate a provided function such that the\n    function's return value is provided as an argument to another function.\n\n    Code generation may be problematic in browser contexts enforcing a strict\n    content security policy] (CSP). If running in or targeting an environment\n    with a CSP, avoid using code generation.\n\n    For non-native functions, the function supports returning a decorator whose\n    API exactly matches the API of the decorated function, including function\n    length and parameter names.\n\n    For native functions, due to how native functions serialize to strings, the\n    function generates placeholder parameter names, which are unlikely to match\n    the canonical parameter names. Using placeholder parameter names ensures\n    that the length of the decorator (i.e., number of parameters) matches the\n    decorated function and, except in scenarios involving function source code\n    inspection, will not affect runtime behavior.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to decorate.\n\n    arity: integer\n        Number of parameters.\n\n    after: Function\n        Function with which to invoke the return value of the decorated\n        function.\n\n    thisArg: any (optional)\n        Evaluation context for `after`.\n\n    Returns\n    -------\n    out: Function\n        Decorator function.\n\n    Examples\n    --------\n    > function f( v ) { return -v; };\n    > var fcn = decorateAfter.factory( base.abs, 1, f );\n    > var v = fcn( -5 )\n    -5\n    > v = fcn( 5 )\n    -5","deepEqual":"\ndeepEqual( a, b )\n    Tests for deep equality between two values.\n\n    Parameters\n    ----------\n    a: any\n        First comparison value.\n\n    b: any\n        Second comparison value.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating if `a` is deep equal to `b`.\n\n    Examples\n    --------\n    > var bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, 3 ] )\n    true\n\n    > bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, '3' ] )\n    false\n\n    > bool = deepEqual( { 'a': 2 }, { 'a': [ 2 ] } )\n    false\n\n    See Also\n    --------\n    isStrictEqual, isSameValue\n","deepGet":"\ndeepGet( obj, path[, options] )\n    Returns a nested property value.\n\n    Parameters\n    ----------\n    obj: ObjectLike\n        Input object.\n\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    out: any\n        Nested property value.\n\n    Examples\n    --------\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var val = deepGet( obj, 'a.b.c' )\n    'd'\n\n    // Specify a custom separator via the `sep` option:\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var val = deepGet( obj, 'a/b/c', { 'sep': '/' } )\n    'd'\n\ndeepGet.factory( path[, options] )\n    Creates a reusable deep get function.\n\n    Parameters\n    ----------\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    out: Function\n        Deep get factory.\n\n    Examples\n    --------\n    > var dget = deepGet.factory( 'a/b/c', { 'sep': '/' } );\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var val = dget( obj )\n    'd'\n\n    See Also\n    --------\n    deepPluck, deepSet\n","deepGet.factory":"\ndeepGet.factory( path[, options] )\n    Creates a reusable deep get function.\n\n    Parameters\n    ----------\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    out: Function\n        Deep get factory.\n\n    Examples\n    --------\n    > var dget = deepGet.factory( 'a/b/c', { 'sep': '/' } );\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var val = dget( obj )\n    'd'\n\n    See Also\n    --------\n    deepPluck, deepSet","deepHasOwnProp":"\ndeepHasOwnProp( value, path[, options] )\n    Returns a boolean indicating whether an object contains a nested key path.\n\n    The function tests for \"own\" properties and will return `false` for\n    inherited properties.\n\n    Value arguments other than `null` or `undefined` are coerced to objects.\n\n    Key path array elements are coerced to strings.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object has a specified path.\n\n    Examples\n    --------\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var bool = deepHasOwnProp( obj, 'a.b.c' )\n    true\n\n    // Specify a custom separator via the `sep` option:\n    > obj = { 'a': { 'b': { 'c': 'd' } } };\n    > bool = deepHasOwnProp( obj, 'a/b/c', { 'sep': '/' } )\n    true\n\ndeepHasOwnProp.factory( path[, options] )\n    Returns a function which tests whether an object contains a nested key path.\n\n    The returned function tests for \"own\" properties and will return `false` for\n    inherited properties.\n\n    Parameters\n    ----------\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    out: Function\n        Function which tests whether an object contains a nested key path.\n\n    Examples\n    --------\n    > var has = deepHasOwnProp.factory( 'a/b/c', { 'sep': '/' } );\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var bool = has( obj )\n    true\n\n    See Also\n    --------\n    deepHasProp, hasOwnProp, deepGet, deepPluck, deepSet\n","deepHasOwnProp.factory":"\ndeepHasOwnProp.factory( path[, options] )\n    Returns a function which tests whether an object contains a nested key path.\n\n    The returned function tests for \"own\" properties and will return `false` for\n    inherited properties.\n\n    Parameters\n    ----------\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    out: Function\n        Function which tests whether an object contains a nested key path.\n\n    Examples\n    --------\n    > var has = deepHasOwnProp.factory( 'a/b/c', { 'sep': '/' } );\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var bool = has( obj )\n    true\n\n    See Also\n    --------\n    deepHasProp, hasOwnProp, deepGet, deepPluck, deepSet","deepHasProp":"\ndeepHasProp( value, path[, options] )\n    Returns a boolean indicating whether an object contains a nested key path,\n    either own or inherited.\n\n    Value arguments other than `null` or `undefined` are coerced to objects.\n\n    Key path array elements are coerced to strings.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object has a specified path.\n\n    Examples\n    --------\n    > function Foo() { return this; };\n    > Foo.prototype.b = { 'c': 'd' };\n    > var obj = { 'a': new Foo() };\n    > var bool = deepHasProp( obj, 'a.b.c' )\n    true\n\n    // Specify a custom separator via the `sep` option:\n    > bool = deepHasProp( obj, 'a/b/c', { 'sep': '/' } )\n    true\n\ndeepHasProp.factory( path[, options] )\n    Returns a function which tests whether an object contains a nested key path,\n    either own or inherited.\n\n    Parameters\n    ----------\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    out: Function\n        Function which tests whether an object contains a nested key path.\n\n    Examples\n    --------\n    > function Foo() { return this; };\n    > Foo.prototype.b = { 'c': 'd' };\n    > var has = deepHasProp.factory( 'a/b/c', { 'sep': '/' } );\n    > var obj = { 'a': new Foo() };\n    > var bool = has( obj )\n    true\n\n    See Also\n    --------\n    deepHasOwnProp, hasOwnProp, deepGet, deepPluck, deepSet\n","deepHasProp.factory":"\ndeepHasProp.factory( path[, options] )\n    Returns a function which tests whether an object contains a nested key path,\n    either own or inherited.\n\n    Parameters\n    ----------\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    out: Function\n        Function which tests whether an object contains a nested key path.\n\n    Examples\n    --------\n    > function Foo() { return this; };\n    > Foo.prototype.b = { 'c': 'd' };\n    > var has = deepHasProp.factory( 'a/b/c', { 'sep': '/' } );\n    > var obj = { 'a': new Foo() };\n    > var bool = has( obj )\n    true\n\n    See Also\n    --------\n    deepHasOwnProp, hasOwnProp, deepGet, deepPluck, deepSet","deepPluck":"\ndeepPluck( arr, path[, options] )\n    Extracts a nested property value from each element of an object array.\n\n    If a key path does not exist, the function sets the plucked value as\n    `undefined`.\n\n    Extracted values are not cloned.\n\n    Parameters\n    ----------\n    arr: Array\n        Source array.\n\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to return a new data structure. Default:\n        true.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    out: Array\n        Destination array.\n\n    Examples\n    --------\n    > var arr = [\n    ...     { 'a': { 'b': { 'c': 1 } } },\n    ...     { 'a': { 'b': { 'c': 2 } } }\n    ... ];\n    > var out = deepPluck( arr, 'a.b.c' )\n    [ 1, 2 ]\n    > arr = [\n    ...     { 'a': [ 0, 1, 2 ] },\n    ...     { 'a': [ 3, 4, 5 ] }\n    ... ];\n    > out = deepPluck( arr, [ 'a', 1 ] )\n    [ 1, 4 ]\n\n    See Also\n    --------\n    deepGet, deepSet\n","deepSet":"\ndeepSet( obj, path, value[, options] )\n    Sets a nested property value.\n\n    Parameters\n    ----------\n    obj: ObjectLike\n        Input object.\n\n    path: string|Array\n        Key path.\n\n    value: any\n        Value to set.\n\n    options: Object (optional)\n        Options.\n\n    options.create: boolean (optional)\n        Boolean indicating whether to create a path if the key path does not\n        already exist. Default: false.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if the property was successfully set.\n\n    Examples\n    --------\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var bool = deepSet( obj, 'a.b.c', 'beep' )\n    true\n\n    // Specify an alternative separator via the sep option:\n    > obj = { 'a': { 'b': { 'c': 'd' } } };\n    > bool = deepSet( obj, 'a/b/c', 'beep', { 'sep': '/' } );\n    > obj\n    { 'a': { 'b': { 'c': 'beep' } } }\n\n    // To create a key path which does not exist, set the create option to true:\n    > bool = deepSet( obj, 'a.e.c', 'boop', { 'create': true } );\n    > obj\n    { 'a': { 'b': { 'c': 'beep' }, 'e': { 'c': 'boop' } } }\n\n\ndeepSet.factory( path[, options] )\n    Creates a reusable deep set function.\n\n    Parameters\n    ----------\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.create: boolean (optional)\n        Boolean indicating whether to create a path if the key path does not\n        already exist. Default: false.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    out: Function\n        Deep get function.\n\n    Examples\n    --------\n    > var dset = deepSet.factory( 'a/b/c', {\n    ...     'create': true,\n    ...     'sep': '/'\n    ... });\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var bool = dset( obj, 'beep' )\n    true\n    > obj\n    { 'a': { 'b': { 'c': 'beep' } } }\n\n    See Also\n    --------\n    deepGet, deepPluck\n","deepSet.factory":"\ndeepSet.factory( path[, options] )\n    Creates a reusable deep set function.\n\n    Parameters\n    ----------\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.create: boolean (optional)\n        Boolean indicating whether to create a path if the key path does not\n        already exist. Default: false.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    out: Function\n        Deep get function.\n\n    Examples\n    --------\n    > var dset = deepSet.factory( 'a/b/c', {\n    ...     'create': true,\n    ...     'sep': '/'\n    ... });\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var bool = dset( obj, 'beep' )\n    true\n    > obj\n    { 'a': { 'b': { 'c': 'beep' } } }\n\n    See Also\n    --------\n    deepGet, deepPluck","defineMemoizedProperty":"\ndefineMemoizedProperty( obj, prop, descriptor )\n    Defines a memoized object property.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    descriptor: Object\n        Property descriptor.\n\n    descriptor.configurable: boolean (optional)\n        Boolean indicating if property descriptor can be changed and if the\n        property can be deleted from the provided object. Default: false.\n\n    descriptor.enumerable: boolean (optional)\n        Boolean indicating if the property shows up when enumerating object\n        properties. Default: false.\n\n    descriptor.writable: boolean (optional)\n        Boolean indicating if the value associated with the property can be\n        changed with an assignment operator. Default: false.\n\n    descriptor.value: Function\n        Synchronous function whose return value will be memoized and set as the\n        property value.\n\n    Examples\n    --------\n    > var obj = {};\n    > function foo() {\n    ...     return 'bar';\n    ... };\n    > defineMemoizedProperty( obj, 'foo', {\n    ...     'configurable': false,\n    ...     'enumerable': true,\n    ...     'writable': false,\n    ...     'value': foo\n    ... });\n    > obj.foo\n    'bar'\n\n    See Also\n    --------\n    setMemoizedReadOnly, defineProperty\n","defineProperties":"\ndefineProperties( obj, properties )\n    Defines (and/or modifies) object properties.\n\n    The second argument is an object whose own enumerable property values are\n    descriptors for the properties to be defined or modified.\n\n    Property descriptors come in two flavors: data descriptors and accessor\n    descriptors. A data descriptor is a property that has a value, which may or\n    may not be writable. An accessor descriptor is a property described by a\n    getter-setter function pair. A descriptor must be one of these two flavors\n    and cannot be both.\n\n    A property descriptor has the following optional properties:\n\n    - configurable: boolean indicating if property descriptor can be changed and\n    if the property can be deleted from the provided object. Default: false.\n\n    - enumerable: boolean indicating if the property shows up when enumerating\n    object properties. Default: false.\n\n    - writable: boolean indicating if the value associated with the property can\n    be changed with an assignment operator. Default: false.\n\n    - value: property value.\n\n    - get: function which serves as a getter for the property, or, if no getter,\n    undefined. When the property is accessed, a getter function is called\n    without arguments and with the `this` context set to the object through\n    which the property is accessed (which may not be the object on which the\n    property is defined due to inheritance). The return value will be used as\n    the property value. Default: undefined.\n\n    - set: function which serves as a setter for the property, or, if no setter,\n    undefined. When assigning a property value, a setter function is called with\n    one argument (the value being assigned to the property) and with the `this`\n    context set to the object through which the property is assigned. Default: undefined.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the properties.\n\n    properties: Object\n        Object with property descriptors.\n\n    Returns\n    -------\n    obj: Object\n        Object on which properties were defined (and/or modified).\n\n    Examples\n    --------\n    > var obj = {};\n    > defineProperties( obj, {\n    ...     'foo': {\n    ...         'value': 'bar',\n    ...         'writable': false,\n    ...         'configurable': false,\n    ...         'enumerable': true\n    ...     },\n    ...     'baz': {\n    ...         'value': 13\n    ...     }\n    ... });\n    > obj.foo\n    'bar'\n    > obj.baz\n    13\n\n    See Also\n    --------\n    defineProperty, setReadOnly\n","defineProperty":"\ndefineProperty( obj, prop, descriptor )\n    Defines (or modifies) an object property.\n\n    Property descriptors come in two flavors: data descriptors and accessor\n    descriptors. A data descriptor is a property that has a value, which may or\n    may not be writable. An accessor descriptor is a property described by a\n    getter-setter function pair. A descriptor must be one of these two flavors\n    and cannot be both.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    descriptor: Object\n        Property descriptor.\n\n    descriptor.configurable: boolean (optional)\n        Boolean indicating if property descriptor can be changed and if the\n        property can be deleted from the provided object. Default: false.\n\n    descriptor.enumerable: boolean (optional)\n        Boolean indicating if the property shows up when enumerating object\n        properties. Default: false.\n\n    descriptor.writable: boolean (optional)\n        Boolean indicating if the value associated with the property can be\n        changed with an assignment operator. Default: false.\n\n    descriptor.value: any (optional)\n        Property value.\n\n    descriptor.get: Function|void (optional)\n        Function which serves as a getter for the property, or, if no getter,\n        undefined. When the property is accessed, a getter function is called\n        without arguments and with the `this` context set to the object through\n        which the property is accessed (which may not be the object on which the\n        property is defined due to inheritance). The return value will be used\n        as the property value. Default: undefined.\n\n    descriptor.set: Function|void (optional)\n        Function which serves as a setter for the property, or, if no setter,\n        undefined. When assigning a property value, a setter function is called\n        with one argument (the value being assigned to the property) and with\n        the `this` context set to the object through which the property is\n        assigned. Default: undefined.\n\n    Returns\n    -------\n    obj: Object\n        Object on which the property was defined (or modified).\n\n    Examples\n    --------\n    > var obj = {};\n    > defineProperty( obj, 'foo', {\n    ...     'value': 'bar',\n    ...     'enumerable': true,\n    ...     'writable': false\n    ... });\n    > obj.foo = 'boop';\n    > obj\n    { 'foo': 'bar' }\n\n    See Also\n    --------\n    defineProperties, setReadOnly\n","dirname":"\ndirname( path )\n    Returns a directory name.\n\n    Parameters\n    ----------\n    path: string\n        Path.\n\n    Returns\n    -------\n    out: string\n        Directory name.\n\n    Examples\n    --------\n    > var dir = dirname( './foo/bar/index.js' )\n    './foo/bar'\n\n    See Also\n    --------\n    extname\n","dotcase":"\ndotcase( str )\n    Converts a string to dot case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Dot-cased string.\n\n    Examples\n    --------\n    > var out = dotcase( 'Hello World!' )\n    'hello.world'\n    > out = dotcase( 'beep boop' )\n    'beep.boop'\n\n    See Also\n    --------\n    camelcase, kebabcase, pascalcase, snakecase","DoublyLinkedList":"\nDoublyLinkedList()\n    Doubly linked list constructor.\n\n    Returns\n    -------\n    list: Object\n        Doubly linked list.\n\n    list.clear: Function\n        Clears the list.\n\n    list.first: Function\n        Returns the first list node. If the list is empty, the returned value is\n        `undefined`.\n\n    list.insert: Function\n        Inserts a value after a provided list node. For its third argument, the\n        method accepts a location: 'before' or 'after'. Default: 'after'.\n\n    list.iterator: Function\n        Returns an iterator for iterating over a list. If an environment\n        supports Symbol.iterator, the returned iterator is iterable. Note that,\n        in order to prevent confusion arising from list mutation during\n        iteration, a returned iterator **always** iterates over a list\n        \"snapshot\", which is defined as the list of list elements at the time\n        of the method's invocation. For its sole argument, the method accepts a\n        direction: 'forward' or 'reverse'. Default: 'forward'.\n\n    list.last: Function\n        Returns the last list node. If the list is empty, the returned value is\n        `undefined`.\n\n    list.length: integer\n        List length.\n\n    list.pop: Function\n        Removes and returns the last list value. If the list is empty, the\n        returned value is `undefined`.\n\n    list.push: Function\n        Adds a value to the end of the list.\n\n    list.remove: Function\n        Removes a list node from the list.\n\n    list.shift: Function\n        Removes and returns the first list value. If the list is empty, the\n        returned value is `undefined`.\n\n    list.toArray: Function\n        Returns an array of list values.\n\n    list.toJSON: Function\n        Serializes a list as JSON.\n\n    list.unshift: Function\n        Adds a value to the beginning of the list.\n\n    Examples\n    --------\n    > var list = DoublyLinkedList();\n    > list.push( 'foo' ).push( 'bar' );\n    > list.length\n    2\n    > list.pop()\n    'bar'\n    > list.length\n    1\n    > list.pop()\n    'foo'\n    > list.length\n    0\n\n    See Also\n    --------\n    LinkedList, Stack\n","doUntil":"\ndoUntil( fcn, predicate[, thisArg] )\n    Invokes a function until a test condition is true.\n\n    The condition is evaluated *after* executing the provided function; thus,\n    `fcn` *always* executes at least once.\n\n    When invoked, both the predicate function and the function to invoke are\n    provided a single argument:\n\n    - i: iteration number (starting from zero).\n\n    Parameters\n    ----------\n    fcn: Function\n        The function to invoke.\n\n    predicate: Function\n        The predicate function which indicates whether to stop invoking a\n        function.\n\n    thisArg: any (optional)\n        Execution context for the invoked function.\n\n    Examples\n    --------\n    > function predicate( i ) { return ( i >= 5 ); };\n    > function beep( i ) { console.log( 'boop: %d', i ); };\n    > doUntil( beep, predicate )\n    boop: 0\n    boop: 1\n    boop: 2\n    boop: 3\n    boop: 4\n\n    See Also\n    --------\n    doUntilAsync, doUntilEach, doWhile, until, whilst\n","doUntilAsync":"\ndoUntilAsync( fcn, predicate, done[, thisArg] )\n    Invokes a function until a test condition is true.\n\n    The condition is evaluated *after* executing the provided function; thus,\n    `fcn` *always* executes at least once.\n\n    The function to invoke is provided two arguments:\n\n    - i: iteration number (starting from zero).\n    - next: a callback which must be invoked before proceeding to the next\n      iteration.\n\n    The first argument of the `next` callback is an `error` argument. If `fcn`\n    calls the `next` callback with a truthy `error` argument, the function\n    suspends execution and immediately calls the `done` callback for subsequent\n    `error` handling.\n\n    The predicate function is provided two arguments:\n\n    - i: iteration number (starting from one).\n    - clbk: a callback indicating whether to invoke `fcn`.\n\n    The `clbk` function accepts two arguments:\n\n    - error: error argument.\n    - bool: test result.\n\n    If the test result is falsy, the function continues invoking `fcn`;\n    otherwise, the function invokes the `done` callback.\n\n    The `done` callback is invoked with an `error` argument and any arguments\n    passed to the final `next` callback.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Parameters\n    ----------\n    fcn: Function\n        The function to invoke.\n\n    predicate: Function\n        The predicate function which indicates whether to continue invoking a\n        function.\n\n    done: Function\n        Callback to invoke upon completion.\n\n    thisArg: any (optional)\n        Execution context for the invoked function.\n\n    Examples\n    --------\n    > function fcn( i, next ) {\n    ...     setTimeout( onTimeout, i );\n    ...     function onTimeout() {\n    ...         next( null, 'boop'+i );\n    ...     }\n    ... };\n    > function predicate( i, clbk ) { clbk( null, i >= 5 ); };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > doUntilAsync( fcn, predicate, done )\n    boop: 4\n\n    See Also\n    --------\n    doUntil, doWhileAsync, untilAsync, whileAsync\n","doUntilEach":"\ndoUntilEach( collection, fcn, predicate[, thisArg] )\n    Until a test condition is true, invokes a function for each element in a\n    collection.\n\n    The condition is evaluated *after* executing the provided function; thus,\n    `fcn` *always* executes at least once.\n\n    When invoked, both the predicate function and the function to apply are\n    provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    If provided an empty collection, both `value` and `index` are `undefined`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    predicate: Function\n        The predicate function which indicates whether to stop iterating over a\n        collection.\n\n    thisArg: any (optional)\n        Execution context for the applied function.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function predicate( v ) { return v !== v; };\n    > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n    > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n    > doUntilEach( arr, logger, predicate )\n    0: 1\n    1: 2\n    2: 3\n    3: 4\n    4: NaN\n\n    See Also\n    --------\n    doUntilEachRight, doWhileEach, untilEach\n","doUntilEachRight":"\ndoUntilEachRight( collection, fcn, predicate[, thisArg] )\n    Until a test condition is true, invokes a function for each element in a\n    collection, iterating from right to left.\n\n    The condition is evaluated *after* executing the provided function; thus,\n    `fcn` *always* executes at least once.\n\n    When invoked, both the predicate function and the function to apply are\n    provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    If provided an empty collection, both `value` and `index` are `undefined`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    predicate: Function\n        The predicate function which indicates whether to stop iterating over a\n        collection.\n\n    thisArg: any (optional)\n        Execution context for the applied function.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function predicate( v ) { return v !== v; };\n    > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n    > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n    > doUntilEachRight( arr, logger, predicate )\n    5: 5\n    4: 4\n    3: 3\n    2: 2\n    1: NaN\n\n    See Also\n    --------\n    doUntilEach, doWhileEachRight, untilEachRight\n","doWhile":"\ndoWhile( fcn, predicate[, thisArg] )\n    Invokes a function while a test condition is true.\n\n    The condition is evaluated *after* executing the provided function; thus,\n    `fcn` *always* executes at least once.\n\n    When invoked, both the predicate function and the function to invoke are\n    provided a single argument:\n\n    - i: iteration number (starting from zero).\n\n    Parameters\n    ----------\n    fcn: Function\n        The function to invoke.\n\n    predicate: Function\n        The predicate function which indicates whether to continue invoking a\n        function.\n\n    thisArg: any (optional)\n        Execution context for the invoked function.\n\n    Examples\n    --------\n    > function predicate( i ) { return ( i < 5 ); };\n    > function beep( i ) { console.log( 'boop: %d', i ); };\n    > doWhile( beep, predicate )\n    boop: 0\n    boop: 1\n    boop: 2\n    boop: 3\n    boop: 4\n\n    See Also\n    --------\n    doUntil, doWhileAsync, doWhileEach, until, whilst\n","doWhileAsync":"\ndoWhileAsync( fcn, predicate, done[, thisArg] )\n    Invokes a function while a test condition is true.\n\n    The condition is evaluated *after* executing the provided function; thus,\n    `fcn` *always* executes at least once.\n\n    The function to invoke is provided two arguments:\n\n    - i: iteration number (starting from zero).\n    - next: a callback which must be invoked before proceeding to the next\n      iteration.\n\n    The first argument of the `next` callback is an `error` argument. If `fcn`\n    calls the `next` callback with a truthy `error` argument, the function\n    suspends execution and immediately calls the `done` callback for subsequent\n    `error` handling.\n\n    The predicate function is provided two arguments:\n\n    - i: iteration number (starting from one).\n    - clbk: a callback indicating whether to invoke `fcn`.\n\n    The `clbk` function accepts two arguments:\n\n    - error: error argument.\n    - bool: test result.\n\n    If the test result is truthy, the function continues invoking `fcn`;\n    otherwise, the function invokes the `done` callback.\n\n    The `done` callback is invoked with an `error` argument and any arguments\n    passed to the final `next` callback.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Parameters\n    ----------\n    fcn: Function\n        The function to invoke.\n\n    predicate: Function\n        The predicate function which indicates whether to continue invoking a\n        function.\n\n    done: Function\n        Callback to invoke upon completion.\n\n    thisArg: any (optional)\n        Execution context for the invoked function.\n\n    Examples\n    --------\n    > function fcn( i, next ) {\n    ...     setTimeout( onTimeout, i );\n    ...     function onTimeout() {\n    ...         next( null, 'boop'+i );\n    ...     }\n    ... };\n    > function predicate( i, clbk ) { clbk( null, i < 5 ); };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > doWhileAsync( fcn, predicate, done )\n    boop: 4\n\n    See Also\n    --------\n    doUntilAsync, doWhile, untilAsync, whileAsync\n","doWhileEach":"\ndoWhileEach( collection, fcn, predicate[, thisArg] )\n    While a test condition is true, invokes a function for each element in a\n    collection.\n\n    The condition is evaluated *after* executing the provided function; thus,\n    `fcn` *always* executes at least once.\n\n    When invoked, both the predicate function and the function to apply are\n    provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    If provided an empty collection, both `value` and `index` are `undefined`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    predicate: Function\n        The predicate function which indicates whether to continue iterating\n        over a collection.\n\n    thisArg: any (optional)\n        Execution context for the applied function.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === v; };\n    > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n    > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n    > doWhileEach( arr, logger, predicate )\n    0: 1\n    1: 2\n    2: 3\n    3: 4\n    4: NaN\n\n    See Also\n    --------\n    doUntilEach, doWhileEachRight, whileEach\n","doWhileEachRight":"\ndoWhileEachRight( collection, fcn, predicate[, thisArg] )\n    While a test condition is true, invokes a function for each element in a\n    collection, iterating from right to left.\n\n    The condition is evaluated *after* executing the provided function; thus,\n    `fcn` *always* executes at least once.\n\n    When invoked, both the predicate function and the function to apply are\n    provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    If provided an empty collection, both `value` and `index` are `undefined`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    predicate: Function\n        The predicate function which indicates whether to continue iterating\n        over a collection.\n\n    thisArg: any (optional)\n        Execution context for the applied function.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === v; };\n    > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n    > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n    > doWhileEachRight( arr, logger, predicate )\n    5: 5\n    4: 4\n    3: 3\n    2: 2\n    1: NaN\n\n    See Also\n    --------\n    doUntilEachRight, doWhileEach, whileEachRight\n","dswap":"\ndswap( x, y[, dim] )\n    Interchanges two double-precision floating-point vectors.\n\n    For multi-dimensional input arrays, the function performs batched\n    computation, such that the function interchanges each pair of vectors in `x`\n    and `y` according to the specified dimension index.\n\n    Both input arrays must have the same shape.\n\n    Parameters\n    ----------\n    x: ndarray\n        First input array. Must have a 'float64' data type. Must have at least\n        one dimension and must have the same shape as the second input array.\n\n    y: ndarray\n        Second input array. Must have a 'float64' data type. Must have at least\n        one dimension and must have the same shape as the first input array.\n\n    dim: integer (optional)\n        Dimension index along which to interchange vectors. Must be a negative\n        integer. Negative indices are resolved relative to the last array\n        dimension, with the last dimension corresponding to `-1`. Default: -1.\n\n    Returns\n    -------\n    y: ndarray\n        The second input array `y`.\n\n    Examples\n    --------\n    > var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n    > var y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n    > dswap( x, y );\n    > x.data\n    <Float64Array>[ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n    > y.data\n    <Float64Array>[ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dswap, gswap, sswap\n","E":"\nE\n    Euler's number.\n\n    Examples\n    --------\n    > E\n    2.718281828459045\n\n","EMOJI":"\nEMOJI()\n    Returns an emoji database.\n\n    Returns\n    -------\n    out: Array\n        Emoji database.\n\n    Examples\n    --------\n    > var data = EMOJI()\n    [ {...}, ... ]\n\n    See Also\n    --------\n    EMOJI_CODE_PICTO, EMOJI_PICTO_CODE\n","EMOJI_CODE_PICTO":"\nEMOJI_CODE_PICTO()\n    Returns an object mapping emoji codes to pictographs.\n\n    Returns\n    -------\n    out: Object\n        An object mapping emoji codes to pictographs.\n\n    Examples\n    --------\n    > var out = EMOJI_CODE_PICTO()\n\n    See Also\n    --------\n    EMOJI, EMOJI_PICTO_CODE\n","EMOJI_PICTO_CODE":"\nEMOJI_PICTO_CODE()\n    Returns an object mapping emoji pictographs to codes.\n\n    Returns\n    -------\n    out: Object\n        An object mapping emoji pictographs to codes.\n\n    Examples\n    --------\n    > var out = EMOJI_PICTO_CODE()\n\n    See Also\n    --------\n    EMOJI, EMOJI_CODE_PICTO\n","emptyStream":"\nemptyStream( [options] )\n    Returns an \"empty\" readable stream.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var s = emptyStream();\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nemptyStream.factory( [options] )\n    Returns a function for creating empty readable streams.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true };\n    > var createStream = emptyStream.factory( opts );\n\n\nemptyStream.objectMode()\n    Returns an \"objectMode\" empty readable stream.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var s = emptyStream.objectMode();\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    constantStream\n","emptyStream.factory":"\nemptyStream.factory( [options] )\n    Returns a function for creating empty readable streams.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true };\n    > var createStream = emptyStream.factory( opts );","emptyStream.objectMode":"\nemptyStream.objectMode()\n    Returns an \"objectMode\" empty readable stream.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var s = emptyStream.objectMode();\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    constantStream","endsWith":"\nendsWith( str, search[, len] )\n    Tests if a string ends with the characters of another string.\n\n    If provided an empty search string, the function always returns `true`.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search string.\n\n    len: integer (optional)\n        Substring length. Restricts the search to a substring within the input\n        string beginning from the leftmost character. If provided a negative\n        value, `len` indicates to ignore the last `len` characters, returning\n        the same output as `str.length + len`. Default: `str.length`.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a string ends with the characters of another\n        string.\n\n    Examples\n    --------\n    > var bool = endsWith( 'beep', 'ep' )\n    true\n    > bool = endsWith( 'Beep', 'op' )\n    false\n    > bool = endsWith( 'Beep', 'ee', 3 )\n    true\n    > bool = endsWith( 'Beep', 'ee', -1 )\n    true\n    > bool = endsWith( 'beep', '' )\n    true\n\n    See Also\n    --------\n    startsWith\n","enumerableProperties":"\nenumerableProperties( value )\n    Returns an array of an object's own enumerable property names and symbols.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    props: Array\n        List of an object's own enumerable properties.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var props = enumerableProperties( obj )\n    [ 'beep' ]\n\n    See Also\n    --------\n    enumerablePropertiesIn, enumerablePropertySymbols, inheritedEnumerableProperties, objectKeys, nonEnumerableProperties, properties\n","enumerablePropertiesIn":"\nenumerablePropertiesIn( value )\n    Returns an array of an object's own and inherited enumerable property names\n    and symbols.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    props: Array\n        List of an object's own and inherited enumerable property names and\n        symbols.\n\n    Examples\n    --------\n    > var props = enumerablePropertiesIn( [] )\n\n    See Also\n    --------\n    enumerableProperties, enumerablePropertySymbolsIn, inheritedEnumerableProperties, keysIn, nonEnumerablePropertiesIn, propertiesIn\n","enumerablePropertySymbols":"\nenumerablePropertySymbols( value )\n    Returns an array of an object's own enumerable symbol properties.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's own enumerable symbol properties.\n\n    Examples\n    --------\n    > var obj = {};\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = true;\n    > desc.writable = true;\n    > desc.value = 'boop';\n    > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n    > defineProperty( obj, sym, desc );\n    > var symbols = enumerablePropertySymbols( obj )\n\n    See Also\n    --------\n    enumerablePropertySymbolsIn, inheritedEnumerablePropertySymbols, objectKeys, nonEnumerablePropertySymbols, propertySymbols\n","enumerablePropertySymbolsIn":"\nenumerablePropertySymbolsIn( value )\n    Returns an array of an object's own and inherited enumerable symbol\n    properties.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's own and inherited enumerable symbol properties.\n\n    Examples\n    --------\n    > var obj = {};\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = true;\n    > desc.writable = true;\n    > desc.value = 'boop';\n    > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n    > defineProperty( obj, sym, desc );\n    > var symbols = enumerablePropertySymbolsIn( obj )\n\n    See Also\n    --------\n    enumerablePropertySymbols, inheritedEnumerablePropertySymbols, keysIn, nonEnumerablePropertySymbolsIn, propertySymbolsIn\n","ENV":"\nENV\n    An object containing the user environment.\n\n    Examples\n    --------\n    > var user = ENV.USER\n    <string>\n\n    See Also\n    --------\n    ARGV\n","EPS":"\nEPS\n    Difference between one and the smallest value greater than one that can be\n    represented as a double-precision floating-point number.\n\n    Examples\n    --------\n    > EPS\n    2.220446049250313e-16\n\n    See Also\n    --------\n    FLOAT32_EPS\n","error2json":"\nerror2json( error )\n    Returns a JSON representation of an error object.\n\n    The following built-in error types are supported:\n\n    - Error\n    - URIError\n    - ReferenceError\n    - SyntaxError\n    - RangeError\n    - EvalError\n    - TypeError\n\n    The JSON object is guaranteed to have the following properties:\n\n    - type: error type.\n    - message: error message.\n\n    The only standardized cross-platform property is `message`. Depending on the\n    platform, the following properties *may* be present:\n\n    - name: error name.\n    - stack: stack trace.\n    - code: error code (Node.js system errors).\n    - errno: error code string (Node.js system errors).\n    - syscall: string representing the failed system call (Node.js system\n      errors).\n\n    The function also serializes all enumerable properties.\n\n    The implementation supports custom error types and sets the `type` field to\n    the closest built-in error type.\n\n    Parameters\n    ----------\n    error: Error\n        Error to serialize.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var err = new Error( 'beep' );\n    > var json = error2json( err )\n    <Object>\n\n    See Also\n    --------\n    reviveError\n","EULERGAMMA":"\nEULERGAMMA\n    The Euler-Mascheroni constant.\n\n    Examples\n    --------\n    > EULERGAMMA\n    0.5772156649015329\n\n","every":"\nevery( collection )\n    Tests whether all elements in a collection are truthy.\n\n    The function immediately returns upon encountering a falsy value.\n\n    If provided an empty collection, the function returns `true`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if all elements are truthy; otherwise, the\n        function returns `false`.\n\n    Examples\n    --------\n    > var arr = [ 1, 1, 1, 1, 1 ];\n    > var bool = every( arr )\n    true\n\n    See Also\n    --------\n    any, everyBy, forEach, none, some\n","everyBy":"\neveryBy( collection, predicate[, thisArg ] )\n    Tests whether all elements in a collection pass a test implemented by a\n    predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    The function immediately returns upon encountering a non-truthy return\n    value.\n\n    If provided an empty collection, the function returns `true`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns a truthy\n        value for all elements; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function positive( v ) { return ( v > 0 ); };\n    > var arr = [ 1, 2, 3, 4 ];\n    > var bool = everyBy( arr, positive )\n    true\n\n    See Also\n    --------\n    anyBy, everyByRight, forEach, noneBy, someBy\n","everyByAsync":"\neveryByAsync( collection, [options,] predicate, done )\n    Tests whether all elements in a collection pass a test implemented by a\n    predicate function.\n\n    When invoked, the predicate function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If the\n    predicate function accepts two arguments, the predicate function is\n    provided:\n\n    - value\n    - next\n\n    If the predicate function accepts three arguments, the predicate function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other predicate function signature, the predicate function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - result: test result.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    The function immediately returns upon encountering a non-truthy `result`\n    value and calls the `done` callback with `null` as the first argument and\n    `false` as the second argument.\n\n    If all elements succeed, the function calls the `done` callback with `null`\n    as the first argument and `true` as the second argument.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, true );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > everyByAsync( arr, predicate, done )\n    1000\n    2500\n    3000\n    true\n\n    // Limit number of concurrent invocations:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, true );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 3000, 2500, 1000 ];\n    > everyByAsync( arr, opts, predicate, done )\n    2500\n    3000\n    1000\n    true\n\n    // Process sequentially:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, true );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 3000, 2500, 1000 ];\n    > everyByAsync( arr, opts, predicate, done )\n    3000\n    2500\n    1000\n    true\n\n\neveryByAsync.factory( [options,] predicate )\n    Returns a function which tests whether all elements in a collection pass a\n    test implemented by a predicate function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, true );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = everyByAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n\n    See Also\n    --------\n    anyByAsync, everyBy, everyByRightAsync, forEachAsync, noneByAsync, someByAsync\n","everyByAsync.factory":"\neveryByAsync.factory( [options,] predicate )\n    Returns a function which tests whether all elements in a collection pass a\n    test implemented by a predicate function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, true );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = everyByAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n\n    See Also\n    --------\n    anyByAsync, everyBy, everyByRightAsync, forEachAsync, noneByAsync, someByAsync","everyByRight":"\neveryByRight( collection, predicate[, thisArg ] )\n    Tests whether all elements in a collection pass a test implemented by a\n    predicate function, iterating from right to left.\n\n    The predicate function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    The function immediately returns upon encountering a non-truthy return\n    value.\n\n    If provided an empty collection, the function returns `true`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns a truthy\n        value for all elements; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function positive( v ) { return ( v > 0 ); };\n    > var arr = [ 1, 2, 3, 4 ];\n    > var bool = everyByRight( arr, positive )\n    true\n\n    See Also\n    --------\n    anyBy, every, everyBy, forEachRight, noneByRight, someByRight\n","everyByRightAsync":"\neveryByRightAsync( collection, [options,] predicate, done )\n    Tests whether all elements in a collection pass a test implemented by a\n    predicate function, iterating from right to left.\n\n    When invoked, the predicate function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If the\n    predicate function accepts two arguments, the predicate function is\n    provided:\n\n    - value\n    - next\n\n    If the predicate function accepts three arguments, the predicate function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other predicate function signature, the predicate function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - result: test result.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    The function immediately returns upon encountering a non-truthy `result`\n    value and calls the `done` callback with `null` as the first argument and\n    `false` as the second argument.\n\n    If all elements succeed, the function calls the `done` callback with `null`\n    as the first argument and `true` as the second argument.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, true );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > everyByRightAsync( arr, predicate, done )\n    1000\n    2500\n    3000\n    true\n\n    // Limit number of concurrent invocations:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, true );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 1000, 2500, 3000 ];\n    > everyByRightAsync( arr, opts, predicate, done )\n    2500\n    3000\n    1000\n    true\n\n    // Process sequentially:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, true );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 1000, 2500, 3000 ];\n    > everyByRightAsync( arr, opts, predicate, done )\n    3000\n    2500\n    1000\n    true\n\n\neveryByRightAsync.factory( [options,] predicate )\n    Returns a function which tests whether all elements in a collection pass a\n    test implemented by a predicate function, iterating from right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, true );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = everyByRightAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n\n    See Also\n    --------\n    anyByRightAsync, everyByAsync, everyByRight, forEachRightAsync, noneByRightAsync, someByRightAsync\n","everyByRightAsync.factory":"\neveryByRightAsync.factory( [options,] predicate )\n    Returns a function which tests whether all elements in a collection pass a\n    test implemented by a predicate function, iterating from right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, true );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = everyByRightAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n\n    See Also\n    --------\n    anyByRightAsync, everyByAsync, everyByRight, forEachRightAsync, noneByRightAsync, someByRightAsync","everyInBy":"\neveryInBy( object, predicate[, thisArg ] )\n   Test whether all properties (own and inherited) of an object pass a\n   test implemented by a predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: object value.\n    - key: object key.\n    - object: the input object.\n\n    The function immediately returns upon encountering a non-truthy return\n    value.\n\n    If provided an empty object, the function returns `true`.\n\n    Parameters\n    ----------\n    object: Object\n        Input object over which to iterate.\n\n    predicate: Function\n        Test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns a truthy\n        value for all elements; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function positive( v ) { return ( v > 0 ); };\n    > var o = {a: 1, b: 2, c: 3};\n    > var bool = everyInBy( o, positive )\n    true\n\n    See Also\n    --------\n    anyInBy, noneInBy, someInBy, everyBy, everyOwnBy\n","everyOwnBy":"\neveryOwnBy( object, predicate[, thisArg ] )\n    Tests whether every own property of an object pass a test implemented by a\n    predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: property value.\n    - index: property key.\n    - object: the input object.\n\n    The function immediately returns upon encountering a non-truthy return\n    value.\n\n    If provided an empty object, the function returns `true`.\n\n    Parameters\n    ----------\n    object: Object\n        Input object.\n\n    predicate: Function\n        Test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns a truthy\n        value for all elements; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function positive( v ) { return ( v > 0 ); };\n    > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n    > var bool = everyOwnBy( obj, positive )\n    true\n\n    See Also\n    --------\n    anyOwnBy, everyInBy, noneOwnBy, someOwnBy, everyBy\n","evil":"\nevil( str )\n    Alias for `eval` global.\n\n    A reference to `eval` is treated differently by the compiler. For example,\n    when evaluating code containing block-scoped declarations  (e.g., `let`,\n    `const`, `function`, `class`), the compiler may throw an `error` complaining\n    that block-scoped declarations are not yet supported outside of\n    `strict mode`. One possible workaround is to include `\"use strict\";` in the\n    evaluated code.\n\n    Parameters\n    ----------\n    str: string\n        Code to evaluate.\n\n    Returns\n    -------\n    out: any\n        Returned value if applicable.\n\n    Examples\n    --------\n    > var v = evil( '5*4*3*2*1' )\n    120\n\n","EXEC_PATH":"\nEXEC_PATH\n    Absolute pathname of the executable which started the current Node.js\n    process.\n\n    Examples\n    --------\n    > EXEC_PATH\n    <string>\n\n","exists":"\nexists( path, clbk )\n    Asynchronously tests whether a path exists on the filesystem.\n\n    Parameters\n    ----------\n    path: string|Buffer\n        Path to test.\n\n    clbk: Function\n        Callback to invoke after testing for path existence. A callback may\n        accept a single argument, a boolean indicating whether a path exists, or\n        two arguments, an error argument and a boolean, matching the error-first\n        callback convention used in most asynchronous Node.js APIs.\n\n    Examples\n    --------\n    > function done( error, bool ) { console.log( bool ); };\n    > exists( './beep/boop', done );\n\n\nexists.sync( path )\n    Synchronously tests whether a path exists on the filesystem.\n\n    Parameters\n    ----------\n    path: string|Buffer\n        Path to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the path exists.\n\n    Examples\n    --------\n    > var bool = exists.sync( './beep/boop' )\n    <boolean>\n\n    See Also\n    --------\n    readFile, readDir\n","exists.sync":"\nexists.sync( path )\n    Synchronously tests whether a path exists on the filesystem.\n\n    Parameters\n    ----------\n    path: string|Buffer\n        Path to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the path exists.\n\n    Examples\n    --------\n    > var bool = exists.sync( './beep/boop' )\n    <boolean>\n\n    See Also\n    --------\n    readFile, readDir","expandAcronyms":"\nexpandAcronyms( str )\n    Expands acronyms in a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        String with expanded acronyms.\n\n    Examples\n    --------\n    > var str = 'LOL, this is fun. I am ROFL.';\n    > var out = expandAcronyms( str )\n    'laughing out loud, this is fun. I am rolling on the floor laughing.'\n\n    > str = 'brb, I need to check my mail. thx!';\n    > out = expandAcronyms( str )\n    'be right back, I need to check my mail. thanks!'\n\n    See Also\n    --------\n    expandContractions\n","expandContractions":"\nexpandContractions( str )\n    Expands all contractions to their formal equivalents.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        String with expanded contractions.\n\n    Examples\n    --------\n    > var str = 'I won\\'t be able to get y\\'all out of this one.';\n    > var out = expandContractions( str )\n    'I will not be able to get you all out of this one.'\n\n    > str = 'It oughtn\\'t to be my fault, because, you know, I didn\\'t know';\n    > out = expandContractions( str )\n    'It ought not to be my fault, because, you know, I did not know'\n\n","extname":"\nextname( filename )\n    Returns a filename extension.\n\n    Parameters\n    ----------\n    filename: string\n        Filename.\n\n    Returns\n    -------\n    ext: string\n        Filename extension.\n\n    Examples\n    --------\n    > var ext = extname( 'index.js' )\n    '.js'\n\n    See Also\n    --------\n    dirname\n","FancyArray":"\nFancyArray( dtype, buffer, shape, strides, offset, order[, options] )\n    Returns a FancyArray instance.\n\n    A FancyArray is an ndarray which supports slicing via indexing expressions.\n\n    A FancyArray is an ndarray instance and supports all ndarray options,\n    attributes, and methods. A FancyArray can be consumed by any API which\n    supports ndarray instances.\n\n    Indexing expressions provide a convenient and powerful means for creating\n    and operating on ndarray views; however, their use does entail a performance\n    cost. Indexing expressions are best suited for interactive use and\n    scripting. For performance critical applications, prefer equivalent\n    functional APIs supporting ndarray instances.\n\n    In older JavaScript environments which do not support Proxy objects, the use\n    of indexing expressions is not supported.\n\n    Parameters\n    ----------\n    dtype: string\n        Underlying data type.\n\n    buffer: ArrayLikeObject|TypedArray|Buffer\n        Data buffer. A data buffer must be an array-like object (i.e., have a\n        `length` property). For data buffers which are not indexed collections\n        (i.e., collections which cannot support direct index access, such as\n        `buffer[ index ]`; e.g., Complex64Array, Complex128Array, etc), a data\n        buffer should provide `#.get( idx )` and `#.set( v[, idx] )` methods.\n        Note that, for `set` methods, the value to set should be the first\n        argument, followed by the linear index, similar to the native typed\n        array `set` method.\n\n    shape: ArrayLikeObject<integer>\n        Array shape.\n\n    strides: ArrayLikeObject<integer>\n        Array strides.\n\n    offset: integer\n        Index offset.\n\n    order: string\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran-style).\n\n    options: Object (optional)\n        Options.\n\n    options.mode: string (optional)\n        Specifies how to handle indices which exceed array dimensions. If equal\n        to 'throw', an ndarray instance throws an error when an index exceeds\n        array dimensions. If equal to 'normalize', an ndarray instance\n        normalizes negative indices and throws an error when an index exceeds\n        array dimensions. If equal to 'wrap', an ndarray instance wraps around\n        indices exceeding array dimensions using modulo arithmetic. If equal to\n        'clamp', an ndarray instance sets an index exceeding array dimensions\n        to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n    options.submode: Array<string> (optional)\n        Specifies how to handle subscripts which exceed array dimensions. If a\n        mode for a corresponding dimension is equal to 'throw', an ndarray\n        instance throws an error when a subscript exceeds array dimensions. If\n        equal to 'normalize', an ndarray instance normalizes negative\n        subscripts and throws an error when a subscript exceeds array\n        dimensions. If equal to 'wrap', an ndarray instance wraps around\n        subscripts exceeding array dimensions using modulo arithmetic. If equal\n        to 'clamp', an ndarray instance sets a subscript exceeding array\n        dimensions to either `0` (minimum index) or the maximum index. If the\n        number of modes is fewer than the number of dimensions, the function\n        recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether an array should be read-only. Default: false.\n\n    Returns\n    -------\n    ndarray: FancyArray\n        FancyArray instance.\n\n    Examples\n    --------\n    // Create a new instance...\n    > var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\n    > var d = [ 2, 2 ]; // shape\n    > var s = [ 2, 1 ]; // strides\n    > var o = 0; // index offset\n    > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' )\n    <FancyArray>\n\n    // Get an element using subscripts:\n    > var v = arr.get( 1, 1 )\n    4.0\n\n    // Get an element using a linear index:\n    > v = arr.iget( 3 )\n    4.0\n\n    // Set an element using subscripts:\n    > arr.set( 1, 1, 40.0 );\n    > arr.get( 1, 1 )\n    40.0\n\n    // Set an element using a linear index:\n    > arr.iset( 3, 99.0 );\n    > arr.get( 1, 1 )\n    99.0\n\n\nFancyArray.prototype.byteLength\n    Size (in bytes) of the array (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of the array.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.byteLength\n    32\n\n\nFancyArray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.BYTES_PER_ELEMENT\n    8\n\n\nFancyArray.prototype.data\n    Pointer to the underlying data buffer.\n\n    Returns\n    -------\n    buf: ArrayLikeObject|TypedArray|Buffer\n        Underlying data buffer.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var buf = arr.data\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n\nFancyArray.prototype.dtype\n    Underlying data type.\n\n    Returns\n    -------\n    dtype: string\n        Underlying data type.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var dt = arr.dtype\n    'float64'\n\n\nFancyArray.prototype.flags\n    Meta information, such as information concerning the memory layout of the\n    array.\n\n    Returns\n    -------\n    flags: Object\n        Info object.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var fl = arr.flags\n    {...}\n\n\nFancyArray.prototype.length\n    Length of the array (i.e., number of elements).\n\n    Returns\n    -------\n    len: integer\n        Array length.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var len = arr.length\n    4\n\n\nFancyArray.prototype.ndims\n    Number of dimensions.\n\n    Returns\n    -------\n    ndims: integer\n        Number of dimensions.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var n = arr.ndims\n    2\n\n\nFancyArray.prototype.offset\n    Index offset which specifies the buffer index at which to start iterating\n    over array elements.\n\n    Returns\n    -------\n    offset: integer\n        Index offset.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.offset\n    0\n\n\nFancyArray.prototype.order\n    Array order.\n\n    The array order is either row-major (C-style) or column-major (Fortran-\n    style).\n\n    Returns\n    -------\n    order: string\n        Array order.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var ord = arr.order\n    'row-major'\n\n\nFancyArray.prototype.shape\n    Array shape.\n\n    Returns\n    -------\n    shape: Array\n        Array shape.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var sh = arr.shape\n    [ 2, 2 ]\n\n\nFancyArray.prototype.strides\n    Index strides which specify how to access data along corresponding array\n    dimensions.\n\n    Returns\n    -------\n    strides: Array\n        Index strides.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var st = arr.strides\n    [ 2, 1 ]\n\n\nFancyArray.prototype.get( ...idx )\n    Returns an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.get( 1, 1 )\n    4.0\n\n\nFancyArray.prototype.iget( idx )\n    Returns an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the input argument is ignored and, for clarity,\n    should not be provided.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.iget( 3 )\n    4.0\n\n\nFancyArray.prototype.set( ...idx, v )\n    Sets an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: FancyArray\n        FancyArray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > arr.set( 1, 1, -4.0 );\n    > arr.get( 1, 1 )\n    -4.0\n\n\nFancyArray.prototype.iset( idx, v )\n    Sets an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the first, and only, argument should be the\n    value to set.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: FancyArray\n        FancyArray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > arr.iset( 3, -4.0 );\n    > arr.iget( 3 )\n    -4.0\n\n\nFancyArray.prototype.toString()\n    Serializes a FancyArray as a string.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    str: string\n        Serialized ndarray string.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toString()\n    '...'\n\n\nFancyArray.prototype.toJSON()\n    Serializes a FancyArray as a JSON object.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toJSON()\n    {...}\n\n    See Also\n    --------\n    array, ndarray\n","FancyArray.prototype.byteLength":"\nFancyArray.prototype.byteLength\n    Size (in bytes) of the array (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of the array.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.byteLength\n    32","FancyArray.prototype.BYTES_PER_ELEMENT":"\nFancyArray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.BYTES_PER_ELEMENT\n    8","FancyArray.prototype.data":"\nFancyArray.prototype.data\n    Pointer to the underlying data buffer.\n\n    Returns\n    -------\n    buf: ArrayLikeObject|TypedArray|Buffer\n        Underlying data buffer.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var buf = arr.data\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]","FancyArray.prototype.dtype":"\nFancyArray.prototype.dtype\n    Underlying data type.\n\n    Returns\n    -------\n    dtype: string\n        Underlying data type.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var dt = arr.dtype\n    'float64'","FancyArray.prototype.flags":"\nFancyArray.prototype.flags\n    Meta information, such as information concerning the memory layout of the\n    array.\n\n    Returns\n    -------\n    flags: Object\n        Info object.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var fl = arr.flags\n    {...}","FancyArray.prototype.length":"\nFancyArray.prototype.length\n    Length of the array (i.e., number of elements).\n\n    Returns\n    -------\n    len: integer\n        Array length.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var len = arr.length\n    4","FancyArray.prototype.ndims":"\nFancyArray.prototype.ndims\n    Number of dimensions.\n\n    Returns\n    -------\n    ndims: integer\n        Number of dimensions.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var n = arr.ndims\n    2","FancyArray.prototype.offset":"\nFancyArray.prototype.offset\n    Index offset which specifies the buffer index at which to start iterating\n    over array elements.\n\n    Returns\n    -------\n    offset: integer\n        Index offset.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.offset\n    0","FancyArray.prototype.order":"\nFancyArray.prototype.order\n    Array order.\n\n    The array order is either row-major (C-style) or column-major (Fortran-\n    style).\n\n    Returns\n    -------\n    order: string\n        Array order.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var ord = arr.order\n    'row-major'","FancyArray.prototype.shape":"\nFancyArray.prototype.shape\n    Array shape.\n\n    Returns\n    -------\n    shape: Array\n        Array shape.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var sh = arr.shape\n    [ 2, 2 ]","FancyArray.prototype.strides":"\nFancyArray.prototype.strides\n    Index strides which specify how to access data along corresponding array\n    dimensions.\n\n    Returns\n    -------\n    strides: Array\n        Index strides.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var st = arr.strides\n    [ 2, 1 ]","FancyArray.prototype.get":"\nFancyArray.prototype.get( ...idx )\n    Returns an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.get( 1, 1 )\n    4.0","FancyArray.prototype.iget":"\nFancyArray.prototype.iget( idx )\n    Returns an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the input argument is ignored and, for clarity,\n    should not be provided.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.iget( 3 )\n    4.0","FancyArray.prototype.set":"\nFancyArray.prototype.set( ...idx, v )\n    Sets an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: FancyArray\n        FancyArray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > arr.set( 1, 1, -4.0 );\n    > arr.get( 1, 1 )\n    -4.0","FancyArray.prototype.iset":"\nFancyArray.prototype.iset( idx, v )\n    Sets an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the first, and only, argument should be the\n    value to set.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: FancyArray\n        FancyArray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > arr.iset( 3, -4.0 );\n    > arr.iget( 3 )\n    -4.0","FancyArray.prototype.toString":"\nFancyArray.prototype.toString()\n    Serializes a FancyArray as a string.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    str: string\n        Serialized ndarray string.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toString()\n    '...'","FancyArray.prototype.toJSON":"\nFancyArray.prototype.toJSON()\n    Serializes a FancyArray as a JSON object.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toJSON()\n    {...}\n\n    See Also\n    --------\n    array, ndarray","fastmath.abs":"\nfastmath.abs( x )\n    Computes an absolute value.\n\n    This implementation is not IEEE 754 compliant. If provided `-0`, the\n    function returns `-0`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    out: number\n        Absolute value.\n\n    Examples\n    --------\n    > var v = fastmath.abs( -1.0 )\n    1.0\n    > v = fastmath.abs( 2.0 )\n    2.0\n    > v = fastmath.abs( 0.0 )\n    0.0\n    > v = fastmath.abs( -0.0 )\n    -0.0\n    > v = fastmath.abs( NaN )\n    NaN\n\n    See Also\n    --------\n    base.abs\n","fastmath.acosh":"\nfastmath.acosh( x )\n    Computes the hyperbolic arccosine of a number.\n\n    The domain of `x` is restricted to `[1,+infinity)`. If `x < 1`, the function\n    will return `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    out: number\n        Hyperbolic arccosine (in radians).\n\n    Examples\n    --------\n    > var v = fastmath.acosh( 1.0 )\n    0.0\n    > v = fastmath.acosh( 2.0 )\n    ~1.317\n    > v = fastmath.acosh( NaN )\n    NaN\n\n    // The function overflows for large `x`:\n    > v = fastmath.acosh( 1.0e308 )\n    Infinity\n\n    See Also\n    --------\n    base.acosh\n","fastmath.ampbm":"\nfastmath.ampbm( x, y )\n    Computes the hypotenuse using the alpha max plus beta min algorithm.\n\n    The algorithm computes only an approximation.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Hypotenuse.\n\n    Examples\n    --------\n    > var h = fastmath.ampbm( 5.0, 12.0 )\n    ~13.514\n\n\nfastmath.ampbm.factory( alpha, beta, [nonnegative[, ints]] )\n    Returns a function to compute a hypotenuse using the alpha max plus beta min\n    algorithm.\n\n    Parameters\n    ----------\n    alpha: number\n        Alpha.\n\n    beta: number\n        Beta.\n\n    nonnegative: boolean (optional)\n        Boolean indicating whether input values are always nonnegative.\n\n    ints: boolean (optional)\n        Boolean indicating whether input values are always 32-bit integers.\n\n    Returns\n    -------\n    fcn: Function\n        Function to compute a hypotenuse.\n\n    Examples\n    --------\n    > var hypot = fastmath.ampbm.factory( 1.0, 0.5 )\n    <Function>\n\n    See Also\n    --------\n    base.hypot\n","fastmath.ampbm.factory":"\nfastmath.ampbm.factory( alpha, beta, [nonnegative[, ints]] )\n    Returns a function to compute a hypotenuse using the alpha max plus beta min\n    algorithm.\n\n    Parameters\n    ----------\n    alpha: number\n        Alpha.\n\n    beta: number\n        Beta.\n\n    nonnegative: boolean (optional)\n        Boolean indicating whether input values are always nonnegative.\n\n    ints: boolean (optional)\n        Boolean indicating whether input values are always 32-bit integers.\n\n    Returns\n    -------\n    fcn: Function\n        Function to compute a hypotenuse.\n\n    Examples\n    --------\n    > var hypot = fastmath.ampbm.factory( 1.0, 0.5 )\n    <Function>\n\n    See Also\n    --------\n    base.hypot","fastmath.asinh":"\nfastmath.asinh( x )\n    Computes the hyperbolic arcsine of a number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    out: number\n        Hyperbolic arcsine (in radians).\n\n    Examples\n    --------\n    > var v = fastmath.asinh( 0.0 )\n    0.0\n    > v = fastmath.asinh( 2.0 )\n    ~1.444\n    > v = fastmath.asinh( -2.0 )\n    ~-1.444\n    > v = fastmath.asinh( NaN )\n    NaN\n\n    // The function overflows for large `x`:\n    > v = fastmath.asinh( 1.0e200 )\n    Infinity\n\n    // The function underflows for small `x`:\n    > v = fastmath.asinh( 1.0e-50 )\n    0.0\n\n    See Also\n    --------\n    base.asinh\n","fastmath.atanh":"\nfastmath.atanh( x )\n    Computes the hyperbolic arctangent of a number.\n\n    The domain of `x` is restricted to `[-1,1]`. If `|x| > 1`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    out: number\n        Hyperbolic arctangent (in radians).\n\n    Examples\n    --------\n    > var v = fastmath.atanh( 0.0 )\n    0.0\n    > v = fastmath.atanh( 0.9 )\n    ~1.472\n    > v = fastmath.atanh( 1.0 )\n    Infinity\n    > v = fastmath.atanh( -1.0 )\n    -Infinity\n    > v = fastmath.atanh( NaN )\n    NaN\n\n    // The function underflows for small `x`:\n    > v = fastmath.atanh( 1.0e-17 )\n    0.0\n\n    See Also\n    --------\n    base.atanh\n","fastmath.hypot":"\nfastmath.hypot( x, y )\n    Computes the hypotenuse.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Hypotenuse.\n\n    Examples\n    --------\n    > var h = fastmath.hypot( -5.0, 12.0 )\n    13.0\n\n    // For a sufficiently large `x` and/or `y`, the function overflows:\n    > h = fastmath.hypot( 1.0e154, 1.0e154 )\n    Infinity\n\n    // For sufficiently small `x` and/or `y`, the function underflows:\n    > h = fastmath.hypot( 1e-200, 1.0e-200 )\n    0.0\n\n    See Also\n    --------\n    base.hypot\n","fastmath.log2Uint32":"\nfastmath.log2Uint32( x )\n    Returns an approximate binary logarithm (base two) of an unsigned 32-bit\n    integer `x`.\n\n    This function provides a performance boost when requiring only approximate\n    computations for integer arguments.\n\n    For high-precision applications, this function is never suitable.\n\n    Parameters\n    ----------\n    x: uinteger\n        Input value.\n\n    Returns\n    -------\n    out: uinteger\n        Integer binary logarithm (base two).\n\n    Examples\n    --------\n    > var v = fastmath.log2Uint32( 4 >>> 0 )\n    2\n    > v = fastmath.log2Uint32( 8 >>> 0 )\n    3\n    > v = fastmath.log2Uint32( 9 >>> 0 )\n    3\n\n    See Also\n    --------\n    base.log2\n","fastmath.max":"\nfastmath.max( x, y )\n    Returns the maximum value.\n\n    The function ignores the sign of `0` and does not check for `NaN` arguments.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    > var v = fastmath.max( 3.14, 4.2 )\n    4.2\n    > v = fastmath.max( 3.14, NaN )\n    NaN\n    > v = fastmath.max( NaN, 3.14 )\n    3.14\n    > v = fastmath.max( -0.0, +0.0 )\n    +0.0\n    > v = fastmath.max( +0.0, -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.max\n","fastmath.min":"\nfastmath.min( x, y )\n    Returns the minimum value.\n\n    The function ignores the sign of `0` and does not check for `NaN` arguments.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    > var v = fastmath.min( 3.14, 4.2 )\n    3.14\n    > v = fastmath.min( 3.14, NaN )\n    NaN\n    > v = fastmath.min( NaN, 3.14 )\n    3.14\n    > v = fastmath.min( -0.0, +0.0 )\n    +0.0\n    > v = fastmath.min( +0.0, -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.min\n","fastmath.powint":"\nfastmath.powint( x, y )\n    Evaluates the exponential function given a signed 32-bit integer exponent.\n\n    This function is not recommended for high-precision applications due to\n    error accumulation.\n\n    If provided a negative exponent, the function first computes the reciprocal\n    of the base and then evaluates the exponential function. This can introduce\n    significant error.\n\n    Parameters\n    ----------\n    x: number\n        Base.\n\n    y: integer\n        Signed 32-bit integer exponent.\n\n    Returns\n    -------\n    out: number\n        Function value.\n\n    Examples\n    --------\n    > var v = fastmath.powint( 2.0, 3 )\n    8.0\n    > v = fastmath.powint( 3.14, 0 )\n    1.0\n    > v = fastmath.powint( 2.0, -2 )\n    0.25\n    > v = fastmath.powint( 0.0, 0 )\n    1.0\n    > v = fastmath.powint( -3.14, 1 )\n    -3.14\n    > v = fastmath.powint( NaN, 0 )\n    NaN\n\n    See Also\n    --------\n    base.pow\n","fastmath.sqrtUint32":"\nfastmath.sqrtUint32( x )\n    Returns an approximate square root of an unsigned 32-bit integer `x`.\n\n    Prefer hardware `sqrt` over a software implementation.\n\n    When using a software `sqrt`, this function provides a performance boost\n    when an application requires only approximate computations for integer\n    arguments.\n\n    For applications requiring high-precision, this function is never suitable.\n\n    Parameters\n    ----------\n    x: uinteger\n        Input value.\n\n    Returns\n    -------\n    out: uinteger\n        Integer square root.\n\n    Examples\n    --------\n    > var v = fastmath.sqrtUint32( 9 >>> 0 )\n    3\n    > v = fastmath.sqrtUint32( 2 >>> 0 )\n    1\n    > v = fastmath.sqrtUint32( 3 >>> 0 )\n    1\n    > v = fastmath.sqrtUint32( 0 >>> 0 )\n    0\n\n    See Also\n    --------\n    base.sqrt\n","FEMALE_FIRST_NAMES_EN":"\nFEMALE_FIRST_NAMES_EN()\n    Returns a list of common female first names in English speaking countries.\n\n    Returns\n    -------\n    out: Array<string>\n        List of common female first names.\n\n    Examples\n    --------\n    > var list = FEMALE_FIRST_NAMES_EN()\n    [ 'Aaren', 'Aarika', 'Abagael', 'Abagail', ... ]\n\n    References\n    ----------\n    - Ward, Grady. 2002. \"Moby Word II.\" <http://www.gutenberg.org/files/3201/\n    3201.txt>.\n\n    See Also\n    --------\n    MALE_FIRST_NAMES_EN\n","FIFO":"\nFIFO()\n    First-in-first-out (FIFO) queue constructor.\n\n    Returns\n    -------\n    queue: Object\n        First-in-first-out queue.\n\n    queue.clear: Function\n        Clears the queue.\n\n    queue.first: Function\n        Returns the \"oldest\" queue value (i.e., the value which is \"first-out\").\n        If the queue is empty, the returned value is `undefined`.\n\n    queue.iterator: Function\n        Returns an iterator for iterating over a queue. If an environment\n        supports Symbol.iterator, the returned iterator is iterable. Note that,\n        in order to prevent confusion arising from queue mutation during\n        iteration, a returned iterator **always** iterates over a queue\n        \"snapshot\", which is defined as the list of queue elements at the time\n        of the method's invocation.\n\n    queue.last: Function\n        Returns the \"newest\" queue value (i.e., the value which is \"last-out\").\n        If the queue is empty, the returned value is `undefined`.\n\n    queue.length: integer\n        Queue length.\n\n    queue.pop: Function\n        Removes and returns the current \"first-out\" value from the queue. If the\n        queue is empty, the returned value is `undefined`.\n\n    queue.push: Function\n        Adds a value to the queue.\n\n    queue.toArray: Function\n        Returns an array of queue values.\n\n    queue.toJSON: Function\n        Serializes a queue as JSON.\n\n    Examples\n    --------\n    > var q = FIFO();\n    > q.push( 'foo' ).push( 'bar' );\n    > q.length\n    2\n    > q.pop()\n    'foo'\n    > q.length\n    1\n    > q.pop()\n    'bar'\n    > q.length\n    0\n\n    See Also\n    --------\n    Stack\n","filledarray":"\nfilledarray( [dtype] )\n    Creates a filled array.\n\n    Parameters\n    ----------\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = filledarray()\n    <Float64Array>\n    > arr = filledarray( 'float32' )\n    <Float32Array>\n\n\nfilledarray( value, length[, dtype] )\n    Returns a filled array having a specified length.\n\n    Parameters\n    ----------\n    value: any\n        Fill value.\n\n    length: integer\n        Array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = filledarray( 1.0, 5 )\n    <Float64Array>[ 1.0, 1.0, 1.0, 1.0, 1.0 ]\n    > arr = filledarray( 1, 5, 'int32' )\n    <Int32Array>[ 1, 1, 1, 1, 1 ]\n\n\nfilledarray( value, array[, dtype] )\n    Creates a filled array from another array (or array-like object).\n\n    Parameters\n    ----------\n    value: any\n        Fill value.\n\n    array: ArrayLikeObject\n        Array from which to generate another array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr1 = filledarray( 2.0, [ 0.5, 0.5, 0.5 ] )\n    <Float64Array>[ 2.0, 2.0, 2.0 ]\n    > var arr2 = filledarray( 1.0, arr1, 'float32' )\n    <Float32Array>[ 1.0, 1.0, 1.0 ]\n\n\nfilledarray( value, iterable[, dtype] )\n    Creates a filled array from an iterable.\n\n    Parameters\n    ----------\n    value: any\n        Fill value.\n\n    iterable: Iterable\n        Iterable from which to generate an array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr1 = iterConstant( 3.0, {'iter': 3} );\n    > var arr2 = filledarray( 1.0, arr1, 'float32' )\n    <Float32Array>[ 1.0, 1.0, 1.0 ]\n\n\nfilledarray( value, buffer[, byteOffset[, length]][, dtype] )\n    Returns a filled typed array view of an ArrayBuffer.\n\n    The 'generic' array data type is *not* supported.\n\n    Parameters\n    ----------\n    value: any\n        Fill value.\n\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 16 );\n    > var arr = filledarray( 1.0, buf, 0, 4, 'float32' )\n    <Float32Array>[ 1.0, 1.0, 1.0, 1.0 ]\n\n    See Also\n    --------\n    filledarrayBy, typedarray\n","filledarrayBy":"\nfilledarrayBy( [dtype] )\n    Creates a filled array.\n\n    Parameters\n    ----------\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = filledarrayBy()\n    <Float64Array>\n    > arr = filledarrayBy( 'float32' )\n    <Float32Array>\n\n\nfilledarrayBy( length[, dtype], clbk[, thisArg] )\n    Returns a filled array according to a provided callback function and having\n    a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > function clbk() { return 1.0; };\n    > var arr = filledarrayBy( 5, clbk )\n    <Float64Array>[ 1.0, 1.0, 1.0, 1.0, 1.0 ]\n    > arr = filledarrayBy( 5, 'int32', clbk )\n    <Int32Array>[ 1, 1, 1, 1, 1 ]\n\n\nfilledarrayBy( array[, dtype], clbk[, thisArg] )\n    Creates a filled array from another array (or array-like object) according\n    to a provided callback function.\n\n    Parameters\n    ----------\n    array: ArrayLikeObject\n        Array from which to generate another array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr1 = filledarrayBy( [ 0.5, 0.5, 0.5 ], constantFunction( 2.0 ) )\n    <Float64Array>[ 2.0, 2.0, 2.0 ]\n    > var arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\n    <Float32Array>[ 1.0, 1.0, 1.0 ]\n\n\nfilledarrayBy( iterable[, dtype], clbk[, thisArg] )\n    Creates a filled array from an iterable according to a provided callback\n    function.\n\n    Parameters\n    ----------\n    iterable: Iterable\n        Iterable from which to generate an array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr1 = iterConstant( 3.0, {'iter': 3} );\n    > var arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\n    <Float32Array>[ 1.0, 1.0, 1.0 ]\n\n\nfilledarrayBy( buffer[, byteOffset[, length]][, dtype], clbk[, thisArg] )\n    Returns a filled typed array view of an ArrayBuffer according to a provided\n    callback function.\n\n    The 'generic' array data type is *not* supported.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 16 );\n    > var arr = filledarrayBy( buf, 0, 4, 'float32', constantFunction( 1.0 ) )\n    <Float32Array>[ 1.0, 1.0, 1.0, 1.0 ]\n\n    See Also\n    --------\n    filledarray, typedarray\n","filterArguments":"\nfilterArguments( fcn, predicate[, thisArg] )\n    Returns a function that applies arguments to a provided function according\n    to a predicate function.\n\n    Only those arguments in which the predicate function returns a truthy value\n    are applied to a provided function.\n\n    The predicate function is provided the following arguments:\n\n    - value: argument value.\n    - index: argument index.\n\n    Parameters\n    ----------\n    fcn: Function\n        Input function.\n\n    predicate: Function\n        Predicate function.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Function\n        Function wrapper.\n\n    Examples\n    --------\n    > function foo( a, b ) { return [ a, b ]; };\n    > function predicate( v ) { return ( v !== 2 ); };\n    > var bar = filterArguments( foo, predicate );\n    > var out = bar( 1, 2, 3 )\n    [ 1, 3 ]\n\n    See Also\n    --------\n    maskArguments, rejectArguments, reorderArguments, reverseArguments\n","find":"\nfind( arr, [options,] clbk )\n    Finds elements in an array-like object that satisfy a test condition.\n\n    Parameters\n    ----------\n    arr: Array|TypedArray|string\n        Object from which elements will be tested.\n\n    options: Object (optional)\n        Options.\n\n    options.k: integer (optional)\n        Limits the number of returned elements. The sign determines the\n        direction in which to search. If set to a negative integer, the function\n        searches from last element to first element. Default: arr.length.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `indices`, indices are returned; if\n        `*`, both indices and values are returned. Default: 'indices'.\n\n    clbk: Function\n        Function invoked for each array element. If the return value is truthy,\n        the value is considered to have satisfied the test condition.\n\n    Returns\n    -------\n    out: Array\n        Array of indices, element values, or arrays of index-value pairs.\n\n    Examples\n    --------\n    > var data = [ 30, 20, 50, 60, 10 ];\n    > function condition( val ) { return val > 20; };\n    > var vals = find( data, condition )\n    [ 0, 2, 3 ]\n\n    // Limit number of results:\n    > data = [ 30, 20, 50, 60, 10 ];\n    > var opts = { 'k': 2, 'returns': 'values' };\n    > vals = find( data, opts, condition )\n    [ 30, 50 ]\n\n    // Return both indices and values as index-value pairs:\n    > data = [ 30, 20, 50, 60, 10 ];\n    > opts = { 'k': -2, 'returns': '*' };\n    > vals = find( data, opts, condition )\n    [ [ 3, 60 ], [ 2, 50 ] ]\n\n","firstChar":"\nfirstChar( str[, n][, options] )\n    Returns the first character(s) of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer (optional)\n        Number of characters to return. Default: 1.\n\n    options: Object (optional)\n        Options.\n\n    options.mode: string (optional)\n        Type of characters to return. The following modes are supported:\n\n        - grapheme: grapheme clusters. Appropriate for strings containing visual\n          characters which can span multiple Unicode code points (e.g., emoji).\n        - code_point: Unicode code points. Appropriate for strings containing\n          visual characters which are comprised of more than one Unicode code\n          unit (e.g., ideographic symbols and punctuation and mathematical\n          alphanumerics).\n        - code_unit': UTF-16 code units. Appropriate for strings containing\n          visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n          common characters, such as those from the Latin, Greek, and Cyrillic\n          alphabets).\n\n        Default: 'grapheme'.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = firstChar( 'beep' )\n    'b'\n    > out = firstChar( 'Boop', 1 )\n    'B'\n    > out = firstChar( 'foo bar', 5 )\n    'foo b'\n\n    See Also\n    --------\n    removeFirst, last\n","FIVETHIRTYEIGHT_FFQ":"\nFIVETHIRTYEIGHT_FFQ()\n    Returns FiveThirtyEight reader responses to a food frequency questionnaire\n    (FFQ).\n\n    Returns\n    -------\n    out: Array<Object>\n        FiveThirtyEight reader responses to a food frequency questionnaire\n        (FFQ).\n\n    Examples\n    --------\n    > var data = FIVETHIRTYEIGHT_FFQ()\n    [ {...}, ... ]\n\n    References\n    ----------\n    - Aschwanden, Christie. 2016. \"You Can't Trust What You Read About\n    Nutrition.\" <https://fivethirtyeight.com/features/you-cant-trust-what-you-\n    read-about-nutrition/>.\n\n    * If you use the data for publication or third party consumption, please\n    cite the listed reference.\n\n","flattenArray":"\nflattenArray( arr[, options] )\n    Flattens an array.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject\n        Input array.\n\n    options: Object (optional)\n        Options.\n\n    options.depth: integer (optional)\n        Maximum depth to flatten.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to deep copy array elements. Default: false.\n\n    Returns\n    -------\n    out: Array\n        Flattened array.\n\n    Examples\n    --------\n    > var arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n    > var out = flattenArray( arr )\n    [ 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n    // Set the maximum depth:\n    > arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n    > out = flattenArray( arr, { 'depth': 2 } )\n    [ 1, 2, 3, [ 4, [ 5 ], 6 ], 7, 8, 9 ]\n    > var bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n    true\n\n    // Deep copy:\n    > arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n    > out = flattenArray( arr, { 'depth': 2, 'copy': true } )\n    [ 1, 2, 3, [ 4, [ 5 ], 6 ], 7, 8, 9 ]\n    > bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n    false\n\n\nflattenArray.factory( dims[, options] )\n    Returns a function for flattening arrays having specified dimensions.\n\n    The returned function does not validate that input arrays actually have the\n    specified dimensions.\n\n    Parameters\n    ----------\n    dims: ArrayLike<integer>\n        Dimensions.\n\n    options: Object (optional)\n        Options.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to deep copy array elements. Default: false.\n\n    Returns\n    -------\n    fcn: Function\n        Flatten function.\n\n    Examples\n    --------\n    > var flatten = flattenArray.factory( [ 2, 2 ], {\n    ...     'copy': false\n    ... });\n    > var out = flatten( [ [ 1, 2 ], [ 3, 4 ] ] )\n    [ 1, 2, 3, 4 ]\n    > out = flatten( [ [ 5, 6 ], [ 7, 8 ] ] )\n    [ 5, 6, 7, 8 ]\n\n    See Also\n    --------\n    flattenObject\n","flattenArray.factory":"\nflattenArray.factory( dims[, options] )\n    Returns a function for flattening arrays having specified dimensions.\n\n    The returned function does not validate that input arrays actually have the\n    specified dimensions.\n\n    Parameters\n    ----------\n    dims: ArrayLike<integer>\n        Dimensions.\n\n    options: Object (optional)\n        Options.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to deep copy array elements. Default: false.\n\n    Returns\n    -------\n    fcn: Function\n        Flatten function.\n\n    Examples\n    --------\n    > var flatten = flattenArray.factory( [ 2, 2 ], {\n    ...     'copy': false\n    ... });\n    > var out = flatten( [ [ 1, 2 ], [ 3, 4 ] ] )\n    [ 1, 2, 3, 4 ]\n    > out = flatten( [ [ 5, 6 ], [ 7, 8 ] ] )\n    [ 5, 6, 7, 8 ]\n\n    See Also\n    --------\n    flattenObject","flattenObject":"\nflattenObject( obj[, options] )\n    Flattens an object.\n\n    Parameters\n    ----------\n    obj: ObjectLike\n        Object to flatten.\n\n    options: Object (optional)\n        Options.\n\n    options.depth: integer (optional)\n        Maximum depth to flatten.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to deep copy. Default: false.\n\n    options.flattenArrays: boolean (optional)\n        Boolean indicating whether to flatten arrays. Default: false.\n\n    options.delimiter: string (optional)\n        Key path delimiter. Default: '.'.\n\n    Returns\n    -------\n    out: ObjectLike\n        Flattened object.\n\n    Examples\n    --------\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var out = flattenObject( obj )\n    { 'a.b.c': 'd' }\n\n    // Set the `depth` option to flatten to a specified depth:\n    > obj = { 'a': { 'b': { 'c': 'd' } } };\n    > out = flattenObject( obj, { 'depth': 1 } )\n    { 'a.b': { 'c': 'd' } }\n    > var bool = ( obj.a.b === out[ 'a.b' ] )\n    true\n\n    // Set the `delimiter` option:\n    > obj = { 'a': { 'b': { 'c': 'd' } } };\n    > out = flattenObject( obj, { 'delimiter': '-|-' } )\n    { 'a-|-b-|-c': 'd' }\n\n    // Flatten arrays:\n    > obj = { 'a': { 'b': [ 1, 2, 3 ] } };\n    > out = flattenObject( obj, { 'flattenArrays': true } )\n    { 'a.b.0': 1, 'a.b.1': 2, 'a.b.2': 3 }\n\n\nflattenObject.factory( [options] )\n    Returns a function to flatten an object.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.depth: integer (optional)\n        Maximum depth to flatten.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to deep copy. Default: false.\n\n    options.flattenArrays: boolean (optional)\n        Boolean indicating whether to flatten arrays. Default: false.\n\n    options.delimiter: string (optional)\n        Key path delimiter. Default: '.'.\n\n    Returns\n    -------\n    fcn: Function\n        Flatten function.\n\n    Examples\n    --------\n    > var flatten = flattenObject.factory({\n    ...     'depth': 1,\n    ...     'copy': true,\n    ...     'delimiter': '|'\n    ... });\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var out = flatten( obj )\n    { 'a|b': { 'c': 'd' } }\n\n    See Also\n    --------\n    flattenArray\n","flattenObject.factory":"\nflattenObject.factory( [options] )\n    Returns a function to flatten an object.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.depth: integer (optional)\n        Maximum depth to flatten.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to deep copy. Default: false.\n\n    options.flattenArrays: boolean (optional)\n        Boolean indicating whether to flatten arrays. Default: false.\n\n    options.delimiter: string (optional)\n        Key path delimiter. Default: '.'.\n\n    Returns\n    -------\n    fcn: Function\n        Flatten function.\n\n    Examples\n    --------\n    > var flatten = flattenObject.factory({\n    ...     'depth': 1,\n    ...     'copy': true,\n    ...     'delimiter': '|'\n    ... });\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var out = flatten( obj )\n    { 'a|b': { 'c': 'd' } }\n\n    See Also\n    --------\n    flattenArray","flignerTest":"\nflignerTest( ...x[, options] )\n    Computes the Fligner-Killeen test for equal variances.\n\n    Parameters\n    ----------\n    x: ...Array\n        Measured values.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.groups: Array (optional)\n        Array of group indicators.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.method: string\n        Name of test.\n\n    out.df: Object\n        Degrees of freedom.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    // Data from Hollander & Wolfe (1973), p. 116:\n    > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n    > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n    > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n    > var out = flignerTest( x, y, z )\n\n    > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n    ...     3.8, 2.7, 4.0, 2.4,\n    ...     2.8, 3.4, 3.7, 2.2, 2.0\n    ... ];\n    > var groups = [\n    ...     'a', 'a', 'a', 'a', 'a',\n    ...     'b', 'b', 'b', 'b',\n    ...     'c', 'c', 'c', 'c', 'c'\n    ... ];\n    > out = flignerTest( arr, { 'groups': groups } )\n\n    See Also\n    --------\n    bartlettTest\n","FLOAT_WORD_ORDER":"\nFLOAT_WORD_ORDER\n    Platform float word order.\n\n    Possible values:\n\n    - 'little-endian'\n    - 'big-endian'\n    - 'unknown'\n\n    Examples\n    --------\n    > FLOAT_WORD_ORDER\n    <string>\n\n    See Also\n    --------\n    BYTE_ORDER\n","FLOAT16_CBRT_EPS":"\nFLOAT16_CBRT_EPS\n    Cube root of half-precision floating-point epsilon.\n\n    Examples\n    --------\n    > FLOAT16_CBRT_EPS\n    0.09921256574801247\n\n    See Also\n    --------\n    FLOAT16_EPS, FLOAT16_SQRT_EPS, FLOAT32_CBRT_EPS, CBRT_EPS\n","FLOAT16_EPS":"\nFLOAT16_EPS\n    Difference between one and the smallest value greater than one that can be\n    represented as a half-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT16_EPS\n    0.0009765625\n\n    See Also\n    --------\n    FLOAT32_EPS, EPS\n","FLOAT16_EXPONENT_BIAS":"\nFLOAT16_EXPONENT_BIAS\n    The bias of a half-precision floating-point number's exponent.\n\n    Examples\n    --------\n    > FLOAT16_EXPONENT_BIAS\n    15\n\n    See Also\n    --------\n    FLOAT32_EXPONENT_BIAS, FLOAT64_EXPONENT_BIAS\n","FLOAT16_MAX":"\nFLOAT16_MAX\n    Maximum half-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT16_MAX\n    65504.0\n\n    See Also\n    --------\n    FLOAT32_MAX, FLOAT64_MAX\n","FLOAT16_MAX_SAFE_INTEGER":"\nFLOAT16_MAX_SAFE_INTEGER\n    Maximum safe half-precision floating-point integer.\n\n    The maximum safe half-precision floating-point integer is given by\n    `2^11 - 1`.\n\n    Examples\n    --------\n    > FLOAT16_MAX_SAFE_INTEGER\n    2047\n\n    See Also\n    --------\n    FLOAT16_MIN_SAFE_INTEGER, FLOAT32_MAX_SAFE_INTEGER, FLOAT64_MAX_SAFE_INTEGER\n","FLOAT16_MIN_SAFE_INTEGER":"\nFLOAT16_MIN_SAFE_INTEGER\n    Minimum safe half-precision floating-point integer.\n\n    The minimum safe half-precision floating-point integer is given by\n    `-(2^11 - 1)`.\n\n    Examples\n    --------\n    > FLOAT16_MIN_SAFE_INTEGER\n    -2047\n\n    See Also\n    --------\n    FLOAT16_MAX_SAFE_INTEGER, FLOAT32_MIN_SAFE_INTEGER, FLOAT64_MIN_SAFE_INTEGER\n","FLOAT16_NINF":"\nFLOAT16_NINF\n    Half-precision floating-point negative infinity.\n\n    Examples\n    --------\n    > FLOAT16_NINF\n    -Infinity\n\n    See Also\n    --------\n    FLOAT16_PINF, FLOAT32_NINF, NINF\n","FLOAT16_NUM_BYTES":"\nFLOAT16_NUM_BYTES\n    Size (in bytes) of a half-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT16_NUM_BYTES\n    2\n\n    See Also\n    --------\n    FLOAT32_NUM_BYTES, FLOAT64_NUM_BYTES\n","FLOAT16_PINF":"\nFLOAT16_PINF\n    Half-precision floating-point positive infinity.\n\n    Examples\n    --------\n    > FLOAT16_PINF\n    Infinity\n\n    See Also\n    --------\n    FLOAT16_NINF, FLOAT32_PINF, PINF\n","FLOAT16_PRECISION":"\nFLOAT16_PRECISION\n    Effective number of bits in the significand of a half-precision floating-\n    point number.\n\n    The effective number of bits is `10` significand bits plus `1` hidden bit.\n\n    Examples\n    --------\n    > FLOAT16_PRECISION\n    11\n\n    See Also\n    --------\n    FLOAT32_PRECISION, FLOAT64_PRECISION\n","FLOAT16_SMALLEST_NORMAL":"\nFLOAT16_SMALLEST_NORMAL\n    Smallest positive normalized half-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT16_SMALLEST_NORMAL\n    6.103515625e-5\n\n    See Also\n    --------\n    FLOAT16_SMALLEST_SUBNORMAL, FLOAT32_SMALLEST_NORMAL, FLOAT64_SMALLEST_NORMAL\n","FLOAT16_SMALLEST_SUBNORMAL":"\nFLOAT16_SMALLEST_SUBNORMAL\n    Smallest positive denormalized half-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT16_SMALLEST_SUBNORMAL\n    5.960464477539063e-8\n\n    See Also\n    --------\n    FLOAT16_SMALLEST_NORMAL, FLOAT32_SMALLEST_SUBNORMAL, FLOAT64_SMALLEST_SUBNORMAL\n","FLOAT16_SQRT_EPS":"\nFLOAT16_SQRT_EPS\n    Square root of half-precision floating-point epsilon.\n\n    Examples\n    --------\n    > FLOAT16_SQRT_EPS\n    0.03125\n\n    See Also\n    --------\n    FLOAT16_EPS, FLOAT32_SQRT_EPS, SQRT_EPS\n","FLOAT32_ABS_MASK":"\nFLOAT32_ABS_MASK\n    Mask for excluding the sign bit of a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_ABS_MASK\n    2147483647\n    > base.toBinaryStringUint32( FLOAT32_ABS_MASK )\n    '01111111111111111111111111111111'\n\n    See Also\n    --------\n    FLOAT32_EXPONENT_MASK, FLOAT32_SIGN_MASK, FLOAT32_SIGNIFICAND_MASK\n","FLOAT32_CBRT_EPS":"\nFLOAT32_CBRT_EPS\n    Cube root of single-precision floating-point epsilon.\n\n    Examples\n    --------\n    > FLOAT32_CBRT_EPS\n    0.004921566694974899\n\n    See Also\n    --------\n    FLOAT32_EPS, FLOAT32_SQRT_EPS, CBRT_EPS\n","FLOAT32_E":"\nFLOAT32_E\n    Euler's number.\n\n    Examples\n    --------\n    > FLOAT32_E\n    2.7182817459106445\n\n    See Also\n    --------\n    E\n","FLOAT32_EPS":"\nFLOAT32_EPS\n    Difference between one and the smallest value greater than one that can be\n    represented as a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_EPS\n    1.1920928955078125e-7\n\n    See Also\n    --------\n    EPS\n","FLOAT32_EXPONENT_BIAS":"\nFLOAT32_EXPONENT_BIAS\n    The bias of a single-precision floating-point number's exponent.\n\n    Examples\n    --------\n    > FLOAT32_EXPONENT_BIAS\n    127\n\n    See Also\n    --------\n    FLOAT16_EXPONENT_BIAS, FLOAT64_EXPONENT_BIAS\n","FLOAT32_EXPONENT_MASK":"\nFLOAT32_EXPONENT_MASK\n    Mask for the exponent of a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_EXPONENT_MASK\n    2139095040\n    > base.toBinaryStringUint32( FLOAT32_EXPONENT_MASK )\n    '01111111100000000000000000000000'\n\n    See Also\n    --------\n    FLOAT32_SIGN_MASK, FLOAT32_SIGNIFICAND_MASK, FLOAT32_ABS_MASK\n","FLOAT32_FOURTH_PI":"\nFLOAT32_FOURTH_PI\n    One fourth times the mathematical constant `π`.\n\n    Examples\n    --------\n    > FLOAT32_FOURTH_PI\n    7.853981852531433e-1\n\n    See Also\n    --------\n    FLOAT32_HALF_PI, FLOAT32_PI, FLOAT32_TWO_PI\n","FLOAT32_HALF_LN_TWO":"\nFLOAT32_HALF_LN_TWO\n    One half times the natural logarithm of 2 as a single-precision\n    floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_HALF_LN_TWO\n    0.3465735912322998\n\n    See Also\n    --------\n    HALF_LN2\n","FLOAT32_HALF_PI":"\nFLOAT32_HALF_PI\n    One half times the mathematical constant `π`.\n\n    Examples\n    --------\n    > FLOAT32_HALF_PI\n    1.5707963705062866\n\n    See Also\n    --------\n    FLOAT32_FOURTH_PI, FLOAT32_PI, FLOAT32_TWO_PI\n","FLOAT32_LN_HALF":"\nFLOAT32_LN_HALF\n    Natural logarithm of `1/2` as a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_LN_HALF\n    -0.6931471824645996\n\n    See Also\n    --------\n    LN_HALF\n","FLOAT32_LN_PI":"\nFLOAT32_LN_PI\n    Natural logarithm of the mathematical constant `π` as a single-precision\n    floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_LN_PI\n    1.1447298526763916\n\n    See Also\n    --------\n    FLOAT32_PI, LN_PI\n","FLOAT32_LN_TEN":"\nFLOAT32_LN_TEN\n    Natural logarithm of `10` as a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_LN_TEN\n     2.3025851249694824\n\n    See Also\n    --------\n    FLOAT32_LN_TWO, LN10\n","FLOAT32_LN_TWO":"\nFLOAT32_LN_TWO\n    Natural logarithm of `2` as a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_LN_TWO\n    0.6931471824645996\n\n    See Also\n    --------\n    FLOAT32_LN_TEN, LN2\n","FLOAT32_MAX":"\nFLOAT32_MAX\n    Maximum single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_MAX\n    3.4028234663852886e+38\n\n    See Also\n    --------\n    FLOAT16_MAX, FLOAT64_MAX\n","FLOAT32_MAX_BASE2_EXPONENT":"\nFLOAT32_MAX_BASE2_EXPONENT\n    The maximum biased base 2 exponent for a single-precision floating-point\n    number.\n\n    Examples\n    --------\n    > FLOAT32_MAX_BASE2_EXPONENT\n    127\n\n    See Also\n    --------\n    FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE2_EXPONENT\n","FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL\n    The maximum biased base 2 exponent for a subnormal single-precision\n    floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL\n    -127\n\n    See Also\n    --------\n    FLOAT32_MAX_BASE2_EXPONENT, FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n","FLOAT32_MAX_BASE10_EXPONENT":"\nFLOAT32_MAX_BASE10_EXPONENT\n    The maximum base 10 exponent for a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_MAX_BASE10_EXPONENT\n    38\n\n    See Also\n    --------\n    FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE10_EXPONENT\n","FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL\n    The maximum base 10 exponent for a subnormal single-precision floating-point\n    number.\n\n    Examples\n    --------\n    > FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL\n    -38\n\n    See Also\n    --------\n    FLOAT32_MAX_BASE10_EXPONENT, FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n","FLOAT32_MAX_SAFE_FIBONACCI":"\nFLOAT32_MAX_SAFE_FIBONACCI\n    Maximum safe Fibonacci number when stored in single-precision floating-point\n    format.\n\n    Examples\n    --------\n    > FLOAT32_MAX_SAFE_FIBONACCI\n    14930352\n\n    See Also\n    --------\n    FLOAT64_MAX_SAFE_FIBONACCI\n","FLOAT32_MAX_SAFE_INTEGER":"\nFLOAT32_MAX_SAFE_INTEGER\n    Maximum safe single-precision floating-point integer.\n\n    The maximum safe single-precision floating-point integer is given by\n    `2^24 - 1`.\n\n    Examples\n    --------\n    > FLOAT32_MAX_SAFE_INTEGER\n    16777215\n\n    See Also\n    --------\n    FLOAT16_MAX_SAFE_INTEGER, FLOAT32_MIN_SAFE_INTEGER, FLOAT64_MAX_SAFE_INTEGER\n","FLOAT32_MAX_SAFE_NTH_FACTORIAL":"\nFLOAT32_MAX_SAFE_NTH_FACTORIAL\n    Maximum safe nth factorial when stored in single-precision floating-\n    point format.\n\n    Examples\n    --------\n    > FLOAT32_MAX_SAFE_NTH_FACTORIAL\n    34\n\n","FLOAT32_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT32_MAX_SAFE_NTH_FIBONACCI\n    Maximum safe nth Fibonacci number when stored in single-precision floating-\n    point format.\n\n    Examples\n    --------\n    > FLOAT32_MAX_SAFE_NTH_FIBONACCI\n    36\n\n    See Also\n    --------\n    FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT32_MAX_SAFE_NTH_LUCAS":"\nFLOAT32_MAX_SAFE_NTH_LUCAS\n    Maximum safe nth Lucas number when stored in single-precision floating-point\n    format.\n\n    Examples\n    --------\n    > FLOAT32_MAX_SAFE_NTH_LUCAS\n    34\n\n    See Also\n    --------\n    FLOAT64_MAX_SAFE_NTH_LUCAS\n","FLOAT32_MIN_BASE2_EXPONENT":"\nFLOAT32_MIN_BASE2_EXPONENT\n    The minimum biased base 2 exponent for a normalized single-precision\n    floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_MIN_BASE2_EXPONENT\n    -126\n\n    See Also\n    --------\n    FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL\n    The minimum biased base 2 exponent for a subnormal single-precision\n    floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL\n    -149\n\n    See Also\n    --------\n    FLOAT32_MIN_BASE2_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT32_MIN_BASE10_EXPONENT":"\nFLOAT32_MIN_BASE10_EXPONENT\n    The minimum base 10 exponent for a normal single-precision floating-\n    point number.\n\n    Examples\n    --------\n    > FLOAT32_MIN_BASE10_EXPONENT\n    -37\n\n    See Also\n    --------\n    FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT\n","FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL\n    The minimum base 10 exponent for a subnormal single-precision floating-\n    point number.\n\n    Examples\n    --------\n    > FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL\n    -45\n\n    See Also\n    --------\n    FLOAT32_MIN_BASE10_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT32_MIN_SAFE_INTEGER":"\nFLOAT32_MIN_SAFE_INTEGER\n    Minimum safe single-precision floating-point integer.\n\n    The minimum safe single-precision floating-point integer is given by\n    `-(2^24 - 1)`.\n\n    Examples\n    --------\n    > FLOAT32_MIN_SAFE_INTEGER\n    -16777215\n\n    See Also\n    --------\n    FLOAT16_MIN_SAFE_INTEGER, FLOAT32_MAX_SAFE_INTEGER, FLOAT64_MIN_SAFE_INTEGER\n","FLOAT32_NAN":"\nFLOAT32_NAN\n    Single-precision floating-point NaN.\n\n    Examples\n    --------\n    > FLOAT32_NAN\n    NaN\n\n    See Also\n    --------\n    NAN\n","FLOAT32_NINF":"\nFLOAT32_NINF\n    Single-precision floating-point negative infinity.\n\n    Examples\n    --------\n    > FLOAT32_NINF\n    -Infinity\n\n    See Also\n    --------\n    FLOAT32_PINF, NINF\n","FLOAT32_NUM_BYTES":"\nFLOAT32_NUM_BYTES\n    Size (in bytes) of a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_NUM_BYTES\n    4\n\n    See Also\n    --------\n    FLOAT16_NUM_BYTES, FLOAT64_NUM_BYTES\n","FLOAT32_PHI":"\nFLOAT32_PHI\n    Golden ratio.\n\n    Examples\n    --------\n    > FLOAT32_PHI\n    1.6180340051651\n\n    See Also\n    --------\n    PHI\n","FLOAT32_PI":"\nFLOAT32_PI\n    The mathematical constant `π`.\n\n    Examples\n    --------\n    > FLOAT32_PI\n    3.1415927410125732\n\n    See Also\n    --------\n    FLOAT32_FOURTH_PI, FLOAT32_HALF_PI, FLOAT32_TWO_PI\n","FLOAT32_PINF":"\nFLOAT32_PINF\n    Single-precision floating-point positive infinity.\n\n    Examples\n    --------\n    > FLOAT32_PINF\n    Infinity\n\n    See Also\n    --------\n    FLOAT32_NINF, PINF\n","FLOAT32_PRECISION":"\nFLOAT32_PRECISION\n    Effective number of bits in the significand of a single-precision floating-\n    point number.\n\n    The effective number of bits is `23` significand bits plus `1` hidden bit.\n\n    Examples\n    --------\n    > FLOAT32_PRECISION\n    24\n\n    See Also\n    --------\n    FLOAT16_PRECISION, FLOAT64_PRECISION\n","FLOAT32_SIGN_MASK":"\nFLOAT32_SIGN_MASK\n    Mask for the sign bit of a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_SIGN_MASK\n    2147483648\n    > base.toBinaryStringUint32( FLOAT32_SIGN_MASK )\n    '10000000000000000000000000000000'\n\n    See Also\n    --------\n    FLOAT32_EXPONENT_MASK, FLOAT32_SIGNIFICAND_MASK, FLOAT32_ABS_MASK\n","FLOAT32_SIGNIFICAND_MASK":"\nFLOAT32_SIGNIFICAND_MASK\n    Mask for the significand of a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_SIGNIFICAND_MASK\n    8388607\n    > base.toBinaryStringUint32( FLOAT32_SIGNIFICAND_MASK )\n    '00000000011111111111111111111111'\n\n    See Also\n    --------\n    FLOAT32_EXPONENT_MASK, FLOAT32_SIGN_MASK, FLOAT32_ABS_MASK\n","FLOAT32_SMALLEST_NORMAL":"\nFLOAT32_SMALLEST_NORMAL\n    Smallest positive normalized single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_SMALLEST_NORMAL\n    1.1754943508222875e-38\n\n    See Also\n    --------\n    FLOAT32_SMALLEST_SUBNORMAL, FLOAT64_SMALLEST_NORMAL\n","FLOAT32_SMALLEST_SUBNORMAL":"\nFLOAT32_SMALLEST_SUBNORMAL\n    Smallest positive denormalized single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_SMALLEST_SUBNORMAL\n    1.401298464324817e-45\n\n    See Also\n    --------\n    FLOAT32_SMALLEST_NORMAL, FLOAT64_SMALLEST_SUBNORMAL\n","FLOAT32_SQRT_EPS":"\nFLOAT32_SQRT_EPS\n    Square root of single-precision floating-point epsilon.\n\n    Examples\n    --------\n    > FLOAT32_SQRT_EPS\n    0.0003452669770922512\n\n    See Also\n    --------\n    FLOAT32_EPS, SQRT_EPS\n","FLOAT32_SQRT_HALF":"\nFLOAT32_SQRT_HALF\n    Square root of `1/2` as a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_SQRT_HALF\n    0.7071067690849304\n\n    See Also\n    --------\n    SQRT_HALF\n","FLOAT32_SQRT_HALF_PI":"\nFLOAT32_SQRT_HALF_PI\n    Square root of `π` divided by `2` as a single-precision \n    floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_SQRT_HALF_PI\n    1.2533141374588013\n\n    See Also\n    --------\n    SQRT_HALF_PI","FLOAT32_SQRT_PHI":"\nFLOAT32_SQRT_PHI\n    Square root of the golden ratio as a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_SQRT_PHI\n    1.272019624710083\n\n    See Also\n    --------\n    SQRT_PHI\n","FLOAT32_SQRT_PI":"\nFLOAT32_SQRT_PI\n    Square root of the mathematical constant `π` as a single-precision\n    floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_SQRT_PI\n    1.7724539041519165\n\n    See Also\n    --------\n    FLOAT32_PI, SQRT_PI\n","FLOAT32_SQRT_THREE":"\nFLOAT32_SQRT_THREE\n    Square root of `3` as a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_SQRT_THREE\n    1.7320507764816284\n\n    See Also\n    --------\n    FLOAT32_SQRT_TWO, SQRT_THREE\n","FLOAT32_SQRT_TWO":"\nFLOAT32_SQRT_TWO\n    Square root of `2` as a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_SQRT_TWO\n    1.4142135381698608\n\n    See Also\n    --------\n    FLOAT32_SQRT_THREE, SQRT_TWO\n","FLOAT32_SQRT_TWO_PI":"\nFLOAT32_SQRT_TWO_PI\n    Square root of the `π` times `2` as single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_SQRT_TWO_PI\n    2.5066282749176025\n\n    See Also\n    --------\n    FLOAT32_PI, FLOAT32_TWO_PI, SQRT_TWO_PI\n","FLOAT32_TWO_PI":"\nFLOAT32_TWO_PI\n    The mathematical constant `π` times `2`.\n\n    Examples\n    --------\n    > FLOAT32_TWO_PI\n    6.2831854820251465\n\n    See Also\n    --------\n    FLOAT32_FOURTH_PI, FLOAT32_HALF_PI, FLOAT32_PI\n","Float32Array":"\nFloat32Array()\n    A typed array constructor which returns a typed array representing an array\n    of single-precision floating-point numbers in the platform byte order.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Float32Array()\n    <Float32Array>\n\n\nFloat32Array( length )\n    Returns a typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( 5 )\n    <Float32Array>[ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat32Array( typedarray )\n    Creates a typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float64Array( [ 0.5, 0.5, 0.5 ] );\n    > var arr2 = new Float32Array( arr1 )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]\n\n\nFloat32Array( obj )\n    Creates a typed array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a typed array.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 0.5, 0.5, 0.5 ];\n    > var arr2 = new Float32Array( arr1 )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]\n\n\nFloat32Array( buffer[, byteOffset[, length]] )\n    Returns a typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 16 );\n    > var arr = new Float32Array( buf, 0, 4 )\n    <Float32Array>[ 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat32Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2.0; };\n    > var arr = Float32Array.from( [ 1.0, -1.0 ], mapFcn )\n    <Float32Array>[ 2.0, -2.0 ]\n\n\nFloat32Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Float32Array.of( 2.0, -2.0 )\n    <Float32Array>[ 2.0, -2.0 ]\n\n\nFloat32Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Float32Array.BYTES_PER_ELEMENT\n    4\n\n\nFloat32Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Float32Array.name\n    'Float32Array'\n\n\nFloat32Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>\n\n\nFloat32Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( 5 );\n    > arr.byteLength\n    20\n\n\nFloat32Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Float32Array( 5 );\n    > arr.byteOffset\n    0\n\n\nFloat32Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Float32Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    4\n\n\nFloat32Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Float32Array( 5 );\n    > arr.length\n    5\n\n\nFloat32Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Float32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    2.0\n    > arr[ 4 ]\n    -2.0\n\n\nFloat32Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1.0 ]\n    > it.next().value\n    [ 1, -1.0 ]\n    > it.next().done\n    true\n\n\nFloat32Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > function predicate( v ) { return ( v >= 0.0 ); };\n    > arr.every( predicate )\n    false\n\n\nFloat32Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Float32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > arr.fill( 2.0 );\n    > arr[ 0 ]\n    2.0\n    > arr[ 1 ]\n    2.0\n\n\nFloat32Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v >= 0.0 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2\n\n\nFloat32Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > var v = arr.find( predicate )\n    -1.0\n\n\nFloat32Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > var idx = arr.findIndex( predicate )\n    2\n\n\nFloat32Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:1 1:0 2:-1 '\n\n\nFloat32Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > var bool = arr.includes( 2.0 )\n    false\n    > bool = arr.includes( -1.0 )\n    true\n\n\nFloat32Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > var idx = arr.indexOf( 2.0 )\n    -1\n    > idx = arr.indexOf( -1.0 )\n    2\n\n\nFloat32Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > arr.join( '|' )\n    '1|0|-1'\n\n\nFloat32Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true\n\n\nFloat32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n    > var idx = arr.lastIndexOf( 2.0 )\n    -1\n    > idx = arr.lastIndexOf( 0.0 )\n    3\n\n\nFloat32Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( v ) { return v * 2.0; };\n    > var arr2 = arr1.map( fcn )\n    <Float32Array>[ 2.0, 0.0, -2.0 ]\n\n\nFloat32Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0.0 )\n    2.0\n\n\nFloat32Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0.0 )\n    2.0\n\n\nFloat32Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Float32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] )\n    <Float32Array>\n    > arr.reverse()\n    <Float32Array>[ -1.0, 0.0, 1.0 ]\n\n\nFloat32Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > arr.set( [ -2.0, 2.0 ], 1 );\n    > arr[ 1 ]\n    -2.0\n    > arr[ 2 ]\n    2.0\n\n\nFloat32Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    0.0\n    > arr2[ 1 ]\n    -1.0\n\n\nFloat32Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > arr.some( predicate )\n    true\n\n\nFloat32Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Float32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n    > arr.sort()\n    <Float32Array>[ -2.0, -1.0, 0.0, 1.0, 2.0 ]\n\n\nFloat32Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Float32Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Float32Array>[ 0.0, 2.0, -2.0 ]\n\n\nFloat32Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n    > arr.toLocaleString()\n    '1,-1,0'\n\n\nFloat32Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n    > arr.toString()\n    '1,-1,0'\n\n\nFloat32Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > it = arr.values();\n    > it.next().value\n    1.0\n    > it.next().value\n    -1.0\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Float32Array.from":"\nFloat32Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2.0; };\n    > var arr = Float32Array.from( [ 1.0, -1.0 ], mapFcn )\n    <Float32Array>[ 2.0, -2.0 ]","Float32Array.of":"\nFloat32Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Float32Array.of( 2.0, -2.0 )\n    <Float32Array>[ 2.0, -2.0 ]","Float32Array.BYTES_PER_ELEMENT":"\nFloat32Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Float32Array.BYTES_PER_ELEMENT\n    4","Float32Array.name":"\nFloat32Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Float32Array.name\n    'Float32Array'","Float32Array.prototype.buffer":"\nFloat32Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>","Float32Array.prototype.byteLength":"\nFloat32Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( 5 );\n    > arr.byteLength\n    20","Float32Array.prototype.byteOffset":"\nFloat32Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Float32Array( 5 );\n    > arr.byteOffset\n    0","Float32Array.prototype.BYTES_PER_ELEMENT":"\nFloat32Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Float32Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    4","Float32Array.prototype.length":"\nFloat32Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Float32Array( 5 );\n    > arr.length\n    5","Float32Array.prototype.copyWithin":"\nFloat32Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Float32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    2.0\n    > arr[ 4 ]\n    -2.0","Float32Array.prototype.entries":"\nFloat32Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1.0 ]\n    > it.next().value\n    [ 1, -1.0 ]\n    > it.next().done\n    true","Float32Array.prototype.every":"\nFloat32Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > function predicate( v ) { return ( v >= 0.0 ); };\n    > arr.every( predicate )\n    false","Float32Array.prototype.fill":"\nFloat32Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Float32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > arr.fill( 2.0 );\n    > arr[ 0 ]\n    2.0\n    > arr[ 1 ]\n    2.0","Float32Array.prototype.filter":"\nFloat32Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v >= 0.0 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2","Float32Array.prototype.find":"\nFloat32Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > var v = arr.find( predicate )\n    -1.0","Float32Array.prototype.findIndex":"\nFloat32Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > var idx = arr.findIndex( predicate )\n    2","Float32Array.prototype.forEach":"\nFloat32Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:1 1:0 2:-1 '","Float32Array.prototype.includes":"\nFloat32Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > var bool = arr.includes( 2.0 )\n    false\n    > bool = arr.includes( -1.0 )\n    true","Float32Array.prototype.indexOf":"\nFloat32Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > var idx = arr.indexOf( 2.0 )\n    -1\n    > idx = arr.indexOf( -1.0 )\n    2","Float32Array.prototype.join":"\nFloat32Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > arr.join( '|' )\n    '1|0|-1'","Float32Array.prototype.keys":"\nFloat32Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true","Float32Array.prototype.lastIndexOf":"\nFloat32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n    > var idx = arr.lastIndexOf( 2.0 )\n    -1\n    > idx = arr.lastIndexOf( 0.0 )\n    3","Float32Array.prototype.map":"\nFloat32Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( v ) { return v * 2.0; };\n    > var arr2 = arr1.map( fcn )\n    <Float32Array>[ 2.0, 0.0, -2.0 ]","Float32Array.prototype.reduce":"\nFloat32Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0.0 )\n    2.0","Float32Array.prototype.reduceRight":"\nFloat32Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0.0 )\n    2.0","Float32Array.prototype.reverse":"\nFloat32Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Float32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] )\n    <Float32Array>\n    > arr.reverse()\n    <Float32Array>[ -1.0, 0.0, 1.0 ]","Float32Array.prototype.set":"\nFloat32Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > arr.set( [ -2.0, 2.0 ], 1 );\n    > arr[ 1 ]\n    -2.0\n    > arr[ 2 ]\n    2.0","Float32Array.prototype.slice":"\nFloat32Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    0.0\n    > arr2[ 1 ]\n    -1.0","Float32Array.prototype.some":"\nFloat32Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > arr.some( predicate )\n    true","Float32Array.prototype.sort":"\nFloat32Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Float32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n    > arr.sort()\n    <Float32Array>[ -2.0, -1.0, 0.0, 1.0, 2.0 ]","Float32Array.prototype.subarray":"\nFloat32Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Float32Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Float32Array>[ 0.0, 2.0, -2.0 ]","Float32Array.prototype.toLocaleString":"\nFloat32Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n    > arr.toLocaleString()\n    '1,-1,0'","Float32Array.prototype.toString":"\nFloat32Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n    > arr.toString()\n    '1,-1,0'","Float32Array.prototype.values":"\nFloat32Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > it = arr.values();\n    > it.next().value\n    1.0\n    > it.next().value\n    -1.0\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","FLOAT64_EXPONENT_BIAS":"\nFLOAT64_EXPONENT_BIAS\n    The bias of a double-precision floating-point number's exponent.\n\n    Examples\n    --------\n    > FLOAT64_EXPONENT_BIAS\n    1023\n\n    See Also\n    --------\n    FLOAT16_EXPONENT_BIAS, FLOAT32_EXPONENT_BIAS\n","FLOAT64_HIGH_WORD_ABS_MASK":"\nFLOAT64_HIGH_WORD_ABS_MASK\n    High word mask for excluding the sign bit of a double-precision floating-\n    point number.\n\n    Examples\n    --------\n    > FLOAT64_HIGH_WORD_ABS_MASK\n    2147483647\n    > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_ABS_MASK )\n    '01111111111111111111111111111111'\n\n    See Also\n    --------\n    FLOAT64_HIGH_WORD_SIGN_MASK, FLOAT64_HIGH_WORD_EXPONENT_MASK, FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n","FLOAT64_HIGH_WORD_EXPONENT_MASK":"\nFLOAT64_HIGH_WORD_EXPONENT_MASK\n    High word mask for the exponent of a double-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT64_HIGH_WORD_EXPONENT_MASK\n    2146435072\n    > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_EXPONENT_MASK )\n    '01111111111100000000000000000000'\n\n    See Also\n    --------\n    FLOAT64_HIGH_WORD_SIGNIFICAND_MASK, FLOAT64_HIGH_WORD_SIGN_MASK, FLOAT64_HIGH_WORD_ABS_MASK\n","FLOAT64_HIGH_WORD_SIGN_MASK":"\nFLOAT64_HIGH_WORD_SIGN_MASK\n    High word mask for the sign bit of a double-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT64_HIGH_WORD_SIGN_MASK\n    2147483648\n    > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGN_MASK )\n    '10000000000000000000000000000000'\n\n    See Also\n    --------\n    FLOAT64_HIGH_WORD_EXPONENT_MASK, FLOAT64_HIGH_WORD_SIGNIFICAND_MASK, FLOAT64_HIGH_WORD_ABS_MASK\n","FLOAT64_HIGH_WORD_SIGNIFICAND_MASK":"\nFLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n    High word mask for the significand of a double-precision floating-point\n    number.\n\n    Examples\n    --------\n    > FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n    1048575\n    > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGNIFICAND_MASK )\n    '00000000000011111111111111111111'\n\n    See Also\n    --------\n    FLOAT64_HIGH_WORD_EXPONENT_MASK, FLOAT64_HIGH_WORD_SIGN_MASK, FLOAT64_HIGH_WORD_ABS_MASK\n","FLOAT64_MAX":"\nFLOAT64_MAX\n    Maximum double-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT64_MAX\n    1.7976931348623157e+308\n\n    See Also\n    --------\n    FLOAT16_MAX, FLOAT32_MAX\n","FLOAT64_MAX_BASE2_EXPONENT":"\nFLOAT64_MAX_BASE2_EXPONENT\n    The maximum biased base 2 exponent for a double-precision floating-point\n    number.\n\n    Examples\n    --------\n    > FLOAT64_MAX_BASE2_EXPONENT\n    1023\n\n    See Also\n    --------\n    FLOAT64_MAX_BASE10_EXPONENT, FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n    The maximum biased base 2 exponent for a subnormal double-precision\n    floating-point number.\n\n    Examples\n    --------\n    > FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n    -1023\n\n    See Also\n    --------\n    FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE2_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_BASE10_EXPONENT":"\nFLOAT64_MAX_BASE10_EXPONENT\n    The maximum base 10 exponent for a double-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT64_MAX_BASE10_EXPONENT\n    308\n\n    See Also\n    --------\n    FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE2_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT\n","FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n    The maximum base 10 exponent for a subnormal double-precision floating-point\n    number.\n\n    Examples\n    --------\n    > FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n    -308\n\n    See Also\n    --------\n    FLOAT64_MAX_BASE10_EXPONENT, FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_LN":"\nFLOAT64_MAX_LN\n    Natural logarithm of the maximum double-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT64_MAX_LN\n    709.782712893384\n\n    See Also\n    --------\n    FLOAT64_MIN_LN\n","FLOAT64_MAX_SAFE_FIBONACCI":"\nFLOAT64_MAX_SAFE_FIBONACCI\n    Maximum safe Fibonacci number when stored in double-precision floating-point\n    format.\n\n    Examples\n    --------\n    > FLOAT64_MAX_SAFE_FIBONACCI\n    8944394323791464\n\n    See Also\n    --------\n    FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT64_MAX_SAFE_INTEGER":"\nFLOAT64_MAX_SAFE_INTEGER\n    Maximum safe double-precision floating-point integer.\n\n    The maximum safe double-precision floating-point integer is given by\n    `2^53 - 1`.\n\n    Examples\n    --------\n    > FLOAT64_MAX_SAFE_INTEGER\n    9007199254740991\n\n    See Also\n    --------\n    FLOAT16_MAX_SAFE_INTEGER, FLOAT32_MAX_SAFE_INTEGER, FLOAT64_MIN_SAFE_INTEGER\n","FLOAT64_MAX_SAFE_LUCAS":"\nFLOAT64_MAX_SAFE_LUCAS\n    Maximum safe Lucas number when stored in double-precision floating-point\n    format.\n\n    Examples\n    --------\n    > FLOAT64_MAX_SAFE_LUCAS\n    7639424778862807\n\n    See Also\n    --------\n    FLOAT64_MAX_SAFE_FIBONACCI, FLOAT64_MAX_SAFE_NTH_LUCAS\n","FLOAT64_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT64_MAX_SAFE_NTH_FIBONACCI\n    Maximum safe nth Fibonacci number when stored in double-precision floating-\n    point format.\n\n    Examples\n    --------\n    > FLOAT64_MAX_SAFE_NTH_FIBONACCI\n    78\n\n    See Also\n    --------\n    FLOAT64_MAX_SAFE_FIBONACCI\n","FLOAT64_MAX_SAFE_NTH_LUCAS":"\nFLOAT64_MAX_SAFE_NTH_LUCAS\n    Maximum safe nth Lucas number when stored in double-precision floating-point\n    format.\n\n    Examples\n    --------\n    > FLOAT64_MAX_SAFE_NTH_LUCAS\n    76\n\n    See Also\n    --------\n    FLOAT64_MAX_SAFE_LUCAS, FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT64_MIN_BASE2_EXPONENT":"\nFLOAT64_MIN_BASE2_EXPONENT\n    The minimum biased base 2 exponent for a normalized double-precision\n    floating-point number.\n\n    Examples\n    --------\n    > FLOAT64_MIN_BASE2_EXPONENT\n    -1022\n\n    See Also\n    --------\n    FLOAT64_MAX_BASE2_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n    The minimum biased base 2 exponent for a subnormal double-precision\n    floating-point number.\n\n    Examples\n    --------\n    > FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n    -1074\n\n    See Also\n    --------\n    FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MIN_BASE10_EXPONENT":"\nFLOAT64_MIN_BASE10_EXPONENT\n    The minimum base 10 exponent for a normalized double-precision floating-\n    point number.\n\n    Examples\n    --------\n    > FLOAT64_MIN_BASE10_EXPONENT\n    -308\n\n    See Also\n    --------\n    FLOAT64_MAX_BASE10_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n    The minimum base 10 exponent for a subnormal double-precision floating-\n    point number.\n\n    Examples\n    --------\n    > FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n    -324\n\n    See Also\n    --------\n    FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_LN":"\nFLOAT64_MIN_LN\n    Natural logarithm of the smallest normalized double-precision floating-point\n    number.\n\n    Examples\n    --------\n    > FLOAT64_MIN_LN\n    -708.3964185322641\n\n    See Also\n    --------\n    FLOAT64_MAX_LN\n","FLOAT64_MIN_SAFE_INTEGER":"\nFLOAT64_MIN_SAFE_INTEGER\n    Minimum safe double-precision floating-point integer.\n\n    The minimum safe double-precision floating-point integer is given by\n    `-(2^53 - 1)`.\n\n    Examples\n    --------\n    > FLOAT64_MIN_SAFE_INTEGER\n    -9007199254740991\n\n    See Also\n    --------\n    FLOAT16_MIN_SAFE_INTEGER, FLOAT32_MIN_SAFE_INTEGER, FLOAT64_MAX_SAFE_INTEGER\n","FLOAT64_NUM_BYTES":"\nFLOAT64_NUM_BYTES\n    Size (in bytes) of a double-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT64_NUM_BYTES\n    8\n\n    See Also\n    --------\n    FLOAT16_NUM_BYTES, FLOAT32_NUM_BYTES\n","FLOAT64_PRECISION":"\nFLOAT64_PRECISION\n    Effective number of bits in the significand of a double-precision floating-\n    point number.\n\n    The effective number of bits is `52` significand bits plus `1` hidden bit.\n\n    Examples\n    --------\n    > FLOAT64_PRECISION\n    53\n\n    See Also\n    --------\n    FLOAT16_PRECISION, FLOAT32_PRECISION\n","FLOAT64_SMALLEST_NORMAL":"\nFLOAT64_SMALLEST_NORMAL\n    Smallest positive normalized double-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT64_SMALLEST_NORMAL\n    2.2250738585072014e-308\n\n    See Also\n    --------\n    FLOAT32_SMALLEST_NORMAL, FLOAT64_SMALLEST_SUBNORMAL\n","FLOAT64_SMALLEST_SUBNORMAL":"\nFLOAT64_SMALLEST_SUBNORMAL\n    Smallest positive denormalized double-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT64_SMALLEST_SUBNORMAL\n    4.940656458412465e-324\n\n    See Also\n    --------\n    FLOAT32_SMALLEST_SUBNORMAL, FLOAT64_SMALLEST_NORMAL\n","Float64Array":"\nFloat64Array()\n    A typed array constructor which returns a typed array representing an array\n    of double-precision floating-point numbers in the platform byte order.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Float64Array()\n    <Float64Array>\n\n\nFloat64Array( length )\n    Returns a typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 5 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat64Array( typedarray )\n    Creates a typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float32Array( [ 0.5, 0.5, 0.5 ] );\n    > var arr2 = new Float64Array( arr1 )\n    <Float64Array>[ 0.5, 0.5, 0.5 ]\n\n\nFloat64Array( obj )\n    Creates a typed array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a typed array.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 0.5, 0.5, 0.5 ];\n    > var arr2 = new Float64Array( arr1 )\n    <Float64Array>[ 0.5, 0.5, 0.5 ]\n\n\nFloat64Array( buffer[, byteOffset[, length]] )\n    Returns a typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 32 );\n    > var arr = new Float64Array( buf, 0, 4 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat64Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2.0; };\n    > var arr = Float64Array.from( [ 1.0, -1.0 ], mapFcn )\n    <Float64Array>[ 2.0, -2.0 ]\n\n\nFloat64Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Float64Array.of( 2.0, -2.0 )\n    <Float64Array>[ 2.0, -2.0 ]\n\n\nFloat64Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Float64Array.BYTES_PER_ELEMENT\n    8\n\n\nFloat64Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Float64Array.name\n    'Float64Array'\n\n\nFloat64Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>\n\n\nFloat64Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 5 );\n    > arr.byteLength\n    40\n\n\nFloat64Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 5 );\n    > arr.byteOffset\n    0\n\n\nFloat64Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    8\n\n\nFloat64Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 5 );\n    > arr.length\n    5\n\n\nFloat64Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Float64Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    2.0\n    > arr[ 4 ]\n    -2.0\n\n\nFloat64Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1.0 ]\n    > it.next().value\n    [ 1, -1.0 ]\n    > it.next().done\n    true\n\n\nFloat64Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > function predicate( v ) { return ( v >= 0.0 ); };\n    > arr.every( predicate )\n    false\n\n\nFloat64Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Float64Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > arr.fill( 2.0 );\n    > arr[ 0 ]\n    2.0\n    > arr[ 1 ]\n    2.0\n\n\nFloat64Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v >= 0.0 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2\n\n\nFloat64Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > var v = arr.find( predicate )\n    -1.0\n\n\nFloat64Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > var idx = arr.findIndex( predicate )\n    2\n\n\nFloat64Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:1 1:0 2:-1 '\n\n\nFloat64Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > var bool = arr.includes( 2.0 )\n    false\n    > bool = arr.includes( -1.0 )\n    true\n\n\nFloat64Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > var idx = arr.indexOf( 2.0 )\n    -1\n    > idx = arr.indexOf( -1.0 )\n    2\n\n\nFloat64Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > arr.join( '|' )\n    '1|0|-1'\n\n\nFloat64Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true\n\n\nFloat64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n    > var idx = arr.lastIndexOf( 2.0 )\n    -1\n    > idx = arr.lastIndexOf( 0.0 )\n    3\n\n\nFloat64Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( v ) { return v * 2.0; };\n    > var arr2 = arr1.map( fcn )\n    <Float64Array>[ 2.0, 0.0, -2.0 ]\n\n\nFloat64Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0.0 )\n    2.0\n\n\nFloat64Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0.0 )\n    2.0\n\n\nFloat64Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Float64Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] )\n    <Float64Array>\n    > arr.reverse()\n    <Float64Array>[ -1.0, 0.0, 1.0 ]\n\n\nFloat64Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > arr.set( [ -2.0, 2.0 ], 1 );\n    > arr[ 1 ]\n    -2.0\n    > arr[ 2 ]\n    2.0\n\n\nFloat64Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    0.0\n    > arr2[ 1 ]\n    -1.0\n\n\nFloat64Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > arr.some( predicate )\n    true\n\n\nFloat64Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Float64Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n    > arr.sort()\n    <Float64Array>[ -2.0, -1.0, 0.0, 1.0, 2.0 ]\n\n\nFloat64Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Float64Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Float64Array>[ 0.0, 2.0, -2.0 ]\n\n\nFloat64Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n    > arr.toLocaleString()\n    '1,-1,0'\n\n\nFloat64Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n    > arr.toString()\n    '1,-1,0'\n\n\nFloat64Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > it = arr.values();\n    > it.next().value\n    1.0\n    > it.next().value\n    -1.0\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Float64Array.from":"\nFloat64Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2.0; };\n    > var arr = Float64Array.from( [ 1.0, -1.0 ], mapFcn )\n    <Float64Array>[ 2.0, -2.0 ]","Float64Array.of":"\nFloat64Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Float64Array.of( 2.0, -2.0 )\n    <Float64Array>[ 2.0, -2.0 ]","Float64Array.BYTES_PER_ELEMENT":"\nFloat64Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Float64Array.BYTES_PER_ELEMENT\n    8","Float64Array.name":"\nFloat64Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Float64Array.name\n    'Float64Array'","Float64Array.prototype.buffer":"\nFloat64Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>","Float64Array.prototype.byteLength":"\nFloat64Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 5 );\n    > arr.byteLength\n    40","Float64Array.prototype.byteOffset":"\nFloat64Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 5 );\n    > arr.byteOffset\n    0","Float64Array.prototype.BYTES_PER_ELEMENT":"\nFloat64Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    8","Float64Array.prototype.length":"\nFloat64Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 5 );\n    > arr.length\n    5","Float64Array.prototype.copyWithin":"\nFloat64Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Float64Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    2.0\n    > arr[ 4 ]\n    -2.0","Float64Array.prototype.entries":"\nFloat64Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1.0 ]\n    > it.next().value\n    [ 1, -1.0 ]\n    > it.next().done\n    true","Float64Array.prototype.every":"\nFloat64Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > function predicate( v ) { return ( v >= 0.0 ); };\n    > arr.every( predicate )\n    false","Float64Array.prototype.fill":"\nFloat64Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Float64Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > arr.fill( 2.0 );\n    > arr[ 0 ]\n    2.0\n    > arr[ 1 ]\n    2.0","Float64Array.prototype.filter":"\nFloat64Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v >= 0.0 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2","Float64Array.prototype.find":"\nFloat64Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > var v = arr.find( predicate )\n    -1.0","Float64Array.prototype.findIndex":"\nFloat64Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > var idx = arr.findIndex( predicate )\n    2","Float64Array.prototype.forEach":"\nFloat64Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:1 1:0 2:-1 '","Float64Array.prototype.includes":"\nFloat64Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > var bool = arr.includes( 2.0 )\n    false\n    > bool = arr.includes( -1.0 )\n    true","Float64Array.prototype.indexOf":"\nFloat64Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > var idx = arr.indexOf( 2.0 )\n    -1\n    > idx = arr.indexOf( -1.0 )\n    2","Float64Array.prototype.join":"\nFloat64Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > arr.join( '|' )\n    '1|0|-1'","Float64Array.prototype.keys":"\nFloat64Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true","Float64Array.prototype.lastIndexOf":"\nFloat64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n    > var idx = arr.lastIndexOf( 2.0 )\n    -1\n    > idx = arr.lastIndexOf( 0.0 )\n    3","Float64Array.prototype.map":"\nFloat64Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( v ) { return v * 2.0; };\n    > var arr2 = arr1.map( fcn )\n    <Float64Array>[ 2.0, 0.0, -2.0 ]","Float64Array.prototype.reduce":"\nFloat64Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0.0 )\n    2.0","Float64Array.prototype.reduceRight":"\nFloat64Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0.0 )\n    2.0","Float64Array.prototype.reverse":"\nFloat64Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Float64Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] )\n    <Float64Array>\n    > arr.reverse()\n    <Float64Array>[ -1.0, 0.0, 1.0 ]","Float64Array.prototype.set":"\nFloat64Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > arr.set( [ -2.0, 2.0 ], 1 );\n    > arr[ 1 ]\n    -2.0\n    > arr[ 2 ]\n    2.0","Float64Array.prototype.slice":"\nFloat64Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    0.0\n    > arr2[ 1 ]\n    -1.0","Float64Array.prototype.some":"\nFloat64Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > arr.some( predicate )\n    true","Float64Array.prototype.sort":"\nFloat64Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Float64Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n    > arr.sort()\n    <Float64Array>[ -2.0, -1.0, 0.0, 1.0, 2.0 ]","Float64Array.prototype.subarray":"\nFloat64Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Float64Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Float64Array>[ 0.0, 2.0, -2.0 ]","Float64Array.prototype.toLocaleString":"\nFloat64Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n    > arr.toLocaleString()\n    '1,-1,0'","Float64Array.prototype.toString":"\nFloat64Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n    > arr.toString()\n    '1,-1,0'","Float64Array.prototype.values":"\nFloat64Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > it = arr.values();\n    > it.next().value\n    1.0\n    > it.next().value\n    -1.0\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","forEach":"\nforEach( collection, fcn[, thisArg] )\n    Invokes a function for each element in a collection.\n\n    When invoked, the input function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n    > var arr = [ 1, 2, 3, 4 ];\n    > forEach( arr, logger )\n    0: 1\n    1: 2\n    2: 3\n    3: 4\n\n    See Also\n    --------\n    forEachAsync, forEachRight\n","forEachAsync":"\nforEachAsync( collection, [options,] fcn, done )\n    Invokes a function once for each element in a collection.\n\n    When invoked, `fcn` is provided a maximum of four arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If `fcn`\n    accepts two arguments, `fcn` is provided:\n\n    - value\n    - next\n\n    If `fcn` accepts three arguments, `fcn` is provided:\n\n    - value\n    - index\n    - next\n\n    For every other `fcn` signature, `fcn` is provided all four arguments.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function onDuration( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next();\n    ...     }\n    ... };\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( 'Done.' );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > forEachAsync( arr, onDuration, done )\n    1000\n    2500\n    3000\n    Done.\n\n    // Limit number of concurrent invocations:\n    > function onDuration( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next();\n    ...     }\n    ... };\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( 'Done.' );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 3000, 2500, 1000 ];\n    > forEachAsync( arr, opts, onDuration, done )\n    2500\n    3000\n    1000\n    Done.\n\n    // Process sequentially:\n    > function onDuration( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next();\n    ...     }\n    ... };\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( 'Done.' );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 3000, 2500, 1000 ];\n    > forEachAsync( arr, opts, onDuration, done )\n    3000\n    2500\n    1000\n    Done.\n\n\nforEachAsync.factory( [options,] fcn )\n    Returns a function which invokes a function once for each element in a\n    collection.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function onDuration( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next();\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = forEachAsync.factory( opts, onDuration );\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( 'Done.' );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    Done.\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    Done.\n\n    See Also\n    --------\n    forEach, forEachRightAsync\n","forEachAsync.factory":"\nforEachAsync.factory( [options,] fcn )\n    Returns a function which invokes a function once for each element in a\n    collection.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function onDuration( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next();\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = forEachAsync.factory( opts, onDuration );\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( 'Done.' );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    Done.\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    Done.\n\n    See Also\n    --------\n    forEach, forEachRightAsync","forEachChar":"\nforEachChar( str, [options,] clbk[, thisArg] )\n    Invokes a function for each character in a string.\n\n    When invoked, the provided function is provided three arguments:\n\n    - value: character.\n    - index: starting character index.\n    - str: input string.\n\n    Parameters\n    ----------\n    str: string\n        Input string over which to iterate.\n\n    options: Object (optional)\n        Options.\n\n    options.mode: string (optional)\n        Type of characters over which to iterate. The following modes are\n        supported:\n\n        - grapheme: grapheme clusters. Appropriate for strings containing visual\n          characters which can span multiple Unicode code points (e.g., emoji).\n        - code_point: Unicode code points. Appropriate for strings containing\n          visual characters which are comprised of more than one Unicode code\n          unit (e.g., ideographic symbols and punctuation and mathematical\n          alphanumerics).\n        - code_unit': UTF-16 code units. Appropriate for strings containing\n          visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n          common characters, such as those from the Latin, Greek, and Cyrillic\n          alphabets).\n\n        Default: 'grapheme'.\n\n    clbk: Function\n        The function to invoke for each character in the input string.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: string\n        Input string.\n\n    Examples\n    --------\n    > var n = 0;\n    > function fcn() { n += 1; };\n    > forEachChar( 'hello world!', fcn );\n    > n\n    12\n\n    See Also\n    --------\n    forEach\n","forEachRight":"\nforEachRight( collection, fcn[, thisArg] )\n    Invokes a function for each element in a collection, iterating from right to\n    left.\n\n    When invoked, the input function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n    > var arr = [ 1, 2, 3, 4 ];\n    > forEachRight( arr, logger )\n    3: 4\n    2: 3\n    1: 2\n    0: 1\n\n    See Also\n    --------\n    forEach, forEachRightAsync\n","forEachRightAsync":"\nforEachRightAsync( collection, [options,] fcn, done )\n    Invokes a function once for each element in a collection, iterating from\n    right to left.\n\n    When invoked, `fcn` is provided a maximum of four arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If `fcn`\n    accepts two arguments, `fcn` is provided:\n\n    - value\n    - next\n\n    If `fcn` accepts three arguments, `fcn` is provided:\n\n    - value\n    - index\n    - next\n\n    For every other `fcn` signature, `fcn` is provided all four arguments.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function onDuration( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next();\n    ...     }\n    ... };\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( 'Done.' );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > forEachRightAsync( arr, onDuration, done )\n    1000\n    2500\n    3000\n    Done.\n\n    // Limit number of concurrent invocations:\n    > function onDuration( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next();\n    ...     }\n    ... };\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( 'Done.' );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 1000, 2500, 3000 ];\n    > forEachRightAsync( arr, opts, onDuration, done )\n    2500\n    3000\n    1000\n    Done.\n\n    // Process sequentially:\n    > function onDuration( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next();\n    ...     }\n    ... };\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( 'Done.' );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 1000, 2500, 3000 ];\n    > forEachRightAsync( arr, opts, onDuration, done )\n    3000\n    2500\n    1000\n    Done.\n\n\nforEachRightAsync.factory( [options,] fcn )\n    Returns a function which invokes a function once for each element in a\n    collection, iterating from right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function onDuration( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next();\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = forEachRightAsync.factory( opts, onDuration );\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( 'Done.' );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    Done.\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    Done.\n\n    See Also\n    --------\n    forEachAsync, forEachRight\n","forEachRightAsync.factory":"\nforEachRightAsync.factory( [options,] fcn )\n    Returns a function which invokes a function once for each element in a\n    collection, iterating from right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function onDuration( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next();\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = forEachRightAsync.factory( opts, onDuration );\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( 'Done.' );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    Done.\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    Done.\n\n    See Also\n    --------\n    forEachAsync, forEachRight","forIn":"\nforIn( obj, fcn[, thisArg] )\n    Invokes a function for each own and inherited enumerable property of an\n    object.\n\n    When invoked, the function is provided three arguments:\n\n    - value: object property value.\n    - key: object property.\n    - obj: the input object.\n\n    To terminate iteration before visiting all properties, the provided function\n    must explicitly return `false`.\n\n    Property iteration order is *not* guaranteed.\n\n    Parameters\n    ----------\n    obj: Object\n        Input object, including arrays, typed arrays, and other collections.\n\n    fcn: Function\n        The function to invoke for each own enumerable property.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Object\n        Input object.\n\n    Examples\n    --------\n    > function logger( v, k ) { console.log( '%s: %d', k, v ); };\n    > function Foo() { return this; };\n    > Foo.prototype.beep = 'boop';\n    > var obj = new Foo();\n    > forIn( obj, logger )\n    beep: boop\n\n    See Also\n    --------\n    forEach, forOwn\n","format":"\nformat( str, ...args )\n    Insert supplied variable values into a format string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    args: ...any\n        Variable values.\n\n    Returns\n    -------\n    out: string\n        Formatted string.\n\n    Examples\n    --------\n    > var out = format( 'Hello, %s!', 'World' )\n    'Hello, World!'\n\n    > out = format( '%s %s', 'Hello', 'World' )\n    'Hello World'\n\n    > out = format( 'Pi: %.2f', PI )\n    'Pi: 3.14'\n\n","forOwn":"\nforOwn( obj, fcn[, thisArg] )\n    Invokes a function for each own enumerable property of an object.\n\n    When invoked, the function is provided three arguments:\n\n    - value: object property value.\n    - key: object property.\n    - obj: the input object.\n\n    To terminate iteration before visiting all properties, the provided function\n    must explicitly return `false`.\n\n    The function determines the list of own enumerable properties *before*\n    invoking the provided function. Hence, any modifications made to the input\n    object *after* calling this function (such as adding and removing\n    properties) will *not* affect the list of visited properties.\n\n    Property iteration order is *not* guaranteed.\n\n    Parameters\n    ----------\n    obj: Object\n        Input object, including arrays, typed arrays, and other collections.\n\n    fcn: Function\n        The function to invoke for each own enumerable property.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Object\n        Input object.\n\n    Examples\n    --------\n    > function logger( v, k ) { console.log( '%s: %d', k, v ); };\n    > var obj = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\n    > forOwn( obj, logger )\n    a: 1\n    b: 2\n    c: 3\n    d: 4\n\n    See Also\n    --------\n    forEach, forIn\n","FOURTH_PI":"\nFOURTH_PI\n    One fourth times the mathematical constant `π`.\n\n    Examples\n    --------\n    > FOURTH_PI\n    7.85398163397448309616e-1\n\n    See Also\n    --------\n    PI\n","FOURTH_ROOT_EPS":"\nFOURTH_ROOT_EPS\n    Fourth root of double-precision floating-point epsilon.\n\n    Examples\n    --------\n    > FOURTH_ROOT_EPS\n    0.0001220703125\n\n    See Also\n    --------\n    EPS\n","FRB_SF_WAGE_RIGIDITY":"\nFRB_SF_WAGE_RIGIDITY()\n    Returns wage rates for U.S. workers that have not changed jobs within the\n    year.\n\n    Each array element has the following fields:\n\n    - date: collection date (month/day/year; e.g., 01/01/1980).\n    - all_workers: wage rates for hourly and non-hourly workers.\n    - hourly_workers: wage rates for hourly workers.\n    - non_hourly_workers: wage rates for non-hourly workers.\n    - less_than_high_school: wage rates for workers with less than a high school\n      education.\n    - high_school: wage rates for workers with a high school education.\n    - some_college: wage rates for workers with some college education.\n    - college: wage rates for workers with a college education.\n    - construction: wage rates for workers in the construction industry.\n    - finance: wage rates for workers in the finance industry.\n    - manufacturing: wage rates for workers in the manufacturing industry.\n\n    Returns\n    -------\n    out: Array<Object>\n        Wage rates.\n\n    Examples\n    --------\n    > var data = FRB_SF_WAGE_RIGIDITY()\n    [ {...}, {...}, ... ]\n\n    References\n    ----------\n    - Federal Reserve Bank of San Francisco. 2017. \"Wage Rigidity.\" <http://www.\n    frbsf.org/economic-research/indicators-data/nominal-wage-rigidity/>.\n\n","fromCodePoint":"\nfromCodePoint( ...pt )\n    Creates a string from a sequence of Unicode code points.\n\n    In addition to multiple arguments, the function also supports providing an\n    array-like object as a single argument containing a sequence of Unicode code\n    points.\n\n    Parameters\n    ----------\n    pt: ...integer\n        Sequence of Unicode code points.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = fromCodePoint( 9731 )\n    '☃'\n    > out = fromCodePoint( [ 9731 ] )\n    '☃'\n    > out = fromCodePoint( 97, 98, 99 )\n    'abc'\n    > out = fromCodePoint( [ 97, 98, 99 ] )\n    'abc'\n\n    See Also\n    --------\n    codePointAt\n","Function":"\nFunction( [...argNames,] body )\n    Returns a Function object.\n\n    Argument names must be strings corresponding to valid JavaScript parameters\n    (i.e., a plain identifier, or, in environments supporting such parameters, a\n    rest parameter or destructured parameter, optionally with a default).\n\n    Parameters\n    ----------\n    argNames: ...any (optional)\n        Parameter names.\n\n    body: string\n        Function body.\n\n    Returns\n    -------\n    fcn: Function\n        Function object.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f( 1, 2 )\n    3\n\n\nFunction.prototype.apply( thisArg, args )\n    Calls a function with a given `this` value and arguments provided as an\n    array (or array-like object).\n\n    Parameters\n    ----------\n    thisArg: any\n        Value to use as `this` when executing the function.\n\n    args: Array\n        Array of arguments to pass to the function.\n\n    Returns\n    -------\n    out: any\n        Function return value.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.apply( null, [ 1, 2 ] )\n    3\n\nFunction.prototype.call( thisArg, ...args )\n    Calls a function with a given `this` value and arguments provided\n    individually.\n\n    Parameters\n    ----------\n    thisArg: any\n        Value to use as `this` when executing the function.\n\n    args: ...any\n        Arguments to pass to the function.\n\n    Returns\n    -------\n    out: any\n        Function return value.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.call( null, 1, 2 )\n    3\n\nFunction.prototype.bind( thisArg, ...args )\n    Creates a new function which, when called, has its `this` keyword set to the\n    provided value, with a given sequence of arguments preceding any provided\n    when the new function is called.\n\n    Parameters\n    ----------\n    thisArg: any\n        Value to use as `this` when executing the function.\n\n    args: ...any\n        Arguments to pass to the function.\n\n    Returns\n    -------\n    fcn: Function\n        Bound function.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > var g = f.bind( null, 1 );\n    > g( 2 )\n    3\n\nFunction.prototype.toString()\n    Returns a string representation of the function.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.toString()\n    'function anonymous( x, y ) { return x + y; }'\n\nFunction.prototype.length\n    The number of arguments expected by the function.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.length\n    2\n\nFunction.prototype.name\n    The name of the function.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.name\n    'anonymous'\n\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.name = 'add';\n    > f.name\n    'add'\n\nFunction.prototype.prototype\n    The prototype of the function.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.prototype\n    {}\n\n","Function.prototype.apply":"\nFunction.prototype.apply( thisArg, args )\n    Calls a function with a given `this` value and arguments provided as an\n    array (or array-like object).\n\n    Parameters\n    ----------\n    thisArg: any\n        Value to use as `this` when executing the function.\n\n    args: Array\n        Array of arguments to pass to the function.\n\n    Returns\n    -------\n    out: any\n        Function return value.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.apply( null, [ 1, 2 ] )\n    3","Function.prototype.call":"\nFunction.prototype.call( thisArg, ...args )\n    Calls a function with a given `this` value and arguments provided\n    individually.\n\n    Parameters\n    ----------\n    thisArg: any\n        Value to use as `this` when executing the function.\n\n    args: ...any\n        Arguments to pass to the function.\n\n    Returns\n    -------\n    out: any\n        Function return value.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.call( null, 1, 2 )\n    3","Function.prototype.bind":"\nFunction.prototype.bind( thisArg, ...args )\n    Creates a new function which, when called, has its `this` keyword set to the\n    provided value, with a given sequence of arguments preceding any provided\n    when the new function is called.\n\n    Parameters\n    ----------\n    thisArg: any\n        Value to use as `this` when executing the function.\n\n    args: ...any\n        Arguments to pass to the function.\n\n    Returns\n    -------\n    fcn: Function\n        Bound function.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > var g = f.bind( null, 1 );\n    > g( 2 )\n    3","Function.prototype.toString":"\nFunction.prototype.toString()\n    Returns a string representation of the function.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.toString()\n    'function anonymous( x, y ) { return x + y; }'","Function.prototype.length":"\nFunction.prototype.length\n    The number of arguments expected by the function.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.length\n    2","Function.prototype.name":"\nFunction.prototype.name\n    The name of the function.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.name\n    'anonymous'\n\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.name = 'add';\n    > f.name\n    'add'","Function.prototype.prototype":"\nFunction.prototype.prototype\n    The prototype of the function.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.prototype\n    {}","function2string":"\nfunction2string( fcn )\n    Returns a string representing the source code of a provided function.\n\n    If called on built-in functions, functions created by `Function#bind()`, or\n    other non-JavaScript functions, the function returns a \"native\" function\n    string similar to the following:\n\n      \"function foo() { [native code] }\"\n\n    For intrinsic object methods and functions, `foo` is the initial name of the\n    function.\n\n    If called on a function created by the `Function` constructor, the function\n    returns the source code of a synthesized function declaration having the\n    name \"anonymous\" and using the provided parameters and function body.\n\n    Starting in ES2018, the ECMAScript specification requires that the returned\n    string contain the exact same source code as it was declared, including any\n    whitespace and/or comments. If the host is unable to access the source code,\n    the specification requires that the returned string be the native function\n    string.\n\n    Parameters\n    ----------\n    fcn: Function\n        Input function.\n\n    Returns\n    -------\n    out: string\n        String representing the function's source code.\n\n    Examples\n    --------\n    > function2string( base.erf )\n    <string>\n\n    See Also\n    --------\n    Function\n","functionName":"\nfunctionName( fcn )\n    Returns the name of a function.\n\n    If provided an anonymous function, the function returns an empty `string` or\n    the string `\"anonymous\"`.\n\n\n    Parameters\n    ----------\n    fcn: Function\n        Input function.\n\n    Returns\n    -------\n    out: string\n        Function name.\n\n    Examples\n    --------\n    > var v = functionName( String )\n    'String'\n    > v = functionName( function foo(){} )\n    'foo'\n    > v = functionName( function(){} )\n    '' || 'anonymous'\n\n    See Also\n    --------\n    constructorName\n","functionSequence":"\nfunctionSequence( ...fcn )\n    Returns a pipeline function.\n\n    Starting from the left, the pipeline function evaluates each function and\n    passes the result as an argument to the next function. The result of the\n    rightmost function is the result of the whole.\n\n    Only the leftmost function is explicitly permitted to accept multiple\n    arguments. All other functions are evaluated as unary functions.\n\n    Parameters\n    ----------\n    fcn: ...Function\n        Functions to evaluate in sequential order.\n\n    Returns\n    -------\n    out: Function\n        Pipeline function.\n\n    Examples\n    --------\n    > function a( x ) { return 2 * x; };\n    > function b( x ) { return x + 3; };\n    > function c( x ) { return x / 5; };\n    > var f = functionSequence( a, b, c );\n    > var z = f( 6 )\n    3\n\n    See Also\n    --------\n    compose, functionSequenceAsync\n","functionSequenceAsync":"\nfunctionSequenceAsync( ...fcn )\n    Returns a pipeline function.\n\n    Starting from the left, the pipeline function evaluates each function and\n    passes the result as the first argument of the next function. The result of\n    the rightmost function is the result of the whole.\n\n    The last argument for each provided function is a `next` callback which\n    should be invoked upon function completion. The callback accepts two\n    arguments:\n\n    - error: error argument.\n    - result: function result.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the pipeline function suspends execution and immediately calls the\n    `done` callback for subsequent `error` handling.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Only the leftmost function is explicitly permitted to accept multiple\n    arguments. All other functions are evaluated as binary functions.\n\n    The function will throw if provided fewer than two input arguments.\n\n    Parameters\n    ----------\n    fcn: ...Function\n        Functions to evaluate in sequential order.\n\n    Returns\n    -------\n    out: Function\n        Pipeline function.\n\n    Examples\n    --------\n    > function a( x, next ) {\n    ...    setTimeout( onTimeout, 0 );\n    ...    function onTimeout() {\n    ...        next( null, 2*x );\n    ...    }\n    ... };\n    > function b( x, next ) {\n    ...    setTimeout( onTimeout, 0 );\n    ...    function onTimeout() {\n    ...        next( null, x+3 );\n    ...    }\n    ... };\n    > function c( x, next ) {\n    ...    setTimeout( onTimeout, 0 );\n    ...    function onTimeout() {\n    ...        next( null, x/5 );\n    ...    }\n    ... };\n    > var f = functionSequenceAsync( a, b, c );\n    > function done( error, result ) {\n    ...    if ( error ) {\n    ...        throw error;\n    ...    }\n    ...    console.log( result );\n    ... };\n    > f( 6, done )\n    3\n\n    See Also\n    --------\n    composeAsync, functionSequence\n","GAMMA_LANCZOS_G":"\nGAMMA_LANCZOS_G\n    Arbitrary constant `g` to be used in Lanczos approximation functions.\n\n    Examples\n    --------\n    > GAMMA_LANCZOS_G\n    10.900511\n\n","gdot":"\ngdot( x, y )\n    Computes the dot product of two vectors.\n\n    In general, for best performance, especially for large vectors, provide\n    1-dimensional ndarrays whose underlying data type is either 'float64' or\n    'float32'.\n\n    If provided empty vectors, the function returns `0.0`.\n\n    Parameters\n    ----------\n    x: ndarray|ArrayLikeObject\n        First input array.\n\n    y: ndarray|ArrayLikeObject\n        Second input array.\n\n    Returns\n    -------\n    dot: number\n        The dot product.\n\n    Examples\n    --------\n    // Using ndarrays...\n    > var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n    > var y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n    > gdot( x, y )\n    -5.0\n\n    // Using array-like objects...\n    > x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n    > y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n    > gdot( x, y )\n    -5.0\n\n    See Also\n    --------\n    base.strided.gdot, ddot, sdot\n","getegid":"\ngetegid()\n    Returns the effective numeric group identity of the calling process.\n\n    The function only returns an effective group identity on POSIX platforms.\n    For all other platforms (e.g., Windows and Android), the function returns\n    `null`.\n\n    Returns\n    -------\n    id: integer|null\n        Effective numeric group identity.\n\n    Examples\n    --------\n    > var gid = getegid()\n\n    See Also\n    --------\n    geteuid, getgid, getuid\n","geteuid":"\ngeteuid()\n    Returns the effective numeric user identity of the calling process.\n\n    The function only returns an effective user identity on POSIX platforms. For\n    all other platforms (e.g., Windows and Android), the function returns\n    `null`.\n\n    Returns\n    -------\n    id: integer|null\n        Effective numeric user identity.\n\n    Examples\n    --------\n    > var uid = geteuid()\n\n    See Also\n    --------\n    getegid, getgid, getuid\n","getgid":"\ngetgid()\n    Returns the numeric group identity of the calling process.\n\n    The function only returns a group identity on POSIX platforms. For all other\n    platforms (e.g., Windows and Android), the function returns `null`.\n\n    Returns\n    -------\n    id: integer|null\n        Numeric group identity.\n\n    Examples\n    --------\n    > var gid = getgid()\n\n    See Also\n    --------\n    getegid, geteuid, getuid\n","getGlobal":"\ngetGlobal( [codegen] )\n    Returns the global object.\n\n    Parameters\n    ----------\n    codegen: boolean (optional)\n        Boolean indicating whether to use code generation to resolve the global\n        object. Code generation is the *most* reliable means for resolving the\n        global object; however, using code generation may violate content\n        security policies (CSPs). Default: false.\n\n    Returns\n    -------\n    global: Object\n        Global object.\n\n    Examples\n    --------\n    > var g = getGlobal()\n    {...}\n\n","getPrototypeOf":"\ngetPrototypeOf( value )\n    Returns the prototype of a provided object.\n\n    In contrast to the native `Object.getPrototypeOf`, this function does not\n    throw when provided `null` or `undefined`. Instead, similar to when provided\n    any value with *no* inherited properties, the function returns `null`.\n\n    Value arguments other than `null` or `undefined` are coerced to objects.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    out: Object|null\n        Prototype.\n\n    Examples\n    --------\n    > var proto = getPrototypeOf( {} )\n    {}\n\n    See Also\n    --------\n    isPrototypeOf\n","getuid":"\ngetuid()\n    Returns the numeric user identity of the calling process.\n\n    The function only returns a user identity on POSIX platforms. For all other\n    platforms (e.g., Windows and Android), the function returns `null`.\n\n    Returns\n    -------\n    id: integer|null\n        Numeric user identity.\n\n    Examples\n    --------\n    > var uid = getuid()\n\n    See Also\n    --------\n    getegid, geteuid, getgid\n","GLAISHER":"\nGLAISHER\n    Glaisher-Kinkelin constant.\n\n    Examples\n    --------\n    > GLAISHER\n    1.2824271291006226\n\n","graphemeClusters2iterator":"\ngraphemeClusters2iterator( src[, mapFcn[, thisArg]] )\n    Returns an iterator which iterates over each grapheme cluster in a string.\n\n    When invoked, an input function is provided three arguments:\n\n    - value: grapheme cluster.\n    - index: iterated value index.\n    - src: source string.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke a string's `@@iterator` method, regardless of whether this method is\n    defined. To convert a string to an implementation defined iterator, invoke\n    this method directly.\n\n    Parameters\n    ----------\n    src: string\n        String from which to create the iterator.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = graphemeClusters2iterator( '🌷🍕' );\n    > var v = it.next().value\n    '🌷'\n    > v = it.next().value\n    '🍕'\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    array2iterator, graphemeClusters2iteratorRight\n","graphemeClusters2iteratorRight":"\ngraphemeClusters2iteratorRight( src[, mapFcn[, thisArg]] )\n    Returns an iterator which iterates from right to left over each grapheme\n    cluster in a string.\n\n    When invoked, an input function is provided three arguments:\n\n    - value: grapheme cluster.\n    - index: iterated value index.\n    - src: source string.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke a string's `@@iterator` method, regardless of whether this method is\n    defined. To convert a string to an implementation defined iterator, invoke\n    this method directly.\n\n    Parameters\n    ----------\n    src: string\n        String from which to create the iterator.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = graphemeClusters2iteratorRight( '🌷🍕' );\n    > var v = it.next().value\n    '🍕'\n    > v = it.next().value\n    '🌷'\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    array2iteratorRight, graphemeClusters2iterator\n","group":"\ngroup( collection, [options,] groups )\n    Groups values as arrays associated with distinct keys.\n\n    If provided an empty collection, the function returns an empty object.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection to group. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Options.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `indices`, indices are returned; if\n        `*`, both indices and values are returned. Default: 'values'.\n\n    groups: Array|TypedArray|Object\n        A collection defining which group an element in the input collection\n        belongs to. Each value in `groups` should resolve to a value which can\n        be serialized as an object key. If provided an object, the object must\n        be array-like (excluding strings and functions).\n\n    Returns\n    -------\n    out: Object\n        Group results.\n\n    Examples\n    --------\n    > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n    > var groups = [ 'b', 'b', 'f', 'b' ];\n    > var out = group( collection, groups )\n    { 'b': [ 'beep', 'boop', 'bar' ], 'f': [ 'foo' ] }\n    > groups = [ 1, 1, 2, 1 ];\n    > out = group( collection, groups )\n    { '1': [ 'beep', 'boop', 'bar' ], '2': [ 'foo' ] }\n\n    // Output group results as indices:\n    > groups = [ 'b', 'b', 'f', 'b' ];\n    > var opts = { 'returns': 'indices' };\n    > out = group( collection, opts, groups )\n    { 'b': [ 0, 1, 3 ], 'f': [ 2 ] }\n\n    // Output group results as index-element pairs:\n    > opts = { 'returns': '*' };\n    > out = group( collection, opts, groups )\n    { 'b': [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], 'f': [ [2, 'foo'] ] }\n\n    See Also\n    --------\n    bifurcate, countBy, groupBy\n","groupBy":"\ngroupBy( collection, [options,] indicator )\n    Groups values according to an indicator function.\n\n    When invoked, the indicator function is provided two arguments:\n\n    - value: collection value.\n    - index: collection index.\n\n    The value returned by an indicator function should be a value which can be\n    serialized as an object key.\n\n    If provided an empty collection, the function returns an empty object.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection to group. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Options.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `indices`, indices are returned; if\n        `*`, both indices and values are returned. Default: 'values'.\n\n    indicator: Function\n        Indicator function specifying which group an element in the input\n        collection belongs to.\n\n    Returns\n    -------\n    out: Object\n        Group results.\n\n    Examples\n    --------\n    > function indicator( v ) {\n    ...     if ( v[ 0 ] === 'b' ) {\n    ...         return 'b';\n    ...     }\n    ...     return 'other';\n    ... };\n    > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n    > var out = groupBy( collection, indicator )\n    { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n    // Output group results as indices:\n    > var opts = { 'returns': 'indices' };\n    > out = groupBy( collection, opts, indicator )\n    { 'b': [ 0, 1, 3 ], 'other': [ 2 ] }\n\n    // Output group results as index-value pairs:\n    > opts = { 'returns': '*' };\n    > out = groupBy( collection, opts, indicator )\n    { 'b': [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], 'other': [ [2, 'foo' ] ] }\n\n    See Also\n    --------\n    bifurcateBy, countBy, group\n","groupByAsync":"\ngroupByAsync( collection, [options,] indicator, done )\n    Groups values according to an indicator function.\n\n    When invoked, the indicator function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If the\n    indicator function accepts two arguments, the indicator function is\n    provided:\n\n    - value\n    - next\n\n    If the indicator function accepts three arguments, the indicator function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other indicator function signature, the indicator function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - group: value group.\n\n    If an indicator function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    If provided an empty collection, the function calls the `done` callback with\n    an empty object as the second argument.\n\n    The `group` returned by an indicator function should be a value which can be\n    serialized as an object key.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `indices`, indices are returned; if\n        `*`, both indices and values are returned. Default: 'values'.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    indicator: Function\n        Indicator function specifying which group an element in the input\n        collection belongs to.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > groupByAsync( arr, indicator, done )\n    1000\n    2500\n    3000\n    { \"true\": [ 1000, 3000 ], \"false\": [ 2500 ] }\n\n    // Output group results as indices:\n    > var opts = { 'returns': 'indices' };\n    > groupByAsync( arr, opts, indicator, done )\n    1000\n    2500\n    3000\n    { \"true\": [ 2, 0 ], \"false\": [ 1 ] }\n\n    // Output group results as index-value pairs:\n    > opts = { 'returns': '*' };\n    > groupByAsync( arr, opts, indicator, done )\n    1000\n    2500\n    3000\n    { \"true\": [ [ 2, 1000 ], [ 0, 3000 ] ], \"false\": [ [ 1, 2500 ] ] }\n\n    // Limit number of concurrent invocations:\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 3000, 2500, 1000 ];\n    > groupByAsync( arr, opts, indicator, done )\n    2500\n    3000\n    1000\n    { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n\n    // Process sequentially:\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 3000, 2500, 1000 ];\n    > groupByAsync( arr, opts, indicator, done )\n    3000\n    2500\n    1000\n    { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n\n\ngroupByAsync.factory( [options,] indicator )\n    Returns a function which groups values according to an indicator function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `indices`, indices are returned; if\n        `*`, both indices and values are returned. Default: 'values'.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    indicator: Function\n        Indicator function specifying which group an element in the input\n        collection belongs to.\n\n    Returns\n    -------\n    out: Function\n        A group-by function.\n\n    Examples\n    --------\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = groupByAsync.factory( opts, indicator );\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    { \"true\": [ 2000, 1000 ], \"false\": [ 1500 ] }\n\n    See Also\n    --------\n    bifurcateByAsync, countByAsync, groupBy\n","groupByAsync.factory":"\ngroupByAsync.factory( [options,] indicator )\n    Returns a function which groups values according to an indicator function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `indices`, indices are returned; if\n        `*`, both indices and values are returned. Default: 'values'.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    indicator: Function\n        Indicator function specifying which group an element in the input\n        collection belongs to.\n\n    Returns\n    -------\n    out: Function\n        A group-by function.\n\n    Examples\n    --------\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = groupByAsync.factory( opts, indicator );\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    { \"true\": [ 2000, 1000 ], \"false\": [ 1500 ] }\n\n    See Also\n    --------\n    bifurcateByAsync, countByAsync, groupBy","groupIn":"\ngroupIn( obj, [options,] indicator )\n    Group values according to an indicator function.\n\n    When invoked, the indicator function is provided two arguments:\n\n    - value: object value.\n    - key: object key.\n\n    The value returned by an indicator function should be a value which can be\n    serialized as an object key.\n\n    If provided an empty object with no prototype, the function returns an empty\n    object.\n\n    The function iterates over an object's own and inherited properties.\n\n    Key iteration order is *not* guaranteed, and, thus, result order is *not*\n    guaranteed.\n\n    Parameters\n    ----------\n    obj: Object|Array|TypedArray\n        Input object to group.\n\n    options: Object (optional)\n        Options.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `keys`, keys are returned; if `*`,\n        both keys and values are returned. Default: 'values'.\n\n    indicator: Function\n        Indicator function indicating which group a value in the input object\n        belongs to.\n\n    Returns\n    -------\n    out: Object\n        Group results.\n\n    Examples\n    --------\n    > function indicator( v ) {\n    ...     if ( v[ 0 ] === 'b' ) {\n    ...         return 'b';\n    ...     }\n    ...     return 'other';\n    ... };\n    > function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\n    > Foo.prototype = Object.create( null );\n    > Foo.prototype.c = 'foo';\n    > Foo.prototype.d = 'bar';\n    > var obj = new Foo();\n    > var out = groupIn( obj, indicator )\n    { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n    // Output group results as keys:\n    > var opts = { 'returns': 'keys' };\n    > out = groupIn( obj, opts, indicator )\n    { 'b': [ 'a', 'b', 'd' ], 'other': [ 'c' ] }\n\n    // Output group results as key-value pairs:\n    > opts = { 'returns': '*' };\n    > out = groupIn( obj, opts, indicator )\n    { 'b': [['a','beep'], ['b','boop'], ['d','bar']], 'other': [['c','foo' ]] }\n\n    See Also\n    --------\n    bifurcateIn, groupBy, groupOwn\n","groupOwn":"\ngroupOwn( obj, [options,] indicator )\n    Group values according to an indicator function.\n\n    When invoked, the indicator function is provided two arguments:\n\n    - value: object value.\n    - key: object key.\n\n    The value returned by an indicator function should be a value which can be\n    serialized as an object key.\n\n    If provided an empty object, the function returns an empty object.\n\n    The function iterates over an object's own properties.\n\n    Key iteration order is *not* guaranteed, and, thus, result order is *not*\n    guaranteed.\n\n    Parameters\n    ----------\n    obj: Object|Array|TypedArray\n        Input object to group.\n\n    options: Object (optional)\n        Options.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `keys`, keys are returned; if `*`,\n        both keys and values are returned. Default: 'values'.\n\n    indicator: Function\n        Indicator function indicating which group a value in the input object\n        belongs to.\n\n    Returns\n    -------\n    out: Object\n        Group results.\n\n    Examples\n    --------\n    > function indicator( v ) {\n    ...     if ( v[ 0 ] === 'b' ) {\n    ...         return 'b';\n    ...     }\n    ...     return 'other';\n    ... };\n    > var obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\n    > var out = groupOwn( obj, indicator )\n    { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n    // Output group results as keys:\n    > var opts = { 'returns': 'keys' };\n    > out = groupOwn( obj, opts, indicator )\n    { 'b': [ 'a', 'b', 'd' ], 'other': [ 'c' ] }\n\n    // Output group results as key-value pairs:\n    > opts = { 'returns': '*' };\n    > out = groupOwn( obj, opts, indicator )\n    { 'b': [['a','beep'], ['b','boop'], ['d','bar']], 'other': [['c','foo' ]] }\n\n    See Also\n    --------\n    bifurcateOwn, group, groupBy\n","gswap":"\ngswap( x, y )\n    Interchanges two vectors.\n\n    In general, for best performance, especially for large vectors, provide\n    1-dimensional ndarrays whose underlying data type is either 'float64' or\n    'float32'.\n\n    Parameters\n    ----------\n    x: ndarray|ArrayLikeObject\n        First input array.\n\n    y: ndarray|ArrayLikeObject\n        Second input array.\n\n    Returns\n    -------\n    y: ndarray\n        The second input array `y`.\n\n    Examples\n    --------\n    // Using ndarrays...\n    > var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n    > var y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n    > gswap( x, y );\n    > x.data\n    <Float64Array>[ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n    > y.data\n    <Float64Array>[ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n    // Using array-like objects...\n    > x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n    > y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n    > gswap( x, y );\n    > x\n    [ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n    > y\n    [ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n    See Also\n    --------\n    base.strided.gswap, dswap, sswap\n","HALF_LN2":"\nHALF_LN2\n    One half times the natural logarithm of `2`.\n\n    Examples\n    --------\n    > HALF_LN2\n    3.46573590279972654709e-01\n\n    See Also\n    --------\n    LN2\n","HALF_PI":"\nHALF_PI\n    One half times the mathematical constant `π`.\n\n    Examples\n    --------\n    > HALF_PI\n    1.5707963267948966\n\n    See Also\n    --------\n    PI\n","HARRISON_BOSTON_HOUSE_PRICES":"\nHARRISON_BOSTON_HOUSE_PRICES()\n    Returns a dataset derived from information collected by the US Census\n    Service concerning housing in Boston, Massachusetts (1978).\n\n    The data consists of 14 attributes:\n\n    - crim: per capita crime rate by town.\n    - zn: proportion of residential land zoned for lots over 25,000 square feet.\n    - indus: proportion of non-retail business acres per town.\n    - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise).\n    - nox: nitric oxides concentration (parts per 10 million).\n    - rm: average number of rooms per dwelling.\n    - age: proportion of owner-occupied units built prior to 1940.\n    - dis: weighted distances to five Boston employment centers.\n    - rad: index of accessibility to radial highways.\n    - tax: full-value property-tax rate per $10,000.\n    - ptratio: pupil-teacher ratio by town.\n    - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town.\n    - lstat: percent lower status of the population.\n    - medv: median value of owner-occupied homes in $1000's.\n\n    The dataset can be used to predict two dependent variables: 1) nitrous oxide\n    level and 2) median home value.\n\n    The median home value field seems to be censored at 50.00 (corresponding to\n    a median value of $50,000). Censoring is suggested by the fact that the\n    highest median value of exactly $50,000 is reported in 16 cases, while 15\n    cases have values between $40,000 and $50,000. Values are rounded to the\n    nearest hundred. Harrison and Rubinfeld do not, however, mention any\n    censoring.\n\n    Additionally, as documented by Gilley and Pace (1996), the dataset contains\n    eight miscoded median values.\n\n    Returns\n    -------\n    out: Array<Object>\n        Boston house prices.\n\n    Examples\n    --------\n    > var data = HARRISON_BOSTON_HOUSE_PRICES()\n    [ {...}, {...}, ... ]\n\n    References\n    ----------\n    - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n    the demand for clean air.\" _Journal of Environmental Economics and\n    Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n    - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n    Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n    doi:10.1006/jeem.1996.0052.\n\n    See Also\n    --------\n    HARRISON_BOSTON_HOUSE_PRICES_CORRECTED, PACE_BOSTON_HOUSE_PRICES\n","HARRISON_BOSTON_HOUSE_PRICES_CORRECTED":"\nHARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n    Returns a (corrected) dataset derived from information collected by the US\n    Census Service concerning housing in Boston, Massachusetts (1978).\n\n    The data consists of 15 attributes:\n\n    - crim: per capita crime rate by town.\n    - zn: proportion of residential land zoned for lots over 25,000 square feet.\n    - indus: proportion of non-retail business acres per town.\n    - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise).\n    - nox: nitric oxides concentration (parts per 10 million).\n    - rm: average number of rooms per dwelling.\n    - age: proportion of owner-occupied units built prior to 1940.\n    - dis: weighted distances to five Boston employment centers.\n    - rad: index of accessibility to radial highways.\n    - tax: full-value property-tax rate per $10,000.\n    - ptratio: pupil-teacher ratio by town.\n    - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town\n    - lstat: percent lower status of the population.\n    - medv: median value of owner-occupied homes in $1000's.\n    - cmedv: corrected median value of owner-occupied homes in $1000's.\n\n    The dataset can be used to predict two dependent variables: 1) nitrous oxide\n    level and 2) median home value.\n\n    The median home value field seems to be censored at 50.00 (corresponding to\n    a median value of $50,000). Censoring is suggested by the fact that the\n    highest median value of exactly $50,000 is reported in 16 cases, while 15\n    cases have values between $40,000 and $50,000. Values are rounded to the\n    nearest hundred. Harrison and Rubinfeld do not, however, mention any\n    censoring.\n\n    The dataset contains eight corrections to miscoded median values, as\n    documented by Gilley and Pace (1996).\n\n    Returns\n    -------\n    out: Array<Object>\n        Boston house prices.\n\n    Examples\n    --------\n    > var data = HARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n    [ {...}, {...}, ... ]\n\n    References\n    ----------\n    - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n    the demand for clean air.\" _Journal of Environmental Economics and\n    Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n    - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n    Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n    doi:10.1006/jeem.1996.0052.\n\n    See Also\n    --------\n    HARRISON_BOSTON_HOUSE_PRICES, PACE_BOSTON_HOUSE_PRICES\n","hasArrayBufferSupport":"\nhasArrayBufferSupport()\n    Tests for native `ArrayBuffer` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `ArrayBuffer` support.\n\n    Examples\n    --------\n    > var bool = hasArrayBufferSupport()\n    <boolean>\n\n    See Also\n    --------\n    hasFloat32ArraySupport, hasFloat64ArraySupport, hasInt16ArraySupport, hasInt32ArraySupport, hasInt8ArraySupport, hasNodeBufferSupport, hasSharedArrayBufferSupport, hasUint16ArraySupport, hasUint32ArraySupport, hasUint8ArraySupport, hasUint8ClampedArraySupport\n","hasArrowFunctionSupport":"\nhasArrowFunctionSupport()\n    Tests whether an environment supports native arrow functions.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment support arrow functions.\n\n    Examples\n    --------\n    > var bool = hasArrowFunctionSupport()\n    <boolean>\n\n","hasAsyncAwaitSupport":"\nhasAsyncAwaitSupport()\n    Tests for native `async`/`await` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has native `async`/`await` support.\n\n    Examples\n    --------\n    > var bool = hasAsyncAwaitSupport()\n    <boolean>\n\n","hasAsyncIteratorSymbolSupport":"\nhasAsyncIteratorSymbolSupport()\n    Tests for native `Symbol.asyncIterator` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has native `Symbol.asyncIterator`\n        support.\n\n    Examples\n    --------\n    > var bool = hasAsyncIteratorSymbolSupport()\n    <boolean>\n\n    See Also\n    --------\n    hasIteratorSymbolSupport, hasSymbolSupport\n","hasAtobSupport":"\nhasAtobSupport()\n    Tests for native `atob` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `atob` support.\n\n    Examples\n    --------\n    > var bool = hasAtobSupport()\n    <boolean>\n\n    See Also\n    --------\n    hasBtoaSupport\n","hasBigInt64ArraySupport":"\nhasBigInt64ArraySupport()\n    Tests for native `BigInt64Array` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `BigInt64Array` support.\n\n    Examples\n    --------\n    > var bool = hasBigInt64ArraySupport()\n    <boolean>\n\n    See Also\n    --------\n    hasBigIntSupport, hasBigUint64ArraySupport\n","hasBigIntSupport":"\nhasBigIntSupport()\n    Tests for native `BigInt` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has native `BigInt` support.\n\n    Examples\n    --------\n    > var bool = hasBigIntSupport()\n    <boolean>\n\n","hasBigUint64ArraySupport":"\nhasBigUint64ArraySupport()\n    Tests for native `BigUint64Array` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `BigUint64Array` support.\n\n    Examples\n    --------\n    > var bool = hasBigUint64ArraySupport()\n    <boolean>\n\n    See Also\n    --------\n    hasBigIntSupport, hasBigInt64ArraySupport\n","hasBtoaSupport":"\nhasBtoaSupport()\n    Tests for native `btoa` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `btoa` support.\n\n    Examples\n    --------\n    > var bool = hasBtoaSupport()\n    <boolean>\n\n    See Also\n    --------\n    hasAtobSupport\n","hasClassSupport":"\nhasClassSupport()\n    Tests for native `class` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has native `class` support.\n\n    Examples\n    --------\n    > var bool = hasClassSupport()\n    <boolean>\n\n","hasDataViewSupport":"\nhasDataViewSupport()\n    Tests for native `DataView` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `DataView` support.\n\n    Examples\n    --------\n    > var bool = hasDataViewSupport()\n    <boolean>\n\n    See Also\n    --------\n    hasArrayBufferSupport\n","hasDefinePropertiesSupport":"\nhasDefinePropertiesSupport()\n    Tests for `Object.defineProperties` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Object.defineProperties`\n        support.\n\n    Examples\n    --------\n    > var bool = hasDefinePropertiesSupport()\n    <boolean>\n\n    See Also\n    --------\n    hasDefinePropertySupport\n","hasDefinePropertySupport":"\nhasDefinePropertySupport()\n    Tests for `Object.defineProperty` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Object.defineProperty`\n        support.\n\n    Examples\n    --------\n    > var bool = hasDefinePropertySupport()\n    <boolean>\n\n    See Also\n    --------\n    hasDefinePropertiesSupport\n","hasFloat32ArraySupport":"\nhasFloat32ArraySupport()\n    Tests for native `Float32Array` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Float32Array` support.\n\n    Examples\n    --------\n    > var bool = hasFloat32ArraySupport()\n    <boolean>\n\n","hasFloat64ArraySupport":"\nhasFloat64ArraySupport()\n    Tests for native `Float64Array` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Float64Array` support.\n\n    Examples\n    --------\n    > var bool = hasFloat64ArraySupport()\n    <boolean>\n\n","hasFunctionNameSupport":"\nhasFunctionNameSupport()\n    Tests for native function `name` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has function `name` support.\n\n    Examples\n    --------\n    > var bool = hasFunctionNameSupport()\n    <boolean>\n\n","hasGeneratorSupport":"\nhasGeneratorSupport()\n    Tests whether an environment supports native generator functions.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment support generator functions.\n\n    Examples\n    --------\n    > var bool = hasGeneratorSupport()\n    <boolean>\n\n","hasGlobalThisSupport":"\nhasGlobalThisSupport()\n    Tests for `globalThis` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `globalThis` support.\n\n    Examples\n    --------\n    > var bool = hasGlobalThisSupport()\n    <boolean>\n\n    See Also\n    --------\n    getGlobal\n","hasInt8ArraySupport":"\nhasInt8ArraySupport()\n    Tests for native `Int8Array` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Int8Array` support.\n\n    Examples\n    --------\n    > var bool = hasInt8ArraySupport()\n    <boolean>\n\n","hasInt16ArraySupport":"\nhasInt16ArraySupport()\n    Tests for native `Int16Array` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Int16Array` support.\n\n    Examples\n    --------\n    > var bool = hasInt16ArraySupport()\n    <boolean>\n\n","hasInt32ArraySupport":"\nhasInt32ArraySupport()\n    Tests for native `Int32Array` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Int32Array` support.\n\n    Examples\n    --------\n    > var bool = hasInt32ArraySupport()\n    <boolean>\n\n","hasIteratorSymbolSupport":"\nhasIteratorSymbolSupport()\n    Tests for native `Symbol.iterator` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has native `Symbol.iterator`\n        support.\n\n    Examples\n    --------\n    > var bool = hasIteratorSymbolSupport()\n    <boolean>\n\n    See Also\n    --------\n    hasAsyncIteratorSymbolSupport, hasSymbolSupport\n","hasMapSupport":"\nhasMapSupport()\n    Tests for native `Map` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Map` support.\n\n    Examples\n    --------\n    > var bool = hasMapSupport()\n    <boolean>\n\n","hasNodeBufferSupport":"\nhasNodeBufferSupport()\n    Tests for native `Buffer` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Buffer` support.\n\n    Examples\n    --------\n    > var bool = hasNodeBufferSupport()\n    <boolean>\n\n","hasOwnProp":"\nhasOwnProp( value, property )\n    Tests if an object has a specified property.\n\n    In contrast to the native `Object.prototype.hasOwnProperty`, this function\n    does not throw when provided `null` or `undefined`. Instead, the function\n    returns `false`.\n\n    Value arguments other than `null` or `undefined` are coerced to objects.\n\n    Property arguments are coerced to strings.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object has a specified property.\n\n    Examples\n    --------\n    > var beep = { 'boop': true };\n    > var bool = hasOwnProp( beep, 'boop' )\n    true\n    > bool = hasOwnProp( beep, 'bop' )\n    false\n\n    See Also\n    --------\n    hasProp\n","hasProp":"\nhasProp( value, property )\n    Tests if an object has a specified property, either own or inherited.\n\n    Value arguments other than `null` or `undefined` are coerced to objects.\n\n    Non-symbol property arguments are coerced to strings.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object has a specified property.\n\n    Examples\n    --------\n    > var beep = { 'boop': true };\n    > var bool = hasProp( beep, 'boop' )\n    true\n    > bool = hasProp( beep, 'toString' )\n    true\n    > bool = hasProp( beep, 'bop' )\n    false\n\n    See Also\n    --------\n    hasOwnProp\n","hasProxySupport":"\nhasProxySupport()\n    Tests whether an environment has native `Proxy` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has native `Proxy` support.\n\n    Examples\n    --------\n    > var bool = hasProxySupport()\n    <boolean>\n\n","hasSetSupport":"\nhasSetSupport()\n    Tests for native `Set` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has native `Set` support.\n\n    Examples\n    --------\n    > var bool = hasSetSupport()\n    <boolean>\n\n","hasSharedArrayBufferSupport":"\nhasSharedArrayBufferSupport()\n    Tests for native `SharedArrayBuffer` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `SharedArrayBuffer` support.\n\n    Examples\n    --------\n    > var bool = hasSharedArrayBufferSupport()\n    <boolean>\n\n    See Also\n    --------\n    hasArrayBufferSupport, hasFloat32ArraySupport, hasFloat64ArraySupport, hasInt16ArraySupport, hasInt32ArraySupport, hasInt8ArraySupport, hasNodeBufferSupport, hasUint16ArraySupport, hasUint32ArraySupport, hasUint8ArraySupport, hasUint8ClampedArraySupport\n","hasSymbolSupport":"\nhasSymbolSupport()\n    Tests for native `Symbol` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has native `Symbol` support.\n\n    Examples\n    --------\n    > var bool = hasSymbolSupport()\n    <boolean>\n\n    See Also\n    --------\n    hasIteratorSymbolSupport\n","hasToStringTagSupport":"\nhasToStringTagSupport()\n    Tests for native `toStringTag` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `toStringTag` support.\n\n    Examples\n    --------\n    > var bool = hasToStringTagSupport()\n    <boolean>\n\n","hasUint8ArraySupport":"\nhasUint8ArraySupport()\n    Tests for native `Uint8Array` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Uint8Array` support.\n\n    Examples\n    --------\n    > var bool = hasUint8ArraySupport()\n    <boolean>\n\n","hasUint8ClampedArraySupport":"\nhasUint8ClampedArraySupport()\n    Tests for native `Uint8ClampedArray` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Uint8ClampedArray` support.\n\n    Examples\n    --------\n    > var bool = hasUint8ClampedArraySupport()\n    <boolean>\n\n","hasUint16ArraySupport":"\nhasUint16ArraySupport()\n    Tests for native `Uint16Array` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Uint16Array` support.\n\n    Examples\n    --------\n    > var bool = hasUint16ArraySupport()\n    <boolean>\n\n","hasUint32ArraySupport":"\nhasUint32ArraySupport()\n    Tests for native `Uint32Array` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Uint32Array` support.\n\n    Examples\n    --------\n    > var bool = hasUint32ArraySupport()\n    <boolean>\n\n","hasUTF16SurrogatePairAt":"\nhasUTF16SurrogatePairAt( str, pos )\n    Tests if a position in a string marks the start of a UTF-16 surrogate pair.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    pos: integer\n        Position.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether surrogate pair exists at specified position.\n\n    Examples\n    --------\n    > var out = hasUTF16SurrogatePairAt( '🌷', 0 )\n    true\n    > out = hasUTF16SurrogatePairAt( '🌷', 1 )\n    false\n\n","hasWeakMapSupport":"\nhasWeakMapSupport()\n    Tests for native `WeakMap` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `WeakMap` support.\n\n    Examples\n    --------\n    > var bool = hasWeakMapSupport()\n    <boolean>\n\n","hasWeakSetSupport":"\nhasWeakSetSupport()\n    Tests for native `WeakSet` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `WeakSet` support.\n\n    Examples\n    --------\n    > var bool = hasWeakSetSupport()\n    <boolean>\n\n","hasWebAssemblySupport":"\nhasWebAssemblySupport()\n    Tests for native WebAssembly support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has native WebAssembly support.\n\n    Examples\n    --------\n    > var bool = hasWebAssemblySupport()\n    <boolean>\n\n","headercase":"\nheadercase( str )\n    Converts a string to HTTP header case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        HTTP header-cased string.\n\n    Examples\n    --------\n    > var out = headercase( 'Hello World!' )\n    'Hello-World'\n    > out = headercase( 'beep boop' )\n    'Beep-Boop'\n\n    See Also\n    --------\n    camelcase, kebabcase, pascalcase, snakecase","HERNDON_VENUS_SEMIDIAMETERS":"\nHERNDON_VENUS_SEMIDIAMETERS()\n    Returns fifteen observations of the vertical semidiameter of Venus, made by\n    Lieutenant Herndon, with the meridian circle at Washington, in the year\n    1846.\n\n    This dataset is a classic dataset commonly used in examples demonstrating\n    outlier detection.\n\n    Returns\n    -------\n    out: Array<number>\n        Observations.\n\n    Examples\n    --------\n    > var d = HERNDON_VENUS_SEMIDIAMETERS()\n    [ -0.30, -0.44, ..., 0.39, 0.10 ]\n\n    References\n    ----------\n    - Chauvenet, William. 1868. _A Manual of Spherical and Practical Astronomy_.\n    5th ed. Vol. 5. London, England: Trübner & Co.\n    - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n    Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n    of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n    - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n    Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n    00401706.1969.10490657.\n    - Tietjen, Gary L., and Roger H. Moore. 1972. \"Some Grubbs-Type Statistics\n    for the Detection of Several Outliers.\" _Technometrics_ 14 (3). Taylor &\n    Francis: 583–97. doi:10.1080/00401706.1972.10488948.\n\n","homedir":"\nhomedir()\n    Returns the current user's home directory.\n\n    If unable to locate a home directory, the function returns `null`.\n\n    Returns\n    -------\n    out: string|null\n        Home directory.\n\n    Examples\n    --------\n    > var home = homedir()\n    e.g., '/Users/<username>'\n\n    See Also\n    --------\n    configdir, tmpdir\n","HOURS_IN_DAY":"\nHOURS_IN_DAY\n    Number of hours in a day.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var days = 3.14;\n    > var hrs = days * HOURS_IN_DAY\n    75.36\n\n    See Also\n    --------\n    HOURS_IN_WEEK\n","HOURS_IN_WEEK":"\nHOURS_IN_WEEK\n    Number of hours in a week.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var wks = 3.14;\n    > var hrs = wks * HOURS_IN_WEEK\n    527.52\n\n    See Also\n    --------\n    HOURS_IN_DAY\n","hoursInMonth":"\nhoursInMonth( [month[, year]] )\n    Returns the number of hours in a month.\n\n    By default, the function returns the number of hours in the current month of\n    the current year (according to local time). To determine the number of hours\n    for a particular month and year, provide `month` and `year` arguments.\n\n    A `month` may be either a month's integer value, three letter abbreviation,\n    or full name (case insensitive).\n\n    The function's return value is a generalization and does **not** take into\n    account inaccuracies due to daylight savings conventions, crossing\n    timezones, or other complications with time and dates.\n\n    Parameters\n    ----------\n    month: string|Date|integer (optional)\n        Month.\n\n    year: integer (optional)\n        Year.\n\n    Returns\n    -------\n    out: integer\n        Hours in a month.\n\n    Examples\n    --------\n    > var num = hoursInMonth()\n    <number>\n    > num = hoursInMonth( 2 )\n    <number>\n    > num = hoursInMonth( 2, 2016 )\n    696\n    > num = hoursInMonth( 2, 2017 )\n    672\n\n    // Other ways to supply month:\n    > num = hoursInMonth( 'feb', 2016 )\n    696\n    > num = hoursInMonth( 'february', 2016 )\n    696\n\n    See Also\n    --------\n    hoursInYear\n","hoursInYear":"\nhoursInYear( [value] )\n    Returns the number of hours in a year according to the Gregorian calendar.\n\n    By default, the function returns the number of hours in the current year\n    (according to local time). To determine the number of hours for a particular\n    year, provide either a year or a `Date` object.\n\n    The function's return value is a generalization and does **not** take into\n    account inaccuracies due to daylight savings conventions, crossing\n    timezones, or other complications with time and dates.\n\n    Parameters\n    ----------\n    value: integer|Date (optional)\n        Year or `Date` object.\n\n    Returns\n    -------\n    out: integer\n        Number of hours in a year.\n\n    Examples\n    --------\n    > var num = hoursInYear()\n    <number>\n    > num = hoursInYear( 2016 )\n    8784\n    > num = hoursInYear( 2017 )\n    8760\n\n    See Also\n    --------\n    hoursInMonth\n","httpServer":"\nhttpServer( [options,] [requestListener] )\n    Returns a function to create an HTTP server.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.port: integer (optional)\n        Server port. Default: `0` (i.e., randomly assigned).\n\n    options.maxport: integer (optional)\n        Max server port when port hunting. Default: `maxport = port`.\n\n    options.hostname: string (optional)\n        Server hostname.\n\n    options.address: string (optional)\n        Server address. Default: `'127.0.0.1'`.\n\n    requestListener: Function (optional)\n        Request callback.\n\n    Returns\n    -------\n    createServer: Function\n        Function to create an HTTP server.\n\n    Examples\n    --------\n    // Basic usage:\n    > var createServer = httpServer()\n    <Function>\n\n    // Provide a request callback:\n    > function onRequest( request, response ) {\n    ...    console.log( request.url );\n    ...    response.end( 'OK' );\n    ... };\n    > createServer = httpServer( onRequest )\n    <Function>\n\n    // Specify a specific port:\n    > var opts = { 'port': 7331 };\n    > createServer = httpServer( opts )\n    <Function>\n\n\ncreateServer( done )\n    Creates an HTTP server.\n\n    Parameters\n    ----------\n    done: Function\n        Callback to invoke after creating a server.\n\n    Examples\n    --------\n    > function done( error, server ) {\n    ...    if ( error ) {\n    ...        throw error;\n    ...    }\n    ...    console.log( 'Success!' );\n    ...    server.close();\n    ... };\n    > var createServer = httpServer();\n    > createServer( done );\n\n","identity":"\nidentity( x )\n    Identity function.\n\n    Parameters\n    ----------\n    x: any\n        Input value.\n\n    Returns\n    -------\n    out: any\n        Input value.\n\n    Examples\n    --------\n    > var v = identity( 3.14 )\n    3.14\n\n    See Also\n    --------\n    constantFunction\n","ifelse":"\nifelse( bool, x, y )\n    If a condition is truthy, returns `x`; otherwise, returns `y`.\n\n    Parameters\n    ----------\n    bool: boolean\n        Condition.\n\n    x: any\n        Value to return if a condition is truthy.\n\n    y: any\n        Value to return if a condition is falsy.\n\n    Returns\n    -------\n    z: any\n        Either `x` or `y`.\n\n    Examples\n    --------\n    > var z = ifelse( true, 1.0, -1.0 )\n    1.0\n    > z = ifelse( false, 1.0, -1.0 )\n    -1.0\n\n    See Also\n    --------\n    ifelseAsync, ifthen\n","ifelseAsync":"\nifelseAsync( predicate, x, y, done )\n    If a predicate function returns a truthy value, returns `x`; otherwise,\n    returns `y`.\n\n    A predicate function is provided a single argument:\n\n    - clbk: callback to invoke upon predicate completion.\n\n    The callback function accepts two arguments:\n\n    - error: error object.\n    - bool: condition used to determine whether to invoke `x` or `y`.\n\n    The `done` callback is invoked upon function completion and is provided at\n    most two arguments:\n\n    - error: error object.\n    - result: either `x` or `y`.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function.\n\n    x: any\n        Value to return if a condition is truthy.\n\n    y: any\n        Value to return if a condition is falsy.\n\n    done: Function\n        Callback to invoke upon completion.\n\n    Examples\n    --------\n    > function predicate( clbk ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         clbk( null, true );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > ifelseAsync( predicate, 'beep', 'boop', done )\n    'beep'\n\n    See Also\n    --------\n    ifthenAsync, ifelse\n","ifthen":"\nifthen( bool, x, y )\n    If a condition is truthy, invoke `x`; otherwise, invoke `y`.\n\n    Parameters\n    ----------\n    bool: boolean\n        Condition.\n\n    x: Function\n        Function to invoke if a condition is truthy.\n\n    y: Function\n        Function to invoke if a condition is falsy.\n\n    Returns\n    -------\n    z: any\n        Return value of either `x` or `y`.\n\n    Examples\n    --------\n    > function x() { return 1.0; };\n    > function y() { return -1.0; };\n    > var z = ifthen( true, x, y )\n    1.0\n    > z = ifthen( false, x, y )\n    -1.0\n\n    See Also\n    --------\n    ifthenAsync, ifelse\n","ifthenAsync":"\nifthenAsync( predicate, x, y, done )\n    If a predicate function returns a truthy value, invokes `x`; otherwise,\n    invokes `y`.\n\n    The predicate function is provided a single argument:\n\n    - clbk: callback to invoke upon predicate function completion.\n\n    The predicate function callback accepts two arguments:\n\n    - error: error object.\n    - bool: condition used to determine whether to invoke `x` or `y`.\n\n    Both `x` and `y` are provided a single argument:\n\n    - clbk: callback to invoke upon function completion.\n\n    The callback function accepts any number of arguments, with the first\n    argument reserved for providing an error.\n\n    If the error argument is falsy, the `done` callback is invoked with its\n    first argument as `null` and all other provided arguments.\n\n    If the error argument is truthy, the `done` callback is invoked with only an\n    error argument.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function.\n\n    x: Function\n        Function to invoke if a condition is truthy.\n\n    y: Function\n        Function to invoke if a condition is falsy.\n\n    done: Function\n        Callback to invoke upon completion.\n\n    Examples\n    --------\n    > function predicate( clbk ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         clbk( null, false );\n    ...     }\n    ... };\n    > function x( clbk ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         clbk( null, 'beep' );\n    ...     }\n    ... };\n    > function y( clbk ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         clbk( null, 'boop' );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > ifthenAsync( predicate, x, y, done )\n    'boop'\n\n    See Also\n    --------\n    ifelseAsync, ifthen\n","imag":"\nimag( z )\n    Returns the imaginary component of a double-precision complex floating-point\n    number.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    im: number\n        Imaginary component.\n\n    Examples\n    --------\n    > var z = new Complex128( 5.0, 3.0 );\n    > var im = imag( z )\n    3.0\n\n    See Also\n    --------\n    real, reim\n","imagf":"\nimagf( z )\n    Returns the imaginary component of a single-precision complex floating-point\n    number.\n\n    Parameters\n    ----------\n    z: Complex64\n        Complex number.\n\n    Returns\n    -------\n    im: number\n        Imaginary component.\n\n    Examples\n    --------\n    > var z = new Complex64( 5.0, 3.0 );\n    > var im = imagf( z )\n    3.0\n\n    See Also\n    --------\n    imag, realf, reimf\n","IMG_ACANTHUS_MOLLIS":"\nIMG_ACANTHUS_MOLLIS()\n    Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n    print *Acanthus mollis*.\n\n    Returns\n    -------\n    out: Buffer\n        Image data.\n\n    Examples\n    --------\n    > var img = IMG_ACANTHUS_MOLLIS()\n    <Buffer>\n\n    References\n    ----------\n    - Blossfeldt, Karl. 1928. *Acanthus mollis*. <http://www.getty.edu/art/\n    collection/objects/35443/karl-blossfeldt-acanthus-mollis-german-1928/>.\n\n    * Digital image courtesy of the Getty's Open Content Program. While there\n    are no restrictions or conditions on the use of open content images, the\n    Getty would appreciate a gratis copy of any scholarly publications in which\n    the images are reproduced in order to maintain the collection bibliography.\n    Copies may be sent to the attention of:\n\n      Open Content Program\n      Registrar's Office\n      The J. Paul Getty Museum\n      1200 Getty Center Drive, Suite 1000\n      Los Angeles, CA 90049\n\n    See Also\n    --------\n    IMG_ALLIUM_OREOPHILUM\n","IMG_AIRPLANE_FROM_ABOVE":"\nIMG_AIRPLANE_FROM_ABOVE()\n    Returns a `Buffer` containing image data of Fédèle Azari's gelatin silver\n    print of an airplane, viewed from above looking down.\n\n    Returns\n    -------\n    out: Buffer\n        Image data.\n\n    Examples\n    --------\n    > var img = IMG_AIRPLANE_FROM_ABOVE()\n    <Buffer>\n\n    References\n    ----------\n    - Azari, Fédèle. 1929. (no title). <http://www.getty.edu/art/collection/\n    objects/134512/fedele-azari-airplane-viewed-from-above-looking-down-italian-\n    1914-1929/>.\n\n    * Digital image courtesy of the Getty's Open Content Program. While there\n    are no restrictions or conditions on the use of open content images, the\n    Getty would appreciate a gratis copy of any scholarly publications in which\n    the images are reproduced in order to maintain the collection bibliography.\n    Copies may be sent to the attention of:\n\n      Open Content Program\n      Registrar's Office\n      The J. Paul Getty Museum\n      1200 Getty Center Drive, Suite 1000\n      Los Angeles, CA 90049\n\n","IMG_ALLIUM_OREOPHILUM":"\nIMG_ALLIUM_OREOPHILUM()\n    Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n    print *Allium ostrowskianum*.\n\n    Returns\n    -------\n    out: Buffer\n        Image data.\n\n    Examples\n    --------\n    > var img = IMG_ALLIUM_OREOPHILUM()\n    <Buffer>\n\n    References\n    ----------\n    - Blossfeldt, Karl. 1928. *Allium ostrowskianum*. <http://www.getty.edu/art/\n    collection/objects/35448/karl-blossfeldt-allium-ostrowskianum-\n    knoblauchpflanze-german-1928/>.\n\n    * Digital image courtesy of the Getty's Open Content Program. While there\n    are no restrictions or conditions on the use of open content images, the\n    Getty would appreciate a gratis copy of any scholarly publications in which\n    the images are reproduced in order to maintain the collection bibliography.\n    Copies may be sent to the attention of:\n\n      Open Content Program\n      Registrar's Office\n      The J. Paul Getty Museum\n      1200 Getty Center Drive, Suite 1000\n      Los Angeles, CA 90049\n\n    See Also\n    --------\n    IMG_ACANTHUS_MOLLIS\n","IMG_BLACK_CANYON":"\nIMG_BLACK_CANYON()\n    Returns a `Buffer` containing image data of Timothy H. O'Sullivan's albumen\n    silver print *Black Cañon, Colorado River, From Camp 8, Looking Above*.\n\n    Returns\n    -------\n    out: Buffer\n        Image data.\n\n    Examples\n    --------\n    > var img = IMG_BLACK_CANYON()\n    <Buffer>\n\n    References\n    ----------\n    - O'Sullivan, Timothy H. 1871. *Black Cañon, Colorado River, From Camp 8,\n    Looking Above*. <http://www.getty.edu/art/collection/objects/40209/timothy-\n    h-o'sullivan-black-canon-colorado-river-from-camp-8-looking-above-american-\n    1871/>.\n\n    * Digital image courtesy of the Getty's Open Content Program. While there\n    are no restrictions or conditions on the use of open content images, the\n    Getty would appreciate a gratis copy of any scholarly publications in which\n    the images are reproduced in order to maintain the collection bibliography.\n    Copies may be sent to the attention of:\n\n      Open Content Program\n      Registrar's Office\n      The J. Paul Getty Museum\n      1200 Getty Center Drive, Suite 1000\n      Los Angeles, CA 90049\n\n","IMG_DUST_BOWL_HOME":"\nIMG_DUST_BOWL_HOME()\n    Returns a `Buffer` containing image data of Dorothea Lange's gelatin silver\n    print of an abandoned Dust Bowl home.\n\n    Returns\n    -------\n    out: Buffer\n        Image data.\n\n    Examples\n    --------\n    > var img = IMG_DUST_BOWL_HOME()\n    <Buffer>\n\n    References\n    ----------\n    - Lange, Dorothea. 1940. *Abandoned Dust Bowl Home*. <http://www.getty.edu/\n    art/collection/objects/128362/dorothea-lange-abandoned-dust-bowl-home-\n    american-about-1935-1940/>.\n\n    * Digital image courtesy of the Getty's Open Content Program. While there\n    are no restrictions or conditions on the use of open content images, the\n    Getty would appreciate a gratis copy of any scholarly publications in which\n    the images are reproduced in order to maintain the collection bibliography.\n    Copies may be sent to the attention of:\n\n      Open Content Program\n      Registrar's Office\n      The J. Paul Getty Museum\n      1200 Getty Center Drive, Suite 1000\n      Los Angeles, CA 90049\n\n","IMG_FRENCH_ALPINE_LANDSCAPE":"\nIMG_FRENCH_ALPINE_LANDSCAPE()\n    Returns a `Buffer` containing image data of Adolphe Braun's carbon print of\n    a French alpine landscape.\n\n    Returns\n    -------\n    out: Buffer\n        Image data.\n\n    Examples\n    --------\n    > var img = IMG_FRENCH_ALPINE_LANDSCAPE()\n    <Buffer>\n\n    References\n    ----------\n    - Braun, Adolphe. 1870. (no title). <http://www.getty.edu/art/collection/\n    objects/54324/adolphe-braun-alpine-landscape-french-1865-1870/>.\n\n    * Digital image courtesy of the Getty's Open Content Program. While there\n    are no restrictions or conditions on the use of open content images, the\n    Getty would appreciate a gratis copy of any scholarly publications in which\n    the images are reproduced in order to maintain the collection bibliography.\n    Copies may be sent to the attention of:\n\n      Open Content Program\n      Registrar's Office\n      The J. Paul Getty Museum\n      1200 Getty Center Drive, Suite 1000\n      Los Angeles, CA 90049\n\n","IMG_LOCOMOTION_HOUSE_CAT":"\nIMG_LOCOMOTION_HOUSE_CAT()\n    Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n    collotype of a house cat (24 views).\n\n    Returns\n    -------\n    out: Buffer\n        Image data.\n\n    Examples\n    --------\n    > var img = IMG_LOCOMOTION_HOUSE_CAT()\n    <Buffer>\n\n    References\n    ----------\n    - Muybridge, Eadweard J. 1887. *Animal Locomotion*. <http://www.getty.edu/\n    art/collection/objects/40918/eadweard-j-muybridge-animal-locomotion-american\n    -1887/>.\n\n    * Digital image courtesy of the Getty's Open Content Program. While there\n    are no restrictions or conditions on the use of open content images, the\n    Getty would appreciate a gratis copy of any scholarly publications in which\n    the images are reproduced in order to maintain the collection bibliography.\n    Copies may be sent to the attention of:\n\n      Open Content Program\n      Registrar's Office\n      The J. Paul Getty Museum\n      1200 Getty Center Drive, Suite 1000\n      Los Angeles, CA 90049\n\n    See Also\n    --------\n    IMG_LOCOMOTION_NUDE_MALE\n","IMG_LOCOMOTION_NUDE_MALE":"\nIMG_LOCOMOTION_NUDE_MALE()\n    Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n    collotype of a nude male moving in place (48 views).\n\n    Returns\n    -------\n    out: Buffer\n        Image data.\n\n    Examples\n    --------\n    > var img = IMG_LOCOMOTION_NUDE_MALE()\n    <Buffer>\n\n    References\n    ----------\n    - Muybridge, Eadweard J. 1887. *Animal Locomotion*. <http://www.getty.edu/\n    art/collection/objects/40918/eadweard-j-muybridge-animal-locomotion-american\n    -1887/>.\n\n    * Digital image courtesy of the Getty's Open Content Program. While there\n    are no restrictions or conditions on the use of open content images, the\n    Getty would appreciate a gratis copy of any scholarly publications in which\n    the images are reproduced in order to maintain the collection bibliography.\n    Copies may be sent to the attention of:\n\n      Open Content Program\n      Registrar's Office\n      The J. Paul Getty Museum\n      1200 Getty Center Drive, Suite 1000\n      Los Angeles, CA 90049\n\n    See Also\n    --------\n    IMG_LOCOMOTION_HOUSE_CAT\n","IMG_MARCH_PASTORAL":"\nIMG_MARCH_PASTORAL()\n    Returns a `Buffer` containing image data of Peter Henry Emerson's\n    photogravure of sheep in a pastoral setting.\n\n    Returns\n    -------\n    out: Buffer\n        Image data.\n\n    Examples\n    --------\n    > var img = IMG_MARCH_PASTORAL()\n    <Buffer>\n\n    References\n    ----------\n    - Emerson, Peter Henry. 1888. *A March Pastoral*. <http://www.getty.edu/art/\n    collection/objects/141994/peter-henry-emerson-a-march-pastoral-suffolk-\n    british-1888/>.\n\n    * Digital image courtesy of the Getty's Open Content Program. While there\n    are no restrictions or conditions on the use of open content images, the\n    Getty would appreciate a gratis copy of any scholarly publications in which\n    the images are reproduced in order to maintain the collection bibliography.\n    Copies may be sent to the attention of:\n\n      Open Content Program\n      Registrar's Office\n      The J. Paul Getty Museum\n      1200 Getty Center Drive, Suite 1000\n      Los Angeles, CA 90049\n\n","IMG_NAGASAKI_BOATS":"\nIMG_NAGASAKI_BOATS()\n    Returns a `Buffer` containing image data of Felice Beato's albumen silver\n    print of boats in a river in Nagasaki.\n\n    Returns\n    -------\n    out: Buffer\n        Image data.\n\n    Examples\n    --------\n    > var img = IMG_NAGASAKI_BOATS()\n    <Buffer>\n\n    References\n    ----------\n    - Beato, Felice. 1865. (no title). <http://www.getty.edu/art/collection/\n    objects/241797/felice-beato-boats-in-river-nagasaki-british-about-1865/>.\n\n    * Digital image courtesy of the Getty's Open Content Program. While there\n    are no restrictions or conditions on the use of open content images, the\n    Getty would appreciate a gratis copy of any scholarly publications in which\n    the images are reproduced in order to maintain the collection bibliography.\n    Copies may be sent to the attention of:\n\n      Open Content Program\n      Registrar's Office\n      The J. Paul Getty Museum\n      1200 Getty Center Drive, Suite 1000\n      Los Angeles, CA 90049\n\n","incrapcorr":"\nincrapcorr( [mx, my] )\n    Returns an accumulator function which incrementally computes the absolute\n    value of the sample Pearson product-moment correlation coefficient.\n\n    If provided values, the accumulator function returns an updated accumulated\n    value. If not provided values, the accumulator function returns the current\n    accumulated value.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    mx: number (optional)\n        Known mean.\n\n    my: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrapcorr();\n    > var ar = accumulator()\n    null\n    > ar = accumulator( 2.0, 1.0 )\n    0.0\n    > ar = accumulator( -5.0, 3.14 )\n    ~1.0\n    > ar = accumulator()\n    ~1.0\n\n    See Also\n    --------\n    incrmapcorr, incrpcorr, incrpcorr2\n","incrBinaryClassification":"\nincrBinaryClassification( N[, options] )\n    Returns an accumulator function which incrementally performs binary\n    classification using stochastic gradient descent (SGD).\n\n    If provided a feature vector and response value, the accumulator function\n    updates a binary classification model and returns updated model\n    coefficients.\n\n    If not provided a feature vector and response value, the accumulator\n    function returns the current model coefficients.\n\n    Stochastic gradient descent is sensitive to the scaling of the features. One\n    is advised to either scale each feature to `[0,1]` or `[-1,1]` or to\n    transform the features into z-scores with zero mean and unit variance. One\n    should keep in mind that the same scaling has to be applied to training data\n    in order to obtain accurate predictions.\n\n    In general, the more data provided to an accumulator, the more reliable the\n    model predictions.\n\n    Parameters\n    ----------\n    N: integer\n        Number of features.\n\n    options: Object (optional)\n        Function options.\n\n    options.intercept: boolean (optional)\n        Boolean indicating whether to include an intercept. Default: true.\n\n    options.lambda: number (optional)\n        Regularization parameter. Default: 1.0e-4.\n\n    options.learningRate: ArrayLike (optional)\n        Learning rate function and associated (optional) parameters. The first\n        array element specifies the learning rate function and must be one of\n        the following:\n\n        - ['constant', ...]: constant learning rate function. To set the\n        learning rate, provide a second array element. By default, when the\n        learn rate function is 'constant', the learning rate is set to 0.02.\n\n        - ['basic']: basic learning rate function according to the formula\n        `10/(10+t)` where `t` is the current iteration.\n\n        - ['invscaling', ...]: inverse scaling learning rate function according\n        to the formula `eta0/pow(t, power_t)` where `eta0` is the initial\n        learning rate and `power_t` is the exponent controlling how quickly the\n        learning rate decreases. To set the initial learning rate, provide a\n        second array element. By default, the initial learning rate is 0.02. To\n        set the exponent, provide a third array element. By default, the\n        exponent is 0.5.\n\n        - ['pegasos']: Pegasos learning rate function according to the formula\n        `1/(lambda*t)` where `t` is the current iteration and `lambda` is the\n        regularization parameter.\n\n        Default: ['basic'].\n\n    options.loss: string (optional)\n        Loss function. Must be one of the following:\n\n        - hinge: hinge loss function. Corresponds to a soft-margin linear\n        Support Vector Machine (SVM), which can handle non-linearly separable\n        data.\n\n        - log: logistic loss function. Corresponds to Logistic Regression.\n\n        - modifiedHuber: Huber loss function variant for classification.\n\n        - perceptron: hinge loss function without a margin. Corresponds to the\n        original Perceptron by Rosenblatt.\n\n        - squaredHinge: squared hinge loss function SVM (L2-SVM).\n\n        Default: 'log'.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    acc.predict: Function\n        Predicts response values for one ore more observation vectors. Provide a\n        second argument to specify the prediction type. Must be one of the\n        following: 'label', 'probability', or 'linear'. Default: 'label'.\n\n        Note that the probability prediction type is only compatible with 'log'\n        and 'modifiedHuber' loss functions.\n\n    Examples\n    --------\n    // Create an accumulator:\n    > var opts = {};\n    > opts.intercept = true;\n    > opts.lambda = 1.0e-5;\n    > var acc = incrBinaryClassification( 3, opts );\n\n    // Update the model:\n    > var buf = new Float64Array( [ 2.3, 1.0, 5.0 ] );\n    > var x = array( buf );\n    > var coefs = acc( x, 1 )\n    <ndarray>\n\n    // Create a new observation vector:\n    > buf = new Float64Array( [ 2.3, 5.3, 8.6 ] );\n    > x = array( buf );\n\n    // Predict the response value:\n    > var yhat = acc.predict( x )\n    <ndarray>\n\n    See Also\n    --------\n    incrSGDRegression\n","incrcount":"\nincrcount()\n    Returns an accumulator function which incrementally updates a count.\n\n    If provided a value, the accumulator function returns an updated count. If\n    not provided a value, the accumulator function returns the current count.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrcount();\n    > var v = accumulator()\n    0\n    > v = accumulator( 2.0 )\n    1\n    > v = accumulator( -5.0 )\n    2\n    > v = accumulator()\n    2\n\n    See Also\n    --------\n    incrmean, incrsum, incrsummary\n","incrcovariance":"\nincrcovariance( [mx, my] )\n    Returns an accumulator function which incrementally computes an unbiased\n    sample covariance.\n\n    If provided values, the accumulator function returns an updated unbiased\n    sample covariance. If not provided values, the accumulator function returns\n    the current unbiased sample covariance.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    mx: number (optional)\n        Known mean.\n\n    my: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrcovariance();\n    > var v = accumulator()\n    null\n    > v = accumulator( 2.0, 1.0 )\n    0.0\n    > v = accumulator( -5.0, 3.14 )\n    ~-7.49\n    > v = accumulator()\n    ~-7.49\n\n    See Also\n    --------\n    incrmcovariance, incrpcorr, incrvariance\n","incrcovmat":"\nincrcovmat( out[, means] )\n    Returns an accumulator function which incrementally computes an unbiased\n    sample covariance matrix.\n\n    If provided a data vector, the accumulator function returns an updated\n    unbiased sample covariance matrix. If not provided a data vector, the\n    accumulator function returns the current unbiased sample covariance matrix.\n\n    Parameters\n    ----------\n    out: integer|ndarray\n        Order of the covariance matrix or a square 2-dimensional ndarray for\n        storing the covariance matrix.\n\n    means: ndarray (optional)\n        Known means.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrcovmat( 2 );\n    > var out = accumulator()\n    <ndarray>\n    > var buf = new Float64Array( 2 );\n    > var shape = [ 2 ];\n    > var strides = [ 1 ];\n    > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n    > v.set( 0, 2.0 );\n    > v.set( 1, 1.0 );\n    > out = accumulator( v )\n    <ndarray>\n    > v.set( 0, -5.0 );\n    > v.set( 1, 3.14 );\n    > out = accumulator( v )\n    <ndarray>\n    > out = accumulator()\n    <ndarray>\n\n    See Also\n    --------\n    incrcovariance, incrpcorrmat\n","incrcv":"\nincrcv( [mean] )\n    Returns an accumulator function which incrementally computes the coefficient\n    of variation (CV).\n\n    If provided a value, the accumulator function returns an updated accumulated\n    value. If not provided a value, the accumulator function returns the current\n    accumulated value.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    mean: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrcv();\n    > var cv = accumulator()\n    null\n    > cv = accumulator( 2.0 )\n    0.0\n    > cv = accumulator( 1.0 )\n    ~0.47\n    > cv = accumulator()\n    ~0.47\n\n    See Also\n    --------\n    incrmean, incrmcv, incrstdev, incrvmr\n","increwmean":"\nincrewmean( α )\n    Returns an accumulator function which incrementally computes an\n    exponentially weighted mean, where α is a smoothing factor between 0 and 1.\n\n    If provided a value, the accumulator function returns an updated mean. If\n    not provided a value, the accumulator function returns the current mean.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    α: number\n        Smoothing factor (value between 0 and 1).\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = increwmean( 0.5 );\n    > var v = accumulator()\n    null\n    > v = accumulator( 2.0 )\n    2.0\n    > v = accumulator( -5.0 )\n    -1.5\n    > v = accumulator()\n    -1.5\n\n    See Also\n    --------\n    increwvariance, incrmean, incrmmean, incrwmean\n","increwstdev":"\nincrewstdev( α )\n    Returns an accumulator function which incrementally computes an\n    exponentially weighted standard deviation, where α is a smoothing factor\n    between 0 and 1.\n\n    If provided a value, the accumulator function returns an updated standard\n    deviation. If not provided a value, the accumulator function returns the\n    current standard deviation.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    α: number\n        Smoothing factor (value between 0 and 1).\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = increwstdev( 0.5 );\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    0.0\n    > s = accumulator( -5.0 )\n    3.5\n    > s = accumulator()\n    3.5\n\n    See Also\n    --------\n    increwvariance, incrmstdev, incrstdev\n","increwvariance":"\nincrewvariance( α )\n    Returns an accumulator function which incrementally computes an\n    exponentially weighted variance, where α is a smoothing factor between 0 and\n    1.\n\n    If provided a value, the accumulator function returns an updated variance.\n    If not provided a value, the accumulator function returns the current\n    variance.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    α: number\n        Smoothing factor (value between 0 and 1).\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = increwvariance( 0.5 );\n    > var v = accumulator()\n    null\n    > v = accumulator( 2.0 )\n    0.0\n    > v = accumulator( -5.0 )\n    12.25\n    > v = accumulator()\n    12.25\n\n    See Also\n    --------\n    increwmean, increwstdev, incrvariance, incrmvariance\n","incrgmean":"\nincrgmean()\n    Returns an accumulator function which incrementally computes a geometric\n    mean.\n\n    If provided a value, the accumulator function returns an updated geometric\n    mean. If not provided a value, the accumulator function returns the current\n    geometric mean.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    If provided a negative value, the accumulated value is `NaN` for all future\n    invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrgmean();\n    > var v = accumulator()\n    null\n    > v = accumulator( 2.0 )\n    2.0\n    > v = accumulator( 5.0 )\n    ~3.16\n    > v = accumulator()\n    ~3.16\n\n    See Also\n    --------\n    incrhmean, incrmean, incrmgmean, incrsummary\n","incrgrubbs":"\nincrgrubbs( [options] )\n    Returns an accumulator function which incrementally performs Grubbs' test\n    for detecting outliers.\n\n    Grubbs' test assumes that data is normally distributed. Accordingly, one\n    should first verify that the data can be reasonably approximated by a normal\n    distribution before applying the Grubbs' test.\n\n    If provided a value, the accumulator function returns updated test results.\n    If not provided a value, the accumulator function returns the current test\n    results.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the test statistic is `NaN` for all future invocations.\n\n    The accumulator must be provided *at least* three data points before\n    performing Grubbs' test. Until at least three data points are provided, the\n    accumulator returns `null`.\n\n    The accumulator function returns an object having the following fields:\n\n    - rejected: boolean indicating whether the null hypothesis should be\n    rejected.\n    - alpha: significance level.\n    - criticalValue: critical value.\n    - statistic: test statistic.\n    - df: degrees of freedom.\n    - mean: sample mean.\n    - sd: corrected sample standard deviation.\n    - min: minimum value.\n    - max: maximum value.\n    - alt: alternative hypothesis.\n    - method: method name.\n    - print: method for pretty-printing test output.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.alpha: number (optional)\n        Significance level. Default: 0.05.\n\n    options.alternative: string (optional)\n        Alternative hypothesis. The option may be one of the following values:\n\n        - 'two-sided': test whether the minimum or maximum value is an outlier.\n        - 'min': test whether the minimum value is an outlier.\n        - 'max': test whether the maximum value is an outlier.\n\n        Default: 'two-sided'.\n\n    options.init: integer (optional)\n        Number of data points the accumulator should use to compute initial\n        statistics *before* testing for an outlier. Until the accumulator is\n        provided the number of data points specified by this option, the\n        accumulator returns `null`. Default: 100.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var acc = incrgrubbs();\n    > var res = acc()\n    null\n    > for ( var i = 0; i < 200; i++ ) {\n    ...     res = acc( base.random.normal( 10.0, 5.0 ) );\n    ... };\n    > res.print()\n\n    References\n    ----------\n    - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n    Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n    of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n    - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n    Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n    00401706.1969.10490657.\n\n    See Also\n    --------\n    incrmgrubbs\n","incrhmean":"\nincrhmean()\n    Returns an accumulator function which incrementally computes a harmonic\n    mean.\n\n    If provided a value, the accumulator function returns an updated harmonic\n    mean. If not provided a value, the accumulator function returns the current\n    harmonic mean.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrhmean();\n    > var v = accumulator()\n    null\n    > v = accumulator( 2.0 )\n    2.0\n    > v = accumulator( 5.0 )\n    ~2.86\n    > v = accumulator()\n    ~2.86\n\n    See Also\n    --------\n    incrgmean, incrmean, incrmhmean, incrsummary\n","incrkmeans":"\nincrkmeans( k[, ndims][, options] )\n    Returns an accumulator function which incrementally partitions data into `k`\n    clusters.\n\n    If not provided initial centroids, the accumulator caches data vectors for\n    subsequent centroid initialization. Until an accumulator computes initial\n    centroids, an accumulator returns `null`.\n\n    Once an accumulator has initial centroids (either provided or computed), if\n    provided a data vector, the accumulator function returns updated cluster\n    results. If not provided a data vector, the accumulator function returns the\n    current cluster results.\n\n    Cluster results are comprised of the following:\n\n    - centroids: a `k x ndims` matrix containing centroid locations. Each\n      centroid is the component-wise mean of the data points assigned to a\n      centroid's corresponding cluster.\n    - stats: a `k x 4` matrix containing cluster statistics.\n\n    Cluster statistics consists of the following columns:\n\n    - 0: number of data points assigned to a cluster.\n    - 1: total within-cluster sum of squared distances.\n    - 2: arithmetic mean of squared distances.\n    - 3: corrected sample standard deviation of squared distances.\n\n    Because an accumulator incrementally partitions data, one should *not*\n    expect cluster statistics to match similar statistics had provided data been\n    analyzed via a batch algorithm. In an incremental context, data points which\n    would not be considered part of a particular cluster when analyzed via a\n    batch algorithm may contribute to that cluster's statistics when analyzed\n    incrementally.\n\n    In general, the more data provided to an accumulator, the more reliable the\n    cluster statistics.\n\n    Parameters\n    ----------\n    k: integer|ndarray\n        Number of clusters or a `k x ndims` matrix containing initial centroids.\n\n    ndims: integer (optional)\n        Number of dimensions. This argument must accompany an integer-valued\n        first argument.\n\n    options: Object (optional)\n        Function options.\n\n    options.metric: string (optional)\n        Distance metric. Must be one of the following: 'euclidean', 'cosine', or\n        'correlation'. Default: 'euclidean'.\n\n    options.init: ArrayLike (optional)\n        Centroid initialization method and associated (optional) parameters. The\n        first array element specifies the initialization method and must be one\n        of the following: 'kmeans++', 'sample', or 'forgy'. The second array\n        element specifies the number of data points to use when calculating\n        initial centroids. When performing kmeans++ initialization, the third\n        array element specifies the number of trials to perform when randomly\n        selecting candidate centroids. Typically, more trials is correlated with\n        initial centroids which lead to better clustering; however, a greater\n        number of trials increases computational overhead. Default: ['kmeans++',\n        k, 2+⌊ln(k)⌋ ].\n\n    options.normalize: boolean (optional)\n        Boolean indicating whether to normalize incoming data. This option is\n        only relevant for non-Euclidean distance metrics. If set to `true`, an\n        accumulator partitioning data based on cosine distance normalizes\n        provided data to unit Euclidean length. If set to `true`, an accumulator\n        partitioning data based on correlation distance first centers provided\n        data and then normalizes data dimensions to have zero mean and unit\n        variance. If this option is set to `false` and the metric is either\n        cosine or correlation distance, then incoming data *must* already be\n        normalized. Default: true.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy incoming data to prevent mutation\n        during normalization. Default: true.\n\n    options.seed: any (optional)\n        PRNG seed. Setting this option is useful when wanting reproducible\n        initial centroids.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    acc.predict: Function\n        Predicts centroid assignment for each data point in a provided matrix.\n        To specify an output vector, provide a 1-dimensional ndarray as the\n        first argument. Each element in the returned vector corresponds to a\n        predicted cluster index for a respective data point.\n\n    Examples\n    --------\n    > var accumulator = incrkmeans( 5, 2 );\n    > var buf = new Float64Array( 2 );\n    > var shape = [ 2 ];\n    > var strides = [ 1 ];\n    > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n    > v.set( 0, 2.0 );\n    > v.set( 1, 1.0 );\n    > out = accumulator( v );\n    > v.set( 0, -5.0 );\n    > v.set( 1, 3.14 );\n    > out = accumulator( v );\n\n","incrkurtosis":"\nincrkurtosis()\n    Returns an accumulator function which incrementally computes a corrected\n    sample excess kurtosis.\n\n    If provided a value, the accumulator function returns an updated corrected\n    sample excess kurtosis. If not provided a value, the accumulator function\n    returns the current corrected sample excess kurtosis.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrkurtosis();\n    > var v = accumulator( 2.0 )\n    null\n    > v = accumulator( 2.0 )\n    null\n    > v = accumulator( -4.0 )\n    null\n    > v = accumulator( -4.0 )\n    -6.0\n\n    See Also\n    --------\n    incrmean, incrskewness, incrstdev, incrsummary, incrvariance\n","incrmaape":"\nincrmaape()\n    Returns an accumulator function which incrementally computes the mean\n    arctangent absolute percentage error (MAAPE).\n\n    If provided input values, the accumulator function returns an updated mean\n    arctangent absolute percentage error. If not provided input values, the\n    accumulator function returns the current mean arctangent absolute percentage\n    error.\n\n    Note that, unlike the mean absolute percentage error (MAPE), the mean\n    arctangent absolute percentage error is expressed in radians on the interval\n    [0,π/2].\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmaape();\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    ~0.3218\n    > m = accumulator( 5.0, 2.0 )\n    ~0.6523\n    > m = accumulator()\n    ~0.6523\n\n    See Also\n    --------\n    incrmae, incrmape, incrmean, incrmmaape\n","incrmae":"\nincrmae()\n    Returns an accumulator function which incrementally computes the mean\n    absolute error (MAE).\n\n    If provided input values, the accumulator function returns an updated mean\n    absolute error. If not provided input values, the accumulator function\n    returns the current mean absolute error.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmae();\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    1.0\n    > m = accumulator( -5.0, 2.0 )\n    4.0\n    > m = accumulator()\n    4.0\n\n    See Also\n    --------\n    incrmape, incrme, incrmean, incrmmae\n","incrmapcorr":"\nincrmapcorr( W[, mx, my] )\n    Returns an accumulator function which incrementally computes a moving\n    sample absolute Pearson product-moment correlation coefficient.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving sample absolute correlation coefficient.\n\n    If provided values, the accumulator function returns an updated moving\n    sample absolute correlation coefficient. If not provided values, the\n    accumulator function returns the current moving sample absolute correlation\n    coefficient.\n\n    As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n    returned values are calculated from smaller sample sizes. Until the window\n    is full, each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    mx: number (optional)\n        Known mean.\n\n    my: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmapcorr( 3 );\n    > var ar = accumulator()\n    null\n    > ar = accumulator( 2.0, 1.0 )\n    0.0\n    > ar = accumulator( -5.0, 3.14 )\n    ~1.0\n    > ar = accumulator( 3.0, -1.0 )\n    ~0.925\n    > ar = accumulator( 5.0, -9.5 )\n    ~0.863\n    > ar = accumulator()\n    ~0.863\n\n    See Also\n    --------\n    incrapcorr, incrmpcorr, incrmpcorr2\n","incrmape":"\nincrmape()\n    Returns an accumulator function which incrementally computes the mean\n    absolute percentage error (MAPE).\n\n    If provided input values, the accumulator function returns an updated mean\n    absolute percentage error. If not provided input values, the accumulator\n    function returns the current mean absolute percentage error.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmape();\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    ~33.33\n    > m = accumulator( 5.0, 2.0 )\n    ~91.67\n    > m = accumulator()\n    ~91.67\n\n    See Also\n    --------\n    incrmaape, incrmae, incrmean, incrmmape\n","incrmax":"\nincrmax()\n    Returns an accumulator function which incrementally computes a maximum\n    value.\n\n    If provided a value, the accumulator function returns an updated maximum\n    value. If not provided a value, the accumulator function returns the current\n    maximum value.\n\n    If provided `NaN`, the maximum value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmax();\n    > var m = accumulator()\n    null\n    > m = accumulator( 3.14 )\n    3.14\n    > m = accumulator( -5.0 )\n    3.14\n    > m = accumulator( 10.1 )\n    10.1\n    > m = accumulator()\n    10.1\n\n    See Also\n    --------\n    incrmidrange, incrmin, incrmmax, incrrange, incrsummary\n","incrmaxabs":"\nincrmaxabs()\n    Returns an accumulator function which incrementally computes a maximum\n    absolute value.\n\n    If provided a value, the accumulator function returns an updated maximum\n    absolute value. If not provided a value, the accumulator function returns\n    the current maximum absolute value.\n\n    If provided `NaN`, the maximum value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmaxabs();\n    > var m = accumulator()\n    null\n    > m = accumulator( 3.14 )\n    3.14\n    > m = accumulator( -5.0 )\n    5.0\n    > m = accumulator( 10.1 )\n    10.1\n    > m = accumulator()\n    10.1\n\n    See Also\n    --------\n    incrmax, incrminabs, incrmmaxabs\n","incrmcovariance":"\nincrmcovariance( W[, mx, my] )\n    Returns an accumulator function which incrementally computes a moving\n    unbiased sample covariance.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving unbiased sample covariance.\n\n    If provided values, the accumulator function returns an updated moving\n    unbiased sample covariance. If not provided values, the accumulator function\n    returns the current moving unbiased sample covariance.\n\n    As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n    returned values are calculated from smaller sample sizes. Until the window\n    is full, each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    mx: number (optional)\n        Known mean.\n\n    my: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmcovariance( 3 );\n    > var v = accumulator()\n    null\n    > v = accumulator( 2.0, 1.0 )\n    0.0\n    > v = accumulator( -5.0, 3.14 )\n    ~-7.49\n    > v = accumulator( 3.0, -1.0 )\n    -8.35\n    > v = accumulator( 5.0, -9.5 )\n    -29.42\n    > v = accumulator()\n    -29.42\n\n    See Also\n    --------\n    incrcovariance, incrmpcorr, incrmvariance\n","incrmcv":"\nincrmcv( W[, mean] )\n    Returns an accumulator function which incrementally computes a moving\n    coefficient of variation (CV).\n\n    The `W` parameter defines the number of values over which to compute the\n    moving coefficient of variation.\n\n    If provided a value, the accumulator function returns an updated moving\n    coefficient of variation. If not provided a value, the accumulator function\n    returns the current moving coefficient of variation.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    mean: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmcv( 3 );\n    > var cv = accumulator()\n    null\n    > cv = accumulator( 2.0 )\n    0.0\n    > cv = accumulator( 1.0 )\n    ~0.47\n    > cv = accumulator( 3.0 )\n    0.5\n    > cv = accumulator( 7.0 )\n    ~0.83\n    > cv = accumulator()\n    ~0.83\n\n    See Also\n    --------\n    incrcv, incrmmean, incrmstdev, incrmvmr\n","incrmda":"\nincrmda()\n    Returns an accumulator function which incrementally computes the mean\n    directional accuracy (MDA).\n\n    If provided input values, the accumulator function returns an updated mean\n    directional accuracy. If not provided input values, the accumulator function\n    returns the current mean directional accuracy.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmda();\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    1.0\n    > m = accumulator( -5.0, 4.0 )\n    0.5\n    > m = accumulator()\n    0.5\n\n    See Also\n    --------\n    incrmape, incrmmda\n","incrme":"\nincrme()\n    Returns an accumulator function which incrementally computes the mean error\n    (ME).\n\n    If provided input values, the accumulator function returns an updated mean\n    error. If not provided input values, the accumulator function returns the\n    current mean error.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrme();\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    1.0\n    > m = accumulator( -5.0, 2.0 )\n    4.0\n    > m = accumulator()\n    4.0\n\n    See Also\n    --------\n    incrmae, incrmean, incrmme\n","incrmean":"\nincrmean()\n    Returns an accumulator function which incrementally computes an arithmetic\n    mean.\n\n    If provided a value, the accumulator function returns an updated mean. If\n    not provided a value, the accumulator function returns the current mean.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmean();\n    > var mu = accumulator()\n    null\n    > mu = accumulator( 2.0 )\n    2.0\n    > mu = accumulator( -5.0 )\n    -1.5\n    > mu = accumulator()\n    -1.5\n\n    See Also\n    --------\n    incrmidrange, incrmmean, incrstdev, incrsum, incrsummary, incrvariance\n","incrmeanabs":"\nincrmeanabs()\n    Returns an accumulator function which incrementally computes an arithmetic\n    mean of absolute values.\n\n    If provided a value, the accumulator function returns an updated mean. If\n    not provided a value, the accumulator function returns the current mean.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmeanabs();\n    > var mu = accumulator()\n    null\n    > mu = accumulator( 2.0 )\n    2.0\n    > mu = accumulator( -5.0 )\n    3.5\n    > mu = accumulator()\n    3.5\n\n    See Also\n    --------\n    incrmean, incrmmeanabs, incrsumabs\n","incrmeanabs2":"\nincrmeanabs2()\n    Returns an accumulator function which incrementally computes an arithmetic\n    mean of squared absolute values.\n\n    If provided a value, the accumulator function returns an updated mean. If\n    not provided a value, the accumulator function returns the current mean.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmeanabs2();\n    > var mu = accumulator()\n    null\n    > mu = accumulator( 2.0 )\n    4.0\n    > mu = accumulator( -5.0 )\n    14.5\n    > mu = accumulator()\n    14.5\n\n    See Also\n    --------\n    incrmean, incrmeanabs, incrmmeanabs2, incrsumabs2\n","incrmeanstdev":"\nincrmeanstdev( [out] )\n    Returns an accumulator function which incrementally computes an arithmetic\n    mean and corrected sample standard deviation.\n\n    If provided a value, the accumulator function returns updated accumulated\n    values. If not provided a value, the accumulator function returns the\n    current accumulated values.\n\n    If provided `NaN`, the accumulated values are equal to `NaN` for all future\n    invocations.\n\n    Parameters\n    ----------\n    out: Array|TypedArray (optional)\n        Output array.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmeanstdev();\n    > var ms = accumulator()\n    null\n    > ms = accumulator( 2.0 )\n    [ 2.0, 0.0 ]\n    > ms = accumulator( -5.0 )\n    [ -1.5, ~4.95 ]\n    > ms = accumulator( 3.0 )\n    [ 0.0, ~4.36 ]\n    > ms = accumulator( 5.0 )\n    [ 1.25, ~4.35 ]\n    > ms = accumulator()\n    [ 1.25, ~4.35 ]\n\n    See Also\n    --------\n    incrmean, incrmeanvar, incrmmeanstdev, incrstdev\n","incrmeanvar":"\nincrmeanvar( [out] )\n    Returns an accumulator function which incrementally computes an arithmetic\n    mean and unbiased sample variance.\n\n    If provided a value, the accumulator function returns updated accumulated\n    values. If not provided a value, the accumulator function returns the\n    current accumulated values.\n\n    If provided `NaN`, the accumulated values are equal to `NaN` for all future\n    invocations.\n\n    Parameters\n    ----------\n    out: Array|TypedArray (optional)\n        Output array.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmeanvar();\n    > var mv = accumulator()\n    null\n    > mv = accumulator( 2.0 )\n    [ 2.0, 0.0 ]\n    > mv = accumulator( -5.0 )\n    [ -1.5, 24.5 ]\n    > mv = accumulator( 3.0 )\n    [ 0.0, 19.0 ]\n    > mv = accumulator( 5.0 )\n    [ 1.25, ~18.92 ]\n    > mv = accumulator()\n    [ 1.25, ~18.92 ]\n\n    See Also\n    --------\n    incrmean, incrmeanstdev, incrmmeanvar, incrvariance\n","incrmgmean":"\nincrmgmean( W )\n    Returns an accumulator function which incrementally computes a moving\n    geometric mean.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving geometric mean.\n\n    If provided a value, the accumulator function returns an updated moving\n    geometric mean. If not provided a value, the accumulator function returns\n    the current moving geometric mean.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmgmean( 3 );\n    > var v = accumulator()\n    null\n    > v = accumulator( 2.0 )\n    2.0\n    > v = accumulator( 5.0 )\n    ~3.16\n    > v = accumulator( 3.0 )\n    ~3.11\n    > v = accumulator( 5.0 )\n    ~4.22\n    > v = accumulator()\n    ~4.22\n\n    See Also\n    --------\n    incrgmean, incrmhmean, incrmmean\n","incrmgrubbs":"\nincrmgrubbs( W[, options] )\n    Returns an accumulator function which incrementally performs a moving\n    Grubbs' test for detecting outliers.\n\n    Grubbs' test assumes that data is normally distributed. Accordingly, one\n    should first verify that the data can be reasonably approximated by a normal\n    distribution before applying the Grubbs' test.\n\n    The `W` parameter defines the number of values over which to perform Grubbs'\n    test. The minimum window size is 3.\n\n    If provided a value, the accumulator function returns updated test results.\n    If not provided a value, the accumulator function returns the current test\n    results.\n\n    Until provided `W` values, the accumulator function returns `null`.\n\n    The accumulator function returns an object having the following fields:\n\n    - rejected: boolean indicating whether the null hypothesis should be\n    rejected.\n    - alpha: significance level.\n    - criticalValue: critical value.\n    - statistic: test statistic.\n    - df: degrees of freedom.\n    - mean: sample mean.\n    - sd: corrected sample standard deviation.\n    - min: minimum value.\n    - max: maximum value.\n    - alt: alternative hypothesis.\n    - method: method name.\n    - print: method for pretty-printing test output.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    options: Object (optional)\n        Function options.\n\n    options.alpha: number (optional)\n        Significance level. Default: 0.05.\n\n    options.alternative: string (optional)\n        Alternative hypothesis. The option may be one of the following values:\n\n        - 'two-sided': test whether the minimum or maximum value is an outlier.\n        - 'min': test whether the minimum value is an outlier.\n        - 'max': test whether the maximum value is an outlier.\n\n        Default: 'two-sided'.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var acc = incrmgrubbs( 20 );\n    > var res = acc()\n    null\n    > for ( var i = 0; i < 200; i++ ) {\n    ...     res = acc( base.random.normal( 10.0, 5.0 ) );\n    ... };\n    > res.print()\n\n    References\n    ----------\n    - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n    Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n    of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n    - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n    Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n    00401706.1969.10490657.\n\n    See Also\n    --------\n    incrgrubbs\n","incrmhmean":"\nincrmhmean( W )\n    Returns an accumulator function which incrementally computes a moving\n    harmonic mean.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving harmonic mean.\n\n    If provided a value, the accumulator function returns an updated moving\n    harmonic mean. If not provided a value, the accumulator function returns the\n    current moving harmonic mean.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmhmean( 3 );\n    > var v = accumulator()\n    null\n    > v = accumulator( 2.0 )\n    2.0\n    > v = accumulator( 5.0 )\n    ~2.86\n    > v = accumulator( 3.0 )\n    ~2.90\n    > v = accumulator( 5.0 )\n    ~4.09\n    > v = accumulator()\n    ~4.09\n\n    See Also\n    --------\n    incrhmean, incrmgmean, incrmmean\n","incrmidrange":"\nincrmidrange()\n    Returns an accumulator function which incrementally computes a mid-range.\n\n    The mid-range is the arithmetic mean of maximum and minimum values.\n    Accordingly, the mid-range is the midpoint of the range and a measure of\n    central tendency.\n\n    If provided a value, the accumulator function returns an updated mid-range.\n    If not provided a value, the accumulator function returns the current mid-\n    range.\n\n    If provided `NaN`, the mid-range is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmidrange();\n    > var v = accumulator()\n    null\n    > v = accumulator( 3.14 )\n    3.14\n    > v = accumulator( -5.0 )\n    ~-0.93\n    > v = accumulator( 10.1 )\n    2.55\n    > v = accumulator()\n    2.55\n\n    See Also\n    --------\n    incrmean, incrmax, incrmin, incrrange, incrsummary\n","incrmin":"\nincrmin()\n    Returns an accumulator function which incrementally computes a minimum\n    value.\n\n    If provided a value, the accumulator function returns an updated minimum\n    value. If not provided a value, the accumulator function returns the current\n    minimum value.\n\n    If provided `NaN`, the minimum value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmin();\n    > var m = accumulator()\n    null\n    > m = accumulator( 3.14 )\n    3.14\n    > m = accumulator( -5.0 )\n    -5.0\n    > m = accumulator( 10.1 )\n    -5.0\n    > m = accumulator()\n    -5.0\n\n    See Also\n    --------\n    incrmax, incrmidrange, incrmmin, incrrange, incrsummary\n","incrminabs":"\nincrminabs()\n    Returns an accumulator function which incrementally computes a minimum\n    absolute value.\n\n    If provided a value, the accumulator function returns an updated minimum\n    absolute value. If not provided a value, the accumulator function returns\n    the current minimum absolute value.\n\n    If provided `NaN`, the minimum value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrminabs();\n    > var m = accumulator()\n    null\n    > m = accumulator( 3.14 )\n    3.14\n    > m = accumulator( -5.0 )\n    3.14\n    > m = accumulator( 10.1 )\n    3.14\n    > m = accumulator()\n    3.14\n\n    See Also\n    --------\n    incrmaxabs, incrmin, incrmminabs\n","incrminmax":"\nincrminmax( [out] )\n    Returns an accumulator function which incrementally computes a minimum and\n    maximum.\n\n    If provided a value, the accumulator function returns an updated minimum and\n    maximum. If not provided a value, the accumulator function returns the\n    current minimum and maximum.\n\n    If provided `NaN`, the minimum and maximum values are equal to `NaN` for all\n    future invocations.\n\n    Parameters\n    ----------\n    out: Array|TypedArray (optional)\n        Output array.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrminmax();\n    > var mm = accumulator()\n    null\n    > mm = accumulator( 2.0 )\n    [ 2.0, 2.0 ]\n    > mm = accumulator( -5.0 )\n    [ -5.0, 2.0 ]\n    > mm = accumulator( 3.0 )\n    [ -5.0, 3.0 ]\n    > mm = accumulator( 5.0 )\n    [ -5.0, 5.0 ]\n    > mm = accumulator()\n    [ -5.0, 5.0 ]\n\n    See Also\n    --------\n    incrmax, incrmin, incrmminmax, incrrange\n","incrminmaxabs":"\nincrminmaxabs( [out] )\n    Returns an accumulator function which incrementally computes a minimum and\n    maximum absolute value.\n\n    If provided a value, the accumulator function returns an updated minimum and\n    maximum. If not provided a value, the accumulator function returns the\n    current minimum and maximum.\n\n    If provided `NaN`, the minimum and maximum values are equal to `NaN` for all\n    future invocations.\n\n    Parameters\n    ----------\n    out: Array|TypedArray (optional)\n        Output array.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrminmaxabs();\n    > var mm = accumulator()\n    null\n    > mm = accumulator( 2.0 )\n    [ 2.0, 2.0 ]\n    > mm = accumulator( -5.0 )\n    [ 2.0, 5.0 ]\n    > mm = accumulator( 3.0 )\n    [ 2.0, 5.0 ]\n    > mm = accumulator( 5.0 )\n    [ 2.0, 5.0 ]\n    > mm = accumulator()\n    [ 2.0, 5.0 ]\n\n    See Also\n    --------\n    incrmaxabs, incrminabs, incrminmax, incrmminmaxabs\n","incrmmaape":"\nincrmmaape( W )\n    Returns an accumulator function which incrementally computes a moving\n    mean arctangent absolute percentage error (MAAPE).\n\n    The `W` parameter defines the number of values over which to compute the\n    moving mean arctangent absolute percentage error.\n\n    If provided input values, the accumulator function returns an updated moving\n    mean arctangent absolute percentage error. If not provided input values, the\n    accumulator function returns the current moving mean arctangent absolute\n    percentage error.\n\n    Note that, unlike the mean absolute percentage error (MAPE), the mean\n    arctangent absolute percentage error is expressed in radians on the interval\n    [0,π/2].\n\n    As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n    returned values are calculated from smaller sample sizes. Until the window\n    is full, each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmaape( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    ~0.32\n    > m = accumulator( 5.0, 2.0 )\n    ~0.65\n    > m = accumulator( 3.0, 2.0 )\n    ~0.59\n    > m = accumulator( 2.0, 5.0 )\n    ~0.66\n    > m = accumulator()\n    ~0.66\n\n    See Also\n    --------\n    incrmaape, incrmmape, incrmmpe, incrmmean\n","incrmmae":"\nincrmmae( W )\n    Returns an accumulator function which incrementally computes a moving\n    mean absolute error (MAE).\n\n    The `W` parameter defines the number of values over which to compute the\n    moving mean absolute error.\n\n    If provided a value, the accumulator function returns an updated moving\n    mean absolute error. If not provided a value, the accumulator function\n    returns the current moving mean absolute error.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmae( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    1.0\n    > m = accumulator( -5.0, 2.0 )\n    4.0\n    > m = accumulator( 3.0, 2.0 )\n    3.0\n    > m = accumulator( 5.0, -2.0 )\n    5.0\n    > m = accumulator()\n    5.0\n\n    See Also\n    --------\n    incrmae, incrmme, incrmmean\n","incrmmape":"\nincrmmape( W )\n    Returns an accumulator function which incrementally computes a moving\n    mean absolute percentage error (MAPE).\n\n    The `W` parameter defines the number of values over which to compute the\n    moving mean absolute percentage error.\n\n    If provided input values, the accumulator function returns an updated moving\n    mean absolute percentage error. If not provided input values, the\n    accumulator function returns the current moving mean absolute percentage\n    error.\n\n    As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n    returned values are calculated from smaller sample sizes. Until the window\n    is full, each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmape( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    ~33.33\n    > m = accumulator( 5.0, 2.0 )\n    ~91.67\n    > m = accumulator( 3.0, 2.0 )\n    ~77.78\n    > m = accumulator( 2.0, 5.0 )\n    ~86.67\n    > m = accumulator()\n    ~86.67\n\n    See Also\n    --------\n    incrmape, incrmmaape, incrmmpe, incrmmean\n","incrmmax":"\nincrmmax( W )\n    Returns an accumulator function which incrementally computes a moving\n    maximum value.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving maximum.\n\n    If provided a value, the accumulator function returns an updated moving\n    maximum. If not provided a value, the accumulator function returns the\n    current moving maximum.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmax( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0 )\n    2.0\n    > m = accumulator( -5.0 )\n    2.0\n    > m = accumulator( 3.0 )\n    3.0\n    > m = accumulator( 5.0 )\n    5.0\n    > m = accumulator()\n    5.0\n\n    See Also\n    --------\n    incrmax, incrmmidrange, incrmmin, incrmrange, incrmsummary\n","incrmmaxabs":"\nincrmmaxabs( W )\n    Returns an accumulator function which incrementally computes a moving\n    maximum absolute value.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving maximum absolute value.\n\n    If provided a value, the accumulator function returns an updated moving\n    maximum absolute value. If not provided a value, the accumulator function\n    returns the current moving maximum absolute value.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmaxabs( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0 )\n    2.0\n    > m = accumulator( -5.0 )\n    5.0\n    > m = accumulator( 3.0 )\n    5.0\n    > m = accumulator( 5.0 )\n    5.0\n    > m = accumulator()\n    5.0\n\n    See Also\n    --------\n    incrmaxabs, incrmmax, incrmminabs\n","incrmmda":"\nincrmmda( W )\n    Returns an accumulator function which incrementally computes a moving\n    mean directional accuracy (MDA).\n\n    The `W` parameter defines the number of values over which to compute the\n    moving mean directional accuracy.\n\n    If provided input values, the accumulator function returns an updated moving\n    mean directional accuracy. If not provided input values, the accumulator\n    function returns the current moving mean directional accuracy.\n\n    As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n    returned values are calculated from smaller sample sizes. Until the window\n    is full, each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmda( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    1.0\n    > m = accumulator( 5.0, 2.0 )\n    0.5\n    > m = accumulator( 3.0, 2.0 )\n    ~0.33\n    > m = accumulator( 4.0, 5.0 )\n    ~0.33\n    > m = accumulator()\n    ~0.33\n\n    See Also\n    --------\n    incrmda, incrmmape\n","incrmme":"\nincrmme( W )\n    Returns an accumulator function which incrementally computes a moving\n    mean error (ME).\n\n    The `W` parameter defines the number of values over which to compute the\n    moving mean error.\n\n    If provided a value, the accumulator function returns an updated moving\n    mean error. If not provided a value, the accumulator function returns the\n    current moving mean error.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmme( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    1.0\n    > m = accumulator( -5.0, 2.0 )\n    4.0\n    > m = accumulator( 3.0, 2.0 )\n    ~2.33\n    > m = accumulator( 5.0, -2.0 )\n    ~-0.33\n    > m = accumulator()\n    ~-0.33\n\n    See Also\n    --------\n    incrme, incrmmae, incrmmean\n","incrmmean":"\nincrmmean( W )\n    Returns an accumulator function which incrementally computes a moving\n    arithmetic mean.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving mean.\n\n    If provided a value, the accumulator function returns an updated moving\n    mean. If not provided a value, the accumulator function returns the current\n    moving mean.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmean( 3 );\n    > var mu = accumulator()\n    null\n    > mu = accumulator( 2.0 )\n    2.0\n    > mu = accumulator( -5.0 )\n    -1.5\n    > mu = accumulator( 3.0 )\n    0.0\n    > mu = accumulator( 5.0 )\n    1.0\n    > mu = accumulator()\n    1.0\n\n    See Also\n    --------\n    incrmean, incrmsum, incrmstdev, incrmsummary, incrmvariance\n","incrmmeanabs":"\nincrmmeanabs( W )\n    Returns an accumulator function which incrementally computes a moving\n    arithmetic mean of absolute values.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving mean.\n\n    If provided a value, the accumulator function returns an updated moving\n    mean. If not provided a value, the accumulator function returns the current\n    moving mean.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmeanabs( 3 );\n    > var mu = accumulator()\n    null\n    > mu = accumulator( 2.0 )\n    2.0\n    > mu = accumulator( -5.0 )\n    3.5\n    > mu = accumulator( 3.0 )\n    ~3.33\n    > mu = accumulator( 5.0 )\n    ~4.33\n    > mu = accumulator()\n    ~4.33\n\n    See Also\n    --------\n    incrmeanabs, incrmmean, incrmsumabs\n","incrmmeanabs2":"\nincrmmeanabs2( W )\n    Returns an accumulator function which incrementally computes a moving\n    arithmetic mean of squared absolute values.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving mean.\n\n    If provided a value, the accumulator function returns an updated moving\n    mean. If not provided a value, the accumulator function returns the current\n    moving mean.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmeanabs2( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0 )\n    4.0\n    > m = accumulator( -5.0 )\n    14.5\n    > m = accumulator( 3.0 )\n    ~12.67\n    > m = accumulator( 5.0 )\n    ~19.67\n    > m = accumulator()\n    ~19.67\n\n    See Also\n    --------\n    incrmeanabs2, incrmmeanabs, incrmsumabs2\n","incrmmeanstdev":"\nincrmmeanstdev( [out,] W )\n    Returns an accumulator function which incrementally computes a moving\n    arithmetic mean and corrected sample standard deviation.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving arithmetic mean and corrected sample standard deviation.\n\n    If provided a value, the accumulator function returns updated accumulated\n    values. If not provided a value, the accumulator function returns the\n    current moving accumulated values.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    accumulated values are calculated from smaller sample sizes. Until the\n    window is full, each returned accumulated value is calculated from all\n    provided values.\n\n    Parameters\n    ----------\n    out: Array|TypedArray (optional)\n        Output array.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmeanstdev( 3 );\n    > var v = accumulator()\n    null\n    > v = accumulator( 2.0 )\n    [ 2.0, 0.0 ]\n    > v = accumulator( -5.0 )\n    [ -1.5, ~4.95 ]\n    > v = accumulator( 3.0 )\n    [ 0.0, ~4.36 ]\n    > v = accumulator( 5.0 )\n    [ 1.0, ~5.29 ]\n    > v = accumulator()\n    [ 1.0, ~5.29 ]\n\n    See Also\n    --------\n    incrmeanstdev, incrmmean, incrmmeanvar, incrmstdev\n","incrmmeanvar":"\nincrmmeanvar( [out,] W )\n    Returns an accumulator function which incrementally computes a moving\n    arithmetic mean and unbiased sample variance.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving arithmetic mean and unbiased sample variance.\n\n    If provided a value, the accumulator function returns updated accumulated\n    values. If not provided a value, the accumulator function returns the\n    current moving accumulated values.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    accumulated values are calculated from smaller sample sizes. Until the\n    window is full, each returned accumulated value is calculated from all\n    provided values.\n\n    Parameters\n    ----------\n    out: Array|TypedArray (optional)\n        Output array.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmeanvar( 3 );\n    > var v = accumulator()\n    null\n    > v = accumulator( 2.0 )\n    [ 2.0, 0.0 ]\n    > v = accumulator( -5.0 )\n    [ -1.5, 24.5 ]\n    > v = accumulator( 3.0 )\n    [ 0.0, 19.0 ]\n    > v = accumulator( 5.0 )\n    [ 1.0, 28.0 ]\n    > v = accumulator()\n    [ 1.0, 28.0 ]\n\n    See Also\n    --------\n    incrmeanvar, incrmmean, incrmmeanstdev, incrmvariance\n","incrmmidrange":"\nincrmmidrange( W )\n    Returns an accumulator function which incrementally computes a moving mid-\n    range.\n\n    The mid-range is the arithmetic mean of maximum and minimum values.\n    Accordingly, the mid-range is the midpoint of the range and a measure of\n    central tendency.\n\n    The `W` parameter defines the number of values over which to compute\n    the moving mid-range.\n\n    If provided a value, the accumulator function returns an updated moving mid-\n    range. If not provided a value, the accumulator function returns the current\n    moving mid-range.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmidrange( 3 );\n    > var mr = accumulator()\n    null\n    > mr = accumulator( 2.0 )\n    2.0\n    > mr = accumulator( -5.0 )\n    -1.5\n    > mr = accumulator( 3.0 )\n    -1.0\n    > mr = accumulator( 5.0 )\n    0.0\n    > mr = accumulator()\n    0.0\n\n    See Also\n    --------\n    incrmmean, incrmmax, incrmmin, incrmrange\n","incrmmin":"\nincrmmin( W )\n    Returns an accumulator function which incrementally computes a moving\n    minimum value.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving minimum.\n\n    If provided a value, the accumulator function returns an updated moving\n    minimum. If not provided a value, the accumulator function returns the\n    current moving minimum.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmin( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0 )\n    2.0\n    > m = accumulator( -5.0 )\n    -5.0\n    > m = accumulator( 3.0 )\n    -5.0\n    > m = accumulator( 5.0 )\n    -5.0\n    > m = accumulator()\n    -5.0\n\n    See Also\n    --------\n    incrmin, incrmmax, incrmmidrange, incrmrange, incrmsummary\n","incrmminabs":"\nincrmminabs( W )\n    Returns an accumulator function which incrementally computes a moving\n    minimum absolute value.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving minimum absolute value.\n\n    If provided a value, the accumulator function returns an updated moving\n    minimum absolute value. If not provided a value, the accumulator function\n    returns the current moving minimum absolute value.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmminabs( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0 )\n    2.0\n    > m = accumulator( -5.0 )\n    2.0\n    > m = accumulator( 3.0 )\n    2.0\n    > m = accumulator( 5.0 )\n    3.0\n    > m = accumulator()\n    3.0\n\n    See Also\n    --------\n    incrminabs, incrmmaxabs, incrmmin\n","incrmminmax":"\nincrmminmax( [out,] W )\n    Returns an accumulator function which incrementally computes a moving\n    minimum and maximum.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving minimum and maximum.\n\n    If provided a value, the accumulator function returns an updated moving\n    minimum and maximum. If not provided a value, the accumulator function\n    returns the current moving minimum and maximum.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    minimum and maximum values are calculated from smaller sample sizes. Until\n    the window is full, each returned minimum and maximum is calculated from all\n    provided values.\n\n    Parameters\n    ----------\n    out: Array|TypedArray (optional)\n        Output array.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmminmax( 3 );\n    > var mm = accumulator()\n    null\n    > mm = accumulator( 2.0 )\n    [ 2.0, 2.0 ]\n    > mm = accumulator( -5.0 )\n    [ -5.0, 2.0 ]\n    > mm = accumulator( 3.0 )\n    [ -5.0, 3.0 ]\n    > mm = accumulator( 5.0 )\n    [ -5.0, 5.0 ]\n    > mm = accumulator()\n    [ -5.0, 5.0 ]\n\n    See Also\n    --------\n    incrmax, incrmin, incrmmax, incrminmax, incrmmin, incrmrange\n","incrmminmaxabs":"\nincrmminmaxabs( [out,] W )\n    Returns an accumulator function which incrementally computes moving minimum\n    and maximum absolute values.\n\n    The `W` parameter defines the number of values over which to compute moving\n    minimum and maximum absolute values.\n\n    If provided a value, the accumulator function returns an updated moving\n    minimum and maximum. If not provided a value, the accumulator function\n    returns the current moving minimum and maximum.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    minimum and maximum values are calculated from smaller sample sizes. Until\n    the window is full, each returned minimum and maximum is calculated from all\n    provided values.\n\n    Parameters\n    ----------\n    out: Array|TypedArray (optional)\n        Output array.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmminmaxabs( 3 );\n    > var mm = accumulator()\n    null\n    > mm = accumulator( 2.0 )\n    [ 2.0, 2.0 ]\n    > mm = accumulator( -5.0 )\n    [ 2.0, 5.0 ]\n    > mm = accumulator( 3.0 )\n    [ 2.0, 5.0 ]\n    > mm = accumulator( 5.0 )\n    [ 3.0, 5.0 ]\n    > mm = accumulator()\n    [ 3.0, 5.0 ]\n\n    See Also\n    --------\n    incrminmaxabs, incrmmax, incrmmaxabs, incrmmin, incrmminabs, incrmminmax\n","incrmmpe":"\nincrmmpe( W )\n    Returns an accumulator function which incrementally computes a moving\n    mean percentage error (MPE).\n\n    The `W` parameter defines the number of values over which to compute the\n    moving mean percentage error.\n\n    If provided input values, the accumulator function returns an updated moving\n    mean percentage error. If not provided input values, the accumulator\n    function returns the current moving mean percentage error.\n\n    As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n    returned values are calculated from smaller sample sizes. Until the window\n    is full, each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmpe( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    ~33.33\n    > m = accumulator( 5.0, 2.0 )\n    ~-58.33\n    > m = accumulator( 3.0, 2.0 )\n    ~-55.56\n    > m = accumulator( 2.0, 5.0 )\n    ~-46.67\n    > m = accumulator()\n    ~-46.67\n\n    See Also\n    --------\n    incrmmape, incrmme, incrmpe\n","incrmmse":"\nincrmmse( W )\n    Returns an accumulator function which incrementally computes a moving mean\n    squared error (MSE).\n\n    The `W` parameter defines the number of values over which to compute the\n    moving mean squared error.\n\n    If provided a value, the accumulator function returns an updated moving mean\n    squared error. If not provided a value, the accumulator function returns the\n    current moving mean squared error.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmse( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    1.0\n    > m = accumulator( -5.0, 2.0 )\n    25.0\n    > m = accumulator( 3.0, 2.0 )\n    17.0\n    > m = accumulator( 5.0, -2.0 )\n    33.0\n    > m = accumulator()\n    33.0\n\n    See Also\n    --------\n    incrmrmse, incrmrss, incrmse\n","incrmpcorr":"\nincrmpcorr( W[, mx, my] )\n    Returns an accumulator function which incrementally computes a moving\n    sample Pearson product-moment correlation coefficient.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving sample correlation coefficient.\n\n    If provided values, the accumulator function returns an updated moving\n    sample correlation coefficient. If not provided values, the accumulator\n    function returns the current moving sample correlation coefficient.\n\n    As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n    returned values are calculated from smaller sample sizes. Until the window\n    is full, each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    mx: number (optional)\n        Known mean.\n\n    my: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmpcorr( 3 );\n    > var r = accumulator()\n    null\n    > r = accumulator( 2.0, 1.0 )\n    0.0\n    > r = accumulator( -5.0, 3.14 )\n    ~-1.0\n    > r = accumulator( 3.0, -1.0 )\n    ~-0.925\n    > r = accumulator( 5.0, -9.5 )\n    ~-0.863\n    > r = accumulator()\n    ~-0.863\n\n    See Also\n    --------\n    incrmcovariance, incrmpcorrdist, incrpcorr\n","incrmpcorr2":"\nincrmpcorr2( W[, mx, my] )\n    Returns an accumulator function which incrementally computes a moving\n    squared sample Pearson product-moment correlation coefficient.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving squared sample correlation coefficient.\n\n    If provided values, the accumulator function returns an updated moving\n    squared sample correlation coefficient. If not provided values, the\n    accumulator function returns the current moving squared sample correlation\n    coefficient.\n\n    As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n    returned values are calculated from smaller sample sizes. Until the window\n    is full, each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    mx: number (optional)\n        Known mean.\n\n    my: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmpcorr2( 3 );\n    > var r2 = accumulator()\n    null\n    > r2 = accumulator( 2.0, 1.0 )\n    0.0\n    > r2 = accumulator( -5.0, 3.14 )\n    ~1.0\n    > r2 = accumulator( 3.0, -1.0 )\n    ~0.86\n    > r2 = accumulator( 5.0, -9.5 )\n    ~0.74\n    > r2 = accumulator()\n    ~0.74\n\n    See Also\n    --------\n    incrmapcorr, incrmpcorr, incrpcorr2\n","incrmpcorrdist":"\nincrmpcorrdist( W[, mx, my] )\n    Returns an accumulator function which incrementally computes a moving\n    sample Pearson product-moment correlation distance.\n\n    The correlation distance is defined as one minus the Pearson product-moment\n    correlation coefficient and, thus, resides on the interval [0,2].\n\n    However, due to limitations inherent in representing numeric values using\n    floating-point format (i.e., the inability to represent numeric values with\n    infinite precision), the correlation distance between perfectly correlated\n    random variables may *not* be `0` or `2`. In fact, the correlation distance\n    is *not* guaranteed to be strictly on the interval [0,2]. Any computed\n    distance should, however, be within floating-point roundoff error.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving sample correlation distance.\n\n    If provided values, the accumulator function returns an updated moving\n    sample correlation distance. If not provided values, the accumulator\n    function returns the current moving sample correlation distance.\n\n    As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n    returned values are calculated from smaller sample sizes. Until the window\n    is full, each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    mx: number (optional)\n        Known mean.\n\n    my: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmpcorrdist( 3 );\n    > var d = accumulator()\n    null\n    > d = accumulator( 2.0, 1.0 )\n    1.0\n    > d = accumulator( -5.0, 3.14 )\n    ~2.0\n    > d = accumulator( 3.0, -1.0 )\n    ~1.925\n    > d = accumulator( 5.0, -9.5 )\n    ~1.863\n    > d = accumulator()\n    ~1.863\n\n    See Also\n    --------\n    incrmpcorr, incrpcorrdist\n","incrmpe":"\nincrmpe()\n    Returns an accumulator function which incrementally computes the mean\n    percentage error (MPE).\n\n    If provided input values, the accumulator function returns an updated mean\n    percentage error. If not provided input values, the accumulator function\n    returns the current mean percentage error.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmpe();\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    ~33.33\n    > m = accumulator( 5.0, 2.0 )\n    ~-58.33\n    > m = accumulator()\n    ~-58.33\n\n    See Also\n    --------\n    incrmape, incrme, incrmmpe\n","incrmprod":"\nincrmprod( W )\n    Returns an accumulator function which incrementally computes a moving\n    product.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving product.\n\n    If provided a value, the accumulator function returns an updated moving\n    product. If not provided a value, the accumulator function returns the\n    current moving product.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    For accumulations over large windows or accumulations of large numbers, care\n    should be taken to prevent overflow. Note, however, that overflow/underflow\n    may be transient, as the accumulator does not use a double-precision\n    floating-point number to store an accumulated product. Instead, the\n    accumulator splits an accumulated product into a normalized fraction and\n    exponent and updates each component separately. Doing so guards against a\n    loss in precision.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmprod( 3 );\n    > var p = accumulator()\n    null\n    > p = accumulator( 2.0 )\n    2.0\n    > p = accumulator( -5.0 )\n    -10.0\n    > p = accumulator( 3.0 )\n    -30.0\n    > p = accumulator( 5.0 )\n    -75.0\n    > p = accumulator()\n    -75.0\n\n    See Also\n    --------\n    incrmsum, incrprod\n","incrmrange":"\nincrmrange( W )\n    Returns an accumulator function which incrementally computes a moving range.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving range.\n\n    If provided a value, the accumulator function returns an updated moving\n    range. If not provided a value, the accumulator function returns the current\n    moving range.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmrange( 3 );\n    > var r = accumulator()\n    null\n    > r = accumulator( 2.0 )\n    0.0\n    > r = accumulator( -5.0 )\n    7.0\n    > r = accumulator( 3.0 )\n    8.0\n    > r = accumulator( 5.0 )\n    10.0\n    > r = accumulator()\n    10.0\n\n    See Also\n    --------\n    incrmmax, incrmmean, incrmmin, incrmsummary, incrrange\n","incrmrmse":"\nincrmrmse( W )\n    Returns an accumulator function which incrementally computes a moving root\n    mean squared error (RMSE).\n\n    The `W` parameter defines the number of values over which to compute the\n    moving root mean squared error.\n\n    If provided a value, the accumulator function returns an updated moving root\n    mean squared error. If not provided a value, the accumulator function\n    returns the current moving root mean squared error.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmrmse( 3 );\n    > var r = accumulator()\n    null\n    > r = accumulator( 2.0, 3.0 )\n    1.0\n    > r = accumulator( -5.0, 2.0 )\n    5.0\n    > r = accumulator( 3.0, 2.0 )\n    ~4.12\n    > r = accumulator( 5.0, -2.0 )\n    ~5.74\n    > r = accumulator()\n    ~5.74\n\n    See Also\n    --------\n    incrmmse, incrmrss, incrrmse\n","incrmrss":"\nincrmrss( W )\n    Returns an accumulator function which incrementally computes a moving\n    residual sum of squares (RSS).\n\n    The `W` parameter defines the number of values over which to compute the\n    moving residual sum of squares.\n\n    If provided a value, the accumulator function returns an updated moving\n    residual sum of squares. If not provided a value, the accumulator function\n    returns the current moving residual sum of squares.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmrss( 3 );\n    > var r = accumulator()\n    null\n    > r = accumulator( 2.0, 3.0 )\n    1.0\n    > r = accumulator( -5.0, 2.0 )\n    50.0\n    > r = accumulator( 3.0, 2.0 )\n    51.0\n    > r = accumulator( 5.0, -2.0 )\n    99.0\n    > r = accumulator()\n    99.0\n\n    See Also\n    --------\n    incrrss, incrmmse, incrmrmse\n","incrmse":"\nincrmse()\n    Returns an accumulator function which incrementally computes the mean\n    squared error (MSE).\n\n    If provided input values, the accumulator function returns an updated mean\n    squared error. If not provided input values, the accumulator function\n    returns the current mean squared error.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmse();\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    1.0\n    > m = accumulator( -5.0, 2.0 )\n    25.0\n    > m = accumulator()\n    25.0\n\n    See Also\n    --------\n    incrmmse, incrrmse, incrrss\n","incrmstdev":"\nincrmstdev( W[, mean] )\n    Returns an accumulator function which incrementally computes a moving\n    corrected sample standard deviation.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving corrected sample standard deviation.\n\n    If provided a value, the accumulator function returns an updated moving\n    corrected sample standard deviation. If not provided a value, the\n    accumulator function returns the current moving corrected sample standard\n    deviation.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    mean: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmstdev( 3 );\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    0.0\n    > s = accumulator( -5.0 )\n    ~4.95\n    > s = accumulator( 3.0 )\n    ~4.36\n    > s = accumulator( 5.0 )\n    ~5.29\n    > s = accumulator()\n    ~5.29\n\n    See Also\n    --------\n    incrmmean, incrmsummary, incrmvariance, incrstdev\n","incrmsum":"\nincrmsum( W )\n    Returns an accumulator function which incrementally computes a moving sum.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving sum.\n\n    If provided a value, the accumulator function returns an updated moving sum.\n    If not provided a value, the accumulator function returns the current moving\n    sum.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmsum( 3 );\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    2.0\n    > s = accumulator( -5.0 )\n    -3.0\n    > s = accumulator( 3.0 )\n    0.0\n    > s = accumulator( 5.0 )\n    3.0\n    > s = accumulator()\n    3.0\n\n    See Also\n    --------\n    incrmmean, incrmsummary, incrsum\n","incrmsumabs":"\nincrmsumabs( W )\n    Returns an accumulator function which incrementally computes a moving sum of\n    absolute values.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving sum.\n\n    If provided a value, the accumulator function returns an updated moving sum.\n    If not provided a value, the accumulator function returns the current moving\n    sum.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmsumabs( 3 );\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    2.0\n    > s = accumulator( -5.0 )\n    7.0\n    > s = accumulator( 3.0 )\n    10.0\n    > s = accumulator( -5.0 )\n    13.0\n    > s = accumulator()\n    13.0\n\n    See Also\n    --------\n    incrmmeanabs, incrmsum, incrsum, incrsumabs\n","incrmsumabs2":"\nincrmsumabs2( W )\n    Returns an accumulator function which incrementally computes a moving sum of\n    squared absolute values.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving sum.\n\n    If provided a value, the accumulator function returns an updated moving sum.\n    If not provided a value, the accumulator function returns the current moving\n    sum.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmsumabs2( 3 );\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    4.0\n    > s = accumulator( -5.0 )\n    29.0\n    > s = accumulator( 3.0 )\n    38.0\n    > s = accumulator( -5.0 )\n    59.0\n    > s = accumulator()\n    59.0\n\n    See Also\n    --------\n    incrmmeanabs2, incrmsumabs, incrsumabs, incrsumabs2\n","incrmsummary":"\nincrmsummary( W )\n    Returns an accumulator function which incrementally computes a moving\n    statistical summary.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving statistical summary.\n\n    If provided a value, the accumulator function returns an updated moving\n    statistical summary. If not provided a value, the accumulator function\n    returns the current moving statistical summary.\n\n    The returned summary is an object containing the following fields:\n\n    - window: window size.\n    - sum: sum.\n    - mean: arithmetic mean.\n    - variance: unbiased sample variance.\n    - stdev: corrected sample standard deviation.\n    - min: minimum value.\n    - max: maximum value.\n    - range: range.\n    - midrange: arithmetic mean of the minimum and maximum values.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    summaries are calculated from smaller sample sizes. Until the window is\n    full, each returned summary is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmsummary( 3 );\n    > var s = accumulator()\n    {}\n    > s = accumulator( 2.0 )\n    {...}\n    > s = accumulator( -5.0 )\n    {...}\n    > s = accumulator()\n    {...}\n\n    See Also\n    --------\n    incrmmean, incrmstdev, incrmsum, incrmvariance, incrsummary\n","incrmsumprod":"\nincrmsumprod( W )\n    Returns an accumulator function which incrementally computes a moving sum of\n    products.\n\n    The `W` parameter defines the number of (x,y) pairs over which to compute\n    the moving sum of products.\n\n    If provided input values, the accumulator function returns an updated moving\n    sum. If not provided input values, the accumulator function returns the\n    current moving sum.\n\n    As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n    returned values are calculated from smaller sample sizes. Until the window\n    is full, each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmsumprod( 3 );\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0, 3.0 )\n    6.0\n    > s = accumulator( -5.0, 2.0 )\n    -4.0\n    > s = accumulator( 3.0, -2.0 )\n    -10.0\n    > s = accumulator( 5.0, 3.0 )\n    -1.0\n    > s = accumulator()\n    -1.0\n\n    See Also\n    --------\n    incrmprod, incrmsum, incrsumprod\n","incrmvariance":"\nincrmvariance( W[, mean] )\n    Returns an accumulator function which incrementally computes a moving\n    unbiased sample variance.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving unbiased sample variance.\n\n    If provided a value, the accumulator function returns an updated moving\n    unbiased sample variance. If not provided a value, the accumulator function\n    returns the current moving unbiased sample variance.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    mean: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmvariance( 3 );\n    > var s2 = accumulator()\n    null\n    > s2 = accumulator( 2.0 )\n    0.0\n    > s2 = accumulator( -5.0 )\n    24.5\n    > s2 = accumulator( 3.0 )\n    19.0\n    > s2 = accumulator( 5.0 )\n    28.0\n    > s2 = accumulator()\n    28.0\n\n    See Also\n    --------\n    incrmmean, incrmstdev, incrmsummary, incrvariance\n","incrmvmr":"\nincrmvmr( W[, mean] )\n    Returns an accumulator function which incrementally computes a moving\n    variance-to-mean (VMR).\n\n    The `W` parameter defines the number of values over which to compute the\n    moving variance-to-mean ratio.\n\n    If provided a value, the accumulator function returns an updated moving\n    variance-to-mean ratio. If not provided a value, the accumulator function\n    returns the current moving variance-to-mean ratio.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    mean: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmvmr( 3 );\n    > var F = accumulator()\n    null\n    > F = accumulator( 2.0 )\n    0.0\n    > F = accumulator( 1.0 )\n    ~0.33\n    > F = accumulator( 3.0 )\n    0.5\n    > F = accumulator( 7.0 )\n    ~2.55\n    > F = accumulator()\n    ~2.55\n\n    See Also\n    --------\n    incrmmean, incrmvariance, incrvmr\n","incrnancount":"\nincrnancount()\n    Returns an accumulator function which incrementally updates a count,\n    ignoring `NaN` values.\n\n    If provided a value, the accumulator function returns an updated count. If\n    not provided a value, the accumulator function returns the current count.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrnancount();\n    > var v = accumulator()\n    0\n    > v = accumulator( 2.0 )\n    1\n    > v = accumulator( -5.0 )\n    2\n    > v = accumulator()\n    2\n\n    See Also\n    --------\n    incrnansum\n","incrnansum":"\nincrnansum()\n    Returns an accumulator function which incrementally computes a sum, ignoring\n    `NaN` values.\n\n    If provided a value, the accumulator function returns an updated sum. If not\n    provided a value, the accumulator function returns the current sum.\n\n    For long running accumulations or accumulations of large numbers, care\n    should be taken to prevent overflow.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrnansum();\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    2.0\n    > s = accumulator( NaN )\n    2.0\n    > s = accumulator( -5.0 )\n    -3.0\n    > s = accumulator()\n    -3.0\n\n    See Also\n    --------\n    incrnansumabs, incrsum\n","incrnansumabs":"\nincrnansumabs()\n    Returns an accumulator function which incrementally computes a sum of\n    absolute values, ignoring NaN values.\n\n    If provided a value, the accumulator function returns an updated sum. If not\n    provided a value, the accumulator function returns the current sum.\n\n    For long running accumulations or accumulations of large numbers, care\n    should be taken to prevent overflow.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrnansumabs();\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    2.0\n    > s = accumulator( NaN )\n    2.0\n    > s = accumulator( -5.0 )\n    7.0\n    > s = accumulator()\n    7.0\n\n    See Also\n    --------\n    incrnansum, incrnansumabs2, incrsumabs\n","incrnansumabs2":"\nincrnansumabs2()\n    Returns an accumulator function which incrementally computes a sum of\n    squared absolute values, ignoring NaN values.\n\n    If provided a value, the accumulator function returns an updated sum. If not\n    provided a value, the accumulator function returns the current sum.\n\n    For long running accumulations or accumulations of large numbers, care\n    should be taken to prevent overflow.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrnansumabs2();\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    4.0\n    > s = accumulator( NaN )\n    4.0\n    > s = accumulator( -5.0 )\n    29.0\n    > s = accumulator()\n    29.0\n\n    See Also\n    --------\n    incrnansum, incrnansumabs, incrsumabs2\n","incrpcorr":"\nincrpcorr( [mx, my] )\n    Returns an accumulator function which incrementally computes a sample\n    Pearson product-moment correlation coefficient.\n\n    If provided values, the accumulator function returns an updated sample\n    correlation coefficient. If not provided values, the accumulator function\n    returns the current sample correlation coefficient.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    mx: number (optional)\n        Known mean.\n\n    my: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrpcorr();\n    > var r = accumulator()\n    null\n    > r = accumulator( 2.0, 1.0 )\n    0.0\n    > r = accumulator( -5.0, 3.14 )\n    ~-1.0\n    > r = accumulator()\n    ~-1.0\n\n    See Also\n    --------\n    incrcovariance, incrmpcorr, incrsummary\n","incrpcorr2":"\nincrpcorr2( [mx, my] )\n    Returns an accumulator function which incrementally computes the squared\n    sample Pearson product-moment correlation coefficient.\n\n    If provided values, the accumulator function returns an updated accumulated\n    value. If not provided values, the accumulator function returns the current\n    accumulated value.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    mx: number (optional)\n        Known mean.\n\n    my: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrpcorr2();\n    > var r2 = accumulator()\n    null\n    > r2 = accumulator( 2.0, 1.0 )\n    0.0\n    > r2 = accumulator( -5.0, 3.14 )\n    ~1.0\n    > r2 = accumulator()\n    ~1.0\n\n    See Also\n    --------\n    incrapcorr, incrmpcorr2, incrpcorr\n","incrpcorrdist":"\nincrpcorrdist( [mx, my] )\n    Returns an accumulator function which incrementally computes a sample\n    Pearson product-moment correlation distance.\n\n    The correlation distance is defined as one minus the Pearson product-moment\n    correlation coefficient and, thus, resides on the interval [0,2].\n\n    If provided values, the accumulator function returns an updated sample\n    correlation distance. If not provided values, the accumulator function\n    returns the current sample correlation distance.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    mx: number (optional)\n        Known mean.\n\n    my: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrpcorrdist();\n    > var d = accumulator()\n    null\n    > d = accumulator( 2.0, 1.0 )\n    1.0\n    > d = accumulator( -5.0, 3.14 )\n    ~2.0\n    > d = accumulator()\n    ~2.0\n\n    See Also\n    --------\n    incrcovariance, incrpcorr, incrsummary\n","incrpcorrdistmat":"\nincrpcorrdistmat( out[, means] )\n    Returns an accumulator function which incrementally computes a sample\n    Pearson product-moment correlation distance matrix.\n\n    If provided a data vector, the accumulator function returns an updated\n    sample correlation distance matrix. If not provided a data vector, the\n    accumulator function returns the current sample correlation distance matrix.\n\n    Due to limitations inherent in representing numeric values using floating-\n    point format (i.e., the inability to represent numeric values with infinite\n    precision), the correlation distance between perfectly correlated random\n    variables may *not* be `0` or `2`. In fact, the correlation distance is\n    *not* guaranteed to be strictly on the interval [0,2]. Any computed distance\n    should, however, be within floating-point roundoff error.\n\n    Parameters\n    ----------\n    out: integer|ndarray\n        Order of the correlation distance matrix or a square 2-dimensional\n        ndarray for storing the correlation distance matrix.\n\n    means: ndarray (optional)\n        Known means.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrpcorrdistmat( 2 );\n    > var out = accumulator()\n    <ndarray>\n    > var buf = new Float64Array( 2 );\n    > var shape = [ 2 ];\n    > var strides = [ 1 ];\n    > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n    > v.set( 0, 2.0 );\n    > v.set( 1, 1.0 );\n    > out = accumulator( v )\n    <ndarray>\n    > v.set( 0, -5.0 );\n    > v.set( 1, 3.14 );\n    > out = accumulator( v )\n    <ndarray>\n    > out = accumulator()\n    <ndarray>\n\n    See Also\n    --------\n    incrpcorrdist, incrpcorrmat\n","incrpcorrmat":"\nincrpcorrmat( out[, means] )\n    Returns an accumulator function which incrementally computes a sample\n    Pearson product-moment correlation matrix.\n\n    If provided a data vector, the accumulator function returns an updated\n    sample correlation matrix. If not provided a data vector, the accumulator\n    function returns the current sample correlation matrix.\n\n    Parameters\n    ----------\n    out: integer|ndarray\n        Order of the correlation matrix or a square 2-dimensional ndarray for\n        storing the correlation matrix.\n\n    means: ndarray (optional)\n        Known means.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrpcorrmat( 2 );\n    > var out = accumulator()\n    <ndarray>\n    > var buf = new Float64Array( 2 );\n    > var shape = [ 2 ];\n    > var strides = [ 1 ];\n    > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n    > v.set( 0, 2.0 );\n    > v.set( 1, 1.0 );\n    > out = accumulator( v )\n    <ndarray>\n    > v.set( 0, -5.0 );\n    > v.set( 1, 3.14 );\n    > out = accumulator( v )\n    <ndarray>\n    > out = accumulator()\n    <ndarray>\n\n    See Also\n    --------\n    incrcovmat, incrpcorr, incrpcorrdistmat\n","incrprod":"\nincrprod()\n    Returns an accumulator function which incrementally computes a product.\n\n    If provided a value, the accumulator function returns an updated product. If\n    not provided a value, the accumulator function returns the current product.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    For long running accumulations or accumulations of large numbers, care\n    should be taken to prevent overflow. Note, however, that overflow/underflow\n    may be transient, as the accumulator does not use a double-precision\n    floating-point number to store an accumulated product. Instead, the\n    accumulator splits an accumulated product into a normalized fraction and\n    exponent and updates each component separately. Doing so guards against a\n    loss in precision.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrprod();\n    > var v = accumulator()\n    null\n    > v = accumulator( 2.0 )\n    2.0\n    > v = accumulator( -5.0 )\n    -10.0\n    > v = accumulator()\n    -10.0\n\n    See Also\n    --------\n    incrmprod, incrsum, incrsummary\n","incrrange":"\nincrrange()\n    Returns an accumulator function which incrementally computes a range.\n\n    If provided a value, the accumulator function returns an updated range. If\n    not provided a value, the accumulator function returns the current range.\n\n    If provided `NaN`, the range is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrrange();\n    > var v = accumulator()\n    null\n    > v = accumulator( -2.0 )\n    0.0\n    > v = accumulator( 1.0 )\n    3.0\n    > v = accumulator( 3.0 )\n    5.0\n    > v = accumulator()\n    5.0\n\n    See Also\n    --------\n    incrmax, incrmean, incrmin, incrmrange, incrsummary\n","incrrmse":"\nincrrmse()\n    Returns an accumulator function which incrementally computes the root mean\n    squared error (RMSE).\n\n    If provided input values, the accumulator function returns an updated root\n    mean squared error. If not provided input values, the accumulator function\n    returns the current root mean squared error.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrrmse();\n    > var r = accumulator()\n    null\n    > r = accumulator( 2.0, 3.0 )\n    1.0\n    > r = accumulator( -5.0, 2.0 )\n    5.0\n    > r = accumulator()\n    5.0\n\n    See Also\n    --------\n    incrmrmse, incrmse, incrrss\n","incrrss":"\nincrrss()\n    Returns an accumulator function which incrementally computes the residual\n    sum of squares (RSS).\n\n    If provided input values, the accumulator function returns an updated\n    residual sum of squares. If not provided input values, the accumulator\n    function returns the current residual sum of squares.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrrss();\n    > var r = accumulator()\n    null\n    > r = accumulator( 2.0, 3.0 )\n    1.0\n    > r = accumulator( -5.0, 2.0 )\n    50.0\n    > r = accumulator()\n    50.0\n\n    See Also\n    --------\n    incrmrss, incrmse, incrrmse\n","incrskewness":"\nincrskewness()\n    Returns an accumulator function which incrementally computes a corrected\n    sample skewness.\n\n    If provided a value, the accumulator function returns an updated corrected\n    sample skewness. If not provided a value, the accumulator function returns\n    the current corrected sample skewness.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrskewness();\n    > var v = accumulator( 2.0 )\n    null\n    > v = accumulator( -5.0 )\n    null\n    > v = accumulator( -10.0 )\n    ~0.492\n    > v = accumulator()\n    ~0.492\n\n    See Also\n    --------\n    incrkurtosis, incrmean, incrstdev, incrsummary, incrvariance\n","incrspace":"\nincrspace( start, stop[, increment] )\n    Generates a linearly spaced numeric array using a provided increment.\n\n    If an `increment` is not provided, the default `increment` is `1`.\n\n    The output array is guaranteed to include the `start` value but does not\n    include the `stop` value.\n\n    Parameters\n    ----------\n    start: number\n        First array value.\n\n    stop: number\n        Array element bound.\n\n    increment: number (optional)\n        Increment. Default: `1`.\n\n    Returns\n    -------\n    arr: Array\n        Linearly spaced numeric array.\n\n    Examples\n    --------\n    > var arr = incrspace( 0, 11, 2 )\n    [ 0, 2, 4, 6, 8, 10 ]\n\n    See Also\n    --------\n    linspace, logspace\n","incrstdev":"\nincrstdev( [mean] )\n    Returns an accumulator function which incrementally computes a corrected\n    sample standard deviation.\n\n    If provided a value, the accumulator function returns an updated corrected\n    sample standard deviation. If not provided a value, the accumulator function\n    returns the current corrected sample standard deviation.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    mean: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrstdev();\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    0.0\n    > s = accumulator( -5.0 )\n    ~4.95\n    > s = accumulator()\n    ~4.95\n\n    See Also\n    --------\n    incrkurtosis, incrmean, incrmstdev, incrskewness, incrsummary, incrvariance\n","incrsum":"\nincrsum()\n    Returns an accumulator function which incrementally computes a sum.\n\n    If provided a value, the accumulator function returns an updated sum. If not\n    provided a value, the accumulator function returns the current sum.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    For long running accumulations or accumulations of large numbers, care\n    should be taken to prevent overflow.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrsum();\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    2.0\n    > s = accumulator( -5.0 )\n    -3.0\n    > s = accumulator()\n    -3.0\n\n    See Also\n    --------\n    incrcount, incrmean, incrmsum, incrprod, incrsummary\n","incrsumabs":"\nincrsumabs()\n    Returns an accumulator function which incrementally computes a sum of\n    absolute values.\n\n    If provided a value, the accumulator function returns an updated sum. If not\n    provided a value, the accumulator function returns the current sum.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    For long running accumulations or accumulations of large numbers, care\n    should be taken to prevent overflow.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrsumabs();\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    2.0\n    > s = accumulator( -5.0 )\n    7.0\n    > s = accumulator()\n    7.0\n\n    See Also\n    --------\n    incrmeanabs, incrmsumabs, incrsum\n","incrsumabs2":"\nincrsumabs2()\n    Returns an accumulator function which incrementally computes a sum of\n    squared absolute values.\n\n    If provided a value, the accumulator function returns an updated sum. If not\n    provided a value, the accumulator function returns the current sum.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    For long running accumulations or accumulations of large numbers, care\n    should be taken to prevent overflow.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrsumabs2();\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    4.0\n    > s = accumulator( -5.0 )\n    29.0\n    > s = accumulator()\n    29.0\n\n    See Also\n    --------\n    incrmeanabs2, incrmsumabs2, incrsumabs\n","incrsummary":"\nincrsummary()\n    Returns an accumulator function which incrementally computes a statistical\n    summary.\n\n    If provided a value, the accumulator function returns an updated summary. If\n    not provided a value, the accumulator function returns the current summary.\n\n    The returned summary is an object containing the following fields:\n\n    - count: count.\n    - max: maximum value.\n    - min: minimum value.\n    - range: range.\n    - midrange: mid-range.\n    - sum: sum.\n    - mean: arithmetic mean.\n    - variance: unbiased sample variance.\n    - stdev: corrected sample standard deviation.\n    - skewness: corrected sample skewness.\n    - kurtosis: corrected sample excess kurtosis.\n\n    For long running accumulations or accumulations of large numbers, care\n    should be taken to prevent overflow.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrsummary();\n    > var s = accumulator()\n    {}\n    > s = accumulator( 2.0 )\n    {...}\n    > s = accumulator( -5.0 )\n    {...}\n    > s = accumulator()\n    {...}\n\n    See Also\n    --------\n    incrcount, incrkurtosis, incrmax, incrmean, incrmidrange, incrmin, incrmsummary, incrrange, incrskewness, incrstdev, incrsum, incrvariance\n","incrsumprod":"\nincrsumprod()\n    Returns an accumulator function which incrementally computes a sum of\n    products.\n\n    If provided input values, the accumulator function returns an updated sum.\n    If not provided input values, the accumulator function returns the current\n    sum.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    For long running accumulations or accumulations of large numbers, care\n    should be taken to prevent overflow.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrsumprod();\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0, 3.0 )\n    6.0\n    > s = accumulator( -5.0, 2.0 )\n    -4.0\n    > s = accumulator()\n    -4.0\n\n    See Also\n    --------\n    incrmsumprod, incrprod, incrsum\n","incrvariance":"\nincrvariance( [mean] )\n    Returns an accumulator function which incrementally computes an unbiased\n    sample variance.\n\n    If provided a value, the accumulator function returns an updated unbiased\n    sample variance. If not provided a value, the accumulator function returns\n    the current unbiased sample variance.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    mean: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrvariance();\n    > var s2 = accumulator()\n    null\n    > s2 = accumulator( 2.0 )\n    0.0\n    > s2 = accumulator( -5.0 )\n    24.5\n    > s2 = accumulator()\n    24.5\n\n    See Also\n    --------\n    incrkurtosis, incrmean, incrmstdev, incrskewness, incrstdev, incrsummary\n","incrvmr":"\nincrvmr( [mean] )\n    Returns an accumulator function which incrementally computes a variance-to-\n    mean ratio (VMR).\n\n    If provided a value, the accumulator function returns an updated accumulated\n    value. If not provided a value, the accumulator function returns the current\n    accumulated value.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    mean: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrvmr();\n    > var D = accumulator()\n    null\n    > D = accumulator( 2.0 )\n    0.0\n    > D = accumulator( 1.0 )\n    ~0.33\n    > D = accumulator()\n    ~0.33\n\n    See Also\n    --------\n    incrmean, incrmvmr, incrvariance\n","incrwmean":"\nincrwmean()\n    Returns an accumulator function which incrementally computes a weighted\n    arithmetic mean.\n\n    If provided arguments, the accumulator function returns an updated weighted\n    mean. If not provided arguments, the accumulator function returns the\n    current weighted mean.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    The accumulator function accepts two arguments:\n\n    - x: value.\n    - w: weight.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrwmean();\n    > var mu = accumulator()\n    null\n    > mu = accumulator( 2.0, 1.0 )\n    2.0\n    > mu = accumulator( 2.0, 0.5 )\n    2.0\n    > mu = accumulator( 3.0, 1.5 )\n    2.5\n    > mu = accumulator()\n    2.5\n\n    See Also\n    --------\n    increwmean, incrmean, incrmmean\n","ind2sub":"\nind2sub( shape, idx[, options] )\n    Converts a linear index to an array of subscripts.\n\n    Parameters\n    ----------\n    shape: ArrayLike\n        Array shape.\n\n    idx: integer\n        Linear index.\n\n    options: Object (optional)\n        Options.\n\n    options.order: string (optional)\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran style). Default: 'row-major'.\n\n    options.mode: string (optional)\n        Specifies how to handle a linear index which exceeds array dimensions.\n        If equal to 'throw', the function throws an error when a linear index\n        exceeds array dimensions. If equal to 'normalize', the function\n        normalizes negative linear indices and throws an error when a linear\n        index exceeds array dimensions. If equal to 'wrap', the function wraps\n        around a linear index exceeding array dimensions using modulo\n        arithmetic. If equal to 'clamp', the function sets a linear index\n        exceeding array dimensions to either `0` (minimum linear index) or the\n        maximum linear index. Default: 'throw'.\n\n    Returns\n    -------\n    out: Array<integer>\n        Subscripts.\n\n    Examples\n    --------\n    > var d = [ 3, 3, 3 ];\n    > var s = ind2sub( d, 17 )\n    [ 1, 2, 2 ]\n\n\nind2sub.assign( shape, idx[, options], out )\n    Converts a linear index to an array of subscripts and assigns results to a\n    provided output array.\n\n    Parameters\n    ----------\n    shape: ArrayLike\n        Array shape.\n\n    idx: integer\n        Linear index.\n\n    options: Object (optional)\n        Options.\n\n    options.order: string (optional)\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran style). Default: 'row-major'.\n\n    options.mode: string (optional)\n        Specifies how to handle a linear index which exceeds array dimensions.\n        If equal to 'throw', the function throws an error when a linear index\n        exceeds array dimensions. If equal to 'normalize', the function\n        normalizes negative linear indices and throws an error when a linear\n        index exceeds array dimensions. If equal to 'wrap', the function wraps\n        around a linear index exceeding array dimensions using modulo\n        arithmetic. If equal to 'clamp', the function sets a linear index\n        exceeding array dimensions to either `0` (minimum linear index) or the\n        maximum linear index. Default: 'throw'.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Subscripts.\n\n    Examples\n    --------\n    > var d = [ 3, 3, 3 ];\n    > var out = [ 0, 0, 0 ];\n    > var s = ind2sub.assign( d, 17, out )\n    [ 1, 2, 2 ]\n    > var bool = ( s === out )\n    true\n\n    See Also\n    --------\n    array, ndarray, sub2ind\n","ind2sub.assign":"\nind2sub.assign( shape, idx[, options], out )\n    Converts a linear index to an array of subscripts and assigns results to a\n    provided output array.\n\n    Parameters\n    ----------\n    shape: ArrayLike\n        Array shape.\n\n    idx: integer\n        Linear index.\n\n    options: Object (optional)\n        Options.\n\n    options.order: string (optional)\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran style). Default: 'row-major'.\n\n    options.mode: string (optional)\n        Specifies how to handle a linear index which exceeds array dimensions.\n        If equal to 'throw', the function throws an error when a linear index\n        exceeds array dimensions. If equal to 'normalize', the function\n        normalizes negative linear indices and throws an error when a linear\n        index exceeds array dimensions. If equal to 'wrap', the function wraps\n        around a linear index exceeding array dimensions using modulo\n        arithmetic. If equal to 'clamp', the function sets a linear index\n        exceeding array dimensions to either `0` (minimum linear index) or the\n        maximum linear index. Default: 'throw'.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Subscripts.\n\n    Examples\n    --------\n    > var d = [ 3, 3, 3 ];\n    > var out = [ 0, 0, 0 ];\n    > var s = ind2sub.assign( d, 17, out )\n    [ 1, 2, 2 ]\n    > var bool = ( s === out )\n    true\n\n    See Also\n    --------\n    array, ndarray, sub2ind","indexOf":"\nindexOf( arr, searchElement[, fromIndex] )\n    Returns the first index at which a given element can be found.\n\n    Search is performed using *strict equality* comparison.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Array-like object.\n\n    searchElement: any\n        Element to find.\n\n    fromIndex: integer (optional)\n        Starting index (if negative, the start index is determined relative to\n        last element).\n\n    Returns\n    -------\n    out: integer\n        Index or -1.\n\n    Examples\n    --------\n    // Basic usage:\n    > var arr = [ 4, 3, 2, 1 ];\n    > var idx = indexOf( arr, 3 )\n    1\n    > arr = [ 4, 3, 2, 1 ];\n    > idx = indexOf( arr, 5 )\n    -1\n\n    // Using a `fromIndex`:\n    > arr = [ 1, 2, 3, 4, 5, 2, 6 ];\n    > idx = indexOf( arr, 2, 3 )\n    5\n\n    // `fromIndex` which exceeds `array` length:\n    > arr = [ 1, 2, 3, 4, 2, 5 ];\n    > idx = indexOf( arr, 2, 10 )\n    -1\n\n    // Negative `fromIndex`:\n    > arr = [ 1, 2, 3, 4, 5, 2, 6, 2 ];\n    > idx = indexOf( arr, 2, -4 )\n    5\n    > idx = indexOf( arr, 2, -1 )\n    7\n\n    // Negative `fromIndex` exceeding input `array` length:\n    > arr = [ 1, 2, 3, 4, 5, 2, 6 ];\n    > idx = indexOf( arr, 2, -10 )\n    1\n\n    // Array-like objects:\n    > var str = 'bebop';\n    > idx = indexOf( str, 'o' )\n    3\n\n","inherit":"\ninherit( ctor, superCtor )\n    Prototypical inheritance by replacing the prototype of one constructor with\n    the prototype of another constructor.\n\n    This function is not designed to work with ES2015/ES6 classes. For\n    ES2015/ES6 classes, use `class` with `extends`.\n\n    Parameters\n    ----------\n    ctor: Object|Function\n        Constructor which will inherit.\n\n    superCtor: Object|Function\n        Super (parent) constructor.\n\n    Returns\n    -------\n    out: Object|Function\n        Child constructor.\n\n    Examples\n    --------\n    // Create a parent constructor:\n    > function Foo() { return this; };\n    > Foo.prototype.beep = function beep() { return 'boop'; };\n\n    // Create a child constructor:\n    > function Bar() { Foo.call( this ); return this; };\n\n    // Setup inheritance:\n    > inherit( Bar, Foo );\n    > var bar = new Bar();\n    > var v = bar.beep()\n    'boop'\n\n","inheritedEnumerableProperties":"\ninheritedEnumerableProperties( value[, level] )\n    Returns an array of an object's inherited enumerable property names and\n    symbols.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    props: Array\n        List of an object's inherited enumerable properties.\n\n    Examples\n    --------\n    > var props = inheritedEnumerableProperties( {} )\n\n    See Also\n    --------\n    enumerableProperties, enumerablePropertiesIn, inheritedEnumerablePropertySymbols, inheritedKeys, inheritedNonEnumerableProperties, inheritedProperties\n","inheritedEnumerablePropertySymbols":"\ninheritedEnumerablePropertySymbols( value[, level] )\n    Returns an array of an object's inherited enumerable symbol properties.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's inherited enumerable symbol properties.\n\n    Examples\n    --------\n    > var symbols = inheritedEnumerablePropertySymbols( [] )\n\n    See Also\n    --------\n    enumerableProperties, enumerablePropertySymbols, inheritedKeys, nonEnumerablePropertySymbols, nonEnumerablePropertySymbolsIn, propertySymbols\n","inheritedKeys":"\ninheritedKeys( value[, level] )\n    Returns an array of an object's inherited enumerable property names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's inherited enumerable property names.\n\n    Examples\n    --------\n    > var keys = inheritedKeys( {} )\n\n    See Also\n    --------\n    objectKeys, keysIn, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedNonEnumerableProperties":"\ninheritedNonEnumerableProperties( value[, level] )\n    Returns an array of an object's inherited non-enumerable property names and\n    symbols.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    props: Array\n        List of an object's inherited non-enumerable properties.\n\n    Examples\n    --------\n    > var props = inheritedNonEnumerableProperties( {} )\n\n    See Also\n    --------\n    inheritedEnumerableProperties, inheritedNonEnumerablePropertyNames, inheritedNonEnumerablePropertySymbols, inheritedKeys, nonEnumerableProperties, nonEnumerablePropertiesIn, properties\n","inheritedNonEnumerablePropertyNames":"\ninheritedNonEnumerablePropertyNames( value[, level] )\n    Returns an array of an object's inherited non-enumerable property names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's inherited non-enumerable property names.\n\n    Examples\n    --------\n    > var keys = inheritedNonEnumerablePropertyNames( {} )\n\n    See Also\n    --------\n    inheritedNonEnumerableProperties, inheritedNonEnumerablePropertySymbols, objectKeys, nonEnumerablePropertyNames, nonEnumerablePropertyNamesIn, nonEnumerablePropertySymbols, propertyNames\n","inheritedNonEnumerablePropertySymbols":"\ninheritedNonEnumerablePropertySymbols( value[, level] )\n    Returns an array of an object's inherited non-enumerable symbol properties.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's inherited non-enumerable symbol properties.\n\n    Examples\n    --------\n    > var symbols = inheritedNonEnumerablePropertySymbols( [] )\n\n    See Also\n    --------\n    inheritedNonEnumerableProperties, inheritedNonEnumerablePropertyNames, nonEnumerableProperties, nonEnumerablePropertyNames, nonEnumerablePropertySymbols, nonEnumerablePropertySymbolsIn, propertySymbols\n","inheritedProperties":"\ninheritedProperties( value[, level] )\n    Returns an array of an object's inherited property names and symbols.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's inherited property names and symbols.\n\n    Examples\n    --------\n    > var symbols = inheritedProperties( [] )\n\n    See Also\n    --------\n    properties, propertiesIn, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedPropertyDescriptor":"\ninheritedPropertyDescriptor( value, property[, level] )\n    Returns a property descriptor for an object's inherited property.\n\n    If provided `null` or `undefined` or provided a non-existent property, the\n    function returns `null`.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    property: string|symbol\n        Property name.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    desc: Object|null\n        Property descriptor.\n\n    Examples\n    --------\n    > var desc = inheritedPropertyDescriptor( {}, 'toString' )\n    {...}\n\n    See Also\n    --------\n    propertyDescriptor, propertyDescriptorIn, inheritedKeys, inheritedPropertyDescriptors, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedPropertyDescriptors":"\ninheritedPropertyDescriptors( value[, level] )\n    Returns an object's inherited property descriptors.\n\n    If provided `null` or `undefined`, the function returns an empty object.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    desc: Object\n        An object's inherited property descriptors.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var desc = inheritedPropertyDescriptors( obj )\n    { 'foo': {...}, ... }\n\n    See Also\n    --------\n    propertyDescriptors, propertyDescriptorsIn, inheritedKeys, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedPropertyNames":"\ninheritedPropertyNames( value[, level] )\n    Returns an array of an object's inherited enumerable and non-enumerable\n    property names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's inherited enumerable and non-enumerable property\n        names.\n\n    Examples\n    --------\n    > var keys = inheritedPropertyNames( [] )\n\n    See Also\n    --------\n    inheritedKeys, inheritedPropertyDescriptors, inheritedPropertySymbols, propertyNames, propertyNamesIn\n","inheritedPropertySymbols":"\ninheritedPropertySymbols( value[, level] )\n    Returns an array of an object's inherited symbol properties.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's inherited symbol properties.\n\n    Examples\n    --------\n    > var symbols = inheritedPropertySymbols( [] )\n\n    See Also\n    --------\n    inheritedKeys, inheritedPropertyDescriptors, inheritedPropertyNames, propertySymbols, propertySymbolsIn\n","inheritedWritableProperties":"\ninheritedWritableProperties( value[, level] )\n    Returns an array of an object's inherited writable property names and\n    symbols.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    props: Array\n        List of an object's inherited writable properties.\n\n    Examples\n    --------\n    > var props = inheritedWritableProperties( {} )\n\n    See Also\n    --------\n    inheritedWritablePropertyNames, inheritedWritablePropertySymbols, writableProperties, writablePropertiesIn, properties\n","inheritedWritablePropertyNames":"\ninheritedWritablePropertyNames( value[, level] )\n    Returns an array of an object's inherited writable property names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's inherited writable property names.\n\n    Examples\n    --------\n    > var keys = inheritedWritablePropertyNames( {} )\n\n    See Also\n    --------\n    inheritedWritablePropertySymbols, writablePropertyNames, writablePropertyNamesIn, properties\n","inheritedWritablePropertySymbols":"\ninheritedWritablePropertySymbols( value[, level] )\n    Returns an array of an object's inherited writable symbol properties.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's inherited writable symbol properties.\n\n    Examples\n    --------\n    > var symbols = inheritedWritablePropertySymbols( [] )\n\n    See Also\n    --------\n    inheritedWritablePropertyNames, writablePropertySymbols, writablePropertySymbolsIn, properties\n","inmap":"\ninmap( collection, fcn[, thisArg] )\n    Invokes a function for each element in a collection and updates the\n    collection in-place.\n\n    When invoked, the input function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection. If provided an object, the object must be array-like\n        (excluding strings and functions).\n\n    fcn: Function\n        Function to invoke for each element in the input collection. The\n        function's return value is used to update the collection in-place.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function foo( v, i ) { return v * i; };\n    > var arr = [ 1.0, 2.0, 3.0 ];\n    > var out = inmap( arr, foo )\n    [ 0.0, 2.0, 6.0 ]\n    > var bool = ( out === arr )\n    true\n\n    See Also\n    --------\n    forEach, inmapRight, map\n","inmapAsync":"\ninmapAsync( collection, [options,] fcn, done )\n    Invokes a function once for each element in a collection and updates a\n    collection in-place.\n\n    When invoked, `fcn` is provided a maximum of four arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If `fcn`\n    accepts two arguments, `fcn` is provided:\n\n    - value\n    - next\n\n    If `fcn` accepts three arguments, `fcn` is provided:\n\n    - value\n    - index\n    - next\n\n    For every other `fcn` signature, `fcn` is provided all four arguments.\n\n    The `next` callback accepts two arguments:\n\n    - error: error argument.\n    - result: value used to update the collection.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling. Note, however, that the function\n    may have mutated an input collection during prior invocations, resulting in\n    a partially mutated collection.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function fcn( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, value*index );\n    ...     }\n    ... };\n    > function done( error, collection ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( collection === arr );\n    ...     console.log( collection );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > inmapAsync( arr, fcn, done )\n    1000\n    2500\n    3000\n    true\n    [ 0, 2500, 2000 ]\n\n    // Limit number of concurrent invocations:\n    > function fcn( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, value*index );\n    ...     }\n    ... };\n    > function done( error, collection ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( collection === arr );\n    ...     console.log( collection );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 3000, 2500, 1000 ];\n    > inmapAsync( arr, opts, fcn, done )\n    2500\n    3000\n    1000\n    true\n    [ 0, 2500, 2000 ]\n\n    // Process sequentially:\n    > function fcn( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, value*index );\n    ...     }\n    ... };\n    > function done( error, collection ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( collection === arr );\n    ...     console.log( collection );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 3000, 2500, 1000 ];\n    > inmapAsync( arr, opts, fcn, done )\n    3000\n    2500\n    1000\n    true\n    [ 0, 2500, 2000 ]\n\n\ninmapAsync.factory( [options,] fcn )\n    Returns a function which invokes a function once for each element in a\n    collection and updates a collection in-place.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function fcn( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, value*index );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = inmapAsync.factory( opts, fcn );\n    > function done( error, collection ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( collection === arr );\n    ...     console.log( collection );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    [ 0, 2500, 2000 ]\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n    [ 0, 1500, 2000 ]\n\n    See Also\n    --------\n    forEachAsync, inmapRightAsync, inmap\n","inmapAsync.factory":"\ninmapAsync.factory( [options,] fcn )\n    Returns a function which invokes a function once for each element in a\n    collection and updates a collection in-place.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function fcn( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, value*index );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = inmapAsync.factory( opts, fcn );\n    > function done( error, collection ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( collection === arr );\n    ...     console.log( collection );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    [ 0, 2500, 2000 ]\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n    [ 0, 1500, 2000 ]\n\n    See Also\n    --------\n    forEachAsync, inmapRightAsync, inmap","inmapRight":"\ninmapRight( collection, fcn[, thisArg] )\n    Invokes a function for each element in a collection and updates the\n    collection in-place, iterating from right to left.\n\n    When invoked, the input function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection. If provided an object, the object must be array-like\n        (excluding strings and functions).\n\n    fcn: Function\n        Function to invoke for each element in the input collection. The\n        function's return value is used to update the collection in-place.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function foo( v, i ) { console.log( '%s: %d', i, v ); return v * i; };\n    > var arr = [ 1.0, 2.0, 3.0 ];\n    > var out = inmapRight( arr, foo )\n    2: 3.0\n    1: 2.0\n    0: 1.0\n    [ 0.0, 2.0, 6.0 ]\n    > var bool = ( out === arr )\n    true\n\n    See Also\n    --------\n    forEachRight, inmap, mapRight\n","inmapRightAsync":"\ninmapRightAsync( collection, [options,] fcn, done )\n    Invokes a function once for each element in a collection and updates a\n    collection in-place, iterating from right to left.\n\n    When invoked, `fcn` is provided a maximum of four arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If `fcn`\n    accepts two arguments, `fcn` is provided:\n\n    - value\n    - next\n\n    If `fcn` accepts three arguments, `fcn` is provided:\n\n    - value\n    - index\n    - next\n\n    For every other `fcn` signature, `fcn` is provided all four arguments.\n\n    The `next` callback accepts two arguments:\n\n    - error: error argument.\n    - result: value used to update the collection.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling. Note, however, that the function\n    may have mutated an input collection during prior invocations, resulting in\n    a partially mutated collection.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function fcn( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, value*index );\n    ...     }\n    ... };\n    > function done( error, collection ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( collection === arr );\n    ...     console.log( collection );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > inmapRightAsync( arr, fcn, done )\n    1000\n    2500\n    3000\n    true\n    [ 0, 2500, 6000 ]\n\n    // Limit number of concurrent invocations:\n    > function fcn( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, value*index );\n    ...     }\n    ... };\n    > function done( error, collection ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( collection === arr );\n    ...     console.log( collection );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 1000, 2500, 3000 ];\n    > inmapRightAsync( arr, opts, fcn, done )\n    2500\n    3000\n    1000\n    true\n    [ 0, 2500, 6000 ]\n\n    // Process sequentially:\n    > function fcn( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, value*index );\n    ...     }\n    ... };\n    > function done( error, collection ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( collection === arr );\n    ...     console.log( collection );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 1000, 2500, 3000 ];\n    > inmapRightAsync( arr, opts, fcn, done )\n    3000\n    2500\n    1000\n    true\n    [ 0, 2500, 6000 ]\n\n\ninmapRightAsync.factory( [options,] fcn )\n    Returns a function which invokes a function once for each element in a\n    collection and updates a collection in-place, iterating from right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function fcn( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, value*index );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = inmapRightAsync.factory( opts, fcn );\n    > function done( error, collection ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( collection === arr );\n    ...     console.log( collection );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    [ 0, 2500, 6000 ]\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n    [ 0, 1500, 4000 ]\n\n    See Also\n    --------\n    forEachRightAsync, inmapAsync, inmapRight\n","inmapRightAsync.factory":"\ninmapRightAsync.factory( [options,] fcn )\n    Returns a function which invokes a function once for each element in a\n    collection and updates a collection in-place, iterating from right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function fcn( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, value*index );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = inmapRightAsync.factory( opts, fcn );\n    > function done( error, collection ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( collection === arr );\n    ...     console.log( collection );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    [ 0, 2500, 6000 ]\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n    [ 0, 1500, 4000 ]\n\n    See Also\n    --------\n    forEachRightAsync, inmapAsync, inmapRight","inspectSinkStream":"\ninspectSinkStream( [options,] clbk )\n    Returns a writable stream for inspecting stream data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to encode strings as `Buffer` objects before writing\n        data to a returned stream. Default: true.\n\n    options.defaultEncoding: string (optional)\n        Default encoding when not explicitly specified when writing data.\n        Default: 'utf8'.\n\n    clbk: Function\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: WritableStream\n        Writable stream.\n\n    Examples\n    --------\n    > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n    > var s = inspectSinkStream( clbk );\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();\n\n\ninspectSinkStream.factory( [options] )\n    Returns a function for creating writable streams for inspecting stream data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to encode strings as `Buffer` objects before writing\n        data to a returned stream. Default: true.\n\n    options.defaultEncoding: string (optional)\n        Default encoding when not explicitly specified when writing data.\n        Default: 'utf8'.\n\n    Returns\n    -------\n    createStream( clbk ): Function\n        Function for creating writable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = inspectSinkStream.factory( opts );\n    > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n    > var s = createStream( clbk );\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();\n\n\ninspectSinkStream.objectMode( [options,] clbk )\n    Returns an \"objectMode\" writable stream for inspecting stream data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to encode strings as `Buffer` objects before writing\n        data to a returned stream. Default: true.\n\n    options.defaultEncoding: string (optional)\n        Default encoding when not explicitly specified when writing data.\n        Default: 'utf8'.\n\n    clbk: Function\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: WritableStream\n        Writable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n    > var s = inspectSinkStream.objectMode( clbk );\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();\n\n    See Also\n    --------\n    debugSinkStream, inspectStream\n","inspectSinkStream.factory":"\ninspectSinkStream.factory( [options] )\n    Returns a function for creating writable streams for inspecting stream data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to encode strings as `Buffer` objects before writing\n        data to a returned stream. Default: true.\n\n    options.defaultEncoding: string (optional)\n        Default encoding when not explicitly specified when writing data.\n        Default: 'utf8'.\n\n    Returns\n    -------\n    createStream( clbk ): Function\n        Function for creating writable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = inspectSinkStream.factory( opts );\n    > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n    > var s = createStream( clbk );\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();","inspectSinkStream.objectMode":"\ninspectSinkStream.objectMode( [options,] clbk )\n    Returns an \"objectMode\" writable stream for inspecting stream data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to encode strings as `Buffer` objects before writing\n        data to a returned stream. Default: true.\n\n    options.defaultEncoding: string (optional)\n        Default encoding when not explicitly specified when writing data.\n        Default: 'utf8'.\n\n    clbk: Function\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: WritableStream\n        Writable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n    > var s = inspectSinkStream.objectMode( clbk );\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();\n\n    See Also\n    --------\n    debugSinkStream, inspectStream","inspectStream":"\ninspectStream( [options,] clbk )\n    Returns a transform stream for inspecting stream data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    clbk: Function\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream.\n\n    Examples\n    --------\n    > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n    > var s = inspectStream( clbk );\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();\n\n\ninspectStream.factory( [options] )\n    Returns a function for creating transform streams for inspecting stream\n    data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    createStream( clbk ): Function\n        Function for creating transform streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = inspectStream.factory( opts );\n    > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n    > var s = createStream( clbk );\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();\n\n\ninspectStream.objectMode( [options,] clbk )\n    Returns an \"objectMode\" transform stream for inspecting stream data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    clbk: Function\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n    > var s = inspectStream.objectMode( clbk );\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();\n\n    See Also\n    --------\n    debugStream\n","inspectStream.factory":"\ninspectStream.factory( [options] )\n    Returns a function for creating transform streams for inspecting stream\n    data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    createStream( clbk ): Function\n        Function for creating transform streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = inspectStream.factory( opts );\n    > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n    > var s = createStream( clbk );\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();","inspectStream.objectMode":"\ninspectStream.objectMode( [options,] clbk )\n    Returns an \"objectMode\" transform stream for inspecting stream data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    clbk: Function\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n    > var s = inspectStream.objectMode( clbk );\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();\n\n    See Also\n    --------\n    debugStream","instanceOf":"\ninstanceOf( value, constructor )\n    Tests whether a value has in its prototype chain a specified constructor as\n    a prototype property.\n\n    While the prototype of an `object` created using object literal notion is\n    `undefined`, the function returns `true` when provided an `object` literal\n    and the `Object` constructor. This maintains consistent behavior with the\n    `instanceof` operator.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    constructor: Function\n        Constructor.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is an instance of a provided constructor.\n\n    Examples\n    --------\n    > var bool = instanceOf( [], Array )\n    true\n    > bool = instanceOf( {}, Object )\n    true\n    > bool = instanceOf( null, Object )\n    false\n\n    See Also\n    --------\n    isPrototypeOf, constructorName, inherit, typeOf\n","INT8_MAX":"\nINT8_MAX\n    Maximum signed 8-bit integer.\n\n    The maximum signed 8-bit integer is given by `2^7 - 1`.\n\n    Examples\n    --------\n    > INT8_MAX\n    127\n\n    See Also\n    --------\n    INT8_MIN\n","INT8_MIN":"\nINT8_MIN\n    Minimum signed 8-bit integer.\n\n    The minimum signed 8-bit integer is given by `-(2^7)`.\n\n    Examples\n    --------\n    > INT8_MIN\n    -128\n\n    See Also\n    --------\n    INT8_MAX\n","INT8_NUM_BYTES":"\nINT8_NUM_BYTES\n    Size (in bytes) of an 8-bit signed integer.\n\n    Examples\n    --------\n    > INT8_NUM_BYTES\n    1\n\n    See Also\n    --------\n    INT16_NUM_BYTES, INT32_NUM_BYTES, UINT8_NUM_BYTES\n","Int8Array":"\nInt8Array()\n    A typed array constructor which returns a typed array representing an array\n    of twos-complement 8-bit signed integers in the platform byte order.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Int8Array()\n    <Int8Array>\n\n\nInt8Array( length )\n    Returns a typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( 5 )\n    <Int8Array>[ 0, 0, 0, 0, 0 ]\n\n\nInt8Array( typedarray )\n    Creates a typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n    > var arr2 = new Int8Array( arr1 )\n    <Int8Array>[ 5, 5, 5 ]\n\n\nInt8Array( obj )\n    Creates a typed array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a typed array.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 5.0, 5.0, 5.0 ];\n    > var arr2 = new Int8Array( arr1 )\n    <Int8Array>[ 5, 5, 5 ]\n\n\nInt8Array( buffer[, byteOffset[, length]] )\n    Returns a typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 4 );\n    > var arr = new Int8Array( buf, 0, 4 )\n    <Int8Array>[ 0, 0, 0, 0 ]\n\n\nInt8Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Int8Array.from( [ 1, 2 ], mapFcn )\n    <Int8Array>[ 2, 4 ]\n\n\nInt8Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Int8Array.of( 1, 2 )\n    <Int8Array>[ 1, 2 ]\n\n\nInt8Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Int8Array.BYTES_PER_ELEMENT\n    1\n\n\nInt8Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Int8Array.name\n    'Int8Array'\n\n\nInt8Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>\n\n\nInt8Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( 5 );\n    > arr.byteLength\n    5\n\n\nInt8Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Int8Array( 5 );\n    > arr.byteOffset\n    0\n\n\nInt8Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Int8Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    1\n\n\nInt8Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Int8Array( 5 );\n    > arr.length\n    5\n\n\nInt8Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Int8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2\n\n\nInt8Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true\n\n\nInt8Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false\n\n\nInt8Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Int8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3\n\n\nInt8Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2\n\n\nInt8Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3\n\n\nInt8Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2\n\n\nInt8Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '\n\n\nInt8Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true\n\n\nInt8Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2\n\n\nInt8Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'\n\n\nInt8Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true\n\n\nInt8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3\n\n\nInt8Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Int8Array>[ 2, 4, 6 ]\n\n\nInt8Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14\n\n\nInt8Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14\n\n\nInt8Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Int8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] )\n    <Int8Array>\n    > arr.reverse()\n    <Int8Array>[ 3, 2, 1 ]\n\n\nInt8Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4\n\n\nInt8Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3\n\n\nInt8Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true\n\n\nInt8Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Int8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Int8Array>[ 0, 1, 1, 2, 2 ]\n\n\nInt8Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int8Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Int8Array>[ 3, 4, 5 ]\n\n\nInt8Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'\n\n\nInt8Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'\n\n\nInt8Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Int8Array.from":"\nInt8Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Int8Array.from( [ 1, 2 ], mapFcn )\n    <Int8Array>[ 2, 4 ]","Int8Array.of":"\nInt8Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Int8Array.of( 1, 2 )\n    <Int8Array>[ 1, 2 ]","Int8Array.BYTES_PER_ELEMENT":"\nInt8Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Int8Array.BYTES_PER_ELEMENT\n    1","Int8Array.name":"\nInt8Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Int8Array.name\n    'Int8Array'","Int8Array.prototype.buffer":"\nInt8Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>","Int8Array.prototype.byteLength":"\nInt8Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( 5 );\n    > arr.byteLength\n    5","Int8Array.prototype.byteOffset":"\nInt8Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Int8Array( 5 );\n    > arr.byteOffset\n    0","Int8Array.prototype.BYTES_PER_ELEMENT":"\nInt8Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Int8Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    1","Int8Array.prototype.length":"\nInt8Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Int8Array( 5 );\n    > arr.length\n    5","Int8Array.prototype.copyWithin":"\nInt8Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Int8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2","Int8Array.prototype.entries":"\nInt8Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true","Int8Array.prototype.every":"\nInt8Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false","Int8Array.prototype.fill":"\nInt8Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Int8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3","Int8Array.prototype.filter":"\nInt8Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2","Int8Array.prototype.find":"\nInt8Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3","Int8Array.prototype.findIndex":"\nInt8Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2","Int8Array.prototype.forEach":"\nInt8Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '","Int8Array.prototype.includes":"\nInt8Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true","Int8Array.prototype.indexOf":"\nInt8Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2","Int8Array.prototype.join":"\nInt8Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'","Int8Array.prototype.keys":"\nInt8Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true","Int8Array.prototype.lastIndexOf":"\nInt8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3","Int8Array.prototype.map":"\nInt8Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Int8Array>[ 2, 4, 6 ]","Int8Array.prototype.reduce":"\nInt8Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14","Int8Array.prototype.reduceRight":"\nInt8Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14","Int8Array.prototype.reverse":"\nInt8Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Int8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] )\n    <Int8Array>\n    > arr.reverse()\n    <Int8Array>[ 3, 2, 1 ]","Int8Array.prototype.set":"\nInt8Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4","Int8Array.prototype.slice":"\nInt8Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3","Int8Array.prototype.some":"\nInt8Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true","Int8Array.prototype.sort":"\nInt8Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Int8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Int8Array>[ 0, 1, 1, 2, 2 ]","Int8Array.prototype.subarray":"\nInt8Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int8Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Int8Array>[ 3, 4, 5 ]","Int8Array.prototype.toLocaleString":"\nInt8Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'","Int8Array.prototype.toString":"\nInt8Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'","Int8Array.prototype.values":"\nInt8Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","INT16_MAX":"\nINT16_MAX\n    Maximum signed 16-bit integer.\n\n    The maximum signed 16-bit integer is given by `2^15 - 1`.\n\n    Examples\n    --------\n    > INT16_MAX\n    32767\n\n    See Also\n    --------\n    INT16_MIN\n","INT16_MIN":"\nINT16_MIN\n    Minimum signed 16-bit integer.\n\n    The minimum signed 16-bit integer is given by `-(2^15)`.\n\n    Examples\n    --------\n    > INT16_MIN\n    -32768\n\n    See Also\n    --------\n    INT16_MAX\n","INT16_NUM_BYTES":"\nINT16_NUM_BYTES\n    Size (in bytes) of a 16-bit signed integer.\n\n    Examples\n    --------\n    > INT16_NUM_BYTES\n    2\n\n    See Also\n    --------\n    INT32_NUM_BYTES, INT8_NUM_BYTES, UINT16_NUM_BYTES\n","Int16Array":"\nInt16Array()\n    A typed array constructor which returns a typed array representing an array\n    of twos-complement 16-bit signed integers in the platform byte order.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Int16Array()\n    <Int16Array>\n\n\nInt16Array( length )\n    Returns a typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( 5 )\n    <Int16Array>[ 0, 0, 0, 0, 0 ]\n\n\nInt16Array( typedarray )\n    Creates a typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n    > var arr2 = new Int16Array( arr1 )\n    <Int16Array>[ 5, 5, 5 ]\n\n\nInt16Array( obj )\n    Creates a typed array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a typed array.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 5.0, 5.0, 5.0 ];\n    > var arr2 = new Int16Array( arr1 )\n    <Int16Array>[ 5, 5, 5 ]\n\n\nInt16Array( buffer[, byteOffset[, length]] )\n    Returns a typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 8 );\n    > var arr = new Int16Array( buf, 0, 4 )\n    <Int16Array>[ 0, 0, 0, 0 ]\n\n\nInt16Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Int16Array.from( [ 1, 2 ], mapFcn )\n    <Int16Array>[ 2, 4 ]\n\n\nInt16Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Int16Array.of( 1, 2 )\n    <Int16Array>[ 1, 2 ]\n\n\nInt16Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Int16Array.BYTES_PER_ELEMENT\n    2\n\n\nInt16Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Int16Array.name\n    'Int16Array'\n\n\nInt16Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>\n\n\nInt16Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( 5 );\n    > arr.byteLength\n    10\n\n\nInt16Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Int16Array( 5 );\n    > arr.byteOffset\n    0\n\n\nInt16Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Int16Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    2\n\n\nInt16Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Int16Array( 5 );\n    > arr.length\n    5\n\n\nInt16Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Int16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2\n\n\nInt16Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true\n\n\nInt16Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false\n\n\nInt16Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Int16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3\n\n\nInt16Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2\n\n\nInt16Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3\n\n\nInt16Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2\n\n\nInt16Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '\n\n\nInt16Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true\n\n\nInt16Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2\n\n\nInt16Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'\n\n\nInt16Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true\n\n\nInt16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3\n\n\nInt16Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Int16Array>[ 2, 4, 6 ]\n\n\nInt16Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14\n\n\nInt16Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14\n\n\nInt16Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Int16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] )\n    <Int16Array>\n    > arr.reverse()\n    <Int16Array>[ 3, 2, 1 ]\n\n\nInt16Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4\n\n\nInt16Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3\n\n\nInt16Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true\n\n\nInt16Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Int16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Int16Array>[ 0, 1, 1, 2, 2 ]\n\n\nInt16Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int16Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Int16Array>[ 3, 4, 5 ]\n\n\nInt16Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'\n\n\nInt16Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'\n\n\nInt16Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Int16Array.from":"\nInt16Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Int16Array.from( [ 1, 2 ], mapFcn )\n    <Int16Array>[ 2, 4 ]","Int16Array.of":"\nInt16Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Int16Array.of( 1, 2 )\n    <Int16Array>[ 1, 2 ]","Int16Array.BYTES_PER_ELEMENT":"\nInt16Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Int16Array.BYTES_PER_ELEMENT\n    2","Int16Array.name":"\nInt16Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Int16Array.name\n    'Int16Array'","Int16Array.prototype.buffer":"\nInt16Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>","Int16Array.prototype.byteLength":"\nInt16Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( 5 );\n    > arr.byteLength\n    10","Int16Array.prototype.byteOffset":"\nInt16Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Int16Array( 5 );\n    > arr.byteOffset\n    0","Int16Array.prototype.BYTES_PER_ELEMENT":"\nInt16Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Int16Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    2","Int16Array.prototype.length":"\nInt16Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Int16Array( 5 );\n    > arr.length\n    5","Int16Array.prototype.copyWithin":"\nInt16Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Int16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2","Int16Array.prototype.entries":"\nInt16Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true","Int16Array.prototype.every":"\nInt16Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false","Int16Array.prototype.fill":"\nInt16Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Int16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3","Int16Array.prototype.filter":"\nInt16Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2","Int16Array.prototype.find":"\nInt16Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3","Int16Array.prototype.findIndex":"\nInt16Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2","Int16Array.prototype.forEach":"\nInt16Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '","Int16Array.prototype.includes":"\nInt16Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true","Int16Array.prototype.indexOf":"\nInt16Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2","Int16Array.prototype.join":"\nInt16Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'","Int16Array.prototype.keys":"\nInt16Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true","Int16Array.prototype.lastIndexOf":"\nInt16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3","Int16Array.prototype.map":"\nInt16Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Int16Array>[ 2, 4, 6 ]","Int16Array.prototype.reduce":"\nInt16Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14","Int16Array.prototype.reduceRight":"\nInt16Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14","Int16Array.prototype.reverse":"\nInt16Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Int16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] )\n    <Int16Array>\n    > arr.reverse()\n    <Int16Array>[ 3, 2, 1 ]","Int16Array.prototype.set":"\nInt16Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4","Int16Array.prototype.slice":"\nInt16Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3","Int16Array.prototype.some":"\nInt16Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true","Int16Array.prototype.sort":"\nInt16Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Int16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Int16Array>[ 0, 1, 1, 2, 2 ]","Int16Array.prototype.subarray":"\nInt16Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int16Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Int16Array>[ 3, 4, 5 ]","Int16Array.prototype.toLocaleString":"\nInt16Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'","Int16Array.prototype.toString":"\nInt16Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'","Int16Array.prototype.values":"\nInt16Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","INT32_MAX":"\nINT32_MAX\n    Maximum signed 32-bit integer.\n\n    The maximum signed 32-bit integer is given by `2^31 - 1`.\n\n    Examples\n    --------\n    > INT32_MAX\n    2147483647\n\n    See Also\n    --------\n    INT32_MIN\n","INT32_MIN":"\nINT32_MIN\n    Minimum signed 32-bit integer.\n\n    The minimum signed 32-bit integer is given by `-(2^31)`.\n\n    Examples\n    --------\n    > INT32_MIN\n    -2147483648\n\n    See Also\n    --------\n    INT32_MAX\n","INT32_NUM_BYTES":"\nINT32_NUM_BYTES\n    Size (in bytes) of a 32-bit signed integer.\n\n    Examples\n    --------\n    > INT32_NUM_BYTES\n    4\n\n    See Also\n    --------\n    INT16_NUM_BYTES, INT8_NUM_BYTES, UINT32_NUM_BYTES\n","Int32Array":"\nInt32Array()\n    A typed array constructor which returns a typed array representing an array\n    of twos-complement 32-bit signed integers in the platform byte order.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Int32Array()\n    <Int32Array>\n\n\nInt32Array( length )\n    Returns a typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( 5 )\n    <Int32Array>[ 0, 0, 0, 0, 0 ]\n\n\nInt32Array( typedarray )\n    Creates a typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int16Array( [ 5, 5, 5 ] );\n    > var arr2 = new Int32Array( arr1 )\n    <Int32Array>[ 5, 5, 5 ]\n\n\nInt32Array( obj )\n    Creates a typed array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a typed array.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 5.0, 5.0, 5.0 ];\n    > var arr2 = new Int32Array( arr1 )\n    <Int32Array>[ 5, 5, 5 ]\n\n\nInt32Array( buffer[, byteOffset[, length]] )\n    Returns a typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 16 );\n    > var arr = new Int32Array( buf, 0, 4 )\n    <Int32Array>[ 0, 0, 0, 0 ]\n\n\nInt32Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Int32Array.from( [ 1, 2 ], mapFcn )\n    <Int32Array>[ 2, 4 ]\n\n\nInt32Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Int32Array.of( 1, 2 )\n    <Int32Array>[ 1, 2 ]\n\n\nInt32Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Int32Array.BYTES_PER_ELEMENT\n    4\n\n\nInt32Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Int32Array.name\n    'Int32Array'\n\n\nInt32Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>\n\n\nInt32Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( 5 );\n    > arr.byteLength\n    20\n\n\nInt32Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Int32Array( 5 );\n    > arr.byteOffset\n    0\n\n\nInt32Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Int32Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    4\n\n\nInt32Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Int32Array( 5 );\n    > arr.length\n    5\n\n\nInt32Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Int32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2\n\n\nInt32Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true\n\n\nInt32Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false\n\n\nInt32Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Int32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3\n\n\nInt32Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2\n\n\nInt32Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3\n\n\nInt32Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2\n\n\nInt32Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '\n\n\nInt32Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true\n\n\nInt32Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2\n\n\nInt32Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'\n\n\nInt32Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true\n\n\nInt32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3\n\n\nInt32Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Int32Array>[ 2, 4, 6 ]\n\n\nInt32Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14\n\n\nInt32Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14\n\n\nInt32Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Int32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] )\n    <Int32Array>\n    > arr.reverse()\n    <Int32Array>[ 3, 2, 1 ]\n\n\nInt32Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4\n\n\nInt32Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3\n\n\nInt32Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true\n\n\nInt32Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Int32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Int32Array>[ 0, 1, 1, 2, 2 ]\n\n\nInt32Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int32Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Int32Array>[ 3, 4, 5 ]\n\n\nInt32Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'\n\n\nInt32Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'\n\n\nInt32Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Int32Array.from":"\nInt32Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Int32Array.from( [ 1, 2 ], mapFcn )\n    <Int32Array>[ 2, 4 ]","Int32Array.of":"\nInt32Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Int32Array.of( 1, 2 )\n    <Int32Array>[ 1, 2 ]","Int32Array.BYTES_PER_ELEMENT":"\nInt32Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Int32Array.BYTES_PER_ELEMENT\n    4","Int32Array.name":"\nInt32Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Int32Array.name\n    'Int32Array'","Int32Array.prototype.buffer":"\nInt32Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>","Int32Array.prototype.byteLength":"\nInt32Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( 5 );\n    > arr.byteLength\n    20","Int32Array.prototype.byteOffset":"\nInt32Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Int32Array( 5 );\n    > arr.byteOffset\n    0","Int32Array.prototype.BYTES_PER_ELEMENT":"\nInt32Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Int32Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    4","Int32Array.prototype.length":"\nInt32Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Int32Array( 5 );\n    > arr.length\n    5","Int32Array.prototype.copyWithin":"\nInt32Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Int32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2","Int32Array.prototype.entries":"\nInt32Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true","Int32Array.prototype.every":"\nInt32Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false","Int32Array.prototype.fill":"\nInt32Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Int32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3","Int32Array.prototype.filter":"\nInt32Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2","Int32Array.prototype.find":"\nInt32Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3","Int32Array.prototype.findIndex":"\nInt32Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2","Int32Array.prototype.forEach":"\nInt32Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '","Int32Array.prototype.includes":"\nInt32Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true","Int32Array.prototype.indexOf":"\nInt32Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2","Int32Array.prototype.join":"\nInt32Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'","Int32Array.prototype.keys":"\nInt32Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true","Int32Array.prototype.lastIndexOf":"\nInt32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3","Int32Array.prototype.map":"\nInt32Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Int32Array>[ 2, 4, 6 ]","Int32Array.prototype.reduce":"\nInt32Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14","Int32Array.prototype.reduceRight":"\nInt32Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14","Int32Array.prototype.reverse":"\nInt32Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Int32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] )\n    <Int32Array>\n    > arr.reverse()\n    <Int32Array>[ 3, 2, 1 ]","Int32Array.prototype.set":"\nInt32Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4","Int32Array.prototype.slice":"\nInt32Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3","Int32Array.prototype.some":"\nInt32Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true","Int32Array.prototype.sort":"\nInt32Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Int32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Int32Array>[ 0, 1, 1, 2, 2 ]","Int32Array.prototype.subarray":"\nInt32Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int32Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Int32Array>[ 3, 4, 5 ]","Int32Array.prototype.toLocaleString":"\nInt32Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'","Int32Array.prototype.toString":"\nInt32Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'","Int32Array.prototype.values":"\nInt32Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","IS_BIG_ENDIAN":"\nIS_BIG_ENDIAN\n    Boolean indicating if the environment is big endian.\n\n    Examples\n    --------\n    > IS_BIG_ENDIAN\n    <boolean>\n\n    See Also\n    --------\n    IS_LITTLE_ENDIAN\n","IS_BROWSER":"\nIS_BROWSER\n    Boolean indicating if the runtime is a web browser.\n\n    Examples\n    --------\n    > IS_BROWSER\n    <boolean>\n\n","IS_DARWIN":"\nIS_DARWIN\n    Boolean indicating if the current process is running on Darwin.\n\n    Examples\n    --------\n    > IS_DARWIN\n    <boolean>\n\n","IS_DOCKER":"\nIS_DOCKER\n    Boolean indicating if the process is running in a Docker container.\n\n    Examples\n    --------\n    > IS_DOCKER\n    <boolean>\n\n","IS_ELECTRON":"\nIS_ELECTRON\n    Boolean indicating if the runtime is Electron.\n\n    Examples\n    --------\n    > IS_ELECTRON\n    <boolean>\n\n    See Also\n    --------\n    IS_ELECTRON_MAIN, IS_ELECTRON_RENDERER\n","IS_ELECTRON_MAIN":"\nIS_ELECTRON_MAIN\n    Boolean indicating if the runtime is the main Electron process.\n\n    Examples\n    --------\n    > IS_ELECTRON_MAIN\n    <boolean>\n\n    See Also\n    --------\n    IS_ELECTRON, IS_ELECTRON_RENDERER\n","IS_ELECTRON_RENDERER":"\nIS_ELECTRON_RENDERER\n    Boolean indicating if the runtime is the Electron renderer process.\n\n    Examples\n    --------\n    > IS_ELECTRON_RENDERER\n    <boolean>\n\n    See Also\n    --------\n    IS_ELECTRON, IS_ELECTRON_MAIN\n","IS_LITTLE_ENDIAN":"\nIS_LITTLE_ENDIAN\n    Boolean indicating if the environment is little endian.\n\n    Examples\n    --------\n    > IS_LITTLE_ENDIAN\n    <boolean>\n\n    See Also\n    --------\n    IS_BIG_ENDIAN\n","IS_MOBILE":"\nIS_MOBILE\n    Boolean indicating if the current environment is a mobile device.\n\n    Examples\n    --------\n    > IS_MOBILE\n    <boolean>\n\n","IS_NODE":"\nIS_NODE\n    Boolean indicating if the runtime is Node.js.\n\n    Examples\n    --------\n    > IS_NODE\n    <boolean>\n\n","IS_TOUCH_DEVICE":"\nIS_TOUCH_DEVICE\n    Boolean indicating if the current environment is a touch device.\n\n    Examples\n    --------\n    > IS_TOUCH_DEVICE\n    <boolean>\n\n","IS_WEB_WORKER":"\nIS_WEB_WORKER\n    Boolean indicating if the runtime is a web worker.\n\n    Examples\n    --------\n    > IS_WEB_WORKER\n    <boolean>\n\n","IS_WINDOWS":"\nIS_WINDOWS\n    Boolean indicating if the current process is running on Windows.\n\n    Examples\n    --------\n    > IS_WINDOWS\n    <boolean>\n\n","isAbsoluteHttpURI":"\nisAbsoluteHttpURI( value )\n    Tests whether a value is an absolute HTTP(S) URI.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether a value is an absolute HTTP(S) URI.\n\n    Examples\n    --------\n    > var bool = isAbsoluteHttpURI( 'http://example.com/' )\n    true\n    > bool = isAbsoluteHttpURI( 'example.com' )\n    false\n    > bool = isAbsoluteHttpURI( 'foo@bar.com' )\n    false\n\n    See Also\n    --------\n    isAbsoluteURI","isAbsolutePath":"\nisAbsolutePath( value )\n    Tests if a value is an absolute path.\n\n    Function behavior is platform-specific. On Windows platforms, the function\n    is equal to `.win32()`. On POSIX platforms, the function is equal to\n    `.posix()`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is an absolute path.\n\n    Examples\n    --------\n    // Windows environment:\n    > var bool = isAbsolutePath( 'C:\\\\foo\\\\bar\\\\baz' )\n    true\n\n    // POSIX environment:\n    > bool = isAbsolutePath( '/foo/bar/baz' )\n    true\n\n\nisAbsolutePath.posix( value )\n    Tests if a value is a POSIX absolute path.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is a POSIX absolute path.\n\n    Examples\n    --------\n    > var bool = isAbsolutePath.posix( '/foo/bar/baz' )\n    true\n    > bool = isAbsolutePath.posix( 'foo/bar/baz' )\n    false\n\n\nisAbsolutePath.win32( value )\n    Tests if a value is a Windows absolute path.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is a Windows absolute path.\n\n    Examples\n    --------\n    > var bool = isAbsolutePath.win32( 'C:\\\\foo\\\\bar\\\\baz' )\n    true\n    > bool = isAbsolutePath.win32( 'foo\\\\bar\\\\baz' )\n    false\n\n    See Also\n    --------\n    isRelativePath\n","isAbsolutePath.posix":"\nisAbsolutePath.posix( value )\n    Tests if a value is a POSIX absolute path.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is a POSIX absolute path.\n\n    Examples\n    --------\n    > var bool = isAbsolutePath.posix( '/foo/bar/baz' )\n    true\n    > bool = isAbsolutePath.posix( 'foo/bar/baz' )\n    false","isAbsolutePath.win32":"\nisAbsolutePath.win32( value )\n    Tests if a value is a Windows absolute path.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is a Windows absolute path.\n\n    Examples\n    --------\n    > var bool = isAbsolutePath.win32( 'C:\\\\foo\\\\bar\\\\baz' )\n    true\n    > bool = isAbsolutePath.win32( 'foo\\\\bar\\\\baz' )\n    false\n\n    See Also\n    --------\n    isRelativePath","isAbsoluteURI":"\nisAbsoluteURI( value )\n    Tests whether a value is an absolute URI.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether a value is an absolute URI.\n\n    Examples\n    --------\n    > var bool = isAbsoluteURI( 'http://example.com/' )\n    true\n    > bool = isAbsoluteURI( 'example.com' )\n    false\n    > bool = isAbsoluteURI( 'foo@bar.com' )\n    false\n\n    See Also\n    --------\n    isRelativeURI","isAccessorArray":"\nisAccessorArray( value )\n    Tests if a value is an array-like object supporting the accessor (get/set)\n    protocol.\n\n    An accessor array is defined as an array, typed array, or an array-like\n    object (excluding strings and functions) having `get` and `set` methods for\n    accessing array elements.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an accessor array.\n\n    Examples\n    --------\n    > var bool = isAccessorArray( new Complex64Array( 10 ) )\n    true\n    > bool = isAccessorArray( [] )\n    false\n    > bool = isAccessorArray( { 'length': 0 } )\n    false\n    > bool = isAccessorArray( {} )\n    false\n\n    See Also\n    --------\n    isArrayLike, isArrayLikeObject, isCollection\n","isAccessorProperty":"\nisAccessorProperty( value, property )\n    Tests if an object's own property has an accessor descriptor.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own property has an accessor\n        descriptor.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.get = function getter() { return 'beep'; };\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isAccessorProperty( obj, 'boop' )\n    false\n    > bool = isAccessorProperty( obj, 'beep' )\n    true\n\n    See Also\n    --------\n    hasOwnProp, isAccessorPropertyIn, isDataProperty\n","isAccessorPropertyIn":"\nisAccessorPropertyIn( value, property )\n    Tests if an object's own or inherited property has an accessor descriptor.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own or inherited property has an\n        accessor descriptor.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.get = function getter() { return 'beep'; };\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isAccessorPropertyIn( obj, 'boop' )\n    false\n    > bool = isAccessorPropertyIn( obj, 'beep' )\n    true\n\n    See Also\n    --------\n    hasProp, isAccessorProperty, isDataPropertyIn\n","isAlphagram":"\nisAlphagram( value )\n    Tests if a value is an alphagram (i.e., a sequence of characters arranged in\n    alphabetical order).\n\n    The function first checks that an input value is a string before validating\n    that the value is an alphagram. For non-string values, the function returns\n    `false`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an alphagram.\n\n    Examples\n    --------\n    > var out = isAlphagram( 'beep' )\n    true\n    > out = isAlphagram( 'zba' )\n    false\n    > out = isAlphagram( '' )\n    false\n\n    See Also\n    --------\n    isAnagram\n","isAlphaNumeric":"\nisAlphaNumeric( str )\n    Tests whether a string contains only alphanumeric characters.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a string contains only alphanumeric\n        characters.\n\n    Examples\n    --------\n    > var bool = isAlphaNumeric( 'abc0123456789' )\n    true\n    > bool = isAlphaNumeric( 'abcdef' )\n    true\n    > bool = isAlphaNumeric( '0xff' )\n    true\n    > bool = isAlphaNumeric( '' )\n    false\n\n    See Also\n    --------\n    isDigitString\n","isAnagram":"\nisAnagram( str, value )\n    Tests if a value is an anagram.\n\n    Parameters\n    ----------\n    str: string\n        Comparison string.\n\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an anagram.\n\n    Examples\n    --------\n    > var str1 = 'I am a weakish speller';\n    > var str2 = 'William Shakespeare';\n    > var bool = isAnagram( str1, str2 )\n    true\n    > bool = isAnagram( 'bat', 'tabba' )\n    false\n\n    See Also\n    --------\n    isAlphagram\n","isArguments":"\nisArguments( value )\n    Tests if a value is an arguments object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an arguments object.\n\n    Examples\n    --------\n    > function foo() { return arguments; };\n    > var bool = isArguments( foo() )\n    true\n    > bool = isArguments( [] )\n    false\n\n","isArray":"\nisArray( value )\n    Tests if a value is an array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array.\n\n    Examples\n    --------\n    > var bool = isArray( [] )\n    true\n    > bool = isArray( {} )\n    false\n\n    See Also\n    --------\n    isArrayLike\n","isArrayArray":"\nisArrayArray( value )\n    Tests if a value is an array of arrays.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array of arrays.\n\n    Examples\n    --------\n    > var bool = isArrayArray( [ [], [] ] )\n    true\n    > bool = isArrayArray( [ {}, {} ] )\n    false\n    > bool = isArrayArray( [] )\n    false\n\n","isArrayBuffer":"\nisArrayBuffer( value )\n    Tests if a value is an ArrayBuffer.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an ArrayBuffer.\n\n    Examples\n    --------\n    > var bool = isArrayBuffer( new ArrayBuffer( 10 ) )\n    true\n    > bool = isArrayBuffer( [] )\n    false\n\n    See Also\n    --------\n    isSharedArrayBuffer, isTypedArray\n","isArrayBufferView":"\nisArrayBufferView( value )\n    Tests if a value is a `ArrayBuffer` view.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a `ArrayBuffer` view.\n\n    Examples\n    --------\n    > var bool = isArrayBufferView( new Int8Array() )\n    true\n    > bool = isArrayBufferView( [] )\n    false\n\n    See Also\n    --------\n    isDataView, isTypedArray\n","isArrayLength":"\nisArrayLength( value )\n    Tests if a value is a valid array length.\n\n    A valid length property for an Array instance is any integer value on the\n    interval [0, 2^32-1].\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a valid array length.\n\n    Examples\n    --------\n    > var bool = isArrayLength( 5 )\n    true\n    > bool = isArrayLength( 2.0e200 )\n    false\n    > bool = isArrayLength( -3.14 )\n    false\n    > bool = isArrayLength( null )\n    false\n\n    See Also\n    --------\n    isArray\n","isArrayLike":"\nisArrayLike( value )\n    Tests if a value is array-like.\n\n    If provided a string, the function returns `true`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is array-like.\n\n    Examples\n    --------\n    > var bool = isArrayLike( [] )\n    true\n    > bool = isArrayLike( { 'length': 10 } )\n    true\n    > bool = isArrayLike( 'beep' )\n    true\n    > bool = isArrayLike( null )\n    false\n\n    See Also\n    --------\n    isArray, isArrayLikeObject, isCollection\n","isArrayLikeObject":"\nisArrayLikeObject( value )\n    Tests if a value is an array-like object.\n\n    If provided a string, the function returns `false`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object.\n\n    Examples\n    --------\n    > var bool = isArrayLikeObject( [] )\n    true\n    > bool = isArrayLikeObject( { 'length': 10 } )\n    true\n    > bool = isArrayLikeObject( 'beep' )\n    false\n\n    See Also\n    --------\n    isArray, isArrayLike, isCollection\n","isArrowFunction":"\nisArrowFunction( value )\n    Tests if a value is an arrow function.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an arrow function.\n\n    Examples\n    --------\n    > function beep() {};\n    > var bool = isArrowFunction( beep )\n    false\n    > bool = isArrowFunction( {} )\n    false\n\n","isASCII":"\nisASCII( str )\n    Tests whether a character belongs to the ASCII character set and whether\n    this is true for all characters in a provided string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a string has all ASCII characters.\n\n    Examples\n    --------\n    > var str = 'beep boop';\n    > var bool = isASCII( str )\n    true\n    > bool = isASCII( fromCodePoint( 130 ) )\n    false\n\n    See Also\n    --------\n    isString\n","isBetween":"\nisBetween( value, a, b[, left, right] )\n    Tests if a value is between two values.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    a: any\n        Left comparison value.\n\n    b: any\n        Right comparison value.\n\n    left: string (optional)\n        Indicates whether the left comparison value is inclusive. Must be either\n        'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n    right: string (optional)\n        Indicates whether the right comparison value is inclusive. Must be\n        either 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is between two values.\n\n    Examples\n    --------\n    > var bool = isBetween( 3.14, 3.0, 4.0 )\n    true\n    > bool = isBetween( 3.0, 3.0, 4.0 )\n    true\n    > bool = isBetween( 4.0, 3.0, 4.0 )\n    true\n    > bool = isBetween( 3.0, 3.14, 4.0 )\n    false\n    > bool = isBetween( 3.14, 3.14, 4.0, 'open', 'closed' )\n    false\n    > bool = isBetween( 3.14, 3.0, 3.14, 'closed', 'open' )\n    false\n\n    See Also\n    --------\n    isBetweenArray\n","isBetweenArray":"\nisBetweenArray( value, a, b[, left, right] )\n    Tests if a value is an array-like object where every element is between two\n    values.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    a: any\n        Left comparison value.\n\n    b: any\n        Right comparison value.\n\n    left: string (optional)\n        Indicates whether the left comparison value is inclusive. Must be either\n        'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n    right: string (optional)\n        Indicates whether the right comparison value is inclusive. Must be\n        either 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object where every\n        element is between two values.\n\n    Examples\n    --------\n    > var arr = [ 3.0, 3.14, 4.0 ];\n    > var bool = isBetweenArray( arr, 3.0, 4.0 )\n    true\n    > bool = isBetweenArray( arr, 3.14, 4.0 )\n    false\n    > bool = isBetweenArray( arr, 3.0, 3.14 )\n    false\n    > bool = isBetweenArray( arr, 3.0, 4.0, 'open', 'closed' )\n    false\n    > bool = isBetweenArray( arr, 3.0, 4.0, 'closed', 'open' )\n    false\n\n    See Also\n    --------\n    isBetween\n","isBigInt":"\nisBigInt( value )\n    Tests if a value is a BigInt.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a BigInt.\n\n    Examples\n    --------\n    > var bool = isBigInt( BigInt( '1' ) )\n    true\n    > bool = isBigInt( Object( BigInt( '1' ) ) )\n    true\n    > bool = isBigInt( {} )\n    false\n    > bool = isBigInt( null )\n    false\n    > bool = isBigInt( true )\n    false\n\n","isBigInt64Array":"\nisBigInt64Array( value )\n    Tests if a value is a BigInt64Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a BigInt64Array.\n\n    Examples\n    --------\n    > var bool = isBigInt64Array( new BigInt64Array( 10 ) )\n    true\n    > bool = isBigInt64Array( [] )\n    false\n\n    See Also\n    --------\n    isBigUint64Array\n","isBigUint64Array":"\nisBigUint64Array( value )\n    Tests if a value is a BigUint64Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a BigUint64Array.\n\n    Examples\n    --------\n    > var bool = isBigUint64Array( new BigUint64Array( 10 ) )\n    true\n    > bool = isBigUint64Array( [] )\n    false\n\n    See Also\n    --------\n    isBigInt64Array\n","isBinaryString":"\nisBinaryString( value )\n    Tests if a value is a binary string.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a binary string.\n\n    Examples\n    --------\n    > var bool = isBinaryString( '1000101' )\n    true\n    > bool = isBinaryString( 'beep' )\n    false\n    > bool = isBinaryString( '' )\n    false\n\n    See Also\n    --------\n    isString\n","isBlankString":"\nisBlankString( value )\n    Tests if a value is a blank string (i.e., an empty string or a string\n    consisting only of whitespace characters).\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a blank string.\n\n    Examples\n    --------\n    > var bool = isBlankString( '   ' )\n    true\n    > bool = isBlankString( 'beep' )\n    false\n    > bool = isBlankString( null )\n    false\n\n    See Also\n    --------\n    isString, isEmptyString\n","isBoolean":"\nisBoolean( value )\n    Tests if a value is a boolean.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a boolean.\n\n    Examples\n    --------\n    > var bool = isBoolean( false )\n    true\n    > bool = isBoolean( new Boolean( false ) )\n    true\n\n\nisBoolean.isPrimitive( value )\n    Tests if a value is a boolean primitive.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a boolean primitive.\n\n    Examples\n    --------\n    > var bool = isBoolean.isPrimitive( true )\n    true\n    > bool = isBoolean.isPrimitive( false )\n    true\n    > bool = isBoolean.isPrimitive( new Boolean( true ) )\n    false\n\n\nisBoolean.isObject( value )\n    Tests if a value is a boolean object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a boolean object.\n\n    Examples\n    --------\n    > var bool = isBoolean.isObject( true )\n    false\n    > bool = isBoolean.isObject( new Boolean( false ) )\n    true\n\n","isBoolean.isPrimitive":"\nisBoolean.isPrimitive( value )\n    Tests if a value is a boolean primitive.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a boolean primitive.\n\n    Examples\n    --------\n    > var bool = isBoolean.isPrimitive( true )\n    true\n    > bool = isBoolean.isPrimitive( false )\n    true\n    > bool = isBoolean.isPrimitive( new Boolean( true ) )\n    false","isBoolean.isObject":"\nisBoolean.isObject( value )\n    Tests if a value is a boolean object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a boolean object.\n\n    Examples\n    --------\n    > var bool = isBoolean.isObject( true )\n    false\n    > bool = isBoolean.isObject( new Boolean( false ) )\n    true","isBooleanArray":"\nisBooleanArray( value )\n    Tests if a value is an array-like object of booleans.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object of booleans.\n\n    Examples\n    --------\n    > var bool = isBooleanArray( [ true, false, true ] )\n    true\n    > bool = isBooleanArray( [ true, 'abc', false ] )\n    false\n\n\nisBooleanArray.primitives( value )\n    Tests if a value is an array-like object containing only boolean primitives.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        boolean primitives.\n\n    Examples\n    --------\n    > var bool = isBooleanArray.primitives( [ true, false ] )\n    true\n    > bool = isBooleanArray.primitives( [ false, new Boolean( true ) ] )\n    false\n\n\nisBooleanArray.objects( value )\n    Tests if a value is an array-like object containing only Boolean objects.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        Boolean objects.\n\n    Examples\n    --------\n    > var bool = isBooleanArray.objects( [ new Boolean( false ), true ] )\n    false\n    > bool = isBooleanArray.objects( [ new Boolean( false ), new Boolean( true ) ] )\n    true\n\n","isBooleanArray.primitives":"\nisBooleanArray.primitives( value )\n    Tests if a value is an array-like object containing only boolean primitives.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        boolean primitives.\n\n    Examples\n    --------\n    > var bool = isBooleanArray.primitives( [ true, false ] )\n    true\n    > bool = isBooleanArray.primitives( [ false, new Boolean( true ) ] )\n    false","isBooleanArray.objects":"\nisBooleanArray.objects( value )\n    Tests if a value is an array-like object containing only Boolean objects.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        Boolean objects.\n\n    Examples\n    --------\n    > var bool = isBooleanArray.objects( [ new Boolean( false ), true ] )\n    false\n    > bool = isBooleanArray.objects( [ new Boolean( false ), new Boolean( true ) ] )\n    true","isBoxedPrimitive":"\nisBoxedPrimitive( value )\n    Tests if a value is a JavaScript boxed primitive.\n\n    Boxed primitive objects can be created with one of the following:\n\n    - new Boolean()\n    - new Number()\n    - new String()\n    - Object( Symbol() ) (ES6/ES2015)\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a JavaScript boxed primitive.\n\n    Examples\n    --------\n    > var bool = isBoxedPrimitive( new Boolean( false ) )\n    true\n    > bool = isBoxedPrimitive( true )\n    false\n\n    See Also\n    --------\n    isPrimitive\n","isBuffer":"\nisBuffer( value )\n    Tests if a value is a Buffer instance.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Buffer instance.\n\n    Examples\n    --------\n    > var bool = isBuffer( new Buffer( 'beep' ) )\n    true\n    > bool = isBuffer( new Buffer( [ 1, 2, 3, 4 ] ) )\n    true\n    > bool = isBuffer( {} )\n    false\n    > bool = isBuffer( [] )\n    false\n\n","isCamelcase":"\nisCamelcase( value )\n    Tests if a value is a camelcase string.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a camelcase string.\n\n    Examples\n    --------\n    > var bool = isCamelcase( 'helloWorld' )\n    true\n    > bool = isCamelcase( 'hello world' )\n    false\n\n    See Also\n    --------\n    isString, isConstantcase","isCapitalized":"\nisCapitalized( value )\n    Tests if a value is a string having an uppercase first character.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a string with an uppercase first\n        character.\n\n    Examples\n    --------\n    > var bool = isCapitalized( 'Hello' )\n    true\n    > bool = isCapitalized( 'world' )\n    false\n\n    See Also\n    --------\n    isString\n","isCentrosymmetricMatrix":"\nisCentrosymmetricMatrix( value )\n    Tests if a value is a matrix which is symmetric about its center.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a centrosymmetric matrix.\n\n    Examples\n    --------\n    > var buf = [ 2, 1, 1, 2 ];\n    > var M = ndarray( 'generic', buf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n    > var bool = isCentrosymmetricMatrix( M )\n    true\n    > bool = isCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isCentrosymmetricMatrix( 3.14 )\n    false\n    > bool = isCentrosymmetricMatrix( {} )\n    false\n\n    See Also\n    --------\n    isMatrixLike, isSquareMatrix, isSymmetricMatrix\n","isCircular":"\nisCircular( value )\n    Tests if an object-like value contains a circular reference.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an object-like value contains a circular\n        reference.\n\n    Examples\n    --------\n    > var obj = { 'beep': 'boop' };\n    > obj.self = obj;\n    > var bool = isCircular( obj )\n    true\n    > bool = isCircular( {} )\n    false\n    > bool = isCircular( null )\n    false\n\n    See Also\n    --------\n    isCircularArray, isCircularPlainObject\n","isCircularArray":"\nisCircularArray( value )\n    Tests if a value is an array containing a circular reference.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array containing a\n        circular reference.\n\n    Examples\n    --------\n    > var arr = [ 1, 2, 3 ];\n    > arr.push( arr );\n    > var bool = isCircularArray( arr )\n    true\n    > bool = isCircularArray( [] )\n    false\n    > bool = isCircularArray( null )\n    false\n\n    See Also\n    --------\n    isCircular, isCircularPlainObject\n","isCircularPlainObject":"\nisCircularPlainObject( value )\n    Tests if a value is a plain object containing a circular reference.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a plain object containing a\n        circular reference.\n\n    Examples\n    --------\n    > var obj = { 'beep': 'boop' };\n    > obj.self = obj;\n    > var bool = isCircularPlainObject( obj )\n    true\n    > bool = isCircularPlainObject( {} )\n    false\n    > bool = isCircularPlainObject( null )\n    false\n\n    See Also\n    --------\n    isCircular, isCircularArray\n","isClass":"\nisClass( value )\n    Tests if a value is a class.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a class.\n\n    Examples\n    --------\n    > var bool = isClass( class Person {} )\n    true\n    > bool = isClass( function Person() {} )\n    false\n    > bool = isClass( {} )\n    false\n    > bool = isClass( null )\n    false\n    > bool = isClass( true )\n    false\n","isCollection":"\nisCollection( value )\n    Tests if a value is a collection.\n\n    A collection is defined as an array, typed array, or an array-like object\n    (excluding strings and functions).\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a collection.\n\n    Examples\n    --------\n    > var bool = isCollection( [] )\n    true\n    > bool = isCollection( { 'length': 0 } )\n    true\n    > bool = isCollection( {} )\n    false\n\n    See Also\n    --------\n    isArrayLike, isArrayLikeObject\n","isComplex":"\nisComplex( value )\n    Tests if a value is a 64-bit or 128-bit complex number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 64-bit or 128-bit complex\n        number.\n\n    Examples\n    --------\n    > var bool = isComplex( new Complex64( 2.0, 2.0 ) )\n    true\n    > bool = isComplex( new Complex128( 3.0, 1.0 ) )\n    true\n    > bool = isComplex( 3.14 )\n    false\n    > bool = isComplex( {} )\n    false\n\n    See Also\n    --------\n    isComplex64, isComplex128\n","isComplex64":"\nisComplex64( value )\n    Tests if a value is a 64-bit complex number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 64-bit complex number.\n\n    Examples\n    --------\n    > var bool = isComplex64( new Complex64( 2.0, 2.0 ) )\n    true\n    > bool = isComplex64( new Complex128( 3.0, 1.0 ) )\n    false\n    > bool = isComplex64( 3.14 )\n    false\n    > bool = isComplex64( {} )\n    false\n\n    See Also\n    --------\n    isComplex, isComplex128\n","isComplex64Array":"\nisComplex64Array( value )\n    Tests if a value is a Complex64Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Complex64Array.\n\n    Examples\n    --------\n    > var bool = isComplex64Array( new Complex64Array( 10 ) )\n    true\n    > bool = isComplex64Array( [] )\n    false\n\n    See Also\n    --------\n    isComplex, isComplex64, isComplex128Array, isComplexTypedArray\n","isComplex64MatrixLike":"\nisComplex64MatrixLike( value )\n    Tests if a value is a 2-dimensional ndarray-like object containing single-\n    precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 2-dimensional ndarray-like\n        object containing single-precision complex floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n    > M.ndims = 2;\n    > M.shape = [ 2, 2 ];\n    > M.strides = [ 2, 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'complex64';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isComplex64MatrixLike( M )\n    true\n    > bool = isComplex64MatrixLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isComplex64MatrixLike( 3.14 )\n    false\n    > bool = isComplex64MatrixLike( {} )\n    false\n\n    See Also\n    --------\n    isComplex128MatrixLike, isndarrayLike, isMatrixLike\n","isComplex64ndarrayLike":"\nisComplex64ndarrayLike( value )\n    Tests if a value is an ndarray-like object containing single-precision\n    complex floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an ndarray-like object containing\n        single-precision complex floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n    > M.ndims = 2;\n    > M.shape = [ 2, 2 ];\n    > M.strides = [ 2, 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'complex64';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isComplex64ndarrayLike( M )\n    true\n    > bool = isComplex64ndarrayLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isComplex64ndarrayLike( 3.14 )\n    false\n    > bool = isComplex64ndarrayLike( {} )\n    false\n\n    See Also\n    --------\n    isComplex128ndarrayLike, isndarrayLike\n","isComplex64VectorLike":"\nisComplex64VectorLike( value )\n    Tests if a value is a 1-dimensional ndarray-like object containing single-\n    precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 1-dimensional ndarray-like\n        object containing single-precision complex floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n    > M.ndims = 1;\n    > M.shape = [ 4 ];\n    > M.strides = [ 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'complex64';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isComplex64VectorLike( M )\n    true\n    > bool = isComplex64VectorLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isComplex64VectorLike( 3.14 )\n    false\n    > bool = isComplex64VectorLike( {} )\n    false\n\n    See Also\n    --------\n    isComplex128VectorLike, isndarrayLike, isVectorLike\n","isComplex128":"\nisComplex128( value )\n    Tests if a value is a 128-bit complex number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 128-bit complex number.\n\n    Examples\n    --------\n    > var bool = isComplex128( new Complex128( 3.0, 1.0 ) )\n    true\n    > bool = isComplex128( new Complex64( 2.0, 2.0 ) )\n    false\n    > bool = isComplex128( 3.14 )\n    false\n    > bool = isComplex128( {} )\n    false\n\n    See Also\n    --------\n    isComplex, isComplex64\n","isComplex128Array":"\nisComplex128Array( value )\n    Tests if a value is a Complex128Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Complex128Array.\n\n    Examples\n    --------\n    > var bool = isComplex128Array( new Complex128Array( 10 ) )\n    true\n    > bool = isComplex128Array( [] )\n    false\n\n    See Also\n    --------\n    isComplex, isComplex128, isComplex64Array, isComplexTypedArray\n","isComplex128MatrixLike":"\nisComplex128MatrixLike( value )\n    Tests if a value is a 2-dimensional ndarray-like object containing double-\n    precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 2-dimensional ndarray-like\n        object containing double-precision complex floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n    > M.ndims = 2;\n    > M.shape = [ 2, 2 ];\n    > M.strides = [ 2, 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'complex128';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isComplex128MatrixLike( M )\n    true\n    > bool = isComplex128MatrixLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isComplex128MatrixLike( 3.14 )\n    false\n    > bool = isComplex128MatrixLike( {} )\n    false\n\n    See Also\n    --------\n    isComplex64MatrixLike, isndarrayLike, isMatrixLike\n","isComplex128ndarrayLike":"\nisComplex128ndarrayLike( value )\n    Tests if a value is an ndarray-like object containing double-precision\n    complex floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an ndarray-like object containing\n        double-precision complex floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n    > M.ndims = 2;\n    > M.shape = [ 2, 2 ];\n    > M.strides = [ 2, 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'complex128';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isComplex128ndarrayLike( M )\n    true\n    > bool = isComplex128ndarrayLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isComplex128ndarrayLike( 3.14 )\n    false\n    > bool = isComplex128ndarrayLike( {} )\n    false\n\n    See Also\n    --------\n    isComplex64ndarrayLike, isndarrayLike\n","isComplex128VectorLike":"\nisComplex128VectorLike( value )\n    Tests if a value is a 1-dimensional ndarray-like object containing double-\n    precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 1-dimensional ndarray-like\n        object containing double-precision complex floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n    > M.ndims = 1;\n    > M.shape = [ 4 ];\n    > M.strides = [ 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'complex128';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isComplex128VectorLike( M )\n    true\n    > bool = isComplex128VectorLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isComplex128VectorLike( 3.14 )\n    false\n    > bool = isComplex128VectorLike( {} )\n    false\n\n    See Also\n    --------\n    isComplex64VectorLike, isndarrayLike, isVectorLike\n","isComplexLike":"\nisComplexLike( value )\n    Tests if a value is a complex number-like object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a complex number-like object.\n\n    Examples\n    --------\n    > var bool = isComplexLike( new Complex64( 2.0, 2.0 ) )\n    true\n    > bool = isComplexLike( new Complex128( 3.0, 1.0 ) )\n    true\n    > bool = isComplexLike( 3.14 )\n    false\n    > bool = isComplexLike( {} )\n    false\n\n    See Also\n    --------\n    isComplex, isComplex64, isComplex128\n","isComplexTypedArray":"\nisComplexTypedArray( value )\n    Tests if a value is a complex typed array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a complex typed array.\n\n    Examples\n    --------\n    > var bool = isComplexTypedArray( new Complex64Array( 10 ) )\n    true\n\n    See Also\n    --------\n    isComplex, isComplex64Array, isComplex128Array\n","isComplexTypedArrayLike":"\nisComplexTypedArrayLike( value )\n    Tests if a value is complex-typed-array-like.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is complex-typed-array-like.\n\n    Examples\n    --------\n    > var bool = isComplexTypedArrayLike( new Complex128Array() )\n    true\n    > bool = isComplexTypedArrayLike({\n    ...    'length': 10,\n    ...    'byteOffset': 0,\n    ...    'byteLength': 10,\n    ...    'BYTES_PER_ELEMENT': 4,\n    ...    'get': function get() {},\n    ...    'set': function set() {}\n    ... })\n    true\n\n    See Also\n    --------\n    isComplexLike, isComplexTypedArray, isComplex64Array, isComplex128Array\n","isComposite":"\nisComposite( value )\n    Tests if a value is a composite number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a composite number.\n\n    Examples\n    --------\n    > var bool = isComposite( 4.0 )\n    true\n    > bool = isComposite( new Number( 4.0 ) )\n    true\n    > bool = isComposite( 3.14 )\n    false\n    > bool = isComposite( -4.0 )\n    false\n    > bool = isComposite( null )\n    false\n\n\nisComposite.isPrimitive( value )\n    Tests if a value is a number primitive which is a composite number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a\n        composite number.\n\n    Examples\n    --------\n    > var bool = isComposite.isPrimitive( 4.0 )\n    true\n    > bool = isComposite.isPrimitive( new Number( 4.0 ) )\n    false\n\n\nisComposite.isObject( value )\n    Tests if a value is a number object having a value which is a composite\n    number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a composite number.\n\n    Examples\n    --------\n    > var bool = isComposite.isObject( 4.0 )\n    false\n    > bool = isComposite.isObject( new Number( 4.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger, isNumber, isPrime\n","isComposite.isPrimitive":"\nisComposite.isPrimitive( value )\n    Tests if a value is a number primitive which is a composite number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a\n        composite number.\n\n    Examples\n    --------\n    > var bool = isComposite.isPrimitive( 4.0 )\n    true\n    > bool = isComposite.isPrimitive( new Number( 4.0 ) )\n    false","isComposite.isObject":"\nisComposite.isObject( value )\n    Tests if a value is a number object having a value which is a composite\n    number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a composite number.\n\n    Examples\n    --------\n    > var bool = isComposite.isObject( 4.0 )\n    false\n    > bool = isComposite.isObject( new Number( 4.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger, isNumber, isPrime","isConfigurableProperty":"\nisConfigurableProperty( value, property )\n    Tests if an object's own property is configurable.\n\n    A property is configurable if the property may be deleted or its descriptor\n    may be changed.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own property is configurable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = true;\n    > desc.writable = true;\n    > desc.value = true;\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isConfigurableProperty( obj, 'boop' )\n    true\n    > bool = isConfigurableProperty( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    isConfigurablePropertyIn, isEnumerableProperty, isReadableProperty, isWritableProperty\n","isConfigurablePropertyIn":"\nisConfigurablePropertyIn( value, property )\n    Tests if an object's own or inherited property is configurable.\n\n    A property is configurable if the property may be deleted or its descriptor\n    may be changed.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own or inherited property is\n        configurable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = true;\n    > desc.writable = true;\n    > desc.value = true;\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isConfigurablePropertyIn( obj, 'boop' )\n    true\n    > bool = isConfigurablePropertyIn( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    isConfigurableProperty, isEnumerablePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isConstantcase":"\nisConstantcase( value )\n    Tests if a value is a constantcase string.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a constantcase string.\n\n    Examples\n    --------\n    > var bool = isConstantcase( 'BEEP_BOOP' )\n    true\n    > bool = isConstantcase( 'BEEP and BOOP' )\n    false\n\n    See Also\n    --------\n    isString, isCamelcase","isCubeNumber":"\nisCubeNumber( value )\n    Tests if a value is a cube number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a cube number.\n\n    Examples\n    --------\n    > var bool = isCubeNumber( 8.0 )\n    true\n    > bool = isCubeNumber( new Number( 8.0 ) )\n    true\n    > bool = isCubeNumber( 3.14 )\n    false\n    > bool = isCubeNumber( -5.0 )\n    false\n    > bool = isCubeNumber( null )\n    false\n\n\nisCubeNumber.isPrimitive( value )\n    Tests if a value is a number primitive which is a cube number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a cube\n        number.\n\n    Examples\n    --------\n    > var bool = isCubeNumber.isPrimitive( 8.0 )\n    true\n    > bool = isCubeNumber.isPrimitive( new Number( 8.0 ) )\n    false\n\n\nisCubeNumber.isObject( value )\n    Tests if a value is a number object having a value which is a cube number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a cube number.\n\n    Examples\n    --------\n    > var bool = isCubeNumber.isObject( 8.0 )\n    false\n    > bool = isCubeNumber.isObject( new Number( 8.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger, isNumber, isSquareNumber\n","isCubeNumber.isPrimitive":"\nisCubeNumber.isPrimitive( value )\n    Tests if a value is a number primitive which is a cube number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a cube\n        number.\n\n    Examples\n    --------\n    > var bool = isCubeNumber.isPrimitive( 8.0 )\n    true\n    > bool = isCubeNumber.isPrimitive( new Number( 8.0 ) )\n    false","isCubeNumber.isObject":"\nisCubeNumber.isObject( value )\n    Tests if a value is a number object having a value which is a cube number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a cube number.\n\n    Examples\n    --------\n    > var bool = isCubeNumber.isObject( 8.0 )\n    false\n    > bool = isCubeNumber.isObject( new Number( 8.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger, isNumber, isSquareNumber","isCurrentYear":"\nisCurrentYear( value )\n    Tests if a value is the current year.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether a value is the current year.\n\n    Examples\n    --------\n    > var bool = isCurrentYear( new Date() )\n    true\n    > bool = isCurrentYear( currentYear() )\n    true\n    > bool = isCurrentYear( 2021 )\n    false\n    > bool = isCurrentYear( null )\n    false\n\n","isDataProperty":"\nisDataProperty( value, property )\n    Tests if an object's own property has a data descriptor.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own property has a data descriptor.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.get = function getter() { return 'beep'; };\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isDataProperty( obj, 'boop' )\n    true\n    > bool = isDataProperty( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    hasOwnProp, isAccessorProperty, isDataPropertyIn\n","isDataPropertyIn":"\nisDataPropertyIn( value, property )\n    Tests if an object's own or inherited property has a data descriptor.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own or inherited property has a data\n        descriptor.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.get = function getter() { return 'beep'; };\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isDataPropertyIn( obj, 'boop' )\n    true\n    > bool = isDataPropertyIn( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    hasProp, isAccessorPropertyIn, isDataProperty\n","isDataView":"\nisDataView( value )\n    Tests if a value is a DataView.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a DataView.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 10 );\n    > var bool = isDataView( new DataView( buf ) )\n    true\n    > bool = isDataView( [] )\n    false\n\n    See Also\n    --------\n    isArrayBuffer, isTypedArray\n","isDateObject":"\nisDateObject( value )\n    Tests if a value is a Date object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Date object.\n\n    Examples\n    --------\n    > var bool = isDateObject( new Date() )\n    true\n    > bool = isDateObject( '2017-01-01' )\n    false\n\n","isDateObjectArray":"\nisDateObjectArray( value )\n    Tests if a value is an array-like object containing only Date objects.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if value is an array-like object containing only Date\n        objects.\n\n    Examples\n    --------\n    > var bool = isDateObjectArray( [ new Date(), new Date() ] )\n    true\n    > bool = isDateObjectArray( [ {}, {} ] )\n    false\n    > bool = isDateObjectArray( [ new Date(), '2011-01-01' ] )\n    false\n    > bool = isDateObjectArray( [] )\n    false\n\n    See Also\n    --------\n    isDateObject\n","isDigitString":"\nisDigitString( str )\n    Tests whether a string contains only numeric digits.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a string contains only numeric digits.\n\n    Examples\n    --------\n    > var bool = isDigitString( '0123456789' )\n    true\n    > bool = isDigitString( 'abcdef' )\n    false\n    > bool = isDigitString( '0xff' )\n    false\n    > bool = isDigitString( '' )\n    false\n\n    See Also\n    --------\n    isHexString, isString\n","isDomainName":"\nisDomainName( value )\n    Tests if a value is a domain name.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a domain name.\n\n    Examples\n    --------\n    > var bool = isDomainName( 'example.com' )\n    true\n    > bool = isDomainName( 'foo@bar.com' )\n    false\n","isDurationString":"\nisDurationString( value )\n    Tests if a value is a duration string.\n\n    The function validates that a value is a string. For all other types, the\n    function returns `false`.\n\n    A duration string is a string containing a sequence of time units. A time\n    unit is a non-negative integer followed by a unit identifier. The following\n    unit identifiers are supported:\n\n    - d: days.\n    - h: hours.\n    - m: minutes.\n    - s: seconds.\n    - ms: milliseconds.\n\n    For example, the string `1m3s10ms` is a duration string containing three\n    time units: `1m` (1 minute), `3s` (3 seconds), and `10ms` (10 milliseconds).\n    The string `60m` is a duration string containing a single time unit: `60m`\n    (60 minutes). Time units must be supplied in descending order of magnitude\n    (i.e., days, hours, minutes, seconds, milliseconds).\n\n    Duration strings are case insensitive. For example, the string `1M3S10MS` is\n    equivalent to `1m3s10ms`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a duration string.\n\n    Examples\n    --------\n    > var bool = isDurationString( '1d' )\n    true\n    > bool = isDurationString( '1h' )\n    true\n    > bool = isDurationString( 'beep' )\n    false\n","isEmailAddress":"\nisEmailAddress( value )\n    Tests if a value is an email address.\n\n    Validation is not rigorous. *9* RFCs relate to email addresses, and\n    accounting for all of them is a fool's errand. The function performs the\n    simplest validation; i.e., requiring at least one `@` symbol.\n\n    For rigorous validation, send a confirmation email. If the email bounces,\n    consider the email invalid.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an email address.\n\n    Examples\n    --------\n    > var bool = isEmailAddress( 'beep@boop.com' )\n    true\n    > bool = isEmailAddress( 'beep' )\n    false\n    > bool = isEmailAddress( null )\n    false\n\n","isEmptyArray":"\nisEmptyArray( value )\n    Tests if a value is an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is an empty array.\n\n    Examples\n    --------\n    > var bool = isEmptyArray( [] )\n    true\n    > bool = isEmptyArray( [ 1, 2, 3 ] )\n    false\n    > bool = isEmptyArray( {} )\n    false\n\n    See Also\n    --------\n    isArray, isEmptyArrayLikeObject, isEmptyCollection\n","isEmptyArrayLikeObject":"\nisEmptyArrayLikeObject( value )\n    Tests if a value is an empty array-like object.\n\n    If provided a string, the function returns `false`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an empty array-like object.\n\n    Examples\n    --------\n    > var bool = isEmptyArrayLikeObject( [] )\n    true\n    > bool = isEmptyArrayLikeObject( { 'length': 0 } )\n    true\n    > bool = isEmptyArrayLikeObject( '' )\n    false\n\n    See Also\n    --------\n    isArrayLikeObject, isEmptyArray, isEmptyCollection\n","isEmptyCollection":"\nisEmptyCollection( value )\n    Tests if a value is an empty collection.\n\n    A collection is defined as an array, typed array, or an array-like object\n    (excluding strings and functions).\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is an empty collection.\n\n    Examples\n    --------\n    > var bool = isEmptyCollection( [] )\n    true\n    > bool = isEmptyCollection( { 'length': 0 } )\n    true\n    > bool = isEmptyCollection( [ 1, 2, 3 ] )\n    false\n    > bool = isEmptyCollection( {} )\n    false\n\n    See Also\n    --------\n    isCollection, isEmptyArray, isEmptyArrayLikeObject\n","isEmptyObject":"\nisEmptyObject( value )\n    Tests if a value is an empty object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is an empty object.\n\n    Examples\n    --------\n    > var bool = isEmptyObject( {} )\n    true\n    > bool = isEmptyObject( { 'beep': 'boop' } )\n    false\n    > bool = isEmptyObject( [] )\n    false\n\n    See Also\n    --------\n    isObject, isPlainObject\n","isEmptyString":"\nisEmptyString( value )\n    Tests if a value is an empty string.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is an empty string.\n\n    Examples\n    --------\n    > var bool = isEmptyString( '' )\n    true\n    > bool = isEmptyString( new String( '' ) )\n    true\n    > bool = isEmptyString( 'beep' )\n    false\n    > bool = isEmptyString( [] )\n    false\n\n\nisEmptyString.isPrimitive( value )\n    Tests if a value is an empty string primitive.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an empty string primitive.\n\n    Examples\n    --------\n    > var bool = isEmptyString.isPrimitive( '' )\n    true\n    > bool = isEmptyString.isPrimitive( new String( '' ) )\n    false\n\n\nisEmptyString.isObject( value )\n    Tests if a value is an empty `String` object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an empty `String` object.\n\n    Examples\n    --------\n    > var bool = isEmptyString.isObject( new String( '' ) )\n    true\n    > bool = isEmptyString.isObject( '' )\n    false\n\n    See Also\n    --------\n    isString\n","isEmptyString.isPrimitive":"\nisEmptyString.isPrimitive( value )\n    Tests if a value is an empty string primitive.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an empty string primitive.\n\n    Examples\n    --------\n    > var bool = isEmptyString.isPrimitive( '' )\n    true\n    > bool = isEmptyString.isPrimitive( new String( '' ) )\n    false","isEmptyString.isObject":"\nisEmptyString.isObject( value )\n    Tests if a value is an empty `String` object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an empty `String` object.\n\n    Examples\n    --------\n    > var bool = isEmptyString.isObject( new String( '' ) )\n    true\n    > bool = isEmptyString.isObject( '' )\n    false\n\n    See Also\n    --------\n    isString","isEnumerableProperty":"\nisEnumerableProperty( value, property )\n    Tests if an object's own property is enumerable.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own property is enumerable.\n\n    Examples\n    --------\n    > var beep = { 'boop': true };\n    > var bool = isEnumerableProperty( beep, 'boop' )\n    true\n    > bool = isEnumerableProperty( beep, 'hasOwnProperty' )\n    false\n\n    See Also\n    --------\n    isConfigurableProperty, isEnumerablePropertyIn, isNonEnumerableProperty, isReadableProperty, isWritableProperty\n","isEnumerablePropertyIn":"\nisEnumerablePropertyIn( value, property )\n    Tests if an object's own or inherited property is enumerable.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own or inherited property is\n        enumerable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = true;\n    > desc.enumerable = false;\n    > desc.writable = true;\n    > desc.value = true;\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isEnumerablePropertyIn( obj, 'boop' )\n    true\n    > bool = isEnumerablePropertyIn( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    isConfigurablePropertyIn, isEnumerableProperty, isNonEnumerablePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isEqualArray":"\nisEqualArray( v1, v2 )\n    Tests if two arguments are both generic arrays and have equal values.\n\n    The function performs strict equality comparison; thus, the function treats\n    `-0` and `+0` as equal and `NaNs` as distinct.\n\n    Parameters\n    ----------\n    v1: any\n        First input value.\n\n    v2: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are equal.\n\n    Examples\n    --------\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > var y = [ 1.0, 2.0, 3.0 ];\n    > var bool = isEqualArray( x, y )\n    true\n\n    > x = [ NaN, NaN, NaN ];\n    > y = [ NaN, NaN, NaN ];\n    > bool = isEqualArray( x, y )\n    false\n\n    See Also\n    --------\n    isArray, isSameArray\n","isError":"\nisError( value )\n    Tests if a value is an Error object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an Error object.\n\n    Examples\n    --------\n    > var bool = isError( new Error( 'beep' ) )\n    true\n    > bool = isError( {} )\n    false\n\n","isEvalError":"\nisEvalError( value )\n    Tests if a value is an EvalError object.\n\n    This function should *not* be considered robust. While the function should\n    always return `true` if provided an EvalError (or a descendant) object,\n    false positives may occur due to the fact that the EvalError constructor\n    inherits from Error and has no internal class of its own. Hence, EvalError\n    impersonation is possible.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an EvalError object.\n\n    Examples\n    --------\n    > var bool = isEvalError( new EvalError( 'beep' ) )\n    true\n    > bool = isEvalError( {} )\n    false\n\n    See Also\n    --------\n    isError\n","isEven":"\nisEven( value )\n    Tests if a value is an even number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether is an even number.\n\n    Examples\n    --------\n    > var bool = isEven( 4.0 )\n    true\n    > bool = isEven( new Number( 4.0 ) )\n    true\n    > bool = isEven( 3.0 )\n    false\n    > bool = isEven( -3.14 )\n    false\n    > bool = isEven( null )\n    false\n\n\nisEven.isPrimitive( value )\n    Tests if a value is a number primitive that is an even number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive that is an even\n        number.\n\n    Examples\n    --------\n    > var bool = isEven.isPrimitive( -4.0 )\n    true\n    > bool = isEven.isPrimitive( new Number( -4.0 ) )\n    false\n\n\nisEven.isObject( value )\n    Tests if a value is a number object that is an even number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object that is an even\n        number.\n\n    Examples\n    --------\n    > var bool = isEven.isObject( 4.0 )\n    false\n    > bool = isEven.isObject( new Number( 4.0 ) )\n    true\n\n    See Also\n    --------\n    isOdd\n","isEven.isPrimitive":"\nisEven.isPrimitive( value )\n    Tests if a value is a number primitive that is an even number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive that is an even\n        number.\n\n    Examples\n    --------\n    > var bool = isEven.isPrimitive( -4.0 )\n    true\n    > bool = isEven.isPrimitive( new Number( -4.0 ) )\n    false","isEven.isObject":"\nisEven.isObject( value )\n    Tests if a value is a number object that is an even number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object that is an even\n        number.\n\n    Examples\n    --------\n    > var bool = isEven.isObject( 4.0 )\n    false\n    > bool = isEven.isObject( new Number( 4.0 ) )\n    true\n\n    See Also\n    --------\n    isOdd","isFalsy":"\nisFalsy( value )\n    Tests if a value is a value which translates to `false` when evaluated in a\n    boolean context.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is falsy.\n\n    Examples\n    --------\n    > var bool = isFalsy( false )\n    true\n    > bool = isFalsy( '' )\n    true\n    > bool = isFalsy( 0 )\n    true\n    > bool = isFalsy( null )\n    true\n    > bool = isFalsy( void 0 )\n    true\n    > bool = isFalsy( NaN )\n    true\n    > bool = isFalsy( {} )\n    false\n    > bool = isFalsy( [] )\n    false\n\n    See Also\n    --------\n    isFalsyArray, isTruthy\n","isFalsyArray":"\nisFalsyArray( value )\n    Tests if a value is an array-like object containing only falsy values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only falsy values.\n\n    Examples\n    --------\n    > var bool = isFalsyArray( [ null, '' ] )\n    true\n    > bool = isFalsyArray( [ {}, [] ] )\n    false\n    > bool = isFalsyArray( [] )\n    false\n\n    See Also\n    --------\n    isFalsy, isTruthyArray\n","isFinite":"\nisFinite( value )\n    Tests if a value is a finite number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a finite number.\n\n    Examples\n    --------\n    > var bool = isFinite( 5.0 )\n    true\n    > bool = isFinite( new Number( 5.0 ) )\n    true\n    > bool = isFinite( 1.0/0.0 )\n    false\n    > bool = isFinite( null )\n    false\n\n\nisFinite.isPrimitive( value )\n    Tests if a value is a number primitive having a finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number primitive having a finite\n        value.\n\n    Examples\n    --------\n    > var bool = isFinite.isPrimitive( -3.0 )\n    true\n    > bool = isFinite.isPrimitive( new Number( -3.0 ) )\n    false\n\n\nisFinite.isObject( value )\n    Tests if a value is a number object having a finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number object having a finite\n        value.\n\n    Examples\n    --------\n    > var bool = isFinite.isObject( 3.0 )\n    false\n    > bool = isFinite.isObject( new Number( 3.0 ) )\n    true\n\n    See Also\n    --------\n    isFiniteArray, isInfinite\n","isFinite.isPrimitive":"\nisFinite.isPrimitive( value )\n    Tests if a value is a number primitive having a finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number primitive having a finite\n        value.\n\n    Examples\n    --------\n    > var bool = isFinite.isPrimitive( -3.0 )\n    true\n    > bool = isFinite.isPrimitive( new Number( -3.0 ) )\n    false","isFinite.isObject":"\nisFinite.isObject( value )\n    Tests if a value is a number object having a finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number object having a finite\n        value.\n\n    Examples\n    --------\n    > var bool = isFinite.isObject( 3.0 )\n    false\n    > bool = isFinite.isObject( new Number( 3.0 ) )\n    true\n\n    See Also\n    --------\n    isFiniteArray, isInfinite","isFiniteArray":"\nisFiniteArray( value )\n    Tests if a value is an array-like object of finite numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object of finite\n        numbers.\n\n    Examples\n    --------\n    > var bool = isFiniteArray( [ -3.0, new Number(0.0), 2.0 ] )\n    true\n    > bool = isFiniteArray( [ -3.0, 1.0/0.0 ] )\n    false\n\n\nisFiniteArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive finite\n    numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only primitive finite numbers.\n\n    Examples\n    --------\n    > var bool = isFiniteArray.primitives( [ -1.0, 10.0 ] )\n    true\n    > bool = isFiniteArray.primitives( [ -1.0, 0.0, 5.0 ] )\n    true\n    > bool = isFiniteArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false\n\n\nisFiniteArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having finite values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only number objects having finite values.\n\n    Examples\n    --------\n    > var bool = isFiniteArray.objects( [ new Number(1.0), new Number(3.0) ] )\n    true\n    > bool = isFiniteArray.objects( [ -1.0, 0.0, 3.0 ] )\n    false\n    > bool = isFiniteArray.objects( [ 3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isFinite, isInfinite\n","isFiniteArray.primitives":"\nisFiniteArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive finite\n    numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only primitive finite numbers.\n\n    Examples\n    --------\n    > var bool = isFiniteArray.primitives( [ -1.0, 10.0 ] )\n    true\n    > bool = isFiniteArray.primitives( [ -1.0, 0.0, 5.0 ] )\n    true\n    > bool = isFiniteArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false","isFiniteArray.objects":"\nisFiniteArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having finite values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only number objects having finite values.\n\n    Examples\n    --------\n    > var bool = isFiniteArray.objects( [ new Number(1.0), new Number(3.0) ] )\n    true\n    > bool = isFiniteArray.objects( [ -1.0, 0.0, 3.0 ] )\n    false\n    > bool = isFiniteArray.objects( [ 3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isFinite, isInfinite","isFloat32Array":"\nisFloat32Array( value )\n    Tests if a value is a Float32Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Float32Array.\n\n    Examples\n    --------\n    > var bool = isFloat32Array( new Float32Array( 10 ) )\n    true\n    > bool = isFloat32Array( [] )\n    false\n\n    See Also\n    --------\n    isFloat64Array\n","isFloat32MatrixLike":"\nisFloat32MatrixLike( value )\n    Tests if a value is a 2-dimensional ndarray-like object containing single-\n    precision floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 2-dimensional ndarray-like\n        object containing single-precision floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Float32Array( [ 0, 0, 0, 0 ] );\n    > M.ndims = 2;\n    > M.shape = [ 2, 2 ];\n    > M.strides = [ 2, 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'float32';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isFloat32MatrixLike( M )\n    true\n    > bool = isFloat32MatrixLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isFloat32MatrixLike( 3.14 )\n    false\n    > bool = isFloat32MatrixLike( {} )\n    false\n\n    See Also\n    --------\n    isFloat64MatrixLike, isndarrayLike, isMatrixLike\n","isFloat32ndarrayLike":"\nisFloat32ndarrayLike( value )\n    Tests if a value is an ndarray-like object containing single-precision\n    floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an ndarray-like object containing\n        single-precision floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Float32Array( [ 0, 0, 0, 0 ] );\n    > M.ndims = 2;\n    > M.shape = [ 2, 2 ];\n    > M.strides = [ 2, 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'float32';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isFloat32ndarrayLike( M )\n    true\n    > bool = isFloat32ndarrayLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isFloat32ndarrayLike( 3.14 )\n    false\n    > bool = isFloat32ndarrayLike( {} )\n    false\n\n    See Also\n    --------\n    isFloat64ndarrayLike, isndarrayLike\n","isFloat32VectorLike":"\nisFloat32VectorLike( value )\n    Tests if a value is a 1-dimensional ndarray-like object containing single-\n    precision floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 1-dimensional ndarray-like\n        object containing single-precision floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Float32Array( [ 0, 0, 0, 0 ] );\n    > M.ndims = 1;\n    > M.shape = [ 4 ];\n    > M.strides = [ 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'float32';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isFloat32VectorLike( M )\n    true\n    > bool = isFloat32VectorLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isFloat32VectorLike( 3.14 )\n    false\n    > bool = isFloat32VectorLike( {} )\n    false\n\n    See Also\n    --------\n    isFloat64VectorLike, isndarrayLike, isVectorLike\n","isFloat64Array":"\nisFloat64Array( value )\n    Tests if a value is a Float64Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Float64Array.\n\n    Examples\n    --------\n    > var bool = isFloat64Array( new Float64Array( 10 ) )\n    true\n    > bool = isFloat64Array( [] )\n    false\n\n    See Also\n    --------\n    isFloat32Array\n","isFloat64MatrixLike":"\nisFloat64MatrixLike( value )\n    Tests if a value is a 2-dimensional ndarray-like object containing double-\n    precision floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 2-dimensional ndarray-like\n        object containing double-precision floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Float64Array( [ 0, 0, 0, 0 ] );\n    > M.ndims = 2;\n    > M.shape = [ 2, 2 ];\n    > M.strides = [ 2, 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'float64';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isFloat64MatrixLike( M )\n    true\n    > bool = isFloat64MatrixLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isFloat64MatrixLike( 3.14 )\n    false\n    > bool = isFloat64MatrixLike( {} )\n    false\n\n    See Also\n    --------\n    isFloat32MatrixLike, isndarrayLike, isMatrixLike\n","isFloat64ndarrayLike":"\nisFloat64ndarrayLike( value )\n    Tests if a value is an ndarray-like object containing double-precision\n    floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an ndarray-like object containing\n        double-precision floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Float64Array( [ 0, 0, 0, 0 ] );\n    > M.ndims = 2;\n    > M.shape = [ 2, 2 ];\n    > M.strides = [ 2, 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'float64';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isFloat64ndarrayLike( M )\n    true\n    > bool = isFloat64ndarrayLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isFloat64ndarrayLike( 3.14 )\n    false\n    > bool = isFloat64ndarrayLike( {} )\n    false\n\n    See Also\n    --------\n    isFloat32ndarrayLike, isndarrayLike\n","isFloat64VectorLike":"\nisFloat64VectorLike( value )\n    Tests if a value is a 1-dimensional ndarray-like object containing double-\n    precision floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 1-dimensional ndarray-like\n        object containing double-precision floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Float64Array( [ 0, 0, 0, 0 ] );\n    > M.ndims = 1;\n    > M.shape = [ 4 ];\n    > M.strides = [ 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'float64';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isFloat64VectorLike( M )\n    true\n    > bool = isFloat64VectorLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isFloat64VectorLike( 3.14 )\n    false\n    > bool = isFloat64VectorLike( {} )\n    false\n\n    See Also\n    --------\n    isFloat32VectorLike, isndarrayLike, isVectorLike\n","isFunction":"\nisFunction( value )\n    Tests if a value is a function.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a function.\n\n    Examples\n    --------\n    > function beep() {};\n    > var bool = isFunction( beep )\n    true\n    > bool = isFunction( {} )\n    false\n\n","isFunctionArray":"\nisFunctionArray( value )\n    Tests if a value is an array-like object containing only functions.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        functions.\n\n    Examples\n    --------\n    > function beep() {};\n    > function boop() {};\n    > var bool = isFunctionArray( [ beep, boop ] )\n    true\n    > bool = isFunctionArray( [ {}, beep ] )\n    false\n    > bool = isFunctionArray( [] )\n    false\n\n    See Also\n    --------\n    isArray\n","isGeneratorObject":"\nisGeneratorObject( value )\n    Tests if a value is a generator object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a generator object.\n\n    Examples\n    --------\n    > function* generateID() {\n    ...     var idx = 0;\n    ...     while ( idx < idx+1 ) {\n    ...         yield idx;\n    ...         idx += 1;\n    ...     }\n    ... };\n    > var bool = isGeneratorObject( generateID() )\n    true\n    > bool = isGeneratorObject( generateID )\n    false\n    > bool = isGeneratorObject( {} )\n    false\n    > bool = isGeneratorObject( null )\n    false\n\n    See Also\n    --------\n    hasGeneratorSupport, isGeneratorObjectLike\n","isGeneratorObjectLike":"\nisGeneratorObjectLike( value )\n    Tests if a value is generator object-like.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is generator object-like.\n\n    Examples\n    --------\n    > var obj = {\n    ...     'next': function noop() {},\n    ...     'return': function noop() {},\n    ...     'throw': function noop() {}\n    ... };\n    > var bool = isGeneratorObjectLike( obj )\n    true\n    > bool = isGeneratorObjectLike( {} )\n    false\n    > bool = isGeneratorObjectLike( null )\n    false\n\n    See Also\n    --------\n    hasGeneratorSupport, isGeneratorObject\n","isgzipBuffer":"\nisgzipBuffer( value )\n    Tests if a value is a gzip buffer.\n\n    A gzip buffer is defined as either a Node.js Buffer or Uint8Array which\n    contains a 10-byte header, a body containing the compressed payload, and an\n    8-byte footer containing a CRC-32 checksum and the length of the original\n    uncompressed data, modulo 2^32.\n\n    This function only examines the 10-byte header to ensure the header includes\n    the expected magic number and compression method. The function does not\n    perform an integrity check.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a gzip buffer.\n\n    Examples\n    --------\n    > var buf = new Uint8Array( 20 );\n    > buf[ 0 ] = 31;  // 0x1f => magic number\n    > buf[ 1 ] = 139; // 0x8b\n    > buf[ 2 ] = 8;   // 0x08 => compression method\n    > var bool = isgzipBuffer( buf )\n    true\n    > bool = isgzipBuffer( [] )\n    false\n\n    See Also\n    --------\n    isBuffer, isUint8Array\n","isHexString":"\nisHexString( str )\n    Tests whether a string contains only hexadecimal digits.\n\n    The function does not recognize `x` (as in the standard `0x` prefix).\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a string contains only hexadecimal digits.\n\n    Examples\n    --------\n    > var bool = isHexString( '0123456789abcdefABCDEF' )\n    true\n    > bool = isHexString( '0xffffff' )\n    false\n    > bool = isHexString( 'x' )\n    false\n    > bool = isHexString( '' )\n    false\n\n    See Also\n    --------\n    isString\n","isInfinite":"\nisInfinite( value )\n    Tests if a value is an infinite number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an infinite number.\n\n    Examples\n    --------\n    > var bool = isInfinite( 1.0/0.0 )\n    true\n    > bool = isInfinite( new Number( -1.0/0.0 ) )\n    true\n    > bool = isInfinite( 5.0 )\n    false\n    > bool = isInfinite( '1.0/0.0' )\n    false\n\n\nisInfinite.isPrimitive( value )\n    Tests if a value is a number primitive having an infinite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number primitive having an\n        infinite value.\n\n    Examples\n    --------\n    > var bool = isInfinite.isPrimitive( -1.0/0.0 )\n    true\n    > bool = isInfinite.isPrimitive( new Number( -1.0/0.0 ) )\n    false\n\n\nisInfinite.isObject( value )\n    Tests if a value is a number object having an infinite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number object having an infinite\n        value.\n\n    Examples\n    --------\n    > var bool = isInfinite.isObject( 1.0/0.0 )\n    false\n    > bool = isInfinite.isObject( new Number( 1.0/0.0 ) )\n    true\n\n    See Also\n    --------\n    isFinite\n","isInfinite.isPrimitive":"\nisInfinite.isPrimitive( value )\n    Tests if a value is a number primitive having an infinite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number primitive having an\n        infinite value.\n\n    Examples\n    --------\n    > var bool = isInfinite.isPrimitive( -1.0/0.0 )\n    true\n    > bool = isInfinite.isPrimitive( new Number( -1.0/0.0 ) )\n    false","isInfinite.isObject":"\nisInfinite.isObject( value )\n    Tests if a value is a number object having an infinite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number object having an infinite\n        value.\n\n    Examples\n    --------\n    > var bool = isInfinite.isObject( 1.0/0.0 )\n    false\n    > bool = isInfinite.isObject( new Number( 1.0/0.0 ) )\n    true\n\n    See Also\n    --------\n    isFinite","isInheritedProperty":"\nisInheritedProperty( value, property )\n    Tests if an object has an inherited property.\n\n    Value arguments other than `null` or `undefined` are coerced to objects.\n\n    Non-symbol property arguments are coerced to strings.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object has an inherited property.\n\n    Examples\n    --------\n    > var beep = { 'boop': true };\n    > var bool = isInheritedProperty( beep, 'boop' )\n    false\n    > bool = isInheritedProperty( beep, 'toString' )\n    true\n    > bool = isInheritedProperty( beep, 'bop' )\n    false\n\n    See Also\n    --------\n    hasOwnProp, hasProp\n","isInt8Array":"\nisInt8Array( value )\n    Tests if a value is an Int8Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an Int8Array.\n\n    Examples\n    --------\n    > var bool = isInt8Array( new Int8Array( 10 ) )\n    true\n    > bool = isInt8Array( [] )\n    false\n\n    See Also\n    --------\n    isInt16Array, isInt32Array\n","isInt16Array":"\nisInt16Array( value )\n    Tests if a value is an Int16Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an Int16Array.\n\n    Examples\n    --------\n    > var bool = isInt16Array( new Int16Array( 10 ) )\n    true\n    > bool = isInt16Array( [] )\n    false\n\n    See Also\n    --------\n    isInt32Array, isInt8Array\n","isInt32Array":"\nisInt32Array( value )\n    Tests if a value is an Int32Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an Int32Array.\n\n    Examples\n    --------\n    > var bool = isInt32Array( new Int32Array( 10 ) )\n    true\n    > bool = isInt32Array( [] )\n    false\n\n    See Also\n    --------\n    isInt16Array, isInt8Array\n","isInteger":"\nisInteger( value )\n    Tests if a value is an integer.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an integer.\n\n    Examples\n    --------\n    > var bool = isInteger( 5.0 )\n    true\n    > bool = isInteger( new Number( 5.0 ) )\n    true\n    > bool = isInteger( -3.14 )\n    false\n    > bool = isInteger( null )\n    false\n\n\nisInteger.isPrimitive( value )\n    Tests if a value is a number primitive having an integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having an integer\n        value.\n\n    Examples\n    --------\n    > var bool = isInteger.isPrimitive( -3.0 )\n    true\n    > bool = isInteger.isPrimitive( new Number( -3.0 ) )\n    false\n\n\nisInteger.isObject( value )\n    Tests if a value is a number object having an integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having an integer\n        value.\n\n    Examples\n    --------\n    > var bool = isInteger.isObject( 3.0 )\n    false\n    > bool = isInteger.isObject( new Number( 3.0 ) )\n    true\n\n    See Also\n    --------\n    isNumber\n","isInteger.isPrimitive":"\nisInteger.isPrimitive( value )\n    Tests if a value is a number primitive having an integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having an integer\n        value.\n\n    Examples\n    --------\n    > var bool = isInteger.isPrimitive( -3.0 )\n    true\n    > bool = isInteger.isPrimitive( new Number( -3.0 ) )\n    false","isInteger.isObject":"\nisInteger.isObject( value )\n    Tests if a value is a number object having an integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having an integer\n        value.\n\n    Examples\n    --------\n    > var bool = isInteger.isObject( 3.0 )\n    false\n    > bool = isInteger.isObject( new Number( 3.0 ) )\n    true\n\n    See Also\n    --------\n    isNumber","isIntegerArray":"\nisIntegerArray( value )\n    Tests if a value is an array-like object of integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object of integer\n        values.\n\n    Examples\n    --------\n    > var bool = isIntegerArray( [ -3.0, new Number(0.0), 2.0 ] )\n    true\n    > bool = isIntegerArray( [ -3.0, '3.0' ] )\n    false\n\n\nisIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive integer\n    values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only primitive integer values.\n\n    Examples\n    --------\n    > var bool = isIntegerArray.primitives( [ -1.0, 10.0 ] )\n    true\n    > bool = isIntegerArray.primitives( [ -1.0, 0.0, 5.0 ] )\n    true\n    > bool = isIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false\n\n\nisIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only number objects having integer values.\n\n    Examples\n    --------\n    > var bool = isIntegerArray.objects( [ new Number(1.0), new Number(3.0) ] )\n    true\n    > bool = isIntegerArray.objects( [ -1.0, 0.0, 3.0 ] )\n    false\n    > bool = isIntegerArray.objects( [ 3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray\n","isIntegerArray.primitives":"\nisIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive integer\n    values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only primitive integer values.\n\n    Examples\n    --------\n    > var bool = isIntegerArray.primitives( [ -1.0, 10.0 ] )\n    true\n    > bool = isIntegerArray.primitives( [ -1.0, 0.0, 5.0 ] )\n    true\n    > bool = isIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false","isIntegerArray.objects":"\nisIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only number objects having integer values.\n\n    Examples\n    --------\n    > var bool = isIntegerArray.objects( [ new Number(1.0), new Number(3.0) ] )\n    true\n    > bool = isIntegerArray.objects( [ -1.0, 0.0, 3.0 ] )\n    false\n    > bool = isIntegerArray.objects( [ 3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray","isIterableLike":"\nisIterableLike( value )\n    Tests if a value is iterable-like.\n\n    In order to be iterable, an object must implement the @@iterator method,\n    which, when called, returns an iterator protocol-compliant object.\n\n    An iterator protocol-compliant object is an object having a `next` method\n    which adheres to the iterator protocol.\n\n    As full iterator compliance is impossible to achieve without evaluating an\n    iterator, this function checks *only* for interface compliance.\n\n    In environments lacking Symbol.iterator support, this function always\n    returns `false`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is iterable-like.\n\n    Examples\n    --------\n    > var bool = isIterableLike( [ 1, 2, 3 ] )\n    <boolean>\n    > bool = isIterableLike( {} )\n    false\n    > bool = isIterableLike( null )\n    false\n\n    See Also\n    --------\n    isIteratorLike\n","isIteratorLike":"\nisIteratorLike( value )\n    Tests if a value is iterator-like.\n\n    An iterator protocol-compliant object is an object having a `next` method\n    which adheres to the iterator protocol.\n\n    As full iterator compliance is impossible to achieve without evaluating an\n    iterator, this function checks *only* for interface compliance.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is iterator-like.\n\n    Examples\n    --------\n    > var obj = {\n    ...     'next': function noop() {}\n    ... };\n    > var bool = isIteratorLike( obj )\n    true\n    > bool = isIteratorLike( {} )\n    false\n    > bool = isIteratorLike( null )\n    false\n\n    See Also\n    --------\n    isIterableLike\n","isJSON":"\nisJSON( value )\n    Tests if a value is a parseable JSON string.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a parseable JSON string.\n\n    Examples\n    --------\n    > var bool = isJSON( '{\"a\":5}' )\n    true\n    > bool = isJSON( '{a\":5}' )\n    false\n\n","isKebabcase":"\nisKebabcase( value )\n    Tests if a value is a string in kebab case.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a string in kebab case.\n\n    Examples\n    --------\n    > var bool = isKebabcase( 'beep-boop' )\n    true\n    > bool = isKebabcase( 'BEEP_BOOP' )\n    false\n\n    See Also\n    --------\n    isString","isLeapYear":"\nisLeapYear( value )\n    Tests whether a value corresponds to a leap year in the Gregorian calendar.\n\n    A leap year is defined as any year which is exactly divisible by 4, except\n    for years which are exactly divisible by 100 and not by 400. In this\n    definition, 100 corresponds to years marking a new century, and 400\n    corresponds to the length of the *leap cycle*.\n\n    If not provided any arguments, the function returns a boolean indicating\n    if the current year (according to local time) is a leap year.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value corresponds to a leap year.\n\n    Examples\n    --------\n    > var bool = isLeapYear( new Date() )\n    <boolean>\n    > bool = isLeapYear( 1996 )\n    true\n    > bool = isLeapYear( 2001 )\n    false\n\n","isLocalhost":"\nisLocalhost( value )\n    Tests whether a value is a localhost hostname.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a localhost hostname.\n\n    Examples\n    --------\n    > var bool = isLocalhost( 'localhost' )\n    true\n    > bool = isLocalhost( '127.0.0.1' )\n    true\n    > bool = isLocalhost( 'stdlib.io' )\n    false\n","isLowercase":"\nisLowercase( value )\n    Tests if a value is a lowercase string.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a lowercase string.\n\n    Examples\n    --------\n    > var bool = isLowercase( 'hello' )\n    true\n    > bool = isLowercase( 'World' )\n    false\n\n    See Also\n    --------\n    isString, isUppercase\n","isMatrixLike":"\nisMatrixLike( value )\n    Tests if a value is a 2-dimensional ndarray-like object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 2-dimensional ndarray-like\n        object.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = [ 0, 0, 0, 0 ];\n    > M.ndims = 2;\n    > M.shape = [ 2, 2 ];\n    > M.strides = [ 2, 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'generic';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isMatrixLike( M )\n    true\n    > bool = isMatrixLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isMatrixLike( 3.14 )\n    false\n    > bool = isMatrixLike( {} )\n    false\n\n    See Also\n    --------\n    isArray, isArrayLike, isndarrayLike, isTypedArrayLike, isVectorLike\n","isMethod":"\nisMethod( value, property )\n    Tests if an object has a specified method name.\n\n    Value arguments other than `null` or `undefined` are coerced to objects.\n\n    Property arguments are coerced to strings.\n\n    The function only searches own properties.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object has a specified method name.\n\n    Examples\n    --------\n    > var beep = { 'boop': function beep() { return 'beep'; } };\n    > var bool = isMethod( beep, 'boop' )\n    true\n    > bool = isMethod( beep, 'toString' )\n    false\n\n    See Also\n    --------\n    hasOwnProp, isFunction, isMethodIn\n","isMethodIn":"\nisMethodIn( value, property )\n    Tests if an object has a specified method name, either own or inherited.\n\n    Value arguments other than `null` or `undefined` are coerced to objects.\n\n    Non-symbol property arguments are coerced to strings.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object has a specified method name.\n\n    Examples\n    --------\n    > var beep = { 'boop': true };\n    > var bool = isMethodIn( beep, 'toString' )\n    true\n    > bool = isMethodIn( beep, 'boop' )\n    false\n    > bool = isMethodIn( beep, 'bop' )\n    false\n\n    See Also\n    --------\n    hasProp, isFunction, isMethod\n","isMultiSlice":"\nisMultiSlice( value )\n    Tests if a value is a MultiSlice object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a MultiSlice object.\n\n    Examples\n    --------\n    > var bool = isMultiSlice( new MultiSlice() )\n    true\n    > bool = isMultiSlice( 3.14 )\n    false\n    > bool = isMultiSlice( {} )\n    false\n\n    See Also\n    --------\n    isSlice, MultiSlice\n","isNamedTypedTupleLike":"\nisNamedTypedTupleLike( value )\n    Tests if a value is named typed tuple-like.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is named typed tuple-like.\n\n    Examples\n    --------\n    > var Point = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = new Point();\n    > var bool = isNamedTypedTupleLike( p )\n    true\n    > bool = isNamedTypedTupleLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isNamedTypedTupleLike( 3.14 )\n    false\n    > bool = isNamedTypedTupleLike( {} )\n    false\n\n    See Also\n    --------\n    namedtypedtuple\n","isnan":"\nisnan( value )\n    Tests if a value is NaN.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is NaN.\n\n    Examples\n    --------\n    > var bool = isnan( NaN )\n    true\n    > bool = isnan( new Number( NaN ) )\n    true\n    > bool = isnan( 3.14 )\n    false\n    > bool = isnan( null )\n    false\n\n\nisnan.isPrimitive( value )\n    Tests if a value is a NaN number primitive.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a NaN number primitive.\n\n    Examples\n    --------\n    > var bool = isnan.isPrimitive( NaN )\n    true\n    > bool = isnan.isPrimitive( 3.14 )\n    false\n    > bool = isnan.isPrimitive( new Number( NaN ) )\n    false\n\n\nisnan.isObject( value )\n    Tests if a value is a number object having a value of NaN.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value of\n        NaN.\n\n    Examples\n    --------\n    > var bool = isnan.isObject( NaN )\n    false\n    > bool = isnan.isObject( new Number( NaN ) )\n    true\n\n    See Also\n    --------\n    isNumber\n","isnan.isPrimitive":"\nisnan.isPrimitive( value )\n    Tests if a value is a NaN number primitive.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a NaN number primitive.\n\n    Examples\n    --------\n    > var bool = isnan.isPrimitive( NaN )\n    true\n    > bool = isnan.isPrimitive( 3.14 )\n    false\n    > bool = isnan.isPrimitive( new Number( NaN ) )\n    false","isnan.isObject":"\nisnan.isObject( value )\n    Tests if a value is a number object having a value of NaN.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value of\n        NaN.\n\n    Examples\n    --------\n    > var bool = isnan.isObject( NaN )\n    false\n    > bool = isnan.isObject( new Number( NaN ) )\n    true\n\n    See Also\n    --------\n    isNumber","isNaNArray":"\nisNaNArray( value )\n    Tests if a value is an array-like object containing only NaN values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        NaN values.\n\n    Examples\n    --------\n    > var bool = isNaNArray( [ NaN, NaN, NaN ] )\n    true\n    > bool = isNaNArray( [ NaN, 2 ] )\n    false\n\n\nisNaNArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive NaN\n    values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive NaN values.\n\n    Examples\n    --------\n    > var bool = isNaNArray.primitives( [ NaN, new Number( NaN ) ] )\n    false\n    > bool = isNaNArray.primitives( [ NaN, NaN, NaN ] )\n    true\n\n\nisNaNArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having NaN values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having NaN values.\n\n    Examples\n    --------\n    > var bool = isNaNArray.objects( [ new Number( NaN ), new Number( NaN ) ] )\n    true\n    > bool = isNaNArray.objects( [ NaN, new Number( NaN ), new Number( NaN ) ] )\n    false\n    > bool = isNaNArray.objects( [ NaN, NaN, NaN ] )\n    false\n\n    See Also\n    --------\n    isnan\n","isNaNArray.primitives":"\nisNaNArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive NaN\n    values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive NaN values.\n\n    Examples\n    --------\n    > var bool = isNaNArray.primitives( [ NaN, new Number( NaN ) ] )\n    false\n    > bool = isNaNArray.primitives( [ NaN, NaN, NaN ] )\n    true","isNaNArray.objects":"\nisNaNArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having NaN values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having NaN values.\n\n    Examples\n    --------\n    > var bool = isNaNArray.objects( [ new Number( NaN ), new Number( NaN ) ] )\n    true\n    > bool = isNaNArray.objects( [ NaN, new Number( NaN ), new Number( NaN ) ] )\n    false\n    > bool = isNaNArray.objects( [ NaN, NaN, NaN ] )\n    false\n\n    See Also\n    --------\n    isnan","isNativeFunction":"\nisNativeFunction( value )\n    Tests if a value is a native function.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a native function.\n\n    Examples\n    --------\n    > var bool = isNativeFunction( Date )\n    true\n    > function beep() {};\n    > bool = isNativeFunction( beep )\n    false\n    > bool = isNativeFunction( {} )\n    false\n\n    See Also\n    --------\n    isFunction\n","isndarrayLike":"\nisndarrayLike( value )\n    Tests if a value is ndarray-like.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is ndarray-like.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = [ 0, 0, 0, 0 ];\n    > M.ndims = 2;\n    > M.shape = [ 2, 2 ];\n    > M.strides = [ 2, 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'generic';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isndarrayLike( M )\n    true\n    > bool = isndarrayLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isndarrayLike( 3.14 )\n    false\n    > bool = isndarrayLike( {} )\n    false\n\n    See Also\n    --------\n    isArray, isArrayLike, isMatrixLike, isTypedArrayLike, isVectorLike\n","isndarrayLikeWithDataType":"\nisndarrayLikeWithDataType( value, dtype )\n    Tests if a value is an ndarray-like object having a specified data type.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    dtype: any\n        Data type value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an ndarray-like object having a\n        specified data type.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = [ 0, 0, 0, 0 ];\n    > M.ndims = 2;\n    > M.shape = [ 2, 2 ];\n    > M.strides = [ 2, 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'generic';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isndarrayLikeWithDataType( M, 'generic' )\n    true\n    > bool = isndarrayLikeWithDataType( [ 1, 2, 3, 4 ], 'generic' )\n    false\n    > bool = isndarrayLikeWithDataType( 3.14, 'generic' )\n    false\n    > bool = isndarrayLikeWithDataType( {}, 'generic' )\n    false\n\n    See Also\n    --------\n    isndarrayLike\n","isNegativeFinite":"\nisNegativeFinite( value )\n    Tests if a value is a finite negative number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a finite negative number.\n\n    Examples\n    --------\n    > var bool = isNegativeFinite( -5.0 )\n    true\n    > bool = isNegativeFinite( new Number( -5.0 ) )\n    true\n    > bool = isNegativeFinite( -3.14 )\n    true\n    > bool = isNegativeFinite( 5.0 )\n    false\n    > bool = isNegativeFinite( null )\n    false\n    > bool = isNegativeFinite( -1.0/0.0 )\n    false\n    > bool = isNegativeFinite( new Number( -1.0/0.0 ) )\n    false\n\n\nisNegativeFinite.isPrimitive( value )\n    Tests if a value is a number primitive having a finite negative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number primitive having a finite\n        negative value.\n\n    Examples\n    --------\n    > var bool = isNegativeFinite.isPrimitive( -3.0 )\n    true\n    > bool = isNegativeFinite.isPrimitive( new Number( -3.0 ) )\n    false\n    > var bool = isNegativeFinite.isPrimitive( -1.0/0.0 )\n    false\n    > bool = isNegativeFinite.isPrimitive( new Number( -1.0/0.0 ) )\n    false\n\n\nisNegativeFinite.isObject( value )\n    Tests if a value is a number object having a finite negative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number object having a finite\n        negative value.\n\n    Examples\n    --------\n    > var bool = isNegativeFinite.isObject( -3.0 )\n    false\n    > bool = isNegativeFinite.isObject( new Number( -3.0 ) )\n    true\n    > bool = isNegativeFinite.isObject( -1.0/0.0 )\n    false\n    > bool = isNegativeFinite.isObject( new Number( -1.0/0.0 ) )\n    false\n\n    See Also\n    --------\n    isFinite, isNegativeNumber, isPositiveFinite\n","isNegativeFinite.isPrimitive":"\nisNegativeFinite.isPrimitive( value )\n    Tests if a value is a number primitive having a finite negative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number primitive having a finite\n        negative value.\n\n    Examples\n    --------\n    > var bool = isNegativeFinite.isPrimitive( -3.0 )\n    true\n    > bool = isNegativeFinite.isPrimitive( new Number( -3.0 ) )\n    false\n    > var bool = isNegativeFinite.isPrimitive( -1.0/0.0 )\n    false\n    > bool = isNegativeFinite.isPrimitive( new Number( -1.0/0.0 ) )\n    false","isNegativeFinite.isObject":"\nisNegativeFinite.isObject( value )\n    Tests if a value is a number object having a finite negative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number object having a finite\n        negative value.\n\n    Examples\n    --------\n    > var bool = isNegativeFinite.isObject( -3.0 )\n    false\n    > bool = isNegativeFinite.isObject( new Number( -3.0 ) )\n    true\n    > bool = isNegativeFinite.isObject( -1.0/0.0 )\n    false\n    > bool = isNegativeFinite.isObject( new Number( -1.0/0.0 ) )\n    false\n\n    See Also\n    --------\n    isFinite, isNegativeNumber, isPositiveFinite","isNegativeInteger":"\nisNegativeInteger( value )\n    Tests if a value is a negative integer.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a negative integer.\n\n    Examples\n    --------\n    > var bool = isNegativeInteger( -5.0 )\n    true\n    > bool = isNegativeInteger( new Number( -5.0 ) )\n    true\n    > bool = isNegativeInteger( 5.0 )\n    false\n    > bool = isNegativeInteger( -3.14 )\n    false\n    > bool = isNegativeInteger( null )\n    false\n\n\nisNegativeInteger.isPrimitive( value )\n    Tests if a value is a number primitive having a negative integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a negative\n        integer value.\n\n    Examples\n    --------\n    > var bool = isNegativeInteger.isPrimitive( -3.0 )\n    true\n    > bool = isNegativeInteger.isPrimitive( new Number( -3.0 ) )\n    false\n\n\nisNegativeInteger.isObject( value )\n    Tests if a value is a number object having a negative integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a negative\n        integer value.\n\n    Examples\n    --------\n    > var bool = isNegativeInteger.isObject( -3.0 )\n    false\n    > bool = isNegativeInteger.isObject( new Number( -3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger\n","isNegativeInteger.isPrimitive":"\nisNegativeInteger.isPrimitive( value )\n    Tests if a value is a number primitive having a negative integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a negative\n        integer value.\n\n    Examples\n    --------\n    > var bool = isNegativeInteger.isPrimitive( -3.0 )\n    true\n    > bool = isNegativeInteger.isPrimitive( new Number( -3.0 ) )\n    false","isNegativeInteger.isObject":"\nisNegativeInteger.isObject( value )\n    Tests if a value is a number object having a negative integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a negative\n        integer value.\n\n    Examples\n    --------\n    > var bool = isNegativeInteger.isObject( -3.0 )\n    false\n    > bool = isNegativeInteger.isObject( new Number( -3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger","isNegativeIntegerArray":"\nisNegativeIntegerArray( value )\n    Tests if a value is an array-like object containing only negative integers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        negative integers.\n\n    Examples\n    --------\n    > var bool = isNegativeIntegerArray( [ -3.0, new Number(-3.0) ] )\n    true\n    > bool = isNegativeIntegerArray( [ -3.0, '-3.0' ] )\n    false\n\n\nisNegativeIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only negative primitive\n    integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        negative primitive integer values.\n\n    Examples\n    --------\n    > var bool = isNegativeIntegerArray.primitives( [ -1.0, -10.0 ] )\n    true\n    > bool = isNegativeIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNegativeIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false\n\n\nisNegativeIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having negative integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having negative integer values.\n\n    Examples\n    --------\n    > var bool = isNegativeIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n    true\n    > bool = isNegativeIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNegativeIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray\n","isNegativeIntegerArray.primitives":"\nisNegativeIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only negative primitive\n    integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        negative primitive integer values.\n\n    Examples\n    --------\n    > var bool = isNegativeIntegerArray.primitives( [ -1.0, -10.0 ] )\n    true\n    > bool = isNegativeIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNegativeIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false","isNegativeIntegerArray.objects":"\nisNegativeIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having negative integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having negative integer values.\n\n    Examples\n    --------\n    > var bool = isNegativeIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n    true\n    > bool = isNegativeIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNegativeIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray","isNegativeNumber":"\nisNegativeNumber( value )\n    Tests if a value is a negative number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a negative number.\n\n    Examples\n    --------\n    > var bool = isNegativeNumber( -5.0 )\n    true\n    > bool = isNegativeNumber( new Number( -5.0 ) )\n    true\n    > bool = isNegativeNumber( -3.14 )\n    true\n    > bool = isNegativeNumber( 5.0 )\n    false\n    > bool = isNegativeNumber( null )\n    false\n\n\nisNegativeNumber.isPrimitive( value )\n    Tests if a value is a number primitive having a negative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a negative\n        value.\n\n    Examples\n    --------\n    > var bool = isNegativeNumber.isPrimitive( -3.0 )\n    true\n    > bool = isNegativeNumber.isPrimitive( new Number( -3.0 ) )\n    false\n\n\nisNegativeNumber.isObject( value )\n    Tests if a value is a number object having a negative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a negative\n        value.\n\n    Examples\n    --------\n    > var bool = isNegativeNumber.isObject( -3.0 )\n    false\n    > bool = isNegativeNumber.isObject( new Number( -3.0 ) )\n    true\n\n    See Also\n    --------\n    isNumber\n","isNegativeNumber.isPrimitive":"\nisNegativeNumber.isPrimitive( value )\n    Tests if a value is a number primitive having a negative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a negative\n        value.\n\n    Examples\n    --------\n    > var bool = isNegativeNumber.isPrimitive( -3.0 )\n    true\n    > bool = isNegativeNumber.isPrimitive( new Number( -3.0 ) )\n    false","isNegativeNumber.isObject":"\nisNegativeNumber.isObject( value )\n    Tests if a value is a number object having a negative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a negative\n        value.\n\n    Examples\n    --------\n    > var bool = isNegativeNumber.isObject( -3.0 )\n    false\n    > bool = isNegativeNumber.isObject( new Number( -3.0 ) )\n    true\n\n    See Also\n    --------\n    isNumber","isNegativeNumberArray":"\nisNegativeNumberArray( value )\n    Tests if a value is an array-like object containing only negative numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        negative numbers.\n\n    Examples\n    --------\n    > var bool = isNegativeNumberArray( [ -3.0, new Number(-3.0) ] )\n    true\n    > bool = isNegativeNumberArray( [ -3.0, '-3.0' ] )\n    false\n\n\nisNegativeNumberArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive negative\n    numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive negative numbers.\n\n    Examples\n    --------\n    > var bool = isNegativeNumberArray.primitives( [ -1.0, -10.0 ] )\n    true\n    > bool = isNegativeNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNegativeNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false\n\n\nisNegativeNumberArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having negative number values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having negative number values.\n\n    Examples\n    --------\n    > var bool = isNegativeNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n    true\n    > bool = isNegativeNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNegativeNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray\n","isNegativeNumberArray.primitives":"\nisNegativeNumberArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive negative\n    numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive negative numbers.\n\n    Examples\n    --------\n    > var bool = isNegativeNumberArray.primitives( [ -1.0, -10.0 ] )\n    true\n    > bool = isNegativeNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNegativeNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false","isNegativeNumberArray.objects":"\nisNegativeNumberArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having negative number values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having negative number values.\n\n    Examples\n    --------\n    > var bool = isNegativeNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n    true\n    > bool = isNegativeNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNegativeNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray","isNegativeZero":"\nisNegativeZero( value )\n    Tests if a value is negative zero.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is negative zero.\n\n    Examples\n    --------\n    > var bool = isNegativeZero( -0.0 )\n    true\n    > bool = isNegativeZero( new Number( -0.0 ) )\n    true\n    > bool = isNegativeZero( -3.14 )\n    false\n    > bool = isNegativeZero( 0.0 )\n    false\n    > bool = isNegativeZero( null )\n    false\n\n\nisNegativeZero.isPrimitive( value )\n    Tests if a value is a number primitive equal to negative zero.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number primitive equal to\n        negative zero.\n\n    Examples\n    --------\n    > var bool = isNegativeZero.isPrimitive( -0.0 )\n    true\n    > bool = isNegativeZero.isPrimitive( new Number( -0.0 ) )\n    false\n\n\nisNegativeZero.isObject( value )\n    Tests if a value is a number object having a value equal to negative zero.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number object having a value\n        equal to negative zero.\n\n    Examples\n    --------\n    > var bool = isNegativeZero.isObject( -0.0 )\n    false\n    > bool = isNegativeZero.isObject( new Number( -0.0 ) )\n    true\n\n    See Also\n    --------\n    isNumber, isPositiveZero\n","isNegativeZero.isPrimitive":"\nisNegativeZero.isPrimitive( value )\n    Tests if a value is a number primitive equal to negative zero.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number primitive equal to\n        negative zero.\n\n    Examples\n    --------\n    > var bool = isNegativeZero.isPrimitive( -0.0 )\n    true\n    > bool = isNegativeZero.isPrimitive( new Number( -0.0 ) )\n    false","isNegativeZero.isObject":"\nisNegativeZero.isObject( value )\n    Tests if a value is a number object having a value equal to negative zero.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number object having a value\n        equal to negative zero.\n\n    Examples\n    --------\n    > var bool = isNegativeZero.isObject( -0.0 )\n    false\n    > bool = isNegativeZero.isObject( new Number( -0.0 ) )\n    true\n\n    See Also\n    --------\n    isNumber, isPositiveZero","isNodeBuiltin":"\nisNodeBuiltin( str )\n    Tests whether a string matches a Node.js built-in module name.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a string matches a Node.js built-in module\n        name.\n\n    Examples\n    --------\n    > var bool = isNodeBuiltin( 'cluster' )\n    true\n    > bool = isNodeBuiltin( 'crypto' )\n    true\n    > bool = isNodeBuiltin( 'fs-extra' )\n    false\n    > bool = isNodeBuiltin( '' )\n    false\n\n","isNodeDuplexStreamLike":"\nisNodeDuplexStreamLike( value )\n    Tests if a value is Node duplex stream-like.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is Node duplex stream-like.\n\n    Examples\n    --------\n    > var Stream = require( 'stream' ).Duplex;\n    > s = new Stream();\n    > var bool = isNodeDuplexStreamLike( s )\n    true\n    > bool = isNodeDuplexStreamLike( {} )\n    false\n\n    See Also\n    --------\n    isNodeStreamLike\n","isNodeReadableStreamLike":"\nisNodeReadableStreamLike( value )\n    Tests if a value is Node readable stream-like.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is Node readable stream-like.\n\n    Examples\n    --------\n    > var Stream = require( 'stream' ).Readable;\n    > s = new Stream();\n    > var bool = isNodeReadableStreamLike( s )\n    true\n    > bool = isNodeReadableStreamLike( {} )\n    false\n\n    See Also\n    --------\n    isNodeStreamLike\n","isNodeREPL":"\nisNodeREPL()\n    Returns a boolean indicating if running in a Node.js REPL environment.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if running in a Node.js REPL environment.\n\n    Examples\n    --------\n    > var bool = isNodeREPL()\n    <boolean>\n\n","isNodeStreamLike":"\nisNodeStreamLike( value )\n    Tests if a value is Node stream-like.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is Node stream-like.\n\n    Examples\n    --------\n    > var Stream = require( 'stream' ).Stream;\n    > s = new Stream();\n    > var bool = isNodeStreamLike( s )\n    true\n    > bool = isNodeStreamLike( {} )\n    false\n\n","isNodeTransformStreamLike":"\nisNodeTransformStreamLike( value )\n    Tests if a value is Node transform stream-like.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is Node transform stream-like.\n\n    Examples\n    --------\n    > var Stream = require( 'stream' ).Transform;\n    > s = new Stream();\n    > var bool = isNodeTransformStreamLike( s )\n    true\n    > bool = isNodeTransformStreamLike( {} )\n    false\n\n    See Also\n    --------\n    isNodeStreamLike\n","isNodeWritableStreamLike":"\nisNodeWritableStreamLike( value )\n    Tests if a value is Node writable stream-like.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is Node writable stream-like.\n\n    Examples\n    --------\n    > var Stream = require( 'stream' ).Writable;\n    > s = new Stream();\n    > var bool = isNodeWritableStreamLike( s )\n    true\n    > bool = isNodeWritableStreamLike( {} )\n    false\n\n    See Also\n    --------\n    isNodeStreamLike\n","isNonConfigurableProperty":"\nisNonConfigurableProperty( value, property )\n    Tests if an object's own property is non-configurable.\n\n    A non-configurable property is a property which cannot be deleted and whose\n    descriptor cannot be changed.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own property is non-configurable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = true;\n    > desc.writable = true;\n    > desc.value = 'beep';\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isNonConfigurableProperty( obj, 'boop' )\n    false\n    > bool = isNonConfigurableProperty( obj, 'beep' )\n    true\n\n    See Also\n    --------\n    isConfigurableProperty, isEnumerableProperty, isNonConfigurablePropertyIn, isNonEnumerableProperty, isReadableProperty, isWritableProperty\n","isNonConfigurablePropertyIn":"\nisNonConfigurablePropertyIn( value, property )\n    Tests if an object's own or inherited property is non-configurable.\n\n    A non-configurable property is a property which cannot be deleted and whose\n    descriptor cannot be changed.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own or inherited property is non-\n        configurable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = true;\n    > desc.writable = true;\n    > desc.value = true;\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isNonConfigurablePropertyIn( obj, 'boop' )\n    false\n    > bool = isNonConfigurablePropertyIn( obj, 'beep' )\n    true\n\n    See Also\n    --------\n    isConfigurablePropertyIn, isEnumerablePropertyIn, isNonConfigurableProperty, isNonEnumerablePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isNonEnumerableProperty":"\nisNonEnumerableProperty( value, property )\n    Tests if an object's own property is non-enumerable.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own property is non-enumerable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.writable = true;\n    > desc.value = 'beep';\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isNonEnumerableProperty( obj, 'boop' )\n    false\n    > bool = isNonEnumerableProperty( obj, 'beep' )\n    true\n\n    See Also\n    --------\n    isConfigurableProperty, isEnumerableProperty, isNonConfigurableProperty, isNonEnumerablePropertyIn, isReadableProperty, isWritableProperty\n","isNonEnumerablePropertyIn":"\nisNonEnumerablePropertyIn( value, property )\n    Tests if an object's own or inherited property is non-enumerable.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own or inherited property is non-\n        enumerable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = true;\n    > desc.enumerable = false;\n    > desc.writable = true;\n    > desc.value = true;\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isNonEnumerablePropertyIn( obj, 'boop' )\n    false\n    > bool = isNonEnumerablePropertyIn( obj, 'beep' )\n    true\n\n    See Also\n    --------\n    isConfigurablePropertyIn, isEnumerablePropertyIn, isNonConfigurablePropertyIn, isNonEnumerableProperty, isReadablePropertyIn, isWritablePropertyIn\n","isNonNegativeFinite":"\nisNonNegativeFinite( value )\n    Tests if a value is a nonnegative finite number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a nonnegative finite number.\n\n    Examples\n    --------\n    > var bool = isNonNegativeFinite( 5.0 )\n    true\n    > bool = isNonNegativeFinite( new Number( 5.0 ) )\n    true\n    > bool = isNonNegativeFinite( 3.14 )\n    true\n    > bool = isNonNegativeFinite( -5.0 )\n    false\n    > bool = isNonNegativeFinite( null )\n    false\n    > bool = isNonNegativeFinite( PINF )\n    false\n\n\nisNonNegativeFinite.isPrimitive( value )\n    Tests if a value is a number primitive having a nonnegative finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonnegative finite value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeFinite.isPrimitive( 3.0 )\n    true\n    > bool = isNonNegativeFinite.isPrimitive( new Number( 3.0 ) )\n    false\n\n\nisNonNegativeFinite.isObject( value )\n    Tests if a value is a number object having a nonnegative finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a \n        nonnegative finite value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeFinite.isObject( 3.0 )\n    false\n    > bool = isNonNegativeFinite.isObject( new Number( 3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isFinite, isNonNegativeNumber, isNumber\n","isNonNegativeFinite.isPrimitive":"\nisNonNegativeFinite.isPrimitive( value )\n    Tests if a value is a number primitive having a nonnegative finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonnegative finite value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeFinite.isPrimitive( 3.0 )\n    true\n    > bool = isNonNegativeFinite.isPrimitive( new Number( 3.0 ) )\n    false","isNonNegativeFinite.isObject":"\nisNonNegativeFinite.isObject( value )\n    Tests if a value is a number object having a nonnegative finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a \n        nonnegative finite value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeFinite.isObject( 3.0 )\n    false\n    > bool = isNonNegativeFinite.isObject( new Number( 3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isFinite, isNonNegativeNumber, isNumber","isNonNegativeInteger":"\nisNonNegativeInteger( value )\n    Tests if a value is a nonnegative integer.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a nonnegative integer.\n\n    Examples\n    --------\n    > var bool = isNonNegativeInteger( 5.0 )\n    true\n    > bool = isNonNegativeInteger( new Number( 5.0 ) )\n    true\n    > bool = isNonNegativeInteger( 3.14 )\n    false\n    > bool = isNonNegativeInteger( -5.0 )\n    false\n    > bool = isNonNegativeInteger( null )\n    false\n\n\nisNonNegativeInteger.isPrimitive( value )\n    Tests if a value is a number primitive having a nonnegative integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonnegative integer value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeInteger.isPrimitive( 3.0 )\n    true\n    > bool = isNonNegativeInteger.isPrimitive( new Number( 3.0 ) )\n    false\n\n\nisNonNegativeInteger.isObject( value )\n    Tests if a value is a number object having a nonnegative integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a nonnegative\n        integer value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeInteger.isObject( 3.0 )\n    false\n    > bool = isNonNegativeInteger.isObject( new Number( 3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger, isNonNegativeNumber, isNumber\n","isNonNegativeInteger.isPrimitive":"\nisNonNegativeInteger.isPrimitive( value )\n    Tests if a value is a number primitive having a nonnegative integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonnegative integer value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeInteger.isPrimitive( 3.0 )\n    true\n    > bool = isNonNegativeInteger.isPrimitive( new Number( 3.0 ) )\n    false","isNonNegativeInteger.isObject":"\nisNonNegativeInteger.isObject( value )\n    Tests if a value is a number object having a nonnegative integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a nonnegative\n        integer value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeInteger.isObject( 3.0 )\n    false\n    > bool = isNonNegativeInteger.isObject( new Number( 3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger, isNonNegativeNumber, isNumber","isNonNegativeIntegerArray":"\nisNonNegativeIntegerArray( value )\n    Tests if a value is an array-like object containing only nonnegative\n    integers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        nonnegative integers.\n\n    Examples\n    --------\n    > var bool = isNonNegativeIntegerArray( [ 3.0, new Number(3.0) ] )\n    true\n    > bool = isNonNegativeIntegerArray( [ 3.0, '3.0' ] )\n    false\n\n\nisNonNegativeIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only nonnegative\n    primitive integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        nonnegative primitive integer values.\n\n    Examples\n    --------\n    > var bool = isNonNegativeIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n    true\n    > bool = isNonNegativeIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n    false\n\n\nisNonNegativeIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having nonnegative integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having nonnegative integer values.\n\n    Examples\n    --------\n    > var bool = isNonNegativeIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n    true\n    > bool = isNonNegativeIntegerArray.objects( [ 1.0, 0.0, 10.0 ] )\n    false\n    > bool = isNonNegativeIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray\n","isNonNegativeIntegerArray.primitives":"\nisNonNegativeIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only nonnegative\n    primitive integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        nonnegative primitive integer values.\n\n    Examples\n    --------\n    > var bool = isNonNegativeIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n    true\n    > bool = isNonNegativeIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n    false","isNonNegativeIntegerArray.objects":"\nisNonNegativeIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having nonnegative integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having nonnegative integer values.\n\n    Examples\n    --------\n    > var bool = isNonNegativeIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n    true\n    > bool = isNonNegativeIntegerArray.objects( [ 1.0, 0.0, 10.0 ] )\n    false\n    > bool = isNonNegativeIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray","isNonNegativeNumber":"\nisNonNegativeNumber( value )\n    Tests if a value is a nonnegative number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a nonnegative number.\n\n    Examples\n    --------\n    > var bool = isNonNegativeNumber( 5.0 )\n    true\n    > bool = isNonNegativeNumber( new Number( 5.0 ) )\n    true\n    > bool = isNonNegativeNumber( 3.14 )\n    true\n    > bool = isNonNegativeNumber( -5.0 )\n    false\n    > bool = isNonNegativeNumber( null )\n    false\n\n\nisNonNegativeNumber.isPrimitive( value )\n    Tests if a value is a number primitive having a nonnegative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonnegative value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeNumber.isPrimitive( 3.0 )\n    true\n    > bool = isNonNegativeNumber.isPrimitive( new Number( 3.0 ) )\n    false\n\n\nisNonNegativeNumber.isObject( value )\n    Tests if a value is a number object having a nonnegative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a nonnegative\n        value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeNumber.isObject( 3.0 )\n    false\n    > bool = isNonNegativeNumber.isObject( new Number( 3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isNonNegativeFinite, isNonNegativeInteger, isNumber\n","isNonNegativeNumber.isPrimitive":"\nisNonNegativeNumber.isPrimitive( value )\n    Tests if a value is a number primitive having a nonnegative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonnegative value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeNumber.isPrimitive( 3.0 )\n    true\n    > bool = isNonNegativeNumber.isPrimitive( new Number( 3.0 ) )\n    false","isNonNegativeNumber.isObject":"\nisNonNegativeNumber.isObject( value )\n    Tests if a value is a number object having a nonnegative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a nonnegative\n        value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeNumber.isObject( 3.0 )\n    false\n    > bool = isNonNegativeNumber.isObject( new Number( 3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isNonNegativeFinite, isNonNegativeInteger, isNumber","isNonNegativeNumberArray":"\nisNonNegativeNumberArray( value )\n    Tests if a value is an array-like object containing only nonnegative\n    numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        nonnegative numbers.\n\n    Examples\n    --------\n    > var bool = isNonNegativeNumberArray( [ 3.0, new Number(3.0) ] )\n    true\n    > bool = isNonNegativeNumberArray( [ 3.0, '3.0' ] )\n    false\n\n\nisNonNegativeNumberArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive\n    nonnegative numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive nonnegative numbers.\n\n    Examples\n    --------\n    > var bool = isNonNegativeNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n    true\n    > bool = isNonNegativeNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n    false\n\n\nisNonNegativeNumberArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having nonnegative number values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having nonnegative number values.\n\n    Examples\n    --------\n    > var bool = isNonNegativeNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n    true\n    > bool = isNonNegativeNumberArray.objects( [ 1.0, 0.0, 10.0 ] )\n    false\n    > bool = isNonNegativeNumberArray.objects( [ 3.0, new Number(1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray\n","isNonNegativeNumberArray.primitives":"\nisNonNegativeNumberArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive\n    nonnegative numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive nonnegative numbers.\n\n    Examples\n    --------\n    > var bool = isNonNegativeNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n    true\n    > bool = isNonNegativeNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n    false","isNonNegativeNumberArray.objects":"\nisNonNegativeNumberArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having nonnegative number values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having nonnegative number values.\n\n    Examples\n    --------\n    > var bool = isNonNegativeNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n    true\n    > bool = isNonNegativeNumberArray.objects( [ 1.0, 0.0, 10.0 ] )\n    false\n    > bool = isNonNegativeNumberArray.objects( [ 3.0, new Number(1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray","isNonPositiveFinite":"\nisNonPositiveFinite( value )\n    Tests if a value is a nonpositive finite number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a nonpositive finite number.\n\n    Examples\n    --------\n    > var bool = isNonPositiveFinite( -5.0 )\n    true\n    > bool = isNonPositiveFinite( new Number( -5.0 ) )\n    true\n    > bool = isNonPositiveFinite( -3.14 )\n    true\n    > bool = isNonPositiveFinite( 5.0 )\n    false\n    > bool = isNonPositiveFinite( null )\n    false\n\n\nisNonPositiveFinite.isPrimitive( value )\n    Tests if a value is a number primitive having a nonpositive finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonpositive finite value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveFinite.isPrimitive( -3.0 )\n    true\n    > bool = isNonPositiveFinite.isPrimitive( new Number( -3.0 ) )\n    false\n\n\nisNonPositiveFinite.isObject( value )\n    Tests if a value is a number object having a nonpositive finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a nonpositive\n        finite value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveFinite.isObject( -3.0 )\n    false\n    > bool = isNonPositiveFinite.isObject( new Number( -3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isFinite, isNonPositiveNumber\n","isNonPositiveFinite.isPrimitive":"\nisNonPositiveFinite.isPrimitive( value )\n    Tests if a value is a number primitive having a nonpositive finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonpositive finite value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveFinite.isPrimitive( -3.0 )\n    true\n    > bool = isNonPositiveFinite.isPrimitive( new Number( -3.0 ) )\n    false","isNonPositiveFinite.isObject":"\nisNonPositiveFinite.isObject( value )\n    Tests if a value is a number object having a nonpositive finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a nonpositive\n        finite value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveFinite.isObject( -3.0 )\n    false\n    > bool = isNonPositiveFinite.isObject( new Number( -3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isFinite, isNonPositiveNumber","isNonPositiveInteger":"\nisNonPositiveInteger( value )\n    Tests if a value is a nonpositive integer.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a nonpositive integer.\n\n    Examples\n    --------\n    > var bool = isNonPositiveInteger( -5.0 )\n    true\n    > bool = isNonPositiveInteger( new Number( -5.0 ) )\n    true\n    > bool = isNonPositiveInteger( 5.0 )\n    false\n    > bool = isNonPositiveInteger( -3.14 )\n    false\n    > bool = isNonPositiveInteger( null )\n    false\n\n\nisNonPositiveInteger.isPrimitive( value )\n    Tests if a value is a number primitive having a nonpositive integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonpositive integer value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveInteger.isPrimitive( -3.0 )\n    true\n    > bool = isNonPositiveInteger.isPrimitive( new Number( -3.0 ) )\n    false\n\n\nisNonPositiveInteger.isObject( value )\n    Tests if a value is a number object having a nonpositive integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a nonpositive\n        integer value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveInteger.isObject( -3.0 )\n    false\n    > bool = isNonPositiveInteger.isObject( new Number( -3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger\n","isNonPositiveInteger.isPrimitive":"\nisNonPositiveInteger.isPrimitive( value )\n    Tests if a value is a number primitive having a nonpositive integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonpositive integer value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveInteger.isPrimitive( -3.0 )\n    true\n    > bool = isNonPositiveInteger.isPrimitive( new Number( -3.0 ) )\n    false","isNonPositiveInteger.isObject":"\nisNonPositiveInteger.isObject( value )\n    Tests if a value is a number object having a nonpositive integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a nonpositive\n        integer value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveInteger.isObject( -3.0 )\n    false\n    > bool = isNonPositiveInteger.isObject( new Number( -3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger","isNonPositiveIntegerArray":"\nisNonPositiveIntegerArray( value )\n    Tests if a value is an array-like object containing only nonpositive\n    integers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        nonpositive integers.\n\n    Examples\n    --------\n    > var bool = isNonPositiveIntegerArray( [ -3.0, new Number(-3.0) ] )\n    true\n    > bool = isNonPositiveIntegerArray( [ -3.0, '-3.0' ] )\n    false\n\n\nisNonPositiveIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only nonpositive\n    primitive integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        nonpositive primitive integer values.\n\n    Examples\n    --------\n    > var bool = isNonPositiveIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n    true\n    > bool = isNonPositiveIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false\n\n\nisNonPositiveIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having nonpositive integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having nonpositive integer values.\n\n    Examples\n    --------\n    > var bool = isNonPositiveIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n    true\n    > bool = isNonPositiveIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNonPositiveIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray\n","isNonPositiveIntegerArray.primitives":"\nisNonPositiveIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only nonpositive\n    primitive integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        nonpositive primitive integer values.\n\n    Examples\n    --------\n    > var bool = isNonPositiveIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n    true\n    > bool = isNonPositiveIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false","isNonPositiveIntegerArray.objects":"\nisNonPositiveIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having nonpositive integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having nonpositive integer values.\n\n    Examples\n    --------\n    > var bool = isNonPositiveIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n    true\n    > bool = isNonPositiveIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNonPositiveIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray","isNonPositiveNumber":"\nisNonPositiveNumber( value )\n    Tests if a value is a nonpositive number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a nonpositive number.\n\n    Examples\n    --------\n    > var bool = isNonPositiveNumber( -5.0 )\n    true\n    > bool = isNonPositiveNumber( new Number( -5.0 ) )\n    true\n    > bool = isNonPositiveNumber( -3.14 )\n    true\n    > bool = isNonPositiveNumber( 5.0 )\n    false\n    > bool = isNonPositiveNumber( null )\n    false\n\n\nisNonPositiveNumber.isPrimitive( value )\n    Tests if a value is a number primitive having a nonpositive value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonpositive value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveNumber.isPrimitive( -3.0 )\n    true\n    > bool = isNonPositiveNumber.isPrimitive( new Number( -3.0 ) )\n    false\n\n\nisNonPositiveNumber.isObject( value )\n    Tests if a value is a number object having a nonpositive value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a nonpositive\n        value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveNumber.isObject( -3.0 )\n    false\n    > bool = isNonPositiveNumber.isObject( new Number( -3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isNumber\n","isNonPositiveNumber.isPrimitive":"\nisNonPositiveNumber.isPrimitive( value )\n    Tests if a value is a number primitive having a nonpositive value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonpositive value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveNumber.isPrimitive( -3.0 )\n    true\n    > bool = isNonPositiveNumber.isPrimitive( new Number( -3.0 ) )\n    false","isNonPositiveNumber.isObject":"\nisNonPositiveNumber.isObject( value )\n    Tests if a value is a number object having a nonpositive value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a nonpositive\n        value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveNumber.isObject( -3.0 )\n    false\n    > bool = isNonPositiveNumber.isObject( new Number( -3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isNumber","isNonPositiveNumberArray":"\nisNonPositiveNumberArray( value )\n    Tests if a value is an array-like object containing only nonpositive\n    numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        nonpositive numbers.\n\n    Examples\n    --------\n    > var bool = isNonPositiveNumberArray( [ -3.0, new Number(-3.0) ] )\n    true\n    > bool = isNonPositiveNumberArray( [ -3.0, '-3.0' ] )\n    false\n\n\nisNonPositiveNumberArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive\n    nonpositive numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive nonpositive numbers.\n\n    Examples\n    --------\n    > var bool = isNonPositiveNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n    true\n    > bool = isNonPositiveNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false\n\n\nisNonPositiveNumberArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having nonpositive number values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having nonpositive number values.\n\n    Examples\n    --------\n    > var bool = isNonPositiveNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n    true\n    > bool = isNonPositiveNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNonPositiveNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray\n","isNonPositiveNumberArray.primitives":"\nisNonPositiveNumberArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive\n    nonpositive numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive nonpositive numbers.\n\n    Examples\n    --------\n    > var bool = isNonPositiveNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n    true\n    > bool = isNonPositiveNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false","isNonPositiveNumberArray.objects":"\nisNonPositiveNumberArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having nonpositive number values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having nonpositive number values.\n\n    Examples\n    --------\n    > var bool = isNonPositiveNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n    true\n    > bool = isNonPositiveNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNonPositiveNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray","isNonSymmetricMatrix":"\nisNonSymmetricMatrix( value )\n    Tests if a value is a non-symmetric matrix.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a non-symmetric matrix.\n\n    Examples\n    --------\n    > var buf = [ 1, 2, 3, 4 ];\n    > var sh = [ 2, 2 ];\n    > var st = [ 2, 1 ];\n    > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n    > var bool = isNonSymmetricMatrix( M )\n    true\n    > bool = isNonSymmetricMatrix( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isNonSymmetricMatrix( 3.14 )\n    false\n    > bool = isNonSymmetricMatrix( {} )\n    false\n\n    See Also\n    --------\n    isMatrixLike, isSquareMatrix, isSymmetricMatrix\n","isNull":"\nisNull( value )\n    Tests if a value is null.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is null.\n\n    Examples\n    --------\n    > var bool = isNull( null )\n    true\n    > bool = isNull( true )\n    false\n\n    See Also\n    --------\n    isUndefined, isUndefinedOrNull\n","isNullArray":"\nisNullArray( value )\n    Tests if a value is an array-like object containing only null values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        null values.\n\n    Examples\n    --------\n    > var bool = isNullArray( [ null, null, null ] )\n    true\n    > bool = isNullArray( [ NaN, 2, null ] )\n    false\n\n    See Also\n    --------\n    isArray, isNull\n","isNumber":"\nisNumber( value )\n    Tests if a value is a number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number.\n\n    Examples\n    --------\n    > var bool = isNumber( 3.14 )\n    true\n    > bool = isNumber( new Number( 3.14 ) )\n    true\n    > bool = isNumber( NaN )\n    true\n    > bool = isNumber( null )\n    false\n\n\nisNumber.isPrimitive( value )\n    Tests if a value is a number primitive.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive.\n\n    Examples\n    --------\n    > var bool = isNumber.isPrimitive( 3.14 )\n    true\n    > bool = isNumber.isPrimitive( NaN )\n    true\n    > bool = isNumber.isPrimitive( new Number( 3.14 ) )\n    false\n\n\nisNumber.isObject( value )\n    Tests if a value is a `Number` object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a `Number` object.\n\n    Examples\n    --------\n    > var bool = isNumber.isObject( 3.14 )\n    false\n    > bool = isNumber.isObject( new Number( 3.14 ) )\n    true\n\n","isNumber.isPrimitive":"\nisNumber.isPrimitive( value )\n    Tests if a value is a number primitive.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive.\n\n    Examples\n    --------\n    > var bool = isNumber.isPrimitive( 3.14 )\n    true\n    > bool = isNumber.isPrimitive( NaN )\n    true\n    > bool = isNumber.isPrimitive( new Number( 3.14 ) )\n    false","isNumber.isObject":"\nisNumber.isObject( value )\n    Tests if a value is a `Number` object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a `Number` object.\n\n    Examples\n    --------\n    > var bool = isNumber.isObject( 3.14 )\n    false\n    > bool = isNumber.isObject( new Number( 3.14 ) )\n    true","isNumberArray":"\nisNumberArray( value )\n    Tests if a value is an array-like object containing only numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        numbers.\n\n    Examples\n    --------\n    > var bool = isNumberArray( [ 1, 2, 3 ] )\n    true\n    > bool = isNumberArray( [ '1', 2, 3 ] )\n    false\n\n\nisNumberArray.primitives( value )\n    Tests if a value is an array-like object containing only number primitives.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number primitives.\n\n    Examples\n    --------\n    > var arr = [ 1, 2, 3 ];\n    > var bool = isNumberArray.primitives( arr )\n    true\n    > arr = [ 1, new Number( 2 ) ];\n    > bool = isNumberArray.primitives( arr )\n    false\n\n\nisNumberArray.objects( value )\n    Tests if a value is an array-like object containing only `Number` objects.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        `Number` objects.\n\n    Examples\n    --------\n    > var arr = [ new Number( 1 ), new Number( 2 ) ];\n    > var bool = isNumberArray.objects( arr )\n    true\n    > arr = [ new Number( 1 ), 2 ];\n    > bool = isNumberArray.objects( arr )\n    false\n\n    See Also\n    --------\n    isArray, isNumber, isNumericArray\n","isNumberArray.primitives":"\nisNumberArray.primitives( value )\n    Tests if a value is an array-like object containing only number primitives.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number primitives.\n\n    Examples\n    --------\n    > var arr = [ 1, 2, 3 ];\n    > var bool = isNumberArray.primitives( arr )\n    true\n    > arr = [ 1, new Number( 2 ) ];\n    > bool = isNumberArray.primitives( arr )\n    false","isNumberArray.objects":"\nisNumberArray.objects( value )\n    Tests if a value is an array-like object containing only `Number` objects.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        `Number` objects.\n\n    Examples\n    --------\n    > var arr = [ new Number( 1 ), new Number( 2 ) ];\n    > var bool = isNumberArray.objects( arr )\n    true\n    > arr = [ new Number( 1 ), 2 ];\n    > bool = isNumberArray.objects( arr )\n    false\n\n    See Also\n    --------\n    isArray, isNumber, isNumericArray","isNumericArray":"\nisNumericArray( value )\n    Tests if a value is a numeric array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is a numeric array.\n\n    Examples\n    --------\n    > var bool = isNumericArray( new Int8Array( 10 ) )\n    true\n    > bool = isNumericArray( [ 1, 2, 3 ] )\n    true\n    > bool = isNumericArray( [ '1', '2', '3' ] )\n    false\n\n    See Also\n    --------\n    isArray, isNumberArray, isTypedArray\n\n","isObject":"\nisObject( value )\n    Tests if a value is an object; e.g., `{}`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an object.\n\n    Examples\n    --------\n    > var bool = isObject( {} )\n    true\n    > bool = isObject( true )\n    false\n\n    See Also\n    --------\n    isObjectLike, isPlainObject\n","isObjectArray":"\nisObjectArray( value )\n    Tests if a value is an array-like object containing only objects.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        objects.\n\n    Examples\n    --------\n    > var bool = isObjectArray( [ {}, new Number(3.0) ] )\n    true\n    > bool = isObjectArray( [ {}, { 'beep': 'boop' } ] )\n    true\n    > bool = isObjectArray( [ {}, '3.0' ] )\n    false\n\n    See Also\n    --------\n    isArray, isObject\n","isObjectLike":"\nisObjectLike( value )\n    Tests if a value is object-like.\n\n    Return values are the same as would be obtained using the built-in `typeof`\n    operator except that `null` is not considered an object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is object-like.\n\n    Examples\n    --------\n    > var bool = isObjectLike( {} )\n    true\n    > bool = isObjectLike( [] )\n    true\n    > bool = isObjectLike( null )\n    false\n\n    See Also\n    --------\n    isObject, isPlainObject\n","isOdd":"\nisOdd( value )\n    Tests if a value is an odd number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an odd number.\n\n    Examples\n    --------\n    > var bool = isOdd( 5.0 )\n    true\n    > bool = isOdd( new Number( 5.0 ) )\n    true\n    > bool = isOdd( 4.0 )\n    false\n    > bool = isOdd( new Number( 4.0 ) )\n    false\n    > bool = isOdd( -3.14 )\n    false\n    > bool = isOdd( null )\n    false\n\nisOdd.isPrimitive( value )\n    Tests if a value is a number primitive that is an odd number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive that is an odd\n        number.\n\n    Examples\n    --------\n    > var bool = isOdd.isPrimitive( -5.0 )\n    true\n    > bool = isOdd.isPrimitive( new Number( -5.0 ) )\n    false\n\n\nisOdd.isObject( value )\n    Tests if a value is a number object that has an odd number value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object that has an odd\n        number value.\n\n    Examples\n    --------\n    > var bool = isOdd.isObject( 5.0 )\n    false\n    > bool = isOdd.isObject( new Number( 5.0 ) )\n    true\n\n    See Also\n    --------\n    isEven\n","isOdd.isPrimitive":"\nisOdd.isPrimitive( value )\n    Tests if a value is a number primitive that is an odd number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive that is an odd\n        number.\n\n    Examples\n    --------\n    > var bool = isOdd.isPrimitive( -5.0 )\n    true\n    > bool = isOdd.isPrimitive( new Number( -5.0 ) )\n    false","isOdd.isObject":"\nisOdd.isObject( value )\n    Tests if a value is a number object that has an odd number value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object that has an odd\n        number value.\n\n    Examples\n    --------\n    > var bool = isOdd.isObject( 5.0 )\n    false\n    > bool = isOdd.isObject( new Number( 5.0 ) )\n    true\n\n    See Also\n    --------\n    isEven","isoWeeksInYear":"\nisoWeeksInYear( [year] )\n    Returns the number of ISO weeks in a year according to the Gregorian\n    calendar.\n\n    By default, the function returns the number of ISO weeks in the current year\n    (according to local time). To determine the number of ISO weeks for a\n    particular year, provide either a year or a `Date` object.\n\n    Parameters\n    ----------\n    year: integer (optional)\n        Year.\n\n    Returns\n    -------\n    out: integer\n        Number of ISO weeks in a year.\n\n    Examples\n    --------\n    > var num = isoWeeksInYear()\n    <number>\n    > num = isoWeeksInYear( 2015 )\n    53\n    > num = isoWeeksInYear( 2017 )\n    52\n\n","isPascalcase":"\nisPascalcase( value )\n    Tests if a value is a string in Pascal case.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a string in Pascal case.\n\n    Examples\n    --------\n    > var bool = isPascalcase( 'HelloWorld' )\n    true\n    > bool = isPascalcase( 'hello-world' )\n    false\n\n    See Also\n    --------\n    isString","isPersymmetricMatrix":"\nisPersymmetricMatrix( value )\n    Tests if a value is a square matrix which is symmetric about its\n    antidiagonal.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a persymmetric matrix.\n\n    Examples\n    --------\n    > var buf = [ 1, 2, 3, 1 ];\n    > var sh = [ 2, 2 ];\n    > var st = [ 2, 1 ];\n    > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n    > var bool = isPersymmetricMatrix( M )\n    true\n    > bool = isPersymmetricMatrix( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isPersymmetricMatrix( 3.14 )\n    false\n    > bool = isPersymmetricMatrix( {} )\n    false\n\n    See Also\n    --------\n    isMatrixLike, isSquareMatrix, isSymmetricMatrix\n","isPlainObject":"\nisPlainObject( value )\n    Tests if a value is a plain object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a plain object.\n\n    Examples\n    --------\n    > var bool = isPlainObject( {} )\n    true\n    > bool = isPlainObject( null )\n    false\n\n    See Also\n    --------\n    isObject\n","isPlainObjectArray":"\nisPlainObjectArray( value )\n    Tests if a value is an array-like object containing only plain objects.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        plain objects.\n\n    Examples\n    --------\n    > var bool = isPlainObjectArray( [ {}, { 'beep': 'boop' } ] )\n    true\n    > bool = isPlainObjectArray( [ {}, new Number(3.0) ] )\n    false\n    > bool = isPlainObjectArray( [ {}, '3.0' ] )\n    false\n\n    See Also\n    --------\n    isArray, isPlainObject\n","isPositiveFinite":"\nisPositiveFinite( value )\n    Tests if a value is a positive finite number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a positive finite number.\n\n    Examples\n    --------\n    > var bool = isPositiveFinite( 5.0 )\n    true\n    > bool = isPositiveFinite( new Number( 5.0 ) )\n    true\n    > bool = isPositiveFinite( 3.14 )\n    true\n    > bool = isPositiveFinite( -5.0 )\n    false\n    > var bool = isPositiveFinite( 1.0/0.0 )\n    false\n    > bool = isPositiveFinite( new Number( 1.0/0.0 ) )\n    false\n    > bool = isPositiveFinite( null )\n    false\n\n\nisPositiveFinite.isPrimitive( value )\n    Tests if a value is a number primitive having a positive finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is a number primitive having a positive\n        finite value.\n\n    Examples\n    --------\n    > var bool = isPositiveFinite.isPrimitive( 3.0 )\n    true\n    > var bool = isPositiveFinite.isPrimitive( 1.0/0.0 )\n    false\n    > bool = isPositiveFinite.isPrimitive( new Number( 3.0 ) )\n    false\n\n\nisPositiveFinite.isObject( value )\n    Tests if a value is a number object having a positive finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a positive\n        finite value.\n\n    Examples\n    --------\n    > var bool = isPositiveFinite.isObject( 3.0 )\n    false\n    > bool = isPositiveFinite.isObject( new Number( 3.0 ) )\n    true\n    > bool = isPositiveFinite.isObject( new Number( 1.0/0.0 ) )\n    false\n\n\n    See Also\n    --------\n    isFinite, isPositiveNumber\n","isPositiveFinite.isPrimitive":"\nisPositiveFinite.isPrimitive( value )\n    Tests if a value is a number primitive having a positive finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is a number primitive having a positive\n        finite value.\n\n    Examples\n    --------\n    > var bool = isPositiveFinite.isPrimitive( 3.0 )\n    true\n    > var bool = isPositiveFinite.isPrimitive( 1.0/0.0 )\n    false\n    > bool = isPositiveFinite.isPrimitive( new Number( 3.0 ) )\n    false","isPositiveFinite.isObject":"\nisPositiveFinite.isObject( value )\n    Tests if a value is a number object having a positive finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a positive\n        finite value.\n\n    Examples\n    --------\n    > var bool = isPositiveFinite.isObject( 3.0 )\n    false\n    > bool = isPositiveFinite.isObject( new Number( 3.0 ) )\n    true\n    > bool = isPositiveFinite.isObject( new Number( 1.0/0.0 ) )\n    false\n\n\n    See Also\n    --------\n    isFinite, isPositiveNumber","isPositiveInteger":"\nisPositiveInteger( value )\n    Tests if a value is a positive integer.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a positive integer.\n\n    Examples\n    --------\n    > var bool = isPositiveInteger( 5.0 )\n    true\n    > bool = isPositiveInteger( new Number( 5.0 ) )\n    true\n    > bool = isPositiveInteger( 3.14 )\n    false\n    > bool = isPositiveInteger( -5.0 )\n    false\n    > bool = isPositiveInteger( null )\n    false\n\n\nisPositiveInteger.isPrimitive( value )\n    Tests if a value is a number primitive having a positive integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        positive integer value.\n\n    Examples\n    --------\n    > var bool = isPositiveInteger.isPrimitive( 3.0 )\n    true\n    > bool = isPositiveInteger.isPrimitive( new Number( 3.0 ) )\n    false\n\n\nisPositiveInteger.isObject( value )\n    Tests if a value is a number object having a positive integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a positive\n        integer value.\n\n    Examples\n    --------\n    > var bool = isPositiveInteger.isObject( 3.0 )\n    false\n    > bool = isPositiveInteger.isObject( new Number( 3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger\n","isPositiveInteger.isPrimitive":"\nisPositiveInteger.isPrimitive( value )\n    Tests if a value is a number primitive having a positive integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        positive integer value.\n\n    Examples\n    --------\n    > var bool = isPositiveInteger.isPrimitive( 3.0 )\n    true\n    > bool = isPositiveInteger.isPrimitive( new Number( 3.0 ) )\n    false","isPositiveInteger.isObject":"\nisPositiveInteger.isObject( value )\n    Tests if a value is a number object having a positive integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a positive\n        integer value.\n\n    Examples\n    --------\n    > var bool = isPositiveInteger.isObject( 3.0 )\n    false\n    > bool = isPositiveInteger.isObject( new Number( 3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger","isPositiveIntegerArray":"\nisPositiveIntegerArray( value )\n    Tests if a value is an array-like object containing only positive integers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        positive integers.\n\n    Examples\n    --------\n    > var bool = isPositiveIntegerArray( [ 3.0, new Number(3.0) ] )\n    true\n    > bool = isPositiveIntegerArray( [ 3.0, '3.0' ] )\n    false\n\n\nisPositiveIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only positive primitive\n    integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        positive primitive integer values.\n\n    Examples\n    --------\n    > var bool = isPositiveIntegerArray.primitives( [ 1.0, 10.0 ] )\n    true\n    > bool = isPositiveIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n    false\n    > bool = isPositiveIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n    false\n\n\nisPositiveIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having positive integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having positive integer values.\n\n    Examples\n    --------\n    > var bool = isPositiveIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n    true\n    > bool = isPositiveIntegerArray.objects( [ 1.0, 2.0, 10.0 ] )\n    false\n    > bool = isPositiveIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray, isInteger, isPositiveInteger\n","isPositiveIntegerArray.primitives":"\nisPositiveIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only positive primitive\n    integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        positive primitive integer values.\n\n    Examples\n    --------\n    > var bool = isPositiveIntegerArray.primitives( [ 1.0, 10.0 ] )\n    true\n    > bool = isPositiveIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n    false\n    > bool = isPositiveIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n    false","isPositiveIntegerArray.objects":"\nisPositiveIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having positive integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having positive integer values.\n\n    Examples\n    --------\n    > var bool = isPositiveIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n    true\n    > bool = isPositiveIntegerArray.objects( [ 1.0, 2.0, 10.0 ] )\n    false\n    > bool = isPositiveIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray, isInteger, isPositiveInteger","isPositiveNumber":"\nisPositiveNumber( value )\n    Tests if a value is a positive number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a positive number.\n\n    Examples\n    --------\n    > var bool = isPositiveNumber( 5.0 )\n    true\n    > bool = isPositiveNumber( new Number( 5.0 ) )\n    true\n    > bool = isPositiveNumber( 3.14 )\n    true\n    > bool = isPositiveNumber( -5.0 )\n    false\n    > bool = isPositiveNumber( null )\n    false\n\n\nisPositiveNumber.isPrimitive( value )\n    Tests if a value is a number primitive having a positive value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a positive\n        value.\n\n    Examples\n    --------\n    > var bool = isPositiveNumber.isPrimitive( 3.0 )\n    true\n    > bool = isPositiveNumber.isPrimitive( new Number( 3.0 ) )\n    false\n\n\nisPositiveNumber.isObject( value )\n    Tests if a value is a number object having a positive value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a positive\n        value.\n\n    Examples\n    --------\n    > var bool = isPositiveNumber.isObject( 3.0 )\n    false\n    > bool = isPositiveNumber.isObject( new Number( 3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isNumber\n","isPositiveNumber.isPrimitive":"\nisPositiveNumber.isPrimitive( value )\n    Tests if a value is a number primitive having a positive value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a positive\n        value.\n\n    Examples\n    --------\n    > var bool = isPositiveNumber.isPrimitive( 3.0 )\n    true\n    > bool = isPositiveNumber.isPrimitive( new Number( 3.0 ) )\n    false","isPositiveNumber.isObject":"\nisPositiveNumber.isObject( value )\n    Tests if a value is a number object having a positive value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a positive\n        value.\n\n    Examples\n    --------\n    > var bool = isPositiveNumber.isObject( 3.0 )\n    false\n    > bool = isPositiveNumber.isObject( new Number( 3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isNumber","isPositiveNumberArray":"\nisPositiveNumberArray( value )\n    Tests if a value is an array-like object containing only positive numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        positive numbers.\n\n    Examples\n    --------\n    > var bool = isPositiveNumberArray( [ 3.0, new Number(3.0) ] )\n    true\n    > bool = isPositiveNumberArray( [ 3.0, '3.0' ] )\n    false\n\n\nisPositiveNumberArray.primitives( value )\n    Tests if a value is an array-like object containing only positive primitive\n    number values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        positive primitive number values.\n\n    Examples\n    --------\n    > var bool = isPositiveNumberArray.primitives( [ 1.0, 10.0 ] )\n    true\n    > bool = isPositiveNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n    false\n    > bool = isPositiveNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n    false\n\n\nisPositiveNumberArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having positive values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having positive values.\n\n    Examples\n    --------\n    > var bool = isPositiveNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n    true\n    > bool = isPositiveNumberArray.objects( [ 1.0, 2.0, 10.0 ] )\n    false\n    > bool = isPositiveNumberArray.objects( [ 3.0, new Number(1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray, isNumber, isPositiveNumber\n","isPositiveNumberArray.primitives":"\nisPositiveNumberArray.primitives( value )\n    Tests if a value is an array-like object containing only positive primitive\n    number values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        positive primitive number values.\n\n    Examples\n    --------\n    > var bool = isPositiveNumberArray.primitives( [ 1.0, 10.0 ] )\n    true\n    > bool = isPositiveNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n    false\n    > bool = isPositiveNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n    false","isPositiveNumberArray.objects":"\nisPositiveNumberArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having positive values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having positive values.\n\n    Examples\n    --------\n    > var bool = isPositiveNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n    true\n    > bool = isPositiveNumberArray.objects( [ 1.0, 2.0, 10.0 ] )\n    false\n    > bool = isPositiveNumberArray.objects( [ 3.0, new Number(1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray, isNumber, isPositiveNumber","isPositiveZero":"\nisPositiveZero( value )\n    Tests if a value is positive zero.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is positive zero.\n\n    Examples\n    --------\n    > var bool = isPositiveZero( 0.0 )\n    true\n    > bool = isPositiveZero( new Number( 0.0 ) )\n    true\n    > bool = isPositiveZero( -3.14 )\n    false\n    > bool = isPositiveZero( -0.0 )\n    false\n    > bool = isPositiveZero( null )\n    false\n\n\nisPositiveZero.isPrimitive( value )\n    Tests if a value is a number primitive equal to positive zero.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number primitive equal to\n        positive zero.\n\n    Examples\n    --------\n    > var bool = isPositiveZero.isPrimitive( 0.0 )\n    true\n    > bool = isPositiveZero.isPrimitive( new Number( 0.0 ) )\n    false\n\n\nisPositiveZero.isObject( value )\n    Tests if a value is a number object having a value equal to positive zero.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number object having a value\n        equal to positive zero.\n\n    Examples\n    --------\n    > var bool = isPositiveZero.isObject( 0.0 )\n    false\n    > bool = isPositiveZero.isObject( new Number( 0.0 ) )\n    true\n\n    See Also\n    --------\n    isNumber, isNegativeZero\n","isPositiveZero.isPrimitive":"\nisPositiveZero.isPrimitive( value )\n    Tests if a value is a number primitive equal to positive zero.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number primitive equal to\n        positive zero.\n\n    Examples\n    --------\n    > var bool = isPositiveZero.isPrimitive( 0.0 )\n    true\n    > bool = isPositiveZero.isPrimitive( new Number( 0.0 ) )\n    false","isPositiveZero.isObject":"\nisPositiveZero.isObject( value )\n    Tests if a value is a number object having a value equal to positive zero.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number object having a value\n        equal to positive zero.\n\n    Examples\n    --------\n    > var bool = isPositiveZero.isObject( 0.0 )\n    false\n    > bool = isPositiveZero.isObject( new Number( 0.0 ) )\n    true\n\n    See Also\n    --------\n    isNumber, isNegativeZero","isPrime":"\nisPrime( value )\n    Tests if a value is a prime number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a prime number.\n\n    Examples\n    --------\n    > var bool = isPrime( 5.0 )\n    true\n    > bool = isPrime( new Number( 5.0 ) )\n    true\n    > bool = isPrime( 3.14 )\n    false\n    > bool = isPrime( -5.0 )\n    false\n    > bool = isPrime( null )\n    false\n\n\nisPrime.isPrimitive( value )\n    Tests if a value is a number primitive which is a prime number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a prime\n        number.\n\n    Examples\n    --------\n    > var bool = isPrime.isPrimitive( 5.0 )\n    true\n    > bool = isPrime.isPrimitive( new Number( 5.0 ) )\n    false\n\n\nisPrime.isObject( value )\n    Tests if a value is a number object having a value which is a prime number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a prime number.\n\n    Examples\n    --------\n    > var bool = isPrime.isObject( 5.0 )\n    false\n    > bool = isPrime.isObject( new Number( 5.0 ) )\n    true\n\n\n    See Also\n    --------\n    isComposite, isInteger, isNumber\n","isPrime.isPrimitive":"\nisPrime.isPrimitive( value )\n    Tests if a value is a number primitive which is a prime number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a prime\n        number.\n\n    Examples\n    --------\n    > var bool = isPrime.isPrimitive( 5.0 )\n    true\n    > bool = isPrime.isPrimitive( new Number( 5.0 ) )\n    false","isPrime.isObject":"\nisPrime.isObject( value )\n    Tests if a value is a number object having a value which is a prime number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a prime number.\n\n    Examples\n    --------\n    > var bool = isPrime.isObject( 5.0 )\n    false\n    > bool = isPrime.isObject( new Number( 5.0 ) )\n    true\n\n\n    See Also\n    --------\n    isComposite, isInteger, isNumber","isPrimitive":"\nisPrimitive( value )\n    Tests if a value is a JavaScript primitive.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a JavaScript primitive.\n\n    Examples\n    --------\n    > var bool = isPrimitive( true )\n    true\n    > bool = isPrimitive( {} )\n    false\n\n    See Also\n    --------\n    isBoxedPrimitive\n","isPrimitiveArray":"\nisPrimitiveArray( value )\n    Tests if a value is an array-like object containing only JavaScript\n    primitives.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        JavaScript primitives.\n\n    Examples\n    --------\n    > var bool = isPrimitiveArray( [ '3', 2, null ] )\n    true\n    > bool = isPrimitiveArray( [ {}, 2, 1 ] )\n    false\n    > bool = isPrimitiveArray( [ new String('abc'), '3.0' ] )\n    false\n\n    See Also\n    --------\n    isArray, isPrimitive\n","isPRNGLike":"\nisPRNGLike( value )\n    Tests if a value is PRNG-like.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is PRNG-like.\n\n    Examples\n    --------\n    > var bool = isPRNGLike( base.random.randu )\n    true\n    > bool = isPRNGLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isPRNGLike( 3.14 )\n    false\n    > bool = isPRNGLike( {} )\n    false\n\n","isProbability":"\nisProbability( value )\n    Tests if a value is a probability.\n\n    A probability is defined as a numeric value on the interval [0,1].\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a probability.\n\n    Examples\n    --------\n    > var bool = isProbability( 0.5 )\n    true\n    > bool = isProbability( new Number( 0.5 ) )\n    true\n    > bool = isProbability( 3.14 )\n    false\n    > bool = isProbability( -5.0 )\n    false\n    > bool = isProbability( null )\n    false\n\n\nisProbability.isPrimitive( value )\n    Tests if a value is a number primitive which is a probability.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a\n        probability.\n\n    Examples\n    --------\n    > var bool = isProbability.isPrimitive( 0.3 )\n    true\n    > bool = isProbability.isPrimitive( new Number( 0.3 ) )\n    false\n\n\nisProbability.isObject( value )\n    Tests if a value is a number object having a value which is a probability.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a probability.\n\n    Examples\n    --------\n    > var bool = isProbability.isObject( 0.77 )\n    false\n    > bool = isProbability.isObject( new Number( 0.77 ) )\n    true\n\n\n    See Also\n    --------\n    isNumber\n","isProbability.isPrimitive":"\nisProbability.isPrimitive( value )\n    Tests if a value is a number primitive which is a probability.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a\n        probability.\n\n    Examples\n    --------\n    > var bool = isProbability.isPrimitive( 0.3 )\n    true\n    > bool = isProbability.isPrimitive( new Number( 0.3 ) )\n    false","isProbability.isObject":"\nisProbability.isObject( value )\n    Tests if a value is a number object having a value which is a probability.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a probability.\n\n    Examples\n    --------\n    > var bool = isProbability.isObject( 0.77 )\n    false\n    > bool = isProbability.isObject( new Number( 0.77 ) )\n    true\n\n\n    See Also\n    --------\n    isNumber","isProbabilityArray":"\nisProbabilityArray( value )\n    Tests if a value is an array-like object containing only probabilities.\n\n    A probability is defined as a numeric value on the interval [0,1].\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        probabilities.\n\n    Examples\n    --------\n    > var bool = isProbabilityArray( [ 0.5, new Number(0.8) ] )\n    true\n    > bool = isProbabilityArray( [ 0.8, 1.2 ] )\n    false\n    > bool = isProbabilityArray( [ 0.8, '0.2' ] )\n    false\n\n\nisProbabilityArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive\n    probabilities.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive probabilities.\n\n    Examples\n    --------\n    > var bool = isProbabilityArray.primitives( [ 1.0, 0.0, 0.5 ] )\n    true\n    > bool = isProbabilityArray.primitives( [ 0.3, new Number(0.4) ] )\n    false\n\n\nisProbabilityArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having probability values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having probability values.\n\n    Examples\n    --------\n    > var bool = isProbabilityArray.objects( [ new Number(0.7), new Number(1.0) ] )\n    true\n    > bool = isProbabilityArray.objects( [ 1.0, 0.0, new Number(0.7) ] )\n    false\n\n    See Also\n    --------\n    isArray, isProbability\n","isProbabilityArray.primitives":"\nisProbabilityArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive\n    probabilities.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive probabilities.\n\n    Examples\n    --------\n    > var bool = isProbabilityArray.primitives( [ 1.0, 0.0, 0.5 ] )\n    true\n    > bool = isProbabilityArray.primitives( [ 0.3, new Number(0.4) ] )\n    false","isProbabilityArray.objects":"\nisProbabilityArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having probability values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having probability values.\n\n    Examples\n    --------\n    > var bool = isProbabilityArray.objects( [ new Number(0.7), new Number(1.0) ] )\n    true\n    > bool = isProbabilityArray.objects( [ 1.0, 0.0, new Number(0.7) ] )\n    false\n\n    See Also\n    --------\n    isArray, isProbability","isPropertyKey":"\nisPropertyKey( value )\n    Tests whether a value is a property key.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether value is a property key.\n\n    Examples\n    --------\n    > var out = isPropertyKey( 'foo' )\n    true\n    > out = isPropertyKey( 1 )\n    true\n    > out = isPropertyKey( true )\n    false\n\n    See Also\n    --------\n    isString, isSymbol, isNonNegativeInteger, hasOwnProp, hasProp","isPrototypeOf":"\nisPrototypeOf( value, proto )\n    Tests if an object's prototype chain contains a provided prototype.\n\n    The function returns `false` if provided a primitive value.\n\n    This function is generally more robust than the `instanceof` operator (e.g.,\n    where inheritance is performed without using constructors).\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    proto: Object|Function\n        Prototype.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a provided prototype exists in a prototype chain.\n\n    Examples\n    --------\n    > function Foo() { return this; };\n    > function Bar() { return this; };\n    > inherit( Bar, Foo );\n    > var bar = new Bar();\n    > var bool = isPrototypeOf( bar, Foo.prototype )\n    true\n\n    See Also\n    --------\n    getPrototypeOf\n","isRaggedNestedArray":"\nisRaggedNestedArray( value )\n    Tests if a value is a ragged nested array. \n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a ragged nested array.\n\n    Examples\n    --------\n    > var bool = isRaggedNestedArray( [ [ 1, 2, 3 ], [ 4, 5 ] ] )\n    true\n    > bool = isRaggedNestedArray( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n    false\n    > bool = isRaggedNestedArray( 'beep' )\n    false\n\n","isRangeError":"\nisRangeError( value )\n    Tests if a value is a RangeError object.\n\n    This function should *not* be considered robust. While the function should\n    always return `true` if provided a RangeError (or a descendant) object,\n    false positives may occur due to the fact that the RangeError constructor\n    inherits from Error and has no internal class of its own. Hence, RangeError\n    impersonation is possible.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a RangeError object.\n\n    Examples\n    --------\n    > var bool = isRangeError( new RangeError( 'beep' ) )\n    true\n    > bool = isRangeError( {} )\n    false\n\n    See Also\n    --------\n    isError\n","isReadableProperty":"\nisReadableProperty( value, property )\n    Tests if an object's own property is readable.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own property is readable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.set = function setter( v ) { obj.boop = v; };\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isReadableProperty( obj, 'boop' )\n    true\n    > bool = isReadableProperty( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    isReadOnlyProperty, isReadWriteProperty, isReadablePropertyIn, isWritableProperty\n","isReadablePropertyIn":"\nisReadablePropertyIn( value, property )\n    Tests if an object's own or inherited property is readable.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own or inherited property is readable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.set = function setter( v ) { obj.boop = v; };\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isReadablePropertyIn( obj, 'boop' )\n    true\n    > bool = isReadablePropertyIn( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    isReadOnlyPropertyIn, isReadWritePropertyIn, isReadableProperty, isWritablePropertyIn\n","isReadOnlyProperty":"\nisReadOnlyProperty( value, property )\n    Tests if an object's own property is read-only.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own property is read-only.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = true;\n    > desc.writable = false;\n    > desc.value = true;\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isReadOnlyProperty( obj, 'boop' )\n    true\n    > bool = isReadOnlyProperty( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    isReadOnlyPropertyIn, isReadWriteProperty, isReadableProperty, isWritableProperty\n","isReadOnlyPropertyIn":"\nisReadOnlyPropertyIn( value, property )\n    Tests if an object's own or inherited property is read-only.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own or inherited property is read-\n        only.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = true;\n    > desc.writable = false;\n    > desc.value = true;\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isReadOnlyPropertyIn( obj, 'boop' )\n    true\n    > bool = isReadOnlyPropertyIn( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    isReadOnlyProperty, isReadWritePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isReadWriteProperty":"\nisReadWriteProperty( value, property )\n    Tests if an object's own property is readable and writable.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own property is readable and writable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.set = function setter( v ) { obj.boop = v; };\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isReadWriteProperty( obj, 'boop' )\n    true\n    > bool = isReadWriteProperty( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    isReadOnlyProperty, isReadWritePropertyIn, isReadableProperty, isWritableProperty\n","isReadWritePropertyIn":"\nisReadWritePropertyIn( value, property )\n    Tests if an object's own or inherited property is readable and writable.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own or inherited property is readable\n        and writable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.set = function setter( v ) { obj.boop = v; };\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isReadWritePropertyIn( obj, 'boop' )\n    true\n    > bool = isReadWritePropertyIn( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    isReadOnlyPropertyIn, isReadWriteProperty, isReadablePropertyIn, isWritablePropertyIn\n","isReferenceError":"\nisReferenceError( value )\n    Tests if a value is a ReferenceError object.\n\n    This function should *not* be considered robust. While the function should\n    always return `true` if provided a ReferenceError (or a descendant)\n    object, false positives may occur due to the fact that the ReferenceError\n    constructor inherits from Error and has no internal class of its own.\n    Hence, ReferenceError impersonation is possible.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a ReferenceError object.\n\n    Examples\n    --------\n    > var bool = isReferenceError( new ReferenceError( 'beep' ) )\n    true\n    > bool = isReferenceError( {} )\n    false\n\n    See Also\n    --------\n    isError\n","isRegExp":"\nisRegExp( value )\n    Tests if a value is a regular expression.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a regular expression.\n\n    Examples\n    --------\n    > var bool = isRegExp( /\\.+/ )\n    true\n    > bool = isRegExp( {} )\n    false\n\n","isRegExpString":"\nisRegExpString( value )\n    Tests if a value is a regular expression string.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a regular expression string.\n\n    Examples\n    --------\n    > var bool = isRegExpString( '/beep/' )\n    true\n    > bool = isRegExpString( 'beep' )\n    false\n    > bool = isRegExpString( '' )\n    false\n    > bool = isRegExpString( null )\n    false\n\n    See Also\n    --------\n    isRegExp\n","isRelativePath":"\nisRelativePath( value )\n    Tests if a value is a relative path.\n\n    Function behavior is platform-specific. On Windows platforms, the function\n    is equal to `.win32()`. On POSIX platforms, the function is equal to\n    `.posix()`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a relative path.\n\n    Examples\n    --------\n    // Windows environments:\n    > var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\n    true\n\n    // POSIX environments:\n    > bool = isRelativePath( './foo/bar/baz' )\n    true\n\n\nisRelativePath.posix( value )\n    Tests if a value is a POSIX relative path.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a POSIX relative path.\n\n    Examples\n    --------\n    > var bool = isRelativePath.posix( './foo/bar/baz' )\n    true\n    > bool = isRelativePath.posix( '/foo/../bar/baz' )\n    false\n\n\nisRelativePath.win32( value )\n    Tests if a value is a Windows relative path.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Windows relative path.\n\n    Examples\n    --------\n    > var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\n    true\n    > bool = isRelativePath( 'C:\\\\foo\\\\..\\\\bar\\\\baz' )\n    false\n\n    See Also\n    --------\n    isAbsolutePath\n","isRelativePath.posix":"\nisRelativePath.posix( value )\n    Tests if a value is a POSIX relative path.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a POSIX relative path.\n\n    Examples\n    --------\n    > var bool = isRelativePath.posix( './foo/bar/baz' )\n    true\n    > bool = isRelativePath.posix( '/foo/../bar/baz' )\n    false","isRelativePath.win32":"\nisRelativePath.win32( value )\n    Tests if a value is a Windows relative path.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Windows relative path.\n\n    Examples\n    --------\n    > var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\n    true\n    > bool = isRelativePath( 'C:\\\\foo\\\\..\\\\bar\\\\baz' )\n    false\n\n    See Also\n    --------\n    isAbsolutePath","isRelativeURI":"\nisRelativeURI( value )\n    Tests whether a value is a relative URI.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether a value is a relative URI.\n\n    Examples\n    --------\n    > var bool = isRelativeURI( '/images/example.png' )\n    true\n    > bool = isRelativeURI( 'http://www.example.com' )\n    false\n    > bool = isRelativeURI( null )\n    false\n\n    See Also\n    --------\n    isURI","isSafeInteger":"\nisSafeInteger( value )\n    Tests if a value is a safe integer.\n\n    An integer valued number is \"safe\" when the number can be exactly\n    represented as a double-precision floating-point number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a safe integer.\n\n    Examples\n    --------\n    > var bool = isSafeInteger( 5.0 )\n    true\n    > bool = isSafeInteger( new Number( 5.0 ) )\n    true\n    > bool = isSafeInteger( 2.0e200 )\n    false\n    > bool = isSafeInteger( -3.14 )\n    false\n    > bool = isSafeInteger( null )\n    false\n\n\nisSafeInteger.isPrimitive( value )\n    Tests if a value is a number primitive having a safe integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a safe\n        integer value.\n\n    Examples\n    --------\n    > var bool = isSafeInteger.isPrimitive( -3.0 )\n    true\n    > bool = isSafeInteger.isPrimitive( new Number( -3.0 ) )\n    false\n\n\nisSafeInteger.isObject( value )\n    Tests if a value is a `Number` object having a safe integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a `Number` object having a safe\n        integer value.\n\n    Examples\n    --------\n    > var bool = isSafeInteger.isObject( 3.0 )\n    false\n    > bool = isSafeInteger.isObject( new Number( 3.0 ) )\n    true\n\n    See Also\n    --------\n    isInteger, isNumber\n","isSafeInteger.isPrimitive":"\nisSafeInteger.isPrimitive( value )\n    Tests if a value is a number primitive having a safe integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a safe\n        integer value.\n\n    Examples\n    --------\n    > var bool = isSafeInteger.isPrimitive( -3.0 )\n    true\n    > bool = isSafeInteger.isPrimitive( new Number( -3.0 ) )\n    false","isSafeInteger.isObject":"\nisSafeInteger.isObject( value )\n    Tests if a value is a `Number` object having a safe integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a `Number` object having a safe\n        integer value.\n\n    Examples\n    --------\n    > var bool = isSafeInteger.isObject( 3.0 )\n    false\n    > bool = isSafeInteger.isObject( new Number( 3.0 ) )\n    true\n\n    See Also\n    --------\n    isInteger, isNumber","isSafeIntegerArray":"\nisSafeIntegerArray( value )\n    Tests if a value is an array-like object containing only safe integers.\n\n    An integer valued number is \"safe\" when the number can be exactly\n    represented as a double-precision floating-point number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing\n        only safe integers.\n\n    Examples\n    --------\n    > var arr = [ -3.0, new Number(0.0), 2.0 ];\n    > var bool = isSafeIntegerArray( arr )\n    true\n    > arr = [ -3.0, '3.0' ];\n    > bool = isSafeIntegerArray( arr )\n    false\n\n\nisSafeIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive safe\n    integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive safe integer values.\n\n    Examples\n    --------\n    > var arr = [ -1.0, 10.0 ];\n    > var bool = isSafeIntegerArray.primitives( arr )\n    true\n    > arr = [ -1.0, 0.0, 5.0 ];\n    > bool = isSafeIntegerArray.primitives( arr )\n    true\n    > arr = [ -3.0, new Number(-1.0) ];\n    > bool = isSafeIntegerArray.primitives( arr )\n    false\n\n\nisSafeIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only `Number` objects\n    having safe integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        `Number` objects having safe integer values.\n\n    Examples\n    --------\n    > var arr = [ new Number(1.0), new Number(3.0) ];\n    > var bool = isSafeIntegerArray.objects( arr )\n    true\n    > arr = [ -1.0, 0.0, 3.0 ];\n    > bool = isSafeIntegerArray.objects( arr )\n    false\n    > arr = [ 3.0, new Number(-1.0) ];\n    > bool = isSafeIntegerArray.objects( arr )\n    false\n\n    See Also\n    --------\n    isArray, isSafeInteger\n","isSafeIntegerArray.primitives":"\nisSafeIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive safe\n    integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive safe integer values.\n\n    Examples\n    --------\n    > var arr = [ -1.0, 10.0 ];\n    > var bool = isSafeIntegerArray.primitives( arr )\n    true\n    > arr = [ -1.0, 0.0, 5.0 ];\n    > bool = isSafeIntegerArray.primitives( arr )\n    true\n    > arr = [ -3.0, new Number(-1.0) ];\n    > bool = isSafeIntegerArray.primitives( arr )\n    false","isSafeIntegerArray.objects":"\nisSafeIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only `Number` objects\n    having safe integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        `Number` objects having safe integer values.\n\n    Examples\n    --------\n    > var arr = [ new Number(1.0), new Number(3.0) ];\n    > var bool = isSafeIntegerArray.objects( arr )\n    true\n    > arr = [ -1.0, 0.0, 3.0 ];\n    > bool = isSafeIntegerArray.objects( arr )\n    false\n    > arr = [ 3.0, new Number(-1.0) ];\n    > bool = isSafeIntegerArray.objects( arr )\n    false\n\n    See Also\n    --------\n    isArray, isSafeInteger","isSameArray":"\nisSameArray( v1, v2 )\n    Tests if two arguments are both generic arrays and have the same values.\n\n    The function differs from the `===` operator in that the function treats\n    `-0` and `+0` as distinct and `NaNs` as the same.\n\n    Parameters\n    ----------\n    v1: any\n        First input value.\n\n    v2: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are the same.\n\n    Examples\n    --------\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > var y = [ 1.0, 2.0, 3.0 ];\n    > var bool = isSameArray( x, y )\n    true\n\n    > x = [ NaN, NaN, NaN ];\n    > y = [ NaN, NaN, NaN ];\n    > bool = isSameArray( x, y )\n    true\n\n    See Also\n    --------\n    isArray, isEqualArray, isSameArrayLike, isSameValue\n","isSameArrayLike":"\nisSameArrayLike( v1, v2 )\n    Tests if two arguments are both array-like and have the same values.\n\n    The function differs from the `===` operator in that the function treats\n    `-0` and `+0` as distinct and `NaNs` as the same.\n\n    Parameters\n    ----------\n    v1: any\n        First input value.\n\n    v2: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are the same.\n\n    Examples\n    --------\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > var y = [ 1.0, 2.0, 3.0 ];\n    > var bool = isSameArrayLike( x, y )\n    true\n\n    > x = [ NaN, NaN, NaN ];\n    > y = [ NaN, NaN, NaN ];\n    > bool = isSameArrayLike( x, y )\n    true\n\n    See Also\n    --------\n    isArrayLike, isSameArray, isSameValue\n","isSameComplex64":"\nisSameComplex64( v1, v2 )\n    Tests if two arguments are both single-precision complex floating-point\n    numbers and have the same value.\n\n    The function differs from the `===` operator in that the function treats\n    `-0` and `+0` as distinct and `NaNs` as the same.\n\n    Parameters\n    ----------\n    v1: any\n        First input value.\n\n    v2: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are the same.\n\n    Examples\n    --------\n    > var x = new Complex64( 1.0, 2.0 );\n    > var y = new Complex64( 1.0, 2.0 );\n    > var bool = isSameComplex64( x, y )\n    true\n\n    > x = new Complex64( NaN, NaN );\n    > y = new Complex64( NaN, NaN );\n    > bool = isSameComplex64( x, y )\n    true\n\n    See Also\n    --------\n    isComplex64, isSameComplex128, isSameValue\n","isSameComplex64Array":"\nisSameComplex64Array( v1, v2 )\n    Tests if two arguments are both Complex64Arrays and have the same values.\n\n    The function differs from the `===` operator in that the function treats\n    `-0` and `+0` as distinct and `NaNs` as the same.\n\n    Parameters\n    ----------\n    v1: any\n        First input value.\n\n    v2: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are the same.\n\n    Examples\n    --------\n    > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var bool = isSameComplex64Array( x, y )\n    true\n\n    > x = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\n    > y = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\n    > bool = isSameComplex64Array( x, y )\n    true\n\n    See Also\n    --------\n    isComplex64Array, isSameComplex128Array, isSameFloat32Array, isSameValue\n","isSameComplex128":"\nisSameComplex128( v1, v2 )\n    Tests if two arguments are both double-precision complex floating-point\n    numbers and have the same value.\n\n    The function differs from the `===` operator in that the function treats\n    `-0` and `+0` as distinct and `NaNs` as the same.\n\n    Parameters\n    ----------\n    v1: any\n        First input value.\n\n    v2: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are the same.\n\n    Examples\n    --------\n    > var x = new Complex128( 1.0, 2.0 );\n    > var y = new Complex128( 1.0, 2.0 );\n    > var bool = isSameComplex128( x, y )\n    true\n\n    > x = new Complex128( NaN, NaN );\n    > y = new Complex128( NaN, NaN );\n    > bool = isSameComplex128( x, y )\n    true\n\n    See Also\n    --------\n    isComplex128, isSameComplex64, isSameValue\n","isSameComplex128Array":"\nisSameComplex128Array( v1, v2 )\n    Tests if two arguments are both Complex128Arrays and have the same values.\n\n    The function differs from the `===` operator in that the function treats\n    `-0` and `+0` as distinct and `NaNs` as the same.\n\n    Parameters\n    ----------\n    v1: any\n        First input value.\n\n    v2: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are the same.\n\n    Examples\n    --------\n    > var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var bool = isSameComplex128Array( x, y )\n    true\n\n    > x = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\n    > y = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\n    > bool = isSameComplex128Array( x, y )\n    true\n\n    See Also\n    --------\n    isComplex128Array, isSameComplex64Array, isSameFloat64Array, isSameValue\n","isSameDateObject":"\nisSameDateObject( d1, d2 )\n    Tests if two values are both Date objects corresponding \n    to the same date and time.\n\n    Parameters\n    ----------\n    d1: any\n        First input value.\n    d2: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether both values are Date objects \n        corresponding to the same date and time.\n\n    Examples\n    --------\n    > var d1 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\n    > var d2 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\n    > var bool = isSameDateObject( d1, d2 )\n    true\n    > var d1 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\n    > var d2 = new Date( 2024, 11, 31, 23, 59, 59, 78 );\n    > var bool = isSameDateObject( d1, d2 )\n    false\n \n    See Also\n    --------\n    isDateObject, isSameValue\n","isSameFloat32Array":"\nisSameFloat32Array( v1, v2 )\n    Tests if two arguments are both Float32Arrays and have the same values.\n\n    The function differs from the `===` operator in that the function treats\n    `-0` and `+0` as distinct and `NaNs` as the same.\n\n    Parameters\n    ----------\n    v1: any\n        First input value.\n\n    v2: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are the same.\n\n    Examples\n    --------\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > var y = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > var bool = isSameFloat32Array( x, y )\n    true\n\n    > x = new Float32Array( [ NaN, NaN, NaN ] );\n    > y = new Float32Array( [ NaN, NaN, NaN ] );\n    > bool = isSameFloat32Array( x, y )\n    true\n\n    See Also\n    --------\n    isSameFloat64Array, isSameValue\n","isSameFloat64Array":"\nisSameFloat64Array( v1, v2 )\n    Tests if two arguments are both Float64Arrays and have the same values.\n\n    The function differs from the `===` operator in that the function treats\n    `-0` and `+0` as distinct and `NaNs` as the same.\n\n    Parameters\n    ----------\n    v1: any\n        First input value.\n\n    v2: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are the same.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > var bool = isSameFloat64Array( x, y )\n    true\n\n    > x = new Float64Array( [ NaN, NaN, NaN ] );\n    > y = new Float64Array( [ NaN, NaN, NaN ] );\n    > bool = isSameFloat64Array( x, y )\n    true\n\n    See Also\n    --------\n    isSameFloat32Array, isSameValue\n","isSameNativeClass":"\nisSameNativeClass( a, b )\n    Tests if two arguments have the same native class.\n\n    Parameters\n    ----------\n    a: any\n        First input value.\n\n    b: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments have the same native class.\n\n    Examples\n    --------\n    > var bool = isSameNativeClass( 3.14, new Number( 3.14 ) )\n    true\n    > bool = isSameNativeClass( 'beep', 'boop' )\n    true\n    > bool = isSameNativeClass( {}, [] )\n    false\n\n    See Also\n    --------\n    isSameType, isSameValue, isStrictEqual\n","isSameType":"\nisSameType( a, b )\n    Tests if two arguments have the same type.\n\n    The function uses the `typeof` operator to test for the same type.\n\n    Parameters\n    ----------\n    a: any\n        First input value.\n\n    b: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments have the same type.\n\n    Examples\n    --------\n    > var bool = isSameType( true, true )\n    true\n    > bool = isSameType( {}, [] )\n    true\n    > bool = isSameType( 3.12, -3.12 )\n    true\n    > bool = isSameType( 0.0, '0.0' )\n    false\n\n    See Also\n    --------\n    isSameNativeClass, isSameValue, isStrictEqual\n","isSameValue":"\nisSameValue( a, b )\n    Tests if two arguments are the same value.\n\n    The function differs from the `===` operator in that the function treats\n    `-0` and `+0` as distinct and `NaNs` as the same.\n\n    Parameters\n    ----------\n    a: any\n        First input value.\n\n    b: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are the same value.\n\n    Examples\n    --------\n    > var bool = isSameValue( true, true )\n    true\n    > bool = isSameValue( {}, {} )\n    false\n    > bool = isSameValue( -0.0, -0.0 )\n    true\n    > bool = isSameValue( -0.0, 0.0 )\n    false\n    > bool = isSameValue( NaN, NaN )\n    true\n\n    See Also\n    --------\n    isSameValueZero, isStrictEqual\n","isSameValueZero":"\nisSameValueZero( a, b )\n    Tests if two arguments are the same value.\n\n    The function differs from the `===` operator in that the function treats\n    `NaNs` as the same.\n\n    Parameters\n    ----------\n    a: any\n        First input value.\n\n    b: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are the same value.\n\n    Examples\n    --------\n    > var bool = isSameValueZero( true, true )\n    true\n    > bool = isSameValueZero( {}, {} )\n    false\n    > bool = isSameValueZero( -0.0, -0.0 )\n    true\n    > bool = isSameValueZero( -0.0, 0.0 )\n    true\n    > bool = isSameValueZero( NaN, NaN )\n    true\n\n    See Also\n    --------\n    isSameValue, isStrictEqual\n","isSemVer":"\nisSemVer( value )\n    Tests if a value is a semantic version string.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether a provided value is a semantic version\n        string.\n\n    Examples\n    --------\n    > var bool = isSemVer( '1.0.0' )\n    true\n    > bool = isSemVer( '1.0.0-alpha.1' )\n    true\n    > bool = isSemVer( '0.1' )\n    false\n    > bool = isSemVer( null )\n    false\n","isSharedArrayBuffer":"\nisSharedArrayBuffer( value )\n    Tests if a value is a SharedArrayBuffer.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a SharedArrayBuffer.\n\n    Examples\n    --------\n    // Assuming an environment supports SharedArrayBuffer...\n    > var bool = isSharedArrayBuffer( new SharedArrayBuffer( 10 ) )\n    true\n    > bool = isSharedArrayBuffer( [] )\n    false\n\n    See Also\n    --------\n    isArrayBuffer, isTypedArray\n","isSkewCentrosymmetricMatrix":"\nisSkewCentrosymmetricMatrix( value )\n    Tests if a value is a skew-centrosymmetric matrix.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a skew-centrosymmetric matrix.\n\n    Examples\n    --------\n    > var buf = [ 2, 1, -1, -2 ];\n    > var sh = [ 2, 2 ];\n    > var st = [ 2, 1 ];\n    > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n    > var bool = isSkewCentrosymmetricMatrix( M )\n    true\n    > bool = isSkewCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isSkewCentrosymmetricMatrix( 3.14 )\n    false\n    > bool = isSkewCentrosymmetricMatrix( {} )\n    false\n\n    See Also\n    --------\n    isCentrosymmetricMatrix, isMatrixLike, isSkewSymmetricMatrix\n","isSkewPersymmetricMatrix":"\nisSkewPersymmetricMatrix( value )\n    Tests if a value is a skew-persymmetric matrix.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a skew-persymmetric matrix.\n\n    Examples\n    --------\n    > var buf = [ 1, 0, 0, -1 ];\n    > var sh = [ 2, 2 ];\n    > var st = [ 2, 1 ];\n    > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n    > var bool = isSkewPersymmetricMatrix( M )\n    true\n    > bool = isSkewPersymmetricMatrix( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isSkewPersymmetricMatrix( 3.14 )\n    false\n    > bool = isSkewPersymmetricMatrix( {} )\n    false\n\n    See Also\n    --------\n    isMatrixLike, isPersymmetricMatrix, isSkewSymmetricMatrix\n","isSkewSymmetricMatrix":"\nisSkewSymmetricMatrix( value )\n    Tests if a value is a skew-symmetric (or antisymmetric) matrix.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a skew-symmetric matrix.\n\n    Examples\n    --------\n    > var buf = [ 0, -1, 1, 0 ];\n    > var sh = [ 2, 2 ];\n    > var st = [ 2, 1 ];\n    > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n    > var bool = isSkewSymmetricMatrix( M )\n    true\n    > bool = isSkewSymmetricMatrix( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isSkewSymmetricMatrix( 3.14 )\n    false\n    > bool = isSkewSymmetricMatrix( {} )\n    false\n\n    See Also\n    --------\n    isMatrixLike, isSkewSymmetricMatrix, isSquareMatrix\n","isSlice":"\nisSlice( value )\n    Tests if a value is a Slice object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a Slice object.\n\n    Examples\n    --------\n    > var bool = isSlice( new Slice( 10 ) )\n    true\n    > bool = isSlice( 3.14 )\n    false\n    > bool = isSlice( {} )\n    false\n\n    See Also\n    --------\n    isMultiSlice, Slice\n","isSnakecase":"\nisSnakecase( value )\n    Tests if a value is a string in snake case.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a string in snake case.\n\n    Examples\n    --------\n    > var bool = isSnakecase( 'hello_world' )\n    true\n    > bool = isSnakecase( 'Hello World' )\n    false\n\n    See Also\n    --------\n    isString","isSquareMatrix":"\nisSquareMatrix( value )\n    Tests if a value is a 2-dimensional ndarray-like object having equal\n    dimensions.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 2-dimensional ndarray-like\n        object having equal dimensions.\n\n    Examples\n    --------\n    > var buf = [ 0, 0, 0, 0 ];\n    > var sh = [ 2, 2 ];\n    > var st = [ 2, 1 ];\n    > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n    > var bool = isSquareMatrix( M )\n    true\n    > bool = isSquareMatrix( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isSquareMatrix( 3.14 )\n    false\n    > bool = isSquareMatrix( {} )\n    false\n\n    See Also\n    --------\n    isMatrixLike, isSymmetricMatrix\n","isSquareNumber":"\nisSquareNumber( value )\n    Tests if a value is a square number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a square number.\n\n    Examples\n    --------\n    > var bool = isSquareNumber( 4.0 )\n    true\n    > bool = isSquareNumber( new Number( 4.0 ) )\n    true\n    > bool = isSquareNumber( 3.14 )\n    false\n    > bool = isSquareNumber( -5.0 )\n    false\n    > bool = isSquareNumber( null )\n    false\n\n\nisSquareNumber.isPrimitive( value )\n    Tests if a value is a number primitive which is a square number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a\n        square number.\n\n    Examples\n    --------\n    > var bool = isSquareNumber.isPrimitive( 4.0 )\n    true\n    > bool = isSquareNumber.isPrimitive( new Number( 4.0 ) )\n    false\n\n\nisSquareNumber.isObject( value )\n    Tests if a value is a number object having a value which is a square number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a square number.\n\n    Examples\n    --------\n    > var bool = isSquareNumber.isObject( 4.0 )\n    false\n    > bool = isSquareNumber.isObject( new Number( 4.0 ) )\n    true\n\n\n    See Also\n    --------\n    isCubeNumber, isInteger, isNumber, isTriangularNumber\n","isSquareNumber.isPrimitive":"\nisSquareNumber.isPrimitive( value )\n    Tests if a value is a number primitive which is a square number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a\n        square number.\n\n    Examples\n    --------\n    > var bool = isSquareNumber.isPrimitive( 4.0 )\n    true\n    > bool = isSquareNumber.isPrimitive( new Number( 4.0 ) )\n    false","isSquareNumber.isObject":"\nisSquareNumber.isObject( value )\n    Tests if a value is a number object having a value which is a square number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a square number.\n\n    Examples\n    --------\n    > var bool = isSquareNumber.isObject( 4.0 )\n    false\n    > bool = isSquareNumber.isObject( new Number( 4.0 ) )\n    true\n\n\n    See Also\n    --------\n    isCubeNumber, isInteger, isNumber, isTriangularNumber","isSquareTriangularNumber":"\nisSquareTriangularNumber( value )\n    Tests if a value is a square triangular number.\n\n    Return values are not reliable for numbers greater than 1125899906842624.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a square triangular number.\n\n    Examples\n    --------\n    > var bool = isSquareTriangularNumber( 36.0 )\n    true\n    > bool = isSquareTriangularNumber( new Number( 36.0 ) )\n    true\n    > bool = isSquareTriangularNumber( 3.14 )\n    false\n    > bool = isSquareTriangularNumber( -5.0 )\n    false\n    > bool = isSquareTriangularNumber( null )\n    false\n\n\nisSquareTriangularNumber.isPrimitive( value )\n    Tests if a value is a number primitive which is a square triangular number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a\n        square triangular number.\n\n    Examples\n    --------\n    > var bool = isSquareTriangularNumber.isPrimitive( 36.0 )\n    true\n    > bool = isSquareTriangularNumber.isPrimitive( new Number( 36.0 ) )\n    false\n\n\nisSquareTriangularNumber.isObject( value )\n    Tests if a value is a number object having a value which is a square\n    triangular number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a square triangular number.\n\n    Examples\n    --------\n    > var bool = isSquareTriangularNumber.isObject( 36.0 )\n    false\n    > bool = isSquareTriangularNumber.isObject( new Number( 36.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger, isNumber, isSquareNumber, isTriangularNumber\n","isSquareTriangularNumber.isPrimitive":"\nisSquareTriangularNumber.isPrimitive( value )\n    Tests if a value is a number primitive which is a square triangular number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a\n        square triangular number.\n\n    Examples\n    --------\n    > var bool = isSquareTriangularNumber.isPrimitive( 36.0 )\n    true\n    > bool = isSquareTriangularNumber.isPrimitive( new Number( 36.0 ) )\n    false","isSquareTriangularNumber.isObject":"\nisSquareTriangularNumber.isObject( value )\n    Tests if a value is a number object having a value which is a square\n    triangular number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a square triangular number.\n\n    Examples\n    --------\n    > var bool = isSquareTriangularNumber.isObject( 36.0 )\n    false\n    > bool = isSquareTriangularNumber.isObject( new Number( 36.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger, isNumber, isSquareNumber, isTriangularNumber","isStartcase":"\nisStartcase( value )\n    Tests if a value is a startcase string.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if value is a startcase string.\n\n    Examples\n    --------\n    > var bool = isStartcase( 'Beep Boop' )\n    true\n    > bool = isStartcase( 'Beep and Boop' )\n    false\n\n    See Also\n    --------\n    isString","isStrictEqual":"\nisStrictEqual( a, b )\n    Tests if two arguments are strictly equal.\n\n    The function differs from the `===` operator in that the function treats\n    `-0` and `+0` as distinct.\n\n    Parameters\n    ----------\n    a: any\n        First input value.\n\n    b: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are strictly equal.\n\n    Examples\n    --------\n    > var bool = isStrictEqual( true, true )\n    true\n    > bool = isStrictEqual( {}, {} )\n    false\n    > bool = isStrictEqual( -0.0, -0.0 )\n    true\n    > bool = isStrictEqual( -0.0, 0.0 )\n    false\n    > bool = isStrictEqual( NaN, NaN )\n    false\n\n    See Also\n    --------\n    isSameValue\n","isString":"\nisString( value )\n    Tests if a value is a string.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a string.\n\n    Examples\n    --------\n    > var bool = isString( 'beep' )\n    true\n    > bool = isString( new String( 'beep' ) )\n    true\n    > bool = isString( 5 )\n    false\n\n\nisString.isPrimitive( value )\n    Tests if a value is a string primitive.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a string primitive.\n\n    Examples\n    --------\n    > var bool = isString.isPrimitive( 'beep' )\n    true\n    > bool = isString.isPrimitive( new String( 'beep' ) )\n    false\n\n\nisString.isObject( value )\n    Tests if a value is a `String` object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a `String` object.\n\n    Examples\n    --------\n    > var bool = isString.isObject( new String( 'beep' ) )\n    true\n    > bool = isString.isObject( 'beep' )\n    false\n\n","isString.isPrimitive":"\nisString.isPrimitive( value )\n    Tests if a value is a string primitive.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a string primitive.\n\n    Examples\n    --------\n    > var bool = isString.isPrimitive( 'beep' )\n    true\n    > bool = isString.isPrimitive( new String( 'beep' ) )\n    false","isString.isObject":"\nisString.isObject( value )\n    Tests if a value is a `String` object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a `String` object.\n\n    Examples\n    --------\n    > var bool = isString.isObject( new String( 'beep' ) )\n    true\n    > bool = isString.isObject( 'beep' )\n    false","isStringArray":"\nisStringArray( value )\n    Tests if a value is an array of strings.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array of strings.\n\n    Examples\n    --------\n    > var bool = isStringArray( [ 'abc', 'def' ] )\n    true\n    > bool = isStringArray( [ 'abc', 123 ] )\n    false\n\n\nisStringArray.primitives( value )\n    Tests if a value is an array containing only string primitives.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array containing only string\n        primitives.\n\n    Examples\n    --------\n    > var arr = [ 'abc', 'def' ];\n    > var bool = isStringArray.primitives( arr )\n    true\n    > arr = [ 'abc', new String( 'def' ) ];\n    > bool = isStringArray.primitives( arr )\n    false\n\n\nisStringArray.objects( value )\n    Tests if a value is an array containing only `String` objects.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array containing only `String`\n        objects.\n\n    Examples\n    --------\n    > var arr = [ new String( 'ab' ), new String( 'cd' ) ];\n    > var bool = isStringArray.objects( arr )\n    true\n    > arr = [ new String( 'abc' ), 'def' ];\n    > bool = isStringArray.objects( arr )\n    false\n\n    See Also\n    --------\n    isArray, isString\n","isStringArray.primitives":"\nisStringArray.primitives( value )\n    Tests if a value is an array containing only string primitives.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array containing only string\n        primitives.\n\n    Examples\n    --------\n    > var arr = [ 'abc', 'def' ];\n    > var bool = isStringArray.primitives( arr )\n    true\n    > arr = [ 'abc', new String( 'def' ) ];\n    > bool = isStringArray.primitives( arr )\n    false","isStringArray.objects":"\nisStringArray.objects( value )\n    Tests if a value is an array containing only `String` objects.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array containing only `String`\n        objects.\n\n    Examples\n    --------\n    > var arr = [ new String( 'ab' ), new String( 'cd' ) ];\n    > var bool = isStringArray.objects( arr )\n    true\n    > arr = [ new String( 'abc' ), 'def' ];\n    > bool = isStringArray.objects( arr )\n    false\n\n    See Also\n    --------\n    isArray, isString","isSymbol":"\nisSymbol( value )\n    Tests if a value is a symbol.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a symbol.\n\n    Examples\n    --------\n    > var bool = isSymbol( Symbol( 'beep' ) )\n    true\n    > bool = isSymbol( Object( Symbol( 'beep' ) ) )\n    true\n    > bool = isSymbol( {} )\n    false\n    > bool = isSymbol( null )\n    false\n    > bool = isSymbol( true )\n    false\n\n","isSymbolArray":"\nisSymbolArray( value )\n    Tests if a value is an array-like object containing only symbols.\n\n    In pre-ES2015 environments, the function always returns `false`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only symbols.\n\n    Examples\n    --------\n    > var bool = isSymbolArray( [ Symbol( 'beep' ), Symbol( 'boop' ) ] )\n    true\n    > bool = isSymbolArray( Symbol( 'beep' ) )\n    false\n    > bool = isSymbolArray( [] )\n    false\n    > bool = isSymbolArray( {} )\n    false\n    > bool = isSymbolArray( null )\n    false\n    > bool = isSymbolArray( true )\n    false\n\n\nisSymbolArray.primitives( value )\n    Tests if a value is an array-like object containing only `symbol`\n    primitives.\n\n    In pre-ES2015 environments, the function always returns `false`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only `symbol` primitives.\n\n    Examples\n    --------\n    > var bool = isSymbolArray.primitives( [ Symbol( 'beep' ) ] )\n    true\n    > bool = isSymbolArray.primitives( [ Object( Symbol( 'beep' ) ) ] )\n    false\n    > bool = isSymbolArray.primitives( [] )\n    false\n    > bool = isSymbolArray.primitives( {} )\n    false\n    > bool = isSymbolArray.primitives( null )\n    false\n    > bool = isSymbolArray.primitives( true )\n    false\n\n\nisSymbolArray.objects( value )\n    Tests if a value is an array-like object containing only `Symbol`\n    objects.\n\n    In pre-ES2015 environments, the function always returns `false`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only `Symbol` objects.\n\n    Examples\n    --------\n    > var bool = isSymbolArray.objects( [ Object( Symbol( 'beep' ) ) ] )\n    true\n    > bool = isSymbolArray.objects( [ Symbol( 'beep' ) ] )\n    false\n    > bool = isSymbolArray.objects( [] )\n    false\n    > bool = isSymbolArray.objects( {} )\n    false\n    > bool = isSymbolArray.objects( null )\n    false\n    > bool = isSymbolArray.objects( true )\n    false\n\n    See Also\n    --------\n    isArray, isSymbol\n","isSymbolArray.primitives":"\nisSymbolArray.primitives( value )\n    Tests if a value is an array-like object containing only `symbol`\n    primitives.\n\n    In pre-ES2015 environments, the function always returns `false`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only `symbol` primitives.\n\n    Examples\n    --------\n    > var bool = isSymbolArray.primitives( [ Symbol( 'beep' ) ] )\n    true\n    > bool = isSymbolArray.primitives( [ Object( Symbol( 'beep' ) ) ] )\n    false\n    > bool = isSymbolArray.primitives( [] )\n    false\n    > bool = isSymbolArray.primitives( {} )\n    false\n    > bool = isSymbolArray.primitives( null )\n    false\n    > bool = isSymbolArray.primitives( true )\n    false","isSymbolArray.objects":"\nisSymbolArray.objects( value )\n    Tests if a value is an array-like object containing only `Symbol`\n    objects.\n\n    In pre-ES2015 environments, the function always returns `false`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only `Symbol` objects.\n\n    Examples\n    --------\n    > var bool = isSymbolArray.objects( [ Object( Symbol( 'beep' ) ) ] )\n    true\n    > bool = isSymbolArray.objects( [ Symbol( 'beep' ) ] )\n    false\n    > bool = isSymbolArray.objects( [] )\n    false\n    > bool = isSymbolArray.objects( {} )\n    false\n    > bool = isSymbolArray.objects( null )\n    false\n    > bool = isSymbolArray.objects( true )\n    false\n\n    See Also\n    --------\n    isArray, isSymbol","isSymmetricMatrix":"\nisSymmetricMatrix( value )\n    Tests if a value is a square matrix which equals its transpose.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a symmetric matrix.\n\n    Examples\n    --------\n    > var buf = [ 0, 1, 1, 2 ];\n    > var sh = [ 2, 2 ];\n    > var st = [ 2, 1 ];\n    > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n    > var bool = isSymmetricMatrix( M )\n    true\n    > bool = isSymmetricMatrix( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isSymmetricMatrix( 3.14 )\n    false\n    > bool = isSymmetricMatrix( {} )\n    false\n\n    See Also\n    --------\n    isMatrixLike, isNonSymmetricMatrix, isSquareMatrix\n","isSyntaxError":"\nisSyntaxError( value )\n    Tests if a value is a SyntaxError object.\n\n    This function should *not* be considered robust. While the function should\n    always return `true` if provided a SyntaxError (or a descendant) object,\n    false positives may occur due to the fact that the SyntaxError constructor\n    inherits from Error and has no internal class of its own. Hence, SyntaxError\n    impersonation is possible.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a SyntaxError object.\n\n    Examples\n    --------\n    > var bool = isSyntaxError( new SyntaxError( 'beep' ) )\n    true\n    > bool = isSyntaxError( {} )\n    false\n\n    See Also\n    --------\n    isError\n","isTriangularNumber":"\nisTriangularNumber( value )\n    Tests if a value is a triangular number.\n\n    Return values are not reliable for numbers greater than 1125899906842624.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a triangular number.\n\n    Examples\n    --------\n    > var bool = isTriangularNumber( 36.0 )\n    true\n    > bool = isTriangularNumber( new Number( 36.0 ) )\n    true\n    > bool = isTriangularNumber( 3.14 )\n    false\n    > bool = isTriangularNumber( -5.0 )\n    false\n    > bool = isTriangularNumber( null )\n    false\n\n\nisTriangularNumber.isPrimitive( value )\n    Tests if a value is a number primitive which is a triangular number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a\n        triangular number.\n\n    Examples\n    --------\n    > var bool = isTriangularNumber.isPrimitive( 36.0 )\n    true\n    > bool = isTriangularNumber.isPrimitive( new Number( 36.0 ) )\n    false\n\n\nisTriangularNumber.isObject( value )\n    Tests if a value is a number object having a value which is a triangular\n    number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a triangular number.\n\n    Examples\n    --------\n    > var bool = isTriangularNumber.isObject( 36.0 )\n    false\n    > bool = isTriangularNumber.isObject( new Number( 36.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger, isNumber, isSquareNumber, isSquareTriangularNumber\n","isTriangularNumber.isPrimitive":"\nisTriangularNumber.isPrimitive( value )\n    Tests if a value is a number primitive which is a triangular number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a\n        triangular number.\n\n    Examples\n    --------\n    > var bool = isTriangularNumber.isPrimitive( 36.0 )\n    true\n    > bool = isTriangularNumber.isPrimitive( new Number( 36.0 ) )\n    false","isTriangularNumber.isObject":"\nisTriangularNumber.isObject( value )\n    Tests if a value is a number object having a value which is a triangular\n    number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a triangular number.\n\n    Examples\n    --------\n    > var bool = isTriangularNumber.isObject( 36.0 )\n    false\n    > bool = isTriangularNumber.isObject( new Number( 36.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger, isNumber, isSquareNumber, isSquareTriangularNumber","isTruthy":"\nisTruthy( value )\n    Tests if a value is a value which translates to `true` when evaluated in a\n    boolean context.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is truthy.\n\n    Examples\n    --------\n     > var bool = isTruthy( true )\n    true\n    > bool = isTruthy( {} )\n    true\n    > bool = isTruthy( [] )\n    true\n    > bool = isTruthy( false )\n    false\n    > bool = isTruthy( '' )\n    false\n    > bool = isTruthy( 0 )\n    false\n    > bool = isTruthy( null )\n    false\n    > bool = isTruthy( void 0 )\n    false\n    > bool = isTruthy( NaN )\n    false\n\n    See Also\n    --------\n    isFalsy\n","isTruthyArray":"\nisTruthyArray( value )\n    Tests if a value is an array-like object containing only truthy values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only truthy values.\n\n    Examples\n    --------\n    > var bool = isTruthyArray( [ {}, [] ] )\n    true\n    > bool = isTruthyArray( [ null, '' ] )\n    false\n    > bool = isTruthyArray( [] )\n    false\n\n    See Also\n    --------\n    isFalsyArray, isTruthy\n","isTypedArray":"\nisTypedArray( value )\n    Tests if a value is a typed array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a typed array.\n\n    Examples\n    --------\n    > var bool = isTypedArray( new Int8Array( 10 ) )\n    true\n\n    See Also\n    --------\n    isArray, isTypedArrayLike\n","isTypedArrayLength":"\nisTypedArrayLength( value )\n    Tests if a value is a valid typed array length.\n\n    A valid length property for a typed array instance is any integer value on\n    the interval [0, 2^53-1].\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a valid typed array length.\n\n    Examples\n    --------\n    > var bool = isTypedArrayLength( 5 )\n    true\n    > bool = isTypedArrayLength( 2.0e200 )\n    false\n    > bool = isTypedArrayLength( -3.14 )\n    false\n    > bool = isTypedArrayLength( null )\n    false\n\n    See Also\n    --------\n    isArrayLength, isTypedArray\n","isTypedArrayLike":"\nisTypedArrayLike( value )\n    Tests if a value is typed-array-like.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is typed-array-like.\n\n    Examples\n    --------\n    > var bool = isTypedArrayLike( new Int16Array() )\n    true\n    > bool = isTypedArrayLike({\n    ...    'length': 10,\n    ...    'byteOffset': 0,\n    ...    'byteLength': 10,\n    ...    'BYTES_PER_ELEMENT': 4\n    ... })\n    true\n\n    See Also\n    --------\n    isTypedArray\n","isTypeError":"\nisTypeError( value )\n    Tests if a value is a TypeError object.\n\n    This function should *not* be considered robust. While the function should\n    always return `true` if provided a TypeError (or a descendant) object,\n    false positives may occur due to the fact that the TypeError constructor\n    inherits from Error and has no internal class of its own. Hence, TypeError\n    impersonation is possible.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a TypeError object.\n\n    Examples\n    --------\n    > var bool = isTypeError( new TypeError( 'beep' ) )\n    true\n    > bool = isTypeError( {} )\n    false\n\n    See Also\n    --------\n    isError\n","isUint8Array":"\nisUint8Array( value )\n    Tests if a value is a Uint8Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Uint8Array.\n\n    Examples\n    --------\n    > var bool = isUint8Array( new Uint8Array( 10 ) )\n    true\n    > bool = isUint8Array( [] )\n    false\n\n    See Also\n    --------\n    isTypedArray, isUint16Array, isUint32Array\n","isUint8ClampedArray":"\nisUint8ClampedArray( value )\n    Tests if a value is a Uint8ClampedArray.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Uint8ClampedArray.\n\n    Examples\n    --------\n    > var bool = isUint8ClampedArray( new Uint8ClampedArray( 10 ) )\n    true\n    > bool = isUint8ClampedArray( [] )\n    false\n\n    See Also\n    --------\n    isTypedArray, isUint8Array\n","isUint16Array":"\nisUint16Array( value )\n    Tests if a value is a Uint16Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Uint16Array.\n\n    Examples\n    --------\n    > var bool = isUint16Array( new Uint16Array( 10 ) )\n    true\n    > bool = isUint16Array( [] )\n    false\n\n    See Also\n    --------\n    isTypedArray, isUint32Array, isUint8Array\n","isUint32Array":"\nisUint32Array( value )\n    Tests if a value is a Uint32Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Uint32Array.\n\n    Examples\n    --------\n    > var bool = isUint32Array( new Uint32Array( 10 ) )\n    true\n    > bool = isUint32Array( [] )\n    false\n\n    See Also\n    --------\n    isTypedArray, isUint16Array, isUint8Array\n","isUNCPath":"\nisUNCPath( value )\n    Tests if a value is a UNC path.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a UNC path.\n\n    Examples\n    --------\n    > var bool = isUNCPath( '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz' )\n    true\n    > bool = isUNCPath( '/foo/bar/baz' )\n    false\n\n","isUndefined":"\nisUndefined( value )\n    Tests if a value is undefined.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is undefined.\n\n    Examples\n    --------\n    > var bool = isUndefined( void 0 )\n    true\n    > bool = isUndefined( null )\n    false\n\n    See Also\n    --------\n    isNull, isUndefinedOrNull\n","isUndefinedOrNull":"\nisUndefinedOrNull( value )\n    Tests if a value is undefined or null.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is undefined or null.\n\n    Examples\n    --------\n    > var bool = isUndefinedOrNull( void 0 )\n    true\n    > bool = isUndefinedOrNull( null )\n    true\n    > bool = isUndefinedOrNull( false )\n    false\n\n    See Also\n    --------\n    isNull, isUndefined\n","isUnityProbabilityArray":"\nisUnityProbabilityArray( value )\n    Tests if a value is an array of probabilities that sum to one.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array of probabilities that sum\n        to one.\n\n    Examples\n    --------\n    > var bool = isUnityProbabilityArray( [ 0.25, 0.5, 0.25 ] )\n    true\n    > bool = isUnityProbabilityArray( new Uint8Array( [ 0, 1 ] ) )\n    true\n    > bool = isUnityProbabilityArray( [ 0.4, 0.4, 0.4 ] )\n    false\n    > bool = isUnityProbabilityArray( [ 3.14, 0.0 ] )\n    false\n\n    See Also\n    --------\n    isProbability, isProbabilityArray\n","isUppercase":"\nisUppercase( value )\n    Tests if a value is an uppercase string.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an uppercase string.\n\n    Examples\n    --------\n    > var bool = isUppercase( 'HELLO' )\n    true\n    > bool = isUppercase( 'World' )\n    false\n\n    See Also\n    --------\n    isLowercase, isString\n","isURI":"\nisURI( value )\n    Tests if a value is a URI.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a URI.\n\n    Examples\n    --------\n    > var bool = isURI( 'http://google.com' )\n    true\n    > bool = isURI( 'http://localhost/' )\n    true\n    > bool = isURI( 'http://example.w3.org/path%20with%20spaces.html' )\n    true\n    > bool = isURI( 'ftp://ftp.is.co.za/rfc/rfc1808.txt' )\n    true\n\n    // No scheme:\n    > bool = isURI( '' )\n    false\n    > bool = isURI( 'foo@bar' )\n    false\n    > bool = isURI( '://foo/' )\n    false\n\n    // Illegal characters:\n    > bool = isURI( 'http://<foo>' )\n    false\n\n    // Invalid path:\n    > bool = isURI( 'http:////foo.html' )\n    false\n\n    // Incomplete hex escapes:\n    > bool = isURI( 'http://example.w3.org/%a' )\n    false\n\n","isURIError":"\nisURIError( value )\n    Tests if a value is a URIError object.\n\n    This function should *not* be considered robust. While the function should\n    always return `true` if provided a URIError (or a descendant) object,\n    false positives may occur due to the fact that the URIError constructor\n    inherits from Error and has no internal class of its own. Hence, URIError\n    impersonation is possible.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a URIError object.\n\n    Examples\n    --------\n    > var bool = isURIError( new URIError( 'beep' ) )\n    true\n    > bool = isURIError( {} )\n    false\n\n    See Also\n    --------\n    isError\n","isVectorLike":"\nisVectorLike( value )\n    Tests if a value is a 1-dimensional ndarray-like object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 1-dimensional ndarray-like\n        object.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = [ 0, 0, 0, 0 ];\n    > M.ndims = 1;\n    > M.shape = [ 4 ];\n    > M.strides = [ 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'generic';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isVectorLike( M )\n    true\n    > bool = isVectorLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isVectorLike( 3.14 )\n    false\n    > bool = isVectorLike( {} )\n    false\n\n    See Also\n    --------\n    isArray, isArrayLike, isMatrixLike, isndarrayLike, isTypedArrayLike\n","isWebAssemblyMemory":"\nisWebAssemblyMemory( value )\n    Tests if a value is a WebAssembly memory instance.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a WebAssembly memory instance.\n\n    Examples\n    --------\n    > var bool = isWebAssemblyMemory( {} )\n    false\n\n    See Also\n    --------\n    hasWebAssemblySupport\n","isWellFormedString":"\nisWellFormedString( str )\n    Tests if a string is well-formed.\n\n    Parameters\n    ----------\n    str: any\n        String to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether str is well-formed.\n\n    Examples\n    --------\n    > var bool = isWellFormedString( '' )\n    true\n\n    > bool = isWellFormedString( new String( '' ) )\n    true\n\n    > bool = isWellFormedString( '\\uDBFF' )\n    false\n\n    > bool = isWellFormedString( '\\uDBFFFF\\uDBFF' )\n    false\n\n    > bool = isWellFormedString( [] )\n    false\n\n    > bool = isWellFormedString( '-5' )\n    true\n\n    > bool = isWellFormedString( null )\n    false\n\n\nisWellFormedString.isPrimitive( str )\n    Tests if a string is a well-formed string primitive.\n\n    Parameters\n    ----------\n    str: any\n        String to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether str is a well-formed string primitive.\n\n    Examples\n    --------\n    > var bool = isWellFormedString.isPrimitive( '' )\n    true\n    > bool = isWellFormedString.isPrimitive( new String( '' ) )\n    false\n\n\nisWellFormedString.isObject( str )\n    Tests if a string is a well-formed string object.\n\n    Parameters\n    ----------\n    str: any\n        String to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether str is a well-formed string object.\n\n    Examples\n    --------\n    > var bool = isWellFormedString.isObject( '' )\n    false\n    > bool = isWellFormedString.isObject( new String( '' ) )\n    true\n\n","isWellFormedString.isPrimitive":"\nisWellFormedString.isPrimitive( str )\n    Tests if a string is a well-formed string primitive.\n\n    Parameters\n    ----------\n    str: any\n        String to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether str is a well-formed string primitive.\n\n    Examples\n    --------\n    > var bool = isWellFormedString.isPrimitive( '' )\n    true\n    > bool = isWellFormedString.isPrimitive( new String( '' ) )\n    false","isWellFormedString.isObject":"\nisWellFormedString.isObject( str )\n    Tests if a string is a well-formed string object.\n\n    Parameters\n    ----------\n    str: any\n        String to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether str is a well-formed string object.\n\n    Examples\n    --------\n    > var bool = isWellFormedString.isObject( '' )\n    false\n    > bool = isWellFormedString.isObject( new String( '' ) )\n    true","isWhitespace":"\nisWhitespace( str )\n    Tests whether a string contains only white space characters.\n\n    A white space character is defined as one of the 25 characters defined as a\n    white space (\"WSpace=Y\",\"WS\") character in the Unicode 9.0 character\n    database, as well as one related white space character without the Unicode\n    character property \"WSpace=Y\" (zero width non-breaking space which was\n    deprecated as of Unicode 3.2).\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a string contains only white space\n        characters.\n\n    Examples\n    --------\n    > var bool = isWhitespace( '       ' )\n    true\n    > bool = isWhitespace( 'abcdef' )\n    false\n    > bool = isWhitespace( '' )\n    false\n\n    See Also\n    --------\n    reWhitespace\n","isWritableProperty":"\nisWritableProperty( value, property )\n    Tests if an object's own property is writable.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own property is writable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.writable = false;\n    > desc.value = 'beep';\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isWritableProperty( obj, 'boop' )\n    true\n    > bool = isWritableProperty( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    isReadableProperty, isReadWriteProperty, isWritablePropertyIn, isWriteOnlyProperty\n","isWritablePropertyIn":"\nisWritablePropertyIn( value, property )\n    Tests if an object's own or inherited property is writable.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own or inherited property is writable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.writable = false;\n    > desc.value = 'beep';\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isWritablePropertyIn( obj, 'boop' )\n    true\n    > bool = isWritablePropertyIn( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    isReadablePropertyIn, isReadWritePropertyIn, isWritableProperty, isWriteOnlyPropertyIn\n","isWriteOnlyProperty":"\nisWriteOnlyProperty( value, property )\n    Tests if an object's own property is write-only.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own property is write-only.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = true;\n    > desc.set = function setter( v ) { obj.boop = v; };\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isWriteOnlyProperty( obj, 'boop' )\n    false\n    > bool = isWriteOnlyProperty( obj, 'beep' )\n    true\n\n    See Also\n    --------\n    isReadOnlyProperty, isReadWriteProperty, isWritableProperty, isWriteOnlyPropertyIn\n","isWriteOnlyPropertyIn":"\nisWriteOnlyPropertyIn( value, property )\n    Tests if an object's own or inherited property is write-only.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own or inherited property is write-\n        only.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = true;\n    > desc.set = function setter( v ) { obj.boop = v; };\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isWriteOnlyPropertyIn( obj, 'boop' )\n    false\n    > bool = isWriteOnlyPropertyIn( obj, 'beep' )\n    true\n\n    See Also\n    --------\n    isReadOnlyPropertyIn, isReadWritePropertyIn, isWritablePropertyIn, isWriteOnlyProperty\n","iterAbs":"\niterAbs( iterator )\n    Returns an iterator which iteratively computes the absolute value.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAbs( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.abs, iterAbs2\n","iterAbs2":"\niterAbs2( iterator )\n    Returns an iterator which iteratively computes the squared absolute value.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAbs2( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.abs2, iterAbs\n","iterAcos":"\niterAcos( iterator )\n    Returns an iterator which iteratively computes the arccosine.\n\n    The domain of arccosine is restricted to [-1,1]. If an iterated value is\n    outside of the domain, the returned iterator returns `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAcos( random.iterators.uniform( -1.0, 1.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.acos, iterAcosh, iterAsin, iterAtan\n","iterAcosh":"\niterAcosh( iterator )\n    Returns an iterator which iteratively computes the hyperbolic arccosine.\n\n    The domain of the hyperbolic arccosine is restricted to [1,+infinity). If an\n    iterated value is outside of the domain, the returned iterator returns\n    `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAcosh( random.iterators.uniform( 1.0, 10.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.acosh, iterAcos, iterAsinh, iterAtanh\n","iterAcot":"\niterAcot( iterator )\n    Returns an iterator which iteratively computes the inverse cotangent.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAcot( random.iterators.uniform( -5.0, 5.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.acot, iterAcos, iterAcoth, iterAsin, iterAtan\n","iterAcoth":"\niterAcoth( iterator )\n    Returns an iterator which iteratively computes the inverse hyperbolic\n    cotangent.\n\n    The domain of the inverse hyperbolic cotangent is restricted to (-inf,-1]\n    and [1,inf). If an iterated value is outside of the domain, the returned\n    iterator returns `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAcoth( random.iterators.uniform( 1.0, 10.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.acoth, iterAcosh, iterAcot, iterAsinh, iterAtanh\n","iterAcovercos":"\niterAcovercos( iterator )\n    Returns an iterator which iteratively computes the inverse coversed cosine.\n\n    The domain of inverse coversed cosine is restricted to [-2,0]. If an\n    iterated value is outside of the domain, the returned iterator returns\n    `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAcovercos( random.iterators.uniform( -2.0, 0.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.acovercos, iterAcoversin, iterAvercos, iterCovercos, iterVercos\n","iterAcoversin":"\niterAcoversin( iterator )\n    Returns an iterator which iteratively computes the inverse coversed sine.\n\n    The domain of inverse coversed sine is restricted to [0,2]. If an iterated\n    value is outside of the domain, the returned iterator returns `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAcoversin( random.iterators.uniform( 0.0, 2.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.acoversin, iterAcovercos, iterAversin, iterCoversin, iterVersin\n","iterAdd":"\niterAdd( iter0, ...iterator )\n    Returns an iterator which performs element-wise addition of two or more\n    iterators.\n\n    The length of the returned iterator is equal to the length of the shortest\n    provided iterator. In other words, the returned iterator ends once *one* of\n    the provided iterators ends.\n\n    If provided a numeric value as an iterator argument, the value is broadcast\n    as an infinite iterator which always returns the provided value.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iter0: Object\n        Input iterator.\n\n    iterator: ...Object\n        Iterators to add.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1.0, 2.0 ] );\n    > var it2 = array2iterator( [ 3.0, 4.0 ] );\n    > var it = iterAdd( it1, it2 );\n    > var v = it.next().value\n    4.0\n    > v = it.next().value\n    6.0\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterDivide, iterMultiply, iterSubtract\n","iterAdvance":"\niterAdvance( iterator[, n] )\n    Advances an entire iterator.\n\n    The function *eagerly* advances an input iterator `n` iterations or until\n    the input iterator finishes, whichever comes first.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator to advance.\n\n    n: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Input iterator.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n    > var it = iterAdvance( arr, 4 );\n    > var v = it.next().value\n    1\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterHead, iterSlice\n","iterAhavercos":"\niterAhavercos( iterator )\n    Returns an iterator which iteratively computes the inverse half-value versed\n    cosine.\n\n    The domain of inverse half-value versed cosine is restricted to [0,1]. If\n    an iterated value is outside of the domain, the returned iterator returns\n    `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAhavercos( random.iterators.uniform( 0.0, 1.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.ahavercos, iterAhaversin, iterHavercos, iterVercos\n","iterAhaversin":"\niterAhaversin( iterator )\n    Returns an iterator which iteratively computes the inverse half-value versed\n    sine.\n\n    The domain of inverse half-value versed sine is restricted to [-2,0]. If an\n    iterated value is outside of the domain, the returned iterator returns\n    `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAhaversin( random.iterators.uniform( 0.0, 1.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.ahaversin, iterAhavercos, iterHaversin, iterVersin\n","iterAny":"\niterAny( iterator )\n    Tests whether at least one iterated value is truthy.\n\n    The function immediately returns upon encountering a truthy value.\n\n    If provided an iterator which does not return any iterated values, the\n    function returns `false`.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if a value is truthy; otherwise, the\n        function returns `false`.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n    > var bool = iterAny( arr )\n    true\n\n    See Also\n    --------\n    iterAnyBy, iterEvery, iterForEach, iterNone, iterSome\n","iterAnyBy":"\niterAnyBy( iterator, predicate[, thisArg ] )\n    Tests whether at least one iterated value passes a test implemented by a\n    predicate function.\n\n    The predicate function is provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index.\n\n    The function immediately returns upon encountering a truthy return value.\n\n    If provided an iterator which does not return any iterated values, the\n    function returns `false`.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if a predicate function returns a truthy\n        value for any iterated value. Otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n    > function fcn( v ) { return ( v === 1 ); };\n    > var bool = iterAnyBy( arr, fcn )\n    true\n\n    See Also\n    --------\n    iterAny, iterEveryBy, iterForEach, iterNoneBy, iterSomeBy\n","iterAsin":"\niterAsin( iterator )\n    Returns an iterator which iteratively computes the arcsine.\n\n    The domain of arcsine is restricted to [-1,1]. If an iterated value is\n    outside of the domain, the returned iterator returns `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAsin( random.iterators.uniform( -1.0, 1.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.asin, iterAcos, iterAsinh, iterAtan\n","iterAsinh":"\niterAsinh( iterator )\n    Returns an iterator which iteratively computes the hyperbolic arcsine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAsinh( random.iterators.uniform( -2.0, 2.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.asinh, iterAcosh, iterAsin, iterAtanh\n","iterAtan":"\niterAtan( iterator )\n    Returns an iterator which iteratively computes the arctangent.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAtan( random.iterators.uniform( -2.0, 2.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.atan, iterAcos, iterAsin, iterAtanh\n","iterAtan2":"\niterAtan2( y, x )\n    Returns an iterator which iteratively computes the angle in the plane (in\n    radians) between the positive x-axis and the ray from (0,0) to the point\n    (x,y).\n\n    The length of the returned iterator is equal to the length of the shortest\n    provided iterator. In other words, the returned iterator ends once *one* of\n    the provided iterators ends.\n\n    If provided a numeric value as an iterator argument, the value is broadcast\n    as an infinite iterator which always returns the provided value.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    y: Object|number\n        Input iterator.\n\n    x: Object|number\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = random.iterators.uniform( -2.0, 2.0 );\n    > var y = random.iterators.uniform( -2.0, 2.0 );\n    > var it = iterAtan2( y, x );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.atan2, iterAtan\n","iterAtanh":"\niterAtanh( iterator )\n    Returns an iterator which iteratively computes the hyperbolic arctangent.\n\n    The domain of hyperbolic arctangent is restricted to [-1,1]. If an iterated\n    value is outside of the domain, the returned iterator returns `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAtanh( random.iterators.uniform( -1.0, 1.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.atanh, iterAcosh, iterAsinh, iterAtan\n","iterator2array":"\niterator2array( iterator[, out][, mapFcn[, thisArg]] )\n    Creates (or fills) an array from an iterator.\n\n    When invoked, an input function is provided two arguments:\n\n    - value: iterated value.\n    - index: iterated value index (zero-based).\n\n    If provided an output array, the function fills the output array with\n    iterated values.\n\n    Iteration stops when an output array is full or an iterator finishes;\n    whichever comes first.\n\n    Parameters\n    ----------\n    iterator: Object\n        Source iterator.\n\n    out: ArrayLikeObject (optional)\n        Output array-like object.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var opts = { 'iter': 10 };\n    > var arr = iterator2array( random.iterators.randu( opts ) )\n\n    See Also\n    --------\n    array2iterator, iterator2arrayview\n","iterator2arrayview":"\niterator2arrayview( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )\n    Fills an array-like object view with values returned from an iterator.\n\n    When invoked, an input function is provided three arguments:\n\n    - value: iterated value.\n    - index: destination index (zero-based).\n    - n: iteration index (zero-based).\n\n    Iteration stops when an output array view is full or an iterator finishes;\n    whichever comes first.\n\n    Parameters\n    ----------\n    iterator: Object\n        Source iterator.\n\n    dest: ArrayLikeObject\n        Output array-like object.\n\n    begin: integer (optional)\n        Starting index (inclusive). When negative, determined relative to the\n        last element. Default: 0.\n\n    end: integer (optional)\n        Ending index (non-inclusive). When negative, determined relative to the\n        last element. Default: dest.length.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var it = random.iterators.randu({ 'iter': 10 });\n    > var out = new Float64Array( 20 );\n    > var arr = iterator2arrayview( it, out, 5, 15 )\n\n    See Also\n    --------\n    iterator2array, arrayview2iterator, iterator2arrayviewRight\n","iterator2arrayviewRight":"\niterator2arrayviewRight( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )\n    Fills an array-like object view from right to left with values returned from\n    an iterator.\n\n    When invoked, an input function is provided three arguments:\n\n    - value: iterated value.\n    - index: destination index (zero-based).\n    - n: iteration index (zero-based).\n\n    Iteration stops when an output array view is full or an iterator finishes;\n    whichever comes first.\n\n    Parameters\n    ----------\n    iterator: Object\n        Source iterator.\n\n    dest: ArrayLikeObject\n        Output array-like object.\n\n    begin: integer (optional)\n        Starting index (inclusive). When negative, determined relative to the\n        last element. Default: 0.\n\n    end: integer (optional)\n        Ending index (non-inclusive). When negative, determined relative to the\n        last element. Default: dest.length.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var it = random.iterators.randu({ 'iter': 10 });\n    > var out = new Float64Array( 20 );\n    > var arr = iterator2arrayviewRight( it, out, 5, 15 )\n\n    See Also\n    --------\n    iterator2array, arrayview2iteratorRight, iterator2arrayview\n","iteratorStream":"\niteratorStream( iterator[, options] )\n    Creates a readable stream from an iterator.\n\n    In object mode, `null` is a reserved value. If an iterator generates `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or explicitly map `null`\n    values to a different value by wrapping the provided iterator with another\n    iterator.\n\n    In binary mode, if an iterator generates `undefined` values, the stream will\n    emit an error. Consider providing a custom serialization function or\n    explicitly map `undefined` values to a different value by wrapping the\n    provided iterator with another iterator.\n\n    If a serialization function fails to return a string or Buffer, the stream\n    emits an error.\n\n    Parameters\n    ----------\n    iterator: Object\n        Source iterator.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing iteration.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize iterated\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var it = random.iterators.randu( opts );\n    > var s = iteratorStream( it );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\niteratorStream.factory( [options] )\n    Returns a function for creating readable streams from iterators.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing iteration.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize iterated\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = iteratorStream.factory( opts );\n\n\niteratorStream.objectMode( iterator[, options] )\n    Returns an \"objectMode\" readable stream from an iterator.\n\n    In object mode, `null` is a reserved value. If an iterator generates `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or explicitly map `null`\n    values to a different value by wrapping the provided iterator with another\n    iterator.\n\n    Parameters\n    ----------\n    iterator: Object\n        Source iterator.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before pausing iteration.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var it = random.iterators.randu( opts );\n    > var s = iteratorStream.objectMode( it );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    arrayStream\n","iteratorStream.factory":"\niteratorStream.factory( [options] )\n    Returns a function for creating readable streams from iterators.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing iteration.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize iterated\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = iteratorStream.factory( opts );","iteratorStream.objectMode":"\niteratorStream.objectMode( iterator[, options] )\n    Returns an \"objectMode\" readable stream from an iterator.\n\n    In object mode, `null` is a reserved value. If an iterator generates `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or explicitly map `null`\n    values to a different value by wrapping the provided iterator with another\n    iterator.\n\n    Parameters\n    ----------\n    iterator: Object\n        Source iterator.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before pausing iteration.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var it = random.iterators.randu( opts );\n    > var s = iteratorStream.objectMode( it );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    arrayStream","IteratorSymbol":"\nIteratorSymbol\n    Iterator symbol.\n\n    This symbol specifies the default iterator for an object.\n\n    The symbol is only supported in ES6/ES2015+ environments. For non-supporting\n    environments, the value is `null`.\n\n    Examples\n    --------\n    > var s = IteratorSymbol\n\n    See Also\n    --------\n    Symbol\n","iterAvercos":"\niterAvercos( iterator )\n    Returns an iterator which iteratively computes the inverse versed cosine.\n\n    The domain of inverse versed cosine is restricted to [-2,0]. If an iterated\n    value is outside of the domain, the returned iterator returns `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAvercos( random.iterators.uniform( -2.0, 0.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.avercos, iterAversin, iterVersin\n","iterAversin":"\niterAversin( iterator )\n    Returns an iterator which iteratively computes the inverse versed sine.\n\n    The domain of inverse versed sine is restricted to [0,2]. If an iterated\n    value is outside of the domain, the returned iterator returns `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAversin( random.iterators.uniform( 0.0, 2.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.aversin, iterAvercos, iterVercos\n","iterawgn":"\niterawgn( iterator, sigma[, options] )\n    Returns an iterator which introduces additive white Gaussian noise (AWGN)\n    with standard deviation `sigma`.\n\n    If an environment supports Symbol.iterator and the provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    sigma: number\n        Standard deviation of the noise.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating pseudorandom numbers\n        drawn from a standard normal distribution. If provided, the `state` and\n        `seed` options are ignored. In order to seed the returned iterator, one\n        must seed the provided `prng` (assuming the provided `prng` is\n        seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function|null\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Pseudorandom random number generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var src = iterSineWave();\n    > var it = iterawgn( src, 0.5 );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterawln, iterawun\n","iterawln":"\niterawln( iterator, sigma[, options] )\n    Returns an iterator which introduces additive white Laplacian noise (AWLN)\n    with standard deviation `sigma`.\n\n    If an environment supports Symbol.iterator and the provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    sigma: number\n        Standard deviation of the noise.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval [0,1). If provided, the\n        `state` and `seed` options are ignored. In order to seed the returned\n        iterator, one must seed the provided `prng` (assuming the provided\n        `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Pseudorandom random number generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var src = iterSineWave();\n    > var it = iterawln( src, 0.5 );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterawgn, iterawun\n","iterawun":"\niterawun( iterator, sigma[, options] )\n    Returns an iterator which introduces additive white uniform noise (AWUN)\n    with standard deviation `sigma`.\n\n    If an environment supports Symbol.iterator and the provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    sigma: number\n        Standard deviation of the noise.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval [0,1). If provided, the\n        `state` and `seed` options are ignored. In order to seed the returned\n        iterator, one must seed the provided `prng` (assuming the provided\n        `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Pseudorandom random number generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var src = iterSineWave();\n    > var it = iterawun( src, 0.5 );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterawgn, iterawln\n","iterBartlettHannPulse":"\niterBartlettHannPulse( [options] )\n    Returns an iterator which generates a Bartlett-Hann pulse waveform.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Pulse period (i.e., the number of iterations until a waveform repeats).\n        Default: 100.\n\n    options.duration: integer (optional)\n        Pulse duration. Must be greater than 2. Default: options.period.\n\n    options.amplitude: number (optional)\n        Amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterBartlettHannPulse();\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterBartlettPulse, iterHannPulse, iterPulse, iterTriangleWave\n","iterBartlettPulse":"\niterBartlettPulse( [options] )\n    Returns an iterator which generates a Bartlett pulse waveform.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Pulse period (i.e., the number of iterations until a waveform repeats).\n        Default: 100.\n\n    options.duration: integer (optional)\n        Pulse duration. Must be greater than 2. Default: options.period.\n\n    options.amplitude: number (optional)\n        Amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterBartlettPulse();\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterBartlettHannPulse, iterPulse, iterTriangleWave\n","iterBesselj0":"\niterBesselj0( iterator )\n    Returns an iterator which iteratively evaluates the Bessel function of the\n    first kind of order zero.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterBesselj0( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.besselj0, iterBesselj1, iterBessely0, iterBessely1\n","iterBesselj1":"\niterBesselj1( iterator )\n    Returns an iterator which iteratively evaluates the Bessel function of the\n    first kind of order one.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterBesselj1( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.besselj1, iterBesselj0, iterBessely0, iterBessely1\n","iterBessely0":"\niterBessely0( iterator )\n    Returns an iterator which iteratively evaluates the Bessel function of the\n    second kind of order zero.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterBessely0( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.bessely0, iterBesselj0, iterBesselj1, iterBessely1\n","iterBessely1":"\niterBessely1( iterator )\n    Returns an iterator which iteratively evaluates the Bessel function of the\n    second kind of order one.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterBessely1( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.bessely1, iterBesselj0, iterBesselj1, iterBessely0\n","iterBeta":"\niterBeta( x, y )\n    Returns an iterator which iteratively evaluates the beta function.\n\n    The length of the returned iterator is equal to the length of the shortest\n    provided iterator. In other words, the returned iterator ends once *one* of\n    the provided iterators ends.\n\n    If provided a numeric value as an iterator argument, the value is broadcast\n    as an infinite iterator which always returns the provided value.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    x: Object|number\n        Input iterator.\n\n    y: Object|number\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = random.iterators.uniform( 0.0, 2.0 );\n    > var y = random.iterators.uniform( 0.0, 2.0 );\n    > var it = iterBeta( x, y );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.beta, iterBetaln\n","iterBetaln":"\niterBetaln( x, y )\n    Returns an iterator which iteratively evaluates the natural logarithm of the\n    beta function.\n\n    The length of the returned iterator is equal to the length of the shortest\n    provided iterator. In other words, the returned iterator ends once *one* of\n    the provided iterators ends.\n\n    If provided a numeric value as an iterator argument, the value is broadcast\n    as an infinite iterator which always returns the provided value.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    x: Object|number\n        Input iterator.\n\n    y: Object|number\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = random.iterators.uniform( 0.0, 2.0 );\n    > var y = random.iterators.uniform( 0.0, 2.0 );\n    > var it = iterBetaln( x, y );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.betaln, iterBeta\n","iterBinet":"\niterBinet( iterator )\n    Returns an iterator which iteratively evaluates Binet's formula extended to\n    real numbers.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterBinet( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.binet\n","iterCbrt":"\niterCbrt( iterator )\n    Returns an iterator which iteratively computes the cube root.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterCbrt( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.cbrt, iterPow, iterSqrt\n","iterCeil":"\niterCeil( iterator )\n    Returns an iterator which rounds each iterated value toward positive\n    infinity.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterCeil( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.ceil, iterFloor, iterRound\n","iterCeil2":"\niterCeil2( iterator )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    two toward positive infinity.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterCeil2( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.ceil2, iterCeil, iterCeil10, iterFloor2, iterRound2\n","iterCeil10":"\niterCeil10( iterator )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    10 toward positive infinity.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterCeil10( random.iterators.uniform( -100.0, 100.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.ceil10, iterCeil, iterCeil2, iterFloor10, iterRound10\n","iterCompositesSeq":"\niterCompositesSeq( [options] )\n    Returns an iterator which generates a sequence of composite numbers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterCompositesSeq();\n    > var v = it.next().value\n    4\n    > v = it.next().value\n    6\n    > v = it.next().value\n    8\n\n    See Also\n    --------\n    iterIntegersSeq, iterPositiveIntegersSeq, iterPrimesSeq\n","iterConcat":"\niterConcat( iter0, ...iterator )\n    Returns an iterator which iterates over the values of two or more iterators.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iter0: Object\n        Input iterator.\n\n    iterator: ...Object\n        Iterators to concatenate.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2 ] );\n    > var it2 = array2iterator( [ 3, 4 ] );\n    > var it = iterConcat( it1, it2 );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    2\n    > v = it.next().value\n    3\n    > v = it.next().value\n    4\n    > var bool = it.next().done\n    true\n\n","iterConstant":"\niterConstant( value[, options] )\n    Returns an iterator which always returns the same value.\n\n    When provided an object reference, the returned iterator always returns the\n    same reference.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    value: any\n        Value to return.\n\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterConstant( 3.14 );\n    > var v = it.next().value\n    3.14\n    > v = it.next().value\n    3.14\n\n    See Also\n    --------\n    constantFunction\n","iterContinuedFraction":"\niterContinuedFraction( iterator[, options] )\n    Evaluates the terms of a continued fraction.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Maximum number of iterations. Default: 1e308.\n\n    options.tol: number (optional)\n        Tolerance at which to terminate further evaluation of the continued\n        fraction. Default: floating-point epsilon.\n\n    Returns\n    -------\n    out: number|null\n        Result.\n\n    Examples\n    --------\n    > var terms = array2iterator( [ 3, 4, 12, 4 ] );\n    > var v = iterContinuedFraction( terms )\n    ~3.245\n\n    See Also\n    --------\n    iterContinuedFractionSeq\n","iterContinuedFractionSeq":"\niterContinuedFractionSeq( x[, options] )\n    Returns an iterator which generates a list of all continued fraction terms\n    which can be obtained given the precision of `x`.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Maximum number of iterations. Default: 1e308.\n\n    options.tol: number (optional)\n        Tolerance at which to terminate further evaluation of the continued\n        fraction. Default: floating-point epsilon.\n\n    options.returns: string (optional)\n        Specifies the type of result to return. Must be one of\n\n        - terms: return continued fraction terms\n        - convergents: return continued fraction convergents\n        - *: return both continued fraction terms and their associated\n          convergents as a two-element array.\n\n        Default: 'terms'.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    // Return continued fraction terms...\n    > var it = iterContinuedFractionSeq( 3.245 );\n    > var v = it.next().value\n    3\n    > v = it.next().value\n    4\n    > v = it.next().value\n    12\n    > v = it.next().value\n    4\n    > var bool = it.next().done\n    true\n\n    // Return continued fraction convergents...\n    > it = iterContinuedFractionSeq( 3.245, { 'returns': 'convergents' } );\n    > v = it.next().value\n    3.0\n    > v = it.next().value\n    3.25\n    > v = it.next().value\n    ~3.2449\n    > v = it.next().value\n    3.245\n    > bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterContinuedFraction\n","iterCos":"\niterCos( iterator )\n    Returns an iterator which iteratively computes the cosine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterCos( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.cos, iterCospi, iterSin, iterTan\n","iterCosh":"\niterCosh( iterator )\n    Returns an iterator which iteratively computes the hyperbolic cosine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -5.0, 5.0 );\n    > var it = iterCosh( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.cosh, iterCos, iterSinh, iterTanh\n","iterCosineWave":"\niterCosineWave( [options] )\n    Returns an iterator which generates a cosine wave.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Period (i.e., the number of iterations before a cosine wave repeats).\n        Default: 10.\n\n    options.amplitude: number (optional)\n        Peak amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterCosineWave();\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterPulse, iterSawtoothWave, iterSineWave, iterSquareWave, iterTriangleWave\n","iterCosm1":"\niterCosm1( iterator )\n    Returns an iterator which iteratively computes `cos(x) - 1`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 6.28 );\n    > var it = iterCosm1( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.cosm1, iterCos\n","iterCospi":"\niterCospi( iterator )\n    Returns an iterator which computes the cosine of each iterated value times\n    π.\n\n    Computes cos(πx) more accurately than cos(pi*x), especially for large x.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterCospi( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.cospi, iterCos\n","iterCounter":"\niterCounter( iterator )\n    Returns an iterator which iteratively computes the number of iterated\n    values.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterCounter( random.iterators.randu() );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    iterLength\n","iterCovercos":"\niterCovercos( iterator )\n    Returns an iterator which iteratively computes the coversed cosine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 6.28 );\n    > var it = iterCovercos( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.covercos, iterCoversin, iterVercos\n","iterCoversin":"\niterCoversin( iterator )\n    Returns an iterator which iteratively computes the coversed sine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 6.28 );\n    > var it = iterCoversin( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.coversin, iterCovercos, iterVersin\n","iterCubesSeq":"\niterCubesSeq( [options] )\n    Returns an iterator which generates a sequence of cubes.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 208063.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterCubesSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().value\n    8\n\n    See Also\n    --------\n    iterFourthPowersSeq, iterSquaresSeq\n","itercugmean":"\nitercugmean( iterator )\n    Returns an iterator which iteratively computes a cumulative geometric mean.\n\n    If provided a negative value, the iterated value is `NaN` for all future\n    invocations.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\n    > var it = itercugmean( arr );\n    > var v = it.next().value\n    2.0\n    > v = it.next().value\n    ~3.16\n    > v = it.next().value\n    ~3.11\n    > v = it.next().value\n    ~3.50\n\n    See Also\n    --------\n    itercuhmean, itercumean\n","itercuhmean":"\nitercuhmean( iterator )\n    Returns an iterator which iteratively computes a cumulative harmonic mean.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\n    > var it = itercuhmean( arr );\n    > var v = it.next().value\n    2.0\n    > v = it.next().value\n    ~2.86\n    > v = it.next().value\n    ~2.90\n    > v = it.next().value\n    ~3.24\n\n    See Also\n    --------\n    itercugmean, itercumean\n","itercumax":"\nitercumax( iterator )\n    Returns an iterator which iteratively computes a cumulative maximum value.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercumax( arr );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    2.0\n    > m = it.next().value\n    3.0\n    > m = it.next().value\n    5.0\n\n    See Also\n    --------\n    itercumidrange, itercumin, itercurange, itermax\n","itercumaxabs":"\nitercumaxabs( iterator )\n    Returns an iterator which iteratively computes a cumulative maximum absolute\n    value.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercumaxabs( arr );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    5.0\n    > m = it.next().value\n    5.0\n    > m = it.next().value\n    5.0\n\n    See Also\n    --------\n    itercumax, itercuminabs, itermaxabs\n","itercumean":"\nitercumean( iterator )\n    Returns an iterator which iteratively computes a cumulative arithmetic mean.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercumean( arr );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    -1.5\n    > m = it.next().value\n    0.0\n    > m = it.next().value\n    1.25\n\n    See Also\n    --------\n    itercumidrange, itercusum, itermean\n","itercumeanabs":"\nitercumeanabs( iterator )\n    Returns an iterator which iteratively computes a cumulative arithmetic mean\n    of absolute values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercumeanabs( arr );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    3.5\n    > m = it.next().value\n    ~3.33\n    > m = it.next().value\n    3.75\n\n    See Also\n    --------\n    itercumean, itercumeanabs2, itercusumabs, itermeanabs\n","itercumeanabs2":"\nitercumeanabs2( iterator )\n    Returns an iterator which iteratively computes a cumulative arithmetic mean\n    of squared absolute values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercumeanabs2( arr );\n    > var m = it.next().value\n    4.0\n    > m = it.next().value\n    14.5\n    > m = it.next().value\n    ~12.67\n    > m = it.next().value\n    15.75\n\n    See Also\n    --------\n    itercumean, itercumeanabs, itercusumabs2, itermeanabs2\n","itercumidrange":"\nitercumidrange( iterator )\n    Returns an iterator which iteratively computes a cumulative mid-range.\n\n    The mid-range is the arithmetic mean of maximum and minimum values.\n    Accordingly, the mid-range is the midpoint of the range and a measure of\n    central tendency.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercumidrange( arr );\n    > var v = it.next().value\n    2.0\n    > v = it.next().value\n    -1.5\n    > v = it.next().value\n    -1.0\n    > v = it.next().value\n    0.0\n\n    See Also\n    --------\n    itercumean, itercumax, itercumin, itercurange, itermidrange\n","itercumin":"\nitercumin( iterator )\n    Returns an iterator which iteratively computes a cumulative minimum value.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercumin( arr );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    -5.0\n    > m = it.next().value\n    -5.0\n    > m = it.next().value\n    -5.0\n\n    See Also\n    --------\n    itercumax, itercumidrange, itercurange, itermin\n","itercuminabs":"\nitercuminabs( iterator )\n    Returns an iterator which iteratively computes a cumulative minimum absolute\n    value.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercuminabs( arr );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    2.0\n    > m = it.next().value\n    2.0\n    > m = it.next().value\n    2.0\n\n    See Also\n    --------\n    itercumaxabs, itercumin, iterminabs\n","itercuprod":"\nitercuprod( iterator )\n    Returns an iterator which iteratively computes a cumulative product.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercuprod( arr );\n    > var p = it.next().value\n    2.0\n    > p = it.next().value\n    -10.0\n    > p = it.next().value\n    -30.0\n    > p = it.next().value\n    -150.0\n\n    See Also\n    --------\n    itercusum, iterprod\n","itercurange":"\nitercurange( iterator )\n    Returns an iterator which iteratively computes a cumulative range.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercurange( arr );\n    > var r = it.next().value\n    0.0\n    > r = it.next().value\n    7.0\n    > r = it.next().value\n    8.0\n    > r = it.next().value\n    10.0\n\n    See Also\n    --------\n    itercumax, itercumean, itercumin, iterrange\n","itercusum":"\nitercusum( iterator )\n    Returns an iterator which iteratively computes a cumulative sum.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercusum( arr );\n    > var s = it.next().value\n    2.0\n    > s = it.next().value\n    -3.0\n    > s = it.next().value\n    0.0\n    > s = it.next().value\n    5.0\n\n    See Also\n    --------\n    itercumean, itersum, itercuprod\n","itercusumabs":"\nitercusumabs( iterator )\n    Returns an iterator which iteratively computes a cumulative sum of absolute\n    values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercusumabs( arr );\n    > var s = it.next().value\n    2.0\n    > s = it.next().value\n    7.0\n    > s = it.next().value\n    10.0\n    > s = it.next().value\n    15.0\n\n    See Also\n    --------\n    itercumeanabs, itercusum, itersumabs\n","itercusumabs2":"\nitercusumabs2( iterator )\n    Returns an iterator which iteratively computes a cumulative sum of squared\n    absolute values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercusumabs2( arr );\n    > var s = it.next().value\n    4.0\n    > s = it.next().value\n    29.0\n    > s = it.next().value\n    38.0\n    > s = it.next().value\n    63.0\n\n    See Also\n    --------\n    itercumeanabs2, itercusumabs, itersumabs2\n","iterDatespace":"\niterDatespace( start, stop[, N][, options] )\n    Returns an iterator which returns evenly spaced dates over a specified\n    interval.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    start: integer|string|Date\n        Starting date either as a `Date` object, JavaScript timestamp, or a date\n        string (inclusive).\n\n    stop: integer|string|Date\n        Stopping value either as a `Date` object, JavaScript timestamp, or a\n        date string (inclusive).\n\n    N: integer (optional)\n        Number of values. Default: 100.\n\n    options: Object (optional)\n        Function options.\n\n    options.round: string (optional)\n        Specifies how sub-millisecond times should be rounded. Must be one of\n        the following: 'floor', 'ceil', or 'round'. Default: 'floor'.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var t1 = new Date();\n    > var it = iterDatespace( t1, new Date( t1.getTime()+86400000 ) );\n    > var v = it.next().value\n    <Date>\n    > v = it.next().value\n    <Date>\n\n    See Also\n    --------\n    iterator2array, iterIncrspace, iterLinspace, iterLogspace, iterStep\n","iterDedupe":"\niterDedupe( iterator[, limit] )\n    Returns an iterator which removes consecutive duplicated values.\n\n    `NaN` values are considered distinct.\n\n    Uniqueness is determined according to strict equality. Accordingly, objects\n    are *not* checked for deep equality.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    limit: integer (optional)\n        Number of allowed consecutive duplicates. Default: 1.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\n    > var it = iterDedupe( arr );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    2\n    > v = it.next().value\n    3\n\n    See Also\n    --------\n    iterDedupeBy, iterUnique\n","iterDedupeBy":"\niterDedupeBy( iterator, [limit,] fcn )\n    Returns an iterator which removes consecutive values that resolve to the\n    same value according to a provided function.\n\n    The provided function is provided five arguments:\n\n    - curr: current source iterated value.\n    - sprev: previous source iterated value.\n    - dprev: previous downstream iterated value.\n    - index: source iteration index (zero-based).\n    - acc: previous resolved value.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    limit: integer (optional)\n        Number of allowed consecutive duplicates. Default: 1.\n\n    fcn: Function\n        Function indicating whether an iterated value is a \"duplicate\".\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\n    > function fcn( v ) { return v; };\n    > var it = iterDedupeBy( arr, fcn );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    2\n    > v = it.next().value\n    3\n\n    See Also\n    --------\n    iterDedupe, iterUnique\n","iterDeg2rad":"\niterDeg2rad( iterator )\n    Returns an iterator which iteratively converts an angle from degrees to\n    radians.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -360.0, 360.0 );\n    > var it = iterDeg2rad( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.deg2rad, iterRad2deg\n","iterDigamma":"\niterDigamma( iterator )\n    Returns an iterator which iteratively evaluates the digamma function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.01, 5.0 );\n    > var it = iterDigamma( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.digamma, iterGamma, iterTrigamma\n","iterDiracComb":"\niterDiracComb( [options] )\n    Returns an iterator which generates a Dirac comb.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Period (i.e., the number of iterations before a waveform repeats).\n        Default: 10.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterDiracComb();\n    > var v = it.next().value\n    Infinity\n    > v = it.next().value\n    0.0\n\n    See Also\n    --------\n    iterPulse\n","iterDiracDelta":"\niterDiracDelta( iterator )\n    Returns an iterator which iteratively evaluates the Dirac delta function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterDiracDelta( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.diracDelta\n","iterDivide":"\niterDivide( iter0, ...iterator )\n    Returns an iterator which performs element-wise division of two or more\n    iterators.\n\n    The length of the returned iterator is equal to the length of the shortest\n    provided iterator. In other words, the returned iterator ends once *one* of\n    the provided iterators ends.\n\n    If provided a numeric value as an iterator argument, the value is broadcast\n    as an infinite iterator which always returns the provided value.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iter0: Object\n        Input iterator.\n\n    iterator: ...Object\n        Iterators whose values are used as divisors.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 3.0, 2.0 ] );\n    > var it2 = array2iterator( [ 1.0, 4.0 ] );\n    > var it = iterDivide( it1, it2 );\n    > var v = it.next().value\n    3.0\n    > v = it.next().value\n    0.5\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterAdd, iterDivide, iterMultiply\n","iterDoWhileEach":"\niterDoWhileEach( iterator, predicate, fcn[, thisArg] )\n    Returns an iterator which invokes a function for each iterated value before\n    returning the iterated value until either a predicate function returns false\n    or the iterator has iterated over all values.\n\n    The condition is evaluated *after* executing the provided function; thus,\n    `fcn` *always* executes at least once.\n\n    When invoked, both input functions are provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index (zero-based).\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    predicate: Function\n        Function which indicates whether to continue iterating.\n\n    fcn: Function\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === v };\n    > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n    > var it = iterDoWhileEach( random.iterators.randu(), predicate, f );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterDoUntilEach, iterUntilEach, iterWhileEach\n","iterEllipe":"\niterEllipe( iterator )\n    Returns an iterator which iteratively computes the complete elliptic\n    integral of the second kind.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -1.0, 1.0 );\n    > var it = iterEllipe( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.ellipe, iterEllipk\n","iterEllipk":"\niterEllipk( iterator )\n    Returns an iterator which iteratively computes the complete elliptic\n    integral of the first kind.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -1.0, 1.0 );\n    > var it = iterEllipk( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.ellipk, iterEllipe\n","iterEmpty":"\niterEmpty()\n    Returns an empty iterator.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterEmpty();\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterConstant\n","iterErf":"\niterErf( iterator )\n    Returns an iterator which iteratively evaluates the error function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterErf( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.erf, iterErfc, iterErfinv, iterErfcinv\n","iterErfc":"\niterErfc( iterator )\n    Returns an iterator which iteratively evaluates the complementary error\n    function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterErfc( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.erfc, iterErf, iterErfinv, iterErfcinv\n","iterErfcinv":"\niterErfcinv( iterator )\n    Returns an iterator which iteratively evaluates the inverse complementary\n    error function.\n\n    The domain of inverse complementary error function is restricted to [0,2].\n    If an iterated value is outside of the domain, the returned iterator returns\n    `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterErfcinv( random.iterators.uniform( 0.0, 2.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.erfcinv, iterErf, iterErfc, iterErfinv\n","iterErfinv":"\niterErfinv( iterator )\n    Returns an iterator which iteratively evaluates the inverse error function.\n\n    The domain of inverse error function is restricted to [-1,1]. If an iterated\n    value is outside of the domain, the returned iterator returns `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterErfinv( random.iterators.uniform( -1.0, 1.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.erfinv, iterErf, iterErfc, iterErfcinv\n","iterEta":"\niterEta( iterator )\n    Returns an iterator which iteratively evaluates the Dirichlet eta function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterEta( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.eta\n","iterEvenIntegersSeq":"\niterEvenIntegersSeq( [options] )\n    Returns an iterator which generates an interleaved sequence of even\n    integers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 9007199254740992.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterEvenIntegersSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    2\n    > v = it.next().value\n    -2\n\n    See Also\n    --------\n    iterIntegersSeq, iterOddIntegersSeq\n","iterEvery":"\niterEvery( iterator )\n    Tests whether all iterated values are truthy.\n\n    The function immediately returns upon encountering a falsy value.\n\n    If provided an iterator which does not return any iterated values, the\n    function returns `true`.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `false` if a value is falsy; otherwise, the\n        function returns `true`.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1, 1, 1, 1, 0 ] );\n    > var bool = iterEvery( arr )\n    false\n\n    See Also\n    --------\n    iterAny, iterEveryBy, iterForEach, iterNone, iterSome\n","iterEveryBy":"\niterEveryBy( iterator, predicate[, thisArg ] )\n    Tests whether every iterated value passes a test implemented by a predicate\n    function.\n\n    The predicate function is provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index.\n\n    The function immediately returns upon encountering a falsy return value.\n\n    If provided an iterator which does not return any iterated values, the\n    function returns `true`.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if a predicate function returns a truthy\n        value for all iterated values. Otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\n    > function fcn( v ) { return ( v > 0 ); };\n    > var bool = iterEveryBy( arr, fcn )\n    true\n\n    See Also\n    --------\n    iterAnyBy, iterEvery, iterForEach, iterNoneBy, iterSomeBy\n","iterExp":"\niterExp( iterator )\n    Returns an iterator which iteratively evaluates the natural exponential\n    function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterExp( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.exp, iterExp10, iterExp2, iterExpm1, iterLn\n","iterExp2":"\niterExp2( iterator )\n    Returns an iterator which iteratively evaluates the base `2` exponential\n    function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -50.0, 50.0 );\n    > var it = iterExp2( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.exp2, iterExp, iterExp10, iterLog2\n","iterExp10":"\niterExp10( iterator )\n    Returns an iterator which iteratively evaluates the base `10` exponential\n    function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -50.0, 50.0 );\n    > var it = iterExp10( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.exp10, iterExp, iterExp2, iterLog10\n","iterExpit":"\niterExpit( iterator )\n    Returns an iterator which iteratively evaluates the standard logistic\n    function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 1.0 );\n    > var it = iterExpit( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.expit, iterExp, iterLogit\n","iterExpm1":"\niterExpm1( iterator )\n    Returns an iterator which iteratively computes `exp(x) - 1`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -5.0, 5.0 );\n    > var it = iterExpm1( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.expm1, iterExp, iterExpm1rel\n","iterExpm1rel":"\niterExpm1rel( iterator )\n    Returns an iterator which iteratively evaluates the relative error\n    exponential.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -50.0, 50.0 );\n    > var it = iterExpm1rel( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.expm1rel, iterExp, iterExpm1\n","iterFactorial":"\niterFactorial( iterator )\n    Returns an iterator which iteratively evaluates the factorial function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterFactorial( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.factorial, iterFactorialln\n","iterFactorialln":"\niterFactorialln( iterator )\n    Returns an iterator which iteratively evaluates the natural logarithm of the\n    factorial function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterFactorialln( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.factorialln, iterFactorial\n","iterFactorialsSeq":"\niterFactorialsSeq( [options] )\n    Returns an iterator which generates a sequence of factorials.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterFactorialsSeq();\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    1\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    iterFactorial\n","iterFibonacciSeq":"\niterFibonacciSeq( [options] )\n    Returns an iterator which generates a Fibonacci sequence.\n\n    The returned iterator can only generate the first 79 Fibonacci numbers, as\n    larger Fibonacci numbers cannot be safely represented in double-precision\n    floating-point format.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 79.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterFibonacciSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n\n    See Also\n    --------\n    base.fibonacci, iterLucasSeq, iterNegaFibonacciSeq, iterNonFibonacciSeq\n","iterFifthPowersSeq":"\niterFifthPowersSeq( [options] )\n    Returns an iterator which generates a sequence of fifth powers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 9741.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterFifthPowersSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().value\n    32\n\n    See Also\n    --------\n    iterCubesSeq, iterFourthPowersSeq, iterSquaresSeq\n","iterFill":"\niterFill( iterator, value[, begin[, end]] )\n    Returns an iterator which replaces all values from a provided iterator from\n    a start index to an end index with a static value.\n\n    If `end` exceeds the length of the provided iterator, the returned iterator\n    replaces the subsequence of iterated values starting from `begin` until the\n    last iterated value of the provided iterator.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    value: any\n        Static value.\n\n    begin: integer (optional)\n        Start iteration index (zero-based and inclusive). Default: 0.\n\n    end: integer (optional)\n        End iteration index (zero-based and non-inclusive).\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterFill( random.iterators.randu(), 3.14, 0, 2 );\n    > var r = it.next().value\n    3.14\n    > r = it.next().value\n    3.14\n    > r = it.next().value\n    <number>\n\n","iterFilter":"\niterFilter( iterator, predicate[, thisArg] )\n    Returns an iterator which filters a provided iterator's values according to\n    a predicate function.\n\n    When invoked, the predicate function is provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index (zero-based).\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    predicate: Function\n        Predicate function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > function f( v ) { return ( v > 2 ); };\n    > var it1 = array2iterator( [ 1, 3, 2, 4 ] );\n    > var it2 = iterFilter( it1, f );\n    > var v = it2.next().value\n    3\n    > v = it2.next().value\n    4\n\n    See Also\n    --------\n    iterFilterMap, iterMap, iterReject\n","iterFilterMap":"\niterFilterMap( iterator, fcn[, thisArg] )\n    Returns an iterator which both filters and maps a provided iterator's\n    values.\n\n    When invoked, the callback function is provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index (zero-based).\n\n    If the callback returns `undefined`, the iterator invokes the function for\n    the next value of the provided iterator; otherwise, the iterator returns\n    the callback's return value.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    fcn: Function\n        Callback function which both filters and maps.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > function f( v ) { if ( v > 2 ) { return v * 10 }; };\n    > var it1 = array2iterator( [ 1, 3, 2, 4 ] );\n    > var it2 = iterFilterMap( it1, f );\n    > var v = it2.next().value\n    30\n    > v = it2.next().value\n    40\n\n    See Also\n    --------\n    iterFilter, iterMap\n","iterFirst":"\niterFirst( iterator )\n    Returns the first iterated value.\n\n    The function does *not* consume an entire iterator before returning.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    Returns\n    -------\n    v: any\n        The first iterated value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1, 0, 0, 0, 0 ] );\n    > var v = iterFirst( arr )\n    1\n\n    See Also\n    --------\n    iterHead, iterLast, iterNth\n","iterFlatTopPulse":"\niterFlatTopPulse( [options] )\n    Returns an iterator which generates a flat top pulse waveform.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Pulse period (i.e., the number of iterations until a waveform repeats).\n        Default: 100.\n\n    options.duration: integer (optional)\n        Pulse duration. Must be greater than 2. Default: options.period.\n\n    options.amplitude: number (optional)\n        Amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterFlatTopPulse();\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterPulse\n","iterFloor":"\niterFloor( iterator )\n    Returns an iterator which rounds each iterated value toward negative\n    infinity.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterFloor( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.floor, iterCeil, iterRound\n","iterFloor2":"\niterFloor2( iterator )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    two toward negative infinity.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterFloor2( random.iterators.uniform( -100.0, 100.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.floor2, iterCeil2, iterFloor, iterFloor10, iterRound2\n","iterFloor10":"\niterFloor10( iterator )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    10 toward negative infinity.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterFloor10( random.iterators.uniform( -100.0, 100.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.floor10, iterCeil10, iterFloor, iterFloor2, iterRound10\n","iterFlow":"\niterFlow( methods )\n    Returns a fluent interface iterator constructor with a customized prototype\n    based on provided methods.\n\n    The methods argument should be an object which maps constructor method names\n    to iterator functions.\n\n    Each iterator function should have the following function signature:\n\n      iterFcn( iterator, ...args )\n\n    When a fluent interface iterator method is invoked, the method invokes the\n    corresponding iterator function with an iterator and provided method\n    arguments.\n\n    If an iterator function returns an iterator, the corresponding fluent\n    interface method returns a new fluent interface instance; otherwise, the\n    corresponding fluent interface method returns the iterator function result.\n\n    The iterator function evaluation context is always `null`.\n\n    Iterator functions which return iterators are expected to return iterator\n    protocol-compliant objects (i.e., an object having a `next` method which\n    returns the next iterated value (if one exists) assigned to a `value`\n    property and a `done` property having a boolean value indicating whether the\n    iterator is finished).\n\n    If an environment supports `Symbol.iterator`, the returned constructor\n    returns iterators which are iterable.\n\n    Parameters\n    ----------\n    methods: Object\n        An object mapping method names to iterator functions.\n\n    Returns\n    -------\n    FluentIterator: Function\n        Fluent interface iterator constructor.\n\n    Examples\n    --------\n    > var o = {};\n    > o.head = iterHead;\n    > o.some = iterSome;\n    > var fiter = iterFlow( o )\n\n\nFluentIterator( iterator )\n    Returns a new fluent interface iterator from a source iterator.\n\n    Parameters\n    ----------\n    iterator: Object\n        Source iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Fluent interface iterator.\n\n    Examples\n    --------\n    > var o = {};\n    > o.head = iterHead;\n    > o.some = iterSome;\n    > var fiter = iterFlow( o );\n    > var it = fiter( array2iterator( [ 0, 0, 1, 1, 1 ] ) );\n    > var bool = it.head( 3 ).some( 2 )\n    false\n\n\nFluentIterator.prototype.next()\n    Returns the next iterated value.\n\n    Returns\n    -------\n    out: Object\n        Iterator protocol-compliant object.\n\n    out.value: any (optional)\n        Next iterated value (if one exists).\n\n    out.done: boolean\n        Boolean flag indicating whether the iterator is finished.\n\n    Examples\n    --------\n    > var o = {};\n    > o.head = iterHead;\n    > o.some = iterSome;\n    > var fiter = iterFlow( o );\n    > var it1 = fiter( array2iterator( [ 0, 0, 1, 1, 1 ] ) );\n    > var it2 = it1.head( 3 );\n    > var v = it2.next().value\n    0\n    > v = it2.next().value\n    0\n    > v = it2.next().value\n    1\n\n\nFluentIterator.prototype.return( [value] )\n    Finishes an iterator and returns a provided value.\n\n    Parameters\n    ----------\n    value: any (optional)\n        Value to return.\n\n    Returns\n    -------\n    out: Object\n        Iterator protocol-compliant object.\n\n    out.value: any (optional)\n        Next iterated value (if one exists).\n\n    out.done: boolean\n        Boolean flag indicating whether the iterator is finished.\n\n    Examples\n    --------\n    > var o = {};\n    > o.head = iterHead;\n    > o.some = iterSome;\n    > var fiter = iterFlow( o );\n    > var it1 = fiter( array2iterator( [ 0, 0, 1, 1, 1 ] ) );\n    > var it2 = it1.head( 3 );\n    > var v = it2.next().value\n    0\n    > var bool = it2.return().done\n    true\n    > v = it2.next().value\n    undefined\n\n    See Also\n    --------\n    iterPipeline\n","iterForEach":"\niterForEach( iterator, fcn[, thisArg] )\n    Returns an iterator which invokes a function for each iterated value before\n    returning the iterated value.\n\n    When invoked, the input function is provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index (zero-based).\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    fcn: Function\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n    > var it = iterForEach( random.iterators.randu(), f );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterMap\n","iterFourthPowersSeq":"\niterFourthPowersSeq( [options] )\n    Returns an iterator which generates a sequence of fourth powers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 9741.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterFourthPowersSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().value\n    16\n\n    See Also\n    --------\n    iterCubesSeq, iterFifthPowersSeq, iterSquaresSeq\n","iterFresnelc":"\niterFresnelc( iterator )\n    Returns an iterator which iteratively computes the Fresnel integral C(x).\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 10.0 );\n    > var it = iterFresnelc( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.fresnelc, iterFresnels\n","iterFresnels":"\niterFresnels( iterator )\n    Returns an iterator which iteratively computes the Fresnel integral S(x).\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 10.0 );\n    > var it = iterFresnels( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.fresnels, iterFresnelc\n","iterGamma":"\niterGamma( iterator )\n    Returns an iterator which iteratively evaluates the gamma function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterGamma( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.gamma, iterGamma1pm1, iterGammaln\n","iterGamma1pm1":"\niterGamma1pm1( iterator )\n    Returns an iterator which iteratively computes `gamma(x+1) - 1` without\n    cancellation errors for small `x`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -5.0, 5.0 );\n    > var it = iterGamma1pm1( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.gamma1pm1, iterGamma\n","iterGammaln":"\niterGammaln( iterator )\n    Returns an iterator which iteratively evaluates the natural logarithm of the\n    gamma function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterGammaln( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.gammaln, iterGamma\n","iterHacovercos":"\niterHacovercos( iterator )\n    Returns an iterator which iteratively computes the half-value coversed\n    cosine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 6.28 );\n    > var it = iterHacovercos( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.hacovercos, iterCovercos, iterHacoversin\n","iterHacoversin":"\niterHacoversin( iterator )\n    Returns an iterator which iteratively computes the half-value coversed sine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 6.28 );\n    > var it = iterHacoversin( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.hacoversin, iterCoversin, iterHacovercos\n","iterHannPulse":"\niterHannPulse( [options] )\n    Returns an iterator which generates a Hann pulse waveform.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Pulse period (i.e., the number of iterations until a waveform repeats).\n        Default: 100.\n\n    options.duration: integer (optional)\n        Pulse duration. Must be greater than 2. Default: options.period.\n\n    options.amplitude: number (optional)\n        Amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterHannPulse();\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterBartlettHannPulse, iterPulse, iterSineWave\n","iterHavercos":"\niterHavercos( iterator )\n    Returns an iterator which iteratively computes the half-value versed cosine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 6.28 );\n    > var it = iterHavercos( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.havercos, iterHaversin, iterVercos\n","iterHaversin":"\niterHaversin( iterator )\n    Returns an iterator which iteratively computes the half-value versed sine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 6.28 );\n    > var it = iterHaversin( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.haversin, iterHavercos, iterVersin\n","iterHead":"\niterHead( iterator, n )\n    Returns an iterator which returns the first `n` values of a provided\n    iterator.\n\n    If a provided iterator only generates `m` values and `m` is less than `n`,\n    the returned iterator only returns `m` values.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    n: integer\n        Number of values.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterHead( random.iterators.randu(), 5 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterFirst, iterSlice\n","iterIncrspace":"\niterIncrspace( start, stop[, increment] )\n    Returns an iterator which returns evenly spaced numbers according to a\n    specified increment.\n\n    Beware that values which follow the starting value are subject to floating-\n    point rounding errors.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    start: number\n        Starting value (inclusive).\n\n    stop: number\n        Stopping value (exclusive).\n\n    increment: number (optional)\n        Increment. Default: 1.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterIncrspace( 0, 101, 2 );\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    iterator2array, iterDatespace, iterLinspace, iterLogspace, iterStep, iterUnitspace\n","iterIntegersSeq":"\niterIntegersSeq( [options] )\n    Returns an iterator which generates an interleaved integer sequence.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 18014398509481984.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterIntegersSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().value\n    -1\n\n    See Also\n    --------\n    iterNegativeIntegersSeq, iterNonNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterPositiveIntegersSeq\n","iterIntersection":"\niterIntersection( iter0, ...iterator )\n    Returns an iterator which returns the intersection of two or more iterators.\n\n    Value \"uniqueness\" is determined according to strict equality.\n\n    A returned iterator internally buffers unique values and, thus, has O(N)\n    memory requirements, where `N` is the length of the first iterator.\n\n    Do *not* provide iterators having infinite length.\n\n    If an environment supports Symbol.iterator and all provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iter0: Object\n        Input iterator.\n\n    iterator: ...Object\n        Input iterators.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n    > var it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\n    > var it = iterIntersection( it1, it2 );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    2\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterIntersectionByHash, iterUnion, iterUnique\n","iterIntersectionByHash":"\niterIntersectionByHash( iter0, ...iterator, hashFcn[, thisArg] )\n    Returns an iterator which returns the intersection of two or more iterators\n    according to a hash function.\n\n    An iterated value is considered \"unique\" if the hash function returns a\n    unique hash value for that iterated value. Beware that this *may* result in\n    unexpected behavior. Namely, only the first iterated value mapping to a\n    particular hash function result is returned, even if subsequent values,\n    while mapping to the same hash, are different. Accordingly, iteration order\n    *does* matter.\n\n    A returned iterator internally buffers unique hashes, along with the *first*\n    iterated value resolving to a hash, and, thus, has O(N) memory requirements,\n    where `N` is the length of the first iterator.\n\n    Do *not* provide iterators having infinite length.\n\n    If an environment supports Symbol.iterator and all provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iter0: Object\n        Input iterator.\n\n    iterator: ...Object\n        Input iterators.\n\n    hashFcn: Function\n        Hash function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n    > var it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\n    > function f( v ) { return v.toString(); };\n    > var it = iterIntersectionByHash( it1, it2, f );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    2\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterIntersection, iterUniqueByHash\n","iterInv":"\niterInv( iterator )\n    Returns an iterator which iteratively computes the multiplicative inverse.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterInv( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.inv, iterPow\n","iterLanczosPulse":"\niterLanczosPulse( [options] )\n    Returns an iterator which generates a Lanczos pulse waveform.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Pulse period (i.e., the number of iterations until a waveform repeats).\n        Default: 100.\n\n    options.duration: integer (optional)\n        Pulse duration. Must be greater than 2. Default: options.period.\n\n    options.amplitude: number (optional)\n        Amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterLanczosPulse();\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterPulse, iterPeriodicSinc\n","iterLast":"\niterLast( iterator )\n    Consumes an entire iterator and returns the last iterated value.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    Returns\n    -------\n    v: any\n        The last iterated value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n    > var v = iterLast( arr )\n    1\n\n    See Also\n    --------\n    iterFirst, iterNth\n","iterLength":"\niterLength( iterator )\n    Consumes an entire iterator and returns the number of iterated values.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    Returns\n    -------\n    len: integer\n        Iterator length.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n    > var len = iterLength( arr )\n    5\n\n    See Also\n    --------\n    iterCounter\n","iterLinspace":"\niterLinspace( start, stop[, N] )\n    Returns an iterator which returns evenly spaced numbers over a specified\n    interval.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    start: number\n        Starting value (inclusive).\n\n    stop: number\n        Stopping value (inclusive).\n\n    N: integer (optional)\n        Number of values. Default: 100.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterLinspace( 0, 99, 100 );\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n\n    See Also\n    --------\n    iterator2array, iterDatespace, iterIncrspace, iterLogspace, iterStep, iterUnitspace\n","iterLn":"\niterLn( iterator )\n    Returns an iterator which iteratively evaluates the natural logarithm.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterLn( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.ln, iterExp, iterLog10, iterLog1p, iterLog2\n","iterLog":"\niterLog( x, b )\n    Returns an iterator which iteratively computes the base `b` logarithm.\n\n    For negative `b` or `x` iterated values, the returned iterator returns\n    `NaN`.\n\n    The length of the returned iterator is equal to the length of the shortest\n    provided iterator. In other words, the returned iterator ends once *one* of\n    the provided iterators ends.\n\n    If provided a numeric value as an iterator argument, the value is broadcast\n    as an infinite iterator which always returns the provided value.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    x: Object|number\n        Input iterator.\n\n    b: Object|number\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = random.iterators.uniform( 0.0, 100.0 );\n    > var y = random.iterators.uniform( 0.0, 10.0 );\n    > var it = iterLog( x, y );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.log, iterLog10, iterLog1p, iterLog2, iterPow\n","iterLog1mexp":"\niterLog1mexp( iterator )\n    Returns an iterator which iteratively evaluates the natural logarithm of\n    `1-exp(-|x|)`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterLog1mexp( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.log1mexp, iterLog, iterLog1p, iterLog1pexp, iterPow\n","iterLog1p":"\niterLog1p( iterator )\n    Returns an iterator which iteratively evaluates the natural logarithm of\n    `1+x`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterLog1p( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.log1p, iterLog, iterLog10, iterLog2, iterPow\n","iterLog1pexp":"\niterLog1pexp( iterator )\n    Returns an iterator which iteratively evaluates the natural logarithm of\n    `1+exp(x)`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterLog1pexp( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.log1pexp, iterLog, iterLog1p, iterLog1mexp, iterPow\n","iterLog2":"\niterLog2( iterator )\n    Returns an iterator which iteratively evaluates the binary logarithm.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterLog2( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.log2, iterLog, iterLog10, iterLog1p, iterPow\n","iterLog10":"\niterLog10( iterator )\n    Returns an iterator which iteratively evaluates the common logarithm\n    (logarithm with base 10).\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterLog10( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.log10, iterLog, iterLog1p, iterLog2, iterPow\n","iterLogit":"\niterLogit( iterator )\n    Returns an iterator which iteratively evaluates the logit function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 1.0 );\n    > var it = iterLogit( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.logit\n","iterLogspace":"\niterLogspace( start, stop[, N][, options] )\n    Returns an iterator which returns evenly spaced numbers on a log scale.\n\n    In linear space, the sequence starts at `base` raised to the power of\n    `start` and ends with `base` raised to the power of `stop`.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    start: number\n        Exponent of starting value.\n\n    stop: number\n        Exponent of stopping value.\n\n    N: integer (optional)\n        Number of values. Default: 100.\n\n    options: Object (optional)\n        Function options.\n\n    options.base: number (optional)\n        Base of log space. Default: 10.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterLogspace( 0, 3, 4 );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    10\n\n    See Also\n    --------\n    iterator2array, iterDatespace, iterIncrspace, iterLinspace, iterStep\n","iterLucasSeq":"\niterLucasSeq( [options] )\n    Returns an iterator which generates a Lucas sequence.\n\n    The returned iterator can only generate the first 77 Lucas numbers, as\n    larger Lucas numbers cannot be safely represented in double-precision\n    floating-point format.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 77.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterLucasSeq();\n    > var v = it.next().value\n    2\n    > v = it.next().value\n    1\n\n    See Also\n    --------\n    base.lucas, iterFibonacciSeq, iterNegaLucasSeq\n","iterMap":"\niterMap( iterator, fcn[, thisArg] )\n    Returns an iterator which invokes a function for each iterated value.\n\n    When invoked, the input function is provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index (zero-based).\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    fcn: Function\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > function f( v ) { return v * 10.0; };\n    > var it = iterMap( random.iterators.randu(), f );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterFilter, iterFilterMap, iterForEach, iterReject\n","iterMapN":"\niterMapN( iter0, ...iterator, fcn[, thisArg] )\n    Returns an iterator which transforms iterated values from two or more\n    iterators by applying the iterated values as arguments to a provided\n    function.\n\n    When invoked, the callback function is provided `N+1` arguments, where `N`\n    is the number of provided iterators and the last argument is the iteration\n    index:\n\n    - ...value: iterated values.\n    - index: iteration index (zero-based).\n\n    The length of the returned iterator is equal to the length of the shortest\n    provided iterator. In other words, the returned iterator ends once *one* of\n    the provided iterators ends.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iter0: Object\n        Input iterator.\n\n    iterator: ...Object\n        Iterators.\n\n    fcn: Function\n        Function to invoke with iterated values.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1.0, 2.0 ] );\n    > var it2 = array2iterator( [ 3.0, 4.0 ] );\n    > function fcn( x, y ) { return x + y; };\n    > var it = iterMapN( it1, it2, fcn );\n    > var v = it.next().value\n    4.0\n    > v = it.next().value\n    6.0\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterMap\n","itermax":"\nitermax( iterator )\n    Computes the maximum value of all iterated values.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Maximum value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var m = itermax( arr )\n    3.0\n\n    See Also\n    --------\n    itermidrange, itermin, itermmax, iterrange\n","itermaxabs":"\nitermaxabs( iterator )\n    Computes the maximum absolute value of all iterated values.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Maximum absolute value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var m = itermaxabs( arr )\n    4.0\n\n    See Also\n    --------\n    itermax, iterminabs, itermmaxabs\n","itermean":"\nitermean( iterator )\n    Computes an arithmetic mean over all iterated values.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Arithmetic mean.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var m = itermean( arr )\n    2.5\n\n    See Also\n    --------\n    itermidrange, itermmean, iterstdev, itersum, itervariance\n","itermeanabs":"\nitermeanabs( iterator )\n    Computes an arithmetic mean of absolute values for all iterated values.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Arithmetic mean of absolute values.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\n    > var m = itermeanabs( arr )\n    2.5\n\n    See Also\n    --------\n    itermean, itermmeanabs, itersumabs\n","itermeanabs2":"\nitermeanabs2( iterator )\n    Computes an arithmetic mean of squared absolute values for all iterated\n    values.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Arithmetic mean of squared absolute values.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\n    > var m = itermeanabs2( arr )\n    7.5\n\n    See Also\n    --------\n    itermean, itermeanabs, itermmeanabs2, itersumabs2\n","itermidrange":"\nitermidrange( iterator )\n    Computes the mid-range of all iterated values.\n\n    The mid-range is the arithmetic mean of maximum and minimum values.\n    Accordingly, the mid-range is the midpoint of the range and a measure of\n    central tendency.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Mid-range.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var v = itermidrange( arr )\n    -0.5\n\n    See Also\n    --------\n    itermean, itermax, itermin, iterrange\n","itermin":"\nitermin( iterator )\n    Computes the minimum value of all iterated values.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Minimum value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\n    > var m = itermin( arr )\n    -3.0\n\n    See Also\n    --------\n    itermax, itermidrange, itermmin, iterrange\n","iterminabs":"\niterminabs( iterator )\n    Computes the minimum absolute value of all iterated values.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Minimum absolute value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var m = iterminabs( arr )\n    1.0\n\n    See Also\n    --------\n    itermaxabs, itermin, itermminabs\n","itermmax":"\nitermmax( iterator, W )\n    Returns an iterator which iteratively computes a moving maximum value.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving maximum value.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermmax( arr, 3 );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    2.0\n    > m = it.next().value\n    3.0\n    > m = it.next().value\n    5.0\n\n    See Also\n    --------\n    itermax, itermmidrange, itermmin, itermrange\n","itermmaxabs":"\nitermmaxabs( iterator, W )\n    Returns an iterator which iteratively computes a moving maximum absolute\n    value.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving maximum absolute value.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermmaxabs( arr, 3 );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    5.0\n    > m = it.next().value\n    5.0\n    > m = it.next().value\n    5.0\n\n    See Also\n    --------\n    itermaxabs, itermmax, itermminabs\n","itermmean":"\nitermmean( iterator, W )\n    Returns an iterator which iteratively computes a moving arithmetic mean.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving mean.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermmean( arr, 3 );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    -1.5\n    > m = it.next().value\n    0.0\n    > m = it.next().value\n    1.0\n\n    See Also\n    --------\n    itermean, itermsum\n","itermmeanabs":"\nitermmeanabs( iterator, W )\n    Returns an iterator which iteratively computes a moving arithmetic mean of\n    absolute values.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving mean of absolute values.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermmeanabs( arr, 3 );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    3.5\n    > m = it.next().value\n    ~3.33\n    > m = it.next().value\n    ~4.33\n\n    See Also\n    --------\n    itermeanabs, itermmean, itermsumabs\n","itermmeanabs2":"\nitermmeanabs2( iterator, W )\n    Returns an iterator which iteratively computes a moving arithmetic mean of\n    squared absolute values.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving mean of squared absolute values.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermmeanabs2( arr, 3 );\n    > var m = it.next().value\n    4.0\n    > m = it.next().value\n    14.5\n    > m = it.next().value\n    ~12.67\n    > m = it.next().value\n    ~19.67\n\n    See Also\n    --------\n    itermeanabs2, itermmeanabs, itermsumabs2\n","itermmidrange":"\nitermmidrange( iterator, W )\n    Returns an iterator which iteratively computes a moving mid-range.\n\n    The mid-range is the arithmetic mean of maximum and minimum values.\n    Accordingly, the mid-range is the midpoint of the range and a measure of\n    central tendency.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving mid-range.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermmidrange( arr, 3 );\n    > var v = it.next().value\n    2.0\n    > v = it.next().value\n    -1.5\n    > v = it.next().value\n    -1.0\n    > v = it.next().value\n    0.0\n\n    See Also\n    --------\n    itermidrange, itermmean, itermmax, itermmin, itermrange\n","itermmin":"\nitermmin( iterator, W )\n    Returns an iterator which iteratively computes a moving minimum value.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving minimum value.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermmin( arr, 3 );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    -5.0\n    > m = it.next().value\n    -5.0\n    > m = it.next().value\n    -5.0\n\n    See Also\n    --------\n    itermin, itermmax, itermmidrange, itermrange\n","itermminabs":"\nitermminabs( iterator, W )\n    Returns an iterator which iteratively computes a moving minimum absolute\n    value.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving minimum absolute value.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermminabs( arr, 3 );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    2.0\n    > m = it.next().value\n    2.0\n    > m = it.next().value\n    3.0\n\n    See Also\n    --------\n    iterminabs, itermmaxabs, itermmin\n","iterMod":"\niterMod( iter0, ...iterator )\n    Returns an iterator which performs an element-wise modulo operation of two\n    or more iterators.\n\n    The length of the returned iterator is equal to the length of the shortest\n    provided iterator. In other words, the returned iterator ends once *one* of\n    the provided iterators ends.\n\n    If provided a numeric value as an iterator argument, the value is broadcast\n    as an infinite iterator which always returns the provided value.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iter0: Object\n        Input iterator.\n\n    iterator: ...Object\n        Iterators whose values are used as divisors.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 3.0, 2.0 ] );\n    > var it2 = array2iterator( [ 1.0, 4.0 ] );\n    > var it = iterMod( it1, it2 );\n    > var v = it.next().value\n    0.0\n    > v = it.next().value\n    2.0\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterDivide\n","itermprod":"\nitermprod( iterator, W )\n    Returns an iterator which iteratively computes a moving product.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving product.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermprod( arr, 3 );\n    > var p = it.next().value\n    2.0\n    > p = it.next().value\n    -10.0\n    > p = it.next().value\n    -30.0\n    > p = it.next().value\n    -75.0\n\n    See Also\n    --------\n    itermsum, iterprod\n","itermrange":"\nitermrange( iterator, W )\n    Returns an iterator which iteratively computes a moving range.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving range.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermrange( arr, 3 );\n    > var m = it.next().value\n    0.0\n    > m = it.next().value\n    7.0\n    > m = it.next().value\n    8.0\n    > m = it.next().value\n    10.0\n\n    See Also\n    --------\n    itermmax, itermmean, itermmin, iterrange\n","itermsum":"\nitermsum( iterator, W )\n    Returns an iterator which iteratively computes a moving sum.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving sum.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator and the provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermsum( arr, 3 );\n    > var s = it.next().value\n    2.0\n    > s = it.next().value\n    -3.0\n    > s = it.next().value\n    0.0\n    > s = it.next().value\n    3.0\n\n    See Also\n    --------\n    itermmean, itersum\n","itermsumabs":"\nitermsumabs( iterator, W )\n    Returns an iterator which iteratively computes a moving sum of absolute\n    values.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving sum.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermsumabs( arr, 3 );\n    > var s = it.next().value\n    2.0\n    > s = it.next().value\n    7.0\n    > s = it.next().value\n    10.0\n    > s = it.next().value\n    13.0\n\n    See Also\n    --------\n    itermmeanabs, itermsum, itersum, itersumabs\n","itermsumabs2":"\nitermsumabs2( iterator, W )\n    Returns an iterator which iteratively computes a moving sum of squared\n    absolute values.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving sum.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermsumabs2( arr, 3 );\n    > var s = it.next().value\n    4.0\n    > s = it.next().value\n    29.0\n    > s = it.next().value\n    38.0\n    > s = it.next().value\n    59.0\n\n    See Also\n    --------\n    itermmeanabs2, itermsumabs, itersumabs, itersumabs2\n","iterMultiply":"\niterMultiply( iter0, ...iterator )\n    Returns an iterator which performs element-wise multiplication of two or\n    more iterators.\n\n    The length of the returned iterator is equal to the length of the shortest\n    provided iterator. In other words, the returned iterator ends once *one* of\n    the provided iterators ends.\n\n    If provided a numeric value as an iterator argument, the value is broadcast\n    as an infinite iterator which always returns the provided value.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iter0: Object\n        Input iterator.\n\n    iterator: ...Object\n        Iterators to multiply.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1.0, 2.0 ] );\n    > var it2 = array2iterator( [ 3.0, 4.0 ] );\n    > var it = iterMultiply( it1, it2 );\n    > var v = it.next().value\n    3.0\n    > v = it.next().value\n    8.0\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterAdd, iterDivide, iterSubtract\n","iterNegaFibonacciSeq":"\niterNegaFibonacciSeq( [options] )\n    Returns an iterator which generates a negaFibonacci sequence.\n\n    The returned iterator can only generate the first 79 negaFibonacci numbers,\n    as larger negaFibonacci numbers cannot be safely represented in double-\n    precision floating-point format.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 79.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterNegaFibonacciSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n\n    See Also\n    --------\n    base.negafibonacci, iterFibonacciSeq, iterNonFibonacciSeq\n","iterNegaLucasSeq":"\niterNegaLucasSeq( [options] )\n    Returns an iterator which generates a negaLucas sequence.\n\n    The returned iterator can only generate the first 77 negaLucas numbers, as\n    larger negaLucas numbers cannot be safely represented in double-precision\n    floating-point format.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 77.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterNegaLucasSeq();\n    > var v = it.next().value\n    2\n    > v = it.next().value\n    -1\n\n    See Also\n    --------\n    base.negalucas, iterLucasSeq, iterNegaFibonacciSeq\n","iterNegativeEvenIntegersSeq":"\niterNegativeEvenIntegersSeq( [options] )\n    Returns an iterator which generates a sequence of negative even integers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 4503599627370496.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterNegativeEvenIntegersSeq();\n    > var v = it.next().value\n    -2\n    > v = it.next().value\n    -4\n\n    See Also\n    --------\n    iterEvenIntegersSeq, iterIntegersSeq, iterNegativeIntegersSeq, iterNegativeOddIntegersSeq, iterPositiveEvenIntegersSeq, iterNonPositiveEvenIntegersSeq\n","iterNegativeIntegersSeq":"\niterNegativeIntegersSeq( [options] )\n    Returns an iterator which generates a negative integer sequence.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 9007199254740991.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterNegativeIntegersSeq();\n    > var v = it.next().value\n    -1\n    > v = it.next().value\n    -2\n\n    See Also\n    --------\n    iterIntegersSeq, iterNonNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterPositiveIntegersSeq\n","iterNegativeOddIntegersSeq":"\niterNegativeOddIntegersSeq( [options] )\n    Returns an iterator which generates a sequence of negative odd integers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 4503599627370496.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterNegativeOddIntegersSeq();\n    > var v = it.next().value\n    -1\n    > v = it.next().value\n    -3\n\n    See Also\n    --------\n    iterOddIntegersSeq, iterIntegersSeq, iterNegativeIntegersSeq, iterNegativeEvenIntegersSeq, iterPositiveOddIntegersSeq\n","iterNone":"\niterNone( iterator )\n    Tests whether all iterated values are falsy.\n\n    The function immediately returns upon encountering a truthy value.\n\n    If provided an iterator which does not return any iterated values, the\n    function returns `true`.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `false` if a value is truthy; otherwise, the\n        function returns `true`.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n    > var bool = iterNone( arr )\n    false\n\n    See Also\n    --------\n    iterAny, iterEvery, iterForEach, iterNoneBy, iterSome\n","iterNoneBy":"\niterNoneBy( iterator, predicate[, thisArg ] )\n    Tests whether every iterated value fails a test implemented by a predicate\n    function.\n\n    The predicate function is provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index.\n\n    The function immediately returns upon encountering a truthy return value.\n\n    If provided an iterator which does not return any iterated values, the\n    function returns `true`.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if a predicate function returns a falsy\n        value for all iterated values. Otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\n    > function fcn( v ) { return ( v <= 0 ); };\n    > var bool = iterNoneBy( arr, fcn )\n    true\n\n    See Also\n    --------\n    iterAnyBy, iterEveryBy, iterForEach, iterNone, iterSomeBy\n","iterNonFibonacciSeq":"\niterNonFibonacciSeq( [options] )\n    Returns an iterator which generates a non-Fibonacci integer sequence.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterNonFibonacciSeq();\n    > var v = it.next().value\n    4\n    > v = it.next().value\n    6\n\n    See Also\n    --------\n    base.nonfibonacci, iterFibonacciSeq\n","iterNonNegativeEvenIntegersSeq":"\niterNonNegativeEvenIntegersSeq( [options] )\n    Returns an iterator which generates a sequence of nonnegative even integers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 4503599627370497.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterNonNegativeEvenIntegersSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    iterEvenIntegersSeq, iterIntegersSeq, iterNonNegativeIntegersSeq, iterNonPositiveEvenIntegersSeq, iterPositiveEvenIntegersSeq\n","iterNonNegativeIntegersSeq":"\niterNonNegativeIntegersSeq( [options] )\n    Returns an iterator which generates a nonnegative integer sequence.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 9007199254740992.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterNonNegativeIntegersSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n\n    See Also\n    --------\n    iterIntegersSeq, iterNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterPositiveIntegersSeq\n","iterNonPositiveEvenIntegersSeq":"\niterNonPositiveEvenIntegersSeq( [options] )\n    Returns an iterator which generates a sequence of nonpositive even integers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 4503599627370497.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterNonPositiveEvenIntegersSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    -2\n\n    See Also\n    --------\n    iterEvenIntegersSeq, iterIntegersSeq, iterNonNegativeEvenIntegersSeq, iterNonPositiveIntegersSeq, iterNegativeEvenIntegersSeq\n","iterNonPositiveIntegersSeq":"\niterNonPositiveIntegersSeq( [options] )\n    Returns an iterator which generates a nonpositive integer sequence.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 9007199254740992.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterNonPositiveIntegersSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    -1\n\n    See Also\n    --------\n    iterIntegersSeq, iterNegativeIntegersSeq, iterNonNegativeIntegersSeq, iterPositiveIntegersSeq\n","iterNonSquaresSeq":"\niterNonSquaresSeq( [options] )\n    Returns an iterator which generates a sequence of nonsquares.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 9007199349647256.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterNonSquaresSeq();\n    > var v = it.next().value\n    2\n    > v = it.next().value\n    3\n    > v = it.next().value\n    5\n\n    See Also\n    --------\n    iterCubesSeq, iterSquaresSeq\n","iterNth":"\niterNth( iterator, n )\n    Returns the nth iterated value.\n\n    If `n` exceeds the total number of iterations, the function returns\n    `undefined`.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    n: integer\n        Iteration number.\n\n    Returns\n    -------\n    v: any\n        The nth iterated value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 0, 0, 1, 0, 0 ] );\n    > var v = iterNth( arr, 3 )\n    1\n\n    See Also\n    --------\n    iterFirst, iterLast\n","iterOddIntegersSeq":"\niterOddIntegersSeq( [options] )\n    Returns an iterator which generates an interleaved sequence of odd integers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 9007199254740992.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterOddIntegersSeq();\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    -1\n    > v = it.next().value\n    3\n\n    See Also\n    --------\n    iterEvenIntegersSeq, iterIntegersSeq\n","iterPeriodicSinc":"\niterPeriodicSinc( n[, options] )\n    Returns an iterator which generates a periodic sinc waveform.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    n: integer\n        Order.\n\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Period (i.e., the number of iterations before a waveform repeats).\n        Default: 100.\n\n    options.amplitude: number (optional)\n        Peak amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterPeriodicSinc( 7 );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterSineWave\n","iterPipeline":"\niterPipeline( iterFcn[, ...iterFcn] )\n    Returns an iterator pipeline.\n\n    Parameters\n    ----------\n    iterFcn: Function|Array\n        Iterator function or an array of iterator functions.\n\n    iterFcn: ...Function (optional)\n        Iterator functions.\n\n    Returns\n    -------\n    fcn( src ): Function\n        Iterator pipeline which accepts a single argument, a source iterator.\n\n    Examples\n    --------\n    > var it1 = iterThunk( iterHead, 100 );\n    > function f( r ) { return ( r > 0.95 ); };\n    > var it2 = iterThunk( iterSomeBy, 5, f );\n    > var p = iterPipeline( it1, it2 );\n    > var bool = p( random.iterators.randu() )\n    <boolean>\n\n    See Also\n    --------\n    iterFlow, iterThunk\n","iterPop":"\niterPop( iterator[, clbk[, thisArg]] )\n    Returns an iterator which skips the last value of a provided iterator.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    clbk: Function (optional)\n        Callback to invoke with the skipped value.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2 ] );\n    > var it2 = iterPop( it1 );\n    > var v = it2.next().value\n    1\n    > var bool = it2.next().done\n    true\n\n    See Also\n    --------\n    iterPush, iterShift, iterSlice\n","iterPositiveEvenIntegersSeq":"\niterPositiveEvenIntegersSeq( [options] )\n    Returns an iterator which generates a sequence of positive even integers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 4503599627370496.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterPositiveEvenIntegersSeq();\n    > var v = it.next().value\n    2\n    > v = it.next().value\n    4\n\n    See Also\n    --------\n    iterEvenIntegersSeq, iterIntegersSeq, iterNegativeEvenIntegersSeq, iterNonNegativeEvenIntegersSeq, iterPositiveIntegersSeq, iterPositiveOddIntegersSeq\n","iterPositiveIntegersSeq":"\niterPositiveIntegersSeq( [options] )\n    Returns an iterator which generates a positive integer sequence.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 9007199254740991.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterPositiveIntegersSeq();\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    iterNonNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterNegativeIntegersSeq\n","iterPositiveOddIntegersSeq":"\niterPositiveOddIntegersSeq( [options] )\n    Returns an iterator which generates a sequence of positive odd integers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 4503599627370496.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterPositiveOddIntegersSeq();\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    3\n\n    See Also\n    --------\n    iterOddIntegersSeq, iterIntegersSeq, iterNegativeOddIntegersSeq, iterPositiveEvenIntegersSeq, iterPositiveIntegersSeq\n","iterPow":"\niterPow( base, exponent )\n    Returns an iterator which iteratively evaluates the exponential function.\n\n    The length of the returned iterator is equal to the length of the shortest\n    provided iterator. In other words, the returned iterator ends once *one* of\n    the provided iterators ends.\n\n    If provided a numeric value as an iterator argument, the value is broadcast\n    as an infinite iterator which always returns the provided value.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    base: Object|number\n        Input iterator.\n\n    exponent: Object|number\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = random.iterators.uniform( 0.0, 2.0 );\n    > var y = random.iterators.uniform( -2.0, 2.0 );\n    > var it = iterPow( x, y );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.pow, iterExp, iterLog\n","iterPrimesSeq":"\niterPrimesSeq( [options] )\n    Returns an iterator which generates a sequence of prime numbers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 245181918813464.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterPrimesSeq();\n    > var v = it.next().value\n    2\n    > v = it.next().value\n    3\n    > v = it.next().value\n    5\n\n    See Also\n    --------\n    iterCompositesSeq, iterIntegersSeq, iterPositiveIntegersSeq\n","iterprod":"\niterprod( iterator )\n    Computes the product of all iterated values.\n\n    For iterators which can generate many values or which may output large\n    numbers, care should be taken to prevent overflow.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Product.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var s = iterprod( arr )\n    24.0\n\n    See Also\n    --------\n    itermprod, itersum\n","iterPulse":"\niterPulse( [options] )\n    Returns an iterator which generates a pulse waveform.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Pulse period (i.e., the number of iterations until a waveform repeats).\n        Default: 10.\n\n    options.duration: integer (optional)\n        Pulse duration (i.e., the number of consecutive iterations of maximum\n        amplitude during one period). Default: floor(options.period/2).\n\n    options.min: number (optional)\n        Minimum amplitude. Default: 0.0.\n\n    options.max: number (optional)\n        Maximum amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterPulse();\n    > var v = it.next().value\n    1.0\n    > v = it.next().value\n    1.0\n\n    See Also\n    --------\n    iterSawtoothWave, iterSineWave, iterSquareWave, iterTriangleWave\n","iterPush":"\niterPush( iterator, ...items )\n    Returns an iterator which appends additional values to the end of a provided\n    iterator.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    items: ...any\n        Items to append.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2 ] );\n    > var it2 = iterPush( it1, 3, 4 );\n    > var v = it2.next().value\n    1\n    > v = it2.next().value\n    2\n    > v = it2.next().value\n    3\n    > v = it2.next().value\n    4\n    > var bool = it2.next().done\n    true\n\n    See Also\n    --------\n    iterConcat, iterUnshift\n","iterRad2deg":"\niterRad2deg( iterator )\n    Returns an iterator which iteratively converts an angle from radians to\n    degrees.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 6.28 );\n    > var it = iterRad2deg( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.rad2deg, iterDeg2rad\n","iterRamp":"\niterRamp( iterator )\n    Returns an iterator which iteratively evaluates the ramp function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterRamp( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.ramp\n","iterrange":"\niterrange( iterator )\n    Computes the range of all iterated values.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Range.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var v = iterrange( arr )\n    7.0\n\n    See Also\n    --------\n    itermax, itermean, itermin, itermrange\n","iterReject":"\niterReject( iterator, predicate[, thisArg] )\n    Returns an iterator which rejects a provided iterator's values according to\n    a predicate function.\n\n    When invoked, the predicate function is provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index (zero-based).\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    predicate: Function\n        Predicate function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > function f( v ) { return ( v > 2 ); };\n    > var it1 = array2iterator( [ 1, 3, 2, 4 ] );\n    > var it2 = iterReject( it1, f );\n    > var v = it2.next().value\n    1\n    > v = it2.next().value\n    2\n\n    See Also\n    --------\n    iterFilter, iterMap\n","iterReplicate":"\niterReplicate( iterator, n )\n    Returns an iterator which replicates each iterated value `n` times.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    n: integer\n        Number of times each iterated value is replicated.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2, 3, 4 ] );\n    > var it2 = iterReplicate( it1, 2 );\n    > var v = it2.next().value\n    1\n    > v = it2.next().value\n    1\n    > v = it2.next().value\n    2\n    > v = it2.next().value\n    2\n\n    See Also\n    --------\n    iterReplicateBy\n","iterReplicateBy":"\niterReplicateBy( iterator, fcn[, thisArg] )\n    Returns an iterator which replicates each iterated value according to a\n    provided function.\n\n    The callback function is provided three arguments:\n\n    - value: iterated value.\n    - index: source iteration index (zero-based).\n    - n: iteration index (zero-based).\n\n    The callback function is invoked *once* per iterated value of the provided\n    iterator.\n\n    The callback function *must* return an integer value. If the return value is\n    less than or equal to zero, the returned iterator skips an iterated value\n    and invokes the callback for the next iterated value of the provided\n    iterator.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    fcn: Function\n        Function which returns the number of times an iterated value should be\n        replicated.\n\n    thisArg: any (optional)\n        Callback function execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2, 3, 4 ] );\n    > function f( v, i ) { return i + 1; };\n    > var it2 = iterReplicateBy( it1, f );\n    > var v = it2.next().value\n    1\n    > v = it2.next().value\n    2\n    > v = it2.next().value\n    2\n    > v = it2.next().value\n    3\n    > v = it2.next().value\n    3\n    > v = it2.next().value\n    3\n    > v = it2.next().value\n    4\n\n    See Also\n    --------\n    iterReplicate\n","iterRound":"\niterRound( iterator )\n    Returns an iterator which rounds each iterated value to the nearest integer.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterRound( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.round, iterCeil, iterFloor, iterTrunc\n","iterRound2":"\niterRound2( iterator )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    two on a linear scale.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterRound2( random.iterators.uniform( -100.0, 100.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.round2, iterCeil2, iterFloor2, iterRound, iterRound10, iterTrunc2\n","iterRound10":"\niterRound10( iterator )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    10 on a linear scale.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterRound10( random.iterators.uniform( -100.0, 100.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.round10, iterCeil10, iterFloor10, iterRound, iterRound2, iterTrunc10\n","iterRsqrt":"\niterRsqrt( iterator )\n    Returns an iterator which iteratively computes the reciprocal (inverse)\n    square root.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterRsqrt( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.rsqrt, iterSqrt\n","iterSawtoothWave":"\niterSawtoothWave( [options] )\n    Returns an iterator which generates a sawtooth wave.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Period (i.e., the number of iterations before a waveform repeats).\n        Default: 10.\n\n    options.amplitude: number (optional)\n        Peak amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterSawtoothWave();\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterPulse, iterSineWave, iterSquareWave, iterTriangleWave\n","iterShift":"\niterShift( iterator[, clbk[, thisArg]] )\n    Returns an iterator which skips the first value of a provided iterator.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    clbk: Function (optional)\n        Callback to invoke with the skipped value.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2 ] );\n    > var it2 = iterShift( it1 );\n    > var v = it2.next().value\n    2\n    > var bool = it2.next().done\n    true\n\n    See Also\n    --------\n    iterPop, iterSlice, iterUnshift\n","iterSignum":"\niterSignum( iterator )\n    Returns an iterator which iteratively evaluates the signum function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterSignum( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.signum\n","iterSin":"\niterSin( iterator )\n    Returns an iterator which iteratively computes the sine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterSin( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.sin, iterCos, iterSinpi, iterTan\n","iterSinc":"\niterSinc( iterator )\n    Returns an iterator which iteratively computes the normalized cardinal sine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -5.0, 5.0 );\n    > var it = iterSinc( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.sinc, iterSin\n","iterSineWave":"\niterSineWave( [options] )\n    Returns an iterator which generates a sine wave.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Period (i.e., the number of iterations before a sine wave repeats).\n        Default: 10.\n\n    options.amplitude: number (optional)\n        Peak amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterSineWave();\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterCosineWave, iterPulse, iterSawtoothWave, iterSquareWave, iterTriangleWave\n","iterSinh":"\niterSinh( iterator )\n    Returns an iterator which iteratively evaluates the hyperbolic sine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -5.0, 5.0 );\n    > var it = iterSinh( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.sinh, iterCosh, iterTanh\n","iterSinpi":"\niterSinpi( iterator )\n    Returns an iterator which computes the sine of each iterated value times π.\n\n    Computes sin(πx) more accurately than sin(pi*x), especially for large x.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterSinpi( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.sinpi, iterSin\n","iterSlice":"\niterSlice( iterator[, begin[, end]] )\n    Returns an iterator which returns a subsequence of iterated values from a\n    provided iterator.\n\n    If `end` exceeds the length of the provided iterator, the returned iterator\n    returns the subsequence of iterated values starting from `begin` until the\n    last iterated value of the provided iterator.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    begin: integer (optional)\n        Start iteration index (zero-based and inclusive). Default: 0.\n\n    end: integer (optional)\n        End iteration index (zero-based and non-inclusive).\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterSlice( random.iterators.randu(), 5, 10 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterFirst, iterHead\n","iterSome":"\niterSome( iterator, n )\n    Tests whether at least `n` iterated values are truthy.\n\n    The function immediately returns upon finding `n` truthy values.\n\n    If provided an iterator which does not return any iterated values, the\n    function returns `false`.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    n: number\n        Minimum number of truthy elements.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if an iterator returns at least `n` truthy\n        elements; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\n    > var bool = iterSome( arr, 3 )\n    true\n\n    See Also\n    --------\n    iterAny, iterEvery, iterForEach, iterNone, iterSomeBy\n","iterSomeBy":"\niterSomeBy( iterator, n, predicate[, thisArg ] )\n    Tests whether at least `n` iterated values pass a test implemented by a\n    predicate function.\n\n    The predicate function is provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index.\n\n    The function immediately returns upon encountering `n` truthy return values.\n\n    If provided an iterator which does not return any iterated values, the\n    function returns `false`.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    n: integer\n        Minimum number of successful values.\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if a predicate function returns a truthy\n        value for at least `n` iterated values. Otherwise, the function returns\n        `false`.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1, 1, 0, 0, 1 ] );\n    > function fcn( v ) { return ( v > 0 ); };\n    > var bool = iterSomeBy( arr, 3, fcn )\n    true\n\n    See Also\n    --------\n    iterAnyBy, iterEveryBy, iterForEach, iterNoneBy, iterSome\n","iterSpence":"\niterSpence( iterator )\n    Returns an iterator which iteratively evaluates Spence's function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 100.0 );\n    > var it = iterSpence( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.spence\n","iterSqrt":"\niterSqrt( iterator )\n    Returns an iterator which iteratively computes the principal square root.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterSqrt( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.sqrt, iterCbrt, iterRsqrt\n","iterSqrt1pm1":"\niterSqrt1pm1( iterator )\n    Returns an iterator which iteratively computes `sqrt(1+x) - 1` more \n    accurately for small `x`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 100.0 );\n    > var it = iterSqrt1pm1( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.sqrt1pm1, iterSqrt\n","iterSquaredTriangularSeq":"\niterSquaredTriangularSeq( [options] )\n    Returns an iterator which generates a sequence of squared triangular\n    numbers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 11585.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterSquaredTriangularSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().value\n    9\n\n    See Also\n    --------\n    iterTriangularSeq\n","iterSquaresSeq":"\niterSquaresSeq( [options] )\n    Returns an iterator which generates a sequence of squares.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 94906265.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterSquaresSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().value\n    4\n\n    See Also\n    --------\n    iterCubesSeq, iterNonSquaresSeq\n","iterSquareWave":"\niterSquareWave( [options] )\n    Returns an iterator which generates a square wave.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Period (i.e., the number of iterations before a square wave repeats).\n        This must be an even integer in order to ensure a 50% duty cycle.\n        Default: 10.\n\n    options.min: number (optional)\n        Minimum amplitude. Default: -1.0.\n\n    options.max: number (optional)\n        Maximum amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterSquareWave();\n    > var v = it.next().value\n    1.0\n    > v = it.next().value\n    1.0\n\n    See Also\n    --------\n    iterPulse, iterSawtoothWave, iterSineWave, iterTriangleWave\n","iterstdev":"\niterstdev( iterator[, mean] )\n    Computes a correct sample standard deviation over all iterated values.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    mean: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    out: number|null\n        Corrected sample standard deviation.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0 ] );\n    > var m = iterstdev( arr )\n    ~4.95\n\n    See Also\n    --------\n    itermean, itervariance\n","iterStep":"\niterStep( start, increment[, N] )\n    Returns an iterator which returns a sequence of numbers according to a\n    specified increment.\n\n    Beware that values which follow the starting value are subject to floating-\n    point rounding errors.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    start: number\n        Starting value (inclusive).\n\n    increment: number\n        Increment.\n\n    N: number (optional)\n        Number of values. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterStep( 0, 2, 10 );\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    iterator2array, iterDatespace, iterIncrspace, iterLinspace, iterLogspace, iterUnitspace\n","iterStrided":"\niterStrided( iterator, stride[, offset[, eager]] )\n    Returns an iterator which steps by a specified amount.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    stride: integer\n        Stride (i.e., step amount).\n\n    offset: integer (optional)\n        Index of the first iterated value. Default: 0.\n\n    eager: boolean (optional)\n        Boolean indicating whether to eagerly advance the input iterator when\n        provided a non-zero offset. Default: false.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\n    > var it = iterStrided( arr, 2, 1 );\n    > var r = it.next().value\n    1\n    > r = it.next().value\n    3\n\n    See Also\n    --------\n    iterAdvance, iterNth, iterStridedBy\n","iterStridedBy":"\niterStridedBy( iterator, fcn[, offset[, eager]][, thisArg] )\n    Returns an iterator which steps according to a provided callback function.\n\n    When invoked, the input function is provided four arguments:\n\n    - value: iterated value.\n    - i: input iteration index (zero-based).\n    - n: output (strided) iteration index (zero-based).\n    - curr: current stride.\n\n    The return value of the input function specifies the next stride.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    fcn: Function\n        Stride function (i.e., a function which returns the step amount).\n\n    offset: integer (optional)\n        Index of the first iterated value. Default: 0.\n\n    eager: boolean (optional)\n        Boolean indicating whether to eagerly advance the input iterator when\n        provided a non-zero offset. Default: false.\n\n    thisArg: any (optional)\n        Stride function execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\n    > function stride( v, i ) { return (i % 10)+1; };\n    > var it = iterStridedBy( arr, stride );\n    > var r = it.next().value\n    0\n    > r = it.next().value\n    1\n    > r = it.next().value\n    3\n\n    See Also\n    --------\n    iterAdvance, iterNth, iterStrided\n","iterSubtract":"\niterSubtract( iter0, ...iterator )\n    Returns an iterator which performs element-wise subtraction of two or more\n    iterators.\n\n    The length of the returned iterator is equal to the length of the shortest\n    provided iterator. In other words, the returned iterator ends once *one* of\n    the provided iterators ends.\n\n    If provided a numeric value as an iterator argument, the value is broadcast\n    as an infinite iterator which always returns the provided value.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iter0: Object\n        Input iterator.\n\n    iterator: ...Object\n        Iterators to subtract.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1.0, 5.0 ] );\n    > var it2 = array2iterator( [ 3.0, 4.0 ] );\n    > var it = iterSubtract( it1, it2 );\n    > var v = it.next().value\n    -2.0\n    > v = it.next().value\n    1.0\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterAdd, iterDivide, iterMultiply\n","itersum":"\nitersum( iterator )\n    Computes the sum of all iterated values.\n\n    For iterators which can generate many values or which may output large\n    numbers, care should be taken to prevent overflow.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Sum.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var s = itersum( arr )\n    10.0\n\n    See Also\n    --------\n    itermean, itermsum, iterprod\n","itersumabs":"\nitersumabs( iterator )\n    Computes the sum of absolute values for all iterated values.\n\n    For iterators which can generate many values or which may output large\n    numbers, care should be taken to prevent overflow.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Sum of absolute values.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\n    > var s = itersumabs( arr )\n    10.0\n\n    See Also\n    --------\n    itermeanabs, itermsumabs, itersum\n","itersumabs2":"\nitersumabs2( iterator )\n    Computes the sum of squared absolute values for all iterated values.\n\n    For iterators which can generate many values or which may output large\n    numbers, care should be taken to prevent overflow.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Sum of squared absolute values.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\n    > var s = itersumabs2( arr )\n    30.0\n\n    See Also\n    --------\n    itermeanabs2, itermsumabs2, itersumabs\n","iterTan":"\niterTan( iterator )\n    Returns an iterator which iteratively evaluates the tangent.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -1.57, 1.57 );\n    > var it = iterTan( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.tan, iterCos, iterSin\n","iterTanh":"\niterTanh( iterator )\n    Returns an iterator which iteratively evaluates the hyperbolic tangent.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -4.0, 4.0 );\n    > var it = iterTanh( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.tanh, iterCosh, iterSinh, iterTan\n","iterThunk":"\niterThunk( iterFcn[, ...args] )\n    Returns an iterator \"thunk\".\n\n    A provided iterator function should have the following function signature:\n\n      iterFcn( iterator, ...args )\n\n    The returned function expects a single argument, an iterator.\n\n    This function is useful within the context of iterator pipelines as a means\n    to defer execution until a pipeline is ready for data flow.\n\n    Parameters\n    ----------\n    iterFcn: Function\n        Iterator function.\n\n    args: ...any (optional)\n        Function arguments.\n\n    Returns\n    -------\n    fcn( iter ): Function\n        Function which accepts a single argument, an iterator, and invokes a\n        previously provided iterator function with the provided iterator and any\n        previously provided arguments.\n\n    Examples\n    --------\n    > var fcn = iterThunk( iterSome, 3 );\n    > var arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\n    > var bool = fcn( arr )\n    true\n\n    See Also\n    --------\n    iterPipeline\n","iterTriangleWave":"\niterTriangleWave( [options] )\n    Returns an iterator which generates a triangle wave.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Period (i.e., the number of iterations before a waveform repeats).\n        Default: 10.\n\n    options.amplitude: number (optional)\n        Peak amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterTriangleWave();\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterPulse, iterSawtoothWave, iterSineWave, iterSquareWave\n","iterTriangularSeq":"\niterTriangularSeq( [options] )\n    Returns an iterator which generates a sequence of triangular numbers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 134217727.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterTriangularSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().value\n    3\n\n    See Also\n    --------\n    iterSquaredTriangularSeq\n","iterTribonnaciSeq":"\niterTribonnaciSeq( [options] )\n    Returns an iterator which generates a Tribonacci sequence.\n    \n    The returned iterator can only generate the first 64 Tribonacci numbers, as\n    larger Tribonacci numbers cannot be safely represented in double-precision\n    floating-point format.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 64.\n\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant\n        object has the next\n        iterated value (if one exists) and a\n        boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n\n    Examples\n    --------\n    > var it = iterTribonnaciSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    0\n\n    See Also\n    --------\n    base.tribonacci, base.fibonacci, iterLucasSeq\n","iterTrigamma":"\niterTrigamma( iterator )\n    Returns an iterator which iteratively evaluates the trigamma function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.01, 50.0 );\n    > var it = iterTrigamma( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.trigamma, iterDigamma, iterGamma\n","iterTrunc":"\niterTrunc( iterator )\n    Returns an iterator which rounds each iterated value toward zero.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterTrunc( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.trunc, iterCeil, iterFloor, iterRound\n","iterTrunc2":"\niterTrunc2( iterator )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    two toward zero.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterTrunc2( random.iterators.uniform( -100.0, 100.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.trunc2, iterCeil2, iterFloor2, iterRound2, iterTrunc\n","iterTrunc10":"\niterTrunc10( iterator )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    10 toward zero.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterTrunc10( random.iterators.uniform( -100.0, 100.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.trunc10, iterCeil10, iterFloor10, iterRound10, iterTrunc\n","iterUnion":"\niterUnion( iter0, ...iterator )\n    Returns an iterator which returns the union of two or more iterators.\n\n    Value \"uniqueness\" is determined according to strict equality.\n\n    A returned iterator internally buffers unique values and, thus, has O(N)\n    memory requirements, where `N` is the total number of source iterator\n    values.\n\n    If an environment supports Symbol.iterator and all provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iter0: Object\n        Input iterator.\n\n    iterator: ...Object\n        Input iterators.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n    > var it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\n    > var it = iterUnion( it1, it2 );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    2\n    > v = it.next().value\n    4\n    > v = it.next().value\n    5\n    > v = it.next().value\n    3\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterIntersection, iterUnique\n","iterUnique":"\niterUnique( iterator )\n    Returns an iterator which returns unique values.\n\n    Value \"uniqueness\" is determined according to strict equality.\n\n    A returned iterator internally buffers unique values and, thus, has O(N)\n    memory requirements.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n    > var it2 = iterUnique( it1 );\n    > var v = it2.next().value\n    1\n    > v = it2.next().value\n    2\n    > v = it2.next().value\n    4\n    > var bool = it2.next().done\n    true\n\n    See Also\n    --------\n    iterUniqueBy, iterUniqueByHash\n","iterUniqueBy":"\niterUniqueBy( iterator, predicate[, thisArg] )\n    Returns an iterator which returns unique values according to a predicate\n    function.\n\n    A returned iterator internally buffers unique values and, thus, has O(N)\n    memory requirements.\n\n    A predicate function is invoked for each iterated value against each value\n    in an internal buffer consisting of previously identified unique values.\n    Thus, as the number of unique values grows, so, too, does the number of\n    predicate function invocations per iterated value.\n\n    An iterated value is considered \"unique\" if the predicate function returns\n    truthy values for all comparisons of the iterated value with each value in\n    the internal buffer.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    predicate: Function\n        A binary function with parameters `a` and `b` corresponding to iterated\n        values. If the values are the same, the function should return `false`\n        (i.e., non-unique); otherwise, if the values are distinct, the function\n        should return `true` (i.e., unique).\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n    > function f( a, b ) { return ( a !== b ); };\n    > var it2 = iterUniqueBy( it1, f );\n    > var v = it2.next().value\n    1\n    > v = it2.next().value\n    2\n    > v = it2.next().value\n    4\n    > var bool = it2.next().done\n    true\n\n    See Also\n    --------\n    iterUnique, iterUniqueByHash\n","iterUniqueByHash":"\niterUniqueByHash( iterator, hashFcn[, thisArg] )\n    Returns an iterator which returns unique values according to a hash\n    function.\n\n    A returned iterator internally buffers unique hashes and, thus, has O(N)\n    memory requirements.\n\n    An iterated value is considered \"unique\" if the hash function returns a\n    unique hash value for that iterated value. Beware that this *may* result in\n    unexpected behavior. Namely, only the first iterated value mapping to a\n    particular hash function result is returned, even if subsequent values,\n    while mapping to the same hash, are different. Accordingly, iteration order\n    *does* matter.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    hashFcn: Function\n        Hash function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n    > function f( v ) { return v.toString(); };\n    > var it2 = iterUniqueByHash( it1, f );\n    > var v = it2.next().value\n    1\n    > v = it2.next().value\n    2\n    > v = it2.next().value\n    4\n    > var bool = it2.next().done\n    true\n\n    See Also\n    --------\n    iterUnique, iterUniqueBy\n","iterUnitspace":"\niterUnitspace( start[, stop] )\n    Returns an iterator which returns numbers incremented by one.\n\n    The iterator stops once the `stop` value is exceeded.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    start: number\n        Starting value (inclusive).\n\n    stop: number (optional)\n        Stopping value. Default: +infinity.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterUnitspace( 0, 99 );\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n\n    See Also\n    --------\n    iterator2array, iterIncrspace, iterLinspace, iterStep\n","iterUnshift":"\niterUnshift( iterator, ...items )\n    Returns an iterator which prepends values to the beginning of a provided\n    iterator.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    items: ...any\n        Items to prepend.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2 ] );\n    > var it2 = iterUnshift( it1, 3, 4 );\n    > var v = it2.next().value\n    3\n    > v = it2.next().value\n    4\n    > v = it2.next().value\n    1\n    > v = it2.next().value\n    2\n    > var bool = it2.next().done\n    true\n\n    See Also\n    --------\n    iterConcat, iterPush, iterShift\n","iterUntilEach":"\niterUntilEach( iterator, predicate, fcn[, thisArg] )\n    Returns an iterator which invokes a function for each iterated value before\n    returning the iterated value until either a predicate function returns true\n    or the iterator has iterated over all values.\n\n    When invoked, both input functions are provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index (zero-based).\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    predicate: Function\n        Function which indicates whether to continue iterating.\n\n    fcn: Function\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > function predicate( v ) { return v !== v };\n    > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n    > var it = iterUntilEach( random.iterators.randu(), predicate, f );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterWhileEach\n","itervariance":"\nitervariance( iterator[, mean] )\n    Computes an unbiased sample variance over all iterated values.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    mean: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    out: number|null\n        Unbiased sample variance.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0 ] );\n    > var s2 = itervariance( arr )\n    24.5\n\n    See Also\n    --------\n    itermean, iterstdev\n","iterVercos":"\niterVercos( iterator )\n    Returns an iterator which iteratively computes the versed cosine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 6.28 );\n    > var it = iterVercos( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.vercos, iterCos, iterSin, iterVersin\n","iterVersin":"\niterVersin( iterator )\n    Returns an iterator which iteratively computes the versed sine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 6.28 );\n    > var it = iterVersin( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.versin, iterCos, iterSin, iterVercos\n","iterWhileEach":"\niterWhileEach( iterator, predicate, fcn[, thisArg] )\n    Returns an iterator which invokes a function for each iterated value before\n    returning the iterated value until either a predicate function returns false\n    or the iterator has iterated over all values.\n\n    When invoked, both input functions are provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index (zero-based).\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    predicate: Function\n        Function which indicates whether to continue iterating.\n\n    fcn: Function\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === v };\n    > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n    > var it = iterWhileEach( random.iterators.randu(), predicate, f );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterUntilEach\n","iterZeta":"\niterZeta( iterator )\n    Returns an iterator which iteratively evaluates the Riemann zeta function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 1.1, 50.0 );\n    > var it = iterZeta( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.zeta\n","joinStream":"\njoinStream( [options] )\n    Returns a transform stream which joins streamed data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. Default: '\\n'.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream.\n\n    Examples\n    --------\n    > var s = joinStream();\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();\n\n\njoinStream.factory( [options] )\n    Returns a function for creating transform streams for joined streamed data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. Default: '\\n'.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    createStream: Function\n        Function for creating transform streams.\n\n    Examples\n    --------\n    > var opts = { 'highWaterMark': 64 };\n    > var createStream = joinStream.factory( opts );\n    > var s = createStream();\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();\n\n\njoinStream.objectMode( [options] )\n    Returns an \"objectMode\" transform stream for joining streamed data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. Default: '\\n'.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > var s = joinStream.objectMode();\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();\n\n    See Also\n    --------\n    splitStream\n","joinStream.factory":"\njoinStream.factory( [options] )\n    Returns a function for creating transform streams for joined streamed data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. Default: '\\n'.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    createStream: Function\n        Function for creating transform streams.\n\n    Examples\n    --------\n    > var opts = { 'highWaterMark': 64 };\n    > var createStream = joinStream.factory( opts );\n    > var s = createStream();\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();","joinStream.objectMode":"\njoinStream.objectMode( [options] )\n    Returns an \"objectMode\" transform stream for joining streamed data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. Default: '\\n'.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > var s = joinStream.objectMode();\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();\n\n    See Also\n    --------\n    splitStream","kde2d":"\nkde2d( x, y[, options] )\n    Two-dimensional kernel density estimation.\n\n    Parameters\n    ----------\n    x: Array<number>\n        Array of x values.\n\n    y: Array<number>\n        Array of y values.\n\n    options: Object (optional)\n        Function options.\n\n    options.h: number (optional)\n        Array of length two containing the bandwidth values for x and y.\n\n    options.n: number (optional)\n        Number of partitions on the x- and y-axes. Default: `25`.\n\n    options.xMin: number (optional)\n        Lower limit of x.\n\n    options.xMax: number (optional)\n        Upper limit of x.\n\n    options.yMin: number (optional)\n        Lower limit of y.\n\n    options.yMax: number (optional)\n        Upper limit of y.\n\n    options.kernel: string|Function\n        A string or function to specifying the used kernel function. Default:\n        `'gaussian'`.\n\n    Returns\n    -------\n    out: Object\n        Object containing the density estimates (`z`) along grid points (`x` and\n        `y` values).\n\n    Examples\n    --------\n    > var x = [ 1, 3, 5, 6, 21, 23, 16, 17, 20, 10 ];\n    > var y = [ 0.40, 0.20, 0.20, 0.15, 0.05, 0.55, 0.6, 0.33, 0.8, 0.41 ];\n    > var out = kde2d( x, y )\n    { 'x': [1, ... ], 'y': [0.05, ...], 'z': ndarray{Float64Array[0.031, ...] }\n\n","kebabcase":"\nkebabcase( str )\n    Converts a string to kebab case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Kebab-cased string.\n\n    Examples\n    --------\n    > var out = kebabcase( 'Hello World!' )\n    'hello-world'\n    > out = kebabcase( 'I am a tiny little teapot' )\n    'i-am-a-tiny-little-teapot'\n\n    See Also\n    --------\n    camelcase, constantcase, pascalcase, snakecase","keyBy":"\nkeyBy( collection, fcn[, thisArg] )\n    Converts a collection to an object whose keys are determined by a provided\n    function and whose values are the collection values.\n\n    When invoked, the input function is provided two arguments:\n\n    - value: collection value.\n    - index: collection index.\n\n    If more than one element in a collection resolves to the same key, the key\n    value is the collection element which last resolved to the key.\n\n    Object values are shallow copies.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Object\n        Output object.\n\n    Examples\n    --------\n    > function toKey( v ) { return v.a; };\n    > var arr = [ { 'a': 1 }, { 'a': 2 } ];\n    > keyBy( arr, toKey )\n    { '1': { 'a': 1 }, '2': { 'a': 2 } }\n\n    See Also\n    --------\n    forEach\n","keyByRight":"\nkeyByRight( collection, fcn[, thisArg] )\n    Converts a collection to an object whose keys are determined by a provided\n    function and whose values are the collection values, iterating from right to\n    left.\n\n    When invoked, the input function is provided two arguments:\n\n    - value: collection value.\n    - index: collection index.\n\n    If more than one element in a collection resolves to the same key, the key\n    value is the collection element which last resolved to the key.\n\n    Object values are shallow copies.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Object\n        Output object.\n\n    Examples\n    --------\n    > function toKey( v ) { return v.a; };\n    > var arr = [ { 'a': 1 }, { 'a': 2 } ];\n    > keyByRight( arr, toKey )\n    { '2': { 'a': 2 }, '1': { 'a': 1 } }\n\n    See Also\n    --------\n    forEachRight, keyBy\n","keysIn":"\nkeysIn( obj )\n    Returns an array of an object's own and inherited enumerable property\n    names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    Parameters\n    ----------\n    obj: any\n        Input value.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's own and inherited enumerable property names.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var keys = keysIn( obj )\n    e.g., [ 'beep', 'foo' ]\n\n    See Also\n    --------\n    objectEntriesIn, objectKeys, objectValuesIn\n","kruskalTest":"\nkruskalTest( ...x[, options] )\n    Computes the Kruskal-Wallis test for equal medians.\n\n    Parameters\n    ----------\n    x: ...Array\n        Measured values.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.groups: Array (optional)\n        Array of group indicators.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.method: string\n        Name of test.\n\n    out.df: Object\n        Degrees of freedom.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    // Data from Hollander & Wolfe (1973), p. 116:\n    > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n    > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n    > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n    > var out = kruskalTest( x, y, z )\n\n    > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n    ...     3.8, 2.7, 4.0, 2.4,\n    ...     2.8, 3.4, 3.7, 2.2, 2.0\n    ... ];\n    > var groups = [\n    ...     'a', 'a', 'a', 'a', 'a',\n    ...     'b', 'b', 'b', 'b',\n    ...     'c', 'c', 'c', 'c', 'c'\n    ... ];\n    > out = kruskalTest( arr, { 'groups': groups } )\n\n","kstest":"\nkstest( x, y[, ...params][, options] )\n    Computes a Kolmogorov-Smirnov goodness-of-fit test.\n\n    For a numeric array or typed array `x`, a Kolmogorov-Smirnov goodness-of-fit\n    is computed for the null hypothesis that the values of `x` come from the\n    distribution specified by `y`. `y` can be either a string with the name of\n    the distribution to test against, or a function.\n\n    In the latter case, `y` is expected to be the cumulative distribution\n    function (CDF) of the distribution to test against, with its first parameter\n    being the value at which to evaluate the CDF and the remaining parameters\n    constituting the parameters of the distribution. The parameters of the\n    distribution are passed as additional arguments after `y` from `kstest` to\n    the chosen CDF. The function returns an object holding the calculated test\n    statistic `statistic` and the `pValue` of the test.\n\n    The returned object comes with a `.print()` method which when invoked will\n    print a formatted output of the hypothesis test results.\n\n    Parameters\n    ----------\n    x: Array<number>\n        Input array holding numeric values.\n\n    y: Function|string\n        Either a CDF function or a string denoting the name of a distribution.\n\n    params: ...number (optional)\n        Distribution parameters passed to reference CDF.\n\n    options: Object (optional)\n        Function options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.sorted: boolean (optional)\n        Boolean indicating if the input array is already in sorted order.\n        Default: `false`.\n\n    options.alternative: string (optional)\n        Either `two-sided`, `less` or `greater`. Indicates whether the\n        alternative hypothesis is that the true distribution of `x` is not equal\n        to the reference distribution specified by `y` (`two-sided`), whether it\n        is `less` than the reference distribution or `greater` than the\n        reference distribution. Default: `'two-sided'`.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Used significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.alternative: string\n        Used test alternative. Either `two-sided`, `less` or `greater`.\n\n    out.method: string\n        Name of test.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    // Verify that data is drawn from a normal distribution:\n    > var rnorm = base.random.normal.factory({ 'seed': 4839 } );\n    > var x = new Array( 100 );\n    > for ( var i = 0; i < 100; i++ ) { x[ i ] = rnorm( 3.0, 1.0 ); }\n\n    // Test against N(0,1)\n    > var out = kstest( x, 'normal', 0.0, 1.0 )\n    { pValue: 0.0, statistic: 0.847, ... }\n\n    // Test against N(3,1)\n    > out = kstest( x, 'normal', 3.0, 1.0 )\n    { pValue: 0.6282, statistic: 0.0733, ... }\n\n    // Verify that data is drawn from a uniform distribution:\n    > runif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } )\n    > x = new Array( 100 );\n    > for ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\n    > out = kstest( x, 'uniform', 0.0, 1.0 )\n    { pValue: ~0.703, statistic: ~0.069, ... }\n\n    // Print output:\n    > out.print()\n    Kolmogorov-Smirnov goodness-of-fit test.\n\n    Null hypothesis: the CDF of `x` is equal equal to the reference CDF.\n\n        pValue: 0.7039\n        statistic: 0.0689\n\n    Test Decision: Fail to reject null in favor of alternative at 5%\n    significance level\n\n    // Set custom significance level:\n    > out = kstest( x, 'uniform', 0.0, 1.0, { 'alpha': 0.1 } )\n    { pValue: ~0.7039, statistic: ~0.069, ... }\n\n    // Carry out one-sided hypothesis tests:\n    > runif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } );\n    > x = new Array( 100 );\n    > for ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\n    > out = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'less' } )\n    { pValue: ~0.358, statistic: ~0.07, ... }\n    > out = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'greater' } )\n    { pValue: ~0.907, statistic: ~0.02, ... }\n\n    // Set `sorted` option to true when data is in increasing order:\n    > x = [ 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 ];\n    > out = kstest( x, 'uniform', 0.0, 1.0, { 'sorted': true } )\n    { pValue: ~1, statistic: 0.1, ... }\n\n","last":"\nlast( str[, n][, options] )\n    Returns the last character(s) of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer (optional)\n        Number of characters to return. Default: 1.\n\n    options: Object (optional)\n        Options.\n\n    options.mode: string (optional)\n        Type of characters to return. The following modes are supported:\n\n        - grapheme: grapheme clusters. Appropriate for strings containing visual\n          characters which can span multiple Unicode code points (e.g., emoji).\n        - code_point: Unicode code points. Appropriate for strings containing\n          visual characters which are comprised of more than one Unicode code\n          unit (e.g., ideographic symbols and punctuation and mathematical\n          alphanumerics).\n        - code_unit': UTF-16 code units. Appropriate for strings containing\n          visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n          common characters, such as those from the Latin, Greek, and Cyrillic\n          alphabets).\n\n        Default: 'grapheme'.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = last( 'beep' )\n    'p'\n    > out = last( 'Boop', 2 )\n    'op'\n    > out = last( 'foo bar', 3 )\n    'bar'\n\n    See Also\n    --------\n    firstChar\n","leveneTest":"\nleveneTest( x[, ...y[, options]] )\n    Computes Levene's test for equal variances.\n\n    Parameters\n    ----------\n    x: Array<number>\n        Measured values.\n\n    y: ...Array<number> (optional)\n        Measured values.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.groups: Array (optional)\n        Array of group indicators.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.method: string\n        Name of test.\n\n    out.df: Array\n        Degrees of freedom.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    // Data from Hollander & Wolfe (1973), p. 116:\n    > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n    > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n    > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n    > var out = leveneTest( x, y, z )\n\n    > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n    ...     3.8, 2.7, 4.0, 2.4,\n    ...     2.8, 3.4, 3.7, 2.2, 2.0\n    ... ];\n    > var groups = [\n    ...     'a', 'a', 'a', 'a', 'a',\n    ...     'b', 'b', 'b', 'b',\n    ...     'c', 'c', 'c', 'c', 'c'\n    ... ];\n    > out = leveneTest( arr, { 'groups': groups } )\n\n    See Also\n    --------\n    vartest, bartlettTest\n","LinkedList":"\nLinkedList()\n    Linked list constructor.\n\n    Returns\n    -------\n    list: Object\n        Linked list.\n\n    list.clear: Function\n        Clears the list.\n\n    list.first: Function\n        Returns the last node. If the list is empty, the returned value is\n        `undefined`.\n\n    list.insert: Function\n        Inserts a value after a provided list node.\n\n    list.iterator: Function\n        Returns an iterator for iterating over a list. If an environment\n        supports Symbol.iterator, the returned iterator is iterable. Note that,\n        in order to prevent confusion arising from list mutation during\n        iteration, a returned iterator **always** iterates over a list\n        \"snapshot\", which is defined as the list of list elements at the time\n        of the method's invocation.\n\n    list.last: Function\n        Returns the last list node. If the list is empty, the returned value is\n        `undefined`.\n\n    list.length: integer\n        List length.\n\n    list.pop: Function\n        Removes and returns the last list value. If the list is empty, the\n        returned value is `undefined`.\n\n    list.push: Function\n        Adds a value to the end of the list.\n\n    list.remove: Function\n        Removes a list node from the list.\n\n    list.shift: Function\n        Removes and returns the first list value. If the list is empty, the\n        returned value is `undefined`.\n\n    list.toArray: Function\n        Returns an array of list values.\n\n    list.toJSON: Function\n        Serializes a list as JSON.\n\n    list.unshift: Function\n        Adds a value to the beginning of the list.\n\n    Examples\n    --------\n    > var list = LinkedList();\n    > list.push( 'foo' ).push( 'bar' );\n    > list.length\n    2\n    > list.pop()\n    'bar'\n    > list.length\n    1\n    > list.pop()\n    'foo'\n    > list.length\n    0\n\n    See Also\n    --------\n    DoublyLinkedList, Stack\n","linspace":"\nlinspace( start, stop, length[, options] )\n    Generates a linearly spaced array over a specified interval.\n\n    If the specified length is zero, the function returns an empty array.\n\n    If the specified length is one, the function returns an array containing\n    `stop`, but not `start`, when `endpoint` is true; otherwise, the function\n    returns an array containing `start`, but not `stop`.\n\n    For real-valued `start` and `stop`, if `start` is less than `stop`, the\n    output array will contain ascending values, and, if `start` is greater than\n    `stop`, the output array will contain descending values.\n\n    When the output array length is greater than one and `endpoint` is true, the\n    output array is guaranteed to include the `start` and `stop` values. Beware,\n    however, that values between `start` and `stop` are subject to floating-\n    point rounding errors.\n\n    If both `start` and `stop` are real-valued, the output array data type may\n    be any floating-point data type or 'generic'. However, if either `start` or\n    `stop` are complex numbers, the output array type must be a complex\n    floating-point data type or 'generic'.\n\n    When writing to a complex floating-point output array, real-valued `start`\n    and `stop` values are treated as complex numbers having a real component\n    equaling the provided value and having an imaginary component equaling zero.\n\n    When generating linearly spaced complex floating-point numbers, the real and\n    imaginary components are generated separately.\n\n    Parameters\n    ----------\n    start: number|ComplexLike\n        Start of interval.\n\n    stop: number|ComplexLike\n        End of interval.\n\n    length: integer\n        Length of output array.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Must be a floating-point data type or 'generic'.\n         If both `start` and `stop` are the same type (either 'float64',\n         'complex64', or 'complex128'), the default output array data type is\n         the same type as the input values (either 'float64', 'complex64', or\n         'complex128', respectively). Otherwise, the default output array data\n         type is 'complex128'.\n\n    options.endpoint: boolean (optional)\n        Boolean indicating whether to include the `stop` value in the output\n        array. If false, the function generates `length + 1` linearly spaced\n        values over the interval `[start, stop]` and only writes `length` values\n        to the output array, thus excluding `stop` from the output array.\n        Accordingly, for a fixed `length`, the spacing between adjacent values\n        in the output array changes depending on the value of `endpoint`.\n        Default: true.\n\n    Returns\n    -------\n    arr: Array\n        Linearly spaced array.\n\n    Examples\n    --------\n    > var arr = linspace( 0.0, 100.0, 6 )\n    <Float64Array>[ 0.0, 20.0, 40.0, 60.0, 80.0, 100.0 ]\n    > arr = linspace( 0.0, 100.0, 5, { 'endpoint': false } )\n    <Float64Array>[ 0.0, 20.0, 40.0, 60.0, 80.0 ]\n    > arr = linspace( 0.0, 100.0, 6, { 'dtype': 'generic' } )\n    [ 0.0, 20.0, 40.0, 60.0, 80.0, 100.0 ]\n\n\nlinspace.assign( start, stop, out[, options] )\n    Generates a linearly spaced sequence over a specified interval and assigns\n    the results to a provided output array.\n\n    If the provided output array is empty, the function returns the provided\n    output array unchanged.\n\n    If the provided output array contains a single element, the function writes\n    the `stop` value, but not `start`, when `endpoint` is true; otherwise, the\n    function writes the `start` value, but not `stop`.\n\n    Parameters\n    ----------\n    start: number|ComplexLike\n        Start of interval.\n\n    stop: number|ComplexLike\n        End of interval.\n\n    out: ArrayLikeObject\n        Output array.\n\n    options: Object (optional)\n        Options.\n\n    options.endpoint: boolean (optional)\n        Boolean indicating whether to include the `stop` value in the output\n        array. If false, the function generates `N+1` linearly spaced values\n        (where `N` is the length of the provided output array) over the interval\n        `[start, stop]` and only writes `N` values to the output array, thus\n        excluding `stop` from the output array. Accordingly, for a fixed `N`,\n        the spacing between adjacent values in the output array changes\n        depending on the value of `endpoint`. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var arr = [ 0, 0, 0, 0, 0, 0 ];\n    > var out = linspace.assign( 0, 100, arr )\n    [ 0, 20, 40, 60, 80, 100 ]\n    > var bool = ( arr === out )\n    true\n    > arr = [ 0, 0, 0, 0, 0 ];\n    > out = linspace.assign( 0, 100, arr, { 'endpoint': false } )\n    [ 0, 20, 40, 60, 80 ]\n\n    See Also\n    --------\n    incrspace, logspace\n","linspace.assign":"\nlinspace.assign( start, stop, out[, options] )\n    Generates a linearly spaced sequence over a specified interval and assigns\n    the results to a provided output array.\n\n    If the provided output array is empty, the function returns the provided\n    output array unchanged.\n\n    If the provided output array contains a single element, the function writes\n    the `stop` value, but not `start`, when `endpoint` is true; otherwise, the\n    function writes the `start` value, but not `stop`.\n\n    Parameters\n    ----------\n    start: number|ComplexLike\n        Start of interval.\n\n    stop: number|ComplexLike\n        End of interval.\n\n    out: ArrayLikeObject\n        Output array.\n\n    options: Object (optional)\n        Options.\n\n    options.endpoint: boolean (optional)\n        Boolean indicating whether to include the `stop` value in the output\n        array. If false, the function generates `N+1` linearly spaced values\n        (where `N` is the length of the provided output array) over the interval\n        `[start, stop]` and only writes `N` values to the output array, thus\n        excluding `stop` from the output array. Accordingly, for a fixed `N`,\n        the spacing between adjacent values in the output array changes\n        depending on the value of `endpoint`. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var arr = [ 0, 0, 0, 0, 0, 0 ];\n    > var out = linspace.assign( 0, 100, arr )\n    [ 0, 20, 40, 60, 80, 100 ]\n    > var bool = ( arr === out )\n    true\n    > arr = [ 0, 0, 0, 0, 0 ];\n    > out = linspace.assign( 0, 100, arr, { 'endpoint': false } )\n    [ 0, 20, 40, 60, 80 ]\n\n    See Also\n    --------\n    incrspace, logspace","LIU_NEGATIVE_OPINION_WORDS_EN":"\nLIU_NEGATIVE_OPINION_WORDS_EN()\n    Returns a list of negative opinion words.\n\n    A word's appearance in a sentence does *not* necessarily imply a positive or\n    negative opinion.\n\n    The list includes misspelled words. Their presence is intentional, as such\n    misspellings frequently occur in social media content.\n\n    Returns\n    -------\n    out: Array<string>\n        List of negative opinion words.\n\n    Examples\n    --------\n    > var list = LIU_NEGATIVE_OPINION_WORDS_EN()\n    [ '2-faced', '2-faces', 'abnormal', 'abolish', ... ]\n\n    References\n    ----------\n    - Hu, Minqing, and Bing Liu. 2004. \"Mining and Summarizing Customer\n    Reviews.\" In *Proceedings of the Tenth Acm Sigkdd International Conference\n    on Knowledge Discovery and Data Mining*, 168–77. KDD '04. New York, NY, USA:\n    ACM. doi:10.1145/1014052.1014073.\n    - Liu, Bing, Minqing Hu, and Junsheng Cheng. 2005. \"Opinion Observer:\n    Analyzing and Comparing Opinions on the Web.\" In *Proceedings of the 14th\n    International Conference on World Wide Web*, 342–51. WWW '05. New York, NY,\n    USA: ACM. doi:10.1145/1060745.1060797.\n\n    * If you use the list for publication or third party consumption, please\n    cite one of the listed references.\n\n    See Also\n    --------\n    LIU_POSITIVE_OPINION_WORDS_EN\n","LIU_POSITIVE_OPINION_WORDS_EN":"\nLIU_POSITIVE_OPINION_WORDS_EN()\n    Returns a list of positive opinion words.\n\n    A word's appearance in a sentence does *not* necessarily imply a positive or\n    negative opinion.\n\n    The list includes misspelled words. Their presence is intentional, as such\n    misspellings frequently occur in social media content.\n\n    Returns\n    -------\n    out: Array<string>\n        List of positive opinion words.\n\n    Examples\n    --------\n    > var list = LIU_POSITIVE_OPINION_WORDS_EN()\n    [ 'a+', 'abound', 'abounds', 'abundance', ... ]\n\n    References\n    ----------\n    - Hu, Minqing, and Bing Liu. 2004. 'Mining and Summarizing Customer\n    Reviews.' In *Proceedings of the Tenth Acm Sigkdd International Conference\n    on Knowledge Discovery and Data Mining*, 168–77. KDD '04. New York, NY, USA:\n    ACM. doi:10.1145/1014052.1014073.\n    - Liu, Bing, Minqing Hu, and Junsheng Cheng. 2005. 'Opinion Observer:\n    Analyzing and Comparing Opinions on the Web.' In *Proceedings of the 14th\n    International Conference on World Wide Web*, 342–51. WWW '05. New York, NY,\n    USA: ACM. doi:10.1145/1060745.1060797.\n\n    * If you use the list for publication or third party consumption, please\n    cite one of the listed references.\n\n    See Also\n    --------\n    LIU_NEGATIVE_OPINION_WORDS_EN\n","LN_HALF":"\nLN_HALF\n    Natural logarithm of `1/2`.\n\n    Examples\n    --------\n    > LN_HALF\n    -0.6931471805599453\n\n","LN_PI":"\nLN_PI\n    Natural logarithm of the mathematical constant `π`.\n\n    Examples\n    --------\n    > LN_PI\n    1.1447298858494002\n\n    See Also\n    --------\n    PI\n","LN_SQRT_TWO_PI":"\nLN_SQRT_TWO_PI\n    Natural logarithm of the square root of `2π`.\n\n    Examples\n    --------\n    > LN_SQRT_TWO_PI\n    0.9189385332046728\n\n    See Also\n    --------\n    PI\n","LN_TWO_PI":"\nLN_TWO_PI\n    Natural logarithm of `2π`.\n\n    Examples\n    --------\n    > LN_TWO_PI\n    1.8378770664093456\n\n    See Also\n    --------\n    TWO_PI\n","LN2":"\nLN2\n    Natural logarithm of `2`.\n\n    Examples\n    --------\n    > LN2\n    0.6931471805599453\n\n    See Also\n    --------\n    LN10\n","LN10":"\nLN10\n    Natural logarithm of `10`.\n\n    Examples\n    --------\n    > LN10\n    2.302585092994046\n\n    See Also\n    --------\n    LN2\n","LOG2E":"\nLOG2E\n    Base 2 logarithm of Euler's number.\n\n    Examples\n    --------\n    > LOG2E\n    1.4426950408889634\n\n    See Also\n    --------\n    E, LOG10E\n","LOG10E":"\nLOG10E\n    Base 10 logarithm of Euler's number.\n\n    Examples\n    --------\n    > LOG10E\n    0.4342944819032518\n\n    See Also\n    --------\n    E, LOG2E\n","logspace":"\nlogspace( a, b[, length] )\n    Generates a logarithmically spaced numeric array between `10^a` and `10^b`.\n\n    If a `length` is not provided, the default output array length is `10`.\n\n    The output array includes the values `10^a` and `10^b`.\n\n    Parameters\n    ----------\n    a: number\n        Exponent of start value.\n\n    b: number\n        Exponent of end value.\n\n    length: integer (optional)\n        Length of output array. Default: `10`.\n\n    Returns\n    -------\n    arr: Array\n        Logarithmically spaced numeric array.\n\n    Examples\n    --------\n    > var arr = logspace( 0, 2, 6 )\n    [ 1, ~2.5, ~6.31, ~15.85, ~39.81, 100 ]\n\n    See Also\n    --------\n    incrspace, linspace\n","lowercase":"\nlowercase( str )\n    Converts a string to lowercase.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Lowercase string.\n\n    Examples\n    --------\n    > var out = lowercase( 'bEEp' )\n    'beep'\n\n    See Also\n    --------\n    uncapitalize, uppercase\n","lowercaseKeys":"\nlowercaseKeys( obj )\n    Converts each object key to lowercase.\n\n    The function only transforms own properties. Hence, the function does not\n    transform inherited properties.\n\n    The function shallow copies key values.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > var obj = { 'A': 1, 'B': 2 };\n    > var out = lowercaseKeys( obj )\n    { 'a': 1, 'b': 2 }\n\n    See Also\n    --------\n    uncapitalizeKeys, uppercaseKeys\n","lowess":"\nlowess( x, y[, options] )\n    Locally-weighted polynomial regression via the LOWESS algorithm.\n\n    Parameters\n    ----------\n    x: Array<number>\n        x-axis values (abscissa values).\n\n    y: Array<number>\n        Corresponding y-axis values (ordinate values).\n\n    options: Object (optional)\n        Function options.\n\n    options.f: number (optional)\n        Positive number specifying the smoothing span, i.e., the proportion of\n        points which influence smoothing at each value. Larger values\n        correspond to more smoothing. Default: `2/3`.\n\n    options.nsteps: number (optional)\n        Number of iterations in the robust fit (fewer iterations translates to\n        faster function execution). If set to zero, the nonrobust fit is\n        returned. Default: `3`.\n\n    options.delta: number (optional)\n        Nonnegative number which may be used to reduce the number of\n        computations. Default: 1/100th of the range of `x`.\n\n    options.sorted: boolean (optional)\n        Boolean indicating if the input array `x` is sorted. Default: `false`.\n\n    Returns\n    -------\n    out: Object\n        Object with ordered x-values and fitted values.\n\n    Examples\n    --------\n    > var x = new Float64Array( 100 );\n    > var y = new Float64Array( x.length );\n    > for ( var i = 0; i < x.length; i++ ) {\n    ...     x[ i ] = i;\n    ...     y[ i ] = ( 0.5*i ) + ( 10.0*base.random.randn() );\n    ... }\n    > var out = lowess( x, y );\n    > var yhat = out.y;\n\n    > var h = Plot( [ x, x ], [ y, yhat ] );\n    > h.lineStyle = [ 'none', '-' ];\n    > h.symbols = [ 'closed-circle', 'none' ];\n\n    > h.view( 'window' );\n\n","lpad":"\nlpad( str, len[, pad] )\n    Left pads a string such that the padded string has a length of at least\n    `len`.\n\n    An output string is not guaranteed to have a length of exactly `len`, but to\n    have a length of at least `len`. To generate a padded string having a length\n    equal to `len`, post-process a padded string by trimming off excess\n    characters.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    len: integer\n        Minimum string length.\n\n    pad: string (optional)\n        String used to pad. Default: ' '.\n\n    Returns\n    -------\n    out: string\n        Padded string.\n\n    Examples\n    --------\n    > var out = lpad( 'a', 5 )\n    '    a'\n    > out = lpad( 'beep', 10, 'b' )\n    'bbbbbbbeep'\n    > out = lpad( 'boop', 12, 'beep' )\n    'beepbeepboop'\n\n    See Also\n    --------\n    pad, rpad\n","ltrim":"\nltrim( str )\n    Trims whitespace from the beginning of a string.\n\n    \"Whitespace\" is defined as the following characters:\n\n    - \\f\n    - \\n\n    - \\r\n    - \\t\n    - \\v\n    - \\u0020\n    - \\u00a0\n    - \\u1680\n    - \\u2000-\\u200a\n    - \\u2028\n    - \\u2029\n    - \\u202f\n    - \\u205f\n    - \\u3000\n    - \\ufeff\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Trimmed string.\n\n    Examples\n    --------\n    > var out = ltrim( ' \\r\\n\\t  Beep \\t\\t\\n  ' )\n    'Beep \\t\\t\\n  '\n\n    See Also\n    --------\n    trim, rtrim\n","ltrimN":"\nltrimN( str, n[, chars] )\n    Trims `n` characters from the beginning of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of characters to trim.\n\n    chars: Array<string>|string (optional)\n        Characters to trim. Default: whitespace characters.\n\n    Returns\n    -------\n    out: string\n        Trimmed string.\n\n    Examples\n    --------\n    > var out = ltrimN( '  abc  ', 2 )\n    'abc  '\n    > var out = ltrimN( '!!!abc!!!', 2, '!' )\n    '!abc!!!'\n\n    See Also\n    --------\n    rtrimN, trim","MALE_FIRST_NAMES_EN":"\nMALE_FIRST_NAMES_EN()\n    Returns a list of common male first names in English speaking countries.\n\n    Returns\n    -------\n    out: Array<string>\n        List of common male first names.\n\n    Examples\n    --------\n    > var list = MALE_FIRST_NAMES_EN()\n    [ 'Aaron', 'Ab', 'Abba', 'Abbe', ... ]\n\n    References\n    ----------\n    - Ward, Grady. 2002. 'Moby Word II.' <http://www.gutenberg.org/files/3201/\n    3201.txt>.\n\n    See Also\n    --------\n    FEMALE_FIRST_NAMES_EN\n","map":"\nmap( arr, fcn[, thisArg] )\n    Applies a function to each element in an array and assigns the result to an\n    element in a new array.\n\n    The applied function is provided the following arguments:\n\n    - value: array element.\n    - index: element index.\n    - arr: input array.\n\n    The returned output array always has a \"generic\" data type. For example, if\n    provided an array-like object, the function returns a generic array. If\n    provided an ndarray, the function returns an ndarray having a \"generic\" data\n    type.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject|ndarray\n        Input array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.abs, 1 );\n    > var arr = [ -1, -2, -3, -4, -5, -6 ];\n    > var out = map( arr, f )\n    [ 1, 2, 3, 4, 5, 6 ]\n\n    // ndarray:\n    > arr = array( arr, { 'shape': [ 2, 3 ] } );\n    > out = map( arr, f );\n    > var v = out.get( 1, 1 )\n    5\n\n\nmap.assign( arr, out, fcn[, thisArg] )\n    Applies a function to each element in an array and assigns the result to an\n    element in an output array.\n\n    The applied function is provided the following arguments:\n\n    - value: array element.\n    - index: element index.\n    - arr: input array.\n\n    Input and output arrays must be either both array-like objects or both\n    ndarray-like objects.\n\n    If input and output arrays are array-like objects, the arrays must have the\n    same number of elements.\n\n    If input and output arrays are both ndarray-like objects, the arrays *must*\n    be broadcast compatible.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject|ndarray\n        Input array.\n\n    out: ArrayLikeObject|ndarray\n        Output array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.abs, 1 );\n    > var arr = [ -1, -2, -3, -4, -5, -6 ];\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > map.assign( arr, out, f );\n    > out\n    [ 1, 2, 3, 4, 5, 6 ]\n\n    // ndarray:\n    > var opts = { 'shape': [ 2, 3 ] };\n    > arr = array( arr, opts );\n    > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n    > map.assign( arr, out, f );\n    > var v = out.get( 1, 1 )\n    5\n\n    See Also\n    --------\n    mapRight, reduce\n","map.assign":"\nmap.assign( arr, out, fcn[, thisArg] )\n    Applies a function to each element in an array and assigns the result to an\n    element in an output array.\n\n    The applied function is provided the following arguments:\n\n    - value: array element.\n    - index: element index.\n    - arr: input array.\n\n    Input and output arrays must be either both array-like objects or both\n    ndarray-like objects.\n\n    If input and output arrays are array-like objects, the arrays must have the\n    same number of elements.\n\n    If input and output arrays are both ndarray-like objects, the arrays *must*\n    be broadcast compatible.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject|ndarray\n        Input array.\n\n    out: ArrayLikeObject|ndarray\n        Output array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.abs, 1 );\n    > var arr = [ -1, -2, -3, -4, -5, -6 ];\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > map.assign( arr, out, f );\n    > out\n    [ 1, 2, 3, 4, 5, 6 ]\n\n    // ndarray:\n    > var opts = { 'shape': [ 2, 3 ] };\n    > arr = array( arr, opts );\n    > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n    > map.assign( arr, out, f );\n    > var v = out.get( 1, 1 )\n    5\n\n    See Also\n    --------\n    mapRight, reduce","map2":"\nmap2( x, y, fcn[, thisArg] )\n    Applies a function to elements in two input arrays and assigns the results\n    to a new array.\n\n    The applied function is provided the following arguments:\n\n    - v1: element from first input array.\n    - v2: element from second input array.\n    - idx: element index.\n    - arrays: input arrays.\n\n    The returned output array always has a \"generic\" data type. For example, if\n    provided an array-like object, the function returns a generic array. If\n    provided an ndarray, the function returns an ndarray having a \"generic\" data\n    type.\n\n    Input arrays must be either both array-like objects or both ndarray-like\n    objects.\n\n    If input arrays are array-like objects, the arrays must have the same number\n    of elements.\n\n    If input arrays are ndarray-like objects, the arrays must be broadcast\n    compatible.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject|ndarray\n        First input array.\n\n    y: ArrayLikeObject|ndarray\n        Second input array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.add, 2 );\n    > var x = [ 1, 2, 3, 4, 5, 6 ];\n    > var y = [ 1, 1, 1, 1, 1, 1 ];\n    > var out = map2( x, y, f )\n    [ 2, 3, 4, 5, 6, 7 ]\n\n    // ndarray:\n    > x = array( x, { 'shape': [ 2, 3 ] } );\n    > y = array( y, { 'shape': [ 2, 3 ] } );\n    > out = map2( x, y, f );\n    > var v = out.get( 1, 1 )\n    6\n\n\nmap2.assign( x, y, out, fcn[, thisArg] )\n    Applies a function to elements in two input arrays and assigns the results\n    to an output array.\n\n    The applied function is provided the following arguments:\n\n    - v1: element from first input array.\n    - v2: element from second input array.\n    - idx: element index.\n    - arrays: input arrays.\n\n    Input and output arrays must be either all array-like objects or all\n    ndarray-like objects.\n\n    If input and output arrays are array-like objects, the arrays must have the\n    same number of elements.\n\n    If input and output arrays are ndarray-like objects, the arrays must be\n    broadcast compatible.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject|ndarray\n        First input array.\n\n    y: ArrayLikeObject|ndarray\n        Second input array.\n\n    out: ArrayLikeObject|ndarray\n        Output array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.add, 2 );\n    > var x = [ 1, 2, 3, 4, 5, 6 ];\n    > var y = [ 1, 1, 1, 1, 1, 1 ];\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > map2.assign( x, y, out, f );\n    > out\n    [ 2, 3, 4, 5, 6, 7 ]\n\n    // ndarray:\n    > var opts = { 'shape': [ 2, 3 ] };\n    > x = array( x, opts );\n    > y = array( y, opts );\n    > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n    > map2.assign( x, y, out, f );\n    > var v = out.get( 1, 1 )\n    6\n\n    See Also\n    --------\n    map\n","map2.assign":"\nmap2.assign( x, y, out, fcn[, thisArg] )\n    Applies a function to elements in two input arrays and assigns the results\n    to an output array.\n\n    The applied function is provided the following arguments:\n\n    - v1: element from first input array.\n    - v2: element from second input array.\n    - idx: element index.\n    - arrays: input arrays.\n\n    Input and output arrays must be either all array-like objects or all\n    ndarray-like objects.\n\n    If input and output arrays are array-like objects, the arrays must have the\n    same number of elements.\n\n    If input and output arrays are ndarray-like objects, the arrays must be\n    broadcast compatible.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject|ndarray\n        First input array.\n\n    y: ArrayLikeObject|ndarray\n        Second input array.\n\n    out: ArrayLikeObject|ndarray\n        Output array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.add, 2 );\n    > var x = [ 1, 2, 3, 4, 5, 6 ];\n    > var y = [ 1, 1, 1, 1, 1, 1 ];\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > map2.assign( x, y, out, f );\n    > out\n    [ 2, 3, 4, 5, 6, 7 ]\n\n    // ndarray:\n    > var opts = { 'shape': [ 2, 3 ] };\n    > x = array( x, opts );\n    > y = array( y, opts );\n    > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n    > map2.assign( x, y, out, f );\n    > var v = out.get( 1, 1 )\n    6\n\n    See Also\n    --------\n    map","map2d":"\nmap2d( arr, fcn[, thisArg] )\n    Applies a function to each nested element in an array of arrays and assigns\n    the result to a nested element in a new array of arrays.\n\n    The applied function is provided the following arguments:\n\n    - value: array element.\n    - indices: current array element indices.\n    - arr: input array.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject<ArrayLikeObject>\n        Input array of arrays.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array<Array>\n        Array of arrays.\n\n    Examples\n    --------\n    > var f = naryFunction( base.abs, 1 );\n    > var arr = [ [ -1, -2, -3 ], [ -4, -5, -6 ] ];\n    > var out = map2d( arr, f );\n    > out[ 0 ]\n    [ 1, 2, 3 ]\n    > out[ 1 ]\n    [ 4, 5, 6 ]\n\n    See Also\n    --------\n    map, map3d, map4d, map5d, reduce2d\n","map2Right":"\nmap2Right( x, y, fcn[, thisArg] )\n    Applies a function to elements in two input arrays while iterating from\n    right to left and assigns the results to a new array.\n\n    The applied function is provided the following arguments:\n\n    - v1: element from first input array.\n    - v2: element from second input array.\n    - idx: element index.\n    - arrays: input arrays.\n\n    The returned output array always has a \"generic\" data type. For example, if\n    provided an array-like object, the function returns a generic array. If\n    provided an ndarray, the function returns an ndarray having a \"generic\" data\n    type.\n\n    Input arrays must be either both array-like objects or both ndarray-like\n    objects.\n\n    If input arrays are array-like objects, the arrays must have the same number\n    of elements.\n\n    If input arrays are ndarray-like objects, the arrays must be broadcast\n    compatible.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject|ndarray\n        First input array.\n\n    y: ArrayLikeObject|ndarray\n        Second input array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.add, 2 );\n    > var x = [ 1, 2, 3, 4, 5, 6 ];\n    > var y = [ 1, 1, 1, 1, 1, 1 ];\n    > var out = map2Right( x, y, f )\n    [ 2, 3, 4, 5, 6, 7 ]\n\n    // ndarray:\n    > x = array( x, { 'shape': [ 2, 3 ] } );\n    > y = array( y, { 'shape': [ 2, 3 ] } );\n    > out = map2Right( x, y, f );\n    > var v = out.get( 1, 1 )\n    6\n\n\nmap2Right.assign( x, y, out, fcn[, thisArg] )\n    Applies a function to elements in two input arrays while iterating from\n    right to left and assigns the results to an output array.\n\n    The applied function is provided the following arguments:\n\n    - v1: element from first input array.\n    - v2: element from second input array.\n    - idx: element index.\n    - arrays: input arrays.\n\n    Input and output arrays must be either all array-like objects or all\n    ndarray-like objects.\n\n    If input and output arrays are array-like objects, the arrays must have the\n    same number of elements.\n\n    If input and output arrays are ndarray-like objects, the arrays must be\n    broadcast compatible.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject|ndarray\n        First input array.\n\n    y: ArrayLikeObject|ndarray\n        Second input array.\n\n    out: ArrayLikeObject|ndarray\n        Output array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.add, 2 );\n    > var x = [ 1, 2, 3, 4, 5, 6 ];\n    > var y = [ 1, 1, 1, 1, 1, 1 ];\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > map2Right.assign( x, y, out, f );\n    > out\n    [ 2, 3, 4, 5, 6, 7 ]\n\n    // ndarray:\n    > var opts = { 'shape': [ 2, 3 ] };\n    > x = array( x, opts );\n    > y = array( y, opts );\n    > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n    > map2Right.assign( x, y, out, f );\n    > var v = out.get( 1, 1 )\n    6\n\n    See Also\n    --------\n    mapRight, map2\n","map2Right.assign":"\nmap2Right.assign( x, y, out, fcn[, thisArg] )\n    Applies a function to elements in two input arrays while iterating from\n    right to left and assigns the results to an output array.\n\n    The applied function is provided the following arguments:\n\n    - v1: element from first input array.\n    - v2: element from second input array.\n    - idx: element index.\n    - arrays: input arrays.\n\n    Input and output arrays must be either all array-like objects or all\n    ndarray-like objects.\n\n    If input and output arrays are array-like objects, the arrays must have the\n    same number of elements.\n\n    If input and output arrays are ndarray-like objects, the arrays must be\n    broadcast compatible.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject|ndarray\n        First input array.\n\n    y: ArrayLikeObject|ndarray\n        Second input array.\n\n    out: ArrayLikeObject|ndarray\n        Output array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.add, 2 );\n    > var x = [ 1, 2, 3, 4, 5, 6 ];\n    > var y = [ 1, 1, 1, 1, 1, 1 ];\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > map2Right.assign( x, y, out, f );\n    > out\n    [ 2, 3, 4, 5, 6, 7 ]\n\n    // ndarray:\n    > var opts = { 'shape': [ 2, 3 ] };\n    > x = array( x, opts );\n    > y = array( y, opts );\n    > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n    > map2Right.assign( x, y, out, f );\n    > var v = out.get( 1, 1 )\n    6\n\n    See Also\n    --------\n    mapRight, map2","map3d":"\nmap3d( arr, fcn[, thisArg] )\n    Applies a function to each nested element in a three-dimensional nested\n    array and assigns the result to a nested element in a new three-dimensional\n    nested array.\n\n    The applied function is provided the following arguments:\n\n    - value: array element.\n    - indices: current array element indices.\n    - arr: input array.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject<ArrayLikeObject<ArrayLikeObject>>\n        Input three-dimensional nested array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array<Array<Array>>\n        Three-dimensional nested array.\n\n    Examples\n    --------\n    > var f = naryFunction( base.abs, 1 );\n    > var arr = [ [ [ -1, -2, -3 ] ], [ [ -4, -5, -6 ] ] ];\n    > var out = map3d( arr, f );\n    > out[ 0 ][ 0 ]\n    [ 1, 2, 3 ]\n    > out[ 1 ][ 0 ]\n    [ 4, 5, 6 ]\n\n    See Also\n    --------\n    map, map2d, map4d, map5d\n","map4d":"\nmap4d( arr, fcn[, thisArg] )\n    Applies a function to each nested element in a four-dimensional nested array\n    and assigns the result to a nested element in a new four-dimensional nested\n    array.\n\n    The applied function is provided the following arguments:\n\n    - value: array element.\n    - indices: current array element indices.\n    - arr: input array.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject<ArrayLikeObject>\n        Input four-dimensional nested array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array<Array<Array<Array>>>\n        Four-dimensional nested array.\n\n    Examples\n    --------\n    > var f = naryFunction( base.abs, 1 );\n    > var arr = [ [ [ [ -1, -2, -3 ] ] ], [ [ [ -4, -5, -6 ] ] ] ];\n    > var out = map4d( arr, f );\n    > out[ 0 ][ 0 ][ 0 ]\n    [ 1, 2, 3 ]\n    > out[ 1 ][ 0 ][ 0 ]\n    [ 4, 5, 6 ]\n\n    See Also\n    --------\n    map, map2d, map3d, map5d\n","map5d":"\nmap5d( arr, fcn[, thisArg] )\n    Applies a function to each nested element in a five-dimensional nested array\n    and assigns the result to a nested element in a new five-dimensional nested\n    array.\n\n    The applied function is provided the following arguments:\n\n    - value: array element.\n    - indices: current array element indices.\n    - arr: input array.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject<ArrayLikeObject>\n        Input five-dimensional nested array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array<Array<Array<Array<Array>>>>\n        Five-dimensional nested array.\n\n    Examples\n    --------\n    > var f = naryFunction( base.abs, 1 );\n    > var arr = [ [ [ [ [ -1, -2, -3 ] ] ] ], [ [ [ [ -4, -5, -6 ] ] ] ] ];\n    > var out = map5d( arr, f );\n    > out[ 0 ][ 0 ][ 0 ][ 0 ]\n    [ 1, 2, 3 ]\n    > out[ 1 ][ 0 ][ 0 ][ 0 ]\n    [ 4, 5, 6 ]\n\n    See Also\n    --------\n    map, map2d, map3d, map4d\n","mapArguments":"\nmapArguments( fcn, clbk[, thisArg] )\n    Returns a function that applies arguments to a provided function after\n    transforming arguments according to a callback function.\n\n    The callback function is provided the following arguments:\n\n    - value: argument value.\n    - index: argument index.\n\n    Parameters\n    ----------\n    fcn: Function\n        Input function.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Function\n        Function wrapper.\n\n    Examples\n    --------\n    > function foo( a, b, c ) { return [ a, b, c ]; };\n    > function clbk( v ) { return v * 2; };\n    > var bar = mapArguments( foo, clbk );\n    > var out = bar( 1, 2, 3 )\n    [ 2, 4, 6 ]\n\n    See Also\n    --------\n    filterArguments\n","mapFun":"\nmapFun( fcn, n[, thisArg] )\n    Invokes a function `n` times and returns an array of accumulated function\n    return values.\n\n    The invoked function is provided a single argument: the invocation index\n    (zero-based).\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke.\n\n    n: integer\n        Number of times to invoke a function.\n\n    thisArg: any (optional)\n        Function execution context.\n\n    Returns\n    -------\n    out: Array\n        Array of accumulated function return values.\n\n    Examples\n    --------\n    > function fcn( i ) { return i; };\n    > var arr = mapFun( fcn, 5 )\n    [ 0, 1, 2, 3, 4 ]\n\n    See Also\n    --------\n    mapFunAsync\n","mapFunAsync":"\nmapFunAsync( fcn, n, [options,] done )\n    Invokes a function `n` times and returns an array of accumulated function\n    return values.\n\n    For each iteration, the provided function is invoked with two arguments:\n\n    - index: invocation index (starting from zero).\n    - next: callback to be invoked upon function completion.\n\n    The `next` callback accepts two arguments:\n\n    - error: error argument.\n    - result: function result.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke.\n\n    n: integer\n        Number of times to invoke a function.\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to allow only one pending invocation at a\n        time. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    done: Function\n        A callback invoked upon executing a provided function `n` times or upon\n        encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function fcn( i, next ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         next( null, i );\n    ...     }\n    ... };\n    > function done( error, arr ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( arr );\n    ... };\n    > mapFunAsync( fcn, 10, done )\n    [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n    // Limit number of concurrent invocations:\n    > function fcn( i, next ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         next( null, i );\n    ...     }\n    ... };\n    > function done( error, arr ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( arr );\n    ... };\n    > var opts = { 'limit': 2 };\n    > mapFunAsync( fcn, 10, opts, done )\n    [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n    // Sequential invocation:\n    > function fcn( i, next ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         next( null, i );\n    ...     }\n    ... };\n    > function done( error, arr ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( arr );\n    ... };\n    > var opts = { 'series': true };\n    > mapFunAsync( fcn, 10, opts, done )\n    [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n\nmapFunAsync.factory( [options,] fcn )\n    Returns a function which invokes a function `n` times and returns an array\n    of accumulated function return values.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to allow only one pending invocation at a\n        time. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        Function to invoke.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function `n` times and returns an array of\n        accumulated function return values.\n\n    Examples\n    --------\n    > function fcn( i, next ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         next( null, i );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = mapFunAsync.factory( opts, fcn );\n    > function done( error, arr ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( arr );\n    ... };\n    > f( 10, done )\n    [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n    See Also\n    --------\n    mapFun\n","mapFunAsync.factory":"\nmapFunAsync.factory( [options,] fcn )\n    Returns a function which invokes a function `n` times and returns an array\n    of accumulated function return values.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to allow only one pending invocation at a\n        time. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        Function to invoke.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function `n` times and returns an array of\n        accumulated function return values.\n\n    Examples\n    --------\n    > function fcn( i, next ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         next( null, i );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = mapFunAsync.factory( opts, fcn );\n    > function done( error, arr ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( arr );\n    ... };\n    > f( 10, done )\n    [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n    See Also\n    --------\n    mapFun","mapKeys":"\nmapKeys( obj, transform )\n    Maps keys from one object to a new object having the same values.\n\n    The transform function is provided three arguments:\n\n    - key: object key.\n    - value: object value corresponding to `key`.\n    - obj: the input object.\n\n    The value returned by a transform function should be a value which can be\n    serialized as an object key.\n\n    The function only maps own properties. Hence, the function does not map\n    inherited properties.\n\n    The function shallow copies key values.\n\n    Key iteration order is *not* guaranteed.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    transform: Function\n        Transform function. Return values specify the keys of the output object.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > function transform( key, value ) { return key + value; };\n    > var obj = { 'a': 1, 'b': 2 };\n    > var out = mapKeys( obj, transform )\n    { 'a1': 1, 'b2': 2 }\n\n    See Also\n    --------\n    mapValues\n","mapKeysAsync":"\nmapKeysAsync( obj, [options,] transform, done )\n    Maps keys from one object to a new object having the same values.\n\n    When invoked, `transform` is provided a maximum of four arguments:\n\n    - key: object key.\n    - value: object value corresponding to `key`.\n    - obj: the input object.\n    - next: a callback to be invoked after processing an object `key`.\n\n    The actual number of provided arguments depends on function length. If\n    `transform` accepts two arguments, `transform` is provided:\n\n    - key\n    - next\n\n    If `transform` accepts three arguments, `transform` is provided:\n\n    - key\n    - value\n    - next\n\n    For every other `transform` signature, `transform` is provided all four\n    arguments.\n\n    The `next` callback accepts two arguments:\n\n    - error: error argument.\n    - key: transformed key.\n\n    If a `transform` function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    The key returned by a transform function should be a value which can be\n    serialized as an object key.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function only maps own properties. Hence, the function does not map\n    inherited properties.\n\n    The function shallow copies key values.\n\n    Key iteration and insertion order are *not* guaranteed.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each property sequentially.\n        Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    transform: Function\n        Transform function. Returned values specify the keys of the output\n        object.\n\n    done: Function\n        A callback invoked either upon processing all own properties or upon\n        encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function transform( key, value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         next( null, key+':'+value );\n    ...     }\n    ... };\n    > function done( error, out ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( out );\n    ... };\n    > var obj = { 'a': 1, 'b': 2 };\n    > mapKeysAsync( obj, transform, done )\n    { 'a:1': 1, 'b:2': 2 }\n\n    // Limit number of concurrent invocations:\n    > function transform( key, value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         next( null, key+':'+value );\n    ...     }\n    ... };\n    > function done( error, out ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( out );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n    > mapKeysAsync( obj, opts, transform, done )\n    { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n\n    // Process sequentially:\n    > function transform( key, value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         next( null, key+':'+value );\n    ...     }\n    ... };\n    > function done( error, out ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( out );\n    ... };\n    > var opts = { 'series': true };\n    > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n    > mapKeysAsync( obj, opts, transform, done )\n    { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n\n\nmapKeysAsync.factory( [options,] transform )\n    Returns a function which maps keys from one object to a new object having\n    the same values.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each property sequentially.\n        Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    transform: Function\n        Transform function. Returned values specify the keys of the output\n        object.\n\n    Returns\n    -------\n    out: Function\n        A function which maps keys from one object to a new object having the\n        same values.\n\n    Examples\n    --------\n    > function transform( key, value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         next( null, key+':'+value );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = mapKeysAsync.factory( opts, transform );\n    > function done( error, out ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( out );\n    ... };\n    > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n    > f( obj, done )\n    { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n    > obj = { 'beep': 'boop' };\n    > f( obj, done )\n    { 'beep:boop': 'beep' }\n\n    See Also\n    --------\n    mapKeys, mapValuesAsync\n","mapKeysAsync.factory":"\nmapKeysAsync.factory( [options,] transform )\n    Returns a function which maps keys from one object to a new object having\n    the same values.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each property sequentially.\n        Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    transform: Function\n        Transform function. Returned values specify the keys of the output\n        object.\n\n    Returns\n    -------\n    out: Function\n        A function which maps keys from one object to a new object having the\n        same values.\n\n    Examples\n    --------\n    > function transform( key, value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         next( null, key+':'+value );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = mapKeysAsync.factory( opts, transform );\n    > function done( error, out ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( out );\n    ... };\n    > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n    > f( obj, done )\n    { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n    > obj = { 'beep': 'boop' };\n    > f( obj, done )\n    { 'beep:boop': 'beep' }\n\n    See Also\n    --------\n    mapKeys, mapValuesAsync","mapReduce":"\nmapReduce( arr, initial, mapper, reducer[, thisArg] )\n    Performs a map-reduce operation for each element in an array and returns the\n    accumulated result.\n\n    When invoked, the mapping function is provided three arguments:\n\n    - value: array element.\n    - index: element index.\n    - arr: input array.\n\n    When invoked, the reducing function is provided four arguments:\n\n    - accumulator: accumulated value.\n    - value: result after applying the mapping function to the current array\n      element.\n    - index: element index.\n    - arr: input array.\n\n    If provided an empty array, the function returns the initial value.\n\n    When provided an ndarray, the function performs a single-pass map-reduce\n    operation over the entire input ndarray (i.e., higher-order ndarray\n    dimensions are flattened to a single-dimension).\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject|ndarray\n        Input array.\n\n    initial: any\n        Accumulator value used in the first invocation of the reduction\n        function.\n\n    mapper: Function\n        Mapping function.\n\n    reducer: Function\n        Reducing function.\n\n    thisArg: any (optional)\n        Execution context for the reducing function.\n\n    Returns\n    -------\n    out: any\n        Accumulated result.\n\n    Examples\n    --------\n    // array-like object:\n    > var f1 = naryFunction( base.abs, 1 );\n    > var f2 = naryFunction( base.add, 2 );\n    > var arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\n    > var out = mapReduce( arr, 0.0, f1, f2 )\n    21.0\n\n    // ndarray:\n    > arr = array( arr, { 'shape': [ 2, 3 ] } );\n    > out = mapReduce( arr, 0.0, f1, f2 )\n    21.0\n\n    See Also\n    --------\n    map, mapReduceRight, reduce\n","mapReduceRight":"\nmapReduceRight( arr, initial, mapper, reducer[, thisArg] )\n    Performs a map-reduce operation for each element in an array while iterating\n    from right to left and returns the accumulated result.\n\n    When invoked, the mapping function is provided three arguments:\n\n    - value: array element.\n    - index: element index.\n    - arr: input array.\n\n    When invoked, the reducing function is provided four arguments:\n\n    - accumulator: accumulated value.\n    - value: result after applying the mapping function to the current array\n      element.\n    - index: element index.\n    - arr: input array.\n\n    If provided an empty array, the function returns the initial value.\n\n    When provided an ndarray, the function performs a single-pass map-reduce\n    operation over the entire input ndarray (i.e., higher-order ndarray\n    dimensions are flattened to a single-dimension).\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject|ndarray\n        Input array.\n\n    initial: any\n        Accumulator value used in the first invocation of the reduction\n        function.\n\n    mapper: Function\n        Mapping function.\n\n    reducer: Function\n        Reducing function.\n\n    thisArg: any (optional)\n        Execution context for the reducing function.\n\n    Returns\n    -------\n    out: any\n        Accumulated result.\n\n    Examples\n    --------\n    // array-like object:\n    > var f1 = naryFunction( base.abs, 1 );\n    > var f2 = naryFunction( base.add, 2 );\n    > var arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\n    > var out = mapReduceRight( arr, 0.0, f1, f2 )\n    21.0\n\n    // ndarray:\n    > arr = array( arr, { 'shape': [ 2, 3 ] } );\n    > out = mapReduceRight( arr, 0.0, f1, f2 )\n    21.0\n\n    See Also\n    --------\n    mapRight, mapReduce, reduceRight\n","mapRight":"\nmapRight( arr, fcn[, thisArg] )\n    Applies a function to each element in an array and assigns the result to an\n    element in a new array, iterating from right to left.\n\n    The applied function is provided the following arguments:\n\n    - value: array element.\n    - index: element index.\n    - arr: input array.\n\n    The returned output array always has a \"generic\" data type. For example, if\n    provided an array-like object, the function returns a generic array. If\n    provided an ndarray, the function returns an ndarray having a \"generic\" data\n    type.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject|ndarray\n        Input array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.abs, 1 );\n    > var arr = [ -1, -2, -3, -4, -5, -6 ];\n    > var out = mapRight( arr, f )\n    [ 1, 2, 3, 4, 5, 6 ]\n\n    // ndarray:\n    > arr = array( arr, { 'shape': [ 2, 3 ] } );\n    > out = mapRight( arr, f );\n    > var v = out.get( 1, 1 )\n    5\n\n\nmapRight.assign( arr, out, fcn[, thisArg] )\n    Applies a function to each element in an array and assigns the result to an\n    element in an output array, iterating from right to left.\n\n    The applied function is provided the following arguments:\n\n    - value: array element.\n    - index: element index.\n    - arr: input array.\n\n    Input and output arrays must be either both array-like objects or both\n    ndarray-like objects.\n\n    If input and output arrays are array-like objects, the arrays must have the\n    same number of elements.\n\n    If input and output arrays are both ndarray-like objects, the arrays *must*\n    be broadcast compatible.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject|ndarray\n        Input array.\n\n    out: ArrayLikeObject|ndarray\n        Output array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.abs, 1 );\n    > var arr = [ -1, -2, -3, -4, -5, -6 ];\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > mapRight.assign( arr, out, f );\n    > out\n    [ 1, 2, 3, 4, 5, 6 ]\n\n    // ndarray:\n    > var opts = { 'shape': [ 2, 3 ] };\n    > arr = array( arr, opts );\n    > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n    > mapRight.assign( arr, out, f );\n    > var v = out.get( 1, 1 )\n    5\n\n    See Also\n    --------\n    map, reduce\n","mapRight.assign":"\nmapRight.assign( arr, out, fcn[, thisArg] )\n    Applies a function to each element in an array and assigns the result to an\n    element in an output array, iterating from right to left.\n\n    The applied function is provided the following arguments:\n\n    - value: array element.\n    - index: element index.\n    - arr: input array.\n\n    Input and output arrays must be either both array-like objects or both\n    ndarray-like objects.\n\n    If input and output arrays are array-like objects, the arrays must have the\n    same number of elements.\n\n    If input and output arrays are both ndarray-like objects, the arrays *must*\n    be broadcast compatible.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject|ndarray\n        Input array.\n\n    out: ArrayLikeObject|ndarray\n        Output array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.abs, 1 );\n    > var arr = [ -1, -2, -3, -4, -5, -6 ];\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > mapRight.assign( arr, out, f );\n    > out\n    [ 1, 2, 3, 4, 5, 6 ]\n\n    // ndarray:\n    > var opts = { 'shape': [ 2, 3 ] };\n    > arr = array( arr, opts );\n    > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n    > mapRight.assign( arr, out, f );\n    > var v = out.get( 1, 1 )\n    5\n\n    See Also\n    --------\n    map, reduce","mapValues":"\nmapValues( obj, transform )\n    Maps values from one object to a new object having the same keys.\n\n    The transform function is provided three arguments:\n\n    - value: object value corresponding to `key`.\n    - key: object key.\n    - obj: the input object.\n\n    The function only maps values from own properties. Hence, the function does\n    not map inherited properties.\n\n    The function shallow copies key values.\n\n    Key iteration order is *not* guaranteed.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    transform: Function\n        Transform function. Return values are the key values of the output\n        object.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > function transform( value, key ) { return key + value; };\n    > var obj = { 'a': 1, 'b': 2 };\n    > var out = mapValues( obj, transform )\n    { 'a': 'a1', 'b': 'b2' }\n\n    See Also\n    --------\n    mapKeys, omitBy, pickBy\n","mapValuesAsync":"\nmapValuesAsync( obj, [options,] transform, done )\n    Maps values from one object to a new object having the same keys.\n\n    When invoked, `transform` is provided a maximum of four arguments:\n\n    - value: object value corresponding to `key`.\n    - key: object key.\n    - obj: the input object.\n    - next: a callback to be invoked after processing an object `value`.\n\n    The actual number of provided arguments depends on function length. If\n    `transform` accepts two arguments, `transform` is provided:\n\n    - value\n    - next\n\n    If `transform` accepts three arguments, `transform` is provided:\n\n    - value\n    - key\n    - next\n\n    For every other `transform` signature, `transform` is provided all four\n    arguments.\n\n    The `next` callback accepts two arguments:\n\n    - error: error argument.\n    - value: transformed value.\n\n    If a `transform` function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function only maps values from own properties. Hence, the function does\n    not map inherited properties.\n\n    The function shallow copies key values.\n\n    Key iteration and insertion order are *not* guaranteed.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each property sequentially.\n        Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    transform: Function\n        Transform function. Return values are the key values of the output\n        object.\n\n    done: Function\n        A callback invoked either upon processing all own properties or upon\n        encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function transform( value, key, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         next( null, key+':'+value );\n    ...     }\n    ... };\n    > function done( error, out ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( out );\n    ... };\n    > var obj = { 'a': 1, 'b': 2 };\n    > mapValuesAsync( obj, transform, done )\n    { 'a': 'a:1', 'b': 'b:2' }\n\n    // Limit number of concurrent invocations:\n    > function transform( value, key, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         next( null, key+':'+value );\n    ...     }\n    ... };\n    > function done( error, out ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( out );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n    > mapValuesAsync( obj, opts, transform, done )\n    { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n\n    // Process sequentially:\n    > function transform( value, key, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         next( null, key+':'+value );\n    ...     }\n    ... };\n    > function done( error, out ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( out );\n    ... };\n    > var opts = { 'series': true };\n    > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n    > mapValuesAsync( obj, opts, transform, done )\n    { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n\n\nmapValuesAsync.factory( [options,] transform )\n    Returns a function which maps values from one object to a new object having\n    the same keys.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each property sequentially.\n        Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    transform: Function\n        Transform function. Return values are the key values of the output\n        object.\n\n    Returns\n    -------\n    out: Function\n        A function which maps values from one object to a new object having the\n        same keys.\n\n    Examples\n    --------\n    > function transform( value, key, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         next( null, key+':'+value );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = mapValuesAsync.factory( opts, transform );\n    > function done( error, out ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( out );\n    ... };\n    > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n    > f( obj, done )\n    { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n    > obj = { 'beep': 'boop' };\n    > f( obj, done )\n    { 'beep': 'beep:boop' }\n\n    See Also\n    --------\n    mapKeysAsync, mapValues\n","mapValuesAsync.factory":"\nmapValuesAsync.factory( [options,] transform )\n    Returns a function which maps values from one object to a new object having\n    the same keys.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each property sequentially.\n        Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    transform: Function\n        Transform function. Return values are the key values of the output\n        object.\n\n    Returns\n    -------\n    out: Function\n        A function which maps values from one object to a new object having the\n        same keys.\n\n    Examples\n    --------\n    > function transform( value, key, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         next( null, key+':'+value );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = mapValuesAsync.factory( opts, transform );\n    > function done( error, out ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( out );\n    ... };\n    > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n    > f( obj, done )\n    { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n    > obj = { 'beep': 'boop' };\n    > f( obj, done )\n    { 'beep': 'beep:boop' }\n\n    See Also\n    --------\n    mapKeysAsync, mapValues","maskArguments":"\nmaskArguments( fcn, mask[, thisArg] )\n    Returns a function that applies arguments to a provided function according\n    to a specified mask.\n\n    Only those arguments having a truthy mask value are applied to a provided\n    function.\n\n    Parameters\n    ----------\n    fcn: Function\n        Input function.\n\n    mask: ArrayLikeObject\n        Mask array.\n\n    thisArg: any (optional)\n        Function context.\n\n    Returns\n    -------\n    out: Function\n        Function wrapper.\n\n    Examples\n    --------\n    > function foo( a, b ) { return [ a, b ]; };\n    > var bar = maskArguments( foo, [ 1, 0, 1 ] );\n    > var out = bar( 1, 2, 3 )\n    [ 1, 3 ]\n\n    See Also\n    --------\n    filterArguments, rejectArguments, reorderArguments, reverseArguments\n","MAX_ARRAY_LENGTH":"\nMAX_ARRAY_LENGTH\n    Maximum length for a generic array.\n\n    Examples\n    --------\n    > MAX_ARRAY_LENGTH\n    4294967295\n\n    See Also\n    --------\n    MAX_TYPED_ARRAY_LENGTH\n","MAX_TYPED_ARRAY_LENGTH":"\nMAX_TYPED_ARRAY_LENGTH\n    Maximum length for a typed array.\n\n    Examples\n    --------\n    > MAX_TYPED_ARRAY_LENGTH\n    9007199254740991\n\n    See Also\n    --------\n    MAX_ARRAY_LENGTH\n","maybeBroadcastArray":"\nmaybeBroadcastArray( x, shape )\n    Broadcasts an ndarray to a specified shape if and only if the specified\n    shape differs from the provided ndarray's shape.\n\n    If a provided ndarray has the same shape as the specified shape, the\n    function returns the provided ndarray.\n\n    If a provided ndarray has a different (broadcast compatible) shape than the\n    specified shape, the function returns a new *read-only* ndarray view of the\n    provided ndarray's data. The view is typically *not* contiguous. As more\n    than one element of a returned view may refer to the same memory location,\n    writing to the input ndarray may affect multiple elements. If you need to\n    write to the input ndarray, copy the input ndarray before broadcasting.\n\n    The function throws an error if a provided ndarray is incompatible with a\n    provided shape.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    shape: ArrayLikeObject\n        Desired shape.\n\n    Returns\n    -------\n    out: ndarray\n        Broadcasted array.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n    <ndarray>\n    > var sh = x.shape\n    [ 2, 2 ]\n    > var y = maybeBroadcastArray( x, [ 3, 2, 2 ] )\n    <ndarray>\n    > sh = y.shape\n    [ 3, 2, 2 ]\n    > var v = y.get( 0, 0, 0 )\n    1\n    > v = y.get( 0, 0, 1 )\n    2\n    > v = y.get( 0, 1, 0 )\n    3\n    > v = y.get( 0, 1, 1 )\n    4\n    > v = y.get( 1, 0, 0 )\n    1\n    > v = y.get( 1, 1, 0 )\n    3\n    > v = y.get( 2, 0, 0 )\n    1\n    > v = y.get( 2, 1, 1 )\n    4\n\n    See Also\n    --------\n    array, ndarray, broadcastArray, maybeBroadcastArrays\n","maybeBroadcastArrays":"\nmaybeBroadcastArrays( ...arrays )\n    Broadcasts ndarrays to a common shape.\n\n    The function supports two (mutually exclusive) means of providing ndarray\n    arguments:\n\n    1. Providing a single array containing ndarray arguments.\n    2. Providing ndarray arguments as separate arguments.\n\n    If a provided ndarray has a shape matching the common shape, the function\n    returns the provided ndarray.\n\n    If a provided ndarray has a different (broadcast compatible) shape than the\n    common shape, the function returns a new *read-only* ndarray view of the\n    provided ndarray's data. The view is typically *not* contiguous. As more\n    than one element of a returned view may refer to the same memory location,\n    writing to a view may affect multiple elements. If you need to write to an\n    input ndarray, copy the input ndarray before broadcasting.\n\n    The function throws an error if a provided broadcast-incompatible ndarrays.\n\n    Parameters\n    ----------\n    arrays: ...ndarray|ArrayLikeObject<ndarray>\n        Array arguments.\n\n    Returns\n    -------\n    out: Array<ndarray>\n        Broadcasted arrays.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n    <ndarray>\n    > var sh = x.shape\n    [ 2, 2 ]\n    > var y = ndzeros( [ 3, 2, 2 ] )\n    <ndarray>\n    > var out = maybeBroadcastArrays( [ x, y ] )\n    [ <ndarray>, <ndarray> ]\n\n    // Retrieve the broadcasted \"x\" array:\n    > var bx = out[ 0 ]\n    <ndarray>\n    > sh = bx.shape\n    [ 3, 2, 2 ]\n\n    // Retrieve broadcasted elements...\n    > var v = bx.get( 0, 0, 0 )\n    1\n    > v = bx.get( 0, 0, 1 )\n    2\n    > v = bx.get( 0, 1, 0 )\n    3\n    > v = bx.get( 0, 1, 1 )\n    4\n    > v = bx.get( 1, 0, 0 )\n    1\n    > v = bx.get( 1, 1, 0 )\n    3\n    > v = bx.get( 2, 0, 0 )\n    1\n    > v = bx.get( 2, 1, 1 )\n    4\n\n    See Also\n    --------\n    array, ndarray, broadcastArrays, maybeBroadcastArray\n","memoize":"\nmemoize( fcn[, hashFunction] )\n    Returns a memoized function.\n\n    The function does not set the `length` property of the returned function.\n    Accordingly, the returned function `length` is always zero.\n\n    The evaluation context is always `null`.\n\n    The function serializes provided arguments as a string and stores results\n    using the string as an identifier. To use a custom hash function, provide a\n    hash function argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to memoize.\n\n    hashFunction: Function (optional)\n        Function to map a set of arguments to a single value identifying that\n        set.\n\n    Returns\n    -------\n    out: Function\n        Memoized function.\n\n    Examples\n    --------\n    > function factorial( n ) {\n    ...     var prod;\n    ...     var i;\n    ...     prod = 1;\n    ...     for ( i = n; i > 1; i-- ) {\n    ...         prod *= i;\n    ...     }\n    ...     return prod;\n    ... };\n    > var memoized = memoize( factorial );\n    > var v = memoized( 5 )\n    120\n    > v = memoized( 5 )\n    120\n\n","merge":"\nmerge( target, ...source )\n    Merges objects into a target object.\n\n    The target object is mutated.\n\n    Only plain objects are merged and extended. Other values/types are either\n    deep copied or assigned.\n\n    Support for deep merging class instances is inherently fragile.\n\n    `Number`, `String`, and `Boolean` objects are merged as primitives.\n\n    Functions are not deep copied.\n\n    Parameters\n    ----------\n    target: Object\n        Target object.\n\n    source: ...Object\n        Source objects (i.e., objects to be merged into the target object).\n\n    Returns\n    -------\n    out: Object\n        Merged (target) object.\n\n    Examples\n    --------\n    > var target = { 'a': 'beep' };\n    > var source = { 'a': 'boop', 'b': 'bap' };\n    > var out = merge( target, source )\n    { 'a': 'boop', 'b': 'bap' }\n    > var bool = ( out === target )\n    true\n\n\nmerge.factory( options )\n    Returns a function for merging and extending objects.\n\n    Parameters\n    ----------\n    options: Object\n        Options.\n\n    options.level: integer (optional)\n        Merge level. Default: Infinity.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to deep copy merged values. Deep copying\n        prevents shared references and source object mutation. Default: true.\n\n    options.override: boolean|Function (optional)\n        Defines the merge strategy. If `true`, source object values will always\n        override target object values. If `false`, source values never override\n        target values (useful for adding, but not overwriting, properties). To\n        define a custom merge strategy, provide a function. Default: true.\n\n    options.extend: boolean (optional)\n        Boolean indicating whether new properties can be added to the target\n        object. If `false`, only shared properties are merged. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function which can be used to merge objects.\n\n    Examples\n    --------\n    > var opts = {\n    ...     'level': 100,\n    ...     'copy': true,\n    ...     'override': true,\n    ...     'extend': true\n    ... };\n    > var merge = merge.factory( opts )\n    <Function>\n\n    // Set the `level` option to limit the merge depth:\n    > merge = merge.factory( { 'level': 2 } );\n    > var target = {\n    ...     '1': { 'a': 'beep', '2': { '3': null, 'b': [ 5, 6, 7 ] } }\n    ... };\n    > var source = {\n    ...     '1': { 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } }\n    ... };\n    > var out = merge( target, source )\n    { '1': { 'a': 'beep', 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } } }\n\n    // Set the `copy` option to `false` to allow shared references:\n    > merge = merge.factory( { 'copy': false } );\n    > target = {};\n    > source = { 'a': [ 1, 2, 3 ] };\n    > out = merge( target, source );\n    > var bool = ( out.a === source.a )\n    true\n\n    // Set the `override` option to `false` to preserve existing properties:\n    > merge = merge.factory( { 'override': false } );\n    > target = { 'a': 'beep', 'b': 'boop' };\n    > source = { 'a': null, 'c': 'bop' };\n    > out = merge( target, source )\n    { 'a': 'beep', 'b': 'boop', 'c': 'bop' }\n\n    // Define a custom merge strategy:\n    > function strategy( a, b, key ) {\n    ...     // a => target value\n    ...     // b => source value\n    ...     // key => object key\n    ...     if ( key === 'a' ) {\n    ...         return b;\n    ...     }\n    ...     if ( key === 'b' ) {\n    ...         return a;\n    ...     }\n    ...     return 'bebop';\n    ... };\n    > merge = merge.factory( { 'override': strategy } );\n    > target = { 'a': 'beep', 'b': 'boop', 'c': 1234 };\n    > source = { 'a': null, 'b': {}, 'c': 'bop' };\n    > out = merge( target, source )\n    { 'a': null, 'b': 'boop', 'c': 'bebop' }\n\n    // Prevent non-existent properties from being added to the target object:\n    > merge = merge.factory( { 'extend': false } );\n    > target = { 'a': 'beep', 'b': 'boop' };\n    > source = { 'b': 'hello', 'c': 'world' };\n    > out = merge( target, source )\n    { 'a': 'beep', 'b': 'hello' }\n\n    See Also\n    --------\n    copy\n","merge.factory":"\nmerge.factory( options )\n    Returns a function for merging and extending objects.\n\n    Parameters\n    ----------\n    options: Object\n        Options.\n\n    options.level: integer (optional)\n        Merge level. Default: Infinity.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to deep copy merged values. Deep copying\n        prevents shared references and source object mutation. Default: true.\n\n    options.override: boolean|Function (optional)\n        Defines the merge strategy. If `true`, source object values will always\n        override target object values. If `false`, source values never override\n        target values (useful for adding, but not overwriting, properties). To\n        define a custom merge strategy, provide a function. Default: true.\n\n    options.extend: boolean (optional)\n        Boolean indicating whether new properties can be added to the target\n        object. If `false`, only shared properties are merged. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function which can be used to merge objects.\n\n    Examples\n    --------\n    > var opts = {\n    ...     'level': 100,\n    ...     'copy': true,\n    ...     'override': true,\n    ...     'extend': true\n    ... };\n    > var merge = merge.factory( opts )\n    <Function>\n\n    // Set the `level` option to limit the merge depth:\n    > merge = merge.factory( { 'level': 2 } );\n    > var target = {\n    ...     '1': { 'a': 'beep', '2': { '3': null, 'b': [ 5, 6, 7 ] } }\n    ... };\n    > var source = {\n    ...     '1': { 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } }\n    ... };\n    > var out = merge( target, source )\n    { '1': { 'a': 'beep', 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } } }\n\n    // Set the `copy` option to `false` to allow shared references:\n    > merge = merge.factory( { 'copy': false } );\n    > target = {};\n    > source = { 'a': [ 1, 2, 3 ] };\n    > out = merge( target, source );\n    > var bool = ( out.a === source.a )\n    true\n\n    // Set the `override` option to `false` to preserve existing properties:\n    > merge = merge.factory( { 'override': false } );\n    > target = { 'a': 'beep', 'b': 'boop' };\n    > source = { 'a': null, 'c': 'bop' };\n    > out = merge( target, source )\n    { 'a': 'beep', 'b': 'boop', 'c': 'bop' }\n\n    // Define a custom merge strategy:\n    > function strategy( a, b, key ) {\n    ...     // a => target value\n    ...     // b => source value\n    ...     // key => object key\n    ...     if ( key === 'a' ) {\n    ...         return b;\n    ...     }\n    ...     if ( key === 'b' ) {\n    ...         return a;\n    ...     }\n    ...     return 'bebop';\n    ... };\n    > merge = merge.factory( { 'override': strategy } );\n    > target = { 'a': 'beep', 'b': 'boop', 'c': 1234 };\n    > source = { 'a': null, 'b': {}, 'c': 'bop' };\n    > out = merge( target, source )\n    { 'a': null, 'b': 'boop', 'c': 'bebop' }\n\n    // Prevent non-existent properties from being added to the target object:\n    > merge = merge.factory( { 'extend': false } );\n    > target = { 'a': 'beep', 'b': 'boop' };\n    > source = { 'b': 'hello', 'c': 'world' };\n    > out = merge( target, source )\n    { 'a': 'beep', 'b': 'hello' }\n\n    See Also\n    --------\n    copy","MILLISECONDS_IN_DAY":"\nMILLISECONDS_IN_DAY\n    Number of milliseconds in a day.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var days = 3.14;\n    > var ms = days * MILLISECONDS_IN_DAY\n    271296000\n\n","MILLISECONDS_IN_HOUR":"\nMILLISECONDS_IN_HOUR\n    Number of milliseconds in an hour.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var hrs = 3.14;\n    > var ms = hrs * MILLISECONDS_IN_HOUR\n    11304000\n\n","MILLISECONDS_IN_MINUTE":"\nMILLISECONDS_IN_MINUTE\n    Number of milliseconds in a minute.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies arising due to complications with time and dates.\n\n    Examples\n    --------\n    > var mins = 3.14;\n    > var ms = mins * MILLISECONDS_IN_MINUTE\n    188400\n\n","MILLISECONDS_IN_SECOND":"\nMILLISECONDS_IN_SECOND\n    Number of milliseconds in a second.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies arising due to complications with time and dates.\n\n    Examples\n    --------\n    > var secs = 3.14;\n    > var ms = secs * MILLISECONDS_IN_SECOND\n    3140\n\n","MILLISECONDS_IN_WEEK":"\nMILLISECONDS_IN_WEEK\n    Number of milliseconds in a week.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var weeks = 3.14;\n    > var ms = weeks * MILLISECONDS_IN_WEEK\n    1899072000\n\n","MINARD_NAPOLEONS_MARCH":"\nMINARD_NAPOLEONS_MARCH( [options] )\n    Returns data for Charles Joseph Minard's cartographic depiction of\n    Napoleon's Russian campaign of 1812.\n\n    Data includes the following:\n\n    - army: army size.\n    - cities: cities.\n    - labels: map labels.\n    - temperature: temperature during the army's return from Russia.\n    - rivers: river data.\n\n    Temperatures are on the Réaumur scale. Multiply each temperature by `1.25`\n    to convert to Celsius.\n\n    River data is formatted as GeoJSON.\n\n    River data is incomplete, with portions of rivers missing.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.data: string (optional)\n        Dataset name.\n\n    Returns\n    -------\n    out: Object|Array<Object>\n        Minard's data.\n\n    Examples\n    --------\n    > var data = MINARD_NAPOLEONS_MARCH();\n    > var army = data.army\n    [...]\n    > var cities = data.cities\n    [...]\n    > var labels = data.labels\n    [...]\n    > var river = data.river\n    {...}\n    > var t = data.temperature\n    [...]\n\n    References\n    ----------\n    - Minard, Charles Joseph. 1869. *Tableaux graphiques et cartes figuratives*.\n    Ecole nationale des ponts et chaussées.\n    - Wilkinson, Leland. 2005. *The Grammar of Graphics*. Springer-Verlag New\n    York. doi:10.1007/0-387-28695-0.\n\n","MINUTES_IN_DAY":"\nMINUTES_IN_DAY\n    Number of minutes in a day.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var days = 3.14;\n    > var mins = days * MINUTES_IN_DAY\n    4521.6\n\n","MINUTES_IN_HOUR":"\nMINUTES_IN_HOUR\n    Number of minutes in an hour.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var hrs = 3.14;\n    > var mins = hrs * MINUTES_IN_HOUR\n    188.4\n\n","MINUTES_IN_WEEK":"\nMINUTES_IN_WEEK\n    Number of minutes in a week.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var wks = 3.14;\n    > var mins = wks * MINUTES_IN_WEEK\n    31651.2\n\n","minutesInMonth":"\nminutesInMonth( [month[, year]] )\n    Returns the number of minutes in a month.\n\n    By default, the function returns the number of minutes in the current month\n    of the current year (according to local time). To determine the number of\n    minutes for a particular month and year, provide `month` and `year`\n    arguments.\n\n    A `month` may be either a month's integer value, three letter abbreviation,\n    or full name (case insensitive).\n\n    The function's return value is a generalization and does **not** take into\n    account inaccuracies due to daylight savings conventions, crossing\n    timezones, or other complications with time and dates.\n\n    Parameters\n    ----------\n    month: string|Date|integer (optional)\n        Month.\n\n    year: integer (optional)\n        Year.\n\n    Returns\n    -------\n    out: integer\n        Minutes in a month.\n\n    Examples\n    --------\n    > var num = minutesInMonth()\n    <number>\n    > num = minutesInMonth( 2 )\n    <number>\n    > num = minutesInMonth( 2, 2016 )\n    41760\n    > num = minutesInMonth( 2, 2017 )\n    40320\n\n    // Other ways to supply month:\n    > num = minutesInMonth( 'feb', 2016 )\n    41760\n    > num = minutesInMonth( 'february', 2016 )\n    41760\n\n    See Also\n    --------\n    minutesInYear\n","minutesInYear":"\nminutesInYear( [value] )\n    Returns the number of minutes in a year according to the Gregorian calendar.\n\n    By default, the function returns the number of minutes in the current year\n    (according to local time). To determine the number of minutes for a\n    particular year, provide either a year or a `Date` object.\n\n    The function's return value is a generalization and does **not** take into\n    account inaccuracies due to daylight savings conventions, crossing\n    timezones, or other complications with time and dates.\n\n    Parameters\n    ----------\n    value: integer|Date (optional)\n        Year or `Date` object.\n\n    Returns\n    -------\n    out: integer\n        Number of minutes in a year.\n\n    Examples\n    --------\n    > var num = minutesInYear()\n    <number>\n    > num = minutesInYear( 2016 )\n    527040\n    > num = minutesInYear( 2017 )\n    525600\n\n    See Also\n    --------\n    minutesInMonth\n","MOBY_DICK":"\nMOBY_DICK()\n    Returns the text of Moby Dick by Herman Melville.\n\n    Each array element has the following fields:\n\n    - chapter: book chapter (number or identifier).\n    - title: chapter title (if available; otherwise, empty).\n    - text: chapter text.\n\n    Returns\n    -------\n    out: Array<Object>\n        Book text.\n\n    Examples\n    --------\n    > var data = MOBY_DICK()\n    [ {...}, {...}, ... ]\n\n","MONTH_NAMES_EN":"\nMONTH_NAMES_EN()\n    Returns a list of month names (English).\n\n    Returns\n    -------\n    out: Array<string>\n        List of month names.\n\n    Examples\n    --------\n    > var list = MONTH_NAMES_EN()\n    [ 'January', 'February', 'March', 'April', ... ]\n\n","MONTHS_IN_YEAR":"\nMONTHS_IN_YEAR\n    Number of months in a year.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var yrs = 3.14;\n    > var mons = yrs * MONTHS_IN_YEAR\n    37.68\n\n","moveProperty":"\nmoveProperty( source, prop, target )\n    Moves a property from one object to another object.\n\n    The property is deleted from the source object and the property's descriptor\n    is preserved during transfer.\n\n    If a source property is not configurable, the function throws an error, as\n    the property cannot be deleted from the source object.\n\n    Parameters\n    ----------\n    source: Object\n        Source object.\n\n    prop: string\n        Property to move.\n\n    target: Object\n        Target object.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether operation was successful.\n\n    Examples\n    --------\n    > var obj1 = { 'a': 'b' };\n    > var obj2 = {};\n    > var bool = moveProperty( obj1, 'a', obj2 )\n    true\n    > bool = moveProperty( obj1, 'c', obj2 )\n    false\n\n","MultiSlice":"\nMultiSlice( ...slice )\n    Returns a multi-slice.\n\n    Parameters\n    ----------\n    ...slice: Slice|integer|null|undefined\n        Slice arguments.\n\n    Returns\n    -------\n    s: MultiSlice\n        MultiSlice instance.\n\n    Examples\n    --------\n    > var s = new Slice( 2, 10 );\n    > var ms = new MultiSlice( 2, s, 1 );\n\n\nMultiSlice.prototype.ndims\n    Read-only property returning the number of slice dimensions.\n\n    Returns\n    -------\n    ndims: integer\n        Number of slice dimensions.\n\n    Examples\n    --------\n    > var s = new Slice( 2, 10 );\n    > var ms = new MultiSlice( 2, s, 1 );\n    > ms.ndims\n    3\n\n\nMultiSlice.prototype.data\n    Read-only property returning the slice data.\n\n    Returns\n    -------\n    data: Array<Slice|integer|null>\n        Slice data.\n\n    Examples\n    --------\n    > var s = new Slice( 2, 10 );\n    > var ms = new MultiSlice( 2, s, 1 );\n    > ms.data\n    [ 2, <Slice>, 1 ]\n\n\nMultiSlice.prototype.toString()\n    Serializes a multi-slice as a string.\n\n    Returns\n    -------\n    str: string\n        Serialized multi-slice string.\n\n    Examples\n    --------\n    > var s = new Slice( 2, 10 );\n    > var ms = new MultiSlice( 2, s, 1 );\n    > ms.toString()\n    'MultiSlice(2,Slice(2,10,null),1)'\n\n\nMultiSlice.prototype.toJSON()\n    Serializes a multi-slice as a JSON object.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var s = new Slice( 2, 10, 1 );\n    > var ms = new MultiSlice( 2, s );\n    > ms.toJSON()\n    {'type':'MultiSlice','data':[2,{'type':'Slice','data':[2,10,1]}]}\n\n    See Also\n    --------\n    ndarray, Slice\n","MultiSlice.prototype.ndims":"\nMultiSlice.prototype.ndims\n    Read-only property returning the number of slice dimensions.\n\n    Returns\n    -------\n    ndims: integer\n        Number of slice dimensions.\n\n    Examples\n    --------\n    > var s = new Slice( 2, 10 );\n    > var ms = new MultiSlice( 2, s, 1 );\n    > ms.ndims\n    3","MultiSlice.prototype.data":"\nMultiSlice.prototype.data\n    Read-only property returning the slice data.\n\n    Returns\n    -------\n    data: Array<Slice|integer|null>\n        Slice data.\n\n    Examples\n    --------\n    > var s = new Slice( 2, 10 );\n    > var ms = new MultiSlice( 2, s, 1 );\n    > ms.data\n    [ 2, <Slice>, 1 ]","MultiSlice.prototype.toString":"\nMultiSlice.prototype.toString()\n    Serializes a multi-slice as a string.\n\n    Returns\n    -------\n    str: string\n        Serialized multi-slice string.\n\n    Examples\n    --------\n    > var s = new Slice( 2, 10 );\n    > var ms = new MultiSlice( 2, s, 1 );\n    > ms.toString()\n    'MultiSlice(2,Slice(2,10,null),1)'","MultiSlice.prototype.toJSON":"\nMultiSlice.prototype.toJSON()\n    Serializes a multi-slice as a JSON object.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var s = new Slice( 2, 10, 1 );\n    > var ms = new MultiSlice( 2, s );\n    > ms.toJSON()\n    {'type':'MultiSlice','data':[2,{'type':'Slice','data':[2,10,1]}]}\n\n    See Also\n    --------\n    ndarray, Slice","namedtypedtuple":"\nnamedtypedtuple( fields[, options] )\n    Returns a named typed tuple factory.\n\n    Named tuples assign a property name, and thus a meaning, to each position in\n    a tuple and allow for more readable, self-documenting code.\n\n    Named typed tuples can be used wherever typed arrays are used, with the\n    added benefit that they allow accessing fields by both field name and\n    position index.\n\n    Named typed tuples may be one the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754).\n    - float32: single-precision floating-point numbers (IEEE 754).\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n\n    Parameters\n    ----------\n    fields: Array<string>\n        Field (property) names.\n\n    options: Object (optional)\n        Function options.\n\n    options.dtype: string (optional)\n        Default tuple data type. If a data type is not provided to a named typed\n        tuple factory, this option specifies the underlying tuple data type.\n        Default: 'float64'.\n\n    options.name: string (optional)\n        Tuple name. Default: 'tuple'.\n\n    Returns\n    -------\n    factory: Function\n        Named typed tuple factory.\n\n    Examples\n    --------\n    > var opts = {};\n    > opts.name = 'Point';\n    > var factory = namedtypedtuple( [ 'x', 'y' ], opts );\n    > var tuple = factory();\n\n\nfactory()\n    Returns a named typed tuple of the default data type.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > p = factory();\n    > p.x\n    0.0\n    > p.y\n    0.0\n    > p[ 0 ]\n    0.0\n    > p[ 1 ]\n    0.0\n\n\nfactory( dtype )\n    Returns a named typed tuple of the specified data type.\n\n    Parameters\n    ----------\n    dtype: string\n        Tuple data type.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > p = factory( 'int32' );\n    > p.x\n    0\n    > p.y\n    0\n    > p[ 0 ]\n    0\n    > p[ 1 ]\n    0\n\n\nfactory( typedarray[, dtype] )\n    Creates a named typed tuple from a typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate a named typed tuple.\n\n    dtype: string (optional)\n        Tuple data type.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > p = factory( Float64Array[ 1.0, -1.0 ] );\n    > p.x\n    1.0\n    > p.y\n    -1.0\n    > p[ 0 ]\n    1.0\n    > p[ 1 ]\n    -1.0\n\n\nfactory( obj[, dtype] )\n    Creates a named typed tuple from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a named typed\n        tuple.\n\n    dtype: string (optional)\n        Tuple data type.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > p = factory( [ 1, -1 ], 'int32' );\n    > p.x\n    1\n    > p.y\n    -1\n    > p[ 0 ]\n    1\n    > p[ 1 ]\n    -1\n\n\nfactory( buffer[, byteOffset][, dtype] )\n    Returns a named typed tuple view of an ArrayBuffer.\n\n    The view length equals the number of tuple fields.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first tuple element.\n        Default: 0.\n\n    dtype: string (optional)\n        Tuple data type.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var buf = new ArrayBuffer( 16 );\n    > var p = factory( buf, 4, 'float32' );\n    > p.x\n    0.0\n    > p.y\n    0.0\n    > p[ 0 ]\n    0.0\n    > p[ 1 ]\n    0.0\n\n\nfactory.from( src[, map[, thisArg]] )\n    Creates a new named typed tuple from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n    - field: tuple field.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of tuple elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > function mapFcn( v ) { return v * 2.0; };\n    > var p = factory.from( [ 1.0, -1.0 ], mapFcn );\n    > p.x\n    2.0\n    > p.y\n    -2.0\n    > p[ 0 ]\n    2.0\n    > p[ 1 ]\n    -2.0\n\n\nfactory.fromObject( obj[, map[, thisArg]] )\n    Creates a new named typed tuple from an object containing tuple fields.\n\n    A callback is provided the following arguments:\n\n    - value: source object tuple field value.\n    - field: source object tuple field name.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    map: Function (optional)\n        Callback to invoke for each source object tuple field.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory.fromObject( { 'x': 2.0, 'y': -2.0 } );\n    > p.x\n    2.0\n    > p.y\n    -2.0\n    > p[ 0 ]\n    2.0\n    > p[ 1 ]\n    -2.0\n\n\nfactory.of( element0[, element1[, ...elementN]] )\n    Creates a new named typed tuple from a variable number of arguments.\n\n    The number of arguments *must* equal the number of tuple fields.\n\n    Parameters\n    ----------\n    element0: number\n        Tuple element.\n\n    element1: number (optional)\n        Tuple element.\n\n    elementN: number (optional)\n        Tuple elements.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory.of( 2.0, -2.0 );\n    > p.x\n    2.0\n    > p.y\n    -2.0\n    > p[ 0 ]\n    2.0\n    > p[ 1 ]\n    -2.0\n\n\ntuple.BYTES_PER_ELEMENT\n    Size (in bytes) of each tuple element.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > p.BYTES_PER_ELEMENT\n    8\n\n\ntuple.buffer\n    Pointer to the underlying data buffer.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > p.buffer\n    <ArrayBuffer>\n\n\ntuple.byteLength\n    Length (in bytes) of the tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > p.byteLength\n    16\n\n\ntuple.byteOffset\n    Offset (in bytes) of a tuple from the start of its underlying ArrayBuffer.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > p.byteOffset\n    0\n\n\ntuple.length\n    Tuple length (i.e., number of elements).\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > p.length\n    2\n\n\ntuple.name\n    Tuple name.\n\n    Examples\n    --------\n    > var opts = { 'name': 'Point' };\n    > var factory = namedtypedtuple( [ 'x', 'y' ], opts );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > p.name\n    'Point'\n\n\ntuple.fields\n    Returns the list of tuple fields.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > p.fields\n    [ 'x', 'y' ]\n\n\ntuple.orderedFields\n    Returns the list of tuple fields in index order.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > p[ 0 ]\n    1.0\n    > p.sort();\n    > p[ 0 ]\n    -1.0\n    > p.fields\n    [ 'x', 'y' ]\n    > p.orderedFields\n    [ 'y', 'x' ]\n\n\ntuple.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the tuple starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: tuple.length.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Modified tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n    > var p = factory( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n    > p.copyWithin( 3, 0, 2 );\n    > p.w\n    2.0\n    > p.v\n    -2.0\n\n\ntuple.entries()\n    Returns an iterator for iterating over tuple key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over tuple key-value pairs.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > it = p.entries();\n    > it.next().value\n    [ 0, 'x', 1.0 ]\n    > it.next().value\n    [ 1, 'y', -1.0 ]\n    > it.next().done\n    true\n\n\ntuple.every( predicate[, thisArg] )\n    Tests whether all tuple elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: tuple element.\n    - index: tuple index.\n    - field: tuple field name.\n    - tuple: tuple on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests tuple elements. If a predicate function\n        returns a truthy value, a tuple element passes; otherwise, a tuple\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all tuple elements pass.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > function predicate( v ) { return ( v >= 0.0 ); };\n    > p.every( predicate )\n    false\n\n\ntuple.fieldOf( searchElement[, fromIndex] )\n    Returns the field of the first tuple element strictly equal to a search\n    element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `undefined`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Tuple index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last tuple element.\n        Default: 0.\n\n    Returns\n    -------\n    field: string|undefined\n        Tuple field.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > var f = p.fieldOf( 2.0 )\n    undefined\n    > f = p.fieldOf( -1.0 )\n    'z'\n\n\ntuple.fill( value[, start[, end]] )\n    Fills a tuple from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last tuple element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last tuple element. Default: tuple.length.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Modified tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > p.fill( 2.0 );\n    > p.x\n    2.0\n    > p.y\n    2.0\n\n\ntuple.filter( predicate[, thisArg] )\n    Creates a new tuple which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: tuple element.\n    - index: tuple index.\n    - field: tuple field name.\n    - tuple: tuple on which the method is invoked.\n\n    The returned tuple has the same data type as the host tuple.\n\n    If a predicate function does not return a truthy value for any tuple\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters tuple elements. If a predicate function\n        returns a truthy value, a tuple element is included in the output tuple;\n        otherwise, a tuple element is not included in the output tuple.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    tuple: TypedArray\n        A new named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v >= 0.0 ); };\n    > var p2 = p1.filter( predicate );\n    > p2.fields\n    [ 'x', 'y' ]\n\n\ntuple.find( predicate[, thisArg] )\n    Returns the first tuple element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: tuple element.\n    - index: tuple index.\n    - field: tuple field name.\n    - tuple: tuple on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests tuple elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Tuple element.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > var v = p.find( predicate )\n    -1.0\n\n\ntuple.findField( predicate[, thisArg] )\n    Returns the field of the first tuple element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: tuple element.\n    - index: tuple index.\n    - field: tuple field name.\n    - tuple: tuple on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests tuple elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    field: string|undefined\n        Tuple field.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > var f = p.findField( predicate )\n    'z'\n\n\ntuple.findIndex( predicate[, thisArg] )\n    Returns the index of the first tuple element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: tuple element.\n    - index: tuple index.\n    - field: tuple field name.\n    - tuple: tuple on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests tuple elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Tuple index.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > var idx = p.findIndex( predicate )\n    2\n\n\ntuple.forEach( fcn[, thisArg] )\n    Invokes a callback for each tuple element.\n\n    A provided function is provided the following arguments:\n\n    - value: tuple element.\n    - index: tuple index.\n    - field: tuple field name.\n    - tuple: tuple on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each tuple element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1, 0, -1 ], 'int32' );\n    > var str = ' ';\n    > function fcn( v, i, f ) { str += f + '=' + v + ' '; };\n    > p.forEach( fcn );\n    > str\n    ' x=1 y=0 z=-1 '\n\n\ntuple.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether a tuple includes a search element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Tuple index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last tuple element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a tuple includes a search element.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > var bool = p.includes( 2.0 )\n    false\n    > bool = p.includes( -1.0 )\n    true\n\n\ntuple.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first tuple element strictly equal to a search\n    element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Tuple index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last tuple element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Tuple index.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > var idx = p.indexOf( 2.0 )\n    -1\n    > idx = p.indexOf( -1.0 )\n    2\n\n\ntuple.ind2key( ind )\n    Converts a tuple index to a field name.\n\n    If provided an out-of-bounds index, the method returns `undefined`.\n\n    Parameters\n    ----------\n    ind: integer\n        Tuple index. If less than zero, the method resolves the index relative\n        to the last tuple element.\n\n    Returns\n    -------\n    field: string|undefined\n        Field name.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > p.ind2key( 1 )\n    'y'\n    > p.ind2key( 100 )\n    undefined\n\n\ntuple.join( [separator] )\n    Serializes a tuple by joining all tuple elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating tuple elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Tuple serialized as a string.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1, 0, -1 ], 'int32' );\n    > p.join( '|' )\n    '1|0|-1'\n\n\ntuple.keys()\n    Returns an iterator for iterating over tuple keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over tuple keys.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > it = p.keys();\n    > it.next().value\n    [ 0, 'x' ]\n    > it.next().value\n    [ 1, 'y' ]\n    > it.next().done\n    true\n\n\ntuple.key2ind( field )\n    Converts a field name to a tuple index.\n\n    If provided an unknown field name, the method returns `-1`.\n\n    Parameters\n    ----------\n    field: string\n        Tuple field name.\n\n    Returns\n    -------\n    idx: integer\n        Tuple index.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > p.key2ind( 'y' )\n    1\n\n\ntuple.lastFieldOf( searchElement[, fromIndex] )\n    Returns the field of the last tuple element strictly equal to a search\n    element.\n\n    The method iterates from the last tuple element to the first tuple element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `undefined`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Tuple index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last tuple element.\n        Default: -1.\n\n    Returns\n    -------\n    field: string|undefined\n        Tuple field.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n    > var f = p.lastFieldOf( 2.0 )\n    undefined\n    > f = p.lastFieldOf( 0.0 )\n    'w'\n\n\ntuple.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last tuple element strictly equal to a search\n    element.\n\n    The method iterates from the last tuple element to the first tuple element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Tuple index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last tuple element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Tuple index.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n    > var idx = p.lastIndexOf( 2.0 )\n    -1\n    > idx = p.lastIndexOf( 0.0 )\n    3\n\n\ntuple.map( fcn[, thisArg] )\n    Maps each tuple element to an element in a new tuple.\n\n    A provided function is provided the following arguments:\n\n    - value: tuple element.\n    - index: tuple index.\n    - field: tuple field name.\n    - tuple: tuple on which the method is invoked.\n\n    The returned tuple has the same data type as the host tuple.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps tuple elements to elements in the new tuple.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    tuple: TypedArray\n        A new named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( v ) { return v * 2.0; };\n    > var p2 = p1.map( fcn );\n    > p2.x\n    2.0\n    > p2.y\n    0.0\n    > p2.z\n    -2.0\n\n\ntuple.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in a tuple and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current tuple element.\n    - index: index of the current tuple element.\n    - field: field name corresponding to the current tuple element.\n    - tuple: tuple on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first tuple element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first tuple element as the first argument and the second tuple\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = p.reduce( fcn, 0.0 )\n    2.0\n\n\ntuple.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in a tuple and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current tuple element.\n    - index: index of the current tuple element.\n    - field: field name corresponding to the current tuple element.\n    - tuple: tuple on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last tuple element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last tuple element as the first argument and the second-to-last\n    tuple element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = p.reduceRight( fcn, 0.0 )\n    2.0\n\n\ntuple.reverse()\n    Reverses a tuple *in-place*.\n\n    This method mutates the tuple on which the method is invoked.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Modified tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > p[ 0 ]\n    1.0\n    > p.x\n    1.0\n    > p.reverse();\n    > p[ 0 ]\n    -1.0\n    > p.x\n    1.0\n\n\ntuple.set( arr[, offset] )\n    Sets tuple elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing tuple values to set.\n\n    offset: integer (optional)\n        Tuple index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > p[ 1 ]\n    0.0\n    > p.y\n    0.0\n    > p.set( [ -2.0, 2.0 ], 1 );\n    > p[ 1 ]\n    -2.0\n    > p.y\n    -2.0\n    > p[ 2 ]\n    2.0\n    > p.z\n    2.0\n\n\ntuple.slice( [begin[, end]] )\n    Copies tuple elements to a new tuple with the same underlying data type as\n    the host tuple.\n\n    If the method is unable to resolve indices to a non-empty tuple subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last tuple element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last tuple element. Default: tuple.length.\n\n    Returns\n    -------\n    tuple: TypedArray\n        A new named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n    > p1.fields\n    [ 'x', 'y', 'z' ]\n    > var p2 = p1.slice( 1 );\n    > p2.fields\n    [ 'y', 'z' ]\n    > p2.y\n    0.0\n    > p2.z\n    -1.0\n\n\ntuple.some( predicate[, thisArg] )\n    Tests whether at least one tuple element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: tuple element.\n    - index: tuple index.\n    - field: tuple field name.\n    - tuple: tuple on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests tuple elements. If a predicate function\n        returns a truthy value, a tuple element passes; otherwise, a tuple\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one tuple element passes.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > p.some( predicate )\n    true\n\n\ntuple.sort( [compareFunction] )\n    Sorts a tuple *in-place*.\n\n    Sorting a tuple does *not* affect field assignments. Accessing a tuple field\n    before and after sorting will always return the same tuple element. However,\n    this behavior is generally not true when accessing tuple elements according\n    to tuple index. In summary, sorting affects index order but not field\n    assignments.\n\n    The comparison function is provided two tuple elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the tuple on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Modified tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n    > var p = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n    > p.sort();\n    > p.orderedFields\n    [ 'v', 'y', 'z', 'x', 'w' ]\n    > p[ 0 ]\n    -2.0\n    > p.x\n    1.0\n    > p[ 1 ]\n    -1.0\n    > p.y\n    -1.0\n    > p.key2ind( 'x' )\n    3\n\n\ntuple.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host tuple.\n\n    If the method is unable to resolve indices to a non-empty tuple subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last tuple element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last tuple element. Default: tuple.length.\n\n    Returns\n    -------\n    arr: TypedArray\n        A new typed array view.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n    > var p = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n    > var arr = p.subarray( 2 )\n    <Float64Array>[ 0.0, 2.0, -2.0 ]\n    > arr.length\n    3\n\n\ntuple.subtuple( [begin[, end]] )\n    Creates a new named typed tuple over the same underlying ArrayBuffer and\n    with the same underlying data type as the host tuple.\n\n    If the function is unable to resolve indices to a non-empty tuple\n    subsequence, the function returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last tuple element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last tuple element. Default: tuple.length.\n\n    Returns\n    -------\n    tuple: TypedArray|null\n        A new named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n    > var p1 = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n    > var p2 = p1.subtuple( 2 );\n    > p2.fields\n    [ 'z', 'w', 'v' ]\n    > p2[ 0 ]\n    0.0\n    > p2.z\n    0.0\n    > p2[ 1 ]\n    2.0\n    > p2.w\n    2.0\n    > p2[ 2 ]\n    -2.0\n    > p2.v\n    -2.0\n    > p2.length\n    3\n\n\ntuple.toJSON()\n    Serializes a tuple as JSON.\n\n    Returns\n    -------\n    obj: Object\n        A tuple JSON representation.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, -1.0, 0.0 ] );\n    > p.toJSON()\n    { 'x': 1.0, 'y': -1.0, 'z': 0.0 }\n\n\ntuple.toLocaleString( [locales[, options]] )\n    Serializes a tuple as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, -1.0, 0.0 ], 'int32' );\n    > p.toLocaleString()\n    '1,-1,0'\n\n\ntuple.toString()\n    Serializes a tuple as a string.\n\n    Returns\n    -------\n    str: string\n        A tuple string representation.\n\n    Examples\n    --------\n    > opts = { 'name': 'Point' };\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ], opts );\n    > var p = factory( [ 1.0, -1.0, 0.0 ] );\n    > p.toString()\n    'Point(x=1, y=-1, z=0)'\n\n\ntuple.values()\n    Returns an iterator for iterating over tuple elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over tuple elements.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > it = p.values();\n    > it.next().value\n    1.0\n    > it.next().value\n    -1.0\n    > it.next().done\n    true\n\n    See Also\n    --------\n    typedarray\n","NAN":"\nNAN\n    Double-precision floating-point NaN.\n\n    Examples\n    --------\n    > NAN\n    NaN\n\n    See Also\n    --------\n    FLOAT32_NAN\n","naryFunction":"\nnaryFunction( fcn, arity[, thisArg] )\n    Returns a function that applies a specified number of arguments to a\n    provided function.\n\n    The returned function *always* invokes the wrapped function with a specified\n    number of arguments, even when the returned function is provided fewer\n    arguments.\n\n    The value for the missing arguments is equal to `undefined`.\n\n    Parameters\n    ----------\n    fcn: Function\n        Input function.\n\n    arity: integer\n        Number of arguments.\n\n    thisArg: any (optional)\n        Function context.\n\n    Returns\n    -------\n    out: Function\n        Function wrapper.\n\n    Examples\n    --------\n    > function foo( a, b, c ) { return [ a, b, c ]; };\n    > var bar = naryFunction( foo, 2 );\n    > var out = bar( 1, 2, 3 )\n    [ 1, 2, undefined ]\n\n    See Also\n    --------\n    maskArguments, pickArguments\n","nativeClass":"\nnativeClass( value )\n    Returns a string value indicating a specification defined classification of\n    an object.\n\n    The function is *not* robust for ES2015+ environments. In ES2015+,\n    `Symbol.toStringTag` allows overriding the default description of an object.\n    While measures are taken to uncover the default description, such measures\n    can be thwarted. While this function remains useful for type-checking, be\n    aware that value impersonation is possible. Where possible, prefer functions\n    tailored to checking for particular value types, as specialized functions\n    are better equipped to address `Symbol.toStringTag`.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    out: string\n        String value indicating a specification defined classification of the\n        input value.\n\n    Examples\n    --------\n    > var str = nativeClass( 'a' )\n    '[object String]'\n    > str = nativeClass( 5 )\n    '[object Number]'\n    > function Beep(){};\n    > str = nativeClass( new Beep() )\n    '[object Object]'\n\n    See Also\n    --------\n    constructorName, typeOf\n","ndarray":"\nndarray( dtype, buffer, shape, strides, offset, order[, options] )\n    Returns an ndarray.\n\n    Parameters\n    ----------\n    dtype: string\n        Underlying data type.\n\n    buffer: ArrayLikeObject|TypedArray|Buffer\n        Data buffer. A data buffer must be an array-like object (i.e., have a\n        `length` property). For data buffers which are not indexed collections\n        (i.e., collections which cannot support direct index access, such as\n        `buffer[ index ]`; e.g., Complex64Array, Complex128Array, etc), a data\n        buffer should provide `#.get( idx )` and `#.set( v[, idx] )` methods.\n        Note that, for `set` methods, the value to set should be the first\n        argument, followed by the linear index, similar to the native typed\n        array `set` method.\n\n    shape: ArrayLikeObject<integer>\n        Array shape.\n\n    strides: ArrayLikeObject<integer>\n        Array strides.\n\n    offset: integer\n        Index offset.\n\n    order: string\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran-style).\n\n    options: Object (optional)\n        Options.\n\n    options.mode: string (optional)\n        Specifies how to handle indices which exceed array dimensions. If equal\n        to 'throw', an ndarray instance throws an error when an index exceeds\n        array dimensions. If equal to 'normalize', an ndarray instance\n        normalizes negative indices and throws an error when an index exceeds\n        array dimensions. If equal to 'wrap', an ndarray instance wraps around\n        indices exceeding array dimensions using modulo arithmetic. If equal to\n        'clamp', an ndarray instance sets an index exceeding array dimensions\n        to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n    options.submode: Array<string> (optional)\n        Specifies how to handle subscripts which exceed array dimensions. If a\n        mode for a corresponding dimension is equal to 'throw', an ndarray\n        instance throws an error when a subscript exceeds array dimensions. If\n        equal to 'normalize', an ndarray instance normalizes negative\n        subscripts and throws an error when a subscript exceeds array\n        dimensions. If equal to 'wrap', an ndarray instance wraps around\n        subscripts exceeding array dimensions using modulo arithmetic. If equal\n        to 'clamp', an ndarray instance sets a subscript exceeding array\n        dimensions to either `0` (minimum index) or the maximum index. If the\n        number of modes is fewer than the number of dimensions, the function\n        recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether an array should be read-only. Default: false.\n\n    Returns\n    -------\n    ndarray: ndarray\n        ndarray instance.\n\n    Examples\n    --------\n    // Create a new instance...\n    > var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\n    > var d = [ 2, 2 ]; // shape\n    > var s = [ 2, 1 ]; // strides\n    > var o = 0; // index offset\n    > var arr = ndarray( 'generic', b, d, s, o, 'row-major' )\n    <ndarray>\n\n    // Get an element using subscripts:\n    > var v = arr.get( 1, 1 )\n    4.0\n\n    // Get an element using a linear index:\n    > v = arr.iget( 3 )\n    4.0\n\n    // Set an element using subscripts:\n    > arr.set( 1, 1, 40.0 );\n    > arr.get( 1, 1 )\n    40.0\n\n    // Set an element using a linear index:\n    > arr.iset( 3, 99.0 );\n    > arr.get( 1, 1 )\n    99.0\n\n\nndarray.prototype.byteLength\n    Size (in bytes) of the array (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of the array.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.byteLength\n    32\n\n\nndarray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.BYTES_PER_ELEMENT\n    8\n\n\nndarray.prototype.data\n    Pointer to the underlying data buffer.\n\n    Returns\n    -------\n    buf: ArrayLikeObject|TypedArray|Buffer\n        Underlying data buffer.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var buf = arr.data\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n\nndarray.prototype.dtype\n    Underlying data type.\n\n    Returns\n    -------\n    dtype: string\n        Underlying data type.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var dt = arr.dtype\n    'float64'\n\n\nndarray.prototype.flags\n    Meta information, such as information concerning the memory layout of the\n    array.\n\n    Returns\n    -------\n    flags: Object\n        Info object.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var fl = arr.flags\n    {...}\n\n\nndarray.prototype.length\n    Length of the array (i.e., number of elements).\n\n    Returns\n    -------\n    len: integer\n        Array length.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var len = arr.length\n    4\n\n\nndarray.prototype.ndims\n    Number of dimensions.\n\n    Returns\n    -------\n    ndims: integer\n        Number of dimensions.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var n = arr.ndims\n    2\n\n\nndarray.prototype.offset\n    Index offset which specifies the buffer index at which to start iterating\n    over array elements.\n\n    Returns\n    -------\n    offset: integer\n        Index offset.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.offset\n    0\n\n\nndarray.prototype.order\n    Array order.\n\n    The array order is either row-major (C-style) or column-major (Fortran-\n    style).\n\n    Returns\n    -------\n    order: string\n        Array order.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var ord = arr.order\n    'row-major'\n\n\nndarray.prototype.shape\n    Array shape.\n\n    Returns\n    -------\n    shape: Array\n        Array shape.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sh = arr.shape\n    [ 2, 2 ]\n\n\nndarray.prototype.strides\n    Index strides which specify how to access data along corresponding array\n    dimensions.\n\n    Returns\n    -------\n    strides: Array\n        Index strides.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var st = arr.strides\n    [ 2, 1 ]\n\n\nndarray.prototype.get( ...idx )\n    Returns an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.get( 1, 1 )\n    4.0\n\n\nndarray.prototype.iget( idx )\n    Returns an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the input argument is ignored and, for clarity,\n    should not be provided.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.iget( 3 )\n    4.0\n\n\nndarray.prototype.set( ...idx, v )\n    Sets an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: ndarray\n        ndarray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > arr.set( 1, 1, -4.0 );\n    > arr.get( 1, 1 )\n    -4.0\n\n\nndarray.prototype.iset( idx, v )\n    Sets an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the first, and only, argument should be the\n    value to set.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: ndarray\n        ndarray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > arr.iset( 3, -4.0 );\n    > arr.iget( 3 )\n    -4.0\n\n\nndarray.prototype.toString()\n    Serializes an ndarray as a string.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    str: string\n        Serialized ndarray string.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toString()\n    '...'\n\n\nndarray.prototype.toJSON()\n    Serializes an ndarray as a JSON object.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toJSON()\n    {...}\n\n    See Also\n    --------\n    array, FancyArray\n","ndarray.prototype.byteLength":"\nndarray.prototype.byteLength\n    Size (in bytes) of the array (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of the array.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.byteLength\n    32","ndarray.prototype.BYTES_PER_ELEMENT":"\nndarray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.BYTES_PER_ELEMENT\n    8","ndarray.prototype.data":"\nndarray.prototype.data\n    Pointer to the underlying data buffer.\n\n    Returns\n    -------\n    buf: ArrayLikeObject|TypedArray|Buffer\n        Underlying data buffer.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var buf = arr.data\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]","ndarray.prototype.dtype":"\nndarray.prototype.dtype\n    Underlying data type.\n\n    Returns\n    -------\n    dtype: string\n        Underlying data type.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var dt = arr.dtype\n    'float64'","ndarray.prototype.flags":"\nndarray.prototype.flags\n    Meta information, such as information concerning the memory layout of the\n    array.\n\n    Returns\n    -------\n    flags: Object\n        Info object.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var fl = arr.flags\n    {...}","ndarray.prototype.length":"\nndarray.prototype.length\n    Length of the array (i.e., number of elements).\n\n    Returns\n    -------\n    len: integer\n        Array length.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var len = arr.length\n    4","ndarray.prototype.ndims":"\nndarray.prototype.ndims\n    Number of dimensions.\n\n    Returns\n    -------\n    ndims: integer\n        Number of dimensions.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var n = arr.ndims\n    2","ndarray.prototype.offset":"\nndarray.prototype.offset\n    Index offset which specifies the buffer index at which to start iterating\n    over array elements.\n\n    Returns\n    -------\n    offset: integer\n        Index offset.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.offset\n    0","ndarray.prototype.order":"\nndarray.prototype.order\n    Array order.\n\n    The array order is either row-major (C-style) or column-major (Fortran-\n    style).\n\n    Returns\n    -------\n    order: string\n        Array order.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var ord = arr.order\n    'row-major'","ndarray.prototype.shape":"\nndarray.prototype.shape\n    Array shape.\n\n    Returns\n    -------\n    shape: Array\n        Array shape.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sh = arr.shape\n    [ 2, 2 ]","ndarray.prototype.strides":"\nndarray.prototype.strides\n    Index strides which specify how to access data along corresponding array\n    dimensions.\n\n    Returns\n    -------\n    strides: Array\n        Index strides.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var st = arr.strides\n    [ 2, 1 ]","ndarray.prototype.get":"\nndarray.prototype.get( ...idx )\n    Returns an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.get( 1, 1 )\n    4.0","ndarray.prototype.iget":"\nndarray.prototype.iget( idx )\n    Returns an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the input argument is ignored and, for clarity,\n    should not be provided.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.iget( 3 )\n    4.0","ndarray.prototype.set":"\nndarray.prototype.set( ...idx, v )\n    Sets an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: ndarray\n        ndarray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > arr.set( 1, 1, -4.0 );\n    > arr.get( 1, 1 )\n    -4.0","ndarray.prototype.iset":"\nndarray.prototype.iset( idx, v )\n    Sets an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the first, and only, argument should be the\n    value to set.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: ndarray\n        ndarray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > arr.iset( 3, -4.0 );\n    > arr.iget( 3 )\n    -4.0","ndarray.prototype.toString":"\nndarray.prototype.toString()\n    Serializes an ndarray as a string.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    str: string\n        Serialized ndarray string.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toString()\n    '...'","ndarray.prototype.toJSON":"\nndarray.prototype.toJSON()\n    Serializes an ndarray as a JSON object.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toJSON()\n    {...}\n\n    See Also\n    --------\n    array, FancyArray","ndarray2array":"\nndarray2array( x )\n    Converts an ndarray to a generic array.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    Returns\n    -------\n    out: Array|Array<Array>\n        Generic array (which may include nested arrays).\n\n    Examples\n    --------\n    > var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > var out = ndarray2array( arr )\n    [ [ 1, 2 ], [ 3, 4 ] ]\n\n    See Also\n    --------\n    array, ndarray, ndarray2json\n","ndarray2fancy":"\nndarray2fancy( x[, options] )\n    Converts an ndarray to an object supporting fancy indexing.\n\n    An ndarray supporting fancy indexing is an ndarray which supports slicing\n    via indexing expressions for both retrieval and assignment.\n\n    A fancy ndarray can be consumed by any API which supports ndarray instances.\n\n    A fancy ndarray shares the *same* data as the provided input ndarray. Hence,\n    any mutations to the returned ndarray will affect the underlying input\n    ndarray and vice versa.\n\n    A fancy ndarray supports indexing using positive and negative integers (both\n    numeric literals and strings), Slice and MultiSlice instances, subsequence\n    expressions, mask ndarrays, boolean ndarrays, and integer ndarrays.\n\n    A fancy ndarray supports all properties and methods of the input ndarray,\n    and, thus, a fancy ndarray can be consumed by any API which supports\n    ndarray-like objects.\n\n    For operations returning a new ndarray (e.g., when slicing or invoking an\n    instance method), a fancy ndarray returns a new fancy ndarray having the\n    same configuration as specified by provided options.\n\n    Indexing expressions provide a convenient and powerful means for creating\n    and operating on ndarray views; however, their use does entail a performance\n    cost. Indexing expressions are best suited for interactive use and\n    scripting. For performance critical applications, prefer equivalent\n    functional APIs supporting ndarray instances.\n\n    Fancy ndarrays support broadcasting in which assigned scalars and ndarrays\n    are repeated (without additional memory allocation) to match the dimensions\n    of a target ndarray instance.\n\n    When assigning ndarrays to slices, the ndarray on the right-hand-side must\n    be broadcast-compatible with dimensions implied by the slice.\n\n    Fancy ndarrays support (mostly) safe casts (i.e., any cast which can be\n    performed without overflow or loss of precision, with the exception of\n    floating-point ndarrays which are also allowed to downcast from higher\n    precision to lower precision).\n\n    When attempting to perform an unsafe cast, fancy ndarrays will raise an\n    exception.\n\n    When assigning a real-valued scalar to a complex number ndarray, a fancy\n    ndarray will cast the real-valued scalar to a complex number argument having\n    an imaginary component equal to zero.\n\n    In older JavaScript environments which do not support Proxy objects, the use\n    of indexing expressions is not supported.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking. Default:\n        false.\n\n    options.cache: Object (optional)\n        Cache for resolving ndarray index objects. Must have a 'get' method\n        which accepts a single argument: a string identifier associated with an\n        ndarray index. If an ndarray index associated with a provided identifier\n        exists, the 'get' method should return an object having the following\n        properties:\n\n        - data: the underlying index ndarray.\n        - type: the index type. Must be either 'mask', 'bool', or 'int'.\n        - kind: the index kind. Must be either '', 'cartesian', or 'linear'.\n        - dtype: the data type of the underlying ndarray.\n\n        If an ndarray index is not associated with a provided identifier, the\n        'get' method should return `null`.\n\n        Default: `ndindex`.\n\n    Returns\n    -------\n    out: ndarray\n        Output ndarray supporting fancy indexing.\n\n    Examples\n    --------\n    // Create a normal ndarray...\n    > var b = [ 1.0, 2.0, 3.0, 4.0 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var x = ndarray( 'generic', b, d, s, o, 'row-major' );\n\n    // Convert to a fancy ndarray:\n    > var arr = ndarray2fancy( x );\n\n    // Get an element using subscripts:\n    > var v = arr.get( 1, 1 )\n    4.0\n\n    // Get an element using a linear index:\n    > v = arr.iget( 3 )\n    4.0\n\n    // Set an element using subscripts:\n    > arr.set( 1, 1, 40.0 );\n    > arr.get( 1, 1 )\n    40.0\n\n    // Set an element using a linear index:\n    > arr.iset( 3, 99.0 );\n    > arr.get( 1, 1 )\n    99.0\n\n\nndarray2fancy.factory( [options] )\n    Returns a function for converting an ndarray to an object supporting fancy\n    indexing.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking by default.\n        Default: false.\n\n    options.cache: Object (optional)\n        Cache for resolving ndarray index objects. Must have a 'get' method\n        which accepts a single argument: a string identifier associated with an\n        ndarray index. If an ndarray index associated with a provided identifier\n        exists, the 'get' method should return an object having the following\n        properties:\n\n        - data: the underlying index ndarray.\n        - type: the index type. Must be either 'mask', 'bool', or 'int'.\n        - kind: the index kind. Must be either '', 'cartesian', or 'linear'.\n        - dtype: the data type of the underlying ndarray.\n\n        If an ndarray index is not associated with a provided identifier, the\n        'get' method should return `null`.\n\n        Default: `ndindex`.\n\n    Returns\n    -------\n    fcn: Function\n        Function for converting an ndarray to an object supporting fancy\n        indexing.\n\n    Examples\n    --------\n    // Create a normal ndarray...\n    > var b = [ 1.0, 2.0, 3.0, 4.0 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var x = ndarray( 'generic', b, d, s, o, 'row-major' );\n\n    // Create a function for converting ndarrays to fancy ndarrays:\n    > var f = ndarray2fancy.factory();\n\n    // Convert the normal ndarray to a fancy ndarray:\n    > var y = f( x );\n\n\nndarray2fancy.idx( x[, options] )\n    Wraps a provided ndarray as an ndarray index object.\n\n    For documentation and usage, see `ndindex`.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.persist: boolean (optional)\n        Boolean indicating whether to continue persisting an index object after\n        first usage. Default: false.\n\n    options.kind: string (optional)\n        Specifies whether a provided ndarray is a specialized input ndarray\n        \"kind\". This option is only applicable for integer input ndarrays. Must\n        be one of the following:\n\n        - cartesian: a provided input ndarray contains Cartesian indices.\n        - linear: a provided input ndarray contains indices representing\n          locations in linear memory.\n\n        Default: ''.\n\n    Returns\n    -------\n    out: ndarrayIndex\n        ndarray index instance.\n\n    Examples\n    --------\n    > var opts = { 'dtype': 'int32' };\n    > var buf = new Int32Array( [ 1, 2, 3, 4 ] );\n    > var arr = array( buf, opts );\n    > var idx = ndarray2fancy.idx( arr );\n\n    See Also\n    --------\n    array2fancy, array, ndarray, FancyArray\n","ndarray2fancy.factory":"\nndarray2fancy.factory( [options] )\n    Returns a function for converting an ndarray to an object supporting fancy\n    indexing.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking by default.\n        Default: false.\n\n    options.cache: Object (optional)\n        Cache for resolving ndarray index objects. Must have a 'get' method\n        which accepts a single argument: a string identifier associated with an\n        ndarray index. If an ndarray index associated with a provided identifier\n        exists, the 'get' method should return an object having the following\n        properties:\n\n        - data: the underlying index ndarray.\n        - type: the index type. Must be either 'mask', 'bool', or 'int'.\n        - kind: the index kind. Must be either '', 'cartesian', or 'linear'.\n        - dtype: the data type of the underlying ndarray.\n\n        If an ndarray index is not associated with a provided identifier, the\n        'get' method should return `null`.\n\n        Default: `ndindex`.\n\n    Returns\n    -------\n    fcn: Function\n        Function for converting an ndarray to an object supporting fancy\n        indexing.\n\n    Examples\n    --------\n    // Create a normal ndarray...\n    > var b = [ 1.0, 2.0, 3.0, 4.0 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var x = ndarray( 'generic', b, d, s, o, 'row-major' );\n\n    // Create a function for converting ndarrays to fancy ndarrays:\n    > var f = ndarray2fancy.factory();\n\n    // Convert the normal ndarray to a fancy ndarray:\n    > var y = f( x );","ndarray2fancy.idx":"\nndarray2fancy.idx( x[, options] )\n    Wraps a provided ndarray as an ndarray index object.\n\n    For documentation and usage, see `ndindex`.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.persist: boolean (optional)\n        Boolean indicating whether to continue persisting an index object after\n        first usage. Default: false.\n\n    options.kind: string (optional)\n        Specifies whether a provided ndarray is a specialized input ndarray\n        \"kind\". This option is only applicable for integer input ndarrays. Must\n        be one of the following:\n\n        - cartesian: a provided input ndarray contains Cartesian indices.\n        - linear: a provided input ndarray contains indices representing\n          locations in linear memory.\n\n        Default: ''.\n\n    Returns\n    -------\n    out: ndarrayIndex\n        ndarray index instance.\n\n    Examples\n    --------\n    > var opts = { 'dtype': 'int32' };\n    > var buf = new Int32Array( [ 1, 2, 3, 4 ] );\n    > var arr = array( buf, opts );\n    > var idx = ndarray2fancy.idx( arr );\n\n    See Also\n    --------\n    array2fancy, array, ndarray, FancyArray","ndarray2json":"\nndarray2json( x )\n    Serializes an ndarray as a JSON object.\n\n    This function does *not* serialize data outside of the buffer region defined\n    by the ndarray view.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    Returns\n    -------\n    out: Object\n        JSON object.\n\n    Examples\n    --------\n    > var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > var out = ndarray2json( arr )\n    {...}\n\n    See Also\n    --------\n    array, ndarray, ndarray2array\n","ndarrayCastingModes":"\nndarrayCastingModes()\n    Returns a list of ndarray casting modes.\n\n    The output array contains the following modes:\n\n    - 'none': only allow casting between identical types.\n    - 'equiv': allow casting between identical and byte swapped types.\n    - 'safe': only allow \"safe\" casts.\n    - 'mostly-safe': allow \"safe\" casts and, for floating-point data types,\n      downcasts.\n    - 'same-kind': allow \"safe\" casts and casts within the same kind (e.g.,\n      between signed integers or between floats).\n    - 'unsafe': allow casting between all types (including between integers and\n      floats).\n\n    Returns\n    -------\n    out: Array<string>\n        List of ndarray casting modes.\n\n    Examples\n    --------\n    > var out = ndarrayCastingModes()\n    [ 'none', 'equiv', 'safe', 'mostly-safe', 'same-kind', 'unsafe' ]\n\n    See Also\n    --------\n    array, ndarray\n","ndarrayDataBuffer":"\nndarrayDataBuffer( x )\n    Returns the underlying data buffer of a provided ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Underlying data buffer.\n\n    Examples\n    --------\n    > var opts = { 'dtype': 'float64' };\n    > var out = ndarrayDataBuffer( ndzeros( [ 3, 3, 3 ], opts ) )\n    <Float64Array>\n\n    See Also\n    --------\n    array, ndarray, ndarrayDataType\n","ndarrayDataType":"\nndarrayDataType( x )\n    Returns the data type of a provided ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    Returns\n    -------\n    dt: string\n        Data type.\n\n    Examples\n    --------\n    > var opts = { 'dtype': 'float64' };\n    > var dt = ndarrayDataType( ndzeros( [ 3, 3, 3 ], opts ) )\n    'float64'\n\n    See Also\n    --------\n    array, ndarray, ndarrayDataTypes\n","ndarrayDataTypes":"\nndarrayDataTypes( [kind] )\n    Returns a list of ndarray data types.\n\n    When not provided a data type \"kind\", the function returns an array\n    containing the following data types:\n\n    - float32: single-precision floating-point numbers.\n    - float64: double-precision floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - complex128: double-precision complex floating-point numbers.\n    - bool: boolean values.\n    - generic: values of any type.\n    - int16: signed 16-bit integers.\n    - int32: signed 32-bit integers.\n    - int8: signed 8-bit integers.\n    - uint16: unsigned 16-bit integers.\n    - uint32: unsigned 32-bit integers.\n    - uint8: unsigned 8-bit integers.\n    - uint8c: unsigned clamped 8-bit integers.\n    - binary: binary.\n\n    The function supports the following data type \"kinds\":\n\n    - floating_point: floating-point data types.\n    - real_floating_point: real-valued floating-point data types.\n    - complex_floating_point: complex-valued floating-point data types.\n    - boolean: boolean data types.\n    - integer: integer data types.\n    - signed_integer: signed integer data types.\n    - unsigned_integer: unsigned integer data types.\n    - real: real-valued data types.\n    - numeric: numeric data types.\n    - typed: typed data types.\n    - all: all data types.\n\n    Additionally, the function supports extending the \"kinds\" listed above by\n    appending a '_and_generic' suffix to the kind name (e.g., real_and_generic).\n\n    Parameters\n    ----------\n    kind: string (optional)\n        Data type kind.\n\n    Returns\n    -------\n    out: Array<string>\n        List of ndarray data types.\n\n    Examples\n    --------\n    > var out = ndarrayDataTypes()\n    [...]\n    > out = ndarrayDataTypes( 'floating_point' )\n    [...]\n    > out = ndarrayDataTypes( 'floating_point_and_generic' )\n    [...]\n\n    See Also\n    --------\n    arrayDataTypes, array, ndarray, typedarrayDataTypes\n","ndarrayDispatch":"\nndarrayDispatch( fcns, types, data, nargs, nin, nout )\n    Returns an ndarray function interface which performs multiple dispatch.\n\n    An ndarray function interface has the following signature:\n\n      f( x, y, ... )\n\n    where\n\n    - x: ndarray.\n    - y: ndarray.\n    - ...: additional ndarrays.\n\n    The number of parameters is derived from `nargs`, the number of input\n    ndarrays is derived from `nin`, and the number of output ndarrays is derived\n    from `nout`.\n\n    Parameters\n    ----------\n    fcns: Function|ArrayLikeObject<Function>\n        List of ndarray functions. An ndarray function should have the following\n        signature:\n\n          f( arrays, data )\n\n        where\n\n        - arrays: array containing input and output ndarrays.\n        - data: ndarray function data (e.g., a callback).\n\n        For convenience, a single ndarray function may be provided which will be\n        invoked whenever the ndarray argument data types match a sequence of\n        types in `types`. Providing a single ndarray function is particularly\n        convenient for the case where, regardless of array data types,\n        traversing arrays remains the same, but the ndarray function `data`\n        differs (e.g., callbacks which differ based on the array data types).\n\n    types: ArrayLikeObject\n        One-dimensional list of ndarray argument data types.\n\n    data: ArrayLikeObject|null\n        ndarray function data (e.g., callbacks). If `null`, a returned ndarray\n        function interface does **not** provide a `data` argument to an invoked\n        ndarray function.\n\n    nargs: integer\n        Total number of ndarray function interface arguments.\n\n    nin: integer\n        Number of input ndarrays.\n\n    nout: integer\n        Number of output ndarrays.\n\n    Returns\n    -------\n    fcn: Function\n        ndarray function interface.\n\n    Examples\n    --------\n    // Define ndarray argument data types:\n    > var t = [ 'float64', 'float64', 'float32', 'float32' ];\n\n    // Define a list of ndarray function data (callbacks):\n    > var d = [ base.abs, base.absf ];\n\n    // Create an ndarray function interface for applying unary callbacks:\n    > var f = ndarrayDispatch( base.ndarrayUnary, t, d, 2, 1, 1 );\n\n    // Create an input ndarray:\n    > var xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var x = ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );\n\n    // Create an output ndarray:\n    > var ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var y = ndarray( 'float64', ybuf, [ 4 ], [ 1 ], 0, 'row-major' );\n\n    // Compute the element-wise absolute value:\n    > f( x, y );\n    > ybuf\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    See Also\n    --------\n    array, ndarray\n","ndarrayFlag":"\nndarrayFlag( x, name )\n    Returns a specified flag for a provided ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    name: string|symbol\n        Flag name.\n\n    Returns\n    -------\n    out: any\n        Flag value.\n\n    Examples\n    --------\n    > var out = ndarrayFlag( ndzeros( [ 3, 3, 3 ] ), 'READONLY' )\n    <boolean>\n\n    See Also\n    --------\n    array, ndarray, ndarrayFlags\n","ndarrayFlags":"\nndarrayFlags( x )\n    Returns the flags of a provided ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    Returns\n    -------\n    out: Object\n        Flags.\n\n    Examples\n    --------\n    > var out = ndarrayFlags( ndzeros( [ 3, 3, 3 ] ) )\n    {...}\n\n    See Also\n    --------\n    array, ndarray, ndarrayFlag\n","ndarrayIndexModes":"\nndarrayIndexModes()\n    Returns a list of ndarray index modes.\n\n    The output array contains the following modes:\n\n    - throw: specifies that a function should throw an error when an index is\n    outside a restricted interval.\n    - normalize: specifies that a function should normalize negative indices and\n    throw an error when an index is outside a restricted interval.\n    - wrap: specifies that a function should wrap around an index using modulo\n    arithmetic.\n    - clamp: specifies that a function should set an index less than zero to\n    zero (minimum index) and set an index greater than a maximum index value to\n    the maximum possible index.\n\n    Returns\n    -------\n    out: Array<string>\n        List of ndarray index modes.\n\n    Examples\n    --------\n    > var out = ndarrayIndexModes()\n    [ 'throw', 'normalize', 'clamp', 'wrap' ]\n\n    See Also\n    --------\n    array, ndarray\n","ndarraylike2ndarray":"\nndarraylike2ndarray( x[, options] )\n    Converts an ndarray-like object to an ndarray.\n\n    If provided a read-only ndarray, the function returns a read-only ndarray.\n\n    Parameters\n    ----------\n    x: ndarrayLike\n        Input ndarray-like object.\n\n    options: Object (optional)\n        Options.\n\n    options.mode: string (optional)\n        Specifies how to handle indices which exceed array dimensions. If equal\n        to 'throw', an ndarray instance throws an error when an index exceeds\n        array dimensions. If equal to 'normalize', an ndarray instance\n        normalizes negative indices and throws an error when an index exceeds\n        array dimensions. If equal to 'wrap', an ndarray instance wraps around\n        indices exceeding array dimensions using modulo arithmetic. If equal to\n        'clamp', an ndarray instance sets an index exceeding array dimensions\n        to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n    options.submode: Array<string> (optional)\n        Specifies how to handle subscripts which exceed array dimensions. If a\n        mode for a corresponding dimension is equal to 'throw', an ndarray\n        instance throws an error when a subscript exceeds array dimensions. If\n        equal to 'normalize', an ndarray instance normalizes negative\n        subscripts and throws an error when a subscript exceeds array\n        dimensions. If equal to 'wrap', an ndarray instance wraps around\n        subscripts exceeding array dimensions using modulo arithmetic. If equal\n        to 'clamp', an ndarray instance sets a subscript exceeding array\n        dimensions to either `0` (minimum index) or the maximum index. If the\n        number of modes is fewer than the number of dimensions, the function\n        recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether an array should be read-only.\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > var out = ndarraylike2ndarray( arr )\n    <ndarray>\n\n    See Also\n    --------\n    array, ndarray, ndemptyLike, ndzerosLike\n","ndarrayMinDataType":"\nndarrayMinDataType( value )\n    Returns the minimum ndarray data type of the closest \"kind\" necessary for\n    storing a provided scalar value.\n\n    The function does *not* provide precision guarantees for non-integer-valued\n    numbers. In other words, the function returns the smallest possible\n    floating-point (i.e., inexact) data type for storing numbers having\n    decimals.\n\n    Parameters\n    ----------\n    value: any\n        Scalar value.\n\n    Returns\n    -------\n    dt: string\n        ndarray data type.\n\n    Examples\n    --------\n    > var dt = ndarrayMinDataType( 3.141592653589793 )\n    'float32'\n    > dt = ndarrayMinDataType( 3 )\n    'uint8'\n    > dt = ndarrayMinDataType( -3 )\n    'int8'\n    > dt = ndarrayMinDataType( '-3' )\n    'generic'\n\n    See Also\n    --------\n    ndarrayDataTypes, ndarrayPromotionRules, ndarraySafeCasts\n","ndarrayMostlySafeCasts":"\nndarrayMostlySafeCasts( [dtype] )\n    Returns a list of ndarray data types to which a provided ndarray data type\n    can be safely cast and, for floating-point data types, can be downcast.\n\n    If not provided an ndarray data type, the function returns a casting table.\n\n    If provided an unrecognized ndarray data type, the function returns `null`.\n\n    Parameters\n    ----------\n    dtype: any (optional)\n        ndarray data type value.\n\n    Returns\n    -------\n    out: Object|Array<string>|null\n        ndarray data types to which a data type can be cast.\n\n    Examples\n    --------\n    > var out = ndarrayMostlySafeCasts( 'float32' )\n    <Array>\n\n    See Also\n    --------\n    ndarrayCastingModes, ndarrayDataTypes, ndarraySafeCasts, ndarraySameKindCasts\n","ndarrayNextDataType":"\nndarrayNextDataType( [dtype] )\n    Returns the next larger ndarray data type of the same kind.\n\n    If not provided a data type, the function returns a table.\n\n    If a data type does not have a next larger data type or the next larger type\n    is not supported, the function returns `-1`.\n\n    If provided an unrecognized data type, the function returns `null`.\n\n    Parameters\n    ----------\n    dtype: any (optional)\n        ndarray data type value.\n\n    Returns\n    -------\n    out: Object|string|integer|null\n        Next larger type(s).\n\n    Examples\n    --------\n    > var out = ndarrayNextDataType( 'float32' )\n    'float64'\n\n    See Also\n    --------\n    ndarrayDataTypes, ndarrayPromotionRules, ndarraySafeCasts\n","ndarrayOffset":"\nndarrayOffset( x )\n    Returns the index offset specifying the underlying buffer index of the first\n    iterated ndarray element.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    Returns\n    -------\n    n: integer\n        Index offset.\n\n    Examples\n    --------\n    > var n = ndarrayOffset( ndzeros( [ 3, 3, 3 ] ) )\n    0\n\n    See Also\n    --------\n    array, ndarray, ndarrayShape, ndarrayStrides\n","ndarrayOrder":"\nndarrayOrder( x )\n    Returns the layout order of a provided ndarray.\n\n    If unable to resolve a layout order, the function returns `null`.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    Returns\n    -------\n    out: string|null\n        Layout order.\n\n    Examples\n    --------\n    > var opts = { 'order': 'row-major' };\n    > var dt = ndarrayOrder( ndzeros( [ 3, 3, 3 ], opts ) )\n    'row-major'\n\n    See Also\n    --------\n    array, ndarray, ndarrayOrders, ndarrayShape, ndarrayStrides\n","ndarrayOrders":"\nndarrayOrders()\n    Returns a list of ndarray orders.\n\n    The output array contains the following orders:\n\n    - row-major: row-major (C-style) order.\n    - column-major: column-major (Fortran-style) order.\n\n    Returns\n    -------\n    out: Array<string>\n        List of ndarray orders.\n\n    Examples\n    --------\n    > var out = ndarrayOrders()\n    [ 'row-major', 'column-major' ]\n\n    See Also\n    --------\n    array, ndarray\n","ndarrayPromotionRules":"\nndarrayPromotionRules( [dtype1, dtype2] )\n    Returns the ndarray data type with the smallest size and closest \"kind\" to\n    which ndarray data types can be safely cast.\n\n    If not provided data types, the function returns a type promotion table.\n\n    If a data type to which data types can be safely cast does *not* exist (or\n    is not supported), the function returns `-1`.\n\n    If provided an unrecognized data type, the function returns `null`.\n\n    Parameters\n    ----------\n    dtype1: any (optional)\n        ndarray data type value.\n\n    dtype2: any (optional)\n        ndarray data type value.\n\n    Returns\n    -------\n    out: Object|string|integer|null\n        Promotion rule(s).\n\n    Examples\n    --------\n    > var out = ndarrayPromotionRules( 'float32', 'int32' )\n    'float64'\n\n    See Also\n    --------\n    ndarrayCastingModes, ndarrayDataTypes, ndarraySafeCasts\n","ndarraySafeCasts":"\nndarraySafeCasts( [dtype] )\n    Returns a list of ndarray data types to which a provided ndarray data type\n    can be safely cast.\n\n    If not provided an ndarray data type, the function returns a casting table.\n\n    If provided an unrecognized ndarray data type, the function returns `null`.\n\n    Parameters\n    ----------\n    dtype: any (optional)\n        ndarray data type value.\n\n    Returns\n    -------\n    out: Object|Array<string>|null\n        ndarray data types to which a data type can be safely cast.\n\n    Examples\n    --------\n    > var out = ndarraySafeCasts( 'float32' )\n    <Array>\n\n    See Also\n    --------\n    ndarrayCastingModes, ndarrayDataTypes, ndarraySameKindCasts\n","ndarraySameKindCasts":"\nndarraySameKindCasts( [dtype] )\n    Returns a list of ndarray data types to which a provided ndarray data type\n    can be safely cast or cast within the same \"kind\".\n\n    If not provided an ndarray data type, the function returns a casting table.\n\n    If provided an unrecognized ndarray data type, the function returns `null`.\n\n    Parameters\n    ----------\n    dtype: any (optional)\n        ndarray data type value.\n\n    Returns\n    -------\n    out: Object|Array<string>|null\n        ndarray data types to which a data type can be safely cast or cast\n        within the same \"kind\".\n\n    Examples\n    --------\n    > var out = ndarraySameKindCasts( 'float32' )\n    <Array>\n\n    See Also\n    --------\n    ndarrayCastingModes, ndarrayDataTypes, ndarraySafeCasts\n","ndarrayShape":"\nndarrayShape( x )\n    Returns the shape of a provided ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    Returns\n    -------\n    out: Array<integer>\n        Shape.\n\n    Examples\n    --------\n    > var out = ndarrayShape( ndzeros( [ 3, 3, 3 ] ) )\n    [ 3, 3, 3 ]\n\n    See Also\n    --------\n    array, ndarray, ndarrayOffset, ndarrayStrides\n","ndarrayStride":"\nndarrayStride( x, dim )\n    Returns the stride along a specified dimension for a provided ndarray.\n\n    A \"stride\" is the linear distance (i.e., number of elements) between\n    adjacent elements along a specified dimension.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    dim: integer\n        Dimension index. If less than zero, the index is resolved relative to\n        the last dimension, with the last dimension corresponding to the value\n        `-1`.\n\n    Returns\n    -------\n    out: integer\n        Stride.\n\n    Examples\n    --------\n    > var out = ndarrayStride( ndzeros( [ 3, 3, 3 ] ), 0 )\n    9\n\n    See Also\n    --------\n    array, ndarray, ndarrayOffset, ndarrayOrder, ndarrayShape, ndarrayStrides\n","ndarrayStrides":"\nndarrayStrides( x )\n    Returns the strides of a provided ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    Returns\n    -------\n    out: Array<integer>\n        Strides.\n\n    Examples\n    --------\n    > var out = ndarrayStrides( ndzeros( [ 3, 3, 3 ] ) )\n    [ 9, 3, 1 ]\n\n    See Also\n    --------\n    array, ndarray, ndarrayOffset, ndarrayOrder, ndarrayShape\n","ndat":"\nndat( x[, ...indices] )\n    Returns an ndarray element.\n\n    Negative indices are resolved relative to the last element along the\n    respective dimension, with the last element corresponding to `-1`.\n\n    If provided out-of-bounds indices, the function always returns `undefined`.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    indices: ...integer (optional)\n        Index arguments. The number of index arguments must equal the number of\n        dimensions.\n\n    Returns\n    -------\n    out: any\n        Element value.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > ndat( x, 0, 1 )\n    2\n    > ndat( x, 1, 0 )\n    3\n\n    See Also\n    --------\n    array, ndslice\n","ndempty":"\nndempty( shape[, options] )\n    Returns an uninitialized ndarray having a specified shape and data type.\n\n    In browser environments, the function always returns zero-filled ndarrays.\n\n    If `dtype` is 'generic', the function always returns a zero-filled ndarray.\n\n    For returned ndarrays whose underlying memory is *not* initialized, memory\n    contents are unknown and may contain *sensitive* data.\n\n    Parameters\n    ----------\n    shape: ArrayLikeObject<integer>|integer\n        Array shape.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Underlying data type. Default: 'float64'.\n\n    options.order: string (optional)\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran-style). Default: 'row-major'.\n\n    options.mode: string (optional)\n        Specifies how to handle indices which exceed array dimensions. If equal\n        to 'throw', an ndarray instance throws an error when an index exceeds\n        array dimensions. If equal to 'normalize', an ndarray instance\n        normalizes negative indices and throws an error when an index exceeds\n        array dimensions. If equal to 'wrap', an ndarray instance wraps around\n        indices exceeding array dimensions using modulo arithmetic. If equal to\n        'clamp', an ndarray instance sets an index exceeding array dimensions\n        to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n    options.submode: Array<string> (optional)\n        Specifies how to handle subscripts which exceed array dimensions. If a\n        mode for a corresponding dimension is equal to 'throw', an ndarray\n        instance throws an error when a subscript exceeds array dimensions. If\n        equal to 'normalize', an ndarray instance normalizes negative\n        subscripts and throws an error when a subscript exceeds array\n        dimensions. If equal to 'wrap', an ndarray instance wraps around\n        subscripts exceeding array dimensions using modulo arithmetic. If equal\n        to 'clamp', an ndarray instance sets a subscript exceeding array\n        dimensions to either `0` (minimum index) or the maximum index. If the\n        number of modes is fewer than the number of dimensions, the function\n        recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var arr = ndempty( [ 2, 2 ] )\n    <ndarray>\n    > var sh = arr.shape\n    [ 2, 2 ]\n    > var dt = arr.dtype\n    'float64'\n\n    See Also\n    --------\n    ndemptyLike, ndzeros\n","ndemptyLike":"\nndemptyLike( x[, options] )\n    Returns an uninitialized ndarray having the same shape and data type as a\n    provided input ndarray.\n\n    The function infers the following attributes from the input array:\n\n    - shape: array shape.\n    - dtype: underlying array data type.\n    - order: whether the array order is row-major (C-style) or column-major\n      (Fortran-style).\n\n    In browser environments, the function always returns zero-filled ndarrays.\n\n    If `dtype` is 'generic', the function always returns a zero-filled ndarray.\n\n    For returned ndarrays whose underlying memory is *not* initialized, memory\n    contents are unknown and may contain *sensitive* data.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    options: Object (optional)\n        Options.\n\n    options.shape: ArrayLikeObject<integer>|integer (optional)\n        Array shape. Overrides the input array's inferred shape.\n\n    options.dtype: string (optional)\n        Array data type. Overrides the input array's inferred data type.\n\n    options.order: string (optional)\n        Array order (either 'row-major' (C-style) or 'column-major' (Fortran-\n        style)). Overrides the input array's inferred order.\n\n    options.mode: string (optional)\n        Specifies how to handle indices which exceed array dimensions. If equal\n        to 'throw', an ndarray instance throws an error when an index exceeds\n        array dimensions. If equal to 'normalize', an ndarray instance\n        normalizes negative indices and throws an error when an index exceeds\n        array dimensions. If equal to 'wrap', an ndarray instance wraps around\n        indices exceeding array dimensions using modulo arithmetic. If equal to\n        'clamp', an ndarray instance sets an index exceeding array dimensions\n        to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n    options.submode: Array<string> (optional)\n        Specifies how to handle subscripts which exceed array dimensions. If a\n        mode for a corresponding dimension is equal to 'throw', an ndarray\n        instance throws an error when a subscript exceeds array dimensions. If\n        equal to 'normalize', an ndarray instance normalizes negative\n        subscripts and throws an error when a subscript exceeds array\n        dimensions. If equal to 'wrap', an ndarray instance wraps around\n        subscripts exceeding array dimensions using modulo arithmetic. If equal\n        to 'clamp', an ndarray instance sets a subscript exceeding array\n        dimensions to either `0` (minimum index) or the maximum index. If the\n        number of modes is fewer than the number of dimensions, the function\n        recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n    <ndarray>\n    > var sh = x.shape\n    [ 2, 2 ]\n    > var dt = x.dtype\n    'float64'\n    > var y = ndemptyLike( x )\n    <ndarray>\n    > sh = y.shape\n    [ 2, 2 ]\n    > dt = y.dtype\n    'float64'\n\n    See Also\n    --------\n    ndempty, ndzerosLike\n","ndfilter":"\nndfilter( x[, options], predicate[, thisArg] )\n    Returns a shallow copy of an ndarray containing only those elements which\n    pass a test implemented by a predicate function.\n\n    The predicate function is provided the following arguments:\n\n    - value: current array element.\n    - indices: current array element indices.\n    - arr: the input ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.dtype: string (optional)\n        Output ndarray data type. Overrides using the input array's inferred\n        data type.\n\n    options.order: string (optional)\n        Index iteration order. By default, the function iterates over elements\n        according to the layout order of the provided array. Accordingly, for\n        row-major input arrays, the last dimension indices increment fastest.\n        For column-major input arrays, the first dimension indices increment\n        fastest. To override the inferred order and ensure that indices\n        increment in a specific manner, regardless of the input array's layout\n        order, explicitly set the iteration order. Note, however, that iterating\n        according to an order which does not match that of the input array may,\n        in some circumstances, result in performance degradation due to cache\n        misses. Must be either 'row-major' or 'column-major'.\n\n    predicate: Function\n        Predicate function.\n\n    thisArg: any (optional)\n        Predicate function execution context.\n\n    Examples\n    --------\n    > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n    > function f( v ) { return v > 2.0; };\n    > var y = ndfilter( x, f );\n    > ndarray2array( y )\n    [ 3.0, 4.0 ]\n\n    See Also\n    --------\n    ndfilterMap, ndmap, ndreject, ndslice","ndfilterMap":"\nndfilterMap( x[, options], fcn[, thisArg] )\n    Filters and maps elements in an input ndarray to elements in a new output\n    ndarray according to a callback function.\n\n    The callback function is provided the following arguments:\n\n    - value: current array element.\n    - indices: current array element indices.\n    - arr: the input ndarray.\n\n    If a provided callback function returns `undefined`, the function skips the\n    respective ndarray element. If the callback function returns a value other\n    than `undefined`, the function stores the callback's return value in the\n    output ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.dtype: string (optional)\n        Output ndarray data type. Overrides using the input array's inferred\n        data type.\n\n    options.order: string (optional)\n        Index iteration order. By default, the function iterates over elements\n        according to the layout order of the provided array. Accordingly, for\n        row-major input arrays, the last dimension indices increment fastest.\n        For column-major input arrays, the first dimension indices increment\n        fastest. To override the inferred order and ensure that indices\n        increment in a specific manner, regardless of the input array's layout\n        order, explicitly set the iteration order. Note, however, that iterating\n        according to an order which does not match that of the input array may,\n        in some circumstances, result in performance degradation due to cache\n        misses. Must be either 'row-major' or 'column-major'.\n\n    fcn: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback function execution context.\n\n    Examples\n    --------\n    > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n    > function f( v ) { if ( v > 2.0 ) { return v * 10.0; } };\n    > var y = ndfilterMap( x, f );\n    > ndarray2array( y )\n    [ 30.0, 40.0 ]\n\n    See Also\n    --------\n    ndfilter, ndmap, ndreject, ndslice","ndforEach":"\nndforEach( x, fcn[, thisArg] )\n    Invokes a callback function once for each ndarray element.\n\n    The callback function is provided the following arguments:\n\n    - value: current array element.\n    - indices: current array element indices.\n    - arr: the input ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    fcn: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback function execution context.\n\n    Examples\n    --------\n    > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n    > function f( v ) { if ( v !== v ) { throw new Error( '...' ); } };\n    > ndforEach( x, f );\n\n    See Also\n    --------\n    ndmap","ndims":"\nndims( x )\n    Returns the number of ndarray dimensions.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    Returns\n    -------\n    n: integer\n        Number of dimensions.\n\n    Examples\n    --------\n    > var n = ndims( ndzeros( [ 3, 3, 3 ] ) )\n    3\n\n    See Also\n    --------\n    array, ndarray, numel, ndarrayShape\n","ndindex":"\nndindex( x[, options] )\n    Wraps a provided array as an ndarray index object.\n\n    ndarray index instances have no explicit functionality; however, they are\n    used by \"fancy\" ndarrays for element retrieval and assignment.\n\n    By default, an instance is invalidated and removed from an internal cache\n    immediately after a consumer resolves the underlying data associated with an\n    instance using the `get` static method. Immediate invalidation and cache\n    removal ensures that references to the underlying ndarray are not the source\n    of memory leaks.\n\n    Because instances leverage an internal cache implementing the Singleton\n    pattern, one must be sure to use the same constructor as consumers. If one\n    uses a different constructor, the consumer will *not* be able to resolve the\n    original wrapped ndarray, as the consumer will attempt to resolve an\n    instance in the wrong internal cache.\n\n    Because non-persisted instances are freed after first use, in order to avoid\n    holding onto memory and to allow garbage collection, one should avoid\n    scenarios in which an instance is never used.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.persist: boolean (optional)\n        Boolean indicating whether to continue persisting an index object after\n        first usage. Default: false.\n\n    options.kind: string (optional)\n        Specifies whether a provided ndarray is a specialized input ndarray\n        \"kind\". This option is only applicable for integer input ndarrays. Must\n        be one of the following:\n\n        - cartesian: a provided input ndarray contains Cartesian indices.\n        - linear: a provided input ndarray contains indices representing\n          locations in linear memory.\n\n        Default: ''.\n\n    Returns\n    -------\n    out: ndindex\n        Index instance.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n\n\nndindex.free( id )\n    Frees the instance associated with a provided identifier.\n\n    Parameters\n    ----------\n    id: string\n        Instance identifier.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an instance was successfully freed.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > ndindex.free( idx.id )\n    <boolean>\n\n\nndindex.get( id )\n    Returns the ndarray associated with the instance having a provided\n    identifier.\n\n    Parameters\n    ----------\n    id: string\n        Instance identifier.\n\n    Returns\n    -------\n    out: Object\n        Object containing ndarray data.\n\n    out.data: ndarray\n        The underlying ndarray associated with the provided identifier.\n\n    out.type: string\n        The type of ndarray index.\n\n    out.dtype: string\n        The data type of the underlying ndarray.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > ndindex.get( idx.id )\n    {...}\n\n\nndindex.cartesianIndex( x[, options] )\n    Returns an ndarray index containing Cartesian indices.\n\n    This is a convenience method for calling `ndindex` with `kind` set to\n    'cartesian'.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.persist: boolean (optional)\n        Boolean indicating whether to continue persisting an index object after\n        first usage. Default: false.\n\n    Returns\n    -------\n    out: ndindex\n        Index instance.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = ndindex.cartesianIndex( x );\n\n\nndindex.linearIndex( x[, options] )\n    Returns an ndarray index for indices representing locations in linear\n    memory.\n\n    This is a convenience method for calling `ndindex` with `kind` set to\n    'linear'.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.persist: boolean (optional)\n        Boolean indicating whether to continue persisting an index object after\n        first usage. Default: false.\n\n    Returns\n    -------\n    out: ndindex\n        Index instance.\n\n    Examples\n    --------\n    > var x = ndempty( [ 5 ], { 'dtype': 'int32' } );\n    > var idx = ndindex.linearIndex( x );\n\n\nndindex.prototype.data\n    Read-only property returning an ndarray view of the underlying index\n    ndarray.\n\n    Returns\n    -------\n    out: ndarray\n        Array data.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.data\n    <ndarray>\n\n\nndindex.prototype.dtype\n    Read-only property returning the underlying data type of the index ndarray.\n\n    Returns\n    -------\n    out: string\n        Array data type.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.dtype\n    'int32'\n\n\nndindex.prototype.id\n    Read-only property returning the unique identifier associated with an\n    instance.\n\n    Returns\n    -------\n    out: string\n        String identifier.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.id\n    <string>\n\n\nndindex.prototype.isCached\n    Read-only property returning a boolean indicating whether an ndarray index\n    is actively cached.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an ndarray index is actively cached.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.isCached\n    true\n\n\nndindex.prototype.kind\n    Read-only property returning the ndarray index kind.\n\n    Returns\n    -------\n    out: string\n        Index kind.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x, { 'kind': 'cartesian' } );\n    > idx.kind\n    'cartesian'\n\n\nndindex.prototype.type\n    Read-only property returning the ndarray index type.\n\n    Returns\n    -------\n    out: string\n        Index type.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.type\n    <string>\n\n\nndindex.prototype.toString()\n    Serializes an instance as a string.\n\n    Returns\n    -------\n    str: string\n        Serialized string.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.toString()\n    <string>\n\n\nndindex.prototype.toJSON()\n    Serializes an instance as a JSON object.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.toJSON()\n    { 'type': 'ndindex', ... }\n\n    See Also\n    --------\n    array, ndarray, FancyArray, ndslice, ndarray2fancy\n","ndindex.free":"\nndindex.free( id )\n    Frees the instance associated with a provided identifier.\n\n    Parameters\n    ----------\n    id: string\n        Instance identifier.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an instance was successfully freed.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > ndindex.free( idx.id )\n    <boolean>","ndindex.get":"\nndindex.get( id )\n    Returns the ndarray associated with the instance having a provided\n    identifier.\n\n    Parameters\n    ----------\n    id: string\n        Instance identifier.\n\n    Returns\n    -------\n    out: Object\n        Object containing ndarray data.\n\n    out.data: ndarray\n        The underlying ndarray associated with the provided identifier.\n\n    out.type: string\n        The type of ndarray index.\n\n    out.dtype: string\n        The data type of the underlying ndarray.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > ndindex.get( idx.id )\n    {...}","ndindex.cartesianIndex":"\nndindex.cartesianIndex( x[, options] )\n    Returns an ndarray index containing Cartesian indices.\n\n    This is a convenience method for calling `ndindex` with `kind` set to\n    'cartesian'.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.persist: boolean (optional)\n        Boolean indicating whether to continue persisting an index object after\n        first usage. Default: false.\n\n    Returns\n    -------\n    out: ndindex\n        Index instance.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = ndindex.cartesianIndex( x );","ndindex.linearIndex":"\nndindex.linearIndex( x[, options] )\n    Returns an ndarray index for indices representing locations in linear\n    memory.\n\n    This is a convenience method for calling `ndindex` with `kind` set to\n    'linear'.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.persist: boolean (optional)\n        Boolean indicating whether to continue persisting an index object after\n        first usage. Default: false.\n\n    Returns\n    -------\n    out: ndindex\n        Index instance.\n\n    Examples\n    --------\n    > var x = ndempty( [ 5 ], { 'dtype': 'int32' } );\n    > var idx = ndindex.linearIndex( x );","ndindex.prototype.data":"\nndindex.prototype.data\n    Read-only property returning an ndarray view of the underlying index\n    ndarray.\n\n    Returns\n    -------\n    out: ndarray\n        Array data.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.data\n    <ndarray>","ndindex.prototype.dtype":"\nndindex.prototype.dtype\n    Read-only property returning the underlying data type of the index ndarray.\n\n    Returns\n    -------\n    out: string\n        Array data type.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.dtype\n    'int32'","ndindex.prototype.id":"\nndindex.prototype.id\n    Read-only property returning the unique identifier associated with an\n    instance.\n\n    Returns\n    -------\n    out: string\n        String identifier.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.id\n    <string>","ndindex.prototype.isCached":"\nndindex.prototype.isCached\n    Read-only property returning a boolean indicating whether an ndarray index\n    is actively cached.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an ndarray index is actively cached.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.isCached\n    true","ndindex.prototype.kind":"\nndindex.prototype.kind\n    Read-only property returning the ndarray index kind.\n\n    Returns\n    -------\n    out: string\n        Index kind.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x, { 'kind': 'cartesian' } );\n    > idx.kind\n    'cartesian'","ndindex.prototype.type":"\nndindex.prototype.type\n    Read-only property returning the ndarray index type.\n\n    Returns\n    -------\n    out: string\n        Index type.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.type\n    <string>","ndindex.prototype.toString":"\nndindex.prototype.toString()\n    Serializes an instance as a string.\n\n    Returns\n    -------\n    str: string\n        Serialized string.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.toString()\n    <string>","ndindex.prototype.toJSON":"\nndindex.prototype.toJSON()\n    Serializes an instance as a JSON object.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.toJSON()\n    { 'type': 'ndindex', ... }\n\n    See Also\n    --------\n    array, ndarray, FancyArray, ndslice, ndarray2fancy","nditerColumnEntries":"\nnditerColumnEntries( x[, options] )\n    Returns an iterator which returns [index, column] pairs for each column in a\n    matrix (or stack of matrices).\n\n    Each returned index is a Cartesian index (i.e., an array of subscripts/\n    dimension indices). A dimension index equal to `null` indicates that all\n    values along the respective dimension are included in the returned ndarray.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    options: Object (optional)\n        Options.\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether returned ndarray views should be read-only.\n        If the input ndarray is read-only, setting this option to `false` raises\n        an exception. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > var it = nditerColumnEntries( x );\n    > var v = it.next().value;\n    > v[ 0 ]\n    [ null, 0 ]\n    > ndarray2array( v[ 1 ] )\n    [ 1, 3 ]\n    > v = it.next().value;\n    > v[ 0 ]\n    [ null, 1 ]\n    > ndarray2array( v[ 1 ] )\n    [ 2, 4 ]\n\n    See Also\n    --------\n    nditerColumns, nditerEntries, nditerRowEntries, ndslice\n","nditerColumns":"\nnditerColumns( x[, options] )\n    Returns an iterator which iterates over each column in a matrix (or stack of\n    matrices).\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray for which to create the iterator.\n\n    options: Object (optional)\n        Options.\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether returned ndarray views should be read-only.\n        If the input ndarray is read-only, setting this option to `false` raises\n        an exception. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > var it = nditerColumns( x );\n    > var v = it.next().value;\n    > ndarray2array( v )\n    [ 1, 3 ]\n    > v = it.next().value;\n    > ndarray2array( v )\n    [ 2, 4 ]\n\n    See Also\n    --------\n    nditerColumnEntries, nditerRows, ndslice\n","nditerEntries":"\nnditerEntries( x[, options] )\n    Returns an iterator which returns [index, value] pairs for each element in a\n    provided ndarray.\n\n    Each returned index is a Cartesian index (i.e., an array of subscripts/\n    dimension indices).\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    options: Object (optional)\n        Options.\n\n    options.order: string (optional)\n        Index iteration order. By default, the returned iterator returns values\n        according to the layout order of the provided array. Accordingly, for\n        row-major input arrays, the last dimension indices increment fastest.\n        For column-major input arrays, the first dimension indices increment\n        fastest. To override the inferred order and ensure that indices\n        increment in a specific manner, regardless of the input array's layout\n        order, explicitly set the iteration order. Note, however, that iterating\n        according to an order which does not match that of the input array may,\n        in some circumstances, result in performance degradation due to cache\n        misses. Must be either 'row-major' or 'column-major'.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > var it = nditerEntries( x );\n    > var v = it.next().value\n    [ [ 0, 0 ], 1 ]\n    > v = it.next().value\n    [ [ 0, 1 ], 2 ]\n\n    See Also\n    --------\n    ndarray, nditerIndices, nditerValues\n","nditerIndices":"\nnditerIndices( shape[, options] )\n    Returns an iterator which returns indices for use indexing into an ndarray\n    having a specified shape.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Input shape.\n\n    options: Object (optional)\n        Options.\n\n    options.order: string (optional)\n        Index iteration order. By default, the returned iterator iterates over\n        the last dimensions first, thus corresponding to iteration over\n        contiguous data stored in row-major order. Must be either 'row-major'\n        or 'column-major'.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > var it = nditerIndices( x.shape );\n    > var v = it.next().value\n    [ 0, 0 ]\n    > v = it.next().value\n    [ 0, 1 ]\n\n    See Also\n    --------\n    ndarray, nditerEntries, nditerValues\n","nditerInterleaveSubarrays":"\nnditerInterleaveSubarrays( arr, ndims )\n    Returns an iterator which iterates over interleaved subarrays.\n\n    For input ndarrays supporting read-only views, the function returns\n    *read-only* views of interleaved subarrays. As input ndarrays may be\n    broadcasted, a view is typically *not* contiguous. As more than one element\n    of a returned view may refer to the same memory location, writing to a view\n    may affect multiple elements. If you need to write to a subarray, copy the\n    subarray before attempting mutation.\n\n    The function throws an error if a provided broadcast-incompatible ndarrays.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    arr: ArrayLike<ndarray>\n        Input ndarrays. All ndarrays must be broadcast-compatible. After\n        broadcasting, each broadcasted input ndarray must have at least\n        `ndims+1` dimensions.\n\n    ndims: integer\n        Number of dimensions to stack after broadcasting.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n    > var it = nditerInterleaveSubarrays( [ x, x ], 2 );\n    > var v = it.next().value;\n    > ndarray2array( v )\n    [ [ 1, 2 ], [ 3, 4 ] ]\n\n    See Also\n    --------\n    nditerSubarrays, ndslice\n","nditerMatrices":"\nnditerMatrices( x[, options] )\n    Returns an iterator which iterates over each matrix in a stack of matrices.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray for which to create the iterator.\n\n    options: Object (optional)\n        Options.\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether returned ndarray views should be read-only.\n        If the input ndarray is read-only, setting this option to `false` raises\n        an exception. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n    > var it = nditerMatrices( x );\n    > var v = it.next().value;\n    > ndarray2array( v )\n    [ [ 1, 2 ], [ 3, 4 ] ]\n\n    See Also\n    --------\n    nditerColumns, nditerMatrixEntries, nditerRows, ndslice\n","nditerMatrixEntries":"\nnditerMatrixEntries( x[, options] )\n    Returns an iterator which returns [index, matrix] pairs for each matrix in a\n    stack of matrices.\n\n    Each returned index is a Cartesian index (i.e., an array of subscripts/\n    dimension indices). A dimension index equal to `null` indicates that all\n    values along the respective dimension are included in the returned ndarray.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    options: Object (optional)\n        Options.\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether returned ndarray views should be read-only.\n        If the input ndarray is read-only, setting this option to `false` raises\n        an exception. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n    > var it = nditerMatrixEntries( x );\n    > var v = it.next().value;\n    > v[ 0 ]\n    [ 0, null, null ]\n    > ndarray2array( v[ 1 ] )\n    [ [ 1, 2 ], [ 3, 4 ] ]\n\n    See Also\n    --------\n    nditerColumnEntries, nditerEntries, nditerMatrices, nditerRowEntries, ndslice\n","nditerRowEntries":"\nnditerRowEntries( x[, options] )\n    Returns an iterator which returns [index, row] pairs for each row in a\n    matrix (or stack of matrices).\n\n    Each returned index is a Cartesian index (i.e., an array of subscripts/\n    dimension indices). A dimension index equal to `null` indicates that all\n    values along the respective dimension are included in the returned ndarray.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    options: Object (optional)\n        Options.\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether returned ndarray views should be read-only.\n        If the input ndarray is read-only, setting this option to `false` raises\n        an exception. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > var it = nditerRowEntries( x );\n    > var v = it.next().value;\n    > v[ 0 ]\n    [ 0, null ]\n    > ndarray2array( v[ 1 ] )\n    [ 1, 2 ]\n    > v = it.next().value;\n    > v[ 0 ]\n    [ 1, null ]\n    > ndarray2array( v[ 1 ] )\n    [ 3, 4 ]\n\n    See Also\n    --------\n    nditerColumnEntries, nditerEntries, nditerRows, ndslice\n","nditerRows":"\nnditerRows( x[, options] )\n    Returns an iterator which iterates over each row in a matrix (or stack of\n    matrices).\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray for which to create the iterator.\n\n    options: Object (optional)\n        Options.\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether returned ndarray views should be read-only.\n        If the input ndarray is read-only, setting this option to `false` raises\n        an exception. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > var it = nditerRows( x );\n    > var v = it.next().value;\n    > ndarray2array( v )\n    [ 1, 2 ]\n    > v = it.next().value;\n    > ndarray2array( v )\n    [ 3, 4 ]\n\n    See Also\n    --------\n    nditerColumns, nditerRowEntries, ndslice\n","nditerSelectDimension":"\nnditerSelectDimension( x, dim[, options] )\n    Returns an iterator which iterates over each view along a specified\n    dimension.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray for which to create the iterator.\n\n    dim: integer\n        Dimension index. If less than zero, the index is resolved relative to\n        the last dimension, with the last dimension corresponding to the value\n        `-1`.\n\n    options: Object (optional)\n        Options.\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether returned ndarray views should be read-only.\n        If the input ndarray is read-only, setting this option to `false` raises\n        an exception. Default: true.\n\n    options.keepdim: boolean (optional)\n        Boolean indicating whether returned views should include the selected\n        dimension as a singleton dimension. Including the selected dimension as\n        a singleton dimension can be useful when wanting to ensure that returned\n        views remain broadcast compatible with the input ndarray. Default:\n        false.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n    > var it = nditerSelectDimension( x, 0 );\n    > var v = it.next().value;\n    > ndarray2array( v )\n    [ [ 1, 2 ], [ 3, 4 ] ]\n\n    See Also\n    --------\n    nditerColumns, nditerMatrices, nditerRows, ndslice\n","nditerStacks":"\nnditerStacks( x, dims[, options] )\n    Returns an iterator which iterates over each subarray in a stack of\n    subarrays according to a list of specified stack dimensions.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray for which to create the iterator. Must have at least\n        `dims.length+1` dimensions.\n\n    dims: Array<integer>\n        Indices of dimensions to stack. If a dimension index is less than zero,\n        the index is resolved relative to the last dimension, with the last\n        dimension corresponding to the value `-1`. The list of indices must be\n        unique and resolve to dimension indices sorted in ascending order.\n\n    options: Object (optional)\n        Options.\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether returned ndarray views should be read-only.\n        If the input ndarray is read-only, setting this option to `false` raises\n        an exception. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n    > var it = nditerStacks( x, [ 1, 2 ] );\n    > var v = it.next().value;\n    > ndarray2array( v )\n    [ [ 1, 2 ], [ 3, 4 ] ]\n\n    See Also\n    --------\n    nditerColumns, nditerMatrices, nditerRows, nditerSubarrays, ndslice\n","nditerSubarrays":"\nnditerSubarrays( x, ndims[, options] )\n    Returns an iterator which iterates over each subarray in a stack of\n    subarrays.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray for which to create the iterator. Must have at least\n        `ndims+1` dimensions.\n\n    ndims: integer\n        Number of dimensions to stack.\n\n    options: Object (optional)\n        Options.\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether returned ndarray views should be read-only.\n        If the input ndarray is read-only, setting this option to `false` raises\n        an exception. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n    > var it = nditerSubarrays( x, 2 );\n    > var v = it.next().value;\n    > ndarray2array( v )\n    [ [ 1, 2 ], [ 3, 4 ] ]\n\n    See Also\n    --------\n    nditerColumns, nditerMatrices, nditerRows, nditerStacks, ndslice\n","nditerValues":"\nnditerValues( x[, options] )\n    Returns an iterator which returns individual elements from a provided\n    ndarray.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    options: Object (optional)\n        Options.\n\n    options.order: string (optional)\n        Index iteration order. By default, the returned iterator returns values\n        according to the layout order of the provided array. Accordingly, for\n        row-major input arrays, the last dimension indices increment fastest.\n        For column-major input arrays, the first dimension indices increment\n        fastest. To override the inferred order and ensure that indices\n        increment in a specific manner, regardless of the input array's layout\n        order, explicitly set the iteration order. Note, however, that iterating\n        according to an order which does not match that of the input array may,\n        in some circumstances, result in performance degradation due to cache\n        misses. Must be either 'row-major' or 'column-major'.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > var it = nditerValues( x );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    ndarray, nditerEntries, nditerIndices\n","ndmap":"\nndmap( x[, options], fcn[, thisArg] )\n    Applies a callback function to elements in an input ndarray and assigns\n    results to elements in a new output ndarray.\n\n    The callback function is provided the following arguments:\n\n    - value: current array element.\n    - indices: current array element indices.\n    - arr: the input ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.dtype: string (optional)\n        Output ndarray data type. Overrides using the input array's inferred\n        data type.\n\n    fcn: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback function execution context.\n\n    Examples\n    --------\n    > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n    > function f( v ) { return v*10.0; };\n    > var y = ndmap( x, f );\n    > ndarray2array( y )\n    [ [ 10.0, 20.0 ], [ 30.0, 40.0 ] ]\n\n    See Also\n    --------\n    ndfilter, ndfilterMap, ndforEach, ndslice","ndreject":"\nndreject( x[, options], predicate[, thisArg] )\n    Returns a shallow copy of an ndarray containing only those elements which\n    fail a test implemented by a predicate function.\n\n    The predicate function is provided the following arguments:\n\n    - value: current array element.\n    - indices: current array element indices.\n    - arr: the input ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.dtype: string (optional)\n        Output ndarray data type. Overrides using the input array's inferred\n        data type.\n\n    options.order: string (optional)\n        Index iteration order. By default, the function iterates over elements\n        according to the layout order of the provided array. Accordingly, for\n        row-major input arrays, the last dimension indices increment fastest.\n        For column-major input arrays, the first dimension indices increment\n        fastest. To override the inferred order and ensure that indices\n        increment in a specific manner, regardless of the input array's layout\n        order, explicitly set the iteration order. Note, however, that iterating\n        according to an order which does not match that of the input array may,\n        in some circumstances, result in performance degradation due to cache\n        misses. Must be either 'row-major' or 'column-major'.\n\n    predicate: Function\n        Predicate function.\n\n    thisArg: any (optional)\n        Predicate function execution context.\n\n    Examples\n    --------\n    > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n    > function f( v ) { return v <= 2.0; };\n    > var y = ndreject( x, f );\n    > ndarray2array( y )\n    [ 3.0, 4.0 ]\n\n    See Also\n    --------\n    ndfilter, ndfilterMap, ndmap, ndslice","ndslice":"\nndslice( x, ...s[, options] )\n    Returns a read-only view of an input ndarray.\n\n    The function supports three (mutually exclusive) means of providing slice\n    arguments:\n\n    1. Providing a single MultiSlice object.\n    2. Providing a single array containing slice arguments.\n    3. Providing slice arguments as separate arguments.\n\n    An individual slice argument must be either a Slice, an integer, null, or\n    undefined.\n\n    In all cases, the number of slice dimensions must match the number of array\n    dimensions.\n\n    If providing a MultiSlice object or an array of slice arguments, no other\n    slice arguments should be provided.\n\n    Mixing function invocation styles (e.g., providing multiple MultiSlice\n    objects or providing an array of slice arguments followed by additional\n    slice arguments) is not supported.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    s: ...MultiSlice|Slice|null|undefined|integer|ArrayLike\n        Slice arguments.\n\n    options: Object (optional)\n        Options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking.\n        Default: true.\n\n    Returns\n    -------\n    out: ndarray\n        Output array view.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n    <ndarray>\n    > x.shape\n    [ 2, 2 ]\n    > var s = new MultiSlice( null, 1 )\n    <MultiSlice>\n    > var y = ndslice( x, s )\n    <ndarray>\n    > y.shape\n    [ 2 ]\n    > ndarray2array( y )\n    [ 2, 4 ]\n\n    See Also\n    --------\n    array, ndat, ndarray, ndsliceAssign, ndsliceDimension\n","ndsliceAssign":"\nndsliceAssign( x, y, ...s[, options] )\n    Assigns element values from a broadcasted input ndarray to corresponding\n    elements in an output ndarray view.\n\n    The function supports three (mutually exclusive) means of providing slice\n    arguments:\n\n    1. Providing a single MultiSlice object.\n    2. Providing a single array containing slice arguments.\n    3. Providing slice arguments as separate arguments.\n\n    An individual slice argument must be either a Slice, an integer, null, or\n    undefined.\n\n    In all cases, the number of slice dimensions must match the number of output\n    array dimensions.\n\n    If providing a MultiSlice object or an array of slice arguments, no other\n    slice arguments should be provided.\n\n    Mixing function invocation styles (e.g., providing multiple MultiSlice\n    objects or providing an array of slice arguments followed by additional\n    slice arguments) is not supported.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array. The input array must be broadcast compatible with the\n        output array view and must have a data type which can be safely cast to\n        the output array data type. Floating-point data types (both real and\n        complex) are allowed to downcast to a lower precision data type of the\n        same kind (e.g., element values from a 'float64' input array can be\n        assigned to corresponding elements in a 'float32' output array).\n\n    y: ndarray\n        Output array. The output array must be writable.\n\n    s: ...MultiSlice|Slice|null|undefined|integer|ArrayLike\n        Slice arguments.\n\n    options: Object (optional)\n        Options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking.\n        Default: true.\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var y = ndzeros( [ 2, 2 ] )\n    <ndarray>\n    > var x = scalar2ndarray( 3.0 )\n    <ndarray>\n    > var s = new MultiSlice( null, 1 )\n    <MultiSlice>\n    > var out = ndsliceAssign( x, y, s )\n    <ndarray>\n    > var bool = ( out === y )\n    true\n    > ndarray2array( y )\n    [ [ 0.0, 3.0 ], [ 0.0, 3.0 ] ]\n\n    See Also\n    --------\n    array, ndarray, ndslice\n","ndsliceDimension":"\nndsliceDimension( x, dim, slice[, options] )\n    Returns a read-only view of an input ndarray when sliced along a specified\n    dimension.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    dim: integer\n        Index of dimension to slice. If less than zero, the index is resolved\n        relative to the last dimension, with the last dimension corresponding to\n        the value `-1`.\n\n    slice: Slice|integer|null|undefined\n        Slice object or an integer. If provided `null` or `undefined`, the\n        returned view includes all elements along a specified dimension. If\n        provided an integer less than zero, the corresponding element along the\n        specified dimension is resolved relative to the last element along that\n        dimension. For negative integers, the last element corresponds to the\n        value `-1`.\n\n    options: Object (optional)\n        Options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking.\n        Default: true.\n\n    Returns\n    -------\n    out: ndarray\n        Output array view.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n    <ndarray>\n    > x.shape\n    [ 2, 2 ]\n    > var y = ndsliceDimension( x, 1, 1 )\n    <ndarray>\n    > y.shape\n    [ 2 ]\n    > ndarray2array( y )\n    [ 2, 4 ]\n\n    See Also\n    --------\n    array, ndarray, ndslice, ndsliceDimensionFrom, ndsliceDimensionTo\n","ndsliceDimensionFrom":"\nndsliceDimensionFrom( x, dim, start[, options] )\n    Returns a read-only shifted view of an input ndarray along a specified\n    dimension.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    dim: integer\n        Index of dimension to slice. If less than zero, the index is resolved\n        relative to the last dimension, with the last dimension corresponding to\n        the value `-1`.\n\n    start: integer\n        Starting index (inclusive). If less than zero, the corresponding element\n        along the specified dimension is resolved relative to the last element\n        along that dimension. For negative integers, the last element\n        corresponds to the value `-1`.\n\n    options: Object (optional)\n        Options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking.\n        Default: true.\n\n    Returns\n    -------\n    out: ndarray\n        Output array view.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n    <ndarray>\n    > x.shape\n    [ 2, 2 ]\n    > var y = ndsliceDimensionFrom( x, 1, 1 )\n    <ndarray>\n    > y.shape\n    [ 2, 1 ]\n    > ndarray2array( y )\n    [ [ 2 ], [ 4 ] ]\n\n    See Also\n    --------\n    array, ndarray, ndslice, ndsliceDimension, ndsliceDimensionTo, ndsliceFrom\n","ndsliceDimensionTo":"\nndsliceDimensionTo( x, dim, stop[, options] )\n    Returns a read-only truncated view of an input ndarray along a specified\n    dimension.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    dim: integer\n        Index of dimension to slice. If less than zero, the index is resolved\n        relative to the last dimension, with the last dimension corresponding to\n        the value `-1`.\n\n    stop: integer\n        Ending index (exclusive). If less than zero, the corresponding element\n        along the specified dimension is resolved relative to the last element\n        along that dimension. For negative integers, the last element\n        corresponds to the value `-1`.\n\n    options: Object (optional)\n        Options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking.\n        Default: true.\n\n    Returns\n    -------\n    out: ndarray\n        Output array view.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n    <ndarray>\n    > x.shape\n    [ 2, 2 ]\n    > var y = ndsliceDimensionTo( x, 1, 1 )\n    <ndarray>\n    > y.shape\n    [ 2, 1 ]\n    > ndarray2array( y )\n    [ [ 1 ], [ 3 ] ]\n\n    See Also\n    --------\n    array, ndarray, ndslice, ndsliceDimension, ndsliceDimensionFrom, ndsliceTo\n","ndsliceFrom":"\nndsliceFrom( x, ...start[, options] )\n    Returns a read-only shifted view of an input ndarray.\n\n    The function supports two (mutually exclusive) means of providing starting\n    indices:\n\n    1. Providing a single array containing start arguments.\n    2. Providing start arguments as separate arguments.\n\n    An individual start argument must be either an integer, null, or undefined.\n\n    In all cases, the number of start indices must match the number of array\n    dimensions.\n\n    If providing an array of start arguments, no other start arguments should be\n    provided.\n\n    Mixing function invocation styles (e.g., providing an array of start\n    arguments followed by additional start arguments) is not supported.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    start: ...null|void|integer\n        Starting indices (inclusive). If an element is either `null` or\n        `undefined`, the function returns a view containing all elements along\n        that dimension. A negative integer indicates to resolve a starting index\n        relative to the last element along a corresponding dimension, with the\n        last element having index `-1`.\n\n    options: Object (optional)\n        Options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking.\n        Default: true.\n\n    Returns\n    -------\n    out: ndarray\n        Output array view.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n    <ndarray>\n    > x.shape\n    [ 2, 2 ]\n    > var y = ndsliceFrom( x, 0, 1 )\n    <ndarray>\n    > y.shape\n    [ 2, 1 ]\n    > ndarray2array( y )\n    [ [ 2 ], [ 4 ] ]\n\n    See Also\n    --------\n    array, ndarray, ndslice, ndsliceDimensionFrom, ndsliceTo\n","ndsliceTo":"\nndsliceTo( x, ...stop[, options] )\n    Returns a read-only truncated view of an input ndarray.\n\n    The function supports two (mutually exclusive) means of providing ending\n    indices:\n\n    1. Providing a single array containing stop arguments.\n    2. Providing stop arguments as separate arguments.\n\n    An individual stop argument must be either an integer, null, or undefined.\n\n    In all cases, the number of stop indices must match the number of array\n    dimensions.\n\n    If providing an array of stop arguments, no other stop arguments should be\n    provided.\n\n    Mixing function invocation styles (e.g., providing an array of stop\n    arguments followed by additional stop arguments) is not supported.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    stop: ...null|void|integer\n        Ending indices (exclusive). If an ending index is either `null` or\n        `undefined`, the function returns a view containing all elements along\n        that dimension. A negative integer indicates to resolve an ending index\n        relative to the last element along a corresponding dimension, with the\n        last element having index `-1`.\n\n    options: Object (optional)\n        Options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking.\n        Default: true.\n\n    Returns\n    -------\n    out: ndarray\n        Output array view.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n    <ndarray>\n    > x.shape\n    [ 2, 2 ]\n    > var y = ndsliceTo( x, 1, 1 )\n    <ndarray>\n    > y.shape\n    [ 1, 1 ]\n    > ndarray2array( y )\n    [ [ 1 ] ]\n\n    See Also\n    --------\n    array, ndarray, ndslice, ndsliceDimensionTo, ndsliceFrom\n","ndzeros":"\nndzeros( shape[, options] )\n    Returns a zero-filled ndarray having a specified shape and data type.\n\n    Parameters\n    ----------\n    shape: ArrayLikeObject<integer>|integer\n        Array shape.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Underlying data type. Must be a numeric data type or \"generic\". Default:\n        'float64'.\n\n    options.order: string (optional)\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran-style). Default: 'row-major'.\n\n    options.mode: string (optional)\n        Specifies how to handle indices which exceed array dimensions. If equal\n        to 'throw', an ndarray instance throws an error when an index exceeds\n        array dimensions. If equal to 'normalize', an ndarray instance\n        normalizes negative indices and throws an error when an index exceeds\n        array dimensions. If equal to 'wrap', an ndarray instance wraps around\n        indices exceeding array dimensions using modulo arithmetic. If equal to\n        'clamp', an ndarray instance sets an index exceeding array dimensions\n        to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n    options.submode: Array<string> (optional)\n        Specifies how to handle subscripts which exceed array dimensions. If a\n        mode for a corresponding dimension is equal to 'throw', an ndarray\n        instance throws an error when a subscript exceeds array dimensions. If\n        equal to 'normalize', an ndarray instance normalizes negative\n        subscripts and throws an error when a subscript exceeds array\n        dimensions. If equal to 'wrap', an ndarray instance wraps around\n        subscripts exceeding array dimensions using modulo arithmetic. If equal\n        to 'clamp', an ndarray instance sets a subscript exceeding array\n        dimensions to either `0` (minimum index) or the maximum index. If the\n        number of modes is fewer than the number of dimensions, the function\n        recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether an array should be read-only. Default: false.\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var arr = ndzeros( [ 2, 2 ] )\n    <ndarray>\n    > var sh = arr.shape\n    [ 2, 2 ]\n    > var dt = arr.dtype\n    'float64'\n\n    See Also\n    --------\n    ndempty, ndzerosLike\n","ndzerosLike":"\nndzerosLike( x[, options] )\n    Returns a zero-filled ndarray having the same shape and data type as a\n    provided input ndarray.\n\n    The function infers the following attributes from the input array:\n\n    - shape: array shape.\n    - dtype: underlying array data type.\n    - order: whether the array order is row-major (C-style) or column-major\n      (Fortran-style).\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    options: Object (optional)\n        Options.\n\n    options.shape: ArrayLikeObject<integer>|integer (optional)\n        Array shape. Overrides the input array's inferred shape.\n\n    options.dtype: string (optional)\n        Array data type. Overrides the input array's inferred data type.\n\n    options.order: string (optional)\n        Array order (either 'row-major' (C-style) or 'column-major' (Fortran-\n        style)). Overrides the input array's inferred order.\n\n    options.mode: string (optional)\n        Specifies how to handle indices which exceed array dimensions. If equal\n        to 'throw', an ndarray instance throws an error when an index exceeds\n        array dimensions. If equal to 'normalize', an ndarray instance\n        normalizes negative indices and throws an error when an index exceeds\n        array dimensions. If equal to 'wrap', an ndarray instance wraps around\n        indices exceeding array dimensions using modulo arithmetic. If equal to\n        'clamp', an ndarray instance sets an index exceeding array dimensions\n        to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n    options.submode: Array<string> (optional)\n        Specifies how to handle subscripts which exceed array dimensions. If a\n        mode for a corresponding dimension is equal to 'throw', an ndarray\n        instance throws an error when a subscript exceeds array dimensions. If\n        equal to 'normalize', an ndarray instance normalizes negative\n        subscripts and throws an error when a subscript exceeds array\n        dimensions. If equal to 'wrap', an ndarray instance wraps around\n        subscripts exceeding array dimensions using modulo arithmetic. If equal\n        to 'clamp', an ndarray instance sets a subscript exceeding array\n        dimensions to either `0` (minimum index) or the maximum index. If the\n        number of modes is fewer than the number of dimensions, the function\n        recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether an array should be read-only. Default: false.\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n    <ndarray>\n    > var sh = x.shape\n    [ 2, 2 ]\n    > var dt = x.dtype\n    'float64'\n    > var y = ndzerosLike( x )\n    <ndarray>\n    > sh = y.shape\n    [ 2, 2 ]\n    > dt = y.dtype\n    'float64'\n\n    See Also\n    --------\n    ndemptyLike, ndzeros\n","nextGraphemeClusterBreak":"\nnextGraphemeClusterBreak( str[, fromIndex] )\n    Returns the next extended grapheme cluster break in a string after a\n    specified position.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    fromIndex: integer (optional)\n        Position. Default: 0.\n\n    Returns\n    -------\n    out: integer\n        Next extended grapheme cluster break position.\n\n    Examples\n    --------\n    > var out = nextGraphemeClusterBreak( 'last man standing', 4 )\n    5\n    > out = nextGraphemeClusterBreak( 'presidential election', 8 )\n    9\n    > out = nextGraphemeClusterBreak( 'अनुच्छेद', 1 )\n    3\n    > out = nextGraphemeClusterBreak( '🌷' )\n    -1\n\n    See Also\n    --------\n    numGraphemeClusters, prevGraphemeClusterBreak","nextTick":"\nnextTick( clbk[, ...args] )\n    Adds a callback to the \"next tick queue\".\n\n    The queue is fully drained after the current operation on the JavaScript\n    stack runs to completion and before the event loop is allowed to continue.\n\n    Parameters\n    ----------\n    clbk: Function\n        Callback to invoke.\n\n    ...args: any (optional)\n        Arguments to provide to the callback upon invocation.\n\n    Examples\n    --------\n    > function f() { console.log( 'beep' ); };\n    > nextTick( f )\n\n","NIGHTINGALES_ROSE":"\nNIGHTINGALES_ROSE()\n    Returns data for Nightingale's famous polar area diagram.\n\n    Returns\n    -------\n    out: Array<Object>\n        Nightingale's data.\n\n    Examples\n    --------\n    > var data = NIGHTINGALES_ROSE()\n    [{...}, {...}, ...]\n\n    References\n    ----------\n    - Nightingale, Florence. 1859. *A contribution to the sanitary history of\n    the British army during the late war with Russia*. London, United Kingdom:\n    John W. Parker and Son.<https://curiosity.lib.harvard.edu/contagion/\n    catalog/36-990101646750203941>.\n\n","NINF":"\nNINF\n    Double-precision floating-point negative infinity.\n\n    Examples\n    --------\n    > NINF\n    -Infinity\n\n    See Also\n    --------\n    FLOAT16_NINF, FLOAT32_NINF, PINF\n","NODE_VERSION":"\nNODE_VERSION\n    Node version.\n\n    Examples\n    --------\n    > NODE_VERSION\n    <string>\n\n","none":"\nnone( collection )\n    Tests whether all elements in a collection are falsy.\n\n    The function immediately returns upon encountering a truthy value.\n\n    If provided an empty collection, the function returns `true`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if all elements are falsy; otherwise, the\n        function returns `false`.\n\n    Examples\n    --------\n    > var arr = [ 0, 0, 0, 0, 0 ];\n    > var bool = none( arr )\n    true\n\n    See Also\n    --------\n    any, every, forEach, noneBy, some\n","noneBy":"\nnoneBy( collection, predicate[, thisArg ] )\n    Tests whether all elements in a collection fail a test implemented by a\n    predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    The function immediately returns upon encountering a truthy return value.\n\n    If provided an empty collection, the function returns `true`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns a falsy\n        value for all elements; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function negative( v ) { return ( v < 0 ); };\n    > var arr = [ 1, 2, 3, 4 ];\n    > var bool = noneBy( arr, negative )\n    true\n\n    See Also\n    --------\n    anyBy, everyBy, forEach, none, noneByRight, someBy\n","noneByAsync":"\nnoneByAsync( collection, [options,] predicate, done )\n    Tests whether all elements in a collection fail a test implemented by a\n    predicate function.\n\n    When invoked, the predicate function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If the\n    predicate function accepts two arguments, the predicate function is\n    provided:\n\n    - value\n    - next\n\n    If the predicate function accepts three arguments, the predicate function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other predicate function signature, the predicate function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - result: test result.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    The function immediately returns upon encountering a truthy `result` value\n    and calls the `done` callback with `null` as the first argument and `false`\n    as the second argument.\n\n    If all elements fail, the function calls the `done` callback with `null` as\n    the first argument and `true` as the second argument.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > noneByAsync( arr, predicate, done )\n    1000\n    2500\n    3000\n    true\n\n    // Limit number of concurrent invocations:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 3000, 2500, 1000 ];\n    > noneByAsync( arr, opts, predicate, done )\n    2500\n    3000\n    1000\n    true\n\n    // Process sequentially:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 3000, 2500, 1000 ];\n    > noneByAsync( arr, opts, predicate, done )\n    3000\n    2500\n    1000\n    true\n\n\nnoneByAsync.factory( [options,] predicate )\n    Returns a function which tests whether all elements in a collection fail a\n    test implemented by a predicate function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = noneByAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n\n    See Also\n    --------\n    anyByAsync, everyByAsync, forEachAsync, noneBy, noneByRightAsync, someByAsync\n","noneByAsync.factory":"\nnoneByAsync.factory( [options,] predicate )\n    Returns a function which tests whether all elements in a collection fail a\n    test implemented by a predicate function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = noneByAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n\n    See Also\n    --------\n    anyByAsync, everyByAsync, forEachAsync, noneBy, noneByRightAsync, someByAsync","noneByRight":"\nnoneByRight( collection, predicate[, thisArg ] )\n    Tests whether all elements in a collection fail a test implemented by a\n    predicate function, iterating from right to left.\n\n    The predicate function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    The function immediately returns upon encountering a truthy return value.\n\n    If provided an empty collection, the function returns `true`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns a falsy\n        value for all elements; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function positive( v ) { return ( v > 0 ); };\n    > var arr = [ -1, -2, -3, -4 ];\n    > var bool = noneByRight( arr, positive )\n    true\n\n    See Also\n    --------\n    anyByRight, everyByRight, forEachRight, none, noneBy, someByRight\n","noneByRightAsync":"\nnoneByRightAsync( collection, [options,] predicate, done )\n    Tests whether all elements in a collection fail a test implemented by a\n    predicate function, iterating from right to left.\n\n    When invoked, the predicate function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If the\n    predicate function accepts two arguments, the predicate function is\n    provided:\n\n    - value\n    - next\n\n    If the predicate function accepts three arguments, the predicate function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other predicate function signature, the predicate function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - result: test result.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    The function immediately returns upon encountering a truthy `result` value\n    and calls the `done` callback with `null` as the first argument and `false`\n    as the second argument.\n\n    If all elements fail, the function calls the `done` callback with `null` as\n    the first argument and `true` as the second argument.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > noneByRightAsync( arr, predicate, done )\n    1000\n    2500\n    3000\n    true\n\n    // Limit number of concurrent invocations:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 1000, 2500, 3000 ];\n    > noneByRightAsync( arr, opts, predicate, done )\n    2500\n    3000\n    1000\n    true\n\n    // Process sequentially:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 1000, 2500, 3000 ];\n    > noneByRightAsync( arr, opts, predicate, done )\n    3000\n    2500\n    1000\n    true\n\n\nnoneByRightAsync.factory( [options,] predicate )\n    Returns a function which tests whether all elements in a collection fail a\n    test implemented by a predicate function, iterating from right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = noneByRightAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n\n    See Also\n    --------\n    anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByAsync, noneByRight, someByRightAsync\n","noneByRightAsync.factory":"\nnoneByRightAsync.factory( [options,] predicate )\n    Returns a function which tests whether all elements in a collection fail a\n    test implemented by a predicate function, iterating from right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = noneByRightAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n\n    See Also\n    --------\n    anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByAsync, noneByRight, someByRightAsync","noneInBy":"\nnoneInBy( object, predicate[, thisArg ] )\n    Tests whether every property in an object fails a test implemented by a\n    predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: object value.\n    - key: object key.\n    - object: the input object.\n\n    The function immediately returns upon encountering a truthy return value.\n\n    If provided an empty object, the function returns `true`.\n\n    Parameters\n    ----------\n    object: Object\n        Input object over which to iterate.\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns a falsy\n        value for all properties; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function negative( v ) { return ( v < 0 ); };\n    > var obj = { 'a': 1, 'b': 2, 'c': 4 };\n    > var bool = noneInBy( obj, negative )\n    true\n\n    See Also\n    --------\n    anyInBy, everyInBy, forIn, noneBy, someInBy\n","nonEnumerableProperties":"\nnonEnumerableProperties( value )\n    Returns an array of an object's own non-enumerable property names and\n    symbols.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    props: Array\n        List of an object's own non-enumerable properties.\n\n    Examples\n    --------\n    > var obj = {};\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.writable = false;\n    > desc.value = 'boop';\n    > defineProperty( obj, 'beep', desc );\n    > var props = nonEnumerableProperties( obj )\n    [ 'beep' ]\n\n    See Also\n    --------\n    enumerableProperties, inheritedNonEnumerableProperties, nonEnumerablePropertiesIn, properties\n","nonEnumerablePropertiesIn":"\nnonEnumerablePropertiesIn( value )\n    Returns an array of an object's own and inherited non-enumerable property\n    names and symbols.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    props: Array\n        List of an object's own and inherited non-enumerable property names and\n        symbols.\n\n    Examples\n    --------\n    > var props = nonEnumerablePropertiesIn( [] )\n\n    See Also\n    --------\n    enumerablePropertiesIn, inheritedNonEnumerableProperties, nonEnumerableProperties, propertiesIn\n","nonEnumerablePropertyNames":"\nnonEnumerablePropertyNames( value )\n    Returns an array of an object's own non-enumerable property names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's own non-enumerable property names.\n\n    Examples\n    --------\n    > var obj = {};\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.writable = true;\n    > desc.value = 'boop';\n    > defineProperty( obj, 'beep', desc );\n    > var keys = nonEnumerablePropertyNames( obj )\n    e.g., [ 'beep', ... ]\n\n    See Also\n    --------\n    objectKeys, inheritedNonEnumerablePropertyNames, nonEnumerablePropertyNamesIn, nonEnumerablePropertySymbols, propertyNames\n","nonEnumerablePropertyNamesIn":"\nnonEnumerablePropertyNamesIn( value )\n    Returns an array of an object's own and inherited non-enumerable property\n    names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's own and inherited non-enumerable property names.\n\n    Examples\n    --------\n    > var obj = {};\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.writable = true;\n    > desc.value = 'boop';\n    > defineProperty( obj, 'beep', desc );\n    > var keys = nonEnumerablePropertyNamesIn( obj )\n    e.g., [ 'beep', ... ]\n\n    See Also\n    --------\n    keysIn, inheritedNonEnumerablePropertyNames, nonEnumerablePropertyNames, propertyNamesIn\n","nonEnumerablePropertySymbols":"\nnonEnumerablePropertySymbols( value )\n    Returns an array of an object's own non-enumerable symbol properties.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's own non-enumerable symbol properties.\n\n    Examples\n    --------\n    > var obj = {};\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.writable = true;\n    > desc.value = 'boop';\n    > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n    > defineProperty( obj, sym, desc );\n    > var symbols = nonEnumerablePropertySymbols( obj )\n\n    See Also\n    --------\n    enumerablePropertySymbols, inheritedNonEnumerablePropertySymbols, nonEnumerablePropertyNames, nonEnumerablePropertySymbolsIn, propertySymbols\n","nonEnumerablePropertySymbolsIn":"\nnonEnumerablePropertySymbolsIn( value )\n    Returns an array of an object's own and inherited non-enumerable symbol\n    properties.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's own and inherited non-enumerable symbol properties.\n\n    Examples\n    --------\n    > var obj = {};\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.writable = true;\n    > desc.value = 'boop';\n    > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n    > defineProperty( obj, sym, desc );\n    > var symbols = nonEnumerablePropertySymbolsIn( obj )\n\n    See Also\n    --------\n    enumerablePropertySymbolsIn, inheritedNonEnumerablePropertySymbols, nonEnumerablePropertyNamesIn, nonEnumerablePropertySymbols, propertySymbolsIn\n","noneOwnBy":"\nnoneOwnBy( object, predicate[, thisArg ] )\n    Tests whether every own property of an object fails a test implemented\n    by a predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: property value.\n    - index: property key.\n    - object: the input object.\n\n    The function immediately returns upon encountering a truthy return value.\n\n    If provided an empty object, the function returns `true`.\n\n    Parameters\n    ----------\n    object: Object\n        Input object.\n\n    predicate: Function\n        Test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns a falsy\n        value for all own properties; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function isUnderage( v ) { return ( v < 18 ); };\n    > var obj = { 'a': 11, 'b': 12, 'c': 22 };\n    > var bool = noneOwnBy( obj, isUnderage )\n    false\n\n    See Also\n    --------\n    anyOwnBy, everyOwnBy, forOwn, noneBy, someOwnBy\n","nonIndexKeys":"\nnonIndexKeys( obj )\n    Returns an array of an object's own enumerable property names which are not\n    integer indices.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    obj: any\n        Input value.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's own enumerable property names.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; this[0] = 3.14; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var keys = nonIndexKeys( obj )\n    e.g., [ 'beep' ]\n\n    See Also\n    --------\n    objectEntries, objectKeys, objectValues\n","noop":"\nnoop()\n    A function which does nothing.\n\n    Examples\n    --------\n    > noop();\n\n","now":"\nnow()\n    Returns the time in seconds since the epoch.\n\n    The Unix epoch is 00:00:00 UTC on 1 January 1970.\n\n    Returns\n    -------\n    out: integer\n        Time in seconds since the epoch.\n\n    Examples\n    --------\n    > var ts = now()\n    <number>\n\n","NUM_CPUS":"\nNUM_CPUS\n    Number of CPUs.\n\n    In browser environments, the number of CPUs is determined by querying the\n    hardware concurrency API.\n\n    In Node.js environments, the number of CPUs is determined via the `os`\n    module.\n\n    Examples\n    --------\n    > NUM_CPUS\n    <number>\n\n","num2words":"\nnum2words( value[, options] )\n    Converts a number to a word representation.\n\n    Parameters\n    ----------\n    value: integer\n        Input value.\n\n    options: Object (optional)\n        Options.\n\n    options.lang: string (optional)\n        Language code. Supported languages:\n\n        - en: English.\n        - de: German.\n\n        Default: `'en'`.\n\n    Returns\n    -------\n    out: string\n        Word representation of number.\n\n    Examples\n    --------\n    > var out = num2words( 123 )\n    'one hundred twenty-three'\n\n    > out = num2words( 16.31 )\n    'sixteen point three one'\n\n    > out = num2words( 123, { 'lang': 'de' } )\n    'einhundertdreiundzwanzig'\n\n","Number":"\nNumber( value )\n    Returns a Number object.\n\n    This constructor should be used sparingly. Always prefer number primitives.\n\n    Parameters\n    ----------\n    value: number\n        Value to wrap in a Number object.\n\n    Returns\n    -------\n    out: Number\n        Number object.\n\n    Examples\n    --------\n    > var v = new Number( 5 )\n    <Number>\n\n","numel":"\nnumel( x )\n    Returns the number of elements in an ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    Returns\n    -------\n    n: integer\n        Number of elements.\n\n    Examples\n    --------\n    > var n = numel( ndzeros( [ 3, 3, 3 ] ) )\n    27\n\n    See Also\n    --------\n    array, ndarray, numelDimension\n","numelDimension":"\nnumelDimension( x, dim )\n    Returns the size (i.e., number of elements) of a specified dimension for a\n    provided ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    dim: integer\n        Dimension index. If less than zero, the index is resolved relative to\n        the last dimension, with the last dimension corresponding to the value\n        `-1`.\n\n    Returns\n    -------\n    out: integer\n        Dimension size.\n\n    Examples\n    --------\n    > var out = numelDimension( ndzeros( [ 4, 2, 3 ] ), 0 )\n    4\n\n    See Also\n    --------\n    array, ndarray, numel\n","numGraphemeClusters":"\nnumGraphemeClusters( str )\n    Returns the number of grapheme clusters in a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Number of grapheme clusters.\n\n    Examples\n    --------\n    > var out = numGraphemeClusters( 'beep' )\n    4\n    > out = numGraphemeClusters( '🌷' )\n    1\n\n    See Also\n    --------\n    nextGraphemeClusterBreak\n","Object":"\nObject( value )\n    Returns an object.\n\n    If provided `null` or `undefined`, the function returns an empty object.\n\n    If provided an existing object, the function returns the input value\n    unchanged.\n\n    Otherwise, if provided any other value (e.g., a number, string, etc), the\n    function will return an object of the corresponding type.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    out: Object\n        Output object.\n\n    Examples\n    --------\n    > var o = new Object( null )\n    {}\n    > o = new Object( 5.0 )\n    <Number>\n    > o = new Object( 'beep' )\n    <String>\n\nObject.assign( target, ...sources )\n    Assigns enumerable and own properties from source objects to a target\n    object.\n\n    Parameters\n    ----------\n    target: Object\n        Target object.\n\n    sources: ...Object\n        Source objects.\n\n    Returns\n    -------\n    out: Object\n        Target object.\n\n    Examples\n    --------\n    > var o = Object.assign( {}, { 'a': 1 }, { 'b': 2 } )\n    { 'a': 1, 'b': 2 }\n\nObject.create( prototype, properties )\n    Creates a new object with a specified prototype object and properties.\n\n    Parameters\n    ----------\n    prototype: Object\n        Prototype object.\n\n    properties: Object\n        Properties object.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > var o = Object.create( {}, { 'a': { 'value': 1 } } )\n    { 'a': 1 }\n\nObject.defineProperties( obj, properties )\n    Defines properties for an object.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    properties: Object\n        Properties object.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.defineProperties( {}, { 'a': { 'value': 1 } } )\n    { 'a': 1 }\n\nObject.defineProperty( obj, key, descriptor )\n    Defines a property for an object.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    key: string\n        Property key.\n\n    descriptor: Object\n        Property descriptor.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.defineProperty( {}, 'a', {\n        'value': 1,\n        'enumerable': true,\n        'configurable': true,\n        'writable': false\n    })\n    { 'a': 1 }\n\nObject.entries( obj )\n    Returns an array of an object's own enumerable string-keyed property\n    [key, value] pairs.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Array\n        Array of [key, value] pairs.\n\n    Examples\n    --------\n    > var o = Object.entries( { 'a': 1, 'b': 2 } )\n    [ [ 'a', 1 ], [ 'b', 2 ] ]\n\nObject.freeze( obj )\n    Freezes an object.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.freeze( { 'a': 1 } )\n    { 'a': 1 }\n\nObject.getOwnPropertyDescriptor( obj, key )\n    Returns an object's own property descriptor.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    key: string\n        Property key.\n\n    Returns\n    -------\n    out: Object\n        Property descriptor.\n\n    Examples\n    --------\n    > var o = Object.getOwnPropertyDescriptor( { 'a': 1 }, 'a' )\n    { 'value': 1, 'enumerable': true, 'configurable': true, 'writable': true }\n\nObject.getOwnPropertyDescriptors( obj )\n    Returns an object's own property descriptors.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Object\n        Property descriptors.\n\n    Examples\n    --------\n    > var o = Object.getOwnPropertyDescriptors( { 'a': 1, 'b': 2 } )\n    {\n        'a': {\n            'value': 1,\n            'enumerable': true,\n            'configurable': true,\n            'writable': true\n        },\n        'b': {\n            'value': 2,\n            'enumerable': true,\n            'configurable': true,\n            'writable': true\n        }\n    }\n\nObject.getOwnPropertyNames( obj )\n    Returns an array of an object's own enumerable and non-enumerable\n    property names.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Array\n        Array of property names.\n\n    Examples\n    --------\n    > var o = Object.getOwnPropertyNames( { 'a': 1, 'b': 2 } )\n    [ 'a', 'b' ]\n\nObject.getOwnPropertySymbols( obj )\n    Returns an array of an object's own enumerable and non-enumerable\n    symbol property names.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Array\n        Array of symbol property names.\n\n    Examples\n    --------\n    > var o = Object.getOwnPropertySymbols( { 'a': 1, 'b': 2 } )\n    []\n\nObject.getPrototypeOf( obj )\n    Returns an object's prototype.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Object\n        Prototype.\n\n    Examples\n    --------\n    > var o = Object.getPrototypeOf( { 'a': 1, 'b': 2 } )\n    <Object>\n\nObject.hasOwn( obj, p )\n    Returns a boolean indicating whether an object has a property with the\n    specified name.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    p: string\n        Property name.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object has a property with the specified\n        name.\n\n    Examples\n    --------\n    > var o = Object.hasOwn( { 'a': 1, 'b': 2 }, 'a' )\n    true\n\nObject.is( value1, value2 )\n    Returns a boolean indicating whether two values are the same value.\n\n    Parameters\n    ----------\n    value1: any\n        First value.\n\n    value2: any\n        Second value.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether two values are the same value.\n\n    Examples\n    --------\n    > var o = Object.is( 1, 1 )\n    true\n    > var o = Object.is( 1, '1' )\n    false\n\nObject.isExtensible( obj )\n    Returns a boolean indicating whether an object is extensible.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object is extensible.\n\n    Examples\n    --------\n    > var o = Object.isExtensible( { 'a': 1 } )\n    true\n\nObject.isFrozen( obj )\n    Returns a boolean indicating whether an object is frozen.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object is frozen.\n\n    Examples\n    --------\n    > var o = Object.isFrozen( { 'a': 1 } )\n    false\n    > var o = Object.isFrozen( Object.freeze( { 'a': 1 } ) )\n    true\n\nObject.isSealed( obj )\n    Returns a boolean indicating whether an object is sealed.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object is sealed.\n\n    Examples\n    --------\n    > var o = Object.isSealed( { 'a': 1 } )\n    false\n    > var o = Object.isSealed( Object.seal( { 'a': 1 } ) )\n    true\n\nObject.keys( obj )\n    Returns an array of an object's own enumerable string-keyed property\n    names.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Array\n        Array of property names.\n\n    Examples\n    --------\n    > var o = Object.keys( { 'a': 1, 'b': 2 } )\n    [ 'a', 'b' ]\n\nObject.preventExtensions( obj )\n    Prevents the addition of new properties to an object.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.preventExtensions( { 'a': 1 } )\n    { 'a': 1 }\n    > o.b = 2;\n    > o\n    { 'a': 1 }\n\nObject.seal( obj )\n    Prevents the addition of new properties to an object and marks all\n    existing properties as non-configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.seal( { 'a': 1 } )\n    { 'a': 1 }\n    > o.b = 2;\n    > o\n    { 'a': 1 }\n    > delete o.a;\n    > o\n    { 'a': 1 }\n\nObject.setPrototypeOf( obj, proto )\n    Sets an object's prototype.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    proto: Object\n        Prototype.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.setPrototypeOf( { 'a': 1 }, { 'b': 2 } )\n    { 'a': 1 }\n    > o.b\n    2\n\nObject.values( obj )\n    Returns an array of an object's own enumerable property values.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Array\n        Array of property values.\n\n    Examples\n    --------\n    > var o = Object.values( { 'a': 1, 'b': 2 } )\n    [ 1, 2 ]\n\nObject.prototype.toLocaleString()\n    Returns a string representing the object.\n\n    Returns\n    -------\n    out: string\n        String representing the object.\n\n    Examples\n    --------\n    > var o = Object.prototype.toLocaleString.call( { 'a': 1, 'b': 2 } )\n    <string>\n\nObject.prototype.toString()\n    Returns a string representing the object.\n\n    Returns\n    -------\n    out: string\n        String representing the object.\n\n    Examples\n    --------\n    > var o = Object.prototype.toString.call( { 'a': 1, 'b': 2 } )\n    <string>\n\nObject.prototype.valueOf()\n    Returns the primitive value of the object.\n\n    Returns\n    -------\n    out: any\n        Primitive value of the object.\n\n    Examples\n    --------\n    > var o = Object.prototype.valueOf.call( { 'a': 1, 'b': 2 } )\n    {}\n\nObject.prototype.hasOwnProperty( p )\n    Returns a boolean indicating whether an object has a property with the\n    specified name.\n\n    Parameters\n    ----------\n    p: string\n        Property name.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object has a property with the specified\n        name.\n\n    Examples\n    --------\n    > var o = Object.prototype.hasOwnProperty.call( { 'a': 1, 'b': 2 }, 'a' )\n    true\n\nObject.prototype.isPrototypeOf( obj )\n    Returns a boolean indicating whether an object exists in another object's\n    prototype chain.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object exists in another object's\n        prototype chain.\n\n    Examples\n    --------\n    > var p = { 'a': 1 };\n    > var o = { '__proto__': p };\n    > var b = o.isPrototypeOf( p );\n    true\n\nObject.prototype.propertyIsEnumerable( p )\n    Returns a boolean indicating whether an object's property is enumerable.\n\n    Parameters\n    ----------\n    p: string\n        Property name.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object's property is enumerable.\n\n    Examples\n    --------\n    > var o = { 'a': 1, 'b': 2 };\n    > var bool = Object.prototype.propertyIsEnumerable.call( o, 'a' )\n    true\n\nObject.prototype.constructor\n    Property whose value is a reference to the constructor function that\n    created the instance object.\n\n    Examples\n    --------\n    > var o = new Object( null );\n    > var ctr = o.constructor;\n    <Object>\n\n","Object.assign":"\nObject.assign( target, ...sources )\n    Assigns enumerable and own properties from source objects to a target\n    object.\n\n    Parameters\n    ----------\n    target: Object\n        Target object.\n\n    sources: ...Object\n        Source objects.\n\n    Returns\n    -------\n    out: Object\n        Target object.\n\n    Examples\n    --------\n    > var o = Object.assign( {}, { 'a': 1 }, { 'b': 2 } )\n    { 'a': 1, 'b': 2 }","Object.create":"\nObject.create( prototype, properties )\n    Creates a new object with a specified prototype object and properties.\n\n    Parameters\n    ----------\n    prototype: Object\n        Prototype object.\n\n    properties: Object\n        Properties object.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > var o = Object.create( {}, { 'a': { 'value': 1 } } )\n    { 'a': 1 }","Object.defineProperties":"\nObject.defineProperties( obj, properties )\n    Defines properties for an object.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    properties: Object\n        Properties object.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.defineProperties( {}, { 'a': { 'value': 1 } } )\n    { 'a': 1 }","Object.defineProperty":"\nObject.defineProperty( obj, key, descriptor )\n    Defines a property for an object.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    key: string\n        Property key.\n\n    descriptor: Object\n        Property descriptor.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.defineProperty( {}, 'a', {\n        'value': 1,\n        'enumerable': true,\n        'configurable': true,\n        'writable': false\n    })\n    { 'a': 1 }","Object.entries":"\nObject.entries( obj )\n    Returns an array of an object's own enumerable string-keyed property\n    [key, value] pairs.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Array\n        Array of [key, value] pairs.\n\n    Examples\n    --------\n    > var o = Object.entries( { 'a': 1, 'b': 2 } )\n    [ [ 'a', 1 ], [ 'b', 2 ] ]","Object.freeze":"\nObject.freeze( obj )\n    Freezes an object.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.freeze( { 'a': 1 } )\n    { 'a': 1 }","Object.getOwnPropertyDescriptor":"\nObject.getOwnPropertyDescriptor( obj, key )\n    Returns an object's own property descriptor.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    key: string\n        Property key.\n\n    Returns\n    -------\n    out: Object\n        Property descriptor.\n\n    Examples\n    --------\n    > var o = Object.getOwnPropertyDescriptor( { 'a': 1 }, 'a' )\n    { 'value': 1, 'enumerable': true, 'configurable': true, 'writable': true }","Object.getOwnPropertyDescriptors":"\nObject.getOwnPropertyDescriptors( obj )\n    Returns an object's own property descriptors.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Object\n        Property descriptors.\n\n    Examples\n    --------\n    > var o = Object.getOwnPropertyDescriptors( { 'a': 1, 'b': 2 } )\n    {\n        'a': {\n            'value': 1,\n            'enumerable': true,\n            'configurable': true,\n            'writable': true\n        },\n        'b': {\n            'value': 2,\n            'enumerable': true,\n            'configurable': true,\n            'writable': true\n        }\n    }","Object.getOwnPropertyNames":"\nObject.getOwnPropertyNames( obj )\n    Returns an array of an object's own enumerable and non-enumerable\n    property names.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Array\n        Array of property names.\n\n    Examples\n    --------\n    > var o = Object.getOwnPropertyNames( { 'a': 1, 'b': 2 } )\n    [ 'a', 'b' ]","Object.getOwnPropertySymbols":"\nObject.getOwnPropertySymbols( obj )\n    Returns an array of an object's own enumerable and non-enumerable\n    symbol property names.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Array\n        Array of symbol property names.\n\n    Examples\n    --------\n    > var o = Object.getOwnPropertySymbols( { 'a': 1, 'b': 2 } )\n    []","Object.getPrototypeOf":"\nObject.getPrototypeOf( obj )\n    Returns an object's prototype.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Object\n        Prototype.\n\n    Examples\n    --------\n    > var o = Object.getPrototypeOf( { 'a': 1, 'b': 2 } )\n    <Object>","Object.hasOwn":"\nObject.hasOwn( obj, p )\n    Returns a boolean indicating whether an object has a property with the\n    specified name.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    p: string\n        Property name.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object has a property with the specified\n        name.\n\n    Examples\n    --------\n    > var o = Object.hasOwn( { 'a': 1, 'b': 2 }, 'a' )\n    true","Object.is":"\nObject.is( value1, value2 )\n    Returns a boolean indicating whether two values are the same value.\n\n    Parameters\n    ----------\n    value1: any\n        First value.\n\n    value2: any\n        Second value.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether two values are the same value.\n\n    Examples\n    --------\n    > var o = Object.is( 1, 1 )\n    true\n    > var o = Object.is( 1, '1' )\n    false","Object.isExtensible":"\nObject.isExtensible( obj )\n    Returns a boolean indicating whether an object is extensible.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object is extensible.\n\n    Examples\n    --------\n    > var o = Object.isExtensible( { 'a': 1 } )\n    true","Object.isFrozen":"\nObject.isFrozen( obj )\n    Returns a boolean indicating whether an object is frozen.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object is frozen.\n\n    Examples\n    --------\n    > var o = Object.isFrozen( { 'a': 1 } )\n    false\n    > var o = Object.isFrozen( Object.freeze( { 'a': 1 } ) )\n    true","Object.isSealed":"\nObject.isSealed( obj )\n    Returns a boolean indicating whether an object is sealed.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object is sealed.\n\n    Examples\n    --------\n    > var o = Object.isSealed( { 'a': 1 } )\n    false\n    > var o = Object.isSealed( Object.seal( { 'a': 1 } ) )\n    true","Object.keys":"\nObject.keys( obj )\n    Returns an array of an object's own enumerable string-keyed property\n    names.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Array\n        Array of property names.\n\n    Examples\n    --------\n    > var o = Object.keys( { 'a': 1, 'b': 2 } )\n    [ 'a', 'b' ]","Object.preventExtensions":"\nObject.preventExtensions( obj )\n    Prevents the addition of new properties to an object.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.preventExtensions( { 'a': 1 } )\n    { 'a': 1 }\n    > o.b = 2;\n    > o\n    { 'a': 1 }","Object.seal":"\nObject.seal( obj )\n    Prevents the addition of new properties to an object and marks all\n    existing properties as non-configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.seal( { 'a': 1 } )\n    { 'a': 1 }\n    > o.b = 2;\n    > o\n    { 'a': 1 }\n    > delete o.a;\n    > o\n    { 'a': 1 }","Object.setPrototypeOf":"\nObject.setPrototypeOf( obj, proto )\n    Sets an object's prototype.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    proto: Object\n        Prototype.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.setPrototypeOf( { 'a': 1 }, { 'b': 2 } )\n    { 'a': 1 }\n    > o.b\n    2","Object.values":"\nObject.values( obj )\n    Returns an array of an object's own enumerable property values.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Array\n        Array of property values.\n\n    Examples\n    --------\n    > var o = Object.values( { 'a': 1, 'b': 2 } )\n    [ 1, 2 ]","Object.prototype.toLocaleString":"\nObject.prototype.toLocaleString()\n    Returns a string representing the object.\n\n    Returns\n    -------\n    out: string\n        String representing the object.\n\n    Examples\n    --------\n    > var o = Object.prototype.toLocaleString.call( { 'a': 1, 'b': 2 } )\n    <string>","Object.prototype.toString":"\nObject.prototype.toString()\n    Returns a string representing the object.\n\n    Returns\n    -------\n    out: string\n        String representing the object.\n\n    Examples\n    --------\n    > var o = Object.prototype.toString.call( { 'a': 1, 'b': 2 } )\n    <string>","Object.prototype.valueOf":"\nObject.prototype.valueOf()\n    Returns the primitive value of the object.\n\n    Returns\n    -------\n    out: any\n        Primitive value of the object.\n\n    Examples\n    --------\n    > var o = Object.prototype.valueOf.call( { 'a': 1, 'b': 2 } )\n    {}","Object.prototype.hasOwnProperty":"\nObject.prototype.hasOwnProperty( p )\n    Returns a boolean indicating whether an object has a property with the\n    specified name.\n\n    Parameters\n    ----------\n    p: string\n        Property name.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object has a property with the specified\n        name.\n\n    Examples\n    --------\n    > var o = Object.prototype.hasOwnProperty.call( { 'a': 1, 'b': 2 }, 'a' )\n    true","Object.prototype.isPrototypeOf":"\nObject.prototype.isPrototypeOf( obj )\n    Returns a boolean indicating whether an object exists in another object's\n    prototype chain.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object exists in another object's\n        prototype chain.\n\n    Examples\n    --------\n    > var p = { 'a': 1 };\n    > var o = { '__proto__': p };\n    > var b = o.isPrototypeOf( p );\n    true","Object.prototype.propertyIsEnumerable":"\nObject.prototype.propertyIsEnumerable( p )\n    Returns a boolean indicating whether an object's property is enumerable.\n\n    Parameters\n    ----------\n    p: string\n        Property name.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object's property is enumerable.\n\n    Examples\n    --------\n    > var o = { 'a': 1, 'b': 2 };\n    > var bool = Object.prototype.propertyIsEnumerable.call( o, 'a' )\n    true","Object.prototype.constructor":"\nObject.prototype.constructor\n    Property whose value is a reference to the constructor function that\n    created the instance object.\n\n    Examples\n    --------\n    > var o = new Object( null );\n    > var ctr = o.constructor;\n    <Object>","objectEntries":"\nobjectEntries( obj )\n    Returns an array of an object's own enumerable property `[key, value]`\n    pairs.\n\n    Entry order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic return values.\n\n    Parameters\n    ----------\n    obj: ObjectLike\n        Input object.\n\n    Returns\n    -------\n    arr: Array\n        Array containing key-value pairs.\n\n    Examples\n    --------\n    > var obj = { 'beep': 'boop', 'foo': 'bar' };\n    > var entries = objectEntries( obj )\n    e.g., [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ]\n\n    See Also\n    --------\n    objectEntriesIn, objectFromEntries, objectKeys, objectValues\n","objectEntriesIn":"\nobjectEntriesIn( obj )\n    Returns an array of an object's own and inherited enumerable property\n    `[key, value]` pairs.\n\n    Entry order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic return values.\n\n    Parameters\n    ----------\n    obj: ObjectLike\n        Input object.\n\n    Returns\n    -------\n    arr: Array\n        Array containing key-value pairs.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var entries = objectEntriesIn( obj )\n    e.g., [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ]\n\n    See Also\n    --------\n    objectEntries, objectFromEntries, keysIn, objectValuesIn\n","objectFromEntries":"\nobjectFromEntries( entries )\n    Creates an object from an array of key-value pairs.\n\n    Parameters\n    ----------\n    entries: Array<Array>\n        Input object.\n\n    Returns\n    -------\n    out: Object\n        Object created from `[key, value]` pairs.\n\n    Examples\n    --------\n    > var entries = [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ];\n    > var obj = objectFromEntries( entries )\n    { 'beep': 'boop', 'foo': 'bar' }\n\n    See Also\n    --------\n    objectEntries\n","objectInverse":"\nobjectInverse( obj[, options] )\n    Inverts an object, such that keys become values and values become keys.\n\n    Beware when providing objects having values which are themselves objects.\n    The function relies on native object serialization (`#toString`) when\n    converting values to keys.\n\n    Insertion order is not guaranteed, as object key enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's keys, thus allowing for\n    deterministic inversion.\n\n    Parameters\n    ----------\n    obj: ObjectLike\n        Input object.\n\n    options: Object (optional)\n        Options.\n\n    options.duplicates: boolean (optional)\n        Boolean indicating whether to store keys mapped to duplicate values in\n        arrays. Default: `true`.\n\n    Returns\n    -------\n    out: Object\n        Inverted object.\n\n    Examples\n    --------\n    // Basic usage:\n    > var obj = { 'a': 'beep', 'b': 'boop' };\n    > var out = objectInverse( obj )\n    { 'beep': 'a', 'boop': 'b' }\n\n    // Duplicate values:\n    > obj = { 'a': 'beep', 'b': 'beep' };\n    > out = objectInverse( obj )\n    { 'beep': [ 'a', 'b' ] }\n\n    // Override duplicate values:\n    > obj = {};\n    > obj.a = 'beep';\n    > obj.b = 'boop';\n    > obj.c = 'beep';\n    > out = objectInverse( obj, { 'duplicates': false } )\n    { 'beep': 'c', 'boop': 'b' }\n\n    See Also\n    --------\n    objectInverseBy\n","objectInverseBy":"\nobjectInverseBy( obj, [options,] transform )\n    Inverts an object, such that keys become values and values become keys,\n    according to a transform function.\n\n    The transform function is provided three arguments:\n\n    - key: object key.\n    - value: object value corresponding to `key`.\n    - obj: the input object.\n\n    The value returned by a transform function should be a value which can be\n    serialized as an object key. Hence, beware when providing objects having\n    values which are themselves objects. The function relies on native object\n    serialization (`#toString`) when converting transform function return values\n    to keys.\n\n    Insertion order is not guaranteed, as object key enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's keys, thus allowing for\n    deterministic inversion.\n\n    Parameters\n    ----------\n    obj: ObjectLike\n        Input object.\n\n    options: Object (optional)\n        Options.\n\n    options.duplicates: boolean (optional)\n        Boolean indicating whether to store keys mapped to duplicate values in\n        arrays. Default: `true`.\n\n    transform: Function\n        Transform function.\n\n    Returns\n    -------\n    out: Object\n        Inverted object.\n\n    Examples\n    --------\n    // Basic usage:\n    > function transform( key, value ) { return key + value; };\n    > var obj = { 'a': 'beep', 'b': 'boop' };\n    > var out = objectInverseBy( obj, transform )\n    { 'abeep': 'a', 'bboop': 'b' }\n\n    // Duplicate values:\n    > function transform( key, value ) { return value; };\n    > obj = { 'a': 'beep', 'b': 'beep' };\n    > out = objectInverseBy( obj, transform )\n    { 'beep': [ 'a', 'b' ] }\n\n    // Override duplicate values:\n    > obj = {};\n    > obj.a = 'beep';\n    > obj.b = 'boop';\n    > obj.c = 'beep';\n    > out = objectInverseBy( obj, { 'duplicates': false }, transform )\n    { 'beep': 'c', 'boop': 'b' }\n\n    See Also\n    --------\n    objectInverse\n","objectKeys":"\nobjectKeys( value )\n    Returns an array of an object's own enumerable property names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's own enumerable property names.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var keys = objectKeys( obj )\n    [ 'beep' ]\n\n    See Also\n    --------\n    objectEntries, keysIn, nonIndexKeys, objectValues\n","objectValues":"\nobjectValues( obj )\n    Returns an array of an object's own enumerable property values.\n\n    Value order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    Parameters\n    ----------\n    obj: ObjectLike\n        Input object.\n\n    Returns\n    -------\n    values: Array\n        Value array.\n\n    Examples\n    --------\n    > var obj = { 'beep': 'boop', 'foo': 'bar' };\n    > var vals = objectValues( obj )\n    e.g., [ 'boop', 'bar' ]\n\n    See Also\n    --------\n    objectEntries, objectKeys\n","objectValuesIn":"\nobjectValuesIn( obj )\n    Returns an array of an object's own and inherited enumerable property\n    values.\n\n    Value order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    Parameters\n    ----------\n    obj: ObjectLike\n        Input object.\n\n    Returns\n    -------\n    values: Array\n        Value array.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var values = objectValuesIn( obj )\n    e.g., [ 'boop', 'bar' ]\n\n    See Also\n    --------\n    objectEntriesIn, keysIn, objectValues\n","omit":"\nomit( obj, keys )\n    Returns a partial object copy excluding specified keys.\n\n    The function returns a shallow copy.\n\n    The function ignores non-existent keys.\n\n    The function only copies own properties. Hence, the function never copies\n    inherited properties.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    keys: string|Array<string>\n        Keys to exclude.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > var obj1 = { 'a': 1, 'b': 2 };\n    > var obj2 = omit( obj1, 'b' )\n    { 'a': 1 }\n\n    See Also\n    --------\n    omitBy\n","omitBy":"\nomitBy( obj, predicate )\n    Returns a partial object copy excluding properties for which a predicate\n    returns a truthy value.\n\n    The function returns a shallow copy.\n\n    The function only copies own properties. Hence, the function never copies\n    inherited properties.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    predicate: Function\n        Predicate function.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > function predicate( key, value ) { return ( value > 1 ); };\n    > var obj1 = { 'a': 1, 'b': 2 };\n    > var obj2 = omitBy( obj1, predicate )\n    { 'a': 1 }\n\n    See Also\n    --------\n    omit\n","open":"\nopen( path[, flags[, mode]], clbk )\n    Asynchronously opens a file.\n\n    Some characters, such as <>:\"/\\|?*, are reserved under Windows.\n    Under NTFS, if the path contains a colon, Node.js will open a file system\n    stream.\n\n    Parameters\n    ----------\n    path: string|Buffer\n        Filename.\n\n    flags: string|number (optional)\n        File system flags. Default: 'r'.\n\n    mode: integer (optional)\n        File mode (permission and sticky bits). This sets the file mode, but\n        only if the file was created. On Windows, only the write permission can\n        be manipulated. Default: 0o666.\n\n    clbk: Function\n        Callback to invoke upon opening a file.\n\n    Examples\n    --------\n    > function onOpen( error, fd ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     } else {\n    ...         close.sync( fd );\n    ...     }\n    ... };\n    > open( './beep/boop.txt', onOpen );\n\n\nopen.sync( path[, flags[, mode]] )\n    Synchronously opens a file.\n\n    Parameters\n    ----------\n    path: string|Buffer\n        Filename.\n\n    flags: string|number (optional)\n        File system flags. Default: 'r'.\n\n    mode: integer (optional)\n        File mode (permission and sticky bits).  This sets the file mode, but\n        only if the file was created. On Windows, only the write permission can\n        be manipulated. Default: 0o666.\n\n    Returns\n    -------\n    fd: Error|integer\n        File descriptor.\n\n    Examples\n    --------\n    > var fd = open.sync( './beep/boop.txt' );\n    > if ( !isError( fd ) ) { close.sync( fd ); };\n\n    See Also\n    --------\n    close, exists, readFile\n","open.sync":"\nopen.sync( path[, flags[, mode]] )\n    Synchronously opens a file.\n\n    Parameters\n    ----------\n    path: string|Buffer\n        Filename.\n\n    flags: string|number (optional)\n        File system flags. Default: 'r'.\n\n    mode: integer (optional)\n        File mode (permission and sticky bits).  This sets the file mode, but\n        only if the file was created. On Windows, only the write permission can\n        be manipulated. Default: 0o666.\n\n    Returns\n    -------\n    fd: Error|integer\n        File descriptor.\n\n    Examples\n    --------\n    > var fd = open.sync( './beep/boop.txt' );\n    > if ( !isError( fd ) ) { close.sync( fd ); };\n\n    See Also\n    --------\n    close, exists, readFile","openURL":"\nopenURL( url )\n    Opens a URL in a user's default browser.\n\n    In a non-browser environment, the function returns an unreferenced child\n    process. In a browser environment, the function returns a reference to a\n    `window` object.\n\n    Parameters\n    ----------\n    url: string\n        URL to open.\n\n    Returns\n    -------\n    out: process|Window\n        Child process or `window` object.\n\n    Examples\n    --------\n    > var out = openURL( 'https://google.com' );\n\n","ordinalize":"\nordinalize( value[, options] )\n    Converts an integer to an ordinal string (e.g., `1st`, `2nd`, etc.).\n\n    Parameters\n    ----------\n    value: string|integer\n        Input value.\n\n    options: Object (optional)\n        Options.\n\n    options.lang: string (optional)\n        Language code. Supported languages:\n\n        - en: English.\n        - es: Spanish.\n        - fin: Finnish.\n        - fr: French.\n        - de: Dutch.\n        - it: Italian.\n        - pt: Portuguese.\n        - swe: Swedish.\n\n        Default: `'en'`.\n\n    options.suffixOnly: boolean (optional)\n        Boolean indicating whether to return only the suffix. Default: `false`.\n\n    options.gender: string (optional)\n       Grammatical gender (used if applicable); must be either 'masculine' or\n       'feminine'. Default: `'masculine'`.\n\n    Returns\n    -------\n    out: string\n        Ordinal string or suffix.\n\n    Examples\n    --------\n    > var out = ordinalize( '1' )\n    '1st'\n    > out = ordinalize( 2, { 'suffixOnly': true } )\n    'nd'\n    > out = ordinalize( '3', { 'lang': 'es' } )\n    '3º'\n\n","PACE_BOSTON_HOUSE_PRICES":"\nPACE_BOSTON_HOUSE_PRICES()\n    Returns a (corrected) dataset derived from information collected by the US\n    Census Service concerning housing in Boston, Massachusetts (1978).\n\n    The data consists of 21 attributes:\n\n    - obs: observation number.\n    - town: town name.\n    - town_id: town identifier.\n    - tract: tract identifier.\n    - lon: longitude.\n    - lat: latitude.\n    - medv: median value of owner-occupied homes in $1000's.\n    - cmedv: corrected median value of owner-occupied homes in $1000's.\n    - crim: per capita crime rate by town.\n    - zn: proportion of residential land zoned for lots over 25,000 square feet.\n    - indus: proportion of non-retail business acres per town.\n    - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise).\n    - nox: nitric oxides concentration (parts per 10 million).\n    - rm: average number of rooms per dwelling.\n    - age: proportion of owner-occupied units built prior to 1940.\n    - dis: weighted distances to five Boston employment centers.\n    - rad: index of accessibility to radial highways.\n    - tax: full-value property-tax rate per $10,000.\n    - ptratio: pupil-teacher ratio by town.\n    - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town.\n    - lstat: percent lower status of the population.\n\n    The dataset can be used to predict two dependent variables: 1) nitrous oxide\n    level and 2) median home value.\n\n    The median home value field seems to be censored at 50.00 (corresponding to\n    a median value of $50,000). Censoring is suggested by the fact that the\n    highest median value of exactly $50,000 is reported in 16 cases, while 15\n    cases have values between $40,000 and $50,000. Values are rounded to the\n    nearest hundred.\n\n    The dataset contains eight corrections to miscoded median values, as\n    documented by Gilley and Pace (1996).\n\n    The dataset augments the original dataset from Harrison and Rubinfeld (1978)\n    by including geo-referencing and spatial estimation for each observation.\n\n    Returns\n    -------\n    out: Array<Object>\n        Boston house prices.\n\n    Examples\n    --------\n    > var data = PACE_BOSTON_HOUSE_PRICES()\n    [ {...}, {...}, ... ]\n\n    References\n    ----------\n    - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n    the demand for clean air.\" _Journal of Environmental Economics and\n    Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n    - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n    Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n    doi:10.1006/jeem.1996.0052.\n    - Pace, R. Kelley, and Otis W. Gilley. 1997. \"Using the Spatial\n    Configuration of the Data to Improve Estimation.\" _The Journal of Real\n    Estate Finance and Economics_ 14 (3): 333–40. doi:10.1023/A:1007762613901.\n\n    See Also\n    --------\n    HARRISON_BOSTON_HOUSE_PRICES, HARRISON_BOSTON_HOUSE_PRICES_CORRECTED\n","pad":"\npad( str, len[, options] )\n    Pads a `string` such that the padded `string` has length `len`.\n\n    Any padding which does not evenly divide available space is trimmed such\n    that the returned string length is always `len`.\n\n    If `len < str.length`, the input string is trimmed.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    len: integer\n        Output string length.\n\n    options: Object (optional)\n        Options.\n\n    options.lpad: string (optional)\n        String used to left pad.\n\n    options.rpad: string (optional)\n        String used to right pad.\n\n    options.centerRight: boolean (optional)\n        Boolean indicating whether to center right in the event of a tie.\n        Default: `false` (i.e., center left).\n\n    Returns\n    -------\n    out: string\n        Padded string.\n\n    Examples\n    --------\n    // Standard usage:\n    > var out = pad( 'a', 5 )\n    'a    '\n\n    // Left pad:\n    > out = pad( 'a', 10, { 'lpad': 'b' } )\n    'bbbbbbbbba'\n\n    // Right pad:\n    > out = pad( 'a', 12, { 'rpad': 'b' } )\n    'abbbbbbbbbbb'\n\n    // Center an input string:\n    > var opts = { 'lpad': 'a', 'rpad': 'c' };\n    > out = pad( 'b', 11, opts )\n    'aaaaabccccc'\n\n    // Left center:\n    > opts.centerRight = false;\n    > out = pad( 'b', 10, opts )\n    'aaaabccccc'\n\n    // Right center:\n    > opts.centerRight = true;\n    > out = pad( 'b', 10, opts )\n    'aaaaabcccc'\n\n    // Output string always length `len`:\n    > opts = { 'lpad': 'boop', 'rpad': 'woot' };\n    > out = pad( 'beep', 10, opts )\n    'boobeepwoo'\n\n    // Pad right, trim right:\n    > out = pad( 'beep', 2 )\n    'be'\n\n    // Pad left, trim left:\n    > opts = { 'lpad': 'b' };\n    > out = pad( 'beep', 2, opts )\n    'ep'\n\n    // Pad both, trim both:\n    > opts = { 'lpad': '@', 'rpad': '!' };\n    > out = pad( 'beep', 2, opts )\n    'ee'\n\n    // Pad both, trim both starting from left:\n    > out = pad( 'abcdef', 3, opts )\n    'cde'\n\n    // Pad both, trim both starting from right:\n    > opts.centerRight = true;\n    > out = pad( 'abcdef', 3, opts )\n    'bcd'\n\n    See Also\n    --------\n    lpad, rpad\n","padjust":"\npadjust( pvals, method[, comparisons] )\n    Adjusts supplied p-values for multiple comparisons via a specified method.\n\n    The `method` parameter can be one of the following values:\n\n    - bh: Benjamini-Hochberg procedure controlling the False Discovery\n    Rate (FDR).\n    - bonferroni: Bonferroni correction fixing the family-wise error rate\n    by multiplying the p-values with the number of comparisons. The Bonferroni\n    correction is usually a too conservative adjustment compared to the others.\n    - by: Procedure by Benjamini & Yekutieli for controlling the False\n    Discovery Rate (FDR) under dependence.\n    - holm: Hommel's method controlling family-wise error rate. It is\n    uniformly more powerful than the Bonferroni correction.\n    - hommel: Hommel's method, which is valid when hypothesis tests are\n    independent. It is more expensive to compute than the other methods.\n\n    By default, the number of comparisons for which the p-values should be\n    corrected is equal to the number of provided p-values. Alternatively, it is\n    possible to set `comparisons` to a number greater than the length of\n    `pvals`. In that case, the methods assume `comparisons - pvals.length`\n    unobserved p-values that are greater than all observed p-values (for Holm's\n    method and the Bonferroni correction) or equal to `1` for the remaining\n    methods.\n\n    Parameters\n    ----------\n    pvals: Array<number>\n        P-values to be adjusted.\n\n    method: string\n        Correction method.\n\n    comparisons: integer (optional)\n        Number of comparisons. Default value: `pvals.length`.\n\n    Returns\n    -------\n    out: Array<number>\n        Array containing the corrected p-values.\n\n    Examples\n    --------\n    > var pvalues = [ 0.008, 0.03, 0.123, 0.6, 0.2 ];\n    > var out = padjust( pvalues, 'bh' )\n    [ 0.04, 0.075, ~0.205, 0.6, 0.25 ]\n\n    > out = padjust( pvalues, 'bonferroni' )\n    [ 0.04, 0.15, 0.615, 1.0, 1.0 ]\n\n    > out = padjust( pvalues, 'by' )\n    [ ~0.457, ~0.856, 1.0, 1.0, 1.0 ]\n\n    > out = padjust( pvalues, 'holm' )\n    [ 0.2, 0.6, 1.0, 1.0, 1.0 ]\n\n    > out = padjust( pvalues, 'hommel' )\n    [ 0.16, 0.6, 1.0, 1.0, 1.0 ]\n\n","papply":"\npapply( fcn, ...args )\n    Returns a function of smaller arity by partially applying arguments.\n\n    The implementation does not set the `length` property of the returned\n    function. Accordingly, the returned function `length` is always zero.\n\n    The evaluation context is always `null`.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to partially apply.\n\n    args: ...any\n        Arguments to partially apply.\n\n    Returns\n    -------\n    out: Function\n        Partially applied function.\n\n    Examples\n    --------\n    > function add( x, y ) { return x + y; };\n    > var add2 = papply( add, 2 );\n    > var sum = add2( 3 )\n    5\n\n    See Also\n    --------\n    papplyRight\n","papplyRight":"\npapplyRight( fcn, ...args )\n    Returns a function of smaller arity by partially applying arguments from the\n    right.\n\n    The implementation does not set the `length` property of the returned\n    function. Accordingly, the returned function `length` is always zero.\n\n    The evaluation context is always `null`.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to partially apply.\n\n    args: ...any\n        Arguments to partially apply.\n\n    Returns\n    -------\n    out: Function\n        Partially applied function.\n\n    Examples\n    --------\n    > function say( text, name ) { return text + ', ' + name + '.'; };\n    > var toGrace = papplyRight( say, 'Grace Hopper' );\n    > var str = toGrace( 'Hello' )\n    'Hello, Grace Hopper.'\n    > str = toGrace( 'Thank you' )\n    'Thank you, Grace Hopper.'\n\n    See Also\n    --------\n    papply\n","parallel":"\nparallel( files, [options,] clbk )\n    Executes scripts in parallel.\n\n    Relative file paths are resolved relative to the current working directory.\n\n    Ordered script output does not imply that scripts are executed in order. To\n    preserve script order, execute the scripts sequentially via some other\n    means.\n\n    Parameters\n    ----------\n    files: Array<string>\n        Script file paths.\n\n    options: Object (optional)\n        Options.\n\n    options.cmd: string (optional)\n        Executable file/command. Default: `'node'`.\n\n    options.concurrency: integer (optional)\n        Number of scripts to execute concurrently. Script concurrency cannot\n        exceed the number of scripts. By specifying a concurrency greater than\n        the number of workers, a worker may be executing more than `1` script at\n        any one time. While not likely to be advantageous for synchronous\n        scripts, setting a higher concurrency may be advantageous for scripts\n        performing asynchronous tasks. If the script concurrency is less than\n        the number of workers, the number of workers is reduced to match the\n        specified concurrency. Default: `options.workers`.\n\n    options.workers: integer (optional)\n        Number of workers. Default: number of CPUs minus `1`.\n\n    options.ordered: boolean (optional)\n        Boolean indicating whether to preserve the order of script output. By\n        default, the `stdio` output for each script is interleaved; i.e., the\n        `stdio` output from one script may be interleaved with the `stdio`\n        output from one or more other scripts. To preserve the `stdio` output\n        order for each script, set the `ordered` option to `true`. Default:\n        `false`.\n\n    options.uid: integer (optional)\n        Process user identity.\n\n    options.gid: integer (optional)\n        Process group identity.\n\n    options.maxBuffer: integer (optional)\n        Max child process `stdio` buffer size. This option is only applied when\n        `options.ordered = true`. Default: `200*1024*1024`.\n\n    clbk: Function\n        Callback to invoke after executing all scripts.\n\n    Examples\n    --------\n    > function done( error ) { if ( error ) { throw error; } };\n    > var files = [ './a.js', './b.js' ];\n    > parallel( files, done );\n\n    // Specify the number of workers:\n    > var opts = { 'workers': 8 };\n    > parallel( files, opts, done );\n\n","parseJSON":"\nparseJSON( str[, reviver] )\n    Attempts to parse a string as JSON.\n\n    Function behavior differs from `JSON.parse()` as follows:\n\n    - throws a `TypeError` if provided any value which is not a string.\n    - throws a `TypeError` if provided a `reviver` argument which is not a\n      function.\n    - returns, rather than throws, a `SyntaxError` if unable to parse a string\n      as JSON.\n\n    Parameters\n    ----------\n    str: string\n        String to parse.\n\n    reviver: Function (optional)\n        Transformation function.\n\n    Returns\n    -------\n    out: any|Error\n        Parsed value or an error.\n\n    Examples\n    --------\n    > var obj = parseJSON( '{\"beep\":\"boop\"}' )\n    { 'beep': 'boop' }\n\n    // Provide a reviver:\n    > function reviver( key, value ) {\n    ...     if ( key === '' ) { return value; }\n    ...     if ( key === 'beep' ) { return value; }\n    ... };\n    > var str = '{\"beep\":\"boop\",\"a\":\"b\"}';\n    > var out = parseJSON( str, reviver )\n    { 'beep': 'boop' }\n\n","pascalcase":"\npascalcase( str )\n    Converts a string to Pascal case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Pascal-cased string.\n\n    Examples\n    --------\n    > var out = pascalcase( 'Hello World!' )\n    'HelloWorld'\n    > out = pascalcase( 'beep boop' )\n    'BeepBoop'\n\n    See Also\n    --------\n    camelcase, constantcase, kebabcase, snakecase","PATH_DELIMITER":"\nPATH_DELIMITER\n    Platform-specific path delimiter.\n\n    Examples\n    --------\n    > PATH_DELIMITER\n    <string>\n\n    // POSIX environment:\n    > var path = '/usr/bin:/bin:/usr/sbin';\n    > var parts = path.split( PATH_DELIMITER )\n    [ '/usr/bin', '/bin', '/usr/sbin' ]\n\n    // Windows environment:\n    > path = 'C:\\\\Windows\\\\system32;C:\\\\Windows';\n    > parts = path.split( PATH_DELIMITER )\n    [ 'C:\\\\Windows\\system32', 'C:\\\\Windows' ]\n\n    See Also\n    --------\n    PATH_DELIMITER_POSIX, PATH_DELIMITER_WIN32\n","PATH_DELIMITER_POSIX":"\nPATH_DELIMITER_POSIX\n    POSIX path delimiter.\n\n    Examples\n    --------\n    > PATH_DELIMITER_POSIX\n    ':'\n    > var PATH = '/usr/bin:/bin:/usr/sbin:/sbin:/usr/local/bin';\n    > var paths = PATH.split( PATH_DELIMITER_POSIX )\n    [ '/usr/bin', '/bin', '/usr/sbin', '/sbin', '/usr/local/bin' ]\n\n    See Also\n    --------\n    PATH_DELIMITER, PATH_DELIMITER_WIN32\n","PATH_DELIMITER_WIN32":"\nPATH_DELIMITER_WIN32\n    Windows path delimiter.\n\n    Examples\n    --------\n    > PATH_DELIMITER_WIN32\n    ';'\n    > var PATH = 'C:\\\\Windows\\\\system32;C:\\\\Windows;C:\\\\Program Files\\\\node\\\\';\n    > var paths = PATH.split( PATH_DELIMITER_WIN32 )\n    [ 'C:\\\\Windows\\\\system32', 'C:\\\\Windows', 'C:\\\\Program Files\\\\node\\\\' ]\n\n    See Also\n    --------\n    PATH_DELIMITER, PATH_DELIMITER_POSIX\n","PATH_SEP":"\nPATH_SEP\n    Platform-specific path segment separator.\n\n    Examples\n    --------\n    > PATH_SEP\n    <string>\n\n    // Windows environment:\n    > var parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP )\n    [ 'foo', 'bar', 'baz' ]\n\n    // POSIX environment:\n    > parts = 'foo/bar/baz'.split( PATH_SEP )\n    [ 'foo', 'bar', 'baz' ]\n\n    See Also\n    --------\n    PATH_SEP_POSIX, PATH_SEP_WIN32\n","PATH_SEP_POSIX":"\nPATH_SEP_POSIX\n    POSIX path segment separator.\n\n    Examples\n    --------\n    > PATH_SEP_POSIX\n    '/'\n    > var parts = 'foo/bar/baz'.split( PATH_SEP_POSIX )\n    [ 'foo', 'bar', 'baz' ]\n\n    See Also\n    --------\n    PATH_SEP, PATH_SEP_WIN32\n","PATH_SEP_WIN32":"\nPATH_SEP_WIN32\n    Windows path segment separator.\n\n    Examples\n    --------\n    > PATH_SEP_WIN32\n    '\\\\'\n    > var parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP_WIN32 )\n    [ 'foo', 'bar', 'baz' ]\n\n    See Also\n    --------\n    PATH_SEP, PATH_SEP_POSIX\n","pcorrtest":"\npcorrtest( x, y[, options] )\n    Computes a Pearson product-moment correlation test between paired samples.\n\n    By default, the function performs a t-test for the null hypothesis that the\n    data in arrays or typed arrays `x` and `y` is not correlated. A test against\n    a different population correlation can be carried out by supplying the `rho`\n    option. In this case, a test using the Fisher's z transform is conducted.\n\n    The returned object comes with a `.print()` method which when invoked will\n    print a formatted output of the results of the hypothesis test.\n\n    Parameters\n    ----------\n    x: Array<number>\n        First data array.\n\n    y: Array<number>\n        Second data array.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Nnumber in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.alternative: string (optional)\n        Either `two-sided`, `less` or `greater`. Indicates whether the\n        alternative hypothesis is that `x` has a larger mean than `y`\n        (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n        the same (`two-sided`). Default: `'two-sided'`.\n\n    options.rho: number (optional)\n        Number denoting the correlation under the null hypothesis.\n        Default: `0`.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Used significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.ci: Array<number>\n        1-alpha confidence interval for the Pearson product-moment correlation\n        coefficient. The confidence interval is calculated using Fisher's\n        z-transform.\n\n    out.nullValue: number\n        Assumed correlation under H0 (equal to the supplied `rho` option).\n\n    out.alternative: string\n        Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n    out.method: string\n        Name of test.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    > var rho = 0.5;\n    > var x = new Array( 300 );\n    > var y = new Array( 300 );\n    > for ( var i = 0; i < 300; i++ ) {\n    ...    x[ i ] = base.random.normal( 0.0, 1.0 );\n    ...    y[ i ] = ( rho * x[ i ] ) + base.random.normal( 0.0,\n    ...    base.sqrt( 1.0 - (rho*rho) ) );\n    ... }\n    > var out = pcorrtest( x, y )\n    {\n        alpha: 0.05,\n        rejected: true,\n        pValue: 0,\n        statistic: 10.115805615994121,\n        ci: [ 0.4161679018930295, 0.5853122968949995 ],\n        alternative: 'two-sided',\n        method: 't-test for Pearson correlation coefficient',\n        nullValue: 0,\n        pcorr: 0.505582072355616,\n    }\n\n    // Print output:\n    > var table = out.print()\n    t-test for Pearson correlation coefficient\n\n    Alternative hypothesis: True correlation coefficient is not equal to 0\n\n        pValue: 0\n        statistic: 9.2106\n        95% confidence interval: [0.3776,0.5544]\n\n    Test Decision: Reject null in favor of alternative at 5% significance level\n\n","percentEncode":"\npercentEncode( str )\n    Percent-encodes a UTF-16 encoded string according to RFC 3986.\n\n    Parameters\n    ----------\n    str: string\n        UTF-16 encoded string.\n\n    Returns\n    -------\n    out: string\n        Percent-encoded string.\n\n    Examples\n    --------\n    > var out = percentEncode( '☃' )\n    '%E2%98%83'\n\n","PHI":"\nPHI\n    Golden ratio.\n\n    Examples\n    --------\n    > PHI\n    1.618033988749895\n\n","PI":"\nPI\n    The mathematical constant `π`.\n\n    Examples\n    --------\n    > PI\n    3.141592653589793\n\n    See Also\n    --------\n    TWO_PI\n","PI_SQUARED":"\nPI_SQUARED\n    Square of the mathematical constant `π`.\n\n    Examples\n    --------\n    > PI_SQUARED\n    9.869604401089358\n\n    See Also\n    --------\n    PI\n","pick":"\npick( obj, keys )\n    Returns a partial object copy containing only specified keys.\n\n    If a key does not exist as an own property in a source object, the key is\n    ignored.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    keys: string|Array<string>\n        Keys to copy.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > var obj1 = { 'a': 1, 'b': 2 };\n    > var obj2 = pick( obj1, 'b' )\n    { 'b': 2 }\n\n    See Also\n    --------\n    pickBy\n","pickArguments":"\npickArguments( fcn, indices[, thisArg] )\n    Returns a function that applies specified arguments to a provided function.\n\n    Parameters\n    ----------\n    fcn: Function\n        Input function.\n\n    indices: Array<integer>\n        Argument indices.\n\n    thisArg: any (optional)\n        Function context.\n\n    Returns\n    -------\n    out: Function\n        Function wrapper.\n\n    Examples\n    --------\n    > function foo( a, b ) { return [ a, b ]; };\n    > var bar = pickArguments( foo, [ 0, 2 ] );\n    > var out = bar( 1, 2, 3 )\n    [ 1, 3 ]\n\n    See Also\n    --------\n    reorderArguments, reverseArguments\n","pickBy":"\npickBy( obj, predicate )\n    Returns a partial object copy containing properties for which a predicate\n    returns a truthy value.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    predicate: Function\n        Predicate function.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > function predicate( key, value ) {\n    ...     return ( value > 1 );\n    ... };\n    > var obj1 = { 'a': 1, 'b': 2 };\n    > var obj2 = pickBy( obj1, predicate )\n    { 'b': 2 }\n\n    See Also\n    --------\n    pick\n","PINF":"\nPINF\n    Double-precision floating-point positive infinity.\n\n    Examples\n    --------\n    > PINF\n    Infinity\n\n    See Also\n    --------\n    NINF\n","pkg2alias":"\npkg2alias( pkg )\n    Returns the alias associated with a specified package name.\n\n    The function supports both internal and standalone package names.\n\n    Parameters\n    ----------\n    pkg: string\n        Package name.\n\n    Returns\n    -------\n    out: string|null\n        Alias.\n\n    Examples\n    --------\n    > var v = pkg2alias( '@stdlib/math/base/special/sin' )\n    <string>\n    > v = pkg2alias( '@stdlib/math-base-special-sin' )\n    <string>\n\n    See Also\n    --------\n    alias2pkg, aliases, pkg2related\n","pkg2related":"\npkg2related( pkg )\n    Returns package names related to a specified package name.\n\n    The function supports both internal and standalone package names.\n\n    Parameters\n    ----------\n    pkg: string\n        Package name.\n\n    Returns\n    -------\n    out: Array|null\n        Related package names.\n\n    Examples\n    --------\n    > var v = pkg2related( '@stdlib/math/base/special/sin' )\n    [...]\n    > v = pkg2related( '@stdlib/math-base-special-sin' )\n    [...]\n\n    See Also\n    --------\n    alias2related, aliases, pkg2alias\n","pkg2standalone":"\npkg2standalone( pkg )\n    Returns the standalone package name associated with a provided internal\n    package name.\n\n    Parameters\n    ----------\n    pkg: string\n        Package name.\n\n    Returns\n    -------\n    out: string|null\n        Standalone package name.\n\n    Examples\n    --------\n    > var v = pkg2standalone( '@stdlib/math/base/special/sin' )\n    '@stdlib/math-base-special-sin'\n\n    See Also\n    --------\n    alias2pkg, alias2standalone, aliases, pkg2alias, pkg2related\n","PLATFORM":"\nPLATFORM\n    Platform on which the current process is running.\n\n    Possible values:\n\n    - win32\n    - darwin\n    - linux\n    - freebsd\n    - sunos\n\n    Examples\n    --------\n    > PLATFORM\n    <string>\n\n    See Also\n    --------\n    ARCH\n","plot":"\nplot( [x, y,] [options] )\n    Returns a plot instance for creating 2-dimensional plots.\n\n    `x` and `y` arguments take precedence over `x` and `y` options.\n\n    Parameters\n    ----------\n    x: Array<Array>|Array<TypedArray> (optional)\n        An array of arrays containing x-coordinate values.\n\n    y: Array<Array>|Array<TypedArray> (optional)\n        An array of arrays containing y-coordinate values.\n\n    options: Object (optional)\n        Options.\n\n    options.autoRender: boolean (optional)\n        Boolean indicating whether to re-render on a 'change' event. Default:\n        false.\n\n    options.autoView: boolean (optional)\n        Boolean indicating whether to generate an updated view on a 'render'\n        event. Default: false.\n\n    options.colors: string|Array<string> (optional)\n        Data color(s). Default: 'category10'.\n\n    options.description: string (optional)\n        Plot description.\n\n    options.engine: string (optional)\n        Plot engine. Default: 'svg'.\n\n    options.height: number (optional)\n        Plot height (in pixels). Default: 400.\n\n    options.labels: Array|Array<string> (optional)\n        Data labels.\n\n    options.isDefined: Function (optional)\n        An accessor function indicating whether a datum is defined.\n\n    options.lineStyle: string|Array<string> (optional)\n        Data line style(s). Must be one of: '-', '--', ':', '-.', or 'none'.\n        Default: '-'.\n\n    options.lineOpacity: number|Array<number> (optional)\n        Data line opacity. Must be on the interval [0,1]. Default: 0.9.\n\n    options.lineWidth: integer|Array<integer> (optional)\n        Data line width (in pixels). Default: 2.\n\n    options.paddingBottom: integer (optional)\n        Bottom padding (in pixels). Default: 80.\n\n    options.paddingLeft: integer (optional)\n        Left padding (in pixels). Default: 90.\n\n    options.paddingRight: integer (optional)\n        Right padding (in pixels). Default: 20.\n\n    options.paddingTop: integer (optional)\n        Top padding (in pixels). Default: 80.\n\n    options.renderFormat: string (optional)\n        Plot render format. Must be one of 'vdom' or 'html'. Default: 'vdom'.\n\n    options.symbols: string|Array<string> (optional)\n        Data symbols. Must be one of 'closed-circle', 'open-circle', or 'none'.\n        Default: 'none'.\n\n    options.symbolsOpacity: number|Array<number> (optional)\n        Symbols opacity. Must be on the interval [0,1]. Default: 0.9.\n\n    options.symbolsSize: integer|Array<integer> (optional)\n        Symbols size (in pixels). Default: 6.\n\n    options.title: string (optional)\n        Plot title.\n\n    options.viewer: string (optional)\n        Plot viewer. Must be one of 'browser', 'terminal', 'stdout', 'window',\n        or 'none'. Default: 'none'.\n\n    options.width: number (optional)\n        Plot width (in pixels). Default: 400.\n\n    options.x: Array<Array>|Array<TypedArray> (optional)\n        x-coordinate values.\n\n    options.xAxisOrient: string (optional)\n        x-axis orientation. Must be either 'bottom' or 'top'. Default: 'bottom'.\n\n    options.xLabel: string (optional)\n        x-axis label. Default: 'x'.\n\n    options.xMax: number|null (optional)\n        Maximum value of the x-axis domain. If `null`, the maximum value is\n        calculated from the data. Default: null.\n\n    options.xMin: number|null (optional)\n        Minimum value of the x-axis domain. If `null`, the minimum value is\n        calculated from the data. Default: null.\n\n    options.xNumTicks: integer (optional)\n        Number of x-axis tick marks. Default: 5.\n\n    options.xRug: boolean|Array<boolean> (optional)\n        Boolean flag(s) indicating whether to render one or more rug plots along\n        the x-axis.\n\n    options.xRugOrient: string|Array<string> (optional)\n        x-axis rug plot orientation(s). Must be either 'bottom' or 'top'.\n        Default: 'bottom'.\n\n    options.xRugOpacity: number|Array<number> (optional)\n       x-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n    options.xRugSize: integer|Array<integer> (optional)\n       x-axis rug tick (tassel) size (in pixels). Default: 6.\n\n    options.xScale: string\n       x-axis scale. Default: 'linear'.\n\n    options.xTickFormat: string|null\n       x-axis tick format. Default: null.\n\n    options.y: Array<Array>|Array<TypedArray> (optional)\n        y-coordinate values.\n\n    options.yAxisOrient: string (optional)\n        x-axis orientation. Must be either 'left' or 'right'. Default: 'left'.\n\n    options.yLabel: string (optional)\n        y-axis label. Default: 'y'.\n\n    options.yMax: number|null (optional)\n        Maximum value of the y-axis domain. If `null`, the maximum value is\n        calculated from the data. Default: null.\n\n    options.yMin: number|null (optional)\n        Minimum value of the y-axis domain. If `null`, the minimum value is\n        calculated from the data. Default: null.\n\n    options.yNumTicks: integer (optional)\n        Number of x-axis tick marks. Default: 5.\n\n    options.yRug: boolean|Array<boolean> (optional)\n        Boolean flag(s) indicating whether to render one or more rug plots along\n        the y-axis.\n\n    options.yRugOrient: string|Array<string> (optional)\n        y-axis rug plot orientation(s). Must be either 'left' or 'right'.\n        Default: 'left'.\n\n    options.yRugOpacity: number|Array<number> (optional)\n       y-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n    options.yRugSize: integer|Array<integer> (optional)\n       y-axis rug tick (tassel) size (in pixels). Default: 6.\n\n    options.yScale: string\n       y-axis scale. Default: 'linear'.\n\n    options.yTickFormat: string|null\n       y-axis tick format. Default: null.\n\n    Returns\n    -------\n    plot: Plot\n        Plot instance.\n\n    plot.render()\n        Renders a plot as a virtual DOM tree.\n\n    plot.view( [viewer] )\n        Generates a plot view.\n\n    plot.x\n        x-coordinate values. An assigned value must be an array where each\n        element corresponds to a plotted dataset.\n\n    plot.y\n        y-coordinate values. An assigned value must be an array, where each\n        element corresponds to a plotted dataset.\n\n    plot.labels\n        Data labels. During plot creation, each plotted dataset is assigned a\n        label. If the number of labels is less than the number of plotted\n        datasets, labels are reused using modulo arithmetic.\n\n    plot.isDefined( d, i )\n        An accessor function which defines whether a datum is defined. This\n        accessor is used to define how missing values are encoded. The default\n        behavior is to ignore values which are `NaN`.\n\n    plot.colors\n        Data colors. To set the color all plotted datasets, provide a color\n        name. To specify the colors for each dataset, provide an array of\n        colors. During plot creation, each plotted dataset is assigned one of\n        the provided colors. If the number of colors is less than the number of\n        plotted datasets, colors are reused using modulo arithmetic. Lastly,\n        colors may also be specified by providing the name of a predefined color\n        scheme. The following schemes are supported: 'category10', 'category20',\n        'category20b', and 'category20c'.\n\n    plot.lineStyle\n        Data line style(s). The following line styles are supported: '-' (solid\n        line), '--' (dashed line), ':' (dotted line), '-.' (alternating dashes\n        and dots), and 'none' (no line). To specify the line style for each\n        dataset, provide an array of line styles. During plot creation, each\n        plotted dataset is assigned a line style. If the number of line styles\n        is less than the number of plotted datasets, line styles are reused\n        using modulo arithmetic.\n\n    plot.lineOpacity\n        Data line opacity, where an opacity of `0.0` make a line completely\n        transparent and an opacity of `1.0` makes a line completely opaque. To\n        specify the line opacity for each dataset, provide an array of\n        opacities. During plot creation, each plotted dataset is assigned an\n        opacity. If the number of opacities is less than the number of plotted\n        datasets, opacities are reused using modulo arithmetic.\n\n    plot.lineWidth\n        Data line width(s). To specify the line width for each dataset, provide\n        an array of widths. During plot creation, each plotted dataset is\n        assigned a line width. If the number of line widths is less than the\n        number of plotted datasets, line widths are reused using modulo\n        arithmetic.\n\n    plot.symbols\n        Data symbols. The following symbols are supported: 'closed-circle'\n        (closed circles), 'open-circle' (open circles), and 'none' (no symbols).\n        To specify the symbols used for each dataset, provide an array of\n        symbols. During plot creation, each plotted dataset is assigned a\n        symbol. If the number of symbols is less than the number of plotted\n        datasets, symbols are reused using modulo arithmetic.\n\n    plot.symbolSize\n        Symbols size. To specify the symbols size for each dataset, provide an\n        array of sizes. During plot creation, each plotted dataset is assigned\n        a symbols size. If the number of sizes is less than the number of\n        plotted datasets, sizes are reused using modulo arithmetic.\n\n    plot.symbolsOpacity\n        Symbols opacity, where an opacity of `0.0` makes a symbol completely\n        transparent and an opacity of `1.0` makes a symbol completely opaque. To\n        specify the opacity for each dataset, provide an array of opacities.\n        During plot creation, each plotted dataset is assigned an opacity. If\n        the number of opacities is less than the number of plotted datasets,\n        opacities are reused using modulo arithmetic.\n\n    plot.width\n        Plot width (in pixels).\n\n    plot.height\n        Plot height (in pixels).\n\n    plot.paddingLeft\n        Plot left padding (in pixels). Left padding is typically used to create\n        space for a left-oriented y-axis.\n\n    plot.paddingRight\n        Plot right padding (in pixels). Right padding is typically used to\n        create space for a right-oriented y-axis.\n\n    plot.paddingTop\n        Plot top padding (in pixels). Top padding is typically used to create\n        space for a title or top-oriented x-axis.\n\n    plot.paddingBottom\n        Plot bottom padding (in pixels). Bottom padding is typically used to\n        create space for a bottom-oriented x-axis.\n\n    plot.xMin\n        Minimum value of the x-axis domain. When retrieved, if the value has\n        been set to `null`, the returned value is computed from the `x` data.\n\n    plot.xMax\n        Maximum value of the x-axis domain. When retrieved, if the value has\n        been set to `null`, the returned value is computed from the `x` data.\n\n    plot.yMin\n        Minimum value of the y-axis domain. When retrieved, if the value has\n        been set to `null`, the returned value is computed from the `y` data.\n\n    plot.yMax\n        Maximum value of the y-axis domain. When retrieved, if the value has\n        been set to `null`, the returned value is computed from the `y` data.\n\n    plot.xScale\n        Scale function for mapping values to a coordinate along the x-axis. The\n        following `scales` are supported: 'linear' (linear scale) and 'time'\n        (time scale). When retrieved, the returned value is a scale function.\n\n    plot.yScale\n        Scale function for mapping values to a coordinate along the y-axis. The\n        following `scales` are supported: 'linear' (linear scale) and 'time'\n        (time scale). When retrieved, the returned value is a scale function.\n\n    plot.xTickFormat\n        x-axis tick format (e.g., '%H:%M'). When retrieved, if the value has not\n        been set to `null`, the returned value is a formatting function.\n\n    plot.yTickFormat\n        y-axis tick format (e.g., '%%'). When retrieved, if the value has not\n        been set to `null`, the returned value is a formatting function.\n\n    plot.xNumTicks\n        Number of x-axis tick marks. If the value is set to `null`, the number\n        of tick marks is computed internally.\n\n    plot.yNumTicks\n        Number of y-axis tick marks. If the value is set to `null`, the number\n        of tick marks is computed internally.\n\n    plot.xAxisOrient\n        x-axis orientation. The following orientations are supported: 'bottom'\n        and 'top'.\n\n    plot.yAxisOrient\n        y-axis orientation. The following orientations are supported: 'left' and\n        'right'.\n\n    plot.xRug\n        Boolean flag(s) indicating whether to display a rug plot along the x-\n        axis. To specify the flag for each dataset, provide an array of\n        booleans. During plot creation, each plotted dataset is assigned a flag.\n        If the number of flags is less than the number of plotted datasets,\n        flags are reused using modulo arithmetic.\n\n    plot.yRug\n        Boolean flag(s) indicating whether to display a rug plot along the y-\n        axis. To specify the flag for each dataset, provide an array of\n        booleans. During plot creation, each plotted dataset is assigned a flag.\n        If the number of flags is less than the number of plotted datasets,\n        flags are reused using modulo arithmetic.\n\n    plot.xRugOrient\n        x-axis rug orientation. The following orientations are supported:\n        'bottom' or 'top'. To specify the x-axis rug orientation for each\n        dataset, provide an array of orientations. During plot creation, each\n        plotted dataset is assigned an orientation. If the number of\n        orientations is less than the number of plotted datasets, orientations\n        are reused using modulo arithmetic.\n\n    plot.yRugOrient\n        y-axis rug orientation. The following orientations are supported: 'left'\n        or 'right'. To specify the y-axis rug orientation for each dataset,\n        provide an array of orientations. During plot creation, each plotted\n        dataset is assigned an orientation. If the number of orientations is\n        less than the number of plotted datasets, orientations are reused using\n        modulo arithmetic.\n\n    plot.xRugOpacity\n        x-axis rug opacity, where an opacity of `0.0` makes a rug completely\n        transparent and an opacity of `1.0` makes a rug completely opaque. To\n        specify the x-axis rug opacity for each dataset, provide an array of\n        opacities. During plot creation, each plotted dataset is assigned an\n        opacity. If the number of opacities is less than the number of plotted\n        datasets, opacities are reused using modulo arithmetic.\n\n    plot.yRugOpacity\n        y-axis rug opacity, where an opacity of `0.0` makes a rug completely\n        transparent and an opacity of `1.0` makes a rug completely opaque. To\n        specify the y-axis rug opacity for each dataset, provide an array of\n        opacities. During plot creation, each plotted dataset is assigned an\n        opacity. If the number of opacities is less than the number of plotted\n        datasets, opacities are reused using modulo arithmetic.\n\n    plot.xRugSize\n        x-axis rug tick (tassel) size. To specify the x-axis rug size for each\n        dataset, provide an array of sizes. During plot creation, each plotted\n        dataset is assigned a tick size. If the number of sizes is less than the\n        number of plotted datasets, sizes are reused using modulo arithmetic.\n\n    plot.yRugSize\n        y-axis rug tick (tassel) size. To specify the y-axis rug size for each\n        dataset, provide an array of sizes. During plot creation, each plotted\n        dataset is assigned a tick size. If the number of sizes is less than the\n        number of plotted datasets, sizes are reused using modulo arithmetic.\n\n    plot.description\n        Plot description.\n\n    plot.title\n        Plot title.\n\n    plot.xLabel\n        x-axis label.\n\n    plot.yLabel\n        y-axis label.\n\n    plot.engine\n        Plot rendering engine. The following engines are supported: 'svg'.\n\n    plot.renderFormat\n        Plot render format. The following formats are supported: 'vdom' and\n        'html'.\n\n    plot.autoRender\n        Rendering mode. If `true`, an instance renders on each 'change' event;\n        otherwise, rendering must be triggered manually.\n\n    plot.viewer\n        Plot viewer. The following viewers are supported: 'none', 'stdout',\n        'window', and 'browser'.\n\n    plot.autoView\n        Viewer mode. If `true`, an instance generates an updated view on each\n        'render' event; otherwise, generating a view must be triggered manually.\n\n    plot.graphWidth\n        Computed property corresponding to the expected graph width.\n\n    plot.graphHeight\n        Computed property corresponding to the expected graph height.\n\n    plot.xDomain\n        Computed property corresponding to the x-axis domain.\n\n    plot.yDomain\n        Computed property corresponding to the y-axis domain.\n\n    plot.xRange\n        Computed property corresponding to the x-axis range.\n\n    plot.yRange\n        Computed property correspond to the y-axis range.\n\n    plot.xPos\n        A function which maps values to x-axis coordinate values.\n\n    plot.yPos\n        A function which maps values to y-axis coordinate values.\n\n    Examples\n    --------\n    > var plot = plot()\n    <Plot>\n\n    // Provide plot data at instantiation:\n    > var x = [[0.10, 0.20, 0.30]];\n    > var y = [[0.52, 0.79, 0.64]];\n    > plot = plot( x, y )\n    <Plot>\n\n    See Also\n    --------\n    Plot\n","Plot":"\nPlot( [x, y,] [options] )\n    Returns a plot instance for creating 2-dimensional plots.\n\n    `x` and `y` arguments take precedence over `x` and `y` options.\n\n    Parameters\n    ----------\n    x: Array<Array>|Array<TypedArray> (optional)\n        An array of arrays containing x-coordinate values.\n\n    y: Array<Array>|Array<TypedArray> (optional)\n        An array of arrays containing y-coordinate values.\n\n    options: Object (optional)\n        Options.\n\n    options.autoRender: boolean (optional)\n        Boolean indicating whether to re-render on a 'change' event. Default:\n        false.\n\n    options.autoView: boolean (optional)\n        Boolean indicating whether to generate an updated view on a 'render'\n        event. Default: false.\n\n    options.colors: string|Array<string> (optional)\n        Data color(s). Default: 'category10'.\n\n    options.description: string (optional)\n        Plot description.\n\n    options.engine: string (optional)\n        Plot engine. Default: 'svg'.\n\n    options.height: number (optional)\n        Plot height (in pixels). Default: 400.\n\n    options.labels: Array|Array<string> (optional)\n        Data labels.\n\n    options.isDefined: Function (optional)\n        An accessor function indicating whether a datum is defined.\n\n    options.lineStyle: string|Array<string> (optional)\n        Data line style(s). Must be one of: '-', '--', ':', '-.', or 'none'.\n        Default: '-'.\n\n    options.lineOpacity: number|Array<number> (optional)\n        Data line opacity. Must be on the interval [0,1]. Default: 0.9.\n\n    options.lineWidth: integer|Array<integer> (optional)\n        Data line width (in pixels). Default: 2.\n\n    options.paddingBottom: integer (optional)\n        Bottom padding (in pixels). Default: 80.\n\n    options.paddingLeft: integer (optional)\n        Left padding (in pixels). Default: 90.\n\n    options.paddingRight: integer (optional)\n        Right padding (in pixels). Default: 20.\n\n    options.paddingTop: integer (optional)\n        Top padding (in pixels). Default: 80.\n\n    options.renderFormat: string (optional)\n        Plot render format. Must be one of 'vdom' or 'html'. Default: 'vdom'.\n\n    options.symbols: string|Array<string> (optional)\n        Data symbols. Must be one of 'closed-circle', 'open-circle', or 'none'.\n        Default: 'none'.\n\n    options.symbolsOpacity: number|Array<number> (optional)\n        Symbols opacity. Must be on the interval [0,1]. Default: 0.9.\n\n    options.symbolsSize: integer|Array<integer> (optional)\n        Symbols size (in pixels). Default: 6.\n\n    options.title: string (optional)\n        Plot title.\n\n    options.viewer: string (optional)\n        Plot viewer. Must be one of 'browser', 'terminal', 'stdout', 'window',\n        or 'none'. Default: 'none'.\n\n    options.width: number (optional)\n        Plot width (in pixels). Default: 400.\n\n    options.x: Array<Array>|Array<TypedArray> (optional)\n        x-coordinate values.\n\n    options.xAxisOrient: string (optional)\n        x-axis orientation. Must be either 'bottom' or 'top'. Default: 'bottom'.\n\n    options.xLabel: string (optional)\n        x-axis label. Default: 'x'.\n\n    options.xMax: number|null (optional)\n        Maximum value of the x-axis domain. If `null`, the maximum value is\n        calculated from the data. Default: null.\n\n    options.xMin: number|null (optional)\n        Minimum value of the x-axis domain. If `null`, the minimum value is\n        calculated from the data. Default: null.\n\n    options.xNumTicks: integer (optional)\n        Number of x-axis tick marks. Default: 5.\n\n    options.xRug: boolean|Array<boolean> (optional)\n        Boolean flag(s) indicating whether to render one or more rug plots along\n        the x-axis.\n\n    options.xRugOrient: string|Array<string> (optional)\n        x-axis rug plot orientation(s). Must be either 'bottom' or 'top'.\n        Default: 'bottom'.\n\n    options.xRugOpacity: number|Array<number> (optional)\n       x-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n    options.xRugSize: integer|Array<integer> (optional)\n       x-axis rug tick (tassel) size (in pixels). Default: 6.\n\n    options.xScale: string\n       x-axis scale. Default: 'linear'.\n\n    options.xTickFormat: string|null\n       x-axis tick format. Default: null.\n\n    options.y: Array<Array>|Array<TypedArray> (optional)\n        y-coordinate values.\n\n    options.yAxisOrient: string (optional)\n        x-axis orientation. Must be either 'left' or 'right'. Default: 'left'.\n\n    options.yLabel: string (optional)\n        y-axis label. Default: 'y'.\n\n    options.yMax: number|null (optional)\n        Maximum value of the y-axis domain. If `null`, the maximum value is\n        calculated from the data. Default: null.\n\n    options.yMin: number|null (optional)\n        Minimum value of the y-axis domain. If `null`, the minimum value is\n        calculated from the data. Default: null.\n\n    options.yNumTicks: integer (optional)\n        Number of x-axis tick marks. Default: 5.\n\n    options.yRug: boolean|Array<boolean> (optional)\n        Boolean flag(s) indicating whether to render one or more rug plots along\n        the y-axis.\n\n    options.yRugOrient: string|Array<string> (optional)\n        y-axis rug plot orientation(s). Must be either 'left' or 'right'.\n        Default: 'left'.\n\n    options.yRugOpacity: number|Array<number> (optional)\n       y-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n    options.yRugSize: integer|Array<integer> (optional)\n       y-axis rug tick (tassel) size (in pixels). Default: 6.\n\n    options.yScale: string\n       y-axis scale. Default: 'linear'.\n\n    options.yTickFormat: string|null\n       y-axis tick format. Default: null.\n\n    Returns\n    -------\n    plot: Plot\n        Plot instance.\n\n    plot.render()\n        Renders a plot as a virtual DOM tree.\n\n    plot.view( [viewer] )\n        Generates a plot view.\n\n    plot.x\n        x-coordinate values. An assigned value must be an array where each\n        element corresponds to a plotted dataset.\n\n    plot.y\n        y-coordinate values. An assigned value must be an array, where each\n        element corresponds to a plotted dataset.\n\n    plot.labels\n        Data labels. During plot creation, each plotted dataset is assigned a\n        label. If the number of labels is less than the number of plotted\n        datasets, labels are reused using modulo arithmetic.\n\n    plot.isDefined( d, i )\n        An accessor function which defines whether a datum is defined. This\n        accessor is used to define how missing values are encoded. The default\n        behavior is to ignore values which are `NaN`.\n\n    plot.colors\n        Data colors. To set the color all plotted datasets, provide a color\n        name. To specify the colors for each dataset, provide an array of\n        colors. During plot creation, each plotted dataset is assigned one of\n        the provided colors. If the number of colors is less than the number of\n        plotted datasets, colors are reused using modulo arithmetic. Lastly,\n        colors may also be specified by providing the name of a predefined color\n        scheme. The following schemes are supported: 'category10', 'category20',\n        'category20b', and 'category20c'.\n\n    plot.lineStyle\n        Data line style(s). The following line styles are supported: '-' (solid\n        line), '--' (dashed line), ':' (dotted line), '-.' (alternating dashes\n        and dots), and 'none' (no line). To specify the line style for each\n        dataset, provide an array of line styles. During plot creation, each\n        plotted dataset is assigned a line style. If the number of line styles\n        is less than the number of plotted datasets, line styles are reused\n        using modulo arithmetic.\n\n    plot.lineOpacity\n        Data line opacity, where an opacity of `0.0` make a line completely\n        transparent and an opacity of `1.0` makes a line completely opaque. To\n        specify the line opacity for each dataset, provide an array of\n        opacities. During plot creation, each plotted dataset is assigned an\n        opacity. If the number of opacities is less than the number of plotted\n        datasets, opacities are reused using modulo arithmetic.\n\n    plot.lineWidth\n        Data line width(s). To specify the line width for each dataset, provide\n        an array of widths. During plot creation, each plotted dataset is\n        assigned a line width. If the number of line widths is less than the\n        number of plotted datasets, line widths are reused using modulo\n        arithmetic.\n\n    plot.symbols\n        Data symbols. The following symbols are supported: 'closed-circle'\n        (closed circles), 'open-circle' (open circles), and 'none' (no symbols).\n        To specify the symbols used for each dataset, provide an array of\n        symbols. During plot creation, each plotted dataset is assigned a\n        symbol. If the number of symbols is less than the number of plotted\n        datasets, symbols are reused using modulo arithmetic.\n\n    plot.symbolSize\n        Symbols size. To specify the symbols size for each dataset, provide an\n        array of sizes. During plot creation, each plotted dataset is assigned\n        a symbols size. If the number of sizes is less than the number of\n        plotted datasets, sizes are reused using modulo arithmetic.\n\n    plot.symbolsOpacity\n        Symbols opacity, where an opacity of `0.0` makes a symbol completely\n        transparent and an opacity of `1.0` makes a symbol completely opaque. To\n        specify the opacity for each dataset, provide an array of opacities.\n        During plot creation, each plotted dataset is assigned an opacity. If\n        the number of opacities is less than the number of plotted datasets,\n        opacities are reused using modulo arithmetic.\n\n    plot.width\n        Plot width (in pixels).\n\n    plot.height\n        Plot height (in pixels).\n\n    plot.paddingLeft\n        Plot left padding (in pixels). Left padding is typically used to create\n        space for a left-oriented y-axis.\n\n    plot.paddingRight\n        Plot right padding (in pixels). Right padding is typically used to\n        create space for a right-oriented y-axis.\n\n    plot.paddingTop\n        Plot top padding (in pixels). Top padding is typically used to create\n        space for a title or top-oriented x-axis.\n\n    plot.paddingBottom\n        Plot bottom padding (in pixels). Bottom padding is typically used to\n        create space for a bottom-oriented x-axis.\n\n    plot.xMin\n        Minimum value of the x-axis domain. When retrieved, if the value has\n        been set to `null`, the returned value is computed from the `x` data.\n\n    plot.xMax\n        Maximum value of the x-axis domain. When retrieved, if the value has\n        been set to `null`, the returned value is computed from the `x` data.\n\n    plot.yMin\n        Minimum value of the y-axis domain. When retrieved, if the value has\n        been set to `null`, the returned value is computed from the `y` data.\n\n    plot.yMax\n        Maximum value of the y-axis domain. When retrieved, if the value has\n        been set to `null`, the returned value is computed from the `y` data.\n\n    plot.xScale\n        Scale function for mapping values to a coordinate along the x-axis. The\n        following `scales` are supported: 'linear' (linear scale) and 'time'\n        (time scale). When retrieved, the returned value is a scale function.\n\n    plot.yScale\n        Scale function for mapping values to a coordinate along the y-axis. The\n        following `scales` are supported: 'linear' (linear scale) and 'time'\n        (time scale). When retrieved, the returned value is a scale function.\n\n    plot.xTickFormat\n        x-axis tick format (e.g., '%H:%M'). When retrieved, if the value has not\n        been set to `null`, the returned value is a formatting function.\n\n    plot.yTickFormat\n        y-axis tick format (e.g., '%%'). When retrieved, if the value has not\n        been set to `null`, the returned value is a formatting function.\n\n    plot.xNumTicks\n        Number of x-axis tick marks. If the value is set to `null`, the number\n        of tick marks is computed internally.\n\n    plot.yNumTicks\n        Number of y-axis tick marks. If the value is set to `null`, the number\n        of tick marks is computed internally.\n\n    plot.xAxisOrient\n        x-axis orientation. The following orientations are supported: 'bottom'\n        and 'top'.\n\n    plot.yAxisOrient\n        y-axis orientation. The following orientations are supported: 'left' and\n        'right'.\n\n    plot.xRug\n        Boolean flag(s) indicating whether to display a rug plot along the x-\n        axis. To specify the flag for each dataset, provide an array of\n        booleans. During plot creation, each plotted dataset is assigned a flag.\n        If the number of flags is less than the number of plotted datasets,\n        flags are reused using modulo arithmetic.\n\n    plot.yRug\n        Boolean flag(s) indicating whether to display a rug plot along the y-\n        axis. To specify the flag for each dataset, provide an array of\n        booleans. During plot creation, each plotted dataset is assigned a flag.\n        If the number of flags is less than the number of plotted datasets,\n        flags are reused using modulo arithmetic.\n\n    plot.xRugOrient\n        x-axis rug orientation. The following orientations are supported:\n        'bottom' or 'top'. To specify the x-axis rug orientation for each\n        dataset, provide an array of orientations. During plot creation, each\n        plotted dataset is assigned an orientation. If the number of\n        orientations is less than the number of plotted datasets, orientations\n        are reused using modulo arithmetic.\n\n    plot.yRugOrient\n        y-axis rug orientation. The following orientations are supported: 'left'\n        or 'right'. To specify the y-axis rug orientation for each dataset,\n        provide an array of orientations. During plot creation, each plotted\n        dataset is assigned an orientation. If the number of orientations is\n        less than the number of plotted datasets, orientations are reused using\n        modulo arithmetic.\n\n    plot.xRugOpacity\n        x-axis rug opacity, where an opacity of `0.0` makes a rug completely\n        transparent and an opacity of `1.0` makes a rug completely opaque. To\n        specify the x-axis rug opacity for each dataset, provide an array of\n        opacities. During plot creation, each plotted dataset is assigned an\n        opacity. If the number of opacities is less than the number of plotted\n        datasets, opacities are reused using modulo arithmetic.\n\n    plot.yRugOpacity\n        y-axis rug opacity, where an opacity of `0.0` makes a rug completely\n        transparent and an opacity of `1.0` makes a rug completely opaque. To\n        specify the y-axis rug opacity for each dataset, provide an array of\n        opacities. During plot creation, each plotted dataset is assigned an\n        opacity. If the number of opacities is less than the number of plotted\n        datasets, opacities are reused using modulo arithmetic.\n\n    plot.xRugSize\n        x-axis rug tick (tassel) size. To specify the x-axis rug size for each\n        dataset, provide an array of sizes. During plot creation, each plotted\n        dataset is assigned a tick size. If the number of sizes is less than the\n        number of plotted datasets, sizes are reused using modulo arithmetic.\n\n    plot.yRugSize\n        y-axis rug tick (tassel) size. To specify the y-axis rug size for each\n        dataset, provide an array of sizes. During plot creation, each plotted\n        dataset is assigned a tick size. If the number of sizes is less than the\n        number of plotted datasets, sizes are reused using modulo arithmetic.\n\n    plot.description\n        Plot description.\n\n    plot.title\n        Plot title.\n\n    plot.xLabel\n        x-axis label.\n\n    plot.yLabel\n        y-axis label.\n\n    plot.engine\n        Plot rendering engine. The following engines are supported: 'svg'.\n\n    plot.renderFormat\n        Plot render format. The following formats are supported: 'vdom' and\n        'html'.\n\n    plot.autoRender\n        Rendering mode. If `true`, an instance renders on each 'change' event;\n        otherwise, rendering must be triggered manually.\n\n    plot.viewer\n        Plot viewer. The following viewers are supported: 'none', 'stdout',\n        'window', and 'browser'.\n\n    plot.autoView\n        Viewer mode. If `true`, an instance generates an updated view on each\n        'render' event; otherwise, generating a view must be triggered manually.\n\n    plot.graphWidth\n        Computed property corresponding to the expected graph width.\n\n    plot.graphHeight\n        Computed property corresponding to the expected graph height.\n\n    plot.xDomain\n        Computed property corresponding to the x-axis domain.\n\n    plot.yDomain\n        Computed property corresponding to the y-axis domain.\n\n    plot.xRange\n        Computed property corresponding to the x-axis range.\n\n    plot.yRange\n        Computed property correspond to the y-axis range.\n\n    plot.xPos\n        A function which maps values to x-axis coordinate values.\n\n    plot.yPos\n        A function which maps values to y-axis coordinate values.\n\n    Examples\n    --------\n    > var plot = Plot()\n    <Plot>\n\n    // Provide plot data at instantiation:\n    > var x = [[0.10, 0.20, 0.30]];\n    > var y = [[0.52, 0.79, 0.64]];\n    > plot = Plot( x, y )\n    <Plot>\n\n    See Also\n    --------\n    plot\n","pluck":"\npluck( arr, prop[, options] )\n    Extracts a property value from each element of an object array.\n\n    The function skips `null` and `undefined` array elements.\n\n    Extracted values are not cloned.\n\n    Parameters\n    ----------\n    arr: Array\n        Source array.\n\n    prop: string\n        Property to access.\n\n    options: Object (optional)\n        Options.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to return a new data structure. To mutate the\n        input data structure (e.g., when input values can be discarded or when\n        optimizing memory usage), set the `copy` option to `false`. Default:\n        true.\n\n    Returns\n    -------\n    out: Array\n        Destination array.\n\n    Examples\n    --------\n    > var arr = [\n    ...     { 'a': 1, 'b': 2 },\n    ...     { 'a': 0.5, 'b': 3 }\n    ... ];\n    > var out = pluck( arr, 'a' )\n    [ 1, 0.5 ]\n\n    > arr = [\n    ...     { 'a': 1, 'b': 2 },\n    ...     { 'a': 0.5, 'b': 3 }\n    ... ];\n    > out = pluck( arr, 'a', { 'copy': false } )\n    [ 1, 0.5 ]\n    > var bool = ( arr[ 0 ] === out[ 0 ] )\n    true\n\n    See Also\n    --------\n    deepPluck, pick\n","pop":"\npop( collection )\n    Removes and returns the last element of a collection.\n\n    The function returns an array with two elements: the shortened collection\n    and the removed element.\n\n    If the input collection is a typed array whose length is greater than `0`,\n    the first return value does not equal the input reference.\n\n    For purposes of generality, always treat the output collection as distinct\n    from the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        A collection. If the collection is an `Object`, the value should be\n        array-like.\n\n    Returns\n    -------\n    out: Array\n        Updated collection and the removed item.\n\n    Examples\n    --------\n    // Arrays:\n    > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > var out = pop( arr )\n    [ [ 1.0, 2.0, 3.0, 4.0 ], 5.0 ]\n\n    // Typed arrays:\n    > arr = new Float64Array( [ 1.0, 2.0 ] );\n    > out = pop( arr )\n    [ <Float64Array>[ 1.0 ], 2.0 ]\n\n    // Array-like object:\n    > arr = { 'length': 2, '0': 1.0, '1': 2.0 };\n    > out = pop( arr )\n    [ { 'length': 1, '0': 1.0 }, 2.0 ]\n\n    See Also\n    --------\n    push, shift, unshift\n","porterStemmer":"\nporterStemmer( word )\n    Extracts the stem of a given word.\n\n    Parameters\n    ----------\n    word: string\n        Input word.\n\n    Returns\n    -------\n    out: string\n        Word stem.\n\n    Examples\n    --------\n    > var out = porterStemmer( 'walking' )\n    'walk'\n    > out = porterStemmer( 'walked' )\n    'walk'\n    > out = porterStemmer( 'walks' )\n    'walk'\n    > out = porterStemmer( '' )\n    ''\n\n","prepend":"\nprepend( collection1, collection2 )\n    Adds the elements of one collection to the beginning of another collection.\n\n    If the input collection is a typed array, the output value does not equal\n    the input reference and the underlying `ArrayBuffer` may *not* be the same\n    as the `ArrayBuffer` belonging to the input view.\n\n    For purposes of generality, always treat the output collection as distinct\n    from the input collection.\n\n    Parameters\n    ----------\n    collection1: Array|TypedArray|Object\n        A collection. If the collection is an `Object`, the collection should be\n        array-like.\n\n    collection2: Array|TypedArray|Object\n        A collection containing the elements to add. If the collection is an\n        `Object`, the collection should be array-like.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Updated collection.\n\n    Examples\n    --------\n    // Arrays:\n    > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > arr = prepend( arr, [ 6.0, 7.0 ] )\n    [ 6.0, 7.0, 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Typed arrays:\n    > arr = new Float64Array( [ 1.0, 2.0 ] );\n    > arr = prepend( arr, [ 3.0, 4.0 ] )\n    <Float64Array>[ 3.0, 4.0, 1.0, 2.0 ]\n\n    // Array-like object:\n    > arr = { 'length': 1, '0': 1.0 };\n    > arr = prepend( arr, [ 2.0, 3.0 ] )\n    { 'length': 3, '0': 2.0, '1': 3.0, '2': 1.0 }\n\n    See Also\n    --------\n    append, unshift\n","prevGraphemeClusterBreak":"\nprevGraphemeClusterBreak( str[, fromIndex] )\n    Returns the previous extended grapheme cluster break in a string before a\n    specified position.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    fromIndex: integer (optional)\n        Position. Default: str.length-1.\n\n    Returns\n    -------\n    out: integer\n        Previous extended grapheme cluster break position.\n\n    Examples\n    --------\n    > var out = prevGraphemeClusterBreak( 'last man standing', 4 )\n    3\n    > out = prevGraphemeClusterBreak( 'presidential election', 8 )\n    7\n    > out = prevGraphemeClusterBreak( 'अनुच्छेद', 2 )\n    0\n    > out = prevGraphemeClusterBreak( '🌷', 1 )\n    -1\n\n    See Also\n    --------\n    numGraphemeClusters, nextGraphemeClusterBreak","PRIMES_100K":"\nPRIMES_100K()\n    Returns an array containing the first 100,000 prime numbers.\n\n    Returns\n    -------\n    out: Array<number>\n        List of primes.\n\n    Examples\n    --------\n    > var list = PRIMES_100K()\n    [ 2, 3, 5, ... ]\n\n    See Also\n    --------\n    iterPrimesSeq\n","properties":"\nproperties( value )\n    Returns an array of an object's own enumerable and non-enumerable property\n    names and symbols.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    props: Array\n        List of an object's own enumerable and non-enumerable properties.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var props = properties( obj )\n    [ 'beep' ]\n\n    See Also\n    --------\n    defineProperties, inheritedProperties, propertiesIn, propertyNames, propertySymbols\n","propertiesIn":"\npropertiesIn( value )\n    Returns an array of an object's own and inherited property names and\n    symbols.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    props: Array\n        List of an object's own and inherited property names and symbols.\n\n    Examples\n    --------\n    > var props = propertiesIn( [] )\n\n    See Also\n    --------\n    defineProperties, inheritedProperties, properties, propertyNamesIn, propertySymbolsIn\n","propertyDescriptor":"\npropertyDescriptor( value, property )\n    Returns a property descriptor for an object's own property.\n\n    If provided `null` or `undefined` or provided a non-existent property, the\n    function returns `null`.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    property: string|symbol\n        Property name.\n\n    Returns\n    -------\n    desc: Object|null\n        Property descriptor.\n\n    Examples\n    --------\n    > var obj = { 'a': 'b' };\n    > var desc = propertyDescriptor( obj, 'a' )\n    {...}\n\n    See Also\n    --------\n    hasOwnProp, defineProperty, propertyDescriptorIn, propertyDescriptors\n","propertyDescriptorIn":"\npropertyDescriptorIn( value, property )\n    Returns a property descriptor for an object's own or inherited property.\n\n    If provided `null` or `undefined` or provided a non-existent property, the\n    function returns `null`.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    property: string|symbol\n        Property name.\n\n    Returns\n    -------\n    desc: Object|null\n        Property descriptor.\n\n    Examples\n    --------\n    > var obj = { 'a': 'b' };\n    > var desc = propertyDescriptorIn( obj, 'a' )\n    {...}\n\n    See Also\n    --------\n    hasProp, defineProperty, propertyDescriptor, propertyDescriptorsIn\n","propertyDescriptors":"\npropertyDescriptors( value )\n    Returns an object's own property descriptors.\n\n    If provided `null` or `undefined`, the function returns an empty object.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    desc: Object\n        Property descriptors.\n\n    Examples\n    --------\n    > var obj = { 'a': 'b' };\n    > var desc = propertyDescriptors( obj )\n    { 'a': {...} }\n\n    See Also\n    --------\n    defineProperty, defineProperties, propertyDescriptor, propertyDescriptorsIn, propertyNames, propertySymbols\n","propertyDescriptorsIn":"\npropertyDescriptorsIn( value )\n    Returns an object's own and inherited property descriptors.\n\n    If provided `null` or `undefined`, the function returns an empty object.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    desc: Object\n        An object's own and inherited property descriptors.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var desc = propertyDescriptorsIn( obj )\n    { 'beep': {...}, 'foo': {...}, ... }\n\n    See Also\n    --------\n    defineProperties, propertyDescriptorIn, propertyDescriptors, propertyNamesIn, propertySymbolsIn\n","propertyNames":"\npropertyNames( value )\n    Returns an array of an object's own enumerable and non-enumerable property\n    names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's own enumerable and non-enumerable property names.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var keys = propertyNames( obj )\n    [ 'beep' ]\n\n    See Also\n    --------\n    objectKeys, nonEnumerablePropertyNames, propertyNamesIn, propertySymbols\n","propertyNamesIn":"\npropertyNamesIn( value )\n    Returns an array of an object's own and inherited enumerable and non-\n    enumerable property names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's own and inherited enumerable and non-enumerable\n        property names.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var keys = propertyNamesIn( obj )\n    e.g., [ 'beep', 'foo', ... ]\n\n    See Also\n    --------\n    objectKeys, nonEnumerablePropertyNamesIn, propertyNames, propertySymbolsIn\n","propertySymbols":"\npropertySymbols( value )\n    Returns an array of an object's own symbol properties.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's own symbol properties.\n\n    Examples\n    --------\n    > var s = propertySymbols( {} )\n\n    See Also\n    --------\n    propertyNames, propertySymbolsIn\n","propertySymbolsIn":"\npropertySymbolsIn( value )\n    Returns an array of an object's own and inherited symbol properties.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's own and inherited symbol properties.\n\n    Examples\n    --------\n    > var s = propertySymbolsIn( [] )\n\n    See Also\n    --------\n    propertyNamesIn, propertySymbols\n","Proxy":"\nProxy( target, handlers )\n    Returns a proxy object implementing custom behavior for specified object\n    operations.\n\n    The following \"traps\" are supported:\n\n    - getPrototypeOf( target )\n        Trap for `Object.getPrototypeOf()`. Can be used to intercept the\n        `instanceof` operator. The method must return an object or `null`.\n\n    - setPrototypeOf( target, prototype )\n        Trap for `Object.setPrototypeOf()`. The method must return a boolean\n        indicating if prototype successfully set.\n\n    - isExtensible( target )\n        Trap for `Object.isExtensible()`. The method must return a boolean.\n\n    - preventExtensions( target )\n        Trap for `Object.preventExtensions()`. The method must return a boolean.\n\n    - getOwnPropertyDescriptor( target, property )\n        Trap for `Object.getOwnPropertyDescriptor()`. The method must return an\n        object or `undefined`.\n\n    - defineProperty( target, property, descriptor )\n        Trap for `Object.defineProperty()`. The method must return a boolean\n        indicating whether the operation succeeded.\n\n    - has( target, property )\n        Trap for the `in` operator. The method must return a boolean.\n\n    - get( target, property, receiver )\n        Trap for retrieving property values. The method can return any value.\n\n    - set( target, property, value, receiver )\n        Trap for setting property values. The method should return a boolean\n        indicating whether assignment succeeded.\n\n    - deleteProperty( target, property )\n        Trap for the `delete` operator. The method must return a boolean\n        indicating whether operation succeeded.\n\n    - ownKeys( target )\n        Trap for `Object.keys`, `Object.getOwnPropertyNames()`, and\n        `Object.getOwnPropertySymbols()`. The method must return an enumerable\n        object.\n\n    - apply( target, thisArg, argumentsList )\n        Trap for a function call. The method can return any value.\n\n    - construct( target, argumentsList, newTarget )\n        Trap for the `new` operator. The method must return an object.\n\n    All traps are optional. If a trap is not defined, the default behavior is to\n    forward the operation to the target.\n\n    Parameters\n    ----------\n    target: Object\n        Object which the proxy virtualizes.\n\n    handlers: Object\n        Object whose properties are functions which define the behavior of the\n        proxy when performing operations.\n\n    Returns\n    -------\n    p: Object\n        Proxy object.\n\n    Examples\n    --------\n    > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n    > var h = { 'get': get };\n    > var p = new Proxy( {}, h );\n    > p.a = 3.14;\n    > p.a\n    6.28\n\n\nProxy.revocable( target, handlers )\n    Returns a revocable proxy object.\n\n    Parameters\n    ----------\n    target: Object\n        Object which the proxy virtualizes.\n\n    handlers: Object\n        Object whose properties are functions which define the behavior of the\n        proxy when performing operations.\n\n    Returns\n    -------\n    p: Object\n        Revocable proxy object.\n\n    p.proxy: Object\n        Proxy object.\n\n    p.revoke: Function\n        Invalidates a proxy, rendering a proxy object unusable.\n\n    Examples\n    --------\n    > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n    > var h = { 'get': get };\n    > var p = Proxy.revocable( {}, h );\n    > p.proxy.a = 3.14;\n    > p.proxy.a\n    6.28\n    > p.revoke();\n\n","Proxy.revocable":"\nProxy.revocable( target, handlers )\n    Returns a revocable proxy object.\n\n    Parameters\n    ----------\n    target: Object\n        Object which the proxy virtualizes.\n\n    handlers: Object\n        Object whose properties are functions which define the behavior of the\n        proxy when performing operations.\n\n    Returns\n    -------\n    p: Object\n        Revocable proxy object.\n\n    p.proxy: Object\n        Proxy object.\n\n    p.revoke: Function\n        Invalidates a proxy, rendering a proxy object unusable.\n\n    Examples\n    --------\n    > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n    > var h = { 'get': get };\n    > var p = Proxy.revocable( {}, h );\n    > p.proxy.a = 3.14;\n    > p.proxy.a\n    6.28\n    > p.revoke();","push":"\npush( collection, ...items )\n    Adds one or more elements to the end of a collection.\n\n    If the input collection is a typed array, the output value does not equal\n    the input reference and the underlying `ArrayBuffer` may *not* be the same\n    as the `ArrayBuffer` belonging to the input view.\n\n    For purposes of generality, always treat the output collection as distinct\n    from the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        A collection. If the collection is an `Object`, the collection should be\n        array-like.\n\n    items: ...any\n        Items to add.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Updated collection.\n\n    Examples\n    --------\n    // Arrays:\n    > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > arr = push( arr, 6.0, 7.0 )\n    [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]\n\n    // Typed arrays:\n    > arr = new Float64Array( [ 1.0, 2.0 ] );\n    > arr = push( arr, 3.0, 4.0 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Array-like object:\n    > arr = { 'length': 0 };\n    > arr = push( arr, 1.0, 2.0 )\n    { 'length': 2, '0': 1.0, '1': 2.0 }\n\n    See Also\n    --------\n    pop, shift, unshift\n","quarterOfYear":"\nquarterOfYear( [month] )\n    Returns the quarter of the year.\n\n    By default, the function returns the quarter of the year for the current\n    month in the current year (according to local time). To determine the\n    quarter for a particular month, provide either a month or a `Date`\n    object.\n\n    A `month` may be either a month's integer value, three letter abbreviation,\n    or full name (case insensitive).\n\n    Parameters\n    ----------\n    month: integer|string|Date (optional)\n        Month (or `Date`).\n\n    Returns\n    -------\n    out: integer\n        Quarter of the year.\n\n    Examples\n    --------\n    > var q = quarterOfYear( new Date() )\n    <number>\n    > q = quarterOfYear( 4 )\n    2\n    > q = quarterOfYear( 'June' )\n    2\n\n    // Other ways to supply month:\n    > q = quarterOfYear( 'April' )\n    2\n    > q = quarterOfYear( 'apr' )\n    2\n\n    See Also\n    --------\n    dayOfYear\n","random.array.arcsine":"\nrandom.array.arcsine( len, a, b[, options] )\n    Returns an array containing pseudorandom numbers drawn from an arcsine\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.arcsine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.arcsine.assign( a, b, out )\n    Fills an array with pseudorandom numbers drawn from an arcsine distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.arcsine.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.arcsine.factory( [a, b, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an arcsine distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.arcsine.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.arcsine.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.arcsine.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.arcsine.PRNG;\n\n\nrandom.array.arcsine.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.arcsine.seed;\n\n\nrandom.array.arcsine.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.arcsine.seedLength;\n\n\nrandom.array.arcsine.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.arcsine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.arcsine.state\n    <Uint32Array>\n\n    > out = random.array.arcsine( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.arcsine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.arcsine.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.arcsine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.arcsine.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.arcsine.stateLength;\n\n\nrandom.array.arcsine.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.arcsine.byteLength;\n\n    See Also\n    --------\n    base.random.arcsine, random.strided.arcsine\n","random.array.arcsine.assign":"\nrandom.array.arcsine.assign( a, b, out )\n    Fills an array with pseudorandom numbers drawn from an arcsine distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.arcsine.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.arcsine.factory":"\nrandom.array.arcsine.factory( [a, b, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an arcsine distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.arcsine.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.arcsine.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.arcsine.PRNG":"\nrandom.array.arcsine.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.arcsine.PRNG;","random.array.arcsine.seed":"\nrandom.array.arcsine.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.arcsine.seed;","random.array.arcsine.seedLength":"\nrandom.array.arcsine.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.arcsine.seedLength;","random.array.arcsine.state":"\nrandom.array.arcsine.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.arcsine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.arcsine.state\n    <Uint32Array>\n\n    > out = random.array.arcsine( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.arcsine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.arcsine.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.arcsine( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.arcsine.stateLength":"\nrandom.array.arcsine.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.arcsine.stateLength;","random.array.arcsine.byteLength":"\nrandom.array.arcsine.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.arcsine.byteLength;\n\n    See Also\n    --------\n    base.random.arcsine, random.strided.arcsine","random.array.bernoulli":"\nrandom.array.bernoulli( len, p[, options] )\n    Returns an array containing pseudorandom numbers drawn from a Bernoulli\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.bernoulli( 3, 0.5 )\n    <Float64Array>\n\n\nrandom.array.bernoulli.assign( p, out )\n    Fills an array with pseudorandom numbers drawn from a Bernoulli\n    distribution.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.bernoulli.assign( 0.5, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.bernoulli.factory( [p, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Bernoulli distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.bernoulli.factory();\n    > var out = fcn( 3, 0.5 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.bernoulli.factory( 0.5 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.bernoulli.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.bernoulli.PRNG;\n\n\nrandom.array.bernoulli.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.bernoulli.seed;\n\n\nrandom.array.bernoulli.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.bernoulli.seedLength;\n\n\nrandom.array.bernoulli.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.bernoulli( 3, 0.5 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.bernoulli.state\n    <Uint32Array>\n\n    > out = random.array.bernoulli( 3, 0.5 )\n    <Float64Array>\n    > out = random.array.bernoulli( 3, 0.5 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.bernoulli.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.bernoulli( 3, 0.5 )\n    <Float64Array>\n\n\nrandom.array.bernoulli.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.bernoulli.stateLength;\n\n\nrandom.array.bernoulli.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.bernoulli.byteLength;\n\n    See Also\n    --------\n    base.random.bernoulli, random.strided.bernoulli\n","random.array.bernoulli.assign":"\nrandom.array.bernoulli.assign( p, out )\n    Fills an array with pseudorandom numbers drawn from a Bernoulli\n    distribution.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.bernoulli.assign( 0.5, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.bernoulli.factory":"\nrandom.array.bernoulli.factory( [p, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Bernoulli distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.bernoulli.factory();\n    > var out = fcn( 3, 0.5 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.bernoulli.factory( 0.5 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.bernoulli.PRNG":"\nrandom.array.bernoulli.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.bernoulli.PRNG;","random.array.bernoulli.seed":"\nrandom.array.bernoulli.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.bernoulli.seed;","random.array.bernoulli.seedLength":"\nrandom.array.bernoulli.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.bernoulli.seedLength;","random.array.bernoulli.state":"\nrandom.array.bernoulli.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.bernoulli( 3, 0.5 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.bernoulli.state\n    <Uint32Array>\n\n    > out = random.array.bernoulli( 3, 0.5 )\n    <Float64Array>\n    > out = random.array.bernoulli( 3, 0.5 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.bernoulli.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.bernoulli( 3, 0.5 )\n    <Float64Array>","random.array.bernoulli.stateLength":"\nrandom.array.bernoulli.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.bernoulli.stateLength;","random.array.bernoulli.byteLength":"\nrandom.array.bernoulli.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.bernoulli.byteLength;\n\n    See Also\n    --------\n    base.random.bernoulli, random.strided.bernoulli","random.array.beta":"\nrandom.array.beta( len, alpha, beta[, options] )\n    Returns an array containing pseudorandom numbers drawn from a beta\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    alpha: number\n        First shape parameter.\n\n    beta: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.beta( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.beta.assign( alpha, beta, out )\n    Fills an array with pseudorandom numbers drawn from a beta distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        First shape parameter.\n\n    beta: number\n        Second shape parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.beta.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.beta.factory( [alpha, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a beta distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        First shape parameter.\n\n    beta: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.beta.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.beta.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.beta.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.beta.PRNG;\n\n\nrandom.array.beta.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.beta.seed;\n\n\nrandom.array.beta.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.beta.seedLength;\n\n\nrandom.array.beta.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.beta( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.beta.state\n    <Uint32Array>\n\n    > out = random.array.beta( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.beta( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.beta.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.beta( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.beta.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.beta.stateLength;\n\n\nrandom.array.beta.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.beta.byteLength;\n\n    See Also\n    --------\n    base.random.beta, random.strided.beta\n","random.array.beta.assign":"\nrandom.array.beta.assign( alpha, beta, out )\n    Fills an array with pseudorandom numbers drawn from a beta distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        First shape parameter.\n\n    beta: number\n        Second shape parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.beta.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.beta.factory":"\nrandom.array.beta.factory( [alpha, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a beta distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        First shape parameter.\n\n    beta: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.beta.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.beta.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.beta.PRNG":"\nrandom.array.beta.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.beta.PRNG;","random.array.beta.seed":"\nrandom.array.beta.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.beta.seed;","random.array.beta.seedLength":"\nrandom.array.beta.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.beta.seedLength;","random.array.beta.state":"\nrandom.array.beta.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.beta( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.beta.state\n    <Uint32Array>\n\n    > out = random.array.beta( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.beta( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.beta.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.beta( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.beta.stateLength":"\nrandom.array.beta.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.beta.stateLength;","random.array.beta.byteLength":"\nrandom.array.beta.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.beta.byteLength;\n\n    See Also\n    --------\n    base.random.beta, random.strided.beta","random.array.betaprime":"\nrandom.array.betaprime( len, alpha, beta[, options] )\n    Returns an array containing pseudorandom numbers drawn from a beta prime\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    alpha: number\n        First shape parameter.\n\n    beta: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.betaprime( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.betaprime.assign( alpha, beta, out )\n    Fills an array with pseudorandom numbers drawn from a beta prime\n    distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        First shape parameter.\n\n    beta: number\n        Second shape parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.betaprime.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.betaprime.factory( [alpha, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a beta prime distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        First shape parameter.\n\n    beta: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.betaprime.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.betaprime.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.betaprime.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.betaprime.PRNG;\n\n\nrandom.array.betaprime.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.betaprime.seed;\n\n\nrandom.array.betaprime.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.betaprime.seedLength;\n\n\nrandom.array.betaprime.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.betaprime( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.betaprime.state\n    <Uint32Array>\n\n    > out = random.array.betaprime( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.betaprime( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.betaprime.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.betaprime( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.betaprime.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.betaprime.stateLength;\n\n\nrandom.array.betaprime.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.betaprime.byteLength;\n\n    See Also\n    --------\n    base.random.betaprime, random.strided.betaprime\n","random.array.betaprime.assign":"\nrandom.array.betaprime.assign( alpha, beta, out )\n    Fills an array with pseudorandom numbers drawn from a beta prime\n    distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        First shape parameter.\n\n    beta: number\n        Second shape parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.betaprime.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.betaprime.factory":"\nrandom.array.betaprime.factory( [alpha, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a beta prime distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        First shape parameter.\n\n    beta: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.betaprime.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.betaprime.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.betaprime.PRNG":"\nrandom.array.betaprime.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.betaprime.PRNG;","random.array.betaprime.seed":"\nrandom.array.betaprime.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.betaprime.seed;","random.array.betaprime.seedLength":"\nrandom.array.betaprime.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.betaprime.seedLength;","random.array.betaprime.state":"\nrandom.array.betaprime.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.betaprime( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.betaprime.state\n    <Uint32Array>\n\n    > out = random.array.betaprime( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.betaprime( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.betaprime.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.betaprime( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.betaprime.stateLength":"\nrandom.array.betaprime.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.betaprime.stateLength;","random.array.betaprime.byteLength":"\nrandom.array.betaprime.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.betaprime.byteLength;\n\n    See Also\n    --------\n    base.random.betaprime, random.strided.betaprime","random.array.binomial":"\nrandom.array.binomial( len, n, p[, options] )\n    Returns an array containing pseudorandom numbers drawn from a binomial\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    n: number\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.binomial( 3, 17, 0.5 )\n    <Float64Array>\n\n\nrandom.array.binomial.assign( n, p, out )\n    Fills an array with pseudorandom numbers drawn from a binomial distribution.\n\n    Parameters\n    ----------\n    n: number\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.binomial.assign( 17, 0.5, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.binomial.factory( [n, p, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a binomial distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    n: number (optional)\n        Number of trials.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.binomial.factory();\n    > var out = fcn( 3, 17, 0.5 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.binomial.factory( 17, 0.5 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.binomial.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.binomial.PRNG;\n\n\nrandom.array.binomial.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.binomial.seed;\n\n\nrandom.array.binomial.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.binomial.seedLength;\n\n\nrandom.array.binomial.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.binomial( 3, 17, 0.5 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.binomial.state\n    <Uint32Array>\n\n    > out = random.array.binomial( 3, 17, 0.5 )\n    <Float64Array>\n    > out = random.array.binomial( 3, 17, 0.5 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.binomial.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.binomial( 3, 17, 0.5 )\n    <Float64Array>\n\n\nrandom.array.binomial.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.binomial.stateLength;\n\n\nrandom.array.binomial.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.binomial.byteLength;\n\n    See Also\n    --------\n    random.array.negativeBinomial, base.random.binomial\n","random.array.binomial.assign":"\nrandom.array.binomial.assign( n, p, out )\n    Fills an array with pseudorandom numbers drawn from a binomial distribution.\n\n    Parameters\n    ----------\n    n: number\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.binomial.assign( 17, 0.5, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.binomial.factory":"\nrandom.array.binomial.factory( [n, p, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a binomial distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    n: number (optional)\n        Number of trials.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.binomial.factory();\n    > var out = fcn( 3, 17, 0.5 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.binomial.factory( 17, 0.5 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.binomial.PRNG":"\nrandom.array.binomial.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.binomial.PRNG;","random.array.binomial.seed":"\nrandom.array.binomial.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.binomial.seed;","random.array.binomial.seedLength":"\nrandom.array.binomial.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.binomial.seedLength;","random.array.binomial.state":"\nrandom.array.binomial.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.binomial( 3, 17, 0.5 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.binomial.state\n    <Uint32Array>\n\n    > out = random.array.binomial( 3, 17, 0.5 )\n    <Float64Array>\n    > out = random.array.binomial( 3, 17, 0.5 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.binomial.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.binomial( 3, 17, 0.5 )\n    <Float64Array>","random.array.binomial.stateLength":"\nrandom.array.binomial.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.binomial.stateLength;","random.array.binomial.byteLength":"\nrandom.array.binomial.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.binomial.byteLength;\n\n    See Also\n    --------\n    random.array.negativeBinomial, base.random.binomial","random.array.cauchy":"\nrandom.array.cauchy( len, x0, gamma[, options] )\n    Returns an array containing pseudorandom numbers drawn from a Cauchy\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    x0: number\n        Location parameter.\n\n    gamma: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.cauchy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.cauchy.assign( x0, gamma, out )\n    Fills an array with pseudorandom numbers drawn from a Cauchy distribution.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    gamma: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.cauchy.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.cauchy.factory( [x0, gamma, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Cauchy distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    x0: number (optional)\n        Location parameter.\n\n    gamma: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.cauchy.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.cauchy.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.cauchy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.cauchy.PRNG;\n\n\nrandom.array.cauchy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.cauchy.seed;\n\n\nrandom.array.cauchy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.cauchy.seedLength;\n\n\nrandom.array.cauchy.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.cauchy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.cauchy.state\n    <Uint32Array>\n\n    > out = random.array.cauchy( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.cauchy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.cauchy.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.cauchy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.cauchy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.cauchy.stateLength;\n\n\nrandom.array.cauchy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.cauchy.byteLength;\n\n    See Also\n    --------\n    base.random.cauchy\n","random.array.cauchy.assign":"\nrandom.array.cauchy.assign( x0, gamma, out )\n    Fills an array with pseudorandom numbers drawn from a Cauchy distribution.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    gamma: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.cauchy.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.cauchy.factory":"\nrandom.array.cauchy.factory( [x0, gamma, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Cauchy distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    x0: number (optional)\n        Location parameter.\n\n    gamma: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.cauchy.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.cauchy.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.cauchy.PRNG":"\nrandom.array.cauchy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.cauchy.PRNG;","random.array.cauchy.seed":"\nrandom.array.cauchy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.cauchy.seed;","random.array.cauchy.seedLength":"\nrandom.array.cauchy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.cauchy.seedLength;","random.array.cauchy.state":"\nrandom.array.cauchy.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.cauchy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.cauchy.state\n    <Uint32Array>\n\n    > out = random.array.cauchy( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.cauchy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.cauchy.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.cauchy( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.cauchy.stateLength":"\nrandom.array.cauchy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.cauchy.stateLength;","random.array.cauchy.byteLength":"\nrandom.array.cauchy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.cauchy.byteLength;\n\n    See Also\n    --------\n    base.random.cauchy","random.array.chi":"\nrandom.array.chi( len, k[, options] )\n    Returns an array containing pseudorandom numbers drawn from a chi\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    k: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.chi( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.chi.assign( k, out )\n    Fills an array with pseudorandom numbers drawn from a chi distribution.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.chi.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.chi.factory( [k, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a chi distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.chi.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.chi.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.chi.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.chi.PRNG;\n\n\nrandom.array.chi.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.chi.seed;\n\n\nrandom.array.chi.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.chi.seedLength;\n\n\nrandom.array.chi.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.chi( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.chi.state\n    <Uint32Array>\n\n    > out = random.array.chi( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.chi( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.chi.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.chi( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.chi.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.chi.stateLength;\n\n\nrandom.array.chi.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.chi.byteLength;\n\n    See Also\n    --------\n    base.random.chi, random.strided.chi\n","random.array.chi.assign":"\nrandom.array.chi.assign( k, out )\n    Fills an array with pseudorandom numbers drawn from a chi distribution.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.chi.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.chi.factory":"\nrandom.array.chi.factory( [k, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a chi distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.chi.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.chi.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.chi.PRNG":"\nrandom.array.chi.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.chi.PRNG;","random.array.chi.seed":"\nrandom.array.chi.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.chi.seed;","random.array.chi.seedLength":"\nrandom.array.chi.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.chi.seedLength;","random.array.chi.state":"\nrandom.array.chi.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.chi( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.chi.state\n    <Uint32Array>\n\n    > out = random.array.chi( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.chi( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.chi.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.chi( 3, 2.0 )\n    <Float64Array>","random.array.chi.stateLength":"\nrandom.array.chi.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.chi.stateLength;","random.array.chi.byteLength":"\nrandom.array.chi.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.chi.byteLength;\n\n    See Also\n    --------\n    base.random.chi, random.strided.chi","random.array.chisquare":"\nrandom.array.chisquare( len, k[, options] )\n    Returns an array containing pseudorandom numbers drawn from a chi-square\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    k: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.chisquare( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.chisquare.assign( k, out )\n    Fills an array with pseudorandom numbers drawn from a chi-square\n    distribution.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.chisquare.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.chisquare.factory( [k, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a chi-square distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.chisquare.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.chisquare.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.chisquare.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.chisquare.PRNG;\n\n\nrandom.array.chisquare.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.chisquare.seed;\n\n\nrandom.array.chisquare.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.chisquare.seedLength;\n\n\nrandom.array.chisquare.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.chisquare( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.chisquare.state\n    <Uint32Array>\n\n    > out = random.array.chisquare( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.chisquare( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.chisquare.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.chisquare( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.chisquare.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.chisquare.stateLength;\n\n\nrandom.array.chisquare.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.chisquare.byteLength;\n\n    See Also\n    --------\n    base.random.chisquare, random.strided.chisquare\n","random.array.chisquare.assign":"\nrandom.array.chisquare.assign( k, out )\n    Fills an array with pseudorandom numbers drawn from a chi-square\n    distribution.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.chisquare.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.chisquare.factory":"\nrandom.array.chisquare.factory( [k, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a chi-square distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.chisquare.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.chisquare.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.chisquare.PRNG":"\nrandom.array.chisquare.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.chisquare.PRNG;","random.array.chisquare.seed":"\nrandom.array.chisquare.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.chisquare.seed;","random.array.chisquare.seedLength":"\nrandom.array.chisquare.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.chisquare.seedLength;","random.array.chisquare.state":"\nrandom.array.chisquare.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.chisquare( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.chisquare.state\n    <Uint32Array>\n\n    > out = random.array.chisquare( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.chisquare( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.chisquare.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.chisquare( 3, 2.0 )\n    <Float64Array>","random.array.chisquare.stateLength":"\nrandom.array.chisquare.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.chisquare.stateLength;","random.array.chisquare.byteLength":"\nrandom.array.chisquare.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.chisquare.byteLength;\n\n    See Also\n    --------\n    base.random.chisquare, random.strided.chisquare","random.array.cosine":"\nrandom.array.cosine( len, mu, s[, options] )\n    Returns an array containing pseudorandom numbers drawn from a raised cosine\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    mu: number\n        Mean.\n\n    s: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.cosine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.cosine.assign( mu, s, out )\n    Fills an array with pseudorandom numbers drawn from a raised cosine\n    distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Mean.\n\n    s: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.cosine.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.cosine.factory( [mu, s, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a raised cosine distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Mean.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.cosine.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.cosine.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.cosine.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.cosine.PRNG;\n\n\nrandom.array.cosine.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.cosine.seed;\n\n\nrandom.array.cosine.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.cosine.seedLength;\n\n\nrandom.array.cosine.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.cosine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.cosine.state\n    <Uint32Array>\n\n    > out = random.array.cosine( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.cosine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.cosine.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.cosine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.cosine.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.cosine.stateLength;\n\n\nrandom.array.cosine.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.cosine.byteLength;\n\n    See Also\n    --------\n    base.random.cosine, random.strided.cosine\n","random.array.cosine.assign":"\nrandom.array.cosine.assign( mu, s, out )\n    Fills an array with pseudorandom numbers drawn from a raised cosine\n    distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Mean.\n\n    s: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.cosine.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.cosine.factory":"\nrandom.array.cosine.factory( [mu, s, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a raised cosine distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Mean.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.cosine.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.cosine.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.cosine.PRNG":"\nrandom.array.cosine.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.cosine.PRNG;","random.array.cosine.seed":"\nrandom.array.cosine.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.cosine.seed;","random.array.cosine.seedLength":"\nrandom.array.cosine.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.cosine.seedLength;","random.array.cosine.state":"\nrandom.array.cosine.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.cosine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.cosine.state\n    <Uint32Array>\n\n    > out = random.array.cosine( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.cosine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.cosine.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.cosine( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.cosine.stateLength":"\nrandom.array.cosine.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.cosine.stateLength;","random.array.cosine.byteLength":"\nrandom.array.cosine.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.cosine.byteLength;\n\n    See Also\n    --------\n    base.random.cosine, random.strided.cosine","random.array.discreteUniform":"\nrandom.array.discreteUniform( len, a, b[, options] )\n    Returns an array containing pseudorandom numbers drawn from a discrete\n    uniform distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.discreteUniform( 3, -10, 10 )\n    <Float64Array>\n\n\nrandom.array.discreteUniform.assign( a, b, out )\n    Fills an array with pseudorandom numbers drawn from a discrete uniform\n    distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.discreteUniform.assign( -10, 10, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.discreteUniform.factory( [a, b, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a discrete uniform distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom integers. If provided, the `state` and `seed`\n        options are ignored. In order to seed the returned pseudorandom number\n        generator, one must seed the provided `prng` (assuming the provided\n        `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n        properties specifying the minimum and maximum possible pseudorandom\n        integers.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.discreteUniform.factory();\n    > var out = fcn( 3, -10, 10 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.discreteUniform.factory( -10, 10 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.discreteUniform.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.discreteUniform.PRNG;\n\n\nrandom.array.discreteUniform.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.discreteUniform.seed;\n\n\nrandom.array.discreteUniform.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.discreteUniform.seedLength;\n\n\nrandom.array.discreteUniform.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.discreteUniform( 3, -10, 10 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.discreteUniform.state\n    <Uint32Array>\n\n    > out = random.array.discreteUniform( 3, -10, 10 )\n    <Float64Array>\n    > out = random.array.discreteUniform( 3, -10, 10 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.discreteUniform.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.discreteUniform( 3, -10, 10 )\n    <Float64Array>\n\n\nrandom.array.discreteUniform.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.discreteUniform.stateLength;\n\n\nrandom.array.discreteUniform.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.discreteUniform.byteLength;\n\n    See Also\n    --------\n    random.array.uniform, base.random.discreteUniform, random.strided.discreteUniform\n","random.array.discreteUniform.assign":"\nrandom.array.discreteUniform.assign( a, b, out )\n    Fills an array with pseudorandom numbers drawn from a discrete uniform\n    distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.discreteUniform.assign( -10, 10, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.discreteUniform.factory":"\nrandom.array.discreteUniform.factory( [a, b, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a discrete uniform distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom integers. If provided, the `state` and `seed`\n        options are ignored. In order to seed the returned pseudorandom number\n        generator, one must seed the provided `prng` (assuming the provided\n        `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n        properties specifying the minimum and maximum possible pseudorandom\n        integers.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.discreteUniform.factory();\n    > var out = fcn( 3, -10, 10 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.discreteUniform.factory( -10, 10 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.discreteUniform.PRNG":"\nrandom.array.discreteUniform.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.discreteUniform.PRNG;","random.array.discreteUniform.seed":"\nrandom.array.discreteUniform.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.discreteUniform.seed;","random.array.discreteUniform.seedLength":"\nrandom.array.discreteUniform.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.discreteUniform.seedLength;","random.array.discreteUniform.state":"\nrandom.array.discreteUniform.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.discreteUniform( 3, -10, 10 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.discreteUniform.state\n    <Uint32Array>\n\n    > out = random.array.discreteUniform( 3, -10, 10 )\n    <Float64Array>\n    > out = random.array.discreteUniform( 3, -10, 10 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.discreteUniform.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.discreteUniform( 3, -10, 10 )\n    <Float64Array>","random.array.discreteUniform.stateLength":"\nrandom.array.discreteUniform.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.discreteUniform.stateLength;","random.array.discreteUniform.byteLength":"\nrandom.array.discreteUniform.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.discreteUniform.byteLength;\n\n    See Also\n    --------\n    random.array.uniform, base.random.discreteUniform, random.strided.discreteUniform","random.array.erlang":"\nrandom.array.erlang( len, k, lambda[, options] )\n    Returns an array containing pseudorandom numbers drawn from an Erlang\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    k: number\n        Shape parameter.\n\n    lambda: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.erlang( 3, 2, 5.0 )\n    <Float64Array>\n\n\nrandom.array.erlang.assign( k, lambda, out )\n    Fills an array with pseudorandom numbers drawn from an Erlang distribution.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    lambda: number\n        Rate parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.erlang.assign( 2, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.erlang.factory( [k, lambda, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an Erlang distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Shape parameter.\n\n    lambda: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.erlang.factory();\n    > var out = fcn( 3, 2, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.erlang.factory( 2, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.erlang.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.erlang.PRNG;\n\n\nrandom.array.erlang.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.erlang.seed;\n\n\nrandom.array.erlang.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.erlang.seedLength;\n\n\nrandom.array.erlang.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.erlang( 3, 2, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.erlang.state\n    <Uint32Array>\n\n    > out = random.array.erlang( 3, 2, 5.0 )\n    <Float64Array>\n    > out = random.array.erlang( 3, 2, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.erlang.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.erlang( 3, 2, 5.0 )\n    <Float64Array>\n\n\nrandom.array.erlang.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.erlang.stateLength;\n\n\nrandom.array.erlang.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.erlang.byteLength;\n\n    See Also\n    --------\n    base.random.erlang\n","random.array.erlang.assign":"\nrandom.array.erlang.assign( k, lambda, out )\n    Fills an array with pseudorandom numbers drawn from an Erlang distribution.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    lambda: number\n        Rate parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.erlang.assign( 2, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.erlang.factory":"\nrandom.array.erlang.factory( [k, lambda, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an Erlang distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Shape parameter.\n\n    lambda: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.erlang.factory();\n    > var out = fcn( 3, 2, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.erlang.factory( 2, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.erlang.PRNG":"\nrandom.array.erlang.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.erlang.PRNG;","random.array.erlang.seed":"\nrandom.array.erlang.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.erlang.seed;","random.array.erlang.seedLength":"\nrandom.array.erlang.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.erlang.seedLength;","random.array.erlang.state":"\nrandom.array.erlang.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.erlang( 3, 2, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.erlang.state\n    <Uint32Array>\n\n    > out = random.array.erlang( 3, 2, 5.0 )\n    <Float64Array>\n    > out = random.array.erlang( 3, 2, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.erlang.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.erlang( 3, 2, 5.0 )\n    <Float64Array>","random.array.erlang.stateLength":"\nrandom.array.erlang.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.erlang.stateLength;","random.array.erlang.byteLength":"\nrandom.array.erlang.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.erlang.byteLength;\n\n    See Also\n    --------\n    base.random.erlang","random.array.exponential":"\nrandom.array.exponential( len, lambda[, options] )\n    Returns an array containing pseudorandom numbers drawn from an exponential\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    lambda: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.exponential( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.exponential.assign( lambda, out )\n    Fills an array with pseudorandom numbers drawn from an exponential\n    distribution.\n\n    Parameters\n    ----------\n    lambda: number\n        Rate parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.exponential.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.exponential.factory( [lambda, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an exponential distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    lambda: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.exponential.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.exponential.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.exponential.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.exponential.PRNG;\n\n\nrandom.array.exponential.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.exponential.seed;\n\n\nrandom.array.exponential.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.exponential.seedLength;\n\n\nrandom.array.exponential.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.exponential( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.exponential.state\n    <Uint32Array>\n\n    > out = random.array.exponential( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.exponential( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.exponential.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.exponential( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.exponential.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.exponential.stateLength;\n\n\nrandom.array.exponential.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.exponential.byteLength;\n\n    See Also\n    --------\n    base.random.exponential, random.strided.exponential\n","random.array.exponential.assign":"\nrandom.array.exponential.assign( lambda, out )\n    Fills an array with pseudorandom numbers drawn from an exponential\n    distribution.\n\n    Parameters\n    ----------\n    lambda: number\n        Rate parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.exponential.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.exponential.factory":"\nrandom.array.exponential.factory( [lambda, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an exponential distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    lambda: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.exponential.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.exponential.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.exponential.PRNG":"\nrandom.array.exponential.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.exponential.PRNG;","random.array.exponential.seed":"\nrandom.array.exponential.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.exponential.seed;","random.array.exponential.seedLength":"\nrandom.array.exponential.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.exponential.seedLength;","random.array.exponential.state":"\nrandom.array.exponential.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.exponential( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.exponential.state\n    <Uint32Array>\n\n    > out = random.array.exponential( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.exponential( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.exponential.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.exponential( 3, 2.0 )\n    <Float64Array>","random.array.exponential.stateLength":"\nrandom.array.exponential.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.exponential.stateLength;","random.array.exponential.byteLength":"\nrandom.array.exponential.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.exponential.byteLength;\n\n    See Also\n    --------\n    base.random.exponential, random.strided.exponential","random.array.f":"\nrandom.array.f( len, d1, d2[, options] )\n    Returns an array containing pseudorandom numbers drawn from an F\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    d1: number\n        Degrees of freedom.\n\n    d2: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.f( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.f.assign( d1, d2, out )\n    Fills an array with pseudorandom numbers drawn from an F distribution.\n\n    Parameters\n    ----------\n    d1: number\n        Degrees of freedom.\n\n    d2: number\n        Degrees of freedom.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.f.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.f.factory( [d1, d2, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an F distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    d1: number (optional)\n        Degrees of freedom.\n\n    d2: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.f.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.f.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.f.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.f.PRNG;\n\n\nrandom.array.f.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.f.seed;\n\n\nrandom.array.f.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.f.seedLength;\n\n\nrandom.array.f.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.f( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.f.state\n    <Uint32Array>\n\n    > out = random.array.f( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.f( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.f.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.f( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.f.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.f.stateLength;\n\n\nrandom.array.f.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.f.byteLength;\n\n    See Also\n    --------\n    base.random.f\n","random.array.f.assign":"\nrandom.array.f.assign( d1, d2, out )\n    Fills an array with pseudorandom numbers drawn from an F distribution.\n\n    Parameters\n    ----------\n    d1: number\n        Degrees of freedom.\n\n    d2: number\n        Degrees of freedom.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.f.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.f.factory":"\nrandom.array.f.factory( [d1, d2, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an F distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    d1: number (optional)\n        Degrees of freedom.\n\n    d2: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.f.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.f.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.f.PRNG":"\nrandom.array.f.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.f.PRNG;","random.array.f.seed":"\nrandom.array.f.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.f.seed;","random.array.f.seedLength":"\nrandom.array.f.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.f.seedLength;","random.array.f.state":"\nrandom.array.f.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.f( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.f.state\n    <Uint32Array>\n\n    > out = random.array.f( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.f( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.f.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.f( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.f.stateLength":"\nrandom.array.f.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.f.stateLength;","random.array.f.byteLength":"\nrandom.array.f.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.f.byteLength;\n\n    See Also\n    --------\n    base.random.f","random.array.frechet":"\nrandom.array.frechet( len, alpha, s, m[, options] )\n    Returns an array containing pseudorandom numbers drawn from a Fréchet\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    alpha: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n\nrandom.array.frechet.assign( alpha, s, m, out )\n    Fills an array with pseudorandom numbers drawn from a Fréchet distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.frechet.assign( 2.0, 5.0, 3.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.frechet.factory( [alpha, s, m, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Fréchet distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        Shape parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    m: number (optional)\n        Location parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.frechet.factory();\n    > var out = fcn( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.frechet.factory( 2.0, 5.0, 3.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.frechet.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.frechet.PRNG;\n\n\nrandom.array.frechet.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.frechet.seed;\n\n\nrandom.array.frechet.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.frechet.seedLength;\n\n\nrandom.array.frechet.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.frechet.state\n    <Uint32Array>\n\n    > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n    > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.frechet.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n\nrandom.array.frechet.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.frechet.stateLength;\n\n\nrandom.array.frechet.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.frechet.byteLength;\n\n    See Also\n    --------\n    base.random.frechet\n","random.array.frechet.assign":"\nrandom.array.frechet.assign( alpha, s, m, out )\n    Fills an array with pseudorandom numbers drawn from a Fréchet distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.frechet.assign( 2.0, 5.0, 3.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.frechet.factory":"\nrandom.array.frechet.factory( [alpha, s, m, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Fréchet distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        Shape parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    m: number (optional)\n        Location parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.frechet.factory();\n    > var out = fcn( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.frechet.factory( 2.0, 5.0, 3.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.frechet.PRNG":"\nrandom.array.frechet.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.frechet.PRNG;","random.array.frechet.seed":"\nrandom.array.frechet.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.frechet.seed;","random.array.frechet.seedLength":"\nrandom.array.frechet.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.frechet.seedLength;","random.array.frechet.state":"\nrandom.array.frechet.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.frechet.state\n    <Uint32Array>\n\n    > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n    > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.frechet.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>","random.array.frechet.stateLength":"\nrandom.array.frechet.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.frechet.stateLength;","random.array.frechet.byteLength":"\nrandom.array.frechet.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.frechet.byteLength;\n\n    See Also\n    --------\n    base.random.frechet","random.array.gamma":"\nrandom.array.gamma( len, alpha, beta[, options] )\n    Returns an array containing pseudorandom numbers drawn from a gamma\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    alpha: number\n        Shape parameter.\n\n    beta: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.gamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.gamma.assign( alpha, beta, out )\n    Fills an array with pseudorandom numbers drawn from a gamma distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        Shape parameter.\n\n    beta: number\n        Rate parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.gamma.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.gamma.factory( [alpha, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a gamma distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        Shape parameter.\n\n    beta: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.gamma.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.gamma.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.gamma.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.gamma.PRNG;\n\n\nrandom.array.gamma.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.gamma.seed;\n\n\nrandom.array.gamma.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.gamma.seedLength;\n\n\nrandom.array.gamma.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.gamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.gamma.state\n    <Uint32Array>\n\n    > out = random.array.gamma( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.gamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.gamma.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.gamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.gamma.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.gamma.stateLength;\n\n\nrandom.array.gamma.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.gamma.byteLength;\n\n    See Also\n    --------\n    base.random.gamma, random.strided.gamma\n","random.array.gamma.assign":"\nrandom.array.gamma.assign( alpha, beta, out )\n    Fills an array with pseudorandom numbers drawn from a gamma distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        Shape parameter.\n\n    beta: number\n        Rate parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.gamma.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.gamma.factory":"\nrandom.array.gamma.factory( [alpha, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a gamma distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        Shape parameter.\n\n    beta: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.gamma.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.gamma.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.gamma.PRNG":"\nrandom.array.gamma.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.gamma.PRNG;","random.array.gamma.seed":"\nrandom.array.gamma.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.gamma.seed;","random.array.gamma.seedLength":"\nrandom.array.gamma.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.gamma.seedLength;","random.array.gamma.state":"\nrandom.array.gamma.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.gamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.gamma.state\n    <Uint32Array>\n\n    > out = random.array.gamma( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.gamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.gamma.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.gamma( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.gamma.stateLength":"\nrandom.array.gamma.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.gamma.stateLength;","random.array.gamma.byteLength":"\nrandom.array.gamma.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.gamma.byteLength;\n\n    See Also\n    --------\n    base.random.gamma, random.strided.gamma","random.array.geometric":"\nrandom.array.geometric( len, p[, options] )\n    Returns an array containing pseudorandom numbers drawn from a geometric\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.geometric( 3, 0.01 )\n    <Float64Array>\n\n\nrandom.array.geometric.assign( p, out )\n    Fills an array with pseudorandom numbers drawn from a geometric\n    distribution.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.geometric.assign( 0.01, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.geometric.factory( [p, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a geometric distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.geometric.factory();\n    > var out = fcn( 3, 0.01 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.geometric.factory( 0.01 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.geometric.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.geometric.PRNG;\n\n\nrandom.array.geometric.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.geometric.seed;\n\n\nrandom.array.geometric.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.geometric.seedLength;\n\n\nrandom.array.geometric.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.geometric( 3, 0.01 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.geometric.state\n    <Uint32Array>\n\n    > out = random.array.geometric( 3, 0.01 )\n    <Float64Array>\n    > out = random.array.geometric( 3, 0.01 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.geometric.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.geometric( 3, 0.01 )\n    <Float64Array>\n\n\nrandom.array.geometric.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.geometric.stateLength;\n\n\nrandom.array.geometric.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.geometric.byteLength;\n\n    See Also\n    --------\n    base.random.geometric, random.strided.geometric\n","random.array.geometric.assign":"\nrandom.array.geometric.assign( p, out )\n    Fills an array with pseudorandom numbers drawn from a geometric\n    distribution.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.geometric.assign( 0.01, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.geometric.factory":"\nrandom.array.geometric.factory( [p, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a geometric distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.geometric.factory();\n    > var out = fcn( 3, 0.01 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.geometric.factory( 0.01 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.geometric.PRNG":"\nrandom.array.geometric.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.geometric.PRNG;","random.array.geometric.seed":"\nrandom.array.geometric.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.geometric.seed;","random.array.geometric.seedLength":"\nrandom.array.geometric.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.geometric.seedLength;","random.array.geometric.state":"\nrandom.array.geometric.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.geometric( 3, 0.01 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.geometric.state\n    <Uint32Array>\n\n    > out = random.array.geometric( 3, 0.01 )\n    <Float64Array>\n    > out = random.array.geometric( 3, 0.01 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.geometric.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.geometric( 3, 0.01 )\n    <Float64Array>","random.array.geometric.stateLength":"\nrandom.array.geometric.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.geometric.stateLength;","random.array.geometric.byteLength":"\nrandom.array.geometric.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.geometric.byteLength;\n\n    See Also\n    --------\n    base.random.geometric, random.strided.geometric","random.array.gumbel":"\nrandom.array.gumbel( len, mu, beta[, options] )\n    Returns an array containing pseudorandom numbers drawn from a Gumbel\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    mu: number\n        Mean.\n\n    beta: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.gumbel( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.gumbel.assign( mu, beta, out )\n    Fills an array with pseudorandom numbers drawn from a Gumbel distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Mean.\n\n    beta: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.gumbel.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.gumbel.factory( [mu, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Gumbel distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Mean.\n\n    beta: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.gumbel.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.gumbel.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.gumbel.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.gumbel.PRNG;\n\n\nrandom.array.gumbel.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.gumbel.seed;\n\n\nrandom.array.gumbel.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.gumbel.seedLength;\n\n\nrandom.array.gumbel.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.gumbel( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.gumbel.state\n    <Uint32Array>\n\n    > out = random.array.gumbel( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.gumbel( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.gumbel.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.gumbel( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.gumbel.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.gumbel.stateLength;\n\n\nrandom.array.gumbel.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.gumbel.byteLength;\n\n    See Also\n    --------\n    base.random.gumbel\n","random.array.gumbel.assign":"\nrandom.array.gumbel.assign( mu, beta, out )\n    Fills an array with pseudorandom numbers drawn from a Gumbel distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Mean.\n\n    beta: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.gumbel.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.gumbel.factory":"\nrandom.array.gumbel.factory( [mu, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Gumbel distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Mean.\n\n    beta: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.gumbel.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.gumbel.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.gumbel.PRNG":"\nrandom.array.gumbel.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.gumbel.PRNG;","random.array.gumbel.seed":"\nrandom.array.gumbel.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.gumbel.seed;","random.array.gumbel.seedLength":"\nrandom.array.gumbel.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.gumbel.seedLength;","random.array.gumbel.state":"\nrandom.array.gumbel.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.gumbel( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.gumbel.state\n    <Uint32Array>\n\n    > out = random.array.gumbel( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.gumbel( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.gumbel.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.gumbel( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.gumbel.stateLength":"\nrandom.array.gumbel.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.gumbel.stateLength;","random.array.gumbel.byteLength":"\nrandom.array.gumbel.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.gumbel.byteLength;\n\n    See Also\n    --------\n    base.random.gumbel","random.array.hypergeometric":"\nrandom.array.hypergeometric( len, N, K, n[, options] )\n    Returns an array containing pseudorandom numbers drawn from a hypergeometric\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    N: number\n        Population size.\n\n    K: number\n        Subpopulation size.\n\n    n: number\n        Number of draws.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.hypergeometric( 3, 20, 10, 7 )\n    <Float64Array>\n\n\nrandom.array.hypergeometric.assign( N, K, n, out )\n    Fills an array with pseudorandom numbers drawn from a hypergeometric\n    distribution.\n\n    Parameters\n    ----------\n    N: number\n        Population size.\n\n    K: number\n        Subpopulation size.\n\n    n: number\n        Number of draws.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.hypergeometric.assign( 20, 10, 7, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.hypergeometric.factory( [N, K, n, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a hypergeometric distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    N: number (optional)\n        Population size.\n\n    K: number (optional)\n        Subpopulation size.\n\n    n: number (optional)\n        Number of draws.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.hypergeometric.factory();\n    > var out = fcn( 3, 20, 10, 7 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.hypergeometric.factory( 20, 10, 7 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.hypergeometric.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.hypergeometric.PRNG;\n\n\nrandom.array.hypergeometric.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.hypergeometric.seed;\n\n\nrandom.array.hypergeometric.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.hypergeometric.seedLength;\n\n\nrandom.array.hypergeometric.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.hypergeometric( 3, 20, 10, 7 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.hypergeometric.state\n    <Uint32Array>\n\n    > out = random.array.hypergeometric( 3, 20, 10, 7 )\n    <Float64Array>\n    > out = random.array.hypergeometric( 3, 20, 10, 7 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.hypergeometric.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.hypergeometric( 3, 20, 10, 7 )\n    <Float64Array>\n\n\nrandom.array.hypergeometric.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.hypergeometric.stateLength;\n\n\nrandom.array.hypergeometric.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.hypergeometric.byteLength;\n\n    See Also\n    --------\n    base.random.hypergeometric\n","random.array.hypergeometric.assign":"\nrandom.array.hypergeometric.assign( N, K, n, out )\n    Fills an array with pseudorandom numbers drawn from a hypergeometric\n    distribution.\n\n    Parameters\n    ----------\n    N: number\n        Population size.\n\n    K: number\n        Subpopulation size.\n\n    n: number\n        Number of draws.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.hypergeometric.assign( 20, 10, 7, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.hypergeometric.factory":"\nrandom.array.hypergeometric.factory( [N, K, n, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a hypergeometric distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    N: number (optional)\n        Population size.\n\n    K: number (optional)\n        Subpopulation size.\n\n    n: number (optional)\n        Number of draws.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.hypergeometric.factory();\n    > var out = fcn( 3, 20, 10, 7 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.hypergeometric.factory( 20, 10, 7 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.hypergeometric.PRNG":"\nrandom.array.hypergeometric.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.hypergeometric.PRNG;","random.array.hypergeometric.seed":"\nrandom.array.hypergeometric.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.hypergeometric.seed;","random.array.hypergeometric.seedLength":"\nrandom.array.hypergeometric.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.hypergeometric.seedLength;","random.array.hypergeometric.state":"\nrandom.array.hypergeometric.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.hypergeometric( 3, 20, 10, 7 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.hypergeometric.state\n    <Uint32Array>\n\n    > out = random.array.hypergeometric( 3, 20, 10, 7 )\n    <Float64Array>\n    > out = random.array.hypergeometric( 3, 20, 10, 7 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.hypergeometric.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.hypergeometric( 3, 20, 10, 7 )\n    <Float64Array>","random.array.hypergeometric.stateLength":"\nrandom.array.hypergeometric.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.hypergeometric.stateLength;","random.array.hypergeometric.byteLength":"\nrandom.array.hypergeometric.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.hypergeometric.byteLength;\n\n    See Also\n    --------\n    base.random.hypergeometric","random.array.invgamma":"\nrandom.array.invgamma( len, alpha, beta[, options] )\n    Returns an array containing pseudorandom numbers drawn from an inverse gamma\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    alpha: number\n        Shape parameter.\n\n    beta: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.invgamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.invgamma.assign( alpha, beta, out )\n    Fills an array with pseudorandom numbers drawn from an inverse gamma\n    distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        Shape parameter.\n\n    beta: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.invgamma.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.invgamma.factory( [alpha, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an inverse gamma distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        Shape parameter.\n\n    beta: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.invgamma.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.invgamma.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.invgamma.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.invgamma.PRNG;\n\n\nrandom.array.invgamma.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.invgamma.seed;\n\n\nrandom.array.invgamma.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.invgamma.seedLength;\n\n\nrandom.array.invgamma.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.invgamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.invgamma.state\n    <Uint32Array>\n\n    > out = random.array.invgamma( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.invgamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.invgamma.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.invgamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.invgamma.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.invgamma.stateLength;\n\n\nrandom.array.invgamma.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.invgamma.byteLength;\n\n    See Also\n    --------\n    base.random.invgamma, random.strided.invgamma\n","random.array.invgamma.assign":"\nrandom.array.invgamma.assign( alpha, beta, out )\n    Fills an array with pseudorandom numbers drawn from an inverse gamma\n    distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        Shape parameter.\n\n    beta: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.invgamma.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.invgamma.factory":"\nrandom.array.invgamma.factory( [alpha, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an inverse gamma distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        Shape parameter.\n\n    beta: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.invgamma.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.invgamma.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.invgamma.PRNG":"\nrandom.array.invgamma.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.invgamma.PRNG;","random.array.invgamma.seed":"\nrandom.array.invgamma.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.invgamma.seed;","random.array.invgamma.seedLength":"\nrandom.array.invgamma.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.invgamma.seedLength;","random.array.invgamma.state":"\nrandom.array.invgamma.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.invgamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.invgamma.state\n    <Uint32Array>\n\n    > out = random.array.invgamma( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.invgamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.invgamma.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.invgamma( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.invgamma.stateLength":"\nrandom.array.invgamma.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.invgamma.stateLength;","random.array.invgamma.byteLength":"\nrandom.array.invgamma.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.invgamma.byteLength;\n\n    See Also\n    --------\n    base.random.invgamma, random.strided.invgamma","random.array.kumaraswamy":"\nrandom.array.kumaraswamy( len, a, b[, options] )\n    Returns an array containing pseudorandom numbers drawn from Kumaraswamy's\n    double bounded distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.kumaraswamy.assign( a, b, out )\n    Fills an array with pseudorandom numbers drawn from Kumaraswamy's double\n    bounded distribution.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.kumaraswamy.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.kumaraswamy.factory( [a, b, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from Kumaraswamy's double bounded distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    a: number (optional)\n        First shape parameter.\n\n    b: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.kumaraswamy.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.kumaraswamy.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.kumaraswamy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.kumaraswamy.PRNG;\n\n\nrandom.array.kumaraswamy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.kumaraswamy.seed;\n\n\nrandom.array.kumaraswamy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.kumaraswamy.seedLength;\n\n\nrandom.array.kumaraswamy.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.kumaraswamy.state\n    <Uint32Array>\n\n    > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.kumaraswamy.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.kumaraswamy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.kumaraswamy.stateLength;\n\n\nrandom.array.kumaraswamy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.kumaraswamy.byteLength;\n\n    See Also\n    --------\n    base.random.kumaraswamy\n","random.array.kumaraswamy.assign":"\nrandom.array.kumaraswamy.assign( a, b, out )\n    Fills an array with pseudorandom numbers drawn from Kumaraswamy's double\n    bounded distribution.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.kumaraswamy.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.kumaraswamy.factory":"\nrandom.array.kumaraswamy.factory( [a, b, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from Kumaraswamy's double bounded distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    a: number (optional)\n        First shape parameter.\n\n    b: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.kumaraswamy.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.kumaraswamy.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.kumaraswamy.PRNG":"\nrandom.array.kumaraswamy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.kumaraswamy.PRNG;","random.array.kumaraswamy.seed":"\nrandom.array.kumaraswamy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.kumaraswamy.seed;","random.array.kumaraswamy.seedLength":"\nrandom.array.kumaraswamy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.kumaraswamy.seedLength;","random.array.kumaraswamy.state":"\nrandom.array.kumaraswamy.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.kumaraswamy.state\n    <Uint32Array>\n\n    > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.kumaraswamy.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.kumaraswamy.stateLength":"\nrandom.array.kumaraswamy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.kumaraswamy.stateLength;","random.array.kumaraswamy.byteLength":"\nrandom.array.kumaraswamy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.kumaraswamy.byteLength;\n\n    See Also\n    --------\n    base.random.kumaraswamy","random.array.laplace":"\nrandom.array.laplace( len, mu, b[, options] )\n    Returns an array containing pseudorandom numbers drawn from a Laplace\n    (double exponential) distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    mu: number\n        Mean.\n\n    b: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.laplace( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.laplace.assign( mu, b, out )\n    Fills an array with pseudorandom numbers drawn from a Laplace (double\n    exponential) distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Mean.\n\n    b: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.laplace.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.laplace.factory( [mu, b, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Laplace (double exponential) distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Mean.\n\n    b: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.laplace.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.laplace.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.laplace.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.laplace.PRNG;\n\n\nrandom.array.laplace.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.laplace.seed;\n\n\nrandom.array.laplace.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.laplace.seedLength;\n\n\nrandom.array.laplace.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.laplace( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.laplace.state\n    <Uint32Array>\n\n    > out = random.array.laplace( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.laplace( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.laplace.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.laplace( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.laplace.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.laplace.stateLength;\n\n\nrandom.array.laplace.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.laplace.byteLength;\n\n    See Also\n    --------\n    base.random.laplace\n","random.array.laplace.assign":"\nrandom.array.laplace.assign( mu, b, out )\n    Fills an array with pseudorandom numbers drawn from a Laplace (double\n    exponential) distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Mean.\n\n    b: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.laplace.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.laplace.factory":"\nrandom.array.laplace.factory( [mu, b, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Laplace (double exponential) distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Mean.\n\n    b: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.laplace.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.laplace.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.laplace.PRNG":"\nrandom.array.laplace.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.laplace.PRNG;","random.array.laplace.seed":"\nrandom.array.laplace.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.laplace.seed;","random.array.laplace.seedLength":"\nrandom.array.laplace.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.laplace.seedLength;","random.array.laplace.state":"\nrandom.array.laplace.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.laplace( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.laplace.state\n    <Uint32Array>\n\n    > out = random.array.laplace( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.laplace( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.laplace.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.laplace( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.laplace.stateLength":"\nrandom.array.laplace.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.laplace.stateLength;","random.array.laplace.byteLength":"\nrandom.array.laplace.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.laplace.byteLength;\n\n    See Also\n    --------\n    base.random.laplace","random.array.levy":"\nrandom.array.levy( len, mu, c[, options] )\n    Returns an array containing pseudorandom numbers drawn from a Lévy\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    mu: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.levy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.levy.assign( mu, c, out )\n    Fills an array with pseudorandom numbers drawn from a Lévy distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.levy.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.levy.factory( [mu, c, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Lévy distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Location parameter.\n\n    c: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.levy.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.levy.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.levy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.levy.PRNG;\n\n\nrandom.array.levy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.levy.seed;\n\n\nrandom.array.levy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.levy.seedLength;\n\n\nrandom.array.levy.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.levy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.levy.state\n    <Uint32Array>\n\n    > out = random.array.levy( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.levy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.levy.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.levy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.levy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.levy.stateLength;\n\n\nrandom.array.levy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.levy.byteLength;\n\n    See Also\n    --------\n    base.random.levy\n","random.array.levy.assign":"\nrandom.array.levy.assign( mu, c, out )\n    Fills an array with pseudorandom numbers drawn from a Lévy distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.levy.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.levy.factory":"\nrandom.array.levy.factory( [mu, c, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Lévy distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Location parameter.\n\n    c: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.levy.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.levy.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.levy.PRNG":"\nrandom.array.levy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.levy.PRNG;","random.array.levy.seed":"\nrandom.array.levy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.levy.seed;","random.array.levy.seedLength":"\nrandom.array.levy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.levy.seedLength;","random.array.levy.state":"\nrandom.array.levy.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.levy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.levy.state\n    <Uint32Array>\n\n    > out = random.array.levy( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.levy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.levy.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.levy( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.levy.stateLength":"\nrandom.array.levy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.levy.stateLength;","random.array.levy.byteLength":"\nrandom.array.levy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.levy.byteLength;\n\n    See Also\n    --------\n    base.random.levy","random.array.logistic":"\nrandom.array.logistic( len, mu, s[, options] )\n    Returns an array containing pseudorandom numbers drawn from a logistic\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    mu: number\n        Mean parameter.\n\n    s: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.logistic( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.logistic.assign( mu, s, out )\n    Fills an array with pseudorandom numbers drawn from a logistic distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Mean parameter.\n\n    s: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.logistic.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.logistic.factory( [mu, s, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a logistic distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Mean parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.logistic.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.logistic.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.logistic.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.logistic.PRNG;\n\n\nrandom.array.logistic.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.logistic.seed;\n\n\nrandom.array.logistic.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.logistic.seedLength;\n\n\nrandom.array.logistic.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.logistic( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.logistic.state\n    <Uint32Array>\n\n    > out = random.array.logistic( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.logistic( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.logistic.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.logistic( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.logistic.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.logistic.stateLength;\n\n\nrandom.array.logistic.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.logistic.byteLength;\n\n    See Also\n    --------\n    base.random.logistic\n","random.array.logistic.assign":"\nrandom.array.logistic.assign( mu, s, out )\n    Fills an array with pseudorandom numbers drawn from a logistic distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Mean parameter.\n\n    s: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.logistic.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.logistic.factory":"\nrandom.array.logistic.factory( [mu, s, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a logistic distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Mean parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.logistic.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.logistic.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.logistic.PRNG":"\nrandom.array.logistic.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.logistic.PRNG;","random.array.logistic.seed":"\nrandom.array.logistic.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.logistic.seed;","random.array.logistic.seedLength":"\nrandom.array.logistic.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.logistic.seedLength;","random.array.logistic.state":"\nrandom.array.logistic.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.logistic( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.logistic.state\n    <Uint32Array>\n\n    > out = random.array.logistic( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.logistic( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.logistic.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.logistic( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.logistic.stateLength":"\nrandom.array.logistic.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.logistic.stateLength;","random.array.logistic.byteLength":"\nrandom.array.logistic.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.logistic.byteLength;\n\n    See Also\n    --------\n    base.random.logistic","random.array.lognormal":"\nrandom.array.lognormal( len, mu, sigma[, options] )\n    Returns an array containing pseudorandom numbers drawn from a lognormal\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    mu: number\n        Location parameter.\n\n    sigma: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.lognormal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.lognormal.assign( mu, sigma, out )\n    Fills an array with pseudorandom numbers drawn from a lognormal\n    distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Location parameter.\n\n    sigma: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.lognormal.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.lognormal.factory( [mu, sigma, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a lognormal distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Location parameter.\n\n    sigma: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.lognormal.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.lognormal.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.lognormal.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.lognormal.PRNG;\n\n\nrandom.array.lognormal.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.lognormal.seed;\n\n\nrandom.array.lognormal.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.lognormal.seedLength;\n\n\nrandom.array.lognormal.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.lognormal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.lognormal.state\n    <Uint32Array>\n\n    > out = random.array.lognormal( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.lognormal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.lognormal.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.lognormal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.lognormal.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.lognormal.stateLength;\n\n\nrandom.array.lognormal.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.lognormal.byteLength;\n\n    See Also\n    --------\n    base.random.lognormal, random.strided.lognormal\n","random.array.lognormal.assign":"\nrandom.array.lognormal.assign( mu, sigma, out )\n    Fills an array with pseudorandom numbers drawn from a lognormal\n    distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Location parameter.\n\n    sigma: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.lognormal.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.lognormal.factory":"\nrandom.array.lognormal.factory( [mu, sigma, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a lognormal distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Location parameter.\n\n    sigma: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.lognormal.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.lognormal.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.lognormal.PRNG":"\nrandom.array.lognormal.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.lognormal.PRNG;","random.array.lognormal.seed":"\nrandom.array.lognormal.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.lognormal.seed;","random.array.lognormal.seedLength":"\nrandom.array.lognormal.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.lognormal.seedLength;","random.array.lognormal.state":"\nrandom.array.lognormal.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.lognormal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.lognormal.state\n    <Uint32Array>\n\n    > out = random.array.lognormal( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.lognormal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.lognormal.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.lognormal( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.lognormal.stateLength":"\nrandom.array.lognormal.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.lognormal.stateLength;","random.array.lognormal.byteLength":"\nrandom.array.lognormal.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.lognormal.byteLength;\n\n    See Also\n    --------\n    base.random.lognormal, random.strided.lognormal","random.array.minstd":"\nrandom.array.minstd( len[, options] )\n    Returns an array containing pseudorandom integers on the interval\n    `[1, 2147483646]`.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.minstd( 3 )\n    <Float64Array>\n\n\nrandom.array.minstd.normalized( len[, options] )\n    Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.minstd.normalized( 3 )\n    <Float64Array>\n\n\nrandom.array.minstd.factory( [options] )\n    Returns a function for creating arrays containing pseudorandom numbers\n    generated using a linear congruential pseudorandom number generator (LCG).\n\n    The returned function and its attached `normalized` method accept the\n    following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.idtype: string (optional)\n        Default output array data type when generating integers. Default:\n        'float64'.\n\n    options.ndtype: string (optional)\n        Default output array data type when generating normalized numbers.\n        Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.minstd.factory();\n    > var out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.minstd.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.minstd.PRNG;\n\n\nrandom.array.minstd.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.minstd.seed;\n\n\nrandom.array.minstd.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.minstd.seedLength;\n\n\nrandom.array.minstd.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.minstd( 3 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.minstd.state;\n\n    > out = random.array.minstd( 3 )\n    <Float64Array>\n    > out = random.array.minstd( 3 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.minstd.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.minstd( 3 )\n    <Float64Array>\n\n\nrandom.array.minstd.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.minstd.stateLength;\n\n\nrandom.array.minstd.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.minstd.byteLength;\n\n    See Also\n    --------\n    random.array.minstdShuffle, random.array.randu, base.random.minstd, random.strided.minstd\n","random.array.minstd.normalized":"\nrandom.array.minstd.normalized( len[, options] )\n    Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.minstd.normalized( 3 )\n    <Float64Array>","random.array.minstd.factory":"\nrandom.array.minstd.factory( [options] )\n    Returns a function for creating arrays containing pseudorandom numbers\n    generated using a linear congruential pseudorandom number generator (LCG).\n\n    The returned function and its attached `normalized` method accept the\n    following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.idtype: string (optional)\n        Default output array data type when generating integers. Default:\n        'float64'.\n\n    options.ndtype: string (optional)\n        Default output array data type when generating normalized numbers.\n        Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.minstd.factory();\n    > var out = fcn( 3 )\n    <Float64Array>","random.array.minstd.PRNG":"\nrandom.array.minstd.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.minstd.PRNG;","random.array.minstd.seed":"\nrandom.array.minstd.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.minstd.seed;","random.array.minstd.seedLength":"\nrandom.array.minstd.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.minstd.seedLength;","random.array.minstd.state":"\nrandom.array.minstd.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.minstd( 3 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.minstd.state;\n\n    > out = random.array.minstd( 3 )\n    <Float64Array>\n    > out = random.array.minstd( 3 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.minstd.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.minstd( 3 )\n    <Float64Array>","random.array.minstd.stateLength":"\nrandom.array.minstd.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.minstd.stateLength;","random.array.minstd.byteLength":"\nrandom.array.minstd.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.minstd.byteLength;\n\n    See Also\n    --------\n    random.array.minstdShuffle, random.array.randu, base.random.minstd, random.strided.minstd","random.array.minstdShuffle":"\nrandom.array.minstdShuffle( len[, options] )\n    Returns an array containing pseudorandom integers on the interval\n    `[1, 2147483646]`.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.minstdShuffle( 3 )\n    <Float64Array>\n\n\nrandom.array.minstdShuffle.normalized( len[, options] )\n    Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.minstdShuffle.normalized( 3 )\n    <Float64Array>\n\n\nrandom.array.minstdShuffle.factory( [options] )\n    Returns a function for creating arrays containing pseudorandom numbers\n    generated using a linear congruential pseudorandom number generator (LCG)\n    whose output is shuffled.\n\n    The returned function and its attached `normalized` method accept the\n    following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.idtype: string (optional)\n        Default output array data type when generating integers. Default:\n        'float64'.\n\n    options.ndtype: string (optional)\n        Default output array data type when generating normalized numbers.\n        Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.minstdShuffle.factory();\n    > var out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.minstdShuffle.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.minstdShuffle.PRNG;\n\n\nrandom.array.minstdShuffle.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.minstdShuffle.seed;\n\n\nrandom.array.minstdShuffle.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.minstdShuffle.seedLength;\n\n\nrandom.array.minstdShuffle.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.minstdShuffle( 3 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.minstdShuffle.state;\n\n    > out = random.array.minstdShuffle( 3 )\n    <Float64Array>\n    > out = random.array.minstdShuffle( 3 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.minstdShuffle.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.minstdShuffle( 3 )\n    <Float64Array>\n\n\nrandom.array.minstdShuffle.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.minstdShuffle.stateLength;\n\n\nrandom.array.minstdShuffle.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.minstdShuffle.byteLength;\n\n    See Also\n    --------\n    random.array.minstd, random.array.randu, base.random.minstdShuffle, random.strided.minstdShuffle\n","random.array.minstdShuffle.normalized":"\nrandom.array.minstdShuffle.normalized( len[, options] )\n    Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.minstdShuffle.normalized( 3 )\n    <Float64Array>","random.array.minstdShuffle.factory":"\nrandom.array.minstdShuffle.factory( [options] )\n    Returns a function for creating arrays containing pseudorandom numbers\n    generated using a linear congruential pseudorandom number generator (LCG)\n    whose output is shuffled.\n\n    The returned function and its attached `normalized` method accept the\n    following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.idtype: string (optional)\n        Default output array data type when generating integers. Default:\n        'float64'.\n\n    options.ndtype: string (optional)\n        Default output array data type when generating normalized numbers.\n        Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.minstdShuffle.factory();\n    > var out = fcn( 3 )\n    <Float64Array>","random.array.minstdShuffle.PRNG":"\nrandom.array.minstdShuffle.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.minstdShuffle.PRNG;","random.array.minstdShuffle.seed":"\nrandom.array.minstdShuffle.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.minstdShuffle.seed;","random.array.minstdShuffle.seedLength":"\nrandom.array.minstdShuffle.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.minstdShuffle.seedLength;","random.array.minstdShuffle.state":"\nrandom.array.minstdShuffle.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.minstdShuffle( 3 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.minstdShuffle.state;\n\n    > out = random.array.minstdShuffle( 3 )\n    <Float64Array>\n    > out = random.array.minstdShuffle( 3 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.minstdShuffle.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.minstdShuffle( 3 )\n    <Float64Array>","random.array.minstdShuffle.stateLength":"\nrandom.array.minstdShuffle.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.minstdShuffle.stateLength;","random.array.minstdShuffle.byteLength":"\nrandom.array.minstdShuffle.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.minstdShuffle.byteLength;\n\n    See Also\n    --------\n    random.array.minstd, random.array.randu, base.random.minstdShuffle, random.strided.minstdShuffle","random.array.mt19937":"\nrandom.array.mt19937( len[, options] )\n    Returns an array containing pseudorandom integers on the interval\n    `[0, 4294967295]`.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.mt19937( 3 )\n    <Float64Array>\n\n\nrandom.array.mt19937.normalized( len[, options] )\n    Returns an array containing pseudorandom numbers on the interval `[0, 1)`\n    with 53-bit precision.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.mt19937.normalized( 3 )\n    <Float64Array>\n\n\nrandom.array.mt19937.factory( [options] )\n    Returns a function for creating arrays containing pseudorandom numbers\n    generated using a 32-bit Mersenne Twister pseudorandom number generator.\n\n    The returned function and its attached `normalized` method accept the\n    following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.idtype: string (optional)\n        Default output array data type when generating integers. Default:\n        'float64'.\n\n    options.ndtype: string (optional)\n        Default output array data type when generating normalized numbers.\n        Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.mt19937.factory();\n    > var out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.mt19937.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.mt19937.PRNG;\n\n\nrandom.array.mt19937.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.mt19937.seed;\n\n\nrandom.array.mt19937.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.mt19937.seedLength;\n\n\nrandom.array.mt19937.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.mt19937( 3 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.mt19937.state;\n\n    > out = random.array.mt19937( 3 )\n    <Float64Array>\n    > out = random.array.mt19937( 3 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.mt19937.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.mt19937( 3 )\n    <Float64Array>\n\n\nrandom.array.mt19937.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.mt19937.stateLength;\n\n\nrandom.array.mt19937.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.mt19937.byteLength;\n\n    See Also\n    --------\n    random.array.randu, base.random.mt19937, random.strided.mt19937\n","random.array.mt19937.normalized":"\nrandom.array.mt19937.normalized( len[, options] )\n    Returns an array containing pseudorandom numbers on the interval `[0, 1)`\n    with 53-bit precision.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.mt19937.normalized( 3 )\n    <Float64Array>","random.array.mt19937.factory":"\nrandom.array.mt19937.factory( [options] )\n    Returns a function for creating arrays containing pseudorandom numbers\n    generated using a 32-bit Mersenne Twister pseudorandom number generator.\n\n    The returned function and its attached `normalized` method accept the\n    following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.idtype: string (optional)\n        Default output array data type when generating integers. Default:\n        'float64'.\n\n    options.ndtype: string (optional)\n        Default output array data type when generating normalized numbers.\n        Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.mt19937.factory();\n    > var out = fcn( 3 )\n    <Float64Array>","random.array.mt19937.PRNG":"\nrandom.array.mt19937.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.mt19937.PRNG;","random.array.mt19937.seed":"\nrandom.array.mt19937.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.mt19937.seed;","random.array.mt19937.seedLength":"\nrandom.array.mt19937.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.mt19937.seedLength;","random.array.mt19937.state":"\nrandom.array.mt19937.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.mt19937( 3 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.mt19937.state;\n\n    > out = random.array.mt19937( 3 )\n    <Float64Array>\n    > out = random.array.mt19937( 3 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.mt19937.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.mt19937( 3 )\n    <Float64Array>","random.array.mt19937.stateLength":"\nrandom.array.mt19937.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.mt19937.stateLength;","random.array.mt19937.byteLength":"\nrandom.array.mt19937.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.mt19937.byteLength;\n\n    See Also\n    --------\n    random.array.randu, base.random.mt19937, random.strided.mt19937","random.array.negativeBinomial":"\nrandom.array.negativeBinomial( len, r, p[, options] )\n    Returns an array containing pseudorandom numbers drawn from a negative\n    binomial distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.negativeBinomial( 3, 10, 0.5 )\n    <Float64Array>\n\n\nrandom.array.negativeBinomial.assign( r, p, out )\n    Fills an array with pseudorandom numbers drawn from a negative binomial\n    distribution.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.negativeBinomial.assign( 10, 0.5, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.negativeBinomial.factory( [r, p, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a negative binomial distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    r: number (optional)\n        Number of successes until experiment is stopped.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.negativeBinomial.factory();\n    > var out = fcn( 3, 10, 0.5 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.negativeBinomial.factory( 10, 0.5 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.negativeBinomial.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.negativeBinomial.PRNG;\n\n\nrandom.array.negativeBinomial.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.negativeBinomial.seed;\n\n\nrandom.array.negativeBinomial.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.negativeBinomial.seedLength;\n\n\nrandom.array.negativeBinomial.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.negativeBinomial( 3, 10, 0.5 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.negativeBinomial.state\n    <Uint32Array>\n\n    > out = random.array.negativeBinomial( 3, 10, 0.5 )\n    <Float64Array>\n    > out = random.array.negativeBinomial( 3, 10, 0.5 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.negativeBinomial.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.negativeBinomial( 3, 10, 0.5 )\n    <Float64Array>\n\n\nrandom.array.negativeBinomial.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.negativeBinomial.stateLength;\n\n\nrandom.array.negativeBinomial.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.negativeBinomial.byteLength;\n\n    See Also\n    --------\n    random.array.binomial, base.random.negativeBinomial\n","random.array.negativeBinomial.assign":"\nrandom.array.negativeBinomial.assign( r, p, out )\n    Fills an array with pseudorandom numbers drawn from a negative binomial\n    distribution.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.negativeBinomial.assign( 10, 0.5, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.negativeBinomial.factory":"\nrandom.array.negativeBinomial.factory( [r, p, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a negative binomial distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    r: number (optional)\n        Number of successes until experiment is stopped.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.negativeBinomial.factory();\n    > var out = fcn( 3, 10, 0.5 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.negativeBinomial.factory( 10, 0.5 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.negativeBinomial.PRNG":"\nrandom.array.negativeBinomial.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.negativeBinomial.PRNG;","random.array.negativeBinomial.seed":"\nrandom.array.negativeBinomial.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.negativeBinomial.seed;","random.array.negativeBinomial.seedLength":"\nrandom.array.negativeBinomial.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.negativeBinomial.seedLength;","random.array.negativeBinomial.state":"\nrandom.array.negativeBinomial.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.negativeBinomial( 3, 10, 0.5 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.negativeBinomial.state\n    <Uint32Array>\n\n    > out = random.array.negativeBinomial( 3, 10, 0.5 )\n    <Float64Array>\n    > out = random.array.negativeBinomial( 3, 10, 0.5 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.negativeBinomial.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.negativeBinomial( 3, 10, 0.5 )\n    <Float64Array>","random.array.negativeBinomial.stateLength":"\nrandom.array.negativeBinomial.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.negativeBinomial.stateLength;","random.array.negativeBinomial.byteLength":"\nrandom.array.negativeBinomial.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.negativeBinomial.byteLength;\n\n    See Also\n    --------\n    random.array.binomial, base.random.negativeBinomial","random.array.normal":"\nrandom.array.normal( len, mu, sigma[, options] )\n    Returns an array containing pseudorandom numbers drawn from a normal\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    mu: number\n        Mean.\n\n    sigma: number\n        Standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.normal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.normal.assign( mu, sigma, out )\n    Fills an array with pseudorandom numbers drawn from a normal distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Mean.\n\n    sigma: number\n        Standard deviation.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.normal.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.normal.factory( [mu, sigma, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a normal distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Mean.\n\n    sigma: number (optional)\n        Standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.normal.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.normal.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.normal.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.normal.PRNG;\n\n\nrandom.array.normal.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.normal.seed;\n\n\nrandom.array.normal.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.normal.seedLength;\n\n\nrandom.array.normal.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.normal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.normal.state\n    <Uint32Array>\n\n    > out = random.array.normal( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.normal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.normal.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.normal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.normal.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.normal.stateLength;\n\n\nrandom.array.normal.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.normal.byteLength;\n\n    See Also\n    --------\n    base.random.normal, random.strided.normal\n","random.array.normal.assign":"\nrandom.array.normal.assign( mu, sigma, out )\n    Fills an array with pseudorandom numbers drawn from a normal distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Mean.\n\n    sigma: number\n        Standard deviation.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.normal.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.normal.factory":"\nrandom.array.normal.factory( [mu, sigma, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a normal distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Mean.\n\n    sigma: number (optional)\n        Standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.normal.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.normal.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.normal.PRNG":"\nrandom.array.normal.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.normal.PRNG;","random.array.normal.seed":"\nrandom.array.normal.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.normal.seed;","random.array.normal.seedLength":"\nrandom.array.normal.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.normal.seedLength;","random.array.normal.state":"\nrandom.array.normal.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.normal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.normal.state\n    <Uint32Array>\n\n    > out = random.array.normal( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.normal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.normal.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.normal( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.normal.stateLength":"\nrandom.array.normal.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.normal.stateLength;","random.array.normal.byteLength":"\nrandom.array.normal.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.normal.byteLength;\n\n    See Also\n    --------\n    base.random.normal, random.strided.normal","random.array.pareto1":"\nrandom.array.pareto1( len, alpha, beta[, options] )\n    Returns an array containing pseudorandom numbers drawn from a Pareto (Type\n    I) distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    alpha: number\n        Shape parameter.\n\n    beta: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.pareto1( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.pareto1.assign( alpha, beta, out )\n    Fills an array with pseudorandom numbers drawn from a Pareto (Type I)\n    distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        Shape parameter.\n\n    beta: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.pareto1.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.pareto1.factory( [alpha, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Pareto (Type I) distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        Shape parameter.\n\n    beta: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.pareto1.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.pareto1.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.pareto1.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.pareto1.PRNG;\n\n\nrandom.array.pareto1.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.pareto1.seed;\n\n\nrandom.array.pareto1.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.pareto1.seedLength;\n\n\nrandom.array.pareto1.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.pareto1( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.pareto1.state\n    <Uint32Array>\n\n    > out = random.array.pareto1( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.pareto1( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.pareto1.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.pareto1( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.pareto1.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.pareto1.stateLength;\n\n\nrandom.array.pareto1.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.pareto1.byteLength;\n\n    See Also\n    --------\n    base.random.pareto1\n","random.array.pareto1.assign":"\nrandom.array.pareto1.assign( alpha, beta, out )\n    Fills an array with pseudorandom numbers drawn from a Pareto (Type I)\n    distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        Shape parameter.\n\n    beta: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.pareto1.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.pareto1.factory":"\nrandom.array.pareto1.factory( [alpha, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Pareto (Type I) distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        Shape parameter.\n\n    beta: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.pareto1.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.pareto1.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.pareto1.PRNG":"\nrandom.array.pareto1.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.pareto1.PRNG;","random.array.pareto1.seed":"\nrandom.array.pareto1.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.pareto1.seed;","random.array.pareto1.seedLength":"\nrandom.array.pareto1.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.pareto1.seedLength;","random.array.pareto1.state":"\nrandom.array.pareto1.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.pareto1( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.pareto1.state\n    <Uint32Array>\n\n    > out = random.array.pareto1( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.pareto1( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.pareto1.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.pareto1( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.pareto1.stateLength":"\nrandom.array.pareto1.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.pareto1.stateLength;","random.array.pareto1.byteLength":"\nrandom.array.pareto1.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.pareto1.byteLength;\n\n    See Also\n    --------\n    base.random.pareto1","random.array.poisson":"\nrandom.array.poisson( len, lambda[, options] )\n    Returns an array containing pseudorandom numbers drawn from a Poisson\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    lambda: number\n        Mean parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.poisson( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.poisson.assign( lambda, out )\n    Fills an array with pseudorandom numbers drawn from a Poisson distribution.\n\n    Parameters\n    ----------\n    lambda: number\n        Mean parameter.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.poisson.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.poisson.factory( [lambda, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Poisson distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    lambda: number (optional)\n        Mean parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.poisson.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.poisson.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.poisson.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.poisson.PRNG;\n\n\nrandom.array.poisson.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.poisson.seed;\n\n\nrandom.array.poisson.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.poisson.seedLength;\n\n\nrandom.array.poisson.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.poisson( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.poisson.state\n    <Uint32Array>\n\n    > out = random.array.poisson( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.poisson( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.poisson.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.poisson( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.poisson.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.poisson.stateLength;\n\n\nrandom.array.poisson.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.poisson.byteLength;\n\n    See Also\n    --------\n    base.random.poisson, random.strided.poisson\n","random.array.poisson.assign":"\nrandom.array.poisson.assign( lambda, out )\n    Fills an array with pseudorandom numbers drawn from a Poisson distribution.\n\n    Parameters\n    ----------\n    lambda: number\n        Mean parameter.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.poisson.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.poisson.factory":"\nrandom.array.poisson.factory( [lambda, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Poisson distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    lambda: number (optional)\n        Mean parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.poisson.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.poisson.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.poisson.PRNG":"\nrandom.array.poisson.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.poisson.PRNG;","random.array.poisson.seed":"\nrandom.array.poisson.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.poisson.seed;","random.array.poisson.seedLength":"\nrandom.array.poisson.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.poisson.seedLength;","random.array.poisson.state":"\nrandom.array.poisson.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.poisson( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.poisson.state\n    <Uint32Array>\n\n    > out = random.array.poisson( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.poisson( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.poisson.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.poisson( 3, 2.0 )\n    <Float64Array>","random.array.poisson.stateLength":"\nrandom.array.poisson.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.poisson.stateLength;","random.array.poisson.byteLength":"\nrandom.array.poisson.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.poisson.byteLength;\n\n    See Also\n    --------\n    base.random.poisson, random.strided.poisson","random.array.randu":"\nrandom.array.randu( len[, options] )\n    Returns an array containing uniformly distributed pseudorandom numbers\n    between 0 and 1.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.randu( 3 )\n    <Float64Array>\n\n\nrandom.array.randu.factory( [options] )\n    Returns a function for creating arrays containing uniformly distributed\n    pseudorandom numbers between 0 and 1.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: `'mt19937'`.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.randu.factory();\n    > var out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.randu.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.randu.PRNG;\n\n\nrandom.array.randu.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.randu.seed;\n\n\nrandom.array.randu.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.randu.seedLength;\n\n\nrandom.array.randu.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.randu( 3 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.randu.state;\n\n    > out = random.array.randu( 3 )\n    <Float64Array>\n    > out = random.array.randu( 3 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.randu.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.randu( 3 )\n    <Float64Array>\n\n\nrandom.array.randu.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.randu.stateLength;\n\n\nrandom.array.randu.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.randu.byteLength;\n\n    See Also\n    --------\n    random.array.uniform, base.random.randu, random.strided.randu\n","random.array.randu.factory":"\nrandom.array.randu.factory( [options] )\n    Returns a function for creating arrays containing uniformly distributed\n    pseudorandom numbers between 0 and 1.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: `'mt19937'`.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.randu.factory();\n    > var out = fcn( 3 )\n    <Float64Array>","random.array.randu.PRNG":"\nrandom.array.randu.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.randu.PRNG;","random.array.randu.seed":"\nrandom.array.randu.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.randu.seed;","random.array.randu.seedLength":"\nrandom.array.randu.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.randu.seedLength;","random.array.randu.state":"\nrandom.array.randu.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.randu( 3 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.randu.state;\n\n    > out = random.array.randu( 3 )\n    <Float64Array>\n    > out = random.array.randu( 3 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.randu.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.randu( 3 )\n    <Float64Array>","random.array.randu.stateLength":"\nrandom.array.randu.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.randu.stateLength;","random.array.randu.byteLength":"\nrandom.array.randu.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.randu.byteLength;\n\n    See Also\n    --------\n    random.array.uniform, base.random.randu, random.strided.randu","random.array.rayleigh":"\nrandom.array.rayleigh( len, sigma[, options] )\n    Returns an array containing pseudorandom numbers drawn from a Rayleigh\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    sigma: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.rayleigh( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.rayleigh.assign( sigma, out )\n    Fills an array with pseudorandom numbers drawn from a Rayleigh distribution.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.rayleigh.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.rayleigh.factory( [sigma, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Rayleigh distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    sigma: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.rayleigh.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.rayleigh.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.rayleigh.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.rayleigh.PRNG;\n\n\nrandom.array.rayleigh.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.rayleigh.seed;\n\n\nrandom.array.rayleigh.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.rayleigh.seedLength;\n\n\nrandom.array.rayleigh.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.rayleigh( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.rayleigh.state\n    <Uint32Array>\n\n    > out = random.array.rayleigh( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.rayleigh( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.rayleigh.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.rayleigh( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.rayleigh.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.rayleigh.stateLength;\n\n\nrandom.array.rayleigh.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.rayleigh.byteLength;\n\n    See Also\n    --------\n    base.random.rayleigh, random.strided.rayleigh\n","random.array.rayleigh.assign":"\nrandom.array.rayleigh.assign( sigma, out )\n    Fills an array with pseudorandom numbers drawn from a Rayleigh distribution.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.rayleigh.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.rayleigh.factory":"\nrandom.array.rayleigh.factory( [sigma, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Rayleigh distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    sigma: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.rayleigh.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.rayleigh.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.rayleigh.PRNG":"\nrandom.array.rayleigh.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.rayleigh.PRNG;","random.array.rayleigh.seed":"\nrandom.array.rayleigh.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.rayleigh.seed;","random.array.rayleigh.seedLength":"\nrandom.array.rayleigh.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.rayleigh.seedLength;","random.array.rayleigh.state":"\nrandom.array.rayleigh.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.rayleigh( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.rayleigh.state\n    <Uint32Array>\n\n    > out = random.array.rayleigh( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.rayleigh( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.rayleigh.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.rayleigh( 3, 2.0 )\n    <Float64Array>","random.array.rayleigh.stateLength":"\nrandom.array.rayleigh.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.rayleigh.stateLength;","random.array.rayleigh.byteLength":"\nrandom.array.rayleigh.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.rayleigh.byteLength;\n\n    See Also\n    --------\n    base.random.rayleigh, random.strided.rayleigh","random.array.t":"\nrandom.array.t( len, v[, options] )\n    Returns an array containing pseudorandom numbers drawn from a Student's t\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    v: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.t( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.t.assign( v, out )\n    Fills an array with pseudorandom numbers drawn from a Student's t\n    distribution.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.t.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.t.factory( [v, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Student's t distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    v: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.t.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.t.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.t.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.t.PRNG;\n\n\nrandom.array.t.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.t.seed;\n\n\nrandom.array.t.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.t.seedLength;\n\n\nrandom.array.t.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.t( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.t.state\n    <Uint32Array>\n\n    > out = random.array.t( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.t( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.t.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.t( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.t.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.t.stateLength;\n\n\nrandom.array.t.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.t.byteLength;\n\n    See Also\n    --------\n    base.random.t, random.strided.t\n","random.array.t.assign":"\nrandom.array.t.assign( v, out )\n    Fills an array with pseudorandom numbers drawn from a Student's t\n    distribution.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.t.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.t.factory":"\nrandom.array.t.factory( [v, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Student's t distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    v: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.t.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.t.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.t.PRNG":"\nrandom.array.t.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.t.PRNG;","random.array.t.seed":"\nrandom.array.t.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.t.seed;","random.array.t.seedLength":"\nrandom.array.t.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.t.seedLength;","random.array.t.state":"\nrandom.array.t.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.t( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.t.state\n    <Uint32Array>\n\n    > out = random.array.t( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.t( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.t.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.t( 3, 2.0 )\n    <Float64Array>","random.array.t.stateLength":"\nrandom.array.t.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.t.stateLength;","random.array.t.byteLength":"\nrandom.array.t.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.t.byteLength;\n\n    See Also\n    --------\n    base.random.t, random.strided.t","random.array.triangular":"\nrandom.array.triangular( len, a, b, c[, options] )\n    Returns an array containing pseudorandom numbers drawn from a triangular\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n\nrandom.array.triangular.assign( a, b, c, out )\n    Fills an array with pseudorandom numbers drawn from a triangular\n    distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.triangular.assign( 2.0, 5.0, 3.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.triangular.factory( [a, b, c, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a triangular distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    c: number (optional)\n        Mode.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.triangular.factory();\n    > var out = fcn( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.triangular.factory( 2.0, 5.0, 3.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.triangular.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.triangular.PRNG;\n\n\nrandom.array.triangular.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.triangular.seed;\n\n\nrandom.array.triangular.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.triangular.seedLength;\n\n\nrandom.array.triangular.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.triangular.state\n    <Uint32Array>\n\n    > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n    > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.triangular.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n\nrandom.array.triangular.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.triangular.stateLength;\n\n\nrandom.array.triangular.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.triangular.byteLength;\n\n    See Also\n    --------\n    base.random.triangular\n","random.array.triangular.assign":"\nrandom.array.triangular.assign( a, b, c, out )\n    Fills an array with pseudorandom numbers drawn from a triangular\n    distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.triangular.assign( 2.0, 5.0, 3.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.triangular.factory":"\nrandom.array.triangular.factory( [a, b, c, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a triangular distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    c: number (optional)\n        Mode.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.triangular.factory();\n    > var out = fcn( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.triangular.factory( 2.0, 5.0, 3.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.triangular.PRNG":"\nrandom.array.triangular.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.triangular.PRNG;","random.array.triangular.seed":"\nrandom.array.triangular.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.triangular.seed;","random.array.triangular.seedLength":"\nrandom.array.triangular.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.triangular.seedLength;","random.array.triangular.state":"\nrandom.array.triangular.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.triangular.state\n    <Uint32Array>\n\n    > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n    > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.triangular.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>","random.array.triangular.stateLength":"\nrandom.array.triangular.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.triangular.stateLength;","random.array.triangular.byteLength":"\nrandom.array.triangular.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.triangular.byteLength;\n\n    See Also\n    --------\n    base.random.triangular","random.array.uniform":"\nrandom.array.uniform( len, a, b[, options] )\n    Returns an array containing pseudorandom numbers drawn from a continuous\n    uniform distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.uniform( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.uniform.assign( a, b, out )\n    Fills an array with pseudorandom numbers drawn from a continuous uniform\n    distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.uniform.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.uniform.factory( [a, b, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a continuous uniform distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.uniform.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.uniform.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.uniform.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.uniform.PRNG;\n\n\nrandom.array.uniform.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.uniform.seed;\n\n\nrandom.array.uniform.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.uniform.seedLength;\n\n\nrandom.array.uniform.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.uniform( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.uniform.state\n    <Uint32Array>\n\n    > out = random.array.uniform( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.uniform( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.uniform.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.uniform( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.uniform.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.uniform.stateLength;\n\n\nrandom.array.uniform.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.uniform.byteLength;\n\n    See Also\n    --------\n    random.array.discreteUniform, base.random.uniform, random.strided.uniform\n","random.array.uniform.assign":"\nrandom.array.uniform.assign( a, b, out )\n    Fills an array with pseudorandom numbers drawn from a continuous uniform\n    distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.uniform.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.uniform.factory":"\nrandom.array.uniform.factory( [a, b, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a continuous uniform distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.uniform.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.uniform.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.uniform.PRNG":"\nrandom.array.uniform.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.uniform.PRNG;","random.array.uniform.seed":"\nrandom.array.uniform.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.uniform.seed;","random.array.uniform.seedLength":"\nrandom.array.uniform.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.uniform.seedLength;","random.array.uniform.state":"\nrandom.array.uniform.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.uniform( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.uniform.state\n    <Uint32Array>\n\n    > out = random.array.uniform( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.uniform( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.uniform.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.uniform( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.uniform.stateLength":"\nrandom.array.uniform.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.uniform.stateLength;","random.array.uniform.byteLength":"\nrandom.array.uniform.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.uniform.byteLength;\n\n    See Also\n    --------\n    random.array.discreteUniform, base.random.uniform, random.strided.uniform","random.array.weibull":"\nrandom.array.weibull( len, k, lambda[, options] )\n    Returns an array containing pseudorandom numbers drawn from a Weibull\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    k: number\n        Scale parameter.\n\n    lambda: number\n        Shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.weibull( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.weibull.assign( k, lambda, out )\n    Fills an array with pseudorandom numbers drawn from a Weibull distribution.\n\n    Parameters\n    ----------\n    k: number\n        Scale parameter.\n\n    lambda: number\n        Shape parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.weibull.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.weibull.factory( [k, lambda, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Weibull distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Scale parameter.\n\n    lambda: number (optional)\n        Shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.weibull.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.weibull.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.weibull.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.weibull.PRNG;\n\n\nrandom.array.weibull.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.weibull.seed;\n\n\nrandom.array.weibull.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.weibull.seedLength;\n\n\nrandom.array.weibull.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.weibull( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.weibull.state\n    <Uint32Array>\n\n    > out = random.array.weibull( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.weibull( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.weibull.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.weibull( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.weibull.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.weibull.stateLength;\n\n\nrandom.array.weibull.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.weibull.byteLength;\n\n    See Also\n    --------\n    base.random.weibull, random.strided.weibull\n","random.array.weibull.assign":"\nrandom.array.weibull.assign( k, lambda, out )\n    Fills an array with pseudorandom numbers drawn from a Weibull distribution.\n\n    Parameters\n    ----------\n    k: number\n        Scale parameter.\n\n    lambda: number\n        Shape parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.weibull.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.weibull.factory":"\nrandom.array.weibull.factory( [k, lambda, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Weibull distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Scale parameter.\n\n    lambda: number (optional)\n        Shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.weibull.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.weibull.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.weibull.PRNG":"\nrandom.array.weibull.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.weibull.PRNG;","random.array.weibull.seed":"\nrandom.array.weibull.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.weibull.seed;","random.array.weibull.seedLength":"\nrandom.array.weibull.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.weibull.seedLength;","random.array.weibull.state":"\nrandom.array.weibull.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.weibull( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.weibull.state\n    <Uint32Array>\n\n    > out = random.array.weibull( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.weibull( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.weibull.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.weibull( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.weibull.stateLength":"\nrandom.array.weibull.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.weibull.stateLength;","random.array.weibull.byteLength":"\nrandom.array.weibull.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.weibull.byteLength;\n\n    See Also\n    --------\n    base.random.weibull, random.strided.weibull","random.iterators.arcsine":"\nrandom.iterators.arcsine( a, b[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from an\n    arcsine distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.arcsine( 0.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.arcsine\n","random.iterators.bernoulli":"\nrandom.iterators.bernoulli( p[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Bernoulli distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.bernoulli( 0.3 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.bernoulli\n","random.iterators.beta":"\nrandom.iterators.beta( α, β[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    beta distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    The function throws an error if `α <= 0` or `β <= 0`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.beta( 1.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.beta\n","random.iterators.betaprime":"\nrandom.iterators.betaprime( α, β[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    beta prime distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    The function throws an error if `α <= 0` or `β <= 0`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.betaprime( 1.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.betaprime\n","random.iterators.binomial":"\nrandom.iterators.binomial( n, p[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    binomial distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.binomial( 10, 0.3 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.binomial\n","random.iterators.boxMuller":"\nrandom.iterators.boxMuller( [options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    standard normal distribution using the Box-Muller transform.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.boxMuller();\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.boxMuller\n","random.iterators.cauchy":"\nrandom.iterators.cauchy( x0, Ɣ[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Cauchy distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.seed: any\n        Pseudorandom number generator seed.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.cauchy( 0.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.cauchy\n","random.iterators.chi":"\nrandom.iterators.chi( k[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a chi\n    distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.chi( 1.5 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.chi\n","random.iterators.chisquare":"\nrandom.iterators.chisquare( k[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    chi-square distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.chisquare( 1.5 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.chisquare\n","random.iterators.cosine":"\nrandom.iterators.cosine( μ, s[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a raised\n    cosine distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.cosine( 0.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.cosine\n","random.iterators.discreteUniform":"\nrandom.iterators.discreteUniform( a, b[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    discrete uniform distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom integers. If provided, the `state` and `seed`\n        options are ignored. In order to seed the returned iterator, one must\n        seed the provided `prng` (assuming the provided `prng` is seedable). The\n        provided PRNG must have `MIN` and `MAX` properties specifying the\n        minimum and maximum possible pseudorandom integers.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.discreteUniform( 0, 3 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.discreteUniform\n","random.iterators.erlang":"\nrandom.iterators.erlang( k, λ[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from an Erlang\n    distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If `k` is not a positive integer or `λ <= 0`, the function throws an error.\n\n    Parameters\n    ----------\n    k: integer\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.erlang( 1, 1.5 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.erlang\n","random.iterators.exponential":"\nrandom.iterators.exponential( λ[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from an\n    exponential distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.exponential( 1.5 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.exponential\n","random.iterators.f":"\nrandom.iterators.f( d1, d2[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from an F\n    distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    The function throws an error if `d1 <= 0` or `d2 <= 0`.\n\n    Parameters\n    ----------\n    d1: number\n        Degrees of freedom.\n\n    d2: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.f( 1.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.f\n","random.iterators.frechet":"\nrandom.iterators.frechet( α, s, m[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Fréchet\n    distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    The function throws an error if `α <= 0` or `s <= 0`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.frechet( 1.0, 1.0, 0.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.frechet\n","random.iterators.gamma":"\nrandom.iterators.gamma( α, β[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a gamma\n    distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    The function throws an error if `α <= 0` or `β <= 0`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.gamma( 1.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.gamma\n","random.iterators.geometric":"\nrandom.iterators.geometric( p[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    geometric distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.geometric( 0.3 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.geometric\n","random.iterators.gumbel":"\nrandom.iterators.gumbel( μ, β[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Gumbel\n    distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.gumbel( 0.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.gumbel\n","random.iterators.hypergeometric":"\nrandom.iterators.hypergeometric( N, K, n[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    hypergeometric distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    `N`, `K`, and `n` must all be nonnegative integers; otherwise, the function\n    throws an error.\n\n    If `n > N` or `K > N`, the function throws an error.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.hypergeometric( 20, 10, 7 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.hypergeometric\n","random.iterators.improvedZiggurat":"\nrandom.iterators.improvedZiggurat( [options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    standard normal distribution using the Improved Ziggurat algorithm.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.improvedZiggurat();\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.improvedZiggurat\n","random.iterators.invgamma":"\nrandom.iterators.invgamma( α, β[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from an\n    inverse gamma distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    The function throws an error if `α <= 0` or `β <= 0`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.invgamma( 1.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.invgamma\n","random.iterators.kumaraswamy":"\nrandom.iterators.kumaraswamy( a, b[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Kumaraswamy's double bounded distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    The function throws an error if `a <= 0` or `b <= 0`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.kumaraswamy( 1.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.kumaraswamy\n","random.iterators.laplace":"\nrandom.iterators.laplace( μ, b[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Laplace\n    (double exponential) distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    b: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.laplace( 0.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.laplace\n","random.iterators.levy":"\nrandom.iterators.levy( μ, c[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Lévy\n    distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    c: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.levy( 0.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.levy\n","random.iterators.logistic":"\nrandom.iterators.logistic( μ, s[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    logistic distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    s: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.logistic( 0.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.logistic\n","random.iterators.lognormal":"\nrandom.iterators.lognormal( μ, σ[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    lognormal distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.lognormal( 0.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.lognormal\n","random.iterators.minstd":"\nrandom.iterators.minstd( [options] )\n    Returns an iterator for generating pseudorandom integers on the interval\n    `[1, 2147483646]`.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    This pseudorandom number generator (PRNG) is a linear congruential\n    pseudorandom number generator (LCG) based on Park and Miller.\n\n    The generator has a period of approximately `2.1e9`.\n\n    An LCG is fast and uses little memory. On the other hand, because the\n    generator is a simple LCG, the generator has recognized shortcomings. By\n    today's PRNG standards, the generator's period is relatively short. More\n    importantly, the \"randomness quality\" of the generator's output is lacking.\n    These defects make the generator unsuitable, for example, in Monte Carlo\n    simulations and in cryptographic applications.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing positive signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.seed: Int32Array\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer\n        Length of generator seed.\n\n    iterator.state: Int32Array\n        Generator state.\n\n    iterator.stateLength: integer\n        Length of generator state.\n\n    iterator.byteLength: integer\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.minstd();\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.minstd, random.iterators.minstdShuffle, random.iterators.mt19937, random.iterators.randi, random.iterators.randu\n","random.iterators.minstdShuffle":"\nrandom.iterators.minstdShuffle( [options] )\n    Returns an iterator for generating pseudorandom integers on the interval\n    `[1, 2147483646]`.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    This pseudorandom number generator (PRNG) is a linear congruential\n    pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n    Durham algorithm. The shuffle step considerably strengthens the \"randomness\n    quality\" of a simple LCG's output.\n\n    The generator has a period of approximately `2.1e9`.\n\n    An LCG is fast and uses little memory. On the other hand, because the\n    generator is a simple LCG, the generator has recognized shortcomings. By\n    today's PRNG standards, the generator's period is relatively short. In\n    general, this generator is unsuitable for Monte Carlo simulations and\n    cryptographic applications.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing positive signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.seed: Int32Array\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer\n        Length of generator seed.\n\n    iterator.state: Int32Array\n        Generator state.\n\n    iterator.stateLength: integer\n        Length of generator state.\n\n    iterator.byteLength: integer\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.minstdShuffle();\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.minstdShuffle, random.iterators.minstd, random.iterators.mt19937, random.iterators.randi, random.iterators.randu\n","random.iterators.mt19937":"\nrandom.iterators.mt19937( [options] )\n    Returns an iterator for generating pseudorandom integers on the interval\n    `[1, 4294967295]`.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    This pseudorandom number generator (PRNG) is a 32-bit Mersenne Twister\n    pseudorandom number generator.\n\n    The PRNG is *not* a cryptographically secure PRNG.\n\n    The PRNG has a period of 2^19937 - 1.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.seed: Uint32Array\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer\n        Length of generator seed.\n\n    iterator.state: Uint32Array\n        Generator state.\n\n    iterator.stateLength: integer\n        Length of generator state.\n\n    iterator.byteLength: integer\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.mt19937();\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.mt19937, random.iterators.minstd, random.iterators.minstdShuffle, random.iterators.randi, random.iterators.randu\n","random.iterators.negativeBinomial":"\nrandom.iterators.negativeBinomial( r, p[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    negative binomial distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.negativeBinomial( 10, 0.3 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.negativeBinomial\n","random.iterators.normal":"\nrandom.iterators.normal( μ, σ[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a normal\n    distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    σ: number\n        Standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.normal( 0.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.normal\n","random.iterators.pareto1":"\nrandom.iterators.pareto1( α, β[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Pareto\n    (Type I) distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    The function throws an error if `α <= 0` or `β <= 0`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.pareto1( 1.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.pareto1\n","random.iterators.poisson":"\nrandom.iterators.poisson( λ[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Poisson\n    distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    λ: number\n        Mean.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.poisson( 1.5 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.poisson\n","random.iterators.randi":"\nrandom.iterators.randi( [options] )\n    Create an iterator for generating pseudorandom numbers having integer\n    values.\n\n    The default underlying pseudorandom number generator (PRNG) *may* change in\n    the future. If exact reproducibility is required, either explicitly specify\n    a PRNG via the `name` option or use an underlying PRNG directly.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: `'mt19937'`.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: any\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer\n        Length of generator seed.\n\n    iterator.state: any\n        Generator state.\n\n    iterator.stateLength: integer\n        Length of generator state.\n\n    iterator.byteLength: integer\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.randi();\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.randi, random.iterators.randu\n","random.iterators.randn":"\nrandom.iterators.randn( [options] )\n    Create an iterator for generating pseudorandom numbers drawn from a standard\n    normal distribution.\n\n    The default underlying pseudorandom number generator (PRNG) *may* change in\n    the future. If exact reproducibility is required, either explicitly specify\n    a PRNG via the `name` option or use an underlying PRNG directly.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - improved-ziggurat: improved ziggurat method.\n        - box-muller: Box-Muller transform.\n\n        Default: `'improved-ziggurat'`.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.randn();\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.randn\n","random.iterators.randu":"\nrandom.iterators.randu( [options] )\n    Create an iterator for generating uniformly distributed pseudorandom numbers\n    between 0 and 1.\n\n    The default underlying pseudorandom number generator (PRNG) *may* change in\n    the future. If exact reproducibility is required, either explicitly specify\n    a PRNG via the `name` option or use an underlying PRNG directly.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: `'mt19937'`.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: any\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer\n        Length of generator seed.\n\n    iterator.state: any\n        Generator state.\n\n    iterator.stateLength: integer\n        Length of generator state.\n\n    iterator.byteLength: integer\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.randu();\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.randu, random.iterators.randi\n","random.iterators.rayleigh":"\nrandom.iterators.rayleigh( σ[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Rayleigh distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.rayleigh( 1.5 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.rayleigh\n","random.iterators.t":"\nrandom.iterators.t( v[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Student's t distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.t( 1.5 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.t\n","random.iterators.triangular":"\nrandom.iterators.triangular( a, b, c[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    triangular distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.triangular( 0.0, 1.0, 0.3 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.triangular\n","random.iterators.uniform":"\nrandom.iterators.uniform( a, b[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    continuous uniform distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.uniform( 0.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.uniform\n","random.iterators.weibull":"\nrandom.iterators.weibull( k, λ[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Weibull distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    The function throws an error if `k <= 0` or `λ <= 0`.\n\n    Parameters\n    ----------\n    k: number\n        Scale parameter.\n\n    λ: number\n        Shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.weibull( 1.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.weibull\n","random.streams.arcsine":"\nrandom.streams.arcsine( a, b[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from an\n    arcsine distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.arcsine( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.arcsine.factory( [a, b, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an arcsine distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.arcsine.factory( opts );\n\n\nrandom.streams.arcsine.objectMode( a, b[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an arcsine distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.arcsine.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.arcsine, random.iterators.arcsine\n","random.streams.arcsine.factory":"\nrandom.streams.arcsine.factory( [a, b, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an arcsine distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.arcsine.factory( opts );","random.streams.arcsine.objectMode":"\nrandom.streams.arcsine.objectMode( a, b[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an arcsine distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.arcsine.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.arcsine, random.iterators.arcsine","random.streams.bernoulli":"\nrandom.streams.bernoulli( p[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Bernoulli distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.bernoulli( 0.5, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.bernoulli.factory( [p, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Bernoulli distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.bernoulli.factory( opts );\n\n\nrandom.streams.bernoulli.objectMode( p[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Bernoulli distribution.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.bernoulli.objectMode( 0.3, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.bernoulli, random.iterators.bernoulli\n","random.streams.bernoulli.factory":"\nrandom.streams.bernoulli.factory( [p, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Bernoulli distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.bernoulli.factory( opts );","random.streams.bernoulli.objectMode":"\nrandom.streams.bernoulli.objectMode( p[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Bernoulli distribution.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.bernoulli.objectMode( 0.3, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.bernoulli, random.iterators.bernoulli","random.streams.beta":"\nrandom.streams.beta( α, β[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    beta distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.beta( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.beta.factory( [α, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a beta distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        First shape parameter.\n\n    β: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.beta.factory( opts );\n\n\nrandom.streams.beta.objectMode( α, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a beta distribution.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.beta.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.beta, random.iterators.beta\n","random.streams.beta.factory":"\nrandom.streams.beta.factory( [α, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a beta distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        First shape parameter.\n\n    β: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.beta.factory( opts );","random.streams.beta.objectMode":"\nrandom.streams.beta.objectMode( α, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a beta distribution.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.beta.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.beta, random.iterators.beta","random.streams.betaprime":"\nrandom.streams.betaprime( α, β[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    beta prime distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.betaprime( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.betaprime.factory( [α, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a beta prime distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        First shape parameter.\n\n    β: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.betaprime.factory( opts );\n\n\nrandom.streams.betaprime.objectMode( α, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a beta prime distribution.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.betaprime.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.betaprime, random.iterators.betaprime\n","random.streams.betaprime.factory":"\nrandom.streams.betaprime.factory( [α, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a beta prime distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        First shape parameter.\n\n    β: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.betaprime.factory( opts );","random.streams.betaprime.objectMode":"\nrandom.streams.betaprime.objectMode( α, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a beta prime distribution.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.betaprime.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.betaprime, random.iterators.betaprime","random.streams.binomial":"\nrandom.streams.binomial( n, p[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    binomial distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.binomial( 20, 0.5, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.binomial.factory( [n, p, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a binomial distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    n: integer (optional)\n        Number of trials.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.binomial.factory( opts );\n\n\nrandom.streams.binomial.objectMode( n, p[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a binomial distribution.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.binomial.objectMode( 20, 0.5, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.binomial, random.iterators.binomial\n","random.streams.binomial.factory":"\nrandom.streams.binomial.factory( [n, p, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a binomial distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    n: integer (optional)\n        Number of trials.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.binomial.factory( opts );","random.streams.binomial.objectMode":"\nrandom.streams.binomial.objectMode( n, p[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a binomial distribution.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.binomial.objectMode( 20, 0.5, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.binomial, random.iterators.binomial","random.streams.boxMuller":"\nrandom.streams.boxMuller( [options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    standard normal distribution using the Box-Muller transform.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.boxMuller( opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.boxMuller.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a standard normal distribution using the Box-Muller\n    transform.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.boxMuller.factory( opts );\n\n\nrandom.streams.boxMuller.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a standard normal distribution using the Box-Muller transform.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.boxMuller.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.boxMuller, random.iterators.boxMuller, random.streams.improvedZiggurat, random.streams.randn\n","random.streams.boxMuller.factory":"\nrandom.streams.boxMuller.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a standard normal distribution using the Box-Muller\n    transform.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.boxMuller.factory( opts );","random.streams.boxMuller.objectMode":"\nrandom.streams.boxMuller.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a standard normal distribution using the Box-Muller transform.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.boxMuller.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.boxMuller, random.iterators.boxMuller, random.streams.improvedZiggurat, random.streams.randn","random.streams.cauchy":"\nrandom.streams.cauchy( x0, γ[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Cauchy distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    γ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.cauchy( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.cauchy.factory( [x0, γ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Cauchy distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    x0: number (optional)\n        Location parameter.\n\n    γ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.cauchy.factory( opts );\n\n\nrandom.streams.cauchy.objectMode( x0, γ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Cauchy distribution.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    γ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.cauchy.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.cauchy, random.iterators.cauchy\n","random.streams.cauchy.factory":"\nrandom.streams.cauchy.factory( [x0, γ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Cauchy distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    x0: number (optional)\n        Location parameter.\n\n    γ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.cauchy.factory( opts );","random.streams.cauchy.objectMode":"\nrandom.streams.cauchy.objectMode( x0, γ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Cauchy distribution.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    γ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.cauchy.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.cauchy, random.iterators.cauchy","random.streams.chi":"\nrandom.streams.chi( k[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    chi distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.chi( 3.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.chi.factory( [k, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a chi distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.chi.factory( opts );\n\n\nrandom.streams.chi.objectMode( k[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a chi distribution.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.chi.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.chi, random.iterators.chi\n","random.streams.chi.factory":"\nrandom.streams.chi.factory( [k, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a chi distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.chi.factory( opts );","random.streams.chi.objectMode":"\nrandom.streams.chi.objectMode( k[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a chi distribution.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.chi.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.chi, random.iterators.chi","random.streams.chisquare":"\nrandom.streams.chisquare( k[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    chi-square distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.chisquare( 3.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.chisquare.factory( [k, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a chi-square distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.chisquare.factory( opts );\n\n\nrandom.streams.chisquare.objectMode( k[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a chi-square distribution.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.chisquare.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.chisquare, random.iterators.chisquare\n","random.streams.chisquare.factory":"\nrandom.streams.chisquare.factory( [k, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a chi-square distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.chisquare.factory( opts );","random.streams.chisquare.objectMode":"\nrandom.streams.chisquare.objectMode( k[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a chi-square distribution.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.chisquare.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.chisquare, random.iterators.chisquare","random.streams.cosine":"\nrandom.streams.cosine( μ, s[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    raised cosine distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.cosine( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.cosine.factory( [μ, s, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a raised cosine distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.cosine.factory( opts );\n\n\nrandom.streams.cosine.objectMode( μ, s[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a raised cosine distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.cosine.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.cosine, random.iterators.cosine\n","random.streams.cosine.factory":"\nrandom.streams.cosine.factory( [μ, s, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a raised cosine distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.cosine.factory( opts );","random.streams.cosine.objectMode":"\nrandom.streams.cosine.objectMode( μ, s[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a raised cosine distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.cosine.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.cosine, random.iterators.cosine","random.streams.discreteUniform":"\nrandom.streams.discreteUniform( a, b[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    discrete uniform distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.discreteUniform( 2, 5, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.discreteUniform.factory( [a, b, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a discrete uniform distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    a: integer (optional)\n        Minimum support.\n\n    b: integer (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.discreteUniform.factory( opts );\n\n\nrandom.streams.discreteUniform.objectMode( a, b[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a discrete uniform distribution.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.discreteUniform.objectMode( 2, 5, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.discreteUniform, random.iterators.discreteUniform\n","random.streams.discreteUniform.factory":"\nrandom.streams.discreteUniform.factory( [a, b, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a discrete uniform distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    a: integer (optional)\n        Minimum support.\n\n    b: integer (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.discreteUniform.factory( opts );","random.streams.discreteUniform.objectMode":"\nrandom.streams.discreteUniform.objectMode( a, b[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a discrete uniform distribution.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.discreteUniform.objectMode( 2, 5, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.discreteUniform, random.iterators.discreteUniform","random.streams.erlang":"\nrandom.streams.erlang( k, λ[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from an\n    Erlang distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    k: integer\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.erlang( 2, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.erlang.factory( [k, λ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an Erlang distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Shape parameter.\n\n    λ: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.erlang.factory( opts );\n\n\nrandom.streams.erlang.objectMode( k, λ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an Erlang distribution.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.erlang.objectMode( 2, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.erlang, random.iterators.erlang\n","random.streams.erlang.factory":"\nrandom.streams.erlang.factory( [k, λ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an Erlang distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Shape parameter.\n\n    λ: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.erlang.factory( opts );","random.streams.erlang.objectMode":"\nrandom.streams.erlang.objectMode( k, λ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an Erlang distribution.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.erlang.objectMode( 2, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.erlang, random.iterators.erlang","random.streams.exponential":"\nrandom.streams.exponential( λ[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from an\n    exponential distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.exponential( 3.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.exponential.factory( [λ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an exponential distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    λ: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.exponential.factory( opts );\n\n\nrandom.streams.exponential.objectMode( λ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an exponential distribution.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.exponential.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.exponential, random.iterators.exponential\n","random.streams.exponential.factory":"\nrandom.streams.exponential.factory( [λ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an exponential distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    λ: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.exponential.factory( opts );","random.streams.exponential.objectMode":"\nrandom.streams.exponential.objectMode( λ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an exponential distribution.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.exponential.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.exponential, random.iterators.exponential","random.streams.f":"\nrandom.streams.f( d1, d2[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from an\n    F distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    d1: number\n        Degrees of freedom.\n\n    d2: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.f( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.f.factory( [d1, d2, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an F distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    d1: number (optional)\n        Degrees of freedom.\n\n    d2: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.f.factory( opts );\n\n\nrandom.streams.f.objectMode( d1, d2[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an F distribution.\n\n    Parameters\n    ----------\n    d1: number\n        Degrees of freedom.\n\n    d2: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.f.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.f, random.iterators.f\n","random.streams.f.factory":"\nrandom.streams.f.factory( [d1, d2, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an F distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    d1: number (optional)\n        Degrees of freedom.\n\n    d2: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.f.factory( opts );","random.streams.f.objectMode":"\nrandom.streams.f.objectMode( d1, d2[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an F distribution.\n\n    Parameters\n    ----------\n    d1: number\n        Degrees of freedom.\n\n    d2: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.f.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.f, random.iterators.f","random.streams.frechet":"\nrandom.streams.frechet( α, s, m[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Fréchet distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.frechet( 2.0, 5.0, 3.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.frechet.factory( [α, s, m,][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Fréchet distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    m: number (optional)\n        Location parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.frechet.factory( opts );\n\n\nrandom.streams.frechet.objectMode( α, s, m[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Fréchet distribution.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.frechet.objectMode( 2.0, 5.0, 3.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.frechet, random.iterators.frechet\n","random.streams.frechet.factory":"\nrandom.streams.frechet.factory( [α, s, m,][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Fréchet distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    m: number (optional)\n        Location parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.frechet.factory( opts );","random.streams.frechet.objectMode":"\nrandom.streams.frechet.objectMode( α, s, m[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Fréchet distribution.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.frechet.objectMode( 2.0, 5.0, 3.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.frechet, random.iterators.frechet","random.streams.gamma":"\nrandom.streams.gamma( α, β[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    gamma distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.gamma( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.gamma.factory( [α, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a gamma distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.gamma.factory( opts );\n\n\nrandom.streams.gamma.objectMode( α, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a gamma distribution.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.gamma.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.gamma, random.iterators.gamma\n","random.streams.gamma.factory":"\nrandom.streams.gamma.factory( [α, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a gamma distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.gamma.factory( opts );","random.streams.gamma.objectMode":"\nrandom.streams.gamma.objectMode( α, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a gamma distribution.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.gamma.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.gamma, random.iterators.gamma","random.streams.geometric":"\nrandom.streams.geometric( p[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    geometric distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.geometric( 0.5, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.geometric.factory( [p, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a geometric distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.geometric.factory( opts );\n\n\nrandom.streams.geometric.objectMode( p[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a geometric distribution.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.geometric.objectMode( 0.3, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.geometric, random.iterators.geometric\n","random.streams.geometric.factory":"\nrandom.streams.geometric.factory( [p, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a geometric distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.geometric.factory( opts );","random.streams.geometric.objectMode":"\nrandom.streams.geometric.objectMode( p[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a geometric distribution.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.geometric.objectMode( 0.3, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.geometric, random.iterators.geometric","random.streams.gumbel":"\nrandom.streams.gumbel( μ, β[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Gumbel distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.gumbel( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.gumbel.factory( [μ, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Gumbel distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.gumbel.factory( opts );\n\n\nrandom.streams.gumbel.objectMode( μ, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Gumbel distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.gumbel.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.gumbel, random.iterators.gumbel\n","random.streams.gumbel.factory":"\nrandom.streams.gumbel.factory( [μ, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Gumbel distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.gumbel.factory( opts );","random.streams.gumbel.objectMode":"\nrandom.streams.gumbel.objectMode( μ, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Gumbel distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.gumbel.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.gumbel, random.iterators.gumbel","random.streams.hypergeometric":"\nrandom.streams.hypergeometric( N, K, n[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    hypergeometric distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.hypergeometric( 5, 3, 2, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.hypergeometric.factory( [N, K, n,][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a hypergeometric distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    N: integer (optional)\n        Population size.\n\n    K: integer (optional)\n        Subpopulation size.\n\n    n: integer (optional)\n        Number of draws.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.hypergeometric.factory( opts );\n\n\nrandom.streams.hypergeometric.objectMode( N, K, n[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a hypergeometric distribution.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.hypergeometric.objectMode( 5, 3, 2, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.hypergeometric, random.iterators.hypergeometric\n","random.streams.hypergeometric.factory":"\nrandom.streams.hypergeometric.factory( [N, K, n,][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a hypergeometric distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    N: integer (optional)\n        Population size.\n\n    K: integer (optional)\n        Subpopulation size.\n\n    n: integer (optional)\n        Number of draws.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.hypergeometric.factory( opts );","random.streams.hypergeometric.objectMode":"\nrandom.streams.hypergeometric.objectMode( N, K, n[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a hypergeometric distribution.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.hypergeometric.objectMode( 5, 3, 2, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.hypergeometric, random.iterators.hypergeometric","random.streams.improvedZiggurat":"\nrandom.streams.improvedZiggurat( [options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    standard normal distribution using the Improved Ziggurat algorithm.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.improvedZiggurat( opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.improvedZiggurat.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a standard normal distribution using the Improved\n    Ziggurat algorithm.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.improvedZiggurat.factory( opts );\n\n\nrandom.streams.improvedZiggurat.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a standard normal distribution using the Improved Ziggurat\n    algorithm.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.improvedZiggurat.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.improvedZiggurat, random.iterators.improvedZiggurat, random.streams.boxMuller, random.streams.randn\n","random.streams.improvedZiggurat.factory":"\nrandom.streams.improvedZiggurat.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a standard normal distribution using the Improved\n    Ziggurat algorithm.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.improvedZiggurat.factory( opts );","random.streams.improvedZiggurat.objectMode":"\nrandom.streams.improvedZiggurat.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a standard normal distribution using the Improved Ziggurat\n    algorithm.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.improvedZiggurat.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.improvedZiggurat, random.iterators.improvedZiggurat, random.streams.boxMuller, random.streams.randn","random.streams.invgamma":"\nrandom.streams.invgamma( α, β[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from an\n    inverse gamma distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.invgamma( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.invgamma.factory( [α, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an inverse gamma distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.invgamma.factory( opts );\n\n\nrandom.streams.invgamma.objectMode( α, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an inverse gamma distribution.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.invgamma.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.invgamma, random.iterators.invgamma\n","random.streams.invgamma.factory":"\nrandom.streams.invgamma.factory( [α, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an inverse gamma distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.invgamma.factory( opts );","random.streams.invgamma.objectMode":"\nrandom.streams.invgamma.objectMode( α, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an inverse gamma distribution.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.invgamma.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.invgamma, random.iterators.invgamma","random.streams.kumaraswamy":"\nrandom.streams.kumaraswamy( a, b[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Kumaraswamy's double bounded distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.kumaraswamy( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.kumaraswamy.factory( [a, b, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Kumaraswamy's double bounded distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        First shape parameter.\n\n    b: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.kumaraswamy.factory( opts );\n\n\nrandom.streams.kumaraswamy.objectMode( a, b[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Kumaraswamy's double bounded distribution.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.kumaraswamy.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.kumaraswamy, random.iterators.kumaraswamy\n","random.streams.kumaraswamy.factory":"\nrandom.streams.kumaraswamy.factory( [a, b, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Kumaraswamy's double bounded distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        First shape parameter.\n\n    b: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.kumaraswamy.factory( opts );","random.streams.kumaraswamy.objectMode":"\nrandom.streams.kumaraswamy.objectMode( a, b[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Kumaraswamy's double bounded distribution.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.kumaraswamy.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.kumaraswamy, random.iterators.kumaraswamy","random.streams.laplace":"\nrandom.streams.laplace( μ, b[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Laplace (double exponential) distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    b: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.laplace( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.laplace.factory( [μ, b, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Laplace (double exponential) distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    b: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.laplace.factory( opts );\n\n\nrandom.streams.laplace.objectMode( μ, b[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Laplace (double exponential) distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    b: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.laplace.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.laplace, random.iterators.laplace\n","random.streams.laplace.factory":"\nrandom.streams.laplace.factory( [μ, b, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Laplace (double exponential) distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    b: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.laplace.factory( opts );","random.streams.laplace.objectMode":"\nrandom.streams.laplace.objectMode( μ, b[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Laplace (double exponential) distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    b: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.laplace.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.laplace, random.iterators.laplace","random.streams.levy":"\nrandom.streams.levy( μ, c[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Lévy distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    c: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.levy( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.levy.factory( [μ, c, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Lévy distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    c: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.levy.factory( opts );\n\n\nrandom.streams.levy.objectMode( μ, c[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Lévy distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    c: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.levy.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.levy, random.iterators.levy\n","random.streams.levy.factory":"\nrandom.streams.levy.factory( [μ, c, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Lévy distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    c: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.levy.factory( opts );","random.streams.levy.objectMode":"\nrandom.streams.levy.objectMode( μ, c[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Lévy distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    c: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.levy.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.levy, random.iterators.levy","random.streams.logistic":"\nrandom.streams.logistic( μ, s[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    logistic distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    s: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.logistic( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.logistic.factory( [μ, s, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a logistic distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.logistic.factory( opts );\n\n\nrandom.streams.logistic.objectMode( μ, s[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a logistic distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    s: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.logistic.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.logistic, random.iterators.logistic\n","random.streams.logistic.factory":"\nrandom.streams.logistic.factory( [μ, s, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a logistic distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.logistic.factory( opts );","random.streams.logistic.objectMode":"\nrandom.streams.logistic.objectMode( μ, s[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a logistic distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    s: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.logistic.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.logistic, random.iterators.logistic","random.streams.lognormal":"\nrandom.streams.lognormal( μ, σ[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    lognormal distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.lognormal( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.lognormal.factory( [μ, σ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a lognormal distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter.\n\n    σ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.lognormal.factory( opts );\n\n\nrandom.streams.lognormal.objectMode( μ, σ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a lognormal distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.lognormal.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.lognormal, random.iterators.lognormal\n","random.streams.lognormal.factory":"\nrandom.streams.lognormal.factory( [μ, σ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a lognormal distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter.\n\n    σ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.lognormal.factory( opts );","random.streams.lognormal.objectMode":"\nrandom.streams.lognormal.objectMode( μ, σ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a lognormal distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.lognormal.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.lognormal, random.iterators.lognormal","random.streams.minstd":"\nrandom.streams.minstd( [options] )\n    Returns a readable stream for generating pseudorandom numbers on the\n    interval `[1, 2147483646]`.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    The underlying pseudorandom number generator (PRNG) is a linear congruential\n    pseudorandom number generator (LCG) based on Park and Miller.\n\n    The generator has a period of approximately `2.1e9`.\n\n    An LCG is fast and uses little memory. On the other hand, because the\n    generator is a simple LCG, the generator has recognized shortcomings. By\n    today's PRNG standards, the generator's period is relatively short. More\n    importantly, the \"randomness quality\" of the generator's output is lacking.\n    These defects make the generator unsuitable, for example, in Monte Carlo\n    simulations and in cryptographic applications.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.seed: Int32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Int32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.minstd( opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.minstd.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers on the interval `[1, 2147483646]`.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.minstd.factory( opts );\n\n\nrandom.streams.minstd.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    on the interval `[1, 2147483646]`.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.seed: Int32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Int32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.minstd.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.minstd, random.iterators.minstd, random.streams.minstdShuffle, random.streams.mt19937, random.streams.randi, random.streams.randu\n","random.streams.minstd.factory":"\nrandom.streams.minstd.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers on the interval `[1, 2147483646]`.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.minstd.factory( opts );","random.streams.minstd.objectMode":"\nrandom.streams.minstd.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    on the interval `[1, 2147483646]`.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.seed: Int32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Int32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.minstd.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.minstd, random.iterators.minstd, random.streams.minstdShuffle, random.streams.mt19937, random.streams.randi, random.streams.randu","random.streams.minstdShuffle":"\nrandom.streams.minstdShuffle( [options] )\n    Returns a readable stream for generating pseudorandom numbers on the\n    interval `[1, 2147483646]`.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    The underlying pseudorandom number generator (PRNG) is a linear congruential\n    pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n    Durham algorithm. The shuffle step considerably strengthens the \"randomness\n    quality\" of a simple LCG's output.\n\n    The generator has a period of approximately `2.1e9`.\n\n    An LCG is fast and uses little memory. On the other hand, because the\n    generator is a simple LCG, the generator has recognized shortcomings. By\n    today's PRNG standards, the generator's period is relatively short. In\n    general, this generator is unsuitable for Monte Carlo simulations and\n    cryptographic applications.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.seed: Int32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Int32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.minstdShuffle( opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.minstdShuffle.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers on the interval `[1, 2147483646]`.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.minstdShuffle.factory( opts );\n\n\nrandom.streams.minstdShuffle.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    on the interval `[1, 2147483646]`.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.seed: Int32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Int32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.minstdShuffle.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstd, random.streams.mt19937, random.streams.randi, random.streams.randu\n","random.streams.minstdShuffle.factory":"\nrandom.streams.minstdShuffle.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers on the interval `[1, 2147483646]`.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.minstdShuffle.factory( opts );","random.streams.minstdShuffle.objectMode":"\nrandom.streams.minstdShuffle.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    on the interval `[1, 2147483646]`.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.seed: Int32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Int32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.minstdShuffle.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstd, random.streams.mt19937, random.streams.randi, random.streams.randu","random.streams.mt19937":"\nrandom.streams.mt19937( [options] )\n    Returns a readable stream for generating pseudorandom numbers on the\n    interval `[1, 4294967295]`.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    The underlying pseudorandom number generator (PRNG) is a 32-bit Mersenne\n    Twister pseudorandom number generator.\n\n    The PRNG is *not* a cryptographically secure PRNG.\n\n    The PRNG has a period of 2^19937 - 1.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.mt19937( opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.mt19937.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers on the interval `[1, 4294967295]`.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.mt19937.factory( opts );\n\n\nrandom.streams.mt19937.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    on the interval `[1, 4294967295]`.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.mt19937.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.mt19937, random.iterators.mt19937, random.streams.minstd, random.streams.minstdShuffle, random.streams.randi, random.streams.randu\n","random.streams.mt19937.factory":"\nrandom.streams.mt19937.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers on the interval `[1, 4294967295]`.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.mt19937.factory( opts );","random.streams.mt19937.objectMode":"\nrandom.streams.mt19937.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    on the interval `[1, 4294967295]`.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.mt19937.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.mt19937, random.iterators.mt19937, random.streams.minstd, random.streams.minstdShuffle, random.streams.randi, random.streams.randu","random.streams.negativeBinomial":"\nrandom.streams.negativeBinomial( r, p[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    negative binomial distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.negativeBinomial( 20.0, 0.5, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.negativeBinomial.factory( [r, p, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a negative binomial distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    r: number (optional)\n        Number of successes until experiment is stopped.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.negativeBinomial.factory( opts );\n\n\nrandom.streams.negativeBinomial.objectMode( r, p[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a negative binomial distribution.\n\n    Parameters\n    ----------\n    r: integer\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.negativeBinomial.objectMode( 20.0, 0.5, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.negativeBinomial, random.iterators.negativeBinomial\n","random.streams.negativeBinomial.factory":"\nrandom.streams.negativeBinomial.factory( [r, p, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a negative binomial distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    r: number (optional)\n        Number of successes until experiment is stopped.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.negativeBinomial.factory( opts );","random.streams.negativeBinomial.objectMode":"\nrandom.streams.negativeBinomial.objectMode( r, p[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a negative binomial distribution.\n\n    Parameters\n    ----------\n    r: integer\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.negativeBinomial.objectMode( 20.0, 0.5, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.negativeBinomial, random.iterators.negativeBinomial","random.streams.normal":"\nrandom.streams.normal( μ, σ[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    normal distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    σ: number\n        Standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.normal( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.normal.factory( [μ, σ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a normal distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    σ: number (optional)\n        Standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.normal.factory( opts );\n\n\nrandom.streams.normal.objectMode( μ, σ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a normal distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    σ: number\n        Standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.normal.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.normal, random.iterators.normal\n","random.streams.normal.factory":"\nrandom.streams.normal.factory( [μ, σ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a normal distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    σ: number (optional)\n        Standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.normal.factory( opts );","random.streams.normal.objectMode":"\nrandom.streams.normal.objectMode( μ, σ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a normal distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    σ: number\n        Standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.normal.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.normal, random.iterators.normal","random.streams.pareto1":"\nrandom.streams.pareto1( α, β[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Pareto (Type I) distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.pareto1( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.pareto1.factory( [α, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Pareto (Type I) distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.pareto1.factory( opts );\n\n\nrandom.streams.pareto1.objectMode( α, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Pareto (Type I) distribution.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.pareto1.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.pareto1, random.iterators.pareto1\n","random.streams.pareto1.factory":"\nrandom.streams.pareto1.factory( [α, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Pareto (Type I) distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.pareto1.factory( opts );","random.streams.pareto1.objectMode":"\nrandom.streams.pareto1.objectMode( α, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Pareto (Type I) distribution.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.pareto1.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.pareto1, random.iterators.pareto1","random.streams.poisson":"\nrandom.streams.poisson( λ[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Poisson distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    λ: number\n        Mean.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.poisson( 3.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.poisson.factory( [λ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Poisson distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    λ: number (optional)\n        Mean.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.poisson.factory( opts );\n\n\nrandom.streams.poisson.objectMode( λ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Poisson distribution.\n\n    Parameters\n    ----------\n    λ: number\n        Mean.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.poisson.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.poisson, random.iterators.poisson\n","random.streams.poisson.factory":"\nrandom.streams.poisson.factory( [λ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Poisson distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    λ: number (optional)\n        Mean.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.poisson.factory( opts );","random.streams.poisson.objectMode":"\nrandom.streams.poisson.objectMode( λ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Poisson distribution.\n\n    Parameters\n    ----------\n    λ: number\n        Mean.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.poisson.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.poisson, random.iterators.poisson","random.streams.randi":"\nrandom.streams.randi( [options] )\n    Returns a readable stream for generating pseudorandom numbers having integer\n    values.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    The default underlying pseudorandom number generator (PRNG) *may* change in\n    the future. If exact reproducibility is required, either explicitly specify\n    a PRNG via the `name` option or use an underlying PRNG directly.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: any\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer\n        Length of generator seed.\n\n    stream.state: any\n        Generator state.\n\n    stream.stateLength: integer\n        Length of generator state.\n\n    stream.byteLength: integer\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.randi( opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.randi.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers having integer values.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.randi.factory( opts );\n\n\nrandom.streams.randi.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    having integer values.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: any\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer\n        Length of generator seed.\n\n    stream.state: any\n        Generator state.\n\n    stream.stateLength: integer\n        Length of generator state.\n\n    stream.byteLength: integer\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.randi.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.randi, random.iterators.randi, random.streams.randu\n","random.streams.randi.factory":"\nrandom.streams.randi.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers having integer values.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.randi.factory( opts );","random.streams.randi.objectMode":"\nrandom.streams.randi.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    having integer values.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: any\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer\n        Length of generator seed.\n\n    stream.state: any\n        Generator state.\n\n    stream.stateLength: integer\n        Length of generator state.\n\n    stream.byteLength: integer\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.randi.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.randi, random.iterators.randi, random.streams.randu","random.streams.randn":"\nrandom.streams.randn( [options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    standard normal distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    The default underlying pseudorandom number generator (PRNG) *may* change in\n    the future. If exact reproducibility is required, either explicitly specify\n    a PRNG via the `name` option or use an underlying PRNG directly.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - improved-ziggurat: improved ziggurat method.\n        - box-muller: Box-Muller transform.\n\n        Default: 'improved-ziggurat'.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.randn( opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.randn.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a standard normal distribution.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - improved-ziggurat: improved ziggurat method.\n        - box-muller: Box-Muller transform.\n\n        Default: 'improved-ziggurat'.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.randn.factory( opts );\n\n\nrandom.streams.randn.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a standard normal distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - improved-ziggurat: improved ziggurat method.\n        - box-muller: Box-Muller transform.\n\n        Default: 'improved-ziggurat'.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.randn.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.randn, random.iterators.randn, random.streams.boxMuller, random.streams.improvedZiggurat\n","random.streams.randn.factory":"\nrandom.streams.randn.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a standard normal distribution.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - improved-ziggurat: improved ziggurat method.\n        - box-muller: Box-Muller transform.\n\n        Default: 'improved-ziggurat'.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.randn.factory( opts );","random.streams.randn.objectMode":"\nrandom.streams.randn.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a standard normal distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - improved-ziggurat: improved ziggurat method.\n        - box-muller: Box-Muller transform.\n\n        Default: 'improved-ziggurat'.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.randn.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.randn, random.iterators.randn, random.streams.boxMuller, random.streams.improvedZiggurat","random.streams.randu":"\nrandom.streams.randu( [options] )\n    Returns a readable stream for generating uniformly distributed pseudorandom\n    numbers between 0 and 1.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    The default underlying pseudorandom number generator (PRNG) *may* change in\n    the future. If exact reproducibility is required, either explicitly specify\n    a PRNG via the `name` option or use an underlying PRNG directly.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: any\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer\n        Length of generator seed.\n\n    stream.state: any\n        Generator state.\n\n    stream.stateLength: integer\n        Length of generator state.\n\n    stream.byteLength: integer\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.randu( opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.randu.factory( [options] )\n    Returns a function for creating readable streams which generate uniformly\n    distributed pseudorandom numbers between 0 and 1.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.randu.factory( opts );\n\n\nrandom.streams.randu.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating uniformly distributed\n    pseudorandom numbers between 0 and 1.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: any\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer\n        Length of generator seed.\n\n    stream.state: any\n        Generator state.\n\n    stream.stateLength: integer\n        Length of generator state.\n\n    stream.byteLength: integer\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.randu.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.randu, random.iterators.randu, random.streams.randi\n","random.streams.randu.factory":"\nrandom.streams.randu.factory( [options] )\n    Returns a function for creating readable streams which generate uniformly\n    distributed pseudorandom numbers between 0 and 1.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.randu.factory( opts );","random.streams.randu.objectMode":"\nrandom.streams.randu.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating uniformly distributed\n    pseudorandom numbers between 0 and 1.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: any\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer\n        Length of generator seed.\n\n    stream.state: any\n        Generator state.\n\n    stream.stateLength: integer\n        Length of generator state.\n\n    stream.byteLength: integer\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.randu.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.randu, random.iterators.randu, random.streams.randi","random.streams.rayleigh":"\nrandom.streams.rayleigh( σ[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Rayleigh distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.rayleigh( 3.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.rayleigh.factory( [σ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Rayleigh distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    σ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.rayleigh.factory( opts );\n\n\nrandom.streams.rayleigh.objectMode( σ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Rayleigh distribution.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.rayleigh.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.rayleigh, random.iterators.rayleigh\n","random.streams.rayleigh.factory":"\nrandom.streams.rayleigh.factory( [σ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Rayleigh distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    σ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.rayleigh.factory( opts );","random.streams.rayleigh.objectMode":"\nrandom.streams.rayleigh.objectMode( σ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Rayleigh distribution.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.rayleigh.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.rayleigh, random.iterators.rayleigh","random.streams.t":"\nrandom.streams.t( v[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Student's t distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.t( 3.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.t.factory( [v, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Student's t distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    v: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.t.factory( opts );\n\n\nrandom.streams.t.objectMode( v[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Student's t distribution.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.t.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.t, random.iterators.t\n","random.streams.t.factory":"\nrandom.streams.t.factory( [v, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Student's t distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    v: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.t.factory( opts );","random.streams.t.objectMode":"\nrandom.streams.t.objectMode( v[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Student's t distribution.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.t.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.t, random.iterators.t","random.streams.triangular":"\nrandom.streams.triangular( a, b, c[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    triangular distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.triangular( 2.0, 5.0, 4.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.triangular.factory( [a, b, c, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a triangular distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    c: number (optional)\n        Mode.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.triangular.factory( opts );\n\n\nrandom.streams.triangular.objectMode( a, b, c[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a triangular distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.triangular.objectMode( 2.0, 5.0, 4.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.triangular, random.iterators.triangular\n","random.streams.triangular.factory":"\nrandom.streams.triangular.factory( [a, b, c, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a triangular distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    c: number (optional)\n        Mode.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.triangular.factory( opts );","random.streams.triangular.objectMode":"\nrandom.streams.triangular.objectMode( a, b, c[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a triangular distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.triangular.objectMode( 2.0, 5.0, 4.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.triangular, random.iterators.triangular","random.streams.uniform":"\nrandom.streams.uniform( a, b[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    uniform distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.uniform( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.uniform.factory( [a, b, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a uniform distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.uniform.factory( opts );\n\n\nrandom.streams.uniform.objectMode( a, b[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a uniform distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.uniform.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.uniform, random.iterators.uniform\n","random.streams.uniform.factory":"\nrandom.streams.uniform.factory( [a, b, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a uniform distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.uniform.factory( opts );","random.streams.uniform.objectMode":"\nrandom.streams.uniform.objectMode( a, b[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a uniform distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.uniform.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.uniform, random.iterators.uniform","random.streams.weibull":"\nrandom.streams.weibull( k, λ[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Weibull distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    k: number\n        Scale parameter.\n\n    λ: number\n        Shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.weibull( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.weibull.factory( [k, λ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Weibull distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Scale parameter.\n\n    λ: number (optional)\n        Shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.weibull.factory( opts );\n\n\nrandom.streams.weibull.objectMode( k, λ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Weibull distribution.\n\n    Parameters\n    ----------\n    k: number\n        Scale parameter.\n\n    λ: number\n        Shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.weibull.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.weibull, random.iterators.weibull\n","random.streams.weibull.factory":"\nrandom.streams.weibull.factory( [k, λ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Weibull distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Scale parameter.\n\n    λ: number (optional)\n        Shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.weibull.factory( opts );","random.streams.weibull.objectMode":"\nrandom.streams.weibull.objectMode( k, λ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Weibull distribution.\n\n    Parameters\n    ----------\n    k: number\n        Scale parameter.\n\n    λ: number\n        Shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.weibull.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.weibull, random.iterators.weibull","random.strided.arcsine":"\nrandom.strided.arcsine( N, a, sa, b, sb, out, so[, options] )\n    Fills a strided array with pseudorandom numbers drawn from an arcsine\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    a: ArrayLikeObject\n        Minimum support.\n\n    sa: integer\n        Index increment for `a`.\n\n    b: ArrayLikeObject\n        Maximum support.\n\n    sb: integer\n        Index increment for `b`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 0.0, 1.0, 5 );\n    > var b = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.arcsine( out.length, a, 1, b, 1, out, 1 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 0.0, 1.0, 6 );\n    > b = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.arcsine( 3, a, -2, b, 1, out, 1 )\n    [...]\n\n\nrandom.strided.arcsine.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from an arcsine\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    a: ArrayLikeObject\n        Minimum support.\n\n    sa: integer\n        Index increment for `a`.\n\n    oa: integer\n        Starting index for `a`.\n\n    b: ArrayLikeObject\n        Maximum support.\n\n    sb: integer\n        Index increment for `b`.\n\n    ob: integer\n        Starting index for `b`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 0.0, 1.0, 5 );\n    > var b = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.arcsine.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 0.0, 1.0, 6 );\n    > b = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.arcsine.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.arcsine, random.array.arcsine\n","random.strided.arcsine.ndarray":"\nrandom.strided.arcsine.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from an arcsine\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    a: ArrayLikeObject\n        Minimum support.\n\n    sa: integer\n        Index increment for `a`.\n\n    oa: integer\n        Starting index for `a`.\n\n    b: ArrayLikeObject\n        Maximum support.\n\n    sb: integer\n        Index increment for `b`.\n\n    ob: integer\n        Starting index for `b`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 0.0, 1.0, 5 );\n    > var b = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.arcsine.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 0.0, 1.0, 6 );\n    > b = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.arcsine.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.arcsine, random.array.arcsine","random.strided.bernoulli":"\nrandom.strided.bernoulli( N, p, sp, out, so )\n    Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    p: ArrayLikeObject\n        Success probability.\n\n    sp: integer\n        Index increment for `p`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.bernoulli.ndarray( N, p, sp, op, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    p: ArrayLikeObject\n        Success probability.\n\n    sp: integer\n        Index increment for `p`.\n\n    op: integer\n        Starting index for `p`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.bernoulli.ndarray( out.length, [ 0.5 ], 0, 0, out, 1, 0 )\n    [...]\n\n\nrandom.strided.bernoulli.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Bernoulli distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.bernoulli.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 0.5 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.bernoulli.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.bernoulli.PRNG;\n\n\nrandom.strided.bernoulli.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.bernoulli.seed;\n\n\nrandom.strided.bernoulli.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.bernoulli.seedLength;\n\n\nrandom.strided.bernoulli.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.bernoulli.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.bernoulli.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.bernoulli.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.bernoulli.stateLength;\n\n\nrandom.strided.bernoulli.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.bernoulli.byteLength;\n\n    See Also\n    --------\n    base.random.bernoulli, random.array.bernoulli\n","random.strided.bernoulli.ndarray":"\nrandom.strided.bernoulli.ndarray( N, p, sp, op, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    p: ArrayLikeObject\n        Success probability.\n\n    sp: integer\n        Index increment for `p`.\n\n    op: integer\n        Starting index for `p`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.bernoulli.ndarray( out.length, [ 0.5 ], 0, 0, out, 1, 0 )\n    [...]","random.strided.bernoulli.factory":"\nrandom.strided.bernoulli.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Bernoulli distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.bernoulli.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 0.5 ], 0, out, 1 )\n    [...]","random.strided.bernoulli.PRNG":"\nrandom.strided.bernoulli.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.bernoulli.PRNG;","random.strided.bernoulli.seed":"\nrandom.strided.bernoulli.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.bernoulli.seed;","random.strided.bernoulli.seedLength":"\nrandom.strided.bernoulli.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.bernoulli.seedLength;","random.strided.bernoulli.state":"\nrandom.strided.bernoulli.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.bernoulli.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.bernoulli.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n    [...]","random.strided.bernoulli.stateLength":"\nrandom.strided.bernoulli.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.bernoulli.stateLength;","random.strided.bernoulli.byteLength":"\nrandom.strided.bernoulli.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.bernoulli.byteLength;\n\n    See Also\n    --------\n    base.random.bernoulli, random.array.bernoulli","random.strided.beta":"\nrandom.strided.beta( N, alpha, sa, beta, sb, out, so[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a beta\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        First shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    beta: ArrayLikeObject\n        Second shape parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.beta( out.length, a, 1, b, 1, out, 1 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.beta( 3, a, -2, b, 1, out, 1 )\n    [...]\n\n\nrandom.strided.beta.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a beta\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        First shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    oa: integer\n        Starting index for `alpha`.\n\n    beta: ArrayLikeObject\n        Second shape parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    ob: integer\n        Starting index for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.beta.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.beta.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.beta, random.array.beta\n","random.strided.beta.ndarray":"\nrandom.strided.beta.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a beta\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        First shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    oa: integer\n        Starting index for `alpha`.\n\n    beta: ArrayLikeObject\n        Second shape parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    ob: integer\n        Starting index for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.beta.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.beta.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.beta, random.array.beta","random.strided.betaprime":"\nrandom.strided.betaprime( N, alpha, sa, beta, sb, out, so[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a beta prime\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        First shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    beta: ArrayLikeObject\n        Second shape parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.betaprime( out.length, a, 1, b, 1, out, 1 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.betaprime( 3, a, -2, b, 1, out, 1 )\n    [...]\n\n\nrandom.strided.betaprime.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a beta prime\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        First shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    oa: integer\n        Starting index for `alpha`.\n\n    beta: ArrayLikeObject\n        Second shape parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    ob: integer\n        Starting index for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.betaprime.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.betaprime.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.betaprime, random.array.betaprime\n","random.strided.betaprime.ndarray":"\nrandom.strided.betaprime.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a beta prime\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        First shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    oa: integer\n        Starting index for `alpha`.\n\n    beta: ArrayLikeObject\n        Second shape parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    ob: integer\n        Starting index for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.betaprime.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.betaprime.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.betaprime, random.array.betaprime","random.strided.chi":"\nrandom.strided.chi( N, k, sk, out, so )\n    Fills a strided array with pseudorandom numbers drawn from a chi\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    k: ArrayLikeObject\n        Degrees of freedom.\n\n    sk: integer\n        Index increment for `k`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.chi.ndarray( N, k, sk, ok, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a chi\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    k: ArrayLikeObject\n        Degrees of freedom.\n\n    sk: integer\n        Index increment for `k`.\n\n    ok: integer\n        Starting index for `k`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.chi.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]\n\n\nrandom.strided.chi.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a chi distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.chi.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.chi.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.chi.PRNG;\n\n\nrandom.strided.chi.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.chi.seed;\n\n\nrandom.strided.chi.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.chi.seedLength;\n\n\nrandom.strided.chi.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.chi.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.chi.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.chi.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.chi.stateLength;\n\n\nrandom.strided.chi.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.chi.byteLength;\n\n    See Also\n    --------\n    base.random.chi, random.array.chi\n","random.strided.chi.ndarray":"\nrandom.strided.chi.ndarray( N, k, sk, ok, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a chi\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    k: ArrayLikeObject\n        Degrees of freedom.\n\n    sk: integer\n        Index increment for `k`.\n\n    ok: integer\n        Starting index for `k`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.chi.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]","random.strided.chi.factory":"\nrandom.strided.chi.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a chi distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.chi.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.chi.PRNG":"\nrandom.strided.chi.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.chi.PRNG;","random.strided.chi.seed":"\nrandom.strided.chi.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.chi.seed;","random.strided.chi.seedLength":"\nrandom.strided.chi.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.chi.seedLength;","random.strided.chi.state":"\nrandom.strided.chi.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.chi.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.chi.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.chi.stateLength":"\nrandom.strided.chi.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.chi.stateLength;","random.strided.chi.byteLength":"\nrandom.strided.chi.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.chi.byteLength;\n\n    See Also\n    --------\n    base.random.chi, random.array.chi","random.strided.chisquare":"\nrandom.strided.chisquare( N, k, sk, out, so )\n    Fills a strided array with pseudorandom numbers drawn from a chi-square\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    k: ArrayLikeObject\n        Degrees of freedom.\n\n    sk: integer\n        Index increment for `k`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.chisquare.ndarray( N, k, sk, ok, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a chi-square\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    k: ArrayLikeObject\n        Degrees of freedom.\n\n    sk: integer\n        Index increment for `k`.\n\n    ok: integer\n        Starting index for `k`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.chisquare.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]\n\n\nrandom.strided.chisquare.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a chi-square distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.chisquare.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.chisquare.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.chisquare.PRNG;\n\n\nrandom.strided.chisquare.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.chisquare.seed;\n\n\nrandom.strided.chisquare.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.chisquare.seedLength;\n\n\nrandom.strided.chisquare.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.chisquare.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.chisquare.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.chisquare.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.chisquare.stateLength;\n\n\nrandom.strided.chisquare.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.chisquare.byteLength;\n\n    See Also\n    --------\n    base.random.chisquare, random.array.chisquare\n","random.strided.chisquare.ndarray":"\nrandom.strided.chisquare.ndarray( N, k, sk, ok, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a chi-square\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    k: ArrayLikeObject\n        Degrees of freedom.\n\n    sk: integer\n        Index increment for `k`.\n\n    ok: integer\n        Starting index for `k`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.chisquare.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]","random.strided.chisquare.factory":"\nrandom.strided.chisquare.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a chi-square distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.chisquare.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.chisquare.PRNG":"\nrandom.strided.chisquare.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.chisquare.PRNG;","random.strided.chisquare.seed":"\nrandom.strided.chisquare.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.chisquare.seed;","random.strided.chisquare.seedLength":"\nrandom.strided.chisquare.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.chisquare.seedLength;","random.strided.chisquare.state":"\nrandom.strided.chisquare.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.chisquare.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.chisquare.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.chisquare.stateLength":"\nrandom.strided.chisquare.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.chisquare.stateLength;","random.strided.chisquare.byteLength":"\nrandom.strided.chisquare.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.chisquare.byteLength;\n\n    See Also\n    --------\n    base.random.chisquare, random.array.chisquare","random.strided.cosine":"\nrandom.strided.cosine( N, mu, sm, s, ss, out, so[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a cosine\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mu: ArrayLikeObject\n        Mean.\n\n    sm: integer\n        Index increment for `mu`.\n\n    s: ArrayLikeObject\n        Scale parameter.\n\n    ss: integer\n        Index increment for `s`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var mu = linspace( 0.0, 1.0, 5 );\n    > var s = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.cosine( out.length, mu, 1, s, 1, out, 1 )\n    [...]\n\n    // Advanced indexing:\n    > mu = linspace( 0.0, 1.0, 6 );\n    > s = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.cosine( 3, mu, -2, s, 1, out, 1 )\n    [...]\n\n\nrandom.strided.cosine.ndarray( N, mu, sm, om, s, ss, os, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a cosine\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mu: ArrayLikeObject\n        Mean.\n\n    sm: integer\n        Index increment for `mu`.\n\n    om: integer\n        Starting index for `mu`.\n\n    s: ArrayLikeObject\n        Scale parameter.\n\n    ss: integer\n        Index increment for `s`.\n\n    os: integer\n        Starting index for `s`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var mu = linspace( 0.0, 1.0, 5 );\n    > var s = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.cosine.ndarray( out.length, mu, 1, 0, s, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > mu = linspace( 0.0, 1.0, 6 );\n    > s = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.cosine.ndarray( 3, mu, 2, 1, s, -1, s.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.cosine, random.array.cosine\n","random.strided.cosine.ndarray":"\nrandom.strided.cosine.ndarray( N, mu, sm, om, s, ss, os, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a cosine\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mu: ArrayLikeObject\n        Mean.\n\n    sm: integer\n        Index increment for `mu`.\n\n    om: integer\n        Starting index for `mu`.\n\n    s: ArrayLikeObject\n        Scale parameter.\n\n    ss: integer\n        Index increment for `s`.\n\n    os: integer\n        Starting index for `s`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var mu = linspace( 0.0, 1.0, 5 );\n    > var s = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.cosine.ndarray( out.length, mu, 1, 0, s, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > mu = linspace( 0.0, 1.0, 6 );\n    > s = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.cosine.ndarray( 3, mu, 2, 1, s, -1, s.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.cosine, random.array.cosine","random.strided.discreteUniform":"\nrandom.strided.discreteUniform( N, a, sa, b, sb, out, so[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a discrete\n    uniform distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    a: ArrayLikeObject\n        Minimum support.\n\n    sa: integer\n        Index increment for `a`.\n\n    b: ArrayLikeObject\n        Maximum support.\n\n    sb: integer\n        Index increment for `b`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = [ -10, -5, 0, 5, 10 ];\n    > var b = [ 20, 20, 20, 20, 20 ];\n    > var out = azeros( 5, 'generic' );\n    > random.strided.discreteUniform( out.length, a, 1, b, 1, out, 1 )\n    [...]\n\n    // Advanced indexing:\n    > a = [ -10, -5, 0, 5, 10, 15 ];\n    > b = [ 20, 20, 20, 20, 20, 20 ];\n    > out = azeros( 6, 'generic' );\n    > random.strided.discreteUniform( 3, a, -2, b, 1, out, 1 )\n    [...]\n\n\nrandom.strided.discreteUniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a discrete\n    uniform distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    a: ArrayLikeObject\n        Minimum support.\n\n    sa: integer\n        Index increment for `a`.\n\n    oa: integer\n        Starting index for `a`.\n\n    b: ArrayLikeObject\n        Maximum support.\n\n    sb: integer\n        Index increment for `b`.\n\n    ob: integer\n        Starting index for `b`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = [ -10, -5, 0, 5, 10 ];\n    > var b = [ 20, 20, 20, 20, 20 ];\n    > var out = azeros( 5, 'generic' );\n    > random.strided.discreteUniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = [ -10, -5, 0, 5, 10, 15 ];\n    > b = [ 20, 20, 20, 20, 20, 20 ];\n    > out = azeros( 6, 'generic' );\n    > random.strided.discreteUniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.discreteUniform, random.array.discreteUniform, random.strided.uniform\n","random.strided.discreteUniform.ndarray":"\nrandom.strided.discreteUniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a discrete\n    uniform distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    a: ArrayLikeObject\n        Minimum support.\n\n    sa: integer\n        Index increment for `a`.\n\n    oa: integer\n        Starting index for `a`.\n\n    b: ArrayLikeObject\n        Maximum support.\n\n    sb: integer\n        Index increment for `b`.\n\n    ob: integer\n        Starting index for `b`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = [ -10, -5, 0, 5, 10 ];\n    > var b = [ 20, 20, 20, 20, 20 ];\n    > var out = azeros( 5, 'generic' );\n    > random.strided.discreteUniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = [ -10, -5, 0, 5, 10, 15 ];\n    > b = [ 20, 20, 20, 20, 20, 20 ];\n    > out = azeros( 6, 'generic' );\n    > random.strided.discreteUniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.discreteUniform, random.array.discreteUniform, random.strided.uniform","random.strided.exponential":"\nrandom.strided.exponential( N, lambda, sl, out, so )\n    Fills a strided array with pseudorandom numbers drawn from an exponential\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    lambda: ArrayLikeObject\n        Rate parameter.\n\n    sl: integer\n        Index increment for `lambda`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.exponential.ndarray( N, lambda, sl, ol, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from an exponential\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    lambda: ArrayLikeObject\n        Rate parameter.\n\n    sl: integer\n        Index increment for `lambda`.\n\n    ol: integer\n        Starting index for `lambda`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.exponential.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]\n\n\nrandom.strided.exponential.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from an exponential distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.exponential.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.exponential.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.exponential.PRNG;\n\n\nrandom.strided.exponential.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.exponential.seed;\n\n\nrandom.strided.exponential.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.exponential.seedLength;\n\n\nrandom.strided.exponential.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.exponential.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.exponential.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.exponential.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.exponential.stateLength;\n\n\nrandom.strided.exponential.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.exponential.byteLength;\n\n    See Also\n    --------\n    base.random.exponential, random.array.exponential\n","random.strided.exponential.ndarray":"\nrandom.strided.exponential.ndarray( N, lambda, sl, ol, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from an exponential\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    lambda: ArrayLikeObject\n        Rate parameter.\n\n    sl: integer\n        Index increment for `lambda`.\n\n    ol: integer\n        Starting index for `lambda`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.exponential.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]","random.strided.exponential.factory":"\nrandom.strided.exponential.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from an exponential distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.exponential.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.exponential.PRNG":"\nrandom.strided.exponential.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.exponential.PRNG;","random.strided.exponential.seed":"\nrandom.strided.exponential.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.exponential.seed;","random.strided.exponential.seedLength":"\nrandom.strided.exponential.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.exponential.seedLength;","random.strided.exponential.state":"\nrandom.strided.exponential.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.exponential.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.exponential.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.exponential.stateLength":"\nrandom.strided.exponential.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.exponential.stateLength;","random.strided.exponential.byteLength":"\nrandom.strided.exponential.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.exponential.byteLength;\n\n    See Also\n    --------\n    base.random.exponential, random.array.exponential","random.strided.gamma":"\nrandom.strided.gamma( N, alpha, sa, beta, sb, out, so[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a gamma\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        Shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    beta: ArrayLikeObject\n        Rate parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.gamma( out.length, a, 1, b, 1, out, 1 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.gamma( 3, a, -2, b, 1, out, 1 )\n    [...]\n\n\nrandom.strided.gamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a gamma\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        Shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    oa: integer\n        Starting index for `alpha`.\n\n    beta: ArrayLikeObject\n        Rate parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    ob: integer\n        Starting index for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.gamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.gamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.gamma, random.array.gamma\n","random.strided.gamma.ndarray":"\nrandom.strided.gamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a gamma\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        Shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    oa: integer\n        Starting index for `alpha`.\n\n    beta: ArrayLikeObject\n        Rate parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    ob: integer\n        Starting index for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.gamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.gamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.gamma, random.array.gamma","random.strided.geometric":"\nrandom.strided.geometric( N, p, sp, out, so )\n    Fills a strided array with pseudorandom numbers drawn from a geometric\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    p: ArrayLikeObject\n        Success probability.\n\n    sp: integer\n        Index increment for `p`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.geometric.ndarray( N, p, sp, op, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a geometric\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    p: ArrayLikeObject\n        Success probability.\n\n    sp: integer\n        Index increment for `p`.\n\n    op: integer\n        Starting index for `p`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.geometric.ndarray( out.length, [ 0.01 ], 0, 0, out, 1, 0 )\n    [...]\n\n\nrandom.strided.geometric.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a geometric distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.geometric.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 0.01 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.geometric.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.geometric.PRNG;\n\n\nrandom.strided.geometric.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.geometric.seed;\n\n\nrandom.strided.geometric.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.geometric.seedLength;\n\n\nrandom.strided.geometric.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.geometric.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.geometric.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.geometric.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.geometric.stateLength;\n\n\nrandom.strided.geometric.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.geometric.byteLength;\n\n    See Also\n    --------\n    base.random.geometric, random.array.geometric\n","random.strided.geometric.ndarray":"\nrandom.strided.geometric.ndarray( N, p, sp, op, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a geometric\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    p: ArrayLikeObject\n        Success probability.\n\n    sp: integer\n        Index increment for `p`.\n\n    op: integer\n        Starting index for `p`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.geometric.ndarray( out.length, [ 0.01 ], 0, 0, out, 1, 0 )\n    [...]","random.strided.geometric.factory":"\nrandom.strided.geometric.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a geometric distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.geometric.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 0.01 ], 0, out, 1 )\n    [...]","random.strided.geometric.PRNG":"\nrandom.strided.geometric.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.geometric.PRNG;","random.strided.geometric.seed":"\nrandom.strided.geometric.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.geometric.seed;","random.strided.geometric.seedLength":"\nrandom.strided.geometric.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.geometric.seedLength;","random.strided.geometric.state":"\nrandom.strided.geometric.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.geometric.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.geometric.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n    [...]","random.strided.geometric.stateLength":"\nrandom.strided.geometric.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.geometric.stateLength;","random.strided.geometric.byteLength":"\nrandom.strided.geometric.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.geometric.byteLength;\n\n    See Also\n    --------\n    base.random.geometric, random.array.geometric","random.strided.invgamma":"\nrandom.strided.invgamma( N, alpha, sa, beta, sb, out, so[, options] )\n    Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        Shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    beta: ArrayLikeObject\n        Scale parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.invgamma( out.length, a, 1, b, 1, out, 1 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.invgamma( 3, a, -2, b, 1, out, 1 )\n    [...]\n\n\nrandom.strided.invgamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        Shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    oa: integer\n        Starting index for `alpha`.\n\n    beta: ArrayLikeObject\n        Scale parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    ob: integer\n        Starting index for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.invgamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.invgamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.invgamma, random.array.invgamma\n","random.strided.invgamma.ndarray":"\nrandom.strided.invgamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        Shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    oa: integer\n        Starting index for `alpha`.\n\n    beta: ArrayLikeObject\n        Scale parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    ob: integer\n        Starting index for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.invgamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.invgamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.invgamma, random.array.invgamma","random.strided.lognormal":"\nrandom.strided.lognormal( N, mu, sm, sigma, ss, out, so[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a lognormal\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mu: ArrayLikeObject\n        Location parameter.\n\n    sm: integer\n        Index increment for `mu`.\n\n    sigma: ArrayLikeObject\n        Scale parameter.\n\n    ss: integer\n        Index increment for `sigma`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var mu = linspace( 0.0, 1.0, 5 );\n    > var sigma = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.lognormal( out.length, mu, 1, sigma, 1, out, 1 )\n    [...]\n\n    // Advanced indexing:\n    > mu = linspace( 0.0, 1.0, 6 );\n    > sigma = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.lognormal( 3, mu, -2, sigma, 1, out, 1 )\n    [...]\n\n\nrandom.strided.lognormal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a lognormal\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mu: ArrayLikeObject\n        Location parameter.\n\n    sm: integer\n        Index increment for `mu`.\n\n    om: integer\n        Starting index for `mu`.\n\n    sigma: ArrayLikeObject\n        Scale parameter.\n\n    ss: integer\n        Index increment for `sigma`.\n\n    os: integer\n        Starting index for `sigma`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var mu = linspace( 0.0, 1.0, 5 );\n    > var sigma = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.lognormal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > mu = linspace( 0.0, 1.0, 6 );\n    > sigma = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.lognormal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.lognormal, random.array.lognormal\n","random.strided.lognormal.ndarray":"\nrandom.strided.lognormal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a lognormal\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mu: ArrayLikeObject\n        Location parameter.\n\n    sm: integer\n        Index increment for `mu`.\n\n    om: integer\n        Starting index for `mu`.\n\n    sigma: ArrayLikeObject\n        Scale parameter.\n\n    ss: integer\n        Index increment for `sigma`.\n\n    os: integer\n        Starting index for `sigma`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var mu = linspace( 0.0, 1.0, 5 );\n    > var sigma = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.lognormal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > mu = linspace( 0.0, 1.0, 6 );\n    > sigma = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.lognormal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.lognormal, random.array.lognormal","random.strided.minstd":"\nrandom.strided.minstd( N, out, so[, options] )\n    Fills a strided array with pseudorandom integers between 1 and 2147483646\n    (inclusive).\n\n    The `N` and stride parameters determine which elements in the provided\n    strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstd( out.length, out, 1 )\n    [...]\n\n\nrandom.strided.minstd.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom integers between 1 and 2147483646\n    (inclusive) using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstd.ndarray( out.length, out, 1, 0 )\n    [...]\n\n\nrandom.strided.minstd.normalized( N, out, so[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstd.normalized( out.length, out, 1 )\n    [...]\n\n\nrandom.strided.minstd.normalized.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1 using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstd.normalized.ndarray( out.length, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.minstd, random.array.minstd, random.strided.minstdShuffle, random.strided.randu\n","random.strided.minstd.ndarray":"\nrandom.strided.minstd.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom integers between 1 and 2147483646\n    (inclusive) using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstd.ndarray( out.length, out, 1, 0 )\n    [...]","random.strided.minstd.normalized":"\nrandom.strided.minstd.normalized( N, out, so[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstd.normalized( out.length, out, 1 )\n    [...]","random.strided.minstd.normalized.ndarray":"\nrandom.strided.minstd.normalized.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1 using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstd.normalized.ndarray( out.length, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.minstd, random.array.minstd, random.strided.minstdShuffle, random.strided.randu","random.strided.minstdShuffle":"\nrandom.strided.minstdShuffle( N, out, so[, options] )\n    Fills a strided array with pseudorandom integers between 1 and 2147483646\n    (inclusive).\n\n    The `N` and stride parameters determine which elements in the provided\n    strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstdShuffle( out.length, out, 1 )\n    [...]\n\n\nrandom.strided.minstdShuffle.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom integers between 1 and 2147483646\n    (inclusive) using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstdShuffle.ndarray( out.length, out, 1, 0 )\n    [...]\n\n\nrandom.strided.minstdShuffle.normalized( N, out, so[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstdShuffle.normalized( out.length, out, 1 )\n    [...]\n\n\nrandom.strided.minstdShuffle.normalized.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1 using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstdShuffle.normalized.ndarray( out.length, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.minstdShuffle, random.array.minstdShuffle, random.strided.minstd, random.strided.randu\n","random.strided.minstdShuffle.ndarray":"\nrandom.strided.minstdShuffle.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom integers between 1 and 2147483646\n    (inclusive) using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstdShuffle.ndarray( out.length, out, 1, 0 )\n    [...]","random.strided.minstdShuffle.normalized":"\nrandom.strided.minstdShuffle.normalized( N, out, so[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstdShuffle.normalized( out.length, out, 1 )\n    [...]","random.strided.minstdShuffle.normalized.ndarray":"\nrandom.strided.minstdShuffle.normalized.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1 using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstdShuffle.normalized.ndarray( out.length, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.minstdShuffle, random.array.minstdShuffle, random.strided.minstd, random.strided.randu","random.strided.mt19937":"\nrandom.strided.mt19937( N, out, so[, options] )\n    Fills a strided array with pseudorandom integers between 0 and 4294967295\n    (inclusive).\n\n    The `N` and stride parameters determine which elements in the provided\n    strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.mt19937( out.length, out, 1 )\n    [...]\n\n\nrandom.strided.mt19937.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom integers between 0 and 4294967295\n    (inclusive) using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.mt19937.ndarray( out.length, out, 1, 0 )\n    [...]\n\n\nrandom.strided.mt19937.normalized( N, out, so[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.mt19937.normalized( out.length, out, 1 )\n    [...]\n\n\nrandom.strided.mt19937.normalized.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1 using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.mt19937.normalized.ndarray( out.length, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.mt19937, random.array.mt19937, random.strided.randu\n","random.strided.mt19937.ndarray":"\nrandom.strided.mt19937.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom integers between 0 and 4294967295\n    (inclusive) using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.mt19937.ndarray( out.length, out, 1, 0 )\n    [...]","random.strided.mt19937.normalized":"\nrandom.strided.mt19937.normalized( N, out, so[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.mt19937.normalized( out.length, out, 1 )\n    [...]","random.strided.mt19937.normalized.ndarray":"\nrandom.strided.mt19937.normalized.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1 using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.mt19937.normalized.ndarray( out.length, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.mt19937, random.array.mt19937, random.strided.randu","random.strided.normal":"\nrandom.strided.normal( N, mu, sm, sigma, ss, out, so[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a normal\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mu: ArrayLikeObject\n        Mean.\n\n    sm: integer\n        Index increment for `mu`.\n\n    sigma: ArrayLikeObject\n        Standard deviation.\n\n    ss: integer\n        Index increment for `sigma`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var mu = linspace( 0.0, 1.0, 5 );\n    > var sigma = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.normal( out.length, mu, 1, sigma, 1, out, 1 )\n    [...]\n\n    // Advanced indexing:\n    > mu = linspace( 0.0, 1.0, 6 );\n    > sigma = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.normal( 3, mu, -2, sigma, 1, out, 1 )\n    [...]\n\n\nrandom.strided.normal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a normal\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mu: ArrayLikeObject\n        Mean.\n\n    sm: integer\n        Index increment for `mu`.\n\n    om: integer\n        Starting index for `mu`.\n\n    sigma: ArrayLikeObject\n        Standard deviation.\n\n    ss: integer\n        Index increment for `sigma`.\n\n    os: integer\n        Starting index for `sigma`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var mu = linspace( 0.0, 1.0, 5 );\n    > var sigma = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.normal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > mu = linspace( 0.0, 1.0, 6 );\n    > sigma = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.normal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.normal, random.array.normal\n","random.strided.normal.ndarray":"\nrandom.strided.normal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a normal\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mu: ArrayLikeObject\n        Mean.\n\n    sm: integer\n        Index increment for `mu`.\n\n    om: integer\n        Starting index for `mu`.\n\n    sigma: ArrayLikeObject\n        Standard deviation.\n\n    ss: integer\n        Index increment for `sigma`.\n\n    os: integer\n        Starting index for `sigma`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var mu = linspace( 0.0, 1.0, 5 );\n    > var sigma = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.normal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > mu = linspace( 0.0, 1.0, 6 );\n    > sigma = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.normal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.normal, random.array.normal","random.strided.poisson":"\nrandom.strided.poisson( N, lambda, sl, out, so )\n    Fills a strided array with pseudorandom numbers drawn from a Poisson\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    lambda: ArrayLikeObject\n        Mean parameter.\n\n    sl: integer\n        Index increment for `lambda`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.poisson.ndarray( N, lambda, sl, ol, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a Poisson\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    lambda: ArrayLikeObject\n        Mean parameter.\n\n    sl: integer\n        Index increment for `lambda`.\n\n    ol: integer\n        Starting index for `lambda`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.poisson.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]\n\n\nrandom.strided.poisson.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Poisson distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.poisson.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.poisson.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.poisson.PRNG;\n\n\nrandom.strided.poisson.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.poisson.seed;\n\n\nrandom.strided.poisson.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.poisson.seedLength;\n\n\nrandom.strided.poisson.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.poisson.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.poisson.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.poisson.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.poisson.stateLength;\n\n\nrandom.strided.poisson.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.poisson.byteLength;\n\n    See Also\n    --------\n    base.random.poisson, random.array.poisson\n","random.strided.poisson.ndarray":"\nrandom.strided.poisson.ndarray( N, lambda, sl, ol, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a Poisson\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    lambda: ArrayLikeObject\n        Mean parameter.\n\n    sl: integer\n        Index increment for `lambda`.\n\n    ol: integer\n        Starting index for `lambda`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.poisson.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]","random.strided.poisson.factory":"\nrandom.strided.poisson.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Poisson distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.poisson.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.poisson.PRNG":"\nrandom.strided.poisson.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.poisson.PRNG;","random.strided.poisson.seed":"\nrandom.strided.poisson.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.poisson.seed;","random.strided.poisson.seedLength":"\nrandom.strided.poisson.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.poisson.seedLength;","random.strided.poisson.state":"\nrandom.strided.poisson.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.poisson.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.poisson.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.poisson.stateLength":"\nrandom.strided.poisson.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.poisson.stateLength;","random.strided.poisson.byteLength":"\nrandom.strided.poisson.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.poisson.byteLength;\n\n    See Also\n    --------\n    base.random.poisson, random.array.poisson","random.strided.randu":"\nrandom.strided.randu( N, out, so[, options] )\n    Fills a strided array with uniformly distributed pseudorandom numbers\n    between 0 and 1.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: `'mt19937'`.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.randu( out.length, out, 1 )\n    [...]\n\n\nrandom.strided.randu.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with uniformly distributed pseudorandom numbers\n    between 0 and 1 using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: `'mt19937'`.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.randu.ndarray( out.length, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.randu, random.array.randu, random.strided.uniform\n","random.strided.randu.ndarray":"\nrandom.strided.randu.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with uniformly distributed pseudorandom numbers\n    between 0 and 1 using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: `'mt19937'`.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.randu.ndarray( out.length, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.randu, random.array.randu, random.strided.uniform","random.strided.rayleigh":"\nrandom.strided.rayleigh( N, sigma, ss, out, so )\n    Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sigma: ArrayLikeObject\n        Scale parameter.\n\n    ss: integer\n        Index increment for `sigma`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.rayleigh.ndarray( N, sigma, ss, os, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sigma: ArrayLikeObject\n        Scale parameter.\n\n    ss: integer\n        Index increment for `sigma`.\n\n    os: integer\n        Starting index for `sigma`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.rayleigh.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]\n\n\nrandom.strided.rayleigh.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Rayleigh distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.rayleigh.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.rayleigh.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.rayleigh.PRNG;\n\n\nrandom.strided.rayleigh.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.rayleigh.seed;\n\n\nrandom.strided.rayleigh.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.rayleigh.seedLength;\n\n\nrandom.strided.rayleigh.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.rayleigh.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.rayleigh.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.rayleigh.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.rayleigh.stateLength;\n\n\nrandom.strided.rayleigh.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.rayleigh.byteLength;\n\n    See Also\n    --------\n    base.random.rayleigh, random.array.rayleigh\n","random.strided.rayleigh.ndarray":"\nrandom.strided.rayleigh.ndarray( N, sigma, ss, os, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sigma: ArrayLikeObject\n        Scale parameter.\n\n    ss: integer\n        Index increment for `sigma`.\n\n    os: integer\n        Starting index for `sigma`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.rayleigh.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]","random.strided.rayleigh.factory":"\nrandom.strided.rayleigh.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Rayleigh distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.rayleigh.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.rayleigh.PRNG":"\nrandom.strided.rayleigh.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.rayleigh.PRNG;","random.strided.rayleigh.seed":"\nrandom.strided.rayleigh.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.rayleigh.seed;","random.strided.rayleigh.seedLength":"\nrandom.strided.rayleigh.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.rayleigh.seedLength;","random.strided.rayleigh.state":"\nrandom.strided.rayleigh.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.rayleigh.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.rayleigh.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.rayleigh.stateLength":"\nrandom.strided.rayleigh.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.rayleigh.stateLength;","random.strided.rayleigh.byteLength":"\nrandom.strided.rayleigh.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.rayleigh.byteLength;\n\n    See Also\n    --------\n    base.random.rayleigh, random.array.rayleigh","random.strided.t":"\nrandom.strided.t( N, v, sv, out, so )\n    Fills a strided array with pseudorandom numbers drawn from a Student's t-\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    v: ArrayLikeObject\n        Degrees of freedom.\n\n    sv: integer\n        Index increment for `v`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.t.ndarray( N, v, sv, ov, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a Student's t-\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    v: ArrayLikeObject\n        Degrees of freedom.\n\n    sv: integer\n        Index increment for `v`.\n\n    ov: integer\n        Starting index for `v`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.t.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]\n\n\nrandom.strided.t.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Student's t-distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.t.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.t.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.t.PRNG;\n\n\nrandom.strided.t.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.t.seed;\n\n\nrandom.strided.t.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.t.seedLength;\n\n\nrandom.strided.t.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.t.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.t.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.t.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.t.stateLength;\n\n\nrandom.strided.t.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.t.byteLength;\n\n    See Also\n    --------\n    base.random.t, random.array.t\n","random.strided.t.ndarray":"\nrandom.strided.t.ndarray( N, v, sv, ov, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a Student's t-\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    v: ArrayLikeObject\n        Degrees of freedom.\n\n    sv: integer\n        Index increment for `v`.\n\n    ov: integer\n        Starting index for `v`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.t.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]","random.strided.t.factory":"\nrandom.strided.t.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Student's t-distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.t.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.t.PRNG":"\nrandom.strided.t.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.t.PRNG;","random.strided.t.seed":"\nrandom.strided.t.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.t.seed;","random.strided.t.seedLength":"\nrandom.strided.t.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.t.seedLength;","random.strided.t.state":"\nrandom.strided.t.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.t.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.t.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.t.stateLength":"\nrandom.strided.t.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.t.stateLength;","random.strided.t.byteLength":"\nrandom.strided.t.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.t.byteLength;\n\n    See Also\n    --------\n    base.random.t, random.array.t","random.strided.uniform":"\nrandom.strided.uniform( N, a, sa, b, sb, out, so[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a continuous\n    uniform distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    a: ArrayLikeObject\n        Minimum support.\n\n    sa: integer\n        Index increment for `a`.\n\n    b: ArrayLikeObject\n        Maximum support.\n\n    sb: integer\n        Index increment for `b`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 0.0, 1.0, 5 );\n    > var b = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.uniform( out.length, a, 1, b, 1, out, 1 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 0.0, 1.0, 6 );\n    > b = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.uniform( 3, a, -2, b, 1, out, 1 )\n    [...]\n\n\nrandom.strided.uniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a continuous\n    uniform distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    a: ArrayLikeObject\n        Minimum support.\n\n    sa: integer\n        Index increment for `a`.\n\n    oa: integer\n        Starting index for `a`.\n\n    b: ArrayLikeObject\n        Maximum support.\n\n    sb: integer\n        Index increment for `b`.\n\n    ob: integer\n        Starting index for `b`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 0.0, 1.0, 5 );\n    > var b = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.uniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 0.0, 1.0, 6 );\n    > b = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.uniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.uniform, random.array.uniform, random.strided.discreteUniform\n","random.strided.uniform.ndarray":"\nrandom.strided.uniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a continuous\n    uniform distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    a: ArrayLikeObject\n        Minimum support.\n\n    sa: integer\n        Index increment for `a`.\n\n    oa: integer\n        Starting index for `a`.\n\n    b: ArrayLikeObject\n        Maximum support.\n\n    sb: integer\n        Index increment for `b`.\n\n    ob: integer\n        Starting index for `b`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 0.0, 1.0, 5 );\n    > var b = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.uniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 0.0, 1.0, 6 );\n    > b = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.uniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.uniform, random.array.uniform, random.strided.discreteUniform","random.strided.weibull":"\nrandom.strided.weibull( N, k, sk, lambda, sl, out, so[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a Weibull\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    k: ArrayLikeObject\n        Scale parameter.\n\n    sk: integer\n        Index increment for `k`.\n\n    lambda: ArrayLikeObject\n        Shape parameter.\n\n    sl: integer\n        Index increment for `lambda`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.weibull( out.length, a, 1, b, 1, out, 1 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.weibull( 3, a, -2, b, 1, out, 1 )\n    [...]\n\n\nrandom.strided.weibull.ndarray( N, k, sk, ok, lambda, sl, ol, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a Weibull\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    k: ArrayLikeObject\n        Scale parameter.\n\n    sk: integer\n        Index increment for `k`.\n\n    ok: integer\n        Starting index for `k`.\n\n    lambda: ArrayLikeObject\n        Shape parameter.\n\n    sl: integer\n        Index increment for `lambda`.\n\n    ol: integer\n        Starting index for `lambda`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.weibull.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.weibull.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.weibull, random.array.weibull\n","random.strided.weibull.ndarray":"\nrandom.strided.weibull.ndarray( N, k, sk, ok, lambda, sl, ol, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a Weibull\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    k: ArrayLikeObject\n        Scale parameter.\n\n    sk: integer\n        Index increment for `k`.\n\n    ok: integer\n        Starting index for `k`.\n\n    lambda: ArrayLikeObject\n        Shape parameter.\n\n    sl: integer\n        Index increment for `lambda`.\n\n    ol: integer\n        Starting index for `lambda`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.weibull.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.weibull.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.weibull, random.array.weibull","ranks":"\nranks( arr[, options] )\n    Computes the sample ranks for the values of an array-like object.\n\n    When all elements of the `array` are different, the ranks are uniquely\n    determined. When there are equal elements (called *ties*), the `method`\n    option determines how they are handled. The default, `'average'`, replaces\n    the ranks of the ties by their mean. Other possible options are `'min'` and\n    `'max'`, which replace the ranks of the ties by their minimum and maximum,\n    respectively. `'dense'` works like `'min'`, with the difference that the\n    next highest element after a tie is assigned the next smallest integer.\n    Finally, `ordinal` gives each element in `arr` a distinct rank, according to\n    the position they appear in.\n\n    The `missing` option is used to specify how to handle missing data.\n    By default, `NaN` or `null` are treated as missing values. `'last'`specifies\n    that missing values are placed last, `'first'` that the are assigned the\n    lowest ranks and `'remove'` means that they are removed from the array\n    before the ranks are calculated.\n\n    Parameters\n    ----------\n    arr: Array<number>\n        Input values.\n\n    options: Object (optional)\n        Function options.\n\n    options.method (optional)\n        Method name determining how ties are treated (`average`, `min`, `max`,\n        `dense`, or `ordinal`). Default: `'average'`.\n\n    options.missing (optional)\n        Determines where missing values go (`first`, `last`, or `remove`).\n        Default: `'last'`.\n\n    options.encoding (optional)\n        Array of values encoding missing values. Default: `[ null, NaN ]`.\n\n    Returns\n    -------\n    out: Array\n        Array containing the computed ranks for the elements of the input array.\n\n    Examples\n    --------\n    > var arr = [ 1.1, 2.0, 3.5, 0.0, 2.4 ] ;\n    > var out = ranks( arr )\n    [ 2, 3, 5, 1, 4 ]\n\n    // Ties are averaged:\n    > arr =  [ 2, 2, 1, 4, 3 ];\n    > out = ranks( arr )\n    [ 2.5, 2.5, 1, 5, 4 ]\n\n    // Missing values are placed last:\n    > arr = [ null, 2, 2, 1, 4, 3, NaN, NaN ];\n    > out = ranks( arr )\n    [ 6, 2.5, 2.5, 1, 5, 4, 7 ,8 ]\n\n","readDir":"\nreadDir( path, clbk )\n    Asynchronously reads the contents of a directory.\n\n    Parameters\n    ----------\n    path: string|Buffer\n        Directory path.\n\n    clbk: Function\n        Callback to invoke after reading directory contents.\n\n    Examples\n    --------\n    > function onRead( error, data ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     } else {\n    ...         console.log( data );\n    ...     }\n    ... };\n    > readDir( './beep/boop', onRead );\n\n\nreadDir.sync( path )\n    Synchronously reads the contents of a directory.\n\n    Parameters\n    ----------\n    path: string|Buffer\n        Directory path.\n\n    Returns\n    -------\n    out: Error|Array|Array<string>\n        Directory contents.\n\n    Examples\n    --------\n    > var out = readDir.sync( './beep/boop' );\n\n    See Also\n    --------\n    exists, readFile\n","readDir.sync":"\nreadDir.sync( path )\n    Synchronously reads the contents of a directory.\n\n    Parameters\n    ----------\n    path: string|Buffer\n        Directory path.\n\n    Returns\n    -------\n    out: Error|Array|Array<string>\n        Directory contents.\n\n    Examples\n    --------\n    > var out = readDir.sync( './beep/boop' );\n\n    See Also\n    --------\n    exists, readFile","readFile":"\nreadFile( file[, options], clbk )\n    Asynchronously reads the entire contents of a file.\n\n    If provided an encoding, the function returns a string. Otherwise, the\n    function returns a Buffer object.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. Default: null.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    clbk: Function\n        Callback to invoke upon reading file contents.\n\n    Examples\n    --------\n    > function onRead( error, data ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     } else {\n    ...         console.log( data );\n    ...     }\n    ... };\n    > readFile( './beep/boop.js', onRead );\n\n\nreadFile.sync( file[, options] )\n    Synchronously reads the entire contents of a file.\n\n    If provided an encoding, the function returns a string. Otherwise, the\n    function returns a Buffer object.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. Default: null.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    Returns\n    -------\n    out: Error|Buffer|string\n        File contents.\n\n    Examples\n    --------\n    > var out = readFile.sync( './beep/boop.js' );\n\n    See Also\n    --------\n    exists, open, readDir, readJSON, writeFile\n","readFile.sync":"\nreadFile.sync( file[, options] )\n    Synchronously reads the entire contents of a file.\n\n    If provided an encoding, the function returns a string. Otherwise, the\n    function returns a Buffer object.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. Default: null.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    Returns\n    -------\n    out: Error|Buffer|string\n        File contents.\n\n    Examples\n    --------\n    > var out = readFile.sync( './beep/boop.js' );\n\n    See Also\n    --------\n    exists, open, readDir, readJSON, writeFile","readFileList":"\nreadFileList( filepaths[, options], clbk )\n    Asynchronously reads the entire contents of each file in a file list.\n\n    If a provided an encoding, the function returns file contents as strings.\n    Otherwise, the function returns Buffer objects.\n\n    Each file is represented by an object with the following fields:\n\n    - file: file path.\n    - data: file contents as either a Buffer or string.\n\n    Parameters\n    ----------\n    filepaths: Array<string>\n        Filepaths.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. Default: null.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    clbk: Function\n        Callback to invoke upon reading file contents.\n\n    Examples\n    --------\n    > function onRead( error, data ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     } else {\n    ...         console.log( data );\n    ...     }\n    ... };\n    > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n    > readFileList( filepaths, onRead );\n\n\nreadFileList.sync( filepaths[, options] )\n    Synchronously reads the entire contents of each file in a file list.\n\n    If a provided an encoding, the function returns file contents as strings.\n    Otherwise, the function returns Buffer objects.\n\n    Parameters\n    ----------\n    filepaths: Array<string>\n        Filepaths.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. Default: null.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    Returns\n    -------\n    out: Error|Array|Array<string>\n        File contents.\n\n    out[ i ].file: string\n        File path.\n\n    out[ i ].data: Buffer|string\n        File contents.\n\n    Examples\n    --------\n    > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n    > var out = readFileList.sync( filepaths );\n\n","readFileList.sync":"\nreadFileList.sync( filepaths[, options] )\n    Synchronously reads the entire contents of each file in a file list.\n\n    If a provided an encoding, the function returns file contents as strings.\n    Otherwise, the function returns Buffer objects.\n\n    Parameters\n    ----------\n    filepaths: Array<string>\n        Filepaths.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. Default: null.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    Returns\n    -------\n    out: Error|Array|Array<string>\n        File contents.\n\n    out[ i ].file: string\n        File path.\n\n    out[ i ].data: Buffer|string\n        File contents.\n\n    Examples\n    --------\n    > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n    > var out = readFileList.sync( filepaths );","readJSON":"\nreadJSON( file[, options], clbk )\n    Asynchronously reads a file as JSON.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. If the encoding option is set to `utf8` and the file has a\n        UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n        attempting to parse as JSON. Default: null.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    options.reviver: Function (optional)\n        JSON transformation function.\n\n    clbk: Function\n        Callback to invoke upon reading file contents.\n\n    Examples\n    --------\n    > function onRead( error, data ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     } else {\n    ...         console.log( data );\n    ...     }\n    ... };\n    > readJSON( './beep/boop.json', onRead );\n\n\nreadJSON.sync( file[, options] )\n    Synchronously reads a file as JSON.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. If the encoding option is set to `utf8` and the file has a\n        UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n        attempting to parse as JSON. Default: null.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    options.reviver: Function (optional)\n        JSON transformation function.\n\n    Returns\n    -------\n    out: Error|JSON\n        File contents.\n\n    Examples\n    --------\n    > var out = readJSON.sync( './beep/boop.json' );\n\n    See Also\n    --------\n    readFile\n","readJSON.sync":"\nreadJSON.sync( file[, options] )\n    Synchronously reads a file as JSON.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. If the encoding option is set to `utf8` and the file has a\n        UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n        attempting to parse as JSON. Default: null.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    options.reviver: Function (optional)\n        JSON transformation function.\n\n    Returns\n    -------\n    out: Error|JSON\n        File contents.\n\n    Examples\n    --------\n    > var out = readJSON.sync( './beep/boop.json' );\n\n    See Also\n    --------\n    readFile","readWASM":"\nreadWASM( file[, options], clbk )\n    Asynchronously reads a file as WebAssembly.\n\n    The function returns file contents as a Uint8Array.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    options: Object (optional)\n        Options.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    clbk: Function\n        Callback to invoke upon reading file contents.\n\n    Examples\n    --------\n    > function onRead( error, data ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     } else {\n    ...         console.log( data );\n    ...     }\n    ... };\n    > readWASM( './beep/boop.wasm', onRead );\n\n\nreadWASM.sync( file[, options] )\n    Synchronously reads a file as WebAssembly.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    options: Object (optional)\n        Options.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    Returns\n    -------\n    out: Error|Uint8Array\n        File contents.\n\n    Examples\n    --------\n    > var out = readWASM.sync( './beep/boop.wasm' );\n\n    See Also\n    --------\n    readFile\n","readWASM.sync":"\nreadWASM.sync( file[, options] )\n    Synchronously reads a file as WebAssembly.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    options: Object (optional)\n        Options.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    Returns\n    -------\n    out: Error|Uint8Array\n        File contents.\n\n    Examples\n    --------\n    > var out = readWASM.sync( './beep/boop.wasm' );\n\n    See Also\n    --------\n    readFile","real":"\nreal( z )\n    Returns the real component of a double-precision complex floating-point\n    number.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    re: number\n        Real component.\n\n    Examples\n    --------\n    > var z = new Complex128( 5.0, 3.0 );\n    > var re = real( z )\n    5.0\n\n    See Also\n    --------\n    imag, reim\n","realarray":"\nrealarray( [dtype] )\n    Creates a typed array.\n\n    The function supports the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754).\n    - float32: single-precision floating-point numbers (IEEE 754).\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n\n    The default typed array data type is `float64`.\n\n    Parameters\n    ----------\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = realarray()\n    <Float64Array>\n    > arr = realarray( 'float32' )\n    <Float32Array>\n\n\nrealarray( length[, dtype] )\n    Returns a typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = realarray( 5 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n    > arr = realarray( 5, 'int32' )\n    <Int32Array>[ 0, 0, 0, 0, 0 ]\n\n\nrealarray( typedarray[, dtype] )\n    Creates a typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = realarray( [ 0.5, 0.5, 0.5 ] );\n    > var arr2 = realarray( arr1, 'float32' )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]\n\n\nrealarray( obj[, dtype] )\n    Creates a typed array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a typed array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 0.5, 0.5, 0.5 ];\n    > var arr2 = realarray( arr1, 'float32' )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]\n\n\nrealarray( buffer[, byteOffset[, length]][, dtype] )\n    Returns a typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 16 );\n    > var arr = realarray( buf, 0, 4, 'float32' )\n    <Float32Array>[ 0.0, 0.0, 0.0, 0.0 ]\n\n    See Also\n    --------\n    Float64Array, Float32Array, Int32Array, Uint32Array, Int16Array, Uint16Array, Int8Array, Uint8Array, Uint8ClampedArray\n","realarrayCtors":"\nrealarrayCtors( dtype )\n    Returns a typed array constructor.\n\n    The function returns constructors for the following data types:\n\n    - float32: single-precision floating-point numbers.\n    - float64: double-precision floating-point numbers.\n    - int16: signed 16-bit integers.\n    - int32: signed 32-bit integers.\n    - int8: signed 8-bit integers.\n    - uint16: unsigned 16-bit integers.\n    - uint32: unsigned 32-bit integers.\n    - uint8: unsigned 8-bit integers.\n    - uint8c: unsigned clamped 8-bit integers.\n\n    Parameters\n    ----------\n    dtype: string\n        Data type.\n\n    Returns\n    -------\n    out: Function|null\n        Typed array constructor.\n\n    Examples\n    --------\n    > var ctor = realarrayCtors( 'float64' )\n    <Function>\n    > ctor = realarrayCtors( 'float' )\n    null\n\n    See Also\n    --------\n    arrayCtors, complexarrayCtors\n","realarrayDataTypes":"\nrealarrayDataTypes()\n    Returns a list of typed array real-valued data types.\n\n    Returns\n    -------\n    out: Array<string>\n        List of typed array data types.\n\n    Examples\n    --------\n    > var out = realarrayDataTypes()\n    <Array>\n\n    See Also\n    --------\n    arrayDataTypes, complexarrayDataTypes\n","realf":"\nrealf( z )\n    Returns the real component of a single-precision complex floating-point\n    number.\n\n    Parameters\n    ----------\n    z: Complex64\n        Complex number.\n\n    Returns\n    -------\n    re: number\n        Real component.\n\n    Examples\n    --------\n    > var z = new Complex64( 5.0, 3.0 );\n    > var re = realf( z )\n    5.0\n\n    See Also\n    --------\n    imagf, real, reimf\n","realmax":"\nrealmax( dtype )\n    Returns the maximum finite value capable of being represented by a numeric\n    real type.\n\n    The following numeric real types are supported:\n\n    - float64: double-precision floating-point numbers.\n    - float32: single-precision floating-point numbers.\n    - float16: half-precision floating-point numbers.\n\n    Parameters\n    ----------\n    dtype: string\n        Numeric type.\n\n    Returns\n    -------\n    out: number\n        Maximum finite value.\n\n    Examples\n    --------\n    > var m = realmax( 'float16' )\n    65504.0\n    > m = realmax( 'float32' )\n    3.4028234663852886e+38\n\n    See Also\n    --------\n    realmin, typemax\n","realmin":"\nrealmin( dtype )\n    Returns the smallest positive normal value capable of being represented by a\n    numeric real type.\n\n    The following numeric real types are supported:\n\n    - float64: double-precision floating-point numbers.\n    - float32: single-precision floating-point numbers.\n    - float16: half-precision floating-point numbers.\n\n    Parameters\n    ----------\n    dtype: string\n        Numeric type.\n\n    Returns\n    -------\n    out: number\n        Smallest finite normal value.\n\n    Examples\n    --------\n    > var m = realmin( 'float16' )\n    0.00006103515625\n    > m = realmin( 'float32' )\n    1.1754943508222875e-38\n\n    See Also\n    --------\n    realmax, typemin\n","reBasename":"\nreBasename( [platform] )\n    Returns a regular expression to capture the last part of a path.\n\n    The regular expression is platform-dependent. If the current process is\n    running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n    `*.REGEXP_POSIX`.\n\n    Parameters\n    ----------\n    platform: string (optional)\n        Path platform (either `posix` or `win32`).\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reBasename()\n    <RegExp>\n    > var RE_POSIX = reBasename( 'posix' );\n    > var RE_WIN32 = reBasename( 'win32' );\n    > var str = RE.toString();\n    > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n    true\n\n\nreBasename.REGEXP\n    Regular expression to capture the last part of a POSIX path.\n\n    Examples\n    --------\n    > var RE = reBasename.REGEXP\n    <RegExp>\n\n\nreBasename.REGEXP_POSIX\n    Regular expression to capture the last part of a POSIX path.\n\n    Examples\n    --------\n    > var base = reBasename.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n    'index.js'\n\n\nreBasename.REGEXP_WIN32\n    Regular expression to capture the last part of a Windows path.\n\n    Examples\n    --------\n    > var base = reBasename.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    'index.js'\n\n    See Also\n    --------\n    reBasenamePosix, reBasenameWindows\n","reBasename.REGEXP":"\nreBasename.REGEXP\n    Regular expression to capture the last part of a POSIX path.\n\n    Examples\n    --------\n    > var RE = reBasename.REGEXP\n    <RegExp>","reBasename.REGEXP_POSIX":"\nreBasename.REGEXP_POSIX\n    Regular expression to capture the last part of a POSIX path.\n\n    Examples\n    --------\n    > var base = reBasename.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n    'index.js'","reBasename.REGEXP_WIN32":"\nreBasename.REGEXP_WIN32\n    Regular expression to capture the last part of a Windows path.\n\n    Examples\n    --------\n    > var base = reBasename.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    'index.js'\n\n    See Also\n    --------\n    reBasenamePosix, reBasenameWindows","reBasenamePosix":"\nreBasenamePosix()\n    Returns a regular expression to capture the last part of a POSIX path.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE_BASENAME_POSIX = reBasenamePosix();\n    > var base = RE_BASENAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n    'index.js'\n    > base = RE_BASENAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\n    '.gitignore'\n    > base = RE_BASENAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\n    'file.pdf'\n    > base = RE_BASENAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\n    'file'\n    > base = RE_BASENAME_POSIX.exec( 'index.js' )[ 1 ]\n    'index.js'\n    > base = RE_BASENAME_POSIX.exec( '.' )[ 1 ]\n    '.'\n    > base = RE_BASENAME_POSIX.exec( './' )[ 1 ]\n    '.'\n    > base = RE_BASENAME_POSIX.exec( '' )[ 1 ]\n    ''\n\n\nreBasenamePosix.REGEXP\n    Regular expression to capture the last part of a POSIX path.\n\n    Examples\n    --------\n    > var base = reBasenamePosix.REGEXP.exec( 'foo/bar/index.js' )[ 1 ]\n    'index.js'\n\n    See Also\n    --------\n    reBasename, reBasenameWindows\n","reBasenamePosix.REGEXP":"\nreBasenamePosix.REGEXP\n    Regular expression to capture the last part of a POSIX path.\n\n    Examples\n    --------\n    > var base = reBasenamePosix.REGEXP.exec( 'foo/bar/index.js' )[ 1 ]\n    'index.js'\n\n    See Also\n    --------\n    reBasename, reBasenameWindows","reBasenameWindows":"\nreBasenameWindows()\n    Returns a regular expression to capture the last part of a Windows path.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE_BASENAME_WINDOWS = reBasenameWindows();\n    > var base = RE_BASENAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    'index.js'\n    > base = RE_BASENAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n    '.gitignore'\n    > base = RE_BASENAME_WINDOWS.exec( 'foo\\\\file.pdf' )[ 1 ]\n    'file.pdf'\n    > base = RE_BASENAME_WINDOWS.exec( 'foo\\\\bar\\\\file' )[ 1 ]\n    'file'\n    > base = RE_BASENAME_WINDOWS.exec( 'index.js' )[ 1 ]\n    'index.js'\n    > base = RE_BASENAME_WINDOWS.exec( '.' )[ 1 ]\n    '.'\n    > base = RE_BASENAME_WINDOWS.exec( '' )[ 1 ]\n    ''\n\n\nreBasenameWindows.REGEXP\n    Regular expression to capture the last part of a Windows path.\n\n    Examples\n    --------\n    > var match = reBasenameWindows.REGEXP.exec( 'foo\\\\file.pdf' )[ 1 ]\n    'file.pdf'\n\n    See Also\n    --------\n    reBasename, reBasenamePosix\n","reBasenameWindows.REGEXP":"\nreBasenameWindows.REGEXP\n    Regular expression to capture the last part of a Windows path.\n\n    Examples\n    --------\n    > var match = reBasenameWindows.REGEXP.exec( 'foo\\\\file.pdf' )[ 1 ]\n    'file.pdf'\n\n    See Also\n    --------\n    reBasename, reBasenamePosix","reColorHexadecimal":"\nreColorHexadecimal( [mode] )\n    Returns a regular expression to match a hexadecimal color.\n\n    Parameters\n    ----------\n    mode: string (optional)\n        Color format (`full`, `shorthand`, or `either`).\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reColorHexadecimal();\n    > var bool = RE.test( 'ffffff' )\n    true\n    > bool = RE.test( '000' )\n    false\n    > bool = RE.test( 'beep' )\n    false\n\n\nreColorHexadecimal.REGEXP\n    Regular expression to match a full hexadecimal color.\n\n    Examples\n    --------\n    > var bool = reColorHexadecimal.REGEXP.test( 'ffffff' )\n    true\n    > bool = reColorHexadecimal.REGEXP.test( '000' )\n    false\n    > bool = reColorHexadecimal.REGEXP.test( 'beep' )\n    false\n\n\nreColorHexadecimal.REGEXP_SHORTHAND\n    Regular expression to match a shorthand hexadecimal color.\n\n    Examples\n    --------\n    > var bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'ffffff' )\n    false\n    > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( '000' )\n    true\n    > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'beep' )\n    false\n\n\nreColorHexadecimal.REGEXP_EITHER\n    Regular expression to match either a shorthand or full length hexadecimal\n    color.\n\n    Examples\n    --------\n    > var bool = reColorHexadecimal.REGEXP_EITHER.test( 'ffffff' )\n    true\n    > bool = reColorHexadecimal.REGEXP_EITHER.test( '000' )\n    true\n    > bool = reColorHexadecimal.REGEXP_EITHER.test( 'beep' )\n    false\n\n","reColorHexadecimal.REGEXP":"\nreColorHexadecimal.REGEXP\n    Regular expression to match a full hexadecimal color.\n\n    Examples\n    --------\n    > var bool = reColorHexadecimal.REGEXP.test( 'ffffff' )\n    true\n    > bool = reColorHexadecimal.REGEXP.test( '000' )\n    false\n    > bool = reColorHexadecimal.REGEXP.test( 'beep' )\n    false","reColorHexadecimal.REGEXP_SHORTHAND":"\nreColorHexadecimal.REGEXP_SHORTHAND\n    Regular expression to match a shorthand hexadecimal color.\n\n    Examples\n    --------\n    > var bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'ffffff' )\n    false\n    > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( '000' )\n    true\n    > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'beep' )\n    false","reColorHexadecimal.REGEXP_EITHER":"\nreColorHexadecimal.REGEXP_EITHER\n    Regular expression to match either a shorthand or full length hexadecimal\n    color.\n\n    Examples\n    --------\n    > var bool = reColorHexadecimal.REGEXP_EITHER.test( 'ffffff' )\n    true\n    > bool = reColorHexadecimal.REGEXP_EITHER.test( '000' )\n    true\n    > bool = reColorHexadecimal.REGEXP_EITHER.test( 'beep' )\n    false","reDecimalNumber":"\nreDecimalNumber( [options] )\n    Returns a regular expression to match a decimal number.\n\n    A leading digit is not required.\n\n    A decimal point and at least one trailing digit is required.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.flags: string (optional)\n        Regular expression flags. Default: ''.\n\n    options.capture: boolean (optional)\n        Boolean indicating whether to create a capture group for the match.\n        Default: false.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reDecimalNumber();\n    > var bool = RE.test( '1.234' )\n    true\n    > bool = RE.test( '-1.234' )\n    true\n    > bool = RE.test( '0.0' )\n    true\n    > bool = RE.test( '.0' )\n    true\n    > bool = RE.test( '0' )\n    false\n    > bool = RE.test( 'beep' )\n    false\n\n    // Create a RegExp to capture all decimal numbers:\n    > var re = reDecimalNumber({ 'flags': 'g' });\n    > var str = '1.234 5.6, 7.8';\n    > var out = str.match( re )\n    [ '1.234', '5.6', '7.8' ]\n\n\nreDecimalNumber.REGEXP\n    Regular expression to match a decimal number.\n\n    A leading digit is not required.\n\n    A decimal point and at least one trailing digit is required.\n\n    Examples\n    --------\n    > var RE = reDecimalNumber.REGEXP;\n    > var bool = RE.test( '1.234' )\n    true\n    > bool = RE.test( '-1.234' )\n    true\n\n\nreDecimalNumber.REGEXP_CAPTURE\n    Regular expression to capture a decimal number.\n\n    A leading digit is not required.\n\n    A decimal point and at least one trailing digit is required.\n\n    Examples\n    --------\n    > var RE = reDecimalNumber.REGEXP_CAPTURE;\n    > var str = '1.02';\n    > var out = replace( str, RE, '$1 x $1' )\n    '1.02 x 1.02'\n","reDecimalNumber.REGEXP":"\nreDecimalNumber.REGEXP\n    Regular expression to match a decimal number.\n\n    A leading digit is not required.\n\n    A decimal point and at least one trailing digit is required.\n\n    Examples\n    --------\n    > var RE = reDecimalNumber.REGEXP;\n    > var bool = RE.test( '1.234' )\n    true\n    > bool = RE.test( '-1.234' )\n    true","reDecimalNumber.REGEXP_CAPTURE":"\nreDecimalNumber.REGEXP_CAPTURE\n    Regular expression to capture a decimal number.\n\n    A leading digit is not required.\n\n    A decimal point and at least one trailing digit is required.\n\n    Examples\n    --------\n    > var RE = reDecimalNumber.REGEXP_CAPTURE;\n    > var str = '1.02';\n    > var out = replace( str, RE, '$1 x $1' )\n    '1.02 x 1.02'","reDirname":"\nreDirname( [platform] )\n    Returns a regular expression to capture a path dirname.\n\n    The regular expression is platform-dependent. If the current process is\n    running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n    `*.REGEXP_POSIX`.\n\n    Parameters\n    ----------\n    platform: string (optional)\n        Path platform (either `posix` or `win32`).\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reDirname()\n    <RegExp>\n    > var RE_POSIX = reDirname( 'posix' );\n    > var dir = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n    '/foo/bar'\n    > var RE_WIN32 = reDirname( 'win32' );\n    > dir = RE_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    'C:\\foo\\bar'\n    > var str = RE.toString();\n    > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n    true\n\n\nreDirname.REGEXP\n    Regular expression to capture a path dirname.\n\n    Examples\n    --------\n    > var RE = reDirname.REGEXP\n    <RegExp>\n\n\nreDirname.REGEXP_POSIX\n    Regular expression to capture a POSIX path dirname.\n\n    Examples\n    --------\n    > var dir = reDirname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n    '/foo/bar'\n\n\nreDirname.REGEXP_WIN32\n    Regular expression to capture a Windows path dirname.\n\n    Examples\n    --------\n    > var dir = reDirname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    'C:\\foo\\bar'\n\n    See Also\n    --------\n    reDirnamePosix, reDirnameWindows, dirname\n","reDirname.REGEXP":"\nreDirname.REGEXP\n    Regular expression to capture a path dirname.\n\n    Examples\n    --------\n    > var RE = reDirname.REGEXP\n    <RegExp>","reDirname.REGEXP_POSIX":"\nreDirname.REGEXP_POSIX\n    Regular expression to capture a POSIX path dirname.\n\n    Examples\n    --------\n    > var dir = reDirname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n    '/foo/bar'","reDirname.REGEXP_WIN32":"\nreDirname.REGEXP_WIN32\n    Regular expression to capture a Windows path dirname.\n\n    Examples\n    --------\n    > var dir = reDirname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    'C:\\foo\\bar'\n\n    See Also\n    --------\n    reDirnamePosix, reDirnameWindows, dirname","reDirnamePosix":"\nreDirnamePosix()\n    Returns a regular expression to capture a POSIX path dirname.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reDirnamePosix();\n    > var dir = RE.exec( '/foo/bar/index.js' )[ 1 ]\n    '/foo/bar'\n    > dir = RE.exec( './foo/bar/.gitignore' )[ 1 ]\n    './foo/bar'\n    > dir = RE.exec( 'foo/file.pdf' )[ 1 ]\n    'foo'\n    > dir = RE.exec( '/foo/bar/file' )[ 1 ]\n    '/foo/bar'\n    > dir = RE.exec( 'index.js' )[ 1 ]\n    ''\n    > dir = RE.exec( '.' )[ 1 ]\n    '.'\n    > dir = RE.exec( './' )[ 1 ]\n    '.'\n    > dir = RE.exec( '' )[ 1 ]\n    ''\n\n\nreDirnamePosix.REGEXP\n    Regular expression to capture a POSIX path dirname.\n\n    Examples\n    --------\n    > var ext = reDirnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n    '/foo/bar'\n\n    See Also\n    --------\n    reDirname, reDirnameWindows, dirname\n","reDirnamePosix.REGEXP":"\nreDirnamePosix.REGEXP\n    Regular expression to capture a POSIX path dirname.\n\n    Examples\n    --------\n    > var ext = reDirnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n    '/foo/bar'\n\n    See Also\n    --------\n    reDirname, reDirnameWindows, dirname","reDirnameWindows":"\nreDirnameWindows()\n    Returns a regular expression to capture a Windows path dirname.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reDirnameWindows();\n    > var dir = RE.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n    'foo\\bar'\n    > dir = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n    'C:\\foo\\bar'\n    > dir = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\n    'foo'\n    > dir = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\n    '\\foo\\bar'\n    > dir = RE.exec( 'index.js' )[ 1 ]\n    ''\n    > dir = RE.exec( '' )[ 1 ]\n    ''\n\n\nreDirnameWindows.REGEXP\n    Regular expression to capture a Windows path dirname.\n\n    Examples\n    --------\n    > var dir = reDirnameWindows.REGEXP.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n    'foo\\bar'\n\n    See Also\n    --------\n    reDirname, reDirnamePosix, dirname\n","reDirnameWindows.REGEXP":"\nreDirnameWindows.REGEXP\n    Regular expression to capture a Windows path dirname.\n\n    Examples\n    --------\n    > var dir = reDirnameWindows.REGEXP.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n    'foo\\bar'\n\n    See Also\n    --------\n    reDirname, reDirnamePosix, dirname","reduce":"\nreduce( arr, initial, reducer[, thisArg] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    When invoked, the reduction function is provided four arguments:\n\n    - accumulator: accumulated value.\n    - value: array element.\n    - index: element index.\n    - arr: input array.\n\n    If provided an empty array, the function returns the initial value.\n\n    When provided an ndarray, the function performs a reduction over the entire\n    input ndarray (i.e., higher-order ndarray dimensions are flattened to a\n    single-dimension).\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject|ndarray\n        Input array.\n\n    initial: any\n        Accumulator value used in the first invocation of the reduction\n        function.\n\n    reducer: Function\n        Function to invoke for each element in the input array.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: any\n        Accumulated result.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.add, 2 );\n    > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > var out = reduce( arr, 0.0, f )\n    21.0\n\n    // ndarray:\n    > arr = array( arr, { 'shape': [ 2, 3 ] } );\n    > out = reduce( arr, 0.0, f )\n    21.0\n\n    See Also\n    --------\n    forEach, map, reduceAsync, reduceRight\n","reduce2d":"\nreduce2d( arr, initial, reducer[, thisArg] )\n    Reduces the number of dimensions by one of a two-dimensional nested array by\n    applying a function against an accumulator and each element along the\n    innermost dimension and returning the accumulation results as a one-\n    dimensional array.\n\n    The applied function is provided the following arguments:\n\n    - accumulator: accumulated value.\n    - value: array element.\n    - indices: current array element indices.\n    - arr: input array.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject<ArrayLikeObject>\n        Input array of arrays.\n\n    initial: ArrayLikeObject\n        Initial values. Must have a length equal to the size of the outermost\n        input array dimension.\n\n    reducer: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array\n        Accumulation results.\n\n    Examples\n    --------\n    > var f = naryFunction( base.add, 2 );\n    > var arr = [ [ 1, 2, 3 ], [ 4, 5, 6 ] ];\n    > var out = reduce2d( arr, [ 0, 0 ], f )\n    [ 6, 15 ]\n\n    See Also\n    --------\n    map2d, reduce\n","reduceAsync":"\nreduceAsync( collection, initial, [options,] reducer, done )\n    Applies a function against an accumulator and each element in a collection\n    and returns the accumulated result.\n\n    When invoked, `reducer` is provided a maximum of five arguments:\n\n    - accumulator: accumulated value.\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If\n    `reducer` accepts three arguments, `reducer` is provided:\n\n    - accumulator\n    - value\n    - next\n\n    If `reducer` accepts four arguments, `reducer` is provided:\n\n    - accumulator\n    - value\n    - index\n    - next\n\n    For every other `reducer` signature, `reducer` is provided all five\n    arguments.\n\n    The `next` callback accepts two arguments:\n\n    - error: error argument.\n    - accumulator: accumulated value.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    If provided an empty collection, the function invokes the `done` callback\n    with the `initial` value as the second argument.\n\n    The function does not skip `undefined` elements.\n\n    When processing collection elements concurrently, *beware* of race\n    conditions when updating an accumulator. This is especially true when an\n    accumulator is a primitive (e.g., a number). In general, prefer object\n    accumulators.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    initial: any\n        Accumulator value used in the first invocation of the reduction\n        function.\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: true.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    reducer: Function\n        The function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function fcn( acc, value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         acc.sum += value;\n    ...         next( null, acc );\n    ...     }\n    ... };\n    > function done( error, acc ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( acc.sum );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > var acc = { 'sum': 0 };\n    > reduceAsync( arr, acc, fcn, done )\n    3000\n    2500\n    1000\n    6500\n\n    // Limit number of concurrent invocations:\n    > function fcn( acc, value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         acc.sum += value;\n    ...         next( null, acc );\n    ...     }\n    ... };\n    > function done( error, acc ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( acc.sum );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 3000, 2500, 1000 ];\n    > var acc = { 'sum': 0 };\n    > reduceAsync( arr, acc, opts, fcn, done )\n    2500\n    3000\n    1000\n    6500\n\n    // Process concurrently:\n    > function fcn( acc, value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         acc.sum += value;\n    ...         next( null, acc );\n    ...     }\n    ... };\n    > function done( error, acc ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( acc.sum );\n    ... };\n    > var opts = { 'series': false };\n    > var arr = [ 3000, 2500, 1000 ];\n    > var acc = { 'sum': 0 };\n    > reduceAsync( arr, acc, opts, fcn, done )\n    1000\n    2500\n    3000\n    6500\n\n\nreduceAsync.factory( [options,] fcn )\n    Returns a function which applies a function against an accumulator and each\n    element in a collection and returns the accumulated result.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: true.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function fcn( acc, value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         acc.sum += value;\n    ...         next( null, acc );\n    ...     }\n    ... };\n    > var opts = { 'series': false };\n    > var f = reduceAsync.factory( opts, fcn );\n    > function done( error, acc ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( acc.sum );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > var acc = { 'sum': 0 };\n    > f( arr, acc, done )\n    1000\n    2500\n    3000\n    6500\n    > acc = { 'sum': 0 };\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, acc, done )\n    1000\n    1500\n    2000\n    4500\n\n    See Also\n    --------\n    forEachAsync, reduce, reduceRightAsync\n","reduceAsync.factory":"\nreduceAsync.factory( [options,] fcn )\n    Returns a function which applies a function against an accumulator and each\n    element in a collection and returns the accumulated result.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: true.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function fcn( acc, value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         acc.sum += value;\n    ...         next( null, acc );\n    ...     }\n    ... };\n    > var opts = { 'series': false };\n    > var f = reduceAsync.factory( opts, fcn );\n    > function done( error, acc ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( acc.sum );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > var acc = { 'sum': 0 };\n    > f( arr, acc, done )\n    1000\n    2500\n    3000\n    6500\n    > acc = { 'sum': 0 };\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, acc, done )\n    1000\n    1500\n    2000\n    4500\n\n    See Also\n    --------\n    forEachAsync, reduce, reduceRightAsync","reduceRight":"\nreduceRight( arr, initial, reducer[, thisArg] )\n    Applies a function against an accumulator and each element in an array while\n    iterating from right to left and returns the accumulated result.\n\n    When invoked, the reduction function is provided four arguments:\n\n    - accumulator: accumulated value.\n    - value: array element.\n    - index: element index.\n    - arr: input array.\n\n    If provided an empty array, the function returns the initial value.\n\n    When provided an ndarray, the function performs a reduction over the entire\n    input ndarray (i.e., higher-order ndarray dimensions are flattened to a\n    single-dimension).\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject|ndarray\n        Input array.\n\n    initial: any\n        Accumulator value used in the first invocation of the reduction\n        function.\n\n    reducer: Function\n        Function to invoke for each element in the input array.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: any\n        Accumulated result.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.add, 2 );\n    > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > var out = reduceRight( arr, 0.0, f )\n    21.0\n\n    // ndarray:\n    > arr = array( arr, { 'shape': [ 2, 3 ] } );\n    > out = reduceRight( arr, 0.0, f )\n    21.0\n\n    See Also\n    --------\n    forEachRight, mapRight, reduce, reduceRightAsync\n","reduceRightAsync":"\nreduceRightAsync( collection, initial, [options,] reducer, done )\n    Applies a function against an accumulator and each element in a collection\n    and returns the accumulated result, iterating from right to left.\n\n    When invoked, `reducer` is provided a maximum of five arguments:\n\n    - accumulator: accumulated value.\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If\n    `reducer` accepts three arguments, `reducer` is provided:\n\n    - accumulator\n    - value\n    - next\n\n    If `reducer` accepts four arguments, `reducer` is provided:\n\n    - accumulator\n    - value\n    - index\n    - next\n\n    For every other `reducer` signature, `reducer` is provided all five\n    arguments.\n\n    The `next` callback accepts two arguments:\n\n    - error: error argument.\n    - accumulator: accumulated value.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    If provided an empty collection, the function invokes the `done` callback\n    with the `initial` value as the second argument.\n\n    The function does not skip `undefined` elements.\n\n    When processing collection elements concurrently, *beware* of race\n    conditions when updating an accumulator. This is especially true when an\n    accumulator is a primitive (e.g., a number). In general, prefer object\n    accumulators.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    initial: any\n        Accumulator value used in the first invocation of the reduction\n        function.\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: true.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    reducer: Function\n        The function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function fcn( acc, value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         acc.sum += value;\n    ...         next( null, acc );\n    ...     }\n    ... };\n    > function done( error, acc ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( acc.sum );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > var acc = { 'sum': 0 };\n    > reduceRightAsync( arr, acc, fcn, done )\n    3000\n    2500\n    1000\n    6500\n\n    // Limit number of concurrent invocations:\n    > function fcn( acc, value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         acc.sum += value;\n    ...         next( null, acc );\n    ...     }\n    ... };\n    > function done( error, acc ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( acc.sum );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 1000, 2500, 3000 ];\n    > var acc = { 'sum': 0 };\n    > reduceRightAsync( arr, acc, opts, fcn, done )\n    2500\n    3000\n    1000\n    6500\n\n    // Process concurrently:\n    > function fcn( acc, value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         acc.sum += value;\n    ...         next( null, acc );\n    ...     }\n    ... };\n    > function done( error, acc ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( acc.sum );\n    ... };\n    > var opts = { 'series': false };\n    > var arr = [ 1000, 2500, 3000 ];\n    > var acc = { 'sum': 0 };\n    > reduceRightAsync( arr, acc, opts, fcn, done )\n    1000\n    2500\n    3000\n    6500\n\n\nreduceRightAsync.factory( [options,] fcn )\n    Returns a function which applies a function against an accumulator and each\n    element in a collection and returns the accumulated result, iterating from\n    right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: true.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function fcn( acc, value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         acc.sum += value;\n    ...         next( null, acc );\n    ...     }\n    ... };\n    > var opts = { 'series': false };\n    > var f = reduceRightAsync.factory( opts, fcn );\n    > function done( error, acc ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( acc.sum );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > var acc = { 'sum': 0 };\n    > f( arr, acc, done )\n    1000\n    2500\n    3000\n    6500\n    > acc = { 'sum': 0 };\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, acc, done )\n    1000\n    1500\n    2000\n    4500\n\n    See Also\n    --------\n    forEachRightAsync, reduceAsync, reduceRight\n","reduceRightAsync.factory":"\nreduceRightAsync.factory( [options,] fcn )\n    Returns a function which applies a function against an accumulator and each\n    element in a collection and returns the accumulated result, iterating from\n    right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: true.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function fcn( acc, value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         acc.sum += value;\n    ...         next( null, acc );\n    ...     }\n    ... };\n    > var opts = { 'series': false };\n    > var f = reduceRightAsync.factory( opts, fcn );\n    > function done( error, acc ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( acc.sum );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > var acc = { 'sum': 0 };\n    > f( arr, acc, done )\n    1000\n    2500\n    3000\n    6500\n    > acc = { 'sum': 0 };\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, acc, done )\n    1000\n    1500\n    2000\n    4500\n\n    See Also\n    --------\n    forEachRightAsync, reduceAsync, reduceRight","reDurationString":"\nreDurationString()\n    Returns a regular expression to match a duration string.\n\n    A duration string is a string containing a sequence of time units. A time\n    unit is a nonnegative integer followed by a unit identifier. The following\n    unit identifiers are supported:\n\n    - d: days.\n    - h: hours.\n    - m: minutes.\n    - s: seconds.\n    - ms: milliseconds.\n\n    For example, the string `1m3s10ms` is a duration string containing three\n    time units: `1m` (1 minute), `3s` (3 seconds), and `10ms` (10 milliseconds).\n    The string `60m` is a duration string containing a single time unit: `60m`\n    (60 minutes). Time units must be supplied in descending order of magnitude\n    (i.e., days, hours, minutes, seconds, milliseconds).\n\n    Duration strings are case insensitive. For example, the string `1M3S10MS` is\n    equivalent to `1m3s10ms`.\n\n    The regular expression captures the following groups:\n\n    1. The days component.\n    2. The hours component.\n    3. The minutes component.\n    4. The seconds component.\n    5. The milliseconds component.\n\n    Returns\n    -------\n    re: RegExp: Regular expression\n        Regular expression to match a duration string.\n\n    Examples\n    --------\n    > var RE = reDurationString();\n    > var parts = RE.exec( '3d2ms' )\n    [...]\n    > parts = RE.exec( '4h3m20s' )\n    [...]\n\n\nreDurationString.REGEXP\n    Regular expression to match a duration string.\n\n    Examples\n    --------\n    > var bool = reDurationString.REGEXP.test( '3d2ms' )\n    true\n    > bool = reDurationString.REGEXP.test( 'foo' )\n    false\n","reDurationString.REGEXP":"\nreDurationString.REGEXP\n    Regular expression to match a duration string.\n\n    Examples\n    --------\n    > var bool = reDurationString.REGEXP.test( '3d2ms' )\n    true\n    > bool = reDurationString.REGEXP.test( 'foo' )\n    false","reEOL":"\nreEOL( [options] )\n    Regular expression to match a newline character sequence: /\\r?\\n/.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.flags: string (optional)\n        Regular expression flags. Default: ''.\n\n    options.capture: boolean (optional)\n        Boolean indicating whether to create a capture group for the match.\n        Default: false.\n\n    Returns\n    -------\n    regexp: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE_EOL = reEOL();\n    > var bool = RE_EOL.test( '\\n' )\n    true\n    > bool = RE_EOL.test( '\\r\\n' )\n    true\n    > bool = RE_EOL.test( '\\\\r\\\\n' )\n    false\n\nreEOL.REGEXP\n    Regular expression to match a newline character sequence: /\\r?\\n/.\n\n    Examples\n    --------\n    > var bool = reEOL.REGEXP.test( 'abc' )\n    false\n\nreEOL.REGEXP_CAPTURE\n    Regular expression to capture a newline character sequence: /\\r?\\n/.\n\n    Examples\n    --------\n    > var parts = reEOL.REGEXP_CAPTURE.exec( '\\n' )\n    [ '\\n', '\\n' ]\n\n","reEOL.REGEXP":"\nreEOL.REGEXP\n    Regular expression to match a newline character sequence: /\\r?\\n/.\n\n    Examples\n    --------\n    > var bool = reEOL.REGEXP.test( 'abc' )\n    false","reEOL.REGEXP_CAPTURE":"\nreEOL.REGEXP_CAPTURE\n    Regular expression to capture a newline character sequence: /\\r?\\n/.\n\n    Examples\n    --------\n    > var parts = reEOL.REGEXP_CAPTURE.exec( '\\n' )\n    [ '\\n', '\\n' ]","reExtendedLengthPath":"\nreExtendedLengthPath()\n    Returns a regular expression to test if a string is an extended-length path.\n\n    Extended-length paths are Windows paths which begin with `\\\\?\\`.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reExtendedLengthPath();\n    > var path = '\\\\\\\\?\\\\C:\\\\foo\\\\bar';\n    > var bool = RE.test( path )\n    true\n    > path = '\\\\\\\\?\\\\UNC\\\\server\\\\share';\n    > bool = RE.test( path )\n    true\n    > path = 'C:\\\\foo\\\\bar';\n    > bool = RE.test( path )\n    false\n    > path = '/c/foo/bar';\n    > bool = RE.test( path )\n    false\n    > path = '/foo/bar';\n    > bool = RE.test( path )\n    false\n\n\nreExtendedLengthPath.REGEXP\n    Regular expression to test if a string is an extended-length path.\n\n    Examples\n    --------\n    > var bool = reExtendedLengthPath.REGEXP.test( 'C:\\\\foo\\\\bar' )\n    false\n\n","reExtendedLengthPath.REGEXP":"\nreExtendedLengthPath.REGEXP\n    Regular expression to test if a string is an extended-length path.\n\n    Examples\n    --------\n    > var bool = reExtendedLengthPath.REGEXP.test( 'C:\\\\foo\\\\bar' )\n    false","reExtname":"\nreExtname( [platform] )\n    Returns a regular expression to capture a filename extension.\n\n    The regular expression is platform-dependent. If the current process is\n    running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n    `*.REGEXP_POSIX`.\n\n    Parameters\n    ----------\n    platform: string (optional)\n        Path platform (either `posix` or `win32`).\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reExtname()\n    <RegExp>\n    > var RE_POSIX = reExtname( 'posix' );\n    > var ext = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n    '.js'\n    > var RE_WIN32 = reExtname( 'win32' );\n    > ext = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    '.js'\n    > var str = RE.toString();\n    > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n    true\n\n\nreExtname.REGEXP\n    Regular expression to capture a filename extension.\n\n    Examples\n    --------\n    > var RE = reExtname.REGEXP\n    <RegExp>\n\n\nreExtname.REGEXP_POSIX\n    Regular expression to capture a POSIX filename extension.\n\n    Examples\n    --------\n    > var ext = reExtname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n    '.js'\n\n\nreExtname.REGEXP_WIN32\n    Regular expression to capture a Windows filename extension.\n\n    Examples\n    --------\n    > var ext = reExtname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    '.js'\n\n    See Also\n    --------\n    reExtnamePosix, reExtnameWindows, extname\n","reExtname.REGEXP":"\nreExtname.REGEXP\n    Regular expression to capture a filename extension.\n\n    Examples\n    --------\n    > var RE = reExtname.REGEXP\n    <RegExp>","reExtname.REGEXP_POSIX":"\nreExtname.REGEXP_POSIX\n    Regular expression to capture a POSIX filename extension.\n\n    Examples\n    --------\n    > var ext = reExtname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n    '.js'","reExtname.REGEXP_WIN32":"\nreExtname.REGEXP_WIN32\n    Regular expression to capture a Windows filename extension.\n\n    Examples\n    --------\n    > var ext = reExtname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    '.js'\n\n    See Also\n    --------\n    reExtnamePosix, reExtnameWindows, extname","reExtnamePosix":"\nreExtnamePosix\n    Returns a regular expression to capture a POSIX filename extension.\n\n    When executed against dotfile filenames (e.g., `.gitignore`), the regular\n    expression does not capture the basename as a filename extension.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reExtnamePosix();\n    > var ext = RE.exec( '/foo/bar/index.js' )[ 1 ]\n    '.js'\n    > ext = RE.exec( './foo/bar/.gitignore' )[ 1 ]\n    ''\n    > ext = RE.exec( 'foo/file.pdf' )[ 1 ]\n    '.pdf'\n    > ext = RE.exec( '/foo/bar/file' )[ 1 ]\n    ''\n    > ext = RE.exec( 'index.js' )[ 1 ]\n    '.js'\n    > ext = RE.exec( '.' )[ 1 ]\n    ''\n    > ext = RE.exec( './' )[ 1 ]\n    ''\n    > ext = RE.exec( '' )[ 1 ]\n    ''\n\n\nreExtnamePosix.REGEXP\n    Regular expression to capture a POSIX filename extension.\n\n    Examples\n    --------\n    > var ext = reExtnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n    '.js'\n\n    See Also\n    --------\n    reExtname, reExtnameWindows, extname\n","reExtnamePosix.REGEXP":"\nreExtnamePosix.REGEXP\n    Regular expression to capture a POSIX filename extension.\n\n    Examples\n    --------\n    > var ext = reExtnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n    '.js'\n\n    See Also\n    --------\n    reExtname, reExtnameWindows, extname","reExtnameWindows":"\nreExtnameWindows\n    Returns a regular expression to capture a Windows filename extension.\n\n    When executed against dotfile filenames (e.g., `.gitignore`), the regular\n    expression does not capture the basename as a filename extension.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reExtnameWindows();\n    > var ext = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    '.js'\n    > ext = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n    ''\n    > ext = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\n    '.pdf'\n    > ext = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\n    ''\n    > ext = RE.exec( 'beep\\\\boop.' )[ 1 ]\n    '.'\n    > ext = RE.exec( 'index.js' )[ 1 ]\n    '.js'\n    > ext = RE.exec( '' )[ 1 ]\n    ''\n\n\nreExtnameWindows.REGEXP\n    Regular expression to capture a Windows filename extension.\n\n    Examples\n    --------\n    > var ext = reExtnameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    '.js'\n\n    See Also\n    --------\n    reExtname, reExtnamePosix, extname\n","reExtnameWindows.REGEXP":"\nreExtnameWindows.REGEXP\n    Regular expression to capture a Windows filename extension.\n\n    Examples\n    --------\n    > var ext = reExtnameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    '.js'\n\n    See Also\n    --------\n    reExtname, reExtnamePosix, extname","reFilename":"\nreFilename( [platform] )\n    Regular expression to split a filename.\n\n    The regular expression is platform-dependent. If the current process is\n    running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n    `*.REGEXP_POSIX`.\n\n    Parameters\n    ----------\n    platform: string (optional)\n        Path platform (either `posix` or `win32`).\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reFilename()\n    <RegExp>\n    > var RE_POSIX = reFilename( 'posix' );\n    > var parts = RE_POSIX.exec( '/foo/bar/index.js' ).slice()\n    <Array>\n    > var RE_WIN32 = reFilename( 'win32' );\n    > parts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n    <Array>\n    > var str = RE.toString();\n    > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n    true\n\n\nreFilename.REGEXP\n    Regular expression to split a filename.\n\n    Examples\n    --------\n    > var RE = reFilename.REGEXP\n    <RegExp>\n\n\nreFilename.REGEXP_POSIX\n    Regular expression to split a POSIX filename.\n\n    When executed, the regular expression splits a POSIX filename into the\n    following parts:\n\n    - input value\n    - root\n    - dirname\n    - basename\n    - extname\n\n    Examples\n    --------\n    > var f = '/foo/bar/index.js';\n    > var parts = reFilename.REGEXP_POSIX.exec( f ).slice()\n    [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n\n\nreFilename.REGEXP_WIN32\n    Regular expression to split a Windows filename.\n\n    When executed, the regular expression splits a Windows filename into the\n    following parts:\n\n    - input value\n    - device\n    - slash\n    - dirname\n    - basename\n    - extname\n\n    Examples\n    --------\n    > var f = 'C:\\\\foo\\\\bar\\\\index.js';\n    > var parts = reFilename.REGEXP_WIN32.exec( f ).slice()\n    [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n    See Also\n    --------\n    reFilenamePosix, reFilenameWindows\n","reFilename.REGEXP":"\nreFilename.REGEXP\n    Regular expression to split a filename.\n\n    Examples\n    --------\n    > var RE = reFilename.REGEXP\n    <RegExp>","reFilename.REGEXP_POSIX":"\nreFilename.REGEXP_POSIX\n    Regular expression to split a POSIX filename.\n\n    When executed, the regular expression splits a POSIX filename into the\n    following parts:\n\n    - input value\n    - root\n    - dirname\n    - basename\n    - extname\n\n    Examples\n    --------\n    > var f = '/foo/bar/index.js';\n    > var parts = reFilename.REGEXP_POSIX.exec( f ).slice()\n    [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]","reFilename.REGEXP_WIN32":"\nreFilename.REGEXP_WIN32\n    Regular expression to split a Windows filename.\n\n    When executed, the regular expression splits a Windows filename into the\n    following parts:\n\n    - input value\n    - device\n    - slash\n    - dirname\n    - basename\n    - extname\n\n    Examples\n    --------\n    > var f = 'C:\\\\foo\\\\bar\\\\index.js';\n    > var parts = reFilename.REGEXP_WIN32.exec( f ).slice()\n    [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n    See Also\n    --------\n    reFilenamePosix, reFilenameWindows","reFilenamePosix":"\nreFilenamePosix()\n    Returns a regular expression to split a POSIX filename.\n\n    When executed, the regular expression splits a POSIX filename into the\n    following parts:\n\n    - input value\n    - root\n    - dirname\n    - basename\n    - extname\n\n    When executed against dotfile filenames (e.g., `.gitignore`), the regular\n    expression does not capture the basename as a filename extension.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reFilenamePosix();\n    > var parts = RE.exec( '/foo/bar/index.js' ).slice()\n    [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n    > parts = RE.exec( './foo/bar/.gitignore' ).slice()\n    [ './foo/bar/.gitignore', '', './foo/bar/', '.gitignore', '' ]\n    > parts = RE.exec( 'foo/file.pdf' ).slice()\n    [ 'foo/file.pdf', '', 'foo/', 'file.pdf', '.pdf' ]\n    > parts = RE.exec( '/foo/bar/file' ).slice()\n    [ '/foo/bar/file', '/', 'foo/bar/', 'file', '' ]\n    > parts = RE.exec( 'index.js' ).slice()\n    [ 'index.js', '', '', 'index.js', '.js' ]\n    > parts = RE.exec( '.' ).slice()\n    [ '.', '', '', '.', '' ]\n    > parts = RE.exec( './' ).slice()\n    [ './', '', ..., '.', '' ]\n    > parts = RE.exec( '' ).slice()\n    [ '', '', '', '', '' ]\n\n\nreFilenamePosix.REGEXP\n    Regular expression to split a POSIX filename.\n\n    Examples\n    --------\n    > var parts = reFilenamePosix.REGEXP.exec( '/foo/bar/index.js' ).slice()\n    [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n\n    See Also\n    --------\n    reFilename, reFilenameWindows\n","reFilenamePosix.REGEXP":"\nreFilenamePosix.REGEXP\n    Regular expression to split a POSIX filename.\n\n    Examples\n    --------\n    > var parts = reFilenamePosix.REGEXP.exec( '/foo/bar/index.js' ).slice()\n    [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n\n    See Also\n    --------\n    reFilename, reFilenameWindows","reFilenameWindows":"\nreFilenameWindows()\n    Returns a regular expression to split a Windows filename.\n\n    When executed, the regular expression splits a Windows filename into the\n    following parts:\n\n    - input value\n    - device\n    - slash\n    - dirname\n    - basename\n    - extname\n\n    When executed against dotfile filenames (e.g., `.gitignore`), the regular\n    expression does not capture the basename as a filename extension.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reFilenameWindows();\n    > var parts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n    [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n    > parts = RE.exec( '\\\\foo\\\\bar\\\\.gitignore' ).slice()\n    [ '\\\\foo\\\\bar\\\\.gitignore', '', '\\\\', 'foo\\\\bar\\\\', '.gitignore', '' ]\n    > parts = RE.exec( 'foo\\\\file.pdf' ).slice()\n    [ 'foo\\\\file.pdf', '', '', 'foo\\\\', 'file.pdf', '.pdf' ]\n    > parts = RE.exec( '\\\\foo\\\\bar\\\\file' ).slice()\n    [ '\\\\foo\\\\bar\\\\file', '', '\\\\', 'foo\\\\bar\\\\', 'file', '' ]\n    > parts = RE.exec( 'index.js' ).slice()\n    [ 'index.js', '', '', '', 'index.js', '.js' ]\n    > parts = RE.exec( '.' ).slice()\n    [ '.', '', '', '', '.', '' ]\n    > parts = RE.exec( './' ).slice()\n    [ './', '', ..., '.', '' ]\n    > parts = RE.exec( '' ).slice()\n    [ '', '', '', '', '', '' ]\n\n\nreFilenameWindows.REGEXP\n    Regular expression to split a Windows filename.\n\n    Examples\n    --------\n    > var parts = reFilenameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n    [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n    See Also\n    --------\n    reFilename, reFilenamePosix","reFilenameWindows.REGEXP":"\nreFilenameWindows.REGEXP\n    Regular expression to split a Windows filename.\n\n    Examples\n    --------\n    > var parts = reFilenameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n    [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n    See Also\n    --------\n    reFilename, reFilenamePosix","reFromString":"\nreFromString( str )\n    Parses a regular expression string and returns a new regular expression.\n\n    Provided strings should be properly escaped.\n\n    If unable to parse a string as a regular expression, the function returns\n    `null`.\n\n    Parameters\n    ----------\n    str: string\n        Regular expression string.\n\n    Returns\n    -------\n    out: RegExp|null\n        Regular expression or null.\n\n    Examples\n    --------\n    > var re = reFromString( '/beep/' )\n    /beep/\n    > re = reFromString( '/beep' )\n    null\n\n","reFunctionName":"\nreFunctionName()\n    Return a regular expression to capture a function name.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE_FUNCTION_NAME = reFunctionName();\n    > function beep() { return 'boop'; };\n    > var name = RE_FUNCTION_NAME.exec( beep.toString() )[ 1 ]\n    'beep'\n    > name = RE_FUNCTION_NAME.exec( function () {} )[ 1 ]\n    ''\n\n\nreFunctionName.REGEXP\n    Regular expression to capture a function name.\n\n    Examples\n    --------\n    > var str = reFunctionName.REGEXP.exec( Math.sqrt.toString() )[ 1 ]\n    'sqrt'\n\n    See Also\n    --------\n    functionName\n","reFunctionName.REGEXP":"\nreFunctionName.REGEXP\n    Regular expression to capture a function name.\n\n    Examples\n    --------\n    > var str = reFunctionName.REGEXP.exec( Math.sqrt.toString() )[ 1 ]\n    'sqrt'\n\n    See Also\n    --------\n    functionName","regexp2json":"\nregexp2json( re )\n    Returns a JSON representation of a regular expression.\n\n    Parameters\n    ----------\n    re: RegExp\n        Regular expression to serialize.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n        \n    out.type: string\n        Value type. The assigned value is always 'RegExp'.\n        \n    out.pattern: string\n        Regular expression pattern.\n        \n    out.flags: string\n        Regular expression flags.\n\n    Examples\n    --------\n    > var json = regexp2json( /ab+c/ )\n    {...}\n\n    See Also\n    --------\n    reviveRegExp    \n","reim":"\nreim( z )\n    Returns the real and imaginary components of a double-precision complex\n    floating-point number.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Float64Array\n        Array containing the real and imaginary components, respectively.\n\n    Examples\n    --------\n    > var z = new Complex128( 5.0, 3.0 );\n    > var out = reim( z )\n    <Float64Array>[ 5.0, 3.0 ]\n\n    See Also\n    --------\n    imag, real\n","reimf":"\nreimf( z )\n    Returns the real and imaginary components of a single-precision complex\n    floating-point number.\n\n    Parameters\n    ----------\n    z: Complex64\n        Complex number.\n\n    Returns\n    -------\n    out: Float32Array\n        Array containing the real and imaginary components, respectively.\n\n    Examples\n    --------\n    > var z = new Complex64( 5.0, 3.0 );\n    > var out = reimf( z )\n    <Float32Array>[ 5.0, 3.0 ]\n\n    See Also\n    --------\n    imagf, realf, reim\n","rejectArguments":"\nrejectArguments( fcn, predicate[, thisArg] )\n    Returns a function that applies arguments to a provided function according\n    to a predicate function.\n\n    Only those arguments in which the predicate function returns a falsy value\n    are applied to a provided function.\n\n    The predicate function is provided the following arguments:\n\n    - value: argument value.\n    - index: argument index.\n\n    Parameters\n    ----------\n    fcn: Function\n        Input function.\n\n    predicate: Function\n        Predicate function.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Function\n        Function wrapper.\n\n    Examples\n    --------\n    > function foo( a, b ) { return [ a, b ]; };\n    > function predicate( v ) { return ( v === 2 ); };\n    > var bar = rejectArguments( foo, predicate );\n    > var out = bar( 1, 2, 3 )\n    [ 1, 3 ]\n\n    See Also\n    --------\n    filterArguments, maskArguments\n","removeFirst":"\nremoveFirst( str[, n][, options] )\n    Removes the first character(s) of a `string`.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer (optional)\n        Number of characters to remove. Default: 1.\n\n    options: Object (optional)\n        Options.\n\n    options.mode: string (optional)\n        Type of characters to return. The following modes are supported:\n\n        - grapheme: grapheme clusters. Appropriate for strings containing visual\n          characters which can span multiple Unicode code points (e.g., emoji).\n        - code_point: Unicode code points. Appropriate for strings containing\n          visual characters which are comprised of more than one Unicode code\n          unit (e.g., ideographic symbols and punctuation and mathematical\n          alphanumerics).\n        - code_unit': UTF-16 code units. Appropriate for strings containing\n          visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n          common characters, such as those from the Latin, Greek, and Cyrillic\n          alphabets).\n\n        Default: 'grapheme'.\n\n    Returns\n    -------\n    out: string\n        Updated string.\n\n    Examples\n    --------\n    > var out = removeFirst( 'beep' )\n    'eep'\n    > out = removeFirst( 'Boop' )\n    'oop'\n    > out = removeFirst( 'foo bar', 4 )\n    'bar'\n\n    See Also\n    --------\n    removeLast\n","removeLast":"\nremoveLast( str[, n][, options] )\n    Removes the last character(s) of a `string`.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer (optional)\n        Number of characters to remove. Default: 1.\n\n    options: Object (optional)\n        Options.\n\n    options.mode: string (optional)\n        Type of characters to remove. The following modes are supported:\n\n        - grapheme: grapheme clusters. Appropriate for strings containing visual\n          characters which can span multiple Unicode code points (e.g., emoji).\n        - code_point: Unicode code points. Appropriate for strings containing\n          visual characters which are comprised of more than one Unicode code\n          unit (e.g., ideographic symbols and punctuation and mathematical\n          alphanumerics).\n        - code_unit': UTF-16 code units. Appropriate for strings containing\n          visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n          common characters, such as those from the Latin, Greek, and Cyrillic\n          alphabets).\n\n        Default: 'grapheme'.\n\n    Returns\n    -------\n    out: string\n        Updated string.\n\n    Examples\n    --------\n    > var out = removeLast( 'beep' )\n    'bee'\n    > out = removeLast( 'Boop' )\n    'Boo'\n    > out = removeLast( 'foo bar', 4 )\n    'foo'\n\n    See Also\n    --------\n    removeFirst\n","removePunctuation":"\nremovePunctuation( str )\n    Removes punctuation characters from a `string`.\n\n    The function removes the following characters:\n\n    - Apostrophe: `\n    - Braces : { }\n    - Brackets: [ ]\n    - Colon: :\n    - Comma: ,\n    - Exclamation Mark: !\n    - Fraction Slash: /\n    - Guillemets: < >\n    - Parentheses: ( )\n    - Period: .\n    - Semicolon: ;\n    - Tilde: ~\n    - Vertical Bar: |\n    - Question Mark: ?\n    - Quotation Marks: ' \"\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        String with punctuation characters removed.\n\n    Examples\n    --------\n    > var str = 'Sun Tzu said: \"A leader leads by example not by force.\"';\n    > var out = removePunctuation( str )\n    'Sun Tzu said A leader leads by example not by force'\n\n    > str = 'This function removes these characters: `{}[]:,!/<>().;~|?\\'\"';\n    > out = removePunctuation( str )\n    'This function removes these characters '\n\n","removeUTF8BOM":"\nremoveUTF8BOM( str )\n    Removes a UTF-8 byte order mark (BOM) from the beginning of a `string`.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        String with BOM removed.\n\n    Examples\n    --------\n    > var out = removeUTF8BOM( '\\ufeffbeep' )\n    'beep'\n\n","removeWords":"\nremoveWords( str, words[, ignoreCase] )\n    Removes all occurrences of the given words from a `string`.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    words: Array<string>\n        Array of words to be removed.\n\n    ignoreCase: boolean (optional)\n        Boolean indicating whether to perform a case-insensitive operation.\n        Default: `false`.\n\n    Returns\n    -------\n    out: string\n        String with words removed.\n\n    Examples\n    --------\n    > var out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ] )\n    'beep  Foo bar'\n\n    // Case-insensitive:\n    > out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ], true )\n    'beep   bar'\n\n","rename":"\nrename( oldPath, newPath, clbk )\n    Asynchronously renames a file.\n\n    The old path can specify a directory. In this case, the new path must either\n    not exist, or it must specify an empty directory.\n\n    The old pathname should not name an ancestor directory of the new pathname.\n\n    If the old path points to the pathname of a file that is not a directory,\n    the new path should not point to the pathname of a directory.\n\n    Write access permission is required for both the directory containing the\n    old path and the directory containing the new path.\n\n    If the link named by the new path exists, the new path is removed and the\n    old path is renamed to the new path. The link named by the new path will\n    remain visible to other threads throughout the renaming operation and refer\n    to either the file referred to by the new path or to the file referred to by\n    the old path before the operation began.\n\n    If the old path and the new path resolve to either the same existing\n    directory entry or to different directory entries for the same existing\n    file, no action is taken, and no error is returned.\n\n    If the old path points to a pathname of a symbolic link, the symbolic link\n    is renamed. If the new path points to a pathname of a symbolic link, the\n    symbolic link is removed.\n\n    If a link named by the new path exists and the file's link count becomes 0\n    when it is removed and no process has the file open, the space occupied by\n    the file is freed and the file is no longer accessible. If one or more\n    processes have the file open when the last link is removed, the link is\n    removed before the function returns, but the removal of file contents is\n    postponed until all references to the file are closed.\n\n    Parameters\n    ----------\n    oldPath: string|Buffer\n        Old path.\n\n    newPath: string|Buffer\n        New path.\n\n    clbk: Function\n        Callback to invoke upon renaming a file.\n\n    Examples\n    --------\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     }\n    ... };\n    > rename( './beep/boop.txt', './beep/foo.txt', done );\n\n\nrename.sync( oldPath, newPath )\n    Synchronously renames a file.\n\n    Parameters\n    ----------\n    oldPath: string|Buffer\n        Old path.\n\n    newPath: string|Buffer\n        New path.\n\n    Returns\n    -------\n    err: Error|null\n        Error object or null.\n\n    Examples\n    --------\n    > var err = rename.sync( './beep/boop.txt', './beep/foo.txt' );\n\n    See Also\n    --------\n    exists, readFile, writeFile, unlink\n","rename.sync":"\nrename.sync( oldPath, newPath )\n    Synchronously renames a file.\n\n    Parameters\n    ----------\n    oldPath: string|Buffer\n        Old path.\n\n    newPath: string|Buffer\n        New path.\n\n    Returns\n    -------\n    err: Error|null\n        Error object or null.\n\n    Examples\n    --------\n    > var err = rename.sync( './beep/boop.txt', './beep/foo.txt' );\n\n    See Also\n    --------\n    exists, readFile, writeFile, unlink","reNativeFunction":"\nreNativeFunction()\n    Returns a regular expression to match a native function.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reNativeFunction();\n    > var bool = RE.test( Date.toString() )\n    true\n    > bool = RE.test( (function noop() {}).toString() )\n    false\n\n\nreNativeFunction.REGEXP\n    Regular expression to match a native function.\n\n    Examples\n    --------\n    > var bool = reNativeFunction.REGEXP.test( Date.toString() )\n    true\n    > bool = reNativeFunction.REGEXP.test( (function noop() {}).toString() )\n    false\n\n    See Also\n    --------\n    reFunctionName, functionName\n","reNativeFunction.REGEXP":"\nreNativeFunction.REGEXP\n    Regular expression to match a native function.\n\n    Examples\n    --------\n    > var bool = reNativeFunction.REGEXP.test( Date.toString() )\n    true\n    > bool = reNativeFunction.REGEXP.test( (function noop() {}).toString() )\n    false\n\n    See Also\n    --------\n    reFunctionName, functionName","reorderArguments":"\nreorderArguments( fcn, indices[, thisArg] )\n    Returns a function that invokes a provided function with reordered\n    arguments.\n\n    Parameters\n    ----------\n    fcn: Function\n        Input function.\n\n    indices: Array<integer>\n        Argument indices.\n\n    thisArg: any (optional)\n        Function context.\n\n    Returns\n    -------\n    out: Function\n        Function with reordered arguments.\n\n    Examples\n    --------\n    > function foo( a, b, c ) { return [ a, b, c ]; };\n    > var bar = reorderArguments( foo, [ 2, 0, 1 ] );\n    > var out = bar( 1, 2, 3 )\n    [ 3, 1, 2 ]\n\n    See Also\n    --------\n    maskArguments, reverseArguments\n","repeat":"\nrepeat( str, n )\n    Repeats a string `n` times and returns the concatenated result.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of repetitions.\n\n    Returns\n    -------\n    out: string\n        Repeated string.\n\n    Examples\n    --------\n    > var out = repeat( 'a', 5 )\n    'aaaaa'\n    > out = repeat( '', 100 )\n    ''\n    > out = repeat( 'beep', 0 )\n    ''\n\n    See Also\n    --------\n    pad\n","replace":"\nreplace( str, search, newval )\n    Replaces search occurrences with a replacement string.\n\n    When provided a string as the search value, the function replaces *all*\n    occurrences. To remove only the first match, use a regular expression.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string|RegExp\n        Search expression.\n\n    newval: string|Function\n        Replacement value or function.\n\n    Returns\n    -------\n    out: string\n        String containing replacement(s).\n\n    Examples\n    --------\n    // Standard usage:\n    > var out = replace( 'beep', 'e', 'o' )\n    'boop'\n\n    // Replacer function:\n    > function replacer( match, p1 ) { return '/'+p1+'/'; };\n    > var str = 'Oranges and lemons';\n    > out = replace( str, /([^\\s]+)/gi, replacer )\n    '/Oranges/ /and/ /lemons/'\n\n    // Replace only first match:\n    > out = replace( 'beep', /e/, 'o' )\n    'boep'\n\n","replaceBefore":"\nreplaceBefore( str, search, replacement )\n    Replaces the substring before the first occurrence of a specified search\n    string. \n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search string.\n    \n    replacement: string\n        Replacement string.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var str = 'beep boop';\n    > var out = replaceBefore( str, ' ', 'foo' )\n    'foo boop'\n    > out = replaceBefore( str, 'o', 'foo' )\n    'foooop'\n\n","reRegExp":"\nreRegExp()\n    Returns a regular expression to parse a regular expression string.\n\n    Regular expression strings should be escaped.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reRegExp();\n    > var bool = RE.test( '/^beep$/' )\n    true\n    > bool = RE.test( '/boop' )\n    false\n\n    // Escape regular expression strings:\n    > bool = RE.test( '/^\\/([^\\/]+)\\/(.*)$/' )\n    false\n    > bool = RE.test( '/^\\\\/([^\\\\/]+)\\\\/(.*)$/' )\n    true\n\n\nreRegExp.REGEXP\n    Regular expression to parse a regular expression string.\n\n    Examples\n    --------\n    > var bool = reRegExp.REGEXP.test( '/^beep$/' )\n    true\n    > bool = reRegExp.REGEXP.test( '/boop' )\n    false\n\n    See Also\n    --------\n    reFromString\n","reRegExp.REGEXP":"\nreRegExp.REGEXP\n    Regular expression to parse a regular expression string.\n\n    Examples\n    --------\n    > var bool = reRegExp.REGEXP.test( '/^beep$/' )\n    true\n    > bool = reRegExp.REGEXP.test( '/boop' )\n    false\n\n    See Also\n    --------\n    reFromString","rescape":"\nrescape( str )\n    Escapes a regular expression string.\n\n    Parameters\n    ----------\n    str: string\n        Regular expression string.\n\n    Returns\n    -------\n    out: string\n        Escaped string.\n\n    Examples\n    --------\n    > var str = rescape( '[A-Z]*' )\n    '\\\\[A\\\\-Z\\\\]\\\\*'\n\n","reSemVer":"\nreSemVer()\n    Returns a regular expression to match a semantic version string.\n\n    Returns\n    -------\n    out: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE_SEMVER = reSemVer()\n    <RegExp>\n    > var bool = RE_SEMVER.test( '1.0.0' )\n    true\n    > bool = RE_SEMVER.test( '1.0.0-alpha.1' )\n    true\n    > bool = RE_SEMVER.test( 'abc' )\n    false\n    > bool = RE_SEMVER.test( '1.0.0-alpha.1+build.1' )\n    true\n\n\nreSemVer.REGEXP\n    Regular expression to match a semantic version string.\n\n    Examples\n    --------\n    > var bool = reSemVer.REGEXP.test( '1.0.0' )\n    true\n    > bool = reSemVer.REGEXP.test( '-1.0.0-alpha.1' )\n    false\n\n\n    See Also\n    --------\n    isSemVer","reSemVer.REGEXP":"\nreSemVer.REGEXP\n    Regular expression to match a semantic version string.\n\n    Examples\n    --------\n    > var bool = reSemVer.REGEXP.test( '1.0.0' )\n    true\n    > bool = reSemVer.REGEXP.test( '-1.0.0-alpha.1' )\n    false\n\n\n    See Also\n    --------\n    isSemVer","resolveParentPath":"\nresolveParentPath( path[, options], clbk )\n    Asynchronously resolves a path by walking parent directories.\n\n    If unable to resolve a path, the function returns `null` as the path result.\n\n    Parameters\n    ----------\n    path: string\n        Path to resolve.\n\n    options: Object (optional)\n        Options.\n\n    options.dir: string (optional)\n        Base directory from which to search. Default: current working directory.\n\n    clbk: Function\n        Callback to invoke after resolving a path.\n\n    Examples\n    --------\n    > function onPath( error, path ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     } else {\n    ...         console.log( path );\n    ...     }\n    ... };\n    > resolveParentPath( 'package.json', onPath );\n\n\nresolveParentPath.sync( path[, options] )\n    Synchronously resolves a path by walking parent directories.\n\n    Parameters\n    ----------\n    path: string\n        Path to resolve.\n\n    options: Object (optional)\n        Options.\n\n    options.dir: string (optional)\n        Base directory from which to search. Default: current working directory.\n\n    Returns\n    -------\n    out: string|null\n        Resolved path.\n\n    Examples\n    --------\n    > var out = resolveParentPath.sync( 'package.json' );\n\n    See Also\n    --------\n    resolveParentPathBy\n","resolveParentPath.sync":"\nresolveParentPath.sync( path[, options] )\n    Synchronously resolves a path by walking parent directories.\n\n    Parameters\n    ----------\n    path: string\n        Path to resolve.\n\n    options: Object (optional)\n        Options.\n\n    options.dir: string (optional)\n        Base directory from which to search. Default: current working directory.\n\n    Returns\n    -------\n    out: string|null\n        Resolved path.\n\n    Examples\n    --------\n    > var out = resolveParentPath.sync( 'package.json' );\n\n    See Also\n    --------\n    resolveParentPathBy","resolveParentPathBy":"\nresolveParentPathBy( path[, options], predicate, clbk )\n    Asynchronously resolves a path according to a predicate function by walking\n    parent directories.\n\n    When invoked, the predicate function is provided two arguments:\n\n    - path: a resolved path.\n    - next: a callback to be invoked after processing a resolved path.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - result: test result.\n\n    If a provided predicate function calls the `next` callback with a truthy\n    `error` argument, the function suspends execution and immediately calls the\n    `done` callback for subsequent `error` handling.\n\n    The function immediately returns upon encountering a non-falsy `result`\n    value and calls the `done` callback with `null` as the first argument and\n    the resolved path as the second argument.\n\n    If unable to resolve a path, the function returns `null` as the path result.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Parameters\n    ----------\n    path: string\n        Path to resolve.\n\n    options: Object (optional)\n        Options.\n\n    options.dir: string (optional)\n        Base directory from which to search. Default: current working directory.\n\n    predicate: Function\n        The test function to invoke for each resolved path.\n\n    clbk: Function\n        Callback to invoke after resolving a path.\n\n    Examples\n    --------\n    > function predicate( path, next ) {\n    ...     setTimeout( onTimeout, path );\n    ...     function onTimeout() {\n    ...         console.log( path );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function onPath( error, path ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     } else {\n    ...         console.log( path );\n    ...     }\n    ... };\n    > resolveParentPathBy( 'package.json', predicate, onPath );\n\n\nresolveParentPathBy.sync( path[, options], predicate )\n    Synchronously resolves a path according to a predicate function by walking\n    parent directories.\n\n    The predicate function is provided one argument:\n\n    - path: a resolved path.\n\n    The function immediately returns upon encountering a truthy return value.\n\n    If unable to resolve a path, the function returns `null` as the path result.\n\n    Parameters\n    ----------\n    path: string\n        Path to resolve.\n\n    options: Object (optional)\n        Options.\n\n    options.dir: string (optional)\n        Base directory from which to search. Default: current working directory.\n\n    predicate: Function\n        The test function to invoke for each resolved path.\n\n    Returns\n    -------\n    out: string|null\n        Resolved path.\n\n    Examples\n    --------\n    > function predicate() { return false; };\n    > var out = resolveParentPathBy.sync( 'package.json', predicate );\n\n    See Also\n    --------\n    resolveParentPath\n","resolveParentPathBy.sync":"\nresolveParentPathBy.sync( path[, options], predicate )\n    Synchronously resolves a path according to a predicate function by walking\n    parent directories.\n\n    The predicate function is provided one argument:\n\n    - path: a resolved path.\n\n    The function immediately returns upon encountering a truthy return value.\n\n    If unable to resolve a path, the function returns `null` as the path result.\n\n    Parameters\n    ----------\n    path: string\n        Path to resolve.\n\n    options: Object (optional)\n        Options.\n\n    options.dir: string (optional)\n        Base directory from which to search. Default: current working directory.\n\n    predicate: Function\n        The test function to invoke for each resolved path.\n\n    Returns\n    -------\n    out: string|null\n        Resolved path.\n\n    Examples\n    --------\n    > function predicate() { return false; };\n    > var out = resolveParentPathBy.sync( 'package.json', predicate );\n\n    See Also\n    --------\n    resolveParentPath","reUncPath":"\nreUncPath()\n    Return a regular expression to parse a UNC path.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reUncPath();\n    > var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\n    > var bool = RE.test( path )\n    true\n    > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\n    > bool = RE.test( path )\n    true\n    > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a';\n    > bool = RE.test( path )\n    true\n    > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz';\n    > bool = RE.test( path )\n    true\n    > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar';\n    > bool = RE.test( path )\n    true\n    > path = '\\\\\\\\server\\\\share\\\\foo';\n    > bool = RE.test( path )\n    true\n    > path = '\\\\\\\\server\\\\share';\n    > bool = RE.test( path )\n    true\n    > path = '\\\\\\\\server\\\\\\\\share';\n    > bool = RE.test( path )\n    false\n    > path = '\\\\\\\\\\\\\\\\server\\\\share';\n    > bool = RE.test( path )\n    false\n    > path = 'beep boop \\\\\\\\server\\\\share';\n    > bool = RE.test( path )\n    false\n    > path = '\\\\\\\\server';\n    > bool = RE.test( path )\n    false\n    > path = '\\\\';\n    > bool = RE.test( path )\n    false\n    > path = '';\n    > bool = RE.test( path )\n    false\n    > path = '\\\\\\\\server\\\\share\\\\';\n    > bool = RE.test( path )\n    false\n    > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:';\n    > bool = RE.test( path )\n    false\n    > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:';\n    > bool = RE.test( path )\n    false\n    > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::';\n    > bool = RE.test( path )\n    false\n    > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b:c';\n    > bool = RE.test( path )\n    false\n    > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\';\n    > bool = RE.test( path )\n    false\n    > path = '//server/share';\n    > bool = RE.test( path )\n    false\n    > path = '/foo/bar';\n    > bool = RE.test( path )\n    false\n    > path = 'foo/bar';\n    > bool = RE.test( path )\n    false\n    > path = './foo/bar';\n    > bool = RE.test( path )\n    false\n    > path = '/foo/../bar';\n    > bool = RE.test( path )\n    false\n\n\nreUncPath.REGEXP\n    Regular expression to parse a UNC path.\n\n    Examples\n    --------\n    > var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\n    > var bool = reUncPath.REGEXP.test( path )\n    true\n    > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\n    > bool = reUncPath.REGEXP.test( path )\n    true\n\n    See Also\n    --------\n    isUNCPath\n","reUncPath.REGEXP":"\nreUncPath.REGEXP\n    Regular expression to parse a UNC path.\n\n    Examples\n    --------\n    > var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\n    > var bool = reUncPath.REGEXP.test( path )\n    true\n    > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\n    > bool = reUncPath.REGEXP.test( path )\n    true\n\n    See Also\n    --------\n    isUNCPath","reUtf16SurrogatePair":"\nreUtf16SurrogatePair()\n    Returns a regular expression to match a UTF-16 surrogate pair.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reUtf16SurrogatePair();\n    > var bool = RE.test( 'abc\\uD800\\uDC00def' )\n    true\n    > bool = RE.test( 'abcdef' )\n    false\n\n\nreUtf16SurrogatePair.REGEXP\n    Regular expression to match a UTF-16 surrogate pair.\n\n    Examples\n    --------\n    > var RE = reUtf16SurrogatePair.REGEXP;\n    > var bool = RE.test( 'abc\\uD800\\uDC00def' )\n    true\n    > bool = RE.test( 'abcdef' )\n    false\n\n    See Also\n    --------\n    reUtf16UnpairedSurrogate","reUtf16SurrogatePair.REGEXP":"\nreUtf16SurrogatePair.REGEXP\n    Regular expression to match a UTF-16 surrogate pair.\n\n    Examples\n    --------\n    > var RE = reUtf16SurrogatePair.REGEXP;\n    > var bool = RE.test( 'abc\\uD800\\uDC00def' )\n    true\n    > bool = RE.test( 'abcdef' )\n    false\n\n    See Also\n    --------\n    reUtf16UnpairedSurrogate","reUtf16UnpairedSurrogate":"\nreUtf16UnpairedSurrogate()\n    Returns a regular expression to match an unpaired UTF-16 surrogate.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reUtf16UnpairedSurrogate();\n    > var bool = RE.test( 'abc' )\n    false\n    > bool = RE.test( '\\uD800' )\n    true\n\n\nreUtf16UnpairedSurrogate.REGEXP\n    Regular expression to match an unpaired UTF-16 surrogate.\n\n    Examples\n    --------\n    > var RE = reUtf16UnpairedSurrogate.REGEXP;\n    > var bool = RE.test( 'abc' )\n    false\n    > bool = RE.test( '\\uD800' )\n    true\n\n    See Also\n    --------\n    reUtf16SurrogatePair","reUtf16UnpairedSurrogate.REGEXP":"\nreUtf16UnpairedSurrogate.REGEXP\n    Regular expression to match an unpaired UTF-16 surrogate.\n\n    Examples\n    --------\n    > var RE = reUtf16UnpairedSurrogate.REGEXP;\n    > var bool = RE.test( 'abc' )\n    false\n    > bool = RE.test( '\\uD800' )\n    true\n\n    See Also\n    --------\n    reUtf16SurrogatePair","reverseArguments":"\nreverseArguments( fcn[, thisArg] )\n    Returns a function that invokes a provided function with arguments in\n    reverse order.\n\n    Parameters\n    ----------\n    fcn: Function\n        Input function.\n\n    thisArg: any (optional)\n        Function context.\n\n    Returns\n    -------\n    out: Function\n        Function with reversed arguments.\n\n    Examples\n    --------\n    > function foo( a, b, c ) { return [ a, b, c ]; };\n    > var bar = reverseArguments( foo );\n    > var out = bar( 1, 2, 3 )\n    [ 3, 2, 1 ]\n\n    See Also\n    --------\n    maskArguments, reorderArguments\n","reverseString":"\nreverseString( str[, options] )\n    Reverses a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    options: Object (optional)\n        Options.\n\n    options.mode: string (optional)\n        Type of characters to reverse. The following modes are supported:\n\n        - grapheme: grapheme clusters. Appropriate for strings containing visual\n          characters which can span multiple Unicode code points (e.g., emoji).\n        - code_point: Unicode code points. Appropriate for strings containing\n          visual characters which are comprised of more than one Unicode code\n          unit (e.g., ideographic symbols and punctuation and mathematical\n          alphanumerics).\n        - code_unit': UTF-16 code units. Appropriate for strings containing\n          visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n          common characters, such as those from the Latin, Greek, and Cyrillic\n          alphabets).\n\n        Default: 'grapheme'.\n\n    Returns\n    -------\n    out: string\n        Reversed string.\n\n    Examples\n    --------\n    > var out = reverseString( 'foo' )\n    'oof'\n    > out = reverseString( 'abcdef' )\n    'fedcba'\n\n","reviveBasePRNG":"\nreviveBasePRNG( key, value )\n    Revives a JSON-serialized pseudorandom number generator (PRNG).\n\n    Parameters\n    ----------\n    key: string\n        Key.\n\n    value: any\n        Value.\n\n    Returns\n    -------\n    out: any\n        Value or PRNG.\n\n    Examples\n    --------\n    > var str = JSON.stringify( base.random.mt19937 );\n    > var r = parseJSON( str, reviveBasePRNG )\n    <Function>\n\n","reviveBuffer":"\nreviveBuffer( key, value )\n    Revives a JSON-serialized Buffer.\n\n    The serialization format for a Buffer is an object having the following\n    fields:\n\n    - type: value type (Buffer).\n    - data: buffer data as an array of integers.\n\n    Parameters\n    ----------\n    key: string\n        Key.\n\n    value: any\n        Value.\n\n    Returns\n    -------\n    out: any\n        Value or Buffer.\n\n    Examples\n    --------\n    > var str = '{\"type\":\"Buffer\",\"data\":[5,3]}';\n    > var buf = parseJSON( str, reviveBuffer )\n    <Buffer>[ 5, 3 ]\n\n    See Also\n    --------\n    buffer2json\n","reviveComplex":"\nreviveComplex( key, value )\n    Revives a JSON-serialized complex number.\n\n    The serialization format for complex numbers is an object having the\n    following fields:\n\n    - type: complex number type (e.g., \"Complex128\", \"Complex64\").\n    - re: real component (number).\n    - im: imaginary component (number).\n\n    Parameters\n    ----------\n    key: string\n        Key.\n\n    value: any\n        Value.\n\n    Returns\n    -------\n    out: any\n        Value or complex number.\n\n    Examples\n    --------\n    > var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\n    > var z = parseJSON( str, reviveComplex )\n    <Complex128>\n\n    See Also\n    --------\n    Complex128, Complex64, reviveComplex128, reviveComplex64\n","reviveComplex64":"\nreviveComplex64( key, value )\n    Revives a JSON-serialized 64-bit complex number.\n\n    Parameters\n    ----------\n    key: string\n        Key.\n\n    value: any\n        Value.\n\n    Returns\n    -------\n    out: any\n        Value or complex number.\n\n    Examples\n    --------\n    > var str = '{\"type\":\"Complex64\",\"re\":5,\"im\":3}';\n    > var z = parseJSON( str, reviveComplex64 )\n    <Complex64>\n\n    See Also\n    --------\n    Complex64, reviveComplex128, reviveComplex\n","reviveComplex128":"\nreviveComplex128( key, value )\n    Revives a JSON-serialized 128-bit complex number.\n\n    Parameters\n    ----------\n    key: string\n        Key.\n\n    value: any\n        Value.\n\n    Returns\n    -------\n    out: any\n        Value or complex number.\n\n    Examples\n    --------\n    > var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\n    > var z = parseJSON( str, reviveComplex128 )\n    <Complex128>\n\n    See Also\n    --------\n    Complex128, reviveComplex64, reviveComplex\n","reviveError":"\nreviveError( key, value )\n    Revives a JSON-serialized error object.\n\n    The following built-in error types are supported:\n\n    - Error\n    - URIError\n    - ReferenceError\n    - SyntaxError\n    - RangeError\n    - EvalError\n    - TypeError\n\n    Parameters\n    ----------\n    key: string\n        Key.\n\n    value: any\n        Value.\n\n    Returns\n    -------\n    out: any\n        Value or error object.\n\n    Examples\n    --------\n    > var str = '{\"type\":\"TypeError\",\"message\":\"beep\"}';\n    > var err = JSON.parse( str, reviveError )\n    <TypeError>\n\n    See Also\n    --------\n    error2json\n","reviveRegExp":"\nreviveRegExp( key, value )\n    Revives a JSON-serialized regular expression.\n\n    The serialization format for a regular expression is an object having the\n    following fields:\n\n    - type: value type (RegExp).\n    - pattern: regular expression pattern.\n    - flags: regular expression flags.\n\n    Parameters\n    ----------\n    key: string\n        Key.\n\n    value: any\n        Value.\n\n    Returns\n    -------\n    out: any\n        Value or regular expression.\n\n    Examples\n    --------\n    > var str = '{\"type\":\"RegExp\",\"pattern\":\"ab+c\",\"flags\":\"\"}';\n    > var v = parseJSON( str, reviveRegExp )\n    <RegExp>\n\n    See Also\n    --------\n    regexp2json","reviveTypedArray":"\nreviveTypedArray( key, value )\n    Revives a JSON-serialized typed array.\n\n    The serialization format for typed array is an object having the following\n    fields:\n\n    - type: typed array type (e.g., \"Float64Array\", \"Int8Array\").\n    - data: typed array data as an array of numbers.\n\n    Parameters\n    ----------\n    key: string\n        Key.\n\n    value: any\n        Value.\n\n    Returns\n    -------\n    out: any\n        Value or typed array.\n\n    Examples\n    --------\n    > var str = '{\"type\":\"Float64Array\",\"data\":[5,3]}';\n    > var arr = parseJSON( str, reviveTypedArray )\n    <Float64Array>[ 5.0, 3.0 ]\n\n    See Also\n    --------\n    typedarray2json\n","reWhitespace":"\nreWhitespace( [options] )\n    Returns a regular expression to match a white space character.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.flags: string (optional)\n        Regular expression flags. Default: ''.\n\n    options.capture: boolean (optional)\n        Boolean indicating whether to wrap a regular expression matching a white\n        space character with a capture group. Default: false.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reWhitespace();\n    > var bool = RE.test( '\\n' )\n    true\n    > bool = RE.test( ' ' )\n    true\n    > bool = RE.test( 'a' )\n    false\n\n\nreWhitespace.REGEXP\n    Regular expression to match a white space character.\n\n    Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n    characters in the Unicode 9.0 character database.\n\n    Matches one related white space character without the Unicode character\n    property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n    of Unicode 3.2).\n\n    Examples\n    --------\n    > var RE = reWhitespace.REGEXP;\n    > var bool = RE.test( '\\n' )\n    true\n    > bool = RE.test( ' ' )\n    true\n    > bool = RE.test( 'a' )\n    false\n\n\nreWhitespace.REGEXP_CAPTURE\n    Regular expression to capture white space characters.\n\n    Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n    characters in the Unicode 9.0 character database.\n\n    Matches one related white space character without the Unicode character\n    property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n    of Unicode 3.2).\n\n    Examples\n    --------\n    > var RE = reWhitespace.REGEXP_CAPTURE;\n    > var str = 'Duplicate capture';\n    > var out = replace( str, RE, '$1$1' )\n    'Duplicate  capture'\n\n    See Also\n    --------\n    isWhitespace","reWhitespace.REGEXP":"\nreWhitespace.REGEXP\n    Regular expression to match a white space character.\n\n    Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n    characters in the Unicode 9.0 character database.\n\n    Matches one related white space character without the Unicode character\n    property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n    of Unicode 3.2).\n\n    Examples\n    --------\n    > var RE = reWhitespace.REGEXP;\n    > var bool = RE.test( '\\n' )\n    true\n    > bool = RE.test( ' ' )\n    true\n    > bool = RE.test( 'a' )\n    false","reWhitespace.REGEXP_CAPTURE":"\nreWhitespace.REGEXP_CAPTURE\n    Regular expression to capture white space characters.\n\n    Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n    characters in the Unicode 9.0 character database.\n\n    Matches one related white space character without the Unicode character\n    property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n    of Unicode 3.2).\n\n    Examples\n    --------\n    > var RE = reWhitespace.REGEXP_CAPTURE;\n    > var str = 'Duplicate capture';\n    > var out = replace( str, RE, '$1$1' )\n    'Duplicate  capture'\n\n    See Also\n    --------\n    isWhitespace","rpad":"\nrpad( str, len[, pad] )\n    Right pads a `string` such that the padded `string` has a length of at least\n    `len`.\n\n    An output string is not guaranteed to have a length of exactly `len`, but to\n    have a length of at least `len`. To generate a padded string having a length\n    equal to `len`, post-process a padded string by trimming off excess\n    characters.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    len: integer\n        Minimum string length.\n\n    pad: string (optional)\n        String used to pad. Default: ' '.\n\n    Returns\n    -------\n    out: string\n        Padded string.\n\n    Examples\n    --------\n    > var out = rpad( 'a', 5 )\n    'a    '\n    > out = rpad( 'beep', 10, 'p' )\n    'beeppppppp'\n    > out = rpad( 'beep', 12, 'boop' )\n    'beepboopboop'\n\n    See Also\n    --------\n    lpad, pad\n","rtrim":"\nrtrim( str )\n    Trims whitespace from the end of a string.\n\n    \"Whitespace\" is defined as the following characters:\n\n    - \\f\n    - \\n\n    - \\r\n    - \\t\n    - \\v\n    - \\u0020\n    - \\u00a0\n    - \\u1680\n    - \\u2000-\\u200a\n    - \\u2028\n    - \\u2029\n    - \\u202f\n    - \\u205f\n    - \\u3000\n    - \\ufeff\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Trimmed string.\n\n    Examples\n    --------\n    > var out = rtrim( ' \\t\\t\\n  Beep \\r\\n\\t  ' )\n    ' \\t\\t\\n  Beep'\n\n    See Also\n    --------\n    ltrim, trim\n","rtrimN":"\nrtrimN( str, n[, chars] )\n    Trims `n` characters from the end of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of characters to trim.\n\n    chars: Array<string>|string (optional)\n        Characters to trim. Default: whitespace characters.\n\n    Returns\n    -------\n    out: string\n        Trimmed string.\n\n    Examples\n    --------\n    > var out = rtrimN( '  abc  ', 2 )\n    '  abc'\n    > var out = rtrimN( '!!!abc!!!', 2, '!' )\n    '!!!abc!'\n\n    See Also\n    --------\n    ltrimN, trim","safeintmax":"\nsafeintmax( dtype )\n    Returns the maximum safe integer capable of being represented by a numeric\n    real type.\n\n    The following numeric real types are supported:\n\n    - float64: double-precision floating-point numbers.\n    - float32: single-precision floating-point numbers.\n    - float16: half-precision floating-point numbers.\n\n    Parameters\n    ----------\n    dtype: string\n        Numeric type.\n\n    Returns\n    -------\n    out: integer\n        Maximum safe integer.\n\n    Examples\n    --------\n    > var m = safeintmax( 'float16' )\n    2047\n    > m = safeintmax( 'float32' )\n    16777215\n\n    See Also\n    --------\n    safeintmin, realmax, typemax\n","safeintmin":"\nsafeintmin( dtype )\n    Returns the minimum safe integer capable of being represented by a numeric\n    real type.\n\n    The following numeric real types are supported:\n\n    - float64: double-precision floating-point numbers.\n    - float32: single-precision floating-point numbers.\n    - float16: half-precision floating-point numbers.\n\n    Parameters\n    ----------\n    dtype: string\n        Numeric type.\n\n    Returns\n    -------\n    out: integer\n        Minimum safe integer.\n\n    Examples\n    --------\n    > var m = safeintmin( 'float16' )\n    -2047\n    > m = safeintmin( 'float32' )\n    -16777215\n\n    See Also\n    --------\n    safeintmax, realmin, typemin\n","sample":"\nsample( x[, options] )\n    Samples elements from an array-like object.\n\n    Parameters\n    ----------\n    x: ArrayLike\n        Array-like object from which to sample.\n\n    options: Object (optional)\n        Options.\n\n    options.size: integer (optional)\n        Sample size. By default, the function returns an array having the same\n        length as `x`. Specify the `size` option to generate a sample of a\n        different size.\n\n    options.probs: Array<number> (optional)\n        Element probabilities. By default, the probability of sampling an\n        element is the same for all elements. To assign elements different\n        probabilities, set the `probs` option. The `probs` option must be a\n        numeric array consisting of nonnegative values which sum to one. When\n        sampling without replacement, note that the `probs` option denotes the\n        initial element probabilities which are then updated after each draw.\n\n    options.replace: boolean (optional)\n        Boolean indicating whether to sample with replacement. If the `replace`\n        option is set to `false`, the `size` option cannot be an integer larger\n        than the number of elements in `x`. Default: `true`.\n\n    Returns\n    -------\n    out: Array\n        Sample.\n\n    Examples\n    --------\n    > var out = sample( 'abc' )\n    e.g., [ 'a', 'a', 'b' ]\n    > out = sample( [ 3, 6, 9 ] )\n    e.g., [ 3, 9, 6 ]\n    > var bool = ( out.length === 3 )\n    true\n\n    > out = sample( [ 3, null, NaN, 'abc', function(){} ] )\n    e.g., [ 3, 'abc', null, 3, null ]\n\n    // Set sample size:\n    > out = sample( [ 3, 6, 9 ], { 'size': 10 } )\n    e.g., [ 6, 3, 9, 9, 9, 6, 9, 6, 9, 3 ]\n    > out = sample( [ 0, 1 ], { 'size': 20 } )\n    e.g., [ 0, 0, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 0 ]\n\n    // Draw without replacement:\n    > out = sample( [ 1, 2, 3, 4, 5, 6 ], { 'replace': false, 'size': 3 } )\n    e.g., [ 6, 1, 5 ]\n    > out = sample( [ 0, 1 ], { 'replace': false } )\n    e.g., [ 0, 1 ]\n\n    // Assigning non-uniform element probabilities:\n    > var x = [ 1, 2, 3, 4, 5, 6 ];\n    > var probs = [ 0.1, 0.1, 0.1, 0.1, 0.1, 0.5 ];\n    > out = sample( x, { 'probs': probs } )\n    e.g., [ 5, 6, 6, 5, 6, 4 ]\n    > out = sample( x, { 'probs': probs, 'size': 3, 'replace': false } )\n    e.g., [ 6, 4, 1 ]\n\n\nsample.factory( [pool, ][options] )\n    Returns a function to sample elements from an array-like object.\n\n    If provided an array-like object `pool`, the returned function will always\n    sample from the supplied object.\n\n    Parameters\n    ----------\n    pool: ArrayLike (optional)\n        Array-like object from which to sample.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer (optional)\n        Integer-valued seed.\n\n    options.size: integer (optional)\n        Sample size.\n\n    options.replace: boolean (optional)\n        Boolean indicating whether to sample with replacement. Default: `true`.\n\n    options.mutate: boolean (optional)\n        Boolean indicating whether to mutate the `pool` when sampling without\n        replacement. If a population from which to sample is provided, the\n        underlying `pool` remains by default constant for each function\n        invocation. To mutate the `pool` by permanently removing observations\n        when sampling without replacement, set the `mutate` option to `true`.\n        The returned function returns `null` after all population units are\n        exhausted. Default: `false`.\n\n    Returns\n    -------\n    fcn: Function\n        Function to sample elements from an array-like object.\n\n    Examples\n    --------\n    // Set a seed:\n    > var mysample = sample.factory({ 'seed': 232 } );\n    > var out = mysample( 'abcdefg' )\n    e.g., [ 'g', 'd', 'g', 'f', 'c', 'e', 'f' ]\n\n    // Provide `pool` and set a seed plus a default sample size:\n    > var pool = [ 1, 2, 3, 4, 5, 6 ];\n    > mysample = sample.factory( pool, { 'seed': 232, 'size': 2 } );\n    > out = mysample()\n    e.g., [ 6, 4 ]\n    > out = mysample()\n    e.g., [ 6, 5 ]\n\n    // Mutate the `pool`:\n    > var opts = { 'seed': 474, 'size': 3, 'mutate': true, 'replace': false };\n    > pool = [ 1, 2, 3, 4, 5, 6 ];\n    > mysample = sample.factory( pool, opts );\n    > out = mysample()\n    e.g., [ 4, 3, 6 ]\n    > out = mysample()\n    e.g., [ 1, 5, 2 ]\n    > out = mysample()\n    null\n\n    // Override default `size` parameter when invoking created function:\n    > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n    > out = mysample()\n    e.g., [ 1, 1 ]\n    > out = mysample({ 'size': 10 })\n    e.g, [ 0, 1, 1, 1, 0, 1, 0, 0, 1, 1 ]\n\n    // Sample with and without replacement:\n    > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n    > out = mysample()\n    e.g., [ 1, 1 ]\n    > out = mysample({ 'replace': false })\n    e.g., [ 0, 1 ] or [ 1, 0 ]\n    > out = mysample()\n    e.g., [ 1, 1 ]\n\n","sample.factory":"\nsample.factory( [pool, ][options] )\n    Returns a function to sample elements from an array-like object.\n\n    If provided an array-like object `pool`, the returned function will always\n    sample from the supplied object.\n\n    Parameters\n    ----------\n    pool: ArrayLike (optional)\n        Array-like object from which to sample.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer (optional)\n        Integer-valued seed.\n\n    options.size: integer (optional)\n        Sample size.\n\n    options.replace: boolean (optional)\n        Boolean indicating whether to sample with replacement. Default: `true`.\n\n    options.mutate: boolean (optional)\n        Boolean indicating whether to mutate the `pool` when sampling without\n        replacement. If a population from which to sample is provided, the\n        underlying `pool` remains by default constant for each function\n        invocation. To mutate the `pool` by permanently removing observations\n        when sampling without replacement, set the `mutate` option to `true`.\n        The returned function returns `null` after all population units are\n        exhausted. Default: `false`.\n\n    Returns\n    -------\n    fcn: Function\n        Function to sample elements from an array-like object.\n\n    Examples\n    --------\n    // Set a seed:\n    > var mysample = sample.factory({ 'seed': 232 } );\n    > var out = mysample( 'abcdefg' )\n    e.g., [ 'g', 'd', 'g', 'f', 'c', 'e', 'f' ]\n\n    // Provide `pool` and set a seed plus a default sample size:\n    > var pool = [ 1, 2, 3, 4, 5, 6 ];\n    > mysample = sample.factory( pool, { 'seed': 232, 'size': 2 } );\n    > out = mysample()\n    e.g., [ 6, 4 ]\n    > out = mysample()\n    e.g., [ 6, 5 ]\n\n    // Mutate the `pool`:\n    > var opts = { 'seed': 474, 'size': 3, 'mutate': true, 'replace': false };\n    > pool = [ 1, 2, 3, 4, 5, 6 ];\n    > mysample = sample.factory( pool, opts );\n    > out = mysample()\n    e.g., [ 4, 3, 6 ]\n    > out = mysample()\n    e.g., [ 1, 5, 2 ]\n    > out = mysample()\n    null\n\n    // Override default `size` parameter when invoking created function:\n    > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n    > out = mysample()\n    e.g., [ 1, 1 ]\n    > out = mysample({ 'size': 10 })\n    e.g, [ 0, 1, 1, 1, 0, 1, 0, 0, 1, 1 ]\n\n    // Sample with and without replacement:\n    > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n    > out = mysample()\n    e.g., [ 1, 1 ]\n    > out = mysample({ 'replace': false })\n    e.g., [ 0, 1 ] or [ 1, 0 ]\n    > out = mysample()\n    e.g., [ 1, 1 ]","SAVOY_STOPWORDS_FIN":"\nSAVOY_STOPWORDS_FIN()\n    Returns a list of Finnish stop words.\n\n    Returns\n    -------\n    out: Array<string>\n        List of stop words.\n\n    Examples\n    --------\n    > var list = SAVOY_STOPWORDS_FIN()\n    [ 'aiemmin', 'aika', 'aikaa', ... ]\n\n    References\n    ----------\n    - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n    <http://members.unine.ch/jacques.savoy/clef/>.\n\n","SAVOY_STOPWORDS_FR":"\nSAVOY_STOPWORDS_FR()\n    Returns a list of French stop words.\n\n    Returns\n    -------\n    out: Array<string>\n        List of stop words.\n\n    Examples\n    --------\n    > var list = SAVOY_STOPWORDS_FR()\n    [ 'a', 'à', 'â', 'abord', ... ]\n\n    References\n    ----------\n    - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n    <http://members.unine.ch/jacques.savoy/clef/>.\n\n","SAVOY_STOPWORDS_GER":"\nSAVOY_STOPWORDS_GER()\n    Returns a list of German stop words.\n\n    Returns\n    -------\n    out: Array<string>\n        List of stop words.\n\n    Examples\n    --------\n    > var list = SAVOY_STOPWORDS_GER()\n    [ 'a', 'ab', 'aber', 'ach', ... ]\n\n    References\n    ----------\n    - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n    <http://members.unine.ch/jacques.savoy/clef/>.\n\n","SAVOY_STOPWORDS_IT":"\nSAVOY_STOPWORDS_IT()\n    Returns a list of Italian stop words.\n\n    Returns\n    -------\n    out: Array<string>\n        List of stop words.\n\n    Examples\n    --------\n    > var list = SAVOY_STOPWORDS_IT()\n    [ 'a', 'abbastanza', 'accidenti', 'ad', ... ]\n\n    References\n    ----------\n    - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n    <http://members.unine.ch/jacques.savoy/clef/>.\n\n","SAVOY_STOPWORDS_POR":"\nSAVOY_STOPWORDS_POR()\n    Returns a list of Portuguese stop words.\n\n    Returns\n    -------\n    out: Array<string>\n        List of stop words.\n\n    Examples\n    --------\n    > var list = SAVOY_STOPWORDS_POR()\n    [ 'aiemmin', 'aika', 'aikaa', ... ]\n\n    References\n    ----------\n    - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n    <http://members.unine.ch/jacques.savoy/clef/>.\n\n","SAVOY_STOPWORDS_SP":"\nSAVOY_STOPWORDS_SP()\n    Returns a list of Spanish stop words.\n\n    Returns\n    -------\n    out: Array<string>\n        List of stop words.\n\n    Examples\n    --------\n    > var list = SAVOY_STOPWORDS_SP()\n    [ 'a', 'acuerdo', 'adelante', 'ademas', ... ]\n\n    References\n    ----------\n    - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n    <http://members.unine.ch/jacques.savoy/clef/>.\n\n","SAVOY_STOPWORDS_SWE":"\nSAVOY_STOPWORDS_SWE()\n    Returns a list of Swedish stop words.\n\n    Returns\n    -------\n    out: Array<string>\n        List of stop words.\n\n    Examples\n    --------\n    > var list = SAVOY_STOPWORDS_SWE()\n    [ 'aderton', 'adertonde', 'adjö', ... ]\n\n    References\n    ----------\n    - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n    <http://members.unine.ch/jacques.savoy/clef/>.\n\n","scalar2array":"\nscalar2array( value[, dtype] )\n    Returns a single-element array containing a provided scalar value.\n\n    If `value` is a number and `dtype` is a complex number data type, the\n    function returns a complex number array containing a complex number whose\n    real component equals the provided scalar value and whose imaginary\n    component is zero.\n\n    Parameters\n    ----------\n    value: any\n        Scalar value.\n\n    dtype: string (optional)\n        Data type. If not provided and `value`\n\n        - is a number, the default data type is the default real-valued\n          floating-point data type.\n        - is a boolean, the default data type is the default boolean data type.\n        - is a complex number object of a known complex data type, the data type\n          is the same as the provided value.\n        - is a complex number object of an unknown data type, the default data\n          type is the default complex-valued floating-point data type.\n        - is any other value type, the default data type is 'generic'.\n\n    Returns\n    -------\n    out: Array|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = scalar2array( 1.0 )\n    <Float64Array>[ 1.0 ]\n\n    See Also\n    --------\n    iterator2array\n","scalar2ndarray":"\nscalar2ndarray( value[, options] )\n    Returns a zero-dimensional ndarray containing a provided scalar value.\n\n    If `value` is a number and `options.dtype` is a complex number data type,\n    the function returns a zero-dimensional ndarray containing a complex number\n    whose real component equals the provided scalar value and whose imaginary\n    component is zero.\n\n    Parameters\n    ----------\n    value: any\n        Scalar value.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Data type. If not provided and `value`\n\n        - is a number, the default data type is the default real-valued\n          floating-point data type.\n        - is a boolean, the default data type is the default boolean data type.\n        - is a complex number object of a known complex data type, the data type\n          is the same as the provided value.\n        - is a complex number object of an unknown data type, the default data\n          type is the default complex-valued floating-point data type.\n        - is any other value type, the default data type is 'generic'.\n\n    options.order: string (optional)\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran-style). Default: 'row-major'.\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether an array should be read-only. Default: false.\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var x = scalar2ndarray( 1.0 )\n    <ndarray>\n    > var sh = x.shape\n    []\n    > var dt = x.dtype\n    'float64'\n    > var v = x.get()\n    1.0\n\n    See Also\n    --------\n    array, ndarray\n","sdot":"\nsdot( x, y[, dim] )\n    Computes the dot product of two single-precision floating-point vectors.\n\n    If provided at least one input array having more than one dimension, the\n    input arrays are broadcasted to a common shape.\n\n    For multi-dimensional input arrays, the function performs batched\n    computation, such that the function computes the dot product for each pair\n    of vectors in `x` and `y` according to the specified dimension index.\n\n    The size of the contracted dimension must be the same for both input arrays.\n\n    The function resolves the dimension index for which to compute the dot\n    product *before* broadcasting.\n\n    If provided empty vectors, the dot product is `0`.\n\n    Parameters\n    ----------\n    x: ndarray\n        First input array. Must have a 'float32' data type. Must have at least\n        one dimension and be broadcast-compatible with the second input array.\n\n    y: ndarray\n        Second input array. Must have a 'float32' data type. Must have at least\n        one dimension and be broadcast-compatible with the first input array.\n\n    dim: integer (optional)\n        Dimension index for which to compute the dot product. Must be a negative\n        integer. Negative indices are resolved relative to the last array\n        dimension, with the last dimension corresponding to `-1`. Default: -1.\n\n    Returns\n    -------\n    out: ndarray\n        The dot product. The output array has the same data type as the input\n        arrays and has a shape which is determined by broadcasting and excludes\n        the contracted dimension.\n\n    Examples\n    --------\n    > var xbuf = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var x = array( xbuf );\n    > var ybuf = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var y = array( ybuf );\n    > var z = sdot( x, y )\n    <ndarray>\n    > z.get()\n    -5.0\n\n    See Also\n    --------\n    base.strided.sdot, ddot, gdot\n","SECONDS_IN_DAY":"\nSECONDS_IN_DAY\n    Number of seconds in a day.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var days = 3.14;\n    > var secs = days * SECONDS_IN_DAY\n    271296\n\n","SECONDS_IN_HOUR":"\nSECONDS_IN_HOUR\n    Number of seconds in an hour.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var hrs = 3.14;\n    > var secs = hrs * SECONDS_IN_HOUR\n    11304\n\n","SECONDS_IN_MINUTE":"\nSECONDS_IN_MINUTE\n    Number of seconds in a minute.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies arising due to complications with time and dates.\n\n    Examples\n    --------\n    > var mins = 3.14;\n    > var secs = mins * SECONDS_IN_MINUTE\n    188.4\n\n","SECONDS_IN_WEEK":"\nSECONDS_IN_WEEK\n    Number of seconds in a week.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var wks = 3.14;\n    > var secs = wks * SECONDS_IN_WEEK\n    1899072\n\n","secondsInMonth":"\nsecondsInMonth( [month[, year]] )\n    Returns the number of seconds in a month.\n\n    By default, the function returns the number of seconds in the current month\n    of the current year (according to local time). To determine the number of\n    seconds for a particular month and year, provide `month` and `year`\n    arguments.\n\n    A `month` may be either a month's integer value, three letter abbreviation,\n    or full name (case insensitive).\n\n    The function's return value is a generalization and does **not** take into\n    account inaccuracies due to daylight savings conventions, crossing\n    timezones, or other complications with time and dates.\n\n    Parameters\n    ----------\n    month: string|Date|integer (optional)\n        Month.\n\n    year: integer (optional)\n        Year.\n\n    Returns\n    -------\n    out: integer\n        Seconds in a month.\n\n    Examples\n    --------\n    > var num = secondsInMonth()\n    <number>\n    > num = secondsInMonth( 2 )\n    <number>\n    > num = secondsInMonth( 2, 2016 )\n    2505600\n    > num = secondsInMonth( 2, 2017 )\n    2419200\n\n    // Other ways to supply month:\n    > num = secondsInMonth( 'feb', 2016 )\n    2505600\n    > num = secondsInMonth( 'february', 2016 )\n    2505600\n\n    See Also\n    --------\n    secondsInYear\n","secondsInYear":"\nsecondsInYear( [value] )\n    Returns the number of seconds in a year according to the Gregorian calendar.\n\n    By default, the function returns the number of seconds in the current year\n    (according to local time). To determine the number of seconds for a\n    particular year, provide either a year or a `Date` object.\n\n    The function's return value is a generalization and does **not** take into\n    account inaccuracies due to daylight savings conventions, crossing\n    timezones, or other complications with time and dates.\n\n    Parameters\n    ----------\n    value: integer|Date (optional)\n        Year or `Date` object.\n\n    Returns\n    -------\n    out: integer\n        Number of seconds in a year.\n\n    Examples\n    --------\n    > var num = secondsInYear()\n    <number>\n    > num = secondsInYear( 2016 )\n    31622400\n    > num = secondsInYear( 2017 )\n    31536000\n\n    See Also\n    --------\n    secondsInMonth\n","sentencize":"\nsentencize( str )\n    Splits a string into an array of sentences.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: Array\n        Array of sentences.\n\n    Examples\n    --------\n    > var out = sentencize( 'Hello Mrs. Maple, could you call me back?' )\n    [ 'Hello Mrs. Maple, could you call me back?' ]\n\n    > out = sentencize( 'Hello World! How are you?' )\n    [ 'Hello World!', 'How are you?' ]\n\n    See Also\n    --------\n    tokenize\n","seq2slice":"\nseq2slice( str, len, strict )\n    Converts a subsequence string to a Slice object.\n\n    A subsequence string has the following format:\n\n      <start>:<stop>:<increment>\n\n    If an increment is not specified, the default increment is one. An increment\n    of zero is not allowed.\n\n    The start index is inclusive.\n\n    The stop index is exclusive.\n\n    Both start and stop indices are optional. If not provided, the start and\n    stop indices default to index extremes. Which extremes correspond to which\n    index depends on whether the increment is positive or negative.\n\n    Both start and stop indices can be negative; in which case, the\n    corresponding index is resolved by subtracting the respective value from the\n    provided length.\n\n    Both start and stop indices can use the 'end' keyword (e.g., 'end-2::2',\n    'end-3:', etc), which supports basic subtraction and division.\n\n    The 'end' keyword resolves to the provided length. Thus, ':-1' is equivalent\n    to ':end-1', ':-2' is equivalent to ':end-2', and so on and so forth. The\n    exception is when performing a division operation when the increment is less\n    than zero; in which case, 'end' is equal to 'len-1' in order to preserve\n    user expectations when 'end/d' equals a whole number and slicing from right-\n    to-left. The result from a division operation is rounded down to the nearest\n    integer value.\n\n    In non-strict mode, the resolved slice start is clamped to the slice index\n    bounds [0, len).\n\n    In non-strict mode, Tte resolved slice end is upper bound clamped to the\n    provided length (i.e., one greater than the last possible index).\n\n    When the increment is negative, the resolved slice end value may be `null`,\n    thus indicating that a non-empty slice should include the first index.\n\n    The function ensures that results satisfy the convention that ':n' combined\n    with 'n:' is equivalent to ':' (i.e., selecting all elements).\n\n    When the provided length is zero, the function always returns a slice object\n    equivalent to '0:0:<increment>'.\n\n    Parameters\n    ----------\n    str: string\n        Subsequence string.\n\n    len: integer\n        Maximum number of elements allowed in the slice.\n\n    strict: boolean\n        Boolean indicating whether to enforce strict bounds checking.\n\n    Returns\n    -------\n    s: Slice\n        Slice instance.\n\n    Examples\n    --------\n    > var s = new seq2slice( '1:10', 10, false );\n    > s.start\n    1\n    > s.stop\n    10\n    > s.step\n    1\n    > s = new seq2slice( '2:5:2', 10, false );\n    > s.start\n    2\n    > s.stop\n    5\n    > s.step\n    2\n\n    See Also\n    --------\n    Slice\n","setConfigurableReadOnly":"\nsetConfigurableReadOnly( obj, prop, value )\n    Defines a configurable read-only property.\n\n    Configurable read-only properties are enumerable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    value: any\n        Value to set.\n\n    Examples\n    --------\n    > var obj = {};\n    > setConfigurableReadOnly( obj, 'foo', 'bar' );\n    > obj.foo = 'boop';\n    > obj\n    { 'foo': 'bar' }\n\n    See Also\n    --------\n    setConfigurableReadOnlyAccessor, setConfigurableReadWriteAccessor, defineProperty, setReadOnly\n","setConfigurableReadOnlyAccessor":"\nsetConfigurableReadOnlyAccessor( obj, prop, getter )\n    Defines a configurable read-only accessor.\n\n    Configurable read-only accessors are enumerable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    getter: Function\n        Get accessor.\n\n    Examples\n    --------\n    > var obj = {};\n    > function getter() { return 'bar'; };\n    > setConfigurableReadOnlyAccessor( obj, 'foo', getter );\n    > obj.foo\n    'bar'\n\n    See Also\n    --------\n    setConfigurableReadOnly, setConfigurableReadWriteAccessor, setConfigurableWriteOnlyAccessor, defineProperty, setReadOnlyAccessor\n","setConfigurableReadWriteAccessor":"\nsetConfigurableReadWriteAccessor( obj, prop, getter, setter )\n    Defines a configurable property having read-write accessors.\n\n    Configurable read-write accessors are enumerable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    getter: Function\n        Get accessor.\n\n    setter: Function\n        Set accessor.\n\n    Examples\n    --------\n    > var obj = {};\n    > var name = 'bar';\n    > function getter() { return name + ' foo'; };\n    > function setter( v ) { name = v; };\n    > setConfigurableReadWriteAccessor( obj, 'foo', getter, setter );\n    > obj.foo\n    'bar foo'\n    > obj.foo = 'beep';\n    > obj.foo\n    'beep foo'\n\n    See Also\n    --------\n    setConfigurableReadOnly, setConfigurableReadOnlyAccessor, setConfigurableWriteOnlyAccessor, defineProperty, setReadWriteAccessor\n","setConfigurableWriteOnlyAccessor":"\nsetConfigurableWriteOnlyAccessor( obj, prop, setter )\n    Defines a configurable write-only accessor.\n\n    Configurable write-only accessors are enumerable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    setter: Function\n        Set accessor.\n\n    Examples\n    --------\n    > var obj = {};\n    > var val = '';\n    > function setter( v ) { val = v; };\n    > setConfigurableWriteOnlyAccessor( obj, 'foo', setter );\n    > obj.foo = 'bar';\n    > val\n    'bar'\n\n    See Also\n    --------\n    setConfigurableReadOnly, setConfigurableReadOnlyAccessor, setConfigurableReadWriteAccessor, defineProperty, setWriteOnlyAccessor\n","setMemoizedConfigurableReadOnly":"\nsetMemoizedConfigurableReadOnly( obj, prop, fcn )\n    Defines a configurable memoized read-only object property.\n\n    Configurable read-only properties are enumerable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    fcn: Function\n        Synchronous function whose return value will be memoized and set as the\n        property value.\n\n    Examples\n    --------\n    > var obj = {};\n    > function foo() { return 'bar'; };\n    > setMemoizedConfigurableReadOnly( obj, 'foo', foo );\n    > obj.foo\n    'bar'\n\n    See Also\n    --------\n    setConfigurableReadOnly, setMemoizedReadOnly, setReadOnly\n","setMemoizedReadOnly":"\nsetMemoizedReadOnly( obj, prop, fcn )\n    Defines a memoized read-only object property.\n\n    Read-only properties are enumerable and non-configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    fcn: Function\n        Synchronous function whose return value will be memoized and set as the\n        property value.\n\n    Examples\n    --------\n    > var obj = {};\n    > function foo() { return 'bar'; };\n    > setMemoizedReadOnly( obj, 'foo', foo );\n    > obj.foo\n    'bar'\n\n    See Also\n    --------\n    defineMemoizedProperty, setReadOnly\n","setNonEnumerableProperty":"\nsetNonEnumerableProperty( obj, prop, value )\n    Defines a non-enumerable property.\n\n    Non-enumerable properties are writable and configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    value: any\n        Value to set.\n\n    Examples\n    --------\n    > var obj = {};\n    > setNonEnumerableProperty( obj, 'foo', 'bar' );\n    > obj.foo\n    'bar'\n    > objectKeys( obj )\n    []\n\n    See Also\n    --------\n    setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnly\n","setNonEnumerableReadOnly":"\nsetNonEnumerableReadOnly( obj, prop, value )\n    Defines a non-enumerable read-only property.\n\n    Non-enumerable read-only properties are non-configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    value: any\n        Value to set.\n\n    Examples\n    --------\n    > var obj = {};\n    > setNonEnumerableReadOnly( obj, 'foo', 'bar' );\n    > obj.foo = 'boop';\n    > obj\n    { 'foo': 'bar' }\n\n    See Also\n    --------\n    setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnly\n","setNonEnumerableReadOnlyAccessor":"\nsetNonEnumerableReadOnlyAccessor( obj, prop, getter )\n    Defines a non-enumerable read-only accessor.\n\n    Non-enumerable read-only accessors are non-configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    getter: Function\n        Get accessor.\n\n    Examples\n    --------\n    > var obj = {};\n    > function getter() { return 'bar'; };\n    > setNonEnumerableReadOnlyAccessor( obj, 'foo', getter );\n    > obj.foo\n    'bar'\n\n    See Also\n    --------\n    setNonEnumerableProperty, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnlyAccessor\n","setNonEnumerableReadWriteAccessor":"\nsetNonEnumerableReadWriteAccessor( obj, prop, getter, setter )\n    Defines a non-enumerable property having read-write accessors.\n\n    Non-enumerable read-write accessors are non-configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    getter: Function\n        Get accessor.\n\n    setter: Function\n        Set accessor.\n\n    Examples\n    --------\n    > var obj = {};\n    > var name = 'bar';\n    > function getter() { return name + ' foo'; };\n    > function setter( v ) { name = v; };\n    > setNonEnumerableReadWriteAccessor( obj, 'foo', getter, setter );\n    > obj.foo\n    'bar foo'\n    > obj.foo = 'beep';\n    > obj.foo\n    'beep foo'\n\n    See Also\n    --------\n    setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableWriteOnlyAccessor, setReadWriteAccessor\n","setNonEnumerableWriteOnlyAccessor":"\nsetNonEnumerableWriteOnlyAccessor( obj, prop, setter )\n    Defines a non-enumerable write-only accessor.\n\n    Non-enumerable write-only accessors are non-configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    setter: Function\n        Set accessor.\n\n    Examples\n    --------\n    > var obj = {};\n    > var val = '';\n    > function setter( v ) { val = v; };\n    > setNonEnumerableWriteOnlyAccessor( obj, 'foo', setter );\n    > obj.foo = 'bar';\n    > val\n    'bar'\n\n    See Also\n    --------\n    setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setWriteOnlyAccessor\n","setReadOnly":"\nsetReadOnly( obj, prop, value )\n    Defines a read-only property.\n\n    Read-only properties are enumerable and non-configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    value: any\n        Value to set.\n\n    Examples\n    --------\n    > var obj = {};\n    > setReadOnly( obj, 'foo', 'bar' );\n    > obj.foo = 'boop';\n    > obj\n    { 'foo': 'bar' }\n\n    See Also\n    --------\n    setReadOnlyAccessor, setReadWriteAccessor, setWriteOnlyAccessor\n","setReadOnlyAccessor":"\nsetReadOnlyAccessor( obj, prop, getter )\n    Defines a read-only accessor.\n\n    Read-only accessors are enumerable and non-configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    getter: Function\n        Get accessor.\n\n    Examples\n    --------\n    > var obj = {};\n    > function getter() { return 'bar'; };\n    > setReadOnlyAccessor( obj, 'foo', getter );\n    > obj.foo\n    'bar'\n\n    See Also\n    --------\n    setReadOnly, setReadWriteAccessor, setWriteOnlyAccessor\n","setReadWriteAccessor":"\nsetReadWriteAccessor( obj, prop, getter, setter )\n    Defines a property having read-write accessors.\n\n    Read-write accessors are enumerable and non-configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    getter: Function\n        Get accessor.\n\n    setter: Function\n        Set accessor.\n\n    Examples\n    --------\n    > var obj = {};\n    > var name = 'bar';\n    > function getter() { return name + ' foo'; };\n    > function setter( v ) { name = v; };\n    > setReadWriteAccessor( obj, 'foo', getter, setter );\n    > obj.foo\n    'bar foo'\n    > obj.foo = 'beep';\n    > obj.foo\n    'beep foo'\n\n    See Also\n    --------\n    setReadOnly, setReadOnlyAccessor, setWriteOnlyAccessor\n","setWriteOnlyAccessor":"\nsetWriteOnlyAccessor( obj, prop, setter )\n    Defines a write-only accessor.\n\n    Write-only accessors are enumerable and non-configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    setter: Function\n        Set accessor.\n\n    Examples\n    --------\n    > var obj = {};\n    > var val = '';\n    > function setter( v ) { val = v; };\n    > setWriteOnlyAccessor( obj, 'foo', setter );\n    > obj.foo = 'bar';\n    > val\n    'bar'\n\n    See Also\n    --------\n    setReadOnly, setReadOnlyAccessor, setReadWriteAccessor\n","SharedArrayBuffer":"\nSharedArrayBuffer( size )\n    Returns a shared array buffer having a specified number of bytes.\n\n    A shared array buffer behaves similarly to a non-shared array buffer, except\n    that a shared array buffer allows creating views of memory shared between\n    threads.\n\n    Buffer contents are initialized to 0.\n\n    If an environment does not support shared array buffers, the function throws\n    an error.\n\n    Parameters\n    ----------\n    size: integer\n        Number of bytes.\n\n    Returns\n    -------\n    out: SharedArrayBuffer\n        A shared array buffer.\n\n    Examples\n    --------\n    // Assuming an environment supports SharedArrayBuffers...\n    > var buf = new SharedArrayBuffer( 5 )\n    <SharedArrayBuffer>\n\n\nSharedArrayBuffer.length\n    Number of input arguments the constructor accepts.\n\n    Examples\n    --------\n    > SharedArrayBuffer.length\n    1\n\n\nSharedArrayBuffer.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the array buffer.\n\n    Examples\n    --------\n    // Assuming an environment supports SharedArrayBuffers...\n    > var buf = new SharedArrayBuffer( 5 );\n    > buf.byteLength\n    5\n\n\nSharedArrayBuffer.prototype.slice( [start[, end]] )\n    Copies the bytes of a shared array buffer to a new shared array buffer.\n\n    Parameters\n    ----------\n    start: integer (optional)\n        Index at which to start copying buffer contents (inclusive). If\n        negative, the index is relative to the end of the buffer.\n\n    end: integer (optional)\n        Index at which to stop copying buffer contents (exclusive). If negative,\n        the index is relative to the end of the buffer.\n\n    Returns\n    -------\n    out: SharedArrayBuffer\n        A new shared array buffer whose contents have been copied from the\n        calling shared array buffer.\n\n    Examples\n    --------\n    // Assuming an environment supports SharedArrayBuffers...\n    > var b1 = new SharedArrayBuffer( 10 );\n    > var b2 = b1.slice( 2, 6 );\n    > var bool = ( b1 === b2 )\n    false\n    > b2.byteLength\n    4\n\n    See Also\n    --------\n    Buffer, ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","SharedArrayBuffer.length":"\nSharedArrayBuffer.length\n    Number of input arguments the constructor accepts.\n\n    Examples\n    --------\n    > SharedArrayBuffer.length\n    1","SharedArrayBuffer.prototype.byteLength":"\nSharedArrayBuffer.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the array buffer.\n\n    Examples\n    --------\n    // Assuming an environment supports SharedArrayBuffers...\n    > var buf = new SharedArrayBuffer( 5 );\n    > buf.byteLength\n    5","SharedArrayBuffer.prototype.slice":"\nSharedArrayBuffer.prototype.slice( [start[, end]] )\n    Copies the bytes of a shared array buffer to a new shared array buffer.\n\n    Parameters\n    ----------\n    start: integer (optional)\n        Index at which to start copying buffer contents (inclusive). If\n        negative, the index is relative to the end of the buffer.\n\n    end: integer (optional)\n        Index at which to stop copying buffer contents (exclusive). If negative,\n        the index is relative to the end of the buffer.\n\n    Returns\n    -------\n    out: SharedArrayBuffer\n        A new shared array buffer whose contents have been copied from the\n        calling shared array buffer.\n\n    Examples\n    --------\n    // Assuming an environment supports SharedArrayBuffers...\n    > var b1 = new SharedArrayBuffer( 10 );\n    > var b2 = b1.slice( 2, 6 );\n    > var bool = ( b1 === b2 )\n    false\n    > b2.byteLength\n    4\n\n    See Also\n    --------\n    Buffer, ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","shift":"\nshift( collection )\n    Removes and returns the first element of a collection.\n\n    The function returns an array with two elements: the shortened collection\n    and the removed element.\n\n    If the input collection is a typed array whose length is greater than `0`,\n    the first return value does not equal the input reference.\n\n    For purposes of generality, always treat the output collection as distinct\n    from the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        A collection. If the collection is an `Object`, the value should be\n        array-like.\n\n    Returns\n    -------\n    out: Array\n        Updated collection and the removed item.\n\n    Examples\n    --------\n    // Arrays:\n    > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > var out = shift( arr )\n    [ [ 2.0, 3.0, 4.0, 5.0 ], 1.0 ]\n\n    // Typed arrays:\n    > arr = new Float64Array( [ 1.0, 2.0 ] );\n    > out = shift( arr )\n    [ <Float64Array>[ 2.0 ], 1.0 ]\n\n    // Array-like object:\n    > arr = { 'length': 2, '0': 1.0, '1': 2.0 };\n    > out = shift( arr )\n    [ { 'length': 1, '0': 2.0 }, 1.0 ]\n\n    See Also\n    --------\n    pop, push, unshift\n","shuffle":"\nshuffle( arr[, options] )\n    Shuffles elements of an array-like object.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Array-like object to shuffle.\n\n    options: Object (optional)\n        Options.\n\n    options.copy: string (optional)\n        String indicating whether to return a copy (`deep`,`shallow` or `none`).\n        Default: `'shallow'`.\n\n    Returns\n    -------\n    out: ArrayLike\n        Shuffled array-like object.\n\n    Examples\n    --------\n    > var data = [ 1, 2, 3 ];\n    > var out = shuffle( data )\n    e.g., [ 3, 1, 2 ]\n    > out = shuffle( data, { 'copy': 'none' } );\n    > var bool = ( data === out )\n    true\n\n\nshuffle.factory( [options] )\n    Returns a function to shuffle elements of array-like objects.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer (optional)\n        Integer-valued seed.\n\n    options.copy: string (optional)\n        String indicating whether to return a copy (`deep`,`shallow` or `none`).\n        Default: `'shallow'`.\n\n    Returns\n    -------\n    fcn: Function\n        Shuffle function.\n\n    Examples\n    --------\n    > var myshuffle = shuffle.factory();\n\n    // Set a seed:\n    > myshuffle = shuffle.factory({ 'seed': 239 });\n    > var arr = [ 0, 1, 2, 3, 4 ];\n    > var out = myshuffle( arr )\n    e.g., [ 3, 4, 1, 0, 2 ]\n\n    // Use a different copy strategy:\n    > myshuffle = shuffle.factory({ 'copy': 'none', 'seed': 867 });\n\n    // Created shuffle function mutates input array by default:\n    > arr = [ 1, 2, 3, 4, 5, 6 ];\n    > out = myshuffle( arr );\n    > var bool = ( arr === out )\n    true\n    // Default option can be overridden:\n    > arr = [ 1, 2, 3, 4 ];\n    > out = myshuffle( arr, { 'copy': 'shallow' } );\n    > bool = ( arr === out )\n    false\n\n    See Also\n    --------\n    sample\n","shuffle.factory":"\nshuffle.factory( [options] )\n    Returns a function to shuffle elements of array-like objects.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer (optional)\n        Integer-valued seed.\n\n    options.copy: string (optional)\n        String indicating whether to return a copy (`deep`,`shallow` or `none`).\n        Default: `'shallow'`.\n\n    Returns\n    -------\n    fcn: Function\n        Shuffle function.\n\n    Examples\n    --------\n    > var myshuffle = shuffle.factory();\n\n    // Set a seed:\n    > myshuffle = shuffle.factory({ 'seed': 239 });\n    > var arr = [ 0, 1, 2, 3, 4 ];\n    > var out = myshuffle( arr )\n    e.g., [ 3, 4, 1, 0, 2 ]\n\n    // Use a different copy strategy:\n    > myshuffle = shuffle.factory({ 'copy': 'none', 'seed': 867 });\n\n    // Created shuffle function mutates input array by default:\n    > arr = [ 1, 2, 3, 4, 5, 6 ];\n    > out = myshuffle( arr );\n    > var bool = ( arr === out )\n    true\n    // Default option can be overridden:\n    > arr = [ 1, 2, 3, 4 ];\n    > out = myshuffle( arr, { 'copy': 'shallow' } );\n    > bool = ( arr === out )\n    false\n\n    See Also\n    --------\n    sample","sizeOf":"\nsizeOf( dtype )\n    Returns the size (in bytes) of the canonical binary representation of a\n    specified numeric type.\n\n    The following numeric types are supported:\n\n    - float64: double-precision floating-point numbers.\n    - float32: single-precision floating-point numbers.\n    - float16: half-precision floating-point numbers.\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n    - complex128: 128-bit complex numbers.\n    - complex64: 64-bit complex numbers.\n\n    Parameters\n    ----------\n    dtype: string\n        Numeric type.\n\n    Returns\n    -------\n    out: number\n        Size (in bytes).\n\n    Examples\n    --------\n    > var s = sizeOf( 'int8' )\n    1\n    > s = sizeOf( 'uint32' )\n    4\n\n    See Also\n    --------\n    realmax, typemax\n","Slice":"\nSlice( [stop] )\n    Returns a Slice.\n\n    Parameters\n    ----------\n    stop: integer|null|undefined (optional)\n        Ending index (exclusive).\n\n    Returns\n    -------\n    s: Slice\n        Slice instance.\n\n    Examples\n    --------\n    > var s = new Slice();\n    > s = new Slice( 10 );\n\n\nSlice( start, stop[, step] )\n    Returns a Slice.\n\n    Parameters\n    ----------\n    start: integer|null|undefined\n        Starting index (inclusive).\n\n    stop: integer|null|undefined\n        Ending index (exclusive).\n\n    step: integer|null|undefined (optional)\n        Index increment. A numeric index increment argument should be a non-zero\n        integer value. Default: null.\n\n    Returns\n    -------\n    s: Slice\n        Slice instance.\n\n    Examples\n    --------\n    > var s = new Slice( 2, 10 );\n    > s = new Slice( 2, 10, 1 );\n\n\nSlice.prototype.start\n    Read-only property returning the starting slice index.\n\n    Returns\n    -------\n    start: integer|null\n        Starting index.\n\n    Examples\n    --------\n    > var s = new Slice( 10 );\n    > s.start\n    null\n    > s = new Slice( 2, 10 );\n    > s.start\n    2\n\n\nSlice.prototype.stop\n    Read-only property returning the ending slice index.\n\n    Returns\n    -------\n    stop: integer|null\n        Ending index.\n\n    Examples\n    --------\n    > var s = new Slice( 10 );\n    > s.stop\n    10\n    > s = new Slice( 2, 10 );\n    > s.stop\n    10\n\n\nSlice.prototype.step\n    Read-only property returning the index increment.\n\n    Returns\n    -------\n    step: integer|null\n        Index increment.\n\n    Examples\n    --------\n    > var s = new Slice( 10 );\n    > s.step\n    null\n    > s = new Slice( 2, 10 );\n    > s.step\n    null\n    > s = new Slice( 2, 10, 1 );\n    > s.step\n    1\n\n\nSlice.prototype.toString()\n    Serializes a Slice as a string.\n\n    Returns\n    -------\n    str: string\n        Serialized Slice string.\n\n    Examples\n    --------\n    > var s = new Slice( 10 );\n    > s.toString()\n    'Slice(null,10,null)'\n    > s = new Slice( 2, 10, 1 );\n    > s.toString()\n    'Slice(2,10,1)'\n\n\nSlice.prototype.toJSON()\n    Serializes a Slice as a JSON object.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var s = new Slice( 10 );\n    > s.toJSON()\n    { 'type': 'Slice', 'data': [ null, 10, null ] }\n    > s = new Slice( 2, 10, 1 );\n    > s.toJSON()\n    { 'type': 'Slice', 'data': [ 2, 10, 1 ] }\n\n    See Also\n    --------\n    ndarray, MultiSlice\n","Slice.prototype.start":"\nSlice.prototype.start\n    Read-only property returning the starting slice index.\n\n    Returns\n    -------\n    start: integer|null\n        Starting index.\n\n    Examples\n    --------\n    > var s = new Slice( 10 );\n    > s.start\n    null\n    > s = new Slice( 2, 10 );\n    > s.start\n    2","Slice.prototype.stop":"\nSlice.prototype.stop\n    Read-only property returning the ending slice index.\n\n    Returns\n    -------\n    stop: integer|null\n        Ending index.\n\n    Examples\n    --------\n    > var s = new Slice( 10 );\n    > s.stop\n    10\n    > s = new Slice( 2, 10 );\n    > s.stop\n    10","Slice.prototype.step":"\nSlice.prototype.step\n    Read-only property returning the index increment.\n\n    Returns\n    -------\n    step: integer|null\n        Index increment.\n\n    Examples\n    --------\n    > var s = new Slice( 10 );\n    > s.step\n    null\n    > s = new Slice( 2, 10 );\n    > s.step\n    null\n    > s = new Slice( 2, 10, 1 );\n    > s.step\n    1","Slice.prototype.toString":"\nSlice.prototype.toString()\n    Serializes a Slice as a string.\n\n    Returns\n    -------\n    str: string\n        Serialized Slice string.\n\n    Examples\n    --------\n    > var s = new Slice( 10 );\n    > s.toString()\n    'Slice(null,10,null)'\n    > s = new Slice( 2, 10, 1 );\n    > s.toString()\n    'Slice(2,10,1)'","Slice.prototype.toJSON":"\nSlice.prototype.toJSON()\n    Serializes a Slice as a JSON object.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var s = new Slice( 10 );\n    > s.toJSON()\n    { 'type': 'Slice', 'data': [ null, 10, null ] }\n    > s = new Slice( 2, 10, 1 );\n    > s.toJSON()\n    { 'type': 'Slice', 'data': [ 2, 10, 1 ] }\n\n    See Also\n    --------\n    ndarray, MultiSlice","snakecase":"\nsnakecase( str )\n    Converts a string to snake case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Snake-cased string.\n\n    Examples\n    --------\n    > var out = snakecase( 'Hello World!' )\n    'hello_world'\n    > out = snakecase( 'I am a tiny little teapot' )\n    'i_am_a_tiny_little_teapot'\n\n    See Also\n    --------\n    camelcase, constantcase, kebabcase, pascalcase","some":"\nsome( collection, n )\n    Tests whether at least `n` elements in a collection are truthy.\n\n    The function immediately returns upon finding `n` truthy elements.\n\n    If provided an empty collection, the function returns `false`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    n: number\n        Minimum number of truthy elements.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if a collection contains at least `n` truthy\n        elements; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > var arr = [ 0, 0, 1, 2, 3 ];\n    > var bool = some( arr, 3 )\n    true\n\n    See Also\n    --------\n    any, every, forEach, none, someBy\n","someBy":"\nsomeBy( collection, n, predicate[, thisArg ] )\n    Tests whether a collection contains at least `n` elements which pass a test\n    implemented by a predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    The function immediately returns upon finding `n` successful elements.\n\n    If provided an empty collection, the function returns `false`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    n: number\n        Minimum number of successful elements.\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if a collection contains at least `n`\n        successful elements; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function negative( v ) { return ( v < 0 ); };\n    > var arr = [ 1, 2, -3, 4, -1 ];\n    > var bool = someBy( arr, 2, negative )\n    true\n\n    See Also\n    --------\n    anyBy, everyBy, forEach, noneBy, someByAsync, someByRight\n","someByAsync":"\nsomeByAsync( collection, n, [options,] predicate, done )\n    Tests whether a collection contains at least `n` elements which pass a test\n    implemented by a predicate function.\n\n    When invoked, the predicate function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If the\n    predicate function accepts two arguments, the predicate function is\n    provided:\n\n    - value\n    - next\n\n    If the predicate function accepts three arguments, the predicate function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other predicate function signature, the predicate function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - result: test result.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    The function immediately returns upon receiving `n` non-falsy `result`\n    values and calls the `done` callback with `null` as the first argument and\n    `true` as the second argument.\n\n    If all elements fail, the function calls the `done` callback with `null`\n    as the first argument and `false` as the second argument.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    n: number\n        Minimum number of successful elements.\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > someByAsync( arr, 2, predicate, done )\n    1000\n    2500\n    3000\n    false\n\n    // Limit number of concurrent invocations:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 3000, 2500, 1000 ];\n    > someByAsync( arr, 2, opts, predicate, done )\n    2500\n    3000\n    1000\n    false\n\n    // Process sequentially:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 3000, 2500, 1000 ];\n    > someByAsync( arr, 2, opts, predicate, done )\n    3000\n    2500\n    1000\n    false\n\n\nsomeByAsync.factory( [options,] predicate )\n    Returns a function which tests whether a collection contains at least `n`\n    elements which pass a test implemented by a predicate function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = someByAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, 2, done )\n    3000\n    2500\n    1000\n    false\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, 2, done )\n    2000\n    1500\n    1000\n    false\n\n    See Also\n    --------\n    anyByAsync, everyByAsync, forEachAsync, noneByAsync, someBy, someByRightAsync\n","someByAsync.factory":"\nsomeByAsync.factory( [options,] predicate )\n    Returns a function which tests whether a collection contains at least `n`\n    elements which pass a test implemented by a predicate function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = someByAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, 2, done )\n    3000\n    2500\n    1000\n    false\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, 2, done )\n    2000\n    1500\n    1000\n    false\n\n    See Also\n    --------\n    anyByAsync, everyByAsync, forEachAsync, noneByAsync, someBy, someByRightAsync","someByRight":"\nsomeByRight( collection, n, predicate[, thisArg ] )\n    Tests whether a collection contains at least `n` elements which pass a test\n    implemented by a predicate function, iterating from right to left.\n\n    The predicate function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    The function immediately returns upon finding `n` successful elements.\n\n    If provided an empty collection, the function returns `false`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    n: number\n        Minimum number of successful elements.\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if a collection contains at least `n`\n        successful elements; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function negative( v ) { return ( v < 0 ); };\n    > var arr = [ -1, 1, -2, 3, 4 ];\n    > var bool = someByRight( arr, 2, negative )\n    true\n\n    See Also\n    --------\n    anyByRight, everyByRight, forEachRight, noneByRight, someBy, someByRightAsync\n","someByRightAsync":"\nsomeByRightAsync( collection, n, [options,] predicate, done )\n    Tests whether a collection contains at least `n` elements which pass a test\n    implemented by a predicate function, iterating from right to left.\n\n    When invoked, the predicate function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection value.\n\n    The actual number of provided arguments depends on function length. If the\n    predicate function accepts two arguments, the predicate function is\n    provided:\n\n    - value\n    - next\n\n    If the predicate function accepts three arguments, the predicate function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other predicate function signature, the predicate function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - result: test result.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    The function immediately returns upon receiving `n` non-falsy `result`\n    values and calls the `done` callback with `null` as the first argument and\n    `true` as the second argument.\n\n    If all elements fail, the function calls the `done` callback with `null`\n    as the first argument and `false` as the second argument.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    n: number\n        Minimum number of successful elements.\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > someByRightAsync( arr, 2, predicate, done )\n    1000\n    2500\n    3000\n    false\n\n    // Limit number of concurrent invocations:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 1000, 2500, 3000 ];\n    > someByRightAsync( arr, 2, opts, predicate, done )\n    2500\n    3000\n    1000\n    false\n\n    // Process sequentially:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 1000, 2500, 3000 ];\n    > someByRightAsync( arr, 2, opts, predicate, done )\n    3000\n    2500\n    1000\n    false\n\n\nsomeByRightAsync.factory( [options,] predicate )\n    Returns a function which tests whether a collection contains at least `n`\n    elements which pass a test implemented by a predicate function, iterating\n    from right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = someByRightAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, 2, done )\n    3000\n    2500\n    1000\n    false\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, 2, done )\n    2000\n    1500\n    1000\n    false\n\n    See Also\n    --------\n    anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByAsync, someByRight\n","someByRightAsync.factory":"\nsomeByRightAsync.factory( [options,] predicate )\n    Returns a function which tests whether a collection contains at least `n`\n    elements which pass a test implemented by a predicate function, iterating\n    from right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = someByRightAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, 2, done )\n    3000\n    2500\n    1000\n    false\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, 2, done )\n    2000\n    1500\n    1000\n    false\n\n    See Also\n    --------\n    anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByAsync, someByRight","someInBy":"\nsomeInBy( obj, n, predicate[, thisArg ] )\n    Tests whether an object contains at least `n` properties\n    (own and inherited) which pass a test\n    implemented by a predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: object value.\n    - key: object key.\n    - obj: the input object.\n\n    The function immediately returns upon finding `n` successful properties.\n\n    If provided an empty object, the function returns `false`.\n\n    Parameters\n    ----------\n    obj: Object\n        Input object over which to iterate.\n\n    n: number\n        Minimum number of successful properties.\n\n    predicate: Function\n        Test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if an object contains at least `n`\n        successful properties; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function negative( v ) { return ( v < 0 ); };\n    > var obj = { 'a': 1, 'b': 2, 'c': -3, 'd': 4, 'e': -1 };\n    > var bool = someInBy( obj, 2, negative )\n    true\n\n    See Also\n    --------\n    anyInBy, everyInBy, someBy, someOwnBy","someOwnBy":"\nsomeOwnBy( obj, n, predicate[, thisArg ] )\n    Tests whether some `own` properties of a provided object\n    satisfy a predicate function for at least `n` properties.\n\n    The predicate function is provided three arguments:\n\n    - value: object value.\n    - key: object key.\n    - obj: the input object.\n\n    The function immediately returns upon finding `n` successful properties.\n\n    If provided an empty object, the function returns `false`.\n\n    Parameters\n    ----------\n    obj: Object\n        Input object over which to iterate.\n\n    n: number\n        Minimum number of successful properties.\n\n    predicate: Function\n        Test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if an object's own properties satisfy a\n        predicate for at least `n` properties; otherwise, the function\n        returns `false`.\n\n    Examples\n    --------\n    > function negative( v ) { return ( v < 0 ); };\n    > var obj = { a: 1, b: 2, c: -3, d: 4, e: -1 };\n    > var bool = someOwnBy( obj, 2, negative )\n    true\n\n    See Also\n    --------\n    anyOwnBy, everyOwnBy, someBy, someInBy","SOTU":"\nSOTU( [options] )\n    Returns State of the Union (SOTU) addresses.\n\n    Each State of the Union address is represented by an object with the\n    following fields:\n\n    - year: speech year.\n    - name: President name.\n    - party: the President's political party.\n    - text: speech text.\n\n    The following political parties are recognized:\n\n    - Democratic\n    - Republican\n    - Democratic-Republican\n    - Federalist\n    - National Union\n    - Whig\n    - Whig & Democratic\n    - none\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.name: String|Array<string> (optional)\n        President name(s).\n\n    options.party: String|Array<string> (optional)\n        Political party (or parties).\n\n    options.year: integer|Array<integer> (optional)\n        Year(s).\n\n    options.range: Array<integer> (optional)\n        Two-element array specifying a year range.\n\n    Returns\n    -------\n    out: Array<Object>\n        State of the Union addresses.\n\n    Examples\n    --------\n    > var out = SOTU()\n    [ {...}, {...}, ... ]\n\n    // Retrieve addresses by one or more Presidents...\n    > var opts = { 'name': 'Barack Obama' };\n    > out = SOTU( opts )\n    [ {...}, {...}, ... ]\n\n    // Retrieve addresses by one or more political parties...\n    > opts = { 'party': [ 'Democratic', 'Federalist' ] };\n    > out = SOTU( opts )\n    [ {...}, {...}, ... ]\n\n    // Retrieve addresses from one or more years...\n    > opts = { 'year': [ 2008, 2009, 2011 ] };\n    > out = SOTU( opts )\n    [ {...}, {...}, {...} ]\n\n    // Retrieve addresses from a range of consecutive years...\n    > opts = { 'range': [ 2008, 2016 ] }\n    > out = SOTU( opts )\n    [ {...}, {...}, ... ]\n\n","SPACHE_REVISED":"\nSPACHE_REVISED()\n    Returns a list of simple American-English words (revised Spache).\n\n    Returns\n    -------\n    out: Array<string>\n        List of simple American-English words.\n\n    Examples\n    --------\n    > var list = SPACHE_REVISED()\n    [ 'a', 'able', 'about', 'above', ... ]\n\n    References\n    ----------\n    - Spache, George. 1953. \"A New Readability Formula for Primary-Grade Reading\n    Materials.\" *The Elementary School Journal* 53 (7): 410–13. doi:10.1086/\n    458513.\n    - Klare, George R. 1974. \"Assessing Readability.\" *Reading Research\n    Quarterly* 10 (1). Wiley, International Reading Association: 62–102.\n    <http://www.jstor.org/stable/747086>.\n    - Stone, Clarence R. 1956. \"Measuring Difficulty of Primary Reading\n    Material: A Constructive Criticism of Spache's Measure.\" *The Elementary\n    School Journal* 57 (1). University of Chicago Press: 36–41.\n    <http://www.jstor.org/stable/999700>.\n    - Perera, Katherine. 2012. \"The assessment of linguistic difficulty in\n    reading material.\" In *Linguistics and the Teacher*, edited by Ronald\n    Carter, 101–13. Routledge Library Editions: Education. Taylor & Francis.\n    <https://books.google.com/books?id=oNXFQ9Gn6XIC>.\n\n","SPAM_ASSASSIN":"\nSPAM_ASSASSIN()\n    Returns the Spam Assassin public mail corpus.\n\n    Each array element has the following fields:\n\n    - id: message id (relative to message group).\n    - group: message group.\n    - checksum: object containing checksum info.\n    - text: message text (including headers).\n\n    The message group may be one of the following:\n\n    - easy-ham-1: easier to detect non-spam e-mails (2500 messages).\n    - easy-ham-2: easier to detect non-spam e-mails collected at a later date\n      (1400 messages).\n    - hard-ham-1: harder to detect non-spam e-mails (250 messages).\n    - spam-1: spam e-mails (500 messages).\n    - spam-2: spam e-mails collected at a later date (1396 messages).\n\n    The checksum object contains the following fields:\n\n    - type: checksum type (e.g., MD5).\n    - value: checksum value.\n\n    Returns\n    -------\n    out: Array<Object>\n        Corpus.\n\n    Examples\n    --------\n    > var data = SPAM_ASSASSIN()\n    [ {...}, {...}, ... ]\n\n","SparklineBase":"\nSparklineBase( [data,] [options] )\n    Returns a Sparkline instance.\n\n    This constructor is a base Sparkline constructor from which constructors\n    tailored to generating particular types of Sparkline graphics should be\n    derived.\n\n    At a minimum, descendants should implement a private `_render()` method\n    which will be automatically invoked by the public `render()` method.\n\n    The `data` argument takes precedence over the `data` option.\n\n    Parameters\n    ----------\n    data: ArrayLike|ndarray (optional)\n        Sparkline data.\n\n    options: Object (optional)\n        Options.\n\n    options.autoRender: boolean (optional)\n        Boolean indicating whether to re-render on a 'change' event. Default:\n        false.\n\n    options.bufferSize: integer|null (optional)\n        Data buffer size. If provided, data is kept in a first-in first-out\n        (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n    options.data: ArrayLike|ndarray (optional)\n        Sparkline data.\n\n    options.description: string (optional)\n        Sparkline description.\n\n    options.isDefined: Function (optional)\n        An accessor function indicating whether a datum is defined.\n\n    options.label: string (optional)\n        Data label.\n\n    Returns\n    -------\n    sparkline: Sparkline\n        Sparkline instance.\n\n    sparkline.autoRender\n        Rendering mode. If `true`, an instance renders on each 'change' event;\n        otherwise, rendering must be triggered manually.\n\n    sparkline.bufferSize\n        Data buffer size.\n\n    sparkline.description\n        Sparkline description.\n\n    sparkline.data\n        Sparkline data.\n\n    sparkline.label\n        Data label.\n\n    sparkline.isDefined( d, i )\n        An accessor function which defines whether a datum is defined. This\n        accessor is used to define how missing values are encoded. The default\n        behavior is to ignore values which are `NaN`.\n\n    sparkline.render()\n        Renders a sparkline. This method calls `_render()` which must be\n        implemented by instances and child classes. The default behavior is\n        throw an error.\n\n    Examples\n    --------\n    > var sparkline = new SparklineBase()\n    <Sparkline>\n\n    // Provide sparkline data at instantiation:\n    > var data = [ 1, 2, 3 ];\n    > sparkline = new SparklineBase( data )\n    <Sparkline>\n\n    See Also\n    --------\n    plot, Plot, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeWinLossChartSparkline\n","sparsearray2iterator":"\nsparsearray2iterator( src[, mapFcn[, thisArg]] )\n    Returns an iterator which iterates over the elements of a sparse array-like\n    object.\n\n    The returned iterator skips elements which are undefined.\n\n    When invoked, an input function is provided three arguments:\n\n    - value: iterated value.\n    - index: iterated value index.\n    - src: source array-like object.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an array's `@@iterator` method, regardless of whether this method is\n    defined. To convert an array to an implementation defined iterator, invoke\n    this method directly.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Sparse array-like object from which to create the iterator.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = sparsearray2iterator( [ 1, , 3, 4 ] );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    3\n\n    See Also\n    --------\n    iterator2array, array2iterator, sparsearray2iteratorRight\n","sparsearray2iteratorRight":"\nsparsearray2iteratorRight( src[, mapFcn[, thisArg]] )\n    Returns an iterator which iterates from right to left over the elements of a\n    sparse array-like object.\n\n    The returned iterator skips elements which are undefined.\n\n    When invoked, an input function is provided three arguments:\n\n    - value: iterated value.\n    - index: iterated value index.\n    - src: source array-like object.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an array's `@@iterator` method, regardless of whether this method is\n    defined. To convert an array to an implementation defined iterator, invoke\n    this method directly.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Sparse array-like object from which to create the iterator.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = sparsearray2iteratorRight( [ 1, 2, , 4 ] );\n    > var v = it.next().value\n    4\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    iterator2array, array2iteratorRight, sparsearray2iterator\n","splitStream":"\nsplitStream( [options] )\n    Returns a transform stream which splits streamed data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Separator used to split streamed data. A separator may be either a\n        regular expression or a string. A separator which is a regular\n        expression containing a matching group will result in the separator\n        being retained in the output stream.Default: /\\r?\\n/.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.writableObjectMode: boolean (optional)\n        Specifies whether the writable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream.\n\n    Examples\n    --------\n    > var s = splitStream();\n    > s.write( 'a\\nb\\nc' );\n    > s.end();\n\n\nsplitStream.factory( [options] )\n    Returns a function for creating transform streams for splitting streamed\n    data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Separator used to split streamed data. A separator may be either a\n        regular expression or a string. A separator which is a regular\n        expression containing a matching group will result in the separator\n        being retained in the output stream. Default: /\\r?\\n/.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.writableObjectMode: boolean (optional)\n        Specifies whether the writable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    createStream: Function\n        Function for creating transform streams.\n\n    Examples\n    --------\n    > var opts = { 'highWaterMark': 64 };\n    > var createStream = splitStream.factory( opts );\n    > var s = createStream();\n    > s.write( 'a\\nb\\nc' );\n    > s.end();\n\n\nsplitStream.objectMode( [options] )\n    Returns an \"objectMode\" transform stream for splitting streamed data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Separator used to split streamed data. A separator may be either a\n        regular expression or a string. A separator which is a regular\n        expression containing a matching group will result in the separator\n        being retained in the output stream. Default: /\\r?\\n/.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.writableObjectMode: boolean (optional)\n        Specifies whether the writable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > var s = splitStream.objectMode();\n    > s.write( 'a\\nb\\c' );\n    > s.end();\n\n    See Also\n    --------\n    joinStream\n","splitStream.factory":"\nsplitStream.factory( [options] )\n    Returns a function for creating transform streams for splitting streamed\n    data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Separator used to split streamed data. A separator may be either a\n        regular expression or a string. A separator which is a regular\n        expression containing a matching group will result in the separator\n        being retained in the output stream. Default: /\\r?\\n/.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.writableObjectMode: boolean (optional)\n        Specifies whether the writable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    createStream: Function\n        Function for creating transform streams.\n\n    Examples\n    --------\n    > var opts = { 'highWaterMark': 64 };\n    > var createStream = splitStream.factory( opts );\n    > var s = createStream();\n    > s.write( 'a\\nb\\nc' );\n    > s.end();","splitStream.objectMode":"\nsplitStream.objectMode( [options] )\n    Returns an \"objectMode\" transform stream for splitting streamed data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Separator used to split streamed data. A separator may be either a\n        regular expression or a string. A separator which is a regular\n        expression containing a matching group will result in the separator\n        being retained in the output stream. Default: /\\r?\\n/.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.writableObjectMode: boolean (optional)\n        Specifies whether the writable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > var s = splitStream.objectMode();\n    > s.write( 'a\\nb\\c' );\n    > s.end();\n\n    See Also\n    --------\n    joinStream","SQRT_EPS":"\nSQRT_EPS\n    Square root of double-precision floating-point epsilon.\n\n    Examples\n    --------\n    > SQRT_EPS\n    0.14901161193847656e-7\n\n    See Also\n    --------\n    EPS\n","SQRT_HALF":"\nSQRT_HALF\n    Square root of `1/2`.\n\n    Examples\n    --------\n    > SQRT_HALF\n    0.7071067811865476\n\n    See Also\n    --------\n    LN_HALF\n","SQRT_HALF_PI":"\nSQRT_HALF_PI\n    Square root of the mathematical constant `π` divided by `2`.\n\n    Examples\n    --------\n    > SQRT_HALF_PI\n    1.2533141373155003\n\n    See Also\n    --------\n    PI\n","SQRT_PHI":"\nSQRT_PHI\n    Square root of the golden ratio.\n\n    Examples\n    --------\n    > SQRT_PHI\n    1.272019649514069\n\n    See Also\n    --------\n    PHI\n","SQRT_PI":"\nSQRT_PI\n    Square root of the mathematical constant `π`.\n\n    Examples\n    --------\n    > SQRT_PI\n    1.7724538509055160\n\n    See Also\n    --------\n    PI\n","SQRT_THREE":"\nSQRT_THREE\n    Square root of `3`.\n\n    Examples\n    --------\n    > SQRT_THREE\n    1.7320508075688772\n\n","SQRT_TWO":"\nSQRT_TWO\n    Square root of `2`.\n\n    Examples\n    --------\n    > SQRT_TWO\n    1.4142135623730951\n\n    See Also\n    --------\n    LN2\n","SQRT_TWO_PI":"\nSQRT_TWO_PI\n    Square root of the mathematical constant `π` times `2`.\n\n    Examples\n    --------\n    > SQRT_TWO_PI\n    2.5066282746310007\n\n    See Also\n    --------\n    TWO_PI\n","SSA_US_BIRTHS_2000_2014":"\nSSA_US_BIRTHS_2000_2014()\n    Returns US birth data from 2000 to 2014, as provided by the Social Security\n    Administration.\n\n    Returns\n    -------\n    out: Array<Object>\n        Birth data.\n\n    Examples\n    --------\n    > var data = SSA_US_BIRTHS_2000_2014()\n    [ {...}, ... ]\n\n    See Also\n    --------\n    CDC_NCHS_US_BIRTHS_1969_1988, CDC_NCHS_US_BIRTHS_1994_2003\n","sswap":"\nsswap( x, y[, dim] )\n    Interchanges two single-precision floating-point vectors.\n\n    For multi-dimensional input arrays, the function performs batched\n    computation, such that the function interchanges each pair of vectors in `x`\n    and `y` according to the specified dimension index.\n\n    Both input arrays must have the same shape.\n\n    Parameters\n    ----------\n    x: ndarray\n        First input array. Must have a 'float32' data type. Must have at least\n        one dimension and must have the same shape as the second input array.\n\n    y: ndarray\n        Second input array. Must have a 'float32' data type. Must have at least\n        one dimension and must have the same shape as the first input array.\n\n    dim: integer (optional)\n        Dimension index along which to interchange vectors. Must be a negative\n        integer. Negative indices are resolved relative to the last array\n        dimension, with the last dimension corresponding to `-1`. Default: -1.\n\n    Returns\n    -------\n    y: ndarray\n        The second input array `y`.\n\n    Examples\n    --------\n    > var x = array( new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n    > var y = array( new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n    > sswap( x, y );\n    > x.data\n    <Float32Array>[ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n    > y.data\n    <Float32Array>[ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n    See Also\n    --------\n    base.strided.sswap, dswap, gswap\n","Stack":"\nStack()\n    Stack constructor.\n\n    A stack is also referred to as a \"last-in-first-out\" queue.\n\n    Returns\n    -------\n    stack: Object\n        Stack data structure.\n\n    stack.clear: Function\n        Clears the stack.\n\n    stack.first: Function\n        Returns the \"newest\" stack value (i.e., the value which is \"first-out\").\n        If the stack is empty, the returned value is `undefined`.\n\n    stack.iterator: Function\n        Returns an iterator for iterating over a stack. If an environment\n        supports Symbol.iterator, the returned iterator is iterable. Note that,\n        in order to prevent confusion arising from stack mutation during\n        iteration, a returned iterator **always** iterates over a stack\n        \"snapshot\", which is defined as the list of stack elements at the time\n        of the method's invocation.\n\n    stack.last: Function\n        Returns the \"oldest\" stack value (i.e., the value which is \"last-out\").\n        If the stack is empty, the returned value is `undefined`.\n\n    stack.length: integer\n        Stack length.\n\n    stack.pop: Function\n        Removes and returns the current \"first-out\" value from the stack. If the\n        stack is empty, the returned value is `undefined`.\n\n    stack.push: Function\n        Adds a value to the stack.\n\n    stack.toArray: Function\n        Returns an array of stack values.\n\n    stack.toJSON: Function\n        Serializes a stack as JSON.\n\n    Examples\n    --------\n    > var s = Stack();\n    > s.push( 'foo' ).push( 'bar' );\n    > s.length\n    2\n    > s.pop()\n    'bar'\n    > s.length\n    1\n    > s.pop()\n    'foo'\n    > s.length\n    0\n\n    See Also\n    --------\n    FIFO\n","standalone2pkg":"\nstandalone2pkg( pkg )\n    Returns the internal package name associated with a provided standalone\n    package name.\n\n    Parameters\n    ----------\n    pkg: string\n        Standalone package name.\n\n    Returns\n    -------\n    out: string|null\n        Internal package name.\n\n    Examples\n    --------\n    > var v = standalone2pkg( '@stdlib/math-base-special-sin' )\n    '@stdlib/math/base/special/sin'\n\n    See Also\n    --------\n    alias2standalone, pkg2alias, pkg2standalone\n","STANDARD_CARD_DECK":"\nSTANDARD_CARD_DECK()\n    Returns a string array containing two or three letter abbreviations for each\n    card in a standard 52-card deck.\n\n    Abbreviation format: <card><suit>\n\n    Cards: A, 2, 3, 4, 5, 6, 7, 8, 9, 10, J, Q, K, where\n\n    - A: ace\n    - J: jack\n    - Q: queen\n    - K: king\n\n    Suit abbreviations:\n\n    - C: clubs\n    - D: diamonds\n    - H: hearts\n    - S: spades\n\n    Returns\n    -------\n    out: Array<string>\n        List of cards.\n\n    Examples\n    --------\n    > var list = STANDARD_CARD_DECK()\n    [ 'AC', '2C', '3C', ... ]\n\n","startcase":"\nstartcase( str )\n    Capitalizes the first letter of each word in an input string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        String containing words where each first letter is capitalized.\n\n    Examples\n    --------\n    > var out = startcase( 'beep boop' )\n    'Beep Boop'\n\n    See Also\n    --------\n    lowercase, uppercase\n","startsWith":"\nstartsWith( str, search[, position] )\n    Tests if a string starts with the characters of another string.\n\n    If provided an empty search string, the function always returns `true`.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search string.\n\n    position: integer (optional)\n        Position at which to start searching for `search`. If less than `0`, the\n        start position is determined relative to the end of the input string.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a string starts with the characters of\n        another string.\n\n    Examples\n    --------\n    > var bool = startsWith( 'Beep', 'Be' )\n    true\n    > bool = startsWith( 'Beep', 'ep' )\n    false\n    > bool = startsWith( 'Beep', 'ee', 1 )\n    true\n    > bool = startsWith( 'Beep', 'ee', -3 )\n    true\n    > bool = startsWith( 'Beep', '' )\n    true\n\n    See Also\n    --------\n    endsWith\n","STOPWORDS_EN":"\nSTOPWORDS_EN()\n    Returns a list of English stop words.\n\n    Returns\n    -------\n    out: Array<string>\n        List of stop words.\n\n    Examples\n    --------\n    > var list = STOPWORDS_EN()\n    [ 'a', 'about', 'above', 'across', ... ]\n\n","strided.abs":"\nstrided.abs( N, dtypeX, x, strideX, dtypeY, y, strideY )\n    Computes the absolute value for each element in a strided array `x` and\n    assigns the results to elements in a strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs( x.length, 'float64', x, 1, 'float64', y, 1 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs( 2, x, 2, y, -1 )\n    <Float64Array>[ 3.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.abs( 2, 'float64', x1, -2, 'float64', y1, 1 )\n    <Float64Array>[ 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nstrided.abs.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the absolute value for each element in a strided array `x` and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    strided.abs2, base.strided.dabs, base.strided.sabs\n","strided.abs.ndarray":"\nstrided.abs.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the absolute value for each element in a strided array `x` and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    strided.abs2, base.strided.dabs, base.strided.sabs","strided.abs2":"\nstrided.abs2( N, dtypeX, x, strideX, dtypeY, y, strideY )\n    Computes the squared absolute value for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs2( x.length, 'float64', x, 1, 'float64', y, 1 )\n    <Float64Array>[ 4.0, 1.0, 9.0, 25.0 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs2( 2, 'float64', x, 2, 'float64', y, -1 )\n    <Float64Array>[ 9.0, 4.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.abs2( 2, 'float64', x1, -2, 'float64', y1, 1 )\n    <Float64Array>[ 25.0, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 25.0, 1.0 ]\n\n\nstrided.abs2.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the squared absolute value for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs2.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 4.0, 1.0, 9.0, 25.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs2.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 25.0, 1.0 ]\n\n    See Also\n    --------\n    strided.abs, base.strided.dabs2, base.strided.sabs2\n","strided.abs2.ndarray":"\nstrided.abs2.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the squared absolute value for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs2.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 4.0, 1.0, 9.0, 25.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs2.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 25.0, 1.0 ]\n\n    See Also\n    --------\n    strided.abs, base.strided.dabs2, base.strided.sabs2","strided.abs2By":"\nstrided.abs2By( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the squared absolute value of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -1.0, -2.0, -3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.abs2By( x.length, x, 1, y, 1, clbk )\n    [ 1.0, 4.0, 9.0, 16.0 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.abs2By( 2, x, 2, y, -1, clbk )\n    [ 9.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.abs2By( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ 16.0, 4.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 16.0, 4.0 ]\n\n\nstrided.abs2By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the squared absolute value of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -1.0, -2.0, -3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.abs2By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 1.0, 4.0, 9.0, 16.0 ]\n\n    // Advanced indexing:\n    > x = [ -1.0, -2.0, -3.0, -4.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.abs2By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, 16.0, 4.0 ]\n\n    See Also\n    --------\n    strided.absBy, strided.abs2\n","strided.abs2By.ndarray":"\nstrided.abs2By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the squared absolute value of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -1.0, -2.0, -3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.abs2By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 1.0, 4.0, 9.0, 16.0 ]\n\n    // Advanced indexing:\n    > x = [ -1.0, -2.0, -3.0, -4.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.abs2By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, 16.0, 4.0 ]\n\n    See Also\n    --------\n    strided.absBy, strided.abs2","strided.absBy":"\nstrided.absBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the absolute value of each element retrieved from a strided input\n    array `x` via a callback function and assigns each result to an element in a\n    strided output array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v * 2.0; };\n    > strided.absBy( x.length, x, 1, y, 1, clbk )\n    [ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.absBy( 2, x, 2, y, -1, clbk )\n    [ 6.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.absBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ 8.0, 4.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 8.0, 4.0 ]\n\n\nstrided.absBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the absolute value of each element retrieved from a strided input\n    array `x` via a callback function and assigns each result to an element in a\n    strided output array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v * 2.0; };\n    > strided.absBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.absBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, 8.0, 4.0 ]\n\n    See Also\n    --------\n    strided.abs, strided.abs2By\n","strided.absBy.ndarray":"\nstrided.absBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the absolute value of each element retrieved from a strided input\n    array `x` via a callback function and assigns each result to an element in a\n    strided output array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v * 2.0; };\n    > strided.absBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.absBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, 8.0, 4.0 ]\n\n    See Also\n    --------\n    strided.abs, strided.abs2By","strided.acosBy":"\nstrided.acosBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the arccosine of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 0.707, 0.866, -0.707 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acosBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, ~0.786, ~0.524, ~2.356 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acosBy( 2, x, 2, y, -1, clbk )\n    [ ~0.524, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 0.707, 0.866, -0.707 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.acosBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~2.356, ~0.786 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~2.356, ~0.786 ]\n\n\nstrided.acosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the arccosine of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 0.707, 0.866, -0.707 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~0.786, ~0.524, ~2.356 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 0.707, 0.866, -0.707 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~2.356, ~0.786 ]\n\n","strided.acosBy.ndarray":"\nstrided.acosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the arccosine of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 0.707, 0.866, -0.707 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~0.786, ~0.524, ~2.356 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 0.707, 0.866, -0.707 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~2.356, ~0.786 ]","strided.acoshBy":"\nstrided.acoshBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the hyperbolic arccosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 1.5, 2.0, 2.5 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acoshBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, ~0.962, ~1.317, ~1.567 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acoshBy( 2, x, 2, y, -1, clbk )\n    [ ~1.317, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 1.5, 2.0, 2.5 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.acoshBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~1.567, ~0.962 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~1.567, ~0.962 ]\n\n\nstrided.acoshBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the hyperbolic arccosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 1.5, 2.0, 2.5 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acoshBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~0.962, ~1.317, ~1.567 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 1.5, 2.0, 2.5 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acoshBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~1.567, ~0.962 ]\n\n","strided.acoshBy.ndarray":"\nstrided.acoshBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the hyperbolic arccosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 1.5, 2.0, 2.5 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acoshBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~0.962, ~1.317, ~1.567 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 1.5, 2.0, 2.5 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acoshBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~1.567, ~0.962 ]","strided.acotBy":"\nstrided.acotBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the inverse cotangent of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -2.5, -1.5, -0.5, 0.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acotBy( x.length, x, 1, y, 1, clbk )\n    [ ~-0.381, ~-0.588, ~-1.107, ~1.571 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acotBy( 2, x, 2, y, -1, clbk )\n    [ ~-1.107, ~-0.381, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -2.5, -1.5, -0.5, 0.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.acotBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~1.571, ~-0.588 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~1.571, ~-0.588 ]\n\n\nstrided.acotBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse cotangent of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -2.5, -1.5, -0.5, 0.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acotBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ ~-0.381, ~-0.588, ~-1.107, ~1.571 ]\n\n    // Advanced indexing:\n    > x = [ -2.5, -1.5, -0.5, 0.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acotBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~1.571, ~-0.588 ]\n\n","strided.acotBy.ndarray":"\nstrided.acotBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse cotangent of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -2.5, -1.5, -0.5, 0.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acotBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ ~-0.381, ~-0.588, ~-1.107, ~1.571 ]\n\n    // Advanced indexing:\n    > x = [ -2.5, -1.5, -0.5, 0.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acotBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~1.571, ~-0.588 ]","strided.acothBy":"\nstrided.acothBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the inverse hyperbolic cotangent of each element retrieved from an\n    input strided array `x` via a callback function and assigns each result to\n    an element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -5.0, -4.0, -3.0, -1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acothBy( x.length, x, 1, y, 1, clbk )\n    [ ~-0.203, ~-0.255, ~-0.347, -Infinity ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acothBy( 2, x, 2, y, -1, clbk )\n    [ ~-0.347, ~-0.203, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -5.0, -4.0, -3.0, -1.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.acothBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ -Infinity, ~-0.255 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, -Infinity, ~-0.255 ]\n\n\nstrided.acothBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse hyperbolic cotangent of each element retrieved from an\n    input strided array `x` via a callback function and assigns each result to\n    an element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -5.0, -4.0, -3.0, -1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acothBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ ~-0.203, ~-0.255, ~-0.347, -Infinity ]\n\n    // Advanced indexing:\n    > x = [ -5.0, -4.0, -3.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acothBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, -Infinity, ~-0.255 ]\n\n","strided.acothBy.ndarray":"\nstrided.acothBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse hyperbolic cotangent of each element retrieved from an\n    input strided array `x` via a callback function and assigns each result to\n    an element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -5.0, -4.0, -3.0, -1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acothBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ ~-0.203, ~-0.255, ~-0.347, -Infinity ]\n\n    // Advanced indexing:\n    > x = [ -5.0, -4.0, -3.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acothBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, -Infinity, ~-0.255 ]","strided.acovercosBy":"\nstrided.acovercosBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the inverse coversed cosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acovercosBy( x.length, x, 1, y, 1, clbk )\n    [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acovercosBy( 2, x, 2, y, -1, clbk )\n    [ ~0.524, ~1.571, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, -1.57, -0.5, -1.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.acovercosBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ 0.0, ~-0.607 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, ~-0.607 ]\n\n\nstrided.acovercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse coversed cosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acovercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -1.57, -0.5, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acovercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, 0.0, ~-0.607 ]\n\n","strided.acovercosBy.ndarray":"\nstrided.acovercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse coversed cosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acovercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -1.57, -0.5, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acovercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, 0.0, ~-0.607 ]","strided.acoversinBy":"\nstrided.acoversinBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the inverse coversed sine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acoversinBy( x.length, x, 1, y, 1, clbk )\n    [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acoversinBy( 2, x, 2, y, -1, clbk )\n    [ ~0.524, ~1.571, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.acoversinBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ 0.0, ~-0.607 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, ~-0.607 ]\n\n\nstrided.acoversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse coversed sine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acoversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.57, 0.5, 1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acoversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, 0.0, ~-0.607 ]\n\n","strided.acoversinBy.ndarray":"\nstrided.acoversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse coversed sine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acoversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.57, 0.5, 1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acoversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, 0.0, ~-0.607 ]","strided.add":"\nstrided.add( N, dx, x, sx, dy, y, sy, dz, z, sz )\n    Adds each element in a strided array `x` to a corresponding element in a\n    strided array `y` and assigns the results to elements in a strided array\n    `z`.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dx: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    dy: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    dz: any\n        Data type for `z`.\n\n    z: ArrayLikeObject\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    Returns\n    -------\n    z: ArrayLikeObject\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var dt = 'float64';\n    > strided.add( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\n    <Float64Array>[ -1.0, 3.0, 6.0, -1.0 ]\n\n    // Using `N` and stride parameters:\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.add( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\n    <Float64Array>[ 1.0, 4.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > strided.add( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\n    <Float64Array>[ -2.0, 5.0 ]\n    > z0\n    <Float64Array>[ 0.0, 0.0, -2.0, 5.0 ]\n\n\nstrided.add.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n    Adds each element in a strided array `x` to a corresponding element in a\n    strided array `y` and assigns the results to elements in a strided array\n    `z` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dx: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    dy: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    dz: any\n        Data type for `z`.\n\n    z: ArrayLikeObject\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    Returns\n    -------\n    z: ArrayLikeObject\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var dt = 'float64';\n    > strided.add.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n    <Float64Array>[ -1.0, 3.0, 6.0, -1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.add.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n    <Float64Array>[ 0.0, 5.0, -2.0, 0.0 ]\n\n    See Also\n    --------\n    strided.mul, strided.sub\n","strided.add.ndarray":"\nstrided.add.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n    Adds each element in a strided array `x` to a corresponding element in a\n    strided array `y` and assigns the results to elements in a strided array\n    `z` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dx: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    dy: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    dz: any\n        Data type for `z`.\n\n    z: ArrayLikeObject\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    Returns\n    -------\n    z: ArrayLikeObject\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var dt = 'float64';\n    > strided.add.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n    <Float64Array>[ -1.0, 3.0, 6.0, -1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.add.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n    <Float64Array>[ 0.0, 5.0, -2.0, 0.0 ]\n\n    See Also\n    --------\n    strided.mul, strided.sub","strided.addBy":"\nstrided.addBy( N, x, sx, y, sy, z, sz, clbk[, thisArg] )\n    Performs element-wise addition of two strided arrays via a callback function\n    and assigns each result to an element in an output strided array.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided four arguments:\n\n    - values: input array elements.\n    - idx: iteration index.\n    - indices: strided array indices (offset + idx*stride).\n    - arrays: input and output arrays.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n    > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( values ) { return values; };\n    > strided.addBy( x.length, x, 1, y, 1, z, 1, clbk )\n    [ 12.0, 14.0, 16.0, 18.0 ]\n\n    // Using `N` and stride parameters:\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.addBy( 2, x, 2, y, -1, z, 1, clbk )\n    [ 13.0, 14.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\n    > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > strided.addBy( 2, x1, -2, y1, 1, z1, 1, clbk )\n    <Float64Array>[ 17.0, 16.0 ]\n    > z0\n    <Float64Array>[ 0.0, 0.0, 17.0, 16.0 ]\n\n\nstrided.addBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n    Performs element-wise addition of two strided arrays via a callback function\n    and assigns each result to an element in an output strided array using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n    > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( values ) { return values; };\n    > strided.addBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n    [ 12.0, 14.0, 16.0, 18.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0 ];\n    > y = [ 11.0, 12.0, 13.0, 14.0 ];\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > var oy = y.length - 1;\n    > var oz = z.length - 1;\n    > strided.addBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n    [ 0.0, 0.0, 17.0, 16.0 ]\n\n    See Also\n    --------\n    strided.add, strided.mulBy, strided.subBy\n","strided.addBy.ndarray":"\nstrided.addBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n    Performs element-wise addition of two strided arrays via a callback function\n    and assigns each result to an element in an output strided array using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n    > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( values ) { return values; };\n    > strided.addBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n    [ 12.0, 14.0, 16.0, 18.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0 ];\n    > y = [ 11.0, 12.0, 13.0, 14.0 ];\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > var oy = y.length - 1;\n    > var oz = z.length - 1;\n    > strided.addBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n    [ 0.0, 0.0, 17.0, 16.0 ]\n\n    See Also\n    --------\n    strided.add, strided.mulBy, strided.subBy","strided.ahavercosBy":"\nstrided.ahavercosBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the inverse half-value versed cosine of each element retrieved from\n    an input strided array `x` via a callback function and assigns each result\n    to an element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.ahavercosBy( x.length, x, 1, y, 1, clbk )\n    [ ~3.142, ~1.571, 0.0, ~2.094 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.ahavercosBy( 2, x, 2, y, -1, clbk )\n    [ 0.0, ~3.142, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 0.5, 1.0, 0.25 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.ahavercosBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~2.094, ~1.571 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~2.094, ~1.571 ]\n\n\nstrided.ahavercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse half-value versed cosine of each element retrieved from\n    an input strided array `x` via a callback function and assigns each result\n    to an element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.ahavercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ ~3.142, ~1.571, 0.0, ~2.094 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 0.5, 1.0, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.ahavercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~2.094, ~1.571 ]\n\n    See Also\n    --------\n    strided.ahaversinBy\n","strided.ahavercosBy.ndarray":"\nstrided.ahavercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse half-value versed cosine of each element retrieved from\n    an input strided array `x` via a callback function and assigns each result\n    to an element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.ahavercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ ~3.142, ~1.571, 0.0, ~2.094 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 0.5, 1.0, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.ahavercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~2.094, ~1.571 ]\n\n    See Also\n    --------\n    strided.ahaversinBy","strided.ahaversinBy":"\nstrided.ahaversinBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the inverse half-value versed sine of each element retrieved from\n    an input strided array `x` via a callback function and assigns each result\n    to an element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.ahaversinBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, ~1.571, ~3.142, ~1.047 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.ahaversinBy( 2, x, 2, y, -1, clbk )\n    [ ~3.142, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 0.5, 1.0, 0.25 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.ahaversinBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~1.047, ~1.571 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~1.047, ~1.571 ]\n\n\nstrided.ahaversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse half-value versed sine of each element retrieved from\n    an input strided array `x` via a callback function and assigns each result\n    to an element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.ahaversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~1.571, ~3.142, ~1.047 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 0.5, 1.0, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.ahaversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~1.047, ~1.571 ]\n\n    See Also\n    --------\n    strided.ahavercosBy\n","strided.ahaversinBy.ndarray":"\nstrided.ahaversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse half-value versed sine of each element retrieved from\n    an input strided array `x` via a callback function and assigns each result\n    to an element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.ahaversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~1.571, ~3.142, ~1.047 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 0.5, 1.0, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.ahaversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~1.047, ~1.571 ]\n\n    See Also\n    --------\n    strided.ahavercosBy","strided.asinBy":"\nstrided.asinBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the arcsine of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.asinBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, ~-0.524, ~1.571, ~-0.253 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.asinBy( 2, x, 2, y, -1, clbk )\n    [ ~1.571, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, -0.5, 1.0, -0.25 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.asinBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~-0.253, ~-0.524 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~-0.253, ~-0.524 ]\n\n\nstrided.asinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the arcsine of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.asinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~-0.524, ~1.571, ~-0.253 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -0.5, 1.0, -0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.asinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.253, ~-0.524 ]\n\n    See Also\n    --------\n    strided.asinhBy\n","strided.asinBy.ndarray":"\nstrided.asinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the arcsine of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.asinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~-0.524, ~1.571, ~-0.253 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -0.5, 1.0, -0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.asinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.253, ~-0.524 ]\n\n    See Also\n    --------\n    strided.asinhBy","strided.asinhBy":"\nstrided.asinhBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the hyperbolic arcsine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.0, 2.0, -2.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.asinhBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, 0.0, ~1.444, ~-1.444 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.asinhBy( 2, x, 2, y, -1, clbk )\n    [ ~1.444, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, -0.0, 2.0, -2.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.asinhBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~-1.444, 0.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~-1.444, 0.0 ]\n\n\nstrided.asinhBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the hyperbolic arcsine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.0, 2.0, -2.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.asinhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, 0.0, ~1.444, ~-1.444 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -0.0, 2.0, -2.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.asinhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-1.444, 0.0 ]\n\n    See Also\n    --------\n    strided.asinBy\n","strided.asinhBy.ndarray":"\nstrided.asinhBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the hyperbolic arcsine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.0, 2.0, -2.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.asinhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, 0.0, ~1.444, ~-1.444 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -0.0, 2.0, -2.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.asinhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-1.444, 0.0 ]\n\n    See Also\n    --------\n    strided.asinBy","strided.atanBy":"\nstrided.atanBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the arctangent of each element retrieved from an input strided\n    array `x` via a callback function and assigns each result to an element in\n    an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.5, 1.0, -1.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.atanBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, ~-0.464, ~0.785, ~-0.896 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.atanBy( 2, x, 2, y, -1, clbk )\n    [ ~0.785, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, -0.5, 1.0, -1.25 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.atanBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~-0.896, ~-0.464 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~-0.896, ~-0.464 ]\n\n\nstrided.atanBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the arctangent of each element retrieved from an input strided\n    array `x` via a callback function and assigns each result to an element in\n    an output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.5, 1.0, -1.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.atanBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~-0.464, ~0.785, ~-0.896 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -0.5, 1.0, -1.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.atanBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.896, ~-0.464 ]\n\n    See Also\n    --------\n    strided.atanhBy\n","strided.atanBy.ndarray":"\nstrided.atanBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the arctangent of each element retrieved from an input strided\n    array `x` via a callback function and assigns each result to an element in\n    an output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.5, 1.0, -1.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.atanBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~-0.464, ~0.785, ~-0.896 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -0.5, 1.0, -1.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.atanBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.896, ~-0.464 ]\n\n    See Also\n    --------\n    strided.atanhBy","strided.atanhBy":"\nstrided.atanhBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the hyperbolic arctangent of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.atanhBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, ~-0.549, Infinity, ~-0.255 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.atanhBy( 2, x, 2, y, -1, clbk )\n    [ Infinity, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, -0.5, 1.0, -0.25 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.atanhBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~-0.255, ~-0.549 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~-0.255, ~-0.549 ]\n\n\nstrided.atanhBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the hyperbolic arctangent of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.atanhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~-0.549, Infinity, ~-0.255 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -0.5, 1.0, -0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.atanhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.255, ~-0.549 ]\n\n    See Also\n    --------\n    strided.atanBy\n","strided.atanhBy.ndarray":"\nstrided.atanhBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the hyperbolic arctangent of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.atanhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~-0.549, Infinity, ~-0.255 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -0.5, 1.0, -0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.atanhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.255, ~-0.549 ]\n\n    See Also\n    --------\n    strided.atanBy","strided.avercosBy":"\nstrided.avercosBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the inverse versed cosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.avercosBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.avercosBy( 2, x, 2, y, -1, clbk )\n    [ ~1.047, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, -1.57, -0.5, -1.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.avercosBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~1.571, ~2.177 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~1.571, ~2.177 ]\n\n\nstrided.avercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse versed cosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.avercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -1.57, -0.5, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.avercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~1.571, ~2.177 ]\n\n","strided.avercosBy.ndarray":"\nstrided.avercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse versed cosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.avercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -1.57, -0.5, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.avercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~1.571, ~2.177 ]","strided.aversinBy":"\nstrided.aversinBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the inverse versed sine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.aversinBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.aversinBy( 2, x, 2, y, -1, clbk )\n    [ ~1.047, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.aversinBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~1.571, ~2.177 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~1.571, ~2.177 ]\n\n\nstrided.aversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse versed sine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.aversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.57, 0.5, 1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.aversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~1.571, ~2.177 ]\n\n","strided.aversinBy.ndarray":"\nstrided.aversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse versed sine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.aversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.57, 0.5, 1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.aversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~1.571, ~2.177 ]","strided.besselj0By":"\nstrided.besselj0By( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the Bessel function of the first kind of order zero for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.besselj0By( x.length, x, 1, y, 1, clbk )\n    [ 1.0, ~0.765, ~0.998, ~0.984 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.besselj0By( 2, x, 2, y, -1, clbk )\n    [ ~0.998, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.besselj0By( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~0.984, ~0.765 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~0.984, ~0.765 ]\n\n\nstrided.besselj0By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the Bessel function of the first kind of order zero for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.besselj0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 1.0, ~0.765, ~0.998, ~0.984 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.besselj0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~0.984, ~0.765 ]\n\n    See Also\n    --------\n    strided.besselj1By, strided.bessely0By, strided.bessely1By\n","strided.besselj0By.ndarray":"\nstrided.besselj0By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the Bessel function of the first kind of order zero for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.besselj0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 1.0, ~0.765, ~0.998, ~0.984 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.besselj0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~0.984, ~0.765 ]\n\n    See Also\n    --------\n    strided.besselj1By, strided.bessely0By, strided.bessely1By","strided.besselj1By":"\nstrided.besselj1By( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the Bessel function of the first kind of order one for each element\n    retrieved from an input strided array `x` via a callback function and\n    assigns each result to an element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.besselj1By( x.length, x, 1, y, 1, clbk )\n    [ 0.0, ~0.44, ~0.05, ~0.124 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.besselj1By( 2, x, 2, y, -1, clbk )\n    [ ~0.05, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.besselj1By( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~0.124, ~0.44 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~0.124, ~0.44 ]\n\n\nstrided.besselj1By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the Bessel function of the first kind of order one for each element\n    retrieved from an input strided array `x` via a callback function and\n    assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.besselj1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~0.44, ~0.05, ~0.124 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.besselj1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~0.124, ~0.44 ]\n\n    See Also\n    --------\n    strided.besselj0By, strided.bessely0By, strided.bessely1By\n","strided.besselj1By.ndarray":"\nstrided.besselj1By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the Bessel function of the first kind of order one for each element\n    retrieved from an input strided array `x` via a callback function and\n    assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.besselj1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~0.44, ~0.05, ~0.124 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.besselj1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~0.124, ~0.44 ]\n\n    See Also\n    --------\n    strided.besselj0By, strided.bessely0By, strided.bessely1By","strided.bessely0By":"\nstrided.bessely0By( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the Bessel function of the second kind of order zero for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.bessely0By( x.length, x, 1, y, 1, clbk )\n    [ -Infinity, ~0.088, ~-1.534, ~-0.932 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.bessely0By( 2, x, 2, y, -1, clbk )\n    [ ~-1.534, -Infinity, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.bessely0By( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~-0.932, ~0.088 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~-0.932, ~0.088 ]\n\n\nstrided.bessely0By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the Bessel function of the second kind of order zero for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.bessely0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ -Infinity, ~0.088, ~-1.534, ~-0.932 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.bessely0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.932, ~0.088 ]\n\n    See Also\n    --------\n    strided.besselj0By, strided.besselj1By, strided.bessely1By\n","strided.bessely0By.ndarray":"\nstrided.bessely0By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the Bessel function of the second kind of order zero for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.bessely0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ -Infinity, ~0.088, ~-1.534, ~-0.932 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.bessely0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.932, ~0.088 ]\n\n    See Also\n    --------\n    strided.besselj0By, strided.besselj1By, strided.bessely1By","strided.bessely1By":"\nstrided.bessely1By( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the Bessel function of the second kind of order one for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.bessely1By( x.length, x, 1, y, 1, clbk )\n    [ -Infinity, ~-0.781, ~-6.459, ~-2.704 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.bessely1By( 2, x, 2, y, -1, clbk )\n    [ ~-6.459, -Infinity, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.bessely1By( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~-2.704, ~-0.781 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~-2.704, ~-0.781 ]\n\n\nstrided.bessely1By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the Bessel function of the second kind of order one for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.bessely1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ -Infinity, ~-0.781, ~-6.459, ~-2.704 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.bessely1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-2.704, ~-0.781 ]\n\n    See Also\n    --------\n    strided.besselj0By, strided.besselj1By, strided.bessely0By\n","strided.bessely1By.ndarray":"\nstrided.bessely1By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the Bessel function of the second kind of order one for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.bessely1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ -Infinity, ~-0.781, ~-6.459, ~-2.704 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.bessely1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-2.704, ~-0.781 ]\n\n    See Also\n    --------\n    strided.besselj0By, strided.besselj1By, strided.bessely0By","strided.binetBy":"\nstrided.binetBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Evaluates Binet's formula extended to real numbers for each element\n    retrieved from an input strided array `x` via a callback function and\n    assigns each result to an element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.binetBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, 1.0, 1.0, 2.0 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.binetBy( 2, x, 2, y, -1, clbk )\n    [ 1.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.binetBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ 2.0, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 2.0, 1.0 ]\n\n\nstrided.binetBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Evaluates Binet's formula extended to real numbers for each element\n    retrieved from an input strided array `x` via a callback function and\n    assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.binetBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, 1.0, 1.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 2.0, 3.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.binetBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, 2.0, 1.0 ]\n\n","strided.binetBy.ndarray":"\nstrided.binetBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Evaluates Binet's formula extended to real numbers for each element\n    retrieved from an input strided array `x` via a callback function and\n    assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.binetBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, 1.0, 1.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 2.0, 3.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.binetBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, 2.0, 1.0 ]","strided.cbrt":"\nstrided.cbrt( N, dtypeX, x, strideX, dtypeY, y, strideY )\n    Computes the cube root of each element in a strided array `x` and assigns\n    the results to elements in a strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.cbrt( x.length, 'float64', x, 1, 'float64', y, 1 )\n    <Float64Array>[ 0.0, 1.0, 2.0, 3.0 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.cbrt( 2, 'float64', x, 2, 'float64', y, -1 )\n    <Float64Array>[ 2.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.cbrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\n    <Float64Array>[ 3.0, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n\nstrided.cbrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the cube root of each element in a strided array `x` and assigns\n    the results to elements in a strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.cbrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 0.0, 1.0, 2.0, 3.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.cbrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dcbrt, base.strided.scbrt, strided.sqrt\n","strided.cbrt.ndarray":"\nstrided.cbrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the cube root of each element in a strided array `x` and assigns\n    the results to elements in a strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.cbrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 0.0, 1.0, 2.0, 3.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.cbrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dcbrt, base.strided.scbrt, strided.sqrt","strided.cbrtBy":"\nstrided.cbrtBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the cube root of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 9.0, -27.0, 81.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.cbrtBy( x.length, x, 1, y, 1, clbk )\n    [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.cbrtBy( 2, x, 2, y, -1, clbk )\n    [ -3.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.cbrtBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~4.327, ~2.08 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~4.327, ~2.08 ]\n\n\nstrided.cbrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the cube root of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 9.0, -27.0, 81.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.cbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 9.0, -27.0, 81.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.cbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~4.327, ~2.08 ]\n\n    See Also\n    --------\n    strided.cbrt\n","strided.cbrtBy.ndarray":"\nstrided.cbrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the cube root of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 9.0, -27.0, 81.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.cbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 9.0, -27.0, 81.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.cbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~4.327, ~2.08 ]\n\n    See Also\n    --------\n    strided.cbrt","strided.ceil":"\nstrided.ceil( N, dtypeX, x, strideX, dtypeY, y, strideY )\n    Rounds each element in a strided array `x` toward positive infinity and\n    assigns the results to elements in a strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ceil( x.length, 'float64', x, 1, 'float64', y, 1 )\n    <Float64Array>[ 2.0, 3.0, -3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ceil( 2, 'float64', x, 2, 'float64', y, -1 )\n    <Float64Array>[ -3.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.ceil( 2, 'float64', x1, -2, 'float64', y1, 1 )\n    <Float64Array>[ 4.0, 3.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n\nstrided.ceil.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Rounds each element in a strided array `x` toward positive infinity and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ceil.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 2.0, 3.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ceil.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n    See Also\n    --------\n    base.strided.dceil, strided.floor, strided.trunc, base.strided.sceil\n","strided.ceil.ndarray":"\nstrided.ceil.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Rounds each element in a strided array `x` toward positive infinity and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ceil.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 2.0, 3.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ceil.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n    See Also\n    --------\n    base.strided.dceil, strided.floor, strided.trunc, base.strided.sceil","strided.cosBy":"\nstrided.cosBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the cosine for each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.cosBy( x.length, x, 1, y, 1, clbk )\n    [ 1.0, ~-1.0, ~-1.0, ~-0.839 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.cosBy( 2, x, 2, y, -1, clbk )\n    [ ~-1.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 3.14, -3.14, 10.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.cosBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~-0.839, ~-1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~-0.839, ~-1.0 ]\n\n\nstrided.cosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the cosine for each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.cosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 1.0, ~-1.0, ~-1.0, ~-0.839 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 3.14, -3.14, 10.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.cosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.839, ~-1.0 ]\n\n","strided.cosBy.ndarray":"\nstrided.cosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the cosine for each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.cosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 1.0, ~-1.0, ~-1.0, ~-0.839 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 3.14, -3.14, 10.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.cosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.839, ~-1.0 ]","strided.deg2rad":"\nstrided.deg2rad( N, dtypeX, x, strideX, dtypeY, y, strideY )\n    Converts each element in a strided array `x` from degrees to radians and\n    assigns the results to elements in a strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.deg2rad( x.length, 'float64', x, 1, 'float64', y, 1 )\n    <Float64Array>[ 0.0, ~0.524, ~0.785, ~1.571 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.deg2rad( 2, 'float64', x, 2, 'float64', y, -1 )\n    <Float64Array>[ ~0.785, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.deg2rad( 2, 'float64', x1, -2, 'float64', y1, 1 )\n    <Float64Array>[ ~1.571, ~0.524 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~1.571, ~0.524 ]\n\n\nstrided.deg2rad.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Converts each element in a strided array `x` from degrees to radians and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.deg2rad.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 0.0, ~0.524, ~0.785, ~1.571 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.deg2rad.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~1.571, ~0.524 ]\n\n    See Also\n    --------\n    base.strided.ddeg2rad, base.strided.sdeg2rad\n","strided.deg2rad.ndarray":"\nstrided.deg2rad.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Converts each element in a strided array `x` from degrees to radians and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.deg2rad.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 0.0, ~0.524, ~0.785, ~1.571 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.deg2rad.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~1.571, ~0.524 ]\n\n    See Also\n    --------\n    base.strided.ddeg2rad, base.strided.sdeg2rad","strided.dataTypes":"\nstrided.dataTypes()\n    Returns a list of strided array data types.\n\n    The output array contains the following data types:\n\n    - binary: binary.\n    - bool: boolean values.\n    - complex64: single-precision complex floating-point numbers.\n    - complex128: double-precision complex floating-point numbers.\n    - float32: single-precision floating-point numbers.\n    - float64: double-precision floating-point numbers.\n    - generic: values of any type.\n    - int16: signed 16-bit integers.\n    - int32: signed 32-bit integers.\n    - int8: signed 8-bit integers.\n    - uint16: unsigned 16-bit integers.\n    - uint32: unsigned 32-bit integers.\n    - uint8: unsigned 8-bit integers.\n    - uint8c: unsigned clamped 8-bit integers.\n\n    Returns\n    -------\n    out: Array<string>\n        List of strided array data types.\n\n    Examples\n    --------\n    > var out = strided.dataTypes()\n    <Array>\n\n","strided.dcbrtBy":"\nstrided.dcbrtBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the cube root of each element retrieved from an input double-\n    precision floating-point strided array via a callback function and assigns\n    each result to an element in an output double-precision floating-point\n    strided array.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - indices: strided array indices (offset + idx*stride).\n    - arrays: input and output arrays.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Float64Array\n        Destination array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > function clbk( v ) { return v; };\n    > strided.dcbrtBy( x.length, x, 1, y, 1, clbk )\n    <Float64Array>[ 1.0, ~2.08, -3.0, ~4.327 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.dcbrtBy( 2, x, 2, y, -1, clbk )\n    <Float64Array>[ -3.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.dcbrtBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~4.327, ~2.08 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~4.327, ~2.08 ]\n\n\nstrided.dcbrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the cube root of each element retrieved from an input double-\n    precision floating-point strided array via a callback function and assigns\n    each result to an element in an output double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - indices: strided array indices (offset + idx*stride).\n    - arrays: input and output arrays.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Float64Array\n        Destination array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > function clbk( v ) { return v; };\n    > strided.dcbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    <Float64Array>[ 1.0, ~2.08, -3.0, ~4.327 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.dcbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    <Float64Array>[ 0.0, 0.0, ~4.327, ~2.08 ]\n\n    See Also\n    --------\n    strided.cbrt\n","strided.dcbrtBy.ndarray":"\nstrided.dcbrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the cube root of each element retrieved from an input double-\n    precision floating-point strided array via a callback function and assigns\n    each result to an element in an output double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - indices: strided array indices (offset + idx*stride).\n    - arrays: input and output arrays.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Float64Array\n        Destination array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > function clbk( v ) { return v; };\n    > strided.dcbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    <Float64Array>[ 1.0, ~2.08, -3.0, ~4.327 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.dcbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    <Float64Array>[ 0.0, 0.0, ~4.327, ~2.08 ]\n\n    See Also\n    --------\n    strided.cbrt","strided.dispatch":"\nstrided.dispatch( fcns, types, data, nargs, nin, nout )\n    Returns a strided array function interface which performs multiple dispatch.\n\n    Without offsets, a strided array function interface has the following\n    signature:\n\n      f( N, dtypeX, x, strideX, dtypeY, y, strideY, ... )\n\n    where\n\n    - N: number of indexed elements.\n    - dtypeX: data type for `x`.\n    - x: strided array.\n    - strideX: index increment for `x`.\n    - dtypeY: data type for `y`.\n    - y: strided array.\n    - strideY: index increment for `y`.\n    - ...: additional strided arrays, data types, and associated strides.\n\n    The number of parameters is derived from `nargs`, the number of input\n    strided arrays is derived from `nin`, and the number of output strided\n    arrays is derived from `nout`.\n\n    Without offsets, the number of parameters must obey the following relation:\n\n      nargs = 3*(nout+nin) + 1\n\n    With offsets, the number of parameters must obey the following relation:\n\n      nargs = 4*(nout+nin) + 1\n\n    With offsets, a strided array function interface has the following\n    signature:\n\n      f( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY, ... )\n\n    where\n\n    - N: number of indexed elements.\n    - dtypeX: data type for `x`.\n    - x: strided array.\n    - strideX: index increment for `x`.\n    - offsetX: starting index for `x`.\n    - dtypeY: data type for `y`.\n    - y: strided array.\n    - strideY: index increment for `y`.\n    - offsetY: starting index for `y`.\n    - ...: additional strided arrays and associated data types, strides, and\n      offsets.\n\n    The choice of which strided array function interface to return depends on\n    the use case. The former is suitable for typed array views; while the latter\n    affords alternative indexing semantics more suitable for n-dimensional\n    arrays (ndarrays).\n\n    Parameters\n    ----------\n    fcns: Function|ArrayLikeObject<Function>\n        List of strided array functions. Without offsets, a strided array\n        function should have the following signature:\n\n          f( arrays, shape, strides, data )\n\n        where\n\n        - arrays: array containing strided input and output arrays.\n        - shape: array containing a single element, the number of indexed\n          elements.\n        - strides: array containing the stride lengths for the strided input and\n          output arrays.\n        - data: strided array function data (e.g., a callback).\n\n        With offsets, a strided array function should have the following\n        signature:\n\n          f( arrays, shape, strides, offsets, data )\n\n        where\n\n        - offsets: array containing the starting indices (i.e., index offsets)\n          for the strided input and output arrays.\n\n        For convenience, a single strided array function may be provided which\n        will be invoked whenever the strided array argument data types match a\n        sequence of types in `types`. Providing a single strided array function\n        is particularly convenient for the case where, regardless of array data\n        types, traversing arrays remains the same, but the strided array\n        function `data` differs (e.g., callbacks which differ based on the array\n        data types).\n\n    types: ArrayLikeObject\n        One-dimensional list of strided array argument data types.\n\n    data: ArrayLikeObject|null\n        Strided array function data (e.g., callbacks). If `null`, a returned\n        strided array function interface does **not** provide a `data` argument\n        to an invoked strided array function.\n\n    nargs: integer\n        Total number of strided array function interface arguments (including\n        data types, strides, and offsets).\n\n    nin: integer\n        Number of input strided arrays.\n\n    nout: integer\n        Number of output strided arrays.\n\n    Returns\n    -------\n    fcn: Function\n        Strided array function interface.\n\n    Examples\n    --------\n    // Define strided array argument data types:\n    > var t = [ 'float64', 'float64', 'float32', 'float32' ];\n\n    // Define a list of strided array function data (callbacks):\n    > var d = [ base.abs, base.absf ];\n\n    // Create a strided array function interface for applying unary callbacks:\n    > var f = strided.dispatch( base.strided.unary, t, d, 7, 1, 1 );\n\n    // Create an input strided array:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n    // Create an output strided array:\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n    // Compute the element-wise absolute value:\n    > f( x.length, 'float64', x, 1, 'float64', y, 1 );\n    > y\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Create a strided array function interface supporting offsets:\n    > f = strided.dispatch( base.strided.unary.ndarray, t, d, 9, 1, 1 );\n\n    // Create an input strided array:\n    > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n    // Create an output strided array:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n    // Compute the element-wise absolute value starting from the third element:\n    > f( 2, 'float64', x, 1, 2, 'float64', y, 1, 2 );\n    > y\n    <Float64Array>[ 0.0, 0.0, 3.0, 4.0 ]\n\n","strided.dispatchBy":"\nstrided.dispatchBy( fcns, types, data, nargs, nin, nout )\n    Returns a strided array function interface which accepts a callback function\n    and performs multiple dispatch.\n\n    Without offsets, a strided array function interface has the following\n    signature:\n\n      f( N, dx, x, sx, dy, y, sy, ..., clbk[, thisArg] )\n\n    where\n\n    - N: number of indexed elements.\n    - dx: data type for `x`.\n    - x: strided array.\n    - sx: index increment for `x`.\n    - dy: data type for `y`.\n    - y: strided array.\n    - sy: index increment for `y`.\n    - ...: additional strided arrays, data types, and associated strides.\n    - clbk: callback function.\n    - thisArg: callback function execution context.\n\n    The number of parameters is derived from `nargs`, the number of input\n    strided arrays is derived from `nin`, and the number of output strided\n    arrays is derived from `nout`.\n\n    Without offsets, the number of parameters must obey the following relation:\n\n      nargs = 3*(nout+nin) + 2\n\n    With offsets, the number of parameters must obey the following relation:\n\n      nargs = 4*(nout+nin) + 2\n\n    With offsets, a strided array function interface has the following\n    signature:\n\n      f( N, dx, x, sx, ox, dy, y, sy, oy, ..., clbk[, thisArg] )\n\n    where\n\n    - N: number of indexed elements.\n    - dx: data type for `x`.\n    - x: strided array.\n    - sx: index increment for `x`.\n    - ox: starting index for `x`.\n    - dy: data type for `y`.\n    - y: strided array.\n    - sy: index increment for `y`.\n    - oy: starting index for `y`.\n    - ...: additional strided arrays and associated data types, strides, and\n      offsets.\n    - clbk: callback function.\n    - thisArg: callback function execution context.\n\n    The choice of which strided array function interface to return depends on\n    the use case. The former is suitable for typed array views; while the latter\n    affords alternative indexing semantics more suitable for n-dimensional\n    arrays (ndarrays).\n\n    Parameters\n    ----------\n    fcns: Function|ArrayLikeObject<Function>\n        List of strided array functions. Without offsets, a strided array\n        function should have the following signature:\n\n          f( arrays, shape, strides, data, clbk, thisArg )\n\n        where\n\n        - arrays: array containing strided input and output arrays.\n        - shape: array containing a single element, the number of indexed\n          elements.\n        - strides: array containing the stride lengths for the strided input and\n          output arrays.\n        - data: strided array function data (e.g., a callback).\n        - clbk: callback function.\n        - thisArg: callback function execution context.\n\n        With offsets, a strided array function should have the following\n        signature:\n\n          f( arrays, shape, strides, offsets, data, clbk, thisArg )\n\n        where\n\n        - offsets: array containing the starting indices (i.e., index offsets)\n          for the strided input and output arrays.\n\n        For convenience, a single strided array function may be provided which\n        will be invoked whenever the strided array argument data types match a\n        sequence of types in `types`. Providing a single strided array function\n        is particularly convenient for the case where, regardless of array data\n        types, traversing arrays remains the same, but the strided array\n        function `data` differs (e.g., callbacks which differ based on the array\n        data types).\n\n    types: ArrayLikeObject\n        One-dimensional list of strided array argument data types.\n\n    data: ArrayLikeObject|null\n        Strided array function data (e.g., callbacks). If `null`, a returned\n        strided array function interface does **not** provide a `data` argument\n        to an invoked strided array function.\n\n    nargs: integer\n        Total number of strided array function interface arguments (including\n        data types, strides, offsets, and the callback function).\n\n    nin: integer\n        Number of input strided arrays.\n\n    nout: integer\n        Number of output strided arrays.\n\n    Returns\n    -------\n    fcn: Function\n        Strided array function interface.\n\n    Examples\n    --------\n    // Define strided array argument data types:\n    > var t = [ 'float64', 'float64', 'float32', 'float32' ];\n\n    // Define a list of strided array function data (callbacks):\n    > var d = [ base.abs, base.absf ];\n\n    // Create a strided array function interface for applying unary callbacks:\n    > var f = strided.dispatchBy( base.strided.unaryBy, t, d, 8, 1, 1 );\n\n    // Create an input strided array:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n    // Create an output strided array:\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n    // Compute the element-wise absolute value:\n    > f( x.length, 'float64', x, 1, 'float64', y, 1, base.identity );\n    > y\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Create a strided array function interface supporting offsets:\n    > f = strided.dispatchBy( base.strided.unary.ndarray, t, d, 10, 1, 1 );\n\n    // Create an input strided array:\n    > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n    // Create an output strided array:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n    // Compute the element-wise absolute value starting from the third element:\n    > f( 2, 'float64', x, 1, 2, 'float64', y, 1, 2, base.identity );\n    > y\n    <Float64Array>[ 0.0, 0.0, 3.0, 4.0 ]\n\n    See Also\n    --------\n    strided.dispatch\n","strided.floor":"\nstrided.floor( N, dtypeX, x, strideX, dtypeY, y, strideY )\n    Rounds each element in a strided array `x` toward negative infinity and\n    assigns the results to elements in a strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.floor( x.length, 'float64', x, 1, 'float64', y, 1 )\n    <Float64Array>[ -2.0, 2.0, -4.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.floor( 2, 'float64', x, 2, 'float64', y, -1 )\n    <Float64Array>[ -4.0, -2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.floor( 2, 'float64', x1, -2, 'float64', y1, 1 )\n    <Float64Array>[ 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nstrided.floor.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Rounds each element in a strided array `x` toward negative infinity and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.floor.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ -2.0, 2.0, -4.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.floor.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    strided.ceil, base.strided.dfloor, strided.trunc, base.strided.sfloor\n","strided.floor.ndarray":"\nstrided.floor.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Rounds each element in a strided array `x` toward negative infinity and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.floor.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ -2.0, 2.0, -4.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.floor.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    strided.ceil, base.strided.dfloor, strided.trunc, base.strided.sfloor","strided.inv":"\nstrided.inv( N, dtypeX, x, strideX, dtypeY, y, strideY )\n    Computes the multiplicative inverse for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.inv( x.length, 'float64', x, 1, 'float64', y, 1 )\n    <Float64Array>[ -0.05, -1.0, 0.5, 0.25 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.inv( 2, 'float64', x, 2, 'float64', y, -1 )\n    <Float64Array>[ 0.5, -0.05, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.inv( 2, 'float64', x1, -2, 'float64', y1, 1 )\n    <Float64Array>[ 0.25, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n\nstrided.inv.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the multiplicative inverse for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.inv.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ -0.05, -1.0, 0.5, 0.25 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.inv.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dinv, base.strided.sinv\n","strided.inv.ndarray":"\nstrided.inv.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the multiplicative inverse for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.inv.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ -0.05, -1.0, 0.5, 0.25 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.inv.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dinv, base.strided.sinv","strided.mul":"\nstrided.mul( N, dx, x, sx, dy, y, sy, dz, z, sz )\n    Multiplies each element in a strided array `x` to a corresponding element in\n    a strided array `y` and assigns the results to elements in a strided array\n    `z`.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dx: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    dy: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    dz: any\n        Data type for `z`.\n\n    z: ArrayLikeObject\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    Returns\n    -------\n    z: ArrayLikeObject\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var dt = 'float64';\n    > strided.mul( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\n    <Float64Array>[ -2.0, 2.0, 9.0, -20.0 ]\n\n    // Using `N` and stride parameters:\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.mul( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\n    <Float64Array>[ -6.0, 3.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > strided.mul( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\n    <Float64Array>[ -15.0, 4.0 ]\n    > z0\n    <Float64Array>[ 0.0, 0.0, -15.0, 4.0 ]\n\n\nstrided.mul.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n    Multiplies each element in a strided array `x` to a corresponding element in\n    a strided array `y` and assigns the results to elements in a strided array\n    `z` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dx: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    dy: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    dz: any\n        Data type for `z`.\n\n    z: ArrayLikeObject\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    Returns\n    -------\n    z: ArrayLikeObject\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var dt = 'float64';\n    > strided.mul.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n    <Float64Array>[ -2.0, 2.0, 9.0, -20.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.mul.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n    <Float64Array>[ 0.0, 4.0, -15.0, 0.0 ]\n\n    See Also\n    --------\n    strided.add, strided.sub\n","strided.mul.ndarray":"\nstrided.mul.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n    Multiplies each element in a strided array `x` to a corresponding element in\n    a strided array `y` and assigns the results to elements in a strided array\n    `z` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dx: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    dy: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    dz: any\n        Data type for `z`.\n\n    z: ArrayLikeObject\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    Returns\n    -------\n    z: ArrayLikeObject\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var dt = 'float64';\n    > strided.mul.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n    <Float64Array>[ -2.0, 2.0, 9.0, -20.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.mul.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n    <Float64Array>[ 0.0, 4.0, -15.0, 0.0 ]\n\n    See Also\n    --------\n    strided.add, strided.sub","strided.mulBy":"\nstrided.mulBy( N, x, sx, y, sy, z, sz, clbk[, thisArg] )\n    Performs element-wise multiplication of two strided arrays via a callback\n    function and assigns each result to an element in an output strided array.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided four arguments:\n\n    - values: input array elements.\n    - idx: iteration index.\n    - indices: strided array indices (offset + idx*stride).\n    - arrays: input and output arrays.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n    > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( values ) { return values; };\n    > strided.mulBy( x.length, x, 1, y, 1, z, 1, clbk )\n    [ 11.0, 24.0, 39.0, 56.0 ]\n\n    // Using `N` and stride parameters:\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.mulBy( 2, x, 2, y, -1, z, 1, clbk )\n    [ 12.0, 33.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\n    > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > strided.mulBy( 2, x1, -2, y1, 1, z1, 1, clbk )\n    <Float64Array>[ 52.0, 28.0 ]\n    > z0\n    <Float64Array>[ 0.0, 0.0, 52.0, 28.0 ]\n\n\nstrided.mulBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n    Performs element-wise multiplication of two strided arrays via a callback\n    function and assigns each result to an element in an output strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n    > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( values ) { return values; };\n    > strided.mulBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n    [ 11.0, 24.0, 39.0, 56.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0 ];\n    > y = [ 11.0, 12.0, 13.0, 14.0 ];\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > var oy = y.length - 1;\n    > var oz = z.length - 1;\n    > strided.mulBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n    [ 0.0, 0.0, 52.0, 28.0 ]\n\n    See Also\n    --------\n    strided.mul, strided.addBy, strided.subBy\n","strided.mulBy.ndarray":"\nstrided.mulBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n    Performs element-wise multiplication of two strided arrays via a callback\n    function and assigns each result to an element in an output strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n    > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( values ) { return values; };\n    > strided.mulBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n    [ 11.0, 24.0, 39.0, 56.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0 ];\n    > y = [ 11.0, 12.0, 13.0, 14.0 ];\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > var oy = y.length - 1;\n    > var oz = z.length - 1;\n    > strided.mulBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n    [ 0.0, 0.0, 52.0, 28.0 ]\n\n    See Also\n    --------\n    strided.mul, strided.addBy, strided.subBy","strided.ramp":"\nstrided.ramp( N, dtypeX, x, strideX, dtypeY, y, strideY )\n    Evaluates the ramp function for each element in a strided array `x` and\n    assigns the results to elements in a strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ramp( x.length, 'float64', x, 1, 'float64', y, 1 )\n    <Float64Array>[ 1.1, 2.5, 0.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ramp( 2, 'float64', x, 2, 'float64', y, -1 )\n    <Float64Array>[ 0.0, 1.1, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.ramp( 2, 'float64', x1, -2, 'float64', y1, 1 )\n    <Float64Array>[ 4.0, 2.5 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.5 ]\n\n\nstrided.ramp.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Evaluates the ramp function for each element in a strided array `x` and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ramp.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 1.1, 2.5, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ramp.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.5 ]\n\n    See Also\n    --------\n    base.strided.dramp, base.strided.sramp\n","strided.ramp.ndarray":"\nstrided.ramp.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Evaluates the ramp function for each element in a strided array `x` and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ramp.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 1.1, 2.5, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ramp.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.5 ]\n\n    See Also\n    --------\n    base.strided.dramp, base.strided.sramp","strided.rsqrt":"\nstrided.rsqrt( N, dtypeX, x, strideX, dtypeY, y, strideY )\n    Computes the reciprocal square root for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.rsqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\n    <Float64Array>[ Infinity, 0.5, ~0.333, ~0.289 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.rsqrt( 2, 'float64', x, 2, 'float64', y, -1 )\n    <Float64Array>[ ~0.333, Infinity, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.rsqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\n    <Float64Array>[ ~0.289, 0.5 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nstrided.rsqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the reciprocal square root for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.rsqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ Infinity, 0.5, ~0.333, ~0.289 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.rsqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n    See Also\n    --------\n    base.strided.drsqrt, strided.sqrt, base.strided.srsqrt\n","strided.rsqrt.ndarray":"\nstrided.rsqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the reciprocal square root for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.rsqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ Infinity, 0.5, ~0.333, ~0.289 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.rsqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n    See Also\n    --------\n    base.strided.drsqrt, strided.sqrt, base.strided.srsqrt","strided.sinBy":"\nstrided.sinBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the sine of each element retrieved from an input strided array `x`\n    via a callback function and assigns each result to an element in an output\n    strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.sinBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, ~0.002, ~-0.002, ~-0.544 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.sinBy( 2, x, 2, y, -1, clbk )\n    [ ~-0.002, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 3.14, -3.14, 10.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.sinBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~-0.544, ~0.002 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~-0.544, ~0.002 ]\n\n\nstrided.sinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the sine of each element retrieved from an input strided array `x`\n    via a callback function and assigns each result to an element in an output\n    strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.sinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~0.002, ~-0.002, ~-0.544 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 3.14, -3.14, 10.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.sinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.544, ~0.002 ]\n\n","strided.sinBy.ndarray":"\nstrided.sinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the sine of each element retrieved from an input strided array `x`\n    via a callback function and assigns each result to an element in an output\n    strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.sinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~0.002, ~-0.002, ~-0.544 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 3.14, -3.14, 10.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.sinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.544, ~0.002 ]","strided.sqrt":"\nstrided.sqrt( N, dtypeX, x, strideX, dtypeY, y, strideY )\n    Computes the principal square root for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.sqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\n    <Float64Array>[ 0.0, 2.0, 3.0, ~3.464 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.sqrt( 2, 'float64', x, 2, 'float64', y, -1 )\n    <Float64Array>[ 3.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.sqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\n    <Float64Array>[ ~3.464, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nstrided.sqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the principal square root for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.sqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 0.0, 2.0, 3.0, ~3.464 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.sqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n    See Also\n    --------\n    strided.cbrt, base.strided.dsqrt, strided.rsqrt, base.strided.ssqrt\n","strided.sqrt.ndarray":"\nstrided.sqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the principal square root for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.sqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 0.0, 2.0, 3.0, ~3.464 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.sqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n    See Also\n    --------\n    strided.cbrt, base.strided.dsqrt, strided.rsqrt, base.strided.ssqrt","strided.sqrtBy":"\nstrided.sqrtBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the principal square root for each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 122.0, 50.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.sqrtBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, 1.0, ~11.045, ~7.071 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.sqrtBy( 2, x, 2, y, -1, clbk )\n    [ ~11.045, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 1.0, 122.0, 50.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.sqrtBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~7.071, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~7.071, 1.0 ]\n\n\nstrided.sqrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the principal square root for each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 122.0, 50.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.sqrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, 1.0, ~11.045, ~7.071 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 122.0, 50.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.sqrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~7.071, 1.0 ]\n\n    See Also\n    --------\n    strided.sqrt\n","strided.sqrtBy.ndarray":"\nstrided.sqrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the principal square root for each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 122.0, 50.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.sqrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, 1.0, ~11.045, ~7.071 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 122.0, 50.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.sqrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~7.071, 1.0 ]\n\n    See Also\n    --------\n    strided.sqrt","strided.sub":"\nstrided.sub( N, dx, x, sx, dy, y, sy, dz, z, sz )\n    Subtracts each element in a strided array `x` to a corresponding element in\n    a strided array `y` and assigns the results to elements in a strided array\n    `z`.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dx: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    dy: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    dz: any\n        Data type for `z`.\n\n    z: ArrayLikeObject\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    Returns\n    -------\n    z: ArrayLikeObject\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var dt = 'float64';\n    > strided.sub( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\n    <Float64Array>[ -3.0, -1.0, 0.0, -9.0 ]\n\n    // Using `N` and stride parameters:\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.sub( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\n    <Float64Array>[ -5.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > strided.sub( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\n    <Float64Array>[ -8.0, -3.0 ]\n    > z0\n    <Float64Array>[ 0.0, 0.0, -8.0, -3.0 ]\n\n\nstrided.sub.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n    Subtracts each element in a strided array `x` to a corresponding element in\n    a strided array `y` and assigns the results to elements in a strided array\n    `z` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dx: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    dy: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    dz: any\n        Data type for `z`.\n\n    z: ArrayLikeObject\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    Returns\n    -------\n    z: ArrayLikeObject\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var dt = 'float64';\n    > strided.sub.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n    <Float64Array>[ -3.0, -1.0, 0.0, -9.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.sub.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n    <Float64Array>[ 0.0, -3.0, -8.0, 0.0 ]\n\n    See Also\n    --------\n    strided.add, strided.mul\n","strided.sub.ndarray":"\nstrided.sub.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n    Subtracts each element in a strided array `x` to a corresponding element in\n    a strided array `y` and assigns the results to elements in a strided array\n    `z` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dx: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    dy: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    dz: any\n        Data type for `z`.\n\n    z: ArrayLikeObject\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    Returns\n    -------\n    z: ArrayLikeObject\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var dt = 'float64';\n    > strided.sub.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n    <Float64Array>[ -3.0, -1.0, 0.0, -9.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.sub.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n    <Float64Array>[ 0.0, -3.0, -8.0, 0.0 ]\n\n    See Also\n    --------\n    strided.add, strided.mul","strided.subBy":"\nstrided.subBy( N, x, sx, y, sy, z, sz, clbk[, thisArg] )\n    Performs element-wise subtraction of two strided arrays via a callback\n    function and assigns each result to an element in an output strided array.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided four arguments:\n\n    - values: input array elements.\n    - idx: iteration index.\n    - indices: strided array indices (offset + idx*stride).\n    - arrays: input and output arrays.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 11.0, 12.0, 13.0, 14.0 ];\n    > var y = [ 8.0, 7.0, 6.0, 5.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( values ) { return values; };\n    > strided.subBy( x.length, x, 1, y, 1, z, 1, clbk )\n    [ 3.0, 5.0, 7.0, 9.0 ]\n\n    // Using `N` and stride parameters:\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.subBy( 2, x, 2, y, -1, z, 1, clbk )\n    [ 4.0, 5.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\n    > var y0 = new Float64Array( [ 8.0, 7.0, 6.0, 5.0 ] );\n    > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > strided.subBy( 2, x1, -2, y1, 1, z1, 1, clbk )\n    <Float64Array>[ 8.0, 7.0 ]\n    > z0\n    <Float64Array>[ 0.0, 0.0, 8.0, 7.0 ]\n\n\nstrided.subBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n    Performs element-wise subtraction of two strided arrays via a callback\n    function and assigns each result to an element in an output strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 11.0, 12.0, 13.0, 14.0 ];\n    > var y = [ 8.0, 7.0, 6.0, 5.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( values ) { return values; };\n    > strided.subBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n    [ 3.0, 5.0, 7.0, 9.0 ]\n\n    // Advanced indexing:\n    > x = [ 11.0, 12.0, 13.0, 14.0 ];\n    > y = [ 8.0, 7.0, 6.0, 5.0 ];\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > var oy = y.length - 1;\n    > var oz = z.length - 1;\n    > strided.subBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n    [ 0.0, 0.0, 8.0, 7.0 ]\n\n    See Also\n    --------\n    strided.sub, strided.addBy, strided.mulBy\n","strided.subBy.ndarray":"\nstrided.subBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n    Performs element-wise subtraction of two strided arrays via a callback\n    function and assigns each result to an element in an output strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 11.0, 12.0, 13.0, 14.0 ];\n    > var y = [ 8.0, 7.0, 6.0, 5.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( values ) { return values; };\n    > strided.subBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n    [ 3.0, 5.0, 7.0, 9.0 ]\n\n    // Advanced indexing:\n    > x = [ 11.0, 12.0, 13.0, 14.0 ];\n    > y = [ 8.0, 7.0, 6.0, 5.0 ];\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > var oy = y.length - 1;\n    > var oz = z.length - 1;\n    > strided.subBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n    [ 0.0, 0.0, 8.0, 7.0 ]\n\n    See Also\n    --------\n    strided.sub, strided.addBy, strided.mulBy","strided.trunc":"\nstrided.trunc( N, dtypeX, x, strideX, dtypeY, y, strideY )\n    Rounds each element in a strided array `x` toward zero and assigns the\n    results to elements in a strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.trunc( x.length, 'float64', x, 1, 'float64', y, 1 )\n    <Float64Array>[ 1.0, 2.0, -3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.trunc( 2, 'float64', x, 2, 'float64', y, -1 )\n    <Float64Array>[ -3.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.trunc( 2, 'float64', x1, -2, 'float64', y1, 1 )\n    <Float64Array>[ 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nstrided.trunc.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Rounds each element in a strided array `x` toward zero and assigns the\n    results to elements in a strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.trunc.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.trunc.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    strided.ceil, base.strided.dtrunc, strided.floor, base.strided.strunc\n","strided.trunc.ndarray":"\nstrided.trunc.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Rounds each element in a strided array `x` toward zero and assigns the\n    results to elements in a strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.trunc.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.trunc.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    strided.ceil, base.strided.dtrunc, strided.floor, base.strided.strunc","stridedarray2iterator":"\nstridedarray2iterator( N, src, stride, offset[, mapFcn[, thisArg]] )\n    Returns an iterator which iterates over elements of an array-like object\n    according to specified stride parameters.\n\n    When invoked, an input function is provided four arguments:\n\n    - value: iterated value.\n    - index: iterated value index.\n    - n: iteration count (zero-based).\n    - src: source array-like object.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an array's `@@iterator` method, regardless of whether this method is\n    defined. To convert an array to an implementation defined iterator, invoke\n    this method directly.\n\n    Parameters\n    ----------\n    N: integer\n        Number of values to iterate.\n\n    src: ArrayLikeObject\n        Array-like object from which to create the iterator.\n\n    stride: integer\n        Stride length.\n\n    offset: integer\n        Starting index.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = stridedarray2iterator( 2, [ 1, 2, 3, 4 ], -2, 3 );\n    > var v = it.next().value\n    4\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    iterator2array, array2iterator\n","stridedArrayStream":"\nstridedArrayStream( N, buffer, stride, offset[, options] )\n    Creates a readable stream from a strided array-like object.\n\n    In object mode, `null` is a reserved value. If an array contains `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or filter `null` values\n    prior to invocation.\n\n    In binary mode, if an array contains `undefined` values, the stream will\n    emit an error. Consider providing a custom serialization function or\n    filtering `undefined` values prior to invocation.\n\n    If a serialization function fails to return a string or Buffer, the stream\n    emits an error.\n\n    Parameters\n    ----------\n    N: integer\n        Number of values to stream.\n\n    buffer: ArrayLikeObject\n        Array-like object from which to create the stream.\n\n    stride: integer\n        Stride length.\n\n    offset: integer\n        Starting index.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing the stream.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize streamed\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var s = stridedArrayStream( 3, [ 1, 2, 3 ], 1, 0 );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nstridedArrayStream.factory( [options] )\n    Returns a function for creating readable streams from array-like objects.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing streaming.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize streamed\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = stridedArrayStream.factory( opts );\n\n\nstridedArrayStream.objectMode( N, buffer, stride, offset[, options] )\n    Returns an \"objectMode\" readable stream from a strided array-like object.\n\n    In object mode, `null` is a reserved value. If an array contains `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or filter `null` values\n    prior to invocation.\n\n    Parameters\n    ----------\n    N: integer\n        Number of values to stream.\n\n    buffer: ArrayLikeObject\n        Array-like object from which to create the stream.\n\n    stride: integer\n        Stride length.\n\n    offset: integer\n        Starting index.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before pausing streaming.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var s = stridedArrayStream.objectMode( 3, [ 1, 2, 3 ], 1, 0 );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    arrayStream\n","stridedArrayStream.factory":"\nstridedArrayStream.factory( [options] )\n    Returns a function for creating readable streams from array-like objects.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing streaming.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize streamed\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = stridedArrayStream.factory( opts );","stridedArrayStream.objectMode":"\nstridedArrayStream.objectMode( N, buffer, stride, offset[, options] )\n    Returns an \"objectMode\" readable stream from a strided array-like object.\n\n    In object mode, `null` is a reserved value. If an array contains `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or filter `null` values\n    prior to invocation.\n\n    Parameters\n    ----------\n    N: integer\n        Number of values to stream.\n\n    buffer: ArrayLikeObject\n        Array-like object from which to create the stream.\n\n    stride: integer\n        Stride length.\n\n    offset: integer\n        Starting index.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before pausing streaming.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var s = stridedArrayStream.objectMode( 3, [ 1, 2, 3 ], 1, 0 );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    arrayStream","string2buffer":"\nstring2buffer( str[, encoding] )\n    Allocates a buffer containing a provided string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    encoding: string (optional)\n        Character encoding. Default: 'utf8'.\n\n    Returns\n    -------\n    out: Buffer\n        Buffer instance.\n\n    Examples\n    --------\n    > var b = string2buffer( 'beep boop' )\n    <Buffer>\n    > b = string2buffer( '7468697320697320612074c3a97374', 'hex' );\n    > b.toString()\n    'this is a tést'\n\n    See Also\n    --------\n    Buffer, array2buffer, arraybuffer2buffer, copyBuffer\n","sub2ind":"\nsub2ind( shape, ...subscript[, options] )\n    Converts subscripts to a linear index.\n\n    Parameters\n    ----------\n    shape: ArrayLike\n        Array shape.\n\n    subscript: ...integer\n        Subscripts.\n\n    options: Object (optional)\n        Options.\n\n    options.order: string (optional)\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran style). Default: 'row-major'.\n\n    options.mode: string|Array<string> (optional)\n        Specifies how to handle subscripts which exceed array dimensions. If\n        equal to 'throw', the function throws an error when a subscript exceeds\n        array dimensions. If equal to 'normalize', the function normalizes\n        negative subscripts and throws an error when a subscript exceeds array\n        dimensions. If equal to 'wrap', the function wraps around subscripts\n        exceeding array dimensions using modulo arithmetic. If equal to\n        'clamp', the function sets subscripts exceeding array dimensions to\n        either `0` (minimum index) or the maximum index along a particular\n        dimension. If provided a mode array, each array element specifies the\n        mode for a corresponding array dimension. If provided fewer modes than\n        dimensions, the function recycles modes using modulo arithmetic.\n        Default: [ 'throw' ].\n\n    Returns\n    -------\n    idx: integer\n        Linear index.\n\n    Examples\n    --------\n    > var d = [ 3, 3, 3 ];\n    > var idx = sub2ind( d, 1, 2, 2 )\n    17\n\n    See Also\n    --------\n    array, ndarray, ind2sub\n","substringAfter":"\nsubstringAfter( str, search[, fromIndex] )\n    Returns the part of a string after a specified substring.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search string.\n\n    fromIndex: integer (optional)\n        Index from which to start the search. Default: `0`.\n\n    Returns\n    -------\n    out: string\n        Substring.\n\n    Examples\n    --------\n    > var out = substringAfter( 'Hello World!', 'World' )\n    '!'\n    > out = substringAfter( 'Hello World!', 'Hello ' )\n    'World!'\n    > out = substringAfter( 'Hello World!', 'l', 5 )\n    'd!'\n\n    See Also\n    --------\n    substringBefore, substringBeforeLast, substringAfterLast","substringAfterLast":"\nsubstringAfterLast( str, search[, fromIndex] )\n    Returns the part of a string after the last occurrence of a specified\n    substring.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search value.\n\n    fromIndex: integer (optional)\n        Index of last character to be considered beginning of a match.\n        Default: `str.length`.\n\n    Returns\n    -------\n    out: string\n        Substring.\n\n    Examples\n    --------\n    > var out = substringAfterLast( 'beep boop beep baz', 'beep' )\n    ' baz'\n    > out = substringAfterLast( 'Hello World!', 'Hello ' )\n    'World!'\n    > out = substringAfterLast( 'Hello World!', 'o', 5 )\n    ' World!'\n\n    See Also\n    --------\n    substringBefore, substringBeforeLast, substringAfter","substringBefore":"\nsubstringBefore( str, search )\n    Returns the part of a string before a specified substring.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search string.\n\n    Returns\n    -------\n    out: string\n        Substring.\n\n    Examples\n    --------\n    > var str = 'beep boop';\n    > var out = substringBefore( str, ' ' )\n    'beep'\n    > out = substringBefore( str, 'o' )\n    'beep b'\n\n    See Also\n    --------\n    substringBeforeLast, substringAfter, substringAfterLast","substringBeforeLast":"\nsubstringBeforeLast( str, search )\n    Returns the part of a string before the last occurrence of a specified\n    substring.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search value.\n\n    Returns\n    -------\n    out: string\n        Substring.\n\n    Examples\n    --------\n    > var str = 'Beep Boop Beep';\n    > var out = substringBeforeLast( str, 'Beep' )\n    'Beep Boop '\n    > out = substringBeforeLast( str, 'Boop' )\n    'Beep '\n\n    See Also\n    --------\n    substringBefore, substringAfter, substringAfterLast","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n    Returns a dataset consisting of labeled wireless sensor network data set\n    collected from a multi-hop wireless sensor network deployment using TelosB\n    motes.\n\n    Humidity and temperature measurements were collected at 5 second intervals\n    over a six hour period on July 10, 2010.\n\n    Temperature is in degrees Celsius.\n\n    Humidity is temperature corrected relative humidity, ranging from 0-100%.\n\n    The label '0' denotes normal data, and the label '1' denotes an introduced\n    event.\n\n    If a mote was an indoor sensor, the corresponding indicator is '1'. If a\n    mote was an outdoor sensor, the indoor indicator is '0'.\n\n    Returns\n    -------\n    out: Array<Object>\n        Sensor data.\n\n    Examples\n    --------\n    > var data = SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n    [{...}, {...}, ...]\n\n    References\n    ----------\n    - Suthaharan, Shan, Mohammed Alzahrani, Sutharshan Rajasegarar, Christopher\n    Leckie, and Marimuthu Palaniswami. 2010. \"Labelled data collection for\n    anomaly detection in wireless sensor networks.\" In _Proceedings of the Sixth\n    International Conference on Intelligent Sensors, Sensor Networks and\n    Information Processing (ISSNIP 2010)_. Brisbane, Australia: IEEE.\n\n    * If you use the data for publication or third party consumption, please\n    cite the listed reference.\n\n    See Also\n    --------\n    SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK\n","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n    Returns a dataset consisting of labeled wireless sensor network data set\n    collected from a simple single-hop wireless sensor network deployment using\n    TelosB motes.\n\n    Humidity and temperature measurements were collected at 5 second intervals\n    over a six hour period on May 9, 2010.\n\n    Temperature is in degrees Celsius.\n\n    Humidity is temperature corrected relative humidity, ranging from 0-100%.\n\n    The label '0' denotes normal data, and the label '1' denotes an introduced\n    event.\n\n    If a mote was an indoor sensor, the corresponding indicator is '1'. If a\n    mote was an outdoor sensor, the indoor indicator is '0'.\n\n    Returns\n    -------\n    out: Array<Object>\n        Sensor data.\n\n    Examples\n    --------\n    > var data = SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n    [{...}, {...}, ...]\n\n    References\n    ----------\n    - Suthaharan, Shan, Mohammed Alzahrani, Sutharshan Rajasegarar, Christopher\n    Leckie, and Marimuthu Palaniswami. 2010. \"Labelled data collection for\n    anomaly detection in wireless sensor networks.\" In _Proceedings of the Sixth\n    International Conference on Intelligent Sensors, Sensor Networks and\n    Information Processing (ISSNIP 2010)_. Brisbane, Australia: IEEE.\n\n    * If you use the data for publication or third party consumption, please\n    cite the listed reference.\n\n    See Also\n    --------\n    SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK\n","Symbol":"\nSymbol( [description] )\n    Returns a symbol.\n\n    Unlike conventional constructors, this function does **not** support the\n    `new` keyword.\n\n    This function is only supported in environments which support symbols.\n\n    Parameters\n    ----------\n    description: string (optional)\n        Symbol description which can be used for debugging but not to access the\n        symbol itself.\n\n    Returns\n    -------\n    out: symbol\n        Symbol.\n\n    Examples\n    --------\n    > var s = ( Symbol ) ? Symbol( 'beep' ) : null\n\n","tabulate":"\ntabulate( collection )\n    Generates a frequency table.\n\n    The table is an array of arrays where each sub-array corresponds to a unique\n    value in the input collection. Each sub-array is structured as follows:\n\n    - 0: unique value.\n    - 1: value count.\n    - 2: frequency percentage.\n\n    If provided an empty collection, the function returns an empty array.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection to tabulate. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    Returns\n    -------\n    out: Array<Array>|Array\n        Frequency table.\n\n    Examples\n    --------\n    > var collection = [ 'beep', 'boop', 'foo', 'beep' ];\n    > var out = tabulate( collection )\n    [ [ 'beep', 2, 0.5 ], [ 'boop', 1, 0.25 ], [ 'foo', 1, 0.25 ] ]\n\n    See Also\n    --------\n    countBy, groupBy, tabulateBy\n","tabulateBy":"\ntabulateBy( collection, [options,] indicator )\n    Generates a frequency table according to an indicator function.\n\n    When invoked, the indicator function is provided two arguments:\n\n    - value: collection value.\n    - index: collection index.\n\n    The table is an array of arrays where each sub-array corresponds to a unique\n    value in the input collection. Each sub-array is structured as follows:\n\n    - 0: unique value.\n    - 1: value count.\n    - 2: frequency percentage.\n\n    If provided an empty collection, the function returns an empty array.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection to tabulate. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Options.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    indicator: Function\n        Indicator function specifying how to categorize a collection element.\n\n    Returns\n    -------\n    out: Array<Array>|Array\n        Frequency table.\n\n    Examples\n    --------\n    > function indicator( value ) { return value[ 0 ]; };\n    > var collection = [ 'beep', 'boop', 'foo', 'beep' ];\n    > var out = tabulateBy( collection, indicator )\n    [ [ 'b', 3, 0.75 ], [ 'f', 1, 0.25 ] ]\n\n    See Also\n    --------\n    countBy, groupBy, tabulate\n","tabulateByAsync":"\ntabulateByAsync( collection, [options,] indicator, done )\n    Generates a frequency table according to an indicator function.\n\n    The table is an array of arrays where each sub-array corresponds to a unique\n    value in the input collection. Each sub-array is structured as follows:\n\n    - 0: unique value.\n    - 1: value count.\n    - 2: frequency percentage.\n\n    When invoked, the indicator function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If the\n    indicator function accepts two arguments, the indicator function is\n    provided:\n\n    - value\n    - next\n\n    If the indicator function accepts three arguments, the indicator function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other indicator function signature, the indicator function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - group: value group.\n\n    If an indicator function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    If provided an empty collection, the function calls the `done` callback with\n    an empty array as the second argument.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    indicator: Function\n        Indicator function specifying how to categorize a collection element.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000, 750 ];\n    > tabulateByAsync( arr, indicator, done )\n    750\n    1000\n    2500\n    3000\n    [ [ 'odd', 2, 0.5 ], [ 'even', 2, 0.5 ] ]\n\n    // Limit number of concurrent invocations:\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 3000, 2500, 1000, 750 ];\n    > tabulateByAsync( arr, opts, indicator, done )\n    2500\n    3000\n    1000\n    750\n    [ [ 'odd', 2, 0.5 ], [ 'even', 2, 0.5 ] ]\n\n    // Process sequentially:\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 3000, 2500, 1000, 750 ];\n    > tabulateByAsync( arr, opts, indicator, done )\n    3000\n    2500\n    1000\n    750\n    [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n\ntabulateByAsync.factory( [options,] indicator )\n    Returns a function which generates a frequency table according to an\n    indicator function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    indicator: Function\n        Indicator function specifying how to categorize a collection element.\n\n    Returns\n    -------\n    out: Function\n        A function which generates a frequency table according to an indicator\n        function.\n\n    Examples\n    --------\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = tabulateByAsync.factory( opts, indicator );\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000, 750 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    750\n    [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n    > arr = [ 2000, 1500, 1000, 750 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    750\n    [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n    See Also\n    --------\n    countByAsync, groupByAsync, tabulateBy\n","tabulateByAsync.factory":"\ntabulateByAsync.factory( [options,] indicator )\n    Returns a function which generates a frequency table according to an\n    indicator function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    indicator: Function\n        Indicator function specifying how to categorize a collection element.\n\n    Returns\n    -------\n    out: Function\n        A function which generates a frequency table according to an indicator\n        function.\n\n    Examples\n    --------\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = tabulateByAsync.factory( opts, indicator );\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000, 750 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    750\n    [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n    > arr = [ 2000, 1500, 1000, 750 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    750\n    [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n    See Also\n    --------\n    countByAsync, groupByAsync, tabulateBy","thunk":"\nthunk( fcn[, ...args] )\n    Returns a thunk.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to convert to a thunk.\n\n    args: ...any (optional)\n        Function arguments.\n\n    Returns\n    -------\n    out: Function\n        Thunk.\n\n    Examples\n    --------\n    > var fcn = thunk( base.add, 2, 3 );\n    > var v = fcn()\n    5\n    > v = fcn()\n    5\n\n","tic":"\ntic()\n    Returns a high-resolution time.\n\n    The returned array has the following format: `[seconds, nanoseconds]`.\n\n    Returns\n    -------\n    out: Array<integer>\n        High resolution time.\n\n    Examples\n    --------\n    > var t = tic()\n    [ <number>, <number> ]\n\n    See Also\n    --------\n    toc\n","timeit":"\ntimeit( code, [options,] clbk )\n    Times a snippet.\n\n    If the `asynchronous` option is set to `true`, the implementation assumes\n    that `before`, `after`, and `code` snippets are all asynchronous.\n    Accordingly, these snippets should invoke a `next( [error] )` callback\n    once complete. The implementation wraps the snippet within a function\n    accepting two arguments: `state` and `next`.\n\n    The `state` parameter is simply an empty object which allows the `before`,\n    `after`, and `code` snippets to share state.\n\n    Notes:\n\n    - Snippets always run in strict mode.\n    - Always verify results. Doing so prevents the compiler from performing dead\n      code elimination and other optimization techniques, which would render\n      timing results meaningless.\n    - Executed code is not sandboxed and has access to the global state. You are\n      strongly advised against timing untrusted code. To time untrusted code,\n      do so in an isolated environment (e.g., a separate process with restricted\n      access to both global state and the host environment).\n    - Wrapping asynchronous code does add overhead, but, in most cases, the\n      overhead should be negligible compared to the execution cost of the timed\n      snippet.\n    - When the `asynchronous` option is `true`, ensure that the main `code`\n      snippet is actually asynchronous. If a snippet releases the zalgo, an\n      error complaining about exceeding the maximum call stack size is highly\n      likely.\n    - While many benchmark frameworks calculate various statistics over raw\n      timing results (e.g., mean and standard deviation), do not do this.\n      Instead, consider the fastest time an approximate lower bound for how fast\n      an environment can execute a snippet. Slower times are more likely\n      attributable to other processes interfering with timing accuracy rather\n      than attributable to variability in JavaScript's speed. In which case, the\n      minimum time is most likely the only result of interest. When considering\n      all raw timing results, apply common sense rather than statistics.\n\n    Parameters\n    ----------\n    code: string\n         Snippet to time.\n\n    options: Object (optional)\n        Options.\n\n    options.before: string (optional)\n        Setup code. Default: `''`.\n\n    options.after: string (optional)\n        Cleanup code. Default: `''`.\n\n    options.iterations: integer|null (optional)\n        Number of iterations. If `null`, the number of iterations is determined\n        by trying successive powers of `10` until the total time is at least\n        `0.1` seconds. Default: `1e6`.\n\n    options.repeats: integer (optional)\n        Number of repeats. Default: `3`.\n\n    options.asynchronous: boolean (optional)\n        Boolean indicating whether a snippet is asynchronous. Default: `false`.\n\n    clbk: Function\n        Callback to invoke upon completion.\n\n    Examples\n    --------\n    > var code = 'var x = Math.pow( Math.random(), 3 );';\n    > code += 'if ( x !== x ) {';\n    > code += 'throw new Error( \\'Something went wrong.\\' );';\n    > code += '}';\n    > function done( error, results ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.dir( results );\n    ... };\n    > timeit( code, done )\n    e.g.,\n    {\n        \"iterations\": 1000000,\n        \"repeats\": 3,\n        \"min\": [ 0, 135734733 ],    // [seconds,nanoseconds]\n        \"elapsed\": 0.135734733,     // seconds\n        \"rate\": 7367311.062526641,  // iterations/second\n        \"times\": [                  // raw timing results\n            [ 0, 145641393 ],\n            [ 0, 135734733 ],\n            [ 0, 140462721 ]\n        ]\n    }\n\n","tmpdir":"\ntmpdir()\n    Returns the directory for storing temporary files.\n\n    Returns\n    -------\n    dir: string\n        Directory for temporary files.\n\n    Examples\n    --------\n    > var dir = tmpdir()\n    e.g., '/path/to/temporary/files/directory'\n\n    See Also\n    --------\n    configdir, homedir\n","toc":"\ntoc( time )\n    Returns a high-resolution time difference, where `time` is a two-element\n    array with format `[seconds, nanoseconds]`.\n\n    Similar to `time`, the returned array has format `[seconds, nanoseconds]`.\n\n    Parameters\n    ----------\n    time: Array<integer>\n        High-resolution time.\n\n    Returns\n    -------\n    out: Array<integer>\n        High resolution time difference.\n\n    Examples\n    --------\n    > var start = tic();\n    > var delta = toc( start )\n    [ <number>, <number> ]\n\n    See Also\n    --------\n    tic\n","tokenize":"\ntokenize( str[, keepWhitespace] )\n    Tokenizes a string.\n\n    To include whitespace characters (spaces, tabs, line breaks) in the output\n    array, set `keepWhitespace` to `true`.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    keepWhitespace: boolean (optional)\n        Boolean indicating whether whitespace characters should be returned as\n        part of the token array. Default: `false`.\n\n    Returns\n    -------\n    out: Array\n        Array of tokens.\n\n    Examples\n    --------\n    > var out = tokenize( 'Hello Mrs. Maple, could you call me back?' )\n    [ 'Hello', 'Mrs.', 'Maple', ',', 'could', 'you', 'call', 'me', 'back', '?' ]\n\n    > out = tokenize( 'Hello World!', true )\n    [ 'Hello', ' ', 'World', '!' ]\n\n","transformStream":"\ntransformStream( [options] )\n    Returns a transform stream.\n\n    If a transform function is not provided, the returned stream will be a\n    simple pass through stream.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.transform: Function (optional)\n        Callback to invoke upon receiving a new chunk.\n\n    options.flush: Function (optional)\n        Callback to invoke after receiving all chunks and prior to a stream\n        closing.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to decode strings into Buffer objects when writing.\n        Default: true.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream.\n\n    Examples\n    --------\n    > var s = transformStream();\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();\n\n\ntransformStream.factory( [options] )\n    Returns a function for creating transform streams.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to decode strings into Buffer objects when writing.\n        Default: true.\n\n    Returns\n    -------\n    createStream( transform[, flush] ): Function\n        Function for creating transform streams.\n\n    Examples\n    --------\n    > var opts = { 'highWaterMark': 64 };\n    > var createStream = transformStream.factory( opts );\n    > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n    > var s = createStream( fcn );\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();\n\n\ntransformStream.objectMode( [options] )\n    Returns an \"objectMode\" transform stream.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.transform: Function (optional)\n        Callback to invoke upon receiving a new chunk.\n\n    options.flush: Function (optional)\n        Callback to invoke after receiving all chunks and prior to a stream\n        closing.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to decode strings into Buffer objects when writing.\n        Default: true.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > var s = transformStream.objectMode();\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();\n\n\ntransformStream.ctor( [options] )\n    Returns a custom transform stream constructor.\n\n    If provided `transform` and `flush` options, these methods are bound to the\n    constructor prototype.\n\n    If not provided a transform function, the returned constructor creates\n    simple pass through streams.\n\n    The returned constructor accepts the same options as the constructor\n    factory, *except* for the `transform` and `flush` options, which are not\n    supported.\n\n    Any options provided to the constructor *override* options provided to the\n    constructor factory.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.transform: Function (optional)\n        Callback to invoke upon receiving a new chunk.\n\n    options.flush: Function (optional)\n        Callback to invoke after receiving all chunks and prior to a stream\n        closing.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to decode strings into Buffer objects when writing.\n        Default: true.\n\n    Returns\n    -------\n    ctor: Function\n        Custom transform stream constructor.\n\n    Examples\n    --------\n    > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n    > var opts = { 'highWaterMark': 64, 'transform': fcn };\n    > var customStream = transformStream.ctor( opts );\n    > var s = customStream();\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();\n\n","transformStream.factory":"\ntransformStream.factory( [options] )\n    Returns a function for creating transform streams.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to decode strings into Buffer objects when writing.\n        Default: true.\n\n    Returns\n    -------\n    createStream( transform[, flush] ): Function\n        Function for creating transform streams.\n\n    Examples\n    --------\n    > var opts = { 'highWaterMark': 64 };\n    > var createStream = transformStream.factory( opts );\n    > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n    > var s = createStream( fcn );\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();","transformStream.objectMode":"\ntransformStream.objectMode( [options] )\n    Returns an \"objectMode\" transform stream.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.transform: Function (optional)\n        Callback to invoke upon receiving a new chunk.\n\n    options.flush: Function (optional)\n        Callback to invoke after receiving all chunks and prior to a stream\n        closing.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to decode strings into Buffer objects when writing.\n        Default: true.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > var s = transformStream.objectMode();\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();","transformStream.ctor":"\ntransformStream.ctor( [options] )\n    Returns a custom transform stream constructor.\n\n    If provided `transform` and `flush` options, these methods are bound to the\n    constructor prototype.\n\n    If not provided a transform function, the returned constructor creates\n    simple pass through streams.\n\n    The returned constructor accepts the same options as the constructor\n    factory, *except* for the `transform` and `flush` options, which are not\n    supported.\n\n    Any options provided to the constructor *override* options provided to the\n    constructor factory.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.transform: Function (optional)\n        Callback to invoke upon receiving a new chunk.\n\n    options.flush: Function (optional)\n        Callback to invoke after receiving all chunks and prior to a stream\n        closing.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to decode strings into Buffer objects when writing.\n        Default: true.\n\n    Returns\n    -------\n    ctor: Function\n        Custom transform stream constructor.\n\n    Examples\n    --------\n    > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n    > var opts = { 'highWaterMark': 64, 'transform': fcn };\n    > var customStream = transformStream.ctor( opts );\n    > var s = customStream();\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();","trim":"\ntrim( str )\n    Trims whitespace from the beginning and end of a `string`.\n\n    \"Whitespace\" is defined as the following characters:\n\n    - \\f\n    - \\n\n    - \\r\n    - \\t\n    - \\v\n    - \\u0020\n    - \\u00a0\n    - \\u1680\n    - \\u2000-\\u200a\n    - \\u2028\n    - \\u2029\n    - \\u202f\n    - \\u205f\n    - \\u3000\n    - \\ufeff\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Trimmed string.\n\n    Examples\n    --------\n    > var out = trim( ' \\t\\t\\n  Beep \\r\\n\\t  ' )\n    'Beep'\n\n    See Also\n    --------\n    ltrim, pad, rtrim\n","truncate":"\ntruncate( str, len[, ending] )\n    Truncates a string to a specified length.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    len: integer\n        Output string length.\n\n    ending: string (optional)\n        Custom ending. Default: '...'.\n\n    Returns\n    -------\n    out: string\n        Truncated string.\n\n    Examples\n    --------\n    > var str = 'beep boop';\n    > var out = truncate( str, 5 )\n    'be...'\n\n    > out = truncate( str, 5, '|' )\n    'beep|'\n\n    See Also\n    --------\n    truncateMiddle","truncateMiddle":"\ntruncateMiddle( str, len[, seq] )\n    Truncates a string in the middle to a specified length.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    len: integer\n        Output string length.\n\n    seq: string (optional)\n        Custom replacement sequence. Default: '...'.\n\n    Returns\n    -------\n    out: string\n        Truncated string.\n\n    Examples\n    --------\n    > var str = 'beep boop';\n    > var out = truncateMiddle( str, 5 )\n    'b...p'\n\n    > out = truncateMiddle( str, 5, '|' )\n    'be|op'\n\n    See Also\n    --------\n    truncate","trycatch":"\ntrycatch( x, y )\n    If a function does not throw, returns the function return value; otherwise,\n    returns `y`.\n\n    Parameters\n    ----------\n    x: Function\n        Function to try invoking.\n\n    y: any\n        Value to return if a function throws an error.\n\n    Returns\n    -------\n    z: any\n        Either the return value of `x` or the provided argument `y`.\n\n    Examples\n    --------\n    > function x() {\n    ...     if ( base.random.randu() < 0.5 ) {\n    ...         throw new Error( 'beep' );\n    ...     }\n    ...     return 1.0;\n    ... };\n    > var z = trycatch( x, -1.0 )\n    <number>\n\n    See Also\n    --------\n    trycatchAsync, trythen\n","trycatchAsync":"\ntrycatchAsync( x, y, done )\n    If a function does not return an error, invokes a callback with the function\n    result; otherwise, invokes a callback with a value `y`.\n\n    A function `x` is provided a single argument:\n\n    - clbk: callback to invoke upon function completion.\n\n    The callback function accepts two arguments:\n\n    - error: error object.\n    - result: function result.\n\n    The `done` callback is invoked upon function completion and is provided two\n    arguments:\n\n    - error: error object.\n    - result: either the result of `x` or the provided argument `y`.\n\n    If `x` invokes `clbk` with an error argument, the function invokes the\n    `done` callback with both the error and the argument `y`.\n\n    If `x` does not invoke `clbk` with an error argument, the function invokes\n    the `done` callback with a first argument equal to `null` and the function\n    `result`.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Parameters\n    ----------\n    x: Function\n        Function to invoke.\n\n    y: any\n        Value to return if `x` returns an error.\n\n    done: Function\n        Callback to invoke upon completion.\n\n    Examples\n    --------\n    > function x( clbk ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         clbk( new Error( 'beep' ) );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         // process error...\n    ...     }\n    ...     console.log( result );\n    ... };\n    > trycatchAsync( x, 'boop', done )\n    'boop'\n\n    See Also\n    --------\n    trycatch, trythenAsync\n","tryFunction":"\ntryFunction( fcn[, thisArg] )\n    Wraps a function in a try/catch block.\n\n    If provided an asynchronous function, the returned function only traps\n    errors which occur during the current event loop tick.\n\n    If a function throws a literal, the literal is serialized as a string and\n    returned as an `Error` object.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to wrap.\n\n    thisArg: any (optional)\n        Function context.\n\n    Returns\n    -------\n    out: Function\n        Wrapped function.\n\n    Examples\n    --------\n    > function fcn() { throw new Error( 'beep boop' ); };\n    > var f = tryFunction( fcn );\n    > var out = f();\n    > out.message\n    'beep boop'\n\n","tryRequire":"\ntryRequire( id )\n    Wraps `require` in a `try/catch` block.\n\n    This function traps and returns any errors encountered when attempting to\n    require a module.\n\n    Use caution when attempting to resolve a relative path or a local module.\n    This function attempts to resolve a module from its current path. Thus, the\n    function is unable to resolve anything which is not along its search path.\n    For local requires, use an absolute file path.\n\n    Parameters\n    ----------\n    id: string\n        Module id.\n\n    Returns\n    -------\n    out: any|Error\n        Resolved module or an `Error`.\n\n    Examples\n    --------\n    > var out = tryRequire( '_unknown_module_id_' )\n    <Error>\n\n","trythen":"\ntrythen( x, y )\n    If a function does not throw, returns the function return value; otherwise,\n    returns the value returned by a second function `y`.\n\n    The function `y` is provided a single argument:\n\n    - error: the error thrown by `x`.\n\n    Parameters\n    ----------\n    x: Function\n        Function to try invoking.\n\n    y: Function\n        Function to invoke if an initial function throws an error.\n\n    Returns\n    -------\n    z: any\n        The return value of either `x` or `y`.\n\n    Examples\n    --------\n    > function x() {\n    ...     if ( base.random.randu() < 0.5 ) {\n    ...         throw new Error( 'beep' );\n    ...     }\n    ...     return 1.0;\n    ... };\n    > function y() {\n    ...     return -1.0;\n    ... };\n    > var z = trythen( x, y )\n    <number>\n\n    See Also\n    --------\n    trycatch, trythenAsync\n","trythenAsync":"\ntrythenAsync( x, y, done )\n    If a function does not return an error, invokes a callback with the function\n    result; otherwise, invokes a second function `y`.\n\n    A function `x` is provided a single argument:\n\n    - clbk: callback to invoke upon function completion.\n\n    The callback function accepts any number of arguments, with the first\n    argument reserved for providing an error.\n\n    If the error argument is falsy, the function invokes a `done` callback with\n    its first argument as `null` and all other provided arguments.\n\n    If the error argument is truthy, the function invokes a function `y`. The\n    number of arguments provided to `y` depends on the function's length. If `y`\n    is a unary function, `y` is provided a single argument:\n\n    - clbk: callback to invoke upon function completion.\n\n    Otherwise, `y` is provided two arguments:\n\n    - error: the error from `x`.\n    - clbk: callback to invoke upon function completion.\n\n    The callback function accepts any number of arguments, with the first\n    argument reserved for providing an error.\n\n    If the error argument is falsy, the `done` callback is invoked with its\n    first argument equal to `null` and all other arguments provided by `y`.\n\n    If the error argument is truthy, the `done` callback is invoked with only\n    the error argument provided by `y`.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Parameters\n    ----------\n    x: Function\n        Function to invoke.\n\n    y: Function\n        Function to invoke if `x` returns an error.\n\n    done: Function\n        Callback to invoke upon completion.\n\n    Examples\n    --------\n    > function x( clbk ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         clbk( new Error( 'beep' ) );\n    ...     }\n    ... };\n    > function y( clbk ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         clbk( null, 'boop' );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > trythenAsync( x, y, done )\n    'boop'\n\n    See Also\n    --------\n    trycatchAsync, trythen\n","ttest":"\nttest( x[, y][, options] )\n    Computes a one-sample or paired Student's t test.\n\n    When no `y` is supplied, the function performs a one-sample t-test for the\n    null hypothesis that the data in array or typed array `x` is drawn from a\n    normal distribution with mean zero and unknown variance.\n\n    When array or typed array `y` is supplied, the function tests whether the\n    differences `x - y` come from a normal distribution with mean zero and\n    unknown variance via the paired t-test.\n\n    The returned object comes with a `.print()` method which when invoked will\n    print a formatted output of the results of the hypothesis test.\n\n    Parameters\n    ----------\n    x: Array<number>\n        Data array.\n\n    y: Array<number> (optional)\n        Paired data array.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.alternative: string (optional)\n        Indicates whether the alternative hypothesis is that the mean of `x` is\n        larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n        `mu` (`two-sided`). Default: `'two-sided'`.\n\n    options.mu: number (optional)\n        Hypothesized true mean under the null hypothesis. Set this option to\n        test whether the data comes from a distribution with the specified `mu`.\n        Default: `0`.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Used significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.ci: Array<number>\n        1-alpha confidence interval for the mean.\n\n    out.nullValue: number\n        Assumed mean under H0 (or difference in means when `y` is supplied).\n\n    out.alternative: string\n        Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n    out.df: number\n        Degrees of freedom.\n\n    out.mean: number\n        Sample mean of `x` or `x - y`, respectively.\n\n    out.sd: number\n        Standard error of the mean.\n\n    out.method: string\n        Name of test.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    // One-sample t-test:\n    > var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 5776 } );\n    > var x = new Array( 100 );\n    > for ( var i = 0; i < x.length; i++ ) {\n    ...     x[ i ] = rnorm();\n    ... }\n    > var out = ttest( x )\n    {\n        rejected: false,\n        pValue: ~0.722,\n        statistic: ~0.357,\n        ci: [~-0.333,~0.479],\n        // ...\n    }\n\n    // Paired t-test:\n    > rnorm = base.random.normal.factory( 1.0, 2.0, { 'seed': 786 } );\n    > x = new Array( 100 );\n    > var y = new Array( 100 );\n    > for ( i = 0; i < x.length; i++ ) {\n    ...     x[ i ] = rnorm();\n    ...     y[ i ] = rnorm();\n    ... }\n    > out = ttest( x, y )\n    {\n        rejected: false,\n        pValue: ~0.191,\n        statistic: ~1.315,\n        ci: [ ~-0.196, ~0.964 ],\n        // ...\n    }\n\n    // Print formatted output:\n    > var table = out.print()\n    Paired t-test\n\n    Alternative hypothesis: True difference in means is not equal to 0\n\n        pValue: 0.1916\n        statistic: 1.3148\n        df: 99\n        95% confidence interval: [-0.1955,0.9635]\n\n    Test Decision: Fail to reject null in favor of alternative at 5%\n    significance level\n\n    // Choose custom significance level:\n    > var arr = [ 2, 4, 3, 1, 0 ];\n    > out = ttest( arr, { 'alpha': 0.01 } );\n    > table = out.print()\n    One-sample t-test\n\n    Alternative hypothesis: True mean is not equal to 0\n\n        pValue: 0.0474\n        statistic: 2.8284\n        df: 4\n        99% confidence interval: [-1.2556,5.2556]\n\n    Test Decision: Fail to reject null in favor of alternative at 1%\n    significance level\n\n    // Test for a mean equal to five:\n    > arr = [ 4, 4, 6, 6, 5 ];\n    > out = ttest( arr, { 'mu': 5 } )\n    {\n        rejected: false,\n        pValue: 1,\n        statistic: 0,\n        ci: [ ~3.758, ~6.242 ],\n        // ...\n    }\n\n    // Perform one-sided tests:\n    > arr = [ 4, 4, 6, 6, 5 ];\n    > out = ttest( arr, { 'alternative': 'less' } );\n    > table = out.print()\n    One-sample t-test\n\n    Alternative hypothesis: True mean is less than 0\n\n        pValue: 0.9998\n        statistic: 11.1803\n        df: 4\n        95% confidence interval: [-Infinity,5.9534]\n\n    Test Decision: Fail to reject null in favor of alternative at 5%\n    significance level\n\n    > out = ttest( arr, { 'alternative': 'greater' } );\n    > table = out.print()\n    One-sample t-test\n\n    Alternative hypothesis: True mean is greater than 0\n\n        pValue: 0.0002\n        statistic: 11.1803\n        df: 4\n        95% confidence interval: [4.0466,Infinity]\n\n    Test Decision: Reject null in favor of alternative at 5% significance level\n\n    See Also\n    --------\n    ttest2\n","ttest2":"\nttest2( x, y[, options] )\n    Computes a two-sample Student's t test.\n\n    By default, the function performs a two-sample t-test for the null\n    hypothesis that the data in arrays or typed arrays `x` and `y` is\n    independently drawn from normal distributions with equal means.\n\n    The returned object comes with a `.print()` method which when invoked will\n    print a formatted output of the results of the hypothesis test.\n\n    Parameters\n    ----------\n    x: Array<number>\n        First data array.\n\n    y: Array<number>\n        Second data array.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.alternative: string (optional)\n        Either `two-sided`, `less` or `greater`. Indicates whether the\n        alternative hypothesis is that `x` has a larger mean than `y`\n        (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n        the same (`two-sided`). Default: `'two-sided'`.\n\n    options.difference: number (optional)\n        Number denoting the difference in means under the null hypothesis.\n        Default: `0`.\n\n    options.variance: string (optional)\n        String indicating if the test should be conducted under the assumption\n        that the unknown variances of the normal distributions are `equal` or\n        `unequal`. As a default choice, the function carries out the Welch test\n        (using the Satterthwaite approximation for the degrees of freedom),\n        which does not have the requirement that the variances of the underlying\n        distributions are equal. If the equal variances assumption seems\n        warranted, set the option to `equal`. Default: `unequal`.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Used significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.ci: Array<number>\n        1-alpha confidence interval for the mean.\n\n    out.nullValue: number\n        Assumed difference in means under H0.\n\n    out.xmean: number\n        Sample mean of `x`.\n\n    out.ymean: number\n        Sample mean of `y`.\n\n    out.alternative: string\n        Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n    out.df: number\n        Degrees of freedom.\n\n    out.method: string\n        Name of test.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    // Student's sleep data:\n    > var x = [ 0.7, -1.6, -0.2, -1.2, -0.1, 3.4, 3.7, 0.8, 0.0, 2.0 ];\n    > var y = [ 1.9, 0.8, 1.1, 0.1, -0.1, 4.4, 5.5, 1.6, 4.6, 3.4 ];\n    > var out = ttest2( x, y )\n    {\n        rejected: false,\n        pValue: ~0.079,\n        statistic: ~-1.861,\n        ci: [ ~-3.365, ~0.205 ],\n        // ...\n    }\n\n    // Print table output:\n    > var table = out.print()\n    Welch two-sample t-test\n\n    Alternative hypothesis: True difference in means is not equal to 0\n\n        pValue: 0.0794\n        statistic: -1.8608\n        95% confidence interval: [-3.3655,0.2055]\n\n    Test Decision: Fail to reject null in favor of alternative at 5%\n    significance level\n\n    // Choose a different significance level than `0.05`:\n    > out = ttest2( x, y, { 'alpha': 0.1 } );\n    > table = out.print()\n    Welch two-sample t-test\n\n    Alternative hypothesis: True difference in means is not equal to 0\n\n        pValue: 0.0794\n        statistic: -1.8608\n        90% confidence interval: [-3.0534,-0.1066]\n\n    Test Decision: Reject null in favor of alternative at 10% significance level\n\n    // Perform one-sided tests:\n    > out = ttest2( x, y, { 'alternative': 'less' } );\n    > table = out.print()\n    Welch two-sample t-test\n\n    Alternative hypothesis: True difference in means is less than 0\n\n        pValue: 0.0397\n        statistic: -1.8608\n        df: 17.7765\n        95% confidence interval: [-Infinity,-0.1066]\n\n    Test Decision: Reject null in favor of alternative at 5% significance level\n\n    > out = ttest2( x, y, { 'alternative': 'greater' } );\n    > table = out.print()\n    Welch two-sample t-test\n\n    Alternative hypothesis: True difference in means is greater than 0\n\n        pValue: 0.9603\n        statistic: -1.8608\n        df: 17.7765\n        95% confidence interval: [-3.0534,Infinity]\n\n    Test Decision: Fail to reject null in favor of alternative at 5%\n    significance level\n\n    // Run tests with equal variances assumption:\n    > x = [ 2, 3, 1, 4 ];\n    > y = [ 1, 2, 3, 1, 2, 5, 3, 4 ];\n    > out = ttest2( x, y, { 'variance': 'equal' } );\n    > table = out.print()\n    Two-sample t-test\n\n    Alternative hypothesis: True difference in means is not equal to 0\n\n        pValue: 0.8848\n        statistic: -0.1486\n        df: 10\n        95% confidence interval: [-1.9996,1.7496]\n\n    Test Decision: Fail to reject null in favor of alternative at 5%\n    significance level\n\n    // Test for a difference in means besides zero:\n    > var rnorm = base.random.normal.factory({ 'seed': 372 } );\n    > x = new Array( 100 );\n    > for ( i = 0; i < x.length; i++ ) {\n    ...     x[ i ] = rnorm( 2.0, 3.0 );\n    ... }\n    > y = new Array( 100 );\n    > for ( i = 0; i < x.length; i++ ) {\n    ...     y[ i ] = rnorm( 1.0, 3.0 );\n    ... }\n    > out = ttest2( x, y, { 'difference': 1.0, 'variance': 'equal' } )\n    {\n        rejected: false,\n        pValue: ~0.642,\n        statistic: ~-0.466,\n        ci: [ ~-0.0455, ~1.646 ],\n        // ...\n    }\n\n    See Also\n    --------\n    ttest\n","TWO_PI":"\nTWO_PI\n    The mathematical constant `π` times `2`.\n\n    Examples\n    --------\n    > TWO_PI\n    6.283185307179586\n\n    See Also\n    --------\n    PI\n","typedarray":"\ntypedarray( [dtype] )\n    Creates a typed array.\n\n    Parameters\n    ----------\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = typedarray()\n    <Float64Array>\n    > arr = typedarray( 'float32' )\n    <Float32Array>\n\n\ntypedarray( length[, dtype] )\n    Returns a typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = typedarray( 5 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n    > arr = typedarray( 5, 'int32' )\n    <Int32Array>[ 0, 0, 0, 0, 0 ]\n\n\ntypedarray( typedarray[, dtype] )\n    Creates a typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = typedarray( [ 0.5, 0.5, 0.5 ] );\n    > var arr2 = typedarray( arr1, 'float32' )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]\n\n\ntypedarray( obj[, dtype] )\n    Creates a typed array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a typed array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 0.5, 0.5, 0.5 ];\n    > var arr2 = typedarray( arr1, 'float32' )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]\n\n\ntypedarray( buffer[, byteOffset[, length]][, dtype] )\n    Returns a typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 16 );\n    > var arr = typedarray( buf, 0, 4, 'float32' )\n    <Float32Array>[ 0.0, 0.0, 0.0, 0.0 ]\n\n    See Also\n    --------\n    Complex128Array, Complex64Array, Float64Array, Float32Array, Int32Array, Uint32Array, Int16Array, Uint16Array, Int8Array, Uint8Array, Uint8ClampedArray\n","typedarray2json":"\ntypedarray2json( arr )\n    Returns a JSON representation of a typed array.\n\n    The following typed array types are supported:\n\n    - Float64Array\n    - Float32Array\n    - Int32Array\n    - Uint32Array\n    - Int16Array\n    - Uint16Array\n    - Int8Array\n    - Uint8Array\n    - Uint8ClampedArray\n    - Complex64Array\n    - Complex128Array\n    - BooleanArray\n\n    The returned JSON object has the following properties:\n\n    - type: typed array type.\n    - data: typed array data as a generic array.\n\n    The implementation supports custom typed arrays and sets the `type` field to\n    the closest known typed array type.\n\n    Parameters\n    ----------\n    arr: TypedArray\n        Typed array to serialize.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 2 );\n    > arr[ 0 ] = 5.0;\n    > arr[ 1 ] = 3.0;\n    > var json = typedarray2json( arr )\n    { 'type': 'Float64Array', 'data': [ 5.0, 3.0 ] }\n\n    See Also\n    --------\n    reviveTypedArray\n","typedarrayCtors":"\ntypedarrayCtors( dtype )\n    Returns a typed array constructor.\n\n    The function returns constructors for the following data types:\n\n    - float32: single-precision floating-point numbers.\n    - float64: double-precision floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - complex128: double-precision complex floating-point numbers.\n    - bool: boolean values.\n    - int16: signed 16-bit integers.\n    - int32: signed 32-bit integers.\n    - int8: signed 8-bit integers.\n    - uint16: unsigned 16-bit integers.\n    - uint32: unsigned 32-bit integers.\n    - uint8: unsigned 8-bit integers.\n    - uint8c: unsigned clamped 8-bit integers.\n\n    Parameters\n    ----------\n    dtype: string\n        Data type.\n\n    Returns\n    -------\n    out: Function|null\n        Typed array constructor.\n\n    Examples\n    --------\n    > var ctor = typedarrayCtors( 'float64' )\n    <Function>\n    > ctor = typedarrayCtors( 'float' )\n    null\n\n    See Also\n    --------\n    arrayCtors\n","typedarrayDataTypes":"\ntypedarrayDataTypes()\n    Returns a list of typed array data types.\n\n    Returns\n    -------\n    out: Array<string>\n        List of typed array data types.\n\n    Examples\n    --------\n    > var out = typedarrayDataTypes()\n    <Array>\n\n    See Also\n    --------\n    arrayDataTypes, ndarrayDataTypes\n","typedarraypool":"\ntypedarraypool( [dtype] )\n    Returns an uninitialized typed array from a typed array memory pool.\n\n    Memory is **uninitialized**, which means that the contents of a returned\n    typed array may contain sensitive contents.\n\n    Parameters\n    ----------\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr = typedarraypool()\n    <Float64Array>[]\n    > arr = typedarraypool( 'float32' )\n    <Float32Array>[]\n\n\ntypedarraypool( length[, dtype] )\n    Returns an uninitialized typed array having a specified length from a typed\n    array memory pool.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr = typedarraypool( 5 )\n    <Float64Array>\n    > arr = typedarraypool( 5, 'int32' )\n    <Int32Array>\n\n\ntypedarraypool( typedarray[, dtype] )\n    Creates a pooled typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr1 = typedarraypool( [ 0.5, 0.5, 0.5 ] );\n    > var arr2 = typedarraypool( arr1, 'float32' )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool( obj[, dtype] )\n    Creates a pooled typed array from an array-like object.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object from which to generate a typed array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr1 = [ 0.5, 0.5, 0.5 ];\n    > var arr2 = typedarraypool( arr1, 'float32' )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.malloc( [dtype] )\n    Returns an uninitialized typed array from a typed array memory pool.\n\n    This method shares the same security vulnerabilities mentioned above.\n\n    Parameters\n    ----------\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr = typedarraypool.malloc()\n    <Float64Array>\n    > arr = typedarraypool.malloc( 'float32' )\n    <Float32Array>\n\n\ntypedarraypool.malloc( length[, dtype] )\n    Returns a typed array having a specified length from a typed array memory\n    pool.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr = typedarraypool.malloc( 5 )\n    <Float64Array>\n    > arr = typedarraypool.malloc( 5, 'int32' )\n    <Int32Array>\n\n\ntypedarraypool.malloc( typedarray[, dtype] )\n    Creates a pooled typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr1 = typedarraypool.malloc( [ 0.5, 0.5, 0.5 ] );\n    > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.malloc( obj[, dtype] )\n    Creates a pooled typed array from an array-like object.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object from which to generate a typed array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr1 = [ 0.5, 0.5, 0.5 ];\n    > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.calloc( [dtype] )\n    Returns a zero-initialized typed array from a typed array memory pool.\n\n    Parameters\n    ----------\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr = typedarraypool.calloc()\n    <Float64Array>[]\n    > arr = typedarraypool.calloc( 'float32' )\n    <Float32Array>[]\n\n\ntypedarraypool.calloc( length[, dtype] )\n    Returns a zero-initialized typed array having a specified length from a\n    typed array memory pool.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr = typedarraypool.calloc( 5 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n    > arr = typedarraypool.calloc( 5, 'int32' )\n    <Int32Array>[ 0, 0, 0, 0, 0 ]\n\n\ntypedarraypool.free( buf )\n    Frees a typed array or typed array buffer for use in a future allocation.\n\n    Parameters\n    ----------\n    buf: TypedArray|ArrayBuffer\n        Typed array or typed array buffer to free.\n\n    Examples\n    --------\n    > var arr = typedarraypool( 5 )\n    <Float64Array>\n    > typedarraypool.free( arr );\n\n\ntypedarraypool.clear()\n    Clears the typed array pool allowing garbage collection of previously\n    allocated (and currently free) array buffers.\n\n    Examples\n    --------\n    > var arr = typedarraypool( 5 )\n    <Float64Array>\n    > typedarraypool.free( arr );\n    > typedarraypool.clear();\n\n\ntypedarraypool.highWaterMark\n    Read-only property returning the pool's high water mark.\n\n    Once a high water mark is reached, typed array allocation fails.\n\n    Examples\n    --------\n    > typedarraypool.highWaterMark\n    <number>\n\n\ntypedarraypool.nbytes\n    Read-only property returning the total number of allocated bytes.\n\n    The returned value is the total accumulated value. Hence, anytime a pool\n    must allocate a new array buffer (i.e., more memory), the pool increments\n    this value.\n\n    The only time this value is decremented is when a pool is cleared.\n\n    This behavior means that, while allocated buffers which are never freed may,\n    in fact, be garbage collected, they continue to count against the high water\n    mark limit.\n\n    Accordingly, you should *always* free allocated buffers in order to prevent\n    the pool from believing that non-freed buffers are continually in use.\n\n    Examples\n    --------\n    > var arr = typedarraypool( 5 )\n    <Float64Array>\n    > typedarraypool.nbytes\n    <number>\n\n\ntypedarraypool.factory( [options] )\n    Creates a typed array pool.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.highWaterMark: integer (optional)\n        Maximum total memory (in bytes) which can be allocated.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating typed arrays from a typed array memory pool.\n\n    Examples\n    --------\n    > var pool = typedarraypool.factory();\n    > var arr1 = pool( 3, 'float64' )\n    <Float64Array>\n\n    See Also\n    --------\n    typedarray\n","typedarraypool.malloc":"\ntypedarraypool.malloc( [dtype] )\n    Returns an uninitialized typed array from a typed array memory pool.\n\n    This method shares the same security vulnerabilities mentioned above.\n\n    Parameters\n    ----------\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr = typedarraypool.malloc()\n    <Float64Array>\n    > arr = typedarraypool.malloc( 'float32' )\n    <Float32Array>typedarraypool.malloc( length[, dtype] )\n    Returns a typed array having a specified length from a typed array memory\n    pool.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr = typedarraypool.malloc( 5 )\n    <Float64Array>\n    > arr = typedarraypool.malloc( 5, 'int32' )\n    <Int32Array>typedarraypool.malloc( typedarray[, dtype] )\n    Creates a pooled typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr1 = typedarraypool.malloc( [ 0.5, 0.5, 0.5 ] );\n    > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]typedarraypool.malloc( obj[, dtype] )\n    Creates a pooled typed array from an array-like object.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object from which to generate a typed array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr1 = [ 0.5, 0.5, 0.5 ];\n    > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]","typedarraypool.calloc":"\ntypedarraypool.calloc( [dtype] )\n    Returns a zero-initialized typed array from a typed array memory pool.\n\n    Parameters\n    ----------\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr = typedarraypool.calloc()\n    <Float64Array>[]\n    > arr = typedarraypool.calloc( 'float32' )\n    <Float32Array>[]typedarraypool.calloc( length[, dtype] )\n    Returns a zero-initialized typed array having a specified length from a\n    typed array memory pool.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr = typedarraypool.calloc( 5 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n    > arr = typedarraypool.calloc( 5, 'int32' )\n    <Int32Array>[ 0, 0, 0, 0, 0 ]","typedarraypool.free":"\ntypedarraypool.free( buf )\n    Frees a typed array or typed array buffer for use in a future allocation.\n\n    Parameters\n    ----------\n    buf: TypedArray|ArrayBuffer\n        Typed array or typed array buffer to free.\n\n    Examples\n    --------\n    > var arr = typedarraypool( 5 )\n    <Float64Array>\n    > typedarraypool.free( arr );","typedarraypool.clear":"\ntypedarraypool.clear()\n    Clears the typed array pool allowing garbage collection of previously\n    allocated (and currently free) array buffers.\n\n    Examples\n    --------\n    > var arr = typedarraypool( 5 )\n    <Float64Array>\n    > typedarraypool.free( arr );\n    > typedarraypool.clear();","typedarraypool.highWaterMark":"\ntypedarraypool.highWaterMark\n    Read-only property returning the pool's high water mark.\n\n    Once a high water mark is reached, typed array allocation fails.\n\n    Examples\n    --------\n    > typedarraypool.highWaterMark\n    <number>","typedarraypool.nbytes":"\ntypedarraypool.nbytes\n    Read-only property returning the total number of allocated bytes.\n\n    The returned value is the total accumulated value. Hence, anytime a pool\n    must allocate a new array buffer (i.e., more memory), the pool increments\n    this value.\n\n    The only time this value is decremented is when a pool is cleared.\n\n    This behavior means that, while allocated buffers which are never freed may,\n    in fact, be garbage collected, they continue to count against the high water\n    mark limit.\n\n    Accordingly, you should *always* free allocated buffers in order to prevent\n    the pool from believing that non-freed buffers are continually in use.\n\n    Examples\n    --------\n    > var arr = typedarraypool( 5 )\n    <Float64Array>\n    > typedarraypool.nbytes\n    <number>","typedarraypool.factory":"\ntypedarraypool.factory( [options] )\n    Creates a typed array pool.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.highWaterMark: integer (optional)\n        Maximum total memory (in bytes) which can be allocated.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating typed arrays from a typed array memory pool.\n\n    Examples\n    --------\n    > var pool = typedarraypool.factory();\n    > var arr1 = pool( 3, 'float64' )\n    <Float64Array>\n\n    See Also\n    --------\n    typedarray","typemax":"\ntypemax( dtype )\n    Returns the maximum value of a specified numeric type.\n\n    The following numeric types are supported:\n\n    - float64: double-precision floating-point numbers.\n    - float32: single-precision floating-point numbers.\n    - float16: half-precision floating-point numbers.\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n\n    Parameters\n    ----------\n    dtype: string\n        Numeric type.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    > var m = typemax( 'int8' )\n    127\n    > m = typemax( 'uint32' )\n    4294967295\n\n    See Also\n    --------\n    realmax, typemin\n","typemin":"\ntypemin( dtype )\n    Returns the minimum value of a specified numeric type.\n\n    The following numeric types are supported:\n\n    - float64: double-precision floating-point numbers.\n    - float32: single-precision floating-point numbers.\n    - float16: half-precision floating-point numbers.\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n\n    Parameters\n    ----------\n    dtype: string\n        Numeric type.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    > var m = typemin( 'int8' )\n    -128\n    > m = typemin( 'uint32' )\n    0\n\n    See Also\n    --------\n    realmin, typemax\n","typeOf":"\ntypeOf( value )\n    Determines a value's type.\n\n    The following values are not natively provided in older JavaScript engines:\n\n    - Map\n    - Set\n    - WeakMap\n    - WeakSet\n    - Symbol\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    out: string\n        The value's type.\n\n    Examples\n    --------\n    // Built-ins:\n    > var t = typeOf( 'a' )\n    'string'\n    > t = typeOf( 5 )\n    'number'\n    > t = typeOf( NaN )\n    'number'\n    > t = typeOf( true )\n    'boolean'\n    > t = typeOf( false )\n    'boolean'\n    > t = typeOf( null )\n    'null'\n    > t = typeOf( undefined )\n    'undefined'\n    > t = typeOf( [] )\n    'array'\n    > t = typeOf( {} )\n    'object'\n    > t = typeOf( function noop() {} )\n    'function'\n    > t = typeOf( Symbol( 'beep' ) )\n    'symbol'\n    > t = typeOf( /.+/ )\n    'regexp'\n    > t = typeOf( new String( 'beep' ) )\n    'string'\n    > t = typeOf( new Number( 5 ) )\n    'number'\n    > t = typeOf( new Boolean( false ) )\n    'boolean'\n    > t = typeOf( new Array() )\n    'array'\n    > t = typeOf( new Object() )\n    'object'\n    > t = typeOf( new Int8Array( 10 ) )\n    'int8array'\n    > t = typeOf( new Uint8Array( 10 ) )\n    'uint8array'\n    > t = typeOf( new Uint8ClampedArray( 10 ) )\n    'uint8clampedarray'\n    > t = typeOf( new Int16Array( 10 ) )\n    'int16array'\n    > t = typeOf( new Uint16Array( 10 ) )\n    'uint16array'\n    > t = typeOf( new Int32Array( 10 ) )\n    'int32array'\n    > t = typeOf( new Uint32Array( 10 ) )\n    'uint32array'\n    > t = typeOf( new Float32Array( 10 ) )\n    'float32array'\n    > t = typeOf( new Float64Array( 10 ) )\n    'float64array'\n    > t = typeOf( new ArrayBuffer( 10 ) )\n    'arraybuffer'\n    > t = typeOf( new Date() )\n    'date'\n    > t = typeOf( new RegExp( '.+' ) )\n    'regexp'\n    > t = typeOf( new Map() )\n    'map'\n    > t = typeOf( new Set() )\n    'set'\n    > t = typeOf( new WeakMap() )\n    'weakmap'\n    > t = typeOf( new WeakSet() )\n    'weakset'\n    > t = typeOf( new Error( 'beep' ) )\n    'error'\n    > t = typeOf( new TypeError( 'beep' ) )\n    'typeerror'\n    > t = typeOf( new SyntaxError( 'beep' ) )\n    'syntaxerror'\n    > t = typeOf( new ReferenceError( 'beep' ) )\n    'referenceerror'\n    > t = typeOf( new URIError( 'beep' ) )\n    'urierror'\n    > t = typeOf( new RangeError( 'beep' ) )\n    'rangeerror'\n    > t = typeOf( new EvalError( 'beep' ) )\n    'evalerror'\n    > t = typeOf( Math )\n    'math'\n    > t = typeOf( JSON )\n    'json'\n\n    // Arguments object:\n    > function beep() { return arguments; };\n    > t = typeOf( beep() )\n    'arguments'\n\n    // Node.js Buffer object:\n    > t = typeOf( new Buffer( 10 ) )\n    'buffer'\n\n    // Custom constructor:\n    > function Person() { return this };\n    > t = typeOf( new Person() )\n    'person'\n\n    // Anonymous constructor:\n    > var Foo = function () { return this; };\n    > t = typeOf( new Foo() )\n    '' || 'foo'\n\n    See Also\n    --------\n    constructorName, nativeClass\n","UINT8_MAX":"\nUINT8_MAX\n    Maximum unsigned 8-bit integer.\n\n    The maximum unsigned 8-bit integer is given by `2^8 - 1`.\n\n    Examples\n    --------\n    > UINT8_MAX\n    255\n\n    See Also\n    --------\n    INT8_MAX\n","UINT8_NUM_BYTES":"\nUINT8_NUM_BYTES\n    Size (in bytes) of an 8-bit unsigned integer.\n\n    Examples\n    --------\n    > UINT8_NUM_BYTES\n    1\n\n    See Also\n    --------\n    INT8_NUM_BYTES, UINT16_NUM_BYTES, UINT32_NUM_BYTES\n","Uint8Array":"\nUint8Array()\n    A typed array constructor which returns a typed array representing an array\n    of 8-bit unsigned integers in the platform byte order.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array()\n    <Uint8Array>\n\n\nUint8Array( length )\n    Returns a typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( 5 )\n    <Uint8Array>[ 0, 0, 0, 0, 0 ]\n\n\nUint8Array( typedarray )\n    Creates a typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n    > var arr2 = new Uint8Array( arr1 )\n    <Uint8Array>[ 5, 5, 5 ]\n\n\nUint8Array( obj )\n    Creates a typed array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a typed array.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 5.0, 5.0, 5.0 ];\n    > var arr2 = new Uint8Array( arr1 )\n    <Uint8Array>[ 5, 5, 5 ]\n\n\nUint8Array( buffer[, byteOffset[, length]] )\n    Returns a typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 4 );\n    > var arr = new Uint8Array( buf, 0, 4 )\n    <Uint8Array>[ 0, 0, 0, 0 ]\n\n\nUint8Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Uint8Array.from( [ 1, 2 ], mapFcn )\n    <Uint8Array>[ 2, 4 ]\n\n\nUint8Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Uint8Array.of( 1, 2 )\n    <Uint8Array>[ 1, 2 ]\n\n\nUint8Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Uint8Array.BYTES_PER_ELEMENT\n    1\n\n\nUint8Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Uint8Array.name\n    'Uint8Array'\n\n\nUint8Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>\n\n\nUint8Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( 5 );\n    > arr.byteLength\n    5\n\n\nUint8Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( 5 );\n    > arr.byteOffset\n    0\n\n\nUint8Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    1\n\n\nUint8Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( 5 );\n    > arr.length\n    5\n\n\nUint8Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Uint8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2\n\n\nUint8Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true\n\n\nUint8Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false\n\n\nUint8Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Uint8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3\n\n\nUint8Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2\n\n\nUint8Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3\n\n\nUint8Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2\n\n\nUint8Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '\n\n\nUint8Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true\n\n\nUint8Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2\n\n\nUint8Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'\n\n\nUint8Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true\n\n\nUint8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3\n\n\nUint8Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Uint8Array>[ 2, 4, 6 ]\n\n\nUint8Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14\n\n\nUint8Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14\n\n\nUint8Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Uint8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] )\n    <Uint8Array>\n    > arr.reverse()\n    <Uint8Array>[ 3, 2, 1 ]\n\n\nUint8Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4\n\n\nUint8Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3\n\n\nUint8Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true\n\n\nUint8Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Uint8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Uint8Array>[ 0, 1, 1, 2, 2 ]\n\n\nUint8Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint8Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Uint8Array>[ 3, 4, 5 ]\n\n\nUint8Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'\n\n\nUint8Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'\n\n\nUint8Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8ClampedArray\n","Uint8Array.from":"\nUint8Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Uint8Array.from( [ 1, 2 ], mapFcn )\n    <Uint8Array>[ 2, 4 ]","Uint8Array.of":"\nUint8Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Uint8Array.of( 1, 2 )\n    <Uint8Array>[ 1, 2 ]","Uint8Array.BYTES_PER_ELEMENT":"\nUint8Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Uint8Array.BYTES_PER_ELEMENT\n    1","Uint8Array.name":"\nUint8Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Uint8Array.name\n    'Uint8Array'","Uint8Array.prototype.buffer":"\nUint8Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>","Uint8Array.prototype.byteLength":"\nUint8Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( 5 );\n    > arr.byteLength\n    5","Uint8Array.prototype.byteOffset":"\nUint8Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( 5 );\n    > arr.byteOffset\n    0","Uint8Array.prototype.BYTES_PER_ELEMENT":"\nUint8Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    1","Uint8Array.prototype.length":"\nUint8Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( 5 );\n    > arr.length\n    5","Uint8Array.prototype.copyWithin":"\nUint8Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Uint8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2","Uint8Array.prototype.entries":"\nUint8Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true","Uint8Array.prototype.every":"\nUint8Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false","Uint8Array.prototype.fill":"\nUint8Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Uint8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3","Uint8Array.prototype.filter":"\nUint8Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2","Uint8Array.prototype.find":"\nUint8Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3","Uint8Array.prototype.findIndex":"\nUint8Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2","Uint8Array.prototype.forEach":"\nUint8Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '","Uint8Array.prototype.includes":"\nUint8Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true","Uint8Array.prototype.indexOf":"\nUint8Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2","Uint8Array.prototype.join":"\nUint8Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'","Uint8Array.prototype.keys":"\nUint8Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true","Uint8Array.prototype.lastIndexOf":"\nUint8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3","Uint8Array.prototype.map":"\nUint8Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Uint8Array>[ 2, 4, 6 ]","Uint8Array.prototype.reduce":"\nUint8Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14","Uint8Array.prototype.reduceRight":"\nUint8Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14","Uint8Array.prototype.reverse":"\nUint8Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Uint8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] )\n    <Uint8Array>\n    > arr.reverse()\n    <Uint8Array>[ 3, 2, 1 ]","Uint8Array.prototype.set":"\nUint8Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4","Uint8Array.prototype.slice":"\nUint8Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3","Uint8Array.prototype.some":"\nUint8Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true","Uint8Array.prototype.sort":"\nUint8Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Uint8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Uint8Array>[ 0, 1, 1, 2, 2 ]","Uint8Array.prototype.subarray":"\nUint8Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint8Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Uint8Array>[ 3, 4, 5 ]","Uint8Array.prototype.toLocaleString":"\nUint8Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'","Uint8Array.prototype.toString":"\nUint8Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'","Uint8Array.prototype.values":"\nUint8Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8ClampedArray","Uint8ClampedArray":"\nUint8ClampedArray()\n    A typed array constructor which returns a typed array representing an array\n    of 8-bit unsigned integers in the platform byte order clamped to 0-255.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray()\n    <Uint8ClampedArray>\n\n\nUint8ClampedArray( length )\n    Returns a typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( 5 )\n    <Uint8ClampedArray>[ 0, 0, 0, 0, 0 ]\n\n\nUint8ClampedArray( typedarray )\n    Creates a typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n    > var arr2 = new Uint8ClampedArray( arr1 )\n    <Uint8ClampedArray>[ 5, 5, 5 ]\n\n\nUint8ClampedArray( obj )\n    Creates a typed array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a typed array.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 5.0, 5.0, 5.0 ];\n    > var arr2 = new Uint8ClampedArray( arr1 )\n    <Uint8ClampedArray>[ 5, 5, 5 ]\n\n\nUint8ClampedArray( buffer[, byteOffset[, length]] )\n    Returns a typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 4 );\n    > var arr = new Uint8ClampedArray( buf, 0, 4 )\n    <Uint8ClampedArray>[ 0, 0, 0, 0 ]\n\n\nUint8ClampedArray.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Uint8ClampedArray.from( [ 1, 2 ], mapFcn )\n    <Uint8ClampedArray>[ 2, 4 ]\n\n\nUint8ClampedArray.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Uint8ClampedArray.of( 1, 2 )\n    <Uint8ClampedArray>[ 1, 2 ]\n\n\nUint8ClampedArray.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Uint8ClampedArray.BYTES_PER_ELEMENT\n    1\n\n\nUint8ClampedArray.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Uint8ClampedArray.name\n    'Uint8ClampedArray'\n\n\nUint8ClampedArray.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( 5 );\n    > arr.buffer\n    <ArrayBuffer>\n\n\nUint8ClampedArray.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( 5 );\n    > arr.byteLength\n    5\n\n\nUint8ClampedArray.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( 5 );\n    > arr.byteOffset\n    0\n\n\nUint8ClampedArray.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( 5 );\n    > arr.BYTES_PER_ELEMENT\n    1\n\n\nUint8ClampedArray.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( 5 );\n    > arr.length\n    5\n\n\nUint8ClampedArray.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2\n\n\nUint8ClampedArray.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true\n\n\nUint8ClampedArray.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false\n\n\nUint8ClampedArray.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3\n\n\nUint8ClampedArray.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2\n\n\nUint8ClampedArray.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3\n\n\nUint8ClampedArray.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2\n\n\nUint8ClampedArray.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '\n\n\nUint8ClampedArray.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true\n\n\nUint8ClampedArray.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2\n\n\nUint8ClampedArray.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'\n\n\nUint8ClampedArray.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true\n\n\nUint8ClampedArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3\n\n\nUint8ClampedArray.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Uint8ClampedArray>[ 2, 4, 6 ]\n\n\nUint8ClampedArray.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14\n\n\nUint8ClampedArray.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14\n\n\nUint8ClampedArray.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] )\n    <Uint8ClampedArray>\n    > arr.reverse()\n    <Uint8ClampedArray>[ 3, 2, 1 ]\n\n\nUint8ClampedArray.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4\n\n\nUint8ClampedArray.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3\n\n\nUint8ClampedArray.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true\n\n\nUint8ClampedArray.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Uint8ClampedArray>[ 0, 1, 1, 2, 2 ]\n\n\nUint8ClampedArray.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Uint8ClampedArray>[ 3, 4, 5 ]\n\n\nUint8ClampedArray.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'\n\n\nUint8ClampedArray.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'\n\n\nUint8ClampedArray.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array\n","Uint8ClampedArray.from":"\nUint8ClampedArray.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Uint8ClampedArray.from( [ 1, 2 ], mapFcn )\n    <Uint8ClampedArray>[ 2, 4 ]","Uint8ClampedArray.of":"\nUint8ClampedArray.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Uint8ClampedArray.of( 1, 2 )\n    <Uint8ClampedArray>[ 1, 2 ]","Uint8ClampedArray.BYTES_PER_ELEMENT":"\nUint8ClampedArray.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Uint8ClampedArray.BYTES_PER_ELEMENT\n    1","Uint8ClampedArray.name":"\nUint8ClampedArray.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Uint8ClampedArray.name\n    'Uint8ClampedArray'","Uint8ClampedArray.prototype.buffer":"\nUint8ClampedArray.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( 5 );\n    > arr.buffer\n    <ArrayBuffer>","Uint8ClampedArray.prototype.byteLength":"\nUint8ClampedArray.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( 5 );\n    > arr.byteLength\n    5","Uint8ClampedArray.prototype.byteOffset":"\nUint8ClampedArray.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( 5 );\n    > arr.byteOffset\n    0","Uint8ClampedArray.prototype.BYTES_PER_ELEMENT":"\nUint8ClampedArray.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( 5 );\n    > arr.BYTES_PER_ELEMENT\n    1","Uint8ClampedArray.prototype.length":"\nUint8ClampedArray.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( 5 );\n    > arr.length\n    5","Uint8ClampedArray.prototype.copyWithin":"\nUint8ClampedArray.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2","Uint8ClampedArray.prototype.entries":"\nUint8ClampedArray.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true","Uint8ClampedArray.prototype.every":"\nUint8ClampedArray.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false","Uint8ClampedArray.prototype.fill":"\nUint8ClampedArray.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3","Uint8ClampedArray.prototype.filter":"\nUint8ClampedArray.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2","Uint8ClampedArray.prototype.find":"\nUint8ClampedArray.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3","Uint8ClampedArray.prototype.findIndex":"\nUint8ClampedArray.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2","Uint8ClampedArray.prototype.forEach":"\nUint8ClampedArray.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '","Uint8ClampedArray.prototype.includes":"\nUint8ClampedArray.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true","Uint8ClampedArray.prototype.indexOf":"\nUint8ClampedArray.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2","Uint8ClampedArray.prototype.join":"\nUint8ClampedArray.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'","Uint8ClampedArray.prototype.keys":"\nUint8ClampedArray.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true","Uint8ClampedArray.prototype.lastIndexOf":"\nUint8ClampedArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3","Uint8ClampedArray.prototype.map":"\nUint8ClampedArray.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Uint8ClampedArray>[ 2, 4, 6 ]","Uint8ClampedArray.prototype.reduce":"\nUint8ClampedArray.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14","Uint8ClampedArray.prototype.reduceRight":"\nUint8ClampedArray.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14","Uint8ClampedArray.prototype.reverse":"\nUint8ClampedArray.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] )\n    <Uint8ClampedArray>\n    > arr.reverse()\n    <Uint8ClampedArray>[ 3, 2, 1 ]","Uint8ClampedArray.prototype.set":"\nUint8ClampedArray.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4","Uint8ClampedArray.prototype.slice":"\nUint8ClampedArray.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3","Uint8ClampedArray.prototype.some":"\nUint8ClampedArray.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true","Uint8ClampedArray.prototype.sort":"\nUint8ClampedArray.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Uint8ClampedArray>[ 0, 1, 1, 2, 2 ]","Uint8ClampedArray.prototype.subarray":"\nUint8ClampedArray.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Uint8ClampedArray>[ 3, 4, 5 ]","Uint8ClampedArray.prototype.toLocaleString":"\nUint8ClampedArray.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'","Uint8ClampedArray.prototype.toString":"\nUint8ClampedArray.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'","Uint8ClampedArray.prototype.values":"\nUint8ClampedArray.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array","UINT16_MAX":"\nUINT16_MAX\n    Maximum unsigned 16-bit integer.\n\n    The maximum unsigned 16-bit integer is given by `2^16 - 1`.\n\n    Examples\n    --------\n    > UINT16_MAX\n    65535\n\n    See Also\n    --------\n    INT16_MAX\n","UINT16_NUM_BYTES":"\nUINT16_NUM_BYTES\n    Size (in bytes) of a 16-bit unsigned integer.\n\n    Examples\n    --------\n    > UINT16_NUM_BYTES\n    2\n\n    See Also\n    --------\n    INT16_NUM_BYTES, UINT32_NUM_BYTES, UINT8_NUM_BYTES\n","Uint16Array":"\nUint16Array()\n    A typed array constructor which returns a typed array representing an array\n    of 16-bit unsigned integers in the platform byte order.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array()\n    <Uint16Array>\n\n\nUint16Array( length )\n    Returns a typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( 5 )\n    <Uint16Array>[ 0, 0, 0, 0, 0 ]\n\n\nUint16Array( typedarray )\n    Creates a typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n    > var arr2 = new Uint16Array( arr1 )\n    <Uint16Array>[ 5, 5, 5 ]\n\n\nUint16Array( obj )\n    Creates a typed array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a typed array.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 5.0, 5.0, 5.0 ];\n    > var arr2 = new Uint16Array( arr1 )\n    <Uint16Array>[ 5, 5, 5 ]\n\n\nUint16Array( buffer[, byteOffset[, length]] )\n    Returns a typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 8 );\n    > var arr = new Uint16Array( buf, 0, 4 )\n    <Uint16Array>[ 0, 0, 0, 0 ]\n\n\nUint16Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Uint16Array.from( [ 1, 2 ], mapFcn )\n    <Uint16Array>[ 2, 4 ]\n\n\nUint16Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Uint16Array.of( 1, 2 )\n    <Uint16Array>[ 1, 2 ]\n\n\nUint16Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Uint16Array.BYTES_PER_ELEMENT\n    2\n\n\nUint16Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Uint16Array.name\n    'Uint16Array'\n\n\nUint16Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>\n\n\nUint16Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( 5 );\n    > arr.byteLength\n    10\n\n\nUint16Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( 5 );\n    > arr.byteOffset\n    0\n\n\nUint16Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    2\n\n\nUint16Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( 5 );\n    > arr.length\n    5\n\n\nUint16Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Uint16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2\n\n\nUint16Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true\n\n\nUint16Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false\n\n\nUint16Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Uint16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3\n\n\nUint16Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2\n\n\nUint16Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3\n\n\nUint16Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2\n\n\nUint16Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '\n\n\nUint16Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true\n\n\nUint16Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2\n\n\nUint16Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'\n\n\nUint16Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true\n\n\nUint16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3\n\n\nUint16Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Uint16Array>[ 2, 4, 6 ]\n\n\nUint16Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14\n\n\nUint16Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14\n\n\nUint16Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Uint16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] )\n    <Uint16Array>\n    > arr.reverse()\n    <Uint16Array>[ 3, 2, 1 ]\n\n\nUint16Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4\n\n\nUint16Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3\n\n\nUint16Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true\n\n\nUint16Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Uint16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Uint16Array>[ 0, 1, 1, 2, 2 ]\n\n\nUint16Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint16Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Uint16Array>[ 3, 4, 5 ]\n\n\nUint16Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'\n\n\nUint16Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'\n\n\nUint16Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Uint16Array.from":"\nUint16Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Uint16Array.from( [ 1, 2 ], mapFcn )\n    <Uint16Array>[ 2, 4 ]","Uint16Array.of":"\nUint16Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Uint16Array.of( 1, 2 )\n    <Uint16Array>[ 1, 2 ]","Uint16Array.BYTES_PER_ELEMENT":"\nUint16Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Uint16Array.BYTES_PER_ELEMENT\n    2","Uint16Array.name":"\nUint16Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Uint16Array.name\n    'Uint16Array'","Uint16Array.prototype.buffer":"\nUint16Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>","Uint16Array.prototype.byteLength":"\nUint16Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( 5 );\n    > arr.byteLength\n    10","Uint16Array.prototype.byteOffset":"\nUint16Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( 5 );\n    > arr.byteOffset\n    0","Uint16Array.prototype.BYTES_PER_ELEMENT":"\nUint16Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    2","Uint16Array.prototype.length":"\nUint16Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( 5 );\n    > arr.length\n    5","Uint16Array.prototype.copyWithin":"\nUint16Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Uint16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2","Uint16Array.prototype.entries":"\nUint16Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true","Uint16Array.prototype.every":"\nUint16Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false","Uint16Array.prototype.fill":"\nUint16Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Uint16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3","Uint16Array.prototype.filter":"\nUint16Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2","Uint16Array.prototype.find":"\nUint16Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3","Uint16Array.prototype.findIndex":"\nUint16Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2","Uint16Array.prototype.forEach":"\nUint16Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '","Uint16Array.prototype.includes":"\nUint16Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true","Uint16Array.prototype.indexOf":"\nUint16Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2","Uint16Array.prototype.join":"\nUint16Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'","Uint16Array.prototype.keys":"\nUint16Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true","Uint16Array.prototype.lastIndexOf":"\nUint16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3","Uint16Array.prototype.map":"\nUint16Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Uint16Array>[ 2, 4, 6 ]","Uint16Array.prototype.reduce":"\nUint16Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14","Uint16Array.prototype.reduceRight":"\nUint16Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14","Uint16Array.prototype.reverse":"\nUint16Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Uint16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] )\n    <Uint16Array>\n    > arr.reverse()\n    <Uint16Array>[ 3, 2, 1 ]","Uint16Array.prototype.set":"\nUint16Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4","Uint16Array.prototype.slice":"\nUint16Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3","Uint16Array.prototype.some":"\nUint16Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true","Uint16Array.prototype.sort":"\nUint16Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Uint16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Uint16Array>[ 0, 1, 1, 2, 2 ]","Uint16Array.prototype.subarray":"\nUint16Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint16Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Uint16Array>[ 3, 4, 5 ]","Uint16Array.prototype.toLocaleString":"\nUint16Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'","Uint16Array.prototype.toString":"\nUint16Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'","Uint16Array.prototype.values":"\nUint16Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint32Array, Uint8Array, Uint8ClampedArray","UINT32_MAX":"\nUINT32_MAX\n    Maximum unsigned 32-bit integer.\n\n    The maximum unsigned 32-bit integer is given by `2^32 - 1`.\n\n    Examples\n    --------\n    > UINT32_MAX\n    4294967295\n\n    See Also\n    --------\n    INT32_MAX\n","UINT32_NUM_BYTES":"\nUINT32_NUM_BYTES\n    Size (in bytes) of a 32-bit unsigned integer.\n\n    Examples\n    --------\n    > UINT32_NUM_BYTES\n    4\n\n    See Also\n    --------\n    INT32_NUM_BYTES, UINT16_NUM_BYTES, UINT8_NUM_BYTES\n","Uint32Array":"\nUint32Array()\n    A typed array constructor which returns a typed array representing an array\n    of 32-bit unsigned integers in the platform byte order.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array()\n    <Uint32Array>\n\n\nUint32Array( length )\n    Returns a typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( 5 )\n    <Uint32Array>[ 0, 0, 0, 0, 0 ]\n\n\nUint32Array( typedarray )\n    Creates a typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n    > var arr2 = new Uint32Array( arr1 )\n    <Uint32Array>[ 5, 5, 5 ]\n\n\nUint32Array( obj )\n    Creates a typed array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a typed array.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 5.0, 5.0, 5.0 ];\n    > var arr2 = new Uint32Array( arr1 )\n    <Uint32Array>[ 5, 5, 5 ]\n\n\nUint32Array( buffer[, byteOffset[, length]] )\n    Returns a typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 16 );\n    > var arr = new Uint32Array( buf, 0, 4 )\n    <Uint32Array>[ 0, 0, 0, 0 ]\n\n\nUint32Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Uint32Array.from( [ 1, 2 ], mapFcn )\n    <Uint32Array>[ 2, 4 ]\n\n\nUint32Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Uint32Array.of( 1, 2 )\n    <Uint32Array>[ 1, 2 ]\n\n\nUint32Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Uint32Array.BYTES_PER_ELEMENT\n    4\n\n\nUint32Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Uint32Array.name\n    'Uint32Array'\n\n\nUint32Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>\n\n\nUint32Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( 5 );\n    > arr.byteLength\n    20\n\n\nUint32Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( 5 );\n    > arr.byteOffset\n    0\n\n\nUint32Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    4\n\n\nUint32Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( 5 );\n    > arr.length\n    5\n\n\nUint32Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Uint32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2\n\n\nUint32Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true\n\n\nUint32Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false\n\n\nUint32Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Uint32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3\n\n\nUint32Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2\n\n\nUint32Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3\n\n\nUint32Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2\n\n\nUint32Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '\n\n\nUint32Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true\n\n\nUint32Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2\n\n\nUint32Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'\n\n\nUint32Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true\n\n\nUint32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3\n\n\nUint32Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Uint32Array>[ 2, 4, 6 ]\n\n\nUint32Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14\n\n\nUint32Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14\n\n\nUint32Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Uint32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] )\n    <Uint32Array>\n    > arr.reverse()\n    <Uint32Array>[ 3, 2, 1 ]\n\n\nUint32Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4\n\n\nUint32Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3\n\n\nUint32Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true\n\n\nUint32Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Uint32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Uint32Array>[ 0, 1, 1, 2, 2 ]\n\n\nUint32Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint32Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Uint32Array>[ 3, 4, 5 ]\n\n\nUint32Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'\n\n\nUint32Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'\n\n\nUint32Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint8Array, Uint8ClampedArray\n","Uint32Array.from":"\nUint32Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Uint32Array.from( [ 1, 2 ], mapFcn )\n    <Uint32Array>[ 2, 4 ]","Uint32Array.of":"\nUint32Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Uint32Array.of( 1, 2 )\n    <Uint32Array>[ 1, 2 ]","Uint32Array.BYTES_PER_ELEMENT":"\nUint32Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Uint32Array.BYTES_PER_ELEMENT\n    4","Uint32Array.name":"\nUint32Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Uint32Array.name\n    'Uint32Array'","Uint32Array.prototype.buffer":"\nUint32Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>","Uint32Array.prototype.byteLength":"\nUint32Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( 5 );\n    > arr.byteLength\n    20","Uint32Array.prototype.byteOffset":"\nUint32Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( 5 );\n    > arr.byteOffset\n    0","Uint32Array.prototype.BYTES_PER_ELEMENT":"\nUint32Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    4","Uint32Array.prototype.length":"\nUint32Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( 5 );\n    > arr.length\n    5","Uint32Array.prototype.copyWithin":"\nUint32Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Uint32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2","Uint32Array.prototype.entries":"\nUint32Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true","Uint32Array.prototype.every":"\nUint32Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false","Uint32Array.prototype.fill":"\nUint32Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Uint32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3","Uint32Array.prototype.filter":"\nUint32Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2","Uint32Array.prototype.find":"\nUint32Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3","Uint32Array.prototype.findIndex":"\nUint32Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2","Uint32Array.prototype.forEach":"\nUint32Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '","Uint32Array.prototype.includes":"\nUint32Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true","Uint32Array.prototype.indexOf":"\nUint32Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2","Uint32Array.prototype.join":"\nUint32Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'","Uint32Array.prototype.keys":"\nUint32Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true","Uint32Array.prototype.lastIndexOf":"\nUint32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3","Uint32Array.prototype.map":"\nUint32Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Uint32Array>[ 2, 4, 6 ]","Uint32Array.prototype.reduce":"\nUint32Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14","Uint32Array.prototype.reduceRight":"\nUint32Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14","Uint32Array.prototype.reverse":"\nUint32Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Uint32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] )\n    <Uint32Array>\n    > arr.reverse()\n    <Uint32Array>[ 3, 2, 1 ]","Uint32Array.prototype.set":"\nUint32Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4","Uint32Array.prototype.slice":"\nUint32Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3","Uint32Array.prototype.some":"\nUint32Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true","Uint32Array.prototype.sort":"\nUint32Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Uint32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Uint32Array>[ 0, 1, 1, 2, 2 ]","Uint32Array.prototype.subarray":"\nUint32Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint32Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Uint32Array>[ 3, 4, 5 ]","Uint32Array.prototype.toLocaleString":"\nUint32Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'","Uint32Array.prototype.toString":"\nUint32Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'","Uint32Array.prototype.values":"\nUint32Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint8Array, Uint8ClampedArray","umask":"\numask( [mask,] [options] )\n    Returns the current process mask, if not provided a mask; otherwise, sets\n    the process mask and returns the previous mask.\n\n    A mask is a set of bits, each of which restricts how its corresponding\n    permission is set for newly created files.\n\n    On POSIX platforms, each file has a set of attributes that control who can\n    read, write, or execute that file. Upon creating a file, file permissions\n    must be set to an initial setting. The process mask restricts those\n    permission settings.\n\n    If the mask contains a bit set to \"1\", the corresponding initial file\n    permission is disabled. If the mask contains a bit set to \"0\", the\n    corresponding permission is left to be determined by the requesting process\n    and the system.\n\n    The process mask is thus a filter that removes permissions as a file is\n    created; i.e., each bit set to a \"1\" removes its corresponding permission.\n\n    In octal representation, a mask is a four digit number, e.g., 0077,\n    comprised as follows:\n\n    - 0: special permissions (setuid, setgid, sticky bit)\n    - 0: (u)ser/owner permissions\n    - 7: (g)roup permissions\n    - 7: (o)thers/non-group permissions\n\n    Octal codes correspond to the following permissions:\n\n    - 0: read, write, execute\n    - 1: read, write\n    - 2: read, execute\n    - 3: read\n    - 4: write, execute\n    - 5: write\n    - 6: execute\n    - 7: no permissions\n\n    If provided fewer than four digits, the mask is left-padded with zeros.\n\n    Note, however, that only the last three digits (i.e., the file permissions\n    digits) of the mask are actually used when the mask is applied.\n\n    Permissions can be represented using the following symbolic form:\n\n        u=rwx,g=rwx,o=rwx\n\n    where\n\n    - u: user permissions\n    - g: group permissions\n    - o: other/non-group permissions\n    - r: read\n    - w: write\n    - x: execute\n\n    When setting permissions using symbolic notation, the function accepts a\n    mask expression of the form:\n\n        [<classes>]<operator><symbols>\n\n    where \"classes\" may be a combination of\n\n    - u: user\n    - g: group\n    - o: other/non-group\n    - a: all\n\n    \"symbols\" may be a combination of\n\n    - r: read\n    - w: write\n    - x: execute\n    - X: special execute\n    - s: setuid/gid on execution\n    - t: sticky\n\n    and \"operator\" may be one of\n\n    - +: enable\n    - -: disable\n    - =: enable specified and disable unspecified permissions\n\n    For example,\n\n    - u-w: disable user write permissions\n    - u+w: enable user write permissions\n    - u=w: enable user write permissions and disable user read and execute\n\n    To specify multiple changes, provide a comma-separated list of mask\n    expressions. For example,\n\n        u+rwx,g-x,o=r\n\n    would enable user read, write, and execute permissions, disable group\n    execute permissions, enable other read permissions, and disable other\n    write and execute permissions.\n\n    The `a` class indicates \"all\", which is the same as specifying \"ugo\". This\n    is the default class if a class is omitted when specifying permissions. For\n    example, `+x` is equivalent to `a+x` which is equivalent to `ugo+x` which\n    is equivalent to `u+x,g+x,o+x` and enables execution for all classes.\n\n    Parameters\n    ----------\n    mask: integer|string (optional)\n        Mask or mask expression. If the mask is a string, the mask is assumed to\n        be in symbolic notation.\n\n    options: Object (optional)\n        Options.\n\n    options.symbolic: boolean (optional)\n        Boolean indicating whether to return the mask using symbolic notation.\n\n    Returns\n    -------\n    mask: integer|string\n        Process mask. If provided a mask, the returned value is the previous\n        mask; otherwise, the returned value is the current process mask.\n\n    Examples\n    --------\n    > var mask = umask()\n    <number>\n    > mask = umask( { 'symbolic': true } )\n    <string>\n\n","uncapitalize":"\nuncapitalize( str )\n    Lowercases the first character of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Uncapitalized string.\n\n    Examples\n    --------\n    > var out = uncapitalize( 'Beep' )\n    'beep'\n    > out = uncapitalize( 'bOOp' )\n    'bOOp'\n\n    See Also\n    --------\n    capitalize, lowercase\n","uncapitalizeKeys":"\nuncapitalizeKeys( obj )\n    Converts the first letter of each object key to lowercase.\n\n    The function only transforms own properties. Hence, the function does not\n    transform inherited properties.\n\n    The function shallow copies key values.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > var obj = { 'AA': 1, 'BB': 2 };\n    > var out = uncapitalizeKeys( obj )\n    { 'aA': 1, 'bB': 2 }\n\n    See Also\n    --------\n    capitalizeKeys, lowercaseKeys\n","uncurry":"\nuncurry( fcn[, arity, ][thisArg] )\n    Transforms a curried function into a function invoked with multiple\n    arguments.\n\n    Parameters\n    ----------\n    fcn: Function\n        Curried function.\n\n    arity: integer (optional)\n        Number of parameters.\n\n    thisArg: any (optional)\n        Evaluation context.\n\n    Returns\n    -------\n    out: Function\n        Uncurried function.\n\n    Examples\n    --------\n    > function addX( x ) {\n    ...     return function addY( y ) {\n    ...         return x + y;\n    ...     };\n    ... };\n    > var fcn = uncurry( addX );\n    > var sum = fcn( 2, 3 )\n    5\n\n    // To enforce a fixed number of parameters, provide an `arity` argument:\n    > function add( x ) {\n    ...     return function add( y ) {\n    ...         return x + y;\n    ...     };\n    ... };\n    > fcn = uncurry( add, 2 );\n    > sum = fcn( 9 )\n    <Error>\n\n    // To specify an execution context, provide a `thisArg` argument:\n    > function addX( x ) {\n    ...     this.x = x;\n    ...     return addY;\n    ... };\n    > function addY( y ) {\n    ...     return this.x + y;\n    ... };\n    > fcn = uncurry( addX, {} );\n    > sum = fcn( 2, 3 )\n    5\n\n    See Also\n    --------\n    curry, uncurryRight\n","uncurryRight":"\nuncurryRight( fcn[, arity, ][thisArg] )\n    Transforms a curried function into a function invoked with multiple\n    arguments.\n\n    Provided arguments are applied starting from the right.\n\n    Parameters\n    ----------\n    fcn: Function\n        Curried function.\n\n    arity: integer (optional)\n        Number of parameters.\n\n    thisArg: any (optional)\n        Evaluation context.\n\n    Returns\n    -------\n    out: Function\n        Uncurried function.\n\n    Examples\n    --------\n    > function addX( x ) {\n    ...     return function addY( y ) {\n    ...         return x + y;\n    ...     };\n    ... };\n    > var fcn = uncurryRight( addX );\n    > var sum = fcn( 3, 2 )\n    5\n\n    // To enforce a fixed number of parameters, provide an `arity` argument:\n    > function add( y ) {\n    ...     return function add( x ) {\n    ...         return x + y;\n    ...     };\n    ... };\n    > fcn = uncurryRight( add, 2 );\n    > sum = fcn( 9 )\n    <Error>\n\n    // To specify an execution context, provide a `thisArg` argument:\n    > function addY( y ) {\n    ...     this.y = y;\n    ...     return addX;\n    ... };\n    > function addX( x ) {\n    ...     return x + this.y;\n    ... };\n    > fcn = uncurryRight( addY, {} );\n    > sum = fcn( 3, 2 )\n    5\n\n    See Also\n    --------\n    curry, curryRight, uncurry\n","UNICODE_MAX":"\nUNICODE_MAX\n    Maximum Unicode code point.\n\n    Examples\n    --------\n    > UNICODE_MAX\n    1114111\n\n    See Also\n    --------\n    UNICODE_MAX_BMP\n","UNICODE_MAX_BMP":"\nUNICODE_MAX_BMP\n    Maximum Unicode code point in the Basic Multilingual Plane (BMP).\n\n    Examples\n    --------\n    > UNICODE_MAX_BMP\n    65535\n\n    See Also\n    --------\n    UNICODE_MAX\n","UnicodeColumnChartSparkline":"\nUnicodeColumnChartSparkline( [data,] [options] )\n    Returns a sparkline column chart instance.\n\n    The `data` argument takes precedence over the `data` option.\n\n    Parameters\n    ----------\n    data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options: Object (optional)\n        Options.\n\n    options.autoRender: boolean (optional)\n        Boolean indicating whether to re-render on a 'change' event. Default:\n        false.\n\n    options.bufferSize: integer|null (optional)\n        Data buffer size. If provided, data is kept in a first-in first-out\n        (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n    options.data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options.description: string (optional)\n        Chart description.\n\n    options.infinities: boolean (optional)\n        Boolean indicating whether to encode infinite values. Default: false.\n\n    options.isDefined: Function (optional)\n        An accessor function indicating whether a datum is defined.\n\n    options.label: string (optional)\n        Data label.\n\n    options.yMax: number|null (optional)\n        Maximum value of the y-axis domain. If `null`, the value is computed\n        from the data. Default: null.\n\n    options.yMin: number|null (optional)\n        Minimum value of the y-axis domain. If `null`, the value is computed\n        from the data. Default: null.\n\n    Returns\n    -------\n    chart: ColumnChart\n        Column chart instance.\n\n    chart.autoRender\n        Rendering mode. If `true`, an instance renders on each 'change' event;\n        otherwise, rendering must be triggered manually.\n\n    chart.bufferSize\n        Data buffer size.\n\n    chart.description\n        Chart description.\n\n    chart.data\n        Chart data.\n\n    chart.label\n        Data label.\n\n    chart.infinities\n        Indicates whether to encode infinite values.\n\n    chart.isDefined( d, i )\n        An accessor function which defines whether a datum is defined. This\n        accessor is used to define how missing values are encoded. The default\n        behavior is to ignore values which are `NaN`.\n\n    chart.render()\n        Renders a column chart sparkline.\n\n    chart.yMax\n        Maximum value of the y-axis domain. If set to `null`, when accessed, the\n        returned value is computed from the data.\n\n    chart.yMin\n        Minimum value of the y-axis domain. If set to `null`, when accessed, the\n        returned value is computed from the data.\n\n    Examples\n    --------\n    > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n    > var chart = new UnicodeColumnChartSparkline( data );\n    > chart.render()\n    '▁█▅▃▆▆▅'\n\n    See Also\n    --------\n    plot, Plot, UnicodeSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeLineChartSparkline":"\nUnicodeLineChartSparkline( [data,] [options] )\n    Returns a sparkline line chart instance.\n\n    The `data` argument takes precedence over the `data` option.\n\n    Parameters\n    ----------\n    data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options: Object (optional)\n        Options.\n\n    options.autoRender: boolean (optional)\n        Boolean indicating whether to re-render on a 'change' event. Default:\n        false.\n\n    options.bufferSize: integer|null (optional)\n        Data buffer size. If provided, data is kept in a first-in first-out\n        (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n    options.data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options.description: string (optional)\n        Chart description.\n\n    options.infinities: boolean (optional)\n        Boolean indicating whether to encode infinite values. Default: false.\n\n    options.isDefined: Function (optional)\n        An accessor function indicating whether a datum is defined.\n\n    options.label: string (optional)\n        Data label.\n\n    options.yMax: number|null (optional)\n        Maximum value of the y-axis domain. If `null`, the value is computed\n        from the data. Default: null.\n\n    options.yMin: number|null (optional)\n        Minimum value of the y-axis domain. If `null`, the value is computed\n        from the data. Default: null.\n\n    Returns\n    -------\n    chart: LineChart\n        Line chart instance.\n\n    chart.autoRender\n        Rendering mode. If `true`, an instance renders on each 'change' event;\n        otherwise, rendering must be triggered manually.\n\n    chart.bufferSize\n        Data buffer size.\n\n    chart.description\n        Chart description.\n\n    chart.data\n        Chart data.\n\n    chart.label\n        Data label.\n\n    chart.infinities\n        Indicates whether to encode infinite values.\n\n    chart.isDefined( d, i )\n        An accessor function which defines whether a datum is defined. This\n        accessor is used to define how missing values are encoded. The default\n        behavior is to ignore values which are `NaN`.\n\n    chart.render()\n        Renders a line chart sparkline.\n\n    chart.yMax\n        Maximum value of the y-axis domain. If set to `null`, when accessed, the\n        returned value is computed from the data.\n\n    chart.yMin\n        Minimum value of the y-axis domain. If set to `null`, when accessed, the\n        returned value is computed from the data.\n\n    Examples\n    --------\n    > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n    > var chart = new UnicodeLineChartSparkline( data );\n    > chart.render()\n    '⡈⠑⠢⠔⠒⠒⠒'\n\n    See Also\n    --------\n    plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeSparkline":"\nUnicodeSparkline( [data,] [options] )\n    Returns a Unicode sparkline instance.\n\n    The following chart types are supported:\n\n    - column: column chart (e.g., ▃▆▂▄▁▅▅).\n    - line: line chart (e.g., ⡈⠑⠢⠔⠒⠒⠒).\n    - tristate: tristate chart (e.g., ▄▀──▀▄▄▀).\n    - up-down: up/down chart (e.g., ↓↑↑↑↑↓↓↑).\n    - win-loss: win/loss chart (e.g., ┌╵└┴╵╷╷╵).\n\n    The `data` argument takes precedence over the `data` option.\n\n    Parameters\n    ----------\n    data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options: Object (optional)\n        Options.\n\n    options.autoRender: boolean (optional)\n        Boolean indicating whether to re-render on a 'change' event. Default:\n        false.\n\n    options.bufferSize: integer|null (optional)\n        Data buffer size. If provided, data is kept in a first-in first-out\n        (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n    options.data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options.description: string (optional)\n        Chart description.\n\n    options.infinities: boolean (optional)\n        Boolean indicating whether to encode infinite values. Default: false.\n\n    options.isDefined: Function (optional)\n        An accessor function indicating whether a datum is defined.\n\n    options.label: string (optional)\n        Data label.\n\n    options.type: string (optional)\n        Chart type. Default: 'column'.\n\n    options.yMax: number|null (optional)\n        Maximum value of the y-axis domain. If `null`, the value is computed\n        from the data. Default: null.\n\n    options.yMin: number|null (optional)\n        Minimum value of the y-axis domain. If `null`, the value is computed\n        from the data. Default: null.\n\n    Returns\n    -------\n    chart: ColumnChart\n        Column chart instance.\n\n    chart.autoRender\n        Rendering mode. If `true`, an instance renders on each 'change' event;\n        otherwise, rendering must be triggered manually.\n\n    chart.bufferSize\n        Data buffer size.\n\n    chart.description\n        Chart description.\n\n    chart.data\n        Chart data.\n\n    chart.label\n        Data label.\n\n    chart.infinities\n        Indicates whether to encode infinite values.\n\n    chart.isDefined( d, i )\n        An accessor function which defines whether a datum is defined. This\n        accessor is used to define how missing values are encoded. The default\n        behavior is to ignore values which are `NaN`.\n\n    chart.render()\n        Renders a column chart sparkline.\n\n    chart.type\n        Chart type.\n\n    chart.yMax\n        Maximum value of the y-axis domain. If set to `null`, when accessed, the\n        returned value is computed from the data.\n\n    chart.yMin\n        Minimum value of the y-axis domain. If set to `null`, when accessed, the\n        returned value is computed from the data.\n\n    Examples\n    --------\n    > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n    > var chart = new UnicodeSparkline( data );\n    > chart.render()\n    '▁█▅▃▆▆▅'\n    > chart.type = 'line';\n    > chart.render()\n    '⡈⠑⠢⠔⠒⠒⠒'\n\n    See Also\n    --------\n    plot, Plot, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeTristateChartSparkline":"\nUnicodeTristateChartSparkline( [data,] [options] )\n    Returns a sparkline tristate chart instance.\n\n    In a tristate chart, negative values are encoded as lower blocks, positive\n    values are encoded as upper blocks, and values equal to zero are encoded as\n    middle lines.\n\n    The `data` argument takes precedence over the `data` option.\n\n    Parameters\n    ----------\n    data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options: Object (optional)\n        Options.\n\n    options.autoRender: boolean (optional)\n        Boolean indicating whether to re-render on a 'change' event. Default:\n        false.\n\n    options.bufferSize: integer|null (optional)\n        Data buffer size. If provided, data is kept in a first-in first-out\n        (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n    options.data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options.description: string (optional)\n        Chart description.\n\n    options.isDefined: Function (optional)\n        An accessor function indicating whether a datum is defined.\n\n    options.label: string (optional)\n        Data label.\n\n    Returns\n    -------\n    chart: TristateChart\n        Tristate chart instance.\n\n    chart.autoRender\n        Rendering mode. If `true`, an instance renders on each 'change' event;\n        otherwise, rendering must be triggered manually.\n\n    chart.bufferSize\n        Data buffer size.\n\n    chart.description\n        Chart description.\n\n    chart.data\n        Chart data.\n\n    chart.label\n        Data label.\n\n    chart.isDefined( d, i )\n        An accessor function which defines whether a datum is defined. This\n        accessor is used to define how missing values are encoded. The default\n        behavior is to ignore values which are `NaN`.\n\n    chart.render()\n        Renders a tristate chart sparkline.\n\n    Examples\n    --------\n    > var data = [ -1, 1, 0, 0, 1, -1, -1, 1 ];\n    > var chart = new UnicodeTristateChartSparkline( data );\n    > chart.render()\n    '▄▀──▀▄▄▀'\n\n    See Also\n    --------\n    plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeUpDownChartSparkline":"\nUnicodeUpDownChartSparkline( [data,] [options] )\n    Returns a sparkline up/down chart instance.\n\n    Glyphs:\n\n    | Value | Glyph |\n    |:-----:|:-----:|\n    |   1   |   ↑   |\n    |   -1  |   ↓   |\n\n    If provided any other value other than 1 or -1, the value is encoded as a\n    missing value.\n\n    The `data` argument takes precedence over the `data` option.\n\n    Parameters\n    ----------\n    data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options: Object (optional)\n        Options.\n\n    options.autoRender: boolean (optional)\n        Boolean indicating whether to re-render on a 'change' event. Default:\n        false.\n\n    options.bufferSize: integer|null (optional)\n        Data buffer size. If provided, data is kept in a first-in first-out\n        (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n    options.data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options.description: string (optional)\n        Chart description.\n\n    options.isDefined: Function (optional)\n        An accessor function indicating whether a datum is defined.\n\n    options.label: string (optional)\n        Data label.\n\n    Returns\n    -------\n    chart: UpDownChart\n        Chart instance.\n\n    chart.autoRender\n        Rendering mode. If `true`, an instance renders on each 'change' event;\n        otherwise, rendering must be triggered manually.\n\n    chart.bufferSize\n        Data buffer size.\n\n    chart.description\n        Chart description.\n\n    chart.data\n        Chart data.\n\n    chart.label\n        Data label.\n\n    chart.isDefined( d, i )\n        An accessor function which defines whether a datum is defined. This\n        accessor is used to define how missing values are encoded. The default\n        behavior is to ignore any values which are not 1 or -1.\n\n    chart.render()\n        Renders an up/down chart sparkline.\n\n    Examples\n    --------\n    > var data = [ -1, 1, 1, 1, 1, -1, -1, 1 ];\n    > var chart = new UnicodeUpDownChartSparkline( data );\n    > chart.render()\n    '↓↑↑↑↑↓↓↑'\n\n    See Also\n    --------\n    plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeWinLossChartSparkline":"\nUnicodeWinLossChartSparkline( [data,] [options] )\n    Returns a sparkline win/loss chart instance.\n\n    Glyphs:\n\n    | Value | Glyph |\n    |:-----:|:-----:|\n    |   1   |   ╵   |\n    |   -1  |   ╷   |\n    |   2   |   └   |\n    |   -2  |   ┌   |\n\n    If a `2` or `-2` is preceded by a `2` or `-2`,\n\n    | Value | Glyph |\n    |:-----:|:-----:|\n    |   2   |   ┴   |\n    |   -2  |   ┬   |\n\n    Based on the win/loss analogy,\n\n    - 1: win away\n    - 2: win at home\n    - -1: loss away\n    - -2: loss at home\n\n    If provided any value other than 1, -1, 2, or -2, the value is encoded as a\n    missing value.\n\n    The `data` argument takes precedence over the `data` option.\n\n    Parameters\n    ----------\n    data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options: Object (optional)\n        Options.\n\n    options.autoRender: boolean (optional)\n        Boolean indicating whether to re-render on a 'change' event. Default:\n        false.\n\n    options.bufferSize: integer|null (optional)\n        Data buffer size. If provided, data is kept in a first-in first-out\n        (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n    options.data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options.description: string (optional)\n        Chart description.\n\n    options.isDefined: Function (optional)\n        An accessor function indicating whether a datum is defined.\n\n    options.label: string (optional)\n        Data label.\n\n    Returns\n    -------\n    chart: WinLossChart\n        Chart instance.\n\n    chart.autoRender\n        Rendering mode. If `true`, an instance renders on each 'change' event;\n        otherwise, rendering must be triggered manually.\n\n    chart.bufferSize\n        Data buffer size.\n\n    chart.description\n        Chart description.\n\n    chart.data\n        Chart data.\n\n    chart.label\n        Data label.\n\n    chart.isDefined( d, i )\n        An accessor function which defines whether a datum is defined. This\n        accessor is used to define how missing values are encoded. The default\n        behavior is to ignore any values which are not 1, -1, 2, or -2.\n\n    chart.render()\n        Renders a win/loss chart sparkline.\n\n    Examples\n    --------\n    > var data = [ -2, 1, 2, 2, 1, -1, -1, 1 ];\n    > var chart = new UnicodeWinLossChartSparkline( data );\n    > chart.render()\n    '┌╵└┴╵╷╷╵'\n\n    See Also\n    --------\n    plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline\n","unlink":"\nunlink( path, clbk )\n    Asynchronously removes a directory entry.\n\n    If a provided path is a symbolic link, the function removes the symbolic\n    link named by the path and does not affect any file or directory named by\n    the contents of the symbolic link.\n\n    Otherwise, the function removes the link named by the provided path and\n    decrements the link count of the file referenced by the link.\n\n    When a file's link count becomes 0 and no process has the file open, the\n    space occupied by the file is freed and the file is no longer accessible.\n\n    If one or more processes have the file open when the last link is removed,\n    the link is removed before the function returns; however, the removal of\n    file contents is postponed until all references to the file are closed.\n\n    If the path refers to a socket, FIFO, or device, processes which have the\n    object open may continue to use it.\n\n    The path argument should *not* be a directory. To remove a directory, use\n    rmdir().\n\n    Parameters\n    ----------\n    path: string|Buffer|integer\n        Entry path.\n\n    clbk: Function\n        Callback to invoke upon removing an entry.\n\n    Examples\n    --------\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     }\n    ... };\n    > unlink( './beep/boop.txt', done );\n\n\nunlink.sync( path )\n    Synchronously removes a directory entry.\n\n   Parameters\n    ----------\n    path: string|Buffer|integer\n        Entry path.\n\n    Returns\n    -------\n    out: Error|null\n        Error object or null.\n\n    Examples\n    --------\n    > var out = unlink.sync( './beep/boop.txt' );\n\n    See Also\n    --------\n    exists\n","unlink.sync":"\nunlink.sync( path )\n    Synchronously removes a directory entry.\n\n   Parameters\n    ----------\n    path: string|Buffer|integer\n        Entry path.\n\n    Returns\n    -------\n    out: Error|null\n        Error object or null.\n\n    Examples\n    --------\n    > var out = unlink.sync( './beep/boop.txt' );\n\n    See Also\n    --------\n    exists","unshift":"\nunshift( collection, ...items )\n    Adds one or more elements to the beginning of a collection.\n\n    If the input collection is a typed array, the output value does not equal\n    the input reference and the underlying `ArrayBuffer` may *not* be the same\n    as the `ArrayBuffer` belonging to the input view.\n\n    For purposes of generality, always treat the output collection as distinct\n    from the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        A collection. If the collection is an `Object`, the collection should be\n        array-like.\n\n    items: ...any\n        Items to add.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Updated collection.\n\n    Examples\n    --------\n    // Arrays:\n    > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > arr = unshift( arr, 6.0, 7.0 )\n    [ 6.0, 7.0, 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Typed arrays:\n    > arr = new Float64Array( [ 1.0, 2.0 ] );\n    > arr = unshift( arr, 3.0, 4.0 )\n    <Float64Array>[ 3.0, 4.0, 1.0, 2.0 ]\n\n    // Array-like object:\n    > arr = { 'length': 1, '0': 1.0 };\n    > arr = unshift( arr, 2.0, 3.0 )\n    { 'length': 3, '0': 2.0, '1': 3.0, '2': 1.0 }\n\n    See Also\n    --------\n    pop, push, shift\n","until":"\nuntil( predicate, fcn[, thisArg] )\n    Invokes a function until a test condition is true.\n\n    When invoked, both the predicate function and the function to invoke are\n    provided a single argument:\n\n    - i: iteration number (starting from zero).\n\n    Parameters\n    ----------\n    predicate: Function\n        The predicate function which indicates whether to stop invoking a\n        function.\n\n    fcn: Function\n        The function to invoke.\n\n    thisArg: any (optional)\n        Execution context for the invoked function.\n\n    Examples\n    --------\n    > function predicate( i ) { return ( i >= 5 ); };\n    > function beep( i ) { console.log( 'boop: %d', i ); };\n    > until( predicate, beep )\n    boop: 0\n    boop: 1\n    boop: 2\n    boop: 3\n    boop: 4\n\n    See Also\n    --------\n    doUntil, doWhile, untilAsync, untilEach, whilst\n","untilAsync":"\nuntilAsync( predicate, fcn, done[, thisArg] )\n    Invokes a function until a test condition is true.\n\n    The predicate function is provided two arguments:\n\n    - i: iteration number (starting from zero).\n    - clbk: a callback indicating whether to invoke `fcn`.\n\n    The `clbk` function accepts two arguments:\n\n    - error: error argument.\n    - bool: test result.\n\n    If the test result is falsy, the function invokes `fcn`; otherwise, the\n    function invokes the `done` callback.\n\n    The function to invoke is provided two arguments:\n\n    - i: iteration number (starting from zero).\n    - next: a callback which must be invoked before proceeding to the next\n      iteration.\n\n    The first argument of the `next` callback is an `error` argument. If `fcn`\n    calls the `next` callback with a truthy `error` argument, the function\n    suspends execution and immediately calls the `done` callback for subsequent\n    `error` handling.\n\n    The `done` callback is invoked with an `error` argument and any arguments\n    passed to the final `next` callback.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Parameters\n    ----------\n    predicate: Function\n        The predicate function which indicates whether to continue invoking a\n        function.\n\n    fcn: Function\n        The function to invoke.\n\n    done: Function\n        Callback to invoke upon completion.\n\n    thisArg: any (optional)\n        Execution context for the invoked function.\n\n    Examples\n    --------\n    > function predicate( i, clbk ) { clbk( null, i >= 5 ); };\n    > function fcn( i, next ) {\n    ...     setTimeout( onTimeout, i );\n    ...     function onTimeout() {\n    ...         next( null, 'boop'+i );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > untilAsync( predicate, fcn, done )\n    boop: 4\n\n    See Also\n    --------\n    doUntilAsync, doWhileAsync, until, whileAsync\n","untilEach":"\nuntilEach( collection, predicate, fcn[, thisArg] )\n    Until a test condition is true, invokes a function for each element in a\n    collection.\n\n    When invoked, both the predicate function and the function to apply are\n    provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    predicate: Function\n        The predicate function which indicates whether to stop iterating over a\n        collection.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    thisArg: any (optional)\n        Execution context for the applied function.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function predicate( v ) { return v !== v; };\n    > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n    > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n    > untilEach( arr, predicate, logger )\n    0: 1\n    1: 2\n    2: 3\n    3: 4\n\n    See Also\n    --------\n    untilEachRight, whileEach\n","untilEachRight":"\nuntilEachRight( collection, predicate, fcn[, thisArg] )\n    Until a test condition is true, invokes a function for each element in a\n    collection, iterating from right to left.\n\n    When invoked, both the predicate function and the function to apply are\n    provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    predicate: Function\n        The predicate function which indicates whether to stop iterating over a\n        collection.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    thisArg: any (optional)\n        Execution context for the applied function.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function predicate( v ) { return v !== v; };\n    > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n    > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n    > untilEachRight( arr, predicate, logger )\n    5: 5\n    4: 4\n    3: 3\n    2: 2\n\n    See Also\n    --------\n    untilEach, whileEachRight\n","unzip":"\nunzip( arr[, idx] )\n    Unzips a zipped array (i.e., a nested array of tuples).\n\n    Parameters\n    ----------\n    arr: Array\n        Zipped array.\n\n    idx: Array<number> (optional)\n        Array of indices specifying which tuple elements to unzip.\n\n    Returns\n    -------\n    out: Array\n        Array of unzipped arrays.\n\n    Examples\n    --------\n    // Basic usage:\n    > var arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\n    > var out = unzip( arr )\n    [ [ 1, 2 ], [ 'a', 'b' ], [ 3, 4 ] ]\n\n    // Provide indices:\n    > arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\n    > out = unzip( arr, [ 0, 2 ] )\n    [ [ 1, 2 ], [ 3, 4 ] ]\n\n    See Also\n    --------\n    zip\n","uppercase":"\nuppercase( str )\n    Converts a string to uppercase.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Uppercase string.\n\n    Examples\n    --------\n    > var out = uppercase( 'bEEp' )\n    'BEEP'\n\n    See Also\n    --------\n    capitalize, lowercase\n","uppercaseKeys":"\nuppercaseKeys( obj )\n    Converts each object key to uppercase.\n\n    The function only transforms own properties. Hence, the function does not\n    transform inherited properties.\n\n    The function shallow copies key values.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > var obj = { 'a': 1, 'b': 2 };\n    > var out = uppercaseKeys( obj )\n    { 'A': 1, 'B': 2 }\n\n    See Also\n    --------\n    capitalizeKeys, lowercaseKeys\n","US_STATES_ABBR":"\nUS_STATES_ABBR()\n    Returns a list of US state two-letter abbreviations in alphabetical order\n    according to state name.\n\n    Returns\n    -------\n    out: Array<string>\n        List of US state two-letter abbreviations.\n\n    Examples\n    --------\n    > var list = US_STATES_ABBR()\n    [ 'AL', 'AK', 'AZ', 'AR', ... ]\n\n    See Also\n    --------\n    US_STATES_CAPITALS, US_STATES_NAMES\n","US_STATES_CAPITALS":"\nUS_STATES_CAPITALS()\n    Returns a list of US state capitals in alphabetical order according to state\n    name.\n\n    Returns\n    -------\n    out: Array<string>\n        List of US state capitals.\n\n    Examples\n    --------\n    > var list = US_STATES_CAPITALS()\n    [ 'Montgomery', 'Juneau', 'Phoenix', ... ]\n\n    See Also\n    --------\n    US_STATES_ABBR, US_STATES_CAPITALS_NAMES, US_STATES_NAMES, US_STATES_NAMES_CAPITALS\n","US_STATES_CAPITALS_NAMES":"\nUS_STATES_CAPITALS_NAMES()\n    Returns an object mapping US state capitals to state names.\n\n    Returns\n    -------\n    out: Object\n        An object mapping US state capitals to state names.\n\n    Examples\n    --------\n    > var out = US_STATES_CAPITALS_NAMES()\n    { 'Montgomery': 'Alabama', 'Juneau': 'Alaska', ... }\n\n    See Also\n    --------\n    US_STATES_CAPITALS, US_STATES_NAMES, US_STATES_NAMES_CAPITALS\n","US_STATES_NAMES":"\nUS_STATES_NAMES()\n    Returns a list of US state names in alphabetical order.\n\n    Returns\n    -------\n    out: Array<string>\n        List of US state names.\n\n    Examples\n    --------\n    > var list = US_STATES_NAMES()\n    [ 'Alabama', 'Alaska', 'Arizona', ... ]\n\n    See Also\n    --------\n    US_STATES_ABBR, US_STATES_CAPITALS, US_STATES_CAPITALS_NAMES, US_STATES_NAMES_CAPITALS\n","US_STATES_NAMES_CAPITALS":"\nUS_STATES_NAMES_CAPITALS()\n    Returns an object mapping US state names to state capitals.\n\n    Returns\n    -------\n    out: Object\n        An object mapping US state names to state capitals.\n\n    Examples\n    --------\n    > var out = US_STATES_NAMES_CAPITALS()\n    { 'Alabama': 'Montgomery', 'Alaska': 'Juneau', ... }\n\n    See Also\n    --------\n    US_STATES_CAPITALS, US_STATES_NAMES, US_STATES_NAMES_CAPITALS\n","utf16ToUTF8Array":"\nutf16ToUTF8Array( str )\n    Converts a UTF-16 encoded string to an array of integers using UTF-8\n    encoding.\n\n    The following byte sequences are used to represent a character. The sequence\n    depends on the code point:\n\n        0x00000000 - 0x0000007F:\n            0xxxxxxx\n\n        0x00000080 - 0x000007FF:\n            110xxxxx 10xxxxxx\n\n        0x00000800 - 0x0000FFFF:\n            1110xxxx 10xxxxxx 10xxxxxx\n\n        0x00010000 - 0x001FFFFF:\n            11110xxx 10xxxxxx 10xxxxxx 10xxxxxx\n\n    The `x` bit positions correspond to code point bits.\n\n    Only the shortest possible multi-byte sequence which can represent a code\n    point is used.\n\n    Parameters\n    ----------\n    str: string\n        UTF-16 encoded string.\n\n    Returns\n    -------\n    out: Array\n        Array of integers.\n\n    Examples\n    --------\n    > var str = '☃';\n    > var out = utf16ToUTF8Array( str )\n    [ 226, 152, 131 ]\n\n","vartest":"\nvartest( x, y[, options] )\n    Computes a two-sample F-test for equal variances.\n\n    The returned object comes with a `.print()` method which when invoked will\n    print a formatted output of the results of the hypothesis test.\n\n    Parameters\n    ----------\n    x: Array<number>\n        First data array.\n\n    y: Array<number>\n        Second data array.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.alternative: string (optional)\n        Either `two-sided`, `less` or `greater`.\n\n    options.ratio: number (optional)\n        Positive number denoting the ratio of the two population variances under\n        the null hypothesis. Default: `1`.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Used significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.ci: Array<number>\n        1-alpha confidence interval for the ratio of variances.\n\n    out.nullValue: number\n        Assumed ratio of variances under H0.\n\n    out.xvar: number\n        Sample variance of `x`.\n\n    out.yvar: number\n        Sample variance of `y`.\n\n    out.alternative: string\n        Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n    out.dfX: number\n        Numerator degrees of freedom.\n\n    out.dfY: number\n        Denominator degrees of freedom.\n\n    out.method: string\n        Name of test.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    > var x = [ 610, 610, 550, 590, 565, 570 ];\n    > var y = [ 560, 550, 580, 550, 560, 590, 550, 590 ];\n    > var out = vartest( x, y )\n    {\n        rejected: false,\n        pValue: ~0.399,\n        statistic: ~1.976,\n        ci: [ ~0.374, ~13.542 ],\n        // ...\n    }\n\n    // Print table output:\n    > var table = out.print()\n    F test for comparing two variances\n\n    Alternative hypothesis: True ratio in variances is not equal to 1\n\n        pValue: 0.3992\n        statistic: 1.976\n        variance of x: 617.5 (df of x: 5)\n        variance of y: 312.5 (df of y: 7)\n        95% confidence interval: [0.3739,13.5417]\n\n    Test Decision: Fail to reject null in favor of alternative at 5%\n    significance level\n\n    See Also\n    --------\n    bartlettTest\n","waterfall":"\nwaterfall( fcns, clbk[, thisArg] )\n    Executes functions in series, passing the results of one function as\n    arguments to the next function.\n\n    The last argument applied to each waterfall function is a callback. The\n    callback should be invoked upon a series function completion. The first\n    argument is reserved as an error argument (which can be `null`). Any results\n    which should be passed to the next function in the series should be provided\n    beginning with the second argument.\n\n    If any function calls the provided callback with a truthy `error` argument,\n    the waterfall suspends execution and immediately calls the completion\n    callback for subsequent error handling.\n\n    Execution is *not* guaranteed to be asynchronous. To ensure asynchrony, wrap\n    the completion callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Parameters\n    ----------\n    fcns: Array<Function>\n        Array of functions.\n\n    clbk: Function\n        Callback to invoke upon completion.\n\n    thisArg: any (optional)\n        Function context.\n\n    Examples\n    --------\n    > function foo( next ) { next( null, 'beep' ); };\n    > function bar( str, next ) { console.log( str ); next(); };\n    > function done( error ) { if ( error ) { throw error; } };\n    > var fcns = [ foo, bar ];\n    > waterfall( fcns, done );\n\n\nwaterfall.factory( fcns, clbk[, thisArg] )\n    Returns a reusable waterfall function.\n\n    Parameters\n    ----------\n    fcns: Array<Function>\n        Array of functions.\n\n    clbk: Function\n        Callback to invoke upon completion.\n\n    thisArg: any (optional)\n        Function context.\n\n    Returns\n    -------\n    fcn: Function\n        Waterfall function.\n\n    Examples\n    --------\n    > function foo( next ) { next( null, 'beep' ); };\n    > function bar( str, next ) { console.log( str ); next(); };\n    > function done( error ) { if ( error ) { throw error; } };\n    > var fcns = [ foo, bar ];\n    > var waterfall = waterfall.factory( fcns, done );\n    > waterfall();\n    > waterfall();\n    > waterfall();\n\n","waterfall.factory":"\nwaterfall.factory( fcns, clbk[, thisArg] )\n    Returns a reusable waterfall function.\n\n    Parameters\n    ----------\n    fcns: Array<Function>\n        Array of functions.\n\n    clbk: Function\n        Callback to invoke upon completion.\n\n    thisArg: any (optional)\n        Function context.\n\n    Returns\n    -------\n    fcn: Function\n        Waterfall function.\n\n    Examples\n    --------\n    > function foo( next ) { next( null, 'beep' ); };\n    > function bar( str, next ) { console.log( str ); next(); };\n    > function done( error ) { if ( error ) { throw error; } };\n    > var fcns = [ foo, bar ];\n    > var waterfall = waterfall.factory( fcns, done );\n    > waterfall();\n    > waterfall();\n    > waterfall();","WebAssemblyMemory":"\nWebAssemblyMemory( descriptor )\n    WebAssembly memory constructor.\n\n    Parameters\n    ----------\n    descriptor: Object\n        Memory descriptor object.\n\n    descriptor.initial: integer\n        Initial memory size in units of WebAssembly pages (i.e., 64KiB).\n\n    descriptor.maximum: integer (optional)\n        Maximum memory size in units of WebAssembly pages (i.e., 64KiB).\n\n    descriptor.shared: boolean (optional)\n        Boolean indicating whether the memory is shared. Default: false.\n\n    Returns\n    -------\n    out: Memory\n        WebAssembly memory instance.\n\n    Examples\n    --------\n    > var mem = new WebAssemblyMemory( { 'initial': 0 } )\n    <Memory>\n\n\nWebAssemblyMemory.prototype.buffer\n    Read-only property which returns the ArrayBuffer (or SharedArrayBuffer)\n    referenced by the memory instance.\n\n    Examples\n    --------\n    > var mem = new WebAssemblyMemory( { 'initial': 0 } );\n    > mem.buffer\n    <ArrayBuffer>\n\n\nWebAssemblyMemory.prototype.grow( delta )\n    Increases the size of the memory instance by a specified number of\n    WebAssembly pages (i.e., 64KiB).\n\n    Upon increasing the size, the previous ArrayBuffer is detached, thus\n    invalidating any typed arrays which were views over the previous\n    ArrayBuffer.\n\n    Detachment means that the previous ArrayBuffer byte length becomes zero, and\n    it no longer has bytes accessible to JavaScript.\n\n    ArrayBuffer detachment applies even when `delta` is zero.\n\n    Detachment only applies for non-shared memory instances. For a shared memory\n    instance, the initial buffer (which is a SharedArrayBuffer) will not become\n    detached and, instead, its length will not be updated.\n\n    Accesses to the `buffer` property after growing a SharedArrayBuffer will\n    yield a larger SharedArrayBuffer which may access a larger span of memory\n    than the buffer before growing memory.\n\n    Every SharedArrayBuffer accessed via the `buffer` property will always refer\n    to the start of the same memory address range and thus manipulate the same\n    data.\n\n    Parameters\n    ----------\n    delta: integer\n        Number of WebAssembly pages (i.e., 64KiB) by which to grow the\n        underlying memory.\n\n    Returns\n    -------\n    out: integer\n        Size of the previous memory (in units of pages).\n\n    Examples\n    --------\n    > var mem = new WebAssemblyMemory( { 'initial': 0 } );\n    > mem.grow( 1 )\n    <number>\n\n","WebAssemblyMemory.prototype.buffer":"\nWebAssemblyMemory.prototype.buffer\n    Read-only property which returns the ArrayBuffer (or SharedArrayBuffer)\n    referenced by the memory instance.\n\n    Examples\n    --------\n    > var mem = new WebAssemblyMemory( { 'initial': 0 } );\n    > mem.buffer\n    <ArrayBuffer>","WebAssemblyMemory.prototype.grow":"\nWebAssemblyMemory.prototype.grow( delta )\n    Increases the size of the memory instance by a specified number of\n    WebAssembly pages (i.e., 64KiB).\n\n    Upon increasing the size, the previous ArrayBuffer is detached, thus\n    invalidating any typed arrays which were views over the previous\n    ArrayBuffer.\n\n    Detachment means that the previous ArrayBuffer byte length becomes zero, and\n    it no longer has bytes accessible to JavaScript.\n\n    ArrayBuffer detachment applies even when `delta` is zero.\n\n    Detachment only applies for non-shared memory instances. For a shared memory\n    instance, the initial buffer (which is a SharedArrayBuffer) will not become\n    detached and, instead, its length will not be updated.\n\n    Accesses to the `buffer` property after growing a SharedArrayBuffer will\n    yield a larger SharedArrayBuffer which may access a larger span of memory\n    than the buffer before growing memory.\n\n    Every SharedArrayBuffer accessed via the `buffer` property will always refer\n    to the start of the same memory address range and thus manipulate the same\n    data.\n\n    Parameters\n    ----------\n    delta: integer\n        Number of WebAssembly pages (i.e., 64KiB) by which to grow the\n        underlying memory.\n\n    Returns\n    -------\n    out: integer\n        Size of the previous memory (in units of pages).\n\n    Examples\n    --------\n    > var mem = new WebAssemblyMemory( { 'initial': 0 } );\n    > mem.grow( 1 )\n    <number>","whileAsync":"\nwhileAsync( predicate, fcn, done[, thisArg] )\n    Invokes a function while a test condition is true.\n\n    The predicate function is provided two arguments:\n\n    - i: iteration number (starting from zero).\n    - clbk: a callback indicating whether to invoke `fcn`.\n\n    The `clbk` function accepts two arguments:\n\n    - error: error argument.\n    - bool: test result.\n\n    If the test result is truthy, the function invokes `fcn`; otherwise, the\n    function invokes the `done` callback.\n\n    The function to invoke is provided two arguments:\n\n    - i: iteration number (starting from zero).\n    - next: a callback which must be invoked before proceeding to the next\n      iteration.\n\n    The first argument of the `next` callback is an `error` argument. If `fcn`\n    calls the `next` callback with a truthy `error` argument, the function\n    suspends execution and immediately calls the `done` callback for subsequent\n    `error` handling.\n\n    The `done` callback is invoked with an `error` argument and any arguments\n    passed to the final `next` callback.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Parameters\n    ----------\n    predicate: Function\n        The predicate function which indicates whether to continue invoking a\n        function.\n\n    fcn: Function\n        The function to invoke.\n\n    done: Function\n        Callback to invoke upon completion.\n\n    thisArg: any (optional)\n        Execution context for the invoked function.\n\n    Examples\n    --------\n    > function predicate( i, clbk ) { clbk( null, i < 5 ); };\n    > function fcn( i, next ) {\n    ...     setTimeout( onTimeout, i );\n    ...     function onTimeout() {\n    ...         next( null, 'boop'+i );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > whileAsync( predicate, fcn, done )\n    boop: 4\n\n    See Also\n    --------\n    doUntilAsync, doWhileAsync, untilAsync, whilst\n","whileEach":"\nwhileEach( collection, predicate, fcn[, thisArg] )\n    While a test condition is true, invokes a function for each element in a\n    collection.\n\n    When invoked, both the predicate function and the function to apply are\n    provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    predicate: Function\n        The predicate function which indicates whether to continue iterating\n        over a collection.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    thisArg: any (optional)\n        Execution context for the applied function.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === v; };\n    > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n    > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n    > whileEach( arr, predicate, logger )\n    0: 1\n    1: 2\n    2: 3\n    3: 4\n\n    See Also\n    --------\n    untilEach, whileEachRight\n","whileEachRight":"\nwhileEachRight( collection, predicate, fcn[, thisArg] )\n    While a test condition is true, invokes a function for each element in a\n    collection, iterating from right to left.\n\n    When invoked, both the predicate function and the function to apply are\n    provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    predicate: Function\n        The predicate function which indicates whether to continue iterating\n        over a collection.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    thisArg: any (optional)\n        Execution context for the applied function.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === v; };\n    > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n    > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n    > whileEachRight( arr, predicate, logger )\n    5: 5\n    4: 4\n    3: 3\n    2: 2\n\n    See Also\n    --------\n    whileEach, untilEachRight\n","whilst":"\nwhilst( predicate, fcn[, thisArg] )\n    Invokes a function while a test condition is true.\n\n    When invoked, both the predicate function and the function to invoke are\n    provided a single argument:\n\n    - i: iteration number (starting from zero).\n\n    Parameters\n    ----------\n    predicate: Function\n        The predicate function which indicates whether to continue invoking a\n        function.\n\n    fcn: Function\n        The function to invoke.\n\n    thisArg: any (optional)\n        Execution context for the invoked function.\n\n    Examples\n    --------\n    > function predicate( i ) { return ( i < 5 ); };\n    > function beep( i ) { console.log( 'boop: %d', i ); };\n    > whilst( predicate, beep )\n    boop: 0\n    boop: 1\n    boop: 2\n    boop: 3\n    boop: 4\n\n    See Also\n    --------\n    doUntil, doWhile, until, whileAsync, whileEach\n","wilcoxon":"\nwilcoxon( x[, y][, options] )\n    Computes a one-sample or paired Wilcoxon signed rank test.\n\n    When no `y` is supplied, the function performs a one-sample  Wilcoxon signed\n    rank test for the null hypothesis that the data is drawn from a symmetric\n    distribution around zero.\n\n    When `y` is supplied, the function tests whether the\n    differences `x - y` come from a symmetric distribution around zero.\n\n    If `x` has less than fifty elements, an exact p-value is computed if there\n    are no zero values or ties. Otherwise, a normal approximation is used.\n\n    The returned object comes with a `.print()` method which when invoked will\n    print a formatted output of the results of the hypothesis test.\n\n    Parameters\n    ----------\n    x: Array<number>|TypedArray\n        Data array.\n\n    y: Array<number>|TypedArray (optional)\n        Paired data array.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.alternative: string (optional)\n        Indicates whether the alternative hypothesis is that the mean of `x` is\n        larger than `mu` (`greater`), smaller than `mu` (`less`), or equal to\n        `mu` (`two-sided`). Default: `'two-sided'`.\n\n    options.correction: boolean (optional)\n        Determines whether to apply continuity correction adjusting the Wilcoxon\n        rank statistic by 0.5 towards the mean when using the normal\n        approximation. Default: `true`.\n\n    options.exact: boolean (optional)\n        Determines whether to force use of the exact distribution instead of a\n        normal approximation when there are more than fifty data points.\n        Default: `false`.\n\n    options.mu: number (optional)\n        Hypothesized true location under the null hypothesis. Set this option to\n        test whether the data comes from a distribution with the specified `mu`.\n        Default: `0`.\n\n    options.zeroMethod: string (optional)\n        Method governing how zero-differences are handled (`pratt`, `wilcox`, or\n        `zsplit`). When set to `pratt`, differences of zero are used to\n        calculate ranks but their ranks are then dropped. When set to `wilcox`,\n        all zero-differences are discarded. When set to `zsplit`, differences of\n        zero are used to rank and their ranks are then split between positive\n        and negative ones. Default: `'wilcox'`.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Used significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.nullValue: number\n        Assumed location parameter under H0.\n\n    out.alternative: string\n        Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n    out.method: string\n        Name of test.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    // One-sample test:\n    > var arr = [ 6, 8, 14, 16, 23, 24, 28, 29, 41, -48, 49, 56, 60, -67, 75 ];\n    > var out = wilcoxon( x )\n    {\n        'rejected': true,\n        'alpha': 0.05,\n        'pValue': 0.04125976562499978,\n        'statistic': 96\n        // ...\n    }\n\n    // Paired test:\n    > runif = base.random.discreteUniform.factory( 1, 5, { 'seed': 786 });\n    > var x = new Array( 100 );\n    > var y = new Array( 100 );\n    > for ( i = 0; i < x.length; i++ ) {\n    ...     x[ i ] = runif();\n    ...     y[ i ] = runif();\n    ... }\n    > out = wilcoxon( x, y )\n    {\n        'rejected': false,\n        'alpha': 0.05,\n        'pValue': 0.21759090963694638,\n        'statistic': 2702.5,\n        // ...\n    }\n\n    // Print formatted output:\n    > var table = out.print()\n    Paired Wilcoxon signed rank test\n\n    Alternative hypothesis: Median of the difference `x - y` is not equal to 0\n\n        pValue: 0.2176\n        statistic: 2702.5\n\n    Test Decision: Fail to reject null in favor of alternative at 5% significance level\n\n\n    // Choose custom significance level:\n    > out = wilcoxon( arr, { 'alpha': 0.01 });\n    > table = out.print()\n    One-Sample Wilcoxon signed rank test\n\n    Alternative hypothesis: Median of `x` is not equal to 0\n\n        pValue: 0.0413\n        statistic: 96\n\n    Test Decision: Fail to reject null in favor of alternative at 1% significance level\n\n\n    // Test for a median equal to ten:\n    > out = wilcoxon( arr, { 'mu': 10 })\n    {\n        'rejected': false,\n        'alpha': 0.05,\n        'pValue': 0.11169650413134602,\n        'statistic': 88.5,\n        'nullValue': 10,\n        // ...\n    }\n\n    // Perform one-sided tests:\n    > out = wilcoxon( arr, { 'alternative': 'less' });\n    > table = out.print()\n    One-Sample Wilcoxon signed rank test\n\n    Alternative hypothesis: Median of `x` is less than 0\n\n        pValue: 0.9823\n        statistic: 96\n\n    Test Decision: Fail to reject null in favor of alternative at 5% significance level\n\n\n    > out = wilcoxon( arr, { 'alternative': 'greater' });\n    > table = out.print()\n    One-Sample Wilcoxon signed rank test\n\n    Alternative hypothesis: Median of `x` is greater than 0\n\n        pValue: 0.0206\n        statistic: 96\n\n    Test Decision: Reject null in favor of alternative at 5% significance level\n\n    See Also\n    --------\n    ttest, ztest\n","writableProperties":"\nwritableProperties( value )\n    Returns an array of an object's own writable property names and symbols.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    props: Array\n        List of an object's own writable properties.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var props = writableProperties( obj )\n    [ 'beep' ]\n\n    See Also\n    --------\n    inheritedWritableProperties, writablePropertiesIn, properties\n","writablePropertiesIn":"\nwritablePropertiesIn( value )\n    Returns an array of an object's own and inherited writable property names\n    and symbols.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    props: Array\n        List of an object's own and inherited writable property names and\n        symbols.\n\n    Examples\n    --------\n    > var props = writablePropertiesIn( [] )\n\n    See Also\n    --------\n    inheritedWritableProperties, writableProperties, propertiesIn\n","writablePropertyNames":"\nwritablePropertyNames( value )\n    Returns an array of an object's own writable property names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's own writable property names.\n\n    Examples\n    --------\n    > var obj = { 'a': 'b' };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = true;\n    > desc.writable = false;\n    > desc.value = 'boop';\n    > defineProperty( obj, 'beep', desc );\n    > var keys = writablePropertyNames( obj )\n    [ 'a' ]\n\n    See Also\n    --------\n    inheritedWritablePropertyNames, writableProperties, writablePropertyNamesIn, writablePropertySymbols, propertyNames\n","writablePropertyNamesIn":"\nwritablePropertyNamesIn( value )\n    Returns an array of an object's own and inherited writable property names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's own and inherited writable property names.\n\n    Examples\n    --------\n    > var obj = { 'a': 'b' };\n    > var desc = {};\n    > desc.configurable = true;\n    > desc.enumerable = true;\n    > desc.writable = false;\n    > desc.value = 'boop';\n    > defineProperty( obj, 'beep', desc );\n    > var keys = writablePropertyNamesIn( obj )\n    e.g., [ 'a', ... ]\n\n    See Also\n    --------\n    inheritedWritablePropertyNames, writablePropertiesIn, writablePropertyNames, writablePropertySymbolsIn, propertyNamesIn\n","writablePropertySymbols":"\nwritablePropertySymbols( value )\n    Returns an array of an object's own writable symbol properties.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's own writable symbol properties.\n\n    Examples\n    --------\n    > var obj = {};\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.writable = true;\n    > desc.value = 'boop';\n    > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n    > defineProperty( obj, sym, desc );\n    > var symbols = writablePropertySymbols( obj )\n\n    See Also\n    --------\n    inheritedWritablePropertySymbols, writableProperties, writablePropertyNames, writablePropertySymbolsIn, propertySymbols\n","writablePropertySymbolsIn":"\nwritablePropertySymbolsIn( value )\n    Returns an array of an object's own and inherited writable symbol\n    properties.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's own and inherited writable symbol properties.\n\n    Examples\n    --------\n    > var obj = {};\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.writable = true;\n    > desc.value = 'boop';\n    > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n    > defineProperty( obj, sym, desc );\n    > var symbols = writablePropertySymbolsIn( obj )\n\n    See Also\n    --------\n    inheritedWritablePropertySymbols, writablePropertiesIn, writablePropertyNamesIn, writablePropertySymbols, propertySymbolsIn\n","writeFile":"\nwriteFile( file, data[, options], clbk )\n    Asynchronously writes data to a file.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    data: string|Buffer\n        Data to write.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. The encoding option is ignored if the data argument is a\n        buffer. Default: 'utf8'.\n\n    options.flag: string (optional)\n        Flag. Default: 'w'.\n\n    options.mode: integer (optional)\n        Mode. Default: 0o666.\n\n    clbk: Function\n        Callback to invoke upon writing data to a file.\n\n    Examples\n    --------\n    > function onWrite( error ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     }\n    ... };\n    > writeFile( './beep/boop.txt', 'beep boop', onWrite );\n\n\nwriteFile.sync( file, data[, options] )\n    Synchronously writes data to a file.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    data: string|Buffer\n        Data to write.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. The encoding option is ignored if the data argument is a\n        buffer. Default: 'utf8'.\n\n    options.flag: string (optional)\n        Flag. Default: 'w'.\n\n    options.mode: integer (optional)\n        Mode. Default: 0o666.\n\n    Returns\n    -------\n    err: Error|null\n        Error object or null.\n\n    Examples\n    --------\n    > var err = writeFile.sync( './beep/boop.txt', 'beep boop' );\n\n    See Also\n    --------\n    exists, readFile\n","writeFile.sync":"\nwriteFile.sync( file, data[, options] )\n    Synchronously writes data to a file.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    data: string|Buffer\n        Data to write.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. The encoding option is ignored if the data argument is a\n        buffer. Default: 'utf8'.\n\n    options.flag: string (optional)\n        Flag. Default: 'w'.\n\n    options.mode: integer (optional)\n        Mode. Default: 0o666.\n\n    Returns\n    -------\n    err: Error|null\n        Error object or null.\n\n    Examples\n    --------\n    > var err = writeFile.sync( './beep/boop.txt', 'beep boop' );\n\n    See Also\n    --------\n    exists, readFile","zip":"\nzip( ...arr[, options] )\n    Generates array tuples from input arrays.\n\n    Parameters\n    ----------\n    arr: ...Array\n        Input arrays to be zipped.\n\n    options: Object (optional)\n        Options.\n\n    options.trunc: boolean (optional)\n        Boolean indicating whether to truncate arrays longer than the shortest\n        input array. Default: `true`.\n\n    options.fill: any (optional)\n        Fill value used for arrays of unequal length. Default: `null`.\n\n    options.arrays: boolean (optional)\n        Boolean indicating whether an input array should be interpreted as an\n        array of arrays to be zipped. Default: `false`.\n\n    Returns\n    -------\n    out: Array\n        Array of arrays.\n\n    Examples\n    --------\n    // Basic usage:\n    > var out = zip( [ 1, 2 ], [ 'a', 'b' ] )\n    [ [ 1, 'a' ], [ 2, 'b' ] ]\n\n    // Turn off truncation:\n    > var opts = { 'trunc': false };\n    > out = zip( [ 1, 2, 3 ], [ 'a', 'b' ], opts )\n    [ [ 1, 'a' ], [ 2, 'b' ], [ 3, null ] ]\n\n    See Also\n    --------\n    unzip\n","ztest":"\nztest( x, sigma[, options] )\n    Computes a one-sample z-test.\n\n    The function performs a one-sample z-test for the null hypothesis that the\n    data in array or typed array `x` is drawn from a normal distribution with\n    mean zero and standard deviation `sigma`.\n\n    The returned object comes with a `.print()` method which when invoked will\n    print a formatted output of the results of the hypothesis test.\n\n    Parameters\n    ----------\n    x: Array<number>\n        Data array.\n\n    sigma: number\n        Known standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.alternative: string (optional)\n        Indicates whether the alternative hypothesis is that the mean of `x` is\n        larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n        `mu` (`two-sided`). Default: `'two-sided'`.\n\n    options.mu: number (optional)\n        Hypothesized true mean under the null hypothesis. Set this option to\n        test whether the data comes from a distribution with the specified `mu`.\n        Default: `0`.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Used significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.ci: Array<number>\n        1-alpha confidence interval for mean.\n\n    out.nullValue: number\n        Assumed mean value under H0.\n\n    out.sd: number\n        Standard error.\n\n    out.alternative: string\n        Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n    out.method: string\n        Name of test (`One-Sample z-test`).\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    // One-sample z-test:\n    > var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 212 } );\n    > var x = new Array( 100 );\n    > for ( var i = 0; i < x.length; i++ ) {\n    ...     x[ i ] = rnorm();\n    ... }\n    > var out = ztest( x, 2.0 )\n    {\n        alpha: 0.05,\n        rejected: false,\n        pValue: ~0.180,\n        statistic: ~-1.34,\n        ci: [ ~-0.66, ~0.124 ],\n        ...\n    }\n\n    // Choose custom significance level and print output:\n    > arr = [ 2, 4, 3, 1, 0 ];\n    > out = ztest( arr, 2.0, { 'alpha': 0.01 } );\n    > table = out.print()\n    One-sample z-test\n\n    Alternative hypothesis: True mean is not equal to 0\n\n        pValue: 0.0253\n        statistic: 2.2361\n        99% confidence interval: [-0.3039,4.3039]\n\n    Test Decision: Fail to reject null in favor of alternative at 1%\n    significance level\n\n\n    // Test for a mean equal to five:\n    > var arr = [ 4, 4, 6, 6, 5 ];\n    > out = ztest( arr, 1.0, { 'mu': 5 } )\n    {\n        rejected: false,\n        pValue: 1,\n        statistic: 0,\n        ci: [ ~4.123, ~5.877 ],\n        // ...\n    }\n\n    // Perform one-sided tests:\n    > arr = [ 4, 4, 6, 6, 5 ];\n    > out = ztest( arr, 1.0, { 'alternative': 'less' } )\n    {\n        alpha: 0.05,\n        rejected: false,\n        pValue: 1,\n        statistic: 11.180339887498949,\n        ci: [ -Infinity, 5.735600904580115 ],\n        // ...\n    }\n    > out = ztest( arr, 1.0, { 'alternative': 'greater' } )\n    {\n        alpha: 0.05,\n        rejected: true,\n        pValue: 0,\n        statistic: 11.180339887498949,\n        ci: [ 4.264399095419885, Infinity ],\n        //...\n    }\n\n    See Also\n    --------\n    ztest2\n","ztest2":"\nztest2( x, y, sigmax, sigmay[, options] )\n    Computes a two-sample z-test.\n\n    By default, the function performs a two-sample z-test for the null\n    hypothesis that the data in arrays or typed arrays `x` and `y` is\n    independently drawn from normal distributions with equal means and known\n    standard deviations `sigmax` and `sigmay`.\n\n    The returned object comes with a `.print()` method which when invoked will\n    print a formatted output of the results of the hypothesis test.\n\n    Parameters\n    ----------\n    x: Array<number>\n        First data array.\n\n    y: Array<number>\n        Second data array.\n\n    sigmax: number\n        Known standard deviation of first group.\n\n    sigmay: number\n        Known standard deviation of second group.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.alternative: string (optional)\n        Either `two-sided`, `less` or `greater`. Indicates whether the\n        alternative hypothesis is that `x` has a larger mean than `y`\n        (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n        the same (`two-sided`). Default: `'two-sided'`.\n\n    options.difference: number (optional)\n        Number denoting the difference in means under the null hypothesis.\n        Default: `0`.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Used significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.ci: Array<number>\n        1-alpha confidence interval for the mean.\n\n    out.nullValue: number\n        Assumed difference in means under H0.\n\n    out.xmean: number\n        Sample mean of `x`.\n\n    out.ymean: number\n        Sample mean of `y`.\n\n    out.alternative: string\n        Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n    out.method: string\n        Name of test.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    // Drawn from Normal(0,2):\n    > var x = [ -0.21, 0.14, 1.65, 2.11, -1.86, -0.29, 1.48, 0.81, 0.86, 1.04 ];\n\n    // Drawn from Normal(1,2):\n    > var y = [ -1.53, -2.93, 2.34, -1.15, 2.7, -0.12, 4.22, 1.66, 3.43, 4.66 ];\n    > var out = ztest2( x, y, 2.0, 2.0 )\n    {\n        alpha: 0.05,\n        rejected: false,\n        pValue: ~0.398,\n        statistic: ~-0.844\n        ci: [ ~-2.508, ~0.988 ],\n        alternative: 'two-sided',\n        method: 'Two-sample z-test',\n        nullValue: 0,\n        xmean: ~0.573,\n        ymean: ~1.328\n    }\n\n    // Print table output:\n    > var table = out.print()\n    Two-sample z-test\n\n    Alternative hypothesis: True difference in means is not equal to 0\n\n        pValue: 0.3986\n        statistic: -0.8441\n        95% confidence interval: [-2.508,0.998]\n\n    Test Decision: Fail to reject null in favor of alternative at 5%\n    significance level\n\n    // Choose a different significance level than `0.05`:\n    > out = ztest2( x, y, 2.0, 2.0, { 'alpha': 0.4 } );\n    > table = out.print()\n    Two-sample z-test\n\n    Alternative hypothesis: True difference in means is not equal to 0\n\n        pValue: 0.3986\n        statistic: -0.8441\n        60% confidence interval: [-1.5078,-0.0022]\n\n    Test Decision: Reject null in favor of alternative at 40% significance level\n\n    // Perform one-sided tests:\n    > out = ztest2( x, y, 2.0, 2.0, { 'alternative': 'less' } );\n    > table = out.print()\n    Two-sample z-test\n\n    Alternative hypothesis: True difference in means is less than 0\n\n        pValue: 0.1993\n        statistic: -0.8441\n        95% confidence interval: [-Infinity,0.7162]\n\n    Test Decision: Fail to reject null in favor of alternative at 5%\n    significance level\n\n\n    > out = ztest2( x, y, 2.0, 2.0, { 'alternative': 'greater' } );\n    > table = out.print()\n    Two-sample z-test\n\n    Alternative hypothesis: True difference in means is greater than 0\n\n        pValue: 0.8007\n        statistic: -0.8441\n        95% confidence interval: [-2.2262,Infinity]\n\n    Test Decision: Fail to reject null in favor of alternative at 5%\n    significance level\n\n    // Test for a difference in means besides zero:\n    > var rnorm = base.random.normal.factory({ 'seed': 372 } );\n    > x = new Array( 100 );\n    > for ( i = 0; i < x.length; i++ ) {\n    ...     x[ i ] = rnorm( 2.0, 1.0 );\n    ... }\n    > y = new Array( 100 );\n    ... for ( i = 0; i < x.length; i++ ) {\n    ...     y[ i ] = rnorm( 0.0, 2.0 );\n    ... }\n    > out = ztest2( x, y, 1.0, 2.0, { 'difference': 2.0 } )\n    {\n        rejected: false,\n        pValue: ~0.35,\n        statistic: ~-0.935\n        ci: [ ~1.353, ~2.229 ],\n        // ...\n    }\n\n    See Also\n    --------\n    ztest\n"}
+{"abs":"\nabs( x[, options] )\n    Computes the absolute value.\n\n    If provided a number, the function returns a number.\n\n    If provided an ndarray or array-like object, the function performs element-\n    wise computation.\n\n    If provided an array-like object, the function returns an array-like object\n    having the same length and data type as `x`.\n\n    If provided an ndarray, the function returns an ndarray having the same\n    shape and data type as `x`.\n\n    Parameters\n    ----------\n    x: ndarray|ArrayLikeObject|number\n        Input value.\n\n    options: Object (optional)\n        Options.\n\n    options.order: string (optional)\n        Output array order (either row-major (C-style) or column-major (Fortran-\n        style)). Only applicable when the input array is an ndarray. By default,\n        the output array order is inferred from the input array.\n\n    options.dtype: string (optional)\n        Output array data type. Only applicable when the input array is either\n        an ndarray or array-like object. By default, the output array data type\n        is inferred from the input array.\n\n    Returns\n    -------\n    y: ndarray|ArrayLikeObject|number\n        Results.\n\n    Examples\n    --------\n    // Provide a number:\n    > var y = abs( -1.0 )\n    1.0\n\n    // Provide an array-like object:\n    > var x = new Float64Array( [ -1.0, -2.0 ] );\n    > y = abs( x )\n    <Float64Array>[ 1.0, 2.0 ]\n\n    > x = [ -1.0, -2.0 ];\n    > y = abs( x )\n    [ 1.0, 2.0 ]\n\n    // Provide an ndarray:\n    > x = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] );\n    > y = abs( x )\n    <ndarray>\n    > y.get( 0, 1 )\n    2.0\n\n\nabs.assign( x, y )\n    Computes the absolute value and assigns results to a provided output array.\n\n    Parameters\n    ----------\n    x: ndarray|ArrayLikeObject\n        Input array.\n\n    y: ndarray|ArrayLikeObject\n        Output array. Must be the same data \"kind\" (i.e., ndarray or array-like\n        object) as the input array.\n\n    Returns\n    -------\n    y: ndarray|ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Provide an array-like object:\n    > var x = new Float64Array( [ -1.0, -2.0 ] );\n    > var y = new Float64Array( x.length );\n    > var out = abs.assign( x, y )\n    <Float64Array>[ 1.0, 2.0 ]\n    > var bool = ( out === y )\n    true\n\n    > x = [ -1.0, -2.0 ];\n    > y = [ 0.0, 0.0 ];\n    > out = abs.assign( x, y )\n    [ 1.0, 2.0 ]\n    > bool = ( out === y )\n    true\n\n    // Provide an ndarray:\n    > x = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] );\n    > y = array( [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ] );\n    > out = abs.assign( x, y )\n    <ndarray>\n    > out.get( 0, 1 )\n    2.0\n    > bool = ( out === y )\n    true\n\n","abs.assign":"\nabs.assign( x, y )\n    Computes the absolute value and assigns results to a provided output array.\n\n    Parameters\n    ----------\n    x: ndarray|ArrayLikeObject\n        Input array.\n\n    y: ndarray|ArrayLikeObject\n        Output array. Must be the same data \"kind\" (i.e., ndarray or array-like\n        object) as the input array.\n\n    Returns\n    -------\n    y: ndarray|ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Provide an array-like object:\n    > var x = new Float64Array( [ -1.0, -2.0 ] );\n    > var y = new Float64Array( x.length );\n    > var out = abs.assign( x, y )\n    <Float64Array>[ 1.0, 2.0 ]\n    > var bool = ( out === y )\n    true\n\n    > x = [ -1.0, -2.0 ];\n    > y = [ 0.0, 0.0 ];\n    > out = abs.assign( x, y )\n    [ 1.0, 2.0 ]\n    > bool = ( out === y )\n    true\n\n    // Provide an ndarray:\n    > x = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] );\n    > y = array( [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ] );\n    > out = abs.assign( x, y )\n    <ndarray>\n    > out.get( 0, 1 )\n    2.0\n    > bool = ( out === y )\n    true","acartesianPower":"\nacartesianPower( x, n )\n    Returns the Cartesian power.\n\n    If provided an empty array, the function returns an empty array.\n\n    If `n` is less than or equal to zero, the function returns an empty array.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    n: integer\n        Power.\n\n    Returns\n    -------\n    out: Array<Array>\n        Cartesian product.\n\n    Examples\n    --------\n    > var x = [ 1, 2 ];\n    > var out = acartesianPower( x, 2 )\n    [ [ 1, 1 ], [ 1, 2 ], [ 2, 1 ], [ 2, 2 ] ]\n\n    See Also\n    --------\n    acartesianProduct, acartesianSquare\n","acartesianProduct":"\nacartesianProduct( x1, x2 )\n    Returns the Cartesian product.\n\n    If provided one or more empty arrays, the function returns an empty array.\n\n    Parameters\n    ----------\n    x1: ArrayLikeObject\n        First input array.\n\n    x2: ArrayLikeObject\n        Second input array.\n\n    Returns\n    -------\n    out: Array<Array>\n        Cartesian product.\n\n    Examples\n    --------\n    > var x1 = [ 1, 2 ];\n    > var x2 = [ 3, 4 ];\n    > var out = acartesianProduct( x1, x2 )\n    [ [ 1, 3 ], [ 1, 4 ], [ 2, 3 ], [ 2, 4 ] ]\n\n    See Also\n    --------\n    acartesianPower, acartesianSquare\n","acartesianSquare":"\nacartesianSquare( x )\n    Returns the Cartesian square.\n\n    If provided an empty array, the function returns an empty array.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    Returns\n    -------\n    out: Array<Array>\n        Cartesian product.\n\n    Examples\n    --------\n    > var out = acartesianSquare( [ 1, 2 ] )\n    [ [ 1, 1 ], [ 1, 2 ], [ 2, 1 ], [ 2, 2 ] ]\n\n    See Also\n    --------\n    acartesianPower, acartesianProduct\n","acronym":"\nacronym( str[, options] )\n    Generates an acronym for a given string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    options: Object (optional)\n        Options.\n\n    options.stopwords: Array<string> (optional)\n        Array of custom stop words.\n\n    Returns\n    -------\n    out: string\n        Acronym for the given string.\n\n    Examples\n    --------\n    > var out = acronym( 'the quick brown fox' )\n    'QBF'\n    > out = acronym( 'Hard-boiled eggs' )\n    'HBE'\n","aempty":"\naempty( length[, dtype] )\n    Creates an uninitialized array having a specified length.\n\n    In browser environments, the function always returns zero-filled arrays.\n\n    If `dtype` is 'generic', the function always returns a zero-filled array.\n\n    In Node.js versions >=3.0.0, the underlying memory of returned typed arrays\n    is *not* initialized. Memory contents are unknown and may contain\n    *sensitive* data.\n\n    Parameters\n    ----------\n    length: integer\n        Array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = aempty( 2 )\n    <Float64Array>\n    > arr = aempty( 2, 'float32' )\n    <Float32Array>\n\n    See Also\n    --------\n    aemptyLike, afull, aones, azeros, ndempty\n","aemptyLike":"\naemptyLike( x[, dtype] )\n    Creates an uninitialized array having the same length and data type as a\n    provided input array.\n\n    In browser environments, the function always returns zero-filled arrays.\n\n    If `dtype` is 'generic', the function always returns a zero-filled array.\n\n    In Node.js versions >=3.0.0, the underlying memory of returned typed arrays\n    is *not* initialized. Memory contents are unknown and may contain\n    *sensitive* data.\n\n    Parameters\n    ----------\n    x: TypedArray|Array\n        Input array.\n\n    dtype: string (optional)\n        Data type. If not provided, the output array data type is inferred from\n        the input array.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var x = new Float64Array( 2 );\n    > var arr = aemptyLike( x )\n    <Float64Array>\n    > arr = aemptyLike( x, 'float32' )\n    <Float32Array>\n\n    See Also\n    --------\n    aempty, afullLike, aonesLike, azerosLike, ndemptyLike\n","AFINN_96":"\nAFINN_96()\n    Returns a list of English words rated for valence.\n\n    The returned list contains 1468 English words (and phrases) rated for\n    valence. Negative words have a negative valence [-5,0). Positive words have\n    a positive valence (0,5]. Neutral words have a valence of 0.\n\n    A few notes:\n\n    - The list is an earlier version of AFINN-111.\n    - The list includes misspelled words. Their presence is intentional, as such\n      misspellings frequently occur in social media content.\n    - All words are lowercase.\n    - Some \"words\" are phrases; e.g., \"cashing in\", \"cool stuff\".\n    - Words may contain apostrophes; e.g., \"can't stand\".\n    - Words may contain dashes; e.g., \"cover-up\", \"made-up\".\n\n    Returns\n    -------\n    out: Array<Array>\n        List of English words and their valence.\n\n    Examples\n    --------\n    > var list = AFINN_96()\n    [ [ 'abandon', -2 ], [ 'abandons', -2 ], [ 'abandoned', -2 ], ... ]\n\n    References\n    ----------\n    - Nielsen, Finn Årup. 2011. \"A new ANEW: Evaluation of a word list for\n    sentiment analysis in microblogs.\" In *Proceedings of the ESWC2011 Workshop\n    on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n    718:93–98. CEUR Workshop Proceedings. <http://ceur-ws.org/Vol-718/paper_16.\n    pdf>.\n\n    * If you use the list for publication or third party consumption, please\n    cite the listed reference.\n\n    See Also\n    --------\n    AFINN_111\n","AFINN_111":"\nAFINN_111()\n    Returns a list of English words rated for valence.\n\n    The returned list contains 2477 English words (and phrases) rated for\n    valence. Negative words have a negative valence [-5,0). Positive words have\n    a positive valence (0,5]. Neutral words have a valence of 0.\n\n    A few notes:\n\n    - The list includes misspelled words. Their presence is intentional, as such\n      misspellings frequently occur in social media content.\n    - All words are lowercase.\n    - Words may contain numbers; e.g., \"n00b\".\n    - Some \"words\" are phrases; e.g., \"cool stuff\", \"not good\".\n    - Words may contain apostrophes; e.g., \"can't stand\".\n    - Words may contain diaeresis; e.g., \"naïve\".\n    - Words may contain dashes; e.g., \"self-deluded\", \"self-confident\".\n\n    Returns\n    -------\n    out: Array<Array>\n        List of English words and their valence.\n\n    Examples\n    --------\n    > var list = AFINN_111()\n    [ [ 'abandon', -2 ], [ 'abandoned', -2 ], [ 'abandons', -2 ], ... ]\n\n    References\n    ----------\n    - Nielsen, Finn Årup. 2011. \"A new ANEW: Evaluation of a word list for\n    sentiment analysis in microblogs.\" In *Proceedings of the ESWC2011 Workshop\n    on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n    718:93–98. CEUR Workshop Proceedings. <http://ceur-ws.org/Vol-718/paper_16.\n    pdf>.\n\n    * If you use the list for publication or third party consumption, please\n    cite the listed reference.\n\n    See Also\n    --------\n    AFINN_96\n","afull":"\nafull( length, value[, dtype] )\n    Returns a filled array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Array length.\n\n    value: any\n        Fill value.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = afull( 2, 1.0 )\n    <Float64Array>[ 1.0, 1.0 ]\n    > arr = afull( 2, 1.0, 'float32' )\n    <Float32Array>[ 1.0, 1.0 ]\n\n    See Also\n    --------\n    afullLike, aones, azeros\n","afullLike":"\nafullLike( x[, dtype] )\n    Returns a filled array having the same length and data type as a provided\n    input array.\n\n    Parameters\n    ----------\n    x: TypedArray|Array\n        Input array.\n\n    dtype: string (optional)\n        Data type. If not provided, the output array data type is inferred from\n        the input array.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var x = new Float64Array( 2 );\n    > var y = afullLike( x, 1.0 )\n    <Float64Array>[ 1.0, 1.0 ]\n    > y = afullLike( x, 1.0, 'float32' )\n    <Float32Array>[ 1.0, 1.0 ]\n\n    See Also\n    --------\n    afull, aonesLike, azerosLike\n","alias2pkg":"\nalias2pkg( alias )\n    Returns the package name associated with a provided alias.\n\n    Parameters\n    ----------\n    alias: string\n        Alias.\n\n    Returns\n    -------\n    out: string|null\n        Package name.\n\n    Examples\n    --------\n    > var v = alias2pkg( 'base.sin' )\n    '@stdlib/math/base/special/sin'\n\n    See Also\n    --------\n    alias2related, aliases, pkg2alias\n","alias2related":"\nalias2related( alias )\n    Returns aliases related to a specified alias.\n\n    Parameters\n    ----------\n    alias: string\n        Alias.\n\n    Returns\n    -------\n    out: Array|null\n        Related aliases.\n\n    Examples\n    --------\n    > var v = alias2related( 'base.sin' )\n    [...]\n\n    See Also\n    --------\n    alias2pkg, aliases, pkg2related\n","alias2standalone":"\nalias2standalone( alias )\n    Returns the standalone package name associated with a provided alias.\n\n    Parameters\n    ----------\n    alias: string\n        Alias.\n\n    Returns\n    -------\n    out: string|null\n        Standalone package name.\n\n    Examples\n    --------\n    > var v = alias2standalone( 'base.sin' )\n    '@stdlib/math-base-special-sin'\n\n    See Also\n    --------\n    alias2pkg, alias2related, aliases, pkg2alias, pkg2standalone\n","aliases":"\naliases( [namespace] )\n    Returns a list of standard library aliases.\n\n    Parameters\n    ----------\n    namespace: string (optional)\n        Namespace filter.\n\n    Returns\n    -------\n    out: Array\n        List of aliases.\n\n    Examples\n    --------\n    > var o = aliases()\n    [...]\n    > o = aliases( '@stdlib/math/base/special' )\n    [...]\n\n    See Also\n    --------\n    alias2pkg, alias2related, pkg2alias\n","allocUnsafe":"\nallocUnsafe( size )\n    Allocates a buffer having a specified number of bytes.\n\n    The underlying memory of returned buffers is not initialized. Memory\n    contents are unknown and may contain sensitive data.\n\n    When the size is less than half a buffer pool size, memory is allocated from\n    the buffer pool for faster allocation of Buffer instances.\n\n    Parameters\n    ----------\n    size: integer\n        Number of bytes to allocate.\n\n    Returns\n    -------\n    out: Buffer\n        Buffer instance.\n\n    Examples\n    --------\n    > var buf = allocUnsafe( 100 )\n    <Buffer>\n\n    See Also\n    --------\n    Buffer, array2buffer, arraybuffer2buffer, copyBuffer, string2buffer\n","amskfilter":"\namskfilter( x, mask )\n    Returns a new array by applying a mask to a provided input array.\n\n    If a mask array element is truthy, the corresponding element in `x` is\n    included in the output array; otherwise, the corresponding element in `x` is\n    \"masked\" and thus excluded from the output array.\n\n    Parameters\n    ----------\n    x: Array|TypedArray|Object\n        Input array.\n\n    mask: Array|TypedArray|Object\n        Mask array.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Output array.\n\n    Examples\n    --------\n    > var x = [ 1, 2, 3, 4 ];\n    > var y = amskfilter( x, [ 0, 1, 0, 1 ] )\n    [ 2, 4 ]\n\n    See Also\n    --------\n    amskreject\n","amskput":"\namskput( x, mask, values[, options] )\n    Replaces elements of an array with provided values according to a provided\n    mask array.\n\n    In broadcasting modes, the function supports broadcasting a values array\n    containing a single element against the number of falsy values in the mask\n    array.\n\n    In repeat mode, the function supports recycling elements in a values array\n    to satisfy the number of falsy values in the mask array.\n\n    The function mutates the input array.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    mask: ArrayLikeObject\n        Mask array. If a mask array element is falsy, the corresponding element\n        in `x` is *replaced*; otherwise, the corresponding element in `x` is\n        \"masked\" and thus left unchanged.\n\n    values: ArrayLikeObject\n        Values to set.\n\n    options: Object (optional)\n        Function options.\n\n    options.mode: string (optional)\n        String specifying behavior when the number of values to set does not\n        equal the number of falsy mask values. The function supports the\n        following modes:\n\n        - 'strict': specifies that the function must raise an exception when the\n        number of values does not *exactly* equal the number of falsy mask\n        values.\n        - 'non_strict': specifies that the function must raise an exception when\n        the function is provided insufficient values to satisfy the mask array.\n        - 'strict_broadcast': specifies that the function must broadcast a\n        single-element values array and otherwise raise an exception when the\n        number of values does not **exactly** equal the number of falsy mask\n        values.\n        - 'broadcast': specifies that the function must broadcast a single-\n        element values array and otherwise raise an exception when the function\n        is provided insufficient values to satisfy the mask array.\n        - 'repeat': specifies that the function must reuse provided values when\n        replacing elements in `x` in order to satisfy the mask array.\n\n        Default: 'repeat'.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Input array.\n\n    Examples\n    --------\n    > var x = [ 1, 2, 3, 4 ];\n    > var out = amskput( x, [ 1, 0, 1, 0 ], [ 20, 40 ] )\n    [ 1, 20, 3, 40 ]\n    > var bool = ( out === x )\n    true\n\n    See Also\n    --------\n    aplace, aput, atake\n","amskreject":"\namskreject( x, mask )\n    Returns a new array by applying a mask to a provided input array.\n\n    If a mask array element is falsy, the corresponding element in `x` is\n    included in the output array; otherwise, the corresponding element in `x` is\n    \"masked\" and thus excluded from the output array.\n\n    Parameters\n    ----------\n    x: Array|TypedArray|Object\n        Input array.\n\n    mask: Array|TypedArray|Object\n        Mask array.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Output array.\n\n    Examples\n    --------\n    > var x = [ 1, 2, 3, 4 ];\n    > var y = amskreject( x, [ 0, 1, 0, 1 ] )\n    [ 1, 3 ]\n\n    See Also\n    --------\n    amskfilter\n","anans":"\nanans( length[, dtype] )\n    Returns an array filled with NaNs and having a specified length.\n\n    The function supports the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754)\n    - float32: single-precision floating-point numbers (IEEE 754)\n    - complex128: double-precision complex floating-point numbers\n    - complex64: single-precision complex floating-point numbers\n    - generic: generic JavaScript values\n\n    The default array data type is `float64`.\n\n    Parameters\n    ----------\n    length: integer\n        Array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = anans( 2 )\n    <Float64Array>[ NaN, NaN ]\n    > arr = anans( 2, 'float32' )\n    <Float32Array>[ NaN, NaN ]\n\n    See Also\n    --------\n    afull, anansLike, aones, azeros\n","anansLike":"\nanansLike( x[, dtype] )\n    Returns an array filled with NaNs and having the same length and data type\n    as a provided input array.\n\n    The function supports the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754).\n    - float32: single-precision floating-point numbers (IEEE 754).\n    - complex128: double-precision complex floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - generic: generic JavaScript values.\n\n    Parameters\n    ----------\n    x: TypedArray|Array\n        Input array.\n\n    dtype: string (optional)\n        Data type. If not provided, the output array data type is inferred from\n        the input array.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var x = new Float64Array( 2 );\n    > var y = anansLike( x )\n    <Float64Array>[ NaN, NaN ]\n    > y = anansLike( x, 'float32' )\n    <Float32Array>[ NaN, NaN ]\n\n    See Also\n    --------\n    afullLike, anans, aonesLike, azerosLike\n","anova1":"\nanova1( x, factor[, options] )\n    Performs a one-way analysis of variance.\n\n    Parameters\n    ----------\n    x: Array<number>\n        Measured values.\n\n    factor: Array\n        Array of treatments.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.method: string\n        Name of test.\n\n    out.means: Object\n        Group means alongside sample sizes and standard errors.\n\n    out.treatment: Object\n        Treatment results.\n\n    out.treatment.df: number\n        Treatment degrees of freedom.\n\n    out.treatment.ss: number\n        Treatment sum of squares.\n\n    out.treatment.ms: number\n        Treatment mean sum of squares.\n\n    out.error: Object\n        Error results.\n\n    out.error.df: number\n        Error degrees of freedom.\n\n    out.error.ss: number\n        Error sum of squares.\n\n    out.error.ms: number\n        Error mean sum of squares.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    > var x = [1, 3, 5, 2, 4, 6, 8, 7, 10, 11, 12, 15];\n    > var f = [\n    ... 'control', 'treatA', 'treatB', 'treatC', 'control',\n    ... 'treatA', 'treatB', 'treatC', 'control', 'treatA', 'treatB', 'treatC'\n    ... ];\n    > var out = anova1( x, f )\n    {...}\n\n","ANSCOMBES_QUARTET":"\nANSCOMBES_QUARTET()\n    Returns Anscombe's quartet.\n\n    Anscombe's quartet is a set of 4 datasets which all have nearly identical\n    simple statistical properties but vary considerably when graphed. Anscombe\n    created the datasets to demonstrate why graphical data exploration should\n    precede statistical data analysis and to show the effect of outliers on\n    statistical properties.\n\n    Returns\n    -------\n    out: Array<Array>\n        Anscombe's quartet.\n\n    Examples\n    --------\n    > var d = ANSCOMBES_QUARTET()\n    [[[10,8.04],...],[[10,9.14],...],[[10,7.46],...],[[8,6.58],...]]\n\n    References\n    ----------\n    - Anscombe, Francis J. 1973. \"Graphs in Statistical Analysis.\" *The American\n    Statistician* 27 (1). [American Statistical Association, Taylor & Francis,\n    Ltd.]: 17–21. <http://www.jstor.org/stable/2682899>.\n\n","any":"\nany( collection )\n    Tests whether at least one element in a collection is truthy.\n\n    The function immediately returns upon encountering a truthy value.\n\n    If provided an empty collection, the function returns `false`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if an element is truthy; otherwise, the\n        function returns `false`.\n\n    Examples\n    --------\n    > var arr = [ 0, 0, 0, 0, 1 ];\n    > var bool = any( arr )\n    true\n\n    See Also\n    --------\n    anyBy, every, forEach, none, some\n","anyBy":"\nanyBy( collection, predicate[, thisArg ] )\n    Tests whether at least one element in a collection passes a test implemented\n    by a predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    The function immediately returns upon encountering a truthy return value.\n\n    If provided an empty collection, the function returns `false`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns `true` for\n        any element; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function negative( v ) { return ( v < 0 ); };\n    > var arr = [ 1, 2, 3, 4, -1 ];\n    > var bool = anyBy( arr, negative )\n    true\n\n    See Also\n    --------\n    anyByAsync, anyByRight, everyBy, forEach, noneBy, someBy\n","anyByAsync":"\nanyByAsync( collection, [options,] predicate, done )\n    Tests whether at least one element in a collection passes a test implemented\n    by a predicate function.\n\n    When invoked, the predicate function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If the\n    predicate function accepts two arguments, the predicate function is\n    provided:\n\n    - value\n    - next\n\n    If the predicate function accepts three arguments, the predicate function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other predicate function signature, the predicate function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - result: test result.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    The function immediately returns upon encountering a non-falsy `result`\n    value and calls the `done` callback with `null` as the first argument and\n    `true` as the second argument.\n\n    If all elements fail, the function calls the `done` callback with `null`\n    as the first argument and `false` as the second argument.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > anyByAsync( arr, predicate, done )\n    1000\n    2500\n    3000\n    false\n\n    // Limit number of concurrent invocations:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 3000, 2500, 1000 ];\n    > anyByAsync( arr, opts, predicate, done )\n    2500\n    3000\n    1000\n    false\n\n    // Process sequentially:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 3000, 2500, 1000 ];\n    > anyByAsync( arr, opts, predicate, done )\n    3000\n    2500\n    1000\n    false\n\n\nanyByAsync.factory( [options,] predicate )\n    Returns a function which tests whether at least one element in a collection\n    passes a test implemented by a predicate function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = anyByAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    false\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    false\n\n    See Also\n    --------\n    anyBy, anyByRightAsync, everyByAsync, forEachAsync, noneByAsync, someByAsync\n","anyByAsync.factory":"\nanyByAsync.factory( [options,] predicate )\n    Returns a function which tests whether at least one element in a collection\n    passes a test implemented by a predicate function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = anyByAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    false\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    false\n\n    See Also\n    --------\n    anyBy, anyByRightAsync, everyByAsync, forEachAsync, noneByAsync, someByAsync","anyByRight":"\nanyByRight( collection, predicate[, thisArg ] )\n    Tests whether at least one element in a collection passes a test implemented\n    by a predicate function, iterating from right to left.\n\n    The predicate function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    The function immediately returns upon encountering a truthy return value.\n\n    If provided an empty collection, the function returns `false`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns `true` for\n        any element; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function negative( v ) { return ( v < 0 ); };\n    > var arr = [ -1, 1, 2, 3, 4 ];\n    > var bool = anyByRight( arr, negative )\n    true\n\n    See Also\n    --------\n    anyBy, anyByRightAsync, everyByRight, forEachRight, noneByRight, someByRight\n","anyByRightAsync":"\nanyByRightAsync( collection, [options,] predicate, done )\n    Tests whether at least one element in a collection passes a test implemented\n    by a predicate function, iterating from right to left.\n\n    When invoked, the predicate function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If the\n    predicate function accepts two arguments, the predicate function is\n    provided:\n\n    - value\n    - next\n\n    If the predicate function accepts three arguments, the predicate function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other predicate function signature, the predicate function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - result: test result.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    The function immediately returns upon encountering a non-falsy `result`\n    value and calls the `done` callback with `null` as the first argument and\n    `true` as the second argument.\n\n    If all elements fail, the function calls the `done` callback with `null`\n    as the first argument and `false` as the second argument.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > anyByRightAsync( arr, predicate, done )\n    1000\n    2500\n    3000\n    false\n\n    // Limit number of concurrent invocations:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 1000, 2500, 3000 ];\n    > anyByRightAsync( arr, opts, predicate, done )\n    2500\n    3000\n    1000\n    false\n\n    // Process sequentially:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 1000, 2500, 3000 ];\n    > anyByRightAsync( arr, opts, predicate, done )\n    3000\n    2500\n    1000\n    false\n\n\nanyByRightAsync.factory( [options,] predicate )\n    Returns a function which tests whether at least one element in a collection\n    passes a test implemented by a predicate function, iterating from right to\n    left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = anyByRightAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    false\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    false\n\n    See Also\n    --------\n    anyByAsync, anyByRight, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByRightAsync\n","anyByRightAsync.factory":"\nanyByRightAsync.factory( [options,] predicate )\n    Returns a function which tests whether at least one element in a collection\n    passes a test implemented by a predicate function, iterating from right to\n    left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = anyByRightAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    false\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    false\n\n    See Also\n    --------\n    anyByAsync, anyByRight, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByRightAsync","anyInBy":"\nanyInBy( object, predicate[, thisArg ] )\n    Tests whether at least one value in an object passes a test implemented by\n    a predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: the value of the current property being processed in the object\n    - key: the key of the current property being processed in the object\n    - object: the input object\n\n    The function immediately returns upon encountering a truthy return value.\n\n    If provided an empty object, the function returns `false`.\n\n    Parameters\n    ----------\n    object: Object\n        Input object over which to iterate. It must be non-null.\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns `true` for\n        any value; otherwise, it returns `false`.\n\n    Examples\n    --------\n    > function isNegative(value) { return value < 0 }\n    > var obj = { a: 1, b: -2, c: 3, d: 4 }\n    > var result = anyInBy(obj, isNegative)\n    true\n\n    See Also\n    --------\n    anyBy, anyOwnBy, everyInBy, someInBy","anyOwnBy":"\nanyOwnBy( object, predicate[, thisArg ] )\n    Tests whether at least one own property of an object passes a\n    test implemented by a predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: property value.\n    - index: property key.\n    - object: the input object.\n\n    The function immediately returns upon encountering a truthy return\n    value.\n\n    If provided an empty object, the function returns `false`.\n\n    Parameters\n    ----------\n    object: Object\n        Input object.\n\n    predicate: Function\n        Test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns a truthy\n        value for one own property; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function positive( v ) { return ( v > 0 ); };\n    > var obj = { 'a': -1, 'b': 2, 'c': -3 };\n    > var bool = anyOwnBy( obj, positive )\n    true\n\n    See Also\n    --------\n    anyBy, anyInBy, everyOwnBy, someOwnBy\n","aones":"\naones( length[, dtype] )\n    Returns an array filled with ones and having a specified length.\n\n    The function supports the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754).\n    - float32: single-precision floating-point numbers (IEEE 754).\n    - complex128: double-precision complex floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n    - generic: generic JavaScript values.\n\n    The default array data type is `float64`.\n\n    Parameters\n    ----------\n    length: integer\n        Array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = aones( 2 )\n    <Float64Array>[ 1.0, 1.0 ]\n    > arr = aones( 2, 'float32' )\n    <Float32Array>[ 1.0, 1.0 ]\n\n    See Also\n    --------\n    afull, anans, aonesLike, azeros\n","aonesLike":"\naonesLike( x[, dtype] )\n    Returns an array filled with ones and having the same length and data type\n    as a provided input array.\n\n    The function supports the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754).\n    - float32: single-precision floating-point numbers (IEEE 754).\n    - complex128: double-precision complex floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n    - generic: generic JavaScript values.\n\n    Parameters\n    ----------\n    x: TypedArray|Array\n        Input array.\n\n    dtype: string (optional)\n        Data type. If not provided, the output array data type is inferred from\n        the input array.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var x = new Float64Array( 2 );\n    > var y = aonesLike( x )\n    <Float64Array>[ 1.0, 1.0 ]\n    > y = aonesLike( x, 'float32' )\n    <Float32Array>[ 1.0, 1.0 ]\n\n    See Also\n    --------\n    afullLike, anansLike, aones, azerosLike\n","aoneTo":"\naoneTo( n[, dtype] )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from one.\n\n    The function supports the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754).\n    - float32: single-precision floating-point numbers (IEEE 754).\n    - complex128: double-precision complex floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n    - generic: generic JavaScript values.\n\n    The default array data type is `float64`.\n\n    If `n` is equal to zero, the function returns an empty array.\n\n    Parameters\n    ----------\n    n: integer\n        Number of elements.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = aoneTo( 2 )\n    <Float64Array>[ 1.0, 2.0 ]\n    > arr = aoneTo( 2, 'float32' )\n    <Float32Array>[ 1.0, 2.0 ]\n\n    See Also\n    --------\n    afull, aones, aoneToLike, azeroTo\n","aoneToLike":"\naoneToLike( x[, dtype] )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from one and having the same length and data type as a provided\n    input array.\n\n    The function supports the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754).\n    - float32: single-precision floating-point numbers (IEEE 754).\n    - complex128: double-precision complex floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n    - generic: generic JavaScript values.\n\n    Parameters\n    ----------\n    x: TypedArray|Array\n        Input array.\n\n    dtype: string (optional)\n        Data type. If not provided, the output array data type is inferred from\n        the input array.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = aoneToLike( [ 0, 0 ] )\n    [ 1, 2 ]\n    > arr = aoneToLike( [ 0, 0 ], 'float32' )\n    <Float32Array>[ 1.0, 2.0 ]\n\n    See Also\n    --------\n    afullLike, aonesLike, aoneTo, azeroToLike\n","APERY":"\nAPERY\n    Apéry's constant.\n\n    Examples\n    --------\n    > APERY\n    1.2020569031595942\n\n","aplace":"\naplace( x, mask, values[, options] )\n    Replaces elements of an array with provided values according to a provided\n    mask array.\n\n    In broadcasting modes, the function supports broadcasting a values array\n    containing a single element against the number of truthy values in the mask\n    array.\n\n    In repeat mode, the function supports recycling elements in a values array\n    to satisfy the number of truthy values in the mask array.\n\n    The function mutates the input array.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    mask: ArrayLikeObject\n        Mask array. If a mask array element is truthy, the corresponding element\n        in `x` is *replaced*; otherwise, the corresponding element in `x` is\n        \"masked\" and thus left unchanged.\n\n    values: ArrayLikeObject\n        Values to set.\n\n    options: Object (optional)\n        Function options.\n\n    options.mode: string (optional)\n        String specifying behavior when the number of values to set does not\n        equal the number of truthy mask values. The function supports the\n        following modes:\n\n        - 'strict': specifies that the function must raise an exception when the\n        number of values does not *exactly* equal the number of truthy mask\n        values.\n        - 'non_strict': specifies that the function must raise an exception when\n        the function is provided insufficient values to satisfy the mask array.\n        - 'strict_broadcast': specifies that the function must broadcast a\n        single-element values array and otherwise raise an exception when the\n        number of values does not **exactly** equal the number of truthy mask\n        values.\n        - 'broadcast': specifies that the function must broadcast a single-\n        element values array and otherwise raise an exception when the function\n        is provided insufficient values to satisfy the mask array.\n        - 'repeat': specifies that the function must reuse provided values when\n        replacing elements in `x` in order to satisfy the mask array.\n\n        Default: 'repeat'.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Input array.\n\n    Examples\n    --------\n    > var x = [ 1, 2, 3, 4 ];\n    > var out = aplace( x, [ 0, 1, 0, 1 ], [ 20, 40 ] )\n    [ 1, 20, 3, 40 ]\n    > var bool = ( out === x )\n    true\n\n    See Also\n    --------\n    amskput, aput, atake\n","append":"\nappend( collection1, collection2 )\n    Adds the elements of one collection to the end of another collection.\n\n    If the input collection is a typed array, the output value does not equal\n    the input reference and the underlying `ArrayBuffer` may *not* be the same\n    as the `ArrayBuffer` belonging to the input view.\n\n    For purposes of generality, always treat the output collection as distinct\n    from the input collection.\n\n    Parameters\n    ----------\n    collection1: Array|TypedArray|Object\n        A collection. If the collection is an `Object`, the collection should be\n        array-like.\n\n    collection2: Array|TypedArray|Object\n        A collection containing the elements to add. If the collection is an\n        `Object`, the collection should be array-like.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Updated collection.\n\n    Examples\n    --------\n    // Arrays:\n    > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > arr = append( arr, [ 6.0, 7.0 ] )\n    [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]\n\n    // Typed arrays:\n    > arr = new Float64Array( [ 1.0, 2.0 ] );\n    > arr = append( arr, [ 3.0, 4.0 ] )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Array-like object:\n    > arr = { 'length': 0 };\n    > arr = append( arr, [ 1.0, 2.0 ] )\n    { 'length': 2, '0': 1.0, '1': 2.0 }\n\n    See Also\n    --------\n    prepend, push\n","aput":"\naput( x, indices, values[, options] )\n    Replaces specified elements of an array with provided values.\n\n    The function supports broadcasting a `values` array containing a single\n    element against an `indices` array containing one or more elements.\n\n    The function mutates the input array.\n\n    Because each index is only validated at the time of replacing a particular\n    element, mutation may occur even when one or more indices are out-of-bounds,\n    including when the index mode indicates to raise an exception.\n\n    If `indices` is an empty array, the function returns the input array\n    unchanged.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    indices: ArrayLikeObject<integer>\n        List of element indices.\n\n    values: ArrayLikeObject\n        Values to set. When `indices` contains one or more elements, `values`\n        must be broadcast compatible with `indices` (i.e., must have either one\n        element or the same number of elements as `indices`).\n\n    options: Object (optional)\n        Function options.\n\n    options.mode: string (optional)\n        Specifies how to handle an index outside the interval [0, max], where\n        `max` is the maximum possible array index. If equal to 'throw', the\n        function throws an error. If equal to 'normalize', the function throws\n        an error if provided an out-of-bounds normalized index. If equal to\n        'wrap', the function wraps around an index using modulo arithmetic. If\n        equal to 'clamp', the function sets an index to either 0 (minimum index)\n        or the maximum index. Default: 'normalize'.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Input array.\n\n    Examples\n    --------\n    > var x = [ 1, 2, 3, 4 ];\n    > var out = aput( x, [ 1, 3 ], [ 20, 40 ] )\n    [ 1, 20, 3, 40 ]\n    > var bool = ( out === x )\n    true\n\n    See Also\n    --------\n    amskput, aplace, atake\n","ARCH":"\nARCH\n    Operating system CPU architecture for which the JavaScript runtime binary\n    was compiled.\n\n    Current possible values:\n\n    - arm\n    - arm64\n    - ia32\n    - mips\n    - mipsel\n    - ppc\n    - ppc64\n    - s390\n    - s390x\n    - x32\n    - x64\n\n    Examples\n    --------\n    > ARCH\n    <string>\n\n    See Also\n    --------\n    PLATFORM\n","argumentFunction":"\nargumentFunction( idx )\n    Returns a function which always returns a specified argument.\n\n    The input argument corresponds to the zero-based index of the argument to\n    return.\n\n    Parameters\n    ----------\n    idx: integer\n        Argument index to return (zero-based).\n\n    Returns\n    -------\n    out: Function\n        Argument function.\n\n    Examples\n    --------\n    > var argn = argumentFunction( 1 );\n    > var v = argn( 3.14, -3.14, 0.0 )\n    -3.14\n    > v = argn( -1.0, -0.0, 1.0 )\n    -0.0\n    > v = argn( 'beep', 'boop', 'bop' )\n    'boop'\n    > v = argn( 'beep' )\n    undefined\n\n    See Also\n    --------\n    constantFunction, identity\n","ARGV":"\nARGV\n    An array containing command-line arguments passed when launching the calling\n    process.\n\n    The first element is the absolute pathname of the executable that started\n    the calling process.\n\n    The second element is the path of the executed file.\n\n    Any additional elements are additional command-line arguments.\n\n    In browser environments, the array is empty.\n\n    Examples\n    --------\n    > var execPath = ARGV[ 0 ]\n    e.g., /usr/local/bin/node\n\n    See Also\n    --------\n    ENV\n","array":"\narray( [buffer,] [options] )\n    Returns a multidimensional array.\n\n    Parameters\n    ----------\n    buffer: Array|TypedArray|Buffer|ndarray (optional)\n        Data source.\n\n    options: Object (optional)\n        Options.\n\n    options.buffer: Array|TypedArray|Buffer|ndarray (optional)\n        Data source. If provided along with a `buffer` argument, the argument\n        takes precedence.\n\n    options.dtype: string (optional)\n        Underlying storage data type. If not specified and a data source is\n        provided, the data type is inferred from the provided data source. If an\n        input data source is not of the same type, this option specifies the\n        data type to which to cast the input data. For non-ndarray generic array\n        data sources, the function casts generic array data elements to the\n        default data type. In order to prevent this cast, the `dtype` option\n        must be explicitly set to `'generic'`. Any time a cast is required, the\n        `copy` option is set to `true`, as memory must be copied from the data\n        source to an output data buffer. Default: 'float64'.\n\n    options.order: string (optional)\n        Specifies the memory layout of the data source as either row-major (C-\n        style) or column-major (Fortran-style). The option may be one of the\n        following values:\n\n        - 'row-major': the order of the returned array is row-major.\n        - 'column-major': the order of the returned array is column-major.\n        - 'any': if a data source is column-major and not row-major, the order\n          of the returned array is column-major; otherwise, the order of the\n          returned array is row-major.\n        - 'same': the order of the returned array matches the order of an input\n          data source.\n\n        Note that specifying an order which differs from the order of a\n        provided data source does *not* entail a conversion from one memory\n        layout to another. In short, this option is descriptive, not\n        prescriptive. Default: 'row-major'.\n\n    options.shape: Array<integer> (optional)\n        Array shape (dimensions). If a shape is not specified, the function\n        attempts to infer a shape based on a provided data source. For example,\n        if provided a nested array, the function resolves nested array\n        dimensions. If provided a multidimensional array data source, the\n        function uses the array's associated shape. For most use cases, such\n        inference suffices. For the remaining use cases, specifying a shape is\n        necessary. For example, provide a shape to create a multidimensional\n        array view over a linear data buffer, ignoring any existing shape meta\n        data associated with a provided data source.\n\n    options.flatten: boolean (optional)\n        Boolean indicating whether to automatically flatten generic array data\n        sources. If an array shape is not specified, the shape is inferred from\n        the dimensions of nested arrays prior to flattening. If a use case\n        requires partial flattening, partially flatten prior to invoking this\n        function and set the option value to `false` to prevent further\n        flattening during invocation. Default: true.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to (shallow) copy source data to a new data\n        buffer. The function does *not* perform a deep copy. To prevent\n        undesired shared changes in state for generic arrays containing objects,\n        perform a deep copy prior to invoking this function. Default: false.\n\n    options.ndmin: integer (optional)\n        Specifies the minimum number of dimensions. If an array shape has fewer\n        dimensions than required by `ndmin`, the function prepends singleton\n        dimensions to the array shape in order to satisfy the dimensions\n        requirement. Default: 0.\n\n    options.casting: string (optional)\n        Specifies the casting rule used to determine acceptable casts. The\n        option may be one of the following values:\n\n        - 'none': only allow casting between identical types.\n        - 'equiv': allow casting between identical and byte swapped types.\n        - 'safe': only allow \"safe\" casts.\n        - 'mostly-safe': allow \"safe casts\" and, for floating-point data types,\n          downcasts.\n        - 'same-kind': allow \"safe\" casts and casts within the same kind (e.g.,\n          between signed integers or between floats).\n        - 'unsafe': allow casting between all types (including between integers\n          and floats).\n\n        Default: 'safe'.\n\n    options.codegen: boolean (optional)\n        Boolean indicating whether to use code generation. Code generation can\n        boost performance, but may be problematic in browser contexts enforcing\n        a strict content security policy (CSP). Default: true.\n\n    options.mode: string (optional)\n        Specifies how to handle indices which exceed array dimensions. The\n        option may be one of the following values:\n\n        - 'throw': an ndarray instance throws an error when an index exceeds\n          array dimensions.\n        - 'normalize': an ndarray instance normalizes negative indices and\n          throws an error when an index exceeds array dimensions.\n        - 'wrap': an ndarray instance wraps around indices exceeding array\n          dimensions using modulo arithmetic.\n        - 'clamp', an ndarray instance sets an index exceeding array dimensions\n          to either `0` (minimum index) or the maximum index.\n\n        Default: 'throw'.\n\n    options.submode: Array<string> (optional)\n        Specifies how to handle subscripts which exceed array dimensions. If a\n        mode for a corresponding dimension is equal to\n\n        - 'throw': an ndarray instance throws an error when a subscript exceeds\n          array dimensions.\n        - 'normalize': an ndarray instance normalizes negative subscripts and\n          throws an error when a subscript exceeds array dimensions.\n        - 'wrap': an ndarray instance wraps around subscripts exceeding array\n          dimensions using modulo arithmetic.\n        - 'clamp': an ndarray instance sets a subscript exceeding array\n          dimensions to either `0` (minimum index) or the maximum index.\n\n        If the number of modes is fewer than the number of dimensions, the\n        function recycles modes using modulo arithmetic.\n\n        Default: [ options.mode ].\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether an array should be read-only. Default: false.\n\n    Returns\n    -------\n    out: ndarray\n        Multidimensional array.\n\n    Examples\n    --------\n    // Create a 2x2 matrix:\n    > var arr = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] )\n    <ndarray>\n\n    // Get an element using subscripts:\n    > var v = arr.get( 1, 1 )\n    4.0\n\n    // Get an element using a linear index:\n    > v = arr.iget( 3 )\n    4.0\n\n    // Set an element using subscripts:\n    > arr.set( 1, 1, 40.0 );\n    > arr.get( 1, 1 )\n    40.0\n\n    // Set an element using a linear index:\n    > arr.iset( 3, 99.0 );\n    > arr.get( 1, 1 )\n    99.0\n\n    See Also\n    --------\n    ndarray\n","array2buffer":"\narray2buffer( arr )\n    Allocates a buffer using an octet array.\n\n    Parameters\n    ----------\n    arr: Array<integer>\n        Array (or array-like object) of octets from which to copy.\n\n    Returns\n    -------\n    out: Buffer\n        Buffer instance.\n\n    Examples\n    --------\n    > var buf = array2buffer( [ 1, 2, 3, 4 ] )\n    <Buffer>[ 1, 2, 3, 4 ]\n\n    See Also\n    --------\n    Buffer, arraybuffer2buffer, copyBuffer, string2buffer\n","array2fancy":"\narray2fancy( x[, options] )\n    Converts an array to an object supporting fancy indexing.\n\n    An array supporting fancy indexing is an array which supports slicing via\n    indexing expressions for both retrieval and assignment.\n\n    A fancy array shares the *same* data as the provided input array. Hence, any\n    mutations to the returned array will affect the underlying input array and\n    vice versa.\n\n    For operations returning a new array (e.g., when slicing or invoking an\n    instance method), a fancy array returns a new fancy array having the same\n    configuration as specified by provided options.\n\n    A fancy array supports indexing using positive and negative integers (both\n    numeric literals and strings), Slice instances, subsequence expressions,\n    mask arrays, boolean arrays, and integer arrays.\n\n    A fancy array supports all properties and methods of the input array, and,\n    thus, a fancy array can be consumed by any API which supports array-like\n    objects.\n\n    Indexing expressions provide a convenient and powerful means for creating\n    and operating on array views; however, their use does entail a performance\n    cost. Indexing expressions are best suited for interactive use (e.g., in the\n    REPL) and scripting. For performance critical applications, prefer\n    equivalent functional APIs supporting array-like objects.\n\n    Fancy arrays support broadcasting in which assigned scalars and single-\n    element arrays are repeated (without additional memory allocation) to match\n    the length of a target array instance.\n\n    Fancy array broadcasting follows the same rules as for ndarrays.\n\n    Consequently, when assigning arrays to slices, the array on the right-hand-\n    side must be broadcast-compatible with number of elements in the slice.\n\n    Fancy arrays support (mostly) safe casts (i.e., any cast which can be\n    performed without overflow or loss of precision, with the exception of\n    floating-point arrays which are also allowed to downcast from higher\n    precision to lower precision).\n\n    When attempting to perform an unsafe cast, fancy arrays will raise an\n    exception.\n\n    When assigning a real-valued scalar to a complex number array (e.g.,\n    Complex128Array or Complex64Array), a fancy array will cast the real-valued\n    scalar to a complex number argument having an imaginary component equal to\n    zero.\n\n    In older JavaScript environments which do not support Proxy objects, the use\n    of indexing expressions is not supported.\n\n    Parameters\n    ----------\n    x: Array|TypedArray|Object\n        Input array.\n\n    options: Object (optional)\n        Function options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking. Default:\n        false.\n\n    options.cache: Object (optional)\n        Cache for resolving array index objects. Must have a 'get' method which\n        accepts a single argument: a string identifier associated with an array\n        index. If an array index associated with a provided identifier exists,\n        the 'get' method should return an object having the following\n        properties:\n\n        - data: the underlying index array.\n        - type: the index type. Must be either 'mask', 'bool', or 'int'.\n        - dtype: the data type of the underlying array.\n\n        If an array index is not associated with a provided identifier, the\n        'get' method should return `null`.\n\n        Default: `ArrayIndex`.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Output array supporting fancy indexing.\n\n    Examples\n    --------\n    > var y = array2fancy( [ 1, 2, 3, 4 ] );\n    > y[ '1::2' ]\n    [ 2, 4 ]\n    > y[ '::-1' ]\n    [ 4, 3, 2, 1 ]\n\n\narray2fancy.factory( [options] )\n    Returns a function for converting an array to an object supporting fancy\n    indexing.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking by default.\n        Default: false.\n\n    options.cache: Object (optional)\n        Cache for resolving array index objects. Must have a 'get' method which\n        accepts a single argument: a string identifier associated with an array\n        index. If an array index associated with a provided identifier exists,\n        the 'get' method should return an object having the following\n        properties:\n\n        - data: the underlying index array.\n        - type: the index type. Must be either 'mask', 'bool', or 'int'.\n        - dtype: the data type of the underlying array.\n\n        If an array index is not associated with a provided identifier, the\n        'get' method should return `null`.\n\n        Default: `ArrayIndex`.\n\n    Returns\n    -------\n    fcn: Function\n        Function for converting an array to an object supporting fancy indexing.\n\n    Examples\n    --------\n    > var f = array2fancy.factory();\n    > var y = f( [ 1, 2, 3, 4 ] );\n    > y[ '1::2' ]\n    [ 2, 4 ]\n    > y[ '::-1' ]\n    [ 4, 3, 2, 1 ]\n\n\narray2fancy.idx( x[, options] )\n    Wraps a provided array as an array index object.\n\n    For documentation and usage, see `ArrayIndex`.\n\n    Parameters\n    ----------\n    x: Array|TypedArray|Object\n        Input array.\n\n    options: Object (optional)\n        Function options.\n\n    options.persist: boolean (optional)\n        Boolean indicating whether to continue persisting an index object after\n        first usage. Default: false.\n\n    Returns\n    -------\n    out: ArrayIndex\n        ArrayIndex instance.\n\n    Examples\n    --------\n    > var idx = array2fancy.idx( [ 1, 2, 3, 4 ] );\n\n    See Also\n    --------\n    aslice, FancyArray\n","array2fancy.factory":"\narray2fancy.factory( [options] )\n    Returns a function for converting an array to an object supporting fancy\n    indexing.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking by default.\n        Default: false.\n\n    options.cache: Object (optional)\n        Cache for resolving array index objects. Must have a 'get' method which\n        accepts a single argument: a string identifier associated with an array\n        index. If an array index associated with a provided identifier exists,\n        the 'get' method should return an object having the following\n        properties:\n\n        - data: the underlying index array.\n        - type: the index type. Must be either 'mask', 'bool', or 'int'.\n        - dtype: the data type of the underlying array.\n\n        If an array index is not associated with a provided identifier, the\n        'get' method should return `null`.\n\n        Default: `ArrayIndex`.\n\n    Returns\n    -------\n    fcn: Function\n        Function for converting an array to an object supporting fancy indexing.\n\n    Examples\n    --------\n    > var f = array2fancy.factory();\n    > var y = f( [ 1, 2, 3, 4 ] );\n    > y[ '1::2' ]\n    [ 2, 4 ]\n    > y[ '::-1' ]\n    [ 4, 3, 2, 1 ]","array2fancy.idx":"\narray2fancy.idx( x[, options] )\n    Wraps a provided array as an array index object.\n\n    For documentation and usage, see `ArrayIndex`.\n\n    Parameters\n    ----------\n    x: Array|TypedArray|Object\n        Input array.\n\n    options: Object (optional)\n        Function options.\n\n    options.persist: boolean (optional)\n        Boolean indicating whether to continue persisting an index object after\n        first usage. Default: false.\n\n    Returns\n    -------\n    out: ArrayIndex\n        ArrayIndex instance.\n\n    Examples\n    --------\n    > var idx = array2fancy.idx( [ 1, 2, 3, 4 ] );\n\n    See Also\n    --------\n    aslice, FancyArray","array2iterator":"\narray2iterator( src[, mapFcn[, thisArg]] )\n    Returns an iterator which iterates over the elements of an array-like\n    object.\n\n    When invoked, an input function is provided three arguments:\n\n    - value: iterated value.\n    - index: iterated value index.\n    - src: source array-like object.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an array's `@@iterator` method, regardless of whether this method is\n    defined. To convert an array to an implementation defined iterator, invoke\n    this method directly.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Array-like object from which to create the iterator.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = array2iterator( [ 1, 2, 3, 4 ] );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    iterator2array, circarray2iterator, array2iteratorRight, stridedarray2iterator\n","array2iteratorRight":"\narray2iteratorRight( src[, mapFcn[, thisArg]] )\n    Returns an iterator which iterates from right to left over the elements of\n    an array-like object.\n\n    When invoked, an input function is provided three arguments:\n\n    - value: iterated value.\n    - index: iterated value index.\n    - src: source array-like object.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an array's `@@iterator` method, regardless of whether this method is\n    defined. To convert an array to an implementation defined iterator, invoke\n    this method directly.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Array-like object from which to create the iterator.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = array2iteratorRight( [ 1, 2, 3, 4 ] );\n    > var v = it.next().value\n    4\n    > v = it.next().value\n    3\n\n    See Also\n    --------\n    iterator2array, array2iterator\n","ArrayBuffer":"\nArrayBuffer( size )\n    Returns an array buffer having a specified number of bytes.\n\n    Buffer contents are initialized to 0.\n\n    Parameters\n    ----------\n    size: integer\n        Number of bytes.\n\n    Returns\n    -------\n    out: ArrayBuffer\n        An array buffer.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 5 )\n    <ArrayBuffer>\n\n\nArrayBuffer.length\n    Number of input arguments the constructor accepts.\n\n    Examples\n    --------\n    > ArrayBuffer.length\n    1\n\n\nArrayBuffer.isView( arr )\n    Returns a boolean indicating if provided an array buffer view.\n\n    Parameters\n    ----------\n    arr: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an input argument is a buffer view.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 10 );\n    > ArrayBuffer.isView( arr )\n    true\n\n\nArrayBuffer.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the array buffer.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 5 );\n    > buf.byteLength\n    5\n\n\nArrayBuffer.prototype.slice( [start[, end]] )\n    Copies the bytes of an array buffer to a new array buffer.\n\n    Parameters\n    ----------\n    start: integer (optional)\n        Index at which to start copying buffer contents (inclusive). If\n        negative, the index is relative to the end of the buffer.\n\n    end: integer (optional)\n        Index at which to stop copying buffer contents (exclusive). If negative,\n        the index is relative to the end of the buffer.\n\n    Returns\n    -------\n    out: ArrayBuffer\n        A new array buffer whose contents have been copied from the calling\n        array buffer.\n\n    Examples\n    --------\n    > var b1 = new ArrayBuffer( 10 );\n    > var b2 = b1.slice( 2, 6 );\n    > var bool = ( b1 === b2 )\n    false\n    > b2.byteLength\n    4\n\n    See Also\n    --------\n    Buffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, SharedArrayBuffer, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","ArrayBuffer.length":"\nArrayBuffer.length\n    Number of input arguments the constructor accepts.\n\n    Examples\n    --------\n    > ArrayBuffer.length\n    1","ArrayBuffer.isView":"\nArrayBuffer.isView( arr )\n    Returns a boolean indicating if provided an array buffer view.\n\n    Parameters\n    ----------\n    arr: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an input argument is a buffer view.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 10 );\n    > ArrayBuffer.isView( arr )\n    true","ArrayBuffer.prototype.byteLength":"\nArrayBuffer.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the array buffer.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 5 );\n    > buf.byteLength\n    5","ArrayBuffer.prototype.slice":"\nArrayBuffer.prototype.slice( [start[, end]] )\n    Copies the bytes of an array buffer to a new array buffer.\n\n    Parameters\n    ----------\n    start: integer (optional)\n        Index at which to start copying buffer contents (inclusive). If\n        negative, the index is relative to the end of the buffer.\n\n    end: integer (optional)\n        Index at which to stop copying buffer contents (exclusive). If negative,\n        the index is relative to the end of the buffer.\n\n    Returns\n    -------\n    out: ArrayBuffer\n        A new array buffer whose contents have been copied from the calling\n        array buffer.\n\n    Examples\n    --------\n    > var b1 = new ArrayBuffer( 10 );\n    > var b2 = b1.slice( 2, 6 );\n    > var bool = ( b1 === b2 )\n    false\n    > b2.byteLength\n    4\n\n    See Also\n    --------\n    Buffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, SharedArrayBuffer, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","arraybuffer2buffer":"\narraybuffer2buffer( buf[, byteOffset[, length]] )\n    Allocates a buffer from an ArrayBuffer.\n\n    The behavior of this function varies across Node.js versions due to changes\n    in the underlying Node.js APIs:\n\n    - <3.0.0: the function copies ArrayBuffer bytes to a new Buffer instance.\n    - >=3.0.0 and <5.10.0: if provided a byte offset, the function copies\n      ArrayBuffer bytes to a new Buffer instance; otherwise, the function\n      returns a view of an ArrayBuffer without copying the underlying memory.\n    - <6.0.0: if provided an empty ArrayBuffer, the function returns an empty\n      Buffer which is not an ArrayBuffer view.\n    - >=6.0.0: the function returns a view of an ArrayBuffer without copying\n      the underlying memory.\n\n    Parameters\n    ----------\n    buf: ArrayBuffer\n        Input array buffer.\n\n    byteOffset: integer (optional)\n        Index offset specifying the location of the first byte.\n\n    length: integer (optional)\n        Number of bytes to expose from the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Buffer\n        Buffer instance.\n\n    Examples\n    --------\n    > var ab = new ArrayBuffer( 10 )\n    <ArrayBuffer>\n    > var buf = arraybuffer2buffer( ab )\n    <Buffer>\n    > var len = buf.length\n    10\n    > buf = arraybuffer2buffer( ab, 2, 6 )\n    <Buffer>\n    > len = buf.length\n    6\n\n    See Also\n    --------\n    Buffer, array2buffer, copyBuffer, string2buffer\n","arrayCtors":"\narrayCtors( dtype )\n    Returns an array constructor.\n\n    The function returns constructors for the following data types:\n\n    - float32: single-precision floating-point numbers.\n    - float64: double-precision floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - complex128: double-precision complex floating-point numbers.\n    - bool: boolean values.\n    - generic: values of any type.\n    - int16: signed 16-bit integers.\n    - int32: signed 32-bit integers.\n    - int8: signed 8-bit integers.\n    - uint16: unsigned 16-bit integers.\n    - uint32: unsigned 32-bit integers.\n    - uint8: unsigned 8-bit integers.\n    - uint8c: unsigned clamped 8-bit integers.\n\n    Parameters\n    ----------\n    dtype: string\n        Data type.\n\n    Returns\n    -------\n    out: Function|null\n        Constructor.\n\n    Examples\n    --------\n    > var ctor = arrayCtors( 'float64' )\n    <Function>\n    > ctor = arrayCtors( 'float' )\n    null\n\n    See Also\n    --------\n    typedarrayCtors\n","arrayDataType":"\narrayDataType( array )\n    Returns the data type of an array.\n\n    If provided an argument having an unknown or unsupported type, the function\n    returns `null`.\n\n    Parameters\n    ----------\n    array: any\n        Input value.\n\n    Returns\n    -------\n    out: string|null\n        Data type.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 10 );\n    > var dt = arrayDataType( arr )\n    'float64'\n    > dt = arrayDataType( 'beep' )\n    null\n\n    See Also\n    --------\n    arrayDataTypes\n","arrayDataTypes":"\narrayDataTypes( [kind] )\n    Returns a list of array data types.\n\n    When not provided a data type \"kind\", the function returns an array\n    containing the following data types:\n\n    - float32: single-precision floating-point numbers.\n    - float64: double-precision floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - complex128: double-precision complex floating-point numbers.\n    - bool: boolean values.\n    - generic: values of any type.\n    - int16: signed 16-bit integers.\n    - int32: signed 32-bit integers.\n    - int8: signed 8-bit integers.\n    - uint16: unsigned 16-bit integers.\n    - uint32: unsigned 32-bit integers.\n    - uint8: unsigned 8-bit integers.\n    - uint8c: unsigned clamped 8-bit integers.\n\n    The function supports the following data type \"kinds\":\n\n    - floating_point: floating-point data types.\n    - real_floating_point: real-valued floating-point data types.\n    - complex_floating_point: complex-valued floating-point data types.\n    - boolean: boolean data types.\n    - integer: integer data types.\n    - signed_integer: signed integer data types.\n    - unsigned_integer: unsigned integer data types.\n    - real: real-valued data types.\n    - numeric: numeric data types.\n    - typed: \"typed\" data types.\n    - all: all data types.\n\n    Additionally, the function supports extending the \"kinds\" listed above by\n    appending a '_and_generic' suffix to the kind name (e.g., real_and_generic).\n\n    Parameters\n    ----------\n    kind: string (optional)\n        Data type kind.\n\n    Returns\n    -------\n    out: Array<string>\n        List of array data types.\n\n    Examples\n    --------\n    > var out = arrayDataTypes()\n    [...]\n    > out = arrayDataTypes( 'floating_point' )\n    [...]\n    > out = arrayDataTypes( 'floating_point_and_generic' )\n    [...]\n\n    See Also\n    --------\n    typedarrayDataTypes, ndarrayDataTypes\n","ArrayIndex":"\nArrayIndex( x[, options] )\n    Wraps a provided array as an array index object.\n\n    Array index instances have no explicit functionality; however, they are used\n    by \"fancy\" arrays for element retrieval and assignment.\n\n    By default, an instance is invalidated and removed from an internal cache\n    immediately after a consumer resolves the underlying data associated with an\n    instance using the `get` static method. Immediate invalidation and cache\n    removal ensures that references to the underlying array are not the source\n    of memory leaks.\n\n    Because instances leverage an internal cache implementing the Singleton\n    pattern, one must be sure to use the same constructor as consumers. If one\n    uses a different constructor, the consumer will *not* be able to resolve the\n    original wrapped array, as the consumer will attempt to resolve an instance\n    in the wrong internal cache.\n\n    Because non-persisted instances are freed after first use, in order to avoid\n    holding onto memory and to allow garbage collection, one should avoid\n    scenarios in which an instance is never used.\n\n    Parameters\n    ----------\n    x: Array|TypedArray|Object\n        Input array.\n\n    options: Object (optional)\n        Function options.\n\n    options.persist: boolean (optional)\n        Boolean indicating whether to continue persisting an index object after\n        first usage. Default: false.\n\n    Returns\n    -------\n    out: ArrayIndex\n        ArrayIndex instance.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n\n\nArrayIndex.free( id )\n    Frees the instance associated with a provided identifier.\n\n    Parameters\n    ----------\n    id: string\n        Instance identifier.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an instance was successfully freed.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > ArrayIndex.free( idx.id )\n    <boolean>\n\n\nArrayIndex.get( id )\n    Returns the array associated with the instance having a provided identifier.\n\n    Parameters\n    ----------\n    id: string\n        Instance identifier.\n\n    Returns\n    -------\n    out: Object\n        Object containing array data.\n\n    out.data: Array|TypedArray|Object\n        The underlying array associated with the provided identifier.\n\n    out.type: string\n        The type of array index.\n\n    out.dtype: string\n        The data type of the underlying array.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > ArrayIndex.get( idx.id )\n    {...}\n\n\nArrayIndex.prototype.data\n    Read-only property returning the underlying index array.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Array data.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.data\n    [ 1, 2, 3, 4 ]\n\n\nArrayIndex.prototype.dtype\n    Read-only property returning the underlying data type of the index array.\n\n    Returns\n    -------\n    out: string\n        Array data type.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.dtype\n    'generic'\n\n\nArrayIndex.prototype.id\n    Read-only property returning the unique identifier associated with an\n    instance.\n\n    Returns\n    -------\n    out: string\n        String identifier.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.id\n    <string>\n\n\nArrayIndex.prototype.isCached\n    Read-only property returning a boolean indicating whether an array index is\n    actively cached.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an array index is actively cached.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.isCached\n    true\n\n\nArrayIndex.prototype.type\n    Read-only property returning the array index type.\n\n    Returns\n    -------\n    out: string\n        Array index type.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.type\n    <string>\n\n\nArrayIndex.prototype.toString()\n    Serializes an instance as a string.\n\n    Returns\n    -------\n    str: string\n        Serialized string.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.toString()\n    <string>\n\n\nArrayIndex.prototype.toJSON()\n    Serializes an instance as a JSON object.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.toJSON()\n    { 'type': 'ArrayIndex', 'data': [ 1, 2, 3, 4 ] }\n\n    See Also\n    --------\n    array2fancy\n","ArrayIndex.free":"\nArrayIndex.free( id )\n    Frees the instance associated with a provided identifier.\n\n    Parameters\n    ----------\n    id: string\n        Instance identifier.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an instance was successfully freed.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > ArrayIndex.free( idx.id )\n    <boolean>","ArrayIndex.get":"\nArrayIndex.get( id )\n    Returns the array associated with the instance having a provided identifier.\n\n    Parameters\n    ----------\n    id: string\n        Instance identifier.\n\n    Returns\n    -------\n    out: Object\n        Object containing array data.\n\n    out.data: Array|TypedArray|Object\n        The underlying array associated with the provided identifier.\n\n    out.type: string\n        The type of array index.\n\n    out.dtype: string\n        The data type of the underlying array.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > ArrayIndex.get( idx.id )\n    {...}","ArrayIndex.prototype.data":"\nArrayIndex.prototype.data\n    Read-only property returning the underlying index array.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Array data.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.data\n    [ 1, 2, 3, 4 ]","ArrayIndex.prototype.dtype":"\nArrayIndex.prototype.dtype\n    Read-only property returning the underlying data type of the index array.\n\n    Returns\n    -------\n    out: string\n        Array data type.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.dtype\n    'generic'","ArrayIndex.prototype.id":"\nArrayIndex.prototype.id\n    Read-only property returning the unique identifier associated with an\n    instance.\n\n    Returns\n    -------\n    out: string\n        String identifier.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.id\n    <string>","ArrayIndex.prototype.isCached":"\nArrayIndex.prototype.isCached\n    Read-only property returning a boolean indicating whether an array index is\n    actively cached.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an array index is actively cached.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.isCached\n    true","ArrayIndex.prototype.type":"\nArrayIndex.prototype.type\n    Read-only property returning the array index type.\n\n    Returns\n    -------\n    out: string\n        Array index type.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.type\n    <string>","ArrayIndex.prototype.toString":"\nArrayIndex.prototype.toString()\n    Serializes an instance as a string.\n\n    Returns\n    -------\n    str: string\n        Serialized string.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.toString()\n    <string>","ArrayIndex.prototype.toJSON":"\nArrayIndex.prototype.toJSON()\n    Serializes an instance as a JSON object.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.toJSON()\n    { 'type': 'ArrayIndex', 'data': [ 1, 2, 3, 4 ] }\n\n    See Also\n    --------\n    array2fancy","arrayMinDataType":"\narrayMinDataType( value )\n    Returns the minimum array data type of the closest \"kind\" necessary for\n    storing a provided scalar value.\n\n    The function does *not* provide precision guarantees for non-integer-valued\n    numbers. In other words, the function returns the smallest possible\n    floating-point (i.e., inexact) data type for storing numbers having\n    decimals.\n\n    Parameters\n    ----------\n    value: any\n        Scalar value.\n\n    Returns\n    -------\n    dt: string\n        Array data type.\n\n    Examples\n    --------\n    > var dt = arrayMinDataType( 3.141592653589793 )\n    'float32'\n    > dt = arrayMinDataType( 3 )\n    'uint8'\n    > dt = arrayMinDataType( -3 )\n    'int8'\n    > dt = arrayMinDataType( '-3' )\n    'generic'\n\n    See Also\n    --------\n    arrayDataTypes, arrayPromotionRules, arraySafeCasts\n","arrayMostlySafeCasts":"\narrayMostlySafeCasts( [dtype] )\n    Returns a list of array data types to which a provided array data type can\n    be safely cast and, for floating-point data types, can be downcast.\n\n    If not provided an array data type, the function returns a casting table.\n\n    If provided an unrecognized array data type, the function returns `null`.\n\n    Parameters\n    ----------\n    dtype: any (optional)\n        Array data type value.\n\n    Returns\n    -------\n    out: Object|Array<string>|null\n        Array data types to which a data type can be cast.\n\n    Examples\n    --------\n    > var out = arrayMostlySafeCasts( 'float32' )\n    <Array>\n\n    See Also\n    --------\n    convertArray, convertArraySame, arrayDataTypes, arraySafeCasts, arraySameKindCasts, ndarrayMostlySafeCasts\n","arrayNextDataType":"\narrayNextDataType( [dtype] )\n    Returns the next larger array data type of the same kind.\n\n    If not provided a data type, the function returns a table.\n\n    If a data type does not have a next larger data type or the next larger type\n    is not supported, the function returns `-1`.\n\n    If provided an unrecognized data type, the function returns `null`.\n\n    Parameters\n    ----------\n    dtype: string (optional)\n        Array data type.\n\n    Returns\n    -------\n    out: Object|string|integer|null\n        Next larger type(s).\n\n    Examples\n    --------\n    > var out = arrayNextDataType( 'float32' )\n    'float64'\n\n    See Also\n    --------\n    arrayDataType, arrayDataTypes\n","arrayPromotionRules":"\narrayPromotionRules( [dtype1, dtype2] )\n    Returns the array data type with the smallest size and closest \"kind\" to\n    which array data types can be safely cast.\n\n    If not provided data types, the function returns a type promotion table.\n\n    If a data type to which data types can be safely cast does *not* exist (or\n    is not supported), the function returns `-1`.\n\n    If provided an unrecognized data type, the function returns `null`.\n\n    Parameters\n    ----------\n    dtype1: any (optional)\n        Array data type.\n\n    dtype2: any (optional)\n        Array data type.\n\n    Returns\n    -------\n    out: Object|string|integer|null\n        Promotion rule(s).\n\n    Examples\n    --------\n    > var out = arrayPromotionRules( 'float32', 'int32' )\n    'float64'\n\n    See Also\n    --------\n    arrayDataTypes, arraySafeCasts, ndarrayPromotionRules\n","arraySafeCasts":"\narraySafeCasts( [dtype] )\n    Returns a list of array data types to which a provided array data type can\n    be safely cast.\n\n    If not provided an array data type, the function returns a casting table.\n\n    If provided an unrecognized array data type, the function returns `null`.\n\n    Parameters\n    ----------\n    dtype: any (optional)\n        Array data type.\n\n    Returns\n    -------\n    out: Object|Array<string>|null\n        Array data types to which a data type can be safely cast.\n\n    Examples\n    --------\n    > var out = arraySafeCasts( 'float32' )\n    <Array>\n\n    See Also\n    --------\n    convertArray, convertArraySame, arrayDataTypes, arrayMostlySafeCasts, arraySameKindCasts, ndarraySafeCasts\n","arraySameKindCasts":"\narraySameKindCasts( [dtype] )\n    Returns a list of array data types to which a provided array data type can\n    be safely cast or cast within the same \"kind\".\n\n    If not provided an array data type, the function returns a casting table.\n\n    If provided an unrecognized array data type, the function returns `null`.\n\n    Parameters\n    ----------\n    dtype: any (optional)\n        Array data type.\n\n    Returns\n    -------\n    out: Object|Array<string>|null\n        Array data types to which a data type can be safely cast or cast within\n        the same \"kind\".\n\n    Examples\n    --------\n    > var out = arraySameKindCasts( 'float32' )\n    <Array>\n\n    See Also\n    --------\n    convertArray, convertArraySame, arrayDataTypes, arraySafeCasts, ndarraySameKindCasts\n","arrayShape":"\narrayShape( arr )\n    Determines array dimensions.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject\n        Input array.\n\n    Returns\n    -------\n    out: Array\n        Array shape.\n\n    Examples\n    --------\n    > var out = arrayShape( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n    [ 2, 3 ]\n\n    See Also\n    --------\n    ndarray\n","arrayStream":"\narrayStream( src[, options] )\n    Creates a readable stream from an array-like object.\n\n    In object mode, `null` is a reserved value. If an array contains `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or filter `null` values\n    prior to invocation.\n\n    In binary mode, if an array contains `undefined` values, the stream will\n    emit an error. Consider providing a custom serialization function or\n    filtering `undefined` values prior to invocation.\n\n    If a serialization function fails to return a string or Buffer, the stream\n    emits an error.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Source value.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing the stream.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize streamed\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    options.dir: integer (optional)\n        Iteration direction. If set to `-1`, a stream iterates over elements\n        from right-to-left. Default: 1.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var s = arrayStream( [ 1, 2, 3 ] );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\narrayStream.factory( [options] )\n    Returns a function for creating readable streams from array-like objects.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing streaming.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize streamed\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    options.dir: integer (optional)\n        Iteration direction. If set to `-1`, a stream iterates over elements\n        from right-to-left. Default: 1.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = arrayStream.factory( opts );\n\n\narrayStream.objectMode( src[, options] )\n    Returns an \"objectMode\" readable stream from an array-like object.\n\n    In object mode, `null` is a reserved value. If an array contains `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or filter `null` values\n    prior to invocation.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Source value.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before pausing streaming.\n\n    options.dir: integer (optional)\n        Iteration direction. If set to `-1`, a stream iterates over elements\n        from right-to-left. Default: 1.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var s = arrayStream.objectMode( [ 1, 2, 3 ] );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    circularArrayStream, iteratorStream, stridedArrayStream\n","arrayStream.factory":"\narrayStream.factory( [options] )\n    Returns a function for creating readable streams from array-like objects.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing streaming.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize streamed\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    options.dir: integer (optional)\n        Iteration direction. If set to `-1`, a stream iterates over elements\n        from right-to-left. Default: 1.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = arrayStream.factory( opts );","arrayStream.objectMode":"\narrayStream.objectMode( src[, options] )\n    Returns an \"objectMode\" readable stream from an array-like object.\n\n    In object mode, `null` is a reserved value. If an array contains `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or filter `null` values\n    prior to invocation.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Source value.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before pausing streaming.\n\n    options.dir: integer (optional)\n        Iteration direction. If set to `-1`, a stream iterates over elements\n        from right-to-left. Default: 1.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var s = arrayStream.objectMode( [ 1, 2, 3 ] );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    circularArrayStream, iteratorStream, stridedArrayStream","arrayview2iterator":"\narrayview2iterator( src[, begin[, end]][, mapFcn[, thisArg]] )\n    Returns an iterator which iterates over the elements of an array-like object\n    view.\n\n    When invoked, an input function is provided four arguments:\n\n    - value: iterated value.\n    - index: iterated value index.\n    - n: iteration count (zero-based).\n    - src: source array-like object.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an array's `@@iterator` method, regardless of whether this method is\n    defined. To convert an array to an implementation defined iterator, invoke\n    this method directly.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Array-like object from which to create the iterator.\n\n    begin: integer (optional)\n        Starting index (inclusive). When negative, determined relative to the\n        last element. Default: 0.\n\n    end: integer (optional)\n        Ending index (non-inclusive). When negative, determined relative to the\n        last element. Default: src.length.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = arrayview2iterator( [ 1, 2, 3, 4 ], 1, 3 );\n    > var v = it.next().value\n    2\n    > v = it.next().value\n    3\n\n    See Also\n    --------\n    iterator2array, array2iterator, stridedarray2iterator, arrayview2iteratorRight\n","arrayview2iteratorRight":"\narrayview2iteratorRight( src[, begin[, end]][, mapFcn[, thisArg]] )\n    Returns an iterator which iterates from right to left over the elements of\n    an array-like object view.\n\n    When invoked, an input function is provided four arguments:\n\n    - value: iterated value.\n    - index: iterated value index.\n    - n: iteration count (zero-based).\n    - src: source array-like object.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an array's `@@iterator` method, regardless of whether this method is\n    defined. To convert an array to an implementation defined iterator, invoke\n    this method directly.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Array-like object from which to create the iterator.\n\n    begin: integer (optional)\n        Starting index (inclusive). When negative, determined relative to the\n        last element. Default: 0.\n\n    end: integer (optional)\n        Ending index (non-inclusive). When negative, determined relative to the\n        last element. Default: src.length.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = arrayview2iteratorRight( [ 1, 2, 3, 4 ], 1, 3 );\n    > var v = it.next().value\n    3\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    iterator2array, array2iteratorRight, stridedarray2iterator, arrayview2iterator\n","aslice":"\naslice( x[, start[, end]] )\n    Returns a shallow copy of a portion of an array.\n\n    If provided an array-like object having a `slice` method, the function\n    defers execution to that method and assumes that the method has the\n    following signature:\n\n      x.slice( start, end )\n\n    If provided an array-like object without a `slice` method, the function\n    copies input array elements to a new generic array.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    start: integer (optional)\n        Starting index (inclusive). Default: 0.\n\n    end: integer (optional)\n        Ending index (exclusive). Default: x.length.\n\n    Returns\n    -------\n    out: Array|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var out = aslice( [ 1, 2, 3, 4 ] )\n    [ 1, 2, 3, 4 ]\n    > out = aslice( [ 1, 2, 3, 4 ], 1 )\n    [ 2, 3, 4 ]\n    > out = aslice( [ 1, 2, 3, 4 ], 1, 3 )\n    [ 2, 3 ]\n\n    See Also\n    --------\n    atake\n","AsyncIteratorSymbol":"\nAsyncIteratorSymbol\n    Async iterator symbol.\n\n    This symbol specifies the default async iterator for an object.\n\n    The symbol is only supported in ES2018+ environments. For non-supporting\n    environments, the value is `null`.\n\n    Examples\n    --------\n    > var s = AsyncIteratorSymbol\n\n    See Also\n    --------\n    Symbol, IteratorSymbol\n","atake":"\natake( x, indices[, options] )\n    Takes elements from an array.\n\n    If `indices` is an empty array, the function returns an empty array.\n\n    Parameters\n    ----------\n    x: Array|TypedArray|Object\n        Input array.\n\n    indices: ArrayLikeObject<integer>\n        List of element indices.\n\n    options: Object (optional)\n        Function options.\n\n    options.mode: string (optional)\n        Specifies how to handle an index outside the interval [0, max], where\n        `max` is the maximum possible array index. If equal to 'throw', the\n        function throws an error. If equal to 'normalize', the function throws\n        an error if provided an out-of-bounds normalized index. If equal to\n        'wrap', the function wraps around an index using modulo arithmetic. If\n        equal to 'clamp', the function sets an index to either 0 (minimum index)\n        or the maximum index. Default: 'normalize'.\n\n    Returns\n    -------\n    out: Array|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = [ 1, 2, 3, 4 ];\n    > var y = atake( x, [ 1, 3 ] )\n    [ 2, 4 ]\n\n    See Also\n    --------\n    aput, aslice\n","azeros":"\nazeros( length[, dtype] )\n    Returns a zero-filled array having a specified length.\n\n    The function supports the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754).\n    - float32: single-precision floating-point numbers (IEEE 754).\n    - complex128: double-precision complex floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n    - generic: generic JavaScript values.\n\n    The default array data type is `float64`.\n\n    Parameters\n    ----------\n    length: integer\n        Array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = azeros( 2 )\n    <Float64Array>[ 0.0, 0.0 ]\n    > arr = azeros( 2, 'float32' )\n    <Float32Array>[ 0.0, 0.0 ]\n\n    See Also\n    --------\n    aempty, afull, anans, aones, azerosLike, ndzeros\n","azerosLike":"\nazerosLike( x[, dtype] )\n    Returns a zero-filled array having the same length and data type as a\n    provided input array.\n\n    The function supports the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754).\n    - float32: single-precision floating-point numbers (IEEE 754).\n    - complex128: double-precision complex floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n    - generic: generic JavaScript values.\n\n    Parameters\n    ----------\n    x: TypedArray|Array\n        Input array.\n\n    dtype: string (optional)\n        Data type. If not provided, the output array data type is inferred from\n        the input array.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var x = new Float64Array( 2 );\n    > var y = azerosLike( x )\n    <Float64Array>[ 0.0, 0.0 ]\n    > y = azerosLike( x, 'float32' )\n    <Float32Array>[ 0.0, 0.0 ]\n\n    See Also\n    --------\n    aemptyLike, afullLike, anansLike, aonesLike, azeros, ndzerosLike\n","azeroTo":"\nazeroTo( n[, dtype] )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from zero.\n\n    The function supports the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754).\n    - float32: single-precision floating-point numbers (IEEE 754).\n    - complex128: double-precision complex floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n    - generic: generic JavaScript values.\n\n    The default array data type is `float64`.\n\n    If `n` is equal to zero, the function returns an empty array.\n\n    Parameters\n    ----------\n    n: integer\n        Number of elements.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = azeroTo( 2 )\n    <Float64Array>[ 0.0, 1.0 ]\n    > arr = azeroTo( 2, 'float32' )\n    <Float32Array>[ 0.0, 1.0 ]\n\n    See Also\n    --------\n    aempty, afull, aoneTo, azeroToLike, azeros\n","azeroToLike":"\nazeroToLike( x[, dtype] )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from zero and having the same length and data type as a provided\n    input array.\n\n    The function supports the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754).\n    - float32: single-precision floating-point numbers (IEEE 754).\n    - complex128: double-precision complex floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n    - generic: generic JavaScript values.\n\n    Parameters\n    ----------\n    x: TypedArray|Array\n        Input array.\n\n    dtype: string (optional)\n        Data type. If not provided, the output array data type is inferred from\n        the input array.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = azeroToLike( [ 0, 0 ] )\n    [ 0, 1 ]\n    > arr = azeroToLike( [ 0, 0 ], 'float32' )\n    <Float32Array>[ 0.0, 1.0 ]\n\n    See Also\n    --------\n    aemptyLike, afullLike, anansLike, aoneToLike, aonesLike, azeroTo, azerosLike\n","bartlettTest":"\nbartlettTest( ...x[, options] )\n    Computes Bartlett’s test for equal variances.\n\n    Parameters\n    ----------\n    x: ...Array\n        Measured values.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.groups: Array (optional)\n        Array of group indicators.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.method: string\n        Name of test.\n\n    out.df: Object\n        Degrees of freedom.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    // Data from Hollander & Wolfe (1973), p. 116:\n    > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n    > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n    > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n    > var out = bartlettTest( x, y, z )\n\n    > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n    ...     3.8, 2.7, 4.0, 2.4,\n    ...     2.8, 3.4, 3.7, 2.2, 2.0\n    ... ];\n    > var groups = [\n    ...     'a', 'a', 'a', 'a', 'a',\n    ...     'b', 'b', 'b', 'b',\n    ...     'c', 'c', 'c', 'c', 'c'\n    ... ];\n    > out = bartlettTest( arr, { 'groups': groups } )\n\n    See Also\n    --------\n    vartest, leveneTest\n","base.abs":"\nbase.abs( x )\n    Computes the absolute value of a double-precision floating-point number `x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Absolute value.\n\n    Examples\n    --------\n    > var y = base.abs( -1.0 )\n    1.0\n    > y = base.abs( 2.0 )\n    2.0\n    > y = base.abs( 0.0 )\n    0.0\n    > y = base.abs( -0.0 )\n    0.0\n    > y = base.abs( NaN )\n    NaN\n\n    See Also\n    --------\n    base.abs2, base.absf, base.labs\n","base.abs2":"\nbase.abs2( x )\n    Computes the squared absolute value of a double-precision floating-point\n    `x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Squared absolute value.\n\n    Examples\n    --------\n    > var y = base.abs2( -1.0 )\n    1.0\n    > y = base.abs2( 2.0 )\n    4.0\n    > y = base.abs2( 0.0 )\n    0.0\n    > y = base.abs2( -0.0 )\n    0.0\n    > y = base.abs2( NaN )\n    NaN\n\n    See Also\n    --------\n    base.abs, base.abs2f\n","base.abs2f":"\nbase.abs2f( x )\n    Computes the squared absolute value of a single-precision floating-point\n    `x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Squared absolute value.\n\n    Examples\n    --------\n    > var y = base.abs2f( -1.0 )\n    1.0\n    > y = base.abs2f( 2.0 )\n    4.0\n    > y = base.abs2f( 0.0 )\n    0.0\n    > y = base.abs2f( -0.0 )\n    0.0\n    > y = base.abs2f( NaN )\n    NaN\n\n    See Also\n    --------\n    base.abs2, base.absf\n","base.absdiff":"\nbase.absdiff( x, y )\n    Computes the absolute difference.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Absolute difference.\n\n    Examples\n    --------\n    > var d = base.absdiff( 2.0, 5.0 )\n    3.0\n    > d = base.absdiff( -1.0, 3.14 )\n    ~4.14\n    > d = base.absdiff( 10.1, -2.05 )\n    ~12.15\n    > d = base.absdiff( -0.0, 0.0 )\n    +0.0\n    > d = base.absdiff( NaN, 5.0 )\n    NaN\n    > d = base.absdiff( PINF, NINF )\n    Infinity\n    > d = base.absdiff( PINF, PINF )\n    NaN\n\n    See Also\n    --------\n    base.reldiff, base.epsdiff\n","base.absf":"\nbase.absf( x )\n    Computes the absolute value of a single-precision floating-point number `x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Absolute value.\n\n    Examples\n    --------\n    > var y = base.absf( -1.0 )\n    1.0\n    > y = base.absf( 2.0 )\n    2.0\n    > y = base.absf( 0.0 )\n    0.0\n    > y = base.absf( -0.0 )\n    0.0\n    > y = base.absf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.abs, base.abs2f, base.labs\n","base.acartesianPower":"\nbase.acartesianPower( x, n )\n    Returns the Cartesian power.\n\n    If provided an empty array, the function returns an empty array.\n\n    If `n` is less than or equal to zero, the function returns an empty array.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    n: integer\n        Power.\n\n    Returns\n    -------\n    out: Array<Array>\n        Cartesian product.\n\n    Examples\n    --------\n    > var x = [ 1, 2 ];\n    > var out = base.acartesianPower( x, 2 )\n    [ [ 1, 1 ], [ 1, 2 ], [ 2, 1 ], [ 2, 2 ] ]\n\n    See Also\n    --------\n    acartesianPower, base.acartesianProduct, base.acartesianSquare\n","base.acartesianProduct":"\nbase.acartesianProduct( x1, x2 )\n    Returns the Cartesian product.\n\n    If provided one or more empty arrays, the function returns an empty array.\n\n    Parameters\n    ----------\n    x1: ArrayLikeObject\n        First input array.\n\n    x2: ArrayLikeObject\n        Second input array.\n\n    Returns\n    -------\n    out: Array<Array>\n        Cartesian product.\n\n    Examples\n    --------\n    > var x1 = [ 1, 2 ];\n    > var x2 = [ 3, 4 ];\n    > var out = base.acartesianProduct( x1, x2 )\n    [ [ 1, 3 ], [ 1, 4 ], [ 2, 3 ], [ 2, 4 ] ]\n\n    See Also\n    --------\n    acartesianProduct, base.acartesianPower, base.acartesianSquare\n","base.acartesianSquare":"\nbase.acartesianSquare( x )\n    Returns the Cartesian square.\n\n    If provided an empty array, the function returns an empty array.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    Returns\n    -------\n    out: Array<Array>\n        Cartesian product.\n\n    Examples\n    --------\n    > var x = [ 1, 2 ];\n    > var out = base.acartesianSquare( x )\n    [ [ 1, 1 ], [ 1, 2 ], [ 2, 1 ], [ 2, 2 ] ]\n\n    See Also\n    --------\n    acartesianSquare, base.acartesianPower, base.acartesianProduct\n","base.acos":"\nbase.acos( x )\n    Compute the arccosine of a double-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arccosine (in radians).\n\n    Examples\n    --------\n    > var y = base.acos( 1.0 )\n    0.0\n    > y = base.acos( 0.707 )\n    ~0.7855\n    > y = base.acos( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acosh, base.asin, base.atan\n","base.acosd":"\nbase.acosd( x )\n    Computes the arccosine (in degrees) of a double-precision floating-point \n    number.\n\n    If `|x| > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arccosine (in degrees).\n\n    Examples\n    --------\n    > var y = base.acosd( 0.0 )\n    90.0\n    > y = base.acosd( PI/6.0 )\n    ~58.43\n    > y = base.acosd( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acos, base.acosh, base.asind, base.atand\n","base.acosf":"\nbase.acosf( x )\n    Computes the arccosine of a single-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arccosine (in radians).\n\n    Examples\n    --------\n    > var y = base.acosf( 1.0 )\n    0.0\n    > y = base.acosf( 0.707 )\n    ~0.7855\n    > y = base.acosf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acos, base.acosh, base.asinf, base.atanf\n","base.acosh":"\nbase.acosh( x )\n    Computes the hyperbolic arccosine of a double-precision floating-point\n    number.\n\n    If `x < 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Hyperbolic arccosine.\n\n    Examples\n    --------\n    > var y = base.acosh( 1.0 )\n    0.0\n    > y = base.acosh( 2.0 )\n    ~1.317\n    > y = base.acosh( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acos, base.asinh, base.atanh\n","base.acot":"\nbase.acot( x )\n    Computes the inverse cotangent of a double-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Inverse cotangent (in radians).\n\n    Examples\n    --------\n    > var y = base.acot( 2.0 )\n    ~0.4636\n    > y = base.acot( 0.0 )\n    ~1.5708\n    > y = base.acot( 0.5 )\n    ~1.1071\n    > y = base.acot( 1.0 )\n    ~0.7854\n    > y = base.acot( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acoth, base.atan, base.cot\n","base.acotd":"\nbase.acotd( x )\n    Computes the arccotangent (in degrees) of a double-precision floating-point\n    number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arccotangent (in degrees).\n\n    Examples\n    --------\n    > var y = base.acotd( 0.0 )\n    90.0\n    > y = base.acotd( PI/6.0 )\n    ~62.36\n    > y = base.acotd( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acot, base.acoth, base.atand, base.cotd\n","base.acotf":"\nbase.acotf( x )\n    Computes the inverse cotangent of a single-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Inverse cotangent (in radians).\n\n    Examples\n    --------\n    > var y = base.acotf( 2.0 )\n    ~0.4636\n    > y = base.acotf( 0.0 )\n    ~1.5708\n    > y = base.acotf( 0.5 )\n    ~1.1071\n    > y = base.acotf( 1.0 )\n    ~0.7854\n    > y = base.acotf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acot, base.acoth, base.atanf\n","base.acoth":"\nbase.acoth( x )\n    Computes the inverse hyperbolic cotangent of a double-precision floating-\n    point number.\n\n    The domain of the inverse hyperbolic cotangent is the union of the intervals\n    (-inf,-1] and [1,inf).\n\n    If provided a value on the open interval (-1,1), the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Inverse hyperbolic cotangent.\n\n    Examples\n    --------\n    > var y = base.acoth( 2.0 )\n    ~0.5493\n    > y = base.acoth( 0.0 )\n    NaN\n    > y = base.acoth( 0.5 )\n    NaN\n    > y = base.acoth( 1.0 )\n    Infinity\n    > y = base.acoth( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acosh, base.acot, base.asinh, base.atanh\n","base.acovercos":"\nbase.acovercos( x )\n    Computes the inverse coversed cosine.\n\n    The inverse coversed cosine is defined as `asin(1+x)`.\n\n    If `x < -2`, `x > 0`, or `x` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Inverse coversed cosine.\n\n    Examples\n    --------\n    > var y = base.acovercos( -1.5 )\n    ~-0.5236\n    > y = base.acovercos( -0.0 )\n    ~1.5708\n\n    See Also\n    --------\n    base.acoversin, base.avercos, base.covercos, base.vercos\n","base.acoversin":"\nbase.acoversin( x )\n    Computes the inverse coversed sine.\n\n    The inverse coversed sine is defined as `asin(1-x)`.\n\n    If `x < 0`, `x > 2`, or `x` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Inverse coversed sine.\n\n    Examples\n    --------\n    > var y = base.acoversin( 1.5 )\n    ~-0.5236\n    > y = base.acoversin( 0.0 )\n    ~1.5708\n\n    See Also\n    --------\n    base.acovercos, base.aversin, base.coversin, base.versin\n","base.acsc":"\nbase.acsc( x )\n    Computes the arccosecant of a number.\n\n    If `|x| < 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arccosecant (in radians).\n\n    Examples\n    --------\n    > var y = base.acsc( 1.0 )\n    ~1.57\n    > y = base.acsc( PI )\n    ~0.32\n    > y = base.acsc( -PI )\n    ~-0.32\n    > y = base.acsc( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acot, base.acsch, base.asec, base.asin, base.csc\n","base.acscd":"\nbase.acscd( x )\n    Computes the arccosecant of (in degrees) a double-precision floating-point\n    number.\n\n    If `x` does not satisy `x >= 1` or `x <= -1`, the function returns NaN.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arccosecant (in degrees).\n\n    Examples\n    --------\n    > var y = base.acscd( 0.0 )\n    NaN\n    > y = base.acscd( PI/6.0 )\n    NaN\n    > y = base.acscd( 1 )\n    90.0\n    > y = base.acscd( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acsc, base.acsch, base.asecd, base.asind, base.cscd\n","base.acscdf":"\nbase.acscdf( x )\n    Computes the arccosecant (in degrees) of a single-precision floating-point\n    number.\n\n    If `x` does not satisy `x >= 1` or `x <= -1`, the function returns NaN.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arccosecant (in degrees).\n\n    Examples\n    --------\n    > var y = base.acscdf( 0.0 )\n    NaN\n    > y = base.acscdf( 3.1415927410125732 / 6.0 )\n    NaN\n    > y = base.acscdf( 1.0 )\n    90.0\n    > y = base.acscdf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acsc, base.acsch, base.asecdf, base.asindf\n","base.acscf":"\nbase.acscf( x )\n    Computes the arccosecant of a single-precision floating-point number.\n\n    If `|x| < 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arccosecant (in radians).\n\n    Examples\n    --------\n    > var y = base.acscf( 1.0 )\n    ~1.57\n    > y = base.acscf( 3.141592653589793 )\n    ~0.32\n    > y = base.acscf( -3.141592653589793 )\n    ~-0.32\n    > y = base.acscf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acsc, base.acsch, base.asecf, base.asinf\n","base.acsch":"\nbase.acsch( x )\n    Computes the hyperbolic arccosecant of a number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Hyperbolic arccosecant.\n\n    Examples\n    --------\n    > var y = base.acsch( 0.0 )\n    Infinity\n    > y = base.acsch( -1.0 )\n    ~-0.881\n    > y = base.acsch( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acoth, base.acsc, base.asech, base.asinh, base.csc, base.csch\n","base.add":"\nbase.add( x, y )\n    Computes the sum of two double-precision floating-point numbers `x` and `y`.\n\n    Parameters\n    ----------\n    x: number\n        First input value.\n\n    y: number\n        Second input value.\n\n    Returns\n    -------\n    z: number\n        Sum.\n\n    Examples\n    --------\n    > var v = base.add( -1.0, 5.0 )\n    4.0\n    > v = base.add( 2.0, 5.0 )\n    7.0\n    > v = base.add( 0.0, 5.0 )\n    5.0\n    > v = base.add( -0.0, 0.0 )\n    0.0\n    > v = base.add( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.div, base.mul, base.sub\n","base.add3":"\nbase.add3( x, y, z )\n    Computes the sum of three double-precision floating-point numbers.\n\n    Parameters\n    ----------\n    x: number\n        First input value.\n\n    y: number\n        Second input value.\n\n    z: number\n        Third input value.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    > var v = base.add3( -1.0, 5.0, 2.0 )\n    6.0\n    > v = base.add3( 2.0, 5.0, 2.0 )\n    9.0\n    > v = base.add3( 0.0, 5.0, 2.0 )\n    7.0\n    > v = base.add3( -0.0, 0.0, -0.0 )\n    0.0\n    > v = base.add3( NaN, NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.add\n","base.add4":"\nbase.add4( x, y, z, w )\n    Computes the sum of four double-precision floating-point numbers.\n\n    Parameters\n    ----------\n    x: number\n        First input value.\n\n    y: number\n        Second input value.\n\n    z: number\n        Third input value.\n\n    w: number\n        Fourth input value.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    > var v = base.add4( -1.0, 5.0, 2.0, -3.0 )\n    3.0\n    > v = base.add4( 2.0, 5.0, 2.0, -3.0 )\n    6.0\n    > v = base.add4( 0.0, 5.0, 2.0, -3.0 )\n    4.0\n    > v = base.add4( -0.0, 0.0, -0.0, -0.0 )\n    0.0\n    > v = base.add4( NaN, NaN, NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.add\n","base.add5":"\nbase.add5( x, y, z, w, u )\n    Computes the sum of five double-precision floating-point numbers.\n\n    Parameters\n    ----------\n    x: number\n        First input value.\n\n    y: number\n        Second input value.\n\n    z: number\n        Third input value.\n\n    w: number\n        Fourth input value.\n\n    u: number\n        Fifth input value.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    > var v = base.add5( -1.0, 5.0, 2.0, -3.0, 4.0 )\n    7.0\n    > v = base.add5( 2.0, 5.0, 2.0, -3.0, 4.0 )\n    10.0\n    > v = base.add5( 0.0, 5.0, 2.0, -3.0, 4.0 )\n    8.0\n    > v = base.add5( -0.0, 0.0, -0.0, -0.0, -0.0 )\n    0.0\n    > v = base.add5( NaN, NaN, NaN, NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.add\n","base.addf":"\nbase.addf( x, y )\n    Computes the sum of two single-precision floating-point numbers `x` and `y`.\n\n    Parameters\n    ----------\n    x: number\n        First input value.\n\n    y: number\n        Second input value.\n\n    Returns\n    -------\n    z: number\n        Sum.\n\n    Examples\n    --------\n    > var v = base.addf( -1.0, 5.0 )\n    4.0\n    > v = base.addf( 2.0, 5.0 )\n    7.0\n    > v = base.addf( 0.0, 5.0 )\n    5.0\n    > v = base.addf( -0.0, 0.0 )\n    0.0\n    > v = base.addf( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.add, base.divf, base.mulf, base.subf\n","base.afilled":"\nbase.afilled( value, len )\n    Returns a filled \"generic\" array.\n\n    Parameters\n    ----------\n    value: any\n        Fill value.\n\n    len: integer\n        Array length.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.afilled( 0.0, 3 )\n    [ 0.0, 0.0, 0.0 ]\n\n","base.afilled2d":"\nbase.afilled2d( value, shape )\n    Returns a filled two-dimensional nested array.\n\n    Parameters\n    ----------\n    value: any\n        Fill value.\n\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.afilled2d( 0.0, [ 1, 3 ] )\n    [ [ 0.0, 0.0, 0.0 ] ]\n\n","base.afilled2dBy":"\nbase.afilled2dBy( shape, clbk[, thisArg] )\n    Returns a filled two-dimensional nested array according to a provided\n    callback function.\n\n    The callback function is provided one argument:\n\n    - indices: current array element indices.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function clbk() { return 1.0; };\n    > var out = base.afilled2dBy( [ 1, 3 ], clbk )\n    [ [ 1.0, 1.0, 1.0 ] ]\n\n    See Also\n    --------\n    base.afilled2d\n","base.afilled3d":"\nbase.afilled3d( value, shape )\n    Returns a filled three-dimensional nested array.\n\n    Parameters\n    ----------\n    value: any\n        Fill value.\n\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.afilled3d( 0.0, [ 1, 1, 3 ] )\n    [ [ [ 0.0, 0.0, 0.0 ] ] ]\n\n","base.afilled3dBy":"\nbase.afilled3dBy( shape, clbk[, thisArg] )\n    Returns a filled three-dimensional nested array according to a provided\n    callback function.\n\n    The callback function is provided one argument:\n\n    - indices: current array element indices.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function clbk() { return 1.0; };\n    > var out = base.afilled3dBy( [ 1, 1, 3 ], clbk )\n    [ [ [ 1.0, 1.0, 1.0 ] ] ]\n\n    See Also\n    --------\n    base.afilled3d\n","base.afilled4d":"\nbase.afilled4d( value, shape )\n    Returns a filled four-dimensional nested array.\n\n    Parameters\n    ----------\n    value: any\n        Fill value.\n\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.afilled4d( 0.0, [ 1, 1, 1, 3 ] )\n    [ [ [ [ 0.0, 0.0, 0.0 ] ] ] ]\n\n","base.afilled4dBy":"\nbase.afilled4dBy( shape, clbk[, thisArg] )\n    Returns a filled four-dimensional nested array according to a provided\n    callback function.\n\n    The callback function is provided one argument:\n\n    - indices: current array element indices.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function clbk() { return 1.0; };\n    > var out = base.afilled4dBy( [ 1, 1, 1, 3 ], clbk )\n    [ [ [ [ 1.0, 1.0, 1.0 ] ] ] ]\n\n    See Also\n    --------\n    base.afilled4d\n","base.afilled5d":"\nbase.afilled5d( value, shape )\n    Returns a filled five-dimensional nested array.\n\n    Parameters\n    ----------\n    value: any\n        Fill value.\n\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.afilled5d( 0.0, [ 1, 1, 1, 1, 3 ] )\n    [ [ [ [ [ 0.0, 0.0, 0.0 ] ] ] ] ]\n\n","base.afilled5dBy":"\nbase.afilled5dBy( shape, clbk[, thisArg] )\n    Returns a filled five-dimensional nested array according to a provided\n    callback function.\n\n    The callback function is provided one argument:\n\n    - indices: current array element indices.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function clbk() { return 1.0; };\n    > var out = base.afilled5dBy( [ 1, 1, 1, 1, 3 ], clbk )\n    [ [ [ [ [ 1.0, 1.0, 1.0 ] ] ] ] ]\n\n    See Also\n    --------\n    base.afilled5d\n","base.afilledBy":"\nbase.afilledBy( len, clbk[, thisArg] )\n    Returns a filled \"generic\" array according to a provided callback function.\n\n    Parameters\n    ----------\n    len: integer\n        Array length.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function clbk() { return 1.0; };\n    > var out = base.afilledBy( 3, clbk )\n    [ 1.0, 1.0, 1.0 ]\n\n    See Also\n    --------\n    base.afilled\n","base.afillednd":"\nbase.afillednd( value, shape )\n    Returns a filled n-dimensional nested array.\n\n    Parameters\n    ----------\n    value: any\n        Fill value.\n\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.afillednd( 0.0, [ 1, 3 ] )\n    [ [ 0.0, 0.0, 0.0 ] ]\n\n","base.afilledndBy":"\nbase.afilledndBy( shape, clbk[, thisArg] )\n    Returns a filled n-dimensional nested array according to a callback\n    function.\n\n    The callback function is provided one argument:\n\n    - indices: current array element indices.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function clbk() { return 1.0; };\n    > var out = base.afilledndBy( [ 1, 3 ], clbk )\n    [ [ 1.0, 1.0, 1.0 ] ]\n\n    See Also\n    --------\n    base.afillednd\n","base.afilter":"\nbase.afilter( x, predicate[, thisArg] )\n    Returns a shallow copy of an array containing only those elements which pass\n    a test implemented by a predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the input array.\n\n    If provided an array-like object having a `filter` method , the function\n    defers execution to that method and assumes that the method has the\n    following signature:\n\n      x.filter( predicate, thisArg )\n\n    If provided an array-like object without a `filter` method, the function\n    performs a linear scan and always returns a generic array.\n\n    Parameters\n    ----------\n    x: Array|TypedArray|Object\n        Input array.\n\n    predicate: Function\n        Predicate function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Output array.\n\n    Examples\n    --------\n    > function f( v ) { return ( v > 0 ); };\n    > var x = [ 1, -2, -3, 4 ];\n    > var out = base.afilter( x, f )\n    [ 1, 4 ]\n\n","base.afirst":"\nbase.afirst( arr )\n    Returns the first element of an array-like object.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject\n        Input array.\n\n    Returns\n    -------\n    out: any\n        First element.\n\n    Examples\n    --------\n    > var out = base.afirst( [ 1, 2, 3 ] )\n    1\n\n","base.aflatten":"\nbase.aflatten( x, shape, colexicographic )\n    Flattens an n-dimensional nested array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    Returns\n    -------\n    out: Array\n        Flattened array.\n\n    Examples\n    --------\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = base.aflatten( x, [ 2, 2 ], false )\n    [ 1, 2, 3, 4 ]\n    > out = base.aflatten( x, [ 2, 2 ], true )\n    [ 1, 3, 2, 4 ]\n\n\nbase.aflatten.assign( x, shape, colexicographic, out, stride, offset )\n    Flattens an n-dimensional nested array and assigns elements to a provided\n    output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten.assign( x, [ 2, 2 ], false, out, 1, 0 )\n    [ 1, 2, 3, 4 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten.assign( x, [ 2, 2 ], true, out, 1, 0 );\n    > out\n    [ 1, 3, 2, 4 ]\n\n    See Also\n    --------\n    base.aflattenBy\n","base.aflatten.assign":"\nbase.aflatten.assign( x, shape, colexicographic, out, stride, offset )\n    Flattens an n-dimensional nested array and assigns elements to a provided\n    output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten.assign( x, [ 2, 2 ], false, out, 1, 0 )\n    [ 1, 2, 3, 4 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten.assign( x, [ 2, 2 ], true, out, 1, 0 );\n    > out\n    [ 1, 3, 2, 4 ]\n\n    See Also\n    --------\n    base.aflattenBy","base.aflatten2d":"\nbase.aflatten2d( x, shape, colexicographic )\n    Flattens a two-dimensional nested array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    Returns\n    -------\n    out: Array\n        Flattened array.\n\n    Examples\n    --------\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = base.aflatten2d( x, [ 2, 2 ], false )\n    [ 1, 2, 3, 4 ]\n    > out = base.aflatten2d( x, [ 2, 2 ], true )\n    [ 1, 3, 2, 4 ]\n\n\nbase.aflatten2d.assign( x, shape, colexicographic, out, stride, offset )\n    Flattens a two-dimensional nested array and assigns elements to a provided\n    output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten2d.assign( x, [ 2, 2 ], false, out, 1, 0 )\n    [ 1, 2, 3, 4 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten2d.assign( x, [ 2, 2 ], true, out, 1, 0 );\n    > out\n    [ 1, 3, 2, 4 ]\n\n    See Also\n    --------\n    base.aflatten2dBy\n","base.aflatten2d.assign":"\nbase.aflatten2d.assign( x, shape, colexicographic, out, stride, offset )\n    Flattens a two-dimensional nested array and assigns elements to a provided\n    output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten2d.assign( x, [ 2, 2 ], false, out, 1, 0 )\n    [ 1, 2, 3, 4 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten2d.assign( x, [ 2, 2 ], true, out, 1, 0 );\n    > out\n    [ 1, 3, 2, 4 ]\n\n    See Also\n    --------\n    base.aflatten2dBy","base.aflatten2dBy":"\nbase.aflatten2dBy( x, shape, colex, clbk[, thisArg] )\n    Flattens a two-dimensional nested array according to a callback function.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Flattened array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = base.aflatten2dBy( x, [ 2, 2 ], false, fcn )\n    [ 2, 4, 6, 8 ]\n    > out = base.aflatten2dBy( x, [ 2, 2 ], true, fcn )\n    [ 2, 6, 4, 8 ]\n\n\nbase.aflatten2dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n    Flattens a two-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten2dBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\n    [ 2, 4, 6, 8 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten2dBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\n    > out\n    [ 2, 6, 4, 8 ]\n\n    See Also\n    --------\n    base.aflatten2d\n","base.aflatten2dBy.assign":"\nbase.aflatten2dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n    Flattens a two-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten2dBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\n    [ 2, 4, 6, 8 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten2dBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\n    > out\n    [ 2, 6, 4, 8 ]\n\n    See Also\n    --------\n    base.aflatten2d","base.aflatten3d":"\nbase.aflatten3d( x, shape, colexicographic )\n    Flattens a three-dimensional nested array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    Returns\n    -------\n    out: Array\n        Flattened array.\n\n    Examples\n    --------\n    > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n    > var out = base.aflatten3d( x, [ 2, 1, 2 ], false )\n    [ 1, 2, 3, 4 ]\n    > out = base.aflatten3d( x, [ 2, 1, 2 ], true )\n    [ 1, 3, 2, 4 ]\n\n\nbase.aflatten3d.assign( x, shape, colexicographic, out, stride, offset )\n    Flattens a three-dimensional nested array and assigns elements to a provided\n    output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten3d.assign( x, [ 2, 1, 2 ], false, out, 1, 0 )\n    [ 1, 2, 3, 4 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten3d.assign( x, [ 2, 1, 2 ], true, out, 1, 0 );\n    > out\n    [ 1, 3, 2, 4 ]\n\n    See Also\n    --------\n    base.aflatten3dBy\n","base.aflatten3d.assign":"\nbase.aflatten3d.assign( x, shape, colexicographic, out, stride, offset )\n    Flattens a three-dimensional nested array and assigns elements to a provided\n    output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten3d.assign( x, [ 2, 1, 2 ], false, out, 1, 0 )\n    [ 1, 2, 3, 4 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten3d.assign( x, [ 2, 1, 2 ], true, out, 1, 0 );\n    > out\n    [ 1, 3, 2, 4 ]\n\n    See Also\n    --------\n    base.aflatten3dBy","base.aflatten3dBy":"\nbase.aflatten3dBy( x, shape, colex, clbk[, thisArg] )\n    Flattens a three-dimensional nested array according to a callback function.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Flattened array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n    > var out = base.aflatten3dBy( x, [ 2, 1, 2 ], false, fcn )\n    [ 2, 4, 6, 8 ]\n    > out = base.aflatten3dBy( x, [ 2, 1, 2 ], true, fcn )\n    [ 2, 6, 4, 8 ]\n\n\nbase.aflatten3dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n    Flattens a three-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten3dBy.assign( x, [ 2, 1, 2 ], false, out, 1, 0, fcn )\n    [ 2, 4, 6, 8 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten3dBy.assign( x, [ 2, 1, 2 ], true, out, 1, 0, fcn );\n    > out\n    [ 2, 6, 4, 8 ]\n\n    See Also\n    --------\n    base.aflatten3d\n","base.aflatten3dBy.assign":"\nbase.aflatten3dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n    Flattens a three-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten3dBy.assign( x, [ 2, 1, 2 ], false, out, 1, 0, fcn )\n    [ 2, 4, 6, 8 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten3dBy.assign( x, [ 2, 1, 2 ], true, out, 1, 0, fcn );\n    > out\n    [ 2, 6, 4, 8 ]\n\n    See Also\n    --------\n    base.aflatten3d","base.aflatten4d":"\nbase.aflatten4d( x, shape, colexicographic )\n    Flattens a four-dimensional nested array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    Returns\n    -------\n    out: Array\n        Flattened array.\n\n    Examples\n    --------\n    > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n    > var out = base.aflatten4d( x, [ 2, 1, 1, 2 ], false )\n    [ 1, 2, 3, 4 ]\n    > out = base.aflatten4d( x, [ 2, 1, 1, 2 ], true )\n    [ 1, 3, 2, 4 ]\n\n\nbase.aflatten4d.assign( x, shape, colexicographic, out, stride, offset )\n    Flattens a four-dimensional nested array and assigns elements to a provided\n    output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0 )\n    [ 1, 2, 3, 4 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0 );\n    > out\n    [ 1, 3, 2, 4 ]\n\n    See Also\n    --------\n    base.aflatten4dBy\n","base.aflatten4d.assign":"\nbase.aflatten4d.assign( x, shape, colexicographic, out, stride, offset )\n    Flattens a four-dimensional nested array and assigns elements to a provided\n    output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0 )\n    [ 1, 2, 3, 4 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0 );\n    > out\n    [ 1, 3, 2, 4 ]\n\n    See Also\n    --------\n    base.aflatten4dBy","base.aflatten4dBy":"\nbase.aflatten4dBy( x, shape, colex, clbk[, thisArg] )\n    Flattens a four-dimensional nested array according to a callback function.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Flattened array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n    > var out = base.aflatten4dBy( x, [ 2, 1, 1, 2 ], false, fcn )\n    [ 2, 4, 6, 8 ]\n    > out = base.aflatten4dBy( x, [ 2, 1, 1, 2 ], true, fcn )\n    [ 2, 6, 4, 8 ]\n\n\nbase.aflatten4dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n    Flattens a four-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0, fcn )\n    [ 2, 4, 6, 8 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0, fcn );\n    > out\n    [ 2, 6, 4, 8 ]\n\n    See Also\n    --------\n    base.aflatten4d\n","base.aflatten4dBy.assign":"\nbase.aflatten4dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n    Flattens a four-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0, fcn )\n    [ 2, 4, 6, 8 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0, fcn );\n    > out\n    [ 2, 6, 4, 8 ]\n\n    See Also\n    --------\n    base.aflatten4d","base.aflatten5d":"\nbase.aflatten5d( x, shape, colexicographic )\n    Flattens a five-dimensional nested array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    Returns\n    -------\n    out: Array\n        Flattened array.\n\n    Examples\n    --------\n    > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n    > var out = base.aflatten5d( x, [ 2, 1, 1, 1, 2 ], false )\n    [ 1, 2, 3, 4 ]\n    > out = base.aflatten5d( x, [ 2, 1, 1, 1, 2 ], true )\n    [ 1, 3, 2, 4 ]\n\n\nbase.aflatten5d.assign( x, shape, colexicographic, out, stride, offset )\n    Flattens a five-dimensional nested array and assigns elements to a provided\n    output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0 )\n    [ 1, 2, 3, 4 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0 );\n    > out\n    [ 1, 3, 2, 4 ]\n\n    See Also\n    --------\n    base.aflatten5dBy\n","base.aflatten5d.assign":"\nbase.aflatten5d.assign( x, shape, colexicographic, out, stride, offset )\n    Flattens a five-dimensional nested array and assigns elements to a provided\n    output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0 )\n    [ 1, 2, 3, 4 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0 );\n    > out\n    [ 1, 3, 2, 4 ]\n\n    See Also\n    --------\n    base.aflatten5dBy","base.aflatten5dBy":"\nbase.aflatten5dBy( x, shape, colex, clbk[, thisArg] )\n    Flattens a five-dimensional nested array according to a callback function.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Flattened array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n    > var out = base.aflatten5dBy( x, [ 2, 1, 1, 1, 2 ], false, fcn )\n    [ 2, 4, 6, 8 ]\n    > out = base.aflatten5dBy( x, [ 2, 1, 1, 1, 2 ], true, fcn )\n    [ 2, 6, 4, 8 ]\n\n\nbase.aflatten5dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n    Flattens a five-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0, fcn )\n    [ 2, 4, 6, 8 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0, fcn );\n    > out\n    [ 2, 6, 4, 8 ]\n\n    See Also\n    --------\n    base.aflatten5d\n","base.aflatten5dBy.assign":"\nbase.aflatten5dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n    Flattens a five-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0, fcn )\n    [ 2, 4, 6, 8 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0, fcn );\n    > out\n    [ 2, 6, 4, 8 ]\n\n    See Also\n    --------\n    base.aflatten5d","base.aflattenBy":"\nbase.aflattenBy( x, shape, colex, clbk[, thisArg] )\n    Flattens an n-dimensional nested array according to a callback function.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Flattened array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = base.aflattenBy( x, [ 2, 2 ], false, fcn )\n    [ 2, 4, 6, 8 ]\n    > out = base.aflattenBy( x, [ 2, 2 ], true, fcn )\n    [ 2, 6, 4, 8 ]\n\n\nbase.aflattenBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n    Flattens an n-dimensional nested array according to a callback function and\n    assigns elements to a provided output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflattenBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\n    [ 2, 4, 6, 8 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflattenBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\n    > out\n    [ 2, 6, 4, 8 ]\n\n    See Also\n    --------\n    base.aflatten\n","base.aflattenBy.assign":"\nbase.aflattenBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n    Flattens an n-dimensional nested array according to a callback function and\n    assigns elements to a provided output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflattenBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\n    [ 2, 4, 6, 8 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflattenBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\n    > out\n    [ 2, 6, 4, 8 ]\n\n    See Also\n    --------\n    base.aflatten","base.afliplr2d":"\nbase.afliplr2d( x )\n    Reverses the order of elements along the last dimension of a two-dimensional\n    nested input array.\n\n    The function does *not* perform a deep copy of nested array elements.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input nested array.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.afliplr2d( [ [ 1, 2 ], [ 3, 4 ] ] )\n    [ [ 2, 1 ], [ 4, 3 ] ]\n\n    See Also\n    --------\n    base.afliplr3d, base.afliplr4d, base.afliplr5d\n","base.afliplr3d":"\nbase.afliplr3d( x )\n    Reverses the order of elements along the last dimension of a three-\n    dimensional nested input array.\n\n    The function does *not* perform a deep copy of nested array elements.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input nested array.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.afliplr3d( [ [ [ 1, 2 ], [ 3, 4 ] ] ] )\n    [ [ [ 2, 1 ], [ 4, 3 ] ] ]\n\n    See Also\n    --------\n    base.afliplr2d, base.afliplr4d, base.afliplr5d\n","base.afliplr4d":"\nbase.afliplr4d( x )\n    Reverses the order of elements along the last dimension of a four-\n    dimensional nested input array.\n\n    The function does *not* perform a deep copy of nested array elements.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input nested array.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.afliplr4d( [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] )\n    [ [ [ [ 2, 1 ], [ 4, 3 ] ] ] ]\n\n    See Also\n    --------\n    base.afliplr2d, base.afliplr3d, base.afliplr5d\n","base.afliplr5d":"\nbase.afliplr5d( x )\n    Reverses the order of elements along the last dimension of a five-\n    dimensional nested input array.\n\n    The function does *not* perform a deep copy of nested array elements.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input nested array.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.afliplr5d( [ [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] ] )\n    [ [ [ [ [ 2, 1 ], [ 4, 3 ] ] ] ] ]\n\n    See Also\n    --------\n    base.afliplr2d, base.afliplr3d, base.afliplr4d\n","base.aflipud2d":"\nbase.aflipud2d( x )\n    Reverses the order of elements along the first dimension of a two-\n    dimensional nested input array.\n\n    The function does *not* perform a deep copy of nested array elements.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input nested array.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.aflipud2d( [ [ 1, 2 ], [ 3, 4 ] ] )\n    [ [ 3, 4 ], [ 1, 2 ] ]\n\n    See Also\n    --------\n    base.aflipud3d, base.aflipud4d, base.aflipud5d\n","base.aflipud3d":"\nbase.aflipud3d( x )\n    Reverses the order of elements along the second-to-last dimension of a\n    three-dimensional nested input array.\n\n    The function does *not* perform a deep copy of nested array elements.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input nested array.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.aflipud3d( [ [ [ 1, 2 ], [ 3, 4 ] ] ] )\n    [ [ [ 3, 4 ], [ 1, 2 ] ] ]\n\n    See Also\n    --------\n    base.aflipud2d, base.aflipud4d, base.aflipud5d\n","base.aflipud4d":"\nbase.aflipud4d( x )\n    Reverses the order of elements along the second-to-last dimension of a four-\n    dimensional nested input array.\n\n    The function does *not* perform a deep copy of nested array elements.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input nested array.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.aflipud4d( [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] )\n    [ [ [ [ 3, 4 ], [ 1, 2 ] ] ] ]\n\n    See Also\n    --------\n    base.aflipud2d, base.aflipud3d, base.aflipud5d\n","base.aflipud5d":"\nbase.aflipud5d( x )\n    Reverses the order of elements along the second-to-last dimension of a five-\n    dimensional nested input array.\n\n    The function does *not* perform a deep copy of nested array elements.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input nested array.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.aflipud5d( [ [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] ] )\n    [ [ [ [ [ 3, 4 ], [ 1, 2 ] ] ] ] ]\n\n    See Also\n    --------\n    base.aflipud2d, base.aflipud3d, base.aflipud4d\n","base.ahavercos":"\nbase.ahavercos( x )\n    Computes the inverse half-value versed cosine.\n\n    The inverse half-value versed cosine is defined as `2*acos(sqrt(x))`.\n\n    If `x < 0`, `x > 1`, or `x` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Inverse half-value versed cosine.\n\n    Examples\n    --------\n    > var y = base.ahavercos( 0.5 )\n    ~1.5708\n    > y = base.ahavercos( 0.0 )\n    ~3.1416\n\n    See Also\n    --------\n    base.ahaversin, base.havercos, base.vercos\n","base.ahaversin":"\nbase.ahaversin( x )\n    Computes the inverse half-value versed sine.\n\n    The inverse half-value versed sine is defined as `2*asin(sqrt(x))`.\n\n    If `x < 0`, `x > 1`, or `x` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Inverse half-value versed sine.\n\n    Examples\n    --------\n    > var y = base.ahaversin( 0.5 )\n    ~1.5708\n    > y = base.ahaversin( 0.0 )\n    0.0\n\n    See Also\n    --------\n    base.ahavercos, base.haversin, base.versin\n","base.altcase":"\nbase.altcase( str )\n    Converts a string to alternate case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Alternate-cased string.\n\n    Examples\n    --------\n    > var out = base.altcase( 'Hello World!' )\n    'hElLo wOrLd!'\n    > out = base.altcase( 'I am a tiny little teapot' )\n    'i aM A TiNy lItTlE TeApOt'\n\n    See Also\n    --------\n    base.lowercase, base.uppercase","base.aones":"\nbase.aones( len )\n    Returns a \"generic\" array filled with ones.\n\n    Parameters\n    ----------\n    len: integer\n        Array length.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.aones( 3 )\n    [ 1.0, 1.0, 1.0 ]\n\n    See Also\n    --------\n    base.azeros, base.aones2d, base.aones3d, base.aones4d, base.aones5d, base.aonesnd\n","base.aones2d":"\nbase.aones2d( shape )\n    Returns a two-dimensional nested array filled with ones.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.aones2d( [ 1, 3 ] )\n    [ [ 1.0, 1.0, 1.0 ] ]\n\n    See Also\n    --------\n    base.azeros2d, base.aones, base.aones3d, base.aones4d, base.aones5d, base.aonesnd\n","base.aones3d":"\nbase.aones3d( shape )\n    Returns a three-dimensional nested array filled with ones.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.aones3d( [ 1, 1, 3 ] )\n    [ [ [ 1.0, 1.0, 1.0 ] ] ]\n\n    See Also\n    --------\n    base.azeros3d, base.aones, base.aones2d, base.aones4d, base.aones5d, base.aonesnd\n","base.aones4d":"\nbase.aones4d( shape )\n    Returns a four-dimensional nested array filled with ones.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.aones4d( [ 1, 1, 1, 3 ] )\n    [ [ [ [ 1.0, 1.0, 1.0 ] ] ] ]\n\n    See Also\n    --------\n    base.azeros4d, base.aones, base.aones2d, base.aones3d, base.aones5d, base.aonesnd\n","base.aones5d":"\nbase.aones5d( shape )\n    Returns a five-dimensional nested array filled with ones.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.aones5d( [ 1, 1, 1, 1, 3 ] )\n    [ [ [ [ [ 1.0, 1.0, 1.0 ] ] ] ] ]\n\n    See Also\n    --------\n    base.azeros5d, base.aones, base.aones2d, base.aones3d, base.aones4d, base.aonesnd\n","base.aonesnd":"\nbase.aonesnd( shape )\n    Returns an n-dimensional nested array filled with ones.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.aonesnd( [ 1, 3 ] )\n    [ [ 1.0, 1.0, 1.0 ] ]\n\n    See Also\n    --------\n    base.azerosnd, base.aones, base.aones2d, base.aones3d, base.aones4d, base.aones5d\n","base.aoneTo":"\nbase.aoneTo( n )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from one.\n\n    If `n` is a non-integer value greater than zero, the function returns an\n    array having `ceil(n)` elements.\n\n    If `n` is less than or equal to zero, the function returns an empty array.\n\n    Parameters\n    ----------\n    n: number\n        Number of elements.\n\n    Returns\n    -------\n    out: Array\n        Linearly spaced numeric array.\n\n    Examples\n    --------\n    > var arr = base.aoneTo( 6 )\n    [ 1, 2, 3, 4, 5, 6 ]\n\n\nbase.aoneTo.assign( out, stride, offset )\n    Fills an array with linearly spaced numeric elements which increment by 1\n    starting from one.\n\n    Parameters\n    ----------\n    out: ArrayLikeObject\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > base.aoneTo.assign( out, -1, out.length-1 );\n    > out\n    [ 6, 5, 4, 3, 2, 1 ]\n\n    See Also\n    --------\n    base.azeroTo, base.aones\n","base.aoneTo.assign":"\nbase.aoneTo.assign( out, stride, offset )\n    Fills an array with linearly spaced numeric elements which increment by 1\n    starting from one.\n\n    Parameters\n    ----------\n    out: ArrayLikeObject\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > base.aoneTo.assign( out, -1, out.length-1 );\n    > out\n    [ 6, 5, 4, 3, 2, 1 ]\n\n    See Also\n    --------\n    base.azeroTo, base.aones","base.args2multislice":"\nbase.args2multislice( args )\n    Creates a MultiSlice object from a list of MultiSlice constructor arguments.\n\n    Parameters\n    ----------\n    args: Array<Slice|integer|null|undefined>\n        Constructor arguments.\n\n    Returns\n    -------\n    s: MultiSlice\n        MultiSlice instance.\n\n    Examples\n    --------\n    > var args = [ null, null, null ];\n    > var s = new base.args2multislice( args );\n    > s.data\n    [ null, null, null ]\n    > args = [ 10, new Slice( 0, 10, 1 ), null ];\n    > s = new base.args2multislice( args );\n    > s.data\n    [ 10, <Slice>, null ]\n\n","base.asec":"\nbase.asec( x )\n    Computes the inverse (arc) secant of a number.\n\n    If `x > -1` and `x < 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Inverse (arc) secant.\n\n    Examples\n    --------\n    > var y = base.asec( 1.0 )\n    0.0\n    > y = base.asec( 2.0 )\n    ~1.0472\n    > y = base.asec( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acot, base.acsc, base.asech, base.acos\n","base.asecd":"\nbase.asecd( x )\n    Computes the arcsecant (in degrees) of a double-precision floating-point\n    number.\n\n    If `x` does not satisy `x >= 1` or `x <= -1`, the function returns NaN.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arcsecant (in degrees).\n\n    Examples\n    --------\n    > var y = base.asecd( 0.0 )\n    NaN\n    > y = base.asecd( 2 )\n    ~60.0\n    > y = base.asecd( NaN )\n    NaN\n\n    See Also\n    --------\n    base.asec, base.asech, base.acosd, base.secd\n","base.asecdf":"\nbase.asecdf( x )\n    Computes the arcsecant (in degrees) of a single-precision floating-point\n    number.\n\n    If `x` does not satisy `x >= 1` or `x <= -1`, the function returns NaN.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arcsecant (in degrees).\n\n    Examples\n    --------\n    > var y = base.asecdf( 2.0 )\n    ~60.0\n    > y = base.asecdf( 0.0 )\n    NaN\n    > y = base.asecdf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.asec, base.asech\n","base.asecf":"\nbase.asecf( x )\n    Computes the inverse (arc) secant of a single-precision\n    floating-point number.\n\n    If `x > -1` and `x < 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Inverse (arc) secant.\n\n    Examples\n    --------\n    > var y = base.asecf( 1.0 )\n    0.0\n    > y = base.asecf( 2.0 )\n    ~1.0472\n    > y = base.asecf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.asec, base.asech, base.acosf\n","base.asech":"\nbase.asech( x )\n    Computes the hyperbolic arcsecant of a number.\n\n    If `x < 0` or `x > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Hyperbolic arcsecant.\n\n    Examples\n    --------\n    > var y = base.asech( 1.0 )\n    0.0\n    > y = base.asech( 0.5 )\n    ~1.317\n    > y = base.asech( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acosh, base.asec, base.asech, base.acoth\n","base.asin":"\nbase.asin( x )\n    Computes the arcsine of a double-precision floating-point number.\n\n    If `|x| > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arcsine (in radians).\n\n    Examples\n    --------\n    > var y = base.asin( 0.0 )\n    0.0\n    > y = base.asin( -PI/6.0 )\n    ~-0.551\n    > y = base.asin( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acos, base.asinh, base.atan\n","base.asind":"\nbase.asind( x )\n    Computes the arcsine (in degrees) of a double-precision floating-point\n    number.\n\n    If `|x| > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arcsine (in degrees).\n\n    Examples\n    --------\n    > var y = base.asind( 0.0 )\n    0.0\n    > y = base.asind( PI / 6.0 )\n    ~31.57\n    > y = base.asind( NaN )\n    NaN\n\n    See Also\n    --------\n    base.asin, base.asinh, base.atand\n","base.asindf":"\nbase.asindf( x )\n    Computes the arcsine (in degrees) of a single-precision floating-point\n    number.\n\n    If `|x| > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arcsine (in degrees).\n\n    Examples\n    --------\n    > var y = base.asindf( 0.0 )\n    0.0\n    > y = base.asindf( 3.1415927410125732 / 6.0 )\n    ~31.57\n    > y = base.asindf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.asinf, base.asind\n","base.asinf":"\nbase.asinf( x )\n    Computes the arcsine of a single-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arcsine (in radians).\n\n    Examples\n    --------\n    > var y = base.asinf( 0.0 )\n    0.0\n    > y = base.asinf( -3.14/6.0 )\n    ~-0.551\n    > y = base.asinf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.asin, base.asindf\n","base.asinh":"\nbase.asinh( x )\n    Computes the hyperbolic arcsine of a double-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Hyperbolic arcsine.\n\n    Examples\n    --------\n    > var y = base.asinh( 0.0 )\n    0.0\n    > y = base.asinh( 2.0 )\n    ~1.444\n    > y = base.asinh( -2.0 )\n    ~-1.444\n    > y = base.asinh( NaN )\n    NaN\n    > y = base.asinh( NINF )\n    -Infinity\n    > y = base.asinh( PINF )\n    Infinity\n\n    See Also\n    --------\n    base.acosh, base.asin, base.atanh\n","base.atan":"\nbase.atan( x )\n    Computes the arctangent of a double-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arctangent (in radians).\n\n    Examples\n    --------\n    > var y = base.atan( 0.0 )\n    ~0.0\n    > y = base.atan( -PI/2.0 )\n    ~-1.004\n    > y = base.atan( PI/2.0 )\n    ~1.004\n    > y = base.atan( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acos, base.asin, base.atanh\n","base.atan2":"\nbase.atan2( y, x )\n    Computes the angle in the plane (in radians) between the positive x-axis and\n    the ray from (0,0) to the point (x,y).\n\n    Parameters\n    ----------\n    y: number\n        Coordinate along y-axis.\n\n    x: number\n        Coordinate along x-axis.\n\n    Returns\n    -------\n    out: number\n        Angle (in radians).\n\n    Examples\n    --------\n    > var v = base.atan2( 2.0, 2.0 )\n    ~0.785\n    > v = base.atan2( 6.0, 2.0 )\n    ~1.249\n    > v = base.atan2( -1.0, -1.0 )\n    ~-2.356\n    > v = base.atan2( 3.0, 0.0 )\n    ~1.571\n    > v = base.atan2( -2.0, 0.0 )\n    ~-1.571\n    > v = base.atan2( 0.0, 0.0 )\n    0.0\n    > v = base.atan2( 3.0, NaN )\n    NaN\n    > v = base.atan2( NaN, 2.0 )\n    NaN\n\n    See Also\n    --------\n    base.atan\n","base.atand":"\nbase.atand( x )\n    Computes the arctangent (in degrees) of a double-precision floating-point\n    number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arctangent (in degrees).\n\n    Examples\n    --------\n    > var y = base.atand( 0.0 )\n    0.0\n    > y = base.atand( PI/6.0 )\n    ~27.64\n    > y = base.atand( NaN )\n    NaN\n\n    See Also\n    --------\n    base.atan, base.atanh, base.acosd\n","base.atanf":"\nbase.atanf( x )\n    Computes the arctangent of a single-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arctangent (in radians).\n\n    Examples\n    --------\n    > var y = base.atanf( 0.0 )\n    0.0\n    > y = base.atanf( -3.14/4.0 )\n    ~-0.666\n    > y = base.atanf( 3.14/4.0 )\n    ~0.666\n    > y = base.atanf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.atan, base.atanh, base.acosf\n","base.atanh":"\nbase.atanh( x )\n    Computes the hyperbolic arctangent of a double-precision floating-point\n    number.\n\n    If `|x| > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Hyperbolic arctangent.\n\n    Examples\n    --------\n    > var y = base.atanh( 0.0 )\n    0.0\n    > y = base.atanh( 0.9 )\n    ~1.472\n    > y = base.atanh( 1.0 )\n    Infinity\n    > y = base.atanh( -1.0 )\n    -Infinity\n    > y = base.atanh( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acosh, base.asinh, base.atan\n","base.avercos":"\nbase.avercos( x )\n    Computes the inverse versed cosine.\n\n    The inverse versed cosine is defined as `acos(1+x)`.\n\n    If `x < -2`, `x > 0`, or `x` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Inverse versed cosine.\n\n    Examples\n    --------\n    > var y = base.avercos( -1.5 )\n    ~2.0944\n    > y = base.avercos( -0.0 )\n    0.0\n\n    See Also\n    --------\n    base.aversin, base.versin\n","base.aversin":"\nbase.aversin( x )\n    Computes the inverse versed sine.\n\n    The inverse versed sine is defined as `acos(1-x)`.\n\n    If `x < 0`, `x > 2`, or `x` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Inverse versed sine.\n\n    Examples\n    --------\n    > var y = base.aversin( 1.5 )\n    ~2.0944\n    > y = base.aversin( 0.0 )\n    0.0\n\n    See Also\n    --------\n    base.avercos, base.vercos\n","base.azeros":"\nbase.azeros( len )\n    Returns a zero-filled \"generic\" array.\n\n    Parameters\n    ----------\n    len: integer\n        Array length.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.azeros( 3 )\n    [ 0.0, 0.0, 0.0 ]\n\n    See Also\n    --------\n    base.aones, base.azeros2d, base.azeros3d, base.azeros4d, base.azeros5d, base.azerosnd\n","base.azeros2d":"\nbase.azeros2d( shape )\n    Returns a zero-filled two-dimensional nested array.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.azeros2d( [ 1, 3 ] )\n    [ [ 0.0, 0.0, 0.0 ] ]\n\n    See Also\n    --------\n    base.azeros, base.aones2d, base.azeros3d, base.azeros4d, base.azeros5d, base.azerosnd\n","base.azeros3d":"\nbase.azeros3d( shape )\n    Returns a zero-filled three-dimensional nested array.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.azeros3d( [ 1, 1, 3 ] )\n    [ [ [ 0.0, 0.0, 0.0 ] ] ]\n\n    See Also\n    --------\n    base.azeros, base.aones3d, base.azeros2d, base.azeros4d, base.azeros5d, base.azerosnd\n","base.azeros4d":"\nbase.azeros4d( shape )\n    Returns a zero-filled four-dimensional nested array.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.azeros4d( [ 1, 1, 1, 3 ] )\n    [ [ [ [ 0.0, 0.0, 0.0 ] ] ] ]\n\n    See Also\n    --------\n    base.azeros, base.aones4d, base.azeros2d, base.azeros3d, base.azeros5d, base.azerosnd\n","base.azeros5d":"\nbase.azeros5d( shape )\n    Returns a zero-filled five-dimensional nested array.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.azeros5d( [ 1, 1, 1, 1, 3 ] )\n    [ [ [ [ [ 0.0, 0.0, 0.0 ] ] ] ] ]\n\n    See Also\n    --------\n    base.azeros, base.aones5d, base.azeros2d, base.azeros3d, base.azeros4d, base.azerosnd\n","base.azerosnd":"\nbase.azerosnd( shape )\n    Returns a zero-filled n-dimensional nested array.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.azerosnd( [ 1, 3 ] )\n    [ [ 0.0, 0.0, 0.0 ] ]\n\n    See Also\n    --------\n    base.azeros, base.aonesnd, base.azeros2d, base.azeros3d, base.azeros4d, base.azeros5d\n","base.azeroTo":"\nbase.azeroTo( n )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from zero.\n\n    If `n` is a non-integer value greater than zero, the function returns an\n    array having `ceil(n)` elements.\n\n    If `n` is less than or equal to zero, the function returns an empty array.\n\n    Parameters\n    ----------\n    n: number\n        Number of elements.\n\n    Returns\n    -------\n    out: Array\n        Linearly spaced numeric array.\n\n    Examples\n    --------\n    > var arr = base.azeroTo( 6 )\n    [ 0, 1, 2, 3, 4, 5 ]\n\n\nbase.azeroTo.assign( out, stride, offset )\n    Fills an array with linearly spaced numeric elements which increment by 1\n    starting from zero.\n\n    Parameters\n    ----------\n    out: ArrayLikeObject\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > base.azeroTo.assign( out, -1, out.length-1 );\n    > out\n    [ 5, 4, 3, 2, 1, 0 ]\n\n    See Also\n    --------\n    base.aoneTo\n","base.azeroTo.assign":"\nbase.azeroTo.assign( out, stride, offset )\n    Fills an array with linearly spaced numeric elements which increment by 1\n    starting from zero.\n\n    Parameters\n    ----------\n    out: ArrayLikeObject\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > base.azeroTo.assign( out, -1, out.length-1 );\n    > out\n    [ 5, 4, 3, 2, 1, 0 ]\n\n    See Also\n    --------\n    base.aoneTo","base.bernoulli":"\nbase.bernoulli( n )\n    Computes the nth Bernoulli number.\n\n    If not provided a nonnegative integer value, the function returns `NaN`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Bernoulli number.\n\n    Examples\n    --------\n    > var y = base.bernoulli( 0 )\n    1.0\n    > y = base.bernoulli( 1 )\n    0.5\n    > y = base.bernoulli( 2 )\n    ~0.167\n    > y = base.bernoulli( 3 )\n    0.0\n    > y = base.bernoulli( 4 )\n    ~-0.033\n    > y = base.bernoulli( 5 )\n    0.0\n    > y = base.bernoulli( 20 )\n    ~-529.124\n    > y = base.bernoulli( 260 )\n    -Infinity\n    > y = base.bernoulli( 262 )\n    Infinity\n    > y = base.bernoulli( NaN )\n    NaN\n\n","base.besselj0":"\nbase.besselj0( x )\n    Computes the Bessel function of the first kind of order zero.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.besselj0( 0.0 )\n    1.0\n    > y = base.besselj0( 1.0 )\n    ~0.765\n    > y = base.besselj0( PINF )\n    0.0\n    > y = base.besselj0( NINF )\n    0.0\n    > y = base.besselj0( NaN )\n    NaN\n\n    See Also\n    --------\n    base.besselj1, base.bessely0, base.bessely1\n","base.besselj1":"\nbase.besselj1( x )\n    Computes the Bessel function of the first kind of order one.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.besselj1( 0.0 )\n    0.0\n    > y = base.besselj1( 1.0 )\n    ~0.440\n    > y = base.besselj1( PINF )\n    0.0\n    > y = base.besselj1( NINF )\n    0.0\n    > y = base.besselj1( NaN )\n    NaN\n\n    See Also\n    --------\n    base.besselj0, base.bessely0, base.bessely1\n","base.bessely0":"\nbase.bessely0( x )\n    Computes the Bessel function of the second kind of order zero.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.bessely0( 0.0 )\n    -Infinity\n    > y = base.bessely0( 1.0 )\n    ~0.088\n    > y = base.bessely0( -1.0 )\n    NaN\n    > y = base.bessely0( PINF )\n    0.0\n    > y = base.bessely0( NINF )\n    NaN\n    > y = base.bessely0( NaN )\n    NaN\n\n    See Also\n    --------\n    base.besselj0, base.besselj1, base.bessely1\n","base.bessely1":"\nbase.bessely1( x )\n    Computes the Bessel function of the second kind of order one.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.bessely1( 0.0 )\n    -Infinity\n    > y = base.bessely1( 1.0 )\n    ~-0.781\n    > y = base.bessely1( -1.0 )\n    NaN\n    > y = base.bessely1( PINF )\n    0.0\n    > y = base.bessely1( NINF )\n    NaN\n    > y = base.bessely1( NaN )\n    NaN\n\n    See Also\n    --------\n    base.besselj0, base.besselj1, base.bessely0\n","base.beta":"\nbase.beta( x, y )\n    Evaluates the beta function.\n\n    Parameters\n    ----------\n    x: number\n        First function parameter (nonnegative).\n\n    y: number\n        Second function parameter (nonnegative).\n\n    Returns\n    -------\n    out: number\n        Evaluated beta function.\n\n    Examples\n    --------\n    > var v = base.beta( 0.0, 0.5 )\n    Infinity\n    > v = base.beta( 1.0, 1.0 )\n    1.0\n    > v = base.beta( -1.0, 2.0 )\n    NaN\n    > v = base.beta( 5.0, 0.2 )\n    ~3.382\n    > v = base.beta( 4.0, 1.0 )\n    0.25\n    > v = base.beta( NaN, 2.0 )\n    NaN\n\n    See Also\n    --------\n    base.betainc, base.betaincinv, base.betaln\n","base.betainc":"\nbase.betainc( x, a, b[, regularized[, upper]] )\n    Computes the regularized incomplete beta function.\n\n    The `regularized` and `upper` parameters specify whether to evaluate the\n    non-regularized and/or upper incomplete beta functions, respectively.\n\n    If provided `x < 0` or `x > 1`, the function returns `NaN`.\n\n    If provided `a < 0` or `b < 0`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        First function parameter.\n\n    a: number\n        Second function parameter.\n\n    b: number\n        Third function parameter.\n\n    regularized: boolean (optional)\n        Boolean indicating whether the function should evaluate the regularized\n        or non-regularized incomplete beta function. Default: `true`.\n\n    upper: boolean (optional)\n        Boolean indicating whether the function should return the upper tail of\n        the incomplete beta function. Default: `false`.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.betainc( 0.5, 2.0, 2.0 )\n    0.5\n    > y = base.betainc( 0.5, 2.0, 2.0, false )\n    ~0.083\n    > y = base.betainc( 0.2, 1.0, 2.0 )\n    0.36\n    > y = base.betainc( 0.2, 1.0, 2.0, true, true )\n    0.64\n    > y = base.betainc( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.betainc( 0.8, NaN, 1.0 )\n    NaN\n    > y = base.betainc( 0.8, 1.0, NaN )\n    NaN\n    > y = base.betainc( 1.5, 1.0, 1.0 )\n    NaN\n    > y = base.betainc( -0.5, 1.0, 1.0 )\n    NaN\n    > y = base.betainc( 0.5, -2.0, 2.0 )\n    NaN\n    > y = base.betainc( 0.5, 2.0, -2.0 )\n    NaN\n\n    See Also\n    --------\n    base.beta, base.betaincinv, base.betaln\n","base.betaincinv":"\nbase.betaincinv( p, a, b[, upper] )\n    Computes the inverse of the lower incomplete beta function.\n\n    In contrast to a more commonly used definition, the first argument is the\n    probability `p` and the second and third arguments are `a` and `b`,\n    respectively.\n\n    By default, the function inverts the lower regularized incomplete beta\n    function. To invert the upper function, set the `upper` argument to `true`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Probability.\n\n    a: number\n        Second function parameter.\n\n    b: number\n        Third function parameter.\n\n    upper: boolean (optional)\n        Boolean indicating if the function should invert the upper tail of the\n        incomplete beta function. Default: `false`.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.betaincinv( 0.2, 3.0, 3.0 )\n    ~0.327\n    > y = base.betaincinv( 0.4, 3.0, 3.0 )\n    ~0.446\n    > y = base.betaincinv( 0.4, 3.0, 3.0, true )\n    ~0.554\n    > y = base.betaincinv( 0.4, 1.0, 6.0 )\n    ~0.082\n    > y = base.betaincinv( 0.8, 1.0, 6.0 )\n    ~0.235\n    > y = base.betaincinv( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.betaincinv( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.betaincinv( 0.5, 1.0, NaN )\n    NaN\n    > y = base.betaincinv( 1.2, 1.0, 1.0 )\n    NaN\n    > y = base.betaincinv( -0.5, 1.0, 1.0 )\n    NaN\n    > y = base.betaincinv( 0.5, -2.0, 2.0 )\n    NaN\n    > y = base.betaincinv( 0.5, 0.0, 2.0 )\n    NaN\n    > y = base.betaincinv( 0.5, 2.0, -2.0 )\n    NaN\n    > y = base.betaincinv( 0.5, 2.0, 0.0 )\n    NaN\n\n    See Also\n    --------\n    base.beta, base.betainc, base.betaln\n","base.betaln":"\nbase.betaln( a, b )\n    Evaluates the natural logarithm of the beta function.\n\n    Parameters\n    ----------\n    a: number\n        First function parameter (nonnegative).\n\n    b: number\n        Second function parameter (nonnegative).\n\n    Returns\n    -------\n    out: number\n        Natural logarithm of the beta function.\n\n    Examples\n    --------\n    > var v = base.betaln( 0.0, 0.0 )\n    Infinity\n    > v = base.betaln( 1.0, 1.0 )\n    0.0\n    > v = base.betaln( -1.0, 2.0 )\n    NaN\n    > v = base.betaln( 5.0, 0.2 )\n    ~1.218\n    > v = base.betaln( 4.0, 1.0 )\n    ~-1.386\n    > v = base.betaln( NaN, 2.0 )\n    NaN\n\n    See Also\n    --------\n    base.beta, base.betainc, base.betaincinv\n","base.binet":"\nbase.binet( x )\n    Evaluates Binet's formula extended to real numbers.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function result.\n\n    Examples\n    --------\n    > var y = base.binet( 0.0 )\n    0.0\n    > y = base.binet( 1.0 )\n    1.0\n    > y = base.binet( 2.0 )\n    1.0\n    > y = base.binet( 3.0 )\n    2.0\n    > y = base.binet( 4.0 )\n    3.0\n    > y = base.binet( 5.0 )\n    ~5.0\n    > y = base.binet( NaN )\n    NaN\n\n    See Also\n    --------\n    base.fibonacci, base.negafibonacci\n","base.binomcoef":"\nbase.binomcoef( n, k )\n    Computes the binomial coefficient of two integers.\n\n    If `k < 0`, the function returns `0`.\n\n    The function returns `NaN` for non-integer `n` or `k`.\n\n    Parameters\n    ----------\n    n: integer\n        First input value.\n\n    k: integer\n        Second input value.\n\n    Returns\n    -------\n    out: number\n        Function value.\n\n    Examples\n    --------\n    > var v = base.binomcoef( 8, 2 )\n    28\n    > v = base.binomcoef( 0, 0 )\n    1\n    > v = base.binomcoef( -4, 2 )\n    10\n    > v = base.binomcoef( 5, 3 )\n    10\n    > v = base.binomcoef( NaN, 3 )\n    NaN\n    > v = base.binomcoef( 5, NaN )\n    NaN\n    > v = base.binomcoef( NaN, NaN )\n    NaN\n\n","base.binomcoefln":"\nbase.binomcoefln( n, k )\n    Computes the natural logarithm of the binomial coefficient of two integers.\n\n    If `k < 0`, the function returns negative infinity.\n\n    The function returns `NaN` for non-integer `n` or `k`.\n\n    Parameters\n    ----------\n    n: integer\n        First input value.\n\n    k: integer\n        Second input value.\n\n    Returns\n    -------\n    out: number\n        Natural logarithm of the binomial coefficient.\n\n    Examples\n    --------\n    > var v = base.binomcoefln( 8, 2 )\n    ~3.332\n    > v = base.binomcoefln( 0, 0 )\n    0.0\n    > v = base.binomcoefln( -4, 2 )\n    ~2.303\n    > v = base.binomcoefln( 88, 3 )\n    ~11.606\n    > v = base.binomcoefln( NaN, 3 )\n    NaN\n    > v = base.binomcoefln( 5, NaN )\n    NaN\n    > v = base.binomcoefln( NaN, NaN )\n    NaN\n\n","base.boxcox":"\nbase.boxcox( x, lambda )\n    Computes a one-parameter Box-Cox transformation.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    lambda: number\n        Power parameter.\n\n    Returns\n    -------\n    b: number\n        Function value.\n\n    Examples\n    --------\n    > var v = base.boxcox( 1.0, 2.5 )\n    0.0\n    > v = base.boxcox( 4.0, 2.5 )\n    12.4\n    > v = base.boxcox( 10.0, 2.5 )\n    ~126.0911\n    > v = base.boxcox( 2.0, 0.0 )\n    ~0.6931\n    > v = base.boxcox( -1.0, 2.5 )\n    NaN\n    > v = base.boxcox( 0.0, -1.0 )\n    -Infinity\n\n    See Also\n    --------\n    base.boxcoxinv, base.boxcox1p, base.boxcox1pinv","base.boxcox1p":"\nbase.boxcox1p( x, lambda )\n    Computes a one-parameter Box-Cox transformation of 1+x.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    lambda: number\n        Power parameter.\n\n    Returns\n    -------\n    b: number\n        Function value.\n\n    Examples\n    --------\n    > var v =  base.boxcox1p( 1.0, 2.5 )\n    ~1.8627\n    > v = base.boxcox1p( 4.0, 2.5 )\n    ~21.9607\n    > v = base.boxcox1p( 10.0, 2.5 )\n    ~160.1246\n    > v = base.boxcox1p( 2.0, 0.0 )\n    ~1.0986\n    > v = base.boxcox1p( -1.0, 2.5 )\n    -0.4\n    > v = base.boxcox1p( 0.0, -1.0 )\n    0.0\n    > v = base.boxcox1p( -1.0, -1.0 )\n    -Infinity\n\n    See Also\n    --------\n    base.boxcox, base.boxcox1pinv, base.boxcoxinv","base.boxcox1pinv":"\nbase.boxcox1pinv( y, lambda )\n    Computes the inverse of a one-parameter Box-Cox transformation for 1+x.\n\n    Parameters\n    ----------\n    y: number\n        Input value.\n\n    lambda: number\n        Power parameter.\n\n    Returns\n    -------\n    v: number\n        Function value.\n\n    Examples\n    --------\n    > var v = base.boxcox1pinv( 1.0, 2.5 )\n    ~0.6505\n    > v = base.boxcox1pinv( 4.0, 2.5 )\n    ~1.6095\n    > v = base.boxcox1pinv( 10.0, 2.5 )\n    ~2.6812\n    > v = base.boxcox1pinv( 2.0, 0.0 )\n    ~6.3891\n    > v = base.boxcox1pinv( -1.0, 2.5 )\n    NaN\n    > v = base.boxcox1pinv( 0.0, -1.0 )\n    0.0\n    > v = base.boxcox1pinv( 1.0, NaN )\n    NaN\n    > v = base.boxcox1pinv( NaN, 3.1 )\n    NaN\n\n    See Also\n    --------\n    base.boxcox, base.boxcox1p, base.boxcoxinv","base.boxcoxinv":"\nbase.boxcoxinv( y, lambda )\n    Computes the inverse of a one-parameter Box-Cox transformation.\n\n    Parameters\n    ----------\n    y: number\n        Input value.\n\n    lambda: number\n        Power parameter.\n\n    Returns\n    -------\n    b: number\n        Function value.\n\n    Examples\n    --------\n    > var v = base.boxcoxinv( 1.0, 2.5 )\n    ~1.6505\n    > v = base.boxcoxinv( 4.0, 2.5 )\n    ~2.6095\n    > v = base.boxcoxinv( 10.0, 2.5 )\n    ~3.6812\n    > v = base.boxcoxinv( 2.0, 0.0 )\n    ~7.3891\n    > v = base.boxcoxinv( -1.0, 2.5 )\n    NaN\n    > v = base.boxcoxinv( 0.0, -1.0 )\n    1.0\n    > v = base.boxcoxinv( 1.0, NaN )\n    NaN\n    > v = base.boxcoxinv( NaN, 3.1 )\n    NaN\n\n    See Also\n    --------\n    base.boxcox, base.boxcox1p, base.boxcox1pinv","base.cabs":"\nbase.cabs( z )\n    Computes the absolute value of a double-precision complex floating-point\n    number.\n\n    The absolute value of a complex number is its distance from zero.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    y: number\n        Absolute value.\n\n    Examples\n    --------\n    > var y = base.cabs( new Complex128( 5.0, 3.0 ) )\n    ~5.831\n\n    See Also\n    --------\n    base.cabs2, base.abs\n","base.cabs2":"\nbase.cabs2( z )\n    Computes the squared absolute value of a double-precision complex floating-\n    point number.\n\n    The absolute value of a complex number is its distance from zero.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    y: number\n        Squared absolute value.\n\n    Examples\n    --------\n    > var y = base.cabs2( new Complex128( 5.0, 3.0 ) )\n    34.0\n\n    See Also\n    --------\n    base.cabs, base.abs2\n","base.cabs2f":"\nbase.cabs2f( z )\n    Computes the squared absolute value of a single-precision complex floating-\n    point number.\n\n    The absolute value of a complex number is its distance from zero.\n\n    Parameters\n    ----------\n    z: Complex64\n        Complex number.\n\n    Returns\n    -------\n    y: number\n        Squared absolute value.\n\n    Examples\n    --------\n    > var y = base.cabs2f( new Complex64( 5.0, 3.0 ) )\n    34.0\n\n    See Also\n    --------\n    base.cabs2, base.cabsf, base.abs2f\n","base.cabsf":"\nbase.cabsf( z )\n    Computes the absolute value of a single-precision complex floating-point\n    number.\n\n    The absolute value of a complex number is its distance from zero.\n\n    Parameters\n    ----------\n    z: Complex64\n        Complex number.\n\n    Returns\n    -------\n    y: number\n        Absolute value.\n\n    Examples\n    --------\n    > var y = base.cabsf( new Complex64( 5.0, 3.0 ) )\n    ~5.831\n\n    See Also\n    --------\n    base.cabs, base.cabs2f, base.absf\n","base.cadd":"\nbase.cadd( z1, z2 )\n    Adds two double-precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    z1: Complex128\n        Complex number.\n\n    z2: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Result.\n\n    Examples\n    --------\n    > var z = new Complex128( 5.0, 3.0 )\n    <Complex128>\n    > var out = base.cadd( z, z )\n    <Complex128>\n    > var re = real( out )\n    10.0\n    > var im = imag( out )\n    6.0\n\n    See Also\n    --------\n    base.cdiv, base.cmul, base.csub\n","base.caddf":"\nbase.caddf( z1, z2 )\n    Adds two single-precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    z1: Complex64\n        Complex number.\n\n    z2: Complex64\n        Complex number.\n\n    Returns\n    -------\n    out: Complex64\n        Result.\n\n    Examples\n    --------\n    > var z = new Complex64( 5.0, 3.0 )\n    <Complex64>\n    > var out = base.caddf( z, z )\n    <Complex64>\n    > var re = realf( out )\n    10.0\n    > var im = imagf( out )\n    6.0\n\n    See Also\n    --------\n    base.cadd, base.cmulf, base.csubf\n","base.camelcase":"\nbase.camelcase( str )\n    Converts a string to camel case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Camel-cased string.\n\n    Examples\n    --------\n    > var out = base.camelcase( 'Hello World!' )\n    'helloWorld'\n    > out = base.camelcase( 'beep boop' )\n    'beepBoop'\n\n    See Also\n    --------\n    base.constantcase, base.lowercase, base.snakecase, base.uppercase","base.capitalize":"\nbase.capitalize( str )\n    Capitalizes the first character in a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Capitalized string.\n\n    Examples\n    --------\n    > var out = base.capitalize( 'beep' )\n    'Beep'\n    > out = base.capitalize( 'Boop' )\n    'Boop'\n\n    See Also\n    --------\n    base.lowercase, base.uppercase\n","base.cbrt":"\nbase.cbrt( x )\n    Computes the cube root of a double-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Cube root.\n\n    Examples\n    --------\n    > var y = base.cbrt( 64.0 )\n    4.0\n    > y = base.cbrt( 27.0 )\n    3.0\n    > y = base.cbrt( 0.0 )\n    0.0\n    > y = base.cbrt( -0.0 )\n    -0.0\n    > y = base.cbrt( -9.0 )\n    ~-2.08\n    > y = base.cbrt( NaN )\n    NaN\n\n    See Also\n    --------\n    base.pow, base.sqrt\n","base.cbrtf":"\nbase.cbrtf( x )\n    Computes the cube root of a single-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Cube root.\n\n    Examples\n    --------\n    > var y = base.cbrtf( 64.0 )\n    4.0\n    > y = base.cbrtf( 27.0 )\n    3.0\n    > y = base.cbrtf( 0.0 )\n    0.0\n    > y = base.cbrtf( -0.0 )\n    -0.0\n    > y = base.cbrtf( -9.0 )\n    ~-2.08\n    > y = base.cbrtf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cbrt, base.sqrtf\n","base.cceil":"\nbase.cceil( z )\n    Rounds each component of a double-precision complex floating-point number\n    toward positive infinity.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Result.\n\n    Examples\n    --------\n    > var v = base.cceil( new Complex128( -1.5, 2.5 ) )\n    <Complex128>\n    > var re = real( v )\n    -1.0\n    > var im = imag( v )\n    3.0\n\n    See Also\n    --------\n    base.cceiln, base.cfloor, base.cround\n","base.cceilf":"\nbase.cceilf( z )\n    Rounds a single-precision complex floating-point number toward positive\n    infinity.\n\n    Parameters\n    ----------\n    z: Complex64\n        Complex number.\n\n    Returns\n    -------\n    out: Complex64\n        Result.\n\n    Examples\n    --------\n    > var v = base.cceilf( new Complex64( -1.5, 2.5 ) )\n    <Complex64>\n    > var re = realf( v )\n    -1.0\n    > var im = imagf( v )\n    3.0\n\n    See Also\n    --------\n    base.cceil\n","base.cceiln":"\nbase.cceiln( z, n )\n    Rounds each component of a double-precision complex number to the nearest\n    multiple of `10^n` toward positive infinity.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    n: integer\n        Integer power of 10.\n\n    Returns\n    -------\n    out: Complex128\n        Real and imaginary components.\n\n    Examples\n    --------\n    > var out = base.cceiln( new Complex128( 5.555, -3.333 ), -2 )\n    <Complex128>\n    > var re = real( out )\n    5.56\n    > var im = imag( out )\n    -3.33\n\n    See Also\n    --------\n    base.cceil, base.cfloorn, base.croundn\n","base.ccis":"\nbase.ccis( z )\n    Evaluates the cis function for a double-precision complex floating-point\n    number.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Complex number.\n\n    Examples\n    --------\n    > var y = base.ccis( new Complex128( 0.0, 0.0 ) )\n    <Complex128>\n    > var re = real( y )\n    1.0\n    > var im = imag( y )\n    0.0\n    > y = base.ccis( new Complex128( 1.0, 0.0 ) )\n    <Complex128>\n    > re = real( y )\n    ~0.540\n    > im = imag( y )\n    ~0.841\n\n","base.cdiv":"\nbase.cdiv( z1, z2 )\n    Divides two double-precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    z1: Complex128\n        Complex number.\n\n    z2: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Result.\n\n    Examples\n    --------\n    > var z1 = new Complex128( -13.0, -1.0 )\n    <Complex128>\n    > var z2 = new Complex128( -2.0, 1.0 )\n    <Complex128>\n    > var y = base.cdiv( z1, z2 )\n    <Complex128>\n    > var re = real( y )\n    5.0\n    > var im = imag( y )\n    3.0\n\n    See Also\n    --------\n    base.cadd, base.cmul, base.csub\n","base.ceil":"\nbase.ceil( x )\n    Rounds a double-precision floating-point number toward positive infinity.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.ceil( 3.14 )\n    4.0\n    > y = base.ceil( -4.2 )\n    -4.0\n    > y = base.ceil( -4.6 )\n    -4.0\n    > y = base.ceil( 9.5 )\n    10.0\n    > y = base.ceil( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceiln, base.floor, base.round\n","base.ceil2":"\nbase.ceil2( x )\n    Rounds a numeric value to the nearest power of two toward positive infinity.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.ceil2( 3.14 )\n    4.0\n    > y = base.ceil2( -4.2 )\n    -4.0\n    > y = base.ceil2( -4.6 )\n    -4.0\n    > y = base.ceil2( 9.5 )\n    16.0\n    > y = base.ceil2( 13.0 )\n    16.0\n    > y = base.ceil2( -13.0 )\n    -8.0\n    > y = base.ceil2( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceil, base.ceil10, base.floor2, base.round2\n","base.ceil10":"\nbase.ceil10( x )\n    Rounds a numeric value to the nearest power of ten toward positive infinity.\n\n    The function may not return accurate results for subnormals due to a general\n    loss in precision.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.ceil10( 3.14 )\n    10.0\n    > y = base.ceil10( -4.2 )\n    -1.0\n    > y = base.ceil10( -4.6 )\n    -1.0\n    > y = base.ceil10( 9.5 )\n    10.0\n    > y = base.ceil10( 13.0 )\n    100.0\n    > y = base.ceil10( -13.0 )\n    -10.0\n    > y = base.ceil10( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceil, base.ceil2, base.floor10, base.round10\n","base.ceilb":"\nbase.ceilb( x, n, b )\n    Rounds a numeric value to the nearest multiple of `b^n` toward positive\n    infinity.\n\n    Due to floating-point rounding error, rounding may not be exact.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Integer power.\n\n    b: integer\n        Base.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    // Round to 4 decimal places:\n    > var y = base.ceilb( 3.14159, -4, 10 )\n    3.1416\n\n    // If `n = 0` or `b = 1`, standard round behavior:\n    > y = base.ceilb( 3.14159, 0, 2 )\n    4.0\n\n    // Round to nearest multiple of two toward positive infinity:\n    > y = base.ceilb( 5.0, 1, 2 )\n    6.0\n\n    See Also\n    --------\n    base.ceil, base.ceiln, base.floorb, base.roundb\n","base.ceilf":"\nbase.ceilf( x )\n    Rounds a single-precision floating-point number toward positive infinity.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.ceilf( 3.14 )\n    4.0\n    > y = base.ceilf( -4.2 )\n    -4.0\n    > y = base.ceilf( -4.6 )\n    -4.0\n    > y = base.ceilf( 9.5 )\n    10.0\n    > y = base.ceilf( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.floorf\n","base.ceiln":"\nbase.ceiln( x, n )\n    Rounds a numeric value to the nearest multiple of `10^n` toward positive\n    infinity.\n\n    When operating on floating-point numbers in bases other than `2`, rounding\n    to specified digits can be inexact.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Integer power of 10.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    // Round to 2 decimal places:\n    > var y = base.ceiln( 3.14159, -2 )\n    3.15\n\n    // If `n = 0`, standard round toward positive infinity behavior:\n    > y = base.ceiln( 3.14159, 0 )\n    4.0\n\n    // Round to nearest thousand:\n    > y = base.ceiln( 12368.0, 3 )\n    13000.0\n\n\n    See Also\n    --------\n    base.ceil, base.ceilb, base.floorn, base.roundn\n","base.ceilsd":"\nbase.ceilsd( x, n, b )\n    Rounds a numeric value to the nearest number toward positive infinity with\n    `n` significant figures.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Number of significant figures. Must be greater than 0.\n\n    b: integer\n        Base. Must be greater than 0.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.ceilsd( 3.14159, 5, 10 )\n    3.1416\n    > y = base.ceilsd( 3.14159, 1, 10 )\n    4.0\n    > y = base.ceilsd( 12368.0, 2, 10 )\n    13000.0\n    > y = base.ceilsd( 0.0313, 2, 2 )\n    0.046875\n\n    See Also\n    --------\n    base.ceil, base.floorsd, base.roundsd, base.truncsd\n","base.cexp":"\nbase.cexp( z )\n    Evaluates the exponential function for a double-precision complex floating-\n    point number.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Complex number.\n\n    Examples\n    --------\n    > var y = base.cexp( new Complex128( 0.0, 0.0 ) )\n    <Complex128>\n    > var re = real( y )\n    1.0\n    > var im = imag( y )\n    0.0\n    > y = base.cexp( new Complex128( 0.0, 1.0 ) )\n    <Complex128>\n    > re = real( y )\n    ~0.540\n    > im = imag( y )\n    ~0.841\n\n","base.cflipsign":"\nbase.cflipsign( z, y )\n    Returns a double-precision complex floating-point number with the same\n    magnitude as `z` and the sign of `y*z`.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    y: number\n        Number from which to derive the sign.\n\n    Returns\n    -------\n    out: Complex128\n        Result.\n\n    Examples\n    --------\n    > var v = base.cflipsign( new Complex128( -4.2, 5.5 ), -9.0 )\n    <Complex128>\n    > var re = real( v )\n    4.2\n    > var im = imag( v )\n    -5.5\n\n    See Also\n    --------\n    base.cneg, base.csignum\n","base.cflipsignf":"\nbase.cflipsignf( z, y )\n    Returns a single-precision complex floating-point number with the same\n    magnitude as `z` and the sign of `y*z`.\n\n    Parameters\n    ----------\n    z: Complex64\n        Complex number.\n\n    y: number\n        Number from which to derive the sign.\n\n    Returns\n    -------\n    out: Complex64\n        Result.\n\n    Examples\n    --------\n    > var v = base.cflipsignf( new Complex64( -4.0, 5.0 ), -9.0 )\n    <Complex64>\n    > var re = realf( v )\n    4.0\n    > var im = imagf( v )\n    -5.0\n\n    See Also\n    --------\n    base.cnegf, base.cflipsign\n","base.cfloor":"\nbase.cfloor( z )\n    Rounds a double-precision complex floating-point number toward negative\n    infinity.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Result.\n\n    Examples\n    --------\n    > var v = base.cfloor( new Complex128( 5.5, 3.3 ) )\n    <Complex128>\n    > var re = real( v )\n    5.0\n    > var im = imag( v )\n    3.0\n\n    See Also\n    --------\n    base.cceil, base.cfloorn, base.cround\n","base.cfloorn":"\nbase.cfloorn( z, n )\n    Rounds each component of a double-precision complex floating-point number\n    to the nearest multiple of `10^n` toward negative infinity.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    n: integer\n        Integer power of 10.\n\n    Returns\n    -------\n    z: Complex128\n        Result.\n\n    Examples\n    --------\n    > var v = base.cfloorn( new Complex128( 5.555, -3.333 ), -2 )\n    <Complex128>\n    > var re = real( v )\n    5.55\n    > var im = imag( v )\n    -3.34\n\n    See Also\n    --------\n    base.cceiln, base.cfloor, base.croundn\n","base.cidentity":"\nbase.cidentity( z )\n    Evaluates the identity function for a double-precision complex floating-\n    point number.\n\n    Parameters\n    ----------\n    z: Complex128\n        Input value.\n\n    Returns\n    -------\n    v: Complex128\n        Input value.\n\n    Examples\n    --------\n    > var v = base.cidentity( new Complex128( -1.0, 2.0 ) )\n    <Complex128>\n    > var re = real( v )\n    -1.0\n    > var img = imag( v )\n    2.0\n\n    See Also\n    --------\n    base.cidentityf, base.identity\n","base.cidentityf":"\nbase.cidentityf( z )\n    Evaluates the identity function for a single-precision complex floating-\n    point number.\n\n    Parameters\n    ----------\n    z: Complex64\n        Input value.\n\n    Returns\n    -------\n    v: Complex64\n        Input value.\n\n    Examples\n    --------\n    > var v = base.cidentityf( new Complex64( -1.0, 2.0 ) )\n    <Complex64>\n    > var re = realf( v )\n    -1.0\n    > var img = imagf( v )\n    2.0\n\n    See Also\n    --------\n    base.cidentity, base.identityf\n","base.cinv":"\nbase.cinv( z )\n    Computes the inverse of a double-precision complex floating-point number.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Result.\n\n    Examples\n    --------\n    > var v = base.cinv( new Complex128( 2.0, 4.0 ) )\n    <Complex128>\n    > var re = real( v )\n    0.1\n    > var im = imag( v )\n    -0.2\n\n    See Also\n    --------\n    base.cdiv\n","base.clamp":"\nbase.clamp( v, min, max )\n    Restricts a double-precision floating-point number to a specified range.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    v: number\n        Value to restrict.\n\n    min: number\n        Minimum value.\n\n    max: number\n        Maximum value.\n\n    Returns\n    -------\n    y: number\n        Restricted value.\n\n    Examples\n    --------\n    > var y = base.clamp( 3.14, 0.0, 5.0 )\n    3.14\n    > y = base.clamp( -3.14, 0.0, 5.0 )\n    0.0\n    > y = base.clamp( 3.14, 0.0, 3.0 )\n    3.0\n    > y = base.clamp( -0.0, 0.0, 5.0 )\n    0.0\n    > y = base.clamp( 0.0, -3.14, -0.0 )\n    -0.0\n    > y = base.clamp( NaN, 0.0, 5.0 )\n    NaN\n\n    See Also\n    --------\n    base.clampf, base.wrap\n","base.clampf":"\nbase.clampf( v, min, max )\n    Restricts a single-precision floating-point number to a specified range.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    v: number\n        Value to restrict.\n\n    min: number\n        Minimum value.\n\n    max: number\n        Maximum value.\n\n    Returns\n    -------\n    y: number\n        Restricted value.\n\n    Examples\n    --------\n    > var y = base.clampf( 3.14, 0.0, 5.0 )\n    3.14\n    > y = base.clampf( -3.14, 0.0, 5.0 )\n    0.0\n    > y = base.clampf( 3.14, 0.0, 3.0 )\n    3.0\n    > y = base.clampf( -0.0, 0.0, 5.0 )\n    0.0\n    > y = base.clampf( 0.0, -3.14, -0.0 )\n    -0.0\n    > y = base.clampf( NaN, 0.0, 5.0 )\n    NaN\n\n    See Also\n    --------\n    base.clamp\n","base.cmul":"\nbase.cmul( z1, z2 )\n    Multiplies two double-precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    z1: Complex128\n        Complex number.\n\n    z2: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Result.\n\n    Examples\n    --------\n    > var z1 = new Complex128( 5.0, 3.0 )\n    <Complex128>\n    > var z2 = new Complex128( -2.0, 1.0 )\n    <Complex128>\n    > var out = base.cmul( z1, z2 )\n    <Complex128>\n    > var re = real( out )\n    -13.0\n    > var im = imag( out )\n    -1.0\n\n    See Also\n    --------\n    base.cadd, base.cdiv, base.csub\n","base.cmulf":"\nbase.cmulf( z1, z2 )\n    Multiplies two single-precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    z1: Complex64\n        Complex number.\n\n    z2: Complex64\n        Complex number.\n\n    Returns\n    -------\n    out: Complex64\n        Result.\n\n    Examples\n    --------\n    > var z1 = new Complex64( 5.0, 3.0 )\n    <Complex64>\n    > var z2 = new Complex64( -2.0, 1.0 )\n    <Complex64>\n    > var out = base.cmulf( z1, z2 )\n    <Complex64>\n    > var re = realf( out )\n    -13.0\n    > var im = imagf( out )\n    -1.0\n\n    See Also\n    --------\n    base.caddf, base.cmul, base.csubf\n","base.cneg":"\nbase.cneg( z )\n    Negates a double-precision complex floating-point number.\n\n    Parameters\n    ----------\n    z: Complex128\n       Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Result.\n\n    Examples\n    --------\n    > var z = new Complex128( -4.2, 5.5 )\n    <Complex128>\n    > var v = base.cneg( z )\n    <Complex128>\n    > var re = real( v )\n    4.2\n    > var im = imag( v )\n    -5.5\n\n    See Also\n    --------\n    base.cabs\n","base.cnegf":"\nbase.cnegf( z )\n    Negates a single-precision complex floating-point number.\n\n    Parameters\n    ----------\n    z: Complex64\n       Complex number.\n\n    Returns\n    -------\n    out: Complex64\n        Result.\n\n    Examples\n    --------\n    > var z = new Complex64( -4.0, 5.0 )\n    <Complex64>\n    > var v = base.cnegf( z )\n    <Complex64>\n    > var re = realf( v )\n    4.0\n    > var im = imagf( v )\n    -5.0\n\n    See Also\n    --------\n    base.cneg, base.cabsf\n","base.codePointAt":"\nbase.codePointAt( str, idx, backward )\n    Returns a Unicode code point from a string at a specified position.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    idx: integer\n        Position. If less than `0`, the string position is determined relative\n        to the end of the input string.\n\n    backward: boolean\n        Backward iteration for low surrogates.\n\n    Returns\n    -------\n    out: integer\n        Unicode code point.\n\n    Examples\n    --------\n    > var out = base.codePointAt( 'last man standing', 4, false )\n    32\n    > out = base.codePointAt( 'presidential election', 8, true )\n    116\n    > out = base.codePointAt( 'अनुच्छेद', 2, false )\n    2369\n    > out = base.codePointAt( '🌷', 1, true )\n    127799\n","base.constantcase":"\nbase.constantcase( str )\n    Converts a string to constant case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Constant-cased string.\n\n    Examples\n    --------\n    > var out = base.constantcase( 'Hello World!' )\n    'HELLO_WORLD'\n    > out = base.constantcase( 'I am a tiny little teapot' )\n    'I_AM_A_TINY_LITTLE_TEAPOT'\n\n    See Also\n    --------\n    base.camelcase, base.lowercase, base.snakecase, base.uppercase","base.continuedFraction":"\nbase.continuedFraction( generator[, options] )\n    Evaluates the continued fraction approximation for the supplied series\n    generator using the modified Lentz algorithm.\n\n    `generator` can be either a function which returns an array with two\n    elements, the `a` and `b` terms of the fraction, or an ES6 Generator object.\n\n    By default, the function computes\n\n             a1\n        ---------------\n        b1 +     a2\n             ----------\n              b2 +   a3\n                  -----\n                  b3 + ...\n\n    To evaluate\n\n        b0 +\t a1\n        ---------------\n        b1 +\t a2\n             ----------\n             b2 +  a3\n                  -----\n                  b3 + ...\n\n    set the `keep` option to `true`.\n\n    Parameters\n    ----------\n    generator: Function\n        Function returning terms of continued fraction expansion.\n\n    options: Object (optional)\n        Options.\n\n    options.maxIter: integer (optional)\n         Maximum number of iterations. Default: `1000000`.\n\n    options.tolerance: number (optional)\n        Further terms are only added as long as the next term is greater than\n        current term times the tolerance. Default: `2.22e-16`.\n\n    options.keep: boolean (optional)\n        Boolean indicating whether to keep the `b0` term in the continued\n        fraction. Default: `false`.\n\n    Returns\n    -------\n    out: number\n       Value of continued fraction.\n\n    Examples\n    --------\n    // Continued fraction for (e-1)^(-1):\n    > function closure() {\n    ...    var i = 0;\n    ...    return function() {\n    ...        i += 1;\n    ...        return [ i, i ];\n    ...    };\n    ... };\n    > var gen = closure();\n    > var out = base.continuedFraction( gen )\n    ~0.582\n\n    // Using an ES6 generator:\n    > function* generator() {\n    ...     var i = 0;\n    ...     while ( true ) {\n    ...         i += 1;\n    ...         yield [ i, i ];\n    ...     }\n    ... };\n    > gen = generator();\n    > out = base.continuedFraction( gen )\n    ~0.582\n\n    // Set options:\n    > out = base.continuedFraction( generator(), { 'keep': true } )\n    ~1.718\n    > out = base.continuedFraction( generator(), { 'maxIter': 10 } )\n    ~0.582\n    > out = base.continuedFraction( generator(), { 'tolerance': 1e-1 } )\n    ~0.579\n\n","base.copysign":"\nbase.copysign( x, y )\n    Returns a double-precision floating-point number with the magnitude of `x`\n    and the sign of `y`.\n\n    Parameters\n    ----------\n    x: number\n        Number from which to derive a magnitude.\n\n    y: number\n        Number from which to derive a sign.\n\n    Returns\n    -------\n    z: number\n        Double-precision floating-point number.\n\n    Examples\n    --------\n    > var z = base.copysign( -3.14, 10.0 )\n    3.14\n    > z = base.copysign( 3.14, -1.0 )\n    -3.14\n    > z = base.copysign( 1.0, -0.0 )\n    -1.0\n    > z = base.copysign( -3.14, -0.0 )\n    -3.14\n    > z = base.copysign( -0.0, 1.0 )\n    0.0\n\n    See Also\n    --------\n    base.flipsign\n","base.copysignf":"\nbase.copysignf( x, y )\n    Returns a single-precision floating-point number with the magnitude of `x`\n    and the sign of `y`.\n\n    Parameters\n    ----------\n    x: number\n        Number from which to derive a magnitude.\n\n    y: number\n        Number from which to derive a sign.\n\n    Returns\n    -------\n    z: number\n        Single-precision floating-point number.\n\n    Examples\n    --------\n    > var z = base.copysignf( -3.0, 10.0 )\n    3.0\n    > z = base.copysignf( 3.0, -1.0 )\n    -3.0\n    > z = base.copysignf( 1.0, -0.0 )\n    -1.0\n    > z = base.copysignf( -3.0, -0.0 )\n    -3.0\n    > z = base.copysignf( -0.0, 1.0 )\n    0.0\n\n    See Also\n    --------\n    base.copysign, base.flipsignf\n","base.cos":"\nbase.cos( x )\n    Computes the cosine of a number.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Cosine.\n\n    Examples\n    --------\n    > var y = base.cos( 0.0 )\n    1.0\n    > y = base.cos( PI/4.0 )\n    ~0.707\n    > y = base.cos( -PI/6.0 )\n    ~0.866\n    > y = base.cos( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cospi, base.cosm1, base.sin, base.tan\n","base.cosd":"\nbase.cosd( x )\n    Computes the cosine of an angle measured in degrees.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in degrees).\n\n    Returns\n    -------\n    y: number\n        Cosine.\n\n    Examples\n    --------\n    > var y = base.cosd( 0.0 )\n    1.0\n    > y = base.cosd( 90.0 )\n    0.0\n    > y = base.cosd( 60.0 )\n    ~0.5\n    > y = base.cosd( NaN )\n    NaN\n\n    See Also\n    --------\n    base.tand\n","base.cosh":"\nbase.cosh( x )\n    Computes the hyperbolic cosine of a double-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Hyperbolic cosine.\n\n    Examples\n    --------\n    > var y = base.cosh( 0.0 )\n    1.0\n    > y = base.cosh( 2.0 )\n    ~3.762\n    > y = base.cosh( -2.0 )\n    ~3.762\n    > y = base.cosh( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cos, base.sinh, base.tanh\n","base.cosm1":"\nbase.cosm1( x )\n    Computes the cosine of a number minus one.\n\n    This function should be used instead of manually calculating `cos(x)-1` when\n    `x` is near unity.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Cosine minus one.\n\n    Examples\n    --------\n    > var y = base.cosm1( 0.0 )\n    0.0\n    > y = base.cosm1( PI/4.0 )\n    ~-0.293\n    > y = base.cosm1( -PI/6.0 )\n    ~-0.134\n    > y = base.cosm1( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cos\n","base.cospi":"\nbase.cospi( x )\n    Computes the value of `cos(πx)`.\n\n    This function computes `cos(πx)` more accurately than the obvious approach,\n    especially for large `x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.cospi( 0.0 )\n    1.0\n    > y = base.cospi( 0.5 )\n    0.0\n    > y = base.cospi( 0.1 )\n    ~0.951\n    > y = base.cospi( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cos\n","base.cot":"\nbase.cot( x )\n    Computes the cotangent of a number.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Cotangent.\n\n    Examples\n    --------\n    > var y = base.cot( 0.0 )\n    Infinity\n    > y = base.cot( -PI/4.0 )\n    ~-1.0\n    > y = base.cot( PI/4.0 )\n    ~1.0\n    > y = base.cot( NaN )\n    NaN\n\n    See Also\n    --------\n    base.csc, base.tan\n","base.cotd":"\nbase.cotd( x )\n    Computes the cotangent of an angle measured in degrees.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in degrees).\n\n    Returns\n    -------\n    y: number\n        Cotangent.\n\n    Examples\n    --------\n    > var y = base.cotd( 0.0 )\n    Infinity\n    > y = base.cotd( 90.0 )\n    0.0\n    > y = base.cotd( 60.0 )\n    ~0.58\n    > y = base.cotd( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cscd, base.secd, base.tand\n","base.coth":"\nbase.coth( x )\n    Computes the hyperbolic cotangent of a number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Hyperbolic cotangent.\n\n    Examples\n    --------\n    > var y = base.coth( 0.0 )\n    Infinity\n    > y = base.coth( -0.0 )\n    -Infinity\n    > y = base.coth( 2.0 )\n    ~1.0373\n    > y = base.coth( -2.0 )\n    ~-1.0373\n    > y = base.coth( +Infinity )\n    ~1\n    > y = base.coth( -Infinity )\n    ~-1\n    > y = base.coth( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acoth, base.cot, base.csch, base.tanh\n","base.covercos":"\nbase.covercos( x )\n    Computes the coversed cosine.\n\n    The coversed cosine is defined as `1 + sin(x)`.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Coversed cosine.\n\n    Examples\n    --------\n    > var y = base.covercos( 3.14 )\n    ~1.0016\n    > y = base.covercos( -4.2 )\n    ~1.8716\n    > y = base.covercos( -4.6 )\n    ~1.9937\n    > y = base.covercos( 9.5 )\n    ~0.9248\n    > y = base.covercos( -0.0 )\n    1.0\n\n    See Also\n    --------\n    base.coversin, base.vercos\n","base.coversin":"\nbase.coversin( x )\n    Computes the coversed sine.\n\n    The coversed sine is defined as `1 - sin(x)`.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Coversed sine.\n\n    Examples\n    --------\n    > var y = base.coversin( 3.14 )\n    ~0.9984\n    > y = base.coversin( -4.2 )\n    ~0.1284\n    > y = base.coversin( -4.6 )\n    ~0.0063\n    > y = base.coversin( 9.5 )\n    ~1.0752\n    > y = base.coversin( -0.0 )\n    1.0\n\n    See Also\n    --------\n    base.covercos, base.versin\n","base.cphase":"\nbase.cphase( z )\n    Computes the argument of a double-precision complex floating-point number\n    in radians.\n\n    The argument of a complex number, also known as the phase, is the angle of\n    the radius extending from the origin to the complex number plotted in the\n    complex plane and the positive real axis.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    phi: number\n        Argument.\n\n    Examples\n    --------\n    > var phi = base.cphase( new Complex128( 5.0, 3.0 ) )\n    ~0.5404\n\n    See Also\n    --------\n    base.cabs\n","base.cpolar":"\nbase.cpolar( z )\n    Returns the absolute value and phase of a double-precision complex\n    floating-point number.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Array<number>\n        Absolute value and phase, respectively.\n\n    Examples\n    --------\n    > var out = base.cpolar( new Complex128( 5.0, 3.0 ) )\n    [ ~5.83, ~0.5404 ]\n\n\nbase.cpolar.assign( z, out, stride, offset )\n    Returns the absolute value and phase of a double-precision complex\n    floating-point number and assigns results to a provided output array.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    out: Array|TypedArray|Object\n        Destination array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Absolute value and phase, respectively.\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var v = base.cpolar.assign( new Complex128( 5.0, 3.0 ), out, 1, 0 )\n    <Float64Array>[ ~5.83, ~0.5404 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.cabs, base.cphase","base.cpolar.assign":"\nbase.cpolar.assign( z, out, stride, offset )\n    Returns the absolute value and phase of a double-precision complex\n    floating-point number and assigns results to a provided output array.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    out: Array|TypedArray|Object\n        Destination array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Absolute value and phase, respectively.\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var v = base.cpolar.assign( new Complex128( 5.0, 3.0 ), out, 1, 0 )\n    <Float64Array>[ ~5.83, ~0.5404 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.cabs, base.cphase","base.cround":"\nbase.cround( z )\n    Rounds each component of a double-precision complex floating-point number\n    to the nearest integer.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Rounded complex number.\n\n    Examples\n    --------\n    > var v = base.cround( new Complex128( 5.5, 3.3 ) )\n    <Complex128>\n    > var re = real( v )\n    6.0\n    > var im = imag( v )\n    3.0\n\n    See Also\n    --------\n    base.cceil, base.cfloor, base.croundn\n","base.croundn":"\nbase.croundn( z, n )\n    Rounds each component of a double-precision complex floating-point number\n    to the nearest multiple of `10^n`.\n\n    When operating on floating-point numbers in bases other than `2`, rounding\n    to specified digits can be inexact.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    n: integer\n        Integer power of 10.\n\n    Returns\n    -------\n    out: Complex128\n        Result.\n\n    Examples\n    --------\n    > var v = base.croundn( new Complex128( 5.555, -3.336 ), -2 )\n    <Complex128>\n    > var re = real( v )\n    5.56\n    > var im = imag( v )\n    -3.34\n\n    See Also\n    --------\n    base.cceiln, base.cfloorn, base.cround\n","base.csc":"\nbase.csc( x )\n    Computes the cosecant of a number.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Cosecant.\n\n    Examples\n    --------\n    > var y = base.csc( 0.0 )\n    Infinity\n    > y = base.csc( PI/2.0 )\n    ~1.0\n    > y = base.csc( -PI/6.0 )\n    ~-2.0\n    > y = base.csc( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cot, base.sin","base.cscd":"\nbase.cscd( x )\n    Computes the cosecant of a degree.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in degrees).\n\n    Returns\n    -------\n    y: number\n        Cosecant.\n\n    Examples\n    --------\n    > var y = base.cscd( 1.0 )\n    ~57.30\n    > y = base.cscd( PI )\n    ~18.25\n    > y = base.cscd( -PI )\n    ~-18.25\n    > y = base.cscd( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cotd, base.secd\n","base.csch":"\nbase.csch( x )\n    Computes the hyperbolic cosecant of a number.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Hyperbolic cosecant.\n\n    Examples\n    --------\n    > var y = base.csch( +0.0 )\n    +Infinity\n    > var y = base.csch( -0.0 )\n    -Infinity\n    > var y = base.csch( +Infinity )\n    +0.0\n    > var y = base.csch( -Infinity )\n    -0.0\n    > y = base.csch( 2.0 )\n    ~0.2757\n    > y = base.csch( -2.0 )\n    ~-0.2757\n    > y = base.csch( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acsch, base.csc, base.coth, base.sinh\n","base.csignum":"\nbase.csignum( z )\n    Evaluates the signum function of a double-precision complex floating-point\n    number.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Result.\n\n    Examples\n    --------\n    > var v = base.csignum( new Complex128( -4.2, 5.5 ) )\n    <Complex128>\n    > var re = real( v )\n    -0.6069136033622302\n    > var im = imag( v )\n    0.79476781392673\n\n    See Also\n    --------\n    base.signum\n","base.csub":"\nbase.csub( z1, z2 )\n    Subtracts two double-precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    z1: Complex128\n        Complex number.\n\n    z2: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Result.\n\n    Examples\n    --------\n    > var z1 = new Complex128( 5.0, 3.0 )\n    <Complex128>\n    > var z2 = new Complex128( -2.0, 1.0 )\n    <Complex128>\n    > var out = base.csub( z1, z2 )\n    <Complex128>\n    > var re = real( out )\n    7.0\n    > var im = imag( out )\n    2.0\n\n    See Also\n    --------\n    base.cadd, base.cdiv, base.cmul\n","base.csubf":"\nbase.csubf( z1, z2 )\n    Subtracts two single-precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    z1: Complex64\n        Complex number.\n\n    z2: Complex64\n        Complex number.\n\n    Returns\n    -------\n    out: Complex64\n        Result.\n\n    Examples\n    --------\n    > var z1 = new Complex64( 5.0, 3.0 )\n    <Complex64>\n    > var z2 = new Complex64( -2.0, 1.0 )\n    <Complex64>\n    > var out = base.csubf( z1, z2 )\n    <Complex64>\n    > var re = realf( out )\n    7.0\n    > var im = imagf( out )\n    2.0\n\n    See Also\n    --------\n    base.caddf, base.cmulf, base.csub\n","base.deg2rad":"\nbase.deg2rad( x )\n    Converts an angle from degrees to radians.\n\n    Parameters\n    ----------\n    x: number\n        Angle in degrees.\n\n    Returns\n    -------\n    r: number\n        Angle in radians.\n\n    Examples\n    --------\n    > var r = base.deg2rad( 90.0 )\n    ~1.571\n    > r = base.deg2rad( -45.0 )\n    ~-0.785\n    > r = base.deg2rad( NaN )\n    NaN\n\n    See Also\n    --------\n    base.rad2deg\n","base.deg2radf":"\nbase.deg2radf( x )\n    Converts an angle from degrees to radians (single-precision).\n\n    Parameters\n    ----------\n    x: number\n        Angle in degrees.\n\n    Returns\n    -------\n    r: number\n        Angle in radians.\n\n    Examples\n    --------\n    > var r = base.deg2radf( 90.0 )\n    ~1.571\n    > r = base.deg2radf( -45.0 )\n    ~-0.785\n    > r = base.deg2radf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.deg2rad, base.rad2degf\n","base.digamma":"\nbase.digamma( x )\n    Evaluates the digamma function.\n\n    If `x` is zero or a negative integer, the function returns `NaN`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.digamma( -2.5 )\n    ~1.103\n    > y = base.digamma( 1.0 )\n    ~-0.577\n    > y = base.digamma( 10.0 )\n    ~2.252\n    > y = base.digamma( NaN )\n    NaN\n    > y = base.digamma( -1.0 )\n    NaN\n\n    See Also\n    --------\n    base.gamma, base.trigamma\n","base.diracDelta":"\nbase.diracDelta( x )\n    Evaluates the Dirac delta function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.diracDelta( 3.14 )\n    0.0\n    > y = base.diracDelta( 0.0 )\n    Infinity\n\n    See Also\n    --------\n    base.kroneckerDelta\n","base.div":"\nbase.div( x, y )\n    Divides two double-precision floating-point numbers `x` and `y`.\n\n    Parameters\n    ----------\n    x: number\n        First input value (dividend).\n\n    y: number\n        Second input value (divisor).\n\n    Returns\n    -------\n    z: number\n        Result.\n\n    Examples\n    --------\n    > var v = base.div( -1.0, 5.0 )\n    -0.2\n    > v = base.div( 2.0, 5.0 )\n    0.4\n    > v = base.div( 0.0, 5.0 )\n    0.0\n    > v = base.div( -0.0, 5.0 )\n    -0.0\n    > v = base.div( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.add, base.mul, base.sub\n","base.divf":"\nbase.divf( x, y )\n    Divides two single-precision floating-point numbers `x` and `y`.\n\n    Parameters\n    ----------\n    x: number\n        First input value (dividend).\n\n    y: number\n        Second input value (divisor).\n\n    Returns\n    -------\n    z: number\n        Result.\n\n    Examples\n    --------\n    > var v = base.divf( -1.0, 5.0 )\n    ~-0.2\n    > v = base.divf( 2.0, 5.0 )\n    ~0.4\n    > v = base.divf( 0.0, 5.0 )\n    0.0\n    > v = base.divf( -0.0, 5.0 )\n    -0.0\n    > v = base.divf( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.addf, base.div, base.mulf, base.subf\n","base.dotcase":"\nbase.dotcase( str )\n    Converts a string to dot case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Dot-cased string.\n\n    Examples\n    --------\n    > var out = base.dotcase( 'Hello World!' )\n    'hello.world'\n    > out = base.dotcase( 'I am a tiny little teapot' )\n    'i.am.a.tiny.little.teapot'\n\n    See Also\n    --------\n    base.camelcase, base.lowercase, base.snakecase, base.uppercase","base.dists.arcsine.Arcsine":"\nbase.dists.arcsine.Arcsine( [a, b] )\n    Returns an arcsine distribution object.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support. Must be less than `b`. Default: `0.0`.\n\n    b: number (optional)\n        Maximum support. Must be greater than `a`. Default: `1.0`.\n\n    Returns\n    -------\n    arcsine: Object\n        Distribution instance.\n\n    arcsine.a: number\n        Minimum support. If set, the value must be less than `b`.\n\n    arcsine.b: number\n        Maximum support. If set, the value must be greater than `a`.\n\n    arcsine.entropy: number\n        Read-only property which returns the differential entropy.\n\n    arcsine.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    arcsine.mean: number\n        Read-only property which returns the expected value.\n\n    arcsine.median: number\n        Read-only property which returns the median.\n\n    arcsine.mode: number\n        Read-only property which returns the mode.\n\n    arcsine.skewness: number\n        Read-only property which returns the skewness.\n\n    arcsine.stdev: number\n        Read-only property which returns the standard deviation.\n\n    arcsine.variance: number\n        Read-only property which returns the variance.\n\n    arcsine.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    arcsine.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    arcsine.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    arcsine.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    arcsine.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var arcsine = base.dists.arcsine.Arcsine( 0.0, 1.0 );\n    > arcsine.a\n    0.0\n    > arcsine.b\n    1.0\n    > arcsine.entropy\n    ~-0.242\n    > arcsine.kurtosis\n    -1.5\n    > arcsine.mean\n    0.5\n    > arcsine.median\n    0.5\n    > arcsine.mode\n    0.0\n    > arcsine.skewness\n    0.0\n    > arcsine.stdev\n    ~0.354\n    > arcsine.variance\n    0.125\n    > arcsine.cdf( 0.8 )\n    ~0.705\n    > arcsine.logcdf( 0.8 )\n    ~-0.35\n    > arcsine.logpdf( 0.4 )\n    ~-0.431\n    > arcsine.pdf( 0.8 )\n    ~0.796\n    > arcsine.quantile( 0.8 )\n    ~0.905\n\n","base.dists.arcsine.cdf":"\nbase.dists.arcsine.cdf( x, a, b )\n    Evaluates the cumulative distribution function (CDF) for an arcsine\n    distribution with minimum support `a` and maximum support `b` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.arcsine.cdf( 9.0, 0.0, 10.0 )\n    ~0.795\n    > y = base.dists.arcsine.cdf( 0.5, 0.0, 2.0 )\n    ~0.333\n    > y = base.dists.arcsine.cdf( PINF, 2.0, 4.0 )\n    1.0\n    > y = base.dists.arcsine.cdf( NINF, 2.0, 4.0 )\n    0.0\n    > y = base.dists.arcsine.cdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.arcsine.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.arcsine.cdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.arcsine.cdf( 2.0, 1.0, 0.0 )\n    NaN\n\n\nbase.dists.arcsine.cdf.factory( a, b )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an arcsine distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.arcsine.cdf.factory( 0.0, 10.0 );\n    > var y = mycdf( 0.5 )\n    ~0.144\n    > y = mycdf( 8.0 )\n    ~0.705\n\n","base.dists.arcsine.cdf.factory":"\nbase.dists.arcsine.cdf.factory( a, b )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an arcsine distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.arcsine.cdf.factory( 0.0, 10.0 );\n    > var y = mycdf( 0.5 )\n    ~0.144\n    > y = mycdf( 8.0 )\n    ~0.705","base.dists.arcsine.entropy":"\nbase.dists.arcsine.entropy( a, b )\n    Returns the differential entropy of an arcsine distribution (in nats).\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.arcsine.entropy( 0.0, 1.0 )\n    ~-0.242\n    > v = base.dists.arcsine.entropy( 4.0, 12.0 )\n    ~1.838\n    > v = base.dists.arcsine.entropy( 2.0, 8.0 )\n    ~1.55\n\n","base.dists.arcsine.kurtosis":"\nbase.dists.arcsine.kurtosis( a, b )\n    Returns the excess kurtosis of an arcsine distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.arcsine.kurtosis( 0.0, 1.0 )\n    -1.5\n    > v = base.dists.arcsine.kurtosis( 4.0, 12.0 )\n    -1.5\n    > v = base.dists.arcsine.kurtosis( 2.0, 8.0 )\n    -1.5\n\n","base.dists.arcsine.logcdf":"\nbase.dists.arcsine.logcdf( x, a, b )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for an\n    arcsine distribution with minimum support `a` and maximum support `b` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.arcsine.logcdf( 9.0, 0.0, 10.0 )\n    ~-0.229\n    > y = base.dists.arcsine.logcdf( 0.5, 0.0, 2.0 )\n    ~-1.1\n    > y = base.dists.arcsine.logcdf( PINF, 2.0, 4.0 )\n    0.0\n    > y = base.dists.arcsine.logcdf( NINF, 2.0, 4.0 )\n    -Infinity\n    > y = base.dists.arcsine.logcdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.arcsine.logcdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.arcsine.logcdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.arcsine.logcdf( 2.0, 1.0, 0.0 )\n    NaN\n\n\nbase.dists.arcsine.logcdf.factory( a, b )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of an arcsine distribution with minimum support\n    `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.arcsine.logcdf.factory( 0.0, 10.0 );\n    > var y = mylogcdf( 0.5 )\n    ~-1.941\n    > y = mylogcdf( 8.0 )\n    ~-0.35\n\n","base.dists.arcsine.logcdf.factory":"\nbase.dists.arcsine.logcdf.factory( a, b )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of an arcsine distribution with minimum support\n    `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.arcsine.logcdf.factory( 0.0, 10.0 );\n    > var y = mylogcdf( 0.5 )\n    ~-1.941\n    > y = mylogcdf( 8.0 )\n    ~-0.35","base.dists.arcsine.logpdf":"\nbase.dists.arcsine.logpdf( x, a, b )\n    Evaluates the logarithm of the probability density function (PDF) for an\n    arcsine distribution with minimum support `a` and maximum support `b` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.arcsine.logpdf( 2.0, 0.0, 4.0 )\n    ~-1.838\n    > y = base.dists.arcsine.logpdf( 5.0, 0.0, 4.0 )\n    -Infinity\n    > y = base.dists.arcsine.logpdf( 0.25, 0.0, 1.0 )\n    ~-0.308\n    > y = base.dists.arcsine.logpdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.arcsine.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.arcsine.logpdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.arcsine.logpdf( 2.0, 3.0, 1.0 )\n    NaN\n\n\nbase.dists.arcsine.logpdf.factory( a, b )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of an arcsine distribution with minimum support `a` and\n    maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.arcsine.logpdf.factory( 6.0, 7.0 );\n    > var y = mylogPDF( 7.0 )\n    Infinity\n    > y = mylogPDF( 5.0 )\n    -Infinity\n\n","base.dists.arcsine.logpdf.factory":"\nbase.dists.arcsine.logpdf.factory( a, b )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of an arcsine distribution with minimum support `a` and\n    maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.arcsine.logpdf.factory( 6.0, 7.0 );\n    > var y = mylogPDF( 7.0 )\n    Infinity\n    > y = mylogPDF( 5.0 )\n    -Infinity","base.dists.arcsine.mean":"\nbase.dists.arcsine.mean( a, b )\n    Returns the expected value of an arcsine distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.arcsine.mean( 0.0, 1.0 )\n    0.5\n    > v = base.dists.arcsine.mean( 4.0, 12.0 )\n    8.0\n    > v = base.dists.arcsine.mean( 2.0, 8.0 )\n    5.0\n\n","base.dists.arcsine.median":"\nbase.dists.arcsine.median( a, b )\n    Returns the median of an arcsine distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.arcsine.median( 0.0, 1.0 )\n    0.5\n    > v = base.dists.arcsine.median( 4.0, 12.0 )\n    8.0\n    > v = base.dists.arcsine.median( 2.0, 8.0 )\n    5.0\n\n","base.dists.arcsine.mode":"\nbase.dists.arcsine.mode( a, b )\n    Returns the mode of an arcsine distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.arcsine.mode( 0.0, 1.0 )\n    0.0\n    > v = base.dists.arcsine.mode( 4.0, 12.0 )\n    4.0\n    > v = base.dists.arcsine.mode( 2.0, 8.0 )\n    2.0\n\n","base.dists.arcsine.pdf":"\nbase.dists.arcsine.pdf( x, a, b )\n    Evaluates the probability density function (PDF) for an arcsine distribution\n    with minimum support `a` and maximum support `b` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.arcsine.pdf( 2.0, 0.0, 4.0 )\n    ~0.159\n    > y = base.dists.arcsine.pdf( 5.0, 0.0, 4.0 )\n    0.0\n    > y = base.dists.arcsine.pdf( 0.25, 0.0, 1.0 )\n    ~0.735\n    > y = base.dists.arcsine.pdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.arcsine.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.arcsine.pdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.arcsine.pdf( 2.0, 3.0, 1.0 )\n    NaN\n\n\nbase.dists.arcsine.pdf.factory( a, b )\n    Returns a function for evaluating the probability density function (PDF) of\n    an arcsine distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.arcsine.pdf.factory( 6.0, 7.0 );\n    > var y = myPDF( 7.0 )\n    Infinity\n    > y = myPDF( 5.0 )\n    0.0\n\n","base.dists.arcsine.pdf.factory":"\nbase.dists.arcsine.pdf.factory( a, b )\n    Returns a function for evaluating the probability density function (PDF) of\n    an arcsine distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.arcsine.pdf.factory( 6.0, 7.0 );\n    > var y = myPDF( 7.0 )\n    Infinity\n    > y = myPDF( 5.0 )\n    0.0","base.dists.arcsine.quantile":"\nbase.dists.arcsine.quantile( p, a, b )\n    Evaluates the quantile function for an arcsine distribution with minimum\n    support `a` and maximum support `b` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.arcsine.quantile( 0.8, 0.0, 1.0 )\n    ~0.905\n    > y = base.dists.arcsine.quantile( 0.5, 0.0, 10.0 )\n    ~5.0\n\n    > y = base.dists.arcsine.quantile( 1.1, 0.0, 1.0 )\n    NaN\n    > y = base.dists.arcsine.quantile( -0.2, 0.0, 1.0 )\n    NaN\n\n    > y = base.dists.arcsine.quantile( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.arcsine.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.arcsine.quantile( 0.0, 0.0, NaN )\n    NaN\n\n    > y = base.dists.arcsine.quantile( 0.5, 2.0, 1.0 )\n    NaN\n\n\nbase.dists.arcsine.quantile.factory( a, b )\n    Returns a function for evaluating the quantile function of an arcsine\n    distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.arcsine.quantile.factory( 0.0, 4.0 );\n    > var y = myQuantile( 0.8 )\n    ~3.618\n\n","base.dists.arcsine.quantile.factory":"\nbase.dists.arcsine.quantile.factory( a, b )\n    Returns a function for evaluating the quantile function of an arcsine\n    distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.arcsine.quantile.factory( 0.0, 4.0 );\n    > var y = myQuantile( 0.8 )\n    ~3.618","base.dists.arcsine.skewness":"\nbase.dists.arcsine.skewness( a, b )\n    Returns the skewness of an arcsine distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.arcsine.skewness( 0.0, 1.0 )\n    0.0\n    > v = base.dists.arcsine.skewness( 4.0, 12.0 )\n    0.0\n    > v = base.dists.arcsine.skewness( 2.0, 8.0 )\n    0.0\n\n","base.dists.arcsine.stdev":"\nbase.dists.arcsine.stdev( a, b )\n    Returns the standard deviation of an arcsine distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.arcsine.stdev( 0.0, 1.0 )\n    ~0.354\n    > v = base.dists.arcsine.stdev( 4.0, 12.0 )\n    ~2.828\n    > v = base.dists.arcsine.stdev( 2.0, 8.0 )\n    ~2.121\n\n","base.dists.arcsine.variance":"\nbase.dists.arcsine.variance( a, b )\n    Returns the variance of an arcsine distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.arcsine.variance( 0.0, 1.0 )\n    ~0.125\n    > v = base.dists.arcsine.variance( 4.0, 12.0 )\n    8.0\n    > v = base.dists.arcsine.variance( 2.0, 8.0 )\n    ~4.5\n\n","base.dists.bernoulli.Bernoulli":"\nbase.dists.bernoulli.Bernoulli( [p] )\n    Returns a Bernoulli distribution object.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability. Must be between `0` and `1`. Default: `0.5`.\n\n    Returns\n    -------\n    bernoulli: Object\n        Distribution instance.\n\n    bernoulli.p: number\n        Success probability. If set, the value must be between `0` and `1`.\n\n    bernoulli.entropy: number\n        Read-only property which returns the differential entropy.\n\n    bernoulli.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    bernoulli.mean: number\n        Read-only property which returns the expected value.\n\n    bernoulli.median: number\n        Read-only property which returns the median.\n\n    bernoulli.skewness: number\n        Read-only property which returns the skewness.\n\n    bernoulli.stdev: number\n        Read-only property which returns the standard deviation.\n\n    bernoulli.variance: number\n        Read-only property which returns the variance.\n\n    bernoulli.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    bernoulli.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    bernoulli.pmf: Function\n        Evaluates the probability mass function (PMF).\n\n    bernoulli.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var bernoulli = base.dists.bernoulli.Bernoulli( 0.6 );\n    > bernoulli.p\n    0.6\n    > bernoulli.entropy\n    ~0.673\n    > bernoulli.kurtosis\n    ~-1.833\n    > bernoulli.mean\n    0.6\n    > bernoulli.median\n    1.0\n    > bernoulli.skewness\n    ~-0.408\n    > bernoulli.stdev\n    ~0.49\n    > bernoulli.variance\n    ~0.24\n    > bernoulli.cdf( 0.5 )\n    0.4\n    > bernoulli.mgf( 3.0 )\n    ~12.451\n    > bernoulli.pmf( 0.0 )\n    0.4\n    > bernoulli.quantile( 0.7 )\n    1.0\n\n","base.dists.bernoulli.cdf":"\nbase.dists.bernoulli.cdf( x, p )\n    Evaluates the cumulative distribution function (CDF) for a Bernoulli\n    distribution with success probability `p` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.bernoulli.cdf( 0.5, 0.5 )\n    0.5\n    > y = base.dists.bernoulli.cdf( 0.8, 0.1 )\n    0.9\n    > y = base.dists.bernoulli.cdf( -1.0, 0.4 )\n    0.0\n    > y = base.dists.bernoulli.cdf( 1.5, 0.4 )\n    1.0\n    > y = base.dists.bernoulli.cdf( NaN, 0.5 )\n    NaN\n    > y = base.dists.bernoulli.cdf( 0.0, NaN )\n    NaN\n    // Invalid probability:\n    > y = base.dists.bernoulli.cdf( 2.0, 1.4 )\n    NaN\n\n\nbase.dists.bernoulli.cdf.factory( p )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Bernoulli distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.bernoulli.cdf.factory( 0.5 );\n    > var y = mycdf( 3.0 )\n    1.0\n    > y = mycdf( 0.7 )\n    0.5\n\n","base.dists.bernoulli.cdf.factory":"\nbase.dists.bernoulli.cdf.factory( p )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Bernoulli distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.bernoulli.cdf.factory( 0.5 );\n    > var y = mycdf( 3.0 )\n    1.0\n    > y = mycdf( 0.7 )\n    0.5","base.dists.bernoulli.entropy":"\nbase.dists.bernoulli.entropy( p )\n    Returns the entropy of a Bernoulli distribution with success probability\n    `p` (in nats).\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.bernoulli.entropy( 0.1 )\n    ~0.325\n    > v = base.dists.bernoulli.entropy( 0.5 )\n    ~0.693\n\n","base.dists.bernoulli.kurtosis":"\nbase.dists.bernoulli.kurtosis( p )\n    Returns the excess kurtosis of a Bernoulli distribution with success\n    probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.bernoulli.kurtosis( 0.1 )\n    ~5.111\n    > v = base.dists.bernoulli.kurtosis( 0.5 )\n    -2.0\n\n","base.dists.bernoulli.mean":"\nbase.dists.bernoulli.mean( p )\n    Returns the expected value of a Bernoulli distribution with success\n    probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.bernoulli.mean( 0.1 )\n    0.1\n    > v = base.dists.bernoulli.mean( 0.5 )\n    0.5\n\n","base.dists.bernoulli.median":"\nbase.dists.bernoulli.median( p )\n    Returns the median of a Bernoulli distribution with success probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: integer\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.bernoulli.median( 0.1 )\n    0\n    > v = base.dists.bernoulli.median( 0.8 )\n    1\n\n","base.dists.bernoulli.mgf":"\nbase.dists.bernoulli.mgf( t, p )\n    Evaluates the moment-generating function (MGF) for a Bernoulli\n    distribution with success probability `p` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.bernoulli.mgf( 0.2, 0.5 )\n    ~1.111\n    > y = base.dists.bernoulli.mgf( 0.4, 0.5 )\n    ~1.246\n    > y = base.dists.bernoulli.mgf( NaN, 0.0 )\n    NaN\n    > y = base.dists.bernoulli.mgf( 0.0, NaN )\n    NaN\n    > y = base.dists.bernoulli.mgf( -2.0, -1.0 )\n    NaN\n    > y = base.dists.bernoulli.mgf( 0.2, 2.0 )\n    NaN\n\n\nbase.dists.bernoulli.mgf.factory( p )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Bernoulli distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.bernoulli.mgf.factory( 0.8 );\n    > var y = mymgf( -0.2 )\n    ~0.855\n\n","base.dists.bernoulli.mgf.factory":"\nbase.dists.bernoulli.mgf.factory( p )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Bernoulli distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.bernoulli.mgf.factory( 0.8 );\n    > var y = mymgf( -0.2 )\n    ~0.855","base.dists.bernoulli.mode":"\nbase.dists.bernoulli.mode( p )\n    Returns the mode of a Bernoulli distribution with success probability `p`.\n\n    For `p = 0.5`, the mode is either `0` or `1`. This implementation returns\n    `0` for `p = 0.5`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: integer\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.bernoulli.mode( 0.1 )\n    0\n    > v = base.dists.bernoulli.mode( 0.8 )\n    1\n\n","base.dists.bernoulli.pmf":"\nbase.dists.bernoulli.pmf( x, p )\n    Evaluates the probability mass function (PMF) for a Bernoulli distribution\n    with success probability `p` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated PMF.\n\n    Examples\n    --------\n    > var y = base.dists.bernoulli.pmf( 1.0, 0.3 )\n    0.3\n    > y = base.dists.bernoulli.pmf( 0.0, 0.7 )\n    0.3\n    > y = base.dists.bernoulli.pmf( -1.0, 0.5 )\n    0.0\n    > y = base.dists.bernoulli.pmf( 0.0, NaN )\n    NaN\n    > y = base.dists.bernoulli.pmf( NaN, 0.5 )\n    NaN\n    // Invalid success probability:\n    > y = base.dists.bernoulli.pmf( 0.0, 1.5 )\n    NaN\n\n\nbase.dists.bernoulli.pmf.factory( p )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    Bernoulli distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var mypmf = base.dists.bernoulli.pmf.factory( 0.5 );\n    > var y = mypmf( 1.0 )\n    0.5\n    > y = mypmf( 0.0 )\n    0.5\n\n","base.dists.bernoulli.pmf.factory":"\nbase.dists.bernoulli.pmf.factory( p )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    Bernoulli distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var mypmf = base.dists.bernoulli.pmf.factory( 0.5 );\n    > var y = mypmf( 1.0 )\n    0.5\n    > y = mypmf( 0.0 )\n    0.5","base.dists.bernoulli.quantile":"\nbase.dists.bernoulli.quantile( r, p )\n    Evaluates the quantile function for a Bernoulli distribution with success\n    probability `p` at a probability `r`.\n\n    If `r < 0` or `r > 1`, the function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    r: number\n        Input probability.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.bernoulli.quantile( 0.8, 0.4 )\n    1\n    > y = base.dists.bernoulli.quantile( 0.5, 0.4 )\n    0\n    > y = base.dists.bernoulli.quantile( 0.9, 0.1 )\n    0\n\n    > y = base.dists.bernoulli.quantile( -0.2, 0.1 )\n    NaN\n\n    > y = base.dists.bernoulli.quantile( NaN, 0.8 )\n    NaN\n    > y = base.dists.bernoulli.quantile( 0.4, NaN )\n    NaN\n\n    > y = base.dists.bernoulli.quantile( 0.5, -1.0 )\n    NaN\n    > y = base.dists.bernoulli.quantile( 0.5, 1.5 )\n    NaN\n\n\nbase.dists.bernoulli.quantile.factory( p )\n    Returns a function for evaluating the quantile function of a Bernoulli\n    distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.bernoulli.quantile.factory( 0.4 );\n    > var y = myquantile( 0.4 )\n    0\n    > y = myquantile( 0.8 )\n    1\n    > y = myquantile( 1.0 )\n    1\n\n","base.dists.bernoulli.quantile.factory":"\nbase.dists.bernoulli.quantile.factory( p )\n    Returns a function for evaluating the quantile function of a Bernoulli\n    distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.bernoulli.quantile.factory( 0.4 );\n    > var y = myquantile( 0.4 )\n    0\n    > y = myquantile( 0.8 )\n    1\n    > y = myquantile( 1.0 )\n    1","base.dists.bernoulli.skewness":"\nbase.dists.bernoulli.skewness( p )\n    Returns the skewness of a Bernoulli distribution with success probability\n    `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.bernoulli.skewness( 0.1 )\n    ~2.667\n    > v = base.dists.bernoulli.skewness( 0.5 )\n    0.0\n\n","base.dists.bernoulli.stdev":"\nbase.dists.bernoulli.stdev( p )\n    Returns the standard deviation of a Bernoulli distribution with success\n    probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.bernoulli.stdev( 0.1 )\n    ~0.3\n    > v = base.dists.bernoulli.stdev( 0.5 )\n    0.5\n\n","base.dists.bernoulli.variance":"\nbase.dists.bernoulli.variance( p )\n    Returns the variance of a Bernoulli distribution with success probability\n    `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.bernoulli.variance( 0.1 )\n    ~0.09\n    > v = base.dists.bernoulli.variance( 0.5 )\n    0.25\n\n","base.dists.beta.Beta":"\nbase.dists.beta.Beta( [α, β] )\n    Returns a beta distribution object.\n\n    Parameters\n    ----------\n    α: number (optional)\n        First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n    β: number (optional)\n        Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    beta: Object\n        Distribution instance.\n\n    beta.alpha: number\n        First shape parameter. If set, the value must be greater than `0`.\n\n    beta.beta: number\n        Second shape parameter. If set, the value must be greater than `0`.\n\n    beta.entropy: number\n        Read-only property which returns the differential entropy.\n\n    beta.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    beta.mean: number\n        Read-only property which returns the expected value.\n\n    beta.median: number\n        Read-only property which returns the median.\n\n    beta.mode: number\n        Read-only property which returns the mode.\n\n    beta.skewness: number\n        Read-only property which returns the skewness.\n\n    beta.stdev: number\n        Read-only property which returns the standard deviation.\n\n    beta.variance: number\n        Read-only property which returns the variance.\n\n    beta.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    beta.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    beta.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    beta.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    beta.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    beta.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var beta = base.dists.beta.Beta( 1.0, 1.0 );\n    > beta.alpha\n    1.0\n    > beta.beta\n    1.0\n    > beta.entropy\n    0.0\n    > beta.kurtosis\n    -1.2\n    > beta.mean\n    0.5\n    > beta.median\n    0.5\n    > beta.mode\n    NaN\n    > beta.skewness\n    0.0\n    > beta.stdev\n    ~0.289\n    > beta.variance\n    ~0.0833\n    > beta.cdf( 0.8 )\n    0.8\n    > beta.logcdf( 0.8 )\n    ~-0.223\n    > beta.logpdf( 1.0 )\n    0.0\n    > beta.mgf( 3.14 )\n    ~7.0394\n    > beta.pdf( 1.0 )\n    1.0\n    > beta.quantile( 0.8 )\n    0.8\n\n","base.dists.beta.cdf":"\nbase.dists.beta.cdf( x, α, β )\n    Evaluates the cumulative distribution function (CDF) for a beta distribution\n    with first shape parameter `α` and second shape parameter `β` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.beta.cdf( 0.5, 1.0, 1.0 )\n    0.5\n    > y = base.dists.beta.cdf( 0.5, 2.0, 4.0 )\n    ~0.813\n    > y = base.dists.beta.cdf( 0.2, 2.0, 2.0 )\n    ~0.104\n    > y = base.dists.beta.cdf( 0.8, 4.0, 4.0 )\n    ~0.967\n    > y = base.dists.beta.cdf( -0.5, 4.0, 2.0 )\n    0.0\n    > y = base.dists.beta.cdf( 1.5, 4.0, 2.0 )\n    1.0\n\n    > y = base.dists.beta.cdf( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.beta.cdf( 2.0, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.beta.cdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.beta.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.beta.cdf( 0.0, 1.0, NaN )\n    NaN\n\n\nbase.dists.beta.cdf.factory( α, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a beta distribution with first shape parameter `α` and second shape\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.beta.cdf.factory( 0.5, 0.5 );\n    > var y = mycdf( 0.8 )\n    ~0.705\n    > y = mycdf( 0.3 )\n    ~0.369\n\n","base.dists.beta.cdf.factory":"\nbase.dists.beta.cdf.factory( α, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a beta distribution with first shape parameter `α` and second shape\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.beta.cdf.factory( 0.5, 0.5 );\n    > var y = mycdf( 0.8 )\n    ~0.705\n    > y = mycdf( 0.3 )\n    ~0.369","base.dists.beta.entropy":"\nbase.dists.beta.entropy( α, β )\n    Returns the differential entropy of a beta distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Differential entropy.\n\n    Examples\n    --------\n    > var v = base.dists.beta.entropy( 1.0, 1.0 )\n    0.0\n    > v = base.dists.beta.entropy( 4.0, 12.0 )\n    ~-0.869\n    > v = base.dists.beta.entropy( 8.0, 2.0 )\n    ~-0.795\n\n    > v = base.dists.beta.entropy( 1.0, -0.1 )\n    NaN\n    > v = base.dists.beta.entropy( -0.1, 1.0 )\n    NaN\n\n    > v = base.dists.beta.entropy( 2.0, NaN )\n    NaN\n    > v = base.dists.beta.entropy( NaN, 2.0 )\n    NaN\n\n","base.dists.beta.kurtosis":"\nbase.dists.beta.kurtosis( α, β )\n    Returns the excess kurtosis of a beta distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.beta.kurtosis( 1.0, 1.0 )\n    -1.2\n    > v = base.dists.beta.kurtosis( 4.0, 12.0 )\n    ~0.082\n    > v = base.dists.beta.kurtosis( 8.0, 2.0 )\n    ~0.490\n\n    > v = base.dists.beta.kurtosis( 1.0, -0.1 )\n    NaN\n    > v = base.dists.beta.kurtosis( -0.1, 1.0 )\n    NaN\n\n    > v = base.dists.beta.kurtosis( 2.0, NaN )\n    NaN\n    > v = base.dists.beta.kurtosis( NaN, 2.0 )\n    NaN\n\n","base.dists.beta.logcdf":"\nbase.dists.beta.logcdf( x, α, β )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a beta distribution with first shape parameter `α` and second\n    shape parameter `β` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.beta.logcdf( 0.5, 1.0, 1.0 )\n    ~-0.693\n    > y = base.dists.beta.logcdf( 0.5, 2.0, 4.0 )\n    ~-0.208\n    > y = base.dists.beta.logcdf( 0.2, 2.0, 2.0 )\n    ~-2.263\n    > y = base.dists.beta.logcdf( 0.8, 4.0, 4.0 )\n    ~-0.034\n    > y = base.dists.beta.logcdf( -0.5, 4.0, 2.0 )\n    -Infinity\n    > y = base.dists.beta.logcdf( 1.5, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.beta.logcdf( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.beta.logcdf( 2.0, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.beta.logcdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.beta.logcdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.beta.logcdf( 0.0, 1.0, NaN )\n    NaN\n\n\nbase.dists.beta.logcdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a beta distribution with first shape\n    parameter `α` and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.beta.logcdf.factory( 0.5, 0.5 );\n    > var y = mylogcdf( 0.8 )\n    ~-0.35\n    > y = mylogcdf( 0.3 )\n    ~-0.997\n\n","base.dists.beta.logcdf.factory":"\nbase.dists.beta.logcdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a beta distribution with first shape\n    parameter `α` and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.beta.logcdf.factory( 0.5, 0.5 );\n    > var y = mylogcdf( 0.8 )\n    ~-0.35\n    > y = mylogcdf( 0.3 )\n    ~-0.997","base.dists.beta.logpdf":"\nbase.dists.beta.logpdf( x, α, β )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a beta distribution with first shape parameter `α` and second shape\n    parameter `β` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Natural logarithm of the PDF.\n\n    Examples\n    --------\n    > var y = base.dists.beta.logpdf( 0.5, 1.0, 1.0 )\n    0.0\n    > y = base.dists.beta.logpdf( 0.5, 2.0, 4.0 )\n    ~0.223\n    > y = base.dists.beta.logpdf( 0.2, 2.0, 2.0 )\n    ~-0.041\n    > y = base.dists.beta.logpdf( 0.8, 4.0, 4.0 )\n    ~-0.556\n    > y = base.dists.beta.logpdf( -0.5, 4.0, 2.0 )\n    -Infinity\n    > y = base.dists.beta.logpdf( 1.5, 4.0, 2.0 )\n    -Infinity\n\n    > y = base.dists.beta.logpdf( 0.5, -1.0, 0.5 )\n    NaN\n    > y = base.dists.beta.logpdf( 0.5, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.beta.logpdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.beta.logpdf( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.dists.beta.logpdf( 0.5, 1.0, NaN )\n    NaN\n\n\nbase.dists.beta.logpdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a beta distribution with first shape parameter `α`\n    and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    fcn: Function\n        Function to evaluate the natural logarithm of the PDF.\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.beta.logpdf.factory( 0.5, 0.5 );\n    > var y = mylogpdf( 0.8 )\n    ~-0.228\n    > y = mylogpdf( 0.3 )\n    ~-0.364\n\n","base.dists.beta.logpdf.factory":"\nbase.dists.beta.logpdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a beta distribution with first shape parameter `α`\n    and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    fcn: Function\n        Function to evaluate the natural logarithm of the PDF.\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.beta.logpdf.factory( 0.5, 0.5 );\n    > var y = mylogpdf( 0.8 )\n    ~-0.228\n    > y = mylogpdf( 0.3 )\n    ~-0.364","base.dists.beta.mean":"\nbase.dists.beta.mean( α, β )\n    Returns the expected value of a beta distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.beta.mean( 1.0, 1.0 )\n    0.5\n    > v = base.dists.beta.mean( 4.0, 12.0 )\n    0.25\n    > v = base.dists.beta.mean( 8.0, 2.0 )\n    0.8\n\n","base.dists.beta.median":"\nbase.dists.beta.median( α, β )\n    Returns the median of a beta distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.beta.median( 1.0, 1.0 )\n    0.5\n    > v = base.dists.beta.median( 4.0, 12.0 )\n    ~0.239\n    > v = base.dists.beta.median( 8.0, 2.0 )\n    ~0.820\n\n    > v = base.dists.beta.median( 1.0, -0.1 )\n    NaN\n    > v = base.dists.beta.median( -0.1, 1.0 )\n    NaN\n\n    > v = base.dists.beta.median( 2.0, NaN )\n    NaN\n    > v = base.dists.beta.median( NaN, 2.0 )\n    NaN\n\n","base.dists.beta.mgf":"\nbase.dists.beta.mgf( t, α, β )\n    Evaluates the moment-generating function (MGF) for a beta distribution with\n    first shape parameter `α` and second shape parameter `β` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.beta.mgf( 0.5, 1.0, 1.0 )\n    ~1.297\n    > y = base.dists.beta.mgf( 0.5, 2.0, 4.0 )\n    ~1.186\n    > y = base.dists.beta.mgf( 3.0, 2.0, 2.0 )\n    ~5.575\n    > y = base.dists.beta.mgf( -0.8, 4.0, 4.0 )\n    ~0.676\n\n    > y = base.dists.beta.mgf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.beta.mgf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.beta.mgf( 0.0, 1.0, NaN )\n    NaN\n\n    > y = base.dists.beta.mgf( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.beta.mgf( 2.0, 0.0, 0.5 )\n    NaN\n\n    > y = base.dists.beta.mgf( 2.0, 0.5, -1.0 )\n    NaN\n    > y = base.dists.beta.mgf( 2.0, 0.5, 0.0 )\n    NaN\n\n\nbase.dists.beta.mgf.factory( α, β )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    beta distribution with first shape parameter `α` and second shape parameter\n    `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.beta.mgf.factory( 0.5, 0.5 );\n    > var y = myMGF( 0.8 )\n    ~1.552\n    > y = myMGF( 0.3 )\n    ~1.168\n\n","base.dists.beta.mgf.factory":"\nbase.dists.beta.mgf.factory( α, β )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    beta distribution with first shape parameter `α` and second shape parameter\n    `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.beta.mgf.factory( 0.5, 0.5 );\n    > var y = myMGF( 0.8 )\n    ~1.552\n    > y = myMGF( 0.3 )\n    ~1.168","base.dists.beta.mode":"\nbase.dists.beta.mode( α, β )\n    Returns the mode of a beta distribution.\n\n    If `α <= 1` or `β <= 1`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.beta.mode( 4.0, 12.0 )\n    ~0.214\n    > v = base.dists.beta.mode( 8.0, 2.0 )\n    ~0.875\n    > v = base.dists.beta.mode( 1.0, 1.0 )\n    NaN\n\n","base.dists.beta.pdf":"\nbase.dists.beta.pdf( x, α, β )\n    Evaluates the probability density function (PDF) for a beta distribution\n    with first shape parameter `α` and second shape parameter `β` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.beta.pdf( 0.5, 1.0, 1.0 )\n    1.0\n    > y = base.dists.beta.pdf( 0.5, 2.0, 4.0 )\n    1.25\n    > y = base.dists.beta.pdf( 0.2, 2.0, 2.0 )\n    ~0.96\n    > y = base.dists.beta.pdf( 0.8, 4.0, 4.0 )\n    ~0.573\n    > y = base.dists.beta.pdf( -0.5, 4.0, 2.0 )\n    0.0\n    > y = base.dists.beta.pdf( 1.5, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.beta.pdf( 0.5, -1.0, 0.5 )\n    NaN\n    > y = base.dists.beta.pdf( 0.5, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.beta.pdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.beta.pdf( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.dists.beta.pdf( 0.5, 1.0, NaN )\n    NaN\n\n\nbase.dists.beta.pdf.factory( α, β )\n    Returns a function for evaluating the probability density function (PDF) of\n    a beta distribution with first shape parameter `α` and second shape\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var mypdf = base.dists.beta.pdf.factory( 0.5, 0.5 );\n    > var y = mypdf( 0.8 )\n    ~0.796\n    > y = mypdf( 0.3 )\n    ~0.695\n\n","base.dists.beta.pdf.factory":"\nbase.dists.beta.pdf.factory( α, β )\n    Returns a function for evaluating the probability density function (PDF) of\n    a beta distribution with first shape parameter `α` and second shape\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var mypdf = base.dists.beta.pdf.factory( 0.5, 0.5 );\n    > var y = mypdf( 0.8 )\n    ~0.796\n    > y = mypdf( 0.3 )\n    ~0.695","base.dists.beta.quantile":"\nbase.dists.beta.quantile( p, α, β )\n    Evaluates the quantile function for a beta distribution with first shape\n    parameter `α` and second shape parameter `β` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input value (probability).\n\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.beta.quantile( 0.8, 2.0, 1.0 )\n    ~0.894\n    > y = base.dists.beta.quantile( 0.5, 4.0, 2.0 )\n    ~0.686\n    > y = base.dists.beta.quantile( 1.1, 1.0, 1.0 )\n    NaN\n    > y = base.dists.beta.quantile( -0.2, 1.0, 1.0 )\n    NaN\n\n    > y = base.dists.beta.quantile( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.beta.quantile( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.dists.beta.quantile( 0.5, 1.0, NaN )\n    NaN\n\n    > y = base.dists.beta.quantile( 0.5, -1.0, 1.0 )\n    NaN\n    > y = base.dists.beta.quantile( 0.5, 1.0, -1.0 )\n    NaN\n\n\nbase.dists.beta.quantile.factory( α, β )\n    Returns a function for evaluating the quantile function of a beta\n    distribution with first shape parameter `α` and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.beta.quantile.factory( 2.0, 2.0 );\n    > y = myquantile( 0.8 )\n    ~0.713\n    > y = myquantile( 0.4 )\n    ~0.433\n\n","base.dists.beta.quantile.factory":"\nbase.dists.beta.quantile.factory( α, β )\n    Returns a function for evaluating the quantile function of a beta\n    distribution with first shape parameter `α` and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.beta.quantile.factory( 2.0, 2.0 );\n    > y = myquantile( 0.8 )\n    ~0.713\n    > y = myquantile( 0.4 )\n    ~0.433","base.dists.beta.skewness":"\nbase.dists.beta.skewness( α, β )\n    Returns the skewness of a beta distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.beta.skewness( 1.0, 1.0 )\n    0.0\n    > v = base.dists.beta.skewness( 4.0, 12.0 )\n    ~0.529\n    > v = base.dists.beta.skewness( 8.0, 2.0 )\n    ~-0.829\n\n    > v = base.dists.beta.skewness( 1.0, -0.1 )\n    NaN\n    > v = base.dists.beta.skewness( -0.1, 1.0 )\n    NaN\n\n    > v = base.dists.beta.skewness( 2.0, NaN )\n    NaN\n    > v = base.dists.beta.skewness( NaN, 2.0 )\n    NaN\n\n","base.dists.beta.stdev":"\nbase.dists.beta.stdev( α, β )\n    Returns the standard deviation of a beta distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.beta.stdev( 1.0, 1.0 )\n    ~0.289\n    > v = base.dists.beta.stdev( 4.0, 12.0 )\n    ~0.105\n    > v = base.dists.beta.stdev( 8.0, 2.0 )\n    ~0.121\n\n    > v = base.dists.beta.stdev( 1.0, -0.1 )\n    NaN\n    > v = base.dists.beta.stdev( -0.1, 1.0 )\n    NaN\n\n    > v = base.dists.beta.stdev( 2.0, NaN )\n    NaN\n    > v = base.dists.beta.stdev( NaN, 2.0 )\n    NaN\n\n","base.dists.beta.variance":"\nbase.dists.beta.variance( α, β )\n    Returns the variance of a beta distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.beta.variance( 1.0, 1.0 )\n    ~0.083\n    > v = base.dists.beta.variance( 4.0, 12.0 )\n    ~0.011\n    > v = base.dists.beta.variance( 8.0, 2.0 )\n    ~0.015\n\n    > v = base.dists.beta.variance( 1.0, -0.1 )\n    NaN\n    > v = base.dists.beta.variance( -0.1, 1.0 )\n    NaN\n\n    > v = base.dists.beta.variance( 2.0, NaN )\n    NaN\n    > v = base.dists.beta.variance( NaN, 2.0 )\n    NaN\n\n","base.dists.betaprime.BetaPrime":"\nbase.dists.betaprime.BetaPrime( [α, β] )\n    Returns a beta prime distribution object.\n\n    Parameters\n    ----------\n    α: number (optional)\n        First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n    β: number (optional)\n        Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    betaprime: Object\n        Distribution instance.\n\n    betaprime.alpha: number\n        First shape parameter. If set, the value must be greater than `0`.\n\n    betaprime.beta: number\n        Second shape parameter. If set, the value must be greater than `0`.\n\n    betaprime.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    betaprime.mean: number\n        Read-only property which returns the expected value.\n\n    betaprime.mode: number\n        Read-only property which returns the mode.\n\n    betaprime.skewness: number\n        Read-only property which returns the skewness.\n\n    betaprime.stdev: number\n        Read-only property which returns the standard deviation.\n\n    betaprime.variance: number\n        Read-only property which returns the variance.\n\n    betaprime.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    betaprime.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    betaprime.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    betaprime.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    betaprime.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var betaprime = base.dists.betaprime.BetaPrime( 6.0, 5.0 );\n    > betaprime.alpha\n    6.0\n    > betaprime.beta\n    5.0\n    > betaprime.kurtosis\n    44.4\n    > betaprime.mean\n    1.5\n    > betaprime.mode\n    ~0.833\n    > betaprime.skewness\n    ~3.578\n    > betaprime.stdev\n    ~1.118\n    > betaprime.variance\n    1.25\n    > betaprime.cdf( 0.8 )\n    ~0.25\n    > betaprime.logcdf( 0.8 )\n    ~-1.387\n    > betaprime.logpdf( 1.0 )\n    ~-0.486\n    > betaprime.pdf( 1.0 )\n    ~0.615\n    > betaprime.quantile( 0.8 )\n    ~2.06\n\n","base.dists.betaprime.cdf":"\nbase.dists.betaprime.cdf( x, α, β )\n    Evaluates the cumulative distribution function (CDF) for a beta prime\n    distribution with first shape parameter `α` and second shape parameter `β`\n    at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.betaprime.cdf( 0.5, 1.0, 1.0 )\n    ~0.333\n    > y = base.dists.betaprime.cdf( 0.5, 2.0, 4.0 )\n    ~0.539\n    > y = base.dists.betaprime.cdf( 0.2, 2.0, 2.0 )\n    ~0.074\n    > y = base.dists.betaprime.cdf( 0.8, 4.0, 4.0 )\n    ~0.38\n    > y = base.dists.betaprime.cdf( -0.5, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.betaprime.cdf( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.betaprime.cdf( 2.0, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.betaprime.cdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.betaprime.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.betaprime.cdf( 0.0, 1.0, NaN )\n    NaN\n\n\nbase.dists.betaprime.cdf.factory( α, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a beta prime distribution with first shape parameter `α` and second shape\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.betaprime.cdf.factory( 0.5, 0.5 );\n    > var y = mycdf( 0.8 )\n    ~0.465\n    > y = mycdf( 0.3 )\n    ~0.319\n\n","base.dists.betaprime.cdf.factory":"\nbase.dists.betaprime.cdf.factory( α, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a beta prime distribution with first shape parameter `α` and second shape\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.betaprime.cdf.factory( 0.5, 0.5 );\n    > var y = mycdf( 0.8 )\n    ~0.465\n    > y = mycdf( 0.3 )\n    ~0.319","base.dists.betaprime.kurtosis":"\nbase.dists.betaprime.kurtosis( α, β )\n    Returns the excess kurtosis of a beta prime distribution.\n\n    If `α <= 0` or `β <= 4`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.betaprime.kurtosis( 2.0, 6.0 )\n    ~26.143\n    > v = base.dists.betaprime.kurtosis( 4.0, 12.0 )\n    ~5.764\n    > v = base.dists.betaprime.kurtosis( 8.0, 6.0 )\n    ~19.962\n\n    > v = base.dists.betaprime.kurtosis( 1.0, 2.8 )\n    NaN\n    > v = base.dists.betaprime.kurtosis( 1.0, -0.1 )\n    NaN\n    > v = base.dists.betaprime.kurtosis( -0.1, 5.0 )\n    NaN\n\n    > v = base.dists.betaprime.kurtosis( 2.0, NaN )\n    NaN\n    > v = base.dists.betaprime.kurtosis( NaN, 6.0 )\n    NaN\n\n","base.dists.betaprime.logcdf":"\nbase.dists.betaprime.logcdf( x, α, β )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a beta prime distribution with first shape parameter `α` and\n    second shape parameter `β` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.betaprime.logcdf( 0.5, 1.0, 1.0 )\n    ~-1.099\n    > y = base.dists.betaprime.logcdf( 0.5, 2.0, 4.0 )\n    ~-0.618\n    > y = base.dists.betaprime.logcdf( 0.2, 2.0, 2.0 )\n    ~-2.603\n    > y = base.dists.betaprime.logcdf( 0.8, 4.0, 4.0 )\n    ~-0.968\n    > y = base.dists.betaprime.logcdf( -0.5, 4.0, 2.0 )\n    -Infinity\n\n    > y = base.dists.betaprime.logcdf( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.betaprime.logcdf( 2.0, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.betaprime.logcdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.betaprime.logcdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.betaprime.logcdf( 0.0, 1.0, NaN )\n    NaN\n\n\nbase.dists.betaprime.logcdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a beta prime distribution with first shape\n    parameter `α` and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.betaprime.logcdf.factory( 0.5, 0.5 );\n    > var y = mylogcdf( 0.8 )\n    ~-0.767\n    > y = mylogcdf( 0.3 )\n    ~-1.143\n\n","base.dists.betaprime.logcdf.factory":"\nbase.dists.betaprime.logcdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a beta prime distribution with first shape\n    parameter `α` and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.betaprime.logcdf.factory( 0.5, 0.5 );\n    > var y = mylogcdf( 0.8 )\n    ~-0.767\n    > y = mylogcdf( 0.3 )\n    ~-1.143","base.dists.betaprime.logpdf":"\nbase.dists.betaprime.logpdf( x, α, β )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a beta prime distribution with first shape parameter `α` and second\n    shape parameter `β` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Natural logarithm of the PDF.\n\n    Examples\n    --------\n    > var y = base.dists.betaprime.logpdf( 0.5, 1.0, 1.0 )\n    ~-0.811\n    > y = base.dists.betaprime.logpdf( 0.5, 2.0, 4.0 )\n    ~-0.13\n    > y = base.dists.betaprime.logpdf( 0.2, 2.0, 2.0 )\n    ~-0.547\n    > y = base.dists.betaprime.logpdf( 0.8, 4.0, 4.0 )\n    ~-0.43\n    > y = base.dists.betaprime.logpdf( -0.5, 4.0, 2.0 )\n    -Infinity\n\n    > y = base.dists.betaprime.logpdf( 0.5, -1.0, 0.5 )\n    NaN\n    > y = base.dists.betaprime.logpdf( 0.5, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.betaprime.logpdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.betaprime.logpdf( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.dists.betaprime.logpdf( 0.5, 1.0, NaN )\n    NaN\n\n\nbase.dists.betaprime.logpdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a beta prime distribution with first shape\n    parameter `α` and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    fcn: Function\n        Function to evaluate the natural logarithm of the PDF.\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.betaprime.logpdf.factory( 0.5, 0.5 );\n    > var y = mylogpdf( 0.8 )\n    ~-1.62\n    > y = mylogpdf( 0.3 )\n    ~-0.805\n\n","base.dists.betaprime.logpdf.factory":"\nbase.dists.betaprime.logpdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a beta prime distribution with first shape\n    parameter `α` and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    fcn: Function\n        Function to evaluate the natural logarithm of the PDF.\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.betaprime.logpdf.factory( 0.5, 0.5 );\n    > var y = mylogpdf( 0.8 )\n    ~-1.62\n    > y = mylogpdf( 0.3 )\n    ~-0.805","base.dists.betaprime.mean":"\nbase.dists.betaprime.mean( α, β )\n    Returns the expected value of a beta prime distribution.\n\n    If `α <= 0` or `β <= 1`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.betaprime.mean( 1.0, 2.0 )\n    1.0\n    > v = base.dists.betaprime.mean( 4.0, 12.0 )\n    ~0.364\n    > v = base.dists.betaprime.mean( 8.0, 2.0 )\n    8.0\n\n","base.dists.betaprime.mode":"\nbase.dists.betaprime.mode( α, β )\n    Returns the mode of a beta prime distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.betaprime.mode( 1.0, 2.0 )\n    0.0\n    > v = base.dists.betaprime.mode( 4.0, 12.0 )\n    ~0.231\n    > v = base.dists.betaprime.mode( 8.0, 2.0 )\n    ~2.333\n\n","base.dists.betaprime.pdf":"\nbase.dists.betaprime.pdf( x, α, β )\n    Evaluates the probability density function (PDF) for a beta prime\n    distribution  with first shape parameter `α` and second shape parameter `β`\n    at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.betaprime.pdf( 0.5, 1.0, 1.0 )\n    ~0.444\n    > y = base.dists.betaprime.pdf( 0.5, 2.0, 4.0 )\n    ~0.878\n    > y = base.dists.betaprime.pdf( 0.2, 2.0, 2.0 )\n    ~0.579\n    > y = base.dists.betaprime.pdf( 0.8, 4.0, 4.0 )\n    ~0.65\n    > y = base.dists.betaprime.pdf( -0.5, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.betaprime.pdf( 0.5, -1.0, 0.5 )\n    NaN\n    > y = base.dists.betaprime.pdf( 0.5, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.betaprime.pdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.betaprime.pdf( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.dists.betaprime.pdf( 0.5, 1.0, NaN )\n    NaN\n\n\nbase.dists.betaprime.pdf.factory( α, β )\n    Returns a function for evaluating the probability density function (PDF) of\n    a beta prime distribution with first shape parameter `α` and second shape\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var mypdf = base.dists.betaprime.pdf.factory( 0.5, 0.5 );\n    > var y = mypdf( 0.8 )\n    ~0.198\n    > y = mypdf( 0.3 )\n    ~0.447\n\n","base.dists.betaprime.pdf.factory":"\nbase.dists.betaprime.pdf.factory( α, β )\n    Returns a function for evaluating the probability density function (PDF) of\n    a beta prime distribution with first shape parameter `α` and second shape\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var mypdf = base.dists.betaprime.pdf.factory( 0.5, 0.5 );\n    > var y = mypdf( 0.8 )\n    ~0.198\n    > y = mypdf( 0.3 )\n    ~0.447","base.dists.betaprime.quantile":"\nbase.dists.betaprime.quantile( p, α, β )\n    Evaluates the quantile function for a beta prime distribution with first\n    shape parameter `α` and second shape parameter `β` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input value (probability).\n\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.betaprime.quantile( 0.8, 2.0, 1.0 )\n    ~8.472\n    > y = base.dists.betaprime.quantile( 0.5, 4.0, 2.0 )\n    ~2.187\n    > y = base.dists.betaprime.quantile( 1.1, 1.0, 1.0 )\n    NaN\n    > y = base.dists.betaprime.quantile( -0.2, 1.0, 1.0 )\n    NaN\n\n    > y = base.dists.betaprime.quantile( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.betaprime.quantile( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.dists.betaprime.quantile( 0.5, 1.0, NaN )\n    NaN\n\n    > y = base.dists.betaprime.quantile( 0.5, -1.0, 1.0 )\n    NaN\n    > y = base.dists.betaprime.quantile( 0.5, 1.0, -1.0 )\n    NaN\n\n\nbase.dists.betaprime.quantile.factory( α, β )\n    Returns a function for evaluating the quantile function of a beta prime\n    distribution with first shape parameter `α` and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.betaprime.quantile.factory( 2.0, 2.0 );\n    > y = myQuantile( 0.8 )\n    ~2.483\n    > y = myQuantile( 0.4 )\n    ~0.763\n\n","base.dists.betaprime.quantile.factory":"\nbase.dists.betaprime.quantile.factory( α, β )\n    Returns a function for evaluating the quantile function of a beta prime\n    distribution with first shape parameter `α` and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.betaprime.quantile.factory( 2.0, 2.0 );\n    > y = myQuantile( 0.8 )\n    ~2.483\n    > y = myQuantile( 0.4 )\n    ~0.763","base.dists.betaprime.skewness":"\nbase.dists.betaprime.skewness( α, β )\n    Returns the skewness of a beta prime distribution.\n\n    If `α <= 0` or `β <= 3`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.betaprime.skewness( 2.0, 4.0 )\n    ~6.261\n    > v = base.dists.betaprime.skewness( 4.0, 12.0 )\n    ~1.724\n    > v = base.dists.betaprime.skewness( 8.0, 4.0 )\n    ~5.729\n\n    > v = base.dists.betaprime.skewness( 1.0, 2.8 )\n    NaN\n    > v = base.dists.betaprime.skewness( 1.0, -0.1 )\n    NaN\n    > v = base.dists.betaprime.skewness( -0.1, 4.0 )\n    NaN\n\n    > v = base.dists.betaprime.skewness( 2.0, NaN )\n    NaN\n    > v = base.dists.betaprime.skewness( NaN, 4.0 )\n    NaN\n\n","base.dists.betaprime.stdev":"\nbase.dists.betaprime.stdev( α, β )\n    Returns the standard deviation of a beta prime distribution.\n\n    If `α <= 0` or `β <= 2`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.betaprime.stdev( 1.0, 2.5 )\n    ~1.491\n    > v = base.dists.betaprime.stdev( 4.0, 12.0 )\n    ~0.223\n    > v = base.dists.betaprime.stdev( 8.0, 2.5 )\n    ~8.219\n\n    > v = base.dists.betaprime.stdev( 8.0, 1.0 )\n    NaN\n    > v = base.dists.betaprime.stdev( 1.0, -0.1 )\n    NaN\n    > v = base.dists.betaprime.stdev( -0.1, 3.0 )\n    NaN\n\n    > v = base.dists.betaprime.stdev( 2.0, NaN )\n    NaN\n    > v = base.dists.betaprime.stdev( NaN, 3.0 )\n    NaN\n\n","base.dists.betaprime.variance":"\nbase.dists.betaprime.variance( α, β )\n    Returns the variance of a beta prime distribution.\n\n    If `α <= 0` or `β <= 2`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.betaprime.variance( 1.0, 2.5 )\n    ~2.222\n    > v = base.dists.betaprime.variance( 4.0, 12.0 )\n    ~0.05\n    > v = base.dists.betaprime.variance( 8.0, 2.5 )\n    ~67.556\n\n    > v = base.dists.betaprime.variance( 8.0, 1.0 )\n    NaN\n    > v = base.dists.betaprime.variance( 1.0, -0.1 )\n    NaN\n    > v = base.dists.betaprime.variance( -0.1, 3.0 )\n    NaN\n\n    > v = base.dists.betaprime.variance( 2.0, NaN )\n    NaN\n    > v = base.dists.betaprime.variance( NaN, 3.0 )\n    NaN\n\n","base.dists.binomial.Binomial":"\nbase.dists.binomial.Binomial( [n, p] )\n    Returns a binomial distribution object.\n\n    Parameters\n    ----------\n    n: integer (optional)\n        Number of trials. Must be a positive integer. Default: `1`.\n\n    p: number (optional)\n        Success probability. Must be a number between `0` and `1`. Default:\n        `0.5`.\n\n    Returns\n    -------\n    binomial: Object\n        Distribution instance.\n\n    binomial.n: number\n        Number of trials. If set, the value must be a positive integer.\n\n    binomial.p: number\n        Success probability. If set, the value must be a number between `0` and\n        `1`.\n\n    binomial.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    binomial.mean: number\n        Read-only property which returns the expected value.\n\n    binomial.median: number\n        Read-only property which returns the median.\n\n    binomial.mode: number\n        Read-only property which returns the mode.\n\n    binomial.skewness: number\n        Read-only property which returns the skewness.\n\n    binomial.stdev: number\n        Read-only property which returns the standard deviation.\n\n    binomial.variance: number\n        Read-only property which returns the variance.\n\n    binomial.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    binomial.logpmf: Function\n        Evaluates the natural logarithm of the probability mass function (PMF).\n\n    binomial.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    binomial.pmf: Function\n        Evaluates the probability mass function (PMF).\n\n    binomial.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var binomial = base.dists.binomial.Binomial( 8, 0.5 );\n    > binomial.n\n    8.0\n    > binomial.p\n    0.5\n    > binomial.kurtosis\n    -0.25\n    > binomial.mean\n    4.0\n    > binomial.median\n    4.0\n    > binomial.mode\n    4.0\n    > binomial.skewness\n    0.0\n    > binomial.stdev\n    ~1.414\n    > binomial.variance\n    2.0\n    > binomial.cdf( 2.9 )\n    ~0.145\n    > binomial.logpmf( 3.0 )\n    ~-1.52\n    > binomial.mgf( 0.2 )\n    ~2.316\n    > binomial.pmf( 3.0 )\n    ~0.219\n    > binomial.quantile( 0.8 )\n    5.0\n\n","base.dists.binomial.cdf":"\nbase.dists.binomial.cdf( x, n, p )\n    Evaluates the cumulative distribution function (CDF) for a binomial\n    distribution with number of trials `n` and success probability `p` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.binomial.cdf( 3.0, 20, 0.2 )\n    ~0.411\n    > y = base.dists.binomial.cdf( 21.0, 20, 0.2 )\n    1.0\n    > y = base.dists.binomial.cdf( 5.0, 10, 0.4 )\n    ~0.834\n    > y = base.dists.binomial.cdf( 0.0, 10, 0.4 )\n    ~0.006\n    > y = base.dists.binomial.cdf( NaN, 20, 0.5 )\n    NaN\n    > y = base.dists.binomial.cdf( 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.binomial.cdf( 0.0, 20, NaN )\n    NaN\n    > y = base.dists.binomial.cdf( 2.0, 1.5, 0.5 )\n    NaN\n    > y = base.dists.binomial.cdf( 2.0, -2.0, 0.5 )\n    NaN\n    > y = base.dists.binomial.cdf( 2.0, 20, -1.0 )\n    NaN\n    > y = base.dists.binomial.cdf( 2.0, 20, 1.5 )\n    NaN\n\n\nbase.dists.binomial.cdf.factory( n, p )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a binomial distribution with number of trials `n` and success probability\n    `p`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.binomial.cdf.factory( 10, 0.5 );\n    > var y = mycdf( 3.0 )\n    ~0.172\n    > y = mycdf( 1.0 )\n    ~0.011\n\n","base.dists.binomial.cdf.factory":"\nbase.dists.binomial.cdf.factory( n, p )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a binomial distribution with number of trials `n` and success probability\n    `p`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.binomial.cdf.factory( 10, 0.5 );\n    > var y = mycdf( 3.0 )\n    ~0.172\n    > y = mycdf( 1.0 )\n    ~0.011","base.dists.binomial.entropy":"\nbase.dists.binomial.entropy( n, p )\n    Returns the entropy of a binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.binomial.entropy( 100, 0.1 )\n    ~2.511\n    > v = base.dists.binomial.entropy( 20, 0.5 )\n    ~2.223\n    > v = base.dists.binomial.entropy( 10.3, 0.5 )\n    NaN\n    > v = base.dists.binomial.entropy( 20, 1.1 )\n    NaN\n    > v = base.dists.binomial.entropy( 20, NaN )\n    NaN\n\n","base.dists.binomial.kurtosis":"\nbase.dists.binomial.kurtosis( n, p )\n    Returns the excess kurtosis of a binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.binomial.kurtosis( 100, 0.1 )\n    ~0.051\n    > v = base.dists.binomial.kurtosis( 20, 0.5 )\n    ~-0.1\n    > v = base.dists.binomial.kurtosis( 10.3, 0.5 )\n    NaN\n    > v = base.dists.binomial.kurtosis( 20, 1.1 )\n    NaN\n    > v = base.dists.binomial.kurtosis( 20, NaN )\n    NaN\n\n","base.dists.binomial.logpmf":"\nbase.dists.binomial.logpmf( x, n, p )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    binomial distribution with number of trials `n` and success probability `p`\n    at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPMF.\n\n    Examples\n    --------\n    > var y = base.dists.binomial.logpmf( 3.0, 20, 0.2 )\n    ~-1.583\n    > y = base.dists.binomial.logpmf( 21.0, 20, 0.2 )\n    -Infinity\n    > y = base.dists.binomial.logpmf( 5.0, 10, 0.4 )\n    ~-1.606\n    > y = base.dists.binomial.logpmf( 0.0, 10, 0.4 )\n    ~-5.108\n    > y = base.dists.binomial.logpmf( NaN, 20, 0.5 )\n    NaN\n    > y = base.dists.binomial.logpmf( 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.binomial.logpmf( 0.0, 20, NaN )\n    NaN\n    > y = base.dists.binomial.logpmf( 2.0, 1.5, 0.5 )\n    NaN\n    > y = base.dists.binomial.logpmf( 2.0, -2.0, 0.5 )\n    NaN\n    > y = base.dists.binomial.logpmf( 2.0, 20, -1.0 )\n    NaN\n    > y = base.dists.binomial.logpmf( 2.0, 20, 1.5 )\n    NaN\n\n\nbase.dists.binomial.logpmf.factory( n, p )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a binomial distribution with number of trials `n` and\n    success probability `p`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogpmf = base.dists.binomial.logpmf.factory( 10, 0.5 );\n    > var y = mylogpmf( 3.0 )\n    ~-2.144\n    > y = mylogpmf( 5.0 )\n    ~-1.402\n\n","base.dists.binomial.logpmf.factory":"\nbase.dists.binomial.logpmf.factory( n, p )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a binomial distribution with number of trials `n` and\n    success probability `p`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogpmf = base.dists.binomial.logpmf.factory( 10, 0.5 );\n    > var y = mylogpmf( 3.0 )\n    ~-2.144\n    > y = mylogpmf( 5.0 )\n    ~-1.402","base.dists.binomial.mean":"\nbase.dists.binomial.mean( n, p )\n    Returns the expected value of a binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.binomial.mean( 100, 0.1 )\n    10.0\n    > v = base.dists.binomial.mean( 20, 0.5 )\n    10.0\n    > v = base.dists.binomial.mean( 10.3, 0.5 )\n    NaN\n    > v = base.dists.binomial.mean( 20, 1.1 )\n    NaN\n    > v = base.dists.binomial.mean( 20, NaN )\n    NaN\n\n","base.dists.binomial.median":"\nbase.dists.binomial.median( n, p )\n    Returns the median of a binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.binomial.median( 100, 0.1 )\n    10\n    > v = base.dists.binomial.median( 20, 0.5 )\n    10\n    > v = base.dists.binomial.median( 10.3, 0.5 )\n    NaN\n    > v = base.dists.binomial.median( 20, 1.1 )\n    NaN\n    > v = base.dists.binomial.median( 20, NaN )\n    NaN\n\n","base.dists.binomial.mgf":"\nbase.dists.binomial.mgf( t, n, p )\n    Evaluates the moment-generating function (MGF) for a binomial distribution\n    with number of trials `n` and success probability `p` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.binomial.mgf( 0.5, 20, 0.2 )\n    ~11.471\n    > y = base.dists.binomial.mgf( 5.0, 20, 0.2 )\n    ~4.798e+29\n    > y = base.dists.binomial.mgf( 0.9, 10, 0.4 )\n    ~99.338\n    > y = base.dists.binomial.mgf( 0.0, 10, 0.4 )\n    1.0\n\n    > y = base.dists.binomial.mgf( NaN, 20, 0.5 )\n    NaN\n    > y = base.dists.binomial.mgf( 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.binomial.mgf( 0.0, 20, NaN )\n    NaN\n\n    > y = base.dists.binomial.mgf( 2.0, 1.5, 0.5 )\n    NaN\n    > y = base.dists.binomial.mgf( 2.0, -2.0, 0.5 )\n    NaN\n    > y = base.dists.binomial.mgf( 2.0, 20, -1.0 )\n    NaN\n    > y = base.dists.binomial.mgf( 2.0, 20, 1.5 )\n    NaN\n\n\nbase.dists.binomial.mgf.factory( n, p )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    binomial distribution with number of trials `n` and success probability `p`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.binomial.mgf.factory( 10, 0.5 );\n    > var y = myMGF( 0.3 )\n    ~5.013\n\n","base.dists.binomial.mgf.factory":"\nbase.dists.binomial.mgf.factory( n, p )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    binomial distribution with number of trials `n` and success probability `p`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.binomial.mgf.factory( 10, 0.5 );\n    > var y = myMGF( 0.3 )\n    ~5.013","base.dists.binomial.mode":"\nbase.dists.binomial.mode( n, p )\n    Returns the mode of a binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.binomial.mode( 100, 0.1 )\n    10\n    > v = base.dists.binomial.mode( 20, 0.5 )\n    10\n    > v = base.dists.binomial.mode( 10.3, 0.5 )\n    NaN\n    > v = base.dists.binomial.mode( 20, 1.1 )\n    NaN\n    > v = base.dists.binomial.mode( 20, NaN )\n    NaN\n\n","base.dists.binomial.pmf":"\nbase.dists.binomial.pmf( x, n, p )\n    Evaluates the probability mass function (PMF) for a binomial distribution\n    with number of trials `n` and success probability `p` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated PMF.\n\n    Examples\n    --------\n    > var y = base.dists.binomial.pmf( 3.0, 20, 0.2 )\n    ~0.205\n    > y = base.dists.binomial.pmf( 21.0, 20, 0.2 )\n    0.0\n    > y = base.dists.binomial.pmf( 5.0, 10, 0.4 )\n    ~0.201\n    > y = base.dists.binomial.pmf( 0.0, 10, 0.4 )\n    ~0.006\n    > y = base.dists.binomial.pmf( NaN, 20, 0.5 )\n    NaN\n    > y = base.dists.binomial.pmf( 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.binomial.pmf( 0.0, 20, NaN )\n    NaN\n    > y = base.dists.binomial.pmf( 2.0, 1.5, 0.5 )\n    NaN\n    > y = base.dists.binomial.pmf( 2.0, -2.0, 0.5 )\n    NaN\n    > y = base.dists.binomial.pmf( 2.0, 20, -1.0 )\n    NaN\n    > y = base.dists.binomial.pmf( 2.0, 20, 1.5 )\n    NaN\n\n\nbase.dists.binomial.pmf.factory( n, p )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    binomial distribution with number of trials `n` and success probability `p`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var mypmf = base.dists.binomial.pmf.factory( 10, 0.5 );\n    > var y = mypmf( 3.0 )\n    ~0.117\n    > y = mypmf( 5.0 )\n    ~0.246\n\n","base.dists.binomial.pmf.factory":"\nbase.dists.binomial.pmf.factory( n, p )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    binomial distribution with number of trials `n` and success probability `p`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var mypmf = base.dists.binomial.pmf.factory( 10, 0.5 );\n    > var y = mypmf( 3.0 )\n    ~0.117\n    > y = mypmf( 5.0 )\n    ~0.246","base.dists.binomial.quantile":"\nbase.dists.binomial.quantile( r, n, p )\n    Evaluates the quantile function for a binomial distribution with number of\n    trials `n` and success probability `p` at a probability `r`.\n\n    If `r < 0` or `r > 1`, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    r: number\n        Input probability.\n\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.binomial.quantile( 0.4, 20, 0.2 )\n    3\n    > y = base.dists.binomial.quantile( 0.8, 20, 0.2 )\n    5\n    > y = base.dists.binomial.quantile( 0.5, 10, 0.4 )\n    4\n    > y = base.dists.binomial.quantile( 0.0, 10, 0.4 )\n    0\n    > y = base.dists.binomial.quantile( 1.0, 10, 0.4 )\n    10\n\n    > y = base.dists.binomial.quantile( NaN, 20, 0.5 )\n    NaN\n    > y = base.dists.binomial.quantile( 0.2, NaN, 0.5 )\n    NaN\n    > y = base.dists.binomial.quantile( 0.2, 20, NaN )\n    NaN\n\n    > y = base.dists.binomial.quantile( 0.5, 1.5, 0.5 )\n    NaN\n    > y = base.dists.binomial.quantile( 0.5, -2.0, 0.5 )\n    NaN\n\n    > y = base.dists.binomial.quantile( 0.5, 20, -1.0 )\n    NaN\n    > y = base.dists.binomial.quantile( 0.5, 20, 1.5 )\n    NaN\n\n\nbase.dists.binomial.quantile.factory( n, p )\n    Returns a function for evaluating the quantile function of a binomial\n    distribution with number of trials `n` and success probability `p`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.binomial.quantile.factory( 10, 0.5 );\n    > var y = myquantile( 0.1 )\n    3\n    > y = myquantile( 0.9 )\n    7\n\n","base.dists.binomial.quantile.factory":"\nbase.dists.binomial.quantile.factory( n, p )\n    Returns a function for evaluating the quantile function of a binomial\n    distribution with number of trials `n` and success probability `p`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.binomial.quantile.factory( 10, 0.5 );\n    > var y = myquantile( 0.1 )\n    3\n    > y = myquantile( 0.9 )\n    7","base.dists.binomial.skewness":"\nbase.dists.binomial.skewness( n, p )\n    Returns the skewness of a binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.binomial.skewness( 100, 0.1 )\n    ~0.267\n    > v = base.dists.binomial.skewness( 20, 0.5 )\n    0.0\n    > v = base.dists.binomial.skewness( 10.3, 0.5 )\n    NaN\n    > v = base.dists.binomial.skewness( 20, 1.1 )\n    NaN\n    > v = base.dists.binomial.skewness( 20, NaN )\n    NaN\n\n","base.dists.binomial.stdev":"\nbase.dists.binomial.stdev( n, p )\n    Returns the standard deviation of a binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.binomial.stdev( 100, 0.1 )\n    3.0\n    > v = base.dists.binomial.stdev( 20, 0.5 )\n    ~2.236\n    > v = base.dists.binomial.stdev( 10.3, 0.5 )\n    NaN\n    > v = base.dists.binomial.stdev( 20, 1.1 )\n    NaN\n    > v = base.dists.binomial.stdev( 20, NaN )\n    NaN\n\n","base.dists.binomial.variance":"\nbase.dists.binomial.variance( n, p )\n    Returns the variance of a binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.binomial.variance( 100, 0.1 )\n    9\n    > v = base.dists.binomial.variance( 20, 0.5 )\n    5\n    > v = base.dists.binomial.variance( 10.3, 0.5 )\n    NaN\n    > v = base.dists.binomial.variance( 20, 1.1 )\n    NaN\n    > v = base.dists.binomial.variance( 20, NaN )\n    NaN\n\n","base.dists.cauchy.Cauchy":"\nbase.dists.cauchy.Cauchy( [x0, Ɣ] )\n    Returns a Cauchy distribution object.\n\n    Parameters\n    ----------\n    x0: number (optional)\n        Location parameter. Default: `0.0`.\n\n    Ɣ: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    cauchy: Object\n        Distribution instance.\n\n    cauchy.x0: number\n        Location parameter.\n\n    cauchy.gamma: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    cauchy.entropy: number\n        Read-only property which returns the differential entropy.\n\n    cauchy.median: number\n        Read-only property which returns the median.\n\n    cauchy.mode: number\n        Read-only property which returns the mode.\n\n    cauchy.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    cauchy.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    cauchy.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    cauchy.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    cauchy.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var cauchy = base.dists.cauchy.Cauchy( 0.0, 1.0 );\n    > cauchy.x0\n    0.0\n    > cauchy.gamma\n    1.0\n    > cauchy.entropy\n    ~2.531\n    > cauchy.median\n    0.0\n    > cauchy.mode\n    0.0\n    > cauchy.cdf( 0.8 )\n    ~0.715\n    > cauchy.logcdf( 1.0 )\n    ~-0.288\n    > cauchy.logpdf( 1.0 )\n    ~-1.838\n    > cauchy.pdf( 1.0 )\n    ~0.159\n    > cauchy.quantile( 0.8 )\n    ~1.376\n\n","base.dists.cauchy.cdf":"\nbase.dists.cauchy.cdf( x, x0, Ɣ )\n    Evaluates the cumulative distribution function (CDF) for a Cauchy\n    distribution with location parameter `x0` and scale parameter `Ɣ` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `Ɣ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.cauchy.cdf( 4.0, 0.0, 2.0 )\n    ~0.852\n    > y = base.dists.cauchy.cdf( 1.0, 0.0, 2.0 )\n    ~0.648\n    > y = base.dists.cauchy.cdf( 1.0, 3.0, 2.0 )\n    0.25\n    > y = base.dists.cauchy.cdf( NaN, 0.0, 2.0 )\n    NaN\n    > y = base.dists.cauchy.cdf( 1.0, 2.0, NaN )\n    NaN\n    > y = base.dists.cauchy.cdf( 1.0, NaN, 3.0 )\n    NaN\n\n\nbase.dists.cauchy.cdf.factory( x0, Ɣ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Cauchy distribution with location parameter `x0` and scale parameter\n    `Ɣ`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.cauchy.cdf.factory( 1.5, 3.0 );\n    > var y = myCDF( 1.0 )\n    ~0.447\n\n","base.dists.cauchy.cdf.factory":"\nbase.dists.cauchy.cdf.factory( x0, Ɣ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Cauchy distribution with location parameter `x0` and scale parameter\n    `Ɣ`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.cauchy.cdf.factory( 1.5, 3.0 );\n    > var y = myCDF( 1.0 )\n    ~0.447","base.dists.cauchy.entropy":"\nbase.dists.cauchy.entropy( x0, Ɣ )\n    Returns the differential entropy of a Cauchy distribution (in nats).\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `Ɣ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.cauchy.entropy( 10.0, 7.0 )\n    ~4.477\n    > v = base.dists.cauchy.entropy( 22.0, 0.5 )\n    ~1.838\n    > v = base.dists.cauchy.entropy( 10.3, -0.5 )\n    NaN\n\n","base.dists.cauchy.logcdf":"\nbase.dists.cauchy.logcdf( x, x0, Ɣ )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (logCDF) for a Cauchy distribution with location parameter `x0` and scale\n    parameter `Ɣ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `Ɣ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Natural logarithm of the CDF.\n\n    Examples\n    --------\n    > var y = base.dists.cauchy.logcdf( 4.0, 0.0, 2.0 )\n    ~-0.16\n    > y = base.dists.cauchy.logcdf( 1.0, 0.0, 2.0 )\n    ~-0.435\n    > y = base.dists.cauchy.logcdf( 1.0, 3.0, 2.0 )\n    ~-1.386\n    > y = base.dists.cauchy.logcdf( NaN, 0.0, 2.0 )\n    NaN\n    > y = base.dists.cauchy.logcdf( 1.0, 2.0, NaN )\n    NaN\n    > y = base.dists.cauchy.logcdf( 1.0, NaN, 3.0 )\n    NaN\n\n\nbase.dists.cauchy.logcdf.factory( x0, Ɣ )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (logCDF) of a Cauchy distribution with location\n    parameter `x0` and scale parameter `Ɣ`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Function to evaluate the natural logarithm of CDF.\n\n    Examples\n    --------\n    > var mylogCDF = base.dists.cauchy.logcdf.factory( 1.5, 3.0 );\n    > var y = mylogCDF( 1.0 )\n    ~-0.804\n\n","base.dists.cauchy.logcdf.factory":"\nbase.dists.cauchy.logcdf.factory( x0, Ɣ )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (logCDF) of a Cauchy distribution with location\n    parameter `x0` and scale parameter `Ɣ`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Function to evaluate the natural logarithm of CDF.\n\n    Examples\n    --------\n    > var mylogCDF = base.dists.cauchy.logcdf.factory( 1.5, 3.0 );\n    > var y = mylogCDF( 1.0 )\n    ~-0.804","base.dists.cauchy.logpdf":"\nbase.dists.cauchy.logpdf( x, x0, Ɣ )\n    Evaluates the natural logarithm of the probability density function (logPDF)\n    for a Cauchy distribution with location parameter `x0` and scale parameter\n    `Ɣ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `Ɣ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Natural logarithm of PDF.\n\n    Examples\n    --------\n    > var y = base.dists.cauchy.logpdf( 2.0, 1.0, 1.0 )\n    ~-1.838\n    > y = base.dists.cauchy.logpdf( 4.0, 3.0, 0.1 )\n    ~-3.457\n    > y = base.dists.cauchy.logpdf( 4.0, 3.0, 3.0 )\n    ~-2.349\n    > y = base.dists.cauchy.logpdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.cauchy.logpdf( 2.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.cauchy.logpdf( 2.0, 1.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.cauchy.logpdf( 2.0, 1.0, -2.0 )\n    NaN\n\n\nbase.dists.cauchy.logpdf.factory( x0, Ɣ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (logPDF) of a Cauchy distribution with location parameter\n    `x0` and scale parameter `Ɣ`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Function to evaluate the natural logarithm of the PDF.\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.cauchy.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogPDF( 10.0 )\n    ~-1.838\n\n","base.dists.cauchy.logpdf.factory":"\nbase.dists.cauchy.logpdf.factory( x0, Ɣ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (logPDF) of a Cauchy distribution with location parameter\n    `x0` and scale parameter `Ɣ`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Function to evaluate the natural logarithm of the PDF.\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.cauchy.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogPDF( 10.0 )\n    ~-1.838","base.dists.cauchy.median":"\nbase.dists.cauchy.median( x0, Ɣ )\n    Returns the median of a Cauchy distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `Ɣ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.cauchy.median( 10.0, 5.0 )\n    10.0\n    > v = base.dists.cauchy.median( 7.0, 0.5 )\n    7.0\n    > v = base.dists.cauchy.median( 10.3, -0.5 )\n    NaN\n\n","base.dists.cauchy.mode":"\nbase.dists.cauchy.mode( x0, Ɣ )\n    Returns the mode of a Cauchy distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `Ɣ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.cauchy.mode( 10.0, 5.0 )\n    10.0\n    > v = base.dists.cauchy.mode( 7.0, 0.5 )\n    7.0\n    > v = base.dists.cauchy.mode( 10.3, -0.5 )\n    NaN\n\n","base.dists.cauchy.pdf":"\nbase.dists.cauchy.pdf( x, x0, Ɣ )\n    Evaluates the probability density function (PDF) for a Cauchy distribution\n    with location parameter `x0` and scale parameter `Ɣ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `Ɣ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.cauchy.pdf( 2.0, 1.0, 1.0 )\n    ~0.159\n    > y = base.dists.cauchy.pdf( 4.0, 3.0, 0.1 )\n    ~0.0315\n    > y = base.dists.cauchy.pdf( 4.0, 3.0, 3.0 )\n    ~0.095\n    > y = base.dists.cauchy.pdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.cauchy.pdf( 2.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.cauchy.pdf( 2.0, 1.0, NaN )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.cauchy.pdf( 2.0, 1.0, -2.0 )\n    NaN\n\n\nbase.dists.cauchy.pdf.factory( x0, Ɣ )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Cauchy distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.cauchy.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    ~0.159\n\n","base.dists.cauchy.pdf.factory":"\nbase.dists.cauchy.pdf.factory( x0, Ɣ )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Cauchy distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.cauchy.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    ~0.159","base.dists.cauchy.quantile":"\nbase.dists.cauchy.quantile( p, x0, Ɣ )\n    Evaluates the quantile function for a Cauchy distribution with location\n    parameter `x0`  and scale parameter `Ɣ` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `Ɣ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.cauchy.quantile( 0.3, 2.0, 2.0 )\n    ~0.547\n    > y = base.dists.cauchy.quantile( 0.8, 10, 2.0 )\n    ~12.753\n    > y = base.dists.cauchy.quantile( 0.1, 10.0, 2.0 )\n    ~3.845\n\n    > y = base.dists.cauchy.quantile( 1.1, 0.0, 1.0 )\n    NaN\n    > y = base.dists.cauchy.quantile( -0.2, 0.0, 1.0 )\n    NaN\n\n    > y = base.dists.cauchy.quantile( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.cauchy.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.cauchy.quantile( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.cauchy.quantile( 0.5, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.cauchy.quantile.factory( x0, Ɣ )\n    Returns a function for evaluating the quantile function of a Cauchy\n    distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.cauchy.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    10.0\n\n","base.dists.cauchy.quantile.factory":"\nbase.dists.cauchy.quantile.factory( x0, Ɣ )\n    Returns a function for evaluating the quantile function of a Cauchy\n    distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.cauchy.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    10.0","base.dists.chi.cdf":"\nbase.dists.chi.cdf( x, k )\n    Evaluates the cumulative distribution function (CDF) for a chi distribution\n    with degrees of freedom `k` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.chi.cdf( 2.0, 3.0 )\n    ~0.739\n    > y = base.dists.chi.cdf( 1.0, 0.5 )\n    ~0.846\n    > y = base.dists.chi.cdf( -1.0, 4.0 )\n    0.0\n    > y = base.dists.chi.cdf( NaN, 1.0 )\n    NaN\n    > y = base.dists.chi.cdf( 0.0, NaN )\n    NaN\n\n    // Negative degrees of freedom:\n    > y = base.dists.chi.cdf( 2.0, -1.0 )\n    NaN\n\n    // Degenerate distribution when `k = 0`:\n    > y = base.dists.chi.cdf( 2.0, 0.0 )\n    1.0\n    > y = base.dists.chi.cdf( -2.0, 0.0 )\n    0.0\n    > y = base.dists.chi.cdf( 0.0, 0.0 )\n    0.0\n\nbase.dists.chi.cdf.factory( k )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a chi distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.chi.cdf.factory( 1.0 );\n    > var y = mycdf( 2.0 )\n    ~0.954\n    > y = mycdf( 1.2 )\n    ~0.77\n\n","base.dists.chi.cdf.factory":"\nbase.dists.chi.cdf.factory( k )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a chi distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.chi.cdf.factory( 1.0 );\n    > var y = mycdf( 2.0 )\n    ~0.954\n    > y = mycdf( 1.2 )\n    ~0.77","base.dists.chi.Chi":"\nbase.dists.chi.Chi( [k] )\n    Returns a chi distribution object.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    chi: Object\n        Distribution instance.\n\n    chi.k: number\n        Degrees of freedom. If set, the value must be greater than `0`.\n\n    chi.entropy: number\n        Read-only property which returns the differential entropy.\n\n    chi.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    chi.mean: number\n        Read-only property which returns the expected value.\n\n    chi.mode: number\n        Read-only property which returns the mode.\n\n    chi.skewness: number\n        Read-only property which returns the skewness.\n\n    chi.stdev: number\n        Read-only property which returns the standard deviation.\n\n    chi.variance: number\n        Read-only property which returns the variance.\n\n    chi.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    chi.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    chi.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    chi.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var chi = base.dists.chi.Chi( 6.0 );\n    > chi.k\n    6.0\n    > chi.entropy\n    ~1.04\n    > chi.kurtosis\n    ~0.025\n    > chi.mean\n    ~2.35\n    > chi.mode\n    ~2.236\n    > chi.skewness\n    ~0.318\n    > chi.stdev\n    ~0.691\n    > chi.variance\n    ~0.478\n    > chi.cdf( 1.0 )\n    ~0.014\n    > chi.logpdf( 1.5 )\n    ~-1.177\n    > chi.pdf( 1.5 )\n    ~0.308\n    > chi.quantile( 0.5 )\n    ~2.313\n\n","base.dists.chi.entropy":"\nbase.dists.chi.entropy( k )\n    Returns the differential entropy of a chi distribution (in nats).\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.chi.entropy( 11.0 )\n    ~1.056\n    > v = base.dists.chi.entropy( 1.5 )\n    ~0.878\n\n","base.dists.chi.kurtosis":"\nbase.dists.chi.kurtosis( k )\n    Returns the excess kurtosis of a chi distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.chi.kurtosis( 9.0 )\n    ~0.011\n    > v = base.dists.chi.kurtosis( 1.5 )\n    ~0.424\n\n","base.dists.chi.logpdf":"\nbase.dists.chi.logpdf( x, k )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a chi distribution with degrees of freedom `k` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.chi.logpdf( 0.3, 4.0 )\n    ~-4.35\n    > y = base.dists.chi.logpdf( 0.7, 0.7 )\n    ~-0.622\n    > y = base.dists.chi.logpdf( -1.0, 0.5 )\n    -Infinity\n    > y = base.dists.chi.logpdf( 0.0, NaN )\n    NaN\n    > y = base.dists.chi.logpdf( NaN, 2.0 )\n    NaN\n\n    // Negative degrees of freedom:\n    > y = base.dists.chi.logpdf( 2.0, -1.0 )\n    NaN\n\n    // Degenerate distribution when `k = 0`:\n    > y = base.dists.chi.logpdf( 2.0, 0.0, 2.0 )\n    -Infinity\n    > y = base.dists.chi.logpdf( 0.0, 0.0, 2.0 )\n    Infinity\n\n\nbase.dists.chi.logpdf.factory( k )\n    Returns a function for evaluating the natural logarithm of the  probability\n    density function (PDF) of a chi distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.chi.logpdf.factory( 6.0 );\n    > var y = mylogPDF( 3.0 )\n    ~-1.086\n\n","base.dists.chi.logpdf.factory":"\nbase.dists.chi.logpdf.factory( k )\n    Returns a function for evaluating the natural logarithm of the  probability\n    density function (PDF) of a chi distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.chi.logpdf.factory( 6.0 );\n    > var y = mylogPDF( 3.0 )\n    ~-1.086","base.dists.chi.mean":"\nbase.dists.chi.mean( k )\n    Returns the expected value of a chi distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.chi.mean( 11.0 )\n    ~3.242\n    > v = base.dists.chi.mean( 4.5 )\n    ~2.008\n\n","base.dists.chi.mode":"\nbase.dists.chi.mode( k )\n    Returns the mode of a chi distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.chi.mode( 11.0 )\n    ~3.162\n    > v = base.dists.chi.mode( 1.5 )\n    ~0.707\n\n","base.dists.chi.pdf":"\nbase.dists.chi.pdf( x, k )\n    Evaluates the probability density function (PDF) for a chi distribution with\n    degrees of freedom `k` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.chi.pdf( 0.3, 4.0 )\n    ~0.013\n    > y = base.dists.chi.pdf( 0.7, 0.7 )\n    ~0.537\n    > y = base.dists.chi.pdf( -1.0, 0.5 )\n    0.0\n    > y = base.dists.chi.pdf( 0.0, NaN )\n    NaN\n    > y = base.dists.chi.pdf( NaN, 2.0 )\n    NaN\n\n    // Negative degrees of freedom:\n    > y = base.dists.chi.pdf( 2.0, -1.0 )\n    NaN\n\n    // Degenerate distribution when `k = 0`:\n    > y = base.dists.chi.pdf( 2.0, 0.0, 2.0 )\n    0.0\n    > y = base.dists.chi.pdf( 0.0, 0.0, 2.0 )\n    Infinity\n\n\nbase.dists.chi.pdf.factory( k )\n    Returns a function for evaluating the probability density function (PDF) of\n    a chi distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.chi.pdf.factory( 6.0 );\n    > var y = myPDF( 3.0 )\n    ~0.337\n\n","base.dists.chi.pdf.factory":"\nbase.dists.chi.pdf.factory( k )\n    Returns a function for evaluating the probability density function (PDF) of\n    a chi distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.chi.pdf.factory( 6.0 );\n    > var y = myPDF( 3.0 )\n    ~0.337","base.dists.chi.quantile":"\nbase.dists.chi.quantile( p, k )\n    Evaluates the quantile function for a chi distribution with degrees of\n    freedom `k` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.chi.quantile( 0.8, 1.0 )\n    ~1.282\n    > y = base.dists.chi.quantile( 0.5, 4.0 )\n    ~1.832\n    > y = base.dists.chi.quantile( 0.8, 0.1 )\n    ~0.116\n    > y = base.dists.chi.quantile( -0.2, 0.5 )\n    NaN\n    > y = base.dists.chi.quantile( 1.1, 0.5 )\n    NaN\n    > y = base.dists.chi.quantile( NaN, 1.0 )\n    NaN\n    > y = base.dists.chi.quantile( 0.0, NaN )\n    NaN\n\n    // Negative degrees of freedom:\n    > y = base.dists.chi.quantile( 0.5, -1.0 )\n    NaN\n\n    // Degenerate distribution when `k = 0`:\n    > y = base.dists.chi.quantile( 0.3, 0.0 )\n    0.0\n    > y = base.dists.chi.quantile( 0.9, 0.0 )\n    0.0\n\n\nbase.dists.chi.quantile.factory( k )\n    Returns a function for evaluating the quantile function of a chi\n    distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.chi.quantile.factory( 2.0 );\n    > var y = myquantile( 0.3 )\n    ~0.845\n    > y = myquantile( 0.7 )\n    ~1.552\n\n","base.dists.chi.quantile.factory":"\nbase.dists.chi.quantile.factory( k )\n    Returns a function for evaluating the quantile function of a chi\n    distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.chi.quantile.factory( 2.0 );\n    > var y = myquantile( 0.3 )\n    ~0.845\n    > y = myquantile( 0.7 )\n    ~1.552","base.dists.chi.skewness":"\nbase.dists.chi.skewness( k )\n    Returns the skewness of a chi distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.chi.skewness( 11.0 )\n    ~0.225\n    > v = base.dists.chi.skewness( 1.5 )\n    ~0.763\n\n","base.dists.chi.stdev":"\nbase.dists.chi.stdev( k )\n    Returns the standard deviation of a chi distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.chi.stdev( 11.0 )\n    ~0.699\n    > v = base.dists.chi.stdev( 1.5 )\n    ~0.637\n\n","base.dists.chi.variance":"\nbase.dists.chi.variance( k )\n    Returns the variance of a chi distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.chi.variance( 11.0 )\n    ~0.488\n    > v = base.dists.chi.variance( 1.5 )\n    ~0.406\n\n","base.dists.chisquare.cdf":"\nbase.dists.chisquare.cdf( x, k )\n    Evaluates the cumulative distribution function (CDF) for a chi-squared\n    distribution with degrees of freedom `k` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.chisquare.cdf( 2.0, 3.0 )\n    ~0.428\n    > y = base.dists.chisquare.cdf( 1.0, 0.5 )\n    ~0.846\n    > y = base.dists.chisquare.cdf( -1.0, 4.0 )\n    0.0\n    > y = base.dists.chisquare.cdf( NaN, 1.0 )\n    NaN\n    > y = base.dists.chisquare.cdf( 0.0, NaN )\n    NaN\n\n    // Negative degrees of freedom:\n    > y = base.dists.chisquare.cdf( 2.0, -1.0 )\n    NaN\n\n    // Degenerate distribution when `k = 0`:\n    > y = base.dists.chisquare.cdf( 2.0, 0.0 )\n    1.0\n    > y = base.dists.chisquare.cdf( -2.0, 0.0 )\n    0.0\n    > y = base.dists.chisquare.cdf( 0.0, 0.0 )\n    0.0\n\nbase.dists.chisquare.cdf.factory( k )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a chi-squared distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.chisquare.cdf.factory( 1.0 );\n    > var y = mycdf( 2.0 )\n    ~0.843\n    > y = mycdf( 1.2 )\n    ~0.727\n\n","base.dists.chisquare.cdf.factory":"\nbase.dists.chisquare.cdf.factory( k )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a chi-squared distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.chisquare.cdf.factory( 1.0 );\n    > var y = mycdf( 2.0 )\n    ~0.843\n    > y = mycdf( 1.2 )\n    ~0.727","base.dists.chisquare.ChiSquare":"\nbase.dists.chisquare.ChiSquare( [k] )\n    Returns a  chi-squared distribution object.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    chisquare: Object\n        Distribution instance.\n\n    chisquare.k: number\n        Degrees of freedom. If set, the value must be greater than `0`.\n\n    chisquare.entropy: number\n        Read-only property which returns the differential entropy.\n\n    chisquare.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    chisquare.mean: number\n        Read-only property which returns the expected value.\n\n    chisquare.median: number\n        Read-only property which returns the median.\n\n    chisquare.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    chisquare.mode: number\n        Read-only property which returns the mode.\n\n    chisquare.skewness: number\n        Read-only property which returns the skewness.\n\n    chisquare.stdev: number\n        Read-only property which returns the standard deviation.\n\n    chisquare.variance: number\n        Read-only property which returns the variance.\n\n    chisquare.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    chisquare.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    chisquare.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var chisquare = base.dists.chisquare.ChiSquare( 6.0 );\n    > chisquare.k\n    6.0\n    > chisquare.entropy\n    ~2.541\n    > chisquare.kurtosis\n    2.0\n    > chisquare.mean\n    6.0\n    > chisquare.median\n    ~5.348\n    > chisquare.mode\n    4.0\n    > chisquare.skewness\n    ~1.155\n    > chisquare.stdev\n    ~3.464\n    > chisquare.variance\n    12.0\n    > chisquare.cdf( 3.0 )\n    ~0.191\n    > chisquare.mgf( 0.2 )\n    ~4.63\n    > chisquare.pdf( 1.5 )\n    ~0.066\n    > chisquare.quantile( 0.5 )\n    ~5.348\n\n","base.dists.chisquare.entropy":"\nbase.dists.chisquare.entropy( k )\n    Returns the differential entropy of a chi-squared distribution (in nats).\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.chisquare.entropy( 11.0 )\n    ~2.901\n    > v = base.dists.chisquare.entropy( 1.5 )\n    ~1.375\n\n","base.dists.chisquare.kurtosis":"\nbase.dists.chisquare.kurtosis( k )\n    Returns the excess kurtosis of a chi-squared distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.chisquare.kurtosis( 9.0 )\n    ~1.333\n    > v = base.dists.chisquare.kurtosis( 1.5 )\n    8.0\n\n","base.dists.chisquare.logpdf":"\nbase.dists.chisquare.logpdf( x, k )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a chi-squared distribution with degrees of freedom `k` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.chisquare.logpdf( 0.3, 4.0 )\n    ~-2.74\n    > y = base.dists.chisquare.logpdf( 0.7, 0.7 )\n    ~-1.295\n    > y = base.dists.chisquare.logpdf( -1.0, 0.5 )\n    -Infinity\n    > y = base.dists.chisquare.logpdf( 0.0, NaN )\n    NaN\n    > y = base.dists.chisquare.logpdf( NaN, 2.0 )\n    NaN\n\n    // Negative degrees of freedom:\n    > y = base.dists.chisquare.logpdf( 2.0, -1.0 )\n    NaN\n\n    // Degenerate distribution when `k = 0`:\n    > y = base.dists.chisquare.logpdf( 2.0, 0.0, 2.0 )\n    -Infinity\n    > y = base.dists.chisquare.logpdf( 0.0, 0.0, 2.0 )\n    Infinity\n\n\nbase.dists.chisquare.logpdf.factory( k )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a chi-squared distribution with degrees of freedom\n    `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var myLogPDF = base.dists.chisquare.logpdf.factory( 6.0 );\n    > var y = myLogPDF( 3.0 )\n    ~-2.075\n\n","base.dists.chisquare.logpdf.factory":"\nbase.dists.chisquare.logpdf.factory( k )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a chi-squared distribution with degrees of freedom\n    `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var myLogPDF = base.dists.chisquare.logpdf.factory( 6.0 );\n    > var y = myLogPDF( 3.0 )\n    ~-2.075","base.dists.chisquare.mean":"\nbase.dists.chisquare.mean( k )\n    Returns the expected value of a chi-squared distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.chisquare.mean( 11.0 )\n    11.0\n    > v = base.dists.chisquare.mean( 4.5 )\n    4.5\n\n","base.dists.chisquare.median":"\nbase.dists.chisquare.median( k )\n    Returns the median of a chi-squared distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var k = base.dists.chisquare.median( 9.0 )\n    ~8.343\n    > k = base.dists.chisquare.median( 2.0 )\n    ~1.386\n\n","base.dists.chisquare.mgf":"\nbase.dists.chisquare.mgf( t, k )\n    Evaluates the moment-generating function (MGF) for a chi-squared\n    distribution with degrees of freedom `k` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.chisquare.mgf( 0.4, 2 )\n    ~5.0\n    > y = base.dists.chisquare.mgf( -1.0, 5.0 )\n    ~0.0642\n    > y = base.dists.chisquare.mgf( 0.0, 10.0 )\n    1.0\n\n\nbase.dists.chisquare.mgf.factory( k )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    chi-squared distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.chisquare.mgf.factory( 1.0 );\n    > var y = mymgf( 0.2 )\n    ~1.291\n    > y = mymgf( 0.4 )\n    ~2.236\n\n","base.dists.chisquare.mgf.factory":"\nbase.dists.chisquare.mgf.factory( k )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    chi-squared distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.chisquare.mgf.factory( 1.0 );\n    > var y = mymgf( 0.2 )\n    ~1.291\n    > y = mymgf( 0.4 )\n    ~2.236","base.dists.chisquare.mode":"\nbase.dists.chisquare.mode( k )\n    Returns the mode of a chi-squared distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.chisquare.mode( 11.0 )\n    9.0\n    > v = base.dists.chisquare.mode( 1.5 )\n    0.0\n\n","base.dists.chisquare.pdf":"\nbase.dists.chisquare.pdf( x, k )\n    Evaluates the probability density function (PDF) for a chi-squared\n    distribution with degrees of freedom `k` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.chisquare.pdf( 0.3, 4.0 )\n    ~0.065\n    > y = base.dists.chisquare.pdf( 0.7, 0.7 )\n    ~0.274\n    > y = base.dists.chisquare.pdf( -1.0, 0.5 )\n    0.0\n    > y = base.dists.chisquare.pdf( 0.0, NaN )\n    NaN\n    > y = base.dists.chisquare.pdf( NaN, 2.0 )\n    NaN\n\n    // Negative degrees of freedom:\n    > y = base.dists.chisquare.pdf( 2.0, -1.0 )\n    NaN\n\n    // Degenerate distribution when `k = 0`:\n    > y = base.dists.chisquare.pdf( 2.0, 0.0, 2.0 )\n    0.0\n    > y = base.dists.chisquare.pdf( 0.0, 0.0, 2.0 )\n    Infinity\n\n\nbase.dists.chisquare.pdf.factory( k )\n    Returns a function for evaluating the probability density function (PDF) of\n    a chi-squared distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.chisquare.pdf.factory( 6.0 );\n    > var y = myPDF( 3.0 )\n    ~0.126\n\n","base.dists.chisquare.pdf.factory":"\nbase.dists.chisquare.pdf.factory( k )\n    Returns a function for evaluating the probability density function (PDF) of\n    a chi-squared distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.chisquare.pdf.factory( 6.0 );\n    > var y = myPDF( 3.0 )\n    ~0.126","base.dists.chisquare.quantile":"\nbase.dists.chisquare.quantile( p, k )\n    Evaluates the quantile function for a chi-squared distribution with degrees\n    of freedom `k` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.chisquare.quantile( 0.8, 1.0 )\n    ~1.642\n    > y = base.dists.chisquare.quantile( 0.5, 4.0 )\n    ~3.357\n    > y = base.dists.chisquare.quantile( 0.8, 0.1 )\n    ~0.014\n    > y = base.dists.chisquare.quantile( -0.2, 0.5 )\n    NaN\n    > y = base.dists.chisquare.quantile( 1.1, 0.5 )\n    NaN\n    > y = base.dists.chisquare.quantile( NaN, 1.0 )\n    NaN\n    > y = base.dists.chisquare.quantile( 0.0, NaN )\n    NaN\n\n    // Negative degrees of freedom:\n    > y = base.dists.chisquare.quantile( 0.5, -1.0 )\n    NaN\n\n    // Degenerate distribution when `k = 0`:\n    > y = base.dists.chisquare.quantile( 0.3, 0.0 )\n    0.0\n    > y = base.dists.chisquare.quantile( 0.9, 0.0 )\n    0.0\n\n\nbase.dists.chisquare.quantile.factory( k )\n    Returns a function for evaluating the quantile function of a chi-squared\n    distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.chisquare.quantile.factory( 2.0 );\n    > var y = myquantile( 0.3 )\n    ~0.713\n    > y = myquantile( 0.7 )\n    ~2.408\n\n","base.dists.chisquare.quantile.factory":"\nbase.dists.chisquare.quantile.factory( k )\n    Returns a function for evaluating the quantile function of a chi-squared\n    distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.chisquare.quantile.factory( 2.0 );\n    > var y = myquantile( 0.3 )\n    ~0.713\n    > y = myquantile( 0.7 )\n    ~2.408","base.dists.chisquare.skewness":"\nbase.dists.chisquare.skewness( k )\n    Returns the skewness of a chi-squared distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.chisquare.skewness( 11.0 )\n    ~0.853\n    > v = base.dists.chisquare.skewness( 1.5 )\n    ~2.309\n\n","base.dists.chisquare.stdev":"\nbase.dists.chisquare.stdev( k )\n    Returns the standard deviation of a chi-squared distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.chisquare.stdev( 11.0 )\n    ~4.69\n    > v = base.dists.chisquare.stdev( 1.5 )\n    ~1.732\n\n","base.dists.chisquare.variance":"\nbase.dists.chisquare.variance( k )\n    Returns the variance of a chi-squared distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.chisquare.variance( 11.0 )\n    22.0\n    > v = base.dists.chisquare.variance( 1.5 )\n    3.0\n\n","base.dists.cosine.cdf":"\nbase.dists.cosine.cdf( x, μ, s )\n    Evaluates the cumulative distribution function (CDF) for a raised cosine\n    distribution with location parameter `μ` and scale parameter `s` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.cdf( 2.0, 0.0, 3.0 )\n    ~0.971\n    > y = base.dists.cosine.cdf( 9.0, 10.0, 3.0 )\n    ~0.196\n\n    > y = base.dists.cosine.cdf( 2.0, 0.0, NaN )\n    NaN\n    > y = base.dists.cosine.cdf( 2.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.cdf( NaN, 0.0, 1.0 )\n    NaN\n\n    // Degenerate distribution centered at `μ` when `s = 0.0`:\n    > y = base.dists.cosine.cdf( 2.0, 8.0, 0.0 )\n    0.0\n    > y = base.dists.cosine.cdf( 8.0, 8.0, 0.0 )\n    1.0\n    > y = base.dists.cosine.cdf( 10.0, 8.0, 0.0 )\n    1.0\n\n\nbase.dists.cosine.cdf.factory( μ, s )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a raised cosine distribution with location parameter `μ` and scale\n    parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.cosine.cdf.factory( 3.0, 1.5 );\n    > var y = mycdf( 1.9 )\n    ~0.015\n\n","base.dists.cosine.cdf.factory":"\nbase.dists.cosine.cdf.factory( μ, s )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a raised cosine distribution with location parameter `μ` and scale\n    parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.cosine.cdf.factory( 3.0, 1.5 );\n    > var y = mycdf( 1.9 )\n    ~0.015","base.dists.cosine.Cosine":"\nbase.dists.cosine.Cosine( [μ, s] )\n    Returns a raised cosine distribution object.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter. Default: `0.0`.\n\n    s: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    cosine: Object\n        Distribution instance.\n\n    cosine.mu: number\n        Location parameter.\n\n    cosine.s: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    cosine.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    cosine.mean: number\n        Read-only property which returns the expected value.\n\n    cosine.median: number\n        Read-only property which returns the median.\n\n    cosine.mode: number\n        Read-only property which returns the mode.\n\n    cosine.skewness: number\n        Read-only property which returns the skewness.\n\n    cosine.stdev: number\n        Read-only property which returns the standard deviation.\n\n    cosine.variance: number\n        Read-only property which returns the variance.\n\n    cosine.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    cosine.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    cosine.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    cosine.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    cosine.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    cosine.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var cosine = base.dists.cosine.Cosine( -2.0, 3.0 );\n    > cosine.mu\n    -2.0\n    > cosine.s\n    3.0\n    > cosine.kurtosis\n    ~-0.594\n    > cosine.mean\n    -2.0\n    > cosine.median\n    -2.0\n    > cosine.mode\n    -2.0\n    > cosine.skewness\n    0.0\n    > cosine.stdev\n    ~1.085\n    > cosine.variance\n    ~1.176\n    > cosine.cdf( 0.5 )\n    ~0.996\n    > cosine.logcdf( 0.5 )\n    ~-0.004\n    > cosine.logpdf( -1.0 )\n    ~-1.386\n    > cosine.mgf( 0.2 )\n    ~0.686\n    > cosine.pdf( -2.0 )\n    ~0.333\n    > cosine.quantile( 0.9 )\n    ~-0.553\n\n","base.dists.cosine.kurtosis":"\nbase.dists.cosine.kurtosis( μ, s )\n    Returns the excess kurtosis of a raised cosine distribution with location\n    parameter `μ` and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.kurtosis( 0.0, 1.0 )\n    ~-0.594\n    > y = base.dists.cosine.kurtosis( 4.0, 2.0 )\n    ~-0.594\n    > y = base.dists.cosine.kurtosis( NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.kurtosis( 0.0, NaN )\n    NaN\n    > y = base.dists.cosine.kurtosis( 0.0, 0.0 )\n    NaN\n\n","base.dists.cosine.logcdf":"\nbase.dists.cosine.logcdf( x, μ, s )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a raised cosine distribution with location parameter `μ` and scale\n     parameter `s` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.logcdf( 2.0, 0.0, 3.0 )\n    ~-0.029\n    > y = base.dists.cosine.logcdf( 9.0, 10.0, 3.0 )\n    ~-1.632\n\n    > y = base.dists.cosine.logcdf( 2.0, 0.0, NaN )\n    NaN\n    > y = base.dists.cosine.logcdf( 2.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.logcdf( NaN, 0.0, 1.0 )\n    NaN\n\n    // Degenerate distribution centered at `μ` when `s = 0.0`:\n    > y = base.dists.cosine.logcdf( 2.0, 8.0, 0.0 )\n    -Infinity\n    > y = base.dists.cosine.logcdf( 8.0, 8.0, 0.0 )\n    0.0\n    > y = base.dists.cosine.logcdf( 10.0, 8.0, 0.0 )\n    0.0\n\n\nbase.dists.cosine.logcdf.factory( μ, s )\n    Returns a function for evaluating the natural logarithm of the  cumulative\n    distribution function (CDF) of a raised cosine distribution with location\n    parameter `μ` and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.cosine.logcdf.factory( 3.0, 1.5 );\n    > var y = mylogcdf( 1.9 )\n    ~-4.2\n\n","base.dists.cosine.logcdf.factory":"\nbase.dists.cosine.logcdf.factory( μ, s )\n    Returns a function for evaluating the natural logarithm of the  cumulative\n    distribution function (CDF) of a raised cosine distribution with location\n    parameter `μ` and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.cosine.logcdf.factory( 3.0, 1.5 );\n    > var y = mylogcdf( 1.9 )\n    ~-4.2","base.dists.cosine.logpdf":"\nbase.dists.cosine.logpdf( x, μ, s )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    raised cosine distribution with location parameter `μ` and scale parameter\n    `s` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.logpdf( 2.0, 0.0, 3.0 )\n    ~-2.485\n    > y = base.dists.cosine.logpdf( -1.0, 2.0, 4.0 )\n    ~-3.307\n    > y = base.dists.cosine.logpdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.cosine.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.logpdf( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.cosine.logpdf( 2.0, 0.0, -1.0 )\n    NaN\n\n    // Degenerate distribution at `s = 0.0`:\n    > y = base.dists.cosine.logpdf( 2.0, 8.0, 0.0 )\n    -Infinity\n    > y = base.dists.cosine.logpdf( 8.0, 8.0, 0.0 )\n    Infinity\n\n\nbase.dists.cosine.logpdf.factory( μ, s )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a raised cosine distribution with location parameter `μ`\n    and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.cosine.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogpdf( 10.0 )\n    ~-0.693\n\n","base.dists.cosine.logpdf.factory":"\nbase.dists.cosine.logpdf.factory( μ, s )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a raised cosine distribution with location parameter `μ`\n    and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.cosine.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogpdf( 10.0 )\n    ~-0.693","base.dists.cosine.mean":"\nbase.dists.cosine.mean( μ, s )\n    Returns the expected value of a raised cosine distribution with location\n    parameter `μ` and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.mean( 0.0, 1.0 )\n    0.0\n    > y = base.dists.cosine.mean( 4.0, 2.0 )\n    4.0\n    > y = base.dists.cosine.mean( NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.mean( 0.0, NaN )\n    NaN\n    > y = base.dists.cosine.mean( 0.0, 0.0 )\n    NaN\n\n","base.dists.cosine.median":"\nbase.dists.cosine.median( μ, s )\n    Returns the median of a raised cosine distribution with location parameter\n    `μ` and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.median( 0.0, 1.0 )\n    0.0\n    > y = base.dists.cosine.median( 4.0, 2.0 )\n    4.0\n    > y = base.dists.cosine.median( NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.median( 0.0, NaN )\n    NaN\n    > y = base.dists.cosine.median( 0.0, 0.0 )\n    NaN\n\n","base.dists.cosine.mgf":"\nbase.dists.cosine.mgf( t, μ, s )\n    Evaluates the moment-generating function (MGF) for a raised cosine\n    distribution with location parameter `μ` and scale parameter `s` at a value\n    `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.mgf( 2.0, 0.0, 3.0 )\n    ~7.234\n    > y = base.dists.cosine.mgf( 9.0, 10.0, 3.0 )\n    ~1.606e+47\n\n    > y = base.dists.cosine.mgf( 0.5, 0.0, NaN )\n    NaN\n    > y = base.dists.cosine.mgf( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.mgf( NaN, 0.0, 1.0 )\n    NaN\n\n\nbase.dists.cosine.mgf.factory( μ, s )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    raised cosine distribution with location parameter `μ` and scale parameter\n    `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.cosine.mgf.factory( 3.0, 1.5 );\n    > var y = mymgf( 1.9 )\n    ~495.57\n\n","base.dists.cosine.mgf.factory":"\nbase.dists.cosine.mgf.factory( μ, s )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    raised cosine distribution with location parameter `μ` and scale parameter\n    `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.cosine.mgf.factory( 3.0, 1.5 );\n    > var y = mymgf( 1.9 )\n    ~495.57","base.dists.cosine.mode":"\nbase.dists.cosine.mode( μ, s )\n    Returns the mode of a raised cosine distribution with location parameter `μ`\n    and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.mode( 0.0, 1.0 )\n    0.0\n    > y = base.dists.cosine.mode( 4.0, 2.0 )\n    4.0\n    > y = base.dists.cosine.mode( NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.mode( 0.0, NaN )\n    NaN\n    > y = base.dists.cosine.mode( 0.0, 0.0 )\n    NaN\n\n","base.dists.cosine.pdf":"\nbase.dists.cosine.pdf( x, μ, s )\n    Evaluates the probability density function (PDF) for a raised cosine\n    distribution with location parameter `μ` and scale parameter `s` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.pdf( 2.0, 0.0, 3.0 )\n    ~0.083\n    > y = base.dists.cosine.pdf( 2.4, 4.0, 2.0 )\n    ~0.048\n    > y = base.dists.cosine.pdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.cosine.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.pdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.cosine.pdf( 2.0, 0.0, -1.0 )\n    NaN\n    > y = base.dists.cosine.pdf( 2.0, 8.0, 0.0 )\n    0.0\n    > y = base.dists.cosine.pdf( 8.0, 8.0, 0.0 )\n    Infinity\n\n\nbase.dists.cosine.pdf.factory( μ, s )\n    Returns a function for evaluating the probability density function (PDF) of\n    a raised cosine distribution with location parameter `μ` and scale parameter\n    `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.cosine.pdf.factory( 0.0, 3.0 );\n    > var y = myPDF( 2.0 )\n    ~0.083\n\n","base.dists.cosine.pdf.factory":"\nbase.dists.cosine.pdf.factory( μ, s )\n    Returns a function for evaluating the probability density function (PDF) of\n    a raised cosine distribution with location parameter `μ` and scale parameter\n    `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.cosine.pdf.factory( 0.0, 3.0 );\n    > var y = myPDF( 2.0 )\n    ~0.083","base.dists.cosine.quantile":"\nbase.dists.cosine.quantile( p, μ, s )\n    Evaluates the quantile function for a raised cosine distribution with\n    location parameter `μ` and scale parameter `s` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.quantile( 0.8, 0.0, 1.0 )\n    ~0.327\n    > y = base.dists.cosine.quantile( 0.5, 4.0, 2.0 )\n    ~4.0\n\n    > y = base.dists.cosine.quantile( 1.1, 0.0, 1.0 )\n    NaN\n    > y = base.dists.cosine.quantile( -0.2, 0.0, 1.0 )\n    NaN\n\n    > y = base.dists.cosine.quantile( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.cosine.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.quantile( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.cosine.quantile( 0.5, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.cosine.quantile.factory( μ, s )\n    Returns a function for evaluating the quantile function of a raised cosine\n    distribution with location parameter `μ` and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.cosine.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.3 )\n    ~9.586\n\n","base.dists.cosine.quantile.factory":"\nbase.dists.cosine.quantile.factory( μ, s )\n    Returns a function for evaluating the quantile function of a raised cosine\n    distribution with location parameter `μ` and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.cosine.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.3 )\n    ~9.586","base.dists.cosine.skewness":"\nbase.dists.cosine.skewness( μ, s )\n    Returns the skewness of a raised cosine distribution with location parameter\n    `μ` and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.skewness( 0.0, 1.0 )\n    0.0\n    > y = base.dists.cosine.skewness( 4.0, 2.0 )\n    0.0\n    > y = base.dists.cosine.skewness( NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.skewness( 0.0, NaN )\n    NaN\n    > y = base.dists.cosine.skewness( 0.0, 0.0 )\n    NaN\n\n","base.dists.cosine.stdev":"\nbase.dists.cosine.stdev( μ, s )\n    Returns the standard deviation of a raised cosine distribution with location\n    parameter `μ` and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.stdev( 0.0, 1.0 )\n    ~0.362\n    > y = base.dists.cosine.stdev( 4.0, 2.0 )\n    ~0.723\n    > y = base.dists.cosine.stdev( NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.stdev( 0.0, NaN )\n    NaN\n    > y = base.dists.cosine.stdev( 0.0, 0.0 )\n    NaN\n\n","base.dists.cosine.variance":"\nbase.dists.cosine.variance( μ, s )\n    Returns the variance of a raised cosine distribution with location parameter\n    `μ` and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.variance( 0.0, 1.0 )\n    ~0.131\n    > y = base.dists.cosine.variance( 4.0, 2.0 )\n    ~0.523\n    > y = base.dists.cosine.variance( NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.variance( 0.0, NaN )\n    NaN\n    > y = base.dists.cosine.variance( 0.0, 0.0 )\n    NaN\n\n","base.dists.degenerate.cdf":"\nbase.dists.degenerate.cdf( x, μ )\n    Evaluates the cumulative distribution function (CDF) for a degenerate\n    distribution with mean value `μ`.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.degenerate.cdf( 2.0, 3.0 )\n    0.0\n    > y = base.dists.degenerate.cdf( 4.0, 3.0 )\n    1.0\n    > y = base.dists.degenerate.cdf( 3.0, 3.0 )\n    1.0\n    > y = base.dists.degenerate.cdf( NaN, 0.0 )\n    NaN\n    > y = base.dists.degenerate.cdf( 0.0, NaN )\n    NaN\n\n\nbase.dists.degenerate.cdf.factory( μ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a degenerate distribution centered at a provided mean value.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.degenerate.cdf.factory( 5.0 );\n    > var y = myCDF( 3.0 )\n    0.0\n    > y = myCDF( 6.0 )\n    1.0\n\n","base.dists.degenerate.cdf.factory":"\nbase.dists.degenerate.cdf.factory( μ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a degenerate distribution centered at a provided mean value.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.degenerate.cdf.factory( 5.0 );\n    > var y = myCDF( 3.0 )\n    0.0\n    > y = myCDF( 6.0 )\n    1.0","base.dists.degenerate.Degenerate":"\nbase.dists.degenerate.Degenerate( [μ] )\n    Returns a degenerate distribution object.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Constant value of distribution.\n\n    Returns\n    -------\n    degenerate: Object\n        Distribution instance.\n\n    degenerate.mu: number\n        Constant value of distribution.\n\n    degenerate.entropy: number\n        Read-only property which returns the differential entropy.\n\n    degenerate.mean: number\n        Read-only property which returns the expected value.\n\n    degenerate.median: number\n        Read-only property which returns the median.\n\n    degenerate.stdev: number\n        Read-only property which returns the standard deviation.\n\n    degenerate.variance: number\n        Read-only property which returns the variance.\n\n    degenerate.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    degenerate.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    degenerate.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    degenerate.logpmf: Function\n        Evaluates the natural logarithm of the probability mass function\n        (PMF).\n\n    degenerate.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    degenerate.pmf: Function\n        Evaluates the probability mass function (PMF).\n\n    degenerate.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    degenerate.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var degenerate = base.dists.degenerate.Degenerate( 2.0 );\n    > degenerate.mu\n    2.0\n    > degenerate.entropy\n    0.0\n    > degenerate.mean\n    2.0\n    > degenerate.mode\n    2.0\n    > degenerate.median\n    2.0\n    > degenerate.stdev\n    0.0\n    > degenerate.variance\n    0.0\n    > degenerate.cdf( 0.5 )\n    0.0\n    > degenerate.logcdf( 2.5 )\n    0.0\n    > degenerate.logpdf( 0.5 )\n    -Infinity\n    > degenerate.logpmf( 2.5 )\n    -Infinity\n    > degenerate.mgf( 0.2 )\n    ~1.492\n    > degenerate.pdf( 2.0 )\n    +Infinity\n    > degenerate.pmf( 2.0 )\n    1.0\n    > degenerate.quantile( 0.7 )\n    2.0\n\n","base.dists.degenerate.entropy":"\nbase.dists.degenerate.entropy( μ )\n    Returns the entropy of a degenerate distribution with constant value `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.degenerate.entropy( 20.0 )\n    0.0\n    > v = base.dists.degenerate.entropy( -10.0 )\n    0.0\n\n","base.dists.degenerate.logcdf":"\nbase.dists.degenerate.logcdf( x, μ )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (logCDF) for a degenerate distribution with mean `μ`.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Natural logarithm of the CDF.\n\n    Examples\n    --------\n    > var y = base.dists.degenerate.logcdf( 2.0, 3.0 )\n    -Infinity\n    > y = base.dists.degenerate.logcdf( 4.0, 3.0 )\n    0\n    > y = base.dists.degenerate.logcdf( 3.0, 3.0 )\n    0\n    > y = base.dists.degenerate.logcdf( NaN, 0.0 )\n    NaN\n    > y = base.dists.degenerate.logcdf( 0.0, NaN )\n    NaN\n\n\nbase.dists.degenerate.logcdf.factory( μ )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (logCDF) of a degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    logcdf: Function\n        Function to evaluate the natural logarithm of cumulative distribution\n        function (logCDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.degenerate.logcdf.factory( 5.0 );\n    > var y = mylogcdf( 3.0 )\n    -Infinity\n    > y = mylogcdf( 6.0 )\n    0\n\n","base.dists.degenerate.logcdf.factory":"\nbase.dists.degenerate.logcdf.factory( μ )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (logCDF) of a degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    logcdf: Function\n        Function to evaluate the natural logarithm of cumulative distribution\n        function (logCDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.degenerate.logcdf.factory( 5.0 );\n    > var y = mylogcdf( 3.0 )\n    -Infinity\n    > y = mylogcdf( 6.0 )\n    0","base.dists.degenerate.logpdf":"\nbase.dists.degenerate.logpdf( x, μ )\n    Evaluates the natural logarithm of the probability density function (logPDF)\n    for a degenerate distribution with mean `μ`.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Natural logarithm of the PDF.\n\n    Examples\n    --------\n    > var y = base.dists.degenerate.logpdf( 2.0, 3.0 )\n    -Infinity\n    > y = base.dists.degenerate.logpdf( 3.0, 3.0 )\n    Infinity\n    > y = base.dists.degenerate.logpdf( NaN, 0.0 )\n    NaN\n    > y = base.dists.degenerate.logpdf( 0.0, NaN )\n    NaN\n\n\nbase.dists.degenerate.logpdf.factory( μ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (logPDF) of a degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    logpdf: Function\n        Function to evaluate the natural logarithm of the PDF.\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.degenerate.logpdf.factory( 10.0 );\n    > var y = mylogPDF( 10.0 )\n    Infinity\n\n","base.dists.degenerate.logpdf.factory":"\nbase.dists.degenerate.logpdf.factory( μ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (logPDF) of a degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    logpdf: Function\n        Function to evaluate the natural logarithm of the PDF.\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.degenerate.logpdf.factory( 10.0 );\n    > var y = mylogPDF( 10.0 )\n    Infinity","base.dists.degenerate.logpmf":"\nbase.dists.degenerate.logpmf( x, μ )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    degenerate distribution with mean `μ`.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPMF.\n\n    Examples\n    --------\n    > var y = base.dists.degenerate.logpmf( 2.0, 3.0 )\n    -Infinity\n    > y = base.dists.degenerate.logpmf( 3.0, 3.0 )\n    0.0\n    > y = base.dists.degenerate.logpmf( NaN, 0.0 )\n    NaN\n    > y = base.dists.degenerate.logpmf( 0.0, NaN )\n    NaN\n\n\nbase.dists.degenerate.logpmf.factory( μ )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogPMF = base.dists.degenerate.logpmf.factory( 10.0 );\n    > var y = mylogPMF( 10.0 )\n    0.0\n\n","base.dists.degenerate.logpmf.factory":"\nbase.dists.degenerate.logpmf.factory( μ )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogPMF = base.dists.degenerate.logpmf.factory( 10.0 );\n    > var y = mylogPMF( 10.0 )\n    0.0","base.dists.degenerate.mean":"\nbase.dists.degenerate.mean( μ )\n    Returns the expected value of a degenerate distribution with constant value\n    `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.degenerate.mean( 20.0 )\n    20.0\n    > v = base.dists.degenerate.mean( -10.0 )\n    -10.0\n\n","base.dists.degenerate.median":"\nbase.dists.degenerate.median( μ )\n    Returns the median of a degenerate distribution with constant value `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.degenerate.median( 20.0 )\n    20.0\n    > v = base.dists.degenerate.median( -10.0 )\n    -10.0\n\n","base.dists.degenerate.mgf":"\nbase.dists.degenerate.mgf( x, μ )\n    Evaluates the moment-generating function (MGF) for a degenerate distribution\n    with mean `μ`.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.degenerate.mgf( 1.0, 1.0 )\n    ~2.718\n    > y = base.dists.degenerate.mgf( 2.0, 3.0 )\n    ~403.429\n    > y = base.dists.degenerate.mgf( NaN, 0.0 )\n    NaN\n    > y = base.dists.degenerate.mgf( 0.0, NaN )\n    NaN\n\n\nbase.dists.degenerate.mgf.factory( μ )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.degenerate.mgf.factory( 10.0 );\n    > var y = myMGF( 0.1 )\n    ~2.718\n\n","base.dists.degenerate.mgf.factory":"\nbase.dists.degenerate.mgf.factory( μ )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.degenerate.mgf.factory( 10.0 );\n    > var y = myMGF( 0.1 )\n    ~2.718","base.dists.degenerate.mode":"\nbase.dists.degenerate.mode( μ )\n    Returns the mode of a degenerate distribution with constant value `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.degenerate.mode( 20.0 )\n    20.0\n    > v = base.dists.degenerate.mode( -10.0 )\n    -10.0\n\n","base.dists.degenerate.pdf":"\nbase.dists.degenerate.pdf( x, μ )\n    Evaluates the probability density function (PDF) for a degenerate\n    distribution with mean `μ`.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.degenerate.pdf( 2.0, 3.0 )\n    0.0\n    > y = base.dists.degenerate.pdf( 3.0, 3.0 )\n    Infinity\n    > y = base.dists.degenerate.pdf( NaN, 0.0 )\n    NaN\n    > y = base.dists.degenerate.pdf( 0.0, NaN )\n    NaN\n\n\nbase.dists.degenerate.pdf.factory( μ )\n    Returns a function for evaluating the probability density function (PDF) of\n    a degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.degenerate.pdf.factory( 10.0 );\n    > var y = myPDF( 10.0 )\n    Infinity\n\n","base.dists.degenerate.pdf.factory":"\nbase.dists.degenerate.pdf.factory( μ )\n    Returns a function for evaluating the probability density function (PDF) of\n    a degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.degenerate.pdf.factory( 10.0 );\n    > var y = myPDF( 10.0 )\n    Infinity","base.dists.degenerate.pmf":"\nbase.dists.degenerate.pmf( x, μ )\n    Evaluates the probability mass function (PMF) for a degenerate distribution\n    with mean `μ`.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Evaluated PMF.\n\n    Examples\n    --------\n    > var y = base.dists.degenerate.pmf( 2.0, 3.0 )\n    0.0\n    > y = base.dists.degenerate.pmf( 3.0, 3.0 )\n    1.0\n    > y = base.dists.degenerate.pmf( NaN, 0.0 )\n    NaN\n    > y = base.dists.degenerate.pmf( 0.0, NaN )\n    NaN\n\n\nbase.dists.degenerate.pmf.factory( μ )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var myPMF = base.dists.degenerate.pmf.factory( 10.0 );\n    > var y = myPMF( 10.0 )\n    1.0\n\n","base.dists.degenerate.pmf.factory":"\nbase.dists.degenerate.pmf.factory( μ )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var myPMF = base.dists.degenerate.pmf.factory( 10.0 );\n    > var y = myPMF( 10.0 )\n    1.0","base.dists.degenerate.quantile":"\nbase.dists.degenerate.quantile( p, μ )\n    Evaluates the quantile function for a degenerate distribution with mean `μ`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.degenerate.quantile( 0.5, 2.0 )\n    2.0\n    > y = base.dists.degenerate.quantile( 0.9, 4.0 )\n    4.0\n    > y = base.dists.degenerate.quantile( 1.1, 0.0 )\n    NaN\n    > y = base.dists.degenerate.quantile( -0.2, 0.0 )\n    NaN\n    > y = base.dists.degenerate.quantile( NaN, 0.0 )\n    NaN\n    > y = base.dists.degenerate.quantile( 0.0, NaN )\n    NaN\n\n\nbase.dists.degenerate.quantile.factory( μ )\n    Returns a function for evaluating the quantile function of a degenerate\n    distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.degenerate.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    10.0\n\n","base.dists.degenerate.quantile.factory":"\nbase.dists.degenerate.quantile.factory( μ )\n    Returns a function for evaluating the quantile function of a degenerate\n    distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.degenerate.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    10.0","base.dists.degenerate.stdev":"\nbase.dists.degenerate.stdev( μ )\n    Returns the standard deviation of a degenerate distribution with constant\n    value `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.degenerate.stdev( 20.0 )\n    0.0\n    > v = base.dists.degenerate.stdev( -10.0 )\n    0.0\n\n","base.dists.degenerate.variance":"\nbase.dists.degenerate.variance( μ )\n    Returns the variance of a degenerate distribution with constant value `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.degenerate.variance( 20.0 )\n    0.0\n    > v = base.dists.degenerate.variance( -10.0 )\n    0.0\n\n","base.dists.discreteUniform.cdf":"\nbase.dists.discreteUniform.cdf( x, a, b )\n    Evaluates the cumulative distribution function (CDF) for a discrete uniform\n    distribution with minimum support `a` and maximum support `b` at a value\n    `x`.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.discreteUniform.cdf( 9.0, 0, 10 )\n    ~0.909\n    > y = base.dists.discreteUniform.cdf( 0.5, 0, 2 )\n    ~0.333\n    > y = base.dists.discreteUniform.cdf( PINF, 2, 4 )\n    1.0\n    > y = base.dists.discreteUniform.cdf( NINF, 2, 4 )\n    0.0\n    > y = base.dists.discreteUniform.cdf( NaN, 0, 1 )\n    NaN\n    > y = base.dists.discreteUniform.cdf( 0.0, NaN, 1 )\n    NaN\n    > y = base.dists.discreteUniform.cdf( 0.0, 0, NaN )\n    NaN\n    > y = base.dists.discreteUniform.cdf( 2.0, 1, 0 )\n    NaN\n\n\nbase.dists.discreteUniform.cdf.factory( a, b )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a discrete uniform distribution with minimum support `a` and maximum\n    support `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.discreteUniform.cdf.factory( 0, 10 );\n    > var y = mycdf( 0.5 )\n    ~0.091\n    > y = mycdf( 8.0 )\n    ~0.818\n\n","base.dists.discreteUniform.cdf.factory":"\nbase.dists.discreteUniform.cdf.factory( a, b )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a discrete uniform distribution with minimum support `a` and maximum\n    support `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.discreteUniform.cdf.factory( 0, 10 );\n    > var y = mycdf( 0.5 )\n    ~0.091\n    > y = mycdf( 8.0 )\n    ~0.818","base.dists.discreteUniform.DiscreteUniform":"\nbase.dists.discreteUniform.DiscreteUniform( [a, b] )\n    Returns a discrete uniform distribution object.\n\n    Parameters\n    ----------\n    a: integer (optional)\n        Minimum support. Must be an integer smaller than `b`. Default: `0`.\n\n    b: integer (optional)\n        Maximum support. Must be an integer greater than `a`. Default: `1`.\n\n    Returns\n    -------\n    discreteUniform: Object\n        Distribution instance.\n\n    discreteUniform.a: integer\n        Minimum support. If set, the value must be an integer smaller than or\n        equal to `b`.\n\n    discreteUniform.b: integer\n        Maximum support. If set, the value must be an integer greater than or\n        equal to `a`.\n\n    discreteUniform.entropy: number\n        Read-only property which returns the entropy.\n\n    discreteUniform.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    discreteUniform.mean: number\n        Read-only property which returns the expected value.\n\n    discreteUniform.median: number\n        Read-only property which returns the median.\n\n    discreteUniform.skewness: number\n        Read-only property which returns the skewness.\n\n    discreteUniform.stdev: number\n        Read-only property which returns the standard deviation.\n\n    discreteUniform.variance: number\n        Read-only property which returns the variance.\n\n    discreteUniform.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    discreteUniform.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    discreteUniform.logpmf: Function\n        Evaluates the natural logarithm of the probability mass function (PMF).\n\n    discreteUniform.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    discreteUniform.pmf: Function\n        Evaluates the probability mass function (PMF).\n\n    discreteUniform.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var discreteUniform = base.dists.discreteUniform.DiscreteUniform( -2, 2 );\n    > discreteUniform.a\n    -2\n    > discreteUniform.b\n    2\n    > discreteUniform.entropy\n    ~1.609\n    > discreteUniform.kurtosis\n    -1.3\n    > discreteUniform.mean\n    0.0\n    > discreteUniform.median\n    0.0\n    > discreteUniform.skewness\n    0.0\n    > discreteUniform.stdev\n    ~1.414\n    > discreteUniform.variance\n    2.0\n    > discreteUniform.cdf( 0.8 )\n    0.6\n    > discreteUniform.logcdf( 0.5 )\n    ~-0.511\n    > discreteUniform.logpmf( 1.0 )\n    ~-1.609\n    > discreteUniform.mgf( 0.8 )\n    ~1.766\n    > discreteUniform.pmf( 0.0 )\n    0.2\n    > discreteUniform.quantile( 0.8 )\n    2.0\n\n","base.dists.discreteUniform.entropy":"\nbase.dists.discreteUniform.entropy( a, b )\n    Returns the entropy of a discrete uniform distribution.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.discreteUniform.entropy( 0, 1 )\n    ~0.693\n    > v = base.dists.discreteUniform.entropy( 4, 12 )\n    ~2.197\n    > v = base.dists.discreteUniform.entropy( 2, 8 )\n    ~1.946\n\n","base.dists.discreteUniform.kurtosis":"\nbase.dists.discreteUniform.kurtosis( a, b )\n    Returns the excess kurtosis of a discrete uniform distribution.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.discreteUniform.kurtosis( 0, 1 )\n    -2.0\n    > v = base.dists.discreteUniform.kurtosis( 4, 12 )\n    ~-1.23\n    > v = base.dists.discreteUniform.kurtosis( -4, 8 )\n    ~-1.214\n\n","base.dists.discreteUniform.logcdf":"\nbase.dists.discreteUniform.logcdf( x, a, b )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a discrete uniform distribution with minimum support `a` and\n    maximum support `b` at a value `x`.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.discreteUniform.logcdf( 9.0, 0, 10 )\n    ~-0.095\n    > y = base.dists.discreteUniform.logcdf( 0.5, 0, 2 )\n    ~-1.099\n    > y = base.dists.discreteUniform.logcdf( PINF, 2, 4 )\n    0.0\n    > y = base.dists.discreteUniform.logcdf( NINF, 2, 4 )\n    -Infinity\n    > y = base.dists.discreteUniform.logcdf( NaN, 0, 1 )\n    NaN\n    > y = base.dists.discreteUniform.logcdf( 0.0, NaN, 1 )\n    NaN\n    > y = base.dists.discreteUniform.logcdf( 0.0, 0, NaN )\n    NaN\n    > y = base.dists.discreteUniform.logcdf( 2.0, 1, 0 )\n    NaN\n\n\nbase.dists.discreteUniform.logcdf.factory( a, b )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a discrete uniform distribution with minimum\n    support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myLogCDF = base.dists.discreteUniform.logcdf.factory( 0, 10 );\n    > var y = myLogCDF( 0.5 )\n    ~-2.398\n    > y = myLogCDF( 8.0 )\n    ~-0.201\n\n","base.dists.discreteUniform.logcdf.factory":"\nbase.dists.discreteUniform.logcdf.factory( a, b )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a discrete uniform distribution with minimum\n    support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myLogCDF = base.dists.discreteUniform.logcdf.factory( 0, 10 );\n    > var y = myLogCDF( 0.5 )\n    ~-2.398\n    > y = myLogCDF( 8.0 )\n    ~-0.201","base.dists.discreteUniform.logpmf":"\nbase.dists.discreteUniform.logpmf( x, a, b )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    discrete uniform distribution with minimum support `a` and maximum support\n    `b` at a value `x`.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPMF.\n\n    Examples\n    --------\n    > var y = base.dists.discreteUniform.logpmf( 2.0, 0, 4 )\n    ~-1.609\n    > y = base.dists.discreteUniform.logpmf( 5.0, 0, 4 )\n    -Infinity\n    > y = base.dists.discreteUniform.logpmf( 3.0, -4, 4 )\n    ~-2.197\n    > y = base.dists.discreteUniform.logpmf( NaN, 0, 1 )\n    NaN\n    > y = base.dists.discreteUniform.logpmf( 0.0, NaN, 1 )\n    NaN\n    > y = base.dists.discreteUniform.logpmf( 0.0, 0, NaN )\n    NaN\n    > y = base.dists.discreteUniform.logpmf( 2.0, 3, 1 )\n    NaN\n    > y = base.dists.discreteUniform.logpmf( 2.0, 1, 2.4 )\n    NaN\n\n\nbase.dists.discreteUniform.logpmf.factory( a, b )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a discrete uniform distribution with minimum support\n    `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var myLogPMF = base.dists.discreteUniform.logpmf.factory( 6, 7 );\n    > var y = myLogPMF( 7.0 )\n    ~-0.693\n    > y = myLogPMF( 5.0 )\n    -Infinity\n\n","base.dists.discreteUniform.logpmf.factory":"\nbase.dists.discreteUniform.logpmf.factory( a, b )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a discrete uniform distribution with minimum support\n    `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var myLogPMF = base.dists.discreteUniform.logpmf.factory( 6, 7 );\n    > var y = myLogPMF( 7.0 )\n    ~-0.693\n    > y = myLogPMF( 5.0 )\n    -Infinity","base.dists.discreteUniform.mean":"\nbase.dists.discreteUniform.mean( a, b )\n    Returns the expected value of a discrete uniform distribution.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.discreteUniform.mean( -2, 2 )\n    0.0\n    > v = base.dists.discreteUniform.mean( 4, 12 )\n    8.0\n    > v = base.dists.discreteUniform.mean( 2, 8 )\n    5.0\n\n","base.dists.discreteUniform.median":"\nbase.dists.discreteUniform.median( a, b )\n    Returns the median of a discrete uniform distribution.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.discreteUniform.median( -2, 2 )\n    0.0\n    > v = base.dists.discreteUniform.median( 4, 12 )\n    8.0\n    > v = base.dists.discreteUniform.median( 2, 8 )\n    5.0\n\n","base.dists.discreteUniform.mgf":"\nbase.dists.discreteUniform.mgf( t, a, b )\n    Evaluates the moment-generating function (MGF) for a discrete uniform\n    distribution with minimum support `a` and maximum support `b` at a value\n    `t`.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.discreteUniform.mgf( 2.0, 0, 4 )\n    ~689.475\n    > y = base.dists.discreteUniform.mgf( -0.2, 0, 4 )\n    ~0.697\n    > y = base.dists.discreteUniform.mgf( 2.0, 0, 1 )\n    ~4.195\n    > y = base.dists.discreteUniform.mgf( 0.5, 3, 2 )\n    NaN\n    > y = base.dists.discreteUniform.mgf( NaN, 0, 1  )\n    NaN\n    > y = base.dists.discreteUniform.mgf( 0.0, NaN, 1 )\n    NaN\n    > y = base.dists.discreteUniform.mgf( 0.0, 0, NaN )\n    NaN\n\n\nbase.dists.discreteUniform.mgf.factory( a, b )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a discrete uniform distribution with minimum support `a` and maximum\n    support `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.discreteUniform.mgf.factory( 6, 7 );\n    > var y = mymgf( 0.1 )\n    ~1.918\n    > y = mymgf( 1.1 )\n    ~1471.722\n\n","base.dists.discreteUniform.mgf.factory":"\nbase.dists.discreteUniform.mgf.factory( a, b )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a discrete uniform distribution with minimum support `a` and maximum\n    support `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.discreteUniform.mgf.factory( 6, 7 );\n    > var y = mymgf( 0.1 )\n    ~1.918\n    > y = mymgf( 1.1 )\n    ~1471.722","base.dists.discreteUniform.pmf":"\nbase.dists.discreteUniform.pmf( x, a, b )\n    Evaluates the probability mass function (PMF) for a discrete uniform\n    distribution with minimum support `a` and maximum support `b` at a value\n    `x`.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated PMF.\n\n    Examples\n    --------\n    > var y = base.dists.discreteUniform.pmf( 2.0, 0, 4 )\n    ~0.2\n    > y = base.dists.discreteUniform.pmf( 5.0, 0, 4 )\n    0.0\n    > y = base.dists.discreteUniform.pmf( 3.0, -4, 4 )\n    ~0.111\n    > y = base.dists.discreteUniform.pmf( NaN, 0, 1 )\n    NaN\n    > y = base.dists.discreteUniform.pmf( 0.0, NaN, 1 )\n    NaN\n    > y = base.dists.discreteUniform.pmf( 0.0, 0, NaN )\n    NaN\n    > y = base.dists.discreteUniform.pmf( 2.0, 3, 1 )\n    NaN\n    > y = base.dists.discreteUniform.pmf( 2.0, 1, 2.4 )\n    NaN\n\n\nbase.dists.discreteUniform.pmf.factory( a, b )\n    Returns a function for evaluating the probability mass function (PMF) of\n    a discrete uniform distribution with minimum support `a` and maximum support\n    `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var myPMF = base.dists.discreteUniform.pmf.factory( 6, 7 );\n    > var y = myPMF( 7.0 )\n    0.5\n    > y = myPMF( 5.0 )\n    0.0\n\n","base.dists.discreteUniform.pmf.factory":"\nbase.dists.discreteUniform.pmf.factory( a, b )\n    Returns a function for evaluating the probability mass function (PMF) of\n    a discrete uniform distribution with minimum support `a` and maximum support\n    `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var myPMF = base.dists.discreteUniform.pmf.factory( 6, 7 );\n    > var y = myPMF( 7.0 )\n    0.5\n    > y = myPMF( 5.0 )\n    0.0","base.dists.discreteUniform.quantile":"\nbase.dists.discreteUniform.quantile( p, a, b )\n    Evaluates the quantile function for a discrete uniform distribution with\n    minimum support `a` and maximum support `b` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    If provided `a > b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.discreteUniform.quantile( 0.8, 0, 1 )\n    1\n    > y = base.dists.discreteUniform.quantile( 0.5, 0.0, 10.0 )\n    5\n\n    > y = base.dists.discreteUniform.quantile( 1.1, 0, 4 )\n    NaN\n    > y = base.dists.discreteUniform.quantile( -0.2, 0, 4 )\n    NaN\n\n    > y = base.dists.discreteUniform.quantile( NaN, -2, 2 )\n    NaN\n    > y = base.dists.discreteUniform.quantile( 0.1, NaN, 2 )\n    NaN\n    > y = base.dists.discreteUniform.quantile( 0.1, -2, NaN )\n    NaN\n\n    > y = base.dists.discreteUniform.quantile( 0.5, 2, 1 )\n    NaN\n\n\nbase.dists.discreteUniform.quantile.factory( a, b )\n    Returns a function for evaluating the quantile function of a discrete\n    uniform distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.discreteUniform.quantile.factory( 0, 4 );\n    > var y = myQuantile( 0.8 )\n    4\n\n","base.dists.discreteUniform.quantile.factory":"\nbase.dists.discreteUniform.quantile.factory( a, b )\n    Returns a function for evaluating the quantile function of a discrete\n    uniform distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.discreteUniform.quantile.factory( 0, 4 );\n    > var y = myQuantile( 0.8 )\n    4","base.dists.discreteUniform.skewness":"\nbase.dists.discreteUniform.skewness( a, b )\n    Returns the skewness of a discrete uniform distribution.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.discreteUniform.skewness( -2, 2 )\n    0.0\n    > v = base.dists.discreteUniform.skewness( 4, 12 )\n    0.0\n    > v = base.dists.discreteUniform.skewness( 2, 8 )\n    0.0\n\n","base.dists.discreteUniform.stdev":"\nbase.dists.discreteUniform.stdev( a, b )\n    Returns the standard deviation of a discrete uniform distribution.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.discreteUniform.stdev( 0, 1 )\n    ~0.5\n    > v = base.dists.discreteUniform.stdev( 4, 12 )\n    ~2.582\n    > v = base.dists.discreteUniform.stdev( 2, 8 )\n    2.0\n\n","base.dists.discreteUniform.variance":"\nbase.dists.discreteUniform.variance( a, b )\n    Returns the variance of a discrete uniform distribution.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.discreteUniform.variance( 0, 1 )\n    ~0.25\n    > v = base.dists.discreteUniform.variance( 4, 12 )\n    ~6.667\n    > v = base.dists.discreteUniform.variance( 2, 8 )\n    4.0\n\n","base.dists.erlang.cdf":"\nbase.dists.erlang.cdf( x, k, λ )\n    Evaluates the cumulative distribution function (CDF) for an Erlang\n    distribution with shape parameter `k` and rate parameter `λ` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.erlang.cdf( 2.0, 1, 1.0 )\n    ~0.865\n    > y = base.dists.erlang.cdf( 2.0, 3, 1.0 )\n    ~0.323\n    > y = base.dists.erlang.cdf( 2.0, 2.5, 1.0 )\n    NaN\n    > y = base.dists.erlang.cdf( -1.0, 2, 2.0 )\n    0.0\n    > y = base.dists.erlang.cdf( PINF, 4, 2.0 )\n    1.0\n    > y = base.dists.erlang.cdf( NINF, 4, 2.0 )\n    0.0\n    > y = base.dists.erlang.cdf( NaN, 0, 1.0 )\n    NaN\n    > y = base.dists.erlang.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.erlang.cdf( 0.0, 0, NaN )\n    NaN\n    > y = base.dists.erlang.cdf( 2.0, -1, 1.0 )\n    NaN\n    > y = base.dists.erlang.cdf( 2.0, 1, -1.0 )\n    NaN\n\n\nbase.dists.erlang.cdf.factory( k, λ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.erlang.cdf.factory( 2, 0.5 );\n    > var y = mycdf( 6.0 )\n    ~0.801\n    > y = mycdf( 2.0 )\n    ~0.264\n\n","base.dists.erlang.cdf.factory":"\nbase.dists.erlang.cdf.factory( k, λ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.erlang.cdf.factory( 2, 0.5 );\n    > var y = mycdf( 6.0 )\n    ~0.801\n    > y = mycdf( 2.0 )\n    ~0.264","base.dists.erlang.entropy":"\nbase.dists.erlang.entropy( k, λ )\n    Returns the differential entropy of an Erlang distribution (in nats).\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a positive integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: integer\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.erlang.entropy( 1, 1.0 )\n    ~1.0\n    > v = base.dists.erlang.entropy( 4, 12.0 )\n    ~-0.462\n    > v = base.dists.erlang.entropy( 8, 2.0 )\n    ~1.723\n\n","base.dists.erlang.Erlang":"\nbase.dists.erlang.Erlang( [k, λ] )\n    Returns an Erlang distribution object.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Shape parameter. Must be a positive integer. Default: `1.0`.\n\n    λ: number (optional)\n        Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    erlang: Object\n        Distribution instance.\n\n    erlang.k: number\n        Shape parameter. If set, the value must be a positive integer.\n\n    erlang.lambda: number\n        Rate parameter. If set, the value must be greater than `0`.\n\n    erlang.entropy: number\n        Read-only property which returns the differential entropy.\n\n    erlang.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    erlang.mean: number\n        Read-only property which returns the expected value.\n\n    erlang.mode: number\n        Read-only property which returns the mode.\n\n    erlang.skewness: number\n        Read-only property which returns the skewness.\n\n    erlang.stdev: number\n        Read-only property which returns the standard deviation.\n\n    erlang.variance: number\n        Read-only property which returns the variance.\n\n    erlang.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    erlang.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    erlang.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    erlang.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    erlang.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var erlang = base.dists.erlang.Erlang( 6, 5.0 );\n    > erlang.k\n    6\n    > erlang.lambda\n    5.0\n    > erlang.entropy\n    ~0.647\n    > erlang.kurtosis\n    1.0\n    > erlang.mean\n    1.2\n    > erlang.mode\n    1.0\n    > erlang.skewness\n    ~0.816\n    > erlang.stdev\n    ~0.49\n    > erlang.variance\n    0.24\n    > erlang.cdf( 3.0 )\n    ~0.997\n    > erlang.logpdf( 3.0 )\n    ~-4.638\n    > erlang.mgf( -0.5 )\n    ~0.564\n    > erlang.pdf( 3.0 )\n    ~0.01\n    > erlang.quantile( 0.8 )\n    ~1.581\n\n","base.dists.erlang.kurtosis":"\nbase.dists.erlang.kurtosis( k, λ )\n    Returns the excess kurtosis of an Erlang distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a positive integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: integer\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.erlang.kurtosis( 1, 1.0 )\n    6.0\n    > v = base.dists.erlang.kurtosis( 4, 12.0 )\n    1.5\n    > v = base.dists.erlang.kurtosis( 8, 2.0 )\n    0.75\n\n","base.dists.erlang.logpdf":"\nbase.dists.erlang.logpdf( x, k, λ )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for an Erlang distribution with shape parameter `k` and rate parameter `λ`\n    at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.erlang.logpdf( 0.1, 1, 1.0 )\n    ~-0.1\n    > y = base.dists.erlang.logpdf( 0.5, 2, 2.5 )\n    ~-0.111\n    > y = base.dists.erlang.logpdf( -1.0, 4, 2.0 )\n    -Infinity\n    > y = base.dists.erlang.logpdf( NaN, 1, 1.0 )\n    NaN\n    > y = base.dists.erlang.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.erlang.logpdf( 0.0, 1, NaN )\n    NaN\n    > y = base.dists.erlang.logpdf( 2.0, -2, 0.5 )\n    NaN\n    > y = base.dists.erlang.logpdf( 2.0, 0.5, 0.5 )\n    NaN\n    > y = base.dists.erlang.logpdf( 2.0, 0.0, 2.0 )\n    -Infinity\n    > y = base.dists.erlang.logpdf( 0.0, 0.0, 2.0 )\n    Infinity\n    > y = base.dists.erlang.logpdf( 2.0, 1, 0.0 )\n    NaN\n    > y = base.dists.erlang.logpdf( 2.0, 1, -1.0 )\n    NaN\n\n\nbase.dists.erlang.logpdf.factory( k, λ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of an Erlang distribution with shape parameter `k`\n    and rate parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var myLogPDF = base.dists.erlang.logpdf.factory( 6.0, 7.0 );\n    > y = myLogPDF( 7.0 )\n    ~-32.382\n\n\n","base.dists.erlang.logpdf.factory":"\nbase.dists.erlang.logpdf.factory( k, λ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of an Erlang distribution with shape parameter `k`\n    and rate parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var myLogPDF = base.dists.erlang.logpdf.factory( 6.0, 7.0 );\n    > y = myLogPDF( 7.0 )\n    ~-32.382","base.dists.erlang.mean":"\nbase.dists.erlang.mean( k, λ )\n    Returns the expected value of an Erlang distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a positive integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: integer\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.erlang.mean( 1, 1.0 )\n    1.0\n    > v = base.dists.erlang.mean( 4, 12.0 )\n    ~0.333\n    > v = base.dists.erlang.mean( 8, 2.0 )\n    4.0\n\n","base.dists.erlang.mgf":"\nbase.dists.erlang.mgf( t, k, λ )\n    Evaluates the moment-generating function (MGF) for an Erlang distribution\n    with shape parameter `k` and rate parameter `λ` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.erlang.mgf( 0.3, 1, 1.0 )\n    ~1.429\n    > y = base.dists.erlang.mgf( 2.0, 2, 3.0 )\n    ~9.0\n    > y = base.dists.erlang.mgf( -1.0, 2, 2.0 )\n    ~0.444\n\n    > y = base.dists.erlang.mgf( NaN, 1, 1.0 )\n    NaN\n    > y = base.dists.erlang.mgf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.erlang.mgf( 0.0, 1, NaN )\n    NaN\n\n    > y = base.dists.erlang.mgf( 0.2, -2, 0.5 )\n    NaN\n    > y = base.dists.erlang.mgf( 0.2, 0.5, 0.5 )\n    NaN\n\n    > y = base.dists.erlang.mgf( 0.2, 1, 0.0 )\n    NaN\n    > y = base.dists.erlang.mgf( 0.2, 1, -5.0 )\n    NaN\n\n\nbase.dists.erlang.mgf.factory( k, λ )\n    Returns a function for evaluating the moment-generating function (MGF) of an\n    Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.erlang.mgf.factory( 2, 0.5 );\n    > var y = myMGF( 0.2 )\n    ~2.778\n    > y = myMGF( -0.5 )\n    0.25\n\n","base.dists.erlang.mgf.factory":"\nbase.dists.erlang.mgf.factory( k, λ )\n    Returns a function for evaluating the moment-generating function (MGF) of an\n    Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.erlang.mgf.factory( 2, 0.5 );\n    > var y = myMGF( 0.2 )\n    ~2.778\n    > y = myMGF( -0.5 )\n    0.25","base.dists.erlang.mode":"\nbase.dists.erlang.mode( k, λ )\n    Returns the mode of an Erlang distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a positive integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: integer\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.erlang.mode( 1, 1.0 )\n    0.0\n    > v = base.dists.erlang.mode( 4, 12.0 )\n    0.25\n    > v = base.dists.erlang.mode( 8, 2.0 )\n    3.5\n\n","base.dists.erlang.pdf":"\nbase.dists.erlang.pdf( x, k, λ )\n    Evaluates the probability density function (PDF) for an Erlang distribution\n    with shape parameter `k` and rate parameter `λ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.erlang.pdf( 0.1, 1, 1.0 )\n    ~0.905\n    > y = base.dists.erlang.pdf( 0.5, 2, 2.5 )\n    ~0.895\n    > y = base.dists.erlang.pdf( -1.0, 4, 2.0 )\n    0.0\n    > y = base.dists.erlang.pdf( NaN, 1, 1.0 )\n    NaN\n    > y = base.dists.erlang.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.erlang.pdf( 0.0, 1, NaN )\n    NaN\n    > y = base.dists.erlang.pdf( 2.0, -2, 0.5 )\n    NaN\n    > y = base.dists.erlang.pdf( 2.0, 0.5, 0.5 )\n    NaN\n    > y = base.dists.erlang.pdf( 2.0, 0.0, 2.0 )\n    0.0\n    > y = base.dists.erlang.pdf( 0.0, 0.0, 2.0 )\n    Infinity\n    > y = base.dists.erlang.pdf( 2.0, 1, 0.0 )\n    NaN\n    > y = base.dists.erlang.pdf( 2.0, 1, -1.0 )\n    NaN\n\n\nbase.dists.erlang.pdf.factory( k, λ )\n    Returns a function for evaluating the probability density function (PDF)\n    of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.erlang.pdf.factory( 6.0, 7.0 );\n    > y = myPDF( 7.0 )\n    ~8.639e-15\n\n\n","base.dists.erlang.pdf.factory":"\nbase.dists.erlang.pdf.factory( k, λ )\n    Returns a function for evaluating the probability density function (PDF)\n    of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.erlang.pdf.factory( 6.0, 7.0 );\n    > y = myPDF( 7.0 )\n    ~8.639e-15","base.dists.erlang.quantile":"\nbase.dists.erlang.quantile( p, k, λ )\n    Evaluates the quantile function for an Erlang distribution with shape\n    parameter `k` and rate parameter `λ` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive number for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.erlang.quantile( 0.8, 2, 1.0 )\n    ~2.994\n    > y = base.dists.erlang.quantile( 0.5, 4, 2.0 )\n    ~1.836\n\n    > y = base.dists.erlang.quantile( 1.1, 1, 1.0 )\n    NaN\n    > y = base.dists.erlang.quantile( -0.2, 1, 1.0 )\n    NaN\n\n    > y = base.dists.erlang.quantile( NaN, 1, 1.0 )\n    NaN\n    > y = base.dists.erlang.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.erlang.quantile( 0.0, 1, NaN )\n    NaN\n\n    // Non-integer shape parameter:\n    > y = base.dists.erlang.quantile( 0.5, 0.5, 1.0 )\n    NaN\n    // Non-positive shape parameter:\n    > y = base.dists.erlang.quantile( 0.5, -1, 1.0 )\n    NaN\n    // Non-positive rate parameter:\n    > y = base.dists.erlang.quantile( 0.5, 1, -1.0 )\n    NaN\n\n\nbase.dists.erlang.quantile.factory( k, λ )\n    Returns a function for evaluating the quantile function of an Erlang\n    distribution with shape parameter `k` and rate parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.erlang.quantile.factory( 10, 2.0 );\n    > var y = myQuantile( 0.4 )\n    ~4.452\n\n","base.dists.erlang.quantile.factory":"\nbase.dists.erlang.quantile.factory( k, λ )\n    Returns a function for evaluating the quantile function of an Erlang\n    distribution with shape parameter `k` and rate parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.erlang.quantile.factory( 10, 2.0 );\n    > var y = myQuantile( 0.4 )\n    ~4.452","base.dists.erlang.skewness":"\nbase.dists.erlang.skewness( k, λ )\n    Returns the skewness of an Erlang distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a positive integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: integer\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.erlang.skewness( 1, 1.0 )\n    2.0\n    > v = base.dists.erlang.skewness( 4, 12.0 )\n    1.0\n    > v = base.dists.erlang.skewness( 8, 2.0 )\n    ~0.707\n\n","base.dists.erlang.stdev":"\nbase.dists.erlang.stdev( k, λ )\n    Returns the standard deviation of an Erlang distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a positive integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: integer\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.erlang.stdev( 1, 1.0 )\n    1.0\n    > v = base.dists.erlang.stdev( 4, 12.0 )\n    ~0.167\n    > v = base.dists.erlang.stdev( 8, 2.0 )\n    ~1.414\n\n","base.dists.erlang.variance":"\nbase.dists.erlang.variance( k, λ )\n    Returns the variance of an Erlang distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a positive integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: integer\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.erlang.variance( 1, 1.0 )\n    1.0\n    > v = base.dists.erlang.variance( 4, 12.0 )\n    ~0.028\n    > v = base.dists.erlang.variance( 8, 2.0 )\n    2.0\n\n","base.dists.exponential.cdf":"\nbase.dists.exponential.cdf( x, λ )\n    Evaluates the cumulative distribution function (CDF) for an exponential\n    distribution with rate parameter `λ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.exponential.cdf( 2.0, 0.1 )\n    ~0.181\n    > y = base.dists.exponential.cdf( 1.0, 2.0 )\n    ~0.865\n    > y = base.dists.exponential.cdf( -1.0, 4.0 )\n    0.0\n    > y = base.dists.exponential.cdf( NaN, 1.0 )\n    NaN\n    > y = base.dists.exponential.cdf( 0.0, NaN )\n    NaN\n\n    // Negative rate parameter:\n    > y = base.dists.exponential.cdf( 2.0, -1.0 )\n    NaN\n\nbase.dists.exponential.cdf.factory( λ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    for an exponential distribution with rate parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.exponential.cdf.factory( 0.5 );\n    > var y = myCDF( 3.0 )\n    ~0.777\n\n","base.dists.exponential.cdf.factory":"\nbase.dists.exponential.cdf.factory( λ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    for an exponential distribution with rate parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.exponential.cdf.factory( 0.5 );\n    > var y = myCDF( 3.0 )\n    ~0.777","base.dists.exponential.entropy":"\nbase.dists.exponential.entropy( λ )\n    Returns the differential entropy of an exponential distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.exponential.entropy( 11.0 )\n    ~-1.398\n    > v = base.dists.exponential.entropy( 4.5 )\n    ~-0.504\n\n","base.dists.exponential.Exponential":"\nbase.dists.exponential.Exponential( [λ] )\n    Returns an exponential distribution object.\n\n    Parameters\n    ----------\n    λ: number (optional)\n        Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    exponential: Object\n        Distribution instance.\n\n    exponential.lambda: number\n        Rate parameter. If set, the value must be greater than `0`.\n\n    exponential.entropy: number\n        Read-only property which returns the differential entropy.\n\n    exponential.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    exponential.mean: number\n        Read-only property which returns the expected value.\n\n    exponential.median: number\n        Read-only property which returns the median.\n\n    exponential.mode: number\n        Read-only property which returns the mode.\n\n    exponential.skewness: number\n        Read-only property which returns the skewness.\n\n    exponential.stdev: number\n        Read-only property which returns the standard deviation.\n\n    exponential.variance: number\n        Read-only property which returns the variance.\n\n    exponential.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    exponential.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    exponential.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    exponential.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    exponential.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    exponential.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var exponential = base.dists.exponential.Exponential( 6.0 );\n    > exponential.lambda\n    6.0\n    > exponential.entropy\n    ~-0.792\n    > exponential.kurtosis\n    6.0\n    > exponential.mean\n    ~0.167\n    > exponential.median\n    ~0.116\n    > exponential.mode\n    0.0\n    > exponential.skewness\n    2.0\n    > exponential.stdev\n    ~0.167\n    > exponential.variance\n    ~0.028\n    > exponential.cdf( 1.0 )\n    ~0.998\n    > exponential.logcdf( 1.0 )\n    ~-0.002\n    > exponential.logpdf( 1.5 )\n    ~-7.208\n    > exponential.mgf( -0.5 )\n    ~0.923\n    > exponential.pdf( 1.5 )\n    ~0.001\n    > exponential.quantile( 0.5 )\n    ~0.116\n\n","base.dists.exponential.kurtosis":"\nbase.dists.exponential.kurtosis( λ )\n    Returns the excess kurtosis of an exponential distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.exponential.kurtosis( 11.0 )\n    6.0\n    > v = base.dists.exponential.kurtosis( 4.5 )\n    6.0\n\n","base.dists.exponential.logcdf":"\nbase.dists.exponential.logcdf( x, λ )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for an exponential distribution with rate parameter `λ` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.exponential.logcdf( 2.0, 0.1 )\n    ~-1.708\n    > y = base.dists.exponential.logcdf( 1.0, 2.0 )\n    ~-0.145\n    > y = base.dists.exponential.logcdf( -1.0, 4.0 )\n    -Infinity\n    > y = base.dists.exponential.logcdf( NaN, 1.0 )\n    NaN\n    > y = base.dists.exponential.logcdf( 0.0, NaN )\n    NaN\n\n    // Negative rate parameter:\n    > y = base.dists.exponential.logcdf( 2.0, -1.0 )\n    NaN\n\nbase.dists.exponential.logcdf.factory( λ )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) for an exponential distribution with rate\n    parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogCDF = base.dists.exponential.logcdf.factory( 0.5 );\n    > var y = mylogCDF( 3.0 )\n    ~-0.252\n\n","base.dists.exponential.logcdf.factory":"\nbase.dists.exponential.logcdf.factory( λ )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) for an exponential distribution with rate\n    parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogCDF = base.dists.exponential.logcdf.factory( 0.5 );\n    > var y = mylogCDF( 3.0 )\n    ~-0.252","base.dists.exponential.logpdf":"\nbase.dists.exponential.logpdf( x, λ )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for an exponential distribution with rate parameter `λ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.exponential.logpdf( 0.3, 4.0 )\n    ~0.186\n    > y = base.dists.exponential.logpdf( 2.0, 0.7 )\n    ~-1.757\n    > y = base.dists.exponential.logpdf( -1.0, 0.5 )\n    -Infinity\n    > y = base.dists.exponential.logpdf( 0, NaN )\n    NaN\n    > y = base.dists.exponential.logpdf( NaN, 2.0 )\n    NaN\n\n    // Negative rate:\n    > y = base.dists.exponential.logpdf( 2.0, -1.0 )\n    NaN\n\nbase.dists.exponential.logpdf.factory( λ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) for an exponential distribution with rate parameter\n    `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.exponential.logpdf.factory( 0.5 );\n    > var y = mylogpdf( 3.0 )\n    ~-2.193\n\n","base.dists.exponential.logpdf.factory":"\nbase.dists.exponential.logpdf.factory( λ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) for an exponential distribution with rate parameter\n    `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.exponential.logpdf.factory( 0.5 );\n    > var y = mylogpdf( 3.0 )\n    ~-2.193","base.dists.exponential.mean":"\nbase.dists.exponential.mean( λ )\n    Returns the expected value of an exponential distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.exponential.mean( 11.0 )\n    ~0.091\n    > v = base.dists.exponential.mean( 4.5 )\n    ~0.222\n\n","base.dists.exponential.median":"\nbase.dists.exponential.median( λ )\n    Returns the median of an exponential distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.exponential.median( 11.0 )\n    ~0.063\n    > v = base.dists.exponential.median( 4.5 )\n    ~0.154\n\n","base.dists.exponential.mgf":"\nbase.dists.exponential.mgf( t, λ )\n    Evaluates the moment-generating function (MGF) for an exponential\n    distribution with rate parameter `λ` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var v = base.dists.exponential.mgf( 2.0, 3.0 )\n    3.0\n    > v = base.dists.exponential.mgf( 0.4, 1.2 )\n    1.5\n    > v = base.dists.exponential.mgf( 0.8, 1.6 )\n    2.0\n    > v = base.dists.exponential.mgf( 4.0, 3.0 )\n    NaN\n    > v = base.dists.exponential.mgf( NaN, 3.0 )\n    NaN\n    > v = base.dists.exponential.mgf( 2.0, NaN )\n    NaN\n\n\nbase.dists.exponential.mgf.factory( λ )\n    Returns a function for evaluating the moment-generating function (MGF) for\n    an exponential distribution with rate parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    mg: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.exponential.mgf.factory( 4.0 );\n    > var y = myMGF( 3.0 )\n    4.0\n    > y = myMGF( 0.5 )\n    ~1.143\n\n","base.dists.exponential.mgf.factory":"\nbase.dists.exponential.mgf.factory( λ )\n    Returns a function for evaluating the moment-generating function (MGF) for\n    an exponential distribution with rate parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    mg: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.exponential.mgf.factory( 4.0 );\n    > var y = myMGF( 3.0 )\n    4.0\n    > y = myMGF( 0.5 )\n    ~1.143","base.dists.exponential.mode":"\nbase.dists.exponential.mode( λ )\n    Returns the mode of an exponential distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.exponential.mode( 11.0 )\n    0.0\n    > v = base.dists.exponential.mode( 4.5 )\n    0.0\n\n","base.dists.exponential.pdf":"\nbase.dists.exponential.pdf( x, λ )\n    Evaluates the probability density function (PDF) for an exponential\n    distribution with rate parameter `λ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.exponential.pdf( 0.3, 4.0 )\n    ~1.205\n    > y = base.dists.exponential.pdf( 2.0, 0.7 )\n    ~0.173\n    > y = base.dists.exponential.pdf( -1.0, 0.5 )\n    0.0\n    > y = base.dists.exponential.pdf( 0, NaN )\n    NaN\n    > y = base.dists.exponential.pdf( NaN, 2.0 )\n    NaN\n\n    // Negative rate:\n    > y = base.dists.exponential.pdf( 2.0, -1.0 )\n    NaN\n\nbase.dists.exponential.pdf.factory( λ )\n    Returns a function for evaluating the probability density function (PDF)\n    for an exponential distribution with rate parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.exponential.pdf.factory( 0.5 );\n    > var y = myPDF( 3.0 )\n    ~0.112\n\n","base.dists.exponential.pdf.factory":"\nbase.dists.exponential.pdf.factory( λ )\n    Returns a function for evaluating the probability density function (PDF)\n    for an exponential distribution with rate parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.exponential.pdf.factory( 0.5 );\n    > var y = myPDF( 3.0 )\n    ~0.112","base.dists.exponential.quantile":"\nbase.dists.exponential.quantile( p, λ )\n    Evaluates the quantile function for an exponential distribution with rate\n    parameter `λ` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.exponential.quantile( 0.8, 1.0 )\n    ~1.609\n    > y = base.dists.exponential.quantile( 0.5, 4.0 )\n    ~0.173\n    > y = base.dists.exponential.quantile( 0.5, 0.1 )\n    ~6.931\n\n    > y = base.dists.exponential.quantile( -0.2, 0.1 )\n    NaN\n\n    > y = base.dists.exponential.quantile( NaN, 1.0 )\n    NaN\n    > y = base.dists.exponential.quantile( 0.0, NaN )\n    NaN\n\n    // Negative rate parameter:\n    > y = base.dists.exponential.quantile( 0.5, -1.0 )\n    NaN\n\n\nbase.dists.exponential.quantile.factory( λ )\n    Returns a function for evaluating the quantile function for an exponential\n    distribution with rate parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.exponential.quantile.factory( 0.4 );\n    > var y = myQuantile( 0.4 )\n    ~1.277\n    > y = myQuantile( 1.0 )\n    Infinity\n\n","base.dists.exponential.quantile.factory":"\nbase.dists.exponential.quantile.factory( λ )\n    Returns a function for evaluating the quantile function for an exponential\n    distribution with rate parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.exponential.quantile.factory( 0.4 );\n    > var y = myQuantile( 0.4 )\n    ~1.277\n    > y = myQuantile( 1.0 )\n    Infinity","base.dists.exponential.skewness":"\nbase.dists.exponential.skewness( λ )\n    Returns the skewness of an exponential distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.exponential.skewness( 11.0 )\n    2.0\n    > v = base.dists.exponential.skewness( 4.5 )\n    2.0\n\n","base.dists.exponential.stdev":"\nbase.dists.exponential.stdev( λ )\n    Returns the standard deviation of an exponential distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.exponential.stdev( 9.0 )\n    ~0.11\n    > v = base.dists.exponential.stdev( 1.0 )\n    1.0\n\n","base.dists.exponential.variance":"\nbase.dists.exponential.variance( λ )\n    Returns the variance of an exponential distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.exponential.variance( 9.0 )\n    ~0.012\n    > v = base.dists.exponential.variance( 1.0 )\n    1.0\n\n","base.dists.f.cdf":"\nbase.dists.f.cdf( x, d1, d2 )\n    Evaluates the cumulative distribution function (CDF) for an F distribution\n    with numerator degrees of freedom `d1` and denominator degrees of freedom\n    `d2` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.f.cdf( 2.0, 1.0, 1.0 )\n    ~0.608\n    > var y = base.dists.f.cdf( 2.0, 8.0, 4.0 )\n    ~0.737\n    > var y = base.dists.f.cdf( -1.0, 2.0, 2.0 )\n    0.0\n    > var y = base.dists.f.cdf( PINF, 4.0, 2.0 )\n    1.0\n    > var y = base.dists.f.cdf( NINF, 4.0, 2.0 )\n    0.0\n\n    > var y = base.dists.f.cdf( NaN, 1.0, 1.0 )\n    NaN\n    > var y = base.dists.f.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > var y = base.dists.f.cdf( 0.0, 1.0, NaN )\n    NaN\n\n    > var y = base.dists.f.cdf( 2.0, 1.0, -1.0 )\n    NaN\n    > var y = base.dists.f.cdf( 2.0, -1.0, 1.0 )\n    NaN\n\n\nbase.dists.f.cdf.factory( d1, d2 )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an F distribution with numerator degrees of freedom `d1` and denominator\n    degrees of freedom `d2`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.f.cdf.factory( 10.0, 2.0 );\n    > var y = myCDF( 10.0 )\n    ~0.906\n    > y = myCDF( 8.0 )\n    ~0.884\n\n","base.dists.f.cdf.factory":"\nbase.dists.f.cdf.factory( d1, d2 )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an F distribution with numerator degrees of freedom `d1` and denominator\n    degrees of freedom `d2`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.f.cdf.factory( 10.0, 2.0 );\n    > var y = myCDF( 10.0 )\n    ~0.906\n    > y = myCDF( 8.0 )\n    ~0.884","base.dists.f.entropy":"\nbase.dists.f.entropy( d1, d2 )\n    Returns the differential entropy of an F distribution (in nats).\n\n    If `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n    If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.f.entropy( 3.0, 7.0 )\n    ~1.298\n    > v = base.dists.f.entropy( 4.0, 12.0 )\n    ~1.12\n    > v = base.dists.f.entropy( 8.0, 2.0 )\n    ~2.144\n\n","base.dists.f.F":"\nbase.dists.f.F( [d1, d2] )\n    Returns an F distribution object.\n\n    Parameters\n    ----------\n    d1: number (optional)\n        Numerator degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n    d2: number (optional)\n        Denominator degrees of freedom. Must be greater than `0`.\n        Default: `1.0`.\n\n    Returns\n    -------\n    f: Object\n        Distribution instance.\n\n    f.d1: number\n        Numerator degrees of freedom. If set, the value must be greater than\n        `0`.\n\n    f.d2: number\n        Denominator degrees of freedom. If set, the value must be greater than\n        `0`.\n\n    f.entropy: number\n        Read-only property which returns the differential entropy.\n\n    f.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    f.mean: number\n        Read-only property which returns the expected value.\n\n    f.mode: number\n        Read-only property which returns the mode.\n\n    f.skewness: number\n        Read-only property which returns the skewness.\n\n    f.stdev: number\n        Read-only property which returns the standard deviation.\n\n    f.variance: number\n        Read-only property which returns the variance.\n\n    f.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    f.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    f.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var f = base.dists.f.F( 6.0, 9.0 );\n    > f.d1\n    6.0\n    > f.d2\n    9.0\n    > f.entropy\n    ~1.134\n    > f.kurtosis\n    ~104.564\n    > f.mean\n    ~1.286\n    > f.mode\n    ~0.545\n    > f.skewness\n    ~4.535\n    > f.stdev\n    ~1.197\n    > f.variance\n    ~1.433\n    > f.cdf( 3.0 )\n    ~0.932\n    > f.pdf( 2.5 )\n    ~0.095\n    > f.quantile( 0.8 )\n    ~1.826\n\n","base.dists.f.kurtosis":"\nbase.dists.f.kurtosis( d1, d2 )\n    Returns the excess kurtosis of an F distribution.\n\n    If `d1 <= 0` or `d2 <= 8`, the function returns `NaN`.\n\n    If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.f.kurtosis( 3.0, 9.0 )\n    ~124.667\n    > v = base.dists.f.kurtosis( 4.0, 12.0 )\n    ~26.143\n    > v = base.dists.f.kurtosis( 8.0, 9.0 )\n    ~100.167\n\n","base.dists.f.mean":"\nbase.dists.f.mean( d1, d2 )\n    Returns the expected value of an F distribution.\n\n    If `d1 <= 0` or `d2 <= 2`, the function returns `NaN`.\n\n    If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.f.mean( 3.0, 5.0 )\n    ~1.667\n    > v = base.dists.f.mean( 4.0, 12.0 )\n    ~1.2\n    > v = base.dists.f.mean( 8.0, 4.0 )\n    2.0\n\n","base.dists.f.mode":"\nbase.dists.f.mode( d1, d2 )\n    Returns the mode of an F distribution.\n\n    If `d1 <= 2` or `d2 <= 0`, the function returns `NaN`.\n\n    If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.f.mode( 3.0, 5.0 )\n    ~0.238\n    > v = base.dists.f.mode( 4.0, 12.0 )\n    ~0.429\n    > v = base.dists.f.mode( 8.0, 4.0 )\n    0.5\n\n","base.dists.f.pdf":"\nbase.dists.f.pdf( x, d1, d2 )\n    Evaluates the probability density function (PDF) for an F distribution with\n    numerator degrees of freedom `d1` and denominator degrees of freedom `d2` at\n    a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.f.pdf( 2.0, 0.5, 1.0 )\n    ~0.057\n    > y = base.dists.f.pdf( 0.1, 1.0, 1.0 )\n    ~0.915\n    > y = base.dists.f.pdf( -1.0, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.f.pdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.f.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.f.pdf( 0.0, 1.0, NaN )\n    NaN\n\n    > y = base.dists.f.pdf( 2.0, 1.0, -1.0 )\n    NaN\n    > y = base.dists.f.pdf( 2.0, -1.0, 1.0 )\n    NaN\n\n\nbase.dists.f.pdf.factory( d1, d2 )\n    Returns a function for evaluating the probability density function (PDF) of\n    an F distribution with numerator degrees of freedom `d1` and denominator\n    degrees of freedom `d2`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.f.pdf.factory( 6.0, 7.0 );\n    > var y = myPDF( 7.0 )\n    ~0.004\n    > y = myPDF( 2.0 )\n    ~0.166\n\n","base.dists.f.pdf.factory":"\nbase.dists.f.pdf.factory( d1, d2 )\n    Returns a function for evaluating the probability density function (PDF) of\n    an F distribution with numerator degrees of freedom `d1` and denominator\n    degrees of freedom `d2`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.f.pdf.factory( 6.0, 7.0 );\n    > var y = myPDF( 7.0 )\n    ~0.004\n    > y = myPDF( 2.0 )\n    ~0.166","base.dists.f.quantile":"\nbase.dists.f.quantile( p, d1, d2 )\n    Evaluates the quantile function for an F distribution with numerator degrees\n    of freedom `d1` and denominator degrees of freedom `d2` at a probability\n    `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.f.quantile( 0.8, 1.0, 1.0 )\n    ~9.472\n    > y = base.dists.f.quantile( 0.5, 4.0, 2.0 )\n    ~1.207\n\n    > y = base.dists.f.quantile( 1.1, 1.0, 1.0 )\n    NaN\n    > y = base.dists.f.quantile( -0.2, 1.0, 1.0 )\n    NaN\n\n    > y = base.dists.f.quantile( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.f.quantile( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.dists.f.quantile( 0.5, 1.0, NaN )\n    NaN\n\n    > y = base.dists.f.quantile( 0.5, -1.0, 1.0 )\n    NaN\n    > y = base.dists.f.quantile( 0.5, 1.0, -1.0 )\n    NaN\n\n\nbase.dists.f.quantile.factory( d1, d2 )\n    Returns a function for evaluating the quantile function of an F distribution\n    with numerator degrees of freedom `d1` and denominator degrees of freedom\n    `d2`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.f.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.2 )\n    ~0.527\n    > y = myQuantile( 0.8 )\n    ~4.382\n\n","base.dists.f.quantile.factory":"\nbase.dists.f.quantile.factory( d1, d2 )\n    Returns a function for evaluating the quantile function of an F distribution\n    with numerator degrees of freedom `d1` and denominator degrees of freedom\n    `d2`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.f.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.2 )\n    ~0.527\n    > y = myQuantile( 0.8 )\n    ~4.382","base.dists.f.skewness":"\nbase.dists.f.skewness( d1, d2 )\n    Returns the skewness of an F distribution.\n\n    If `d1 <= 0` or `d2 <= 6`, the function returns `NaN`.\n\n    If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.f.skewness( 3.0, 7.0 )\n    11.0\n    > v = base.dists.f.skewness( 4.0, 12.0 )\n    ~3.207\n    > v = base.dists.f.skewness( 8.0, 7.0 )\n    ~10.088\n\n","base.dists.f.stdev":"\nbase.dists.f.stdev( d1, d2 )\n    Returns the standard deviation of an F distribution.\n\n    If `d1 <= 0` or `d2 <= 4`, the function returns `NaN`.\n\n    If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.f.stdev( 3.0, 5.0 )\n    ~3.333\n    > v = base.dists.f.stdev( 4.0, 12.0 )\n    ~1.122\n    > v = base.dists.f.stdev( 8.0, 5.0 )\n    ~2.764\n\n","base.dists.f.variance":"\nbase.dists.f.variance( d1, d2 )\n    Returns the variance of an F distribution.\n\n    If `d1 <= 0` or `d2 <= 4`, the function returns `NaN`.\n\n    If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.f.variance( 3.0, 5.0 )\n    ~11.111\n    > v = base.dists.f.variance( 4.0, 12.0 )\n    ~1.26\n    > v = base.dists.f.variance( 8.0, 5.0 )\n    ~7.639\n\n","base.dists.frechet.cdf":"\nbase.dists.frechet.cdf( x, α, s, m )\n    Evaluates the cumulative distribution function (CDF) for a Fréchet\n    distribution with shape parameter `α`, scale parameter `s`, and location\n    `m`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.cdf( 10.0, 2.0, 3.0, 0.0 )\n    ~0.914\n    > y = base.dists.frechet.cdf( -1.0, 2.0, 3.0, -3.0 )\n    ~0.105\n    > y = base.dists.frechet.cdf( 2.5, 2.0, 1.0, 2.0 )\n    ~0.018\n    > y = base.dists.frechet.cdf( NaN, 1.0, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.cdf( 0.0, NaN, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.cdf( 0.0, 1.0, NaN, 0.0 )\n    NaN\n    > y = base.dists.frechet.cdf( 0.0, 1.0, 1.0, NaN )\n    NaN\n    > y = base.dists.frechet.cdf( 0.0, -1.0, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.cdf( 0.0, 1.0, -1.0, 0.0 )\n    NaN\n\n\nbase.dists.frechet.cdf.factory( α, s, m )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n    location `m`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.frechet.cdf.factory( 3.0, 3.0, 5.0 );\n    > var y = myCDF( 10.0 )\n    ~0.806\n    > y = myCDF( 7.0 )\n    ~0.034\n\n","base.dists.frechet.cdf.factory":"\nbase.dists.frechet.cdf.factory( α, s, m )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n    location `m`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.frechet.cdf.factory( 3.0, 3.0, 5.0 );\n    > var y = myCDF( 10.0 )\n    ~0.806\n    > y = myCDF( 7.0 )\n    ~0.034","base.dists.frechet.entropy":"\nbase.dists.frechet.entropy( α, s, m )\n    Returns the differential entropy of a Fréchet distribution with shape\n    parameter `α`, scale parameter `s`, and location `m` (in nats).\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.entropy( 1.0, 1.0, 1.0 )\n    ~2.154\n    > y = base.dists.frechet.entropy( 4.0, 2.0, 1.0 )\n    ~1.028\n    > y = base.dists.frechet.entropy( NaN, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.entropy( 1.0, NaN, 0.0 )\n    NaN\n    > y = base.dists.frechet.entropy( 1.0, 1.0, NaN )\n    NaN\n\n","base.dists.frechet.Frechet":"\nbase.dists.frechet.Frechet( [α, s, m] )\n    Returns a Fréchet distribution object.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n    s: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    m: number (optional)\n        Location parameter. Default: `0.0`.\n\n    Returns\n    -------\n    frechet: Object\n        Distribution instance.\n\n    frechet.alpha: number\n        Shape parameter. If set, the value must be greater than `0`.\n\n    frechet.s: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    frechet.m: number\n        Location parameter.\n\n    frechet.entropy: number\n        Read-only property which returns the differential entropy.\n\n    frechet.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    frechet.mean: number\n        Read-only property which returns the expected value.\n\n    frechet.median: number\n        Read-only property which returns the median.\n\n    frechet.mode: number\n        Read-only property which returns the mode.\n\n    frechet.skewness: number\n        Read-only property which returns the skewness.\n\n    frechet.stdev: number\n        Read-only property which returns the standard deviation.\n\n    frechet.variance: number\n        Read-only property which returns the variance.\n\n    frechet.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    frechet.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    frechet.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    frechet.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    frechet.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var frechet = base.dists.frechet.Frechet( 1.0, 1.0, 0.0 );\n    > frechet.alpha\n    1.0\n    > frechet.s\n    1.0\n    > frechet.m\n    0.0\n    > frechet.entropy\n    ~2.154\n    > frechet.kurtosis\n    Infinity\n    > frechet.mean\n    Infinity\n    > frechet.median\n    ~1.443\n    > frechet.mode\n    0.5\n    > frechet.skewness\n    Infinity\n    > frechet.stdev\n    Infinity\n    > frechet.variance\n    Infinity\n    > frechet.cdf( 0.8 )\n    ~0.287\n    > frechet.logcdf( 0.8 )\n    -1.25\n    > frechet.logpdf( 0.8 )\n    ~-0.804\n    > frechet.pdf( 0.8 )\n    ~0.448\n    > frechet.quantile( 0.8 )\n    ~4.481\n\n","base.dists.frechet.kurtosis":"\nbase.dists.frechet.kurtosis( α, s, m )\n    Returns the excess kurtosis of a Fréchet distribution with shape parameter\n    `α`, scale parameter `s`, and location `m`.\n\n    If provided `0 < α <= 4` and `s > 0`, the function returns positive\n    infinity.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.kurtosis( 5.0, 2.0, 1.0 )\n    ~45.092\n    > var y = base.dists.frechet.kurtosis( 5.0, 10.0, -3.0 )\n    ~45.092\n    > y = base.dists.frechet.kurtosis( 3.5, 2.0, 1.0 )\n    Infinity\n    > y = base.dists.frechet.kurtosis( NaN, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.kurtosis( 1.0, NaN, 0.0 )\n    NaN\n    > y = base.dists.frechet.kurtosis( 1.0, 1.0, NaN )\n    NaN\n\n","base.dists.frechet.logcdf":"\nbase.dists.frechet.logcdf( x, α, s, m )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a Fréchet distribution with shape parameter `α`, scale parameter\n    `s`, and location `m`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.logcdf( 10.0, 2.0, 3.0, 0.0 )\n    ~-0.09\n    > y = base.dists.frechet.logcdf( -1.0, 2.0, 3.0, -3.0 )\n    ~-2.25\n    > y = base.dists.frechet.logcdf( 2.5, 2.0, 1.0, 2.0 )\n    -4.0\n    > y = base.dists.frechet.logcdf( NaN, 1.0, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.logcdf( 0.0, NaN, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.logcdf( 0.0, 1.0, NaN, 0.0 )\n    NaN\n    > y = base.dists.frechet.logcdf( 0.0, 1.0, 1.0, NaN )\n    NaN\n    > y = base.dists.frechet.logcdf( 0.0, -1.0, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.logcdf( 0.0, 1.0, -1.0, 0.0 )\n    NaN\n\n\nbase.dists.frechet.logcdf.factory( α, s, m )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Fréchet distribution with shape parameter\n    `α`, scale parameter `s`, and location `m`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.frechet.logcdf.factory( 3.0, 3.0, 5.0 );\n    > var y = mylogcdf( 10.0 )\n    ~-0.216\n    > y = mylogcdf( 7.0 )\n    ~-3.375\n\n","base.dists.frechet.logcdf.factory":"\nbase.dists.frechet.logcdf.factory( α, s, m )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Fréchet distribution with shape parameter\n    `α`, scale parameter `s`, and location `m`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.frechet.logcdf.factory( 3.0, 3.0, 5.0 );\n    > var y = mylogcdf( 10.0 )\n    ~-0.216\n    > y = mylogcdf( 7.0 )\n    ~-3.375","base.dists.frechet.logpdf":"\nbase.dists.frechet.logpdf( x, α, s, m )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n    location `m`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.logpdf( 10.0, 1.0, 3.0, 5.0 )\n    ~-2.72\n    > y = base.dists.frechet.logpdf( -2.0, 1.0, 3.0, -3.0 )\n    ~-1.901\n    > y = base.dists.frechet.logpdf( 0.0, 2.0, 1.0, -1.0 )\n    ~-0.307\n    > y = base.dists.frechet.logpdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.frechet.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.frechet.logpdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.frechet.logpdf( 0.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.frechet.logpdf.factory( α, s, m )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Fréchet distribution with shape parameter `α`, scale\n    parameter `s`, and location `m`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.frechet.logpdf.factory( 2.0, 3.0, 1.0 );\n    > var y = mylogPDF( 10.0 )\n    ~-3.812\n    > y = mylogPDF( 2.0 )\n    ~-6.11\n\n","base.dists.frechet.logpdf.factory":"\nbase.dists.frechet.logpdf.factory( α, s, m )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Fréchet distribution with shape parameter `α`, scale\n    parameter `s`, and location `m`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.frechet.logpdf.factory( 2.0, 3.0, 1.0 );\n    > var y = mylogPDF( 10.0 )\n    ~-3.812\n    > y = mylogPDF( 2.0 )\n    ~-6.11","base.dists.frechet.mean":"\nbase.dists.frechet.mean( α, s, m )\n    Returns the expected value of a Fréchet distribution with shape parameter\n    `α`, scale parameter `s`, and location `m`.\n\n    If provided `0 < α <= 1` and `s > 0`, the function returns positive\n    infinity.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Mean.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.mean( 4.0, 2.0, 1.0 )\n    ~3.451\n    > y = base.dists.frechet.mean( 0.5, 2.0, 1.0 )\n    Infinity\n    > y = base.dists.frechet.mean( NaN, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.mean( 1.0, NaN, 0.0 )\n    NaN\n    > y = base.dists.frechet.mean( 1.0, 1.0, NaN )\n    NaN\n\n","base.dists.frechet.median":"\nbase.dists.frechet.median( α, s, m )\n    Returns the median of a Fréchet distribution with shape parameter\n    `α`, scale parameter `s`, and location `m`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.median( 4.0, 2.0, 1.0 )\n    ~3.192\n    > var y = base.dists.frechet.median( 4.0, 2.0, -3.0 )\n    ~-0.808\n    > y = base.dists.frechet.median( 0.5, 2.0, 1.0 )\n    ~5.163\n    > y = base.dists.frechet.median( NaN, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.median( 1.0, NaN, 0.0 )\n    NaN\n    > y = base.dists.frechet.median( 1.0, 1.0, NaN )\n    NaN\n\n","base.dists.frechet.mode":"\nbase.dists.frechet.mode( α, s, m )\n    Returns the mode of a Fréchet distribution with shape parameter `α`, scale\n    parameter `s`, and location `m`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.mode( 4.0, 2.0, 1.0 )\n    ~2.891\n    > var y = base.dists.frechet.mode( 4.0, 2.0, -3.0 )\n    ~-1.109\n    > y = base.dists.frechet.mode( 0.5, 2.0, 1.0 )\n    ~1.222\n    > y = base.dists.frechet.mode( NaN, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.mode( 1.0, NaN, 0.0 )\n    NaN\n    > y = base.dists.frechet.mode( 1.0, 1.0, NaN )\n    NaN\n\n","base.dists.frechet.pdf":"\nbase.dists.frechet.pdf( x, α, s, m )\n    Evaluates the probability density function (PDF) for a Fréchet distribution\n    with shape parameter `α`, scale parameter `s`, and location `m`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.pdf( 10.0, 0.0, 3.0 )\n    ~0.965\n    > y = base.dists.frechet.pdf( -2.0, 0.0, 3.0 )\n    ~0.143\n    > y = base.dists.frechet.pdf( 0.0, 0.0, 1.0 )\n    ~0.368\n    > y = base.dists.frechet.pdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.frechet.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.frechet.pdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.frechet.pdf( 0.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.frechet.pdf.factory( α, s, m )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n    location `m`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.frechet.pdf.factory( 2.0, 3.0 );\n    > var y = myPDF( 10.0 )\n    ~0.933\n    > y = myPDF( 2.0 )\n    ~0.368\n\n","base.dists.frechet.pdf.factory":"\nbase.dists.frechet.pdf.factory( α, s, m )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n    location `m`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.frechet.pdf.factory( 2.0, 3.0 );\n    > var y = myPDF( 10.0 )\n    ~0.933\n    > y = myPDF( 2.0 )\n    ~0.368","base.dists.frechet.quantile":"\nbase.dists.frechet.quantile( p, α, s, m )\n    Evaluates the quantile function for a Fréchet distribution with shape\n    parameter `α`, scale parameter `s`, and location `m`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.quantile( 0.3, 10.0, 2.0, 3.0 )\n    ~4.963\n    > y = base.dists.frechet.quantile( 0.2, 3.0, 3.0, 3.0 )\n    ~5.56\n    > y = base.dists.frechet.quantile( 0.9, 1.0, 1.0, -3.0 )\n    ~6.491\n    > y = base.dists.frechet.quantile( NaN, 1.0, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.quantile( 0.0, NaN, 1.0, 0.0)\n    NaN\n    > y = base.dists.frechet.quantile( 0.0, 1.0, NaN, 0.0 )\n    NaN\n    > y = base.dists.frechet.quantile( 0.0, 1.0, 1.0, NaN )\n    NaN\n    > y = base.dists.frechet.quantile( 0.0, -1.0, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.quantile( 0.0, 1.0, -1.0, 0.0 )\n    NaN\n\n\nbase.dists.frechet.quantile.factory( α, s, m )\n    Returns a function for evaluating the quantile function of a Fréchet\n    distribution with shape parameter `α`, scale parameter `s`, and location\n    `m`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.frechet.quantile.factory( 2.0, 2.0, 3.0 );\n    > var y = myQuantile( 0.5 )\n    ~5.402\n    > y = myQuantile( 0.2 )\n    ~4.576\n\n","base.dists.frechet.quantile.factory":"\nbase.dists.frechet.quantile.factory( α, s, m )\n    Returns a function for evaluating the quantile function of a Fréchet\n    distribution with shape parameter `α`, scale parameter `s`, and location\n    `m`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.frechet.quantile.factory( 2.0, 2.0, 3.0 );\n    > var y = myQuantile( 0.5 )\n    ~5.402\n    > y = myQuantile( 0.2 )\n    ~4.576","base.dists.frechet.skewness":"\nbase.dists.frechet.skewness( α, s, m )\n    Returns the skewness of a Fréchet distribution with shape parameter `α`,\n    scale parameter `s`, and location `m`.\n\n    If provided `0 < α <= 3` and `s > 0`, the function returns positive\n    infinity.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.skewness( 4.0, 2.0, 1.0 )\n    ~5.605\n    > var y = base.dists.frechet.skewness( 4.0, 2.0, -3.0 )\n    ~5.605\n    > y = base.dists.frechet.skewness( 0.5, 2.0, 1.0 )\n    Infinity\n    > y = base.dists.frechet.skewness( NaN, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.skewness( 1.0, NaN, 0.0 )\n    NaN\n    > y = base.dists.frechet.skewness( 1.0, 1.0, NaN )\n    NaN\n\n","base.dists.frechet.stdev":"\nbase.dists.frechet.stdev( α, s, m )\n    Returns the standard deviation of a Fréchet distribution with shape\n    parameter `α`, scale parameter `s`, and location `m`.\n\n    If provided `0 < α <= 2` and `s > 0`, the function returns positive\n    infinity.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.stdev( 4.0, 2.0, 1.0 )\n    ~1.041\n    > var y = base.dists.frechet.stdev( 4.0, 2.0, -3.0 )\n    ~1.041\n    > y = base.dists.frechet.stdev( 0.5, 2.0, 1.0 )\n    Infinity\n    > y = base.dists.frechet.stdev( NaN, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.stdev( 1.0, NaN, 0.0 )\n    NaN\n    > y = base.dists.frechet.stdev( 1.0, 1.0, NaN )\n    NaN\n\n","base.dists.frechet.variance":"\nbase.dists.frechet.variance( α, s, m )\n    Returns the variance of a Fréchet distribution with shape parameter `α`,\n    scale parameter `s`, and location `m`.\n\n    If provided `0 < α <= 2` and `s > 0`, the function returns positive\n    infinity.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.variance( 4.0, 2.0, 1.0 )\n    ~1.083\n    > var y = base.dists.frechet.variance( 4.0, 2.0, -3.0 )\n    ~1.083\n    > y = base.dists.frechet.variance( 0.5, 2.0, 1.0 )\n    Infinity\n    > y = base.dists.frechet.variance( NaN, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.variance( 1.0, NaN, 0.0 )\n    NaN\n    > y = base.dists.frechet.variance( 1.0, 1.0, NaN )\n    NaN\n\n","base.dists.gamma.cdf":"\nbase.dists.gamma.cdf( x, α, β )\n    Evaluates the cumulative distribution function (CDF) for a gamma\n    distribution with shape parameter `α` and rate parameter `β` at a value `x`.\n\n    If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.gamma.cdf( 2.0, 1.0, 1.0 )\n    ~0.865\n    > y = base.dists.gamma.cdf( 2.0, 3.0, 1.0 )\n    ~0.323\n    > y = base.dists.gamma.cdf( -1.0, 2.0, 2.0 )\n    0.0\n    > y = base.dists.gamma.cdf( PINF, 4.0, 2.0 )\n    1.0\n    > y = base.dists.gamma.cdf( NINF, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.gamma.cdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.gamma.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gamma.cdf( 0.0, 0.0, NaN )\n    NaN\n\n    > y = base.dists.gamma.cdf( 2.0, -1.0, 1.0 )\n    NaN\n    > y = base.dists.gamma.cdf( 2.0, 1.0, -1.0 )\n    NaN\n\n    // Degenerate distribution centered at `0` when `α = 0.0`:\n    > y = base.dists.gamma.cdf( 2.0, 0.0, 2.0 )\n    1.0\n    > y = base.dists.gamma.cdf( -2.0, 0.0, 2.0 )\n    0.0\n    > y = base.dists.gamma.cdf( 0.0, 0.0, 2.0 )\n    0.0\n\n\nbase.dists.gamma.cdf.factory( α, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.gamma.cdf.factory( 2.0, 0.5 );\n    > var y = myCDF( 6.0 )\n    ~0.801\n    > y = myCDF( 2.0 )\n    ~0.264\n\n","base.dists.gamma.cdf.factory":"\nbase.dists.gamma.cdf.factory( α, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.gamma.cdf.factory( 2.0, 0.5 );\n    > var y = myCDF( 6.0 )\n    ~0.801\n    > y = myCDF( 2.0 )\n    ~0.264","base.dists.gamma.entropy":"\nbase.dists.gamma.entropy( α, β )\n    Returns the differential entropy of a gamma distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.gamma.entropy( 1.0, 1.0 )\n    1.0\n    > v = base.dists.gamma.entropy( 4.0, 12.0 )\n    ~-0.462\n    > v = base.dists.gamma.entropy( 8.0, 2.0 )\n    ~1.723\n\n","base.dists.gamma.Gamma":"\nbase.dists.gamma.Gamma( [α, β] )\n    Returns a gamma distribution object.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n    β: number (optional)\n        Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    gamma: Object\n        Distribution instance.\n\n    gamma.alpha: number\n        Shape parameter. If set, the value must be greater than `0`.\n\n    gamma.beta: number\n        Rate parameter. If set, the value must be greater than `0`.\n\n    gamma.entropy: number\n        Read-only property which returns the differential entropy.\n\n    gamma.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    gamma.mean: number\n        Read-only property which returns the expected value.\n\n    gamma.mode: number\n        Read-only property which returns the mode.\n\n    gamma.skewness: number\n        Read-only property which returns the skewness.\n\n    gamma.stdev: number\n        Read-only property which returns the standard deviation.\n\n    gamma.variance: number\n        Read-only property which returns the variance.\n\n    gamma.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    gamma.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    gamma.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    gamma.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    gamma.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    gamma.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var gamma = base.dists.gamma.Gamma( 6.0, 5.0 );\n    > gamma.alpha\n    6.0\n    > gamma.beta\n    5.0\n    > gamma.entropy\n    ~0.647\n    > gamma.kurtosis\n    1.0\n    > gamma.mean\n    1.2\n    > gamma.mode\n    1.0\n    > gamma.skewness\n    ~0.816\n    > gamma.stdev\n    ~0.49\n    > gamma.variance\n    0.24\n    > gamma.cdf( 0.8 )\n    ~0.215\n    > gamma.logcdf( 0.8 )\n    ~-1.538\n    > gamma.logpdf( 1.0 )\n    ~-0.131\n    > gamma.mgf( -0.5 )\n    ~0.564\n    > gamma.pdf( 1.0 )\n    ~0.877\n    > gamma.quantile( 0.8 )\n    ~1.581\n\n","base.dists.gamma.kurtosis":"\nbase.dists.gamma.kurtosis( α, β )\n    Returns the excess kurtosis of a gamma distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.gamma.kurtosis( 1.0, 1.0 )\n    6.0\n    > v = base.dists.gamma.kurtosis( 4.0, 12.0 )\n    1.5\n    > v = base.dists.gamma.kurtosis( 8.0, 2.0 )\n    0.75\n\n","base.dists.gamma.logcdf":"\nbase.dists.gamma.logcdf( x, α, β )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    gamma distribution with shape parameter `α` and rate parameter `β` at a\n    value `x`.\n\n    If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.gamma.logcdf( 2.0, 0.5, 1.0 )\n    ~-0.047\n    > y = base.dists.gamma.logcdf( 0.1, 1.0, 1.0 )\n    ~-2.352\n    > y = base.dists.gamma.logcdf( -1.0, 4.0, 2.0 )\n    -Infinity\n\n    > y = base.dists.gamma.logcdf( NaN, 0.6, 1.0 )\n    NaN\n    > y = base.dists.gamma.logcdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gamma.logcdf( 0.0, 1.0, NaN )\n    NaN\n\n    // Negative shape parameter:\n    > y = base.dists.gamma.logcdf( 2.0, -1.0, 1.0 )\n    NaN\n    // Non-positive rate parameter:\n    > y = base.dists.gamma.logcdf( 2.0, 1.0, -1.0 )\n    NaN\n\n\nbase.dists.gamma.logcdf.factory( α, β )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a gamma distribution with shape parameter `α`\n    and rate parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogCDF = base.dists.gamma.logcdf.factory( 6.0, 7.0 );\n    > var y = mylogCDF( 2.0 )\n    ~-0.006\n\n","base.dists.gamma.logcdf.factory":"\nbase.dists.gamma.logcdf.factory( α, β )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a gamma distribution with shape parameter `α`\n    and rate parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogCDF = base.dists.gamma.logcdf.factory( 6.0, 7.0 );\n    > var y = mylogCDF( 2.0 )\n    ~-0.006","base.dists.gamma.logpdf":"\nbase.dists.gamma.logpdf( x, α, β )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    gamma distribution with shape parameter `α` and rate parameter `β` at a\n    value `x`.\n\n    If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.gamma.logpdf( 2.0, 0.5, 1.0 )\n    ~-2.919\n    > y = base.dists.gamma.logpdf( 0.1, 1.0, 1.0 )\n    ~-0.1\n    > y = base.dists.gamma.logpdf( -1.0, 4.0, 2.0 )\n    -Infinity\n\n    > y = base.dists.gamma.logpdf( NaN, 0.6, 1.0 )\n    NaN\n    > y = base.dists.gamma.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gamma.logpdf( 0.0, 1.0, NaN )\n    NaN\n\n    // Negative shape parameter:\n    > y = base.dists.gamma.logpdf( 2.0, -1.0, 1.0 )\n    NaN\n    // Non-positive rate parameter:\n    > y = base.dists.gamma.logpdf( 2.0, 1.0, -1.0 )\n    NaN\n\n    // Degenerate distribution centered at `0.0` when `α = 0.0`:\n    > y = base.dists.gamma.logpdf( 2.0, 0.0, 2.0 )\n    -Infinity\n    > y = base.dists.gamma.logpdf( 0.0, 0.0, 2.0 )\n    Infinity\n\n\nbase.dists.gamma.logpdf.factory( α, β )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a gamma distribution with shape parameter `α` and rate\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.gamma.logpdf.factory( 6.0, 7.0 );\n    > var y = mylogPDF( 2.0 )\n    ~-3.646\n\n","base.dists.gamma.logpdf.factory":"\nbase.dists.gamma.logpdf.factory( α, β )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a gamma distribution with shape parameter `α` and rate\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.gamma.logpdf.factory( 6.0, 7.0 );\n    > var y = mylogPDF( 2.0 )\n    ~-3.646","base.dists.gamma.mean":"\nbase.dists.gamma.mean( α, β )\n    Returns the expected value of a gamma distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.gamma.mean( 1.0, 1.0 )\n    1.0\n    > v = base.dists.gamma.mean( 4.0, 12.0 )\n    ~0.333\n    > v = base.dists.gamma.mean( 8.0, 2.0 )\n    4.0\n\n","base.dists.gamma.mgf":"\nbase.dists.gamma.mgf( t, α, β )\n    Evaluates the moment-generating function (MGF) for a gamma distribution with\n    shape parameter `α` and rate parameter `β` at a value `t`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.gamma.mgf( 0.5, 0.5, 1.0 )\n    ~1.414\n    > y = base.dists.gamma.mgf( 0.1, 1.0, 1.0 )\n    ~1.111\n    > y = base.dists.gamma.mgf( -1.0, 4.0, 2.0 )\n    ~0.198\n\n    > y = base.dists.gamma.mgf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.gamma.mgf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gamma.mgf( 0.0, 1.0, NaN )\n    NaN\n\n    > y = base.dists.gamma.mgf( 2.0, 4.0, 1.0 )\n    NaN\n    > y = base.dists.gamma.mgf( 2.0, -0.5, 1.0 )\n    NaN\n    > y = base.dists.gamma.mgf( 2.0, 1.0, 0.0 )\n    NaN\n    > y = base.dists.gamma.mgf( 2.0, 1.0, -1.0 )\n    NaN\n\n\nbase.dists.gamma.mgf.factory( α, β )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    gamma distribution with shape parameter `α` and rate parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.gamma.mgf.factory( 3.0, 1.5 );\n    > var y = myMGF( 1.0 )\n    ~27.0\n    > y = myMGF( 0.5 )\n    ~3.375\n\n","base.dists.gamma.mgf.factory":"\nbase.dists.gamma.mgf.factory( α, β )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    gamma distribution with shape parameter `α` and rate parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.gamma.mgf.factory( 3.0, 1.5 );\n    > var y = myMGF( 1.0 )\n    ~27.0\n    > y = myMGF( 0.5 )\n    ~3.375","base.dists.gamma.mode":"\nbase.dists.gamma.mode( α, β )\n    Returns the mode of a gamma distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.gamma.mode( 1.0, 1.0 )\n    0.0\n    > v = base.dists.gamma.mode( 4.0, 12.0 )\n    0.25\n    > v = base.dists.gamma.mode( 8.0, 2.0 )\n    3.5\n\n","base.dists.gamma.pdf":"\nbase.dists.gamma.pdf( x, α, β )\n    Evaluates the probability density function (PDF) for a gamma distribution\n    with shape parameter `α` and rate parameter `β` at a value `x`.\n\n    If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.gamma.pdf( 2.0, 0.5, 1.0 )\n    ~0.054\n    > y = base.dists.gamma.pdf( 0.1, 1.0, 1.0 )\n    ~0.905\n    > y = base.dists.gamma.pdf( -1.0, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.gamma.pdf( NaN, 0.6, 1.0 )\n    NaN\n    > y = base.dists.gamma.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gamma.pdf( 0.0, 1.0, NaN )\n    NaN\n\n    // Negative shape parameter:\n    > y = base.dists.gamma.pdf( 2.0, -1.0, 1.0 )\n    NaN\n    // Non-positive rate parameter:\n    > y = base.dists.gamma.pdf( 2.0, 1.0, -1.0 )\n    NaN\n\n    // Degenerate distribution centered at `0.0` when `α = 0.0`:\n    > y = base.dists.gamma.pdf( 2.0, 0.0, 2.0 )\n    0.0\n    > y = base.dists.gamma.pdf( 0.0, 0.0, 2.0 )\n    Infinity\n\n\nbase.dists.gamma.pdf.factory( α, β )\n    Returns a function for evaluating the probability density function (PDF) of\n    a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.gamma.pdf.factory( 6.0, 7.0 );\n    > var y = myPDF( 2.0 )\n    ~0.026\n\n","base.dists.gamma.pdf.factory":"\nbase.dists.gamma.pdf.factory( α, β )\n    Returns a function for evaluating the probability density function (PDF) of\n    a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.gamma.pdf.factory( 6.0, 7.0 );\n    > var y = myPDF( 2.0 )\n    ~0.026","base.dists.gamma.quantile":"\nbase.dists.gamma.quantile( p, α, β )\n    Evaluates the quantile function for a gamma distribution with shape\n    parameter `α` and rate parameter `β` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.gamma.quantile( 0.8, 2.0, 1.0 )\n    ~2.994\n    > y = base.dists.gamma.quantile( 0.5, 4.0, 2.0 )\n    ~1.836\n\n    > y = base.dists.gamma.quantile( 1.1, 1.0, 1.0 )\n    NaN\n    > y = base.dists.gamma.quantile( -0.2, 1.0, 1.0 )\n    NaN\n\n    > y = base.dists.gamma.quantile( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.gamma.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gamma.quantile( 0.0, 1.0, NaN )\n    NaN\n\n    // Non-positive shape parameter:\n    > y = base.dists.gamma.quantile( 0.5, -1.0, 1.0 )\n    NaN\n    // Non-positive rate parameter:\n    > y = base.dists.gamma.quantile( 0.5, 1.0, -1.0 )\n    NaN\n\n    // Degenerate distribution centered at `0.0` when `α = 0.0`:\n    > y = base.dists.gamma.quantile( 0.3, 0.0, 2.0 )\n    0.0\n    > y = base.dists.gamma.quantile( 0.9, 0.0, 2.0 )\n    0.0\n\n\nbase.dists.gamma.quantile.factory( α, β )\n    Returns a function for evaluating the quantile function of a gamma\n    distribution with shape parameter `α` and rate parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.gamma.quantile.factory( 2.0, 2.0 );\n    > var y = myQuantile( 0.8 )\n    ~1.497\n    > y = myQuantile( 0.4 )\n    ~0.688\n\n","base.dists.gamma.quantile.factory":"\nbase.dists.gamma.quantile.factory( α, β )\n    Returns a function for evaluating the quantile function of a gamma\n    distribution with shape parameter `α` and rate parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.gamma.quantile.factory( 2.0, 2.0 );\n    > var y = myQuantile( 0.8 )\n    ~1.497\n    > y = myQuantile( 0.4 )\n    ~0.688","base.dists.gamma.skewness":"\nbase.dists.gamma.skewness( α, β )\n    Returns the skewness of a gamma distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.gamma.skewness( 1.0, 1.0 )\n    2.0\n    > v = base.dists.gamma.skewness( 4.0, 12.0 )\n    1.0\n    > v = base.dists.gamma.skewness( 8.0, 2.0 )\n    ~0.707\n\n","base.dists.gamma.stdev":"\nbase.dists.gamma.stdev( α, β )\n    Returns the standard deviation of a gamma distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.gamma.stdev( 1.0, 1.0 )\n    1.0\n    > v = base.dists.gamma.stdev( 4.0, 12.0 )\n    ~0.167\n    > v = base.dists.gamma.stdev( 8.0, 2.0 )\n    ~1.414\n\n","base.dists.gamma.variance":"\nbase.dists.gamma.variance( α, β )\n    Returns the variance of a gamma distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.gamma.variance( 1.0, 1.0 )\n    1.0\n    > v = base.dists.gamma.variance( 4.0, 12.0 )\n    ~0.028\n    > v = base.dists.gamma.variance( 8.0, 2.0 )\n    2.0\n\n","base.dists.geometric.cdf":"\nbase.dists.geometric.cdf( x, p )\n    Evaluates the cumulative distribution function (CDF) for a geometric\n    distribution with success probability `p` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.geometric.cdf( 2.0, 0.5 )\n    0.875\n    > y = base.dists.geometric.cdf( 2.0, 0.1 )\n    ~0.271\n    > y = base.dists.geometric.cdf( -1.0, 4.0 )\n    0.0\n    > y = base.dists.geometric.cdf( NaN, 0.5 )\n    NaN\n    > y = base.dists.geometric.cdf( 0.0, NaN )\n    NaN\n    // Invalid probability\n    > y = base.dists.geometric.cdf( 2.0, 1.4 )\n    NaN\n\n\nbase.dists.geometric.cdf.factory( p )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a geometric distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.geometric.cdf.factory( 0.5 );\n    > var y = mycdf( 3.0 )\n    0.9375\n    > y = mycdf( 1.0 )\n    0.75\n\n","base.dists.geometric.cdf.factory":"\nbase.dists.geometric.cdf.factory( p )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a geometric distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.geometric.cdf.factory( 0.5 );\n    > var y = mycdf( 3.0 )\n    0.9375\n    > y = mycdf( 1.0 )\n    0.75","base.dists.geometric.entropy":"\nbase.dists.geometric.entropy( p )\n    Returns the entropy of a geometric distribution with success probability\n    `p` (in nats).\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.geometric.entropy( 0.1 )\n    ~3.251\n    > v = base.dists.geometric.entropy( 0.5 )\n    ~1.386\n\n","base.dists.geometric.Geometric":"\nbase.dists.geometric.Geometric( [p] )\n    Returns a geometric distribution object.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability. Must be between `0` and `1`. Default: `0.5`.\n\n    Returns\n    -------\n    geometric: Object\n        Distribution instance.\n\n    geometric.p: number\n        Success probability. If set, the value must be between `0` and `1`.\n\n    geometric.entropy: number\n        Read-only property which returns the differential entropy.\n\n    geometric.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    geometric.mean: number\n        Read-only property which returns the expected value.\n\n    geometric.median: number\n        Read-only property which returns the median.\n\n    geometric.mode: number\n        Read-only property which returns the mode.\n\n    geometric.skewness: number\n        Read-only property which returns the skewness.\n\n    geometric.stdev: number\n        Read-only property which returns the standard deviation.\n\n    geometric.variance: number\n        Read-only property which returns the variance.\n\n    geometric.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    geometric.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    geometric.logpmf: Function\n        Evaluates the natural logarithm of the probability mass function (PMF).\n\n    geometric.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    geometric.pmf: Function\n        Evaluates the probability mass function (PMF).\n\n    geometric.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var geometric = base.dists.geometric.Geometric( 0.6 );\n    > geometric.p\n    0.6\n    > geometric.entropy\n    ~1.122\n    > geometric.kurtosis\n    ~6.9\n    > geometric.mean\n    ~0.667\n    > geometric.median\n    0.0\n    > geometric.mode\n    0.0\n    > geometric.skewness\n    ~2.214\n    > geometric.stdev\n    ~1.054\n    > geometric.variance\n    ~1.111\n    > geometric.cdf( 3.0 )\n    ~0.974\n    > geometric.logcdf( 3.0 )\n    ~-0.026\n    > geometric.logpmf( 4.0 )\n    ~-4.176\n    > geometric.mgf( 0.5 )\n    ~2.905\n    > geometric.pmf( 2.0 )\n    ~0.096\n    > geometric.quantile( 0.7 )\n    1.0\n\n","base.dists.geometric.kurtosis":"\nbase.dists.geometric.kurtosis( p )\n    Returns the excess kurtosis of a geometric distribution with success\n    probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.geometric.kurtosis( 0.1 )\n    ~6.011\n    > v = base.dists.geometric.kurtosis( 0.5 )\n    6.5\n\n","base.dists.geometric.logcdf":"\nbase.dists.geometric.logcdf( x, p )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    geometric distribution with success probability `p` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.geometric.logcdf( 2.0, 0.5 )\n    ~-0.134\n    > y = base.dists.geometric.logcdf( 2.0, 0.1 )\n    ~-1.306\n    > y = base.dists.geometric.logcdf( -1.0, 4.0 )\n    -Infinity\n    > y = base.dists.geometric.logcdf( NaN, 0.5 )\n    NaN\n    > y = base.dists.geometric.logcdf( 0.0, NaN )\n    NaN\n    // Invalid probability\n    > y = base.dists.geometric.logcdf( 2.0, 1.4 )\n    NaN\n\n\nbase.dists.geometric.logcdf.factory( p )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a geometric distribution with success\n    probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.geometric.logcdf.factory( 0.5 );\n    > var y = mylogcdf( 3.0 )\n    ~-0.065\n    > y = mylogcdf( 1.0 )\n    ~-0.288\n\n","base.dists.geometric.logcdf.factory":"\nbase.dists.geometric.logcdf.factory( p )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a geometric distribution with success\n    probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.geometric.logcdf.factory( 0.5 );\n    > var y = mylogcdf( 3.0 )\n    ~-0.065\n    > y = mylogcdf( 1.0 )\n    ~-0.288","base.dists.geometric.logpmf":"\nbase.dists.geometric.logpmf( x, p )\n    Evaluates the logarithm of the probability mass function (PMF) for a\n    geometric distribution with success probability `p` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPMF.\n\n    Examples\n    --------\n    > var y = base.dists.geometric.logpmf( 4.0, 0.3 )\n    ~-2.631\n    > y = base.dists.geometric.logpmf( 2.0, 0.7 )\n    ~-2.765\n    > y = base.dists.geometric.logpmf( -1.0, 0.5 )\n    -Infinity\n    > y = base.dists.geometric.logpmf( 0.0, NaN )\n    NaN\n    > y = base.dists.geometric.logpmf( NaN, 0.5 )\n    NaN\n    // Invalid success probability:\n    > y = base.dists.geometric.logpmf( 2.0, 1.5 )\n    NaN\n\n\nbase.dists.geometric.logpmf.factory( p )\n    Returns a function for evaluating the logarithm of the probability mass\n    function (PMF) of a geometric distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogpmf = base.dists.geometric.logpmf.factory( 0.5 );\n    > var y = mylogpmf( 3.0 )\n    ~-2.773\n    > y = mylogpmf( 1.0 )\n    ~-1.386\n\n","base.dists.geometric.logpmf.factory":"\nbase.dists.geometric.logpmf.factory( p )\n    Returns a function for evaluating the logarithm of the probability mass\n    function (PMF) of a geometric distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogpmf = base.dists.geometric.logpmf.factory( 0.5 );\n    > var y = mylogpmf( 3.0 )\n    ~-2.773\n    > y = mylogpmf( 1.0 )\n    ~-1.386","base.dists.geometric.mean":"\nbase.dists.geometric.mean( p )\n    Returns the expected value of a geometric distribution with success\n    probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.geometric.mean( 0.1 )\n    9.0\n    > v = base.dists.geometric.mean( 0.5 )\n    1.0\n\n","base.dists.geometric.median":"\nbase.dists.geometric.median( p )\n    Returns the median of a geometric distribution with success probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: integer\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.geometric.median( 0.1 )\n    6\n    > v = base.dists.geometric.median( 0.5 )\n    0\n\n","base.dists.geometric.mgf":"\nbase.dists.geometric.mgf( t, p )\n    Evaluates the moment-generating function (MGF) for a geometric\n    distribution with success probability `p` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If `t >= -ln(1-p)`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.geometric.mgf( 0.2, 0.5 )\n    ~1.569\n    > y = base.dists.geometric.mgf( 0.4, 0.5 )\n    ~2.936\n    // Case: t >= -ln(1-p)\n    > y = base.dists.geometric.mgf( 0.8, 0.5 )\n    NaN\n    > y = base.dists.geometric.mgf( NaN, 0.0 )\n    NaN\n    > y = base.dists.geometric.mgf( 0.0, NaN )\n    NaN\n    > y = base.dists.geometric.mgf( -2.0, -1.0 )\n    NaN\n    > y = base.dists.geometric.mgf( 0.2, 2.0 )\n    NaN\n\n\nbase.dists.geometric.mgf.factory( p )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    geometric distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.geometric.mgf.factory( 0.8 );\n    > var y = mymgf( -0.2 )\n    ~0.783\n\n","base.dists.geometric.mgf.factory":"\nbase.dists.geometric.mgf.factory( p )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    geometric distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.geometric.mgf.factory( 0.8 );\n    > var y = mymgf( -0.2 )\n    ~0.783","base.dists.geometric.mode":"\nbase.dists.geometric.mode( p )\n    Returns the mode of a geometric distribution with success probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: integer\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.geometric.mode( 0.1 )\n    0\n    > v = base.dists.geometric.mode( 0.5 )\n    0\n\n","base.dists.geometric.pmf":"\nbase.dists.geometric.pmf( x, p )\n    Evaluates the probability mass function (PMF) for a geometric distribution\n    with success probability `p` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated PMF.\n\n    Examples\n    --------\n    > var y = base.dists.geometric.pmf( 4.0, 0.3 )\n    ~0.072\n    > y = base.dists.geometric.pmf( 2.0, 0.7 )\n    ~0.063\n    > y = base.dists.geometric.pmf( -1.0, 0.5 )\n    0.0\n    > y = base.dists.geometric.pmf( 0.0, NaN )\n    NaN\n    > y = base.dists.geometric.pmf( NaN, 0.5 )\n    NaN\n    // Invalid success probability:\n    > y = base.dists.geometric.pmf( 2.0, 1.5 )\n    NaN\n\n\nbase.dists.geometric.pmf.factory( p )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    geometric distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var mypmf = base.dists.geometric.pmf.factory( 0.5 );\n    > var y = mypmf( 3.0 )\n    0.0625\n    > y = mypmf( 1.0 )\n    0.25\n\n","base.dists.geometric.pmf.factory":"\nbase.dists.geometric.pmf.factory( p )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    geometric distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var mypmf = base.dists.geometric.pmf.factory( 0.5 );\n    > var y = mypmf( 3.0 )\n    0.0625\n    > y = mypmf( 1.0 )\n    0.25","base.dists.geometric.quantile":"\nbase.dists.geometric.quantile( r, p )\n    Evaluates the quantile function for a geometric distribution with success\n    probability `p` at a probability `r`.\n\n    If `r < 0` or `r > 1`, the function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    r: number\n        Input probability.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.geometric.quantile( 0.8, 0.4 )\n    3\n    > y = base.dists.geometric.quantile( 0.5, 0.4 )\n    1\n    > y = base.dists.geometric.quantile( 0.9, 0.1 )\n    21\n\n    > y = base.dists.geometric.quantile( -0.2, 0.1 )\n    NaN\n\n    > y = base.dists.geometric.quantile( NaN, 0.8 )\n    NaN\n    > y = base.dists.geometric.quantile( 0.4, NaN )\n    NaN\n\n    > y = base.dists.geometric.quantile( 0.5, -1.0 )\n    NaN\n    > y = base.dists.geometric.quantile( 0.5, 1.5 )\n    NaN\n\n\nbase.dists.geometric.quantile.factory( p )\n    Returns a function for evaluating the quantile function of a geometric\n    distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.geometric.quantile.factory( 0.4 );\n    > var y = myquantile( 0.4 )\n    0\n    > y = myquantile( 0.8 )\n    3\n    > y = myquantile( 1.0 )\n    Infinity\n\n","base.dists.geometric.quantile.factory":"\nbase.dists.geometric.quantile.factory( p )\n    Returns a function for evaluating the quantile function of a geometric\n    distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.geometric.quantile.factory( 0.4 );\n    > var y = myquantile( 0.4 )\n    0\n    > y = myquantile( 0.8 )\n    3\n    > y = myquantile( 1.0 )\n    Infinity","base.dists.geometric.skewness":"\nbase.dists.geometric.skewness( p )\n    Returns the skewness of a geometric distribution with success probability\n    `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.geometric.skewness( 0.1 )\n    ~2.003\n    > v = base.dists.geometric.skewness( 0.5 )\n    ~2.121\n\n","base.dists.geometric.stdev":"\nbase.dists.geometric.stdev( p )\n    Returns the standard deviation of a geometric distribution with success\n    probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.geometric.stdev( 0.1 )\n    ~9.487\n    > v = base.dists.geometric.stdev( 0.5 )\n    ~1.414\n\n","base.dists.geometric.variance":"\nbase.dists.geometric.variance( p )\n    Returns the variance of a geometric distribution with success probability\n    `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.geometric.variance( 0.1 )\n    ~90.0\n    > v = base.dists.geometric.variance( 0.5 )\n    2.0\n\n","base.dists.gumbel.cdf":"\nbase.dists.gumbel.cdf( x, μ, β )\n    Evaluates the cumulative distribution function (CDF) for a Gumbel\n    distribution with location parameter `μ` and scale parameter `β` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.cdf( 10.0, 0.0, 3.0 )\n    ~0.965\n    > y = base.dists.gumbel.cdf( -2.0, 0.0, 3.0 )\n    ~0.143\n    > y = base.dists.gumbel.cdf( 0.0, 0.0, 1.0 )\n    ~0.368\n    > y = base.dists.gumbel.cdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.gumbel.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.cdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.gumbel.cdf( 0.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.gumbel.cdf.factory( μ, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Gumbel distribution with location parameter `μ` and scale parameter\n    `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.gumbel.cdf.factory( 2.0, 3.0 );\n    > var y = myCDF( 10.0 )\n    ~0.933\n    > y = myCDF( 2.0 )\n    ~0.368\n\n","base.dists.gumbel.cdf.factory":"\nbase.dists.gumbel.cdf.factory( μ, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Gumbel distribution with location parameter `μ` and scale parameter\n    `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.gumbel.cdf.factory( 2.0, 3.0 );\n    > var y = myCDF( 10.0 )\n    ~0.933\n    > y = myCDF( 2.0 )\n    ~0.368","base.dists.gumbel.entropy":"\nbase.dists.gumbel.entropy( μ, β )\n    Returns the differential entropy of a Gumbel distribution with location\n    parameter `μ` and scale parameter `β` (in nats).\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.entropy( 0.0, 1.0 )\n    ~1.577\n    > y = base.dists.gumbel.entropy( 4.0, 2.0 )\n    ~2.27\n    > y = base.dists.gumbel.entropy( NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.entropy( 0.0, NaN )\n    NaN\n    > y = base.dists.gumbel.entropy( 0.0, 0.0 )\n    NaN\n\n","base.dists.gumbel.Gumbel":"\nbase.dists.gumbel.Gumbel( [μ, β] )\n    Returns a Gumbel distribution object.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter. Default: `0.0`.\n\n    β: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    gumbel: Object\n        Distribution instance.\n\n    gumbel.mu: number\n        Location parameter.\n\n    gumbel.beta: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    gumbel.entropy: number\n        Read-only property which returns the differential entropy.\n\n    gumbel.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    gumbel.mean: number\n        Read-only property which returns the expected value.\n\n    gumbel.median: number\n        Read-only property which returns the median.\n\n    gumbel.mode: number\n        Read-only property which returns the mode.\n\n    gumbel.skewness: number\n        Read-only property which returns the skewness.\n\n    gumbel.stdev: number\n        Read-only property which returns the standard deviation.\n\n    gumbel.variance: number\n        Read-only property which returns the variance.\n\n    gumbel.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    gumbel.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    gumbel.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    gumbel.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    gumbel.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    gumbel.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var gumbel = base.dists.gumbel.Gumbel( -2.0, 3.0 );\n    > gumbel.mu\n    -2.0\n    > gumbel.beta\n    3.0\n    > gumbel.entropy\n    ~2.676\n    > gumbel.kurtosis\n    2.4\n    > gumbel.mean\n    ~-0.268\n    > gumbel.median\n    ~-0.9\n    > gumbel.mode\n    -2.0\n    > gumbel.skewness\n    ~1.14\n    > gumbel.stdev\n    ~3.848\n    > gumbel.variance\n    ~14.804\n    > gumbel.cdf( 0.8 )\n    ~0.675\n    > gumbel.logcdf( 0.8 )\n    ~-0.393\n    > gumbel.logpdf( 1.0 )\n    ~-2.466\n    > gumbel.mgf( 0.2 )\n    ~1.487\n    > gumbel.pdf( 1.0 )\n    ~0.085\n    > gumbel.quantile( 0.8 )\n    ~2.5\n\n","base.dists.gumbel.kurtosis":"\nbase.dists.gumbel.kurtosis( μ, β )\n    Returns the excess kurtosis of a Gumbel distribution with location parameter\n    `μ` and scale parameter `β`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.kurtosis( 0.0, 1.0 )\n    2.4\n    > y = base.dists.gumbel.kurtosis( 4.0, 2.0 )\n    2.4\n    > y = base.dists.gumbel.kurtosis( NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.kurtosis( 0.0, NaN )\n    NaN\n    > y = base.dists.gumbel.kurtosis( 0.0, 0.0 )\n    NaN\n\n","base.dists.gumbel.logcdf":"\nbase.dists.gumbel.logcdf( x, μ, β )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.logcdf( 10.0, 0.0, 3.0 )\n    ~-0.036\n    > y = base.dists.gumbel.logcdf( -2.0, 0.0, 3.0 )\n    ~-1.948\n    > y = base.dists.gumbel.logcdf( 0.0, 0.0, 1.0 )\n    ~-1.0\n    > y = base.dists.gumbel.logcdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.gumbel.logcdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.logcdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.gumbel.logcdf( 0.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.gumbel.logcdf.factory( μ, β )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Gumbel distribution with location parameter\n    `μ` and scale parameter `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myLCDF = base.dists.gumbel.logcdf.factory( 2.0, 3.0 );\n    > var y = myLCDF( 10.0 )\n    ~-0.069\n    > y = myLCDF( 2.0 )\n    ~-1.0\n\n","base.dists.gumbel.logcdf.factory":"\nbase.dists.gumbel.logcdf.factory( μ, β )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Gumbel distribution with location parameter\n    `μ` and scale parameter `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myLCDF = base.dists.gumbel.logcdf.factory( 2.0, 3.0 );\n    > var y = myLCDF( 10.0 )\n    ~-0.069\n    > y = myLCDF( 2.0 )\n    ~-1.0","base.dists.gumbel.logpdf":"\nbase.dists.gumbel.logpdf( x, μ, β )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.logpdf( 0.0, 0.0, 2.0 )\n    ~-1.693\n    > y = base.dists.gumbel.logpdf( 0.0, 0.0, 1.0 )\n    ~-1\n    > y = base.dists.gumbel.logpdf( 1.0, 3.0, 2.0 )\n    ~-2.411\n    > y = base.dists.gumbel.logpdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.gumbel.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.logpdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.gumbel.logpdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.gumbel.logpdf.factory( μ, β )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Gumbel distribution with location parameter `μ` and\n    scale parameter `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.gumbel.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogpdf( 10.0 )\n    ~-1.693\n    > y = mylogpdf( 12.0 )\n    ~-2.061\n\n","base.dists.gumbel.logpdf.factory":"\nbase.dists.gumbel.logpdf.factory( μ, β )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Gumbel distribution with location parameter `μ` and\n    scale parameter `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.gumbel.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogpdf( 10.0 )\n    ~-1.693\n    > y = mylogpdf( 12.0 )\n    ~-2.061","base.dists.gumbel.mean":"\nbase.dists.gumbel.mean( μ, β )\n    Returns the expected value of a Gumbel distribution with location parameter\n    `μ` and scale parameter `β`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.mean( 0.0, 1.0 )\n    ~0.577\n    > y = base.dists.gumbel.mean( 4.0, 2.0 )\n    ~5.154\n    > y = base.dists.gumbel.mean( NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.mean( 0.0, NaN )\n    NaN\n    > y = base.dists.gumbel.mean( 0.0, 0.0 )\n    NaN\n\n","base.dists.gumbel.median":"\nbase.dists.gumbel.median( μ, β )\n    Returns the median of a Gumbel distribution with location parameter `μ` and\n    scale parameter `β`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.median( 0.0, 1.0 )\n    ~0.367\n    > y = base.dists.gumbel.median( 4.0, 2.0 )\n    ~4.733\n    > y = base.dists.gumbel.median( NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.median( 0.0, NaN )\n    NaN\n    > y = base.dists.gumbel.median( 0.0, 0.0 )\n    NaN\n\n","base.dists.gumbel.mgf":"\nbase.dists.gumbel.mgf( t, μ, β )\n    Evaluates the moment-generating function (MGF) for a Gumbel distribution\n    with location parameter `μ` and scale parameter `β` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.mgf( -1.0, 0.0, 3.0 )\n    6.0\n    > y = base.dists.gumbel.mgf( 0.0, 0.0, 1.0 )\n    1.0\n    > y = base.dists.gumbel.mgf( 0.1, 0.0, 3.0 )\n    ~1.298\n\n    > y = base.dists.gumbel.mgf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.gumbel.mgf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.mgf( 0.0, 0.0, NaN )\n    NaN\n\n    // Case: `t >= 1/beta`\n    > y = base.dists.gumbel.mgf( 0.8, 0.0, 2.0 )\n    NaN\n\n    // Non-positive scale parameter:\n    > y = base.dists.gumbel.mgf( 0.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.gumbel.mgf.factory( μ, β )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Gumbel distribution with location parameter `μ` and scale parameter `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.gumbel.mgf.factory( 0.0, 3.0 );\n    > var y = myMGF( -1.5 )\n    ~52.343\n    > y = myMGF( -1.0 )\n    6.0\n\n","base.dists.gumbel.mgf.factory":"\nbase.dists.gumbel.mgf.factory( μ, β )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Gumbel distribution with location parameter `μ` and scale parameter `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.gumbel.mgf.factory( 0.0, 3.0 );\n    > var y = myMGF( -1.5 )\n    ~52.343\n    > y = myMGF( -1.0 )\n    6.0","base.dists.gumbel.mode":"\nbase.dists.gumbel.mode( μ, β )\n    Returns the mode of a Gumbel distribution with location parameter `μ` and\n    scale parameter `β`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.mode( 0.0, 1.0 )\n    0.0\n    > y = base.dists.gumbel.mode( 4.0, 2.0 )\n    4.0\n    > y = base.dists.gumbel.mode( NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.mode( 0.0, NaN )\n    NaN\n    > y = base.dists.gumbel.mode( 0.0, 0.0 )\n    NaN\n\n","base.dists.gumbel.pdf":"\nbase.dists.gumbel.pdf( x, μ, β )\n    Evaluates the probability density function (PDF) for a Gumbel distribution\n    with location parameter `μ` and scale parameter `β` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.pdf( 0.0, 0.0, 2.0 )\n    ~0.184\n    > y = base.dists.gumbel.pdf( 0.0, 0.0, 1.0 )\n    ~0.368\n    > y = base.dists.gumbel.pdf( 1.0, 3.0, 2.0 )\n    ~0.09\n    > y = base.dists.gumbel.pdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.gumbel.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.pdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.gumbel.pdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.gumbel.pdf.factory( μ, β )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Gumbel distribution with location parameter `μ` and scale parameter\n    `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.gumbel.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    ~0.184\n    > y = myPDF( 12.0 )\n    ~0.127\n\n","base.dists.gumbel.pdf.factory":"\nbase.dists.gumbel.pdf.factory( μ, β )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Gumbel distribution with location parameter `μ` and scale parameter\n    `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.gumbel.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    ~0.184\n    > y = myPDF( 12.0 )\n    ~0.127","base.dists.gumbel.quantile":"\nbase.dists.gumbel.quantile( p, μ, β )\n    Evaluates the quantile function for a Gumbel distribution with location\n    parameter `μ` and scale parameter `β` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.quantile( 0.8, 0.0, 1.0 )\n    ~1.5\n    > y = base.dists.gumbel.quantile( 0.5, 4.0, 2.0 )\n    ~4.733\n    > y = base.dists.gumbel.quantile( 0.5, 4.0, 4.0 )\n    ~5.466\n\n    > y = base.dists.gumbel.quantile( 1.1, 0.0, 1.0 )\n    NaN\n    > y = base.dists.gumbel.quantile( -0.2, 0.0, 1.0 )\n    NaN\n\n    > y = base.dists.gumbel.quantile( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.gumbel.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.quantile( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.gumbel.quantile( 0.5, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.gumbel.quantile.factory( μ, β )\n    Returns a function for evaluating the quantile function of a Gumbel\n    distribution with location parameter `μ` and scale parameter `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.gumbel.quantile.factory( 8.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    ~8.733\n    > y = myQuantile( 0.7 )\n    ~10.062\n\n","base.dists.gumbel.quantile.factory":"\nbase.dists.gumbel.quantile.factory( μ, β )\n    Returns a function for evaluating the quantile function of a Gumbel\n    distribution with location parameter `μ` and scale parameter `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.gumbel.quantile.factory( 8.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    ~8.733\n    > y = myQuantile( 0.7 )\n    ~10.062","base.dists.gumbel.skewness":"\nbase.dists.gumbel.skewness( μ, β )\n    Returns the skewness of a Gumbel distribution with location parameter `μ`\n    and scale parameter `β`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.skewness( 0.0, 1.0 )\n    ~1.14\n    > y = base.dists.gumbel.skewness( 4.0, 2.0 )\n    ~1.14\n    > y = base.dists.gumbel.skewness( NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.skewness( 0.0, NaN )\n    NaN\n    > y = base.dists.gumbel.skewness( 0.0, 0.0 )\n    NaN\n\n","base.dists.gumbel.stdev":"\nbase.dists.gumbel.stdev( μ, β )\n    Returns the standard deviation of a Gumbel distribution with location\n    parameter `μ` and scale parameter `β`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.stdev( 0.0, 1.0 )\n    ~1.283\n    > y = base.dists.gumbel.stdev( 4.0, 2.0 )\n    ~2.565\n    > y = base.dists.gumbel.stdev( NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.stdev( 0.0, NaN )\n    NaN\n    > y = base.dists.gumbel.stdev( 0.0, 0.0 )\n    NaN\n\n","base.dists.gumbel.variance":"\nbase.dists.gumbel.variance( μ, β )\n    Returns the variance of a Gumbel distribution with location parameter `μ`\n    and scale parameter `β`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.variance( 0.0, 1.0 )\n    ~1.645\n    > y = base.dists.gumbel.variance( 4.0, 2.0 )\n    ~6.58\n    > y = base.dists.gumbel.variance( NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.variance( 0.0, NaN )\n    NaN\n    > y = base.dists.gumbel.variance( 0.0, 0.0 )\n    NaN\n\n","base.dists.hypergeometric.cdf":"\nbase.dists.hypergeometric.cdf( x, N, K, n )\n    Evaluates the cumulative distribution function (CDF) for a hypergeometric\n    distribution with population size `N`, subpopulation size `K`, and number of\n    draws `n` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a population size `N`, subpopulation size `K` or draws `n` which\n    is not a nonnegative integer, the function returns `NaN`.\n\n    If the number of draws `n` or subpopulation size `K` exceeds population size\n     `N`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.hypergeometric.cdf( 1.0, 8, 4, 2 )\n    ~0.786\n    > y = base.dists.hypergeometric.cdf( 1.5, 8, 4, 2 )\n    ~0.786\n    > y = base.dists.hypergeometric.cdf( 2.0, 8, 4, 2 )\n    1.0\n    > y = base.dists.hypergeometric.cdf( 0, 8, 4, 2)\n    ~0.214\n\n    > y = base.dists.hypergeometric.cdf( NaN, 10, 5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.cdf( 0.0, NaN, 5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.cdf( 0.0, 10, NaN, 2 )\n    NaN\n    > y = base.dists.hypergeometric.cdf( 0.0, 10, 5, NaN )\n    NaN\n\n    > y = base.dists.hypergeometric.cdf( 2.0, 10.5, 5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.cdf( 2.0, 10, 1.5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.cdf( 2.0, 10, 5, -2.0 )\n    NaN\n    > y = base.dists.hypergeometric.cdf( 2.0, 10, 5, 12 )\n    NaN\n    > y = base.dists.hypergeometric.cdf( 2.0, 8, 3, 9 )\n    NaN\n\n\nbase.dists.hypergeometric.cdf.factory( N, K, n )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a hypergeometric distribution with population size `N`, subpopulation\n    size `K`, and number of draws `n`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.hypergeometric.cdf.factory( 30, 20, 5 );\n    > var y = myCDF( 4.0 )\n    ~0.891\n    > y = myCDF( 1.0 )\n    ~0.031\n\n","base.dists.hypergeometric.cdf.factory":"\nbase.dists.hypergeometric.cdf.factory( N, K, n )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a hypergeometric distribution with population size `N`, subpopulation\n    size `K`, and number of draws `n`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.hypergeometric.cdf.factory( 30, 20, 5 );\n    > var y = myCDF( 4.0 )\n    ~0.891\n    > y = myCDF( 1.0 )\n    ~0.031","base.dists.hypergeometric.Hypergeometric":"\nbase.dists.hypergeometric.Hypergeometric( [N, K, n] )\n    Returns a hypergeometric distribution object.\n\n    Parameters\n    ----------\n    N: integer (optional)\n        Population size. Must be a nonnegative integer larger than or equal to\n        `K` and `n`.\n\n    K: integer (optional)\n        Subpopulation size. Must be a nonnegative integer smaller than or equal\n        to `N`.\n\n    n: integer (optional)\n        Number of draws. Must be a nonnegative integer smaller than or equal to\n        `N`.\n\n    Returns\n    -------\n    hypergeometric: Object\n        Distribution instance.\n\n    hypergeometric.N: number\n        Population size. If set, the value must be a nonnegative integer larger\n        than or equal to `K` and `n`.\n\n    hypergeometric.K: number\n        Subpopulation size. If set, the value must be a nonnegative integer\n        smaller than or equal to `N`.\n\n    hypergeometric.n: number\n        Number of draws. If set, the value must be a nonnegative integer\n        smaller than or equal to `N`.\n\n    hypergeometric.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    hypergeometric.mean: number\n        Read-only property which returns the expected value.\n\n    hypergeometric.mode: number\n        Read-only property which returns the mode.\n\n    hypergeometric.skewness: number\n        Read-only property which returns the skewness.\n\n    hypergeometric.stdev: number\n        Read-only property which returns the standard deviation.\n\n    hypergeometric.variance: number\n        Read-only property which returns the variance.\n\n    hypergeometric.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    hypergeometric.logpmf: Function\n        Evaluates the natural logarithm of the probability mass function (PMF).\n\n    hypergeometric.pmf: Function\n        Evaluates the probability mass function (PMF).\n\n    hypergeometric.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var hypergeometric = base.dists.hypergeometric.Hypergeometric( 100, 70, 20 );\n    > hypergeometric.N\n    100.0\n    > hypergeometric.K\n    70.0\n    > hypergeometric.n\n    20.0\n    > hypergeometric.kurtosis\n    ~-0.063\n    > hypergeometric.mean\n    14.0\n    > hypergeometric.mode\n    14.0\n    > hypergeometric.skewness\n    ~-0.133\n    > hypergeometric.stdev\n    ~1.842\n    > hypergeometric.variance\n    ~3.394\n    > hypergeometric.cdf( 2.9 )\n    ~0.0\n    > hypergeometric.logpmf( 10 )\n    ~-3.806\n    > hypergeometric.pmf( 10 )\n    ~0.022\n    > hypergeometric.quantile( 0.8 )\n    16.0\n\n","base.dists.hypergeometric.kurtosis":"\nbase.dists.hypergeometric.kurtosis( N, K, n )\n    Returns the excess kurtosis of a hypergeometric distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a population size `N`, subpopulation size `K` or draws `n` which\n    is not a nonnegative integer, the function returns `NaN`.\n\n    If the number of draws `n` or subpopulation size `K` exceed population size\n    `N`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.hypergeometric.kurtosis( 16, 11, 4 )\n    ~-0.326\n    > v = base.dists.hypergeometric.kurtosis( 4, 2, 2 )\n    0.0\n\n    > v = base.dists.hypergeometric.kurtosis( 10, 5, 12 )\n    NaN\n    > v = base.dists.hypergeometric.kurtosis( 10.3, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.kurtosis( 10, 5.5, 4 )\n    NaN\n    > v = base.dists.hypergeometric.kurtosis( 10, 5, 4.5 )\n    NaN\n\n    > v = base.dists.hypergeometric.kurtosis( NaN, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.kurtosis( 20, NaN, 4 )\n    NaN\n    > v = base.dists.hypergeometric.kurtosis( 20, 10, NaN )\n    NaN\n\n","base.dists.hypergeometric.logpmf":"\nbase.dists.hypergeometric.logpmf( x, N, K, n )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    hypergeometric distribution with population size `N`, subpopulation size\n    `K`, and number of draws `n` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a population size `N`, subpopulation size `K`, or draws `n`\n    which is not a nonnegative integer, the function returns `NaN`.\n\n    If the number of draws `n` or the subpopulation size `K` exceed population\n    size `N`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPMF.\n\n    Examples\n    --------\n    > var y = base.dists.hypergeometric.logpmf( 1.0, 8, 4, 2 )\n    ~-0.56\n    > y = base.dists.hypergeometric.logpmf( 2.0, 8, 4, 2 )\n    ~-1.54\n    > y = base.dists.hypergeometric.logpmf( 0.0, 8, 4, 2 )\n    ~-1.54\n    > y = base.dists.hypergeometric.logpmf( 1.5, 8, 4, 2 )\n    -Infinity\n\n    > y = base.dists.hypergeometric.logpmf( NaN, 10, 5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.logpmf( 0.0, NaN, 5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.logpmf( 0.0, 10, NaN, 2 )\n    NaN\n    > y = base.dists.hypergeometric.logpmf( 0.0, 10, 5, NaN )\n    NaN\n\n    > y = base.dists.hypergeometric.logpmf( 2.0, 10.5, 5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.logpmf( 2.0, 5, 1.5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.logpmf( 2.0, 10, 5, -2.0 )\n    NaN\n    > y = base.dists.hypergeometric.logpmf( 2.0, 10, 5, 12 )\n    NaN\n    > y = base.dists.hypergeometric.logpmf( 2.0, 8, 3, 9 )\n    NaN\n\n\nbase.dists.hypergeometric.logpmf.factory( N, K, n )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a hypergeometric distribution with population size\n    `N`, subpopulation size `K`, and number of draws `n`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogPMF = base.dists.hypergeometric.logpmf.factory( 30, 20, 5 );\n    > var y = mylogPMF( 4.0 )\n    ~-1.079\n    > y = mylogPMF( 1.0 )\n    ~-3.524\n\n","base.dists.hypergeometric.logpmf.factory":"\nbase.dists.hypergeometric.logpmf.factory( N, K, n )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a hypergeometric distribution with population size\n    `N`, subpopulation size `K`, and number of draws `n`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogPMF = base.dists.hypergeometric.logpmf.factory( 30, 20, 5 );\n    > var y = mylogPMF( 4.0 )\n    ~-1.079\n    > y = mylogPMF( 1.0 )\n    ~-3.524","base.dists.hypergeometric.mean":"\nbase.dists.hypergeometric.mean( N, K, n )\n    Returns the expected value of a hypergeometric distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a population size `N`, subpopulation size `K` or draws `n` which\n    is not a nonnegative integer, the function returns `NaN`.\n\n    If the number of draws `n` or the subpopulation size `K` exceed population\n    size `N`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.hypergeometric.mean( 16, 11, 4 )\n    2.75\n    > v = base.dists.hypergeometric.mean( 2, 1, 1 )\n    0.5\n\n    > v = base.dists.hypergeometric.mean( 10, 5, 12 )\n    NaN\n    > v = base.dists.hypergeometric.mean( 10.3, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.mean( 10, 5.5, 4 )\n    NaN\n    > v = base.dists.hypergeometric.mean( 10, 5, 4.5 )\n    NaN\n\n    > v = base.dists.hypergeometric.mean( NaN, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.mean( 20, NaN, 4 )\n    NaN\n    > v = base.dists.hypergeometric.mean( 20, 10, NaN )\n    NaN\n\n","base.dists.hypergeometric.mode":"\nbase.dists.hypergeometric.mode( N, K, n )\n    Returns the mode of a hypergeometric distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a population size `N`, subpopulation size `K` or draws `n` which\n    is not a nonnegative integer, the function returns `NaN`.\n\n    If the number of draws `n` or the subpopulation size `K` exceed population\n    size `N`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.hypergeometric.mode( 16, 11, 4 )\n    3\n    > v = base.dists.hypergeometric.mode( 2, 1, 1 )\n    1\n\n    > v = base.dists.hypergeometric.mode( 10, 5, 12 )\n    NaN\n    > v = base.dists.hypergeometric.mode( 10.3, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.mode( 10, 5.5, 4 )\n    NaN\n    > v = base.dists.hypergeometric.mode( 10, 5, 4.5 )\n    NaN\n\n    > v = base.dists.hypergeometric.mode( NaN, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.mode( 20, NaN, 4 )\n    NaN\n    > v = base.dists.hypergeometric.mode( 20, 10, NaN )\n    NaN\n\n","base.dists.hypergeometric.pmf":"\nbase.dists.hypergeometric.pmf( x, N, K, n )\n    Evaluates the probability mass function (PMF) for a hypergeometric\n    distribution with population size `N`, subpopulation size `K`, and number of\n    draws `n` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a population size `N`, subpopulation size `K` or draws `n` which\n    is not a nonnegative integer, the function returns `NaN`.\n\n    If the number of draws `n` or the subpopulation size `K` exceed population\n    size `N`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    out: number\n        Evaluated PMF.\n\n    Examples\n    --------\n    > var y = base.dists.hypergeometric.pmf( 1.0, 8, 4, 2 )\n    ~0.571\n    > y = base.dists.hypergeometric.pmf( 2.0, 8, 4, 2 )\n    ~0.214\n    > y = base.dists.hypergeometric.pmf( 0.0, 8, 4, 2 )\n    ~0.214\n    > y = base.dists.hypergeometric.pmf( 1.5, 8, 4, 2 )\n    0.0\n\n    > y = base.dists.hypergeometric.pmf( NaN, 10, 5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.pmf( 0.0, NaN, 5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.pmf( 0.0, 10, NaN, 2 )\n    NaN\n    > y = base.dists.hypergeometric.pmf( 0.0, 10, 5, NaN )\n    NaN\n\n    > y = base.dists.hypergeometric.pmf( 2.0, 10.5, 5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.pmf( 2.0, 5, 1.5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.pmf( 2.0, 10, 5, -2.0 )\n    NaN\n    > y = base.dists.hypergeometric.pmf( 2.0, 10, 5, 12 )\n    NaN\n    > y = base.dists.hypergeometric.pmf( 2.0, 8, 3, 9 )\n    NaN\n\n\nbase.dists.hypergeometric.pmf.factory( N, K, n )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    hypergeometric distribution with population size `N`, subpopulation size\n    `K`, and number of draws `n`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var myPMF = base.dists.hypergeometric.pmf.factory( 30, 20, 5 );\n    > var y = myPMF( 4.0 )\n    ~0.34\n    > y = myPMF( 1.0 )\n    ~0.029\n\n","base.dists.hypergeometric.pmf.factory":"\nbase.dists.hypergeometric.pmf.factory( N, K, n )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    hypergeometric distribution with population size `N`, subpopulation size\n    `K`, and number of draws `n`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var myPMF = base.dists.hypergeometric.pmf.factory( 30, 20, 5 );\n    > var y = myPMF( 4.0 )\n    ~0.34\n    > y = myPMF( 1.0 )\n    ~0.029","base.dists.hypergeometric.quantile":"\nbase.dists.hypergeometric.quantile( p, N, K, n )\n    Evaluates the quantile function for a hypergeometric distribution with\n    population size `N`, subpopulation size `K`, and number of draws `n` at a\n    probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a population size `N`, subpopulation size `K` or draws `n` which\n    is not a nonnegative integer, the function returns `NaN`.\n\n    If the number of draws `n` or the subpopulation size `K` exceed population\n    size `N`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.hypergeometric.quantile( 0.4, 40, 20, 10 )\n    5\n    > y = base.dists.hypergeometric.quantile( 0.8, 60, 40, 20 )\n    15\n    > y = base.dists.hypergeometric.quantile( 0.5, 100, 10, 10 )\n    1\n    > y = base.dists.hypergeometric.quantile( 0.0, 100, 40, 20 )\n    0\n    > y = base.dists.hypergeometric.quantile( 1.0, 100, 40, 20 )\n    20\n\n    > y = base.dists.hypergeometric.quantile( NaN, 40, 20, 10 )\n    NaN\n    > y = base.dists.hypergeometric.quantile( 0.2, NaN, 20, 10 )\n    NaN\n    > y = base.dists.hypergeometric.quantile( 0.2, 40, NaN, 10 )\n    NaN\n    > y = base.dists.hypergeometric.quantile( 0.2, 40, 20, NaN )\n    NaN\n\n\nbase.dists.hypergeometric.quantile.factory( N, K, n )\n    Returns a function for evaluating the quantile function of a hypergeometric\n    distribution with population size `N`, subpopulation size `K`, and number of\n    draws `n`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.hypergeometric.quantile.factory( 100, 20, 10 );\n    > var y = myQuantile( 0.2 )\n    1\n    > y = myQuantile( 0.9 )\n    4\n\n","base.dists.hypergeometric.quantile.factory":"\nbase.dists.hypergeometric.quantile.factory( N, K, n )\n    Returns a function for evaluating the quantile function of a hypergeometric\n    distribution with population size `N`, subpopulation size `K`, and number of\n    draws `n`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.hypergeometric.quantile.factory( 100, 20, 10 );\n    > var y = myQuantile( 0.2 )\n    1\n    > y = myQuantile( 0.9 )\n    4","base.dists.hypergeometric.skewness":"\nbase.dists.hypergeometric.skewness( N, K, n )\n    Returns the skewness of a hypergeometric distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a population size `N`, subpopulation size `K` or draws `n` which\n    is not a nonnegative integer, the function returns `NaN`.\n\n    If the number of draws `n` or the subpopulation size `K` exceed population\n    size `N`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.hypergeometric.skewness( 16, 11, 4 )\n    ~-0.258\n    > v = base.dists.hypergeometric.skewness( 4, 2, 2 )\n    0.0\n\n    > v = base.dists.hypergeometric.skewness( 10, 5, 12 )\n    NaN\n    > v = base.dists.hypergeometric.skewness( 10.3, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.skewness( 10, 5.5, 4 )\n    NaN\n    > v = base.dists.hypergeometric.skewness( 10, 5, 4.5 )\n    NaN\n\n    > v = base.dists.hypergeometric.skewness( NaN, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.skewness( 20, NaN, 4 )\n    NaN\n    > v = base.dists.hypergeometric.skewness( 20, 10, NaN )\n    NaN\n\n","base.dists.hypergeometric.stdev":"\nbase.dists.hypergeometric.stdev( N, K, n )\n    Returns the standard deviation of a hypergeometric distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a population size `N`, subpopulation size `K` or draws `n` which\n    is not a nonnegative integer, the function returns `NaN`.\n\n    If the number of draws `n` or the subpopulation size `K` exceed population\n    size `N`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.hypergeometric.stdev( 16, 11, 4 )\n    ~0.829\n    > v = base.dists.hypergeometric.stdev( 2, 1, 1 )\n    0.5\n\n    > v = base.dists.hypergeometric.stdev( 10, 5, 12 )\n    NaN\n    > v = base.dists.hypergeometric.stdev( 10.3, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.stdev( 10, 5.5, 4 )\n    NaN\n    > v = base.dists.hypergeometric.stdev( 10, 5, 4.5 )\n    NaN\n\n    > v = base.dists.hypergeometric.stdev( NaN, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.stdev( 20, NaN, 4 )\n    NaN\n    > v = base.dists.hypergeometric.stdev( 20, 10, NaN )\n    NaN\n\n","base.dists.hypergeometric.variance":"\nbase.dists.hypergeometric.variance( N, K, n )\n    Returns the variance of a hypergeometric distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a population size `N`, subpopulation size `K` or draws `n` which\n    is not a nonnegative integer, the function returns `NaN`.\n\n    If the number of draws `n` or the subpopulation size `K` exceed population\n    size `N`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.hypergeometric.variance( 16, 11, 4 )\n    ~0.688\n    > v = base.dists.hypergeometric.variance( 2, 1, 1 )\n    0.25\n\n    > v = base.dists.hypergeometric.variance( 10, 5, 12 )\n    NaN\n    > v = base.dists.hypergeometric.variance( 10.3, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.variance( 10, 5.5, 4 )\n    NaN\n    > v = base.dists.hypergeometric.variance( 10, 5, 4.5 )\n    NaN\n\n    > v = base.dists.hypergeometric.variance( NaN, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.variance( 20, NaN, 4 )\n    NaN\n    > v = base.dists.hypergeometric.variance( 20, 10, NaN )\n    NaN\n\n","base.dists.invgamma.cdf":"\nbase.dists.invgamma.cdf( x, α, β )\n    Evaluates the cumulative distribution function (CDF) for an inverse gamma\n    distribution with shape parameter `α` and scale parameter `β` at a value\n    `x`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.invgamma.cdf( 2.0, 1.0, 1.0 )\n    ~0.607\n    > y = base.dists.invgamma.cdf( 2.0, 3.0, 1.0 )\n    ~0.986\n    > y = base.dists.invgamma.cdf( -1.0, 2.0, 2.0 )\n    0.0\n    > y = base.dists.invgamma.cdf( PINF, 4.0, 2.0 )\n    1.0\n    > y = base.dists.invgamma.cdf( NINF, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.invgamma.cdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.invgamma.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.invgamma.cdf( 0.0, 0.0, NaN )\n    NaN\n\n    > y = base.dists.invgamma.cdf( 2.0, -1.0, 1.0 )\n    NaN\n    > y = base.dists.invgamma.cdf( 2.0, 1.0, -1.0 )\n    NaN\n\n\nbase.dists.invgamma.cdf.factory( α, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an inverse gamma distribution with shape parameter `α` and scale\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.invgamma.cdf.factory( 2.0, 0.5 );\n    > var y = myCDF( 0.5 )\n    ~0.736\n    > y = myCDF( 2.0 )\n    ~0.974\n\n","base.dists.invgamma.cdf.factory":"\nbase.dists.invgamma.cdf.factory( α, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an inverse gamma distribution with shape parameter `α` and scale\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.invgamma.cdf.factory( 2.0, 0.5 );\n    > var y = myCDF( 0.5 )\n    ~0.736\n    > y = myCDF( 2.0 )\n    ~0.974","base.dists.invgamma.entropy":"\nbase.dists.invgamma.entropy( α, β )\n    Returns the differential entropy of an inverse gamma distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.invgamma.entropy( 1.0, 1.0 )\n    ~2.154\n    > v = base.dists.invgamma.entropy( 4.0, 12.0 )\n    ~1.996\n    > v = base.dists.invgamma.entropy( 8.0, 2.0 )\n    ~-0.922\n\n","base.dists.invgamma.InvGamma":"\nbase.dists.invgamma.InvGamma( [α, β] )\n    Returns an inverse gamma distribution object.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n    β: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    invgamma: Object\n        Distribution instance.\n\n    invgamma.alpha: number\n        Shape parameter. If set, the value must be greater than `0`.\n\n    invgamma.beta: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    invgamma.entropy: number\n        Read-only property which returns the differential entropy.\n\n    invgamma.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    invgamma.mean: number\n        Read-only property which returns the expected value.\n\n    invgamma.mode: number\n        Read-only property which returns the mode.\n\n    invgamma.skewness: number\n        Read-only property which returns the skewness.\n\n    invgamma.stdev: number\n        Read-only property which returns the standard deviation.\n\n    invgamma.variance: number\n        Read-only property which returns the variance.\n\n    invgamma.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    invgamma.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    invgamma.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    invgamma.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var invgamma = base.dists.invgamma.InvGamma( 6.0, 5.0 );\n    > invgamma.alpha\n    6.0\n    > invgamma.beta\n    5.0\n    > invgamma.entropy\n    ~0.454\n    > invgamma.kurtosis\n    19.0\n    > invgamma.mean\n    1.0\n    > invgamma.mode\n    ~0.714\n    > invgamma.skewness\n    ~2.667\n    > invgamma.stdev\n    0.5\n    > invgamma.variance\n    0.25\n    > invgamma.cdf( 0.8 )\n    ~0.406\n    > invgamma.pdf( 1.0 )\n    ~0.877\n    > invgamma.logpdf( 1.0 )\n    ~-0.131\n    > invgamma.quantile( 0.8 )\n    ~1.281\n\n","base.dists.invgamma.kurtosis":"\nbase.dists.invgamma.kurtosis( α, β )\n    Returns the excess kurtosis of an inverse gamma distribution.\n\n    If `α <= 4` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.invgamma.kurtosis( 7.0, 5.0 )\n    12.0\n    > v = base.dists.invgamma.kurtosis( 6.0, 12.0 )\n    19.0\n    > v = base.dists.invgamma.kurtosis( 8.0, 2.0 )\n    ~8.7\n\n","base.dists.invgamma.logpdf":"\nbase.dists.invgamma.logpdf( x, α, β )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for an inverse gamma distribution with shape parameter `α` and scale\n    parameter `β` at a value `x`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.invgamma.logpdf( 2.0, 0.5, 1.0 )\n    ~-2.112\n    > y = base.dists.invgamma.logpdf( 0.2, 1.0, 1.0 )\n    ~-1.781\n    > y = base.dists.invgamma.logpdf( -1.0, 4.0, 2.0 )\n    -Infinity\n\n    > y = base.dists.invgamma.logpdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.invgamma.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.invgamma.logpdf( 0.0, 1.0, NaN )\n    NaN\n\n    // Negative shape parameter:\n    > y = base.dists.invgamma.logpdf( 2.0, -1.0, 1.0 )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.invgamma.logpdf( 2.0, 1.0, -1.0 )\n    NaN\n\n\nbase.dists.invgamma.logpdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) for an inverse gamma distribution with shape\n    parameter `α` and scale parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.invgamma.logpdf.factory( 6.0, 7.0 );\n    > var y = mylogPDF( 2.0 )\n    ~-1.464\n\n","base.dists.invgamma.logpdf.factory":"\nbase.dists.invgamma.logpdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) for an inverse gamma distribution with shape\n    parameter `α` and scale parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.invgamma.logpdf.factory( 6.0, 7.0 );\n    > var y = mylogPDF( 2.0 )\n    ~-1.464","base.dists.invgamma.mean":"\nbase.dists.invgamma.mean( α, β )\n    Returns the expected value of an inverse gamma distribution.\n\n    If `α <= 1` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.invgamma.mean( 4.0, 12.0 )\n    4.0\n    > v = base.dists.invgamma.mean( 8.0, 2.0 )\n    ~0.286\n\n","base.dists.invgamma.mode":"\nbase.dists.invgamma.mode( α, β )\n    Returns the mode of an inverse gamma distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.invgamma.mode( 1.0, 1.0 )\n    0.5\n    > v = base.dists.invgamma.mode( 4.0, 12.0 )\n    2.4\n    > v = base.dists.invgamma.mode( 8.0, 2.0 )\n    ~0.222\n\n","base.dists.invgamma.pdf":"\nbase.dists.invgamma.pdf( x, α, β )\n    Evaluates the probability density function (PDF) for an inverse gamma\n    distribution with shape parameter `α` and scale parameter `β` at a value\n    `x`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.invgamma.pdf( 2.0, 0.5, 1.0 )\n    ~0.121\n    > y = base.dists.invgamma.pdf( 0.2, 1.0, 1.0 )\n    ~0.168\n    > y = base.dists.invgamma.pdf( -1.0, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.invgamma.pdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.invgamma.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.invgamma.pdf( 0.0, 1.0, NaN )\n    NaN\n\n    // Negative shape parameter:\n    > y = base.dists.invgamma.pdf( 2.0, -1.0, 1.0 )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.invgamma.pdf( 2.0, 1.0, -1.0 )\n    NaN\n\n\nbase.dists.invgamma.pdf.factory( α, β )\n    Returns a function for evaluating the probability density function (PDF)\n    of an inverse gamma distribution with shape parameter `α` and scale\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.invgamma.pdf.factory( 6.0, 7.0 );\n    > var y = myPDF( 2.0 )\n    ~0.231\n\n","base.dists.invgamma.pdf.factory":"\nbase.dists.invgamma.pdf.factory( α, β )\n    Returns a function for evaluating the probability density function (PDF)\n    of an inverse gamma distribution with shape parameter `α` and scale\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.invgamma.pdf.factory( 6.0, 7.0 );\n    > var y = myPDF( 2.0 )\n    ~0.231","base.dists.invgamma.quantile":"\nbase.dists.invgamma.quantile( p, α, β )\n    Evaluates the quantile function for an inverse gamma distribution with shape\n    parameter `α` and scale parameter `β` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.invgamma.quantile( 0.8, 2.0, 1.0 )\n    ~1.213\n    > y = base.dists.invgamma.quantile( 0.5, 4.0, 2.0 )\n    ~0.545\n    > y = base.dists.invgamma.quantile( 1.1, 1.0, 1.0 )\n    NaN\n    > y = base.dists.invgamma.quantile( -0.2, 1.0, 1.0 )\n    NaN\n\n    > y = base.dists.invgamma.quantile( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.invgamma.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.invgamma.quantile( 0.0, 1.0, NaN )\n    NaN\n\n    // Non-positive shape parameter:\n    > y = base.dists.invgamma.quantile( 0.5, -1.0, 1.0 )\n    NaN\n\n    // Non-positive rate parameter:\n    > y = base.dists.invgamma.quantile( 0.5, 1.0, -1.0 )\n    NaN\n\n\nbase.dists.invgamma.quantile.factory( α, β )\n    Returns a function for evaluating the quantile function of an inverse gamma\n    distribution with shape parameter `α` and scale parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.invgamma.quantile.factory( 2.0, 2.0 );\n    > var y = myQuantile( 0.8 )\n    ~2.426\n    > y = myQuantile( 0.4 )\n    ~0.989\n\n","base.dists.invgamma.quantile.factory":"\nbase.dists.invgamma.quantile.factory( α, β )\n    Returns a function for evaluating the quantile function of an inverse gamma\n    distribution with shape parameter `α` and scale parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.invgamma.quantile.factory( 2.0, 2.0 );\n    > var y = myQuantile( 0.8 )\n    ~2.426\n    > y = myQuantile( 0.4 )\n    ~0.989","base.dists.invgamma.skewness":"\nbase.dists.invgamma.skewness( α, β )\n    Returns the skewness of an inverse gamma distribution.\n\n    If `α <= 3` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.invgamma.skewness( 4.0, 12.0 )\n    ~5.657\n    > v = base.dists.invgamma.skewness( 8.0, 2.0 )\n    ~1.96\n\n","base.dists.invgamma.stdev":"\nbase.dists.invgamma.stdev( α, β )\n    Returns the standard deviation of an inverse gamma distribution.\n\n    If `α <= 2` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.invgamma.stdev( 5.0, 7.0 )\n    ~1.01\n    > v = base.dists.invgamma.stdev( 4.0, 12.0 )\n    ~2.828\n    > v = base.dists.invgamma.stdev( 8.0, 2.0 )\n    ~0.117\n\n","base.dists.invgamma.variance":"\nbase.dists.invgamma.variance( α, β )\n    Returns the variance of an inverse gamma distribution.\n\n    If `α <= 2` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.invgamma.variance( 5.0, 7.0 )\n    ~1.021\n    > v = base.dists.invgamma.variance( 4.0, 12.0 )\n    8.0\n    > v = base.dists.invgamma.variance( 8.0, 2.0 )\n    ~0.014\n\n","base.dists.kumaraswamy.cdf":"\nbase.dists.kumaraswamy.cdf( x, a, b )\n    Evaluates the cumulative distribution function (CDF) for Kumaraswamy's\n    double bounded distribution with first shape parameter `a` and second shape\n    parameter `b` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.kumaraswamy.cdf( 0.5, 1.0, 1.0 )\n    ~0.5\n    > y = base.dists.kumaraswamy.cdf( 0.5, 2.0, 4.0 )\n    ~0.684\n    > y = base.dists.kumaraswamy.cdf( 0.2, 2.0, 2.0 )\n    ~0.078\n    > y = base.dists.kumaraswamy.cdf( 0.8, 4.0, 4.0 )\n    ~0.878\n    > y = base.dists.kumaraswamy.cdf( -0.5, 4.0, 2.0 )\n    0.0\n    > y = base.dists.kumaraswamy.cdf( 1.5, 4.0, 2.0 )\n    1.0\n\n    > y = base.dists.kumaraswamy.cdf( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.kumaraswamy.cdf( 2.0, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.kumaraswamy.cdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.kumaraswamy.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.kumaraswamy.cdf( 0.0, 1.0, NaN )\n    NaN\n\n\nbase.dists.kumaraswamy.cdf.factory( a, b )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Kumaraswamy's double bounded distribution with first shape parameter\n    `a` and second shape parameter `b`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.kumaraswamy.cdf.factory( 0.5, 1.0 );\n    > var y = mycdf( 0.8 )\n    ~0.894\n    > y = mycdf( 0.3 )\n    ~0.548\n\n","base.dists.kumaraswamy.cdf.factory":"\nbase.dists.kumaraswamy.cdf.factory( a, b )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Kumaraswamy's double bounded distribution with first shape parameter\n    `a` and second shape parameter `b`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.kumaraswamy.cdf.factory( 0.5, 1.0 );\n    > var y = mycdf( 0.8 )\n    ~0.894\n    > y = mycdf( 0.3 )\n    ~0.548","base.dists.kumaraswamy.Kumaraswamy":"\nbase.dists.kumaraswamy.Kumaraswamy( [a, b] )\n    Returns a Kumaraswamy's double bounded distribution object.\n\n    Parameters\n    ----------\n    a: number (optional)\n        First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n    b: number (optional)\n        Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    kumaraswamy: Object\n        Distribution instance.\n\n    kumaraswamy.a: number\n        First shape parameter. If set, the value must be greater than `0`.\n\n    kumaraswamy.b: number\n        Second shape parameter. If set, the value must be greater than `0`.\n\n    kumaraswamy.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    kumaraswamy.mean: number\n        Read-only property which returns the expected value.\n\n    kumaraswamy.mode: number\n        Read-only property which returns the mode.\n\n    kumaraswamy.skewness: number\n        Read-only property which returns the skewness.\n\n    kumaraswamy.stdev: number\n        Read-only property which returns the standard deviation.\n\n    kumaraswamy.variance: number\n        Read-only property which returns the variance.\n\n    kumaraswamy.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    kumaraswamy.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    kumaraswamy.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var kumaraswamy = base.dists.kumaraswamy.Kumaraswamy( 6.0, 5.0 );\n    > kumaraswamy.a\n    6.0\n    > kumaraswamy.b\n    5.0\n    > kumaraswamy.kurtosis\n    ~3.194\n    > kumaraswamy.mean\n    ~0.696\n    > kumaraswamy.mode\n    ~0.746\n    > kumaraswamy.skewness\n    ~-0.605\n    > kumaraswamy.stdev\n    ~0.126\n    > kumaraswamy.variance\n    ~0.016\n    > kumaraswamy.cdf( 0.8 )\n    ~0.781\n    > kumaraswamy.pdf( 1.0 )\n    ~0.0\n    > kumaraswamy.quantile( 0.8 )\n    ~0.807\n\n","base.dists.kumaraswamy.kurtosis":"\nbase.dists.kumaraswamy.kurtosis( a, b )\n    Returns the excess kurtosis of a Kumaraswamy's double bounded distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.kumaraswamy.kurtosis( 1.0, 1.0 )\n    ~1.8\n    > v = base.dists.kumaraswamy.kurtosis( 4.0, 12.0 )\n    ~2.704\n    > v = base.dists.kumaraswamy.kurtosis( 16.0, 8.0 )\n    ~4.311\n\n","base.dists.kumaraswamy.logcdf":"\nbase.dists.kumaraswamy.logcdf( x, a, b )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for Kumaraswamy's double bounded distribution with first shape\n    parameter `a` and second shape parameter `b` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.kumaraswamy.logcdf( 0.5, 1.0, 1.0 )\n    ~-0.693\n    > y = base.dists.kumaraswamy.logcdf( 0.5, 2.0, 4.0 )\n    ~-0.38\n    > y = base.dists.kumaraswamy.logcdf( 0.2, 2.0, 2.0 )\n    ~-2.546\n    > y = base.dists.kumaraswamy.logcdf( 0.8, 4.0, 4.0 )\n    ~-0.13\n    > y = base.dists.kumaraswamy.logcdf( -0.5, 4.0, 2.0 )\n    -Infinity\n    > y = base.dists.kumaraswamy.logcdf( 1.5, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.kumaraswamy.logcdf( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.kumaraswamy.logcdf( 2.0, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.kumaraswamy.logcdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.kumaraswamy.logcdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.kumaraswamy.logcdf( 0.0, 1.0, NaN )\n    NaN\n\n\nbase.dists.kumaraswamy.logcdf.factory( a, b )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Kumaraswamy's double bounded distribution\n    with first shape parameter `a` and second shape parameter `b`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.kumaraswamy.logcdf.factory( 0.5, 1.0 );\n    > var y = mylogcdf( 0.8 )\n    ~-0.112\n    > y = mylogcdf( 0.3 )\n    ~-0.602\n\n","base.dists.kumaraswamy.logcdf.factory":"\nbase.dists.kumaraswamy.logcdf.factory( a, b )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Kumaraswamy's double bounded distribution\n    with first shape parameter `a` and second shape parameter `b`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.kumaraswamy.logcdf.factory( 0.5, 1.0 );\n    > var y = mylogcdf( 0.8 )\n    ~-0.112\n    > y = mylogcdf( 0.3 )\n    ~-0.602","base.dists.kumaraswamy.logpdf":"\nbase.dists.kumaraswamy.logpdf( x, a, b )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for Kumaraswamy's double bounded distribution with first shape parameter `a`\n    and second shape parameter `b` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.kumaraswamy.logpdf( 0.5, 1.0, 1.0 )\n    0.0\n    > y = base.dists.kumaraswamy.logpdf( 0.5, 2.0, 4.0 )\n    ~0.523\n    > y = base.dists.kumaraswamy.logpdf( 0.2, 2.0, 2.0 )\n    ~-0.264\n    > y = base.dists.kumaraswamy.logpdf( 0.8, 4.0, 4.0 )\n    ~0.522\n    > y = base.dists.kumaraswamy.logpdf( -0.5, 4.0, 2.0 )\n    -Infinity\n    > y = base.dists.kumaraswamy.logpdf( 1.5, 4.0, 2.0 )\n    -Infinity\n\n    > y = base.dists.kumaraswamy.logpdf( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.kumaraswamy.logpdf( 2.0, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.kumaraswamy.logpdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.kumaraswamy.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.kumaraswamy.logpdf( 0.0, 1.0, NaN )\n    NaN\n\n\nbase.dists.kumaraswamy.logpdf.factory( a, b )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a Kumaraswamy's double bounded distribution with\n    first shape parameter `a` and second shape parameter `b`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.kumaraswamy.logpdf.factory( 0.5, 1.0 );\n    > var y = mylogpdf( 0.8 )\n    ~-0.582\n    > y = mylogpdf( 0.3 )\n    ~-0.091\n\n","base.dists.kumaraswamy.logpdf.factory":"\nbase.dists.kumaraswamy.logpdf.factory( a, b )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a Kumaraswamy's double bounded distribution with\n    first shape parameter `a` and second shape parameter `b`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.kumaraswamy.logpdf.factory( 0.5, 1.0 );\n    > var y = mylogpdf( 0.8 )\n    ~-0.582\n    > y = mylogpdf( 0.3 )\n    ~-0.091","base.dists.kumaraswamy.mean":"\nbase.dists.kumaraswamy.mean( a, b )\n    Returns the mean of a Kumaraswamy's double bounded distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Mean.\n\n    Examples\n    --------\n    > var v = base.dists.kumaraswamy.mean( 1.5, 1.5 )\n    ~0.512\n    > v = base.dists.kumaraswamy.mean( 4.0, 12.0 )\n    ~0.481\n    > v = base.dists.kumaraswamy.mean( 16.0, 8.0 )\n    ~0.846\n\n","base.dists.kumaraswamy.median":"\nbase.dists.kumaraswamy.median( a, b )\n    Returns the median of a Kumaraswamy's double bounded distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.kumaraswamy.median( 1.0, 1.0 )\n    0.5\n    > v = base.dists.kumaraswamy.median( 4.0, 12.0 )\n    ~0.487\n    > v = base.dists.kumaraswamy.median( 16.0, 8.0 )\n    ~0.856\n\n","base.dists.kumaraswamy.mode":"\nbase.dists.kumaraswamy.mode( a, b )\n    Returns the mode of a Kumaraswamy's double bounded distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a < 1`, `b < 1`, or `a = b = 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.kumaraswamy.mode( 1.5, 1.5 )\n    ~0.543\n    > v = base.dists.kumaraswamy.mode( 4.0, 12.0 )\n    ~0.503\n    > v = base.dists.kumaraswamy.mode( 16.0, 8.0 )\n    ~0.875\n\n","base.dists.kumaraswamy.pdf":"\nbase.dists.kumaraswamy.pdf( x, a, b )\n    Evaluates the probability density function (PDF) for Kumaraswamy's double\n    bounded distribution with first shape parameter `a` and second shape\n    parameter `b` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.kumaraswamy.pdf( 0.5, 1.0, 1.0 )\n    1.0\n    > y = base.dists.kumaraswamy.pdf( 0.5, 2.0, 4.0 )\n    ~1.688\n    > y = base.dists.kumaraswamy.pdf( 0.2, 2.0, 2.0 )\n    ~0.768\n    > y = base.dists.kumaraswamy.pdf( 0.8, 4.0, 4.0 )\n    ~1.686\n    > y = base.dists.kumaraswamy.pdf( -0.5, 4.0, 2.0 )\n    0.0\n    > y = base.dists.kumaraswamy.pdf( 1.5, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.kumaraswamy.pdf( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.kumaraswamy.pdf( 2.0, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.kumaraswamy.pdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.kumaraswamy.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.kumaraswamy.pdf( 0.0, 1.0, NaN )\n    NaN\n\n\nbase.dists.kumaraswamy.pdf.factory( a, b )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Kumaraswamy's double bounded distribution with first shape parameter\n    `a` and second shape parameter `b`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var mypdf = base.dists.kumaraswamy.pdf.factory( 0.5, 1.0 );\n    > var y = mypdf( 0.8 )\n    ~0.559\n    > y = mypdf( 0.3 )\n    ~0.913\n\n","base.dists.kumaraswamy.pdf.factory":"\nbase.dists.kumaraswamy.pdf.factory( a, b )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Kumaraswamy's double bounded distribution with first shape parameter\n    `a` and second shape parameter `b`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var mypdf = base.dists.kumaraswamy.pdf.factory( 0.5, 1.0 );\n    > var y = mypdf( 0.8 )\n    ~0.559\n    > y = mypdf( 0.3 )\n    ~0.913","base.dists.kumaraswamy.quantile":"\nbase.dists.kumaraswamy.quantile( p, a, b )\n    Evaluates the quantile function for a Kumaraswamy's double bounded\n    distribution with first shape parameter `a` and second shape parameter `b`\n    at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.kumaraswamy.quantile( 0.5, 1.0, 1.0 )\n    0.5\n    > y = base.dists.kumaraswamy.quantile( 0.5, 2.0, 4.0 )\n    ~0.399\n    > y = base.dists.kumaraswamy.quantile( 0.2, 2.0, 2.0 )\n    ~0.325\n    > y = base.dists.kumaraswamy.quantile( 0.8, 4.0, 4.0 )\n    ~0.759\n\n    > y = base.dists.kumaraswamy.quantile( -0.5, 4.0, 2.0 )\n    NaN\n    > y = base.dists.kumaraswamy.quantile( 1.5, 4.0, 2.0 )\n    NaN\n\n    > y = base.dists.kumaraswamy.quantile( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.kumaraswamy.quantile( 2.0, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.kumaraswamy.quantile( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.kumaraswamy.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.kumaraswamy.quantile( 0.0, 1.0, NaN )\n    NaN\n\n\nbase.dists.kumaraswamy.quantile.factory( a, b )\n    Returns a function for evaluating the quantile function of a Kumaraswamy's\n    double bounded distribution with first shape parameter `a` and second shape\n    parameter `b`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.kumaraswamy.quantile.factory( 0.5, 1.0 );\n    > var y = myQuantile( 0.8 )\n    ~0.64\n    > y = myQuantile( 0.3 )\n    ~0.09\n\n","base.dists.kumaraswamy.quantile.factory":"\nbase.dists.kumaraswamy.quantile.factory( a, b )\n    Returns a function for evaluating the quantile function of a Kumaraswamy's\n    double bounded distribution with first shape parameter `a` and second shape\n    parameter `b`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.kumaraswamy.quantile.factory( 0.5, 1.0 );\n    > var y = myQuantile( 0.8 )\n    ~0.64\n    > y = myQuantile( 0.3 )\n    ~0.09","base.dists.kumaraswamy.skewness":"\nbase.dists.kumaraswamy.skewness( a, b )\n    Returns the skewness of a Kumaraswamy's double bounded distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.kumaraswamy.skewness( 1.0, 1.0 )\n    ~1.154e-15\n    > v = base.dists.kumaraswamy.skewness( 4.0, 12.0 )\n    ~-0.201\n    > v = base.dists.kumaraswamy.skewness( 16.0, 8.0 )\n    ~-0.94\n\n","base.dists.kumaraswamy.stdev":"\nbase.dists.kumaraswamy.stdev( a, b )\n    Returns the standard deviation of a Kumaraswamy's double bounded\n    distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.kumaraswamy.stdev( 1.0, 1.0 )\n    ~0.289\n    > v = base.dists.kumaraswamy.stdev( 4.0, 12.0 )\n    ~0.13\n    > v = base.dists.kumaraswamy.stdev( 16.0, 8.0 )\n    ~0.062\n\n","base.dists.kumaraswamy.variance":"\nbase.dists.kumaraswamy.variance( a, b )\n    Returns the variance of a Kumaraswamy's double bounded distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.kumaraswamy.variance( 1.0, 1.0 )\n    ~0.083\n    > v = base.dists.kumaraswamy.variance( 4.0, 12.0 )\n    ~0.017\n    > v = base.dists.kumaraswamy.variance( 16.0, 8.0 )\n    ~0.004\n\n","base.dists.laplace.cdf":"\nbase.dists.laplace.cdf( x, μ, b )\n    Evaluates the cumulative distribution function (CDF) for a Laplace\n    distribution with scale parameter `b` and location parameter `μ` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.cdf( 2.0, 0.0, 1.0 )\n    ~0.932\n    > y = base.dists.laplace.cdf( 5.0, 10.0, 3.0 )\n    ~0.094\n    > y = base.dists.laplace.cdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.laplace.cdf( 2, NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.cdf( 2.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.laplace.cdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.laplace.cdf.factory( μ, b )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Laplace distribution with scale parameter `b` and location parameter\n    `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.laplace.cdf.factory( 2.0, 3.0 );\n    > var y = myCDF( 10.0 )\n    ~0.965\n    > y = myCDF( 2.0 )\n    0.5\n\n","base.dists.laplace.cdf.factory":"\nbase.dists.laplace.cdf.factory( μ, b )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Laplace distribution with scale parameter `b` and location parameter\n    `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.laplace.cdf.factory( 2.0, 3.0 );\n    > var y = myCDF( 10.0 )\n    ~0.965\n    > y = myCDF( 2.0 )\n    0.5","base.dists.laplace.entropy":"\nbase.dists.laplace.entropy( μ, b )\n    Returns the differential entropy of a Laplace distribution with location\n    parameter `μ` and scale parameter `b`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Differential entropy.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.entropy( 0.0, 1.0 )\n    ~1.693\n    > y = base.dists.laplace.entropy( 4.0, 2.0 )\n    ~2.386\n    > y = base.dists.laplace.entropy( NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.entropy( 0.0, NaN )\n    NaN\n    > y = base.dists.laplace.entropy( 0.0, 0.0 )\n    NaN\n\n","base.dists.laplace.kurtosis":"\nbase.dists.laplace.kurtosis( μ, b )\n    Returns the excess kurtosis of a Laplace distribution with location\n    parameter `μ` and scale parameter `b`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.kurtosis( 0.0, 1.0 )\n    3.0\n    > y = base.dists.laplace.kurtosis( 4.0, 2.0 )\n    3.0\n    > y = base.dists.laplace.kurtosis( NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.kurtosis( 0.0, NaN )\n    NaN\n    > y = base.dists.laplace.kurtosis( 0.0, 0.0 )\n    NaN\n\n","base.dists.laplace.Laplace":"\nbase.dists.laplace.Laplace( [μ, b] )\n    Returns a Laplace distribution object.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter. Default: `0.0`.\n\n    b: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    laplace: Object\n        Distribution instance.\n\n    laplace.mu: number\n        Location parameter.\n\n    laplace.b: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    laplace.entropy: number\n        Read-only property which returns the differential entropy.\n\n    laplace.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    laplace.mean: number\n        Read-only property which returns the expected value.\n\n    laplace.median: number\n        Read-only property which returns the median.\n\n    laplace.mode: number\n        Read-only property which returns the mode.\n\n    laplace.skewness: number\n        Read-only property which returns the skewness.\n\n    laplace.stdev: number\n        Read-only property which returns the standard deviation.\n\n    laplace.variance: number\n        Read-only property which returns the variance.\n\n    laplace.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    laplace.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    laplace.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    laplace.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    laplace.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    laplace.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var laplace = base.dists.laplace.Laplace( -2.0, 3.0 );\n    > laplace.mu\n    -2.0\n    > laplace.b\n    3.0\n    > laplace.entropy\n    ~2.792\n    > laplace.kurtosis\n    3.0\n    > laplace.mean\n    -2.0\n    > laplace.median\n    -2.0\n    > laplace.mode\n    -2.0\n    > laplace.skewness\n    0.0\n    > laplace.stdev\n    ~4.243\n    > laplace.variance\n    18.0\n    > laplace.cdf( 0.8 )\n    ~0.803\n    > laplace.logcdf( 0.8 )\n    ~-0.219\n    > laplace.logpdf( 1.0 )\n    ~-2.792\n    > laplace.mgf( 0.2 )\n    ~1.047\n    > laplace.pdf( 2.0 )\n    ~0.044\n    > laplace.quantile( 0.9 )\n    ~2.828\n\n","base.dists.laplace.logcdf":"\nbase.dists.laplace.logcdf( x, μ, b )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    Laplace distribution with scale parameter `b` and location parameter `μ` at\n    a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.logcdf( 2.0, 0.0, 1.0 )\n    ~-0.07\n    > y = base.dists.laplace.logcdf( 5.0, 10.0, 3.0 )\n    ~-2.36\n    > y = base.dists.laplace.logcdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.laplace.logcdf( 2, NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.logcdf( 2.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.laplace.logcdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.laplace.logcdf.factory( μ, b )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Laplace distribution with scale parameter\n    `b` and location parameter `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.laplace.logcdf.factory( 2.0, 3.0 );\n    > var y = mylogcdf( 10.0 )\n    ~-0.035\n    > y = mylogcdf( 2.0 )\n    ~-0.693\n\n","base.dists.laplace.logcdf.factory":"\nbase.dists.laplace.logcdf.factory( μ, b )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Laplace distribution with scale parameter\n    `b` and location parameter `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.laplace.logcdf.factory( 2.0, 3.0 );\n    > var y = mylogcdf( 10.0 )\n    ~-0.035\n    > y = mylogcdf( 2.0 )\n    ~-0.693","base.dists.laplace.logpdf":"\nbase.dists.laplace.logpdf( x, μ, b )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    Laplace distribution with scale parameter `b` and location parameter `μ` at\n    a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.logpdf( 2.0, 0.0, 1.0 )\n    ~-2.693\n    > y = base.dists.laplace.logpdf( -1.0, 2.0, 3.0 )\n    ~-2.792\n    > y = base.dists.laplace.logpdf( 2.5, 2.0, 3.0 )\n    ~-1.958\n    > y = base.dists.laplace.logpdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.laplace.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.logpdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.laplace.logpdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.laplace.logpdf.factory( μ, b )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Laplace distribution with scale parameter `b` and\n    location parameter `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.laplace.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogPDF( 10.0 )\n    ~-1.386\n\n","base.dists.laplace.logpdf.factory":"\nbase.dists.laplace.logpdf.factory( μ, b )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Laplace distribution with scale parameter `b` and\n    location parameter `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.laplace.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogPDF( 10.0 )\n    ~-1.386","base.dists.laplace.mean":"\nbase.dists.laplace.mean( μ, b )\n    Returns the expected value of a Laplace distribution with location parameter\n    `μ` and scale parameter `b`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.mean( 0.0, 1.0 )\n    0.0\n    > y = base.dists.laplace.mean( 4.0, 2.0 )\n    4.0\n    > y = base.dists.laplace.mean( NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.mean( 0.0, NaN )\n    NaN\n    > y = base.dists.laplace.mean( 0.0, 0.0 )\n    NaN\n\n","base.dists.laplace.median":"\nbase.dists.laplace.median( μ, b )\n    Returns the median of a Laplace distribution with location parameter `μ` and\n    scale parameter `b`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.median( 0.0, 1.0 )\n    0.0\n    > y = base.dists.laplace.median( 4.0, 2.0 )\n    4.0\n    > y = base.dists.laplace.median( NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.median( 0.0, NaN )\n    NaN\n    > y = base.dists.laplace.median( 0.0, 0.0 )\n    NaN\n\n","base.dists.laplace.mgf":"\nbase.dists.laplace.mgf( t, μ, b )\n    Evaluates the moment-generating function (MGF) for a Laplace\n    distribution with scale parameter `b` and location parameter `μ` at a\n    value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.mgf( 0.5, 0.0, 1.0 )\n    ~1.333\n    > y = base.dists.laplace.mgf( 0.0, 0.0, 1.0 )\n    1.0\n    > y = base.dists.laplace.mgf( -1.0, 4.0, 0.2 )\n    ~0.019\n    > y = base.dists.laplace.mgf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.laplace.mgf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.mgf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.laplace.mgf( 1.0, 0.0, 2.0 )\n    NaN\n    > y = base.dists.laplace.mgf( -0.5, 0.0, 4.0 )\n    NaN\n    > y = base.dists.laplace.mgf( 2.0, 0.0, 0.0 )\n    NaN\n    > y = base.dists.laplace.mgf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.laplace.mgf.factory( μ, b )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a Laplace distribution with scale parameter `b` and location parameter\n    `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.laplace.mgf.factory( 4.0, 2.0 );\n    > var y = mymgf( 0.2 )\n    ~2.649\n    > y = mymgf( 0.4 )\n    ~13.758\n\n","base.dists.laplace.mgf.factory":"\nbase.dists.laplace.mgf.factory( μ, b )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a Laplace distribution with scale parameter `b` and location parameter\n    `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.laplace.mgf.factory( 4.0, 2.0 );\n    > var y = mymgf( 0.2 )\n    ~2.649\n    > y = mymgf( 0.4 )\n    ~13.758","base.dists.laplace.mode":"\nbase.dists.laplace.mode( μ, b )\n    Returns the mode of a Laplace distribution with location parameter `μ` and\n    scale parameter `b`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.mode( 0.0, 1.0 )\n    0.0\n    > y = base.dists.laplace.mode( 4.0, 2.0 )\n    4.0\n    > y = base.dists.laplace.mode( NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.mode( 0.0, NaN )\n    NaN\n    > y = base.dists.laplace.mode( 0.0, 0.0 )\n    NaN\n\n","base.dists.laplace.pdf":"\nbase.dists.laplace.pdf( x, μ, b )\n    Evaluates the probability density function (PDF) for a Laplace\n    distribution with scale parameter `b` and location parameter `μ` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.pdf( 2.0, 0.0, 1.0 )\n    ~0.068\n    > y = base.dists.laplace.pdf( -1.0, 2.0, 3.0 )\n    ~0.061\n    > y = base.dists.laplace.pdf( 2.5, 2.0, 3.0 )\n    ~0.141\n    > y = base.dists.laplace.pdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.laplace.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.pdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.laplace.pdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.laplace.pdf.factory( μ, b )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Laplace distribution with scale parameter `b` and location parameter\n    `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.laplace.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    0.25\n\n","base.dists.laplace.pdf.factory":"\nbase.dists.laplace.pdf.factory( μ, b )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Laplace distribution with scale parameter `b` and location parameter\n    `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.laplace.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    0.25","base.dists.laplace.quantile":"\nbase.dists.laplace.quantile( p, μ, b )\n    Evaluates the quantile function for a Laplace distribution with scale\n    parameter `b` and location parameter `μ` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.quantile( 0.8, 0.0, 1.0 )\n    ~0.916\n    > y = base.dists.laplace.quantile( 0.5, 4.0, 2.0 )\n    4.0\n\n    > y = base.dists.laplace.quantile( 1.1, 0.0, 1.0 )\n    NaN\n    > y = base.dists.laplace.quantile( -0.2, 0.0, 1.0 )\n    NaN\n\n    > y = base.dists.laplace.quantile( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.laplace.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.quantile( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.laplace.quantile( 0.5, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.laplace.quantile.factory( μ, b )\n    Returns a function for evaluating the quantile function of a Laplace\n    distribution with scale parameter `b` and location parameter `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.laplace.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    10.0\n    > y = myQuantile( 0.8 )\n    ~11.833\n\n","base.dists.laplace.quantile.factory":"\nbase.dists.laplace.quantile.factory( μ, b )\n    Returns a function for evaluating the quantile function of a Laplace\n    distribution with scale parameter `b` and location parameter `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.laplace.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    10.0\n    > y = myQuantile( 0.8 )\n    ~11.833","base.dists.laplace.skewness":"\nbase.dists.laplace.skewness( μ, b )\n    Returns the skewness of a Laplace distribution with location parameter `μ`\n    and scale parameter `b`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.skewness( 0.0, 1.0 )\n    0.0\n    > y = base.dists.laplace.skewness( 4.0, 2.0 )\n    0.0\n    > y = base.dists.laplace.skewness( NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.skewness( 0.0, NaN )\n    NaN\n    > y = base.dists.laplace.skewness( 0.0, 0.0 )\n    NaN\n\n","base.dists.laplace.stdev":"\nbase.dists.laplace.stdev( μ, b )\n    Returns the standard deviation of a Laplace distribution with location\n    parameter `μ` and scale parameter `b`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.stdev( 0.0, 1.0 )\n    ~1.414\n    > y = base.dists.laplace.stdev( 4.0, 2.0 )\n    ~2.828\n    > y = base.dists.laplace.stdev( NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.stdev( 0.0, NaN )\n    NaN\n    > y = base.dists.laplace.stdev( 0.0, 0.0 )\n    NaN\n\n","base.dists.laplace.variance":"\nbase.dists.laplace.variance( μ, b )\n    Returns the variance of a Laplace distribution with location parameter `μ`\n    and scale parameter `b`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.variance( 0.0, 1.0 )\n    2.0\n    > y = base.dists.laplace.variance( 4.0, 2.0 )\n    8.0\n    > y = base.dists.laplace.variance( NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.variance( 0.0, NaN )\n    NaN\n    > y = base.dists.laplace.variance( 0.0, 0.0 )\n    NaN\n\n","base.dists.levy.cdf":"\nbase.dists.levy.cdf( x, μ, c )\n    Evaluates the cumulative distribution function (CDF) for a Lévy distribution\n    with location parameter `μ` and scale parameter `c` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.levy.cdf( 2.0, 0.0, 1.0 )\n    ~0.48\n    > y = base.dists.levy.cdf( 12.0, 10.0, 3.0 )\n    ~0.221\n    > y = base.dists.levy.cdf( 9.0, 10.0, 3.0 )\n    0.0\n    > y = base.dists.levy.cdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.levy.cdf( 2, NaN, 1.0 )\n    NaN\n    > y = base.dists.levy.cdf( 2.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.levy.cdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.levy.cdf.factory( μ, c )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.levy.cdf.factory( 2.0, 3.0 );\n    > var y = myCDF( 10.0 )\n    ~0.54\n    > y = myCDF( 2.0 )\n    0.0\n\n","base.dists.levy.cdf.factory":"\nbase.dists.levy.cdf.factory( μ, c )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.levy.cdf.factory( 2.0, 3.0 );\n    > var y = myCDF( 10.0 )\n    ~0.54\n    > y = myCDF( 2.0 )\n    0.0","base.dists.levy.entropy":"\nbase.dists.levy.entropy( μ, c )\n    Returns the entropy of a Lévy distribution with location parameter `μ` and\n    scale parameter `c`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var y = base.dists.levy.entropy( 0.0, 1.0 )\n    ~3.324\n    > y = base.dists.levy.entropy( 4.0, 2.0 )\n    ~4.018\n    > y = base.dists.levy.entropy( NaN, 1.0 )\n    NaN\n    > y = base.dists.levy.entropy( 0.0, NaN )\n    NaN\n    > y = base.dists.levy.entropy( 0.0, 0.0 )\n    NaN\n\n","base.dists.levy.Levy":"\nbase.dists.levy.Levy( [μ, c] )\n    Returns a Lévy distribution object.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter. Default: `0.0`.\n\n    c: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    levy: Object\n        Distribution instance.\n\n    levy.mu: number\n        Location parameter.\n\n    levy.c: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    levy.entropy: number\n        Read-only property which returns the differential entropy.\n\n    levy.mean: number\n        Read-only property which returns the expected value.\n\n    levy.median: number\n        Read-only property which returns the median.\n\n    levy.mode: number\n        Read-only property which returns the mode.\n\n    levy.stdev: number\n        Read-only property which returns the standard deviation.\n\n    levy.variance: number\n        Read-only property which returns the variance.\n\n    levy.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    levy.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    levy.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    levy.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    levy.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var levy = base.dists.levy.Levy( -2.0, 3.0 );\n    > levy.mu\n    -2.0\n    > levy.c\n    3.0\n    > levy.entropy\n    ~4.423\n    > levy.mean\n    Infinity\n    > levy.median\n    ~4.594\n    > levy.mode\n    -1.0\n    > levy.stdev\n    Infinity\n    > levy.variance\n    Infinity\n    > levy.cdf( 0.8 )\n    ~0.3\n    > levy.logcdf( 0.8 )\n    ~-1.2\n    > levy.logpdf( 1.0 )\n    ~-2.518\n    > levy.pdf( 1.0 )\n    ~0.081\n    > levy.quantile( 0.8 )\n    ~44.74\n\n","base.dists.levy.logcdf":"\nbase.dists.levy.logcdf( x, μ, c )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    Lévy distribution with location parameter `μ` and scale parameter `c` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.levy.logcdf( 2.0, 0.0, 1.0 )\n    ~-0.735\n    > y = base.dists.levy.logcdf( 12.0, 10.0, 3.0 )\n    ~-1.51\n    > y = base.dists.levy.logcdf( 9.0, 10.0, 3.0 )\n    -Infinity\n    > y = base.dists.levy.logcdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.levy.logcdf( 2, NaN, 1.0 )\n    NaN\n    > y = base.dists.levy.logcdf( 2.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.levy.logcdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.levy.logcdf.factory( μ, c )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Lévy distribution with location parameter\n    `μ` and scale parameter `c`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.levy.logcdf.factory( 2.0, 3.0 );\n    > var y = mylogcdf( 10.0 )\n    ~-0.616\n    > y = mylogcdf( 2.0 )\n    -Infinity\n\n","base.dists.levy.logcdf.factory":"\nbase.dists.levy.logcdf.factory( μ, c )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Lévy distribution with location parameter\n    `μ` and scale parameter `c`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.levy.logcdf.factory( 2.0, 3.0 );\n    > var y = mylogcdf( 10.0 )\n    ~-0.616\n    > y = mylogcdf( 2.0 )\n    -Infinity","base.dists.levy.logpdf":"\nbase.dists.levy.logpdf( x, μ, c )\n    Evaluates the logarithm of the probability density function (PDF) for a Lévy\n    distribution with location parameter `μ` and scale parameter `c` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.levy.logpdf( 2.0, 0.0, 1.0 )\n    ~-2.209\n    > y = base.dists.levy.logpdf( -1.0, 4.0, 2.0 )\n    -Infinity\n    > y = base.dists.levy.logpdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.levy.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.levy.logpdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.levy.logpdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.levy.logpdf.factory( μ, c )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Lévy distribution with location parameter `μ` and scale\n    parameter `c`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.levy.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogPDF( 11.0 )\n    ~-1.572\n\n","base.dists.levy.logpdf.factory":"\nbase.dists.levy.logpdf.factory( μ, c )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Lévy distribution with location parameter `μ` and scale\n    parameter `c`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.levy.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogPDF( 11.0 )\n    ~-1.572","base.dists.levy.mean":"\nbase.dists.levy.mean( μ, c )\n    Returns the expected value of a Lévy distribution with location parameter\n    `μ` and scale parameter `c`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var y = base.dists.levy.mean( 0.0, 1.0 )\n    Infinity\n    > y = base.dists.levy.mean( 4.0, 3.0 )\n    Infinity\n    > y = base.dists.levy.mean( NaN, 1.0 )\n    NaN\n    > y = base.dists.levy.mean( 0.0, NaN )\n    NaN\n    > y = base.dists.levy.mean( 0.0, 0.0 )\n    NaN\n\n","base.dists.levy.median":"\nbase.dists.levy.median( μ, c )\n    Returns the median of a Lévy distribution with location parameter `μ` and\n    scale parameter `c`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var y = base.dists.levy.median( 0.0, 1.0 )\n    ~2.198\n    > y = base.dists.levy.median( 4.0, 3.0 )\n    ~10.594\n    > y = base.dists.levy.median( NaN, 1.0 )\n    NaN\n    > y = base.dists.levy.median( 0.0, NaN )\n    NaN\n    > y = base.dists.levy.median( 0.0, 0.0 )\n    NaN\n\n","base.dists.levy.mode":"\nbase.dists.levy.mode( μ, c )\n    Returns the mode of a Lévy distribution with location parameter `μ` and\n    scale parameter `c`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var y = base.dists.levy.mode( 0.0, 1.0 )\n    ~0.333\n    > y = base.dists.levy.mode( 4.0, 3.0 )\n    5.0\n    > y = base.dists.levy.mode( NaN, 1.0 )\n    NaN\n    > y = base.dists.levy.mode( 0.0, NaN )\n    NaN\n    > y = base.dists.levy.mode( 0.0, 0.0 )\n    NaN\n\n","base.dists.levy.pdf":"\nbase.dists.levy.pdf( x, μ, c )\n    Evaluates the probability density function (PDF) for a Lévy distribution\n    with location parameter `μ` and scale parameter `c` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.levy.pdf( 2.0, 0.0, 1.0 )\n    ~0.11\n    > y = base.dists.levy.pdf( -1.0, 4.0, 2.0 )\n    0.0\n    > y = base.dists.levy.pdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.levy.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.levy.pdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.levy.pdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.levy.pdf.factory( μ, c )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.levy.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 11.0 )\n    ~0.208\n\n","base.dists.levy.pdf.factory":"\nbase.dists.levy.pdf.factory( μ, c )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.levy.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 11.0 )\n    ~0.208","base.dists.levy.quantile":"\nbase.dists.levy.quantile( p, μ, c )\n    Evaluates the quantile function for a Lévy distribution with location\n    parameter `μ` and scale parameter `c` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.levy.quantile( 0.8, 0.0, 1.0 )\n    ~15.58\n    > y = base.dists.levy.quantile( 0.5, 4.0, 2.0 )\n    ~8.396\n\n    > y = base.dists.levy.quantile( 1.1, 0.0, 1.0 )\n    NaN\n    > y = base.dists.levy.quantile( -0.2, 0.0, 1.0 )\n    NaN\n\n    > y = base.dists.levy.quantile( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.levy.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.levy.quantile( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.levy.quantile( 0.5, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.levy.quantile.factory( μ, c )\n    Returns a function for evaluating the quantile function of a Lévy\n    distribution with location parameter `μ` and scale parameter `c`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.levy.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    ~14.396\n\n","base.dists.levy.quantile.factory":"\nbase.dists.levy.quantile.factory( μ, c )\n    Returns a function for evaluating the quantile function of a Lévy\n    distribution with location parameter `μ` and scale parameter `c`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.levy.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    ~14.396","base.dists.levy.stdev":"\nbase.dists.levy.stdev( μ, c )\n    Returns the standard deviation of a Lévy distribution with location\n    parameter `μ` and scale parameter `c`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var y = base.dists.levy.stdev( 0.0, 1.0 )\n    Infinity\n    > y = base.dists.levy.stdev( 4.0, 3.0 )\n    Infinity\n    > y = base.dists.levy.stdev( NaN, 1.0 )\n    NaN\n    > y = base.dists.levy.stdev( 0.0, NaN )\n    NaN\n    > y = base.dists.levy.stdev( 0.0, 0.0 )\n    NaN\n\n","base.dists.levy.variance":"\nbase.dists.levy.variance( μ, c )\n    Returns the variance of a Lévy distribution with location parameter `μ` and\n    scale parameter `c`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var y = base.dists.levy.variance( 0.0, 1.0 )\n    Infinity\n    > y = base.dists.levy.variance( 4.0, 3.0 )\n    Infinity\n    > y = base.dists.levy.variance( NaN, 1.0 )\n    NaN\n    > y = base.dists.levy.variance( 0.0, NaN )\n    NaN\n    > y = base.dists.levy.variance( 0.0, 0.0 )\n    NaN\n\n","base.dists.logistic.cdf":"\nbase.dists.logistic.cdf( x, μ, s )\n    Evaluates the cumulative distribution function (CDF) for a logistic\n    distribution with location parameter `μ` and scale parameter `s` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.cdf( 2.0, 0.0, 1.0 )\n    ~0.881\n    > y = base.dists.logistic.cdf( 5.0, 10.0, 3.0 )\n    ~0.159\n\n    > y = base.dists.logistic.cdf( 2.0, 0.0, NaN )\n    NaN\n    > y = base.dists.logistic.cdf( 2.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.cdf( NaN, 0.0, 1.0 )\n    NaN\n\n    // Degenerate distribution centered at `μ` when `s = 0.0`:\n    > y = base.dists.logistic.cdf( 2.0, 8.0, 0.0 )\n    0.0\n    > y = base.dists.logistic.cdf( 8.0, 8.0, 0.0 )\n    1.0\n    > y = base.dists.logistic.cdf( 10.0, 8.0, 0.0 )\n    1.0\n\n\nbase.dists.logistic.cdf.factory( μ, s )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a logistic distribution with location parameter `μ` and scale parameter\n    `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.logistic.cdf.factory( 3.0, 1.5 );\n    > var y = mycdf( 1.0 )\n    ~0.209\n\n","base.dists.logistic.cdf.factory":"\nbase.dists.logistic.cdf.factory( μ, s )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a logistic distribution with location parameter `μ` and scale parameter\n    `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.logistic.cdf.factory( 3.0, 1.5 );\n    > var y = mycdf( 1.0 )\n    ~0.209","base.dists.logistic.entropy":"\nbase.dists.logistic.entropy( μ, s )\n    Returns the entropy of a logistic distribution with location parameter `μ`\n    and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.entropy( 0.0, 1.0 )\n    2.0\n    > y = base.dists.logistic.entropy( 4.0, 2.0 )\n    ~2.693\n    > y = base.dists.logistic.entropy( NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.entropy( 0.0, NaN )\n    NaN\n    > y = base.dists.logistic.entropy( 0.0, 0.0 )\n    NaN\n\n","base.dists.logistic.kurtosis":"\nbase.dists.logistic.kurtosis( μ, s )\n    Returns the excess kurtosis of a logistic distribution with location\n    parameter `μ` and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.kurtosis( 0.0, 1.0 )\n    1.2\n    > y = base.dists.logistic.kurtosis( 4.0, 2.0 )\n    1.2\n    > y = base.dists.logistic.kurtosis( NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.kurtosis( 0.0, NaN )\n    NaN\n    > y = base.dists.logistic.kurtosis( 0.0, 0.0 )\n    NaN\n\n\n","base.dists.logistic.logcdf":"\nbase.dists.logistic.logcdf( x, μ, s )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    logistic distribution with location parameter `μ` and scale parameter `s` at\n    a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.logcdf( 2.0, 0.0, 1.0 )\n    ~-0.127\n    > y = base.dists.logistic.logcdf( 5.0, 10.0, 3.0 )\n    ~-1.84\n    > y = base.dists.logistic.logcdf( 2.0, 0.0, NaN )\n    NaN\n    > y = base.dists.logistic.logcdf( 2, NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.logcdf( NaN, 0.0, 1.0 )\n    NaN\n\n\nbase.dists.logistic.logcdf.factory( μ, s )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Logistic distribution with location\n    parameter `μ` and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.logistic.logcdf.factory( 3.0, 1.5 );\n    > var y = mylogcdf( 1.0 )\n    ~-1.567\n\n","base.dists.logistic.logcdf.factory":"\nbase.dists.logistic.logcdf.factory( μ, s )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Logistic distribution with location\n    parameter `μ` and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.logistic.logcdf.factory( 3.0, 1.5 );\n    > var y = mylogcdf( 1.0 )\n    ~-1.567","base.dists.logistic.Logistic":"\nbase.dists.logistic.Logistic( [μ, s] )\n    Returns a logistic distribution object.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter. Default: `0.0`.\n\n    s: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    logistic: Object\n        Distribution instance.\n\n    logistic.mu: number\n        Location parameter.\n\n    logistic.s: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    logistic.entropy: number\n        Read-only property which returns the differential entropy.\n\n    logistic.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    logistic.mean: number\n        Read-only property which returns the expected value.\n\n    logistic.median: number\n        Read-only property which returns the median.\n\n    logistic.mode: number\n        Read-only property which returns the mode.\n\n    logistic.skewness: number\n        Read-only property which returns the skewness.\n\n    logistic.stdev: number\n        Read-only property which returns the standard deviation.\n\n    logistic.variance: number\n        Read-only property which returns the variance.\n\n    logistic.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    logistic.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    logistic.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    logistic.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    logistic.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    logistic.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var logistic = base.dists.logistic.Logistic( -2.0, 3.0 );\n    > logistic.mu\n    -2.0\n    > logistic.s\n    3.0\n    > logistic.entropy\n    ~3.1\n    > logistic.kurtosis\n    1.2\n    > logistic.mean\n    -2.0\n    > logistic.median\n    -2.0\n    > logistic.mode\n    -2.0\n    > logistic.skewness\n    0.0\n    > logistic.stdev\n    ~5.441\n    > logistic.variance\n    ~29.609\n    > logistic.cdf( 0.8 )\n    ~0.718\n    > logistic.logcdf( 0.8 )\n    ~-0.332\n    > logistic.logpdf( 2.0 )\n    ~-2.9\n    > logistic.mgf( 0.2 )\n    ~1.329\n    > logistic.pdf( 2.0 )\n    ~0.055\n    > logistic.quantile( 0.9 )\n    ~4.592\n\n","base.dists.logistic.logpdf":"\nbase.dists.logistic.logpdf( x, μ, s )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    logistic distribution with location parameter `μ` and scale parameter `s` at\n    a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.logpdf( 2.0, 0.0, 1.0 )\n    ~-2.254\n    > y = base.dists.logistic.logpdf( -1.0, 4.0, 2.0 )\n    ~-3.351\n    > y = base.dists.logistic.logpdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.logistic.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.logpdf( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.logistic.logpdf( 2.0, 0.0, -1.0 )\n    NaN\n\n    // Degenerate distribution at `s = 0.0`:\n    > y = base.dists.logistic.logpdf( 2.0, 8.0, 0.0 )\n    -Infinity\n    > y = base.dists.logistic.logpdf( 8.0, 8.0, 0.0 )\n    Infinity\n\n\nbase.dists.logistic.logpdf.factory( μ, s )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Logistic distribution with location parameter `μ` and\n    scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.logistic.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogpdf( 10.0 )\n    ~-2.079\n\n","base.dists.logistic.logpdf.factory":"\nbase.dists.logistic.logpdf.factory( μ, s )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Logistic distribution with location parameter `μ` and\n    scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.logistic.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogpdf( 10.0 )\n    ~-2.079","base.dists.logistic.mean":"\nbase.dists.logistic.mean( μ, s )\n    Returns the expected value of a logistic distribution with location\n    parameter `μ` and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.mean( 0.0, 1.0 )\n    0.0\n    > y = base.dists.logistic.mean( 4.0, 2.0 )\n    4.0\n    > y = base.dists.logistic.mean( NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.mean( 0.0, NaN )\n    NaN\n    > y = base.dists.logistic.mean( 0.0, 0.0 )\n    NaN\n\n","base.dists.logistic.median":"\nbase.dists.logistic.median( μ, s )\n    Returns the median of a logistic distribution with location parameter `μ`\n    and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.median( 0.0, 1.0 )\n    0.0\n    > y = base.dists.logistic.median( 4.0, 2.0 )\n    4.0\n    > y = base.dists.logistic.median( NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.median( 0.0, NaN )\n    NaN\n    > y = base.dists.logistic.median( 0.0, 0.0 )\n    NaN\n\n","base.dists.logistic.mgf":"\nbase.dists.logistic.mgf( t, μ, s )\n    Evaluates the moment-generating function (MGF) for a logistic distribution\n    with location parameter `μ` and scale parameter `s` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.mgf( 0.9, 0.0, 1.0 )\n    ~9.15\n    > y = base.dists.logistic.mgf( 0.1, 4.0, 4.0 )\n    ~1.971\n    > y = base.dists.logistic.mgf( -0.2, 4.0, 4.0 )\n    ~1.921\n    > y = base.dists.logistic.mgf( 0.5, 0.0, -1.0 )\n    NaN\n    > y = base.dists.logistic.mgf( 0.5, 0.0, 4.0 )\n    Infinity\n    > y = base.dists.logistic.mgf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.logistic.mgf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.mgf( 0.0, 0.0, NaN )\n    NaN\n\n\nbase.dists.logistic.mgf.factory( μ, s )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a Logistic distribution with location parameter `μ` and scale parameter\n    `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.logistic.mgf.factory( 10.0, 0.5 );\n    > var y = mymgf( 0.5 )\n    ~164.846\n    > y = mymgf( 2.0 )\n    Infinity\n\n","base.dists.logistic.mgf.factory":"\nbase.dists.logistic.mgf.factory( μ, s )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a Logistic distribution with location parameter `μ` and scale parameter\n    `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.logistic.mgf.factory( 10.0, 0.5 );\n    > var y = mymgf( 0.5 )\n    ~164.846\n    > y = mymgf( 2.0 )\n    Infinity","base.dists.logistic.mode":"\nbase.dists.logistic.mode( μ, s )\n    Returns the mode of a logistic distribution with location parameter `μ` and\n    scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.mode( 0.0, 1.0 )\n    0.0\n    > y = base.dists.logistic.mode( 4.0, 2.0 )\n    4.0\n    > y = base.dists.logistic.mode( NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.mode( 0.0, NaN )\n    NaN\n    > y = base.dists.logistic.mode( 0.0, 0.0 )\n    NaN\n\n","base.dists.logistic.pdf":"\nbase.dists.logistic.pdf( x, μ, s )\n    Evaluates the probability density function (PDF) for a logistic distribution\n    with location parameter `μ` and scale parameter `s` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.pdf( 2.0, 0.0, 1.0 )\n    ~0.105\n    > y = base.dists.logistic.pdf( -1.0, 4.0, 2.0 )\n    ~0.035\n    > y = base.dists.logistic.pdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.logistic.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.pdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.logistic.pdf( 2.0, 0.0, -1.0 )\n    NaN\n    > y = base.dists.logistic.pdf( 2.0, 8.0, 0.0 )\n    0.0\n    > y = base.dists.logistic.pdf( 8.0, 8.0, 0.0 )\n    Infinity\n\n\nbase.dists.logistic.pdf.factory( μ, s )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Logistic distribution with location parameter `μ` and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.logistic.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    0.125\n\n","base.dists.logistic.pdf.factory":"\nbase.dists.logistic.pdf.factory( μ, s )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Logistic distribution with location parameter `μ` and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.logistic.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    0.125","base.dists.logistic.quantile":"\nbase.dists.logistic.quantile( p, μ, s )\n    Evaluates the quantile function for a logistic distribution with location\n    parameter `μ` and scale parameter `s` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.quantile( 0.8, 0.0, 1.0 )\n    ~1.386\n    > y = base.dists.logistic.quantile( 0.5, 4.0, 2.0 )\n    4\n\n    > y = base.dists.logistic.quantile( 1.1, 0.0, 1.0 )\n    NaN\n    > y = base.dists.logistic.quantile( -0.2, 0.0, 1.0 )\n    NaN\n\n    > y = base.dists.logistic.quantile( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.logistic.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.quantile( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.logistic.quantile( 0.5, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.logistic.quantile.factory( μ, s )\n    Returns a function for evaluating the quantile function of a logistic\n    distribution with location parameter `μ` and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.logistic.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    10.0\n\n","base.dists.logistic.quantile.factory":"\nbase.dists.logistic.quantile.factory( μ, s )\n    Returns a function for evaluating the quantile function of a logistic\n    distribution with location parameter `μ` and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.logistic.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    10.0","base.dists.logistic.skewness":"\nbase.dists.logistic.skewness( μ, s )\n    Returns the skewness of a logistic distribution with location parameter `μ`\n    and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.skewness( 0.0, 1.0 )\n    0.0\n    > y = base.dists.logistic.skewness( 4.0, 2.0 )\n    0.0\n    > y = base.dists.logistic.skewness( NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.skewness( 0.0, NaN )\n    NaN\n    > y = base.dists.logistic.skewness( 0.0, 0.0 )\n    NaN\n\n","base.dists.logistic.stdev":"\nbase.dists.logistic.stdev( μ, s )\n    Returns the standard deviation of a logistic distribution with location\n    parameter `μ` and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.stdev( 0.0, 1.0 )\n    ~1.814\n    > y = base.dists.logistic.stdev( 4.0, 2.0 )\n    ~3.628\n    > y = base.dists.logistic.stdev( NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.stdev( 0.0, NaN )\n    NaN\n    > y = base.dists.logistic.stdev( 0.0, 0.0 )\n    NaN\n\n","base.dists.logistic.variance":"\nbase.dists.logistic.variance( μ, s )\n    Returns the variance of a logistic distribution with location parameter `μ`\n    and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.variance( 0.0, 1.0 )\n    ~3.29\n    > y = base.dists.logistic.variance( 4.0, 2.0 )\n    ~13.159\n    > y = base.dists.logistic.variance( NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.variance( 0.0, NaN )\n    NaN\n    > y = base.dists.logistic.variance( 0.0, 0.0 )\n    NaN\n\n","base.dists.lognormal.cdf":"\nbase.dists.lognormal.cdf( x, μ, σ )\n    Evaluates the cumulative distribution function (CDF) for a lognormal\n    distribution with location parameter `μ` and scale parameter `σ` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.cdf( 2.0, 0.0, 1.0 )\n    ~0.756\n    > y = base.dists.lognormal.cdf( 5.0, 10.0, 3.0 )\n    ~0.003\n\n    > y = base.dists.lognormal.cdf( 2.0, 0.0, NaN )\n    NaN\n    > y = base.dists.lognormal.cdf( 2.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.cdf( NaN, 0.0, 1.0 )\n    NaN\n\n    // Non-positive scale parameter `σ`:\n    > y = base.dists.lognormal.cdf( 2.0, 0.0, -1.0 )\n    NaN\n    > y = base.dists.lognormal.cdf( 2.0, 0.0, 0.0 )\n    NaN\n\n\nbase.dists.lognormal.cdf.factory( μ, σ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a lognormal distribution with location parameter `μ` and scale parameter\n    `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.lognormal.cdf.factory( 3.0, 1.5 );\n    > var y = myCDF( 1.0 )\n    ~0.023\n    > y = myCDF( 4.0 )\n    ~0.141\n\n","base.dists.lognormal.cdf.factory":"\nbase.dists.lognormal.cdf.factory( μ, σ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a lognormal distribution with location parameter `μ` and scale parameter\n    `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.lognormal.cdf.factory( 3.0, 1.5 );\n    > var y = myCDF( 1.0 )\n    ~0.023\n    > y = myCDF( 4.0 )\n    ~0.141","base.dists.lognormal.entropy":"\nbase.dists.lognormal.entropy( μ, σ )\n    Returns the differential entropy of a lognormal distribution with location\n    `μ` and scale `σ` (in nats).\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.entropy( 0.0, 1.0 )\n    ~1.419\n    > y = base.dists.lognormal.entropy( 5.0, 2.0 )\n    ~7.112\n    > y = base.dists.lognormal.entropy( NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.entropy( 0.0, NaN )\n    NaN\n    > y = base.dists.lognormal.entropy( 0.0, 0.0 )\n    NaN\n\n","base.dists.lognormal.kurtosis":"\nbase.dists.lognormal.kurtosis( μ, σ )\n    Returns the excess kurtosis of a lognormal distribution with location `μ`\n    and scale `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Kurtosis.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.kurtosis( 0.0, 1.0 )\n    ~110.936\n    > y = base.dists.lognormal.kurtosis( 5.0, 2.0 )\n    ~9220556.977\n    > y = base.dists.lognormal.kurtosis( NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.kurtosis( 0.0, NaN )\n    NaN\n    > y = base.dists.lognormal.kurtosis( 0.0, 0.0 )\n    NaN\n\n","base.dists.lognormal.LogNormal":"\nbase.dists.lognormal.LogNormal( [μ, σ] )\n    Returns a lognormal distribution object.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter. Default: `0.0`.\n\n    σ: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    lognormal: Object\n        Distribution instance.\n\n    lognormal.mu: number\n        Location parameter.\n\n    lognormal.sigma: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    lognormal.entropy: number\n        Read-only property which returns the differential entropy.\n\n    lognormal.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    lognormal.mean: number\n        Read-only property which returns the expected value.\n\n    lognormal.median: number\n        Read-only property which returns the median.\n\n    lognormal.mode: number\n        Read-only property which returns the mode.\n\n    lognormal.skewness: number\n        Read-only property which returns the skewness.\n\n    lognormal.stdev: number\n        Read-only property which returns the standard deviation.\n\n    lognormal.variance: number\n        Read-only property which returns the variance.\n\n    lognormal.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    lognormal.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    lognormal.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    lognormal.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    lognormal.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var lognormal = base.dists.lognormal.LogNormal( -2.0, 3.0 );\n    > lognormal.mu\n    -2.0\n    > lognormal.sigma\n    3.0\n    > lognormal.entropy\n    ~0.518\n    > lognormal.kurtosis\n    4312295840576300\n    > lognormal.mean\n    ~12.182\n    > lognormal.median\n    ~0.135\n    > lognormal.mode\n    ~0.0\n    > lognormal.skewness\n    ~729551.383\n    > lognormal.stdev\n    ~1096.565\n    > lognormal.variance\n    ~1202455.871\n    > lognormal.cdf( 0.8 )\n    ~0.723\n    > lognormal.logcdf( 0.8 )\n    ~-4.334\n    > lognormal.logpdf( 2.0 )\n    ~-3.114\n    > lognormal.pdf( 2.0 )\n    ~0.044\n    > lognormal.quantile( 0.9 )\n    ~6.326\n\n","base.dists.lognormal.logcdf":"\nbase.dists.lognormal.logcdf( x, μ, σ )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a lognormal distribution with mean `μ` and standard deviation `σ`\n    at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Evaluated logcdf.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.logcdf( 2.0, 0.0, 1.0 )\n    ~-0.2799\n    > y = base.dists.lognormal.logcdf( 13.0, 4.0, 2.0 )\n    ~-1.442\n    > y = base.dists.lognormal.logcdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.lognormal.logcdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.logcdf( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative standard deviation:\n    > y = base.dists.lognormal.logcdf( 2.0, 0.0, -1.0 )\n    NaN\n\n    // Degenerate distribution centered at `μ` when `σ = 0.0`:\n    > y = base.dists.lognormal.logcdf( 2.0, 8.0, 0.0 )\n    -Infinity\n    > y = base.dists.lognormal.logcdf( 8.0, 8.0, 0.0 )\n    -Infinity\n\n\nbase.dists.lognormal.logcdf.factory( μ, σ )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a lognormal distribution with mean `μ` and\n    standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.lognormal.logcdf.factory( 10.0, 2.0 );\n    > var y = mylogcdf( 10.0 )\n    ~-9.732\n\n","base.dists.lognormal.logcdf.factory":"\nbase.dists.lognormal.logcdf.factory( μ, σ )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a lognormal distribution with mean `μ` and\n    standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.lognormal.logcdf.factory( 10.0, 2.0 );\n    > var y = mylogcdf( 10.0 )\n    ~-9.732","base.dists.lognormal.logpdf":"\nbase.dists.lognormal.logpdf( x, μ, σ )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a lognormal distribution with location parameter `μ` and scale parameter\n    `σ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.logpdf( 2.0, 0.0, 1.0 )\n    ~-1.852\n    > y = base.dists.lognormal.logpdf( 1.0, 0.0, 1.0 )\n    ~-0.919\n    > y = base.dists.lognormal.logpdf( 1.0, 3.0, 1.0 )\n    ~-5.419\n    > y = base.dists.lognormal.logpdf( -1.0, 4.0, 2.0 )\n    -Infinity\n\n    > y = base.dists.lognormal.logpdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.lognormal.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.logpdf( 0.0, 0.0, NaN )\n    NaN\n\n    // Non-positive scale parameter `σ`:\n    > y = base.dists.lognormal.logpdf( 2.0, 0.0, -1.0 )\n    NaN\n    > y = base.dists.lognormal.logpdf( 2.0, 0.0, 0.0 )\n    NaN\n\n\nbase.dists.lognormal.logpdf.factory( μ, σ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a lognormal distribution with location parameter\n    `μ` and scale parameter `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.lognormal.logpdf.factory( 4.0, 2.0 );\n    > var y = mylogPDF( 10.0 )\n    ~-4.275\n    > y = mylogPDF( 2.0 )\n    ~-3.672\n\n","base.dists.lognormal.logpdf.factory":"\nbase.dists.lognormal.logpdf.factory( μ, σ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a lognormal distribution with location parameter\n    `μ` and scale parameter `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.lognormal.logpdf.factory( 4.0, 2.0 );\n    > var y = mylogPDF( 10.0 )\n    ~-4.275\n    > y = mylogPDF( 2.0 )\n    ~-3.672","base.dists.lognormal.mean":"\nbase.dists.lognormal.mean( μ, σ )\n    Returns the expected value of a lognormal distribution with location `μ` and\n    scale `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.mean( 0.0, 1.0 )\n    ~1.649\n    > y = base.dists.lognormal.mean( 4.0, 2.0 )\n    ~403.429\n    > y = base.dists.lognormal.mean( NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.mean( 0.0, NaN )\n    NaN\n    > y = base.dists.lognormal.mean( 0.0, 0.0 )\n    NaN\n\n","base.dists.lognormal.median":"\nbase.dists.lognormal.median( μ, σ )\n    Returns the median of a lognormal distribution with location `μ` and scale\n    `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.median( 0.0, 1.0 )\n    1.0\n    > y = base.dists.lognormal.median( 5.0, 2.0 )\n    ~148.413\n    > y = base.dists.lognormal.median( NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.median( 0.0, NaN )\n    NaN\n    > y = base.dists.lognormal.median( 0.0, 0.0 )\n    NaN\n\n","base.dists.lognormal.mode":"\nbase.dists.lognormal.mode( μ, σ )\n    Returns the mode of a lognormal distribution with location `μ` and scale\n    `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.mode( 0.0, 1.0 )\n    ~0.368\n    > y = base.dists.lognormal.mode( 5.0, 2.0 )\n    ~2.718\n    > y = base.dists.lognormal.mode( NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.mode( 0.0, NaN )\n    NaN\n    > y = base.dists.lognormal.mode( 0.0, 0.0 )\n    NaN\n\n","base.dists.lognormal.pdf":"\nbase.dists.lognormal.pdf( x, μ, σ )\n    Evaluates the probability density function (PDF) for a lognormal\n    distribution with location parameter `μ` and scale parameter `σ` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.pdf( 2.0, 0.0, 1.0 )\n    ~0.157\n    > y = base.dists.lognormal.pdf( 1.0, 0.0, 1.0 )\n    ~0.399\n    > y = base.dists.lognormal.pdf( 1.0, 3.0, 1.0 )\n    ~0.004\n    > y = base.dists.lognormal.pdf( -1.0, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.lognormal.pdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.lognormal.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.pdf( 0.0, 0.0, NaN )\n    NaN\n\n    // Non-positive scale parameter `σ`:\n    > y = base.dists.lognormal.pdf( 2.0, 0.0, -1.0 )\n    NaN\n    > y = base.dists.lognormal.pdf( 2.0, 0.0, 0.0 )\n    NaN\n\n\nbase.dists.lognormal.pdf.factory( μ, σ )\n    Returns a function for evaluating the probability density function (PDF) of\n    a lognormal distribution with location parameter `μ` and scale parameter\n    `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.lognormal.pdf.factory( 4.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    ~0.014\n    > y = myPDF( 2.0 )\n    ~0.025\n\n","base.dists.lognormal.pdf.factory":"\nbase.dists.lognormal.pdf.factory( μ, σ )\n    Returns a function for evaluating the probability density function (PDF) of\n    a lognormal distribution with location parameter `μ` and scale parameter\n    `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.lognormal.pdf.factory( 4.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    ~0.014\n    > y = myPDF( 2.0 )\n    ~0.025","base.dists.lognormal.quantile":"\nbase.dists.lognormal.quantile( p, μ, σ )\n    Evaluates the quantile function for a lognormal distribution with location\n    parameter `μ` and scale parameter `σ` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.quantile( 0.8, 0.0, 1.0 )\n    ~2.32\n    > y = base.dists.lognormal.quantile( 0.5, 4.0, 2.0 )\n    ~54.598\n    > y = base.dists.lognormal.quantile( 1.1, 0.0, 1.0 )\n    NaN\n    > y = base.dists.lognormal.quantile( -0.2, 0.0, 1.0 )\n    NaN\n\n    > y = base.dists.lognormal.quantile( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.lognormal.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.quantile( 0.0, 0.0, NaN )\n    NaN\n\n    // Non-positive scale parameter `σ`:\n    > y = base.dists.lognormal.quantile( 0.5, 0.0, -1.0 )\n    NaN\n    > y = base.dists.lognormal.quantile( 0.5, 0.0, 0.0 )\n    NaN\n\n\nbase.dists.lognormal.quantile.factory( μ, σ )\n    Returns a function for evaluating the quantile function of a lognormal\n    distribution with location parameter `μ` and scale parameter `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.lognormal.quantile.factory( 4.0, 2.0 );\n    > var y = myQuantile( 0.2 )\n    ~10.143\n    > y = myQuantile( 0.8 )\n    ~293.901\n\n","base.dists.lognormal.quantile.factory":"\nbase.dists.lognormal.quantile.factory( μ, σ )\n    Returns a function for evaluating the quantile function of a lognormal\n    distribution with location parameter `μ` and scale parameter `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.lognormal.quantile.factory( 4.0, 2.0 );\n    > var y = myQuantile( 0.2 )\n    ~10.143\n    > y = myQuantile( 0.8 )\n    ~293.901","base.dists.lognormal.skewness":"\nbase.dists.lognormal.skewness( μ, σ )\n    Returns the skewness of a lognormal distribution with location `μ` and scale\n    `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.skewness( 0.0, 1.0 )\n    ~6.185\n    > y = base.dists.lognormal.skewness( 5.0, 2.0 )\n    ~414.359\n    > y = base.dists.lognormal.skewness( NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.skewness( 0.0, NaN )\n    NaN\n    > y = base.dists.lognormal.skewness( 0.0, 0.0 )\n    NaN\n\n","base.dists.lognormal.stdev":"\nbase.dists.lognormal.stdev( μ, σ )\n    Returns the standard deviation of a lognormal distribution with location `μ`\n    and scale `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.stdev( 0.0, 1.0 )\n    ~2.161\n    > y = base.dists.lognormal.stdev( 4.0, 2.0 )\n    ~2953.533\n    > y = base.dists.lognormal.stdev( NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.stdev( 0.0, NaN )\n    NaN\n    > y = base.dists.lognormal.stdev( 0.0, 0.0 )\n    NaN\n\n","base.dists.lognormal.variance":"\nbase.dists.lognormal.variance( μ, σ )\n    Returns the variance of a lognormal distribution with location `μ` and scale\n    `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.variance( 0.0, 1.0 )\n    ~4.671\n    > y = base.dists.lognormal.variance( 4.0, 2.0 )\n    ~8723355.729\n    > y = base.dists.lognormal.variance( NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.variance( 0.0, NaN )\n    NaN\n    > y = base.dists.lognormal.variance( 0.0, 0.0 )\n    NaN\n\n","base.dists.negativeBinomial.cdf":"\nbase.dists.negativeBinomial.cdf( x, r, p )\n    Evaluates the cumulative distribution function (CDF) for a negative binomial\n    distribution with number of successes until experiment is stopped `r` and\n    success probability `p` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a `r` which is not a positive number, the function returns\n    `NaN`.\n\n    If provided a success probability `p` outside of `[0,1]`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.negativeBinomial.cdf( 5.0, 20.0, 0.8 )\n    ~0.617\n    > y = base.dists.negativeBinomial.cdf( 21.0, 20.0, 0.5 )\n    ~0.622\n    > y = base.dists.negativeBinomial.cdf( 5.0, 10.0, 0.4 )\n    ~0.034\n    > y = base.dists.negativeBinomial.cdf( 0.0, 10.0, 0.9 )\n    ~0.349\n    > y = base.dists.negativeBinomial.cdf( 21.0, 15.5, 0.5 )\n    ~0.859\n    > y = base.dists.negativeBinomial.cdf( 5.0, 7.4, 0.4 )\n    ~0.131\n\n    > y = base.dists.negativeBinomial.cdf( 2.0, 0.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.cdf( 2.0, -2.0, 0.5 )\n    NaN\n\n    > y = base.dists.negativeBinomial.cdf( NaN, 20.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.cdf( 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.cdf( 0.0, 20.0, NaN )\n    NaN\n\n    > y = base.dists.negativeBinomial.cdf( 2.0, 20, -1.0 )\n    NaN\n    > y = base.dists.negativeBinomial.cdf( 2.0, 20, 1.5 )\n    NaN\n\n\nbase.dists.negativeBinomial.cdf.factory( r, p )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a negative binomial distribution with number of successes until\n    experiment is stopped `r` and success probability `p`.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.negativeBinomial.cdf.factory( 10, 0.5 );\n    > var y = myCDF( 3.0 )\n    ~0.046\n    > y = myCDF( 11.0 )\n    ~0.668\n\n","base.dists.negativeBinomial.cdf.factory":"\nbase.dists.negativeBinomial.cdf.factory( r, p )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a negative binomial distribution with number of successes until\n    experiment is stopped `r` and success probability `p`.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.negativeBinomial.cdf.factory( 10, 0.5 );\n    > var y = myCDF( 3.0 )\n    ~0.046\n    > y = myCDF( 11.0 )\n    ~0.668","base.dists.negativeBinomial.kurtosis":"\nbase.dists.negativeBinomial.kurtosis( r, p )\n    Returns the excess kurtosis of a negative binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a `r` which is not a positive number, the function returns\n    `NaN`.\n\n    If provided a success probability `p` outside of `[0,1]`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    r: integer\n        Number of failures until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.negativeBinomial.kurtosis( 100, 0.2 )\n    ~0.061\n    > v = base.dists.negativeBinomial.kurtosis( 20, 0.5 )\n    ~0.325\n\n","base.dists.negativeBinomial.logpmf":"\nbase.dists.negativeBinomial.logpmf( x, r, p )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    negative binomial distribution with number of successes until experiment is\n    stopped `r` and success probability `p` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a `r` which is not a positive number, the function returns\n    `NaN`.\n\n    If provided a success probability `p` outside of `[0,1]`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPMF.\n\n    Examples\n    --------\n    > var y = base.dists.negativeBinomial.logpmf( 5.0, 20.0, 0.8 )\n    ~-1.853\n    > y = base.dists.negativeBinomial.logpmf( 21.0, 20.0, 0.5 )\n    ~-2.818\n    > y = base.dists.negativeBinomial.logpmf( 5.0, 10.0, 0.4 )\n    ~-4.115\n    > y = base.dists.negativeBinomial.logpmf( 0.0, 10.0, 0.9 )\n    ~-1.054\n    > y = base.dists.negativeBinomial.logpmf( 21.0, 15.5, 0.5 )\n    ~-3.292\n    > y = base.dists.negativeBinomial.logpmf( 5.0, 7.4, 0.4 )\n    ~-2.976\n\n    > y = base.dists.negativeBinomial.logpmf( 2.0, 0.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.logpmf( 2.0, -2.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.logpmf( 2.0, 20, -1.0 )\n    NaN\n    > y = base.dists.negativeBinomial.logpmf( 2.0, 20, 1.5 )\n    NaN\n\n    > y = base.dists.negativeBinomial.logpmf( NaN, 20.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.logpmf( 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.logpmf( 0.0, 20.0, NaN )\n    NaN\n\n\nbase.dists.negativeBinomial.logpmf.factory( r, p )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a negative binomial distribution with number of\n    successes until experiment is stopped `r` and success probability `p`.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogPMF = base.dists.negativeBinomial.logpmf.factory( 10, 0.5 );\n    > var y = mylogPMF( 3.0 )\n    ~-3.617\n    > y = mylogPMF( 5.0 )\n    ~-2.795\n\n","base.dists.negativeBinomial.logpmf.factory":"\nbase.dists.negativeBinomial.logpmf.factory( r, p )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a negative binomial distribution with number of\n    successes until experiment is stopped `r` and success probability `p`.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogPMF = base.dists.negativeBinomial.logpmf.factory( 10, 0.5 );\n    > var y = mylogPMF( 3.0 )\n    ~-3.617\n    > y = mylogPMF( 5.0 )\n    ~-2.795","base.dists.negativeBinomial.mean":"\nbase.dists.negativeBinomial.mean( r, p )\n    Returns the expected value of a negative binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a `r` which is not a positive number, the function returns\n    `NaN`.\n\n    If provided a success probability `p` outside of `[0,1]`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    r: integer\n        Number of failures until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.negativeBinomial.mean( 100, 0.2 )\n    400\n    > v = base.dists.negativeBinomial.mean( 20, 0.5 )\n    20\n\n","base.dists.negativeBinomial.mgf":"\nbase.dists.negativeBinomial.mgf( x, r, p )\n    Evaluates the moment-generating function (MGF) for a negative binomial\n    distribution with number of successes until experiment is stopped `r` and\n    success probability `p` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a `r` which is not a positive number, the function returns\n    `NaN`.\n\n    If provided a success probability `p` outside of `[0,1]`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.negativeBinomial.mgf( 0.05, 20.0, 0.8 )\n    ~267.839\n    > y = base.dists.negativeBinomial.mgf( 0.1, 20.0, 0.1 )\n    ~9.347\n    > y = base.dists.negativeBinomial.mgf( 0.5, 10.0, 0.4 )\n    ~42822.023\n\n    > y = base.dists.negativeBinomial.mgf( 0.1, 0.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.mgf( 0.1, -2.0, 0.5 )\n    NaN\n\n    > y = base.dists.negativeBinomial.mgf( NaN, 20.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.mgf( 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.mgf( 0.0, 20.0, NaN )\n    NaN\n\n    > y = base.dists.negativeBinomial.mgf( 0.2, 20, -1.0 )\n    NaN\n    > y = base.dists.negativeBinomial.mgf( 0.2, 20, 1.5 )\n    NaN\n\n\nbase.dists.negativeBinomial.mgf.factory( r, p )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    negative binomial distribution with number of successes until experiment is\n    stopped `r` and success probability `p`.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.negativeBinomial.mgf.factory( 4.3, 0.4 );\n    > var y = myMGF( 0.2 )\n    ~4.696\n    > y = myMGF( 0.4 )\n    ~30.83\n\n","base.dists.negativeBinomial.mgf.factory":"\nbase.dists.negativeBinomial.mgf.factory( r, p )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    negative binomial distribution with number of successes until experiment is\n    stopped `r` and success probability `p`.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.negativeBinomial.mgf.factory( 4.3, 0.4 );\n    > var y = myMGF( 0.2 )\n    ~4.696\n    > y = myMGF( 0.4 )\n    ~30.83","base.dists.negativeBinomial.mode":"\nbase.dists.negativeBinomial.mode( r, p )\n    Returns the mode of a negative binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a `r` which is not a positive number, the function returns\n    `NaN`.\n\n    If provided a success probability `p` outside of `[0,1]`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    r: integer\n        Number of failures until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.negativeBinomial.mode( 100, 0.2 )\n    396\n    > v = base.dists.negativeBinomial.mode( 20, 0.5 )\n    19\n\n","base.dists.negativeBinomial.NegativeBinomial":"\nbase.dists.negativeBinomial.NegativeBinomial( [r, p] )\n    Returns a negative binomial distribution object.\n\n    Parameters\n    ----------\n    r: number (optional)\n        Number of successes until experiment is stopped. Must be a positive\n        number. Default: `1`.\n\n    p: number (optional)\n        Success probability. Must be a number between `0` and `1`. Default:\n        `0.5`.\n\n    Returns\n    -------\n    nbinomial: Object\n        Distribution instance.\n\n    nbinomial.r: number\n        Number of trials. If set, the value must be a positive number.\n\n    nbinomial.p: number\n        Success probability. If set, the value must be a number between `0` and\n        `1`.\n\n    nbinomial.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    nbinomial.mean: number\n        Read-only property which returns the expected value.\n\n    nbinomial.mode: number\n        Read-only property which returns the mode.\n\n    nbinomial.skewness: number\n        Read-only property which returns the skewness.\n\n    nbinomial.stdev: number\n        Read-only property which returns the standard deviation.\n\n    nbinomial.variance: number\n        Read-only property which returns the variance.\n\n    nbinomial.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    nbinomial.logpmf: Function\n        Evaluates the natural logarithm of the probability mass function (PMF).\n\n    nbinomial.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    nbinomial.pmf: Function\n        Evaluates the probability mass function (PMF).\n\n    nbinomial.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var nbinomial = base.dists.negativeBinomial.NegativeBinomial( 8.0, 0.5 );\n    > nbinomial.r\n    8.0\n    > nbinomial.p\n    0.5\n    > nbinomial.kurtosis\n    0.8125\n    > nbinomial.mean\n    8.0\n    > nbinomial.mode\n    7.0\n    > nbinomial.skewness\n    0.75\n    > nbinomial.stdev\n    4.0\n    > nbinomial.variance\n    16.0\n    > nbinomial.cdf( 2.9 )\n    ~0.055\n    > nbinomial.logpmf( 3.0 )\n    ~-2.837\n    > nbinomial.mgf( 0.2 )\n    ~36.675\n    > nbinomial.pmf( 3.0 )\n    ~0.059\n    > nbinomial.quantile( 0.8 )\n    11.0\n\n","base.dists.negativeBinomial.pmf":"\nbase.dists.negativeBinomial.pmf( x, r, p )\n    Evaluates the probability mass function (PMF) for a negative binomial\n    distribution with number of successes until experiment is stopped `r` and\n    success probability `p` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a `r` which is not a positive number, the function returns\n    `NaN`.\n\n    If provided a success probability `p` outside of `[0,1]`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated PMF.\n\n    Examples\n    --------\n    > var y = base.dists.negativeBinomial.pmf( 5.0, 20.0, 0.8 )\n    ~0.157\n    > y = base.dists.negativeBinomial.pmf( 21.0, 20.0, 0.5 )\n    ~0.06\n    > y = base.dists.negativeBinomial.pmf( 5.0, 10.0, 0.4 )\n    ~0.016\n    > y = base.dists.negativeBinomial.pmf( 0.0, 10.0, 0.9 )\n    ~0.349\n    > y = base.dists.negativeBinomial.pmf( 21.0, 15.5, 0.5 )\n    ~0.037\n    > y = base.dists.negativeBinomial.pmf( 5.0, 7.4, 0.4 )\n    ~0.051\n\n    > y = base.dists.negativeBinomial.pmf( 2.0, 0.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.pmf( 2.0, -2.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.pmf( 2.0, 20, -1.0 )\n    NaN\n    > y = base.dists.negativeBinomial.pmf( 2.0, 20, 1.5 )\n    NaN\n\n    > y = base.dists.negativeBinomial.pmf( NaN, 20.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.pmf( 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.pmf( 0.0, 20.0, NaN )\n    NaN\n\n\nbase.dists.negativeBinomial.pmf.factory( r, p )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    negative binomial distribution with number of successes until experiment is\n    stopped `r` and success probability `p`.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var myPMF = base.dists.negativeBinomial.pmf.factory( 10, 0.5 );\n    > var y = myPMF( 3.0 )\n    ~0.027\n    > y = myPMF( 5.0 )\n    ~0.061\n\n","base.dists.negativeBinomial.pmf.factory":"\nbase.dists.negativeBinomial.pmf.factory( r, p )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    negative binomial distribution with number of successes until experiment is\n    stopped `r` and success probability `p`.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var myPMF = base.dists.negativeBinomial.pmf.factory( 10, 0.5 );\n    > var y = myPMF( 3.0 )\n    ~0.027\n    > y = myPMF( 5.0 )\n    ~0.061","base.dists.negativeBinomial.quantile":"\nbase.dists.negativeBinomial.quantile( k, r, p )\n    Evaluates the quantile function for a negative binomial distribution with\n    number of successes until experiment is stopped `r` and success probability\n    `p` at a probability `k`.\n\n    If provided a `k` outside of `[0,1]`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a `r` which is not a positive number, the function returns\n    `NaN`.\n\n    If provided a success probability `p` outside of `[0,1]`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Input probability.\n\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.2 )\n    106\n    > y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.8 )\n    8\n    > y = base.dists.negativeBinomial.quantile( 0.5, 10.0, 0.4 )\n    14\n    > y = base.dists.negativeBinomial.quantile( 0.0, 10.0, 0.9 )\n    0\n\n    > y = base.dists.negativeBinomial.quantile( 1.1, 20.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.quantile( -0.1, 20.0, 0.5 )\n    NaN\n\n    > y = base.dists.negativeBinomial.quantile( 21.0, 15.5, 0.5 )\n    12\n    > y = base.dists.negativeBinomial.quantile( 5.0, 7.4, 0.4 )\n    10\n\n    > y = base.dists.negativeBinomial.quantile( 0.5, 0.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.quantile( 0.5, -2.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, -1.0 )\n    NaN\n    > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, 1.5 )\n    NaN\n\n    > y = base.dists.negativeBinomial.quantile( NaN, 20.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.quantile( 0.3, NaN, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, NaN )\n    NaN\n\n\nbase.dists.negativeBinomial.quantile.factory( r, p )\n    Returns a function for evaluating the quantile function of a negative\n    binomial distribution with number of successes until experiment is stopped\n    `r` and success probability `p`.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.negativeBinomial.quantile.factory( 10.0, 0.5 );\n    > var y = myQuantile( 0.1 )\n    5\n    > y = myQuantile( 0.9 )\n    16\n\n","base.dists.negativeBinomial.quantile.factory":"\nbase.dists.negativeBinomial.quantile.factory( r, p )\n    Returns a function for evaluating the quantile function of a negative\n    binomial distribution with number of successes until experiment is stopped\n    `r` and success probability `p`.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.negativeBinomial.quantile.factory( 10.0, 0.5 );\n    > var y = myQuantile( 0.1 )\n    5\n    > y = myQuantile( 0.9 )\n    16","base.dists.negativeBinomial.skewness":"\nbase.dists.negativeBinomial.skewness( r, p )\n    Returns the skewness of a negative binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a `r` which is not a positive number, the function returns\n    `NaN`.\n\n    If provided a success probability `p` outside of `[0,1]`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    r: integer\n        Number of failures until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.negativeBinomial.skewness( 100, 0.2 )\n    ~0.201\n    > v = base.dists.negativeBinomial.skewness( 20, 0.5 )\n    ~0.474\n\n","base.dists.negativeBinomial.stdev":"\nbase.dists.negativeBinomial.stdev( r, p )\n    Returns the standard deviation of a negative binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a `r` which is not a positive number, the function returns\n    `NaN`.\n\n    If provided a success probability `p` outside of `[0,1]`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    r: integer\n        Number of failures until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.negativeBinomial.stdev( 100, 0.2 )\n    ~44.721\n    > v = base.dists.negativeBinomial.stdev( 20, 0.5 )\n    ~6.325\n\n","base.dists.negativeBinomial.variance":"\nbase.dists.negativeBinomial.variance( r, p )\n    Returns the variance of a negative binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a `r` which is not a positive number, the function returns\n    `NaN`.\n\n    If provided a success probability `p` outside of `[0,1]`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    r: integer\n        Number of failures until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.negativeBinomial.variance( 100, 0.2 )\n    2000.0\n    > v = base.dists.negativeBinomial.variance( 20, 0.5 )\n    40.0\n\n","base.dists.normal.cdf":"\nbase.dists.normal.cdf( x, μ, σ )\n    Evaluates the cumulative distribution function (CDF) for a normal\n    distribution with mean `μ` and standard deviation `σ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.normal.cdf( 2.0, 0.0, 1.0 )\n    ~0.977\n    > y = base.dists.normal.cdf( -1.0, -1.0, 2.0 )\n    0.5\n    > y = base.dists.normal.cdf( -1.0, 4.0, 2.0 )\n    ~0.006\n    > y = base.dists.normal.cdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.normal.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.cdf( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative standard deviation:\n    > y = base.dists.normal.cdf( 2.0, 0.0, -1.0 )\n    NaN\n\n    // Degenerate distribution centered at `μ` when `σ = 0.0`:\n    > y = base.dists.normal.cdf( 2.0, 8.0, 0.0 )\n    0.0\n    > y = base.dists.normal.cdf( 8.0, 8.0, 0.0 )\n    1.0\n    > y = base.dists.normal.cdf( 10.0, 8.0, 0.0 )\n    1.0\n\n\nbase.dists.normal.cdf.factory( μ, σ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a normal distribution with mean `μ` and standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.normal.cdf.factory( 10.0, 2.0 );\n    > var y = myCDF( 10.0 )\n    0.5\n\n","base.dists.normal.cdf.factory":"\nbase.dists.normal.cdf.factory( μ, σ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a normal distribution with mean `μ` and standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.normal.cdf.factory( 10.0, 2.0 );\n    > var y = myCDF( 10.0 )\n    0.5","base.dists.normal.entropy":"\nbase.dists.normal.entropy( μ, σ )\n    Returns the differential entropy of a normal distribution with mean `μ` and\n    standard deviation `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var y = base.dists.normal.entropy( 0.0, 1.0 )\n    ~1.419\n    > y = base.dists.normal.entropy( 4.0, 3.0 )\n    ~2.518\n    > y = base.dists.normal.entropy( NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.entropy( 0.0, NaN )\n    NaN\n    > y = base.dists.normal.entropy( 0.0, 0.0 )\n    NaN\n\n","base.dists.normal.kurtosis":"\nbase.dists.normal.kurtosis( μ, σ )\n    Returns the excess kurtosis of a normal distribution with mean `μ` and\n    standard deviation `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var y = base.dists.normal.kurtosis( 0.0, 1.0 )\n    0.0\n    > y = base.dists.normal.kurtosis( 4.0, 3.0 )\n    0.0\n    > y = base.dists.normal.kurtosis( NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.kurtosis( 0.0, NaN )\n    NaN\n    > y = base.dists.normal.kurtosis( 0.0, 0.0 )\n    NaN\n\n","base.dists.normal.logcdf":"\nbase.dists.normal.logcdf( x, μ, σ )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a normal distribution with mean `μ` and standard deviation `σ` at\n    a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Evaluated logcdf.\n\n    Examples\n    --------\n    > var y = base.dists.normal.logcdf( 2.0, 0.0, 1.0 )\n    ~-0.023\n    > y = base.dists.normal.logcdf( -1.0, 4.0, 2.0 )\n    ~-5.082\n    > y = base.dists.normal.logcdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.normal.logcdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.logcdf( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative standard deviation:\n    > y = base.dists.normal.logcdf( 2.0, 0.0, -1.0 )\n    NaN\n\n    // Degenerate distribution centered at `μ` when `σ = 0.0`:\n    > y = base.dists.normal.logcdf( 2.0, 8.0, 0.0 )\n    -Infinity\n    > y = base.dists.normal.logcdf( 8.0, 8.0, 0.0 )\n    0.0\n\n\nbase.dists.normal.logcdf.factory( μ, σ )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a normal distribution with mean `μ` and\n    standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.normal.logcdf.factory( 10.0, 2.0 );\n    > var y = mylogcdf( 10.0 )\n    ~-0.693\n\n","base.dists.normal.logcdf.factory":"\nbase.dists.normal.logcdf.factory( μ, σ )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a normal distribution with mean `μ` and\n    standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.normal.logcdf.factory( 10.0, 2.0 );\n    > var y = mylogcdf( 10.0 )\n    ~-0.693","base.dists.normal.logpdf":"\nbase.dists.normal.logpdf( x, μ, σ )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a normal distribution with mean `μ` and standard deviation `σ` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.normal.logpdf( 2.0, 0.0, 1.0 )\n    ~-2.919\n    > y = base.dists.normal.logpdf( -1.0, 4.0, 2.0 )\n    ~-4.737\n    > y = base.dists.normal.logpdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.normal.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.logpdf( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative standard deviation:\n    > y = base.dists.normal.logpdf( 2.0, 0.0, -1.0 )\n    NaN\n\n    // Degenerate distribution centered at `μ` when `σ = 0.0`:\n    > y = base.dists.normal.logpdf( 2.0, 8.0, 0.0 )\n    -Infinity\n    > y = base.dists.normal.logpdf( 8.0, 8.0, 0.0 )\n    Infinity\n\n\nbase.dists.normal.logpdf.factory( μ, σ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a normal distribution with mean `μ` and standard\n    deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var myLogPDF = base.dists.normal.logpdf.factory( 10.0, 2.0 );\n    > var y = myLogPDF( 10.0 )\n    ~-1.612\n\n","base.dists.normal.logpdf.factory":"\nbase.dists.normal.logpdf.factory( μ, σ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a normal distribution with mean `μ` and standard\n    deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var myLogPDF = base.dists.normal.logpdf.factory( 10.0, 2.0 );\n    > var y = myLogPDF( 10.0 )\n    ~-1.612","base.dists.normal.mean":"\nbase.dists.normal.mean( μ, σ )\n    Returns the expected value of a normal distribution with mean `μ` and\n    standard deviation `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var y = base.dists.normal.mean( 0.0, 1.0 )\n    0.0\n    > y = base.dists.normal.mean( 4.0, 2.0 )\n    4.0\n    > y = base.dists.normal.mean( NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.mean( 0.0, NaN )\n    NaN\n    > y = base.dists.normal.mean( 0.0, 0.0 )\n    NaN\n\n","base.dists.normal.median":"\nbase.dists.normal.median( μ, σ )\n    Returns the median of a normal distribution with mean `μ` and standard\n    deviation `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var y = base.dists.normal.median( 0.0, 1.0 )\n    0.0\n    > y = base.dists.normal.median( 4.0, 2.0 )\n    4.0\n    > y = base.dists.normal.median( NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.median( 0.0, NaN )\n    NaN\n    > y = base.dists.normal.median( 0.0, 0.0 )\n    NaN\n\n","base.dists.normal.mgf":"\nbase.dists.normal.mgf( x, μ, σ )\n    Evaluates the moment-generating function (MGF) for a normal distribution\n    with mean `μ` and standard deviation `σ` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.normal.mgf( 2.0, 0.0, 1.0 )\n    ~7.389\n    > y = base.dists.normal.mgf( 0.0, 0.0, 1.0 )\n    1.0\n    > y = base.dists.normal.mgf( -1.0, 4.0, 2.0 )\n    ~0.1353\n    > y = base.dists.normal.mgf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.normal.mgf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.mgf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.normal.mgf( 2.0, 0.0, 0.0 )\n    NaN\n\n\nbase.dists.normal.mgf.factory( μ, σ )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    normal distribution with mean `μ` and standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.normal.mgf.factory( 4.0, 2.0 );\n    > var y = myMGF( 1.0 )\n    ~403.429\n    > y = myMGF( 0.5 )\n    ~12.182\n\n","base.dists.normal.mgf.factory":"\nbase.dists.normal.mgf.factory( μ, σ )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    normal distribution with mean `μ` and standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.normal.mgf.factory( 4.0, 2.0 );\n    > var y = myMGF( 1.0 )\n    ~403.429\n    > y = myMGF( 0.5 )\n    ~12.182","base.dists.normal.mode":"\nbase.dists.normal.mode( μ, σ )\n    Returns the mode of a normal distribution with mean `μ` and standard\n    deviation `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var y = base.dists.normal.mode( 0.0, 1.0 )\n    0.0\n    > y = base.dists.normal.mode( 4.0, 2.0 )\n    4.0\n    > y = base.dists.normal.mode( NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.mode( 0.0, NaN )\n    NaN\n    > y = base.dists.normal.mode( 0.0, 0.0 )\n    NaN\n\n","base.dists.normal.Normal":"\nbase.dists.normal.Normal( [μ, σ] )\n    Returns a normal distribution object.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean parameter. Default: `0.0`.\n\n    σ: number (optional)\n        Standard deviation. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    normal: Object\n        Distribution instance.\n\n    normal.mu: number\n        Mean parameter.\n\n    normal.sigma: number\n        Standard deviation. If set, the value must be greater than `0`.\n\n    normal.entropy: number\n        Read-only property which returns the differential entropy.\n\n    normal.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    normal.mean: number\n        Read-only property which returns the expected value.\n\n    normal.median: number\n        Read-only property which returns the median.\n\n    normal.mode: number\n        Read-only property which returns the mode.\n\n    normal.skewness: number\n        Read-only property which returns the skewness.\n\n    normal.stdev: number\n        Read-only property which returns the standard deviation.\n\n    normal.variance: number\n        Read-only property which returns the variance.\n\n    normal.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    normal.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    normal.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    normal.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    normal.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    normal.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var normal = base.dists.normal.Normal( -2.0, 3.0 );\n    > normal.mu\n    -2.0\n    > normal.sigma\n    3.0\n    > normal.entropy\n    ~2.518\n    > normal.kurtosis\n    0.0\n    > normal.mean\n    -2.0\n    > normal.median\n    -2.0\n    > normal.mode\n    -2.0\n    > normal.skewness\n    0.0\n    > normal.stdev\n    3.0\n    > normal.variance\n    9.0\n    > normal.cdf( 0.8 )\n    ~0.825\n    > normal.logcdf( 0.8 )\n    ~-0.193\n    > normal.logpdf( 2.0 )\n    ~-2.9\n    > normal.mgf( 0.2 )\n    ~0.803\n    > normal.pdf( 2.0 )\n    ~0.055\n    > normal.quantile( 0.9 )\n    ~1.845\n\n","base.dists.normal.pdf":"\nbase.dists.normal.pdf( x, μ, σ )\n    Evaluates the probability density function (PDF) for a normal distribution\n    with mean `μ` and standard deviation `σ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.normal.pdf( 2.0, 0.0, 1.0 )\n    ~0.054\n    > y = base.dists.normal.pdf( -1.0, 4.0, 2.0 )\n    ~0.009\n    > y = base.dists.normal.pdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.normal.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.pdf( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative standard deviation:\n    > y = base.dists.normal.pdf( 2.0, 0.0, -1.0 )\n    NaN\n\n    // Degenerate distribution centered at `μ` when `σ = 0.0`:\n    > y = base.dists.normal.pdf( 2.0, 8.0, 0.0 )\n    0.0\n    > y = base.dists.normal.pdf( 8.0, 8.0, 0.0 )\n    infinity\n\n\nbase.dists.normal.pdf.factory( μ, σ )\n    Returns a function for evaluating the probability density function (PDF) of\n    a normal distribution with mean `μ` and standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.normal.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    ~0.199\n\n","base.dists.normal.pdf.factory":"\nbase.dists.normal.pdf.factory( μ, σ )\n    Returns a function for evaluating the probability density function (PDF) of\n    a normal distribution with mean `μ` and standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.normal.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    ~0.199","base.dists.normal.quantile":"\nbase.dists.normal.quantile( p, μ, σ )\n    Evaluates the quantile function for a normal distribution with mean `μ` and\n    standard deviation `σ` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.normal.quantile( 0.8, 0.0, 1.0 )\n    ~0.842\n    > y = base.dists.normal.quantile( 0.5, 4.0, 2.0 )\n    4\n\n    > y = base.dists.normal.quantile( 1.1, 0.0, 1.0 )\n    NaN\n    > y = base.dists.normal.quantile( -0.2, 0.0, 1.0 )\n    NaN\n\n    > y = base.dists.normal.quantile( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.normal.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.quantile( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative standard deviation:\n    > y = base.dists.normal.quantile( 0.5, 0.0, -1.0 )\n    NaN\n\n    // Degenerate distribution centered at `μ` when `σ = 0.0`:\n    > y = base.dists.normal.quantile( 0.3, 8.0, 0.0 )\n    8.0\n    > y = base.dists.normal.quantile( 0.9, 8.0, 0.0 )\n    8.0\n\n\nbase.dists.normal.quantile.factory( μ, σ )\n    Returns a function for evaluating the quantile function\n    of a normal distribution with mean `μ` and standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.normal.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    10.0\n\n","base.dists.normal.quantile.factory":"\nbase.dists.normal.quantile.factory( μ, σ )\n    Returns a function for evaluating the quantile function\n    of a normal distribution with mean `μ` and standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.normal.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    10.0","base.dists.normal.skewness":"\nbase.dists.normal.skewness( μ, σ )\n    Returns the skewness of a normal distribution with mean `μ` and standard\n    deviation `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var y = base.dists.normal.skewness( 0.0, 1.0 )\n    0.0\n    > y = base.dists.normal.skewness( 4.0, 3.0 )\n    0.0\n    > y = base.dists.normal.skewness( NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.skewness( 0.0, NaN )\n    NaN\n    > y = base.dists.normal.skewness( 0.0, 0.0 )\n    NaN\n\n","base.dists.normal.stdev":"\nbase.dists.normal.stdev( μ, σ )\n    Returns the standard deviation of a normal distribution with mean `μ` and\n    standard deviation `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var y = base.dists.normal.stdev( 0.0, 1.0 )\n    1.0\n    > y = base.dists.normal.stdev( 4.0, 3.0 )\n    3.0\n    > y = base.dists.normal.stdev( NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.stdev( 0.0, NaN )\n    NaN\n    > y = base.dists.normal.stdev( 0.0, 0.0 )\n    NaN\n\n","base.dists.normal.variance":"\nbase.dists.normal.variance( μ, σ )\n    Returns the variance of a normal distribution with mean `μ` and standard\n    deviation `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var y = base.dists.normal.variance( 0.0, 1.0 )\n    1.0\n    > y = base.dists.normal.variance( 4.0, 3.0 )\n    9.0\n    > y = base.dists.normal.variance( NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.variance( 0.0, NaN )\n    NaN\n    > y = base.dists.normal.variance( 0.0, 0.0 )\n    NaN\n\n","base.dists.pareto1.cdf":"\nbase.dists.pareto1.cdf( x, α, β )\n    Evaluates the cumulative distribution function (CDF) for a Pareto (Type I)\n    distribution with shape parameter `α` and scale parameter `β` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.pareto1.cdf( 2.0, 1.0, 1.0 )\n    0.5\n    > y = base.dists.pareto1.cdf( 5.0, 2.0, 4.0 )\n    ~0.36\n    > y = base.dists.pareto1.cdf( 4.0, 2.0, 2.0 )\n    0.75\n    > y = base.dists.pareto1.cdf( 1.9, 2.0, 2.0 )\n    0.0\n    > y = base.dists.pareto1.cdf( PINF, 4.0, 2.0 )\n    1.0\n\n    > y = base.dists.pareto1.cdf( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.pareto1.cdf( 2.0, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.pareto1.cdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.pareto1.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.pareto1.cdf( 0.0, 1.0, NaN )\n    NaN\n\n\nbase.dists.pareto1.cdf.factory( α, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Pareto (Type I) distribution with shape parameter `α` and scale\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.pareto1.cdf.factory( 10.0, 2.0 );\n    > var y = myCDF( 3.0 )\n    ~0.983\n    > y = myCDF( 2.5 )\n    ~0.893\n\n","base.dists.pareto1.cdf.factory":"\nbase.dists.pareto1.cdf.factory( α, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Pareto (Type I) distribution with shape parameter `α` and scale\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.pareto1.cdf.factory( 10.0, 2.0 );\n    > var y = myCDF( 3.0 )\n    ~0.983\n    > y = myCDF( 2.5 )\n    ~0.893","base.dists.pareto1.entropy":"\nbase.dists.pareto1.entropy( α, β )\n    Returns the differential entropy of a Pareto (Type I) distribution\n    (in nats).\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Differential entropy.\n\n    Examples\n    --------\n    > var v = base.dists.pareto1.entropy( 0.8, 1.0 )\n    ~2.473\n    > v = base.dists.pareto1.entropy( 4.0, 12.0 )\n    ~2.349\n    > v = base.dists.pareto1.entropy( 8.0, 2.0 )\n    ~-0.261\n\n","base.dists.pareto1.kurtosis":"\nbase.dists.pareto1.kurtosis( α, β )\n    Returns the excess kurtosis of a Pareto (Type I) distribution.\n\n    If `α <= 4` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.pareto1.kurtosis( 5.0, 1.0 )\n    ~70.8\n    > v = base.dists.pareto1.kurtosis( 4.5, 12.0 )\n    ~146.444\n    > v = base.dists.pareto1.kurtosis( 8.0, 2.0 )\n    ~19.725\n\n","base.dists.pareto1.logcdf":"\nbase.dists.pareto1.logcdf( x, α, β )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a Pareto (Type I) distribution with shape parameter `α` and scale\n    parameter `β` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.pareto1.logcdf( 2.0, 1.0, 1.0 )\n    ~-0.693\n    > y = base.dists.pareto1.logcdf( 5.0, 2.0, 4.0 )\n    ~-1.022\n    > y = base.dists.pareto1.logcdf( 4.0, 2.0, 2.0 )\n    ~-0.288\n    > y = base.dists.pareto1.logcdf( 1.9, 2.0, 2.0 )\n    -Infinity\n    > y = base.dists.pareto1.logcdf( PINF, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.pareto1.logcdf( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.pareto1.logcdf( 2.0, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.pareto1.logcdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.pareto1.logcdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.pareto1.logcdf( 0.0, 1.0, NaN )\n    NaN\n\n\nbase.dists.pareto1.logcdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Pareto (Type I) distribution with shape\n    parameter `α` and scale parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogCDF = base.dists.pareto1.logcdf.factory( 10.0, 2.0 );\n    > var y = mylogCDF( 3.0 )\n    ~-0.017\n    > y = mylogCDF( 2.5 )\n    ~-0.114\n\n","base.dists.pareto1.logcdf.factory":"\nbase.dists.pareto1.logcdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Pareto (Type I) distribution with shape\n    parameter `α` and scale parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogCDF = base.dists.pareto1.logcdf.factory( 10.0, 2.0 );\n    > var y = mylogCDF( 3.0 )\n    ~-0.017\n    > y = mylogCDF( 2.5 )\n    ~-0.114","base.dists.pareto1.logpdf":"\nbase.dists.pareto1.logpdf( x, α, β )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a Pareto (Type I) distribution with shape parameter `α` and scale\n    parameter `β` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.pareto1.logpdf( 4.0, 1.0, 1.0 )\n    ~-2.773\n    > y = base.dists.pareto1.logpdf( 20.0, 1.0, 10.0 )\n    ~-3.689\n    > y = base.dists.pareto1.logpdf( 7.0, 2.0, 6.0 )\n    ~-1.561\n    > y = base.dists.pareto1.logpdf( 7.0, 6.0, 3.0 )\n    ~-5.238\n    > y = base.dists.pareto1.logpdf( 1.0, 4.0, 2.0 )\n    -Infinity\n    > y = base.dists.pareto1.logpdf( 1.5, 4.0, 2.0 )\n    -Infinity\n\n    > y = base.dists.pareto1.logpdf( 0.5, -1.0, 0.5 )\n    NaN\n    > y = base.dists.pareto1.logpdf( 0.5, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.pareto1.logpdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.pareto1.logpdf( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.dists.pareto1.logpdf( 0.5, 1.0, NaN )\n    NaN\n\n\nbase.dists.pareto1.logpdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a Pareto (Type I) distribution with shape\n    parameter `α` and scale parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.pareto1.logpdf.factory( 0.5, 0.5 );\n    > var y = mylogPDF( 0.8 )\n    ~-0.705\n    > y = mylogPDF( 2.0 )\n    ~-2.079\n\n","base.dists.pareto1.logpdf.factory":"\nbase.dists.pareto1.logpdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a Pareto (Type I) distribution with shape\n    parameter `α` and scale parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.pareto1.logpdf.factory( 0.5, 0.5 );\n    > var y = mylogPDF( 0.8 )\n    ~-0.705\n    > y = mylogPDF( 2.0 )\n    ~-2.079","base.dists.pareto1.mean":"\nbase.dists.pareto1.mean( α, β )\n    Returns the expected value of a Pareto (Type I) distribution.\n\n    If `0 < α <= 1`, the function returns `Infinity`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.pareto1.mean( 0.8, 1.0 )\n    Infinity\n    > v = base.dists.pareto1.mean( 4.0, 12.0 )\n    16.0\n    > v = base.dists.pareto1.mean( 8.0, 2.0 )\n    ~2.286\n\n","base.dists.pareto1.median":"\nbase.dists.pareto1.median( α, β )\n    Returns the median of a Pareto (Type I) distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.pareto1.median( 0.8, 1.0 )\n    ~2.378\n    > v = base.dists.pareto1.median( 4.0, 12.0 )\n    ~14.27\n    > v = base.dists.pareto1.median( 8.0, 2.0 )\n    ~2.181\n\n","base.dists.pareto1.mode":"\nbase.dists.pareto1.mode( α, β )\n    Returns the mode of a Pareto (Type I) distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.pareto1.mode( 0.8, 1.0 )\n    1.0\n    > v = base.dists.pareto1.mode( 4.0, 12.0 )\n    12.0\n    > v = base.dists.pareto1.mode( 8.0, 2.0 )\n    2.0\n\n","base.dists.pareto1.Pareto1":"\nbase.dists.pareto1.Pareto1( [α, β] )\n    Returns a Pareto (Type I) distribution object.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n    β: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    pareto1: Object\n        Distribution instance.\n\n    pareto1.alpha: number\n        Shape parameter. If set, the value must be greater than `0`.\n\n    pareto1.beta: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    pareto1.entropy: number\n        Read-only property which returns the differential entropy.\n\n    pareto1.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    pareto1.mean: number\n        Read-only property which returns the expected value.\n\n    pareto1.median: number\n        Read-only property which returns the median.\n\n    pareto1.mode: number\n        Read-only property which returns the mode.\n\n    pareto1.skewness: number\n        Read-only property which returns the skewness.\n\n    pareto1.variance: number\n        Read-only property which returns the variance.\n\n    pareto1.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    pareto1.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (logCDF).\n\n    pareto1.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (logPDF).\n\n    pareto1.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    pareto1.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var pareto1 = base.dists.pareto1.Pareto1( 6.0, 5.0 );\n    > pareto1.alpha\n    6.0\n    > pareto1.beta\n    5.0\n    > pareto1.entropy\n    ~0.984\n    > pareto1.kurtosis\n    ~35.667\n    > pareto1.mean\n    6.0\n    > pareto1.median\n    ~5.612\n    > pareto1.mode\n    5.0\n    > pareto1.skewness\n    ~3.81\n    > pareto1.variance\n    1.5\n    > pareto1.cdf( 7.0 )\n    ~0.867\n    > pareto1.logcdf( 7.0 )\n    ~-0.142\n    > pareto1.logpdf( 5.0 )\n    ~0.182\n    > pareto1.pdf( 5.0 )\n    1.2\n    > pareto1.quantile( 0.8 )\n    ~6.538\n\n","base.dists.pareto1.pdf":"\nbase.dists.pareto1.pdf( x, α, β )\n    Evaluates the probability density function (PDF) for a Pareto (Type I)\n    distribution with shape parameter `α` and scale parameter `β` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.pareto1.pdf( 4.0, 1.0, 1.0 )\n    ~0.063\n    > y = base.dists.pareto1.pdf( 20.0, 1.0, 10.0 )\n    0.025\n    > y = base.dists.pareto1.pdf( 7.0, 2.0, 6.0 )\n    ~0.21\n    > y = base.dists.pareto1.pdf( 7.0, 6.0, 3.0 )\n    ~0.005\n    > y = base.dists.pareto1.pdf( 1.0, 4.0, 2.0 )\n    0.0\n    > y = base.dists.pareto1.pdf( 1.5, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.pareto1.pdf( 0.5, -1.0, 0.5 )\n    NaN\n    > y = base.dists.pareto1.pdf( 0.5, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.pareto1.pdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.pareto1.pdf( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.dists.pareto1.pdf( 0.5, 1.0, NaN )\n    NaN\n\n\nbase.dists.pareto1.pdf.factory( α, β )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Pareto (Type I) distribution with shape parameter `α` and scale parameter\n    `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.pareto1.pdf.factory( 0.5, 0.5 );\n    > var y = myPDF( 0.8 )\n    ~0.494\n    > y = myPDF( 2.0 )\n    ~0.125\n\n","base.dists.pareto1.pdf.factory":"\nbase.dists.pareto1.pdf.factory( α, β )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Pareto (Type I) distribution with shape parameter `α` and scale parameter\n    `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.pareto1.pdf.factory( 0.5, 0.5 );\n    > var y = myPDF( 0.8 )\n    ~0.494\n    > y = myPDF( 2.0 )\n    ~0.125","base.dists.pareto1.quantile":"\nbase.dists.pareto1.quantile( p, α, β )\n    Evaluates the quantile function for a Pareto (Type I) distribution with\n    shape parameter `α` and scale parameter `β` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.pareto1.quantile( 0.8, 2.0, 1.0 )\n    ~2.236\n    > y = base.dists.pareto1.quantile( 0.8, 1.0, 10.0 )\n    ~50.0\n    > y = base.dists.pareto1.quantile( 0.1, 1.0, 10.0 )\n    ~11.111\n\n    > y = base.dists.pareto1.quantile( 1.1, 1.0, 1.0 )\n    NaN\n    > y = base.dists.pareto1.quantile( -0.2, 1.0, 1.0 )\n    NaN\n\n    > y = base.dists.pareto1.quantile( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.pareto1.quantile( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.dists.pareto1.quantile( 0.5, 1.0, NaN )\n    NaN\n\n    > y = base.dists.pareto1.quantile( 0.5, -1.0, 1.0 )\n    NaN\n    > y = base.dists.pareto1.quantile( 0.5, 1.0, -1.0 )\n    NaN\n\n\nbase.dists.pareto1.quantile.factory( α, β )\n    Returns a function for evaluating the quantile function of a Pareto (Type I)\n    distribution with shape parameter `α` and scale parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.pareto1.quantile.factory( 2.5, 0.5 );\n    > var y = myQuantile( 0.5 )\n    ~0.66\n    > y = myQuantile( 0.8 )\n    ~0.952\n\n","base.dists.pareto1.quantile.factory":"\nbase.dists.pareto1.quantile.factory( α, β )\n    Returns a function for evaluating the quantile function of a Pareto (Type I)\n    distribution with shape parameter `α` and scale parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.pareto1.quantile.factory( 2.5, 0.5 );\n    > var y = myQuantile( 0.5 )\n    ~0.66\n    > y = myQuantile( 0.8 )\n    ~0.952","base.dists.pareto1.skewness":"\nbase.dists.pareto1.skewness( α, β )\n    Returns the skewness of a Pareto (Type I) distribution.\n\n    If `α <= 3` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.pareto1.skewness( 3.5, 1.0 )\n    ~11.784\n    > v = base.dists.pareto1.skewness( 4.0, 12.0 )\n    ~7.071\n    > v = base.dists.pareto1.skewness( 8.0, 2.0 )\n    ~3.118\n\n","base.dists.pareto1.stdev":"\nbase.dists.pareto1.stdev( α, β )\n    Returns the standard deviation of a Pareto (Type I) distribution.\n\n    If `0 < α <= 2` and `β > 0`, the function returns positive infinity.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.pareto1.stdev( 0.8, 1.0 )\n    Infinity\n    > v = base.dists.pareto1.stdev( 4.0, 12.0 )\n    ~5.657\n    > v = base.dists.pareto1.stdev( 8.0, 2.0 )\n    ~0.33\n\n","base.dists.pareto1.variance":"\nbase.dists.pareto1.variance( α, β )\n    Returns the variance of a Pareto (Type I) distribution.\n\n    If `0 < α <= 2` and `β > 0`, the function returns positive infinity.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.pareto1.variance( 0.8, 1.0 )\n    Infinity\n    > v = base.dists.pareto1.variance( 4.0, 12.0 )\n    32.0\n    > v = base.dists.pareto1.variance( 8.0, 2.0 )\n    ~0.109\n\n","base.dists.poisson.cdf":"\nbase.dists.poisson.cdf( x, λ )\n    Evaluates the cumulative distribution function (CDF) for a Poisson\n    distribution with mean parameter `λ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.poisson.cdf( 2.0, 0.5 )\n    ~0.986\n    > y = base.dists.poisson.cdf( 2.0, 10.0 )\n    ~0.003\n    > y = base.dists.poisson.cdf( -1.0, 4.0 )\n    0.0\n    > y = base.dists.poisson.cdf( NaN, 1.0 )\n    NaN\n    > y = base.dists.poisson.cdf( 0.0, NaN )\n    NaN\n\n    // Negative mean parameter:\n    > y = base.dists.poisson.cdf( 2.0, -1.0 )\n    NaN\n\n    // Degenerate distribution at `λ = 0`:\n    > y = base.dists.poisson.cdf( -2.0, 0.0 )\n    0.0\n    > y = base.dists.poisson.cdf( 0.0, 0.0 )\n    1.0\n    > y = base.dists.poisson.cdf( 10.0, 0.0 )\n    1.0\n\n\nbase.dists.poisson.cdf.factory( λ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Poisson distribution with mean parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.poisson.cdf.factory( 5.0 );\n    > var y = mycdf( 3.0 )\n    ~0.265\n    > y = mycdf( 8.0 )\n    ~0.932\n\n","base.dists.poisson.cdf.factory":"\nbase.dists.poisson.cdf.factory( λ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Poisson distribution with mean parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.poisson.cdf.factory( 5.0 );\n    > var y = mycdf( 3.0 )\n    ~0.265\n    > y = mycdf( 8.0 )\n    ~0.932","base.dists.poisson.entropy":"\nbase.dists.poisson.entropy( λ )\n    Returns the entropy of a Poisson distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.poisson.entropy( 11.0 )\n    ~2.61\n    > v = base.dists.poisson.entropy( 4.5 )\n    ~2.149\n\n","base.dists.poisson.kurtosis":"\nbase.dists.poisson.kurtosis( λ )\n    Returns the excess kurtosis of a Poisson distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.poisson.kurtosis( 11.0 )\n    ~0.091\n    > v = base.dists.poisson.kurtosis( 4.5 )\n    ~0.222\n\n","base.dists.poisson.logpmf":"\nbase.dists.poisson.logpmf( x, λ )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    Poisson distribution with mean parameter `λ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPMF.\n\n    Examples\n    --------\n    > var y = base.dists.poisson.logpmf( 4.0, 3.0 )\n    ~-1.784\n    > y = base.dists.poisson.logpmf( 1.0, 3.0 )\n    ~-1.901\n    > y = base.dists.poisson.logpmf( -1.0, 2.0 )\n    -Infinity\n    > y = base.dists.poisson.logpmf( 0.0, NaN )\n    NaN\n    > y = base.dists.poisson.logpmf( NaN, 0.5 )\n    NaN\n\n    // Negative mean parameter:\n    > y = base.dists.poisson.logpmf( 2.0, -0.5 )\n    NaN\n\n    // Degenerate distribution at `λ = 0`:\n    > y = base.dists.poisson.logpmf( 2.0, 0.0 )\n    -Infinity\n    > y = base.dists.poisson.logpmf( 0.0, 0.0 )\n    0.0\n\n\nbase.dists.poisson.logpmf.factory( λ )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a Poisson distribution with mean parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogpmf = base.dists.poisson.logpmf.factory( 1.0 );\n    > var y = mylogpmf( 3.0 )\n    ~-2.792\n    > y = mylogpmf( 1.0 )\n    ~-1.0\n\n","base.dists.poisson.logpmf.factory":"\nbase.dists.poisson.logpmf.factory( λ )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a Poisson distribution with mean parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogpmf = base.dists.poisson.logpmf.factory( 1.0 );\n    > var y = mylogpmf( 3.0 )\n    ~-2.792\n    > y = mylogpmf( 1.0 )\n    ~-1.0","base.dists.poisson.mean":"\nbase.dists.poisson.mean( λ )\n    Returns the expected value of a Poisson distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.poisson.mean( 11.0 )\n    11.0\n    > v = base.dists.poisson.mean( 4.5 )\n    4.5\n\n","base.dists.poisson.median":"\nbase.dists.poisson.median( λ )\n    Returns the median of a Poisson distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: integer\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.poisson.median( 11.0 )\n    11\n    > v = base.dists.poisson.median( 4.5 )\n    4\n\n","base.dists.poisson.mgf":"\nbase.dists.poisson.mgf( x, λ )\n    Evaluates the moment-generating function (MGF) for a Poisson distribution\n    with mean parameter `λ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.poisson.mgf( 1.0, 1.5 )\n    ~13.163\n    > y = base.dists.poisson.mgf( 0.5, 0.5 )\n    ~1.383\n    > y = base.dists.poisson.mgf( NaN, 0.5 )\n    NaN\n    > y = base.dists.poisson.mgf( 0.0, NaN )\n    NaN\n    > y = base.dists.poisson.mgf( -2.0, -1.0 )\n    NaN\n\n\nbase.dists.poisson.mgf.factory( λ )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Poisson distribution with mean parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.poisson.mgf.factory( 2.0 );\n    > var y = myMGF( 0.1 )\n    ~1.234\n\n","base.dists.poisson.mgf.factory":"\nbase.dists.poisson.mgf.factory( λ )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Poisson distribution with mean parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.poisson.mgf.factory( 2.0 );\n    > var y = myMGF( 0.1 )\n    ~1.234","base.dists.poisson.mode":"\nbase.dists.poisson.mode( λ )\n    Returns the mode of a Poisson distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: integer\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.poisson.mode( 11.0 )\n    11\n    > v = base.dists.poisson.mode( 4.5 )\n    4\n\n","base.dists.poisson.pmf":"\nbase.dists.poisson.pmf( x, λ )\n    Evaluates the probability mass function (PMF) for a Poisson\n    distribution with mean parameter `λ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PMF.\n\n    Examples\n    --------\n    > var y = base.dists.poisson.pmf( 4.0, 3.0 )\n    ~0.168\n    > y = base.dists.poisson.pmf( 1.0, 3.0 )\n    ~0.149\n    > y = base.dists.poisson.pmf( -1.0, 2.0 )\n    0.0\n    > y = base.dists.poisson.pmf( 0.0, NaN )\n    NaN\n    > y = base.dists.poisson.pmf( NaN, 0.5 )\n    NaN\n\n    // Negative mean parameter:\n    > y = base.dists.poisson.pmf( 2.0, -0.5 )\n    NaN\n\n    // Degenerate distribution at `λ = 0`:\n    > y = base.dists.poisson.pmf( 2.0, 0.0 )\n    0.0\n    > y = base.dists.poisson.pmf( 0.0, 0.0 )\n    1.0\n\n\nbase.dists.poisson.pmf.factory( λ )\n    Returns a function for evaluating the probability mass function (PMF)\n    of a Poisson distribution with mean parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var mypmf = base.dists.poisson.pmf.factory( 1.0 );\n    > var y = mypmf( 3.0 )\n    ~0.061\n    > y = mypmf( 1.0 )\n    ~0.368\n\n","base.dists.poisson.pmf.factory":"\nbase.dists.poisson.pmf.factory( λ )\n    Returns a function for evaluating the probability mass function (PMF)\n    of a Poisson distribution with mean parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var mypmf = base.dists.poisson.pmf.factory( 1.0 );\n    > var y = mypmf( 3.0 )\n    ~0.061\n    > y = mypmf( 1.0 )\n    ~0.368","base.dists.poisson.Poisson":"\nbase.dists.poisson.Poisson( [λ] )\n    Returns a Poisson distribution object.\n\n    Parameters\n    ----------\n    λ: number (optional)\n        Mean parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    poisson: Object\n        Distribution instance.\n\n    poisson.lambda: number\n        Mean parameter. If set, the value must be greater than `0`.\n\n    poisson.entropy: number\n        Read-only property which returns the differential entropy.\n\n    poisson.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    poisson.mean: number\n        Read-only property which returns the expected value.\n\n    poisson.median: number\n        Read-only property which returns the median.\n\n    poisson.mode: number\n        Read-only property which returns the mode.\n\n    poisson.skewness: number\n        Read-only property which returns the skewness.\n\n    poisson.stdev: number\n        Read-only property which returns the standard deviation.\n\n    poisson.variance: number\n        Read-only property which returns the variance.\n\n    poisson.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    poisson.logpmf: Function\n        Evaluates the natural logarithm of the probability mass function (PMF).\n\n    poisson.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    poisson.pmf: Function\n        Evaluates the probability mass function (PMF).\n\n    poisson.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var poisson = base.dists.poisson.Poisson( 6.0 );\n    > poisson.lambda\n    6.0\n    > poisson.entropy\n    ~2.3\n    > poisson.kurtosis\n    ~0.167\n    > poisson.mean\n    6.0\n    > poisson.median\n    6.0\n    > poisson.mode\n    6.0\n    > poisson.skewness\n    ~0.408\n    > poisson.stdev\n    ~2.449\n    > poisson.variance\n    6.0\n    > poisson.cdf( 4.0 )\n    ~0.285\n    > poisson.logpmf( 2.0 )\n    ~-3.11\n    > poisson.mgf( 0.5 )\n    ~49.025\n    > poisson.pmf( 2.0 )\n    ~0.045\n    > poisson.quantile( 0.5 )\n    6.0\n\n","base.dists.poisson.quantile":"\nbase.dists.poisson.quantile( p, λ )\n    Evaluates the quantile function for a Poisson distribution with mean\n    parameter `λ` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.poisson.quantile( 0.5, 2.0 )\n    2\n    > y = base.dists.poisson.quantile( 0.9, 4.0 )\n    7\n    > y = base.dists.poisson.quantile( 0.1, 200.0 )\n    182\n\n    > y = base.dists.poisson.quantile( 1.1, 0.0 )\n    NaN\n    > y = base.dists.poisson.quantile( -0.2, 0.0 )\n    NaN\n\n    > y = base.dists.poisson.quantile( NaN, 0.5 )\n    NaN\n    > y = base.dists.poisson.quantile( 0.0, NaN )\n    NaN\n\n    // Negative mean parameter:\n    > y = base.dists.poisson.quantile( 2.0, -1.0 )\n    NaN\n\n    // Degenerate distribution at `λ = 0`:\n    > y = base.dists.poisson.quantile( 0.1, 0.0 )\n    0.0\n    > y = base.dists.poisson.quantile( 0.9, 0.0 )\n    0.0\n\n\nbase.dists.poisson.quantile.factory( λ )\n    Returns a function for evaluating the quantile function of a Poisson\n    distribution with mean parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.poisson.quantile.factory( 0.4 );\n    > var y = myQuantile( 0.4 )\n    0.0\n    > y = myQuantile( 1.0 )\n    Infinity\n\n","base.dists.poisson.quantile.factory":"\nbase.dists.poisson.quantile.factory( λ )\n    Returns a function for evaluating the quantile function of a Poisson\n    distribution with mean parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.poisson.quantile.factory( 0.4 );\n    > var y = myQuantile( 0.4 )\n    0.0\n    > y = myQuantile( 1.0 )\n    Infinity","base.dists.poisson.skewness":"\nbase.dists.poisson.skewness( λ )\n    Returns the skewness of a Poisson distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a nonpositive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.poisson.skewness( 11.0 )\n    ~0.302\n    > v = base.dists.poisson.skewness( 4.5 )\n    ~0.471\n\n","base.dists.poisson.stdev":"\nbase.dists.poisson.stdev( λ )\n    Returns the standard deviation of a Poisson distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.poisson.stdev( 11.0 )\n    ~3.317\n    > v = base.dists.poisson.stdev( 4.5 )\n    ~2.121\n\n","base.dists.poisson.variance":"\nbase.dists.poisson.variance( λ )\n    Returns the variance of a Poisson distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.poisson.variance( 11.0 )\n    11.0\n    > v = base.dists.poisson.variance( 4.5 )\n    4.5\n\n","base.dists.rayleigh.cdf":"\nbase.dists.rayleigh.cdf( x, sigma )\n    Evaluates the cumulative distribution function (CDF) for a Rayleigh\n    distribution with scale parameter `sigma` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `sigma`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.rayleigh.cdf( 2.0, 3.0 )\n    ~0.199\n    > y = base.dists.rayleigh.cdf( 1.0, 2.0 )\n    ~0.118\n    > y = base.dists.rayleigh.cdf( -1.0, 4.0 )\n    0.0\n    > y = base.dists.rayleigh.cdf( NaN, 1.0 )\n    NaN\n    > y = base.dists.rayleigh.cdf( 0.0, NaN )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.rayleigh.cdf( 2.0, -1.0 )\n    NaN\n\n    // Degenerate distribution when `sigma = 0.0`:\n    > y = base.dists.rayleigh.cdf( -2.0, 0.0 )\n    0.0\n    > y = base.dists.rayleigh.cdf( 0.0, 0.0 )\n    1.0\n    > y = base.dists.rayleigh.cdf( 2.0, 0.0 )\n    1.0\n\n\nbase.dists.rayleigh.cdf.factory( sigma )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Rayleigh distribution with scale parameter `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.rayleigh.cdf.factory( 0.5 );\n    > var y = myCDF( 1.0 )\n    ~0.865\n    > y = myCDF( 0.5 )\n    ~0.393\n\n","base.dists.rayleigh.cdf.factory":"\nbase.dists.rayleigh.cdf.factory( sigma )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Rayleigh distribution with scale parameter `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.rayleigh.cdf.factory( 0.5 );\n    > var y = myCDF( 1.0 )\n    ~0.865\n    > y = myCDF( 0.5 )\n    ~0.393","base.dists.rayleigh.entropy":"\nbase.dists.rayleigh.entropy( σ )\n    Returns the differential entropy of a Rayleigh distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.rayleigh.entropy( 11.0 )\n    ~3.34\n    > v = base.dists.rayleigh.entropy( 4.5 )\n    ~2.446\n\n","base.dists.rayleigh.kurtosis":"\nbase.dists.rayleigh.kurtosis( σ )\n    Returns the excess kurtosis of a Rayleigh distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.rayleigh.kurtosis( 11.0 )\n    ~0.245\n    > v = base.dists.rayleigh.kurtosis( 4.5 )\n    ~0.245\n\n","base.dists.rayleigh.logcdf":"\nbase.dists.rayleigh.logcdf( x, sigma )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    Rayleigh distribution with scale parameter `sigma` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `sigma`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.rayleigh.logcdf( 2.0, 3.0 )\n    ~-1.613\n    > y = base.dists.rayleigh.logcdf( 1.0, 2.0 )\n    ~-2.141\n    > y = base.dists.rayleigh.logcdf( -1.0, 4.0 )\n    -Infinity\n    > y = base.dists.rayleigh.logcdf( NaN, 1.0 )\n    NaN\n    > y = base.dists.rayleigh.logcdf( 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.rayleigh.logcdf( 2.0, -1.0 )\n    NaN\n\n\nbase.dists.rayleigh.logcdf.factory( sigma )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Rayleigh distribution with scale parameter\n    `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.rayleigh.logcdf.factory( 0.5 );\n    > var y = mylogcdf( 1.0 )\n    ~-0.145\n    > y = mylogcdf( 0.5 )\n    ~-0.933\n\n","base.dists.rayleigh.logcdf.factory":"\nbase.dists.rayleigh.logcdf.factory( sigma )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Rayleigh distribution with scale parameter\n    `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.rayleigh.logcdf.factory( 0.5 );\n    > var y = mylogcdf( 1.0 )\n    ~-0.145\n    > y = mylogcdf( 0.5 )\n    ~-0.933","base.dists.rayleigh.logpdf":"\nbase.dists.rayleigh.logpdf( x, sigma )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    Rayleigh distribution with scale parameter `sigma` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `sigma`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.rayleigh.logpdf( 0.3, 1.0 )\n    ~-1.249\n    > y = base.dists.rayleigh.logpdf( 2.0, 0.8 )\n    ~-1.986\n    > y = base.dists.rayleigh.logpdf( -1.0, 0.5 )\n    -Infinity\n    > y = base.dists.rayleigh.logpdf( 0.0, NaN )\n    NaN\n    > y = base.dists.rayleigh.logpdf( NaN, 2.0 )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.rayleigh.logpdf( 2.0, -1.0 )\n    NaN\n\n\nbase.dists.rayleigh.logpdf.factory( sigma )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Rayleigh distribution with scale parameter `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.rayleigh.logpdf.factory( 4.0 );\n    > var y = mylogpdf( 6.0 )\n    ~-2.106\n    > y = mylogpdf( 4.0 )\n    ~-1.886\n\n","base.dists.rayleigh.logpdf.factory":"\nbase.dists.rayleigh.logpdf.factory( sigma )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Rayleigh distribution with scale parameter `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.rayleigh.logpdf.factory( 4.0 );\n    > var y = mylogpdf( 6.0 )\n    ~-2.106\n    > y = mylogpdf( 4.0 )\n    ~-1.886","base.dists.rayleigh.mean":"\nbase.dists.rayleigh.mean( σ )\n    Returns the expected value of a Rayleigh distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.rayleigh.mean( 11.0 )\n    ~13.786\n    > v = base.dists.rayleigh.mean( 4.5 )\n    ~5.64\n\n","base.dists.rayleigh.median":"\nbase.dists.rayleigh.median( σ )\n    Returns the median of a Rayleigh distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.rayleigh.median( 11.0 )\n    ~12.952\n    > v = base.dists.rayleigh.median( 4.5 )\n    ~5.298\n\n","base.dists.rayleigh.mgf":"\nbase.dists.rayleigh.mgf( t, sigma )\n    Evaluates the moment-generating function (MGF) for a Rayleigh distribution\n    with scale parameter `sigma` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `sigma`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.rayleigh.mgf( 1.0, 3.0 )\n    ~678.508\n    > y = base.dists.rayleigh.mgf( 1.0, 2.0 )\n    ~38.65\n    > y = base.dists.rayleigh.mgf( -1.0, 4.0 )\n    ~-0.947\n    > y = base.dists.rayleigh.mgf( NaN, 1.0 )\n    NaN\n    > y = base.dists.rayleigh.mgf( 0.0, NaN )\n    NaN\n    > y = base.dists.rayleigh.mgf( 0.5, -1.0 )\n    NaN\n\n\nbase.dists.rayleigh.mgf.factory( sigma )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Rayleigh distribution with scale parameter `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.rayleigh.mgf.factory( 0.5 );\n    > var y = myMGF( 1.0 )\n    ~2.715\n    > y = myMGF( 0.5 )\n    ~1.888\n\n","base.dists.rayleigh.mgf.factory":"\nbase.dists.rayleigh.mgf.factory( sigma )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Rayleigh distribution with scale parameter `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.rayleigh.mgf.factory( 0.5 );\n    > var y = myMGF( 1.0 )\n    ~2.715\n    > y = myMGF( 0.5 )\n    ~1.888","base.dists.rayleigh.mode":"\nbase.dists.rayleigh.mode( σ )\n    Returns the mode of a Rayleigh distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.rayleigh.mode( 11.0 )\n    11.0\n    > v = base.dists.rayleigh.mode( 4.5 )\n    4.5\n\n","base.dists.rayleigh.pdf":"\nbase.dists.rayleigh.pdf( x, sigma )\n    Evaluates the probability density function (PDF) for a Rayleigh\n    distribution with scale parameter `sigma` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `sigma`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.rayleigh.pdf( 0.3, 1.0 )\n    ~0.287\n    > y = base.dists.rayleigh.pdf( 2.0, 0.8 )\n    ~0.137\n    > y = base.dists.rayleigh.pdf( -1.0, 0.5 )\n    0.0\n    > y = base.dists.rayleigh.pdf( 0.0, NaN )\n    NaN\n    > y = base.dists.rayleigh.pdf( NaN, 2.0 )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.rayleigh.pdf( 2.0, -1.0 )\n    NaN\n\n    // Degenerate distribution when `sigma = 0.0`:\n    > y = base.dists.rayleigh.pdf( -2.0, 0.0 )\n    0.0\n    > y = base.dists.rayleigh.pdf( 0.0, 0.0 )\n    Infinity\n    > y = base.dists.rayleigh.pdf( 2.0, 0.0 )\n    0.0\n\n\nbase.dists.rayleigh.pdf.factory( sigma )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Rayleigh distribution with scale parameter `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.rayleigh.pdf.factory( 4.0 );\n    > var y = myPDF( 6.0 )\n    ~0.122\n    > y = myPDF( 4.0 )\n    ~0.152\n\n","base.dists.rayleigh.pdf.factory":"\nbase.dists.rayleigh.pdf.factory( sigma )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Rayleigh distribution with scale parameter `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.rayleigh.pdf.factory( 4.0 );\n    > var y = myPDF( 6.0 )\n    ~0.122\n    > y = myPDF( 4.0 )\n    ~0.152","base.dists.rayleigh.quantile":"\nbase.dists.rayleigh.quantile( p, sigma )\n    Evaluates the quantile function for a Rayleigh distribution with scale\n    parameter `sigma` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative probability for `sigma`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.rayleigh.quantile( 0.8, 1.0 )\n    ~1.794\n    > y = base.dists.rayleigh.quantile( 0.5, 4.0 )\n    ~4.71\n\n    > y = base.dists.rayleigh.quantile( 1.1, 1.0 )\n    NaN\n    > y = base.dists.rayleigh.quantile( -0.2, 1.0 )\n    NaN\n\n    > y = base.dists.rayleigh.quantile( NaN, 1.0 )\n    NaN\n    > y = base.dists.rayleigh.quantile( 0.0, NaN )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.rayleigh.quantile( 0.5, -1.0 )\n    NaN\n\n\nbase.dists.rayleigh.quantile.factory( sigma )\n    Returns a function for evaluating the quantile function of a Rayleigh\n    distribution with scale parameter `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.rayleigh.quantile.factory( 0.4 );\n    > var y = myQuantile( 0.4 )\n    ~0.404\n    > y = myQuantile( 1.0 )\n    Infinity\n\n","base.dists.rayleigh.quantile.factory":"\nbase.dists.rayleigh.quantile.factory( sigma )\n    Returns a function for evaluating the quantile function of a Rayleigh\n    distribution with scale parameter `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.rayleigh.quantile.factory( 0.4 );\n    > var y = myQuantile( 0.4 )\n    ~0.404\n    > y = myQuantile( 1.0 )\n    Infinity","base.dists.rayleigh.Rayleigh":"\nbase.dists.rayleigh.Rayleigh( [σ] )\n    Returns a Rayleigh distribution object.\n\n    Parameters\n    ----------\n    σ: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    rayleigh: Object\n        Distribution instance.\n\n    rayleigh.sigma: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    rayleigh.entropy: number\n        Read-only property which returns the differential entropy.\n\n    rayleigh.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    rayleigh.mean: number\n        Read-only property which returns the expected value.\n\n    rayleigh.median: number\n        Read-only property which returns the median.\n\n    rayleigh.mode: number\n        Read-only property which returns the mode.\n\n    rayleigh.skewness: number\n        Read-only property which returns the skewness.\n\n    rayleigh.stdev: number\n        Read-only property which returns the standard deviation.\n\n    rayleigh.variance: number\n        Read-only property which returns the variance.\n\n    rayleigh.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    rayleigh.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    rayleigh.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    rayleigh.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    rayleigh.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    rayleigh.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var rayleigh = base.dists.rayleigh.Rayleigh( 6.0 );\n    > rayleigh.sigma\n    6.0\n    > rayleigh.entropy\n    ~2.734\n    > rayleigh.kurtosis\n    ~0.245\n    > rayleigh.mean\n    ~7.52\n    > rayleigh.median\n    ~7.064\n    > rayleigh.mode\n    6.0\n    > rayleigh.skewness\n    ~0.631\n    > rayleigh.stdev\n    ~3.931\n    > rayleigh.variance\n    ~15.451\n    > rayleigh.cdf( 1.0 )\n    ~0.014\n    > rayleigh.logcdf( 1.0 )\n    ~-4.284\n    > rayleigh.logpdf( 1.5 )\n    ~-3.209\n    > rayleigh.mgf( -0.5 )\n    ~-0.91\n    > rayleigh.pdf( 1.5 )\n    ~0.04\n    > rayleigh.quantile( 0.5 )\n    ~7.064\n\n","base.dists.rayleigh.skewness":"\nbase.dists.rayleigh.skewness( σ )\n    Returns the skewness of a Rayleigh distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.rayleigh.skewness( 11.0 )\n    ~0.631\n    > v = base.dists.rayleigh.skewness( 4.5 )\n    ~0.631\n\n","base.dists.rayleigh.stdev":"\nbase.dists.rayleigh.stdev( σ )\n    Returns the standard deviation of a Rayleigh distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.rayleigh.stdev( 9.0 )\n    ~5.896\n    > v = base.dists.rayleigh.stdev( 4.5 )\n    ~2.948\n\n","base.dists.rayleigh.variance":"\nbase.dists.rayleigh.variance( σ )\n    Returns the variance of a Rayleigh distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.rayleigh.variance( 9.0 )\n    ~34.765\n    > v = base.dists.rayleigh.variance( 4.5 )\n    ~8.691\n\n","base.dists.signrank.cdf":"\nbase.dists.signrank.cdf( x, n )\n    Evaluates the cumulative distribution function (CDF) for the distribution of\n    the Wilcoxon signed rank test statistic with `n` observations.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `x`, the function returns `NaN`.\n\n    If not provided a positive integer for `n`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Number of observations.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.signrank.cdf( 3, 7 )\n    ~0.039\n    > y = base.dists.signrank.cdf( 1.8, 3 )\n    ~0.375\n    > y = base.dists.signrank.cdf( -1.0, 40 )\n    0.0\n    > y = base.dists.signrank.cdf( NaN, 10 )\n    NaN\n    > y = base.dists.signrank.cdf( 0.0, NaN )\n    NaN\n\n\nbase.dists.signrank.cdf.factory( n )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of the distribution of the Wilcoxon signed rank test statistic.\n\n    Parameters\n    ----------\n    n: integer\n        Number of observations.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.signrank.cdf.factory( 8 );\n    > var y = myCDF( 5.7 )\n    ~0.055\n    > y = myCDF( 2.2 )\n    ~0.012\n\n","base.dists.signrank.cdf.factory":"\nbase.dists.signrank.cdf.factory( n )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of the distribution of the Wilcoxon signed rank test statistic.\n\n    Parameters\n    ----------\n    n: integer\n        Number of observations.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.signrank.cdf.factory( 8 );\n    > var y = myCDF( 5.7 )\n    ~0.055\n    > y = myCDF( 2.2 )\n    ~0.012","base.dists.signrank.pdf":"\nbase.dists.signrank.pdf( x, n )\n    Evaluates the probability density function (PDF) for the distribution of\n    the Wilcoxon signed rank test statistic with `n` observations.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `x`, the function returns `NaN`.\n\n    If not provided a positive integer for `n`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Number of observations.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.signrank.pdf( 3, 7 )\n    ~0.0156\n    > y = base.dists.signrank.pdf( 1.8, 3 )\n    0.0\n    > y = base.dists.signrank.pdf( -1.0, 40 )\n    0.0\n    > y = base.dists.signrank.pdf( NaN, 10 )\n    NaN\n    > y = base.dists.signrank.pdf( 0.0, NaN )\n    NaN\n\n\nbase.dists.signrank.pdf.factory( n )\n    Returns a function for evaluating the probability density function (PDF)\n    of the distribution of the Wilcoxon signed rank test statistic.\n\n    Parameters\n    ----------\n    n: integer\n        Number of observations.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.signrank.pdf.factory( 8 );\n    > var y = myPDF( 6.0 )\n    ~0.0156\n    > y = myPDF( 2.0 )\n    ~0.0039\n\n","base.dists.signrank.pdf.factory":"\nbase.dists.signrank.pdf.factory( n )\n    Returns a function for evaluating the probability density function (PDF)\n    of the distribution of the Wilcoxon signed rank test statistic.\n\n    Parameters\n    ----------\n    n: integer\n        Number of observations.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.signrank.pdf.factory( 8 );\n    > var y = myPDF( 6.0 )\n    ~0.0156\n    > y = myPDF( 2.0 )\n    ~0.0039","base.dists.signrank.quantile":"\nbase.dists.signrank.quantile( p, n )\n    Evaluates the quantile function for the Wilcoxon signed rank test statistic\n    with `n` observations at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a positive integer for `n`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    n: integer\n        Number of observations.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.signrank.quantile( 0.8, 5 )\n    11\n    > y = base.dists.signrank.quantile( 0.5, 4 )\n    5\n\n    > y = base.dists.signrank.quantile( 1.1, 5 )\n    NaN\n    > y = base.dists.signrank.quantile( -0.2, 5 )\n    NaN\n\n    > y = base.dists.signrank.quantile( NaN, 5 )\n    NaN\n    > y = base.dists.signrank.quantile( 0.0, NaN )\n    NaN\n\n\nbase.dists.signrank.quantile.factory( n )\n    Returns a function for evaluating the quantile function of the Wilcoxon\n    signed rank test statistic with `n` observations.\n\n    Parameters\n    ----------\n    n: integer\n        Number of observations.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.signrank.quantile.factory( 8 );\n    > var y = myQuantile( 0.4 )\n    16\n    > y = myQuantile( 1.0 )\n    36\n\n","base.dists.signrank.quantile.factory":"\nbase.dists.signrank.quantile.factory( n )\n    Returns a function for evaluating the quantile function of the Wilcoxon\n    signed rank test statistic with `n` observations.\n\n    Parameters\n    ----------\n    n: integer\n        Number of observations.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.signrank.quantile.factory( 8 );\n    > var y = myQuantile( 0.4 )\n    16\n    > y = myQuantile( 1.0 )\n    36","base.dists.studentizedRange.cdf":"\nbase.dists.studentizedRange.cdf( x, r, v[, nranges] )\n    Evaluates the cumulative distribution function (CDF) of a studentized range\n    distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `r < 2` or `v < 2`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    r: number\n        Sample size for range (same for each group).\n\n    v: number\n        Degrees of freedom.\n\n    nranges: integer\n        Number of groups whose maximum range is considered. Default: 1.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.studentizedRange.cdf( 0.5, 3.0, 2.0 )\n    ~0.0644\n\n    > y = base.dists.studentizedRange.cdf( 12.1, 17.0, 2.0 )\n    ~0.913\n\n\nbase.dists.studentizedRange.cdf.factory( r, v[, nranges] )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a studentized range distribution.\n\n    Parameters\n    ----------\n    r: number\n        Number of samples.\n\n    v: number\n        Degrees of freedom.\n\n    nranges: integer\n        Number of groups whose maximum range is considered. Default: 1.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.studentizedRange.cdf.factory( 3.0, 2.0 );\n    > var y = mycdf( 3.0 )\n    ~0.712\n    > y = mycdf( 1.0 )\n    ~0.216\n\n","base.dists.studentizedRange.cdf.factory":"\nbase.dists.studentizedRange.cdf.factory( r, v[, nranges] )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a studentized range distribution.\n\n    Parameters\n    ----------\n    r: number\n        Number of samples.\n\n    v: number\n        Degrees of freedom.\n\n    nranges: integer\n        Number of groups whose maximum range is considered. Default: 1.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.studentizedRange.cdf.factory( 3.0, 2.0 );\n    > var y = mycdf( 3.0 )\n    ~0.712\n    > y = mycdf( 1.0 )\n    ~0.216","base.dists.studentizedRange.quantile":"\nbase.dists.studentizedRange.quantile( p, r, v[, nranges] )\n    Evaluates the quantile function for a studentized range distribution.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `r < 2` or `v < 2`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    r: number\n        Sample size for range (same for each group).\n\n    v: number\n        Degrees of freedom.\n\n    nranges: integer\n        Number of groups whose maximum range is considered. Default: 1.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = quantile( 0.5, 3.0, 2.0 )\n     ~0.0644\n\n    > y = quantile( 0.9, 17.0, 2.0 )\n     ~0.913\n\n    > y = quantile( 0.5, 3.0, 2.0, 2 )\n     ~0.01\n\n    > y = base.dists.studentizedRange.quantile( -0.2, 3.0, 3.0 )\n    NaN\n\n    > y = base.dists.studentizedRange.quantile( NaN, 2.0, 2.0 )\n    NaN\n    > y = base.dists.studentizedRange.quantile( 0.0, NaN, 2.0 )\n    NaN\n\n    > y = base.dists.studentizedRange.quantile( 0.5, -1.0, 2.0 )\n    NaN\n\n\nbase.dists.studentizedRange.quantile.factory( r, v[, nranges] )\n    Returns a function for evaluating the quantile function of a studentized\n    range distribution.\n\n    Parameters\n    ----------\n    r: number\n        Sample size for range (same for each group).\n\n    v: number\n        Degrees of freedom.\n\n    nranges: integer\n        Number of groups whose maximum range is considered. Default: 1.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = quantile.factory( 3.0, 3.0 );\n    > var y = myQuantile( 0.5 )\n   ~1.791\n\n    > y = myQuantile( 0.8 )\n   ~3.245\n\n","base.dists.studentizedRange.quantile.factory":"\nbase.dists.studentizedRange.quantile.factory( r, v[, nranges] )\n    Returns a function for evaluating the quantile function of a studentized\n    range distribution.\n\n    Parameters\n    ----------\n    r: number\n        Sample size for range (same for each group).\n\n    v: number\n        Degrees of freedom.\n\n    nranges: integer\n        Number of groups whose maximum range is considered. Default: 1.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = quantile.factory( 3.0, 3.0 );\n    > var y = myQuantile( 0.5 )\n   ~1.791\n\n    > y = myQuantile( 0.8 )\n   ~3.245","base.dists.t.cdf":"\nbase.dists.t.cdf( x, v )\n    Evaluates the cumulative distribution function (CDF) for a Student's t\n    distribution with degrees of freedom `v` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a non-positive value for `v`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.t.cdf( 2.0, 0.1 )\n    ~0.611\n    > y = base.dists.t.cdf( 1.0, 2.0 )\n    ~0.789\n    > y = base.dists.t.cdf( -1.0, 4.0 )\n    ~0.187\n    > y = base.dists.t.cdf( NaN, 1.0 )\n    NaN\n    > y = base.dists.t.cdf( 0.0, NaN )\n    NaN\n    > y = base.dists.t.cdf( 2.0, -1.0 )\n    NaN\n\n\nbase.dists.t.cdf.factory( v )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Student's t distribution with degrees of freedom `v`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.t.cdf.factory( 0.5 );\n    > var y = mycdf( 3.0 )\n    ~0.816\n    > y = mycdf( 1.0 )\n    ~0.699\n\n","base.dists.t.cdf.factory":"\nbase.dists.t.cdf.factory( v )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Student's t distribution with degrees of freedom `v`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.t.cdf.factory( 0.5 );\n    > var y = mycdf( 3.0 )\n    ~0.816\n    > y = mycdf( 1.0 )\n    ~0.699","base.dists.t.entropy":"\nbase.dists.t.entropy( v )\n    Returns the differential entropy of a Student's t distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `v < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.t.entropy( 11.0 )\n    ~1.512\n    > v = base.dists.t.entropy( 4.5 )\n    ~1.652\n\n","base.dists.t.kurtosis":"\nbase.dists.t.kurtosis( v )\n    Returns the excess kurtosis of a Student's t distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `v <= 2`, the function returns `NaN`.\n\n    If provided `2 < v <= 4`, the function returns positive infinity.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.t.kurtosis( 11.0 )\n    ~0.857\n    > v = base.dists.t.kurtosis( 4.5 )\n    12.0\n\n","base.dists.t.logcdf":"\nbase.dists.t.logcdf( x, v )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a Student's t distribution with degrees of freedom `v` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a non-positive value for `v`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.t.logcdf( 2.0, 0.1 )\n    ~-0.493\n    > y = base.dists.t.logcdf( 1.0, 2.0 )\n    ~-0.237\n    > y = base.dists.t.logcdf( -1.0, 4.0 )\n    ~-1.677\n    > y = base.dists.t.logcdf( NaN, 1.0 )\n    NaN\n    > y = base.dists.t.logcdf( 0.0, NaN )\n    NaN\n    > y = base.dists.t.logcdf( 2.0, -1.0 )\n    NaN\n\n\nbase.dists.t.logcdf.factory( v )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Student's t distribution with degrees of\n    freedom `v`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.t.logcdf.factory( 0.5 );\n    > var y = mylogcdf( 3.0 )\n    ~-0.203\n    > y = mylogcdf( 1.0 )\n    ~-0.358\n\n","base.dists.t.logcdf.factory":"\nbase.dists.t.logcdf.factory( v )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Student's t distribution with degrees of\n    freedom `v`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.t.logcdf.factory( 0.5 );\n    > var y = mylogcdf( 3.0 )\n    ~-0.203\n    > y = mylogcdf( 1.0 )\n    ~-0.358","base.dists.t.logpdf":"\nbase.dists.t.logpdf( x, v )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a Student's t distribution with degrees of freedom `v` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a non-positive value for `v`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.t.logpdf( 0.3, 4.0 )\n    ~-1.036\n    > y = base.dists.t.logpdf( 2.0, 0.7 )\n    ~-2.841\n    > y = base.dists.t.logpdf( -1.0, 0.5 )\n    ~-2.134\n    > y = base.dists.t.logpdf( 0.0, NaN )\n    NaN\n    > y = base.dists.t.logpdf( NaN, 2.0 )\n    NaN\n    > y = base.dists.t.logpdf( 2.0, -1.0 )\n    NaN\n\n\nbase.dists.t.logpdf.factory( v )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a Student's t distribution with degrees of\n    freedom `v`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.t.logpdf.factory( 3.0 );\n    > var y = mylogPDF( 1.0 )\n    ~-1.576\n\n","base.dists.t.logpdf.factory":"\nbase.dists.t.logpdf.factory( v )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a Student's t distribution with degrees of\n    freedom `v`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.t.logpdf.factory( 3.0 );\n    > var y = mylogPDF( 1.0 )\n    ~-1.576","base.dists.t.mean":"\nbase.dists.t.mean( v )\n    Returns the expected value of a Student's t distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `v <= 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.t.mean( 11.0 )\n    0.0\n    > v = base.dists.t.mean( 4.5 )\n    0.0\n\n","base.dists.t.median":"\nbase.dists.t.median( v )\n    Returns the median of a Student's t distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `v < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.t.median( 11.0 )\n    0.0\n    > v = base.dists.t.median( 4.5 )\n    0.0\n\n","base.dists.t.mode":"\nbase.dists.t.mode( v )\n    Returns the mode of a Student's t distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `v < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.t.mode( 11.0 )\n    0.0\n    > v = base.dists.t.mode( 4.5 )\n    0.0\n\n","base.dists.t.pdf":"\nbase.dists.t.pdf( x, v )\n    Evaluates the probability density function (PDF) for a Student's t\n    distribution with degrees of freedom `v` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a non-positive value for `v`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.t.pdf( 0.3, 4.0 )\n    ~0.355\n    > y = base.dists.t.pdf( 2.0, 0.7 )\n    ~0.058\n    > y = base.dists.t.pdf( -1.0, 0.5 )\n    ~0.118\n    > y = base.dists.t.pdf( 0.0, NaN )\n    NaN\n    > y = base.dists.t.pdf( NaN, 2.0 )\n    NaN\n    > y = base.dists.t.pdf( 2.0, -1.0 )\n    NaN\n\n\nbase.dists.t.pdf.factory( v )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Student's t distribution with degrees of freedom `v`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.t.pdf.factory( 3.0 );\n    > var y = myPDF( 1.0 )\n    ~0.207\n\n","base.dists.t.pdf.factory":"\nbase.dists.t.pdf.factory( v )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Student's t distribution with degrees of freedom `v`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.t.pdf.factory( 3.0 );\n    > var y = myPDF( 1.0 )\n    ~0.207","base.dists.t.quantile":"\nbase.dists.t.quantile( p, v )\n    Evaluates the quantile function for a Student's t distribution with degrees\n    of freedom `v` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a non-positive value for `v`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.t.quantile( 0.8, 1.0 )\n    ~1.376\n    > y = base.dists.t.quantile( 0.1, 1.0 )\n    ~-3.078\n    > y = base.dists.t.quantile( 0.5, 0.1 )\n    0.0\n\n    > y = base.dists.t.quantile( -0.2, 0.1 )\n    NaN\n\n    > y = base.dists.t.quantile( NaN, 1.0 )\n    NaN\n    > y = base.dists.t.quantile( 0.0, NaN )\n    NaN\n\n    > y = base.dists.t.quantile( 0.5, -1.0 )\n    NaN\n\n\nbase.dists.t.quantile.factory( v )\n    Returns a function for evaluating the quantile function of a Student's t\n    distribution with degrees of freedom `v`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.t.quantile.factory( 4.0 );\n    > var y = myQuantile( 0.2 )\n    ~-0.941\n    > y = myQuantile( 0.9 )\n    ~1.533\n\n","base.dists.t.quantile.factory":"\nbase.dists.t.quantile.factory( v )\n    Returns a function for evaluating the quantile function of a Student's t\n    distribution with degrees of freedom `v`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.t.quantile.factory( 4.0 );\n    > var y = myQuantile( 0.2 )\n    ~-0.941\n    > y = myQuantile( 0.9 )\n    ~1.533","base.dists.t.skewness":"\nbase.dists.t.skewness( v )\n    Returns the skewness of a Student's t distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `v <= 3`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.t.skewness( 11.0 )\n    0.0\n    > v = base.dists.t.skewness( 4.5 )\n    0.0\n\n","base.dists.t.stdev":"\nbase.dists.t.stdev( v )\n    Returns the standard deviation of a Student's t distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `1 < v <= 2`, the function returns positive infinity.\n\n    If provided `v <= 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.t.stdev( 9.0 )\n    ~1.134\n    > v = base.dists.t.stdev( 4.5 )\n    ~1.342\n\n","base.dists.t.T":"\nbase.dists.t.T( [v] )\n    Returns a Student's t distribution object.\n\n    Parameters\n    ----------\n    v: number (optional)\n        Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    t: Object\n        Distribution instance.\n\n    t.v: number\n        Degrees of freedom. If set, the value must be greater than `0`.\n\n    t.entropy: number\n        Read-only property which returns the differential entropy.\n\n    t.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    t.mean: number\n        Read-only property which returns the expected value.\n\n    t.median: number\n        Read-only property which returns the median.\n\n    t.mode: number\n        Read-only property which returns the mode.\n\n    t.skewness: number\n        Read-only property which returns the skewness.\n\n    t.stdev: number\n        Read-only property which returns the standard deviation.\n\n    t.variance: number\n        Read-only property which returns the variance.\n\n    t.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    t.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    t.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    t.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    t.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var t = base.dists.t.T( 6.0 );\n    > t.v\n    6.0\n    > t.entropy\n    ~1.592\n    > t.kurtosis\n    3.0\n    > t.mean\n    0.0\n    > t.median\n    0.0\n    > t.mode\n    0.0\n    > t.skewness\n    0.0\n    > t.stdev\n    ~1.225\n    > t.variance\n    1.5\n    > t.cdf( 1.0 )\n    ~0.822\n    > t.logcdf( 1.0 )\n    ~-0.196\n    > t.logpdf( 1.5 )\n    ~-2.075\n    > t.pdf( 1.5 )\n    ~0.126\n    > t.quantile( 0.8 )\n    ~0.906\n\n","base.dists.t.variance":"\nbase.dists.t.variance( v )\n    Returns the variance of a Student's t distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `1 < v <= 2`, the function returns positive infinity.\n\n    If provided `v <= 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.t.variance( 9.0 )\n    ~1.286\n    > v = base.dists.t.variance( 4.5 )\n    ~1.8\n\n","base.dists.triangular.cdf":"\nbase.dists.triangular.cdf( x, a, b, c )\n    Evaluates the cumulative distribution function (CDF) for a triangular\n    distribution with minimum support `a`, maximum support `b`, and mode `c` at\n    a value `x`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.0 )\n    0.875\n    > y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.5 )\n    0.75\n    > y = base.dists.triangular.cdf( -10.0, -20.0, 0.0, -2.0 )\n    ~0.278\n    > y = base.dists.triangular.cdf( -2.0, -1.0, 1.0, 0.0 )\n    0.0\n    > y = base.dists.triangular.cdf( NaN, 0.0, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.cdf( 0.0, NaN, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.cdf( 0.0, 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.triangular.cdf( 2.0, 1.0, 0.0, NaN )\n    NaN\n    > y = base.dists.triangular.cdf( 2.0, 1.0, 0.0, 1.5 )\n    NaN\n\n\nbase.dists.triangular.cdf.factory( a, b, c )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a triangular distribution with minimum support `a`, maximum support `b`,\n    and mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.triangular.cdf.factory( 0.0, 10.0, 2.0 );\n    > var y = mycdf( 0.5 )\n    0.0125\n    > y = mycdf( 8.0 )\n    0.95\n\n\n","base.dists.triangular.cdf.factory":"\nbase.dists.triangular.cdf.factory( a, b, c )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a triangular distribution with minimum support `a`, maximum support `b`,\n    and mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.triangular.cdf.factory( 0.0, 10.0, 2.0 );\n    > var y = mycdf( 0.5 )\n    0.0125\n    > y = mycdf( 8.0 )\n    0.95","base.dists.triangular.entropy":"\nbase.dists.triangular.entropy( a, b, c )\n    Returns the differential entropy of a triangular distribution (in nats).\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.triangular.entropy( 0.0, 1.0, 0.8 )\n    ~-0.193\n    > v = base.dists.triangular.entropy( 4.0, 12.0, 5.0 )\n    ~1.886\n    > v = base.dists.triangular.entropy( 2.0, 8.0, 5.0 )\n    ~1.599\n\n","base.dists.triangular.kurtosis":"\nbase.dists.triangular.kurtosis( a, b, c )\n    Returns the excess kurtosis of a triangular distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.triangular.kurtosis( 0.0, 1.0, 0.8 )\n    -0.6\n    > v = base.dists.triangular.kurtosis( 4.0, 12.0, 5.0 )\n    -0.6\n    > v = base.dists.triangular.kurtosis( 2.0, 8.0, 5.0 )\n    -0.6\n\n","base.dists.triangular.logcdf":"\nbase.dists.triangular.logcdf( x, a, b, c )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a triangular distribution with minimum support `a`, maximum\n    support `b`, and mode `c` at a value `x`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.0 )\n    ~-0.134\n    > y = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.5 )\n    ~-0.288\n    > y = base.dists.triangular.logcdf( -10.0, -20.0, 0.0, -2.0 )\n    ~-1.281\n    > y = base.dists.triangular.logcdf( -2.0, -1.0, 1.0, 0.0 )\n    -Infinity\n    > y = base.dists.triangular.logcdf( NaN, 0.0, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.logcdf( 0.0, NaN, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.logcdf( 0.0, 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, NaN )\n    NaN\n    > y = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, 1.5 )\n    NaN\n\n\nbase.dists.triangular.logcdf.factory( a, b, c )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a triangular distribution with minimum\n    support `a`, maximum support `b`, and mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    cdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.triangular.logcdf.factory( 0.0, 10.0, 2.0 );\n    > var y = mylogcdf( 0.5 )\n    ~-4.382\n    > y = mylogcdf( 8.0 )\n    ~-0.051\n\n\n","base.dists.triangular.logcdf.factory":"\nbase.dists.triangular.logcdf.factory( a, b, c )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a triangular distribution with minimum\n    support `a`, maximum support `b`, and mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    cdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.triangular.logcdf.factory( 0.0, 10.0, 2.0 );\n    > var y = mylogcdf( 0.5 )\n    ~-4.382\n    > y = mylogcdf( 8.0 )\n    ~-0.051","base.dists.triangular.logpdf":"\nbase.dists.triangular.logpdf( x, a, b, c )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a triangular distribution with minimum support `a`, maximum support `b`,\n    and mode `c` at a value `x`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.0 )\n    ~-0.693\n    > y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.5 )\n    0.0\n    > y = base.dists.triangular.logpdf( -10.0, -20.0, 0.0, -2.0 )\n    ~-2.89\n    > y = base.dists.triangular.logpdf( -2.0, -1.0, 1.0, 0.0 )\n    -Infinity\n    > y = base.dists.triangular.logpdf( NaN, 0.0, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.logpdf( 0.0, NaN, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.logpdf( 0.0, 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, NaN )\n    NaN\n    > y = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, 1.5 )\n    NaN\n\n\nbase.dists.triangular.logpdf.factory( a, b, c )\n    Returns a function for evaluating the natural logarithm of the  probability\n    density function (PDF) of a triangular distribution with minimum support\n    `a`, maximum support `b`, and mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.triangular.logpdf.factory( 0.0, 10.0, 5.0 );\n    > var y = mylogpdf( 2.0 )\n    ~-2.526\n    > y = mylogpdf( 12.0 )\n    -Infinity\n\n\n","base.dists.triangular.logpdf.factory":"\nbase.dists.triangular.logpdf.factory( a, b, c )\n    Returns a function for evaluating the natural logarithm of the  probability\n    density function (PDF) of a triangular distribution with minimum support\n    `a`, maximum support `b`, and mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.triangular.logpdf.factory( 0.0, 10.0, 5.0 );\n    > var y = mylogpdf( 2.0 )\n    ~-2.526\n    > y = mylogpdf( 12.0 )\n    -Infinity","base.dists.triangular.mean":"\nbase.dists.triangular.mean( a, b, c )\n    Returns the expected value of a triangular distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.triangular.mean( 0.0, 1.0, 0.8 )\n    ~0.6\n    > v = base.dists.triangular.mean( 4.0, 12.0, 5.0 )\n    7.0\n    > v = base.dists.triangular.mean( 2.0, 8.0, 5.0 )\n    5.0\n\n","base.dists.triangular.median":"\nbase.dists.triangular.median( a, b, c )\n    Returns the median of a triangular distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.triangular.median( 0.0, 1.0, 0.8 )\n    ~0.632\n    > v = base.dists.triangular.median( 4.0, 12.0, 5.0 )\n    ~6.708\n    > v = base.dists.triangular.median( 2.0, 8.0, 5.0 )\n    5.0\n\n","base.dists.triangular.mgf":"\nbase.dists.triangular.mgf( t, a, b, c )\n    Evaluates the moment-generating function (MGF) for a triangular distribution\n    with minimum support `a`, maximum support `b`, and mode `c` at a value `t`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.0 )\n    ~1.021\n    > y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.5 )\n    ~1.111\n    > y = base.dists.triangular.mgf( -0.3, -20.0, 0.0, -2.0 )\n    ~24.334\n    > y = base.dists.triangular.mgf( -2.0, -1.0, 1.0, 0.0 )\n    ~1.381\n    > y = base.dists.triangular.mgf( NaN, 0.0, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.mgf( 0.0, NaN, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.mgf( 0.0, 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.triangular.mgf( 0.5, 1.0, 0.0, NaN )\n    NaN\n    > y = base.dists.triangular.mgf( 0.5, 1.0, 0.0, 1.5 )\n    NaN\n\n\nbase.dists.triangular.mgf.factory( a, b, c )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    triangular distribution with minimum support `a`, maximum support `b`, and\n    mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.triangular.mgf.factory( 0.0, 2.0, 1.0 );\n    > var y = mymgf( -1.0 )\n    ~0.3996\n    > y = mymgf( 2.0 )\n    ~10.205\n\n\n","base.dists.triangular.mgf.factory":"\nbase.dists.triangular.mgf.factory( a, b, c )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    triangular distribution with minimum support `a`, maximum support `b`, and\n    mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.triangular.mgf.factory( 0.0, 2.0, 1.0 );\n    > var y = mymgf( -1.0 )\n    ~0.3996\n    > y = mymgf( 2.0 )\n    ~10.205","base.dists.triangular.mode":"\nbase.dists.triangular.mode( a, b, c )\n    Returns the mode of a triangular distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.triangular.mode( 0.0, 1.0, 0.8 )\n    0.8\n    > v = base.dists.triangular.mode( 4.0, 12.0, 5.0 )\n    5.0\n    > v = base.dists.triangular.mode( 2.0, 8.0, 5.0 )\n    5.0\n\n","base.dists.triangular.pdf":"\nbase.dists.triangular.pdf( x, a, b, c )\n    Evaluates the probability density function (PDF) for a triangular\n    distribution with minimum support `a`, maximum support `b`, and mode `c` at\n    a value `x`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.0 )\n    0.5\n    > y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.5 )\n    1.0\n    > y = base.dists.triangular.pdf( -10.0, -20.0, 0.0, -2.0 )\n    ~0.056\n    > y = base.dists.triangular.pdf( -2.0, -1.0, 1.0, 0.0 )\n    0.0\n    > y = base.dists.triangular.pdf( NaN, 0.0, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.pdf( 0.0, NaN, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.pdf( 0.0, 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.triangular.pdf( 2.0, 1.0, 0.0, NaN )\n    NaN\n    > y = base.dists.triangular.pdf( 2.0, 1.0, 0.0, 1.5 )\n    NaN\n\n\nbase.dists.triangular.pdf.factory( a, b, c )\n    Returns a function for evaluating the probability density function (PDF) of\n    a triangular distribution with minimum support `a`, maximum support `b`, and\n    mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var mypdf = base.dists.triangular.pdf.factory( 0.0, 10.0, 5.0 );\n    > var y = mypdf( 2.0 )\n    0.08\n    > y = mypdf( 12.0 )\n    0.0\n\n\n","base.dists.triangular.pdf.factory":"\nbase.dists.triangular.pdf.factory( a, b, c )\n    Returns a function for evaluating the probability density function (PDF) of\n    a triangular distribution with minimum support `a`, maximum support `b`, and\n    mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var mypdf = base.dists.triangular.pdf.factory( 0.0, 10.0, 5.0 );\n    > var y = mypdf( 2.0 )\n    0.08\n    > y = mypdf( 12.0 )\n    0.0","base.dists.triangular.quantile":"\nbase.dists.triangular.quantile( p, a, b, c )\n    Evaluates the quantile function for a triangular distribution with minimum\n    support `a`, maximum support `b`, and mode `c` at a value `x`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.triangular.quantile( 0.9, -1.0, 1.0, 0.0 )\n    ~0.553\n    > y = base.dists.triangular.quantile( 0.1, -1.0, 1.0, 0.5 )\n    ~-0.452\n    > y = base.dists.triangular.quantile( 0.1, -20.0, 0.0, -2.0 )\n    -14.0\n    > y = base.dists.triangular.quantile( 0.8, 0.0, 20.0, 0.0 )\n    ~11.056\n\n    > y = base.dists.triangular.quantile( 1.1, -1.0, 1.0, 0.0 )\n    NaN\n    > y = base.dists.triangular.quantile( -0.1, -1.0, 1.0, 0.0 )\n    NaN\n\n    > y = base.dists.triangular.quantile( NaN, 0.0, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.quantile( 0.3, NaN, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.quantile( 0.3, 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.triangular.quantile( 0.3, 1.0, 0.0, NaN )\n    NaN\n\n    > y = base.dists.triangular.quantile( 0.3, 1.0, 0.0, 1.5 )\n    NaN\n\n\nbase.dists.triangular.quantile.factory( a, b, c )\n    Returns a function for evaluating the quantile function of a triangular\n    distribution with minimum support `a`, maximum support `b`, and mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.triangular.quantile.factory( 2.0, 4.0, 2.5 );\n    > var y = myquantile( 0.4 )\n    ~2.658\n    > y = myquantile( 0.8 )\n    ~3.225\n\n\n","base.dists.triangular.quantile.factory":"\nbase.dists.triangular.quantile.factory( a, b, c )\n    Returns a function for evaluating the quantile function of a triangular\n    distribution with minimum support `a`, maximum support `b`, and mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.triangular.quantile.factory( 2.0, 4.0, 2.5 );\n    > var y = myquantile( 0.4 )\n    ~2.658\n    > y = myquantile( 0.8 )\n    ~3.225","base.dists.triangular.skewness":"\nbase.dists.triangular.skewness( a, b, c )\n    Returns the skewness of a triangular distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.triangular.skewness( 0.0, 1.0, 0.8 )\n    ~-0.476\n    > v = base.dists.triangular.skewness( 4.0, 12.0, 5.0 )\n    ~0.532\n    > v = base.dists.triangular.skewness( 2.0, 8.0, 5.0 )\n    0.0\n\n","base.dists.triangular.stdev":"\nbase.dists.triangular.stdev( a, b, c )\n    Returns the standard deviation of a triangular distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.triangular.stdev( 0.0, 1.0, 0.8 )\n    ~0.216\n    > v = base.dists.triangular.stdev( 4.0, 12.0, 5.0 )\n    ~1.78\n    > v = base.dists.triangular.stdev( 2.0, 8.0, 5.0 )\n    ~1.225\n\n","base.dists.triangular.Triangular":"\nbase.dists.triangular.Triangular( [a, b, c] )\n    Returns a triangular distribution object.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support. Must be smaller than `b` and `c`. Default: `0.0`.\n\n    b: number (optional)\n        Maximum support. Must be greater than `a` and `c`. Default: `1.0`.\n\n    c: number (optional)\n        Mode. Must be greater than `a` and smaller than `b`. Default: `0.5`.\n\n    Returns\n    -------\n    triangular: Object\n        Distribution instance.\n\n    triangular.a: number\n        Minimum support. If set, the value must be smaller or equal to `b` and\n        `c`.\n\n    triangular.b: number\n        Maximum support. If set, the value must be greater than or equal to `a`\n        and `c`.\n\n    triangular.c: number\n        Mode. If set, the value must be greater than or equal to `a` and smaller\n        than or equal to `b`.\n\n    triangular.entropy: number\n        Read-only property which returns the differential entropy.\n\n    triangular.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    triangular.mean: number\n        Read-only property which returns the expected value.\n\n    triangular.median: number\n        Read-only property which returns the median.\n\n    triangular.mode: number\n        Read-only property which returns the mode.\n\n    triangular.skewness: number\n        Read-only property which returns the skewness.\n\n    triangular.stdev: number\n        Read-only property which returns the standard deviation.\n\n    triangular.variance: number\n        Read-only property which returns the variance.\n\n    triangular.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    triangular.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    triangular.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    triangular.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    triangular.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    triangular.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var triangular = base.dists.triangular.Triangular( 0.0, 1.0, 0.5 );\n    > triangular.a\n    0.0\n    > triangular.b\n    1.0\n    > triangular.c\n    0.5\n    > triangular.entropy\n    ~-0.193\n    > triangular.kurtosis\n    -0.6\n    > triangular.mean\n    0.5\n    > triangular.median\n    0.5\n    > triangular.mode\n    0.5\n    > triangular.skewness\n    0.0\n    > triangular.stdev\n    ~0.204\n    > triangular.variance\n    ~0.042\n    > triangular.cdf( 0.8 )\n    0.92\n    > triangular.logcdf( 0.8 )\n    ~-0.083\n    > triangular.logpdf( 0.8 )\n    ~-0.223\n    > triangular.mgf( 0.8 )\n    ~1.512\n    > triangular.pdf( 0.8 )\n    ~0.8\n    > triangular.quantile( 0.8 )\n    ~0.684\n\n","base.dists.triangular.variance":"\nbase.dists.triangular.variance( a, b, c )\n    Returns the variance of a triangular distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.triangular.variance( 0.0, 1.0, 0.8 )\n    ~0.047\n    > v = base.dists.triangular.variance( 4.0, 12.0, 5.0 )\n    ~3.167\n    > v = base.dists.triangular.variance( 2.0, 8.0, 5.0 )\n    ~1.5\n\n","base.dists.uniform.cdf":"\nbase.dists.uniform.cdf( x, a, b )\n    Evaluates the cumulative distribution function (CDF) for a uniform\n    distribution with minimum support `a` and maximum support `b` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.uniform.cdf( 9.0, 0.0, 10.0 )\n    0.9\n    > y = base.dists.uniform.cdf( 0.5, 0.0, 2.0 )\n    0.25\n    > y = base.dists.uniform.cdf( PINF, 2.0, 4.0 )\n    1.0\n    > y = base.dists.uniform.cdf( NINF, 2.0, 4.0 )\n    0.0\n    > y = base.dists.uniform.cdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.uniform.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.uniform.cdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.uniform.cdf( 2.0, 1.0, 0.0 )\n    NaN\n\n\nbase.dists.uniform.cdf.factory( a, b )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a uniform distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.uniform.cdf.factory( 0.0, 10.0 );\n    > var y = mycdf( 0.5 )\n    0.05\n    > y = mycdf( 8.0 )\n    0.8\n\n","base.dists.uniform.cdf.factory":"\nbase.dists.uniform.cdf.factory( a, b )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a uniform distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.uniform.cdf.factory( 0.0, 10.0 );\n    > var y = mycdf( 0.5 )\n    0.05\n    > y = mycdf( 8.0 )\n    0.8","base.dists.uniform.entropy":"\nbase.dists.uniform.entropy( a, b )\n    Returns the differential entropy of a uniform distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Differential entropy.\n\n    Examples\n    --------\n    > var v = base.dists.uniform.entropy( 0.0, 1.0 )\n    0.0\n    > v = base.dists.uniform.entropy( 4.0, 12.0 )\n    ~2.079\n    > v = base.dists.uniform.entropy( 2.0, 8.0 )\n    ~1.792\n\n","base.dists.uniform.kurtosis":"\nbase.dists.uniform.kurtosis( a, b )\n    Returns the excess kurtosis of a uniform distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.uniform.kurtosis( 0.0, 1.0 )\n    -1.2\n    > v = base.dists.uniform.kurtosis( 4.0, 12.0 )\n    -1.2\n    > v = base.dists.uniform.kurtosis( 2.0, 8.0 )\n    -1.2\n\n","base.dists.uniform.logcdf":"\nbase.dists.uniform.logcdf( x, a, b )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    uniform distribution with minimum support `a` and maximum support `b` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.uniform.logcdf( 9.0, 0.0, 10.0 )\n    ~-0.105\n    > y = base.dists.uniform.logcdf( 0.5, 0.0, 2.0 )\n    ~-1.386\n    > y = base.dists.uniform.logcdf( PINF, 2.0, 4.0 )\n    0.0\n    > y = base.dists.uniform.logcdf( NINF, 2.0, 4.0 )\n    -Infinity\n    > y = base.dists.uniform.logcdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.uniform.logcdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.uniform.logcdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.uniform.logcdf( 2.0, 1.0, 0.0 )\n    NaN\n\n\nbase.dists.uniform.logcdf.factory( a, b )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a uniform distribution with minimum support\n    `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.uniform.logcdf.factory( 0.0, 10.0 );\n    > var y = mylogcdf( 0.5 )\n    ~-2.996\n    > y = mylogcdf( 8.0 )\n    ~-0.223\n\n","base.dists.uniform.logcdf.factory":"\nbase.dists.uniform.logcdf.factory( a, b )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a uniform distribution with minimum support\n    `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.uniform.logcdf.factory( 0.0, 10.0 );\n    > var y = mylogcdf( 0.5 )\n    ~-2.996\n    > y = mylogcdf( 8.0 )\n    ~-0.223","base.dists.uniform.logpdf":"\nbase.dists.uniform.logpdf( x, a, b )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    uniform distribution with minimum support `a` and maximum support `b` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.uniform.logpdf( 2.0, 0.0, 4.0 )\n    ~-1.386\n    > y = base.dists.uniform.logpdf( 5.0, 0.0, 4.0 )\n    -infinity\n    > y = base.dists.uniform.logpdf( 0.25, 0.0, 1.0 )\n    0.0\n    > y = base.dists.uniform.logpdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.uniform.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.uniform.logpdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.uniform.logpdf( 2.0, 3.0, 1.0 )\n    NaN\n\n\nbase.dists.uniform.logpdf.factory( a, b )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a uniform distribution with minimum support `a` and\n    maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.uniform.logpdf.factory( 6.0, 7.0 );\n    > var y = mylogPDF( 7.0 )\n    0.0\n    > y = mylogPDF( 5.0 )\n    -infinity\n\n","base.dists.uniform.logpdf.factory":"\nbase.dists.uniform.logpdf.factory( a, b )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a uniform distribution with minimum support `a` and\n    maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.uniform.logpdf.factory( 6.0, 7.0 );\n    > var y = mylogPDF( 7.0 )\n    0.0\n    > y = mylogPDF( 5.0 )\n    -infinity","base.dists.uniform.mean":"\nbase.dists.uniform.mean( a, b )\n    Returns the expected value of a uniform distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.uniform.mean( 0.0, 1.0 )\n    0.5\n    > v = base.dists.uniform.mean( 4.0, 12.0 )\n    8.0\n    > v = base.dists.uniform.mean( 2.0, 8.0 )\n    5.0\n\n","base.dists.uniform.median":"\nbase.dists.uniform.median( a, b )\n    Returns the median of a uniform distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.uniform.median( 0.0, 1.0 )\n    0.5\n    > v = base.dists.uniform.median( 4.0, 12.0 )\n    8.0\n    > v = base.dists.uniform.median( 2.0, 8.0 )\n    5.0\n\n","base.dists.uniform.mgf":"\nbase.dists.uniform.mgf( t, a, b )\n    Evaluates the moment-generating function (MGF) for a uniform\n    distribution with minimum support `a` and maximum support `b` at a value\n    `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.uniform.mgf( 2.0, 0.0, 4.0 )\n    ~372.495\n    > y = base.dists.uniform.mgf( -0.2, 0.0, 4.0 )\n    ~0.688\n    > y = base.dists.uniform.mgf( 2.0, 0.0, 1.0 )\n    ~3.195\n    > y = base.dists.uniform.mgf( 0.5, 3.0, 2.0 )\n    NaN\n    > y = base.dists.uniform.mgf( 0.5, 3.0, 3.0 )\n    NaN\n    > y = base.dists.uniform.mgf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.uniform.mgf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.uniform.mgf( 0.0, 0.0, NaN )\n    NaN\n\n\nbase.dists.uniform.mgf.factory( a, b )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a uniform distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.uniform.mgf.factory( 6.0, 7.0 );\n    > var y = mymgf( 0.1 )\n    ~1.916\n    > y = mymgf( 1.1 )\n    ~1339.321\n\n","base.dists.uniform.mgf.factory":"\nbase.dists.uniform.mgf.factory( a, b )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a uniform distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.uniform.mgf.factory( 6.0, 7.0 );\n    > var y = mymgf( 0.1 )\n    ~1.916\n    > y = mymgf( 1.1 )\n    ~1339.321","base.dists.uniform.pdf":"\nbase.dists.uniform.pdf( x, a, b )\n    Evaluates the probability density function (PDF) for a uniform distribution\n    with minimum support `a` and maximum support `b` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.uniform.pdf( 2.0, 0.0, 4.0 )\n    0.25\n    > y = base.dists.uniform.pdf( 5.0, 0.0, 4.0 )\n    0.0\n    > y = base.dists.uniform.pdf( 0.25, 0.0, 1.0 )\n    1.0\n    > y = base.dists.uniform.pdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.uniform.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.uniform.pdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.uniform.pdf( 2.0, 3.0, 1.0 )\n    NaN\n\n\nbase.dists.uniform.pdf.factory( a, b )\n    Returns a function for evaluating the probability density function (PDF) of\n    a uniform distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.uniform.pdf.factory( 6.0, 7.0 );\n    > var y = myPDF( 7.0 )\n    1.0\n    > y = myPDF( 5.0 )\n    0.0\n\n","base.dists.uniform.pdf.factory":"\nbase.dists.uniform.pdf.factory( a, b )\n    Returns a function for evaluating the probability density function (PDF) of\n    a uniform distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.uniform.pdf.factory( 6.0, 7.0 );\n    > var y = myPDF( 7.0 )\n    1.0\n    > y = myPDF( 5.0 )\n    0.0","base.dists.uniform.quantile":"\nbase.dists.uniform.quantile( p, a, b )\n    Evaluates the quantile function for a uniform distribution with minimum\n    support `a` and maximum support `b` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.uniform.quantile( 0.8, 0.0, 1.0 )\n    0.8\n    > y = base.dists.uniform.quantile( 0.5, 0.0, 10.0 )\n    5.0\n\n    > y = base.dists.uniform.quantile( 1.1, 0.0, 1.0 )\n    NaN\n    > y = base.dists.uniform.quantile( -0.2, 0.0, 1.0 )\n    NaN\n\n    > y = base.dists.uniform.quantile( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.uniform.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.uniform.quantile( 0.0, 0.0, NaN )\n    NaN\n\n    > y = base.dists.uniform.quantile( 0.5, 2.0, 1.0 )\n    NaN\n\n\nbase.dists.uniform.quantile.factory( a, b )\n    Returns a function for evaluating the quantile function of a uniform\n    distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.uniform.quantile.factory( 0.0, 4.0 );\n    > var y = myQuantile( 0.8 )\n    3.2\n\n","base.dists.uniform.quantile.factory":"\nbase.dists.uniform.quantile.factory( a, b )\n    Returns a function for evaluating the quantile function of a uniform\n    distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.uniform.quantile.factory( 0.0, 4.0 );\n    > var y = myQuantile( 0.8 )\n    3.2","base.dists.uniform.skewness":"\nbase.dists.uniform.skewness( a, b )\n    Returns the skewness of a uniform distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.uniform.skewness( 0.0, 1.0 )\n    0.0\n    > v = base.dists.uniform.skewness( 4.0, 12.0 )\n    0.0\n    > v = base.dists.uniform.skewness( 2.0, 8.0 )\n    0.0\n\n","base.dists.uniform.stdev":"\nbase.dists.uniform.stdev( a, b )\n    Returns the standard deviation of a uniform distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.uniform.stdev( 0.0, 1.0 )\n    ~0.289\n    > v = base.dists.uniform.stdev( 4.0, 12.0 )\n    ~2.309\n    > v = base.dists.uniform.stdev( 2.0, 8.0 )\n    ~1.732\n\n","base.dists.uniform.Uniform":"\nbase.dists.uniform.Uniform( [a, b] )\n    Returns a uniform distribution object.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support. Must be smaller than `b`. Default: `0.0`.\n\n    b: number (optional)\n        Maximum support. Must be greater than `a`. Default: `1.0`.\n\n    Returns\n    -------\n    uniform: Object\n        Distribution instance.\n\n    uniform.a: number\n        Minimum support. If set, the value must be smaller than `b`.\n\n    uniform.b: number\n        Maximum support. If set, the value must be greater than `a`.\n\n    uniform.entropy: number\n        Read-only property which returns the differential entropy.\n\n    uniform.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    uniform.mean: number\n        Read-only property which returns the expected value.\n\n    uniform.median: number\n        Read-only property which returns the median.\n\n    uniform.skewness: number\n        Read-only property which returns the skewness.\n\n    uniform.stdev: number\n        Read-only property which returns the standard deviation.\n\n    uniform.variance: number\n        Read-only property which returns the variance.\n\n    uniform.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    uniform.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    uniform.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    uniform.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    uniform.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    uniform.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var uniform = base.dists.uniform.Uniform( 0.0, 1.0 );\n    > uniform.a\n    0.0\n    > uniform.b\n    1.0\n    > uniform.entropy\n    0.0\n    > uniform.kurtosis\n    -1.2\n    > uniform.mean\n    0.5\n    > uniform.median\n    0.5\n    > uniform.skewness\n    0.0\n    > uniform.stdev\n    ~0.289\n    > uniform.variance\n    ~0.083\n    > uniform.cdf( 0.8 )\n    0.8\n    > uniform.logcdf( 0.5 )\n    ~-0.693\n    > uniform.logpdf( 1.0 )\n    ~-0.0\n    > uniform.mgf( 0.8 )\n    ~1.532\n    > uniform.pdf( 0.8 )\n    1.0\n    > uniform.quantile( 0.8 )\n    0.8\n\n","base.dists.uniform.variance":"\nbase.dists.uniform.variance( a, b )\n    Returns the variance of a uniform distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.uniform.variance( 0.0, 1.0 )\n    ~0.083\n    > v = base.dists.uniform.variance( 4.0, 12.0 )\n    ~5.333\n    > v = base.dists.uniform.variance( 2.0, 8.0 )\n    3.0\n\n","base.dists.weibull.cdf":"\nbase.dists.weibull.cdf( x, k, λ )\n    Evaluates the cumulative distribution function (CDF) for a Weibull\n    distribution with shape parameter `k` and scale parameter `λ` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a non-positive value for `λ` or `k`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.weibull.cdf( 2.0, 1.0, 1.0 )\n    ~0.865\n    > y = base.dists.weibull.cdf( -1.0, 2.0, 2.0 )\n    0.0\n    > y = base.dists.weibull.cdf( PINF, 4.0, 2.0 )\n    1.0\n    > y = base.dists.weibull.cdf( NINF, 4.0, 2.0 )\n    0.0\n    > y = base.dists.weibull.cdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.weibull.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.weibull.cdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.weibull.cdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.weibull.cdf.factory( k, λ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.weibull.cdf.factory( 2.0, 10.0 );\n    > var y = myCDF( 12.0 )\n    ~0.763\n\n","base.dists.weibull.cdf.factory":"\nbase.dists.weibull.cdf.factory( k, λ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.weibull.cdf.factory( 2.0, 10.0 );\n    > var y = myCDF( 12.0 )\n    ~0.763","base.dists.weibull.entropy":"\nbase.dists.weibull.entropy( k, λ )\n    Returns the differential entropy of a Weibull distribution (in nats).\n\n    If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n    If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.weibull.entropy( 1.0, 1.0 )\n    1.0\n    > v = base.dists.weibull.entropy( 4.0, 12.0 )\n    ~2.532\n    > v = base.dists.weibull.entropy( 8.0, 2.0 )\n    ~0.119\n\n","base.dists.weibull.kurtosis":"\nbase.dists.weibull.kurtosis( k, λ )\n    Returns the excess kurtosis of a Weibull distribution.\n\n    If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n    If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.weibull.kurtosis( 1.0, 1.0 )\n    6.0\n    > v = base.dists.weibull.kurtosis( 4.0, 12.0 )\n    ~-0.252\n    > v = base.dists.weibull.kurtosis( 8.0, 2.0 )\n    ~0.328\n\n","base.dists.weibull.logcdf":"\nbase.dists.weibull.logcdf( x, k, λ )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.weibull.logcdf( 2.0, 1.0, 1.0 )\n    ~-0.145\n    > y = base.dists.weibull.logcdf( -1.0, 2.0, 2.0 )\n    -Infinity\n    > y = base.dists.weibull.logcdf( PINF, 4.0, 2.0 )\n    0.0\n    > y = base.dists.weibull.logcdf( NINF, 4.0, 2.0 )\n    -Infinity\n    > y = base.dists.weibull.logcdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.weibull.logcdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.weibull.logcdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.weibull.logcdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.weibull.logcdf.factory( k, λ)\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Weibull distribution with scale parameter\n    `λ` and shape parameter `k`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.weibull.logcdf.factory( 2.0, 10.0 );\n    > var y = mylogcdf( 12.0 )\n    ~-0.27\n\n","base.dists.weibull.logcdf.factory":"\nbase.dists.weibull.logcdf.factory( k, λ)\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Weibull distribution with scale parameter\n    `λ` and shape parameter `k`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.weibull.logcdf.factory( 2.0, 10.0 );\n    > var y = mylogcdf( 12.0 )\n    ~-0.27","base.dists.weibull.logpdf":"\nbase.dists.weibull.logpdf( x, k, λ )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.weibull.logpdf( 2.0, 1.0, 0.5 )\n    ~-3.307\n    > y = base.dists.weibull.logpdf( 0.1, 1.0, 1.0 )\n    ~-0.1\n    > y = base.dists.weibull.logpdf( -1.0, 4.0, 2.0 )\n    -Infinity\n    > y = base.dists.weibull.logpdf( NaN, 0.6, 1.0 )\n    NaN\n    > y = base.dists.weibull.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.weibull.logpdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.weibull.logpdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.weibull.logpdf.factory( k, λ )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Weibull distribution with shape parameter `k` and scale\n    parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylofpdf = base.dists.weibull.logpdf.factory( 7.0, 6.0 );\n    > y = mylofpdf( 7.0 )\n    ~-1.863\n\n","base.dists.weibull.logpdf.factory":"\nbase.dists.weibull.logpdf.factory( k, λ )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Weibull distribution with shape parameter `k` and scale\n    parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylofpdf = base.dists.weibull.logpdf.factory( 7.0, 6.0 );\n    > y = mylofpdf( 7.0 )\n    ~-1.863","base.dists.weibull.mean":"\nbase.dists.weibull.mean( k, λ )\n    Returns the expected value of a Weibull distribution.\n\n    If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n    If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.weibull.mean( 1.0, 1.0 )\n    1.0\n    > v = base.dists.weibull.mean( 4.0, 12.0 )\n    ~10.877\n    > v = base.dists.weibull.mean( 8.0, 2.0 )\n    ~1.883\n\n","base.dists.weibull.median":"\nbase.dists.weibull.median( k, λ )\n    Returns the median of a Weibull distribution.\n\n    If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n    If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.weibull.median( 1.0, 1.0 )\n    ~0.693\n    > v = base.dists.weibull.median( 4.0, 12.0 )\n    ~10.949\n    > v = base.dists.weibull.median( 8.0, 2.0 )\n    ~1.91\n\n","base.dists.weibull.mgf":"\nbase.dists.weibull.mgf( x, k, λ )\n    Evaluates the moment-generating function (MGF) for a Weibull distribution\n    with shape parameter `k` and scale parameter `λ` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a non-positive value for `λ` or `k`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.weibull.mgf( 1.0, 1.0, 0.5 )\n    ~2.0\n    > y = base.dists.weibull.mgf( -1.0, 4.0, 4.0 )\n    ~0.019\n\n    > y = base.dists.weibull.mgf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.weibull.mgf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.weibull.mgf( 0.0, 1.0, NaN )\n    NaN\n\n    > y = base.dists.weibull.mgf( 0.2, -1.0, 0.5 )\n    NaN\n    > y = base.dists.weibull.mgf( 0.2, 0.0, 0.5 )\n    NaN\n\n    > y = base.dists.weibull.mgf( 0.2, 0.5, -1.0 )\n    NaN\n    > y = base.dists.weibull.mgf( 0.2, 0.5, 0.0 )\n    NaN\n\n\nbase.dists.weibull.mgf.factory( k, λ )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.weibull.mgf.factory( 8.0, 10.0 );\n    > var y = myMGF( 0.8 )\n    ~3150.149\n    > y = myMGF( 0.08 )\n    ~2.137\n\n","base.dists.weibull.mgf.factory":"\nbase.dists.weibull.mgf.factory( k, λ )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.weibull.mgf.factory( 8.0, 10.0 );\n    > var y = myMGF( 0.8 )\n    ~3150.149\n    > y = myMGF( 0.08 )\n    ~2.137","base.dists.weibull.mode":"\nbase.dists.weibull.mode( k, λ )\n    Returns the mode of a Weibull distribution.\n\n    If `0 < k <= 1`, the function returns `0.0`.\n\n    If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n    If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.weibull.mode( 1.0, 1.0 )\n    0.0\n    > v = base.dists.weibull.mode( 4.0, 12.0 )\n    ~11.167\n    > v = base.dists.weibull.mode( 8.0, 2.0 )\n    ~1.967\n\n","base.dists.weibull.pdf":"\nbase.dists.weibull.pdf( x, k, λ )\n    Evaluates the probability density function (PDF) for a Weibull distribution\n    with shape parameter `k` and scale parameter `λ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.weibull.pdf( 2.0, 1.0, 0.5 )\n    ~0.037\n    > y = base.dists.weibull.pdf( 0.1, 1.0, 1.0 )\n    ~0.905\n    > y = base.dists.weibull.pdf( -1.0, 4.0, 2.0 )\n    0.0\n    > y = base.dists.weibull.pdf( NaN, 0.6, 1.0 )\n    NaN\n    > y = base.dists.weibull.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.weibull.pdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.weibull.pdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.weibull.pdf.factory( k, λ )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.weibull.pdf.factory( 7.0, 6.0 );\n    > var y = myPDF( 7.0 )\n    ~0.155\n\n","base.dists.weibull.pdf.factory":"\nbase.dists.weibull.pdf.factory( k, λ )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.weibull.pdf.factory( 7.0, 6.0 );\n    > var y = myPDF( 7.0 )\n    ~0.155","base.dists.weibull.quantile":"\nbase.dists.weibull.quantile( p, k, λ )\n    Evaluates the quantile function for a Weibull distribution with scale\n    parameter `k` and shape parameter `λ` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.weibull.quantile( 0.8, 1.0, 1.0 )\n    ~1.609\n    > y = base.dists.weibull.quantile( 0.5, 2.0, 4.0 )\n    ~3.33\n\n    > y = base.dists.weibull.quantile( 1.1, 1.0, 1.0 )\n    NaN\n    > y = base.dists.weibull.quantile( -0.2, 1.0, 1.0 )\n    NaN\n\n    > y = base.dists.weibull.quantile( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.weibull.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.weibull.quantile( 0.0, 0.0, NaN )\n    NaN\n\n    > y = base.dists.weibull.quantile( 0.5, 1.0, -1.0 )\n    NaN\n\n\nbase.dists.weibull.quantile.factory( k, λ )\n    Returns a function for evaluating the quantile function of a Weibull\n    distribution with scale parameter `k` and shape parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.weibull.quantile.factory( 2.0, 10.0 );\n    > var y = myQuantile( 0.4 )\n    ~7.147\n\n","base.dists.weibull.quantile.factory":"\nbase.dists.weibull.quantile.factory( k, λ )\n    Returns a function for evaluating the quantile function of a Weibull\n    distribution with scale parameter `k` and shape parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.weibull.quantile.factory( 2.0, 10.0 );\n    > var y = myQuantile( 0.4 )\n    ~7.147","base.dists.weibull.skewness":"\nbase.dists.weibull.skewness( k, λ )\n    Returns the skewness of a Weibull distribution.\n\n    If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n    If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.weibull.skewness( 1.0, 1.0 )\n    2.0\n    > v = base.dists.weibull.skewness( 4.0, 12.0 )\n    ~-0.087\n    > v = base.dists.weibull.skewness( 8.0, 2.0 )\n    ~-0.534\n\n","base.dists.weibull.stdev":"\nbase.dists.weibull.stdev( k, λ )\n    Returns the standard deviation of a Weibull distribution.\n\n    If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n    If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.weibull.stdev( 1.0, 1.0 )\n    1.0\n    > v = base.dists.weibull.stdev( 4.0, 12.0 )\n    ~3.051\n    > v = base.dists.weibull.stdev( 8.0, 2.0 )\n    ~0.279\n\n","base.dists.weibull.variance":"\nbase.dists.weibull.variance( k, λ )\n    Returns the variance of a Weibull distribution.\n\n    If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n    If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.weibull.variance( 1.0, 1.0 )\n    1.0\n    > v = base.dists.weibull.variance( 4.0, 12.0 )\n    ~9.311\n    > v = base.dists.weibull.variance( 8.0, 2.0 )\n    ~0.078\n\n","base.dists.weibull.Weibull":"\nbase.dists.weibull.Weibull( [k, λ] )\n    Returns a Weibull distribution object.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n    λ: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    weibull: Object\n        Distribution instance.\n\n    weibull.k: number\n        Shape parameter. If set, the value must be greater than `0`.\n\n    weibull.lambda: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    weibull.entropy: number\n        Read-only property which returns the differential entropy.\n\n    weibull.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    weibull.mean: number\n        Read-only property which returns the expected value.\n\n    weibull.median: number\n        Read-only property which returns the median.\n\n    weibull.mode: number\n        Read-only property which returns the mode.\n\n    weibull.skewness: number\n        Read-only property which returns the skewness.\n\n    weibull.stdev: number\n        Read-only property which returns the standard deviation.\n\n    weibull.variance: number\n        Read-only property which returns the variance.\n\n    weibull.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    weibull.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    weibull.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    weibull.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    weibull.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    weibull.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var weibull = base.dists.weibull.Weibull( 6.0, 5.0 );\n    > weibull.k\n    6.0\n    > weibull.lambda\n    5.0\n    > weibull.entropy\n    ~1.299\n    > weibull.kurtosis\n    ~0.035\n    > weibull.mean\n    ~4.639\n    > weibull.median\n    ~4.704\n    > weibull.mode\n    ~4.85\n    > weibull.skewness\n    ~-0.373\n    > weibull.stdev\n    ~0.899\n    > weibull.variance\n    ~0.808\n    > weibull.cdf( 3.0 )\n    ~0.046\n    > weibull.logcdf( 3.0 )\n    ~-3.088\n    > weibull.logpdf( 1.0 )\n    ~-7.865\n    > weibull.mgf( -0.5 )\n    ~0.075\n    > weibull.pdf( 3.0 )\n    ~0.089\n    > weibull.quantile( 0.8 )\n    ~5.413\n\n","base.ellipe":"\nbase.ellipe( m )\n    Computes the complete elliptic integral of the second kind.\n\n    Parameters\n    ----------\n    m: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.ellipe( 0.5 )\n    ~1.351\n    > y = base.ellipe( -1.0 )\n    ~1.910\n    > y = base.ellipe( 2.0 )\n    NaN\n    > y = base.ellipe( PINF )\n    NaN\n    > y = base.ellipe( NINF )\n    NaN\n    > y = base.ellipe( NaN )\n    NaN\n\n    See Also\n    --------\n    base.ellipj, base.ellipk\n","base.ellipj":"\nbase.ellipj( u, m )\n    Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n    amplitude am.\n\n    Parameters\n    ----------\n    u: number\n        Input value.\n\n    m: number\n        Modulus m, equivalent to k².\n\n    Returns\n    -------\n    out: Array\n        Jacobi elliptic functions and Jacobi amplitude.\n\n    Examples\n    --------\n    > var v = base.ellipj( 0.3, 0.5 )\n    [ ~0.293, ~0.956, ~0.978, ~0.298 ]\n    > v = base.ellipj( 0.0, 0.0 )\n    [ ~0.0, ~1.0, ~1.0, ~0.0 ]\n    > v = base.ellipj( Infinity, 1.0 )\n    [ ~1.0, ~0.0, ~0.0, ~1.571 ]\n    > v = base.ellipj( 0.0, -2.0)\n    [ ~0.0, ~1.0, ~1.0, NaN ]\n    > v = base.ellipj( NaN, NaN )\n    [ NaN, NaN, NaN, NaN ]\n\n\nbase.ellipj.assign( u, m, out, stride, offset )\n    Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n    amplitude am and assigns results to a provided output array.\n\n    Parameters\n    ----------\n    u: number\n        Input value.\n\n    m: number\n        Modulus m, equivalent to k².\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Jacobi elliptic functions and Jacobi amplitude.\n\n    Examples\n    --------\n    > var out = new Float64Array( 4 );\n    > var v = base.ellipj.assign( 0.3, 0.5, out, 1, 0 )\n    <Float64Array>[ ~0.293, ~0.956, ~0.978, ~0.298 ]\n    > var bool = ( v === out )\n    true\n\n\nbase.ellipj.sn( u, m )\n    Computes the Jacobi elliptic function sn.\n\n    Parameters\n    ----------\n    u: number\n        Input value.\n\n    m: number\n        Modulus m, equivalent to k².\n\n    Returns\n    -------\n    out: number\n        Jacobi elliptic function sn.\n\n    Examples\n    --------\n    > var v = base.ellipj.sn( 0.3, 0.5 )\n    ~0.293\n\n\nbase.ellipj.cn( u, m )\n    Computes the Jacobi elliptic functions cn.\n\n    Parameters\n    ----------\n    u: number\n        Input value.\n\n    m: number\n        Modulus m, equivalent to k².\n\n    Returns\n    -------\n    out: number\n        Jacobi elliptic function cn.\n\n    Examples\n    --------\n    > var v = base.ellipj.cn( 0.3, 0.5 )\n    ~0.956\n\n\nbase.ellipj.dn( u, m )\n    Computes the Jacobi elliptic function dn.\n\n    Parameters\n    ----------\n    u: number\n        Input value.\n\n    m: number\n        Modulus m, equivalent to k².\n\n    Returns\n    -------\n    out: number\n        Jacobi elliptic function dn.\n\n    Examples\n    --------\n    > var v = base.ellipj.dn( 0.3, 0.5 )\n    ~0.978\n\n\nbase.ellipj.am( u, m )\n    Computes the Jacobi amplitude am.\n\n    Parameters\n    ----------\n    u: number\n        Input value.\n\n    m: number\n        Modulus m, equivalent to k².\n\n    Returns\n    -------\n    out: number\n        Jacobi elliptic function am.\n\n    Examples\n    --------\n    > var v = base.ellipj.am( 0.3, 0.5 )\n    ~0.298\n\n    See Also\n    --------\n    base.ellipe, base.ellipk","base.ellipj.assign":"\nbase.ellipj.assign( u, m, out, stride, offset )\n    Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n    amplitude am and assigns results to a provided output array.\n\n    Parameters\n    ----------\n    u: number\n        Input value.\n\n    m: number\n        Modulus m, equivalent to k².\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Jacobi elliptic functions and Jacobi amplitude.\n\n    Examples\n    --------\n    > var out = new Float64Array( 4 );\n    > var v = base.ellipj.assign( 0.3, 0.5, out, 1, 0 )\n    <Float64Array>[ ~0.293, ~0.956, ~0.978, ~0.298 ]\n    > var bool = ( v === out )\n    true","base.ellipj.sn":"\nbase.ellipj.sn( u, m )\n    Computes the Jacobi elliptic function sn.\n\n    Parameters\n    ----------\n    u: number\n        Input value.\n\n    m: number\n        Modulus m, equivalent to k².\n\n    Returns\n    -------\n    out: number\n        Jacobi elliptic function sn.\n\n    Examples\n    --------\n    > var v = base.ellipj.sn( 0.3, 0.5 )\n    ~0.293","base.ellipj.cn":"\nbase.ellipj.cn( u, m )\n    Computes the Jacobi elliptic functions cn.\n\n    Parameters\n    ----------\n    u: number\n        Input value.\n\n    m: number\n        Modulus m, equivalent to k².\n\n    Returns\n    -------\n    out: number\n        Jacobi elliptic function cn.\n\n    Examples\n    --------\n    > var v = base.ellipj.cn( 0.3, 0.5 )\n    ~0.956","base.ellipj.dn":"\nbase.ellipj.dn( u, m )\n    Computes the Jacobi elliptic function dn.\n\n    Parameters\n    ----------\n    u: number\n        Input value.\n\n    m: number\n        Modulus m, equivalent to k².\n\n    Returns\n    -------\n    out: number\n        Jacobi elliptic function dn.\n\n    Examples\n    --------\n    > var v = base.ellipj.dn( 0.3, 0.5 )\n    ~0.978","base.ellipj.am":"\nbase.ellipj.am( u, m )\n    Computes the Jacobi amplitude am.\n\n    Parameters\n    ----------\n    u: number\n        Input value.\n\n    m: number\n        Modulus m, equivalent to k².\n\n    Returns\n    -------\n    out: number\n        Jacobi elliptic function am.\n\n    Examples\n    --------\n    > var v = base.ellipj.am( 0.3, 0.5 )\n    ~0.298\n\n    See Also\n    --------\n    base.ellipe, base.ellipk","base.ellipk":"\nbase.ellipk( m )\n    Computes the complete elliptic integral of the first kind.\n\n    Parameters\n    ----------\n    m: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.ellipk( 0.5 )\n    ~1.854\n    > y = base.ellipk( -1.0 )\n    ~1.311\n    > y = base.ellipk( 2.0 )\n    NaN\n    > y = base.ellipk( PINF )\n    NaN\n    > y = base.ellipk( NINF )\n    NaN\n    > y = base.ellipk( NaN )\n    NaN\n\n    See Also\n    --------\n    base.ellipe, base.ellipj\n","base.endsWith":"\nbase.endsWith( str, search, len )\n    Tests if a string ends with the characters of another string.\n\n    If provided an empty search string, the function always returns `true`.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search string.\n\n    len: integer\n        Substring length. Restricts the search to a substring within the input\n        string beginning from the leftmost character. If provided a negative\n        value, `len` indicates to ignore the last `len` characters, and is thus\n        equivalent to `str.length + len`. Default: str.length.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a string ends with the characters of another\n        string.\n\n    Examples\n    --------\n    > var bool = base.endsWith( 'beep', 'ep', 4 )\n    true\n    > bool = base.endsWith( 'Beep', 'op', 4 )\n    false\n    > bool = base.endsWith( 'Beep', 'ee', 3 )\n    true\n    > bool = base.endsWith( 'Beep', 'ee', -1 )\n    true\n    > bool = base.endsWith( 'beep', '', 4 )\n    true\n\n    See Also\n    --------\n    base.startsWith\n","base.epsdiff":"\nbase.epsdiff( x, y[, scale] )\n    Computes the relative difference of two real numbers in units of double-\n    precision floating-point epsilon.\n\n    By default, the function scales the absolute difference by dividing the\n    absolute difference by the maximum absolute value of `x` and `y`. To scale\n    by a different function, specify a scale function name.\n\n    The following `scale` functions are supported:\n\n    - 'max-abs': maximum absolute value of `x` and `y` (default).\n    - 'max': maximum value of `x` and `y`.\n    - 'min-abs': minimum absolute value of `x` and `y`.\n    - 'min': minimum value of `x` and `y`.\n    - 'mean-abs': arithmetic mean of the absolute values of `x` and `y`.\n    - 'mean': arithmetic mean of `x` and `y`.\n    - 'x': `x` (*noncommutative*).\n    - 'y': `y` (*noncommutative*).\n\n    To use a custom scale function, provide a function which accepts two numeric\n    arguments `x` and `y`.\n\n    If computing the relative difference in units of epsilon will result in\n    overflow, the function returns the maximum double-precision floating-point\n    number.\n\n    If the absolute difference of `x` and `y` is `0`, the relative difference is\n    always `0`.\n\n    If `|x| = |y| = infinity`, the function returns `NaN`.\n\n    If `|x| = |-y| = infinity`, the relative difference is `+infinity`.\n\n    If a `scale` function returns `0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    scale: string|Function (optional)\n        Scale function. Default: `'max-abs'`.\n\n    Returns\n    -------\n    out: number\n        Relative difference in units of double-precision floating-point epsilon.\n\n    Examples\n    --------\n    > var d = base.epsdiff( 12.15, 12.149999999999999 )\n    ~0.658\n    > d = base.epsdiff( 2.4341309458983933, 2.4341309458633909, 'mean-abs' )\n    ~64761.512\n\n    // Custom scale function:\n    > function scale( x, y ) { return ( x > y ) ? y : x; };\n    > d = base.epsdiff( 1.0000000000000002, 1.0000000000000100, scale )\n    ~44\n\n    See Also\n    --------\n    base.absdiff, base.reldiff\n","base.erf":"\nbase.erf( x )\n    Evaluates the error function.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    As the error function is an odd function (i.e., `erf(-x) == -erf(x)`), if\n    provided `-0`, the function returns `-0`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.erf( 2.0 )\n    ~0.9953\n    > y = base.erf( -1.0 )\n    ~-0.8427\n    > y = base.erf( -0.0 )\n    -0.0\n    > y = base.erf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.erfc, base.erfinv, base.erfcinv\n","base.erfc":"\nbase.erfc( x )\n    Evaluates the complementary error function.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.erfc( 2.0 )\n    ~0.0047\n    > y = base.erfc( -1.0 )\n    ~1.8427\n    > y = base.erfc( 0.0 )\n    1.0\n    > y = base.erfc( PINF )\n    0.0\n    > y = base.erfc( NINF )\n    2.0\n    > y = base.erfc( NaN )\n    NaN\n\n    See Also\n    --------\n    base.erf, base.erfinv, base.erfcinv, base.erfcx\n","base.erfcinv":"\nbase.erfcinv( x )\n    Evaluates the inverse complementary error function.\n\n    The domain of `x` is restricted to `[0,2]`. If `x` is outside this interval,\n    the function returns `NaN`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.erfcinv( 0.5 )\n    ~0.4769\n    > y = base.erfcinv( 0.8 )\n    ~0.1791\n    > y = base.erfcinv( 0.0 )\n    Infinity\n    > y = base.erfcinv( 2.0 )\n    -Infinity\n    > y = base.erfcinv( NaN )\n    NaN\n\n    See Also\n    --------\n    base.erf, base.erfc, base.erfinv, base.erfcx\n","base.erfcx":"\nbase.erfcx( x )\n    Evaluates the scaled complementary error function.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.erfcx( 1.0 )\n    ~0.4276\n    > y = base.erfcx( -1.0 )\n    ~5.01\n    > y = base.erfcx( 0.0 )\n    1.0\n    > y = base.erfcx( NaN )\n    NaN\n\n    See Also\n    --------\n    base.erfc, base.erfcinv, base.erf, base.erfinv","base.erfinv":"\nbase.erfinv( x )\n    Evaluates the inverse error function.\n\n    If `|x| > 1`, the function returns `NaN`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    As the inverse error function is an odd function (i.e., `erfinv(-x) ==\n    -erfinv(x)`), if provided `-0`, the function returns `-0`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.erfinv( 0.5 )\n    ~0.4769\n    > y = base.erfinv( 0.8 )\n    ~0.9062\n    > y = base.erfinv( 0.0 )\n    0.0\n    > y = base.erfinv( -0.0 )\n    -0.0\n    > y = base.erfinv( -1.0 )\n    -Infinity\n    > y = base.erfinv( 1.0 )\n    Infinity\n    > y = base.erfinv( NaN )\n    NaN\n\n    See Also\n    --------\n    base.erf, base.erfc, base.erfcinv\n","base.eta":"\nbase.eta( s )\n    Evaluates the Dirichlet eta function for a double-precision\n    floating-point number `s`.\n\n    Parameters\n    ----------\n    s: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.eta( 0.0 )\n    0.5\n    > y = base.eta( -1.0 )\n    0.25\n    > y = base.eta( 1.0 )\n    ~0.6931\n    > y = base.eta( 3.14 )\n    ~0.9096\n    > y = base.eta( NaN )\n    NaN\n\n","base.evalpoly":"\nbase.evalpoly( c, x )\n    Evaluates a polynomial using double-precision floating-point arithmetic.\n\n    Parameters\n    ----------\n    c: Array<number>\n        Polynomial coefficients sorted in ascending degree.\n\n    x: number\n        Value at which to evaluate the polynomial.\n\n    Returns\n    -------\n    out: number\n        Evaluated polynomial.\n\n    Examples\n    --------\n    > var arr = [ 3.0, 2.0, 1.0 ];\n\n    // 3*10^0 + 2*10^1 + 1*10^2\n    > var v = base.evalpoly( arr, 10.0 )\n    123.0\n\n\nbase.evalpoly.factory( c )\n    Returns a function for evaluating a polynomial using double-precision\n    floating-point arithmetic.\n\n    Parameters\n    ----------\n    c: Array<number>\n        Polynomial coefficients sorted in ascending degree.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a polynomial.\n\n    Examples\n    --------\n    > var f = base.evalpoly.factory( [ 3.0, 2.0, 1.0 ] );\n\n    // 3*10^0 + 2*10^1 + 1*10^2\n    > var v = f( 10.0 )\n    123.0\n\n    // 3*5^0 + 2*5^1 + 1*5^2\n    > v = f( 5.0 )\n    38.0\n\n    See Also\n    --------\n    base.evalrational\n","base.evalpoly.factory":"\nbase.evalpoly.factory( c )\n    Returns a function for evaluating a polynomial using double-precision\n    floating-point arithmetic.\n\n    Parameters\n    ----------\n    c: Array<number>\n        Polynomial coefficients sorted in ascending degree.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a polynomial.\n\n    Examples\n    --------\n    > var f = base.evalpoly.factory( [ 3.0, 2.0, 1.0 ] );\n\n    // 3*10^0 + 2*10^1 + 1*10^2\n    > var v = f( 10.0 )\n    123.0\n\n    // 3*5^0 + 2*5^1 + 1*5^2\n    > v = f( 5.0 )\n    38.0\n\n    See Also\n    --------\n    base.evalrational","base.evalrational":"\nbase.evalrational( P, Q, x )\n    Evaluates a rational function using double-precision floating-point\n    arithmetic.\n\n    A rational function `f(x)` is defined as\n\n               P(x)\n        f(x) = ----\n               Q(x)\n\n    where both `P(x)` and `Q(x)` are polynomials in `x`.\n\n    The coefficients for both `P` and `Q` should be sorted in ascending degree.\n\n    For polynomials of different degree, the coefficient array for the lower\n    degree polynomial should be padded with zeros.\n\n    Parameters\n    ----------\n    P: Array<number>\n        Numerator polynomial coefficients sorted in ascending degree.\n\n    Q: Array<number>\n        Denominator polynomial coefficients sorted in ascending degree.\n\n    x: number\n        Value at which to evaluate the rational function.\n\n    Returns\n    -------\n    out: number\n        Evaluated rational function.\n\n    Examples\n    --------\n    // 2x^3 + 4x^2 - 5x^1 - 6x^0\n    > var P = [ -6.0, -5.0, 4.0, 2.0 ];\n\n    // 0.5x^1 + 3x^0\n    > var Q = [ 3.0, 0.5, 0.0, 0.0 ]; // zero-padded\n\n    // Evaluate the rational function:\n    > var v = base.evalrational( P, Q, 6.0 )\n    90.0\n\n\nbase.evalrational.factory( P, Q )\n    Returns a function for evaluating a rational function using double-precision\n    floating-point arithmetic.\n\n    Parameters\n    ----------\n    P: Array<number>\n        Numerator polynomial coefficients sorted in ascending degree.\n\n    Q: Array<number>\n        Denominator polynomial coefficients sorted in ascending degree.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a rational function.\n\n    Examples\n    --------\n    > var P = [ 20.0, 8.0, 3.0 ];\n    > var Q = [ 10.0, 9.0, 1.0 ];\n    > var f = base.evalrational.factory( P, Q );\n\n    // (20*10^0 + 8*10^1 + 3*10^2) / (10*10^0 + 9*10^1 + 1*10^2):\n    > var v = f( 10.0 )\n    2.0\n\n    // (20*2^0 + 8*2^1 + 3*2^2) / (10*2^0 + 9*2^1 + 1*2^2):\n    > v = f( 2.0 )\n    1.5\n\n    See Also\n    --------\n    base.evalpoly\n","base.evalrational.factory":"\nbase.evalrational.factory( P, Q )\n    Returns a function for evaluating a rational function using double-precision\n    floating-point arithmetic.\n\n    Parameters\n    ----------\n    P: Array<number>\n        Numerator polynomial coefficients sorted in ascending degree.\n\n    Q: Array<number>\n        Denominator polynomial coefficients sorted in ascending degree.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a rational function.\n\n    Examples\n    --------\n    > var P = [ 20.0, 8.0, 3.0 ];\n    > var Q = [ 10.0, 9.0, 1.0 ];\n    > var f = base.evalrational.factory( P, Q );\n\n    // (20*10^0 + 8*10^1 + 3*10^2) / (10*10^0 + 9*10^1 + 1*10^2):\n    > var v = f( 10.0 )\n    2.0\n\n    // (20*2^0 + 8*2^1 + 3*2^2) / (10*2^0 + 9*2^1 + 1*2^2):\n    > v = f( 2.0 )\n    1.5\n\n    See Also\n    --------\n    base.evalpoly","base.exp":"\nbase.exp( x )\n    Evaluates the natural exponential function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.exp( 4.0 )\n    ~54.5982\n    > y = base.exp( -9.0 )\n    ~1.234e-4\n    > y = base.exp( 0.0 )\n    1.0\n    > y = base.exp( NaN )\n    NaN\n\n    See Also\n    --------\n    base.exp10, base.exp2, base.expm1, base.ln\n","base.exp2":"\nbase.exp2( x )\n    Evaluates the base 2 exponential function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.exp2( 3.0 )\n    8.0\n    > y = base.exp2( -9.0 )\n    ~0.002\n    > y = base.exp2( 0.0 )\n    1.0\n    > y = base.exp2( NaN )\n    NaN\n\n    See Also\n    --------\n    base.exp, base.exp10, base.log2\n","base.exp10":"\nbase.exp10( x )\n    Evaluates the base 10 exponential function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.exp10( 3.0 )\n    1000\n    > y = base.exp10( -9.0 )\n    1.0e-9\n    > y = base.exp10( 0.0 )\n    1.0\n    > y = base.exp10( NaN )\n    NaN\n\n    See Also\n    --------\n    base.exp, base.exp2, base.log10\n","base.expit":"\nbase.expit( x )\n    Evaluates the standard logistic function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.expit( 0.0 )\n    0.5\n    > y = base.expit( 1.0 )\n    ~0.731\n    > y = base.expit( -1.0 )\n    ~0.269\n    > y = base.expit( Infinity )\n    1.0\n    > y = base.expit( NaN )\n    NaN\n\n    See Also\n    --------\n    base.exp, base.logit","base.expm1":"\nbase.expm1( x )\n    Computes `exp(x)-1`, where `exp(x)` is the natural exponential function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.expm1( 0.2 )\n    ~0.221\n    > y = base.expm1( -9.0 )\n    ~-1.0\n    > y = base.expm1( 0.0 )\n    0.0\n    > y = base.expm1( NaN )\n    NaN\n\n    See Also\n    --------\n    base.exp, base.expm1rel\n","base.expm1rel":"\nbase.expm1rel( x )\n    Relative error exponential.\n\n    When `x` is near zero,\n\n        e^x - 1\n\n    can suffer catastrophic cancellation (i.e., significant loss of precision).\n    This function avoids the loss of precision when `x` is near zero.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.expm1rel( 0.0 )\n    1.0\n    > y = base.expm1rel( 1.0 )\n    ~1.718\n    > y = base.expm1rel( -1.0 )\n    ~0.632\n    > y = base.expm1rel( NaN )\n    NaN\n\t\n    See Also\n    --------\n    base.exp, base.expm1\n","base.exponent":"\nbase.exponent( x )\n    Returns an integer corresponding to the unbiased exponent of a double-\n    precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    Returns\n    -------\n    out: integer\n        Unbiased exponent.\n\n    Examples\n    --------\n    > var exponent = base.exponent( 3.14e-307 )\n    -1019\n    > exponent = base.exponent( -3.14 )\n    1\n    > exponent = base.exponent( 0.0 )\n    -1023\n    > exponent = base.exponent( NaN )\n    1024\n\n    See Also\n    --------\n    base.exponentf\n","base.exponentf":"\nbase.exponentf( x )\n    Returns an integer corresponding to the unbiased exponent of a single-\n    precision floating-point number.\n\n    Parameters\n    ----------\n    x: float\n        Single-precision floating-point number.\n\n    Returns\n    -------\n    out: integer\n        Unbiased exponent.\n\n    Examples\n    --------\n    > var exponent = base.exponentf( base.float64ToFloat32( 3.14e34 ) )\n    114\n    > exponent = base.exponentf( base.float64ToFloat32( 3.14e-34 ) )\n    -112\n    > exponent = base.exponentf( base.float64ToFloat32( -3.14 ) )\n    1\n    > exponent = base.exponentf( 0.0 )\n    -127\n    > exponent = base.exponentf( NaN )\n    128\n\n    See Also\n    --------\n    base.exponent\n","base.factorial":"\nbase.factorial( x )\n    Evaluates the factorial of `x`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Factorial.\n\n    Examples\n    --------\n    > var y = base.factorial( 3.0 )\n    6.0\n    > y = base.factorial( -1.5 )\n    ~-3.545\n    > y = base.factorial( -0.5 )\n    ~1.772\n    > y = base.factorial( 0.5 )\n    ~0.886\n    > y = base.factorial( -10.0 )\n    NaN\n    > y = base.factorial( 171.0 )\n    Infinity\n    > y = base.factorial( NaN )\n    NaN\n\n    See Also\n    --------\n    base.factorialln\n","base.factorial2":"\nbase.factorial2( n )\n    Evaluates the double factorial of `n`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Double factorial.\n\n    Examples\n    --------\n    > var y = base.factorial2( 3 )\n    3\n    > y = base.factorial2( 5 )\n    15\n    > y = base.factorial2( 6 )\n    48\n    > y = base.factorial2( 301 )\n    Infinity\n    > y = base.factorial2( NaN )\n    NaN\n\n    See Also\n    --------\n    base.factorial\n","base.factorialln":"\nbase.factorialln( x )\n    Evaluates the natural logarithm of the factorial of `x`.\n\n    For input values other than negative integers, the function returns\n\n      ln( x! ) = ln( Γ(x+1) )\n\n    where `Γ` is the Gamma function. For negative integers, the function returns\n    `NaN`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Natural logarithm of the factorial of `x`.\n\n    Examples\n    --------\n    > var y = base.factorialln( 3.0 )\n    ~1.792\n    > y = base.factorialln( 2.4 )\n    ~1.092\n    > y = base.factorialln( -1.0 )\n    NaN\n    > y = base.factorialln( -1.5 )\n    ~1.266\n    > y = base.factorialln( NaN )\n    NaN\n\n    See Also\n    --------\n    base.factorial\n","base.fallingFactorial":"\nbase.fallingFactorial( x, n )\n    Computes the falling factorial of `x` and `n`.\n\n    If not provided a nonnegative integer for `n`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        First function parameter.\n\n    n: integer\n        Second function parameter.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var v = base.fallingFactorial( 0.9, 5 )\n    ~0.644\n    > v = base.fallingFactorial( -9.0, 3 )\n    -990.0\n    > v = base.fallingFactorial( 0.0, 2 )\n    0.0\n    > v = base.fallingFactorial( 3.0, -2 )\n    NaN\n\n    See Also\n    --------\n    base.risingFactorial\n","base.fibonacci":"\nbase.fibonacci( n )\n    Computes the nth Fibonacci number.\n\n    Fibonacci numbers follow the recurrence relation\n\n      F_n = F_{n-1} + F_{n-2}\n\n    with seed values F_0 = 0 and F_1 = 1.\n\n    If `n` is greater than `78`, the function returns `NaN`, as larger Fibonacci\n    numbers cannot be accurately represented due to limitations of double-\n    precision floating-point format.\n\n    If not provided a nonnegative integer value, the function returns `NaN`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Input value.\n\n    Returns\n    -------\n    y: integer\n        Fibonacci number.\n\n    Examples\n    --------\n    > var y = base.fibonacci( 0 )\n    0\n    > y = base.fibonacci( 1 )\n    1\n    > y = base.fibonacci( 2 )\n    1\n    > y = base.fibonacci( 3 )\n    2\n    > y = base.fibonacci( 4 )\n    3\n    > y = base.fibonacci( 79 )\n    NaN\n    > y = base.fibonacci( NaN )\n    NaN\n\n    See Also\n    --------\n    base.binet, base.fibonacciIndex, base.lucas, base.negafibonacci\n","base.fibonacciIndex":"\nbase.fibonacciIndex( F )\n    Computes the Fibonacci number index.\n\n    If not provided a nonnegative integer value, the function returns `NaN`.\n\n    If provided `F <= 1` or `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    F: integer\n        Fibonacci number.\n\n    Returns\n    -------\n    n: number\n        Fibonacci number index.\n\n    Examples\n    --------\n    > var n = base.fibonacciIndex( 2 )\n    3\n    > n = base.fibonacciIndex( 3 )\n    4\n    > n = base.fibonacciIndex( 5 )\n    5\n    > n = base.fibonacciIndex( NaN )\n    NaN\n    > n = base.fibonacciIndex( 1 )\n    NaN\n\n    See Also\n    --------\n    base.fibonacci\n","base.fibpoly":"\nbase.fibpoly( n, x )\n    Evaluates a Fibonacci polynomial.\n\n    Parameters\n    ----------\n    n: integer\n        Fibonacci polynomial to evaluate.\n\n    x: number\n        Value at which to evaluate the Fibonacci polynomial.\n\n    Returns\n    -------\n    out: number\n        Evaluated Fibonacci polynomial.\n\n    Examples\n    --------\n    // 2^4 + 3*2^2 + 1\n    > var v = base.fibpoly( 5, 2.0 )\n    29.0\n\n\nbase.fibpoly.factory( n )\n    Returns a function for evaluating a Fibonacci polynomial.\n\n    Parameters\n    ----------\n    n: integer\n        Fibonacci polynomial to evaluate.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a Fibonacci polynomial.\n\n    Examples\n    --------\n    > var polyval = base.fibpoly.factory( 5 );\n\n    // 1^4 + 3*1^2 + 1\n    > var v = polyval( 1.0 )\n    5.0\n\n    // 2^4 + 3*2^2 + 1\n    > v = polyval( 2.0 )\n    29.0\n\n    See Also\n    --------\n    base.evalpoly, base.lucaspoly\n","base.fibpoly.factory":"\nbase.fibpoly.factory( n )\n    Returns a function for evaluating a Fibonacci polynomial.\n\n    Parameters\n    ----------\n    n: integer\n        Fibonacci polynomial to evaluate.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a Fibonacci polynomial.\n\n    Examples\n    --------\n    > var polyval = base.fibpoly.factory( 5 );\n\n    // 1^4 + 3*1^2 + 1\n    > var v = polyval( 1.0 )\n    5.0\n\n    // 2^4 + 3*2^2 + 1\n    > v = polyval( 2.0 )\n    29.0\n\n    See Also\n    --------\n    base.evalpoly, base.lucaspoly","base.firstCodePoint":"\nbase.firstCodePoint( str, n )\n    Returns the first `n` Unicode code points of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of Unicode code points to return.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.firstCodePoint( 'beep', 1 )\n    'b'\n    > out = base.firstCodePoint( 'Boop', 1 )\n    'B'\n    > out = base.firstCodePoint( 'foo bar', 5 )\n    'foo b'\n\n    See Also\n    --------\n    base.firstCodeUnit, base.firstGraphemeCluster, base.lastCodePoint, base.removeFirstCodePoint, firstChar\n","base.firstCodeUnit":"\nbase.firstCodeUnit( str, n )\n    Returns the first `n` UTF-16 code units of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of UTF-16 code units to return.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.firstCodeUnit( 'beep', 1 )\n    'b'\n    > out = base.firstCodeUnit( 'Boop', 1 )\n    'B'\n    > out = base.firstCodeUnit( 'foo bar', 5 )\n    'foo b'\n\n    See Also\n    --------\n    base.firstCodePoint, base.firstGraphemeCluster, base.last, base.removeFirst, firstChar\n","base.firstGraphemeCluster":"\nbase.firstGraphemeCluster( str, n )\n    Returns the first `n` grapheme clusters (i.e., user-perceived characters) of\n    a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of grapheme clusters to return.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.firstGraphemeCluster( 'beep', 1 )\n    'b'\n    > out = base.firstGraphemeCluster( 'Boop', 1 )\n    'B'\n    > out = base.firstGraphemeCluster( 'foo bar', 5 )\n    'foo b'\n\n    See Also\n    --------\n    base.firstCodeUnit, base.firstCodePoint, base.lastGraphemeCluster, base.removeFirstGraphemeCluster, firstChar\n","base.flipsign":"\nbase.flipsign( x, y )\n    Returns a double-precision floating-point number with the magnitude of `x`\n    and the sign of `x*y`.\n\n    The function only returns `-x` when `y` is a negative number.\n\n    According to the IEEE 754 standard, a `NaN` has a biased exponent equal to\n    `2047`, a significand greater than `0`, and a sign bit equal to either `1`\n    or `0`. In which case, `NaN` may not correspond to just one but many binary\n    representations. Accordingly, care should be taken to ensure that `y` is not\n    `NaN`; otherwise, behavior may be indeterminate.\n\n    Parameters\n    ----------\n    x: number\n        Number from which to derive a magnitude.\n\n    y: number\n        Number from which to derive a sign.\n\n    Returns\n    -------\n    z: number\n        Double-precision floating-point number.\n\n    Examples\n    --------\n    > var z = base.flipsign( -3.0, 10.0 )\n    -3.0\n    > z = base.flipsign( -3.0, -1.0 )\n    3.0\n    > z = base.flipsign( 1.0, -0.0 )\n    -1.0\n    > z = base.flipsign( -3.0, -0.0 )\n    3.0\n    > z = base.flipsign( -0.0, 1.0 )\n    -0.0\n    > z = base.flipsign( 0.0, -1.0 )\n    -0.0\n\n    See Also\n    --------\n    base.copysign\n","base.flipsignf":"\nbase.flipsignf( x, y )\n    Returns a single-precision floating-point number with the magnitude of `x`\n    and the sign of `x*y`.\n\n    The function only returns `-x` when `y` is a negative number.\n\n    According to the IEEE 754 standard, a `NaN` has a biased exponent equal to\n    `255`, a significand greater than `0`, and a sign bit equal to either `1` or\n    `0`. In which case, `NaN` may not correspond to just one but many binary\n    representations. Accordingly, care should be taken to ensure that `y` is not\n    `NaN`; otherwise, behavior may be indeterminate.\n\n    Parameters\n    ----------\n    x: number\n        Number from which to derive a magnitude.\n\n    y: number\n        Number from which to derive a sign.\n\n    Returns\n    -------\n    z: number\n        Single-precision floating-point number.\n\n    Examples\n    --------\n    > var z = base.flipsignf( -3.0, 10.0 )\n    -3.0\n    > z = base.flipsignf( -3.0, -1.0 )\n    3.0\n    > z = base.flipsignf( 1.0, -0.0 )\n    -1.0\n    > z = base.flipsignf( -3.0, -0.0 )\n    3.0\n    > z = base.flipsignf( -0.0, 1.0 )\n    -0.0\n    > z = base.flipsignf( 0.0, -1.0 )\n    -0.0\n\n    See Also\n    --------\n    base.copysignf, base.flipsign\n","base.float32ToInt32":"\nbase.float32ToInt32( x )\n    Converts a single-precision floating-point number to a signed 32-bit\n    integer.\n\n    Parameters\n    ----------\n    x: float\n        Single-precision floating-point number.\n\n    Returns\n    -------\n    out: integer\n        Signed 32-bit integer.\n\n    Examples\n    --------\n    > var y = base.float32ToInt32( base.float64ToFloat32( 4294967295.0 ) )\n    0\n    > y = base.float32ToInt32( base.float64ToFloat32( 3.14 ) )\n    3\n    > y = base.float32ToInt32( base.float64ToFloat32( -3.14 ) )\n    -3\n    > y = base.float32ToInt32( base.float64ToFloat32( NaN ) )\n    0\n    > y = base.float32ToInt32( FLOAT32_PINF )\n    0\n    > y = base.float32ToInt32( FLOAT32_NINF )\n    0\n\n    See Also\n    --------\n    base.float32ToUint32","base.float32ToUint32":"\nbase.float32ToUint32( x )\n    Converts a single-precision floating-point number to a unsigned 32-bit\n    integer.\n\n    Parameters\n    ----------\n    x: float\n        Single-precision floating-point number.\n\n    Returns\n    -------\n    out: integer\n        Unsigned 32-bit integer.\n\n    Examples\n    --------\n    > var y = base.float32ToUint32( base.float64ToFloat32( 4294967297.0 ) )\n    0\n    > y = base.float32ToUint32( base.float64ToFloat32( 3.14 ) )\n    3\n    > y = base.float32ToUint32( base.float64ToFloat32( -3.14 ) )\n    4294967293\n    > y = base.float32ToUint32( base.float64ToFloat32( NaN ) )\n    0\n    > y = base.float32ToUint32( FLOAT32_PINF )\n    0\n    > y = base.float32ToUint32( FLOAT32_NINF )\n    0\n\n    See Also\n    --------\n    base.float32ToInt32","base.float64ToFloat32":"\nbase.float64ToFloat32( x )\n    Converts a double-precision floating-point number to the nearest single-\n    precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    Returns\n    -------\n    out: float\n        Nearest single-precision floating-point number.\n\n    Examples\n    --------\n    > var y = base.float64ToFloat32( 1.337 )\n    1.3370000123977661\n","base.float64ToInt32":"\nbase.float64ToInt32( x )\n    Converts a double-precision floating-point number to a signed 32-bit\n    integer.\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    Returns\n    -------\n    out: integer\n        Signed 32-bit integer.\n\n    Examples\n    --------\n    > var y = base.float64ToInt32( 4294967295.0 )\n    -1\n    > y = base.float64ToInt32( 3.14 )\n    3\n    > y = base.float64ToInt32( -3.14 )\n    -3\n    > y = base.float64ToInt32( NaN )\n    0\n    > y = base.float64ToInt32( PINF )\n    0\n    > y = base.float64ToInt32( NINF )\n    0\n\n    See Also\n    --------\n    base.float64ToUint32","base.float64ToInt64Bytes":"\nbase.float64ToInt64Bytes( x )\n    Converts an integer-valued double-precision floating-point number to a\n    signed 64-bit integer byte array according to host byte order (endianness).\n\n    This function assumes that the input value is less than the maximum safe\n    double-precision floating-point integer plus one (i.e., `2**53`).\n\n    Parameters\n    ----------\n    x: integer\n        Integer-valued double-precision floating-point number.\n\n    Returns\n    -------\n    out: Uint8Array\n        Byte array.\n\n    Examples\n    --------\n    > var y = base.float64ToInt64Bytes( 4294967297.0 )\n    <Uint8Array>\n\n\nbase.float64ToInt64Bytes.assign( x, out, stride, offset )\n    Converts an integer-valued double-precision floating-point number to a\n    signed 64-bit integer byte array according to host byte order (endianness)\n    and assigns results to a provided output array.\n\n    This function assumes that the input value is less than the maximum safe\n    double-precision floating-point integer plus one (i.e., `2**53`).\n\n    Parameters\n    ----------\n    x: integer\n        Integer-valued double-precision floating-point number.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Output array.\n\n    Examples\n    --------\n    > var out = new Uint8Array( 16 );\n    > var y = base.float64ToInt64Bytes( 4294967297.0, out, 2, 1 )\n    <Uint8Array>\n\n    See Also\n    --------\n    base.float64ToInt32","base.float64ToInt64Bytes.assign":"\nbase.float64ToInt64Bytes.assign( x, out, stride, offset )\n    Converts an integer-valued double-precision floating-point number to a\n    signed 64-bit integer byte array according to host byte order (endianness)\n    and assigns results to a provided output array.\n\n    This function assumes that the input value is less than the maximum safe\n    double-precision floating-point integer plus one (i.e., `2**53`).\n\n    Parameters\n    ----------\n    x: integer\n        Integer-valued double-precision floating-point number.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Output array.\n\n    Examples\n    --------\n    > var out = new Uint8Array( 16 );\n    > var y = base.float64ToInt64Bytes( 4294967297.0, out, 2, 1 )\n    <Uint8Array>\n\n    See Also\n    --------\n    base.float64ToInt32","base.float64ToUint32":"\nbase.float64ToUint32( x )\n    Converts a double-precision floating-point number to a unsigned 32-bit\n    integer.\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    Returns\n    -------\n    out: integer\n        Unsigned 32-bit integer.\n\n    Examples\n    --------\n    > var y = base.float64ToUint32( 4294967297.0 )\n    1\n    > y = base.float64ToUint32( 3.14 )\n    3\n    > y = base.float64ToUint32( -3.14 )\n    4294967293\n    > y = base.float64ToUint32( NaN )\n    0\n    > y = base.float64ToUint32( PINF )\n    0\n    > y = base.float64ToUint32( NINF )\n    0\n\n    See Also\n    --------\n    base.float64ToInt32","base.floor":"\nbase.floor( x )\n    Rounds a double-precision floating-point number toward negative infinity.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.floor( 3.14 )\n    3.0\n    > y = base.floor( -4.2 )\n    -5.0\n    > y = base.floor( -4.6 )\n    -5.0\n    > y = base.floor( 9.5 )\n    9.0\n    > y = base.floor( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceil, base.round\n","base.floor2":"\nbase.floor2( x )\n    Rounds a numeric value to the nearest power of two toward negative infinity.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.floor2( 3.14 )\n    2.0\n    > y = base.floor2( -4.2 )\n    -8.0\n    > y = base.floor2( -4.6 )\n    -8.0\n    > y = base.floor2( 9.5 )\n    8.0\n    > y = base.floor2( 13.0 )\n    8.0\n    > y = base.floor2( -13.0 )\n    -16.0\n    > y = base.floor2( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceil2, base.floor, base.floor10, base.round2\n","base.floor10":"\nbase.floor10( x )\n    Rounds a numeric value to the nearest power of ten toward negative infinity.\n\n    The function may not return accurate results for subnormals due to a general\n    loss in precision.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.floor10( 3.14 )\n    1.0\n    > y = base.floor10( -4.2 )\n    -10.0\n    > y = base.floor10( -4.6 )\n    -10.0\n    > y = base.floor10( 9.5 )\n    1.0\n    > y = base.floor10( 13.0 )\n    10.0\n    > y = base.floor10( -13.0 )\n    -100.0\n    > y = base.floor10( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceil10, base.floor, base.floor2, base.round10\n","base.floorb":"\nbase.floorb( x, n, b )\n    Rounds a numeric value to the nearest multiple of `b^n` toward negative\n    infinity.\n\n    Due to floating-point rounding error, rounding may not be exact.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Integer power.\n\n    b: integer\n        Base.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    // Round to 4 decimal places:\n    > var y = base.floorb( 3.14159, -4, 10 )\n    3.1415\n\n    // If `n = 0` or `b = 1`, standard round behavior:\n    > y = base.floorb( 3.14159, 0, 2 )\n    3.0\n\n    // Round to nearest multiple of two toward negative infinity:\n    > y = base.floorb( 5.0, 1, 2 )\n    4.0\n\n    See Also\n    --------\n    base.ceilb, base.floor, base.floorn, base.roundb\n","base.floorf":"\nbase.floorf( x )\n    Rounds a single-precision floating-point number toward negative infinity.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.floorf( 3.14 )\n    3.0\n    > y = base.floorf( -4.2 )\n    -5.0\n    > y = base.floorf( -4.6 )\n    -5.0\n    > y = base.floorf( 9.5 )\n    9.0\n    > y = base.floorf( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceilf, base.floor\n","base.floorn":"\nbase.floorn( x, n )\n    Rounds a double-precision floating-point number to the nearest multiple of\n    `10^n` toward negative infinity.\n\n    When operating on floating-point numbers in bases other than `2`, rounding\n    to specified digits can be inexact.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Integer power of 10.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    // Round to 4 decimal places:\n    > var y = base.floorn( 3.14159, -4 )\n    3.1415\n\n    // If `n = 0`, standard round toward negative infinity behavior:\n    > y = base.floorn( 3.14159, 0 )\n    3.0\n\n    // Round to nearest thousand:\n    > y = base.floorn( 12368.0, 3 )\n    12000.0\n\n\n    See Also\n    --------\n    base.ceiln, base.floor, base.floorb, base.roundn\n","base.floorsd":"\nbase.floorsd( x, n, b )\n    Rounds a numeric value to the nearest number toward negative infinity with\n    `n` significant figures.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Number of significant figures. Must be greater than 0.\n\n    b: integer\n        Base. Must be greater than 0.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.floorsd( 3.14159, 5, 10 )\n    3.1415\n    > y = base.floorsd( 3.14159, 1, 10 )\n    3.0\n    > y = base.floorsd( 12368.0, 2, 10 )\n    12000.0\n    > y = base.floorsd( 0.0313, 2, 2 )\n    0.03125\n\n    See Also\n    --------\n    base.ceilsd, base.floor, base.roundsd, base.truncsd\n","base.forEachChar":"\nbase.forEachChar( str, clbk[, thisArg] )\n    Invokes a function for each UTF-16 code unit in a string.\n\n    When invoked, the provided function is provided three arguments:\n\n    - value: character.\n    - index: character index.\n    - str: input string.\n\n    Parameters\n    ----------\n    str: string\n        Input string over which to iterate.\n\n    clbk: Function\n        The function to invoke for each UTF-16 code unit in the input string.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: string\n        Input string.\n\n    Examples\n    --------\n    > var n = 0;\n    > function fcn() { n += 1; };\n    > base.forEachChar( 'hello world!', fcn );\n    > n\n    12\n\n    See Also\n    --------\n    base.forEachCodePoint, base.forEachGraphemeCluster, forEachChar\n","base.forEachCodePoint":"\nbase.forEachCodePoint( str, clbk[, thisArg] )\n    Invokes a function for each Unicode code point in a string.\n\n    When invoked, the provided function is provided three arguments:\n\n    - value: code point.\n    - index: starting code point index.\n    - str: input string.\n\n    Parameters\n    ----------\n    str: string\n        Input string over which to iterate.\n\n    clbk: Function\n        The function to invoke for each Unicode code point in the input string.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: string\n        Input string.\n\n    Examples\n    --------\n    > var n = 0;\n    > function fcn() { n += 1; };\n    > base.forEachCodePoint( 'hello world!', fcn );\n    > n\n    12\n\n    See Also\n    --------\n    base.forEachChar, base.forEachGraphemeCluster, forEachChar\n","base.forEachCodePointRight":"\nbase.forEachCodePointRight( str, clbk[, thisArg] )\n    Invokes a function for each Unicode code point in a string, iterating from\n    right to left.\n\n    When invoked, the provided function is provided three arguments:\n\n    - value: code point.\n    - index: starting code point index.\n    - str: input string.\n\n    Parameters\n    ----------\n    str: string\n        Input string over which to iterate.\n\n    clbk: Function\n        The function to invoke for each Unicode code point in the input string.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: string\n        Input string.\n\n    Examples\n    --------\n    > var n = 0;\n    > function fcn() { n += 1; };\n    > base.forEachCodePointRight( 'hello world!', fcn );\n    > n\n    12\n\n    See Also\n    --------\n    base.forEachCodePoint, base.forEachRight\n","base.forEachGraphemeCluster":"\nbase.forEachGraphemeCluster( str, clbk[, thisArg] )\n    Invokes a function for each grapheme cluster (i.e., user-perceived\n    character) in a string.\n\n    When invoked, the provided function is provided three arguments:\n\n    - value: grapheme cluster.\n    - index: starting grapheme cluster index.\n    - str: input string.\n\n    Parameters\n    ----------\n    str: string\n        Input string over which to iterate.\n\n    clbk: Function\n        The function to invoke for each grapheme cluster in the input string.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: string\n        Input string.\n\n    Examples\n    --------\n    > var n = 0;\n    > function fcn() { n += 1; };\n    > base.forEachGraphemeCluster( 'hello world!', fcn );\n    > n\n    12\n\n    See Also\n    --------\n    base.forEachChar, base.forEachCodePoint, forEachChar\n","base.forEachRight":"\nbase.forEachRight( str, clbk[, thisArg] )\n    Invokes a function for each UTF-16 code unit in a string, iterating from\n    right to left.\n\n    When invoked, the provided function is provided three arguments:\n\n    - value: character.\n    - index: character index.\n    - str: input string.\n\n    Parameters\n    ----------\n    str: string\n        Input string over which to iterate.\n\n    clbk: Function\n        Function to invoke for each UTF-16 code unit in the input string.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: string\n        Input string.\n\n    Examples\n    --------\n    > var n = 0;\n    > function fcn() { n += 1; };\n    > base.forEachRight( 'hello world!', fcn );\n    > n\n    12\n\n    See Also\n    --------\n    base.forEachChar, base.forEachCodePointRight\n","base.formatInterpolate":"\nbase.formatInterpolate( tokens, ...args )\n    Generate string from a token array by interpolating values.\n\n    Parameters\n    ----------\n    tokens: Array\n        Array of string parts and format identifier objects.\n\n    args: ...any\n        Variable values.\n\n    Returns\n    -------\n    out: string\n        Formatted string.\n\n    Examples\n    --------\n    > var out = base.formatInterpolate( [ 'beep ', { 'specifier': 's' } ], 'boop' )\n    'beep boop'\n    > out = base.formatInterpolate( [ 'baz ', { 'specifier': 'd', 'precision': 2 } ], 1 )\n    'baz 1.00'\n    > out = base.formatInterpolate( [ { 'specifier': 'u', 'width': 6 } ], 12 )\n    '    12'\n\n    See Also\n    --------\n    base.formatTokenize\n","base.formatTokenize":"\nbase.formatTokenize( str )\n    Tokenize a string into an array of string parts and format identifier\n    objects.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: Array\n        Array of string parts and format identifier objects.\n\n    Examples\n    --------\n    > var out = base.formatTokenize( 'Hello %s!' )\n    [ 'Hello ', {...}, '!' ]\n    > out = base.formatTokenize( '%s %s %d' )\n    [ {...}, ' ', {...}, ' ', {...}, ' ' ]\n    > out = base.formatTokenize( 'Pi: %.2f' )\n    [ 'Pi: ', {...} ]\n\n    See Also\n    --------\n    base.formatInterpolate\n","base.fresnel":"\nbase.fresnel( x )\n    Computes the Fresnel integrals S(x) and C(x).\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: Array<number>\n        S(x) and C(x).\n\n    Examples\n    --------\n    > var y = base.fresnel( 0.0 )\n    [ ~0.0, ~0.0 ]\n    > y = base.fresnel( 1.0 )\n    [ ~0.438, ~0.780 ]\n    > y = base.fresnel( PINF )\n    [ ~0.5, ~0.5 ]\n    > y = base.fresnel( NINF )\n    [ ~-0.5, ~-0.5 ]\n    > y = base.fresnel( NaN )\n    [ NaN, NaN ]\n\n\nbase.fresnel.assign( x, out, stride, offset )\n    Computes the Fresnel integrals S(x) and C(x) and assigns results to a\n    provided output array.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    out: Array<number>\n        Destination array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array<number>\n        S(x) and C(x).\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var v = base.fresnel.assign( 0.0, out, 1, 0 )\n    <Float64Array>[ ~0.0, ~0.0 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.fresnelc, base.fresnels","base.fresnel.assign":"\nbase.fresnel.assign( x, out, stride, offset )\n    Computes the Fresnel integrals S(x) and C(x) and assigns results to a\n    provided output array.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    out: Array<number>\n        Destination array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array<number>\n        S(x) and C(x).\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var v = base.fresnel.assign( 0.0, out, 1, 0 )\n    <Float64Array>[ ~0.0, ~0.0 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.fresnelc, base.fresnels","base.fresnelc":"\nbase.fresnelc( x )\n    Computes the Fresnel integral C(x).\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        C(x).\n\n    Examples\n    --------\n    > var y = base.fresnelc( 0.0 )\n    ~0.0\n    > y = base.fresnelc( 1.0 )\n    ~0.780\n    > y = base.fresnelc( PINF )\n    ~0.5\n    > y = base.fresnelc( NINF )\n    ~-0.5\n    > y = base.fresnelc( NaN )\n    NaN\n\n    See Also\n    --------\n    base.fresnel, base.fresnels\n","base.fresnels":"\nbase.fresnels( x )\n    Computes the Fresnel integral S(x).\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        S(x).\n\n    Examples\n    --------\n    > var y = base.fresnels( 0.0 )\n    ~0.0\n    > y = base.fresnels( 1.0 )\n    ~0.438\n    > y = base.fresnels( PINF )\n    ~0.5\n    > y = base.fresnels( NINF )\n    ~-0.5\n    > y = base.fresnels( NaN )\n    NaN\n\n    See Also\n    --------\n    base.fresnel, base.fresnelc\n","base.frexp":"\nbase.frexp( x )\n    Splits a double-precision floating-point number into a normalized fraction\n    and an integer power of two.\n\n    The first element of the returned array is the normalized fraction and the\n    second is the exponent. The normalized fraction and exponent satisfy the\n    relation\n\n      x = frac * 2^exp\n\n    If provided positive or negative zero, `NaN`, or positive or negative\n    infinity, the function returns a two-element array containing the input\n    value and an exponent equal to zero.\n\n    For all other numeric input values, the absolute value of the normalized\n    fraction resides on the interval [0.5,1).\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    out: Array<number>\n        A normalized fraction and an exponent.\n\n    Examples\n    --------\n    > var out = base.frexp( 4.0 )\n    [ 0.5, 3 ]\n    > out = base.frexp( 0.0 )\n    [ 0.0, 0 ]\n    > out = base.frexp( -0.0 )\n    [ -0.0, 0 ]\n    > out = base.frexp( NaN )\n    [ NaN, 0 ]\n    > out = base.frexp( PINF )\n    [ Infinity, 0 ]\n    > out = base.frexp( NINF )\n    [ -Infinity, 0 ]\n\n\nbase.frexp.assign( x, out, stride, offset )\n    Splits a double-precision floating-point number into a normalized fraction\n    and an integer power of two and assigns results to a provided output array.\n\n    The first element of the returned array is the normalized fraction and the\n    second is the exponent. The normalized fraction and exponent satisfy the\n    relation\n\n      x = frac * 2^exp\n\n    If provided positive or negative zero, `NaN`, or positive or negative\n    infinity, the function returns a two-element array containing the input\n    value and an exponent equal to zero.\n\n    For all other numeric input values, the absolute value of the normalized\n    fraction resides on the interval [0.5,1).\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    out: Array<number>\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array<number>\n        A normalized fraction and an exponent.\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var y = base.frexp.assign( 4.0, out, 1, 0 )\n    <Float64Array>[ 0.5, 3 ]\n    > var bool = ( y === out )\n    true\n\n    See Also\n    --------\n    base.ldexp\n","base.frexp.assign":"\nbase.frexp.assign( x, out, stride, offset )\n    Splits a double-precision floating-point number into a normalized fraction\n    and an integer power of two and assigns results to a provided output array.\n\n    The first element of the returned array is the normalized fraction and the\n    second is the exponent. The normalized fraction and exponent satisfy the\n    relation\n\n      x = frac * 2^exp\n\n    If provided positive or negative zero, `NaN`, or positive or negative\n    infinity, the function returns a two-element array containing the input\n    value and an exponent equal to zero.\n\n    For all other numeric input values, the absolute value of the normalized\n    fraction resides on the interval [0.5,1).\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    out: Array<number>\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array<number>\n        A normalized fraction and an exponent.\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var y = base.frexp.assign( 4.0, out, 1, 0 )\n    <Float64Array>[ 0.5, 3 ]\n    > var bool = ( y === out )\n    true\n\n    See Also\n    --------\n    base.ldexp","base.fromBinaryString":"\nbase.fromBinaryString( bstr )\n    Creates a double-precision floating-point number from a literal bit\n    representation.\n\n    Parameters\n    ----------\n    bstr: string\n        Literal bit representation.\n\n    Returns\n    -------\n    out: number\n        Double-precision floating-point number.\n\n    Examples\n    --------\n    > var bstr;\n    > bstr = '0100000000010000000000000000000000000000000000000000000000000000';\n    > var val = base.fromBinaryString( bstr )\n    4.0\n    > bstr = '0100000000001001001000011111101101010100010001000010110100011000';\n    > val = base.fromBinaryString( bstr )\n    3.141592653589793\n    > bstr = '1111111111100001110011001111001110000101111010111100100010100000';\n    > val = base.fromBinaryString( bstr )\n    -1.0e308\n\n    // The function handles subnormals:\n    > bstr = '1000000000000000000000000000000000000000000000000001100011010011';\n    > val = base.fromBinaryString( bstr )\n    -3.14e-320\n    > bstr = '0000000000000000000000000000000000000000000000000000000000000001';\n    > val = base.fromBinaryString( bstr )\n    5.0e-324\n\n    // The function handles special values:\n    > bstr = '0000000000000000000000000000000000000000000000000000000000000000';\n    > val = base.fromBinaryString( bstr )\n    0.0\n    > bstr = '1000000000000000000000000000000000000000000000000000000000000000';\n    > val = base.fromBinaryString( bstr )\n    -0.0\n    > bstr = '0111111111111000000000000000000000000000000000000000000000000000';\n    > val = base.fromBinaryString( bstr )\n    NaN\n    > bstr = '0111111111110000000000000000000000000000000000000000000000000000';\n    > val = base.fromBinaryString( bstr )\n    Infinity\n    > bstr = '1111111111110000000000000000000000000000000000000000000000000000';\n    > val = base.fromBinaryString( bstr )\n    -Infinity\n\n    See Also\n    --------\n    base.fromBinaryStringf, base.toBinaryString\n","base.fromBinaryStringf":"\nbase.fromBinaryStringf( bstr )\n    Creates a single-precision floating-point number from an IEEE 754 literal\n    bit representation.\n\n    Parameters\n    ----------\n    bstr: string\n        Literal bit representation.\n\n    Returns\n    -------\n    out: float\n        Single-precision floating-point number.\n\n    Examples\n    --------\n    > var bstr = '01000000100000000000000000000000';\n    > var val = base.fromBinaryStringf( bstr )\n    4.0\n    > bstr = '01000000010010010000111111011011';\n    > val = base.fromBinaryStringf( bstr )\n    ~3.14\n    > bstr = '11111111011011000011101000110011';\n    > val = base.fromBinaryStringf( bstr )\n    ~-3.14e+38\n\n    // The function handles subnormals:\n    > bstr = '10000000000000000000000000010110';\n    > val = base.fromBinaryStringf( bstr )\n    ~-3.08e-44\n    > bstr = '00000000000000000000000000000001';\n    > val = base.fromBinaryStringf( bstr )\n    ~1.40e-45\n\n    // The function handles special values:\n    > bstr = '00000000000000000000000000000000';\n    > val = base.fromBinaryStringf( bstr )\n    0.0\n    > bstr = '10000000000000000000000000000000';\n    > val = base.fromBinaryStringf( bstr )\n    -0.0\n    > bstr = '01111111110000000000000000000000';\n    > val = base.fromBinaryStringf( bstr )\n    NaN\n    > bstr = '01111111100000000000000000000000';\n    > val = base.fromBinaryStringf( bstr )\n    Infinity\n    > bstr = '11111111100000000000000000000000';\n    > val = base.fromBinaryStringf( bstr )\n    -Infinity\n\n    See Also\n    --------\n    base.toBinaryStringf, base.fromBinaryString\n","base.fromBinaryStringUint8":"\nbase.fromBinaryStringUint8( bstr )\n    Creates an unsigned 8-bit integer from a literal bit representation.\n\n    Parameters\n    ----------\n    bstr: string\n        Literal bit representation.\n\n    Returns\n    -------\n    out: integer\n        Unsigned 8-bit integer.\n\n    Examples\n    --------\n    > var bstr = '01010101';\n    > var val = base.fromBinaryStringUint8( bstr )\n    85\n    > bstr = '00000000';\n    > val = base.fromBinaryStringUint8( bstr )\n    0\n    > bstr = '00000010';\n    > val = base.fromBinaryStringUint8( bstr )\n    2\n    > bstr = '11111111';\n    > val = base.fromBinaryStringUint8( bstr )\n    255\n\n    See Also\n    --------\n    base.fromBinaryStringUint16, base.fromBinaryStringUint32, base.toBinaryStringUint8\n","base.fromBinaryStringUint16":"\nbase.fromBinaryStringUint16( bstr )\n    Creates an unsigned 16-bit integer from a literal bit representation.\n\n    Parameters\n    ----------\n    bstr: string\n        Literal bit representation.\n\n    Returns\n    -------\n    out: integer\n        Unsigned 16-bit integer.\n\n    Examples\n    --------\n    > var bstr = '0101010101010101';\n    > var val = base.fromBinaryStringUint16( bstr )\n    21845\n    > bstr = '0000000000000000';\n    > val = base.fromBinaryStringUint16( bstr )\n    0\n    > bstr = '0000000000000010';\n    > val = base.fromBinaryStringUint16( bstr )\n    2\n    > bstr = '1111111111111111';\n    > val = base.fromBinaryStringUint16( bstr )\n    65535\n\n    See Also\n    --------\n    base.toBinaryStringUint16, base.fromBinaryStringUint32, base.fromBinaryStringUint8\n","base.fromBinaryStringUint32":"\nbase.fromBinaryStringUint32( bstr )\n    Creates an unsigned 32-bit integer from a literal bit representation.\n\n    Parameters\n    ----------\n    bstr: string\n        Literal bit representation.\n\n    Returns\n    -------\n    out: integer\n        Unsigned 32-bit integer.\n\n    Examples\n    --------\n    > var bstr = '01010101010101010101010101010101';\n    > var val = base.fromBinaryStringUint32( bstr )\n    1431655765\n    > bstr = '00000000000000000000000000000000';\n    > val = base.fromBinaryStringUint32( bstr )\n    0\n    > bstr = '00000000000000000000000000000010';\n    > val = base.fromBinaryStringUint32( bstr )\n    2\n    > bstr = '11111111111111111111111111111111';\n    > val = base.fromBinaryStringUint32( bstr )\n    4294967295\n\n    See Also\n    --------\n    base.fromBinaryStringUint16, base.toBinaryStringUint32, base.fromBinaryStringUint8\n","base.fromInt64Bytes":"\nbase.fromInt64Bytes( bytes, stride, offset )\n    Converts a signed 64-bit integer byte array to a double-precision floating-\n    point number.\n\n    The function assumes host byte order (endianness).\n\n    Parameters\n    ----------\n    bytes: Array<number>|TypedArray|Object\n        Byte array.\n\n    stride: integer\n        Index stride.\n\n    offset: integer\n        Index offset.\n\n    Returns\n    -------\n    out: number\n        Number.\n\n    Examples\n    --------\n    > var bytes = new Uint8Array( [ 255, 255, 255, 255, 255, 255, 255, 255 ] );\n    > var y = base.fromInt64Bytes( bytes, 1, 0 )\n    -1.0\n\n    See Also\n    --------\n    base.float64ToInt64Bytes","base.fromWordf":"\nbase.fromWordf( word )\n    Creates a single-precision floating-point number from an unsigned integer\n    corresponding to an IEEE 754 binary representation.\n\n    Parameters\n    ----------\n    word: integer\n        Unsigned integer.\n\n    Returns\n    -------\n    out: float\n        Single-precision floating-point number.\n\n    Examples\n    --------\n    > var word = 1068180177; // => 0 01111111 01010110010001011010001\n    > var f32 = base.fromWordf( word ) // when printed, promoted to float64\n    1.3370000123977661\n\n    See Also\n    --------\n    base.fromWords\n","base.fromWords":"\nbase.fromWords( high, low )\n    Creates a double-precision floating-point number from a higher order word\n    (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n\n    Parameters\n    ----------\n    high: integer\n        Higher order word (unsigned 32-bit integer).\n\n    low: integer\n        Lower order word (unsigned 32-bit integer).\n\n    Returns\n    -------\n    out: number\n        Double-precision floating-point number.\n\n    Examples\n    --------\n    > var v = base.fromWords( 1774486211, 2479577218 )\n    3.14e201\n    > v = base.fromWords( 3221823995, 1413754136 )\n    -3.141592653589793\n    > v = base.fromWords( 0, 0 )\n    0.0\n    > v = base.fromWords( 2147483648, 0 )\n    -0.0\n    > v = base.fromWords( 2146959360, 0 )\n    NaN\n    > v = base.fromWords( 2146435072, 0 )\n    Infinity\n    > v = base.fromWords( 4293918720, 0 )\n    -Infinity\n\n    See Also\n    --------\n    base.fromWordf\n","base.gamma":"\nbase.gamma( x )\n    Evaluates the gamma function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.gamma( 4.0 )\n    6.0\n    > y = base.gamma( -1.5 )\n    ~2.363\n    > y = base.gamma( -0.5 )\n    ~-3.545\n    > y = base.gamma( 0.5 )\n    ~1.772\n    > y = base.gamma( 0.0 )\n    Infinity\n    > y = base.gamma( -0.0 )\n    -Infinity\n    > y = base.gamma( NaN )\n    NaN\n\n    See Also\n    --------\n    base.gamma1pm1, base.gammainc, base.gammaincinv, base.gammaln\n","base.gamma1pm1":"\nbase.gamma1pm1( x )\n    Computes `gamma(x+1) - 1` without cancellation errors, where `gamma(x)` is\n    the gamma function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.gamma1pm1( 0.2 )\n    ~-0.082\n    > y = base.gamma1pm1( -6.7 )\n    ~-0.991\n    > y = base.gamma1pm1( 0.0 )\n    0.0\n    > y = base.gamma1pm1( NaN )\n    NaN\n\n    See Also\n    --------\n    base.gamma, base.gammainc, base.gammaincinv, base.gammaln\n","base.gammaDeltaRatio":"\nbase.gammaDeltaRatio( z, delta )\n    Computes the ratio of two gamma functions.\n\n    The ratio is defined as: Γ(z) / Γ(z+Δ).\n\n    Parameters\n    ----------\n    z: number\n        First gamma parameter.\n\n    delta: number\n        Difference.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.gammaDeltaRatio( 2.0, 3.0 )\n    ~0.042\n    > y = base.gammaDeltaRatio( 4.0, 0.5 )\n    ~0.516\n    > y = base.gammaDeltaRatio( 100.0, 0.0 )\n    1.0\n    > y = base.gammaDeltaRatio( NaN, 3.0 )\n    NaN\n    > y = base.gammaDeltaRatio( 5.0, NaN )\n    NaN\n    > y = base.gammaDeltaRatio( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.gamma\n","base.gammainc":"\nbase.gammainc( x, s[, regularized[, upper]] )\n    Computes the regularized incomplete gamma function.\n\n    The `regularized` and `upper` parameters specify whether to evaluate the\n    non-regularized and/or upper incomplete gamma functions, respectively.\n\n    If provided `x < 0` or `s <= 0`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        First function parameter.\n\n    s: number\n        Second function parameter.\n\n    regularized: boolean (optional)\n        Boolean indicating whether the function should evaluate the regularized\n        or non-regularized incomplete gamma function. Default: `true`.\n\n    upper: boolean (optional)\n        Boolean indicating whether the function should return the upper tail of\n        the incomplete gamma function. Default: `false`.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.gammainc( 6.0, 2.0 )\n    ~0.9826\n    > y = base.gammainc( 1.0, 2.0, true, true )\n    ~0.7358\n    > y = base.gammainc( 7.0, 5.0 )\n    ~0.8270\n    > y = base.gammainc( 7.0, 5.0, false )\n    ~19.8482\n    > y = base.gammainc( NaN, 2.0 )\n    NaN\n    > y = base.gammainc( 6.0, NaN )\n    NaN\n\n    See Also\n    --------\n    base.gamma, base.gamma1pm1, base.gammaincinv, base.gammaln\n","base.gammaincinv":"\nbase.gammaincinv( p, a[, upper] )\n    Computes the inverse of the lower incomplete gamma function.\n\n    In contrast to a more commonly used definition, the first argument is the\n    probability `p` and the second argument is the scale factor `a`.\n\n    By default, the function inverts the lower regularized incomplete gamma\n    function, `P(x,a)`. To invert the upper function `Q(x,a)`, set the `upper`\n    argument to `true`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Probability.\n\n    a: number\n        Scale parameter.\n\n    upper: boolean (optional)\n        Boolean indicating if the function should invert the upper tail of the\n        incomplete gamma function; i.e., compute `xr` such that `Q(a,xr) = p`.\n        Default: `false`.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.gammaincinv( 0.5, 2.0 )\n    ~1.678\n    > y = base.gammaincinv( 0.1, 10.0 )\n    ~6.221\n    > y = base.gammaincinv( 0.75, 3.0 )\n    ~3.92\n    > y = base.gammaincinv( 0.75, 3.0, true )\n    ~1.727\n    > y = base.gammaincinv( 0.75, NaN )\n    NaN\n    > y = base.gammaincinv( NaN, 3.0 )\n    NaN\n\n    See Also\n    --------\n    base.gamma, base.gamma1pm1, base.gammainc, base.gammaln\n","base.gammaLanczosSum":"\nbase.gammaLanczosSum( x )\n    Calculates the Lanczos sum for the approximation of the gamma function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Lanczos sum.\n\n    Examples\n    --------\n    > var y = base.gammaLanczosSum( 4.0 )\n    ~950.366\n    > y = base.gammaLanczosSum( -1.5 )\n    ~1373366.245\n    > y = base.gammaLanczosSum( -0.5 )\n    ~-699841.735\n    > y = base.gammaLanczosSum( 0.5 )\n    ~96074.186\n    > y = base.gammaLanczosSum( 0.0 )\n    Infinity\n    > y = base.gammaLanczosSum( NaN )\n    NaN\n\n    See Also\n    --------\n    base.gamma, base.gammaLanczosSumExpGScaled\n","base.gammaLanczosSumExpGScaled":"\nbase.gammaLanczosSumExpGScaled( x )\n    Calculates the scaled Lanczos sum for the approximation of the gamma\n    function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Scaled Lanczos sum.\n\n    Examples\n    --------\n    > var y = base.gammaLanczosSumExpGScaled( 4.0 )\n    ~0.018\n    > y = base.gammaLanczosSumExpGScaled( -1.5 )\n    ~25.337\n    > y = base.gammaLanczosSumExpGScaled( -0.5 )\n    ~-12.911\n    > y = base.gammaLanczosSumExpGScaled( 0.5 )\n    ~1.772\n    > y = base.gammaLanczosSumExpGScaled( 0.0 )\n    Infinity\n    > y = base.gammaLanczosSumExpGScaled( NaN )\n    NaN\n\n    See Also\n    --------\n    base.gamma, base.gammaLanczosSum\n","base.gammaln":"\nbase.gammaln( x )\n    Evaluates the natural logarithm of the gamma function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Natural logarithm of the gamma function.\n\n    Examples\n    --------\n    > var y = base.gammaln( 1.0 )\n    0.0\n    > y = base.gammaln( 2.0 )\n    0.0\n    > y = base.gammaln( 4.0 )\n    ~1.792\n    > y = base.gammaln( -0.5 )\n    ~1.266\n    > y = base.gammaln( 0.5 )\n    ~0.572\n    > y = base.gammaln( 0.0 )\n    Infinity\n    > y = base.gammaln( NaN )\n    NaN\n\n    See Also\n    --------\n    base.gamma, base.gammainc, base.gammaincinv\n","base.gammasgn":"\nbase.gammasgn( x )\n    Computes the sign of the gamma function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Sign of the gamma function.\n\n    Examples\n    --------\n    > var y = base.gammasgn( 1.0 )\n    1.0\n    > y = base.gammasgn( -2.5 )\n    -1.0\n    > y = base.gammasgn( 0.0 )\n    0.0\n    > y = base.gammasgn( NaN )\n    NaN\n\n    See Also\n    --------\n    base.gamma","base.gcd":"\nbase.gcd( a, b )\n    Computes the greatest common divisor (gcd).\n\n    If both `a` and `b` are `0`, the function returns `0`.\n\n    Both `a` and `b` must have integer values; otherwise, the function returns\n    `NaN`.\n\n    Parameters\n    ----------\n    a: integer\n        First number.\n\n    b: integer\n        Second number.\n\n    Returns\n    -------\n    out: integer\n        Greatest common divisor.\n\n    Examples\n    --------\n    > var v = base.gcd( 48, 18 )\n    6\n\n    See Also\n    --------\n    base.lcm\n","base.getHighWord":"\nbase.getHighWord( x )\n    Returns an unsigned 32-bit integer corresponding to the more significant 32\n    bits of a double-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    out: integer\n        Higher order word (unsigned 32-bit integer).\n\n    Examples\n    --------\n    > var w = base.getHighWord( 3.14e201 )\n    1774486211\n\n    See Also\n    --------\n    base.getLowWord, base.setHighWord\n","base.getLowWord":"\nbase.getLowWord( x )\n    Returns an unsigned 32-bit integer corresponding to the less significant 32\n    bits of a double-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    out: integer\n        Lower order word (unsigned 32-bit integer).\n\n    Examples\n    --------\n    > var w = base.getLowWord( 3.14e201 )\n    2479577218\n\n    See Also\n    --------\n    base.getHighWord, base.setHighWord\n","base.hacovercos":"\nbase.hacovercos( x )\n    Computes the half-value coversed cosine.\n\n    The half-value coversed cosine is defined as `(1 + sin(x)) / 2`.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Half-value coversed cosine.\n\n    Examples\n    --------\n    > var y = base.hacovercos( 3.14 )\n    ~0.5008\n    > y = base.hacovercos( -4.2 )\n    ~0.9358\n    > y = base.hacovercos( -4.6 )\n    ~0.9968\n    > y = base.hacovercos( 9.5 )\n    ~0.4624\n    > y = base.hacovercos( -0.0 )\n    0.5\n\n    See Also\n    --------\n    base.hacoversin, base.havercos\n","base.hacoversin":"\nbase.hacoversin( x )\n    Computes the half-value coversed sine.\n\n    The half-value coversed sine is defined as `(1 - sin(x)) / 2`.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Half-value coversed sine.\n\n    Examples\n    --------\n    > var y = base.hacoversin( 3.14 )\n    ~0.4992\n    > y = base.hacoversin( -4.2 )\n    ~0.0642\n    > y = base.hacoversin( -4.6 )\n    ~0.0032\n    > y = base.hacoversin( 9.5 )\n    ~0.538\n    > y = base.hacoversin( -0.0 )\n    0.5\n\n    See Also\n    --------\n    base.hacovercos, base.haversin\n","base.havercos":"\nbase.havercos( x )\n    Computes the half-value versed cosine.\n\n    The half-value versed cosine is defined as `(1 + cos(x)) / 2`.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Half-value versed cosine.\n\n    Examples\n    --------\n    > var y = base.havercos( 3.14 )\n    ~0.0\n    > y = base.havercos( -4.2 )\n    ~0.2549\n    > y = base.havercos( -4.6 )\n    ~0.4439\n    > y = base.havercos( 9.5 )\n    ~0.0014\n    > y = base.havercos( -0.0 )\n    1.0\n\n    See Also\n    --------\n    base.haversin, base.vercos\n","base.haversin":"\nbase.haversin( x )\n    Computes the half-value versed sine.\n\n    The half-value versed sine is defined as `(1 - cos(x)) / 2`.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Half-value versed sine.\n\n    Examples\n    --------\n    > var y = base.haversin( 3.14 )\n    ~1.0\n    > y = base.haversin( -4.2 )\n    ~0.7451\n    > y = base.haversin( -4.6 )\n    ~0.5561\n    > y = base.haversin( 9.5 )\n    ~0.9986\n    > y = base.haversin( -0.0 )\n    0.0\n\n    See Also\n    --------\n    base.havercos, base.versin\n","base.headercase":"\nbase.headercase( str )\n    Converts a string to HTTP header case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        HTTP header-cased string.\n\n    Examples\n    --------\n    > var out = base.headercase( 'Hello World!' )\n    'Hello-World'\n    > out = base.headercase( 'beep boop' )\n    'Beep-Boop'\n\n    See Also\n    --------\n    base.camelcase, base.pascalcase, base.uppercase","base.heaviside":"\nbase.heaviside( x[, continuity] )\n    Evaluates the Heaviside function.\n\n    The `continuity` parameter may be one of the following:\n\n    - 'half-maximum': if `x == 0`, the function returns `0.5`.\n    - 'left-continuous': if `x == 0`, the function returns `0`.\n    - 'right-continuous': if `x == 0`, the function returns `1`.\n\n    By default, if `x == 0`, the function returns `NaN` (i.e., the function is\n    discontinuous).\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    continuity: string (optional)\n        Specifies how to handle `x == 0`. By default, if `x == 0`, the function\n        returns `NaN`.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.heaviside( 3.14 )\n    1.0\n    > y = base.heaviside( -3.14 )\n    0.0\n    > y = base.heaviside( 0.0 )\n    NaN\n    > y = base.heaviside( 0.0, 'half-maximum' )\n    0.5\n    > y = base.heaviside( 0.0, 'left-continuous' )\n    0.0\n    > y = base.heaviside( 0.0, 'right-continuous' )\n    1.0\n\n    See Also\n    --------\n    base.ramp\n","base.hermitepoly":"\nbase.hermitepoly( n, x )\n    Evaluates a physicist's Hermite polynomial.\n\n    Parameters\n    ----------\n    n: integer\n        Nonnegative polynomial degree.\n\n    x: number\n        Value at which to evaluate the polynomial.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.hermitepoly( 1, 0.5 )\n    1.0\n    > y = base.hermitepoly( -1, 0.5 )\n    NaN\n    > y = base.hermitepoly( 0, 0.5 )\n    1.0\n    > y = base.hermitepoly( 2, 0.5 )\n    -1.0\n\n\nbase.hermitepoly.factory( n )\n    Returns a function for evaluating a physicist's Hermite polynomial.\n\n    Parameters\n    ----------\n    n: integer\n        Nonnegative polynomial degree.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a physicist's Hermite polynomial.\n\n    Examples\n    --------\n    > var polyval = base.hermitepoly.factory( 2 );\n    > var v = polyval( 0.5 )\n    -1.0\n\n    See Also\n    --------\n    base.evalpoly, base.normhermitepoly\n","base.hermitepoly.factory":"\nbase.hermitepoly.factory( n )\n    Returns a function for evaluating a physicist's Hermite polynomial.\n\n    Parameters\n    ----------\n    n: integer\n        Nonnegative polynomial degree.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a physicist's Hermite polynomial.\n\n    Examples\n    --------\n    > var polyval = base.hermitepoly.factory( 2 );\n    > var v = polyval( 0.5 )\n    -1.0\n\n    See Also\n    --------\n    base.evalpoly, base.normhermitepoly","base.hypot":"\nbase.hypot( x, y )\n    Computes the hypotenuse avoiding overflow and underflow.\n\n    If either argument is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Hypotenuse.\n\n    Examples\n    --------\n    > var h = base.hypot( -5.0, 12.0 )\n    13.0\n    > h = base.hypot( NaN, 12.0 )\n    NaN\n    > h = base.hypot( -0.0, -0.0 )\n    0.0\n\n","base.hypotf":"\nbase.hypotf( x, y )\n    Computes the hypotenuse avoiding overflow and underflow (single-precision).\n\n    If either argument is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Hypotenuse.\n\n    Examples\n    --------\n    > var h = base.hypotf( -5.0, 12.0 )\n    13.0\n    > h = base.hypotf( NaN, 12.0 )\n    NaN\n    > h = base.hypotf( -0.0, -0.0 )\n    0.0\n\n    See Also\n    --------\n    base.hypot\n","base.identity":"\nbase.identity( x )\n    Evaluates the identity function for a double-precision floating-point number\n    `x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Input value.\n\n    Examples\n    --------\n    > var y = base.identity( -1.0 )\n    -1.0\n    > y = base.identity( 2.0 )\n    2.0\n    > y = base.identity( 0.0 )\n    0.0\n    > y = base.identity( -0.0 )\n    -0.0\n    > y = base.identity( NaN )\n    NaN\n\n","base.identityf":"\nbase.identityf( x )\n    Evaluates the identity function for a single-precision floating-point number\n    `x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Input value.\n\n    Examples\n    --------\n    > var y = base.identityf( -1.0 )\n    -1.0\n    > y = base.identityf( 2.0 )\n    2.0\n    > y = base.identityf( 0.0 )\n    0.0\n    > y = base.identityf( -0.0 )\n    -0.0\n    > y = base.identityf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.identityf\n","base.imul":"\nbase.imul( a, b )\n    Performs C-like multiplication of two signed 32-bit integers.\n\n    Parameters\n    ----------\n    a: integer\n        Signed 32-bit integer.\n\n    b: integer\n        Signed 32-bit integer.\n\n    Returns\n    -------\n    out: integer\n        Product.\n\n    Examples\n    --------\n    > var v = base.imul( -10|0, 4|0 )\n    -40\n\n    See Also\n    --------\n    base.imuldw\n","base.imuldw":"\nbase.imuldw( a, b )\n    Multiplies two signed 32-bit integers and returns an array of two signed 32-\n    bit integers which represents the signed 64-bit integer product.\n\n    When computing the product of 32-bit integer values in double-precision\n    floating-point format (the default JavaScript numeric data type), computing\n    the double word product is necessary in order to avoid exceeding the maximum\n    safe double-precision floating-point integer value.\n\n    Parameters\n    ----------\n    a: integer\n        Signed 32-bit integer.\n\n    b: integer\n        Signed 32-bit integer.\n\n    Returns\n    -------\n    out: Array<number>\n        Double word product (in big endian order; i.e., the first element\n        corresponds to the most significant bits and the second element to the\n        least significant bits).\n\n    Examples\n    --------\n    > var v = base.imuldw( 1, 10 )\n    [ 0, 10 ]\n\n\nbase.imuldw.assign( a, b, out, stride, offset )\n    Multiplies two signed 32-bit integers and assigns results representing the\n    signed 64-bit integer product to a provided output array.\n\n    When computing the product of 32-bit integer values in double-precision\n    floating-point format (the default JavaScript numeric data type), computing\n    the double word product is necessary in order to avoid exceeding the maximum\n    safe double-precision floating-point integer value.\n\n    Parameters\n    ----------\n    a: integer\n        Signed 32-bit integer.\n\n    b: integer\n        Signed 32-bit integer.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Double word product (in big endian order; i.e., the first element\n        corresponds to the most significant bits and the second element to the\n        least significant bits).\n\n    Examples\n    --------\n    > var out = [ 0, 0 ];\n    > var v = base.imuldw.assign( 1, 10, out, 1, 0 )\n    [ 0, 10 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.imul","base.imuldw.assign":"\nbase.imuldw.assign( a, b, out, stride, offset )\n    Multiplies two signed 32-bit integers and assigns results representing the\n    signed 64-bit integer product to a provided output array.\n\n    When computing the product of 32-bit integer values in double-precision\n    floating-point format (the default JavaScript numeric data type), computing\n    the double word product is necessary in order to avoid exceeding the maximum\n    safe double-precision floating-point integer value.\n\n    Parameters\n    ----------\n    a: integer\n        Signed 32-bit integer.\n\n    b: integer\n        Signed 32-bit integer.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Double word product (in big endian order; i.e., the first element\n        corresponds to the most significant bits and the second element to the\n        least significant bits).\n\n    Examples\n    --------\n    > var out = [ 0, 0 ];\n    > var v = base.imuldw.assign( 1, 10, out, 1, 0 )\n    [ 0, 10 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.imul","base.int2slice":"\nbase.int2slice( value, max, strict )\n    Converts an integer to a Slice object.\n\n    In strict mode, the function returns an error object if an input value\n    exceeds index bounds.\n\n    A returned error object is a plain object having the following properties:\n\n    - code: error code.\n\n    A returned error object may have one of the following error codes:\n\n    - ERR_SLICE_OUT_OF_BOUNDS: a slice exceeds index bounds.\n\n    Parameters\n    ----------\n    value: integer\n        Input value.\n\n    max: integer\n        Index upper bound (exclusive).\n\n    strict: boolean\n        Boolean indicating whether to enforce strict bounds checking.\n\n    Returns\n    -------\n    s: Slice|Object\n        Slice instance (or an error object).\n\n    Examples\n    --------\n    > var s = base.int2slice( -1, 5, false );\n    > s.start\n    4\n    > s.stop\n    5\n    > s.step\n    1\n\n    See Also\n    --------\n    base.seq2slice, base.str2slice\n","base.int32ToUint32":"\nbase.int32ToUint32( x )\n    Converts a signed 32-bit integer to an unsigned 32-bit integer.\n\n    Parameters\n    ----------\n    x: integer\n        Signed 32-bit integer.\n\n    Returns\n    -------\n    out: integer\n        Unsigned 32-bit integer.\n\n    Examples\n    --------\n    > var y = base.int32ToUint32( base.float64ToInt32( -32 ) )\n    4294967264\n    > y = base.int32ToUint32( base.float64ToInt32( 3 ) )\n    3\n\n    See Also\n    --------\n    base.uint32ToInt32\n","base.inv":"\nbase.inv( x )\n    Computes the multiplicative inverse of a double-precision floating-point\n    number `x`.\n\n    The multiplicative inverse is defined as `1/x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Multiplicative inverse.\n\n    Examples\n    --------\n    > var y = base.inv( -1.0 )\n    -1.0\n    > y = base.inv( 2.0 )\n    0.5\n    > y = base.inv( 0.0 )\n    Infinity\n    > y = base.inv( -0.0 )\n    -Infinity\n    > y = base.inv( NaN )\n    NaN\n\n    See Also\n    --------\n    base.pow\n","base.invcase":"\nbase.invcase( str )\n    Converts a string to inverse case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Inverse-cased string.\n\n    Examples\n    --------\n    > var out = base.invcase( 'Hello World!' )\n    'hELLO wORLD!'\n    > out = base.invcase( 'I am A tiny LITTLE teapot' )\n    'i AM a TINY little TEAPOT'\n\n    See Also\n    --------\n    base.lowercase, base.uppercase","base.invf":"\nbase.invf( x )\n    Computes the multiplicative inverse of a single-precision floating-point\n    number `x`.\n\n    The multiplicative inverse is defined as `1/x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Multiplicative inverse.\n\n    Examples\n    --------\n    > var y = base.invf( -1.0 )\n    -1.0\n    > y = base.invf( 2.0 )\n    0.5\n    > y = base.invf( 0.0 )\n    Infinity\n    > y = base.invf( -0.0 )\n    -Infinity\n    > y = base.invf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.inv\n","base.isComposite":"\nbase.isComposite( x )\n    Tests if a number is composite.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is a composite number.\n\n    Examples\n    --------\n    > var bool = base.isComposite( 10.0 )\n    true\n    > bool = base.isComposite( 11.0 )\n    false\n\n    See Also\n    --------\n    base.isInteger, base.isPrime\n","base.isCoprime":"\nbase.isCoprime( a, b )\n    Tests if two numbers are coprime.\n\n    Parameters\n    ----------\n    a: number\n        First value.\n\n    b: number\n        Second value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the values are coprime.\n\n    Examples\n    --------\n    > var bool = base.isCoprime( 14.0, 15.0 )\n    true\n    > bool = base.isCoprime( 14.0, 21.0 )\n    false\n\n    See Also\n    --------\n    base.isComposite, base.isPrime, base.gcd\n","base.isEven":"\nbase.isEven( x )\n    Tests if a finite numeric value is an even number.\n\n    The function assumes a finite number. If provided positive or negative\n    infinity, the function will return `true`, when, in fact, the result is\n    undefined.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is an even number.\n\n    Examples\n    --------\n    > var bool = base.isEven( 5.0 )\n    false\n    > bool = base.isEven( -2.0 )\n    true\n    > bool = base.isEven( 0.0 )\n    true\n    > bool = base.isEven( NaN )\n    false\n\n    See Also\n    --------\n    base.isOdd\n","base.isEvenInt32":"\nbase.isEvenInt32( x )\n    Tests if a 32-bit integer is even.\n\n    Parameters\n    ----------\n    x: integer\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is an even number.\n\n    Examples\n    --------\n    > var bool = base.isEvenInt32( 5 )\n    false\n    > bool = base.isEvenInt32( -2 )\n    true\n    > bool = base.isEvenInt32( 0 )\n    true\n\n    See Also\n    --------\n    base.isEven, base.isOddInt32\n","base.isFinite":"\nbase.isFinite( x )\n    Tests if a double-precision floating-point numeric value is finite.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is finite.\n\n    Examples\n    --------\n    > var bool = base.isFinite( 5.0 )\n    true\n    > bool = base.isFinite( -2.0e64 )\n    true\n    > bool = base.isFinite( PINF )\n    false\n    > bool = base.isFinite( NINF )\n    false\n\n    See Also\n    --------\n    base.isInfinite\n","base.isFinitef":"\nbase.isFinitef( x )\n    Tests if a single-precision floating-point numeric value is finite.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is finite.\n\n    Examples\n    --------\n    > var bool = base.isFinitef( 5.0 )\n    true\n    > bool = base.isFinitef( -1.0e38 )\n    true\n    > bool = base.isFinitef( FLOAT32_PINF )\n    false\n    > bool = base.isFinitef( FLOAT32_NINF )\n    false\n\n    See Also\n    --------\n    base.isInfinitef\n","base.isInfinite":"\nbase.isInfinite( x )\n    Tests if a double-precision floating-point numeric value is infinite.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is infinite.\n\n    Examples\n    --------\n    > var bool = base.isInfinite( PINF )\n    true\n    > bool = base.isInfinite( NINF )\n    true\n    > bool = base.isInfinite( 5.0 )\n    false\n    > bool = base.isInfinite( NaN )\n    false\n\n    See Also\n    --------\n    base.isFinite\n","base.isInfinitef":"\nbase.isInfinitef( x )\n    Tests if a single-precision floating-point numeric value is infinite.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is infinite.\n\n    Examples\n    --------\n    > var bool = base.isInfinitef( FLOAT32_PINF )\n    true\n    > bool = base.isInfinitef( FLOAT32_NINF )\n    true\n    > bool = base.isInfinitef( 5.0 )\n    false\n    > bool = base.isInfinitef( NaN )\n    false\n\n    See Also\n    --------\n    base.isFinitef\n","base.isInteger":"\nbase.isInteger( x )\n    Tests if a finite double-precision floating-point number is an integer.\n\n    The function assumes a finite number. If provided positive or negative\n    infinity, the function will return `true`, when, in fact, the result is\n    undefined.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is an integer.\n\n    Examples\n    --------\n    > var bool = base.isInteger( 1.0 )\n    true\n    > bool = base.isInteger( 3.14 )\n    false\n\n","base.isnan":"\nbase.isnan( x )\n     Tests if a double-precision floating-point numeric value is `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is `NaN`.\n\n    Examples\n    --------\n    > var bool = base.isnan( NaN )\n    true\n    > bool = base.isnan( 7.0 )\n    false\n\n    See Also\n    --------\n    base.isnanf\n","base.isnanf":"\nbase.isnanf( x )\n     Tests if a single-precision floating-point numeric value is `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is `NaN`.\n\n    Examples\n    --------\n    > var bool = base.isnanf( NaN )\n    true\n    > bool = base.isnanf( 7.0 )\n    false\n\n    See Also\n    --------\n    base.isnan\n","base.isNegativeFinite":"\nbase.isNegativeFinite( x )\n    Tests if a double-precision floating-point numeric value is a negative\n    finite number.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether the value is a negative finite number.\n\n    Examples\n    --------\n    > var bool = base.isNegativeFinite( -3.14 )\n    true\n    > bool = base.isNegativeFinite( -Infinity )\n    false\n    > bool = base.isNegativeFinite( 2.0 )\n    false\n    > bool = base.isNegativeFinite( NaN )\n    false\n    > bool = base.isNegativeFinite( -0.0 )\n    false\n\n    See Also\n    --------\n    base.isPositiveFinite, base.isNonNegativeFinite, base.isNonPositiveFinite\n","base.isNegativeInteger":"\nbase.isNegativeInteger( x )\n    Tests if a finite double-precision floating-point number is a negative\n    integer.\n\n    The function assumes a finite number. If provided negative infinity, the\n    function will return `true`, when, in fact, the result is undefined.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is a negative integer.\n\n    Examples\n    --------\n    > var bool = base.isNegativeInteger( -1.0 )\n    true\n    > bool = base.isNegativeInteger( 0.0 )\n    false\n    > bool = base.isNegativeInteger( 10.0 )\n    false\n\n    See Also\n    --------\n    base.isInteger, base.isNonNegativeInteger, base.isNonPositiveInteger, base.isPositiveInteger\n","base.isNegativeZero":"\nbase.isNegativeZero( x )\n    Tests if a double-precision floating-point numeric value is negative zero.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is negative zero.\n\n    Examples\n    --------\n    > var bool = base.isNegativeZero( -0.0 )\n    true\n    > bool = base.isNegativeZero( 0.0 )\n    false\n\n    See Also\n    --------\n    base.isPositiveZero\n","base.isNegativeZerof":"\nbase.isNegativeZerof( x )\n    Tests if a single-precision floating-point numeric value is negative zero.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is negative zero.\n\n    Examples\n    --------\n    > var bool = base.isNegativeZerof( -0.0 )\n    true\n    > bool = base.isNegativeZerof( 0.0 )\n    false\n\n    See Also\n    --------\n    base.isNegativeZero, base.isPositiveZerof\n","base.isNonNegativeFinite":"\nbase.isNonNegativeFinite( x )\n    Tests if a double-precision floating-point numeric value is a nonnegative\n    finite number.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is a nonnegative finite number.\n\n    Examples\n    --------\n    > var out = base.isNonNegativeFinite( 5.0 )\n    true\n    > out = base.isNonNegativeFinite( 3.14 )\n    true\n    > out = base.isNonNegativeFinite( 0.0 )\n    true\n    > out = base.isNonNegativeFinite( Infinity )\n    false\n    > out = base.isNonNegativeFinite( -3.14 )\n    false\n    > out = base.isNonNegativeFinite( NaN )\n    false\n\n    See Also\n    --------\n    base.isNegativeFinite, base.isPositiveFinite, base.isNonPositiveFinite\n","base.isNonNegativeInteger":"\nbase.isNonNegativeInteger( x )\n    Tests if a finite double-precision floating-point number is a nonnegative\n    integer.\n\n    The function assumes a finite number. If provided positive infinity, the\n    function will return `true`, when, in fact, the result is undefined.\n\n    The function does not distinguish between positive and negative zero.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is a nonnegative integer.\n\n    Examples\n    --------\n    > var bool = base.isNonNegativeInteger( 1.0 )\n    true\n    > bool = base.isNonNegativeInteger( 0.0 )\n    true\n    > bool = base.isNonNegativeInteger( -10.0 )\n    false\n\n    See Also\n    --------\n    base.isInteger, base.isNegativeInteger, base.isNonPositiveInteger, base.isPositiveInteger\n","base.isNonPositiveFinite":"\nbase.isNonPositiveFinite( x )\n    Tests if a double-precision floating-point numeric value is a nonpositive\n    finite number.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether the value is a nonpositive finite number.\n\n    Examples\n    --------\n    > var bool = base.isNonPositiveFinite( -3.14 )\n    true\n    > var bool = base.isNonPositiveFinite( 0.0 )\n    true\n    > var bool = base.isNonPositiveFinite( -Infinity )\n    false\n    > var bool = base.isNonPositiveFinite( 3.14 )\n    false\n    > var bool = base.isNonPositiveFinite( NaN )\n    false\n\n    See Also\n    --------\n    base.isNegativeFinite, base.isPositiveFinite, base.isNonNegativeFinite\n","base.isNonPositiveInteger":"\nbase.isNonPositiveInteger( x )\n    Tests if a finite double-precision floating-point number is a nonpositive\n    integer.\n\n    The function assumes a finite number. If provided negative infinity, the\n    function will return `true`, when, in fact, the result is undefined.\n\n    The function does not distinguish between positive and negative zero.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is a nonpositive integer.\n\n    Examples\n    --------\n    > var bool = base.isNonPositiveInteger( -1.0 )\n    true\n    > bool = base.isNonPositiveInteger( 0.0 )\n    true\n    > bool = base.isNonPositiveInteger( 10.0 )\n    false\n\n    See Also\n    --------\n    base.isInteger, base.isNegativeInteger, base.isNonNegativeInteger, base.isPositiveInteger\n","base.isOdd":"\nbase.isOdd( x )\n    Tests if a finite numeric value is an odd number.\n\n    The function assumes a finite number. If provided positive or negative\n    infinity, the function will return `true`, when, in fact, the result is\n    undefined.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is an odd number.\n\n    Examples\n    --------\n    > var bool = base.isOdd( 5.0 )\n    true\n    > bool = base.isOdd( -2.0 )\n    false\n    > bool = base.isOdd( 0.0 )\n    false\n    > bool = base.isOdd( NaN )\n    false\n\n    See Also\n    --------\n    base.isEven\n","base.isOddInt32":"\nbase.isOddInt32( x )\n    Tests if a 32-bit integer is odd.\n\n    Parameters\n    ----------\n    x: integer\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is an odd number.\n\n    Examples\n    --------\n    > var bool = base.isOddInt32( 5 )\n    true\n    > bool = base.isOddInt32( -2 )\n    false\n    > bool = base.isOddInt32( 0 )\n    false\n\n    See Also\n    --------\n    base.isEvenInt32, base.isOdd\n","base.isPositiveFinite":"\nbase.isPositiveFinite( x )\n    Tests if a double-precision floating-point numeric value is a positive\n    finite number.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is a positive finite number.\n\n    Examples\n    --------\n    > var bool = base.isPositiveFinite( 5.0 )\n    true\n    > bool = base.isPositiveFinite( 3.14 )\n    true\n    > bool = base.isPositiveFinite( 0.0 )\n    false\n    > bool = base.isPositiveFinite( Infinity )\n    false\n    > bool = base.isPositiveFinite( -3.14 )\n    false\n    > bool = base.isPositiveFinite( NaN )\n    false\n\n    See Also\n    --------\n    base.isNegativeFinite, base.isNonNegativeFinite, base.isNonPositiveFinite\n","base.isPositiveInteger":"\nbase.isPositiveInteger( x )\n    Tests if a finite double-precision floating-point number is a positive\n    integer.\n\n    The function assumes a finite number. If provided positive infinity, the\n    function will return `true`, when, in fact, the result is undefined.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is a positive integer.\n\n    Examples\n    --------\n    > var bool = base.isPositiveInteger( 1.0 )\n    true\n    > bool = base.isPositiveInteger( 0.0 )\n    false\n    > bool = base.isPositiveInteger( -10.0 )\n    false\n\n    See Also\n    --------\n    base.isInteger, base.isNegativeInteger, base.isNonNegativeInteger, base.isNonPositiveInteger\n","base.isPositiveZero":"\nbase.isPositiveZero( x )\n    Tests if a double-precision floating-point numeric value is positive zero.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is positive zero.\n\n    Examples\n    --------\n    > var bool = base.isPositiveZero( 0.0 )\n    true\n    > bool = base.isPositiveZero( -0.0 )\n    false\n\n    See Also\n    --------\n    base.isNegativeZero\n","base.isPositiveZerof":"\nbase.isPositiveZerof( x )\n    Tests if a single-precision floating-point numeric value is positive zero.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is positive zero.\n\n    Examples\n    --------\n    > var bool = base.isPositiveZerof( 0.0 )\n    true\n    > bool = base.isPositiveZerof( -0.0 )\n    false\n\n    See Also\n    --------\n    base.isNegativeZerof, base.isPositiveZero\n","base.isPow2Uint32":"\nbase.isPow2Uint32( x )\n    Tests whether an unsigned integer is a power of 2.\n\n    Parameters\n    ----------\n    x: integer\n        Unsigned integer.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is a power of 2.\n\n    Examples\n    --------\n    > var bool = base.isPow2Uint32( 2 )\n    true\n    > bool = base.isPow2Uint32( 5 )\n    false\n\n","base.isPrime":"\nbase.isPrime( x )\n    Tests if a number is prime.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is a prime number.\n\n    Examples\n    --------\n    > var bool = base.isPrime( 11.0 )\n    true\n    > bool = base.isPrime( 3.14 )\n    false\n\n    See Also\n    --------\n    base.isComposite, base.isInteger\n","base.isProbability":"\nbase.isProbability( x )\n    Tests if a double-precision floating-point number value is a probability.\n\n    A probability is defined as a number on the closed interval [0,1].\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is a probability.\n\n    Examples\n    --------\n    > var bool = base.isProbability( 0.5 )\n    true\n    > bool = base.isProbability( 3.14 )\n    false\n    > bool = base.isProbability( NaN )\n    false\n\n","base.isSafeInteger":"\nbase.isSafeInteger( x )\n    Tests if a finite double-precision floating-point number is a safe integer.\n\n    An integer valued number is \"safe\" when the number can be exactly\n    represented as a double-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is a safe integer.\n\n    Examples\n    --------\n    > var bool = base.isSafeInteger( 1.0 )\n    true\n    > bool = base.isSafeInteger( 2.0e200 )\n    false\n    > bool = base.isSafeInteger( 3.14 )\n    false\n\n","base.kebabcase":"\nbase.kebabcase( str )\n    Converts a string to kebab case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Kebab-cased string.\n\n    Examples\n    --------\n    > var out = base.kebabcase( 'Hello World!' )\n    'hello-world'\n    > out = base.kebabcase( 'I am a tiny little teapot' )\n    'i-am-a-tiny-little-teapot'\n\n    See Also\n    --------\n    base.camelcase, base.lowercase, base.pascalcase, base.snakecase, base.uppercase","base.kernelBetainc":"\nbase.kernelBetainc( x, a, b, regularized, upper )\n    Computes the kernel function for the regularized incomplete beta function.\n\n    The `regularized` and `upper` parameters specify whether to evaluate the\n    non-regularized and/or upper incomplete beta functions, respectively.\n\n    If provided `x < 0` or `x > 1`, the function returns `[ NaN, NaN ]`.\n\n    If provided `a < 0` or `b < 0`, the function returns `[ NaN, NaN ]`.\n\n    If provided `NaN` for `x`, `a`, or `b`, the function returns `[ NaN, NaN ]`.\n\n    Parameters\n    ----------\n    x: number\n        First function parameter.\n\n    a: number\n        Second function parameter.\n\n    b: number\n        Third function parameter.\n\n    regularized: boolean\n        Boolean indicating whether the function should evaluate the regularized\n        or non-regularized incomplete beta function.\n\n    upper: boolean\n        Boolean indicating whether the function should return the upper tail of\n        the incomplete beta function.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Function value and first derivative.\n\n    Examples\n    --------\n    > var out = base.kernelBetainc( 0.8, 1.0, 0.3, false, false )\n    [ ~1.277, ~0.926 ]\n    > out = base.kernelBetainc( 0.2, 1.0, 2.0, true, false )\n    [ 0.36, 1.6 ]\n\n\nbase.kernelBetainc.assign( x, a, b, regularized, upper, out, stride, offset )\n    Computes the kernel function for the regularized incomplete beta function.\n\n    The `regularized` and `upper` parameters specify whether to evaluate the\n    non-regularized and/or upper incomplete beta functions, respectively.\n\n    If provided `x < 0` or `x > 1`, the function returns `[ NaN, NaN ]`.\n\n    If provided `a < 0` or `b < 0`, the function returns `[ NaN, NaN ]`.\n\n    If provided `NaN` for `x`, `a`, or `b`, the function returns `[ NaN, NaN ]`.\n\n    Parameters\n    ----------\n    x: number\n        First function parameter.\n\n    a: number\n        Second function parameter.\n\n    b: number\n        Third function parameter.\n\n    regularized: boolean\n        Boolean indicating whether the function should evaluate the regularized\n        or non-regularized incomplete beta function.\n\n    upper: boolean\n        Boolean indicating whether the function should return the upper tail of\n        the incomplete beta function.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Function value and first derivative.\n\n    Examples\n    --------\n    > var out = [ 0.0, 0.0 ];\n    > var v = base.kernelBetainc.assign( 0.2, 1.0, 2.0, true, true, out, 1, 0 )\n    [ 0.64, 1.6 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.betainc\n","base.kernelBetainc.assign":"\nbase.kernelBetainc.assign( x, a, b, regularized, upper, out, stride, offset )\n    Computes the kernel function for the regularized incomplete beta function.\n\n    The `regularized` and `upper` parameters specify whether to evaluate the\n    non-regularized and/or upper incomplete beta functions, respectively.\n\n    If provided `x < 0` or `x > 1`, the function returns `[ NaN, NaN ]`.\n\n    If provided `a < 0` or `b < 0`, the function returns `[ NaN, NaN ]`.\n\n    If provided `NaN` for `x`, `a`, or `b`, the function returns `[ NaN, NaN ]`.\n\n    Parameters\n    ----------\n    x: number\n        First function parameter.\n\n    a: number\n        Second function parameter.\n\n    b: number\n        Third function parameter.\n\n    regularized: boolean\n        Boolean indicating whether the function should evaluate the regularized\n        or non-regularized incomplete beta function.\n\n    upper: boolean\n        Boolean indicating whether the function should return the upper tail of\n        the incomplete beta function.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Function value and first derivative.\n\n    Examples\n    --------\n    > var out = [ 0.0, 0.0 ];\n    > var v = base.kernelBetainc.assign( 0.2, 1.0, 2.0, true, true, out, 1, 0 )\n    [ 0.64, 1.6 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.betainc","base.kernelBetaincinv":"\nbase.kernelBetaincinv( a, b, p, q )\n    Computes the inverse of the lower incomplete beta function.\n\n    Probabilities `p` and `q` must satisfy `p = 1 - q`.\n\n    Parameters\n    ----------\n    a: number\n        First function parameter (a positive number).\n\n    b: number\n        Second function parameter (a positive number).\n\n    p: number\n        Probability.\n\n    q: number\n        Probability equal to `1-p`.\n\n    Returns\n    -------\n    out: Array\n        Two-element array holding function value `y` and `1-y`.\n\n    Examples\n    --------\n    > var y = base.kernelBetaincinv( 3.0, 3.0, 0.2, 0.8 )\n    [ ~0.327, ~0.673 ]\n    > y = base.kernelBetaincinv( 3.0, 3.0, 0.4, 0.6 )\n    [ ~0.446, ~0.554 ]\n    > y = base.kernelBetaincinv( 1.0, 6.0, 0.4, 0.6 )\n    [ ~0.082, ~0.918 ]\n    > y = base.kernelBetaincinv( 1.0, 6.0, 0.8, 0.2 )\n    [ ~0.235, ~0.765 ]\n\n    See Also\n    --------\n    base.betaincinv\n","base.kernelCos":"\nbase.kernelCos( x, y )\n    Computes the cosine of a double-precision floating-point number on the\n    interval [-π/4, π/4].\n\n    For increased accuracy, the number for which the cosine should be evaluated\n    can be supplied as a double-double number (i.e., a non-evaluated sum of two\n    double-precision floating-point numbers `x` and `y`).\n\n    The two numbers must satisfy `|y| < 0.5 * ulp( x )`.\n\n    If either argument is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    y: number\n        Tail of `x`.\n\n    Returns\n    -------\n    out: number\n        Cosine.\n\n    Examples\n    --------\n    > var out = base.kernelCos( 0.0, 0.0 )\n    ~1.0\n    > out = base.kernelCos( PI/6.0, 0.0 )\n    ~0.866\n    > out = base.kernelCos( 0.785, -1.144e-17 )\n    ~0.707\n    > out = base.kernelCos( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cos, base.kernelSin, base.kernelTan\n","base.kernelLog1p":"\nbase.kernelLog1p( f )\n    Computes `log(1+f) - f` for `1+f` in ~[sqrt(2)/2, sqrt(2)].\n\n    This function provides a common means for computing logarithms in base e.\n    Argument reduction and adding the final term of the polynomial must be done\n    by the caller for increased accuracy when different bases are used.\n\n    Parameters\n    ----------\n    f: number\n        Input value.\n\n    Returns\n    -------\n    out: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.kernelLog1p( 1.0 )\n    ~0.1931\n    > y = base.kernelLog1p( 1.4142135623730951 )\n    ~0.4672\n    > y = base.kernelLog1p( NaN )\n    NaN\n\n    See Also\n    --------\n    base.log1p\n","base.kernelSin":"\nbase.kernelSin( x, y )\n    Computes the sine of a double-precision floating-point number on [-π/4,π/4].\n\n    For increased accuracy, the number for which the cosine should be evaluated\n    can be supplied as a double-double number (i.e., a non-evaluated sum of two\n    double-precision floating-point numbers `x` and `y`).\n\n    The two numbers must satisfy `|y| < 0.5 * ulp( x )`.\n\n    If either argument is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    y: number\n        Tail of `x`.\n\n    Returns\n    -------\n    out: number\n        Sine.\n\n    Examples\n    --------\n    > var y = base.kernelSin( 0.0, 0.0 )\n    ~0.0\n    > y = base.kernelSin( PI/6.0, 0.0 )\n    ~0.5\n    > y = base.kernelSin( 0.619, 9.279e-18 )\n    ~0.58\n\n    > y = base.kernelSin( NaN, 0.0 )\n    NaN\n    > y = base.kernelSin( 2.0, NaN )\n    NaN\n    > y = base.kernelSin( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.kernelCos, base.kernelTan, base.sin\n","base.kernelTan":"\nbase.kernelTan( x, y, k )\n    Computes the tangent of a double-precision floating-point number on the\n    interval [-π/4, π/4].\n\n    For increased accuracy, the number for which the tangent should be evaluated\n    can be supplied as a double-double number (i.e., a non-evaluated sum of two\n    double-precision floating-point numbers `x` and `y`).\n\n    The numbers `x` and `y` must satisfy `|y| < 0.5 * ulp( x )`.\n\n    If either `x` or `y` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    y: number\n        Tail of `x`.\n\n    k: integer\n        If `k=1`, the function returns `tan(x+y)`. If `k=-1`, the function\n        returns the negative inverse `-1/tan(x+y)`.\n\n    Returns\n    -------\n    out: number\n        Tangent.\n\n    Examples\n    --------\n    > var out = base.kernelTan( PI/4.0, 0.0, 1 )\n    ~1.0\n    > out = base.kernelTan( PI/4.0, 0.0, -1 )\n    ~-1.0\n    > out = base.kernelTan( PI/6.0, 0.0, 1 )\n    ~0.577\n    > out = base.kernelTan( 0.664, 5.288e-17, 1 )\n    ~0.783\n\n    > out = base.kernelTan( NaN, 0.0, 1 )\n    NaN\n    > out = base.kernelTan( 3.0, NaN, 1 )\n    NaN\n    > out = base.kernelTan( 3.0, 0.0, NaN )\n    NaN\n\n    See Also\n    --------\n    base.kernelCos, base.kernelSin, base.tan\n","base.kroneckerDelta":"\nbase.kroneckerDelta( i, j )\n    Evaluates the Kronecker delta.\n\n    If `i == j`, the function returns `1`; otherwise, the function returns zero.\n\n    Parameters\n    ----------\n    i: number\n        Input value.\n\n    j: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.kroneckerDelta( 3.14, 0.0 )\n    0.0\n    > y = base.kroneckerDelta( 3.14, 3.14 )\n    1.0\n\n    See Also\n    --------\n    base.diracDelta\n","base.kroneckerDeltaf":"\nbase.kroneckerDeltaf( i, j )\n    Evaluates the Kronecker delta (single-precision).\n\n    If `i == j`, the function returns `1`; otherwise, the function returns zero.\n\n    Parameters\n    ----------\n    i: number\n        Input value.\n\n    j: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.kroneckerDeltaf( 3.14, 0.0 )\n    0.0\n    > y = base.kroneckerDeltaf( 3.14, 3.14 )\n    1.0\n\n    See Also\n    --------\n    base.kroneckerDelta\n","base.labs":"\nbase.labs( x )\n    Computes an absolute value of a signed 32-bit integer in two's complement\n    format.\n\n    Parameters\n    ----------\n    x: integer\n        Signed 32-bit integer.\n\n    Returns\n    -------\n    out: integer\n        Absolute value.\n\n    Examples\n    --------\n    > var v = base.labs( -1|0 )\n    1\n    > v = base.labs( 2|0 )\n    2\n    > v = base.labs( 0|0 )\n    0\n\n    See Also\n    --------\n    base.abs\n","base.last":"\nbase.last( str, n )\n    Returns the last `n` UTF-16 code units of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of UTF-16 code units to return.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.last( 'hello', 1 )\n    'o'\n    > out = base.last( 'JavaScript', 6 )\n    'Script'\n    > out = base.last( 'foo bar', 10 )\n    'foo bar'\n\n    See Also\n    --------\n    base.firstCodeUnit, base.lastCodePoint, base.lastGraphemeCluster\n","base.lastCodePoint":"\nbase.lastCodePoint( str, n )\n    Returns the last `n` Unicode code points of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of Unicode code points to return.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.lastCodePoint( 'hello world', 1 )\n    'd'\n    > out = base.lastCodePoint( 'JavaScript', 6 )\n    'Script'\n    > out = base.lastCodePoint( 'अनुच्छेद', 1 )\n    'द'\n\n    See Also\n    --------\n    base.firstCodePoint, base.lastGraphemeCluster, base.last\n","base.lastGraphemeCluster":"\nbase.lastGraphemeCluster( str, n )\n    Returns the last `n` grapheme clusters (i.e., user-perceived characters) of\n    a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of grapheme clusters to return.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.lastGraphemeCluster( 'beep', 1 )\n    'p'\n    > out = base.lastGraphemeCluster( 'Boop', 2 )\n    'op'\n    > out = base.lastGraphemeCluster( 'JavaScript', 6 )\n    'Script'\n\n    See Also\n    --------\n    base.firstGraphemeCluster, base.lastCodePoint, base.last\n","base.lcm":"\nbase.lcm( a, b )\n    Computes the least common multiple (lcm).\n\n    If either `a` or `b` is `0`, the function returns `0`.\n\n    Both `a` and `b` must have integer values; otherwise, the function returns\n    `NaN`.\n\n    Parameters\n    ----------\n    a: integer\n        First integer.\n\n    b: integer\n        Second integer.\n\n    Returns\n    -------\n    out: integer\n        Least common multiple.\n\n    Examples\n    --------\n    > var v = base.lcm( 21, 6 )\n    42\n\n    See Also\n    --------\n    base.gcd\n","base.ldexp":"\nbase.ldexp( frac, exp )\n    Multiplies a double-precision floating-point number by an integer power of\n    two; i.e., `x = frac * 2^exp`.\n\n    If `frac` equals positive or negative `zero`, `NaN`, or positive or negative\n    infinity, the function returns a value equal to `frac`.\n\n    Parameters\n    ----------\n    frac: number\n        Fraction.\n\n    exp: number\n        Exponent.\n\n    Returns\n    -------\n    out: number\n        Double-precision floating-point number equal to `frac * 2^exp`.\n\n    Examples\n    --------\n    > var x = base.ldexp( 0.5, 3 )\n    4.0\n    > x = base.ldexp( 4.0, -2 )\n    1.0\n    > x = base.ldexp( 0.0, 20 )\n    0.0\n    > x = base.ldexp( -0.0, 39 )\n    -0.0\n    > x = base.ldexp( NaN, -101 )\n    NaN\n    > x = base.ldexp( PINF, 11 )\n    Infinity\n    > x = base.ldexp( NINF, -118 )\n    -Infinity\n\n    See Also\n    --------\n    base.frexp\n","base.leftPad":"\nbase.leftPad( str, len, pad )\n    Left pads a string such that the padded string has a length of at least\n    `len`.\n\n    An output string is not guaranteed to have a length of exactly `len`, but to\n    have a length of at least `len`. To generate a padded string having a length\n    equal to `len`, post-process a padded string by trimming off excess\n    characters.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    len: integer\n        Minimum string length.\n\n    pad: string\n        String used to pad.\n\n    Returns\n    -------\n    out: string\n        Padded string.\n\n    Examples\n    --------\n    > var out = base.leftPad( 'a', 5, ' ' )\n    '    a'\n    > out = base.leftPad( 'beep', 10, 'b' )\n    'bbbbbbbeep'\n    > out = base.leftPad( 'boop', 12, 'beep' )\n    'beepbeepboop'\n\n    See Also\n    --------\n    base.rightPad\n","base.leftTrim":"\nbase.leftTrim( str )\n    Trims whitespace from the beginning of a string.\n\n    \"Whitespace\" is defined as the following characters:\n\n    - \\f\n    - \\n\n    - \\r\n    - \\t\n    - \\v\n    - \\u0020\n    - \\u00a0\n    - \\u1680\n    - \\u2000-\\u200a\n    - \\u2028\n    - \\u2029\n    - \\u202f\n    - \\u205f\n    - \\u3000\n    - \\ufeff\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Trimmed string.\n\n    Examples\n    --------\n    > var out = base.leftTrim( ' \\r\\n\\t  Beep \\t\\t\\n  ' )\n    'Beep \\t\\t\\n  '\n\n    See Also\n    --------\n    base.rightTrim, base.trim\n","base.ln":"\nbase.ln( x )\n    Evaluates the natural logarithm of a double-precision floating-point number.\n\n    For negative numbers, the natural logarithm is not defined.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.ln( 4.0 )\n    ~1.386\n    > y = base.ln( 0.0 )\n    -Infinity\n    > y = base.ln( PINF )\n    Infinity\n    > y = base.ln( NaN )\n    NaN\n    > y = base.ln( -4.0 )\n    NaN\n\n    See Also\n    --------\n    base.exp, base.log10, base.log1p, base.log2\n","base.log":"\nbase.log( x, b )\n    Computes the base `b` logarithm of a double-precision floating-point number.\n\n    For negative `b` or `x`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    b: number\n        Base.\n\n    Returns\n    -------\n    y: number\n        Logarithm (base `b`).\n\n    Examples\n    --------\n    > var y = base.log( 100.0, 10.0 )\n    2.0\n    > y = base.log( 16.0, 2.0 )\n    4.0\n    > y = base.log( 5.0, 1.0 )\n    Infinity\n    > y = base.log( NaN, 2.0 )\n    NaN\n    > y = base.log( 1.0, NaN )\n    NaN\n    > y = base.log( -4.0, 2.0 )\n    NaN\n    > y = base.log( 4.0, -2.0 )\n    NaN\n\n    See Also\n    --------\n    base.exp, base.ln, base.log10, base.log1p, base.log2\n","base.log1mexp":"\nbase.log1mexp( x )\n    Evaluates the natural logarithm of `1-exp(-|x|)`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.log1mexp( -10.0 )\n    ~-0.00005\n    > y = base.log1mexp( 0.0 )\n    -Infinity\n    > y = base.log1mexp( 5.0 )\n    ~-0.00676\n    > y = base.log1mexp( 10.0 )\n    ~-0.00005\n    > y = base.log1mexp( NaN )\n    NaN\n\n    See Also\n    --------\n    base.exp, base.ln, base.log1p, base.log1pexp","base.log1p":"\nbase.log1p( x )\n    Evaluates the natural logarithm of `1+x`.\n\n    For `x < -1`, the function returns `NaN`, as the natural logarithm is not\n    defined for negative numbers.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.log1p( 4.0 )\n    ~1.609\n    > y = base.log1p( -1.0 )\n    -Infinity\n    > y = base.log1p( 0.0 )\n    0.0\n    > y = base.log1p( -0.0 )\n    -0.0\n    > y = base.log1p( -2.0 )\n    NaN\n    > y = base.log1p( NaN )\n    NaN\n\n    See Also\n    --------\n    base.ln, base.log\n","base.log1pexp":"\nbase.log1pexp( x )\n    Evaluates the natural logarithm of `1+exp(x)`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.log1pexp( -10.0 )\n    ~0.000045\n    > y = base.log1pexp( 0.0 )\n    ~0.693147\n    > y = base.log1pexp( 5.0 )\n    ~5.006715\n    > y = base.log1pexp( 34.0 )\n    34.0\n    > y = base.log1pexp( NaN )\n    NaN\n\n    See Also\n    --------\n    base.exp, base.ln, base.log1mexp, base.log1p","base.log1pmx":"\nbase.log1pmx( x )\n    Evaluates `ln(1+x) - x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > base.log1pmx( 1.1 )\n    ~-0.358\n    > base.log1pmx( 0.99 )\n    ~-0.302\n    > base.log1pmx( -0.99 )\n    ~-3.615\n    > base.log1pmx( -1.1 )\n    NaN\n    > base.log1pmx( NaN )\n    NaN\n\n    See Also\n    --------\n    base.ln, base.log1p","base.log2":"\nbase.log2( x )\n    Evaluates the binary logarithm (base two).\n\n    For negative numbers, the binary logarithm is not defined.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.log2( 4.0 )\n    2.0\n    > y = base.log2( 8.0 )\n    3.0\n    > y = base.log2( 0.0 )\n    -Infinity\n    > y = base.log2( PINF )\n    Infinity\n    > y = base.log2( NaN )\n    NaN\n    > y = base.log2( -4.0 )\n    NaN\n\n    See Also\n    --------\n    base.exp2, base.ln, base.log\n","base.log10":"\nbase.log10( x )\n    Evaluates the common logarithm (base 10).\n\n    For negative numbers, the common logarithm is not defined.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.log10( 100.0 )\n    2.0\n    > y = base.log10( 8.0 )\n    ~0.903\n    > y = base.log10( 0.0 )\n    -Infinity\n    > y = base.log10( PINF )\n    Infinity\n    > y = base.log10( NaN )\n    NaN\n    > y = base.log10( -4.0 )\n    NaN\n\n    See Also\n    --------\n    base.exp10, base.ln, base.log\n","base.logaddexp":"\nbase.logaddexp( x, y )\n    Computes the natural logarithm of `exp(x) + exp(y)`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    y: number\n        Input value.\n\n    Returns\n    -------\n    v: number\n        Function value.\n\n    Examples\n    --------\n    > var v = base.logaddexp( 90.0, 90.0 )\n    ~90.6931\n    > v = base.logaddexp( -20.0, 90.0 )\n    90.0\n    > v = base.logaddexp( 0.0, -100.0 )\n    ~3.7201e-44\n    > v = base.logaddexp( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.exp, base.ln\n","base.logit":"\nbase.logit( p )\n    Evaluates the logit function.\n\n    Let `p` be the probability of some event. The logit function is defined as\n    the logarithm of the odds `p / (1-p)`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.logit( 0.2 )\n    ~-1.386\n    > y = base.logit( 0.9 )\n    ~2.197\n    > y = base.logit( -4.0 )\n    NaN\n    > y = base.logit( 1.5 )\n    NaN\n    > y = base.logit( NaN )\n    NaN\n\n","base.lowercase":"\nbase.lowercase( str )\n    Converts a string to lowercase.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Lowercase string.\n\n    Examples\n    --------\n    > var out = base.lowercase( 'bEEp' )\n    'beep'\n\n    See Also\n    --------\n    base.snakecase, base.uppercase\n","base.lucas":"\nbase.lucas( n )\n    Computes the nth Lucas number.\n\n    Lucas numbers follow the recurrence relation\n\n      L_n = L_{n-1} + L_{n-2}\n\n    with seed values L_0 = 2 and L_1 = 1.\n\n    If `n` is greater than `76`, the function returns `NaN`, as larger Lucas\n    numbers cannot be accurately represented due to limitations of double-\n    precision floating-point format.\n\n    If not provided a nonnegative integer value, the function returns `NaN`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Input value.\n\n    Returns\n    -------\n    y: integer\n        Lucas number.\n\n    Examples\n    --------\n    > var y = base.lucas( 0 )\n    2\n    > y = base.lucas( 1 )\n    1\n    > y = base.lucas( 2 )\n    3\n    > y = base.lucas( 3 )\n    4\n    > y = base.lucas( 4 )\n    7\n    > y = base.lucas( 77 )\n    NaN\n    > y = base.lucas( NaN )\n    NaN\n\n    See Also\n    --------\n    base.fibonacci, base.negalucas\n","base.lucaspoly":"\nbase.lucaspoly( n, x )\n    Evaluates a Lucas polynomial.\n\n    Parameters\n    ----------\n    n: integer\n        Lucas polynomial to evaluate.\n\n    x: number\n        Value at which to evaluate the Lucas polynomial.\n\n    Returns\n    -------\n    out: number\n        Evaluated Lucas polynomial.\n\n    Examples\n    --------\n    // 2^5 + 5*2^3 + 5*2\n    > var v = base.lucaspoly( 5, 2.0 )\n    82.0\n\n\nbase.lucaspoly.factory( n )\n    Returns a function for evaluating a Lucas polynomial.\n\n    Parameters\n    ----------\n    n: integer\n        Lucas polynomial to evaluate.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a Lucas polynomial.\n\n    Examples\n    --------\n    > var polyval = base.lucaspoly.factory( 5 );\n\n    // 1^5 + 5*1^2 + 5\n    > var v = polyval( 1.0 )\n    11.0\n\n    // 2^5 + 5*2^3 + 5*2\n    > v = polyval( 2.0 )\n    82.0\n\n    See Also\n    --------\n    base.evalpoly, base.fibpoly\n","base.lucaspoly.factory":"\nbase.lucaspoly.factory( n )\n    Returns a function for evaluating a Lucas polynomial.\n\n    Parameters\n    ----------\n    n: integer\n        Lucas polynomial to evaluate.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a Lucas polynomial.\n\n    Examples\n    --------\n    > var polyval = base.lucaspoly.factory( 5 );\n\n    // 1^5 + 5*1^2 + 5\n    > var v = polyval( 1.0 )\n    11.0\n\n    // 2^5 + 5*2^3 + 5*2\n    > v = polyval( 2.0 )\n    82.0\n\n    See Also\n    --------\n    base.evalpoly, base.fibpoly","base.max":"\nbase.max( x, y )\n    Returns the maximum value.\n\n    If any argument is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    > var v = base.max( 3.14, 4.2 )\n    4.2\n    > v = base.max( 3.14, NaN )\n    NaN\n    > v = base.max( +0.0, -0.0 )\n    +0.0\n\n    See Also\n    --------\n    base.maxabs, base.maxn, base.min\n","base.maxabs":"\nbase.maxabs( x, y )\n    Returns the maximum absolute value.\n\n    If any argument is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    > var v = base.maxabs( 3.14, -4.2 )\n    4.2\n    > v = base.maxabs( 3.14, NaN )\n    NaN\n    > v = base.maxabs( +0.0, -0.0 )\n    +0.0\n\n    See Also\n    --------\n    base.max, base.minabs\n","base.maxabsn":"\nbase.maxabsn( [x[, y[, ...args]]] )\n    Returns the maximum absolute value.\n\n    If any argument is `NaN`, the function returns `NaN`.\n\n    When an empty set is considered a subset of the extended reals (all real\n    numbers, including positive and negative infinity), negative infinity is the\n    least upper bound. Similar to zero being the identity element for the sum of\n    an empty set and to one being the identity element for the product of an\n    empty set, negative infinity is the identity element for the maximum, and\n    thus, if not provided any arguments, the function returns `+infinity` (i.e.,\n    the absolute value of `-infinity`).\n\n    Parameters\n    ----------\n    x: number (optional)\n        First number.\n\n    y: number (optional)\n        Second number.\n\n    args: ...number (optional)\n        Numbers.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    > var v = base.maxabsn( 3.14, -4.2 )\n    4.2\n    > v = base.maxabsn( 5.9, 3.14, 4.2 )\n    5.9\n    > v = base.maxabsn( 3.14, NaN )\n    NaN\n    > v = base.maxabsn( +0.0, -0.0 )\n    +0.0\n\n    See Also\n    --------\n    base.maxn, base.maxabs, base.minabsn\n","base.maxn":"\nbase.maxn( [x[, y[, ...args]]] )\n    Returns the maximum value.\n\n    If any argument is `NaN`, the function returns `NaN`.\n\n    When an empty set is considered a subset of the extended reals (all real\n    numbers, including positive and negative infinity), negative infinity is the\n    least upper bound. Similar to zero being the identity element for the sum of\n    an empty set and to one being the identity element for the product of an\n    empty set, negative infinity is the identity element for the maximum, and\n    thus, if not provided any arguments, the function returns negative infinity.\n\n    Parameters\n    ----------\n    x: number (optional)\n        First number.\n\n    y: number (optional)\n        Second number.\n\n    args: ...number (optional)\n        Numbers.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    > var v = base.maxn( 3.14, 4.2 )\n    4.2\n    > v = base.maxn( 5.9, 3.14, 4.2 )\n    5.9\n    > v = base.maxn( 3.14, NaN )\n    NaN\n    > v = base.maxn( +0.0, -0.0 )\n    +0.0\n\n    See Also\n    --------\n    base.max, base.maxabsn, base.minn\n","base.min":"\nbase.min( x, y )\n    Returns the minimum value.\n\n    If any argument is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    > var v = base.min( 3.14, 4.2 )\n    3.14\n    > v = base.min( 3.14, NaN )\n    NaN\n    > v = base.min( +0.0, -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.max, base.minabs, base.minn\n","base.minabs":"\nbase.minabs( x, y )\n    Returns the minimum absolute value.\n\n    If any argument is `NaN`, the function returns `NaN`.\n\n    When an empty set is considered a subset of the extended reals (all real\n    numbers, including positive and negative infinity), positive infinity is the\n    greatest upper bound. Similar to zero being the identity element for the sum\n    of an empty set and to one being the identity element for the product of an\n    empty set, positive infinity is the identity element for the minimum, and\n    thus, if not provided any arguments, the function returns positive infinity.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    > var v = base.minabs( 3.14, -4.2 )\n    3.14\n    > v = base.minabs( 3.14, NaN )\n    NaN\n    > v = base.minabs( +0.0, -0.0 )\n    +0.0\n\n    See Also\n    --------\n    base.maxabs, base.min\n","base.minabsn":"\nbase.minabsn( [x[, y[, ...args]]] )\n    Returns the minimum absolute value.\n\n    If any argument is `NaN`, the function returns `NaN`.\n\n    When an empty set is considered a subset of the extended reals (all real\n    numbers, including positive and negative infinity), positive infinity is the\n    greatest upper bound. Similar to zero being the identity element for the sum\n    of an empty set and to one being the identity element for the product of an\n    empty set, positive infinity is the identity element for the minimum, and\n    thus, if not provided any arguments, the function returns positive infinity.\n\n    Parameters\n    ----------\n    x: number (optional)\n        First number.\n\n    y: number (optional)\n        Second number.\n\n    args: ...number (optional)\n        Numbers.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    > var v = base.minabsn( 3.14, -4.2 )\n    3.14\n    > v = base.minabsn( 5.9, 3.14, 4.2 )\n    3.14\n    > v = base.minabsn( 3.14, NaN )\n    NaN\n    > v = base.minabsn( +0.0, -0.0 )\n    +0.0\n\n    See Also\n    --------\n    base.maxabsn, base.minn, base.minabs\n","base.minmax":"\nbase.minmax( x, y )\n    Returns the minimum and maximum values.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum values.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: Array<number>\n        Minimum and maximum values.\n\n    Examples\n    --------\n    > var v = base.minmax( 3.14, 4.2 )\n    [ 3.14, 4.2 ]\n    > v = base.minmax( 3.14, NaN )\n    [ NaN, NaN ]\n    > v = base.minmax( +0.0, -0.0 )\n    [ -0.0, +0.0 ]\n\n\nbase.minmax.assign( x, y, out, stride, offset )\n    Returns the minimum and maximum values and assigns results to a provided\n    output array.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum values.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    out: Array|TypedArray|Object\n        Output object.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Minimum and maximum values.\n\n    Examples\n    --------\n    > var out = [ 0.0, 0.0 ];\n    > var v = base.minmax.assign( 3.14, -1.5, out, 1, 0 )\n    [ -1.5, 3.14 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.max, base.min, base.minmaxabs","base.minmax.assign":"\nbase.minmax.assign( x, y, out, stride, offset )\n    Returns the minimum and maximum values and assigns results to a provided\n    output array.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum values.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    out: Array|TypedArray|Object\n        Output object.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Minimum and maximum values.\n\n    Examples\n    --------\n    > var out = [ 0.0, 0.0 ];\n    > var v = base.minmax.assign( 3.14, -1.5, out, 1, 0 )\n    [ -1.5, 3.14 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.max, base.min, base.minmaxabs","base.minmaxabs":"\nbase.minmaxabs( x, y )\n    Returns the minimum and maximum absolute values.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum absolute values.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: Array<number>\n        Minimum and maximum absolute values.\n\n    Examples\n    --------\n    > var v = base.minmaxabs( 3.14, 4.2 )\n    [ 3.14, 4.2 ]\n    > v = base.minmaxabs( -5.9, 3.14)\n    [ 3.14, 5.9 ]\n    > v = base.minmaxabs( 3.14, NaN )\n    [ NaN, NaN ]\n    > v = base.minmaxabs( +0.0, -0.0 )\n    [ 0.0, 0.0 ]\n\n\nbase.minmaxabs.assign( x, y, out, stride, offset )\n    Returns the minimum and maximum absolute values.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum absolute values.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    out: Array|TypedArray|Object\n        Output object.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Minimum and maximum absolute values.\n\n    Examples\n    --------\n    > var out = [ 0.0, 0.0 ];\n    > var v = base.minmaxabs.assign( 3.14, -3.14, out, 1, 0 )\n    [ 3.14, 3.14 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.maxabs, base.minabs, base.minmax\n","base.minmaxabs.assign":"\nbase.minmaxabs.assign( x, y, out, stride, offset )\n    Returns the minimum and maximum absolute values.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum absolute values.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    out: Array|TypedArray|Object\n        Output object.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Minimum and maximum absolute values.\n\n    Examples\n    --------\n    > var out = [ 0.0, 0.0 ];\n    > var v = base.minmaxabs.assign( 3.14, -3.14, out, 1, 0 )\n    [ 3.14, 3.14 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.maxabs, base.minabs, base.minmax","base.minmaxabsn":"\nbase.minmaxabsn( [x[, y[, ...args]]] )\n    Returns the minimum and maximum absolute values.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum absolute values.\n\n    When an empty set is considered a subset of the extended reals (all real\n    numbers, including positive and negative infinity), positive infinity is the\n    greatest lower bound and negative infinity is the least upper bound. Similar\n    to zero being the identity element for the sum of an empty set and to one\n    being the identity element for the product of an empty set, positive\n    infinity is the identity element for the minimum and negative infinity is\n    the identity element for the maximum, and thus, if not provided any\n    arguments, the function returns positive infinity for both the minimum and\n    maximum absolute values.\n\n    Parameters\n    ----------\n    x: number (optional)\n        First number.\n\n    y: number (optional)\n        Second number.\n\n    args: ...number (optional)\n        Numbers.\n\n    Returns\n    -------\n    out: Array<number>\n        Minimum and maximum absolute values.\n\n    Examples\n    --------\n    > var v = base.minmaxabsn( 3.14, 4.2 )\n    [ 3.14, 4.2 ]\n    > v = base.minmaxabsn( -5.9, 3.14, 4.2 )\n    [ 3.14, 5.9 ]\n    > v = base.minmaxabsn( 3.14, NaN )\n    [ NaN, NaN ]\n    > v = base.minmaxabsn( +0.0, -0.0 )\n    [ 0.0, 0.0 ]\n    > v = base.minmaxabsn( 3.14 )\n    [ 3.14, 3.14 ]\n\n\nbase.minmaxabsn.assign( [x[, y[, ...args]]], out, stride, offset )\n    Returns the minimum and maximum absolute values.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum absolute values.\n\n    Parameters\n    ----------\n    x: number (optional)\n        First number.\n\n    y: number (optional)\n        Second number.\n\n    args: ...number (optional)\n        Numbers.\n\n    out: Array|TypedArray|Object\n        Output object.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Minimum and maximum absolute values.\n\n    Examples\n    --------\n    > var out = [ 0.0, 0.0 ];\n    > var v = base.minmaxabsn.assign( 3.14, out, 1, 0 )\n    [ 3.14, 3.14 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.maxabsn, base.minabsn, base.minmaxn\n","base.minmaxabsn.assign":"\nbase.minmaxabsn.assign( [x[, y[, ...args]]], out, stride, offset )\n    Returns the minimum and maximum absolute values.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum absolute values.\n\n    Parameters\n    ----------\n    x: number (optional)\n        First number.\n\n    y: number (optional)\n        Second number.\n\n    args: ...number (optional)\n        Numbers.\n\n    out: Array|TypedArray|Object\n        Output object.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Minimum and maximum absolute values.\n\n    Examples\n    --------\n    > var out = [ 0.0, 0.0 ];\n    > var v = base.minmaxabsn.assign( 3.14, out, 1, 0 )\n    [ 3.14, 3.14 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.maxabsn, base.minabsn, base.minmaxn","base.minmaxn":"\nbase.minmaxn( [x[, y[, ...args]]] )\n    Returns the minimum and maximum values.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum values.\n\n    When an empty set is considered a subset of the extended reals (all real\n    numbers, including positive and negative infinity), positive infinity is the\n    greatest lower bound and negative infinity is the least upper bound. Similar\n    to zero being the identity element for the sum of an empty set and to one\n    being the identity element for the product of an empty set, positive\n    infinity is the identity element for the minimum and negative infinity is\n    the identity element for the maximum, and thus, if not provided any\n    arguments, the function returns positive infinity for the minimum value and\n    negative infinity for the maximum value.\n\n    Parameters\n    ----------\n    x: number (optional)\n        First number.\n\n    y: number (optional)\n        Second number.\n\n    args: ...number (optional)\n        Numbers.\n\n    Returns\n    -------\n    out: Array<number>\n        Minimum and maximum values.\n\n    Examples\n    --------\n    > var v = base.minmaxn( 3.14, 4.2 )\n    [ 3.14, 4.2 ]\n    > v = base.minmaxn( 5.9, 3.14, 4.2 )\n    [ 3.14, 5.9 ]\n    > v = base.minmaxn( 3.14, NaN )\n    [ NaN, NaN ]\n    > v = base.minmaxn( +0.0, -0.0 )\n    [ -0.0, +0.0 ]\n    > v = base.minmaxn( 3.14 )\n    [ 3.14, 3.14 ]\n\n\nbase.minmaxn.assign( [x[, y[, ...args]]], out, stride, offset )\n    Returns the minimum and maximum values and assigns results to a provided\n    output array.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum values.\n\n    Parameters\n    ----------\n    x: number (optional)\n        First number.\n\n    y: number (optional)\n        Second number.\n\n    args: ...number (optional)\n        Numbers.\n\n    out: Array|TypedArray|Object\n        Output object.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Minimum and maximum values.\n\n    Examples\n    --------\n    > var out = [ 0.0, 0.0 ];\n    > var v = base.minmaxn.assign( 3.14, -1.5, out, 1, 0 )\n    [ -1.5, 3.14 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.maxn, base.minn, base.minmaxabsn","base.minmaxn.assign":"\nbase.minmaxn.assign( [x[, y[, ...args]]], out, stride, offset )\n    Returns the minimum and maximum values and assigns results to a provided\n    output array.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum values.\n\n    Parameters\n    ----------\n    x: number (optional)\n        First number.\n\n    y: number (optional)\n        Second number.\n\n    args: ...number (optional)\n        Numbers.\n\n    out: Array|TypedArray|Object\n        Output object.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Minimum and maximum values.\n\n    Examples\n    --------\n    > var out = [ 0.0, 0.0 ];\n    > var v = base.minmaxn.assign( 3.14, -1.5, out, 1, 0 )\n    [ -1.5, 3.14 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.maxn, base.minn, base.minmaxabsn","base.minn":"\nbase.minn( [x[, y[, ...args]]] )\n    Returns the minimum value.\n\n    If any argument is `NaN`, the function returns `NaN`.\n\n    When an empty set is considered a subset of the extended reals (all real\n    numbers, including positive and negative infinity), positive infinity is the\n    greatest lower bound. Similar to zero being the identity element for the sum\n    of an empty set and to one being the identity element for the product of an\n    empty set, positive infinity is the identity element for the minimum, and\n    thus, if not provided any arguments, the function returns positive infinity.\n\n    Parameters\n    ----------\n    x: number (optional)\n        First number.\n\n    y: number (optional)\n        Second number.\n\n    args: ...number (optional)\n        Numbers.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    > var v = base.minn( 3.14, 4.2 )\n    3.14\n    > v = base.minn( 5.9, 3.14, 4.2 )\n    3.14\n    > v = base.minn( 3.14, NaN )\n    NaN\n    > v = base.minn( +0.0, -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.maxn, base.min, base.minabsn\n","base.modf":"\nbase.modf( x )\n    Decomposes a double-precision floating-point number into integral and\n    fractional parts, each having the same type and sign as the input value.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    out: Array<number>\n        Integral and fractional parts.\n\n    Examples\n    --------\n    > var parts = base.modf( 3.14 )\n    [ 3.0, 0.14000000000000012 ]\n    > parts = base.modf( 3.14 )\n    [ 3.0, 0.14000000000000012 ]\n    > parts = base.modf( +0.0 )\n    [ +0.0, +0.0 ]\n    > parts = base.modf( -0.0 )\n    [ -0.0, -0.0 ]\n    > parts = base.modf( PINF )\n    [ Infinity, +0.0 ]\n    > parts = base.modf( NINF )\n    [ -Infinity, -0.0 ]\n    > parts = base.modf( NaN )\n    [ NaN, NaN ]\n\n\nbase.modf.assign( x, out, stride, offset )\n    Decomposes a double-precision floating-point number into integral and\n    fractional parts, each having the same type and sign as the input value,\n    and assigns results to a provided output array.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Integral and fractional parts.\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var parts = base.modf.assign( 3.14, out, 1, 0 )\n    <Float64Array>[ 3.0, 0.14000000000000012 ]\n    > var bool = ( parts === out )\n    true\n","base.modf.assign":"\nbase.modf.assign( x, out, stride, offset )\n    Decomposes a double-precision floating-point number into integral and\n    fractional parts, each having the same type and sign as the input value,\n    and assigns results to a provided output array.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Integral and fractional parts.\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var parts = base.modf.assign( 3.14, out, 1, 0 )\n    <Float64Array>[ 3.0, 0.14000000000000012 ]\n    > var bool = ( parts === out )\n    true","base.mul":"\nbase.mul( x, y )\n    Multiplies two double-precision floating-point numbers `x` and `y`.\n\n    Parameters\n    ----------\n    x: number\n        First input value.\n\n    y: number\n        Second input value.\n\n    Returns\n    -------\n    z: number\n        Result.\n\n    Examples\n    --------\n    > var v = base.mul( -1.0, 5.0 )\n    -5.0\n    > v = base.mul( 2.0, 5.0 )\n    10.0\n    > v = base.mul( 0.0, 5.0 )\n    0.0\n    > v = base.mul( -0.0, 0.0 )\n    -0.0\n    > v = base.mul( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.add, base.div, base.sub\n","base.mulf":"\nbase.mulf( x, y )\n    Multiplies two single-precision floating-point numbers `x` and `y`.\n\n    Parameters\n    ----------\n    x: number\n        First input value.\n\n    y: number\n        Second input value.\n\n    Returns\n    -------\n    z: number\n        Result.\n\n    Examples\n    --------\n    > var v = base.mulf( -1.0, 5.0 )\n    -5.0\n    > v = base.mulf( 2.0, 5.0 )\n    10.0\n    > v = base.mulf( 0.0, 5.0 )\n    0.0\n    > v = base.mulf( -0.0, 0.0 )\n    -0.0\n    > v = base.mulf( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.addf, base.divf, base.mul, base.subf\n","base.ndarray":"\nbase.ndarray( dtype, buffer, shape, strides, offset, order )\n    Returns an ndarray.\n\n    Parameters\n    ----------\n    dtype: string\n        Underlying data type.\n\n    buffer: ArrayLikeObject|TypedArray|Buffer\n        Data buffer. A data buffer must be an array-like object (i.e., have a\n        `length` property). For data buffers which are not indexed collections\n        (i.e., collections which cannot support direct index access, such as\n        `buffer[ index ]`; e.g., Complex64Array, Complex128Array, etc), a data\n        buffer should provide `#.get( idx )` and `#.set( v[, idx] )` methods.\n        Note that, for `set` methods, the value to set should be the first\n        argument, followed by the linear index, similar to the native typed\n        array `set` method.\n\n    shape: ArrayLikeObject<integer>\n        Array shape.\n\n    strides: ArrayLikeObject<integer>\n        Array strides.\n\n    offset: integer\n        Index offset.\n\n    order: string\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran-style).\n\n    Returns\n    -------\n    ndarray: ndarray\n        ndarray instance.\n\n    Examples\n    --------\n    // Create a new instance...\n    > var b = [ 1, 2, 3, 4 ]; // underlying data buffer\n    > var d = [ 2, 2 ]; // shape\n    > var s = [ 2, 1 ]; // strides\n    > var o = 0; // index offset\n    > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' )\n    <ndarray>\n\n    // Get an element using subscripts:\n    > var v = arr.get( 1, 1 )\n    4\n\n    // Get an element using a linear index:\n    > v = arr.iget( 3 )\n    4\n\n    // Set an element using subscripts:\n    > arr.set( 1, 1, 40 );\n    > arr.get( 1, 1 )\n    40\n\n    // Set an element using a linear index:\n    > arr.iset( 3, 99 );\n    > arr.get( 1, 1 )\n    99\n\n\nbase.ndarray.prototype.byteLength\n    Size (in bytes) of the array (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of the array.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.byteLength\n    32\n\n\nbase.ndarray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.BYTES_PER_ELEMENT\n    8\n\n\nbase.ndarray.prototype.data\n    Pointer to the underlying data buffer.\n\n    Returns\n    -------\n    buf: ArrayLikeObject|TypedArray|Buffer\n        Underlying data buffer.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var buf = arr.data\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n\nbase.ndarray.prototype.dtype\n    Underlying data type.\n\n    Returns\n    -------\n    dtype: string\n        Underlying data type.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var dt = arr.dtype\n    'float64'\n\n\nbase.ndarray.prototype.flags\n    Meta information, such as information concerning the memory layout of the\n    array.\n\n    Returns\n    -------\n    flags: Object\n        Info object.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var fl = arr.flags\n    {...}\n\n\nbase.ndarray.prototype.length\n    Length of the array (i.e., number of elements).\n\n    Returns\n    -------\n    len: integer\n        Array length.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var len = arr.length\n    4\n\n\nbase.ndarray.prototype.ndims\n    Number of dimensions.\n\n    Returns\n    -------\n    ndims: integer\n        Number of dimensions.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var n = arr.ndims\n    2\n\n\nbase.ndarray.prototype.offset\n    Index offset which specifies the buffer index at which to start iterating\n    over array elements.\n\n    Returns\n    -------\n    offset: integer\n        Index offset.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.offset\n    0\n\n\nbase.ndarray.prototype.order: string\n    Array order.\n\n    The array order is either row-major (C-style) or column-major (Fortran-\n    style).\n\n    Returns\n    -------\n    order: string\n        Array order.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var ord = arr.order\n    'row-major'\n\n\nbase.ndarray.prototype.shape\n    Array shape.\n\n    Returns\n    -------\n    shape: Array\n        Array shape.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sh = arr.shape\n    [ 2, 2 ]\n\n\nbase.ndarray.prototype.strides\n    Index strides which specify how to access data along corresponding array\n    dimensions.\n\n    Returns\n    -------\n    strides: Array\n        Index strides.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var st = arr.strides\n    [ 2, 1 ]\n\n\nbase.ndarray.prototype.get( ...idx )\n    Returns an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.get( 1, 1 )\n    4.0\n\n\nbase.ndarray.prototype.iget( idx )\n    Returns an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the input argument is ignored and, for clarity,\n    should not be provided.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.iget( 3 )\n    4.0\n\n\nbase.ndarray.prototype.set( ...idx, v )\n    Sets an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: ndarray\n        ndarray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > arr.set( 1, 1, -4.0 );\n    > arr.get( 1, 1 )\n    -4.0\n\n\nbase.ndarray.prototype.iset( idx, v )\n    Sets an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the first, and only, argument should be the\n    value to set.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: ndarray\n        ndarray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > arr.iset( 3, -4.0 );\n    > arr.iget( 3 )\n    -4.0\n\n\nbase.ndarray.prototype.toString()\n    Serializes an ndarray as a string.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    str: string\n        Serialized ndarray string.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toString()\n    '...'\n\n\nbase.ndarray.prototype.toJSON()\n    Serializes an ndarray as a JSON object.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toJSON()\n    {...}\n\n    See Also\n    --------\n    array, ndarray\n","base.ndarray.prototype.byteLength":"\nbase.ndarray.prototype.byteLength\n    Size (in bytes) of the array (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of the array.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.byteLength\n    32","base.ndarray.prototype.BYTES_PER_ELEMENT":"\nbase.ndarray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.BYTES_PER_ELEMENT\n    8","base.ndarray.prototype.data":"\nbase.ndarray.prototype.data\n    Pointer to the underlying data buffer.\n\n    Returns\n    -------\n    buf: ArrayLikeObject|TypedArray|Buffer\n        Underlying data buffer.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var buf = arr.data\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]","base.ndarray.prototype.dtype":"\nbase.ndarray.prototype.dtype\n    Underlying data type.\n\n    Returns\n    -------\n    dtype: string\n        Underlying data type.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var dt = arr.dtype\n    'float64'","base.ndarray.prototype.flags":"\nbase.ndarray.prototype.flags\n    Meta information, such as information concerning the memory layout of the\n    array.\n\n    Returns\n    -------\n    flags: Object\n        Info object.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var fl = arr.flags\n    {...}","base.ndarray.prototype.length":"\nbase.ndarray.prototype.length\n    Length of the array (i.e., number of elements).\n\n    Returns\n    -------\n    len: integer\n        Array length.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var len = arr.length\n    4","base.ndarray.prototype.ndims":"\nbase.ndarray.prototype.ndims\n    Number of dimensions.\n\n    Returns\n    -------\n    ndims: integer\n        Number of dimensions.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var n = arr.ndims\n    2","base.ndarray.prototype.offset":"\nbase.ndarray.prototype.offset\n    Index offset which specifies the buffer index at which to start iterating\n    over array elements.\n\n    Returns\n    -------\n    offset: integer\n        Index offset.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.offset\n    0","base.ndarray.prototype.order: string":"\nbase.ndarray.prototype.order: string\n    Array order.\n\n    The array order is either row-major (C-style) or column-major (Fortran-\n    style).\n\n    Returns\n    -------\n    order: string\n        Array order.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var ord = arr.order\n    'row-major'","base.ndarray.prototype.shape":"\nbase.ndarray.prototype.shape\n    Array shape.\n\n    Returns\n    -------\n    shape: Array\n        Array shape.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sh = arr.shape\n    [ 2, 2 ]","base.ndarray.prototype.strides":"\nbase.ndarray.prototype.strides\n    Index strides which specify how to access data along corresponding array\n    dimensions.\n\n    Returns\n    -------\n    strides: Array\n        Index strides.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var st = arr.strides\n    [ 2, 1 ]","base.ndarray.prototype.get":"\nbase.ndarray.prototype.get( ...idx )\n    Returns an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.get( 1, 1 )\n    4.0","base.ndarray.prototype.iget":"\nbase.ndarray.prototype.iget( idx )\n    Returns an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the input argument is ignored and, for clarity,\n    should not be provided.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.iget( 3 )\n    4.0","base.ndarray.prototype.set":"\nbase.ndarray.prototype.set( ...idx, v )\n    Sets an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: ndarray\n        ndarray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > arr.set( 1, 1, -4.0 );\n    > arr.get( 1, 1 )\n    -4.0","base.ndarray.prototype.iset":"\nbase.ndarray.prototype.iset( idx, v )\n    Sets an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the first, and only, argument should be the\n    value to set.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: ndarray\n        ndarray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > arr.iset( 3, -4.0 );\n    > arr.iget( 3 )\n    -4.0","base.ndarray.prototype.toString":"\nbase.ndarray.prototype.toString()\n    Serializes an ndarray as a string.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    str: string\n        Serialized ndarray string.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toString()\n    '...'","base.ndarray.prototype.toJSON":"\nbase.ndarray.prototype.toJSON()\n    Serializes an ndarray as a JSON object.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toJSON()\n    {...}\n\n    See Also\n    --------\n    array, ndarray","base.ndarrayUnary":"\nbase.ndarrayUnary( arrays, fcn )\n    Applies a unary callback to elements in an input ndarray and assigns results\n    to elements in an output ndarray.\n\n    Each provided \"ndarray\" should be an object with the following properties:\n\n    - dtype: data type.\n    - data: data buffer.\n    - shape: dimensions.\n    - strides: stride lengths.\n    - offset: index offset.\n    - order: specifies whether an ndarray is row-major (C-style) or column-major\n    (Fortran-style).\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ndarray>\n        Array-like object containing one input ndarray and one output ndarray.\n\n    fcn: Function\n        Unary callback.\n\n    Examples\n    --------\n    // Define ndarray data and meta data...\n    > var xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var dtype = 'float64';\n    > var shape = [ 2, 2 ];\n    > var sx = [ 2, 1 ];\n    > var sy = [ 2, 1 ];\n    > var ox = 0;\n    > var oy = 0;\n    > var order = 'row-major';\n\n    // Using ndarrays...\n    > var x = ndarray( dtype, xbuf, shape, sx, ox, order );\n    > var y = ndarray( dtype, ybuf, shape, sy, oy, order );\n    > base.ndarrayUnary( [ x, y ], base.abs );\n    > y.data\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Using minimal ndarray-like objects...\n    > x = {\n    ...     'dtype': dtype,\n    ...     'data': xbuf,\n    ...     'shape': shape,\n    ...     'strides': sx,\n    ...     'offset': ox,\n    ...     'order': order\n    ... };\n    > y = {\n    ...     'dtype': dtype,\n    ...     'data': ybuf,\n    ...     'shape': shape,\n    ...     'strides': sy,\n    ...     'offset': oy,\n    ...     'order': order\n    ... };\n    > base.ndarrayUnary( [ x, y ], base.abs );\n    > y.data\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    See Also\n    --------\n    ndarrayDispatch\n","base.ndzeros":"\nbase.ndzeros( dtype, shape, order )\n    Returns a zero-filled ndarray having a specified shape and data type.\n\n    Parameters\n    ----------\n    dtype: string\n        Underlying data type. Must be a numeric data type or \"generic\".\n\n    shape: ArrayLikeObject<integer>\n        Array shape.\n\n    order: string\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran-style).\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var arr = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n    <ndarray>\n    > var sh = arr.shape\n    [ 2, 2 ]\n    > var dt = arr.dtype\n    'float64'\n\n    See Also\n    --------\n    base.ndarray, base.ndzerosLike\n","base.ndzerosLike":"\nbase.ndzerosLike( x )\n    Returns a zero-filled ndarray having the same shape and data type as a\n    provided input ndarray.\n\n    Along with data type, shape, and order, the function infers the \"class\" of\n    the returned ndarray from the provided ndarray. For example, if provided a\n    \"base\" ndarray, the function returns a base ndarray. If provided a non-base\n    ndarray, the function returns a non-base ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n    <ndarray>\n    > var sh = x.shape\n    [ 2, 2 ]\n    > var dt = x.dtype\n    'float64'\n    > var y = base.ndzerosLike( x )\n    <ndarray>\n    > sh = y.shape\n    [ 2, 2 ]\n    > dt = y.dtype\n    'float64'\n\n    See Also\n    --------\n    base.ndarray, base.ndzeros\n","base.negafibonacci":"\nbase.negafibonacci( n )\n    Computes the nth negaFibonacci number.\n\n    The negaFibonacci numbers follow the recurrence relation\n\n      F_{n-2} = F_{n} - F_{n-1}\n\n    with seed values F_0 = 0 and F_{-1} = 1.\n\n    If `|n|` is greater than `78`, the function returns `NaN` as larger\n    negaFibonacci numbers cannot be accurately represented due to limitations of\n    double-precision floating-point format.\n\n    If not provided a non-positive integer value, the function returns `NaN`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Input value.\n\n    Returns\n    -------\n    y: integer\n        NegaFibonacci number.\n\n    Examples\n    --------\n    > var y = base.negafibonacci( 0 )\n    0\n    > y = base.negafibonacci( -1 )\n    1\n    > y = base.negafibonacci( -2 )\n    -1\n    > y = base.negafibonacci( -3 )\n    2\n    > y = base.negafibonacci( -4 )\n    -3\n    > y = base.negafibonacci( -79 )\n    NaN\n    > y = base.negafibonacci( -80 )\n    NaN\n    > y = base.negafibonacci( NaN )\n    NaN\n\n    See Also\n    --------\n    base.fibonacci, base.negalucas\n","base.negalucas":"\nbase.negalucas( n )\n    Computes the nth negaLucas number.\n\n    The negaLucas numbers follow the recurrence relation\n\n      L_{n-2} = L_{n} - L_{n-1}\n\n    with seed values L_0 = 2 and L_{-1} = -1.\n\n    If `|n|` is greater than `76`, the function returns `NaN` as larger\n    negaLucas numbers cannot be accurately represented due to limitations of\n    double-precision floating-point format.\n\n    If not provided a non-positive integer value, the function returns `NaN`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Input value.\n\n    Returns\n    -------\n    y: integer\n        NegaLucas number.\n\n    Examples\n    --------\n    > var y = base.negalucas( 0 )\n    2\n    > y = base.negalucas( -1 )\n    -1\n    > y = base.negalucas( -2 )\n    3\n    > y = base.negalucas( -3 )\n    -4\n    > y = base.negalucas( -4 )\n    7\n    > y = base.negalucas( -77 )\n    NaN\n    > y = base.negalucas( -78 )\n    NaN\n    > y = base.negalucas( NaN )\n    NaN\n\n    See Also\n    --------\n    base.fibonacci, base.lucas, base.negafibonacci\n","base.nonfibonacci":"\nbase.nonfibonacci( n )\n    Computes the nth non-Fibonacci number.\n\n    If not provided a nonnegative integer value, the function returns `NaN`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Non-Fibonacci number.\n\n    Examples\n    --------\n    > var v = base.nonfibonacci( 1 )\n    4\n    > v = base.nonfibonacci( 2 )\n    6\n    > v = base.nonfibonacci( 3 )\n    7\n    > v = base.nonfibonacci( NaN )\n    NaN\n\n    See Also\n    --------\n    base.fibonacci\n","base.normalize":"\nbase.normalize( x )\n    Returns a normal number and exponent satisfying `x = y * 2^exp` as an array.\n\n    The first element of the returned array corresponds to `y` and the second to\n    `exp`.\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    Returns\n    -------\n    out: Array<number>\n        An array containing `y` and `exp`.\n\n    Examples\n    --------\n    > var out = base.normalize( 3.14e-319 )\n    [ 1.4141234400356668e-303, -52 ]\n    > var y = out[ 0 ];\n    > var exponent = out[ 1 ];\n    > var bool = ( y*base.pow(2.0, exponent) === 3.14e-319 )\n    true\n\n    // Special cases:\n    > out = base.normalize( 0.0 )\n    [ 0.0, 0 ];\n    > out = base.normalize( PINF )\n    [ Infinity, 0 ]\n    > out = base.normalize( NINF )\n    [ -Infinity, 0 ]\n    > out = base.normalize( NaN )\n    [ NaN, 0 ]\n\n\nbase.normalize.assign( x, out, stride, offset )\n    Returns a normal number and exponent satisfying `x = y * 2^exp` and assigns\n    results to a provided output array.\n\n    The first element of the returned array corresponds to `y` and the second to\n    `exp`.\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Output array.\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 )\n    > var v = base.normalize.assign( 3.14e-319, out, 1, 0 )\n    <Float64Array>[ 1.4141234400356668e-303, -52 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.normalizef\n","base.normalize.assign":"\nbase.normalize.assign( x, out, stride, offset )\n    Returns a normal number and exponent satisfying `x = y * 2^exp` and assigns\n    results to a provided output array.\n\n    The first element of the returned array corresponds to `y` and the second to\n    `exp`.\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Output array.\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 )\n    > var v = base.normalize.assign( 3.14e-319, out, 1, 0 )\n    <Float64Array>[ 1.4141234400356668e-303, -52 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.normalizef","base.normalizef":"\nbase.normalizef( x )\n    Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` as\n    an array.\n\n    The first element of the returned array corresponds to `y` and the second to\n    `exp`.\n\n    While the function accepts higher precision floating-point numbers, beware\n    that providing such numbers can be a source of subtle bugs as the relation\n    `x = y * 2^exp` may not hold.\n\n    Parameters\n    ----------\n    x: float\n        Single-precision floating-point number.\n\n    Returns\n    -------\n    out: Array<number>\n        An array containing `y` and `exp`.\n\n    Examples\n    --------\n    > var out = base.normalizef( base.float64ToFloat32( 1.401e-45 ) )\n    [ 1.1754943508222875e-38, -23 ]\n    > var y = out[ 0 ];\n    > var exp = out[ 1 ];\n    > var bool = ( y*base.pow(2,exp) === base.float64ToFloat32(1.401e-45) )\n    true\n\n    // Special cases:\n    > out = base.normalizef( FLOAT32_PINF )\n    [ Infinity, 0 ]\n    > out = base.normalizef( FLOAT32_NINF )\n    [ -Infinity, 0 ]\n    > out = base.normalizef( NaN )\n    [ NaN, 0 ]\n\n\nbase.normalizef.assign( x, out, stride, offset )\n    Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` and\n    assigns results to a provided output array.\n\n    The first element of the returned array corresponds to `y` and the second to\n    `exp`.\n\n    While the function accepts higher precision floating-point numbers, beware\n    that providing such numbers can be a source of subtle bugs as the relation\n    `x = y * 2^exp` may not hold.\n\n    Parameters\n    ----------\n    x: float\n        Single-precision floating-point number.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        An array containing `y` and `exp`.\n\n    Examples\n    --------\n    > out = new Float32Array( 2 );\n    > var v = base.normalizef.assign( base.float64ToFloat32( 1.401e-45 ), out, 1, 0 )\n    <Float32Array>[ 1.1754943508222875e-38, -23.0 ]\n    > bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.normalize","base.normalizef.assign":"\nbase.normalizef.assign( x, out, stride, offset )\n    Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` and\n    assigns results to a provided output array.\n\n    The first element of the returned array corresponds to `y` and the second to\n    `exp`.\n\n    While the function accepts higher precision floating-point numbers, beware\n    that providing such numbers can be a source of subtle bugs as the relation\n    `x = y * 2^exp` may not hold.\n\n    Parameters\n    ----------\n    x: float\n        Single-precision floating-point number.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        An array containing `y` and `exp`.\n\n    Examples\n    --------\n    > out = new Float32Array( 2 );\n    > var v = base.normalizef.assign( base.float64ToFloat32( 1.401e-45 ), out, 1, 0 )\n    <Float32Array>[ 1.1754943508222875e-38, -23.0 ]\n    > bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.normalize","base.normalizeSlice":"\nbase.normalizeSlice( slice, len, strict )\n    Returns a normalized Slice object.\n\n    In strict mode, the function returns an error object if an input slice\n    exceeds index bounds.\n\n    A returned error object is a plain object having the following properties:\n\n    - code: error code.\n\n    A returned error object may have one of the following error codes:\n\n    - ERR_SLICE_OUT_OF_BOUNDS: a slice exceeds index bounds.\n\n    Parameters\n    ----------\n    slice: Slice\n        Input slice object.\n\n    len: integer\n        Maximum number of elements allowed in the slice.\n\n    strict: boolean\n        Boolean indicating whether to enforce strict bounds checking.\n\n    Returns\n    -------\n    s: Slice|Object\n        Slice instance (or an error object).\n\n    Examples\n    --------\n    > var s1 = new Slice( 1, 10, 1 );\n    > var s2 = base.normalizeSlice( s1, 5, false );\n    > s2.start\n    1\n    > s2.stop\n    5\n    > s2.step\n    1\n    > s1 = new Slice( -2, null, -1 );\n    > s2 = base.normalizeSlice( s1, 10, false );\n    > s2.start\n    8\n    > s2.stop\n    null\n    > s2.step\n    -1\n\n    See Also\n    --------\n    base.normalizeMultiSlice\n","base.normhermitepoly":"\nbase.normhermitepoly( n, x )\n    Evaluates a normalized Hermite polynomial using double-precision floating-\n    point arithmetic.\n\n    Parameters\n    ----------\n    n: integer\n        Nonnegative polynomial degree.\n\n    x: number\n        Value at which to evaluate the polynomial.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.normhermitepoly( 1, 0.5 )\n    0.5\n    > y = base.normhermitepoly( -1, 0.5 )\n    NaN\n    > y = base.normhermitepoly( 0, 0.5 )\n    1.0\n    > y = base.normhermitepoly( 2, 0.5 )\n    -0.75\n\n\nbase.normhermitepoly.factory( n )\n    Returns a function for evaluating a normalized Hermite polynomial using\n    double-precision floating-point arithmetic.\n\n    Parameters\n    ----------\n    n: integer\n        Nonnegative polynomial degree.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a normalized Hermite polynomial.\n\n    Examples\n    --------\n    > var f = base.normhermitepoly.factory( 2 );\n    > var v = f( 0.5 )\n    -0.75\n\n    See Also\n    --------\n    base.evalpoly, base.hermitepoly\n","base.normhermitepoly.factory":"\nbase.normhermitepoly.factory( n )\n    Returns a function for evaluating a normalized Hermite polynomial using\n    double-precision floating-point arithmetic.\n\n    Parameters\n    ----------\n    n: integer\n        Nonnegative polynomial degree.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a normalized Hermite polynomial.\n\n    Examples\n    --------\n    > var f = base.normhermitepoly.factory( 2 );\n    > var v = f( 0.5 )\n    -0.75\n\n    See Also\n    --------\n    base.evalpoly, base.hermitepoly","base.pascalcase":"\nbase.pascalcase( str )\n    Converts a string to Pascal case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Pascal-cased string.\n\n    Examples\n    --------\n    > var out = base.pascalcase( 'Hello World!' )\n    'HelloWorld'\n    > out = base.pascalcase( 'beep boop' )\n    'BeepBoop'\n\n    See Also\n    --------\n    base.camelcase, base.lowercase, base.uppercase","base.pdiff":"\nbase.pdiff( x, y )\n    Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n    returns `0`.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Positive difference.\n\n    Examples\n    --------\n    > var v = base.pdiff( 5.9, 3.14 )\n    2.76\n    > v = base.pdiff( 3.14, 4.2 )\n    0.0\n    > v = base.pdiff( 3.14, NaN )\n    NaN\n    > v = base.pdiff( -0.0, +0.0 )\n    +0.0\n\n","base.pdifff":"\nbase.pdifff( x, y )\n    Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n    returns `0`.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Positive difference.\n\n    Examples\n    --------\n    > var v = base.pdifff( 5.9, 3.15 )\n    2.75\n    > v = base.pdifff( 3.14, 4.2 )\n    0.0\n    > v = base.pdifff( 3.14, NaN )\n    NaN\n    > v = base.pdifff( -0.0, +0.0 )\n    +0.0\n\n    See Also\n    --------\n    base.pdiff\n","base.percentEncode":"\nbase.percentEncode( str )\n    Percent-encodes a UTF-16 encoded string according to RFC 3986.\n\n    Parameters\n    ----------\n    str: string\n        UTF-16 encoded string.\n\n    Returns\n    -------\n    out: string\n        Percent-encoded string.\n\n    Examples\n    --------\n    > var out = base.percentEncode( '☃' )\n    '%E2%98%83'\n\n","base.polygamma":"\nbase.polygamma( n, x )\n    Evaluates the polygamma function of order `n`; i.e., the (n+1)th derivative\n    of the natural logarithm of the gamma function.\n\n    If `n` is not a nonnegative integer, the function returns `NaN`.\n\n    If `x` is zero or a negative integer, the function returns `NaN`.\n\n    If provided `NaN` as either parameter, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Derivative order.\n\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var v = base.polygamma( 3, 1.2 )\n    ~3.245\n    > v = base.polygamma( 5, 1.2 )\n    ~41.39\n    > v = base.polygamma( 3, -4.9 )\n    ~60014.239\n    > v = base.polygamma( -1, 5.3 )\n    NaN\n    > v = base.polygamma( 2, -1.0 )\n    Infinity\n\n    See Also\n    --------\n    base.trigamma, base.digamma, base.gamma\n","base.pow":"\nbase.pow( b, x )\n    Evaluates the exponential function `bˣ`.\n\n    Parameters\n    ----------\n    b: number\n        Base.\n\n    x: number\n        Exponent.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.pow( 2.0, 3.0 )\n    8.0\n    > y = base.pow( 4.0, 0.5 )\n    2.0\n    > y = base.pow( 100.0, 0.0 )\n    1.0\n    > y = base.pow( PI, 5.0 )\n    ~306.0197\n    > y = base.pow( PI, -0.2 )\n    ~0.7954\n    > y = base.pow( NaN, 3.0 )\n    NaN\n    > y = base.pow( 5.0, NaN )\n    NaN\n    > y = base.pow( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.exp, base.powm1\n","base.powm1":"\nbase.powm1( b, x )\n    Evaluates `bˣ - 1`.\n\n    When `b` is close to `1` and/or `x` is small, this function is more accurate\n    than naively computing `bˣ` and subtracting `1`.\n\n    Parameters\n    ----------\n    b: number\n        Base.\n\n    x: number\n        Exponent.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.powm1( 2.0, 3.0 )\n    7.0\n    > y = base.powm1( 4.0, 0.5 )\n    1.0\n    > y = base.powm1( 0.0, 100.0 )\n    -1.0\n    > y = base.powm1( 100.0, 0.0 )\n    0.0\n    > y = base.powm1( 0.0, 0.0 )\n    0.0\n    > y = base.powm1( PI, 5.0 )\n    ~305.0197\n    > y = base.powm1( NaN, 3.0 )\n    NaN\n    > y = base.powm1( 5.0, NaN )\n    NaN\n\n    See Also\n    --------\n    base.pow\n","base.rad2deg":"\nbase.rad2deg( x )\n    Converts an angle from radians to degrees.\n\n    Parameters\n    ----------\n    x: number\n        Angle in radians.\n\n    Returns\n    -------\n    d: number\n        Angle in degrees.\n\n    Examples\n    --------\n    > var d = base.rad2deg( PI/2.0 )\n    90.0\n    > d = base.rad2deg( -PI/4.0 )\n    -45.0\n    > d = base.rad2deg( NaN )\n    NaN\n\n    // Due to finite precision, canonical values may not be returned:\n    > d = base.rad2deg( PI/6.0 )\n    29.999999999999996\n\n    See Also\n    --------\n    base.deg2rad\n","base.rad2degf":"\nbase.rad2degf( x )\n    Converts an angle from radians to degrees (single-precision).\n\n    Parameters\n    ----------\n    x: number\n        Angle in radians.\n\n    Returns\n    -------\n    d: number\n        Angle in degrees.\n\n    Examples\n    --------\n    > var d = base.rad2degf( 3.141592653589793 / 2.0 )\n    90.0\n    > d = base.rad2degf( -3.141592653589793 / 4.0 )\n    -45.0\n    > d = base.rad2degf( NaN )\n    NaN\n\n    // Due to finite precision, canonical values may not be returned:\n    > d = base.rad2degf( 3.141592653589793 / 6.0 )\n    30.000001907348633\n\n    See Also\n    --------\n    base.rad2deg\n","base.ramp":"\nbase.ramp( x )\n    Evaluates the ramp function.\n\n    If `x >= 0`, the function returns `x`; otherwise, the function returns zero.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.ramp( 3.14 )\n    3.14\n    > y = base.ramp( -3.14 )\n    0.0\n\n    See Also\n    --------\n    base.heaviside\n","base.rampf":"\nbase.rampf( x )\n    Evaluates the ramp function (single-precision).\n\n    If `x >= 0`, the function returns `x`; otherwise, the function returns zero.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.rampf( 3.14 )\n    3.14\n    > y = base.rampf( -3.14 )\n    0.0\n\n    See Also\n    --------\n    base.ramp\n","base.random.arcsine":"\nbase.random.arcsine( a, b )\n    Returns a pseudorandom number drawn from an arcsine distribution.\n\n    If `a >= b`, the function returns `NaN`.\n\n    If `a` or `b` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.arcsine( 2.0, 5.0 )\n    <number>\n\n\nbase.random.arcsine.factory( [a, b, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an arcsine distribution.\n\n    If provided `a` and `b`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `a` and `b`, the returned PRNG requires that both `a` and\n    `b` be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.arcsine.factory();\n    > var r = rand( 0.0, 1.0 )\n    <number>\n    > r = rand( -2.0, 2.0 )\n    <number>\n\n    // Provide `a` and `b`:\n    > rand = base.random.arcsine.factory( 0.0, 1.0 );\n    > r = rand()\n    <number>\n    > r = rand()\n    <number>\n\n\nbase.random.arcsine.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.arcsine.NAME\n    'arcsine'\n\n\nbase.random.arcsine.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.arcsine.PRNG;\n\n\nbase.random.arcsine.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.arcsine.seed;\n\n\nbase.random.arcsine.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.arcsine.seedLength;\n\n\nbase.random.arcsine.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.arcsine.state\n    <Uint32Array>\n\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n\n    // Set the state:\n    > base.random.arcsine.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n\n\nbase.random.arcsine.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.arcsine.stateLength;\n\n\nbase.random.arcsine.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.arcsine.byteLength;\n\n\nbase.random.arcsine.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.arcsine.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.arcsine, random.iterators.arcsine, random.streams.arcsine, base.random.beta\n","base.random.arcsine.factory":"\nbase.random.arcsine.factory( [a, b, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an arcsine distribution.\n\n    If provided `a` and `b`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `a` and `b`, the returned PRNG requires that both `a` and\n    `b` be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.arcsine.factory();\n    > var r = rand( 0.0, 1.0 )\n    <number>\n    > r = rand( -2.0, 2.0 )\n    <number>\n\n    // Provide `a` and `b`:\n    > rand = base.random.arcsine.factory( 0.0, 1.0 );\n    > r = rand()\n    <number>\n    > r = rand()\n    <number>","base.random.arcsine.NAME":"\nbase.random.arcsine.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.arcsine.NAME\n    'arcsine'","base.random.arcsine.PRNG":"\nbase.random.arcsine.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.arcsine.PRNG;","base.random.arcsine.seed":"\nbase.random.arcsine.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.arcsine.seed;","base.random.arcsine.seedLength":"\nbase.random.arcsine.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.arcsine.seedLength;","base.random.arcsine.state":"\nbase.random.arcsine.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.arcsine.state\n    <Uint32Array>\n\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n\n    // Set the state:\n    > base.random.arcsine.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>","base.random.arcsine.stateLength":"\nbase.random.arcsine.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.arcsine.stateLength;","base.random.arcsine.byteLength":"\nbase.random.arcsine.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.arcsine.byteLength;","base.random.arcsine.toJSON":"\nbase.random.arcsine.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.arcsine.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.arcsine, random.iterators.arcsine, random.streams.arcsine, base.random.beta","base.random.bernoulli":"\nbase.random.bernoulli( p )\n    Returns a pseudorandom number drawn from a Bernoulli distribution.\n\n    If `p < 0` or `p > 1` or `p` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.bernoulli( 0.8 );\n\n\nbase.random.bernoulli.factory( [p, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Bernoulli distribution.\n\n    If provided `p`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `p`, the returned PRNG requires that `p` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.bernoulli.factory();\n    > var r = rand( 0.3 );\n    > r = rand( 0.59 );\n\n    // Provide `p`:\n    > rand = base.random.bernoulli.factory( 0.3 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.bernoulli.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.bernoulli.NAME\n    'bernoulli'\n\n\nbase.random.bernoulli.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.bernoulli.PRNG;\n\n\nbase.random.bernoulli.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.bernoulli.seed;\n\n\nbase.random.bernoulli.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.bernoulli.seedLength;\n\n\nbase.random.bernoulli.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.bernoulli( 0.3 )\n    <number>\n    > r = base.random.bernoulli( 0.3 )\n    <number>\n    > r = base.random.bernoulli( 0.3 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.bernoulli.state\n    <Uint32Array>\n\n    > r = base.random.bernoulli( 0.3 )\n    <number>\n    > r = base.random.bernoulli( 0.3 )\n    <number>\n\n    // Set the state:\n    > base.random.bernoulli.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.bernoulli( 0.3 )\n    <number>\n    > r = base.random.bernoulli( 0.3 )\n    <number>\n\n\nbase.random.bernoulli.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.bernoulli.stateLength;\n\n\nbase.random.bernoulli.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.bernoulli.byteLength;\n\n\nbase.random.bernoulli.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.bernoulli.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.bernoulli, random.iterators.bernoulli, random.streams.bernoulli, base.random.binomial\n","base.random.bernoulli.factory":"\nbase.random.bernoulli.factory( [p, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Bernoulli distribution.\n\n    If provided `p`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `p`, the returned PRNG requires that `p` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.bernoulli.factory();\n    > var r = rand( 0.3 );\n    > r = rand( 0.59 );\n\n    // Provide `p`:\n    > rand = base.random.bernoulli.factory( 0.3 );\n    > r = rand();\n    > r = rand();","base.random.bernoulli.NAME":"\nbase.random.bernoulli.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.bernoulli.NAME\n    'bernoulli'","base.random.bernoulli.PRNG":"\nbase.random.bernoulli.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.bernoulli.PRNG;","base.random.bernoulli.seed":"\nbase.random.bernoulli.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.bernoulli.seed;","base.random.bernoulli.seedLength":"\nbase.random.bernoulli.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.bernoulli.seedLength;","base.random.bernoulli.state":"\nbase.random.bernoulli.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.bernoulli( 0.3 )\n    <number>\n    > r = base.random.bernoulli( 0.3 )\n    <number>\n    > r = base.random.bernoulli( 0.3 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.bernoulli.state\n    <Uint32Array>\n\n    > r = base.random.bernoulli( 0.3 )\n    <number>\n    > r = base.random.bernoulli( 0.3 )\n    <number>\n\n    // Set the state:\n    > base.random.bernoulli.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.bernoulli( 0.3 )\n    <number>\n    > r = base.random.bernoulli( 0.3 )\n    <number>","base.random.bernoulli.stateLength":"\nbase.random.bernoulli.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.bernoulli.stateLength;","base.random.bernoulli.byteLength":"\nbase.random.bernoulli.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.bernoulli.byteLength;","base.random.bernoulli.toJSON":"\nbase.random.bernoulli.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.bernoulli.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.bernoulli, random.iterators.bernoulli, random.streams.bernoulli, base.random.binomial","base.random.beta":"\nbase.random.beta( α, β )\n    Returns a pseudorandom number drawn from a beta distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.beta( 2.0, 5.0 );\n\n\nbase.random.beta.factory( [α, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a beta distribution.\n\n    If provided `α` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `α` and `β`, the returned PRNG requires that both `α` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        First shape parameter.\n\n    β: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.beta.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `α` and `β`:\n    > rand = base.random.beta.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.beta.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.beta.NAME\n    'beta'\n\n\nbase.random.beta.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.beta.PRNG;\n\n\nbase.random.beta.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.beta.seed;\n\n\nbase.random.beta.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.beta.seedLength;\n\n\nbase.random.beta.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.beta( 2.0, 5.0 )\n    <number>\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.beta.state\n    <Uint32Array>\n\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.beta.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>\n\n\nbase.random.beta.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.beta.stateLength;\n\n\nbase.random.beta.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.beta.byteLength;\n\n\nbase.random.beta.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.beta.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.beta, random.iterators.beta, random.streams.beta\n","base.random.beta.factory":"\nbase.random.beta.factory( [α, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a beta distribution.\n\n    If provided `α` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `α` and `β`, the returned PRNG requires that both `α` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        First shape parameter.\n\n    β: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.beta.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `α` and `β`:\n    > rand = base.random.beta.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.beta.NAME":"\nbase.random.beta.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.beta.NAME\n    'beta'","base.random.beta.PRNG":"\nbase.random.beta.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.beta.PRNG;","base.random.beta.seed":"\nbase.random.beta.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.beta.seed;","base.random.beta.seedLength":"\nbase.random.beta.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.beta.seedLength;","base.random.beta.state":"\nbase.random.beta.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.beta( 2.0, 5.0 )\n    <number>\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.beta.state\n    <Uint32Array>\n\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.beta.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>","base.random.beta.stateLength":"\nbase.random.beta.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.beta.stateLength;","base.random.beta.byteLength":"\nbase.random.beta.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.beta.byteLength;","base.random.beta.toJSON":"\nbase.random.beta.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.beta.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.beta, random.iterators.beta, random.streams.beta","base.random.betaprime":"\nbase.random.betaprime( α, β )\n    Returns a pseudorandom number drawn from a beta prime distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.betaprime( 2.0, 5.0 );\n\n\nbase.random.betaprime.factory( [α, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a beta prime distribution.\n\n    If provided `α` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `α` and `β`, the returned PRNG requires that both `α` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        First shape parameter.\n\n    β: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.betaprime.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `α` and `β`:\n    > rand = base.random.betaprime.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.betaprime.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.betaprime.NAME\n    'betaprime'\n\n\nbase.random.betaprime.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.betaprime.PRNG;\n\n\nbase.random.betaprime.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.betaprime.seed;\n\n\nbase.random.betaprime.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.betaprime.seedLength;\n\n\nbase.random.betaprime.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.betaprime.state\n    <Uint32Array>\n\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.betaprime.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n\n\nbase.random.betaprime.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.betaprime.stateLength;\n\n\nbase.random.betaprime.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.betaprime.byteLength;\n\n\nbase.random.betaprime.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.betaprime.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.betaprime, random.iterators.betaprime, random.streams.betaprime\n","base.random.betaprime.factory":"\nbase.random.betaprime.factory( [α, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a beta prime distribution.\n\n    If provided `α` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `α` and `β`, the returned PRNG requires that both `α` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        First shape parameter.\n\n    β: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.betaprime.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `α` and `β`:\n    > rand = base.random.betaprime.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.betaprime.NAME":"\nbase.random.betaprime.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.betaprime.NAME\n    'betaprime'","base.random.betaprime.PRNG":"\nbase.random.betaprime.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.betaprime.PRNG;","base.random.betaprime.seed":"\nbase.random.betaprime.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.betaprime.seed;","base.random.betaprime.seedLength":"\nbase.random.betaprime.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.betaprime.seedLength;","base.random.betaprime.state":"\nbase.random.betaprime.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.betaprime.state\n    <Uint32Array>\n\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.betaprime.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>","base.random.betaprime.stateLength":"\nbase.random.betaprime.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.betaprime.stateLength;","base.random.betaprime.byteLength":"\nbase.random.betaprime.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.betaprime.byteLength;","base.random.betaprime.toJSON":"\nbase.random.betaprime.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.betaprime.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.betaprime, random.iterators.betaprime, random.streams.betaprime","base.random.binomial":"\nbase.random.binomial( n, p )\n    Returns a pseudorandom number drawn from a binomial distribution.\n\n    If `n` is not a positive integer or `p` is not a probability, the function\n    returns `NaN`.\n\n    If `n` or `p` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.binomial( 20, 0.8 );\n\n\nbase.random.binomial.factory( [n, p, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a binomial distribution.\n\n    If provided `n` and `p`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `n` and `p`, the returned PRNG requires that both `n` and\n    `p` be provided at each invocation.\n\n    Parameters\n    ----------\n    n: integer (optional)\n        Number of trials.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.binomial.factory();\n    > var r = rand( 20, 0.3 );\n    > r = rand( 10, 0.77 );\n\n    // Provide `n` and `p`:\n    > rand = base.random.binomial.factory( 10, 0.8 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.binomial.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.binomial.NAME\n    'binomial'\n\n\nbase.random.binomial.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.binomial.PRNG;\n\n\nbase.random.binomial.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.binomial.seed;\n\n\nbase.random.binomial.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.binomial.seedLength;\n\n\nbase.random.binomial.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.binomial( 20, 0.8 )\n    <number>\n    > r = base.random.binomial( 20, 0.8 )\n    <number>\n    > r = base.random.binomial( 20, 0.8 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.binomial.state\n    <Uint32Array>\n\n    > r = base.random.binomial( 20, 0.8 )\n    <number>\n    > r = base.random.binomial( 20, 0.8 )\n    <number>\n\n    // Set the state:\n    > base.random.binomial.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.binomial( 20, 0.8 )\n    <number>\n    > r = base.random.binomial( 20, 0.8 )\n    <number>\n\n\nbase.random.binomial.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.binomial.stateLength;\n\n\nbase.random.binomial.byteLength\n    Size of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.binomial.byteLength;\n\n\nbase.random.binomial.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.binomial.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.binomial, random.iterators.binomial, random.streams.binomial\n","base.random.binomial.factory":"\nbase.random.binomial.factory( [n, p, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a binomial distribution.\n\n    If provided `n` and `p`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `n` and `p`, the returned PRNG requires that both `n` and\n    `p` be provided at each invocation.\n\n    Parameters\n    ----------\n    n: integer (optional)\n        Number of trials.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.binomial.factory();\n    > var r = rand( 20, 0.3 );\n    > r = rand( 10, 0.77 );\n\n    // Provide `n` and `p`:\n    > rand = base.random.binomial.factory( 10, 0.8 );\n    > r = rand();\n    > r = rand();","base.random.binomial.NAME":"\nbase.random.binomial.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.binomial.NAME\n    'binomial'","base.random.binomial.PRNG":"\nbase.random.binomial.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.binomial.PRNG;","base.random.binomial.seed":"\nbase.random.binomial.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.binomial.seed;","base.random.binomial.seedLength":"\nbase.random.binomial.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.binomial.seedLength;","base.random.binomial.state":"\nbase.random.binomial.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.binomial( 20, 0.8 )\n    <number>\n    > r = base.random.binomial( 20, 0.8 )\n    <number>\n    > r = base.random.binomial( 20, 0.8 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.binomial.state\n    <Uint32Array>\n\n    > r = base.random.binomial( 20, 0.8 )\n    <number>\n    > r = base.random.binomial( 20, 0.8 )\n    <number>\n\n    // Set the state:\n    > base.random.binomial.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.binomial( 20, 0.8 )\n    <number>\n    > r = base.random.binomial( 20, 0.8 )\n    <number>","base.random.binomial.stateLength":"\nbase.random.binomial.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.binomial.stateLength;","base.random.binomial.byteLength":"\nbase.random.binomial.byteLength\n    Size of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.binomial.byteLength;","base.random.binomial.toJSON":"\nbase.random.binomial.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.binomial.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.binomial, random.iterators.binomial, random.streams.binomial","base.random.boxMuller":"\nbase.random.boxMuller()\n    Returns a pseudorandom number drawn from a standard normal distribution.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.boxMuller();\n\n\nbase.random.boxMuller.factory( [options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a standard normal distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.boxMuller.factory();\n    > r = rand();\n    > r = rand();\n\n\nbase.random.boxMuller.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.boxMuller.NAME\n    'box-muller'\n\n\nbase.random.boxMuller.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.boxMuller.PRNG;\n\n\nbase.random.boxMuller.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.boxMuller.seed;\n\n\nbase.random.boxMuller.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.boxMuller.seedLength;\n\n\nbase.random.boxMuller.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.boxMuller()\n    <number>\n    > r = base.random.boxMuller()\n    <number>\n    > r = base.random.boxMuller()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.boxMuller.state\n    <Uint32Array>\n\n    > r = base.random.boxMuller()\n    <number>\n    > r = base.random.boxMuller()\n    <number>\n\n    // Set the state:\n    > base.random.boxMuller.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.boxMuller()\n    <number>\n    > r = base.random.boxMuller()\n    <number>\n\n\nbase.random.boxMuller.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.boxMuller.stateLength;\n\n\nbase.random.boxMuller.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.boxMuller.byteLength;\n\n\nbase.random.boxMuller.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.boxMuller.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.iterators.boxMuller, random.streams.boxMuller\n","base.random.boxMuller.factory":"\nbase.random.boxMuller.factory( [options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a standard normal distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.boxMuller.factory();\n    > r = rand();\n    > r = rand();","base.random.boxMuller.NAME":"\nbase.random.boxMuller.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.boxMuller.NAME\n    'box-muller'","base.random.boxMuller.PRNG":"\nbase.random.boxMuller.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.boxMuller.PRNG;","base.random.boxMuller.seed":"\nbase.random.boxMuller.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.boxMuller.seed;","base.random.boxMuller.seedLength":"\nbase.random.boxMuller.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.boxMuller.seedLength;","base.random.boxMuller.state":"\nbase.random.boxMuller.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.boxMuller()\n    <number>\n    > r = base.random.boxMuller()\n    <number>\n    > r = base.random.boxMuller()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.boxMuller.state\n    <Uint32Array>\n\n    > r = base.random.boxMuller()\n    <number>\n    > r = base.random.boxMuller()\n    <number>\n\n    // Set the state:\n    > base.random.boxMuller.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.boxMuller()\n    <number>\n    > r = base.random.boxMuller()\n    <number>","base.random.boxMuller.stateLength":"\nbase.random.boxMuller.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.boxMuller.stateLength;","base.random.boxMuller.byteLength":"\nbase.random.boxMuller.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.boxMuller.byteLength;","base.random.boxMuller.toJSON":"\nbase.random.boxMuller.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.boxMuller.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.iterators.boxMuller, random.streams.boxMuller","base.random.cauchy":"\nbase.random.cauchy( x0, Ɣ )\n    Returns a pseudorandom number drawn from a Cauchy distribution.\n\n    If `x0` or `Ɣ` is `NaN` or `Ɣ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.cauchy( 2.0, 5.0 );\n\n\nbase.random.cauchy.factory( [x0, Ɣ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Cauchy distribution.\n\n    If provided `x0` and `Ɣ`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `x0` and `Ɣ`, the returned PRNG requires that both `x0` and\n    `Ɣ` be provided at each invocation.\n\n    Parameters\n    ----------\n    x0: number (optional)\n        Location parameter.\n\n    Ɣ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.cauchy.factory();\n    > var r = rand( 0.0, 1.5 );\n    > r = rand( -2.0, 2.0 );\n\n    // Provide `x0` and `Ɣ`:\n    > rand = base.random.cauchy.factory( 0.0, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.cauchy.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.cauchy.NAME\n    'cauchy'\n\n\nbase.random.cauchy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.cauchy.PRNG;\n\n\nbase.random.cauchy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.cauchy.seed;\n\n\nbase.random.cauchy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.cauchy.seedLength;\n\n\nbase.random.cauchy.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.cauchy.state\n    <Uint32Array>\n\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.cauchy.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n\n\nbase.random.cauchy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.cauchy.stateLength;\n\n\nbase.random.cauchy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.cauchy.byteLength;\n\n\nbase.random.cauchy.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.cauchy.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.cauchy, random.iterators.cauchy, random.streams.cauchy\n","base.random.cauchy.factory":"\nbase.random.cauchy.factory( [x0, Ɣ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Cauchy distribution.\n\n    If provided `x0` and `Ɣ`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `x0` and `Ɣ`, the returned PRNG requires that both `x0` and\n    `Ɣ` be provided at each invocation.\n\n    Parameters\n    ----------\n    x0: number (optional)\n        Location parameter.\n\n    Ɣ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.cauchy.factory();\n    > var r = rand( 0.0, 1.5 );\n    > r = rand( -2.0, 2.0 );\n\n    // Provide `x0` and `Ɣ`:\n    > rand = base.random.cauchy.factory( 0.0, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.cauchy.NAME":"\nbase.random.cauchy.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.cauchy.NAME\n    'cauchy'","base.random.cauchy.PRNG":"\nbase.random.cauchy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.cauchy.PRNG;","base.random.cauchy.seed":"\nbase.random.cauchy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.cauchy.seed;","base.random.cauchy.seedLength":"\nbase.random.cauchy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.cauchy.seedLength;","base.random.cauchy.state":"\nbase.random.cauchy.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.cauchy.state\n    <Uint32Array>\n\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.cauchy.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>","base.random.cauchy.stateLength":"\nbase.random.cauchy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.cauchy.stateLength;","base.random.cauchy.byteLength":"\nbase.random.cauchy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.cauchy.byteLength;","base.random.cauchy.toJSON":"\nbase.random.cauchy.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.cauchy.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.cauchy, random.iterators.cauchy, random.streams.cauchy","base.random.chi":"\nbase.random.chi( k )\n    Returns a pseudorandom number drawn from a chi distribution.\n\n    If `k <= 0` or `k` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.chi( 2 );\n\n\nbase.random.chi.factory( [k, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a chi distribution.\n\n    If provided `k`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `k`, the returned PRNG requires that `k` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.chi.factory();\n    > var r = rand( 5 );\n    > r = rand( 3.14 );\n\n    // Provide `k`:\n    > rand = base.random.chi.factory( 3 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.chi.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.chi.NAME\n    'chi'\n\n\nbase.random.chi.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.chi.PRNG;\n\n\nbase.random.chi.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.chi.seed;\n\n\nbase.random.chi.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.chi.seedLength;\n\n\nbase.random.chi.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.chi( 2 )\n    <number>\n    > r = base.random.chi( 2 )\n    <number>\n    > r = base.random.chi( 2 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.chi.state\n    <Uint32Array>\n\n    > r = base.random.chi( 2 )\n    <number>\n    > r = base.random.chi( 2 )\n    <number>\n\n    // Set the state:\n    > base.random.chi.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.chi( 2 )\n    <number>\n    > r = base.random.chi( 2 )\n    <number>\n\n\nbase.random.chi.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.chi.stateLength;\n\n\nbase.random.chi.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.chi.byteLength;\n\n\nbase.random.chi.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.chi.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.chi, random.iterators.chi, random.streams.chi\n","base.random.chi.factory":"\nbase.random.chi.factory( [k, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a chi distribution.\n\n    If provided `k`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `k`, the returned PRNG requires that `k` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.chi.factory();\n    > var r = rand( 5 );\n    > r = rand( 3.14 );\n\n    // Provide `k`:\n    > rand = base.random.chi.factory( 3 );\n    > r = rand();\n    > r = rand();","base.random.chi.NAME":"\nbase.random.chi.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.chi.NAME\n    'chi'","base.random.chi.PRNG":"\nbase.random.chi.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.chi.PRNG;","base.random.chi.seed":"\nbase.random.chi.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.chi.seed;","base.random.chi.seedLength":"\nbase.random.chi.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.chi.seedLength;","base.random.chi.state":"\nbase.random.chi.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.chi( 2 )\n    <number>\n    > r = base.random.chi( 2 )\n    <number>\n    > r = base.random.chi( 2 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.chi.state\n    <Uint32Array>\n\n    > r = base.random.chi( 2 )\n    <number>\n    > r = base.random.chi( 2 )\n    <number>\n\n    // Set the state:\n    > base.random.chi.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.chi( 2 )\n    <number>\n    > r = base.random.chi( 2 )\n    <number>","base.random.chi.stateLength":"\nbase.random.chi.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.chi.stateLength;","base.random.chi.byteLength":"\nbase.random.chi.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.chi.byteLength;","base.random.chi.toJSON":"\nbase.random.chi.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.chi.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.chi, random.iterators.chi, random.streams.chi","base.random.chisquare":"\nbase.random.chisquare( k )\n    Returns a pseudorandom number drawn from a chi-square distribution.\n\n    If `k <= 0` or `k` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.chisquare( 2 );\n\n\nbase.random.chisquare.factory( [k, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a chi-square distribution.\n\n    If provided `k`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `k`, the returned PRNG requires that `k` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.chisquare.factory();\n    > var r = rand( 5 );\n    > r = rand( 3.14 );\n\n    // Provide `k`:\n    > rand = base.random.chisquare.factory( 3 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.chisquare.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.chisquare.NAME\n    'chisquare'\n\n\nbase.random.chisquare.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.chisquare.PRNG;\n\n\nbase.random.chisquare.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.chisquare.seed;\n\n\nbase.random.chisquare.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.chisquare.seedLength;\n\n\nbase.random.chisquare.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.chisquare( 2 )\n    <number>\n    > r = base.random.chisquare( 2 )\n    <number>\n    > r = base.random.chisquare( 2 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.chisquare.state\n    <Uint32Array>\n\n    > r = base.random.chisquare( 2 )\n    <number>\n    > r = base.random.chisquare( 2 )\n    <number>\n\n    // Set the state:\n    > base.random.chisquare.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.chisquare( 2 )\n    <number>\n    > r = base.random.chisquare( 2 )\n    <number>\n\n\nbase.random.chisquare.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.chisquare.stateLength;\n\n\nbase.random.chisquare.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.chisquare.byteLength;\n\n\nbase.random.chisquare.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.chisquare.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.chisquare, random.iterators.chisquare, random.streams.chisquare\n","base.random.chisquare.factory":"\nbase.random.chisquare.factory( [k, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a chi-square distribution.\n\n    If provided `k`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `k`, the returned PRNG requires that `k` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.chisquare.factory();\n    > var r = rand( 5 );\n    > r = rand( 3.14 );\n\n    // Provide `k`:\n    > rand = base.random.chisquare.factory( 3 );\n    > r = rand();\n    > r = rand();","base.random.chisquare.NAME":"\nbase.random.chisquare.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.chisquare.NAME\n    'chisquare'","base.random.chisquare.PRNG":"\nbase.random.chisquare.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.chisquare.PRNG;","base.random.chisquare.seed":"\nbase.random.chisquare.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.chisquare.seed;","base.random.chisquare.seedLength":"\nbase.random.chisquare.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.chisquare.seedLength;","base.random.chisquare.state":"\nbase.random.chisquare.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.chisquare( 2 )\n    <number>\n    > r = base.random.chisquare( 2 )\n    <number>\n    > r = base.random.chisquare( 2 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.chisquare.state\n    <Uint32Array>\n\n    > r = base.random.chisquare( 2 )\n    <number>\n    > r = base.random.chisquare( 2 )\n    <number>\n\n    // Set the state:\n    > base.random.chisquare.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.chisquare( 2 )\n    <number>\n    > r = base.random.chisquare( 2 )\n    <number>","base.random.chisquare.stateLength":"\nbase.random.chisquare.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.chisquare.stateLength;","base.random.chisquare.byteLength":"\nbase.random.chisquare.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.chisquare.byteLength;","base.random.chisquare.toJSON":"\nbase.random.chisquare.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.chisquare.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.chisquare, random.iterators.chisquare, random.streams.chisquare","base.random.cosine":"\nbase.random.cosine( μ, s )\n    Returns a pseudorandom number drawn from a raised cosine distribution.\n\n    If `μ` or `s` is `NaN` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.cosine( 2.0, 5.0 );\n\n\nbase.random.cosine.factory( [μ, s, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a raised cosine distribution.\n\n    If provided `μ` and `s`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n    `s` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.cosine.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `s`:\n    > rand = base.random.cosine.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.cosine.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.cosine.NAME\n    'cosine'\n\n\nbase.random.cosine.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.cosine.PRNG;\n\n\nbase.random.cosine.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.cosine.seed;\n\n\nbase.random.cosine.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.cosine.seedLength;\n\n\nbase.random.cosine.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.cosine( 2.0, 5.0 )\n    <number>\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.cosine.state\n    <Uint32Array>\n\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.cosine.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>\n\n\nbase.random.cosine.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.cosine.stateLength;\n\n\nbase.random.cosine.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.cosine.byteLength;\n\n\nbase.random.cosine.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.cosine.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.cosine, random.iterators.cosine, random.streams.cosine\n","base.random.cosine.factory":"\nbase.random.cosine.factory( [μ, s, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a raised cosine distribution.\n\n    If provided `μ` and `s`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n    `s` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.cosine.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `s`:\n    > rand = base.random.cosine.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.cosine.NAME":"\nbase.random.cosine.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.cosine.NAME\n    'cosine'","base.random.cosine.PRNG":"\nbase.random.cosine.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.cosine.PRNG;","base.random.cosine.seed":"\nbase.random.cosine.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.cosine.seed;","base.random.cosine.seedLength":"\nbase.random.cosine.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.cosine.seedLength;","base.random.cosine.state":"\nbase.random.cosine.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.cosine( 2.0, 5.0 )\n    <number>\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.cosine.state\n    <Uint32Array>\n\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.cosine.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>","base.random.cosine.stateLength":"\nbase.random.cosine.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.cosine.stateLength;","base.random.cosine.byteLength":"\nbase.random.cosine.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.cosine.byteLength;","base.random.cosine.toJSON":"\nbase.random.cosine.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.cosine.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.cosine, random.iterators.cosine, random.streams.cosine","base.random.discreteUniform":"\nbase.random.discreteUniform( a, b )\n    Returns a pseudorandom number drawn from a discrete uniform distribution.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.discreteUniform( 2, 50 );\n\n\nbase.random.discreteUniform.factory( [a, b, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a discrete uniform distribution.\n\n    If provided `a` and `b`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `a` and `b`, the returned PRNG requires that both `a` and\n    `b` be provided at each invocation.\n\n    Parameters\n    ----------\n    a: integer (optional)\n        Minimum support.\n\n    b: integer (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom integers. If provided, the `state` and `seed`\n        options are ignored. In order to seed the returned pseudorandom number\n        generator, one must seed the provided `prng` (assuming the provided\n        `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n        properties specifying the minimum and maximum possible pseudorandom\n        integers.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.discreteUniform.factory();\n    > var r = rand( 0, 10 );\n    > r = rand( -20, 20 );\n\n    // Provide `a` and `b`:\n    > rand = base.random.discreteUniform.factory( 0, 10 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.discreteUniform.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.discreteUniform.NAME\n    'discrete-uniform'\n\n\nbase.random.discreteUniform.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.discreteUniform.PRNG;\n\n\nbase.random.discreteUniform.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.discreteUniform.seed;\n\n\nbase.random.discreteUniform.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.discreteUniform.seedLength;\n\n\nbase.random.discreteUniform.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.discreteUniform( 2, 50 )\n    <number>\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.discreteUniform.state\n    <Uint32Array>\n\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>\n\n    // Set the state:\n    > base.random.discreteUniform.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>\n\n\nbase.random.discreteUniform.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.discreteUniform.stateLength;\n\n\nbase.random.discreteUniform.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.discreteUniform.byteLength;\n\n\nbase.random.discreteUniform.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.discreteUniform.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.discreteUniform, random.iterators.discreteUniform, random.streams.discreteUniform\n","base.random.discreteUniform.factory":"\nbase.random.discreteUniform.factory( [a, b, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a discrete uniform distribution.\n\n    If provided `a` and `b`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `a` and `b`, the returned PRNG requires that both `a` and\n    `b` be provided at each invocation.\n\n    Parameters\n    ----------\n    a: integer (optional)\n        Minimum support.\n\n    b: integer (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom integers. If provided, the `state` and `seed`\n        options are ignored. In order to seed the returned pseudorandom number\n        generator, one must seed the provided `prng` (assuming the provided\n        `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n        properties specifying the minimum and maximum possible pseudorandom\n        integers.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.discreteUniform.factory();\n    > var r = rand( 0, 10 );\n    > r = rand( -20, 20 );\n\n    // Provide `a` and `b`:\n    > rand = base.random.discreteUniform.factory( 0, 10 );\n    > r = rand();\n    > r = rand();","base.random.discreteUniform.NAME":"\nbase.random.discreteUniform.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.discreteUniform.NAME\n    'discrete-uniform'","base.random.discreteUniform.PRNG":"\nbase.random.discreteUniform.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.discreteUniform.PRNG;","base.random.discreteUniform.seed":"\nbase.random.discreteUniform.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.discreteUniform.seed;","base.random.discreteUniform.seedLength":"\nbase.random.discreteUniform.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.discreteUniform.seedLength;","base.random.discreteUniform.state":"\nbase.random.discreteUniform.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.discreteUniform( 2, 50 )\n    <number>\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.discreteUniform.state\n    <Uint32Array>\n\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>\n\n    // Set the state:\n    > base.random.discreteUniform.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>","base.random.discreteUniform.stateLength":"\nbase.random.discreteUniform.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.discreteUniform.stateLength;","base.random.discreteUniform.byteLength":"\nbase.random.discreteUniform.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.discreteUniform.byteLength;","base.random.discreteUniform.toJSON":"\nbase.random.discreteUniform.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.discreteUniform.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.discreteUniform, random.iterators.discreteUniform, random.streams.discreteUniform","base.random.erlang":"\nbase.random.erlang( k, λ )\n    Returns a pseudorandom number drawn from an Erlang distribution.\n\n    If `k` is not a positive integer or `λ <= 0`, the function returns `NaN`.\n\n    If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: integer\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.erlang( 2, 5.0 );\n\n\nbase.random.erlang.factory( [k, λ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an Erlang distribution.\n\n    If provided `k` and `λ`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `k` and `λ`, the returned PRNG requires that both `k` and\n    `λ` be provided at each invocation.\n\n    Parameters\n    ----------\n    k: integer (optional)\n        Shape parameter.\n\n    λ: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.erlang.factory();\n    > var r = rand( 2, 1.0 );\n    > r = rand( 4, 3.14 );\n\n    // Provide `k` and `λ`:\n    > rand = base.random.erlang.factory( 2, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.erlang.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.erlang.NAME\n    'erlang'\n\n\nbase.random.erlang.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.erlang.PRNG;\n\n\nbase.random.erlang.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.erlang.seed;\n\n\nbase.random.erlang.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.erlang.seedLength;\n\n\nbase.random.erlang.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.erlang( 2, 5.0 )\n    <number>\n    > r = base.random.erlang( 2, 5.0 )\n    <number>\n    > r = base.random.erlang( 2, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.erlang.state\n    <Uint32Array>\n\n    > r = base.random.erlang( 2, 5.0 )\n    <number>\n    > r = base.random.erlang( 2, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.erlang.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.erlang( 2, 5.0 )\n    <number>\n    > r = base.random.erlang( 2, 5.0 )\n    <number>\n\n\nbase.random.erlang.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.erlang.stateLength;\n\n\nbase.random.erlang.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.erlang.byteLength;\n\n\nbase.random.erlang.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.erlang.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.erlang, random.iterators.erlang, random.streams.erlang\n","base.random.erlang.factory":"\nbase.random.erlang.factory( [k, λ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an Erlang distribution.\n\n    If provided `k` and `λ`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `k` and `λ`, the returned PRNG requires that both `k` and\n    `λ` be provided at each invocation.\n\n    Parameters\n    ----------\n    k: integer (optional)\n        Shape parameter.\n\n    λ: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.erlang.factory();\n    > var r = rand( 2, 1.0 );\n    > r = rand( 4, 3.14 );\n\n    // Provide `k` and `λ`:\n    > rand = base.random.erlang.factory( 2, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.erlang.NAME":"\nbase.random.erlang.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.erlang.NAME\n    'erlang'","base.random.erlang.PRNG":"\nbase.random.erlang.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.erlang.PRNG;","base.random.erlang.seed":"\nbase.random.erlang.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.erlang.seed;","base.random.erlang.seedLength":"\nbase.random.erlang.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.erlang.seedLength;","base.random.erlang.state":"\nbase.random.erlang.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.erlang( 2, 5.0 )\n    <number>\n    > r = base.random.erlang( 2, 5.0 )\n    <number>\n    > r = base.random.erlang( 2, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.erlang.state\n    <Uint32Array>\n\n    > r = base.random.erlang( 2, 5.0 )\n    <number>\n    > r = base.random.erlang( 2, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.erlang.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.erlang( 2, 5.0 )\n    <number>\n    > r = base.random.erlang( 2, 5.0 )\n    <number>","base.random.erlang.stateLength":"\nbase.random.erlang.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.erlang.stateLength;","base.random.erlang.byteLength":"\nbase.random.erlang.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.erlang.byteLength;","base.random.erlang.toJSON":"\nbase.random.erlang.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.erlang.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.erlang, random.iterators.erlang, random.streams.erlang","base.random.exponential":"\nbase.random.exponential( λ )\n    Returns a pseudorandom number drawn from an exponential distribution.\n\n    If `λ <= 0` or `λ` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.exponential( 7.9 );\n\n\nbase.random.exponential.factory( [λ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an exponential distribution.\n\n    If provided `λ`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    λ: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.exponential.factory();\n    > var r = rand( 5.0 );\n    > r = rand( 3.14 );\n\n    // Provide `λ`:\n    > rand = base.random.exponential.factory( 10.0 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.exponential.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.exponential.NAME\n    'exponential'\n\n\nbase.random.exponential.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.exponential.PRNG;\n\n\nbase.random.exponential.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.exponential.seed;\n\n\nbase.random.exponential.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.exponential.seedLength;\n\n\nbase.random.exponential.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.exponential( 7.9 )\n    <number>\n    > r = base.random.exponential( 7.9 )\n    <number>\n    > r = base.random.exponential( 7.9 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.exponential.state\n    <Uint32Array>\n\n    > r = base.random.exponential( 7.9 )\n    <number>\n    > r = base.random.exponential( 7.9 )\n    <number>\n\n    // Set the state:\n    > base.random.exponential.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.exponential( 7.9 )\n    <number>\n    > r = base.random.exponential( 7.9 )\n    <number>\n\n\nbase.random.exponential.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.exponential.stateLength;\n\n\nbase.random.exponential.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.exponential.byteLength;\n\n\nbase.random.exponential.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.exponential.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.exponential, random.iterators.exponential, random.streams.exponential\n","base.random.exponential.factory":"\nbase.random.exponential.factory( [λ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an exponential distribution.\n\n    If provided `λ`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    λ: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.exponential.factory();\n    > var r = rand( 5.0 );\n    > r = rand( 3.14 );\n\n    // Provide `λ`:\n    > rand = base.random.exponential.factory( 10.0 );\n    > r = rand();\n    > r = rand();","base.random.exponential.NAME":"\nbase.random.exponential.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.exponential.NAME\n    'exponential'","base.random.exponential.PRNG":"\nbase.random.exponential.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.exponential.PRNG;","base.random.exponential.seed":"\nbase.random.exponential.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.exponential.seed;","base.random.exponential.seedLength":"\nbase.random.exponential.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.exponential.seedLength;","base.random.exponential.state":"\nbase.random.exponential.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.exponential( 7.9 )\n    <number>\n    > r = base.random.exponential( 7.9 )\n    <number>\n    > r = base.random.exponential( 7.9 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.exponential.state\n    <Uint32Array>\n\n    > r = base.random.exponential( 7.9 )\n    <number>\n    > r = base.random.exponential( 7.9 )\n    <number>\n\n    // Set the state:\n    > base.random.exponential.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.exponential( 7.9 )\n    <number>\n    > r = base.random.exponential( 7.9 )\n    <number>","base.random.exponential.stateLength":"\nbase.random.exponential.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.exponential.stateLength;","base.random.exponential.byteLength":"\nbase.random.exponential.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.exponential.byteLength;","base.random.exponential.toJSON":"\nbase.random.exponential.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.exponential.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.exponential, random.iterators.exponential, random.streams.exponential","base.random.f":"\nbase.random.f( d1, d2 )\n    Returns a pseudorandom number drawn from an F distribution.\n\n    If `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n    If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    d1: number\n        Degrees of freedom.\n\n    d2: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.f( 2.0, 5.0 );\n\n\nbase.random.f.factory( [d1, d2, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an F distribution.\n\n    If provided `d1` and `d2`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `d1` and `d2`, the returned PRNG requires that both `d1` and\n    `d2` be provided at each invocation.\n\n    Parameters\n    ----------\n    d1: number (optional)\n        Degrees of freedom.\n\n    d2: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.f.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 3.0, 3.14 );\n\n    // Provide `d1` and `d2`:\n    > rand = base.random.f.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.f.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.f.NAME\n    'f'\n\n\nbase.random.f.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.f.PRNG;\n\n\nbase.random.f.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.f.seed;\n\n\nbase.random.f.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.f.seedLength;\n\n\nbase.random.f.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.f( 1.5, 1.5 )\n    <number>\n    > r = base.random.f( 1.5, 1.5 )\n    <number>\n    > r = base.random.f( 1.5, 1.5 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.f.state\n    <Uint32Array>\n\n    > r = base.random.f( 1.5, 1.5 )\n    <number>\n    > r = base.random.f( 1.5, 1.5 )\n    <number>\n\n    // Set the state:\n    > base.random.f.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.f( 1.5, 1.5 )\n    <number>\n    > r = base.random.f( 1.5, 1.5 )\n    <number>\n\n\nbase.random.f.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.f.stateLength;\n\n\nbase.random.f.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.f.byteLength;\n\n\nbase.random.f.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.f.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.f, random.iterators.f, random.streams.f\n","base.random.f.factory":"\nbase.random.f.factory( [d1, d2, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an F distribution.\n\n    If provided `d1` and `d2`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `d1` and `d2`, the returned PRNG requires that both `d1` and\n    `d2` be provided at each invocation.\n\n    Parameters\n    ----------\n    d1: number (optional)\n        Degrees of freedom.\n\n    d2: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.f.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 3.0, 3.14 );\n\n    // Provide `d1` and `d2`:\n    > rand = base.random.f.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.f.NAME":"\nbase.random.f.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.f.NAME\n    'f'","base.random.f.PRNG":"\nbase.random.f.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.f.PRNG;","base.random.f.seed":"\nbase.random.f.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.f.seed;","base.random.f.seedLength":"\nbase.random.f.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.f.seedLength;","base.random.f.state":"\nbase.random.f.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.f( 1.5, 1.5 )\n    <number>\n    > r = base.random.f( 1.5, 1.5 )\n    <number>\n    > r = base.random.f( 1.5, 1.5 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.f.state\n    <Uint32Array>\n\n    > r = base.random.f( 1.5, 1.5 )\n    <number>\n    > r = base.random.f( 1.5, 1.5 )\n    <number>\n\n    // Set the state:\n    > base.random.f.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.f( 1.5, 1.5 )\n    <number>\n    > r = base.random.f( 1.5, 1.5 )\n    <number>","base.random.f.stateLength":"\nbase.random.f.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.f.stateLength;","base.random.f.byteLength":"\nbase.random.f.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.f.byteLength;","base.random.f.toJSON":"\nbase.random.f.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.f.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.f, random.iterators.f, random.streams.f","base.random.frechet":"\nbase.random.frechet( α, s, m )\n    Returns a pseudorandom number drawn from a Fréchet distribution.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    If either `α`, `s`, or `m` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.frechet( 2.0, 5.0, 3.33 );\n\n\nbase.random.frechet.factory( [α, s, m, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a triangular distribution.\n\n    If provided `α`, `s`, and `m`, the returned PRNG returns random variates\n    drawn from the specified distribution.\n\n    If not provided `α`, `s`, and `m`, the returned PRNG requires that `α`, `s`,\n    and `m` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    m: number (optional)\n        Location parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.frechet.factory();\n    > var r = rand( 1.0, 1.0, 0.5 );\n    > r = rand( 2.0, 2.0, 1.0 );\n\n    // Provide `α`, `s`, and `m`:\n    > rand = base.random.frechet.factory( 1.0, 1.0, 0.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.frechet.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.frechet.NAME\n    'frechet'\n\n\nbase.random.frechet.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.frechet.PRNG;\n\n\nbase.random.frechet.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.frechet.seed;\n\n\nbase.random.frechet.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.frechet.seedLength;\n\n\nbase.random.frechet.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.frechet.state\n    <Uint32Array>\n\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n\n    // Set the state:\n    > base.random.frechet.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n\n\nbase.random.frechet.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.frechet.stateLength;\n\n\nbase.random.frechet.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.frechet.byteLength;\n\n\nbase.random.frechet.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.frechet.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.frechet, random.iterators.frechet, random.streams.frechet\n","base.random.frechet.factory":"\nbase.random.frechet.factory( [α, s, m, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a triangular distribution.\n\n    If provided `α`, `s`, and `m`, the returned PRNG returns random variates\n    drawn from the specified distribution.\n\n    If not provided `α`, `s`, and `m`, the returned PRNG requires that `α`, `s`,\n    and `m` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    m: number (optional)\n        Location parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.frechet.factory();\n    > var r = rand( 1.0, 1.0, 0.5 );\n    > r = rand( 2.0, 2.0, 1.0 );\n\n    // Provide `α`, `s`, and `m`:\n    > rand = base.random.frechet.factory( 1.0, 1.0, 0.5 );\n    > r = rand();\n    > r = rand();","base.random.frechet.NAME":"\nbase.random.frechet.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.frechet.NAME\n    'frechet'","base.random.frechet.PRNG":"\nbase.random.frechet.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.frechet.PRNG;","base.random.frechet.seed":"\nbase.random.frechet.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.frechet.seed;","base.random.frechet.seedLength":"\nbase.random.frechet.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.frechet.seedLength;","base.random.frechet.state":"\nbase.random.frechet.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.frechet.state\n    <Uint32Array>\n\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n\n    // Set the state:\n    > base.random.frechet.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>","base.random.frechet.stateLength":"\nbase.random.frechet.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.frechet.stateLength;","base.random.frechet.byteLength":"\nbase.random.frechet.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.frechet.byteLength;","base.random.frechet.toJSON":"\nbase.random.frechet.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.frechet.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.frechet, random.iterators.frechet, random.streams.frechet","base.random.gamma":"\nbase.random.gamma( α, β )\n    Returns a pseudorandom number drawn from a gamma distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.gamma( 2.0, 5.0 );\n\n\nbase.random.gamma.factory( [α, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a gamma distribution.\n\n    If provided `α` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `α` and `β`, the returned PRNG requires that both `α` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.gamma.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 3.14, 2.25 );\n\n    // Provide `α` and `β`:\n    > rand = base.random.gamma.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.gamma.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.gamma.NAME\n    'gamma'\n\n\nbase.random.gamma.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.gamma.PRNG;\n\n\nbase.random.gamma.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.gamma.seed;\n\n\nbase.random.gamma.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.gamma.seedLength;\n\n\nbase.random.gamma.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.gamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.gamma.state\n    <Uint32Array>\n\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.gamma.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>\n\n\nbase.random.gamma.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.gamma.stateLength;\n\n\nbase.random.gamma.byteLength\n    Size of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.gamma.byteLength;\n\n\nbase.random.gamma.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.gamma.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.gamma, random.iterators.gamma, random.streams.gamma\n","base.random.gamma.factory":"\nbase.random.gamma.factory( [α, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a gamma distribution.\n\n    If provided `α` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `α` and `β`, the returned PRNG requires that both `α` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.gamma.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 3.14, 2.25 );\n\n    // Provide `α` and `β`:\n    > rand = base.random.gamma.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.gamma.NAME":"\nbase.random.gamma.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.gamma.NAME\n    'gamma'","base.random.gamma.PRNG":"\nbase.random.gamma.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.gamma.PRNG;","base.random.gamma.seed":"\nbase.random.gamma.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.gamma.seed;","base.random.gamma.seedLength":"\nbase.random.gamma.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.gamma.seedLength;","base.random.gamma.state":"\nbase.random.gamma.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.gamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.gamma.state\n    <Uint32Array>\n\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.gamma.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>","base.random.gamma.stateLength":"\nbase.random.gamma.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.gamma.stateLength;","base.random.gamma.byteLength":"\nbase.random.gamma.byteLength\n    Size of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.gamma.byteLength;","base.random.gamma.toJSON":"\nbase.random.gamma.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.gamma.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.gamma, random.iterators.gamma, random.streams.gamma","base.random.geometric":"\nbase.random.geometric( p )\n    Returns a pseudorandom number drawn from a geometric distribution.\n\n    If `p < 0` or `p > 1` or `p` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.geometric( 0.8 );\n\n\nbase.random.geometric.factory( [p, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a geometric distribution.\n\n    If provided `p`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `p`, the returned PRNG requires that `p` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.geometric.factory();\n    > var r = rand( 0.3 );\n    > r = rand( 0.59 );\n\n    // Provide `p`:\n    > rand = base.random.geometric.factory( 0.3 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.geometric.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.geometric.NAME\n    'geometric'\n\n\nbase.random.geometric.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.geometric.PRNG;\n\n\nbase.random.geometric.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.geometric.seed;\n\n\nbase.random.geometric.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.geometric.seedLength;\n\n\nbase.random.geometric.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.geometric( 0.3 )\n    <number>\n    > r = base.random.geometric( 0.3 )\n    <number>\n    > r = base.random.geometric( 0.3 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.geometric.state\n    <Uint32Array>\n\n    > r = base.random.geometric( 0.3 )\n    <number>\n    > r = base.random.geometric( 0.3 )\n    <number>\n\n    // Set the state:\n    > base.random.geometric.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.geometric( 0.3 )\n    <number>\n    > r = base.random.geometric( 0.3 )\n    <number>\n\n\nbase.random.geometric.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.geometric.stateLength;\n\n\nbase.random.geometric.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.geometric.byteLength;\n\n\nbase.random.geometric.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.geometric.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.geometric, random.iterators.geometric, random.streams.geometric\n","base.random.geometric.factory":"\nbase.random.geometric.factory( [p, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a geometric distribution.\n\n    If provided `p`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `p`, the returned PRNG requires that `p` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.geometric.factory();\n    > var r = rand( 0.3 );\n    > r = rand( 0.59 );\n\n    // Provide `p`:\n    > rand = base.random.geometric.factory( 0.3 );\n    > r = rand();\n    > r = rand();","base.random.geometric.NAME":"\nbase.random.geometric.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.geometric.NAME\n    'geometric'","base.random.geometric.PRNG":"\nbase.random.geometric.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.geometric.PRNG;","base.random.geometric.seed":"\nbase.random.geometric.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.geometric.seed;","base.random.geometric.seedLength":"\nbase.random.geometric.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.geometric.seedLength;","base.random.geometric.state":"\nbase.random.geometric.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.geometric( 0.3 )\n    <number>\n    > r = base.random.geometric( 0.3 )\n    <number>\n    > r = base.random.geometric( 0.3 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.geometric.state\n    <Uint32Array>\n\n    > r = base.random.geometric( 0.3 )\n    <number>\n    > r = base.random.geometric( 0.3 )\n    <number>\n\n    // Set the state:\n    > base.random.geometric.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.geometric( 0.3 )\n    <number>\n    > r = base.random.geometric( 0.3 )\n    <number>","base.random.geometric.stateLength":"\nbase.random.geometric.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.geometric.stateLength;","base.random.geometric.byteLength":"\nbase.random.geometric.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.geometric.byteLength;","base.random.geometric.toJSON":"\nbase.random.geometric.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.geometric.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.geometric, random.iterators.geometric, random.streams.geometric","base.random.gumbel":"\nbase.random.gumbel( μ, β )\n    Returns a pseudorandom number drawn from a Gumbel distribution.\n\n    If `μ` or `β` is `NaN` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.gumbel( 2.0, 5.0 );\n\n\nbase.random.gumbel.factory( [μ, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Gumbel distribution.\n\n    If provided `μ` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `β`, the returned PRNG requires that both `μ` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.gumbel.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `β`:\n    > rand = base.random.gumbel.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.gumbel.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.gumbel.NAME\n    'gumbel'\n\n\nbase.random.gumbel.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.gumbel.PRNG;\n\n\nbase.random.gumbel.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.gumbel.seed;\n\n\nbase.random.gumbel.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.gumbel.seedLength;\n\n\nbase.random.gumbel.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.gumbel.state\n    <Uint32Array>\n\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.gumbel.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n\n\nbase.random.gumbel.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.gumbel.stateLength;\n\n\nbase.random.gumbel.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.gumbel.byteLength;\n\n\nbase.random.gumbel.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.gumbel.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.gumbel, random.iterators.gumbel, random.streams.gumbel\n","base.random.gumbel.factory":"\nbase.random.gumbel.factory( [μ, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Gumbel distribution.\n\n    If provided `μ` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `β`, the returned PRNG requires that both `μ` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.gumbel.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `β`:\n    > rand = base.random.gumbel.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.gumbel.NAME":"\nbase.random.gumbel.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.gumbel.NAME\n    'gumbel'","base.random.gumbel.PRNG":"\nbase.random.gumbel.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.gumbel.PRNG;","base.random.gumbel.seed":"\nbase.random.gumbel.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.gumbel.seed;","base.random.gumbel.seedLength":"\nbase.random.gumbel.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.gumbel.seedLength;","base.random.gumbel.state":"\nbase.random.gumbel.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.gumbel.state\n    <Uint32Array>\n\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.gumbel.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>","base.random.gumbel.stateLength":"\nbase.random.gumbel.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.gumbel.stateLength;","base.random.gumbel.byteLength":"\nbase.random.gumbel.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.gumbel.byteLength;","base.random.gumbel.toJSON":"\nbase.random.gumbel.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.gumbel.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.gumbel, random.iterators.gumbel, random.streams.gumbel","base.random.hypergeometric":"\nbase.random.hypergeometric( N, K, n )\n    Returns a pseudorandom number drawn from a hypergeometric distribution.\n\n    `N`, `K`, and `n` must all be nonnegative integers; otherwise, the function\n    returns `NaN`.\n\n    If `n > N` or `K > N`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.hypergeometric( 20, 10, 7 );\n\n\nbase.random.hypergeometric.factory( [N, K, n, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a hypergeometric distribution.\n\n    If provided `N`, `K`, and `n`, the returned PRNG returns random variates\n    drawn from the specified distribution.\n\n    If not provided `N`, `K`, and `n`, the returned PRNG requires that `N`, `K`,\n    and `n` be provided at each invocation.\n\n    Parameters\n    ----------\n    N: integer (optional)\n        Population size.\n\n    K: integer (optional)\n        Subpopulation size.\n\n    n: integer (optional)\n        Number of draws.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.hypergeometric.factory();\n    > var r = rand( 20, 10, 15 );\n    > r = rand( 20, 10, 7 );\n\n    // Provide `N`, `K`, and `n`:\n    > rand = base.random.hypergeometric.factory( 20, 10, 15 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.hypergeometric.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.hypergeometric.NAME\n    'hypergeometric'\n\n\nbase.random.hypergeometric.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.hypergeometric.PRNG;\n\n\nbase.random.hypergeometric.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.hypergeometric.seed;\n\n\nbase.random.hypergeometric.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.hypergeometric.seedLength;\n\n\nbase.random.hypergeometric.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.hypergeometric.state\n    <Uint32Array>\n\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n\n    // Set the state:\n    > base.random.hypergeometric.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n\n\nbase.random.hypergeometric.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.hypergeometric.stateLength;\n\n\nbase.random.hypergeometric.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.hypergeometric.byteLength;\n\n\nbase.random.hypergeometric.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.hypergeometric.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.hypergeometric, random.iterators.hypergeometric, random.streams.hypergeometric\n","base.random.hypergeometric.factory":"\nbase.random.hypergeometric.factory( [N, K, n, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a hypergeometric distribution.\n\n    If provided `N`, `K`, and `n`, the returned PRNG returns random variates\n    drawn from the specified distribution.\n\n    If not provided `N`, `K`, and `n`, the returned PRNG requires that `N`, `K`,\n    and `n` be provided at each invocation.\n\n    Parameters\n    ----------\n    N: integer (optional)\n        Population size.\n\n    K: integer (optional)\n        Subpopulation size.\n\n    n: integer (optional)\n        Number of draws.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.hypergeometric.factory();\n    > var r = rand( 20, 10, 15 );\n    > r = rand( 20, 10, 7 );\n\n    // Provide `N`, `K`, and `n`:\n    > rand = base.random.hypergeometric.factory( 20, 10, 15 );\n    > r = rand();\n    > r = rand();","base.random.hypergeometric.NAME":"\nbase.random.hypergeometric.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.hypergeometric.NAME\n    'hypergeometric'","base.random.hypergeometric.PRNG":"\nbase.random.hypergeometric.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.hypergeometric.PRNG;","base.random.hypergeometric.seed":"\nbase.random.hypergeometric.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.hypergeometric.seed;","base.random.hypergeometric.seedLength":"\nbase.random.hypergeometric.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.hypergeometric.seedLength;","base.random.hypergeometric.state":"\nbase.random.hypergeometric.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.hypergeometric.state\n    <Uint32Array>\n\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n\n    // Set the state:\n    > base.random.hypergeometric.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>","base.random.hypergeometric.stateLength":"\nbase.random.hypergeometric.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.hypergeometric.stateLength;","base.random.hypergeometric.byteLength":"\nbase.random.hypergeometric.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.hypergeometric.byteLength;","base.random.hypergeometric.toJSON":"\nbase.random.hypergeometric.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.hypergeometric.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.hypergeometric, random.iterators.hypergeometric, random.streams.hypergeometric","base.random.improvedZiggurat":"\nbase.random.improvedZiggurat()\n    Returns a pseudorandom number drawn from a standard normal distribution.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.improvedZiggurat();\n\n\nbase.random.improvedZiggurat.factory( [options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a standard normal distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.improvedZiggurat.factory();\n    > r = rand();\n    > r = rand();\n\n\nbase.random.improvedZiggurat.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.improvedZiggurat.NAME\n    'improved-ziggurat'\n\n\nbase.random.improvedZiggurat.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.improvedZiggurat.PRNG;\n\n\nbase.random.improvedZiggurat.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.improvedZiggurat.seed;\n\n\nbase.random.improvedZiggurat.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.improvedZiggurat.seedLength;\n\n\nbase.random.improvedZiggurat.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.improvedZiggurat()\n    <number>\n    > r = base.random.improvedZiggurat()\n    <number>\n    > r = base.random.improvedZiggurat()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.improvedZiggurat.state\n    <Uint32Array>\n\n    > r = base.random.improvedZiggurat()\n    <number>\n    > r = base.random.improvedZiggurat()\n    <number>\n\n    // Set the state:\n    > base.random.improvedZiggurat.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.improvedZiggurat()\n    <number>\n    > r = base.random.improvedZiggurat()\n    <number>\n\n\nbase.random.improvedZiggurat.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.improvedZiggurat.stateLength;\n\n\nbase.random.improvedZiggurat.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.improvedZiggurat.byteLength;\n\n\nbase.random.improvedZiggurat.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.improvedZiggurat.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.iterators.improvedZiggurat, random.streams.improvedZiggurat\n","base.random.improvedZiggurat.factory":"\nbase.random.improvedZiggurat.factory( [options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a standard normal distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.improvedZiggurat.factory();\n    > r = rand();\n    > r = rand();","base.random.improvedZiggurat.NAME":"\nbase.random.improvedZiggurat.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.improvedZiggurat.NAME\n    'improved-ziggurat'","base.random.improvedZiggurat.PRNG":"\nbase.random.improvedZiggurat.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.improvedZiggurat.PRNG;","base.random.improvedZiggurat.seed":"\nbase.random.improvedZiggurat.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.improvedZiggurat.seed;","base.random.improvedZiggurat.seedLength":"\nbase.random.improvedZiggurat.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.improvedZiggurat.seedLength;","base.random.improvedZiggurat.state":"\nbase.random.improvedZiggurat.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.improvedZiggurat()\n    <number>\n    > r = base.random.improvedZiggurat()\n    <number>\n    > r = base.random.improvedZiggurat()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.improvedZiggurat.state\n    <Uint32Array>\n\n    > r = base.random.improvedZiggurat()\n    <number>\n    > r = base.random.improvedZiggurat()\n    <number>\n\n    // Set the state:\n    > base.random.improvedZiggurat.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.improvedZiggurat()\n    <number>\n    > r = base.random.improvedZiggurat()\n    <number>","base.random.improvedZiggurat.stateLength":"\nbase.random.improvedZiggurat.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.improvedZiggurat.stateLength;","base.random.improvedZiggurat.byteLength":"\nbase.random.improvedZiggurat.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.improvedZiggurat.byteLength;","base.random.improvedZiggurat.toJSON":"\nbase.random.improvedZiggurat.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.improvedZiggurat.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.iterators.improvedZiggurat, random.streams.improvedZiggurat","base.random.invgamma":"\nbase.random.invgamma( α, β )\n    Returns a pseudorandom number drawn from an inverse gamma distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.invgamma( 2.0, 5.0 );\n\n\nbase.random.invgamma.factory( [α, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an inverse gamma distribution.\n\n    If provided `α` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `α` and `β`, the returned PRNG requires that both `α` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.invgamma.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 3.14, 2.25 );\n\n    // Provide `α` and `β`:\n    > rand = base.random.invgamma.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.invgamma.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.invgamma.NAME\n    'invgamma'\n\n\nbase.random.invgamma.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.invgamma.PRNG;\n\n\nbase.random.invgamma.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.invgamma.seed;\n\n\nbase.random.invgamma.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.invgamma.seedLength;\n\n\nbase.random.invgamma.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.invgamma.state\n    <Uint32Array>\n\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.invgamma.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n\n\nbase.random.invgamma.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.invgamma.stateLength;\n\n\nbase.random.invgamma.byteLength\n    Size of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.invgamma.byteLength;\n\n\nbase.random.invgamma.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.invgamma.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.invgamma, random.iterators.invgamma, random.streams.invgamma\n","base.random.invgamma.factory":"\nbase.random.invgamma.factory( [α, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an inverse gamma distribution.\n\n    If provided `α` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `α` and `β`, the returned PRNG requires that both `α` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.invgamma.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 3.14, 2.25 );\n\n    // Provide `α` and `β`:\n    > rand = base.random.invgamma.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.invgamma.NAME":"\nbase.random.invgamma.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.invgamma.NAME\n    'invgamma'","base.random.invgamma.PRNG":"\nbase.random.invgamma.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.invgamma.PRNG;","base.random.invgamma.seed":"\nbase.random.invgamma.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.invgamma.seed;","base.random.invgamma.seedLength":"\nbase.random.invgamma.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.invgamma.seedLength;","base.random.invgamma.state":"\nbase.random.invgamma.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.invgamma.state\n    <Uint32Array>\n\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.invgamma.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>","base.random.invgamma.stateLength":"\nbase.random.invgamma.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.invgamma.stateLength;","base.random.invgamma.byteLength":"\nbase.random.invgamma.byteLength\n    Size of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.invgamma.byteLength;","base.random.invgamma.toJSON":"\nbase.random.invgamma.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.invgamma.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.invgamma, random.iterators.invgamma, random.streams.invgamma","base.random.kumaraswamy":"\nbase.random.kumaraswamy( a, b )\n    Returns a pseudorandom number drawn from Kumaraswamy's double bounded\n    distribution.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    If `a` or `b` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.kumaraswamy( 2.0, 5.0 );\n\n\nbase.random.kumaraswamy.factory( [a, b, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from Kumaraswamy's double bounded distribution.\n\n    If provided `a` and `b`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `a` and `b`, the returned PRNG requires that both `a` and\n    `b` be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        First shape parameter.\n\n    b: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.kumaraswamy.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `a` and `b`:\n    > rand = base.random.kumaraswamy.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.kumaraswamy.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.kumaraswamy.NAME\n    'kumaraswamy'\n\n\nbase.random.kumaraswamy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.kumaraswamy.PRNG;\n\n\nbase.random.kumaraswamy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.kumaraswamy.seed;\n\n\nbase.random.kumaraswamy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.kumaraswamy.seedLength;\n\n\nbase.random.kumaraswamy.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.kumaraswamy.state\n    <Uint32Array>\n\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n\n    // Set the state:\n    > base.random.kumaraswamy.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n\n\nbase.random.kumaraswamy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.kumaraswamy.stateLength;\n\n\nbase.random.kumaraswamy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.kumaraswamy.byteLength;\n\n\nbase.random.kumaraswamy.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.kumaraswamy.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.kumaraswamy, random.iterators.kumaraswamy, random.streams.kumaraswamy\n","base.random.kumaraswamy.factory":"\nbase.random.kumaraswamy.factory( [a, b, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from Kumaraswamy's double bounded distribution.\n\n    If provided `a` and `b`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `a` and `b`, the returned PRNG requires that both `a` and\n    `b` be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        First shape parameter.\n\n    b: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.kumaraswamy.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `a` and `b`:\n    > rand = base.random.kumaraswamy.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.kumaraswamy.NAME":"\nbase.random.kumaraswamy.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.kumaraswamy.NAME\n    'kumaraswamy'","base.random.kumaraswamy.PRNG":"\nbase.random.kumaraswamy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.kumaraswamy.PRNG;","base.random.kumaraswamy.seed":"\nbase.random.kumaraswamy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.kumaraswamy.seed;","base.random.kumaraswamy.seedLength":"\nbase.random.kumaraswamy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.kumaraswamy.seedLength;","base.random.kumaraswamy.state":"\nbase.random.kumaraswamy.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.kumaraswamy.state\n    <Uint32Array>\n\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n\n    // Set the state:\n    > base.random.kumaraswamy.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>","base.random.kumaraswamy.stateLength":"\nbase.random.kumaraswamy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.kumaraswamy.stateLength;","base.random.kumaraswamy.byteLength":"\nbase.random.kumaraswamy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.kumaraswamy.byteLength;","base.random.kumaraswamy.toJSON":"\nbase.random.kumaraswamy.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.kumaraswamy.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.kumaraswamy, random.iterators.kumaraswamy, random.streams.kumaraswamy","base.random.laplace":"\nbase.random.laplace( μ, b )\n    Returns a pseudorandom number drawn from a Laplace distribution.\n\n    If `μ` or `b` is `NaN` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.laplace( 2.0, 5.0 );\n\n\nbase.random.laplace.factory( [μ, b, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Laplace distribution.\n\n    If provided `μ` and `b`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `b`, the returned PRNG requires that both `μ` and\n    `b` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    b: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.laplace.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `b`:\n    > rand = base.random.laplace.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.laplace.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.laplace.NAME\n    'laplace'\n\n\nbase.random.laplace.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.laplace.PRNG;\n\n\nbase.random.laplace.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.laplace.seed;\n\n\nbase.random.laplace.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.laplace.seedLength;\n\n\nbase.random.laplace.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.laplace( 2.0, 5.0 )\n    <number>\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.laplace.state\n    <Uint32Array>\n\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.laplace.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>\n\n\nbase.random.laplace.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.laplace.stateLength;\n\n\nbase.random.laplace.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.laplace.byteLength;\n\n\nbase.random.laplace.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.laplace.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.laplace, random.iterators.laplace, random.streams.laplace\n","base.random.laplace.factory":"\nbase.random.laplace.factory( [μ, b, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Laplace distribution.\n\n    If provided `μ` and `b`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `b`, the returned PRNG requires that both `μ` and\n    `b` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    b: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.laplace.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `b`:\n    > rand = base.random.laplace.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.laplace.NAME":"\nbase.random.laplace.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.laplace.NAME\n    'laplace'","base.random.laplace.PRNG":"\nbase.random.laplace.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.laplace.PRNG;","base.random.laplace.seed":"\nbase.random.laplace.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.laplace.seed;","base.random.laplace.seedLength":"\nbase.random.laplace.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.laplace.seedLength;","base.random.laplace.state":"\nbase.random.laplace.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.laplace( 2.0, 5.0 )\n    <number>\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.laplace.state\n    <Uint32Array>\n\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.laplace.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>","base.random.laplace.stateLength":"\nbase.random.laplace.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.laplace.stateLength;","base.random.laplace.byteLength":"\nbase.random.laplace.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.laplace.byteLength;","base.random.laplace.toJSON":"\nbase.random.laplace.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.laplace.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.laplace, random.iterators.laplace, random.streams.laplace","base.random.levy":"\nbase.random.levy( μ, c )\n    Returns a pseudorandom number drawn from a Lévy distribution.\n\n    If `μ` or `c` is `NaN` or `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.levy( 2.0, 5.0 );\n\n\nbase.random.levy.factory( [μ, c, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Lévy distribution.\n\n    If provided `μ` and `c`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `c`, the returned PRNG requires that both `μ` and\n    `c` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    c: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.levy.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `b`:\n    > rand = base.random.levy.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.levy.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.levy.NAME\n    'levy'\n\n\nbase.random.levy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.levy.PRNG;\n\n\nbase.random.levy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.levy.seed;\n\n\nbase.random.levy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.levy.seedLength;\n\n\nbase.random.levy.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.levy( 2.0, 5.0 )\n    <number>\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.levy.state\n    <Uint32Array>\n\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.levy.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>\n\n\nbase.random.levy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.levy.stateLength;\n\n\nbase.random.levy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.levy.byteLength;\n\n\nbase.random.levy.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.levy.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.levy, random.iterators.levy, random.streams.levy\n","base.random.levy.factory":"\nbase.random.levy.factory( [μ, c, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Lévy distribution.\n\n    If provided `μ` and `c`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `c`, the returned PRNG requires that both `μ` and\n    `c` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    c: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.levy.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `b`:\n    > rand = base.random.levy.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.levy.NAME":"\nbase.random.levy.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.levy.NAME\n    'levy'","base.random.levy.PRNG":"\nbase.random.levy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.levy.PRNG;","base.random.levy.seed":"\nbase.random.levy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.levy.seed;","base.random.levy.seedLength":"\nbase.random.levy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.levy.seedLength;","base.random.levy.state":"\nbase.random.levy.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.levy( 2.0, 5.0 )\n    <number>\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.levy.state\n    <Uint32Array>\n\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.levy.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>","base.random.levy.stateLength":"\nbase.random.levy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.levy.stateLength;","base.random.levy.byteLength":"\nbase.random.levy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.levy.byteLength;","base.random.levy.toJSON":"\nbase.random.levy.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.levy.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.levy, random.iterators.levy, random.streams.levy","base.random.logistic":"\nbase.random.logistic( μ, s )\n    Returns a pseudorandom number drawn from a logistic distribution.\n\n    If `μ` or `s` is `NaN` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.logistic( 2.0, 5.0 );\n\n\nbase.random.logistic.factory( [μ, s, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a logistic distribution.\n\n    If provided `μ` and `s`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n    `s` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.logistic.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `s`:\n    > rand = base.random.logistic.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.logistic.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.logistic.NAME\n    'logistic'\n\n\nbase.random.logistic.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.logistic.PRNG;\n\n\nbase.random.logistic.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.logistic.seed;\n\n\nbase.random.logistic.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.logistic.seedLength;\n\n\nbase.random.logistic.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.logistic( 2.0, 5.0 )\n    <number>\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.logistic.state\n    <Uint32Array>\n\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.logistic.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>\n\n\nbase.random.logistic.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.logistic.stateLength;\n\n\nbase.random.logistic.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.logistic.byteLength;\n\n\nbase.random.logistic.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.logistic.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.logistic, random.iterators.logistic, random.streams.logistic\n","base.random.logistic.factory":"\nbase.random.logistic.factory( [μ, s, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a logistic distribution.\n\n    If provided `μ` and `s`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n    `s` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.logistic.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `s`:\n    > rand = base.random.logistic.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.logistic.NAME":"\nbase.random.logistic.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.logistic.NAME\n    'logistic'","base.random.logistic.PRNG":"\nbase.random.logistic.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.logistic.PRNG;","base.random.logistic.seed":"\nbase.random.logistic.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.logistic.seed;","base.random.logistic.seedLength":"\nbase.random.logistic.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.logistic.seedLength;","base.random.logistic.state":"\nbase.random.logistic.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.logistic( 2.0, 5.0 )\n    <number>\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.logistic.state\n    <Uint32Array>\n\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.logistic.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>","base.random.logistic.stateLength":"\nbase.random.logistic.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.logistic.stateLength;","base.random.logistic.byteLength":"\nbase.random.logistic.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.logistic.byteLength;","base.random.logistic.toJSON":"\nbase.random.logistic.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.logistic.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.logistic, random.iterators.logistic, random.streams.logistic","base.random.lognormal":"\nbase.random.lognormal( μ, σ )\n    Returns a pseudorandom number drawn from a lognormal distribution.\n\n    If `μ` or `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.lognormal( 2.0, 5.0 );\n\n\nbase.random.lognormal.factory( [μ, σ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a lognormal distribution.\n\n    If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n    `σ` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter.\n\n    σ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.lognormal.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `σ`:\n    > rand = base.random.lognormal.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.lognormal.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.lognormal.NAME\n    'lognormal'\n\n\nbase.random.lognormal.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.lognormal.PRNG;\n\n\nbase.random.lognormal.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.lognormal.seed;\n\n\nbase.random.lognormal.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.lognormal.seedLength;\n\n\nbase.random.lognormal.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.lognormal.state\n    <Uint32Array>\n\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.lognormal.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n\n\nbase.random.lognormal.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.lognormal.stateLength;\n\n\nbase.random.lognormal.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.lognormal.byteLength;\n\n\nbase.random.lognormal.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.lognormal.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.lognormal, random.iterators.lognormal, random.streams.lognormal\n","base.random.lognormal.factory":"\nbase.random.lognormal.factory( [μ, σ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a lognormal distribution.\n\n    If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n    `σ` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter.\n\n    σ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.lognormal.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `σ`:\n    > rand = base.random.lognormal.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.lognormal.NAME":"\nbase.random.lognormal.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.lognormal.NAME\n    'lognormal'","base.random.lognormal.PRNG":"\nbase.random.lognormal.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.lognormal.PRNG;","base.random.lognormal.seed":"\nbase.random.lognormal.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.lognormal.seed;","base.random.lognormal.seedLength":"\nbase.random.lognormal.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.lognormal.seedLength;","base.random.lognormal.state":"\nbase.random.lognormal.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.lognormal.state\n    <Uint32Array>\n\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.lognormal.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>","base.random.lognormal.stateLength":"\nbase.random.lognormal.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.lognormal.stateLength;","base.random.lognormal.byteLength":"\nbase.random.lognormal.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.lognormal.byteLength;","base.random.lognormal.toJSON":"\nbase.random.lognormal.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.lognormal.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.lognormal, random.iterators.lognormal, random.streams.lognormal","base.random.minstd":"\nbase.random.minstd()\n    Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n\n    This pseudorandom number generator (PRNG) is a linear congruential\n    pseudorandom number generator (LCG) based on Park and Miller.\n\n    The generator has a period of approximately `2.1e9`.\n\n    An LCG is fast and uses little memory. On the other hand, because the\n    generator is a simple LCG, the generator has recognized shortcomings. By\n    today's PRNG standards, the generator's period is relatively short. More\n    importantly, the \"randomness quality\" of the generator's output is lacking.\n    These defects make the generator unsuitable, for example, in Monte Carlo\n    simulations and in cryptographic applications.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.minstd();\n\n\nbase.random.minstd.normalized()\n    Returns a pseudorandom number on the interval `[0,1)`.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.minstd.normalized();\n\n\nbase.random.minstd.factory( [options] )\n    Returns a linear congruential pseudorandom number generator (LCG).\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.minstd.factory();\n    > r = rand();\n    > r = rand();\n\n    // Provide a seed:\n    > rand = base.random.minstd.factory( { 'seed': 1234 } );\n    > r = rand()\n    20739838\n\n\nbase.random.minstd.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.minstd.NAME\n    'minstd'\n\n\nbase.random.minstd.MIN\n    Minimum possible value.\n\n    Examples\n    --------\n    > var v = base.random.minstd.MIN\n    1\n\n\nbase.random.minstd.MAX\n    Maximum possible value.\n\n    Examples\n    --------\n    > var v = base.random.minstd.MAX\n    2147483646\n\n\nbase.random.minstd.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.minstd.seed;\n\n\nbase.random.minstd.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.minstd.seedLength;\n\n\nbase.random.minstd.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.minstd()\n    <number>\n    > r = base.random.minstd()\n    <number>\n    > r = base.random.minstd()\n    <number>\n\n    // Get the current state:\n    > var state = base.random.minstd.state\n    <Int32Array>\n\n    > r = base.random.minstd()\n    <number>\n    > r = base.random.minstd()\n    <number>\n\n    // Set the state:\n    > base.random.minstd.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.minstd()\n    <number>\n    > r = base.random.minstd()\n    <number>\n\n\nbase.random.minstd.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.minstd.stateLength;\n\n\nbase.random.minstd.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.minstd.byteLength;\n\n\nbase.random.minstd.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.minstd.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.minstd, random.iterators.minstd, random.streams.minstd, base.random.minstdShuffle, base.random.mt19937, base.random.randi\n","base.random.minstd.normalized":"\nbase.random.minstd.normalized()\n    Returns a pseudorandom number on the interval `[0,1)`.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.minstd.normalized();","base.random.minstd.factory":"\nbase.random.minstd.factory( [options] )\n    Returns a linear congruential pseudorandom number generator (LCG).\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.minstd.factory();\n    > r = rand();\n    > r = rand();\n\n    // Provide a seed:\n    > rand = base.random.minstd.factory( { 'seed': 1234 } );\n    > r = rand()\n    20739838","base.random.minstd.NAME":"\nbase.random.minstd.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.minstd.NAME\n    'minstd'","base.random.minstd.MIN":"\nbase.random.minstd.MIN\n    Minimum possible value.\n\n    Examples\n    --------\n    > var v = base.random.minstd.MIN\n    1","base.random.minstd.MAX":"\nbase.random.minstd.MAX\n    Maximum possible value.\n\n    Examples\n    --------\n    > var v = base.random.minstd.MAX\n    2147483646","base.random.minstd.seed":"\nbase.random.minstd.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.minstd.seed;","base.random.minstd.seedLength":"\nbase.random.minstd.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.minstd.seedLength;","base.random.minstd.state":"\nbase.random.minstd.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.minstd()\n    <number>\n    > r = base.random.minstd()\n    <number>\n    > r = base.random.minstd()\n    <number>\n\n    // Get the current state:\n    > var state = base.random.minstd.state\n    <Int32Array>\n\n    > r = base.random.minstd()\n    <number>\n    > r = base.random.minstd()\n    <number>\n\n    // Set the state:\n    > base.random.minstd.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.minstd()\n    <number>\n    > r = base.random.minstd()\n    <number>","base.random.minstd.stateLength":"\nbase.random.minstd.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.minstd.stateLength;","base.random.minstd.byteLength":"\nbase.random.minstd.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.minstd.byteLength;","base.random.minstd.toJSON":"\nbase.random.minstd.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.minstd.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.minstd, random.iterators.minstd, random.streams.minstd, base.random.minstdShuffle, base.random.mt19937, base.random.randi","base.random.minstdShuffle":"\nbase.random.minstdShuffle()\n    Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n\n    This pseudorandom number generator (PRNG) is a linear congruential\n    pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n    Durham algorithm. The shuffle step considerably strengthens the \"randomness\n    quality\" of a simple LCG's output.\n\n    The generator has a period of approximately `2.1e9`.\n\n    An LCG is fast and uses little memory. On the other hand, because the\n    generator is a simple LCG, the generator has recognized shortcomings. By\n    today's PRNG standards, the generator's period is relatively short. In\n    general, this generator is unsuitable for Monte Carlo simulations and\n    cryptographic applications.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.minstdShuffle();\n\n\nbase.random.minstdShuffle.normalized()\n    Returns a pseudorandom number on the interval `[0,1)`.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.minstdShuffle.normalized();\n\n\nbase.random.minstdShuffle.factory( [options] )\n    Returns a linear congruential pseudorandom number generator (LCG) whose\n    output is shuffled.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.minstdShuffle.factory();\n    > r = rand();\n    > r = rand();\n\n    // Provide a seed:\n    > rand = base.random.minstdShuffle.factory( { 'seed': 1234 } );\n    > r = rand()\n    1421600654\n\n\nbase.random.minstdShuffle.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.minstdShuffle.NAME\n    'minstd-shuffle'\n\n\nbase.random.minstdShuffle.MIN\n    Minimum possible value.\n\n    Examples\n    --------\n    > var v = base.random.minstdShuffle.MIN\n    1\n\n\nbase.random.minstdShuffle.MAX\n    Maximum possible value.\n\n    Examples\n    --------\n    > var v = base.random.minstdShuffle.MAX\n    2147483646\n\n\nbase.random.minstdShuffle.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.minstdShuffle.seed;\n\n\nbase.random.minstdShuffle.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.minstdShuffle.seedLength;\n\n\nbase.random.minstdShuffle.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.minstdShuffle()\n    <number>\n    > r = base.random.minstdShuffle()\n    <number>\n    > r = base.random.minstdShuffle()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.minstdShuffle.state\n    <Int32Array>\n\n    > r = base.random.minstdShuffle()\n    <number>\n    > r = base.random.minstdShuffle()\n    <number>\n\n    // Set the state:\n    > base.random.minstdShuffle.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.minstdShuffle()\n    <number>\n    > r = base.random.minstdShuffle()\n    <number>\n\n\nbase.random.minstdShuffle.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.minstdShuffle.stateLength;\n\n\nbase.random.minstdShuffle.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.minstdShuffle.byteLength;\n\n\nbase.random.minstdShuffle.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.minstdShuffle.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstdShuffle, base.random.minstd, base.random.mt19937, base.random.randi\n","base.random.minstdShuffle.normalized":"\nbase.random.minstdShuffle.normalized()\n    Returns a pseudorandom number on the interval `[0,1)`.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.minstdShuffle.normalized();","base.random.minstdShuffle.factory":"\nbase.random.minstdShuffle.factory( [options] )\n    Returns a linear congruential pseudorandom number generator (LCG) whose\n    output is shuffled.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.minstdShuffle.factory();\n    > r = rand();\n    > r = rand();\n\n    // Provide a seed:\n    > rand = base.random.minstdShuffle.factory( { 'seed': 1234 } );\n    > r = rand()\n    1421600654","base.random.minstdShuffle.NAME":"\nbase.random.minstdShuffle.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.minstdShuffle.NAME\n    'minstd-shuffle'","base.random.minstdShuffle.MIN":"\nbase.random.minstdShuffle.MIN\n    Minimum possible value.\n\n    Examples\n    --------\n    > var v = base.random.minstdShuffle.MIN\n    1","base.random.minstdShuffle.MAX":"\nbase.random.minstdShuffle.MAX\n    Maximum possible value.\n\n    Examples\n    --------\n    > var v = base.random.minstdShuffle.MAX\n    2147483646","base.random.minstdShuffle.seed":"\nbase.random.minstdShuffle.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.minstdShuffle.seed;","base.random.minstdShuffle.seedLength":"\nbase.random.minstdShuffle.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.minstdShuffle.seedLength;","base.random.minstdShuffle.state":"\nbase.random.minstdShuffle.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.minstdShuffle()\n    <number>\n    > r = base.random.minstdShuffle()\n    <number>\n    > r = base.random.minstdShuffle()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.minstdShuffle.state\n    <Int32Array>\n\n    > r = base.random.minstdShuffle()\n    <number>\n    > r = base.random.minstdShuffle()\n    <number>\n\n    // Set the state:\n    > base.random.minstdShuffle.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.minstdShuffle()\n    <number>\n    > r = base.random.minstdShuffle()\n    <number>","base.random.minstdShuffle.stateLength":"\nbase.random.minstdShuffle.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.minstdShuffle.stateLength;","base.random.minstdShuffle.byteLength":"\nbase.random.minstdShuffle.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.minstdShuffle.byteLength;","base.random.minstdShuffle.toJSON":"\nbase.random.minstdShuffle.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.minstdShuffle.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstdShuffle, base.random.minstd, base.random.mt19937, base.random.randi","base.random.mt19937":"\nbase.random.mt19937()\n    Returns a pseudorandom integer on the interval `[0, 4294967295]`.\n\n    This pseudorandom number generator (PRNG) is a 32-bit Mersenne Twister\n    pseudorandom number generator.\n\n    The PRNG is *not* a cryptographically secure PRNG.\n\n    The PRNG has a period of 2^19937 - 1.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.mt19937();\n\n\nbase.random.mt19937.normalized()\n    Returns a pseudorandom number on the interval `[0,1)` with 53-bit precision.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.mt19937.normalized();\n\n\nbase.random.mt19937.factory( [options] )\n    Returns a 32-bit Mersenne Twister pseudorandom number generator.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.mt19937.factory();\n    > r = rand();\n    > r = rand();\n\n    // Provide a seed:\n    > rand = base.random.mt19937.factory( { 'seed': 1234 } );\n    > r = rand()\n    822569775\n\n\nbase.random.mt19937.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.mt19937.NAME\n    'mt19937'\n\n\nbase.random.mt19937.MIN\n    Minimum possible value.\n\n    Examples\n    --------\n    > var v = base.random.mt19937.MIN\n    0\n\n\nbase.random.mt19937.MAX\n    Maximum possible value.\n\n    Examples\n    --------\n    > var v = base.random.mt19937.MAX\n    4294967295\n\n\nbase.random.mt19937.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.mt19937.seed;\n\n\nbase.random.mt19937.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.mt19937.seedLength;\n\n\nbase.random.mt19937.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.mt19937()\n    <number>\n    > r = base.random.mt19937()\n    <number>\n    > r = base.random.mt19937()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.mt19937.state\n    <Uint32Array>\n\n    > r = base.random.mt19937()\n    <number>\n    > r = base.random.mt19937()\n    <number>\n\n    // Set the state:\n    > base.random.mt19937.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.mt19937()\n    <number>\n    > r = base.random.mt19937()\n    <number>\n\n\nbase.random.mt19937.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.mt19937.stateLength;\n\n\nbase.random.mt19937.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.mt19937.byteLength;\n\n\nbase.random.mt19937.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.mt19937.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.mt19937, random.iterators.mt19937, random.streams.mt19937, base.random.minstd, base.random.randi\n","base.random.mt19937.normalized":"\nbase.random.mt19937.normalized()\n    Returns a pseudorandom number on the interval `[0,1)` with 53-bit precision.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.mt19937.normalized();","base.random.mt19937.factory":"\nbase.random.mt19937.factory( [options] )\n    Returns a 32-bit Mersenne Twister pseudorandom number generator.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.mt19937.factory();\n    > r = rand();\n    > r = rand();\n\n    // Provide a seed:\n    > rand = base.random.mt19937.factory( { 'seed': 1234 } );\n    > r = rand()\n    822569775","base.random.mt19937.NAME":"\nbase.random.mt19937.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.mt19937.NAME\n    'mt19937'","base.random.mt19937.MIN":"\nbase.random.mt19937.MIN\n    Minimum possible value.\n\n    Examples\n    --------\n    > var v = base.random.mt19937.MIN\n    0","base.random.mt19937.MAX":"\nbase.random.mt19937.MAX\n    Maximum possible value.\n\n    Examples\n    --------\n    > var v = base.random.mt19937.MAX\n    4294967295","base.random.mt19937.seed":"\nbase.random.mt19937.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.mt19937.seed;","base.random.mt19937.seedLength":"\nbase.random.mt19937.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.mt19937.seedLength;","base.random.mt19937.state":"\nbase.random.mt19937.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.mt19937()\n    <number>\n    > r = base.random.mt19937()\n    <number>\n    > r = base.random.mt19937()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.mt19937.state\n    <Uint32Array>\n\n    > r = base.random.mt19937()\n    <number>\n    > r = base.random.mt19937()\n    <number>\n\n    // Set the state:\n    > base.random.mt19937.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.mt19937()\n    <number>\n    > r = base.random.mt19937()\n    <number>","base.random.mt19937.stateLength":"\nbase.random.mt19937.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.mt19937.stateLength;","base.random.mt19937.byteLength":"\nbase.random.mt19937.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.mt19937.byteLength;","base.random.mt19937.toJSON":"\nbase.random.mt19937.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.mt19937.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.mt19937, random.iterators.mt19937, random.streams.mt19937, base.random.minstd, base.random.randi","base.random.negativeBinomial":"\nbase.random.negativeBinomial( r, p )\n    Returns a pseudorandom number drawn from a negative binomial distribution.\n\n    If `p` is not in the interval `(0,1)`, the function returns `NaN`.\n\n    If `r` or `p` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.negativeBinomial( 20, 0.8 );\n\n\nbase.random.negativeBinomial.factory( [r, p, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a negative binomial distribution.\n\n    If provided `r` and `p`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `r` and `p`, the returned PRNG requires that both `r` and\n    `p` be provided at each invocation.\n\n    Parameters\n    ----------\n    r: number (optional)\n        Number of successes until experiment is stopped.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.negativeBinomial.factory();\n    > var r = rand( 20, 0.3 );\n    > r = rand( 10, 0.77 );\n\n    // Provide `r` and `p`:\n    > rand = base.random.negativeBinomial.factory( 10, 0.8 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.negativeBinomial.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.negativeBinomial.NAME\n    'negative-binomial'\n\n\nbase.random.negativeBinomial.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.negativeBinomial.PRNG;\n\n\nbase.random.negativeBinomial.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.negativeBinomial.seed;\n\n\nbase.random.negativeBinomial.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.negativeBinomial.seedLength;\n\n\nbase.random.negativeBinomial.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.negativeBinomial.state\n    <Uint32Array>\n\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n\n    // Set the state:\n    > base.random.negativeBinomial.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n\n\nbase.random.negativeBinomial.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.negativeBinomial.stateLength;\n\n\nbase.random.negativeBinomial.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.negativeBinomial.byteLength;\n\n\nbase.random.negativeBinomial.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.negativeBinomial.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.negativeBinomial, random.iterators.negativeBinomial, random.streams.negativeBinomial\n","base.random.negativeBinomial.factory":"\nbase.random.negativeBinomial.factory( [r, p, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a negative binomial distribution.\n\n    If provided `r` and `p`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `r` and `p`, the returned PRNG requires that both `r` and\n    `p` be provided at each invocation.\n\n    Parameters\n    ----------\n    r: number (optional)\n        Number of successes until experiment is stopped.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.negativeBinomial.factory();\n    > var r = rand( 20, 0.3 );\n    > r = rand( 10, 0.77 );\n\n    // Provide `r` and `p`:\n    > rand = base.random.negativeBinomial.factory( 10, 0.8 );\n    > r = rand();\n    > r = rand();","base.random.negativeBinomial.NAME":"\nbase.random.negativeBinomial.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.negativeBinomial.NAME\n    'negative-binomial'","base.random.negativeBinomial.PRNG":"\nbase.random.negativeBinomial.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.negativeBinomial.PRNG;","base.random.negativeBinomial.seed":"\nbase.random.negativeBinomial.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.negativeBinomial.seed;","base.random.negativeBinomial.seedLength":"\nbase.random.negativeBinomial.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.negativeBinomial.seedLength;","base.random.negativeBinomial.state":"\nbase.random.negativeBinomial.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.negativeBinomial.state\n    <Uint32Array>\n\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n\n    // Set the state:\n    > base.random.negativeBinomial.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>","base.random.negativeBinomial.stateLength":"\nbase.random.negativeBinomial.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.negativeBinomial.stateLength;","base.random.negativeBinomial.byteLength":"\nbase.random.negativeBinomial.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.negativeBinomial.byteLength;","base.random.negativeBinomial.toJSON":"\nbase.random.negativeBinomial.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.negativeBinomial.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.negativeBinomial, random.iterators.negativeBinomial, random.streams.negativeBinomial","base.random.normal":"\nbase.random.normal( μ, σ )\n    Returns a pseudorandom number drawn from a normal distribution.\n\n    If `μ` or `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.normal( 2.0, 5.0 );\n\n\nbase.random.normal.factory( [μ, σ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a normal distribution.\n\n    If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n    `σ` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    σ: number (optional)\n        Standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.normal.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `σ`:\n    > rand = base.random.normal.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.normal.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.normal.NAME\n    'normal'\n\n\nbase.random.normal.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.normal.PRNG;\n\n\nbase.random.normal.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.normal.seed;\n\n\nbase.random.normal.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.normal.seedLength;\n\n\nbase.random.normal.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.normal( 2.0, 5.0 )\n    <number>\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.normal.state\n    <Uint32Array>\n\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.normal.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>\n\n\nbase.random.normal.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.normal.stateLength;\n\n\nbase.random.normal.byteLength\n    Size of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.normal.byteLength;\n\n\nbase.random.normal.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.normal.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.normal, random.iterators.normal, random.streams.normal\n","base.random.normal.factory":"\nbase.random.normal.factory( [μ, σ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a normal distribution.\n\n    If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n    `σ` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    σ: number (optional)\n        Standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.normal.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `σ`:\n    > rand = base.random.normal.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.normal.NAME":"\nbase.random.normal.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.normal.NAME\n    'normal'","base.random.normal.PRNG":"\nbase.random.normal.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.normal.PRNG;","base.random.normal.seed":"\nbase.random.normal.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.normal.seed;","base.random.normal.seedLength":"\nbase.random.normal.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.normal.seedLength;","base.random.normal.state":"\nbase.random.normal.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.normal( 2.0, 5.0 )\n    <number>\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.normal.state\n    <Uint32Array>\n\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.normal.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>","base.random.normal.stateLength":"\nbase.random.normal.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.normal.stateLength;","base.random.normal.byteLength":"\nbase.random.normal.byteLength\n    Size of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.normal.byteLength;","base.random.normal.toJSON":"\nbase.random.normal.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.normal.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.normal, random.iterators.normal, random.streams.normal","base.random.pareto1":"\nbase.random.pareto1( α, β )\n    Returns a pseudorandom number drawn from a Pareto (Type I) distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.pareto1( 2.0, 5.0 );\n\n\nbase.random.pareto1.factory( [α, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Pareto (Type I) distribution.\n\n    If provided `α` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `α` and `β`, the returned PRNG requires that both `α` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.pareto1.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `α` and `β`:\n    > rand = base.random.pareto1.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.pareto1.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.pareto1.NAME\n    'pareto-type1'\n\n\nbase.random.pareto1.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.pareto1.PRNG;\n\n\nbase.random.pareto1.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.pareto1.seed;\n\n\nbase.random.pareto1.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.pareto1.seedLength;\n\n\nbase.random.pareto1.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.pareto1.state\n    <Uint32Array>\n\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.pareto1.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n\n\nbase.random.pareto1.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.pareto1.stateLength;\n\n\nbase.random.pareto1.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.pareto1.byteLength;\n\n\nbase.random.pareto1.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.pareto1.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.pareto1, random.iterators.pareto1, random.streams.pareto1\n","base.random.pareto1.factory":"\nbase.random.pareto1.factory( [α, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Pareto (Type I) distribution.\n\n    If provided `α` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `α` and `β`, the returned PRNG requires that both `α` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.pareto1.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `α` and `β`:\n    > rand = base.random.pareto1.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.pareto1.NAME":"\nbase.random.pareto1.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.pareto1.NAME\n    'pareto-type1'","base.random.pareto1.PRNG":"\nbase.random.pareto1.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.pareto1.PRNG;","base.random.pareto1.seed":"\nbase.random.pareto1.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.pareto1.seed;","base.random.pareto1.seedLength":"\nbase.random.pareto1.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.pareto1.seedLength;","base.random.pareto1.state":"\nbase.random.pareto1.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.pareto1.state\n    <Uint32Array>\n\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.pareto1.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>","base.random.pareto1.stateLength":"\nbase.random.pareto1.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.pareto1.stateLength;","base.random.pareto1.byteLength":"\nbase.random.pareto1.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.pareto1.byteLength;","base.random.pareto1.toJSON":"\nbase.random.pareto1.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.pareto1.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.pareto1, random.iterators.pareto1, random.streams.pareto1","base.random.poisson":"\nbase.random.poisson( λ )\n    Returns a pseudorandom number drawn from a Poisson distribution.\n\n    If `λ <= 0` or `λ` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.poisson( 7.9 );\n\n\nbase.random.poisson.factory( [λ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Poisson distribution.\n\n    If provided `λ`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    λ: number (optional)\n        Mean.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.poisson.factory();\n    > var r = rand( 4.0 );\n    > r = rand( 3.14 );\n\n    // Provide `λ`:\n    > rand = base.random.poisson.factory( 10.0 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.poisson.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.poisson.NAME\n    'poisson'\n\n\nbase.random.poisson.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.poisson.PRNG;\n\n\nbase.random.poisson.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.poisson.seed;\n\n\nbase.random.poisson.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.poisson.seedLength;\n\n\nbase.random.poisson.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.poisson( 10.0 )\n    <number>\n    > r = base.random.poisson( 10.0 )\n    <number>\n    > r = base.random.poisson( 10.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.poisson.state\n    <Uint32Array>\n\n    > r = base.random.poisson( 10.0 )\n    <number>\n    > r = base.random.poisson( 10.0 )\n    <number>\n\n    // Set the state:\n    > base.random.poisson.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.poisson( 10.0 )\n    <number>\n    > r = base.random.poisson( 10.0 )\n    <number>\n\n\nbase.random.poisson.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.poisson.stateLength;\n\n\nbase.random.poisson.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.poisson.byteLength;\n\n\nbase.random.poisson.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.poisson.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.poisson, random.iterators.poisson, random.streams.poisson\n","base.random.poisson.factory":"\nbase.random.poisson.factory( [λ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Poisson distribution.\n\n    If provided `λ`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    λ: number (optional)\n        Mean.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.poisson.factory();\n    > var r = rand( 4.0 );\n    > r = rand( 3.14 );\n\n    // Provide `λ`:\n    > rand = base.random.poisson.factory( 10.0 );\n    > r = rand();\n    > r = rand();","base.random.poisson.NAME":"\nbase.random.poisson.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.poisson.NAME\n    'poisson'","base.random.poisson.PRNG":"\nbase.random.poisson.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.poisson.PRNG;","base.random.poisson.seed":"\nbase.random.poisson.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.poisson.seed;","base.random.poisson.seedLength":"\nbase.random.poisson.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.poisson.seedLength;","base.random.poisson.state":"\nbase.random.poisson.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.poisson( 10.0 )\n    <number>\n    > r = base.random.poisson( 10.0 )\n    <number>\n    > r = base.random.poisson( 10.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.poisson.state\n    <Uint32Array>\n\n    > r = base.random.poisson( 10.0 )\n    <number>\n    > r = base.random.poisson( 10.0 )\n    <number>\n\n    // Set the state:\n    > base.random.poisson.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.poisson( 10.0 )\n    <number>\n    > r = base.random.poisson( 10.0 )\n    <number>","base.random.poisson.stateLength":"\nbase.random.poisson.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.poisson.stateLength;","base.random.poisson.byteLength":"\nbase.random.poisson.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.poisson.byteLength;","base.random.poisson.toJSON":"\nbase.random.poisson.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.poisson.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.poisson, random.iterators.poisson, random.streams.poisson","base.random.randi":"\nbase.random.randi()\n    Returns a pseudorandom number having an integer value.\n\n    The default underlying pseudorandom number generator (PRNG) *may* change in\n    the future. If exact reproducibility is required, either use the `factory`\n    method to explicitly specify a PRNG via the `name` option or use an\n    underlying PRNG directly.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.randi();\n\n\nbase.random.randi.factory( [options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers having integer values.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of the underlying pseudorandom number generator (PRNG). The\n        following PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underlying PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var randi = base.random.randi.factory();\n    > var r = randi();\n    > r = randi();\n\n    // Specify alternative PRNG:\n    > randi = base.random.randi.factory({ 'name': 'minstd' });\n    > r = randi();\n    > r = randi();\n\n\nbase.random.randi.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.randi.NAME\n    'randi'\n\n\nbase.random.randi.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.randi.PRNG;\n\n\nbase.random.randi.MIN\n    Minimum possible value (specific to underlying PRNG).\n\n    Examples\n    --------\n    > var v = base.random.randi.MIN;\n\n\nbase.random.randi.MAX\n    Maximum possible value (specific to underlying PRNG).\n\n    Examples\n    --------\n    > var v = base.random.randi.MAX;\n\n\nbase.random.randi.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.randi.seed;\n\n\nbase.random.randi.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.randi.seedLength;\n\n\nbase.random.randi.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.randi()\n    <number>\n    > r = base.random.randi()\n    <number>\n    > r = base.random.randi()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.randi.state;\n\n    > r = base.random.randi()\n    <number>\n    > r = base.random.randi()\n    <number>\n\n    // Set the state:\n    > base.random.randi.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.randi()\n    <number>\n    > r = base.random.randi()\n    <number>\n\n\nbase.random.randi.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.randi.stateLength;\n\n\nbase.random.randi.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.randi.byteLength;\n\n\nbase.random.randi.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.randi.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.iterators.randi, random.streams.randi, base.random.minstd, base.random.minstdShuffle, base.random.mt19937\n","base.random.randi.factory":"\nbase.random.randi.factory( [options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers having integer values.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of the underlying pseudorandom number generator (PRNG). The\n        following PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underlying PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var randi = base.random.randi.factory();\n    > var r = randi();\n    > r = randi();\n\n    // Specify alternative PRNG:\n    > randi = base.random.randi.factory({ 'name': 'minstd' });\n    > r = randi();\n    > r = randi();","base.random.randi.NAME":"\nbase.random.randi.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.randi.NAME\n    'randi'","base.random.randi.PRNG":"\nbase.random.randi.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.randi.PRNG;","base.random.randi.MIN":"\nbase.random.randi.MIN\n    Minimum possible value (specific to underlying PRNG).\n\n    Examples\n    --------\n    > var v = base.random.randi.MIN;","base.random.randi.MAX":"\nbase.random.randi.MAX\n    Maximum possible value (specific to underlying PRNG).\n\n    Examples\n    --------\n    > var v = base.random.randi.MAX;","base.random.randi.seed":"\nbase.random.randi.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.randi.seed;","base.random.randi.seedLength":"\nbase.random.randi.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.randi.seedLength;","base.random.randi.state":"\nbase.random.randi.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.randi()\n    <number>\n    > r = base.random.randi()\n    <number>\n    > r = base.random.randi()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.randi.state;\n\n    > r = base.random.randi()\n    <number>\n    > r = base.random.randi()\n    <number>\n\n    // Set the state:\n    > base.random.randi.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.randi()\n    <number>\n    > r = base.random.randi()\n    <number>","base.random.randi.stateLength":"\nbase.random.randi.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.randi.stateLength;","base.random.randi.byteLength":"\nbase.random.randi.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.randi.byteLength;","base.random.randi.toJSON":"\nbase.random.randi.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.randi.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.iterators.randi, random.streams.randi, base.random.minstd, base.random.minstdShuffle, base.random.mt19937","base.random.randn":"\nbase.random.randn()\n    Returns a pseudorandom number drawn from a standard normal distribution.\n\n    The default underlying pseudorandom number generator (PRNG) *may* change in\n    the future. If exact reproducibility is required, either use the `factory`\n    method to explicitly specify a PRNG via the `name` option or use an\n    underlying PRNG directly.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.randn();\n\n\nbase.random.randn.factory( [options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a standard normal distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of the underlying pseudorandom number generator (PRNG) that samples\n        from a standard normal distribution. The following PRNGs are supported:\n\n        - improved-ziggurat: improved ziggurat method.\n        - box-muller: Box-Muller transform.\n\n        Default: 'improved-ziggurat'.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underlying PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.randn.factory();\n    > var r = rand();\n    > r = rand();\n\n    // Specify alternative PRNG:\n    > var rand = base.random.randn.factory({ 'name': 'box-muller' });\n    > r = rand();\n    > r = rand();\n\n\nbase.random.randn.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.randn.NAME\n    'randn'\n\n\nbase.random.randn.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.randn.PRNG;\n\n\nbase.random.randn.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.randn.seed;\n\n\nbase.random.randn.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.randn.seedLength;\n\n\nbase.random.randn.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.randn()\n    <number>\n    > r = base.random.randn()\n    <number>\n    > r = base.random.randn()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.randn.state;\n\n    > r = base.random.randn()\n    <number>\n    > r = base.random.randn()\n    <number>\n\n    // Set the state:\n    > base.random.randn.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.randn()\n    <number>\n    > r = base.random.randn()\n    <number>\n\n\nbase.random.randn.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.randn.stateLength;\n\n\nbase.random.randn.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.randn.byteLength;\n\n\nbase.random.randn.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.randn.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.iterators.randn, random.streams.randn, base.random.improvedZiggurat, base.random.randu\n","base.random.randn.factory":"\nbase.random.randn.factory( [options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a standard normal distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of the underlying pseudorandom number generator (PRNG) that samples\n        from a standard normal distribution. The following PRNGs are supported:\n\n        - improved-ziggurat: improved ziggurat method.\n        - box-muller: Box-Muller transform.\n\n        Default: 'improved-ziggurat'.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underlying PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.randn.factory();\n    > var r = rand();\n    > r = rand();\n\n    // Specify alternative PRNG:\n    > var rand = base.random.randn.factory({ 'name': 'box-muller' });\n    > r = rand();\n    > r = rand();","base.random.randn.NAME":"\nbase.random.randn.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.randn.NAME\n    'randn'","base.random.randn.PRNG":"\nbase.random.randn.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.randn.PRNG;","base.random.randn.seed":"\nbase.random.randn.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.randn.seed;","base.random.randn.seedLength":"\nbase.random.randn.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.randn.seedLength;","base.random.randn.state":"\nbase.random.randn.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.randn()\n    <number>\n    > r = base.random.randn()\n    <number>\n    > r = base.random.randn()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.randn.state;\n\n    > r = base.random.randn()\n    <number>\n    > r = base.random.randn()\n    <number>\n\n    // Set the state:\n    > base.random.randn.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.randn()\n    <number>\n    > r = base.random.randn()\n    <number>","base.random.randn.stateLength":"\nbase.random.randn.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.randn.stateLength;","base.random.randn.byteLength":"\nbase.random.randn.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.randn.byteLength;","base.random.randn.toJSON":"\nbase.random.randn.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.randn.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.iterators.randn, random.streams.randn, base.random.improvedZiggurat, base.random.randu","base.random.randu":"\nbase.random.randu()\n    Returns a pseudorandom number drawn from a uniform distribution.\n\n    The default underlying pseudorandom number generator (PRNG) *may* change in\n    the future. If exact reproducibility is required, either use the `factory`\n    method to explicitly specify a PRNG via the `name` option or use an\n    underlying PRNG directly.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number on the interval `[0,1)`.\n\n    Examples\n    --------\n    > var r = base.random.randu();\n\n\nbase.random.randu.factory( [options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a uniform distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of the underlying pseudorandom number generator (PRNG). The\n        following PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underlying PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.randu.factory();\n    > var r = rand();\n    > r = rand();\n\n    // Specify alternative PRNG:\n    > var rand = base.random.randu.factory({ 'name': 'minstd' });\n    > r = rand();\n    > r = rand();\n\n\nbase.random.randu.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.randu.NAME\n    'randu'\n\n\nbase.random.randu.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.randu.PRNG;\n\n\nbase.random.randu.MIN\n    Minimum possible value (specific to underlying PRNG).\n\n    Examples\n    --------\n    > var v = base.random.randu.MIN;\n\n\nbase.random.randu.MAX\n    Maximum possible value (specific to underlying PRNG).\n\n    Examples\n    --------\n    > var v = base.random.randu.MAX;\n\n\nbase.random.randu.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.randu.seed;\n\n\nbase.random.randu.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.randu.seedLength;\n\n\nbase.random.randu.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.randu()\n    <number>\n    > r = base.random.randu()\n    <number>\n    > r = base.random.randu()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.randu.state;\n\n    > r = base.random.randu()\n    <number>\n    > r = base.random.randu()\n    <number>\n\n    // Set the state:\n    > base.random.randu.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.randu()\n    <number>\n    > r = base.random.randu()\n    <number>\n\n\nbase.random.randu.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.randu.stateLength;\n\n\nbase.random.randu.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.randu.byteLength;\n\n\nbase.random.randu.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.randu.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.randu, random.iterators.randu, random.streams.randu, base.random.discreteUniform, base.random.randn\n","base.random.randu.factory":"\nbase.random.randu.factory( [options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a uniform distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of the underlying pseudorandom number generator (PRNG). The\n        following PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underlying PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.randu.factory();\n    > var r = rand();\n    > r = rand();\n\n    // Specify alternative PRNG:\n    > var rand = base.random.randu.factory({ 'name': 'minstd' });\n    > r = rand();\n    > r = rand();","base.random.randu.NAME":"\nbase.random.randu.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.randu.NAME\n    'randu'","base.random.randu.PRNG":"\nbase.random.randu.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.randu.PRNG;","base.random.randu.MIN":"\nbase.random.randu.MIN\n    Minimum possible value (specific to underlying PRNG).\n\n    Examples\n    --------\n    > var v = base.random.randu.MIN;","base.random.randu.MAX":"\nbase.random.randu.MAX\n    Maximum possible value (specific to underlying PRNG).\n\n    Examples\n    --------\n    > var v = base.random.randu.MAX;","base.random.randu.seed":"\nbase.random.randu.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.randu.seed;","base.random.randu.seedLength":"\nbase.random.randu.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.randu.seedLength;","base.random.randu.state":"\nbase.random.randu.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.randu()\n    <number>\n    > r = base.random.randu()\n    <number>\n    > r = base.random.randu()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.randu.state;\n\n    > r = base.random.randu()\n    <number>\n    > r = base.random.randu()\n    <number>\n\n    // Set the state:\n    > base.random.randu.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.randu()\n    <number>\n    > r = base.random.randu()\n    <number>","base.random.randu.stateLength":"\nbase.random.randu.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.randu.stateLength;","base.random.randu.byteLength":"\nbase.random.randu.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.randu.byteLength;","base.random.randu.toJSON":"\nbase.random.randu.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.randu.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.randu, random.iterators.randu, random.streams.randu, base.random.discreteUniform, base.random.randn","base.random.rayleigh":"\nbase.random.rayleigh( σ )\n    Returns a pseudorandom number drawn from a Rayleigh distribution.\n\n    If `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.rayleigh( 2.5 );\n\n\nbase.random.rayleigh.factory( [σ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Rayleigh distribution.\n\n    If provided `σ`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `σ`, the returned PRNG requires that `σ` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    σ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.rayleigh.factory();\n    > var r = rand( 5.0 );\n    > r = rand( 10.0 );\n\n    // Provide `σ`:\n    > rand = base.random.rayleigh.factory( 5.0 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.rayleigh.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.rayleigh.NAME\n    'rayleigh'\n\n\nbase.random.rayleigh.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.rayleigh.PRNG;\n\n\nbase.random.rayleigh.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.rayleigh.seed;\n\n\nbase.random.rayleigh.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.rayleigh.seedLength;\n\n\nbase.random.rayleigh.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.rayleigh( 5.0 )\n    <number>\n    > r = base.random.rayleigh( 5.0 )\n    <number>\n    > r = base.random.rayleigh( 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.rayleigh.state\n    <Uint32Array>\n\n    > r = base.random.rayleigh( 5.0 )\n    <number>\n    > r = base.random.rayleigh( 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.rayleigh.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.rayleigh( 5.0 )\n    <number>\n    > r = base.random.rayleigh( 5.0 )\n    <number>\n\n\nbase.random.rayleigh.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.rayleigh.stateLength;\n\n\nbase.random.rayleigh.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.rayleigh.byteLength;\n\n\nbase.random.rayleigh.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.rayleigh.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.rayleigh, random.iterators.rayleigh, random.streams.rayleigh\n","base.random.rayleigh.factory":"\nbase.random.rayleigh.factory( [σ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Rayleigh distribution.\n\n    If provided `σ`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `σ`, the returned PRNG requires that `σ` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    σ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.rayleigh.factory();\n    > var r = rand( 5.0 );\n    > r = rand( 10.0 );\n\n    // Provide `σ`:\n    > rand = base.random.rayleigh.factory( 5.0 );\n    > r = rand();\n    > r = rand();","base.random.rayleigh.NAME":"\nbase.random.rayleigh.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.rayleigh.NAME\n    'rayleigh'","base.random.rayleigh.PRNG":"\nbase.random.rayleigh.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.rayleigh.PRNG;","base.random.rayleigh.seed":"\nbase.random.rayleigh.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.rayleigh.seed;","base.random.rayleigh.seedLength":"\nbase.random.rayleigh.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.rayleigh.seedLength;","base.random.rayleigh.state":"\nbase.random.rayleigh.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.rayleigh( 5.0 )\n    <number>\n    > r = base.random.rayleigh( 5.0 )\n    <number>\n    > r = base.random.rayleigh( 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.rayleigh.state\n    <Uint32Array>\n\n    > r = base.random.rayleigh( 5.0 )\n    <number>\n    > r = base.random.rayleigh( 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.rayleigh.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.rayleigh( 5.0 )\n    <number>\n    > r = base.random.rayleigh( 5.0 )\n    <number>","base.random.rayleigh.stateLength":"\nbase.random.rayleigh.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.rayleigh.stateLength;","base.random.rayleigh.byteLength":"\nbase.random.rayleigh.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.rayleigh.byteLength;","base.random.rayleigh.toJSON":"\nbase.random.rayleigh.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.rayleigh.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.rayleigh, random.iterators.rayleigh, random.streams.rayleigh","base.random.t":"\nbase.random.t( v )\n    Returns a pseudorandom number drawn from a Student's t distribution.\n\n    If `v <= 0` or `v` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.t( 2.0 );\n\n\nbase.random.t.factory( [v, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Student's t distribution.\n\n    If provided `v`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `v`, the returned PRNG requires that `v` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    v: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.t.factory();\n    > var r = rand( 5.0 );\n    > r = rand( 3.14 );\n\n    // Provide `v`:\n    > rand = base.random.t.factory( 5.0 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.t.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.t.NAME\n    't'\n\n\nbase.random.t.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.t.PRNG;\n\n\nbase.random.t.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.t.seed;\n\n\nbase.random.t.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.t.seedLength;\n\n\nbase.random.t.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.t( 10.0 )\n    <number>\n    > r = base.random.t( 10.0 )\n    <number>\n    > r = base.random.t( 10.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.t.state\n    <Uint32Array>\n\n    > r = base.random.t( 10.0 )\n    <number>\n    > r = base.random.t( 10.0 )\n    <number>\n\n    // Set the state:\n    > base.random.t.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.t( 10.0 )\n    <number>\n    > r = base.random.t( 10.0 )\n    <number>\n\n\nbase.random.t.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.t.stateLength;\n\n\nbase.random.t.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.t.byteLength;\n\n\nbase.random.t.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.t.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.t, random.iterators.t, random.streams.t\n","base.random.t.factory":"\nbase.random.t.factory( [v, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Student's t distribution.\n\n    If provided `v`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `v`, the returned PRNG requires that `v` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    v: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.t.factory();\n    > var r = rand( 5.0 );\n    > r = rand( 3.14 );\n\n    // Provide `v`:\n    > rand = base.random.t.factory( 5.0 );\n    > r = rand();\n    > r = rand();","base.random.t.NAME":"\nbase.random.t.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.t.NAME\n    't'","base.random.t.PRNG":"\nbase.random.t.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.t.PRNG;","base.random.t.seed":"\nbase.random.t.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.t.seed;","base.random.t.seedLength":"\nbase.random.t.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.t.seedLength;","base.random.t.state":"\nbase.random.t.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.t( 10.0 )\n    <number>\n    > r = base.random.t( 10.0 )\n    <number>\n    > r = base.random.t( 10.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.t.state\n    <Uint32Array>\n\n    > r = base.random.t( 10.0 )\n    <number>\n    > r = base.random.t( 10.0 )\n    <number>\n\n    // Set the state:\n    > base.random.t.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.t( 10.0 )\n    <number>\n    > r = base.random.t( 10.0 )\n    <number>","base.random.t.stateLength":"\nbase.random.t.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.t.stateLength;","base.random.t.byteLength":"\nbase.random.t.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.t.byteLength;","base.random.t.toJSON":"\nbase.random.t.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.t.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.t, random.iterators.t, random.streams.t","base.random.triangular":"\nbase.random.triangular( a, b, c )\n    Returns a pseudorandom number drawn from a triangular distribution.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.triangular( 2.0, 5.0, 3.33 );\n\n\nbase.random.triangular.factory( [a, b, c, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a triangular distribution.\n\n    If provided `a`, `b`, and `c`, the returned PRNG returns random variates\n    drawn from the specified distribution.\n\n    If not provided `a`, `b`, and `c`, the returned PRNG requires that `a`, `b`,\n    and `c` be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    c: number (optional)\n        Mode.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.triangular.factory();\n    > var r = rand( 0.0, 1.0, 0.5 );\n    > r = rand( -2.0, 2.0, 1.0 );\n\n    // Provide `a`, `b`, and `c`:\n    > rand = base.random.triangular.factory( 0.0, 1.0, 0.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.triangular.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.triangular.NAME\n    'triangular'\n\n\nbase.random.triangular.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.triangular.PRNG;\n\n\nbase.random.triangular.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.triangular.seed;\n\n\nbase.random.triangular.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.triangular.seedLength;\n\n\nbase.random.triangular.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.triangular.state\n    <Uint32Array>\n\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n\n    // Set the state:\n    > base.random.triangular.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n\n\nbase.random.triangular.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.triangular.stateLength;\n\n\nbase.random.triangular.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.triangular.byteLength;\n\n\nbase.random.triangular.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.triangular.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.triangular, random.iterators.triangular, random.streams.triangular\n","base.random.triangular.factory":"\nbase.random.triangular.factory( [a, b, c, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a triangular distribution.\n\n    If provided `a`, `b`, and `c`, the returned PRNG returns random variates\n    drawn from the specified distribution.\n\n    If not provided `a`, `b`, and `c`, the returned PRNG requires that `a`, `b`,\n    and `c` be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    c: number (optional)\n        Mode.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.triangular.factory();\n    > var r = rand( 0.0, 1.0, 0.5 );\n    > r = rand( -2.0, 2.0, 1.0 );\n\n    // Provide `a`, `b`, and `c`:\n    > rand = base.random.triangular.factory( 0.0, 1.0, 0.5 );\n    > r = rand();\n    > r = rand();","base.random.triangular.NAME":"\nbase.random.triangular.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.triangular.NAME\n    'triangular'","base.random.triangular.PRNG":"\nbase.random.triangular.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.triangular.PRNG;","base.random.triangular.seed":"\nbase.random.triangular.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.triangular.seed;","base.random.triangular.seedLength":"\nbase.random.triangular.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.triangular.seedLength;","base.random.triangular.state":"\nbase.random.triangular.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.triangular.state\n    <Uint32Array>\n\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n\n    // Set the state:\n    > base.random.triangular.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>","base.random.triangular.stateLength":"\nbase.random.triangular.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.triangular.stateLength;","base.random.triangular.byteLength":"\nbase.random.triangular.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.triangular.byteLength;","base.random.triangular.toJSON":"\nbase.random.triangular.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.triangular.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.triangular, random.iterators.triangular, random.streams.triangular","base.random.uniform":"\nbase.random.uniform( a, b )\n    Returns a pseudorandom number drawn from a continuous uniform distribution.\n\n    If `a >= b`, the function returns `NaN`.\n\n    If `a` or `b` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support (inclusive).\n\n    b: number\n        Maximum support (exclusive).\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.uniform( 2.0, 5.0 );\n\n\nbase.random.uniform.factory( [a, b, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a continuous uniform distribution.\n\n    If provided `a` and `b`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `a` and `b`, the returned PRNG requires that both `a` and\n    `b` be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support (inclusive).\n\n    b: number (optional)\n        Maximum support (exclusive).\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.uniform.factory();\n    > var r = rand( 0.0, 1.0 );\n    > r = rand( -2.0, 2.0 );\n\n    // Provide `a` and `b`:\n    > rand = base.random.uniform.factory( 0.0, 1.0 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.uniform.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.uniform.NAME\n    'uniform'\n\n\nbase.random.uniform.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.uniform.PRNG;\n\n\nbase.random.uniform.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.uniform.seed;\n\n\nbase.random.uniform.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.uniform.seedLength;\n\n\nbase.random.uniform.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.uniform( 2.0, 5.0 )\n    <number>\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.uniform.state\n    <Uint32Array>\n\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.uniform.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>\n\n\nbase.random.uniform.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.uniform.stateLength;\n\n\nbase.random.uniform.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.uniform.byteLength;\n\n\nbase.random.uniform.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.uniform.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.uniform, random.iterators.uniform, random.streams.uniform, base.random.discreteUniform, base.random.randu\n","base.random.uniform.factory":"\nbase.random.uniform.factory( [a, b, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a continuous uniform distribution.\n\n    If provided `a` and `b`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `a` and `b`, the returned PRNG requires that both `a` and\n    `b` be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support (inclusive).\n\n    b: number (optional)\n        Maximum support (exclusive).\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.uniform.factory();\n    > var r = rand( 0.0, 1.0 );\n    > r = rand( -2.0, 2.0 );\n\n    // Provide `a` and `b`:\n    > rand = base.random.uniform.factory( 0.0, 1.0 );\n    > r = rand();\n    > r = rand();","base.random.uniform.NAME":"\nbase.random.uniform.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.uniform.NAME\n    'uniform'","base.random.uniform.PRNG":"\nbase.random.uniform.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.uniform.PRNG;","base.random.uniform.seed":"\nbase.random.uniform.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.uniform.seed;","base.random.uniform.seedLength":"\nbase.random.uniform.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.uniform.seedLength;","base.random.uniform.state":"\nbase.random.uniform.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.uniform( 2.0, 5.0 )\n    <number>\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.uniform.state\n    <Uint32Array>\n\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.uniform.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>","base.random.uniform.stateLength":"\nbase.random.uniform.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.uniform.stateLength;","base.random.uniform.byteLength":"\nbase.random.uniform.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.uniform.byteLength;","base.random.uniform.toJSON":"\nbase.random.uniform.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.uniform.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.uniform, random.iterators.uniform, random.streams.uniform, base.random.discreteUniform, base.random.randu","base.random.weibull":"\nbase.random.weibull( k, λ )\n    Returns a pseudorandom number drawn from a Weibull distribution.\n\n    If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n    If either `λ` or `k` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Scale parameter.\n\n    λ: number\n        Shape parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.weibull( 2.0, 5.0 );\n\n\nbase.random.weibull.factory( [k, λ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Weibull distribution.\n\n    If provided `k` and `λ`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `k` and `λ`, the returned PRNG requires that both\n    `k` and `λ` be provided at each invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Scale parameter.\n\n    λ: number (optional)\n        Shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.weibull.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `λ` and `k`:\n    > rand = base.random.weibull.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.weibull.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.weibull.NAME\n    'weibull'\n\n\nbase.random.weibull.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.weibull.PRNG;\n\n\nbase.random.weibull.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.weibull.seed;\n\n\nbase.random.weibull.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.weibull.seedLength;\n\n\nbase.random.weibull.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.weibull( 2.0, 5.0 )\n    <number>\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.weibull.state\n    <Uint32Array>\n\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.weibull.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>\n\n\nbase.random.weibull.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.weibull.stateLength;\n\n\nbase.random.weibull.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.weibull.byteLength;\n\n\nbase.random.weibull.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.weibull.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.weibull, random.iterators.weibull, random.streams.weibull\n","base.random.weibull.factory":"\nbase.random.weibull.factory( [k, λ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Weibull distribution.\n\n    If provided `k` and `λ`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `k` and `λ`, the returned PRNG requires that both\n    `k` and `λ` be provided at each invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Scale parameter.\n\n    λ: number (optional)\n        Shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.weibull.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `λ` and `k`:\n    > rand = base.random.weibull.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.weibull.NAME":"\nbase.random.weibull.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.weibull.NAME\n    'weibull'","base.random.weibull.PRNG":"\nbase.random.weibull.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.weibull.PRNG;","base.random.weibull.seed":"\nbase.random.weibull.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.weibull.seed;","base.random.weibull.seedLength":"\nbase.random.weibull.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.weibull.seedLength;","base.random.weibull.state":"\nbase.random.weibull.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.weibull( 2.0, 5.0 )\n    <number>\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.weibull.state\n    <Uint32Array>\n\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.weibull.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>","base.random.weibull.stateLength":"\nbase.random.weibull.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.weibull.stateLength;","base.random.weibull.byteLength":"\nbase.random.weibull.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.weibull.byteLength;","base.random.weibull.toJSON":"\nbase.random.weibull.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.weibull.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.weibull, random.iterators.weibull, random.streams.weibull","base.rcbrt":"\nbase.rcbrt( x )\n    Computes the reciprocal cube root of a double-precision floating-point\n    number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Reciprocal cube root.\n\n    Examples\n    --------\n    > var y = base.rcbrt( 8.0 )\n    0.5\n    > y = base.rcbrt( 1000.0 )\n    0.1\n    > y = base.rcbrt( 0.0 )\n    Infinity\n    > y = base.rcbrt( PINF )\n    0.0\n    > y = base.rcbrt( -8.0 )\n    -0.5\n    > y = base.rcbrt( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cbrt\n","base.rcbrtf":"\nbase.rcbrtf( x )\n    Computes the reciprocal cube root of a single-precision floating-point\n    number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Reciprocal cube root.\n\n    Examples\n    --------\n    > var y = base.rcbrtf( 8.0 )\n    0.5\n    > y = base.rcbrtf( 1000.0 )\n    ~0.1\n    > y = base.rcbrtf( 0.0 )\n    Infinity\n    > y = base.rcbrtf( PINF )\n    0.0\n    > y = base.rcbrtf( -8.0 )\n    -0.5\n    > y = base.rcbrtf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.rcbrt, base.cbrtf\n","base.reldiff":"\nbase.reldiff( x, y[, scale] )\n    Computes the relative difference of two real numbers.\n\n    By default, the function scales the absolute difference by dividing the\n    absolute difference by the maximum absolute value of `x` and `y`. To scale\n    by a different function, specify a scale function name.\n\n    The following `scale` functions are supported:\n\n    - 'max-abs': maximum absolute value of `x` and `y` (default).\n    - 'max': maximum value of `x` and `y`.\n    - 'min-abs': minimum absolute value of `x` and `y`.\n    - 'min': minimum value of `x` and `y`.\n    - 'mean-abs': arithmetic mean of the absolute values of `x` and `y`.\n    - 'mean': arithmetic mean of `x` and `y`.\n    - 'x': `x` (*noncommutative*).\n    - 'y': `y` (*noncommutative*).\n\n    To use a custom scale function, provide a function which accepts two numeric\n    arguments `x` and `y`.\n\n    If the absolute difference of `x` and `y` is `0`, the relative difference is\n    always `0`.\n\n    If `|x| = |y| = infinity`, the function returns `NaN`.\n\n    If `|x| = |-y| = infinity`, the relative difference is `+infinity`.\n\n    If a `scale` function returns `0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    scale: string|Function (optional)\n        Scale function. Default: `'max-abs'`.\n\n    Returns\n    -------\n    out: number\n        Relative difference.\n\n    Examples\n    --------\n    > var d = base.reldiff( 2.0, 5.0 )\n    0.6\n    > d = base.reldiff( -1.0, 3.14 )\n    ~1.318\n    > d = base.reldiff( -2.0, 5.0, 'max-abs' )\n    1.4\n    > d = base.reldiff( -2.0, 5.0, 'max' )\n    1.4\n    > d = base.reldiff( -2.0, 5.0, 'min-abs' )\n    3.5\n    > d = base.reldiff( -2.0, 5.0, 'min' )\n    3.5\n    > d = base.reldiff( -2.0, 5.0, 'mean-abs' )\n    2.0\n    > d = base.reldiff( -2.0, 5.0, 'mean' )\n    ~4.667\n    > d = base.reldiff( -2.0, 5.0, 'x' )\n    3.5\n    > d = base.reldiff( 5.0, -2.0, 'x' )\n    1.4\n    > d = base.reldiff( -2.0, 5.0, 'y' )\n    1.4\n    > d = base.reldiff( 5.0, -2.0, 'y' )\n    3.5\n\n    // Custom scale function:\n    > function scale( x, y ) {\n    ...     var s;\n    ...\n    ...     x = base.abs( x );\n    ...     y = base.abs( y );\n    ...\n    ...     // Maximum absolute value:\n    ...     s = (x < y ) ? y : x;\n    ...\n    ...     // Scale in units of epsilon:\n    ...     return s * EPS;\n    ... };\n    > d = base.reldiff( 12.15, 12.149999999999999, scale )\n    ~0.658\n\n    See Also\n    --------\n    base.absdiff, base.epsdiff\n","base.removeFirst":"\nbase.removeFirst( str, n )\n    Removes the first `n` UTF-16 code units of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of UTF-16 code units to remove.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.removeFirst( 'beep', 1 )\n    'eep'\n    > out = base.removeFirst( 'Boop', 1 )\n    'oop'\n    > out = base.removeFirst( 'foo bar', 5 )\n    'ar'\n\n    See Also\n    --------\n    base.removeFirstCodePoint, base.removeFirstGraphemeCluster, base.removeLast\n","base.removeFirstCodePoint":"\nbase.removeFirstCodePoint( str, n )\n    Removes the first `n` Unicode code points of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of Unicode code points to remove.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.removeFirstCodePoint( 'beep', 1 )\n    'eep'\n    > out = base.removeFirstCodePoint( 'Boop', 1 )\n    'oop'\n    > out = base.removeFirstCodePoint( 'foo bar', 5 )\n    'ar'\n\n    See Also\n    --------\n    base.removeLastCodePoint, base.removeFirstGraphemeCluster, base.removeFirst\n","base.removeFirstGraphemeCluster":"\nbase.removeFirstGraphemeCluster( str, n )\n    Removes the first `n` grapheme clusters (i.e., user-perceived characters)\n    of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of grapheme clusters to remove.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.removeFirstGraphemeCluster( 'beep', 1 )\n    'eep'\n    > out = base.removeFirstGraphemeCluster( 'Boop', 1 )\n    'oop'\n    > out = base.removeFirstGraphemeCluster( 'foo bar', 5 )\n    'ar'\n\n    See Also\n    --------\n    base.removeFirstCodePoint, base.removeLastGraphemeCluster, base.removeFirst\n","base.removeLast":"\nbase.removeLast( str, n )\n    Removes the last `n` UTF-16 code units of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of UTF-16 code units to remove.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.removeLast( 'beep', 1 )\n    'bee'\n    > out = base.removeLast( 'Boop', 1 )\n    'Boo'\n    > out = base.removeLast( 'foo bar', 5 )\n    'fo'\n\n    See Also\n    --------\n    base.removeLastCodePoint, base.removeLastGraphemeCluster, base.removeFirst\n","base.removeLastCodePoint":"\nbase.removeLastCodePoint( str, n )\n    Removes the last `n` Unicode code points of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of Unicode code points to remove.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.removeLastCodePoint( 'beep', 1 )\n    'bee'\n    > out = base.removeLastCodePoint( 'Boop', 1 )\n    'Boo'\n    > out = base.removeLastCodePoint( 'foo bar', 5 )\n    'fo'\n\n    See Also\n    --------\n    base.removeFirstCodePoint, base.removeLastGraphemeCluster, base.removeLast\n","base.removeLastGraphemeCluster":"\nbase.removeLastGraphemeCluster( str, n )\n    Removes the last `n` grapheme clusters (i.e., user-perceived characters)\n    of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of grapheme clusters to remove.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.removeLastGraphemeCluster( 'beep', 1 )\n    'bee'\n    > out = base.removeLastGraphemeCluster( 'Boop', 1 )\n    'Boo'\n    > out = base.removeLastGraphemeCluster( 'foo bar', 5 )\n    'fo'\n\n    See Also\n    --------\n    base.removeFirstCodePoint, base.removeLastCodePoint, base.removeLast\n","base.rempio2":"\nbase.rempio2( x, y )\n    Computes `x - nπ/2 = r`.\n\n    The function returns `n` and stores the remainder `r` as the two numbers\n    `y[0]` and `y[1]`, such that `y[0] + y[1] = r`.\n\n    For input values larger than `2^20 * π/2` in magnitude, the function only\n    returns the last three binary digits of `n` and not the full result.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    y: Array|TypedArray|Object\n        Remainder elements.\n\n    Returns\n    -------\n    n: integer\n        Factor of `π/2`.\n\n    Examples\n    --------\n    > var y = [ 0.0, 0.0 ];\n    > var n = base.rempio2( 128.0, y )\n    81\n    > var y1 = y[ 0 ]\n    ~0.765\n    > var y2 = y[ 1 ]\n    ~3.618e-17\n\n\n","base.repeat":"\nbase.repeat( str, n )\n    Repeats a string `n` times and returns the concatenated result.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of repetitions.\n\n    Returns\n    -------\n    out: string\n        Repeated string.\n\n    Examples\n    --------\n    > var out = base.repeat( 'a', 5 )\n    'aaaaa'\n    > out = base.repeat( '', 100 )\n    ''\n    > out = base.repeat( 'beep', 0 )\n    ''\n\n","base.replace":"\nbase.replace( str, search, newval )\n    Replaces search occurrences with a replacement string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: RegExp\n        Search expression.\n\n    newval: string|Function\n        Replacement value or function.\n\n    Returns\n    -------\n    out: string\n        String containing replacement(s).\n\n    Examples\n    --------\n    > function replacer( match, p1 ) { return '/'+p1+'/'; };\n    > var str = 'Oranges and lemons';\n    > var out = base.replace( str, /([^\\s]+)/gi, replacer )\n    '/Oranges/ /and/ /lemons/'\n\n    // Replace only first match:\n    > out = base.replace( 'beep', /e/, 'o' )\n    'boep'\n\n    See Also\n    --------\n    base.replaceAfter, base.replaceBefore, base.replaceAfterLast, base.replaceBeforeLast\n","base.replaceAfter":"\nbase.replaceAfter( str, search, replacement, fromIndex )\n    Replaces the substring after the first occurrence of a specified search\n    string.\n\n    If unable to find a search string, the function returns the input string\n    unchanged.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search string.\n\n    replacement: string\n        Replacement string.\n\n    fromIndex: integer\n        Starting index (inclusive). If less than zero, the starting index is\n        resolved relative to the last string character, with the last string\n        character corresponding to `fromIndex = -1`.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.replaceAfter( 'beep boop', ' ', 'foo', 0 )\n    'beep foo'\n    > out = base.replaceAfter( 'beep boop', 'o', 'foo', 0 )\n    'beep bofoo'\n    > out = base.replaceAfter( 'Hello World!', 'o', 'foo', 5 )\n    'Hello Wofoo'\n    > out = base.replaceAfter( 'beep boop beep baz', 'beep', 'foo', 5 )\n    'beep boop beepfoo'\n\n    See Also\n    --------\n    base.replaceAfterLast, base.replaceBefore, base.replaceBeforeLast\n","base.replaceAfterLast":"\nbase.replaceAfterLast( str, search, replacement, fromIndex )\n    Replaces the substring after the last occurrence of a specified search\n    string.\n\n    If unable to find a search string, the function returns the input string\n    unchanged.\n\n    The function scans an input string from the starting index to the beginning\n    of the string (i.e., backward).\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search string.\n\n    replacement: string\n        Replacement string.\n\n    fromIndex: integer\n        Starting index (inclusive). If less than zero, the starting index is\n        resolved relative to the last string character, with the last string\n        character corresponding to `fromIndex = -1`.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var str = 'beep boop';\n    > var out = base.replaceAfterLast( str, ' ', 'foo', str.length )\n    'beep foo'\n    > out = base.replaceAfterLast( str, 'o', 'foo', str.length )\n    'beep boofoo'\n    > out = base.replaceAfterLast( 'Hello World!', 'o', 'foo', 5 )\n    'Hellofoo'\n\n    See Also\n    --------\n    base.replaceAfter, base.replaceBeforeLast, base.replaceBefore\n","base.replaceBefore":"\nbase.replaceBefore( str, search, replacement, fromIndex )\n    Replaces the substring before the first occurrence of a specified search\n    string.\n\n    If unable to find a search string, the function returns the input string\n    unchanged.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search string.\n\n    replacement: string\n        Replacement string.\n\n    fromIndex: integer\n        Starting index (inclusive). If less than zero, the starting index is\n        resolved relative to the last string character, with the last string\n        character corresponding to `fromIndex = -1`.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.replaceBefore( 'beep boop', ' ', 'foo', 0 )\n    'foo boop'\n    > out = base.replaceBefore( 'beep boop', 'o', 'foo', 0 )\n    'foooop'\n\n    See Also\n    --------\n    base.replaceAfter, base.replaceBeforeLast, base.replaceAfterLast\n","base.replaceBeforeLast":"\nbase.replaceBeforeLast( str, search, replacement, fromIndex )\n    Replaces the substring before the last occurrence of a specified search\n    string.\n\n    If unable to find a search string, the function returns the input string\n    unchanged.\n\n    The function scans an input string from the starting index to the beginning\n    of the string (i.e., backward).\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search string.\n\n    replacement: string\n        Replacement string.\n\n    fromIndex: integer\n        Starting index (inclusive). If less than zero, the starting index is\n        resolved relative to the last string character, with the last string\n        character corresponding to `fromIndex = -1`.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var str = 'beep boop';\n    > var out = base.replaceBeforeLast( str, ' ', 'foo', str.length )\n    'foo boop'\n    > out = base.replaceBeforeLast( str, 'o', 'foo', str.length )\n    'fooop'\n    > out = base.replaceBeforeLast( 'Hello World!', 'o', 'foo', 5 )\n    'fooo World!'\n\n    See Also\n    --------\n    base.replaceAfterLast, base.replaceAfter, base.replaceBefore\n","base.reverse":"\nbase.reverse( str )\n    Reverses the UTF-16 code units of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.reverse( 'beep' )\n    'peeb'\n    > out = base.reverse( 'Boop' )\n    'pooB'\n    > out = base.reverse( 'foo bar' )\n    'rab oof'\n\n    See Also\n    --------\n    base.reverseCodePoints, base.reverseGraphemeClusters\n","base.reverseCodePoints":"\nbase.reverseCodePoints( str )\n    Reverses the Unicode code points of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.reverseCodePoints( 'beep' )\n    'peeb'\n    > out = base.reverseCodePoints( 'Boop' )\n    'pooB'\n    > out = base.reverseCodePoints( 'foo bar' )\n    'rab oof'\n\n    See Also\n    --------\n    base.reverseGraphemeClusters, base.reverse\n","base.reverseGraphemeClusters":"\nbase.reverseGraphemeClusters( str )\n    Reverses the grapheme clusters (i.e., user-perceived characters) of a\n    string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.reverseGraphemeClusters( 'beep' )\n    'peeb'\n    > out = base.reverseGraphemeClusters( 'Boop' )\n    'pooB'\n    > out = base.reverseGraphemeClusters( 'foo bar' )\n    'rab oof'\n\n    See Also\n    --------\n    base.reverseCodePoints, base.reverse\n","base.rightPad":"\nbase.rightPad( str, len, pad )\n    Right pads a string such that the padded string has a length of at least\n    `len`.\n\n    An output string is not guaranteed to have a length of exactly `len`, but to\n    have a length of at least `len`. To generate a padded string having a length\n    equal to `len`, post-process a padded string by trimming off excess\n    characters.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    len: integer\n        Minimum string length.\n\n    pad: string\n        String used to pad.\n\n    Returns\n    -------\n    out: string\n        Padded string.\n\n    Examples\n    --------\n    > var out = base.rightPad( 'a', 5, ' ' )\n    'a    '\n    > out = base.rightPad( 'beep', 10, 'b' )\n    'beepbbbbbb'\n    > out = base.rightPad( 'boop', 12, 'beep' )\n    'boopbeepbeep'\n\n    See Also\n    --------\n    base.leftPad\n","base.rightTrim":"\nbase.rightTrim( str )\n    Trims whitespace from the end of a string.\n\n    \"Whitespace\" is defined as the following characters:\n\n    - \\f\n    - \\n\n    - \\r\n    - \\t\n    - \\v\n    - \\u0020\n    - \\u00a0\n    - \\u1680\n    - \\u2000-\\u200a\n    - \\u2028\n    - \\u2029\n    - \\u202f\n    - \\u205f\n    - \\u3000\n    - \\ufeff\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Trimmed string.\n\n    Examples\n    --------\n    > var out = base.rightTrim( ' \\t\\t\\n  Beep \\r\\n\\t  ' )\n    ' \\t\\t\\n  Beep'\n\n    See Also\n    --------\n    base.leftTrim\n","base.risingFactorial":"\nbase.risingFactorial( x, n )\n    Computes the rising factorial of `x` and `n`.\n\n    If provided a non-integer for `n`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        First function parameter.\n\n    n: integer\n        Second function parameter.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var v = base.risingFactorial( 0.9, 5 )\n    ~94.766\n    > v = base.risingFactorial( -9.0, 3 )\n    -504.0\n    > v = base.risingFactorial( 0.0, 2 )\n    0.0\n    > v = base.risingFactorial( 3.0, -2 )\n    0.5\n\n    See Also\n    --------\n    base.fallingFactorial\n","base.rotl32":"\nbase.rotl32( x, shift )\n    Performs a bitwise rotation to the left.\n\n    If `shift = 0`, the function returns `x`.\n\n    If `shift >= 32`, the function only considers the five least significant\n    bits of `shift` (i.e., `shift % 32`).\n\n    Parameters\n    ----------\n    x: integer\n        Unsigned 32-bit integer.\n\n    shift: integer\n        Number of bits to shift.\n\n    Returns\n    -------\n    out: integer\n        Unsigned 32-bit integer.\n\n    Examples\n    --------\n    > var x = 2147483649;\n    > var bStr = base.toBinaryStringUint32( x )\n    '10000000000000000000000000000001'\n    > var y = base.rotl32( x, 10 )\n    1536\n    > bstr = base.toBinaryStringUint32( y )\n    '00000000000000000000011000000000'\n\n    See Also\n    --------\n    base.rotr32\n","base.rotr32":"\nbase.rotr32( x, shift )\n    Performs a bitwise rotation to the right.\n\n    If `shift = 0`, the function returns `x`.\n\n    If `shift >= 32`, the function only considers the five least significant\n    bits of `shift` (i.e., `shift % 32`).\n\n    Parameters\n    ----------\n    x: integer\n        Unsigned 32-bit integer.\n\n    shift: integer\n        Number of bits to shift.\n\n    Returns\n    -------\n    out: integer\n        Unsigned 32-bit integer.\n\n    Examples\n    --------\n    > var x = 1;\n    > var bStr = base.toBinaryStringUint32( x )\n    '00000000000000000000000000000001'\n    > var y = base.rotr32( x, 10 )\n    4194304\n    > bstr = base.toBinaryStringUint32( y )\n    '00000000010000000000000000000000'\n\n    See Also\n    --------\n    base.rotl32\n","base.round":"\nbase.round( x )\n    Rounds a numeric value to the nearest integer.\n\n    Ties are rounded toward positive infinity.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.round( 3.14 )\n    3.0\n    > y = base.round( -4.2 )\n    -4.0\n    > y = base.round( -4.6 )\n    -5.0\n    > y = base.round( 9.5 )\n    10.0\n    > y = base.round( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceil, base.floor, base.roundn, base.trunc\n","base.round2":"\nbase.round2( x )\n    Rounds a numeric value to the nearest power of two on a linear scale.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.round2( 3.14 )\n    4.0\n    > y = base.round2( -4.2 )\n    -4.0\n    > y = base.round2( -4.6 )\n    -4.0\n    > y = base.round2( 9.5 )\n    8.0\n    > y = base.round2( 13.0 )\n    16.0\n    > y = base.round2( -13.0 )\n    -16.0\n    > y = base.round2( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceil2, base.floor2, base.round, base.round10\n","base.round10":"\nbase.round10( x )\n    Rounds a numeric value to the nearest power of ten on a linear scale.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.round10( 3.14 )\n    1.0\n    > y = base.round10( -4.2 )\n    -1.0\n    > y = base.round10( -4.6 )\n    -1.0\n    > y = base.round10( 9.5 )\n    10.0\n    > y = base.round10( 13.0 )\n    10.0\n    > y = base.round10( -13.0 )\n    -10.0\n    > y = base.round10( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceil10, base.floor10, base.round, base.round2\n","base.roundb":"\nbase.roundb( x, n, b )\n    Rounds a numeric value to the nearest multiple of `b^n` on a linear scale.\n\n    Due to floating-point rounding error, rounding may not be exact.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Integer power.\n\n    b: integer\n        Base.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    // Round to 2 decimal places:\n    > var y = base.roundb( 3.14159, -2, 10 )\n    3.14\n\n    // If `n = 0` or `b = 1`, standard round behavior:\n    > y = base.roundb( 3.14159, 0, 2 )\n    3.0\n\n    // Round to nearest multiple of two:\n    > y = base.roundb( 5.0, 1, 2 )\n    6.0\n\n    See Also\n    --------\n    base.ceilb, base.floorb, base.round, base.roundn\n","base.roundn":"\nbase.roundn( x, n )\n    Rounds a numeric value to the nearest multiple of `10^n`.\n\n    When operating on floating-point numbers in bases other than `2`, rounding\n    to specified digits can be inexact.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Integer power of 10.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    // Round to 2 decimal places:\n    > var y = base.roundn( 3.14159, -2 )\n    3.14\n\n    // If `n = 0`, standard round behavior:\n    > y = base.roundn( 3.14159, 0 )\n    3.0\n\n    // Round to nearest thousand:\n    > y = base.roundn( 12368.0, 3 )\n    12000.0\n\n\n    See Also\n    --------\n    base.ceiln, base.floorn, base.round, base.roundb\n","base.roundsd":"\nbase.roundsd( x, n[, b] )\n    Rounds a numeric value to the nearest number with `n` significant figures.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Number of significant figures. Must be greater than 0.\n\n    b: integer (optional)\n        Base. Must be greater than 0. Default: 10.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.roundsd( 3.14159, 3 )\n    3.14\n    > y = base.roundsd( 3.14159, 1 )\n    3.0\n    > y = base.roundsd( 12368.0, 2 )\n    12000.0\n    > y = base.roundsd( 0.0313, 2, 2 )\n    0.03125\n\n    See Also\n    --------\n    base.ceilsd, base.floorsd, base.round, base.truncsd\n","base.rsqrt":"\nbase.rsqrt( x )\n    Computes the reciprocal square root of a double-precision floating-point\n    number.\n\n    For `x < 0`, the reciprocal square root is not defined.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Reciprocal square root.\n\n    Examples\n    --------\n    > var y = base.rsqrt( 4.0 )\n    0.5\n    > y = base.rsqrt( 100.0 )\n    0.1\n    > y = base.rsqrt( 0.0 )\n    Infinity\n    > y = base.rsqrt( Infinity )\n    0.0\n    > y = base.rsqrt( -4.0 )\n    NaN\n    > y = base.rsqrt( NaN )\n    NaN\n\n    See Also\n    --------\n    base.sqrt\n","base.rsqrtf":"\nbase.rsqrtf( x )\n    Computes the reciprocal square root of a single-precision floating-point\n    number.\n\n    For `x < 0`, the reciprocal square root is not defined.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Reciprocal square root.\n\n    Examples\n    --------\n    > var y = base.rsqrtf( 4.0 )\n    0.5\n    > y = base.rsqrtf( 0.0 )\n    Infinity\n    > y = base.rsqrtf( Infinity )\n    0.0\n    > y = base.rsqrtf( -4.0 )\n    NaN\n    > y = base.rsqrtf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.rsqrt, base.sqrtf\n","base.sargs2multislice":"\nbase.sargs2multislice( str )\n    Creates a MultiSlice object from a comma-separated list of string-serialized\n    MultiSlice constructor arguments.\n\n    The function returns `null` if provided an invalid string.\n\n    Parameters\n    ----------\n    str: string\n        Input string containing constructor arguments.\n\n    Returns\n    -------\n    s: MultiSlice|null\n        MultiSlice instance (or null).\n\n    Examples\n    --------\n    > var s = new base.sargs2multislice( 'null,null,null' );\n    > s.data\n    [ null, null, null ]\n    > s = new base.sargs2multislice( '10,Slice(0,10,1),null' );\n    > s.data\n    [ 10, <Slice>, null ]\n\n    See Also\n    --------\n    base.args2multislice, base.seq2multislice\n","base.scalar2ndarray":"\nbase.scalar2ndarray( value, dtype, order )\n    Returns a zero-dimensional ndarray containing a provided scalar value.\n\n    If `value` is a number and `dtype` is a complex number data type, the\n    function returns a zero-dimensional ndarray containing a complex number\n    whose real component equals the provided scalar value and whose imaginary\n    component is zero.\n\n    Parameters\n    ----------\n    value: any\n        Scalar value.\n\n    dtype: string\n        Data type.\n\n    order: string\n        Memory layout (either 'row-major' or 'column-major').\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var x = base.scalar2ndarray( 1.0, 'float64', 'row-major' )\n    <ndarray>\n    > var sh = x.shape\n    []\n    > var dt = x.dtype\n    'float64'\n    > var v = x.get()\n    1.0\n\n    See Also\n    --------\n    array, base.ndarray, ndarray\n","base.secd":"\nbase.secd( x )\n    Computes the secant of an angle measured in degrees.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in degrees).\n\n    Returns\n    -------\n    y: number\n        Secant.\n\n    Examples\n    --------\n    > var y = base.secd( 1.0 )\n    ~1.0\n    > y = base.secd( PI )\n    ~1.0\n    > y = base.secd( -PI )\n    ~1.0\n    > y = base.secd( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cosd, base.cos\n","base.seq2multislice":"\nbase.seq2multislice( str, shape, strict )\n    Converts a multidimensional subsequence string to a MultiSlice object.\n\n    A multidimensional subsequence string is a comma-separated list of single-\n    dimension indexing expressions (i.e., integers and/or subsequence strings).\n\n    For example, the following\n\n      2\n      :\n      2:\n      :10\n      2:10\n      ::-1\n      10:2:-1\n      :2:\n      2:10:\n      2::2\n      :10:2\n      :, :, :\n      1, 2, 3\n      0:10, 1:20:2, ::-1\n      ...\n      :, ..., 2\n\n    are all valid multidimensional subsequence strings.\n\n    Providing a single nonnegative integer `i` as a single-dimension index\n    indexes the same elements as the subsequence `i:i+1`.\n\n    Providing a single negative integer `i` as a single-dimension index indexes\n    the same elements as the subsequence `n+i:n+i+i`, where `n` is the dimension\n    size.\n\n    While integers index the same elements as equivalent subsequences, providing\n    an integer as a single-dimension index indicates to reduce the number of\n    dimensions by one (e.g., if the provided shape corresponds to an array\n    having rank 2, then rank(A)-1 == rank(A['0,:'])).\n\n    In contrast, providing a subsequence indicates to retain a respective\n    dimension (e.g., if the provided shape corresponds to an array having rank\n    2, then rank(A) == rank(A[':,:'])).\n\n    A multidimensional subsequence string can only contain **one** ellipsis\n    ('...') operator. An ellipsis indicates to apply ':' to each dimension\n    necessary to index all dimensions (e.g., if A has rank 4, A['1:,...,2:5']\n    equals A['1:,:,:,2:5']).\n\n    Except in the case of providing a single ellipsis, the number of single-\n    dimension indexing expressions must equal the number of dimensions in the\n    input shape.\n\n    The function returns an error object if provided an invalid subsequence\n    string.\n\n    In strict mode, the function returns an error object if a single-dimension\n    index expression which exceeds index bounds.\n\n    A returned error object is a plain object having the following properties:\n\n    - code: error code.\n\n    A returned error object may have one of the following error codes:\n\n    - ERR_SLICE_INVALID_SUBSEQUENCE: a subsequence string is invalid.\n    - ERR_SLICE_INVALID_INCREMENT: a subsequence string must have a non-zero\n      increment.\n    - ERR_SLICE_OUT_OF_BOUNDS: a subsequence string resolves to a slice\n      exceeding index bounds.\n    - ERR_SLICE_TOO_MANY_DIMENSIONS: a subsequence string has more dimensions\n      than the provided shape.\n    - ERR_SLICE_INSUFFICIENT_DIMENSIONS: a subsequence string has too few\n      dimensions.\n    - ERR_SLICE_INVALID_ELLIPSIS: a subsequence string must only contain at most\n      one ellipsis.\n\n    Parameters\n    ----------\n    str: string\n        Subsequence string.\n\n    shape: Array<integer>\n        Maximum allowed slice shape.\n\n    strict: boolean\n        Boolean indicating whether to enforce strict bounds checking.\n\n    Returns\n    -------\n    s: MultiSlice|Object\n        MultiSlice instance or an error object.\n\n    Examples\n    --------\n    > var s = new base.seq2multislice( '1:10', [ 10 ], false );\n    > s.data\n    [ <Slice> ]\n    > s = new base.seq2multislice( '4,2:5:2,:', [ 10, 10, 10 ], false );\n    > s.data\n    [ 4, <Slice>, <Slice> ]\n\n    See Also\n    --------\n    base.seq2slice, base.sargs2multislice\n","base.seq2slice":"\nbase.seq2slice( str, len, strict )\n    Converts a subsequence string to a Slice object.\n\n    A subsequence string has the following format:\n\n      <start>:<stop>:<increment>\n\n    If an increment is not specified, the default increment is one. An increment\n    of zero is not allowed.\n\n    The start index is inclusive.\n\n    The stop index is exclusive.\n\n    Both start and stop indices are optional. If not provided, the start and\n    stop indices default to index extremes. Which extremes correspond to which\n    index depends on whether the increment is positive or negative.\n\n    Both start and stop indices can be negative; in which case, the\n    corresponding index is resolved by subtracting the respective value from the\n    provided length.\n\n    Both start and stop indices can use the 'end' keyword (e.g., 'end-2::2',\n    'end-3:', etc), which supports basic subtraction and division.\n\n    The 'end' keyword resolves to the provided length. Thus, ':-1' is equivalent\n    to ':end-1', ':-2' is equivalent to ':end-2', and so on and so forth. The\n    exception is when performing a division operation when the increment is less\n    than zero; in which case, 'end' is equal to 'len-1' in order to preserve\n    user expectations when 'end/d' equals a whole number and slicing from right-\n    to-left. The result from a division operation is rounded down to the nearest\n    integer value.\n\n    In non-strict mode, the resolved slice start is clamped to the slice index\n    bounds [0, len).\n\n    In non-strict mode, Tte resolved slice end is upper bound clamped to the\n    provided length (i.e., one greater than the last possible index).\n\n    When the increment is negative, the resolved slice end value may be `null`,\n    thus indicating that a non-empty slice should include the first index.\n\n    The function ensures that results satisfy the convention that ':n' combined\n    with 'n:' is equivalent to ':' (i.e., selecting all elements).\n\n    When the provided length is zero, the function always returns a slice object\n    equivalent to '0:0:<increment>'.\n\n    The function returns an error object if provided an invalid subsequence\n    string.\n\n    In strict mode, the function returns an error object if provided a\n    subsequence string which exceeds index bounds.\n\n    A returned error object is a plain object having the following properties:\n\n    - code: error code.\n\n    A returned error object may have one of the following error codes:\n\n    - ERR_SLICE_INVALID_SUBSEQUENCE: a subsequence string is invalid.\n    - ERR_SLICE_INVALID_INCREMENT: a subsequence string must have a non-zero\n      increment.\n    - ERR_SLICE_OUT_OF_BOUNDS: a subsequence string resolves to a slice\n      exceeding index bounds.\n\n    Parameters\n    ----------\n    str: string\n        Subsequence string.\n\n    len: integer\n        Maximum number of elements allowed in the slice.\n\n    strict: boolean\n        Boolean indicating whether to enforce strict bounds checking.\n\n    Returns\n    -------\n    s: Slice|Object\n        Slice instance or an error object.\n\n    Examples\n    --------\n    > var s = new base.seq2slice( '1:10', 10, false );\n    > s.start\n    1\n    > s.stop\n    10\n    > s.step\n    1\n    > s = new base.seq2slice( '2:5:2', 10, false );\n    > s.start\n    2\n    > s.stop\n    5\n    > s.step\n    2\n\n    See Also\n    --------\n    base.seq2multislice, base.slice2seq\n","base.setHighWord":"\nbase.setHighWord( x, high )\n    Sets the more significant 32 bits of a double-precision floating-point\n    number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    high: integer\n        Unsigned 32-bit integer to replace the higher order word of `x`.\n\n    Returns\n    -------\n    out: number\n        Double having the same lower order word as `x`.\n\n    Examples\n    --------\n    // Set the higher order bits of `+infinity` to return `1`:\n    > var high = 1072693248 >>> 0;\n    > var y = base.setHighWord( PINF, high )\n    1.0\n\n    See Also\n    --------\n    base.getHighWord, base.setLowWord\n","base.setLowWord":"\nbase.setLowWord( x, low )\n    Sets the less significant 32 bits of a double-precision floating-point\n    number.\n\n    Setting the lower order bits of `NaN` or positive or negative infinity will\n    return `NaN`, as `NaN` is defined as a double whose exponent bit sequence is\n    all ones and whose fraction can be any bit sequence except all zeros.\n    Positive and negative infinity are defined as doubles with an exponent bit\n    sequence equal to all ones and a fraction equal to all zeros. Hence,\n    changing the less significant bits of positive and negative infinity\n    converts each value to `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    low: integer\n        Unsigned 32-bit integer to replace the lower order word of `x`.\n\n    Returns\n    -------\n    out: number\n        Double having the same higher order word as `x`.\n\n    Examples\n    --------\n    > var low = 5 >>> 0;\n    > var x = 3.14e201;\n    > var y = base.setLowWord( x, low )\n    3.139998651394392e+201\n\n    // Special cases:\n    > var low = 12345678;\n    > var y = base.setLowWord( PINF, low )\n    NaN\n    > y = base.setLowWord( NINF, low )\n    NaN\n    > y = base.setLowWord( NaN, low )\n    NaN\n\n    See Also\n    --------\n    base.getLowWord, base.setHighWord\n","base.sici":"\nbase.sici( x )\n    Computes the sine and cosine integrals.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    out: Array<number>\n        Sine and cosine integrals.\n\n    Examples\n    --------\n    > var y = base.sici( 3.0 )\n    [ ~1.849, ~0.12 ]\n    > y = base.sici( 0.0 )\n    [ 0.0, -Infinity ]\n    > y = base.sici( -9.0 )\n    [ ~-1.665, ~0.055 ]\n    > y = base.sici( NaN )\n    [ NaN, NaN ]\n\n\nbase.sici.assign( x, out, stride, offset )\n    Computes the sine and cosine integrals and assigns results to a provided\n    output array.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Sine and cosine integrals.\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var y = base.sici.assign( 3.0, out, 1, 0 )\n    <Float64Array>[ ~1.849, ~0.12 ]\n    > var bool = ( y === out )\n    true\n","base.sici.assign":"\nbase.sici.assign( x, out, stride, offset )\n    Computes the sine and cosine integrals and assigns results to a provided\n    output array.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Sine and cosine integrals.\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var y = base.sici.assign( 3.0, out, 1, 0 )\n    <Float64Array>[ ~1.849, ~0.12 ]\n    > var bool = ( y === out )\n    true","base.signbit":"\nbase.signbit( x )\n    Returns a boolean indicating if the sign bit is on (true) or off (false).\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if sign bit is on or off.\n\n    Examples\n    --------\n    > var bool = base.signbit( 4.0 )\n    false\n    > bool = base.signbit( -9.14e-34 )\n    true\n    > bool = base.signbit( 0.0 )\n    false\n    > bool = base.signbit( -0.0 )\n    true\n\n    See Also\n    --------\n    base.signbitf\n","base.signbitf":"\nbase.signbitf( x )\n    Returns a boolean indicating if the sign bit is on (true) or off (false).\n\n    Parameters\n    ----------\n    x: float\n        Single-precision floating-point number.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if sign bit is on or off.\n\n    Examples\n    --------\n    > var bool = base.signbitf( base.float64ToFloat32( 4.0 ) )\n    false\n    > bool = base.signbitf( base.float64ToFloat32( -9.14e-34 ) )\n    true\n    > bool = base.signbitf( 0.0 )\n    false\n    > bool = base.signbitf( -0.0 )\n    true\n\n    See Also\n    --------\n    base.signbit\n","base.significandf":"\nbase.significandf( x )\n    Returns an integer corresponding to the significand of a single-precision\n    floating-point number.\n\n    Parameters\n    ----------\n    x: float\n        Single-precision floating-point number.\n\n    Returns\n    -------\n    out: integer\n        Significand.\n\n    Examples\n    --------\n    > var s = base.significandf( base.float64ToFloat32( 3.14e34 ) )\n    4293751\n    > s = base.significandf( base.float64ToFloat32( 3.14e-34 ) )\n    5288021\n    > s = base.significandf( base.float64ToFloat32( -3.14 ) )\n    4781507\n    > s = base.significandf( 0.0 )\n    0\n    > s = base.significandf( NaN )\n    4194304\n\n","base.signum":"\nbase.signum( x )\n    Evaluates the signum function for a double-precision floating-point number.\n\n    Value | Sign\n    ----- | -----\n    x > 0 |    +1\n    x < 0 |    -1\n        0 |     0\n       -0 |    -0\n      NaN |   NaN\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    sign: number\n        Function value.\n\n    Examples\n    --------\n    > var sign = base.signum( -5.0 )\n    -1.0\n    > sign = base.signum( 5.0 )\n    1.0\n    > sign = base.signum( -0.0 )\n    -0.0\n    > sign = base.signum( 0.0 )\n    0.0\n    > sign = base.signum( NaN )\n    NaN\n\n","base.signumf":"\nbase.signumf( x )\n    Evaluates the signum function for a single-precision floating-point number.\n\n    Value | Sign\n    ----- | -----\n    x > 0 |    +1\n    x < 0 |    -1\n        0 |     0\n       -0 |    -0\n      NaN |   NaN\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    sign: number\n        Function value.\n\n    Examples\n    --------\n    > var sign = base.signumf( -5.0 )\n    -1.0\n    > sign = base.signumf( 5.0 )\n    1.0\n    > sign = base.signumf( -0.0 )\n    -0.0\n    > sign = base.signumf( 0.0 )\n    0.0\n    > sign = base.signumf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.signum\n","base.sin":"\nbase.sin( x )\n    Computes the sine of a number.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Sine.\n\n    Examples\n    --------\n    > var y = base.sin( 0.0 )\n    ~0.0\n    > y = base.sin( PI/2.0 )\n    ~1.0\n    > y = base.sin( -PI/6.0 )\n    ~-0.5\n    > y = base.sin( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cos, base.sinpi, base.tan\n","base.sinc":"\nbase.sinc( x )\n    Computes the normalized cardinal sine of a number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Cardinal sine.\n\n    Examples\n    --------\n    > var y = base.sinc( 0.5 )\n    ~0.637\n    > y = base.sinc( -1.2 )\n    ~-0.156\n    > y = base.sinc( 0.0 )\n    1.0\n    > y = base.sinc( NaN )\n    NaN\n\n    See Also\n    --------\n    base.sin\n","base.sincos":"\nbase.sincos( x )\n    Simultaneously computes the sine and cosine of a number.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: Array<number>\n        Sine and cosine.\n\n    Examples\n    --------\n    > var y = base.sincos( 0.0 )\n    [ ~0.0, ~1.0 ]\n    > y = base.sincos( PI/2.0 )\n    [ ~1.0, ~0.0 ]\n    > y = base.sincos( -PI/6.0 )\n    [ ~-0.5, ~0.866 ]\n    > y = base.sincos( NaN )\n    [ NaN, NaN ]\n\n\nbase.sincos( x, out, stride, offset )\n    Simultaneously computes the sine and cosine of a number and assigns\n    results to a provided output array.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Sine and cosine.\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var v = base.sincos.assign( 0.0, out, 1, 0 )\n    <Float64Array>[ ~0.0, ~1.0 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.cos, base.sin, base.sincospi","base.sincospi":"\nbase.sincospi( x )\n    Simultaneously computes the sine and cosine of a number times π.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: Array<number>\n        Two-element array containing sin(πx) and cos(πx).\n\n    Examples\n    --------\n    > var y = base.sincospi( 0.0 )\n    [ 0.0, 1.0 ]\n    > y = base.sincospi( 0.5 )\n    [ 1.0, 0.0 ]\n    > y = base.sincospi( 0.1 )\n    [ ~0.309, ~0.951 ]\n    > y = base.sincospi( NaN )\n    [ NaN, NaN ]\n\n\nbase.sincospi.assign( x, out, stride, offset )\n    Simultaneously computes the sine and cosine of a number times π and\n    assigns results to a provided output array.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Two-element array containing sin(πx) and cos(πx).\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var v = base.sincospi.assign( 0.0, out, 1, 0 )\n    <Float64Array>[ 0.0, 1.0 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.cospi, base.sincos, base.sinpi","base.sincospi.assign":"\nbase.sincospi.assign( x, out, stride, offset )\n    Simultaneously computes the sine and cosine of a number times π and\n    assigns results to a provided output array.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Two-element array containing sin(πx) and cos(πx).\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var v = base.sincospi.assign( 0.0, out, 1, 0 )\n    <Float64Array>[ 0.0, 1.0 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.cospi, base.sincos, base.sinpi","base.sinh":"\nbase.sinh( x )\n    Computes the hyperbolic sine of a double-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Hyperbolic sine.\n\n    Examples\n    --------\n    > var y = base.sinh( 0.0 )\n    0.0\n    > y = base.sinh( 2.0 )\n    ~3.627\n    > y = base.sinh( -2.0 )\n    ~-3.627\n    > y = base.sinh( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cosh, base.sin, base.tanh\n","base.sinpi":"\nbase.sinpi( x )\n    Computes the value of `sin(πx)`.\n\n    The function computes `sin(πx)` more accurately than the obvious approach,\n    especially for large `x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.sinpi( 0.0 )\n    0.0\n    > y = base.sinpi( 0.5 )\n    1.0\n    > y = base.sinpi( 0.9 )\n    ~0.309\n    > y = base.sinpi( NaN )\n    NaN\n\n    See Also\n    --------\n    base.sin\n","base.slice2seq":"\nbase.slice2seq( slice )\n    Converts a Slice object to a subsequence string.\n\n    Parameters\n    ----------\n    slice: Slice\n        Input slice.\n\n    Returns\n    -------\n    out: string\n        Subsequence string.\n\n    Examples\n    --------\n    > var out = base.slice2seq( new Slice( 1, 10, 1 ) )\n    '1:10:1'\n    > out = base.slice2seq( new Slice( null, 10 ) )\n    ':10'\n\n    See Also\n    --------\n    base.seq2slice\n","base.sliceLength":"\nbase.sliceLength( slice )\n    Returns the number of elements in a normalized slice.\n\n    Parameters\n    ----------\n    slice: Slice\n        Input normalized slice object.\n\n    Returns\n    -------\n    len: integer\n        Number of elements.\n\n    Examples\n    --------\n    > var s = new Slice( 1, 10, 1 );\n    > base.sliceLength( s )\n    9\n\n    See Also\n    --------\n    base.sliceNonReducedDimensions, base.sliceReducedDimensions, base.sliceShape\n","base.sliceNonReducedDimensions":"\nbase.sliceNonReducedDimensions( slice )\n    Returns a list of non-reduced dimensions in an un-normalized multi-slice.\n\n    Parameters\n    ----------\n    slice: MultiSlice\n        Input slice object.\n\n    Returns\n    -------\n    out: Array<integer>\n        Dimension indices.\n\n    Examples\n    --------\n    > var s = new MultiSlice( 1, 3, null );\n    > var out = base.sliceNonReducedDimensions( s )\n    [ 2 ]\n\n    See Also\n    --------\n    base.sliceLength, base.sliceReducedDimensions, base.sliceShape\n","base.sliceReducedDimensions":"\nbase.sliceReducedDimensions( slice )\n    Returns a list of reduced dimensions in an un-normalized multi-slice.\n\n    Parameters\n    ----------\n    slice: MultiSlice\n        Input slice object.\n\n    Returns\n    -------\n    out: Array<integer>\n        Dimension indices.\n\n    Examples\n    --------\n    > var s = new MultiSlice( 1, 3, null );\n    > var out = base.sliceReducedDimensions( s )\n    [ 0, 1 ]\n\n    See Also\n    --------\n    base.sliceLength, base.sliceNonReducedDimensions, base.sliceShape\n","base.sliceShape":"\nbase.sliceShape( slice )\n    Returns the shape of a normalized multi-slice.\n\n    Parameters\n    ----------\n    slice: MultiSlice\n        Input normalized multi-slice object.\n\n    Returns\n    -------\n    sh: Array<integer>\n        Slice shape.\n\n    Examples\n    --------\n    > var s = new Slice( 1, 10, 1 );\n    > var ms = new MultiSlice( s, s );\n    > base.sliceShape( ms )\n    [ 9, 9 ]\n\n    See Also\n    --------\n    base.sliceLength, base.sliceNonReducedDimensions, base.sliceReducedDimensions\n","base.snakecase":"\nbase.snakecase( str )\n    Converts a string to snake case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Snake-cased string.\n\n    Examples\n    --------\n    > var out = base.snakecase( 'Hello World!' )\n    'hello_world'\n    > out = base.snakecase( 'I am a tiny little teapot' )\n    'i_am_a_tiny_little_teapot'\n\n    See Also\n    --------\n    base.camelcase, base.lowercase, base.stickycase, base.uppercase","base.spence":"\nbase.spence( x )\n    Evaluates Spence's function, which is also known as the dilogarithm.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.spence( 3.0 )\n    ~-1.437\n    > y = base.spence( 0.0 )\n    ~1.645\n    > y = base.spence( -9.0 )\n    NaN\n    > y = base.spence( NaN )\n    NaN\n\n","base.sqrt":"\nbase.sqrt( x )\n    Computes the principal square root of a double-precision floating-point\n    number.\n\n    For `x < 0`, the principal square root is not defined.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Principal square root.\n\n    Examples\n    --------\n    > var y = base.sqrt( 4.0 )\n    2.0\n    > y = base.sqrt( 9.0 )\n    3.0\n    > y = base.sqrt( 0.0 )\n    0.0\n    > y = base.sqrt( -4.0 )\n    NaN\n    > y = base.sqrt( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cbrt, base.rsqrt\n","base.sqrt1pm1":"\nbase.sqrt1pm1( x )\n    Computes the principal square root of `1+x` minus one.\n\n    This function is more accurate than the obvious approach for small `x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Square root of `1+x` minus one.\n\n    Examples\n    --------\n    > var y = base.sqrt1pm1( 3.0 )\n    1.0\n    > y = base.sqrt1pm1( 0.5 )\n    ~0.225\n    > y = base.sqrt1pm1( 0.02 )\n    ~0.01\n    > y = base.sqrt1pm1( -0.5 )\n    ~-0.293\n    > y = base.sqrt1pm1( -1.1 )\n    NaN\n    > y = base.sqrt1pm1( NaN )\n    NaN\n\n    See Also\n    --------\n    base.sqrt\n","base.sqrtf":"\nbase.sqrtf( x )\n    Computes the principal square root of a single-precision floating-point\n    number.\n\n    For `x < 0`, the principal square root is not defined.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Principal square root.\n\n    Examples\n    --------\n    > var y = base.sqrtf( 4.0 )\n    2.0\n    > y = base.sqrtf( 9.0 )\n    3.0\n    > y = base.sqrtf( 0.0 )\n    0.0\n    > y = base.sqrtf( -4.0 )\n    NaN\n    > y = base.sqrtf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cbrtf, base.rsqrtf, base.sqrt\n","base.sqrtpi":"\nbase.sqrtpi( x )\n    Computes the principal square root of the product of π and a positive\n    double-precision floating-point number.\n\n    For `x < 0`, the square root is not defined.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Principal square root of the product of π and the input value.\n\n    Examples\n    --------\n    > var y = base.sqrtpi( 4.0 )\n    ~3.5449\n    > y = base.sqrtpi( 10.0 )\n    ~5.60499\n    > y = base.sqrtpi( 0.0 )\n    0.0\n    > y = base.sqrtpi( -4.0 )\n    NaN\n    > y = base.sqrtpi( NaN )\n    NaN\n\n    See Also\n    --------\n    base.sqrt","base.startcase":"\nbase.startcase( str )\n    Capitalizes the first letter of each word in an input string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        String containing words where each first letter is capitalized.\n\n    Examples\n    --------\n    > var out = base.startcase( 'beep boop' )\n    'Beep Boop'\n\n    See Also\n    --------\n    base.capitalize, base.lowercase, base.uppercase\n","base.startsWith":"\nbase.startsWith( str, search, position )\n    Tests if a string starts with the characters of another string.\n\n    If provided an empty search string, the function always returns `true`.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search string.\n\n    position: integer\n        Position at which to start searching for `search`. If less than `0`, the\n        start position is determined relative to the end of the input string.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a string starts with the characters of\n        another string.\n\n    Examples\n    --------\n    > var bool = base.startsWith( 'Beep', 'Be', 0 )\n    true\n    > bool = base.startsWith( 'Beep', 'ep', 0 )\n    false\n    > bool = base.startsWith( 'Beep', 'ee', 1 )\n    true\n    > bool = base.startsWith( 'Beep', 'ee', -3 )\n    true\n    > bool = base.startsWith( 'Beep', '', 0 )\n    true\n\n    See Also\n    --------\n    base.endsWith\n","base.stickycase":"\nbase.stickycase( str[, p] )\n    Converts a string to sticky case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n \n    p: number\n        Probability of capitalization.\n\n    Returns\n    -------\n    out: string\n        Sticky-cased string.\n\n    Examples\n    --------\n    > var out = base.stickycase( 'Hello World!' )\n    <string>\n\n    > out = base.stickycase( 'I am a tiny little teapot' )\n    <string>\n    See Also\n    --------\n    base.camelcase, base.lowercase, base.snakecase, base.uppercase\n","base.strided.binary":"\nbase.strided.binary( arrays, shape, strides, fcn )\n    Applies a binary callback to strided input array elements and assigns\n    results to elements in a strided output array.\n\n    The `shape` and `strides` parameters determine which elements in the strided\n    input and output arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing two strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    fcn: Function\n        Binary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1 ];\n    > function f( x, y ) { return x + y; };\n    > base.strided.binary( [ x, y, z ], shape, strides, f );\n    > z\n    <Float64Array>[ 2.0, 4.0, 6.0, 8.0 ]\n\n\nbase.strided.binary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a binary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing two strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Binary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1 ];\n    > var offsets = [ 0, 0, 0 ];\n    > function f( x, y ) { return x + y; };\n    > base.strided.binary.ndarray( [ x, y, z ], shape, strides, offsets, f );\n    > z\n    <Float64Array>[ 2.0, 4.0, 6.0, 8.0 ]\n\n    See Also\n    --------\n    base.strided.dmap2, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap2, base.strided.ternary, base.strided.unary\n","base.strided.binary.ndarray":"\nbase.strided.binary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a binary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing two strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Binary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1 ];\n    > var offsets = [ 0, 0, 0 ];\n    > function f( x, y ) { return x + y; };\n    > base.strided.binary.ndarray( [ x, y, z ], shape, strides, offsets, f );\n    > z\n    <Float64Array>[ 2.0, 4.0, 6.0, 8.0 ]\n\n    See Also\n    --------\n    base.strided.dmap2, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap2, base.strided.ternary, base.strided.unary","base.strided.binaryDtypeSignatures":"\nbase.strided.binaryDtypeSignatures( dtypes1, dtypes2, dtypes3[, options] )\n    Generates a list of binary interface signatures from strided array data\n    types.\n\n    The function returns a strided array having a stride length of `3` (i.e.,\n    every `3` elements define a binary interface signature).\n\n    For each signature (i.e., set of three consecutive non-overlapping strided\n    array elements), the first two elements are the input data types and the\n    third element is the return data type.\n\n    All signatures follow type promotion rules.\n\n    Parameters\n    ----------\n    dtypes1: ArrayLike<any>\n        List of supported data types for the first input argument.\n\n    dtypes2: ArrayLike<any>\n        List of supported data types for the second input argument.\n\n    dtypes3: ArrayLike<any>\n        List of supported data types for the output value.\n\n    options: Object (optional)\n        Options.\n\n    options.enums: boolean (optional)\n        Boolean flag indicating whether to return signatures as a list of data\n        type enumeration constants. Default: false.\n\n    Returns\n    -------\n    out: Array\n        Strided array containing binary interface signatures.\n\n    Examples\n    --------\n    > var dt = strided.dataTypes();\n    > var out = base.strided.binaryDtypeSignatures( dt, dt, dt )\n    [...]\n\n    See Also\n    --------\n    base.strided.binarySignatureCallbacks\n","base.strided.binarySignatureCallbacks":"\nbase.strided.binarySignatureCallbacks( table, signatures )\n    Assigns callbacks to binary interfaces according to type promotion rules.\n\n    Parameters\n    ----------\n    table: Object\n        Object mapping callbacks to data types.\n\n    table.default: Function\n        Default callback.\n\n    table.complex64: Function\n        Callback to be invoked when input arrays promote to single-precision\n        complex floating-point numbers.\n\n    table.complex128: Function\n        Callback to be invoked when input arrays promote to double precision\n        complex floating-point numbers.\n\n    signatures: ArrayLike<any>\n        Strided array containing binary interface signatures.\n\n    Returns\n    -------\n    out: Array<Function>\n        List of callbacks, one per signature.\n\n    Examples\n    --------\n    > var dt = strided.dataTypes();\n    > var sigs = base.strided.binaryDtypeSignatures( dt, dt, dt );\n    > var t = {\n    ...     'default': base.add,\n    ...     'complex64': base.caddf,\n    ...     'complex128': base.cadd\n    ... };\n    > var out = base.strided.binarySignatureCallbacks( t, sigs )\n    [...]\n\n    See Also\n    --------\n    base.strided.binaryDtypeSignatures\n","base.strided.ccopy":"\nbase.strided.ccopy( N, x, strideX, y, strideY )\n    Copies values from one complex single-precision floating-point vector to\n    another complex single-precision floating-point vector.\n\n    The `N` and stride parameters determine how values from `x` are copied into\n    `y`.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Complex64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Complex64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n    > base.strided.ccopy( x.length, x, 1, y, 1 );\n    > var z = y.get( 0 );\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    2.0\n\n    // Advanced indexing:\n    > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n    > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.ccopy( 2, x, -2, y, 1 );\n    > z = y.get( 0 );\n    > re = realf( z )\n    5.0\n    > im = imagf( z )\n    6.0\n\n    // Using typed array views:\n    > var x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n    > var y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.ccopy( 2, x1, -2, y1, 1 );\n    > z = y0.get( 2 );\n    > re = realf( z )\n    7.0\n    > im = imagf( z )\n    8.0\n\n\nbase.strided.ccopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Copies values from one complex single-precision floating-point vector to\n    another complex single-precision floating-point vector using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Complex64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Complex64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n    > base.strided.ccopy.ndarray( x.length, x, 1, 0, y, 1, 0 );\n    > var z = y.get( 0 );\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    2.0\n\n    // Advanced indexing:\n    > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n    > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.ccopy.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\n    > z = y.get( y.length-1 );\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    4.0\n\n    See Also\n    --------\n    base.strided.cswap\n","base.strided.ccopy.ndarray":"\nbase.strided.ccopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Copies values from one complex single-precision floating-point vector to\n    another complex single-precision floating-point vector using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Complex64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Complex64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n    > base.strided.ccopy.ndarray( x.length, x, 1, 0, y, 1, 0 );\n    > var z = y.get( 0 );\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    2.0\n\n    // Advanced indexing:\n    > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n    > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.ccopy.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\n    > z = y.get( y.length-1 );\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    4.0\n\n    See Also\n    --------\n    base.strided.cswap","base.strided.cmap":"\nbase.strided.cmap( N, x, strideX, y, strideY, fcn )\n    Applies a unary function to a single-precision complex floating-point\n    strided input array and assigns results to a single-precision complex\n    floating-point strided output array.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Complex64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Complex64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n    > var x = new Complex64Array( xbuf );\n    > var y = new Complex64Array( x.length );\n    > base.strided.cmap( x.length, x, 1, y, 1, base.cidentityf );\n    > var v = y.get( 0 )\n    <Complex64>\n    > var re = real( v )\n    1.0\n    > var im = imag( v )\n    2.0\n\n    // Using `N` and stride parameters:\n    > y = new Complex64Array( x.length );\n    > base.strided.cmap( 2, x, 2, y, -1, base.cidentityf );\n    > v = y.get( 0 )\n    <Complex64>\n    > re = real( v )\n    5.0\n    > im = imag( v )\n    6.0\n\n    // Using view offsets:\n    > var x0 = new Complex64Array( xbuf );\n    > var y0 = new Complex64Array( x0.length );\n    > var x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.cmap( 2, x1, -2, y1, 1, base.cidentityf );\n    > v = y1.get( 0 )\n    <Complex64>\n    > re = real( v )\n    7.0\n    > im = imag( v )\n    8.0\n\n\nbase.strided.cmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n    Applies a unary function to a single-precision complex floating-point\n    strided input array and assigns results to a single-precision complex\n    floating-point strided output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Complex64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Complex64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n    > var x = new Complex64Array( xbuf );\n    > var y = new Complex64Array( x.length );\n    > base.strided.cmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentityf );\n    > var v = y.get( 0 )\n    <Complex64>\n    > var re = real( v )\n    1.0\n    > var im = imag( v )\n    2.0\n\n    // Advanced indexing:\n    > x = new Complex64Array( xbuf );\n    > y = new Complex64Array( x.length );\n    > base.strided.cmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentityf );\n    > v = y.get( y.length-1 )\n    <Complex64>\n    > re = real( v )\n    3.0\n    > im = imag( v )\n    4.0\n\n    See Also\n    --------\n    base.strided.zmap, base.strided.unary\n","base.strided.cmap.ndarray":"\nbase.strided.cmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n    Applies a unary function to a single-precision complex floating-point\n    strided input array and assigns results to a single-precision complex\n    floating-point strided output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Complex64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Complex64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n    > var x = new Complex64Array( xbuf );\n    > var y = new Complex64Array( x.length );\n    > base.strided.cmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentityf );\n    > var v = y.get( 0 )\n    <Complex64>\n    > var re = real( v )\n    1.0\n    > var im = imag( v )\n    2.0\n\n    // Advanced indexing:\n    > x = new Complex64Array( xbuf );\n    > y = new Complex64Array( x.length );\n    > base.strided.cmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentityf );\n    > v = y.get( y.length-1 )\n    <Complex64>\n    > re = real( v )\n    3.0\n    > im = imag( v )\n    4.0\n\n    See Also\n    --------\n    base.strided.zmap, base.strided.unary","base.strided.cswap":"\nbase.strided.cswap( N, x, strideX, y, strideY )\n    Interchanges two complex single-precision floating-point vectors.\n\n    The `N` and stride parameters determine how values from `x` are swapped with\n    values from `y`.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the vectors are unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Complex64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Complex64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n    > base.strided.cswap( x.length, x, 1, y, 1 );\n    > var z = y.get( 0 );\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    2.0\n    > z = x.get( 0 );\n    > re = realf( z )\n    6.0\n    > im = imagf( z )\n    7.0\n\n    // Advanced indexing:\n    > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n    > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.cswap( 2, x, -2, y, 1 );\n    > z = y.get( 0 );\n    > re = realf( z )\n    5.0\n    > im = imagf( z )\n    6.0\n    > z = x.get( 0 );\n    > re = realf( z )\n    0.0\n    > im = imagf( z )\n    0.0\n\n    // Using typed array views:\n    > var x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n    > var y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.cswap( 2, x1, -2, y1, 1 );\n    > z = y0.get( 2 );\n    > re = realf( z )\n    7.0\n    > im = imagf( z )\n    8.0\n    > z = x0.get( 1 );\n    > re = realf( z )\n    0.0\n    > im = imagf( z )\n    0.0\n\n\nbase.strided.cswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Interchanges two complex single-precision floating-point vectors using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Complex64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Complex64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n    > base.strided.cswap.ndarray( x.length, x, 1, 0, y, 1, 0 );\n    > var z = y.get( 0 );\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    2.0\n    > z = x.get( 0 );\n    > re = realf( z )\n    6.0\n    > im = imagf( z )\n    7.0\n\n    // Advanced indexing:\n    > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n    > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.cswap.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\n    > z = y.get( y.length-1 );\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    4.0\n    > z = x.get( 1 );\n    > re = realf( z )\n    0.0\n    > im = imagf( z )\n    0.0\n\n    See Also\n    --------\n    base.strided.ccopy\n","base.strided.cswap.ndarray":"\nbase.strided.cswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Interchanges two complex single-precision floating-point vectors using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Complex64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Complex64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n    > base.strided.cswap.ndarray( x.length, x, 1, 0, y, 1, 0 );\n    > var z = y.get( 0 );\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    2.0\n    > z = x.get( 0 );\n    > re = realf( z )\n    6.0\n    > im = imagf( z )\n    7.0\n\n    // Advanced indexing:\n    > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n    > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.cswap.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\n    > z = y.get( y.length-1 );\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    4.0\n    > z = x.get( 1 );\n    > re = realf( z )\n    0.0\n    > im = imagf( z )\n    0.0\n\n    See Also\n    --------\n    base.strided.ccopy","base.strided.cumax":"\nbase.strided.cumax( N, x, strideX, y, strideY )\n    Computes the cumulative maximum of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cumax( x.length, x, 1, y, 1 )\n    [ 1.0, 1.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cumax( N, x, 2, y, 2 )\n    [ -2.0, 0.0, 1.0, 0.0, 2.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.cumax( N, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 2.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 2.0, 2.0 ]\n\nbase.strided.cumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum of a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, 1.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cumax.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumin, base.strided.dcumax, base.strided.scumax\n","base.strided.cumax.ndarray":"\nbase.strided.cumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum of a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, 1.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cumax.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumin, base.strided.dcumax, base.strided.scumax","base.strided.cumaxabs":"\nbase.strided.cumaxabs( N, x, strideX, y, strideY )\n    Computes the cumulative maximum absolute value of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cumaxabs( x.length, x, 1, y, 1 )\n    [ 1.0, 2.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cumaxabs( N, x, 2, y, 2 )\n    [ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.cumaxabs( N, x1, 2, y1, 1 )\n    <Float64Array>[ 2.0, 2.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\nbase.strided.cumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum absolute value of a strided array using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, 2.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cumax, base.strided.cuminabs, base.strided.dcumaxabs, base.strided.scumaxabs\n","base.strided.cumaxabs.ndarray":"\nbase.strided.cumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum absolute value of a strided array using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, 2.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cumax, base.strided.cuminabs, base.strided.dcumaxabs, base.strided.scumaxabs","base.strided.cumin":"\nbase.strided.cumin( N, x, strideX, y, strideY )\n    Computes the cumulative minimum of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cumin( x.length, x, 1, y, 1 )\n    [ 1.0, -2.0, -2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cumin( N, x, 2, y, 2 )\n    [ -2.0, 0.0, -2.0, 0.0, -2.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.cumin( N, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, -2.0, -2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\nbase.strided.cumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum of a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, -2.0, -2.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumax, base.strided.dcumin, base.strided.scumin\n","base.strided.cumin.ndarray":"\nbase.strided.cumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum of a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, -2.0, -2.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumax, base.strided.dcumin, base.strided.scumin","base.strided.cuminabs":"\nbase.strided.cuminabs( N, x, strideX, y, strideY )\n    Computes the cumulative minimum absolute value of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cuminabs( x.length, x, 1, y, 1 )\n    [ 1.0, 1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cuminabs( N, x, 2, y, 2 )\n    [ 2.0, 0.0, 1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.cuminabs( N, x1, 2, y1, 1 )\n    <Float64Array>[ 2.0, 2.0, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 1.0 ]\n\nbase.strided.cuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum absolute value of a strided array using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, 1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cumaxabs, base.strided.cumin, base.strided.dcuminabs, base.strided.scuminabs\n","base.strided.cuminabs.ndarray":"\nbase.strided.cuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum absolute value of a strided array using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, 1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cumaxabs, base.strided.cumin, base.strided.dcuminabs, base.strided.scuminabs","base.strided.dabs":"\nbase.strided.dabs( N, x, strideX, y, strideY )\n    Computes the absolute value for each element in a double-precision floating-\n    point strided array `x` and assigns the results to elements in a double-\n    precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dabs( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dabs( N, x, 2, y, -1 )\n    <Float64Array>[ 3.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dabs( N, x1, -2, y1, 1 )\n    <Float64Array>[ 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the absolute value for each element in a double-precision floating-\n    point strided array `x` and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    strided.abs, base.strided.dabs2, base.strided.sabs\n","base.strided.dabs.ndarray":"\nbase.strided.dabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the absolute value for each element in a double-precision floating-\n    point strided array `x` and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    strided.abs, base.strided.dabs2, base.strided.sabs","base.strided.dabs2":"\nbase.strided.dabs2( N, x, strideX, y, strideY )\n    Computes the squared absolute value for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dabs2( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.0, 4.0, 9.0, 16.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dabs2( N, x, 2, y, -1 )\n    <Float64Array>[ 9.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dabs2( N, x1, -2, y1, 1 )\n    <Float64Array>[ 16.0, 4.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 16.0, 4.0 ]\n\n\nbase.strided.dabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the squared absolute value for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 4.0, 9.0, 16.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 16.0, 4.0 ]\n\n    See Also\n    --------\n    strided.abs2, base.strided.dabs, base.strided.sabs2\n","base.strided.dabs2.ndarray":"\nbase.strided.dabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the squared absolute value for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 4.0, 9.0, 16.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 16.0, 4.0 ]\n\n    See Also\n    --------\n    strided.abs2, base.strided.dabs, base.strided.sabs2","base.strided.dapx":"\nbase.strided.dapx( N, alpha, x, strideX )\n    Adds a scalar constant to each element in a double-precision floating-point\n    strided array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns the strided array unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dapx( x.length, 5.0, x, 1 )\n    <Float64Array>[ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dapx( 3, 5.0, x, 2 )\n    <Float64Array>[ 3.0, 1.0, 8.0, -5.0, 9.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dapx( 3, 5.0, x1, 2 )\n    <Float64Array>[ 3.0, 3.0, 1.0, 5.0, -1.0 ]\n    > x0\n    <Float64Array>[ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n\nbase.strided.dapx.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each element in a double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dapx.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float64Array>[ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.dapx.ndarray( 3, 5.0, x, 2, 1 )\n    <Float64Array>[ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n    See Also\n    --------\n    base.strided.gapx, base.strided.sapx\n","base.strided.dapx.ndarray":"\nbase.strided.dapx.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each element in a double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dapx.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float64Array>[ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.dapx.ndarray( 3, 5.0, x, 2, 1 )\n    <Float64Array>[ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n    See Also\n    --------\n    base.strided.gapx, base.strided.sapx","base.strided.dapxsum":"\nbase.strided.dapxsum( N, alpha, x, strideX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsum( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dapxsum( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dapxsum( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.dapxsum.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dapxsum.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumpw, base.strided.dsum, base.strided.gapxsum, base.strided.sapxsum\n","base.strided.dapxsum.ndarray":"\nbase.strided.dapxsum.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dapxsum.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumpw, base.strided.dsum, base.strided.gapxsum, base.strided.sapxsum","base.strided.dapxsumkbn":"\nbase.strided.dapxsumkbn( N, alpha, x, strideX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using an improved Kahan–Babuška\n    algorithm.\n\n    The `N` and stride parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumkbn( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dapxsumkbn( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dapxsumkbn( 3, 5.0, x1, 2)\n    14.0\n\n\nbase.strided.dapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using an improved Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.dsumkbn, base.strided.gapxsumkbn, base.strided.sapxsumkbn\n","base.strided.dapxsumkbn.ndarray":"\nbase.strided.dapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using an improved Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.dsumkbn, base.strided.gapxsumkbn, base.strided.sapxsumkbn","base.strided.dapxsumkbn2":"\nbase.strided.dapxsumkbn2( N, alpha, x, strideX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using a second-order iterative\n    Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumkbn2( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dapxsumkbn2( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dapxsumkbn2( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.dapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using a second-order iterative\n    Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.dsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsumkbn2\n","base.strided.dapxsumkbn2.ndarray":"\nbase.strided.dapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using a second-order iterative\n    Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.dsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsumkbn2","base.strided.dapxsumors":"\nbase.strided.dapxsumors( N, alpha, x, strideX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using ordinary recursive summation.\n\n    The `N` and stride parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumors( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dapxsumors( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dapxsumors( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.dapxsumors.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using ordinary recursive summation\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.dsumors, base.strided.gapxsumors, base.strided.sapxsumors\n","base.strided.dapxsumors.ndarray":"\nbase.strided.dapxsumors.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using ordinary recursive summation\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.dsumors, base.strided.gapxsumors, base.strided.sapxsumors","base.strided.dapxsumpw":"\nbase.strided.dapxsumpw( N, alpha, x, strideX )\n    Adds a scalar constant to each double-precision floating-point strided array\n    element and computes the sum using pairwise summation.\n\n    The `N` and stride parameters determine which elements in\n    the strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumpw( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dapxsumpw( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dapxsumpw( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.dapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a constant to each double-precision floating-point strided array\n    element and computes the sum using pairwise summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.dsumpw, base.strided.gapxsumpw, base.strided.sapxsumpw\n","base.strided.dapxsumpw.ndarray":"\nbase.strided.dapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a constant to each double-precision floating-point strided array\n    element and computes the sum using pairwise summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.dsumpw, base.strided.gapxsumpw, base.strided.sapxsumpw","base.strided.dasum":"\nbase.strided.dasum( N, x, stride )\n    Computes the sum of the absolute values.\n\n    The sum of absolute values corresponds to the *L1* norm.\n\n    The `N` and `stride` parameters determine which elements in `x` are used to\n    compute the sum.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the function returns `0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    sum: number\n        Sum of absolute values.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n    > var s = base.strided.dasum( x.length, x, 1 )\n    15.0\n\n    // Sum every other value:\n    > s = base.strided.dasum( 3, x, 2 )\n    9.0\n\n    // Use view offset; e.g., starting at 2nd element:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > s = base.strided.dasum( 3, x1, 2 )\n    12.0\n\n\nbase.strided.dasum.ndarray( N, x, stride, offset )\n    Computes the sum of absolute values using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    sum: number\n        Sum of absolute values.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n    > var s = base.strided.dasum.ndarray( x.length, x, 1, 0 )\n    15.0\n\n    // Sum the last three elements:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > s = base.strided.dasum.ndarray( 3, x, -1, x.length-1 )\n    15.0\n\n    See Also\n    --------\n    base.strided.daxpy, base.strided.gasum, base.strided.sasum, base.strided.dsum\n","base.strided.dasum.ndarray":"\nbase.strided.dasum.ndarray( N, x, stride, offset )\n    Computes the sum of absolute values using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    sum: number\n        Sum of absolute values.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n    > var s = base.strided.dasum.ndarray( x.length, x, 1, 0 )\n    15.0\n\n    // Sum the last three elements:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > s = base.strided.dasum.ndarray( 3, x, -1, x.length-1 )\n    15.0\n\n    See Also\n    --------\n    base.strided.daxpy, base.strided.gasum, base.strided.sasum, base.strided.dsum","base.strided.dasumpw":"\nbase.strided.dasumpw( N, x, strideX )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements using pairwise summation.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dasumpw( x.length, x, 1 )\n    5.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var stride = 2;\n    > base.strided.dasumpw( 3, x, stride )\n    5.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > stride = 2;\n    > base.strided.dasumpw( 3, x1, stride )\n    5.0\n\n\nbase.strided.dasumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements using pairwise summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dasumpw.ndarray( x.length, x, 1, 0 )\n    5.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dasumpw.ndarray( 3, x, 2, 1 )\n    5.0\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.dsumpw, base.strided.gasumpw, base.strided.sasumpw\n","base.strided.dasumpw.ndarray":"\nbase.strided.dasumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements using pairwise summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dasumpw.ndarray( x.length, x, 1, 0 )\n    5.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dasumpw.ndarray( 3, x, 2, 1 )\n    5.0\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.dsumpw, base.strided.gasumpw, base.strided.sasumpw","base.strided.daxpy":"\nbase.strided.daxpy( N, alpha, x, strideX, y, strideY )\n    Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > var alpha = 5.0;\n    > base.strided.daxpy( x.length, alpha, x, 1, y, 1 )\n    <Float64Array>[ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > base.strided.daxpy( 3, alpha, x, 2, y, -1 )\n    <Float64Array>[ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.daxpy( 3, 5.0, x1, -2, y1, 1 )\n    <Float64Array>[ 40.0, 31.0, 22.0 ]\n    > y0\n    <Float64Array>[ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.strided.daxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n    Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > var alpha = 5.0;\n    > base.strided.daxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.daxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.gaxpy, base.strided.saxpy\n","base.strided.daxpy.ndarray":"\nbase.strided.daxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n    Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > var alpha = 5.0;\n    > base.strided.daxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.daxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.gaxpy, base.strided.saxpy","base.strided.dcbrt":"\nbase.strided.dcbrt( N, x, strideX, y, strideY )\n    Computes the cube root of each element in a double-precision floating-point\n    strided array `x` and assigns the results to elements in a double-precision\n    floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dcbrt( x.length, x, 1, y, 1 )\n    <Float64Array>[ 0.0, 1.0, 2.0, 3.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dcbrt( N, x, 2, y, -1 )\n    <Float64Array>[ 2.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dcbrt( N, x1, -2, y1, 1 )\n    <Float64Array>[ 3.0, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.dcbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cube root of each element in a double-precision floating-point\n    strided array `x` and assigns the results to elements in a double-precision\n    floating-point strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dcbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, 1.0, 2.0, 3.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dcbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n    See Also\n    --------\n    strided.cbrt, base.strided.dsqrt, base.strided.scbrt\n","base.strided.dcbrt.ndarray":"\nbase.strided.dcbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cube root of each element in a double-precision floating-point\n    strided array `x` and assigns the results to elements in a double-precision\n    floating-point strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dcbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, 1.0, 2.0, 3.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dcbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n    See Also\n    --------\n    strided.cbrt, base.strided.dsqrt, base.strided.scbrt","base.strided.dceil":"\nbase.strided.dceil( N, x, strideX, y, strideY )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward positive infinity and assigns the results to elements in a double-\n    precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dceil( x.length, x, 1, y, 1 )\n    <Float64Array>[ 2.0, 3.0, -3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dceil( N, x, 2, y, -1 )\n    <Float64Array>[ -3.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dceil( N, x1, -2, y1, 1 )\n    <Float64Array>[ 4.0, 3.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.dceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward positive infinity and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 2.0, 3.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n    See Also\n    --------\n    strided.ceil, base.strided.dfloor, base.strided.dtrunc, base.strided.sceil\n","base.strided.dceil.ndarray":"\nbase.strided.dceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward positive infinity and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 2.0, 3.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n    See Also\n    --------\n    strided.ceil, base.strided.dfloor, base.strided.dtrunc, base.strided.sceil","base.strided.dcopy":"\nbase.strided.dcopy( N, x, strideX, y, strideY )\n    Copies values from `x` into `y`.\n\n    The `N` and stride parameters determine how values from `x` are copied into\n    `y`.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.dcopy( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.dcopy( 3, x, -2, y, 1 )\n    <Float64Array>[ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n    // Using typed array views:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dcopy( 3, x1, -2, y1, 1 )\n    <Float64Array>[ 6.0, 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.dcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Copies values from `x` into `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.dcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dswap, base.strided.gcopy, base.strided.scopy\n","base.strided.dcopy.ndarray":"\nbase.strided.dcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Copies values from `x` into `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.dcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dswap, base.strided.gcopy, base.strided.scopy","base.strided.dcumax":"\nbase.strided.dcumax( N, x, strideX, y, strideY )\n    Computes the cumulative maximum of double-precision floating-point strided\n    array elements.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumax( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.0, 1.0, 2.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcumax( 3, x, 2, y, 2 )\n    <Float64Array>[ -2.0, 0.0, 1.0, 0.0, 2.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dcumax( 3, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 2.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 2.0, 2.0 ]\n\n\nbase.strided.dcumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum of double-precision floating-point strided\n    array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 1.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumax, base.strided.dcumin, base.strided.scumax\n","base.strided.dcumax.ndarray":"\nbase.strided.dcumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum of double-precision floating-point strided\n    array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 1.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumax, base.strided.dcumin, base.strided.scumax","base.strided.dcumaxabs":"\nbase.strided.dcumaxabs( N, x, strideX, y, strideY )\n    Computes the cumulative maximum absolute value of double-precision floating-\n    point strided array elements.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumaxabs( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.0, 2.0, 2.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcumaxabs( 3, x, 2, y, 2 )\n    <Float64Array>[ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dcumaxabs( 3, x1, 2, y1, 1 )\n    <Float64Array>[ 2.0, 2.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n\nbase.strided.dcumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum absolute value of double-precision floating-\n    point strided array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cumaxabs, base.strided.dcumax, base.strided.dcuminabs, base.strided.scumaxabs\n","base.strided.dcumaxabs.ndarray":"\nbase.strided.dcumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum absolute value of double-precision floating-\n    point strided array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cumaxabs, base.strided.dcumax, base.strided.dcuminabs, base.strided.scumaxabs","base.strided.dcumin":"\nbase.strided.dcumin( N, x, strideX, y, strideY )\n    Computes the cumulative minimum of double-precision floating-point strided\n    array elements.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumin( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.0, -2.0, -2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcumin( 3, x, 2, y, 2 )\n    <Float64Array>[ -2.0, 0.0, -2.0, 0.0, -2.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dcumin( 3, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, -2.0, -2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n\nbase.strided.dcumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum of double-precision floating-point strided\n    array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -2.0, -2.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumin, base.strided.dcumax, base.strided.scumin\n","base.strided.dcumin.ndarray":"\nbase.strided.dcumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum of double-precision floating-point strided\n    array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -2.0, -2.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumin, base.strided.dcumax, base.strided.scumin","base.strided.dcuminabs":"\nbase.strided.dcuminabs( N, x, strideX, y, strideY )\n    Computes the cumulative minimum absolute value of double-precision floating-\n    point strided array elements.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcuminabs( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.0, 1.0, 1.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcuminabs( 3, x, 2, y, 2 )\n    <Float64Array>[ 2.0, 0.0, 1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dcuminabs( 3, x1, 2, y1, 1 )\n    <Float64Array>[ 2.0, 2.0, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 1.0 ]\n\n\nbase.strided.dcuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum absolute value of double-precision floating-\n    point strided array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cuminabs, base.strided.dcumaxabs, base.strided.dcumin, base.strided.scuminabs\n","base.strided.dcuminabs.ndarray":"\nbase.strided.dcuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum absolute value of double-precision floating-\n    point strided array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cuminabs, base.strided.dcumaxabs, base.strided.dcumin, base.strided.scuminabs","base.strided.dcusum":"\nbase.strided.dcusum( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements.\n\n    The `N` and stride parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusum( x.length, 0.0, x, 1, y, 1 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusum( 3, 0.0, x, 2, y, 2 )\n    <Float64Array>[ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dcusum( 3, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumpw, base.strided.gcusum, base.strided.scusum\n","base.strided.dcusum.ndarray":"\nbase.strided.dcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumpw, base.strided.gcusum, base.strided.scusum","base.strided.dcusumkbn":"\nbase.strided.dcusumkbn( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using an improved Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumkbn( x.length, 0.0, x, 1, y, 1 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumkbn( 3, 0.0, x, 2, y, 2 )\n    <Float64Array>[ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dcusumkbn( 3, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusumkbn, base.strided.scusumkbn\n","base.strided.dcusumkbn.ndarray":"\nbase.strided.dcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusumkbn, base.strided.scusumkbn","base.strided.dcusumkbn2":"\nbase.strided.dcusumkbn2( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of double-precision floating-point strided\n    array elements using a second-order iterative Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumkbn2( x.length, 0.0, x, 1, y, 1 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumkbn2( 3, 0.0, x, 2, y, 2 )\n    <Float64Array>[ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dcusumkbn2( 3, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of double-precision floating-point strided\n    array elements using a second-order iterative Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusumkbn2, base.strided.scusumkbn2\n","base.strided.dcusumkbn2.ndarray":"\nbase.strided.dcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of double-precision floating-point strided\n    array elements using a second-order iterative Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusumkbn2, base.strided.scusumkbn2","base.strided.dcusumors":"\nbase.strided.dcusumors( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using ordinary recursive summation.\n\n    The `N` and stride parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumors( x.length, 0.0, x, 1, y, 1 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumors( 3, 0.0, x, 2, y, 2 )\n    <Float64Array>[ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dcusumors( 3, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using ordinary recursive summation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusumors, base.strided.scusumors\n","base.strided.dcusumors.ndarray":"\nbase.strided.dcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using ordinary recursive summation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusumors, base.strided.scusumors","base.strided.dcusumpw":"\nbase.strided.dcusumpw( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using pairwise summation.\n\n    The `N` and stride parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumpw( x.length, 0.0, x, 1, y, 1 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumpw( 3, 0.0, x, 2, y, 2 )\n    <Float64Array>[ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dcusumpw( 3, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusumpw, base.strided.scusumpw\n","base.strided.dcusumpw.ndarray":"\nbase.strided.dcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusumpw, base.strided.scusumpw","base.strided.ddeg2rad":"\nbase.strided.ddeg2rad( N, x, strideX, y, strideY )\n    Converts each element in a double-precision floating-point strided array `x`\n    from degrees to radians and assigns the results to elements in a double-\n    precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.ddeg2rad( x.length, x, 1, y, 1 )\n    <Float64Array>[ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.ddeg2rad( N, x, 2, y, -1 )\n    <Float64Array>[ ~0.785, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.ddeg2rad( N, x1, -2, y1, 1 )\n    <Float64Array>[ ~1.047, ~0.524 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.ddeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Converts each element in a double-precision floating-point strided array `x`\n    from degrees to radians and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.ddeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.ddeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n    See Also\n    --------\n    strided.deg2rad, base.strided.sdeg2rad\n","base.strided.ddeg2rad.ndarray":"\nbase.strided.ddeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Converts each element in a double-precision floating-point strided array `x`\n    from degrees to radians and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.ddeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.ddeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n    See Also\n    --------\n    strided.deg2rad, base.strided.sdeg2rad","base.strided.ddot":"\nbase.strided.ddot( N, x, strideX, y, strideY )\n    Computes the dot product of two double-precision floating-point vectors.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: number\n        Dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var out = base.strided.ddot( x.length, x, 1, y, 1 )\n    -5.0\n\n    // Strides:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > out = base.strided.ddot( 3, x, 2, y, -1 )\n    9.0\n\n    // Using view offsets:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n    > out = base.strided.ddot( 3, x1, -2, y1, 1 )\n    128.0\n\n\nbase.strided.ddot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the dot product of two double-precision floating-point vectors\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing based on a starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: number\n        Dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var out = base.strided.ddot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    -5.0\n\n    // Strides:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > out = base.strided.ddot.ndarray( 3, x, 2, 0, y, 2, 0 )\n    9.0\n\n    // Using offset indices:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > out = base.strided.ddot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n    128.0\n\n    See Also\n    --------\n    base.strided.dsdot, base.strided.gdot, base.strided.sdot, base.strided.sdsdot, ddot\n","base.strided.ddot.ndarray":"\nbase.strided.ddot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the dot product of two double-precision floating-point vectors\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing based on a starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: number\n        Dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var out = base.strided.ddot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    -5.0\n\n    // Strides:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > out = base.strided.ddot.ndarray( 3, x, 2, 0, y, 2, 0 )\n    9.0\n\n    // Using offset indices:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > out = base.strided.ddot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n    128.0\n\n    See Also\n    --------\n    base.strided.dsdot, base.strided.gdot, base.strided.sdot, base.strided.sdsdot, ddot","base.strided.dfill":"\nbase.strided.dfill( N, alpha, x, strideX )\n    Fills a double-precision floating-point strided array with a specified\n    scalar value.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dfill( x.length, 5.0, x, 1 )\n    <Float64Array>[ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dfill( 3, 5.0, x, 2 )\n    <Float64Array>[ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dfill( 3, 5.0, x1, 2 )\n    <Float64Array>[ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n    > x0\n    <Float64Array>[ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.dfill.ndarray( N, alpha, x, strideX, offsetX )\n    Fills a double-precision floating-point strided array with a specified\n    scalar value using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dfill.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float64Array>[ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.dfill.ndarray( 3, 5.0, x, 2, 1 )\n    <Float64Array>[ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n    See Also\n    --------\n    base.strided.gfill, base.strided.sfill\n","base.strided.dfill.ndarray":"\nbase.strided.dfill.ndarray( N, alpha, x, strideX, offsetX )\n    Fills a double-precision floating-point strided array with a specified\n    scalar value using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dfill.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float64Array>[ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.dfill.ndarray( 3, 5.0, x, 2, 1 )\n    <Float64Array>[ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n    See Also\n    --------\n    base.strided.gfill, base.strided.sfill","base.strided.dfloor":"\nbase.strided.dfloor( N, x, strideX, y, strideY )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward negative infinity and assigns the results to elements in a double-\n    precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dfloor( x.length, x, 1, y, 1 )\n    <Float64Array>[ -2.0, 1.0, 3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dfloor( N, x, 2, y, -1 )\n    <Float64Array>[ 3.0, -2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dfloor( N, x1, -2, y1, 1 )\n    <Float64Array>[ 4.0, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 1.0 ]\n\n\nbase.strided.dfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward negative infinity and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ -2.0, 1.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dceil, base.strided.dtrunc, strided.floor, base.strided.sfloor\n","base.strided.dfloor.ndarray":"\nbase.strided.dfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward negative infinity and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ -2.0, 1.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dceil, base.strided.dtrunc, strided.floor, base.strided.sfloor","base.strided.dinv":"\nbase.strided.dinv( N, x, strideX, y, strideY )\n    Computes the multiplicative inverse for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dinv( x.length, x, 1, y, 1 )\n    <Float64Array>[ -0.05, -1.0, 0.5, 0.25 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dinv( N, x, 2, y, -1 )\n    <Float64Array>[ 0.5, -0.05, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dinv( N, x1, -2, y1, 1 )\n    <Float64Array>[ 0.25, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.dinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the multiplicative inverse for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ -0.05, -1.0, 0.5, 0.25 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n    See Also\n    --------\n    strided.inv, base.strided.sinv\n","base.strided.dinv.ndarray":"\nbase.strided.dinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the multiplicative inverse for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ -0.05, -1.0, 0.5, 0.25 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n    See Also\n    --------\n    strided.inv, base.strided.sinv","base.strided.dmap":"\nbase.strided.dmap( N, x, strideX, y, strideY, fcn )\n    Applies a unary function to a double-precision floating-point strided input\n    array and assigns results to a double-precision floating-point strided\n    output array.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap( x.length, x, 1, y, 1, base.identity )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap( 2, x, 2, y, -1, base.identity )\n    <Float64Array>[ 3.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmap( 2, x1, -2, y1, 1, base.identity )\n    <Float64Array>[ 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n    Applies a unary function to a double-precision floating-point strided input\n    array and assigns results to a double-precision floating-point strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identity )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identity )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.smap, base.strided.unary\n","base.strided.dmap.ndarray":"\nbase.strided.dmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n    Applies a unary function to a double-precision floating-point strided input\n    array and assigns results to a double-precision floating-point strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identity )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identity )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.smap, base.strided.unary","base.strided.dmap2":"\nbase.strided.dmap2( N, x, sx, y, sy, z, sz, fcn )\n    Applies a binary function to double-precision floating-point strided input\n    arrays and assigns results to a double-precision floating-point strided\n    output array.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    z: Float64Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float64Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap2( x.length, x, 1, y, 1, z, 1, base.add )\n    <Float64Array>[ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Using `N` and stride parameters:\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap2( 2, x, 2, y, -1, z, 1, base.add )\n    <Float64Array>[ 3.0, 4.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmap2( 2, x1, -2, y1, 1, z1, 1, base.add )\n    <Float64Array>[ 7.0, 6.0 ]\n    > z0\n    <Float64Array>[ 0.0, 0.0, 7.0, 6.0 ]\n\n\nbase.strided.dmap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Float64Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float64Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.add )\n    <Float64Array>[ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.add )\n    <Float64Array>[ 0.0, 6.0, 7.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.smap2, base.strided.binary\n","base.strided.dmap2.ndarray":"\nbase.strided.dmap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Float64Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float64Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.add )\n    <Float64Array>[ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.add )\n    <Float64Array>[ 0.0, 6.0, 7.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.smap2, base.strided.binary","base.strided.dmax":"\nbase.strided.dmax( N, x, strideX )\n    Computes the maximum value of a double-precision floating-point strided\n    array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmax( x.length, x, 1 )\n    2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dmax( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dmax( 3, x1, 2 )\n    2.0\n\n\nbase.strided.dmax.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a double-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmax.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dmax.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dnanmax, base.strided.max, base.strided.smax\n","base.strided.dmax.ndarray":"\nbase.strided.dmax.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a double-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmax.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dmax.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dnanmax, base.strided.max, base.strided.smax","base.strided.dmaxabs":"\nbase.strided.dmaxabs( N, x, strideX )\n    Computes the maximum absolute value of a double-precision floating-point\n    strided array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmaxabs( x.length, x, 1 )\n    2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dmaxabs( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dmaxabs( 3, x1, 2 )\n    2.0\n\n\nbase.strided.dmaxabs.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmaxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dmaxabs.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dminabs, base.strided.dnanmaxabs, base.strided.maxabs, base.strided.smaxabs\n","base.strided.dmaxabs.ndarray":"\nbase.strided.dmaxabs.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmaxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dmaxabs.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dminabs, base.strided.dnanmaxabs, base.strided.maxabs, base.strided.smaxabs","base.strided.dmaxabssorted":"\nbase.strided.dmaxabssorted( N, x, strideX )\n    Computes the maximum absolute value of a sorted double-precision floating-\n    point strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n    > base.strided.dmaxabssorted( x.length, x, 1 )\n    3.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dmaxabssorted( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dmaxabssorted( 3, x1, 2 )\n    3.0\n\n\nbase.strided.dmaxabssorted.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a sorted double-precision floating-\n    point strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n    > base.strided.dmaxabssorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.dmaxabssorted.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmaxabs, base.strided.dmaxsorted, base.strided.smaxabssorted\n","base.strided.dmaxabssorted.ndarray":"\nbase.strided.dmaxabssorted.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a sorted double-precision floating-\n    point strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n    > base.strided.dmaxabssorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.dmaxabssorted.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmaxabs, base.strided.dmaxsorted, base.strided.smaxabssorted","base.strided.dmaxsorted":"\nbase.strided.dmaxsorted( N, x, strideX )\n    Computes the maximum value of a sorted double-precision floating-point\n    strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dmaxsorted( x.length, x, 1 )\n    3.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dmaxsorted( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dmaxsorted( 3, x1, 2 )\n    3.0\n\n\nbase.strided.dmaxsorted.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dmaxsorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.dmaxsorted.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dminsorted, base.strided.maxsorted, base.strided.smaxsorted\n","base.strided.dmaxsorted.ndarray":"\nbase.strided.dmaxsorted.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dmaxsorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.dmaxsorted.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dminsorted, base.strided.maxsorted, base.strided.smaxsorted","base.strided.dmean":"\nbase.strided.dmean( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmean( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dmean( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmean( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.mean, base.strided.smean\n","base.strided.dmean.ndarray":"\nbase.strided.dmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.mean, base.strided.smean","base.strided.dmeankbn":"\nbase.strided.dmeankbn( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeankbn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dmeankbn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmeankbn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dmeankbn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeankbn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeankbn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.meankbn, base.strided.smeankbn\n","base.strided.dmeankbn.ndarray":"\nbase.strided.dmeankbn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeankbn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeankbn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.meankbn, base.strided.smeankbn","base.strided.dmeankbn2":"\nbase.strided.dmeankbn2( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a second-order iterative Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeankbn2( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dmeankbn2( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmeankbn2( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dmeankbn2.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeankbn2.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeankbn2.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.meankbn2, base.strided.smeankbn2\n","base.strided.dmeankbn2.ndarray":"\nbase.strided.dmeankbn2.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeankbn2.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeankbn2.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.meankbn2, base.strided.smeankbn2","base.strided.dmeanli":"\nbase.strided.dmeanli( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanli( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dmeanli( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmeanli( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dmeanli.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanli.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanli.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dmeanlipw, base.strided.smeanli\n","base.strided.dmeanli.ndarray":"\nbase.strided.dmeanli.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanli.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanli.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dmeanlipw, base.strided.smeanli","base.strided.dmeanlipw":"\nbase.strided.dmeanlipw( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm with pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanlipw( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dmeanlipw( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmeanlipw( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dmeanlipw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm with pairwise summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanlipw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanlipw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dmeanli, base.strided.dmeanpw, base.strided.smeanlipw\n","base.strided.dmeanlipw.ndarray":"\nbase.strided.dmeanlipw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm with pairwise summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanlipw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanlipw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dmeanli, base.strided.dmeanpw, base.strided.smeanlipw","base.strided.dmeanors":"\nbase.strided.dmeanors( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using ordinary recursive summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanors( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dmeanors( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmeanors( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dnanmeanors, base.strided.meanors, base.strided.smeanors\n","base.strided.dmeanors.ndarray":"\nbase.strided.dmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dnanmeanors, base.strided.meanors, base.strided.smeanors","base.strided.dmeanpn":"\nbase.strided.dmeanpn( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a two-pass error correction algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanpn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dmeanpn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmeanpn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a two-pass error correction algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dnanmeanpn, base.strided.meanpn, base.strided.smeanpn\n","base.strided.dmeanpn.ndarray":"\nbase.strided.dmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a two-pass error correction algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dnanmeanpn, base.strided.meanpn, base.strided.smeanpn","base.strided.dmeanpw":"\nbase.strided.dmeanpw( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanpw( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dmeanpw( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmeanpw( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dmeanpw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanpw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanpw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dnanmeanpw, base.strided.meanpw, base.strided.smeanpw\n","base.strided.dmeanpw.ndarray":"\nbase.strided.dmeanpw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanpw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanpw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dnanmeanpw, base.strided.meanpw, base.strided.smeanpw","base.strided.dmeanstdev":"\nbase.strided.dmeanstdev( N, c, x, strideX, out, strideOut )\n    Computes the mean and standard deviation of a double-precision floating-\n    point strided array.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns a mean and standard deviation equal to\n    `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanstdev( x.length, 1, x, 1, out, 1 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > out = new Float64Array( 2 );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanstdev( N, 1, x, 2, out, 1 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanstdev( N, 1, x1, 2, out, 1 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\nbase.strided.dmeanstdev.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the mean and standard deviation of a double-precision floating-\n    point strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanstdev.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanstdev.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dmeanvar, base.strided.dstdev\n","base.strided.dmeanstdev.ndarray":"\nbase.strided.dmeanstdev.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the mean and standard deviation of a double-precision floating-\n    point strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanstdev.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanstdev.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dmeanvar, base.strided.dstdev","base.strided.dmeanstdevpn":"\nbase.strided.dmeanstdevpn( N, c, x, strideX, out, strideOut )\n    Computes the mean and standard deviation of a double-precision floating-\n    point strided array using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns a mean and standard deviation equal to\n    `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanstdevpn( x.length, 1, x, 1, out, 1 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > out = new Float64Array( 2 );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanstdevpn( N, 1, x, 2, out, 1 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanstdevpn( N, 1, x1, 2, out, 1 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\nbase.strided.dmeanstdevpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the mean and standard deviation of a double-precision floating-\n    point strided array using a two-pass algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanstdevpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanstdevpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.dmeanstdev, base.strided.dmeanvarpn, base.strided.dstdevpn\n","base.strided.dmeanstdevpn.ndarray":"\nbase.strided.dmeanstdevpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the mean and standard deviation of a double-precision floating-\n    point strided array using a two-pass algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanstdevpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanstdevpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.dmeanstdev, base.strided.dmeanvarpn, base.strided.dstdevpn","base.strided.dmeanvar":"\nbase.strided.dmeanvar( N, c, x, strideX, out, strideOut )\n    Computes the mean and variance of a double-precision floating-point strided\n    array.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns a mean and variance equal to `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanvar( x.length, 1, x, 1, out, 1 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > out = new Float64Array( 2 );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanvar( N, 1, x, 2, out, 1 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanvar( N, 1, x1, 2, out, 1 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\nbase.strided.dmeanvar.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the mean and variance of a double-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanvar.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanvar.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dvariance\n","base.strided.dmeanvar.ndarray":"\nbase.strided.dmeanvar.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the mean and variance of a double-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanvar.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanvar.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dvariance","base.strided.dmeanvarpn":"\nbase.strided.dmeanvarpn( N, c, x, strideX, out, strideOut )\n    Computes the mean and variance of a double-precision floating-point strided\n    array using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns a mean and variance equal to `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanvarpn( x.length, 1, x, 1, out, 1 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > out = new Float64Array( 2 );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanvarpn( N, 1, x, 2, out, 1 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanvarpn( N, 1, x1, 2, out, 1 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\nbase.strided.dmeanvarpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the mean and variance of a double-precision floating-point strided\n    array using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanvarpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanvarpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.dmeanstdevpn, base.strided.dmeanvar, base.strided.dvariancepn\n","base.strided.dmeanvarpn.ndarray":"\nbase.strided.dmeanvarpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the mean and variance of a double-precision floating-point strided\n    array using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanvarpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanvarpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.dmeanstdevpn, base.strided.dmeanvar, base.strided.dvariancepn","base.strided.dmeanwd":"\nbase.strided.dmeanwd( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanwd( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dmeanwd( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmeanwd( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dnanmeanwd, base.strided.meanwd, base.strided.smeanwd\n","base.strided.dmeanwd.ndarray":"\nbase.strided.dmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dnanmeanwd, base.strided.meanwd, base.strided.smeanwd","base.strided.dmediansorted":"\nbase.strided.dmediansorted( N, x, strideX )\n    Computes the median value of a sorted double-precision floating-point\n    strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dmediansorted( x.length, x, 1 )\n    2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dmediansorted( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dmediansorted( 3, x1, 2 )\n    2.0\n\n\nbase.strided.dmediansorted.ndarray( N, x, strideX, offsetX )\n    Computes the median value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.dmediansorted.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.mediansorted, base.strided.smediansorted\n","base.strided.dmediansorted.ndarray":"\nbase.strided.dmediansorted.ndarray( N, x, strideX, offsetX )\n    Computes the median value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.dmediansorted.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.mediansorted, base.strided.smediansorted","base.strided.dmidrange":"\nbase.strided.dmidrange( N, x, strideX )\n    Computes the mid-range of a double-precision floating-point strided array.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Mid-range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmidrange( x.length, x, 1 )\n    0.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dmidrange( 3, x, 2 )\n    0.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dmidrange( 3, x1, 2 )\n    0.0\n\n\nbase.strided.dmidrange.ndarray( N, x, strideX, offsetX )\n    Computes the mid-range of a double-precision floating-point strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Mid-range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmidrange.ndarray( x.length, x, 1, 0 )\n    0.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dmidrange.ndarray( 3, x, 2, 1 )\n    0.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dmean, base.strided.dmin, base.strided.drange, base.strided.smidrange\n","base.strided.dmidrange.ndarray":"\nbase.strided.dmidrange.ndarray( N, x, strideX, offsetX )\n    Computes the mid-range of a double-precision floating-point strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Mid-range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmidrange.ndarray( x.length, x, 1, 0 )\n    0.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dmidrange.ndarray( 3, x, 2, 1 )\n    0.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dmean, base.strided.dmin, base.strided.drange, base.strided.smidrange","base.strided.dmin":"\nbase.strided.dmin( N, x, strideX )\n    Computes the minimum value of a double-precision floating-point strided\n    array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmin( x.length, x, 1 )\n    -2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dmin( 3, x, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmin( N, x1, stride )\n    -2.0\n\n\nbase.strided.dmin.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a double-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dmin.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dnanmin, base.strided.min, base.strided.smin\n","base.strided.dmin.ndarray":"\nbase.strided.dmin.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a double-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dmin.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dnanmin, base.strided.min, base.strided.smin","base.strided.dminabs":"\nbase.strided.dminabs( N, x, strideX )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dminabs( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dminabs( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dminabs( 3, x1, 2 )\n    1.0\n\n\nbase.strided.dminabs.ndarray( N, x, strideX, offsetX )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dminabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dminabs.ndarray( 3, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dmaxabs, base.strided.dnanminabs, base.strided.minabs, base.strided.sminabs\n","base.strided.dminabs.ndarray":"\nbase.strided.dminabs.ndarray( N, x, strideX, offsetX )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dminabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dminabs.ndarray( 3, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dmaxabs, base.strided.dnanminabs, base.strided.minabs, base.strided.sminabs","base.strided.dminsorted":"\nbase.strided.dminsorted( N, x, strideX )\n    Computes the minimum value of a sorted double-precision floating-point\n    strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dminsorted( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dminsorted( 3, x, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dminsorted( 3, x1, 2 )\n    -2.0\n\n\nbase.strided.dminsorted.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dminsorted.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.dminsorted.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dmaxsorted, base.strided.minsorted, base.strided.sminsorted\n","base.strided.dminsorted.ndarray":"\nbase.strided.dminsorted.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dminsorted.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.dminsorted.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dmaxsorted, base.strided.minsorted, base.strided.sminsorted","base.strided.dmskabs":"\nbase.strided.dmskabs( N, x, sx, m, sm, y, sy )\n    Computes the absolute value for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ 2.0, 1.0, 0.0, 5.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskabs( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ 5.0, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 5.0, 1.0 ]\n\n\nbase.strided.dmskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the absolute value for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 2.0, 1.0, 0.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 5.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dabs, base.strided.dmskabs2, base.strided.smskabs\n","base.strided.dmskabs.ndarray":"\nbase.strided.dmskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the absolute value for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 2.0, 1.0, 0.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 5.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dabs, base.strided.dmskabs2, base.strided.smskabs","base.strided.dmskabs2":"\nbase.strided.dmskabs2( N, x, sx, m, sm, y, sy )\n    Computes the squared absolute value for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point\n    strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs2( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ 4.0, 1.0, 0.0, 25.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs2( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, 4.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskabs2( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ 25.0, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 25.0, 1.0 ]\n\n\nbase.strided.dmskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the squared absolute value for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point\n    strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 4.0, 1.0, 0.0, 25.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 25.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dabs2, base.strided.dmskabs, base.strided.smskabs2\n","base.strided.dmskabs2.ndarray":"\nbase.strided.dmskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the squared absolute value for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point\n    strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 4.0, 1.0, 0.0, 25.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 25.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dabs2, base.strided.dmskabs, base.strided.smskabs2","base.strided.dmskcbrt":"\nbase.strided.dmskcbrt( N, x, sx, m, sm, y, sy )\n    Computes the cube root for each element in a double-precision floating-point\n    strided array `x` according to a strided mask array and assigns the results\n    to elements in a double-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskcbrt( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ 0.0, 1.0, 0.0, 3.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskcbrt( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskcbrt( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ 3.0, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.dmskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the cube root for each element in a double-precision floating-point\n    strided array `x` according to a strided mask array and assigns the results\n    to elements in a double-precision floating-point strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, 1.0, 0.0, 3.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dcbrt, base.strided.dmsksqrt, base.strided.smskcbrt\n","base.strided.dmskcbrt.ndarray":"\nbase.strided.dmskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the cube root for each element in a double-precision floating-point\n    strided array `x` according to a strided mask array and assigns the results\n    to elements in a double-precision floating-point strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, 1.0, 0.0, 3.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dcbrt, base.strided.dmsksqrt, base.strided.smskcbrt","base.strided.dmskceil":"\nbase.strided.dmskceil( N, x, sx, m, sm, y, sy )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward positive infinity according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskceil( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ 2.0, 3.0, 0.0, 4.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskceil( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskceil( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ 4.0, 3.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.dmskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward positive infinity according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 2.0, 3.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n    See Also\n    --------\n    base.strided.dceil, base.strided.dmskfloor, base.strided.dmsktrunc, base.strided.smskceil\n","base.strided.dmskceil.ndarray":"\nbase.strided.dmskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward positive infinity according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 2.0, 3.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n    See Also\n    --------\n    base.strided.dceil, base.strided.dmskfloor, base.strided.dmsktrunc, base.strided.smskceil","base.strided.dmskdeg2rad":"\nbase.strided.dmskdeg2rad( N, x, sx, m, sm, y, sy )\n    Converts each element in a double-precision floating-point strided array `x`\n    from degrees to radians according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskdeg2rad( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ 0.0, ~0.524, 0.0, ~1.047 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskdeg2rad( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ ~1.047, ~0.524 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.dmskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Converts each element in a double-precision floating-point strided array `x`\n    from degrees to radians according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, ~0.524, 0.0, ~1.047 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n    See Also\n    --------\n    base.strided.ddeg2rad, base.strided.dmskdeg2rad, base.strided.smskdeg2rad\n","base.strided.dmskdeg2rad.ndarray":"\nbase.strided.dmskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Converts each element in a double-precision floating-point strided array `x`\n    from degrees to radians according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, ~0.524, 0.0, ~1.047 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n    See Also\n    --------\n    base.strided.ddeg2rad, base.strided.dmskdeg2rad, base.strided.smskdeg2rad","base.strided.dmskfloor":"\nbase.strided.dmskfloor( N, x, sx, m, sm, y, sy )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward negative infinity according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskfloor( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskfloor( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskfloor( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dmskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward negative infinity according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dfloor, base.strided.dmskceil, base.strided.dmsktrunc, base.strided.smskfloor\n","base.strided.dmskfloor.ndarray":"\nbase.strided.dmskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward negative infinity according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dfloor, base.strided.dmskceil, base.strided.dmsktrunc, base.strided.smskfloor","base.strided.dmskinv":"\nbase.strided.dmskinv( N, x, sx, m, sm, y, sy )\n    Computes the multiplicative inverse for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskinv( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ -0.05, -1.0, 0.0, 0.25 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskinv( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, -0.05, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskinv( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ 0.25, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.dmskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the multiplicative inverse for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ -0.05, -1.0, 0.0, 0.25 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dinv, base.strided.smskinv\n","base.strided.dmskinv.ndarray":"\nbase.strided.dmskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the multiplicative inverse for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ -0.05, -1.0, 0.0, 0.25 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dinv, base.strided.smskinv","base.strided.dmskmap":"\nbase.strided.dmskmap( N, x, sx, m, sm, y, sy, fcn )\n    Applies a unary function to a double-precision floating-point strided input\n    array according to a strided mask array and assigns results to a double-\n    precision floating-point strided output array.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskmap( x.length, x, 1, m, 1, y, 1, base.identity )\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskmap( 2, x, 2, m, 2, y, -1, base.identity )\n    <Float64Array>[ 0.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\n    <Float64Array>[ 0.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, 2.0 ]\n\n\nbase.strided.dmskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n    Applies a unary function to a double-precision floating-point strided input\n    array according to a strided mask array and assigns results to a double-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n    <Float64Array>[ 0.0, 0.0, 4.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmap, base.strided.dmskmap2, base.strided.mskunary, base.strided.smskmap\n","base.strided.dmskmap.ndarray":"\nbase.strided.dmskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n    Applies a unary function to a double-precision floating-point strided input\n    array according to a strided mask array and assigns results to a double-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n    <Float64Array>[ 0.0, 0.0, 4.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmap, base.strided.dmskmap2, base.strided.mskunary, base.strided.smskmap","base.strided.dmskmap2":"\nbase.strided.dmskmap2( N, x, sx, y, sy, m, sm, z, sz, fcn )\n    Applies a binary function to double-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a double-\n    precision floating-point strided output array.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    z: Float64Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float64Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.dmskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.add )\n    <Float64Array>[ 2.0, 4.0, 0.0, 8.0 ]\n\n    // Using `N` and stride parameters:\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.add )\n    <Float64Array>[ 0.0, 3.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.add )\n    <Float64Array>[ 0.0, 6.0 ]\n    > z0\n    <Float64Array>[ 0.0, 0.0, 0.0, 6.0 ]\n\n\nbase.strided.dmskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n    Applies a binary function to double-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a double-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    z: Float64Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float64Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.dmskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.add )\n    <Float64Array>[ 2.0, 4.0, 0.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.dmskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.add )\n    <Float64Array>[ 0.0, 0.0, 7.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmap2, base.strided.dmskmap, base.strided.smskmap2\n","base.strided.dmskmap2.ndarray":"\nbase.strided.dmskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n    Applies a binary function to double-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a double-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    z: Float64Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float64Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.dmskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.add )\n    <Float64Array>[ 2.0, 4.0, 0.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.dmskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.add )\n    <Float64Array>[ 0.0, 0.0, 7.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmap2, base.strided.dmskmap, base.strided.smskmap2","base.strided.dmskmax":"\nbase.strided.dmskmax( N, x, strideX, mask, strideMask )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask.\n\n    The `N` and stride parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.dmskmax( x.length, x, 1, mask, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.dmskmax( 3, x, 2, mask, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dmskmax( 3, x1, 2, mask1, 2 )\n    2.0\n\n\nbase.strided.dmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.dmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dmskmin, base.strided.dnanmax, base.strided.dnanmskmax, base.strided.mskmax, base.strided.smskmax\n","base.strided.dmskmax.ndarray":"\nbase.strided.dmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.dmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dmskmin, base.strided.dnanmax, base.strided.dnanmskmax, base.strided.mskmax, base.strided.smskmax","base.strided.dmskmin":"\nbase.strided.dmskmin( N, x, strideX, mask, strideMask )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.dmskmin( x.length, x, 1, mask, 1 )\n    -2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.dmskmin( 3, x, 2, mask, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dmskmin( 3, x1, 2, mask1, 2 )\n    -2.0\n\n\nbase.strided.dmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.dmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dmskmax, base.strided.dnanmin, base.strided.dnanmskmin, base.strided.mskmin, base.strided.smskmin\n","base.strided.dmskmin.ndarray":"\nbase.strided.dmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.dmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dmskmax, base.strided.dnanmin, base.strided.dnanmskmin, base.strided.mskmin, base.strided.smskmin","base.strided.dmskramp":"\nbase.strided.dmskramp( N, x, sx, m, sm, y, sy )\n    Evaluates the ramp function for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskramp( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ 1.1, 2.5, 0.0, 4.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskramp( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, 1.1, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskramp( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ 4.0, 2.5 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.5 ]\n\n\nbase.strided.dmskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Evaluates the ramp function for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.1, 2.5, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.5 ]\n\n    See Also\n    --------\n    base.strided.dramp, base.strided.smskramp\n","base.strided.dmskramp.ndarray":"\nbase.strided.dmskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Evaluates the ramp function for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.1, 2.5, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.5 ]\n\n    See Also\n    --------\n    base.strided.dramp, base.strided.smskramp","base.strided.dmskrange":"\nbase.strided.dmskrange( N, x, strideX, mask, strideMask )\n    Computes the range of a double-precision floating-point strided array\n    according to a mask.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.dmskrange( x.length, x, 1, mask, 1 )\n    4.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.dmskrange( 3, x, 2, mask, 2 )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dmskrange( 3, x1, 2, mask1, 2 )\n    4.0\n\n\nbase.strided.dmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a double-precision floating-point strided array\n    according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.dmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.dmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dmskmax, base.strided.dmskmin, base.strided.dnanrange, base.strided.drange, base.strided.mskrange, base.strided.smskrange\n","base.strided.dmskrange.ndarray":"\nbase.strided.dmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a double-precision floating-point strided array\n    according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.dmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.dmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dmskmax, base.strided.dmskmin, base.strided.dnanrange, base.strided.drange, base.strided.mskrange, base.strided.smskrange","base.strided.dmskrsqrt":"\nbase.strided.dmskrsqrt( N, x, sx, m, sm, y, sy )\n    Computes the reciprocal square root for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskrsqrt( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ Infinity, 0.5, 0.0, ~0.289 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskrsqrt( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, Infinity, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ ~0.289, 0.5 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.dmskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the reciprocal square root for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ Infinity, 0.5, 0.0, ~0.289 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n    See Also\n    --------\n    base.strided.dmsksqrt, base.strided.dsqrt, base.strided.smskrsqrt\n","base.strided.dmskrsqrt.ndarray":"\nbase.strided.dmskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the reciprocal square root for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ Infinity, 0.5, 0.0, ~0.289 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n    See Also\n    --------\n    base.strided.dmsksqrt, base.strided.dsqrt, base.strided.smskrsqrt","base.strided.dmsksqrt":"\nbase.strided.dmsksqrt( N, x, sx, m, sm, y, sy )\n    Computes the principal square root for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsksqrt( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ 0.0, 2.0, 0.0, ~3.464 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsksqrt( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmsksqrt( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ ~3.464, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.dmsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the principal square root for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, 2.0, 0.0, ~3.464 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmskcbrt, base.strided.dmskrsqrt, base.strided.dsqrt, base.strided.smsksqrt\n","base.strided.dmsksqrt.ndarray":"\nbase.strided.dmsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the principal square root for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, 2.0, 0.0, ~3.464 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmskcbrt, base.strided.dmskrsqrt, base.strided.dsqrt, base.strided.smsksqrt","base.strided.dmsktrunc":"\nbase.strided.dmsktrunc( N, x, sx, m, sm, y, sy )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward zero according to a strided mask array and assigns the results to\n    elements in a double-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsktrunc( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsktrunc( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmsktrunc( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dmsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward zero according to a strided mask array and assigns the results to\n    elements in a double-precision floating-point strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmskceil, base.strided.dmskfloor, base.strided.dtrunc, base.strided.smsktrunc\n","base.strided.dmsktrunc.ndarray":"\nbase.strided.dmsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward zero according to a strided mask array and assigns the results to\n    elements in a double-precision floating-point strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmskceil, base.strided.dmskfloor, base.strided.dtrunc, base.strided.smsktrunc","base.strided.dnanasum":"\nbase.strided.dnanasum( N, x, strideX )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements, ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanasum( x.length, x, 1 )\n    5.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.dnanasum( 4, x, 2 )\n    5.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnanasum( 4, x1, 2 )\n    5.0\n\n\nbase.strided.dnanasum.ndarray( N, x, strideX, offsetX )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements, ignoring `NaN` values and using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanasum.ndarray( x.length, x, 1, 0 )\n    5.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnanasum.ndarray( 4, x, 2, 1 )\n    5.0\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.dasumpw","base.strided.dnanasum.ndarray":"\nbase.strided.dnanasum.ndarray( N, x, strideX, offsetX )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements, ignoring `NaN` values and using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanasum.ndarray( x.length, x, 1, 0 )\n    5.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnanasum.ndarray( 4, x, 2, 1 )\n    5.0\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.dasumpw","base.strided.dnanasumors":"\nbase.strided.dnanasumors( N, x, strideX )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements, ignoring `NaN` values and using ordinary\n    recursive summation.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanasumors( x.length, x, 1 )\n    5.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanasumors( N, x, stride )\n    5.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanasumors( N, x1, stride )\n    5.0\n\n\nbase.strided.dnanasumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements, ignoring `NaN` values and using ordinary\n    recursive summation alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanasumors.ndarray( x.length, x, 1, 0 )\n    5.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanasumors.ndarray( N, x, 2, 1 )\n    5.0\n\n    See Also\n    --------\n    base.strided.dnanasum\n","base.strided.dnanasumors.ndarray":"\nbase.strided.dnanasumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements, ignoring `NaN` values and using ordinary\n    recursive summation alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanasumors.ndarray( x.length, x, 1, 0 )\n    5.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanasumors.ndarray( N, x, 2, 1 )\n    5.0\n\n    See Also\n    --------\n    base.strided.dnanasum","base.strided.dnanmax":"\nbase.strided.dnanmax( N, x, strideX )\n    Computes the maximum value of a double-precision floating-point strided\n    array, ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmax( x.length, x, 1 )\n    2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > base.strided.dnanmax( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnanmax( 3, x1, 2 )\n    2.0\n\n\nbase.strided.dnanmax.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a double-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.dnanmax.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanmax.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dnanmin, base.strided.nanmax, base.strided.snanmax\n","base.strided.dnanmax.ndarray":"\nbase.strided.dnanmax.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a double-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.dnanmax.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanmax.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dnanmin, base.strided.nanmax, base.strided.snanmax","base.strided.dnanmaxabs":"\nbase.strided.dnanmaxabs( N, x, strideX )\n    Computes the maximum absolute value of a double-precision floating-point\n    strided array, ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmaxabs( x.length, x, 1 )\n    2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > base.strided.dnanmaxabs( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnanmaxabs( 3, x1, 2 )\n    2.0\n\n\nbase.strided.dnanmaxabs.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a double-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.dnanmaxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanmaxabs.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmaxabs, base.strided.dnanmax, base.strided.dnanminabs, base.strided.nanmaxabs, base.strided.snanmaxabs\n","base.strided.dnanmaxabs.ndarray":"\nbase.strided.dnanmaxabs.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a double-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.dnanmaxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanmaxabs.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmaxabs, base.strided.dnanmax, base.strided.dnanminabs, base.strided.nanmaxabs, base.strided.snanmaxabs","base.strided.dnanmean":"\nbase.strided.dnanmean( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmean( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanmean( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanmean( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dnanmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.nanmean, base.strided.snanmean\n","base.strided.dnanmean.ndarray":"\nbase.strided.dnanmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.nanmean, base.strided.snanmean","base.strided.dnanmeanors":"\nbase.strided.dnanmeanors( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanors( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanmeanors( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanmeanors( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dnanmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanors, base.strided.dnanmean, base.strided.nanmeanors, base.strided.snanmeanors\n","base.strided.dnanmeanors.ndarray":"\nbase.strided.dnanmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanors, base.strided.dnanmean, base.strided.nanmeanors, base.strided.snanmeanors","base.strided.dnanmeanpn":"\nbase.strided.dnanmeanpn( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction\n    algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanpn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanmeanpn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanmeanpn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dnanmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction algorithm\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.dnanmean, base.strided.nanmeanpn, base.strided.snanmeanpn\n","base.strided.dnanmeanpn.ndarray":"\nbase.strided.dnanmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction algorithm\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.dnanmean, base.strided.nanmeanpn, base.strided.snanmeanpn","base.strided.dnanmeanpw":"\nbase.strided.dnanmeanpw( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanpw( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanmeanpw( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanmeanpw( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dnanmeanpw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using pairwise summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanpw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmeanpw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpw, base.strided.dnanmean\n","base.strided.dnanmeanpw.ndarray":"\nbase.strided.dnanmeanpw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using pairwise summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanpw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmeanpw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpw, base.strided.dnanmean","base.strided.dnanmeanwd":"\nbase.strided.dnanmeanwd( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, using Welford's algorithm and ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanwd( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanmeanwd( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanmeanwd( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dnanmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanwd, base.strided.dnanmean, base.strided.nanmeanwd, base.strided.snanmeanwd\n","base.strided.dnanmeanwd.ndarray":"\nbase.strided.dnanmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanwd, base.strided.dnanmean, base.strided.nanmeanwd, base.strided.snanmeanwd","base.strided.dnanmin":"\nbase.strided.dnanmin( N, x, strideX )\n    Computes the minimum value of a double-precision floating-point strided\n    array, ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmin( x.length, x, 1 )\n    -2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > base.strided.dnanmin( 3, x, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnanmin( 3, x1, 2 )\n    -2.0\n\n\nbase.strided.dnanmin.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a double-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.dnanmin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanmin.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dnanmax, base.strided.nanmin, base.strided.snanmin\n","base.strided.dnanmin.ndarray":"\nbase.strided.dnanmin.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a double-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.dnanmin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanmin.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dnanmax, base.strided.nanmin, base.strided.snanmin","base.strided.dnanminabs":"\nbase.strided.dnanminabs( N, x, strideX )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array, ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanminabs( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > base.strided.dnanminabs( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnanminabs( 3, x1, 2 )\n    1.0\n\n\nbase.strided.dnanminabs.ndarray( N, x, strideX, offsetX )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.dnanminabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanminabs.ndarray( 3, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dminabs, base.strided.dnanmaxabs, base.strided.dnanmin, base.strided.nanminabs, base.strided.snanminabs\n","base.strided.dnanminabs.ndarray":"\nbase.strided.dnanminabs.ndarray( N, x, strideX, offsetX )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.dnanminabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanminabs.ndarray( 3, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dminabs, base.strided.dnanmaxabs, base.strided.dnanmin, base.strided.nanminabs, base.strided.snanminabs","base.strided.dnanmskmax":"\nbase.strided.dnanmskmax( N, x, strideX, mask, strideMask )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n    > base.strided.dnanmskmax( x.length, x, 1, mask, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmskmax( N, x, 2, mask, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dnanmskmax( N, x1, 2, mask1, 2 )\n    2.0\n\nbase.strided.dnanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.dnanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmskmax, base.strided.dnanmax, base.strided.dnanmskmin, base.strided.nanmskmax, base.strided.snanmskmax\n","base.strided.dnanmskmax.ndarray":"\nbase.strided.dnanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.dnanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmskmax, base.strided.dnanmax, base.strided.dnanmskmin, base.strided.nanmskmax, base.strided.snanmskmax","base.strided.dnanmskmin":"\nbase.strided.dnanmskmin( N, x, strideX, mask, strideMask )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n    > base.strided.dnanmskmin( x.length, x, 1, mask, 1 )\n    -2.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmskmin( N, x, 2, mask, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dnanmskmin( N, x1, 2, mask1, 2 )\n    -2.0\n\nbase.strided.dnanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.dnanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmskmin, base.strided.dnanmin, base.strided.dnanmskmax, base.strided.nanmskmin, base.strided.snanmskmin\n","base.strided.dnanmskmin.ndarray":"\nbase.strided.dnanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.dnanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmskmin, base.strided.dnanmin, base.strided.dnanmskmax, base.strided.nanmskmin, base.strided.snanmskmin","base.strided.dnanmskrange":"\nbase.strided.dnanmskrange( N, x, strideX, mask, strideMask )\n    Computes the range of a double-precision floating-point strided array\n    according to a mask, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n    > base.strided.dnanmskrange( x.length, x, 1, mask, 1 )\n    4.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmskrange( N, x, 2, mask, 2 )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dnanmskrange( N, x1, 2, mask1, 2 )\n    4.0\n\nbase.strided.dnanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a double-precision floating-point strided array\n    according to a mask, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.dnanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dmskrange, base.strided.dnanrange, base.strided.dnanmskmax, base.strided.dnanmskmin, base.strided.nanmskrange, base.strided.snanmskrange\n","base.strided.dnanmskrange.ndarray":"\nbase.strided.dnanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a double-precision floating-point strided array\n    according to a mask, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.dnanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dmskrange, base.strided.dnanrange, base.strided.dnanmskmax, base.strided.dnanmskmin, base.strided.nanmskrange, base.strided.snanmskrange","base.strided.dnannsum":"\nbase.strided.dnannsum( N, x, strideX, out, strideOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns a sum equal to `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsum( x.length, x, 1, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsum( 4, x, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsum( 4, x1, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n\nbase.strided.dnannsum.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsum.ndarray( x.length, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsum.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.dsum","base.strided.dnannsum.ndarray":"\nbase.strided.dnannsum.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsum.ndarray( x.length, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsum.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.dsum","base.strided.dnannsumkbn":"\nbase.strided.dnannsumkbn( N, x, strideX, out, strideOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns a sum equal to `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn( x.length, x, 1, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn( 4, x, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn( 4, x1, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n\nbase.strided.dnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn.ndarray( 4, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsum, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn, base.strided.gnannsumkbn\n","base.strided.dnannsumkbn.ndarray":"\nbase.strided.dnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn.ndarray( 4, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsum, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn, base.strided.gnannsumkbn","base.strided.dnannsumkbn2":"\nbase.strided.dnannsumkbn2( N, x, strideX, out, strideOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm.\n\n    The `N` and stride parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns a sum equal to `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn2( x.length, x, 1, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn2( 4, x, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn2( 4, x1, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n\nbase.strided.dnannsumkbn2.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn2.ndarray( 4, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn2.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn2\n","base.strided.dnannsumkbn2.ndarray":"\nbase.strided.dnannsumkbn2.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn2.ndarray( 4, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn2.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn2","base.strided.dnannsumors":"\nbase.strided.dnannsumors( N, x, strideX, out, strideOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation.\n\n    The `N` and stride parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns a sum equal to `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumors( x.length, x, 1, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumors( 4, x, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumors( 4, x1, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n\nbase.strided.dnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumpw, base.strided.dsumors\n","base.strided.dnannsumors.ndarray":"\nbase.strided.dnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumpw, base.strided.dsumors","base.strided.dnannsumpw":"\nbase.strided.dnannsumpw( N, x, strideX, out, strideOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation.\n\n    The `N` and stride parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns a sum equal to `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumpw( x.length, x, 1, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumpw( 4, x, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumpw( 4, x1, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n\nbase.strided.dnannsumpw.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for the strided array.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumpw.ndarray( x.length, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumpw.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dsumpw\n","base.strided.dnannsumpw.ndarray":"\nbase.strided.dnannsumpw.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for the strided array.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumpw.ndarray( x.length, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumpw.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dsumpw","base.strided.dnanrange":"\nbase.strided.dnanrange( N, x, strideX )\n    Computes the range of a double-precision floating-point strided array,\n    ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanrange( x.length, x, 1 )\n    4.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > base.strided.dnanrange( 3, x, 2 )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnanrange( 3, x1, 2 )\n    4.0\n\n\nbase.strided.dnanrange.ndarray( N, x, strideX, offsetX )\n    Computes the range of a double-precision floating-point strided array,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.dnanrange.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanrange.ndarray( 3, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dnanmax, base.strided.dnanmin, base.strided.drange, base.strided.nanrange, base.strided.snanrange\n","base.strided.dnanrange.ndarray":"\nbase.strided.dnanrange.ndarray( N, x, strideX, offsetX )\n    Computes the range of a double-precision floating-point strided array,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.dnanrange.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanrange.ndarray( 3, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dnanmax, base.strided.dnanmin, base.strided.drange, base.strided.nanrange, base.strided.snanrange","base.strided.dnanstdev":"\nbase.strided.dnanstdev( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdev( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanstdev( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanstdev( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dnanstdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanvariance, base.strided.dstdev, base.strided.nanstdev, base.strided.snanstdev\n","base.strided.dnanstdev.ndarray":"\nbase.strided.dnanstdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanvariance, base.strided.dstdev, base.strided.nanstdev, base.strided.snanstdev","base.strided.dnanstdevch":"\nbase.strided.dnanstdevch( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevch( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanstdevch( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanstdevch( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dnanstdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dnanvariancech, base.strided.dstdevch, base.strided.nanstdevch, base.strided.snanstdevch\n","base.strided.dnanstdevch.ndarray":"\nbase.strided.dnanstdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dnanvariancech, base.strided.dstdevch, base.strided.nanstdevch, base.strided.snanstdevch","base.strided.dnanstdevpn":"\nbase.strided.dnanstdevpn( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevpn( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanstdevpn( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanstdevpn( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dnanstdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.snanstdevpn\n","base.strided.dnanstdevpn.ndarray":"\nbase.strided.dnanstdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.snanstdevpn","base.strided.dnanstdevtk":"\nbase.strided.dnanstdevtk( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevtk( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanstdevtk( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanstdevtk( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dnanstdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.snanstdevtk\n","base.strided.dnanstdevtk.ndarray":"\nbase.strided.dnanstdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.snanstdevtk","base.strided.dnanstdevwd":"\nbase.strided.dnanstdevwd( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevwd( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanstdevwd( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanstdevwd( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dnanstdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.snanstdevwd\n","base.strided.dnanstdevwd.ndarray":"\nbase.strided.dnanstdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.snanstdevwd","base.strided.dnanstdevyc":"\nbase.strided.dnanstdevyc( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass algorithm proposed by\n    Youngs and Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevyc( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanstdevyc( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanstdevyc( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dnanstdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass algorithm proposed by\n    Youngs and Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.snanstdevyc\n","base.strided.dnanstdevyc.ndarray":"\nbase.strided.dnanstdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass algorithm proposed by\n    Youngs and Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.snanstdevyc","base.strided.dnansum":"\nbase.strided.dnansum( N, x, strideX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansum( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansum( 4, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnansum( 4, x1, 2 )\n    -1.0\n\n\nbase.strided.dnansum.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansum.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.dsum, base.strided.snansum, base.strided.gnansum\n","base.strided.dnansum.ndarray":"\nbase.strided.dnansum.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansum.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.dsum, base.strided.snansum, base.strided.gnansum","base.strided.dnansumkbn":"\nbase.strided.dnansumkbn( N, x, strideX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumkbn( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumkbn( 4, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnansumkbn( 4, x1, 2 )\n    -1.0\n\n\nbase.strided.dnansumkbn.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumkbn.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.snansumkbn\n","base.strided.dnansumkbn.ndarray":"\nbase.strided.dnansumkbn.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumkbn.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.snansumkbn","base.strided.dnansumkbn2":"\nbase.strided.dnansumkbn2( N, x, strideX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm.\n\n    The `N` and stride parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumkbn2( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumkbn2( 4, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnansumkbn2( 4, x1, 2 )\n    -1.0\n\n\nbase.strided.dnansumkbn2.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumkbn2.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.snansumkbn2\n","base.strided.dnansumkbn2.ndarray":"\nbase.strided.dnansumkbn2.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumkbn2.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.snansumkbn2","base.strided.dnansumors":"\nbase.strided.dnansumors( N, x, strideX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumors( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumors( 4, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnansumors( 4, x1, 2 )\n    -1.0\n\n\nbase.strided.dnansumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumors.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumpw, base.strided.dsumors, base.strided.gnansumors, base.strided.snansumors\n","base.strided.dnansumors.ndarray":"\nbase.strided.dnansumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumors.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumpw, base.strided.dsumors, base.strided.gnansumors, base.strided.snansumors","base.strided.dnansumpw":"\nbase.strided.dnansumpw( N, x, strideX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumpw( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumpw( 4, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnansumpw( 4, x1, 2 )\n    -1.0\n\n\nbase.strided.dnansumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumpw.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumors, base.strided.dsumpw, base.strided.gnansumpw, base.strided.snansumpw\n","base.strided.dnansumpw.ndarray":"\nbase.strided.dnansumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumpw.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumors, base.strided.dsumpw, base.strided.gnansumpw, base.strided.snansumpw","base.strided.dnanvariance":"\nbase.strided.dnanvariance( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariance( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanvariance( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanvariance( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dnanvariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dvariance, base.strided.nanvariance, base.strided.snanvariance\n","base.strided.dnanvariance.ndarray":"\nbase.strided.dnanvariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dvariance, base.strided.nanvariance, base.strided.snanvariance","base.strided.dnanvariancech":"\nbase.strided.dnanvariancech( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancech( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanvariancech( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanvariancech( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dnanvariancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvariancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancech, base.strided.dnanvariance, base.strided.nanvariancech, base.strided.snanvariancech\n","base.strided.dnanvariancech.ndarray":"\nbase.strided.dnanvariancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvariancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancech, base.strided.dnanvariance, base.strided.nanvariancech, base.strided.snanvariancech","base.strided.dnanvariancepn":"\nbase.strided.dnanvariancepn( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancepn( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanvariancepn( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanvariancepn( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dnanvariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancepn, base.strided.dnanvariance, base.strided.nanvariancepn, base.strided.snanvariancepn\n","base.strided.dnanvariancepn.ndarray":"\nbase.strided.dnanvariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancepn, base.strided.dnanvariance, base.strided.nanvariancepn, base.strided.snanvariancepn","base.strided.dnanvariancetk":"\nbase.strided.dnanvariancetk( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancetk( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanvariancetk( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanvariancetk( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dnanvariancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvariancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancetk, base.strided.dnanvariance, base.strided.nanvariancetk, base.strided.snanvariancetk\n","base.strided.dnanvariancetk.ndarray":"\nbase.strided.dnanvariancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvariancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancetk, base.strided.dnanvariance, base.strided.nanvariancetk, base.strided.snanvariancetk","base.strided.dnanvariancewd":"\nbase.strided.dnanvariancewd( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancewd( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanvariancewd( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanvariancewd( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dnanvariancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using Welford's algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvariancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancewd, base.strided.dnanvariance, base.strided.nanvariancewd, base.strided.snanvariancewd\n","base.strided.dnanvariancewd.ndarray":"\nbase.strided.dnanvariancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using Welford's algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvariancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancewd, base.strided.dnanvariance, base.strided.nanvariancewd, base.strided.snanvariancewd","base.strided.dnanvarianceyc":"\nbase.strided.dnanvarianceyc( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n    Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvarianceyc( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanvarianceyc( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanvarianceyc( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dnanvarianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n    Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvarianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvarianceyc, base.strided.dnanvariance, base.strided.nanvarianceyc, base.strided.snanvarianceyc\n","base.strided.dnanvarianceyc.ndarray":"\nbase.strided.dnanvarianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n    Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvarianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvarianceyc, base.strided.dnanvariance, base.strided.nanvarianceyc, base.strided.snanvarianceyc","base.strided.dnrm2":"\nbase.strided.dnrm2( N, x, stride )\n    Computes the L2-norm of a double-precision floating-point vector.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    nrm2: number\n        The L2-norm.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dnrm2( x.length, x, 1 )\n    3.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dnrm2( 3, x, 2 )\n    3.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnrm2( 3, x1, 2 )\n    3.0\n\n\nbase.strided.dnrm2.ndarray( N, x, stride, offset )\n    Computes the L2-norm of a double-precision floating-point vector using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    nrm2: number\n        The L2-norm.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dnrm2.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dnrm2.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.gnrm2, base.strided.snrm2\n","base.strided.dnrm2.ndarray":"\nbase.strided.dnrm2.ndarray( N, x, stride, offset )\n    Computes the L2-norm of a double-precision floating-point vector using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    nrm2: number\n        The L2-norm.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dnrm2.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dnrm2.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.gnrm2, base.strided.snrm2","base.strided.dramp":"\nbase.strided.dramp( N, x, strideX, y, strideY )\n    Evaluates the ramp function for each element in a double-precision floating-\n    point strided array `x` and assigns the results to elements in a double-\n    precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dramp( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.1, 2.5, 0.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dramp( N, x, 2, y, -1 )\n    <Float64Array>[ 0.0, 1.1, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dramp( N, x1, -2, y1, 1 )\n    <Float64Array>[ 4.0, 2.5 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.5 ]\n\n\nbase.strided.dramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Evaluates the ramp function for each element in a double-precision floating-\n    point strided array `x` and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.1, 2.5, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.5 ]\n\n    See Also\n    --------\n    strided.ramp, base.strided.sramp\n","base.strided.dramp.ndarray":"\nbase.strided.dramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Evaluates the ramp function for each element in a double-precision floating-\n    point strided array `x` and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.1, 2.5, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.5 ]\n\n    See Also\n    --------\n    strided.ramp, base.strided.sramp","base.strided.drange":"\nbase.strided.drange( N, x, strideX )\n    Computes the range of a double-precision floating-point strided array.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.drange( x.length, x, 1 )\n    4.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.drange( 3, x, 2 )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > stride = 2;\n    > base.strided.drange( 3, x1, 2 )\n    4.0\n\n\nbase.strided.drange.ndarray( N, x, strideX, offsetX )\n    Computes the range of a double-precision floating-point strided array using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.drange.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.drange.ndarray( 3, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dmin, base.strided.dnanrange, base.strided.range, base.strided.srange\n","base.strided.drange.ndarray":"\nbase.strided.drange.ndarray( N, x, strideX, offsetX )\n    Computes the range of a double-precision floating-point strided array using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.drange.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.drange.ndarray( 3, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dmin, base.strided.dnanrange, base.strided.range, base.strided.srange","base.strided.drev":"\nbase.strided.drev( N, x, strideX )\n    Reverses a double-precision floating-point strided array in-place.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.drev( x.length, x, 1 )\n    <Float64Array>[ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.drev( 3, x, 2 )\n    <Float64Array>[ 4.0, 1.0, 3.0, -5.0, -2.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.drev( 3, x1, 2 )\n    <Float64Array>[ -6.0, 3.0, -4.0, 5.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n\nbase.strided.drev.ndarray( N, x, strideX, offsetX )\n    Reverses a double-precision floating-point strided array in-place using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.drev.ndarray( x.length, x, 1, 0 )\n    <Float64Array>[ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.drev.ndarray( 3, x, 2, 1 )\n    <Float64Array>[ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.grev, base.strided.srev\n","base.strided.drev.ndarray":"\nbase.strided.drev.ndarray( N, x, strideX, offsetX )\n    Reverses a double-precision floating-point strided array in-place using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.drev.ndarray( x.length, x, 1, 0 )\n    <Float64Array>[ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.drev.ndarray( 3, x, 2, 1 )\n    <Float64Array>[ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.grev, base.strided.srev","base.strided.drsqrt":"\nbase.strided.drsqrt( N, x, strideX, y, strideY )\n    Computes the reciprocal square root for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.drsqrt( x.length, x, 1, y, 1 )\n    <Float64Array>[ Infinity, 0.5, ~0.333, ~0.289 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.drsqrt( N, x, 2, y, -1 )\n    <Float64Array>[ ~0.333, Infinity, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.drsqrt( N, x1, -2, y1, 1 )\n    <Float64Array>[ ~0.289, 0.5 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.drsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the reciprocal square root for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.drsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ Infinity, 0.5, ~0.333, ~0.289 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.drsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n    See Also\n    --------\n    base.strided.dsqrt, strided.rsqrt, base.strided.srsqrt\n","base.strided.drsqrt.ndarray":"\nbase.strided.drsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the reciprocal square root for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.drsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ Infinity, 0.5, ~0.333, ~0.289 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.drsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n    See Also\n    --------\n    base.strided.dsqrt, strided.rsqrt, base.strided.srsqrt","base.strided.dsapxsum":"\nbase.strided.dsapxsum( N, alpha, x, strideX )\n    Adds a scalar constant to each single-precision floating-point strided array\n    element, and computes the sum using extended accumulation and returning\n    an extended precision result.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsapxsum( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dsapxsum( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsapxsum( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.dsapxsum.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each single-precision floating-point strided array\n    element, and computes the sum using pairwise summation with extended\n    accumulation and alternative indexing semantics and returning an extended\n    precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.dssum, base.strided.sapxsum\n","base.strided.dsapxsum.ndarray":"\nbase.strided.dsapxsum.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each single-precision floating-point strided array\n    element, and computes the sum using pairwise summation with extended\n    accumulation and alternative indexing semantics and returning an extended\n    precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.dssum, base.strided.sapxsum","base.strided.dsapxsumpw":"\nbase.strided.dsapxsumpw( N, alpha, x, strideX )\n    Adds a constant to each single-precision floating-point strided array\n    element, and computes the sum using pairwise summation with extended\n    accumulation and returning an extended precision result.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsapxsumpw( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dsapxsumpw( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsapxsumpw( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.dsapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a constant to each single-precision floating-point strided array\n    element, and computes the sum using pairwise summation with extended\n    accumulation and alternative indexing semantics and returning an extended\n    precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumpw, base.strided.dsapxsum, base.strided.dssumpw, base.strided.sapxsumpw\n","base.strided.dsapxsumpw.ndarray":"\nbase.strided.dsapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a constant to each single-precision floating-point strided array\n    element, and computes the sum using pairwise summation with extended\n    accumulation and alternative indexing semantics and returning an extended\n    precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumpw, base.strided.dsapxsum, base.strided.dssumpw, base.strided.sapxsumpw","base.strided.dscal":"\nbase.strided.dscal( N, alpha, x, stride )\n    Multiplies a double-precision floating-point vector `x` by a constant\n    `alpha`.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dscal( x.length, 5.0, x, 1 )\n    <Float64Array>[ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dscal( 3, 5.0, x, 2 )\n    <Float64Array>[ -10.0, 1.0, 15.0, -5.0, 20.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dscal( 3, 5.0, x1, 2 )\n    <Float64Array>[ -10.0, 3.0, -20.0, 5.0, -30.0 ]\n    > x0\n    <Float64Array>[ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n\nbase.strided.dscal.ndarray( N, alpha, x, stride, offset )\n    Multiplies a double-precision floating-point vector `x` by a constant\n    `alpha` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dscal.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float64Array>[ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.dscal.ndarray( 3, 5.0, x, 2, 1 )\n    <Float64Array>[ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n    See Also\n    --------\n    base.strided.daxpy, base.strided.gscal, base.strided.sscal, base.strided.saxpy\n","base.strided.dscal.ndarray":"\nbase.strided.dscal.ndarray( N, alpha, x, stride, offset )\n    Multiplies a double-precision floating-point vector `x` by a constant\n    `alpha` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dscal.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float64Array>[ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.dscal.ndarray( 3, 5.0, x, 2, 1 )\n    <Float64Array>[ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n    See Also\n    --------\n    base.strided.daxpy, base.strided.gscal, base.strided.sscal, base.strided.saxpy","base.strided.dsdot":"\nbase.strided.dsdot( N, x, strideX, y, strideY )\n    Computes the dot product of two single-precision floating-point vectors with\n    extended accumulation and result.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0` the function returns `0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    dot: number\n        Dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var dot = base.strided.dsdot( x.length, x, 1, y, 1 )\n    -5.0\n\n    // Strides:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > dot = base.strided.dsdot( 3, x, 2, y, -1 )\n    9.0\n\n    // Using view offsets:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n    > dot = base.strided.dsdot( 3, x1, -2, y1, 1 )\n    128.0\n\n\nbase.strided.dsdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the dot product of two single-precision floating-point vectors\n    using alternative indexing semantics and with extended accumulation and\n    result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing based on a starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    dot: number\n        Dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var dot = base.strided.dsdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    -5.0\n\n    // Strides:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > dot = base.strided.dsdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n    9.0\n\n    // Using offset indices:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > dot = base.strided.dsdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n    128.0\n\n    References\n    ----------\n    - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n    Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n    Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n    NY, USA: Association for Computing Machinery: 324–25.\n    doi:10.1145/355841.355848.\n\n    See Also\n    --------\n    base.strided.ddot, base.strided.sdot, base.strided.sdsdot\n","base.strided.dsdot.ndarray":"\nbase.strided.dsdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the dot product of two single-precision floating-point vectors\n    using alternative indexing semantics and with extended accumulation and\n    result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing based on a starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    dot: number\n        Dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var dot = base.strided.dsdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    -5.0\n\n    // Strides:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > dot = base.strided.dsdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n    9.0\n\n    // Using offset indices:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > dot = base.strided.dsdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n    128.0\n\n    References\n    ----------\n    - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n    Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n    Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n    NY, USA: Association for Computing Machinery: 324–25.\n    doi:10.1145/355841.355848.\n\n    See Also\n    --------\n    base.strided.ddot, base.strided.sdot, base.strided.sdsdot","base.strided.dsem":"\nbase.strided.dsem( N, correction, x, stride )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsem( x.length, 1, x, 1 )\n    ~1.20185\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsem( N, 1, x, stride )\n    ~1.20185\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsem( N, 1, x1, stride )\n    ~1.20185\n\nbase.strided.dsem.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsem.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsem.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dstdev\n","base.strided.dsem.ndarray":"\nbase.strided.dsem.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsem.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsem.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dstdev","base.strided.dsemch":"\nbase.strided.dsemch( N, correction, x, stride )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemch( x.length, 1, x, 1 )\n    ~1.20185\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsemch( N, 1, x, stride )\n    ~1.20185\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsemch( N, 1, x1, stride )\n    ~1.20185\n\nbase.strided.dsemch.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass trial mean algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemch.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsemch.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dsem, base.strided.dstdevch\n","base.strided.dsemch.ndarray":"\nbase.strided.dsemch.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass trial mean algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemch.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsemch.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dsem, base.strided.dstdevch","base.strided.dsempn":"\nbase.strided.dsempn( N, correction, x, stride )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsempn( x.length, 1, x, 1 )\n    ~1.20185\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsempn( N, 1, x, stride )\n    ~1.20185\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsempn( N, 1, x1, stride )\n    ~1.20185\n\nbase.strided.dsempn.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a two-pass algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsempn.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsempn.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dsem, base.strided.dstdevpn\n","base.strided.dsempn.ndarray":"\nbase.strided.dsempn.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a two-pass algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsempn.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsempn.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dsem, base.strided.dstdevpn","base.strided.dsemtk":"\nbase.strided.dsemtk( N, correction, x, stride )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemtk( x.length, 1, x, 1 )\n    ~1.20185\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsemtk( N, 1, x, stride )\n    ~1.20185\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsemtk( N, 1, x1, stride )\n    ~1.20185\n\nbase.strided.dsemtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass textbook algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemtk.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsemtk.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dsem, base.strided.dstdevtk\n","base.strided.dsemtk.ndarray":"\nbase.strided.dsemtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass textbook algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemtk.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsemtk.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dsem, base.strided.dstdevtk","base.strided.dsemwd":"\nbase.strided.dsemwd( N, correction, x, stride )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemwd( x.length, 1, x, 1 )\n    ~1.20185\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsemwd( N, 1, x, stride )\n    ~1.20185\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsemwd( N, 1, x1, stride )\n    ~1.20185\n\nbase.strided.dsemwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using Welford's algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemwd.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsemwd.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dsem, base.strided.dstdevwd\n","base.strided.dsemwd.ndarray":"\nbase.strided.dsemwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using Welford's algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemwd.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsemwd.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dsem, base.strided.dstdevwd","base.strided.dsemyc":"\nbase.strided.dsemyc( N, correction, x, stride )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass algorithm proposed by Youngs and\n    Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemyc( x.length, 1, x, 1 )\n    ~1.20185\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsemyc( N, 1, x, stride )\n    ~1.20185\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsemyc( N, 1, x1, stride )\n    ~1.20185\n\nbase.strided.dsemyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass algorithm proposed by Youngs and Cramer\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemyc.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsemyc.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dsem, base.strided.dstdevyc\n","base.strided.dsemyc.ndarray":"\nbase.strided.dsemyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass algorithm proposed by Youngs and Cramer\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemyc.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsemyc.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dsem, base.strided.dstdevyc","base.strided.dsmean":"\nbase.strided.dsmean( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using extended accumulation and returning an extended precision\n    result.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmean( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsmean( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsmean( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dsmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using extended accumulation and alternative indexing semantics and\n    returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dsnanmean, base.strided.mean, base.strided.sdsmean, base.strided.smean\n","base.strided.dsmean.ndarray":"\nbase.strided.dsmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using extended accumulation and alternative indexing semantics and\n    returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dsnanmean, base.strided.mean, base.strided.sdsmean, base.strided.smean","base.strided.dsmeanors":"\nbase.strided.dsmeanors( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation with extended accumulation and\n    returning an extended precision result.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanors( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsmeanors( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsmeanors( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dsmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation with extended accumulation and\n    alternative indexing semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanors, base.strided.dsmean, base.strided.dsnanmeanors, base.strided.meanors, base.strided.smeanors\n","base.strided.dsmeanors.ndarray":"\nbase.strided.dsmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation with extended accumulation and\n    alternative indexing semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanors, base.strided.dsmean, base.strided.dsnanmeanors, base.strided.meanors, base.strided.smeanors","base.strided.dsmeanpn":"\nbase.strided.dsmeanpn( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a two-pass error correction algorithm with extended accumulation\n    and returning an extended precision result.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanpn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsmeanpn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsmeanpn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dsmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a two-pass error correction algorithm with extended accumulation\n    and alternative indexing semantics and returning an extended precision\n    result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.dsmean, base.strided.dsnanmeanpn, base.strided.meanpn, base.strided.smeanpn\n","base.strided.dsmeanpn.ndarray":"\nbase.strided.dsmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a two-pass error correction algorithm with extended accumulation\n    and alternative indexing semantics and returning an extended precision\n    result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.dsmean, base.strided.dsnanmeanpn, base.strided.meanpn, base.strided.smeanpn","base.strided.dsmeanpw":"\nbase.strided.dsmeanpw( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using pairwise summation with extended accumulation and returning an\n    extended precision result.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanpw( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsmeanpw( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsmeanpw( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dsmeanpw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using pairwise summation with extended accumulation and alternative\n    indexing semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanpw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsmeanpw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpw, base.strided.dsmean, base.strided.meanpw, base.strided.smeanpw\n","base.strided.dsmeanpw.ndarray":"\nbase.strided.dsmeanpw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using pairwise summation with extended accumulation and alternative\n    indexing semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanpw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsmeanpw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpw, base.strided.dsmean, base.strided.meanpw, base.strided.smeanpw","base.strided.dsmeanwd":"\nbase.strided.dsmeanwd( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using Welford's algorithm with extended accumulation and returning an\n    extended precision result.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanwd( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsmeanwd( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsmeanwd( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dsmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using Welford's algorithm with extended accumulation and alternative\n    indexing semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanwd, base.strided.dsmean, base.strided.dsnanmeanwd, base.strided.meanwd, base.strided.smeanwd\n","base.strided.dsmeanwd.ndarray":"\nbase.strided.dsmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using Welford's algorithm with extended accumulation and alternative\n    indexing semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanwd, base.strided.dsmean, base.strided.dsnanmeanwd, base.strided.meanwd, base.strided.smeanwd","base.strided.dsnanmean":"\nbase.strided.dsnanmean( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values, using extended accumulation, and returning an\n    extended precision result.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmean( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsnanmean( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsnanmean( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dsnanmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using extended accumulation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsnanmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.dsmean, base.strided.nanmean, base.strided.sdsnanmean, base.strided.snanmean\n","base.strided.dsnanmean.ndarray":"\nbase.strided.dsnanmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using extended accumulation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsnanmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.dsmean, base.strided.nanmean, base.strided.sdsnanmean, base.strided.snanmean","base.strided.dsnanmeanors":"\nbase.strided.dsnanmeanors( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values, using ordinary recursive summation with\n    extended accumulation, and returning an extended precision result.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmeanors( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsnanmeanors( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsnanmeanors( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dsnanmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation with\n    extended accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsnanmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanors, base.strided.dsmeanors, base.strided.dsnanmean, base.strided.nanmeanors, base.strided.sdsnanmean, base.strided.snanmeanors\n","base.strided.dsnanmeanors.ndarray":"\nbase.strided.dsnanmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation with\n    extended accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsnanmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanors, base.strided.dsmeanors, base.strided.dsnanmean, base.strided.nanmeanors, base.strided.sdsnanmean, base.strided.snanmeanors","base.strided.dsnanmeanpn":"\nbase.strided.dsnanmeanpn( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values, using a two-pass error correction algorithm\n    with extended accumulation, and returning an extended precision result.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmeanpn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsnanmeanpn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsnanmeanpn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dsnanmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction algorithm\n    with extended accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsnanmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanpn, base.strided.dsmeanpn, base.strided.dsnanmean, base.strided.nanmeanpn, base.strided.sdsnanmean, base.strided.snanmeanpn\n","base.strided.dsnanmeanpn.ndarray":"\nbase.strided.dsnanmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction algorithm\n    with extended accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsnanmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanpn, base.strided.dsmeanpn, base.strided.dsnanmean, base.strided.nanmeanpn, base.strided.sdsnanmean, base.strided.snanmeanpn","base.strided.dsnanmeanwd":"\nbase.strided.dsnanmeanwd( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values, using Welford's algorithm with extended\n    accumulation, and returning an extended precision result.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmeanwd( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsnanmeanwd( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsnanmeanwd( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dsnanmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm with extended\n    accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsnanmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanwd, base.strided.dsmeanwd, base.strided.dsnanmean, base.strided.nanmeanwd, base.strided.sdsnanmean, base.strided.snanmeanwd\n","base.strided.dsnanmeanwd.ndarray":"\nbase.strided.dsnanmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm with extended\n    accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsnanmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanwd, base.strided.dsmeanwd, base.strided.dsnanmean, base.strided.nanmeanwd, base.strided.sdsnanmean, base.strided.snanmeanwd","base.strided.dsnannsumors":"\nbase.strided.dsnannsumors( N, x, strideX, out, strideOut )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using ordinary recursive summation with extended\n    accumulation, and returning an extended precision result.\n\n    The `N` and stride parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns a sum equal to `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dsnannsumors( x.length, x, 1, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dsnannsumors( 4, x, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dsnannsumors( N, x1, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n\nbase.strided.dsnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using ordinary recursive summation with extended\n    accumulation and alternative indexing semantics, and returning an extended\n    precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dsnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dsnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsumors, base.strided.dsnansumors, base.strided.dssumors\n","base.strided.dsnannsumors.ndarray":"\nbase.strided.dsnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using ordinary recursive summation with extended\n    accumulation and alternative indexing semantics, and returning an extended\n    precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dsnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dsnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsumors, base.strided.dsnansumors, base.strided.dssumors","base.strided.dsnansum":"\nbase.strided.dsnansum( N, x, strideX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using extended accumulation, and returning an\n    extended precision result.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnansum( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.dsnansum( 4, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsnansum( 4, x1, 2 )\n    -1.0\n\n\nbase.strided.dsnansum.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using extended accumulation and alternative\n    indexing semantics, and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnansum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsnansum.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnanmean, base.strided.dssum, base.strided.sdsnansum, base.strided.snansum\n","base.strided.dsnansum.ndarray":"\nbase.strided.dsnansum.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using extended accumulation and alternative\n    indexing semantics, and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnansum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsnansum.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnanmean, base.strided.dssum, base.strided.sdsnansum, base.strided.snansum","base.strided.dsnansumors":"\nbase.strided.dsnansumors( N, x, strideX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using ordinary recursive summation with extended\n    accumulation, and returning an extended precision result.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnansumors( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.dsnansumors( 4, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsnansumors( 4, x1, 2 )\n    -1.0\n\n\nbase.strided.dsnansumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation with extended\n    accumulation and alternative indexing semantics, and returning an extended\n    precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnansumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dsnansumors.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnanmeanors, base.strided.dssum, base.strided.dssumors, base.strided.snansumors\n","base.strided.dsnansumors.ndarray":"\nbase.strided.dsnansumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation with extended\n    accumulation and alternative indexing semantics, and returning an extended\n    precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnansumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dsnansumors.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnanmeanors, base.strided.dssum, base.strided.dssumors, base.strided.snansumors","base.strided.dsnansumpw":"\nbase.strided.dsnansumpw( N, x, strideX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using pairwise summation with extended accumulation,\n    and returning an extended precision result.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnansumpw( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.dsnansumpw( 4, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsnansumpw( 4, x1, 2 )\n    -1.0\n\n\nbase.strided.dsnansumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using pairwise summation with extended accumulation\n    and alternative indexing semantics, and returning an extended precision\n    result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnansumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dsnansumpw.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumpw, base.strided.dssum, base.strided.dssumpw, base.strided.snansumpw\n","base.strided.dsnansumpw.ndarray":"\nbase.strided.dsnansumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using pairwise summation with extended accumulation\n    and alternative indexing semantics, and returning an extended precision\n    result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnansumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dsnansumpw.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumpw, base.strided.dssum, base.strided.dssumpw, base.strided.snansumpw","base.strided.dsort2hp":"\nbase.strided.dsort2hp( N, order, x, strideX, y, strideY )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using heapsort.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided arrays are sorted *in-place* (i.e., the input strided\n    arrays are *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2hp( x.length, 1, x, 1, y, 1 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float64Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsort2hp( N, -1, x, 2, y, 2 )\n    <Float64Array>[ 3.0, -2.0, 1.0, -4.0 ]\n    > y\n    <Float64Array>[ 2.0, 1.0, 0.0, 3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dsort2hp( N, 1, x1, 2, y1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.dsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using heapsort and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float64Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssort2hp\n","base.strided.dsort2hp.ndarray":"\nbase.strided.dsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using heapsort and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float64Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssort2hp","base.strided.dsort2ins":"\nbase.strided.dsort2ins( N, order, x, strideX, y, strideY )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using insertion sort.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^2).\n\n    The algorithm is efficient for *small* strided arrays (typically N <= 20)\n    and is particularly efficient for sorting strided arrays which are already\n    substantially sorted.\n\n    The algorithm is *stable*, meaning that the algorithm does *not* change the\n    order of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided arrays are sorted *in-place* (i.e., the input strided\n    arrays is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2ins( x.length, 1, x, 1, y, 1 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float64Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2ins( 2, -1, x, 2, y, 2 )\n    <Float64Array>[ 3.0, -2.0, 1.0, -4.0 ]\n    > y\n    <Float64Array>[ 2.0, 1.0, 0.0, 3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsort2ins( 2, 1, x1, 2, y1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.dsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using insertion sort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float64Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsortins, base.strided.gsort2ins, base.strided.ssort2ins\n","base.strided.dsort2ins.ndarray":"\nbase.strided.dsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using insertion sort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float64Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsortins, base.strided.gsort2ins, base.strided.ssort2ins","base.strided.dsort2sh":"\nbase.strided.dsort2sh( N, order, x, strideX, y, strideY )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using Shellsort.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^(4/3)).\n\n    The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided arrays are sorted *in-place* (i.e., the input strided\n    arrays are *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2sh( x.length, 1, x, 1, y, 1 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float64Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsort2sh( N, -1, x, 2, y, 2 )\n    <Float64Array>[ 3.0, -2.0, 1.0, -4.0 ]\n    > y\n    <Float64Array>[ 2.0, 1.0, 0.0, 3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dsort2sh( N, 1, x1, 2, y1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.dsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using Shellsort and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float64Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssort2sh\n","base.strided.dsort2sh.ndarray":"\nbase.strided.dsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using Shellsort and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float64Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssort2sh","base.strided.dsorthp":"\nbase.strided.dsorthp( N, order, x, stride )\n    Sorts a double-precision floating-point strided array using heapsort.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided array is sorted *in-place* (i.e., the input strided array\n    is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.dsorthp( x.length, 1, x, 1 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsorthp( N, -1, x, 2 )\n    <Float64Array>[ 3.0, -2.0, 1.0, -4.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dsorthp( N, 1, x1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.dsorthp.ndarray( N, order, x, stride, offset )\n    Sorts a double-precision floating-point strided array using heapsort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.dsorthp.ndarray( x.length, 1, x, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsorthp.ndarray( N, 1, x, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssorthp\n","base.strided.dsorthp.ndarray":"\nbase.strided.dsorthp.ndarray( N, order, x, stride, offset )\n    Sorts a double-precision floating-point strided array using heapsort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.dsorthp.ndarray( x.length, 1, x, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsorthp.ndarray( N, 1, x, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssorthp","base.strided.dsortins":"\nbase.strided.dsortins( N, order, x, stride )\n    Sorts a double-precision floating-point strided array using insertion sort.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^2).\n\n    The algorithm is efficient for *small* strided arrays (typically N <= 20)\n    and is particularly efficient for sorting strided arrays which are already\n    substantially sorted.\n\n    The algorithm is *stable*, meaning that the algorithm does *not* change the\n    order of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided array is sorted *in-place* (i.e., the input strided array\n    is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.dsortins( x.length, 1, x, 1 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsortins( N, -1, x, 2 )\n    <Float64Array>[ 3.0, -2.0, 1.0, -4.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dsortins( N, 1, x1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.dsortins.ndarray( N, order, x, stride, offset )\n    Sorts a double-precision floating-point strided array using insertion sort\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.dsortins.ndarray( x.length, 1, x, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsortins.ndarray( N, 1, x, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2ins, base.strided.gsortins, base.strided.ssortins\n","base.strided.dsortins.ndarray":"\nbase.strided.dsortins.ndarray( N, order, x, stride, offset )\n    Sorts a double-precision floating-point strided array using insertion sort\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.dsortins.ndarray( x.length, 1, x, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsortins.ndarray( N, 1, x, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2ins, base.strided.gsortins, base.strided.ssortins","base.strided.dsortsh":"\nbase.strided.dsortsh( N, order, x, stride )\n    Sorts a double-precision floating-point strided array using Shellsort.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^(4/3)).\n\n    The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided array is sorted *in-place* (i.e., the input strided array\n    is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.dsortsh( x.length, 1, x, 1 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsortsh( N, -1, x, 2 )\n    <Float64Array>[ 3.0, -2.0, 1.0, -4.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dsortsh( N, 1, x1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.dsortsh.ndarray( N, order, x, stride, offset )\n    Sorts a double-precision floating-point strided array using Shellsort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.dsortsh.ndarray( x.length, 1, x, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsortsh.ndarray( N, 1, x, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssortsh\n","base.strided.dsortsh.ndarray":"\nbase.strided.dsortsh.ndarray( N, order, x, stride, offset )\n    Sorts a double-precision floating-point strided array using Shellsort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.dsortsh.ndarray( x.length, 1, x, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsortsh.ndarray( N, 1, x, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssortsh","base.strided.dsqrt":"\nbase.strided.dsqrt( N, x, strideX, y, strideY )\n    Computes the principal square root for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dsqrt( x.length, x, 1, y, 1 )\n    <Float64Array>[ 0.0, 2.0, 3.0, ~3.464 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dsqrt( N, x, 2, y, -1 )\n    <Float64Array>[ 3.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dsqrt( N, x1, -2, y1, 1 )\n    <Float64Array>[ ~3.464, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.dsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the principal square root for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, 2.0, 3.0, ~3.464 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dcbrt, base.strided.drsqrt, strided.sqrt, base.strided.ssqrt\n","base.strided.dsqrt.ndarray":"\nbase.strided.dsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the principal square root for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, 2.0, 3.0, ~3.464 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dcbrt, base.strided.drsqrt, strided.sqrt, base.strided.ssqrt","base.strided.dssum":"\nbase.strided.dssum( N, x, strideX )\n    Computes the sum of single-precision floating-point strided array elements\n    using extended accumulation and returning an extended precision result.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dssum( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dssum( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dssum( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.dssum.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements\n    using extended accumulation and alternative indexing semantics and returning\n    an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dssum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dssum.ndarray(3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnansum, base.strided.sdssum, base.strided.ssum, base.strided.dsmean\n","base.strided.dssum.ndarray":"\nbase.strided.dssum.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements\n    using extended accumulation and alternative indexing semantics and returning\n    an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dssum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dssum.ndarray(3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnansum, base.strided.sdssum, base.strided.ssum, base.strided.dsmean","base.strided.dssumors":"\nbase.strided.dssumors( N, x, strideX )\n    Computes the sum of single-precision floating-point strided array elements\n    using ordinary recursive summation with extended accumulation and returning\n    an extended precision result.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dssumors( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dssumors( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dssumors( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.dssumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements\n    using ordinary recursive summation with extended accumulation and\n    alternative indexing semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dssumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dssumors.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnansumors, base.strided.dssum, base.strided.dsumors, base.strided.ssumors\n","base.strided.dssumors.ndarray":"\nbase.strided.dssumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements\n    using ordinary recursive summation with extended accumulation and\n    alternative indexing semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dssumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dssumors.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnansumors, base.strided.dssum, base.strided.dsumors, base.strided.ssumors","base.strided.dssumpw":"\nbase.strided.dssumpw( N, x, strideX )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation with extended accumulation and returning an\n    extended precision result.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dssumpw( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dssumpw( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dssumpw( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.dssumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation with extended accumulation and alternative indexing\n    semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dssumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dssumpw.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnansumpw, base.strided.dssum, base.strided.dsumpw, base.strided.ssumpw\n","base.strided.dssumpw.ndarray":"\nbase.strided.dssumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation with extended accumulation and alternative indexing\n    semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dssumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dssumpw.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnansumpw, base.strided.dssum, base.strided.dsumpw, base.strided.ssumpw","base.strided.dstdev":"\nbase.strided.dstdev( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdev( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dstdev( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dstdev( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dstdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dvariance, base.strided.sstdev, base.strided.stdev\n","base.strided.dstdev.ndarray":"\nbase.strided.dstdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dvariance, base.strided.sstdev, base.strided.stdev","base.strided.dstdevch":"\nbase.strided.dstdevch( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevch( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dstdevch( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dstdevch( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dstdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevch, base.strided.dstdev, base.strided.dvariancech, base.strided.sstdevch, base.strided.stdevch\n","base.strided.dstdevch.ndarray":"\nbase.strided.dstdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevch, base.strided.dstdev, base.strided.dvariancech, base.strided.sstdevch, base.strided.stdevch","base.strided.dstdevpn":"\nbase.strided.dstdevpn( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevpn( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dstdevpn( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dstdevpn( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dstdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevpn, base.strided.dstdev, base.strided.dvariancepn, base.strided.sstdevpn, base.strided.stdevpn\n","base.strided.dstdevpn.ndarray":"\nbase.strided.dstdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevpn, base.strided.dstdev, base.strided.dvariancepn, base.strided.sstdevpn, base.strided.stdevpn","base.strided.dstdevtk":"\nbase.strided.dstdevtk( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevtk( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dstdevtk( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dstdevtk( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dstdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass textbook algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevtk, base.strided.dstdev, base.strided.dvariancetk, base.strided.sstdevtk, base.strided.stdevtk\n","base.strided.dstdevtk.ndarray":"\nbase.strided.dstdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass textbook algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevtk, base.strided.dstdev, base.strided.dvariancetk, base.strided.sstdevtk, base.strided.stdevtk","base.strided.dstdevwd":"\nbase.strided.dstdevwd( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevwd( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dstdevwd( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dstdevwd( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dstdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevwd, base.strided.dstdev, base.strided.dvariancewd, base.strided.sstdevwd, base.strided.stdevwd\n","base.strided.dstdevwd.ndarray":"\nbase.strided.dstdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevwd, base.strided.dstdev, base.strided.dvariancewd, base.strided.sstdevwd, base.strided.stdevwd","base.strided.dstdevyc":"\nbase.strided.dstdevyc( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevyc( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dstdevyc( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dstdevyc( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dstdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevyc, base.strided.dstdev, base.strided.dvarianceyc, base.strided.sstdevyc, base.strided.stdevyc\n","base.strided.dstdevyc.ndarray":"\nbase.strided.dstdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevyc, base.strided.dstdev, base.strided.dvarianceyc, base.strided.sstdevyc, base.strided.stdevyc","base.strided.dsum":"\nbase.strided.dsum( N, x, strideX )\n    Computes the sum of double-precision floating-point strided array elements.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsum( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dsum( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsum( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.dsum.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsum.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.dmean, base.strided.dnansum, base.strided.ssum, base.strided.gsum\n","base.strided.dsum.ndarray":"\nbase.strided.dsum.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsum.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.dmean, base.strided.dnansum, base.strided.ssum, base.strided.gsum","base.strided.dsumkbn":"\nbase.strided.dsumkbn( N, x, strideX )\n    Computes the sum of double-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumkbn( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dsumkbn( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsumkbn( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.dsumkbn.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsumkbn.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn, base.strided.ssumkbn\n","base.strided.dsumkbn.ndarray":"\nbase.strided.dsumkbn.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsumkbn.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn, base.strided.ssumkbn","base.strided.dsumkbn2":"\nbase.strided.dsumkbn2( N, x, strideX )\n    Computes the sum of double-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumkbn2( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dsumkbn2( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsumkbn2( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.dsumkbn2.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsumkbn2.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn2, base.strided.dsum, base.strided.dsumkbn, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn2, base.strided.ssumkbn2\n","base.strided.dsumkbn2.ndarray":"\nbase.strided.dsumkbn2.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsumkbn2.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn2, base.strided.dsum, base.strided.dsumkbn, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn2, base.strided.ssumkbn2","base.strided.dsumors":"\nbase.strided.dsumors( N, x, stride )\n    Computes the sum of double-precision floating-point strided array elements\n    using ordinary recursive summation.\n\n    The `N` and `stride` parameters determine which elements in \n    the strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumors( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dsumors( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsumors( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.dsumors.ndarray( N, x, stride, offset )\n    Computes the sum of double-precision floating-point strided array elements\n    using ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsumors.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumors, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumpw, base.strided.gsumors, base.strided.ssumors\n","base.strided.dsumors.ndarray":"\nbase.strided.dsumors.ndarray( N, x, stride, offset )\n    Computes the sum of double-precision floating-point strided array elements\n    using ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsumors.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumors, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumpw, base.strided.gsumors, base.strided.ssumors","base.strided.dsumpw":"\nbase.strided.dsumpw( N, x, stride )\n    Computes the sum of double-precision floating-point strided array elements\n    using pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumpw( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dsumpw( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsumpw( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.dsumpw.ndarray( N, x, stride, offset )\n    Computes the sum of double-precision floating-point strided array elements\n    using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsumpw.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumpw, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.gsumpw, base.strided.ssumpw\n","base.strided.dsumpw.ndarray":"\nbase.strided.dsumpw.ndarray( N, x, stride, offset )\n    Computes the sum of double-precision floating-point strided array elements\n    using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsumpw.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumpw, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.gsumpw, base.strided.ssumpw","base.strided.dsvariance":"\nbase.strided.dsvariance( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    using extended accumulation and returning an extended precision result.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsvariance( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsvariance( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsvariance( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dsvariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using extended accumulation and alternative indexing semantics and\n    returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsvariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsvariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariance, base.strided.variance, base.strided.svariance\n","base.strided.dsvariance.ndarray":"\nbase.strided.dsvariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using extended accumulation and alternative indexing semantics and\n    returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsvariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsvariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariance, base.strided.variance, base.strided.svariance","base.strided.dsvariancepn":"\nbase.strided.dsvariancepn( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    using a two-pass algorithm with extended accumulation and returning an\n    extended precision result.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsvariancepn( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsvariancepn( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsvariancepn( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dsvariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using a two-pass algorithm with extended accumulation and alternative\n    indexing semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsvariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsvariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancepn, base.strided.dsvariance, base.strided.variancepn, base.strided.svariancepn\n","base.strided.dsvariancepn.ndarray":"\nbase.strided.dsvariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using a two-pass algorithm with extended accumulation and alternative\n    indexing semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsvariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsvariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancepn, base.strided.dsvariance, base.strided.variancepn, base.strided.svariancepn","base.strided.dswap":"\nbase.strided.dswap( N, x, strideX, y, strideY )\n    Interchanges two double-precision floating-point vectors.\n\n    The `N` and stride parameters determine how values from `x` are swapped\n    with values from `y`.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the vectors are unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Second input array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.dswap( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.dswap( 3, x, -2, y, 1 )\n    <Float64Array>[ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n    // Using typed array views:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dswap( 3, x1, -2, y1, 1 )\n    <Float64Array>[ 6.0, 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.dswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Interchanges two double-precision floating-point vectors using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Second input array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.dswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.dswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dcopy, base.strided.gswap, base.strided.sswap, dswap\n","base.strided.dswap.ndarray":"\nbase.strided.dswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Interchanges two double-precision floating-point vectors using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Second input array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.dswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.dswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dcopy, base.strided.gswap, base.strided.sswap, dswap","base.strided.dtrunc":"\nbase.strided.dtrunc( N, x, strideX, y, strideY )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward zero and assigns the results to elements in a double-precision\n    floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dtrunc( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.0, 2.0, -3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dtrunc( N, x, 2, y, -1 )\n    <Float64Array>[ -3.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dtrunc( N, x1, -2, y1, 1 )\n    <Float64Array>[ 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dtrunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward zero and assigns the results to elements in a double-precision\n    floating-point strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dtrunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dtrunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dceil, base.strided.dfloor, strided.trunc, base.strided.strunc\n","base.strided.dtrunc.ndarray":"\nbase.strided.dtrunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward zero and assigns the results to elements in a double-precision\n    floating-point strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dtrunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dtrunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dceil, base.strided.dfloor, strided.trunc, base.strided.strunc","base.strided.dtypeEnum2Str":"\nbase.strided.dtypeEnum2Str( dtype )\n    Returns the data type string associated with a strided array data type\n    enumeration constant.\n\n    Parameters\n    ----------\n    dtype: integer\n        Data type enumeration constant.\n\n    Returns\n    -------\n    out: string|null\n        Data type string.\n\n    Examples\n    --------\n    > var out = base.strided.dtypeEnum2Str( base.strided.dtypeStr2Enum( 'float64' ) )\n    'float64'\n\n    See Also\n    --------\n    base.strided.dtypeStr2Enum\n","base.strided.dtypeResolveEnum":"\nbase.strided.dtypeResolveEnum( dtype )\n    Returns the enumeration constant associated with a supported strided array\n    data type value.\n\n    Downstream consumers of this function should *not* rely on specific integer\n    values (e.g., `INT8 == 0`). Instead, the function should be used in an\n    opaque manner.\n\n    Parameters\n    ----------\n    dtype: any\n        Data type value.\n\n    Returns\n    -------\n    out: integer|null\n        Enumeration constant.\n\n    Examples\n    --------\n    > var out = base.strided.dtypeResolveEnum( 'float64' )\n    <number>\n    > out = base.strided.dtypeResolveEnum( base.strided.dtypeStr2Enum( 'float64' ) )\n    <number>\n\n    See Also\n    --------\n    base.strided.dtypeResolveStr\n","base.strided.dtypeResolveStr":"\nbase.strided.dtypeResolveStr( dtype )\n    Returns the data type string associated with a supported data type value.\n\n    Parameters\n    ----------\n    dtype: any\n        Data type value.\n\n    Returns\n    -------\n    out: string|null\n        Data type string.\n\n    Examples\n    --------\n    > var out = base.strided.dtypeResolveStr( 'float64' )\n    'float64'\n    > out = base.strided.dtypeResolveStr( base.strided.dtypeStr2Enum( 'float64' ) )\n    'float64'\n\n    See Also\n    --------\n    base.strided.dtypeResolveEnum\n","base.strided.dtypeStr2Enum":"\nbase.strided.dtypeStr2Enum( dtype )\n    Returns the enumeration constant associated with a strided array data type\n    string.\n\n    Downstream consumers of this function should *not* rely on specific integer\n    values (e.g., `INT8 == 0`). Instead, the function should be used in an\n    opaque manner.\n\n    Parameters\n    ----------\n    dtype: string\n        Data type string.\n\n    Returns\n    -------\n    out: integer|null\n        Enumeration constant.\n\n    Examples\n    --------\n    > var out = base.strided.dtypeStr2Enum( 'float64' )\n    <number>\n\n    See Also\n    --------\n    base.strided.dtypeEnum2Str\n","base.strided.dvariance":"\nbase.strided.dvariance( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariance( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dvariance( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dvariance( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dvariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariance, base.strided.dstdev, base.strided.dvarm, base.strided.svariance, base.strided.variance\n","base.strided.dvariance.ndarray":"\nbase.strided.dvariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariance, base.strided.dstdev, base.strided.dvarm, base.strided.svariance, base.strided.variance","base.strided.dvariancech":"\nbase.strided.dvariancech( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancech( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dvariancech( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dvariancech( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dvariancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass trial mean algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvariancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancech, base.strided.dstdevch, base.strided.dvariance, base.strided.svariancech, base.strided.variancech\n","base.strided.dvariancech.ndarray":"\nbase.strided.dvariancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass trial mean algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvariancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancech, base.strided.dstdevch, base.strided.dvariance, base.strided.svariancech, base.strided.variancech","base.strided.dvariancepn":"\nbase.strided.dvariancepn( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancepn( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dvariancepn( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dvariancepn( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dvariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.dvariance, base.strided.svariancepn, base.strided.variancepn\n","base.strided.dvariancepn.ndarray":"\nbase.strided.dvariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.dvariance, base.strided.svariancepn, base.strided.variancepn","base.strided.dvariancetk":"\nbase.strided.dvariancetk( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancetk( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dvariancetk( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dvariancetk( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dvariancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass textbook algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvariancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.dvariance, base.strided.svariancetk, base.strided.variancetk\n","base.strided.dvariancetk.ndarray":"\nbase.strided.dvariancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass textbook algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvariancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.dvariance, base.strided.svariancetk, base.strided.variancetk","base.strided.dvariancewd":"\nbase.strided.dvariancewd( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancewd( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dvariancewd( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dvariancewd( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dvariancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvariancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.dvariance, base.strided.svariancewd, base.strided.variancewd\n","base.strided.dvariancewd.ndarray":"\nbase.strided.dvariancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvariancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.dvariance, base.strided.svariancewd, base.strided.variancewd","base.strided.dvarianceyc":"\nbase.strided.dvarianceyc( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass algorithm proposed by Youngs and Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarianceyc( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dvarianceyc( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dvarianceyc( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dvarianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass algorithm proposed by Youngs and Cramer and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvarianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.dvariance, base.strided.svarianceyc, base.strided.varianceyc\n","base.strided.dvarianceyc.ndarray":"\nbase.strided.dvarianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass algorithm proposed by Youngs and Cramer and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvarianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.dvariance, base.strided.svarianceyc, base.strided.varianceyc","base.strided.dvarm":"\nbase.strided.dvarm( N, mean, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mean: number\n        Mean.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarm( x.length, 1.0/3.0, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvarm( N, 1.0/3.0, 1, x, 2 )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dvarm( N, 1.0/3.0, 1, x1, 2 )\n    ~4.3333\n\nbase.strided.dvarm.ndarray( N, mean, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mean: number\n        Mean.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarm.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvarm.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariance\n","base.strided.dvarm.ndarray":"\nbase.strided.dvarm.ndarray( N, mean, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mean: number\n        Mean.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarm.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvarm.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariance","base.strided.dvarmpn":"\nbase.strided.dvarmpn( N, mean, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using Neely's correction algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mean: number\n        Mean.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarmpn( x.length, 1.0/3.0, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvarmpn( N, 1.0/3.0, 1, x, 2 )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dvarmpn( N, 1.0/3.0, 1, x1, 2 )\n    ~4.3333\n\nbase.strided.dvarmpn.ndarray( N, mean, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using Neely's correction algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mean: number\n        Mean.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarmpn.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvarmpn.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvarm\n","base.strided.dvarmpn.ndarray":"\nbase.strided.dvarmpn.ndarray( N, mean, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using Neely's correction algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mean: number\n        Mean.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarmpn.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvarmpn.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvarm","base.strided.dvarmtk":"\nbase.strided.dvarmtk( N, mean, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using a one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mean: number\n        Mean.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarmtk( x.length, 1.0/3.0, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvarmtk( N, 1.0/3.0, 1, x, 2 )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dvarmtk( N, 1.0/3.0, 1, x1, 2 )\n    ~4.3333\n\nbase.strided.dvarmtk.ndarray( N, mean, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mean: number\n        Mean.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarmtk.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvarmtk.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvarm\n","base.strided.dvarmtk.ndarray":"\nbase.strided.dvarmtk.ndarray( N, mean, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mean: number\n        Mean.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarmtk.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvarmtk.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvarm","base.strided.gapx":"\nbase.strided.gapx( N, alpha, x, stride )\n    Adds a constant to each element in a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > var alpha = 5.0;\n    > base.strided.gapx( x.length, alpha, x, 1 )\n    [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > alpha = 5.0;\n    > var stride = 2;\n    > base.strided.gapx( N, alpha, x, stride )\n    [ 3.0, 1.0, 8.0, -5.0, 9.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > alpha = 5.0;\n    > stride = 2;\n    > base.strided.gapx( N, alpha, x1, stride )\n    <Float64Array>[ 3.0, 3.0, 1.0, 5.0, -1.0 ]\n    > x0\n    <Float64Array>[ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\nbase.strided.gapx.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each element in a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > var alpha = 5.0;\n    > base.strided.gapx.ndarray( x.length, alpha, x, 1, 0 )\n    [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > alpha = 5.0;\n    > var stride = 2;\n    > base.strided.gapx.ndarray( N, alpha, x, stride, 1 )\n    [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dapx, base.strided.sapx\n","base.strided.gapx.ndarray":"\nbase.strided.gapx.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each element in a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > var alpha = 5.0;\n    > base.strided.gapx.ndarray( x.length, alpha, x, 1, 0 )\n    [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > alpha = 5.0;\n    > var stride = 2;\n    > base.strided.gapx.ndarray( N, alpha, x, stride, 1 )\n    [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dapx, base.strided.sapx","base.strided.gapxsum":"\nbase.strided.gapxsum( N, alpha, x, stride )\n    Adds a constant to each strided array element and computes the sum.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsum( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gapxsum( N, 5.0, x, stride )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gapxsum( N, 5.0, x1, stride )\n    14.0\n\nbase.strided.gapxsum.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each strided array element and computes the sum using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gapxsum.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.gapxsumpw, base.strided.gsum, base.strided.sapxsum\n","base.strided.gapxsum.ndarray":"\nbase.strided.gapxsum.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each strided array element and computes the sum using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gapxsum.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.gapxsumpw, base.strided.gsum, base.strided.sapxsum","base.strided.gapxsumkbn":"\nbase.strided.gapxsumkbn( N, alpha, x, strideX )\n    Adds a scalar constant to each strided array element and computes the sum\n    using an improved Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumkbn( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and stride parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > base.strided.gapxsumkbn( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.gapxsumkbn( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.gapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each strided array element and computes the sum\n    using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > base.strided.gapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumkbn, base.strided.gapxsum, base.strided.gsumkbn, base.strided.sapxsumkbn\n","base.strided.gapxsumkbn.ndarray":"\nbase.strided.gapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each strided array element and computes the sum\n    using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > base.strided.gapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumkbn, base.strided.gapxsum, base.strided.gsumkbn, base.strided.sapxsumkbn","base.strided.gapxsumkbn2":"\nbase.strided.gapxsumkbn2( N, alpha, x, stride )\n    Adds a constant to each strided array element and computes the sum using a\n    second-order iterative Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumkbn2( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gapxsumkbn2( N, 5.0, x, stride )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gapxsumkbn2( N, 5.0, x1, stride )\n    14.0\n\nbase.strided.gapxsumkbn2.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each strided array element and computes the sum using a\n    second-order iterative Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gapxsumkbn2.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumkbn2, base.strided.gapxsum, base.strided.gsumkbn2, base.strided.sapxsumkbn2\n","base.strided.gapxsumkbn2.ndarray":"\nbase.strided.gapxsumkbn2.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each strided array element and computes the sum using a\n    second-order iterative Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gapxsumkbn2.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumkbn2, base.strided.gapxsum, base.strided.gsumkbn2, base.strided.sapxsumkbn2","base.strided.gapxsumors":"\nbase.strided.gapxsumors( N, alpha, x, stride )\n    Adds a constant to each strided array element and computes the sum using\n    ordinary recursive summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumors( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gapxsumors( N, 5.0, x, stride )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gapxsumors( N, 5.0, x1, stride )\n    14.0\n\nbase.strided.gapxsumors.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each strided array element and computes the sum using\n    ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gapxsumors.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumors, base.strided.gapxsum, base.strided.gsumors, base.strided.sapxsumors\n","base.strided.gapxsumors.ndarray":"\nbase.strided.gapxsumors.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each strided array element and computes the sum using\n    ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gapxsumors.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumors, base.strided.gapxsum, base.strided.gsumors, base.strided.sapxsumors","base.strided.gapxsumpw":"\nbase.strided.gapxsumpw( N, alpha, x, stride )\n    Adds a constant to each strided array element and computes the sum using\n    pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumpw( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gapxsumpw( N, 5.0, x, stride )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gapxsumpw( N, 5.0, x1, stride )\n    14.0\n\nbase.strided.gapxsumpw.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each strided array element and computes the sum using\n    pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumpw, base.strided.gapxsum, base.strided.gsumpw, base.strided.sapxsumpw\n","base.strided.gapxsumpw.ndarray":"\nbase.strided.gapxsumpw.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each strided array element and computes the sum using\n    pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumpw, base.strided.gapxsum, base.strided.gsumpw, base.strided.sapxsumpw","base.strided.gasum":"\nbase.strided.gasum( N, x, stride )\n    Computes the sum of the absolute values.\n\n    The sum of absolute values corresponds to the *L1* norm.\n\n    The `N` and `stride` parameters determine which elements in `x` are used to\n    compute the sum.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` or `stride` is less than or equal to `0`, the function returns `0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    sum: number\n        Sum of absolute values.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n    > var s = base.strided.gasum( x.length, x, 1 )\n    19.0\n\n    // Sum every other value:\n    > s = base.strided.gasum( 3, x, 2 )\n    10.0\n\n    // Use view offset; e.g., starting at 2nd element:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > s = base.strided.gasum( 3, x1, 2 )\n    12.0\n\n\nbase.strided.gasum.ndarray( N, x, stride, offset )\n    Computes the sum of absolute values using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    sum: number\n        Sum of absolute values.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n    > var s = base.strided.gasum.ndarray( x.length, x, 1, 0 )\n    19.0\n\n    // Sum the last three elements:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > s = base.strided.gasum.ndarray( 3, x, -1, x.length-1 )\n    15.0\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.sasum\n","base.strided.gasum.ndarray":"\nbase.strided.gasum.ndarray( N, x, stride, offset )\n    Computes the sum of absolute values using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    sum: number\n        Sum of absolute values.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n    > var s = base.strided.gasum.ndarray( x.length, x, 1, 0 )\n    19.0\n\n    // Sum the last three elements:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > s = base.strided.gasum.ndarray( 3, x, -1, x.length-1 )\n    15.0\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.sasum","base.strided.gasumpw":"\nbase.strided.gasumpw( N, x, stride )\n    Computes the sum of absolute values (L1 norm) of strided array elements\n    using pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.gasumpw( x.length, x, 1 )\n    5.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gasumpw( N, x, stride )\n    5.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gasumpw( N, x1, stride )\n    5.0\n\nbase.strided.gasumpw.ndarray( N, x, stride, offset )\n    Computes the sum of absolute values (L1 norm) of strided array elements\n    using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.gasumpw.ndarray( x.length, x, 1, 0 )\n    5.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gasumpw.ndarray( N, x, 2, 1 )\n    5.0\n\n    See Also\n    --------\n    base.strided.gasum, base.strided.dasumpw, base.strided.gsumpw, base.strided.sasumpw\n","base.strided.gasumpw.ndarray":"\nbase.strided.gasumpw.ndarray( N, x, stride, offset )\n    Computes the sum of absolute values (L1 norm) of strided array elements\n    using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.gasumpw.ndarray( x.length, x, 1, 0 )\n    5.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gasumpw.ndarray( N, x, 2, 1 )\n    5.0\n\n    See Also\n    --------\n    base.strided.gasum, base.strided.dasumpw, base.strided.gsumpw, base.strided.sasumpw","base.strided.gaxpy":"\nbase.strided.gaxpy( N, alpha, x, strideX, y, strideY )\n    Multiplies `x` by a constant `alpha` and adds the result to `y`.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n    > base.strided.gaxpy( x.length, 5.0, x, 1, y, 1 )\n    [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n    // Using `N` and stride parameters:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n    > base.strided.gaxpy( 3, 5.0, x, 2, y, -1 )\n    [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.gaxpy( 3, 5.0, x1, -2, y1, 1 )\n    <Float64Array>[ 40.0, 31.0, 22.0 ]\n    > y0\n    <Float64Array>[ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.strided.gaxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n    Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n    > base.strided.gaxpy.ndarray( x.length, 5.0, x, 1, 0, y, 1, 0 )\n    [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n    > base.strided.gaxpy.ndarray( 3, 5.0, x, 2, 1, y, -1, y.length-1 )\n    [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n    See Also\n    --------\n    base.strided.daxpy, base.strided.saxpy\n","base.strided.gaxpy.ndarray":"\nbase.strided.gaxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n    Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n    > base.strided.gaxpy.ndarray( x.length, 5.0, x, 1, 0, y, 1, 0 )\n    [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n    > base.strided.gaxpy.ndarray( 3, 5.0, x, 2, 1, y, -1, y.length-1 )\n    [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n    See Also\n    --------\n    base.strided.daxpy, base.strided.saxpy","base.strided.gcopy":"\nbase.strided.gcopy( N, x, strideX, y, strideY )\n    Copies values from `x` into `y`.\n\n    The `N` and stride parameters determine how values from `x` are copied into\n    `y`.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: ArrayLikeObject\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n    > base.strided.gcopy( x.length, x, 1, y, 1 )\n    [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n    > base.strided.gcopy( 3, x, -2, y, 1 )\n    [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n    // Using typed array views:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.gcopy( 3, x1, -2, y1, 1 )\n    <Float64Array>[ 6.0, 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.gcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Copies values from `x` into `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: ArrayLikeObject\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n    > base.strided.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n    > base.strided.gcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dcopy, base.strided.scopy\n","base.strided.gcopy.ndarray":"\nbase.strided.gcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Copies values from `x` into `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: ArrayLikeObject\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n    > base.strided.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n    > base.strided.gcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dcopy, base.strided.scopy","base.strided.gcusum":"\nbase.strided.gcusum( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of strided array elements.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusum( x.length, 0.0, x, 1, y, 1 )\n    [ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusum( N, 0.0, x, 2, y, 2 )\n    [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gcusum( N, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.gcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusum.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusumpw, base.strided.scusum\n","base.strided.gcusum.ndarray":"\nbase.strided.gcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusum.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusumpw, base.strided.scusum","base.strided.gcusumkbn":"\nbase.strided.gcusumkbn( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of strided array elements using an improved\n    Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Stride length for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumkbn( x.length, 0.0, x, 1, y, 1 )\n    [ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and stride parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumkbn( 3, 0.0, x, 2, y, 2 )\n    [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.gcusumkbn( 3, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.gcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using an improved\n    Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Stride length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumkbn, base.strided.gcusum, base.strided.gcusumkbn2, base.strided.scusumkbn\n","base.strided.gcusumkbn.ndarray":"\nbase.strided.gcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using an improved\n    Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Stride length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumkbn, base.strided.gcusum, base.strided.gcusumkbn2, base.strided.scusumkbn","base.strided.gcusumkbn2":"\nbase.strided.gcusumkbn2( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of strided array elements using a second-order\n    iterative Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumkbn2( x.length, 0.0, x, 1, y, 1 )\n    [ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumkbn2( N, 0.0, x, 2, y, 2 )\n    [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gcusumkbn2( N, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.gcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using a second-order\n    iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumkbn2.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumkbn2, base.strided.gcusum, base.strided.gcusumkbn, base.strided.scusumkbn2\n","base.strided.gcusumkbn2.ndarray":"\nbase.strided.gcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using a second-order\n    iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumkbn2.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumkbn2, base.strided.gcusum, base.strided.gcusumkbn, base.strided.scusumkbn2","base.strided.gcusumors":"\nbase.strided.gcusumors( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of strided array elements using ordinary\n    recursive summation.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumors( x.length, 0.0, x, 1, y, 1 )\n    [ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumors( N, 0.0, x, 2, y, 2 )\n    [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gcusumors( N, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.gcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using ordinary\n    recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumors.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumors, base.strided.gcusum, base.strided.gcusumpw, base.strided.scusumors\n","base.strided.gcusumors.ndarray":"\nbase.strided.gcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using ordinary\n    recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumors.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumors, base.strided.gcusum, base.strided.gcusumpw, base.strided.scusumors","base.strided.gcusumpw":"\nbase.strided.gcusumpw( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of strided array elements using pairwise\n    summation.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumpw( x.length, 0.0, x, 1, y, 1 )\n    [ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumpw( N, 0.0, x, 2, y, 2 )\n    [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gcusumpw( N, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.gcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using pairwise\n    summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumpw.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumpw, base.strided.gcusum, base.strided.scusumpw\n","base.strided.gcusumpw.ndarray":"\nbase.strided.gcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using pairwise\n    summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumpw.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumpw, base.strided.gcusum, base.strided.scusumpw","base.strided.gdot":"\nbase.strided.gdot( N, x, strideX, y, strideY )\n    Computes the dot product of two vectors.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: number\n        The dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n    > var y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n    > var out = base.strided.gdot( x.length, x, 1, y, 1 )\n    -5.0\n\n    // Strides:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n    > out = base.strided.gdot( 3, x, 2, y, -1 )\n    9.0\n\n    // Using view offsets:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n    > out = base.strided.gdot( 3, x1, -2, y1, 1 )\n    128.0\n\n\nbase.strided.gdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the dot product of two vectors using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing based on a starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: number\n        The dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n    > var y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n    > var out = base.strided.gdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    -5.0\n\n    // Strides:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n    > out = base.strided.gdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n    9.0\n\n    // Using offset indices:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n    > out = base.strided.gdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n    128.0\n\n    See Also\n    --------\n    base.strided.ddot, base.strided.sdot, gdot\n","base.strided.gdot.ndarray":"\nbase.strided.gdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the dot product of two vectors using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing based on a starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: number\n        The dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n    > var y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n    > var out = base.strided.gdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    -5.0\n\n    // Strides:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n    > out = base.strided.gdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n    9.0\n\n    // Using offset indices:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n    > out = base.strided.gdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n    128.0\n\n    See Also\n    --------\n    base.strided.ddot, base.strided.sdot, gdot","base.strided.gfill":"\nbase.strided.gfill( N, alpha, x, stride )\n    Fills a strided array with a specified scalar value.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: any\n        Constant.\n\n    x: ArrayLikeObject\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: ArrayLikeObject\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.gfill( x.length, 5.0, x, 1 )\n    [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gfill( N, 5.0, x, 2 )\n    [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gfill( N, 5.0, x1, 2 )\n    <Float64Array>[ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n    > x0\n    <Float64Array>[ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.gfill.ndarray( N, alpha, x, stride, offset )\n    Fills a strided array with a specified scalar value using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: any\n        Constant.\n\n    x: ArrayLikeObject\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: ArrayLikeObject\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.gfill.ndarray( x.length, 5.0, x, 1, 0 )\n    [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gfill.ndarray( N, 5.0, x, 2, 1 )\n    [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n    See Also\n    --------\n    base.strided.dfill, base.strided.sfill\n","base.strided.gfill.ndarray":"\nbase.strided.gfill.ndarray( N, alpha, x, stride, offset )\n    Fills a strided array with a specified scalar value using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: any\n        Constant.\n\n    x: ArrayLikeObject\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: ArrayLikeObject\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.gfill.ndarray( x.length, 5.0, x, 1, 0 )\n    [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gfill.ndarray( N, 5.0, x, 2, 1 )\n    [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n    See Also\n    --------\n    base.strided.dfill, base.strided.sfill","base.strided.gfillBy":"\nbase.strided.gfillBy( N, x, stride, clbk[, thisArg] )\n    Fills a strided array according to a provided callback function.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - aidx: array index.\n    - sidx: strided index (offset + aidx*stride).\n    - array: the input array.\n\n    The callback return value is used as the fill value for the current array\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    x: ArrayLikeObject\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function fill() { return 5.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.gfillBy( x.length, x, 1, fill )\n    [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gfillBy( N, x, 2, fill )\n    [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gfillBy( N, x1, 2, fill )\n    <Float64Array>[ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n    > x0\n    <Float64Array>[ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.gfillBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Fills a strided array according to a provided callback function and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    x: ArrayLikeObject\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function fill() { return 5.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.gfillBy.ndarray( x.length, x, 1, 0, fill )\n    [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gfillBy.ndarray( N, x, 2, 1, fill )\n    [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n    See Also\n    --------\n    base.strided.gfill\n","base.strided.gfillBy.ndarray":"\nbase.strided.gfillBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Fills a strided array according to a provided callback function and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    x: ArrayLikeObject\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function fill() { return 5.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.gfillBy.ndarray( x.length, x, 1, 0, fill )\n    [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gfillBy.ndarray( N, x, 2, 1, fill )\n    [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n    See Also\n    --------\n    base.strided.gfill","base.strided.gnannsumkbn":"\nbase.strided.gnannsumkbn( N, x, strideX, out, strideOut )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    an improved Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns a sum equal to `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > var out = [ 0.0, 0 ];\n    > base.strided.gnannsumkbn( x.length, x, 1, out, 1 )\n    [ 1.0, 3 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n    > out = [ 0.0, 0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gnannsumkbn( N, x, 2, out, 1 )\n    [ 1.0, 3 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > out = [ 0.0, 0 ];\n    > base.strided.gnannsumkbn( N, x1, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\nbase.strided.gnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > var out = [ 0.0, 0 ];\n    > base.strided.gnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\n    [ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > out = [ 0.0, 0 ];\n    > base.strided.gnannsumkbn.ndarray( N, x, 2, 1, out, 1, 0 )\n    [ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsumkbn\n","base.strided.gnannsumkbn.ndarray":"\nbase.strided.gnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > var out = [ 0.0, 0 ];\n    > base.strided.gnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\n    [ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > out = [ 0.0, 0 ];\n    > base.strided.gnannsumkbn.ndarray( N, x, 2, 1, out, 1, 0 )\n    [ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsumkbn","base.strided.gnansum":"\nbase.strided.gnansum( N, x, stride )\n    Computes the sum of strided array elements, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansum( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gnansum( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gnansum( N, x1, stride )\n    -1.0\n\nbase.strided.gnansum.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gnansum.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.snansum, base.strided.gsum, base.strided.nanmean\n","base.strided.gnansum.ndarray":"\nbase.strided.gnansum.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gnansum.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.snansum, base.strided.gsum, base.strided.nanmean","base.strided.gnansumkbn":"\nbase.strided.gnansumkbn( N, x, stride )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    an improved Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumkbn( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gnansumkbn( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gnansumkbn( N, x1, stride )\n    -1.0\n\nbase.strided.gnansumkbn.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gnansumkbn.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn, base.strided.snansumkbn\n","base.strided.gnansumkbn.ndarray":"\nbase.strided.gnansumkbn.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gnansumkbn.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn, base.strided.snansumkbn","base.strided.gnansumkbn2":"\nbase.strided.gnansumkbn2( N, x, stride )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    a second-order iterative Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumkbn2( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gnansumkbn2( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gnansumkbn2( N, x1, stride )\n    -1.0\n\nbase.strided.gnansumkbn2.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    a second-order iterative Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gnansumkbn2.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn2, base.strided.gnansum, base.strided.gnansumkbn, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn2, base.strided.snansumkbn2\n","base.strided.gnansumkbn2.ndarray":"\nbase.strided.gnansumkbn2.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    a second-order iterative Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gnansumkbn2.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn2, base.strided.gnansum, base.strided.gnansumkbn, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn2, base.strided.snansumkbn2","base.strided.gnansumors":"\nbase.strided.gnansumors( N, x, stride )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    ordinary recursive summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumors( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gnansumors( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gnansumors( N, x1, stride )\n    -1.0\n\nbase.strided.gnansumors.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gnansumors.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumors, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumpw, base.strided.gsumors, base.strided.snansumors\n","base.strided.gnansumors.ndarray":"\nbase.strided.gnansumors.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gnansumors.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumors, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumpw, base.strided.gsumors, base.strided.snansumors","base.strided.gnansumpw":"\nbase.strided.gnansumpw( N, x, stride )\n    Computes the sum of strided array elements, ignoring `NaN` values and\n    pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumpw( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gnansumpw( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gnansumpw( N, x1, stride )\n    -1.0\n\nbase.strided.gnansumpw.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gnansumpw.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumpw, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gsumpw, base.strided.snansumpw\n","base.strided.gnansumpw.ndarray":"\nbase.strided.gnansumpw.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gnansumpw.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumpw, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gsumpw, base.strided.snansumpw","base.strided.gnrm2":"\nbase.strided.gnrm2( N, x, stride )\n    Computes the L2-norm of a vector.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0` or `stride <= 0`, the function returns `0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The L2-norm.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gnrm2( x.length, x, 1 )\n    3.0\n\n    // Using `N` and stride parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > base.strided.gnrm2( 3, x, 2 )\n    3.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.gnrm2( 3, x1, 2 )\n    3.0\n\n\nbase.strided.gnrm2.ndarray( N, x, stride, offset )\n    Computes the L2-norm of a vector using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    nrm2: number\n        The L2-norm.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gnrm2.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > base.strided.gnrm2.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dnrm2, base.strided.snrm2\n","base.strided.gnrm2.ndarray":"\nbase.strided.gnrm2.ndarray( N, x, stride, offset )\n    Computes the L2-norm of a vector using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    nrm2: number\n        The L2-norm.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gnrm2.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > base.strided.gnrm2.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dnrm2, base.strided.snrm2","base.strided.grev":"\nbase.strided.grev( N, x, stride )\n    Reverses a strided array in-place.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: ArrayLikeObject\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.grev( x.length, x, 1 )\n    [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.grev( N, x, 2 )\n    [ 4.0, 1.0, 3.0, -5.0, -2.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.grev( N, x1, 2 )\n    <Float64Array>[ -6.0, 3.0, -4.0, 5.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n\nbase.strided.grev.ndarray( N, x, stride, offset )\n    Reverses a strided array in-place using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: ArrayLikeObject\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.grev.ndarray( x.length, x, 1, 0 )\n    [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.grev.ndarray( N, x, 2, 1 )\n    [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.drev, base.strided.srev\n","base.strided.grev.ndarray":"\nbase.strided.grev.ndarray( N, x, stride, offset )\n    Reverses a strided array in-place using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: ArrayLikeObject\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.grev.ndarray( x.length, x, 1, 0 )\n    [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.grev.ndarray( N, x, 2, 1 )\n    [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.drev, base.strided.srev","base.strided.gscal":"\nbase.strided.gscal( N, alpha, x, stride )\n    Multiplies a vector `x` by a constant `alpha`.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `stride <= 0`, the function returns `x` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > var alpha = 5.0;\n    > base.strided.gscal( x.length, alpha, x, 1 )\n    [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.gscal( 3, 5.0, x, 2 )\n    [ -10.0, 1.0, 15.0, -5.0, 20.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.gscal( 3, 5.0, x1, 2 )\n    <Float64Array>[ -10.0, 3.0, -20.0, 5.0, -30.0 ]\n    > x0\n    <Float64Array>[ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n\nbase.strided.gscal.ndarray( N, alpha, x, stride, offset )\n    Multiplies `x` by a constant `alpha` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.gscal.ndarray( x.length, 5.0, x, 1, 0 )\n    [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > base.strided.gscal.ndarray( 3, 5.0, x, 2, 1 )\n    [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n    See Also\n    --------\n    base.strided.dscal, base.strided.gaxpy, base.strided.sscal\n","base.strided.gscal.ndarray":"\nbase.strided.gscal.ndarray( N, alpha, x, stride, offset )\n    Multiplies `x` by a constant `alpha` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.gscal.ndarray( x.length, 5.0, x, 1, 0 )\n    [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > base.strided.gscal.ndarray( 3, 5.0, x, 2, 1 )\n    [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n    See Also\n    --------\n    base.strided.dscal, base.strided.gaxpy, base.strided.sscal","base.strided.gsort2hp":"\nbase.strided.gsort2hp( N, order, x, strideX, y, strideY )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using heapsort.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided arrays are sorted *in-place* (i.e., the input strided\n    arrays is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > base.strided.gsort2hp( x.length, 1, x, 1, y, 1 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    [ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsort2hp( N, -1, x, 2, y, 2 )\n    [ 3.0, -2.0, 1.0, -4.0 ]\n    > y\n    [ 2.0, 1.0, 0.0, 3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gsort2hp( N, 1, x1, 2, y1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.gsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using heapsort and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > base.strided.gsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    [ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    [ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssort2hp\n","base.strided.gsort2hp.ndarray":"\nbase.strided.gsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using heapsort and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > base.strided.gsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    [ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    [ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssort2hp","base.strided.gsort2ins":"\nbase.strided.gsort2ins( N, order, x, strideX, y, strideY )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using insertion sort.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^2).\n\n    The algorithm is efficient for *small* strided arrays (typically N <= 20)\n    and is particularly efficient for sorting strided arrays which are already\n    substantially sorted.\n\n    The algorithm is *stable*, meaning that the algorithm does *not* change the\n    order of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided arrays are sorted *in-place* (i.e., the input strided\n    arrays is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > base.strided.gsort2ins( x.length, 1, x, 1, y, 1 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    [ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsort2ins( N, -1, x, 2, y, 2 )\n    [ 3.0, -2.0, 1.0, -4.0 ]\n    > y\n    [ 2.0, 1.0, 0.0, 3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gsort2ins( N, 1, x1, 2, y1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.gsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using insertion sort and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > base.strided.gsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    [ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsort2ins.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    [ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2ins, base.strided.gsortins, base.strided.ssort2ins\n","base.strided.gsort2ins.ndarray":"\nbase.strided.gsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using insertion sort and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > base.strided.gsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    [ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsort2ins.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    [ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2ins, base.strided.gsortins, base.strided.ssort2ins","base.strided.gsort2sh":"\nbase.strided.gsort2sh( N, order, x, strideX, y, strideY )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using Shellsort.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^(4/3)).\n\n    The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided arrays are sorted *in-place* (i.e., the input strided\n    arrays is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > base.strided.gsort2sh( x.length, 1, x, 1, y, 1 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    [ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsort2sh( N, -1, x, 2, y, 2 )\n    [ 3.0, -2.0, 1.0, -4.0 ]\n    > y\n    [ 2.0, 1.0, 0.0, 3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gsort2sh( N, 1, x1, 2, y1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.gsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using Shellsort and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > base.strided.gsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    [ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    [ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssort2sh\n","base.strided.gsort2sh.ndarray":"\nbase.strided.gsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using Shellsort and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > base.strided.gsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    [ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    [ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssort2sh","base.strided.gsorthp":"\nbase.strided.gsorthp( N, order, x, stride )\n    Sorts a strided array using heapsort.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided array is sorted *in-place* (i.e., the input strided array\n    is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > base.strided.gsorthp( x.length, 1, x, 1 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsorthp( N, -1, x, 2 )\n    [ 3.0, -2.0, 1.0, -4.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gsorthp( N, 1, x1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.gsorthp.ndarray( N, order, x, stride, offset )\n    Sorts a strided array using heapsort and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > base.strided.gsorthp.ndarray( x.length, 1, x, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsorthp.ndarray( N, 1, x, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssorthp\n","base.strided.gsorthp.ndarray":"\nbase.strided.gsorthp.ndarray( N, order, x, stride, offset )\n    Sorts a strided array using heapsort and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > base.strided.gsorthp.ndarray( x.length, 1, x, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsorthp.ndarray( N, 1, x, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssorthp","base.strided.gsortins":"\nbase.strided.gsortins( N, order, x, stride )\n    Sorts a strided array using insertion sort.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^2).\n\n    The algorithm is efficient for *small* strided arrays (typically N <= 20)\n    and is particularly efficient for sorting strided arrays which are already\n    substantially sorted.\n\n    The algorithm is *stable*, meaning that the algorithm does *not* change the\n    order of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided array is sorted *in-place* (i.e., the input strided array\n    is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > base.strided.gsortins( x.length, 1, x, 1 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsortins( N, -1, x, 2 )\n    [ 3.0, -2.0, 1.0, -4.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gsortins( N, 1, x1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.gsortins.ndarray( N, order, x, stride, offset )\n    Sorts a strided array using insertion sort and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > base.strided.gsortins.ndarray( x.length, 1, x, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsortins.ndarray( N, 1, x, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsortins, base.strided.gsort2ins, base.strided.ssortins\n","base.strided.gsortins.ndarray":"\nbase.strided.gsortins.ndarray( N, order, x, stride, offset )\n    Sorts a strided array using insertion sort and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > base.strided.gsortins.ndarray( x.length, 1, x, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsortins.ndarray( N, 1, x, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsortins, base.strided.gsort2ins, base.strided.ssortins","base.strided.gsortsh":"\nbase.strided.gsortsh( N, order, x, stride )\n    Sorts a strided array using Shellsort.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^(4/3)).\n\n    The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided array is sorted *in-place* (i.e., the input strided array\n    is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > base.strided.gsortsh( x.length, 1, x, 1 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsortsh( N, -1, x, 2 )\n    [ 3.0, -2.0, 1.0, -4.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gsortsh( N, 1, x1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.gsortsh.ndarray( N, order, x, stride, offset )\n    Sorts a strided array using Shellsort and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > base.strided.gsortsh.ndarray( x.length, 1, x, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsortsh.ndarray( N, 1, x, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssortsh\n","base.strided.gsortsh.ndarray":"\nbase.strided.gsortsh.ndarray( N, order, x, stride, offset )\n    Sorts a strided array using Shellsort and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > base.strided.gsortsh.ndarray( x.length, 1, x, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsortsh.ndarray( N, 1, x, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssortsh","base.strided.gsum":"\nbase.strided.gsum( N, x, stride )\n    Computes the sum of strided array elements.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsum( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gsum( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gsum( N, x1, stride )\n    -1.0\n\nbase.strided.gsum.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsum.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsum, base.strided.gnansum, base.strided.ssum, base.strided.mean\n","base.strided.gsum.ndarray":"\nbase.strided.gsum.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsum.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsum, base.strided.gnansum, base.strided.ssum, base.strided.mean","base.strided.gsumkbn":"\nbase.strided.gsumkbn( N, x, stride )\n    Computes the sum of strided array elements using an improved Kahan–Babuška\n    algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumkbn( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gsumkbn( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gsumkbn( N, x1, stride )\n    -1.0\n\nbase.strided.gsumkbn.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements using an improved Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsumkbn.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn\n","base.strided.gsumkbn.ndarray":"\nbase.strided.gsumkbn.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements using an improved Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsumkbn.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn","base.strided.gsumkbn2":"\nbase.strided.gsumkbn2( N, x, stride )\n    Computes the sum of strided array elements using a second-order iterative\n    Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumkbn2( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gsumkbn2( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gsumkbn2( N, x1, stride )\n    -1.0\n\nbase.strided.gsumkbn2.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements using a second-order iterative\n    Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsumkbn2.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.gsum, base.strided.gsumkbn, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn2\n","base.strided.gsumkbn2.ndarray":"\nbase.strided.gsumkbn2.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements using a second-order iterative\n    Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsumkbn2.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.gsum, base.strided.gsumkbn, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn2","base.strided.gsumors":"\nbase.strided.gsumors( N, x, stride )\n    Computes the sum of strided array elements using ordinary recursive\n    summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumors( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gsumors( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gsumors( N, x1, stride )\n    -1.0\n\nbase.strided.gsumors.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements using ordinary recursive\n    summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsumors.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumors, base.strided.gnansumors, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumpw, base.strided.ssumors\n","base.strided.gsumors.ndarray":"\nbase.strided.gsumors.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements using ordinary recursive\n    summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsumors.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumors, base.strided.gnansumors, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumpw, base.strided.ssumors","base.strided.gsumpw":"\nbase.strided.gsumpw( N, x, stride )\n    Computes the sum of strided array elements using pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumpw( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gsumpw( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gsumpw( N, x1, stride )\n    -1.0\n\nbase.strided.gsumpw.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements using pairwise summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsumpw.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumpw, base.strided.gnansumpw, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.ssumpw\n","base.strided.gsumpw.ndarray":"\nbase.strided.gsumpw.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements using pairwise summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsumpw.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumpw, base.strided.gnansumpw, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.ssumpw","base.strided.gswap":"\nbase.strided.gswap( N, x, strideX, y, strideY )\n    Interchanges vectors `x` and `y`.\n\n    The `N` and stride parameters determine how values from `x` are swapped with\n    values from `y`.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the vectors are unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: ArrayLikeObject\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n    > base.strided.gswap( x.length, x, 1, y, 1 )\n    [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n    > base.strided.gswap( 3, x, -2, y, 1 )\n    [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n    // Using typed array views:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.gswap( 3, x1, -2, y1, 1 )\n    <Float64Array>[ 6.0, 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.gswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Interchanges vectors `x` and `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: ArrayLikeObject\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n    > base.strided.gswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n    > base.strided.gswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dswap, base.strided.gcopy, base.strided.sswap, gswap\n","base.strided.gswap.ndarray":"\nbase.strided.gswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Interchanges vectors `x` and `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: ArrayLikeObject\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n    > base.strided.gswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n    > base.strided.gswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dswap, base.strided.gcopy, base.strided.sswap, gswap","base.strided.mapBy":"\nbase.strided.mapBy( N, x, sx, y, sy, fcn, clbk[, thisArg] )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - indices: strided indices (offset + idx*stride).\n    - arrays: input and output arrays.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    fcn: Function\n        Unary function to apply to callback return values.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v * 2.0; };\n    > base.strided.mapBy( x.length, x, 1, y, 1, base.abs, clbk )\n    [ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > base.strided.mapBy( 2, x, 2, y, -1, base.abs, clbk )\n    [ 6.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.mapBy( 2, x1, -2, y1, 1, base.abs, clbk )\n    <Float64Array>[ 8.0, 4.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 8.0, 4.0 ]\n\n\nbase.strided.mapBy.ndarray( N, x, sx, ox, y, sy, oy, fcn, clbk[, thisArg] )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offsest parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply to callback return values.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v * 2.0; };\n    > base.strided.mapBy.ndarray( x.length, x, 1, 0, y, 1, 0, base.abs, clbk )\n    [ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > base.strided.mapBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.abs, clbk )\n    [ 0.0, 0.0, 8.0, 4.0 ]\n\n    See Also\n    --------\n    base.strided.mapBy2, base.strided.unary\n","base.strided.mapBy.ndarray":"\nbase.strided.mapBy.ndarray( N, x, sx, ox, y, sy, oy, fcn, clbk[, thisArg] )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offsest parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply to callback return values.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v * 2.0; };\n    > base.strided.mapBy.ndarray( x.length, x, 1, 0, y, 1, 0, base.abs, clbk )\n    [ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > base.strided.mapBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.abs, clbk )\n    [ 0.0, 0.0, 8.0, 4.0 ]\n\n    See Also\n    --------\n    base.strided.mapBy2, base.strided.unary","base.strided.mapBy2":"\nbase.strided.mapBy2( N, x, sx, y, sy, z, sz, fcn, clbk[, thisArg] )\n    Applies a binary function to each pair of elements retrieved from strided\n    input arrays according to a callback function and assigns results to a\n    strided output array.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided four arguments:\n\n    - values: input array elements.\n    - idx: iteration index.\n    - indices: strided array indices (offset + idx*stride).\n    - arrays: input and output arrays.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    fcn: Function\n        Binary function to apply to callback return values.\n\n    clbk: Function\n        Callback function which returns an array-like object containing two\n        values.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 1.0, 1.0, 2.0, 2.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\n    > base.strided.mapBy2( x.length, x, 1, y, 1, z, 1, base.add, clbk )\n    [ 4.0, -2.0, 10.0, -4.0 ]\n\n    // Using `N` and stride parameters:\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > base.strided.mapBy2( 2, x, 2, y, -1, z, -1, base.add, clbk )\n    [ 8.0, 4.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y0 = new Float64Array( [ 1.0, 1.0, 2.0, 2.0 ] );\n    > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > base.strided.mapBy2( 2, x1, -2, y1, 1, z1, 1, base.add, clbk )\n    <Float64Array>[ -4.0, 0.0 ]\n    > z0\n    <Float64Array>[ 0.0, 0.0, -4.0, 0.0 ]\n\n\nbase.strided.mapBy2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn, clbk[, thisArg] )\n    Applies a binary function to each pair of elements retrieved from strided\n    input arrays according to a callback function and assigns results to a\n    strided output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offsest parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    fcn: Function\n        Binary function to apply to callback return values.\n\n    clbk: Function\n        Callback function which returns an array-like object containing two\n        values.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 1.0, 1.0, 2.0, 2.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\n    > base.strided.mapBy2.ndarray( 4, x, 1, 0, y, 1, 0, z, 1, 0, base.add, clbk )\n    [ 4.0, -2.0, 10.0, -4.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 1.0, 1.0, 2.0, 2.0 ];\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > base.strided.mapBy2.ndarray( 2, x, 2, 1, y, -1, 3, z, 1, 0, base.add, clbk )\n    [ 0.0, -4.0, 0.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.mapBy, base.strided.binary\n","base.strided.mapBy2.ndarray":"\nbase.strided.mapBy2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn, clbk[, thisArg] )\n    Applies a binary function to each pair of elements retrieved from strided\n    input arrays according to a callback function and assigns results to a\n    strided output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offsest parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    fcn: Function\n        Binary function to apply to callback return values.\n\n    clbk: Function\n        Callback function which returns an array-like object containing two\n        values.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 1.0, 1.0, 2.0, 2.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\n    > base.strided.mapBy2.ndarray( 4, x, 1, 0, y, 1, 0, z, 1, 0, base.add, clbk )\n    [ 4.0, -2.0, 10.0, -4.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 1.0, 1.0, 2.0, 2.0 ];\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > base.strided.mapBy2.ndarray( 2, x, 2, 1, y, -1, 3, z, 1, 0, base.add, clbk )\n    [ 0.0, -4.0, 0.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.mapBy, base.strided.binary","base.strided.max":"\nbase.strided.max( N, x, stride )\n    Computes the maximum value of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.max( x.length, x, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.max( N, x, stride )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.max( N, x1, stride )\n    2.0\n\nbase.strided.max.ndarray( N, x, stride, offset )\n    Computes the maximum value of a strided array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.max.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.max.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.min, base.strided.nanmax, base.strided.smax\n","base.strided.max.ndarray":"\nbase.strided.max.ndarray( N, x, stride, offset )\n    Computes the maximum value of a strided array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.max.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.max.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.min, base.strided.nanmax, base.strided.smax","base.strided.maxabs":"\nbase.strided.maxabs( N, x, stride )\n    Computes the maximum absolute value of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.maxabs( x.length, x, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.maxabs( N, x, stride )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.maxabs( N, x1, stride )\n    2.0\n\nbase.strided.maxabs.ndarray( N, x, stride, offset )\n    Computes the maximum absolute value of a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.maxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.maxabs.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmaxabs, base.strided.max, base.strided.minabs, base.strided.nanmaxabs, base.strided.smaxabs\n","base.strided.maxabs.ndarray":"\nbase.strided.maxabs.ndarray( N, x, stride, offset )\n    Computes the maximum absolute value of a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.maxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.maxabs.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmaxabs, base.strided.max, base.strided.minabs, base.strided.nanmaxabs, base.strided.smaxabs","base.strided.maxBy":"\nbase.strided.maxBy( N, x, stride, clbk[, thisArg] )\n    Calculates the maximum value of a strided array via a callback function.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - aidx: array index.\n    - sidx: strided index (offset + aidx*stride).\n    - array: the input array.\n\n    The callback function should return a numeric value.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.maxBy( x.length, x, 1, accessor )\n    8.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.maxBy( N, x, 2, accessor )\n    8.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.maxBy( N, x1, 2, accessor )\n    -4.0\n\nbase.strided.maxBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the maximum value of a strided array via a callback function and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.maxBy.ndarray( x.length, x, 1, 0, accessor )\n    8.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.maxBy.ndarray( N, x, 2, 1, accessor )\n    -4.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.max, base.strided.minBy, base.strided.nanmaxBy, base.strided.smax\n","base.strided.maxBy.ndarray":"\nbase.strided.maxBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the maximum value of a strided array via a callback function and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.maxBy.ndarray( x.length, x, 1, 0, accessor )\n    8.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.maxBy.ndarray( N, x, 2, 1, accessor )\n    -4.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.max, base.strided.minBy, base.strided.nanmaxBy, base.strided.smax","base.strided.maxsorted":"\nbase.strided.maxsorted( N, x, stride )\n    Computes the maximum value of a sorted strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > base.strided.maxsorted( x.length, x, 1 )\n    3.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.maxsorted( N, x, stride )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.maxsorted( N, x1, stride )\n    3.0\n\nbase.strided.maxsorted.ndarray( N, x, stride, offset )\n    Computes the maximum value of a sorted strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > base.strided.maxsorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.maxsorted.ndarray( N, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmaxsorted, base.strided.max, base.strided.minsorted, base.strided.smaxsorted\n","base.strided.maxsorted.ndarray":"\nbase.strided.maxsorted.ndarray( N, x, stride, offset )\n    Computes the maximum value of a sorted strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > base.strided.maxsorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.maxsorted.ndarray( N, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmaxsorted, base.strided.max, base.strided.minsorted, base.strided.smaxsorted","base.strided.maxViewBufferIndex":"\nbase.strided.maxViewBufferIndex( N, stride, offset )\n    Returns the maximum accessible index based on a set of provided strided\n    array parameters.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    stride: integer\n        Stride length.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    idx: integer\n        Minimum accessible index.\n\n    Examples\n    --------\n    > var idx = base.strided.maxViewBufferIndex( 3, 2, 10 )\n    14\n\n","base.strided.mean":"\nbase.strided.mean( N, x, stride )\n    Computes the arithmetic mean of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.mean( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.mean( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.mean( N, x1, stride )\n    ~-0.3333\n\nbase.strided.mean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.mean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.nanmean, base.strided.smean\n","base.strided.mean.ndarray":"\nbase.strided.mean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.mean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.nanmean, base.strided.smean","base.strided.meankbn":"\nbase.strided.meankbn( N, x, stride )\n    Computes the arithmetic mean of a strided array using an improved Kahan–\n    Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.meankbn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.meankbn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.meankbn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.meankbn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using an improved Kahan–\n    Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meankbn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meankbn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeankbn, base.strided.mean, base.strided.smeankbn\n","base.strided.meankbn.ndarray":"\nbase.strided.meankbn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using an improved Kahan–\n    Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meankbn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meankbn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeankbn, base.strided.mean, base.strided.smeankbn","base.strided.meankbn2":"\nbase.strided.meankbn2( N, x, stride )\n    Computes the arithmetic mean of a strided array using a second-order\n    iterative Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.meankbn2( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.meankbn2( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.meankbn2( N, x1, stride )\n    ~-0.3333\n\nbase.strided.meankbn2.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using a second-order\n    iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meankbn2.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meankbn2.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeankbn2, base.strided.mean, base.strided.smeankbn2\n","base.strided.meankbn2.ndarray":"\nbase.strided.meankbn2.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using a second-order\n    iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meankbn2.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meankbn2.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeankbn2, base.strided.mean, base.strided.smeankbn2","base.strided.meanors":"\nbase.strided.meanors( N, x, stride )\n    Computes the arithmetic mean of a strided array using ordinary recursive\n    summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.meanors( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.meanors( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.meanors( N, x1, stride )\n    ~-0.3333\n\nbase.strided.meanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using ordinary recursive\n    summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanors, base.strided.mean, base.strided.nanmeanors, base.strided.smeanors\n","base.strided.meanors.ndarray":"\nbase.strided.meanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using ordinary recursive\n    summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanors, base.strided.mean, base.strided.nanmeanors, base.strided.smeanors","base.strided.meanpn":"\nbase.strided.meanpn( N, x, stride )\n    Computes the arithmetic mean of a strided array using a two-pass error\n    correction algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.meanpn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.meanpn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.meanpn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.meanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using a two-pass error\n    correction algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.mean, base.strided.nanmeanpn, base.strided.smeanpn\n","base.strided.meanpn.ndarray":"\nbase.strided.meanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using a two-pass error\n    correction algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.mean, base.strided.nanmeanpn, base.strided.smeanpn","base.strided.meanpw":"\nbase.strided.meanpw( N, x, stride )\n    Computes the arithmetic mean of a strided array using pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.meanpw( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.meanpw( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.meanpw( N, x1, stride )\n    ~-0.3333\n\nbase.strided.meanpw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using pairwise summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meanpw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meanpw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpw, base.strided.mean, base.strided.smeanpw\n","base.strided.meanpw.ndarray":"\nbase.strided.meanpw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using pairwise summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meanpw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meanpw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpw, base.strided.mean, base.strided.smeanpw","base.strided.meanwd":"\nbase.strided.meanwd( N, x, stride )\n    Computes the arithmetic mean of a strided array using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.meanwd( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.meanwd( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.meanwd( N, x1, stride )\n    ~-0.3333\n\nbase.strided.meanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using Welford's algorithm\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanwd, base.strided.mean, base.strided.nanmeanwd, base.strided.smeanwd\n","base.strided.meanwd.ndarray":"\nbase.strided.meanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using Welford's algorithm\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanwd, base.strided.mean, base.strided.nanmeanwd, base.strided.smeanwd","base.strided.mediansorted":"\nbase.strided.mediansorted( N, x, stride )\n    Computes the median value of a sorted strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > base.strided.mediansorted( x.length, x, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mediansorted( N, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.mediansorted( N, x1, 2 )\n    2.0\n\nbase.strided.mediansorted.ndarray( N, x, stride, offset )\n    Computes the median value of a sorted strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > base.strided.mediansorted.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mediansorted.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmediansorted, base.strided.mean, base.strided.smediansorted\n","base.strided.mediansorted.ndarray":"\nbase.strided.mediansorted.ndarray( N, x, stride, offset )\n    Computes the median value of a sorted strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > base.strided.mediansorted.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mediansorted.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmediansorted, base.strided.mean, base.strided.smediansorted","base.strided.metaDataProps":"\nbase.strided.metaDataProps( meta, dtypes, obj, bool )\n    Defines non-enumerable read-only properties which expose strided array\n    function meta data.\n\n    Parameters\n    ----------\n    meta: Object\n        Function meta data.\n\n    meta.nargs: integer\n        Total number of arguments (excluding offsets).\n\n    meta.nin: integer\n        Total number of input arrays.\n\n    meta.nout: integer\n        Total number of output arrays.\n\n    dtypes: ArrayLikeObject\n        List of strided array data types.\n\n    obj: Object|Function\n        Object on which to define properties.\n\n    bool: boolean\n        Boolean indicating whether the provided object should describe an\n        \"ndarray\" function interface.\n\n    Returns\n    -------\n    out: Object|Function\n        Object on which properties were defined.\n\n    Examples\n    --------\n    > var meta = { 'nargs': 7, 'nin': 1, 'nout': 1 };\n    > var dt = [ 'float64', 'float64' ];\n    > var obj = {};\n    > base.strided.metaDataProps( meta, dt, obj, false );\n    > obj.nargs\n    7\n    > obj.nin\n    1\n    > obj.nout\n    1\n    > obj.types\n    [...]\n\n","base.strided.min":"\nbase.strided.min( N, x, stride )\n    Computes the minimum value of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.min( x.length, x, 1 )\n    -2.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.min( N, x, stride )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.min( N, x1, stride )\n    -2.0\n\nbase.strided.min.ndarray( N, x, stride, offset )\n    Computes the minimum value of a strided array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.min.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.min.ndarray( N, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.max, base.strided.nanmin, base.strided.smin\n","base.strided.min.ndarray":"\nbase.strided.min.ndarray( N, x, stride, offset )\n    Computes the minimum value of a strided array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.min.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.min.ndarray( N, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.max, base.strided.nanmin, base.strided.smin","base.strided.minabs":"\nbase.strided.minabs( N, x, stride )\n    Computes the minimum absolute value of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.minabs( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.minabs( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.minabs( N, x1, stride )\n    1.0\n\nbase.strided.minabs.ndarray( N, x, stride, offset )\n    Computes the minimum absolute value of a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.minabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.minabs.ndarray( N, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dminabs, base.strided.maxabs, base.strided.min, base.strided.nanminabs, base.strided.sminabs\n","base.strided.minabs.ndarray":"\nbase.strided.minabs.ndarray( N, x, stride, offset )\n    Computes the minimum absolute value of a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.minabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.minabs.ndarray( N, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dminabs, base.strided.maxabs, base.strided.min, base.strided.nanminabs, base.strided.sminabs","base.strided.minBy":"\nbase.strided.minBy( N, x, stride, clbk[, thisArg] )\n    Calculates the minimum value of a strided array via a callback function.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - aidx: array index.\n    - sidx: strided index (offset + aidx*stride).\n    - array: the input array.\n\n    The callback function should return a numeric value.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.minBy( x.length, x, 1, accessor )\n    -10.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.minBy( N, x, 2, accessor )\n    -4.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.minBy( N, x1, 2, accessor )\n    -12.0\n\nbase.strided.minBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the minimum value of a strided array via a callback function and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.minBy.ndarray( x.length, x, 1, 0, accessor )\n    -10.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.minBy.ndarray( N, x, 2, 1, accessor )\n    -12.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.maxBy, base.strided.min, base.strided.nanminBy, base.strided.smin\n","base.strided.minBy.ndarray":"\nbase.strided.minBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the minimum value of a strided array via a callback function and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.minBy.ndarray( x.length, x, 1, 0, accessor )\n    -10.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.minBy.ndarray( N, x, 2, 1, accessor )\n    -12.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.maxBy, base.strided.min, base.strided.nanminBy, base.strided.smin","base.strided.minsorted":"\nbase.strided.minsorted( N, x, stride )\n    Computes the minimum value of a sorted strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > base.strided.minsorted( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.minsorted( N, x, stride )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.minsorted( N, x1, stride )\n    -2.0\n\nbase.strided.minsorted.ndarray( N, x, stride, offset )\n    Computes the minimum value of a sorted strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > base.strided.minsorted.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.minsorted.ndarray( N, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dminsorted, base.strided.maxsorted, base.strided.min, base.strided.sminsorted\n","base.strided.minsorted.ndarray":"\nbase.strided.minsorted.ndarray( N, x, stride, offset )\n    Computes the minimum value of a sorted strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > base.strided.minsorted.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.minsorted.ndarray( N, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dminsorted, base.strided.maxsorted, base.strided.min, base.strided.sminsorted","base.strided.minViewBufferIndex":"\nbase.strided.minViewBufferIndex( N, stride, offset )\n    Returns the minimum accessible index based on a set of provided strided\n    array parameters.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    stride: integer\n        Stride length.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    idx: integer\n        Minimum accessible index.\n\n    Examples\n    --------\n    > var idx = base.strided.minViewBufferIndex( 3, -2, 10 )\n    6\n\n    See Also\n    --------\n    base.strided.offsetView\n","base.strided.mskmax":"\nbase.strided.mskmax( N, x, strideX, mask, strideMask )\n    Computes the maximum value of a strided array according to a mask.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 4.0, 2.0 ];\n    > var mask = [ 0, 0, 1, 0 ];\n    > base.strided.mskmax( x.length, x, 1, mask, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mskmax( N, x, 2, mask, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.mskmax( N, x1, 2, mask1, 2 )\n    2.0\n\nbase.strided.mskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a strided array according to a mask and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n    > var mask = [ 0, 0, 0, 1 ];\n    > base.strided.mskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmskmax, base.strided.max, base.strided.mskmin, base.strided.nanmax, base.strided.smskmax\n","base.strided.mskmax.ndarray":"\nbase.strided.mskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a strided array according to a mask and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n    > var mask = [ 0, 0, 0, 1 ];\n    > base.strided.mskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmskmax, base.strided.max, base.strided.mskmin, base.strided.nanmax, base.strided.smskmax","base.strided.mskmin":"\nbase.strided.mskmin( N, x, strideX, mask, strideMask )\n    Computes the minimum value of a strided array according to a mask.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, -4.0, 2.0 ];\n    > var mask = [ 0, 0, 1, 0 ];\n    > base.strided.mskmin( x.length, x, 1, mask, 1 )\n    -2.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mskmin( N, x, 2, mask, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.mskmin( N, x1, 2, mask1, 2 )\n    -2.0\n\nbase.strided.mskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a strided array according to a mask and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, -4.0 ];\n    > var mask = [ 0, 0, 0, 1 ];\n    > base.strided.mskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmskmin, base.strided.min, base.strided.mskmax, base.strided.nanmin, base.strided.smskmin\n","base.strided.mskmin.ndarray":"\nbase.strided.mskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a strided array according to a mask and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, -4.0 ];\n    > var mask = [ 0, 0, 0, 1 ];\n    > base.strided.mskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmskmin, base.strided.min, base.strided.mskmax, base.strided.nanmin, base.strided.smskmin","base.strided.mskrange":"\nbase.strided.mskrange( N, x, strideX, mask, strideMask )\n    Computes the range of a strided array according to a mask.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 4.0, 2.0 ];\n    > var mask = [ 0, 0, 1, 0 ];\n    > base.strided.mskrange( x.length, x, 1, mask, 1 )\n    4.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mskrange( N, x, 2, mask, 2 )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.mskrange( N, x1, 2, mask1, 2 )\n    4.0\n\nbase.strided.mskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a strided array according to a mask and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n    > var mask = [ 0, 0, 0, 1 ];\n    > base.strided.mskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dmskrange, base.strided.range, base.strided.mskmax, base.strided.mskmin, base.strided.nanrange, base.strided.smskrange\n","base.strided.mskrange.ndarray":"\nbase.strided.mskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a strided array according to a mask and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n    > var mask = [ 0, 0, 0, 1 ];\n    > base.strided.mskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dmskrange, base.strided.range, base.strided.mskmax, base.strided.mskmin, base.strided.nanrange, base.strided.smskrange","base.strided.mskunary":"\nbase.strided.mskunary( arrays, shape, strides, fcn )\n    Applies a unary callback to elements in a strided input array according to\n    elements in a strided mask array and assigns results to elements in a\n    strided output array.\n\n    The `shape` and `strides` parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided input array, a strided mask\n        array, and one strided output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided arrays.\n\n    fcn: Function\n        Unary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1 ];\n    > base.strided.mskunary( [ x, m, y ], shape, strides, base.abs );\n    > y\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n\nbase.strided.mskunary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a unary callback to elements in a strided input array according to\n    elements in a strided mask array, and assigns results to elements in a\n    strided output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided input array, a strided mask\n        array, and one strided output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided arrays.\n\n    fcn: Function\n        Unary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1 ];\n    > var offsets = [ 0, 0, 0 ];\n    > base.strided.mskunary.ndarray( [ x, m, y ], shape, strides, offsets, base.abs );\n    > y\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    See Also\n    --------\n    base.strided.dmskmap, base.strided.smskmap, base.strided.unary\n","base.strided.mskunary.ndarray":"\nbase.strided.mskunary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a unary callback to elements in a strided input array according to\n    elements in a strided mask array, and assigns results to elements in a\n    strided output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided input array, a strided mask\n        array, and one strided output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided arrays.\n\n    fcn: Function\n        Unary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1 ];\n    > var offsets = [ 0, 0, 0 ];\n    > base.strided.mskunary.ndarray( [ x, m, y ], shape, strides, offsets, base.abs );\n    > y\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    See Also\n    --------\n    base.strided.dmskmap, base.strided.smskmap, base.strided.unary","base.strided.mskunaryDtypeSignatures":"\nbase.strided.mskunaryDtypeSignatures( dtypes1, dtypes2[, options] )\n    Generates a list of masked unary interface signatures from strided array\n    data types.\n\n    The function returns a strided array having a stride length of three (i.e.,\n    every three elements define a masked unary interface signature).\n\n    For each signature (i.e., set of three consecutive non-overlapping strided\n    array elements), the first element is the input data type, the second\n    element is the mask data type, and the last element is the return data type.\n\n    All signatures follow type promotion rules.\n\n    The mask array data type is always `uint8`.\n\n    Parameters\n    ----------\n    dtypes1: ArrayLike<any>\n        List of supported data types for the input argument.\n\n    dtypes2: ArrayLike<any>\n        List of supported data types for the output argument.\n\n    options: Object (optional)\n        Options.\n\n    options.enums: boolean (optional)\n        Boolean flag indicating whether to return signatures as a list of data\n        type enumeration constants. Default: false.\n\n    Returns\n    -------\n    out: Array\n        Strided array containing masked unary interface signatures.\n\n    Examples\n    --------\n    > var dt = strided.dataTypes();\n    > var out = base.strided.mskunaryDtypeSignatures( dt, dt )\n    [...]\n\n    See Also\n    --------\n    base.strided.mskunarySignatureCallbacks\n","base.strided.mskunarySignatureCallbacks":"\nbase.strided.mskunarySignatureCallbacks( table, signatures )\n    Assigns callbacks to masked unary interfaces according to type promotion\n    rules.\n\n    Parameters\n    ----------\n    table: Object\n        Object mapping callbacks to data types.\n\n    table.default: Function\n        Default callback.\n\n    table.complex64: Function\n        Callback to be invoked when input arrays promote to single-precision\n        complex floating-point numbers.\n\n    table.complex128: Function\n        Callback to be invoked when input arrays promote to double precision\n        complex floating-point numbers.\n\n    signatures: ArrayLike<any>\n        Strided array containing masked unary interface signatures.\n\n    Returns\n    -------\n    out: Array<Function>\n        List of callbacks, one per signature.\n\n    Examples\n    --------\n    > var dt = strided.dataTypes();\n    > var sigs = base.strided.mskunaryDtypeSignatures( dt, dt );\n    > var t = {\n    ...     'default': base.identity,\n    ...     'complex64': base.cidentityf,\n    ...     'complex128': base.cidentity\n    ... };\n    > var out = base.strided.mskunarySignatureCallbacks( t, sigs )\n    [...]\n\n    See Also\n    --------\n    base.strided.mskunaryDtypeSignatures\n","base.strided.nanmax":"\nbase.strided.nanmax( N, x, stride )\n    Computes the maximum value of a strided array, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmax( x.length, x, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanmax( N, x, stride )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanmax( N, x1, stride )\n    2.0\n\nbase.strided.nanmax.ndarray( N, x, stride, offset )\n    Computes the maximum value of a strided array, ignoring `NaN` values and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmax.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmax.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmax, base.strided.max, base.strided.nanmin, base.strided.snanmax\n","base.strided.nanmax.ndarray":"\nbase.strided.nanmax.ndarray( N, x, stride, offset )\n    Computes the maximum value of a strided array, ignoring `NaN` values and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmax.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmax.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmax, base.strided.max, base.strided.nanmin, base.strided.snanmax","base.strided.nanmaxabs":"\nbase.strided.nanmaxabs( N, x, stride )\n    Computes the maximum absolute value of a strided array, ignoring `NaN`\n    values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmaxabs( x.length, x, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanmaxabs( N, x, stride )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanmaxabs( N, x1, stride )\n    2.0\n\nbase.strided.nanmaxabs.ndarray( N, x, stride, offset )\n    Computes the maximum absolute value of a strided array, ignoring `NaN`\n    values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmaxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmaxabs.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmaxabs, base.strided.maxabs, base.strided.nanmax, base.strided.nanminabs, base.strided.snanmaxabs\n","base.strided.nanmaxabs.ndarray":"\nbase.strided.nanmaxabs.ndarray( N, x, stride, offset )\n    Computes the maximum absolute value of a strided array, ignoring `NaN`\n    values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmaxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmaxabs.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmaxabs, base.strided.maxabs, base.strided.nanmax, base.strided.nanminabs, base.strided.snanmaxabs","base.strided.nanmaxBy":"\nbase.strided.nanmaxBy( N, x, stride, clbk[, thisArg] )\n    Calculates the maximum value of a strided array via a callback function,\n    ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - aidx: array index.\n    - sidx: strided index (offset + aidx*stride).\n    - array: the input array.\n\n    The callback function should return a numeric value.\n\n    If the callback function returns `NaN`, the value is ignored.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n    > base.strided.nanmaxBy( x.length, x, 1, accessor )\n    8.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmaxBy( N, x, 2, accessor )\n    8.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanmaxBy( N, x1, 2, accessor )\n    -4.0\n\nbase.strided.nanmaxBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the maximum value of a strided array via a callback function,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n    > base.strided.nanmaxBy.ndarray( x.length, x, 1, 0, accessor )\n    8.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmaxBy.ndarray( N, x, 2, 1, accessor )\n    -4.0\n\n    See Also\n    --------\n    base.strided.dnanmax, base.strided.maxBy, base.strided.nanmax, base.strided.nanminBy, base.strided.snanmax\n","base.strided.nanmaxBy.ndarray":"\nbase.strided.nanmaxBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the maximum value of a strided array via a callback function,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n    > base.strided.nanmaxBy.ndarray( x.length, x, 1, 0, accessor )\n    8.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmaxBy.ndarray( N, x, 2, 1, accessor )\n    -4.0\n\n    See Also\n    --------\n    base.strided.dnanmax, base.strided.maxBy, base.strided.nanmax, base.strided.nanminBy, base.strided.snanmax","base.strided.nanmean":"\nbase.strided.nanmean( N, x, stride )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmean( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanmean( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanmean( N, x1, stride )\n    ~-0.3333\n\nbase.strided.nanmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.mean, base.strided.snanmean\n","base.strided.nanmean.ndarray":"\nbase.strided.nanmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.mean, base.strided.snanmean","base.strided.nanmeanors":"\nbase.strided.nanmeanors( N, x, stride )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using ordinary recursive summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmeanors( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanmeanors( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanmeanors( N, x1, stride )\n    ~-0.3333\n\nbase.strided.nanmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanors, base.strided.meanors, base.strided.nanmean, base.strided.snanmeanors\n","base.strided.nanmeanors.ndarray":"\nbase.strided.nanmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanors, base.strided.meanors, base.strided.nanmean, base.strided.snanmeanors","base.strided.nanmeanpn":"\nbase.strided.nanmeanpn( N, x, stride )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using a two-pass error correction algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmeanpn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanmeanpn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanmeanpn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.nanmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using a two-pass error correction algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanpn, base.strided.meanpn, base.strided.nanmean, base.strided.snanmeanpn\n","base.strided.nanmeanpn.ndarray":"\nbase.strided.nanmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using a two-pass error correction algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanpn, base.strided.meanpn, base.strided.nanmean, base.strided.snanmeanpn","base.strided.nanmeanwd":"\nbase.strided.nanmeanwd( N, x, stride )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmeanwd( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanmeanwd( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanmeanwd( N, x1, stride )\n    ~-0.3333\n\nbase.strided.nanmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanwd, base.strided.meanwd, base.strided.nanmean, base.strided.snanmeanwd\n","base.strided.nanmeanwd.ndarray":"\nbase.strided.nanmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanwd, base.strided.meanwd, base.strided.nanmean, base.strided.snanmeanwd","base.strided.nanmin":"\nbase.strided.nanmin( N, x, stride )\n    Computes the minimum value of a strided array, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmin( x.length, x, 1 )\n    -2.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanmin( N, x, stride )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanmin( N, x1, stride )\n    -2.0\n\nbase.strided.nanmin.ndarray( N, x, stride, offset )\n    Computes the minimum value of a strided array, ignoring `NaN` values and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmin.ndarray( N, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dnanmin, base.strided.min, base.strided.nanmax, base.strided.snanmin\n","base.strided.nanmin.ndarray":"\nbase.strided.nanmin.ndarray( N, x, stride, offset )\n    Computes the minimum value of a strided array, ignoring `NaN` values and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmin.ndarray( N, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dnanmin, base.strided.min, base.strided.nanmax, base.strided.snanmin","base.strided.nanminabs":"\nbase.strided.nanminabs( N, x, stride )\n    Computes the minimum absolute value of a strided array, ignoring `NaN`\n    values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanminabs( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanminabs( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanminabs( N, x1, stride )\n    1.0\n\nbase.strided.nanminabs.ndarray( N, x, stride, offset )\n    Computes the minimum absolute value of a strided array, ignoring `NaN`\n    values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanminabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanminabs.ndarray( N, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dnanminabs, base.strided.minabs, base.strided.nanmaxabs, base.strided.nanmin, base.strided.snanminabs\n","base.strided.nanminabs.ndarray":"\nbase.strided.nanminabs.ndarray( N, x, stride, offset )\n    Computes the minimum absolute value of a strided array, ignoring `NaN`\n    values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanminabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanminabs.ndarray( N, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dnanminabs, base.strided.minabs, base.strided.nanmaxabs, base.strided.nanmin, base.strided.snanminabs","base.strided.nanminBy":"\nbase.strided.nanminBy( N, x, stride, clbk[, thisArg] )\n    Calculates the minimum value of a strided array via a callback function,\n    ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - aidx: array index.\n    - sidx: strided index (offset + aidx*stride).\n    - array: the input array.\n\n    The callback function should return a numeric value.\n\n    If the callback function returns `NaN`, the value is ignored.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n    > base.strided.nanminBy( x.length, x, 1, accessor )\n    -10.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, NaN, -3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanminBy( N, x, 2, accessor )\n    -4.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanminBy( N, x1, 2, accessor )\n    -12.0\n\nbase.strided.nanminBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the minimum value of a strided array via a callback function,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n    > base.strided.nanminBy.ndarray( x.length, x, 1, 0, accessor )\n    -10.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanminBy.ndarray( N, x, 2, 1, accessor )\n    -12.0\n\n    See Also\n    --------\n    base.strided.dnanmin, base.strided.minBy, base.strided.nanmaxBy, base.strided.nanmin, base.strided.snanmin\n","base.strided.nanminBy.ndarray":"\nbase.strided.nanminBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the minimum value of a strided array via a callback function,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n    > base.strided.nanminBy.ndarray( x.length, x, 1, 0, accessor )\n    -10.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanminBy.ndarray( N, x, 2, 1, accessor )\n    -12.0\n\n    See Also\n    --------\n    base.strided.dnanmin, base.strided.minBy, base.strided.nanmaxBy, base.strided.nanmin, base.strided.snanmin","base.strided.nanmskmax":"\nbase.strided.nanmskmax( N, x, strideX, mask, strideMask )\n    Computes the maximum value of a strided array according to a mask and\n    ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\n    > var mask = [ 0, 0, 1, 0, 0 ];\n    > base.strided.nanmskmax( x.length, x, 1, mask, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmskmax( N, x, 2, mask, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanmskmax( N, x1, 2, mask1, 2 )\n    2.0\n\nbase.strided.nanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a strided array according to a mask,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n    > var mask = [ 0, 0, 0, 1, 0 ];\n    > base.strided.nanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmskmax, base.strided.mskmax, base.strided.nanmax, base.strided.nanmskmin, base.strided.snanmskmax\n","base.strided.nanmskmax.ndarray":"\nbase.strided.nanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a strided array according to a mask,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n    > var mask = [ 0, 0, 0, 1, 0 ];\n    > base.strided.nanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmskmax, base.strided.mskmax, base.strided.nanmax, base.strided.nanmskmin, base.strided.snanmskmax","base.strided.nanmskmin":"\nbase.strided.nanmskmin( N, x, strideX, mask, strideMask )\n    Computes the minimum value of a strided array according to a mask and\n    ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, -4.0, 2.0, NaN ];\n    > var mask = [ 0, 0, 1, 0, 0 ];\n    > base.strided.nanmskmin( x.length, x, 1, mask, 1 )\n    -2.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmskmin( N, x, 2, mask, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanmskmin( N, x1, 2, mask1, 2 )\n    -2.0\n\nbase.strided.nanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a strided array according to a mask, ignoring\n    `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, -4.0, NaN ];\n    > var mask = [ 0, 0, 0, 1, 0 ];\n    > base.strided.nanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dnanmskmin, base.strided.mskmin, base.strided.nanmin, base.strided.nanmskmax, base.strided.snanmskmin\n","base.strided.nanmskmin.ndarray":"\nbase.strided.nanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a strided array according to a mask, ignoring\n    `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, -4.0, NaN ];\n    > var mask = [ 0, 0, 0, 1, 0 ];\n    > base.strided.nanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dnanmskmin, base.strided.mskmin, base.strided.nanmin, base.strided.nanmskmax, base.strided.snanmskmin","base.strided.nanmskrange":"\nbase.strided.nanmskrange( N, x, strideX, mask, strideMask )\n    Computes the range of a strided array according to a mask and ignoring `NaN`\n    values.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\n    > var mask = [ 0, 0, 1, 0, 0 ];\n    > base.strided.nanmskrange( x.length, x, 1, mask, 1 )\n    4.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmskrange( N, x, 2, mask, 2 )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanmskrange( N, x1, 2, mask1, 2 )\n    4.0\n\nbase.strided.nanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a strided array according to a mask, ignoring `NaN`\n    values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n    > var mask = [ 0, 0, 0, 1, 0 ];\n    > base.strided.nanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dnanmskrange, base.strided.mskrange, base.strided.nanrange, base.strided.nanmskmax, base.strided.nanmskmin, base.strided.snanmskrange\n","base.strided.nanmskrange.ndarray":"\nbase.strided.nanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a strided array according to a mask, ignoring `NaN`\n    values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n    > var mask = [ 0, 0, 0, 1, 0 ];\n    > base.strided.nanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dnanmskrange, base.strided.mskrange, base.strided.nanrange, base.strided.nanmskmax, base.strided.nanmskmin, base.strided.snanmskrange","base.strided.nanrange":"\nbase.strided.nanrange( N, x, stride )\n    Computes the range of a strided array, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanrange( x.length, x, 1 )\n    4.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanrange( N, x, stride )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanrange( N, x1, stride )\n    4.0\n\nbase.strided.nanrange.ndarray( N, x, stride, offset )\n    Computes the range of a strided array, ignoring `NaN` values and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanrange.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanrange.ndarray( N, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dnanrange, base.strided.nanmax, base.strided.nanmin, base.strided.range, base.strided.snanrange\n","base.strided.nanrange.ndarray":"\nbase.strided.nanrange.ndarray( N, x, stride, offset )\n    Computes the range of a strided array, ignoring `NaN` values and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanrange.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanrange.ndarray( N, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dnanrange, base.strided.nanmax, base.strided.nanmin, base.strided.range, base.strided.snanrange","base.strided.nanrangeBy":"\nbase.strided.nanrangeBy( N, x, stride, clbk[, thisArg] )\n    Calculates the range of a strided array via a callback function, ignoring\n    `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - aidx: array index.\n    - sidx: strided index (offset + aidx*stride).\n    - array: the input array.\n\n    The callback function should return a numeric value.\n\n    If the callback function returns `NaN`, the value is ignored.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n    > base.strided.nanrangeBy( x.length, x, 1, accessor )\n    18.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0, 1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanrangeBy( N, x, 2, accessor )\n    14.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanrangeBy( N, x1, 2, accessor )\n    8.0\n\nbase.strided.nanrangeBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the range of a strided array via a callback function, ignoring\n    `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n    > base.strided.nanrangeBy.ndarray( x.length, x, 1, 0, accessor )\n    18.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanrangeBy.ndarray( N, x, 2, 1, accessor )\n    8.0\n\n    See Also\n    --------\n    base.strided.dnanrange, base.strided.nanmaxBy, base.strided.nanminBy, base.strided.nanrange, base.strided.rangeBy, base.strided.snanrange\n","base.strided.nanrangeBy.ndarray":"\nbase.strided.nanrangeBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the range of a strided array via a callback function, ignoring\n    `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n    > base.strided.nanrangeBy.ndarray( x.length, x, 1, 0, accessor )\n    18.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanrangeBy.ndarray( N, x, 2, 1, accessor )\n    8.0\n\n    See Also\n    --------\n    base.strided.dnanrange, base.strided.nanmaxBy, base.strided.nanminBy, base.strided.nanrange, base.strided.rangeBy, base.strided.snanrange","base.strided.nanstdev":"\nbase.strided.nanstdev( N, correction, x, stride )\n    Computes the standard deviation of a strided array ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdev( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdev( N, 1, x, 2 )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanstdev( N, 1, x1, 2 )\n    ~2.0817\n\nbase.strided.nanstdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.nanvariance, base.strided.snanstdev, base.strided.stdev\n","base.strided.nanstdev.ndarray":"\nbase.strided.nanstdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.nanvariance, base.strided.snanstdev, base.strided.stdev","base.strided.nanstdevch":"\nbase.strided.nanstdevch( N, correction, x, stride )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevch( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevch( N, 1, x, 2 )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanstdevch( N, 1, x1, 2 )\n    ~2.0817\n\nbase.strided.nanstdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass trial mean algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevch, base.strided.nanvariancech, base.strided.nanstdev, base.strided.snanstdevch, base.strided.stdevch\n","base.strided.nanstdevch.ndarray":"\nbase.strided.nanstdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass trial mean algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevch, base.strided.nanvariancech, base.strided.nanstdev, base.strided.snanstdevch, base.strided.stdevch","base.strided.nanstdevpn":"\nbase.strided.nanstdevpn( N, correction, x, stride )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevpn( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevpn( N, 1, x, 2 )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanstdevpn( N, 1, x1, 2 )\n    ~2.0817\n\nbase.strided.nanstdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevpn, base.strided.nanvariancepn, base.strided.nanstdev, base.strided.snanstdevpn, base.strided.stdevpn\n","base.strided.nanstdevpn.ndarray":"\nbase.strided.nanstdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevpn, base.strided.nanvariancepn, base.strided.nanstdev, base.strided.snanstdevpn, base.strided.stdevpn","base.strided.nanstdevtk":"\nbase.strided.nanstdevtk( N, correction, x, stride )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevtk( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevtk( N, 1, x, 2 )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanstdevtk( N, 1, x1, 2 )\n    ~2.0817\n\nbase.strided.nanstdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass textbook algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevtk, base.strided.nanvariancetk, base.strided.nanstdev, base.strided.snanstdevtk, base.strided.stdevtk\n","base.strided.nanstdevtk.ndarray":"\nbase.strided.nanstdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass textbook algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevtk, base.strided.nanvariancetk, base.strided.nanstdev, base.strided.snanstdevtk, base.strided.stdevtk","base.strided.nanstdevwd":"\nbase.strided.nanstdevwd( N, correction, x, stride )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevwd( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevwd( N, 1, x, 2 )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanstdevwd( N, 1, x1, 2 )\n    ~2.0817\n\nbase.strided.nanstdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevwd, base.strided.nanvariancewd, base.strided.nanstdev, base.strided.snanstdevwd, base.strided.stdevwd\n","base.strided.nanstdevwd.ndarray":"\nbase.strided.nanstdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevwd, base.strided.nanvariancewd, base.strided.nanstdev, base.strided.snanstdevwd, base.strided.stdevwd","base.strided.nanstdevyc":"\nbase.strided.nanstdevyc( N, correction, x, stride )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass algorithm proposed by Youngs and Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevyc( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevyc( N, 1, x, 2 )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanstdevyc( N, 1, x1, 2 )\n    ~2.0817\n\nbase.strided.nanstdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass algorithm proposed by Youngs and Cramer and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevyc, base.strided.nanvarianceyc, base.strided.nanstdev, base.strided.snanstdevyc, base.strided.stdevyc\n","base.strided.nanstdevyc.ndarray":"\nbase.strided.nanstdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass algorithm proposed by Youngs and Cramer and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevyc, base.strided.nanvarianceyc, base.strided.nanstdev, base.strided.snanstdevyc, base.strided.stdevyc","base.strided.nanvariance":"\nbase.strided.nanvariance( N, correction, x, stride )\n    Computes the variance of a strided array ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariance( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanvariance( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanvariance( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.nanvariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariance, base.strided.nanstdev, base.strided.snanvariance, base.strided.variance\n","base.strided.nanvariance.ndarray":"\nbase.strided.nanvariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariance, base.strided.nanstdev, base.strided.snanvariance, base.strided.variance","base.strided.nanvariancech":"\nbase.strided.nanvariancech( N, correction, x, stride )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancech( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanvariancech( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanvariancech( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.nanvariancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass trial mean algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvariancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancech, base.strided.nanstdevch, base.strided.nanvariance, base.strided.snanvariancech, base.strided.variancech\n","base.strided.nanvariancech.ndarray":"\nbase.strided.nanvariancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass trial mean algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvariancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancech, base.strided.nanstdevch, base.strided.nanvariance, base.strided.snanvariancech, base.strided.variancech","base.strided.nanvariancepn":"\nbase.strided.nanvariancepn( N, correction, x, stride )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancepn( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanvariancepn( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanvariancepn( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.nanvariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancepn, base.strided.nanstdevpn, base.strided.nanvariance, base.strided.snanvariancepn, base.strided.variancepn\n","base.strided.nanvariancepn.ndarray":"\nbase.strided.nanvariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancepn, base.strided.nanstdevpn, base.strided.nanvariance, base.strided.snanvariancepn, base.strided.variancepn","base.strided.nanvariancetk":"\nbase.strided.nanvariancetk( N, correction, x, stride )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancetk( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanvariancetk( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanvariancetk( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.nanvariancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass textbook algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvariancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancetk, base.strided.nanstdevtk, base.strided.nanvariance, base.strided.snanvariancetk, base.strided.variancetk\n","base.strided.nanvariancetk.ndarray":"\nbase.strided.nanvariancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass textbook algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvariancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancetk, base.strided.nanstdevtk, base.strided.nanvariance, base.strided.snanvariancetk, base.strided.variancetk","base.strided.nanvariancewd":"\nbase.strided.nanvariancewd( N, correction, x, stride )\n    Computes the variance of a strided array ignoring `NaN` values and using\n    Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancewd( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanvariancewd( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanvariancewd( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.nanvariancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using\n    Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvariancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancewd, base.strided.nanstdevwd, base.strided.nanvariance, base.strided.snanvariancewd, base.strided.variancewd\n","base.strided.nanvariancewd.ndarray":"\nbase.strided.nanvariancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using\n    Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvariancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancewd, base.strided.nanstdevwd, base.strided.nanvariance, base.strided.snanvariancewd, base.strided.variancewd","base.strided.nanvarianceyc":"\nbase.strided.nanvarianceyc( N, correction, x, stride )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass algorithm proposed by Youngs and Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvarianceyc( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanvarianceyc( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanvarianceyc( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.nanvarianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass algorithm proposed by Youngs and Cramer and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvarianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvarianceyc, base.strided.nanstdevyc, base.strided.nanvariance, base.strided.snanvarianceyc, base.strided.varianceyc\n","base.strided.nanvarianceyc.ndarray":"\nbase.strided.nanvarianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass algorithm proposed by Youngs and Cramer and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvarianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvarianceyc, base.strided.nanstdevyc, base.strided.nanvariance, base.strided.snanvarianceyc, base.strided.varianceyc","base.strided.nullary":"\nbase.strided.nullary( arrays, shape, strides, fcn )\n    Applies a nullary callback and assigns results to elements in a strided\n    output array.\n\n    The `shape` and `strides` parameters determine which elements in the strided\n    output array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride length for the strided output\n        array.\n\n    fcn: Function\n        Nullary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1 ];\n    > var fcn = constantFunction( 3.0 );\n    > base.strided.nullary( [ x ], shape, strides, fcn );\n    > x\n    <Float64Array>[ 3.0, 3.0, 3.0, 3.0 ]\n\n\nbase.strided.nullary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a nullary callback and assigns results to elements in a strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride length for the strided output\n        array.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting index (i.e., index offset) for\n        the strided output array.\n\n    fcn: Function\n        Nullary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1 ];\n    > var offsets = [ 0 ];\n    > var fcn = constantFunction( 3.0 );\n    > base.strided.nullary.ndarray( [ x ], shape, strides, offsets, fcn );\n    > x\n    <Float64Array>[ 3.0, 3.0, 3.0, 3.0 ]\n\n    See Also\n    --------\n    base.strided.binary, base.strided.quaternary, base.strided.quinary, base.strided.ternary, base.strided.unary\n","base.strided.nullary.ndarray":"\nbase.strided.nullary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a nullary callback and assigns results to elements in a strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride length for the strided output\n        array.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting index (i.e., index offset) for\n        the strided output array.\n\n    fcn: Function\n        Nullary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1 ];\n    > var offsets = [ 0 ];\n    > var fcn = constantFunction( 3.0 );\n    > base.strided.nullary.ndarray( [ x ], shape, strides, offsets, fcn );\n    > x\n    <Float64Array>[ 3.0, 3.0, 3.0, 3.0 ]\n\n    See Also\n    --------\n    base.strided.binary, base.strided.quaternary, base.strided.quinary, base.strided.ternary, base.strided.unary","base.strided.offsetView":"\nbase.strided.offsetView( x, offset )\n    Returns a typed array view having the same data type as a provided input\n    typed array and starting at a specified index offset.\n\n    Parameters\n    ----------\n    x: TypedArray\n        Input array.\n\n    offset: integer\n        Starting index of the view relative to the input array.\n\n    Returns\n    -------\n    out: TypedArray\n        Typed array view having the same data type as the input array.\n\n    Examples\n    --------\n    > var x = new Float64Array( 10 );\n    > var out = base.strided.offsetView( x, 0 )\n    <Float64Array>\n    > var bool = ( out.buffer === x.buffer )\n    true\n\n    See Also\n    --------\n    base.strided.minViewBufferIndex\n","base.strided.quaternary":"\nbase.strided.quaternary( arrays, shape, strides, fcn )\n    Applies a quaternary callback to strided input array elements and assigns\n    results to elements in a strided output array.\n\n    The `shape` and `strides` parameters determine which elements in the strided\n    input and output arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing four strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    fcn: Function\n        Quaternary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1, 1, 1 ];\n    > function f( x, y, z, w ) { return x + y + z + w; };\n    > base.strided.quaternary( [ x, y, z, w, u ], shape, strides, f );\n    > u\n    <Float64Array>[ 4.0, 8.0, 12.0, 16.0 ]\n\n\nbase.strided.quaternary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a quaternary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing four strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Quaternary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1, 1, 1 ];\n    > var offsets = [ 0, 0, 0, 0, 0 ];\n    > function f( x, y, z, w ) { return x + y + z + w; };\n    > base.strided.quaternary.ndarray( [ x, y, z, w, u ], shape, strides, offsets, f );\n    > u\n    <Float64Array>[ 4.0, 8.0, 12.0, 16.0 ]\n\n    See Also\n    --------\n    base.strided.binary, base.strided.nullary, base.strided.quinary, base.strided.ternary, base.strided.unary\n","base.strided.quaternary.ndarray":"\nbase.strided.quaternary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a quaternary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing four strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Quaternary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1, 1, 1 ];\n    > var offsets = [ 0, 0, 0, 0, 0 ];\n    > function f( x, y, z, w ) { return x + y + z + w; };\n    > base.strided.quaternary.ndarray( [ x, y, z, w, u ], shape, strides, offsets, f );\n    > u\n    <Float64Array>[ 4.0, 8.0, 12.0, 16.0 ]\n\n    See Also\n    --------\n    base.strided.binary, base.strided.nullary, base.strided.quinary, base.strided.ternary, base.strided.unary","base.strided.quinary":"\nbase.strided.quinary( arrays, shape, strides, fcn )\n    Applies a quinary callback to strided input array elements and assigns\n    results to elements in a strided output array.\n\n    The `shape` and `strides` parameters determine which elements in the strided\n    input and output arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing five strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    fcn: Function\n        Quinary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1, 1, 1, 1 ];\n    > function f( x, y, z, w, u ) { return x + y + z + w + u; };\n    > base.strided.quinary( [ x, y, z, w, u, v ], shape, strides, f );\n    > v\n    <Float64Array>[ 5.0, 10.0, 15.0, 20.0 ]\n\n\nbase.strided.quinary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a quinary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing five strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Quinary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1, 1, 1, 1 ];\n    > var offsets = [ 0, 0, 0, 0, 0, 0 ];\n    > function f( x, y, z, w, u ) { return x + y + z + w + u; };\n    > base.strided.quinary.ndarray( [ x, y, z, w, u, v ], shape, strides, offsets, f );\n    > v\n    <Float64Array>[ 5.0, 10.0, 15.0, 20.0 ]\n\n    See Also\n    --------\n    base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.ternary, base.strided.unary\n","base.strided.quinary.ndarray":"\nbase.strided.quinary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a quinary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing five strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Quinary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1, 1, 1, 1 ];\n    > var offsets = [ 0, 0, 0, 0, 0, 0 ];\n    > function f( x, y, z, w, u ) { return x + y + z + w + u; };\n    > base.strided.quinary.ndarray( [ x, y, z, w, u, v ], shape, strides, offsets, f );\n    > v\n    <Float64Array>[ 5.0, 10.0, 15.0, 20.0 ]\n\n    See Also\n    --------\n    base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.ternary, base.strided.unary","base.strided.range":"\nbase.strided.range( N, x, stride )\n    Computes the range of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.range( x.length, x, 1 )\n    4.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.range( N, x, stride )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.range( N, x1, stride )\n    4.0\n\nbase.strided.range.ndarray( N, x, stride, offset )\n    Computes the range of a strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.range.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.range.ndarray( N, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.drange, base.strided.max, base.strided.min, base.strided.nanrange, base.strided.srange\n","base.strided.range.ndarray":"\nbase.strided.range.ndarray( N, x, stride, offset )\n    Computes the range of a strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.range.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.range.ndarray( N, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.drange, base.strided.max, base.strided.min, base.strided.nanrange, base.strided.srange","base.strided.rangeBy":"\nbase.strided.rangeBy( N, x, stride, clbk[, thisArg] )\n    Calculates the range of a strided array via a callback function.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - aidx: array index.\n    - sidx: strided index (offset + aidx*stride).\n    - array: the input array.\n\n    The callback function should return a numeric value.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.rangeBy( x.length, x, 1, accessor )\n    18.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.rangeBy( N, x, 2, accessor )\n    12.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.rangeBy( N, x1, 2, accessor )\n    8.0\n\nbase.strided.rangeBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the range of a strided array via a callback function and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.rangeBy.ndarray( x.length, x, 1, 0, accessor )\n    18.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.rangeBy.ndarray( N, x, 2, 1, accessor )\n    8.0\n\n    See Also\n    --------\n    base.strided.drange, base.strided.maxBy, base.strided.minBy, base.strided.nanrangeBy, base.strided.range, base.strided.srange\n","base.strided.rangeBy.ndarray":"\nbase.strided.rangeBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the range of a strided array via a callback function and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.rangeBy.ndarray( x.length, x, 1, 0, accessor )\n    18.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.rangeBy.ndarray( N, x, 2, 1, accessor )\n    8.0\n\n    See Also\n    --------\n    base.strided.drange, base.strided.maxBy, base.strided.minBy, base.strided.nanrangeBy, base.strided.range, base.strided.srange","base.strided.reinterpretComplex":"\nbase.strided.reinterpretComplex( x, offset )\n    Returns a real-valued floating-point array view of a complex-valued\n    floating-point array having the same precision.\n\n    Parameters\n    ----------\n    x: Complex128Array|Complex64Array\n        Input array.\n\n    offset: integer\n        Starting index of the view relative to the input array.\n\n    Returns\n    -------\n    out: Float64Array|Float32Array\n        Real-valued floating-point array view.\n\n    Examples\n    --------\n    > var x = new Complex128Array( 10 );\n    > var out = base.strided.reinterpretComplex( x, 0 )\n    <Float64Array>\n    > var bool = ( out.buffer === x.buffer )\n    true\n    > x = new Complex64Array( 10 );\n    > out = base.strided.reinterpretComplex( x, 0 )\n    <Float32Array>\n    > bool = ( out.buffer === x.buffer )\n    true\n\n    See Also\n    --------\n    base.strided.reinterpretComplex128, base.strided.reinterpretComplex64\n","base.strided.reinterpretComplex64":"\nbase.strided.reinterpretComplex64( x, offset )\n    Returns a Float32Array view of a Complex64Array.\n\n    Parameters\n    ----------\n    x: Complex64Array\n        Input array.\n\n    offset: integer\n        Starting index of the view relative to the Complex64Array.\n\n    Returns\n    -------\n    out: Float32Array\n        Float32Array view.\n\n    Examples\n    --------\n    > var x = new Complex64Array( 10 );\n    > var out = base.strided.reinterpretComplex64( x, 0 )\n    <Float32Array>\n    > var bool = ( out.buffer === x.buffer )\n    true\n\n    See Also\n    --------\n    base.strided.reinterpretComplex, base.strided.reinterpretComplex128\n","base.strided.reinterpretComplex128":"\nbase.strided.reinterpretComplex128( x, offset )\n    Returns a Float64Array view of a Complex128Array.\n\n    Parameters\n    ----------\n    x: Complex128Array\n        Input array.\n\n    offset: integer\n        Starting index of the view relative to the Complex128Array.\n\n    Returns\n    -------\n    out: Float64Array\n        Float64Array view.\n\n    Examples\n    --------\n    > var x = new Complex128Array( 10 );\n    > var out = base.strided.reinterpretComplex128( x, 0 )\n    <Float64Array>\n    > var bool = ( out.buffer === x.buffer )\n    true\n\n    See Also\n    --------\n    base.strided.reinterpretComplex, base.strided.reinterpretComplex64\n","base.strided.sabs":"\nbase.strided.sabs( N, x, strideX, y, strideY )\n    Computes the absolute value for each element in a single-precision floating-\n    point strided array `x` and assigns the results to elements in a single-\n    precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sabs( x.length, x, 1, y, 1 )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sabs( N, x, 2, y, -1 )\n    <Float32Array>[ 3.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.sabs( N, x1, -2, y1, 1 )\n    <Float32Array>[ 4.0, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.sabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the absolute value for each element in a single-precision floating-\n    point strided array `x` and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    strided.abs, base.strided.dabs, base.strided.sabs2\n","base.strided.sabs.ndarray":"\nbase.strided.sabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the absolute value for each element in a single-precision floating-\n    point strided array `x` and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    strided.abs, base.strided.dabs, base.strided.sabs2","base.strided.sabs2":"\nbase.strided.sabs2( N, x, strideX, y, strideY )\n    Computes the squared absolute value for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sabs2( x.length, x, 1, y, 1 )\n    <Float32Array>[ 1.0, 4.0, 9.0, 16.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sabs2( N, x, 2, y, -1 )\n    <Float32Array>[ 9.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.sabs2( N, x1, -2, y1, 1 )\n    <Float32Array>[ 16.0, 4.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 16.0, 4.0 ]\n\n\nbase.strided.sabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the squared absolute value for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 4.0, 9.0, 16.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 16.0, 4.0 ]\n\n    See Also\n    --------\n    strided.abs2, base.strided.dabs2, base.strided.sabs\n","base.strided.sabs2.ndarray":"\nbase.strided.sabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the squared absolute value for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 4.0, 9.0, 16.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 16.0, 4.0 ]\n\n    See Also\n    --------\n    strided.abs2, base.strided.dabs2, base.strided.sabs","base.strided.sapx":"\nbase.strided.sapx( N, alpha, x, stride )\n    Adds a constant to each element in a single-precision floating-point strided\n    array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns the strided array unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sapx( x.length, 5.0, x, 1 )\n    <Float32Array>[ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sapx( 3, 5.0, x, 2 )\n    <Float32Array>[ 3.0, 1.0, 8.0, -5.0, 9.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sapx( 3, 5.0, x1, 2 )\n    <Float32Array>[ 3.0, 3.0, 1.0, 5.0, -1.0 ]\n    > x0\n    <Float32Array>[ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n\nbase.strided.sapx.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each element in a single-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sapx.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float32Array>[ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.sapx.ndarray( 3, 5.0, x, 2, 1 )\n    <Float32Array>[ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dapx, base.strided.gapx\n","base.strided.sapx.ndarray":"\nbase.strided.sapx.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each element in a single-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sapx.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float32Array>[ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.sapx.ndarray( 3, 5.0, x, 2, 1 )\n    <Float32Array>[ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dapx, base.strided.gapx","base.strided.sapxsum":"\nbase.strided.sapxsum( N, alpha, x, stride )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum.\n\n    The `N` and stride parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsum( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.sapxsum( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sapxsum( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.sapxsum.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sapxsum.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.gapxsum, base.strided.sapxsumpw, base.strided.ssum\n","base.strided.sapxsum.ndarray":"\nbase.strided.sapxsum.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sapxsum.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.gapxsum, base.strided.sapxsumpw, base.strided.ssum","base.strided.sapxsumkbn":"\nbase.strided.sapxsumkbn( N, alpha, x, stride )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using an improved Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumkbn( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.sapxsumkbn( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sapxsumkbn( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.sapxsumkbn.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumkbn, base.strided.gapxsumkbn, base.strided.sapxsum, base.strided.ssumkbn\n","base.strided.sapxsumkbn.ndarray":"\nbase.strided.sapxsumkbn.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumkbn, base.strided.gapxsumkbn, base.strided.sapxsum, base.strided.ssumkbn","base.strided.sapxsumkbn2":"\nbase.strided.sapxsumkbn2( N, alpha, x, stride )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using a second-order iterative Kahan–Babuška\n    algorithm.\n\n    The `N` and `stride` parameters determine which elements in the \n    strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumkbn2( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.sapxsumkbn2( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sapxsumkbn2( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.sapxsumkbn2.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsum, base.strided.ssumkbn2\n","base.strided.sapxsumkbn2.ndarray":"\nbase.strided.sapxsumkbn2.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsum, base.strided.ssumkbn2","base.strided.sapxsumors":"\nbase.strided.sapxsumors( N, alpha, x, stride )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using ordinary recursive summation.\n\n    The `N` and `stride` parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumors( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sapxsumors( N, 5.0, x, stride )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sapxsumors( N, 5.0, x1, stride )\n    14.0\n\n\nbase.strided.sapxsumors.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using ordinary recursive summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sapxsumors.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumors, base.strided.gapxsumors, base.strided.sapxsum, base.strided.ssumors\n","base.strided.sapxsumors.ndarray":"\nbase.strided.sapxsumors.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using ordinary recursive summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sapxsumors.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumors, base.strided.gapxsumors, base.strided.sapxsum, base.strided.ssumors","base.strided.sapxsumpw":"\nbase.strided.sapxsumpw( N, alpha, x, stride )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using pairwise summation.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumpw( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var stride = 2;\n    > base.strided.sapxsumpw( 3, 5.0, x, stride )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > stride = 2;\n    > base.strided.sapxsumpw( 3, 5.0, x1, stride )\n    14.0\n\n\nbase.strided.sapxsumpw.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using pairwise summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumpw, base.strided.gapxsumpw, base.strided.sapxsum, base.strided.ssumpw\n","base.strided.sapxsumpw.ndarray":"\nbase.strided.sapxsumpw.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using pairwise summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumpw, base.strided.gapxsumpw, base.strided.sapxsum, base.strided.ssumpw","base.strided.sasum":"\nbase.strided.sasum( N, x, stride )\n    Computes the sum of the absolute values.\n\n    The sum of absolute values corresponds to the *L1* norm.\n\n    The `N` and stride parameters determine which elements in `x` are used to\n    compute the sum.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the function returns `0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    sum: float\n        Sum of absolute values.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n    > var s = base.strided.sasum( x.length, x, 1 )\n    15.0\n\n    // Sum every other value:\n    > s = base.strided.sasum( 3, x, 2 )\n    9.0\n\n    // Use view offset; e.g., starting at 2nd element:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > s = base.strided.sasum( 3, x1, 2 )\n    12.0\n\n\nbase.strided.sasum.ndarray( N, x, stride, offset )\n    Computes the sum of absolute values using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    sum: float\n        Sum of absolute values.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n    > var s = base.strided.sasum.ndarray( x.length, x, 1, 0 )\n    15.0\n\n    // Sum the last three elements:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > s = base.strided.sasum.ndarray( 3, x, -1, x.length-1 )\n    15.0\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.gasum\n","base.strided.sasum.ndarray":"\nbase.strided.sasum.ndarray( N, x, stride, offset )\n    Computes the sum of absolute values using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    sum: float\n        Sum of absolute values.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n    > var s = base.strided.sasum.ndarray( x.length, x, 1, 0 )\n    15.0\n\n    // Sum the last three elements:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > s = base.strided.sasum.ndarray( 3, x, -1, x.length-1 )\n    15.0\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.gasum","base.strided.sasumpw":"\nbase.strided.sasumpw( N, x, stride )\n    Computes the sum of absolute values (L1 norm) of single-precision floating-\n    point strided array elements using pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in the strided \n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sasumpw( x.length, x, 1 )\n    5.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.sasumpw( 3, x, 2 )\n    5.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sasumpw( 3, x1, 2 )\n    5.0\n\n\nbase.strided.sasumpw.ndarray( N, x, stride, offset )\n    Computes the sum of absolute values (L1 norm) of single-precision floating-\n    point strided array elements using pairwise summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sasumpw.ndarray( x.length, x, 1, 0 )\n    5.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sasumpw.ndarray( 3, x, 2, 1 )\n    5.0\n\n    See Also\n    --------\n    base.strided.sasum, base.strided.dasumpw, base.strided.gasumpw, base.strided.ssumpw\n","base.strided.sasumpw.ndarray":"\nbase.strided.sasumpw.ndarray( N, x, stride, offset )\n    Computes the sum of absolute values (L1 norm) of single-precision floating-\n    point strided array elements using pairwise summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sasumpw.ndarray( x.length, x, 1, 0 )\n    5.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sasumpw.ndarray( 3, x, 2, 1 )\n    5.0\n\n    See Also\n    --------\n    base.strided.sasum, base.strided.dasumpw, base.strided.gasumpw, base.strided.ssumpw","base.strided.saxpy":"\nbase.strided.saxpy( N, alpha, x, strideX, y, strideY )\n    Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > var alpha = 5.0;\n    > base.strided.saxpy( x.length, alpha, x, 1, y, 1 )\n    <Float32Array>[ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > base.strided.saxpy( 3, alpha, x, 2, y, -1 )\n    <Float32Array>[ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.saxpy( 3, 5.0, x1, -2, y1, 1 )\n    <Float32Array>[ 40.0, 31.0, 22.0 ]\n    > y0\n    <Float32Array>[ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.strided.saxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n    Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > var alpha = 5.0;\n    > base.strided.saxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.saxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n    See Also\n    --------\n    base.strided.daxpy, base.strided.gaxpy\n","base.strided.saxpy.ndarray":"\nbase.strided.saxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n    Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > var alpha = 5.0;\n    > base.strided.saxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.saxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n    See Also\n    --------\n    base.strided.daxpy, base.strided.gaxpy","base.strided.scbrt":"\nbase.strided.scbrt( N, x, strideX, y, strideY )\n    Computes the cube root of each element in a single-precision floating-point \n    strided array `x` and assigns the results to elements in a single-precision \n    floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.scbrt( x.length, x, 1, y, 1 )\n    <Float32Array>[ 0.0, 1.0, 2.0, 3.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.scbrt( N, x, 2, y, -1 )\n    <Float32Array>[ 2.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.scbrt( N, x1, -2, y1, 1 )\n    <Float32Array>[ 3.0, 1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.scbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cube root of each element in a single-precision floating-point \n    strided array `x` and assigns the results to elements in a single-precision \n    floating-point strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.scbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, 1.0, 2.0, 3.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.scbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dcbrt, strided.cbrt, base.strided.ssqrt\n","base.strided.scbrt.ndarray":"\nbase.strided.scbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cube root of each element in a single-precision floating-point \n    strided array `x` and assigns the results to elements in a single-precision \n    floating-point strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.scbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, 1.0, 2.0, 3.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.scbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dcbrt, strided.cbrt, base.strided.ssqrt","base.strided.sceil":"\nbase.strided.sceil( N, x, strideX, y, strideY )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward positive infinity and assigns the results to elements in a single-\n    precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sceil( x.length, x, 1, y, 1 )\n    <Float32Array>[ 2.0, 3.0, -3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sceil( N, x, 2, y, -1 )\n    <Float32Array>[ -3.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.sceil( N, x1, -2, y1, 1 )\n    <Float32Array>[ 4.0, 3.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.sceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward positive infinity and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 2.0, 3.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n    See Also\n    --------\n    strided.ceil, base.strided.dceil, base.strided.sfloor, base.strided.strunc\n","base.strided.sceil.ndarray":"\nbase.strided.sceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward positive infinity and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 2.0, 3.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n    See Also\n    --------\n    strided.ceil, base.strided.dceil, base.strided.sfloor, base.strided.strunc","base.strided.scopy":"\nbase.strided.scopy( N, x, strideX, y, strideY )\n    Copies values from `x` into `y`.\n\n    The `N` and stride parameters determine how values from `x` are copied\n    into `y`.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.scopy( x.length, x, 1, y, 1 )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.scopy( 3, x, -2, y, 1 )\n    <Float32Array>[ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n    // Using typed array views:\n    > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.scopy( 3, x1, -2, y1, 1 )\n    <Float32Array>[ 6.0, 4.0, 2.0 ]\n    > y0\n    <Float32Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.scopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Copies values from `x` into `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.scopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dcopy, base.strided.gcopy, base.strided.sswap\n","base.strided.scopy.ndarray":"\nbase.strided.scopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Copies values from `x` into `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.scopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dcopy, base.strided.gcopy, base.strided.sswap","base.strided.scumax":"\nbase.strided.scumax( N, x, strideX, y, strideY )\n    Computes the cumulative maximum of single-precision floating-point strided\n    array elements.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scumax( x.length, x, 1, y, 1 )\n    <Float32Array>[ 1.0, 1.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scumax( 3, x, 2, y, 2 )\n    <Float32Array>[ -2.0, 0.0, 1.0, 0.0, 2.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float32Array( x0.length );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.scumax( 3, x1, 2, y1, 1 )\n    <Float32Array>[ -2.0, 2.0, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.0, -2.0, 2.0, 2.0 ]\n\n\nbase.strided.scumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum of single-precision floating-point strided\n    array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 1.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumax, base.strided.dcumax, base.strided.scumin\n","base.strided.scumax.ndarray":"\nbase.strided.scumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum of single-precision floating-point strided\n    array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 1.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumax, base.strided.dcumax, base.strided.scumin","base.strided.scumaxabs":"\nbase.strided.scumaxabs( N, x, strideX, y, strideY )\n    Computes the cumulative maximum absolute value of single-precision floating-\n    point strided array elements.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scumaxabs( x.length, x, 1, y, 1 )\n    <Float32Array>[ 1.0, 2.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.scumaxabs( N, x, 2, y, 2 )\n    <Float32Array>[ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float32Array( x0.length );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.scumaxabs( N, x1, 2, y1, 1 )\n    <Float32Array>[ 2.0, 2.0, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\nbase.strided.scumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum absolute value of single-precision floating-\n    point strided array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.scumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cumaxabs, base.strided.dcumaxabs, base.strided.scumax, base.strided.scuminabs\n","base.strided.scumaxabs.ndarray":"\nbase.strided.scumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum absolute value of single-precision floating-\n    point strided array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.scumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cumaxabs, base.strided.dcumaxabs, base.strided.scumax, base.strided.scuminabs","base.strided.scumin":"\nbase.strided.scumin( N, x, strideX, y, strideY )\n    Computes the cumulative minimum of single-precision floating-point strided\n    array elements.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scumin( x.length, x, 1, y, 1 )\n    <Float32Array>[ 1.0, -2.0, -2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.scumin( N, x, 2, y, 2 )\n    <Float32Array>[ -2.0, 0.0, -2.0, 0.0, -2.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float32Array( x0.length );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.scumin( N, x1, 2, y1, 1 )\n    <Float32Array>[ -2.0, -2.0, -2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\nbase.strided.scumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum of single-precision floating-point strided\n    array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -2.0, -2.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.scumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumin, base.strided.dcumin, base.strided.scumax\n","base.strided.scumin.ndarray":"\nbase.strided.scumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum of single-precision floating-point strided\n    array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -2.0, -2.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.scumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumin, base.strided.dcumin, base.strided.scumax","base.strided.scuminabs":"\nbase.strided.scuminabs( N, x, strideX, y, strideY )\n    Computes the cumulative minimum absolute value of single-precision floating-\n    point strided array elements.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scuminabs( x.length, x, 1, y, 1 )\n    <Float32Array>[ 1.0, 1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.scuminabs( N, x, 2, y, 2 )\n    <Float32Array>[ 2.0, 0.0, 1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float32Array( x0.length );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.scuminabs( N, x1, 2, y1, 1 )\n    <Float32Array>[ 2.0, 2.0, 1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 1.0 ]\n\nbase.strided.scuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum absolute value of single-precision floating-\n    point strided array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.scuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cuminabs, base.strided.dcuminabs, base.strided.scumaxabs, base.strided.scumin\n","base.strided.scuminabs.ndarray":"\nbase.strided.scuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum absolute value of single-precision floating-\n    point strided array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.scuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cuminabs, base.strided.dcuminabs, base.strided.scumaxabs, base.strided.scumin","base.strided.scusum":"\nbase.strided.scusum( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements.\n\n    The `N` and `stride` parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusum( x.length, 0.0, x, 1, y, 1 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusum( 3, 0.0, x, 2, y, 2 )\n    <Float32Array>[ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float32Array( x0.length );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.scusum( 3, 0.0, x1, 2, y1, 1 )\n    <Float32Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusum, base.strided.scusumpw\n","base.strided.scusum.ndarray":"\nbase.strided.scusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusum, base.strided.scusumpw","base.strided.scusumkbn":"\nbase.strided.scusumkbn( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using an improved Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumkbn( x.length, 0.0, x, 1, y, 1 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumkbn( 3, 0.0, x, 2, y, 2 )\n    <Float32Array>[ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float32Array( x0.length );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.scusumkbn( N, 0.0, x1, 2, y1, 1 )\n    <Float32Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumkbn, base.strided.gcusumkbn, base.strided.scusum, base.strided.scusumkbn2\n","base.strided.scusumkbn.ndarray":"\nbase.strided.scusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumkbn, base.strided.gcusumkbn, base.strided.scusum, base.strided.scusumkbn2","base.strided.scusumkbn2":"\nbase.strided.scusumkbn2( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of single-precision floating-point strided \n    array elements using a second-order iterative Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use \n    a typed array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumkbn2( x.length, 0.0, x, 1, y, 1 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumkbn2( 3, 0.0, x, 2, y, 2 )\n    <Float32Array>[ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float32Array( x0.length );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.scusumkbn2( N, 0.0, x1, 2, y1, 1 )\n    <Float32Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of single-precision floating-point strided\n    array elements using a second-order iterative Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameter supports indexing semantics\n    based on starting indices.\n\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n\n    See Also\n    --------\n    base.strided.dcusumkbn2, base.strided.gcusumkbn2, base.strided.scusum, base.strided.scusumkbn\n","base.strided.scusumkbn2.ndarray":"\nbase.strided.scusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of single-precision floating-point strided\n    array elements using a second-order iterative Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameter supports indexing semantics\n    based on starting indices.\n\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n\n    See Also\n    --------\n    base.strided.dcusumkbn2, base.strided.gcusumkbn2, base.strided.scusum, base.strided.scusumkbn","base.strided.scusumors":"\nbase.strided.scusumors( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using ordinary recursive summation.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n     are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumors( x.length, 0.0, x, 1, y, 1 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumors( 3, 0.0, x, 2, y, 2 )\n    <Float32Array>[ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float32Array( x0.length );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.scusumors( 3, 0.0, x1, 2, y1, 1 )\n    <Float32Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using ordinary recursive summation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumors, base.strided.gcusumors, base.strided.scusum\n","base.strided.scusumors.ndarray":"\nbase.strided.scusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using ordinary recursive summation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumors, base.strided.gcusumors, base.strided.scusum","base.strided.scusumpw":"\nbase.strided.scusumpw( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using pairwise summation.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumpw( x.length, 0.0, x, 1, y, 1 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumpw( 3, 0.0, x, 2, y, 2 )\n    <Float32Array>[ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float32Array( x0.length );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.scusumpw( 3, 0.0, x1, 2, y1, 1 )\n    <Float32Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumpw, base.strided.gcusumpw, base.strided.scusum\n","base.strided.scusumpw.ndarray":"\nbase.strided.scusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumpw, base.strided.gcusumpw, base.strided.scusum","base.strided.sdeg2rad":"\nbase.strided.sdeg2rad( N, x, strideX, y, strideY )\n    Converts each element in a single-precision floating-point strided array `x`\n    from degrees to radians and assigns the results to elements in a single-\n    precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sdeg2rad( x.length, x, 1, y, 1 )\n    <Float32Array>[ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sdeg2rad( N, x, 2, y, -1 )\n    <Float32Array>[ ~0.785, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.sdeg2rad( N, x1, -2, y1, 1 )\n    <Float32Array>[ ~1.047, ~0.524 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.sdeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Converts each element in a single-precision floating-point strided array `x`\n    from degrees to radians and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sdeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sdeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n    See Also\n    --------\n    base.strided.ddeg2rad, strided.deg2rad\n","base.strided.sdeg2rad.ndarray":"\nbase.strided.sdeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Converts each element in a single-precision floating-point strided array `x`\n    from degrees to radians and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sdeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sdeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n    See Also\n    --------\n    base.strided.ddeg2rad, strided.deg2rad","base.strided.sdot":"\nbase.strided.sdot( N, x, strideX, y, strideY )\n    Computes the dot product of two single-precision floating-point vectors.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: float\n        The dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var out = base.strided.sdot( x.length, x, 1, y, 1 )\n    -5.0\n\n    // Strides:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > out = base.strided.sdot( 3, x, 2, y, -1 )\n    9.0\n\n    // Using view offsets:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n    > out = base.strided.sdot( 3, x1, -2, y1, 1 )\n    128.0\n\n\nbase.strided.sdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the dot product of two single-precision floating-point vectors\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing based on a starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: float\n        The dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var out = base.strided.sdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    -5.0\n\n    // Strides:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > out = base.strided.sdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n    9.0\n\n    // Using offset indices:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > out = base.strided.sdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n    128.0\n\n    See Also\n    --------\n    base.strided.ddot, base.strided.dsdot, base.strided.sdsdot, sdot\n","base.strided.sdot.ndarray":"\nbase.strided.sdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the dot product of two single-precision floating-point vectors\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing based on a starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: float\n        The dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var out = base.strided.sdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    -5.0\n\n    // Strides:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > out = base.strided.sdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n    9.0\n\n    // Using offset indices:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > out = base.strided.sdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n    128.0\n\n    See Also\n    --------\n    base.strided.ddot, base.strided.dsdot, base.strided.sdsdot, sdot","base.strided.sdsapxsum":"\nbase.strided.sdsapxsum( N, alpha, x, stride )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using extended accumulation.\n\n    The `N` and `stride` parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsapxsum( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.sdsapxsum( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sdsapxsum( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.sdsapxsum.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using extended accumulation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sdsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dsapxsum, base.strided.sapxsum, base.strided.sdssum\n","base.strided.sdsapxsum.ndarray":"\nbase.strided.sdsapxsum.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using extended accumulation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sdsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dsapxsum, base.strided.sapxsum, base.strided.sdssum","base.strided.sdsapxsumpw":"\nbase.strided.sdsapxsumpw( N, alpha, x, stride )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using pairwise summation with extended\n    accumulation.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsapxsumpw( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.sdsapxsumpw( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sdsapxsumpw( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.sdsapxsumpw.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using pairwise summation with extended\n    accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sdsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dsapxsumpw, base.strided.sapxsumpw, base.strided.sdsapxsum, base.strided.sdssumpw","base.strided.sdsapxsumpw.ndarray":"\nbase.strided.sdsapxsumpw.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using pairwise summation with extended\n    accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sdsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dsapxsumpw, base.strided.sapxsumpw, base.strided.sdsapxsum, base.strided.sdssumpw","base.strided.sdsdot":"\nbase.strided.sdsdot( N, scalar, x, strideX, y, strideY )\n    Computes the dot product of two single-precision floating-point vectors with\n    extended accumulation.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0` the function returns the provided scalar constant.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    scalar: number\n        Scalar constant added to dot product.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: number\n        The dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var out = base.strided.sdsdot( x.length, 0.0, x, 1, y, 1 )\n    -5.0\n\n    // Strides:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > out = base.strided.sdsdot( 3, 0.0, x, 2, y, -1 )\n    9.0\n\n    // Using view offsets:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n    > out = base.strided.sdsdot( 3, 0.0, x1, -2, y1, 1 )\n    128.0\n\n\nbase.strided.sdsdot.ndarray( N, scalar, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the dot product of two single-precision floating-point vectors\n    using alternative indexing semantics and with extended accumulation.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing based on a starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    scalar: number\n        Scalar constant added to dot product.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: number\n        The dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var out = base.strided.sdsdot.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    -5.0\n\n    // Strides:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > out = base.strided.sdsdot.ndarray( 3, 0.0, x, 2, 0, y, 2, 0 )\n    9.0\n\n    // Using offset indices:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > out = base.strided.sdsdot.ndarray( 3, 0.0, x, -2, x.length-1, y, 1, 3 )\n    128.0\n\n    References\n    ----------\n    - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n    Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n    Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n    NY, USA: Association for Computing Machinery: 324–25.\n    doi:10.1145/355841.355848.\n\n    See Also\n    --------\n    base.strided.ddot, base.strided.dsdot, base.strided.sdot\n","base.strided.sdsdot.ndarray":"\nbase.strided.sdsdot.ndarray( N, scalar, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the dot product of two single-precision floating-point vectors\n    using alternative indexing semantics and with extended accumulation.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing based on a starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    scalar: number\n        Scalar constant added to dot product.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: number\n        The dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var out = base.strided.sdsdot.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    -5.0\n\n    // Strides:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > out = base.strided.sdsdot.ndarray( 3, 0.0, x, 2, 0, y, 2, 0 )\n    9.0\n\n    // Using offset indices:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > out = base.strided.sdsdot.ndarray( 3, 0.0, x, -2, x.length-1, y, 1, 3 )\n    128.0\n\n    References\n    ----------\n    - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n    Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n    Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n    NY, USA: Association for Computing Machinery: 324–25.\n    doi:10.1145/355841.355848.\n\n    See Also\n    --------\n    base.strided.ddot, base.strided.dsdot, base.strided.sdot","base.strided.sdsmean":"\nbase.strided.sdsmean( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using extended accumulation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsmean( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sdsmean( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sdsmean( N, x1, stride )\n    ~-0.3333\n\nbase.strided.sdsmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using extended accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sdsmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsnanmean, base.strided.smean\n","base.strided.sdsmean.ndarray":"\nbase.strided.sdsmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using extended accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sdsmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsnanmean, base.strided.smean","base.strided.sdsmeanors":"\nbase.strided.sdsmeanors( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation with extended accumulation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsmeanors( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sdsmeanors( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sdsmeanors( N, x1, stride )\n    ~-0.3333\n\nbase.strided.sdsmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation with extended accumulation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sdsmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.sdsmean, base.strided.sdsnanmeanors\n","base.strided.sdsmeanors.ndarray":"\nbase.strided.sdsmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation with extended accumulation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sdsmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.sdsmean, base.strided.sdsnanmeanors","base.strided.sdsnanmean":"\nbase.strided.sdsnanmean( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using extended accumulation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnanmean( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sdsnanmean( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sdsnanmean( N, x1, stride )\n    ~-0.3333\n\nbase.strided.sdsnanmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using extended accumulation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnanmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sdsnanmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.dsnanmean, base.strided.nanmean, base.strided.sdsmean, base.strided.snanmean\n","base.strided.sdsnanmean.ndarray":"\nbase.strided.sdsnanmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using extended accumulation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnanmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sdsnanmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.dsnanmean, base.strided.nanmean, base.strided.sdsmean, base.strided.snanmean","base.strided.sdsnanmeanors":"\nbase.strided.sdsnanmeanors( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation with\n    extended accumulation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnanmeanors( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sdsnanmeanors( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sdsnanmeanors( N, x1, stride )\n    ~-0.3333\n\nbase.strided.sdsnanmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation with\n    extended accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnanmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sdsnanmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.sdsmeanors, base.strided.sdsnanmean\n","base.strided.sdsnanmeanors.ndarray":"\nbase.strided.sdsnanmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation with\n    extended accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnanmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sdsnanmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.sdsmeanors, base.strided.sdsnanmean","base.strided.sdsnansum":"\nbase.strided.sdsnansum( N, x, stride )\n    Computes the sum of single-precision floating-point strided array\n    elements, ignore `NaN` values and using extended accumulation.\n\n    The `N` and `stride` parameters determine which elements in the\n    strided array are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnansum( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > var stride = 2;\n    > base.strided.sdsnansum( 4, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > stride = 2;\n    > base.strided.sdsnansum( 4, x1, stride )\n    -1.0\n\n\nbase.strided.sdsnansum.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using extended accumulation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnansum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.sdsnansum.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnansum, base.strided.dnansum, base.strided.gnansum, base.strided.sdssum, base.strided.snansum\n","base.strided.sdsnansum.ndarray":"\nbase.strided.sdsnansum.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using extended accumulation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnansum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.sdsnansum.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnansum, base.strided.dnansum, base.strided.gnansum, base.strided.sdssum, base.strided.snansum","base.strided.sdsnansumpw":"\nbase.strided.sdsnansumpw( N, x, stride )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation with extended\n    accumulation.\n\n    The `N` and `stride` parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnansumpw( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.sdsnansumpw( 4, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sdsnansumpw( 4, x1, 2 )\n    -1.0\n\n\nbase.strided.sdsnansumpw.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation with extended\n    accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnansumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.sdsnansumpw.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnansumpw, base.strided.dnansumpw, base.strided.gnansumpw, base.strided.sdsnansum, base.strided.sdssumpw, base.strided.snansumpw\n","base.strided.sdsnansumpw.ndarray":"\nbase.strided.sdsnansumpw.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation with extended\n    accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnansumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.sdsnansumpw.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnansumpw, base.strided.dnansumpw, base.strided.gnansumpw, base.strided.sdsnansum, base.strided.sdssumpw, base.strided.snansumpw","base.strided.sdssum":"\nbase.strided.sdssum( N, x, stride )\n    Computes the sum of single-precision floating-point strided array elements\n    using extended accumulation.\n\n    The `N` and stride parameters determine which elements in \n    the strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdssum( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var stride = 2;\n    > base.strided.sdssum( 3, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > stride = 2;\n    > base.strided.sdssum( 3, x1, stride )\n    -1.0\n\n\nbase.strided.sdssum.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements\n    using extended accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdssum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sdssum.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dssum, base.strided.dsum, base.strided.sdsnansum, base.strided.ssum, base.strided.gsum\n","base.strided.sdssum.ndarray":"\nbase.strided.sdssum.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements\n    using extended accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdssum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sdssum.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dssum, base.strided.dsum, base.strided.sdsnansum, base.strided.ssum, base.strided.gsum","base.strided.sdssumpw":"\nbase.strided.sdssumpw( N, x, stride )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation with extended accumulation.\n\n    The `N` and stride parameters determine which elements in the strided\n    array are accessed are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset,\n    use a typed array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdssumpw( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var stride = 2;\n    > base.strided.sdssumpw( 3, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > stride = 2;\n    > base.strided.sdssumpw( 3, x1, stride )\n    -1.0\n\n\nbase.strided.sdssumpw.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation with extended accumulation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdssumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sdssumpw.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dssumpw, base.strided.dsumpw, base.strided.sdsnansumpw, base.strided.sdssum, base.strided.ssumpw, base.strided.gsumpw\n","base.strided.sdssumpw.ndarray":"\nbase.strided.sdssumpw.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation with extended accumulation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdssumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sdssumpw.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dssumpw, base.strided.dsumpw, base.strided.sdsnansumpw, base.strided.sdssum, base.strided.ssumpw, base.strided.gsumpw","base.strided.sfill":"\nbase.strided.sfill( N, alpha, x, strideX )\n    Fills a single-precision floating-point strided array with a specified\n    scalar value.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sfill( x.length, 5.0, x, 1 )\n    <Float32Array>[ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sfill( 3, 5.0, x, 2 )\n    <Float32Array>[ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sfill( 3, 5.0, x1, 2 )\n    <Float32Array>[ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n    > x0\n    <Float32Array>[ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.sfill.ndarray( N, alpha, x, strideX, offsetX )\n    Fills a single-precision floating-point strided array with a specified\n    scalar value using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sfill.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float32Array>[ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.sfill.ndarray( 3, 5.0, x, 2, 1 )\n    <Float32Array>[ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n    See Also\n    --------\n    base.strided.dfill, base.strided.gfill\n","base.strided.sfill.ndarray":"\nbase.strided.sfill.ndarray( N, alpha, x, strideX, offsetX )\n    Fills a single-precision floating-point strided array with a specified\n    scalar value using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sfill.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float32Array>[ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.sfill.ndarray( 3, 5.0, x, 2, 1 )\n    <Float32Array>[ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n    See Also\n    --------\n    base.strided.dfill, base.strided.gfill","base.strided.sfloor":"\nbase.strided.sfloor( N, x, strideX, y, strideY )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward negative infinity and assigns the results to elements in a single-\n    precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sfloor( x.length, x, 1, y, 1 )\n    <Float32Array>[ -2.0, 1.0, 3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sfloor( N, x, 2, y, -1 )\n    <Float32Array>[ 3.0, -2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.sfloor( N, x1, -2, y1, 1 )\n    <Float32Array>[ 4.0, 1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 4.0, 1.0 ]\n\n\nbase.strided.sfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward negative infinity and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ -2.0, 1.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dfloor, strided.floor, base.strided.sceil, base.strided.strunc\n","base.strided.sfloor.ndarray":"\nbase.strided.sfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward negative infinity and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ -2.0, 1.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dfloor, strided.floor, base.strided.sceil, base.strided.strunc","base.strided.sinv":"\nbase.strided.sinv( N, x, strideX, y, strideY )\n    Computes the multiplicative inverse for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sinv( x.length, x, 1, y, 1 )\n    <Float32Array>[ ~-0.05, -1.0, 0.5, 0.25 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sinv( N, x, 2, y, -1 )\n    <Float32Array>[ 0.5, ~-0.05, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.sinv( N, x1, -2, y1, 1 )\n    <Float32Array>[ 0.25, -1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.sinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the multiplicative inverse for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ ~-0.05, -1.0, 0.5, 0.25 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dinv, strided.inv\n","base.strided.sinv.ndarray":"\nbase.strided.sinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the multiplicative inverse for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ ~-0.05, -1.0, 0.5, 0.25 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dinv, strided.inv","base.strided.smap":"\nbase.strided.smap( N, x, strideX, y, strideY, fcn )\n    Applies a unary function to a single-precision floating-point strided input\n    array and assigns results to a single-precision floating-point strided\n    output array.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap( x.length, x, 1, y, 1, base.identityf )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap( 2, x, 2, y, -1, base.identityf )\n    <Float32Array>[ 3.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smap( 2, x1, -2, y1, 1, base.identityf )\n    <Float32Array>[ 4.0, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n    Applies a unary function to a single-precision floating-point strided input\n    array and assigns results to a single-precision floating-point strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identityf )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identityf )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmap, base.strided.unary\n","base.strided.smap.ndarray":"\nbase.strided.smap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n    Applies a unary function to a single-precision floating-point strided input\n    array and assigns results to a single-precision floating-point strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identityf )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identityf )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmap, base.strided.unary","base.strided.smap2":"\nbase.strided.smap2( N, x, sx, y, sy, z, sz, fcn )\n    Applies a binary function to single-precision floating-point strided input\n    arrays and assigns results to a single-precision floating-point strided\n    output array.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    z: Float32Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float32Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap2( x.length, x, 1, y, 1, z, 1, base.addf )\n    <Float32Array>[ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Using `N` and stride parameters:\n    > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap2( 2, x, 2, y, -1, z, 1, base.addf )\n    <Float32Array>[ 3.0, 4.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smap2( 2, x1, -2, y1, 1, z1, 1, base.addf )\n    <Float32Array>[ 7.0, 6.0 ]\n    > z0\n    <Float32Array>[ 0.0, 0.0, 7.0, 6.0 ]\n\n\nbase.strided.smap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n    Applies a binary function to single-precision floating-point strided input\n    arrays and assigns results to a single-precision floating-point strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Float32Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float32Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.addf )\n    <Float32Array>[ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.addf )\n    <Float32Array>[ 0.0, 6.0, 7.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmap2, base.strided.binary\n","base.strided.smap2.ndarray":"\nbase.strided.smap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n    Applies a binary function to single-precision floating-point strided input\n    arrays and assigns results to a single-precision floating-point strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Float32Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float32Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.addf )\n    <Float32Array>[ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.addf )\n    <Float32Array>[ 0.0, 6.0, 7.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmap2, base.strided.binary","base.strided.smax":"\nbase.strided.smax( N, x, strideX )\n    Computes the maximum value of a single-precision floating-point strided\n    array.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smax( x.length, x, 1 )\n    2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.smax( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.smax( 3, x1, 2 )\n    2.0\n\n\nbase.strided.smax.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a single-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smax.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smax.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.max, base.strided.smin, base.strided.snanmax\n","base.strided.smax.ndarray":"\nbase.strided.smax.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a single-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smax.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smax.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.max, base.strided.smin, base.strided.snanmax","base.strided.smaxabs":"\nbase.strided.smaxabs( N, x, strideX )\n    Computes the maximum absolute value of a single-precision floating-point\n    strided array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smaxabs( x.length, x, 1 )\n    2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.smaxabs( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.smaxabs( 3, x1, 2 )\n    2.0\n\n\nbase.strided.smaxabs.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smaxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.smaxabs.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmaxabs, base.strided.maxabs, base.strided.smax, base.strided.sminabs, base.strided.snanmaxabs\n","base.strided.smaxabs.ndarray":"\nbase.strided.smaxabs.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smaxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.smaxabs.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmaxabs, base.strided.maxabs, base.strided.smax, base.strided.sminabs, base.strided.snanmaxabs","base.strided.smaxabssorted":"\nbase.strided.smaxabssorted( N, x, strideX )\n    Computes the maximum absolute value of a sorted single-precision floating-\n    point strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n    > base.strided.smaxabssorted( x.length, x, 1 )\n    3.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.smaxabssorted( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.smaxabssorted( 3, x1, 2 )\n    3.0\n\n\nbase.strided.smaxabssorted.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a sorted single-precision floating-\n    point strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n    > base.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.smaxabssorted.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmaxabssorted, base.strided.smaxabs, base.strided.smaxsorted\n","base.strided.smaxabssorted.ndarray":"\nbase.strided.smaxabssorted.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a sorted single-precision floating-\n    point strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n    > base.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.smaxabssorted.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmaxabssorted, base.strided.smaxabs, base.strided.smaxsorted","base.strided.smaxsorted":"\nbase.strided.smaxsorted( N, x, strideX )\n    Computes the maximum value of a sorted single-precision floating-point\n    strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.smaxsorted( x.length, x, 1 )\n    3.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.smaxsorted( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.smaxsorted( 3, x1, 2 )\n    3.0\n\n\nbase.strided.smaxsorted.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.smaxsorted.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmaxsorted, base.strided.maxsorted, base.strided.smax, base.strided.sminsorted\n","base.strided.smaxsorted.ndarray":"\nbase.strided.smaxsorted.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.smaxsorted.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmaxsorted, base.strided.maxsorted, base.strided.smax, base.strided.sminsorted","base.strided.smean":"\nbase.strided.smean( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smean( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.smean( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.smean( N, x1, stride )\n    ~-0.3333\n\nbase.strided.smean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsmean, base.strided.snanmean\n","base.strided.smean.ndarray":"\nbase.strided.smean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsmean, base.strided.snanmean","base.strided.smeankbn":"\nbase.strided.smeankbn( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeankbn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.smeankbn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.smeankbn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.smeankbn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeankbn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeankbn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeankbn, base.strided.meankbn, base.strided.smean\n","base.strided.smeankbn.ndarray":"\nbase.strided.smeankbn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeankbn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeankbn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeankbn, base.strided.meankbn, base.strided.smean","base.strided.smeankbn2":"\nbase.strided.smeankbn2( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a second-order iterative Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeankbn2( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.smeankbn2( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.smeankbn2( N, x1, stride )\n    ~-0.3333\n\nbase.strided.smeankbn2.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeankbn2.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeankbn2.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeankbn2, base.strided.meankbn2, base.strided.smean\n","base.strided.smeankbn2.ndarray":"\nbase.strided.smeankbn2.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeankbn2.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeankbn2.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeankbn2, base.strided.meankbn2, base.strided.smean","base.strided.smeanli":"\nbase.strided.smeanli( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanli( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.smeanli( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.smeanli( N, x1, stride )\n    ~-0.3333\n\nbase.strided.smeanli.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanli.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanli.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanli, base.strided.smean, base.strided.smeanlipw\n","base.strided.smeanli.ndarray":"\nbase.strided.smeanli.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanli.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanli.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanli, base.strided.smean, base.strided.smeanlipw","base.strided.smeanlipw":"\nbase.strided.smeanlipw( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm with pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanlipw( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.smeanlipw( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.smeanlipw( N, x1, stride )\n    ~-0.3333\n\nbase.strided.smeanlipw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm with pairwise summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanlipw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanlipw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanlipw, base.strided.smean, base.strided.smeanli\n","base.strided.smeanlipw.ndarray":"\nbase.strided.smeanlipw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm with pairwise summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanlipw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanlipw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanlipw, base.strided.smean, base.strided.smeanli","base.strided.smeanors":"\nbase.strided.smeanors( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanors( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.smeanors( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.smeanors( N, x1, stride )\n    ~-0.3333\n\nbase.strided.smeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanors, base.strided.meanors, base.strided.smean, base.strided.snanmeanors\n","base.strided.smeanors.ndarray":"\nbase.strided.smeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanors, base.strided.meanors, base.strided.smean, base.strided.snanmeanors","base.strided.smeanpn":"\nbase.strided.smeanpn( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a two-pass error correction algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanpn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.smeanpn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.smeanpn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.smeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a two-pass error correction algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.meanpn, base.strided.smean, base.strided.snanmeanpn\n","base.strided.smeanpn.ndarray":"\nbase.strided.smeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a two-pass error correction algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.meanpn, base.strided.smean, base.strided.snanmeanpn","base.strided.smeanpw":"\nbase.strided.smeanpw( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanpw( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.smeanpw( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.smeanpw( N, x1, stride )\n    ~-0.3333\n\nbase.strided.smeanpw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanpw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanpw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpw, base.strided.meanpw, base.strided.smean\n","base.strided.smeanpw.ndarray":"\nbase.strided.smeanpw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanpw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanpw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpw, base.strided.meanpw, base.strided.smean","base.strided.smeanwd":"\nbase.strided.smeanwd( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanwd( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.smeanwd( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.smeanwd( N, x1, stride )\n    ~-0.3333\n\nbase.strided.smeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanwd, base.strided.meanwd, base.strided.smean, base.strided.snanmeanwd\n","base.strided.smeanwd.ndarray":"\nbase.strided.smeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanwd, base.strided.meanwd, base.strided.smean, base.strided.snanmeanwd","base.strided.smediansorted":"\nbase.strided.smediansorted( N, x, stride )\n    Computes the median value of a sorted single-precision floating-point\n    strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.smediansorted( x.length, x, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smediansorted( N, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.smediansorted( N, x1, 2 )\n    2.0\n\nbase.strided.smediansorted.ndarray( N, x, stride, offset )\n    Computes the median value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.smediansorted.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smediansorted.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmediansorted, base.strided.mediansorted, base.strided.smean\n","base.strided.smediansorted.ndarray":"\nbase.strided.smediansorted.ndarray( N, x, stride, offset )\n    Computes the median value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.smediansorted.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smediansorted.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmediansorted, base.strided.mediansorted, base.strided.smean","base.strided.smidrange":"\nbase.strided.smidrange( N, x, strideX )\n    Computes the mid-range of a single-precision floating-point strided array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Mid-range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smidrange( x.length, x, 1 )\n    0.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.smidrange( 3, x, 2 )\n    0.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.smidrange( 3, x1, 2 )\n    0.0\n\n\nbase.strided.smidrange.ndarray( N, x, strideX, offsetX )\n    Computes the mid-range of a single-precision floating-point strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Mid-range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smidrange.ndarray( x.length, x, 1, 0 )\n    0.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.smidrange.ndarray( 3, x, 2, 1 )\n    0.0\n\n    See Also\n    --------\n    base.strided.dmidrange, base.strided.smax, base.strided.smean, base.strided.smin, base.strided.srange\n","base.strided.smidrange.ndarray":"\nbase.strided.smidrange.ndarray( N, x, strideX, offsetX )\n    Computes the mid-range of a single-precision floating-point strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Mid-range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smidrange.ndarray( x.length, x, 1, 0 )\n    0.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.smidrange.ndarray( 3, x, 2, 1 )\n    0.0\n\n    See Also\n    --------\n    base.strided.dmidrange, base.strided.smax, base.strided.smean, base.strided.smin, base.strided.srange","base.strided.smin":"\nbase.strided.smin( N, x, strideX )\n    Computes the minimum value of a single-precision floating-point strided\n    array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smin( x.length, x, 1 )\n    -2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.smin( 3, x, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.smin( 3, x1, 2 )\n    -2.0\n\n\nbase.strided.smin.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a single-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.smin.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.min, base.strided.smax, base.strided.snanmin\n","base.strided.smin.ndarray":"\nbase.strided.smin.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a single-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.smin.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.min, base.strided.smax, base.strided.snanmin","base.strided.sminabs":"\nbase.strided.sminabs( N, x, strideX )\n    Computes the minimum absolute value of a single-precision floating-point\n    strided array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sminabs( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.sminabs( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sminabs( 3, x1, 2 )\n    1.0\n\n\nbase.strided.sminabs.ndarray( N, x, strideX, offsetX )\n    Computes the minimum absolute value of a single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sminabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sminabs.ndarray( 3, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dminabs, base.strided.minabs, base.strided.smaxabs, base.strided.smin, base.strided.snanminabs\n","base.strided.sminabs.ndarray":"\nbase.strided.sminabs.ndarray( N, x, strideX, offsetX )\n    Computes the minimum absolute value of a single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sminabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sminabs.ndarray( 3, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dminabs, base.strided.minabs, base.strided.smaxabs, base.strided.smin, base.strided.snanminabs","base.strided.sminsorted":"\nbase.strided.sminsorted( N, x, stride )\n    Computes the minimum value of a sorted single-precision floating-point\n    strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.sminsorted( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sminsorted( N, x, stride )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sminsorted( N, x1, stride )\n    -2.0\n\nbase.strided.sminsorted.ndarray( N, x, stride, offset )\n    Computes the minimum value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.sminsorted.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sminsorted.ndarray( N, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dminsorted, base.strided.minsorted, base.strided.smaxsorted, base.strided.smin\n","base.strided.sminsorted.ndarray":"\nbase.strided.sminsorted.ndarray( N, x, stride, offset )\n    Computes the minimum value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.sminsorted.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sminsorted.ndarray( N, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dminsorted, base.strided.minsorted, base.strided.smaxsorted, base.strided.smin","base.strided.smskabs":"\nbase.strided.smskabs( N, x, sx, m, sm, y, sy )\n    Computes the absolute value for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ 2.0, 1.0, 0.0, 5.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskabs( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ 5.0, 1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 5.0, 1.0 ]\n\n\nbase.strided.smskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the absolute value for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 2.0, 1.0, 0.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 5.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dmskabs, base.strided.sabs, base.strided.smskabs2\n","base.strided.smskabs.ndarray":"\nbase.strided.smskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the absolute value for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 2.0, 1.0, 0.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 5.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dmskabs, base.strided.sabs, base.strided.smskabs2","base.strided.smskabs2":"\nbase.strided.smskabs2( N, x, sx, m, sm, y, sy )\n    Computes the squared absolute value for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point\n    strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs2( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ 4.0, 1.0, 0.0, 25.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs2( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, 4.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskabs2( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ 25.0, 1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 25.0, 1.0 ]\n\n\nbase.strided.smskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the squared absolute value for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point\n    strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 4.0, 1.0, 0.0, 25.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 25.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dmskabs2, base.strided.sabs2, base.strided.smskabs\n","base.strided.smskabs2.ndarray":"\nbase.strided.smskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the squared absolute value for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point\n    strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 4.0, 1.0, 0.0, 25.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 25.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dmskabs2, base.strided.sabs2, base.strided.smskabs","base.strided.smskcbrt":"\nbase.strided.smskcbrt( N, x, sx, m, sm, y, sy )\n    Computes the cube root for each element in a single-precision floating-point\n    strided array `x` according to a strided mask array and assigns the results\n    to elements in a single-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskcbrt( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ 0.0, 1.0, 0.0, 3.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskcbrt( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskcbrt( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ 3.0, 1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.smskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the cube root for each element in a single-precision floating-point\n    strided array `x` according to a strided mask array and assigns the results\n    to elements in a single-precision floating-point strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, 1.0, 0.0, 3.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dmskcbrt, base.strided.scbrt, base.strided.ssqrt\n","base.strided.smskcbrt.ndarray":"\nbase.strided.smskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the cube root for each element in a single-precision floating-point\n    strided array `x` according to a strided mask array and assigns the results\n    to elements in a single-precision floating-point strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, 1.0, 0.0, 3.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dmskcbrt, base.strided.scbrt, base.strided.ssqrt","base.strided.smskceil":"\nbase.strided.smskceil( N, x, sx, m, sm, y, sy )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward positive infinity according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskceil( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ 2.0, 3.0, 0.0, 4.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskceil( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskceil( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ 4.0, 3.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.smskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward positive infinity according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 2.0, 3.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n    See Also\n    --------\n    base.strided.dmskceil, base.strided.sceil, base.strided.smskfloor, base.strided.smsktrunc\n","base.strided.smskceil.ndarray":"\nbase.strided.smskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward positive infinity according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 2.0, 3.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n    See Also\n    --------\n    base.strided.dmskceil, base.strided.sceil, base.strided.smskfloor, base.strided.smsktrunc","base.strided.smskdeg2rad":"\nbase.strided.smskdeg2rad( N, x, sx, m, sm, y, sy )\n    Converts each element in a single-precision floating-point strided array `x`\n    from degrees to radians according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskdeg2rad( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ 0.0, ~0.524, 0.0, ~1.047 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskdeg2rad( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ ~1.047, ~0.524 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.smskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Converts each element in a single-precision floating-point strided array `x`\n    from degrees to radians according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, ~0.524, 0.0, ~1.047 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n    See Also\n    --------\n    base.strided.dmskdeg2rad, base.strided.sdeg2rad\n","base.strided.smskdeg2rad.ndarray":"\nbase.strided.smskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Converts each element in a single-precision floating-point strided array `x`\n    from degrees to radians according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, ~0.524, 0.0, ~1.047 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n    See Also\n    --------\n    base.strided.dmskdeg2rad, base.strided.sdeg2rad","base.strided.smskfloor":"\nbase.strided.smskfloor( N, x, sx, m, sm, y, sy )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward negative infinity according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskfloor( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskfloor( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskfloor( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ 4.0, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward negative infinity according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmskfloor, base.strided.sfloor, base.strided.smskceil, base.strided.smsktrunc\n","base.strided.smskfloor.ndarray":"\nbase.strided.smskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward negative infinity according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmskfloor, base.strided.sfloor, base.strided.smskceil, base.strided.smsktrunc","base.strided.smskinv":"\nbase.strided.smskinv( N, x, sx, m, sm, y, sy )\n    Computes the multiplicative inverse for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskinv( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ ~-0.05, -1.0, 0.0, 0.25 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskinv( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, ~-0.05, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskinv( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ 0.25, -1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.smskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the multiplicative inverse for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ ~-0.05, -1.0, 0.0, 0.25 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dinv, base.strided.dmskinv\n","base.strided.smskinv.ndarray":"\nbase.strided.smskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the multiplicative inverse for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ ~-0.05, -1.0, 0.0, 0.25 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dinv, base.strided.dmskinv","base.strided.smskmap":"\nbase.strided.smskmap( N, x, sx, m, sm, y, sy, fcn )\n    Applies a unary function to a single-precision floating-point strided input\n    array according to a strided mask array and assigns results to a single-\n    precision floating-point strided output array.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskmap( x.length, x, 1, m, 1, y, 1, base.identity )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskmap( 2, x, 2, m, 2, y, -1, base.identity )\n    <Float32Array>[ 0.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\n    <Float32Array>[ 0.0, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.0, 2.0 ]\n\n\nbase.strided.smskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n    Applies a unary function to a single-precision floating-point strided input\n    array according to a strided mask array and assigns results to a single-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n    <Float32Array>[ 0.0, 0.0, 4.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmskmap, base.strided.mskunary, base.strided.smap, base.strided.smskmap2\n","base.strided.smskmap.ndarray":"\nbase.strided.smskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n    Applies a unary function to a single-precision floating-point strided input\n    array according to a strided mask array and assigns results to a single-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n    <Float32Array>[ 0.0, 0.0, 4.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmskmap, base.strided.mskunary, base.strided.smap, base.strided.smskmap2","base.strided.smskmap2":"\nbase.strided.smskmap2( N, x, sx, y, sy, m, sm, z, sz, fcn )\n    Applies a binary function to single-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a single-\n    precision floating-point strided output array.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    z: Float32Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float32Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.smskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.addf )\n    <Float32Array>[ 2.0, 4.0, 0.0, 8.0 ]\n\n    // Using `N` and stride parameters:\n    > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.addf )\n    <Float32Array>[ 0.0, 3.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.addf )\n    <Float32Array>[ 0.0, 6.0 ]\n    > z0\n    <Float32Array>[ 0.0, 0.0, 0.0, 6.0 ]\n\n\nbase.strided.smskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n    Applies a binary function to single-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a single-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    z: Float32Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float32Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.smskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.addf )\n    <Float32Array>[ 2.0, 4.0, 0.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.smskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.addf )\n    <Float32Array>[ 0.0, 0.0, 7.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmskmap2, base.strided.smap2, base.strided.smskmap\n","base.strided.smskmap2.ndarray":"\nbase.strided.smskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n    Applies a binary function to single-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a single-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    z: Float32Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float32Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.smskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.addf )\n    <Float32Array>[ 2.0, 4.0, 0.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.smskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.addf )\n    <Float32Array>[ 0.0, 0.0, 7.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmskmap2, base.strided.smap2, base.strided.smskmap","base.strided.smskmax":"\nbase.strided.smskmax( N, x, strideX, mask, strideMask )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.smskmax( x.length, x, 1, mask, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.smskmax( 3, x, 2, mask, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > base.strided.smskmax( 3, x1, 2, mask1, 2 )\n    2.0\n\n\nbase.strided.smskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.smskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmskmax, base.strided.mskmax, base.strided.smax, base.strided.smskmin, base.strided.snanmax, base.strided.snanmskmax\n","base.strided.smskmax.ndarray":"\nbase.strided.smskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.smskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmskmax, base.strided.mskmax, base.strided.smax, base.strided.smskmin, base.strided.snanmax, base.strided.snanmskmax","base.strided.smskmin":"\nbase.strided.smskmin( N, x, strideX, mask, strideMask )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.smskmin( x.length, x, 1, mask, 1 )\n    -2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.smskmin( 3, x, 2, mask, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > base.strided.smskmin( 3, x1, 2, mask1, 2 )\n    -2.0\n\n\nbase.strided.smskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.smskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmskmin, base.strided.mskmin, base.strided.smin, base.strided.smskmax, base.strided.snanmin, base.strided.snanmskmin\n","base.strided.smskmin.ndarray":"\nbase.strided.smskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.smskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmskmin, base.strided.mskmin, base.strided.smin, base.strided.smskmax, base.strided.snanmin, base.strided.snanmskmin","base.strided.smskramp":"\nbase.strided.smskramp( N, x, sx, m, sm, y, sy )\n    Evaluates the ramp function for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskramp( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskramp( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskramp( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ 4.0, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Evaluates the ramp function for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmskramp, base.strided.sramp\n","base.strided.smskramp.ndarray":"\nbase.strided.smskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Evaluates the ramp function for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmskramp, base.strided.sramp","base.strided.smskrange":"\nbase.strided.smskrange( N, x, strideX, mask, strideMask )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.smskrange( x.length, x, 1, mask, 1 )\n    4.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.smskrange( 3, x, 2, mask, 2 )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > base.strided.smskrange( 3, x1, 2, mask1, 2 )\n    4.0\n\n\nbase.strided.smskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.smskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dmskrange, base.strided.mskrange, base.strided.smskmax, base.strided.smskmin, base.strided.snanrange, base.strided.srange\n","base.strided.smskrange.ndarray":"\nbase.strided.smskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.smskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dmskrange, base.strided.mskrange, base.strided.smskmax, base.strided.smskmin, base.strided.snanrange, base.strided.srange","base.strided.smskrsqrt":"\nbase.strided.smskrsqrt( N, x, sx, m, sm, y, sy )\n    Computes the reciprocal square root for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskrsqrt( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ Infinity, 0.5, 0.0, ~0.289 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskrsqrt( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, Infinity, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ ~0.289, 0.5 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.smskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the reciprocal square root for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ Infinity, 0.5, 0.0, ~0.289 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n    See Also\n    --------\n    base.strided.dmskrsqrt, base.strided.smsksqrt, base.strided.srsqrt\n","base.strided.smskrsqrt.ndarray":"\nbase.strided.smskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the reciprocal square root for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ Infinity, 0.5, 0.0, ~0.289 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n    See Also\n    --------\n    base.strided.dmskrsqrt, base.strided.smsksqrt, base.strided.srsqrt","base.strided.smsksqrt":"\nbase.strided.smsksqrt( N, x, sx, m, sm, y, sy )\n    Computes the principal square root for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsksqrt( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ 0.0, 2.0, 0.0, ~3.464 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsksqrt( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smsksqrt( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ ~3.464, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.smsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the principal square root for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, 2.0, 0.0, ~3.464 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmsksqrt, base.strided.smskcbrt, base.strided.smskrsqrt, base.strided.srsqrt\n","base.strided.smsksqrt.ndarray":"\nbase.strided.smsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the principal square root for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, 2.0, 0.0, ~3.464 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmsksqrt, base.strided.smskcbrt, base.strided.smskrsqrt, base.strided.srsqrt","base.strided.smsktrunc":"\nbase.strided.smsktrunc( N, x, sx, m, sm, y, sy )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward zero according to a strided mask array and assigns the results to\n    elements in a single-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsktrunc( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsktrunc( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smsktrunc( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ 4.0, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward zero according to a strided mask array and assigns the results to\n    elements in a single-precision floating-point strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmsktrunc, base.strided.smskceil, base.strided.smskfloor, base.strided.strunc\n","base.strided.smsktrunc.ndarray":"\nbase.strided.smsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward zero according to a strided mask array and assigns the results to\n    elements in a single-precision floating-point strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmsktrunc, base.strided.smskceil, base.strided.smskfloor, base.strided.strunc","base.strided.snanmax":"\nbase.strided.snanmax( N, x, strideX )\n    Computes the maximum value of a single-precision floating-point strided\n    array, ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmax( x.length, x, 1 )\n    2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > base.strided.snanmax( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.snanmax( 3, x1, 2 )\n    2.0\n\n\nbase.strided.snanmax.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a single-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.snanmax.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.snanmax.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmax, base.strided.nanmax, base.strided.smax, base.strided.snanmin\n","base.strided.snanmax.ndarray":"\nbase.strided.snanmax.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a single-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.snanmax.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.snanmax.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmax, base.strided.nanmax, base.strided.smax, base.strided.snanmin","base.strided.snanmaxabs":"\nbase.strided.snanmaxabs( N, x, strideX )\n    Computes the maximum absolute value of a single-precision floating-point\n    strided array, ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmaxabs( x.length, x, 1 )\n    2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > base.strided.snanmaxabs( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.snanmaxabs( 3, x1, 2 )\n    2.0\n\n\nbase.strided.snanmaxabs.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a single-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.snanmaxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.snanmaxabs.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmaxabs, base.strided.nanmaxabs, base.strided.smaxabs, base.strided.snanmax, base.strided.snanminabs\n","base.strided.snanmaxabs.ndarray":"\nbase.strided.snanmaxabs.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a single-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.snanmaxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.snanmaxabs.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmaxabs, base.strided.nanmaxabs, base.strided.smaxabs, base.strided.snanmax, base.strided.snanminabs","base.strided.snanmean":"\nbase.strided.snanmean( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmean( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.snanmean( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.snanmean( N, x1, stride )\n    ~-0.3333\n\nbase.strided.snanmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.smean, base.strided.nanmean\n","base.strided.snanmean.ndarray":"\nbase.strided.snanmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.smean, base.strided.nanmean","base.strided.snanmeanors":"\nbase.strided.snanmeanors( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmeanors( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.snanmeanors( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.snanmeanors( N, x1, stride )\n    ~-0.3333\n\nbase.strided.snanmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanors, base.strided.nanmeanors, base.strided.smeanors, base.strided.snanmean\n","base.strided.snanmeanors.ndarray":"\nbase.strided.snanmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanors, base.strided.nanmeanors, base.strided.smeanors, base.strided.snanmean","base.strided.snanmeanpn":"\nbase.strided.snanmeanpn( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction\n    algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmeanpn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.snanmeanpn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.snanmeanpn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.snanmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction algorithm\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanpn, base.strided.nanmeanpn, base.strided.smeanpn, base.strided.snanmean\n","base.strided.snanmeanpn.ndarray":"\nbase.strided.snanmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction algorithm\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanpn, base.strided.nanmeanpn, base.strided.smeanpn, base.strided.snanmean","base.strided.snanmeanwd":"\nbase.strided.snanmeanwd( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmeanwd( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.snanmeanwd( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.snanmeanwd( N, x1, stride )\n    ~-0.3333\n\nbase.strided.snanmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanwd, base.strided.nanmeanwd, base.strided.smeanwd, base.strided.snanmean\n","base.strided.snanmeanwd.ndarray":"\nbase.strided.snanmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanwd, base.strided.nanmeanwd, base.strided.smeanwd, base.strided.snanmean","base.strided.snanmin":"\nbase.strided.snanmin( N, x, strideX )\n    Computes the minimum value of a single-precision floating-point strided\n    array, ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmin( x.length, x, 1 )\n    -2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > base.strided.snanmin( 3, x, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.snanmin( 3, x1, 2 )\n    -2.0\n\n\nbase.strided.snanmin.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a single-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.snanmin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.snanmin.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dnanmin, base.strided.nanmin, base.strided.smin, base.strided.snanmax\n","base.strided.snanmin.ndarray":"\nbase.strided.snanmin.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a single-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.snanmin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.snanmin.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dnanmin, base.strided.nanmin, base.strided.smin, base.strided.snanmax","base.strided.snanminabs":"\nbase.strided.snanminabs( N, x, strideX )\n    Computes the minimum absolute value of a single-precision floating-point\n    strided array, ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanminabs( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > base.strided.snanminabs( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.snanminabs( 3, x1, 2 )\n    1.0\n\n\nbase.strided.snanminabs.ndarray( N, x, strideX, offsetX )\n    Computes the minimum absolute value of a single-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.snanminabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.snanminabs.ndarray( 3, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dnanminabs, base.strided.nanminabs, base.strided.sminabs, base.strided.snanmaxabs, base.strided.snanmin\n","base.strided.snanminabs.ndarray":"\nbase.strided.snanminabs.ndarray( N, x, strideX, offsetX )\n    Computes the minimum absolute value of a single-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.snanminabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.snanminabs.ndarray( 3, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dnanminabs, base.strided.nanminabs, base.strided.sminabs, base.strided.snanmaxabs, base.strided.snanmin","base.strided.snanmskmax":"\nbase.strided.snanmskmax( N, x, strideX, mask, strideMask )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n    > base.strided.snanmskmax( x.length, x, 1, mask, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmskmax( N, x, 2, mask, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.snanmskmax( N, x1, 2, mask1, 2 )\n    2.0\n\nbase.strided.snanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.snanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmskmax, base.strided.nanmskmax, base.strided.smskmax, base.strided.snanmax, base.strided.snanmskmin\n","base.strided.snanmskmax.ndarray":"\nbase.strided.snanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.snanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmskmax, base.strided.nanmskmax, base.strided.smskmax, base.strided.snanmax, base.strided.snanmskmin","base.strided.snanmskmin":"\nbase.strided.snanmskmin( N, x, strideX, mask, strideMask )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n    > base.strided.snanmskmin( x.length, x, 1, mask, 1 )\n    -2.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmskmin( N, x, 2, mask, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.snanmskmin( N, x1, 2, mask1, 2 )\n    -2.0\n\nbase.strided.snanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.snanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dnanmskmin, base.strided.nanmskmin, base.strided.smskmin, base.strided.snanmin, base.strided.snanmskmax\n","base.strided.snanmskmin.ndarray":"\nbase.strided.snanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.snanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dnanmskmin, base.strided.nanmskmin, base.strided.smskmin, base.strided.snanmin, base.strided.snanmskmax","base.strided.snanmskrange":"\nbase.strided.snanmskrange( N, x, strideX, mask, strideMask )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n    > base.strided.snanmskrange( x.length, x, 1, mask, 1 )\n    4.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmskrange( N, x, 2, mask, 2 )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.snanmskrange( N, x1, 2, mask1, 2 )\n    4.0\n\nbase.strided.snanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.snanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dnanmskrange, base.strided.nanmskrange, base.strided.smskrange, base.strided.snanrange, base.strided.snanmskmax, base.strided.snanmskmin\n","base.strided.snanmskrange.ndarray":"\nbase.strided.snanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.snanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dnanmskrange, base.strided.nanmskrange, base.strided.smskrange, base.strided.snanrange, base.strided.snanmskmax, base.strided.snanmskmin","base.strided.snanrange":"\nbase.strided.snanrange( N, x, strideX )\n    Computes the range of a single-precision floating-point strided array,\n    ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanrange( x.length, x, 1 )\n    4.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > base.strided.snanrange( 3, x, 2 )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.snanrange( 3, x1, 2 )\n    4.0\n\n\nbase.strided.snanrange.ndarray( N, x, strideX, offsetX )\n    Computes the range of a single-precision floating-point strided array,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.snanrange.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.snanrange.ndarray( 3, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dnanrange, base.strided.nanrange, base.strided.snanmax, base.strided.snanmin, base.strided.srange\n","base.strided.snanrange.ndarray":"\nbase.strided.snanrange.ndarray( N, x, strideX, offsetX )\n    Computes the range of a single-precision floating-point strided array,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.snanrange.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.snanrange.ndarray( 3, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dnanrange, base.strided.nanrange, base.strided.snanmax, base.strided.snanmin, base.strided.srange","base.strided.snanstdev":"\nbase.strided.snanstdev( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdev( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.snanstdev( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.snanstdev( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.snanstdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.nanstdev, base.strided.snanvariance, base.strided.sstdev\n","base.strided.snanstdev.ndarray":"\nbase.strided.snanstdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.nanstdev, base.strided.snanvariance, base.strided.sstdev","base.strided.snanstdevch":"\nbase.strided.snanstdevch( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevch( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.snanstdevch( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.snanstdevch( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.snanstdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevch, base.strided.nanstdevch, base.strided.snanstdev, base.strided.snanvariancech, base.strided.sstdevch\n","base.strided.snanstdevch.ndarray":"\nbase.strided.snanstdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevch, base.strided.nanstdevch, base.strided.snanstdev, base.strided.snanvariancech, base.strided.sstdevch","base.strided.snanstdevpn":"\nbase.strided.snanstdevpn( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevpn( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.snanstdevpn( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.snanstdevpn( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.snanstdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevpn, base.strided.nanstdevpn, base.strided.snanstdev, base.strided.snanvariancepn, base.strided.sstdevpn\n","base.strided.snanstdevpn.ndarray":"\nbase.strided.snanstdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevpn, base.strided.nanstdevpn, base.strided.snanstdev, base.strided.snanvariancepn, base.strided.sstdevpn","base.strided.snanstdevtk":"\nbase.strided.snanstdevtk( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevtk( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.snanstdevtk( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.snanstdevtk( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.snanstdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevtk, base.strided.nanstdevtk, base.strided.snanstdev, base.strided.snanvariancetk, base.strided.sstdevtk\n","base.strided.snanstdevtk.ndarray":"\nbase.strided.snanstdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevtk, base.strided.nanstdevtk, base.strided.snanstdev, base.strided.snanvariancetk, base.strided.sstdevtk","base.strided.snanstdevwd":"\nbase.strided.snanstdevwd( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevwd( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.snanstdevwd( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.snanstdevwd( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.snanstdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevwd, base.strided.nanstdevwd, base.strided.snanstdev, base.strided.snanvariancewd, base.strided.sstdevwd\n","base.strided.snanstdevwd.ndarray":"\nbase.strided.snanstdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevwd, base.strided.nanstdevwd, base.strided.snanstdev, base.strided.snanvariancewd, base.strided.sstdevwd","base.strided.snanstdevyc":"\nbase.strided.snanstdevyc( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass algorithm proposed by\n    Youngs and Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevyc( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.snanstdevyc( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.snanstdevyc( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.snanstdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass algorithm proposed by\n    Youngs and Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevyc, base.strided.nanstdevyc, base.strided.snanstdev, base.strided.snanvarianceyc, base.strided.sstdevyc\n","base.strided.snanstdevyc.ndarray":"\nbase.strided.snanstdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass algorithm proposed by\n    Youngs and Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevyc, base.strided.nanstdevyc, base.strided.snanstdev, base.strided.snanvarianceyc, base.strided.sstdevyc","base.strided.snansum":"\nbase.strided.snansum( N, x, stride )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansum( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.snansum( 4, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.snansum( 4, x1, 2 )\n    -1.0\n\n\nbase.strided.snansum.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.snansum.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.gnansum, base.strided.snanmean, base.strided.ssum\n","base.strided.snansum.ndarray":"\nbase.strided.snansum.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.snansum.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.gnansum, base.strided.snanmean, base.strided.ssum","base.strided.snansumkbn":"\nbase.strided.snansumkbn( N, x, stride )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in the strided \n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, \n    use a typed array view. \n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumkbn( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > var stride = 2;\n    > base.strided.snansumkbn( 4, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > stride = 2;\n    > base.strided.snansumkbn( 4, x1, stride )\n    -1.0\n\n\nbase.strided.snansumkbn.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.snansumkbn.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn, base.strided.gnansumkbn, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn\n","base.strided.snansumkbn.ndarray":"\nbase.strided.snansumkbn.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.snansumkbn.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn, base.strided.gnansumkbn, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn","base.strided.snansumkbn2":"\nbase.strided.snansumkbn2( N, x, stride )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset,\n    use a typed array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumkbn2( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > var stride = 2;\n    > base.strided.snansumkbn2( 4, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > stride = 2;\n    > base.strided.snansumkbn2( 4, x1, stride )\n    -1.0\n\n\nbase.strided.snansumkbn2.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.snansumkbn2.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn2, base.strided.gnansumkbn2, base.strided.snansum, base.strided.snansumkbn, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn2\n","base.strided.snansumkbn2.ndarray":"\nbase.strided.snansumkbn2.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.snansumkbn2.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn2, base.strided.gnansumkbn2, base.strided.snansum, base.strided.snansumkbn, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn2","base.strided.snansumors":"\nbase.strided.snansumors( N, x, strideX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumors( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > var stride = 2;\n    > base.strided.snansumors( 4, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > stride = 2;\n    > base.strided.snansumors( 4, x1, stride )\n    -1.0\n\n\nbase.strided.snansumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.snansumors.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumors, base.strided.gnansumors, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumpw, base.strided.ssumors\n","base.strided.snansumors.ndarray":"\nbase.strided.snansumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.snansumors.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumors, base.strided.gnansumors, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumpw, base.strided.ssumors","base.strided.snansumpw":"\nbase.strided.snansumpw( N, x, strideX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumpw( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.snansumpw( 4, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.snansumpw( 4, x1, 2 )\n    -1.0\n\n\nbase.strided.snansumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.snansumpw.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumpw, base.strided.gnansumpw, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.ssumpw\n","base.strided.snansumpw.ndarray":"\nbase.strided.snansumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.snansumpw.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumpw, base.strided.gnansumpw, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.ssumpw","base.strided.snanvariance":"\nbase.strided.snanvariance( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariance( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariance( N, 1, x, 2 )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.snanvariance( N, 1, x1, 2 )\n    ~4.3333\n\nbase.strided.snanvariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariance, base.strided.nanvariance, base.strided.snanstdev, base.strided.svariance\n","base.strided.snanvariance.ndarray":"\nbase.strided.snanvariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariance, base.strided.nanvariance, base.strided.snanstdev, base.strided.svariance","base.strided.snanvariancech":"\nbase.strided.snanvariancech( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancech( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancech( N, 1, x, 2 )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.snanvariancech( N, 1, x1, 2 )\n    ~4.3333\n\nbase.strided.snanvariancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancech, base.strided.nanvariancech, base.strided.snanstdevch, base.strided.snanvariance, base.strided.svariancech\n","base.strided.snanvariancech.ndarray":"\nbase.strided.snanvariancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancech, base.strided.nanvariancech, base.strided.snanstdevch, base.strided.snanvariance, base.strided.svariancech","base.strided.snanvariancepn":"\nbase.strided.snanvariancepn( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancepn( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancepn( N, 1, x, 2 )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.snanvariancepn( N, 1, x1, 2 )\n    ~4.3333\n\nbase.strided.snanvariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancepn, base.strided.nanvariancepn, base.strided.snanstdevpn, base.strided.snanvariance, base.strided.svariancepn\n","base.strided.snanvariancepn.ndarray":"\nbase.strided.snanvariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancepn, base.strided.nanvariancepn, base.strided.snanstdevpn, base.strided.snanvariance, base.strided.svariancepn","base.strided.snanvariancetk":"\nbase.strided.snanvariancetk( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancetk( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancetk( N, 1, x, 2 )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.snanvariancetk( N, 1, x1, 2 )\n    ~4.3333\n\nbase.strided.snanvariancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancetk, base.strided.nanvariancetk, base.strided.snanstdevtk, base.strided.snanvariance, base.strided.svariancetk\n","base.strided.snanvariancetk.ndarray":"\nbase.strided.snanvariancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancetk, base.strided.nanvariancetk, base.strided.snanstdevtk, base.strided.snanvariance, base.strided.svariancetk","base.strided.snanvariancewd":"\nbase.strided.snanvariancewd( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancewd( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancewd( N, 1, x, 2 )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.snanvariancewd( N, 1, x1, 2 )\n    ~4.3333\n\nbase.strided.snanvariancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using Welford's algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancewd, base.strided.nanvariancewd, base.strided.snanstdevwd, base.strided.snanvariance, base.strided.svariancewd\n","base.strided.snanvariancewd.ndarray":"\nbase.strided.snanvariancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using Welford's algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancewd, base.strided.nanvariancewd, base.strided.snanstdevwd, base.strided.snanvariance, base.strided.svariancewd","base.strided.snanvarianceyc":"\nbase.strided.snanvarianceyc( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n    Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvarianceyc( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvarianceyc( N, 1, x, 2 )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.snanvarianceyc( N, 1, x1, 2 )\n    ~4.3333\n\nbase.strided.snanvarianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n    Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvarianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvarianceyc, base.strided.nanvarianceyc, base.strided.snanstdevyc, base.strided.snanvariance, base.strided.svarianceyc\n","base.strided.snanvarianceyc.ndarray":"\nbase.strided.snanvarianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n    Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvarianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvarianceyc, base.strided.nanvarianceyc, base.strided.snanstdevyc, base.strided.snanvariance, base.strided.svarianceyc","base.strided.snrm2":"\nbase.strided.snrm2( N, x, stride )\n    Computes the L2-norm of a single-precision floating-point vector.\n\n    The `N` and `stride` parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0` the function returns `0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The L2-norm.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.snrm2( x.length, x, 1 )\n    3.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.snrm2( 3, x, 2 )\n    3.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.snrm2( 3, x1, 2 )\n    3.0\n\n\nbase.strided.snrm2.ndarray( N, x, stride, offset )\n    Computes the L2-norm of a single-precision floating-point vector using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The L2-norm.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.snrm2.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.snrm2.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dnrm2, base.strided.gnrm2\n","base.strided.snrm2.ndarray":"\nbase.strided.snrm2.ndarray( N, x, stride, offset )\n    Computes the L2-norm of a single-precision floating-point vector using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The L2-norm.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.snrm2.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.snrm2.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dnrm2, base.strided.gnrm2","base.strided.sramp":"\nbase.strided.sramp( N, x, strideX, y, strideY )\n    Evaluates the ramp function for each element in a single-precision floating-\n    point strided array `x` and assigns the results to elements in a single-\n    precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sramp( x.length, x, 1, y, 1 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sramp( N, x, 2, y, -1 )\n    <Float32Array>[ 0.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.sramp( N, x1, -2, y1, 1 )\n    <Float32Array>[ 4.0, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.sramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Evaluates the ramp function for each element in a single-precision floating-\n    point strided array `x` and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dramp, strided.ramp\n","base.strided.sramp.ndarray":"\nbase.strided.sramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Evaluates the ramp function for each element in a single-precision floating-\n    point strided array `x` and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dramp, strided.ramp","base.strided.srange":"\nbase.strided.srange( N, x, strideX )\n    Computes the range of a single-precision floating-point strided array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.srange( x.length, x, 1 )\n    4.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.srange( 3, x, 2 )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.srange( 3, x1, 2 )\n    4.0\n\n\nbase.strided.srange.ndarray( N, x, strideX, offsetX )\n    Computes the range of a single-precision floating-point strided array using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.srange.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.srange.ndarray( 3, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.drange, base.strided.smax, base.strided.smin, base.strided.snanrange, base.strided.range\n","base.strided.srange.ndarray":"\nbase.strided.srange.ndarray( N, x, strideX, offsetX )\n    Computes the range of a single-precision floating-point strided array using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.srange.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.srange.ndarray( 3, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.drange, base.strided.smax, base.strided.smin, base.strided.snanrange, base.strided.range","base.strided.srev":"\nbase.strided.srev( N, x, stride )\n    Reverses a single-precision floating-point strided array in-place.\n\n    The `N` and `stride` parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.srev( x.length, x, 1 )\n    <Float32Array>[ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.srev( 3, x, 2 )\n    <Float32Array>[ 4.0, 1.0, 3.0, -5.0, -2.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.srev( 3, x1, 2 )\n    <Float32Array>[ -6.0, 3.0, -4.0, 5.0, -2.0 ]\n    > x0\n    <Float32Array>[ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n\nbase.strided.srev.ndarray( N, x, stride, offset )\n    Reverses a single-precision floating-point strided array in-place using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.srev.ndarray( x.length, x, 1, 0 )\n    <Float32Array>[ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.srev.ndarray( 3, x, 2, 1 )\n    <Float32Array>[ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.drev, base.strided.grev\n","base.strided.srev.ndarray":"\nbase.strided.srev.ndarray( N, x, stride, offset )\n    Reverses a single-precision floating-point strided array in-place using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.srev.ndarray( x.length, x, 1, 0 )\n    <Float32Array>[ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.srev.ndarray( 3, x, 2, 1 )\n    <Float32Array>[ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.drev, base.strided.grev","base.strided.srsqrt":"\nbase.strided.srsqrt( N, x, strideX, y, strideY )\n    Computes the reciprocal square root for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.srsqrt( x.length, x, 1, y, 1 )\n    <Float32Array>[ 1.0, 0.5, ~0.333, ~0.289 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.srsqrt( N, x, 2, y, -1 )\n    <Float32Array>[ ~0.333, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.srsqrt( N, x1, -2, y1, 1 )\n    <Float32Array>[ ~0.289, 0.5 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.srsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the reciprocal square root for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.srsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 0.5, ~0.333, ~0.289 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.srsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n    See Also\n    --------\n    base.strided.drsqrt, strided.rsqrt, base.strided.ssqrt\n","base.strided.srsqrt.ndarray":"\nbase.strided.srsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the reciprocal square root for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.srsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 0.5, ~0.333, ~0.289 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.srsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n    See Also\n    --------\n    base.strided.drsqrt, strided.rsqrt, base.strided.ssqrt","base.strided.sscal":"\nbase.strided.sscal( N, alpha, x, stride )\n    Multiplies a single-precision floating-point vector `x` by a constant\n    `alpha`.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sscal( x.length, 5.0, x, 1 )\n    <Float32Array>[ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sscal( 3, 5.0, x, 2 )\n    <Float32Array>[ -10.0, 1.0, 15.0, -5.0, 20.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sscal( 3, 5.0, x1, 2 )\n    <Float32Array>[ -10.0, 3.0, -20.0, 5.0, -30.0 ]\n    > x0\n    <Float32Array>[ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n\nbase.strided.sscal.ndarray( N, alpha, x, stride, offset )\n    Multiplies a single-precision floating-point vector `x` by a constant\n    `alpha` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sscal.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float32Array>[ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.sscal.ndarray( 3, 5.0, x, 2, 1 )\n    <Float32Array>[ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n    See Also\n    --------\n    base.strided.daxpy, base.strided.dscal, base.strided.gscal, base.strided.saxpy\n","base.strided.sscal.ndarray":"\nbase.strided.sscal.ndarray( N, alpha, x, stride, offset )\n    Multiplies a single-precision floating-point vector `x` by a constant\n    `alpha` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sscal.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float32Array>[ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.sscal.ndarray( 3, 5.0, x, 2, 1 )\n    <Float32Array>[ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n    See Also\n    --------\n    base.strided.daxpy, base.strided.dscal, base.strided.gscal, base.strided.saxpy","base.strided.ssort2hp":"\nbase.strided.ssort2hp( N, order, x, strideX, y, strideY )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using heapsort.\n\n    The `N` and `stride` parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided arrays are sorted *in-place* (i.e., the input strided\n    arrays are *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2hp( x.length, 1, x, 1, y, 1 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float32Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2hp( 2, -1, x, 2, y, 2 )\n    <Float32Array>[ 3.0, -2.0, 1.0, -4.0 ]\n    > y\n    <Float32Array>[ 2.0, 1.0, 0.0, 3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n    > base.strided.ssort2hp( 2, 1, x1, 2, y1, 2 )\n    <Float32Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.ssort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using heapsort and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float32Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2hp.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float32Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2hp, base.strided.gsort2hp, base.strided.ssorthp\n","base.strided.ssort2hp.ndarray":"\nbase.strided.ssort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using heapsort and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float32Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2hp.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float32Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2hp, base.strided.gsort2hp, base.strided.ssorthp","base.strided.ssort2ins":"\nbase.strided.ssort2ins( N, order, x, strideX, y, strideY )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using insertion sort.\n\n    The `N` and stride parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function leaves the strided arrays\n    are unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^2).\n\n    The algorithm is efficient for *small* strided arrays (typically N <= 20)\n    and is particularly efficient for sorting strided arrays which are already\n    substantially sorted.\n\n    The algorithm is *stable*, meaning that the algorithm does *not* change the\n    order of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided arrays are sorted *in-place* (i.e., the input strided\n    arrays is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    x: Float32Array\n        First input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2ins( x.length, 1, x, 1, y, 1 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float32Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2ins( 2, -1, x, 2, y, 2 )\n    <Float32Array>[ 3.0, -2.0, 1.0, -4.0 ]\n    > y\n    <Float32Array>[ 2.0, 1.0, 0.0, 3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n    > base.strided.ssort2ins( 2, 1, x1, 2, y1, 2 )\n    <Float32Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.ssort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using insertion sort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float32Array\n        First input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float32Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float32Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2ins, base.strided.gsort2ins, base.strided.ssortins\n","base.strided.ssort2ins.ndarray":"\nbase.strided.ssort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using insertion sort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float32Array\n        First input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float32Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float32Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2ins, base.strided.gsort2ins, base.strided.ssortins","base.strided.ssort2sh":"\nbase.strided.ssort2sh( N, order, x, strideX, y, strideY )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using Shellsort.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^(4/3)).\n\n    The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided arrays are sorted *in-place* (i.e., the input strided\n    arrays are *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2sh( x.length, 1, x, 1, y, 1 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float32Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2sh( 2, -1, x, 2, y, 2 )\n    <Float32Array>[ 3.0, -2.0, 1.0, -4.0 ]\n    > y\n    <Float32Array>[ 2.0, 1.0, 0.0, 3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n    > base.strided.ssort2sh( 2, 1, x1, 2, y1, 2 )\n    <Float32Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.ssort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using Shellsort and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float32Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2sh.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float32Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2sh, base.strided.gsort2sh, base.strided.ssortsh\n","base.strided.ssort2sh.ndarray":"\nbase.strided.ssort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using Shellsort and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float32Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2sh.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float32Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2sh, base.strided.gsort2sh, base.strided.ssortsh","base.strided.ssorthp":"\nbase.strided.ssorthp( N, order, x, stride )\n    Sorts a single-precision floating-point strided array using heapsort.\n\n    The `N` and stride parameters determine which elements in the strided\n    array are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function returns the strided\n    array unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided array is sorted *in-place* (i.e., the input strided array\n    is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts the strided array in\n        decreasing order. If `order > 0`, the function sorts the strided array\n        in increasing order.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for the strided array.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array the strided array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssorthp( x.length, 1, x, 1 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssorthp( 2, -1, x, 2 )\n    <Float32Array>[ 3.0, -2.0, 1.0, -4.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.ssorthp( 2, 1, x1, 2 )\n    <Float32Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.ssorthp.ndarray( N, order, x, stride, offset )\n    Sorts a single-precision floating-point strided array using heapsort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts the strided array in\n        decreasing order. If `order > 0`, the function sorts the strided array\n        in increasing order.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for the strided array.\n\n    offset: integer\n        Starting index of the strided array.\n\n    Returns\n    -------\n    x: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssorthp.ndarray( x.length, 1, x, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssorthp.ndarray( 2, 1, x, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsorthp, base.strided.gsorthp, base.strided.ssort2hp\n","base.strided.ssorthp.ndarray":"\nbase.strided.ssorthp.ndarray( N, order, x, stride, offset )\n    Sorts a single-precision floating-point strided array using heapsort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts the strided array in\n        decreasing order. If `order > 0`, the function sorts the strided array\n        in increasing order.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for the strided array.\n\n    offset: integer\n        Starting index of the strided array.\n\n    Returns\n    -------\n    x: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssorthp.ndarray( x.length, 1, x, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssorthp.ndarray( 2, 1, x, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsorthp, base.strided.gsorthp, base.strided.ssort2hp","base.strided.ssortins":"\nbase.strided.ssortins( N, order, x, stride )\n    Sorts a single-precision floating-point strided array using insertion sort.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^2).\n\n    The algorithm is efficient for *small* strided arrays (typically N <= 20)\n    and is particularly efficient for sorting strided arrays which are already\n    substantially sorted.\n\n    The algorithm is *stable*, meaning that the algorithm does *not* change the\n    order of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided array is sorted *in-place* (i.e., the input strided array\n    is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortins( x.length, 1, x, 1 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortins( 2, -1, x, 2 )\n    <Float32Array>[ 3.0, -2.0, 1.0, -4.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.ssortins( 2, 1, x1, 2 )\n    <Float32Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.ssortins.ndarray( N, order, x, stride, offset )\n    Sorts a single-precision floating-point strided array using insertion sort\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortins.ndarray( x.length, 1, x, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortins.ndarray( 2, 1, x, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsortins, base.strided.gsortins, base.strided.ssort2ins\n","base.strided.ssortins.ndarray":"\nbase.strided.ssortins.ndarray( N, order, x, stride, offset )\n    Sorts a single-precision floating-point strided array using insertion sort\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortins.ndarray( x.length, 1, x, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortins.ndarray( 2, 1, x, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsortins, base.strided.gsortins, base.strided.ssort2ins","base.strided.ssortsh":"\nbase.strided.ssortsh( N, order, x, stride )\n    Sorts a single-precision floating-point strided array using Shellsort.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^(4/3)).\n\n    The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided array is sorted *in-place* (i.e., the input strided array\n    is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortsh( x.length, 1, x, 1 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortsh( 2, -1, x, 2 )\n    <Float32Array>[ 3.0, -2.0, 1.0, -4.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.ssortsh( 2, 1, x1, 2 )\n    <Float32Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.ssortsh.ndarray( N, order, x, stride, offset )\n    Sorts a single-precision floating-point strided array using Shellsort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortsh.ndarray( x.length, 1, x, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortsh.ndarray( 2, 1, x, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsortsh, base.strided.gsortsh, base.strided.ssort2sh\n","base.strided.ssortsh.ndarray":"\nbase.strided.ssortsh.ndarray( N, order, x, stride, offset )\n    Sorts a single-precision floating-point strided array using Shellsort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortsh.ndarray( x.length, 1, x, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortsh.ndarray( 2, 1, x, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsortsh, base.strided.gsortsh, base.strided.ssort2sh","base.strided.ssqrt":"\nbase.strided.ssqrt( N, x, strideX, y, strideY )\n    Computes the principal square root for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.ssqrt( x.length, x, 1, y, 1 )\n    <Float32Array>[ 0.0, 2.0, 3.0, ~3.464 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.ssqrt( N, x, 2, y, -1 )\n    <Float32Array>[ 3.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.ssqrt( N, x1, -2, y1, 1 )\n    <Float32Array>[ ~3.464, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.ssqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the principal square root for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.ssqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, 2.0, 3.0, ~3.464 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.ssqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dsqrt, base.strided.scbrt, strided.sqrt, base.strided.srsqrt\n","base.strided.ssqrt.ndarray":"\nbase.strided.ssqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the principal square root for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.ssqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, 2.0, 3.0, ~3.464 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.ssqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dsqrt, base.strided.scbrt, strided.sqrt, base.strided.srsqrt","base.strided.sstdev":"\nbase.strided.sstdev( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdev( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sstdev( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sstdev( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.sstdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdev, base.strided.snanstdev, base.strided.stdev, base.strided.svariance\n","base.strided.sstdev.ndarray":"\nbase.strided.sstdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdev, base.strided.snanstdev, base.strided.stdev, base.strided.svariance","base.strided.sstdevch":"\nbase.strided.sstdevch( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevch( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sstdevch( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sstdevch( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.sstdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevch, base.strided.snanstdevch, base.strided.sstdev, base.strided.stdevch, base.strided.svariancech\n","base.strided.sstdevch.ndarray":"\nbase.strided.sstdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevch, base.strided.snanstdevch, base.strided.sstdev, base.strided.stdevch, base.strided.svariancech","base.strided.sstdevpn":"\nbase.strided.sstdevpn( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevpn( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sstdevpn( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sstdevpn( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.sstdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevpn, base.strided.snanstdevpn, base.strided.sstdev, base.strided.stdevpn, base.strided.svariancepn\n","base.strided.sstdevpn.ndarray":"\nbase.strided.sstdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevpn, base.strided.snanstdevpn, base.strided.sstdev, base.strided.stdevpn, base.strided.svariancepn","base.strided.sstdevtk":"\nbase.strided.sstdevtk( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevtk( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sstdevtk( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sstdevtk( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.sstdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass textbook algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevtk, base.strided.snanstdevtk, base.strided.sstdev, base.strided.stdevtk, base.strided.svariancetk\n","base.strided.sstdevtk.ndarray":"\nbase.strided.sstdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass textbook algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevtk, base.strided.snanstdevtk, base.strided.sstdev, base.strided.stdevtk, base.strided.svariancetk","base.strided.sstdevwd":"\nbase.strided.sstdevwd( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevwd( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sstdevwd( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sstdevwd( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.sstdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevwd, base.strided.snanstdevwd, base.strided.sstdev, base.strided.stdevwd, base.strided.svariancewd\n","base.strided.sstdevwd.ndarray":"\nbase.strided.sstdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevwd, base.strided.snanstdevwd, base.strided.sstdev, base.strided.stdevwd, base.strided.svariancewd","base.strided.sstdevyc":"\nbase.strided.sstdevyc( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevyc( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sstdevyc( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sstdevyc( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.sstdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevyc, base.strided.snanstdevyc, base.strided.sstdev, base.strided.stdevyc, base.strided.svarianceyc\n","base.strided.sstdevyc.ndarray":"\nbase.strided.sstdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevyc, base.strided.snanstdevyc, base.strided.sstdev, base.strided.stdevyc, base.strided.svarianceyc","base.strided.ssum":"\nbase.strided.ssum( N, x, stride )\n    Computes the sum of single-precision floating-point strided array elements.\n\n    The `N` and `stride` parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssum( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.ssum( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.ssum( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.ssum.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.ssum.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsum, base.strided.smean, base.strided.snansum, base.strided.gsum\n","base.strided.ssum.ndarray":"\nbase.strided.ssum.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.ssum.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsum, base.strided.smean, base.strided.snansum, base.strided.gsum","base.strided.ssumkbn":"\nbase.strided.ssumkbn( N, x, stride )\n    Computes the sum of single-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumkbn( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.ssumkbn( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.ssumkbn( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.ssumkbn.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.ssumkbn.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumkbn, base.strided.gsumkbn, base.strided.snansumkbn, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors, base.strided.ssumpw\n","base.strided.ssumkbn.ndarray":"\nbase.strided.ssumkbn.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.ssumkbn.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumkbn, base.strided.gsumkbn, base.strided.snansumkbn, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors, base.strided.ssumpw","base.strided.ssumkbn2":"\nbase.strided.ssumkbn2( N, x, stride )\n    Computes the sum of single-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in  the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumkbn2( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.ssumkbn2( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.ssumkbn2( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.ssumkbn2.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.ssumkbn2.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumkbn2, base.strided.gsumkbn2, base.strided.snansumkbn2, base.strided.ssum, base.strided.ssumkbn, base.strided.ssumors, base.strided.ssumpw\n","base.strided.ssumkbn2.ndarray":"\nbase.strided.ssumkbn2.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.ssumkbn2.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumkbn2, base.strided.gsumkbn2, base.strided.snansumkbn2, base.strided.ssum, base.strided.ssumkbn, base.strided.ssumors, base.strided.ssumpw","base.strided.ssumors":"\nbase.strided.ssumors( N, x, strideX )\n    Computes the sum of single-precision floating-point strided array elements\n    using ordinary recursive summation.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumors( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.ssumors( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.ssumors( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.ssumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements\n    using ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.ssumors.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumors, base.strided.gsumors, base.strided.snansumors, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumpw\n","base.strided.ssumors.ndarray":"\nbase.strided.ssumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements\n    using ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.ssumors.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumors, base.strided.gsumors, base.strided.snansumors, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumpw","base.strided.ssumpw":"\nbase.strided.ssumpw( N, x, strideX )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumpw( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.ssumpw( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.ssumpw( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.ssumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.ssumpw.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumpw, base.strided.gsumpw, base.strided.snansumpw, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors\n","base.strided.ssumpw.ndarray":"\nbase.strided.ssumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.ssumpw.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumpw, base.strided.gsumpw, base.strided.snansumpw, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors","base.strided.sswap":"\nbase.strided.sswap( N, x, strideX, y, strideY )\n    Interchanges two single-precision floating-point vectors.\n\n    The `N` and stride parameters determine how values from `x` are swapped\n    with values from `y`.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the vectors are unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Second input array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.sswap( x.length, x, 1, y, 1 )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.sswap( 3, x, -2, y, 1 )\n    <Float32Array>[ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n    // Using typed array views:\n    > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.sswap( 3, x1, -2, y1, 1 )\n    <Float32Array>[ 6.0, 4.0, 2.0 ]\n    > y0\n    <Float32Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.sswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Interchanges two single-precision floating-point vectors using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Second input array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.sswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.sswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dswap, base.strided.gswap, base.strided.scopy, sswap\n","base.strided.sswap.ndarray":"\nbase.strided.sswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Interchanges two single-precision floating-point vectors using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Second input array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.sswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.sswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dswap, base.strided.gswap, base.strided.scopy, sswap","base.strided.stdev":"\nbase.strided.stdev( N, correction, x, stride )\n    Computes the standard deviation of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdev( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.stdev( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.stdev( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.stdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdev, base.strided.nanstdev, base.strided.sstdev, base.strided.variance\n","base.strided.stdev.ndarray":"\nbase.strided.stdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdev, base.strided.nanstdev, base.strided.sstdev, base.strided.variance","base.strided.stdevch":"\nbase.strided.stdevch( N, correction, x, stride )\n    Computes the standard deviation of a strided array using a one-pass trial\n    mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevch( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.stdevch( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.stdevch( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.stdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using a one-pass trial\n    mean algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevch, base.strided.nanstdevch, base.strided.sstdevch, base.strided.stdev, base.strided.variancech\n","base.strided.stdevch.ndarray":"\nbase.strided.stdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using a one-pass trial\n    mean algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevch, base.strided.nanstdevch, base.strided.sstdevch, base.strided.stdev, base.strided.variancech","base.strided.stdevpn":"\nbase.strided.stdevpn( N, correction, x, stride )\n    Computes the standard deviation of a strided array using a two-pass\n    algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevpn( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.stdevpn( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.stdevpn( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.stdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using a two-pass\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.sstdevpn, base.strided.stdev, base.strided.variancepn\n","base.strided.stdevpn.ndarray":"\nbase.strided.stdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using a two-pass\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.sstdevpn, base.strided.stdev, base.strided.variancepn","base.strided.stdevtk":"\nbase.strided.stdevtk( N, correction, x, stride )\n    Computes the standard deviation of a strided array using a one-pass textbook\n    algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevtk( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.stdevtk( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.stdevtk( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.stdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using a one-pass textbook\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.sstdevtk, base.strided.stdev, base.strided.variancetk\n","base.strided.stdevtk.ndarray":"\nbase.strided.stdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using a one-pass textbook\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.sstdevtk, base.strided.stdev, base.strided.variancetk","base.strided.stdevwd":"\nbase.strided.stdevwd( N, correction, x, stride )\n    Computes the standard deviation of a strided array using Welford's\n    algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevwd( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.stdevwd( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.stdevwd( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.stdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using Welford's algorithm\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.sstdevwd, base.strided.stdev, base.strided.variancewd\n","base.strided.stdevwd.ndarray":"\nbase.strided.stdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using Welford's algorithm\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.sstdevwd, base.strided.stdev, base.strided.variancewd","base.strided.stdevyc":"\nbase.strided.stdevyc( N, correction, x, stride )\n    Computes the standard deviation of a strided array using a one-pass\n    algorithm proposed by Youngs and Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevyc( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.stdevyc( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.stdevyc( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.stdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using a one-pass\n    algorithm proposed by Youngs and Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.sstdevyc, base.strided.stdev, base.strided.varianceyc\n","base.strided.stdevyc.ndarray":"\nbase.strided.stdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using a one-pass\n    algorithm proposed by Youngs and Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.sstdevyc, base.strided.stdev, base.strided.varianceyc","base.strided.strunc":"\nbase.strided.strunc( N, x, strideX, y, strideY )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward zero and assigns the results to elements in a single-precision\n    floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.strunc( x.length, x, 1, y, 1 )\n    <Float32Array>[ 1.0, 2.0, -3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.strunc( N, x, 2, y, -1 )\n    <Float32Array>[ -3.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.strunc( N, x1, -2, y1, 1 )\n    <Float32Array>[ 4.0, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.strunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward zero and assigns the results to elements in a single-precision\n    floating-point strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.strunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.strunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dtrunc, base.strided.sceil, base.strided.sfloor, strided.trunc\n","base.strided.strunc.ndarray":"\nbase.strided.strunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward zero and assigns the results to elements in a single-precision\n    floating-point strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.strunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.strunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dtrunc, base.strided.sceil, base.strided.sfloor, strided.trunc","base.strided.svariance":"\nbase.strided.svariance( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariance( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.svariance( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.svariance( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.svariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariance, base.strided.snanvariance, base.strided.sstdev, base.strided.variance\n","base.strided.svariance.ndarray":"\nbase.strided.svariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariance, base.strided.snanvariance, base.strided.sstdev, base.strided.variance","base.strided.svariancech":"\nbase.strided.svariancech( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancech( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.svariancech( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.svariancech( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.svariancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass trial mean algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svariancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancech, base.strided.snanvariancech, base.strided.sstdevch, base.strided.svariance, base.strided.variancech\n","base.strided.svariancech.ndarray":"\nbase.strided.svariancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass trial mean algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svariancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancech, base.strided.snanvariancech, base.strided.sstdevch, base.strided.svariance, base.strided.variancech","base.strided.svariancepn":"\nbase.strided.svariancepn( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancepn( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.svariancepn( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.svariancepn( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.svariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancepn, base.strided.snanvariancepn, base.strided.sstdevpn, base.strided.svariance, base.strided.variancepn\n","base.strided.svariancepn.ndarray":"\nbase.strided.svariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancepn, base.strided.snanvariancepn, base.strided.sstdevpn, base.strided.svariance, base.strided.variancepn","base.strided.svariancetk":"\nbase.strided.svariancetk( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancetk( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.svariancetk( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.svariancetk( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.svariancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass textbook algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svariancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancetk, base.strided.snanvariancetk, base.strided.sstdevtk, base.strided.svariance, base.strided.variancetk\n","base.strided.svariancetk.ndarray":"\nbase.strided.svariancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass textbook algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svariancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancetk, base.strided.snanvariancetk, base.strided.sstdevtk, base.strided.svariance, base.strided.variancetk","base.strided.svariancewd":"\nbase.strided.svariancewd( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancewd( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.svariancewd( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.svariancewd( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.svariancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svariancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancewd, base.strided.snanvariancewd, base.strided.sstdevwd, base.strided.svariance, base.strided.variancewd\n","base.strided.svariancewd.ndarray":"\nbase.strided.svariancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svariancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancewd, base.strided.snanvariancewd, base.strided.sstdevwd, base.strided.svariance, base.strided.variancewd","base.strided.svarianceyc":"\nbase.strided.svarianceyc( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass algorithm proposed by Youngs and Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svarianceyc( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.svarianceyc( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.svarianceyc( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.svarianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass algorithm proposed by Youngs and Cramer and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svarianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svarianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvarianceyc, base.strided.snanvarianceyc, base.strided.sstdevyc, base.strided.svariance, base.strided.varianceyc\n","base.strided.svarianceyc.ndarray":"\nbase.strided.svarianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass algorithm proposed by Youngs and Cramer and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svarianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svarianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvarianceyc, base.strided.snanvarianceyc, base.strided.sstdevyc, base.strided.svariance, base.strided.varianceyc","base.strided.ternary":"\nbase.strided.ternary( arrays, shape, strides, fcn )\n    Applies a ternary callback to strided input array elements and assigns\n    results to elements in a strided output array.\n\n    The `shape` and `strides` parameters determine which elements in the strided\n    input and output arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing three strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    fcn: Function\n        Ternary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1, 1 ];\n    > function f( x, y, z ) { return x + y + z; };\n    > base.strided.ternary( [ x, y, z, w ], shape, strides, f );\n    > w\n    <Float64Array>[ 3.0, 6.0, 9.0, 12.0 ]\n\n\nbase.strided.ternary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a ternary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing three strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Ternary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1, 1 ];\n    > var offsets = [ 0, 0, 0, 0 ];\n    > function f( x, y, z ) { return x + y + z; };\n    > base.strided.ternary.ndarray( [ x, y, z, w ], shape, strides, offsets, f );\n    > w\n    <Float64Array>[ 3.0, 6.0, 9.0, 12.0 ]\n\n    See Also\n    --------\n    base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.unary\n","base.strided.ternary.ndarray":"\nbase.strided.ternary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a ternary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing three strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Ternary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1, 1 ];\n    > var offsets = [ 0, 0, 0, 0 ];\n    > function f( x, y, z ) { return x + y + z; };\n    > base.strided.ternary.ndarray( [ x, y, z, w ], shape, strides, offsets, f );\n    > w\n    <Float64Array>[ 3.0, 6.0, 9.0, 12.0 ]\n\n    See Also\n    --------\n    base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.unary","base.strided.unary":"\nbase.strided.unary( arrays, shape, strides, fcn )\n    Applies a unary callback to elements in a strided input array and assigns\n    results to elements in a strided output array.\n\n    The `shape` and `strides` parameters determine which elements in the strided\n    input and output arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided input array and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    fcn: Function\n        Unary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1 ];\n    > base.strided.unary( [ x, y ], shape, strides, base.abs );\n    > y\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n\nbase.strided.unary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a unary callback to elements in a strided input array and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided input array and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Unary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1 ];\n    > var offsets = [ 0, 0 ];\n    > base.strided.unary.ndarray( [ x, y ], shape, strides, offsets, base.abs );\n    > y\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    See Also\n    --------\n    base.strided.unary, base.strided.dmap, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap, base.strided.ternary\n","base.strided.unary.ndarray":"\nbase.strided.unary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a unary callback to elements in a strided input array and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided input array and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Unary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1 ];\n    > var offsets = [ 0, 0 ];\n    > base.strided.unary.ndarray( [ x, y ], shape, strides, offsets, base.abs );\n    > y\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    See Also\n    --------\n    base.strided.unary, base.strided.dmap, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap, base.strided.ternary","base.strided.unaryBy":"\nbase.strided.unaryBy( arrays, shape, strides, fcn, clbk[, thisArg] )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array.\n\n    The shape and stride parameters determine which elements in the strided\n    input and output arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - indices: strided indices (offset + idx*stride).\n    - arrays: input and output arrays.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided input array and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    fcn: Function\n        Unary function to apply to callback return values.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > var sh = [ x.length ];\n    > var st = [ 1, 1 ];\n    > function clbk( v ) { return v * 2.0; };\n    > base.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\n    > y\n    [ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Using shape and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > sh = [ 2 ];\n    > st = [ 2, -1 ];\n    > base.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\n    > y\n    [ 6.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > sh = [ 2 ];\n    > st = [ -2, 1 ];\n    > base.strided.unaryBy( [ x1, y1 ], sh, st, base.abs, clbk );\n    > y1\n    <Float64Array>[ 8.0, 4.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 8.0, 4.0 ]\n\n\nbase.strided.unaryBy.ndarray( arrays, shape, strides, offsets, fcn, clbk[, thisArg] )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offsest parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided input array and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Unary function to apply to callback return values.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > var sh = [ x.length ];\n    > var st = [ 1, 1 ];\n    > var o = [ 0, 0 ];\n    > function clbk( v ) { return v * 2.0; };\n    > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n    > y\n    [ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > sh = [ 2 ];\n    > st = [ 2, -1 ];\n    > o = [ 1, y.length-1 ];\n    > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n    > y\n    [ 0.0, 0.0, 8.0, 4.0 ]\n\n    See Also\n    --------\n    base.strided.mapBy, base.strided.unary\n","base.strided.unaryBy.ndarray":"\nbase.strided.unaryBy.ndarray( arrays, shape, strides, offsets, fcn, clbk[, thisArg] )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offsest parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided input array and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Unary function to apply to callback return values.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > var sh = [ x.length ];\n    > var st = [ 1, 1 ];\n    > var o = [ 0, 0 ];\n    > function clbk( v ) { return v * 2.0; };\n    > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n    > y\n    [ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > sh = [ 2 ];\n    > st = [ 2, -1 ];\n    > o = [ 1, y.length-1 ];\n    > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n    > y\n    [ 0.0, 0.0, 8.0, 4.0 ]\n\n    See Also\n    --------\n    base.strided.mapBy, base.strided.unary","base.strided.unaryDtypeSignatures":"\nbase.strided.unaryDtypeSignatures( dtypes1, dtypes2[, options] )\n    Generates a list of unary interface signatures from strided array data\n    types.\n\n    The function returns a strided array having a stride length of two (i.e.,\n    every two elements define a unary interface signature).\n\n    For each signature (i.e., set of two consecutive non-overlapping strided\n    array elements), the first element is the input data type and the second\n    element is the return data type.\n\n    All signatures follow type promotion rules.\n\n    Parameters\n    ----------\n    dtypes1: ArrayLike<any>\n        List of supported data types for the input argument.\n\n    dtypes2: ArrayLike<any>\n        List of supported data types for the output argument.\n\n    options: Object (optional)\n        Options.\n\n    options.enums: boolean (optional)\n        Boolean flag indicating whether to return signatures as a list of data\n        type enumeration constants. Default: false.\n\n    Returns\n    -------\n    out: Array\n        Strided array containing unary interface signatures.\n\n    Examples\n    --------\n    > var dt = strided.dataTypes();\n    > var out = base.strided.unaryDtypeSignatures( dt, dt )\n    [...]\n\n    See Also\n    --------\n    base.strided.unarySignatureCallbacks\n","base.strided.unarySignatureCallbacks":"\nbase.strided.unarySignatureCallbacks( table, signatures )\n    Assigns callbacks to unary interfaces according to type promotion rules.\n\n    Parameters\n    ----------\n    table: Object\n        Object mapping callbacks to data types.\n\n    table.default: Function\n        Default callback.\n\n    table.complex64: Function\n        Callback to be invoked when input arrays promote to single-precision\n        complex floating-point numbers.\n\n    table.complex128: Function\n        Callback to be invoked when input arrays promote to double precision\n        complex floating-point numbers.\n\n    signatures: ArrayLike<any>\n        Strided array containing unary interface signatures.\n\n    Returns\n    -------\n    out: Array<Function>\n        List of callbacks, one per signature.\n\n    Examples\n    --------\n    > var dt = strided.dataTypes();\n    > var sigs = base.strided.unaryDtypeSignatures( dt, dt );\n    > var t = {\n    ...     'default': base.identity,\n    ...     'complex64': base.cidentityf,\n    ...     'complex128': base.cidentity\n    ... };\n    > var out = base.strided.unarySignatureCallbacks( t, sigs )\n    [...]\n\n    See Also\n    --------\n    base.strided.unaryDtypeSignatures\n","base.strided.variance":"\nbase.strided.variance( N, correction, x, stride )\n    Computes the variance of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variance( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.variance( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.variance( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.variance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.variance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariance, base.strided.nanvariance, base.strided.stdev, base.strided.svariance\n","base.strided.variance.ndarray":"\nbase.strided.variance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.variance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariance, base.strided.nanvariance, base.strided.stdev, base.strided.svariance","base.strided.variancech":"\nbase.strided.variancech( N, correction, x, stride )\n    Computes the variance of a strided array using a one-pass trial mean\n    algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancech( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.variancech( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.variancech( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.variancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using a one-pass trial mean\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.variancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancech, base.strided.nanvariancech, base.strided.stdevch, base.strided.variance\n","base.strided.variancech.ndarray":"\nbase.strided.variancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using a one-pass trial mean\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.variancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancech, base.strided.nanvariancech, base.strided.stdevch, base.strided.variance","base.strided.variancepn":"\nbase.strided.variancepn( N, correction, x, stride )\n    Computes the variance of a strided array using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancepn( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.variancepn( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.variancepn( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.variancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using a two-pass algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.variancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancepn, base.strided.nanvariancepn, base.strided.stdevpn, base.strided.variance\n","base.strided.variancepn.ndarray":"\nbase.strided.variancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using a two-pass algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.variancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancepn, base.strided.nanvariancepn, base.strided.stdevpn, base.strided.variance","base.strided.variancetk":"\nbase.strided.variancetk( N, correction, x, stride )\n    Computes the variance of a strided array using a one-pass textbook\n    algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancetk( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.variancetk( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.variancetk( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.variancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using a one-pass textbook algorithm\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.variancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancetk, base.strided.nanvariancetk, base.strided.stdevtk, base.strided.variance\n","base.strided.variancetk.ndarray":"\nbase.strided.variancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using a one-pass textbook algorithm\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.variancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancetk, base.strided.nanvariancetk, base.strided.stdevtk, base.strided.variance","base.strided.variancewd":"\nbase.strided.variancewd( N, correction, x, stride )\n    Computes the variance of a strided array using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancewd( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.variancewd( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.variancewd( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.variancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using Welford's algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.variancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancewd, base.strided.nanvariancewd, base.strided.stdevwd, base.strided.variance\n","base.strided.variancewd.ndarray":"\nbase.strided.variancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using Welford's algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.variancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancewd, base.strided.nanvariancewd, base.strided.stdevwd, base.strided.variance","base.strided.varianceyc":"\nbase.strided.varianceyc( N, correction, x, stride )\n    Computes the variance of a strided array using a one-pass algorithm proposed\n    by Youngs and Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.varianceyc( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.varianceyc( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.varianceyc( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.varianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using a one-pass algorithm proposed\n    by Youngs and Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.varianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.varianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvarianceyc, base.strided.nanvarianceyc, base.strided.stdevyc, base.strided.variance\n","base.strided.varianceyc.ndarray":"\nbase.strided.varianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using a one-pass algorithm proposed\n    by Youngs and Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.varianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.varianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvarianceyc, base.strided.nanvarianceyc, base.strided.stdevyc, base.strided.variance","base.strided.zmap":"\nbase.strided.zmap( N, x, strideX, y, strideY, fcn )\n    Applies a unary function to a double-precision complex floating-point\n    strided input array and assigns results to a double-precision complex\n    floating-point strided output array.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex128Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Complex128Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Complex128Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n    > var x = new Complex128Array( xbuf );\n    > var y = new Complex128Array( x.length );\n    > base.strided.zmap( x.length, x, 1, y, 1, base.cidentity );\n    > var v = y.get( 0 )\n    <Complex128>\n    > var re = real( v )\n    1.0\n    > var im = imag( v )\n    2.0\n\n    // Using `N` and stride parameters:\n    > y = new Complex128Array( x.length );\n    > base.strided.zmap( 2, x, 2, y, -1, base.cidentity );\n    > v = y.get( 0 )\n    <Complex128>\n    > re = real( v )\n    5.0\n    > im = imag( v )\n    6.0\n\n    // Using view offsets:\n    > var x0 = new Complex128Array( xbuf );\n    > var y0 = new Complex128Array( x0.length );\n    > var x1 = new Complex128Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Complex128Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.zmap( 2, x1, -2, y1, 1, base.cidentity );\n    > v = y1.get( 0 )\n    <Complex128>\n    > re = real( v )\n    7.0\n    > im = imag( v )\n    8.0\n\n\nbase.strided.zmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n    Applies a unary function to a double-precision complex floating-point\n    strided input array and assigns results to a double-precision complex\n    floating-point strided output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex128Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Complex128Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Complex128Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n    > var x = new Complex128Array( xbuf );\n    > var y = new Complex128Array( x.length );\n    > base.strided.zmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentity );\n    > var v = y.get( 0 )\n    <Complex128>\n    > var re = real( v )\n    1.0\n    > var im = imag( v )\n    2.0\n\n    // Advanced indexing:\n    > x = new Complex128Array( xbuf );\n    > y = new Complex128Array( x.length );\n    > base.strided.zmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentity );\n    > v = y.get( y.length-1 )\n    <Complex128>\n    > re = real( v )\n    3.0\n    > im = imag( v )\n    4.0\n\n    See Also\n    --------\n    base.strided.cmap, base.strided.unary\n","base.strided.zmap.ndarray":"\nbase.strided.zmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n    Applies a unary function to a double-precision complex floating-point\n    strided input array and assigns results to a double-precision complex\n    floating-point strided output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex128Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Complex128Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Complex128Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n    > var x = new Complex128Array( xbuf );\n    > var y = new Complex128Array( x.length );\n    > base.strided.zmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentity );\n    > var v = y.get( 0 )\n    <Complex128>\n    > var re = real( v )\n    1.0\n    > var im = imag( v )\n    2.0\n\n    // Advanced indexing:\n    > x = new Complex128Array( xbuf );\n    > y = new Complex128Array( x.length );\n    > base.strided.zmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentity );\n    > v = y.get( y.length-1 )\n    <Complex128>\n    > re = real( v )\n    3.0\n    > im = imag( v )\n    4.0\n\n    See Also\n    --------\n    base.strided.cmap, base.strided.unary","base.str2multislice":"\nbase.str2multislice( str )\n    Parses a string-serialized MultiSlice object.\n\n    The function returns `null` if provided an invalid string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    s: MultiSlice|null\n        MultiSlice instance (or null).\n\n    Examples\n    --------\n    > var s = new base.str2multislice( 'MultiSlice(null,null,null)' );\n    > s.data\n    [ null, null, null ]\n    > s = new base.str2multislice( 'MultiSlice(10,Slice(0,10,1),null)' );\n    > s.data\n    [ 10, <Slice>, null ]\n\n    See Also\n    --------\n    base.str2slice\n","base.str2slice":"\nbase.str2slice( str )\n    Parses a string-serialized Slice object.\n\n    The function returns `null` if provided an invalid string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    s: Slice|null\n        Slice instance (or null).\n\n    Examples\n    --------\n    > var s = new base.str2slice( 'Slice(1,10,1)' );\n    > s.start\n    1\n    > s.stop\n    10\n    > s.step\n    1\n    > s = new base.str2slice( 'Slice(2,5,2)' );\n    > s.start\n    2\n    > s.stop\n    5\n    > s.step\n    2\n\n    See Also\n    --------\n    base.str2multislice\n","base.sub":"\nbase.sub( x, y )\n    Subtracts two double-precision floating-point numbers `x` and `y`.\n\n    Parameters\n    ----------\n    x: number\n        First input value.\n\n    y: number\n        Second input value.\n\n    Returns\n    -------\n    z: number\n        Result.\n\n    Examples\n    --------\n    > var v = base.sub( -1.0, 5.0 )\n    -6.0\n    > v = base.sub( 2.0, 5.0 )\n    -3.0\n    > v = base.sub( 0.0, 5.0 )\n    -5.0\n    > v = base.sub( -0.0, 0.0 )\n    -0.0\n    > v = base.sub( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.add, base.div, base.mul\n","base.subf":"\nbase.subf( x, y )\n    Subtracts two single-precision floating-point numbers `x` and `y`.\n\n    Parameters\n    ----------\n    x: number\n        First input value.\n\n    y: number\n        Second input value.\n\n    Returns\n    -------\n    z: number\n        Result.\n\n    Examples\n    --------\n    > var v = base.subf( -1.0, 5.0 )\n    -6.0\n    > v = base.subf( 2.0, 5.0 )\n    -3.0\n    > v = base.subf( 0.0, 5.0 )\n    -5.0\n    > v = base.subf( -0.0, 0.0 )\n    -0.0\n    > v = base.subf( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.addf, base.divf, base.mulf, base.sub\n","base.sumSeries":"\nbase.sumSeries( generator[, options] )\n    Sum the elements of the series given by the supplied function.\n\n    Parameters\n    ----------\n    generator: Function\n        Series function.\n\n    options: Object (optional)\n        Options.\n\n    options.maxTerms: integer (optional)\n        Maximum number of terms to be added. Default: `1000000`.\n\n    options.tolerance: number (optional)\n        Further terms are only added as long as the next term is greater than\n        the current term times the tolerance. Default: `2.22e-16`.\n\n    options.initialValue: number (optional)\n        Initial value of the resulting sum. Default: `0`.\n\n    Returns\n    -------\n    out: number\n        Sum of series terms.\n\n    Examples\n    --------\n    // Using an ES6 generator function:\n    > function* geometricSeriesGenerator( x ) {\n    ...     var exponent = 0;\n    ...     while ( true ) {\n    ...         yield Math.pow( x, exponent );\n    ...         exponent += 1;\n    ...     }\n    ... };\n    > var gen = geometricSeriesGenerator( 0.9 );\n    > var out = base.sumSeries( gen )\n    10\n\n    // Using a closure:\n    > function geometricSeriesClosure( x ) {\n    ...     var exponent = -1;\n    ...     return function() {\n    ...         exponent += 1;\n    ...         return Math.pow( x, exponent );\n    ...     };\n    ... };\n    > gen = geometricSeriesClosure( 0.9 );\n    > out = base.sumSeries( gen )\n    10\n\n    // Setting an initial value for the sum:\n    > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'initialValue': 1 } )\n    3\n    // Changing the maximum number of terms to be summed:\n    > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'maxTerms': 10 } )\n    ~1.998 // Infinite sum is 2\n\n    // Adjusting the used tolerance:\n    > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'tolerance': 1e-3 } )\n    ~1.998\n\n","base.tan":"\nbase.tan( x )\n    Computes the tangent of a number.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Tangent.\n\n    Examples\n    --------\n    > var y = base.tan( 0.0 )\n    ~0.0\n    > y = base.tan( -PI/4.0 )\n    ~-1.0\n    > y = base.tan( PI/4.0 )\n    ~1.0\n    > y = base.tan( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cos, base.sin\n","base.tand":"\nbase.tand( x )\n    Computes the tangent of an angle measured in degrees.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in degrees).\n\n    Returns\n    -------\n    y: number\n        Tangent.\n\n    Examples\n    --------\n    > var y = base.tand( 0.0 )\n    0.0\n    > y = base.tand( 90.0 )\n    Infinity\n    > y = base.tand( 60.0 )\n    ~1.73\n    > y = base.tand( NaN )\n    NaN\n\n    See Also\n    --------\n    base.tan, base.cosd\n","base.tanh":"\nbase.tanh( x )\n    Computes the hyperbolic tangent of a double-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Hyperbolic tangent.\n\n    Examples\n    --------\n    > var y = base.tanh( 0.0 )\n    0.0\n    > var y = base.tanh( -0.0 )\n    -0.0\n    > y = base.tanh( 2.0 )\n    ~0.964\n    > y = base.tanh( -2.0 )\n    ~-0.964\n    > y = base.tanh( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cosh, base.sinh, base.tan\n","base.toBinaryString":"\nbase.toBinaryString( x )\n    Returns a string giving the literal bit representation of a double-precision\n    floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    Returns\n    -------\n    bstr: string\n        Bit representation.\n\n    Examples\n    --------\n    > var str = base.toBinaryString( 4.0 )\n    '0100000000010000000000000000000000000000000000000000000000000000'\n    > str = base.toBinaryString( PI )\n    '0100000000001001001000011111101101010100010001000010110100011000'\n    > str = base.toBinaryString( -1.0e308 )\n    '1111111111100001110011001111001110000101111010111100100010100000'\n    > str = base.toBinaryString( -3.14e-320 )\n    '1000000000000000000000000000000000000000000000000001100011010011'\n    > str = base.toBinaryString( 5.0e-324 )\n    '0000000000000000000000000000000000000000000000000000000000000001'\n    > str = base.toBinaryString( 0.0 )\n    '0000000000000000000000000000000000000000000000000000000000000000'\n    > str = base.toBinaryString( -0.0 )\n    '1000000000000000000000000000000000000000000000000000000000000000'\n    > str = base.toBinaryString( NaN )\n    '0111111111111000000000000000000000000000000000000000000000000000'\n    > str = base.toBinaryString( PINF )\n    '0111111111110000000000000000000000000000000000000000000000000000'\n    > str = base.toBinaryString( NINF )\n    '1111111111110000000000000000000000000000000000000000000000000000'\n\n    See Also\n    --------\n    base.fromBinaryString, base.toBinaryStringf\n","base.toBinaryStringf":"\nbase.toBinaryStringf( x )\n    Returns a string giving the literal bit representation of a single-precision\n    floating-point number.\n\n    Parameters\n    ----------\n    x: float\n        Single-precision floating-point number.\n\n    Returns\n    -------\n    str: string\n        Bit representation.\n\n    Examples\n    --------\n    > var str = base.toBinaryStringf( base.float64ToFloat32( 4.0 ) )\n    '01000000100000000000000000000000'\n    > str = base.toBinaryStringf( base.float64ToFloat32( PI ) )\n    '01000000010010010000111111011011'\n    > str = base.toBinaryStringf( base.float64ToFloat32( -1.0e38 ) )\n    '11111110100101100111011010011001'\n    > str = base.toBinaryStringf( base.float64ToFloat32( -3.14e-39 ) )\n    '10000000001000100011000100001011'\n    > str = base.toBinaryStringf( base.float64ToFloat32( 1.4e-45 ) )\n    '00000000000000000000000000000001'\n    > str = base.toBinaryStringf( 0.0 )\n    '00000000000000000000000000000000'\n    > str = base.toBinaryStringf( -0.0 )\n    '10000000000000000000000000000000'\n    > str = base.toBinaryStringf( NaN )\n    '01111111110000000000000000000000'\n    > str = base.toBinaryStringf( FLOAT32_PINF )\n    '01111111100000000000000000000000'\n    > str = base.toBinaryStringf( FLOAT32_NINF )\n    '11111111100000000000000000000000'\n\n    See Also\n    --------\n    base.fromBinaryStringf, base.toBinaryString\n","base.toBinaryStringUint8":"\nbase.toBinaryStringUint8( x )\n    Returns a string giving the literal bit representation of an unsigned 8-bit\n    integer.\n\n    Except for typed arrays, JavaScript does not provide native user support for\n    unsigned 8-bit integers. According to the ECMAScript standard, `number`\n    values correspond to double-precision floating-point numbers. While this\n    function is intended for unsigned 8-bit integers, the function will accept\n    floating-point values and represent the values as if they are unsigned 8-bit\n    integers. Accordingly, care should be taken to ensure that only nonnegative\n    integer values less than `256` (`2^8`) are provided.\n\n    Parameters\n    ----------\n    x: integer\n        Input value.\n\n    Returns\n    -------\n    str: string\n        Bit representation.\n\n    Examples\n    --------\n    > var a = new Uint8Array( [ 1, 4, 9 ] );\n    > var str = base.toBinaryStringUint8( a[ 0 ] )\n    '00000001'\n    > str = base.toBinaryStringUint8( a[ 1 ] )\n    '00000100'\n    > str = base.toBinaryStringUint8( a[ 2 ] )\n    '00001001'\n\n    See Also\n    --------\n    base.toBinaryString\n","base.toBinaryStringUint16":"\nbase.toBinaryStringUint16( x )\n    Returns a string giving the literal bit representation of an unsigned 16-bit\n    integer.\n\n    Except for typed arrays, JavaScript does not provide native user support for\n    unsigned 16-bit integers. According to the ECMAScript standard, `number`\n    values correspond to double-precision floating-point numbers. While this\n    function is intended for unsigned 16-bit integers, the function will accept\n    floating-point values and represent the values as if they are unsigned\n    16-bit integers. Accordingly, care should be taken to ensure that only\n    nonnegative integer values less than `65536` (`2^16`) are provided.\n\n    Parameters\n    ----------\n    x: integer\n        Input value.\n\n    Returns\n    -------\n    str: string\n        Bit representation.\n\n    Examples\n    --------\n    > var a = new Uint16Array( [ 1, 4, 9 ] );\n    > var str = base.toBinaryStringUint16( a[ 0 ] )\n    '0000000000000001'\n    > str = base.toBinaryStringUint16( a[ 1 ] )\n    '0000000000000100'\n    > str = base.toBinaryStringUint16( a[ 2 ] )\n    '0000000000001001'\n\n    See Also\n    --------\n    base.toBinaryString\n","base.toBinaryStringUint32":"\nbase.toBinaryStringUint32( x )\n    Returns a string giving the literal bit representation of an unsigned 32-bit\n    integer.\n\n    Except for typed arrays, JavaScript does not provide native user support for\n    unsigned 32-bit integers. According to the ECMAScript standard, `number`\n    values correspond to double-precision floating-point numbers. While this\n    function is intended for unsigned 32-bit integers, the function will accept\n    floating-point values and represent the values as if they are unsigned\n    32-bit integers. Accordingly, care should be taken to ensure that only\n    nonnegative integer values less than `4,294,967,296` (`2^32`) are provided.\n\n    Parameters\n    ----------\n    x: integer\n        Input value.\n\n    Returns\n    -------\n    str: string\n        Bit representation.\n\n    Examples\n    --------\n    > var a = new Uint32Array( [ 1, 4, 9 ] );\n    > var str = base.toBinaryStringUint32( a[ 0 ] )\n    '00000000000000000000000000000001'\n    > str = base.toBinaryStringUint32( a[ 1 ] )\n    '00000000000000000000000000000100'\n    > str = base.toBinaryStringUint32( a[ 2 ] )\n    '00000000000000000000000000001001'\n\n    See Also\n    --------\n    base.toBinaryString\n","base.toWordf":"\nbase.toWordf( x )\n    Returns an unsigned 32-bit integer corresponding to the IEEE 754 binary\n    representation of a single-precision floating-point number.\n\n    Parameters\n    ----------\n    x: float\n        Single-precision floating-point number.\n\n    Returns\n    -------\n    out: integer\n        Unsigned 32-bit integer.\n\n    Examples\n    --------\n    > var f32 = base.float64ToFloat32( 1.337 )\n    1.3370000123977661\n    > var w = base.toWordf( f32 )\n    1068180177\n\n    See Also\n    --------\n    base.fromWordf, base.toWords\n","base.toWords":"\nbase.toWords( x )\n    Splits a double-precision floating-point number into a higher order word\n    (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n\n    When provided a destination object, the function returns an array with two\n    elements: a higher order word and a lower order word, respectively. The\n    lower order word contains the less significant bits, while the higher order\n    word contains the more significant bits and includes the exponent and sign.\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    Returns\n    -------\n    out: Array<integer>\n        Higher and lower order words.\n\n    Examples\n    --------\n    > var w = base.toWords( 3.14e201 )\n    [ 1774486211, 2479577218 ]\n\n\nbase.toWords.assign( x, out, stride, offset )\n    Splits a double-precision floating-point number into a higher order word\n    (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer)\n    and assigns results to a provided output array.\n\n    When provided a destination object, the function returns an array with two\n    elements: a higher order word and a lower order word, respectively. The\n    lower order word contains the less significant bits, while the higher order\n    word contains the more significant bits and includes the exponent and sign.\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Higher and lower order words.\n\n    Examples\n    --------\n    > var out = new Uint32Array( 2 );\n    > var w = base.toWords.assign( 3.14e201, out, 1, 0 )\n    <Uint32Array>[ 1774486211, 2479577218 ]\n    > var bool = ( w === out )\n    true\n\n    See Also\n    --------\n    base.fromWords, base.toWordf","base.toWords.assign":"\nbase.toWords.assign( x, out, stride, offset )\n    Splits a double-precision floating-point number into a higher order word\n    (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer)\n    and assigns results to a provided output array.\n\n    When provided a destination object, the function returns an array with two\n    elements: a higher order word and a lower order word, respectively. The\n    lower order word contains the less significant bits, while the higher order\n    word contains the more significant bits and includes the exponent and sign.\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Higher and lower order words.\n\n    Examples\n    --------\n    > var out = new Uint32Array( 2 );\n    > var w = base.toWords.assign( 3.14e201, out, 1, 0 )\n    <Uint32Array>[ 1774486211, 2479577218 ]\n    > var bool = ( w === out )\n    true\n\n    See Also\n    --------\n    base.fromWords, base.toWordf","base.transpose":"\nbase.transpose( x )\n    Transposes a matrix (or a stack of matrices).\n\n    The returned ndarray is a *view* of the input ndarray. Accordingly, writing\n    to the original ndarray will mutate the returned ndarray and vice versa.\n    While powerful, this can lead to subtle bugs. In general, one should handle\n    the returned ndarray as read-only.\n\n    If provided an ndarray with fewer than two dimensions, the function raises\n    an exception.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n    <ndarray>\n    > var sh = x.shape\n    [ 2, 3 ]\n    > var y = base.transpose( x )\n    <ndarray>\n    > sh = y.shape\n    [ 3, 2 ]\n    > var bool = ( x.data === y.data )\n    true\n    > bool = ( x.get( 0, 1 ) === y.get( 1, 0 ) )\n    true\n\n    See Also\n    --------\n    ndarray\n","base.tribonacci":"\nbase.tribonacci( n )\n    Computes the nth Tribonacci number.\n\n    Tribonacci numbers follow the recurrence relation\n\n      F_n = F_{n-1} + F_{n-2} + F_{n-3}\n\n    with seed values F_0 = 0, F_1 = 0, and F_2 = 1.\n\n    If `n` is greater than `63`, the function returns `NaN`, as larger\n    Tribonacci numbers cannot be accurately represented due to limitations of\n    double-precision floating-point format.\n\n    If not provided a nonnegative integer value, the function returns `NaN`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Input value.\n\n    Returns\n    -------\n    y: integer\n        Tribonacci number.\n\n    Examples\n    --------\n    > var y = base.tribonacci( 0 )\n    0\n    > y = base.tribonacci( 1 )\n    0\n    > y = base.tribonacci( 2 )\n    1\n    > y = base.tribonacci( 3 )\n    1\n    > y = base.tribonacci( 4 )\n    2\n    > y = base.tribonacci( 64 )\n    NaN\n    > y = base.tribonacci( NaN )\n    NaN\n\n    See Also\n    --------\n    base.fibonacci\n","base.trigamma":"\nbase.trigamma( x )\n    Evaluates the trigamma function.\n\n    If `x` is `0` or a negative `integer`, the `function` returns `NaN`.\n\n    If provided `NaN`, the `function` returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.trigamma( -2.5 )\n    ~9.539\n    > y = base.trigamma( 1.0 )\n    ~1.645\n    > y = base.trigamma( 10.0 )\n    ~0.105\n    > y = base.trigamma( NaN )\n    NaN\n    > y = base.trigamma( -1.0 )\n    NaN\n\n    See Also\n    --------\n    base.digamma, base.gamma\n","base.trim":"\nbase.trim( str )\n    Trims whitespace from the beginning and end of a `string`.\n\n    \"Whitespace\" is defined as the following characters:\n\n    - \\f\n    - \\n\n    - \\r\n    - \\t\n    - \\v\n    - \\u0020\n    - \\u00a0\n    - \\u1680\n    - \\u2000-\\u200a\n    - \\u2028\n    - \\u2029\n    - \\u202f\n    - \\u205f\n    - \\u3000\n    - \\ufeff\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Trimmed string.\n\n    Examples\n    --------\n    > var out = base.trim( ' \\t\\t\\n  Beep \\r\\n\\t  ' )\n    'Beep'\n\n    See Also\n    --------\n    base.leftTrim, base.rightTrim\n","base.trunc":"\nbase.trunc( x )\n    Rounds a double-precision floating-point number toward zero.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.trunc( 3.14 )\n    3.0\n    > y = base.trunc( -4.2 )\n    -4.0\n    > y = base.trunc( -4.6 )\n    -4.0\n    > y = base.trunc( 9.5 )\n    9.0\n    > y = base.trunc( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceil, base.floor, base.round\n","base.trunc2":"\nbase.trunc2( x )\n    Rounds a numeric value to the nearest power of two toward zero.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.trunc2( 3.14 )\n    2.0\n    > y = base.trunc2( -4.2 )\n    -4.0\n    > y = base.trunc2( -4.6 )\n    -4.0\n    > y = base.trunc2( 9.5 )\n    8.0\n    > y = base.trunc2( 13.0 )\n    8.0\n    > y = base.trunc2( -13.0 )\n    -8.0\n    > y = base.trunc2( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceil2, base.floor2, base.round2, base.trunc, base.trunc10\n","base.trunc10":"\nbase.trunc10( x )\n    Rounds a numeric value to the nearest power of ten toward zero.\n\n    The function may not return accurate results for subnormals due to a general\n    loss in precision.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.trunc10( 3.14 )\n    1.0\n    > y = base.trunc10( -4.2 )\n    -1.0\n    > y = base.trunc10( -4.6 )\n    -1.0\n    > y = base.trunc10( 9.5 )\n    1.0\n    > y = base.trunc10( 13.0 )\n    10.0\n    > y = base.trunc10( -13.0 )\n    -10.0\n    > y = base.trunc10( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceil10, base.floor10, base.round10, base.trunc, base.trunc2\n","base.truncateMiddle":"\nbase.truncateMiddle( str, len, seq )\n    Truncates the middle UTF-16 code units of a string to return a string\n    having a specified length.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    len: integer\n        Output string length.\n\n    seq: string\n        Custom replacement sequence.\n\n    Returns\n    -------\n    out: string\n        Truncated string.\n\n    Examples\n    --------\n    > var str = 'beep boop';\n    > var out = base.truncateMiddle( str, 5, '...' )\n    'b...p'\n    > out = base.truncateMiddle( str, 5, '|' )\n    'be|op'\n","base.truncb":"\nbase.truncb( x, n, b )\n    Rounds a numeric value to the nearest multiple of `b^n` toward zero.\n\n    Due to floating-point rounding error, rounding may not be exact.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Integer power.\n\n    b: integer\n        Base.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    // Round to 4 decimal places:\n    > var y = base.truncb( 3.14159, -4, 10 )\n    3.1415\n\n    // If `n = 0` or `b = 1`, standard round behavior:\n    > y = base.truncb( 3.14159, 0, 2 )\n    3.0\n\n    // Round to nearest multiple of two toward zero:\n    > y = base.truncb( 5.0, 1, 2 )\n    4.0\n\n    See Also\n    --------\n    base.ceilb, base.floorb, base.roundb, base.trunc, base.truncn\n","base.truncf":"\nbase.truncf( x )\n    Rounds a single-precision floating-point number toward zero.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.truncf( 3.14 )\n    3.0\n    > y = base.truncf( -4.2 )\n    -4.0\n    > y = base.truncf( -4.6 )\n    -4.0\n    > y = base.truncf( 9.5 )\n    9.0\n    > y = base.truncf( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceilf, base.floorf, base.trunc\n","base.truncn":"\nbase.truncn( x, n )\n    Rounds a numeric value to the nearest multiple of `10^n` toward zero.\n\n    When operating on floating-point numbers in bases other than `2`, rounding\n    to specified digits can be inexact.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Integer power of 10.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    // Round to 4 decimal places:\n    > var y = base.truncn( 3.14159, -4 )\n    3.1415\n\n    // If `n = 0`, standard round behavior:\n    > y = base.truncn( 3.14159, 0 )\n    3.0\n\n    // Round to nearest thousand:\n    > y = base.truncn( 12368.0, 3 )\n    12000.0\n\n\n    See Also\n    --------\n    base.ceiln, base.floorn, base.roundn, base.trunc, base.truncb\n","base.truncsd":"\nbase.truncsd( x, n, b )\n    Rounds a numeric value to the nearest number toward zero with `n`\n    significant figures.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Number of significant figures. Must be greater than 0.\n\n    b: integer\n        Base. Must be greater than 0.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.truncsd( 3.14159, 5, 10 )\n    3.1415\n    > y = base.truncsd( 3.14159, 1, 10 )\n    3.0\n    > y = base.truncsd( 12368.0, 2, 10 )\n    12000.0\n    > y = base.truncsd( 0.0313, 2, 2 )\n    0.03125\n\n    See Also\n    --------\n    base.ceilsd, base.floorsd, base.roundsd, base.trunc\n","base.uint32ToInt32":"\nbase.uint32ToInt32( x )\n    Converts an unsigned 32-bit integer to a signed 32-bit integer.\n\n    Parameters\n    ----------\n    x: integer\n        Unsigned 32-bit integer.\n\n    Returns\n    -------\n    out: integer\n        Signed 32-bit integer.\n\n    Examples\n    --------\n    > var y = base.uint32ToInt32( base.float64ToUint32( 4294967295 ) )\n    -1\n    > y = base.uint32ToInt32( base.float64ToUint32( 3 ) )\n    3\n\n","base.umul":"\nbase.umul( a, b )\n    Performs C-like multiplication of two unsigned 32-bit integers.\n\n    Parameters\n    ----------\n    a: integer\n        Unsigned 32-bit integer.\n\n    b: integer\n        Unsigned 32-bit integer.\n\n    Returns\n    -------\n    out: integer\n        Product.\n\n    Examples\n    --------\n    > var v = base.umul( 10>>>0, 4>>>0 )\n    40\n\n    See Also\n    --------\n    base.imul\n","base.umuldw":"\nbase.umuldw( a, b )\n    Multiplies two unsigned 32-bit integers and returns an array of two unsigned\n    32-bit integers which represents the unsigned 64-bit integer product.\n\n    When computing the product of 32-bit integer values in double-precision\n    floating-point format (the default JavaScript numeric data type), computing\n    the double word product is necessary in order to avoid exceeding the maximum\n    safe double-precision floating-point integer value.\n\n    Parameters\n    ----------\n    a: integer\n        Unsigned 32-bit integer.\n\n    b: integer\n        Unsigned 32-bit integer.\n\n    Returns\n    -------\n    out: Array<number>\n        Double word product (in big endian order; i.e., the first element\n        corresponds to the most significant bits and the second element to the\n        least significant bits).\n\n    Examples\n    --------\n    > var v = base.umuldw( 1, 10 )\n    [ 0, 10 ]\n\n\nbase.umuldw.assign( a, b, out, stride, offset )\n    Multiplies two unsigned 32-bit integers and assigns results representing\n    the unsigned 64-bit integer product to a provided output array.\n\n    When computing the product of 32-bit integer values in double-precision\n    floating-point format (the default JavaScript numeric data type), computing\n    the double word product is necessary in order to avoid exceeding the maximum\n    safe double-precision floating-point integer value.\n\n    Parameters\n    ----------\n    a: integer\n        Unsigned 32-bit integer.\n\n    b: integer\n        Unsigned 32-bit integer.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Double word product (in big endian order; i.e., the first element\n        corresponds to the most significant bits and the second element to the\n        least significant bits).\n\n    Examples\n    --------\n    > var out = [ 0, 0 ];\n    > var v = base.umuldw.assign( 1, 10, out, 1, 0 )\n    [ 0, 10 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.imuldw, base.umul\n","base.umuldw.assign":"\nbase.umuldw.assign( a, b, out, stride, offset )\n    Multiplies two unsigned 32-bit integers and assigns results representing\n    the unsigned 64-bit integer product to a provided output array.\n\n    When computing the product of 32-bit integer values in double-precision\n    floating-point format (the default JavaScript numeric data type), computing\n    the double word product is necessary in order to avoid exceeding the maximum\n    safe double-precision floating-point integer value.\n\n    Parameters\n    ----------\n    a: integer\n        Unsigned 32-bit integer.\n\n    b: integer\n        Unsigned 32-bit integer.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Double word product (in big endian order; i.e., the first element\n        corresponds to the most significant bits and the second element to the\n        least significant bits).\n\n    Examples\n    --------\n    > var out = [ 0, 0 ];\n    > var v = base.umuldw.assign( 1, 10, out, 1, 0 )\n    [ 0, 10 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.imuldw, base.umul","base.uncapitalize":"\nbase.uncapitalize( str )\n    Lowercases the first character of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Uncapitalized string.\n\n    Examples\n    --------\n    > var out = base.uncapitalize( 'Beep' )\n    'beep'\n    > out = base.uncapitalize( 'bOOp' )\n    'bOOp'\n\n    See Also\n    --------\n    base.capitalize\n","base.uppercase":"\nbase.uppercase( str )\n    Converts a string to uppercase.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Uppercase string.\n\n    Examples\n    --------\n    > var out = base.uppercase( 'bEEp' )\n    'BEEP'\n\n    See Also\n    --------\n    base.lowercase\n","base.vercos":"\nbase.vercos( x )\n    Computes the versed cosine.\n\n    The versed cosine is defined as `1 + cos(x)`.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Versed cosine.\n\n    Examples\n    --------\n    > var y = base.vercos( 3.14 )\n    ~0.0\n    > y = base.vercos( -4.2 )\n    ~0.5097\n    > y = base.vercos( -4.6 )\n    ~0.8878\n    > y = base.vercos( 9.5 )\n    ~0.0028\n    > y = base.vercos( -0.0 )\n    2.0\n\n    See Also\n    --------\n    base.cos, base.versin\n","base.versin":"\nbase.versin( x )\n    Computes the versed sine.\n\n    The versed sine is defined as `1 - cos(x)`.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Versed sine.\n\n    Examples\n    --------\n    > var y = base.versin( 3.14 )\n    ~2.0\n    > y = base.versin( -4.2 )\n    ~1.490\n    > y = base.versin( -4.6 )\n    ~1.112\n    > y = base.versin( 9.5 )\n    ~1.997\n    > y = base.versin( -0.0 )\n    0.0\n\n    See Also\n    --------\n    base.cos, base.sin, base.vercos\n","base.wrap":"\nbase.wrap( v, min, max )\n    Wraps a value on the half-open interval `[min,max)`.\n\n    The function does not distinguish between positive and negative zero. Where\n    appropriate, the function returns positive zero.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    v: number\n        Value to wrap.\n\n    min: number\n        Minimum value.\n\n    max: number\n        Maximum value.\n\n    Returns\n    -------\n    y: number\n        Wrapped value.\n\n    Examples\n    --------\n    > var y = base.wrap( 3.14, 0.0, 5.0 )\n    3.14\n    > y = base.wrap( -3.14, 0.0, 5.0 )\n    ~1.86\n    > y = base.wrap( 3.14, 0.0, 3.0 )\n    ~0.14\n    > y = base.wrap( -0.0, 0.0, 5.0 )\n    0.0\n    > y = base.wrap( 0.0, -3.14, -0.0 )\n    -3.14\n    > y = base.wrap( NaN, 0.0, 5.0 )\n    NaN\n\n    See Also\n    --------\n    base.clamp\n","base.xlog1py":"\nbase.xlog1py( x, y )\n    Computes `x * ln(y+1)` so that the result is `0` if `x = 0`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    y: number\n        Input value.\n\n    Returns\n    -------\n    out: number\n        Function value.\n\n    Examples\n    --------\n    > var out = base.xlog1py( 3.0, 2.0 )\n    ~3.296\n    > out = base.xlog1py( 1.5, 5.9 )\n    ~2.897\n    > out = base.xlog1py( 0.9, 1.0 )\n    ~0.624\n    > out = base.xlog1py( 1.0, 0.0 )\n    0.0\n    > out = base.xlog1py( 0.0, -2.0 )\n    0.0\n    > out = base.xlog1py( 1.5, NaN )\n    NaN\n    > out = base.xlog1py( 0.0, NaN )\n    NaN\n    > out = base.xlog1py( NaN, 2.3 )\n    NaN\n\n    See Also\n    --------\n    base.log1p, base.xlogy\n","base.xlogy":"\nbase.xlogy( x, y )\n    Computes `x * ln(y)` so that the result is `0` if `x = 0`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    y: number\n        Input value.\n\n    Returns\n    -------\n    out: number\n        Function value.\n\n    Examples\n    --------\n    > var out = base.xlogy( 3.0, 2.0 )\n    ~2.079\n    > out = base.xlogy( 1.5, 5.9 )\n    ~2.662\n    > out = base.xlogy( 0.9, 1.0 )\n    0.0\n    > out = base.xlogy( 0.0, -2.0 )\n    0.0\n    > out = base.xlogy( 1.5, NaN )\n    NaN\n    > out = base.xlogy( 0.0, NaN )\n    NaN\n    > out = base.xlogy( NaN, 2.3 )\n    NaN\n\n    See Also\n    --------\n    base.ln, base.xlog1py\n","base.zeta":"\nbase.zeta( s )\n    Evaluates the Riemann zeta function as a function of a real variable `s`.\n\n    Parameters\n    ----------\n    s: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.zeta( 1.1 )\n    ~10.584\n    > y = base.zeta( -4.0 )\n    0.0\n    > y = base.zeta( 70.0 )\n    1.0\n    > y = base.zeta( 0.5 )\n    ~-1.46\n    > y = base.zeta( NaN )\n    NaN\n\n    // Evaluate at a pole:\n    > y = base.zeta( 1.0 )\n    NaN\n\n","BERNDT_CPS_WAGES_1985":"\nBERNDT_CPS_WAGES_1985()\n    Returns a random sample of 534 workers from the Current Population Survey\n    (CPS) from 1985, including their wages and and other characteristics.\n\n    Each array element has the following eleven fields:\n\n    - education: number of years of education.\n    - south: indicator variable for southern region (1 if a person lives in the\n    South; 0 if a person does not live in the South).\n    - gender: gender of the person.\n    - experience: number of years of work experience.\n    - union: indicator variable for union membership (1 if union member; 0 if\n    not a union member).\n    - wage: wage (in dollars per hour).\n    - age: age (in years).\n    - race: ethnicity/race (white, hispanic, and other).\n    - occupation: occupational category (management, sales, clerical, service,\n    professional, and other).\n    - sector: sector (other, manufacturing, or construction).\n    - married: marital status (0 if unmarried; 1 if married).\n\n    Based on residual plots, wages were log-transformed to stabilize the\n    variance.\n\n    Returns\n    -------\n    out: Array<Object>\n        CPS data.\n\n    Examples\n    --------\n    > var data = BERNDT_CPS_WAGES_1985()\n    [ {...}, {...}, ... ]\n\n    References\n    ----------\n    - Berndt, Ernst R. 1991. _The Practice of Econometrics_. Addison Wesley\n    Longman Publishing Co.\n\n","bifurcate":"\nbifurcate( collection, [options,] filter )\n    Splits values into two groups.\n\n    If an element in `filter` is truthy, then the corresponding element in the\n    input collection belongs to the first group; otherwise, the collection\n    element belongs to the second group.\n\n    If provided an empty collection, the function returns an empty array.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection to group. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Options.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `indices`, indices are returned; if\n        `*`, both indices and values are returned. Default: 'values'.\n\n    filter: Array|TypedArray|Object\n        A collection indicating which group an element in the input collection\n        belongs to. If an element in `filter` is truthy, the corresponding\n        element in `collection` belongs to the first group; otherwise, the\n        collection element belongs to the second group. If provided an object,\n        the object must be array-like (excluding strings and functions).\n\n    Returns\n    -------\n    out: Array<Array>|Array\n        Group results.\n\n    Examples\n    --------\n    > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n    > var f = [ true, true, false, true ];\n    > var out = bifurcate( collection, f )\n    [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n    > f = [ 1, 1, 0, 1 ];\n    > out = bifurcate( collection, f )\n    [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n    // Output group results as indices:\n    > f = [ true, true, false, true ];\n    > var opts = { 'returns': 'indices' };\n    > out = bifurcate( collection, opts, f )\n    [ [ 0, 1, 3 ], [ 2 ] ]\n\n    // Output group results as index-element pairs:\n    > opts = { 'returns': '*' };\n    > out = bifurcate( collection, opts, f )\n    [ [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], [ [2, 'foo'] ] ]\n\n    See Also\n    --------\n    bifurcateBy, bifurcateOwn, group\n","bifurcateBy":"\nbifurcateBy( collection, [options,] predicate )\n    Splits values into two groups according to a predicate function.\n\n    When invoked, the predicate function is provided two arguments:\n\n    - value: collection value.\n    - index: collection index.\n\n    If a predicate function returns a truthy value, a collection value is\n    placed in the first group; otherwise, a collection value is placed in the\n    second group.\n\n    If provided an empty collection, the function returns an empty array.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection to group. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Options.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `indices`, indices are returned; if\n        `*`, both indices and values are returned. Default: 'values'.\n\n    predicate: Function\n        Predicate function indicating which group an element in the input\n        collection belongs to.\n\n    Returns\n    -------\n    out: Array<Array>|Array\n        Group results.\n\n    Examples\n    --------\n    > function predicate( v ) { return v[ 0 ] === 'b'; };\n    > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n    > var out = bifurcateBy( collection, predicate )\n    [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n    // Output group results as indices:\n    > var opts = { 'returns': 'indices' };\n    > out = bifurcateBy( collection, opts, predicate )\n    [ [ 0, 1, 3 ], [ 2 ] ]\n\n    // Output group results as index-value pairs:\n    > opts = { 'returns': '*' };\n    > out = bifurcateBy( collection, opts, predicate )\n    [ [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], [ [2, 'foo' ] ] ]\n\n    See Also\n    --------\n    bifurcate, groupBy\n","bifurcateByAsync":"\nbifurcateByAsync( collection, [options,] predicate, done )\n    Splits values into two groups according to a predicate function.\n\n    When invoked, the predicate function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If the\n    predicate function accepts two arguments, the predicate function is\n    provided:\n\n    - value\n    - next\n\n    If the predicate function accepts three arguments, the predicate function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other predicate function signature, the predicate function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - group: value group.\n\n    If an predicate function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    If a predicate function calls the `next` callback with a truthy group value,\n    a collection value is placed in the first group; otherwise, a collection\n    value is placed in the second group.\n\n    If provided an empty collection, the function calls the `done` callback with\n    an empty array as the second argument.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `indices`, indices are returned; if\n        `*`, both indices and values are returned. Default: 'values'.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        Predicate function indicating which group an element in the input\n        collection belongs to.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function predicate( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > bifurcateByAsync( arr, predicate, done )\n    1000\n    2500\n    3000\n    [ [ 1000, 3000 ], [ 2500 ] ]\n\n    // Output group results as indices:\n    > var opts = { 'returns': 'indices' };\n    > bifurcateByAsync( arr, opts, predicate, done )\n    1000\n    2500\n    3000\n    [ [ 2, 0 ], [ 1 ] ]\n\n    // Output group results as index-value pairs:\n    > opts = { 'returns': '*' };\n    > bifurcateByAsync( arr, opts, predicate, done )\n    1000\n    2500\n    3000\n    [ [ [ 2, 1000 ], [ 0, 3000 ] ], [ [ 1, 2500 ] ] ]\n\n    // Limit number of concurrent invocations:\n    > function predicate( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 3000, 2500, 1000 ];\n    > bifurcateByAsync( arr, opts, predicate, done )\n    2500\n    3000\n    1000\n    [ [ 3000, 1000 ], [ 2500 ] ]\n\n    // Process sequentially:\n    > function predicate( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 3000, 2500, 1000 ];\n    > bifurcateByAsync( arr, opts, predicate, done )\n    3000\n    2500\n    1000\n    [ [ 3000, 1000 ], [ 2500 ] ]\n\n\nbifurcateByAsync.factory( [options,] predicate )\n    Returns a function which splits values into two groups according to an\n    predicate function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `indices`, indices are returned; if\n        `*`, both indices and values are returned. Default: 'values'.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        Predicate function indicating which group an element in the input\n        collection belongs to.\n\n    Returns\n    -------\n    out: Function\n        A function which splits values into two groups.\n\n    Examples\n    --------\n    > function predicate( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = bifurcateByAsync.factory( opts, predicate );\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    [ [ 3000, 1000 ], [ 2500 ] ]\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    [ [ 2000, 1000 ], [ 1500 ] ]\n\n    See Also\n    --------\n    bifurcateBy, groupByAsync\n","bifurcateByAsync.factory":"\nbifurcateByAsync.factory( [options,] predicate )\n    Returns a function which splits values into two groups according to an\n    predicate function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `indices`, indices are returned; if\n        `*`, both indices and values are returned. Default: 'values'.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        Predicate function indicating which group an element in the input\n        collection belongs to.\n\n    Returns\n    -------\n    out: Function\n        A function which splits values into two groups.\n\n    Examples\n    --------\n    > function predicate( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = bifurcateByAsync.factory( opts, predicate );\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    [ [ 3000, 1000 ], [ 2500 ] ]\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    [ [ 2000, 1000 ], [ 1500 ] ]\n\n    See Also\n    --------\n    bifurcateBy, groupByAsync","bifurcateIn":"\nbifurcateIn( obj, [options,] predicate )\n    Splits values into two groups according to a predicate function.\n\n    When invoked, the predicate function is provided two arguments:\n\n    - value: object value.\n    - key: object key.\n\n    If a predicate function returns a truthy value, a value is placed in the\n    first group; otherwise, a value is placed in the second group.\n\n    If provided an empty object with no prototype, the function returns an empty\n    array.\n\n    The function iterates over an object's own and inherited properties.\n\n    Key iteration order is *not* guaranteed, and, thus, result order is *not*\n    guaranteed.\n\n    Parameters\n    ----------\n    obj: Object|Array|TypedArray\n        Input object to group.\n\n    options: Object (optional)\n        Options.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `keys`, keys are returned; if `*`,\n        both keys and values are returned. Default: 'values'.\n\n    predicate: Function\n        Predicate function indicating which group a value in the input object\n        belongs to.\n\n    Returns\n    -------\n    out: Array<Array>|Array\n        Group results.\n\n    Examples\n    --------\n    > function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\n    > Foo.prototype = Object.create( null );\n    > Foo.prototype.c = 'foo';\n    > Foo.prototype.d = 'bar';\n    > var obj = new Foo();\n    > function predicate( v ) { return v[ 0 ] === 'b'; };\n    > var out = bifurcateIn( obj, predicate )\n    [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n    // Output group results as keys:\n    > var opts = { 'returns': 'keys' };\n    > out = bifurcateIn( obj, opts, predicate )\n    [ [ 'a', 'b', 'd' ], [ 'c' ] ]\n\n    // Output group results as key-value pairs:\n    > opts = { 'returns': '*' };\n    > out = bifurcateIn( obj, opts, predicate )\n    [ [ ['a', 'beep'], ['b', 'boop'], ['d', 'bar'] ], [ ['c', 'foo' ] ] ]\n\n    See Also\n    --------\n    bifurcate, bifurcateBy, bifurcateOwn, groupIn\n","bifurcateOwn":"\nbifurcateOwn( obj, [options,] predicate )\n    Splits values into two groups according to a predicate function.\n\n    When invoked, the predicate function is provided two arguments:\n\n    - value: object value.\n    - key: object key.\n\n    If a predicate function returns a truthy value, a value is placed in the\n    first group; otherwise, a value is placed in the second group.\n\n    If provided an empty object, the function returns an empty array.\n\n    The function iterates over an object's own properties.\n\n    Key iteration order is *not* guaranteed, and, thus, result order is *not*\n    guaranteed.\n\n    Parameters\n    ----------\n    obj: Object|Array|TypedArray\n        Input object to group.\n\n    options: Object (optional)\n        Options.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `keys`, keys are returned; if `*`,\n        both keys and values are returned. Default: 'values'.\n\n    predicate: Function\n        Predicate function indicating which group a value in the input object\n        belongs to.\n\n    Returns\n    -------\n    out: Array<Array>|Array\n        Group results.\n\n    Examples\n    --------\n    > function predicate( v ) { return v[ 0 ] === 'b'; };\n    > var obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\n    > var out = bifurcateOwn( obj, predicate )\n    [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n    // Output group results as keys:\n    > var opts = { 'returns': 'keys' };\n    > out = bifurcateOwn( obj, opts, predicate )\n    [ [ 'a', 'b', 'd' ], [ 'c' ] ]\n\n    // Output group results as key-value pairs:\n    > opts = { 'returns': '*' };\n    > out = bifurcateOwn( obj, opts, predicate )\n    [ [ ['a', 'beep'], ['b', 'boop'], ['d', 'bar'] ], [ ['c', 'foo' ] ] ]\n\n    See Also\n    --------\n    bifurcate, bifurcateBy, bifurcateIn, groupOwn\n","BigInt":"\nBigInt( value )\n    Returns a BigInt.\n\n    Unlike conventional constructors, this function does **not** support the\n    `new` keyword.\n\n    This function is only supported in environments which support BigInts.\n\n    Parameters\n    ----------\n    value: integer|string\n        Value of the BigInt.\n\n    Returns\n    -------\n    out: BigInt\n        BigInt.\n\n    Examples\n    --------\n    > var v = ( BigInt ) ? BigInt( '1' ) : null\n\n\nTODO: document properties/methods\n\n","binomialTest":"\nbinomialTest( x[, n][, options] )\n    Computes an exact test for the success probability in a Bernoulli\n    experiment.\n\n    The returned object comes with a `.print()` method which when invoked will\n    print a formatted output of the results of the hypothesis test.\n\n    Parameters\n    ----------\n    x: (number|Array<number>)\n        Number of successes or two-element array with successes and failures.\n\n    n: Array<number> (optional)\n        Total number of observations.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.alternative: string (optional)\n        Indicates whether the alternative hypothesis is that the mean of `x` is\n        larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n        `mu` (`two-sided`). Default: `'two-sided'`.\n\n    options.p: number (optional)\n        Hypothesized probability under the null hypothesis. Default: `0.5`.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Used significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Sample proportion.\n\n    out.ci: Array<number>\n        1-alpha confidence interval for the success probability.\n\n    out.nullValue: number\n        Assumed success probability under H0.\n\n    out.alternative: string\n        Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n    out.method: string\n        Name of test.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    > var out = binomialTest( 682, 925 )\n    {\n        'pValue': ~3.544e-49,\n        'statistic': ~0.737\n        // ...\n    }\n\n    > out = binomialTest( [ 682, 925 - 682 ] )\n    {\n        'pValue': ~3.544e-49,\n        'statistic': ~0.737\n        // ...\n    }\n\n    > out = binomialTest( 21, 40, {\n    ...     'p': 0.4,\n    ...     'alternative': 'greater'\n    ... })\n    {\n        'pValue': ~0.074,\n        'statistic': 0.525\n        // ...\n    }\n\n","Boolean":"\nBoolean( value )\n    Returns a boolean.\n\n    When invoked without `new`,\n\n    - if provided `false`, `null`, `undefined`, `-0`, `0`, `NaN`, or an empty\n      string, the function returns `false`.\n    - if provided any other value, including an empty object, an empty array,\n      the string `'false'`, or a `Boolean` object (including a `Boolean` object\n      whose value is `false`), the function returns `true`.\n\n    When invoked with `new`, the constructor returns a `Boolean` object, which\n    is an object wrapper for a primitive boolean value. The value of the\n    returned `Boolean` object follows the same conversion semantics as when the\n    constructor is invoked without `new`.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    out: boolean|Boolean\n        Boolean primitive or object.\n\n    Examples\n    --------\n    > var b = new Boolean( null )\n    <Boolean>\n    > b = Boolean( null )\n    false\n    > b = Boolean( [] )\n    true\n\nBoolean.prototype.toString()\n    Returns a string representing the `Boolean` object.\n\n    Returns\n    -------\n    out: string\n        String representation.\n\n    Examples\n    --------\n    > var b = new Boolean( true )\n    <Boolean>\n    > b.toString()\n    'true'\n\nBoolean.prototype.valueOf()\n    Returns the primitive value of a `Boolean` object.\n\n    Returns\n    -------\n    out: boolean\n        Boolean primitive.\n\n    Examples\n    --------\n    > var b = new Boolean( true )\n    <Boolean>\n    > b.valueOf()\n    true\n\n","Boolean.prototype.toString":"\nBoolean.prototype.toString()\n    Returns a string representing the `Boolean` object.\n\n    Returns\n    -------\n    out: string\n        String representation.\n\n    Examples\n    --------\n    > var b = new Boolean( true )\n    <Boolean>\n    > b.toString()\n    'true'","Boolean.prototype.valueOf":"\nBoolean.prototype.valueOf()\n    Returns the primitive value of a `Boolean` object.\n\n    Returns\n    -------\n    out: boolean\n        Boolean primitive.\n\n    Examples\n    --------\n    > var b = new Boolean( true )\n    <Boolean>\n    > b.valueOf()\n    true","BooleanArray":"\nBooleanArray()\n    A Boolean array.\n\n    Returns\n    -------\n    out: BooleanArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new BooleanArray()\n    <BooleanArray>\n\n\nBooleanArray( length )\n    Creates a boolean array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: BooleanArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 10 )\n    <BooleanArray>\n    > var len = arr.length\n    10\n\n\nBooleanArray( booleanarray )\n    Creates a boolean array from another boolean array.\n\n    Parameters\n    ----------\n    booleanarray: BooleanArray\n        Boolean array from which to generate another boolean array.\n\n    Returns\n    -------\n    out: BooleanArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new BooleanArray( [ true, false, false, true ] )\n    <BooleanArray>\n    > var arr2 = new BooleanArray( arr1 )\n    <BooleanArray>\n    > var len = arr2.length\n    4\n\n\nBooleanArray( typedarray )\n    Creates a boolean array from a typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate boolean array.\n\n    Returns\n    -------\n    out: BooleanArray\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new Uint8Array( [ 1, 0, 0, 1 ] )\n    <Uint8Array>\n    > var arr = new BooleanArray( buf )\n    <BooleanArray>\n    > var len = arr.length\n    4\n\n\nBooleanArray( obj )\n    Creates a boolean array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a boolean array.\n\n    Returns\n    -------\n    out: BooleanArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new BooleanArray( [ true, false, false, true ] )\n    <BooleanArray>\n    > var len = arr1.length\n    4\n    > var arr2 = new BooleanArray( [ {}, null, '', 4 ] );\n    > len = arr2.length\n    4\n\n\nBooleanArray( buffer[, byteOffset[, length]] )\n    Returns a boolean array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: BooleanArray\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 240 );\n    > var arr1 = new BooleanArray( buf )\n    <BooleanArray>\n    > var len = arr1.length\n    240\n    > var arr2 = new BooleanArray( buf, 8 )\n    <BooleanArray>\n    > len = arr2.length\n    232\n    > var arr3 = new BooleanArray( buf, 8, 20 )\n    <BooleanArray>\n    > len = arr3.length\n    20\n\n\nBooleanArray.from( src[, clbk[, thisArg]] )\n    Creates a new boolean array from an array-like object or an iterable.\n\n    A callback function is provided two arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    clbk: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: BooleanArray\n        A typed array.\n\n    Examples\n    --------\n    > function map( v ) { return !v };\n    > var src = [ true, false ];\n    > var arr = BooleanArray.from( src, map )\n    <BooleanArray>\n    > var len = arr.length\n    2\n    > var v = arr.get( 0 )\n    false\n    > v = arr.get( 1 )\n    true\n\n\nBooleanArray.of( element0[, element1[, ...elementN]] )\n    Creates a new boolean array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: bool\n        Array element.\n\n    element1: bool (optional)\n        Array element.\n\n    elementN: ...bool (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: BooleanArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = BooleanArray.of( true, false, false, true )\n    <BooleanArray>\n    > var len = arr.length\n    4\n\n\nBooleanArray.BYTES_PER_ELEMENT\n    The size of each array element in bytes.\n\n    Examples\n    --------\n    > var nbytes = BooleanArray.BYTES_PER_ELEMENT\n    1\n\n\nBooleanArray.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > var str = BooleanArray.name\n    'BooleanArray'\n\n\nBooleanArray.prototype.buffer\n    Pointer to the underlying data buffer.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 2 )\n    <BooleanArray>\n    > var buf = arr.buffer\n    <ArrayBuffer>\n\n\nBooleanArray.prototype.byteLength\n    Size of the array in bytes.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 10 )\n    <BooleanArray>\n    > var nbytes = arr.byteLength\n    10\n\n\nBooleanArray.prototype.byteOffset\n    Offset (in bytes) of the array from the start of its underlying\n    ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 10 )\n    <BooleanArray>\n    > var offset = arr.byteOffset\n    0\n    > var buf = new ArrayBuffer( 240 );\n    > arr = new BooleanArray( buf, 64 )\n    <BooleanArray>\n    > offset = arr.byteOffset\n    64\n\n\nBooleanArray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 10 )\n    <BooleanArray>\n    > arr.BYTES_PER_ELEMENT\n    1\n\n\nBooleanArray.prototype.length\n    The number of array elements.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 10 )\n    <BooleanArray>\n    > var len = arr.length\n    10\n\n\nBooleanArray.prototype.at( i )\n    Returns an array element located at integer position (index) `i`, with\n    support for noth nonnegative and negative integer positions.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n\n    Returns\n    -------\n    out: boolean|void\n        An array element.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, false, true ] )\n    <BooleanArray>\n    > var v = arr.at( 1 )\n    false\n    > v = arr.at( -1 )\n    true\n\n\nBooleanArray.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n    \n    start: integer\n        Source start index position.\n    \n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: BooleanArray\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, false, true ] )\n    <BooleanArray>\n    > arr.copyWithin( 0, 2 )\n    <BooleanArray>\n    > var v = arr.get( 0 )\n    false\n    > v = arr.get( 1 )\n    true\n\n\nBooleanArray.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var it = arr.entries();\n    > var v = it.next().value\n    [ 0, true ]\n    > v = it.next().value\n    [ 1, false ]\n    > v = it.next().value\n    [ 2, true ]\n    > var bool = it.next().done\n    true\n\n\nBooleanArray.prototype.every( predicate[, thisArg] )\n    Returns a boolean indicating whether all elements in the array pass a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all elements pass the test.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ true, true, true ] )\n    <BooleanArray>\n    > var bool = arr.every( predicate )\n    true\n\n\nBooleanArray.prototype.fill( value[, start[, end]] )\n    Returns a modified typed array filled with a fill value.\n\n    Parameters\n    ----------\n    value: boolean\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: BooleanArray\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new BooleanArray( 3 )\n    <BooleanArray>\n    > arr.fill( true );\n    > var v = arr.get( 0 )\n    true\n    > v = arr.get( 1 )\n    true\n    > v = arr.get( 2 )\n    true\n\n\nBooleanArray.prototype.filter( predicate[, thisArg] )\n    Returns a new array containing the elements of an array which pass a test\n    implemented by a predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: BooleanArray\n        A new typed array.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( v === true ); };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.filter( predicate )\n    <BooleanArray>\n    > var len = out.length\n    2\n    > var v = out.get( 0 )\n    true\n    > v = out.get( 1 )\n    true\n\n\nBooleanArray.prototype.find( predicate[, thisArg] )\n    Returns the first element in an array for which a predicate function returns\n    a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: boolean|void\n        Array element or `undefined`.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var v = arr.find( predicate )\n    true\n\n\nBooleanArray.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var idx = arr.findIndex( predicate )\n    0\n\n\nBooleanArray.prototype.findLast( predicate[, thisArg] )\n    Returns the last element in an array for which a predicate function returns\n    a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: boolean|void\n        Array element or `undefined`.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var v = arr.findLast( predicate )\n    true\n\n\nBooleanArray.prototype.findLastIndex( predicate[, thisArg] )\n    Returns the index of the last element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var idx = arr.findLastIndex( predicate )\n    2\n\n\nBooleanArray.prototype.forEach( clbk[, thisArg] )\n    Invokes a function once for each array element.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Examples\n    --------\n    > var str = '%';\n    > function clbk( v ) { str += v.toString() + '%'; };\n    > var arr = new BooleanArray( [ true, false, false, true ] )\n    <BooleanArray>\n    > arr.forEach( clbk );\n    > str\n    '%true%false%false%true%'\n\n\nBooleanArray.prototype.get( i )\n    Returns an array element located at integer position (index) `i`.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n\n    Returns\n    -------\n    out: boolean|void\n        Array element or `undefined`.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 10 )\n    <BooleanArray>\n    > arr.set( true, 0 );\n    > var v = arr.get( 0 )\n    true\n\n\nBooleanArray.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a provided value.\n\n    Parameters\n    ----------\n    searchElement: boolean\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true, true, true ] )\n    <BooleanArray>\n    > var bool = arr.includes( true )\n    true\n    > bool = arr.includes( false, 3 )\n    false\n\n\nBooleanArray.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the first index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: boolean\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true, true, true ] )\n    <BooleanArray>\n    > var idx = arr.indexOf( true )\n    0\n    > idx = arr.indexOf( false, 3 )\n    -1\n\n\nBooleanArray.prototype.join( [separator] )\n    Returns a new string by concatenating all array elements separated by a\n    separator string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        Separator string. Default: ','.\n\n    Returns\n    -------\n    out: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var str = arr.join()\n    'true,false,true'\n    > str = arr.join( '|' )\n    'true|false|true'\n\n\nBooleanArray.prototype.keys()\n    Returns an iterator for iterating over each index key in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array index keys.\n    \n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false ] )\n    <BooleanArray>\n    > var it = arr.keys();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().done\n    true\n\n\nBooleanArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the last index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: boolean\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: out.length-1.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, true, true, false, true ] )\n    <BooleanArray>\n    > var idx = arr.lastIndexOf( false )\n    3\n    > idx = arr.lastIndexOf( false, 2 )\n    -1\n\n\nBooleanArray.prototype.map( clbk[, thisArg] )\n    Returns a new array with each element being the result of a provided\n    callback function.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: BooleanArray\n        A new typed array.\n\n    Examples\n    --------\n    > function invert( v ) { return !v; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.map( invert )\n    <BooleanArray>\n    > var v = out.get( 0 )\n    false\n    > v = out.get( 1 )\n    true\n    > v = out.get( 2 )\n    false\n\n\nBooleanArray.prototype.reduce( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in order, passing\n    in the return value from the calculation on the preceding element and\n    returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.\n\n    initialValue: any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: any\n        Accumulated result.\n\n    Examples\n    --------\n    > function reducer( acc, v ) { return ( acc && v ); };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.reduce( reducer )\n    false\n\n\nBooleanArray.prototype.reduceRight( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in reverse order,\n    passing in the return value from the calculation on the preceding element\n    and returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.\n\n    initialValue: any (optional)\n        Initial accumulation value.\n    \n    Returns\n    -------\n    out: any\n        Accumulated result.\n    \n    Examples\n    --------\n    > function reducer( acc, v ) { return ( acc && v ); };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.reduceRight( reducer )\n    false\n\n\nBooleanArray.prototype.reverse()\n    Reverses the array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: BooleanArray\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, false ] )\n    <BooleanArray>\n    > arr.reverse();\n    > var v = arr.get( 0 )\n    false\n    > v = arr.get( 1 )\n    false\n    > v = arr.get( 2 )\n    true\n\n\nBooleanArray.prototype.set( v[, i] )\n    Sets one or more array elements.\n\n    If provided a single argument, the method sets array elements starting at\n    position (index) `i = 0`. To set elements starting elsewhere in the array,\n    provide an index argument `i`.\n\n    To set one or more array elements, provide an array-like object containing\n    truthy and falsy values.\n\n    Parameters\n    ----------\n    v: bool|BooleanArray|ArrayLikeObject\n        Boolean value or Boolean value array.\n\n    i: integer (optional)\n        Array index at which to start setting elements. Default: 0.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 2 )\n    <BooleanArray>\n    > arr.set( false );\n    > var v = arr.get( 0 )\n    false\n    > arr.set( true, 1 );\n    > v = arr.get( 1 )\n    true\n\n\nBooleanArray.prototype.slice( [start[, end]] )\n    Copies a portion of a typed array to a new typed array.\n\n    Parameters\n    ----------\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: BooleanArray\n        New typed array.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true, false, true ] )\n    <BooleanArray>\n    > var out = arr.slice( 1 )\n    <BooleanArray>\n    > var len = out.length\n    4\n    > var v = out.get( 0 )\n    false\n    > v = out.get( 1 )\n    true\n\n\nBooleanArray.prototype.some( predicate[, thisArg] )\n    Returns a boolean indicating whether at least one element passes a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one element passes the test.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ false, true, false ] )\n    <BooleanArray>\n    > var bool = arr.some( predicate )\n    true\n\n\nBooleanArray.prototype.sort( [compareFunction] )\n    Sorts an array in-place.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first boolean value for comparison.\n    - b: second boolean value for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Comparison function.\n\n    Returns\n    -------\n    out: BooleanArray\n        Modified array.\n\n    Examples\n    --------\n    > function compare( a, b ) { return a === true ? -1 : 1; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > arr.sort( compare );\n    > var v = arr.get( 0 )\n    true\n    > v = arr.get( 1 )\n    true\n    > v = arr.get( 2 )\n    false\n\n\nBooleanArray.prototype.subarray( [begin[, end]] )\n    Creates a new typed array view over the same underlying `ArrayBuffer` and\n    with the same underlying data type as the host array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: BooleanArray\n        New typed array view.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true, false, true ] )\n    <BooleanArray>\n    > var out = arr.subarray( 1, 3 )\n    <BooleanArray>\n    > var len = out.length\n    2\n    > var v = out.get( 0 )\n    false\n    > v = out.get( 1 )\n    true\n\n\nBooleanArray.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array (optional)\n        Locale identifier(s).\n    \n    options: Object (optional)\n        An object containing serialization options.\n    \n    Returns\n    -------\n    str: string\n        Local-specific string.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var str = arr.toLocaleString()\n    'true,false,true'\n\n\nBooleanArray.prototype.toReversed()\n    Returns a new typed array containing the elements in reversed order.\n\n    Returns\n    -------\n    out: BooleanArray\n        New typed array.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, false ] )\n    <BooleanArray>\n    > var out = arr.toReversed()\n    <BooleanArray>\n    > var v = out.get( 0 )\n    false\n    > v = out.get( 1 )\n    false\n    > v = out.get( 2 )\n    true\n\n\nBooleanArray.prototype.toSorted( [compareFunction] )\n    Returns a new typed array containing the elements in sorted order.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first boolean value for comparison.\n    - b: second boolean value for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Comparison function.\n\n    Returns\n    -------\n    out: BooleanArray\n        New typed array.\n\n    Examples\n    --------\n    > function compare( a, b ) { return a === true ? -1 : 1; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.toSorted( compare );\n    > var v = out.get( 0 )\n    true\n    > v = out.get( 1 )\n    true\n    > v = out.get( 2 )\n    false\n\n\nBooleanArray.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    out: string\n        String serialization of the array.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var str = arr.toString()\n    'true,false,true'\n\n\nBooleanArray.prototype.values()\n    Returns an iterator for iterating over each value in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array values.\n    \n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false ] )\n    <BooleanArray>\n    > var it = arr.values();\n    > var v = it.next().value\n    true\n    > v = it.next().value\n    false\n    > var bool = it.next().done\n    true\n\n\nBooleanArray.prototype.with( index, value )\n    Returns a new typed array with the element at a provided index replaced\n    with a provided value.\n\n    Parameters\n    ----------\n    index: integer\n        Element index.\n    \n    value: boolean\n        Element value.  \n\n    Returns\n    -------\n    out: BooleanArray\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.with( 0, false )\n    <BooleanArray>\n    > var v = out.get( 0 )\n    false\n\n\n    See Also\n    --------\n    ArrayBuffer","BooleanArray.from":"\nBooleanArray.from( src[, clbk[, thisArg]] )\n    Creates a new boolean array from an array-like object or an iterable.\n\n    A callback function is provided two arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    clbk: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: BooleanArray\n        A typed array.\n\n    Examples\n    --------\n    > function map( v ) { return !v };\n    > var src = [ true, false ];\n    > var arr = BooleanArray.from( src, map )\n    <BooleanArray>\n    > var len = arr.length\n    2\n    > var v = arr.get( 0 )\n    false\n    > v = arr.get( 1 )\n    true","BooleanArray.of":"\nBooleanArray.of( element0[, element1[, ...elementN]] )\n    Creates a new boolean array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: bool\n        Array element.\n\n    element1: bool (optional)\n        Array element.\n\n    elementN: ...bool (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: BooleanArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = BooleanArray.of( true, false, false, true )\n    <BooleanArray>\n    > var len = arr.length\n    4","BooleanArray.BYTES_PER_ELEMENT":"\nBooleanArray.BYTES_PER_ELEMENT\n    The size of each array element in bytes.\n\n    Examples\n    --------\n    > var nbytes = BooleanArray.BYTES_PER_ELEMENT\n    1","BooleanArray.name":"\nBooleanArray.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > var str = BooleanArray.name\n    'BooleanArray'","BooleanArray.prototype.buffer":"\nBooleanArray.prototype.buffer\n    Pointer to the underlying data buffer.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 2 )\n    <BooleanArray>\n    > var buf = arr.buffer\n    <ArrayBuffer>","BooleanArray.prototype.byteLength":"\nBooleanArray.prototype.byteLength\n    Size of the array in bytes.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 10 )\n    <BooleanArray>\n    > var nbytes = arr.byteLength\n    10","BooleanArray.prototype.byteOffset":"\nBooleanArray.prototype.byteOffset\n    Offset (in bytes) of the array from the start of its underlying\n    ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 10 )\n    <BooleanArray>\n    > var offset = arr.byteOffset\n    0\n    > var buf = new ArrayBuffer( 240 );\n    > arr = new BooleanArray( buf, 64 )\n    <BooleanArray>\n    > offset = arr.byteOffset\n    64","BooleanArray.prototype.BYTES_PER_ELEMENT":"\nBooleanArray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 10 )\n    <BooleanArray>\n    > arr.BYTES_PER_ELEMENT\n    1","BooleanArray.prototype.length":"\nBooleanArray.prototype.length\n    The number of array elements.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 10 )\n    <BooleanArray>\n    > var len = arr.length\n    10","BooleanArray.prototype.at":"\nBooleanArray.prototype.at( i )\n    Returns an array element located at integer position (index) `i`, with\n    support for noth nonnegative and negative integer positions.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n\n    Returns\n    -------\n    out: boolean|void\n        An array element.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, false, true ] )\n    <BooleanArray>\n    > var v = arr.at( 1 )\n    false\n    > v = arr.at( -1 )\n    true","BooleanArray.prototype.copyWithin":"\nBooleanArray.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n    \n    start: integer\n        Source start index position.\n    \n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: BooleanArray\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, false, true ] )\n    <BooleanArray>\n    > arr.copyWithin( 0, 2 )\n    <BooleanArray>\n    > var v = arr.get( 0 )\n    false\n    > v = arr.get( 1 )\n    true","BooleanArray.prototype.entries":"\nBooleanArray.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var it = arr.entries();\n    > var v = it.next().value\n    [ 0, true ]\n    > v = it.next().value\n    [ 1, false ]\n    > v = it.next().value\n    [ 2, true ]\n    > var bool = it.next().done\n    true","BooleanArray.prototype.every":"\nBooleanArray.prototype.every( predicate[, thisArg] )\n    Returns a boolean indicating whether all elements in the array pass a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all elements pass the test.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ true, true, true ] )\n    <BooleanArray>\n    > var bool = arr.every( predicate )\n    true","BooleanArray.prototype.fill":"\nBooleanArray.prototype.fill( value[, start[, end]] )\n    Returns a modified typed array filled with a fill value.\n\n    Parameters\n    ----------\n    value: boolean\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: BooleanArray\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new BooleanArray( 3 )\n    <BooleanArray>\n    > arr.fill( true );\n    > var v = arr.get( 0 )\n    true\n    > v = arr.get( 1 )\n    true\n    > v = arr.get( 2 )\n    true","BooleanArray.prototype.filter":"\nBooleanArray.prototype.filter( predicate[, thisArg] )\n    Returns a new array containing the elements of an array which pass a test\n    implemented by a predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: BooleanArray\n        A new typed array.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( v === true ); };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.filter( predicate )\n    <BooleanArray>\n    > var len = out.length\n    2\n    > var v = out.get( 0 )\n    true\n    > v = out.get( 1 )\n    true","BooleanArray.prototype.find":"\nBooleanArray.prototype.find( predicate[, thisArg] )\n    Returns the first element in an array for which a predicate function returns\n    a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: boolean|void\n        Array element or `undefined`.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var v = arr.find( predicate )\n    true","BooleanArray.prototype.findIndex":"\nBooleanArray.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var idx = arr.findIndex( predicate )\n    0","BooleanArray.prototype.findLast":"\nBooleanArray.prototype.findLast( predicate[, thisArg] )\n    Returns the last element in an array for which a predicate function returns\n    a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: boolean|void\n        Array element or `undefined`.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var v = arr.findLast( predicate )\n    true","BooleanArray.prototype.findLastIndex":"\nBooleanArray.prototype.findLastIndex( predicate[, thisArg] )\n    Returns the index of the last element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var idx = arr.findLastIndex( predicate )\n    2","BooleanArray.prototype.forEach":"\nBooleanArray.prototype.forEach( clbk[, thisArg] )\n    Invokes a function once for each array element.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Examples\n    --------\n    > var str = '%';\n    > function clbk( v ) { str += v.toString() + '%'; };\n    > var arr = new BooleanArray( [ true, false, false, true ] )\n    <BooleanArray>\n    > arr.forEach( clbk );\n    > str\n    '%true%false%false%true%'","BooleanArray.prototype.get":"\nBooleanArray.prototype.get( i )\n    Returns an array element located at integer position (index) `i`.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n\n    Returns\n    -------\n    out: boolean|void\n        Array element or `undefined`.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 10 )\n    <BooleanArray>\n    > arr.set( true, 0 );\n    > var v = arr.get( 0 )\n    true","BooleanArray.prototype.includes":"\nBooleanArray.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a provided value.\n\n    Parameters\n    ----------\n    searchElement: boolean\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true, true, true ] )\n    <BooleanArray>\n    > var bool = arr.includes( true )\n    true\n    > bool = arr.includes( false, 3 )\n    false","BooleanArray.prototype.indexOf":"\nBooleanArray.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the first index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: boolean\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true, true, true ] )\n    <BooleanArray>\n    > var idx = arr.indexOf( true )\n    0\n    > idx = arr.indexOf( false, 3 )\n    -1","BooleanArray.prototype.join":"\nBooleanArray.prototype.join( [separator] )\n    Returns a new string by concatenating all array elements separated by a\n    separator string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        Separator string. Default: ','.\n\n    Returns\n    -------\n    out: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var str = arr.join()\n    'true,false,true'\n    > str = arr.join( '|' )\n    'true|false|true'","BooleanArray.prototype.keys":"\nBooleanArray.prototype.keys()\n    Returns an iterator for iterating over each index key in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array index keys.\n    \n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false ] )\n    <BooleanArray>\n    > var it = arr.keys();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().done\n    true","BooleanArray.prototype.lastIndexOf":"\nBooleanArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the last index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: boolean\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: out.length-1.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, true, true, false, true ] )\n    <BooleanArray>\n    > var idx = arr.lastIndexOf( false )\n    3\n    > idx = arr.lastIndexOf( false, 2 )\n    -1","BooleanArray.prototype.map":"\nBooleanArray.prototype.map( clbk[, thisArg] )\n    Returns a new array with each element being the result of a provided\n    callback function.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: BooleanArray\n        A new typed array.\n\n    Examples\n    --------\n    > function invert( v ) { return !v; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.map( invert )\n    <BooleanArray>\n    > var v = out.get( 0 )\n    false\n    > v = out.get( 1 )\n    true\n    > v = out.get( 2 )\n    false","BooleanArray.prototype.reduce":"\nBooleanArray.prototype.reduce( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in order, passing\n    in the return value from the calculation on the preceding element and\n    returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.\n\n    initialValue: any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: any\n        Accumulated result.\n\n    Examples\n    --------\n    > function reducer( acc, v ) { return ( acc && v ); };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.reduce( reducer )\n    false","BooleanArray.prototype.reduceRight":"\nBooleanArray.prototype.reduceRight( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in reverse order,\n    passing in the return value from the calculation on the preceding element\n    and returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.\n\n    initialValue: any (optional)\n        Initial accumulation value.\n    \n    Returns\n    -------\n    out: any\n        Accumulated result.\n    \n    Examples\n    --------\n    > function reducer( acc, v ) { return ( acc && v ); };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.reduceRight( reducer )\n    false","BooleanArray.prototype.reverse":"\nBooleanArray.prototype.reverse()\n    Reverses the array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: BooleanArray\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, false ] )\n    <BooleanArray>\n    > arr.reverse();\n    > var v = arr.get( 0 )\n    false\n    > v = arr.get( 1 )\n    false\n    > v = arr.get( 2 )\n    true","BooleanArray.prototype.set":"\nBooleanArray.prototype.set( v[, i] )\n    Sets one or more array elements.\n\n    If provided a single argument, the method sets array elements starting at\n    position (index) `i = 0`. To set elements starting elsewhere in the array,\n    provide an index argument `i`.\n\n    To set one or more array elements, provide an array-like object containing\n    truthy and falsy values.\n\n    Parameters\n    ----------\n    v: bool|BooleanArray|ArrayLikeObject\n        Boolean value or Boolean value array.\n\n    i: integer (optional)\n        Array index at which to start setting elements. Default: 0.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 2 )\n    <BooleanArray>\n    > arr.set( false );\n    > var v = arr.get( 0 )\n    false\n    > arr.set( true, 1 );\n    > v = arr.get( 1 )\n    true","BooleanArray.prototype.slice":"\nBooleanArray.prototype.slice( [start[, end]] )\n    Copies a portion of a typed array to a new typed array.\n\n    Parameters\n    ----------\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: BooleanArray\n        New typed array.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true, false, true ] )\n    <BooleanArray>\n    > var out = arr.slice( 1 )\n    <BooleanArray>\n    > var len = out.length\n    4\n    > var v = out.get( 0 )\n    false\n    > v = out.get( 1 )\n    true","BooleanArray.prototype.some":"\nBooleanArray.prototype.some( predicate[, thisArg] )\n    Returns a boolean indicating whether at least one element passes a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one element passes the test.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ false, true, false ] )\n    <BooleanArray>\n    > var bool = arr.some( predicate )\n    true","BooleanArray.prototype.sort":"\nBooleanArray.prototype.sort( [compareFunction] )\n    Sorts an array in-place.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first boolean value for comparison.\n    - b: second boolean value for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Comparison function.\n\n    Returns\n    -------\n    out: BooleanArray\n        Modified array.\n\n    Examples\n    --------\n    > function compare( a, b ) { return a === true ? -1 : 1; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > arr.sort( compare );\n    > var v = arr.get( 0 )\n    true\n    > v = arr.get( 1 )\n    true\n    > v = arr.get( 2 )\n    false","BooleanArray.prototype.subarray":"\nBooleanArray.prototype.subarray( [begin[, end]] )\n    Creates a new typed array view over the same underlying `ArrayBuffer` and\n    with the same underlying data type as the host array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: BooleanArray\n        New typed array view.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true, false, true ] )\n    <BooleanArray>\n    > var out = arr.subarray( 1, 3 )\n    <BooleanArray>\n    > var len = out.length\n    2\n    > var v = out.get( 0 )\n    false\n    > v = out.get( 1 )\n    true","BooleanArray.prototype.toLocaleString":"\nBooleanArray.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array (optional)\n        Locale identifier(s).\n    \n    options: Object (optional)\n        An object containing serialization options.\n    \n    Returns\n    -------\n    str: string\n        Local-specific string.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var str = arr.toLocaleString()\n    'true,false,true'","BooleanArray.prototype.toReversed":"\nBooleanArray.prototype.toReversed()\n    Returns a new typed array containing the elements in reversed order.\n\n    Returns\n    -------\n    out: BooleanArray\n        New typed array.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, false ] )\n    <BooleanArray>\n    > var out = arr.toReversed()\n    <BooleanArray>\n    > var v = out.get( 0 )\n    false\n    > v = out.get( 1 )\n    false\n    > v = out.get( 2 )\n    true","BooleanArray.prototype.toSorted":"\nBooleanArray.prototype.toSorted( [compareFunction] )\n    Returns a new typed array containing the elements in sorted order.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first boolean value for comparison.\n    - b: second boolean value for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Comparison function.\n\n    Returns\n    -------\n    out: BooleanArray\n        New typed array.\n\n    Examples\n    --------\n    > function compare( a, b ) { return a === true ? -1 : 1; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.toSorted( compare );\n    > var v = out.get( 0 )\n    true\n    > v = out.get( 1 )\n    true\n    > v = out.get( 2 )\n    false","BooleanArray.prototype.toString":"\nBooleanArray.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    out: string\n        String serialization of the array.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var str = arr.toString()\n    'true,false,true'","BooleanArray.prototype.values":"\nBooleanArray.prototype.values()\n    Returns an iterator for iterating over each value in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array values.\n    \n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false ] )\n    <BooleanArray>\n    > var it = arr.values();\n    > var v = it.next().value\n    true\n    > v = it.next().value\n    false\n    > var bool = it.next().done\n    true","BooleanArray.prototype.with":"\nBooleanArray.prototype.with( index, value )\n    Returns a new typed array with the element at a provided index replaced\n    with a provided value.\n\n    Parameters\n    ----------\n    index: integer\n        Element index.\n    \n    value: boolean\n        Element value.  \n\n    Returns\n    -------\n    out: BooleanArray\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.with( 0, false )\n    <BooleanArray>\n    > var v = out.get( 0 )\n    false\n\n\n    See Also\n    --------\n    ArrayBuffer","broadcastArray":"\nbroadcastArray( x, shape )\n    Broadcasts an ndarray to a specified shape.\n\n    The returned array is a read-only view on the input array data buffer. The\n    view is typically *not* contiguous. As more than one element of a returned\n    view may refer to the same memory location, writing to the input array may\n    affect multiple elements. If you need to write to the input array, copy the\n    input array before broadcasting.\n\n    The function throws an error if a provided ndarray is incompatible with a\n    provided shape.\n\n    The function always returns a new ndarray instance even if the input ndarray\n    shape and the desired shape are the same.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    shape: ArrayLikeObject\n        Desired shape.\n\n    Returns\n    -------\n    out: ndarray\n        Broadcasted array.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n    <ndarray>\n    > var sh = x.shape\n    [ 2, 2 ]\n    > var y = broadcastArray( x, [ 3, 2, 2 ] )\n    <ndarray>\n    > sh = y.shape\n    [ 3, 2, 2 ]\n    > var v = y.get( 0, 0, 0 )\n    1\n    > v = y.get( 0, 0, 1 )\n    2\n    > v = y.get( 0, 1, 0 )\n    3\n    > v = y.get( 0, 1, 1 )\n    4\n    > v = y.get( 1, 0, 0 )\n    1\n    > v = y.get( 1, 1, 0 )\n    3\n    > v = y.get( 2, 0, 0 )\n    1\n    > v = y.get( 2, 1, 1 )\n    4\n\n    See Also\n    --------\n    array, broadcastArrays, ndarray, maybeBroadcastArray\n","broadcastArrays":"\nbroadcastArrays( ...arrays )\n    Broadcasts ndarrays to a common shape.\n\n    The function supports two (mutually exclusive) means of providing ndarray\n    arguments:\n\n    1. Providing a single array containing ndarray arguments.\n    2. Providing ndarray arguments as separate arguments.\n\n    The returned arrays are read-only views on their respective underlying\n    array data buffers. The views are typically **not** contiguous. As more\n    than one element of a returned view may refer to the same memory location,\n    writing to a view may affect multiple elements. If you need to write to an\n    input array, copy the array before broadcasting.\n\n    The function throws an error if provided broadcast-incompatible ndarrays.\n\n    The function always returns new ndarray instances even if an input ndarray\n    and the broadcasted shape are the same.\n\n    Parameters\n    ----------\n    arrays: ...ndarray|ArrayLikeObject<ndarray>\n        Array arguments.\n\n    Returns\n    -------\n    out: Array<ndarray>\n        Broadcasted arrays.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n    <ndarray>\n    > var sh = x.shape\n    [ 2, 2 ]\n    > var y = ndzeros( [ 3, 2, 2 ] )\n    <ndarray>\n    > var out = broadcastArrays( [ x, y ] )\n    [ <ndarray>, <ndarray> ]\n\n    // Retrieve the broadcasted \"x\" array:\n    > var bx = out[ 0 ]\n    <ndarray>\n    > sh = bx.shape\n    [ 3, 2, 2 ]\n\n    // Retrieve broadcasted elements...\n    > var v = bx.get( 0, 0, 0 )\n    1\n    > v = bx.get( 0, 0, 1 )\n    2\n    > v = bx.get( 0, 1, 0 )\n    3\n    > v = bx.get( 0, 1, 1 )\n    4\n    > v = bx.get( 1, 0, 0 )\n    1\n    > v = bx.get( 1, 1, 0 )\n    3\n    > v = bx.get( 2, 0, 0 )\n    1\n    > v = bx.get( 2, 1, 1 )\n    4\n\n    See Also\n    --------\n    array, broadcastArray, ndarray, maybeBroadcastArrays\n","Buffer":"\nBuffer\n    Buffer constructor.\n\n\nBuffer( size )\n    Allocates a buffer having a specified number of bytes.\n\n    Parameters\n    ----------\n    size: integer\n        Number of bytes to allocate.\n\n    Returns\n    -------\n    out: Buffer\n        Buffer instance.\n\n    Examples\n    --------\n    > var b = new Buffer( 4 )\n    <Buffer>\n\n\nBuffer( buffer )\n    Copies buffer data to a new Buffer instance.\n\n    Parameters\n    ----------\n    buffer: Buffer\n        Buffer to copy from.\n\n    Returns\n    -------\n    out: Buffer\n        Buffer instance.\n\n    Examples\n    --------\n    > var b1 = new Buffer( [ 1, 2, 3, 4 ] );\n    > var b2 = new Buffer( b1 )\n    <Buffer>[ 1, 2, 3, 4 ]\n\n\nBuffer( array )\n    Allocates a buffer using an array of octets.\n\n    Parameters\n    ----------\n    array: Array\n        Array of octets.\n\n    Returns\n    -------\n    out: Buffer\n        Buffer instance.\n\n    Examples\n    --------\n    > var b = new Buffer( [ 1, 2, 3, 4 ] )\n    <Buffer>[ 1, 2, 3, 4 ]\n\n\nBuffer( str[, encoding] )\n    Allocates a buffer containing a provided string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    encoding: string (optional)\n        Character encoding. Default: 'utf8'.\n\n    Returns\n    -------\n    out: Buffer\n        Buffer instance.\n\n    Examples\n    --------\n    > var b = new Buffer( 'beep boop' )\n    <Buffer>\n\n\nTODO: add methods and properties\n\n\n    See Also\n    --------\n    ArrayBuffer\n","buffer2json":"\nbuffer2json( buffer )\n    Returns a JSON representation of a buffer.\n\n    Parameters\n    ----------\n    buffer: Buffer\n        Buffer to serialize.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    out.type: string\n        Value type. The assigned value is always \"Buffer\".\n\n    out.data: Array\n        Buffer data.\n\n    Examples\n    --------\n    > var buf = new allocUnsafe( 2 );\n    > buf[ 0 ] = 1;\n    > buf[ 1 ] = 2;\n    > var json = buffer2json( buf )\n    { 'type': 'Buffer', 'data': [ 1, 2 ] }\n\n    See Also\n    --------\n    typedarray2json, reviveBuffer\n","BYTE_ORDER":"\nBYTE_ORDER\n    Platform byte order.\n\n    Possible values:\n\n    - 'little-endian'\n    - 'big-endian'\n    - 'mixed-endian'\n    - 'unknown'\n\n    Examples\n    --------\n    > BYTE_ORDER\n    <string>\n\n    See Also\n    --------\n    IS_BIG_ENDIAN, IS_LITTLE_ENDIAN\n","camelcase":"\ncamelcase( str )\n    Converts a string to camel case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Camel-cased string.\n\n    Examples\n    --------\n    > var out = camelcase( 'Hello World!' )\n    'helloWorld'\n    > out = camelcase( 'beep boop' )\n    'beepBoop'\n\n    See Also\n    --------\n    constantcase, kebabcase, pascalcase, snakecase","capitalize":"\ncapitalize( str )\n    Capitalizes the first character in a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Capitalized string.\n\n    Examples\n    --------\n    > var out = capitalize( 'beep' )\n    'Beep'\n    > out = capitalize( 'Boop' )\n    'Boop'\n\n    See Also\n    --------\n    uncapitalize, uppercase\n","capitalizeKeys":"\ncapitalizeKeys( obj )\n    Converts the first letter of each object key to uppercase.\n\n    The function only transforms own properties. Hence, the function does not\n    transform inherited properties.\n\n    The function shallow copies key values.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > var obj = { 'aa': 1, 'bb': 2 };\n    > var out = capitalizeKeys( obj )\n    { 'Aa': 1, 'Bb': 2 }\n\n    See Also\n    --------\n    uncapitalizeKeys, uppercaseKeys\n","CATALAN":"\nCATALAN\n    Catalan's constant.\n\n    Examples\n    --------\n    > CATALAN\n    0.915965594177219\n\n","CBRT_EPS":"\nCBRT_EPS\n    Cube root of double-precision floating-point epsilon.\n\n    Examples\n    --------\n    > CBRT_EPS\n    0.0000060554544523933395\n\n    See Also\n    --------\n    EPS, SQRT_EPS\n","CDC_NCHS_US_BIRTHS_1969_1988":"\nCDC_NCHS_US_BIRTHS_1969_1988()\n    Returns US birth data from 1969 to 1988, as provided by the Center for\n    Disease Control and Prevention's National Center for Health Statistics.\n\n    Returns\n    -------\n    out: Array<Object>\n        Birth data.\n\n    Examples\n    --------\n    > var data = CDC_NCHS_US_BIRTHS_1969_1988()\n    [ {...}, ... ]\n\n    See Also\n    --------\n    CDC_NCHS_US_BIRTHS_1994_2003, SSA_US_BIRTHS_2000_2014\n","CDC_NCHS_US_BIRTHS_1994_2003":"\nCDC_NCHS_US_BIRTHS_1994_2003()\n    Returns US birth data from 1994 to 2003, as provided by the Center for\n    Disease Control and Prevention's National Center for Health Statistics.\n\n    Returns\n    -------\n    out: Array<Object>\n        Birth data.\n\n    Examples\n    --------\n    > var data = CDC_NCHS_US_BIRTHS_1994_2003()\n    [ {...}, ... ]\n\n    See Also\n    --------\n    CDC_NCHS_US_BIRTHS_1969_1988, SSA_US_BIRTHS_2000_2014\n","CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013":"\nCDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n    Returns US infant mortality data, by race, from 1915 to 2013, as provided by\n    the Center for Disease Control and Prevention's National Center for Health\n    Statistics.\n\n    All birth data by race before 1980 are based on race of the child. Starting\n    in 1980, birth data by race are based on race of the mother. Birth data are\n    used to calculate infant mortality rate.\n\n    Returns\n    -------\n    out: Array<Object>\n        Infant mortality data.\n\n    Examples\n    --------\n    > var data = CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n    { 'black': [...], 'white': [...] }\n\n","chdir":"\nchdir( path )\n    Changes the current working directory.\n\n    If unable to set the current working directory (e.g., due to a non-existent\n    path), the function returns an error; otherwise, the function returns\n    `null`.\n\n    Parameters\n    ----------\n    path: string\n        Desired working directory.\n\n    Returns\n    -------\n    err: Error|null\n        Error object or null.\n\n    Examples\n    --------\n    > var err = chdir( '/path/to/current/working/directory' )\n\n    See Also\n    --------\n    cwd\n","chi2gof":"\nchi2gof( x, y[, ...args][, options] )\n    Performs a chi-square goodness-of-fit test.\n\n    A chi-square goodness-of-fit test is computed for the null hypothesis that\n    the values of `x` come from the discrete probability distribution specified\n    by `y`.\n\n    The second argument can either be expected frequencies, population\n    probabilities summing to one, or a discrete probability distribution name to\n    test against.\n\n    When providing a discrete probability distribution name, distribution\n    parameters *must* be supplied as additional arguments.\n\n    The function returns an object containing the test statistic, p-value, and\n    decision.\n\n    By default, the p-value is computed using a chi-square distribution with\n    `k-1` degrees of freedom, where `k` is the length of `x`.\n\n    If provided distribution arguments are estimated (e.g., via maximum\n    likelihood estimation), the degrees of freedom should be corrected. Set the\n    `ddof` option to use `k-1-n` degrees of freedom, where `n` is the degrees of\n    freedom adjustment.\n\n    The chi-square approximation may be incorrect if the observed or expected\n    frequencies in each category are too small. Common practice is to require\n    frequencies greater than five.\n\n    Instead of relying on chi-square approximation to calculate the p-value, one\n    can use Monte Carlo simulation. When the `simulate` option is `true`, the\n    simulation is performed by re-sampling from the discrete probability\n    distribution specified by `y`.\n\n    Parameters\n    ----------\n    x: ndarray|Array<number>|TypedArray\n        Observation frequencies.\n\n    y: ndarray|Array<number>|TypedArray|string\n        Expected frequencies, population probabilities, or a discrete\n        probability distribution name.\n\n    args: ...number (optional)\n        Distribution parameters. Distribution parameters will be passed to a\n        probability mass function (PMF) as arguments.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Significance level of the hypothesis test. Must be on the interval\n        [0,1]. Default: 0.05.\n\n    options.ddof: number (optional)\n        Delta degrees of freedom adjustment. Default: 0.\n\n    options.simulate: boolean (optional)\n        Boolean indicating whether to calculate p-values by Monte Carlo\n        simulation. The simulation is performed by re-sampling from the discrete\n        distribution specified by `y`. Default: false.\n\n    options.iterations: number (optional)\n        Number of Monte Carlo iterations. Default: 500.\n\n    Returns\n    -------\n    out: Object\n        Test results object.\n\n    out.alpha: number\n        Significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        Test p-value.\n\n    out.statistic: number\n        Test statistic.\n\n    out.df: number|null\n        Degrees of freedom.\n\n    out.method: string\n        Test name.\n\n    out.toString: Function\n        Serializes results as formatted output.\n\n    out.toJSON: Function\n        Serializes results as JSON.\n\n    Examples\n    --------\n    // Provide expected probabilities...\n    > var x = [ 89, 37, 30, 28, 2 ];\n    > var p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\n    > var out = chi2gof( x, p );\n    > var o = out.toJSON()\n    { 'pValue': ~0.0406, 'statistic': ~9.9901, ... }\n    > out.toString()\n\n    // Set significance level...\n    > var opts = { 'alpha': 0.01 };\n    > out = chi2gof( x, p, opts );\n    > out.toString()\n\n    // Calculate the test p-value via Monte Carlo simulation...\n    > x = [ 89, 37, 30, 28, 2 ];\n    > p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\n    > opts = { 'simulate': true, 'iterations': 1000 };\n    > out = chi2gof( x, p, opts );\n    > out.toString()\n\n    // Verify that data comes from Poisson distribution...\n    > var lambda = 3.0;\n    > var rpois = base.random.poisson.factory( lambda );\n    > var len = 400;\n    > x = [];\n    > for ( var i = 0; i < len; i++ ) { x.push( rpois() ); };\n\n    // Generate a frequency table...\n    > var freqs = new Int32Array( len );\n    > for ( i = 0; i < len; i++ ) { freqs[ x[ i ] ] += 1; };\n    > out = chi2gof( freqs, 'poisson', lambda );\n    > out.toString()\n\n","chi2test":"\nchi2test( x[, options] )\n    Performs a chi-square independence test.\n\n    For a two-way contingency table, the function computes a chi-square\n    independence test for the null hypothesis that the joint distribution of the\n    cell counts is the product of the row and column marginals (i.e. that the\n    row and column variables are independent).\n\n    The chi-square approximation may be incorrect if the observed or expected\n    frequencies in each category are too small. Common practice is to require\n    frequencies greater than five. The Yates' continuity correction is enabled\n    by default for 2x2 tables to account for this, although it tends to\n    over-correct.\n\n    The function returns an object containing the test statistic, p-value, and\n    decision.\n\n    Parameters\n    ----------\n    x: ndarray|Array<Collection<number>>\n        Two-way table of observed frequencies.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Significance level of the hypothesis test. Must be on the interval\n        [0,1]. Default: 0.05.\n\n    options.correct: boolean (optional)\n        Boolean indicating whether to use Yates' continuity correction when\n        provided a 2x2 contingency table. Default: true.\n\n    Returns\n    -------\n    out: Object\n        Test results object.\n\n    out.alpha: number\n        Significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        Test p-value.\n\n    out.statistic: number\n        Test statistic.\n\n    out.df: number\n        Degrees of freedom.\n\n    out.expected: ndarray\n        Expected frequencies.\n\n    out.method: string\n        Test name.\n\n    out.toString: Function\n        Serializes results as formatted output.\n\n    out.toJSON: Function\n        Serializes results as JSON.\n\n    Examples\n    --------\n    > var x = [ [ 20, 30 ], [ 30, 20 ] ];\n    > var out = chi2test( x );\n    > var o = out.toJSON()\n    { 'rejected': false, 'pValue': ~0.072, 'statistic': 3.24, ... }\n    > out.toString()\n\n    // Set significance level...\n    > var opts = { 'alpha': 0.1 };\n    > out = chi2test( x, opts );\n    > o = out.toJSON()\n    { 'rejected': true, 'pValue': ~0.072, 'statistic': 3.24, ... }\n    > out.toString()\n\n    // Disable Yates' continuity correction (primarily used with small counts):\n    > opts = { 'correct': false };\n    > out = chi2test( x, opts );\n    > out.toString()\n\n","circarray2iterator":"\ncircarray2iterator( src[, options][, mapFcn[, thisArg]] )\n    Returns an iterator which repeatedly iterates over the elements of an array-\n    like object.\n\n    When invoked, an input function is provided four arguments:\n\n    - value: iterated value.\n    - index: iterated value index.\n    - n: iteration count.\n    - src: source array-like object.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an array's `@@iterator` method, regardless of whether this method is\n    defined. To convert an array to an implementation defined iterator, invoke\n    this method directly.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Array-like object from which to create the iterator.\n\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    options.dir: integer (optional)\n        Iteration direction. If set to `-1`, an iterator iterates over elements\n        from right-to-left. Default: 1.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = circarray2iterator( [ 1, 2, 3, 4 ] );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    array2iterator, stridedarray2iterator\n","circularArrayStream":"\ncircularArrayStream( src[, options] )\n    Creates a readable stream from an array-like object which repeatedly\n    iterates over the provided value's elements.\n\n    In object mode, `null` is a reserved value. If an array contains `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or filter `null` values\n    prior to invocation.\n\n    In binary mode, if an array contains `undefined` values, the stream will\n    emit an error. Consider providing a custom serialization function or\n    filtering `undefined` values prior to invocation.\n\n    If a serialization function fails to return a string or Buffer, the stream\n    emits an error.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Source value.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing the stream.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize streamed\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    options.dir: integer (optional)\n        Iteration direction. If set to `-1`, a stream iterates over elements\n        from right-to-left. Default: 1.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 15 };\n    > var s = circularArrayStream( [ 1, 2, 3 ], opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\ncircularArrayStream.factory( [options] )\n    Returns a function for creating readable streams from array-like objects\n    which repeatedly iterate over the elements of provided values.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing streaming.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize streamed\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    options.dir: integer (optional)\n        Iteration direction. If set to `-1`, a stream iterates over elements\n        from right-to-left. Default: 1.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = circularArrayStream.factory( opts );\n\n\ncircularArrayStream.objectMode( src[, options] )\n    Returns an \"objectMode\" readable stream from an array-like object which\n    repeatedly iterates over a provided value's elements.\n\n    In object mode, `null` is a reserved value. If an array contains `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or filter `null` values\n    prior to invocation.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Source value.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before pausing streaming.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    options.dir: integer (optional)\n        Iteration direction. If set to `-1`, a stream iterates over elements\n        from right-to-left. Default: 1.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 15 };\n    > var s = circularArrayStream.objectMode( [ 1, 2, 3 ], opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    arrayStream, iteratorStream, stridedArrayStream\n","circularArrayStream.factory":"\ncircularArrayStream.factory( [options] )\n    Returns a function for creating readable streams from array-like objects\n    which repeatedly iterate over the elements of provided values.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing streaming.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize streamed\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    options.dir: integer (optional)\n        Iteration direction. If set to `-1`, a stream iterates over elements\n        from right-to-left. Default: 1.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = circularArrayStream.factory( opts );","circularArrayStream.objectMode":"\ncircularArrayStream.objectMode( src[, options] )\n    Returns an \"objectMode\" readable stream from an array-like object which\n    repeatedly iterates over a provided value's elements.\n\n    In object mode, `null` is a reserved value. If an array contains `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or filter `null` values\n    prior to invocation.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Source value.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before pausing streaming.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    options.dir: integer (optional)\n        Iteration direction. If set to `-1`, a stream iterates over elements\n        from right-to-left. Default: 1.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 15 };\n    > var s = circularArrayStream.objectMode( [ 1, 2, 3 ], opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    arrayStream, iteratorStream, stridedArrayStream","CircularBuffer":"\nCircularBuffer( buffer )\n    Circular buffer constructor.\n\n    Parameters\n    ----------\n    buffer: integer|ArrayLike\n        Buffer size or an array-like object to use as the underlying buffer.\n\n    Returns\n    -------\n    buf: Object\n        Circular buffer data structure.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.push( 'foo' );\n    > b.push( 'bar' );\n    > b.push( 'beep' );\n    > b.length\n    3\n    > b.count\n    3\n    > b.push( 'boop' )\n    'foo'\n\n\nCircularBuffer.prototype.clear()\n    Clears a buffer.\n\n    Returns\n    -------\n    out: Object\n        Circular buffer instance.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.push( 'foo' );\n    > b.push( 'bar' );\n    > b.push( 'beep' );\n    > b.count\n    3\n    > b.clear();\n    > b.count\n    0\n\n\nCircularBuffer.prototype.count\n    Read-only property returning the number of elements currently in the buffer.\n\n    Returns\n    -------\n    out: integer\n        Number of elements currently in the buffer.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.count\n    0\n    > b.push( 'foo' );\n    > b.count\n    1\n    > b.push( 'bar' );\n    > b.count\n    2\n\n\nCircularBuffer.prototype.full\n    Read-only property returning a boolean indicating whether a circular buffer\n    is full.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether a circular buffer is full.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.full\n    false\n    > b.push( 'foo' );\n    > b.push( 'bar' );\n    > b.push( 'beep' );\n    > b.full\n    true\n\n\nCircularBuffer.prototype.iterator( [niters] )\n    Returns an iterator for iterating over a circular buffer.\n\n    A returned iterator does not iterate over partially full buffers.\n\n    Parameters\n    ----------\n    niters: integer (optional)\n        Number of iterations. Default: infinity.\n\n    Returns\n    -------\n    out: Iterator\n        Iterator.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.push( 'foo' );\n    > b.push( 'bar' );\n    > b.push( 'beep' );\n    > b.push( 'boop' );\n    > var it = b.iterator( b.length );\n    > var v = it.next().value\n    'bar'\n    > v = it.next().value\n    'beep'\n    > v = it.next().value\n    'boop'\n    > var bool = it.next().done\n    true\n\n\nCircularBuffer.prototype.length\n    Read-only property returning the buffer length (i.e., capacity).\n\n    Returns\n    -------\n    out: integer\n        Buffer length.\n\n    Examples\n    --------\n    > var b = CircularBuffer( [ 0, 0, 0 ] );\n    > var len = b.length\n    3\n\n\nCircularBuffer.prototype.push( value )\n    Adds a value to a circular buffer.\n\n    Parameters\n    ----------\n    value: any\n        Value to add.\n\n    Returns\n    -------\n    out: any\n        Removed element (or undefined).\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.push( 'foo' )\n    undefined\n    > b.push( 'bar' )\n    undefined\n    > b.push( 'beep' )\n    undefined\n    > b.push( 'boop' )\n    'foo'\n\n\nCircularBuffer.prototype.toArray()\n    Returns an array of circular buffer values.\n\n    Returns\n    -------\n    out: Array\n        Circular buffer values.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.push( 'foo' );\n    > b.push( 'bar' );\n    > b.push( 'beep' );\n    > b.push( 'boop' );\n    > var vals = b.toArray()\n    [ 'bar', 'beep', 'boop' ]\n\n\nCircularBuffer.prototype.toJSON()\n    Serializes a circular buffer as JSON.\n\n    Returns\n    -------\n    out: Object\n        Serialized circular buffer.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.push( 'foo' );\n    > b.push( 'bar' );\n    > b.push( 'beep' );\n    > b.push( 'boop' );\n    > var o = b.toJSON()\n    {'type':'circular-buffer','length':3,'data':['bar','beep','boop']}\n\n    See Also\n    --------\n    FIFO, Stack\n","CircularBuffer.prototype.clear":"\nCircularBuffer.prototype.clear()\n    Clears a buffer.\n\n    Returns\n    -------\n    out: Object\n        Circular buffer instance.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.push( 'foo' );\n    > b.push( 'bar' );\n    > b.push( 'beep' );\n    > b.count\n    3\n    > b.clear();\n    > b.count\n    0","CircularBuffer.prototype.count":"\nCircularBuffer.prototype.count\n    Read-only property returning the number of elements currently in the buffer.\n\n    Returns\n    -------\n    out: integer\n        Number of elements currently in the buffer.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.count\n    0\n    > b.push( 'foo' );\n    > b.count\n    1\n    > b.push( 'bar' );\n    > b.count\n    2","CircularBuffer.prototype.full":"\nCircularBuffer.prototype.full\n    Read-only property returning a boolean indicating whether a circular buffer\n    is full.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether a circular buffer is full.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.full\n    false\n    > b.push( 'foo' );\n    > b.push( 'bar' );\n    > b.push( 'beep' );\n    > b.full\n    true","CircularBuffer.prototype.iterator":"\nCircularBuffer.prototype.iterator( [niters] )\n    Returns an iterator for iterating over a circular buffer.\n\n    A returned iterator does not iterate over partially full buffers.\n\n    Parameters\n    ----------\n    niters: integer (optional)\n        Number of iterations. Default: infinity.\n\n    Returns\n    -------\n    out: Iterator\n        Iterator.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.push( 'foo' );\n    > b.push( 'bar' );\n    > b.push( 'beep' );\n    > b.push( 'boop' );\n    > var it = b.iterator( b.length );\n    > var v = it.next().value\n    'bar'\n    > v = it.next().value\n    'beep'\n    > v = it.next().value\n    'boop'\n    > var bool = it.next().done\n    true","CircularBuffer.prototype.length":"\nCircularBuffer.prototype.length\n    Read-only property returning the buffer length (i.e., capacity).\n\n    Returns\n    -------\n    out: integer\n        Buffer length.\n\n    Examples\n    --------\n    > var b = CircularBuffer( [ 0, 0, 0 ] );\n    > var len = b.length\n    3","CircularBuffer.prototype.push":"\nCircularBuffer.prototype.push( value )\n    Adds a value to a circular buffer.\n\n    Parameters\n    ----------\n    value: any\n        Value to add.\n\n    Returns\n    -------\n    out: any\n        Removed element (or undefined).\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.push( 'foo' )\n    undefined\n    > b.push( 'bar' )\n    undefined\n    > b.push( 'beep' )\n    undefined\n    > b.push( 'boop' )\n    'foo'","CircularBuffer.prototype.toArray":"\nCircularBuffer.prototype.toArray()\n    Returns an array of circular buffer values.\n\n    Returns\n    -------\n    out: Array\n        Circular buffer values.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.push( 'foo' );\n    > b.push( 'bar' );\n    > b.push( 'beep' );\n    > b.push( 'boop' );\n    > var vals = b.toArray()\n    [ 'bar', 'beep', 'boop' ]","CircularBuffer.prototype.toJSON":"\nCircularBuffer.prototype.toJSON()\n    Serializes a circular buffer as JSON.\n\n    Returns\n    -------\n    out: Object\n        Serialized circular buffer.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.push( 'foo' );\n    > b.push( 'bar' );\n    > b.push( 'beep' );\n    > b.push( 'boop' );\n    > var o = b.toJSON()\n    {'type':'circular-buffer','length':3,'data':['bar','beep','boop']}\n\n    See Also\n    --------\n    FIFO, Stack","close":"\nclose( fd, clbk )\n    Asynchronously closes a file descriptor, so that the file descriptor no\n    longer refers to any file and may be reused.\n\n    Parameters\n    ----------\n    fd: integer\n        File descriptor.\n\n    clbk: Function\n        Callback to invoke upon closing a file descriptor.\n\n    Examples\n    --------\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     }\n    ... };\n    > var fd = open.sync( './beep/boop.js', 'r+' );\n    > if ( !isError( fd ) ) { close( fd, done ); };\n\n\nclose.sync( fd )\n    Synchronously closes a file descriptor.\n\n    Parameters\n    ----------\n    fd: integer\n        File descriptor.\n\n    Returns\n    -------\n    out: Error|void\n        If an error occurs, an error object; otherwise, undefined.\n\n    Examples\n    --------\n    > var fd = open.sync( './beep/boop.js', 'r+' );\n    > if ( !isError( fd ) ) { close.sync( fd ); };\n\n    See Also\n    --------\n    exists, open, readFile\n","close.sync":"\nclose.sync( fd )\n    Synchronously closes a file descriptor.\n\n    Parameters\n    ----------\n    fd: integer\n        File descriptor.\n\n    Returns\n    -------\n    out: Error|void\n        If an error occurs, an error object; otherwise, undefined.\n\n    Examples\n    --------\n    > var fd = open.sync( './beep/boop.js', 'r+' );\n    > if ( !isError( fd ) ) { close.sync( fd ); };\n\n    See Also\n    --------\n    exists, open, readFile","CMUDICT":"\nCMUDICT( [options] )\n    Returns datasets from the Carnegie Mellon Pronouncing Dictionary (CMUdict).\n\n    Data includes the following:\n\n    - dict: the main pronouncing dictionary.\n    - phones: manners of articulation for each sound.\n    - symbols: complete list of ARPABET symbols used by the dictionary.\n    - vp: verbal pronunciations of punctuation marks.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.data: string (optional)\n        Dataset name.\n\n    Returns\n    -------\n    out: Object|Array\n        CMUdict dataset.\n\n    Examples\n    --------\n    > var data = CMUDICT();\n    > var dict = data.dict\n    {...}\n    > var phones = data.phones\n    {...}\n    > var symbols = data.symbols\n    [...]\n    > var vp = data.vp\n    {...}\n\n","codePointAt":"\ncodePointAt( str, idx[, backward] )\n    Returns a Unicode code point from a string at a specified position.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    idx: integer\n        Position. If less than `0`, the string position is determined relative\n        to the end of the input string.\n\n    backward: boolean (optional)\n        Backward iteration for low surrogates. Default: false.\n\n    Returns\n    -------\n    out: integer\n        Unicode code point.\n\n    Examples\n    --------\n    > var out = codePointAt( 'last man standing', 4 )\n    32\n    > out = codePointAt( 'presidential election', 8, true )\n    116\n    > out = codePointAt( 'अनुच्छेद', 2 )\n    2369\n    > out = codePointAt( '🌷', 1, true )\n    127799\n\n    See Also\n    --------\n    fromCodePoint","commonKeys":"\ncommonKeys( obj1, obj2[, ...obj] )\n    Returns the common own property names of two or more objects.\n\n    Parameters\n    ----------\n    obj1: any\n        First object.\n\n    obj2: any\n        Second object.\n\n    obj: ...any (optional)\n        Additional objects.\n\n    Returns\n    -------\n    out: Array<string>\n        Common keys of objects.\n\n    Examples\n    --------\n    > var obj1 = { 'a': 1, 'b': 2 };\n    > var obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\n    > var keys = commonKeys( obj1, obj2 )\n    [ 'a', 'b' ]\n\n    See Also\n    --------\n    commonKeysIn, objectKeys","commonKeysIn":"\ncommonKeysIn( obj1, obj2[, ...obj] )\n    Returns the common own and inherited property names of two or more objects.\n\n    Parameters\n    ----------\n    obj1: any\n        First object.\n\n    obj2: any\n        Second object.\n\n    obj: ...any (optional)\n        Additional objects.\n\n    Returns\n    -------\n    out: Array<string>\n        Common keys.\n\n    Examples\n    --------\n    > var obj1 = { 'a': 1, 'b': 2 };\n    > var obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\n    > var keys = commonKeysIn( obj1, obj2 )\n    [ 'a', 'b' ]\n\n    See Also\n    --------\n    commonKeys, keysIn","complex":"\ncomplex( real, imag[, dtype] )\n    Creates a complex number.\n\n    The function supports the following data types:\n\n    - float64\n    - float32\n\n    Parameters\n    ----------\n    real: number\n        Real component.\n\n    imag: number\n        Imaginary component.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    z: Complex\n        Complex number.\n\n    Examples\n    --------\n    > var z = complex( 5.0, 3.0, 'float64' )\n    <Complex128>\n    > z = complex( 5.0, 3.0, 'float32' )\n    <Complex64>\n\n    See Also\n    --------\n    Complex128, Complex64\n","Complex64":"\nComplex64( real, imag )\n    64-bit complex number constructor.\n\n    Both the real and imaginary components are stored as single-precision\n    floating-point numbers.\n\n    Parameters\n    ----------\n    real: number\n        Real component.\n\n    imag: number\n        Imaginary component.\n\n    Returns\n    -------\n    z: Complex64\n        64-bit complex number.\n\n    z.re: number\n        Read-only property returning the real component.\n\n    z.im: number\n        Read-only property returning the imaginary component.\n\n    Examples\n    --------\n    > var z = new Complex64( 5.0, 3.0 )\n    <Complex64>\n    > z.re\n    5.0\n    > z.im\n    3.0\n\n\nComplex64.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n\n    Returns\n    -------\n    v: integer\n        Size (in bytes) of each component.\n\n    Examples\n    --------\n    > var s = Complex64.BYTES_PER_ELEMENT\n    4\n\n\nComplex64.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n\n    Returns\n    -------\n    s: integer\n        Size (in bytes) of each component.\n\n    Examples\n    --------\n    > var z = new Complex64( 5.0, 3.0 )\n    <Complex64>\n    > var s = z.BYTES_PER_ELEMENT\n    4\n\n\nComplex64.prototype.byteLength\n    Length (in bytes) of a complex number.\n\n    Returns\n    -------\n    len: integer\n        Length (in bytes) of a complex number.\n\n    Examples\n    --------\n    > var z = new Complex64( 5.0, 3.0 )\n    <Complex64>\n    > var s = z.byteLength\n    8\n\n    See Also\n    --------\n    complex, Complex128\n","Complex64.BYTES_PER_ELEMENT":"\nComplex64.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n\n    Returns\n    -------\n    v: integer\n        Size (in bytes) of each component.\n\n    Examples\n    --------\n    > var s = Complex64.BYTES_PER_ELEMENT\n    4","Complex64.prototype.BYTES_PER_ELEMENT":"\nComplex64.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n\n    Returns\n    -------\n    s: integer\n        Size (in bytes) of each component.\n\n    Examples\n    --------\n    > var z = new Complex64( 5.0, 3.0 )\n    <Complex64>\n    > var s = z.BYTES_PER_ELEMENT\n    4","Complex64.prototype.byteLength":"\nComplex64.prototype.byteLength\n    Length (in bytes) of a complex number.\n\n    Returns\n    -------\n    len: integer\n        Length (in bytes) of a complex number.\n\n    Examples\n    --------\n    > var z = new Complex64( 5.0, 3.0 )\n    <Complex64>\n    > var s = z.byteLength\n    8\n\n    See Also\n    --------\n    complex, Complex128","COMPLEX64_NAN":"\nCOMPLEX64_NAN\n    Canonical single-precision complex floating-point NaN.\n\n    Examples\n    --------\n    > COMPLEX64_NAN\n    <Complex64>\n\n    See Also\n    --------\n    COMPLEX128_NAN\n","COMPLEX64_NUM_BYTES":"\nCOMPLEX64_NUM_BYTES\n    Size (in bytes) of a 64-bit complex number.\n\n    Examples\n    --------\n    > COMPLEX64_NUM_BYTES\n    8\n\n    See Also\n    --------\n    COMPLEX128_NUM_BYTES, FLOAT32_NUM_BYTES\n","COMPLEX64_ZERO":"\nCOMPLEX64_ZERO\n    Single-precision complex floating-point zero.\n\n    Examples\n    --------\n    > COMPLEX64_ZERO\n    <Complex64>\n\n    See Also\n    --------\n    COMPLEX128_ZERO\n","Complex64Array":"\nComplex64Array()\n    A 64-bit complex number array.\n\n    Returns\n    -------\n    out: Complex64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Complex64Array()\n    <Complex64Array>\n\n\nComplex64Array( length )\n    Creates a 64-bit complex number array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: Complex64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 10 )\n    <Complex64Array>\n    > var len = arr.length\n    10\n\n\nComplex64Array( complexarray )\n    Creates a 64-bit complex number array from another complex number array.\n\n    Parameters\n    ----------\n    complexarray: Complex64Array\n        Complex array from which to generate another complex array.\n\n    Returns\n    -------\n    out: Complex64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var arr2 = new Complex64Array( arr1 )\n    <Complex64Array>\n    > var len = arr2.length\n    2\n\n\nComplex64Array( typedarray )\n    Creates a 64-bit complex number array from a typed array\n    containing interleaved real and imaginary components.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate complex array.\n\n    Returns\n    -------\n    out: Complex64Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new Float32Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Float32Array>\n    > var arr = new Complex64Array( buf )\n    <Complex64Array>\n    > var len = arr.length\n    2\n\n\nComplex64Array( obj )\n    Creates a 64-bit complex number array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a complex array.\n\n    Returns\n    -------\n    out: Complex64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var len = arr1.length\n    2\n    > var buf = [ new Complex64( 1.0, -1.0 ), new Complex64( 2.0, -2.0 )];\n    > var arr2 = new Complex64Array( buf )\n    <Complex64Array>\n    > len = arr2.length\n    2\n\n\nComplex64Array( buffer[, byteOffset[, length]] )\n    Returns a 64-bit complex number array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Complex64Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 240 );\n    > var arr1 = new Complex64Array( buf )\n    <Complex64Array>\n    > var len = arr1.length\n    30\n    > var arr2 = new Complex64Array( buf, 8 )\n    <Complex64Array>\n    > len = arr2.length\n    29\n    > var arr3 = new Complex64Array( buf, 8, 20 )\n    <Complex64Array>\n    > len = arr3.length\n    20\n\n\nComplex64Array.from( src[, clbk[, thisArg]] )\n    Creates a new 64-bit complex number array from an array-like object or an\n    iterable.\n\n    A callback function is provided two arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    clbk: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n    \n    Returns\n    -------\n    out: Complex64Array\n        A typed array.\n    \n    Examples\n    --------\n    > function clbkFcn( v ) { return v * 2.0 };\n    > var arr = Complex64Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\n    <Complex64Array>\n    > var len = arr.length\n    2\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    -2.0\n\n\nComplex64Array.of( element0[, element1[, ...elementN]] )\n    Creates a new 64-bit complex number array from a variable number of\n    arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Complex64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Complex64Array.of( 1.0, -1.0, 2.0, -2.0 )\n    <Complex64Array>\n    > var len = arr.length\n    2\n    > var z1 = new Complex64( 1.0, -1.0 );\n    > var z2 = new Complex64( 2.0, -2.0 );\n    > arr = Complex64Array.of( z1, z2 )\n    <Complex64Array>\n    > len = arr.length\n    2\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    -1.0\n\n\nComplex64Array.BYTES_PER_ELEMENT\n    The size of each array element in bytes.\n\n    Examples\n    --------\n    > var nbytes = Complex64Array.BYTES_PER_ELEMENT\n    8\n\n\nComplex64Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > var str = Complex64Array.name\n    'Complex64Array'\n\n\nComplex64Array.prototype.buffer\n    Pointer to the underlying data buffer.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 2 )\n    <Complex64Array>\n    > var buf = arr.buffer\n    <ArrayBuffer>\n\n\nComplex64Array.prototype.byteLength\n    Length of the array in bytes.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 10 )\n    <Complex64Array>\n    > var nbytes = arr.byteLength\n    80\n\n\nComplex64Array.prototype.byteOffset\n    Offset (in bytes) of the array from the start of its underlying\n    ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 5 )\n    <Complex64Array>\n    > var offset = arr.byteOffset\n    0\n    > var buf = new ArrayBuffer( 240 );\n    > arr = new Complex64Array( buf, 64 )\n    <Complex64Array>\n    > offset = arr.byteOffset\n    64\n\n\nComplex64Array.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 10 )\n    <Complex64Array>\n    > arr.BYTES_PER_ELEMENT\n    8\n\n\nComplex64Array.prototype.length\n    The number of array elements.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 10 )\n    <Complex64Array>\n    > var len = arr.length\n    10\n\n\nComplex64Array.prototype.at( i )\n    Returns an array element located at integer position (index) `i`, with\n    support for noth nonnegative and negative integer positions.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n\n    Returns\n    -------\n    out: Complex64|void\n        An array element.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var z = arr.at( 1 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    -2.0\n\n\nComplex64Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n    \n    start: integer\n        Source start index position.\n    \n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Complex64Array\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex64Array>\n    > arr.copyWithin( 0, 2 )\n    <Complex64Array>\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    -3.0\n\n\nComplex64Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var it = arr.entries();\n    > var v = it.next().value\n    [ 0, <Complex64> ]\n    > var re = realf( v[ 1 ] )\n    1.0\n    > var im = imagf( v[ 1 ] )\n    -1.0\n    > v = it.next().value\n    [ 1, <Complex64> ]\n    > re = realf( v[ 1 ] )\n    2.0\n    > im = imagf( v[ 1 ] )\n    -2.0\n    > v = it.next().value\n    [ 2, <Complex64> ]\n    > re = realf( v[ 1 ] )\n    3.0\n    > im = imagf( v[ 1 ] )\n    -3.0\n    > var bool = it.next().done\n    true\n\n\nComplex64Array.prototype.every( predicate[, thisArg] )\n    Returns a boolean indicating whether all elements in the array pass a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all elements pass the test.\n\n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) > 0.0 ); };\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var bool = arr.every( predicate )\n    true\n\n\nComplex64Array.prototype.fill( value[, start[, end]] )\n    Returns a modified typed array filled with a fill value.\n\n    Parameters\n    ----------\n    value: Complex64\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Complex64Array\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( 3 )\n    <Complex64Array>\n    > arr.fill( new Complex64( 1.0, 1.0 ) );\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    1.0\n    > z = arr.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    1.0\n    > im = imagf( z )\n    1.0\n    > z = arr.get( 2 )\n    <Complex64>\n    > re = realf( z )\n    1.0\n    > im = imagf( z )\n    1.0\n\n\nComplex64Array.prototype.filter( predicate[, thisArg] )\n    Returns a new array containing the elements of an array which pass a test\n    implemented by a predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Complex64Array\n        A new typed array.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var out = arr.filter( predicate )\n    <Complex64Array>\n    > var len = out.length\n    1\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    2.0\n\n\nComplex64Array.prototype.find( predicate[, thisArg] )\n    Returns the first element in an array for which a predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    out: Complex64|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var z = arr.find( predicate )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    1.0\n\n\nComplex64Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var idx = arr.findIndex( predicate )\n    0\n\n\nComplex64Array.prototype.findLast( predicate[, thisArg] )\n    Returns the last element in an array for which a predicate function returns\n    a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.  \n    \n    Returns\n    -------\n    out: Complex64|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var z = arr.findLast( predicate )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    2.0\n\n\nComplex64Array.prototype.findLastIndex( predicate[, thisArg] )\n    Returns the index of the last element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var idx = arr.findLastIndex( predicate )\n    1\n\n\nComplex64Array.prototype.forEach( clbk[, thisArg] )\n    Invokes a function once for each array element.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Examples\n    --------\n    > var str = '%';\n    > function clbk( v ) { str += v.toString() + '%'; };\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > arr.forEach( clbk );\n    > str\n    '%1 - 1i%2 - 2i%'\n\n\nComplex64Array.prototype.get( i )\n    Returns an array element located at integer position (index) `i`.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n    \n    Returns\n    -------\n    out: Complex64|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var z = arr.get( 1 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    -2.0\n\n\nComplex64Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a provided value.\n\n    Parameters\n    ----------\n    searchElement: Complex64\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n    \n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex64Array>\n    > var bool = arr.includes( new Complex64( 3.0, -3.0 ) )\n    true\n    > bool = arr.includes( new Complex64( 3.0, -3.0 ), 3 )\n    false\n\n\nComplex64Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the first index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: Complex64\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex64Array>\n    > var idx = arr.indexOf( new Complex64( 3.0, -3.0 ) )\n    2\n    > idx = arr.indexOf( new Complex64( 3.0, -3.0 ), 3 )\n    -1\n\n\nComplex64Array.prototype.join( [separator] )\n    Returns a new string by concatenating all array elements separated by a\n    separator string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        Separator string. Default: ','.\n    \n    Returns\n    -------\n    out: string\n        Array serialized as a string.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var str = arr.join()\n    '1 - 1i,2 - 2i'\n    > str = arr.join( '/' )\n    '1 - 1i/2 - 2i'\n\n\nComplex64Array.prototype.keys()\n    Returns an iterator for iterating over each index key in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array index keys.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var it = arr.keys();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().done\n    true\n\n\nComplex64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the last index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: Complex64\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: out.length-1.\n    \n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex64Array>\n    > var idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ) )\n    3\n    > idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ), 2 )\n    0\n\n\nComplex64Array.prototype.map( clbk[, thisArg] )\n    Returns a new array with each element being the result of a provided\n    callback function.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Complex64Array\n        A new typed array.\n    \n    Examples\n    --------\n    > function clbk( v ) { return v; };\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var out = arr.map( clbk )\n    <Complex64Array>\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    -1.0\n    > z = out.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    -2.0\n\n\nComplex64Array.prototype.reduce( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in order, passing\n    in the return value from the calculation on the preceding element and\n    returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.    \n\n    initialValue: any (optional)\n        Initial accumulation value.\n    \n    Returns\n    -------\n    out: any\n        Accumulated result.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var z = arr.reduce( base.caddf )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    -3.0\n\n\nComplex64Array.prototype.reduceRight( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in reverse order,\n    passing in the return value from the calculation on the preceding element\n    and returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.\n\n    initialValue: any (optional)\n        Initial accumulation value.\n    \n    Returns\n    -------\n    out: any\n        Accumulated result.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var z = arr.reduceRight( base.caddf )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    -3.0\n\n\nComplex64Array.prototype.reverse()\n    Reverses the array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Complex64Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > arr.reverse();\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    -3.0\n    > z = arr.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    -2.0\n    > z = arr.get( 2 )\n    <Complex64>\n    > re = realf( z )\n    1.0\n    > im = imagf( z )\n    -1.0\n\n\nComplex64Array.prototype.set( z[, i] )\n    Sets one or more array elements.\n\n    If provided a single argument, the method sets array elements starting at\n    position (index) `i = 0`. To set elements starting elsewhere in the array,\n    provide an index argument `i`.\n\n    To set one or more array elements, provide an array-like object containing\n    either complex numbers or interleaved real and imaginary components.\n\n    Parameters\n    ----------\n    z: Complex64|Complex64Array|ArrayLikeObject\n        Complex number or complex number array.\n\n    i: integer (optional)\n        Array index at which to start setting elements. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 2 )\n    <Complex64Array>\n    > arr.set( new Complex64( 1.0, -1.0 ) );\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    -1.0\n    > arr.set( new Complex64( 2.0, -2.0 ), 1 );\n    > z = arr.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    -2.0\n\n\nComplex64Array.prototype.slice( [start[, end]] )\n    Copies a portion of a typed array to a new typed array.\n\n    Parameters\n    ----------\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n    \n    Returns\n    -------\n    out: Complex64Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var out = arr.slice( 1 )\n    <Complex64Array>\n    > var len = out.length\n    2\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    -2.0\n    > z = out.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    -3.0\n\n\nComplex64Array.prototype.some( predicate[, thisArg] )\n    Returns a boolean indicating whether at least one element passes a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n    \n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one element passes the test.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var bool = arr.some( predicate )\n    true\n\n\nComplex64Array.prototype.sort( compareFunction )\n    Sorts an array in-place.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first element for comparison.\n    - b: second element for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFunction: Function\n        Comparison function.\n    \n    Returns\n    -------\n    out: Complex64Array\n        Modified array.\n    \n    Examples\n    --------\n    > function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\n    > var arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex64Array>\n    > arr.sort( compare );\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    -1.0\n    > z = arr.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    -2.0\n    > z = arr.get( 2 )\n    <Complex64>\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    -3.0\n\n\nComplex64Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array view over the same underlying `ArrayBuffer` and\n    with the same underlying data type as the host array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Complex64Array\n        New typed array view.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex64Array>\n    > var out = arr.subarray( 1, 3 )\n    <Complex64Array>\n    > var len = out.length\n    2\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    -2.0\n    > z = out.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    -3.0\n\n\nComplex64Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array (optional)\n        Locale identifier(s).\n    \n    options: Object (optional)\n        An object containing serialization options.\n    \n    Returns\n    -------\n    str: string\n        Local-specific string.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0 ] )\n    <Complex64Array>\n    > var str = arr.toLocaleString()\n    '1 + 1i,2 + 2i'\n\n\nComplex64Array.prototype.toReversed()\n    Returns a new typed array containing the elements in reversed order.\n\n    Returns\n    -------\n    out: Complex64Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\n    <Complex64Array>\n    > var out = arr.toReversed()\n    <Complex64Array>\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    3.0\n    > z = out.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    2.0\n    > z = out.get( 2 )\n    <Complex64>\n    > re = realf( z )\n    1.0\n    > im = imagf( z )\n    1.0\n\n\nComplex64Array.prototype.toSorted( compareFcn )\n    Returns a new typed array containing the elements in sorted order.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first element for comparison.\n    - b: second element for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFcn: Function\n        Comparison function.\n    \n    Returns\n    -------\n    out: Complex64Array\n        New typed array.\n    \n    Examples\n    --------\n    > function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\n    > var arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex64Array>\n    > var out = arr.toSorted( compare );\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    -1.0\n    > z = out.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    -2.0\n    > z = out.get( 2 )\n    <Complex64>\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    -3.0\n\n\nComplex64Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        String serialization of the array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\n    <Complex64Array>\n    > var str = arr.toString()\n    '1 + 1i,2 - 2i,3 + 3i'\n\n\nComplex64Array.prototype.values()\n    Returns an iterator for iterating over each value in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array values.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var it = arr.values();\n    > var v = it.next().value\n    <Complex64>\n    > var re = realf( v )\n    1.0\n    > var im = imagf( v )\n    -1.0\n    > v = it.next().value\n    <Complex64>\n    > re = realf( v )\n    2.0\n    > im = imagf( v )\n    -2.0\n    > var bool = it.next().done\n    true\n\n\nComplex64Array.prototype.with( index, value )\n    Returns a new typed array with the element at a provided index replaced\n    with a provided value.\n\n    Parameters\n    ----------\n    index: integer\n        Element index.\n    \n    value: Complex64\n        Element value.  \n\n    Returns\n    -------\n    out: Complex64Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n    <Complex64Array>\n    > var z = out.get( 1 )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    -3.0\n\n\n    See Also\n    --------\n    Complex128Array, complex, Complex64","Complex64Array.from":"\nComplex64Array.from( src[, clbk[, thisArg]] )\n    Creates a new 64-bit complex number array from an array-like object or an\n    iterable.\n\n    A callback function is provided two arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    clbk: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n    \n    Returns\n    -------\n    out: Complex64Array\n        A typed array.\n    \n    Examples\n    --------\n    > function clbkFcn( v ) { return v * 2.0 };\n    > var arr = Complex64Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\n    <Complex64Array>\n    > var len = arr.length\n    2\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    -2.0","Complex64Array.of":"\nComplex64Array.of( element0[, element1[, ...elementN]] )\n    Creates a new 64-bit complex number array from a variable number of\n    arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Complex64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Complex64Array.of( 1.0, -1.0, 2.0, -2.0 )\n    <Complex64Array>\n    > var len = arr.length\n    2\n    > var z1 = new Complex64( 1.0, -1.0 );\n    > var z2 = new Complex64( 2.0, -2.0 );\n    > arr = Complex64Array.of( z1, z2 )\n    <Complex64Array>\n    > len = arr.length\n    2\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    -1.0","Complex64Array.BYTES_PER_ELEMENT":"\nComplex64Array.BYTES_PER_ELEMENT\n    The size of each array element in bytes.\n\n    Examples\n    --------\n    > var nbytes = Complex64Array.BYTES_PER_ELEMENT\n    8","Complex64Array.name":"\nComplex64Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > var str = Complex64Array.name\n    'Complex64Array'","Complex64Array.prototype.buffer":"\nComplex64Array.prototype.buffer\n    Pointer to the underlying data buffer.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 2 )\n    <Complex64Array>\n    > var buf = arr.buffer\n    <ArrayBuffer>","Complex64Array.prototype.byteLength":"\nComplex64Array.prototype.byteLength\n    Length of the array in bytes.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 10 )\n    <Complex64Array>\n    > var nbytes = arr.byteLength\n    80","Complex64Array.prototype.byteOffset":"\nComplex64Array.prototype.byteOffset\n    Offset (in bytes) of the array from the start of its underlying\n    ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 5 )\n    <Complex64Array>\n    > var offset = arr.byteOffset\n    0\n    > var buf = new ArrayBuffer( 240 );\n    > arr = new Complex64Array( buf, 64 )\n    <Complex64Array>\n    > offset = arr.byteOffset\n    64","Complex64Array.prototype.BYTES_PER_ELEMENT":"\nComplex64Array.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 10 )\n    <Complex64Array>\n    > arr.BYTES_PER_ELEMENT\n    8","Complex64Array.prototype.length":"\nComplex64Array.prototype.length\n    The number of array elements.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 10 )\n    <Complex64Array>\n    > var len = arr.length\n    10","Complex64Array.prototype.at":"\nComplex64Array.prototype.at( i )\n    Returns an array element located at integer position (index) `i`, with\n    support for noth nonnegative and negative integer positions.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n\n    Returns\n    -------\n    out: Complex64|void\n        An array element.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var z = arr.at( 1 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    -2.0","Complex64Array.prototype.copyWithin":"\nComplex64Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n    \n    start: integer\n        Source start index position.\n    \n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Complex64Array\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex64Array>\n    > arr.copyWithin( 0, 2 )\n    <Complex64Array>\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    -3.0","Complex64Array.prototype.entries":"\nComplex64Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var it = arr.entries();\n    > var v = it.next().value\n    [ 0, <Complex64> ]\n    > var re = realf( v[ 1 ] )\n    1.0\n    > var im = imagf( v[ 1 ] )\n    -1.0\n    > v = it.next().value\n    [ 1, <Complex64> ]\n    > re = realf( v[ 1 ] )\n    2.0\n    > im = imagf( v[ 1 ] )\n    -2.0\n    > v = it.next().value\n    [ 2, <Complex64> ]\n    > re = realf( v[ 1 ] )\n    3.0\n    > im = imagf( v[ 1 ] )\n    -3.0\n    > var bool = it.next().done\n    true","Complex64Array.prototype.every":"\nComplex64Array.prototype.every( predicate[, thisArg] )\n    Returns a boolean indicating whether all elements in the array pass a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all elements pass the test.\n\n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) > 0.0 ); };\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var bool = arr.every( predicate )\n    true","Complex64Array.prototype.fill":"\nComplex64Array.prototype.fill( value[, start[, end]] )\n    Returns a modified typed array filled with a fill value.\n\n    Parameters\n    ----------\n    value: Complex64\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Complex64Array\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( 3 )\n    <Complex64Array>\n    > arr.fill( new Complex64( 1.0, 1.0 ) );\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    1.0\n    > z = arr.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    1.0\n    > im = imagf( z )\n    1.0\n    > z = arr.get( 2 )\n    <Complex64>\n    > re = realf( z )\n    1.0\n    > im = imagf( z )\n    1.0","Complex64Array.prototype.filter":"\nComplex64Array.prototype.filter( predicate[, thisArg] )\n    Returns a new array containing the elements of an array which pass a test\n    implemented by a predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Complex64Array\n        A new typed array.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var out = arr.filter( predicate )\n    <Complex64Array>\n    > var len = out.length\n    1\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    2.0","Complex64Array.prototype.find":"\nComplex64Array.prototype.find( predicate[, thisArg] )\n    Returns the first element in an array for which a predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    out: Complex64|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var z = arr.find( predicate )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    1.0","Complex64Array.prototype.findIndex":"\nComplex64Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var idx = arr.findIndex( predicate )\n    0","Complex64Array.prototype.findLast":"\nComplex64Array.prototype.findLast( predicate[, thisArg] )\n    Returns the last element in an array for which a predicate function returns\n    a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.  \n    \n    Returns\n    -------\n    out: Complex64|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var z = arr.findLast( predicate )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    2.0","Complex64Array.prototype.findLastIndex":"\nComplex64Array.prototype.findLastIndex( predicate[, thisArg] )\n    Returns the index of the last element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var idx = arr.findLastIndex( predicate )\n    1","Complex64Array.prototype.forEach":"\nComplex64Array.prototype.forEach( clbk[, thisArg] )\n    Invokes a function once for each array element.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Examples\n    --------\n    > var str = '%';\n    > function clbk( v ) { str += v.toString() + '%'; };\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > arr.forEach( clbk );\n    > str\n    '%1 - 1i%2 - 2i%'","Complex64Array.prototype.get":"\nComplex64Array.prototype.get( i )\n    Returns an array element located at integer position (index) `i`.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n    \n    Returns\n    -------\n    out: Complex64|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var z = arr.get( 1 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    -2.0","Complex64Array.prototype.includes":"\nComplex64Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a provided value.\n\n    Parameters\n    ----------\n    searchElement: Complex64\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n    \n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex64Array>\n    > var bool = arr.includes( new Complex64( 3.0, -3.0 ) )\n    true\n    > bool = arr.includes( new Complex64( 3.0, -3.0 ), 3 )\n    false","Complex64Array.prototype.indexOf":"\nComplex64Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the first index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: Complex64\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex64Array>\n    > var idx = arr.indexOf( new Complex64( 3.0, -3.0 ) )\n    2\n    > idx = arr.indexOf( new Complex64( 3.0, -3.0 ), 3 )\n    -1","Complex64Array.prototype.join":"\nComplex64Array.prototype.join( [separator] )\n    Returns a new string by concatenating all array elements separated by a\n    separator string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        Separator string. Default: ','.\n    \n    Returns\n    -------\n    out: string\n        Array serialized as a string.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var str = arr.join()\n    '1 - 1i,2 - 2i'\n    > str = arr.join( '/' )\n    '1 - 1i/2 - 2i'","Complex64Array.prototype.keys":"\nComplex64Array.prototype.keys()\n    Returns an iterator for iterating over each index key in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array index keys.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var it = arr.keys();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().done\n    true","Complex64Array.prototype.lastIndexOf":"\nComplex64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the last index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: Complex64\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: out.length-1.\n    \n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex64Array>\n    > var idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ) )\n    3\n    > idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ), 2 )\n    0","Complex64Array.prototype.map":"\nComplex64Array.prototype.map( clbk[, thisArg] )\n    Returns a new array with each element being the result of a provided\n    callback function.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Complex64Array\n        A new typed array.\n    \n    Examples\n    --------\n    > function clbk( v ) { return v; };\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var out = arr.map( clbk )\n    <Complex64Array>\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    -1.0\n    > z = out.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    -2.0","Complex64Array.prototype.reduce":"\nComplex64Array.prototype.reduce( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in order, passing\n    in the return value from the calculation on the preceding element and\n    returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.    \n\n    initialValue: any (optional)\n        Initial accumulation value.\n    \n    Returns\n    -------\n    out: any\n        Accumulated result.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var z = arr.reduce( base.caddf )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    -3.0","Complex64Array.prototype.reduceRight":"\nComplex64Array.prototype.reduceRight( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in reverse order,\n    passing in the return value from the calculation on the preceding element\n    and returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.\n\n    initialValue: any (optional)\n        Initial accumulation value.\n    \n    Returns\n    -------\n    out: any\n        Accumulated result.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var z = arr.reduceRight( base.caddf )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    -3.0","Complex64Array.prototype.reverse":"\nComplex64Array.prototype.reverse()\n    Reverses the array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Complex64Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > arr.reverse();\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    -3.0\n    > z = arr.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    -2.0\n    > z = arr.get( 2 )\n    <Complex64>\n    > re = realf( z )\n    1.0\n    > im = imagf( z )\n    -1.0","Complex64Array.prototype.set":"\nComplex64Array.prototype.set( z[, i] )\n    Sets one or more array elements.\n\n    If provided a single argument, the method sets array elements starting at\n    position (index) `i = 0`. To set elements starting elsewhere in the array,\n    provide an index argument `i`.\n\n    To set one or more array elements, provide an array-like object containing\n    either complex numbers or interleaved real and imaginary components.\n\n    Parameters\n    ----------\n    z: Complex64|Complex64Array|ArrayLikeObject\n        Complex number or complex number array.\n\n    i: integer (optional)\n        Array index at which to start setting elements. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 2 )\n    <Complex64Array>\n    > arr.set( new Complex64( 1.0, -1.0 ) );\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    -1.0\n    > arr.set( new Complex64( 2.0, -2.0 ), 1 );\n    > z = arr.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    -2.0","Complex64Array.prototype.slice":"\nComplex64Array.prototype.slice( [start[, end]] )\n    Copies a portion of a typed array to a new typed array.\n\n    Parameters\n    ----------\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n    \n    Returns\n    -------\n    out: Complex64Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var out = arr.slice( 1 )\n    <Complex64Array>\n    > var len = out.length\n    2\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    -2.0\n    > z = out.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    -3.0","Complex64Array.prototype.some":"\nComplex64Array.prototype.some( predicate[, thisArg] )\n    Returns a boolean indicating whether at least one element passes a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n    \n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one element passes the test.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var bool = arr.some( predicate )\n    true","Complex64Array.prototype.sort":"\nComplex64Array.prototype.sort( compareFunction )\n    Sorts an array in-place.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first element for comparison.\n    - b: second element for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFunction: Function\n        Comparison function.\n    \n    Returns\n    -------\n    out: Complex64Array\n        Modified array.\n    \n    Examples\n    --------\n    > function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\n    > var arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex64Array>\n    > arr.sort( compare );\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    -1.0\n    > z = arr.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    -2.0\n    > z = arr.get( 2 )\n    <Complex64>\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    -3.0","Complex64Array.prototype.subarray":"\nComplex64Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array view over the same underlying `ArrayBuffer` and\n    with the same underlying data type as the host array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Complex64Array\n        New typed array view.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex64Array>\n    > var out = arr.subarray( 1, 3 )\n    <Complex64Array>\n    > var len = out.length\n    2\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    -2.0\n    > z = out.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    -3.0","Complex64Array.prototype.toLocaleString":"\nComplex64Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array (optional)\n        Locale identifier(s).\n    \n    options: Object (optional)\n        An object containing serialization options.\n    \n    Returns\n    -------\n    str: string\n        Local-specific string.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0 ] )\n    <Complex64Array>\n    > var str = arr.toLocaleString()\n    '1 + 1i,2 + 2i'","Complex64Array.prototype.toReversed":"\nComplex64Array.prototype.toReversed()\n    Returns a new typed array containing the elements in reversed order.\n\n    Returns\n    -------\n    out: Complex64Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\n    <Complex64Array>\n    > var out = arr.toReversed()\n    <Complex64Array>\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    3.0\n    > z = out.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    2.0\n    > z = out.get( 2 )\n    <Complex64>\n    > re = realf( z )\n    1.0\n    > im = imagf( z )\n    1.0","Complex64Array.prototype.toSorted":"\nComplex64Array.prototype.toSorted( compareFcn )\n    Returns a new typed array containing the elements in sorted order.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first element for comparison.\n    - b: second element for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFcn: Function\n        Comparison function.\n    \n    Returns\n    -------\n    out: Complex64Array\n        New typed array.\n    \n    Examples\n    --------\n    > function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\n    > var arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex64Array>\n    > var out = arr.toSorted( compare );\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    -1.0\n    > z = out.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    -2.0\n    > z = out.get( 2 )\n    <Complex64>\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    -3.0","Complex64Array.prototype.toString":"\nComplex64Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        String serialization of the array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\n    <Complex64Array>\n    > var str = arr.toString()\n    '1 + 1i,2 - 2i,3 + 3i'","Complex64Array.prototype.values":"\nComplex64Array.prototype.values()\n    Returns an iterator for iterating over each value in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array values.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var it = arr.values();\n    > var v = it.next().value\n    <Complex64>\n    > var re = realf( v )\n    1.0\n    > var im = imagf( v )\n    -1.0\n    > v = it.next().value\n    <Complex64>\n    > re = realf( v )\n    2.0\n    > im = imagf( v )\n    -2.0\n    > var bool = it.next().done\n    true","Complex64Array.prototype.with":"\nComplex64Array.prototype.with( index, value )\n    Returns a new typed array with the element at a provided index replaced\n    with a provided value.\n\n    Parameters\n    ----------\n    index: integer\n        Element index.\n    \n    value: Complex64\n        Element value.  \n\n    Returns\n    -------\n    out: Complex64Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n    <Complex64Array>\n    > var z = out.get( 1 )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    -3.0\n\n\n    See Also\n    --------\n    Complex128Array, complex, Complex64","Complex128":"\nComplex128( real, imag )\n    128-bit complex number constructor.\n\n    Both the real and imaginary components are stored as double-precision\n    floating-point numbers.\n\n    Parameters\n    ----------\n    real: number\n        Real component.\n\n    imag: number\n        Imaginary component.\n\n    Returns\n    -------\n    z: Complex128\n        128-bit complex number.\n\n    z.re: number\n        Read-only property returning the real component.\n\n    z.im: number\n        Read-only property returning the imaginary component.\n\n\nComplex128.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n\n    Returns\n    -------\n    v: integer\n        Size (in bytes) of each component.\n\n    Examples\n    --------\n    > var s = Complex128.BYTES_PER_ELEMENT\n    8\n\n\nComplex128.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n\n    Returns\n    -------\n    s: integer\n        Size (in bytes) of each component.\n\n    Examples\n    --------\n    > var z = new Complex128( 5.0, 3.0 )\n    <Complex128>\n    > var s = z.BYTES_PER_ELEMENT\n    8\n\n\nComplex128.prototype.byteLength\n    Length (in bytes) of a complex number.\n\n    Returns\n    -------\n    len: integer\n        Length (in bytes) of a complex number.\n\n    Examples\n    --------\n    > var z = new Complex128( 5.0, 3.0 )\n    <Complex128>\n    > var s = z.byteLength\n    16\n\n    See Also\n    --------\n    complex, Complex64\n","Complex128.BYTES_PER_ELEMENT":"\nComplex128.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n\n    Returns\n    -------\n    v: integer\n        Size (in bytes) of each component.\n\n    Examples\n    --------\n    > var s = Complex128.BYTES_PER_ELEMENT\n    8","Complex128.prototype.BYTES_PER_ELEMENT":"\nComplex128.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n\n    Returns\n    -------\n    s: integer\n        Size (in bytes) of each component.\n\n    Examples\n    --------\n    > var z = new Complex128( 5.0, 3.0 )\n    <Complex128>\n    > var s = z.BYTES_PER_ELEMENT\n    8","Complex128.prototype.byteLength":"\nComplex128.prototype.byteLength\n    Length (in bytes) of a complex number.\n\n    Returns\n    -------\n    len: integer\n        Length (in bytes) of a complex number.\n\n    Examples\n    --------\n    > var z = new Complex128( 5.0, 3.0 )\n    <Complex128>\n    > var s = z.byteLength\n    16\n\n    See Also\n    --------\n    complex, Complex64","COMPLEX128_NAN":"\nCOMPLEX128_NAN\n    Canonical double-precision complex floating-point NaN.\n\n    Examples\n    --------\n    > COMPLEX128_NAN\n    <Complex128>\n\n    See Also\n    --------\n    COMPLEX64_NAN\n","COMPLEX128_NUM_BYTES":"\nCOMPLEX128_NUM_BYTES\n    Size (in bytes) of a 128-bit complex number.\n\n    Examples\n    --------\n    > COMPLEX128_NUM_BYTES\n    16\n\n    See Also\n    --------\n    COMPLEX64_NUM_BYTES, FLOAT64_NUM_BYTES\n","COMPLEX128_ZERO":"\nCOMPLEX128_ZERO\n    Double-precision complex floating-point zero.\n\n    Examples\n    --------\n    > COMPLEX128_ZERO\n    <Complex128>\n\n    See Also\n    --------\n    COMPLEX64_ZERO\n","Complex128Array":"\nComplex128Array()\n    A 128-bit complex number array.\n\n    Returns\n    -------\n    out: Complex128Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Complex128Array()\n    <Complex128Array>\n\n\nComplex128Array( length )\n    Creates a 128-bit complex number array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: Complex128Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 10 )\n    <Complex128Array>\n    > var len = arr.length\n    10\n\n\nComplex128Array( complexarray )\n    Creates a 64-bit complex number array from another complex number array.\n\n    Parameters\n    ----------\n    complexarray: Complex128Array\n        Complex array from which to generate another complex array.\n\n    Returns\n    -------\n    out: Complex128Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var arr2 = new Complex128Array( arr1 )\n    <Complex128Array>\n    > var len = arr2.length\n    2\n\n\nComplex128Array( typedarray )\n    Creates a 128-bit complex number array from a typed array\n    containing interleaved real and imaginary components.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate a complex array.\n\n    Returns\n    -------\n    out: Complex128Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new Float64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Float64Array>\n    > var arr = new Complex128Array( buf )\n    <Complex128Array>\n    > var len = arr.length\n    2\n\n\nComplex128Array( obj )\n    Creates a 128-bit complex number array from an array-like object or \n    iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a complex array.\n\n    Returns\n    -------\n    out: Complex128Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var len = arr1.length\n    2\n    > var buf = [ new Complex128( 1.0, -1.0 ), new Complex128( 2.0, -2.0 ) ];\n    > var arr2 = new Complex128Array( buf )\n    <Complex128Array>\n    > len = arr2.length\n    2\n\n\nComplex128Array( buffer[, byteOffset[, length]] )\n    Returns a 128-bit complex number array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Complex128Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 480 );\n    > var arr1 = new Complex128Array( buf )\n    <Complex128Array>\n    > var len = arr1.length\n    30\n    > var arr2 = new Complex128Array( buf, 16 )\n    <Complex128Array>\n    > len = arr2.length\n    29\n    > var arr3 = new Complex128Array( buf, 16, 20 )\n    <Complex128Array>\n    > len = arr3.length\n    20\n\n\nComplex128Array.from( src[, clbk[, thisArg]] )\n    Creates a new 128-bit complex number array from an array-like object or an\n    iterable.\n\n    A callback function is provided two arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    clbk: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n    \n    Returns\n    -------\n    out: Complex128Array\n        A typed array.\n    \n    Examples\n    --------\n    > function clbkFcn( v ) { return v * 2.0 };\n    > var arr = Complex128Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\n    <Complex128Array>\n    > var len = arr.length\n    2\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    -2.0\n\n\nComplex128Array.of( element0[, element1[, ...elementN]] )\n    Creates a new 128-bit complex number array from a variable number of\n    arguments.\n\n    Parameters\n    ----------\n    element0: number|ComplexLike\n        Array element.\n\n    element1: number |ComplexLike(optional)\n        Array element.\n\n    elementN: ...number|ComplexLike (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Complex128Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Complex128Array.of( 1.0, -1.0, 2.0, -2.0 )\n    <Complex128Array>\n    > var len = arr.length\n    2\n    > var z1 = new Complex128( 1.0, -1.0 );\n    > var z2 = new Complex128( 2.0, -2.0 );\n    > arr = Complex128Array.of( z1, z2 )\n    <Complex128Array>\n    > len = arr.length\n    2\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    -1.0\n\n\nComplex128Array.BYTES_PER_ELEMENT\n    The size of each array element in bytes.\n\n    Examples\n    --------\n    > var nbytes = Complex128Array.BYTES_PER_ELEMENT\n    16\n\n\nComplex128Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > var str = Complex128Array.name\n    'Complex128Array'\n\n\nComplex128Array.prototype.buffer\n    Pointer to the underlying data buffer.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 2 )\n    <Complex128Array>\n    > var buf = arr.buffer\n    <ArrayBuffer>\n\n\nComplex128Array.prototype.byteLength\n    Length of the array in bytes.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 10 )\n    <Complex128Array>\n    > var nbytes = arr.byteLength\n    160\n\n\nComplex128Array.prototype.byteOffset\n    Offset (in bytes) of the array from the start of its underlying\n    ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 10 )\n    <Complex128Array>\n    > var offset = arr.byteOffset\n    0\n    > var buf = new ArrayBuffer( 480 );\n    > arr = new Complex128Array( buf, 128 )\n    <Complex128Array>\n    > offset = arr.byteOffset\n    128\n\n\nComplex128Array.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 10 )\n    <Complex128Array>\n    > arr.BYTES_PER_ELEMENT\n    16\n\n\nComplex128Array.prototype.length\n    The number of array elements.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 10 )\n    <Complex128Array>\n    > var len = arr.length\n    10\n\n\nComplex128Array.prototype.at( i )\n    Returns an array element located at integer position (index) `i`, with\n    support for both nonnegative and negative integer positions.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n\n    Returns\n    -------\n    out: Complex128|void\n        An array element.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var z = arr.at( 1 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    -2.0\n\n\nComplex128Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n    \n    start: integer\n        Source start index position.\n    \n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Complex128Array\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex128Array>\n    > arr.copyWithin( 0, 2 )\n    <Complex128Array>\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    -3.0\n\n\nComplex128Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var it = arr.entries();\n    > var v = it.next().value\n    [ 0, <Complex128> ]\n    > var re = real( v[ 1 ] )\n    1.0\n    > var im = imag( v[ 1 ] )\n    -1.0\n    > v = it.next().value\n    [ 1, <Complex128> ]\n    > re = real( v[ 1 ] )\n    2.0\n    > im = imag( v[ 1 ] )\n    -2.0\n    > v = it.next().value\n    [ 2, <Complex128> ]\n    > re = real( v[ 1 ] )\n    3.0\n    > im = imag( v[ 1 ] )\n    -3.0\n    > var bool = it.next().done\n    true\n\n\nComplex128Array.prototype.every( predicate[, thisArg] )\n    Returns a boolean indicating whether all elements in the array pass a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all elements pass the test.\n\n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) > 0.0 ); };\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var bool = arr.every( predicate )\n    true\n\n\nComplex128Array.prototype.fill( value[, start[, end]] )\n    Returns a modified typed array filled with a fill value.\n\n    Parameters\n    ----------\n    value: Complex128\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Complex128Array\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( 3 )\n    <Complex128Array>\n    > arr.fill( new Complex128( 1.0, 1.0 ) );\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    1.0\n    > z = arr.get( 1 )\n    <Complex128>\n    > re = real( z )\n    1.0\n    > im = imag( z )\n    1.0\n    > z = arr.get( 2 )\n    <Complex128>\n    > re = real( z )\n    1.0\n    > im = imag( z )\n    1.0\n\n\nComplex128Array.prototype.filter( predicate[, thisArg] )\n    Returns a new array containing the elements of an array which pass a test\n    implemented by a predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Complex128Array\n        A new typed array.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var out = arr.filter( predicate )\n    <Complex128Array>\n    > var len = out.length\n    1\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    2.0\n\n\nComplex128Array.prototype.find( predicate[, thisArg] )\n    Returns the first element in an array for which a predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    out: Complex128|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var z = arr.find( predicate )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    1.0\n\n\nComplex128Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var idx = arr.findIndex( predicate )\n    0\n\n\nComplex128Array.prototype.findLast( predicate[, thisArg] )\n    Returns the last element in an array for which a predicate function returns\n    a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.  \n    \n    Returns\n    -------\n    out: Complex128|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var z = arr.findLast( predicate )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    2.0\n\n\nComplex128Array.prototype.findLastIndex( predicate[, thisArg] )\n    Returns the index of the last element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var idx = arr.findLastIndex( predicate )\n    1\n\n\nComplex128Array.prototype.forEach( clbk[, thisArg] )\n    Invokes a function once for each array element.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Examples\n    --------\n    > var str = '%';\n    > function clbk( v ) { str += v.toString() + '%'; };\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > arr.forEach( clbk );\n    > str\n    '%1 - 1i%2 - 2i%'\n\n\nComplex128Array.prototype.get( i )\n    Returns an array element located at integer position (index) `i`.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n    \n    Returns\n    -------\n    out: Complex128|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var z = arr.get( 1 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    -2.0\n\n\nComplex128Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a provided value.\n\n    Parameters\n    ----------\n    searchElement: Complex128\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n    \n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex128Array>\n    > var bool = arr.includes( new Complex128( 3.0, -3.0 ) )\n    true\n    > bool = arr.includes( new Complex128( 3.0, -3.0 ), 3 )\n    false\n\n\nComplex128Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the first index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: Complex128\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex128Array>\n    > var idx = arr.indexOf( new Complex128( 3.0, -3.0 ) )\n    2\n    > idx = arr.indexOf( new Complex128( 3.0, -3.0 ), 3 )\n    -1\n\n\nComplex128Array.prototype.join( [separator] )\n    Returns a new string by concatenating all array elements separated by a\n    separator string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        Separator string. Default: ','.\n    \n    Returns\n    -------\n    out: string\n        Array serialized as a string.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var str = arr.join()\n    '1 - 1i,2 - 2i'\n    > str = arr.join( '/' )\n    '1 - 1i/2 - 2i'\n\n\nComplex128Array.prototype.keys()\n    Returns an iterator for iterating over each index key in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array index keys.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var it = arr.keys();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().done\n    true\n\n\nComplex128Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the last index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: Complex128\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: out.length-1.\n    \n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex128Array>\n    > var idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ) )\n    3\n    > idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ), 2 )\n    0\n\n\nComplex128Array.prototype.map( clbk[, thisArg] )\n    Returns a new array with each element being the result of a provided\n    callback function.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Complex128Array\n        A new typed array.\n    \n    Examples\n    --------\n    > function clbk( v ) { return v; };\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var out = arr.map( clbk )\n    <Complex128Array>\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    -1.0\n    > z = out.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    -2.0\n\n\nComplex128Array.prototype.reduce( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in order, passing\n    in the return value from the calculation on the preceding element and\n    returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.    \n\n    initialValue: any (optional)\n        Initial accumulation value.\n    \n    Returns\n    -------\n    out: any\n        Accumulated result.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var z = arr.reduce( base.cadd )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    -3.0\n\n\nComplex128Array.prototype.reduceRight( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in reverse order,\n    passing in the return value from the calculation on the preceding element\n    and returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.\n\n    initialValue: any (optional)\n        Initial accumulation value.\n    \n    Returns\n    -------\n    out: any\n        Accumulated result.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var z = arr.reduceRight( base.cadd )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    -3.0\n\n\nComplex128Array.prototype.reverse()\n    Reverses the array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Complex128Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > arr.reverse();\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    -3.0\n    > z = arr.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    -2.0\n    > z = arr.get( 2 )\n    <Complex128>\n    > re = real( z )\n    1.0\n    > im = imag( z )\n    -1.0\n\n\nComplex128Array.prototype.set( z[, i] )\n    Sets one or more array elements.\n\n    If provided a single argument, the method sets array elements starting at\n    position (index) `i = 0`. To set elements starting elsewhere in the array,\n    provide an index argument `i`.\n\n    To set one or more array elements, provide an array-like object containing\n    either complex numbers or interleaved real and imaginary components.\n\n    Parameters\n    ----------\n    z: Complex128|Complex128Array|ArrayLikeObject\n        Complex number or complex number array.\n\n    i: integer (optional)\n        Array index at which to start setting elements. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 2 )\n    <Complex128Array>\n    > arr.set( new Complex128( 1.0, -1.0 ) );\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    -1.0\n    > arr.set( new Complex128( 2.0, -2.0 ), 1 );\n    > z = arr.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    -2.0\n\n\nComplex128Array.prototype.slice( [start[, end]] )\n    Copies a portion of a typed array to a new typed array.\n\n    Parameters\n    ----------\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n    \n    Returns\n    -------\n    out: Complex128Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var out = arr.slice( 1 )\n    <Complex128Array>\n    > var len = out.length\n    2\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    -2.0\n    > z = out.get( 1 )\n    <Complex128>\n    > re = real( z )\n    3.0\n    > im = imag( z )\n    -3.0\n\n\nComplex128Array.prototype.some( predicate[, thisArg] )\n    Returns a boolean indicating whether at least one element passes a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n    \n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one element passes the test.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var bool = arr.some( predicate )\n    true\n\n\nComplex128Array.prototype.sort( compareFunction )\n    Sorts an array in-place.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first element for comparison.\n    - b: second element for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFunction: Function\n        Comparison function.\n    \n    Returns\n    -------\n    out: Complex128Array\n        Modified array.\n    \n    Examples\n    --------\n    > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n    > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex128Array>\n    > arr.sort( compare );\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    -1.0\n    > z = arr.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    -2.0\n    > z = arr.get( 2 )\n    <Complex128>\n    > re = real( z )\n    3.0\n    > im = imag( z )\n    -3.0\n\n\nComplex128Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array view over the same underlying `ArrayBuffer` and\n    with the same underlying data type as the host array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Complex128Array\n        New typed array view.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex128Array>\n    > var out = arr.subarray( 1, 3 )\n    <Complex128Array>\n    > var len = out.length\n    2\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    -2.0\n    > z = out.get( 1 )\n    <Complex128>\n    > re = real( z )\n    3.0\n    > im = imag( z )\n    -3.0\n\n\nComplex128Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array (optional)\n        Locale identifier(s).\n    \n    options: Object (optional)\n        An object containing serialization options.\n    \n    Returns\n    -------\n    str: string\n        Local-specific string.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0 ] )\n    <Complex128Array>\n    > var str = arr.toLocaleString()\n    '1 + 1i,2 + 2i'\n\n\nComplex128Array.prototype.toReversed()\n    Returns a new typed array containing the elements in reversed order.\n\n    Returns\n    -------\n    out: Complex128Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\n    <Complex128Array>\n    > var out = arr.toReversed()\n    <Complex128Array>\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    3.0\n    > z = out.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    2.0\n    > z = out.get( 2 )\n    <Complex128>\n    > re = real( z )\n    1.0\n    > im = imag( z )\n    1.0\n\n\nComplex128Array.prototype.toSorted( compareFcn )\n    Returns a new typed array containing the elements in sorted order.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first element for comparison.\n    - b: second element for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFcn: Function\n        Comparison function.\n    \n    Returns\n    -------\n    out: Complex128Array\n        New typed array.\n    \n    Examples\n    --------\n    > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n    > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex128Array>\n    > var out = arr.toSorted( compare );\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    -1.0\n    > z = out.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    -2.0\n    > z = out.get( 2 )\n    <Complex128>\n    > re = real( z )\n    3.0\n    > im = imag( z )\n    -3.0\n\n\nComplex128Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        String serialization of the array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\n    <Complex128Array>\n    > var str = arr.toString()\n    '1 + 1i,2 - 2i,3 + 3i'\n\n\nComplex128Array.prototype.values()\n    Returns an iterator for iterating over each value in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array values.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var it = arr.values();\n    > var v = it.next().value\n    <Complex128>\n    > var re = real( v )\n    1.0\n    > var im = imag( v )\n    -1.0\n    > v = it.next().value\n    <Complex128>\n    > re = real( v )\n    2.0\n    > im = imag( v )\n    -2.0\n    > var bool = it.next().done\n    true\n\n\nComplex128Array.prototype.with( index, value )\n    Returns a new typed array with the element at a provided index replaced\n    with a provided value.\n\n    Parameters\n    ----------\n    index: integer\n        Element index.\n    \n    value: Complex128\n        Element value.  \n\n    Returns\n    -------\n    out: Complex128Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n    <Complex128Array>\n    > var z = out.get( 1 )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    -3.0\n\n\n    See Also\n    --------\n    Complex64Array, complex, Complex128","Complex128Array.from":"\nComplex128Array.from( src[, clbk[, thisArg]] )\n    Creates a new 128-bit complex number array from an array-like object or an\n    iterable.\n\n    A callback function is provided two arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    clbk: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n    \n    Returns\n    -------\n    out: Complex128Array\n        A typed array.\n    \n    Examples\n    --------\n    > function clbkFcn( v ) { return v * 2.0 };\n    > var arr = Complex128Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\n    <Complex128Array>\n    > var len = arr.length\n    2\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    -2.0","Complex128Array.of":"\nComplex128Array.of( element0[, element1[, ...elementN]] )\n    Creates a new 128-bit complex number array from a variable number of\n    arguments.\n\n    Parameters\n    ----------\n    element0: number|ComplexLike\n        Array element.\n\n    element1: number |ComplexLike(optional)\n        Array element.\n\n    elementN: ...number|ComplexLike (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Complex128Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Complex128Array.of( 1.0, -1.0, 2.0, -2.0 )\n    <Complex128Array>\n    > var len = arr.length\n    2\n    > var z1 = new Complex128( 1.0, -1.0 );\n    > var z2 = new Complex128( 2.0, -2.0 );\n    > arr = Complex128Array.of( z1, z2 )\n    <Complex128Array>\n    > len = arr.length\n    2\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    -1.0","Complex128Array.BYTES_PER_ELEMENT":"\nComplex128Array.BYTES_PER_ELEMENT\n    The size of each array element in bytes.\n\n    Examples\n    --------\n    > var nbytes = Complex128Array.BYTES_PER_ELEMENT\n    16","Complex128Array.name":"\nComplex128Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > var str = Complex128Array.name\n    'Complex128Array'","Complex128Array.prototype.buffer":"\nComplex128Array.prototype.buffer\n    Pointer to the underlying data buffer.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 2 )\n    <Complex128Array>\n    > var buf = arr.buffer\n    <ArrayBuffer>","Complex128Array.prototype.byteLength":"\nComplex128Array.prototype.byteLength\n    Length of the array in bytes.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 10 )\n    <Complex128Array>\n    > var nbytes = arr.byteLength\n    160","Complex128Array.prototype.byteOffset":"\nComplex128Array.prototype.byteOffset\n    Offset (in bytes) of the array from the start of its underlying\n    ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 10 )\n    <Complex128Array>\n    > var offset = arr.byteOffset\n    0\n    > var buf = new ArrayBuffer( 480 );\n    > arr = new Complex128Array( buf, 128 )\n    <Complex128Array>\n    > offset = arr.byteOffset\n    128","Complex128Array.prototype.BYTES_PER_ELEMENT":"\nComplex128Array.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 10 )\n    <Complex128Array>\n    > arr.BYTES_PER_ELEMENT\n    16","Complex128Array.prototype.length":"\nComplex128Array.prototype.length\n    The number of array elements.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 10 )\n    <Complex128Array>\n    > var len = arr.length\n    10","Complex128Array.prototype.at":"\nComplex128Array.prototype.at( i )\n    Returns an array element located at integer position (index) `i`, with\n    support for both nonnegative and negative integer positions.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n\n    Returns\n    -------\n    out: Complex128|void\n        An array element.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var z = arr.at( 1 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    -2.0","Complex128Array.prototype.copyWithin":"\nComplex128Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n    \n    start: integer\n        Source start index position.\n    \n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Complex128Array\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex128Array>\n    > arr.copyWithin( 0, 2 )\n    <Complex128Array>\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    -3.0","Complex128Array.prototype.entries":"\nComplex128Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var it = arr.entries();\n    > var v = it.next().value\n    [ 0, <Complex128> ]\n    > var re = real( v[ 1 ] )\n    1.0\n    > var im = imag( v[ 1 ] )\n    -1.0\n    > v = it.next().value\n    [ 1, <Complex128> ]\n    > re = real( v[ 1 ] )\n    2.0\n    > im = imag( v[ 1 ] )\n    -2.0\n    > v = it.next().value\n    [ 2, <Complex128> ]\n    > re = real( v[ 1 ] )\n    3.0\n    > im = imag( v[ 1 ] )\n    -3.0\n    > var bool = it.next().done\n    true","Complex128Array.prototype.every":"\nComplex128Array.prototype.every( predicate[, thisArg] )\n    Returns a boolean indicating whether all elements in the array pass a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all elements pass the test.\n\n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) > 0.0 ); };\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var bool = arr.every( predicate )\n    true","Complex128Array.prototype.fill":"\nComplex128Array.prototype.fill( value[, start[, end]] )\n    Returns a modified typed array filled with a fill value.\n\n    Parameters\n    ----------\n    value: Complex128\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Complex128Array\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( 3 )\n    <Complex128Array>\n    > arr.fill( new Complex128( 1.0, 1.0 ) );\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    1.0\n    > z = arr.get( 1 )\n    <Complex128>\n    > re = real( z )\n    1.0\n    > im = imag( z )\n    1.0\n    > z = arr.get( 2 )\n    <Complex128>\n    > re = real( z )\n    1.0\n    > im = imag( z )\n    1.0","Complex128Array.prototype.filter":"\nComplex128Array.prototype.filter( predicate[, thisArg] )\n    Returns a new array containing the elements of an array which pass a test\n    implemented by a predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Complex128Array\n        A new typed array.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var out = arr.filter( predicate )\n    <Complex128Array>\n    > var len = out.length\n    1\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    2.0","Complex128Array.prototype.find":"\nComplex128Array.prototype.find( predicate[, thisArg] )\n    Returns the first element in an array for which a predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    out: Complex128|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var z = arr.find( predicate )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    1.0","Complex128Array.prototype.findIndex":"\nComplex128Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var idx = arr.findIndex( predicate )\n    0","Complex128Array.prototype.findLast":"\nComplex128Array.prototype.findLast( predicate[, thisArg] )\n    Returns the last element in an array for which a predicate function returns\n    a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.  \n    \n    Returns\n    -------\n    out: Complex128|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var z = arr.findLast( predicate )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    2.0","Complex128Array.prototype.findLastIndex":"\nComplex128Array.prototype.findLastIndex( predicate[, thisArg] )\n    Returns the index of the last element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var idx = arr.findLastIndex( predicate )\n    1","Complex128Array.prototype.forEach":"\nComplex128Array.prototype.forEach( clbk[, thisArg] )\n    Invokes a function once for each array element.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Examples\n    --------\n    > var str = '%';\n    > function clbk( v ) { str += v.toString() + '%'; };\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > arr.forEach( clbk );\n    > str\n    '%1 - 1i%2 - 2i%'","Complex128Array.prototype.get":"\nComplex128Array.prototype.get( i )\n    Returns an array element located at integer position (index) `i`.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n    \n    Returns\n    -------\n    out: Complex128|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var z = arr.get( 1 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    -2.0","Complex128Array.prototype.includes":"\nComplex128Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a provided value.\n\n    Parameters\n    ----------\n    searchElement: Complex128\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n    \n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex128Array>\n    > var bool = arr.includes( new Complex128( 3.0, -3.0 ) )\n    true\n    > bool = arr.includes( new Complex128( 3.0, -3.0 ), 3 )\n    false","Complex128Array.prototype.indexOf":"\nComplex128Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the first index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: Complex128\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex128Array>\n    > var idx = arr.indexOf( new Complex128( 3.0, -3.0 ) )\n    2\n    > idx = arr.indexOf( new Complex128( 3.0, -3.0 ), 3 )\n    -1","Complex128Array.prototype.join":"\nComplex128Array.prototype.join( [separator] )\n    Returns a new string by concatenating all array elements separated by a\n    separator string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        Separator string. Default: ','.\n    \n    Returns\n    -------\n    out: string\n        Array serialized as a string.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var str = arr.join()\n    '1 - 1i,2 - 2i'\n    > str = arr.join( '/' )\n    '1 - 1i/2 - 2i'","Complex128Array.prototype.keys":"\nComplex128Array.prototype.keys()\n    Returns an iterator for iterating over each index key in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array index keys.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var it = arr.keys();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().done\n    true","Complex128Array.prototype.lastIndexOf":"\nComplex128Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the last index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: Complex128\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: out.length-1.\n    \n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex128Array>\n    > var idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ) )\n    3\n    > idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ), 2 )\n    0","Complex128Array.prototype.map":"\nComplex128Array.prototype.map( clbk[, thisArg] )\n    Returns a new array with each element being the result of a provided\n    callback function.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Complex128Array\n        A new typed array.\n    \n    Examples\n    --------\n    > function clbk( v ) { return v; };\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var out = arr.map( clbk )\n    <Complex128Array>\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    -1.0\n    > z = out.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    -2.0","Complex128Array.prototype.reduce":"\nComplex128Array.prototype.reduce( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in order, passing\n    in the return value from the calculation on the preceding element and\n    returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.    \n\n    initialValue: any (optional)\n        Initial accumulation value.\n    \n    Returns\n    -------\n    out: any\n        Accumulated result.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var z = arr.reduce( base.cadd )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    -3.0","Complex128Array.prototype.reduceRight":"\nComplex128Array.prototype.reduceRight( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in reverse order,\n    passing in the return value from the calculation on the preceding element\n    and returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.\n\n    initialValue: any (optional)\n        Initial accumulation value.\n    \n    Returns\n    -------\n    out: any\n        Accumulated result.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var z = arr.reduceRight( base.cadd )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    -3.0","Complex128Array.prototype.reverse":"\nComplex128Array.prototype.reverse()\n    Reverses the array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Complex128Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > arr.reverse();\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    -3.0\n    > z = arr.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    -2.0\n    > z = arr.get( 2 )\n    <Complex128>\n    > re = real( z )\n    1.0\n    > im = imag( z )\n    -1.0","Complex128Array.prototype.set":"\nComplex128Array.prototype.set( z[, i] )\n    Sets one or more array elements.\n\n    If provided a single argument, the method sets array elements starting at\n    position (index) `i = 0`. To set elements starting elsewhere in the array,\n    provide an index argument `i`.\n\n    To set one or more array elements, provide an array-like object containing\n    either complex numbers or interleaved real and imaginary components.\n\n    Parameters\n    ----------\n    z: Complex128|Complex128Array|ArrayLikeObject\n        Complex number or complex number array.\n\n    i: integer (optional)\n        Array index at which to start setting elements. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 2 )\n    <Complex128Array>\n    > arr.set( new Complex128( 1.0, -1.0 ) );\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    -1.0\n    > arr.set( new Complex128( 2.0, -2.0 ), 1 );\n    > z = arr.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    -2.0","Complex128Array.prototype.slice":"\nComplex128Array.prototype.slice( [start[, end]] )\n    Copies a portion of a typed array to a new typed array.\n\n    Parameters\n    ----------\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n    \n    Returns\n    -------\n    out: Complex128Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var out = arr.slice( 1 )\n    <Complex128Array>\n    > var len = out.length\n    2\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    -2.0\n    > z = out.get( 1 )\n    <Complex128>\n    > re = real( z )\n    3.0\n    > im = imag( z )\n    -3.0","Complex128Array.prototype.some":"\nComplex128Array.prototype.some( predicate[, thisArg] )\n    Returns a boolean indicating whether at least one element passes a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n    \n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one element passes the test.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var bool = arr.some( predicate )\n    true","Complex128Array.prototype.sort":"\nComplex128Array.prototype.sort( compareFunction )\n    Sorts an array in-place.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first element for comparison.\n    - b: second element for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFunction: Function\n        Comparison function.\n    \n    Returns\n    -------\n    out: Complex128Array\n        Modified array.\n    \n    Examples\n    --------\n    > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n    > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex128Array>\n    > arr.sort( compare );\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    -1.0\n    > z = arr.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    -2.0\n    > z = arr.get( 2 )\n    <Complex128>\n    > re = real( z )\n    3.0\n    > im = imag( z )\n    -3.0","Complex128Array.prototype.subarray":"\nComplex128Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array view over the same underlying `ArrayBuffer` and\n    with the same underlying data type as the host array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Complex128Array\n        New typed array view.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex128Array>\n    > var out = arr.subarray( 1, 3 )\n    <Complex128Array>\n    > var len = out.length\n    2\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    -2.0\n    > z = out.get( 1 )\n    <Complex128>\n    > re = real( z )\n    3.0\n    > im = imag( z )\n    -3.0","Complex128Array.prototype.toLocaleString":"\nComplex128Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array (optional)\n        Locale identifier(s).\n    \n    options: Object (optional)\n        An object containing serialization options.\n    \n    Returns\n    -------\n    str: string\n        Local-specific string.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0 ] )\n    <Complex128Array>\n    > var str = arr.toLocaleString()\n    '1 + 1i,2 + 2i'","Complex128Array.prototype.toReversed":"\nComplex128Array.prototype.toReversed()\n    Returns a new typed array containing the elements in reversed order.\n\n    Returns\n    -------\n    out: Complex128Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\n    <Complex128Array>\n    > var out = arr.toReversed()\n    <Complex128Array>\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    3.0\n    > z = out.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    2.0\n    > z = out.get( 2 )\n    <Complex128>\n    > re = real( z )\n    1.0\n    > im = imag( z )\n    1.0","Complex128Array.prototype.toSorted":"\nComplex128Array.prototype.toSorted( compareFcn )\n    Returns a new typed array containing the elements in sorted order.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first element for comparison.\n    - b: second element for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFcn: Function\n        Comparison function.\n    \n    Returns\n    -------\n    out: Complex128Array\n        New typed array.\n    \n    Examples\n    --------\n    > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n    > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex128Array>\n    > var out = arr.toSorted( compare );\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    -1.0\n    > z = out.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    -2.0\n    > z = out.get( 2 )\n    <Complex128>\n    > re = real( z )\n    3.0\n    > im = imag( z )\n    -3.0","Complex128Array.prototype.toString":"\nComplex128Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        String serialization of the array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\n    <Complex128Array>\n    > var str = arr.toString()\n    '1 + 1i,2 - 2i,3 + 3i'","Complex128Array.prototype.values":"\nComplex128Array.prototype.values()\n    Returns an iterator for iterating over each value in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array values.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var it = arr.values();\n    > var v = it.next().value\n    <Complex128>\n    > var re = real( v )\n    1.0\n    > var im = imag( v )\n    -1.0\n    > v = it.next().value\n    <Complex128>\n    > re = real( v )\n    2.0\n    > im = imag( v )\n    -2.0\n    > var bool = it.next().done\n    true","Complex128Array.prototype.with":"\nComplex128Array.prototype.with( index, value )\n    Returns a new typed array with the element at a provided index replaced\n    with a provided value.\n\n    Parameters\n    ----------\n    index: integer\n        Element index.\n    \n    value: Complex128\n        Element value.  \n\n    Returns\n    -------\n    out: Complex128Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n    <Complex128Array>\n    > var z = out.get( 1 )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    -3.0\n\n\n    See Also\n    --------\n    Complex64Array, complex, Complex128","complexarray":"\ncomplexarray( [dtype] )\n    Creates a complex typed array.\n\n    The function supports the following data types:\n\n    - complex128: double-precision complex floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n\n    The default typed array data type is `complex128`.\n\n    Parameters\n    ----------\n    dtype: string (optional)\n        Data type. Default: 'complex128'.\n\n    Returns\n    -------\n    out: ComplexArray\n        A complex number typed array.\n\n    Examples\n    --------\n    > var arr = complexarray()\n    <Complex128Array>\n    > arr = complexarray( 'complex64' )\n    <Complex64Array>\n\n\ncomplexarray( length[, dtype] )\n    Returns a complex number typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Array length.\n\n    dtype: string (optional)\n        Data type. Default: 'complex128'.\n\n    Returns\n    -------\n    out: ComplexArray\n        A complex number typed array.\n\n    Examples\n    --------\n    > var arr = complexarray( 5 )\n    <Complex128Array>\n    > arr = complexarray( 5, 'complex64' )\n    <Complex64Array>\n\n\ncomplexarray( complexarray[, dtype] )\n    Creates a complex number typed array from another complex number typed\n    array.\n\n    Parameters\n    ----------\n    complexarray: ComplexArray\n        Complex number typed array from which to generate another complex number\n        typed array.\n\n    dtype: string (optional)\n        Data type. Default: 'complex128'.\n\n    Returns\n    -------\n    out: ComplexArray\n        A complex number typed array.\n\n    Examples\n    --------\n    > var arr1 = complexarray( [ 0.5, 0.5, 0.5, 0.5 ] );\n    > var arr2 = complexarray( arr1, 'complex64' )\n    <Complex64Array>\n\n\ncomplexarray( obj[, dtype] )\n    Creates a complex number typed array from an array-like object or iterable.\n\n    If an array-like object contains interleaved real and imaginary components,\n    the array-like object must have a length which is a multiple of two.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate an array.\n\n    dtype: string (optional)\n        Data type. Default: 'complex128'.\n\n    Returns\n    -------\n    out: ComplexArray\n        A complex number typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 0.5, 0.5, 0.5, 0.5 ];\n    > var arr2 = complexarray( arr1, 'complex64' )\n    <Complex64Array>\n\n\ncomplexarray( buffer[, byteOffset[, length]][, dtype] )\n    Returns a complex number typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first array element.\n        Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    dtype: string (optional)\n        Data type. Default: 'complex128'.\n\n    Returns\n    -------\n    out: ComplexArray\n        A complex number typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 64 );\n    > var arr = complexarray( buf, 0, 8, 'complex64' )\n    <Complex64Array>\n\n    See Also\n    --------\n    typedarray, realarray\n","complexarrayCtors":"\ncomplexarrayCtors( dtype )\n    Returns a complex typed array constructor.\n\n    The function returns constructors for the following data types:\n\n    - complex64: single-precision floating-point complex numbers.\n    - complex128: double-precision floating-point complex numbers.\n\n    Parameters\n    ----------\n    dtype: string\n        Data type.\n\n    Returns\n    -------\n    out: Function|null\n        Complex typed array constructor.\n\n    Examples\n    --------\n    > var ctor = complexarrayCtors( 'complex64' )\n    <Function>\n    > ctor = complexarrayCtors( 'float32' )\n    null\n\n    See Also\n    --------\n    arrayCtors, typedarrayCtors, realarrayCtors\n","complexarrayDataTypes":"\ncomplexarrayDataTypes()\n    Returns a list of complex typed array data types.\n\n    Returns\n    -------\n    out: Array<string>\n        List of complex typed array data types.\n\n    Examples\n    --------\n    > var out = complexarrayDataTypes()\n    <Array>\n\n    See Also\n    --------\n    arrayDataTypes, typedarrayDataTypes, realarrayDataTypes, ndarrayDataTypes\n","complexCtors":"\ncomplexCtors( dtype )\n    Returns a complex number constructor.\n\n    The function returns constructors for the following data types:\n\n    - complex64: single-precision complex floating-point numbers.\n    - complex128: double-precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    dtype: string\n        Data type.\n\n    Returns\n    -------\n    out: Function|null\n        Constructor.\n\n    Examples\n    --------\n    > var ctor = complexCtors( 'complex128' )\n    <Function>\n    > ctor = complexCtors( 'complex' )\n    null\n\n    See Also\n    --------\n    complexarrayCtors\n","complexDataType":"\ncomplexDataType( value )\n    Returns the data type of a complex number object.\n\n    If provided an argument having an unknown or unsupported type, the function\n    returns `null`.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    out: string|null\n        Data type.\n\n    Examples\n    --------\n    > var v = new Complex128( 1.0, 2.0 );\n    > var dt = complexDataType( v )\n    'complex128'\n    > dt = complexDataType( 'beep' )\n    null\n\n    See Also\n    --------\n    arrayDataType\n","complexDataTypes":"\ncomplexDataTypes()\n    Returns a list of complex number data types.\n\n    The output array contains the following data types:\n\n    - complex64: single-precision complex floating-point numbers.\n    - complex128: double-precision complex floating-point numbers.\n\n    Returns\n    -------\n    out: Array<string>\n        List of complex number data types.\n\n    Examples\n    --------\n    > var out = complexDataTypes()\n    <Array>\n\n    See Also\n    --------\n    complexarrayDataTypes\n","complexPromotionRules":"\ncomplexPromotionRules( [dtype1, dtype2] )\n    Returns the complex number data type with the smallest size and closest\n    \"kind\" to which data types can be safely cast.\n\n    If not provided data types, the function returns a type promotion table.\n\n    If a data type to which data types can be safely cast does *not* exist (or\n    is not supported), the function returns `-1`.\n\n    If provided an unrecognized data type, the function returns `null`.\n\n    Parameters\n    ----------\n    dtype1: string (optional)\n        Data type.\n\n    dtype2: string (optional)\n        Data type.\n\n    Returns\n    -------\n    out: Object|string|integer|null\n        Promotion rule(s).\n\n    Examples\n    --------\n    > var out = complexPromotionRules( 'complex128', 'complex64' )\n    'complex128'\n\n    See Also\n    --------\n    arrayPromotionRules, ndarrayPromotionRules\n","compose":"\ncompose( ...f )\n    Function composition.\n\n    Returns a composite function. Starting from the right, the composite\n    function evaluates each function and passes the result as an argument\n    to the next function. The result of the leftmost function is the result\n    of the whole.\n\n    Notes:\n\n    - Only the rightmost function is explicitly permitted to accept multiple\n      arguments. All other functions are evaluated as unary functions.\n    - The function will throw if provided fewer than two input arguments.\n\n    Parameters\n    ----------\n    f: ...Function\n        Functions to compose.\n\n    Returns\n    -------\n    out: Function\n        Composite function.\n\n    Examples\n    --------\n    > function a( x ) {\n    ...    return 2 * x;\n    ... }\n    > function b( x ) {\n    ...    return x + 3;\n    ... }\n    > function c( x ) {\n    ...    return x / 5;\n    ... }\n    > var f = compose( c, b, a );\n    > var z = f( 6 )\n    3\n\n    See Also\n    --------\n    composeAsync\n","composeAsync":"\ncomposeAsync( ...f )\n    Function composition.\n\n    Returns a composite function. Starting from the right, the composite\n    function evaluates each function and passes the result as the first argument\n    of the next function. The result of the leftmost function is the result\n    of the whole.\n\n    The last argument for each provided function is a `next` callback which\n    should be invoked upon function completion. The callback accepts two\n    arguments:\n\n    - error: error argument.\n    - result: function result.\n\n    If a composed function calls the `next` callback with a truthy `error`\n    argument, the composite function suspends execution and immediately calls\n    the `done` callback for subsequent `error` handling.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Only the rightmost function is explicitly permitted to accept multiple\n    arguments. All other functions are evaluated as binary functions.\n\n    The function will throw if provided fewer than two input arguments.\n\n    Parameters\n    ----------\n    f: ...Function\n        Functions to compose.\n\n    Returns\n    -------\n    out: Function\n        Composite function.\n\n    Examples\n    --------\n    > function a( x, next ) {\n    ...    setTimeout( onTimeout, 0 );\n    ...    function onTimeout() {\n    ...        next( null, 2*x );\n    ...    }\n    ... };\n    > function b( x, next ) {\n    ...    setTimeout( onTimeout, 0 );\n    ...    function onTimeout() {\n    ...        next( null, x+3 );\n    ...    }\n    ... };\n    > function c( x, next ) {\n    ...    setTimeout( onTimeout, 0 );\n    ...    function onTimeout() {\n    ...        next( null, x/5 );\n    ...    }\n    ... };\n    > var f = composeAsync( c, b, a );\n    > function done( error, result ) {\n    ...    if ( error ) {\n    ...        throw error;\n    ...    }\n    ...    console.log( result );\n    ... };\n    > f( 6, done )\n    3\n\n    See Also\n    --------\n    compose\n","configdir":"\nconfigdir( [p] )\n    Returns a directory for user-specific configuration files.\n\n    On Windows platforms, the function first checks for a `LOCALAPPDATA`\n    environment variable before checking for an `APPDATA` environment variable.\n    This means that machine specific user configuration files have precedence\n    over roaming user configuration files.\n\n    On non-Windows platforms, if the function is unable to locate the current\n    user's `home` directory, the function returns `null`. Similarly, on Windows\n    platforms, if the function is unable to locate an application data\n    directory, the function also returns `null`.\n\n    Parameters\n    ----------\n    p: string (optional)\n        Path to append to a base directory.\n\n    Returns\n    -------\n    out: string|null\n        Directory.\n\n    Examples\n    --------\n    > var dir = configdir()\n    e.g., '/Users/<username>/Library/Preferences'\n    > dir = configdir( 'appname/config' )\n    e.g., '/Users/<username>/Library/Preferences/appname/config'\n\n    See Also\n    --------\n    homedir, tmpdir\n","conj":"\nconj( z )\n    Returns the complex conjugate of a double-precision complex floating-point\n    number.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Complex conjugate.\n\n    Examples\n    --------\n    > var z = new Complex128( 5.0, 3.0 );\n    > z.toString()\n    '5 + 3i'\n    > var v = conj( z );\n    > v.toString()\n    '5 - 3i'\n\n    See Also\n    --------\n    imag, real, reim\n","conjf":"\nconjf( z )\n    Returns the complex conjugate of a single-precision complex floating-point\n    number.\n\n    Parameters\n    ----------\n    z: Complex64\n        Complex number.\n\n    Returns\n    -------\n    out: Complex64\n        Complex conjugate.\n\n    Examples\n    --------\n    > var z = new Complex64( 5.0, 3.0 );\n    > z.toString()\n    '5 + 3i'\n    > var v = conjf( z );\n    > v.toString()\n    '5 - 3i'\n\n    See Also\n    --------\n    conj, imagf, realf, reimf\n","constantcase":"\nconstantcase( str )\n    Converts a string to constant case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Constant-cased string.\n\n    Examples\n    --------\n    > var out = constantcase( 'Hello World!' )\n    'HELLO_WORLD'\n    > out = constantcase( 'I am a tiny little teapot' )\n    'I_AM_A_TINY_LITTLE_TEAPOT'\n\n    See Also\n    --------\n    camelcase, kebabcase, pascalcase, snakecase","constantFunction":"\nconstantFunction( val )\n    Creates a function which always returns the same value.\n\n    Notes:\n\n    - When provided an object reference, the returned `function` always returns\n      the same reference.\n\n    Parameters\n    ----------\n    val: any\n        Value to always return.\n\n    Returns\n    -------\n    out: Function\n        Constant function.\n\n    Examples\n    --------\n    > var fcn = constantFunction( 3.14 );\n    > var v = fcn()\n    3.14\n    > v = fcn()\n    3.14\n    > v = fcn()\n    3.14\n\n    See Also\n    --------\n    argumentFunction, identity\n","constantStream":"\nconstantStream( value[, options] )\n    Returns a readable stream which always streams the same value.\n\n    In object mode, `null` is a reserved value. If provided `null`, the\n    returned stream will prematurely end.\n\n    Parameters\n    ----------\n    value: string|Buffer|Uint8Array|any\n        Value to stream.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing streaming.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = constantStream( 'beep', opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nconstantStream.factory( [value, ][options] )\n    Returns a function for creating readable streams which always stream the\n    same value.\n\n    If provided a value to stream, the returned function returns readable always\n    streams the provided value.\n\n    If not provided a value to stream, the returned function requires that a\n    value be provided at each invocation.\n\n    If provided only one argument and that argument is an object (either empty\n    or not containing any recognized options properties), the function treats\n    the argument as a value to be streamed, not as an options argument.\n\n    Parameters\n    ----------\n    value: string|Buffer|Uint8Array|any (optional)\n        Value to stream.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing streaming.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = constantStream.factory( opts );\n\n\nconstantStream.objectMode( value[, options] )\n    Returns an \"objectMode\" readable stream which always streams the same value.\n\n    In object mode, `null` is a reserved value. If provided `null`, the\n    returned stream will prematurely end.\n\n    Parameters\n    ----------\n    value: any\n        Value to stream.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before pausing streaming.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = constantStream.objectMode( 3.14, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    arrayStream, iteratorStream\n","constantStream.factory":"\nconstantStream.factory( [value, ][options] )\n    Returns a function for creating readable streams which always stream the\n    same value.\n\n    If provided a value to stream, the returned function returns readable always\n    streams the provided value.\n\n    If not provided a value to stream, the returned function requires that a\n    value be provided at each invocation.\n\n    If provided only one argument and that argument is an object (either empty\n    or not containing any recognized options properties), the function treats\n    the argument as a value to be streamed, not as an options argument.\n\n    Parameters\n    ----------\n    value: string|Buffer|Uint8Array|any (optional)\n        Value to stream.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing streaming.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = constantStream.factory( opts );","constantStream.objectMode":"\nconstantStream.objectMode( value[, options] )\n    Returns an \"objectMode\" readable stream which always streams the same value.\n\n    In object mode, `null` is a reserved value. If provided `null`, the\n    returned stream will prematurely end.\n\n    Parameters\n    ----------\n    value: any\n        Value to stream.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before pausing streaming.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = constantStream.objectMode( 3.14, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    arrayStream, iteratorStream","constructorName":"\nconstructorName( val )\n    Determines the name of a value's constructor.\n\n    Parameters\n    ----------\n    val: any\n        Input value.\n\n    Returns\n    -------\n    out: string\n        Name of a value's constructor.\n\n    Examples\n    --------\n    > var v = constructorName( 'a' )\n    'String'\n    > v = constructorName( {} )\n    'Object'\n    > v = constructorName( true )\n    'Boolean'\n\n    See Also\n    --------\n    functionName\n","contains":"\ncontains( val, searchValue[, position] )\n    Tests if an array-like value contains a search value.\n\n    When `val` is a string, the function checks whether the characters of the\n    search string are found in the input string. The search is case-sensitive.\n\n    When `val` is an array-like object, the function checks whether the input\n    array contains an element strictly equal to the specified search value.\n\n    For strings, this function is modeled after `String.prototype.includes`,\n    part of the ECMAScript 6 specification. This function is different from a\n    call to `String.prototype.includes.call` insofar as type-checking is\n    performed for all arguments.\n\n    The function does not distinguish between positive and negative zero.\n\n    If `position < 0`, the search is performed for the entire input array or\n    string.\n\n\n    Parameters\n    ----------\n    val: ArrayLike\n        Input value.\n\n    searchValue: any\n        Value to search for.\n\n    position: integer (optional)\n        Position at which to start searching for `searchValue`. Default: `0`.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an input value contains another value.\n\n    Examples\n    --------\n    > var bool = contains( 'Hello World', 'World' )\n    true\n    > bool = contains( 'Hello World', 'world' )\n    false\n    > bool = contains( [ 1, 2, 3, 4 ], 2 )\n    true\n    > bool = contains( [ NaN, 2, 3, 4 ], NaN )\n    true\n\n    // Supply a position:\n    > bool = contains( 'Hello World', 'Hello', 6 )\n    false\n    > bool = contains( [ true, NaN, false ], true, 1 )\n    false\n\n","convertArray":"\nconvertArray( arr, dtype )\n    Converts an input array to an array of a different data type.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject\n        Array to convert.\n\n    dtype: string\n        Output data type.\n\n    Returns\n    -------\n    out: Array|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var arr = [ 1.0, 2.0, 3.0, 4.0 ];\n    > var out = convertArray( arr, 'float32' )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    See Also\n    --------\n    convertArraySame\n","convertArraySame":"\nconvertArraySame( x, y )\n    Converts an input array to the same data type as a second input array.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Array to convert.\n\n    y: Array|TypedArray\n        Array having desired output data type.\n\n    Returns\n    -------\n    out: Array|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n    > var y = new Float32Array( 0 );\n    > var out = convertArraySame( x, y )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    See Also\n    --------\n    convertArray\n","convertPath":"\nconvertPath( from, to )\n    Converts between POSIX and Windows paths.\n\n    Parameters\n    ----------\n    from: string\n        Input path.\n\n    to: string\n        Output path convention: 'win32', 'mixed', or 'posix'.\n\n    Returns\n    -------\n    out: string\n        Converted path.\n\n    Examples\n    --------\n    > var out = convertPath( '/c/foo/bar/beep.c', 'win32' )\n    'c:\\\\foo\\\\bar\\\\beep.c'\n    > out = convertPath( '/c/foo/bar/beep.c', 'mixed' )\n    'c:/foo/bar/beep.c'\n    > out = convertPath( '/c/foo/bar/beep.c', 'posix' )\n    '/c/foo/bar/beep.c'\n    > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'win32' )\n    'C:\\\\\\\\foo\\\\bar\\\\beep.c'\n    > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'mixed' )\n    'C:/foo/bar/beep.c'\n    > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'posix' )\n    '/c/foo/bar/beep.c'\n\n","copy":"\ncopy( value[, level] )\n    Copy or deep clone a value to an arbitrary depth.\n\n    The implementation can handle circular references.\n\n    If a `Number`, `String`, or `Boolean` object is encountered, the value is\n    cloned as a primitive. This behavior is intentional.\n\n    For objects, the implementation only copies enumerable keys and their\n    associated property descriptors.\n\n    The implementation only checks whether basic `Objects`, `Arrays`, and class\n    instances are extensible, sealed, and/or frozen.\n\n    Functions are not cloned; their reference is copied.\n\n    The implementation supports custom error types which are `Error` instances\n    (e.g., ES2015 subclasses).\n\n    Support for copying class instances is inherently fragile. Any instances\n    with privileged access to variables (e.g., within closures) cannot be\n    cloned. This stated, basic copying of class instances is supported. Provided\n    an environment which supports ES5, the implementation is greedy and performs\n    a deep clone of any arbitrary class instance and its properties. The\n    implementation assumes that the concept of `level` applies only to the class\n    instance reference, but not to its internal state.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    level: integer (optional)\n         Copy depth. Default: Infinity.\n\n    Returns\n    -------\n    out: any\n        Value copy.\n\n    Examples\n    --------\n    > var value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\n    > var out = copy( value )\n    [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ]\n    > var bool = ( value[ 0 ].c === out[ 0 ].c )\n    false\n\n    // Set the `level` option to limit the copy depth:\n    > value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\n    > out = copy( value, 1 );\n    > bool = ( value[ 0 ] === out[ 0 ] )\n    true\n    > bool = ( value[ 0 ].c === out[ 0 ].c )\n    true\n\n\n    See Also\n    --------\n    merge\n","copyBuffer":"\ncopyBuffer( buffer )\n    Copies buffer data to a new Buffer instance.\n\n    Parameters\n    ----------\n    buffer: Buffer\n        Buffer to copy from.\n\n    Returns\n    -------\n    out: Buffer\n        Buffer instance.\n\n    Examples\n    --------\n    > var b1 = array2buffer( [ 1, 2, 3, 4 ] );\n    > var b2 = copyBuffer( b1 )\n    <Buffer>[ 1, 2, 3, 4 ]\n\n    See Also\n    --------\n    allocUnsafe, Buffer\n","countBy":"\ncountBy( collection, [options,] indicator )\n    Groups values according to an indicator function and returns group counts.\n\n    When invoked, the indicator function is provided two arguments:\n\n    - value: collection value.\n    - index: collection index.\n\n    The value returned by an indicator function should be a value which can be\n    serialized as an object key.\n\n    If provided an empty collection, the function returns an empty object.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection to group. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Options.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    indicator: Function\n        Indicator function specifying which group an element in the input\n        collection belongs to.\n\n    Returns\n    -------\n    out: Object\n        Group results.\n\n    Examples\n    --------\n    > function indicator( v ) {\n    ...     if ( v[ 0 ] === 'b' ) {\n    ...         return 'b';\n    ...     }\n    ...     return 'other';\n    ... };\n    > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n    > var out = countBy( collection, indicator )\n    { 'b': 3, 'other': 1 }\n\n    See Also\n    --------\n    group, groupBy\n","countByAsync":"\ncountByAsync( collection, [options,] indicator, done )\n    Groups values according to an indicator function and returns group counts.\n\n    When invoked, the indicator function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If the\n    indicator function accepts two arguments, the indicator function is\n    provided:\n\n    - value\n    - next\n\n    If the indicator function accepts three arguments, the indicator function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other indicator function signature, the indicator function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - group: value group.\n\n    If an indicator function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    If provided an empty collection, the function calls the `done` callback with\n    an empty object as the second argument.\n\n    The `group` returned by an indicator function should be a value which can be\n    serialized as an object key.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    indicator: Function\n        Indicator function specifying which group an element in the input\n        collection belongs to.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > countByAsync( arr, indicator, done )\n    1000\n    2500\n    3000\n    { \"even\": 2, \"odd\": 1 }\n\n    // Limit number of concurrent invocations:\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 3000, 2500, 1000 ];\n    > countByAsync( arr, opts, indicator, done )\n    2500\n    3000\n    1000\n    { \"even\": 2, \"odd\": 1 }\n\n    // Process sequentially:\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 3000, 2500, 1000 ];\n    > countByAsync( arr, opts, indicator, done )\n    3000\n    2500\n    1000\n    { \"even\": 2, \"odd\": 1 }\n\n\ncountByAsync.factory( [options,] indicator )\n    Returns a function which groups values according to an indicator function\n    and returns group counts.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    indicator: Function\n        Indicator function specifying which group an element in the input\n        collection belongs to.\n\n    Returns\n    -------\n    out: Function\n        A function which groups values and returns group counts.\n\n    Examples\n    --------\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = countByAsync.factory( opts, indicator );\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    { \"even\": 2, \"odd\": 1 }\n    > arr = [ 2000, 1500, 1000, 500 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    500\n    { \"even\": 2, \"odd\": 2 }\n\n    See Also\n    --------\n    countBy, groupByAsync, tabulateByAsync\n","countByAsync.factory":"\ncountByAsync.factory( [options,] indicator )\n    Returns a function which groups values according to an indicator function\n    and returns group counts.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    indicator: Function\n        Indicator function specifying which group an element in the input\n        collection belongs to.\n\n    Returns\n    -------\n    out: Function\n        A function which groups values and returns group counts.\n\n    Examples\n    --------\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = countByAsync.factory( opts, indicator );\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    { \"even\": 2, \"odd\": 1 }\n    > arr = [ 2000, 1500, 1000, 500 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    500\n    { \"even\": 2, \"odd\": 2 }\n\n    See Also\n    --------\n    countBy, groupByAsync, tabulateByAsync","currentYear":"\ncurrentYear()\n    Returns the current year.\n\n    Returns\n    -------\n    out: integer\n        Current year.\n\n    Examples\n    --------\n    > var y = currentYear()\n    <number>\n\n    See Also\n    --------\n    isCurrentYear\n","curry":"\ncurry( fcn[, arity][, thisArg] )\n    Transforms a function into a sequence of functions each accepting a single\n    argument.\n\n    Until return value resolution, each invocation returns a new partially\n    applied curry function.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to curry.\n\n    arity: integer (optional)\n        Number of parameters. Default: `fcn.length`.\n\n    thisArg: any (optional)\n        Evaluation context.\n\n    Returns\n    -------\n    out: Function\n        Curry function.\n\n    Examples\n    --------\n    > function add( x, y ) { return x + y; };\n    > var f = curry( add );\n    > var sum = f( 2 )( 3 )\n    5\n\n    // Supply arity:\n    > function add() { return arguments[ 0 ] + arguments[ 1 ]; };\n    > f = curry( add, 2 );\n    > sum = f( 2 )( 3 )\n    5\n\n    // Provide function context:\n    > var obj = {\n    ...     'name': 'Ada',\n    ...     'greet': function greet( word1, word2 ) {\n    ...        return word1 + ' ' + word2 + ', ' + this.name + '!'\n    ...     }\n    ... };\n    > f = curry( obj.greet, obj );\n    > var str = f( 'Hello' )( 'there' )\n    'Hello there, Ada!'\n\n    See Also\n    --------\n    curryRight, uncurry, uncurryRight\n","curryRight":"\ncurryRight( fcn[, arity][, thisArg] )\n    Transforms a function into a sequence of functions each accepting a single\n    argument.\n\n    Until return value resolution, each invocation returns a new partially\n    applied curry function.\n\n    This function applies arguments starting from the right.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to curry.\n\n    arity: integer (optional)\n        Number of parameters. Default: `fcn.length`.\n\n    thisArg: any (optional)\n        Evaluation context.\n\n    Returns\n    -------\n    out: Function\n        Curry function.\n\n    Examples\n    --------\n    > function add( x, y ) { return x + y; };\n    > var f = curryRight( add );\n    > var sum = f( 2 )( 3 )\n    5\n\n    // Supply arity:\n    > function add() { return arguments[ 0 ] + arguments[ 1 ]; };\n    > f = curryRight( add, 2 );\n    > sum = f( 2 )( 3 )\n    5\n\n    // Provide function context:\n    > var obj = {\n    ...     'name': 'Ada',\n    ...     'greet': function greet( word1, word2 ) {\n    ...         return word1 + ' ' + word2 + ', ' + this.name + '!'\n    ...     }\n    ... };\n    > f = curryRight( obj.greet, obj );\n    > var str = f( 'there' )( 'Hello' )\n    'Hello there, Ada!'\n\n    See Also\n    --------\n    curry, uncurry, uncurryRight\n","cwd":"\ncwd()\n    Returns the current working directory.\n\n    Returns\n    -------\n    path: string\n        Current working directory of the process.\n\n    Examples\n    --------\n    > var dir = cwd()\n    '/path/to/current/working/directory'\n\n    See Also\n    --------\n    chdir\n","DALE_CHALL_NEW":"\nDALE_CHALL_NEW()\n    Returns a list of familiar English words.\n\n    Returns\n    -------\n    out: Array<string>\n        List of familiar English words.\n\n    Examples\n    --------\n    > var list = DALE_CHALL_NEW()\n    [ 'a', 'able', 'aboard', 'about', 'above', ... ]\n\n    References\n    ----------\n    - Chall, Jeanne Sternlicht, and Edgar Dale. 1995. *Readability revisited:\n    the new Dale-Chall readability formula*. Brookline Books.\n    <https://books.google.com/books?id=2nbuAAAAMAAJ>.\n\n","datasets":"\ndatasets( name[, options] )\n    Returns a dataset.\n\n    The function forwards provided options to the dataset interface specified\n    by `name`.\n\n    Parameters\n    ----------\n    name: string\n        Dataset name.\n\n    options: Object (optional)\n        Function options.\n\n    Returns\n    -------\n    out: any\n        Dataset.\n\n    Examples\n    --------\n    > var out = datasets( 'MONTH_NAMES_EN' )\n    [ 'January', 'February', ... ]\n    > var opts = { 'data': 'cities' };\n    > out = datasets( 'MINARD_NAPOLEONS_MARCH', opts )\n    [ {...}, {...}, ... ]\n\n","DataView":"\nDataView( buffer[, byteOffset[, byteLength]] )\n    Returns a data view representing a provided array buffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer|SharedArrayBuffer\n        Array buffer.\n\n    byteOffset: integer (optional)\n        Offset (in bytes) to the first byte in the array buffer for the new view\n        to reference. Default: 0.\n\n    byteLength: integer (optional)\n        Number of elements in the byte array. If not provided, the view's length\n        will equal the buffer's length.\n\n    Returns\n    -------\n    out: DataView\n        A data view.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 5 )\n    <ArrayBuffer>\n    > var dv = new DataView( buf )\n    <DataView>\n\n\nDataView.prototype.buffer\n    Read-only property which returns the underyling array buffer.\n\n    Examples\n    --------\n    > var buf1 = new ArrayBuffer( 5 );\n    > var dv = new DataView( buf1 );\n    > var buf2 = dv.buffer\n    <ArrayBuffer>\n    > var b = ( buf1 === buf2 )\n    true\n\n\nDataView.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the view.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 5 );\n    > var dv = new DataView( buf );\n    > dv.byteLength\n    5\n\n\nDataView.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the view to the\n    start of the underlying array buffer.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 5 );\n    > var dv = new DataView( buf, 2 );\n    > dv.byteLength\n    3\n    > dv.byteOffset\n    2\n\n\nTODO: document properties/methods\n\n\n    See Also\n    --------\n    ArrayBuffer, typedarray\n","DataView.prototype.buffer":"\nDataView.prototype.buffer\n    Read-only property which returns the underyling array buffer.\n\n    Examples\n    --------\n    > var buf1 = new ArrayBuffer( 5 );\n    > var dv = new DataView( buf1 );\n    > var buf2 = dv.buffer\n    <ArrayBuffer>\n    > var b = ( buf1 === buf2 )\n    true","DataView.prototype.byteLength":"\nDataView.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the view.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 5 );\n    > var dv = new DataView( buf );\n    > dv.byteLength\n    5","DataView.prototype.byteOffset":"\nDataView.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the view to the\n    start of the underlying array buffer.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 5 );\n    > var dv = new DataView( buf, 2 );\n    > dv.byteLength\n    3\n    > dv.byteOffset\n    2","datespace":"\ndatespace( start, stop[, length][ , options] )\n    Generates an array of linearly spaced dates.\n\n    Parameters\n    ----------\n    start: number\n        Start time as either a `Date` object, Unix timestamp, JavaScript\n        timestamp, or date string.\n\n    stop: number\n        Stop time as either a `Date` object, Unix timestamp, JavaScript\n        timestamp, or date string.\n\n    length: integer (optional)\n        Length of output array. Default: `100`.\n\n    options: Object (optional)\n        Options.\n\n    options.round: string (optional)\n        Specifies how sub-millisecond times should be rounded:\n        [ 'floor', 'ceil', 'round' ]. Default: 'floor'.\n\n    Returns\n    -------\n    arr: Array\n        Array of dates.\n\n    Examples\n    --------\n    > var stop = '2014-12-02T07:00:54.973Z';\n    > var start = new Date( stop ) - 60000;\n    > var arr = datespace( start, stop, 6 )\n    [...]\n\n    // Equivalent of Math.ceil():\n    > var opts = { 'round': 'ceil' };\n    > arr = datespace( 1417503655000, 1417503655001, 3, opts )\n    [...]\n\n    See Also\n    --------\n    linspace, logspace\n","dayOfQuarter":"\ndayOfQuarter( [month[, day, year]] )\n    Returns the day of the quarter.\n\n    By default, the function returns the day of the quarter for the current date\n    (according to local time). To determine the day of the quarter for a\n    particular day, provide `month`, `day`, and `year` arguments.\n\n    A `month` may be either a month's integer value, three letter abbreviation,\n    or full name (case insensitive).\n\n    The function also accepts a `Date` object.\n\n    Parameters\n    ----------\n    month: string|integer|Date (optional)\n        Month (or `Date`).\n\n    day: integer (optional)\n        Day.\n\n    year: integer (optional)\n        Year.\n\n    Returns\n    -------\n    out: integer\n        Day of the quarter.\n\n    Examples\n    --------\n    > var day = dayOfQuarter()\n    <number>\n    > day = dayOfQuarter( new Date() )\n    <number>\n    > day = dayOfQuarter( 12, 31, 2017 )\n    92\n\n    // Other ways to supply month:\n    > day = dayOfQuarter( 'dec', 31, 2017 )\n    92\n    > day = dayOfQuarter( 'december', 31, 2017 )\n    92\n\n    See Also\n    --------\n    dayOfYear\n","dayOfYear":"\ndayOfYear( [month[, day, year]] )\n    Returns the day of the year.\n\n    By default, the function returns the day of the year for the current date\n    (according to local time). To determine the day of the year for a particular\n    day, provide `month`, `day`, and `year` arguments.\n\n    A `month` may be either a month's integer value, three letter abbreviation,\n    or full name (case insensitive).\n\n    The function also accepts a `Date` object.\n\n    Parameters\n    ----------\n    month: string|integer|Date (optional)\n        Month (or `Date`).\n\n    day: integer (optional)\n        Day.\n\n    year: integer (optional)\n        Year.\n\n    Returns\n    -------\n    out: integer\n        Day of the year.\n\n    Examples\n    --------\n    > var day = dayOfYear()\n    <number>\n    > day = dayOfYear( new Date() )\n    <number>\n    > day = dayOfYear( 12, 31, 2016 )\n    366\n\n    // Other ways to supply month:\n    > day = dayOfYear( 'dec', 31, 2016 )\n    366\n    > day = dayOfYear( 'december', 31, 2016 )\n    366\n\n    See Also\n    --------\n    dayOfQuarter\n","daysInMonth":"\ndaysInMonth( [month[, year]] )\n    Returns the number of days in a month.\n\n    By default, the function returns the number of days in the current month\n    of the current year (according to local time). To determine the number of\n    days for a particular month and year, provide `month` and `year` arguments.\n\n    A `month` may be either a month's integer value, three letter abbreviation,\n    or full name (case insensitive).\n\n    The function's return value is a generalization and does **not** take into\n    account inaccuracies due to daylight savings conventions, crossing\n    timezones, or other complications with time and dates.\n\n    Parameters\n    ----------\n    month: string|integer|Date (optional)\n        Month (or `Date`).\n\n    year: integer (optional)\n        Year.\n\n    Returns\n    -------\n    out: integer\n        Days in a month.\n\n    Examples\n    --------\n    > var num = daysInMonth()\n    <number>\n    > num = daysInMonth( 2 )\n    <number>\n    > num = daysInMonth( 2, 2016 )\n    29\n    > num = daysInMonth( 2, 2017 )\n    28\n\n    // Other ways to supply month:\n    > num = daysInMonth( 'feb', 2016 )\n    29\n    > num = daysInMonth( 'february', 2016 )\n    29\n\n    See Also\n    --------\n    daysInYear\n","daysInYear":"\ndaysInYear( [value] )\n    Returns the number of days in a year according to the Gregorian calendar.\n\n    By default, the function returns the number of days in the current year\n    (according to local time). To determine the number of days for a particular\n    year, provide either a year or a `Date` object.\n\n    The function's return value is a generalization and does **not** take into\n    account inaccuracies due to daylight savings conventions, crossing\n    timezones, or other complications with time and dates.\n\n    Parameters\n    ----------\n    value: integer|Date (optional)\n        Year or `Date` object.\n\n    Returns\n    -------\n    out: integer\n        Number of days in a year.\n\n    Examples\n    --------\n    > var num = daysInYear()\n    <number>\n    > num = daysInYear( 2016 )\n    366\n    > num = daysInYear( 2017 )\n    365\n\n    See Also\n    --------\n    daysInMonth\n","ddot":"\nddot( x, y[, dim] )\n    Computes the dot product of two double-precision floating-point vectors.\n\n    If provided at least one input array having more than one dimension, the\n    input arrays are broadcasted to a common shape.\n\n    For multi-dimensional input arrays, the function performs batched\n    computation, such that the function computes the dot product for each pair\n    of vectors in `x` and `y` according to the specified dimension index.\n\n    The size of the contracted dimension must be the same for both input arrays.\n\n    The function resolves the dimension index for which to compute the dot\n    product *before* broadcasting.\n\n    If provided empty vectors, the dot product is `0`.\n\n    Parameters\n    ----------\n    x: ndarray\n        First input array. Must have a 'float64' data type. Must have at least\n        one dimension and be broadcast-compatible with the second input array.\n\n    y: ndarray\n        Second input array. Must have a 'float64' data type. Must have at least\n        one dimension and be broadcast-compatible with the first input array.\n\n    dim: integer (optional)\n        Dimension index for which to compute the dot product. Must be a negative\n        integer. Negative indices are resolved relative to the last array\n        dimension, with the last dimension corresponding to `-1`. Default: -1.\n\n    Returns\n    -------\n    out: ndarray\n        The dot product. The output array has the same data type as the input\n        arrays and has a shape which is determined by broadcasting and excludes\n        the contracted dimension.\n\n    Examples\n    --------\n    > var xbuf = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var x = array( xbuf );\n    > var ybuf = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var y = array( ybuf );\n    > var z = ddot( x, y )\n    <ndarray>\n    > z.get()\n    -5.0\n\n    See Also\n    --------\n    base.strided.ddot, gdot, sdot\n","debugSinkStream":"\ndebugSinkStream( [options,] [clbk] )\n    Returns a writable stream for debugging stream pipelines.\n\n    If the `DEBUG` environment variable is not set, no data is logged.\n\n    Providing a `name` option is *strongly* encouraged, as the `DEBUG`\n    environment variable can be used to filter debuggers.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Debug namespace.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to encode strings as `Buffer` objects before writing\n        data to a returned stream. Default: true.\n\n    options.defaultEncoding: string (optional)\n        Default encoding when not explicitly specified when writing data.\n        Default: 'utf8'.\n\n    clbk: Function (optional)\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: WritableStream\n        Writable stream.\n\n    Examples\n    --------\n    > var s = debugSinkStream( { 'name': 'foo' } );\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();\n\n\ndebugSinkStream.factory( [options] )\n    Returns a function for creating writable streams for debugging stream\n    pipelines.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to encode strings as `Buffer` objects before writing\n        data to a returned stream. Default: true.\n\n    options.defaultEncoding: string (optional)\n        Default encoding when not explicitly specified when writing data.\n        Default: 'utf8'.\n\n    Returns\n    -------\n    createStream( name[, clbk] ): Function\n        Function for creating writable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = debugSinkStream.factory( opts );\n\n\ndebugSinkStream.objectMode( [options,] [clbk] )\n    Returns an \"objectMode\" writable stream for debugging stream pipelines.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Debug namespace.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to encode strings as `Buffer` objects before writing\n        data to a returned stream. Default: true.\n\n    options.defaultEncoding: string (optional)\n        Default encoding when not explicitly specified when writing data.\n        Default: 'utf8'.\n\n    clbk: Function (optional)\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: WritableStream\n        Writable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > var s = debugSinkStream.objectMode( { 'name': 'foo' } );\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();\n\n    See Also\n    --------\n    debugStream, inspectSinkStream\n","debugSinkStream.factory":"\ndebugSinkStream.factory( [options] )\n    Returns a function for creating writable streams for debugging stream\n    pipelines.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to encode strings as `Buffer` objects before writing\n        data to a returned stream. Default: true.\n\n    options.defaultEncoding: string (optional)\n        Default encoding when not explicitly specified when writing data.\n        Default: 'utf8'.\n\n    Returns\n    -------\n    createStream( name[, clbk] ): Function\n        Function for creating writable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = debugSinkStream.factory( opts );","debugSinkStream.objectMode":"\ndebugSinkStream.objectMode( [options,] [clbk] )\n    Returns an \"objectMode\" writable stream for debugging stream pipelines.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Debug namespace.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to encode strings as `Buffer` objects before writing\n        data to a returned stream. Default: true.\n\n    options.defaultEncoding: string (optional)\n        Default encoding when not explicitly specified when writing data.\n        Default: 'utf8'.\n\n    clbk: Function (optional)\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: WritableStream\n        Writable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > var s = debugSinkStream.objectMode( { 'name': 'foo' } );\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();\n\n    See Also\n    --------\n    debugStream, inspectSinkStream","debugStream":"\ndebugStream( [options,] [clbk] )\n    Returns a transform stream for debugging stream pipelines.\n\n    If the `DEBUG` environment variable is not set, no data is logged.\n\n    Providing a `name` option is *strongly* encouraged, as the `DEBUG`\n    environment variable can be used to filter debuggers.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Debug namespace.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    clbk: Function (optional)\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream.\n\n    Examples\n    --------\n    > var s = debugStream( { 'name': 'foo' } );\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();\n\n\ndebugStream.factory( [options] )\n    Returns a function for creating transform streams for debugging stream\n    pipelines.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    createStream( name[, clbk] ): Function\n        Function for creating transform streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = debugStream.factory( opts );\n\n\ndebugStream.objectMode( [options,] [clbk] )\n    Returns an \"objectMode\" transform stream for debugging stream pipelines.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Debug namespace.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    clbk: Function (optional)\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > var s = debugStream.objectMode( { 'name': 'foo' } );\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();\n\n    See Also\n    --------\n    debugSinkStream, inspectStream\n","debugStream.factory":"\ndebugStream.factory( [options] )\n    Returns a function for creating transform streams for debugging stream\n    pipelines.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    createStream( name[, clbk] ): Function\n        Function for creating transform streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = debugStream.factory( opts );","debugStream.objectMode":"\ndebugStream.objectMode( [options,] [clbk] )\n    Returns an \"objectMode\" transform stream for debugging stream pipelines.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Debug namespace.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    clbk: Function (optional)\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > var s = debugStream.objectMode( { 'name': 'foo' } );\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();\n\n    See Also\n    --------\n    debugSinkStream, inspectStream","decorateAfter":"\ndecorateAfter( fcn, arity, after[, thisArg] )\n    Decorates a provided function such that the function's return value is\n    provided as an argument to another function.\n\n    Decorators are intended to be transparent, meaning that, when interfacing\n    with an API, the decorated API should have the same signature (i.e., number\n    of parameters) as the decorated function.\n\n    Thus, a typical value for `arity` is `fcn.length`. This function does not\n    require equality, however, and the `arity` argument is allowed to diverge\n    from that of the decorated function. Specifying a differing `arity` does\n    *not* affect function evaluation behavior, as the returned function passes\n    all provided arguments to the decorated function.\n\n    If the `after` function returns `undefined`, the returned decorator returns\n    the return value of the decorated function `fcn`; otherwise, the returned\n    decorator returns the return value of `after`.\n\n    The returned decorator supports an `arity` less than or equal to `10` (i.e.,\n    the maximum arity of the returned function is `10`). For an arity greater\n    than `10`, the returned function has an arity equal to `0`. While this\n    violates strict notions of a decorator, for all practical purposes, this is\n    unlikely to be an issue, as the vast majority of functions have fewer than\n    `10` parameters and the need for explicitly checking function length is\n    relatively uncommon.\n\n    Common use cases for decorating a function with additional actions *after*\n    invocation include logging, capturing invocation statistics, and validating\n    return values.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to decorate.\n\n    arity: integer\n        Number of parameters.\n\n    after: Function\n        Function with which to invoke the return value of the decorated\n        function.\n\n    thisArg: any (optional)\n        Evaluation context for `after`.\n\n    Returns\n    -------\n    out: Function\n        Decorator function.\n\n    Examples\n    --------\n    > function f( v ) { return -v; };\n    > var fcn = decorateAfter( base.abs, 1, f );\n    > var v = fcn( -5 )\n    -5\n    > v = fcn( 5 )\n    -5\n\n\ndecorateAfter.factory( fcn, arity, after[, thisArg] )\n    Uses code generation to decorate a provided function such that the\n    function's return value is provided as an argument to another function.\n\n    Code generation may be problematic in browser contexts enforcing a strict\n    content security policy] (CSP). If running in or targeting an environment\n    with a CSP, avoid using code generation.\n\n    For non-native functions, the function supports returning a decorator whose\n    API exactly matches the API of the decorated function, including function\n    length and parameter names.\n\n    For native functions, due to how native functions serialize to strings, the\n    function generates placeholder parameter names, which are unlikely to match\n    the canonical parameter names. Using placeholder parameter names ensures\n    that the length of the decorator (i.e., number of parameters) matches the\n    decorated function and, except in scenarios involving function source code\n    inspection, will not affect runtime behavior.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to decorate.\n\n    arity: integer\n        Number of parameters.\n\n    after: Function\n        Function with which to invoke the return value of the decorated\n        function.\n\n    thisArg: any (optional)\n        Evaluation context for `after`.\n\n    Returns\n    -------\n    out: Function\n        Decorator function.\n\n    Examples\n    --------\n    > function f( v ) { return -v; };\n    > var fcn = decorateAfter.factory( base.abs, 1, f );\n    > var v = fcn( -5 )\n    -5\n    > v = fcn( 5 )\n    -5\n\n","decorateAfter.factory":"\ndecorateAfter.factory( fcn, arity, after[, thisArg] )\n    Uses code generation to decorate a provided function such that the\n    function's return value is provided as an argument to another function.\n\n    Code generation may be problematic in browser contexts enforcing a strict\n    content security policy] (CSP). If running in or targeting an environment\n    with a CSP, avoid using code generation.\n\n    For non-native functions, the function supports returning a decorator whose\n    API exactly matches the API of the decorated function, including function\n    length and parameter names.\n\n    For native functions, due to how native functions serialize to strings, the\n    function generates placeholder parameter names, which are unlikely to match\n    the canonical parameter names. Using placeholder parameter names ensures\n    that the length of the decorator (i.e., number of parameters) matches the\n    decorated function and, except in scenarios involving function source code\n    inspection, will not affect runtime behavior.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to decorate.\n\n    arity: integer\n        Number of parameters.\n\n    after: Function\n        Function with which to invoke the return value of the decorated\n        function.\n\n    thisArg: any (optional)\n        Evaluation context for `after`.\n\n    Returns\n    -------\n    out: Function\n        Decorator function.\n\n    Examples\n    --------\n    > function f( v ) { return -v; };\n    > var fcn = decorateAfter.factory( base.abs, 1, f );\n    > var v = fcn( -5 )\n    -5\n    > v = fcn( 5 )\n    -5","deepEqual":"\ndeepEqual( a, b )\n    Tests for deep equality between two values.\n\n    Parameters\n    ----------\n    a: any\n        First comparison value.\n\n    b: any\n        Second comparison value.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating if `a` is deep equal to `b`.\n\n    Examples\n    --------\n    > var bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, 3 ] )\n    true\n\n    > bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, '3' ] )\n    false\n\n    > bool = deepEqual( { 'a': 2 }, { 'a': [ 2 ] } )\n    false\n\n    See Also\n    --------\n    isStrictEqual, isSameValue\n","deepGet":"\ndeepGet( obj, path[, options] )\n    Returns a nested property value.\n\n    Parameters\n    ----------\n    obj: ObjectLike\n        Input object.\n\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    out: any\n        Nested property value.\n\n    Examples\n    --------\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var val = deepGet( obj, 'a.b.c' )\n    'd'\n\n    // Specify a custom separator via the `sep` option:\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var val = deepGet( obj, 'a/b/c', { 'sep': '/' } )\n    'd'\n\ndeepGet.factory( path[, options] )\n    Creates a reusable deep get function.\n\n    Parameters\n    ----------\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    out: Function\n        Deep get factory.\n\n    Examples\n    --------\n    > var dget = deepGet.factory( 'a/b/c', { 'sep': '/' } );\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var val = dget( obj )\n    'd'\n\n    See Also\n    --------\n    deepPluck, deepSet\n","deepGet.factory":"\ndeepGet.factory( path[, options] )\n    Creates a reusable deep get function.\n\n    Parameters\n    ----------\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    out: Function\n        Deep get factory.\n\n    Examples\n    --------\n    > var dget = deepGet.factory( 'a/b/c', { 'sep': '/' } );\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var val = dget( obj )\n    'd'\n\n    See Also\n    --------\n    deepPluck, deepSet","deepHasOwnProp":"\ndeepHasOwnProp( value, path[, options] )\n    Returns a boolean indicating whether an object contains a nested key path.\n\n    The function tests for \"own\" properties and will return `false` for\n    inherited properties.\n\n    Value arguments other than `null` or `undefined` are coerced to objects.\n\n    Key path array elements are coerced to strings.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object has a specified path.\n\n    Examples\n    --------\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var bool = deepHasOwnProp( obj, 'a.b.c' )\n    true\n\n    // Specify a custom separator via the `sep` option:\n    > obj = { 'a': { 'b': { 'c': 'd' } } };\n    > bool = deepHasOwnProp( obj, 'a/b/c', { 'sep': '/' } )\n    true\n\ndeepHasOwnProp.factory( path[, options] )\n    Returns a function which tests whether an object contains a nested key path.\n\n    The returned function tests for \"own\" properties and will return `false` for\n    inherited properties.\n\n    Parameters\n    ----------\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    out: Function\n        Function which tests whether an object contains a nested key path.\n\n    Examples\n    --------\n    > var has = deepHasOwnProp.factory( 'a/b/c', { 'sep': '/' } );\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var bool = has( obj )\n    true\n\n    See Also\n    --------\n    deepHasProp, hasOwnProp, deepGet, deepPluck, deepSet\n","deepHasOwnProp.factory":"\ndeepHasOwnProp.factory( path[, options] )\n    Returns a function which tests whether an object contains a nested key path.\n\n    The returned function tests for \"own\" properties and will return `false` for\n    inherited properties.\n\n    Parameters\n    ----------\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    out: Function\n        Function which tests whether an object contains a nested key path.\n\n    Examples\n    --------\n    > var has = deepHasOwnProp.factory( 'a/b/c', { 'sep': '/' } );\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var bool = has( obj )\n    true\n\n    See Also\n    --------\n    deepHasProp, hasOwnProp, deepGet, deepPluck, deepSet","deepHasProp":"\ndeepHasProp( value, path[, options] )\n    Returns a boolean indicating whether an object contains a nested key path,\n    either own or inherited.\n\n    Value arguments other than `null` or `undefined` are coerced to objects.\n\n    Key path array elements are coerced to strings.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object has a specified path.\n\n    Examples\n    --------\n    > function Foo() { return this; };\n    > Foo.prototype.b = { 'c': 'd' };\n    > var obj = { 'a': new Foo() };\n    > var bool = deepHasProp( obj, 'a.b.c' )\n    true\n\n    // Specify a custom separator via the `sep` option:\n    > bool = deepHasProp( obj, 'a/b/c', { 'sep': '/' } )\n    true\n\ndeepHasProp.factory( path[, options] )\n    Returns a function which tests whether an object contains a nested key path,\n    either own or inherited.\n\n    Parameters\n    ----------\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    out: Function\n        Function which tests whether an object contains a nested key path.\n\n    Examples\n    --------\n    > function Foo() { return this; };\n    > Foo.prototype.b = { 'c': 'd' };\n    > var has = deepHasProp.factory( 'a/b/c', { 'sep': '/' } );\n    > var obj = { 'a': new Foo() };\n    > var bool = has( obj )\n    true\n\n    See Also\n    --------\n    deepHasOwnProp, hasOwnProp, deepGet, deepPluck, deepSet\n","deepHasProp.factory":"\ndeepHasProp.factory( path[, options] )\n    Returns a function which tests whether an object contains a nested key path,\n    either own or inherited.\n\n    Parameters\n    ----------\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    out: Function\n        Function which tests whether an object contains a nested key path.\n\n    Examples\n    --------\n    > function Foo() { return this; };\n    > Foo.prototype.b = { 'c': 'd' };\n    > var has = deepHasProp.factory( 'a/b/c', { 'sep': '/' } );\n    > var obj = { 'a': new Foo() };\n    > var bool = has( obj )\n    true\n\n    See Also\n    --------\n    deepHasOwnProp, hasOwnProp, deepGet, deepPluck, deepSet","deepPluck":"\ndeepPluck( arr, path[, options] )\n    Extracts a nested property value from each element of an object array.\n\n    If a key path does not exist, the function sets the plucked value as\n    `undefined`.\n\n    Extracted values are not cloned.\n\n    Parameters\n    ----------\n    arr: Array\n        Source array.\n\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to return a new data structure. Default:\n        true.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    out: Array\n        Destination array.\n\n    Examples\n    --------\n    > var arr = [\n    ...     { 'a': { 'b': { 'c': 1 } } },\n    ...     { 'a': { 'b': { 'c': 2 } } }\n    ... ];\n    > var out = deepPluck( arr, 'a.b.c' )\n    [ 1, 2 ]\n    > arr = [\n    ...     { 'a': [ 0, 1, 2 ] },\n    ...     { 'a': [ 3, 4, 5 ] }\n    ... ];\n    > out = deepPluck( arr, [ 'a', 1 ] )\n    [ 1, 4 ]\n\n    See Also\n    --------\n    deepGet, deepSet\n","deepSet":"\ndeepSet( obj, path, value[, options] )\n    Sets a nested property value.\n\n    Parameters\n    ----------\n    obj: ObjectLike\n        Input object.\n\n    path: string|Array\n        Key path.\n\n    value: any\n        Value to set.\n\n    options: Object (optional)\n        Options.\n\n    options.create: boolean (optional)\n        Boolean indicating whether to create a path if the key path does not\n        already exist. Default: false.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if the property was successfully set.\n\n    Examples\n    --------\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var bool = deepSet( obj, 'a.b.c', 'beep' )\n    true\n\n    // Specify an alternative separator via the sep option:\n    > obj = { 'a': { 'b': { 'c': 'd' } } };\n    > bool = deepSet( obj, 'a/b/c', 'beep', { 'sep': '/' } );\n    > obj\n    { 'a': { 'b': { 'c': 'beep' } } }\n\n    // To create a key path which does not exist, set the create option to true:\n    > bool = deepSet( obj, 'a.e.c', 'boop', { 'create': true } );\n    > obj\n    { 'a': { 'b': { 'c': 'beep' }, 'e': { 'c': 'boop' } } }\n\n\ndeepSet.factory( path[, options] )\n    Creates a reusable deep set function.\n\n    Parameters\n    ----------\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.create: boolean (optional)\n        Boolean indicating whether to create a path if the key path does not\n        already exist. Default: false.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    out: Function\n        Deep get function.\n\n    Examples\n    --------\n    > var dset = deepSet.factory( 'a/b/c', {\n    ...     'create': true,\n    ...     'sep': '/'\n    ... });\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var bool = dset( obj, 'beep' )\n    true\n    > obj\n    { 'a': { 'b': { 'c': 'beep' } } }\n\n    See Also\n    --------\n    deepGet, deepPluck\n","deepSet.factory":"\ndeepSet.factory( path[, options] )\n    Creates a reusable deep set function.\n\n    Parameters\n    ----------\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.create: boolean (optional)\n        Boolean indicating whether to create a path if the key path does not\n        already exist. Default: false.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    out: Function\n        Deep get function.\n\n    Examples\n    --------\n    > var dset = deepSet.factory( 'a/b/c', {\n    ...     'create': true,\n    ...     'sep': '/'\n    ... });\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var bool = dset( obj, 'beep' )\n    true\n    > obj\n    { 'a': { 'b': { 'c': 'beep' } } }\n\n    See Also\n    --------\n    deepGet, deepPluck","defineMemoizedProperty":"\ndefineMemoizedProperty( obj, prop, descriptor )\n    Defines a memoized object property.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    descriptor: Object\n        Property descriptor.\n\n    descriptor.configurable: boolean (optional)\n        Boolean indicating if property descriptor can be changed and if the\n        property can be deleted from the provided object. Default: false.\n\n    descriptor.enumerable: boolean (optional)\n        Boolean indicating if the property shows up when enumerating object\n        properties. Default: false.\n\n    descriptor.writable: boolean (optional)\n        Boolean indicating if the value associated with the property can be\n        changed with an assignment operator. Default: false.\n\n    descriptor.value: Function\n        Synchronous function whose return value will be memoized and set as the\n        property value.\n\n    Examples\n    --------\n    > var obj = {};\n    > function foo() {\n    ...     return 'bar';\n    ... };\n    > defineMemoizedProperty( obj, 'foo', {\n    ...     'configurable': false,\n    ...     'enumerable': true,\n    ...     'writable': false,\n    ...     'value': foo\n    ... });\n    > obj.foo\n    'bar'\n\n    See Also\n    --------\n    setMemoizedReadOnly, defineProperty\n","defineProperties":"\ndefineProperties( obj, properties )\n    Defines (and/or modifies) object properties.\n\n    The second argument is an object whose own enumerable property values are\n    descriptors for the properties to be defined or modified.\n\n    Property descriptors come in two flavors: data descriptors and accessor\n    descriptors. A data descriptor is a property that has a value, which may or\n    may not be writable. An accessor descriptor is a property described by a\n    getter-setter function pair. A descriptor must be one of these two flavors\n    and cannot be both.\n\n    A property descriptor has the following optional properties:\n\n    - configurable: boolean indicating if property descriptor can be changed and\n    if the property can be deleted from the provided object. Default: false.\n\n    - enumerable: boolean indicating if the property shows up when enumerating\n    object properties. Default: false.\n\n    - writable: boolean indicating if the value associated with the property can\n    be changed with an assignment operator. Default: false.\n\n    - value: property value.\n\n    - get: function which serves as a getter for the property, or, if no getter,\n    undefined. When the property is accessed, a getter function is called\n    without arguments and with the `this` context set to the object through\n    which the property is accessed (which may not be the object on which the\n    property is defined due to inheritance). The return value will be used as\n    the property value. Default: undefined.\n\n    - set: function which serves as a setter for the property, or, if no setter,\n    undefined. When assigning a property value, a setter function is called with\n    one argument (the value being assigned to the property) and with the `this`\n    context set to the object through which the property is assigned. Default: undefined.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the properties.\n\n    properties: Object\n        Object with property descriptors.\n\n    Returns\n    -------\n    obj: Object\n        Object on which properties were defined (and/or modified).\n\n    Examples\n    --------\n    > var obj = {};\n    > defineProperties( obj, {\n    ...     'foo': {\n    ...         'value': 'bar',\n    ...         'writable': false,\n    ...         'configurable': false,\n    ...         'enumerable': true\n    ...     },\n    ...     'baz': {\n    ...         'value': 13\n    ...     }\n    ... });\n    > obj.foo\n    'bar'\n    > obj.baz\n    13\n\n    See Also\n    --------\n    defineProperty, setReadOnly\n","defineProperty":"\ndefineProperty( obj, prop, descriptor )\n    Defines (or modifies) an object property.\n\n    Property descriptors come in two flavors: data descriptors and accessor\n    descriptors. A data descriptor is a property that has a value, which may or\n    may not be writable. An accessor descriptor is a property described by a\n    getter-setter function pair. A descriptor must be one of these two flavors\n    and cannot be both.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    descriptor: Object\n        Property descriptor.\n\n    descriptor.configurable: boolean (optional)\n        Boolean indicating if property descriptor can be changed and if the\n        property can be deleted from the provided object. Default: false.\n\n    descriptor.enumerable: boolean (optional)\n        Boolean indicating if the property shows up when enumerating object\n        properties. Default: false.\n\n    descriptor.writable: boolean (optional)\n        Boolean indicating if the value associated with the property can be\n        changed with an assignment operator. Default: false.\n\n    descriptor.value: any (optional)\n        Property value.\n\n    descriptor.get: Function|void (optional)\n        Function which serves as a getter for the property, or, if no getter,\n        undefined. When the property is accessed, a getter function is called\n        without arguments and with the `this` context set to the object through\n        which the property is accessed (which may not be the object on which the\n        property is defined due to inheritance). The return value will be used\n        as the property value. Default: undefined.\n\n    descriptor.set: Function|void (optional)\n        Function which serves as a setter for the property, or, if no setter,\n        undefined. When assigning a property value, a setter function is called\n        with one argument (the value being assigned to the property) and with\n        the `this` context set to the object through which the property is\n        assigned. Default: undefined.\n\n    Returns\n    -------\n    obj: Object\n        Object on which the property was defined (or modified).\n\n    Examples\n    --------\n    > var obj = {};\n    > defineProperty( obj, 'foo', {\n    ...     'value': 'bar',\n    ...     'enumerable': true,\n    ...     'writable': false\n    ... });\n    > obj.foo = 'boop';\n    > obj\n    { 'foo': 'bar' }\n\n    See Also\n    --------\n    defineProperties, setReadOnly\n","dirname":"\ndirname( path )\n    Returns a directory name.\n\n    Parameters\n    ----------\n    path: string\n        Path.\n\n    Returns\n    -------\n    out: string\n        Directory name.\n\n    Examples\n    --------\n    > var dir = dirname( './foo/bar/index.js' )\n    './foo/bar'\n\n    See Also\n    --------\n    extname\n","dotcase":"\ndotcase( str )\n    Converts a string to dot case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Dot-cased string.\n\n    Examples\n    --------\n    > var out = dotcase( 'Hello World!' )\n    'hello.world'\n    > out = dotcase( 'beep boop' )\n    'beep.boop'\n\n    See Also\n    --------\n    camelcase, kebabcase, pascalcase, snakecase","DoublyLinkedList":"\nDoublyLinkedList()\n    Doubly linked list constructor.\n\n    Returns\n    -------\n    list: Object\n        Doubly linked list.\n\n    list.clear: Function\n        Clears the list.\n\n    list.first: Function\n        Returns the first list node. If the list is empty, the returned value is\n        `undefined`.\n\n    list.insert: Function\n        Inserts a value after a provided list node. For its third argument, the\n        method accepts a location: 'before' or 'after'. Default: 'after'.\n\n    list.iterator: Function\n        Returns an iterator for iterating over a list. If an environment\n        supports Symbol.iterator, the returned iterator is iterable. Note that,\n        in order to prevent confusion arising from list mutation during\n        iteration, a returned iterator **always** iterates over a list\n        \"snapshot\", which is defined as the list of list elements at the time\n        of the method's invocation. For its sole argument, the method accepts a\n        direction: 'forward' or 'reverse'. Default: 'forward'.\n\n    list.last: Function\n        Returns the last list node. If the list is empty, the returned value is\n        `undefined`.\n\n    list.length: integer\n        List length.\n\n    list.pop: Function\n        Removes and returns the last list value. If the list is empty, the\n        returned value is `undefined`.\n\n    list.push: Function\n        Adds a value to the end of the list.\n\n    list.remove: Function\n        Removes a list node from the list.\n\n    list.shift: Function\n        Removes and returns the first list value. If the list is empty, the\n        returned value is `undefined`.\n\n    list.toArray: Function\n        Returns an array of list values.\n\n    list.toJSON: Function\n        Serializes a list as JSON.\n\n    list.unshift: Function\n        Adds a value to the beginning of the list.\n\n    Examples\n    --------\n    > var list = DoublyLinkedList();\n    > list.push( 'foo' ).push( 'bar' );\n    > list.length\n    2\n    > list.pop()\n    'bar'\n    > list.length\n    1\n    > list.pop()\n    'foo'\n    > list.length\n    0\n\n    See Also\n    --------\n    LinkedList, Stack\n","doUntil":"\ndoUntil( fcn, predicate[, thisArg] )\n    Invokes a function until a test condition is true.\n\n    The condition is evaluated *after* executing the provided function; thus,\n    `fcn` *always* executes at least once.\n\n    When invoked, both the predicate function and the function to invoke are\n    provided a single argument:\n\n    - i: iteration number (starting from zero).\n\n    Parameters\n    ----------\n    fcn: Function\n        The function to invoke.\n\n    predicate: Function\n        The predicate function which indicates whether to stop invoking a\n        function.\n\n    thisArg: any (optional)\n        Execution context for the invoked function.\n\n    Examples\n    --------\n    > function predicate( i ) { return ( i >= 5 ); };\n    > function beep( i ) { console.log( 'boop: %d', i ); };\n    > doUntil( beep, predicate )\n    boop: 0\n    boop: 1\n    boop: 2\n    boop: 3\n    boop: 4\n\n    See Also\n    --------\n    doUntilAsync, doUntilEach, doWhile, until, whilst\n","doUntilAsync":"\ndoUntilAsync( fcn, predicate, done[, thisArg] )\n    Invokes a function until a test condition is true.\n\n    The condition is evaluated *after* executing the provided function; thus,\n    `fcn` *always* executes at least once.\n\n    The function to invoke is provided two arguments:\n\n    - i: iteration number (starting from zero).\n    - next: a callback which must be invoked before proceeding to the next\n      iteration.\n\n    The first argument of the `next` callback is an `error` argument. If `fcn`\n    calls the `next` callback with a truthy `error` argument, the function\n    suspends execution and immediately calls the `done` callback for subsequent\n    `error` handling.\n\n    The predicate function is provided two arguments:\n\n    - i: iteration number (starting from one).\n    - clbk: a callback indicating whether to invoke `fcn`.\n\n    The `clbk` function accepts two arguments:\n\n    - error: error argument.\n    - bool: test result.\n\n    If the test result is falsy, the function continues invoking `fcn`;\n    otherwise, the function invokes the `done` callback.\n\n    The `done` callback is invoked with an `error` argument and any arguments\n    passed to the final `next` callback.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Parameters\n    ----------\n    fcn: Function\n        The function to invoke.\n\n    predicate: Function\n        The predicate function which indicates whether to continue invoking a\n        function.\n\n    done: Function\n        Callback to invoke upon completion.\n\n    thisArg: any (optional)\n        Execution context for the invoked function.\n\n    Examples\n    --------\n    > function fcn( i, next ) {\n    ...     setTimeout( onTimeout, i );\n    ...     function onTimeout() {\n    ...         next( null, 'boop'+i );\n    ...     }\n    ... };\n    > function predicate( i, clbk ) { clbk( null, i >= 5 ); };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > doUntilAsync( fcn, predicate, done )\n    boop: 4\n\n    See Also\n    --------\n    doUntil, doWhileAsync, untilAsync, whileAsync\n","doUntilEach":"\ndoUntilEach( collection, fcn, predicate[, thisArg] )\n    Until a test condition is true, invokes a function for each element in a\n    collection.\n\n    The condition is evaluated *after* executing the provided function; thus,\n    `fcn` *always* executes at least once.\n\n    When invoked, both the predicate function and the function to apply are\n    provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    If provided an empty collection, both `value` and `index` are `undefined`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    predicate: Function\n        The predicate function which indicates whether to stop iterating over a\n        collection.\n\n    thisArg: any (optional)\n        Execution context for the applied function.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function predicate( v ) { return v !== v; };\n    > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n    > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n    > doUntilEach( arr, logger, predicate )\n    0: 1\n    1: 2\n    2: 3\n    3: 4\n    4: NaN\n\n    See Also\n    --------\n    doUntilEachRight, doWhileEach, untilEach\n","doUntilEachRight":"\ndoUntilEachRight( collection, fcn, predicate[, thisArg] )\n    Until a test condition is true, invokes a function for each element in a\n    collection, iterating from right to left.\n\n    The condition is evaluated *after* executing the provided function; thus,\n    `fcn` *always* executes at least once.\n\n    When invoked, both the predicate function and the function to apply are\n    provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    If provided an empty collection, both `value` and `index` are `undefined`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    predicate: Function\n        The predicate function which indicates whether to stop iterating over a\n        collection.\n\n    thisArg: any (optional)\n        Execution context for the applied function.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function predicate( v ) { return v !== v; };\n    > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n    > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n    > doUntilEachRight( arr, logger, predicate )\n    5: 5\n    4: 4\n    3: 3\n    2: 2\n    1: NaN\n\n    See Also\n    --------\n    doUntilEach, doWhileEachRight, untilEachRight\n","doWhile":"\ndoWhile( fcn, predicate[, thisArg] )\n    Invokes a function while a test condition is true.\n\n    The condition is evaluated *after* executing the provided function; thus,\n    `fcn` *always* executes at least once.\n\n    When invoked, both the predicate function and the function to invoke are\n    provided a single argument:\n\n    - i: iteration number (starting from zero).\n\n    Parameters\n    ----------\n    fcn: Function\n        The function to invoke.\n\n    predicate: Function\n        The predicate function which indicates whether to continue invoking a\n        function.\n\n    thisArg: any (optional)\n        Execution context for the invoked function.\n\n    Examples\n    --------\n    > function predicate( i ) { return ( i < 5 ); };\n    > function beep( i ) { console.log( 'boop: %d', i ); };\n    > doWhile( beep, predicate )\n    boop: 0\n    boop: 1\n    boop: 2\n    boop: 3\n    boop: 4\n\n    See Also\n    --------\n    doUntil, doWhileAsync, doWhileEach, until, whilst\n","doWhileAsync":"\ndoWhileAsync( fcn, predicate, done[, thisArg] )\n    Invokes a function while a test condition is true.\n\n    The condition is evaluated *after* executing the provided function; thus,\n    `fcn` *always* executes at least once.\n\n    The function to invoke is provided two arguments:\n\n    - i: iteration number (starting from zero).\n    - next: a callback which must be invoked before proceeding to the next\n      iteration.\n\n    The first argument of the `next` callback is an `error` argument. If `fcn`\n    calls the `next` callback with a truthy `error` argument, the function\n    suspends execution and immediately calls the `done` callback for subsequent\n    `error` handling.\n\n    The predicate function is provided two arguments:\n\n    - i: iteration number (starting from one).\n    - clbk: a callback indicating whether to invoke `fcn`.\n\n    The `clbk` function accepts two arguments:\n\n    - error: error argument.\n    - bool: test result.\n\n    If the test result is truthy, the function continues invoking `fcn`;\n    otherwise, the function invokes the `done` callback.\n\n    The `done` callback is invoked with an `error` argument and any arguments\n    passed to the final `next` callback.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Parameters\n    ----------\n    fcn: Function\n        The function to invoke.\n\n    predicate: Function\n        The predicate function which indicates whether to continue invoking a\n        function.\n\n    done: Function\n        Callback to invoke upon completion.\n\n    thisArg: any (optional)\n        Execution context for the invoked function.\n\n    Examples\n    --------\n    > function fcn( i, next ) {\n    ...     setTimeout( onTimeout, i );\n    ...     function onTimeout() {\n    ...         next( null, 'boop'+i );\n    ...     }\n    ... };\n    > function predicate( i, clbk ) { clbk( null, i < 5 ); };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > doWhileAsync( fcn, predicate, done )\n    boop: 4\n\n    See Also\n    --------\n    doUntilAsync, doWhile, untilAsync, whileAsync\n","doWhileEach":"\ndoWhileEach( collection, fcn, predicate[, thisArg] )\n    While a test condition is true, invokes a function for each element in a\n    collection.\n\n    The condition is evaluated *after* executing the provided function; thus,\n    `fcn` *always* executes at least once.\n\n    When invoked, both the predicate function and the function to apply are\n    provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    If provided an empty collection, both `value` and `index` are `undefined`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    predicate: Function\n        The predicate function which indicates whether to continue iterating\n        over a collection.\n\n    thisArg: any (optional)\n        Execution context for the applied function.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === v; };\n    > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n    > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n    > doWhileEach( arr, logger, predicate )\n    0: 1\n    1: 2\n    2: 3\n    3: 4\n    4: NaN\n\n    See Also\n    --------\n    doUntilEach, doWhileEachRight, whileEach\n","doWhileEachRight":"\ndoWhileEachRight( collection, fcn, predicate[, thisArg] )\n    While a test condition is true, invokes a function for each element in a\n    collection, iterating from right to left.\n\n    The condition is evaluated *after* executing the provided function; thus,\n    `fcn` *always* executes at least once.\n\n    When invoked, both the predicate function and the function to apply are\n    provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    If provided an empty collection, both `value` and `index` are `undefined`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    predicate: Function\n        The predicate function which indicates whether to continue iterating\n        over a collection.\n\n    thisArg: any (optional)\n        Execution context for the applied function.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === v; };\n    > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n    > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n    > doWhileEachRight( arr, logger, predicate )\n    5: 5\n    4: 4\n    3: 3\n    2: 2\n    1: NaN\n\n    See Also\n    --------\n    doUntilEachRight, doWhileEach, whileEachRight\n","dswap":"\ndswap( x, y[, dim] )\n    Interchanges two double-precision floating-point vectors.\n\n    For multi-dimensional input arrays, the function performs batched\n    computation, such that the function interchanges each pair of vectors in `x`\n    and `y` according to the specified dimension index.\n\n    Both input arrays must have the same shape.\n\n    Parameters\n    ----------\n    x: ndarray\n        First input array. Must have a 'float64' data type. Must have at least\n        one dimension and must have the same shape as the second input array.\n\n    y: ndarray\n        Second input array. Must have a 'float64' data type. Must have at least\n        one dimension and must have the same shape as the first input array.\n\n    dim: integer (optional)\n        Dimension index along which to interchange vectors. Must be a negative\n        integer. Negative indices are resolved relative to the last array\n        dimension, with the last dimension corresponding to `-1`. Default: -1.\n\n    Returns\n    -------\n    y: ndarray\n        The second input array `y`.\n\n    Examples\n    --------\n    > var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n    > var y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n    > dswap( x, y );\n    > x.data\n    <Float64Array>[ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n    > y.data\n    <Float64Array>[ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dswap, gswap, sswap\n","E":"\nE\n    Euler's number.\n\n    Examples\n    --------\n    > E\n    2.718281828459045\n\n","EMOJI":"\nEMOJI()\n    Returns an emoji database.\n\n    Returns\n    -------\n    out: Array\n        Emoji database.\n\n    Examples\n    --------\n    > var data = EMOJI()\n    [ {...}, ... ]\n\n    See Also\n    --------\n    EMOJI_CODE_PICTO, EMOJI_PICTO_CODE\n","EMOJI_CODE_PICTO":"\nEMOJI_CODE_PICTO()\n    Returns an object mapping emoji codes to pictographs.\n\n    Returns\n    -------\n    out: Object\n        An object mapping emoji codes to pictographs.\n\n    Examples\n    --------\n    > var out = EMOJI_CODE_PICTO()\n\n    See Also\n    --------\n    EMOJI, EMOJI_PICTO_CODE\n","EMOJI_PICTO_CODE":"\nEMOJI_PICTO_CODE()\n    Returns an object mapping emoji pictographs to codes.\n\n    Returns\n    -------\n    out: Object\n        An object mapping emoji pictographs to codes.\n\n    Examples\n    --------\n    > var out = EMOJI_PICTO_CODE()\n\n    See Also\n    --------\n    EMOJI, EMOJI_CODE_PICTO\n","emptyStream":"\nemptyStream( [options] )\n    Returns an \"empty\" readable stream.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var s = emptyStream();\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nemptyStream.factory( [options] )\n    Returns a function for creating empty readable streams.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true };\n    > var createStream = emptyStream.factory( opts );\n\n\nemptyStream.objectMode()\n    Returns an \"objectMode\" empty readable stream.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var s = emptyStream.objectMode();\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    constantStream\n","emptyStream.factory":"\nemptyStream.factory( [options] )\n    Returns a function for creating empty readable streams.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true };\n    > var createStream = emptyStream.factory( opts );","emptyStream.objectMode":"\nemptyStream.objectMode()\n    Returns an \"objectMode\" empty readable stream.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var s = emptyStream.objectMode();\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    constantStream","endsWith":"\nendsWith( str, search[, len] )\n    Tests if a string ends with the characters of another string.\n\n    If provided an empty search string, the function always returns `true`.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search string.\n\n    len: integer (optional)\n        Substring length. Restricts the search to a substring within the input\n        string beginning from the leftmost character. If provided a negative\n        value, `len` indicates to ignore the last `len` characters, returning\n        the same output as `str.length + len`. Default: `str.length`.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a string ends with the characters of another\n        string.\n\n    Examples\n    --------\n    > var bool = endsWith( 'beep', 'ep' )\n    true\n    > bool = endsWith( 'Beep', 'op' )\n    false\n    > bool = endsWith( 'Beep', 'ee', 3 )\n    true\n    > bool = endsWith( 'Beep', 'ee', -1 )\n    true\n    > bool = endsWith( 'beep', '' )\n    true\n\n    See Also\n    --------\n    startsWith\n","enumerableProperties":"\nenumerableProperties( value )\n    Returns an array of an object's own enumerable property names and symbols.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    props: Array\n        List of an object's own enumerable properties.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var props = enumerableProperties( obj )\n    [ 'beep' ]\n\n    See Also\n    --------\n    enumerablePropertiesIn, enumerablePropertySymbols, inheritedEnumerableProperties, objectKeys, nonEnumerableProperties, properties\n","enumerablePropertiesIn":"\nenumerablePropertiesIn( value )\n    Returns an array of an object's own and inherited enumerable property names\n    and symbols.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    props: Array\n        List of an object's own and inherited enumerable property names and\n        symbols.\n\n    Examples\n    --------\n    > var props = enumerablePropertiesIn( [] )\n\n    See Also\n    --------\n    enumerableProperties, enumerablePropertySymbolsIn, inheritedEnumerableProperties, keysIn, nonEnumerablePropertiesIn, propertiesIn\n","enumerablePropertySymbols":"\nenumerablePropertySymbols( value )\n    Returns an array of an object's own enumerable symbol properties.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's own enumerable symbol properties.\n\n    Examples\n    --------\n    > var obj = {};\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = true;\n    > desc.writable = true;\n    > desc.value = 'boop';\n    > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n    > defineProperty( obj, sym, desc );\n    > var symbols = enumerablePropertySymbols( obj )\n\n    See Also\n    --------\n    enumerablePropertySymbolsIn, inheritedEnumerablePropertySymbols, objectKeys, nonEnumerablePropertySymbols, propertySymbols\n","enumerablePropertySymbolsIn":"\nenumerablePropertySymbolsIn( value )\n    Returns an array of an object's own and inherited enumerable symbol\n    properties.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's own and inherited enumerable symbol properties.\n\n    Examples\n    --------\n    > var obj = {};\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = true;\n    > desc.writable = true;\n    > desc.value = 'boop';\n    > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n    > defineProperty( obj, sym, desc );\n    > var symbols = enumerablePropertySymbolsIn( obj )\n\n    See Also\n    --------\n    enumerablePropertySymbols, inheritedEnumerablePropertySymbols, keysIn, nonEnumerablePropertySymbolsIn, propertySymbolsIn\n","ENV":"\nENV\n    An object containing the user environment.\n\n    Examples\n    --------\n    > var user = ENV.USER\n    <string>\n\n    See Also\n    --------\n    ARGV\n","EPS":"\nEPS\n    Difference between one and the smallest value greater than one that can be\n    represented as a double-precision floating-point number.\n\n    Examples\n    --------\n    > EPS\n    2.220446049250313e-16\n\n    See Also\n    --------\n    FLOAT32_EPS\n","error2json":"\nerror2json( error )\n    Returns a JSON representation of an error object.\n\n    The following built-in error types are supported:\n\n    - Error\n    - URIError\n    - ReferenceError\n    - SyntaxError\n    - RangeError\n    - EvalError\n    - TypeError\n\n    The JSON object is guaranteed to have the following properties:\n\n    - type: error type.\n    - message: error message.\n\n    The only standardized cross-platform property is `message`. Depending on the\n    platform, the following properties *may* be present:\n\n    - name: error name.\n    - stack: stack trace.\n    - code: error code (Node.js system errors).\n    - errno: error code string (Node.js system errors).\n    - syscall: string representing the failed system call (Node.js system\n      errors).\n\n    The function also serializes all enumerable properties.\n\n    The implementation supports custom error types and sets the `type` field to\n    the closest built-in error type.\n\n    Parameters\n    ----------\n    error: Error\n        Error to serialize.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var err = new Error( 'beep' );\n    > var json = error2json( err )\n    <Object>\n\n    See Also\n    --------\n    reviveError\n","EULERGAMMA":"\nEULERGAMMA\n    The Euler-Mascheroni constant.\n\n    Examples\n    --------\n    > EULERGAMMA\n    0.5772156649015329\n\n","every":"\nevery( collection )\n    Tests whether all elements in a collection are truthy.\n\n    The function immediately returns upon encountering a falsy value.\n\n    If provided an empty collection, the function returns `true`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if all elements are truthy; otherwise, the\n        function returns `false`.\n\n    Examples\n    --------\n    > var arr = [ 1, 1, 1, 1, 1 ];\n    > var bool = every( arr )\n    true\n\n    See Also\n    --------\n    any, everyBy, forEach, none, some\n","everyBy":"\neveryBy( collection, predicate[, thisArg ] )\n    Tests whether all elements in a collection pass a test implemented by a\n    predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    The function immediately returns upon encountering a non-truthy return\n    value.\n\n    If provided an empty collection, the function returns `true`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns a truthy\n        value for all elements; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function positive( v ) { return ( v > 0 ); };\n    > var arr = [ 1, 2, 3, 4 ];\n    > var bool = everyBy( arr, positive )\n    true\n\n    See Also\n    --------\n    anyBy, everyByRight, forEach, noneBy, someBy\n","everyByAsync":"\neveryByAsync( collection, [options,] predicate, done )\n    Tests whether all elements in a collection pass a test implemented by a\n    predicate function.\n\n    When invoked, the predicate function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If the\n    predicate function accepts two arguments, the predicate function is\n    provided:\n\n    - value\n    - next\n\n    If the predicate function accepts three arguments, the predicate function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other predicate function signature, the predicate function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - result: test result.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    The function immediately returns upon encountering a non-truthy `result`\n    value and calls the `done` callback with `null` as the first argument and\n    `false` as the second argument.\n\n    If all elements succeed, the function calls the `done` callback with `null`\n    as the first argument and `true` as the second argument.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, true );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > everyByAsync( arr, predicate, done )\n    1000\n    2500\n    3000\n    true\n\n    // Limit number of concurrent invocations:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, true );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 3000, 2500, 1000 ];\n    > everyByAsync( arr, opts, predicate, done )\n    2500\n    3000\n    1000\n    true\n\n    // Process sequentially:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, true );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 3000, 2500, 1000 ];\n    > everyByAsync( arr, opts, predicate, done )\n    3000\n    2500\n    1000\n    true\n\n\neveryByAsync.factory( [options,] predicate )\n    Returns a function which tests whether all elements in a collection pass a\n    test implemented by a predicate function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, true );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = everyByAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n\n    See Also\n    --------\n    anyByAsync, everyBy, everyByRightAsync, forEachAsync, noneByAsync, someByAsync\n","everyByAsync.factory":"\neveryByAsync.factory( [options,] predicate )\n    Returns a function which tests whether all elements in a collection pass a\n    test implemented by a predicate function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, true );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = everyByAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n\n    See Also\n    --------\n    anyByAsync, everyBy, everyByRightAsync, forEachAsync, noneByAsync, someByAsync","everyByRight":"\neveryByRight( collection, predicate[, thisArg ] )\n    Tests whether all elements in a collection pass a test implemented by a\n    predicate function, iterating from right to left.\n\n    The predicate function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    The function immediately returns upon encountering a non-truthy return\n    value.\n\n    If provided an empty collection, the function returns `true`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns a truthy\n        value for all elements; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function positive( v ) { return ( v > 0 ); };\n    > var arr = [ 1, 2, 3, 4 ];\n    > var bool = everyByRight( arr, positive )\n    true\n\n    See Also\n    --------\n    anyBy, every, everyBy, forEachRight, noneByRight, someByRight\n","everyByRightAsync":"\neveryByRightAsync( collection, [options,] predicate, done )\n    Tests whether all elements in a collection pass a test implemented by a\n    predicate function, iterating from right to left.\n\n    When invoked, the predicate function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If the\n    predicate function accepts two arguments, the predicate function is\n    provided:\n\n    - value\n    - next\n\n    If the predicate function accepts three arguments, the predicate function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other predicate function signature, the predicate function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - result: test result.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    The function immediately returns upon encountering a non-truthy `result`\n    value and calls the `done` callback with `null` as the first argument and\n    `false` as the second argument.\n\n    If all elements succeed, the function calls the `done` callback with `null`\n    as the first argument and `true` as the second argument.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, true );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > everyByRightAsync( arr, predicate, done )\n    1000\n    2500\n    3000\n    true\n\n    // Limit number of concurrent invocations:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, true );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 1000, 2500, 3000 ];\n    > everyByRightAsync( arr, opts, predicate, done )\n    2500\n    3000\n    1000\n    true\n\n    // Process sequentially:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, true );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 1000, 2500, 3000 ];\n    > everyByRightAsync( arr, opts, predicate, done )\n    3000\n    2500\n    1000\n    true\n\n\neveryByRightAsync.factory( [options,] predicate )\n    Returns a function which tests whether all elements in a collection pass a\n    test implemented by a predicate function, iterating from right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, true );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = everyByRightAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n\n    See Also\n    --------\n    anyByRightAsync, everyByAsync, everyByRight, forEachRightAsync, noneByRightAsync, someByRightAsync\n","everyByRightAsync.factory":"\neveryByRightAsync.factory( [options,] predicate )\n    Returns a function which tests whether all elements in a collection pass a\n    test implemented by a predicate function, iterating from right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, true );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = everyByRightAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n\n    See Also\n    --------\n    anyByRightAsync, everyByAsync, everyByRight, forEachRightAsync, noneByRightAsync, someByRightAsync","everyInBy":"\neveryInBy( object, predicate[, thisArg ] )\n   Test whether all properties (own and inherited) of an object pass a\n   test implemented by a predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: object value.\n    - key: object key.\n    - object: the input object.\n\n    The function immediately returns upon encountering a non-truthy return\n    value.\n\n    If provided an empty object, the function returns `true`.\n\n    Parameters\n    ----------\n    object: Object\n        Input object over which to iterate.\n\n    predicate: Function\n        Test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns a truthy\n        value for all elements; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function positive( v ) { return ( v > 0 ); };\n    > var o = {a: 1, b: 2, c: 3};\n    > var bool = everyInBy( o, positive )\n    true\n\n    See Also\n    --------\n    anyInBy, noneInBy, someInBy, everyBy, everyOwnBy\n","everyOwnBy":"\neveryOwnBy( object, predicate[, thisArg ] )\n    Tests whether every own property of an object pass a test implemented by a\n    predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: property value.\n    - index: property key.\n    - object: the input object.\n\n    The function immediately returns upon encountering a non-truthy return\n    value.\n\n    If provided an empty object, the function returns `true`.\n\n    Parameters\n    ----------\n    object: Object\n        Input object.\n\n    predicate: Function\n        Test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns a truthy\n        value for all elements; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function positive( v ) { return ( v > 0 ); };\n    > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n    > var bool = everyOwnBy( obj, positive )\n    true\n\n    See Also\n    --------\n    anyOwnBy, everyInBy, noneOwnBy, someOwnBy, everyBy\n","evil":"\nevil( str )\n    Alias for `eval` global.\n\n    A reference to `eval` is treated differently by the compiler. For example,\n    when evaluating code containing block-scoped declarations  (e.g., `let`,\n    `const`, `function`, `class`), the compiler may throw an `error` complaining\n    that block-scoped declarations are not yet supported outside of\n    `strict mode`. One possible workaround is to include `\"use strict\";` in the\n    evaluated code.\n\n    Parameters\n    ----------\n    str: string\n        Code to evaluate.\n\n    Returns\n    -------\n    out: any\n        Returned value if applicable.\n\n    Examples\n    --------\n    > var v = evil( '5*4*3*2*1' )\n    120\n\n","EXEC_PATH":"\nEXEC_PATH\n    Absolute pathname of the executable which started the current Node.js\n    process.\n\n    Examples\n    --------\n    > EXEC_PATH\n    <string>\n\n","exists":"\nexists( path, clbk )\n    Asynchronously tests whether a path exists on the filesystem.\n\n    Parameters\n    ----------\n    path: string|Buffer\n        Path to test.\n\n    clbk: Function\n        Callback to invoke after testing for path existence. A callback may\n        accept a single argument, a boolean indicating whether a path exists, or\n        two arguments, an error argument and a boolean, matching the error-first\n        callback convention used in most asynchronous Node.js APIs.\n\n    Examples\n    --------\n    > function done( error, bool ) { console.log( bool ); };\n    > exists( './beep/boop', done );\n\n\nexists.sync( path )\n    Synchronously tests whether a path exists on the filesystem.\n\n    Parameters\n    ----------\n    path: string|Buffer\n        Path to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the path exists.\n\n    Examples\n    --------\n    > var bool = exists.sync( './beep/boop' )\n    <boolean>\n\n    See Also\n    --------\n    readFile, readDir\n","exists.sync":"\nexists.sync( path )\n    Synchronously tests whether a path exists on the filesystem.\n\n    Parameters\n    ----------\n    path: string|Buffer\n        Path to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the path exists.\n\n    Examples\n    --------\n    > var bool = exists.sync( './beep/boop' )\n    <boolean>\n\n    See Also\n    --------\n    readFile, readDir","expandAcronyms":"\nexpandAcronyms( str )\n    Expands acronyms in a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        String with expanded acronyms.\n\n    Examples\n    --------\n    > var str = 'LOL, this is fun. I am ROFL.';\n    > var out = expandAcronyms( str )\n    'laughing out loud, this is fun. I am rolling on the floor laughing.'\n\n    > str = 'brb, I need to check my mail. thx!';\n    > out = expandAcronyms( str )\n    'be right back, I need to check my mail. thanks!'\n\n    See Also\n    --------\n    expandContractions\n","expandContractions":"\nexpandContractions( str )\n    Expands all contractions to their formal equivalents.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        String with expanded contractions.\n\n    Examples\n    --------\n    > var str = 'I won\\'t be able to get y\\'all out of this one.';\n    > var out = expandContractions( str )\n    'I will not be able to get you all out of this one.'\n\n    > str = 'It oughtn\\'t to be my fault, because, you know, I didn\\'t know';\n    > out = expandContractions( str )\n    'It ought not to be my fault, because, you know, I did not know'\n\n","extname":"\nextname( filename )\n    Returns a filename extension.\n\n    Parameters\n    ----------\n    filename: string\n        Filename.\n\n    Returns\n    -------\n    ext: string\n        Filename extension.\n\n    Examples\n    --------\n    > var ext = extname( 'index.js' )\n    '.js'\n\n    See Also\n    --------\n    dirname\n","FancyArray":"\nFancyArray( dtype, buffer, shape, strides, offset, order[, options] )\n    Returns a FancyArray instance.\n\n    A FancyArray is an ndarray which supports slicing via indexing expressions.\n\n    A FancyArray is an ndarray instance and supports all ndarray options,\n    attributes, and methods. A FancyArray can be consumed by any API which\n    supports ndarray instances.\n\n    Indexing expressions provide a convenient and powerful means for creating\n    and operating on ndarray views; however, their use does entail a performance\n    cost. Indexing expressions are best suited for interactive use and\n    scripting. For performance critical applications, prefer equivalent\n    functional APIs supporting ndarray instances.\n\n    In older JavaScript environments which do not support Proxy objects, the use\n    of indexing expressions is not supported.\n\n    Parameters\n    ----------\n    dtype: string\n        Underlying data type.\n\n    buffer: ArrayLikeObject|TypedArray|Buffer\n        Data buffer. A data buffer must be an array-like object (i.e., have a\n        `length` property). For data buffers which are not indexed collections\n        (i.e., collections which cannot support direct index access, such as\n        `buffer[ index ]`; e.g., Complex64Array, Complex128Array, etc), a data\n        buffer should provide `#.get( idx )` and `#.set( v[, idx] )` methods.\n        Note that, for `set` methods, the value to set should be the first\n        argument, followed by the linear index, similar to the native typed\n        array `set` method.\n\n    shape: ArrayLikeObject<integer>\n        Array shape.\n\n    strides: ArrayLikeObject<integer>\n        Array strides.\n\n    offset: integer\n        Index offset.\n\n    order: string\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran-style).\n\n    options: Object (optional)\n        Options.\n\n    options.mode: string (optional)\n        Specifies how to handle indices which exceed array dimensions. If equal\n        to 'throw', an ndarray instance throws an error when an index exceeds\n        array dimensions. If equal to 'normalize', an ndarray instance\n        normalizes negative indices and throws an error when an index exceeds\n        array dimensions. If equal to 'wrap', an ndarray instance wraps around\n        indices exceeding array dimensions using modulo arithmetic. If equal to\n        'clamp', an ndarray instance sets an index exceeding array dimensions\n        to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n    options.submode: Array<string> (optional)\n        Specifies how to handle subscripts which exceed array dimensions. If a\n        mode for a corresponding dimension is equal to 'throw', an ndarray\n        instance throws an error when a subscript exceeds array dimensions. If\n        equal to 'normalize', an ndarray instance normalizes negative\n        subscripts and throws an error when a subscript exceeds array\n        dimensions. If equal to 'wrap', an ndarray instance wraps around\n        subscripts exceeding array dimensions using modulo arithmetic. If equal\n        to 'clamp', an ndarray instance sets a subscript exceeding array\n        dimensions to either `0` (minimum index) or the maximum index. If the\n        number of modes is fewer than the number of dimensions, the function\n        recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether an array should be read-only. Default: false.\n\n    Returns\n    -------\n    ndarray: FancyArray\n        FancyArray instance.\n\n    Examples\n    --------\n    // Create a new instance...\n    > var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\n    > var d = [ 2, 2 ]; // shape\n    > var s = [ 2, 1 ]; // strides\n    > var o = 0; // index offset\n    > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' )\n    <FancyArray>\n\n    // Get an element using subscripts:\n    > var v = arr.get( 1, 1 )\n    4.0\n\n    // Get an element using a linear index:\n    > v = arr.iget( 3 )\n    4.0\n\n    // Set an element using subscripts:\n    > arr.set( 1, 1, 40.0 );\n    > arr.get( 1, 1 )\n    40.0\n\n    // Set an element using a linear index:\n    > arr.iset( 3, 99.0 );\n    > arr.get( 1, 1 )\n    99.0\n\n\nFancyArray.prototype.byteLength\n    Size (in bytes) of the array (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of the array.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.byteLength\n    32\n\n\nFancyArray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.BYTES_PER_ELEMENT\n    8\n\n\nFancyArray.prototype.data\n    Pointer to the underlying data buffer.\n\n    Returns\n    -------\n    buf: ArrayLikeObject|TypedArray|Buffer\n        Underlying data buffer.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var buf = arr.data\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n\nFancyArray.prototype.dtype\n    Underlying data type.\n\n    Returns\n    -------\n    dtype: string\n        Underlying data type.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var dt = arr.dtype\n    'float64'\n\n\nFancyArray.prototype.flags\n    Meta information, such as information concerning the memory layout of the\n    array.\n\n    Returns\n    -------\n    flags: Object\n        Info object.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var fl = arr.flags\n    {...}\n\n\nFancyArray.prototype.length\n    Length of the array (i.e., number of elements).\n\n    Returns\n    -------\n    len: integer\n        Array length.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var len = arr.length\n    4\n\n\nFancyArray.prototype.ndims\n    Number of dimensions.\n\n    Returns\n    -------\n    ndims: integer\n        Number of dimensions.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var n = arr.ndims\n    2\n\n\nFancyArray.prototype.offset\n    Index offset which specifies the buffer index at which to start iterating\n    over array elements.\n\n    Returns\n    -------\n    offset: integer\n        Index offset.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.offset\n    0\n\n\nFancyArray.prototype.order\n    Array order.\n\n    The array order is either row-major (C-style) or column-major (Fortran-\n    style).\n\n    Returns\n    -------\n    order: string\n        Array order.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var ord = arr.order\n    'row-major'\n\n\nFancyArray.prototype.shape\n    Array shape.\n\n    Returns\n    -------\n    shape: Array\n        Array shape.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var sh = arr.shape\n    [ 2, 2 ]\n\n\nFancyArray.prototype.strides\n    Index strides which specify how to access data along corresponding array\n    dimensions.\n\n    Returns\n    -------\n    strides: Array\n        Index strides.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var st = arr.strides\n    [ 2, 1 ]\n\n\nFancyArray.prototype.get( ...idx )\n    Returns an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.get( 1, 1 )\n    4.0\n\n\nFancyArray.prototype.iget( idx )\n    Returns an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the input argument is ignored and, for clarity,\n    should not be provided.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.iget( 3 )\n    4.0\n\n\nFancyArray.prototype.set( ...idx, v )\n    Sets an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: FancyArray\n        FancyArray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > arr.set( 1, 1, -4.0 );\n    > arr.get( 1, 1 )\n    -4.0\n\n\nFancyArray.prototype.iset( idx, v )\n    Sets an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the first, and only, argument should be the\n    value to set.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: FancyArray\n        FancyArray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > arr.iset( 3, -4.0 );\n    > arr.iget( 3 )\n    -4.0\n\n\nFancyArray.prototype.toString()\n    Serializes a FancyArray as a string.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    str: string\n        Serialized ndarray string.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toString()\n    '...'\n\n\nFancyArray.prototype.toJSON()\n    Serializes a FancyArray as a JSON object.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toJSON()\n    {...}\n\n    See Also\n    --------\n    array, ndarray\n","FancyArray.prototype.byteLength":"\nFancyArray.prototype.byteLength\n    Size (in bytes) of the array (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of the array.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.byteLength\n    32","FancyArray.prototype.BYTES_PER_ELEMENT":"\nFancyArray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.BYTES_PER_ELEMENT\n    8","FancyArray.prototype.data":"\nFancyArray.prototype.data\n    Pointer to the underlying data buffer.\n\n    Returns\n    -------\n    buf: ArrayLikeObject|TypedArray|Buffer\n        Underlying data buffer.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var buf = arr.data\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]","FancyArray.prototype.dtype":"\nFancyArray.prototype.dtype\n    Underlying data type.\n\n    Returns\n    -------\n    dtype: string\n        Underlying data type.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var dt = arr.dtype\n    'float64'","FancyArray.prototype.flags":"\nFancyArray.prototype.flags\n    Meta information, such as information concerning the memory layout of the\n    array.\n\n    Returns\n    -------\n    flags: Object\n        Info object.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var fl = arr.flags\n    {...}","FancyArray.prototype.length":"\nFancyArray.prototype.length\n    Length of the array (i.e., number of elements).\n\n    Returns\n    -------\n    len: integer\n        Array length.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var len = arr.length\n    4","FancyArray.prototype.ndims":"\nFancyArray.prototype.ndims\n    Number of dimensions.\n\n    Returns\n    -------\n    ndims: integer\n        Number of dimensions.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var n = arr.ndims\n    2","FancyArray.prototype.offset":"\nFancyArray.prototype.offset\n    Index offset which specifies the buffer index at which to start iterating\n    over array elements.\n\n    Returns\n    -------\n    offset: integer\n        Index offset.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.offset\n    0","FancyArray.prototype.order":"\nFancyArray.prototype.order\n    Array order.\n\n    The array order is either row-major (C-style) or column-major (Fortran-\n    style).\n\n    Returns\n    -------\n    order: string\n        Array order.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var ord = arr.order\n    'row-major'","FancyArray.prototype.shape":"\nFancyArray.prototype.shape\n    Array shape.\n\n    Returns\n    -------\n    shape: Array\n        Array shape.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var sh = arr.shape\n    [ 2, 2 ]","FancyArray.prototype.strides":"\nFancyArray.prototype.strides\n    Index strides which specify how to access data along corresponding array\n    dimensions.\n\n    Returns\n    -------\n    strides: Array\n        Index strides.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var st = arr.strides\n    [ 2, 1 ]","FancyArray.prototype.get":"\nFancyArray.prototype.get( ...idx )\n    Returns an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.get( 1, 1 )\n    4.0","FancyArray.prototype.iget":"\nFancyArray.prototype.iget( idx )\n    Returns an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the input argument is ignored and, for clarity,\n    should not be provided.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.iget( 3 )\n    4.0","FancyArray.prototype.set":"\nFancyArray.prototype.set( ...idx, v )\n    Sets an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: FancyArray\n        FancyArray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > arr.set( 1, 1, -4.0 );\n    > arr.get( 1, 1 )\n    -4.0","FancyArray.prototype.iset":"\nFancyArray.prototype.iset( idx, v )\n    Sets an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the first, and only, argument should be the\n    value to set.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: FancyArray\n        FancyArray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > arr.iset( 3, -4.0 );\n    > arr.iget( 3 )\n    -4.0","FancyArray.prototype.toString":"\nFancyArray.prototype.toString()\n    Serializes a FancyArray as a string.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    str: string\n        Serialized ndarray string.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toString()\n    '...'","FancyArray.prototype.toJSON":"\nFancyArray.prototype.toJSON()\n    Serializes a FancyArray as a JSON object.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toJSON()\n    {...}\n\n    See Also\n    --------\n    array, ndarray","fastmath.abs":"\nfastmath.abs( x )\n    Computes an absolute value.\n\n    This implementation is not IEEE 754 compliant. If provided `-0`, the\n    function returns `-0`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    out: number\n        Absolute value.\n\n    Examples\n    --------\n    > var v = fastmath.abs( -1.0 )\n    1.0\n    > v = fastmath.abs( 2.0 )\n    2.0\n    > v = fastmath.abs( 0.0 )\n    0.0\n    > v = fastmath.abs( -0.0 )\n    -0.0\n    > v = fastmath.abs( NaN )\n    NaN\n\n    See Also\n    --------\n    base.abs\n","fastmath.acosh":"\nfastmath.acosh( x )\n    Computes the hyperbolic arccosine of a number.\n\n    The domain of `x` is restricted to `[1,+infinity)`. If `x < 1`, the function\n    will return `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    out: number\n        Hyperbolic arccosine (in radians).\n\n    Examples\n    --------\n    > var v = fastmath.acosh( 1.0 )\n    0.0\n    > v = fastmath.acosh( 2.0 )\n    ~1.317\n    > v = fastmath.acosh( NaN )\n    NaN\n\n    // The function overflows for large `x`:\n    > v = fastmath.acosh( 1.0e308 )\n    Infinity\n\n    See Also\n    --------\n    base.acosh\n","fastmath.ampbm":"\nfastmath.ampbm( x, y )\n    Computes the hypotenuse using the alpha max plus beta min algorithm.\n\n    The algorithm computes only an approximation.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Hypotenuse.\n\n    Examples\n    --------\n    > var h = fastmath.ampbm( 5.0, 12.0 )\n    ~13.514\n\n\nfastmath.ampbm.factory( alpha, beta, [nonnegative[, ints]] )\n    Returns a function to compute a hypotenuse using the alpha max plus beta min\n    algorithm.\n\n    Parameters\n    ----------\n    alpha: number\n        Alpha.\n\n    beta: number\n        Beta.\n\n    nonnegative: boolean (optional)\n        Boolean indicating whether input values are always nonnegative.\n\n    ints: boolean (optional)\n        Boolean indicating whether input values are always 32-bit integers.\n\n    Returns\n    -------\n    fcn: Function\n        Function to compute a hypotenuse.\n\n    Examples\n    --------\n    > var hypot = fastmath.ampbm.factory( 1.0, 0.5 )\n    <Function>\n\n    See Also\n    --------\n    base.hypot\n","fastmath.ampbm.factory":"\nfastmath.ampbm.factory( alpha, beta, [nonnegative[, ints]] )\n    Returns a function to compute a hypotenuse using the alpha max plus beta min\n    algorithm.\n\n    Parameters\n    ----------\n    alpha: number\n        Alpha.\n\n    beta: number\n        Beta.\n\n    nonnegative: boolean (optional)\n        Boolean indicating whether input values are always nonnegative.\n\n    ints: boolean (optional)\n        Boolean indicating whether input values are always 32-bit integers.\n\n    Returns\n    -------\n    fcn: Function\n        Function to compute a hypotenuse.\n\n    Examples\n    --------\n    > var hypot = fastmath.ampbm.factory( 1.0, 0.5 )\n    <Function>\n\n    See Also\n    --------\n    base.hypot","fastmath.asinh":"\nfastmath.asinh( x )\n    Computes the hyperbolic arcsine of a number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    out: number\n        Hyperbolic arcsine (in radians).\n\n    Examples\n    --------\n    > var v = fastmath.asinh( 0.0 )\n    0.0\n    > v = fastmath.asinh( 2.0 )\n    ~1.444\n    > v = fastmath.asinh( -2.0 )\n    ~-1.444\n    > v = fastmath.asinh( NaN )\n    NaN\n\n    // The function overflows for large `x`:\n    > v = fastmath.asinh( 1.0e200 )\n    Infinity\n\n    // The function underflows for small `x`:\n    > v = fastmath.asinh( 1.0e-50 )\n    0.0\n\n    See Also\n    --------\n    base.asinh\n","fastmath.atanh":"\nfastmath.atanh( x )\n    Computes the hyperbolic arctangent of a number.\n\n    The domain of `x` is restricted to `[-1,1]`. If `|x| > 1`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    out: number\n        Hyperbolic arctangent (in radians).\n\n    Examples\n    --------\n    > var v = fastmath.atanh( 0.0 )\n    0.0\n    > v = fastmath.atanh( 0.9 )\n    ~1.472\n    > v = fastmath.atanh( 1.0 )\n    Infinity\n    > v = fastmath.atanh( -1.0 )\n    -Infinity\n    > v = fastmath.atanh( NaN )\n    NaN\n\n    // The function underflows for small `x`:\n    > v = fastmath.atanh( 1.0e-17 )\n    0.0\n\n    See Also\n    --------\n    base.atanh\n","fastmath.hypot":"\nfastmath.hypot( x, y )\n    Computes the hypotenuse.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Hypotenuse.\n\n    Examples\n    --------\n    > var h = fastmath.hypot( -5.0, 12.0 )\n    13.0\n\n    // For a sufficiently large `x` and/or `y`, the function overflows:\n    > h = fastmath.hypot( 1.0e154, 1.0e154 )\n    Infinity\n\n    // For sufficiently small `x` and/or `y`, the function underflows:\n    > h = fastmath.hypot( 1e-200, 1.0e-200 )\n    0.0\n\n    See Also\n    --------\n    base.hypot\n","fastmath.log2Uint32":"\nfastmath.log2Uint32( x )\n    Returns an approximate binary logarithm (base two) of an unsigned 32-bit\n    integer `x`.\n\n    This function provides a performance boost when requiring only approximate\n    computations for integer arguments.\n\n    For high-precision applications, this function is never suitable.\n\n    Parameters\n    ----------\n    x: uinteger\n        Input value.\n\n    Returns\n    -------\n    out: uinteger\n        Integer binary logarithm (base two).\n\n    Examples\n    --------\n    > var v = fastmath.log2Uint32( 4 >>> 0 )\n    2\n    > v = fastmath.log2Uint32( 8 >>> 0 )\n    3\n    > v = fastmath.log2Uint32( 9 >>> 0 )\n    3\n\n    See Also\n    --------\n    base.log2\n","fastmath.max":"\nfastmath.max( x, y )\n    Returns the maximum value.\n\n    The function ignores the sign of `0` and does not check for `NaN` arguments.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    > var v = fastmath.max( 3.14, 4.2 )\n    4.2\n    > v = fastmath.max( 3.14, NaN )\n    NaN\n    > v = fastmath.max( NaN, 3.14 )\n    3.14\n    > v = fastmath.max( -0.0, +0.0 )\n    +0.0\n    > v = fastmath.max( +0.0, -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.max\n","fastmath.min":"\nfastmath.min( x, y )\n    Returns the minimum value.\n\n    The function ignores the sign of `0` and does not check for `NaN` arguments.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    > var v = fastmath.min( 3.14, 4.2 )\n    3.14\n    > v = fastmath.min( 3.14, NaN )\n    NaN\n    > v = fastmath.min( NaN, 3.14 )\n    3.14\n    > v = fastmath.min( -0.0, +0.0 )\n    +0.0\n    > v = fastmath.min( +0.0, -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.min\n","fastmath.powint":"\nfastmath.powint( x, y )\n    Evaluates the exponential function given a signed 32-bit integer exponent.\n\n    This function is not recommended for high-precision applications due to\n    error accumulation.\n\n    If provided a negative exponent, the function first computes the reciprocal\n    of the base and then evaluates the exponential function. This can introduce\n    significant error.\n\n    Parameters\n    ----------\n    x: number\n        Base.\n\n    y: integer\n        Signed 32-bit integer exponent.\n\n    Returns\n    -------\n    out: number\n        Function value.\n\n    Examples\n    --------\n    > var v = fastmath.powint( 2.0, 3 )\n    8.0\n    > v = fastmath.powint( 3.14, 0 )\n    1.0\n    > v = fastmath.powint( 2.0, -2 )\n    0.25\n    > v = fastmath.powint( 0.0, 0 )\n    1.0\n    > v = fastmath.powint( -3.14, 1 )\n    -3.14\n    > v = fastmath.powint( NaN, 0 )\n    NaN\n\n    See Also\n    --------\n    base.pow\n","fastmath.sqrtUint32":"\nfastmath.sqrtUint32( x )\n    Returns an approximate square root of an unsigned 32-bit integer `x`.\n\n    Prefer hardware `sqrt` over a software implementation.\n\n    When using a software `sqrt`, this function provides a performance boost\n    when an application requires only approximate computations for integer\n    arguments.\n\n    For applications requiring high-precision, this function is never suitable.\n\n    Parameters\n    ----------\n    x: uinteger\n        Input value.\n\n    Returns\n    -------\n    out: uinteger\n        Integer square root.\n\n    Examples\n    --------\n    > var v = fastmath.sqrtUint32( 9 >>> 0 )\n    3\n    > v = fastmath.sqrtUint32( 2 >>> 0 )\n    1\n    > v = fastmath.sqrtUint32( 3 >>> 0 )\n    1\n    > v = fastmath.sqrtUint32( 0 >>> 0 )\n    0\n\n    See Also\n    --------\n    base.sqrt\n","FEMALE_FIRST_NAMES_EN":"\nFEMALE_FIRST_NAMES_EN()\n    Returns a list of common female first names in English speaking countries.\n\n    Returns\n    -------\n    out: Array<string>\n        List of common female first names.\n\n    Examples\n    --------\n    > var list = FEMALE_FIRST_NAMES_EN()\n    [ 'Aaren', 'Aarika', 'Abagael', 'Abagail', ... ]\n\n    References\n    ----------\n    - Ward, Grady. 2002. \"Moby Word II.\" <http://www.gutenberg.org/files/3201/\n    3201.txt>.\n\n    See Also\n    --------\n    MALE_FIRST_NAMES_EN\n","FIFO":"\nFIFO()\n    First-in-first-out (FIFO) queue constructor.\n\n    Returns\n    -------\n    queue: Object\n        First-in-first-out queue.\n\n    queue.clear: Function\n        Clears the queue.\n\n    queue.first: Function\n        Returns the \"oldest\" queue value (i.e., the value which is \"first-out\").\n        If the queue is empty, the returned value is `undefined`.\n\n    queue.iterator: Function\n        Returns an iterator for iterating over a queue. If an environment\n        supports Symbol.iterator, the returned iterator is iterable. Note that,\n        in order to prevent confusion arising from queue mutation during\n        iteration, a returned iterator **always** iterates over a queue\n        \"snapshot\", which is defined as the list of queue elements at the time\n        of the method's invocation.\n\n    queue.last: Function\n        Returns the \"newest\" queue value (i.e., the value which is \"last-out\").\n        If the queue is empty, the returned value is `undefined`.\n\n    queue.length: integer\n        Queue length.\n\n    queue.pop: Function\n        Removes and returns the current \"first-out\" value from the queue. If the\n        queue is empty, the returned value is `undefined`.\n\n    queue.push: Function\n        Adds a value to the queue.\n\n    queue.toArray: Function\n        Returns an array of queue values.\n\n    queue.toJSON: Function\n        Serializes a queue as JSON.\n\n    Examples\n    --------\n    > var q = FIFO();\n    > q.push( 'foo' ).push( 'bar' );\n    > q.length\n    2\n    > q.pop()\n    'foo'\n    > q.length\n    1\n    > q.pop()\n    'bar'\n    > q.length\n    0\n\n    See Also\n    --------\n    Stack\n","filledarray":"\nfilledarray( [dtype] )\n    Creates a filled array.\n\n    Parameters\n    ----------\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = filledarray()\n    <Float64Array>\n    > arr = filledarray( 'float32' )\n    <Float32Array>\n\n\nfilledarray( value, length[, dtype] )\n    Returns a filled array having a specified length.\n\n    Parameters\n    ----------\n    value: any\n        Fill value.\n\n    length: integer\n        Array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = filledarray( 1.0, 5 )\n    <Float64Array>[ 1.0, 1.0, 1.0, 1.0, 1.0 ]\n    > arr = filledarray( 1, 5, 'int32' )\n    <Int32Array>[ 1, 1, 1, 1, 1 ]\n\n\nfilledarray( value, array[, dtype] )\n    Creates a filled array from another array (or array-like object).\n\n    Parameters\n    ----------\n    value: any\n        Fill value.\n\n    array: ArrayLikeObject\n        Array from which to generate another array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr1 = filledarray( 2.0, [ 0.5, 0.5, 0.5 ] )\n    <Float64Array>[ 2.0, 2.0, 2.0 ]\n    > var arr2 = filledarray( 1.0, arr1, 'float32' )\n    <Float32Array>[ 1.0, 1.0, 1.0 ]\n\n\nfilledarray( value, iterable[, dtype] )\n    Creates a filled array from an iterable.\n\n    Parameters\n    ----------\n    value: any\n        Fill value.\n\n    iterable: Iterable\n        Iterable from which to generate an array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr1 = iterConstant( 3.0, {'iter': 3} );\n    > var arr2 = filledarray( 1.0, arr1, 'float32' )\n    <Float32Array>[ 1.0, 1.0, 1.0 ]\n\n\nfilledarray( value, buffer[, byteOffset[, length]][, dtype] )\n    Returns a filled typed array view of an ArrayBuffer.\n\n    The 'generic' array data type is *not* supported.\n\n    Parameters\n    ----------\n    value: any\n        Fill value.\n\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 16 );\n    > var arr = filledarray( 1.0, buf, 0, 4, 'float32' )\n    <Float32Array>[ 1.0, 1.0, 1.0, 1.0 ]\n\n    See Also\n    --------\n    filledarrayBy, typedarray\n","filledarrayBy":"\nfilledarrayBy( [dtype] )\n    Creates a filled array.\n\n    Parameters\n    ----------\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = filledarrayBy()\n    <Float64Array>\n    > arr = filledarrayBy( 'float32' )\n    <Float32Array>\n\n\nfilledarrayBy( length[, dtype], clbk[, thisArg] )\n    Returns a filled array according to a provided callback function and having\n    a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > function clbk() { return 1.0; };\n    > var arr = filledarrayBy( 5, clbk )\n    <Float64Array>[ 1.0, 1.0, 1.0, 1.0, 1.0 ]\n    > arr = filledarrayBy( 5, 'int32', clbk )\n    <Int32Array>[ 1, 1, 1, 1, 1 ]\n\n\nfilledarrayBy( array[, dtype], clbk[, thisArg] )\n    Creates a filled array from another array (or array-like object) according\n    to a provided callback function.\n\n    Parameters\n    ----------\n    array: ArrayLikeObject\n        Array from which to generate another array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr1 = filledarrayBy( [ 0.5, 0.5, 0.5 ], constantFunction( 2.0 ) )\n    <Float64Array>[ 2.0, 2.0, 2.0 ]\n    > var arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\n    <Float32Array>[ 1.0, 1.0, 1.0 ]\n\n\nfilledarrayBy( iterable[, dtype], clbk[, thisArg] )\n    Creates a filled array from an iterable according to a provided callback\n    function.\n\n    Parameters\n    ----------\n    iterable: Iterable\n        Iterable from which to generate an array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr1 = iterConstant( 3.0, {'iter': 3} );\n    > var arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\n    <Float32Array>[ 1.0, 1.0, 1.0 ]\n\n\nfilledarrayBy( buffer[, byteOffset[, length]][, dtype], clbk[, thisArg] )\n    Returns a filled typed array view of an ArrayBuffer according to a provided\n    callback function.\n\n    The 'generic' array data type is *not* supported.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 16 );\n    > var arr = filledarrayBy( buf, 0, 4, 'float32', constantFunction( 1.0 ) )\n    <Float32Array>[ 1.0, 1.0, 1.0, 1.0 ]\n\n    See Also\n    --------\n    filledarray, typedarray\n","filterArguments":"\nfilterArguments( fcn, predicate[, thisArg] )\n    Returns a function that applies arguments to a provided function according\n    to a predicate function.\n\n    Only those arguments in which the predicate function returns a truthy value\n    are applied to a provided function.\n\n    The predicate function is provided the following arguments:\n\n    - value: argument value.\n    - index: argument index.\n\n    Parameters\n    ----------\n    fcn: Function\n        Input function.\n\n    predicate: Function\n        Predicate function.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Function\n        Function wrapper.\n\n    Examples\n    --------\n    > function foo( a, b ) { return [ a, b ]; };\n    > function predicate( v ) { return ( v !== 2 ); };\n    > var bar = filterArguments( foo, predicate );\n    > var out = bar( 1, 2, 3 )\n    [ 1, 3 ]\n\n    See Also\n    --------\n    maskArguments, rejectArguments, reorderArguments, reverseArguments\n","find":"\nfind( arr, [options,] clbk )\n    Finds elements in an array-like object that satisfy a test condition.\n\n    Parameters\n    ----------\n    arr: Array|TypedArray|string\n        Object from which elements will be tested.\n\n    options: Object (optional)\n        Options.\n\n    options.k: integer (optional)\n        Limits the number of returned elements. The sign determines the\n        direction in which to search. If set to a negative integer, the function\n        searches from last element to first element. Default: arr.length.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `indices`, indices are returned; if\n        `*`, both indices and values are returned. Default: 'indices'.\n\n    clbk: Function\n        Function invoked for each array element. If the return value is truthy,\n        the value is considered to have satisfied the test condition.\n\n    Returns\n    -------\n    out: Array\n        Array of indices, element values, or arrays of index-value pairs.\n\n    Examples\n    --------\n    > var data = [ 30, 20, 50, 60, 10 ];\n    > function condition( val ) { return val > 20; };\n    > var vals = find( data, condition )\n    [ 0, 2, 3 ]\n\n    // Limit number of results:\n    > data = [ 30, 20, 50, 60, 10 ];\n    > var opts = { 'k': 2, 'returns': 'values' };\n    > vals = find( data, opts, condition )\n    [ 30, 50 ]\n\n    // Return both indices and values as index-value pairs:\n    > data = [ 30, 20, 50, 60, 10 ];\n    > opts = { 'k': -2, 'returns': '*' };\n    > vals = find( data, opts, condition )\n    [ [ 3, 60 ], [ 2, 50 ] ]\n\n","firstChar":"\nfirstChar( str[, n][, options] )\n    Returns the first character(s) of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer (optional)\n        Number of characters to return. Default: 1.\n\n    options: Object (optional)\n        Options.\n\n    options.mode: string (optional)\n        Type of characters to return. The following modes are supported:\n\n        - grapheme: grapheme clusters. Appropriate for strings containing visual\n          characters which can span multiple Unicode code points (e.g., emoji).\n        - code_point: Unicode code points. Appropriate for strings containing\n          visual characters which are comprised of more than one Unicode code\n          unit (e.g., ideographic symbols and punctuation and mathematical\n          alphanumerics).\n        - code_unit': UTF-16 code units. Appropriate for strings containing\n          visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n          common characters, such as those from the Latin, Greek, and Cyrillic\n          alphabets).\n\n        Default: 'grapheme'.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = firstChar( 'beep' )\n    'b'\n    > out = firstChar( 'Boop', 1 )\n    'B'\n    > out = firstChar( 'foo bar', 5 )\n    'foo b'\n\n    See Also\n    --------\n    removeFirst, last\n","FIVETHIRTYEIGHT_FFQ":"\nFIVETHIRTYEIGHT_FFQ()\n    Returns FiveThirtyEight reader responses to a food frequency questionnaire\n    (FFQ).\n\n    Returns\n    -------\n    out: Array<Object>\n        FiveThirtyEight reader responses to a food frequency questionnaire\n        (FFQ).\n\n    Examples\n    --------\n    > var data = FIVETHIRTYEIGHT_FFQ()\n    [ {...}, ... ]\n\n    References\n    ----------\n    - Aschwanden, Christie. 2016. \"You Can't Trust What You Read About\n    Nutrition.\" <https://fivethirtyeight.com/features/you-cant-trust-what-you-\n    read-about-nutrition/>.\n\n    * If you use the data for publication or third party consumption, please\n    cite the listed reference.\n\n","flattenArray":"\nflattenArray( arr[, options] )\n    Flattens an array.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject\n        Input array.\n\n    options: Object (optional)\n        Options.\n\n    options.depth: integer (optional)\n        Maximum depth to flatten.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to deep copy array elements. Default: false.\n\n    Returns\n    -------\n    out: Array\n        Flattened array.\n\n    Examples\n    --------\n    > var arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n    > var out = flattenArray( arr )\n    [ 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n    // Set the maximum depth:\n    > arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n    > out = flattenArray( arr, { 'depth': 2 } )\n    [ 1, 2, 3, [ 4, [ 5 ], 6 ], 7, 8, 9 ]\n    > var bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n    true\n\n    // Deep copy:\n    > arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n    > out = flattenArray( arr, { 'depth': 2, 'copy': true } )\n    [ 1, 2, 3, [ 4, [ 5 ], 6 ], 7, 8, 9 ]\n    > bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n    false\n\n\nflattenArray.factory( dims[, options] )\n    Returns a function for flattening arrays having specified dimensions.\n\n    The returned function does not validate that input arrays actually have the\n    specified dimensions.\n\n    Parameters\n    ----------\n    dims: ArrayLike<integer>\n        Dimensions.\n\n    options: Object (optional)\n        Options.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to deep copy array elements. Default: false.\n\n    Returns\n    -------\n    fcn: Function\n        Flatten function.\n\n    Examples\n    --------\n    > var flatten = flattenArray.factory( [ 2, 2 ], {\n    ...     'copy': false\n    ... });\n    > var out = flatten( [ [ 1, 2 ], [ 3, 4 ] ] )\n    [ 1, 2, 3, 4 ]\n    > out = flatten( [ [ 5, 6 ], [ 7, 8 ] ] )\n    [ 5, 6, 7, 8 ]\n\n    See Also\n    --------\n    flattenObject\n","flattenArray.factory":"\nflattenArray.factory( dims[, options] )\n    Returns a function for flattening arrays having specified dimensions.\n\n    The returned function does not validate that input arrays actually have the\n    specified dimensions.\n\n    Parameters\n    ----------\n    dims: ArrayLike<integer>\n        Dimensions.\n\n    options: Object (optional)\n        Options.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to deep copy array elements. Default: false.\n\n    Returns\n    -------\n    fcn: Function\n        Flatten function.\n\n    Examples\n    --------\n    > var flatten = flattenArray.factory( [ 2, 2 ], {\n    ...     'copy': false\n    ... });\n    > var out = flatten( [ [ 1, 2 ], [ 3, 4 ] ] )\n    [ 1, 2, 3, 4 ]\n    > out = flatten( [ [ 5, 6 ], [ 7, 8 ] ] )\n    [ 5, 6, 7, 8 ]\n\n    See Also\n    --------\n    flattenObject","flattenObject":"\nflattenObject( obj[, options] )\n    Flattens an object.\n\n    Parameters\n    ----------\n    obj: ObjectLike\n        Object to flatten.\n\n    options: Object (optional)\n        Options.\n\n    options.depth: integer (optional)\n        Maximum depth to flatten.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to deep copy. Default: false.\n\n    options.flattenArrays: boolean (optional)\n        Boolean indicating whether to flatten arrays. Default: false.\n\n    options.delimiter: string (optional)\n        Key path delimiter. Default: '.'.\n\n    Returns\n    -------\n    out: ObjectLike\n        Flattened object.\n\n    Examples\n    --------\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var out = flattenObject( obj )\n    { 'a.b.c': 'd' }\n\n    // Set the `depth` option to flatten to a specified depth:\n    > obj = { 'a': { 'b': { 'c': 'd' } } };\n    > out = flattenObject( obj, { 'depth': 1 } )\n    { 'a.b': { 'c': 'd' } }\n    > var bool = ( obj.a.b === out[ 'a.b' ] )\n    true\n\n    // Set the `delimiter` option:\n    > obj = { 'a': { 'b': { 'c': 'd' } } };\n    > out = flattenObject( obj, { 'delimiter': '-|-' } )\n    { 'a-|-b-|-c': 'd' }\n\n    // Flatten arrays:\n    > obj = { 'a': { 'b': [ 1, 2, 3 ] } };\n    > out = flattenObject( obj, { 'flattenArrays': true } )\n    { 'a.b.0': 1, 'a.b.1': 2, 'a.b.2': 3 }\n\n\nflattenObject.factory( [options] )\n    Returns a function to flatten an object.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.depth: integer (optional)\n        Maximum depth to flatten.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to deep copy. Default: false.\n\n    options.flattenArrays: boolean (optional)\n        Boolean indicating whether to flatten arrays. Default: false.\n\n    options.delimiter: string (optional)\n        Key path delimiter. Default: '.'.\n\n    Returns\n    -------\n    fcn: Function\n        Flatten function.\n\n    Examples\n    --------\n    > var flatten = flattenObject.factory({\n    ...     'depth': 1,\n    ...     'copy': true,\n    ...     'delimiter': '|'\n    ... });\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var out = flatten( obj )\n    { 'a|b': { 'c': 'd' } }\n\n    See Also\n    --------\n    flattenArray\n","flattenObject.factory":"\nflattenObject.factory( [options] )\n    Returns a function to flatten an object.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.depth: integer (optional)\n        Maximum depth to flatten.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to deep copy. Default: false.\n\n    options.flattenArrays: boolean (optional)\n        Boolean indicating whether to flatten arrays. Default: false.\n\n    options.delimiter: string (optional)\n        Key path delimiter. Default: '.'.\n\n    Returns\n    -------\n    fcn: Function\n        Flatten function.\n\n    Examples\n    --------\n    > var flatten = flattenObject.factory({\n    ...     'depth': 1,\n    ...     'copy': true,\n    ...     'delimiter': '|'\n    ... });\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var out = flatten( obj )\n    { 'a|b': { 'c': 'd' } }\n\n    See Also\n    --------\n    flattenArray","flignerTest":"\nflignerTest( ...x[, options] )\n    Computes the Fligner-Killeen test for equal variances.\n\n    Parameters\n    ----------\n    x: ...Array\n        Measured values.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.groups: Array (optional)\n        Array of group indicators.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.method: string\n        Name of test.\n\n    out.df: Object\n        Degrees of freedom.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    // Data from Hollander & Wolfe (1973), p. 116:\n    > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n    > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n    > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n    > var out = flignerTest( x, y, z )\n\n    > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n    ...     3.8, 2.7, 4.0, 2.4,\n    ...     2.8, 3.4, 3.7, 2.2, 2.0\n    ... ];\n    > var groups = [\n    ...     'a', 'a', 'a', 'a', 'a',\n    ...     'b', 'b', 'b', 'b',\n    ...     'c', 'c', 'c', 'c', 'c'\n    ... ];\n    > out = flignerTest( arr, { 'groups': groups } )\n\n    See Also\n    --------\n    bartlettTest\n","FLOAT_WORD_ORDER":"\nFLOAT_WORD_ORDER\n    Platform float word order.\n\n    Possible values:\n\n    - 'little-endian'\n    - 'big-endian'\n    - 'unknown'\n\n    Examples\n    --------\n    > FLOAT_WORD_ORDER\n    <string>\n\n    See Also\n    --------\n    BYTE_ORDER\n","FLOAT16_CBRT_EPS":"\nFLOAT16_CBRT_EPS\n    Cube root of half-precision floating-point epsilon.\n\n    Examples\n    --------\n    > FLOAT16_CBRT_EPS\n    0.09921256574801247\n\n    See Also\n    --------\n    FLOAT16_EPS, FLOAT16_SQRT_EPS, FLOAT32_CBRT_EPS, CBRT_EPS\n","FLOAT16_EPS":"\nFLOAT16_EPS\n    Difference between one and the smallest value greater than one that can be\n    represented as a half-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT16_EPS\n    0.0009765625\n\n    See Also\n    --------\n    FLOAT32_EPS, EPS\n","FLOAT16_EXPONENT_BIAS":"\nFLOAT16_EXPONENT_BIAS\n    The bias of a half-precision floating-point number's exponent.\n\n    Examples\n    --------\n    > FLOAT16_EXPONENT_BIAS\n    15\n\n    See Also\n    --------\n    FLOAT32_EXPONENT_BIAS, FLOAT64_EXPONENT_BIAS\n","FLOAT16_MAX":"\nFLOAT16_MAX\n    Maximum half-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT16_MAX\n    65504.0\n\n    See Also\n    --------\n    FLOAT32_MAX, FLOAT64_MAX\n","FLOAT16_MAX_SAFE_INTEGER":"\nFLOAT16_MAX_SAFE_INTEGER\n    Maximum safe half-precision floating-point integer.\n\n    The maximum safe half-precision floating-point integer is given by\n    `2^11 - 1`.\n\n    Examples\n    --------\n    > FLOAT16_MAX_SAFE_INTEGER\n    2047\n\n    See Also\n    --------\n    FLOAT16_MIN_SAFE_INTEGER, FLOAT32_MAX_SAFE_INTEGER, FLOAT64_MAX_SAFE_INTEGER\n","FLOAT16_MIN_SAFE_INTEGER":"\nFLOAT16_MIN_SAFE_INTEGER\n    Minimum safe half-precision floating-point integer.\n\n    The minimum safe half-precision floating-point integer is given by\n    `-(2^11 - 1)`.\n\n    Examples\n    --------\n    > FLOAT16_MIN_SAFE_INTEGER\n    -2047\n\n    See Also\n    --------\n    FLOAT16_MAX_SAFE_INTEGER, FLOAT32_MIN_SAFE_INTEGER, FLOAT64_MIN_SAFE_INTEGER\n","FLOAT16_NINF":"\nFLOAT16_NINF\n    Half-precision floating-point negative infinity.\n\n    Examples\n    --------\n    > FLOAT16_NINF\n    -Infinity\n\n    See Also\n    --------\n    FLOAT16_PINF, FLOAT32_NINF, NINF\n","FLOAT16_NUM_BYTES":"\nFLOAT16_NUM_BYTES\n    Size (in bytes) of a half-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT16_NUM_BYTES\n    2\n\n    See Also\n    --------\n    FLOAT32_NUM_BYTES, FLOAT64_NUM_BYTES\n","FLOAT16_PINF":"\nFLOAT16_PINF\n    Half-precision floating-point positive infinity.\n\n    Examples\n    --------\n    > FLOAT16_PINF\n    Infinity\n\n    See Also\n    --------\n    FLOAT16_NINF, FLOAT32_PINF, PINF\n","FLOAT16_PRECISION":"\nFLOAT16_PRECISION\n    Effective number of bits in the significand of a half-precision floating-\n    point number.\n\n    The effective number of bits is `10` significand bits plus `1` hidden bit.\n\n    Examples\n    --------\n    > FLOAT16_PRECISION\n    11\n\n    See Also\n    --------\n    FLOAT32_PRECISION, FLOAT64_PRECISION\n","FLOAT16_SMALLEST_NORMAL":"\nFLOAT16_SMALLEST_NORMAL\n    Smallest positive normalized half-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT16_SMALLEST_NORMAL\n    6.103515625e-5\n\n    See Also\n    --------\n    FLOAT16_SMALLEST_SUBNORMAL, FLOAT32_SMALLEST_NORMAL, FLOAT64_SMALLEST_NORMAL\n","FLOAT16_SMALLEST_SUBNORMAL":"\nFLOAT16_SMALLEST_SUBNORMAL\n    Smallest positive denormalized half-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT16_SMALLEST_SUBNORMAL\n    5.960464477539063e-8\n\n    See Also\n    --------\n    FLOAT16_SMALLEST_NORMAL, FLOAT32_SMALLEST_SUBNORMAL, FLOAT64_SMALLEST_SUBNORMAL\n","FLOAT16_SQRT_EPS":"\nFLOAT16_SQRT_EPS\n    Square root of half-precision floating-point epsilon.\n\n    Examples\n    --------\n    > FLOAT16_SQRT_EPS\n    0.03125\n\n    See Also\n    --------\n    FLOAT16_EPS, FLOAT32_SQRT_EPS, SQRT_EPS\n","FLOAT32_ABS_MASK":"\nFLOAT32_ABS_MASK\n    Mask for excluding the sign bit of a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_ABS_MASK\n    2147483647\n    > base.toBinaryStringUint32( FLOAT32_ABS_MASK )\n    '01111111111111111111111111111111'\n\n    See Also\n    --------\n    FLOAT32_EXPONENT_MASK, FLOAT32_SIGN_MASK, FLOAT32_SIGNIFICAND_MASK\n","FLOAT32_CBRT_EPS":"\nFLOAT32_CBRT_EPS\n    Cube root of single-precision floating-point epsilon.\n\n    Examples\n    --------\n    > FLOAT32_CBRT_EPS\n    0.004921566694974899\n\n    See Also\n    --------\n    FLOAT32_EPS, FLOAT32_SQRT_EPS, CBRT_EPS\n","FLOAT32_E":"\nFLOAT32_E\n    Euler's number.\n\n    Examples\n    --------\n    > FLOAT32_E\n    2.7182817459106445\n\n    See Also\n    --------\n    E\n","FLOAT32_EPS":"\nFLOAT32_EPS\n    Difference between one and the smallest value greater than one that can be\n    represented as a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_EPS\n    1.1920928955078125e-7\n\n    See Also\n    --------\n    EPS\n","FLOAT32_EXPONENT_BIAS":"\nFLOAT32_EXPONENT_BIAS\n    The bias of a single-precision floating-point number's exponent.\n\n    Examples\n    --------\n    > FLOAT32_EXPONENT_BIAS\n    127\n\n    See Also\n    --------\n    FLOAT16_EXPONENT_BIAS, FLOAT64_EXPONENT_BIAS\n","FLOAT32_EXPONENT_MASK":"\nFLOAT32_EXPONENT_MASK\n    Mask for the exponent of a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_EXPONENT_MASK\n    2139095040\n    > base.toBinaryStringUint32( FLOAT32_EXPONENT_MASK )\n    '01111111100000000000000000000000'\n\n    See Also\n    --------\n    FLOAT32_SIGN_MASK, FLOAT32_SIGNIFICAND_MASK, FLOAT32_ABS_MASK\n","FLOAT32_FOURTH_PI":"\nFLOAT32_FOURTH_PI\n    One fourth times the mathematical constant `π`.\n\n    Examples\n    --------\n    > FLOAT32_FOURTH_PI\n    7.853981852531433e-1\n\n    See Also\n    --------\n    FLOAT32_HALF_PI, FLOAT32_PI, FLOAT32_TWO_PI\n","FLOAT32_HALF_LN_TWO":"\nFLOAT32_HALF_LN_TWO\n    One half times the natural logarithm of 2 as a single-precision\n    floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_HALF_LN_TWO\n    0.3465735912322998\n\n    See Also\n    --------\n    HALF_LN2\n","FLOAT32_HALF_PI":"\nFLOAT32_HALF_PI\n    One half times the mathematical constant `π`.\n\n    Examples\n    --------\n    > FLOAT32_HALF_PI\n    1.5707963705062866\n\n    See Also\n    --------\n    FLOAT32_FOURTH_PI, FLOAT32_PI, FLOAT32_TWO_PI\n","FLOAT32_LN_HALF":"\nFLOAT32_LN_HALF\n    Natural logarithm of `1/2` as a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_LN_HALF\n    -0.6931471824645996\n\n    See Also\n    --------\n    LN_HALF\n","FLOAT32_LN_PI":"\nFLOAT32_LN_PI\n    Natural logarithm of the mathematical constant `π` as a single-precision\n    floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_LN_PI\n    1.1447298526763916\n\n    See Also\n    --------\n    FLOAT32_PI, LN_PI\n","FLOAT32_LN_TEN":"\nFLOAT32_LN_TEN\n    Natural logarithm of `10` as a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_LN_TEN\n     2.3025851249694824\n\n    See Also\n    --------\n    FLOAT32_LN_TWO, LN10\n","FLOAT32_LN_TWO":"\nFLOAT32_LN_TWO\n    Natural logarithm of `2` as a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_LN_TWO\n    0.6931471824645996\n\n    See Also\n    --------\n    FLOAT32_LN_TEN, LN2\n","FLOAT32_MAX":"\nFLOAT32_MAX\n    Maximum single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_MAX\n    3.4028234663852886e+38\n\n    See Also\n    --------\n    FLOAT16_MAX, FLOAT64_MAX\n","FLOAT32_MAX_BASE2_EXPONENT":"\nFLOAT32_MAX_BASE2_EXPONENT\n    The maximum biased base 2 exponent for a single-precision floating-point\n    number.\n\n    Examples\n    --------\n    > FLOAT32_MAX_BASE2_EXPONENT\n    127\n\n    See Also\n    --------\n    FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE2_EXPONENT\n","FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL\n    The maximum biased base 2 exponent for a subnormal single-precision\n    floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL\n    -127\n\n    See Also\n    --------\n    FLOAT32_MAX_BASE2_EXPONENT, FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n","FLOAT32_MAX_BASE10_EXPONENT":"\nFLOAT32_MAX_BASE10_EXPONENT\n    The maximum base 10 exponent for a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_MAX_BASE10_EXPONENT\n    38\n\n    See Also\n    --------\n    FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE10_EXPONENT\n","FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL\n    The maximum base 10 exponent for a subnormal single-precision floating-point\n    number.\n\n    Examples\n    --------\n    > FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL\n    -38\n\n    See Also\n    --------\n    FLOAT32_MAX_BASE10_EXPONENT, FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n","FLOAT32_MAX_SAFE_FIBONACCI":"\nFLOAT32_MAX_SAFE_FIBONACCI\n    Maximum safe Fibonacci number when stored in single-precision floating-point\n    format.\n\n    Examples\n    --------\n    > FLOAT32_MAX_SAFE_FIBONACCI\n    14930352\n\n    See Also\n    --------\n    FLOAT64_MAX_SAFE_FIBONACCI\n","FLOAT32_MAX_SAFE_INTEGER":"\nFLOAT32_MAX_SAFE_INTEGER\n    Maximum safe single-precision floating-point integer.\n\n    The maximum safe single-precision floating-point integer is given by\n    `2^24 - 1`.\n\n    Examples\n    --------\n    > FLOAT32_MAX_SAFE_INTEGER\n    16777215\n\n    See Also\n    --------\n    FLOAT16_MAX_SAFE_INTEGER, FLOAT32_MIN_SAFE_INTEGER, FLOAT64_MAX_SAFE_INTEGER\n","FLOAT32_MAX_SAFE_NTH_FACTORIAL":"\nFLOAT32_MAX_SAFE_NTH_FACTORIAL\n    Maximum safe nth factorial when stored in single-precision floating-\n    point format.\n\n    Examples\n    --------\n    > FLOAT32_MAX_SAFE_NTH_FACTORIAL\n    34\n\n","FLOAT32_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT32_MAX_SAFE_NTH_FIBONACCI\n    Maximum safe nth Fibonacci number when stored in single-precision floating-\n    point format.\n\n    Examples\n    --------\n    > FLOAT32_MAX_SAFE_NTH_FIBONACCI\n    36\n\n    See Also\n    --------\n    FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT32_MAX_SAFE_NTH_LUCAS":"\nFLOAT32_MAX_SAFE_NTH_LUCAS\n    Maximum safe nth Lucas number when stored in single-precision floating-point\n    format.\n\n    Examples\n    --------\n    > FLOAT32_MAX_SAFE_NTH_LUCAS\n    34\n\n    See Also\n    --------\n    FLOAT64_MAX_SAFE_NTH_LUCAS\n","FLOAT32_MIN_BASE2_EXPONENT":"\nFLOAT32_MIN_BASE2_EXPONENT\n    The minimum biased base 2 exponent for a normalized single-precision\n    floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_MIN_BASE2_EXPONENT\n    -126\n\n    See Also\n    --------\n    FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL\n    The minimum biased base 2 exponent for a subnormal single-precision\n    floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL\n    -149\n\n    See Also\n    --------\n    FLOAT32_MIN_BASE2_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT32_MIN_BASE10_EXPONENT":"\nFLOAT32_MIN_BASE10_EXPONENT\n    The minimum base 10 exponent for a normal single-precision floating-\n    point number.\n\n    Examples\n    --------\n    > FLOAT32_MIN_BASE10_EXPONENT\n    -37\n\n    See Also\n    --------\n    FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT\n","FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL\n    The minimum base 10 exponent for a subnormal single-precision floating-\n    point number.\n\n    Examples\n    --------\n    > FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL\n    -45\n\n    See Also\n    --------\n    FLOAT32_MIN_BASE10_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT32_MIN_SAFE_INTEGER":"\nFLOAT32_MIN_SAFE_INTEGER\n    Minimum safe single-precision floating-point integer.\n\n    The minimum safe single-precision floating-point integer is given by\n    `-(2^24 - 1)`.\n\n    Examples\n    --------\n    > FLOAT32_MIN_SAFE_INTEGER\n    -16777215\n\n    See Also\n    --------\n    FLOAT16_MIN_SAFE_INTEGER, FLOAT32_MAX_SAFE_INTEGER, FLOAT64_MIN_SAFE_INTEGER\n","FLOAT32_NAN":"\nFLOAT32_NAN\n    Single-precision floating-point NaN.\n\n    Examples\n    --------\n    > FLOAT32_NAN\n    NaN\n\n    See Also\n    --------\n    NAN\n","FLOAT32_NINF":"\nFLOAT32_NINF\n    Single-precision floating-point negative infinity.\n\n    Examples\n    --------\n    > FLOAT32_NINF\n    -Infinity\n\n    See Also\n    --------\n    FLOAT32_PINF, NINF\n","FLOAT32_NUM_BYTES":"\nFLOAT32_NUM_BYTES\n    Size (in bytes) of a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_NUM_BYTES\n    4\n\n    See Also\n    --------\n    FLOAT16_NUM_BYTES, FLOAT64_NUM_BYTES\n","FLOAT32_PHI":"\nFLOAT32_PHI\n    Golden ratio.\n\n    Examples\n    --------\n    > FLOAT32_PHI\n    1.6180340051651\n\n    See Also\n    --------\n    PHI\n","FLOAT32_PI":"\nFLOAT32_PI\n    The mathematical constant `π`.\n\n    Examples\n    --------\n    > FLOAT32_PI\n    3.1415927410125732\n\n    See Also\n    --------\n    FLOAT32_FOURTH_PI, FLOAT32_HALF_PI, FLOAT32_TWO_PI\n","FLOAT32_PINF":"\nFLOAT32_PINF\n    Single-precision floating-point positive infinity.\n\n    Examples\n    --------\n    > FLOAT32_PINF\n    Infinity\n\n    See Also\n    --------\n    FLOAT32_NINF, PINF\n","FLOAT32_PRECISION":"\nFLOAT32_PRECISION\n    Effective number of bits in the significand of a single-precision floating-\n    point number.\n\n    The effective number of bits is `23` significand bits plus `1` hidden bit.\n\n    Examples\n    --------\n    > FLOAT32_PRECISION\n    24\n\n    See Also\n    --------\n    FLOAT16_PRECISION, FLOAT64_PRECISION\n","FLOAT32_SIGN_MASK":"\nFLOAT32_SIGN_MASK\n    Mask for the sign bit of a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_SIGN_MASK\n    2147483648\n    > base.toBinaryStringUint32( FLOAT32_SIGN_MASK )\n    '10000000000000000000000000000000'\n\n    See Also\n    --------\n    FLOAT32_EXPONENT_MASK, FLOAT32_SIGNIFICAND_MASK, FLOAT32_ABS_MASK\n","FLOAT32_SIGNIFICAND_MASK":"\nFLOAT32_SIGNIFICAND_MASK\n    Mask for the significand of a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_SIGNIFICAND_MASK\n    8388607\n    > base.toBinaryStringUint32( FLOAT32_SIGNIFICAND_MASK )\n    '00000000011111111111111111111111'\n\n    See Also\n    --------\n    FLOAT32_EXPONENT_MASK, FLOAT32_SIGN_MASK, FLOAT32_ABS_MASK\n","FLOAT32_SMALLEST_NORMAL":"\nFLOAT32_SMALLEST_NORMAL\n    Smallest positive normalized single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_SMALLEST_NORMAL\n    1.1754943508222875e-38\n\n    See Also\n    --------\n    FLOAT32_SMALLEST_SUBNORMAL, FLOAT64_SMALLEST_NORMAL\n","FLOAT32_SMALLEST_SUBNORMAL":"\nFLOAT32_SMALLEST_SUBNORMAL\n    Smallest positive denormalized single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_SMALLEST_SUBNORMAL\n    1.401298464324817e-45\n\n    See Also\n    --------\n    FLOAT32_SMALLEST_NORMAL, FLOAT64_SMALLEST_SUBNORMAL\n","FLOAT32_SQRT_EPS":"\nFLOAT32_SQRT_EPS\n    Square root of single-precision floating-point epsilon.\n\n    Examples\n    --------\n    > FLOAT32_SQRT_EPS\n    0.0003452669770922512\n\n    See Also\n    --------\n    FLOAT32_EPS, SQRT_EPS\n","FLOAT32_SQRT_HALF":"\nFLOAT32_SQRT_HALF\n    Square root of `1/2` as a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_SQRT_HALF\n    0.7071067690849304\n\n    See Also\n    --------\n    SQRT_HALF\n","FLOAT32_SQRT_HALF_PI":"\nFLOAT32_SQRT_HALF_PI\n    Square root of `π` divided by `2` as a single-precision \n    floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_SQRT_HALF_PI\n    1.2533141374588013\n\n    See Also\n    --------\n    SQRT_HALF_PI","FLOAT32_SQRT_PHI":"\nFLOAT32_SQRT_PHI\n    Square root of the golden ratio as a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_SQRT_PHI\n    1.272019624710083\n\n    See Also\n    --------\n    SQRT_PHI\n","FLOAT32_SQRT_PI":"\nFLOAT32_SQRT_PI\n    Square root of the mathematical constant `π` as a single-precision\n    floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_SQRT_PI\n    1.7724539041519165\n\n    See Also\n    --------\n    FLOAT32_PI, SQRT_PI\n","FLOAT32_SQRT_THREE":"\nFLOAT32_SQRT_THREE\n    Square root of `3` as a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_SQRT_THREE\n    1.7320507764816284\n\n    See Also\n    --------\n    FLOAT32_SQRT_TWO, SQRT_THREE\n","FLOAT32_SQRT_TWO":"\nFLOAT32_SQRT_TWO\n    Square root of `2` as a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_SQRT_TWO\n    1.4142135381698608\n\n    See Also\n    --------\n    FLOAT32_SQRT_THREE, SQRT_TWO\n","FLOAT32_SQRT_TWO_PI":"\nFLOAT32_SQRT_TWO_PI\n    Square root of the `π` times `2` as single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_SQRT_TWO_PI\n    2.5066282749176025\n\n    See Also\n    --------\n    FLOAT32_PI, FLOAT32_TWO_PI, SQRT_TWO_PI\n","FLOAT32_TWO_PI":"\nFLOAT32_TWO_PI\n    The mathematical constant `π` times `2`.\n\n    Examples\n    --------\n    > FLOAT32_TWO_PI\n    6.2831854820251465\n\n    See Also\n    --------\n    FLOAT32_FOURTH_PI, FLOAT32_HALF_PI, FLOAT32_PI\n","Float32Array":"\nFloat32Array()\n    A typed array constructor which returns a typed array representing an array\n    of single-precision floating-point numbers in the platform byte order.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Float32Array()\n    <Float32Array>\n\n\nFloat32Array( length )\n    Returns a typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( 5 )\n    <Float32Array>[ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat32Array( typedarray )\n    Creates a typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float64Array( [ 0.5, 0.5, 0.5 ] );\n    > var arr2 = new Float32Array( arr1 )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]\n\n\nFloat32Array( obj )\n    Creates a typed array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a typed array.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 0.5, 0.5, 0.5 ];\n    > var arr2 = new Float32Array( arr1 )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]\n\n\nFloat32Array( buffer[, byteOffset[, length]] )\n    Returns a typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 16 );\n    > var arr = new Float32Array( buf, 0, 4 )\n    <Float32Array>[ 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat32Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2.0; };\n    > var arr = Float32Array.from( [ 1.0, -1.0 ], mapFcn )\n    <Float32Array>[ 2.0, -2.0 ]\n\n\nFloat32Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Float32Array.of( 2.0, -2.0 )\n    <Float32Array>[ 2.0, -2.0 ]\n\n\nFloat32Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Float32Array.BYTES_PER_ELEMENT\n    4\n\n\nFloat32Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Float32Array.name\n    'Float32Array'\n\n\nFloat32Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>\n\n\nFloat32Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( 5 );\n    > arr.byteLength\n    20\n\n\nFloat32Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Float32Array( 5 );\n    > arr.byteOffset\n    0\n\n\nFloat32Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Float32Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    4\n\n\nFloat32Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Float32Array( 5 );\n    > arr.length\n    5\n\n\nFloat32Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Float32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    2.0\n    > arr[ 4 ]\n    -2.0\n\n\nFloat32Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1.0 ]\n    > it.next().value\n    [ 1, -1.0 ]\n    > it.next().done\n    true\n\n\nFloat32Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > function predicate( v ) { return ( v >= 0.0 ); };\n    > arr.every( predicate )\n    false\n\n\nFloat32Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Float32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > arr.fill( 2.0 );\n    > arr[ 0 ]\n    2.0\n    > arr[ 1 ]\n    2.0\n\n\nFloat32Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v >= 0.0 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2\n\n\nFloat32Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > var v = arr.find( predicate )\n    -1.0\n\n\nFloat32Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > var idx = arr.findIndex( predicate )\n    2\n\n\nFloat32Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:1 1:0 2:-1 '\n\n\nFloat32Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > var bool = arr.includes( 2.0 )\n    false\n    > bool = arr.includes( -1.0 )\n    true\n\n\nFloat32Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > var idx = arr.indexOf( 2.0 )\n    -1\n    > idx = arr.indexOf( -1.0 )\n    2\n\n\nFloat32Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > arr.join( '|' )\n    '1|0|-1'\n\n\nFloat32Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true\n\n\nFloat32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n    > var idx = arr.lastIndexOf( 2.0 )\n    -1\n    > idx = arr.lastIndexOf( 0.0 )\n    3\n\n\nFloat32Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( v ) { return v * 2.0; };\n    > var arr2 = arr1.map( fcn )\n    <Float32Array>[ 2.0, 0.0, -2.0 ]\n\n\nFloat32Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0.0 )\n    2.0\n\n\nFloat32Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0.0 )\n    2.0\n\n\nFloat32Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Float32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] )\n    <Float32Array>\n    > arr.reverse()\n    <Float32Array>[ -1.0, 0.0, 1.0 ]\n\n\nFloat32Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > arr.set( [ -2.0, 2.0 ], 1 );\n    > arr[ 1 ]\n    -2.0\n    > arr[ 2 ]\n    2.0\n\n\nFloat32Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    0.0\n    > arr2[ 1 ]\n    -1.0\n\n\nFloat32Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > arr.some( predicate )\n    true\n\n\nFloat32Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Float32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n    > arr.sort()\n    <Float32Array>[ -2.0, -1.0, 0.0, 1.0, 2.0 ]\n\n\nFloat32Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Float32Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Float32Array>[ 0.0, 2.0, -2.0 ]\n\n\nFloat32Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n    > arr.toLocaleString()\n    '1,-1,0'\n\n\nFloat32Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n    > arr.toString()\n    '1,-1,0'\n\n\nFloat32Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > it = arr.values();\n    > it.next().value\n    1.0\n    > it.next().value\n    -1.0\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Float32Array.from":"\nFloat32Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2.0; };\n    > var arr = Float32Array.from( [ 1.0, -1.0 ], mapFcn )\n    <Float32Array>[ 2.0, -2.0 ]","Float32Array.of":"\nFloat32Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Float32Array.of( 2.0, -2.0 )\n    <Float32Array>[ 2.0, -2.0 ]","Float32Array.BYTES_PER_ELEMENT":"\nFloat32Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Float32Array.BYTES_PER_ELEMENT\n    4","Float32Array.name":"\nFloat32Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Float32Array.name\n    'Float32Array'","Float32Array.prototype.buffer":"\nFloat32Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>","Float32Array.prototype.byteLength":"\nFloat32Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( 5 );\n    > arr.byteLength\n    20","Float32Array.prototype.byteOffset":"\nFloat32Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Float32Array( 5 );\n    > arr.byteOffset\n    0","Float32Array.prototype.BYTES_PER_ELEMENT":"\nFloat32Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Float32Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    4","Float32Array.prototype.length":"\nFloat32Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Float32Array( 5 );\n    > arr.length\n    5","Float32Array.prototype.copyWithin":"\nFloat32Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Float32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    2.0\n    > arr[ 4 ]\n    -2.0","Float32Array.prototype.entries":"\nFloat32Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1.0 ]\n    > it.next().value\n    [ 1, -1.0 ]\n    > it.next().done\n    true","Float32Array.prototype.every":"\nFloat32Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > function predicate( v ) { return ( v >= 0.0 ); };\n    > arr.every( predicate )\n    false","Float32Array.prototype.fill":"\nFloat32Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Float32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > arr.fill( 2.0 );\n    > arr[ 0 ]\n    2.0\n    > arr[ 1 ]\n    2.0","Float32Array.prototype.filter":"\nFloat32Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v >= 0.0 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2","Float32Array.prototype.find":"\nFloat32Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > var v = arr.find( predicate )\n    -1.0","Float32Array.prototype.findIndex":"\nFloat32Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > var idx = arr.findIndex( predicate )\n    2","Float32Array.prototype.forEach":"\nFloat32Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:1 1:0 2:-1 '","Float32Array.prototype.includes":"\nFloat32Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > var bool = arr.includes( 2.0 )\n    false\n    > bool = arr.includes( -1.0 )\n    true","Float32Array.prototype.indexOf":"\nFloat32Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > var idx = arr.indexOf( 2.0 )\n    -1\n    > idx = arr.indexOf( -1.0 )\n    2","Float32Array.prototype.join":"\nFloat32Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > arr.join( '|' )\n    '1|0|-1'","Float32Array.prototype.keys":"\nFloat32Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true","Float32Array.prototype.lastIndexOf":"\nFloat32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n    > var idx = arr.lastIndexOf( 2.0 )\n    -1\n    > idx = arr.lastIndexOf( 0.0 )\n    3","Float32Array.prototype.map":"\nFloat32Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( v ) { return v * 2.0; };\n    > var arr2 = arr1.map( fcn )\n    <Float32Array>[ 2.0, 0.0, -2.0 ]","Float32Array.prototype.reduce":"\nFloat32Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0.0 )\n    2.0","Float32Array.prototype.reduceRight":"\nFloat32Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0.0 )\n    2.0","Float32Array.prototype.reverse":"\nFloat32Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Float32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] )\n    <Float32Array>\n    > arr.reverse()\n    <Float32Array>[ -1.0, 0.0, 1.0 ]","Float32Array.prototype.set":"\nFloat32Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > arr.set( [ -2.0, 2.0 ], 1 );\n    > arr[ 1 ]\n    -2.0\n    > arr[ 2 ]\n    2.0","Float32Array.prototype.slice":"\nFloat32Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    0.0\n    > arr2[ 1 ]\n    -1.0","Float32Array.prototype.some":"\nFloat32Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > arr.some( predicate )\n    true","Float32Array.prototype.sort":"\nFloat32Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Float32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n    > arr.sort()\n    <Float32Array>[ -2.0, -1.0, 0.0, 1.0, 2.0 ]","Float32Array.prototype.subarray":"\nFloat32Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Float32Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Float32Array>[ 0.0, 2.0, -2.0 ]","Float32Array.prototype.toLocaleString":"\nFloat32Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n    > arr.toLocaleString()\n    '1,-1,0'","Float32Array.prototype.toString":"\nFloat32Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n    > arr.toString()\n    '1,-1,0'","Float32Array.prototype.values":"\nFloat32Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > it = arr.values();\n    > it.next().value\n    1.0\n    > it.next().value\n    -1.0\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","FLOAT64_EXPONENT_BIAS":"\nFLOAT64_EXPONENT_BIAS\n    The bias of a double-precision floating-point number's exponent.\n\n    Examples\n    --------\n    > FLOAT64_EXPONENT_BIAS\n    1023\n\n    See Also\n    --------\n    FLOAT16_EXPONENT_BIAS, FLOAT32_EXPONENT_BIAS\n","FLOAT64_HIGH_WORD_ABS_MASK":"\nFLOAT64_HIGH_WORD_ABS_MASK\n    High word mask for excluding the sign bit of a double-precision floating-\n    point number.\n\n    Examples\n    --------\n    > FLOAT64_HIGH_WORD_ABS_MASK\n    2147483647\n    > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_ABS_MASK )\n    '01111111111111111111111111111111'\n\n    See Also\n    --------\n    FLOAT64_HIGH_WORD_SIGN_MASK, FLOAT64_HIGH_WORD_EXPONENT_MASK, FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n","FLOAT64_HIGH_WORD_EXPONENT_MASK":"\nFLOAT64_HIGH_WORD_EXPONENT_MASK\n    High word mask for the exponent of a double-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT64_HIGH_WORD_EXPONENT_MASK\n    2146435072\n    > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_EXPONENT_MASK )\n    '01111111111100000000000000000000'\n\n    See Also\n    --------\n    FLOAT64_HIGH_WORD_SIGNIFICAND_MASK, FLOAT64_HIGH_WORD_SIGN_MASK, FLOAT64_HIGH_WORD_ABS_MASK\n","FLOAT64_HIGH_WORD_SIGN_MASK":"\nFLOAT64_HIGH_WORD_SIGN_MASK\n    High word mask for the sign bit of a double-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT64_HIGH_WORD_SIGN_MASK\n    2147483648\n    > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGN_MASK )\n    '10000000000000000000000000000000'\n\n    See Also\n    --------\n    FLOAT64_HIGH_WORD_EXPONENT_MASK, FLOAT64_HIGH_WORD_SIGNIFICAND_MASK, FLOAT64_HIGH_WORD_ABS_MASK\n","FLOAT64_HIGH_WORD_SIGNIFICAND_MASK":"\nFLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n    High word mask for the significand of a double-precision floating-point\n    number.\n\n    Examples\n    --------\n    > FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n    1048575\n    > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGNIFICAND_MASK )\n    '00000000000011111111111111111111'\n\n    See Also\n    --------\n    FLOAT64_HIGH_WORD_EXPONENT_MASK, FLOAT64_HIGH_WORD_SIGN_MASK, FLOAT64_HIGH_WORD_ABS_MASK\n","FLOAT64_MAX":"\nFLOAT64_MAX\n    Maximum double-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT64_MAX\n    1.7976931348623157e+308\n\n    See Also\n    --------\n    FLOAT16_MAX, FLOAT32_MAX\n","FLOAT64_MAX_BASE2_EXPONENT":"\nFLOAT64_MAX_BASE2_EXPONENT\n    The maximum biased base 2 exponent for a double-precision floating-point\n    number.\n\n    Examples\n    --------\n    > FLOAT64_MAX_BASE2_EXPONENT\n    1023\n\n    See Also\n    --------\n    FLOAT64_MAX_BASE10_EXPONENT, FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n    The maximum biased base 2 exponent for a subnormal double-precision\n    floating-point number.\n\n    Examples\n    --------\n    > FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n    -1023\n\n    See Also\n    --------\n    FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE2_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_BASE10_EXPONENT":"\nFLOAT64_MAX_BASE10_EXPONENT\n    The maximum base 10 exponent for a double-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT64_MAX_BASE10_EXPONENT\n    308\n\n    See Also\n    --------\n    FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE2_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT\n","FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n    The maximum base 10 exponent for a subnormal double-precision floating-point\n    number.\n\n    Examples\n    --------\n    > FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n    -308\n\n    See Also\n    --------\n    FLOAT64_MAX_BASE10_EXPONENT, FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_LN":"\nFLOAT64_MAX_LN\n    Natural logarithm of the maximum double-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT64_MAX_LN\n    709.782712893384\n\n    See Also\n    --------\n    FLOAT64_MIN_LN\n","FLOAT64_MAX_SAFE_FIBONACCI":"\nFLOAT64_MAX_SAFE_FIBONACCI\n    Maximum safe Fibonacci number when stored in double-precision floating-point\n    format.\n\n    Examples\n    --------\n    > FLOAT64_MAX_SAFE_FIBONACCI\n    8944394323791464\n\n    See Also\n    --------\n    FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT64_MAX_SAFE_INTEGER":"\nFLOAT64_MAX_SAFE_INTEGER\n    Maximum safe double-precision floating-point integer.\n\n    The maximum safe double-precision floating-point integer is given by\n    `2^53 - 1`.\n\n    Examples\n    --------\n    > FLOAT64_MAX_SAFE_INTEGER\n    9007199254740991\n\n    See Also\n    --------\n    FLOAT16_MAX_SAFE_INTEGER, FLOAT32_MAX_SAFE_INTEGER, FLOAT64_MIN_SAFE_INTEGER\n","FLOAT64_MAX_SAFE_LUCAS":"\nFLOAT64_MAX_SAFE_LUCAS\n    Maximum safe Lucas number when stored in double-precision floating-point\n    format.\n\n    Examples\n    --------\n    > FLOAT64_MAX_SAFE_LUCAS\n    7639424778862807\n\n    See Also\n    --------\n    FLOAT64_MAX_SAFE_FIBONACCI, FLOAT64_MAX_SAFE_NTH_LUCAS\n","FLOAT64_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT64_MAX_SAFE_NTH_FIBONACCI\n    Maximum safe nth Fibonacci number when stored in double-precision floating-\n    point format.\n\n    Examples\n    --------\n    > FLOAT64_MAX_SAFE_NTH_FIBONACCI\n    78\n\n    See Also\n    --------\n    FLOAT64_MAX_SAFE_FIBONACCI\n","FLOAT64_MAX_SAFE_NTH_LUCAS":"\nFLOAT64_MAX_SAFE_NTH_LUCAS\n    Maximum safe nth Lucas number when stored in double-precision floating-point\n    format.\n\n    Examples\n    --------\n    > FLOAT64_MAX_SAFE_NTH_LUCAS\n    76\n\n    See Also\n    --------\n    FLOAT64_MAX_SAFE_LUCAS, FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT64_MIN_BASE2_EXPONENT":"\nFLOAT64_MIN_BASE2_EXPONENT\n    The minimum biased base 2 exponent for a normalized double-precision\n    floating-point number.\n\n    Examples\n    --------\n    > FLOAT64_MIN_BASE2_EXPONENT\n    -1022\n\n    See Also\n    --------\n    FLOAT64_MAX_BASE2_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n    The minimum biased base 2 exponent for a subnormal double-precision\n    floating-point number.\n\n    Examples\n    --------\n    > FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n    -1074\n\n    See Also\n    --------\n    FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MIN_BASE10_EXPONENT":"\nFLOAT64_MIN_BASE10_EXPONENT\n    The minimum base 10 exponent for a normalized double-precision floating-\n    point number.\n\n    Examples\n    --------\n    > FLOAT64_MIN_BASE10_EXPONENT\n    -308\n\n    See Also\n    --------\n    FLOAT64_MAX_BASE10_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n    The minimum base 10 exponent for a subnormal double-precision floating-\n    point number.\n\n    Examples\n    --------\n    > FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n    -324\n\n    See Also\n    --------\n    FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_LN":"\nFLOAT64_MIN_LN\n    Natural logarithm of the smallest normalized double-precision floating-point\n    number.\n\n    Examples\n    --------\n    > FLOAT64_MIN_LN\n    -708.3964185322641\n\n    See Also\n    --------\n    FLOAT64_MAX_LN\n","FLOAT64_MIN_SAFE_INTEGER":"\nFLOAT64_MIN_SAFE_INTEGER\n    Minimum safe double-precision floating-point integer.\n\n    The minimum safe double-precision floating-point integer is given by\n    `-(2^53 - 1)`.\n\n    Examples\n    --------\n    > FLOAT64_MIN_SAFE_INTEGER\n    -9007199254740991\n\n    See Also\n    --------\n    FLOAT16_MIN_SAFE_INTEGER, FLOAT32_MIN_SAFE_INTEGER, FLOAT64_MAX_SAFE_INTEGER\n","FLOAT64_NUM_BYTES":"\nFLOAT64_NUM_BYTES\n    Size (in bytes) of a double-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT64_NUM_BYTES\n    8\n\n    See Also\n    --------\n    FLOAT16_NUM_BYTES, FLOAT32_NUM_BYTES\n","FLOAT64_PRECISION":"\nFLOAT64_PRECISION\n    Effective number of bits in the significand of a double-precision floating-\n    point number.\n\n    The effective number of bits is `52` significand bits plus `1` hidden bit.\n\n    Examples\n    --------\n    > FLOAT64_PRECISION\n    53\n\n    See Also\n    --------\n    FLOAT16_PRECISION, FLOAT32_PRECISION\n","FLOAT64_SMALLEST_NORMAL":"\nFLOAT64_SMALLEST_NORMAL\n    Smallest positive normalized double-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT64_SMALLEST_NORMAL\n    2.2250738585072014e-308\n\n    See Also\n    --------\n    FLOAT32_SMALLEST_NORMAL, FLOAT64_SMALLEST_SUBNORMAL\n","FLOAT64_SMALLEST_SUBNORMAL":"\nFLOAT64_SMALLEST_SUBNORMAL\n    Smallest positive denormalized double-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT64_SMALLEST_SUBNORMAL\n    4.940656458412465e-324\n\n    See Also\n    --------\n    FLOAT32_SMALLEST_SUBNORMAL, FLOAT64_SMALLEST_NORMAL\n","Float64Array":"\nFloat64Array()\n    A typed array constructor which returns a typed array representing an array\n    of double-precision floating-point numbers in the platform byte order.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Float64Array()\n    <Float64Array>\n\n\nFloat64Array( length )\n    Returns a typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 5 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat64Array( typedarray )\n    Creates a typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float32Array( [ 0.5, 0.5, 0.5 ] );\n    > var arr2 = new Float64Array( arr1 )\n    <Float64Array>[ 0.5, 0.5, 0.5 ]\n\n\nFloat64Array( obj )\n    Creates a typed array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a typed array.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 0.5, 0.5, 0.5 ];\n    > var arr2 = new Float64Array( arr1 )\n    <Float64Array>[ 0.5, 0.5, 0.5 ]\n\n\nFloat64Array( buffer[, byteOffset[, length]] )\n    Returns a typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 32 );\n    > var arr = new Float64Array( buf, 0, 4 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat64Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2.0; };\n    > var arr = Float64Array.from( [ 1.0, -1.0 ], mapFcn )\n    <Float64Array>[ 2.0, -2.0 ]\n\n\nFloat64Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Float64Array.of( 2.0, -2.0 )\n    <Float64Array>[ 2.0, -2.0 ]\n\n\nFloat64Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Float64Array.BYTES_PER_ELEMENT\n    8\n\n\nFloat64Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Float64Array.name\n    'Float64Array'\n\n\nFloat64Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>\n\n\nFloat64Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 5 );\n    > arr.byteLength\n    40\n\n\nFloat64Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 5 );\n    > arr.byteOffset\n    0\n\n\nFloat64Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    8\n\n\nFloat64Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 5 );\n    > arr.length\n    5\n\n\nFloat64Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Float64Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    2.0\n    > arr[ 4 ]\n    -2.0\n\n\nFloat64Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1.0 ]\n    > it.next().value\n    [ 1, -1.0 ]\n    > it.next().done\n    true\n\n\nFloat64Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > function predicate( v ) { return ( v >= 0.0 ); };\n    > arr.every( predicate )\n    false\n\n\nFloat64Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Float64Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > arr.fill( 2.0 );\n    > arr[ 0 ]\n    2.0\n    > arr[ 1 ]\n    2.0\n\n\nFloat64Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v >= 0.0 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2\n\n\nFloat64Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > var v = arr.find( predicate )\n    -1.0\n\n\nFloat64Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > var idx = arr.findIndex( predicate )\n    2\n\n\nFloat64Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:1 1:0 2:-1 '\n\n\nFloat64Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > var bool = arr.includes( 2.0 )\n    false\n    > bool = arr.includes( -1.0 )\n    true\n\n\nFloat64Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > var idx = arr.indexOf( 2.0 )\n    -1\n    > idx = arr.indexOf( -1.0 )\n    2\n\n\nFloat64Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > arr.join( '|' )\n    '1|0|-1'\n\n\nFloat64Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true\n\n\nFloat64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n    > var idx = arr.lastIndexOf( 2.0 )\n    -1\n    > idx = arr.lastIndexOf( 0.0 )\n    3\n\n\nFloat64Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( v ) { return v * 2.0; };\n    > var arr2 = arr1.map( fcn )\n    <Float64Array>[ 2.0, 0.0, -2.0 ]\n\n\nFloat64Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0.0 )\n    2.0\n\n\nFloat64Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0.0 )\n    2.0\n\n\nFloat64Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Float64Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] )\n    <Float64Array>\n    > arr.reverse()\n    <Float64Array>[ -1.0, 0.0, 1.0 ]\n\n\nFloat64Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > arr.set( [ -2.0, 2.0 ], 1 );\n    > arr[ 1 ]\n    -2.0\n    > arr[ 2 ]\n    2.0\n\n\nFloat64Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    0.0\n    > arr2[ 1 ]\n    -1.0\n\n\nFloat64Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > arr.some( predicate )\n    true\n\n\nFloat64Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Float64Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n    > arr.sort()\n    <Float64Array>[ -2.0, -1.0, 0.0, 1.0, 2.0 ]\n\n\nFloat64Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Float64Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Float64Array>[ 0.0, 2.0, -2.0 ]\n\n\nFloat64Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n    > arr.toLocaleString()\n    '1,-1,0'\n\n\nFloat64Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n    > arr.toString()\n    '1,-1,0'\n\n\nFloat64Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > it = arr.values();\n    > it.next().value\n    1.0\n    > it.next().value\n    -1.0\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Float64Array.from":"\nFloat64Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2.0; };\n    > var arr = Float64Array.from( [ 1.0, -1.0 ], mapFcn )\n    <Float64Array>[ 2.0, -2.0 ]","Float64Array.of":"\nFloat64Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Float64Array.of( 2.0, -2.0 )\n    <Float64Array>[ 2.0, -2.0 ]","Float64Array.BYTES_PER_ELEMENT":"\nFloat64Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Float64Array.BYTES_PER_ELEMENT\n    8","Float64Array.name":"\nFloat64Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Float64Array.name\n    'Float64Array'","Float64Array.prototype.buffer":"\nFloat64Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>","Float64Array.prototype.byteLength":"\nFloat64Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 5 );\n    > arr.byteLength\n    40","Float64Array.prototype.byteOffset":"\nFloat64Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 5 );\n    > arr.byteOffset\n    0","Float64Array.prototype.BYTES_PER_ELEMENT":"\nFloat64Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    8","Float64Array.prototype.length":"\nFloat64Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 5 );\n    > arr.length\n    5","Float64Array.prototype.copyWithin":"\nFloat64Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Float64Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    2.0\n    > arr[ 4 ]\n    -2.0","Float64Array.prototype.entries":"\nFloat64Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1.0 ]\n    > it.next().value\n    [ 1, -1.0 ]\n    > it.next().done\n    true","Float64Array.prototype.every":"\nFloat64Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > function predicate( v ) { return ( v >= 0.0 ); };\n    > arr.every( predicate )\n    false","Float64Array.prototype.fill":"\nFloat64Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Float64Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > arr.fill( 2.0 );\n    > arr[ 0 ]\n    2.0\n    > arr[ 1 ]\n    2.0","Float64Array.prototype.filter":"\nFloat64Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v >= 0.0 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2","Float64Array.prototype.find":"\nFloat64Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > var v = arr.find( predicate )\n    -1.0","Float64Array.prototype.findIndex":"\nFloat64Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > var idx = arr.findIndex( predicate )\n    2","Float64Array.prototype.forEach":"\nFloat64Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:1 1:0 2:-1 '","Float64Array.prototype.includes":"\nFloat64Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > var bool = arr.includes( 2.0 )\n    false\n    > bool = arr.includes( -1.0 )\n    true","Float64Array.prototype.indexOf":"\nFloat64Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > var idx = arr.indexOf( 2.0 )\n    -1\n    > idx = arr.indexOf( -1.0 )\n    2","Float64Array.prototype.join":"\nFloat64Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > arr.join( '|' )\n    '1|0|-1'","Float64Array.prototype.keys":"\nFloat64Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true","Float64Array.prototype.lastIndexOf":"\nFloat64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n    > var idx = arr.lastIndexOf( 2.0 )\n    -1\n    > idx = arr.lastIndexOf( 0.0 )\n    3","Float64Array.prototype.map":"\nFloat64Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( v ) { return v * 2.0; };\n    > var arr2 = arr1.map( fcn )\n    <Float64Array>[ 2.0, 0.0, -2.0 ]","Float64Array.prototype.reduce":"\nFloat64Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0.0 )\n    2.0","Float64Array.prototype.reduceRight":"\nFloat64Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0.0 )\n    2.0","Float64Array.prototype.reverse":"\nFloat64Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Float64Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] )\n    <Float64Array>\n    > arr.reverse()\n    <Float64Array>[ -1.0, 0.0, 1.0 ]","Float64Array.prototype.set":"\nFloat64Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > arr.set( [ -2.0, 2.0 ], 1 );\n    > arr[ 1 ]\n    -2.0\n    > arr[ 2 ]\n    2.0","Float64Array.prototype.slice":"\nFloat64Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    0.0\n    > arr2[ 1 ]\n    -1.0","Float64Array.prototype.some":"\nFloat64Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > arr.some( predicate )\n    true","Float64Array.prototype.sort":"\nFloat64Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Float64Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n    > arr.sort()\n    <Float64Array>[ -2.0, -1.0, 0.0, 1.0, 2.0 ]","Float64Array.prototype.subarray":"\nFloat64Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Float64Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Float64Array>[ 0.0, 2.0, -2.0 ]","Float64Array.prototype.toLocaleString":"\nFloat64Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n    > arr.toLocaleString()\n    '1,-1,0'","Float64Array.prototype.toString":"\nFloat64Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n    > arr.toString()\n    '1,-1,0'","Float64Array.prototype.values":"\nFloat64Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > it = arr.values();\n    > it.next().value\n    1.0\n    > it.next().value\n    -1.0\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","forEach":"\nforEach( collection, fcn[, thisArg] )\n    Invokes a function for each element in a collection.\n\n    When invoked, the input function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n    > var arr = [ 1, 2, 3, 4 ];\n    > forEach( arr, logger )\n    0: 1\n    1: 2\n    2: 3\n    3: 4\n\n    See Also\n    --------\n    forEachAsync, forEachRight\n","forEachAsync":"\nforEachAsync( collection, [options,] fcn, done )\n    Invokes a function once for each element in a collection.\n\n    When invoked, `fcn` is provided a maximum of four arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If `fcn`\n    accepts two arguments, `fcn` is provided:\n\n    - value\n    - next\n\n    If `fcn` accepts three arguments, `fcn` is provided:\n\n    - value\n    - index\n    - next\n\n    For every other `fcn` signature, `fcn` is provided all four arguments.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function onDuration( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next();\n    ...     }\n    ... };\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( 'Done.' );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > forEachAsync( arr, onDuration, done )\n    1000\n    2500\n    3000\n    Done.\n\n    // Limit number of concurrent invocations:\n    > function onDuration( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next();\n    ...     }\n    ... };\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( 'Done.' );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 3000, 2500, 1000 ];\n    > forEachAsync( arr, opts, onDuration, done )\n    2500\n    3000\n    1000\n    Done.\n\n    // Process sequentially:\n    > function onDuration( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next();\n    ...     }\n    ... };\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( 'Done.' );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 3000, 2500, 1000 ];\n    > forEachAsync( arr, opts, onDuration, done )\n    3000\n    2500\n    1000\n    Done.\n\n\nforEachAsync.factory( [options,] fcn )\n    Returns a function which invokes a function once for each element in a\n    collection.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function onDuration( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next();\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = forEachAsync.factory( opts, onDuration );\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( 'Done.' );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    Done.\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    Done.\n\n    See Also\n    --------\n    forEach, forEachRightAsync\n","forEachAsync.factory":"\nforEachAsync.factory( [options,] fcn )\n    Returns a function which invokes a function once for each element in a\n    collection.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function onDuration( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next();\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = forEachAsync.factory( opts, onDuration );\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( 'Done.' );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    Done.\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    Done.\n\n    See Also\n    --------\n    forEach, forEachRightAsync","forEachChar":"\nforEachChar( str, [options,] clbk[, thisArg] )\n    Invokes a function for each character in a string.\n\n    When invoked, the provided function is provided three arguments:\n\n    - value: character.\n    - index: starting character index.\n    - str: input string.\n\n    Parameters\n    ----------\n    str: string\n        Input string over which to iterate.\n\n    options: Object (optional)\n        Options.\n\n    options.mode: string (optional)\n        Type of characters over which to iterate. The following modes are\n        supported:\n\n        - grapheme: grapheme clusters. Appropriate for strings containing visual\n          characters which can span multiple Unicode code points (e.g., emoji).\n        - code_point: Unicode code points. Appropriate for strings containing\n          visual characters which are comprised of more than one Unicode code\n          unit (e.g., ideographic symbols and punctuation and mathematical\n          alphanumerics).\n        - code_unit': UTF-16 code units. Appropriate for strings containing\n          visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n          common characters, such as those from the Latin, Greek, and Cyrillic\n          alphabets).\n\n        Default: 'grapheme'.\n\n    clbk: Function\n        The function to invoke for each character in the input string.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: string\n        Input string.\n\n    Examples\n    --------\n    > var n = 0;\n    > function fcn() { n += 1; };\n    > forEachChar( 'hello world!', fcn );\n    > n\n    12\n\n    See Also\n    --------\n    forEach\n","forEachRight":"\nforEachRight( collection, fcn[, thisArg] )\n    Invokes a function for each element in a collection, iterating from right to\n    left.\n\n    When invoked, the input function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n    > var arr = [ 1, 2, 3, 4 ];\n    > forEachRight( arr, logger )\n    3: 4\n    2: 3\n    1: 2\n    0: 1\n\n    See Also\n    --------\n    forEach, forEachRightAsync\n","forEachRightAsync":"\nforEachRightAsync( collection, [options,] fcn, done )\n    Invokes a function once for each element in a collection, iterating from\n    right to left.\n\n    When invoked, `fcn` is provided a maximum of four arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If `fcn`\n    accepts two arguments, `fcn` is provided:\n\n    - value\n    - next\n\n    If `fcn` accepts three arguments, `fcn` is provided:\n\n    - value\n    - index\n    - next\n\n    For every other `fcn` signature, `fcn` is provided all four arguments.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function onDuration( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next();\n    ...     }\n    ... };\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( 'Done.' );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > forEachRightAsync( arr, onDuration, done )\n    1000\n    2500\n    3000\n    Done.\n\n    // Limit number of concurrent invocations:\n    > function onDuration( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next();\n    ...     }\n    ... };\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( 'Done.' );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 1000, 2500, 3000 ];\n    > forEachRightAsync( arr, opts, onDuration, done )\n    2500\n    3000\n    1000\n    Done.\n\n    // Process sequentially:\n    > function onDuration( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next();\n    ...     }\n    ... };\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( 'Done.' );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 1000, 2500, 3000 ];\n    > forEachRightAsync( arr, opts, onDuration, done )\n    3000\n    2500\n    1000\n    Done.\n\n\nforEachRightAsync.factory( [options,] fcn )\n    Returns a function which invokes a function once for each element in a\n    collection, iterating from right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function onDuration( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next();\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = forEachRightAsync.factory( opts, onDuration );\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( 'Done.' );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    Done.\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    Done.\n\n    See Also\n    --------\n    forEachAsync, forEachRight\n","forEachRightAsync.factory":"\nforEachRightAsync.factory( [options,] fcn )\n    Returns a function which invokes a function once for each element in a\n    collection, iterating from right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function onDuration( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next();\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = forEachRightAsync.factory( opts, onDuration );\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( 'Done.' );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    Done.\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    Done.\n\n    See Also\n    --------\n    forEachAsync, forEachRight","forIn":"\nforIn( obj, fcn[, thisArg] )\n    Invokes a function for each own and inherited enumerable property of an\n    object.\n\n    When invoked, the function is provided three arguments:\n\n    - value: object property value.\n    - key: object property.\n    - obj: the input object.\n\n    To terminate iteration before visiting all properties, the provided function\n    must explicitly return `false`.\n\n    Property iteration order is *not* guaranteed.\n\n    Parameters\n    ----------\n    obj: Object\n        Input object, including arrays, typed arrays, and other collections.\n\n    fcn: Function\n        The function to invoke for each own enumerable property.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Object\n        Input object.\n\n    Examples\n    --------\n    > function logger( v, k ) { console.log( '%s: %d', k, v ); };\n    > function Foo() { return this; };\n    > Foo.prototype.beep = 'boop';\n    > var obj = new Foo();\n    > forIn( obj, logger )\n    beep: boop\n\n    See Also\n    --------\n    forEach, forOwn\n","format":"\nformat( str, ...args )\n    Insert supplied variable values into a format string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    args: ...any\n        Variable values.\n\n    Returns\n    -------\n    out: string\n        Formatted string.\n\n    Examples\n    --------\n    > var out = format( 'Hello, %s!', 'World' )\n    'Hello, World!'\n\n    > out = format( '%s %s', 'Hello', 'World' )\n    'Hello World'\n\n    > out = format( 'Pi: %.2f', PI )\n    'Pi: 3.14'\n\n","forOwn":"\nforOwn( obj, fcn[, thisArg] )\n    Invokes a function for each own enumerable property of an object.\n\n    When invoked, the function is provided three arguments:\n\n    - value: object property value.\n    - key: object property.\n    - obj: the input object.\n\n    To terminate iteration before visiting all properties, the provided function\n    must explicitly return `false`.\n\n    The function determines the list of own enumerable properties *before*\n    invoking the provided function. Hence, any modifications made to the input\n    object *after* calling this function (such as adding and removing\n    properties) will *not* affect the list of visited properties.\n\n    Property iteration order is *not* guaranteed.\n\n    Parameters\n    ----------\n    obj: Object\n        Input object, including arrays, typed arrays, and other collections.\n\n    fcn: Function\n        The function to invoke for each own enumerable property.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Object\n        Input object.\n\n    Examples\n    --------\n    > function logger( v, k ) { console.log( '%s: %d', k, v ); };\n    > var obj = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\n    > forOwn( obj, logger )\n    a: 1\n    b: 2\n    c: 3\n    d: 4\n\n    See Also\n    --------\n    forEach, forIn\n","FOURTH_PI":"\nFOURTH_PI\n    One fourth times the mathematical constant `π`.\n\n    Examples\n    --------\n    > FOURTH_PI\n    7.85398163397448309616e-1\n\n    See Also\n    --------\n    PI\n","FOURTH_ROOT_EPS":"\nFOURTH_ROOT_EPS\n    Fourth root of double-precision floating-point epsilon.\n\n    Examples\n    --------\n    > FOURTH_ROOT_EPS\n    0.0001220703125\n\n    See Also\n    --------\n    EPS\n","FRB_SF_WAGE_RIGIDITY":"\nFRB_SF_WAGE_RIGIDITY()\n    Returns wage rates for U.S. workers that have not changed jobs within the\n    year.\n\n    Each array element has the following fields:\n\n    - date: collection date (month/day/year; e.g., 01/01/1980).\n    - all_workers: wage rates for hourly and non-hourly workers.\n    - hourly_workers: wage rates for hourly workers.\n    - non_hourly_workers: wage rates for non-hourly workers.\n    - less_than_high_school: wage rates for workers with less than a high school\n      education.\n    - high_school: wage rates for workers with a high school education.\n    - some_college: wage rates for workers with some college education.\n    - college: wage rates for workers with a college education.\n    - construction: wage rates for workers in the construction industry.\n    - finance: wage rates for workers in the finance industry.\n    - manufacturing: wage rates for workers in the manufacturing industry.\n\n    Returns\n    -------\n    out: Array<Object>\n        Wage rates.\n\n    Examples\n    --------\n    > var data = FRB_SF_WAGE_RIGIDITY()\n    [ {...}, {...}, ... ]\n\n    References\n    ----------\n    - Federal Reserve Bank of San Francisco. 2017. \"Wage Rigidity.\" <http://www.\n    frbsf.org/economic-research/indicators-data/nominal-wage-rigidity/>.\n\n","fromCodePoint":"\nfromCodePoint( ...pt )\n    Creates a string from a sequence of Unicode code points.\n\n    In addition to multiple arguments, the function also supports providing an\n    array-like object as a single argument containing a sequence of Unicode code\n    points.\n\n    Parameters\n    ----------\n    pt: ...integer\n        Sequence of Unicode code points.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = fromCodePoint( 9731 )\n    '☃'\n    > out = fromCodePoint( [ 9731 ] )\n    '☃'\n    > out = fromCodePoint( 97, 98, 99 )\n    'abc'\n    > out = fromCodePoint( [ 97, 98, 99 ] )\n    'abc'\n\n    See Also\n    --------\n    codePointAt\n","Function":"\nFunction( [...argNames,] body )\n    Returns a Function object.\n\n    Argument names must be strings corresponding to valid JavaScript parameters\n    (i.e., a plain identifier, or, in environments supporting such parameters, a\n    rest parameter or destructured parameter, optionally with a default).\n\n    Parameters\n    ----------\n    argNames: ...any (optional)\n        Parameter names.\n\n    body: string\n        Function body.\n\n    Returns\n    -------\n    fcn: Function\n        Function object.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f( 1, 2 )\n    3\n\n\nFunction.prototype.apply( thisArg, args )\n    Calls a function with a given `this` value and arguments provided as an\n    array (or array-like object).\n\n    Parameters\n    ----------\n    thisArg: any\n        Value to use as `this` when executing the function.\n\n    args: Array\n        Array of arguments to pass to the function.\n\n    Returns\n    -------\n    out: any\n        Function return value.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.apply( null, [ 1, 2 ] )\n    3\n\nFunction.prototype.call( thisArg, ...args )\n    Calls a function with a given `this` value and arguments provided\n    individually.\n\n    Parameters\n    ----------\n    thisArg: any\n        Value to use as `this` when executing the function.\n\n    args: ...any\n        Arguments to pass to the function.\n\n    Returns\n    -------\n    out: any\n        Function return value.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.call( null, 1, 2 )\n    3\n\nFunction.prototype.bind( thisArg, ...args )\n    Creates a new function which, when called, has its `this` keyword set to the\n    provided value, with a given sequence of arguments preceding any provided\n    when the new function is called.\n\n    Parameters\n    ----------\n    thisArg: any\n        Value to use as `this` when executing the function.\n\n    args: ...any\n        Arguments to pass to the function.\n\n    Returns\n    -------\n    fcn: Function\n        Bound function.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > var g = f.bind( null, 1 );\n    > g( 2 )\n    3\n\nFunction.prototype.toString()\n    Returns a string representation of the function.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.toString()\n    'function anonymous( x, y ) { return x + y; }'\n\nFunction.prototype.length\n    The number of arguments expected by the function.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.length\n    2\n\nFunction.prototype.name\n    The name of the function.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.name\n    'anonymous'\n\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.name = 'add';\n    > f.name\n    'add'\n\nFunction.prototype.prototype\n    The prototype of the function.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.prototype\n    {}\n\n","Function.prototype.apply":"\nFunction.prototype.apply( thisArg, args )\n    Calls a function with a given `this` value and arguments provided as an\n    array (or array-like object).\n\n    Parameters\n    ----------\n    thisArg: any\n        Value to use as `this` when executing the function.\n\n    args: Array\n        Array of arguments to pass to the function.\n\n    Returns\n    -------\n    out: any\n        Function return value.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.apply( null, [ 1, 2 ] )\n    3","Function.prototype.call":"\nFunction.prototype.call( thisArg, ...args )\n    Calls a function with a given `this` value and arguments provided\n    individually.\n\n    Parameters\n    ----------\n    thisArg: any\n        Value to use as `this` when executing the function.\n\n    args: ...any\n        Arguments to pass to the function.\n\n    Returns\n    -------\n    out: any\n        Function return value.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.call( null, 1, 2 )\n    3","Function.prototype.bind":"\nFunction.prototype.bind( thisArg, ...args )\n    Creates a new function which, when called, has its `this` keyword set to the\n    provided value, with a given sequence of arguments preceding any provided\n    when the new function is called.\n\n    Parameters\n    ----------\n    thisArg: any\n        Value to use as `this` when executing the function.\n\n    args: ...any\n        Arguments to pass to the function.\n\n    Returns\n    -------\n    fcn: Function\n        Bound function.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > var g = f.bind( null, 1 );\n    > g( 2 )\n    3","Function.prototype.toString":"\nFunction.prototype.toString()\n    Returns a string representation of the function.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.toString()\n    'function anonymous( x, y ) { return x + y; }'","Function.prototype.length":"\nFunction.prototype.length\n    The number of arguments expected by the function.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.length\n    2","Function.prototype.name":"\nFunction.prototype.name\n    The name of the function.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.name\n    'anonymous'\n\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.name = 'add';\n    > f.name\n    'add'","Function.prototype.prototype":"\nFunction.prototype.prototype\n    The prototype of the function.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.prototype\n    {}","function2string":"\nfunction2string( fcn )\n    Returns a string representing the source code of a provided function.\n\n    If called on built-in functions, functions created by `Function#bind()`, or\n    other non-JavaScript functions, the function returns a \"native\" function\n    string similar to the following:\n\n      \"function foo() { [native code] }\"\n\n    For intrinsic object methods and functions, `foo` is the initial name of the\n    function.\n\n    If called on a function created by the `Function` constructor, the function\n    returns the source code of a synthesized function declaration having the\n    name \"anonymous\" and using the provided parameters and function body.\n\n    Starting in ES2018, the ECMAScript specification requires that the returned\n    string contain the exact same source code as it was declared, including any\n    whitespace and/or comments. If the host is unable to access the source code,\n    the specification requires that the returned string be the native function\n    string.\n\n    Parameters\n    ----------\n    fcn: Function\n        Input function.\n\n    Returns\n    -------\n    out: string\n        String representing the function's source code.\n\n    Examples\n    --------\n    > function2string( base.erf )\n    <string>\n\n    See Also\n    --------\n    Function\n","functionName":"\nfunctionName( fcn )\n    Returns the name of a function.\n\n    If provided an anonymous function, the function returns an empty `string` or\n    the string `\"anonymous\"`.\n\n\n    Parameters\n    ----------\n    fcn: Function\n        Input function.\n\n    Returns\n    -------\n    out: string\n        Function name.\n\n    Examples\n    --------\n    > var v = functionName( String )\n    'String'\n    > v = functionName( function foo(){} )\n    'foo'\n    > v = functionName( function(){} )\n    '' || 'anonymous'\n\n    See Also\n    --------\n    constructorName\n","functionSequence":"\nfunctionSequence( ...fcn )\n    Returns a pipeline function.\n\n    Starting from the left, the pipeline function evaluates each function and\n    passes the result as an argument to the next function. The result of the\n    rightmost function is the result of the whole.\n\n    Only the leftmost function is explicitly permitted to accept multiple\n    arguments. All other functions are evaluated as unary functions.\n\n    Parameters\n    ----------\n    fcn: ...Function\n        Functions to evaluate in sequential order.\n\n    Returns\n    -------\n    out: Function\n        Pipeline function.\n\n    Examples\n    --------\n    > function a( x ) { return 2 * x; };\n    > function b( x ) { return x + 3; };\n    > function c( x ) { return x / 5; };\n    > var f = functionSequence( a, b, c );\n    > var z = f( 6 )\n    3\n\n    See Also\n    --------\n    compose, functionSequenceAsync\n","functionSequenceAsync":"\nfunctionSequenceAsync( ...fcn )\n    Returns a pipeline function.\n\n    Starting from the left, the pipeline function evaluates each function and\n    passes the result as the first argument of the next function. The result of\n    the rightmost function is the result of the whole.\n\n    The last argument for each provided function is a `next` callback which\n    should be invoked upon function completion. The callback accepts two\n    arguments:\n\n    - error: error argument.\n    - result: function result.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the pipeline function suspends execution and immediately calls the\n    `done` callback for subsequent `error` handling.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Only the leftmost function is explicitly permitted to accept multiple\n    arguments. All other functions are evaluated as binary functions.\n\n    The function will throw if provided fewer than two input arguments.\n\n    Parameters\n    ----------\n    fcn: ...Function\n        Functions to evaluate in sequential order.\n\n    Returns\n    -------\n    out: Function\n        Pipeline function.\n\n    Examples\n    --------\n    > function a( x, next ) {\n    ...    setTimeout( onTimeout, 0 );\n    ...    function onTimeout() {\n    ...        next( null, 2*x );\n    ...    }\n    ... };\n    > function b( x, next ) {\n    ...    setTimeout( onTimeout, 0 );\n    ...    function onTimeout() {\n    ...        next( null, x+3 );\n    ...    }\n    ... };\n    > function c( x, next ) {\n    ...    setTimeout( onTimeout, 0 );\n    ...    function onTimeout() {\n    ...        next( null, x/5 );\n    ...    }\n    ... };\n    > var f = functionSequenceAsync( a, b, c );\n    > function done( error, result ) {\n    ...    if ( error ) {\n    ...        throw error;\n    ...    }\n    ...    console.log( result );\n    ... };\n    > f( 6, done )\n    3\n\n    See Also\n    --------\n    composeAsync, functionSequence\n","GAMMA_LANCZOS_G":"\nGAMMA_LANCZOS_G\n    Arbitrary constant `g` to be used in Lanczos approximation functions.\n\n    Examples\n    --------\n    > GAMMA_LANCZOS_G\n    10.900511\n\n","gdot":"\ngdot( x, y )\n    Computes the dot product of two vectors.\n\n    In general, for best performance, especially for large vectors, provide\n    1-dimensional ndarrays whose underlying data type is either 'float64' or\n    'float32'.\n\n    If provided empty vectors, the function returns `0.0`.\n\n    Parameters\n    ----------\n    x: ndarray|ArrayLikeObject\n        First input array.\n\n    y: ndarray|ArrayLikeObject\n        Second input array.\n\n    Returns\n    -------\n    dot: number\n        The dot product.\n\n    Examples\n    --------\n    // Using ndarrays...\n    > var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n    > var y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n    > gdot( x, y )\n    -5.0\n\n    // Using array-like objects...\n    > x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n    > y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n    > gdot( x, y )\n    -5.0\n\n    See Also\n    --------\n    base.strided.gdot, ddot, sdot\n","getegid":"\ngetegid()\n    Returns the effective numeric group identity of the calling process.\n\n    The function only returns an effective group identity on POSIX platforms.\n    For all other platforms (e.g., Windows and Android), the function returns\n    `null`.\n\n    Returns\n    -------\n    id: integer|null\n        Effective numeric group identity.\n\n    Examples\n    --------\n    > var gid = getegid()\n\n    See Also\n    --------\n    geteuid, getgid, getuid\n","geteuid":"\ngeteuid()\n    Returns the effective numeric user identity of the calling process.\n\n    The function only returns an effective user identity on POSIX platforms. For\n    all other platforms (e.g., Windows and Android), the function returns\n    `null`.\n\n    Returns\n    -------\n    id: integer|null\n        Effective numeric user identity.\n\n    Examples\n    --------\n    > var uid = geteuid()\n\n    See Also\n    --------\n    getegid, getgid, getuid\n","getgid":"\ngetgid()\n    Returns the numeric group identity of the calling process.\n\n    The function only returns a group identity on POSIX platforms. For all other\n    platforms (e.g., Windows and Android), the function returns `null`.\n\n    Returns\n    -------\n    id: integer|null\n        Numeric group identity.\n\n    Examples\n    --------\n    > var gid = getgid()\n\n    See Also\n    --------\n    getegid, geteuid, getuid\n","getGlobal":"\ngetGlobal( [codegen] )\n    Returns the global object.\n\n    Parameters\n    ----------\n    codegen: boolean (optional)\n        Boolean indicating whether to use code generation to resolve the global\n        object. Code generation is the *most* reliable means for resolving the\n        global object; however, using code generation may violate content\n        security policies (CSPs). Default: false.\n\n    Returns\n    -------\n    global: Object\n        Global object.\n\n    Examples\n    --------\n    > var g = getGlobal()\n    {...}\n\n","getPrototypeOf":"\ngetPrototypeOf( value )\n    Returns the prototype of a provided object.\n\n    In contrast to the native `Object.getPrototypeOf`, this function does not\n    throw when provided `null` or `undefined`. Instead, similar to when provided\n    any value with *no* inherited properties, the function returns `null`.\n\n    Value arguments other than `null` or `undefined` are coerced to objects.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    out: Object|null\n        Prototype.\n\n    Examples\n    --------\n    > var proto = getPrototypeOf( {} )\n    {}\n\n    See Also\n    --------\n    isPrototypeOf\n","getuid":"\ngetuid()\n    Returns the numeric user identity of the calling process.\n\n    The function only returns a user identity on POSIX platforms. For all other\n    platforms (e.g., Windows and Android), the function returns `null`.\n\n    Returns\n    -------\n    id: integer|null\n        Numeric user identity.\n\n    Examples\n    --------\n    > var uid = getuid()\n\n    See Also\n    --------\n    getegid, geteuid, getgid\n","GLAISHER":"\nGLAISHER\n    Glaisher-Kinkelin constant.\n\n    Examples\n    --------\n    > GLAISHER\n    1.2824271291006226\n\n","graphemeClusters2iterator":"\ngraphemeClusters2iterator( src[, mapFcn[, thisArg]] )\n    Returns an iterator which iterates over each grapheme cluster in a string.\n\n    When invoked, an input function is provided three arguments:\n\n    - value: grapheme cluster.\n    - index: iterated value index.\n    - src: source string.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke a string's `@@iterator` method, regardless of whether this method is\n    defined. To convert a string to an implementation defined iterator, invoke\n    this method directly.\n\n    Parameters\n    ----------\n    src: string\n        String from which to create the iterator.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = graphemeClusters2iterator( '🌷🍕' );\n    > var v = it.next().value\n    '🌷'\n    > v = it.next().value\n    '🍕'\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    array2iterator, graphemeClusters2iteratorRight\n","graphemeClusters2iteratorRight":"\ngraphemeClusters2iteratorRight( src[, mapFcn[, thisArg]] )\n    Returns an iterator which iterates from right to left over each grapheme\n    cluster in a string.\n\n    When invoked, an input function is provided three arguments:\n\n    - value: grapheme cluster.\n    - index: iterated value index.\n    - src: source string.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke a string's `@@iterator` method, regardless of whether this method is\n    defined. To convert a string to an implementation defined iterator, invoke\n    this method directly.\n\n    Parameters\n    ----------\n    src: string\n        String from which to create the iterator.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = graphemeClusters2iteratorRight( '🌷🍕' );\n    > var v = it.next().value\n    '🍕'\n    > v = it.next().value\n    '🌷'\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    array2iteratorRight, graphemeClusters2iterator\n","group":"\ngroup( collection, [options,] groups )\n    Groups values as arrays associated with distinct keys.\n\n    If provided an empty collection, the function returns an empty object.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection to group. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Options.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `indices`, indices are returned; if\n        `*`, both indices and values are returned. Default: 'values'.\n\n    groups: Array|TypedArray|Object\n        A collection defining which group an element in the input collection\n        belongs to. Each value in `groups` should resolve to a value which can\n        be serialized as an object key. If provided an object, the object must\n        be array-like (excluding strings and functions).\n\n    Returns\n    -------\n    out: Object\n        Group results.\n\n    Examples\n    --------\n    > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n    > var groups = [ 'b', 'b', 'f', 'b' ];\n    > var out = group( collection, groups )\n    { 'b': [ 'beep', 'boop', 'bar' ], 'f': [ 'foo' ] }\n    > groups = [ 1, 1, 2, 1 ];\n    > out = group( collection, groups )\n    { '1': [ 'beep', 'boop', 'bar' ], '2': [ 'foo' ] }\n\n    // Output group results as indices:\n    > groups = [ 'b', 'b', 'f', 'b' ];\n    > var opts = { 'returns': 'indices' };\n    > out = group( collection, opts, groups )\n    { 'b': [ 0, 1, 3 ], 'f': [ 2 ] }\n\n    // Output group results as index-element pairs:\n    > opts = { 'returns': '*' };\n    > out = group( collection, opts, groups )\n    { 'b': [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], 'f': [ [2, 'foo'] ] }\n\n    See Also\n    --------\n    bifurcate, countBy, groupBy\n","groupBy":"\ngroupBy( collection, [options,] indicator )\n    Groups values according to an indicator function.\n\n    When invoked, the indicator function is provided two arguments:\n\n    - value: collection value.\n    - index: collection index.\n\n    The value returned by an indicator function should be a value which can be\n    serialized as an object key.\n\n    If provided an empty collection, the function returns an empty object.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection to group. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Options.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `indices`, indices are returned; if\n        `*`, both indices and values are returned. Default: 'values'.\n\n    indicator: Function\n        Indicator function specifying which group an element in the input\n        collection belongs to.\n\n    Returns\n    -------\n    out: Object\n        Group results.\n\n    Examples\n    --------\n    > function indicator( v ) {\n    ...     if ( v[ 0 ] === 'b' ) {\n    ...         return 'b';\n    ...     }\n    ...     return 'other';\n    ... };\n    > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n    > var out = groupBy( collection, indicator )\n    { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n    // Output group results as indices:\n    > var opts = { 'returns': 'indices' };\n    > out = groupBy( collection, opts, indicator )\n    { 'b': [ 0, 1, 3 ], 'other': [ 2 ] }\n\n    // Output group results as index-value pairs:\n    > opts = { 'returns': '*' };\n    > out = groupBy( collection, opts, indicator )\n    { 'b': [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], 'other': [ [2, 'foo' ] ] }\n\n    See Also\n    --------\n    bifurcateBy, countBy, group\n","groupByAsync":"\ngroupByAsync( collection, [options,] indicator, done )\n    Groups values according to an indicator function.\n\n    When invoked, the indicator function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If the\n    indicator function accepts two arguments, the indicator function is\n    provided:\n\n    - value\n    - next\n\n    If the indicator function accepts three arguments, the indicator function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other indicator function signature, the indicator function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - group: value group.\n\n    If an indicator function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    If provided an empty collection, the function calls the `done` callback with\n    an empty object as the second argument.\n\n    The `group` returned by an indicator function should be a value which can be\n    serialized as an object key.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `indices`, indices are returned; if\n        `*`, both indices and values are returned. Default: 'values'.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    indicator: Function\n        Indicator function specifying which group an element in the input\n        collection belongs to.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > groupByAsync( arr, indicator, done )\n    1000\n    2500\n    3000\n    { \"true\": [ 1000, 3000 ], \"false\": [ 2500 ] }\n\n    // Output group results as indices:\n    > var opts = { 'returns': 'indices' };\n    > groupByAsync( arr, opts, indicator, done )\n    1000\n    2500\n    3000\n    { \"true\": [ 2, 0 ], \"false\": [ 1 ] }\n\n    // Output group results as index-value pairs:\n    > opts = { 'returns': '*' };\n    > groupByAsync( arr, opts, indicator, done )\n    1000\n    2500\n    3000\n    { \"true\": [ [ 2, 1000 ], [ 0, 3000 ] ], \"false\": [ [ 1, 2500 ] ] }\n\n    // Limit number of concurrent invocations:\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 3000, 2500, 1000 ];\n    > groupByAsync( arr, opts, indicator, done )\n    2500\n    3000\n    1000\n    { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n\n    // Process sequentially:\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 3000, 2500, 1000 ];\n    > groupByAsync( arr, opts, indicator, done )\n    3000\n    2500\n    1000\n    { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n\n\ngroupByAsync.factory( [options,] indicator )\n    Returns a function which groups values according to an indicator function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `indices`, indices are returned; if\n        `*`, both indices and values are returned. Default: 'values'.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    indicator: Function\n        Indicator function specifying which group an element in the input\n        collection belongs to.\n\n    Returns\n    -------\n    out: Function\n        A group-by function.\n\n    Examples\n    --------\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = groupByAsync.factory( opts, indicator );\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    { \"true\": [ 2000, 1000 ], \"false\": [ 1500 ] }\n\n    See Also\n    --------\n    bifurcateByAsync, countByAsync, groupBy\n","groupByAsync.factory":"\ngroupByAsync.factory( [options,] indicator )\n    Returns a function which groups values according to an indicator function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `indices`, indices are returned; if\n        `*`, both indices and values are returned. Default: 'values'.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    indicator: Function\n        Indicator function specifying which group an element in the input\n        collection belongs to.\n\n    Returns\n    -------\n    out: Function\n        A group-by function.\n\n    Examples\n    --------\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = groupByAsync.factory( opts, indicator );\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    { \"true\": [ 2000, 1000 ], \"false\": [ 1500 ] }\n\n    See Also\n    --------\n    bifurcateByAsync, countByAsync, groupBy","groupIn":"\ngroupIn( obj, [options,] indicator )\n    Group values according to an indicator function.\n\n    When invoked, the indicator function is provided two arguments:\n\n    - value: object value.\n    - key: object key.\n\n    The value returned by an indicator function should be a value which can be\n    serialized as an object key.\n\n    If provided an empty object with no prototype, the function returns an empty\n    object.\n\n    The function iterates over an object's own and inherited properties.\n\n    Key iteration order is *not* guaranteed, and, thus, result order is *not*\n    guaranteed.\n\n    Parameters\n    ----------\n    obj: Object|Array|TypedArray\n        Input object to group.\n\n    options: Object (optional)\n        Options.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `keys`, keys are returned; if `*`,\n        both keys and values are returned. Default: 'values'.\n\n    indicator: Function\n        Indicator function indicating which group a value in the input object\n        belongs to.\n\n    Returns\n    -------\n    out: Object\n        Group results.\n\n    Examples\n    --------\n    > function indicator( v ) {\n    ...     if ( v[ 0 ] === 'b' ) {\n    ...         return 'b';\n    ...     }\n    ...     return 'other';\n    ... };\n    > function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\n    > Foo.prototype = Object.create( null );\n    > Foo.prototype.c = 'foo';\n    > Foo.prototype.d = 'bar';\n    > var obj = new Foo();\n    > var out = groupIn( obj, indicator )\n    { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n    // Output group results as keys:\n    > var opts = { 'returns': 'keys' };\n    > out = groupIn( obj, opts, indicator )\n    { 'b': [ 'a', 'b', 'd' ], 'other': [ 'c' ] }\n\n    // Output group results as key-value pairs:\n    > opts = { 'returns': '*' };\n    > out = groupIn( obj, opts, indicator )\n    { 'b': [['a','beep'], ['b','boop'], ['d','bar']], 'other': [['c','foo' ]] }\n\n    See Also\n    --------\n    bifurcateIn, groupBy, groupOwn\n","groupOwn":"\ngroupOwn( obj, [options,] indicator )\n    Group values according to an indicator function.\n\n    When invoked, the indicator function is provided two arguments:\n\n    - value: object value.\n    - key: object key.\n\n    The value returned by an indicator function should be a value which can be\n    serialized as an object key.\n\n    If provided an empty object, the function returns an empty object.\n\n    The function iterates over an object's own properties.\n\n    Key iteration order is *not* guaranteed, and, thus, result order is *not*\n    guaranteed.\n\n    Parameters\n    ----------\n    obj: Object|Array|TypedArray\n        Input object to group.\n\n    options: Object (optional)\n        Options.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `keys`, keys are returned; if `*`,\n        both keys and values are returned. Default: 'values'.\n\n    indicator: Function\n        Indicator function indicating which group a value in the input object\n        belongs to.\n\n    Returns\n    -------\n    out: Object\n        Group results.\n\n    Examples\n    --------\n    > function indicator( v ) {\n    ...     if ( v[ 0 ] === 'b' ) {\n    ...         return 'b';\n    ...     }\n    ...     return 'other';\n    ... };\n    > var obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\n    > var out = groupOwn( obj, indicator )\n    { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n    // Output group results as keys:\n    > var opts = { 'returns': 'keys' };\n    > out = groupOwn( obj, opts, indicator )\n    { 'b': [ 'a', 'b', 'd' ], 'other': [ 'c' ] }\n\n    // Output group results as key-value pairs:\n    > opts = { 'returns': '*' };\n    > out = groupOwn( obj, opts, indicator )\n    { 'b': [['a','beep'], ['b','boop'], ['d','bar']], 'other': [['c','foo' ]] }\n\n    See Also\n    --------\n    bifurcateOwn, group, groupBy\n","gswap":"\ngswap( x, y )\n    Interchanges two vectors.\n\n    In general, for best performance, especially for large vectors, provide\n    1-dimensional ndarrays whose underlying data type is either 'float64' or\n    'float32'.\n\n    Parameters\n    ----------\n    x: ndarray|ArrayLikeObject\n        First input array.\n\n    y: ndarray|ArrayLikeObject\n        Second input array.\n\n    Returns\n    -------\n    y: ndarray\n        The second input array `y`.\n\n    Examples\n    --------\n    // Using ndarrays...\n    > var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n    > var y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n    > gswap( x, y );\n    > x.data\n    <Float64Array>[ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n    > y.data\n    <Float64Array>[ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n    // Using array-like objects...\n    > x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n    > y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n    > gswap( x, y );\n    > x\n    [ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n    > y\n    [ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n    See Also\n    --------\n    base.strided.gswap, dswap, sswap\n","HALF_LN2":"\nHALF_LN2\n    One half times the natural logarithm of `2`.\n\n    Examples\n    --------\n    > HALF_LN2\n    3.46573590279972654709e-01\n\n    See Also\n    --------\n    LN2\n","HALF_PI":"\nHALF_PI\n    One half times the mathematical constant `π`.\n\n    Examples\n    --------\n    > HALF_PI\n    1.5707963267948966\n\n    See Also\n    --------\n    PI\n","HARRISON_BOSTON_HOUSE_PRICES":"\nHARRISON_BOSTON_HOUSE_PRICES()\n    Returns a dataset derived from information collected by the US Census\n    Service concerning housing in Boston, Massachusetts (1978).\n\n    The data consists of 14 attributes:\n\n    - crim: per capita crime rate by town.\n    - zn: proportion of residential land zoned for lots over 25,000 square feet.\n    - indus: proportion of non-retail business acres per town.\n    - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise).\n    - nox: nitric oxides concentration (parts per 10 million).\n    - rm: average number of rooms per dwelling.\n    - age: proportion of owner-occupied units built prior to 1940.\n    - dis: weighted distances to five Boston employment centers.\n    - rad: index of accessibility to radial highways.\n    - tax: full-value property-tax rate per $10,000.\n    - ptratio: pupil-teacher ratio by town.\n    - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town.\n    - lstat: percent lower status of the population.\n    - medv: median value of owner-occupied homes in $1000's.\n\n    The dataset can be used to predict two dependent variables: 1) nitrous oxide\n    level and 2) median home value.\n\n    The median home value field seems to be censored at 50.00 (corresponding to\n    a median value of $50,000). Censoring is suggested by the fact that the\n    highest median value of exactly $50,000 is reported in 16 cases, while 15\n    cases have values between $40,000 and $50,000. Values are rounded to the\n    nearest hundred. Harrison and Rubinfeld do not, however, mention any\n    censoring.\n\n    Additionally, as documented by Gilley and Pace (1996), the dataset contains\n    eight miscoded median values.\n\n    Returns\n    -------\n    out: Array<Object>\n        Boston house prices.\n\n    Examples\n    --------\n    > var data = HARRISON_BOSTON_HOUSE_PRICES()\n    [ {...}, {...}, ... ]\n\n    References\n    ----------\n    - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n    the demand for clean air.\" _Journal of Environmental Economics and\n    Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n    - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n    Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n    doi:10.1006/jeem.1996.0052.\n\n    See Also\n    --------\n    HARRISON_BOSTON_HOUSE_PRICES_CORRECTED, PACE_BOSTON_HOUSE_PRICES\n","HARRISON_BOSTON_HOUSE_PRICES_CORRECTED":"\nHARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n    Returns a (corrected) dataset derived from information collected by the US\n    Census Service concerning housing in Boston, Massachusetts (1978).\n\n    The data consists of 15 attributes:\n\n    - crim: per capita crime rate by town.\n    - zn: proportion of residential land zoned for lots over 25,000 square feet.\n    - indus: proportion of non-retail business acres per town.\n    - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise).\n    - nox: nitric oxides concentration (parts per 10 million).\n    - rm: average number of rooms per dwelling.\n    - age: proportion of owner-occupied units built prior to 1940.\n    - dis: weighted distances to five Boston employment centers.\n    - rad: index of accessibility to radial highways.\n    - tax: full-value property-tax rate per $10,000.\n    - ptratio: pupil-teacher ratio by town.\n    - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town\n    - lstat: percent lower status of the population.\n    - medv: median value of owner-occupied homes in $1000's.\n    - cmedv: corrected median value of owner-occupied homes in $1000's.\n\n    The dataset can be used to predict two dependent variables: 1) nitrous oxide\n    level and 2) median home value.\n\n    The median home value field seems to be censored at 50.00 (corresponding to\n    a median value of $50,000). Censoring is suggested by the fact that the\n    highest median value of exactly $50,000 is reported in 16 cases, while 15\n    cases have values between $40,000 and $50,000. Values are rounded to the\n    nearest hundred. Harrison and Rubinfeld do not, however, mention any\n    censoring.\n\n    The dataset contains eight corrections to miscoded median values, as\n    documented by Gilley and Pace (1996).\n\n    Returns\n    -------\n    out: Array<Object>\n        Boston house prices.\n\n    Examples\n    --------\n    > var data = HARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n    [ {...}, {...}, ... ]\n\n    References\n    ----------\n    - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n    the demand for clean air.\" _Journal of Environmental Economics and\n    Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n    - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n    Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n    doi:10.1006/jeem.1996.0052.\n\n    See Also\n    --------\n    HARRISON_BOSTON_HOUSE_PRICES, PACE_BOSTON_HOUSE_PRICES\n","hasArrayBufferSupport":"\nhasArrayBufferSupport()\n    Tests for native `ArrayBuffer` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `ArrayBuffer` support.\n\n    Examples\n    --------\n    > var bool = hasArrayBufferSupport()\n    <boolean>\n\n    See Also\n    --------\n    hasFloat32ArraySupport, hasFloat64ArraySupport, hasInt16ArraySupport, hasInt32ArraySupport, hasInt8ArraySupport, hasNodeBufferSupport, hasSharedArrayBufferSupport, hasUint16ArraySupport, hasUint32ArraySupport, hasUint8ArraySupport, hasUint8ClampedArraySupport\n","hasArrowFunctionSupport":"\nhasArrowFunctionSupport()\n    Tests whether an environment supports native arrow functions.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment support arrow functions.\n\n    Examples\n    --------\n    > var bool = hasArrowFunctionSupport()\n    <boolean>\n\n","hasAsyncAwaitSupport":"\nhasAsyncAwaitSupport()\n    Tests for native `async`/`await` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has native `async`/`await` support.\n\n    Examples\n    --------\n    > var bool = hasAsyncAwaitSupport()\n    <boolean>\n\n","hasAsyncIteratorSymbolSupport":"\nhasAsyncIteratorSymbolSupport()\n    Tests for native `Symbol.asyncIterator` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has native `Symbol.asyncIterator`\n        support.\n\n    Examples\n    --------\n    > var bool = hasAsyncIteratorSymbolSupport()\n    <boolean>\n\n    See Also\n    --------\n    hasIteratorSymbolSupport, hasSymbolSupport\n","hasAtobSupport":"\nhasAtobSupport()\n    Tests for native `atob` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `atob` support.\n\n    Examples\n    --------\n    > var bool = hasAtobSupport()\n    <boolean>\n\n    See Also\n    --------\n    hasBtoaSupport\n","hasBigInt64ArraySupport":"\nhasBigInt64ArraySupport()\n    Tests for native `BigInt64Array` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `BigInt64Array` support.\n\n    Examples\n    --------\n    > var bool = hasBigInt64ArraySupport()\n    <boolean>\n\n    See Also\n    --------\n    hasBigIntSupport, hasBigUint64ArraySupport\n","hasBigIntSupport":"\nhasBigIntSupport()\n    Tests for native `BigInt` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has native `BigInt` support.\n\n    Examples\n    --------\n    > var bool = hasBigIntSupport()\n    <boolean>\n\n","hasBigUint64ArraySupport":"\nhasBigUint64ArraySupport()\n    Tests for native `BigUint64Array` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `BigUint64Array` support.\n\n    Examples\n    --------\n    > var bool = hasBigUint64ArraySupport()\n    <boolean>\n\n    See Also\n    --------\n    hasBigIntSupport, hasBigInt64ArraySupport\n","hasBtoaSupport":"\nhasBtoaSupport()\n    Tests for native `btoa` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `btoa` support.\n\n    Examples\n    --------\n    > var bool = hasBtoaSupport()\n    <boolean>\n\n    See Also\n    --------\n    hasAtobSupport\n","hasClassSupport":"\nhasClassSupport()\n    Tests for native `class` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has native `class` support.\n\n    Examples\n    --------\n    > var bool = hasClassSupport()\n    <boolean>\n\n","hasDataViewSupport":"\nhasDataViewSupport()\n    Tests for native `DataView` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `DataView` support.\n\n    Examples\n    --------\n    > var bool = hasDataViewSupport()\n    <boolean>\n\n    See Also\n    --------\n    hasArrayBufferSupport\n","hasDefinePropertiesSupport":"\nhasDefinePropertiesSupport()\n    Tests for `Object.defineProperties` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Object.defineProperties`\n        support.\n\n    Examples\n    --------\n    > var bool = hasDefinePropertiesSupport()\n    <boolean>\n\n    See Also\n    --------\n    hasDefinePropertySupport\n","hasDefinePropertySupport":"\nhasDefinePropertySupport()\n    Tests for `Object.defineProperty` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Object.defineProperty`\n        support.\n\n    Examples\n    --------\n    > var bool = hasDefinePropertySupport()\n    <boolean>\n\n    See Also\n    --------\n    hasDefinePropertiesSupport\n","hasFloat32ArraySupport":"\nhasFloat32ArraySupport()\n    Tests for native `Float32Array` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Float32Array` support.\n\n    Examples\n    --------\n    > var bool = hasFloat32ArraySupport()\n    <boolean>\n\n","hasFloat64ArraySupport":"\nhasFloat64ArraySupport()\n    Tests for native `Float64Array` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Float64Array` support.\n\n    Examples\n    --------\n    > var bool = hasFloat64ArraySupport()\n    <boolean>\n\n","hasFunctionNameSupport":"\nhasFunctionNameSupport()\n    Tests for native function `name` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has function `name` support.\n\n    Examples\n    --------\n    > var bool = hasFunctionNameSupport()\n    <boolean>\n\n","hasGeneratorSupport":"\nhasGeneratorSupport()\n    Tests whether an environment supports native generator functions.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment support generator functions.\n\n    Examples\n    --------\n    > var bool = hasGeneratorSupport()\n    <boolean>\n\n","hasGlobalThisSupport":"\nhasGlobalThisSupport()\n    Tests for `globalThis` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `globalThis` support.\n\n    Examples\n    --------\n    > var bool = hasGlobalThisSupport()\n    <boolean>\n\n    See Also\n    --------\n    getGlobal\n","hasInt8ArraySupport":"\nhasInt8ArraySupport()\n    Tests for native `Int8Array` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Int8Array` support.\n\n    Examples\n    --------\n    > var bool = hasInt8ArraySupport()\n    <boolean>\n\n","hasInt16ArraySupport":"\nhasInt16ArraySupport()\n    Tests for native `Int16Array` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Int16Array` support.\n\n    Examples\n    --------\n    > var bool = hasInt16ArraySupport()\n    <boolean>\n\n","hasInt32ArraySupport":"\nhasInt32ArraySupport()\n    Tests for native `Int32Array` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Int32Array` support.\n\n    Examples\n    --------\n    > var bool = hasInt32ArraySupport()\n    <boolean>\n\n","hasIteratorSymbolSupport":"\nhasIteratorSymbolSupport()\n    Tests for native `Symbol.iterator` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has native `Symbol.iterator`\n        support.\n\n    Examples\n    --------\n    > var bool = hasIteratorSymbolSupport()\n    <boolean>\n\n    See Also\n    --------\n    hasAsyncIteratorSymbolSupport, hasSymbolSupport\n","hasMapSupport":"\nhasMapSupport()\n    Tests for native `Map` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Map` support.\n\n    Examples\n    --------\n    > var bool = hasMapSupport()\n    <boolean>\n\n","hasNodeBufferSupport":"\nhasNodeBufferSupport()\n    Tests for native `Buffer` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Buffer` support.\n\n    Examples\n    --------\n    > var bool = hasNodeBufferSupport()\n    <boolean>\n\n","hasOwnProp":"\nhasOwnProp( value, property )\n    Tests if an object has a specified property.\n\n    In contrast to the native `Object.prototype.hasOwnProperty`, this function\n    does not throw when provided `null` or `undefined`. Instead, the function\n    returns `false`.\n\n    Value arguments other than `null` or `undefined` are coerced to objects.\n\n    Property arguments are coerced to strings.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object has a specified property.\n\n    Examples\n    --------\n    > var beep = { 'boop': true };\n    > var bool = hasOwnProp( beep, 'boop' )\n    true\n    > bool = hasOwnProp( beep, 'bop' )\n    false\n\n    See Also\n    --------\n    hasProp\n","hasProp":"\nhasProp( value, property )\n    Tests if an object has a specified property, either own or inherited.\n\n    Value arguments other than `null` or `undefined` are coerced to objects.\n\n    Non-symbol property arguments are coerced to strings.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object has a specified property.\n\n    Examples\n    --------\n    > var beep = { 'boop': true };\n    > var bool = hasProp( beep, 'boop' )\n    true\n    > bool = hasProp( beep, 'toString' )\n    true\n    > bool = hasProp( beep, 'bop' )\n    false\n\n    See Also\n    --------\n    hasOwnProp\n","hasProxySupport":"\nhasProxySupport()\n    Tests whether an environment has native `Proxy` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has native `Proxy` support.\n\n    Examples\n    --------\n    > var bool = hasProxySupport()\n    <boolean>\n\n","hasSetSupport":"\nhasSetSupport()\n    Tests for native `Set` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has native `Set` support.\n\n    Examples\n    --------\n    > var bool = hasSetSupport()\n    <boolean>\n\n","hasSharedArrayBufferSupport":"\nhasSharedArrayBufferSupport()\n    Tests for native `SharedArrayBuffer` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `SharedArrayBuffer` support.\n\n    Examples\n    --------\n    > var bool = hasSharedArrayBufferSupport()\n    <boolean>\n\n    See Also\n    --------\n    hasArrayBufferSupport, hasFloat32ArraySupport, hasFloat64ArraySupport, hasInt16ArraySupport, hasInt32ArraySupport, hasInt8ArraySupport, hasNodeBufferSupport, hasUint16ArraySupport, hasUint32ArraySupport, hasUint8ArraySupport, hasUint8ClampedArraySupport\n","hasSymbolSupport":"\nhasSymbolSupport()\n    Tests for native `Symbol` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has native `Symbol` support.\n\n    Examples\n    --------\n    > var bool = hasSymbolSupport()\n    <boolean>\n\n    See Also\n    --------\n    hasIteratorSymbolSupport\n","hasToStringTagSupport":"\nhasToStringTagSupport()\n    Tests for native `toStringTag` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `toStringTag` support.\n\n    Examples\n    --------\n    > var bool = hasToStringTagSupport()\n    <boolean>\n\n","hasUint8ArraySupport":"\nhasUint8ArraySupport()\n    Tests for native `Uint8Array` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Uint8Array` support.\n\n    Examples\n    --------\n    > var bool = hasUint8ArraySupport()\n    <boolean>\n\n","hasUint8ClampedArraySupport":"\nhasUint8ClampedArraySupport()\n    Tests for native `Uint8ClampedArray` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Uint8ClampedArray` support.\n\n    Examples\n    --------\n    > var bool = hasUint8ClampedArraySupport()\n    <boolean>\n\n","hasUint16ArraySupport":"\nhasUint16ArraySupport()\n    Tests for native `Uint16Array` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Uint16Array` support.\n\n    Examples\n    --------\n    > var bool = hasUint16ArraySupport()\n    <boolean>\n\n","hasUint32ArraySupport":"\nhasUint32ArraySupport()\n    Tests for native `Uint32Array` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Uint32Array` support.\n\n    Examples\n    --------\n    > var bool = hasUint32ArraySupport()\n    <boolean>\n\n","hasUTF16SurrogatePairAt":"\nhasUTF16SurrogatePairAt( str, pos )\n    Tests if a position in a string marks the start of a UTF-16 surrogate pair.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    pos: integer\n        Position.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether surrogate pair exists at specified position.\n\n    Examples\n    --------\n    > var out = hasUTF16SurrogatePairAt( '🌷', 0 )\n    true\n    > out = hasUTF16SurrogatePairAt( '🌷', 1 )\n    false\n\n","hasWeakMapSupport":"\nhasWeakMapSupport()\n    Tests for native `WeakMap` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `WeakMap` support.\n\n    Examples\n    --------\n    > var bool = hasWeakMapSupport()\n    <boolean>\n\n","hasWeakSetSupport":"\nhasWeakSetSupport()\n    Tests for native `WeakSet` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `WeakSet` support.\n\n    Examples\n    --------\n    > var bool = hasWeakSetSupport()\n    <boolean>\n\n","hasWebAssemblySupport":"\nhasWebAssemblySupport()\n    Tests for native WebAssembly support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has native WebAssembly support.\n\n    Examples\n    --------\n    > var bool = hasWebAssemblySupport()\n    <boolean>\n\n","headercase":"\nheadercase( str )\n    Converts a string to HTTP header case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        HTTP header-cased string.\n\n    Examples\n    --------\n    > var out = headercase( 'Hello World!' )\n    'Hello-World'\n    > out = headercase( 'beep boop' )\n    'Beep-Boop'\n\n    See Also\n    --------\n    camelcase, kebabcase, pascalcase, snakecase","HERNDON_VENUS_SEMIDIAMETERS":"\nHERNDON_VENUS_SEMIDIAMETERS()\n    Returns fifteen observations of the vertical semidiameter of Venus, made by\n    Lieutenant Herndon, with the meridian circle at Washington, in the year\n    1846.\n\n    This dataset is a classic dataset commonly used in examples demonstrating\n    outlier detection.\n\n    Returns\n    -------\n    out: Array<number>\n        Observations.\n\n    Examples\n    --------\n    > var d = HERNDON_VENUS_SEMIDIAMETERS()\n    [ -0.30, -0.44, ..., 0.39, 0.10 ]\n\n    References\n    ----------\n    - Chauvenet, William. 1868. _A Manual of Spherical and Practical Astronomy_.\n    5th ed. Vol. 5. London, England: Trübner & Co.\n    - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n    Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n    of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n    - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n    Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n    00401706.1969.10490657.\n    - Tietjen, Gary L., and Roger H. Moore. 1972. \"Some Grubbs-Type Statistics\n    for the Detection of Several Outliers.\" _Technometrics_ 14 (3). Taylor &\n    Francis: 583–97. doi:10.1080/00401706.1972.10488948.\n\n","homedir":"\nhomedir()\n    Returns the current user's home directory.\n\n    If unable to locate a home directory, the function returns `null`.\n\n    Returns\n    -------\n    out: string|null\n        Home directory.\n\n    Examples\n    --------\n    > var home = homedir()\n    e.g., '/Users/<username>'\n\n    See Also\n    --------\n    configdir, tmpdir\n","HOURS_IN_DAY":"\nHOURS_IN_DAY\n    Number of hours in a day.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var days = 3.14;\n    > var hrs = days * HOURS_IN_DAY\n    75.36\n\n    See Also\n    --------\n    HOURS_IN_WEEK\n","HOURS_IN_WEEK":"\nHOURS_IN_WEEK\n    Number of hours in a week.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var wks = 3.14;\n    > var hrs = wks * HOURS_IN_WEEK\n    527.52\n\n    See Also\n    --------\n    HOURS_IN_DAY\n","hoursInMonth":"\nhoursInMonth( [month[, year]] )\n    Returns the number of hours in a month.\n\n    By default, the function returns the number of hours in the current month of\n    the current year (according to local time). To determine the number of hours\n    for a particular month and year, provide `month` and `year` arguments.\n\n    A `month` may be either a month's integer value, three letter abbreviation,\n    or full name (case insensitive).\n\n    The function's return value is a generalization and does **not** take into\n    account inaccuracies due to daylight savings conventions, crossing\n    timezones, or other complications with time and dates.\n\n    Parameters\n    ----------\n    month: string|Date|integer (optional)\n        Month.\n\n    year: integer (optional)\n        Year.\n\n    Returns\n    -------\n    out: integer\n        Hours in a month.\n\n    Examples\n    --------\n    > var num = hoursInMonth()\n    <number>\n    > num = hoursInMonth( 2 )\n    <number>\n    > num = hoursInMonth( 2, 2016 )\n    696\n    > num = hoursInMonth( 2, 2017 )\n    672\n\n    // Other ways to supply month:\n    > num = hoursInMonth( 'feb', 2016 )\n    696\n    > num = hoursInMonth( 'february', 2016 )\n    696\n\n    See Also\n    --------\n    hoursInYear\n","hoursInYear":"\nhoursInYear( [value] )\n    Returns the number of hours in a year according to the Gregorian calendar.\n\n    By default, the function returns the number of hours in the current year\n    (according to local time). To determine the number of hours for a particular\n    year, provide either a year or a `Date` object.\n\n    The function's return value is a generalization and does **not** take into\n    account inaccuracies due to daylight savings conventions, crossing\n    timezones, or other complications with time and dates.\n\n    Parameters\n    ----------\n    value: integer|Date (optional)\n        Year or `Date` object.\n\n    Returns\n    -------\n    out: integer\n        Number of hours in a year.\n\n    Examples\n    --------\n    > var num = hoursInYear()\n    <number>\n    > num = hoursInYear( 2016 )\n    8784\n    > num = hoursInYear( 2017 )\n    8760\n\n    See Also\n    --------\n    hoursInMonth\n","httpServer":"\nhttpServer( [options,] [requestListener] )\n    Returns a function to create an HTTP server.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.port: integer (optional)\n        Server port. Default: `0` (i.e., randomly assigned).\n\n    options.maxport: integer (optional)\n        Max server port when port hunting. Default: `maxport = port`.\n\n    options.hostname: string (optional)\n        Server hostname.\n\n    options.address: string (optional)\n        Server address. Default: `'127.0.0.1'`.\n\n    requestListener: Function (optional)\n        Request callback.\n\n    Returns\n    -------\n    createServer: Function\n        Function to create an HTTP server.\n\n    Examples\n    --------\n    // Basic usage:\n    > var createServer = httpServer()\n    <Function>\n\n    // Provide a request callback:\n    > function onRequest( request, response ) {\n    ...    console.log( request.url );\n    ...    response.end( 'OK' );\n    ... };\n    > createServer = httpServer( onRequest )\n    <Function>\n\n    // Specify a specific port:\n    > var opts = { 'port': 7331 };\n    > createServer = httpServer( opts )\n    <Function>\n\n\ncreateServer( done )\n    Creates an HTTP server.\n\n    Parameters\n    ----------\n    done: Function\n        Callback to invoke after creating a server.\n\n    Examples\n    --------\n    > function done( error, server ) {\n    ...    if ( error ) {\n    ...        throw error;\n    ...    }\n    ...    console.log( 'Success!' );\n    ...    server.close();\n    ... };\n    > var createServer = httpServer();\n    > createServer( done );\n\n","identity":"\nidentity( x )\n    Identity function.\n\n    Parameters\n    ----------\n    x: any\n        Input value.\n\n    Returns\n    -------\n    out: any\n        Input value.\n\n    Examples\n    --------\n    > var v = identity( 3.14 )\n    3.14\n\n    See Also\n    --------\n    constantFunction\n","ifelse":"\nifelse( bool, x, y )\n    If a condition is truthy, returns `x`; otherwise, returns `y`.\n\n    Parameters\n    ----------\n    bool: boolean\n        Condition.\n\n    x: any\n        Value to return if a condition is truthy.\n\n    y: any\n        Value to return if a condition is falsy.\n\n    Returns\n    -------\n    z: any\n        Either `x` or `y`.\n\n    Examples\n    --------\n    > var z = ifelse( true, 1.0, -1.0 )\n    1.0\n    > z = ifelse( false, 1.0, -1.0 )\n    -1.0\n\n    See Also\n    --------\n    ifelseAsync, ifthen\n","ifelseAsync":"\nifelseAsync( predicate, x, y, done )\n    If a predicate function returns a truthy value, returns `x`; otherwise,\n    returns `y`.\n\n    A predicate function is provided a single argument:\n\n    - clbk: callback to invoke upon predicate completion.\n\n    The callback function accepts two arguments:\n\n    - error: error object.\n    - bool: condition used to determine whether to invoke `x` or `y`.\n\n    The `done` callback is invoked upon function completion and is provided at\n    most two arguments:\n\n    - error: error object.\n    - result: either `x` or `y`.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function.\n\n    x: any\n        Value to return if a condition is truthy.\n\n    y: any\n        Value to return if a condition is falsy.\n\n    done: Function\n        Callback to invoke upon completion.\n\n    Examples\n    --------\n    > function predicate( clbk ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         clbk( null, true );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > ifelseAsync( predicate, 'beep', 'boop', done )\n    'beep'\n\n    See Also\n    --------\n    ifthenAsync, ifelse\n","ifthen":"\nifthen( bool, x, y )\n    If a condition is truthy, invoke `x`; otherwise, invoke `y`.\n\n    Parameters\n    ----------\n    bool: boolean\n        Condition.\n\n    x: Function\n        Function to invoke if a condition is truthy.\n\n    y: Function\n        Function to invoke if a condition is falsy.\n\n    Returns\n    -------\n    z: any\n        Return value of either `x` or `y`.\n\n    Examples\n    --------\n    > function x() { return 1.0; };\n    > function y() { return -1.0; };\n    > var z = ifthen( true, x, y )\n    1.0\n    > z = ifthen( false, x, y )\n    -1.0\n\n    See Also\n    --------\n    ifthenAsync, ifelse\n","ifthenAsync":"\nifthenAsync( predicate, x, y, done )\n    If a predicate function returns a truthy value, invokes `x`; otherwise,\n    invokes `y`.\n\n    The predicate function is provided a single argument:\n\n    - clbk: callback to invoke upon predicate function completion.\n\n    The predicate function callback accepts two arguments:\n\n    - error: error object.\n    - bool: condition used to determine whether to invoke `x` or `y`.\n\n    Both `x` and `y` are provided a single argument:\n\n    - clbk: callback to invoke upon function completion.\n\n    The callback function accepts any number of arguments, with the first\n    argument reserved for providing an error.\n\n    If the error argument is falsy, the `done` callback is invoked with its\n    first argument as `null` and all other provided arguments.\n\n    If the error argument is truthy, the `done` callback is invoked with only an\n    error argument.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function.\n\n    x: Function\n        Function to invoke if a condition is truthy.\n\n    y: Function\n        Function to invoke if a condition is falsy.\n\n    done: Function\n        Callback to invoke upon completion.\n\n    Examples\n    --------\n    > function predicate( clbk ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         clbk( null, false );\n    ...     }\n    ... };\n    > function x( clbk ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         clbk( null, 'beep' );\n    ...     }\n    ... };\n    > function y( clbk ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         clbk( null, 'boop' );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > ifthenAsync( predicate, x, y, done )\n    'boop'\n\n    See Also\n    --------\n    ifelseAsync, ifthen\n","imag":"\nimag( z )\n    Returns the imaginary component of a double-precision complex floating-point\n    number.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    im: number\n        Imaginary component.\n\n    Examples\n    --------\n    > var z = new Complex128( 5.0, 3.0 );\n    > var im = imag( z )\n    3.0\n\n    See Also\n    --------\n    real, reim\n","imagf":"\nimagf( z )\n    Returns the imaginary component of a single-precision complex floating-point\n    number.\n\n    Parameters\n    ----------\n    z: Complex64\n        Complex number.\n\n    Returns\n    -------\n    im: number\n        Imaginary component.\n\n    Examples\n    --------\n    > var z = new Complex64( 5.0, 3.0 );\n    > var im = imagf( z )\n    3.0\n\n    See Also\n    --------\n    imag, realf, reimf\n","IMG_ACANTHUS_MOLLIS":"\nIMG_ACANTHUS_MOLLIS()\n    Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n    print *Acanthus mollis*.\n\n    Returns\n    -------\n    out: Buffer\n        Image data.\n\n    Examples\n    --------\n    > var img = IMG_ACANTHUS_MOLLIS()\n    <Buffer>\n\n    References\n    ----------\n    - Blossfeldt, Karl. 1928. *Acanthus mollis*. <http://www.getty.edu/art/\n    collection/objects/35443/karl-blossfeldt-acanthus-mollis-german-1928/>.\n\n    * Digital image courtesy of the Getty's Open Content Program. While there\n    are no restrictions or conditions on the use of open content images, the\n    Getty would appreciate a gratis copy of any scholarly publications in which\n    the images are reproduced in order to maintain the collection bibliography.\n    Copies may be sent to the attention of:\n\n      Open Content Program\n      Registrar's Office\n      The J. Paul Getty Museum\n      1200 Getty Center Drive, Suite 1000\n      Los Angeles, CA 90049\n\n    See Also\n    --------\n    IMG_ALLIUM_OREOPHILUM\n","IMG_AIRPLANE_FROM_ABOVE":"\nIMG_AIRPLANE_FROM_ABOVE()\n    Returns a `Buffer` containing image data of Fédèle Azari's gelatin silver\n    print of an airplane, viewed from above looking down.\n\n    Returns\n    -------\n    out: Buffer\n        Image data.\n\n    Examples\n    --------\n    > var img = IMG_AIRPLANE_FROM_ABOVE()\n    <Buffer>\n\n    References\n    ----------\n    - Azari, Fédèle. 1929. (no title). <http://www.getty.edu/art/collection/\n    objects/134512/fedele-azari-airplane-viewed-from-above-looking-down-italian-\n    1914-1929/>.\n\n    * Digital image courtesy of the Getty's Open Content Program. While there\n    are no restrictions or conditions on the use of open content images, the\n    Getty would appreciate a gratis copy of any scholarly publications in which\n    the images are reproduced in order to maintain the collection bibliography.\n    Copies may be sent to the attention of:\n\n      Open Content Program\n      Registrar's Office\n      The J. Paul Getty Museum\n      1200 Getty Center Drive, Suite 1000\n      Los Angeles, CA 90049\n\n","IMG_ALLIUM_OREOPHILUM":"\nIMG_ALLIUM_OREOPHILUM()\n    Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n    print *Allium ostrowskianum*.\n\n    Returns\n    -------\n    out: Buffer\n        Image data.\n\n    Examples\n    --------\n    > var img = IMG_ALLIUM_OREOPHILUM()\n    <Buffer>\n\n    References\n    ----------\n    - Blossfeldt, Karl. 1928. *Allium ostrowskianum*. <http://www.getty.edu/art/\n    collection/objects/35448/karl-blossfeldt-allium-ostrowskianum-\n    knoblauchpflanze-german-1928/>.\n\n    * Digital image courtesy of the Getty's Open Content Program. While there\n    are no restrictions or conditions on the use of open content images, the\n    Getty would appreciate a gratis copy of any scholarly publications in which\n    the images are reproduced in order to maintain the collection bibliography.\n    Copies may be sent to the attention of:\n\n      Open Content Program\n      Registrar's Office\n      The J. Paul Getty Museum\n      1200 Getty Center Drive, Suite 1000\n      Los Angeles, CA 90049\n\n    See Also\n    --------\n    IMG_ACANTHUS_MOLLIS\n","IMG_BLACK_CANYON":"\nIMG_BLACK_CANYON()\n    Returns a `Buffer` containing image data of Timothy H. O'Sullivan's albumen\n    silver print *Black Cañon, Colorado River, From Camp 8, Looking Above*.\n\n    Returns\n    -------\n    out: Buffer\n        Image data.\n\n    Examples\n    --------\n    > var img = IMG_BLACK_CANYON()\n    <Buffer>\n\n    References\n    ----------\n    - O'Sullivan, Timothy H. 1871. *Black Cañon, Colorado River, From Camp 8,\n    Looking Above*. <http://www.getty.edu/art/collection/objects/40209/timothy-\n    h-o'sullivan-black-canon-colorado-river-from-camp-8-looking-above-american-\n    1871/>.\n\n    * Digital image courtesy of the Getty's Open Content Program. While there\n    are no restrictions or conditions on the use of open content images, the\n    Getty would appreciate a gratis copy of any scholarly publications in which\n    the images are reproduced in order to maintain the collection bibliography.\n    Copies may be sent to the attention of:\n\n      Open Content Program\n      Registrar's Office\n      The J. Paul Getty Museum\n      1200 Getty Center Drive, Suite 1000\n      Los Angeles, CA 90049\n\n","IMG_DUST_BOWL_HOME":"\nIMG_DUST_BOWL_HOME()\n    Returns a `Buffer` containing image data of Dorothea Lange's gelatin silver\n    print of an abandoned Dust Bowl home.\n\n    Returns\n    -------\n    out: Buffer\n        Image data.\n\n    Examples\n    --------\n    > var img = IMG_DUST_BOWL_HOME()\n    <Buffer>\n\n    References\n    ----------\n    - Lange, Dorothea. 1940. *Abandoned Dust Bowl Home*. <http://www.getty.edu/\n    art/collection/objects/128362/dorothea-lange-abandoned-dust-bowl-home-\n    american-about-1935-1940/>.\n\n    * Digital image courtesy of the Getty's Open Content Program. While there\n    are no restrictions or conditions on the use of open content images, the\n    Getty would appreciate a gratis copy of any scholarly publications in which\n    the images are reproduced in order to maintain the collection bibliography.\n    Copies may be sent to the attention of:\n\n      Open Content Program\n      Registrar's Office\n      The J. Paul Getty Museum\n      1200 Getty Center Drive, Suite 1000\n      Los Angeles, CA 90049\n\n","IMG_FRENCH_ALPINE_LANDSCAPE":"\nIMG_FRENCH_ALPINE_LANDSCAPE()\n    Returns a `Buffer` containing image data of Adolphe Braun's carbon print of\n    a French alpine landscape.\n\n    Returns\n    -------\n    out: Buffer\n        Image data.\n\n    Examples\n    --------\n    > var img = IMG_FRENCH_ALPINE_LANDSCAPE()\n    <Buffer>\n\n    References\n    ----------\n    - Braun, Adolphe. 1870. (no title). <http://www.getty.edu/art/collection/\n    objects/54324/adolphe-braun-alpine-landscape-french-1865-1870/>.\n\n    * Digital image courtesy of the Getty's Open Content Program. While there\n    are no restrictions or conditions on the use of open content images, the\n    Getty would appreciate a gratis copy of any scholarly publications in which\n    the images are reproduced in order to maintain the collection bibliography.\n    Copies may be sent to the attention of:\n\n      Open Content Program\n      Registrar's Office\n      The J. Paul Getty Museum\n      1200 Getty Center Drive, Suite 1000\n      Los Angeles, CA 90049\n\n","IMG_LOCOMOTION_HOUSE_CAT":"\nIMG_LOCOMOTION_HOUSE_CAT()\n    Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n    collotype of a house cat (24 views).\n\n    Returns\n    -------\n    out: Buffer\n        Image data.\n\n    Examples\n    --------\n    > var img = IMG_LOCOMOTION_HOUSE_CAT()\n    <Buffer>\n\n    References\n    ----------\n    - Muybridge, Eadweard J. 1887. *Animal Locomotion*. <http://www.getty.edu/\n    art/collection/objects/40918/eadweard-j-muybridge-animal-locomotion-american\n    -1887/>.\n\n    * Digital image courtesy of the Getty's Open Content Program. While there\n    are no restrictions or conditions on the use of open content images, the\n    Getty would appreciate a gratis copy of any scholarly publications in which\n    the images are reproduced in order to maintain the collection bibliography.\n    Copies may be sent to the attention of:\n\n      Open Content Program\n      Registrar's Office\n      The J. Paul Getty Museum\n      1200 Getty Center Drive, Suite 1000\n      Los Angeles, CA 90049\n\n    See Also\n    --------\n    IMG_LOCOMOTION_NUDE_MALE\n","IMG_LOCOMOTION_NUDE_MALE":"\nIMG_LOCOMOTION_NUDE_MALE()\n    Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n    collotype of a nude male moving in place (48 views).\n\n    Returns\n    -------\n    out: Buffer\n        Image data.\n\n    Examples\n    --------\n    > var img = IMG_LOCOMOTION_NUDE_MALE()\n    <Buffer>\n\n    References\n    ----------\n    - Muybridge, Eadweard J. 1887. *Animal Locomotion*. <http://www.getty.edu/\n    art/collection/objects/40918/eadweard-j-muybridge-animal-locomotion-american\n    -1887/>.\n\n    * Digital image courtesy of the Getty's Open Content Program. While there\n    are no restrictions or conditions on the use of open content images, the\n    Getty would appreciate a gratis copy of any scholarly publications in which\n    the images are reproduced in order to maintain the collection bibliography.\n    Copies may be sent to the attention of:\n\n      Open Content Program\n      Registrar's Office\n      The J. Paul Getty Museum\n      1200 Getty Center Drive, Suite 1000\n      Los Angeles, CA 90049\n\n    See Also\n    --------\n    IMG_LOCOMOTION_HOUSE_CAT\n","IMG_MARCH_PASTORAL":"\nIMG_MARCH_PASTORAL()\n    Returns a `Buffer` containing image data of Peter Henry Emerson's\n    photogravure of sheep in a pastoral setting.\n\n    Returns\n    -------\n    out: Buffer\n        Image data.\n\n    Examples\n    --------\n    > var img = IMG_MARCH_PASTORAL()\n    <Buffer>\n\n    References\n    ----------\n    - Emerson, Peter Henry. 1888. *A March Pastoral*. <http://www.getty.edu/art/\n    collection/objects/141994/peter-henry-emerson-a-march-pastoral-suffolk-\n    british-1888/>.\n\n    * Digital image courtesy of the Getty's Open Content Program. While there\n    are no restrictions or conditions on the use of open content images, the\n    Getty would appreciate a gratis copy of any scholarly publications in which\n    the images are reproduced in order to maintain the collection bibliography.\n    Copies may be sent to the attention of:\n\n      Open Content Program\n      Registrar's Office\n      The J. Paul Getty Museum\n      1200 Getty Center Drive, Suite 1000\n      Los Angeles, CA 90049\n\n","IMG_NAGASAKI_BOATS":"\nIMG_NAGASAKI_BOATS()\n    Returns a `Buffer` containing image data of Felice Beato's albumen silver\n    print of boats in a river in Nagasaki.\n\n    Returns\n    -------\n    out: Buffer\n        Image data.\n\n    Examples\n    --------\n    > var img = IMG_NAGASAKI_BOATS()\n    <Buffer>\n\n    References\n    ----------\n    - Beato, Felice. 1865. (no title). <http://www.getty.edu/art/collection/\n    objects/241797/felice-beato-boats-in-river-nagasaki-british-about-1865/>.\n\n    * Digital image courtesy of the Getty's Open Content Program. While there\n    are no restrictions or conditions on the use of open content images, the\n    Getty would appreciate a gratis copy of any scholarly publications in which\n    the images are reproduced in order to maintain the collection bibliography.\n    Copies may be sent to the attention of:\n\n      Open Content Program\n      Registrar's Office\n      The J. Paul Getty Museum\n      1200 Getty Center Drive, Suite 1000\n      Los Angeles, CA 90049\n\n","incrapcorr":"\nincrapcorr( [mx, my] )\n    Returns an accumulator function which incrementally computes the absolute\n    value of the sample Pearson product-moment correlation coefficient.\n\n    If provided values, the accumulator function returns an updated accumulated\n    value. If not provided values, the accumulator function returns the current\n    accumulated value.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    mx: number (optional)\n        Known mean.\n\n    my: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrapcorr();\n    > var ar = accumulator()\n    null\n    > ar = accumulator( 2.0, 1.0 )\n    0.0\n    > ar = accumulator( -5.0, 3.14 )\n    ~1.0\n    > ar = accumulator()\n    ~1.0\n\n    See Also\n    --------\n    incrmapcorr, incrpcorr, incrpcorr2\n","incrBinaryClassification":"\nincrBinaryClassification( N[, options] )\n    Returns an accumulator function which incrementally performs binary\n    classification using stochastic gradient descent (SGD).\n\n    If provided a feature vector and response value, the accumulator function\n    updates a binary classification model and returns updated model\n    coefficients.\n\n    If not provided a feature vector and response value, the accumulator\n    function returns the current model coefficients.\n\n    Stochastic gradient descent is sensitive to the scaling of the features. One\n    is advised to either scale each feature to `[0,1]` or `[-1,1]` or to\n    transform the features into z-scores with zero mean and unit variance. One\n    should keep in mind that the same scaling has to be applied to training data\n    in order to obtain accurate predictions.\n\n    In general, the more data provided to an accumulator, the more reliable the\n    model predictions.\n\n    Parameters\n    ----------\n    N: integer\n        Number of features.\n\n    options: Object (optional)\n        Function options.\n\n    options.intercept: boolean (optional)\n        Boolean indicating whether to include an intercept. Default: true.\n\n    options.lambda: number (optional)\n        Regularization parameter. Default: 1.0e-4.\n\n    options.learningRate: ArrayLike (optional)\n        Learning rate function and associated (optional) parameters. The first\n        array element specifies the learning rate function and must be one of\n        the following:\n\n        - ['constant', ...]: constant learning rate function. To set the\n        learning rate, provide a second array element. By default, when the\n        learn rate function is 'constant', the learning rate is set to 0.02.\n\n        - ['basic']: basic learning rate function according to the formula\n        `10/(10+t)` where `t` is the current iteration.\n\n        - ['invscaling', ...]: inverse scaling learning rate function according\n        to the formula `eta0/pow(t, power_t)` where `eta0` is the initial\n        learning rate and `power_t` is the exponent controlling how quickly the\n        learning rate decreases. To set the initial learning rate, provide a\n        second array element. By default, the initial learning rate is 0.02. To\n        set the exponent, provide a third array element. By default, the\n        exponent is 0.5.\n\n        - ['pegasos']: Pegasos learning rate function according to the formula\n        `1/(lambda*t)` where `t` is the current iteration and `lambda` is the\n        regularization parameter.\n\n        Default: ['basic'].\n\n    options.loss: string (optional)\n        Loss function. Must be one of the following:\n\n        - hinge: hinge loss function. Corresponds to a soft-margin linear\n        Support Vector Machine (SVM), which can handle non-linearly separable\n        data.\n\n        - log: logistic loss function. Corresponds to Logistic Regression.\n\n        - modifiedHuber: Huber loss function variant for classification.\n\n        - perceptron: hinge loss function without a margin. Corresponds to the\n        original Perceptron by Rosenblatt.\n\n        - squaredHinge: squared hinge loss function SVM (L2-SVM).\n\n        Default: 'log'.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    acc.predict: Function\n        Predicts response values for one ore more observation vectors. Provide a\n        second argument to specify the prediction type. Must be one of the\n        following: 'label', 'probability', or 'linear'. Default: 'label'.\n\n        Note that the probability prediction type is only compatible with 'log'\n        and 'modifiedHuber' loss functions.\n\n    Examples\n    --------\n    // Create an accumulator:\n    > var opts = {};\n    > opts.intercept = true;\n    > opts.lambda = 1.0e-5;\n    > var acc = incrBinaryClassification( 3, opts );\n\n    // Update the model:\n    > var buf = new Float64Array( [ 2.3, 1.0, 5.0 ] );\n    > var x = array( buf );\n    > var coefs = acc( x, 1 )\n    <ndarray>\n\n    // Create a new observation vector:\n    > buf = new Float64Array( [ 2.3, 5.3, 8.6 ] );\n    > x = array( buf );\n\n    // Predict the response value:\n    > var yhat = acc.predict( x )\n    <ndarray>\n\n    See Also\n    --------\n    incrSGDRegression\n","incrcount":"\nincrcount()\n    Returns an accumulator function which incrementally updates a count.\n\n    If provided a value, the accumulator function returns an updated count. If\n    not provided a value, the accumulator function returns the current count.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrcount();\n    > var v = accumulator()\n    0\n    > v = accumulator( 2.0 )\n    1\n    > v = accumulator( -5.0 )\n    2\n    > v = accumulator()\n    2\n\n    See Also\n    --------\n    incrmean, incrsum, incrsummary\n","incrcovariance":"\nincrcovariance( [mx, my] )\n    Returns an accumulator function which incrementally computes an unbiased\n    sample covariance.\n\n    If provided values, the accumulator function returns an updated unbiased\n    sample covariance. If not provided values, the accumulator function returns\n    the current unbiased sample covariance.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    mx: number (optional)\n        Known mean.\n\n    my: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrcovariance();\n    > var v = accumulator()\n    null\n    > v = accumulator( 2.0, 1.0 )\n    0.0\n    > v = accumulator( -5.0, 3.14 )\n    ~-7.49\n    > v = accumulator()\n    ~-7.49\n\n    See Also\n    --------\n    incrmcovariance, incrpcorr, incrvariance\n","incrcovmat":"\nincrcovmat( out[, means] )\n    Returns an accumulator function which incrementally computes an unbiased\n    sample covariance matrix.\n\n    If provided a data vector, the accumulator function returns an updated\n    unbiased sample covariance matrix. If not provided a data vector, the\n    accumulator function returns the current unbiased sample covariance matrix.\n\n    Parameters\n    ----------\n    out: integer|ndarray\n        Order of the covariance matrix or a square 2-dimensional ndarray for\n        storing the covariance matrix.\n\n    means: ndarray (optional)\n        Known means.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrcovmat( 2 );\n    > var out = accumulator()\n    <ndarray>\n    > var buf = new Float64Array( 2 );\n    > var shape = [ 2 ];\n    > var strides = [ 1 ];\n    > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n    > v.set( 0, 2.0 );\n    > v.set( 1, 1.0 );\n    > out = accumulator( v )\n    <ndarray>\n    > v.set( 0, -5.0 );\n    > v.set( 1, 3.14 );\n    > out = accumulator( v )\n    <ndarray>\n    > out = accumulator()\n    <ndarray>\n\n    See Also\n    --------\n    incrcovariance, incrpcorrmat\n","incrcv":"\nincrcv( [mean] )\n    Returns an accumulator function which incrementally computes the coefficient\n    of variation (CV).\n\n    If provided a value, the accumulator function returns an updated accumulated\n    value. If not provided a value, the accumulator function returns the current\n    accumulated value.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    mean: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrcv();\n    > var cv = accumulator()\n    null\n    > cv = accumulator( 2.0 )\n    0.0\n    > cv = accumulator( 1.0 )\n    ~0.47\n    > cv = accumulator()\n    ~0.47\n\n    See Also\n    --------\n    incrmean, incrmcv, incrstdev, incrvmr\n","increwmean":"\nincrewmean( α )\n    Returns an accumulator function which incrementally computes an\n    exponentially weighted mean, where α is a smoothing factor between 0 and 1.\n\n    If provided a value, the accumulator function returns an updated mean. If\n    not provided a value, the accumulator function returns the current mean.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    α: number\n        Smoothing factor (value between 0 and 1).\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = increwmean( 0.5 );\n    > var v = accumulator()\n    null\n    > v = accumulator( 2.0 )\n    2.0\n    > v = accumulator( -5.0 )\n    -1.5\n    > v = accumulator()\n    -1.5\n\n    See Also\n    --------\n    increwvariance, incrmean, incrmmean, incrwmean\n","increwstdev":"\nincrewstdev( α )\n    Returns an accumulator function which incrementally computes an\n    exponentially weighted standard deviation, where α is a smoothing factor\n    between 0 and 1.\n\n    If provided a value, the accumulator function returns an updated standard\n    deviation. If not provided a value, the accumulator function returns the\n    current standard deviation.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    α: number\n        Smoothing factor (value between 0 and 1).\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = increwstdev( 0.5 );\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    0.0\n    > s = accumulator( -5.0 )\n    3.5\n    > s = accumulator()\n    3.5\n\n    See Also\n    --------\n    increwvariance, incrmstdev, incrstdev\n","increwvariance":"\nincrewvariance( α )\n    Returns an accumulator function which incrementally computes an\n    exponentially weighted variance, where α is a smoothing factor between 0 and\n    1.\n\n    If provided a value, the accumulator function returns an updated variance.\n    If not provided a value, the accumulator function returns the current\n    variance.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    α: number\n        Smoothing factor (value between 0 and 1).\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = increwvariance( 0.5 );\n    > var v = accumulator()\n    null\n    > v = accumulator( 2.0 )\n    0.0\n    > v = accumulator( -5.0 )\n    12.25\n    > v = accumulator()\n    12.25\n\n    See Also\n    --------\n    increwmean, increwstdev, incrvariance, incrmvariance\n","incrgmean":"\nincrgmean()\n    Returns an accumulator function which incrementally computes a geometric\n    mean.\n\n    If provided a value, the accumulator function returns an updated geometric\n    mean. If not provided a value, the accumulator function returns the current\n    geometric mean.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    If provided a negative value, the accumulated value is `NaN` for all future\n    invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrgmean();\n    > var v = accumulator()\n    null\n    > v = accumulator( 2.0 )\n    2.0\n    > v = accumulator( 5.0 )\n    ~3.16\n    > v = accumulator()\n    ~3.16\n\n    See Also\n    --------\n    incrhmean, incrmean, incrmgmean, incrsummary\n","incrgrubbs":"\nincrgrubbs( [options] )\n    Returns an accumulator function which incrementally performs Grubbs' test\n    for detecting outliers.\n\n    Grubbs' test assumes that data is normally distributed. Accordingly, one\n    should first verify that the data can be reasonably approximated by a normal\n    distribution before applying the Grubbs' test.\n\n    If provided a value, the accumulator function returns updated test results.\n    If not provided a value, the accumulator function returns the current test\n    results.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the test statistic is `NaN` for all future invocations.\n\n    The accumulator must be provided *at least* three data points before\n    performing Grubbs' test. Until at least three data points are provided, the\n    accumulator returns `null`.\n\n    The accumulator function returns an object having the following fields:\n\n    - rejected: boolean indicating whether the null hypothesis should be\n    rejected.\n    - alpha: significance level.\n    - criticalValue: critical value.\n    - statistic: test statistic.\n    - df: degrees of freedom.\n    - mean: sample mean.\n    - sd: corrected sample standard deviation.\n    - min: minimum value.\n    - max: maximum value.\n    - alt: alternative hypothesis.\n    - method: method name.\n    - print: method for pretty-printing test output.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.alpha: number (optional)\n        Significance level. Default: 0.05.\n\n    options.alternative: string (optional)\n        Alternative hypothesis. The option may be one of the following values:\n\n        - 'two-sided': test whether the minimum or maximum value is an outlier.\n        - 'min': test whether the minimum value is an outlier.\n        - 'max': test whether the maximum value is an outlier.\n\n        Default: 'two-sided'.\n\n    options.init: integer (optional)\n        Number of data points the accumulator should use to compute initial\n        statistics *before* testing for an outlier. Until the accumulator is\n        provided the number of data points specified by this option, the\n        accumulator returns `null`. Default: 100.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var acc = incrgrubbs();\n    > var res = acc()\n    null\n    > for ( var i = 0; i < 200; i++ ) {\n    ...     res = acc( base.random.normal( 10.0, 5.0 ) );\n    ... };\n    > res.print()\n\n    References\n    ----------\n    - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n    Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n    of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n    - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n    Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n    00401706.1969.10490657.\n\n    See Also\n    --------\n    incrmgrubbs\n","incrhmean":"\nincrhmean()\n    Returns an accumulator function which incrementally computes a harmonic\n    mean.\n\n    If provided a value, the accumulator function returns an updated harmonic\n    mean. If not provided a value, the accumulator function returns the current\n    harmonic mean.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrhmean();\n    > var v = accumulator()\n    null\n    > v = accumulator( 2.0 )\n    2.0\n    > v = accumulator( 5.0 )\n    ~2.86\n    > v = accumulator()\n    ~2.86\n\n    See Also\n    --------\n    incrgmean, incrmean, incrmhmean, incrsummary\n","incrkmeans":"\nincrkmeans( k[, ndims][, options] )\n    Returns an accumulator function which incrementally partitions data into `k`\n    clusters.\n\n    If not provided initial centroids, the accumulator caches data vectors for\n    subsequent centroid initialization. Until an accumulator computes initial\n    centroids, an accumulator returns `null`.\n\n    Once an accumulator has initial centroids (either provided or computed), if\n    provided a data vector, the accumulator function returns updated cluster\n    results. If not provided a data vector, the accumulator function returns the\n    current cluster results.\n\n    Cluster results are comprised of the following:\n\n    - centroids: a `k x ndims` matrix containing centroid locations. Each\n      centroid is the component-wise mean of the data points assigned to a\n      centroid's corresponding cluster.\n    - stats: a `k x 4` matrix containing cluster statistics.\n\n    Cluster statistics consists of the following columns:\n\n    - 0: number of data points assigned to a cluster.\n    - 1: total within-cluster sum of squared distances.\n    - 2: arithmetic mean of squared distances.\n    - 3: corrected sample standard deviation of squared distances.\n\n    Because an accumulator incrementally partitions data, one should *not*\n    expect cluster statistics to match similar statistics had provided data been\n    analyzed via a batch algorithm. In an incremental context, data points which\n    would not be considered part of a particular cluster when analyzed via a\n    batch algorithm may contribute to that cluster's statistics when analyzed\n    incrementally.\n\n    In general, the more data provided to an accumulator, the more reliable the\n    cluster statistics.\n\n    Parameters\n    ----------\n    k: integer|ndarray\n        Number of clusters or a `k x ndims` matrix containing initial centroids.\n\n    ndims: integer (optional)\n        Number of dimensions. This argument must accompany an integer-valued\n        first argument.\n\n    options: Object (optional)\n        Function options.\n\n    options.metric: string (optional)\n        Distance metric. Must be one of the following: 'euclidean', 'cosine', or\n        'correlation'. Default: 'euclidean'.\n\n    options.init: ArrayLike (optional)\n        Centroid initialization method and associated (optional) parameters. The\n        first array element specifies the initialization method and must be one\n        of the following: 'kmeans++', 'sample', or 'forgy'. The second array\n        element specifies the number of data points to use when calculating\n        initial centroids. When performing kmeans++ initialization, the third\n        array element specifies the number of trials to perform when randomly\n        selecting candidate centroids. Typically, more trials is correlated with\n        initial centroids which lead to better clustering; however, a greater\n        number of trials increases computational overhead. Default: ['kmeans++',\n        k, 2+⌊ln(k)⌋ ].\n\n    options.normalize: boolean (optional)\n        Boolean indicating whether to normalize incoming data. This option is\n        only relevant for non-Euclidean distance metrics. If set to `true`, an\n        accumulator partitioning data based on cosine distance normalizes\n        provided data to unit Euclidean length. If set to `true`, an accumulator\n        partitioning data based on correlation distance first centers provided\n        data and then normalizes data dimensions to have zero mean and unit\n        variance. If this option is set to `false` and the metric is either\n        cosine or correlation distance, then incoming data *must* already be\n        normalized. Default: true.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy incoming data to prevent mutation\n        during normalization. Default: true.\n\n    options.seed: any (optional)\n        PRNG seed. Setting this option is useful when wanting reproducible\n        initial centroids.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    acc.predict: Function\n        Predicts centroid assignment for each data point in a provided matrix.\n        To specify an output vector, provide a 1-dimensional ndarray as the\n        first argument. Each element in the returned vector corresponds to a\n        predicted cluster index for a respective data point.\n\n    Examples\n    --------\n    > var accumulator = incrkmeans( 5, 2 );\n    > var buf = new Float64Array( 2 );\n    > var shape = [ 2 ];\n    > var strides = [ 1 ];\n    > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n    > v.set( 0, 2.0 );\n    > v.set( 1, 1.0 );\n    > out = accumulator( v );\n    > v.set( 0, -5.0 );\n    > v.set( 1, 3.14 );\n    > out = accumulator( v );\n\n","incrkurtosis":"\nincrkurtosis()\n    Returns an accumulator function which incrementally computes a corrected\n    sample excess kurtosis.\n\n    If provided a value, the accumulator function returns an updated corrected\n    sample excess kurtosis. If not provided a value, the accumulator function\n    returns the current corrected sample excess kurtosis.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrkurtosis();\n    > var v = accumulator( 2.0 )\n    null\n    > v = accumulator( 2.0 )\n    null\n    > v = accumulator( -4.0 )\n    null\n    > v = accumulator( -4.0 )\n    -6.0\n\n    See Also\n    --------\n    incrmean, incrskewness, incrstdev, incrsummary, incrvariance\n","incrmaape":"\nincrmaape()\n    Returns an accumulator function which incrementally computes the mean\n    arctangent absolute percentage error (MAAPE).\n\n    If provided input values, the accumulator function returns an updated mean\n    arctangent absolute percentage error. If not provided input values, the\n    accumulator function returns the current mean arctangent absolute percentage\n    error.\n\n    Note that, unlike the mean absolute percentage error (MAPE), the mean\n    arctangent absolute percentage error is expressed in radians on the interval\n    [0,π/2].\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmaape();\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    ~0.3218\n    > m = accumulator( 5.0, 2.0 )\n    ~0.6523\n    > m = accumulator()\n    ~0.6523\n\n    See Also\n    --------\n    incrmae, incrmape, incrmean, incrmmaape\n","incrmae":"\nincrmae()\n    Returns an accumulator function which incrementally computes the mean\n    absolute error (MAE).\n\n    If provided input values, the accumulator function returns an updated mean\n    absolute error. If not provided input values, the accumulator function\n    returns the current mean absolute error.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmae();\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    1.0\n    > m = accumulator( -5.0, 2.0 )\n    4.0\n    > m = accumulator()\n    4.0\n\n    See Also\n    --------\n    incrmape, incrme, incrmean, incrmmae\n","incrmapcorr":"\nincrmapcorr( W[, mx, my] )\n    Returns an accumulator function which incrementally computes a moving\n    sample absolute Pearson product-moment correlation coefficient.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving sample absolute correlation coefficient.\n\n    If provided values, the accumulator function returns an updated moving\n    sample absolute correlation coefficient. If not provided values, the\n    accumulator function returns the current moving sample absolute correlation\n    coefficient.\n\n    As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n    returned values are calculated from smaller sample sizes. Until the window\n    is full, each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    mx: number (optional)\n        Known mean.\n\n    my: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmapcorr( 3 );\n    > var ar = accumulator()\n    null\n    > ar = accumulator( 2.0, 1.0 )\n    0.0\n    > ar = accumulator( -5.0, 3.14 )\n    ~1.0\n    > ar = accumulator( 3.0, -1.0 )\n    ~0.925\n    > ar = accumulator( 5.0, -9.5 )\n    ~0.863\n    > ar = accumulator()\n    ~0.863\n\n    See Also\n    --------\n    incrapcorr, incrmpcorr, incrmpcorr2\n","incrmape":"\nincrmape()\n    Returns an accumulator function which incrementally computes the mean\n    absolute percentage error (MAPE).\n\n    If provided input values, the accumulator function returns an updated mean\n    absolute percentage error. If not provided input values, the accumulator\n    function returns the current mean absolute percentage error.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmape();\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    ~33.33\n    > m = accumulator( 5.0, 2.0 )\n    ~91.67\n    > m = accumulator()\n    ~91.67\n\n    See Also\n    --------\n    incrmaape, incrmae, incrmean, incrmmape\n","incrmax":"\nincrmax()\n    Returns an accumulator function which incrementally computes a maximum\n    value.\n\n    If provided a value, the accumulator function returns an updated maximum\n    value. If not provided a value, the accumulator function returns the current\n    maximum value.\n\n    If provided `NaN`, the maximum value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmax();\n    > var m = accumulator()\n    null\n    > m = accumulator( 3.14 )\n    3.14\n    > m = accumulator( -5.0 )\n    3.14\n    > m = accumulator( 10.1 )\n    10.1\n    > m = accumulator()\n    10.1\n\n    See Also\n    --------\n    incrmidrange, incrmin, incrmmax, incrrange, incrsummary\n","incrmaxabs":"\nincrmaxabs()\n    Returns an accumulator function which incrementally computes a maximum\n    absolute value.\n\n    If provided a value, the accumulator function returns an updated maximum\n    absolute value. If not provided a value, the accumulator function returns\n    the current maximum absolute value.\n\n    If provided `NaN`, the maximum value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmaxabs();\n    > var m = accumulator()\n    null\n    > m = accumulator( 3.14 )\n    3.14\n    > m = accumulator( -5.0 )\n    5.0\n    > m = accumulator( 10.1 )\n    10.1\n    > m = accumulator()\n    10.1\n\n    See Also\n    --------\n    incrmax, incrminabs, incrmmaxabs\n","incrmcovariance":"\nincrmcovariance( W[, mx, my] )\n    Returns an accumulator function which incrementally computes a moving\n    unbiased sample covariance.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving unbiased sample covariance.\n\n    If provided values, the accumulator function returns an updated moving\n    unbiased sample covariance. If not provided values, the accumulator function\n    returns the current moving unbiased sample covariance.\n\n    As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n    returned values are calculated from smaller sample sizes. Until the window\n    is full, each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    mx: number (optional)\n        Known mean.\n\n    my: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmcovariance( 3 );\n    > var v = accumulator()\n    null\n    > v = accumulator( 2.0, 1.0 )\n    0.0\n    > v = accumulator( -5.0, 3.14 )\n    ~-7.49\n    > v = accumulator( 3.0, -1.0 )\n    -8.35\n    > v = accumulator( 5.0, -9.5 )\n    -29.42\n    > v = accumulator()\n    -29.42\n\n    See Also\n    --------\n    incrcovariance, incrmpcorr, incrmvariance\n","incrmcv":"\nincrmcv( W[, mean] )\n    Returns an accumulator function which incrementally computes a moving\n    coefficient of variation (CV).\n\n    The `W` parameter defines the number of values over which to compute the\n    moving coefficient of variation.\n\n    If provided a value, the accumulator function returns an updated moving\n    coefficient of variation. If not provided a value, the accumulator function\n    returns the current moving coefficient of variation.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    mean: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmcv( 3 );\n    > var cv = accumulator()\n    null\n    > cv = accumulator( 2.0 )\n    0.0\n    > cv = accumulator( 1.0 )\n    ~0.47\n    > cv = accumulator( 3.0 )\n    0.5\n    > cv = accumulator( 7.0 )\n    ~0.83\n    > cv = accumulator()\n    ~0.83\n\n    See Also\n    --------\n    incrcv, incrmmean, incrmstdev, incrmvmr\n","incrmda":"\nincrmda()\n    Returns an accumulator function which incrementally computes the mean\n    directional accuracy (MDA).\n\n    If provided input values, the accumulator function returns an updated mean\n    directional accuracy. If not provided input values, the accumulator function\n    returns the current mean directional accuracy.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmda();\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    1.0\n    > m = accumulator( -5.0, 4.0 )\n    0.5\n    > m = accumulator()\n    0.5\n\n    See Also\n    --------\n    incrmape, incrmmda\n","incrme":"\nincrme()\n    Returns an accumulator function which incrementally computes the mean error\n    (ME).\n\n    If provided input values, the accumulator function returns an updated mean\n    error. If not provided input values, the accumulator function returns the\n    current mean error.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrme();\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    1.0\n    > m = accumulator( -5.0, 2.0 )\n    4.0\n    > m = accumulator()\n    4.0\n\n    See Also\n    --------\n    incrmae, incrmean, incrmme\n","incrmean":"\nincrmean()\n    Returns an accumulator function which incrementally computes an arithmetic\n    mean.\n\n    If provided a value, the accumulator function returns an updated mean. If\n    not provided a value, the accumulator function returns the current mean.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmean();\n    > var mu = accumulator()\n    null\n    > mu = accumulator( 2.0 )\n    2.0\n    > mu = accumulator( -5.0 )\n    -1.5\n    > mu = accumulator()\n    -1.5\n\n    See Also\n    --------\n    incrmidrange, incrmmean, incrstdev, incrsum, incrsummary, incrvariance\n","incrmeanabs":"\nincrmeanabs()\n    Returns an accumulator function which incrementally computes an arithmetic\n    mean of absolute values.\n\n    If provided a value, the accumulator function returns an updated mean. If\n    not provided a value, the accumulator function returns the current mean.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmeanabs();\n    > var mu = accumulator()\n    null\n    > mu = accumulator( 2.0 )\n    2.0\n    > mu = accumulator( -5.0 )\n    3.5\n    > mu = accumulator()\n    3.5\n\n    See Also\n    --------\n    incrmean, incrmmeanabs, incrsumabs\n","incrmeanabs2":"\nincrmeanabs2()\n    Returns an accumulator function which incrementally computes an arithmetic\n    mean of squared absolute values.\n\n    If provided a value, the accumulator function returns an updated mean. If\n    not provided a value, the accumulator function returns the current mean.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmeanabs2();\n    > var mu = accumulator()\n    null\n    > mu = accumulator( 2.0 )\n    4.0\n    > mu = accumulator( -5.0 )\n    14.5\n    > mu = accumulator()\n    14.5\n\n    See Also\n    --------\n    incrmean, incrmeanabs, incrmmeanabs2, incrsumabs2\n","incrmeanstdev":"\nincrmeanstdev( [out] )\n    Returns an accumulator function which incrementally computes an arithmetic\n    mean and corrected sample standard deviation.\n\n    If provided a value, the accumulator function returns updated accumulated\n    values. If not provided a value, the accumulator function returns the\n    current accumulated values.\n\n    If provided `NaN`, the accumulated values are equal to `NaN` for all future\n    invocations.\n\n    Parameters\n    ----------\n    out: Array|TypedArray (optional)\n        Output array.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmeanstdev();\n    > var ms = accumulator()\n    null\n    > ms = accumulator( 2.0 )\n    [ 2.0, 0.0 ]\n    > ms = accumulator( -5.0 )\n    [ -1.5, ~4.95 ]\n    > ms = accumulator( 3.0 )\n    [ 0.0, ~4.36 ]\n    > ms = accumulator( 5.0 )\n    [ 1.25, ~4.35 ]\n    > ms = accumulator()\n    [ 1.25, ~4.35 ]\n\n    See Also\n    --------\n    incrmean, incrmeanvar, incrmmeanstdev, incrstdev\n","incrmeanvar":"\nincrmeanvar( [out] )\n    Returns an accumulator function which incrementally computes an arithmetic\n    mean and unbiased sample variance.\n\n    If provided a value, the accumulator function returns updated accumulated\n    values. If not provided a value, the accumulator function returns the\n    current accumulated values.\n\n    If provided `NaN`, the accumulated values are equal to `NaN` for all future\n    invocations.\n\n    Parameters\n    ----------\n    out: Array|TypedArray (optional)\n        Output array.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmeanvar();\n    > var mv = accumulator()\n    null\n    > mv = accumulator( 2.0 )\n    [ 2.0, 0.0 ]\n    > mv = accumulator( -5.0 )\n    [ -1.5, 24.5 ]\n    > mv = accumulator( 3.0 )\n    [ 0.0, 19.0 ]\n    > mv = accumulator( 5.0 )\n    [ 1.25, ~18.92 ]\n    > mv = accumulator()\n    [ 1.25, ~18.92 ]\n\n    See Also\n    --------\n    incrmean, incrmeanstdev, incrmmeanvar, incrvariance\n","incrmgmean":"\nincrmgmean( W )\n    Returns an accumulator function which incrementally computes a moving\n    geometric mean.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving geometric mean.\n\n    If provided a value, the accumulator function returns an updated moving\n    geometric mean. If not provided a value, the accumulator function returns\n    the current moving geometric mean.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmgmean( 3 );\n    > var v = accumulator()\n    null\n    > v = accumulator( 2.0 )\n    2.0\n    > v = accumulator( 5.0 )\n    ~3.16\n    > v = accumulator( 3.0 )\n    ~3.11\n    > v = accumulator( 5.0 )\n    ~4.22\n    > v = accumulator()\n    ~4.22\n\n    See Also\n    --------\n    incrgmean, incrmhmean, incrmmean\n","incrmgrubbs":"\nincrmgrubbs( W[, options] )\n    Returns an accumulator function which incrementally performs a moving\n    Grubbs' test for detecting outliers.\n\n    Grubbs' test assumes that data is normally distributed. Accordingly, one\n    should first verify that the data can be reasonably approximated by a normal\n    distribution before applying the Grubbs' test.\n\n    The `W` parameter defines the number of values over which to perform Grubbs'\n    test. The minimum window size is 3.\n\n    If provided a value, the accumulator function returns updated test results.\n    If not provided a value, the accumulator function returns the current test\n    results.\n\n    Until provided `W` values, the accumulator function returns `null`.\n\n    The accumulator function returns an object having the following fields:\n\n    - rejected: boolean indicating whether the null hypothesis should be\n    rejected.\n    - alpha: significance level.\n    - criticalValue: critical value.\n    - statistic: test statistic.\n    - df: degrees of freedom.\n    - mean: sample mean.\n    - sd: corrected sample standard deviation.\n    - min: minimum value.\n    - max: maximum value.\n    - alt: alternative hypothesis.\n    - method: method name.\n    - print: method for pretty-printing test output.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    options: Object (optional)\n        Function options.\n\n    options.alpha: number (optional)\n        Significance level. Default: 0.05.\n\n    options.alternative: string (optional)\n        Alternative hypothesis. The option may be one of the following values:\n\n        - 'two-sided': test whether the minimum or maximum value is an outlier.\n        - 'min': test whether the minimum value is an outlier.\n        - 'max': test whether the maximum value is an outlier.\n\n        Default: 'two-sided'.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var acc = incrmgrubbs( 20 );\n    > var res = acc()\n    null\n    > for ( var i = 0; i < 200; i++ ) {\n    ...     res = acc( base.random.normal( 10.0, 5.0 ) );\n    ... };\n    > res.print()\n\n    References\n    ----------\n    - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n    Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n    of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n    - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n    Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n    00401706.1969.10490657.\n\n    See Also\n    --------\n    incrgrubbs\n","incrmhmean":"\nincrmhmean( W )\n    Returns an accumulator function which incrementally computes a moving\n    harmonic mean.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving harmonic mean.\n\n    If provided a value, the accumulator function returns an updated moving\n    harmonic mean. If not provided a value, the accumulator function returns the\n    current moving harmonic mean.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmhmean( 3 );\n    > var v = accumulator()\n    null\n    > v = accumulator( 2.0 )\n    2.0\n    > v = accumulator( 5.0 )\n    ~2.86\n    > v = accumulator( 3.0 )\n    ~2.90\n    > v = accumulator( 5.0 )\n    ~4.09\n    > v = accumulator()\n    ~4.09\n\n    See Also\n    --------\n    incrhmean, incrmgmean, incrmmean\n","incrmidrange":"\nincrmidrange()\n    Returns an accumulator function which incrementally computes a mid-range.\n\n    The mid-range is the arithmetic mean of maximum and minimum values.\n    Accordingly, the mid-range is the midpoint of the range and a measure of\n    central tendency.\n\n    If provided a value, the accumulator function returns an updated mid-range.\n    If not provided a value, the accumulator function returns the current mid-\n    range.\n\n    If provided `NaN`, the mid-range is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmidrange();\n    > var v = accumulator()\n    null\n    > v = accumulator( 3.14 )\n    3.14\n    > v = accumulator( -5.0 )\n    ~-0.93\n    > v = accumulator( 10.1 )\n    2.55\n    > v = accumulator()\n    2.55\n\n    See Also\n    --------\n    incrmean, incrmax, incrmin, incrrange, incrsummary\n","incrmin":"\nincrmin()\n    Returns an accumulator function which incrementally computes a minimum\n    value.\n\n    If provided a value, the accumulator function returns an updated minimum\n    value. If not provided a value, the accumulator function returns the current\n    minimum value.\n\n    If provided `NaN`, the minimum value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmin();\n    > var m = accumulator()\n    null\n    > m = accumulator( 3.14 )\n    3.14\n    > m = accumulator( -5.0 )\n    -5.0\n    > m = accumulator( 10.1 )\n    -5.0\n    > m = accumulator()\n    -5.0\n\n    See Also\n    --------\n    incrmax, incrmidrange, incrmmin, incrrange, incrsummary\n","incrminabs":"\nincrminabs()\n    Returns an accumulator function which incrementally computes a minimum\n    absolute value.\n\n    If provided a value, the accumulator function returns an updated minimum\n    absolute value. If not provided a value, the accumulator function returns\n    the current minimum absolute value.\n\n    If provided `NaN`, the minimum value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrminabs();\n    > var m = accumulator()\n    null\n    > m = accumulator( 3.14 )\n    3.14\n    > m = accumulator( -5.0 )\n    3.14\n    > m = accumulator( 10.1 )\n    3.14\n    > m = accumulator()\n    3.14\n\n    See Also\n    --------\n    incrmaxabs, incrmin, incrmminabs\n","incrminmax":"\nincrminmax( [out] )\n    Returns an accumulator function which incrementally computes a minimum and\n    maximum.\n\n    If provided a value, the accumulator function returns an updated minimum and\n    maximum. If not provided a value, the accumulator function returns the\n    current minimum and maximum.\n\n    If provided `NaN`, the minimum and maximum values are equal to `NaN` for all\n    future invocations.\n\n    Parameters\n    ----------\n    out: Array|TypedArray (optional)\n        Output array.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrminmax();\n    > var mm = accumulator()\n    null\n    > mm = accumulator( 2.0 )\n    [ 2.0, 2.0 ]\n    > mm = accumulator( -5.0 )\n    [ -5.0, 2.0 ]\n    > mm = accumulator( 3.0 )\n    [ -5.0, 3.0 ]\n    > mm = accumulator( 5.0 )\n    [ -5.0, 5.0 ]\n    > mm = accumulator()\n    [ -5.0, 5.0 ]\n\n    See Also\n    --------\n    incrmax, incrmin, incrmminmax, incrrange\n","incrminmaxabs":"\nincrminmaxabs( [out] )\n    Returns an accumulator function which incrementally computes a minimum and\n    maximum absolute value.\n\n    If provided a value, the accumulator function returns an updated minimum and\n    maximum. If not provided a value, the accumulator function returns the\n    current minimum and maximum.\n\n    If provided `NaN`, the minimum and maximum values are equal to `NaN` for all\n    future invocations.\n\n    Parameters\n    ----------\n    out: Array|TypedArray (optional)\n        Output array.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrminmaxabs();\n    > var mm = accumulator()\n    null\n    > mm = accumulator( 2.0 )\n    [ 2.0, 2.0 ]\n    > mm = accumulator( -5.0 )\n    [ 2.0, 5.0 ]\n    > mm = accumulator( 3.0 )\n    [ 2.0, 5.0 ]\n    > mm = accumulator( 5.0 )\n    [ 2.0, 5.0 ]\n    > mm = accumulator()\n    [ 2.0, 5.0 ]\n\n    See Also\n    --------\n    incrmaxabs, incrminabs, incrminmax, incrmminmaxabs\n","incrmmaape":"\nincrmmaape( W )\n    Returns an accumulator function which incrementally computes a moving\n    mean arctangent absolute percentage error (MAAPE).\n\n    The `W` parameter defines the number of values over which to compute the\n    moving mean arctangent absolute percentage error.\n\n    If provided input values, the accumulator function returns an updated moving\n    mean arctangent absolute percentage error. If not provided input values, the\n    accumulator function returns the current moving mean arctangent absolute\n    percentage error.\n\n    Note that, unlike the mean absolute percentage error (MAPE), the mean\n    arctangent absolute percentage error is expressed in radians on the interval\n    [0,π/2].\n\n    As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n    returned values are calculated from smaller sample sizes. Until the window\n    is full, each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmaape( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    ~0.32\n    > m = accumulator( 5.0, 2.0 )\n    ~0.65\n    > m = accumulator( 3.0, 2.0 )\n    ~0.59\n    > m = accumulator( 2.0, 5.0 )\n    ~0.66\n    > m = accumulator()\n    ~0.66\n\n    See Also\n    --------\n    incrmaape, incrmmape, incrmmpe, incrmmean\n","incrmmae":"\nincrmmae( W )\n    Returns an accumulator function which incrementally computes a moving\n    mean absolute error (MAE).\n\n    The `W` parameter defines the number of values over which to compute the\n    moving mean absolute error.\n\n    If provided a value, the accumulator function returns an updated moving\n    mean absolute error. If not provided a value, the accumulator function\n    returns the current moving mean absolute error.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmae( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    1.0\n    > m = accumulator( -5.0, 2.0 )\n    4.0\n    > m = accumulator( 3.0, 2.0 )\n    3.0\n    > m = accumulator( 5.0, -2.0 )\n    5.0\n    > m = accumulator()\n    5.0\n\n    See Also\n    --------\n    incrmae, incrmme, incrmmean\n","incrmmape":"\nincrmmape( W )\n    Returns an accumulator function which incrementally computes a moving\n    mean absolute percentage error (MAPE).\n\n    The `W` parameter defines the number of values over which to compute the\n    moving mean absolute percentage error.\n\n    If provided input values, the accumulator function returns an updated moving\n    mean absolute percentage error. If not provided input values, the\n    accumulator function returns the current moving mean absolute percentage\n    error.\n\n    As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n    returned values are calculated from smaller sample sizes. Until the window\n    is full, each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmape( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    ~33.33\n    > m = accumulator( 5.0, 2.0 )\n    ~91.67\n    > m = accumulator( 3.0, 2.0 )\n    ~77.78\n    > m = accumulator( 2.0, 5.0 )\n    ~86.67\n    > m = accumulator()\n    ~86.67\n\n    See Also\n    --------\n    incrmape, incrmmaape, incrmmpe, incrmmean\n","incrmmax":"\nincrmmax( W )\n    Returns an accumulator function which incrementally computes a moving\n    maximum value.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving maximum.\n\n    If provided a value, the accumulator function returns an updated moving\n    maximum. If not provided a value, the accumulator function returns the\n    current moving maximum.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmax( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0 )\n    2.0\n    > m = accumulator( -5.0 )\n    2.0\n    > m = accumulator( 3.0 )\n    3.0\n    > m = accumulator( 5.0 )\n    5.0\n    > m = accumulator()\n    5.0\n\n    See Also\n    --------\n    incrmax, incrmmidrange, incrmmin, incrmrange, incrmsummary\n","incrmmaxabs":"\nincrmmaxabs( W )\n    Returns an accumulator function which incrementally computes a moving\n    maximum absolute value.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving maximum absolute value.\n\n    If provided a value, the accumulator function returns an updated moving\n    maximum absolute value. If not provided a value, the accumulator function\n    returns the current moving maximum absolute value.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmaxabs( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0 )\n    2.0\n    > m = accumulator( -5.0 )\n    5.0\n    > m = accumulator( 3.0 )\n    5.0\n    > m = accumulator( 5.0 )\n    5.0\n    > m = accumulator()\n    5.0\n\n    See Also\n    --------\n    incrmaxabs, incrmmax, incrmminabs\n","incrmmda":"\nincrmmda( W )\n    Returns an accumulator function which incrementally computes a moving\n    mean directional accuracy (MDA).\n\n    The `W` parameter defines the number of values over which to compute the\n    moving mean directional accuracy.\n\n    If provided input values, the accumulator function returns an updated moving\n    mean directional accuracy. If not provided input values, the accumulator\n    function returns the current moving mean directional accuracy.\n\n    As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n    returned values are calculated from smaller sample sizes. Until the window\n    is full, each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmda( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    1.0\n    > m = accumulator( 5.0, 2.0 )\n    0.5\n    > m = accumulator( 3.0, 2.0 )\n    ~0.33\n    > m = accumulator( 4.0, 5.0 )\n    ~0.33\n    > m = accumulator()\n    ~0.33\n\n    See Also\n    --------\n    incrmda, incrmmape\n","incrmme":"\nincrmme( W )\n    Returns an accumulator function which incrementally computes a moving\n    mean error (ME).\n\n    The `W` parameter defines the number of values over which to compute the\n    moving mean error.\n\n    If provided a value, the accumulator function returns an updated moving\n    mean error. If not provided a value, the accumulator function returns the\n    current moving mean error.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmme( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    1.0\n    > m = accumulator( -5.0, 2.0 )\n    4.0\n    > m = accumulator( 3.0, 2.0 )\n    ~2.33\n    > m = accumulator( 5.0, -2.0 )\n    ~-0.33\n    > m = accumulator()\n    ~-0.33\n\n    See Also\n    --------\n    incrme, incrmmae, incrmmean\n","incrmmean":"\nincrmmean( W )\n    Returns an accumulator function which incrementally computes a moving\n    arithmetic mean.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving mean.\n\n    If provided a value, the accumulator function returns an updated moving\n    mean. If not provided a value, the accumulator function returns the current\n    moving mean.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmean( 3 );\n    > var mu = accumulator()\n    null\n    > mu = accumulator( 2.0 )\n    2.0\n    > mu = accumulator( -5.0 )\n    -1.5\n    > mu = accumulator( 3.0 )\n    0.0\n    > mu = accumulator( 5.0 )\n    1.0\n    > mu = accumulator()\n    1.0\n\n    See Also\n    --------\n    incrmean, incrmsum, incrmstdev, incrmsummary, incrmvariance\n","incrmmeanabs":"\nincrmmeanabs( W )\n    Returns an accumulator function which incrementally computes a moving\n    arithmetic mean of absolute values.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving mean.\n\n    If provided a value, the accumulator function returns an updated moving\n    mean. If not provided a value, the accumulator function returns the current\n    moving mean.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmeanabs( 3 );\n    > var mu = accumulator()\n    null\n    > mu = accumulator( 2.0 )\n    2.0\n    > mu = accumulator( -5.0 )\n    3.5\n    > mu = accumulator( 3.0 )\n    ~3.33\n    > mu = accumulator( 5.0 )\n    ~4.33\n    > mu = accumulator()\n    ~4.33\n\n    See Also\n    --------\n    incrmeanabs, incrmmean, incrmsumabs\n","incrmmeanabs2":"\nincrmmeanabs2( W )\n    Returns an accumulator function which incrementally computes a moving\n    arithmetic mean of squared absolute values.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving mean.\n\n    If provided a value, the accumulator function returns an updated moving\n    mean. If not provided a value, the accumulator function returns the current\n    moving mean.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmeanabs2( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0 )\n    4.0\n    > m = accumulator( -5.0 )\n    14.5\n    > m = accumulator( 3.0 )\n    ~12.67\n    > m = accumulator( 5.0 )\n    ~19.67\n    > m = accumulator()\n    ~19.67\n\n    See Also\n    --------\n    incrmeanabs2, incrmmeanabs, incrmsumabs2\n","incrmmeanstdev":"\nincrmmeanstdev( [out,] W )\n    Returns an accumulator function which incrementally computes a moving\n    arithmetic mean and corrected sample standard deviation.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving arithmetic mean and corrected sample standard deviation.\n\n    If provided a value, the accumulator function returns updated accumulated\n    values. If not provided a value, the accumulator function returns the\n    current moving accumulated values.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    accumulated values are calculated from smaller sample sizes. Until the\n    window is full, each returned accumulated value is calculated from all\n    provided values.\n\n    Parameters\n    ----------\n    out: Array|TypedArray (optional)\n        Output array.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmeanstdev( 3 );\n    > var v = accumulator()\n    null\n    > v = accumulator( 2.0 )\n    [ 2.0, 0.0 ]\n    > v = accumulator( -5.0 )\n    [ -1.5, ~4.95 ]\n    > v = accumulator( 3.0 )\n    [ 0.0, ~4.36 ]\n    > v = accumulator( 5.0 )\n    [ 1.0, ~5.29 ]\n    > v = accumulator()\n    [ 1.0, ~5.29 ]\n\n    See Also\n    --------\n    incrmeanstdev, incrmmean, incrmmeanvar, incrmstdev\n","incrmmeanvar":"\nincrmmeanvar( [out,] W )\n    Returns an accumulator function which incrementally computes a moving\n    arithmetic mean and unbiased sample variance.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving arithmetic mean and unbiased sample variance.\n\n    If provided a value, the accumulator function returns updated accumulated\n    values. If not provided a value, the accumulator function returns the\n    current moving accumulated values.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    accumulated values are calculated from smaller sample sizes. Until the\n    window is full, each returned accumulated value is calculated from all\n    provided values.\n\n    Parameters\n    ----------\n    out: Array|TypedArray (optional)\n        Output array.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmeanvar( 3 );\n    > var v = accumulator()\n    null\n    > v = accumulator( 2.0 )\n    [ 2.0, 0.0 ]\n    > v = accumulator( -5.0 )\n    [ -1.5, 24.5 ]\n    > v = accumulator( 3.0 )\n    [ 0.0, 19.0 ]\n    > v = accumulator( 5.0 )\n    [ 1.0, 28.0 ]\n    > v = accumulator()\n    [ 1.0, 28.0 ]\n\n    See Also\n    --------\n    incrmeanvar, incrmmean, incrmmeanstdev, incrmvariance\n","incrmmidrange":"\nincrmmidrange( W )\n    Returns an accumulator function which incrementally computes a moving mid-\n    range.\n\n    The mid-range is the arithmetic mean of maximum and minimum values.\n    Accordingly, the mid-range is the midpoint of the range and a measure of\n    central tendency.\n\n    The `W` parameter defines the number of values over which to compute\n    the moving mid-range.\n\n    If provided a value, the accumulator function returns an updated moving mid-\n    range. If not provided a value, the accumulator function returns the current\n    moving mid-range.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmidrange( 3 );\n    > var mr = accumulator()\n    null\n    > mr = accumulator( 2.0 )\n    2.0\n    > mr = accumulator( -5.0 )\n    -1.5\n    > mr = accumulator( 3.0 )\n    -1.0\n    > mr = accumulator( 5.0 )\n    0.0\n    > mr = accumulator()\n    0.0\n\n    See Also\n    --------\n    incrmmean, incrmmax, incrmmin, incrmrange\n","incrmmin":"\nincrmmin( W )\n    Returns an accumulator function which incrementally computes a moving\n    minimum value.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving minimum.\n\n    If provided a value, the accumulator function returns an updated moving\n    minimum. If not provided a value, the accumulator function returns the\n    current moving minimum.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmin( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0 )\n    2.0\n    > m = accumulator( -5.0 )\n    -5.0\n    > m = accumulator( 3.0 )\n    -5.0\n    > m = accumulator( 5.0 )\n    -5.0\n    > m = accumulator()\n    -5.0\n\n    See Also\n    --------\n    incrmin, incrmmax, incrmmidrange, incrmrange, incrmsummary\n","incrmminabs":"\nincrmminabs( W )\n    Returns an accumulator function which incrementally computes a moving\n    minimum absolute value.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving minimum absolute value.\n\n    If provided a value, the accumulator function returns an updated moving\n    minimum absolute value. If not provided a value, the accumulator function\n    returns the current moving minimum absolute value.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmminabs( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0 )\n    2.0\n    > m = accumulator( -5.0 )\n    2.0\n    > m = accumulator( 3.0 )\n    2.0\n    > m = accumulator( 5.0 )\n    3.0\n    > m = accumulator()\n    3.0\n\n    See Also\n    --------\n    incrminabs, incrmmaxabs, incrmmin\n","incrmminmax":"\nincrmminmax( [out,] W )\n    Returns an accumulator function which incrementally computes a moving\n    minimum and maximum.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving minimum and maximum.\n\n    If provided a value, the accumulator function returns an updated moving\n    minimum and maximum. If not provided a value, the accumulator function\n    returns the current moving minimum and maximum.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    minimum and maximum values are calculated from smaller sample sizes. Until\n    the window is full, each returned minimum and maximum is calculated from all\n    provided values.\n\n    Parameters\n    ----------\n    out: Array|TypedArray (optional)\n        Output array.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmminmax( 3 );\n    > var mm = accumulator()\n    null\n    > mm = accumulator( 2.0 )\n    [ 2.0, 2.0 ]\n    > mm = accumulator( -5.0 )\n    [ -5.0, 2.0 ]\n    > mm = accumulator( 3.0 )\n    [ -5.0, 3.0 ]\n    > mm = accumulator( 5.0 )\n    [ -5.0, 5.0 ]\n    > mm = accumulator()\n    [ -5.0, 5.0 ]\n\n    See Also\n    --------\n    incrmax, incrmin, incrmmax, incrminmax, incrmmin, incrmrange\n","incrmminmaxabs":"\nincrmminmaxabs( [out,] W )\n    Returns an accumulator function which incrementally computes moving minimum\n    and maximum absolute values.\n\n    The `W` parameter defines the number of values over which to compute moving\n    minimum and maximum absolute values.\n\n    If provided a value, the accumulator function returns an updated moving\n    minimum and maximum. If not provided a value, the accumulator function\n    returns the current moving minimum and maximum.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    minimum and maximum values are calculated from smaller sample sizes. Until\n    the window is full, each returned minimum and maximum is calculated from all\n    provided values.\n\n    Parameters\n    ----------\n    out: Array|TypedArray (optional)\n        Output array.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmminmaxabs( 3 );\n    > var mm = accumulator()\n    null\n    > mm = accumulator( 2.0 )\n    [ 2.0, 2.0 ]\n    > mm = accumulator( -5.0 )\n    [ 2.0, 5.0 ]\n    > mm = accumulator( 3.0 )\n    [ 2.0, 5.0 ]\n    > mm = accumulator( 5.0 )\n    [ 3.0, 5.0 ]\n    > mm = accumulator()\n    [ 3.0, 5.0 ]\n\n    See Also\n    --------\n    incrminmaxabs, incrmmax, incrmmaxabs, incrmmin, incrmminabs, incrmminmax\n","incrmmpe":"\nincrmmpe( W )\n    Returns an accumulator function which incrementally computes a moving\n    mean percentage error (MPE).\n\n    The `W` parameter defines the number of values over which to compute the\n    moving mean percentage error.\n\n    If provided input values, the accumulator function returns an updated moving\n    mean percentage error. If not provided input values, the accumulator\n    function returns the current moving mean percentage error.\n\n    As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n    returned values are calculated from smaller sample sizes. Until the window\n    is full, each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmpe( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    ~33.33\n    > m = accumulator( 5.0, 2.0 )\n    ~-58.33\n    > m = accumulator( 3.0, 2.0 )\n    ~-55.56\n    > m = accumulator( 2.0, 5.0 )\n    ~-46.67\n    > m = accumulator()\n    ~-46.67\n\n    See Also\n    --------\n    incrmmape, incrmme, incrmpe\n","incrmmse":"\nincrmmse( W )\n    Returns an accumulator function which incrementally computes a moving mean\n    squared error (MSE).\n\n    The `W` parameter defines the number of values over which to compute the\n    moving mean squared error.\n\n    If provided a value, the accumulator function returns an updated moving mean\n    squared error. If not provided a value, the accumulator function returns the\n    current moving mean squared error.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmse( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    1.0\n    > m = accumulator( -5.0, 2.0 )\n    25.0\n    > m = accumulator( 3.0, 2.0 )\n    17.0\n    > m = accumulator( 5.0, -2.0 )\n    33.0\n    > m = accumulator()\n    33.0\n\n    See Also\n    --------\n    incrmrmse, incrmrss, incrmse\n","incrmpcorr":"\nincrmpcorr( W[, mx, my] )\n    Returns an accumulator function which incrementally computes a moving\n    sample Pearson product-moment correlation coefficient.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving sample correlation coefficient.\n\n    If provided values, the accumulator function returns an updated moving\n    sample correlation coefficient. If not provided values, the accumulator\n    function returns the current moving sample correlation coefficient.\n\n    As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n    returned values are calculated from smaller sample sizes. Until the window\n    is full, each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    mx: number (optional)\n        Known mean.\n\n    my: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmpcorr( 3 );\n    > var r = accumulator()\n    null\n    > r = accumulator( 2.0, 1.0 )\n    0.0\n    > r = accumulator( -5.0, 3.14 )\n    ~-1.0\n    > r = accumulator( 3.0, -1.0 )\n    ~-0.925\n    > r = accumulator( 5.0, -9.5 )\n    ~-0.863\n    > r = accumulator()\n    ~-0.863\n\n    See Also\n    --------\n    incrmcovariance, incrmpcorrdist, incrpcorr\n","incrmpcorr2":"\nincrmpcorr2( W[, mx, my] )\n    Returns an accumulator function which incrementally computes a moving\n    squared sample Pearson product-moment correlation coefficient.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving squared sample correlation coefficient.\n\n    If provided values, the accumulator function returns an updated moving\n    squared sample correlation coefficient. If not provided values, the\n    accumulator function returns the current moving squared sample correlation\n    coefficient.\n\n    As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n    returned values are calculated from smaller sample sizes. Until the window\n    is full, each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    mx: number (optional)\n        Known mean.\n\n    my: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmpcorr2( 3 );\n    > var r2 = accumulator()\n    null\n    > r2 = accumulator( 2.0, 1.0 )\n    0.0\n    > r2 = accumulator( -5.0, 3.14 )\n    ~1.0\n    > r2 = accumulator( 3.0, -1.0 )\n    ~0.86\n    > r2 = accumulator( 5.0, -9.5 )\n    ~0.74\n    > r2 = accumulator()\n    ~0.74\n\n    See Also\n    --------\n    incrmapcorr, incrmpcorr, incrpcorr2\n","incrmpcorrdist":"\nincrmpcorrdist( W[, mx, my] )\n    Returns an accumulator function which incrementally computes a moving\n    sample Pearson product-moment correlation distance.\n\n    The correlation distance is defined as one minus the Pearson product-moment\n    correlation coefficient and, thus, resides on the interval [0,2].\n\n    However, due to limitations inherent in representing numeric values using\n    floating-point format (i.e., the inability to represent numeric values with\n    infinite precision), the correlation distance between perfectly correlated\n    random variables may *not* be `0` or `2`. In fact, the correlation distance\n    is *not* guaranteed to be strictly on the interval [0,2]. Any computed\n    distance should, however, be within floating-point roundoff error.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving sample correlation distance.\n\n    If provided values, the accumulator function returns an updated moving\n    sample correlation distance. If not provided values, the accumulator\n    function returns the current moving sample correlation distance.\n\n    As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n    returned values are calculated from smaller sample sizes. Until the window\n    is full, each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    mx: number (optional)\n        Known mean.\n\n    my: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmpcorrdist( 3 );\n    > var d = accumulator()\n    null\n    > d = accumulator( 2.0, 1.0 )\n    1.0\n    > d = accumulator( -5.0, 3.14 )\n    ~2.0\n    > d = accumulator( 3.0, -1.0 )\n    ~1.925\n    > d = accumulator( 5.0, -9.5 )\n    ~1.863\n    > d = accumulator()\n    ~1.863\n\n    See Also\n    --------\n    incrmpcorr, incrpcorrdist\n","incrmpe":"\nincrmpe()\n    Returns an accumulator function which incrementally computes the mean\n    percentage error (MPE).\n\n    If provided input values, the accumulator function returns an updated mean\n    percentage error. If not provided input values, the accumulator function\n    returns the current mean percentage error.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmpe();\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    ~33.33\n    > m = accumulator( 5.0, 2.0 )\n    ~-58.33\n    > m = accumulator()\n    ~-58.33\n\n    See Also\n    --------\n    incrmape, incrme, incrmmpe\n","incrmprod":"\nincrmprod( W )\n    Returns an accumulator function which incrementally computes a moving\n    product.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving product.\n\n    If provided a value, the accumulator function returns an updated moving\n    product. If not provided a value, the accumulator function returns the\n    current moving product.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    For accumulations over large windows or accumulations of large numbers, care\n    should be taken to prevent overflow. Note, however, that overflow/underflow\n    may be transient, as the accumulator does not use a double-precision\n    floating-point number to store an accumulated product. Instead, the\n    accumulator splits an accumulated product into a normalized fraction and\n    exponent and updates each component separately. Doing so guards against a\n    loss in precision.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmprod( 3 );\n    > var p = accumulator()\n    null\n    > p = accumulator( 2.0 )\n    2.0\n    > p = accumulator( -5.0 )\n    -10.0\n    > p = accumulator( 3.0 )\n    -30.0\n    > p = accumulator( 5.0 )\n    -75.0\n    > p = accumulator()\n    -75.0\n\n    See Also\n    --------\n    incrmsum, incrprod\n","incrmrange":"\nincrmrange( W )\n    Returns an accumulator function which incrementally computes a moving range.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving range.\n\n    If provided a value, the accumulator function returns an updated moving\n    range. If not provided a value, the accumulator function returns the current\n    moving range.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmrange( 3 );\n    > var r = accumulator()\n    null\n    > r = accumulator( 2.0 )\n    0.0\n    > r = accumulator( -5.0 )\n    7.0\n    > r = accumulator( 3.0 )\n    8.0\n    > r = accumulator( 5.0 )\n    10.0\n    > r = accumulator()\n    10.0\n\n    See Also\n    --------\n    incrmmax, incrmmean, incrmmin, incrmsummary, incrrange\n","incrmrmse":"\nincrmrmse( W )\n    Returns an accumulator function which incrementally computes a moving root\n    mean squared error (RMSE).\n\n    The `W` parameter defines the number of values over which to compute the\n    moving root mean squared error.\n\n    If provided a value, the accumulator function returns an updated moving root\n    mean squared error. If not provided a value, the accumulator function\n    returns the current moving root mean squared error.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmrmse( 3 );\n    > var r = accumulator()\n    null\n    > r = accumulator( 2.0, 3.0 )\n    1.0\n    > r = accumulator( -5.0, 2.0 )\n    5.0\n    > r = accumulator( 3.0, 2.0 )\n    ~4.12\n    > r = accumulator( 5.0, -2.0 )\n    ~5.74\n    > r = accumulator()\n    ~5.74\n\n    See Also\n    --------\n    incrmmse, incrmrss, incrrmse\n","incrmrss":"\nincrmrss( W )\n    Returns an accumulator function which incrementally computes a moving\n    residual sum of squares (RSS).\n\n    The `W` parameter defines the number of values over which to compute the\n    moving residual sum of squares.\n\n    If provided a value, the accumulator function returns an updated moving\n    residual sum of squares. If not provided a value, the accumulator function\n    returns the current moving residual sum of squares.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmrss( 3 );\n    > var r = accumulator()\n    null\n    > r = accumulator( 2.0, 3.0 )\n    1.0\n    > r = accumulator( -5.0, 2.0 )\n    50.0\n    > r = accumulator( 3.0, 2.0 )\n    51.0\n    > r = accumulator( 5.0, -2.0 )\n    99.0\n    > r = accumulator()\n    99.0\n\n    See Also\n    --------\n    incrrss, incrmmse, incrmrmse\n","incrmse":"\nincrmse()\n    Returns an accumulator function which incrementally computes the mean\n    squared error (MSE).\n\n    If provided input values, the accumulator function returns an updated mean\n    squared error. If not provided input values, the accumulator function\n    returns the current mean squared error.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmse();\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    1.0\n    > m = accumulator( -5.0, 2.0 )\n    25.0\n    > m = accumulator()\n    25.0\n\n    See Also\n    --------\n    incrmmse, incrrmse, incrrss\n","incrmstdev":"\nincrmstdev( W[, mean] )\n    Returns an accumulator function which incrementally computes a moving\n    corrected sample standard deviation.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving corrected sample standard deviation.\n\n    If provided a value, the accumulator function returns an updated moving\n    corrected sample standard deviation. If not provided a value, the\n    accumulator function returns the current moving corrected sample standard\n    deviation.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    mean: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmstdev( 3 );\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    0.0\n    > s = accumulator( -5.0 )\n    ~4.95\n    > s = accumulator( 3.0 )\n    ~4.36\n    > s = accumulator( 5.0 )\n    ~5.29\n    > s = accumulator()\n    ~5.29\n\n    See Also\n    --------\n    incrmmean, incrmsummary, incrmvariance, incrstdev\n","incrmsum":"\nincrmsum( W )\n    Returns an accumulator function which incrementally computes a moving sum.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving sum.\n\n    If provided a value, the accumulator function returns an updated moving sum.\n    If not provided a value, the accumulator function returns the current moving\n    sum.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmsum( 3 );\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    2.0\n    > s = accumulator( -5.0 )\n    -3.0\n    > s = accumulator( 3.0 )\n    0.0\n    > s = accumulator( 5.0 )\n    3.0\n    > s = accumulator()\n    3.0\n\n    See Also\n    --------\n    incrmmean, incrmsummary, incrsum\n","incrmsumabs":"\nincrmsumabs( W )\n    Returns an accumulator function which incrementally computes a moving sum of\n    absolute values.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving sum.\n\n    If provided a value, the accumulator function returns an updated moving sum.\n    If not provided a value, the accumulator function returns the current moving\n    sum.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmsumabs( 3 );\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    2.0\n    > s = accumulator( -5.0 )\n    7.0\n    > s = accumulator( 3.0 )\n    10.0\n    > s = accumulator( -5.0 )\n    13.0\n    > s = accumulator()\n    13.0\n\n    See Also\n    --------\n    incrmmeanabs, incrmsum, incrsum, incrsumabs\n","incrmsumabs2":"\nincrmsumabs2( W )\n    Returns an accumulator function which incrementally computes a moving sum of\n    squared absolute values.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving sum.\n\n    If provided a value, the accumulator function returns an updated moving sum.\n    If not provided a value, the accumulator function returns the current moving\n    sum.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmsumabs2( 3 );\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    4.0\n    > s = accumulator( -5.0 )\n    29.0\n    > s = accumulator( 3.0 )\n    38.0\n    > s = accumulator( -5.0 )\n    59.0\n    > s = accumulator()\n    59.0\n\n    See Also\n    --------\n    incrmmeanabs2, incrmsumabs, incrsumabs, incrsumabs2\n","incrmsummary":"\nincrmsummary( W )\n    Returns an accumulator function which incrementally computes a moving\n    statistical summary.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving statistical summary.\n\n    If provided a value, the accumulator function returns an updated moving\n    statistical summary. If not provided a value, the accumulator function\n    returns the current moving statistical summary.\n\n    The returned summary is an object containing the following fields:\n\n    - window: window size.\n    - sum: sum.\n    - mean: arithmetic mean.\n    - variance: unbiased sample variance.\n    - stdev: corrected sample standard deviation.\n    - min: minimum value.\n    - max: maximum value.\n    - range: range.\n    - midrange: arithmetic mean of the minimum and maximum values.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    summaries are calculated from smaller sample sizes. Until the window is\n    full, each returned summary is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmsummary( 3 );\n    > var s = accumulator()\n    {}\n    > s = accumulator( 2.0 )\n    {...}\n    > s = accumulator( -5.0 )\n    {...}\n    > s = accumulator()\n    {...}\n\n    See Also\n    --------\n    incrmmean, incrmstdev, incrmsum, incrmvariance, incrsummary\n","incrmsumprod":"\nincrmsumprod( W )\n    Returns an accumulator function which incrementally computes a moving sum of\n    products.\n\n    The `W` parameter defines the number of (x,y) pairs over which to compute\n    the moving sum of products.\n\n    If provided input values, the accumulator function returns an updated moving\n    sum. If not provided input values, the accumulator function returns the\n    current moving sum.\n\n    As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n    returned values are calculated from smaller sample sizes. Until the window\n    is full, each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmsumprod( 3 );\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0, 3.0 )\n    6.0\n    > s = accumulator( -5.0, 2.0 )\n    -4.0\n    > s = accumulator( 3.0, -2.0 )\n    -10.0\n    > s = accumulator( 5.0, 3.0 )\n    -1.0\n    > s = accumulator()\n    -1.0\n\n    See Also\n    --------\n    incrmprod, incrmsum, incrsumprod\n","incrmvariance":"\nincrmvariance( W[, mean] )\n    Returns an accumulator function which incrementally computes a moving\n    unbiased sample variance.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving unbiased sample variance.\n\n    If provided a value, the accumulator function returns an updated moving\n    unbiased sample variance. If not provided a value, the accumulator function\n    returns the current moving unbiased sample variance.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    mean: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmvariance( 3 );\n    > var s2 = accumulator()\n    null\n    > s2 = accumulator( 2.0 )\n    0.0\n    > s2 = accumulator( -5.0 )\n    24.5\n    > s2 = accumulator( 3.0 )\n    19.0\n    > s2 = accumulator( 5.0 )\n    28.0\n    > s2 = accumulator()\n    28.0\n\n    See Also\n    --------\n    incrmmean, incrmstdev, incrmsummary, incrvariance\n","incrmvmr":"\nincrmvmr( W[, mean] )\n    Returns an accumulator function which incrementally computes a moving\n    variance-to-mean (VMR).\n\n    The `W` parameter defines the number of values over which to compute the\n    moving variance-to-mean ratio.\n\n    If provided a value, the accumulator function returns an updated moving\n    variance-to-mean ratio. If not provided a value, the accumulator function\n    returns the current moving variance-to-mean ratio.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    mean: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmvmr( 3 );\n    > var F = accumulator()\n    null\n    > F = accumulator( 2.0 )\n    0.0\n    > F = accumulator( 1.0 )\n    ~0.33\n    > F = accumulator( 3.0 )\n    0.5\n    > F = accumulator( 7.0 )\n    ~2.55\n    > F = accumulator()\n    ~2.55\n\n    See Also\n    --------\n    incrmmean, incrmvariance, incrvmr\n","incrnancount":"\nincrnancount()\n    Returns an accumulator function which incrementally updates a count,\n    ignoring `NaN` values.\n\n    If provided a value, the accumulator function returns an updated count. If\n    not provided a value, the accumulator function returns the current count.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrnancount();\n    > var v = accumulator()\n    0\n    > v = accumulator( 2.0 )\n    1\n    > v = accumulator( -5.0 )\n    2\n    > v = accumulator()\n    2\n\n    See Also\n    --------\n    incrnansum\n","incrnansum":"\nincrnansum()\n    Returns an accumulator function which incrementally computes a sum, ignoring\n    `NaN` values.\n\n    If provided a value, the accumulator function returns an updated sum. If not\n    provided a value, the accumulator function returns the current sum.\n\n    For long running accumulations or accumulations of large numbers, care\n    should be taken to prevent overflow.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrnansum();\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    2.0\n    > s = accumulator( NaN )\n    2.0\n    > s = accumulator( -5.0 )\n    -3.0\n    > s = accumulator()\n    -3.0\n\n    See Also\n    --------\n    incrnansumabs, incrsum\n","incrnansumabs":"\nincrnansumabs()\n    Returns an accumulator function which incrementally computes a sum of\n    absolute values, ignoring NaN values.\n\n    If provided a value, the accumulator function returns an updated sum. If not\n    provided a value, the accumulator function returns the current sum.\n\n    For long running accumulations or accumulations of large numbers, care\n    should be taken to prevent overflow.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrnansumabs();\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    2.0\n    > s = accumulator( NaN )\n    2.0\n    > s = accumulator( -5.0 )\n    7.0\n    > s = accumulator()\n    7.0\n\n    See Also\n    --------\n    incrnansum, incrnansumabs2, incrsumabs\n","incrnansumabs2":"\nincrnansumabs2()\n    Returns an accumulator function which incrementally computes a sum of\n    squared absolute values, ignoring NaN values.\n\n    If provided a value, the accumulator function returns an updated sum. If not\n    provided a value, the accumulator function returns the current sum.\n\n    For long running accumulations or accumulations of large numbers, care\n    should be taken to prevent overflow.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrnansumabs2();\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    4.0\n    > s = accumulator( NaN )\n    4.0\n    > s = accumulator( -5.0 )\n    29.0\n    > s = accumulator()\n    29.0\n\n    See Also\n    --------\n    incrnansum, incrnansumabs, incrsumabs2\n","incrpcorr":"\nincrpcorr( [mx, my] )\n    Returns an accumulator function which incrementally computes a sample\n    Pearson product-moment correlation coefficient.\n\n    If provided values, the accumulator function returns an updated sample\n    correlation coefficient. If not provided values, the accumulator function\n    returns the current sample correlation coefficient.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    mx: number (optional)\n        Known mean.\n\n    my: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrpcorr();\n    > var r = accumulator()\n    null\n    > r = accumulator( 2.0, 1.0 )\n    0.0\n    > r = accumulator( -5.0, 3.14 )\n    ~-1.0\n    > r = accumulator()\n    ~-1.0\n\n    See Also\n    --------\n    incrcovariance, incrmpcorr, incrsummary\n","incrpcorr2":"\nincrpcorr2( [mx, my] )\n    Returns an accumulator function which incrementally computes the squared\n    sample Pearson product-moment correlation coefficient.\n\n    If provided values, the accumulator function returns an updated accumulated\n    value. If not provided values, the accumulator function returns the current\n    accumulated value.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    mx: number (optional)\n        Known mean.\n\n    my: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrpcorr2();\n    > var r2 = accumulator()\n    null\n    > r2 = accumulator( 2.0, 1.0 )\n    0.0\n    > r2 = accumulator( -5.0, 3.14 )\n    ~1.0\n    > r2 = accumulator()\n    ~1.0\n\n    See Also\n    --------\n    incrapcorr, incrmpcorr2, incrpcorr\n","incrpcorrdist":"\nincrpcorrdist( [mx, my] )\n    Returns an accumulator function which incrementally computes a sample\n    Pearson product-moment correlation distance.\n\n    The correlation distance is defined as one minus the Pearson product-moment\n    correlation coefficient and, thus, resides on the interval [0,2].\n\n    If provided values, the accumulator function returns an updated sample\n    correlation distance. If not provided values, the accumulator function\n    returns the current sample correlation distance.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    mx: number (optional)\n        Known mean.\n\n    my: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrpcorrdist();\n    > var d = accumulator()\n    null\n    > d = accumulator( 2.0, 1.0 )\n    1.0\n    > d = accumulator( -5.0, 3.14 )\n    ~2.0\n    > d = accumulator()\n    ~2.0\n\n    See Also\n    --------\n    incrcovariance, incrpcorr, incrsummary\n","incrpcorrdistmat":"\nincrpcorrdistmat( out[, means] )\n    Returns an accumulator function which incrementally computes a sample\n    Pearson product-moment correlation distance matrix.\n\n    If provided a data vector, the accumulator function returns an updated\n    sample correlation distance matrix. If not provided a data vector, the\n    accumulator function returns the current sample correlation distance matrix.\n\n    Due to limitations inherent in representing numeric values using floating-\n    point format (i.e., the inability to represent numeric values with infinite\n    precision), the correlation distance between perfectly correlated random\n    variables may *not* be `0` or `2`. In fact, the correlation distance is\n    *not* guaranteed to be strictly on the interval [0,2]. Any computed distance\n    should, however, be within floating-point roundoff error.\n\n    Parameters\n    ----------\n    out: integer|ndarray\n        Order of the correlation distance matrix or a square 2-dimensional\n        ndarray for storing the correlation distance matrix.\n\n    means: ndarray (optional)\n        Known means.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrpcorrdistmat( 2 );\n    > var out = accumulator()\n    <ndarray>\n    > var buf = new Float64Array( 2 );\n    > var shape = [ 2 ];\n    > var strides = [ 1 ];\n    > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n    > v.set( 0, 2.0 );\n    > v.set( 1, 1.0 );\n    > out = accumulator( v )\n    <ndarray>\n    > v.set( 0, -5.0 );\n    > v.set( 1, 3.14 );\n    > out = accumulator( v )\n    <ndarray>\n    > out = accumulator()\n    <ndarray>\n\n    See Also\n    --------\n    incrpcorrdist, incrpcorrmat\n","incrpcorrmat":"\nincrpcorrmat( out[, means] )\n    Returns an accumulator function which incrementally computes a sample\n    Pearson product-moment correlation matrix.\n\n    If provided a data vector, the accumulator function returns an updated\n    sample correlation matrix. If not provided a data vector, the accumulator\n    function returns the current sample correlation matrix.\n\n    Parameters\n    ----------\n    out: integer|ndarray\n        Order of the correlation matrix or a square 2-dimensional ndarray for\n        storing the correlation matrix.\n\n    means: ndarray (optional)\n        Known means.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrpcorrmat( 2 );\n    > var out = accumulator()\n    <ndarray>\n    > var buf = new Float64Array( 2 );\n    > var shape = [ 2 ];\n    > var strides = [ 1 ];\n    > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n    > v.set( 0, 2.0 );\n    > v.set( 1, 1.0 );\n    > out = accumulator( v )\n    <ndarray>\n    > v.set( 0, -5.0 );\n    > v.set( 1, 3.14 );\n    > out = accumulator( v )\n    <ndarray>\n    > out = accumulator()\n    <ndarray>\n\n    See Also\n    --------\n    incrcovmat, incrpcorr, incrpcorrdistmat\n","incrprod":"\nincrprod()\n    Returns an accumulator function which incrementally computes a product.\n\n    If provided a value, the accumulator function returns an updated product. If\n    not provided a value, the accumulator function returns the current product.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    For long running accumulations or accumulations of large numbers, care\n    should be taken to prevent overflow. Note, however, that overflow/underflow\n    may be transient, as the accumulator does not use a double-precision\n    floating-point number to store an accumulated product. Instead, the\n    accumulator splits an accumulated product into a normalized fraction and\n    exponent and updates each component separately. Doing so guards against a\n    loss in precision.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrprod();\n    > var v = accumulator()\n    null\n    > v = accumulator( 2.0 )\n    2.0\n    > v = accumulator( -5.0 )\n    -10.0\n    > v = accumulator()\n    -10.0\n\n    See Also\n    --------\n    incrmprod, incrsum, incrsummary\n","incrrange":"\nincrrange()\n    Returns an accumulator function which incrementally computes a range.\n\n    If provided a value, the accumulator function returns an updated range. If\n    not provided a value, the accumulator function returns the current range.\n\n    If provided `NaN`, the range is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrrange();\n    > var v = accumulator()\n    null\n    > v = accumulator( -2.0 )\n    0.0\n    > v = accumulator( 1.0 )\n    3.0\n    > v = accumulator( 3.0 )\n    5.0\n    > v = accumulator()\n    5.0\n\n    See Also\n    --------\n    incrmax, incrmean, incrmin, incrmrange, incrsummary\n","incrrmse":"\nincrrmse()\n    Returns an accumulator function which incrementally computes the root mean\n    squared error (RMSE).\n\n    If provided input values, the accumulator function returns an updated root\n    mean squared error. If not provided input values, the accumulator function\n    returns the current root mean squared error.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrrmse();\n    > var r = accumulator()\n    null\n    > r = accumulator( 2.0, 3.0 )\n    1.0\n    > r = accumulator( -5.0, 2.0 )\n    5.0\n    > r = accumulator()\n    5.0\n\n    See Also\n    --------\n    incrmrmse, incrmse, incrrss\n","incrrss":"\nincrrss()\n    Returns an accumulator function which incrementally computes the residual\n    sum of squares (RSS).\n\n    If provided input values, the accumulator function returns an updated\n    residual sum of squares. If not provided input values, the accumulator\n    function returns the current residual sum of squares.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrrss();\n    > var r = accumulator()\n    null\n    > r = accumulator( 2.0, 3.0 )\n    1.0\n    > r = accumulator( -5.0, 2.0 )\n    50.0\n    > r = accumulator()\n    50.0\n\n    See Also\n    --------\n    incrmrss, incrmse, incrrmse\n","incrskewness":"\nincrskewness()\n    Returns an accumulator function which incrementally computes a corrected\n    sample skewness.\n\n    If provided a value, the accumulator function returns an updated corrected\n    sample skewness. If not provided a value, the accumulator function returns\n    the current corrected sample skewness.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrskewness();\n    > var v = accumulator( 2.0 )\n    null\n    > v = accumulator( -5.0 )\n    null\n    > v = accumulator( -10.0 )\n    ~0.492\n    > v = accumulator()\n    ~0.492\n\n    See Also\n    --------\n    incrkurtosis, incrmean, incrstdev, incrsummary, incrvariance\n","incrspace":"\nincrspace( start, stop[, increment] )\n    Generates a linearly spaced numeric array using a provided increment.\n\n    If an `increment` is not provided, the default `increment` is `1`.\n\n    The output array is guaranteed to include the `start` value but does not\n    include the `stop` value.\n\n    Parameters\n    ----------\n    start: number\n        First array value.\n\n    stop: number\n        Array element bound.\n\n    increment: number (optional)\n        Increment. Default: `1`.\n\n    Returns\n    -------\n    arr: Array\n        Linearly spaced numeric array.\n\n    Examples\n    --------\n    > var arr = incrspace( 0, 11, 2 )\n    [ 0, 2, 4, 6, 8, 10 ]\n\n    See Also\n    --------\n    linspace, logspace\n","incrstdev":"\nincrstdev( [mean] )\n    Returns an accumulator function which incrementally computes a corrected\n    sample standard deviation.\n\n    If provided a value, the accumulator function returns an updated corrected\n    sample standard deviation. If not provided a value, the accumulator function\n    returns the current corrected sample standard deviation.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    mean: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrstdev();\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    0.0\n    > s = accumulator( -5.0 )\n    ~4.95\n    > s = accumulator()\n    ~4.95\n\n    See Also\n    --------\n    incrkurtosis, incrmean, incrmstdev, incrskewness, incrsummary, incrvariance\n","incrsum":"\nincrsum()\n    Returns an accumulator function which incrementally computes a sum.\n\n    If provided a value, the accumulator function returns an updated sum. If not\n    provided a value, the accumulator function returns the current sum.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    For long running accumulations or accumulations of large numbers, care\n    should be taken to prevent overflow.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrsum();\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    2.0\n    > s = accumulator( -5.0 )\n    -3.0\n    > s = accumulator()\n    -3.0\n\n    See Also\n    --------\n    incrcount, incrmean, incrmsum, incrprod, incrsummary\n","incrsumabs":"\nincrsumabs()\n    Returns an accumulator function which incrementally computes a sum of\n    absolute values.\n\n    If provided a value, the accumulator function returns an updated sum. If not\n    provided a value, the accumulator function returns the current sum.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    For long running accumulations or accumulations of large numbers, care\n    should be taken to prevent overflow.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrsumabs();\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    2.0\n    > s = accumulator( -5.0 )\n    7.0\n    > s = accumulator()\n    7.0\n\n    See Also\n    --------\n    incrmeanabs, incrmsumabs, incrsum\n","incrsumabs2":"\nincrsumabs2()\n    Returns an accumulator function which incrementally computes a sum of\n    squared absolute values.\n\n    If provided a value, the accumulator function returns an updated sum. If not\n    provided a value, the accumulator function returns the current sum.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    For long running accumulations or accumulations of large numbers, care\n    should be taken to prevent overflow.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrsumabs2();\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    4.0\n    > s = accumulator( -5.0 )\n    29.0\n    > s = accumulator()\n    29.0\n\n    See Also\n    --------\n    incrmeanabs2, incrmsumabs2, incrsumabs\n","incrsummary":"\nincrsummary()\n    Returns an accumulator function which incrementally computes a statistical\n    summary.\n\n    If provided a value, the accumulator function returns an updated summary. If\n    not provided a value, the accumulator function returns the current summary.\n\n    The returned summary is an object containing the following fields:\n\n    - count: count.\n    - max: maximum value.\n    - min: minimum value.\n    - range: range.\n    - midrange: mid-range.\n    - sum: sum.\n    - mean: arithmetic mean.\n    - variance: unbiased sample variance.\n    - stdev: corrected sample standard deviation.\n    - skewness: corrected sample skewness.\n    - kurtosis: corrected sample excess kurtosis.\n\n    For long running accumulations or accumulations of large numbers, care\n    should be taken to prevent overflow.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrsummary();\n    > var s = accumulator()\n    {}\n    > s = accumulator( 2.0 )\n    {...}\n    > s = accumulator( -5.0 )\n    {...}\n    > s = accumulator()\n    {...}\n\n    See Also\n    --------\n    incrcount, incrkurtosis, incrmax, incrmean, incrmidrange, incrmin, incrmsummary, incrrange, incrskewness, incrstdev, incrsum, incrvariance\n","incrsumprod":"\nincrsumprod()\n    Returns an accumulator function which incrementally computes a sum of\n    products.\n\n    If provided input values, the accumulator function returns an updated sum.\n    If not provided input values, the accumulator function returns the current\n    sum.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    For long running accumulations or accumulations of large numbers, care\n    should be taken to prevent overflow.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrsumprod();\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0, 3.0 )\n    6.0\n    > s = accumulator( -5.0, 2.0 )\n    -4.0\n    > s = accumulator()\n    -4.0\n\n    See Also\n    --------\n    incrmsumprod, incrprod, incrsum\n","incrvariance":"\nincrvariance( [mean] )\n    Returns an accumulator function which incrementally computes an unbiased\n    sample variance.\n\n    If provided a value, the accumulator function returns an updated unbiased\n    sample variance. If not provided a value, the accumulator function returns\n    the current unbiased sample variance.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    mean: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrvariance();\n    > var s2 = accumulator()\n    null\n    > s2 = accumulator( 2.0 )\n    0.0\n    > s2 = accumulator( -5.0 )\n    24.5\n    > s2 = accumulator()\n    24.5\n\n    See Also\n    --------\n    incrkurtosis, incrmean, incrmstdev, incrskewness, incrstdev, incrsummary\n","incrvmr":"\nincrvmr( [mean] )\n    Returns an accumulator function which incrementally computes a variance-to-\n    mean ratio (VMR).\n\n    If provided a value, the accumulator function returns an updated accumulated\n    value. If not provided a value, the accumulator function returns the current\n    accumulated value.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    mean: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrvmr();\n    > var D = accumulator()\n    null\n    > D = accumulator( 2.0 )\n    0.0\n    > D = accumulator( 1.0 )\n    ~0.33\n    > D = accumulator()\n    ~0.33\n\n    See Also\n    --------\n    incrmean, incrmvmr, incrvariance\n","incrwmean":"\nincrwmean()\n    Returns an accumulator function which incrementally computes a weighted\n    arithmetic mean.\n\n    If provided arguments, the accumulator function returns an updated weighted\n    mean. If not provided arguments, the accumulator function returns the\n    current weighted mean.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    The accumulator function accepts two arguments:\n\n    - x: value.\n    - w: weight.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrwmean();\n    > var mu = accumulator()\n    null\n    > mu = accumulator( 2.0, 1.0 )\n    2.0\n    > mu = accumulator( 2.0, 0.5 )\n    2.0\n    > mu = accumulator( 3.0, 1.5 )\n    2.5\n    > mu = accumulator()\n    2.5\n\n    See Also\n    --------\n    increwmean, incrmean, incrmmean\n","ind2sub":"\nind2sub( shape, idx[, options] )\n    Converts a linear index to an array of subscripts.\n\n    Parameters\n    ----------\n    shape: ArrayLike\n        Array shape.\n\n    idx: integer\n        Linear index.\n\n    options: Object (optional)\n        Options.\n\n    options.order: string (optional)\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran style). Default: 'row-major'.\n\n    options.mode: string (optional)\n        Specifies how to handle a linear index which exceeds array dimensions.\n        If equal to 'throw', the function throws an error when a linear index\n        exceeds array dimensions. If equal to 'normalize', the function\n        normalizes negative linear indices and throws an error when a linear\n        index exceeds array dimensions. If equal to 'wrap', the function wraps\n        around a linear index exceeding array dimensions using modulo\n        arithmetic. If equal to 'clamp', the function sets a linear index\n        exceeding array dimensions to either `0` (minimum linear index) or the\n        maximum linear index. Default: 'throw'.\n\n    Returns\n    -------\n    out: Array<integer>\n        Subscripts.\n\n    Examples\n    --------\n    > var d = [ 3, 3, 3 ];\n    > var s = ind2sub( d, 17 )\n    [ 1, 2, 2 ]\n\n\nind2sub.assign( shape, idx[, options], out )\n    Converts a linear index to an array of subscripts and assigns results to a\n    provided output array.\n\n    Parameters\n    ----------\n    shape: ArrayLike\n        Array shape.\n\n    idx: integer\n        Linear index.\n\n    options: Object (optional)\n        Options.\n\n    options.order: string (optional)\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran style). Default: 'row-major'.\n\n    options.mode: string (optional)\n        Specifies how to handle a linear index which exceeds array dimensions.\n        If equal to 'throw', the function throws an error when a linear index\n        exceeds array dimensions. If equal to 'normalize', the function\n        normalizes negative linear indices and throws an error when a linear\n        index exceeds array dimensions. If equal to 'wrap', the function wraps\n        around a linear index exceeding array dimensions using modulo\n        arithmetic. If equal to 'clamp', the function sets a linear index\n        exceeding array dimensions to either `0` (minimum linear index) or the\n        maximum linear index. Default: 'throw'.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Subscripts.\n\n    Examples\n    --------\n    > var d = [ 3, 3, 3 ];\n    > var out = [ 0, 0, 0 ];\n    > var s = ind2sub.assign( d, 17, out )\n    [ 1, 2, 2 ]\n    > var bool = ( s === out )\n    true\n\n    See Also\n    --------\n    array, ndarray, sub2ind\n","ind2sub.assign":"\nind2sub.assign( shape, idx[, options], out )\n    Converts a linear index to an array of subscripts and assigns results to a\n    provided output array.\n\n    Parameters\n    ----------\n    shape: ArrayLike\n        Array shape.\n\n    idx: integer\n        Linear index.\n\n    options: Object (optional)\n        Options.\n\n    options.order: string (optional)\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran style). Default: 'row-major'.\n\n    options.mode: string (optional)\n        Specifies how to handle a linear index which exceeds array dimensions.\n        If equal to 'throw', the function throws an error when a linear index\n        exceeds array dimensions. If equal to 'normalize', the function\n        normalizes negative linear indices and throws an error when a linear\n        index exceeds array dimensions. If equal to 'wrap', the function wraps\n        around a linear index exceeding array dimensions using modulo\n        arithmetic. If equal to 'clamp', the function sets a linear index\n        exceeding array dimensions to either `0` (minimum linear index) or the\n        maximum linear index. Default: 'throw'.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Subscripts.\n\n    Examples\n    --------\n    > var d = [ 3, 3, 3 ];\n    > var out = [ 0, 0, 0 ];\n    > var s = ind2sub.assign( d, 17, out )\n    [ 1, 2, 2 ]\n    > var bool = ( s === out )\n    true\n\n    See Also\n    --------\n    array, ndarray, sub2ind","indexOf":"\nindexOf( arr, searchElement[, fromIndex] )\n    Returns the first index at which a given element can be found.\n\n    Search is performed using *strict equality* comparison.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Array-like object.\n\n    searchElement: any\n        Element to find.\n\n    fromIndex: integer (optional)\n        Starting index (if negative, the start index is determined relative to\n        last element).\n\n    Returns\n    -------\n    out: integer\n        Index or -1.\n\n    Examples\n    --------\n    // Basic usage:\n    > var arr = [ 4, 3, 2, 1 ];\n    > var idx = indexOf( arr, 3 )\n    1\n    > arr = [ 4, 3, 2, 1 ];\n    > idx = indexOf( arr, 5 )\n    -1\n\n    // Using a `fromIndex`:\n    > arr = [ 1, 2, 3, 4, 5, 2, 6 ];\n    > idx = indexOf( arr, 2, 3 )\n    5\n\n    // `fromIndex` which exceeds `array` length:\n    > arr = [ 1, 2, 3, 4, 2, 5 ];\n    > idx = indexOf( arr, 2, 10 )\n    -1\n\n    // Negative `fromIndex`:\n    > arr = [ 1, 2, 3, 4, 5, 2, 6, 2 ];\n    > idx = indexOf( arr, 2, -4 )\n    5\n    > idx = indexOf( arr, 2, -1 )\n    7\n\n    // Negative `fromIndex` exceeding input `array` length:\n    > arr = [ 1, 2, 3, 4, 5, 2, 6 ];\n    > idx = indexOf( arr, 2, -10 )\n    1\n\n    // Array-like objects:\n    > var str = 'bebop';\n    > idx = indexOf( str, 'o' )\n    3\n\n","inherit":"\ninherit( ctor, superCtor )\n    Prototypical inheritance by replacing the prototype of one constructor with\n    the prototype of another constructor.\n\n    This function is not designed to work with ES2015/ES6 classes. For\n    ES2015/ES6 classes, use `class` with `extends`.\n\n    Parameters\n    ----------\n    ctor: Object|Function\n        Constructor which will inherit.\n\n    superCtor: Object|Function\n        Super (parent) constructor.\n\n    Returns\n    -------\n    out: Object|Function\n        Child constructor.\n\n    Examples\n    --------\n    // Create a parent constructor:\n    > function Foo() { return this; };\n    > Foo.prototype.beep = function beep() { return 'boop'; };\n\n    // Create a child constructor:\n    > function Bar() { Foo.call( this ); return this; };\n\n    // Setup inheritance:\n    > inherit( Bar, Foo );\n    > var bar = new Bar();\n    > var v = bar.beep()\n    'boop'\n\n","inheritedEnumerableProperties":"\ninheritedEnumerableProperties( value[, level] )\n    Returns an array of an object's inherited enumerable property names and\n    symbols.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    props: Array\n        List of an object's inherited enumerable properties.\n\n    Examples\n    --------\n    > var props = inheritedEnumerableProperties( {} )\n\n    See Also\n    --------\n    enumerableProperties, enumerablePropertiesIn, inheritedEnumerablePropertySymbols, inheritedKeys, inheritedNonEnumerableProperties, inheritedProperties\n","inheritedEnumerablePropertySymbols":"\ninheritedEnumerablePropertySymbols( value[, level] )\n    Returns an array of an object's inherited enumerable symbol properties.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's inherited enumerable symbol properties.\n\n    Examples\n    --------\n    > var symbols = inheritedEnumerablePropertySymbols( [] )\n\n    See Also\n    --------\n    enumerableProperties, enumerablePropertySymbols, inheritedKeys, nonEnumerablePropertySymbols, nonEnumerablePropertySymbolsIn, propertySymbols\n","inheritedKeys":"\ninheritedKeys( value[, level] )\n    Returns an array of an object's inherited enumerable property names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's inherited enumerable property names.\n\n    Examples\n    --------\n    > var keys = inheritedKeys( {} )\n\n    See Also\n    --------\n    objectKeys, keysIn, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedNonEnumerableProperties":"\ninheritedNonEnumerableProperties( value[, level] )\n    Returns an array of an object's inherited non-enumerable property names and\n    symbols.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    props: Array\n        List of an object's inherited non-enumerable properties.\n\n    Examples\n    --------\n    > var props = inheritedNonEnumerableProperties( {} )\n\n    See Also\n    --------\n    inheritedEnumerableProperties, inheritedNonEnumerablePropertyNames, inheritedNonEnumerablePropertySymbols, inheritedKeys, nonEnumerableProperties, nonEnumerablePropertiesIn, properties\n","inheritedNonEnumerablePropertyNames":"\ninheritedNonEnumerablePropertyNames( value[, level] )\n    Returns an array of an object's inherited non-enumerable property names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's inherited non-enumerable property names.\n\n    Examples\n    --------\n    > var keys = inheritedNonEnumerablePropertyNames( {} )\n\n    See Also\n    --------\n    inheritedNonEnumerableProperties, inheritedNonEnumerablePropertySymbols, objectKeys, nonEnumerablePropertyNames, nonEnumerablePropertyNamesIn, nonEnumerablePropertySymbols, propertyNames\n","inheritedNonEnumerablePropertySymbols":"\ninheritedNonEnumerablePropertySymbols( value[, level] )\n    Returns an array of an object's inherited non-enumerable symbol properties.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's inherited non-enumerable symbol properties.\n\n    Examples\n    --------\n    > var symbols = inheritedNonEnumerablePropertySymbols( [] )\n\n    See Also\n    --------\n    inheritedNonEnumerableProperties, inheritedNonEnumerablePropertyNames, nonEnumerableProperties, nonEnumerablePropertyNames, nonEnumerablePropertySymbols, nonEnumerablePropertySymbolsIn, propertySymbols\n","inheritedProperties":"\ninheritedProperties( value[, level] )\n    Returns an array of an object's inherited property names and symbols.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's inherited property names and symbols.\n\n    Examples\n    --------\n    > var symbols = inheritedProperties( [] )\n\n    See Also\n    --------\n    properties, propertiesIn, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedPropertyDescriptor":"\ninheritedPropertyDescriptor( value, property[, level] )\n    Returns a property descriptor for an object's inherited property.\n\n    If provided `null` or `undefined` or provided a non-existent property, the\n    function returns `null`.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    property: string|symbol\n        Property name.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    desc: Object|null\n        Property descriptor.\n\n    Examples\n    --------\n    > var desc = inheritedPropertyDescriptor( {}, 'toString' )\n    {...}\n\n    See Also\n    --------\n    propertyDescriptor, propertyDescriptorIn, inheritedKeys, inheritedPropertyDescriptors, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedPropertyDescriptors":"\ninheritedPropertyDescriptors( value[, level] )\n    Returns an object's inherited property descriptors.\n\n    If provided `null` or `undefined`, the function returns an empty object.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    desc: Object\n        An object's inherited property descriptors.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var desc = inheritedPropertyDescriptors( obj )\n    { 'foo': {...}, ... }\n\n    See Also\n    --------\n    propertyDescriptors, propertyDescriptorsIn, inheritedKeys, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedPropertyNames":"\ninheritedPropertyNames( value[, level] )\n    Returns an array of an object's inherited enumerable and non-enumerable\n    property names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's inherited enumerable and non-enumerable property\n        names.\n\n    Examples\n    --------\n    > var keys = inheritedPropertyNames( [] )\n\n    See Also\n    --------\n    inheritedKeys, inheritedPropertyDescriptors, inheritedPropertySymbols, propertyNames, propertyNamesIn\n","inheritedPropertySymbols":"\ninheritedPropertySymbols( value[, level] )\n    Returns an array of an object's inherited symbol properties.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's inherited symbol properties.\n\n    Examples\n    --------\n    > var symbols = inheritedPropertySymbols( [] )\n\n    See Also\n    --------\n    inheritedKeys, inheritedPropertyDescriptors, inheritedPropertyNames, propertySymbols, propertySymbolsIn\n","inheritedWritableProperties":"\ninheritedWritableProperties( value[, level] )\n    Returns an array of an object's inherited writable property names and\n    symbols.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    props: Array\n        List of an object's inherited writable properties.\n\n    Examples\n    --------\n    > var props = inheritedWritableProperties( {} )\n\n    See Also\n    --------\n    inheritedWritablePropertyNames, inheritedWritablePropertySymbols, writableProperties, writablePropertiesIn, properties\n","inheritedWritablePropertyNames":"\ninheritedWritablePropertyNames( value[, level] )\n    Returns an array of an object's inherited writable property names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's inherited writable property names.\n\n    Examples\n    --------\n    > var keys = inheritedWritablePropertyNames( {} )\n\n    See Also\n    --------\n    inheritedWritablePropertySymbols, writablePropertyNames, writablePropertyNamesIn, properties\n","inheritedWritablePropertySymbols":"\ninheritedWritablePropertySymbols( value[, level] )\n    Returns an array of an object's inherited writable symbol properties.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's inherited writable symbol properties.\n\n    Examples\n    --------\n    > var symbols = inheritedWritablePropertySymbols( [] )\n\n    See Also\n    --------\n    inheritedWritablePropertyNames, writablePropertySymbols, writablePropertySymbolsIn, properties\n","inmap":"\ninmap( collection, fcn[, thisArg] )\n    Invokes a function for each element in a collection and updates the\n    collection in-place.\n\n    When invoked, the input function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection. If provided an object, the object must be array-like\n        (excluding strings and functions).\n\n    fcn: Function\n        Function to invoke for each element in the input collection. The\n        function's return value is used to update the collection in-place.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function foo( v, i ) { return v * i; };\n    > var arr = [ 1.0, 2.0, 3.0 ];\n    > var out = inmap( arr, foo )\n    [ 0.0, 2.0, 6.0 ]\n    > var bool = ( out === arr )\n    true\n\n    See Also\n    --------\n    forEach, inmapRight, map\n","inmapAsync":"\ninmapAsync( collection, [options,] fcn, done )\n    Invokes a function once for each element in a collection and updates a\n    collection in-place.\n\n    When invoked, `fcn` is provided a maximum of four arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If `fcn`\n    accepts two arguments, `fcn` is provided:\n\n    - value\n    - next\n\n    If `fcn` accepts three arguments, `fcn` is provided:\n\n    - value\n    - index\n    - next\n\n    For every other `fcn` signature, `fcn` is provided all four arguments.\n\n    The `next` callback accepts two arguments:\n\n    - error: error argument.\n    - result: value used to update the collection.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling. Note, however, that the function\n    may have mutated an input collection during prior invocations, resulting in\n    a partially mutated collection.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function fcn( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, value*index );\n    ...     }\n    ... };\n    > function done( error, collection ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( collection === arr );\n    ...     console.log( collection );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > inmapAsync( arr, fcn, done )\n    1000\n    2500\n    3000\n    true\n    [ 0, 2500, 2000 ]\n\n    // Limit number of concurrent invocations:\n    > function fcn( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, value*index );\n    ...     }\n    ... };\n    > function done( error, collection ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( collection === arr );\n    ...     console.log( collection );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 3000, 2500, 1000 ];\n    > inmapAsync( arr, opts, fcn, done )\n    2500\n    3000\n    1000\n    true\n    [ 0, 2500, 2000 ]\n\n    // Process sequentially:\n    > function fcn( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, value*index );\n    ...     }\n    ... };\n    > function done( error, collection ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( collection === arr );\n    ...     console.log( collection );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 3000, 2500, 1000 ];\n    > inmapAsync( arr, opts, fcn, done )\n    3000\n    2500\n    1000\n    true\n    [ 0, 2500, 2000 ]\n\n\ninmapAsync.factory( [options,] fcn )\n    Returns a function which invokes a function once for each element in a\n    collection and updates a collection in-place.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function fcn( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, value*index );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = inmapAsync.factory( opts, fcn );\n    > function done( error, collection ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( collection === arr );\n    ...     console.log( collection );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    [ 0, 2500, 2000 ]\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n    [ 0, 1500, 2000 ]\n\n    See Also\n    --------\n    forEachAsync, inmapRightAsync, inmap\n","inmapAsync.factory":"\ninmapAsync.factory( [options,] fcn )\n    Returns a function which invokes a function once for each element in a\n    collection and updates a collection in-place.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function fcn( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, value*index );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = inmapAsync.factory( opts, fcn );\n    > function done( error, collection ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( collection === arr );\n    ...     console.log( collection );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    [ 0, 2500, 2000 ]\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n    [ 0, 1500, 2000 ]\n\n    See Also\n    --------\n    forEachAsync, inmapRightAsync, inmap","inmapRight":"\ninmapRight( collection, fcn[, thisArg] )\n    Invokes a function for each element in a collection and updates the\n    collection in-place, iterating from right to left.\n\n    When invoked, the input function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection. If provided an object, the object must be array-like\n        (excluding strings and functions).\n\n    fcn: Function\n        Function to invoke for each element in the input collection. The\n        function's return value is used to update the collection in-place.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function foo( v, i ) { console.log( '%s: %d', i, v ); return v * i; };\n    > var arr = [ 1.0, 2.0, 3.0 ];\n    > var out = inmapRight( arr, foo )\n    2: 3.0\n    1: 2.0\n    0: 1.0\n    [ 0.0, 2.0, 6.0 ]\n    > var bool = ( out === arr )\n    true\n\n    See Also\n    --------\n    forEachRight, inmap, mapRight\n","inmapRightAsync":"\ninmapRightAsync( collection, [options,] fcn, done )\n    Invokes a function once for each element in a collection and updates a\n    collection in-place, iterating from right to left.\n\n    When invoked, `fcn` is provided a maximum of four arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If `fcn`\n    accepts two arguments, `fcn` is provided:\n\n    - value\n    - next\n\n    If `fcn` accepts three arguments, `fcn` is provided:\n\n    - value\n    - index\n    - next\n\n    For every other `fcn` signature, `fcn` is provided all four arguments.\n\n    The `next` callback accepts two arguments:\n\n    - error: error argument.\n    - result: value used to update the collection.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling. Note, however, that the function\n    may have mutated an input collection during prior invocations, resulting in\n    a partially mutated collection.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function fcn( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, value*index );\n    ...     }\n    ... };\n    > function done( error, collection ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( collection === arr );\n    ...     console.log( collection );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > inmapRightAsync( arr, fcn, done )\n    1000\n    2500\n    3000\n    true\n    [ 0, 2500, 6000 ]\n\n    // Limit number of concurrent invocations:\n    > function fcn( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, value*index );\n    ...     }\n    ... };\n    > function done( error, collection ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( collection === arr );\n    ...     console.log( collection );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 1000, 2500, 3000 ];\n    > inmapRightAsync( arr, opts, fcn, done )\n    2500\n    3000\n    1000\n    true\n    [ 0, 2500, 6000 ]\n\n    // Process sequentially:\n    > function fcn( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, value*index );\n    ...     }\n    ... };\n    > function done( error, collection ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( collection === arr );\n    ...     console.log( collection );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 1000, 2500, 3000 ];\n    > inmapRightAsync( arr, opts, fcn, done )\n    3000\n    2500\n    1000\n    true\n    [ 0, 2500, 6000 ]\n\n\ninmapRightAsync.factory( [options,] fcn )\n    Returns a function which invokes a function once for each element in a\n    collection and updates a collection in-place, iterating from right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function fcn( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, value*index );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = inmapRightAsync.factory( opts, fcn );\n    > function done( error, collection ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( collection === arr );\n    ...     console.log( collection );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    [ 0, 2500, 6000 ]\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n    [ 0, 1500, 4000 ]\n\n    See Also\n    --------\n    forEachRightAsync, inmapAsync, inmapRight\n","inmapRightAsync.factory":"\ninmapRightAsync.factory( [options,] fcn )\n    Returns a function which invokes a function once for each element in a\n    collection and updates a collection in-place, iterating from right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function fcn( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, value*index );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = inmapRightAsync.factory( opts, fcn );\n    > function done( error, collection ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( collection === arr );\n    ...     console.log( collection );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    [ 0, 2500, 6000 ]\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n    [ 0, 1500, 4000 ]\n\n    See Also\n    --------\n    forEachRightAsync, inmapAsync, inmapRight","inspectSinkStream":"\ninspectSinkStream( [options,] clbk )\n    Returns a writable stream for inspecting stream data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to encode strings as `Buffer` objects before writing\n        data to a returned stream. Default: true.\n\n    options.defaultEncoding: string (optional)\n        Default encoding when not explicitly specified when writing data.\n        Default: 'utf8'.\n\n    clbk: Function\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: WritableStream\n        Writable stream.\n\n    Examples\n    --------\n    > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n    > var s = inspectSinkStream( clbk );\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();\n\n\ninspectSinkStream.factory( [options] )\n    Returns a function for creating writable streams for inspecting stream data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to encode strings as `Buffer` objects before writing\n        data to a returned stream. Default: true.\n\n    options.defaultEncoding: string (optional)\n        Default encoding when not explicitly specified when writing data.\n        Default: 'utf8'.\n\n    Returns\n    -------\n    createStream( clbk ): Function\n        Function for creating writable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = inspectSinkStream.factory( opts );\n    > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n    > var s = createStream( clbk );\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();\n\n\ninspectSinkStream.objectMode( [options,] clbk )\n    Returns an \"objectMode\" writable stream for inspecting stream data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to encode strings as `Buffer` objects before writing\n        data to a returned stream. Default: true.\n\n    options.defaultEncoding: string (optional)\n        Default encoding when not explicitly specified when writing data.\n        Default: 'utf8'.\n\n    clbk: Function\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: WritableStream\n        Writable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n    > var s = inspectSinkStream.objectMode( clbk );\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();\n\n    See Also\n    --------\n    debugSinkStream, inspectStream\n","inspectSinkStream.factory":"\ninspectSinkStream.factory( [options] )\n    Returns a function for creating writable streams for inspecting stream data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to encode strings as `Buffer` objects before writing\n        data to a returned stream. Default: true.\n\n    options.defaultEncoding: string (optional)\n        Default encoding when not explicitly specified when writing data.\n        Default: 'utf8'.\n\n    Returns\n    -------\n    createStream( clbk ): Function\n        Function for creating writable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = inspectSinkStream.factory( opts );\n    > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n    > var s = createStream( clbk );\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();","inspectSinkStream.objectMode":"\ninspectSinkStream.objectMode( [options,] clbk )\n    Returns an \"objectMode\" writable stream for inspecting stream data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to encode strings as `Buffer` objects before writing\n        data to a returned stream. Default: true.\n\n    options.defaultEncoding: string (optional)\n        Default encoding when not explicitly specified when writing data.\n        Default: 'utf8'.\n\n    clbk: Function\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: WritableStream\n        Writable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n    > var s = inspectSinkStream.objectMode( clbk );\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();\n\n    See Also\n    --------\n    debugSinkStream, inspectStream","inspectStream":"\ninspectStream( [options,] clbk )\n    Returns a transform stream for inspecting stream data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    clbk: Function\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream.\n\n    Examples\n    --------\n    > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n    > var s = inspectStream( clbk );\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();\n\n\ninspectStream.factory( [options] )\n    Returns a function for creating transform streams for inspecting stream\n    data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    createStream( clbk ): Function\n        Function for creating transform streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = inspectStream.factory( opts );\n    > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n    > var s = createStream( clbk );\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();\n\n\ninspectStream.objectMode( [options,] clbk )\n    Returns an \"objectMode\" transform stream for inspecting stream data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    clbk: Function\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n    > var s = inspectStream.objectMode( clbk );\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();\n\n    See Also\n    --------\n    debugStream\n","inspectStream.factory":"\ninspectStream.factory( [options] )\n    Returns a function for creating transform streams for inspecting stream\n    data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    createStream( clbk ): Function\n        Function for creating transform streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = inspectStream.factory( opts );\n    > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n    > var s = createStream( clbk );\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();","inspectStream.objectMode":"\ninspectStream.objectMode( [options,] clbk )\n    Returns an \"objectMode\" transform stream for inspecting stream data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    clbk: Function\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n    > var s = inspectStream.objectMode( clbk );\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();\n\n    See Also\n    --------\n    debugStream","instanceOf":"\ninstanceOf( value, constructor )\n    Tests whether a value has in its prototype chain a specified constructor as\n    a prototype property.\n\n    While the prototype of an `object` created using object literal notion is\n    `undefined`, the function returns `true` when provided an `object` literal\n    and the `Object` constructor. This maintains consistent behavior with the\n    `instanceof` operator.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    constructor: Function\n        Constructor.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is an instance of a provided constructor.\n\n    Examples\n    --------\n    > var bool = instanceOf( [], Array )\n    true\n    > bool = instanceOf( {}, Object )\n    true\n    > bool = instanceOf( null, Object )\n    false\n\n    See Also\n    --------\n    isPrototypeOf, constructorName, inherit, typeOf\n","INT8_MAX":"\nINT8_MAX\n    Maximum signed 8-bit integer.\n\n    The maximum signed 8-bit integer is given by `2^7 - 1`.\n\n    Examples\n    --------\n    > INT8_MAX\n    127\n\n    See Also\n    --------\n    INT8_MIN\n","INT8_MIN":"\nINT8_MIN\n    Minimum signed 8-bit integer.\n\n    The minimum signed 8-bit integer is given by `-(2^7)`.\n\n    Examples\n    --------\n    > INT8_MIN\n    -128\n\n    See Also\n    --------\n    INT8_MAX\n","INT8_NUM_BYTES":"\nINT8_NUM_BYTES\n    Size (in bytes) of an 8-bit signed integer.\n\n    Examples\n    --------\n    > INT8_NUM_BYTES\n    1\n\n    See Also\n    --------\n    INT16_NUM_BYTES, INT32_NUM_BYTES, UINT8_NUM_BYTES\n","Int8Array":"\nInt8Array()\n    A typed array constructor which returns a typed array representing an array\n    of twos-complement 8-bit signed integers in the platform byte order.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Int8Array()\n    <Int8Array>\n\n\nInt8Array( length )\n    Returns a typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( 5 )\n    <Int8Array>[ 0, 0, 0, 0, 0 ]\n\n\nInt8Array( typedarray )\n    Creates a typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n    > var arr2 = new Int8Array( arr1 )\n    <Int8Array>[ 5, 5, 5 ]\n\n\nInt8Array( obj )\n    Creates a typed array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a typed array.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 5.0, 5.0, 5.0 ];\n    > var arr2 = new Int8Array( arr1 )\n    <Int8Array>[ 5, 5, 5 ]\n\n\nInt8Array( buffer[, byteOffset[, length]] )\n    Returns a typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 4 );\n    > var arr = new Int8Array( buf, 0, 4 )\n    <Int8Array>[ 0, 0, 0, 0 ]\n\n\nInt8Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Int8Array.from( [ 1, 2 ], mapFcn )\n    <Int8Array>[ 2, 4 ]\n\n\nInt8Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Int8Array.of( 1, 2 )\n    <Int8Array>[ 1, 2 ]\n\n\nInt8Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Int8Array.BYTES_PER_ELEMENT\n    1\n\n\nInt8Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Int8Array.name\n    'Int8Array'\n\n\nInt8Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>\n\n\nInt8Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( 5 );\n    > arr.byteLength\n    5\n\n\nInt8Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Int8Array( 5 );\n    > arr.byteOffset\n    0\n\n\nInt8Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Int8Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    1\n\n\nInt8Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Int8Array( 5 );\n    > arr.length\n    5\n\n\nInt8Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Int8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2\n\n\nInt8Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true\n\n\nInt8Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false\n\n\nInt8Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Int8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3\n\n\nInt8Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2\n\n\nInt8Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3\n\n\nInt8Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2\n\n\nInt8Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '\n\n\nInt8Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true\n\n\nInt8Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2\n\n\nInt8Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'\n\n\nInt8Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true\n\n\nInt8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3\n\n\nInt8Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Int8Array>[ 2, 4, 6 ]\n\n\nInt8Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14\n\n\nInt8Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14\n\n\nInt8Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Int8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] )\n    <Int8Array>\n    > arr.reverse()\n    <Int8Array>[ 3, 2, 1 ]\n\n\nInt8Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4\n\n\nInt8Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3\n\n\nInt8Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true\n\n\nInt8Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Int8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Int8Array>[ 0, 1, 1, 2, 2 ]\n\n\nInt8Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int8Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Int8Array>[ 3, 4, 5 ]\n\n\nInt8Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'\n\n\nInt8Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'\n\n\nInt8Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Int8Array.from":"\nInt8Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Int8Array.from( [ 1, 2 ], mapFcn )\n    <Int8Array>[ 2, 4 ]","Int8Array.of":"\nInt8Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Int8Array.of( 1, 2 )\n    <Int8Array>[ 1, 2 ]","Int8Array.BYTES_PER_ELEMENT":"\nInt8Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Int8Array.BYTES_PER_ELEMENT\n    1","Int8Array.name":"\nInt8Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Int8Array.name\n    'Int8Array'","Int8Array.prototype.buffer":"\nInt8Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>","Int8Array.prototype.byteLength":"\nInt8Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( 5 );\n    > arr.byteLength\n    5","Int8Array.prototype.byteOffset":"\nInt8Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Int8Array( 5 );\n    > arr.byteOffset\n    0","Int8Array.prototype.BYTES_PER_ELEMENT":"\nInt8Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Int8Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    1","Int8Array.prototype.length":"\nInt8Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Int8Array( 5 );\n    > arr.length\n    5","Int8Array.prototype.copyWithin":"\nInt8Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Int8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2","Int8Array.prototype.entries":"\nInt8Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true","Int8Array.prototype.every":"\nInt8Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false","Int8Array.prototype.fill":"\nInt8Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Int8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3","Int8Array.prototype.filter":"\nInt8Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2","Int8Array.prototype.find":"\nInt8Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3","Int8Array.prototype.findIndex":"\nInt8Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2","Int8Array.prototype.forEach":"\nInt8Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '","Int8Array.prototype.includes":"\nInt8Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true","Int8Array.prototype.indexOf":"\nInt8Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2","Int8Array.prototype.join":"\nInt8Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'","Int8Array.prototype.keys":"\nInt8Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true","Int8Array.prototype.lastIndexOf":"\nInt8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3","Int8Array.prototype.map":"\nInt8Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Int8Array>[ 2, 4, 6 ]","Int8Array.prototype.reduce":"\nInt8Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14","Int8Array.prototype.reduceRight":"\nInt8Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14","Int8Array.prototype.reverse":"\nInt8Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Int8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] )\n    <Int8Array>\n    > arr.reverse()\n    <Int8Array>[ 3, 2, 1 ]","Int8Array.prototype.set":"\nInt8Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4","Int8Array.prototype.slice":"\nInt8Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3","Int8Array.prototype.some":"\nInt8Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true","Int8Array.prototype.sort":"\nInt8Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Int8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Int8Array>[ 0, 1, 1, 2, 2 ]","Int8Array.prototype.subarray":"\nInt8Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int8Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Int8Array>[ 3, 4, 5 ]","Int8Array.prototype.toLocaleString":"\nInt8Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'","Int8Array.prototype.toString":"\nInt8Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'","Int8Array.prototype.values":"\nInt8Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","INT16_MAX":"\nINT16_MAX\n    Maximum signed 16-bit integer.\n\n    The maximum signed 16-bit integer is given by `2^15 - 1`.\n\n    Examples\n    --------\n    > INT16_MAX\n    32767\n\n    See Also\n    --------\n    INT16_MIN\n","INT16_MIN":"\nINT16_MIN\n    Minimum signed 16-bit integer.\n\n    The minimum signed 16-bit integer is given by `-(2^15)`.\n\n    Examples\n    --------\n    > INT16_MIN\n    -32768\n\n    See Also\n    --------\n    INT16_MAX\n","INT16_NUM_BYTES":"\nINT16_NUM_BYTES\n    Size (in bytes) of a 16-bit signed integer.\n\n    Examples\n    --------\n    > INT16_NUM_BYTES\n    2\n\n    See Also\n    --------\n    INT32_NUM_BYTES, INT8_NUM_BYTES, UINT16_NUM_BYTES\n","Int16Array":"\nInt16Array()\n    A typed array constructor which returns a typed array representing an array\n    of twos-complement 16-bit signed integers in the platform byte order.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Int16Array()\n    <Int16Array>\n\n\nInt16Array( length )\n    Returns a typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( 5 )\n    <Int16Array>[ 0, 0, 0, 0, 0 ]\n\n\nInt16Array( typedarray )\n    Creates a typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n    > var arr2 = new Int16Array( arr1 )\n    <Int16Array>[ 5, 5, 5 ]\n\n\nInt16Array( obj )\n    Creates a typed array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a typed array.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 5.0, 5.0, 5.0 ];\n    > var arr2 = new Int16Array( arr1 )\n    <Int16Array>[ 5, 5, 5 ]\n\n\nInt16Array( buffer[, byteOffset[, length]] )\n    Returns a typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 8 );\n    > var arr = new Int16Array( buf, 0, 4 )\n    <Int16Array>[ 0, 0, 0, 0 ]\n\n\nInt16Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Int16Array.from( [ 1, 2 ], mapFcn )\n    <Int16Array>[ 2, 4 ]\n\n\nInt16Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Int16Array.of( 1, 2 )\n    <Int16Array>[ 1, 2 ]\n\n\nInt16Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Int16Array.BYTES_PER_ELEMENT\n    2\n\n\nInt16Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Int16Array.name\n    'Int16Array'\n\n\nInt16Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>\n\n\nInt16Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( 5 );\n    > arr.byteLength\n    10\n\n\nInt16Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Int16Array( 5 );\n    > arr.byteOffset\n    0\n\n\nInt16Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Int16Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    2\n\n\nInt16Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Int16Array( 5 );\n    > arr.length\n    5\n\n\nInt16Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Int16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2\n\n\nInt16Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true\n\n\nInt16Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false\n\n\nInt16Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Int16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3\n\n\nInt16Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2\n\n\nInt16Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3\n\n\nInt16Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2\n\n\nInt16Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '\n\n\nInt16Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true\n\n\nInt16Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2\n\n\nInt16Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'\n\n\nInt16Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true\n\n\nInt16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3\n\n\nInt16Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Int16Array>[ 2, 4, 6 ]\n\n\nInt16Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14\n\n\nInt16Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14\n\n\nInt16Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Int16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] )\n    <Int16Array>\n    > arr.reverse()\n    <Int16Array>[ 3, 2, 1 ]\n\n\nInt16Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4\n\n\nInt16Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3\n\n\nInt16Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true\n\n\nInt16Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Int16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Int16Array>[ 0, 1, 1, 2, 2 ]\n\n\nInt16Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int16Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Int16Array>[ 3, 4, 5 ]\n\n\nInt16Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'\n\n\nInt16Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'\n\n\nInt16Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Int16Array.from":"\nInt16Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Int16Array.from( [ 1, 2 ], mapFcn )\n    <Int16Array>[ 2, 4 ]","Int16Array.of":"\nInt16Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Int16Array.of( 1, 2 )\n    <Int16Array>[ 1, 2 ]","Int16Array.BYTES_PER_ELEMENT":"\nInt16Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Int16Array.BYTES_PER_ELEMENT\n    2","Int16Array.name":"\nInt16Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Int16Array.name\n    'Int16Array'","Int16Array.prototype.buffer":"\nInt16Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>","Int16Array.prototype.byteLength":"\nInt16Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( 5 );\n    > arr.byteLength\n    10","Int16Array.prototype.byteOffset":"\nInt16Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Int16Array( 5 );\n    > arr.byteOffset\n    0","Int16Array.prototype.BYTES_PER_ELEMENT":"\nInt16Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Int16Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    2","Int16Array.prototype.length":"\nInt16Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Int16Array( 5 );\n    > arr.length\n    5","Int16Array.prototype.copyWithin":"\nInt16Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Int16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2","Int16Array.prototype.entries":"\nInt16Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true","Int16Array.prototype.every":"\nInt16Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false","Int16Array.prototype.fill":"\nInt16Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Int16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3","Int16Array.prototype.filter":"\nInt16Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2","Int16Array.prototype.find":"\nInt16Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3","Int16Array.prototype.findIndex":"\nInt16Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2","Int16Array.prototype.forEach":"\nInt16Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '","Int16Array.prototype.includes":"\nInt16Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true","Int16Array.prototype.indexOf":"\nInt16Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2","Int16Array.prototype.join":"\nInt16Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'","Int16Array.prototype.keys":"\nInt16Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true","Int16Array.prototype.lastIndexOf":"\nInt16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3","Int16Array.prototype.map":"\nInt16Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Int16Array>[ 2, 4, 6 ]","Int16Array.prototype.reduce":"\nInt16Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14","Int16Array.prototype.reduceRight":"\nInt16Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14","Int16Array.prototype.reverse":"\nInt16Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Int16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] )\n    <Int16Array>\n    > arr.reverse()\n    <Int16Array>[ 3, 2, 1 ]","Int16Array.prototype.set":"\nInt16Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4","Int16Array.prototype.slice":"\nInt16Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3","Int16Array.prototype.some":"\nInt16Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true","Int16Array.prototype.sort":"\nInt16Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Int16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Int16Array>[ 0, 1, 1, 2, 2 ]","Int16Array.prototype.subarray":"\nInt16Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int16Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Int16Array>[ 3, 4, 5 ]","Int16Array.prototype.toLocaleString":"\nInt16Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'","Int16Array.prototype.toString":"\nInt16Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'","Int16Array.prototype.values":"\nInt16Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","INT32_MAX":"\nINT32_MAX\n    Maximum signed 32-bit integer.\n\n    The maximum signed 32-bit integer is given by `2^31 - 1`.\n\n    Examples\n    --------\n    > INT32_MAX\n    2147483647\n\n    See Also\n    --------\n    INT32_MIN\n","INT32_MIN":"\nINT32_MIN\n    Minimum signed 32-bit integer.\n\n    The minimum signed 32-bit integer is given by `-(2^31)`.\n\n    Examples\n    --------\n    > INT32_MIN\n    -2147483648\n\n    See Also\n    --------\n    INT32_MAX\n","INT32_NUM_BYTES":"\nINT32_NUM_BYTES\n    Size (in bytes) of a 32-bit signed integer.\n\n    Examples\n    --------\n    > INT32_NUM_BYTES\n    4\n\n    See Also\n    --------\n    INT16_NUM_BYTES, INT8_NUM_BYTES, UINT32_NUM_BYTES\n","Int32Array":"\nInt32Array()\n    A typed array constructor which returns a typed array representing an array\n    of twos-complement 32-bit signed integers in the platform byte order.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Int32Array()\n    <Int32Array>\n\n\nInt32Array( length )\n    Returns a typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( 5 )\n    <Int32Array>[ 0, 0, 0, 0, 0 ]\n\n\nInt32Array( typedarray )\n    Creates a typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int16Array( [ 5, 5, 5 ] );\n    > var arr2 = new Int32Array( arr1 )\n    <Int32Array>[ 5, 5, 5 ]\n\n\nInt32Array( obj )\n    Creates a typed array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a typed array.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 5.0, 5.0, 5.0 ];\n    > var arr2 = new Int32Array( arr1 )\n    <Int32Array>[ 5, 5, 5 ]\n\n\nInt32Array( buffer[, byteOffset[, length]] )\n    Returns a typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 16 );\n    > var arr = new Int32Array( buf, 0, 4 )\n    <Int32Array>[ 0, 0, 0, 0 ]\n\n\nInt32Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Int32Array.from( [ 1, 2 ], mapFcn )\n    <Int32Array>[ 2, 4 ]\n\n\nInt32Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Int32Array.of( 1, 2 )\n    <Int32Array>[ 1, 2 ]\n\n\nInt32Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Int32Array.BYTES_PER_ELEMENT\n    4\n\n\nInt32Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Int32Array.name\n    'Int32Array'\n\n\nInt32Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>\n\n\nInt32Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( 5 );\n    > arr.byteLength\n    20\n\n\nInt32Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Int32Array( 5 );\n    > arr.byteOffset\n    0\n\n\nInt32Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Int32Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    4\n\n\nInt32Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Int32Array( 5 );\n    > arr.length\n    5\n\n\nInt32Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Int32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2\n\n\nInt32Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true\n\n\nInt32Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false\n\n\nInt32Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Int32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3\n\n\nInt32Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2\n\n\nInt32Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3\n\n\nInt32Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2\n\n\nInt32Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '\n\n\nInt32Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true\n\n\nInt32Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2\n\n\nInt32Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'\n\n\nInt32Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true\n\n\nInt32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3\n\n\nInt32Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Int32Array>[ 2, 4, 6 ]\n\n\nInt32Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14\n\n\nInt32Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14\n\n\nInt32Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Int32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] )\n    <Int32Array>\n    > arr.reverse()\n    <Int32Array>[ 3, 2, 1 ]\n\n\nInt32Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4\n\n\nInt32Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3\n\n\nInt32Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true\n\n\nInt32Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Int32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Int32Array>[ 0, 1, 1, 2, 2 ]\n\n\nInt32Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int32Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Int32Array>[ 3, 4, 5 ]\n\n\nInt32Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'\n\n\nInt32Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'\n\n\nInt32Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Int32Array.from":"\nInt32Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Int32Array.from( [ 1, 2 ], mapFcn )\n    <Int32Array>[ 2, 4 ]","Int32Array.of":"\nInt32Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Int32Array.of( 1, 2 )\n    <Int32Array>[ 1, 2 ]","Int32Array.BYTES_PER_ELEMENT":"\nInt32Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Int32Array.BYTES_PER_ELEMENT\n    4","Int32Array.name":"\nInt32Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Int32Array.name\n    'Int32Array'","Int32Array.prototype.buffer":"\nInt32Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>","Int32Array.prototype.byteLength":"\nInt32Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( 5 );\n    > arr.byteLength\n    20","Int32Array.prototype.byteOffset":"\nInt32Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Int32Array( 5 );\n    > arr.byteOffset\n    0","Int32Array.prototype.BYTES_PER_ELEMENT":"\nInt32Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Int32Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    4","Int32Array.prototype.length":"\nInt32Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Int32Array( 5 );\n    > arr.length\n    5","Int32Array.prototype.copyWithin":"\nInt32Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Int32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2","Int32Array.prototype.entries":"\nInt32Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true","Int32Array.prototype.every":"\nInt32Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false","Int32Array.prototype.fill":"\nInt32Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Int32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3","Int32Array.prototype.filter":"\nInt32Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2","Int32Array.prototype.find":"\nInt32Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3","Int32Array.prototype.findIndex":"\nInt32Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2","Int32Array.prototype.forEach":"\nInt32Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '","Int32Array.prototype.includes":"\nInt32Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true","Int32Array.prototype.indexOf":"\nInt32Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2","Int32Array.prototype.join":"\nInt32Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'","Int32Array.prototype.keys":"\nInt32Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true","Int32Array.prototype.lastIndexOf":"\nInt32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3","Int32Array.prototype.map":"\nInt32Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Int32Array>[ 2, 4, 6 ]","Int32Array.prototype.reduce":"\nInt32Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14","Int32Array.prototype.reduceRight":"\nInt32Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14","Int32Array.prototype.reverse":"\nInt32Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Int32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] )\n    <Int32Array>\n    > arr.reverse()\n    <Int32Array>[ 3, 2, 1 ]","Int32Array.prototype.set":"\nInt32Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4","Int32Array.prototype.slice":"\nInt32Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3","Int32Array.prototype.some":"\nInt32Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true","Int32Array.prototype.sort":"\nInt32Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Int32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Int32Array>[ 0, 1, 1, 2, 2 ]","Int32Array.prototype.subarray":"\nInt32Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int32Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Int32Array>[ 3, 4, 5 ]","Int32Array.prototype.toLocaleString":"\nInt32Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'","Int32Array.prototype.toString":"\nInt32Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'","Int32Array.prototype.values":"\nInt32Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","IS_BIG_ENDIAN":"\nIS_BIG_ENDIAN\n    Boolean indicating if the environment is big endian.\n\n    Examples\n    --------\n    > IS_BIG_ENDIAN\n    <boolean>\n\n    See Also\n    --------\n    IS_LITTLE_ENDIAN\n","IS_BROWSER":"\nIS_BROWSER\n    Boolean indicating if the runtime is a web browser.\n\n    Examples\n    --------\n    > IS_BROWSER\n    <boolean>\n\n","IS_DARWIN":"\nIS_DARWIN\n    Boolean indicating if the current process is running on Darwin.\n\n    Examples\n    --------\n    > IS_DARWIN\n    <boolean>\n\n","IS_DOCKER":"\nIS_DOCKER\n    Boolean indicating if the process is running in a Docker container.\n\n    Examples\n    --------\n    > IS_DOCKER\n    <boolean>\n\n","IS_ELECTRON":"\nIS_ELECTRON\n    Boolean indicating if the runtime is Electron.\n\n    Examples\n    --------\n    > IS_ELECTRON\n    <boolean>\n\n    See Also\n    --------\n    IS_ELECTRON_MAIN, IS_ELECTRON_RENDERER\n","IS_ELECTRON_MAIN":"\nIS_ELECTRON_MAIN\n    Boolean indicating if the runtime is the main Electron process.\n\n    Examples\n    --------\n    > IS_ELECTRON_MAIN\n    <boolean>\n\n    See Also\n    --------\n    IS_ELECTRON, IS_ELECTRON_RENDERER\n","IS_ELECTRON_RENDERER":"\nIS_ELECTRON_RENDERER\n    Boolean indicating if the runtime is the Electron renderer process.\n\n    Examples\n    --------\n    > IS_ELECTRON_RENDERER\n    <boolean>\n\n    See Also\n    --------\n    IS_ELECTRON, IS_ELECTRON_MAIN\n","IS_LITTLE_ENDIAN":"\nIS_LITTLE_ENDIAN\n    Boolean indicating if the environment is little endian.\n\n    Examples\n    --------\n    > IS_LITTLE_ENDIAN\n    <boolean>\n\n    See Also\n    --------\n    IS_BIG_ENDIAN\n","IS_MOBILE":"\nIS_MOBILE\n    Boolean indicating if the current environment is a mobile device.\n\n    Examples\n    --------\n    > IS_MOBILE\n    <boolean>\n\n","IS_NODE":"\nIS_NODE\n    Boolean indicating if the runtime is Node.js.\n\n    Examples\n    --------\n    > IS_NODE\n    <boolean>\n\n","IS_TOUCH_DEVICE":"\nIS_TOUCH_DEVICE\n    Boolean indicating if the current environment is a touch device.\n\n    Examples\n    --------\n    > IS_TOUCH_DEVICE\n    <boolean>\n\n","IS_WEB_WORKER":"\nIS_WEB_WORKER\n    Boolean indicating if the runtime is a web worker.\n\n    Examples\n    --------\n    > IS_WEB_WORKER\n    <boolean>\n\n","IS_WINDOWS":"\nIS_WINDOWS\n    Boolean indicating if the current process is running on Windows.\n\n    Examples\n    --------\n    > IS_WINDOWS\n    <boolean>\n\n","isAbsoluteHttpURI":"\nisAbsoluteHttpURI( value )\n    Tests whether a value is an absolute HTTP(S) URI.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether a value is an absolute HTTP(S) URI.\n\n    Examples\n    --------\n    > var bool = isAbsoluteHttpURI( 'http://example.com/' )\n    true\n    > bool = isAbsoluteHttpURI( 'example.com' )\n    false\n    > bool = isAbsoluteHttpURI( 'foo@bar.com' )\n    false\n\n    See Also\n    --------\n    isAbsoluteURI","isAbsolutePath":"\nisAbsolutePath( value )\n    Tests if a value is an absolute path.\n\n    Function behavior is platform-specific. On Windows platforms, the function\n    is equal to `.win32()`. On POSIX platforms, the function is equal to\n    `.posix()`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is an absolute path.\n\n    Examples\n    --------\n    // Windows environment:\n    > var bool = isAbsolutePath( 'C:\\\\foo\\\\bar\\\\baz' )\n    true\n\n    // POSIX environment:\n    > bool = isAbsolutePath( '/foo/bar/baz' )\n    true\n\n\nisAbsolutePath.posix( value )\n    Tests if a value is a POSIX absolute path.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is a POSIX absolute path.\n\n    Examples\n    --------\n    > var bool = isAbsolutePath.posix( '/foo/bar/baz' )\n    true\n    > bool = isAbsolutePath.posix( 'foo/bar/baz' )\n    false\n\n\nisAbsolutePath.win32( value )\n    Tests if a value is a Windows absolute path.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is a Windows absolute path.\n\n    Examples\n    --------\n    > var bool = isAbsolutePath.win32( 'C:\\\\foo\\\\bar\\\\baz' )\n    true\n    > bool = isAbsolutePath.win32( 'foo\\\\bar\\\\baz' )\n    false\n\n    See Also\n    --------\n    isRelativePath\n","isAbsolutePath.posix":"\nisAbsolutePath.posix( value )\n    Tests if a value is a POSIX absolute path.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is a POSIX absolute path.\n\n    Examples\n    --------\n    > var bool = isAbsolutePath.posix( '/foo/bar/baz' )\n    true\n    > bool = isAbsolutePath.posix( 'foo/bar/baz' )\n    false","isAbsolutePath.win32":"\nisAbsolutePath.win32( value )\n    Tests if a value is a Windows absolute path.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is a Windows absolute path.\n\n    Examples\n    --------\n    > var bool = isAbsolutePath.win32( 'C:\\\\foo\\\\bar\\\\baz' )\n    true\n    > bool = isAbsolutePath.win32( 'foo\\\\bar\\\\baz' )\n    false\n\n    See Also\n    --------\n    isRelativePath","isAbsoluteURI":"\nisAbsoluteURI( value )\n    Tests whether a value is an absolute URI.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether a value is an absolute URI.\n\n    Examples\n    --------\n    > var bool = isAbsoluteURI( 'http://example.com/' )\n    true\n    > bool = isAbsoluteURI( 'example.com' )\n    false\n    > bool = isAbsoluteURI( 'foo@bar.com' )\n    false\n\n    See Also\n    --------\n    isRelativeURI","isAccessorArray":"\nisAccessorArray( value )\n    Tests if a value is an array-like object supporting the accessor (get/set)\n    protocol.\n\n    An accessor array is defined as an array, typed array, or an array-like\n    object (excluding strings and functions) having `get` and `set` methods for\n    accessing array elements.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an accessor array.\n\n    Examples\n    --------\n    > var bool = isAccessorArray( new Complex64Array( 10 ) )\n    true\n    > bool = isAccessorArray( [] )\n    false\n    > bool = isAccessorArray( { 'length': 0 } )\n    false\n    > bool = isAccessorArray( {} )\n    false\n\n    See Also\n    --------\n    isArrayLike, isArrayLikeObject, isCollection\n","isAccessorProperty":"\nisAccessorProperty( value, property )\n    Tests if an object's own property has an accessor descriptor.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own property has an accessor\n        descriptor.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.get = function getter() { return 'beep'; };\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isAccessorProperty( obj, 'boop' )\n    false\n    > bool = isAccessorProperty( obj, 'beep' )\n    true\n\n    See Also\n    --------\n    hasOwnProp, isAccessorPropertyIn, isDataProperty\n","isAccessorPropertyIn":"\nisAccessorPropertyIn( value, property )\n    Tests if an object's own or inherited property has an accessor descriptor.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own or inherited property has an\n        accessor descriptor.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.get = function getter() { return 'beep'; };\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isAccessorPropertyIn( obj, 'boop' )\n    false\n    > bool = isAccessorPropertyIn( obj, 'beep' )\n    true\n\n    See Also\n    --------\n    hasProp, isAccessorProperty, isDataPropertyIn\n","isAlphagram":"\nisAlphagram( value )\n    Tests if a value is an alphagram (i.e., a sequence of characters arranged in\n    alphabetical order).\n\n    The function first checks that an input value is a string before validating\n    that the value is an alphagram. For non-string values, the function returns\n    `false`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an alphagram.\n\n    Examples\n    --------\n    > var out = isAlphagram( 'beep' )\n    true\n    > out = isAlphagram( 'zba' )\n    false\n    > out = isAlphagram( '' )\n    false\n\n    See Also\n    --------\n    isAnagram\n","isAlphaNumeric":"\nisAlphaNumeric( str )\n    Tests whether a string contains only alphanumeric characters.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a string contains only alphanumeric\n        characters.\n\n    Examples\n    --------\n    > var bool = isAlphaNumeric( 'abc0123456789' )\n    true\n    > bool = isAlphaNumeric( 'abcdef' )\n    true\n    > bool = isAlphaNumeric( '0xff' )\n    true\n    > bool = isAlphaNumeric( '' )\n    false\n\n    See Also\n    --------\n    isDigitString\n","isAnagram":"\nisAnagram( str, value )\n    Tests if a value is an anagram.\n\n    Parameters\n    ----------\n    str: string\n        Comparison string.\n\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an anagram.\n\n    Examples\n    --------\n    > var str1 = 'I am a weakish speller';\n    > var str2 = 'William Shakespeare';\n    > var bool = isAnagram( str1, str2 )\n    true\n    > bool = isAnagram( 'bat', 'tabba' )\n    false\n\n    See Also\n    --------\n    isAlphagram\n","isArguments":"\nisArguments( value )\n    Tests if a value is an arguments object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an arguments object.\n\n    Examples\n    --------\n    > function foo() { return arguments; };\n    > var bool = isArguments( foo() )\n    true\n    > bool = isArguments( [] )\n    false\n\n","isArray":"\nisArray( value )\n    Tests if a value is an array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array.\n\n    Examples\n    --------\n    > var bool = isArray( [] )\n    true\n    > bool = isArray( {} )\n    false\n\n    See Also\n    --------\n    isArrayLike\n","isArrayArray":"\nisArrayArray( value )\n    Tests if a value is an array of arrays.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array of arrays.\n\n    Examples\n    --------\n    > var bool = isArrayArray( [ [], [] ] )\n    true\n    > bool = isArrayArray( [ {}, {} ] )\n    false\n    > bool = isArrayArray( [] )\n    false\n\n","isArrayBuffer":"\nisArrayBuffer( value )\n    Tests if a value is an ArrayBuffer.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an ArrayBuffer.\n\n    Examples\n    --------\n    > var bool = isArrayBuffer( new ArrayBuffer( 10 ) )\n    true\n    > bool = isArrayBuffer( [] )\n    false\n\n    See Also\n    --------\n    isSharedArrayBuffer, isTypedArray\n","isArrayBufferView":"\nisArrayBufferView( value )\n    Tests if a value is a `ArrayBuffer` view.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a `ArrayBuffer` view.\n\n    Examples\n    --------\n    > var bool = isArrayBufferView( new Int8Array() )\n    true\n    > bool = isArrayBufferView( [] )\n    false\n\n    See Also\n    --------\n    isDataView, isTypedArray\n","isArrayLength":"\nisArrayLength( value )\n    Tests if a value is a valid array length.\n\n    A valid length property for an Array instance is any integer value on the\n    interval [0, 2^32-1].\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a valid array length.\n\n    Examples\n    --------\n    > var bool = isArrayLength( 5 )\n    true\n    > bool = isArrayLength( 2.0e200 )\n    false\n    > bool = isArrayLength( -3.14 )\n    false\n    > bool = isArrayLength( null )\n    false\n\n    See Also\n    --------\n    isArray\n","isArrayLike":"\nisArrayLike( value )\n    Tests if a value is array-like.\n\n    If provided a string, the function returns `true`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is array-like.\n\n    Examples\n    --------\n    > var bool = isArrayLike( [] )\n    true\n    > bool = isArrayLike( { 'length': 10 } )\n    true\n    > bool = isArrayLike( 'beep' )\n    true\n    > bool = isArrayLike( null )\n    false\n\n    See Also\n    --------\n    isArray, isArrayLikeObject, isCollection\n","isArrayLikeObject":"\nisArrayLikeObject( value )\n    Tests if a value is an array-like object.\n\n    If provided a string, the function returns `false`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object.\n\n    Examples\n    --------\n    > var bool = isArrayLikeObject( [] )\n    true\n    > bool = isArrayLikeObject( { 'length': 10 } )\n    true\n    > bool = isArrayLikeObject( 'beep' )\n    false\n\n    See Also\n    --------\n    isArray, isArrayLike, isCollection\n","isArrowFunction":"\nisArrowFunction( value )\n    Tests if a value is an arrow function.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an arrow function.\n\n    Examples\n    --------\n    > function beep() {};\n    > var bool = isArrowFunction( beep )\n    false\n    > bool = isArrowFunction( {} )\n    false\n\n","isASCII":"\nisASCII( str )\n    Tests whether a character belongs to the ASCII character set and whether\n    this is true for all characters in a provided string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a string has all ASCII characters.\n\n    Examples\n    --------\n    > var str = 'beep boop';\n    > var bool = isASCII( str )\n    true\n    > bool = isASCII( fromCodePoint( 130 ) )\n    false\n\n    See Also\n    --------\n    isString\n","isBetween":"\nisBetween( value, a, b[, left, right] )\n    Tests if a value is between two values.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    a: any\n        Left comparison value.\n\n    b: any\n        Right comparison value.\n\n    left: string (optional)\n        Indicates whether the left comparison value is inclusive. Must be either\n        'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n    right: string (optional)\n        Indicates whether the right comparison value is inclusive. Must be\n        either 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is between two values.\n\n    Examples\n    --------\n    > var bool = isBetween( 3.14, 3.0, 4.0 )\n    true\n    > bool = isBetween( 3.0, 3.0, 4.0 )\n    true\n    > bool = isBetween( 4.0, 3.0, 4.0 )\n    true\n    > bool = isBetween( 3.0, 3.14, 4.0 )\n    false\n    > bool = isBetween( 3.14, 3.14, 4.0, 'open', 'closed' )\n    false\n    > bool = isBetween( 3.14, 3.0, 3.14, 'closed', 'open' )\n    false\n\n    See Also\n    --------\n    isBetweenArray\n","isBetweenArray":"\nisBetweenArray( value, a, b[, left, right] )\n    Tests if a value is an array-like object where every element is between two\n    values.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    a: any\n        Left comparison value.\n\n    b: any\n        Right comparison value.\n\n    left: string (optional)\n        Indicates whether the left comparison value is inclusive. Must be either\n        'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n    right: string (optional)\n        Indicates whether the right comparison value is inclusive. Must be\n        either 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object where every\n        element is between two values.\n\n    Examples\n    --------\n    > var arr = [ 3.0, 3.14, 4.0 ];\n    > var bool = isBetweenArray( arr, 3.0, 4.0 )\n    true\n    > bool = isBetweenArray( arr, 3.14, 4.0 )\n    false\n    > bool = isBetweenArray( arr, 3.0, 3.14 )\n    false\n    > bool = isBetweenArray( arr, 3.0, 4.0, 'open', 'closed' )\n    false\n    > bool = isBetweenArray( arr, 3.0, 4.0, 'closed', 'open' )\n    false\n\n    See Also\n    --------\n    isBetween\n","isBigInt":"\nisBigInt( value )\n    Tests if a value is a BigInt.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a BigInt.\n\n    Examples\n    --------\n    > var bool = isBigInt( BigInt( '1' ) )\n    true\n    > bool = isBigInt( Object( BigInt( '1' ) ) )\n    true\n    > bool = isBigInt( {} )\n    false\n    > bool = isBigInt( null )\n    false\n    > bool = isBigInt( true )\n    false\n\n","isBigInt64Array":"\nisBigInt64Array( value )\n    Tests if a value is a BigInt64Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a BigInt64Array.\n\n    Examples\n    --------\n    > var bool = isBigInt64Array( new BigInt64Array( 10 ) )\n    true\n    > bool = isBigInt64Array( [] )\n    false\n\n    See Also\n    --------\n    isBigUint64Array\n","isBigUint64Array":"\nisBigUint64Array( value )\n    Tests if a value is a BigUint64Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a BigUint64Array.\n\n    Examples\n    --------\n    > var bool = isBigUint64Array( new BigUint64Array( 10 ) )\n    true\n    > bool = isBigUint64Array( [] )\n    false\n\n    See Also\n    --------\n    isBigInt64Array\n","isBinaryString":"\nisBinaryString( value )\n    Tests if a value is a binary string.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a binary string.\n\n    Examples\n    --------\n    > var bool = isBinaryString( '1000101' )\n    true\n    > bool = isBinaryString( 'beep' )\n    false\n    > bool = isBinaryString( '' )\n    false\n\n    See Also\n    --------\n    isString\n","isBlankString":"\nisBlankString( value )\n    Tests if a value is a blank string (i.e., an empty string or a string\n    consisting only of whitespace characters).\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a blank string.\n\n    Examples\n    --------\n    > var bool = isBlankString( '   ' )\n    true\n    > bool = isBlankString( 'beep' )\n    false\n    > bool = isBlankString( null )\n    false\n\n    See Also\n    --------\n    isString, isEmptyString\n","isBoolean":"\nisBoolean( value )\n    Tests if a value is a boolean.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a boolean.\n\n    Examples\n    --------\n    > var bool = isBoolean( false )\n    true\n    > bool = isBoolean( new Boolean( false ) )\n    true\n\n\nisBoolean.isPrimitive( value )\n    Tests if a value is a boolean primitive.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a boolean primitive.\n\n    Examples\n    --------\n    > var bool = isBoolean.isPrimitive( true )\n    true\n    > bool = isBoolean.isPrimitive( false )\n    true\n    > bool = isBoolean.isPrimitive( new Boolean( true ) )\n    false\n\n\nisBoolean.isObject( value )\n    Tests if a value is a boolean object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a boolean object.\n\n    Examples\n    --------\n    > var bool = isBoolean.isObject( true )\n    false\n    > bool = isBoolean.isObject( new Boolean( false ) )\n    true\n\n","isBoolean.isPrimitive":"\nisBoolean.isPrimitive( value )\n    Tests if a value is a boolean primitive.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a boolean primitive.\n\n    Examples\n    --------\n    > var bool = isBoolean.isPrimitive( true )\n    true\n    > bool = isBoolean.isPrimitive( false )\n    true\n    > bool = isBoolean.isPrimitive( new Boolean( true ) )\n    false","isBoolean.isObject":"\nisBoolean.isObject( value )\n    Tests if a value is a boolean object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a boolean object.\n\n    Examples\n    --------\n    > var bool = isBoolean.isObject( true )\n    false\n    > bool = isBoolean.isObject( new Boolean( false ) )\n    true","isBooleanArray":"\nisBooleanArray( value )\n    Tests if a value is an array-like object of booleans.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object of booleans.\n\n    Examples\n    --------\n    > var bool = isBooleanArray( [ true, false, true ] )\n    true\n    > bool = isBooleanArray( [ true, 'abc', false ] )\n    false\n\n\nisBooleanArray.primitives( value )\n    Tests if a value is an array-like object containing only boolean primitives.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        boolean primitives.\n\n    Examples\n    --------\n    > var bool = isBooleanArray.primitives( [ true, false ] )\n    true\n    > bool = isBooleanArray.primitives( [ false, new Boolean( true ) ] )\n    false\n\n\nisBooleanArray.objects( value )\n    Tests if a value is an array-like object containing only Boolean objects.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        Boolean objects.\n\n    Examples\n    --------\n    > var bool = isBooleanArray.objects( [ new Boolean( false ), true ] )\n    false\n    > bool = isBooleanArray.objects( [ new Boolean( false ), new Boolean( true ) ] )\n    true\n\n","isBooleanArray.primitives":"\nisBooleanArray.primitives( value )\n    Tests if a value is an array-like object containing only boolean primitives.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        boolean primitives.\n\n    Examples\n    --------\n    > var bool = isBooleanArray.primitives( [ true, false ] )\n    true\n    > bool = isBooleanArray.primitives( [ false, new Boolean( true ) ] )\n    false","isBooleanArray.objects":"\nisBooleanArray.objects( value )\n    Tests if a value is an array-like object containing only Boolean objects.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        Boolean objects.\n\n    Examples\n    --------\n    > var bool = isBooleanArray.objects( [ new Boolean( false ), true ] )\n    false\n    > bool = isBooleanArray.objects( [ new Boolean( false ), new Boolean( true ) ] )\n    true","isBoxedPrimitive":"\nisBoxedPrimitive( value )\n    Tests if a value is a JavaScript boxed primitive.\n\n    Boxed primitive objects can be created with one of the following:\n\n    - new Boolean()\n    - new Number()\n    - new String()\n    - Object( Symbol() ) (ES6/ES2015)\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a JavaScript boxed primitive.\n\n    Examples\n    --------\n    > var bool = isBoxedPrimitive( new Boolean( false ) )\n    true\n    > bool = isBoxedPrimitive( true )\n    false\n\n    See Also\n    --------\n    isPrimitive\n","isBuffer":"\nisBuffer( value )\n    Tests if a value is a Buffer instance.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Buffer instance.\n\n    Examples\n    --------\n    > var bool = isBuffer( new Buffer( 'beep' ) )\n    true\n    > bool = isBuffer( new Buffer( [ 1, 2, 3, 4 ] ) )\n    true\n    > bool = isBuffer( {} )\n    false\n    > bool = isBuffer( [] )\n    false\n\n","isCamelcase":"\nisCamelcase( value )\n    Tests if a value is a camelcase string.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a camelcase string.\n\n    Examples\n    --------\n    > var bool = isCamelcase( 'helloWorld' )\n    true\n    > bool = isCamelcase( 'hello world' )\n    false\n\n    See Also\n    --------\n    isString, isConstantcase","isCapitalized":"\nisCapitalized( value )\n    Tests if a value is a string having an uppercase first character.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a string with an uppercase first\n        character.\n\n    Examples\n    --------\n    > var bool = isCapitalized( 'Hello' )\n    true\n    > bool = isCapitalized( 'world' )\n    false\n\n    See Also\n    --------\n    isString\n","isCentrosymmetricMatrix":"\nisCentrosymmetricMatrix( value )\n    Tests if a value is a matrix which is symmetric about its center.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a centrosymmetric matrix.\n\n    Examples\n    --------\n    > var buf = [ 2, 1, 1, 2 ];\n    > var M = ndarray( 'generic', buf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n    > var bool = isCentrosymmetricMatrix( M )\n    true\n    > bool = isCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isCentrosymmetricMatrix( 3.14 )\n    false\n    > bool = isCentrosymmetricMatrix( {} )\n    false\n\n    See Also\n    --------\n    isMatrixLike, isSquareMatrix, isSymmetricMatrix\n","isCircular":"\nisCircular( value )\n    Tests if an object-like value contains a circular reference.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an object-like value contains a circular\n        reference.\n\n    Examples\n    --------\n    > var obj = { 'beep': 'boop' };\n    > obj.self = obj;\n    > var bool = isCircular( obj )\n    true\n    > bool = isCircular( {} )\n    false\n    > bool = isCircular( null )\n    false\n\n    See Also\n    --------\n    isCircularArray, isCircularPlainObject\n","isCircularArray":"\nisCircularArray( value )\n    Tests if a value is an array containing a circular reference.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array containing a\n        circular reference.\n\n    Examples\n    --------\n    > var arr = [ 1, 2, 3 ];\n    > arr.push( arr );\n    > var bool = isCircularArray( arr )\n    true\n    > bool = isCircularArray( [] )\n    false\n    > bool = isCircularArray( null )\n    false\n\n    See Also\n    --------\n    isCircular, isCircularPlainObject\n","isCircularPlainObject":"\nisCircularPlainObject( value )\n    Tests if a value is a plain object containing a circular reference.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a plain object containing a\n        circular reference.\n\n    Examples\n    --------\n    > var obj = { 'beep': 'boop' };\n    > obj.self = obj;\n    > var bool = isCircularPlainObject( obj )\n    true\n    > bool = isCircularPlainObject( {} )\n    false\n    > bool = isCircularPlainObject( null )\n    false\n\n    See Also\n    --------\n    isCircular, isCircularArray\n","isClass":"\nisClass( value )\n    Tests if a value is a class.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a class.\n\n    Examples\n    --------\n    > var bool = isClass( class Person {} )\n    true\n    > bool = isClass( function Person() {} )\n    false\n    > bool = isClass( {} )\n    false\n    > bool = isClass( null )\n    false\n    > bool = isClass( true )\n    false\n","isCollection":"\nisCollection( value )\n    Tests if a value is a collection.\n\n    A collection is defined as an array, typed array, or an array-like object\n    (excluding strings and functions).\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a collection.\n\n    Examples\n    --------\n    > var bool = isCollection( [] )\n    true\n    > bool = isCollection( { 'length': 0 } )\n    true\n    > bool = isCollection( {} )\n    false\n\n    See Also\n    --------\n    isArrayLike, isArrayLikeObject\n","isComplex":"\nisComplex( value )\n    Tests if a value is a 64-bit or 128-bit complex number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 64-bit or 128-bit complex\n        number.\n\n    Examples\n    --------\n    > var bool = isComplex( new Complex64( 2.0, 2.0 ) )\n    true\n    > bool = isComplex( new Complex128( 3.0, 1.0 ) )\n    true\n    > bool = isComplex( 3.14 )\n    false\n    > bool = isComplex( {} )\n    false\n\n    See Also\n    --------\n    isComplex64, isComplex128\n","isComplex64":"\nisComplex64( value )\n    Tests if a value is a 64-bit complex number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 64-bit complex number.\n\n    Examples\n    --------\n    > var bool = isComplex64( new Complex64( 2.0, 2.0 ) )\n    true\n    > bool = isComplex64( new Complex128( 3.0, 1.0 ) )\n    false\n    > bool = isComplex64( 3.14 )\n    false\n    > bool = isComplex64( {} )\n    false\n\n    See Also\n    --------\n    isComplex, isComplex128\n","isComplex64Array":"\nisComplex64Array( value )\n    Tests if a value is a Complex64Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Complex64Array.\n\n    Examples\n    --------\n    > var bool = isComplex64Array( new Complex64Array( 10 ) )\n    true\n    > bool = isComplex64Array( [] )\n    false\n\n    See Also\n    --------\n    isComplex, isComplex64, isComplex128Array, isComplexTypedArray\n","isComplex64MatrixLike":"\nisComplex64MatrixLike( value )\n    Tests if a value is a 2-dimensional ndarray-like object containing single-\n    precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 2-dimensional ndarray-like\n        object containing single-precision complex floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n    > M.ndims = 2;\n    > M.shape = [ 2, 2 ];\n    > M.strides = [ 2, 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'complex64';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isComplex64MatrixLike( M )\n    true\n    > bool = isComplex64MatrixLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isComplex64MatrixLike( 3.14 )\n    false\n    > bool = isComplex64MatrixLike( {} )\n    false\n\n    See Also\n    --------\n    isComplex128MatrixLike, isndarrayLike, isMatrixLike\n","isComplex64ndarrayLike":"\nisComplex64ndarrayLike( value )\n    Tests if a value is an ndarray-like object containing single-precision\n    complex floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an ndarray-like object containing\n        single-precision complex floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n    > M.ndims = 2;\n    > M.shape = [ 2, 2 ];\n    > M.strides = [ 2, 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'complex64';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isComplex64ndarrayLike( M )\n    true\n    > bool = isComplex64ndarrayLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isComplex64ndarrayLike( 3.14 )\n    false\n    > bool = isComplex64ndarrayLike( {} )\n    false\n\n    See Also\n    --------\n    isComplex128ndarrayLike, isndarrayLike\n","isComplex64VectorLike":"\nisComplex64VectorLike( value )\n    Tests if a value is a 1-dimensional ndarray-like object containing single-\n    precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 1-dimensional ndarray-like\n        object containing single-precision complex floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n    > M.ndims = 1;\n    > M.shape = [ 4 ];\n    > M.strides = [ 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'complex64';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isComplex64VectorLike( M )\n    true\n    > bool = isComplex64VectorLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isComplex64VectorLike( 3.14 )\n    false\n    > bool = isComplex64VectorLike( {} )\n    false\n\n    See Also\n    --------\n    isComplex128VectorLike, isndarrayLike, isVectorLike\n","isComplex128":"\nisComplex128( value )\n    Tests if a value is a 128-bit complex number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 128-bit complex number.\n\n    Examples\n    --------\n    > var bool = isComplex128( new Complex128( 3.0, 1.0 ) )\n    true\n    > bool = isComplex128( new Complex64( 2.0, 2.0 ) )\n    false\n    > bool = isComplex128( 3.14 )\n    false\n    > bool = isComplex128( {} )\n    false\n\n    See Also\n    --------\n    isComplex, isComplex64\n","isComplex128Array":"\nisComplex128Array( value )\n    Tests if a value is a Complex128Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Complex128Array.\n\n    Examples\n    --------\n    > var bool = isComplex128Array( new Complex128Array( 10 ) )\n    true\n    > bool = isComplex128Array( [] )\n    false\n\n    See Also\n    --------\n    isComplex, isComplex128, isComplex64Array, isComplexTypedArray\n","isComplex128MatrixLike":"\nisComplex128MatrixLike( value )\n    Tests if a value is a 2-dimensional ndarray-like object containing double-\n    precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 2-dimensional ndarray-like\n        object containing double-precision complex floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n    > M.ndims = 2;\n    > M.shape = [ 2, 2 ];\n    > M.strides = [ 2, 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'complex128';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isComplex128MatrixLike( M )\n    true\n    > bool = isComplex128MatrixLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isComplex128MatrixLike( 3.14 )\n    false\n    > bool = isComplex128MatrixLike( {} )\n    false\n\n    See Also\n    --------\n    isComplex64MatrixLike, isndarrayLike, isMatrixLike\n","isComplex128ndarrayLike":"\nisComplex128ndarrayLike( value )\n    Tests if a value is an ndarray-like object containing double-precision\n    complex floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an ndarray-like object containing\n        double-precision complex floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n    > M.ndims = 2;\n    > M.shape = [ 2, 2 ];\n    > M.strides = [ 2, 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'complex128';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isComplex128ndarrayLike( M )\n    true\n    > bool = isComplex128ndarrayLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isComplex128ndarrayLike( 3.14 )\n    false\n    > bool = isComplex128ndarrayLike( {} )\n    false\n\n    See Also\n    --------\n    isComplex64ndarrayLike, isndarrayLike\n","isComplex128VectorLike":"\nisComplex128VectorLike( value )\n    Tests if a value is a 1-dimensional ndarray-like object containing double-\n    precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 1-dimensional ndarray-like\n        object containing double-precision complex floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n    > M.ndims = 1;\n    > M.shape = [ 4 ];\n    > M.strides = [ 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'complex128';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isComplex128VectorLike( M )\n    true\n    > bool = isComplex128VectorLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isComplex128VectorLike( 3.14 )\n    false\n    > bool = isComplex128VectorLike( {} )\n    false\n\n    See Also\n    --------\n    isComplex64VectorLike, isndarrayLike, isVectorLike\n","isComplexLike":"\nisComplexLike( value )\n    Tests if a value is a complex number-like object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a complex number-like object.\n\n    Examples\n    --------\n    > var bool = isComplexLike( new Complex64( 2.0, 2.0 ) )\n    true\n    > bool = isComplexLike( new Complex128( 3.0, 1.0 ) )\n    true\n    > bool = isComplexLike( 3.14 )\n    false\n    > bool = isComplexLike( {} )\n    false\n\n    See Also\n    --------\n    isComplex, isComplex64, isComplex128\n","isComplexTypedArray":"\nisComplexTypedArray( value )\n    Tests if a value is a complex typed array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a complex typed array.\n\n    Examples\n    --------\n    > var bool = isComplexTypedArray( new Complex64Array( 10 ) )\n    true\n\n    See Also\n    --------\n    isComplex, isComplex64Array, isComplex128Array\n","isComplexTypedArrayLike":"\nisComplexTypedArrayLike( value )\n    Tests if a value is complex-typed-array-like.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is complex-typed-array-like.\n\n    Examples\n    --------\n    > var bool = isComplexTypedArrayLike( new Complex128Array() )\n    true\n    > bool = isComplexTypedArrayLike({\n    ...    'length': 10,\n    ...    'byteOffset': 0,\n    ...    'byteLength': 10,\n    ...    'BYTES_PER_ELEMENT': 4,\n    ...    'get': function get() {},\n    ...    'set': function set() {}\n    ... })\n    true\n\n    See Also\n    --------\n    isComplexLike, isComplexTypedArray, isComplex64Array, isComplex128Array\n","isComposite":"\nisComposite( value )\n    Tests if a value is a composite number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a composite number.\n\n    Examples\n    --------\n    > var bool = isComposite( 4.0 )\n    true\n    > bool = isComposite( new Number( 4.0 ) )\n    true\n    > bool = isComposite( 3.14 )\n    false\n    > bool = isComposite( -4.0 )\n    false\n    > bool = isComposite( null )\n    false\n\n\nisComposite.isPrimitive( value )\n    Tests if a value is a number primitive which is a composite number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a\n        composite number.\n\n    Examples\n    --------\n    > var bool = isComposite.isPrimitive( 4.0 )\n    true\n    > bool = isComposite.isPrimitive( new Number( 4.0 ) )\n    false\n\n\nisComposite.isObject( value )\n    Tests if a value is a number object having a value which is a composite\n    number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a composite number.\n\n    Examples\n    --------\n    > var bool = isComposite.isObject( 4.0 )\n    false\n    > bool = isComposite.isObject( new Number( 4.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger, isNumber, isPrime\n","isComposite.isPrimitive":"\nisComposite.isPrimitive( value )\n    Tests if a value is a number primitive which is a composite number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a\n        composite number.\n\n    Examples\n    --------\n    > var bool = isComposite.isPrimitive( 4.0 )\n    true\n    > bool = isComposite.isPrimitive( new Number( 4.0 ) )\n    false","isComposite.isObject":"\nisComposite.isObject( value )\n    Tests if a value is a number object having a value which is a composite\n    number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a composite number.\n\n    Examples\n    --------\n    > var bool = isComposite.isObject( 4.0 )\n    false\n    > bool = isComposite.isObject( new Number( 4.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger, isNumber, isPrime","isConfigurableProperty":"\nisConfigurableProperty( value, property )\n    Tests if an object's own property is configurable.\n\n    A property is configurable if the property may be deleted or its descriptor\n    may be changed.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own property is configurable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = true;\n    > desc.writable = true;\n    > desc.value = true;\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isConfigurableProperty( obj, 'boop' )\n    true\n    > bool = isConfigurableProperty( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    isConfigurablePropertyIn, isEnumerableProperty, isReadableProperty, isWritableProperty\n","isConfigurablePropertyIn":"\nisConfigurablePropertyIn( value, property )\n    Tests if an object's own or inherited property is configurable.\n\n    A property is configurable if the property may be deleted or its descriptor\n    may be changed.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own or inherited property is\n        configurable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = true;\n    > desc.writable = true;\n    > desc.value = true;\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isConfigurablePropertyIn( obj, 'boop' )\n    true\n    > bool = isConfigurablePropertyIn( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    isConfigurableProperty, isEnumerablePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isConstantcase":"\nisConstantcase( value )\n    Tests if a value is a constantcase string.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a constantcase string.\n\n    Examples\n    --------\n    > var bool = isConstantcase( 'BEEP_BOOP' )\n    true\n    > bool = isConstantcase( 'BEEP and BOOP' )\n    false\n\n    See Also\n    --------\n    isString, isCamelcase","isCubeNumber":"\nisCubeNumber( value )\n    Tests if a value is a cube number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a cube number.\n\n    Examples\n    --------\n    > var bool = isCubeNumber( 8.0 )\n    true\n    > bool = isCubeNumber( new Number( 8.0 ) )\n    true\n    > bool = isCubeNumber( 3.14 )\n    false\n    > bool = isCubeNumber( -5.0 )\n    false\n    > bool = isCubeNumber( null )\n    false\n\n\nisCubeNumber.isPrimitive( value )\n    Tests if a value is a number primitive which is a cube number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a cube\n        number.\n\n    Examples\n    --------\n    > var bool = isCubeNumber.isPrimitive( 8.0 )\n    true\n    > bool = isCubeNumber.isPrimitive( new Number( 8.0 ) )\n    false\n\n\nisCubeNumber.isObject( value )\n    Tests if a value is a number object having a value which is a cube number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a cube number.\n\n    Examples\n    --------\n    > var bool = isCubeNumber.isObject( 8.0 )\n    false\n    > bool = isCubeNumber.isObject( new Number( 8.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger, isNumber, isSquareNumber\n","isCubeNumber.isPrimitive":"\nisCubeNumber.isPrimitive( value )\n    Tests if a value is a number primitive which is a cube number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a cube\n        number.\n\n    Examples\n    --------\n    > var bool = isCubeNumber.isPrimitive( 8.0 )\n    true\n    > bool = isCubeNumber.isPrimitive( new Number( 8.0 ) )\n    false","isCubeNumber.isObject":"\nisCubeNumber.isObject( value )\n    Tests if a value is a number object having a value which is a cube number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a cube number.\n\n    Examples\n    --------\n    > var bool = isCubeNumber.isObject( 8.0 )\n    false\n    > bool = isCubeNumber.isObject( new Number( 8.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger, isNumber, isSquareNumber","isCurrentYear":"\nisCurrentYear( value )\n    Tests if a value is the current year.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether a value is the current year.\n\n    Examples\n    --------\n    > var bool = isCurrentYear( new Date() )\n    true\n    > bool = isCurrentYear( currentYear() )\n    true\n    > bool = isCurrentYear( 2021 )\n    false\n    > bool = isCurrentYear( null )\n    false\n\n","isDataProperty":"\nisDataProperty( value, property )\n    Tests if an object's own property has a data descriptor.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own property has a data descriptor.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.get = function getter() { return 'beep'; };\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isDataProperty( obj, 'boop' )\n    true\n    > bool = isDataProperty( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    hasOwnProp, isAccessorProperty, isDataPropertyIn\n","isDataPropertyIn":"\nisDataPropertyIn( value, property )\n    Tests if an object's own or inherited property has a data descriptor.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own or inherited property has a data\n        descriptor.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.get = function getter() { return 'beep'; };\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isDataPropertyIn( obj, 'boop' )\n    true\n    > bool = isDataPropertyIn( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    hasProp, isAccessorPropertyIn, isDataProperty\n","isDataView":"\nisDataView( value )\n    Tests if a value is a DataView.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a DataView.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 10 );\n    > var bool = isDataView( new DataView( buf ) )\n    true\n    > bool = isDataView( [] )\n    false\n\n    See Also\n    --------\n    isArrayBuffer, isTypedArray\n","isDateObject":"\nisDateObject( value )\n    Tests if a value is a Date object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Date object.\n\n    Examples\n    --------\n    > var bool = isDateObject( new Date() )\n    true\n    > bool = isDateObject( '2017-01-01' )\n    false\n\n","isDateObjectArray":"\nisDateObjectArray( value )\n    Tests if a value is an array-like object containing only Date objects.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if value is an array-like object containing only Date\n        objects.\n\n    Examples\n    --------\n    > var bool = isDateObjectArray( [ new Date(), new Date() ] )\n    true\n    > bool = isDateObjectArray( [ {}, {} ] )\n    false\n    > bool = isDateObjectArray( [ new Date(), '2011-01-01' ] )\n    false\n    > bool = isDateObjectArray( [] )\n    false\n\n    See Also\n    --------\n    isDateObject\n","isDigitString":"\nisDigitString( str )\n    Tests whether a string contains only numeric digits.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a string contains only numeric digits.\n\n    Examples\n    --------\n    > var bool = isDigitString( '0123456789' )\n    true\n    > bool = isDigitString( 'abcdef' )\n    false\n    > bool = isDigitString( '0xff' )\n    false\n    > bool = isDigitString( '' )\n    false\n\n    See Also\n    --------\n    isHexString, isString\n","isDomainName":"\nisDomainName( value )\n    Tests if a value is a domain name.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a domain name.\n\n    Examples\n    --------\n    > var bool = isDomainName( 'example.com' )\n    true\n    > bool = isDomainName( 'foo@bar.com' )\n    false\n","isDurationString":"\nisDurationString( value )\n    Tests if a value is a duration string.\n\n    The function validates that a value is a string. For all other types, the\n    function returns `false`.\n\n    A duration string is a string containing a sequence of time units. A time\n    unit is a non-negative integer followed by a unit identifier. The following\n    unit identifiers are supported:\n\n    - d: days.\n    - h: hours.\n    - m: minutes.\n    - s: seconds.\n    - ms: milliseconds.\n\n    For example, the string `1m3s10ms` is a duration string containing three\n    time units: `1m` (1 minute), `3s` (3 seconds), and `10ms` (10 milliseconds).\n    The string `60m` is a duration string containing a single time unit: `60m`\n    (60 minutes). Time units must be supplied in descending order of magnitude\n    (i.e., days, hours, minutes, seconds, milliseconds).\n\n    Duration strings are case insensitive. For example, the string `1M3S10MS` is\n    equivalent to `1m3s10ms`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a duration string.\n\n    Examples\n    --------\n    > var bool = isDurationString( '1d' )\n    true\n    > bool = isDurationString( '1h' )\n    true\n    > bool = isDurationString( 'beep' )\n    false\n","isEmailAddress":"\nisEmailAddress( value )\n    Tests if a value is an email address.\n\n    Validation is not rigorous. *9* RFCs relate to email addresses, and\n    accounting for all of them is a fool's errand. The function performs the\n    simplest validation; i.e., requiring at least one `@` symbol.\n\n    For rigorous validation, send a confirmation email. If the email bounces,\n    consider the email invalid.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an email address.\n\n    Examples\n    --------\n    > var bool = isEmailAddress( 'beep@boop.com' )\n    true\n    > bool = isEmailAddress( 'beep' )\n    false\n    > bool = isEmailAddress( null )\n    false\n\n","isEmptyArray":"\nisEmptyArray( value )\n    Tests if a value is an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is an empty array.\n\n    Examples\n    --------\n    > var bool = isEmptyArray( [] )\n    true\n    > bool = isEmptyArray( [ 1, 2, 3 ] )\n    false\n    > bool = isEmptyArray( {} )\n    false\n\n    See Also\n    --------\n    isArray, isEmptyArrayLikeObject, isEmptyCollection\n","isEmptyArrayLikeObject":"\nisEmptyArrayLikeObject( value )\n    Tests if a value is an empty array-like object.\n\n    If provided a string, the function returns `false`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an empty array-like object.\n\n    Examples\n    --------\n    > var bool = isEmptyArrayLikeObject( [] )\n    true\n    > bool = isEmptyArrayLikeObject( { 'length': 0 } )\n    true\n    > bool = isEmptyArrayLikeObject( '' )\n    false\n\n    See Also\n    --------\n    isArrayLikeObject, isEmptyArray, isEmptyCollection\n","isEmptyCollection":"\nisEmptyCollection( value )\n    Tests if a value is an empty collection.\n\n    A collection is defined as an array, typed array, or an array-like object\n    (excluding strings and functions).\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is an empty collection.\n\n    Examples\n    --------\n    > var bool = isEmptyCollection( [] )\n    true\n    > bool = isEmptyCollection( { 'length': 0 } )\n    true\n    > bool = isEmptyCollection( [ 1, 2, 3 ] )\n    false\n    > bool = isEmptyCollection( {} )\n    false\n\n    See Also\n    --------\n    isCollection, isEmptyArray, isEmptyArrayLikeObject\n","isEmptyObject":"\nisEmptyObject( value )\n    Tests if a value is an empty object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is an empty object.\n\n    Examples\n    --------\n    > var bool = isEmptyObject( {} )\n    true\n    > bool = isEmptyObject( { 'beep': 'boop' } )\n    false\n    > bool = isEmptyObject( [] )\n    false\n\n    See Also\n    --------\n    isObject, isPlainObject\n","isEmptyString":"\nisEmptyString( value )\n    Tests if a value is an empty string.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is an empty string.\n\n    Examples\n    --------\n    > var bool = isEmptyString( '' )\n    true\n    > bool = isEmptyString( new String( '' ) )\n    true\n    > bool = isEmptyString( 'beep' )\n    false\n    > bool = isEmptyString( [] )\n    false\n\n\nisEmptyString.isPrimitive( value )\n    Tests if a value is an empty string primitive.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an empty string primitive.\n\n    Examples\n    --------\n    > var bool = isEmptyString.isPrimitive( '' )\n    true\n    > bool = isEmptyString.isPrimitive( new String( '' ) )\n    false\n\n\nisEmptyString.isObject( value )\n    Tests if a value is an empty `String` object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an empty `String` object.\n\n    Examples\n    --------\n    > var bool = isEmptyString.isObject( new String( '' ) )\n    true\n    > bool = isEmptyString.isObject( '' )\n    false\n\n    See Also\n    --------\n    isString\n","isEmptyString.isPrimitive":"\nisEmptyString.isPrimitive( value )\n    Tests if a value is an empty string primitive.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an empty string primitive.\n\n    Examples\n    --------\n    > var bool = isEmptyString.isPrimitive( '' )\n    true\n    > bool = isEmptyString.isPrimitive( new String( '' ) )\n    false","isEmptyString.isObject":"\nisEmptyString.isObject( value )\n    Tests if a value is an empty `String` object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an empty `String` object.\n\n    Examples\n    --------\n    > var bool = isEmptyString.isObject( new String( '' ) )\n    true\n    > bool = isEmptyString.isObject( '' )\n    false\n\n    See Also\n    --------\n    isString","isEnumerableProperty":"\nisEnumerableProperty( value, property )\n    Tests if an object's own property is enumerable.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own property is enumerable.\n\n    Examples\n    --------\n    > var beep = { 'boop': true };\n    > var bool = isEnumerableProperty( beep, 'boop' )\n    true\n    > bool = isEnumerableProperty( beep, 'hasOwnProperty' )\n    false\n\n    See Also\n    --------\n    isConfigurableProperty, isEnumerablePropertyIn, isNonEnumerableProperty, isReadableProperty, isWritableProperty\n","isEnumerablePropertyIn":"\nisEnumerablePropertyIn( value, property )\n    Tests if an object's own or inherited property is enumerable.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own or inherited property is\n        enumerable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = true;\n    > desc.enumerable = false;\n    > desc.writable = true;\n    > desc.value = true;\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isEnumerablePropertyIn( obj, 'boop' )\n    true\n    > bool = isEnumerablePropertyIn( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    isConfigurablePropertyIn, isEnumerableProperty, isNonEnumerablePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isEqualArray":"\nisEqualArray( v1, v2 )\n    Tests if two arguments are both generic arrays and have equal values.\n\n    The function performs strict equality comparison; thus, the function treats\n    `-0` and `+0` as equal and `NaNs` as distinct.\n\n    Parameters\n    ----------\n    v1: any\n        First input value.\n\n    v2: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are equal.\n\n    Examples\n    --------\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > var y = [ 1.0, 2.0, 3.0 ];\n    > var bool = isEqualArray( x, y )\n    true\n\n    > x = [ NaN, NaN, NaN ];\n    > y = [ NaN, NaN, NaN ];\n    > bool = isEqualArray( x, y )\n    false\n\n    See Also\n    --------\n    isArray, isSameArray\n","isError":"\nisError( value )\n    Tests if a value is an Error object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an Error object.\n\n    Examples\n    --------\n    > var bool = isError( new Error( 'beep' ) )\n    true\n    > bool = isError( {} )\n    false\n\n","isEvalError":"\nisEvalError( value )\n    Tests if a value is an EvalError object.\n\n    This function should *not* be considered robust. While the function should\n    always return `true` if provided an EvalError (or a descendant) object,\n    false positives may occur due to the fact that the EvalError constructor\n    inherits from Error and has no internal class of its own. Hence, EvalError\n    impersonation is possible.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an EvalError object.\n\n    Examples\n    --------\n    > var bool = isEvalError( new EvalError( 'beep' ) )\n    true\n    > bool = isEvalError( {} )\n    false\n\n    See Also\n    --------\n    isError\n","isEven":"\nisEven( value )\n    Tests if a value is an even number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether is an even number.\n\n    Examples\n    --------\n    > var bool = isEven( 4.0 )\n    true\n    > bool = isEven( new Number( 4.0 ) )\n    true\n    > bool = isEven( 3.0 )\n    false\n    > bool = isEven( -3.14 )\n    false\n    > bool = isEven( null )\n    false\n\n\nisEven.isPrimitive( value )\n    Tests if a value is a number primitive that is an even number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive that is an even\n        number.\n\n    Examples\n    --------\n    > var bool = isEven.isPrimitive( -4.0 )\n    true\n    > bool = isEven.isPrimitive( new Number( -4.0 ) )\n    false\n\n\nisEven.isObject( value )\n    Tests if a value is a number object that is an even number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object that is an even\n        number.\n\n    Examples\n    --------\n    > var bool = isEven.isObject( 4.0 )\n    false\n    > bool = isEven.isObject( new Number( 4.0 ) )\n    true\n\n    See Also\n    --------\n    isOdd\n","isEven.isPrimitive":"\nisEven.isPrimitive( value )\n    Tests if a value is a number primitive that is an even number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive that is an even\n        number.\n\n    Examples\n    --------\n    > var bool = isEven.isPrimitive( -4.0 )\n    true\n    > bool = isEven.isPrimitive( new Number( -4.0 ) )\n    false","isEven.isObject":"\nisEven.isObject( value )\n    Tests if a value is a number object that is an even number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object that is an even\n        number.\n\n    Examples\n    --------\n    > var bool = isEven.isObject( 4.0 )\n    false\n    > bool = isEven.isObject( new Number( 4.0 ) )\n    true\n\n    See Also\n    --------\n    isOdd","isFalsy":"\nisFalsy( value )\n    Tests if a value is a value which translates to `false` when evaluated in a\n    boolean context.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is falsy.\n\n    Examples\n    --------\n    > var bool = isFalsy( false )\n    true\n    > bool = isFalsy( '' )\n    true\n    > bool = isFalsy( 0 )\n    true\n    > bool = isFalsy( null )\n    true\n    > bool = isFalsy( void 0 )\n    true\n    > bool = isFalsy( NaN )\n    true\n    > bool = isFalsy( {} )\n    false\n    > bool = isFalsy( [] )\n    false\n\n    See Also\n    --------\n    isFalsyArray, isTruthy\n","isFalsyArray":"\nisFalsyArray( value )\n    Tests if a value is an array-like object containing only falsy values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only falsy values.\n\n    Examples\n    --------\n    > var bool = isFalsyArray( [ null, '' ] )\n    true\n    > bool = isFalsyArray( [ {}, [] ] )\n    false\n    > bool = isFalsyArray( [] )\n    false\n\n    See Also\n    --------\n    isFalsy, isTruthyArray\n","isFinite":"\nisFinite( value )\n    Tests if a value is a finite number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a finite number.\n\n    Examples\n    --------\n    > var bool = isFinite( 5.0 )\n    true\n    > bool = isFinite( new Number( 5.0 ) )\n    true\n    > bool = isFinite( 1.0/0.0 )\n    false\n    > bool = isFinite( null )\n    false\n\n\nisFinite.isPrimitive( value )\n    Tests if a value is a number primitive having a finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number primitive having a finite\n        value.\n\n    Examples\n    --------\n    > var bool = isFinite.isPrimitive( -3.0 )\n    true\n    > bool = isFinite.isPrimitive( new Number( -3.0 ) )\n    false\n\n\nisFinite.isObject( value )\n    Tests if a value is a number object having a finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number object having a finite\n        value.\n\n    Examples\n    --------\n    > var bool = isFinite.isObject( 3.0 )\n    false\n    > bool = isFinite.isObject( new Number( 3.0 ) )\n    true\n\n    See Also\n    --------\n    isFiniteArray, isInfinite\n","isFinite.isPrimitive":"\nisFinite.isPrimitive( value )\n    Tests if a value is a number primitive having a finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number primitive having a finite\n        value.\n\n    Examples\n    --------\n    > var bool = isFinite.isPrimitive( -3.0 )\n    true\n    > bool = isFinite.isPrimitive( new Number( -3.0 ) )\n    false","isFinite.isObject":"\nisFinite.isObject( value )\n    Tests if a value is a number object having a finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number object having a finite\n        value.\n\n    Examples\n    --------\n    > var bool = isFinite.isObject( 3.0 )\n    false\n    > bool = isFinite.isObject( new Number( 3.0 ) )\n    true\n\n    See Also\n    --------\n    isFiniteArray, isInfinite","isFiniteArray":"\nisFiniteArray( value )\n    Tests if a value is an array-like object of finite numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object of finite\n        numbers.\n\n    Examples\n    --------\n    > var bool = isFiniteArray( [ -3.0, new Number(0.0), 2.0 ] )\n    true\n    > bool = isFiniteArray( [ -3.0, 1.0/0.0 ] )\n    false\n\n\nisFiniteArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive finite\n    numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only primitive finite numbers.\n\n    Examples\n    --------\n    > var bool = isFiniteArray.primitives( [ -1.0, 10.0 ] )\n    true\n    > bool = isFiniteArray.primitives( [ -1.0, 0.0, 5.0 ] )\n    true\n    > bool = isFiniteArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false\n\n\nisFiniteArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having finite values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only number objects having finite values.\n\n    Examples\n    --------\n    > var bool = isFiniteArray.objects( [ new Number(1.0), new Number(3.0) ] )\n    true\n    > bool = isFiniteArray.objects( [ -1.0, 0.0, 3.0 ] )\n    false\n    > bool = isFiniteArray.objects( [ 3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isFinite, isInfinite\n","isFiniteArray.primitives":"\nisFiniteArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive finite\n    numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only primitive finite numbers.\n\n    Examples\n    --------\n    > var bool = isFiniteArray.primitives( [ -1.0, 10.0 ] )\n    true\n    > bool = isFiniteArray.primitives( [ -1.0, 0.0, 5.0 ] )\n    true\n    > bool = isFiniteArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false","isFiniteArray.objects":"\nisFiniteArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having finite values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only number objects having finite values.\n\n    Examples\n    --------\n    > var bool = isFiniteArray.objects( [ new Number(1.0), new Number(3.0) ] )\n    true\n    > bool = isFiniteArray.objects( [ -1.0, 0.0, 3.0 ] )\n    false\n    > bool = isFiniteArray.objects( [ 3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isFinite, isInfinite","isFloat32Array":"\nisFloat32Array( value )\n    Tests if a value is a Float32Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Float32Array.\n\n    Examples\n    --------\n    > var bool = isFloat32Array( new Float32Array( 10 ) )\n    true\n    > bool = isFloat32Array( [] )\n    false\n\n    See Also\n    --------\n    isFloat64Array\n","isFloat32MatrixLike":"\nisFloat32MatrixLike( value )\n    Tests if a value is a 2-dimensional ndarray-like object containing single-\n    precision floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 2-dimensional ndarray-like\n        object containing single-precision floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Float32Array( [ 0, 0, 0, 0 ] );\n    > M.ndims = 2;\n    > M.shape = [ 2, 2 ];\n    > M.strides = [ 2, 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'float32';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isFloat32MatrixLike( M )\n    true\n    > bool = isFloat32MatrixLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isFloat32MatrixLike( 3.14 )\n    false\n    > bool = isFloat32MatrixLike( {} )\n    false\n\n    See Also\n    --------\n    isFloat64MatrixLike, isndarrayLike, isMatrixLike\n","isFloat32ndarrayLike":"\nisFloat32ndarrayLike( value )\n    Tests if a value is an ndarray-like object containing single-precision\n    floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an ndarray-like object containing\n        single-precision floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Float32Array( [ 0, 0, 0, 0 ] );\n    > M.ndims = 2;\n    > M.shape = [ 2, 2 ];\n    > M.strides = [ 2, 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'float32';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isFloat32ndarrayLike( M )\n    true\n    > bool = isFloat32ndarrayLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isFloat32ndarrayLike( 3.14 )\n    false\n    > bool = isFloat32ndarrayLike( {} )\n    false\n\n    See Also\n    --------\n    isFloat64ndarrayLike, isndarrayLike\n","isFloat32VectorLike":"\nisFloat32VectorLike( value )\n    Tests if a value is a 1-dimensional ndarray-like object containing single-\n    precision floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 1-dimensional ndarray-like\n        object containing single-precision floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Float32Array( [ 0, 0, 0, 0 ] );\n    > M.ndims = 1;\n    > M.shape = [ 4 ];\n    > M.strides = [ 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'float32';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isFloat32VectorLike( M )\n    true\n    > bool = isFloat32VectorLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isFloat32VectorLike( 3.14 )\n    false\n    > bool = isFloat32VectorLike( {} )\n    false\n\n    See Also\n    --------\n    isFloat64VectorLike, isndarrayLike, isVectorLike\n","isFloat64Array":"\nisFloat64Array( value )\n    Tests if a value is a Float64Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Float64Array.\n\n    Examples\n    --------\n    > var bool = isFloat64Array( new Float64Array( 10 ) )\n    true\n    > bool = isFloat64Array( [] )\n    false\n\n    See Also\n    --------\n    isFloat32Array\n","isFloat64MatrixLike":"\nisFloat64MatrixLike( value )\n    Tests if a value is a 2-dimensional ndarray-like object containing double-\n    precision floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 2-dimensional ndarray-like\n        object containing double-precision floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Float64Array( [ 0, 0, 0, 0 ] );\n    > M.ndims = 2;\n    > M.shape = [ 2, 2 ];\n    > M.strides = [ 2, 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'float64';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isFloat64MatrixLike( M )\n    true\n    > bool = isFloat64MatrixLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isFloat64MatrixLike( 3.14 )\n    false\n    > bool = isFloat64MatrixLike( {} )\n    false\n\n    See Also\n    --------\n    isFloat32MatrixLike, isndarrayLike, isMatrixLike\n","isFloat64ndarrayLike":"\nisFloat64ndarrayLike( value )\n    Tests if a value is an ndarray-like object containing double-precision\n    floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an ndarray-like object containing\n        double-precision floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Float64Array( [ 0, 0, 0, 0 ] );\n    > M.ndims = 2;\n    > M.shape = [ 2, 2 ];\n    > M.strides = [ 2, 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'float64';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isFloat64ndarrayLike( M )\n    true\n    > bool = isFloat64ndarrayLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isFloat64ndarrayLike( 3.14 )\n    false\n    > bool = isFloat64ndarrayLike( {} )\n    false\n\n    See Also\n    --------\n    isFloat32ndarrayLike, isndarrayLike\n","isFloat64VectorLike":"\nisFloat64VectorLike( value )\n    Tests if a value is a 1-dimensional ndarray-like object containing double-\n    precision floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 1-dimensional ndarray-like\n        object containing double-precision floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Float64Array( [ 0, 0, 0, 0 ] );\n    > M.ndims = 1;\n    > M.shape = [ 4 ];\n    > M.strides = [ 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'float64';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isFloat64VectorLike( M )\n    true\n    > bool = isFloat64VectorLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isFloat64VectorLike( 3.14 )\n    false\n    > bool = isFloat64VectorLike( {} )\n    false\n\n    See Also\n    --------\n    isFloat32VectorLike, isndarrayLike, isVectorLike\n","isFunction":"\nisFunction( value )\n    Tests if a value is a function.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a function.\n\n    Examples\n    --------\n    > function beep() {};\n    > var bool = isFunction( beep )\n    true\n    > bool = isFunction( {} )\n    false\n\n","isFunctionArray":"\nisFunctionArray( value )\n    Tests if a value is an array-like object containing only functions.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        functions.\n\n    Examples\n    --------\n    > function beep() {};\n    > function boop() {};\n    > var bool = isFunctionArray( [ beep, boop ] )\n    true\n    > bool = isFunctionArray( [ {}, beep ] )\n    false\n    > bool = isFunctionArray( [] )\n    false\n\n    See Also\n    --------\n    isArray\n","isGeneratorObject":"\nisGeneratorObject( value )\n    Tests if a value is a generator object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a generator object.\n\n    Examples\n    --------\n    > function* generateID() {\n    ...     var idx = 0;\n    ...     while ( idx < idx+1 ) {\n    ...         yield idx;\n    ...         idx += 1;\n    ...     }\n    ... };\n    > var bool = isGeneratorObject( generateID() )\n    true\n    > bool = isGeneratorObject( generateID )\n    false\n    > bool = isGeneratorObject( {} )\n    false\n    > bool = isGeneratorObject( null )\n    false\n\n    See Also\n    --------\n    hasGeneratorSupport, isGeneratorObjectLike\n","isGeneratorObjectLike":"\nisGeneratorObjectLike( value )\n    Tests if a value is generator object-like.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is generator object-like.\n\n    Examples\n    --------\n    > var obj = {\n    ...     'next': function noop() {},\n    ...     'return': function noop() {},\n    ...     'throw': function noop() {}\n    ... };\n    > var bool = isGeneratorObjectLike( obj )\n    true\n    > bool = isGeneratorObjectLike( {} )\n    false\n    > bool = isGeneratorObjectLike( null )\n    false\n\n    See Also\n    --------\n    hasGeneratorSupport, isGeneratorObject\n","isgzipBuffer":"\nisgzipBuffer( value )\n    Tests if a value is a gzip buffer.\n\n    A gzip buffer is defined as either a Node.js Buffer or Uint8Array which\n    contains a 10-byte header, a body containing the compressed payload, and an\n    8-byte footer containing a CRC-32 checksum and the length of the original\n    uncompressed data, modulo 2^32.\n\n    This function only examines the 10-byte header to ensure the header includes\n    the expected magic number and compression method. The function does not\n    perform an integrity check.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a gzip buffer.\n\n    Examples\n    --------\n    > var buf = new Uint8Array( 20 );\n    > buf[ 0 ] = 31;  // 0x1f => magic number\n    > buf[ 1 ] = 139; // 0x8b\n    > buf[ 2 ] = 8;   // 0x08 => compression method\n    > var bool = isgzipBuffer( buf )\n    true\n    > bool = isgzipBuffer( [] )\n    false\n\n    See Also\n    --------\n    isBuffer, isUint8Array\n","isHexString":"\nisHexString( str )\n    Tests whether a string contains only hexadecimal digits.\n\n    The function does not recognize `x` (as in the standard `0x` prefix).\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a string contains only hexadecimal digits.\n\n    Examples\n    --------\n    > var bool = isHexString( '0123456789abcdefABCDEF' )\n    true\n    > bool = isHexString( '0xffffff' )\n    false\n    > bool = isHexString( 'x' )\n    false\n    > bool = isHexString( '' )\n    false\n\n    See Also\n    --------\n    isString\n","isInfinite":"\nisInfinite( value )\n    Tests if a value is an infinite number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an infinite number.\n\n    Examples\n    --------\n    > var bool = isInfinite( 1.0/0.0 )\n    true\n    > bool = isInfinite( new Number( -1.0/0.0 ) )\n    true\n    > bool = isInfinite( 5.0 )\n    false\n    > bool = isInfinite( '1.0/0.0' )\n    false\n\n\nisInfinite.isPrimitive( value )\n    Tests if a value is a number primitive having an infinite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number primitive having an\n        infinite value.\n\n    Examples\n    --------\n    > var bool = isInfinite.isPrimitive( -1.0/0.0 )\n    true\n    > bool = isInfinite.isPrimitive( new Number( -1.0/0.0 ) )\n    false\n\n\nisInfinite.isObject( value )\n    Tests if a value is a number object having an infinite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number object having an infinite\n        value.\n\n    Examples\n    --------\n    > var bool = isInfinite.isObject( 1.0/0.0 )\n    false\n    > bool = isInfinite.isObject( new Number( 1.0/0.0 ) )\n    true\n\n    See Also\n    --------\n    isFinite\n","isInfinite.isPrimitive":"\nisInfinite.isPrimitive( value )\n    Tests if a value is a number primitive having an infinite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number primitive having an\n        infinite value.\n\n    Examples\n    --------\n    > var bool = isInfinite.isPrimitive( -1.0/0.0 )\n    true\n    > bool = isInfinite.isPrimitive( new Number( -1.0/0.0 ) )\n    false","isInfinite.isObject":"\nisInfinite.isObject( value )\n    Tests if a value is a number object having an infinite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number object having an infinite\n        value.\n\n    Examples\n    --------\n    > var bool = isInfinite.isObject( 1.0/0.0 )\n    false\n    > bool = isInfinite.isObject( new Number( 1.0/0.0 ) )\n    true\n\n    See Also\n    --------\n    isFinite","isInheritedProperty":"\nisInheritedProperty( value, property )\n    Tests if an object has an inherited property.\n\n    Value arguments other than `null` or `undefined` are coerced to objects.\n\n    Non-symbol property arguments are coerced to strings.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object has an inherited property.\n\n    Examples\n    --------\n    > var beep = { 'boop': true };\n    > var bool = isInheritedProperty( beep, 'boop' )\n    false\n    > bool = isInheritedProperty( beep, 'toString' )\n    true\n    > bool = isInheritedProperty( beep, 'bop' )\n    false\n\n    See Also\n    --------\n    hasOwnProp, hasProp\n","isInt8Array":"\nisInt8Array( value )\n    Tests if a value is an Int8Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an Int8Array.\n\n    Examples\n    --------\n    > var bool = isInt8Array( new Int8Array( 10 ) )\n    true\n    > bool = isInt8Array( [] )\n    false\n\n    See Also\n    --------\n    isInt16Array, isInt32Array\n","isInt16Array":"\nisInt16Array( value )\n    Tests if a value is an Int16Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an Int16Array.\n\n    Examples\n    --------\n    > var bool = isInt16Array( new Int16Array( 10 ) )\n    true\n    > bool = isInt16Array( [] )\n    false\n\n    See Also\n    --------\n    isInt32Array, isInt8Array\n","isInt32Array":"\nisInt32Array( value )\n    Tests if a value is an Int32Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an Int32Array.\n\n    Examples\n    --------\n    > var bool = isInt32Array( new Int32Array( 10 ) )\n    true\n    > bool = isInt32Array( [] )\n    false\n\n    See Also\n    --------\n    isInt16Array, isInt8Array\n","isInteger":"\nisInteger( value )\n    Tests if a value is an integer.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an integer.\n\n    Examples\n    --------\n    > var bool = isInteger( 5.0 )\n    true\n    > bool = isInteger( new Number( 5.0 ) )\n    true\n    > bool = isInteger( -3.14 )\n    false\n    > bool = isInteger( null )\n    false\n\n\nisInteger.isPrimitive( value )\n    Tests if a value is a number primitive having an integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having an integer\n        value.\n\n    Examples\n    --------\n    > var bool = isInteger.isPrimitive( -3.0 )\n    true\n    > bool = isInteger.isPrimitive( new Number( -3.0 ) )\n    false\n\n\nisInteger.isObject( value )\n    Tests if a value is a number object having an integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having an integer\n        value.\n\n    Examples\n    --------\n    > var bool = isInteger.isObject( 3.0 )\n    false\n    > bool = isInteger.isObject( new Number( 3.0 ) )\n    true\n\n    See Also\n    --------\n    isNumber\n","isInteger.isPrimitive":"\nisInteger.isPrimitive( value )\n    Tests if a value is a number primitive having an integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having an integer\n        value.\n\n    Examples\n    --------\n    > var bool = isInteger.isPrimitive( -3.0 )\n    true\n    > bool = isInteger.isPrimitive( new Number( -3.0 ) )\n    false","isInteger.isObject":"\nisInteger.isObject( value )\n    Tests if a value is a number object having an integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having an integer\n        value.\n\n    Examples\n    --------\n    > var bool = isInteger.isObject( 3.0 )\n    false\n    > bool = isInteger.isObject( new Number( 3.0 ) )\n    true\n\n    See Also\n    --------\n    isNumber","isIntegerArray":"\nisIntegerArray( value )\n    Tests if a value is an array-like object of integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object of integer\n        values.\n\n    Examples\n    --------\n    > var bool = isIntegerArray( [ -3.0, new Number(0.0), 2.0 ] )\n    true\n    > bool = isIntegerArray( [ -3.0, '3.0' ] )\n    false\n\n\nisIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive integer\n    values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only primitive integer values.\n\n    Examples\n    --------\n    > var bool = isIntegerArray.primitives( [ -1.0, 10.0 ] )\n    true\n    > bool = isIntegerArray.primitives( [ -1.0, 0.0, 5.0 ] )\n    true\n    > bool = isIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false\n\n\nisIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only number objects having integer values.\n\n    Examples\n    --------\n    > var bool = isIntegerArray.objects( [ new Number(1.0), new Number(3.0) ] )\n    true\n    > bool = isIntegerArray.objects( [ -1.0, 0.0, 3.0 ] )\n    false\n    > bool = isIntegerArray.objects( [ 3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray\n","isIntegerArray.primitives":"\nisIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive integer\n    values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only primitive integer values.\n\n    Examples\n    --------\n    > var bool = isIntegerArray.primitives( [ -1.0, 10.0 ] )\n    true\n    > bool = isIntegerArray.primitives( [ -1.0, 0.0, 5.0 ] )\n    true\n    > bool = isIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false","isIntegerArray.objects":"\nisIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only number objects having integer values.\n\n    Examples\n    --------\n    > var bool = isIntegerArray.objects( [ new Number(1.0), new Number(3.0) ] )\n    true\n    > bool = isIntegerArray.objects( [ -1.0, 0.0, 3.0 ] )\n    false\n    > bool = isIntegerArray.objects( [ 3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray","isIterableLike":"\nisIterableLike( value )\n    Tests if a value is iterable-like.\n\n    In order to be iterable, an object must implement the @@iterator method,\n    which, when called, returns an iterator protocol-compliant object.\n\n    An iterator protocol-compliant object is an object having a `next` method\n    which adheres to the iterator protocol.\n\n    As full iterator compliance is impossible to achieve without evaluating an\n    iterator, this function checks *only* for interface compliance.\n\n    In environments lacking Symbol.iterator support, this function always\n    returns `false`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is iterable-like.\n\n    Examples\n    --------\n    > var bool = isIterableLike( [ 1, 2, 3 ] )\n    <boolean>\n    > bool = isIterableLike( {} )\n    false\n    > bool = isIterableLike( null )\n    false\n\n    See Also\n    --------\n    isIteratorLike\n","isIteratorLike":"\nisIteratorLike( value )\n    Tests if a value is iterator-like.\n\n    An iterator protocol-compliant object is an object having a `next` method\n    which adheres to the iterator protocol.\n\n    As full iterator compliance is impossible to achieve without evaluating an\n    iterator, this function checks *only* for interface compliance.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is iterator-like.\n\n    Examples\n    --------\n    > var obj = {\n    ...     'next': function noop() {}\n    ... };\n    > var bool = isIteratorLike( obj )\n    true\n    > bool = isIteratorLike( {} )\n    false\n    > bool = isIteratorLike( null )\n    false\n\n    See Also\n    --------\n    isIterableLike\n","isJSON":"\nisJSON( value )\n    Tests if a value is a parseable JSON string.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a parseable JSON string.\n\n    Examples\n    --------\n    > var bool = isJSON( '{\"a\":5}' )\n    true\n    > bool = isJSON( '{a\":5}' )\n    false\n\n","isKebabcase":"\nisKebabcase( value )\n    Tests if a value is a string in kebab case.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a string in kebab case.\n\n    Examples\n    --------\n    > var bool = isKebabcase( 'beep-boop' )\n    true\n    > bool = isKebabcase( 'BEEP_BOOP' )\n    false\n\n    See Also\n    --------\n    isString","isLeapYear":"\nisLeapYear( value )\n    Tests whether a value corresponds to a leap year in the Gregorian calendar.\n\n    A leap year is defined as any year which is exactly divisible by 4, except\n    for years which are exactly divisible by 100 and not by 400. In this\n    definition, 100 corresponds to years marking a new century, and 400\n    corresponds to the length of the *leap cycle*.\n\n    If not provided any arguments, the function returns a boolean indicating\n    if the current year (according to local time) is a leap year.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value corresponds to a leap year.\n\n    Examples\n    --------\n    > var bool = isLeapYear( new Date() )\n    <boolean>\n    > bool = isLeapYear( 1996 )\n    true\n    > bool = isLeapYear( 2001 )\n    false\n\n","isLocalhost":"\nisLocalhost( value )\n    Tests whether a value is a localhost hostname.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a localhost hostname.\n\n    Examples\n    --------\n    > var bool = isLocalhost( 'localhost' )\n    true\n    > bool = isLocalhost( '127.0.0.1' )\n    true\n    > bool = isLocalhost( 'stdlib.io' )\n    false\n","isLowercase":"\nisLowercase( value )\n    Tests if a value is a lowercase string.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a lowercase string.\n\n    Examples\n    --------\n    > var bool = isLowercase( 'hello' )\n    true\n    > bool = isLowercase( 'World' )\n    false\n\n    See Also\n    --------\n    isString, isUppercase\n","isMatrixLike":"\nisMatrixLike( value )\n    Tests if a value is a 2-dimensional ndarray-like object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 2-dimensional ndarray-like\n        object.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = [ 0, 0, 0, 0 ];\n    > M.ndims = 2;\n    > M.shape = [ 2, 2 ];\n    > M.strides = [ 2, 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'generic';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isMatrixLike( M )\n    true\n    > bool = isMatrixLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isMatrixLike( 3.14 )\n    false\n    > bool = isMatrixLike( {} )\n    false\n\n    See Also\n    --------\n    isArray, isArrayLike, isndarrayLike, isTypedArrayLike, isVectorLike\n","isMethod":"\nisMethod( value, property )\n    Tests if an object has a specified method name.\n\n    Value arguments other than `null` or `undefined` are coerced to objects.\n\n    Property arguments are coerced to strings.\n\n    The function only searches own properties.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object has a specified method name.\n\n    Examples\n    --------\n    > var beep = { 'boop': function beep() { return 'beep'; } };\n    > var bool = isMethod( beep, 'boop' )\n    true\n    > bool = isMethod( beep, 'toString' )\n    false\n\n    See Also\n    --------\n    hasOwnProp, isFunction, isMethodIn\n","isMethodIn":"\nisMethodIn( value, property )\n    Tests if an object has a specified method name, either own or inherited.\n\n    Value arguments other than `null` or `undefined` are coerced to objects.\n\n    Non-symbol property arguments are coerced to strings.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object has a specified method name.\n\n    Examples\n    --------\n    > var beep = { 'boop': true };\n    > var bool = isMethodIn( beep, 'toString' )\n    true\n    > bool = isMethodIn( beep, 'boop' )\n    false\n    > bool = isMethodIn( beep, 'bop' )\n    false\n\n    See Also\n    --------\n    hasProp, isFunction, isMethod\n","isMultiSlice":"\nisMultiSlice( value )\n    Tests if a value is a MultiSlice object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a MultiSlice object.\n\n    Examples\n    --------\n    > var bool = isMultiSlice( new MultiSlice() )\n    true\n    > bool = isMultiSlice( 3.14 )\n    false\n    > bool = isMultiSlice( {} )\n    false\n\n    See Also\n    --------\n    isSlice, MultiSlice\n","isNamedTypedTupleLike":"\nisNamedTypedTupleLike( value )\n    Tests if a value is named typed tuple-like.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is named typed tuple-like.\n\n    Examples\n    --------\n    > var Point = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = new Point();\n    > var bool = isNamedTypedTupleLike( p )\n    true\n    > bool = isNamedTypedTupleLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isNamedTypedTupleLike( 3.14 )\n    false\n    > bool = isNamedTypedTupleLike( {} )\n    false\n\n    See Also\n    --------\n    namedtypedtuple\n","isnan":"\nisnan( value )\n    Tests if a value is NaN.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is NaN.\n\n    Examples\n    --------\n    > var bool = isnan( NaN )\n    true\n    > bool = isnan( new Number( NaN ) )\n    true\n    > bool = isnan( 3.14 )\n    false\n    > bool = isnan( null )\n    false\n\n\nisnan.isPrimitive( value )\n    Tests if a value is a NaN number primitive.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a NaN number primitive.\n\n    Examples\n    --------\n    > var bool = isnan.isPrimitive( NaN )\n    true\n    > bool = isnan.isPrimitive( 3.14 )\n    false\n    > bool = isnan.isPrimitive( new Number( NaN ) )\n    false\n\n\nisnan.isObject( value )\n    Tests if a value is a number object having a value of NaN.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value of\n        NaN.\n\n    Examples\n    --------\n    > var bool = isnan.isObject( NaN )\n    false\n    > bool = isnan.isObject( new Number( NaN ) )\n    true\n\n    See Also\n    --------\n    isNumber\n","isnan.isPrimitive":"\nisnan.isPrimitive( value )\n    Tests if a value is a NaN number primitive.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a NaN number primitive.\n\n    Examples\n    --------\n    > var bool = isnan.isPrimitive( NaN )\n    true\n    > bool = isnan.isPrimitive( 3.14 )\n    false\n    > bool = isnan.isPrimitive( new Number( NaN ) )\n    false","isnan.isObject":"\nisnan.isObject( value )\n    Tests if a value is a number object having a value of NaN.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value of\n        NaN.\n\n    Examples\n    --------\n    > var bool = isnan.isObject( NaN )\n    false\n    > bool = isnan.isObject( new Number( NaN ) )\n    true\n\n    See Also\n    --------\n    isNumber","isNaNArray":"\nisNaNArray( value )\n    Tests if a value is an array-like object containing only NaN values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        NaN values.\n\n    Examples\n    --------\n    > var bool = isNaNArray( [ NaN, NaN, NaN ] )\n    true\n    > bool = isNaNArray( [ NaN, 2 ] )\n    false\n\n\nisNaNArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive NaN\n    values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive NaN values.\n\n    Examples\n    --------\n    > var bool = isNaNArray.primitives( [ NaN, new Number( NaN ) ] )\n    false\n    > bool = isNaNArray.primitives( [ NaN, NaN, NaN ] )\n    true\n\n\nisNaNArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having NaN values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having NaN values.\n\n    Examples\n    --------\n    > var bool = isNaNArray.objects( [ new Number( NaN ), new Number( NaN ) ] )\n    true\n    > bool = isNaNArray.objects( [ NaN, new Number( NaN ), new Number( NaN ) ] )\n    false\n    > bool = isNaNArray.objects( [ NaN, NaN, NaN ] )\n    false\n\n    See Also\n    --------\n    isnan\n","isNaNArray.primitives":"\nisNaNArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive NaN\n    values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive NaN values.\n\n    Examples\n    --------\n    > var bool = isNaNArray.primitives( [ NaN, new Number( NaN ) ] )\n    false\n    > bool = isNaNArray.primitives( [ NaN, NaN, NaN ] )\n    true","isNaNArray.objects":"\nisNaNArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having NaN values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having NaN values.\n\n    Examples\n    --------\n    > var bool = isNaNArray.objects( [ new Number( NaN ), new Number( NaN ) ] )\n    true\n    > bool = isNaNArray.objects( [ NaN, new Number( NaN ), new Number( NaN ) ] )\n    false\n    > bool = isNaNArray.objects( [ NaN, NaN, NaN ] )\n    false\n\n    See Also\n    --------\n    isnan","isNativeFunction":"\nisNativeFunction( value )\n    Tests if a value is a native function.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a native function.\n\n    Examples\n    --------\n    > var bool = isNativeFunction( Date )\n    true\n    > function beep() {};\n    > bool = isNativeFunction( beep )\n    false\n    > bool = isNativeFunction( {} )\n    false\n\n    See Also\n    --------\n    isFunction\n","isndarrayLike":"\nisndarrayLike( value )\n    Tests if a value is ndarray-like.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is ndarray-like.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = [ 0, 0, 0, 0 ];\n    > M.ndims = 2;\n    > M.shape = [ 2, 2 ];\n    > M.strides = [ 2, 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'generic';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isndarrayLike( M )\n    true\n    > bool = isndarrayLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isndarrayLike( 3.14 )\n    false\n    > bool = isndarrayLike( {} )\n    false\n\n    See Also\n    --------\n    isArray, isArrayLike, isMatrixLike, isTypedArrayLike, isVectorLike\n","isndarrayLikeWithDataType":"\nisndarrayLikeWithDataType( value, dtype )\n    Tests if a value is an ndarray-like object having a specified data type.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    dtype: any\n        Data type value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an ndarray-like object having a\n        specified data type.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = [ 0, 0, 0, 0 ];\n    > M.ndims = 2;\n    > M.shape = [ 2, 2 ];\n    > M.strides = [ 2, 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'generic';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isndarrayLikeWithDataType( M, 'generic' )\n    true\n    > bool = isndarrayLikeWithDataType( [ 1, 2, 3, 4 ], 'generic' )\n    false\n    > bool = isndarrayLikeWithDataType( 3.14, 'generic' )\n    false\n    > bool = isndarrayLikeWithDataType( {}, 'generic' )\n    false\n\n    See Also\n    --------\n    isndarrayLike\n","isNegativeFinite":"\nisNegativeFinite( value )\n    Tests if a value is a finite negative number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a finite negative number.\n\n    Examples\n    --------\n    > var bool = isNegativeFinite( -5.0 )\n    true\n    > bool = isNegativeFinite( new Number( -5.0 ) )\n    true\n    > bool = isNegativeFinite( -3.14 )\n    true\n    > bool = isNegativeFinite( 5.0 )\n    false\n    > bool = isNegativeFinite( null )\n    false\n    > bool = isNegativeFinite( -1.0/0.0 )\n    false\n    > bool = isNegativeFinite( new Number( -1.0/0.0 ) )\n    false\n\n\nisNegativeFinite.isPrimitive( value )\n    Tests if a value is a number primitive having a finite negative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number primitive having a finite\n        negative value.\n\n    Examples\n    --------\n    > var bool = isNegativeFinite.isPrimitive( -3.0 )\n    true\n    > bool = isNegativeFinite.isPrimitive( new Number( -3.0 ) )\n    false\n    > var bool = isNegativeFinite.isPrimitive( -1.0/0.0 )\n    false\n    > bool = isNegativeFinite.isPrimitive( new Number( -1.0/0.0 ) )\n    false\n\n\nisNegativeFinite.isObject( value )\n    Tests if a value is a number object having a finite negative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number object having a finite\n        negative value.\n\n    Examples\n    --------\n    > var bool = isNegativeFinite.isObject( -3.0 )\n    false\n    > bool = isNegativeFinite.isObject( new Number( -3.0 ) )\n    true\n    > bool = isNegativeFinite.isObject( -1.0/0.0 )\n    false\n    > bool = isNegativeFinite.isObject( new Number( -1.0/0.0 ) )\n    false\n\n    See Also\n    --------\n    isFinite, isNegativeNumber, isPositiveFinite\n","isNegativeFinite.isPrimitive":"\nisNegativeFinite.isPrimitive( value )\n    Tests if a value is a number primitive having a finite negative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number primitive having a finite\n        negative value.\n\n    Examples\n    --------\n    > var bool = isNegativeFinite.isPrimitive( -3.0 )\n    true\n    > bool = isNegativeFinite.isPrimitive( new Number( -3.0 ) )\n    false\n    > var bool = isNegativeFinite.isPrimitive( -1.0/0.0 )\n    false\n    > bool = isNegativeFinite.isPrimitive( new Number( -1.0/0.0 ) )\n    false","isNegativeFinite.isObject":"\nisNegativeFinite.isObject( value )\n    Tests if a value is a number object having a finite negative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number object having a finite\n        negative value.\n\n    Examples\n    --------\n    > var bool = isNegativeFinite.isObject( -3.0 )\n    false\n    > bool = isNegativeFinite.isObject( new Number( -3.0 ) )\n    true\n    > bool = isNegativeFinite.isObject( -1.0/0.0 )\n    false\n    > bool = isNegativeFinite.isObject( new Number( -1.0/0.0 ) )\n    false\n\n    See Also\n    --------\n    isFinite, isNegativeNumber, isPositiveFinite","isNegativeInteger":"\nisNegativeInteger( value )\n    Tests if a value is a negative integer.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a negative integer.\n\n    Examples\n    --------\n    > var bool = isNegativeInteger( -5.0 )\n    true\n    > bool = isNegativeInteger( new Number( -5.0 ) )\n    true\n    > bool = isNegativeInteger( 5.0 )\n    false\n    > bool = isNegativeInteger( -3.14 )\n    false\n    > bool = isNegativeInteger( null )\n    false\n\n\nisNegativeInteger.isPrimitive( value )\n    Tests if a value is a number primitive having a negative integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a negative\n        integer value.\n\n    Examples\n    --------\n    > var bool = isNegativeInteger.isPrimitive( -3.0 )\n    true\n    > bool = isNegativeInteger.isPrimitive( new Number( -3.0 ) )\n    false\n\n\nisNegativeInteger.isObject( value )\n    Tests if a value is a number object having a negative integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a negative\n        integer value.\n\n    Examples\n    --------\n    > var bool = isNegativeInteger.isObject( -3.0 )\n    false\n    > bool = isNegativeInteger.isObject( new Number( -3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger\n","isNegativeInteger.isPrimitive":"\nisNegativeInteger.isPrimitive( value )\n    Tests if a value is a number primitive having a negative integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a negative\n        integer value.\n\n    Examples\n    --------\n    > var bool = isNegativeInteger.isPrimitive( -3.0 )\n    true\n    > bool = isNegativeInteger.isPrimitive( new Number( -3.0 ) )\n    false","isNegativeInteger.isObject":"\nisNegativeInteger.isObject( value )\n    Tests if a value is a number object having a negative integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a negative\n        integer value.\n\n    Examples\n    --------\n    > var bool = isNegativeInteger.isObject( -3.0 )\n    false\n    > bool = isNegativeInteger.isObject( new Number( -3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger","isNegativeIntegerArray":"\nisNegativeIntegerArray( value )\n    Tests if a value is an array-like object containing only negative integers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        negative integers.\n\n    Examples\n    --------\n    > var bool = isNegativeIntegerArray( [ -3.0, new Number(-3.0) ] )\n    true\n    > bool = isNegativeIntegerArray( [ -3.0, '-3.0' ] )\n    false\n\n\nisNegativeIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only negative primitive\n    integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        negative primitive integer values.\n\n    Examples\n    --------\n    > var bool = isNegativeIntegerArray.primitives( [ -1.0, -10.0 ] )\n    true\n    > bool = isNegativeIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNegativeIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false\n\n\nisNegativeIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having negative integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having negative integer values.\n\n    Examples\n    --------\n    > var bool = isNegativeIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n    true\n    > bool = isNegativeIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNegativeIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray\n","isNegativeIntegerArray.primitives":"\nisNegativeIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only negative primitive\n    integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        negative primitive integer values.\n\n    Examples\n    --------\n    > var bool = isNegativeIntegerArray.primitives( [ -1.0, -10.0 ] )\n    true\n    > bool = isNegativeIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNegativeIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false","isNegativeIntegerArray.objects":"\nisNegativeIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having negative integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having negative integer values.\n\n    Examples\n    --------\n    > var bool = isNegativeIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n    true\n    > bool = isNegativeIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNegativeIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray","isNegativeNumber":"\nisNegativeNumber( value )\n    Tests if a value is a negative number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a negative number.\n\n    Examples\n    --------\n    > var bool = isNegativeNumber( -5.0 )\n    true\n    > bool = isNegativeNumber( new Number( -5.0 ) )\n    true\n    > bool = isNegativeNumber( -3.14 )\n    true\n    > bool = isNegativeNumber( 5.0 )\n    false\n    > bool = isNegativeNumber( null )\n    false\n\n\nisNegativeNumber.isPrimitive( value )\n    Tests if a value is a number primitive having a negative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a negative\n        value.\n\n    Examples\n    --------\n    > var bool = isNegativeNumber.isPrimitive( -3.0 )\n    true\n    > bool = isNegativeNumber.isPrimitive( new Number( -3.0 ) )\n    false\n\n\nisNegativeNumber.isObject( value )\n    Tests if a value is a number object having a negative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a negative\n        value.\n\n    Examples\n    --------\n    > var bool = isNegativeNumber.isObject( -3.0 )\n    false\n    > bool = isNegativeNumber.isObject( new Number( -3.0 ) )\n    true\n\n    See Also\n    --------\n    isNumber\n","isNegativeNumber.isPrimitive":"\nisNegativeNumber.isPrimitive( value )\n    Tests if a value is a number primitive having a negative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a negative\n        value.\n\n    Examples\n    --------\n    > var bool = isNegativeNumber.isPrimitive( -3.0 )\n    true\n    > bool = isNegativeNumber.isPrimitive( new Number( -3.0 ) )\n    false","isNegativeNumber.isObject":"\nisNegativeNumber.isObject( value )\n    Tests if a value is a number object having a negative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a negative\n        value.\n\n    Examples\n    --------\n    > var bool = isNegativeNumber.isObject( -3.0 )\n    false\n    > bool = isNegativeNumber.isObject( new Number( -3.0 ) )\n    true\n\n    See Also\n    --------\n    isNumber","isNegativeNumberArray":"\nisNegativeNumberArray( value )\n    Tests if a value is an array-like object containing only negative numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        negative numbers.\n\n    Examples\n    --------\n    > var bool = isNegativeNumberArray( [ -3.0, new Number(-3.0) ] )\n    true\n    > bool = isNegativeNumberArray( [ -3.0, '-3.0' ] )\n    false\n\n\nisNegativeNumberArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive negative\n    numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive negative numbers.\n\n    Examples\n    --------\n    > var bool = isNegativeNumberArray.primitives( [ -1.0, -10.0 ] )\n    true\n    > bool = isNegativeNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNegativeNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false\n\n\nisNegativeNumberArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having negative number values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having negative number values.\n\n    Examples\n    --------\n    > var bool = isNegativeNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n    true\n    > bool = isNegativeNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNegativeNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray\n","isNegativeNumberArray.primitives":"\nisNegativeNumberArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive negative\n    numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive negative numbers.\n\n    Examples\n    --------\n    > var bool = isNegativeNumberArray.primitives( [ -1.0, -10.0 ] )\n    true\n    > bool = isNegativeNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNegativeNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false","isNegativeNumberArray.objects":"\nisNegativeNumberArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having negative number values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having negative number values.\n\n    Examples\n    --------\n    > var bool = isNegativeNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n    true\n    > bool = isNegativeNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNegativeNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray","isNegativeZero":"\nisNegativeZero( value )\n    Tests if a value is negative zero.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is negative zero.\n\n    Examples\n    --------\n    > var bool = isNegativeZero( -0.0 )\n    true\n    > bool = isNegativeZero( new Number( -0.0 ) )\n    true\n    > bool = isNegativeZero( -3.14 )\n    false\n    > bool = isNegativeZero( 0.0 )\n    false\n    > bool = isNegativeZero( null )\n    false\n\n\nisNegativeZero.isPrimitive( value )\n    Tests if a value is a number primitive equal to negative zero.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number primitive equal to\n        negative zero.\n\n    Examples\n    --------\n    > var bool = isNegativeZero.isPrimitive( -0.0 )\n    true\n    > bool = isNegativeZero.isPrimitive( new Number( -0.0 ) )\n    false\n\n\nisNegativeZero.isObject( value )\n    Tests if a value is a number object having a value equal to negative zero.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number object having a value\n        equal to negative zero.\n\n    Examples\n    --------\n    > var bool = isNegativeZero.isObject( -0.0 )\n    false\n    > bool = isNegativeZero.isObject( new Number( -0.0 ) )\n    true\n\n    See Also\n    --------\n    isNumber, isPositiveZero\n","isNegativeZero.isPrimitive":"\nisNegativeZero.isPrimitive( value )\n    Tests if a value is a number primitive equal to negative zero.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number primitive equal to\n        negative zero.\n\n    Examples\n    --------\n    > var bool = isNegativeZero.isPrimitive( -0.0 )\n    true\n    > bool = isNegativeZero.isPrimitive( new Number( -0.0 ) )\n    false","isNegativeZero.isObject":"\nisNegativeZero.isObject( value )\n    Tests if a value is a number object having a value equal to negative zero.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number object having a value\n        equal to negative zero.\n\n    Examples\n    --------\n    > var bool = isNegativeZero.isObject( -0.0 )\n    false\n    > bool = isNegativeZero.isObject( new Number( -0.0 ) )\n    true\n\n    See Also\n    --------\n    isNumber, isPositiveZero","isNodeBuiltin":"\nisNodeBuiltin( str )\n    Tests whether a string matches a Node.js built-in module name.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a string matches a Node.js built-in module\n        name.\n\n    Examples\n    --------\n    > var bool = isNodeBuiltin( 'cluster' )\n    true\n    > bool = isNodeBuiltin( 'crypto' )\n    true\n    > bool = isNodeBuiltin( 'fs-extra' )\n    false\n    > bool = isNodeBuiltin( '' )\n    false\n\n","isNodeDuplexStreamLike":"\nisNodeDuplexStreamLike( value )\n    Tests if a value is Node duplex stream-like.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is Node duplex stream-like.\n\n    Examples\n    --------\n    > var Stream = require( 'stream' ).Duplex;\n    > s = new Stream();\n    > var bool = isNodeDuplexStreamLike( s )\n    true\n    > bool = isNodeDuplexStreamLike( {} )\n    false\n\n    See Also\n    --------\n    isNodeStreamLike\n","isNodeReadableStreamLike":"\nisNodeReadableStreamLike( value )\n    Tests if a value is Node readable stream-like.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is Node readable stream-like.\n\n    Examples\n    --------\n    > var Stream = require( 'stream' ).Readable;\n    > s = new Stream();\n    > var bool = isNodeReadableStreamLike( s )\n    true\n    > bool = isNodeReadableStreamLike( {} )\n    false\n\n    See Also\n    --------\n    isNodeStreamLike\n","isNodeREPL":"\nisNodeREPL()\n    Returns a boolean indicating if running in a Node.js REPL environment.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if running in a Node.js REPL environment.\n\n    Examples\n    --------\n    > var bool = isNodeREPL()\n    <boolean>\n\n","isNodeStreamLike":"\nisNodeStreamLike( value )\n    Tests if a value is Node stream-like.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is Node stream-like.\n\n    Examples\n    --------\n    > var Stream = require( 'stream' ).Stream;\n    > s = new Stream();\n    > var bool = isNodeStreamLike( s )\n    true\n    > bool = isNodeStreamLike( {} )\n    false\n\n","isNodeTransformStreamLike":"\nisNodeTransformStreamLike( value )\n    Tests if a value is Node transform stream-like.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is Node transform stream-like.\n\n    Examples\n    --------\n    > var Stream = require( 'stream' ).Transform;\n    > s = new Stream();\n    > var bool = isNodeTransformStreamLike( s )\n    true\n    > bool = isNodeTransformStreamLike( {} )\n    false\n\n    See Also\n    --------\n    isNodeStreamLike\n","isNodeWritableStreamLike":"\nisNodeWritableStreamLike( value )\n    Tests if a value is Node writable stream-like.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is Node writable stream-like.\n\n    Examples\n    --------\n    > var Stream = require( 'stream' ).Writable;\n    > s = new Stream();\n    > var bool = isNodeWritableStreamLike( s )\n    true\n    > bool = isNodeWritableStreamLike( {} )\n    false\n\n    See Also\n    --------\n    isNodeStreamLike\n","isNonConfigurableProperty":"\nisNonConfigurableProperty( value, property )\n    Tests if an object's own property is non-configurable.\n\n    A non-configurable property is a property which cannot be deleted and whose\n    descriptor cannot be changed.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own property is non-configurable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = true;\n    > desc.writable = true;\n    > desc.value = 'beep';\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isNonConfigurableProperty( obj, 'boop' )\n    false\n    > bool = isNonConfigurableProperty( obj, 'beep' )\n    true\n\n    See Also\n    --------\n    isConfigurableProperty, isEnumerableProperty, isNonConfigurablePropertyIn, isNonEnumerableProperty, isReadableProperty, isWritableProperty\n","isNonConfigurablePropertyIn":"\nisNonConfigurablePropertyIn( value, property )\n    Tests if an object's own or inherited property is non-configurable.\n\n    A non-configurable property is a property which cannot be deleted and whose\n    descriptor cannot be changed.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own or inherited property is non-\n        configurable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = true;\n    > desc.writable = true;\n    > desc.value = true;\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isNonConfigurablePropertyIn( obj, 'boop' )\n    false\n    > bool = isNonConfigurablePropertyIn( obj, 'beep' )\n    true\n\n    See Also\n    --------\n    isConfigurablePropertyIn, isEnumerablePropertyIn, isNonConfigurableProperty, isNonEnumerablePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isNonEnumerableProperty":"\nisNonEnumerableProperty( value, property )\n    Tests if an object's own property is non-enumerable.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own property is non-enumerable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.writable = true;\n    > desc.value = 'beep';\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isNonEnumerableProperty( obj, 'boop' )\n    false\n    > bool = isNonEnumerableProperty( obj, 'beep' )\n    true\n\n    See Also\n    --------\n    isConfigurableProperty, isEnumerableProperty, isNonConfigurableProperty, isNonEnumerablePropertyIn, isReadableProperty, isWritableProperty\n","isNonEnumerablePropertyIn":"\nisNonEnumerablePropertyIn( value, property )\n    Tests if an object's own or inherited property is non-enumerable.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own or inherited property is non-\n        enumerable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = true;\n    > desc.enumerable = false;\n    > desc.writable = true;\n    > desc.value = true;\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isNonEnumerablePropertyIn( obj, 'boop' )\n    false\n    > bool = isNonEnumerablePropertyIn( obj, 'beep' )\n    true\n\n    See Also\n    --------\n    isConfigurablePropertyIn, isEnumerablePropertyIn, isNonConfigurablePropertyIn, isNonEnumerableProperty, isReadablePropertyIn, isWritablePropertyIn\n","isNonNegativeFinite":"\nisNonNegativeFinite( value )\n    Tests if a value is a nonnegative finite number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a nonnegative finite number.\n\n    Examples\n    --------\n    > var bool = isNonNegativeFinite( 5.0 )\n    true\n    > bool = isNonNegativeFinite( new Number( 5.0 ) )\n    true\n    > bool = isNonNegativeFinite( 3.14 )\n    true\n    > bool = isNonNegativeFinite( -5.0 )\n    false\n    > bool = isNonNegativeFinite( null )\n    false\n    > bool = isNonNegativeFinite( PINF )\n    false\n\n\nisNonNegativeFinite.isPrimitive( value )\n    Tests if a value is a number primitive having a nonnegative finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonnegative finite value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeFinite.isPrimitive( 3.0 )\n    true\n    > bool = isNonNegativeFinite.isPrimitive( new Number( 3.0 ) )\n    false\n\n\nisNonNegativeFinite.isObject( value )\n    Tests if a value is a number object having a nonnegative finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a \n        nonnegative finite value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeFinite.isObject( 3.0 )\n    false\n    > bool = isNonNegativeFinite.isObject( new Number( 3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isFinite, isNonNegativeNumber, isNumber\n","isNonNegativeFinite.isPrimitive":"\nisNonNegativeFinite.isPrimitive( value )\n    Tests if a value is a number primitive having a nonnegative finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonnegative finite value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeFinite.isPrimitive( 3.0 )\n    true\n    > bool = isNonNegativeFinite.isPrimitive( new Number( 3.0 ) )\n    false","isNonNegativeFinite.isObject":"\nisNonNegativeFinite.isObject( value )\n    Tests if a value is a number object having a nonnegative finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a \n        nonnegative finite value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeFinite.isObject( 3.0 )\n    false\n    > bool = isNonNegativeFinite.isObject( new Number( 3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isFinite, isNonNegativeNumber, isNumber","isNonNegativeInteger":"\nisNonNegativeInteger( value )\n    Tests if a value is a nonnegative integer.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a nonnegative integer.\n\n    Examples\n    --------\n    > var bool = isNonNegativeInteger( 5.0 )\n    true\n    > bool = isNonNegativeInteger( new Number( 5.0 ) )\n    true\n    > bool = isNonNegativeInteger( 3.14 )\n    false\n    > bool = isNonNegativeInteger( -5.0 )\n    false\n    > bool = isNonNegativeInteger( null )\n    false\n\n\nisNonNegativeInteger.isPrimitive( value )\n    Tests if a value is a number primitive having a nonnegative integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonnegative integer value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeInteger.isPrimitive( 3.0 )\n    true\n    > bool = isNonNegativeInteger.isPrimitive( new Number( 3.0 ) )\n    false\n\n\nisNonNegativeInteger.isObject( value )\n    Tests if a value is a number object having a nonnegative integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a nonnegative\n        integer value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeInteger.isObject( 3.0 )\n    false\n    > bool = isNonNegativeInteger.isObject( new Number( 3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger, isNonNegativeNumber, isNumber\n","isNonNegativeInteger.isPrimitive":"\nisNonNegativeInteger.isPrimitive( value )\n    Tests if a value is a number primitive having a nonnegative integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonnegative integer value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeInteger.isPrimitive( 3.0 )\n    true\n    > bool = isNonNegativeInteger.isPrimitive( new Number( 3.0 ) )\n    false","isNonNegativeInteger.isObject":"\nisNonNegativeInteger.isObject( value )\n    Tests if a value is a number object having a nonnegative integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a nonnegative\n        integer value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeInteger.isObject( 3.0 )\n    false\n    > bool = isNonNegativeInteger.isObject( new Number( 3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger, isNonNegativeNumber, isNumber","isNonNegativeIntegerArray":"\nisNonNegativeIntegerArray( value )\n    Tests if a value is an array-like object containing only nonnegative\n    integers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        nonnegative integers.\n\n    Examples\n    --------\n    > var bool = isNonNegativeIntegerArray( [ 3.0, new Number(3.0) ] )\n    true\n    > bool = isNonNegativeIntegerArray( [ 3.0, '3.0' ] )\n    false\n\n\nisNonNegativeIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only nonnegative\n    primitive integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        nonnegative primitive integer values.\n\n    Examples\n    --------\n    > var bool = isNonNegativeIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n    true\n    > bool = isNonNegativeIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n    false\n\n\nisNonNegativeIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having nonnegative integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having nonnegative integer values.\n\n    Examples\n    --------\n    > var bool = isNonNegativeIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n    true\n    > bool = isNonNegativeIntegerArray.objects( [ 1.0, 0.0, 10.0 ] )\n    false\n    > bool = isNonNegativeIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray\n","isNonNegativeIntegerArray.primitives":"\nisNonNegativeIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only nonnegative\n    primitive integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        nonnegative primitive integer values.\n\n    Examples\n    --------\n    > var bool = isNonNegativeIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n    true\n    > bool = isNonNegativeIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n    false","isNonNegativeIntegerArray.objects":"\nisNonNegativeIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having nonnegative integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having nonnegative integer values.\n\n    Examples\n    --------\n    > var bool = isNonNegativeIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n    true\n    > bool = isNonNegativeIntegerArray.objects( [ 1.0, 0.0, 10.0 ] )\n    false\n    > bool = isNonNegativeIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray","isNonNegativeNumber":"\nisNonNegativeNumber( value )\n    Tests if a value is a nonnegative number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a nonnegative number.\n\n    Examples\n    --------\n    > var bool = isNonNegativeNumber( 5.0 )\n    true\n    > bool = isNonNegativeNumber( new Number( 5.0 ) )\n    true\n    > bool = isNonNegativeNumber( 3.14 )\n    true\n    > bool = isNonNegativeNumber( -5.0 )\n    false\n    > bool = isNonNegativeNumber( null )\n    false\n\n\nisNonNegativeNumber.isPrimitive( value )\n    Tests if a value is a number primitive having a nonnegative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonnegative value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeNumber.isPrimitive( 3.0 )\n    true\n    > bool = isNonNegativeNumber.isPrimitive( new Number( 3.0 ) )\n    false\n\n\nisNonNegativeNumber.isObject( value )\n    Tests if a value is a number object having a nonnegative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a nonnegative\n        value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeNumber.isObject( 3.0 )\n    false\n    > bool = isNonNegativeNumber.isObject( new Number( 3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isNonNegativeFinite, isNonNegativeInteger, isNumber\n","isNonNegativeNumber.isPrimitive":"\nisNonNegativeNumber.isPrimitive( value )\n    Tests if a value is a number primitive having a nonnegative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonnegative value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeNumber.isPrimitive( 3.0 )\n    true\n    > bool = isNonNegativeNumber.isPrimitive( new Number( 3.0 ) )\n    false","isNonNegativeNumber.isObject":"\nisNonNegativeNumber.isObject( value )\n    Tests if a value is a number object having a nonnegative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a nonnegative\n        value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeNumber.isObject( 3.0 )\n    false\n    > bool = isNonNegativeNumber.isObject( new Number( 3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isNonNegativeFinite, isNonNegativeInteger, isNumber","isNonNegativeNumberArray":"\nisNonNegativeNumberArray( value )\n    Tests if a value is an array-like object containing only nonnegative\n    numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        nonnegative numbers.\n\n    Examples\n    --------\n    > var bool = isNonNegativeNumberArray( [ 3.0, new Number(3.0) ] )\n    true\n    > bool = isNonNegativeNumberArray( [ 3.0, '3.0' ] )\n    false\n\n\nisNonNegativeNumberArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive\n    nonnegative numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive nonnegative numbers.\n\n    Examples\n    --------\n    > var bool = isNonNegativeNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n    true\n    > bool = isNonNegativeNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n    false\n\n\nisNonNegativeNumberArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having nonnegative number values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having nonnegative number values.\n\n    Examples\n    --------\n    > var bool = isNonNegativeNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n    true\n    > bool = isNonNegativeNumberArray.objects( [ 1.0, 0.0, 10.0 ] )\n    false\n    > bool = isNonNegativeNumberArray.objects( [ 3.0, new Number(1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray\n","isNonNegativeNumberArray.primitives":"\nisNonNegativeNumberArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive\n    nonnegative numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive nonnegative numbers.\n\n    Examples\n    --------\n    > var bool = isNonNegativeNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n    true\n    > bool = isNonNegativeNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n    false","isNonNegativeNumberArray.objects":"\nisNonNegativeNumberArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having nonnegative number values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having nonnegative number values.\n\n    Examples\n    --------\n    > var bool = isNonNegativeNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n    true\n    > bool = isNonNegativeNumberArray.objects( [ 1.0, 0.0, 10.0 ] )\n    false\n    > bool = isNonNegativeNumberArray.objects( [ 3.0, new Number(1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray","isNonPositiveFinite":"\nisNonPositiveFinite( value )\n    Tests if a value is a nonpositive finite number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a nonpositive finite number.\n\n    Examples\n    --------\n    > var bool = isNonPositiveFinite( -5.0 )\n    true\n    > bool = isNonPositiveFinite( new Number( -5.0 ) )\n    true\n    > bool = isNonPositiveFinite( -3.14 )\n    true\n    > bool = isNonPositiveFinite( 5.0 )\n    false\n    > bool = isNonPositiveFinite( null )\n    false\n\n\nisNonPositiveFinite.isPrimitive( value )\n    Tests if a value is a number primitive having a nonpositive finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonpositive finite value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveFinite.isPrimitive( -3.0 )\n    true\n    > bool = isNonPositiveFinite.isPrimitive( new Number( -3.0 ) )\n    false\n\n\nisNonPositiveFinite.isObject( value )\n    Tests if a value is a number object having a nonpositive finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a nonpositive\n        finite value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveFinite.isObject( -3.0 )\n    false\n    > bool = isNonPositiveFinite.isObject( new Number( -3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isFinite, isNonPositiveNumber\n","isNonPositiveFinite.isPrimitive":"\nisNonPositiveFinite.isPrimitive( value )\n    Tests if a value is a number primitive having a nonpositive finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonpositive finite value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveFinite.isPrimitive( -3.0 )\n    true\n    > bool = isNonPositiveFinite.isPrimitive( new Number( -3.0 ) )\n    false","isNonPositiveFinite.isObject":"\nisNonPositiveFinite.isObject( value )\n    Tests if a value is a number object having a nonpositive finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a nonpositive\n        finite value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveFinite.isObject( -3.0 )\n    false\n    > bool = isNonPositiveFinite.isObject( new Number( -3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isFinite, isNonPositiveNumber","isNonPositiveInteger":"\nisNonPositiveInteger( value )\n    Tests if a value is a nonpositive integer.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a nonpositive integer.\n\n    Examples\n    --------\n    > var bool = isNonPositiveInteger( -5.0 )\n    true\n    > bool = isNonPositiveInteger( new Number( -5.0 ) )\n    true\n    > bool = isNonPositiveInteger( 5.0 )\n    false\n    > bool = isNonPositiveInteger( -3.14 )\n    false\n    > bool = isNonPositiveInteger( null )\n    false\n\n\nisNonPositiveInteger.isPrimitive( value )\n    Tests if a value is a number primitive having a nonpositive integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonpositive integer value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveInteger.isPrimitive( -3.0 )\n    true\n    > bool = isNonPositiveInteger.isPrimitive( new Number( -3.0 ) )\n    false\n\n\nisNonPositiveInteger.isObject( value )\n    Tests if a value is a number object having a nonpositive integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a nonpositive\n        integer value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveInteger.isObject( -3.0 )\n    false\n    > bool = isNonPositiveInteger.isObject( new Number( -3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger\n","isNonPositiveInteger.isPrimitive":"\nisNonPositiveInteger.isPrimitive( value )\n    Tests if a value is a number primitive having a nonpositive integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonpositive integer value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveInteger.isPrimitive( -3.0 )\n    true\n    > bool = isNonPositiveInteger.isPrimitive( new Number( -3.0 ) )\n    false","isNonPositiveInteger.isObject":"\nisNonPositiveInteger.isObject( value )\n    Tests if a value is a number object having a nonpositive integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a nonpositive\n        integer value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveInteger.isObject( -3.0 )\n    false\n    > bool = isNonPositiveInteger.isObject( new Number( -3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger","isNonPositiveIntegerArray":"\nisNonPositiveIntegerArray( value )\n    Tests if a value is an array-like object containing only nonpositive\n    integers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        nonpositive integers.\n\n    Examples\n    --------\n    > var bool = isNonPositiveIntegerArray( [ -3.0, new Number(-3.0) ] )\n    true\n    > bool = isNonPositiveIntegerArray( [ -3.0, '-3.0' ] )\n    false\n\n\nisNonPositiveIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only nonpositive\n    primitive integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        nonpositive primitive integer values.\n\n    Examples\n    --------\n    > var bool = isNonPositiveIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n    true\n    > bool = isNonPositiveIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false\n\n\nisNonPositiveIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having nonpositive integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having nonpositive integer values.\n\n    Examples\n    --------\n    > var bool = isNonPositiveIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n    true\n    > bool = isNonPositiveIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNonPositiveIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray\n","isNonPositiveIntegerArray.primitives":"\nisNonPositiveIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only nonpositive\n    primitive integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        nonpositive primitive integer values.\n\n    Examples\n    --------\n    > var bool = isNonPositiveIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n    true\n    > bool = isNonPositiveIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false","isNonPositiveIntegerArray.objects":"\nisNonPositiveIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having nonpositive integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having nonpositive integer values.\n\n    Examples\n    --------\n    > var bool = isNonPositiveIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n    true\n    > bool = isNonPositiveIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNonPositiveIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray","isNonPositiveNumber":"\nisNonPositiveNumber( value )\n    Tests if a value is a nonpositive number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a nonpositive number.\n\n    Examples\n    --------\n    > var bool = isNonPositiveNumber( -5.0 )\n    true\n    > bool = isNonPositiveNumber( new Number( -5.0 ) )\n    true\n    > bool = isNonPositiveNumber( -3.14 )\n    true\n    > bool = isNonPositiveNumber( 5.0 )\n    false\n    > bool = isNonPositiveNumber( null )\n    false\n\n\nisNonPositiveNumber.isPrimitive( value )\n    Tests if a value is a number primitive having a nonpositive value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonpositive value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveNumber.isPrimitive( -3.0 )\n    true\n    > bool = isNonPositiveNumber.isPrimitive( new Number( -3.0 ) )\n    false\n\n\nisNonPositiveNumber.isObject( value )\n    Tests if a value is a number object having a nonpositive value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a nonpositive\n        value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveNumber.isObject( -3.0 )\n    false\n    > bool = isNonPositiveNumber.isObject( new Number( -3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isNumber\n","isNonPositiveNumber.isPrimitive":"\nisNonPositiveNumber.isPrimitive( value )\n    Tests if a value is a number primitive having a nonpositive value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonpositive value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveNumber.isPrimitive( -3.0 )\n    true\n    > bool = isNonPositiveNumber.isPrimitive( new Number( -3.0 ) )\n    false","isNonPositiveNumber.isObject":"\nisNonPositiveNumber.isObject( value )\n    Tests if a value is a number object having a nonpositive value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a nonpositive\n        value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveNumber.isObject( -3.0 )\n    false\n    > bool = isNonPositiveNumber.isObject( new Number( -3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isNumber","isNonPositiveNumberArray":"\nisNonPositiveNumberArray( value )\n    Tests if a value is an array-like object containing only nonpositive\n    numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        nonpositive numbers.\n\n    Examples\n    --------\n    > var bool = isNonPositiveNumberArray( [ -3.0, new Number(-3.0) ] )\n    true\n    > bool = isNonPositiveNumberArray( [ -3.0, '-3.0' ] )\n    false\n\n\nisNonPositiveNumberArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive\n    nonpositive numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive nonpositive numbers.\n\n    Examples\n    --------\n    > var bool = isNonPositiveNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n    true\n    > bool = isNonPositiveNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false\n\n\nisNonPositiveNumberArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having nonpositive number values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having nonpositive number values.\n\n    Examples\n    --------\n    > var bool = isNonPositiveNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n    true\n    > bool = isNonPositiveNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNonPositiveNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray\n","isNonPositiveNumberArray.primitives":"\nisNonPositiveNumberArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive\n    nonpositive numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive nonpositive numbers.\n\n    Examples\n    --------\n    > var bool = isNonPositiveNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n    true\n    > bool = isNonPositiveNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false","isNonPositiveNumberArray.objects":"\nisNonPositiveNumberArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having nonpositive number values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having nonpositive number values.\n\n    Examples\n    --------\n    > var bool = isNonPositiveNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n    true\n    > bool = isNonPositiveNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNonPositiveNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray","isNonSymmetricMatrix":"\nisNonSymmetricMatrix( value )\n    Tests if a value is a non-symmetric matrix.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a non-symmetric matrix.\n\n    Examples\n    --------\n    > var buf = [ 1, 2, 3, 4 ];\n    > var sh = [ 2, 2 ];\n    > var st = [ 2, 1 ];\n    > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n    > var bool = isNonSymmetricMatrix( M )\n    true\n    > bool = isNonSymmetricMatrix( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isNonSymmetricMatrix( 3.14 )\n    false\n    > bool = isNonSymmetricMatrix( {} )\n    false\n\n    See Also\n    --------\n    isMatrixLike, isSquareMatrix, isSymmetricMatrix\n","isNull":"\nisNull( value )\n    Tests if a value is null.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is null.\n\n    Examples\n    --------\n    > var bool = isNull( null )\n    true\n    > bool = isNull( true )\n    false\n\n    See Also\n    --------\n    isUndefined, isUndefinedOrNull\n","isNullArray":"\nisNullArray( value )\n    Tests if a value is an array-like object containing only null values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        null values.\n\n    Examples\n    --------\n    > var bool = isNullArray( [ null, null, null ] )\n    true\n    > bool = isNullArray( [ NaN, 2, null ] )\n    false\n\n    See Also\n    --------\n    isArray, isNull\n","isNumber":"\nisNumber( value )\n    Tests if a value is a number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number.\n\n    Examples\n    --------\n    > var bool = isNumber( 3.14 )\n    true\n    > bool = isNumber( new Number( 3.14 ) )\n    true\n    > bool = isNumber( NaN )\n    true\n    > bool = isNumber( null )\n    false\n\n\nisNumber.isPrimitive( value )\n    Tests if a value is a number primitive.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive.\n\n    Examples\n    --------\n    > var bool = isNumber.isPrimitive( 3.14 )\n    true\n    > bool = isNumber.isPrimitive( NaN )\n    true\n    > bool = isNumber.isPrimitive( new Number( 3.14 ) )\n    false\n\n\nisNumber.isObject( value )\n    Tests if a value is a `Number` object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a `Number` object.\n\n    Examples\n    --------\n    > var bool = isNumber.isObject( 3.14 )\n    false\n    > bool = isNumber.isObject( new Number( 3.14 ) )\n    true\n\n","isNumber.isPrimitive":"\nisNumber.isPrimitive( value )\n    Tests if a value is a number primitive.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive.\n\n    Examples\n    --------\n    > var bool = isNumber.isPrimitive( 3.14 )\n    true\n    > bool = isNumber.isPrimitive( NaN )\n    true\n    > bool = isNumber.isPrimitive( new Number( 3.14 ) )\n    false","isNumber.isObject":"\nisNumber.isObject( value )\n    Tests if a value is a `Number` object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a `Number` object.\n\n    Examples\n    --------\n    > var bool = isNumber.isObject( 3.14 )\n    false\n    > bool = isNumber.isObject( new Number( 3.14 ) )\n    true","isNumberArray":"\nisNumberArray( value )\n    Tests if a value is an array-like object containing only numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        numbers.\n\n    Examples\n    --------\n    > var bool = isNumberArray( [ 1, 2, 3 ] )\n    true\n    > bool = isNumberArray( [ '1', 2, 3 ] )\n    false\n\n\nisNumberArray.primitives( value )\n    Tests if a value is an array-like object containing only number primitives.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number primitives.\n\n    Examples\n    --------\n    > var arr = [ 1, 2, 3 ];\n    > var bool = isNumberArray.primitives( arr )\n    true\n    > arr = [ 1, new Number( 2 ) ];\n    > bool = isNumberArray.primitives( arr )\n    false\n\n\nisNumberArray.objects( value )\n    Tests if a value is an array-like object containing only `Number` objects.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        `Number` objects.\n\n    Examples\n    --------\n    > var arr = [ new Number( 1 ), new Number( 2 ) ];\n    > var bool = isNumberArray.objects( arr )\n    true\n    > arr = [ new Number( 1 ), 2 ];\n    > bool = isNumberArray.objects( arr )\n    false\n\n    See Also\n    --------\n    isArray, isNumber, isNumericArray\n","isNumberArray.primitives":"\nisNumberArray.primitives( value )\n    Tests if a value is an array-like object containing only number primitives.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number primitives.\n\n    Examples\n    --------\n    > var arr = [ 1, 2, 3 ];\n    > var bool = isNumberArray.primitives( arr )\n    true\n    > arr = [ 1, new Number( 2 ) ];\n    > bool = isNumberArray.primitives( arr )\n    false","isNumberArray.objects":"\nisNumberArray.objects( value )\n    Tests if a value is an array-like object containing only `Number` objects.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        `Number` objects.\n\n    Examples\n    --------\n    > var arr = [ new Number( 1 ), new Number( 2 ) ];\n    > var bool = isNumberArray.objects( arr )\n    true\n    > arr = [ new Number( 1 ), 2 ];\n    > bool = isNumberArray.objects( arr )\n    false\n\n    See Also\n    --------\n    isArray, isNumber, isNumericArray","isNumericArray":"\nisNumericArray( value )\n    Tests if a value is a numeric array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is a numeric array.\n\n    Examples\n    --------\n    > var bool = isNumericArray( new Int8Array( 10 ) )\n    true\n    > bool = isNumericArray( [ 1, 2, 3 ] )\n    true\n    > bool = isNumericArray( [ '1', '2', '3' ] )\n    false\n\n    See Also\n    --------\n    isArray, isNumberArray, isTypedArray\n\n","isObject":"\nisObject( value )\n    Tests if a value is an object; e.g., `{}`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an object.\n\n    Examples\n    --------\n    > var bool = isObject( {} )\n    true\n    > bool = isObject( true )\n    false\n\n    See Also\n    --------\n    isObjectLike, isPlainObject\n","isObjectArray":"\nisObjectArray( value )\n    Tests if a value is an array-like object containing only objects.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        objects.\n\n    Examples\n    --------\n    > var bool = isObjectArray( [ {}, new Number(3.0) ] )\n    true\n    > bool = isObjectArray( [ {}, { 'beep': 'boop' } ] )\n    true\n    > bool = isObjectArray( [ {}, '3.0' ] )\n    false\n\n    See Also\n    --------\n    isArray, isObject\n","isObjectLike":"\nisObjectLike( value )\n    Tests if a value is object-like.\n\n    Return values are the same as would be obtained using the built-in `typeof`\n    operator except that `null` is not considered an object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is object-like.\n\n    Examples\n    --------\n    > var bool = isObjectLike( {} )\n    true\n    > bool = isObjectLike( [] )\n    true\n    > bool = isObjectLike( null )\n    false\n\n    See Also\n    --------\n    isObject, isPlainObject\n","isOdd":"\nisOdd( value )\n    Tests if a value is an odd number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an odd number.\n\n    Examples\n    --------\n    > var bool = isOdd( 5.0 )\n    true\n    > bool = isOdd( new Number( 5.0 ) )\n    true\n    > bool = isOdd( 4.0 )\n    false\n    > bool = isOdd( new Number( 4.0 ) )\n    false\n    > bool = isOdd( -3.14 )\n    false\n    > bool = isOdd( null )\n    false\n\nisOdd.isPrimitive( value )\n    Tests if a value is a number primitive that is an odd number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive that is an odd\n        number.\n\n    Examples\n    --------\n    > var bool = isOdd.isPrimitive( -5.0 )\n    true\n    > bool = isOdd.isPrimitive( new Number( -5.0 ) )\n    false\n\n\nisOdd.isObject( value )\n    Tests if a value is a number object that has an odd number value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object that has an odd\n        number value.\n\n    Examples\n    --------\n    > var bool = isOdd.isObject( 5.0 )\n    false\n    > bool = isOdd.isObject( new Number( 5.0 ) )\n    true\n\n    See Also\n    --------\n    isEven\n","isOdd.isPrimitive":"\nisOdd.isPrimitive( value )\n    Tests if a value is a number primitive that is an odd number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive that is an odd\n        number.\n\n    Examples\n    --------\n    > var bool = isOdd.isPrimitive( -5.0 )\n    true\n    > bool = isOdd.isPrimitive( new Number( -5.0 ) )\n    false","isOdd.isObject":"\nisOdd.isObject( value )\n    Tests if a value is a number object that has an odd number value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object that has an odd\n        number value.\n\n    Examples\n    --------\n    > var bool = isOdd.isObject( 5.0 )\n    false\n    > bool = isOdd.isObject( new Number( 5.0 ) )\n    true\n\n    See Also\n    --------\n    isEven","isoWeeksInYear":"\nisoWeeksInYear( [year] )\n    Returns the number of ISO weeks in a year according to the Gregorian\n    calendar.\n\n    By default, the function returns the number of ISO weeks in the current year\n    (according to local time). To determine the number of ISO weeks for a\n    particular year, provide either a year or a `Date` object.\n\n    Parameters\n    ----------\n    year: integer (optional)\n        Year.\n\n    Returns\n    -------\n    out: integer\n        Number of ISO weeks in a year.\n\n    Examples\n    --------\n    > var num = isoWeeksInYear()\n    <number>\n    > num = isoWeeksInYear( 2015 )\n    53\n    > num = isoWeeksInYear( 2017 )\n    52\n\n","isPascalcase":"\nisPascalcase( value )\n    Tests if a value is a string in Pascal case.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a string in Pascal case.\n\n    Examples\n    --------\n    > var bool = isPascalcase( 'HelloWorld' )\n    true\n    > bool = isPascalcase( 'hello-world' )\n    false\n\n    See Also\n    --------\n    isString","isPersymmetricMatrix":"\nisPersymmetricMatrix( value )\n    Tests if a value is a square matrix which is symmetric about its\n    antidiagonal.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a persymmetric matrix.\n\n    Examples\n    --------\n    > var buf = [ 1, 2, 3, 1 ];\n    > var sh = [ 2, 2 ];\n    > var st = [ 2, 1 ];\n    > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n    > var bool = isPersymmetricMatrix( M )\n    true\n    > bool = isPersymmetricMatrix( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isPersymmetricMatrix( 3.14 )\n    false\n    > bool = isPersymmetricMatrix( {} )\n    false\n\n    See Also\n    --------\n    isMatrixLike, isSquareMatrix, isSymmetricMatrix\n","isPlainObject":"\nisPlainObject( value )\n    Tests if a value is a plain object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a plain object.\n\n    Examples\n    --------\n    > var bool = isPlainObject( {} )\n    true\n    > bool = isPlainObject( null )\n    false\n\n    See Also\n    --------\n    isObject\n","isPlainObjectArray":"\nisPlainObjectArray( value )\n    Tests if a value is an array-like object containing only plain objects.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        plain objects.\n\n    Examples\n    --------\n    > var bool = isPlainObjectArray( [ {}, { 'beep': 'boop' } ] )\n    true\n    > bool = isPlainObjectArray( [ {}, new Number(3.0) ] )\n    false\n    > bool = isPlainObjectArray( [ {}, '3.0' ] )\n    false\n\n    See Also\n    --------\n    isArray, isPlainObject\n","isPositiveFinite":"\nisPositiveFinite( value )\n    Tests if a value is a positive finite number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a positive finite number.\n\n    Examples\n    --------\n    > var bool = isPositiveFinite( 5.0 )\n    true\n    > bool = isPositiveFinite( new Number( 5.0 ) )\n    true\n    > bool = isPositiveFinite( 3.14 )\n    true\n    > bool = isPositiveFinite( -5.0 )\n    false\n    > var bool = isPositiveFinite( 1.0/0.0 )\n    false\n    > bool = isPositiveFinite( new Number( 1.0/0.0 ) )\n    false\n    > bool = isPositiveFinite( null )\n    false\n\n\nisPositiveFinite.isPrimitive( value )\n    Tests if a value is a number primitive having a positive finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is a number primitive having a positive\n        finite value.\n\n    Examples\n    --------\n    > var bool = isPositiveFinite.isPrimitive( 3.0 )\n    true\n    > var bool = isPositiveFinite.isPrimitive( 1.0/0.0 )\n    false\n    > bool = isPositiveFinite.isPrimitive( new Number( 3.0 ) )\n    false\n\n\nisPositiveFinite.isObject( value )\n    Tests if a value is a number object having a positive finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a positive\n        finite value.\n\n    Examples\n    --------\n    > var bool = isPositiveFinite.isObject( 3.0 )\n    false\n    > bool = isPositiveFinite.isObject( new Number( 3.0 ) )\n    true\n    > bool = isPositiveFinite.isObject( new Number( 1.0/0.0 ) )\n    false\n\n\n    See Also\n    --------\n    isFinite, isPositiveNumber\n","isPositiveFinite.isPrimitive":"\nisPositiveFinite.isPrimitive( value )\n    Tests if a value is a number primitive having a positive finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is a number primitive having a positive\n        finite value.\n\n    Examples\n    --------\n    > var bool = isPositiveFinite.isPrimitive( 3.0 )\n    true\n    > var bool = isPositiveFinite.isPrimitive( 1.0/0.0 )\n    false\n    > bool = isPositiveFinite.isPrimitive( new Number( 3.0 ) )\n    false","isPositiveFinite.isObject":"\nisPositiveFinite.isObject( value )\n    Tests if a value is a number object having a positive finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a positive\n        finite value.\n\n    Examples\n    --------\n    > var bool = isPositiveFinite.isObject( 3.0 )\n    false\n    > bool = isPositiveFinite.isObject( new Number( 3.0 ) )\n    true\n    > bool = isPositiveFinite.isObject( new Number( 1.0/0.0 ) )\n    false\n\n\n    See Also\n    --------\n    isFinite, isPositiveNumber","isPositiveInteger":"\nisPositiveInteger( value )\n    Tests if a value is a positive integer.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a positive integer.\n\n    Examples\n    --------\n    > var bool = isPositiveInteger( 5.0 )\n    true\n    > bool = isPositiveInteger( new Number( 5.0 ) )\n    true\n    > bool = isPositiveInteger( 3.14 )\n    false\n    > bool = isPositiveInteger( -5.0 )\n    false\n    > bool = isPositiveInteger( null )\n    false\n\n\nisPositiveInteger.isPrimitive( value )\n    Tests if a value is a number primitive having a positive integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        positive integer value.\n\n    Examples\n    --------\n    > var bool = isPositiveInteger.isPrimitive( 3.0 )\n    true\n    > bool = isPositiveInteger.isPrimitive( new Number( 3.0 ) )\n    false\n\n\nisPositiveInteger.isObject( value )\n    Tests if a value is a number object having a positive integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a positive\n        integer value.\n\n    Examples\n    --------\n    > var bool = isPositiveInteger.isObject( 3.0 )\n    false\n    > bool = isPositiveInteger.isObject( new Number( 3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger\n","isPositiveInteger.isPrimitive":"\nisPositiveInteger.isPrimitive( value )\n    Tests if a value is a number primitive having a positive integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        positive integer value.\n\n    Examples\n    --------\n    > var bool = isPositiveInteger.isPrimitive( 3.0 )\n    true\n    > bool = isPositiveInteger.isPrimitive( new Number( 3.0 ) )\n    false","isPositiveInteger.isObject":"\nisPositiveInteger.isObject( value )\n    Tests if a value is a number object having a positive integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a positive\n        integer value.\n\n    Examples\n    --------\n    > var bool = isPositiveInteger.isObject( 3.0 )\n    false\n    > bool = isPositiveInteger.isObject( new Number( 3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger","isPositiveIntegerArray":"\nisPositiveIntegerArray( value )\n    Tests if a value is an array-like object containing only positive integers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        positive integers.\n\n    Examples\n    --------\n    > var bool = isPositiveIntegerArray( [ 3.0, new Number(3.0) ] )\n    true\n    > bool = isPositiveIntegerArray( [ 3.0, '3.0' ] )\n    false\n\n\nisPositiveIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only positive primitive\n    integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        positive primitive integer values.\n\n    Examples\n    --------\n    > var bool = isPositiveIntegerArray.primitives( [ 1.0, 10.0 ] )\n    true\n    > bool = isPositiveIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n    false\n    > bool = isPositiveIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n    false\n\n\nisPositiveIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having positive integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having positive integer values.\n\n    Examples\n    --------\n    > var bool = isPositiveIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n    true\n    > bool = isPositiveIntegerArray.objects( [ 1.0, 2.0, 10.0 ] )\n    false\n    > bool = isPositiveIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray, isInteger, isPositiveInteger\n","isPositiveIntegerArray.primitives":"\nisPositiveIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only positive primitive\n    integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        positive primitive integer values.\n\n    Examples\n    --------\n    > var bool = isPositiveIntegerArray.primitives( [ 1.0, 10.0 ] )\n    true\n    > bool = isPositiveIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n    false\n    > bool = isPositiveIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n    false","isPositiveIntegerArray.objects":"\nisPositiveIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having positive integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having positive integer values.\n\n    Examples\n    --------\n    > var bool = isPositiveIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n    true\n    > bool = isPositiveIntegerArray.objects( [ 1.0, 2.0, 10.0 ] )\n    false\n    > bool = isPositiveIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray, isInteger, isPositiveInteger","isPositiveNumber":"\nisPositiveNumber( value )\n    Tests if a value is a positive number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a positive number.\n\n    Examples\n    --------\n    > var bool = isPositiveNumber( 5.0 )\n    true\n    > bool = isPositiveNumber( new Number( 5.0 ) )\n    true\n    > bool = isPositiveNumber( 3.14 )\n    true\n    > bool = isPositiveNumber( -5.0 )\n    false\n    > bool = isPositiveNumber( null )\n    false\n\n\nisPositiveNumber.isPrimitive( value )\n    Tests if a value is a number primitive having a positive value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a positive\n        value.\n\n    Examples\n    --------\n    > var bool = isPositiveNumber.isPrimitive( 3.0 )\n    true\n    > bool = isPositiveNumber.isPrimitive( new Number( 3.0 ) )\n    false\n\n\nisPositiveNumber.isObject( value )\n    Tests if a value is a number object having a positive value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a positive\n        value.\n\n    Examples\n    --------\n    > var bool = isPositiveNumber.isObject( 3.0 )\n    false\n    > bool = isPositiveNumber.isObject( new Number( 3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isNumber\n","isPositiveNumber.isPrimitive":"\nisPositiveNumber.isPrimitive( value )\n    Tests if a value is a number primitive having a positive value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a positive\n        value.\n\n    Examples\n    --------\n    > var bool = isPositiveNumber.isPrimitive( 3.0 )\n    true\n    > bool = isPositiveNumber.isPrimitive( new Number( 3.0 ) )\n    false","isPositiveNumber.isObject":"\nisPositiveNumber.isObject( value )\n    Tests if a value is a number object having a positive value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a positive\n        value.\n\n    Examples\n    --------\n    > var bool = isPositiveNumber.isObject( 3.0 )\n    false\n    > bool = isPositiveNumber.isObject( new Number( 3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isNumber","isPositiveNumberArray":"\nisPositiveNumberArray( value )\n    Tests if a value is an array-like object containing only positive numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        positive numbers.\n\n    Examples\n    --------\n    > var bool = isPositiveNumberArray( [ 3.0, new Number(3.0) ] )\n    true\n    > bool = isPositiveNumberArray( [ 3.0, '3.0' ] )\n    false\n\n\nisPositiveNumberArray.primitives( value )\n    Tests if a value is an array-like object containing only positive primitive\n    number values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        positive primitive number values.\n\n    Examples\n    --------\n    > var bool = isPositiveNumberArray.primitives( [ 1.0, 10.0 ] )\n    true\n    > bool = isPositiveNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n    false\n    > bool = isPositiveNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n    false\n\n\nisPositiveNumberArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having positive values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having positive values.\n\n    Examples\n    --------\n    > var bool = isPositiveNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n    true\n    > bool = isPositiveNumberArray.objects( [ 1.0, 2.0, 10.0 ] )\n    false\n    > bool = isPositiveNumberArray.objects( [ 3.0, new Number(1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray, isNumber, isPositiveNumber\n","isPositiveNumberArray.primitives":"\nisPositiveNumberArray.primitives( value )\n    Tests if a value is an array-like object containing only positive primitive\n    number values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        positive primitive number values.\n\n    Examples\n    --------\n    > var bool = isPositiveNumberArray.primitives( [ 1.0, 10.0 ] )\n    true\n    > bool = isPositiveNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n    false\n    > bool = isPositiveNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n    false","isPositiveNumberArray.objects":"\nisPositiveNumberArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having positive values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having positive values.\n\n    Examples\n    --------\n    > var bool = isPositiveNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n    true\n    > bool = isPositiveNumberArray.objects( [ 1.0, 2.0, 10.0 ] )\n    false\n    > bool = isPositiveNumberArray.objects( [ 3.0, new Number(1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray, isNumber, isPositiveNumber","isPositiveZero":"\nisPositiveZero( value )\n    Tests if a value is positive zero.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is positive zero.\n\n    Examples\n    --------\n    > var bool = isPositiveZero( 0.0 )\n    true\n    > bool = isPositiveZero( new Number( 0.0 ) )\n    true\n    > bool = isPositiveZero( -3.14 )\n    false\n    > bool = isPositiveZero( -0.0 )\n    false\n    > bool = isPositiveZero( null )\n    false\n\n\nisPositiveZero.isPrimitive( value )\n    Tests if a value is a number primitive equal to positive zero.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number primitive equal to\n        positive zero.\n\n    Examples\n    --------\n    > var bool = isPositiveZero.isPrimitive( 0.0 )\n    true\n    > bool = isPositiveZero.isPrimitive( new Number( 0.0 ) )\n    false\n\n\nisPositiveZero.isObject( value )\n    Tests if a value is a number object having a value equal to positive zero.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number object having a value\n        equal to positive zero.\n\n    Examples\n    --------\n    > var bool = isPositiveZero.isObject( 0.0 )\n    false\n    > bool = isPositiveZero.isObject( new Number( 0.0 ) )\n    true\n\n    See Also\n    --------\n    isNumber, isNegativeZero\n","isPositiveZero.isPrimitive":"\nisPositiveZero.isPrimitive( value )\n    Tests if a value is a number primitive equal to positive zero.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number primitive equal to\n        positive zero.\n\n    Examples\n    --------\n    > var bool = isPositiveZero.isPrimitive( 0.0 )\n    true\n    > bool = isPositiveZero.isPrimitive( new Number( 0.0 ) )\n    false","isPositiveZero.isObject":"\nisPositiveZero.isObject( value )\n    Tests if a value is a number object having a value equal to positive zero.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number object having a value\n        equal to positive zero.\n\n    Examples\n    --------\n    > var bool = isPositiveZero.isObject( 0.0 )\n    false\n    > bool = isPositiveZero.isObject( new Number( 0.0 ) )\n    true\n\n    See Also\n    --------\n    isNumber, isNegativeZero","isPrime":"\nisPrime( value )\n    Tests if a value is a prime number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a prime number.\n\n    Examples\n    --------\n    > var bool = isPrime( 5.0 )\n    true\n    > bool = isPrime( new Number( 5.0 ) )\n    true\n    > bool = isPrime( 3.14 )\n    false\n    > bool = isPrime( -5.0 )\n    false\n    > bool = isPrime( null )\n    false\n\n\nisPrime.isPrimitive( value )\n    Tests if a value is a number primitive which is a prime number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a prime\n        number.\n\n    Examples\n    --------\n    > var bool = isPrime.isPrimitive( 5.0 )\n    true\n    > bool = isPrime.isPrimitive( new Number( 5.0 ) )\n    false\n\n\nisPrime.isObject( value )\n    Tests if a value is a number object having a value which is a prime number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a prime number.\n\n    Examples\n    --------\n    > var bool = isPrime.isObject( 5.0 )\n    false\n    > bool = isPrime.isObject( new Number( 5.0 ) )\n    true\n\n\n    See Also\n    --------\n    isComposite, isInteger, isNumber\n","isPrime.isPrimitive":"\nisPrime.isPrimitive( value )\n    Tests if a value is a number primitive which is a prime number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a prime\n        number.\n\n    Examples\n    --------\n    > var bool = isPrime.isPrimitive( 5.0 )\n    true\n    > bool = isPrime.isPrimitive( new Number( 5.0 ) )\n    false","isPrime.isObject":"\nisPrime.isObject( value )\n    Tests if a value is a number object having a value which is a prime number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a prime number.\n\n    Examples\n    --------\n    > var bool = isPrime.isObject( 5.0 )\n    false\n    > bool = isPrime.isObject( new Number( 5.0 ) )\n    true\n\n\n    See Also\n    --------\n    isComposite, isInteger, isNumber","isPrimitive":"\nisPrimitive( value )\n    Tests if a value is a JavaScript primitive.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a JavaScript primitive.\n\n    Examples\n    --------\n    > var bool = isPrimitive( true )\n    true\n    > bool = isPrimitive( {} )\n    false\n\n    See Also\n    --------\n    isBoxedPrimitive\n","isPrimitiveArray":"\nisPrimitiveArray( value )\n    Tests if a value is an array-like object containing only JavaScript\n    primitives.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        JavaScript primitives.\n\n    Examples\n    --------\n    > var bool = isPrimitiveArray( [ '3', 2, null ] )\n    true\n    > bool = isPrimitiveArray( [ {}, 2, 1 ] )\n    false\n    > bool = isPrimitiveArray( [ new String('abc'), '3.0' ] )\n    false\n\n    See Also\n    --------\n    isArray, isPrimitive\n","isPRNGLike":"\nisPRNGLike( value )\n    Tests if a value is PRNG-like.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is PRNG-like.\n\n    Examples\n    --------\n    > var bool = isPRNGLike( base.random.randu )\n    true\n    > bool = isPRNGLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isPRNGLike( 3.14 )\n    false\n    > bool = isPRNGLike( {} )\n    false\n\n","isProbability":"\nisProbability( value )\n    Tests if a value is a probability.\n\n    A probability is defined as a numeric value on the interval [0,1].\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a probability.\n\n    Examples\n    --------\n    > var bool = isProbability( 0.5 )\n    true\n    > bool = isProbability( new Number( 0.5 ) )\n    true\n    > bool = isProbability( 3.14 )\n    false\n    > bool = isProbability( -5.0 )\n    false\n    > bool = isProbability( null )\n    false\n\n\nisProbability.isPrimitive( value )\n    Tests if a value is a number primitive which is a probability.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a\n        probability.\n\n    Examples\n    --------\n    > var bool = isProbability.isPrimitive( 0.3 )\n    true\n    > bool = isProbability.isPrimitive( new Number( 0.3 ) )\n    false\n\n\nisProbability.isObject( value )\n    Tests if a value is a number object having a value which is a probability.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a probability.\n\n    Examples\n    --------\n    > var bool = isProbability.isObject( 0.77 )\n    false\n    > bool = isProbability.isObject( new Number( 0.77 ) )\n    true\n\n\n    See Also\n    --------\n    isNumber\n","isProbability.isPrimitive":"\nisProbability.isPrimitive( value )\n    Tests if a value is a number primitive which is a probability.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a\n        probability.\n\n    Examples\n    --------\n    > var bool = isProbability.isPrimitive( 0.3 )\n    true\n    > bool = isProbability.isPrimitive( new Number( 0.3 ) )\n    false","isProbability.isObject":"\nisProbability.isObject( value )\n    Tests if a value is a number object having a value which is a probability.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a probability.\n\n    Examples\n    --------\n    > var bool = isProbability.isObject( 0.77 )\n    false\n    > bool = isProbability.isObject( new Number( 0.77 ) )\n    true\n\n\n    See Also\n    --------\n    isNumber","isProbabilityArray":"\nisProbabilityArray( value )\n    Tests if a value is an array-like object containing only probabilities.\n\n    A probability is defined as a numeric value on the interval [0,1].\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        probabilities.\n\n    Examples\n    --------\n    > var bool = isProbabilityArray( [ 0.5, new Number(0.8) ] )\n    true\n    > bool = isProbabilityArray( [ 0.8, 1.2 ] )\n    false\n    > bool = isProbabilityArray( [ 0.8, '0.2' ] )\n    false\n\n\nisProbabilityArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive\n    probabilities.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive probabilities.\n\n    Examples\n    --------\n    > var bool = isProbabilityArray.primitives( [ 1.0, 0.0, 0.5 ] )\n    true\n    > bool = isProbabilityArray.primitives( [ 0.3, new Number(0.4) ] )\n    false\n\n\nisProbabilityArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having probability values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having probability values.\n\n    Examples\n    --------\n    > var bool = isProbabilityArray.objects( [ new Number(0.7), new Number(1.0) ] )\n    true\n    > bool = isProbabilityArray.objects( [ 1.0, 0.0, new Number(0.7) ] )\n    false\n\n    See Also\n    --------\n    isArray, isProbability\n","isProbabilityArray.primitives":"\nisProbabilityArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive\n    probabilities.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive probabilities.\n\n    Examples\n    --------\n    > var bool = isProbabilityArray.primitives( [ 1.0, 0.0, 0.5 ] )\n    true\n    > bool = isProbabilityArray.primitives( [ 0.3, new Number(0.4) ] )\n    false","isProbabilityArray.objects":"\nisProbabilityArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having probability values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having probability values.\n\n    Examples\n    --------\n    > var bool = isProbabilityArray.objects( [ new Number(0.7), new Number(1.0) ] )\n    true\n    > bool = isProbabilityArray.objects( [ 1.0, 0.0, new Number(0.7) ] )\n    false\n\n    See Also\n    --------\n    isArray, isProbability","isPropertyKey":"\nisPropertyKey( value )\n    Tests whether a value is a property key.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether value is a property key.\n\n    Examples\n    --------\n    > var out = isPropertyKey( 'foo' )\n    true\n    > out = isPropertyKey( 1 )\n    true\n    > out = isPropertyKey( true )\n    false\n\n    See Also\n    --------\n    isString, isSymbol, isNonNegativeInteger, hasOwnProp, hasProp","isPrototypeOf":"\nisPrototypeOf( value, proto )\n    Tests if an object's prototype chain contains a provided prototype.\n\n    The function returns `false` if provided a primitive value.\n\n    This function is generally more robust than the `instanceof` operator (e.g.,\n    where inheritance is performed without using constructors).\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    proto: Object|Function\n        Prototype.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a provided prototype exists in a prototype chain.\n\n    Examples\n    --------\n    > function Foo() { return this; };\n    > function Bar() { return this; };\n    > inherit( Bar, Foo );\n    > var bar = new Bar();\n    > var bool = isPrototypeOf( bar, Foo.prototype )\n    true\n\n    See Also\n    --------\n    getPrototypeOf\n","isRaggedNestedArray":"\nisRaggedNestedArray( value )\n    Tests if a value is a ragged nested array. \n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a ragged nested array.\n\n    Examples\n    --------\n    > var bool = isRaggedNestedArray( [ [ 1, 2, 3 ], [ 4, 5 ] ] )\n    true\n    > bool = isRaggedNestedArray( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n    false\n    > bool = isRaggedNestedArray( 'beep' )\n    false\n\n","isRangeError":"\nisRangeError( value )\n    Tests if a value is a RangeError object.\n\n    This function should *not* be considered robust. While the function should\n    always return `true` if provided a RangeError (or a descendant) object,\n    false positives may occur due to the fact that the RangeError constructor\n    inherits from Error and has no internal class of its own. Hence, RangeError\n    impersonation is possible.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a RangeError object.\n\n    Examples\n    --------\n    > var bool = isRangeError( new RangeError( 'beep' ) )\n    true\n    > bool = isRangeError( {} )\n    false\n\n    See Also\n    --------\n    isError\n","isReadableProperty":"\nisReadableProperty( value, property )\n    Tests if an object's own property is readable.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own property is readable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.set = function setter( v ) { obj.boop = v; };\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isReadableProperty( obj, 'boop' )\n    true\n    > bool = isReadableProperty( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    isReadOnlyProperty, isReadWriteProperty, isReadablePropertyIn, isWritableProperty\n","isReadablePropertyIn":"\nisReadablePropertyIn( value, property )\n    Tests if an object's own or inherited property is readable.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own or inherited property is readable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.set = function setter( v ) { obj.boop = v; };\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isReadablePropertyIn( obj, 'boop' )\n    true\n    > bool = isReadablePropertyIn( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    isReadOnlyPropertyIn, isReadWritePropertyIn, isReadableProperty, isWritablePropertyIn\n","isReadOnlyProperty":"\nisReadOnlyProperty( value, property )\n    Tests if an object's own property is read-only.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own property is read-only.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = true;\n    > desc.writable = false;\n    > desc.value = true;\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isReadOnlyProperty( obj, 'boop' )\n    true\n    > bool = isReadOnlyProperty( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    isReadOnlyPropertyIn, isReadWriteProperty, isReadableProperty, isWritableProperty\n","isReadOnlyPropertyIn":"\nisReadOnlyPropertyIn( value, property )\n    Tests if an object's own or inherited property is read-only.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own or inherited property is read-\n        only.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = true;\n    > desc.writable = false;\n    > desc.value = true;\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isReadOnlyPropertyIn( obj, 'boop' )\n    true\n    > bool = isReadOnlyPropertyIn( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    isReadOnlyProperty, isReadWritePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isReadWriteProperty":"\nisReadWriteProperty( value, property )\n    Tests if an object's own property is readable and writable.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own property is readable and writable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.set = function setter( v ) { obj.boop = v; };\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isReadWriteProperty( obj, 'boop' )\n    true\n    > bool = isReadWriteProperty( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    isReadOnlyProperty, isReadWritePropertyIn, isReadableProperty, isWritableProperty\n","isReadWritePropertyIn":"\nisReadWritePropertyIn( value, property )\n    Tests if an object's own or inherited property is readable and writable.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own or inherited property is readable\n        and writable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.set = function setter( v ) { obj.boop = v; };\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isReadWritePropertyIn( obj, 'boop' )\n    true\n    > bool = isReadWritePropertyIn( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    isReadOnlyPropertyIn, isReadWriteProperty, isReadablePropertyIn, isWritablePropertyIn\n","isReferenceError":"\nisReferenceError( value )\n    Tests if a value is a ReferenceError object.\n\n    This function should *not* be considered robust. While the function should\n    always return `true` if provided a ReferenceError (or a descendant)\n    object, false positives may occur due to the fact that the ReferenceError\n    constructor inherits from Error and has no internal class of its own.\n    Hence, ReferenceError impersonation is possible.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a ReferenceError object.\n\n    Examples\n    --------\n    > var bool = isReferenceError( new ReferenceError( 'beep' ) )\n    true\n    > bool = isReferenceError( {} )\n    false\n\n    See Also\n    --------\n    isError\n","isRegExp":"\nisRegExp( value )\n    Tests if a value is a regular expression.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a regular expression.\n\n    Examples\n    --------\n    > var bool = isRegExp( /\\.+/ )\n    true\n    > bool = isRegExp( {} )\n    false\n\n","isRegExpString":"\nisRegExpString( value )\n    Tests if a value is a regular expression string.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a regular expression string.\n\n    Examples\n    --------\n    > var bool = isRegExpString( '/beep/' )\n    true\n    > bool = isRegExpString( 'beep' )\n    false\n    > bool = isRegExpString( '' )\n    false\n    > bool = isRegExpString( null )\n    false\n\n    See Also\n    --------\n    isRegExp\n","isRelativePath":"\nisRelativePath( value )\n    Tests if a value is a relative path.\n\n    Function behavior is platform-specific. On Windows platforms, the function\n    is equal to `.win32()`. On POSIX platforms, the function is equal to\n    `.posix()`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a relative path.\n\n    Examples\n    --------\n    // Windows environments:\n    > var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\n    true\n\n    // POSIX environments:\n    > bool = isRelativePath( './foo/bar/baz' )\n    true\n\n\nisRelativePath.posix( value )\n    Tests if a value is a POSIX relative path.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a POSIX relative path.\n\n    Examples\n    --------\n    > var bool = isRelativePath.posix( './foo/bar/baz' )\n    true\n    > bool = isRelativePath.posix( '/foo/../bar/baz' )\n    false\n\n\nisRelativePath.win32( value )\n    Tests if a value is a Windows relative path.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Windows relative path.\n\n    Examples\n    --------\n    > var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\n    true\n    > bool = isRelativePath( 'C:\\\\foo\\\\..\\\\bar\\\\baz' )\n    false\n\n    See Also\n    --------\n    isAbsolutePath\n","isRelativePath.posix":"\nisRelativePath.posix( value )\n    Tests if a value is a POSIX relative path.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a POSIX relative path.\n\n    Examples\n    --------\n    > var bool = isRelativePath.posix( './foo/bar/baz' )\n    true\n    > bool = isRelativePath.posix( '/foo/../bar/baz' )\n    false","isRelativePath.win32":"\nisRelativePath.win32( value )\n    Tests if a value is a Windows relative path.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Windows relative path.\n\n    Examples\n    --------\n    > var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\n    true\n    > bool = isRelativePath( 'C:\\\\foo\\\\..\\\\bar\\\\baz' )\n    false\n\n    See Also\n    --------\n    isAbsolutePath","isRelativeURI":"\nisRelativeURI( value )\n    Tests whether a value is a relative URI.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether a value is a relative URI.\n\n    Examples\n    --------\n    > var bool = isRelativeURI( '/images/example.png' )\n    true\n    > bool = isRelativeURI( 'http://www.example.com' )\n    false\n    > bool = isRelativeURI( null )\n    false\n\n    See Also\n    --------\n    isURI","isSafeInteger":"\nisSafeInteger( value )\n    Tests if a value is a safe integer.\n\n    An integer valued number is \"safe\" when the number can be exactly\n    represented as a double-precision floating-point number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a safe integer.\n\n    Examples\n    --------\n    > var bool = isSafeInteger( 5.0 )\n    true\n    > bool = isSafeInteger( new Number( 5.0 ) )\n    true\n    > bool = isSafeInteger( 2.0e200 )\n    false\n    > bool = isSafeInteger( -3.14 )\n    false\n    > bool = isSafeInteger( null )\n    false\n\n\nisSafeInteger.isPrimitive( value )\n    Tests if a value is a number primitive having a safe integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a safe\n        integer value.\n\n    Examples\n    --------\n    > var bool = isSafeInteger.isPrimitive( -3.0 )\n    true\n    > bool = isSafeInteger.isPrimitive( new Number( -3.0 ) )\n    false\n\n\nisSafeInteger.isObject( value )\n    Tests if a value is a `Number` object having a safe integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a `Number` object having a safe\n        integer value.\n\n    Examples\n    --------\n    > var bool = isSafeInteger.isObject( 3.0 )\n    false\n    > bool = isSafeInteger.isObject( new Number( 3.0 ) )\n    true\n\n    See Also\n    --------\n    isInteger, isNumber\n","isSafeInteger.isPrimitive":"\nisSafeInteger.isPrimitive( value )\n    Tests if a value is a number primitive having a safe integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a safe\n        integer value.\n\n    Examples\n    --------\n    > var bool = isSafeInteger.isPrimitive( -3.0 )\n    true\n    > bool = isSafeInteger.isPrimitive( new Number( -3.0 ) )\n    false","isSafeInteger.isObject":"\nisSafeInteger.isObject( value )\n    Tests if a value is a `Number` object having a safe integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a `Number` object having a safe\n        integer value.\n\n    Examples\n    --------\n    > var bool = isSafeInteger.isObject( 3.0 )\n    false\n    > bool = isSafeInteger.isObject( new Number( 3.0 ) )\n    true\n\n    See Also\n    --------\n    isInteger, isNumber","isSafeIntegerArray":"\nisSafeIntegerArray( value )\n    Tests if a value is an array-like object containing only safe integers.\n\n    An integer valued number is \"safe\" when the number can be exactly\n    represented as a double-precision floating-point number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing\n        only safe integers.\n\n    Examples\n    --------\n    > var arr = [ -3.0, new Number(0.0), 2.0 ];\n    > var bool = isSafeIntegerArray( arr )\n    true\n    > arr = [ -3.0, '3.0' ];\n    > bool = isSafeIntegerArray( arr )\n    false\n\n\nisSafeIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive safe\n    integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive safe integer values.\n\n    Examples\n    --------\n    > var arr = [ -1.0, 10.0 ];\n    > var bool = isSafeIntegerArray.primitives( arr )\n    true\n    > arr = [ -1.0, 0.0, 5.0 ];\n    > bool = isSafeIntegerArray.primitives( arr )\n    true\n    > arr = [ -3.0, new Number(-1.0) ];\n    > bool = isSafeIntegerArray.primitives( arr )\n    false\n\n\nisSafeIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only `Number` objects\n    having safe integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        `Number` objects having safe integer values.\n\n    Examples\n    --------\n    > var arr = [ new Number(1.0), new Number(3.0) ];\n    > var bool = isSafeIntegerArray.objects( arr )\n    true\n    > arr = [ -1.0, 0.0, 3.0 ];\n    > bool = isSafeIntegerArray.objects( arr )\n    false\n    > arr = [ 3.0, new Number(-1.0) ];\n    > bool = isSafeIntegerArray.objects( arr )\n    false\n\n    See Also\n    --------\n    isArray, isSafeInteger\n","isSafeIntegerArray.primitives":"\nisSafeIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive safe\n    integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive safe integer values.\n\n    Examples\n    --------\n    > var arr = [ -1.0, 10.0 ];\n    > var bool = isSafeIntegerArray.primitives( arr )\n    true\n    > arr = [ -1.0, 0.0, 5.0 ];\n    > bool = isSafeIntegerArray.primitives( arr )\n    true\n    > arr = [ -3.0, new Number(-1.0) ];\n    > bool = isSafeIntegerArray.primitives( arr )\n    false","isSafeIntegerArray.objects":"\nisSafeIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only `Number` objects\n    having safe integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        `Number` objects having safe integer values.\n\n    Examples\n    --------\n    > var arr = [ new Number(1.0), new Number(3.0) ];\n    > var bool = isSafeIntegerArray.objects( arr )\n    true\n    > arr = [ -1.0, 0.0, 3.0 ];\n    > bool = isSafeIntegerArray.objects( arr )\n    false\n    > arr = [ 3.0, new Number(-1.0) ];\n    > bool = isSafeIntegerArray.objects( arr )\n    false\n\n    See Also\n    --------\n    isArray, isSafeInteger","isSameArray":"\nisSameArray( v1, v2 )\n    Tests if two arguments are both generic arrays and have the same values.\n\n    The function differs from the `===` operator in that the function treats\n    `-0` and `+0` as distinct and `NaNs` as the same.\n\n    Parameters\n    ----------\n    v1: any\n        First input value.\n\n    v2: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are the same.\n\n    Examples\n    --------\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > var y = [ 1.0, 2.0, 3.0 ];\n    > var bool = isSameArray( x, y )\n    true\n\n    > x = [ NaN, NaN, NaN ];\n    > y = [ NaN, NaN, NaN ];\n    > bool = isSameArray( x, y )\n    true\n\n    See Also\n    --------\n    isArray, isEqualArray, isSameArrayLike, isSameValue\n","isSameArrayLike":"\nisSameArrayLike( v1, v2 )\n    Tests if two arguments are both array-like and have the same values.\n\n    The function differs from the `===` operator in that the function treats\n    `-0` and `+0` as distinct and `NaNs` as the same.\n\n    Parameters\n    ----------\n    v1: any\n        First input value.\n\n    v2: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are the same.\n\n    Examples\n    --------\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > var y = [ 1.0, 2.0, 3.0 ];\n    > var bool = isSameArrayLike( x, y )\n    true\n\n    > x = [ NaN, NaN, NaN ];\n    > y = [ NaN, NaN, NaN ];\n    > bool = isSameArrayLike( x, y )\n    true\n\n    See Also\n    --------\n    isArrayLike, isSameArray, isSameValue\n","isSameComplex64":"\nisSameComplex64( v1, v2 )\n    Tests if two arguments are both single-precision complex floating-point\n    numbers and have the same value.\n\n    The function differs from the `===` operator in that the function treats\n    `-0` and `+0` as distinct and `NaNs` as the same.\n\n    Parameters\n    ----------\n    v1: any\n        First input value.\n\n    v2: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are the same.\n\n    Examples\n    --------\n    > var x = new Complex64( 1.0, 2.0 );\n    > var y = new Complex64( 1.0, 2.0 );\n    > var bool = isSameComplex64( x, y )\n    true\n\n    > x = new Complex64( NaN, NaN );\n    > y = new Complex64( NaN, NaN );\n    > bool = isSameComplex64( x, y )\n    true\n\n    See Also\n    --------\n    isComplex64, isSameComplex128, isSameValue\n","isSameComplex64Array":"\nisSameComplex64Array( v1, v2 )\n    Tests if two arguments are both Complex64Arrays and have the same values.\n\n    The function differs from the `===` operator in that the function treats\n    `-0` and `+0` as distinct and `NaNs` as the same.\n\n    Parameters\n    ----------\n    v1: any\n        First input value.\n\n    v2: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are the same.\n\n    Examples\n    --------\n    > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var bool = isSameComplex64Array( x, y )\n    true\n\n    > x = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\n    > y = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\n    > bool = isSameComplex64Array( x, y )\n    true\n\n    See Also\n    --------\n    isComplex64Array, isSameComplex128Array, isSameFloat32Array, isSameValue\n","isSameComplex128":"\nisSameComplex128( v1, v2 )\n    Tests if two arguments are both double-precision complex floating-point\n    numbers and have the same value.\n\n    The function differs from the `===` operator in that the function treats\n    `-0` and `+0` as distinct and `NaNs` as the same.\n\n    Parameters\n    ----------\n    v1: any\n        First input value.\n\n    v2: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are the same.\n\n    Examples\n    --------\n    > var x = new Complex128( 1.0, 2.0 );\n    > var y = new Complex128( 1.0, 2.0 );\n    > var bool = isSameComplex128( x, y )\n    true\n\n    > x = new Complex128( NaN, NaN );\n    > y = new Complex128( NaN, NaN );\n    > bool = isSameComplex128( x, y )\n    true\n\n    See Also\n    --------\n    isComplex128, isSameComplex64, isSameValue\n","isSameComplex128Array":"\nisSameComplex128Array( v1, v2 )\n    Tests if two arguments are both Complex128Arrays and have the same values.\n\n    The function differs from the `===` operator in that the function treats\n    `-0` and `+0` as distinct and `NaNs` as the same.\n\n    Parameters\n    ----------\n    v1: any\n        First input value.\n\n    v2: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are the same.\n\n    Examples\n    --------\n    > var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var bool = isSameComplex128Array( x, y )\n    true\n\n    > x = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\n    > y = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\n    > bool = isSameComplex128Array( x, y )\n    true\n\n    See Also\n    --------\n    isComplex128Array, isSameComplex64Array, isSameFloat64Array, isSameValue\n","isSameDateObject":"\nisSameDateObject( d1, d2 )\n    Tests if two values are both Date objects corresponding \n    to the same date and time.\n\n    Parameters\n    ----------\n    d1: any\n        First input value.\n    d2: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether both values are Date objects \n        corresponding to the same date and time.\n\n    Examples\n    --------\n    > var d1 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\n    > var d2 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\n    > var bool = isSameDateObject( d1, d2 )\n    true\n    > var d1 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\n    > var d2 = new Date( 2024, 11, 31, 23, 59, 59, 78 );\n    > var bool = isSameDateObject( d1, d2 )\n    false\n \n    See Also\n    --------\n    isDateObject, isSameValue\n","isSameFloat32Array":"\nisSameFloat32Array( v1, v2 )\n    Tests if two arguments are both Float32Arrays and have the same values.\n\n    The function differs from the `===` operator in that the function treats\n    `-0` and `+0` as distinct and `NaNs` as the same.\n\n    Parameters\n    ----------\n    v1: any\n        First input value.\n\n    v2: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are the same.\n\n    Examples\n    --------\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > var y = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > var bool = isSameFloat32Array( x, y )\n    true\n\n    > x = new Float32Array( [ NaN, NaN, NaN ] );\n    > y = new Float32Array( [ NaN, NaN, NaN ] );\n    > bool = isSameFloat32Array( x, y )\n    true\n\n    See Also\n    --------\n    isSameFloat64Array, isSameValue\n","isSameFloat64Array":"\nisSameFloat64Array( v1, v2 )\n    Tests if two arguments are both Float64Arrays and have the same values.\n\n    The function differs from the `===` operator in that the function treats\n    `-0` and `+0` as distinct and `NaNs` as the same.\n\n    Parameters\n    ----------\n    v1: any\n        First input value.\n\n    v2: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are the same.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > var bool = isSameFloat64Array( x, y )\n    true\n\n    > x = new Float64Array( [ NaN, NaN, NaN ] );\n    > y = new Float64Array( [ NaN, NaN, NaN ] );\n    > bool = isSameFloat64Array( x, y )\n    true\n\n    See Also\n    --------\n    isSameFloat32Array, isSameValue\n","isSameNativeClass":"\nisSameNativeClass( a, b )\n    Tests if two arguments have the same native class.\n\n    Parameters\n    ----------\n    a: any\n        First input value.\n\n    b: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments have the same native class.\n\n    Examples\n    --------\n    > var bool = isSameNativeClass( 3.14, new Number( 3.14 ) )\n    true\n    > bool = isSameNativeClass( 'beep', 'boop' )\n    true\n    > bool = isSameNativeClass( {}, [] )\n    false\n\n    See Also\n    --------\n    isSameType, isSameValue, isStrictEqual\n","isSameType":"\nisSameType( a, b )\n    Tests if two arguments have the same type.\n\n    The function uses the `typeof` operator to test for the same type.\n\n    Parameters\n    ----------\n    a: any\n        First input value.\n\n    b: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments have the same type.\n\n    Examples\n    --------\n    > var bool = isSameType( true, true )\n    true\n    > bool = isSameType( {}, [] )\n    true\n    > bool = isSameType( 3.12, -3.12 )\n    true\n    > bool = isSameType( 0.0, '0.0' )\n    false\n\n    See Also\n    --------\n    isSameNativeClass, isSameValue, isStrictEqual\n","isSameValue":"\nisSameValue( a, b )\n    Tests if two arguments are the same value.\n\n    The function differs from the `===` operator in that the function treats\n    `-0` and `+0` as distinct and `NaNs` as the same.\n\n    Parameters\n    ----------\n    a: any\n        First input value.\n\n    b: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are the same value.\n\n    Examples\n    --------\n    > var bool = isSameValue( true, true )\n    true\n    > bool = isSameValue( {}, {} )\n    false\n    > bool = isSameValue( -0.0, -0.0 )\n    true\n    > bool = isSameValue( -0.0, 0.0 )\n    false\n    > bool = isSameValue( NaN, NaN )\n    true\n\n    See Also\n    --------\n    isSameValueZero, isStrictEqual\n","isSameValueZero":"\nisSameValueZero( a, b )\n    Tests if two arguments are the same value.\n\n    The function differs from the `===` operator in that the function treats\n    `NaNs` as the same.\n\n    Parameters\n    ----------\n    a: any\n        First input value.\n\n    b: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are the same value.\n\n    Examples\n    --------\n    > var bool = isSameValueZero( true, true )\n    true\n    > bool = isSameValueZero( {}, {} )\n    false\n    > bool = isSameValueZero( -0.0, -0.0 )\n    true\n    > bool = isSameValueZero( -0.0, 0.0 )\n    true\n    > bool = isSameValueZero( NaN, NaN )\n    true\n\n    See Also\n    --------\n    isSameValue, isStrictEqual\n","isSemVer":"\nisSemVer( value )\n    Tests if a value is a semantic version string.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether a provided value is a semantic version\n        string.\n\n    Examples\n    --------\n    > var bool = isSemVer( '1.0.0' )\n    true\n    > bool = isSemVer( '1.0.0-alpha.1' )\n    true\n    > bool = isSemVer( '0.1' )\n    false\n    > bool = isSemVer( null )\n    false\n","isSharedArrayBuffer":"\nisSharedArrayBuffer( value )\n    Tests if a value is a SharedArrayBuffer.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a SharedArrayBuffer.\n\n    Examples\n    --------\n    // Assuming an environment supports SharedArrayBuffer...\n    > var bool = isSharedArrayBuffer( new SharedArrayBuffer( 10 ) )\n    true\n    > bool = isSharedArrayBuffer( [] )\n    false\n\n    See Also\n    --------\n    isArrayBuffer, isTypedArray\n","isSkewCentrosymmetricMatrix":"\nisSkewCentrosymmetricMatrix( value )\n    Tests if a value is a skew-centrosymmetric matrix.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a skew-centrosymmetric matrix.\n\n    Examples\n    --------\n    > var buf = [ 2, 1, -1, -2 ];\n    > var sh = [ 2, 2 ];\n    > var st = [ 2, 1 ];\n    > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n    > var bool = isSkewCentrosymmetricMatrix( M )\n    true\n    > bool = isSkewCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isSkewCentrosymmetricMatrix( 3.14 )\n    false\n    > bool = isSkewCentrosymmetricMatrix( {} )\n    false\n\n    See Also\n    --------\n    isCentrosymmetricMatrix, isMatrixLike, isSkewSymmetricMatrix\n","isSkewPersymmetricMatrix":"\nisSkewPersymmetricMatrix( value )\n    Tests if a value is a skew-persymmetric matrix.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a skew-persymmetric matrix.\n\n    Examples\n    --------\n    > var buf = [ 1, 0, 0, -1 ];\n    > var sh = [ 2, 2 ];\n    > var st = [ 2, 1 ];\n    > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n    > var bool = isSkewPersymmetricMatrix( M )\n    true\n    > bool = isSkewPersymmetricMatrix( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isSkewPersymmetricMatrix( 3.14 )\n    false\n    > bool = isSkewPersymmetricMatrix( {} )\n    false\n\n    See Also\n    --------\n    isMatrixLike, isPersymmetricMatrix, isSkewSymmetricMatrix\n","isSkewSymmetricMatrix":"\nisSkewSymmetricMatrix( value )\n    Tests if a value is a skew-symmetric (or antisymmetric) matrix.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a skew-symmetric matrix.\n\n    Examples\n    --------\n    > var buf = [ 0, -1, 1, 0 ];\n    > var sh = [ 2, 2 ];\n    > var st = [ 2, 1 ];\n    > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n    > var bool = isSkewSymmetricMatrix( M )\n    true\n    > bool = isSkewSymmetricMatrix( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isSkewSymmetricMatrix( 3.14 )\n    false\n    > bool = isSkewSymmetricMatrix( {} )\n    false\n\n    See Also\n    --------\n    isMatrixLike, isSkewSymmetricMatrix, isSquareMatrix\n","isSlice":"\nisSlice( value )\n    Tests if a value is a Slice object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a Slice object.\n\n    Examples\n    --------\n    > var bool = isSlice( new Slice( 10 ) )\n    true\n    > bool = isSlice( 3.14 )\n    false\n    > bool = isSlice( {} )\n    false\n\n    See Also\n    --------\n    isMultiSlice, Slice\n","isSnakecase":"\nisSnakecase( value )\n    Tests if a value is a string in snake case.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a string in snake case.\n\n    Examples\n    --------\n    > var bool = isSnakecase( 'hello_world' )\n    true\n    > bool = isSnakecase( 'Hello World' )\n    false\n\n    See Also\n    --------\n    isString","isSquareMatrix":"\nisSquareMatrix( value )\n    Tests if a value is a 2-dimensional ndarray-like object having equal\n    dimensions.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 2-dimensional ndarray-like\n        object having equal dimensions.\n\n    Examples\n    --------\n    > var buf = [ 0, 0, 0, 0 ];\n    > var sh = [ 2, 2 ];\n    > var st = [ 2, 1 ];\n    > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n    > var bool = isSquareMatrix( M )\n    true\n    > bool = isSquareMatrix( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isSquareMatrix( 3.14 )\n    false\n    > bool = isSquareMatrix( {} )\n    false\n\n    See Also\n    --------\n    isMatrixLike, isSymmetricMatrix\n","isSquareNumber":"\nisSquareNumber( value )\n    Tests if a value is a square number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a square number.\n\n    Examples\n    --------\n    > var bool = isSquareNumber( 4.0 )\n    true\n    > bool = isSquareNumber( new Number( 4.0 ) )\n    true\n    > bool = isSquareNumber( 3.14 )\n    false\n    > bool = isSquareNumber( -5.0 )\n    false\n    > bool = isSquareNumber( null )\n    false\n\n\nisSquareNumber.isPrimitive( value )\n    Tests if a value is a number primitive which is a square number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a\n        square number.\n\n    Examples\n    --------\n    > var bool = isSquareNumber.isPrimitive( 4.0 )\n    true\n    > bool = isSquareNumber.isPrimitive( new Number( 4.0 ) )\n    false\n\n\nisSquareNumber.isObject( value )\n    Tests if a value is a number object having a value which is a square number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a square number.\n\n    Examples\n    --------\n    > var bool = isSquareNumber.isObject( 4.0 )\n    false\n    > bool = isSquareNumber.isObject( new Number( 4.0 ) )\n    true\n\n\n    See Also\n    --------\n    isCubeNumber, isInteger, isNumber, isTriangularNumber\n","isSquareNumber.isPrimitive":"\nisSquareNumber.isPrimitive( value )\n    Tests if a value is a number primitive which is a square number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a\n        square number.\n\n    Examples\n    --------\n    > var bool = isSquareNumber.isPrimitive( 4.0 )\n    true\n    > bool = isSquareNumber.isPrimitive( new Number( 4.0 ) )\n    false","isSquareNumber.isObject":"\nisSquareNumber.isObject( value )\n    Tests if a value is a number object having a value which is a square number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a square number.\n\n    Examples\n    --------\n    > var bool = isSquareNumber.isObject( 4.0 )\n    false\n    > bool = isSquareNumber.isObject( new Number( 4.0 ) )\n    true\n\n\n    See Also\n    --------\n    isCubeNumber, isInteger, isNumber, isTriangularNumber","isSquareTriangularNumber":"\nisSquareTriangularNumber( value )\n    Tests if a value is a square triangular number.\n\n    Return values are not reliable for numbers greater than 1125899906842624.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a square triangular number.\n\n    Examples\n    --------\n    > var bool = isSquareTriangularNumber( 36.0 )\n    true\n    > bool = isSquareTriangularNumber( new Number( 36.0 ) )\n    true\n    > bool = isSquareTriangularNumber( 3.14 )\n    false\n    > bool = isSquareTriangularNumber( -5.0 )\n    false\n    > bool = isSquareTriangularNumber( null )\n    false\n\n\nisSquareTriangularNumber.isPrimitive( value )\n    Tests if a value is a number primitive which is a square triangular number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a\n        square triangular number.\n\n    Examples\n    --------\n    > var bool = isSquareTriangularNumber.isPrimitive( 36.0 )\n    true\n    > bool = isSquareTriangularNumber.isPrimitive( new Number( 36.0 ) )\n    false\n\n\nisSquareTriangularNumber.isObject( value )\n    Tests if a value is a number object having a value which is a square\n    triangular number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a square triangular number.\n\n    Examples\n    --------\n    > var bool = isSquareTriangularNumber.isObject( 36.0 )\n    false\n    > bool = isSquareTriangularNumber.isObject( new Number( 36.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger, isNumber, isSquareNumber, isTriangularNumber\n","isSquareTriangularNumber.isPrimitive":"\nisSquareTriangularNumber.isPrimitive( value )\n    Tests if a value is a number primitive which is a square triangular number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a\n        square triangular number.\n\n    Examples\n    --------\n    > var bool = isSquareTriangularNumber.isPrimitive( 36.0 )\n    true\n    > bool = isSquareTriangularNumber.isPrimitive( new Number( 36.0 ) )\n    false","isSquareTriangularNumber.isObject":"\nisSquareTriangularNumber.isObject( value )\n    Tests if a value is a number object having a value which is a square\n    triangular number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a square triangular number.\n\n    Examples\n    --------\n    > var bool = isSquareTriangularNumber.isObject( 36.0 )\n    false\n    > bool = isSquareTriangularNumber.isObject( new Number( 36.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger, isNumber, isSquareNumber, isTriangularNumber","isStartcase":"\nisStartcase( value )\n    Tests if a value is a startcase string.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if value is a startcase string.\n\n    Examples\n    --------\n    > var bool = isStartcase( 'Beep Boop' )\n    true\n    > bool = isStartcase( 'Beep and Boop' )\n    false\n\n    See Also\n    --------\n    isString","isStrictEqual":"\nisStrictEqual( a, b )\n    Tests if two arguments are strictly equal.\n\n    The function differs from the `===` operator in that the function treats\n    `-0` and `+0` as distinct.\n\n    Parameters\n    ----------\n    a: any\n        First input value.\n\n    b: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are strictly equal.\n\n    Examples\n    --------\n    > var bool = isStrictEqual( true, true )\n    true\n    > bool = isStrictEqual( {}, {} )\n    false\n    > bool = isStrictEqual( -0.0, -0.0 )\n    true\n    > bool = isStrictEqual( -0.0, 0.0 )\n    false\n    > bool = isStrictEqual( NaN, NaN )\n    false\n\n    See Also\n    --------\n    isSameValue\n","isString":"\nisString( value )\n    Tests if a value is a string.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a string.\n\n    Examples\n    --------\n    > var bool = isString( 'beep' )\n    true\n    > bool = isString( new String( 'beep' ) )\n    true\n    > bool = isString( 5 )\n    false\n\n\nisString.isPrimitive( value )\n    Tests if a value is a string primitive.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a string primitive.\n\n    Examples\n    --------\n    > var bool = isString.isPrimitive( 'beep' )\n    true\n    > bool = isString.isPrimitive( new String( 'beep' ) )\n    false\n\n\nisString.isObject( value )\n    Tests if a value is a `String` object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a `String` object.\n\n    Examples\n    --------\n    > var bool = isString.isObject( new String( 'beep' ) )\n    true\n    > bool = isString.isObject( 'beep' )\n    false\n\n","isString.isPrimitive":"\nisString.isPrimitive( value )\n    Tests if a value is a string primitive.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a string primitive.\n\n    Examples\n    --------\n    > var bool = isString.isPrimitive( 'beep' )\n    true\n    > bool = isString.isPrimitive( new String( 'beep' ) )\n    false","isString.isObject":"\nisString.isObject( value )\n    Tests if a value is a `String` object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a `String` object.\n\n    Examples\n    --------\n    > var bool = isString.isObject( new String( 'beep' ) )\n    true\n    > bool = isString.isObject( 'beep' )\n    false","isStringArray":"\nisStringArray( value )\n    Tests if a value is an array of strings.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array of strings.\n\n    Examples\n    --------\n    > var bool = isStringArray( [ 'abc', 'def' ] )\n    true\n    > bool = isStringArray( [ 'abc', 123 ] )\n    false\n\n\nisStringArray.primitives( value )\n    Tests if a value is an array containing only string primitives.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array containing only string\n        primitives.\n\n    Examples\n    --------\n    > var arr = [ 'abc', 'def' ];\n    > var bool = isStringArray.primitives( arr )\n    true\n    > arr = [ 'abc', new String( 'def' ) ];\n    > bool = isStringArray.primitives( arr )\n    false\n\n\nisStringArray.objects( value )\n    Tests if a value is an array containing only `String` objects.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array containing only `String`\n        objects.\n\n    Examples\n    --------\n    > var arr = [ new String( 'ab' ), new String( 'cd' ) ];\n    > var bool = isStringArray.objects( arr )\n    true\n    > arr = [ new String( 'abc' ), 'def' ];\n    > bool = isStringArray.objects( arr )\n    false\n\n    See Also\n    --------\n    isArray, isString\n","isStringArray.primitives":"\nisStringArray.primitives( value )\n    Tests if a value is an array containing only string primitives.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array containing only string\n        primitives.\n\n    Examples\n    --------\n    > var arr = [ 'abc', 'def' ];\n    > var bool = isStringArray.primitives( arr )\n    true\n    > arr = [ 'abc', new String( 'def' ) ];\n    > bool = isStringArray.primitives( arr )\n    false","isStringArray.objects":"\nisStringArray.objects( value )\n    Tests if a value is an array containing only `String` objects.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array containing only `String`\n        objects.\n\n    Examples\n    --------\n    > var arr = [ new String( 'ab' ), new String( 'cd' ) ];\n    > var bool = isStringArray.objects( arr )\n    true\n    > arr = [ new String( 'abc' ), 'def' ];\n    > bool = isStringArray.objects( arr )\n    false\n\n    See Also\n    --------\n    isArray, isString","isSymbol":"\nisSymbol( value )\n    Tests if a value is a symbol.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a symbol.\n\n    Examples\n    --------\n    > var bool = isSymbol( Symbol( 'beep' ) )\n    true\n    > bool = isSymbol( Object( Symbol( 'beep' ) ) )\n    true\n    > bool = isSymbol( {} )\n    false\n    > bool = isSymbol( null )\n    false\n    > bool = isSymbol( true )\n    false\n\n","isSymbolArray":"\nisSymbolArray( value )\n    Tests if a value is an array-like object containing only symbols.\n\n    In pre-ES2015 environments, the function always returns `false`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only symbols.\n\n    Examples\n    --------\n    > var bool = isSymbolArray( [ Symbol( 'beep' ), Symbol( 'boop' ) ] )\n    true\n    > bool = isSymbolArray( Symbol( 'beep' ) )\n    false\n    > bool = isSymbolArray( [] )\n    false\n    > bool = isSymbolArray( {} )\n    false\n    > bool = isSymbolArray( null )\n    false\n    > bool = isSymbolArray( true )\n    false\n\n\nisSymbolArray.primitives( value )\n    Tests if a value is an array-like object containing only `symbol`\n    primitives.\n\n    In pre-ES2015 environments, the function always returns `false`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only `symbol` primitives.\n\n    Examples\n    --------\n    > var bool = isSymbolArray.primitives( [ Symbol( 'beep' ) ] )\n    true\n    > bool = isSymbolArray.primitives( [ Object( Symbol( 'beep' ) ) ] )\n    false\n    > bool = isSymbolArray.primitives( [] )\n    false\n    > bool = isSymbolArray.primitives( {} )\n    false\n    > bool = isSymbolArray.primitives( null )\n    false\n    > bool = isSymbolArray.primitives( true )\n    false\n\n\nisSymbolArray.objects( value )\n    Tests if a value is an array-like object containing only `Symbol`\n    objects.\n\n    In pre-ES2015 environments, the function always returns `false`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only `Symbol` objects.\n\n    Examples\n    --------\n    > var bool = isSymbolArray.objects( [ Object( Symbol( 'beep' ) ) ] )\n    true\n    > bool = isSymbolArray.objects( [ Symbol( 'beep' ) ] )\n    false\n    > bool = isSymbolArray.objects( [] )\n    false\n    > bool = isSymbolArray.objects( {} )\n    false\n    > bool = isSymbolArray.objects( null )\n    false\n    > bool = isSymbolArray.objects( true )\n    false\n\n    See Also\n    --------\n    isArray, isSymbol\n","isSymbolArray.primitives":"\nisSymbolArray.primitives( value )\n    Tests if a value is an array-like object containing only `symbol`\n    primitives.\n\n    In pre-ES2015 environments, the function always returns `false`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only `symbol` primitives.\n\n    Examples\n    --------\n    > var bool = isSymbolArray.primitives( [ Symbol( 'beep' ) ] )\n    true\n    > bool = isSymbolArray.primitives( [ Object( Symbol( 'beep' ) ) ] )\n    false\n    > bool = isSymbolArray.primitives( [] )\n    false\n    > bool = isSymbolArray.primitives( {} )\n    false\n    > bool = isSymbolArray.primitives( null )\n    false\n    > bool = isSymbolArray.primitives( true )\n    false","isSymbolArray.objects":"\nisSymbolArray.objects( value )\n    Tests if a value is an array-like object containing only `Symbol`\n    objects.\n\n    In pre-ES2015 environments, the function always returns `false`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only `Symbol` objects.\n\n    Examples\n    --------\n    > var bool = isSymbolArray.objects( [ Object( Symbol( 'beep' ) ) ] )\n    true\n    > bool = isSymbolArray.objects( [ Symbol( 'beep' ) ] )\n    false\n    > bool = isSymbolArray.objects( [] )\n    false\n    > bool = isSymbolArray.objects( {} )\n    false\n    > bool = isSymbolArray.objects( null )\n    false\n    > bool = isSymbolArray.objects( true )\n    false\n\n    See Also\n    --------\n    isArray, isSymbol","isSymmetricMatrix":"\nisSymmetricMatrix( value )\n    Tests if a value is a square matrix which equals its transpose.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a symmetric matrix.\n\n    Examples\n    --------\n    > var buf = [ 0, 1, 1, 2 ];\n    > var sh = [ 2, 2 ];\n    > var st = [ 2, 1 ];\n    > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n    > var bool = isSymmetricMatrix( M )\n    true\n    > bool = isSymmetricMatrix( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isSymmetricMatrix( 3.14 )\n    false\n    > bool = isSymmetricMatrix( {} )\n    false\n\n    See Also\n    --------\n    isMatrixLike, isNonSymmetricMatrix, isSquareMatrix\n","isSyntaxError":"\nisSyntaxError( value )\n    Tests if a value is a SyntaxError object.\n\n    This function should *not* be considered robust. While the function should\n    always return `true` if provided a SyntaxError (or a descendant) object,\n    false positives may occur due to the fact that the SyntaxError constructor\n    inherits from Error and has no internal class of its own. Hence, SyntaxError\n    impersonation is possible.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a SyntaxError object.\n\n    Examples\n    --------\n    > var bool = isSyntaxError( new SyntaxError( 'beep' ) )\n    true\n    > bool = isSyntaxError( {} )\n    false\n\n    See Also\n    --------\n    isError\n","isTriangularNumber":"\nisTriangularNumber( value )\n    Tests if a value is a triangular number.\n\n    Return values are not reliable for numbers greater than 1125899906842624.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a triangular number.\n\n    Examples\n    --------\n    > var bool = isTriangularNumber( 36.0 )\n    true\n    > bool = isTriangularNumber( new Number( 36.0 ) )\n    true\n    > bool = isTriangularNumber( 3.14 )\n    false\n    > bool = isTriangularNumber( -5.0 )\n    false\n    > bool = isTriangularNumber( null )\n    false\n\n\nisTriangularNumber.isPrimitive( value )\n    Tests if a value is a number primitive which is a triangular number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a\n        triangular number.\n\n    Examples\n    --------\n    > var bool = isTriangularNumber.isPrimitive( 36.0 )\n    true\n    > bool = isTriangularNumber.isPrimitive( new Number( 36.0 ) )\n    false\n\n\nisTriangularNumber.isObject( value )\n    Tests if a value is a number object having a value which is a triangular\n    number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a triangular number.\n\n    Examples\n    --------\n    > var bool = isTriangularNumber.isObject( 36.0 )\n    false\n    > bool = isTriangularNumber.isObject( new Number( 36.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger, isNumber, isSquareNumber, isSquareTriangularNumber\n","isTriangularNumber.isPrimitive":"\nisTriangularNumber.isPrimitive( value )\n    Tests if a value is a number primitive which is a triangular number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a\n        triangular number.\n\n    Examples\n    --------\n    > var bool = isTriangularNumber.isPrimitive( 36.0 )\n    true\n    > bool = isTriangularNumber.isPrimitive( new Number( 36.0 ) )\n    false","isTriangularNumber.isObject":"\nisTriangularNumber.isObject( value )\n    Tests if a value is a number object having a value which is a triangular\n    number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a triangular number.\n\n    Examples\n    --------\n    > var bool = isTriangularNumber.isObject( 36.0 )\n    false\n    > bool = isTriangularNumber.isObject( new Number( 36.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger, isNumber, isSquareNumber, isSquareTriangularNumber","isTruthy":"\nisTruthy( value )\n    Tests if a value is a value which translates to `true` when evaluated in a\n    boolean context.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is truthy.\n\n    Examples\n    --------\n     > var bool = isTruthy( true )\n    true\n    > bool = isTruthy( {} )\n    true\n    > bool = isTruthy( [] )\n    true\n    > bool = isTruthy( false )\n    false\n    > bool = isTruthy( '' )\n    false\n    > bool = isTruthy( 0 )\n    false\n    > bool = isTruthy( null )\n    false\n    > bool = isTruthy( void 0 )\n    false\n    > bool = isTruthy( NaN )\n    false\n\n    See Also\n    --------\n    isFalsy\n","isTruthyArray":"\nisTruthyArray( value )\n    Tests if a value is an array-like object containing only truthy values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only truthy values.\n\n    Examples\n    --------\n    > var bool = isTruthyArray( [ {}, [] ] )\n    true\n    > bool = isTruthyArray( [ null, '' ] )\n    false\n    > bool = isTruthyArray( [] )\n    false\n\n    See Also\n    --------\n    isFalsyArray, isTruthy\n","isTypedArray":"\nisTypedArray( value )\n    Tests if a value is a typed array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a typed array.\n\n    Examples\n    --------\n    > var bool = isTypedArray( new Int8Array( 10 ) )\n    true\n\n    See Also\n    --------\n    isArray, isTypedArrayLike\n","isTypedArrayLength":"\nisTypedArrayLength( value )\n    Tests if a value is a valid typed array length.\n\n    A valid length property for a typed array instance is any integer value on\n    the interval [0, 2^53-1].\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a valid typed array length.\n\n    Examples\n    --------\n    > var bool = isTypedArrayLength( 5 )\n    true\n    > bool = isTypedArrayLength( 2.0e200 )\n    false\n    > bool = isTypedArrayLength( -3.14 )\n    false\n    > bool = isTypedArrayLength( null )\n    false\n\n    See Also\n    --------\n    isArrayLength, isTypedArray\n","isTypedArrayLike":"\nisTypedArrayLike( value )\n    Tests if a value is typed-array-like.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is typed-array-like.\n\n    Examples\n    --------\n    > var bool = isTypedArrayLike( new Int16Array() )\n    true\n    > bool = isTypedArrayLike({\n    ...    'length': 10,\n    ...    'byteOffset': 0,\n    ...    'byteLength': 10,\n    ...    'BYTES_PER_ELEMENT': 4\n    ... })\n    true\n\n    See Also\n    --------\n    isTypedArray\n","isTypeError":"\nisTypeError( value )\n    Tests if a value is a TypeError object.\n\n    This function should *not* be considered robust. While the function should\n    always return `true` if provided a TypeError (or a descendant) object,\n    false positives may occur due to the fact that the TypeError constructor\n    inherits from Error and has no internal class of its own. Hence, TypeError\n    impersonation is possible.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a TypeError object.\n\n    Examples\n    --------\n    > var bool = isTypeError( new TypeError( 'beep' ) )\n    true\n    > bool = isTypeError( {} )\n    false\n\n    See Also\n    --------\n    isError\n","isUint8Array":"\nisUint8Array( value )\n    Tests if a value is a Uint8Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Uint8Array.\n\n    Examples\n    --------\n    > var bool = isUint8Array( new Uint8Array( 10 ) )\n    true\n    > bool = isUint8Array( [] )\n    false\n\n    See Also\n    --------\n    isTypedArray, isUint16Array, isUint32Array\n","isUint8ClampedArray":"\nisUint8ClampedArray( value )\n    Tests if a value is a Uint8ClampedArray.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Uint8ClampedArray.\n\n    Examples\n    --------\n    > var bool = isUint8ClampedArray( new Uint8ClampedArray( 10 ) )\n    true\n    > bool = isUint8ClampedArray( [] )\n    false\n\n    See Also\n    --------\n    isTypedArray, isUint8Array\n","isUint16Array":"\nisUint16Array( value )\n    Tests if a value is a Uint16Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Uint16Array.\n\n    Examples\n    --------\n    > var bool = isUint16Array( new Uint16Array( 10 ) )\n    true\n    > bool = isUint16Array( [] )\n    false\n\n    See Also\n    --------\n    isTypedArray, isUint32Array, isUint8Array\n","isUint32Array":"\nisUint32Array( value )\n    Tests if a value is a Uint32Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Uint32Array.\n\n    Examples\n    --------\n    > var bool = isUint32Array( new Uint32Array( 10 ) )\n    true\n    > bool = isUint32Array( [] )\n    false\n\n    See Also\n    --------\n    isTypedArray, isUint16Array, isUint8Array\n","isUNCPath":"\nisUNCPath( value )\n    Tests if a value is a UNC path.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a UNC path.\n\n    Examples\n    --------\n    > var bool = isUNCPath( '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz' )\n    true\n    > bool = isUNCPath( '/foo/bar/baz' )\n    false\n\n","isUndefined":"\nisUndefined( value )\n    Tests if a value is undefined.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is undefined.\n\n    Examples\n    --------\n    > var bool = isUndefined( void 0 )\n    true\n    > bool = isUndefined( null )\n    false\n\n    See Also\n    --------\n    isNull, isUndefinedOrNull\n","isUndefinedOrNull":"\nisUndefinedOrNull( value )\n    Tests if a value is undefined or null.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is undefined or null.\n\n    Examples\n    --------\n    > var bool = isUndefinedOrNull( void 0 )\n    true\n    > bool = isUndefinedOrNull( null )\n    true\n    > bool = isUndefinedOrNull( false )\n    false\n\n    See Also\n    --------\n    isNull, isUndefined\n","isUnityProbabilityArray":"\nisUnityProbabilityArray( value )\n    Tests if a value is an array of probabilities that sum to one.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array of probabilities that sum\n        to one.\n\n    Examples\n    --------\n    > var bool = isUnityProbabilityArray( [ 0.25, 0.5, 0.25 ] )\n    true\n    > bool = isUnityProbabilityArray( new Uint8Array( [ 0, 1 ] ) )\n    true\n    > bool = isUnityProbabilityArray( [ 0.4, 0.4, 0.4 ] )\n    false\n    > bool = isUnityProbabilityArray( [ 3.14, 0.0 ] )\n    false\n\n    See Also\n    --------\n    isProbability, isProbabilityArray\n","isUppercase":"\nisUppercase( value )\n    Tests if a value is an uppercase string.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an uppercase string.\n\n    Examples\n    --------\n    > var bool = isUppercase( 'HELLO' )\n    true\n    > bool = isUppercase( 'World' )\n    false\n\n    See Also\n    --------\n    isLowercase, isString\n","isURI":"\nisURI( value )\n    Tests if a value is a URI.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a URI.\n\n    Examples\n    --------\n    > var bool = isURI( 'http://google.com' )\n    true\n    > bool = isURI( 'http://localhost/' )\n    true\n    > bool = isURI( 'http://example.w3.org/path%20with%20spaces.html' )\n    true\n    > bool = isURI( 'ftp://ftp.is.co.za/rfc/rfc1808.txt' )\n    true\n\n    // No scheme:\n    > bool = isURI( '' )\n    false\n    > bool = isURI( 'foo@bar' )\n    false\n    > bool = isURI( '://foo/' )\n    false\n\n    // Illegal characters:\n    > bool = isURI( 'http://<foo>' )\n    false\n\n    // Invalid path:\n    > bool = isURI( 'http:////foo.html' )\n    false\n\n    // Incomplete hex escapes:\n    > bool = isURI( 'http://example.w3.org/%a' )\n    false\n\n","isURIError":"\nisURIError( value )\n    Tests if a value is a URIError object.\n\n    This function should *not* be considered robust. While the function should\n    always return `true` if provided a URIError (or a descendant) object,\n    false positives may occur due to the fact that the URIError constructor\n    inherits from Error and has no internal class of its own. Hence, URIError\n    impersonation is possible.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a URIError object.\n\n    Examples\n    --------\n    > var bool = isURIError( new URIError( 'beep' ) )\n    true\n    > bool = isURIError( {} )\n    false\n\n    See Also\n    --------\n    isError\n","isVectorLike":"\nisVectorLike( value )\n    Tests if a value is a 1-dimensional ndarray-like object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 1-dimensional ndarray-like\n        object.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = [ 0, 0, 0, 0 ];\n    > M.ndims = 1;\n    > M.shape = [ 4 ];\n    > M.strides = [ 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'generic';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isVectorLike( M )\n    true\n    > bool = isVectorLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isVectorLike( 3.14 )\n    false\n    > bool = isVectorLike( {} )\n    false\n\n    See Also\n    --------\n    isArray, isArrayLike, isMatrixLike, isndarrayLike, isTypedArrayLike\n","isWebAssemblyMemory":"\nisWebAssemblyMemory( value )\n    Tests if a value is a WebAssembly memory instance.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a WebAssembly memory instance.\n\n    Examples\n    --------\n    > var bool = isWebAssemblyMemory( {} )\n    false\n\n    See Also\n    --------\n    hasWebAssemblySupport\n","isWellFormedString":"\nisWellFormedString( str )\n    Tests if a string is well-formed.\n\n    Parameters\n    ----------\n    str: any\n        String to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether str is well-formed.\n\n    Examples\n    --------\n    > var bool = isWellFormedString( '' )\n    true\n\n    > bool = isWellFormedString( new String( '' ) )\n    true\n\n    > bool = isWellFormedString( '\\uDBFF' )\n    false\n\n    > bool = isWellFormedString( '\\uDBFFFF\\uDBFF' )\n    false\n\n    > bool = isWellFormedString( [] )\n    false\n\n    > bool = isWellFormedString( '-5' )\n    true\n\n    > bool = isWellFormedString( null )\n    false\n\n\nisWellFormedString.isPrimitive( str )\n    Tests if a string is a well-formed string primitive.\n\n    Parameters\n    ----------\n    str: any\n        String to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether str is a well-formed string primitive.\n\n    Examples\n    --------\n    > var bool = isWellFormedString.isPrimitive( '' )\n    true\n    > bool = isWellFormedString.isPrimitive( new String( '' ) )\n    false\n\n\nisWellFormedString.isObject( str )\n    Tests if a string is a well-formed string object.\n\n    Parameters\n    ----------\n    str: any\n        String to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether str is a well-formed string object.\n\n    Examples\n    --------\n    > var bool = isWellFormedString.isObject( '' )\n    false\n    > bool = isWellFormedString.isObject( new String( '' ) )\n    true\n\n","isWellFormedString.isPrimitive":"\nisWellFormedString.isPrimitive( str )\n    Tests if a string is a well-formed string primitive.\n\n    Parameters\n    ----------\n    str: any\n        String to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether str is a well-formed string primitive.\n\n    Examples\n    --------\n    > var bool = isWellFormedString.isPrimitive( '' )\n    true\n    > bool = isWellFormedString.isPrimitive( new String( '' ) )\n    false","isWellFormedString.isObject":"\nisWellFormedString.isObject( str )\n    Tests if a string is a well-formed string object.\n\n    Parameters\n    ----------\n    str: any\n        String to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether str is a well-formed string object.\n\n    Examples\n    --------\n    > var bool = isWellFormedString.isObject( '' )\n    false\n    > bool = isWellFormedString.isObject( new String( '' ) )\n    true","isWhitespace":"\nisWhitespace( str )\n    Tests whether a string contains only white space characters.\n\n    A white space character is defined as one of the 25 characters defined as a\n    white space (\"WSpace=Y\",\"WS\") character in the Unicode 9.0 character\n    database, as well as one related white space character without the Unicode\n    character property \"WSpace=Y\" (zero width non-breaking space which was\n    deprecated as of Unicode 3.2).\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a string contains only white space\n        characters.\n\n    Examples\n    --------\n    > var bool = isWhitespace( '       ' )\n    true\n    > bool = isWhitespace( 'abcdef' )\n    false\n    > bool = isWhitespace( '' )\n    false\n\n    See Also\n    --------\n    reWhitespace\n","isWritableProperty":"\nisWritableProperty( value, property )\n    Tests if an object's own property is writable.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own property is writable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.writable = false;\n    > desc.value = 'beep';\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isWritableProperty( obj, 'boop' )\n    true\n    > bool = isWritableProperty( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    isReadableProperty, isReadWriteProperty, isWritablePropertyIn, isWriteOnlyProperty\n","isWritablePropertyIn":"\nisWritablePropertyIn( value, property )\n    Tests if an object's own or inherited property is writable.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own or inherited property is writable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.writable = false;\n    > desc.value = 'beep';\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isWritablePropertyIn( obj, 'boop' )\n    true\n    > bool = isWritablePropertyIn( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    isReadablePropertyIn, isReadWritePropertyIn, isWritableProperty, isWriteOnlyPropertyIn\n","isWriteOnlyProperty":"\nisWriteOnlyProperty( value, property )\n    Tests if an object's own property is write-only.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own property is write-only.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = true;\n    > desc.set = function setter( v ) { obj.boop = v; };\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isWriteOnlyProperty( obj, 'boop' )\n    false\n    > bool = isWriteOnlyProperty( obj, 'beep' )\n    true\n\n    See Also\n    --------\n    isReadOnlyProperty, isReadWriteProperty, isWritableProperty, isWriteOnlyPropertyIn\n","isWriteOnlyPropertyIn":"\nisWriteOnlyPropertyIn( value, property )\n    Tests if an object's own or inherited property is write-only.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own or inherited property is write-\n        only.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = true;\n    > desc.set = function setter( v ) { obj.boop = v; };\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isWriteOnlyPropertyIn( obj, 'boop' )\n    false\n    > bool = isWriteOnlyPropertyIn( obj, 'beep' )\n    true\n\n    See Also\n    --------\n    isReadOnlyPropertyIn, isReadWritePropertyIn, isWritablePropertyIn, isWriteOnlyProperty\n","iterAbs":"\niterAbs( iterator )\n    Returns an iterator which iteratively computes the absolute value.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAbs( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.abs, iterAbs2\n","iterAbs2":"\niterAbs2( iterator )\n    Returns an iterator which iteratively computes the squared absolute value.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAbs2( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.abs2, iterAbs\n","iterAcos":"\niterAcos( iterator )\n    Returns an iterator which iteratively computes the arccosine.\n\n    The domain of arccosine is restricted to [-1,1]. If an iterated value is\n    outside of the domain, the returned iterator returns `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAcos( random.iterators.uniform( -1.0, 1.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.acos, iterAcosh, iterAsin, iterAtan\n","iterAcosh":"\niterAcosh( iterator )\n    Returns an iterator which iteratively computes the hyperbolic arccosine.\n\n    The domain of the hyperbolic arccosine is restricted to [1,+infinity). If an\n    iterated value is outside of the domain, the returned iterator returns\n    `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAcosh( random.iterators.uniform( 1.0, 10.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.acosh, iterAcos, iterAsinh, iterAtanh\n","iterAcot":"\niterAcot( iterator )\n    Returns an iterator which iteratively computes the inverse cotangent.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAcot( random.iterators.uniform( -5.0, 5.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.acot, iterAcos, iterAcoth, iterAsin, iterAtan\n","iterAcoth":"\niterAcoth( iterator )\n    Returns an iterator which iteratively computes the inverse hyperbolic\n    cotangent.\n\n    The domain of the inverse hyperbolic cotangent is restricted to (-inf,-1]\n    and [1,inf). If an iterated value is outside of the domain, the returned\n    iterator returns `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAcoth( random.iterators.uniform( 1.0, 10.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.acoth, iterAcosh, iterAcot, iterAsinh, iterAtanh\n","iterAcovercos":"\niterAcovercos( iterator )\n    Returns an iterator which iteratively computes the inverse coversed cosine.\n\n    The domain of inverse coversed cosine is restricted to [-2,0]. If an\n    iterated value is outside of the domain, the returned iterator returns\n    `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAcovercos( random.iterators.uniform( -2.0, 0.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.acovercos, iterAcoversin, iterAvercos, iterCovercos, iterVercos\n","iterAcoversin":"\niterAcoversin( iterator )\n    Returns an iterator which iteratively computes the inverse coversed sine.\n\n    The domain of inverse coversed sine is restricted to [0,2]. If an iterated\n    value is outside of the domain, the returned iterator returns `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAcoversin( random.iterators.uniform( 0.0, 2.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.acoversin, iterAcovercos, iterAversin, iterCoversin, iterVersin\n","iterAdd":"\niterAdd( iter0, ...iterator )\n    Returns an iterator which performs element-wise addition of two or more\n    iterators.\n\n    The length of the returned iterator is equal to the length of the shortest\n    provided iterator. In other words, the returned iterator ends once *one* of\n    the provided iterators ends.\n\n    If provided a numeric value as an iterator argument, the value is broadcast\n    as an infinite iterator which always returns the provided value.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iter0: Object\n        Input iterator.\n\n    iterator: ...Object\n        Iterators to add.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1.0, 2.0 ] );\n    > var it2 = array2iterator( [ 3.0, 4.0 ] );\n    > var it = iterAdd( it1, it2 );\n    > var v = it.next().value\n    4.0\n    > v = it.next().value\n    6.0\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterDivide, iterMultiply, iterSubtract\n","iterAdvance":"\niterAdvance( iterator[, n] )\n    Advances an entire iterator.\n\n    The function *eagerly* advances an input iterator `n` iterations or until\n    the input iterator finishes, whichever comes first.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator to advance.\n\n    n: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Input iterator.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n    > var it = iterAdvance( arr, 4 );\n    > var v = it.next().value\n    1\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterHead, iterSlice\n","iterAhavercos":"\niterAhavercos( iterator )\n    Returns an iterator which iteratively computes the inverse half-value versed\n    cosine.\n\n    The domain of inverse half-value versed cosine is restricted to [0,1]. If\n    an iterated value is outside of the domain, the returned iterator returns\n    `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAhavercos( random.iterators.uniform( 0.0, 1.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.ahavercos, iterAhaversin, iterHavercos, iterVercos\n","iterAhaversin":"\niterAhaversin( iterator )\n    Returns an iterator which iteratively computes the inverse half-value versed\n    sine.\n\n    The domain of inverse half-value versed sine is restricted to [-2,0]. If an\n    iterated value is outside of the domain, the returned iterator returns\n    `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAhaversin( random.iterators.uniform( 0.0, 1.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.ahaversin, iterAhavercos, iterHaversin, iterVersin\n","iterAny":"\niterAny( iterator )\n    Tests whether at least one iterated value is truthy.\n\n    The function immediately returns upon encountering a truthy value.\n\n    If provided an iterator which does not return any iterated values, the\n    function returns `false`.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if a value is truthy; otherwise, the\n        function returns `false`.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n    > var bool = iterAny( arr )\n    true\n\n    See Also\n    --------\n    iterAnyBy, iterEvery, iterForEach, iterNone, iterSome\n","iterAnyBy":"\niterAnyBy( iterator, predicate[, thisArg ] )\n    Tests whether at least one iterated value passes a test implemented by a\n    predicate function.\n\n    The predicate function is provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index.\n\n    The function immediately returns upon encountering a truthy return value.\n\n    If provided an iterator which does not return any iterated values, the\n    function returns `false`.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if a predicate function returns a truthy\n        value for any iterated value. Otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n    > function fcn( v ) { return ( v === 1 ); };\n    > var bool = iterAnyBy( arr, fcn )\n    true\n\n    See Also\n    --------\n    iterAny, iterEveryBy, iterForEach, iterNoneBy, iterSomeBy\n","iterAsin":"\niterAsin( iterator )\n    Returns an iterator which iteratively computes the arcsine.\n\n    The domain of arcsine is restricted to [-1,1]. If an iterated value is\n    outside of the domain, the returned iterator returns `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAsin( random.iterators.uniform( -1.0, 1.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.asin, iterAcos, iterAsinh, iterAtan\n","iterAsinh":"\niterAsinh( iterator )\n    Returns an iterator which iteratively computes the hyperbolic arcsine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAsinh( random.iterators.uniform( -2.0, 2.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.asinh, iterAcosh, iterAsin, iterAtanh\n","iterAtan":"\niterAtan( iterator )\n    Returns an iterator which iteratively computes the arctangent.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAtan( random.iterators.uniform( -2.0, 2.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.atan, iterAcos, iterAsin, iterAtanh\n","iterAtan2":"\niterAtan2( y, x )\n    Returns an iterator which iteratively computes the angle in the plane (in\n    radians) between the positive x-axis and the ray from (0,0) to the point\n    (x,y).\n\n    The length of the returned iterator is equal to the length of the shortest\n    provided iterator. In other words, the returned iterator ends once *one* of\n    the provided iterators ends.\n\n    If provided a numeric value as an iterator argument, the value is broadcast\n    as an infinite iterator which always returns the provided value.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    y: Object|number\n        Input iterator.\n\n    x: Object|number\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = random.iterators.uniform( -2.0, 2.0 );\n    > var y = random.iterators.uniform( -2.0, 2.0 );\n    > var it = iterAtan2( y, x );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.atan2, iterAtan\n","iterAtanh":"\niterAtanh( iterator )\n    Returns an iterator which iteratively computes the hyperbolic arctangent.\n\n    The domain of hyperbolic arctangent is restricted to [-1,1]. If an iterated\n    value is outside of the domain, the returned iterator returns `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAtanh( random.iterators.uniform( -1.0, 1.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.atanh, iterAcosh, iterAsinh, iterAtan\n","iterator2array":"\niterator2array( iterator[, out][, mapFcn[, thisArg]] )\n    Creates (or fills) an array from an iterator.\n\n    When invoked, an input function is provided two arguments:\n\n    - value: iterated value.\n    - index: iterated value index (zero-based).\n\n    If provided an output array, the function fills the output array with\n    iterated values.\n\n    Iteration stops when an output array is full or an iterator finishes;\n    whichever comes first.\n\n    Parameters\n    ----------\n    iterator: Object\n        Source iterator.\n\n    out: ArrayLikeObject (optional)\n        Output array-like object.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var opts = { 'iter': 10 };\n    > var arr = iterator2array( random.iterators.randu( opts ) )\n\n    See Also\n    --------\n    array2iterator, iterator2arrayview\n","iterator2arrayview":"\niterator2arrayview( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )\n    Fills an array-like object view with values returned from an iterator.\n\n    When invoked, an input function is provided three arguments:\n\n    - value: iterated value.\n    - index: destination index (zero-based).\n    - n: iteration index (zero-based).\n\n    Iteration stops when an output array view is full or an iterator finishes;\n    whichever comes first.\n\n    Parameters\n    ----------\n    iterator: Object\n        Source iterator.\n\n    dest: ArrayLikeObject\n        Output array-like object.\n\n    begin: integer (optional)\n        Starting index (inclusive). When negative, determined relative to the\n        last element. Default: 0.\n\n    end: integer (optional)\n        Ending index (non-inclusive). When negative, determined relative to the\n        last element. Default: dest.length.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var it = random.iterators.randu({ 'iter': 10 });\n    > var out = new Float64Array( 20 );\n    > var arr = iterator2arrayview( it, out, 5, 15 )\n\n    See Also\n    --------\n    iterator2array, arrayview2iterator, iterator2arrayviewRight\n","iterator2arrayviewRight":"\niterator2arrayviewRight( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )\n    Fills an array-like object view from right to left with values returned from\n    an iterator.\n\n    When invoked, an input function is provided three arguments:\n\n    - value: iterated value.\n    - index: destination index (zero-based).\n    - n: iteration index (zero-based).\n\n    Iteration stops when an output array view is full or an iterator finishes;\n    whichever comes first.\n\n    Parameters\n    ----------\n    iterator: Object\n        Source iterator.\n\n    dest: ArrayLikeObject\n        Output array-like object.\n\n    begin: integer (optional)\n        Starting index (inclusive). When negative, determined relative to the\n        last element. Default: 0.\n\n    end: integer (optional)\n        Ending index (non-inclusive). When negative, determined relative to the\n        last element. Default: dest.length.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var it = random.iterators.randu({ 'iter': 10 });\n    > var out = new Float64Array( 20 );\n    > var arr = iterator2arrayviewRight( it, out, 5, 15 )\n\n    See Also\n    --------\n    iterator2array, arrayview2iteratorRight, iterator2arrayview\n","iteratorStream":"\niteratorStream( iterator[, options] )\n    Creates a readable stream from an iterator.\n\n    In object mode, `null` is a reserved value. If an iterator generates `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or explicitly map `null`\n    values to a different value by wrapping the provided iterator with another\n    iterator.\n\n    In binary mode, if an iterator generates `undefined` values, the stream will\n    emit an error. Consider providing a custom serialization function or\n    explicitly map `undefined` values to a different value by wrapping the\n    provided iterator with another iterator.\n\n    If a serialization function fails to return a string or Buffer, the stream\n    emits an error.\n\n    Parameters\n    ----------\n    iterator: Object\n        Source iterator.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing iteration.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize iterated\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var it = random.iterators.randu( opts );\n    > var s = iteratorStream( it );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\niteratorStream.factory( [options] )\n    Returns a function for creating readable streams from iterators.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing iteration.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize iterated\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = iteratorStream.factory( opts );\n\n\niteratorStream.objectMode( iterator[, options] )\n    Returns an \"objectMode\" readable stream from an iterator.\n\n    In object mode, `null` is a reserved value. If an iterator generates `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or explicitly map `null`\n    values to a different value by wrapping the provided iterator with another\n    iterator.\n\n    Parameters\n    ----------\n    iterator: Object\n        Source iterator.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before pausing iteration.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var it = random.iterators.randu( opts );\n    > var s = iteratorStream.objectMode( it );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    arrayStream\n","iteratorStream.factory":"\niteratorStream.factory( [options] )\n    Returns a function for creating readable streams from iterators.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing iteration.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize iterated\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = iteratorStream.factory( opts );","iteratorStream.objectMode":"\niteratorStream.objectMode( iterator[, options] )\n    Returns an \"objectMode\" readable stream from an iterator.\n\n    In object mode, `null` is a reserved value. If an iterator generates `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or explicitly map `null`\n    values to a different value by wrapping the provided iterator with another\n    iterator.\n\n    Parameters\n    ----------\n    iterator: Object\n        Source iterator.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before pausing iteration.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var it = random.iterators.randu( opts );\n    > var s = iteratorStream.objectMode( it );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    arrayStream","IteratorSymbol":"\nIteratorSymbol\n    Iterator symbol.\n\n    This symbol specifies the default iterator for an object.\n\n    The symbol is only supported in ES6/ES2015+ environments. For non-supporting\n    environments, the value is `null`.\n\n    Examples\n    --------\n    > var s = IteratorSymbol\n\n    See Also\n    --------\n    Symbol\n","iterAvercos":"\niterAvercos( iterator )\n    Returns an iterator which iteratively computes the inverse versed cosine.\n\n    The domain of inverse versed cosine is restricted to [-2,0]. If an iterated\n    value is outside of the domain, the returned iterator returns `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAvercos( random.iterators.uniform( -2.0, 0.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.avercos, iterAversin, iterVersin\n","iterAversin":"\niterAversin( iterator )\n    Returns an iterator which iteratively computes the inverse versed sine.\n\n    The domain of inverse versed sine is restricted to [0,2]. If an iterated\n    value is outside of the domain, the returned iterator returns `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAversin( random.iterators.uniform( 0.0, 2.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.aversin, iterAvercos, iterVercos\n","iterawgn":"\niterawgn( iterator, sigma[, options] )\n    Returns an iterator which introduces additive white Gaussian noise (AWGN)\n    with standard deviation `sigma`.\n\n    If an environment supports Symbol.iterator and the provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    sigma: number\n        Standard deviation of the noise.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating pseudorandom numbers\n        drawn from a standard normal distribution. If provided, the `state` and\n        `seed` options are ignored. In order to seed the returned iterator, one\n        must seed the provided `prng` (assuming the provided `prng` is\n        seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function|null\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Pseudorandom random number generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var src = iterSineWave();\n    > var it = iterawgn( src, 0.5 );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterawln, iterawun\n","iterawln":"\niterawln( iterator, sigma[, options] )\n    Returns an iterator which introduces additive white Laplacian noise (AWLN)\n    with standard deviation `sigma`.\n\n    If an environment supports Symbol.iterator and the provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    sigma: number\n        Standard deviation of the noise.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval [0,1). If provided, the\n        `state` and `seed` options are ignored. In order to seed the returned\n        iterator, one must seed the provided `prng` (assuming the provided\n        `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Pseudorandom random number generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var src = iterSineWave();\n    > var it = iterawln( src, 0.5 );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterawgn, iterawun\n","iterawun":"\niterawun( iterator, sigma[, options] )\n    Returns an iterator which introduces additive white uniform noise (AWUN)\n    with standard deviation `sigma`.\n\n    If an environment supports Symbol.iterator and the provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    sigma: number\n        Standard deviation of the noise.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval [0,1). If provided, the\n        `state` and `seed` options are ignored. In order to seed the returned\n        iterator, one must seed the provided `prng` (assuming the provided\n        `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Pseudorandom random number generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var src = iterSineWave();\n    > var it = iterawun( src, 0.5 );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterawgn, iterawln\n","iterBartlettHannPulse":"\niterBartlettHannPulse( [options] )\n    Returns an iterator which generates a Bartlett-Hann pulse waveform.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Pulse period (i.e., the number of iterations until a waveform repeats).\n        Default: 100.\n\n    options.duration: integer (optional)\n        Pulse duration. Must be greater than 2. Default: options.period.\n\n    options.amplitude: number (optional)\n        Amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterBartlettHannPulse();\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterBartlettPulse, iterHannPulse, iterPulse, iterTriangleWave\n","iterBartlettPulse":"\niterBartlettPulse( [options] )\n    Returns an iterator which generates a Bartlett pulse waveform.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Pulse period (i.e., the number of iterations until a waveform repeats).\n        Default: 100.\n\n    options.duration: integer (optional)\n        Pulse duration. Must be greater than 2. Default: options.period.\n\n    options.amplitude: number (optional)\n        Amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterBartlettPulse();\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterBartlettHannPulse, iterPulse, iterTriangleWave\n","iterBesselj0":"\niterBesselj0( iterator )\n    Returns an iterator which iteratively evaluates the Bessel function of the\n    first kind of order zero.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterBesselj0( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.besselj0, iterBesselj1, iterBessely0, iterBessely1\n","iterBesselj1":"\niterBesselj1( iterator )\n    Returns an iterator which iteratively evaluates the Bessel function of the\n    first kind of order one.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterBesselj1( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.besselj1, iterBesselj0, iterBessely0, iterBessely1\n","iterBessely0":"\niterBessely0( iterator )\n    Returns an iterator which iteratively evaluates the Bessel function of the\n    second kind of order zero.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterBessely0( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.bessely0, iterBesselj0, iterBesselj1, iterBessely1\n","iterBessely1":"\niterBessely1( iterator )\n    Returns an iterator which iteratively evaluates the Bessel function of the\n    second kind of order one.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterBessely1( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.bessely1, iterBesselj0, iterBesselj1, iterBessely0\n","iterBeta":"\niterBeta( x, y )\n    Returns an iterator which iteratively evaluates the beta function.\n\n    The length of the returned iterator is equal to the length of the shortest\n    provided iterator. In other words, the returned iterator ends once *one* of\n    the provided iterators ends.\n\n    If provided a numeric value as an iterator argument, the value is broadcast\n    as an infinite iterator which always returns the provided value.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    x: Object|number\n        Input iterator.\n\n    y: Object|number\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = random.iterators.uniform( 0.0, 2.0 );\n    > var y = random.iterators.uniform( 0.0, 2.0 );\n    > var it = iterBeta( x, y );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.beta, iterBetaln\n","iterBetaln":"\niterBetaln( x, y )\n    Returns an iterator which iteratively evaluates the natural logarithm of the\n    beta function.\n\n    The length of the returned iterator is equal to the length of the shortest\n    provided iterator. In other words, the returned iterator ends once *one* of\n    the provided iterators ends.\n\n    If provided a numeric value as an iterator argument, the value is broadcast\n    as an infinite iterator which always returns the provided value.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    x: Object|number\n        Input iterator.\n\n    y: Object|number\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = random.iterators.uniform( 0.0, 2.0 );\n    > var y = random.iterators.uniform( 0.0, 2.0 );\n    > var it = iterBetaln( x, y );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.betaln, iterBeta\n","iterBinet":"\niterBinet( iterator )\n    Returns an iterator which iteratively evaluates Binet's formula extended to\n    real numbers.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterBinet( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.binet\n","iterCbrt":"\niterCbrt( iterator )\n    Returns an iterator which iteratively computes the cube root.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterCbrt( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.cbrt, iterPow, iterSqrt\n","iterCeil":"\niterCeil( iterator )\n    Returns an iterator which rounds each iterated value toward positive\n    infinity.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterCeil( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.ceil, iterFloor, iterRound\n","iterCeil2":"\niterCeil2( iterator )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    two toward positive infinity.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterCeil2( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.ceil2, iterCeil, iterCeil10, iterFloor2, iterRound2\n","iterCeil10":"\niterCeil10( iterator )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    10 toward positive infinity.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterCeil10( random.iterators.uniform( -100.0, 100.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.ceil10, iterCeil, iterCeil2, iterFloor10, iterRound10\n","iterCompositesSeq":"\niterCompositesSeq( [options] )\n    Returns an iterator which generates a sequence of composite numbers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterCompositesSeq();\n    > var v = it.next().value\n    4\n    > v = it.next().value\n    6\n    > v = it.next().value\n    8\n\n    See Also\n    --------\n    iterIntegersSeq, iterPositiveIntegersSeq, iterPrimesSeq\n","iterConcat":"\niterConcat( iter0, ...iterator )\n    Returns an iterator which iterates over the values of two or more iterators.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iter0: Object\n        Input iterator.\n\n    iterator: ...Object\n        Iterators to concatenate.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2 ] );\n    > var it2 = array2iterator( [ 3, 4 ] );\n    > var it = iterConcat( it1, it2 );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    2\n    > v = it.next().value\n    3\n    > v = it.next().value\n    4\n    > var bool = it.next().done\n    true\n\n","iterConstant":"\niterConstant( value[, options] )\n    Returns an iterator which always returns the same value.\n\n    When provided an object reference, the returned iterator always returns the\n    same reference.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    value: any\n        Value to return.\n\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterConstant( 3.14 );\n    > var v = it.next().value\n    3.14\n    > v = it.next().value\n    3.14\n\n    See Also\n    --------\n    constantFunction\n","iterContinuedFraction":"\niterContinuedFraction( iterator[, options] )\n    Evaluates the terms of a continued fraction.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Maximum number of iterations. Default: 1e308.\n\n    options.tol: number (optional)\n        Tolerance at which to terminate further evaluation of the continued\n        fraction. Default: floating-point epsilon.\n\n    Returns\n    -------\n    out: number|null\n        Result.\n\n    Examples\n    --------\n    > var terms = array2iterator( [ 3, 4, 12, 4 ] );\n    > var v = iterContinuedFraction( terms )\n    ~3.245\n\n    See Also\n    --------\n    iterContinuedFractionSeq\n","iterContinuedFractionSeq":"\niterContinuedFractionSeq( x[, options] )\n    Returns an iterator which generates a list of all continued fraction terms\n    which can be obtained given the precision of `x`.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Maximum number of iterations. Default: 1e308.\n\n    options.tol: number (optional)\n        Tolerance at which to terminate further evaluation of the continued\n        fraction. Default: floating-point epsilon.\n\n    options.returns: string (optional)\n        Specifies the type of result to return. Must be one of\n\n        - terms: return continued fraction terms\n        - convergents: return continued fraction convergents\n        - *: return both continued fraction terms and their associated\n          convergents as a two-element array.\n\n        Default: 'terms'.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    // Return continued fraction terms...\n    > var it = iterContinuedFractionSeq( 3.245 );\n    > var v = it.next().value\n    3\n    > v = it.next().value\n    4\n    > v = it.next().value\n    12\n    > v = it.next().value\n    4\n    > var bool = it.next().done\n    true\n\n    // Return continued fraction convergents...\n    > it = iterContinuedFractionSeq( 3.245, { 'returns': 'convergents' } );\n    > v = it.next().value\n    3.0\n    > v = it.next().value\n    3.25\n    > v = it.next().value\n    ~3.2449\n    > v = it.next().value\n    3.245\n    > bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterContinuedFraction\n","iterCos":"\niterCos( iterator )\n    Returns an iterator which iteratively computes the cosine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterCos( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.cos, iterCospi, iterSin, iterTan\n","iterCosh":"\niterCosh( iterator )\n    Returns an iterator which iteratively computes the hyperbolic cosine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -5.0, 5.0 );\n    > var it = iterCosh( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.cosh, iterCos, iterSinh, iterTanh\n","iterCosineWave":"\niterCosineWave( [options] )\n    Returns an iterator which generates a cosine wave.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Period (i.e., the number of iterations before a cosine wave repeats).\n        Default: 10.\n\n    options.amplitude: number (optional)\n        Peak amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterCosineWave();\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterPulse, iterSawtoothWave, iterSineWave, iterSquareWave, iterTriangleWave\n","iterCosm1":"\niterCosm1( iterator )\n    Returns an iterator which iteratively computes `cos(x) - 1`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 6.28 );\n    > var it = iterCosm1( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.cosm1, iterCos\n","iterCospi":"\niterCospi( iterator )\n    Returns an iterator which computes the cosine of each iterated value times\n    π.\n\n    Computes cos(πx) more accurately than cos(pi*x), especially for large x.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterCospi( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.cospi, iterCos\n","iterCounter":"\niterCounter( iterator )\n    Returns an iterator which iteratively computes the number of iterated\n    values.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterCounter( random.iterators.randu() );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    iterLength\n","iterCovercos":"\niterCovercos( iterator )\n    Returns an iterator which iteratively computes the coversed cosine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 6.28 );\n    > var it = iterCovercos( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.covercos, iterCoversin, iterVercos\n","iterCoversin":"\niterCoversin( iterator )\n    Returns an iterator which iteratively computes the coversed sine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 6.28 );\n    > var it = iterCoversin( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.coversin, iterCovercos, iterVersin\n","iterCubesSeq":"\niterCubesSeq( [options] )\n    Returns an iterator which generates a sequence of cubes.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 208063.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterCubesSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().value\n    8\n\n    See Also\n    --------\n    iterFourthPowersSeq, iterSquaresSeq\n","itercugmean":"\nitercugmean( iterator )\n    Returns an iterator which iteratively computes a cumulative geometric mean.\n\n    If provided a negative value, the iterated value is `NaN` for all future\n    invocations.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\n    > var it = itercugmean( arr );\n    > var v = it.next().value\n    2.0\n    > v = it.next().value\n    ~3.16\n    > v = it.next().value\n    ~3.11\n    > v = it.next().value\n    ~3.50\n\n    See Also\n    --------\n    itercuhmean, itercumean\n","itercuhmean":"\nitercuhmean( iterator )\n    Returns an iterator which iteratively computes a cumulative harmonic mean.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\n    > var it = itercuhmean( arr );\n    > var v = it.next().value\n    2.0\n    > v = it.next().value\n    ~2.86\n    > v = it.next().value\n    ~2.90\n    > v = it.next().value\n    ~3.24\n\n    See Also\n    --------\n    itercugmean, itercumean\n","itercumax":"\nitercumax( iterator )\n    Returns an iterator which iteratively computes a cumulative maximum value.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercumax( arr );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    2.0\n    > m = it.next().value\n    3.0\n    > m = it.next().value\n    5.0\n\n    See Also\n    --------\n    itercumidrange, itercumin, itercurange, itermax\n","itercumaxabs":"\nitercumaxabs( iterator )\n    Returns an iterator which iteratively computes a cumulative maximum absolute\n    value.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercumaxabs( arr );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    5.0\n    > m = it.next().value\n    5.0\n    > m = it.next().value\n    5.0\n\n    See Also\n    --------\n    itercumax, itercuminabs, itermaxabs\n","itercumean":"\nitercumean( iterator )\n    Returns an iterator which iteratively computes a cumulative arithmetic mean.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercumean( arr );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    -1.5\n    > m = it.next().value\n    0.0\n    > m = it.next().value\n    1.25\n\n    See Also\n    --------\n    itercumidrange, itercusum, itermean\n","itercumeanabs":"\nitercumeanabs( iterator )\n    Returns an iterator which iteratively computes a cumulative arithmetic mean\n    of absolute values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercumeanabs( arr );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    3.5\n    > m = it.next().value\n    ~3.33\n    > m = it.next().value\n    3.75\n\n    See Also\n    --------\n    itercumean, itercumeanabs2, itercusumabs, itermeanabs\n","itercumeanabs2":"\nitercumeanabs2( iterator )\n    Returns an iterator which iteratively computes a cumulative arithmetic mean\n    of squared absolute values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercumeanabs2( arr );\n    > var m = it.next().value\n    4.0\n    > m = it.next().value\n    14.5\n    > m = it.next().value\n    ~12.67\n    > m = it.next().value\n    15.75\n\n    See Also\n    --------\n    itercumean, itercumeanabs, itercusumabs2, itermeanabs2\n","itercumidrange":"\nitercumidrange( iterator )\n    Returns an iterator which iteratively computes a cumulative mid-range.\n\n    The mid-range is the arithmetic mean of maximum and minimum values.\n    Accordingly, the mid-range is the midpoint of the range and a measure of\n    central tendency.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercumidrange( arr );\n    > var v = it.next().value\n    2.0\n    > v = it.next().value\n    -1.5\n    > v = it.next().value\n    -1.0\n    > v = it.next().value\n    0.0\n\n    See Also\n    --------\n    itercumean, itercumax, itercumin, itercurange, itermidrange\n","itercumin":"\nitercumin( iterator )\n    Returns an iterator which iteratively computes a cumulative minimum value.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercumin( arr );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    -5.0\n    > m = it.next().value\n    -5.0\n    > m = it.next().value\n    -5.0\n\n    See Also\n    --------\n    itercumax, itercumidrange, itercurange, itermin\n","itercuminabs":"\nitercuminabs( iterator )\n    Returns an iterator which iteratively computes a cumulative minimum absolute\n    value.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercuminabs( arr );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    2.0\n    > m = it.next().value\n    2.0\n    > m = it.next().value\n    2.0\n\n    See Also\n    --------\n    itercumaxabs, itercumin, iterminabs\n","itercuprod":"\nitercuprod( iterator )\n    Returns an iterator which iteratively computes a cumulative product.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercuprod( arr );\n    > var p = it.next().value\n    2.0\n    > p = it.next().value\n    -10.0\n    > p = it.next().value\n    -30.0\n    > p = it.next().value\n    -150.0\n\n    See Also\n    --------\n    itercusum, iterprod\n","itercurange":"\nitercurange( iterator )\n    Returns an iterator which iteratively computes a cumulative range.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercurange( arr );\n    > var r = it.next().value\n    0.0\n    > r = it.next().value\n    7.0\n    > r = it.next().value\n    8.0\n    > r = it.next().value\n    10.0\n\n    See Also\n    --------\n    itercumax, itercumean, itercumin, iterrange\n","itercusum":"\nitercusum( iterator )\n    Returns an iterator which iteratively computes a cumulative sum.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercusum( arr );\n    > var s = it.next().value\n    2.0\n    > s = it.next().value\n    -3.0\n    > s = it.next().value\n    0.0\n    > s = it.next().value\n    5.0\n\n    See Also\n    --------\n    itercumean, itersum, itercuprod\n","itercusumabs":"\nitercusumabs( iterator )\n    Returns an iterator which iteratively computes a cumulative sum of absolute\n    values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercusumabs( arr );\n    > var s = it.next().value\n    2.0\n    > s = it.next().value\n    7.0\n    > s = it.next().value\n    10.0\n    > s = it.next().value\n    15.0\n\n    See Also\n    --------\n    itercumeanabs, itercusum, itersumabs\n","itercusumabs2":"\nitercusumabs2( iterator )\n    Returns an iterator which iteratively computes a cumulative sum of squared\n    absolute values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercusumabs2( arr );\n    > var s = it.next().value\n    4.0\n    > s = it.next().value\n    29.0\n    > s = it.next().value\n    38.0\n    > s = it.next().value\n    63.0\n\n    See Also\n    --------\n    itercumeanabs2, itercusumabs, itersumabs2\n","iterDatespace":"\niterDatespace( start, stop[, N][, options] )\n    Returns an iterator which returns evenly spaced dates over a specified\n    interval.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    start: integer|string|Date\n        Starting date either as a `Date` object, JavaScript timestamp, or a date\n        string (inclusive).\n\n    stop: integer|string|Date\n        Stopping value either as a `Date` object, JavaScript timestamp, or a\n        date string (inclusive).\n\n    N: integer (optional)\n        Number of values. Default: 100.\n\n    options: Object (optional)\n        Function options.\n\n    options.round: string (optional)\n        Specifies how sub-millisecond times should be rounded. Must be one of\n        the following: 'floor', 'ceil', or 'round'. Default: 'floor'.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var t1 = new Date();\n    > var it = iterDatespace( t1, new Date( t1.getTime()+86400000 ) );\n    > var v = it.next().value\n    <Date>\n    > v = it.next().value\n    <Date>\n\n    See Also\n    --------\n    iterator2array, iterIncrspace, iterLinspace, iterLogspace, iterStep\n","iterDedupe":"\niterDedupe( iterator[, limit] )\n    Returns an iterator which removes consecutive duplicated values.\n\n    `NaN` values are considered distinct.\n\n    Uniqueness is determined according to strict equality. Accordingly, objects\n    are *not* checked for deep equality.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    limit: integer (optional)\n        Number of allowed consecutive duplicates. Default: 1.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\n    > var it = iterDedupe( arr );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    2\n    > v = it.next().value\n    3\n\n    See Also\n    --------\n    iterDedupeBy, iterUnique\n","iterDedupeBy":"\niterDedupeBy( iterator, [limit,] fcn )\n    Returns an iterator which removes consecutive values that resolve to the\n    same value according to a provided function.\n\n    The provided function is provided five arguments:\n\n    - curr: current source iterated value.\n    - sprev: previous source iterated value.\n    - dprev: previous downstream iterated value.\n    - index: source iteration index (zero-based).\n    - acc: previous resolved value.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    limit: integer (optional)\n        Number of allowed consecutive duplicates. Default: 1.\n\n    fcn: Function\n        Function indicating whether an iterated value is a \"duplicate\".\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\n    > function fcn( v ) { return v; };\n    > var it = iterDedupeBy( arr, fcn );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    2\n    > v = it.next().value\n    3\n\n    See Also\n    --------\n    iterDedupe, iterUnique\n","iterDeg2rad":"\niterDeg2rad( iterator )\n    Returns an iterator which iteratively converts an angle from degrees to\n    radians.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -360.0, 360.0 );\n    > var it = iterDeg2rad( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.deg2rad, iterRad2deg\n","iterDigamma":"\niterDigamma( iterator )\n    Returns an iterator which iteratively evaluates the digamma function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.01, 5.0 );\n    > var it = iterDigamma( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.digamma, iterGamma, iterTrigamma\n","iterDiracComb":"\niterDiracComb( [options] )\n    Returns an iterator which generates a Dirac comb.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Period (i.e., the number of iterations before a waveform repeats).\n        Default: 10.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterDiracComb();\n    > var v = it.next().value\n    Infinity\n    > v = it.next().value\n    0.0\n\n    See Also\n    --------\n    iterPulse\n","iterDiracDelta":"\niterDiracDelta( iterator )\n    Returns an iterator which iteratively evaluates the Dirac delta function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterDiracDelta( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.diracDelta\n","iterDivide":"\niterDivide( iter0, ...iterator )\n    Returns an iterator which performs element-wise division of two or more\n    iterators.\n\n    The length of the returned iterator is equal to the length of the shortest\n    provided iterator. In other words, the returned iterator ends once *one* of\n    the provided iterators ends.\n\n    If provided a numeric value as an iterator argument, the value is broadcast\n    as an infinite iterator which always returns the provided value.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iter0: Object\n        Input iterator.\n\n    iterator: ...Object\n        Iterators whose values are used as divisors.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 3.0, 2.0 ] );\n    > var it2 = array2iterator( [ 1.0, 4.0 ] );\n    > var it = iterDivide( it1, it2 );\n    > var v = it.next().value\n    3.0\n    > v = it.next().value\n    0.5\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterAdd, iterDivide, iterMultiply\n","iterDoWhileEach":"\niterDoWhileEach( iterator, predicate, fcn[, thisArg] )\n    Returns an iterator which invokes a function for each iterated value before\n    returning the iterated value until either a predicate function returns false\n    or the iterator has iterated over all values.\n\n    The condition is evaluated *after* executing the provided function; thus,\n    `fcn` *always* executes at least once.\n\n    When invoked, both input functions are provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index (zero-based).\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    predicate: Function\n        Function which indicates whether to continue iterating.\n\n    fcn: Function\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === v };\n    > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n    > var it = iterDoWhileEach( random.iterators.randu(), predicate, f );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterDoUntilEach, iterUntilEach, iterWhileEach\n","iterEllipe":"\niterEllipe( iterator )\n    Returns an iterator which iteratively computes the complete elliptic\n    integral of the second kind.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -1.0, 1.0 );\n    > var it = iterEllipe( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.ellipe, iterEllipk\n","iterEllipk":"\niterEllipk( iterator )\n    Returns an iterator which iteratively computes the complete elliptic\n    integral of the first kind.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -1.0, 1.0 );\n    > var it = iterEllipk( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.ellipk, iterEllipe\n","iterEmpty":"\niterEmpty()\n    Returns an empty iterator.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterEmpty();\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterConstant\n","iterErf":"\niterErf( iterator )\n    Returns an iterator which iteratively evaluates the error function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterErf( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.erf, iterErfc, iterErfinv, iterErfcinv\n","iterErfc":"\niterErfc( iterator )\n    Returns an iterator which iteratively evaluates the complementary error\n    function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterErfc( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.erfc, iterErf, iterErfinv, iterErfcinv\n","iterErfcinv":"\niterErfcinv( iterator )\n    Returns an iterator which iteratively evaluates the inverse complementary\n    error function.\n\n    The domain of inverse complementary error function is restricted to [0,2].\n    If an iterated value is outside of the domain, the returned iterator returns\n    `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterErfcinv( random.iterators.uniform( 0.0, 2.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.erfcinv, iterErf, iterErfc, iterErfinv\n","iterErfinv":"\niterErfinv( iterator )\n    Returns an iterator which iteratively evaluates the inverse error function.\n\n    The domain of inverse error function is restricted to [-1,1]. If an iterated\n    value is outside of the domain, the returned iterator returns `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterErfinv( random.iterators.uniform( -1.0, 1.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.erfinv, iterErf, iterErfc, iterErfcinv\n","iterEta":"\niterEta( iterator )\n    Returns an iterator which iteratively evaluates the Dirichlet eta function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterEta( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.eta\n","iterEvenIntegersSeq":"\niterEvenIntegersSeq( [options] )\n    Returns an iterator which generates an interleaved sequence of even\n    integers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 9007199254740992.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterEvenIntegersSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    2\n    > v = it.next().value\n    -2\n\n    See Also\n    --------\n    iterIntegersSeq, iterOddIntegersSeq\n","iterEvery":"\niterEvery( iterator )\n    Tests whether all iterated values are truthy.\n\n    The function immediately returns upon encountering a falsy value.\n\n    If provided an iterator which does not return any iterated values, the\n    function returns `true`.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `false` if a value is falsy; otherwise, the\n        function returns `true`.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1, 1, 1, 1, 0 ] );\n    > var bool = iterEvery( arr )\n    false\n\n    See Also\n    --------\n    iterAny, iterEveryBy, iterForEach, iterNone, iterSome\n","iterEveryBy":"\niterEveryBy( iterator, predicate[, thisArg ] )\n    Tests whether every iterated value passes a test implemented by a predicate\n    function.\n\n    The predicate function is provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index.\n\n    The function immediately returns upon encountering a falsy return value.\n\n    If provided an iterator which does not return any iterated values, the\n    function returns `true`.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if a predicate function returns a truthy\n        value for all iterated values. Otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\n    > function fcn( v ) { return ( v > 0 ); };\n    > var bool = iterEveryBy( arr, fcn )\n    true\n\n    See Also\n    --------\n    iterAnyBy, iterEvery, iterForEach, iterNoneBy, iterSomeBy\n","iterExp":"\niterExp( iterator )\n    Returns an iterator which iteratively evaluates the natural exponential\n    function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterExp( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.exp, iterExp10, iterExp2, iterExpm1, iterLn\n","iterExp2":"\niterExp2( iterator )\n    Returns an iterator which iteratively evaluates the base `2` exponential\n    function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -50.0, 50.0 );\n    > var it = iterExp2( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.exp2, iterExp, iterExp10, iterLog2\n","iterExp10":"\niterExp10( iterator )\n    Returns an iterator which iteratively evaluates the base `10` exponential\n    function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -50.0, 50.0 );\n    > var it = iterExp10( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.exp10, iterExp, iterExp2, iterLog10\n","iterExpit":"\niterExpit( iterator )\n    Returns an iterator which iteratively evaluates the standard logistic\n    function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 1.0 );\n    > var it = iterExpit( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.expit, iterExp, iterLogit\n","iterExpm1":"\niterExpm1( iterator )\n    Returns an iterator which iteratively computes `exp(x) - 1`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -5.0, 5.0 );\n    > var it = iterExpm1( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.expm1, iterExp, iterExpm1rel\n","iterExpm1rel":"\niterExpm1rel( iterator )\n    Returns an iterator which iteratively evaluates the relative error\n    exponential.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -50.0, 50.0 );\n    > var it = iterExpm1rel( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.expm1rel, iterExp, iterExpm1\n","iterFactorial":"\niterFactorial( iterator )\n    Returns an iterator which iteratively evaluates the factorial function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterFactorial( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.factorial, iterFactorialln\n","iterFactorialln":"\niterFactorialln( iterator )\n    Returns an iterator which iteratively evaluates the natural logarithm of the\n    factorial function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterFactorialln( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.factorialln, iterFactorial\n","iterFactorialsSeq":"\niterFactorialsSeq( [options] )\n    Returns an iterator which generates a sequence of factorials.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterFactorialsSeq();\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    1\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    iterFactorial\n","iterFibonacciSeq":"\niterFibonacciSeq( [options] )\n    Returns an iterator which generates a Fibonacci sequence.\n\n    The returned iterator can only generate the first 79 Fibonacci numbers, as\n    larger Fibonacci numbers cannot be safely represented in double-precision\n    floating-point format.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 79.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterFibonacciSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n\n    See Also\n    --------\n    base.fibonacci, iterLucasSeq, iterNegaFibonacciSeq, iterNonFibonacciSeq\n","iterFifthPowersSeq":"\niterFifthPowersSeq( [options] )\n    Returns an iterator which generates a sequence of fifth powers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 9741.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterFifthPowersSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().value\n    32\n\n    See Also\n    --------\n    iterCubesSeq, iterFourthPowersSeq, iterSquaresSeq\n","iterFill":"\niterFill( iterator, value[, begin[, end]] )\n    Returns an iterator which replaces all values from a provided iterator from\n    a start index to an end index with a static value.\n\n    If `end` exceeds the length of the provided iterator, the returned iterator\n    replaces the subsequence of iterated values starting from `begin` until the\n    last iterated value of the provided iterator.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    value: any\n        Static value.\n\n    begin: integer (optional)\n        Start iteration index (zero-based and inclusive). Default: 0.\n\n    end: integer (optional)\n        End iteration index (zero-based and non-inclusive).\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterFill( random.iterators.randu(), 3.14, 0, 2 );\n    > var r = it.next().value\n    3.14\n    > r = it.next().value\n    3.14\n    > r = it.next().value\n    <number>\n\n","iterFilter":"\niterFilter( iterator, predicate[, thisArg] )\n    Returns an iterator which filters a provided iterator's values according to\n    a predicate function.\n\n    When invoked, the predicate function is provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index (zero-based).\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    predicate: Function\n        Predicate function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > function f( v ) { return ( v > 2 ); };\n    > var it1 = array2iterator( [ 1, 3, 2, 4 ] );\n    > var it2 = iterFilter( it1, f );\n    > var v = it2.next().value\n    3\n    > v = it2.next().value\n    4\n\n    See Also\n    --------\n    iterFilterMap, iterMap, iterReject\n","iterFilterMap":"\niterFilterMap( iterator, fcn[, thisArg] )\n    Returns an iterator which both filters and maps a provided iterator's\n    values.\n\n    When invoked, the callback function is provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index (zero-based).\n\n    If the callback returns `undefined`, the iterator invokes the function for\n    the next value of the provided iterator; otherwise, the iterator returns\n    the callback's return value.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    fcn: Function\n        Callback function which both filters and maps.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > function f( v ) { if ( v > 2 ) { return v * 10 }; };\n    > var it1 = array2iterator( [ 1, 3, 2, 4 ] );\n    > var it2 = iterFilterMap( it1, f );\n    > var v = it2.next().value\n    30\n    > v = it2.next().value\n    40\n\n    See Also\n    --------\n    iterFilter, iterMap\n","iterFirst":"\niterFirst( iterator )\n    Returns the first iterated value.\n\n    The function does *not* consume an entire iterator before returning.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    Returns\n    -------\n    v: any\n        The first iterated value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1, 0, 0, 0, 0 ] );\n    > var v = iterFirst( arr )\n    1\n\n    See Also\n    --------\n    iterHead, iterLast, iterNth\n","iterFlatTopPulse":"\niterFlatTopPulse( [options] )\n    Returns an iterator which generates a flat top pulse waveform.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Pulse period (i.e., the number of iterations until a waveform repeats).\n        Default: 100.\n\n    options.duration: integer (optional)\n        Pulse duration. Must be greater than 2. Default: options.period.\n\n    options.amplitude: number (optional)\n        Amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterFlatTopPulse();\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterPulse\n","iterFloor":"\niterFloor( iterator )\n    Returns an iterator which rounds each iterated value toward negative\n    infinity.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterFloor( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.floor, iterCeil, iterRound\n","iterFloor2":"\niterFloor2( iterator )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    two toward negative infinity.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterFloor2( random.iterators.uniform( -100.0, 100.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.floor2, iterCeil2, iterFloor, iterFloor10, iterRound2\n","iterFloor10":"\niterFloor10( iterator )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    10 toward negative infinity.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterFloor10( random.iterators.uniform( -100.0, 100.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.floor10, iterCeil10, iterFloor, iterFloor2, iterRound10\n","iterFlow":"\niterFlow( methods )\n    Returns a fluent interface iterator constructor with a customized prototype\n    based on provided methods.\n\n    The methods argument should be an object which maps constructor method names\n    to iterator functions.\n\n    Each iterator function should have the following function signature:\n\n      iterFcn( iterator, ...args )\n\n    When a fluent interface iterator method is invoked, the method invokes the\n    corresponding iterator function with an iterator and provided method\n    arguments.\n\n    If an iterator function returns an iterator, the corresponding fluent\n    interface method returns a new fluent interface instance; otherwise, the\n    corresponding fluent interface method returns the iterator function result.\n\n    The iterator function evaluation context is always `null`.\n\n    Iterator functions which return iterators are expected to return iterator\n    protocol-compliant objects (i.e., an object having a `next` method which\n    returns the next iterated value (if one exists) assigned to a `value`\n    property and a `done` property having a boolean value indicating whether the\n    iterator is finished).\n\n    If an environment supports `Symbol.iterator`, the returned constructor\n    returns iterators which are iterable.\n\n    Parameters\n    ----------\n    methods: Object\n        An object mapping method names to iterator functions.\n\n    Returns\n    -------\n    FluentIterator: Function\n        Fluent interface iterator constructor.\n\n    Examples\n    --------\n    > var o = {};\n    > o.head = iterHead;\n    > o.some = iterSome;\n    > var fiter = iterFlow( o )\n\n\nFluentIterator( iterator )\n    Returns a new fluent interface iterator from a source iterator.\n\n    Parameters\n    ----------\n    iterator: Object\n        Source iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Fluent interface iterator.\n\n    Examples\n    --------\n    > var o = {};\n    > o.head = iterHead;\n    > o.some = iterSome;\n    > var fiter = iterFlow( o );\n    > var it = fiter( array2iterator( [ 0, 0, 1, 1, 1 ] ) );\n    > var bool = it.head( 3 ).some( 2 )\n    false\n\n\nFluentIterator.prototype.next()\n    Returns the next iterated value.\n\n    Returns\n    -------\n    out: Object\n        Iterator protocol-compliant object.\n\n    out.value: any (optional)\n        Next iterated value (if one exists).\n\n    out.done: boolean\n        Boolean flag indicating whether the iterator is finished.\n\n    Examples\n    --------\n    > var o = {};\n    > o.head = iterHead;\n    > o.some = iterSome;\n    > var fiter = iterFlow( o );\n    > var it1 = fiter( array2iterator( [ 0, 0, 1, 1, 1 ] ) );\n    > var it2 = it1.head( 3 );\n    > var v = it2.next().value\n    0\n    > v = it2.next().value\n    0\n    > v = it2.next().value\n    1\n\n\nFluentIterator.prototype.return( [value] )\n    Finishes an iterator and returns a provided value.\n\n    Parameters\n    ----------\n    value: any (optional)\n        Value to return.\n\n    Returns\n    -------\n    out: Object\n        Iterator protocol-compliant object.\n\n    out.value: any (optional)\n        Next iterated value (if one exists).\n\n    out.done: boolean\n        Boolean flag indicating whether the iterator is finished.\n\n    Examples\n    --------\n    > var o = {};\n    > o.head = iterHead;\n    > o.some = iterSome;\n    > var fiter = iterFlow( o );\n    > var it1 = fiter( array2iterator( [ 0, 0, 1, 1, 1 ] ) );\n    > var it2 = it1.head( 3 );\n    > var v = it2.next().value\n    0\n    > var bool = it2.return().done\n    true\n    > v = it2.next().value\n    undefined\n\n    See Also\n    --------\n    iterPipeline\n","iterForEach":"\niterForEach( iterator, fcn[, thisArg] )\n    Returns an iterator which invokes a function for each iterated value before\n    returning the iterated value.\n\n    When invoked, the input function is provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index (zero-based).\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    fcn: Function\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n    > var it = iterForEach( random.iterators.randu(), f );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterMap\n","iterFourthPowersSeq":"\niterFourthPowersSeq( [options] )\n    Returns an iterator which generates a sequence of fourth powers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 9741.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterFourthPowersSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().value\n    16\n\n    See Also\n    --------\n    iterCubesSeq, iterFifthPowersSeq, iterSquaresSeq\n","iterFresnelc":"\niterFresnelc( iterator )\n    Returns an iterator which iteratively computes the Fresnel integral C(x).\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 10.0 );\n    > var it = iterFresnelc( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.fresnelc, iterFresnels\n","iterFresnels":"\niterFresnels( iterator )\n    Returns an iterator which iteratively computes the Fresnel integral S(x).\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 10.0 );\n    > var it = iterFresnels( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.fresnels, iterFresnelc\n","iterGamma":"\niterGamma( iterator )\n    Returns an iterator which iteratively evaluates the gamma function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterGamma( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.gamma, iterGamma1pm1, iterGammaln\n","iterGamma1pm1":"\niterGamma1pm1( iterator )\n    Returns an iterator which iteratively computes `gamma(x+1) - 1` without\n    cancellation errors for small `x`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -5.0, 5.0 );\n    > var it = iterGamma1pm1( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.gamma1pm1, iterGamma\n","iterGammaln":"\niterGammaln( iterator )\n    Returns an iterator which iteratively evaluates the natural logarithm of the\n    gamma function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterGammaln( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.gammaln, iterGamma\n","iterHacovercos":"\niterHacovercos( iterator )\n    Returns an iterator which iteratively computes the half-value coversed\n    cosine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 6.28 );\n    > var it = iterHacovercos( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.hacovercos, iterCovercos, iterHacoversin\n","iterHacoversin":"\niterHacoversin( iterator )\n    Returns an iterator which iteratively computes the half-value coversed sine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 6.28 );\n    > var it = iterHacoversin( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.hacoversin, iterCoversin, iterHacovercos\n","iterHannPulse":"\niterHannPulse( [options] )\n    Returns an iterator which generates a Hann pulse waveform.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Pulse period (i.e., the number of iterations until a waveform repeats).\n        Default: 100.\n\n    options.duration: integer (optional)\n        Pulse duration. Must be greater than 2. Default: options.period.\n\n    options.amplitude: number (optional)\n        Amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterHannPulse();\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterBartlettHannPulse, iterPulse, iterSineWave\n","iterHavercos":"\niterHavercos( iterator )\n    Returns an iterator which iteratively computes the half-value versed cosine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 6.28 );\n    > var it = iterHavercos( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.havercos, iterHaversin, iterVercos\n","iterHaversin":"\niterHaversin( iterator )\n    Returns an iterator which iteratively computes the half-value versed sine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 6.28 );\n    > var it = iterHaversin( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.haversin, iterHavercos, iterVersin\n","iterHead":"\niterHead( iterator, n )\n    Returns an iterator which returns the first `n` values of a provided\n    iterator.\n\n    If a provided iterator only generates `m` values and `m` is less than `n`,\n    the returned iterator only returns `m` values.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    n: integer\n        Number of values.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterHead( random.iterators.randu(), 5 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterFirst, iterSlice\n","iterIncrspace":"\niterIncrspace( start, stop[, increment] )\n    Returns an iterator which returns evenly spaced numbers according to a\n    specified increment.\n\n    Beware that values which follow the starting value are subject to floating-\n    point rounding errors.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    start: number\n        Starting value (inclusive).\n\n    stop: number\n        Stopping value (exclusive).\n\n    increment: number (optional)\n        Increment. Default: 1.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterIncrspace( 0, 101, 2 );\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    iterator2array, iterDatespace, iterLinspace, iterLogspace, iterStep, iterUnitspace\n","iterIntegersSeq":"\niterIntegersSeq( [options] )\n    Returns an iterator which generates an interleaved integer sequence.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 18014398509481984.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterIntegersSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().value\n    -1\n\n    See Also\n    --------\n    iterNegativeIntegersSeq, iterNonNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterPositiveIntegersSeq\n","iterIntersection":"\niterIntersection( iter0, ...iterator )\n    Returns an iterator which returns the intersection of two or more iterators.\n\n    Value \"uniqueness\" is determined according to strict equality.\n\n    A returned iterator internally buffers unique values and, thus, has O(N)\n    memory requirements, where `N` is the length of the first iterator.\n\n    Do *not* provide iterators having infinite length.\n\n    If an environment supports Symbol.iterator and all provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iter0: Object\n        Input iterator.\n\n    iterator: ...Object\n        Input iterators.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n    > var it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\n    > var it = iterIntersection( it1, it2 );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    2\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterIntersectionByHash, iterUnion, iterUnique\n","iterIntersectionByHash":"\niterIntersectionByHash( iter0, ...iterator, hashFcn[, thisArg] )\n    Returns an iterator which returns the intersection of two or more iterators\n    according to a hash function.\n\n    An iterated value is considered \"unique\" if the hash function returns a\n    unique hash value for that iterated value. Beware that this *may* result in\n    unexpected behavior. Namely, only the first iterated value mapping to a\n    particular hash function result is returned, even if subsequent values,\n    while mapping to the same hash, are different. Accordingly, iteration order\n    *does* matter.\n\n    A returned iterator internally buffers unique hashes, along with the *first*\n    iterated value resolving to a hash, and, thus, has O(N) memory requirements,\n    where `N` is the length of the first iterator.\n\n    Do *not* provide iterators having infinite length.\n\n    If an environment supports Symbol.iterator and all provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iter0: Object\n        Input iterator.\n\n    iterator: ...Object\n        Input iterators.\n\n    hashFcn: Function\n        Hash function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n    > var it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\n    > function f( v ) { return v.toString(); };\n    > var it = iterIntersectionByHash( it1, it2, f );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    2\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterIntersection, iterUniqueByHash\n","iterInv":"\niterInv( iterator )\n    Returns an iterator which iteratively computes the multiplicative inverse.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterInv( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.inv, iterPow\n","iterLanczosPulse":"\niterLanczosPulse( [options] )\n    Returns an iterator which generates a Lanczos pulse waveform.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Pulse period (i.e., the number of iterations until a waveform repeats).\n        Default: 100.\n\n    options.duration: integer (optional)\n        Pulse duration. Must be greater than 2. Default: options.period.\n\n    options.amplitude: number (optional)\n        Amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterLanczosPulse();\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterPulse, iterPeriodicSinc\n","iterLast":"\niterLast( iterator )\n    Consumes an entire iterator and returns the last iterated value.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    Returns\n    -------\n    v: any\n        The last iterated value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n    > var v = iterLast( arr )\n    1\n\n    See Also\n    --------\n    iterFirst, iterNth\n","iterLength":"\niterLength( iterator )\n    Consumes an entire iterator and returns the number of iterated values.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    Returns\n    -------\n    len: integer\n        Iterator length.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n    > var len = iterLength( arr )\n    5\n\n    See Also\n    --------\n    iterCounter\n","iterLinspace":"\niterLinspace( start, stop[, N] )\n    Returns an iterator which returns evenly spaced numbers over a specified\n    interval.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    start: number\n        Starting value (inclusive).\n\n    stop: number\n        Stopping value (inclusive).\n\n    N: integer (optional)\n        Number of values. Default: 100.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterLinspace( 0, 99, 100 );\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n\n    See Also\n    --------\n    iterator2array, iterDatespace, iterIncrspace, iterLogspace, iterStep, iterUnitspace\n","iterLn":"\niterLn( iterator )\n    Returns an iterator which iteratively evaluates the natural logarithm.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterLn( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.ln, iterExp, iterLog10, iterLog1p, iterLog2\n","iterLog":"\niterLog( x, b )\n    Returns an iterator which iteratively computes the base `b` logarithm.\n\n    For negative `b` or `x` iterated values, the returned iterator returns\n    `NaN`.\n\n    The length of the returned iterator is equal to the length of the shortest\n    provided iterator. In other words, the returned iterator ends once *one* of\n    the provided iterators ends.\n\n    If provided a numeric value as an iterator argument, the value is broadcast\n    as an infinite iterator which always returns the provided value.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    x: Object|number\n        Input iterator.\n\n    b: Object|number\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = random.iterators.uniform( 0.0, 100.0 );\n    > var y = random.iterators.uniform( 0.0, 10.0 );\n    > var it = iterLog( x, y );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.log, iterLog10, iterLog1p, iterLog2, iterPow\n","iterLog1mexp":"\niterLog1mexp( iterator )\n    Returns an iterator which iteratively evaluates the natural logarithm of\n    `1-exp(-|x|)`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterLog1mexp( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.log1mexp, iterLog, iterLog1p, iterLog1pexp, iterPow\n","iterLog1p":"\niterLog1p( iterator )\n    Returns an iterator which iteratively evaluates the natural logarithm of\n    `1+x`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterLog1p( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.log1p, iterLog, iterLog10, iterLog2, iterPow\n","iterLog1pexp":"\niterLog1pexp( iterator )\n    Returns an iterator which iteratively evaluates the natural logarithm of\n    `1+exp(x)`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterLog1pexp( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.log1pexp, iterLog, iterLog1p, iterLog1mexp, iterPow\n","iterLog2":"\niterLog2( iterator )\n    Returns an iterator which iteratively evaluates the binary logarithm.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterLog2( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.log2, iterLog, iterLog10, iterLog1p, iterPow\n","iterLog10":"\niterLog10( iterator )\n    Returns an iterator which iteratively evaluates the common logarithm\n    (logarithm with base 10).\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterLog10( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.log10, iterLog, iterLog1p, iterLog2, iterPow\n","iterLogit":"\niterLogit( iterator )\n    Returns an iterator which iteratively evaluates the logit function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 1.0 );\n    > var it = iterLogit( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.logit\n","iterLogspace":"\niterLogspace( start, stop[, N][, options] )\n    Returns an iterator which returns evenly spaced numbers on a log scale.\n\n    In linear space, the sequence starts at `base` raised to the power of\n    `start` and ends with `base` raised to the power of `stop`.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    start: number\n        Exponent of starting value.\n\n    stop: number\n        Exponent of stopping value.\n\n    N: integer (optional)\n        Number of values. Default: 100.\n\n    options: Object (optional)\n        Function options.\n\n    options.base: number (optional)\n        Base of log space. Default: 10.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterLogspace( 0, 3, 4 );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    10\n\n    See Also\n    --------\n    iterator2array, iterDatespace, iterIncrspace, iterLinspace, iterStep\n","iterLucasSeq":"\niterLucasSeq( [options] )\n    Returns an iterator which generates a Lucas sequence.\n\n    The returned iterator can only generate the first 77 Lucas numbers, as\n    larger Lucas numbers cannot be safely represented in double-precision\n    floating-point format.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 77.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterLucasSeq();\n    > var v = it.next().value\n    2\n    > v = it.next().value\n    1\n\n    See Also\n    --------\n    base.lucas, iterFibonacciSeq, iterNegaLucasSeq\n","iterMap":"\niterMap( iterator, fcn[, thisArg] )\n    Returns an iterator which invokes a function for each iterated value.\n\n    When invoked, the input function is provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index (zero-based).\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    fcn: Function\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > function f( v ) { return v * 10.0; };\n    > var it = iterMap( random.iterators.randu(), f );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterFilter, iterFilterMap, iterForEach, iterReject\n","iterMapN":"\niterMapN( iter0, ...iterator, fcn[, thisArg] )\n    Returns an iterator which transforms iterated values from two or more\n    iterators by applying the iterated values as arguments to a provided\n    function.\n\n    When invoked, the callback function is provided `N+1` arguments, where `N`\n    is the number of provided iterators and the last argument is the iteration\n    index:\n\n    - ...value: iterated values.\n    - index: iteration index (zero-based).\n\n    The length of the returned iterator is equal to the length of the shortest\n    provided iterator. In other words, the returned iterator ends once *one* of\n    the provided iterators ends.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iter0: Object\n        Input iterator.\n\n    iterator: ...Object\n        Iterators.\n\n    fcn: Function\n        Function to invoke with iterated values.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1.0, 2.0 ] );\n    > var it2 = array2iterator( [ 3.0, 4.0 ] );\n    > function fcn( x, y ) { return x + y; };\n    > var it = iterMapN( it1, it2, fcn );\n    > var v = it.next().value\n    4.0\n    > v = it.next().value\n    6.0\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterMap\n","itermax":"\nitermax( iterator )\n    Computes the maximum value of all iterated values.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Maximum value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var m = itermax( arr )\n    3.0\n\n    See Also\n    --------\n    itermidrange, itermin, itermmax, iterrange\n","itermaxabs":"\nitermaxabs( iterator )\n    Computes the maximum absolute value of all iterated values.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Maximum absolute value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var m = itermaxabs( arr )\n    4.0\n\n    See Also\n    --------\n    itermax, iterminabs, itermmaxabs\n","itermean":"\nitermean( iterator )\n    Computes an arithmetic mean over all iterated values.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Arithmetic mean.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var m = itermean( arr )\n    2.5\n\n    See Also\n    --------\n    itermidrange, itermmean, iterstdev, itersum, itervariance\n","itermeanabs":"\nitermeanabs( iterator )\n    Computes an arithmetic mean of absolute values for all iterated values.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Arithmetic mean of absolute values.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\n    > var m = itermeanabs( arr )\n    2.5\n\n    See Also\n    --------\n    itermean, itermmeanabs, itersumabs\n","itermeanabs2":"\nitermeanabs2( iterator )\n    Computes an arithmetic mean of squared absolute values for all iterated\n    values.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Arithmetic mean of squared absolute values.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\n    > var m = itermeanabs2( arr )\n    7.5\n\n    See Also\n    --------\n    itermean, itermeanabs, itermmeanabs2, itersumabs2\n","itermidrange":"\nitermidrange( iterator )\n    Computes the mid-range of all iterated values.\n\n    The mid-range is the arithmetic mean of maximum and minimum values.\n    Accordingly, the mid-range is the midpoint of the range and a measure of\n    central tendency.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Mid-range.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var v = itermidrange( arr )\n    -0.5\n\n    See Also\n    --------\n    itermean, itermax, itermin, iterrange\n","itermin":"\nitermin( iterator )\n    Computes the minimum value of all iterated values.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Minimum value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\n    > var m = itermin( arr )\n    -3.0\n\n    See Also\n    --------\n    itermax, itermidrange, itermmin, iterrange\n","iterminabs":"\niterminabs( iterator )\n    Computes the minimum absolute value of all iterated values.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Minimum absolute value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var m = iterminabs( arr )\n    1.0\n\n    See Also\n    --------\n    itermaxabs, itermin, itermminabs\n","itermmax":"\nitermmax( iterator, W )\n    Returns an iterator which iteratively computes a moving maximum value.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving maximum value.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermmax( arr, 3 );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    2.0\n    > m = it.next().value\n    3.0\n    > m = it.next().value\n    5.0\n\n    See Also\n    --------\n    itermax, itermmidrange, itermmin, itermrange\n","itermmaxabs":"\nitermmaxabs( iterator, W )\n    Returns an iterator which iteratively computes a moving maximum absolute\n    value.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving maximum absolute value.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermmaxabs( arr, 3 );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    5.0\n    > m = it.next().value\n    5.0\n    > m = it.next().value\n    5.0\n\n    See Also\n    --------\n    itermaxabs, itermmax, itermminabs\n","itermmean":"\nitermmean( iterator, W )\n    Returns an iterator which iteratively computes a moving arithmetic mean.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving mean.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermmean( arr, 3 );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    -1.5\n    > m = it.next().value\n    0.0\n    > m = it.next().value\n    1.0\n\n    See Also\n    --------\n    itermean, itermsum\n","itermmeanabs":"\nitermmeanabs( iterator, W )\n    Returns an iterator which iteratively computes a moving arithmetic mean of\n    absolute values.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving mean of absolute values.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermmeanabs( arr, 3 );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    3.5\n    > m = it.next().value\n    ~3.33\n    > m = it.next().value\n    ~4.33\n\n    See Also\n    --------\n    itermeanabs, itermmean, itermsumabs\n","itermmeanabs2":"\nitermmeanabs2( iterator, W )\n    Returns an iterator which iteratively computes a moving arithmetic mean of\n    squared absolute values.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving mean of squared absolute values.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermmeanabs2( arr, 3 );\n    > var m = it.next().value\n    4.0\n    > m = it.next().value\n    14.5\n    > m = it.next().value\n    ~12.67\n    > m = it.next().value\n    ~19.67\n\n    See Also\n    --------\n    itermeanabs2, itermmeanabs, itermsumabs2\n","itermmidrange":"\nitermmidrange( iterator, W )\n    Returns an iterator which iteratively computes a moving mid-range.\n\n    The mid-range is the arithmetic mean of maximum and minimum values.\n    Accordingly, the mid-range is the midpoint of the range and a measure of\n    central tendency.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving mid-range.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermmidrange( arr, 3 );\n    > var v = it.next().value\n    2.0\n    > v = it.next().value\n    -1.5\n    > v = it.next().value\n    -1.0\n    > v = it.next().value\n    0.0\n\n    See Also\n    --------\n    itermidrange, itermmean, itermmax, itermmin, itermrange\n","itermmin":"\nitermmin( iterator, W )\n    Returns an iterator which iteratively computes a moving minimum value.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving minimum value.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermmin( arr, 3 );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    -5.0\n    > m = it.next().value\n    -5.0\n    > m = it.next().value\n    -5.0\n\n    See Also\n    --------\n    itermin, itermmax, itermmidrange, itermrange\n","itermminabs":"\nitermminabs( iterator, W )\n    Returns an iterator which iteratively computes a moving minimum absolute\n    value.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving minimum absolute value.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermminabs( arr, 3 );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    2.0\n    > m = it.next().value\n    2.0\n    > m = it.next().value\n    3.0\n\n    See Also\n    --------\n    iterminabs, itermmaxabs, itermmin\n","iterMod":"\niterMod( iter0, ...iterator )\n    Returns an iterator which performs an element-wise modulo operation of two\n    or more iterators.\n\n    The length of the returned iterator is equal to the length of the shortest\n    provided iterator. In other words, the returned iterator ends once *one* of\n    the provided iterators ends.\n\n    If provided a numeric value as an iterator argument, the value is broadcast\n    as an infinite iterator which always returns the provided value.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iter0: Object\n        Input iterator.\n\n    iterator: ...Object\n        Iterators whose values are used as divisors.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 3.0, 2.0 ] );\n    > var it2 = array2iterator( [ 1.0, 4.0 ] );\n    > var it = iterMod( it1, it2 );\n    > var v = it.next().value\n    0.0\n    > v = it.next().value\n    2.0\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterDivide\n","itermprod":"\nitermprod( iterator, W )\n    Returns an iterator which iteratively computes a moving product.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving product.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermprod( arr, 3 );\n    > var p = it.next().value\n    2.0\n    > p = it.next().value\n    -10.0\n    > p = it.next().value\n    -30.0\n    > p = it.next().value\n    -75.0\n\n    See Also\n    --------\n    itermsum, iterprod\n","itermrange":"\nitermrange( iterator, W )\n    Returns an iterator which iteratively computes a moving range.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving range.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermrange( arr, 3 );\n    > var m = it.next().value\n    0.0\n    > m = it.next().value\n    7.0\n    > m = it.next().value\n    8.0\n    > m = it.next().value\n    10.0\n\n    See Also\n    --------\n    itermmax, itermmean, itermmin, iterrange\n","itermsum":"\nitermsum( iterator, W )\n    Returns an iterator which iteratively computes a moving sum.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving sum.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator and the provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermsum( arr, 3 );\n    > var s = it.next().value\n    2.0\n    > s = it.next().value\n    -3.0\n    > s = it.next().value\n    0.0\n    > s = it.next().value\n    3.0\n\n    See Also\n    --------\n    itermmean, itersum\n","itermsumabs":"\nitermsumabs( iterator, W )\n    Returns an iterator which iteratively computes a moving sum of absolute\n    values.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving sum.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermsumabs( arr, 3 );\n    > var s = it.next().value\n    2.0\n    > s = it.next().value\n    7.0\n    > s = it.next().value\n    10.0\n    > s = it.next().value\n    13.0\n\n    See Also\n    --------\n    itermmeanabs, itermsum, itersum, itersumabs\n","itermsumabs2":"\nitermsumabs2( iterator, W )\n    Returns an iterator which iteratively computes a moving sum of squared\n    absolute values.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving sum.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermsumabs2( arr, 3 );\n    > var s = it.next().value\n    4.0\n    > s = it.next().value\n    29.0\n    > s = it.next().value\n    38.0\n    > s = it.next().value\n    59.0\n\n    See Also\n    --------\n    itermmeanabs2, itermsumabs, itersumabs, itersumabs2\n","iterMultiply":"\niterMultiply( iter0, ...iterator )\n    Returns an iterator which performs element-wise multiplication of two or\n    more iterators.\n\n    The length of the returned iterator is equal to the length of the shortest\n    provided iterator. In other words, the returned iterator ends once *one* of\n    the provided iterators ends.\n\n    If provided a numeric value as an iterator argument, the value is broadcast\n    as an infinite iterator which always returns the provided value.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iter0: Object\n        Input iterator.\n\n    iterator: ...Object\n        Iterators to multiply.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1.0, 2.0 ] );\n    > var it2 = array2iterator( [ 3.0, 4.0 ] );\n    > var it = iterMultiply( it1, it2 );\n    > var v = it.next().value\n    3.0\n    > v = it.next().value\n    8.0\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterAdd, iterDivide, iterSubtract\n","iterNegaFibonacciSeq":"\niterNegaFibonacciSeq( [options] )\n    Returns an iterator which generates a negaFibonacci sequence.\n\n    The returned iterator can only generate the first 79 negaFibonacci numbers,\n    as larger negaFibonacci numbers cannot be safely represented in double-\n    precision floating-point format.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 79.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterNegaFibonacciSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n\n    See Also\n    --------\n    base.negafibonacci, iterFibonacciSeq, iterNonFibonacciSeq\n","iterNegaLucasSeq":"\niterNegaLucasSeq( [options] )\n    Returns an iterator which generates a negaLucas sequence.\n\n    The returned iterator can only generate the first 77 negaLucas numbers, as\n    larger negaLucas numbers cannot be safely represented in double-precision\n    floating-point format.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 77.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterNegaLucasSeq();\n    > var v = it.next().value\n    2\n    > v = it.next().value\n    -1\n\n    See Also\n    --------\n    base.negalucas, iterLucasSeq, iterNegaFibonacciSeq\n","iterNegativeEvenIntegersSeq":"\niterNegativeEvenIntegersSeq( [options] )\n    Returns an iterator which generates a sequence of negative even integers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 4503599627370496.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterNegativeEvenIntegersSeq();\n    > var v = it.next().value\n    -2\n    > v = it.next().value\n    -4\n\n    See Also\n    --------\n    iterEvenIntegersSeq, iterIntegersSeq, iterNegativeIntegersSeq, iterNegativeOddIntegersSeq, iterPositiveEvenIntegersSeq, iterNonPositiveEvenIntegersSeq\n","iterNegativeIntegersSeq":"\niterNegativeIntegersSeq( [options] )\n    Returns an iterator which generates a negative integer sequence.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 9007199254740991.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterNegativeIntegersSeq();\n    > var v = it.next().value\n    -1\n    > v = it.next().value\n    -2\n\n    See Also\n    --------\n    iterIntegersSeq, iterNonNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterPositiveIntegersSeq\n","iterNegativeOddIntegersSeq":"\niterNegativeOddIntegersSeq( [options] )\n    Returns an iterator which generates a sequence of negative odd integers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 4503599627370496.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterNegativeOddIntegersSeq();\n    > var v = it.next().value\n    -1\n    > v = it.next().value\n    -3\n\n    See Also\n    --------\n    iterOddIntegersSeq, iterIntegersSeq, iterNegativeIntegersSeq, iterNegativeEvenIntegersSeq, iterPositiveOddIntegersSeq\n","iterNone":"\niterNone( iterator )\n    Tests whether all iterated values are falsy.\n\n    The function immediately returns upon encountering a truthy value.\n\n    If provided an iterator which does not return any iterated values, the\n    function returns `true`.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `false` if a value is truthy; otherwise, the\n        function returns `true`.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n    > var bool = iterNone( arr )\n    false\n\n    See Also\n    --------\n    iterAny, iterEvery, iterForEach, iterNoneBy, iterSome\n","iterNoneBy":"\niterNoneBy( iterator, predicate[, thisArg ] )\n    Tests whether every iterated value fails a test implemented by a predicate\n    function.\n\n    The predicate function is provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index.\n\n    The function immediately returns upon encountering a truthy return value.\n\n    If provided an iterator which does not return any iterated values, the\n    function returns `true`.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if a predicate function returns a falsy\n        value for all iterated values. Otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\n    > function fcn( v ) { return ( v <= 0 ); };\n    > var bool = iterNoneBy( arr, fcn )\n    true\n\n    See Also\n    --------\n    iterAnyBy, iterEveryBy, iterForEach, iterNone, iterSomeBy\n","iterNonFibonacciSeq":"\niterNonFibonacciSeq( [options] )\n    Returns an iterator which generates a non-Fibonacci integer sequence.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterNonFibonacciSeq();\n    > var v = it.next().value\n    4\n    > v = it.next().value\n    6\n\n    See Also\n    --------\n    base.nonfibonacci, iterFibonacciSeq\n","iterNonNegativeEvenIntegersSeq":"\niterNonNegativeEvenIntegersSeq( [options] )\n    Returns an iterator which generates a sequence of nonnegative even integers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 4503599627370497.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterNonNegativeEvenIntegersSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    iterEvenIntegersSeq, iterIntegersSeq, iterNonNegativeIntegersSeq, iterNonPositiveEvenIntegersSeq, iterPositiveEvenIntegersSeq\n","iterNonNegativeIntegersSeq":"\niterNonNegativeIntegersSeq( [options] )\n    Returns an iterator which generates a nonnegative integer sequence.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 9007199254740992.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterNonNegativeIntegersSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n\n    See Also\n    --------\n    iterIntegersSeq, iterNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterPositiveIntegersSeq\n","iterNonPositiveEvenIntegersSeq":"\niterNonPositiveEvenIntegersSeq( [options] )\n    Returns an iterator which generates a sequence of nonpositive even integers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 4503599627370497.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterNonPositiveEvenIntegersSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    -2\n\n    See Also\n    --------\n    iterEvenIntegersSeq, iterIntegersSeq, iterNonNegativeEvenIntegersSeq, iterNonPositiveIntegersSeq, iterNegativeEvenIntegersSeq\n","iterNonPositiveIntegersSeq":"\niterNonPositiveIntegersSeq( [options] )\n    Returns an iterator which generates a nonpositive integer sequence.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 9007199254740992.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterNonPositiveIntegersSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    -1\n\n    See Also\n    --------\n    iterIntegersSeq, iterNegativeIntegersSeq, iterNonNegativeIntegersSeq, iterPositiveIntegersSeq\n","iterNonSquaresSeq":"\niterNonSquaresSeq( [options] )\n    Returns an iterator which generates a sequence of nonsquares.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 9007199349647256.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterNonSquaresSeq();\n    > var v = it.next().value\n    2\n    > v = it.next().value\n    3\n    > v = it.next().value\n    5\n\n    See Also\n    --------\n    iterCubesSeq, iterSquaresSeq\n","iterNth":"\niterNth( iterator, n )\n    Returns the nth iterated value.\n\n    If `n` exceeds the total number of iterations, the function returns\n    `undefined`.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    n: integer\n        Iteration number.\n\n    Returns\n    -------\n    v: any\n        The nth iterated value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 0, 0, 1, 0, 0 ] );\n    > var v = iterNth( arr, 3 )\n    1\n\n    See Also\n    --------\n    iterFirst, iterLast\n","iterOddIntegersSeq":"\niterOddIntegersSeq( [options] )\n    Returns an iterator which generates an interleaved sequence of odd integers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 9007199254740992.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterOddIntegersSeq();\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    -1\n    > v = it.next().value\n    3\n\n    See Also\n    --------\n    iterEvenIntegersSeq, iterIntegersSeq\n","iterPeriodicSinc":"\niterPeriodicSinc( n[, options] )\n    Returns an iterator which generates a periodic sinc waveform.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    n: integer\n        Order.\n\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Period (i.e., the number of iterations before a waveform repeats).\n        Default: 100.\n\n    options.amplitude: number (optional)\n        Peak amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterPeriodicSinc( 7 );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterSineWave\n","iterPipeline":"\niterPipeline( iterFcn[, ...iterFcn] )\n    Returns an iterator pipeline.\n\n    Parameters\n    ----------\n    iterFcn: Function|Array\n        Iterator function or an array of iterator functions.\n\n    iterFcn: ...Function (optional)\n        Iterator functions.\n\n    Returns\n    -------\n    fcn( src ): Function\n        Iterator pipeline which accepts a single argument, a source iterator.\n\n    Examples\n    --------\n    > var it1 = iterThunk( iterHead, 100 );\n    > function f( r ) { return ( r > 0.95 ); };\n    > var it2 = iterThunk( iterSomeBy, 5, f );\n    > var p = iterPipeline( it1, it2 );\n    > var bool = p( random.iterators.randu() )\n    <boolean>\n\n    See Also\n    --------\n    iterFlow, iterThunk\n","iterPop":"\niterPop( iterator[, clbk[, thisArg]] )\n    Returns an iterator which skips the last value of a provided iterator.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    clbk: Function (optional)\n        Callback to invoke with the skipped value.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2 ] );\n    > var it2 = iterPop( it1 );\n    > var v = it2.next().value\n    1\n    > var bool = it2.next().done\n    true\n\n    See Also\n    --------\n    iterPush, iterShift, iterSlice\n","iterPositiveEvenIntegersSeq":"\niterPositiveEvenIntegersSeq( [options] )\n    Returns an iterator which generates a sequence of positive even integers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 4503599627370496.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterPositiveEvenIntegersSeq();\n    > var v = it.next().value\n    2\n    > v = it.next().value\n    4\n\n    See Also\n    --------\n    iterEvenIntegersSeq, iterIntegersSeq, iterNegativeEvenIntegersSeq, iterNonNegativeEvenIntegersSeq, iterPositiveIntegersSeq, iterPositiveOddIntegersSeq\n","iterPositiveIntegersSeq":"\niterPositiveIntegersSeq( [options] )\n    Returns an iterator which generates a positive integer sequence.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 9007199254740991.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterPositiveIntegersSeq();\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    iterNonNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterNegativeIntegersSeq\n","iterPositiveOddIntegersSeq":"\niterPositiveOddIntegersSeq( [options] )\n    Returns an iterator which generates a sequence of positive odd integers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 4503599627370496.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterPositiveOddIntegersSeq();\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    3\n\n    See Also\n    --------\n    iterOddIntegersSeq, iterIntegersSeq, iterNegativeOddIntegersSeq, iterPositiveEvenIntegersSeq, iterPositiveIntegersSeq\n","iterPow":"\niterPow( base, exponent )\n    Returns an iterator which iteratively evaluates the exponential function.\n\n    The length of the returned iterator is equal to the length of the shortest\n    provided iterator. In other words, the returned iterator ends once *one* of\n    the provided iterators ends.\n\n    If provided a numeric value as an iterator argument, the value is broadcast\n    as an infinite iterator which always returns the provided value.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    base: Object|number\n        Input iterator.\n\n    exponent: Object|number\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = random.iterators.uniform( 0.0, 2.0 );\n    > var y = random.iterators.uniform( -2.0, 2.0 );\n    > var it = iterPow( x, y );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.pow, iterExp, iterLog\n","iterPrimesSeq":"\niterPrimesSeq( [options] )\n    Returns an iterator which generates a sequence of prime numbers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 245181918813464.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterPrimesSeq();\n    > var v = it.next().value\n    2\n    > v = it.next().value\n    3\n    > v = it.next().value\n    5\n\n    See Also\n    --------\n    iterCompositesSeq, iterIntegersSeq, iterPositiveIntegersSeq\n","iterprod":"\niterprod( iterator )\n    Computes the product of all iterated values.\n\n    For iterators which can generate many values or which may output large\n    numbers, care should be taken to prevent overflow.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Product.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var s = iterprod( arr )\n    24.0\n\n    See Also\n    --------\n    itermprod, itersum\n","iterPulse":"\niterPulse( [options] )\n    Returns an iterator which generates a pulse waveform.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Pulse period (i.e., the number of iterations until a waveform repeats).\n        Default: 10.\n\n    options.duration: integer (optional)\n        Pulse duration (i.e., the number of consecutive iterations of maximum\n        amplitude during one period). Default: floor(options.period/2).\n\n    options.min: number (optional)\n        Minimum amplitude. Default: 0.0.\n\n    options.max: number (optional)\n        Maximum amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterPulse();\n    > var v = it.next().value\n    1.0\n    > v = it.next().value\n    1.0\n\n    See Also\n    --------\n    iterSawtoothWave, iterSineWave, iterSquareWave, iterTriangleWave\n","iterPush":"\niterPush( iterator, ...items )\n    Returns an iterator which appends additional values to the end of a provided\n    iterator.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    items: ...any\n        Items to append.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2 ] );\n    > var it2 = iterPush( it1, 3, 4 );\n    > var v = it2.next().value\n    1\n    > v = it2.next().value\n    2\n    > v = it2.next().value\n    3\n    > v = it2.next().value\n    4\n    > var bool = it2.next().done\n    true\n\n    See Also\n    --------\n    iterConcat, iterUnshift\n","iterRad2deg":"\niterRad2deg( iterator )\n    Returns an iterator which iteratively converts an angle from radians to\n    degrees.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 6.28 );\n    > var it = iterRad2deg( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.rad2deg, iterDeg2rad\n","iterRamp":"\niterRamp( iterator )\n    Returns an iterator which iteratively evaluates the ramp function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterRamp( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.ramp\n","iterrange":"\niterrange( iterator )\n    Computes the range of all iterated values.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Range.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var v = iterrange( arr )\n    7.0\n\n    See Also\n    --------\n    itermax, itermean, itermin, itermrange\n","iterReject":"\niterReject( iterator, predicate[, thisArg] )\n    Returns an iterator which rejects a provided iterator's values according to\n    a predicate function.\n\n    When invoked, the predicate function is provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index (zero-based).\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    predicate: Function\n        Predicate function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > function f( v ) { return ( v > 2 ); };\n    > var it1 = array2iterator( [ 1, 3, 2, 4 ] );\n    > var it2 = iterReject( it1, f );\n    > var v = it2.next().value\n    1\n    > v = it2.next().value\n    2\n\n    See Also\n    --------\n    iterFilter, iterMap\n","iterReplicate":"\niterReplicate( iterator, n )\n    Returns an iterator which replicates each iterated value `n` times.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    n: integer\n        Number of times each iterated value is replicated.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2, 3, 4 ] );\n    > var it2 = iterReplicate( it1, 2 );\n    > var v = it2.next().value\n    1\n    > v = it2.next().value\n    1\n    > v = it2.next().value\n    2\n    > v = it2.next().value\n    2\n\n    See Also\n    --------\n    iterReplicateBy\n","iterReplicateBy":"\niterReplicateBy( iterator, fcn[, thisArg] )\n    Returns an iterator which replicates each iterated value according to a\n    provided function.\n\n    The callback function is provided three arguments:\n\n    - value: iterated value.\n    - index: source iteration index (zero-based).\n    - n: iteration index (zero-based).\n\n    The callback function is invoked *once* per iterated value of the provided\n    iterator.\n\n    The callback function *must* return an integer value. If the return value is\n    less than or equal to zero, the returned iterator skips an iterated value\n    and invokes the callback for the next iterated value of the provided\n    iterator.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    fcn: Function\n        Function which returns the number of times an iterated value should be\n        replicated.\n\n    thisArg: any (optional)\n        Callback function execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2, 3, 4 ] );\n    > function f( v, i ) { return i + 1; };\n    > var it2 = iterReplicateBy( it1, f );\n    > var v = it2.next().value\n    1\n    > v = it2.next().value\n    2\n    > v = it2.next().value\n    2\n    > v = it2.next().value\n    3\n    > v = it2.next().value\n    3\n    > v = it2.next().value\n    3\n    > v = it2.next().value\n    4\n\n    See Also\n    --------\n    iterReplicate\n","iterRound":"\niterRound( iterator )\n    Returns an iterator which rounds each iterated value to the nearest integer.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterRound( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.round, iterCeil, iterFloor, iterTrunc\n","iterRound2":"\niterRound2( iterator )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    two on a linear scale.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterRound2( random.iterators.uniform( -100.0, 100.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.round2, iterCeil2, iterFloor2, iterRound, iterRound10, iterTrunc2\n","iterRound10":"\niterRound10( iterator )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    10 on a linear scale.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterRound10( random.iterators.uniform( -100.0, 100.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.round10, iterCeil10, iterFloor10, iterRound, iterRound2, iterTrunc10\n","iterRsqrt":"\niterRsqrt( iterator )\n    Returns an iterator which iteratively computes the reciprocal (inverse)\n    square root.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterRsqrt( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.rsqrt, iterSqrt\n","iterSawtoothWave":"\niterSawtoothWave( [options] )\n    Returns an iterator which generates a sawtooth wave.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Period (i.e., the number of iterations before a waveform repeats).\n        Default: 10.\n\n    options.amplitude: number (optional)\n        Peak amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterSawtoothWave();\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterPulse, iterSineWave, iterSquareWave, iterTriangleWave\n","iterShift":"\niterShift( iterator[, clbk[, thisArg]] )\n    Returns an iterator which skips the first value of a provided iterator.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    clbk: Function (optional)\n        Callback to invoke with the skipped value.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2 ] );\n    > var it2 = iterShift( it1 );\n    > var v = it2.next().value\n    2\n    > var bool = it2.next().done\n    true\n\n    See Also\n    --------\n    iterPop, iterSlice, iterUnshift\n","iterSignum":"\niterSignum( iterator )\n    Returns an iterator which iteratively evaluates the signum function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterSignum( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.signum\n","iterSin":"\niterSin( iterator )\n    Returns an iterator which iteratively computes the sine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterSin( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.sin, iterCos, iterSinpi, iterTan\n","iterSinc":"\niterSinc( iterator )\n    Returns an iterator which iteratively computes the normalized cardinal sine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -5.0, 5.0 );\n    > var it = iterSinc( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.sinc, iterSin\n","iterSineWave":"\niterSineWave( [options] )\n    Returns an iterator which generates a sine wave.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Period (i.e., the number of iterations before a sine wave repeats).\n        Default: 10.\n\n    options.amplitude: number (optional)\n        Peak amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterSineWave();\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterCosineWave, iterPulse, iterSawtoothWave, iterSquareWave, iterTriangleWave\n","iterSinh":"\niterSinh( iterator )\n    Returns an iterator which iteratively evaluates the hyperbolic sine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -5.0, 5.0 );\n    > var it = iterSinh( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.sinh, iterCosh, iterTanh\n","iterSinpi":"\niterSinpi( iterator )\n    Returns an iterator which computes the sine of each iterated value times π.\n\n    Computes sin(πx) more accurately than sin(pi*x), especially for large x.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterSinpi( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.sinpi, iterSin\n","iterSlice":"\niterSlice( iterator[, begin[, end]] )\n    Returns an iterator which returns a subsequence of iterated values from a\n    provided iterator.\n\n    If `end` exceeds the length of the provided iterator, the returned iterator\n    returns the subsequence of iterated values starting from `begin` until the\n    last iterated value of the provided iterator.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    begin: integer (optional)\n        Start iteration index (zero-based and inclusive). Default: 0.\n\n    end: integer (optional)\n        End iteration index (zero-based and non-inclusive).\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterSlice( random.iterators.randu(), 5, 10 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterFirst, iterHead\n","iterSome":"\niterSome( iterator, n )\n    Tests whether at least `n` iterated values are truthy.\n\n    The function immediately returns upon finding `n` truthy values.\n\n    If provided an iterator which does not return any iterated values, the\n    function returns `false`.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    n: number\n        Minimum number of truthy elements.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if an iterator returns at least `n` truthy\n        elements; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\n    > var bool = iterSome( arr, 3 )\n    true\n\n    See Also\n    --------\n    iterAny, iterEvery, iterForEach, iterNone, iterSomeBy\n","iterSomeBy":"\niterSomeBy( iterator, n, predicate[, thisArg ] )\n    Tests whether at least `n` iterated values pass a test implemented by a\n    predicate function.\n\n    The predicate function is provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index.\n\n    The function immediately returns upon encountering `n` truthy return values.\n\n    If provided an iterator which does not return any iterated values, the\n    function returns `false`.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    n: integer\n        Minimum number of successful values.\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if a predicate function returns a truthy\n        value for at least `n` iterated values. Otherwise, the function returns\n        `false`.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1, 1, 0, 0, 1 ] );\n    > function fcn( v ) { return ( v > 0 ); };\n    > var bool = iterSomeBy( arr, 3, fcn )\n    true\n\n    See Also\n    --------\n    iterAnyBy, iterEveryBy, iterForEach, iterNoneBy, iterSome\n","iterSpence":"\niterSpence( iterator )\n    Returns an iterator which iteratively evaluates Spence's function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 100.0 );\n    > var it = iterSpence( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.spence\n","iterSqrt":"\niterSqrt( iterator )\n    Returns an iterator which iteratively computes the principal square root.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterSqrt( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.sqrt, iterCbrt, iterRsqrt\n","iterSqrt1pm1":"\niterSqrt1pm1( iterator )\n    Returns an iterator which iteratively computes `sqrt(1+x) - 1` more \n    accurately for small `x`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 100.0 );\n    > var it = iterSqrt1pm1( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.sqrt1pm1, iterSqrt\n","iterSquaredTriangularSeq":"\niterSquaredTriangularSeq( [options] )\n    Returns an iterator which generates a sequence of squared triangular\n    numbers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 11585.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterSquaredTriangularSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().value\n    9\n\n    See Also\n    --------\n    iterTriangularSeq\n","iterSquaresSeq":"\niterSquaresSeq( [options] )\n    Returns an iterator which generates a sequence of squares.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 94906265.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterSquaresSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().value\n    4\n\n    See Also\n    --------\n    iterCubesSeq, iterNonSquaresSeq\n","iterSquareWave":"\niterSquareWave( [options] )\n    Returns an iterator which generates a square wave.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Period (i.e., the number of iterations before a square wave repeats).\n        This must be an even integer in order to ensure a 50% duty cycle.\n        Default: 10.\n\n    options.min: number (optional)\n        Minimum amplitude. Default: -1.0.\n\n    options.max: number (optional)\n        Maximum amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterSquareWave();\n    > var v = it.next().value\n    1.0\n    > v = it.next().value\n    1.0\n\n    See Also\n    --------\n    iterPulse, iterSawtoothWave, iterSineWave, iterTriangleWave\n","iterstdev":"\niterstdev( iterator[, mean] )\n    Computes a correct sample standard deviation over all iterated values.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    mean: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    out: number|null\n        Corrected sample standard deviation.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0 ] );\n    > var m = iterstdev( arr )\n    ~4.95\n\n    See Also\n    --------\n    itermean, itervariance\n","iterStep":"\niterStep( start, increment[, N] )\n    Returns an iterator which returns a sequence of numbers according to a\n    specified increment.\n\n    Beware that values which follow the starting value are subject to floating-\n    point rounding errors.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    start: number\n        Starting value (inclusive).\n\n    increment: number\n        Increment.\n\n    N: number (optional)\n        Number of values. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterStep( 0, 2, 10 );\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    iterator2array, iterDatespace, iterIncrspace, iterLinspace, iterLogspace, iterUnitspace\n","iterStrided":"\niterStrided( iterator, stride[, offset[, eager]] )\n    Returns an iterator which steps by a specified amount.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    stride: integer\n        Stride (i.e., step amount).\n\n    offset: integer (optional)\n        Index of the first iterated value. Default: 0.\n\n    eager: boolean (optional)\n        Boolean indicating whether to eagerly advance the input iterator when\n        provided a non-zero offset. Default: false.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\n    > var it = iterStrided( arr, 2, 1 );\n    > var r = it.next().value\n    1\n    > r = it.next().value\n    3\n\n    See Also\n    --------\n    iterAdvance, iterNth, iterStridedBy\n","iterStridedBy":"\niterStridedBy( iterator, fcn[, offset[, eager]][, thisArg] )\n    Returns an iterator which steps according to a provided callback function.\n\n    When invoked, the input function is provided four arguments:\n\n    - value: iterated value.\n    - i: input iteration index (zero-based).\n    - n: output (strided) iteration index (zero-based).\n    - curr: current stride.\n\n    The return value of the input function specifies the next stride.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    fcn: Function\n        Stride function (i.e., a function which returns the step amount).\n\n    offset: integer (optional)\n        Index of the first iterated value. Default: 0.\n\n    eager: boolean (optional)\n        Boolean indicating whether to eagerly advance the input iterator when\n        provided a non-zero offset. Default: false.\n\n    thisArg: any (optional)\n        Stride function execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\n    > function stride( v, i ) { return (i % 10)+1; };\n    > var it = iterStridedBy( arr, stride );\n    > var r = it.next().value\n    0\n    > r = it.next().value\n    1\n    > r = it.next().value\n    3\n\n    See Also\n    --------\n    iterAdvance, iterNth, iterStrided\n","iterSubtract":"\niterSubtract( iter0, ...iterator )\n    Returns an iterator which performs element-wise subtraction of two or more\n    iterators.\n\n    The length of the returned iterator is equal to the length of the shortest\n    provided iterator. In other words, the returned iterator ends once *one* of\n    the provided iterators ends.\n\n    If provided a numeric value as an iterator argument, the value is broadcast\n    as an infinite iterator which always returns the provided value.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iter0: Object\n        Input iterator.\n\n    iterator: ...Object\n        Iterators to subtract.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1.0, 5.0 ] );\n    > var it2 = array2iterator( [ 3.0, 4.0 ] );\n    > var it = iterSubtract( it1, it2 );\n    > var v = it.next().value\n    -2.0\n    > v = it.next().value\n    1.0\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterAdd, iterDivide, iterMultiply\n","itersum":"\nitersum( iterator )\n    Computes the sum of all iterated values.\n\n    For iterators which can generate many values or which may output large\n    numbers, care should be taken to prevent overflow.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Sum.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var s = itersum( arr )\n    10.0\n\n    See Also\n    --------\n    itermean, itermsum, iterprod\n","itersumabs":"\nitersumabs( iterator )\n    Computes the sum of absolute values for all iterated values.\n\n    For iterators which can generate many values or which may output large\n    numbers, care should be taken to prevent overflow.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Sum of absolute values.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\n    > var s = itersumabs( arr )\n    10.0\n\n    See Also\n    --------\n    itermeanabs, itermsumabs, itersum\n","itersumabs2":"\nitersumabs2( iterator )\n    Computes the sum of squared absolute values for all iterated values.\n\n    For iterators which can generate many values or which may output large\n    numbers, care should be taken to prevent overflow.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Sum of squared absolute values.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\n    > var s = itersumabs2( arr )\n    30.0\n\n    See Also\n    --------\n    itermeanabs2, itermsumabs2, itersumabs\n","iterTan":"\niterTan( iterator )\n    Returns an iterator which iteratively evaluates the tangent.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -1.57, 1.57 );\n    > var it = iterTan( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.tan, iterCos, iterSin\n","iterTanh":"\niterTanh( iterator )\n    Returns an iterator which iteratively evaluates the hyperbolic tangent.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -4.0, 4.0 );\n    > var it = iterTanh( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.tanh, iterCosh, iterSinh, iterTan\n","iterThunk":"\niterThunk( iterFcn[, ...args] )\n    Returns an iterator \"thunk\".\n\n    A provided iterator function should have the following function signature:\n\n      iterFcn( iterator, ...args )\n\n    The returned function expects a single argument, an iterator.\n\n    This function is useful within the context of iterator pipelines as a means\n    to defer execution until a pipeline is ready for data flow.\n\n    Parameters\n    ----------\n    iterFcn: Function\n        Iterator function.\n\n    args: ...any (optional)\n        Function arguments.\n\n    Returns\n    -------\n    fcn( iter ): Function\n        Function which accepts a single argument, an iterator, and invokes a\n        previously provided iterator function with the provided iterator and any\n        previously provided arguments.\n\n    Examples\n    --------\n    > var fcn = iterThunk( iterSome, 3 );\n    > var arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\n    > var bool = fcn( arr )\n    true\n\n    See Also\n    --------\n    iterPipeline\n","iterTriangleWave":"\niterTriangleWave( [options] )\n    Returns an iterator which generates a triangle wave.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Period (i.e., the number of iterations before a waveform repeats).\n        Default: 10.\n\n    options.amplitude: number (optional)\n        Peak amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterTriangleWave();\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterPulse, iterSawtoothWave, iterSineWave, iterSquareWave\n","iterTriangularSeq":"\niterTriangularSeq( [options] )\n    Returns an iterator which generates a sequence of triangular numbers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 134217727.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterTriangularSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().value\n    3\n\n    See Also\n    --------\n    iterSquaredTriangularSeq\n","iterTribonnaciSeq":"\niterTribonnaciSeq( [options] )\n    Returns an iterator which generates a Tribonacci sequence.\n    \n    The returned iterator can only generate the first 64 Tribonacci numbers, as\n    larger Tribonacci numbers cannot be safely represented in double-precision\n    floating-point format.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 64.\n\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant\n        object has the next\n        iterated value (if one exists) and a\n        boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n\n    Examples\n    --------\n    > var it = iterTribonnaciSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    0\n\n    See Also\n    --------\n    base.tribonacci, base.fibonacci, iterLucasSeq\n","iterTrigamma":"\niterTrigamma( iterator )\n    Returns an iterator which iteratively evaluates the trigamma function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.01, 50.0 );\n    > var it = iterTrigamma( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.trigamma, iterDigamma, iterGamma\n","iterTrunc":"\niterTrunc( iterator )\n    Returns an iterator which rounds each iterated value toward zero.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterTrunc( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.trunc, iterCeil, iterFloor, iterRound\n","iterTrunc2":"\niterTrunc2( iterator )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    two toward zero.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterTrunc2( random.iterators.uniform( -100.0, 100.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.trunc2, iterCeil2, iterFloor2, iterRound2, iterTrunc\n","iterTrunc10":"\niterTrunc10( iterator )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    10 toward zero.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterTrunc10( random.iterators.uniform( -100.0, 100.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.trunc10, iterCeil10, iterFloor10, iterRound10, iterTrunc\n","iterUnion":"\niterUnion( iter0, ...iterator )\n    Returns an iterator which returns the union of two or more iterators.\n\n    Value \"uniqueness\" is determined according to strict equality.\n\n    A returned iterator internally buffers unique values and, thus, has O(N)\n    memory requirements, where `N` is the total number of source iterator\n    values.\n\n    If an environment supports Symbol.iterator and all provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iter0: Object\n        Input iterator.\n\n    iterator: ...Object\n        Input iterators.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n    > var it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\n    > var it = iterUnion( it1, it2 );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    2\n    > v = it.next().value\n    4\n    > v = it.next().value\n    5\n    > v = it.next().value\n    3\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterIntersection, iterUnique\n","iterUnique":"\niterUnique( iterator )\n    Returns an iterator which returns unique values.\n\n    Value \"uniqueness\" is determined according to strict equality.\n\n    A returned iterator internally buffers unique values and, thus, has O(N)\n    memory requirements.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n    > var it2 = iterUnique( it1 );\n    > var v = it2.next().value\n    1\n    > v = it2.next().value\n    2\n    > v = it2.next().value\n    4\n    > var bool = it2.next().done\n    true\n\n    See Also\n    --------\n    iterUniqueBy, iterUniqueByHash\n","iterUniqueBy":"\niterUniqueBy( iterator, predicate[, thisArg] )\n    Returns an iterator which returns unique values according to a predicate\n    function.\n\n    A returned iterator internally buffers unique values and, thus, has O(N)\n    memory requirements.\n\n    A predicate function is invoked for each iterated value against each value\n    in an internal buffer consisting of previously identified unique values.\n    Thus, as the number of unique values grows, so, too, does the number of\n    predicate function invocations per iterated value.\n\n    An iterated value is considered \"unique\" if the predicate function returns\n    truthy values for all comparisons of the iterated value with each value in\n    the internal buffer.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    predicate: Function\n        A binary function with parameters `a` and `b` corresponding to iterated\n        values. If the values are the same, the function should return `false`\n        (i.e., non-unique); otherwise, if the values are distinct, the function\n        should return `true` (i.e., unique).\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n    > function f( a, b ) { return ( a !== b ); };\n    > var it2 = iterUniqueBy( it1, f );\n    > var v = it2.next().value\n    1\n    > v = it2.next().value\n    2\n    > v = it2.next().value\n    4\n    > var bool = it2.next().done\n    true\n\n    See Also\n    --------\n    iterUnique, iterUniqueByHash\n","iterUniqueByHash":"\niterUniqueByHash( iterator, hashFcn[, thisArg] )\n    Returns an iterator which returns unique values according to a hash\n    function.\n\n    A returned iterator internally buffers unique hashes and, thus, has O(N)\n    memory requirements.\n\n    An iterated value is considered \"unique\" if the hash function returns a\n    unique hash value for that iterated value. Beware that this *may* result in\n    unexpected behavior. Namely, only the first iterated value mapping to a\n    particular hash function result is returned, even if subsequent values,\n    while mapping to the same hash, are different. Accordingly, iteration order\n    *does* matter.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    hashFcn: Function\n        Hash function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n    > function f( v ) { return v.toString(); };\n    > var it2 = iterUniqueByHash( it1, f );\n    > var v = it2.next().value\n    1\n    > v = it2.next().value\n    2\n    > v = it2.next().value\n    4\n    > var bool = it2.next().done\n    true\n\n    See Also\n    --------\n    iterUnique, iterUniqueBy\n","iterUnitspace":"\niterUnitspace( start[, stop] )\n    Returns an iterator which returns numbers incremented by one.\n\n    The iterator stops once the `stop` value is exceeded.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    start: number\n        Starting value (inclusive).\n\n    stop: number (optional)\n        Stopping value. Default: +infinity.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterUnitspace( 0, 99 );\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n\n    See Also\n    --------\n    iterator2array, iterIncrspace, iterLinspace, iterStep\n","iterUnshift":"\niterUnshift( iterator, ...items )\n    Returns an iterator which prepends values to the beginning of a provided\n    iterator.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    items: ...any\n        Items to prepend.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2 ] );\n    > var it2 = iterUnshift( it1, 3, 4 );\n    > var v = it2.next().value\n    3\n    > v = it2.next().value\n    4\n    > v = it2.next().value\n    1\n    > v = it2.next().value\n    2\n    > var bool = it2.next().done\n    true\n\n    See Also\n    --------\n    iterConcat, iterPush, iterShift\n","iterUntilEach":"\niterUntilEach( iterator, predicate, fcn[, thisArg] )\n    Returns an iterator which invokes a function for each iterated value before\n    returning the iterated value until either a predicate function returns true\n    or the iterator has iterated over all values.\n\n    When invoked, both input functions are provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index (zero-based).\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    predicate: Function\n        Function which indicates whether to continue iterating.\n\n    fcn: Function\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > function predicate( v ) { return v !== v };\n    > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n    > var it = iterUntilEach( random.iterators.randu(), predicate, f );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterWhileEach\n","itervariance":"\nitervariance( iterator[, mean] )\n    Computes an unbiased sample variance over all iterated values.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    mean: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    out: number|null\n        Unbiased sample variance.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0 ] );\n    > var s2 = itervariance( arr )\n    24.5\n\n    See Also\n    --------\n    itermean, iterstdev\n","iterVercos":"\niterVercos( iterator )\n    Returns an iterator which iteratively computes the versed cosine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 6.28 );\n    > var it = iterVercos( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.vercos, iterCos, iterSin, iterVersin\n","iterVersin":"\niterVersin( iterator )\n    Returns an iterator which iteratively computes the versed sine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 6.28 );\n    > var it = iterVersin( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.versin, iterCos, iterSin, iterVercos\n","iterWhileEach":"\niterWhileEach( iterator, predicate, fcn[, thisArg] )\n    Returns an iterator which invokes a function for each iterated value before\n    returning the iterated value until either a predicate function returns false\n    or the iterator has iterated over all values.\n\n    When invoked, both input functions are provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index (zero-based).\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    predicate: Function\n        Function which indicates whether to continue iterating.\n\n    fcn: Function\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === v };\n    > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n    > var it = iterWhileEach( random.iterators.randu(), predicate, f );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterUntilEach\n","iterZeta":"\niterZeta( iterator )\n    Returns an iterator which iteratively evaluates the Riemann zeta function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 1.1, 50.0 );\n    > var it = iterZeta( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.zeta\n","joinStream":"\njoinStream( [options] )\n    Returns a transform stream which joins streamed data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. Default: '\\n'.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream.\n\n    Examples\n    --------\n    > var s = joinStream();\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();\n\n\njoinStream.factory( [options] )\n    Returns a function for creating transform streams for joined streamed data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. Default: '\\n'.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    createStream: Function\n        Function for creating transform streams.\n\n    Examples\n    --------\n    > var opts = { 'highWaterMark': 64 };\n    > var createStream = joinStream.factory( opts );\n    > var s = createStream();\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();\n\n\njoinStream.objectMode( [options] )\n    Returns an \"objectMode\" transform stream for joining streamed data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. Default: '\\n'.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > var s = joinStream.objectMode();\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();\n\n    See Also\n    --------\n    splitStream\n","joinStream.factory":"\njoinStream.factory( [options] )\n    Returns a function for creating transform streams for joined streamed data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. Default: '\\n'.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    createStream: Function\n        Function for creating transform streams.\n\n    Examples\n    --------\n    > var opts = { 'highWaterMark': 64 };\n    > var createStream = joinStream.factory( opts );\n    > var s = createStream();\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();","joinStream.objectMode":"\njoinStream.objectMode( [options] )\n    Returns an \"objectMode\" transform stream for joining streamed data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. Default: '\\n'.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > var s = joinStream.objectMode();\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();\n\n    See Also\n    --------\n    splitStream","kde2d":"\nkde2d( x, y[, options] )\n    Two-dimensional kernel density estimation.\n\n    Parameters\n    ----------\n    x: Array<number>\n        Array of x values.\n\n    y: Array<number>\n        Array of y values.\n\n    options: Object (optional)\n        Function options.\n\n    options.h: number (optional)\n        Array of length two containing the bandwidth values for x and y.\n\n    options.n: number (optional)\n        Number of partitions on the x- and y-axes. Default: `25`.\n\n    options.xMin: number (optional)\n        Lower limit of x.\n\n    options.xMax: number (optional)\n        Upper limit of x.\n\n    options.yMin: number (optional)\n        Lower limit of y.\n\n    options.yMax: number (optional)\n        Upper limit of y.\n\n    options.kernel: string|Function\n        A string or function to specifying the used kernel function. Default:\n        `'gaussian'`.\n\n    Returns\n    -------\n    out: Object\n        Object containing the density estimates (`z`) along grid points (`x` and\n        `y` values).\n\n    Examples\n    --------\n    > var x = [ 1, 3, 5, 6, 21, 23, 16, 17, 20, 10 ];\n    > var y = [ 0.40, 0.20, 0.20, 0.15, 0.05, 0.55, 0.6, 0.33, 0.8, 0.41 ];\n    > var out = kde2d( x, y )\n    { 'x': [1, ... ], 'y': [0.05, ...], 'z': ndarray{Float64Array[0.031, ...] }\n\n","kebabcase":"\nkebabcase( str )\n    Converts a string to kebab case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Kebab-cased string.\n\n    Examples\n    --------\n    > var out = kebabcase( 'Hello World!' )\n    'hello-world'\n    > out = kebabcase( 'I am a tiny little teapot' )\n    'i-am-a-tiny-little-teapot'\n\n    See Also\n    --------\n    camelcase, constantcase, pascalcase, snakecase","keyBy":"\nkeyBy( collection, fcn[, thisArg] )\n    Converts a collection to an object whose keys are determined by a provided\n    function and whose values are the collection values.\n\n    When invoked, the input function is provided two arguments:\n\n    - value: collection value.\n    - index: collection index.\n\n    If more than one element in a collection resolves to the same key, the key\n    value is the collection element which last resolved to the key.\n\n    Object values are shallow copies.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Object\n        Output object.\n\n    Examples\n    --------\n    > function toKey( v ) { return v.a; };\n    > var arr = [ { 'a': 1 }, { 'a': 2 } ];\n    > keyBy( arr, toKey )\n    { '1': { 'a': 1 }, '2': { 'a': 2 } }\n\n    See Also\n    --------\n    forEach\n","keyByRight":"\nkeyByRight( collection, fcn[, thisArg] )\n    Converts a collection to an object whose keys are determined by a provided\n    function and whose values are the collection values, iterating from right to\n    left.\n\n    When invoked, the input function is provided two arguments:\n\n    - value: collection value.\n    - index: collection index.\n\n    If more than one element in a collection resolves to the same key, the key\n    value is the collection element which last resolved to the key.\n\n    Object values are shallow copies.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Object\n        Output object.\n\n    Examples\n    --------\n    > function toKey( v ) { return v.a; };\n    > var arr = [ { 'a': 1 }, { 'a': 2 } ];\n    > keyByRight( arr, toKey )\n    { '2': { 'a': 2 }, '1': { 'a': 1 } }\n\n    See Also\n    --------\n    forEachRight, keyBy\n","keysIn":"\nkeysIn( obj )\n    Returns an array of an object's own and inherited enumerable property\n    names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    Parameters\n    ----------\n    obj: any\n        Input value.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's own and inherited enumerable property names.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var keys = keysIn( obj )\n    e.g., [ 'beep', 'foo' ]\n\n    See Also\n    --------\n    objectEntriesIn, objectKeys, objectValuesIn\n","kruskalTest":"\nkruskalTest( ...x[, options] )\n    Computes the Kruskal-Wallis test for equal medians.\n\n    Parameters\n    ----------\n    x: ...Array\n        Measured values.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.groups: Array (optional)\n        Array of group indicators.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.method: string\n        Name of test.\n\n    out.df: Object\n        Degrees of freedom.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    // Data from Hollander & Wolfe (1973), p. 116:\n    > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n    > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n    > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n    > var out = kruskalTest( x, y, z )\n\n    > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n    ...     3.8, 2.7, 4.0, 2.4,\n    ...     2.8, 3.4, 3.7, 2.2, 2.0\n    ... ];\n    > var groups = [\n    ...     'a', 'a', 'a', 'a', 'a',\n    ...     'b', 'b', 'b', 'b',\n    ...     'c', 'c', 'c', 'c', 'c'\n    ... ];\n    > out = kruskalTest( arr, { 'groups': groups } )\n\n","kstest":"\nkstest( x, y[, ...params][, options] )\n    Computes a Kolmogorov-Smirnov goodness-of-fit test.\n\n    For a numeric array or typed array `x`, a Kolmogorov-Smirnov goodness-of-fit\n    is computed for the null hypothesis that the values of `x` come from the\n    distribution specified by `y`. `y` can be either a string with the name of\n    the distribution to test against, or a function.\n\n    In the latter case, `y` is expected to be the cumulative distribution\n    function (CDF) of the distribution to test against, with its first parameter\n    being the value at which to evaluate the CDF and the remaining parameters\n    constituting the parameters of the distribution. The parameters of the\n    distribution are passed as additional arguments after `y` from `kstest` to\n    the chosen CDF. The function returns an object holding the calculated test\n    statistic `statistic` and the `pValue` of the test.\n\n    The returned object comes with a `.print()` method which when invoked will\n    print a formatted output of the hypothesis test results.\n\n    Parameters\n    ----------\n    x: Array<number>\n        Input array holding numeric values.\n\n    y: Function|string\n        Either a CDF function or a string denoting the name of a distribution.\n\n    params: ...number (optional)\n        Distribution parameters passed to reference CDF.\n\n    options: Object (optional)\n        Function options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.sorted: boolean (optional)\n        Boolean indicating if the input array is already in sorted order.\n        Default: `false`.\n\n    options.alternative: string (optional)\n        Either `two-sided`, `less` or `greater`. Indicates whether the\n        alternative hypothesis is that the true distribution of `x` is not equal\n        to the reference distribution specified by `y` (`two-sided`), whether it\n        is `less` than the reference distribution or `greater` than the\n        reference distribution. Default: `'two-sided'`.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Used significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.alternative: string\n        Used test alternative. Either `two-sided`, `less` or `greater`.\n\n    out.method: string\n        Name of test.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    // Verify that data is drawn from a normal distribution:\n    > var rnorm = base.random.normal.factory({ 'seed': 4839 } );\n    > var x = new Array( 100 );\n    > for ( var i = 0; i < 100; i++ ) { x[ i ] = rnorm( 3.0, 1.0 ); }\n\n    // Test against N(0,1)\n    > var out = kstest( x, 'normal', 0.0, 1.0 )\n    { pValue: 0.0, statistic: 0.847, ... }\n\n    // Test against N(3,1)\n    > out = kstest( x, 'normal', 3.0, 1.0 )\n    { pValue: 0.6282, statistic: 0.0733, ... }\n\n    // Verify that data is drawn from a uniform distribution:\n    > runif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } )\n    > x = new Array( 100 );\n    > for ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\n    > out = kstest( x, 'uniform', 0.0, 1.0 )\n    { pValue: ~0.703, statistic: ~0.069, ... }\n\n    // Print output:\n    > out.print()\n    Kolmogorov-Smirnov goodness-of-fit test.\n\n    Null hypothesis: the CDF of `x` is equal equal to the reference CDF.\n\n        pValue: 0.7039\n        statistic: 0.0689\n\n    Test Decision: Fail to reject null in favor of alternative at 5%\n    significance level\n\n    // Set custom significance level:\n    > out = kstest( x, 'uniform', 0.0, 1.0, { 'alpha': 0.1 } )\n    { pValue: ~0.7039, statistic: ~0.069, ... }\n\n    // Carry out one-sided hypothesis tests:\n    > runif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } );\n    > x = new Array( 100 );\n    > for ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\n    > out = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'less' } )\n    { pValue: ~0.358, statistic: ~0.07, ... }\n    > out = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'greater' } )\n    { pValue: ~0.907, statistic: ~0.02, ... }\n\n    // Set `sorted` option to true when data is in increasing order:\n    > x = [ 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 ];\n    > out = kstest( x, 'uniform', 0.0, 1.0, { 'sorted': true } )\n    { pValue: ~1, statistic: 0.1, ... }\n\n","last":"\nlast( str[, n][, options] )\n    Returns the last character(s) of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer (optional)\n        Number of characters to return. Default: 1.\n\n    options: Object (optional)\n        Options.\n\n    options.mode: string (optional)\n        Type of characters to return. The following modes are supported:\n\n        - grapheme: grapheme clusters. Appropriate for strings containing visual\n          characters which can span multiple Unicode code points (e.g., emoji).\n        - code_point: Unicode code points. Appropriate for strings containing\n          visual characters which are comprised of more than one Unicode code\n          unit (e.g., ideographic symbols and punctuation and mathematical\n          alphanumerics).\n        - code_unit': UTF-16 code units. Appropriate for strings containing\n          visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n          common characters, such as those from the Latin, Greek, and Cyrillic\n          alphabets).\n\n        Default: 'grapheme'.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = last( 'beep' )\n    'p'\n    > out = last( 'Boop', 2 )\n    'op'\n    > out = last( 'foo bar', 3 )\n    'bar'\n\n    See Also\n    --------\n    firstChar\n","leveneTest":"\nleveneTest( x[, ...y[, options]] )\n    Computes Levene's test for equal variances.\n\n    Parameters\n    ----------\n    x: Array<number>\n        Measured values.\n\n    y: ...Array<number> (optional)\n        Measured values.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.groups: Array (optional)\n        Array of group indicators.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.method: string\n        Name of test.\n\n    out.df: Array\n        Degrees of freedom.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    // Data from Hollander & Wolfe (1973), p. 116:\n    > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n    > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n    > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n    > var out = leveneTest( x, y, z )\n\n    > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n    ...     3.8, 2.7, 4.0, 2.4,\n    ...     2.8, 3.4, 3.7, 2.2, 2.0\n    ... ];\n    > var groups = [\n    ...     'a', 'a', 'a', 'a', 'a',\n    ...     'b', 'b', 'b', 'b',\n    ...     'c', 'c', 'c', 'c', 'c'\n    ... ];\n    > out = leveneTest( arr, { 'groups': groups } )\n\n    See Also\n    --------\n    vartest, bartlettTest\n","LinkedList":"\nLinkedList()\n    Linked list constructor.\n\n    Returns\n    -------\n    list: Object\n        Linked list.\n\n    list.clear: Function\n        Clears the list.\n\n    list.first: Function\n        Returns the last node. If the list is empty, the returned value is\n        `undefined`.\n\n    list.insert: Function\n        Inserts a value after a provided list node.\n\n    list.iterator: Function\n        Returns an iterator for iterating over a list. If an environment\n        supports Symbol.iterator, the returned iterator is iterable. Note that,\n        in order to prevent confusion arising from list mutation during\n        iteration, a returned iterator **always** iterates over a list\n        \"snapshot\", which is defined as the list of list elements at the time\n        of the method's invocation.\n\n    list.last: Function\n        Returns the last list node. If the list is empty, the returned value is\n        `undefined`.\n\n    list.length: integer\n        List length.\n\n    list.pop: Function\n        Removes and returns the last list value. If the list is empty, the\n        returned value is `undefined`.\n\n    list.push: Function\n        Adds a value to the end of the list.\n\n    list.remove: Function\n        Removes a list node from the list.\n\n    list.shift: Function\n        Removes and returns the first list value. If the list is empty, the\n        returned value is `undefined`.\n\n    list.toArray: Function\n        Returns an array of list values.\n\n    list.toJSON: Function\n        Serializes a list as JSON.\n\n    list.unshift: Function\n        Adds a value to the beginning of the list.\n\n    Examples\n    --------\n    > var list = LinkedList();\n    > list.push( 'foo' ).push( 'bar' );\n    > list.length\n    2\n    > list.pop()\n    'bar'\n    > list.length\n    1\n    > list.pop()\n    'foo'\n    > list.length\n    0\n\n    See Also\n    --------\n    DoublyLinkedList, Stack\n","linspace":"\nlinspace( start, stop, length[, options] )\n    Generates a linearly spaced array over a specified interval.\n\n    If the specified length is zero, the function returns an empty array.\n\n    If the specified length is one, the function returns an array containing\n    `stop`, but not `start`, when `endpoint` is true; otherwise, the function\n    returns an array containing `start`, but not `stop`.\n\n    For real-valued `start` and `stop`, if `start` is less than `stop`, the\n    output array will contain ascending values, and, if `start` is greater than\n    `stop`, the output array will contain descending values.\n\n    When the output array length is greater than one and `endpoint` is true, the\n    output array is guaranteed to include the `start` and `stop` values. Beware,\n    however, that values between `start` and `stop` are subject to floating-\n    point rounding errors.\n\n    If both `start` and `stop` are real-valued, the output array data type may\n    be any floating-point data type or 'generic'. However, if either `start` or\n    `stop` are complex numbers, the output array type must be a complex\n    floating-point data type or 'generic'.\n\n    When writing to a complex floating-point output array, real-valued `start`\n    and `stop` values are treated as complex numbers having a real component\n    equaling the provided value and having an imaginary component equaling zero.\n\n    When generating linearly spaced complex floating-point numbers, the real and\n    imaginary components are generated separately.\n\n    Parameters\n    ----------\n    start: number|ComplexLike\n        Start of interval.\n\n    stop: number|ComplexLike\n        End of interval.\n\n    length: integer\n        Length of output array.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Must be a floating-point data type or 'generic'.\n         If both `start` and `stop` are the same type (either 'float64',\n         'complex64', or 'complex128'), the default output array data type is\n         the same type as the input values (either 'float64', 'complex64', or\n         'complex128', respectively). Otherwise, the default output array data\n         type is 'complex128'.\n\n    options.endpoint: boolean (optional)\n        Boolean indicating whether to include the `stop` value in the output\n        array. If false, the function generates `length + 1` linearly spaced\n        values over the interval `[start, stop]` and only writes `length` values\n        to the output array, thus excluding `stop` from the output array.\n        Accordingly, for a fixed `length`, the spacing between adjacent values\n        in the output array changes depending on the value of `endpoint`.\n        Default: true.\n\n    Returns\n    -------\n    arr: Array\n        Linearly spaced array.\n\n    Examples\n    --------\n    > var arr = linspace( 0.0, 100.0, 6 )\n    <Float64Array>[ 0.0, 20.0, 40.0, 60.0, 80.0, 100.0 ]\n    > arr = linspace( 0.0, 100.0, 5, { 'endpoint': false } )\n    <Float64Array>[ 0.0, 20.0, 40.0, 60.0, 80.0 ]\n    > arr = linspace( 0.0, 100.0, 6, { 'dtype': 'generic' } )\n    [ 0.0, 20.0, 40.0, 60.0, 80.0, 100.0 ]\n\n\nlinspace.assign( start, stop, out[, options] )\n    Generates a linearly spaced sequence over a specified interval and assigns\n    the results to a provided output array.\n\n    If the provided output array is empty, the function returns the provided\n    output array unchanged.\n\n    If the provided output array contains a single element, the function writes\n    the `stop` value, but not `start`, when `endpoint` is true; otherwise, the\n    function writes the `start` value, but not `stop`.\n\n    Parameters\n    ----------\n    start: number|ComplexLike\n        Start of interval.\n\n    stop: number|ComplexLike\n        End of interval.\n\n    out: ArrayLikeObject\n        Output array.\n\n    options: Object (optional)\n        Options.\n\n    options.endpoint: boolean (optional)\n        Boolean indicating whether to include the `stop` value in the output\n        array. If false, the function generates `N+1` linearly spaced values\n        (where `N` is the length of the provided output array) over the interval\n        `[start, stop]` and only writes `N` values to the output array, thus\n        excluding `stop` from the output array. Accordingly, for a fixed `N`,\n        the spacing between adjacent values in the output array changes\n        depending on the value of `endpoint`. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var arr = [ 0, 0, 0, 0, 0, 0 ];\n    > var out = linspace.assign( 0, 100, arr )\n    [ 0, 20, 40, 60, 80, 100 ]\n    > var bool = ( arr === out )\n    true\n    > arr = [ 0, 0, 0, 0, 0 ];\n    > out = linspace.assign( 0, 100, arr, { 'endpoint': false } )\n    [ 0, 20, 40, 60, 80 ]\n\n    See Also\n    --------\n    incrspace, logspace\n","linspace.assign":"\nlinspace.assign( start, stop, out[, options] )\n    Generates a linearly spaced sequence over a specified interval and assigns\n    the results to a provided output array.\n\n    If the provided output array is empty, the function returns the provided\n    output array unchanged.\n\n    If the provided output array contains a single element, the function writes\n    the `stop` value, but not `start`, when `endpoint` is true; otherwise, the\n    function writes the `start` value, but not `stop`.\n\n    Parameters\n    ----------\n    start: number|ComplexLike\n        Start of interval.\n\n    stop: number|ComplexLike\n        End of interval.\n\n    out: ArrayLikeObject\n        Output array.\n\n    options: Object (optional)\n        Options.\n\n    options.endpoint: boolean (optional)\n        Boolean indicating whether to include the `stop` value in the output\n        array. If false, the function generates `N+1` linearly spaced values\n        (where `N` is the length of the provided output array) over the interval\n        `[start, stop]` and only writes `N` values to the output array, thus\n        excluding `stop` from the output array. Accordingly, for a fixed `N`,\n        the spacing between adjacent values in the output array changes\n        depending on the value of `endpoint`. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var arr = [ 0, 0, 0, 0, 0, 0 ];\n    > var out = linspace.assign( 0, 100, arr )\n    [ 0, 20, 40, 60, 80, 100 ]\n    > var bool = ( arr === out )\n    true\n    > arr = [ 0, 0, 0, 0, 0 ];\n    > out = linspace.assign( 0, 100, arr, { 'endpoint': false } )\n    [ 0, 20, 40, 60, 80 ]\n\n    See Also\n    --------\n    incrspace, logspace","LIU_NEGATIVE_OPINION_WORDS_EN":"\nLIU_NEGATIVE_OPINION_WORDS_EN()\n    Returns a list of negative opinion words.\n\n    A word's appearance in a sentence does *not* necessarily imply a positive or\n    negative opinion.\n\n    The list includes misspelled words. Their presence is intentional, as such\n    misspellings frequently occur in social media content.\n\n    Returns\n    -------\n    out: Array<string>\n        List of negative opinion words.\n\n    Examples\n    --------\n    > var list = LIU_NEGATIVE_OPINION_WORDS_EN()\n    [ '2-faced', '2-faces', 'abnormal', 'abolish', ... ]\n\n    References\n    ----------\n    - Hu, Minqing, and Bing Liu. 2004. \"Mining and Summarizing Customer\n    Reviews.\" In *Proceedings of the Tenth Acm Sigkdd International Conference\n    on Knowledge Discovery and Data Mining*, 168–77. KDD '04. New York, NY, USA:\n    ACM. doi:10.1145/1014052.1014073.\n    - Liu, Bing, Minqing Hu, and Junsheng Cheng. 2005. \"Opinion Observer:\n    Analyzing and Comparing Opinions on the Web.\" In *Proceedings of the 14th\n    International Conference on World Wide Web*, 342–51. WWW '05. New York, NY,\n    USA: ACM. doi:10.1145/1060745.1060797.\n\n    * If you use the list for publication or third party consumption, please\n    cite one of the listed references.\n\n    See Also\n    --------\n    LIU_POSITIVE_OPINION_WORDS_EN\n","LIU_POSITIVE_OPINION_WORDS_EN":"\nLIU_POSITIVE_OPINION_WORDS_EN()\n    Returns a list of positive opinion words.\n\n    A word's appearance in a sentence does *not* necessarily imply a positive or\n    negative opinion.\n\n    The list includes misspelled words. Their presence is intentional, as such\n    misspellings frequently occur in social media content.\n\n    Returns\n    -------\n    out: Array<string>\n        List of positive opinion words.\n\n    Examples\n    --------\n    > var list = LIU_POSITIVE_OPINION_WORDS_EN()\n    [ 'a+', 'abound', 'abounds', 'abundance', ... ]\n\n    References\n    ----------\n    - Hu, Minqing, and Bing Liu. 2004. 'Mining and Summarizing Customer\n    Reviews.' In *Proceedings of the Tenth Acm Sigkdd International Conference\n    on Knowledge Discovery and Data Mining*, 168–77. KDD '04. New York, NY, USA:\n    ACM. doi:10.1145/1014052.1014073.\n    - Liu, Bing, Minqing Hu, and Junsheng Cheng. 2005. 'Opinion Observer:\n    Analyzing and Comparing Opinions on the Web.' In *Proceedings of the 14th\n    International Conference on World Wide Web*, 342–51. WWW '05. New York, NY,\n    USA: ACM. doi:10.1145/1060745.1060797.\n\n    * If you use the list for publication or third party consumption, please\n    cite one of the listed references.\n\n    See Also\n    --------\n    LIU_NEGATIVE_OPINION_WORDS_EN\n","LN_HALF":"\nLN_HALF\n    Natural logarithm of `1/2`.\n\n    Examples\n    --------\n    > LN_HALF\n    -0.6931471805599453\n\n","LN_PI":"\nLN_PI\n    Natural logarithm of the mathematical constant `π`.\n\n    Examples\n    --------\n    > LN_PI\n    1.1447298858494002\n\n    See Also\n    --------\n    PI\n","LN_SQRT_TWO_PI":"\nLN_SQRT_TWO_PI\n    Natural logarithm of the square root of `2π`.\n\n    Examples\n    --------\n    > LN_SQRT_TWO_PI\n    0.9189385332046728\n\n    See Also\n    --------\n    PI\n","LN_TWO_PI":"\nLN_TWO_PI\n    Natural logarithm of `2π`.\n\n    Examples\n    --------\n    > LN_TWO_PI\n    1.8378770664093456\n\n    See Also\n    --------\n    TWO_PI\n","LN2":"\nLN2\n    Natural logarithm of `2`.\n\n    Examples\n    --------\n    > LN2\n    0.6931471805599453\n\n    See Also\n    --------\n    LN10\n","LN10":"\nLN10\n    Natural logarithm of `10`.\n\n    Examples\n    --------\n    > LN10\n    2.302585092994046\n\n    See Also\n    --------\n    LN2\n","LOG2E":"\nLOG2E\n    Base 2 logarithm of Euler's number.\n\n    Examples\n    --------\n    > LOG2E\n    1.4426950408889634\n\n    See Also\n    --------\n    E, LOG10E\n","LOG10E":"\nLOG10E\n    Base 10 logarithm of Euler's number.\n\n    Examples\n    --------\n    > LOG10E\n    0.4342944819032518\n\n    See Also\n    --------\n    E, LOG2E\n","logspace":"\nlogspace( a, b[, length] )\n    Generates a logarithmically spaced numeric array between `10^a` and `10^b`.\n\n    If a `length` is not provided, the default output array length is `10`.\n\n    The output array includes the values `10^a` and `10^b`.\n\n    Parameters\n    ----------\n    a: number\n        Exponent of start value.\n\n    b: number\n        Exponent of end value.\n\n    length: integer (optional)\n        Length of output array. Default: `10`.\n\n    Returns\n    -------\n    arr: Array\n        Logarithmically spaced numeric array.\n\n    Examples\n    --------\n    > var arr = logspace( 0, 2, 6 )\n    [ 1, ~2.5, ~6.31, ~15.85, ~39.81, 100 ]\n\n    See Also\n    --------\n    incrspace, linspace\n","lowercase":"\nlowercase( str )\n    Converts a string to lowercase.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Lowercase string.\n\n    Examples\n    --------\n    > var out = lowercase( 'bEEp' )\n    'beep'\n\n    See Also\n    --------\n    uncapitalize, uppercase\n","lowercaseKeys":"\nlowercaseKeys( obj )\n    Converts each object key to lowercase.\n\n    The function only transforms own properties. Hence, the function does not\n    transform inherited properties.\n\n    The function shallow copies key values.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > var obj = { 'A': 1, 'B': 2 };\n    > var out = lowercaseKeys( obj )\n    { 'a': 1, 'b': 2 }\n\n    See Also\n    --------\n    uncapitalizeKeys, uppercaseKeys\n","lowess":"\nlowess( x, y[, options] )\n    Locally-weighted polynomial regression via the LOWESS algorithm.\n\n    Parameters\n    ----------\n    x: Array<number>\n        x-axis values (abscissa values).\n\n    y: Array<number>\n        Corresponding y-axis values (ordinate values).\n\n    options: Object (optional)\n        Function options.\n\n    options.f: number (optional)\n        Positive number specifying the smoothing span, i.e., the proportion of\n        points which influence smoothing at each value. Larger values\n        correspond to more smoothing. Default: `2/3`.\n\n    options.nsteps: number (optional)\n        Number of iterations in the robust fit (fewer iterations translates to\n        faster function execution). If set to zero, the nonrobust fit is\n        returned. Default: `3`.\n\n    options.delta: number (optional)\n        Nonnegative number which may be used to reduce the number of\n        computations. Default: 1/100th of the range of `x`.\n\n    options.sorted: boolean (optional)\n        Boolean indicating if the input array `x` is sorted. Default: `false`.\n\n    Returns\n    -------\n    out: Object\n        Object with ordered x-values and fitted values.\n\n    Examples\n    --------\n    > var x = new Float64Array( 100 );\n    > var y = new Float64Array( x.length );\n    > for ( var i = 0; i < x.length; i++ ) {\n    ...     x[ i ] = i;\n    ...     y[ i ] = ( 0.5*i ) + ( 10.0*base.random.randn() );\n    ... }\n    > var out = lowess( x, y );\n    > var yhat = out.y;\n\n    > var h = Plot( [ x, x ], [ y, yhat ] );\n    > h.lineStyle = [ 'none', '-' ];\n    > h.symbols = [ 'closed-circle', 'none' ];\n\n    > h.view( 'window' );\n\n","lpad":"\nlpad( str, len[, pad] )\n    Left pads a string such that the padded string has a length of at least\n    `len`.\n\n    An output string is not guaranteed to have a length of exactly `len`, but to\n    have a length of at least `len`. To generate a padded string having a length\n    equal to `len`, post-process a padded string by trimming off excess\n    characters.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    len: integer\n        Minimum string length.\n\n    pad: string (optional)\n        String used to pad. Default: ' '.\n\n    Returns\n    -------\n    out: string\n        Padded string.\n\n    Examples\n    --------\n    > var out = lpad( 'a', 5 )\n    '    a'\n    > out = lpad( 'beep', 10, 'b' )\n    'bbbbbbbeep'\n    > out = lpad( 'boop', 12, 'beep' )\n    'beepbeepboop'\n\n    See Also\n    --------\n    pad, rpad\n","ltrim":"\nltrim( str )\n    Trims whitespace from the beginning of a string.\n\n    \"Whitespace\" is defined as the following characters:\n\n    - \\f\n    - \\n\n    - \\r\n    - \\t\n    - \\v\n    - \\u0020\n    - \\u00a0\n    - \\u1680\n    - \\u2000-\\u200a\n    - \\u2028\n    - \\u2029\n    - \\u202f\n    - \\u205f\n    - \\u3000\n    - \\ufeff\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Trimmed string.\n\n    Examples\n    --------\n    > var out = ltrim( ' \\r\\n\\t  Beep \\t\\t\\n  ' )\n    'Beep \\t\\t\\n  '\n\n    See Also\n    --------\n    trim, rtrim\n","ltrimN":"\nltrimN( str, n[, chars] )\n    Trims `n` characters from the beginning of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of characters to trim.\n\n    chars: Array<string>|string (optional)\n        Characters to trim. Default: whitespace characters.\n\n    Returns\n    -------\n    out: string\n        Trimmed string.\n\n    Examples\n    --------\n    > var out = ltrimN( '  abc  ', 2 )\n    'abc  '\n    > var out = ltrimN( '!!!abc!!!', 2, '!' )\n    '!abc!!!'\n\n    See Also\n    --------\n    rtrimN, trim","MALE_FIRST_NAMES_EN":"\nMALE_FIRST_NAMES_EN()\n    Returns a list of common male first names in English speaking countries.\n\n    Returns\n    -------\n    out: Array<string>\n        List of common male first names.\n\n    Examples\n    --------\n    > var list = MALE_FIRST_NAMES_EN()\n    [ 'Aaron', 'Ab', 'Abba', 'Abbe', ... ]\n\n    References\n    ----------\n    - Ward, Grady. 2002. 'Moby Word II.' <http://www.gutenberg.org/files/3201/\n    3201.txt>.\n\n    See Also\n    --------\n    FEMALE_FIRST_NAMES_EN\n","map":"\nmap( arr, fcn[, thisArg] )\n    Applies a function to each element in an array and assigns the result to an\n    element in a new array.\n\n    The applied function is provided the following arguments:\n\n    - value: array element.\n    - index: element index.\n    - arr: input array.\n\n    The returned output array always has a \"generic\" data type. For example, if\n    provided an array-like object, the function returns a generic array. If\n    provided an ndarray, the function returns an ndarray having a \"generic\" data\n    type.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject|ndarray\n        Input array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.abs, 1 );\n    > var arr = [ -1, -2, -3, -4, -5, -6 ];\n    > var out = map( arr, f )\n    [ 1, 2, 3, 4, 5, 6 ]\n\n    // ndarray:\n    > arr = array( arr, { 'shape': [ 2, 3 ] } );\n    > out = map( arr, f );\n    > var v = out.get( 1, 1 )\n    5\n\n\nmap.assign( arr, out, fcn[, thisArg] )\n    Applies a function to each element in an array and assigns the result to an\n    element in an output array.\n\n    The applied function is provided the following arguments:\n\n    - value: array element.\n    - index: element index.\n    - arr: input array.\n\n    Input and output arrays must be either both array-like objects or both\n    ndarray-like objects.\n\n    If input and output arrays are array-like objects, the arrays must have the\n    same number of elements.\n\n    If input and output arrays are both ndarray-like objects, the arrays *must*\n    be broadcast compatible.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject|ndarray\n        Input array.\n\n    out: ArrayLikeObject|ndarray\n        Output array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.abs, 1 );\n    > var arr = [ -1, -2, -3, -4, -5, -6 ];\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > map.assign( arr, out, f );\n    > out\n    [ 1, 2, 3, 4, 5, 6 ]\n\n    // ndarray:\n    > var opts = { 'shape': [ 2, 3 ] };\n    > arr = array( arr, opts );\n    > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n    > map.assign( arr, out, f );\n    > var v = out.get( 1, 1 )\n    5\n\n    See Also\n    --------\n    mapRight, reduce\n","map.assign":"\nmap.assign( arr, out, fcn[, thisArg] )\n    Applies a function to each element in an array and assigns the result to an\n    element in an output array.\n\n    The applied function is provided the following arguments:\n\n    - value: array element.\n    - index: element index.\n    - arr: input array.\n\n    Input and output arrays must be either both array-like objects or both\n    ndarray-like objects.\n\n    If input and output arrays are array-like objects, the arrays must have the\n    same number of elements.\n\n    If input and output arrays are both ndarray-like objects, the arrays *must*\n    be broadcast compatible.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject|ndarray\n        Input array.\n\n    out: ArrayLikeObject|ndarray\n        Output array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.abs, 1 );\n    > var arr = [ -1, -2, -3, -4, -5, -6 ];\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > map.assign( arr, out, f );\n    > out\n    [ 1, 2, 3, 4, 5, 6 ]\n\n    // ndarray:\n    > var opts = { 'shape': [ 2, 3 ] };\n    > arr = array( arr, opts );\n    > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n    > map.assign( arr, out, f );\n    > var v = out.get( 1, 1 )\n    5\n\n    See Also\n    --------\n    mapRight, reduce","map2":"\nmap2( x, y, fcn[, thisArg] )\n    Applies a function to elements in two input arrays and assigns the results\n    to a new array.\n\n    The applied function is provided the following arguments:\n\n    - v1: element from first input array.\n    - v2: element from second input array.\n    - idx: element index.\n    - arrays: input arrays.\n\n    The returned output array always has a \"generic\" data type. For example, if\n    provided an array-like object, the function returns a generic array. If\n    provided an ndarray, the function returns an ndarray having a \"generic\" data\n    type.\n\n    Input arrays must be either both array-like objects or both ndarray-like\n    objects.\n\n    If input arrays are array-like objects, the arrays must have the same number\n    of elements.\n\n    If input arrays are ndarray-like objects, the arrays must be broadcast\n    compatible.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject|ndarray\n        First input array.\n\n    y: ArrayLikeObject|ndarray\n        Second input array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.add, 2 );\n    > var x = [ 1, 2, 3, 4, 5, 6 ];\n    > var y = [ 1, 1, 1, 1, 1, 1 ];\n    > var out = map2( x, y, f )\n    [ 2, 3, 4, 5, 6, 7 ]\n\n    // ndarray:\n    > x = array( x, { 'shape': [ 2, 3 ] } );\n    > y = array( y, { 'shape': [ 2, 3 ] } );\n    > out = map2( x, y, f );\n    > var v = out.get( 1, 1 )\n    6\n\n\nmap2.assign( x, y, out, fcn[, thisArg] )\n    Applies a function to elements in two input arrays and assigns the results\n    to an output array.\n\n    The applied function is provided the following arguments:\n\n    - v1: element from first input array.\n    - v2: element from second input array.\n    - idx: element index.\n    - arrays: input arrays.\n\n    Input and output arrays must be either all array-like objects or all\n    ndarray-like objects.\n\n    If input and output arrays are array-like objects, the arrays must have the\n    same number of elements.\n\n    If input and output arrays are ndarray-like objects, the arrays must be\n    broadcast compatible.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject|ndarray\n        First input array.\n\n    y: ArrayLikeObject|ndarray\n        Second input array.\n\n    out: ArrayLikeObject|ndarray\n        Output array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.add, 2 );\n    > var x = [ 1, 2, 3, 4, 5, 6 ];\n    > var y = [ 1, 1, 1, 1, 1, 1 ];\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > map2.assign( x, y, out, f );\n    > out\n    [ 2, 3, 4, 5, 6, 7 ]\n\n    // ndarray:\n    > var opts = { 'shape': [ 2, 3 ] };\n    > x = array( x, opts );\n    > y = array( y, opts );\n    > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n    > map2.assign( x, y, out, f );\n    > var v = out.get( 1, 1 )\n    6\n\n    See Also\n    --------\n    map\n","map2.assign":"\nmap2.assign( x, y, out, fcn[, thisArg] )\n    Applies a function to elements in two input arrays and assigns the results\n    to an output array.\n\n    The applied function is provided the following arguments:\n\n    - v1: element from first input array.\n    - v2: element from second input array.\n    - idx: element index.\n    - arrays: input arrays.\n\n    Input and output arrays must be either all array-like objects or all\n    ndarray-like objects.\n\n    If input and output arrays are array-like objects, the arrays must have the\n    same number of elements.\n\n    If input and output arrays are ndarray-like objects, the arrays must be\n    broadcast compatible.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject|ndarray\n        First input array.\n\n    y: ArrayLikeObject|ndarray\n        Second input array.\n\n    out: ArrayLikeObject|ndarray\n        Output array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.add, 2 );\n    > var x = [ 1, 2, 3, 4, 5, 6 ];\n    > var y = [ 1, 1, 1, 1, 1, 1 ];\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > map2.assign( x, y, out, f );\n    > out\n    [ 2, 3, 4, 5, 6, 7 ]\n\n    // ndarray:\n    > var opts = { 'shape': [ 2, 3 ] };\n    > x = array( x, opts );\n    > y = array( y, opts );\n    > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n    > map2.assign( x, y, out, f );\n    > var v = out.get( 1, 1 )\n    6\n\n    See Also\n    --------\n    map","map2d":"\nmap2d( arr, fcn[, thisArg] )\n    Applies a function to each nested element in an array of arrays and assigns\n    the result to a nested element in a new array of arrays.\n\n    The applied function is provided the following arguments:\n\n    - value: array element.\n    - indices: current array element indices.\n    - arr: input array.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject<ArrayLikeObject>\n        Input array of arrays.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array<Array>\n        Array of arrays.\n\n    Examples\n    --------\n    > var f = naryFunction( base.abs, 1 );\n    > var arr = [ [ -1, -2, -3 ], [ -4, -5, -6 ] ];\n    > var out = map2d( arr, f );\n    > out[ 0 ]\n    [ 1, 2, 3 ]\n    > out[ 1 ]\n    [ 4, 5, 6 ]\n\n    See Also\n    --------\n    map, map3d, map4d, map5d, reduce2d\n","map2Right":"\nmap2Right( x, y, fcn[, thisArg] )\n    Applies a function to elements in two input arrays while iterating from\n    right to left and assigns the results to a new array.\n\n    The applied function is provided the following arguments:\n\n    - v1: element from first input array.\n    - v2: element from second input array.\n    - idx: element index.\n    - arrays: input arrays.\n\n    The returned output array always has a \"generic\" data type. For example, if\n    provided an array-like object, the function returns a generic array. If\n    provided an ndarray, the function returns an ndarray having a \"generic\" data\n    type.\n\n    Input arrays must be either both array-like objects or both ndarray-like\n    objects.\n\n    If input arrays are array-like objects, the arrays must have the same number\n    of elements.\n\n    If input arrays are ndarray-like objects, the arrays must be broadcast\n    compatible.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject|ndarray\n        First input array.\n\n    y: ArrayLikeObject|ndarray\n        Second input array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.add, 2 );\n    > var x = [ 1, 2, 3, 4, 5, 6 ];\n    > var y = [ 1, 1, 1, 1, 1, 1 ];\n    > var out = map2Right( x, y, f )\n    [ 2, 3, 4, 5, 6, 7 ]\n\n    // ndarray:\n    > x = array( x, { 'shape': [ 2, 3 ] } );\n    > y = array( y, { 'shape': [ 2, 3 ] } );\n    > out = map2Right( x, y, f );\n    > var v = out.get( 1, 1 )\n    6\n\n\nmap2Right.assign( x, y, out, fcn[, thisArg] )\n    Applies a function to elements in two input arrays while iterating from\n    right to left and assigns the results to an output array.\n\n    The applied function is provided the following arguments:\n\n    - v1: element from first input array.\n    - v2: element from second input array.\n    - idx: element index.\n    - arrays: input arrays.\n\n    Input and output arrays must be either all array-like objects or all\n    ndarray-like objects.\n\n    If input and output arrays are array-like objects, the arrays must have the\n    same number of elements.\n\n    If input and output arrays are ndarray-like objects, the arrays must be\n    broadcast compatible.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject|ndarray\n        First input array.\n\n    y: ArrayLikeObject|ndarray\n        Second input array.\n\n    out: ArrayLikeObject|ndarray\n        Output array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.add, 2 );\n    > var x = [ 1, 2, 3, 4, 5, 6 ];\n    > var y = [ 1, 1, 1, 1, 1, 1 ];\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > map2Right.assign( x, y, out, f );\n    > out\n    [ 2, 3, 4, 5, 6, 7 ]\n\n    // ndarray:\n    > var opts = { 'shape': [ 2, 3 ] };\n    > x = array( x, opts );\n    > y = array( y, opts );\n    > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n    > map2Right.assign( x, y, out, f );\n    > var v = out.get( 1, 1 )\n    6\n\n    See Also\n    --------\n    mapRight, map2\n","map2Right.assign":"\nmap2Right.assign( x, y, out, fcn[, thisArg] )\n    Applies a function to elements in two input arrays while iterating from\n    right to left and assigns the results to an output array.\n\n    The applied function is provided the following arguments:\n\n    - v1: element from first input array.\n    - v2: element from second input array.\n    - idx: element index.\n    - arrays: input arrays.\n\n    Input and output arrays must be either all array-like objects or all\n    ndarray-like objects.\n\n    If input and output arrays are array-like objects, the arrays must have the\n    same number of elements.\n\n    If input and output arrays are ndarray-like objects, the arrays must be\n    broadcast compatible.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject|ndarray\n        First input array.\n\n    y: ArrayLikeObject|ndarray\n        Second input array.\n\n    out: ArrayLikeObject|ndarray\n        Output array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.add, 2 );\n    > var x = [ 1, 2, 3, 4, 5, 6 ];\n    > var y = [ 1, 1, 1, 1, 1, 1 ];\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > map2Right.assign( x, y, out, f );\n    > out\n    [ 2, 3, 4, 5, 6, 7 ]\n\n    // ndarray:\n    > var opts = { 'shape': [ 2, 3 ] };\n    > x = array( x, opts );\n    > y = array( y, opts );\n    > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n    > map2Right.assign( x, y, out, f );\n    > var v = out.get( 1, 1 )\n    6\n\n    See Also\n    --------\n    mapRight, map2","map3d":"\nmap3d( arr, fcn[, thisArg] )\n    Applies a function to each nested element in a three-dimensional nested\n    array and assigns the result to a nested element in a new three-dimensional\n    nested array.\n\n    The applied function is provided the following arguments:\n\n    - value: array element.\n    - indices: current array element indices.\n    - arr: input array.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject<ArrayLikeObject<ArrayLikeObject>>\n        Input three-dimensional nested array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array<Array<Array>>\n        Three-dimensional nested array.\n\n    Examples\n    --------\n    > var f = naryFunction( base.abs, 1 );\n    > var arr = [ [ [ -1, -2, -3 ] ], [ [ -4, -5, -6 ] ] ];\n    > var out = map3d( arr, f );\n    > out[ 0 ][ 0 ]\n    [ 1, 2, 3 ]\n    > out[ 1 ][ 0 ]\n    [ 4, 5, 6 ]\n\n    See Also\n    --------\n    map, map2d, map4d, map5d\n","map4d":"\nmap4d( arr, fcn[, thisArg] )\n    Applies a function to each nested element in a four-dimensional nested array\n    and assigns the result to a nested element in a new four-dimensional nested\n    array.\n\n    The applied function is provided the following arguments:\n\n    - value: array element.\n    - indices: current array element indices.\n    - arr: input array.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject<ArrayLikeObject>\n        Input four-dimensional nested array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array<Array<Array<Array>>>\n        Four-dimensional nested array.\n\n    Examples\n    --------\n    > var f = naryFunction( base.abs, 1 );\n    > var arr = [ [ [ [ -1, -2, -3 ] ] ], [ [ [ -4, -5, -6 ] ] ] ];\n    > var out = map4d( arr, f );\n    > out[ 0 ][ 0 ][ 0 ]\n    [ 1, 2, 3 ]\n    > out[ 1 ][ 0 ][ 0 ]\n    [ 4, 5, 6 ]\n\n    See Also\n    --------\n    map, map2d, map3d, map5d\n","map5d":"\nmap5d( arr, fcn[, thisArg] )\n    Applies a function to each nested element in a five-dimensional nested array\n    and assigns the result to a nested element in a new five-dimensional nested\n    array.\n\n    The applied function is provided the following arguments:\n\n    - value: array element.\n    - indices: current array element indices.\n    - arr: input array.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject<ArrayLikeObject>\n        Input five-dimensional nested array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array<Array<Array<Array<Array>>>>\n        Five-dimensional nested array.\n\n    Examples\n    --------\n    > var f = naryFunction( base.abs, 1 );\n    > var arr = [ [ [ [ [ -1, -2, -3 ] ] ] ], [ [ [ [ -4, -5, -6 ] ] ] ] ];\n    > var out = map5d( arr, f );\n    > out[ 0 ][ 0 ][ 0 ][ 0 ]\n    [ 1, 2, 3 ]\n    > out[ 1 ][ 0 ][ 0 ][ 0 ]\n    [ 4, 5, 6 ]\n\n    See Also\n    --------\n    map, map2d, map3d, map4d\n","mapArguments":"\nmapArguments( fcn, clbk[, thisArg] )\n    Returns a function that applies arguments to a provided function after\n    transforming arguments according to a callback function.\n\n    The callback function is provided the following arguments:\n\n    - value: argument value.\n    - index: argument index.\n\n    Parameters\n    ----------\n    fcn: Function\n        Input function.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Function\n        Function wrapper.\n\n    Examples\n    --------\n    > function foo( a, b, c ) { return [ a, b, c ]; };\n    > function clbk( v ) { return v * 2; };\n    > var bar = mapArguments( foo, clbk );\n    > var out = bar( 1, 2, 3 )\n    [ 2, 4, 6 ]\n\n    See Also\n    --------\n    filterArguments\n","mapFun":"\nmapFun( fcn, n[, thisArg] )\n    Invokes a function `n` times and returns an array of accumulated function\n    return values.\n\n    The invoked function is provided a single argument: the invocation index\n    (zero-based).\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke.\n\n    n: integer\n        Number of times to invoke a function.\n\n    thisArg: any (optional)\n        Function execution context.\n\n    Returns\n    -------\n    out: Array\n        Array of accumulated function return values.\n\n    Examples\n    --------\n    > function fcn( i ) { return i; };\n    > var arr = mapFun( fcn, 5 )\n    [ 0, 1, 2, 3, 4 ]\n\n    See Also\n    --------\n    mapFunAsync\n","mapFunAsync":"\nmapFunAsync( fcn, n, [options,] done )\n    Invokes a function `n` times and returns an array of accumulated function\n    return values.\n\n    For each iteration, the provided function is invoked with two arguments:\n\n    - index: invocation index (starting from zero).\n    - next: callback to be invoked upon function completion.\n\n    The `next` callback accepts two arguments:\n\n    - error: error argument.\n    - result: function result.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke.\n\n    n: integer\n        Number of times to invoke a function.\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to allow only one pending invocation at a\n        time. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    done: Function\n        A callback invoked upon executing a provided function `n` times or upon\n        encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function fcn( i, next ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         next( null, i );\n    ...     }\n    ... };\n    > function done( error, arr ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( arr );\n    ... };\n    > mapFunAsync( fcn, 10, done )\n    [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n    // Limit number of concurrent invocations:\n    > function fcn( i, next ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         next( null, i );\n    ...     }\n    ... };\n    > function done( error, arr ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( arr );\n    ... };\n    > var opts = { 'limit': 2 };\n    > mapFunAsync( fcn, 10, opts, done )\n    [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n    // Sequential invocation:\n    > function fcn( i, next ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         next( null, i );\n    ...     }\n    ... };\n    > function done( error, arr ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( arr );\n    ... };\n    > var opts = { 'series': true };\n    > mapFunAsync( fcn, 10, opts, done )\n    [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n\nmapFunAsync.factory( [options,] fcn )\n    Returns a function which invokes a function `n` times and returns an array\n    of accumulated function return values.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to allow only one pending invocation at a\n        time. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        Function to invoke.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function `n` times and returns an array of\n        accumulated function return values.\n\n    Examples\n    --------\n    > function fcn( i, next ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         next( null, i );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = mapFunAsync.factory( opts, fcn );\n    > function done( error, arr ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( arr );\n    ... };\n    > f( 10, done )\n    [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n    See Also\n    --------\n    mapFun\n","mapFunAsync.factory":"\nmapFunAsync.factory( [options,] fcn )\n    Returns a function which invokes a function `n` times and returns an array\n    of accumulated function return values.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to allow only one pending invocation at a\n        time. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        Function to invoke.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function `n` times and returns an array of\n        accumulated function return values.\n\n    Examples\n    --------\n    > function fcn( i, next ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         next( null, i );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = mapFunAsync.factory( opts, fcn );\n    > function done( error, arr ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( arr );\n    ... };\n    > f( 10, done )\n    [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n    See Also\n    --------\n    mapFun","mapKeys":"\nmapKeys( obj, transform )\n    Maps keys from one object to a new object having the same values.\n\n    The transform function is provided three arguments:\n\n    - key: object key.\n    - value: object value corresponding to `key`.\n    - obj: the input object.\n\n    The value returned by a transform function should be a value which can be\n    serialized as an object key.\n\n    The function only maps own properties. Hence, the function does not map\n    inherited properties.\n\n    The function shallow copies key values.\n\n    Key iteration order is *not* guaranteed.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    transform: Function\n        Transform function. Return values specify the keys of the output object.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > function transform( key, value ) { return key + value; };\n    > var obj = { 'a': 1, 'b': 2 };\n    > var out = mapKeys( obj, transform )\n    { 'a1': 1, 'b2': 2 }\n\n    See Also\n    --------\n    mapValues\n","mapKeysAsync":"\nmapKeysAsync( obj, [options,] transform, done )\n    Maps keys from one object to a new object having the same values.\n\n    When invoked, `transform` is provided a maximum of four arguments:\n\n    - key: object key.\n    - value: object value corresponding to `key`.\n    - obj: the input object.\n    - next: a callback to be invoked after processing an object `key`.\n\n    The actual number of provided arguments depends on function length. If\n    `transform` accepts two arguments, `transform` is provided:\n\n    - key\n    - next\n\n    If `transform` accepts three arguments, `transform` is provided:\n\n    - key\n    - value\n    - next\n\n    For every other `transform` signature, `transform` is provided all four\n    arguments.\n\n    The `next` callback accepts two arguments:\n\n    - error: error argument.\n    - key: transformed key.\n\n    If a `transform` function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    The key returned by a transform function should be a value which can be\n    serialized as an object key.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function only maps own properties. Hence, the function does not map\n    inherited properties.\n\n    The function shallow copies key values.\n\n    Key iteration and insertion order are *not* guaranteed.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each property sequentially.\n        Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    transform: Function\n        Transform function. Returned values specify the keys of the output\n        object.\n\n    done: Function\n        A callback invoked either upon processing all own properties or upon\n        encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function transform( key, value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         next( null, key+':'+value );\n    ...     }\n    ... };\n    > function done( error, out ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( out );\n    ... };\n    > var obj = { 'a': 1, 'b': 2 };\n    > mapKeysAsync( obj, transform, done )\n    { 'a:1': 1, 'b:2': 2 }\n\n    // Limit number of concurrent invocations:\n    > function transform( key, value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         next( null, key+':'+value );\n    ...     }\n    ... };\n    > function done( error, out ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( out );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n    > mapKeysAsync( obj, opts, transform, done )\n    { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n\n    // Process sequentially:\n    > function transform( key, value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         next( null, key+':'+value );\n    ...     }\n    ... };\n    > function done( error, out ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( out );\n    ... };\n    > var opts = { 'series': true };\n    > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n    > mapKeysAsync( obj, opts, transform, done )\n    { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n\n\nmapKeysAsync.factory( [options,] transform )\n    Returns a function which maps keys from one object to a new object having\n    the same values.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each property sequentially.\n        Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    transform: Function\n        Transform function. Returned values specify the keys of the output\n        object.\n\n    Returns\n    -------\n    out: Function\n        A function which maps keys from one object to a new object having the\n        same values.\n\n    Examples\n    --------\n    > function transform( key, value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         next( null, key+':'+value );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = mapKeysAsync.factory( opts, transform );\n    > function done( error, out ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( out );\n    ... };\n    > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n    > f( obj, done )\n    { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n    > obj = { 'beep': 'boop' };\n    > f( obj, done )\n    { 'beep:boop': 'beep' }\n\n    See Also\n    --------\n    mapKeys, mapValuesAsync\n","mapKeysAsync.factory":"\nmapKeysAsync.factory( [options,] transform )\n    Returns a function which maps keys from one object to a new object having\n    the same values.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each property sequentially.\n        Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    transform: Function\n        Transform function. Returned values specify the keys of the output\n        object.\n\n    Returns\n    -------\n    out: Function\n        A function which maps keys from one object to a new object having the\n        same values.\n\n    Examples\n    --------\n    > function transform( key, value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         next( null, key+':'+value );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = mapKeysAsync.factory( opts, transform );\n    > function done( error, out ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( out );\n    ... };\n    > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n    > f( obj, done )\n    { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n    > obj = { 'beep': 'boop' };\n    > f( obj, done )\n    { 'beep:boop': 'beep' }\n\n    See Also\n    --------\n    mapKeys, mapValuesAsync","mapReduce":"\nmapReduce( arr, initial, mapper, reducer[, thisArg] )\n    Performs a map-reduce operation for each element in an array and returns the\n    accumulated result.\n\n    When invoked, the mapping function is provided three arguments:\n\n    - value: array element.\n    - index: element index.\n    - arr: input array.\n\n    When invoked, the reducing function is provided four arguments:\n\n    - accumulator: accumulated value.\n    - value: result after applying the mapping function to the current array\n      element.\n    - index: element index.\n    - arr: input array.\n\n    If provided an empty array, the function returns the initial value.\n\n    When provided an ndarray, the function performs a single-pass map-reduce\n    operation over the entire input ndarray (i.e., higher-order ndarray\n    dimensions are flattened to a single-dimension).\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject|ndarray\n        Input array.\n\n    initial: any\n        Accumulator value used in the first invocation of the reduction\n        function.\n\n    mapper: Function\n        Mapping function.\n\n    reducer: Function\n        Reducing function.\n\n    thisArg: any (optional)\n        Execution context for the reducing function.\n\n    Returns\n    -------\n    out: any\n        Accumulated result.\n\n    Examples\n    --------\n    // array-like object:\n    > var f1 = naryFunction( base.abs, 1 );\n    > var f2 = naryFunction( base.add, 2 );\n    > var arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\n    > var out = mapReduce( arr, 0.0, f1, f2 )\n    21.0\n\n    // ndarray:\n    > arr = array( arr, { 'shape': [ 2, 3 ] } );\n    > out = mapReduce( arr, 0.0, f1, f2 )\n    21.0\n\n    See Also\n    --------\n    map, mapReduceRight, reduce\n","mapReduceRight":"\nmapReduceRight( arr, initial, mapper, reducer[, thisArg] )\n    Performs a map-reduce operation for each element in an array while iterating\n    from right to left and returns the accumulated result.\n\n    When invoked, the mapping function is provided three arguments:\n\n    - value: array element.\n    - index: element index.\n    - arr: input array.\n\n    When invoked, the reducing function is provided four arguments:\n\n    - accumulator: accumulated value.\n    - value: result after applying the mapping function to the current array\n      element.\n    - index: element index.\n    - arr: input array.\n\n    If provided an empty array, the function returns the initial value.\n\n    When provided an ndarray, the function performs a single-pass map-reduce\n    operation over the entire input ndarray (i.e., higher-order ndarray\n    dimensions are flattened to a single-dimension).\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject|ndarray\n        Input array.\n\n    initial: any\n        Accumulator value used in the first invocation of the reduction\n        function.\n\n    mapper: Function\n        Mapping function.\n\n    reducer: Function\n        Reducing function.\n\n    thisArg: any (optional)\n        Execution context for the reducing function.\n\n    Returns\n    -------\n    out: any\n        Accumulated result.\n\n    Examples\n    --------\n    // array-like object:\n    > var f1 = naryFunction( base.abs, 1 );\n    > var f2 = naryFunction( base.add, 2 );\n    > var arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\n    > var out = mapReduceRight( arr, 0.0, f1, f2 )\n    21.0\n\n    // ndarray:\n    > arr = array( arr, { 'shape': [ 2, 3 ] } );\n    > out = mapReduceRight( arr, 0.0, f1, f2 )\n    21.0\n\n    See Also\n    --------\n    mapRight, mapReduce, reduceRight\n","mapRight":"\nmapRight( arr, fcn[, thisArg] )\n    Applies a function to each element in an array and assigns the result to an\n    element in a new array, iterating from right to left.\n\n    The applied function is provided the following arguments:\n\n    - value: array element.\n    - index: element index.\n    - arr: input array.\n\n    The returned output array always has a \"generic\" data type. For example, if\n    provided an array-like object, the function returns a generic array. If\n    provided an ndarray, the function returns an ndarray having a \"generic\" data\n    type.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject|ndarray\n        Input array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.abs, 1 );\n    > var arr = [ -1, -2, -3, -4, -5, -6 ];\n    > var out = mapRight( arr, f )\n    [ 1, 2, 3, 4, 5, 6 ]\n\n    // ndarray:\n    > arr = array( arr, { 'shape': [ 2, 3 ] } );\n    > out = mapRight( arr, f );\n    > var v = out.get( 1, 1 )\n    5\n\n\nmapRight.assign( arr, out, fcn[, thisArg] )\n    Applies a function to each element in an array and assigns the result to an\n    element in an output array, iterating from right to left.\n\n    The applied function is provided the following arguments:\n\n    - value: array element.\n    - index: element index.\n    - arr: input array.\n\n    Input and output arrays must be either both array-like objects or both\n    ndarray-like objects.\n\n    If input and output arrays are array-like objects, the arrays must have the\n    same number of elements.\n\n    If input and output arrays are both ndarray-like objects, the arrays *must*\n    be broadcast compatible.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject|ndarray\n        Input array.\n\n    out: ArrayLikeObject|ndarray\n        Output array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.abs, 1 );\n    > var arr = [ -1, -2, -3, -4, -5, -6 ];\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > mapRight.assign( arr, out, f );\n    > out\n    [ 1, 2, 3, 4, 5, 6 ]\n\n    // ndarray:\n    > var opts = { 'shape': [ 2, 3 ] };\n    > arr = array( arr, opts );\n    > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n    > mapRight.assign( arr, out, f );\n    > var v = out.get( 1, 1 )\n    5\n\n    See Also\n    --------\n    map, reduce\n","mapRight.assign":"\nmapRight.assign( arr, out, fcn[, thisArg] )\n    Applies a function to each element in an array and assigns the result to an\n    element in an output array, iterating from right to left.\n\n    The applied function is provided the following arguments:\n\n    - value: array element.\n    - index: element index.\n    - arr: input array.\n\n    Input and output arrays must be either both array-like objects or both\n    ndarray-like objects.\n\n    If input and output arrays are array-like objects, the arrays must have the\n    same number of elements.\n\n    If input and output arrays are both ndarray-like objects, the arrays *must*\n    be broadcast compatible.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject|ndarray\n        Input array.\n\n    out: ArrayLikeObject|ndarray\n        Output array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.abs, 1 );\n    > var arr = [ -1, -2, -3, -4, -5, -6 ];\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > mapRight.assign( arr, out, f );\n    > out\n    [ 1, 2, 3, 4, 5, 6 ]\n\n    // ndarray:\n    > var opts = { 'shape': [ 2, 3 ] };\n    > arr = array( arr, opts );\n    > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n    > mapRight.assign( arr, out, f );\n    > var v = out.get( 1, 1 )\n    5\n\n    See Also\n    --------\n    map, reduce","mapValues":"\nmapValues( obj, transform )\n    Maps values from one object to a new object having the same keys.\n\n    The transform function is provided three arguments:\n\n    - value: object value corresponding to `key`.\n    - key: object key.\n    - obj: the input object.\n\n    The function only maps values from own properties. Hence, the function does\n    not map inherited properties.\n\n    The function shallow copies key values.\n\n    Key iteration order is *not* guaranteed.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    transform: Function\n        Transform function. Return values are the key values of the output\n        object.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > function transform( value, key ) { return key + value; };\n    > var obj = { 'a': 1, 'b': 2 };\n    > var out = mapValues( obj, transform )\n    { 'a': 'a1', 'b': 'b2' }\n\n    See Also\n    --------\n    mapKeys, omitBy, pickBy\n","mapValuesAsync":"\nmapValuesAsync( obj, [options,] transform, done )\n    Maps values from one object to a new object having the same keys.\n\n    When invoked, `transform` is provided a maximum of four arguments:\n\n    - value: object value corresponding to `key`.\n    - key: object key.\n    - obj: the input object.\n    - next: a callback to be invoked after processing an object `value`.\n\n    The actual number of provided arguments depends on function length. If\n    `transform` accepts two arguments, `transform` is provided:\n\n    - value\n    - next\n\n    If `transform` accepts three arguments, `transform` is provided:\n\n    - value\n    - key\n    - next\n\n    For every other `transform` signature, `transform` is provided all four\n    arguments.\n\n    The `next` callback accepts two arguments:\n\n    - error: error argument.\n    - value: transformed value.\n\n    If a `transform` function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function only maps values from own properties. Hence, the function does\n    not map inherited properties.\n\n    The function shallow copies key values.\n\n    Key iteration and insertion order are *not* guaranteed.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each property sequentially.\n        Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    transform: Function\n        Transform function. Return values are the key values of the output\n        object.\n\n    done: Function\n        A callback invoked either upon processing all own properties or upon\n        encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function transform( value, key, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         next( null, key+':'+value );\n    ...     }\n    ... };\n    > function done( error, out ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( out );\n    ... };\n    > var obj = { 'a': 1, 'b': 2 };\n    > mapValuesAsync( obj, transform, done )\n    { 'a': 'a:1', 'b': 'b:2' }\n\n    // Limit number of concurrent invocations:\n    > function transform( value, key, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         next( null, key+':'+value );\n    ...     }\n    ... };\n    > function done( error, out ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( out );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n    > mapValuesAsync( obj, opts, transform, done )\n    { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n\n    // Process sequentially:\n    > function transform( value, key, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         next( null, key+':'+value );\n    ...     }\n    ... };\n    > function done( error, out ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( out );\n    ... };\n    > var opts = { 'series': true };\n    > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n    > mapValuesAsync( obj, opts, transform, done )\n    { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n\n\nmapValuesAsync.factory( [options,] transform )\n    Returns a function which maps values from one object to a new object having\n    the same keys.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each property sequentially.\n        Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    transform: Function\n        Transform function. Return values are the key values of the output\n        object.\n\n    Returns\n    -------\n    out: Function\n        A function which maps values from one object to a new object having the\n        same keys.\n\n    Examples\n    --------\n    > function transform( value, key, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         next( null, key+':'+value );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = mapValuesAsync.factory( opts, transform );\n    > function done( error, out ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( out );\n    ... };\n    > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n    > f( obj, done )\n    { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n    > obj = { 'beep': 'boop' };\n    > f( obj, done )\n    { 'beep': 'beep:boop' }\n\n    See Also\n    --------\n    mapKeysAsync, mapValues\n","mapValuesAsync.factory":"\nmapValuesAsync.factory( [options,] transform )\n    Returns a function which maps values from one object to a new object having\n    the same keys.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each property sequentially.\n        Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    transform: Function\n        Transform function. Return values are the key values of the output\n        object.\n\n    Returns\n    -------\n    out: Function\n        A function which maps values from one object to a new object having the\n        same keys.\n\n    Examples\n    --------\n    > function transform( value, key, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         next( null, key+':'+value );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = mapValuesAsync.factory( opts, transform );\n    > function done( error, out ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( out );\n    ... };\n    > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n    > f( obj, done )\n    { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n    > obj = { 'beep': 'boop' };\n    > f( obj, done )\n    { 'beep': 'beep:boop' }\n\n    See Also\n    --------\n    mapKeysAsync, mapValues","maskArguments":"\nmaskArguments( fcn, mask[, thisArg] )\n    Returns a function that applies arguments to a provided function according\n    to a specified mask.\n\n    Only those arguments having a truthy mask value are applied to a provided\n    function.\n\n    Parameters\n    ----------\n    fcn: Function\n        Input function.\n\n    mask: ArrayLikeObject\n        Mask array.\n\n    thisArg: any (optional)\n        Function context.\n\n    Returns\n    -------\n    out: Function\n        Function wrapper.\n\n    Examples\n    --------\n    > function foo( a, b ) { return [ a, b ]; };\n    > var bar = maskArguments( foo, [ 1, 0, 1 ] );\n    > var out = bar( 1, 2, 3 )\n    [ 1, 3 ]\n\n    See Also\n    --------\n    filterArguments, rejectArguments, reorderArguments, reverseArguments\n","MAX_ARRAY_LENGTH":"\nMAX_ARRAY_LENGTH\n    Maximum length for a generic array.\n\n    Examples\n    --------\n    > MAX_ARRAY_LENGTH\n    4294967295\n\n    See Also\n    --------\n    MAX_TYPED_ARRAY_LENGTH\n","MAX_TYPED_ARRAY_LENGTH":"\nMAX_TYPED_ARRAY_LENGTH\n    Maximum length for a typed array.\n\n    Examples\n    --------\n    > MAX_TYPED_ARRAY_LENGTH\n    9007199254740991\n\n    See Also\n    --------\n    MAX_ARRAY_LENGTH\n","maybeBroadcastArray":"\nmaybeBroadcastArray( x, shape )\n    Broadcasts an ndarray to a specified shape if and only if the specified\n    shape differs from the provided ndarray's shape.\n\n    If a provided ndarray has the same shape as the specified shape, the\n    function returns the provided ndarray.\n\n    If a provided ndarray has a different (broadcast compatible) shape than the\n    specified shape, the function returns a new *read-only* ndarray view of the\n    provided ndarray's data. The view is typically *not* contiguous. As more\n    than one element of a returned view may refer to the same memory location,\n    writing to the input ndarray may affect multiple elements. If you need to\n    write to the input ndarray, copy the input ndarray before broadcasting.\n\n    The function throws an error if a provided ndarray is incompatible with a\n    provided shape.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    shape: ArrayLikeObject\n        Desired shape.\n\n    Returns\n    -------\n    out: ndarray\n        Broadcasted array.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n    <ndarray>\n    > var sh = x.shape\n    [ 2, 2 ]\n    > var y = maybeBroadcastArray( x, [ 3, 2, 2 ] )\n    <ndarray>\n    > sh = y.shape\n    [ 3, 2, 2 ]\n    > var v = y.get( 0, 0, 0 )\n    1\n    > v = y.get( 0, 0, 1 )\n    2\n    > v = y.get( 0, 1, 0 )\n    3\n    > v = y.get( 0, 1, 1 )\n    4\n    > v = y.get( 1, 0, 0 )\n    1\n    > v = y.get( 1, 1, 0 )\n    3\n    > v = y.get( 2, 0, 0 )\n    1\n    > v = y.get( 2, 1, 1 )\n    4\n\n    See Also\n    --------\n    array, ndarray, broadcastArray, maybeBroadcastArrays\n","maybeBroadcastArrays":"\nmaybeBroadcastArrays( ...arrays )\n    Broadcasts ndarrays to a common shape.\n\n    The function supports two (mutually exclusive) means of providing ndarray\n    arguments:\n\n    1. Providing a single array containing ndarray arguments.\n    2. Providing ndarray arguments as separate arguments.\n\n    If a provided ndarray has a shape matching the common shape, the function\n    returns the provided ndarray.\n\n    If a provided ndarray has a different (broadcast compatible) shape than the\n    common shape, the function returns a new *read-only* ndarray view of the\n    provided ndarray's data. The view is typically *not* contiguous. As more\n    than one element of a returned view may refer to the same memory location,\n    writing to a view may affect multiple elements. If you need to write to an\n    input ndarray, copy the input ndarray before broadcasting.\n\n    The function throws an error if a provided broadcast-incompatible ndarrays.\n\n    Parameters\n    ----------\n    arrays: ...ndarray|ArrayLikeObject<ndarray>\n        Array arguments.\n\n    Returns\n    -------\n    out: Array<ndarray>\n        Broadcasted arrays.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n    <ndarray>\n    > var sh = x.shape\n    [ 2, 2 ]\n    > var y = ndzeros( [ 3, 2, 2 ] )\n    <ndarray>\n    > var out = maybeBroadcastArrays( [ x, y ] )\n    [ <ndarray>, <ndarray> ]\n\n    // Retrieve the broadcasted \"x\" array:\n    > var bx = out[ 0 ]\n    <ndarray>\n    > sh = bx.shape\n    [ 3, 2, 2 ]\n\n    // Retrieve broadcasted elements...\n    > var v = bx.get( 0, 0, 0 )\n    1\n    > v = bx.get( 0, 0, 1 )\n    2\n    > v = bx.get( 0, 1, 0 )\n    3\n    > v = bx.get( 0, 1, 1 )\n    4\n    > v = bx.get( 1, 0, 0 )\n    1\n    > v = bx.get( 1, 1, 0 )\n    3\n    > v = bx.get( 2, 0, 0 )\n    1\n    > v = bx.get( 2, 1, 1 )\n    4\n\n    See Also\n    --------\n    array, ndarray, broadcastArrays, maybeBroadcastArray\n","memoize":"\nmemoize( fcn[, hashFunction] )\n    Returns a memoized function.\n\n    The function does not set the `length` property of the returned function.\n    Accordingly, the returned function `length` is always zero.\n\n    The evaluation context is always `null`.\n\n    The function serializes provided arguments as a string and stores results\n    using the string as an identifier. To use a custom hash function, provide a\n    hash function argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to memoize.\n\n    hashFunction: Function (optional)\n        Function to map a set of arguments to a single value identifying that\n        set.\n\n    Returns\n    -------\n    out: Function\n        Memoized function.\n\n    Examples\n    --------\n    > function factorial( n ) {\n    ...     var prod;\n    ...     var i;\n    ...     prod = 1;\n    ...     for ( i = n; i > 1; i-- ) {\n    ...         prod *= i;\n    ...     }\n    ...     return prod;\n    ... };\n    > var memoized = memoize( factorial );\n    > var v = memoized( 5 )\n    120\n    > v = memoized( 5 )\n    120\n\n","merge":"\nmerge( target, ...source )\n    Merges objects into a target object.\n\n    The target object is mutated.\n\n    Only plain objects are merged and extended. Other values/types are either\n    deep copied or assigned.\n\n    Support for deep merging class instances is inherently fragile.\n\n    `Number`, `String`, and `Boolean` objects are merged as primitives.\n\n    Functions are not deep copied.\n\n    Parameters\n    ----------\n    target: Object\n        Target object.\n\n    source: ...Object\n        Source objects (i.e., objects to be merged into the target object).\n\n    Returns\n    -------\n    out: Object\n        Merged (target) object.\n\n    Examples\n    --------\n    > var target = { 'a': 'beep' };\n    > var source = { 'a': 'boop', 'b': 'bap' };\n    > var out = merge( target, source )\n    { 'a': 'boop', 'b': 'bap' }\n    > var bool = ( out === target )\n    true\n\n\nmerge.factory( options )\n    Returns a function for merging and extending objects.\n\n    Parameters\n    ----------\n    options: Object\n        Options.\n\n    options.level: integer (optional)\n        Merge level. Default: Infinity.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to deep copy merged values. Deep copying\n        prevents shared references and source object mutation. Default: true.\n\n    options.override: boolean|Function (optional)\n        Defines the merge strategy. If `true`, source object values will always\n        override target object values. If `false`, source values never override\n        target values (useful for adding, but not overwriting, properties). To\n        define a custom merge strategy, provide a function. Default: true.\n\n    options.extend: boolean (optional)\n        Boolean indicating whether new properties can be added to the target\n        object. If `false`, only shared properties are merged. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function which can be used to merge objects.\n\n    Examples\n    --------\n    > var opts = {\n    ...     'level': 100,\n    ...     'copy': true,\n    ...     'override': true,\n    ...     'extend': true\n    ... };\n    > var merge = merge.factory( opts )\n    <Function>\n\n    // Set the `level` option to limit the merge depth:\n    > merge = merge.factory( { 'level': 2 } );\n    > var target = {\n    ...     '1': { 'a': 'beep', '2': { '3': null, 'b': [ 5, 6, 7 ] } }\n    ... };\n    > var source = {\n    ...     '1': { 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } }\n    ... };\n    > var out = merge( target, source )\n    { '1': { 'a': 'beep', 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } } }\n\n    // Set the `copy` option to `false` to allow shared references:\n    > merge = merge.factory( { 'copy': false } );\n    > target = {};\n    > source = { 'a': [ 1, 2, 3 ] };\n    > out = merge( target, source );\n    > var bool = ( out.a === source.a )\n    true\n\n    // Set the `override` option to `false` to preserve existing properties:\n    > merge = merge.factory( { 'override': false } );\n    > target = { 'a': 'beep', 'b': 'boop' };\n    > source = { 'a': null, 'c': 'bop' };\n    > out = merge( target, source )\n    { 'a': 'beep', 'b': 'boop', 'c': 'bop' }\n\n    // Define a custom merge strategy:\n    > function strategy( a, b, key ) {\n    ...     // a => target value\n    ...     // b => source value\n    ...     // key => object key\n    ...     if ( key === 'a' ) {\n    ...         return b;\n    ...     }\n    ...     if ( key === 'b' ) {\n    ...         return a;\n    ...     }\n    ...     return 'bebop';\n    ... };\n    > merge = merge.factory( { 'override': strategy } );\n    > target = { 'a': 'beep', 'b': 'boop', 'c': 1234 };\n    > source = { 'a': null, 'b': {}, 'c': 'bop' };\n    > out = merge( target, source )\n    { 'a': null, 'b': 'boop', 'c': 'bebop' }\n\n    // Prevent non-existent properties from being added to the target object:\n    > merge = merge.factory( { 'extend': false } );\n    > target = { 'a': 'beep', 'b': 'boop' };\n    > source = { 'b': 'hello', 'c': 'world' };\n    > out = merge( target, source )\n    { 'a': 'beep', 'b': 'hello' }\n\n    See Also\n    --------\n    copy\n","merge.factory":"\nmerge.factory( options )\n    Returns a function for merging and extending objects.\n\n    Parameters\n    ----------\n    options: Object\n        Options.\n\n    options.level: integer (optional)\n        Merge level. Default: Infinity.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to deep copy merged values. Deep copying\n        prevents shared references and source object mutation. Default: true.\n\n    options.override: boolean|Function (optional)\n        Defines the merge strategy. If `true`, source object values will always\n        override target object values. If `false`, source values never override\n        target values (useful for adding, but not overwriting, properties). To\n        define a custom merge strategy, provide a function. Default: true.\n\n    options.extend: boolean (optional)\n        Boolean indicating whether new properties can be added to the target\n        object. If `false`, only shared properties are merged. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function which can be used to merge objects.\n\n    Examples\n    --------\n    > var opts = {\n    ...     'level': 100,\n    ...     'copy': true,\n    ...     'override': true,\n    ...     'extend': true\n    ... };\n    > var merge = merge.factory( opts )\n    <Function>\n\n    // Set the `level` option to limit the merge depth:\n    > merge = merge.factory( { 'level': 2 } );\n    > var target = {\n    ...     '1': { 'a': 'beep', '2': { '3': null, 'b': [ 5, 6, 7 ] } }\n    ... };\n    > var source = {\n    ...     '1': { 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } }\n    ... };\n    > var out = merge( target, source )\n    { '1': { 'a': 'beep', 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } } }\n\n    // Set the `copy` option to `false` to allow shared references:\n    > merge = merge.factory( { 'copy': false } );\n    > target = {};\n    > source = { 'a': [ 1, 2, 3 ] };\n    > out = merge( target, source );\n    > var bool = ( out.a === source.a )\n    true\n\n    // Set the `override` option to `false` to preserve existing properties:\n    > merge = merge.factory( { 'override': false } );\n    > target = { 'a': 'beep', 'b': 'boop' };\n    > source = { 'a': null, 'c': 'bop' };\n    > out = merge( target, source )\n    { 'a': 'beep', 'b': 'boop', 'c': 'bop' }\n\n    // Define a custom merge strategy:\n    > function strategy( a, b, key ) {\n    ...     // a => target value\n    ...     // b => source value\n    ...     // key => object key\n    ...     if ( key === 'a' ) {\n    ...         return b;\n    ...     }\n    ...     if ( key === 'b' ) {\n    ...         return a;\n    ...     }\n    ...     return 'bebop';\n    ... };\n    > merge = merge.factory( { 'override': strategy } );\n    > target = { 'a': 'beep', 'b': 'boop', 'c': 1234 };\n    > source = { 'a': null, 'b': {}, 'c': 'bop' };\n    > out = merge( target, source )\n    { 'a': null, 'b': 'boop', 'c': 'bebop' }\n\n    // Prevent non-existent properties from being added to the target object:\n    > merge = merge.factory( { 'extend': false } );\n    > target = { 'a': 'beep', 'b': 'boop' };\n    > source = { 'b': 'hello', 'c': 'world' };\n    > out = merge( target, source )\n    { 'a': 'beep', 'b': 'hello' }\n\n    See Also\n    --------\n    copy","MILLISECONDS_IN_DAY":"\nMILLISECONDS_IN_DAY\n    Number of milliseconds in a day.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var days = 3.14;\n    > var ms = days * MILLISECONDS_IN_DAY\n    271296000\n\n","MILLISECONDS_IN_HOUR":"\nMILLISECONDS_IN_HOUR\n    Number of milliseconds in an hour.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var hrs = 3.14;\n    > var ms = hrs * MILLISECONDS_IN_HOUR\n    11304000\n\n","MILLISECONDS_IN_MINUTE":"\nMILLISECONDS_IN_MINUTE\n    Number of milliseconds in a minute.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies arising due to complications with time and dates.\n\n    Examples\n    --------\n    > var mins = 3.14;\n    > var ms = mins * MILLISECONDS_IN_MINUTE\n    188400\n\n","MILLISECONDS_IN_SECOND":"\nMILLISECONDS_IN_SECOND\n    Number of milliseconds in a second.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies arising due to complications with time and dates.\n\n    Examples\n    --------\n    > var secs = 3.14;\n    > var ms = secs * MILLISECONDS_IN_SECOND\n    3140\n\n","MILLISECONDS_IN_WEEK":"\nMILLISECONDS_IN_WEEK\n    Number of milliseconds in a week.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var weeks = 3.14;\n    > var ms = weeks * MILLISECONDS_IN_WEEK\n    1899072000\n\n","MINARD_NAPOLEONS_MARCH":"\nMINARD_NAPOLEONS_MARCH( [options] )\n    Returns data for Charles Joseph Minard's cartographic depiction of\n    Napoleon's Russian campaign of 1812.\n\n    Data includes the following:\n\n    - army: army size.\n    - cities: cities.\n    - labels: map labels.\n    - temperature: temperature during the army's return from Russia.\n    - rivers: river data.\n\n    Temperatures are on the Réaumur scale. Multiply each temperature by `1.25`\n    to convert to Celsius.\n\n    River data is formatted as GeoJSON.\n\n    River data is incomplete, with portions of rivers missing.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.data: string (optional)\n        Dataset name.\n\n    Returns\n    -------\n    out: Object|Array<Object>\n        Minard's data.\n\n    Examples\n    --------\n    > var data = MINARD_NAPOLEONS_MARCH();\n    > var army = data.army\n    [...]\n    > var cities = data.cities\n    [...]\n    > var labels = data.labels\n    [...]\n    > var river = data.river\n    {...}\n    > var t = data.temperature\n    [...]\n\n    References\n    ----------\n    - Minard, Charles Joseph. 1869. *Tableaux graphiques et cartes figuratives*.\n    Ecole nationale des ponts et chaussées.\n    - Wilkinson, Leland. 2005. *The Grammar of Graphics*. Springer-Verlag New\n    York. doi:10.1007/0-387-28695-0.\n\n","MINUTES_IN_DAY":"\nMINUTES_IN_DAY\n    Number of minutes in a day.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var days = 3.14;\n    > var mins = days * MINUTES_IN_DAY\n    4521.6\n\n","MINUTES_IN_HOUR":"\nMINUTES_IN_HOUR\n    Number of minutes in an hour.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var hrs = 3.14;\n    > var mins = hrs * MINUTES_IN_HOUR\n    188.4\n\n","MINUTES_IN_WEEK":"\nMINUTES_IN_WEEK\n    Number of minutes in a week.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var wks = 3.14;\n    > var mins = wks * MINUTES_IN_WEEK\n    31651.2\n\n","minutesInMonth":"\nminutesInMonth( [month[, year]] )\n    Returns the number of minutes in a month.\n\n    By default, the function returns the number of minutes in the current month\n    of the current year (according to local time). To determine the number of\n    minutes for a particular month and year, provide `month` and `year`\n    arguments.\n\n    A `month` may be either a month's integer value, three letter abbreviation,\n    or full name (case insensitive).\n\n    The function's return value is a generalization and does **not** take into\n    account inaccuracies due to daylight savings conventions, crossing\n    timezones, or other complications with time and dates.\n\n    Parameters\n    ----------\n    month: string|Date|integer (optional)\n        Month.\n\n    year: integer (optional)\n        Year.\n\n    Returns\n    -------\n    out: integer\n        Minutes in a month.\n\n    Examples\n    --------\n    > var num = minutesInMonth()\n    <number>\n    > num = minutesInMonth( 2 )\n    <number>\n    > num = minutesInMonth( 2, 2016 )\n    41760\n    > num = minutesInMonth( 2, 2017 )\n    40320\n\n    // Other ways to supply month:\n    > num = minutesInMonth( 'feb', 2016 )\n    41760\n    > num = minutesInMonth( 'february', 2016 )\n    41760\n\n    See Also\n    --------\n    minutesInYear\n","minutesInYear":"\nminutesInYear( [value] )\n    Returns the number of minutes in a year according to the Gregorian calendar.\n\n    By default, the function returns the number of minutes in the current year\n    (according to local time). To determine the number of minutes for a\n    particular year, provide either a year or a `Date` object.\n\n    The function's return value is a generalization and does **not** take into\n    account inaccuracies due to daylight savings conventions, crossing\n    timezones, or other complications with time and dates.\n\n    Parameters\n    ----------\n    value: integer|Date (optional)\n        Year or `Date` object.\n\n    Returns\n    -------\n    out: integer\n        Number of minutes in a year.\n\n    Examples\n    --------\n    > var num = minutesInYear()\n    <number>\n    > num = minutesInYear( 2016 )\n    527040\n    > num = minutesInYear( 2017 )\n    525600\n\n    See Also\n    --------\n    minutesInMonth\n","MOBY_DICK":"\nMOBY_DICK()\n    Returns the text of Moby Dick by Herman Melville.\n\n    Each array element has the following fields:\n\n    - chapter: book chapter (number or identifier).\n    - title: chapter title (if available; otherwise, empty).\n    - text: chapter text.\n\n    Returns\n    -------\n    out: Array<Object>\n        Book text.\n\n    Examples\n    --------\n    > var data = MOBY_DICK()\n    [ {...}, {...}, ... ]\n\n","MONTH_NAMES_EN":"\nMONTH_NAMES_EN()\n    Returns a list of month names (English).\n\n    Returns\n    -------\n    out: Array<string>\n        List of month names.\n\n    Examples\n    --------\n    > var list = MONTH_NAMES_EN()\n    [ 'January', 'February', 'March', 'April', ... ]\n\n","MONTHS_IN_YEAR":"\nMONTHS_IN_YEAR\n    Number of months in a year.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var yrs = 3.14;\n    > var mons = yrs * MONTHS_IN_YEAR\n    37.68\n\n","moveProperty":"\nmoveProperty( source, prop, target )\n    Moves a property from one object to another object.\n\n    The property is deleted from the source object and the property's descriptor\n    is preserved during transfer.\n\n    If a source property is not configurable, the function throws an error, as\n    the property cannot be deleted from the source object.\n\n    Parameters\n    ----------\n    source: Object\n        Source object.\n\n    prop: string\n        Property to move.\n\n    target: Object\n        Target object.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether operation was successful.\n\n    Examples\n    --------\n    > var obj1 = { 'a': 'b' };\n    > var obj2 = {};\n    > var bool = moveProperty( obj1, 'a', obj2 )\n    true\n    > bool = moveProperty( obj1, 'c', obj2 )\n    false\n\n","MultiSlice":"\nMultiSlice( ...slice )\n    Returns a multi-slice.\n\n    Parameters\n    ----------\n    ...slice: Slice|integer|null|undefined\n        Slice arguments.\n\n    Returns\n    -------\n    s: MultiSlice\n        MultiSlice instance.\n\n    Examples\n    --------\n    > var s = new Slice( 2, 10 );\n    > var ms = new MultiSlice( 2, s, 1 );\n\n\nMultiSlice.prototype.ndims\n    Read-only property returning the number of slice dimensions.\n\n    Returns\n    -------\n    ndims: integer\n        Number of slice dimensions.\n\n    Examples\n    --------\n    > var s = new Slice( 2, 10 );\n    > var ms = new MultiSlice( 2, s, 1 );\n    > ms.ndims\n    3\n\n\nMultiSlice.prototype.data\n    Read-only property returning the slice data.\n\n    Returns\n    -------\n    data: Array<Slice|integer|null>\n        Slice data.\n\n    Examples\n    --------\n    > var s = new Slice( 2, 10 );\n    > var ms = new MultiSlice( 2, s, 1 );\n    > ms.data\n    [ 2, <Slice>, 1 ]\n\n\nMultiSlice.prototype.toString()\n    Serializes a multi-slice as a string.\n\n    Returns\n    -------\n    str: string\n        Serialized multi-slice string.\n\n    Examples\n    --------\n    > var s = new Slice( 2, 10 );\n    > var ms = new MultiSlice( 2, s, 1 );\n    > ms.toString()\n    'MultiSlice(2,Slice(2,10,null),1)'\n\n\nMultiSlice.prototype.toJSON()\n    Serializes a multi-slice as a JSON object.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var s = new Slice( 2, 10, 1 );\n    > var ms = new MultiSlice( 2, s );\n    > ms.toJSON()\n    {'type':'MultiSlice','data':[2,{'type':'Slice','data':[2,10,1]}]}\n\n    See Also\n    --------\n    ndarray, Slice\n","MultiSlice.prototype.ndims":"\nMultiSlice.prototype.ndims\n    Read-only property returning the number of slice dimensions.\n\n    Returns\n    -------\n    ndims: integer\n        Number of slice dimensions.\n\n    Examples\n    --------\n    > var s = new Slice( 2, 10 );\n    > var ms = new MultiSlice( 2, s, 1 );\n    > ms.ndims\n    3","MultiSlice.prototype.data":"\nMultiSlice.prototype.data\n    Read-only property returning the slice data.\n\n    Returns\n    -------\n    data: Array<Slice|integer|null>\n        Slice data.\n\n    Examples\n    --------\n    > var s = new Slice( 2, 10 );\n    > var ms = new MultiSlice( 2, s, 1 );\n    > ms.data\n    [ 2, <Slice>, 1 ]","MultiSlice.prototype.toString":"\nMultiSlice.prototype.toString()\n    Serializes a multi-slice as a string.\n\n    Returns\n    -------\n    str: string\n        Serialized multi-slice string.\n\n    Examples\n    --------\n    > var s = new Slice( 2, 10 );\n    > var ms = new MultiSlice( 2, s, 1 );\n    > ms.toString()\n    'MultiSlice(2,Slice(2,10,null),1)'","MultiSlice.prototype.toJSON":"\nMultiSlice.prototype.toJSON()\n    Serializes a multi-slice as a JSON object.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var s = new Slice( 2, 10, 1 );\n    > var ms = new MultiSlice( 2, s );\n    > ms.toJSON()\n    {'type':'MultiSlice','data':[2,{'type':'Slice','data':[2,10,1]}]}\n\n    See Also\n    --------\n    ndarray, Slice","namedtypedtuple":"\nnamedtypedtuple( fields[, options] )\n    Returns a named typed tuple factory.\n\n    Named tuples assign a property name, and thus a meaning, to each position in\n    a tuple and allow for more readable, self-documenting code.\n\n    Named typed tuples can be used wherever typed arrays are used, with the\n    added benefit that they allow accessing fields by both field name and\n    position index.\n\n    Named typed tuples may be one the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754).\n    - float32: single-precision floating-point numbers (IEEE 754).\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n\n    Parameters\n    ----------\n    fields: Array<string>\n        Field (property) names.\n\n    options: Object (optional)\n        Function options.\n\n    options.dtype: string (optional)\n        Default tuple data type. If a data type is not provided to a named typed\n        tuple factory, this option specifies the underlying tuple data type.\n        Default: 'float64'.\n\n    options.name: string (optional)\n        Tuple name. Default: 'tuple'.\n\n    Returns\n    -------\n    factory: Function\n        Named typed tuple factory.\n\n    Examples\n    --------\n    > var opts = {};\n    > opts.name = 'Point';\n    > var factory = namedtypedtuple( [ 'x', 'y' ], opts );\n    > var tuple = factory();\n\n\nfactory()\n    Returns a named typed tuple of the default data type.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > p = factory();\n    > p.x\n    0.0\n    > p.y\n    0.0\n    > p[ 0 ]\n    0.0\n    > p[ 1 ]\n    0.0\n\n\nfactory( dtype )\n    Returns a named typed tuple of the specified data type.\n\n    Parameters\n    ----------\n    dtype: string\n        Tuple data type.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > p = factory( 'int32' );\n    > p.x\n    0\n    > p.y\n    0\n    > p[ 0 ]\n    0\n    > p[ 1 ]\n    0\n\n\nfactory( typedarray[, dtype] )\n    Creates a named typed tuple from a typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate a named typed tuple.\n\n    dtype: string (optional)\n        Tuple data type.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > p = factory( Float64Array[ 1.0, -1.0 ] );\n    > p.x\n    1.0\n    > p.y\n    -1.0\n    > p[ 0 ]\n    1.0\n    > p[ 1 ]\n    -1.0\n\n\nfactory( obj[, dtype] )\n    Creates a named typed tuple from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a named typed\n        tuple.\n\n    dtype: string (optional)\n        Tuple data type.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > p = factory( [ 1, -1 ], 'int32' );\n    > p.x\n    1\n    > p.y\n    -1\n    > p[ 0 ]\n    1\n    > p[ 1 ]\n    -1\n\n\nfactory( buffer[, byteOffset][, dtype] )\n    Returns a named typed tuple view of an ArrayBuffer.\n\n    The view length equals the number of tuple fields.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first tuple element.\n        Default: 0.\n\n    dtype: string (optional)\n        Tuple data type.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var buf = new ArrayBuffer( 16 );\n    > var p = factory( buf, 4, 'float32' );\n    > p.x\n    0.0\n    > p.y\n    0.0\n    > p[ 0 ]\n    0.0\n    > p[ 1 ]\n    0.0\n\n\nfactory.from( src[, map[, thisArg]] )\n    Creates a new named typed tuple from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n    - field: tuple field.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of tuple elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > function mapFcn( v ) { return v * 2.0; };\n    > var p = factory.from( [ 1.0, -1.0 ], mapFcn );\n    > p.x\n    2.0\n    > p.y\n    -2.0\n    > p[ 0 ]\n    2.0\n    > p[ 1 ]\n    -2.0\n\n\nfactory.fromObject( obj[, map[, thisArg]] )\n    Creates a new named typed tuple from an object containing tuple fields.\n\n    A callback is provided the following arguments:\n\n    - value: source object tuple field value.\n    - field: source object tuple field name.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    map: Function (optional)\n        Callback to invoke for each source object tuple field.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory.fromObject( { 'x': 2.0, 'y': -2.0 } );\n    > p.x\n    2.0\n    > p.y\n    -2.0\n    > p[ 0 ]\n    2.0\n    > p[ 1 ]\n    -2.0\n\n\nfactory.of( element0[, element1[, ...elementN]] )\n    Creates a new named typed tuple from a variable number of arguments.\n\n    The number of arguments *must* equal the number of tuple fields.\n\n    Parameters\n    ----------\n    element0: number\n        Tuple element.\n\n    element1: number (optional)\n        Tuple element.\n\n    elementN: number (optional)\n        Tuple elements.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory.of( 2.0, -2.0 );\n    > p.x\n    2.0\n    > p.y\n    -2.0\n    > p[ 0 ]\n    2.0\n    > p[ 1 ]\n    -2.0\n\n\ntuple.BYTES_PER_ELEMENT\n    Size (in bytes) of each tuple element.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > p.BYTES_PER_ELEMENT\n    8\n\n\ntuple.buffer\n    Pointer to the underlying data buffer.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > p.buffer\n    <ArrayBuffer>\n\n\ntuple.byteLength\n    Length (in bytes) of the tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > p.byteLength\n    16\n\n\ntuple.byteOffset\n    Offset (in bytes) of a tuple from the start of its underlying ArrayBuffer.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > p.byteOffset\n    0\n\n\ntuple.length\n    Tuple length (i.e., number of elements).\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > p.length\n    2\n\n\ntuple.name\n    Tuple name.\n\n    Examples\n    --------\n    > var opts = { 'name': 'Point' };\n    > var factory = namedtypedtuple( [ 'x', 'y' ], opts );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > p.name\n    'Point'\n\n\ntuple.fields\n    Returns the list of tuple fields.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > p.fields\n    [ 'x', 'y' ]\n\n\ntuple.orderedFields\n    Returns the list of tuple fields in index order.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > p[ 0 ]\n    1.0\n    > p.sort();\n    > p[ 0 ]\n    -1.0\n    > p.fields\n    [ 'x', 'y' ]\n    > p.orderedFields\n    [ 'y', 'x' ]\n\n\ntuple.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the tuple starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: tuple.length.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Modified tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n    > var p = factory( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n    > p.copyWithin( 3, 0, 2 );\n    > p.w\n    2.0\n    > p.v\n    -2.0\n\n\ntuple.entries()\n    Returns an iterator for iterating over tuple key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over tuple key-value pairs.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > it = p.entries();\n    > it.next().value\n    [ 0, 'x', 1.0 ]\n    > it.next().value\n    [ 1, 'y', -1.0 ]\n    > it.next().done\n    true\n\n\ntuple.every( predicate[, thisArg] )\n    Tests whether all tuple elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: tuple element.\n    - index: tuple index.\n    - field: tuple field name.\n    - tuple: tuple on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests tuple elements. If a predicate function\n        returns a truthy value, a tuple element passes; otherwise, a tuple\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all tuple elements pass.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > function predicate( v ) { return ( v >= 0.0 ); };\n    > p.every( predicate )\n    false\n\n\ntuple.fieldOf( searchElement[, fromIndex] )\n    Returns the field of the first tuple element strictly equal to a search\n    element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `undefined`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Tuple index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last tuple element.\n        Default: 0.\n\n    Returns\n    -------\n    field: string|undefined\n        Tuple field.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > var f = p.fieldOf( 2.0 )\n    undefined\n    > f = p.fieldOf( -1.0 )\n    'z'\n\n\ntuple.fill( value[, start[, end]] )\n    Fills a tuple from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last tuple element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last tuple element. Default: tuple.length.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Modified tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > p.fill( 2.0 );\n    > p.x\n    2.0\n    > p.y\n    2.0\n\n\ntuple.filter( predicate[, thisArg] )\n    Creates a new tuple which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: tuple element.\n    - index: tuple index.\n    - field: tuple field name.\n    - tuple: tuple on which the method is invoked.\n\n    The returned tuple has the same data type as the host tuple.\n\n    If a predicate function does not return a truthy value for any tuple\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters tuple elements. If a predicate function\n        returns a truthy value, a tuple element is included in the output tuple;\n        otherwise, a tuple element is not included in the output tuple.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    tuple: TypedArray\n        A new named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v >= 0.0 ); };\n    > var p2 = p1.filter( predicate );\n    > p2.fields\n    [ 'x', 'y' ]\n\n\ntuple.find( predicate[, thisArg] )\n    Returns the first tuple element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: tuple element.\n    - index: tuple index.\n    - field: tuple field name.\n    - tuple: tuple on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests tuple elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Tuple element.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > var v = p.find( predicate )\n    -1.0\n\n\ntuple.findField( predicate[, thisArg] )\n    Returns the field of the first tuple element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: tuple element.\n    - index: tuple index.\n    - field: tuple field name.\n    - tuple: tuple on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests tuple elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    field: string|undefined\n        Tuple field.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > var f = p.findField( predicate )\n    'z'\n\n\ntuple.findIndex( predicate[, thisArg] )\n    Returns the index of the first tuple element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: tuple element.\n    - index: tuple index.\n    - field: tuple field name.\n    - tuple: tuple on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests tuple elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Tuple index.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > var idx = p.findIndex( predicate )\n    2\n\n\ntuple.forEach( fcn[, thisArg] )\n    Invokes a callback for each tuple element.\n\n    A provided function is provided the following arguments:\n\n    - value: tuple element.\n    - index: tuple index.\n    - field: tuple field name.\n    - tuple: tuple on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each tuple element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1, 0, -1 ], 'int32' );\n    > var str = ' ';\n    > function fcn( v, i, f ) { str += f + '=' + v + ' '; };\n    > p.forEach( fcn );\n    > str\n    ' x=1 y=0 z=-1 '\n\n\ntuple.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether a tuple includes a search element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Tuple index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last tuple element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a tuple includes a search element.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > var bool = p.includes( 2.0 )\n    false\n    > bool = p.includes( -1.0 )\n    true\n\n\ntuple.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first tuple element strictly equal to a search\n    element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Tuple index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last tuple element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Tuple index.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > var idx = p.indexOf( 2.0 )\n    -1\n    > idx = p.indexOf( -1.0 )\n    2\n\n\ntuple.ind2key( ind )\n    Converts a tuple index to a field name.\n\n    If provided an out-of-bounds index, the method returns `undefined`.\n\n    Parameters\n    ----------\n    ind: integer\n        Tuple index. If less than zero, the method resolves the index relative\n        to the last tuple element.\n\n    Returns\n    -------\n    field: string|undefined\n        Field name.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > p.ind2key( 1 )\n    'y'\n    > p.ind2key( 100 )\n    undefined\n\n\ntuple.join( [separator] )\n    Serializes a tuple by joining all tuple elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating tuple elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Tuple serialized as a string.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1, 0, -1 ], 'int32' );\n    > p.join( '|' )\n    '1|0|-1'\n\n\ntuple.keys()\n    Returns an iterator for iterating over tuple keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over tuple keys.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > it = p.keys();\n    > it.next().value\n    [ 0, 'x' ]\n    > it.next().value\n    [ 1, 'y' ]\n    > it.next().done\n    true\n\n\ntuple.key2ind( field )\n    Converts a field name to a tuple index.\n\n    If provided an unknown field name, the method returns `-1`.\n\n    Parameters\n    ----------\n    field: string\n        Tuple field name.\n\n    Returns\n    -------\n    idx: integer\n        Tuple index.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > p.key2ind( 'y' )\n    1\n\n\ntuple.lastFieldOf( searchElement[, fromIndex] )\n    Returns the field of the last tuple element strictly equal to a search\n    element.\n\n    The method iterates from the last tuple element to the first tuple element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `undefined`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Tuple index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last tuple element.\n        Default: -1.\n\n    Returns\n    -------\n    field: string|undefined\n        Tuple field.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n    > var f = p.lastFieldOf( 2.0 )\n    undefined\n    > f = p.lastFieldOf( 0.0 )\n    'w'\n\n\ntuple.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last tuple element strictly equal to a search\n    element.\n\n    The method iterates from the last tuple element to the first tuple element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Tuple index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last tuple element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Tuple index.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n    > var idx = p.lastIndexOf( 2.0 )\n    -1\n    > idx = p.lastIndexOf( 0.0 )\n    3\n\n\ntuple.map( fcn[, thisArg] )\n    Maps each tuple element to an element in a new tuple.\n\n    A provided function is provided the following arguments:\n\n    - value: tuple element.\n    - index: tuple index.\n    - field: tuple field name.\n    - tuple: tuple on which the method is invoked.\n\n    The returned tuple has the same data type as the host tuple.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps tuple elements to elements in the new tuple.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    tuple: TypedArray\n        A new named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( v ) { return v * 2.0; };\n    > var p2 = p1.map( fcn );\n    > p2.x\n    2.0\n    > p2.y\n    0.0\n    > p2.z\n    -2.0\n\n\ntuple.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in a tuple and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current tuple element.\n    - index: index of the current tuple element.\n    - field: field name corresponding to the current tuple element.\n    - tuple: tuple on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first tuple element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first tuple element as the first argument and the second tuple\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = p.reduce( fcn, 0.0 )\n    2.0\n\n\ntuple.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in a tuple and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current tuple element.\n    - index: index of the current tuple element.\n    - field: field name corresponding to the current tuple element.\n    - tuple: tuple on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last tuple element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last tuple element as the first argument and the second-to-last\n    tuple element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = p.reduceRight( fcn, 0.0 )\n    2.0\n\n\ntuple.reverse()\n    Reverses a tuple *in-place*.\n\n    This method mutates the tuple on which the method is invoked.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Modified tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > p[ 0 ]\n    1.0\n    > p.x\n    1.0\n    > p.reverse();\n    > p[ 0 ]\n    -1.0\n    > p.x\n    1.0\n\n\ntuple.set( arr[, offset] )\n    Sets tuple elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing tuple values to set.\n\n    offset: integer (optional)\n        Tuple index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > p[ 1 ]\n    0.0\n    > p.y\n    0.0\n    > p.set( [ -2.0, 2.0 ], 1 );\n    > p[ 1 ]\n    -2.0\n    > p.y\n    -2.0\n    > p[ 2 ]\n    2.0\n    > p.z\n    2.0\n\n\ntuple.slice( [begin[, end]] )\n    Copies tuple elements to a new tuple with the same underlying data type as\n    the host tuple.\n\n    If the method is unable to resolve indices to a non-empty tuple subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last tuple element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last tuple element. Default: tuple.length.\n\n    Returns\n    -------\n    tuple: TypedArray\n        A new named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n    > p1.fields\n    [ 'x', 'y', 'z' ]\n    > var p2 = p1.slice( 1 );\n    > p2.fields\n    [ 'y', 'z' ]\n    > p2.y\n    0.0\n    > p2.z\n    -1.0\n\n\ntuple.some( predicate[, thisArg] )\n    Tests whether at least one tuple element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: tuple element.\n    - index: tuple index.\n    - field: tuple field name.\n    - tuple: tuple on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests tuple elements. If a predicate function\n        returns a truthy value, a tuple element passes; otherwise, a tuple\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one tuple element passes.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > p.some( predicate )\n    true\n\n\ntuple.sort( [compareFunction] )\n    Sorts a tuple *in-place*.\n\n    Sorting a tuple does *not* affect field assignments. Accessing a tuple field\n    before and after sorting will always return the same tuple element. However,\n    this behavior is generally not true when accessing tuple elements according\n    to tuple index. In summary, sorting affects index order but not field\n    assignments.\n\n    The comparison function is provided two tuple elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the tuple on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Modified tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n    > var p = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n    > p.sort();\n    > p.orderedFields\n    [ 'v', 'y', 'z', 'x', 'w' ]\n    > p[ 0 ]\n    -2.0\n    > p.x\n    1.0\n    > p[ 1 ]\n    -1.0\n    > p.y\n    -1.0\n    > p.key2ind( 'x' )\n    3\n\n\ntuple.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host tuple.\n\n    If the method is unable to resolve indices to a non-empty tuple subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last tuple element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last tuple element. Default: tuple.length.\n\n    Returns\n    -------\n    arr: TypedArray\n        A new typed array view.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n    > var p = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n    > var arr = p.subarray( 2 )\n    <Float64Array>[ 0.0, 2.0, -2.0 ]\n    > arr.length\n    3\n\n\ntuple.subtuple( [begin[, end]] )\n    Creates a new named typed tuple over the same underlying ArrayBuffer and\n    with the same underlying data type as the host tuple.\n\n    If the function is unable to resolve indices to a non-empty tuple\n    subsequence, the function returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last tuple element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last tuple element. Default: tuple.length.\n\n    Returns\n    -------\n    tuple: TypedArray|null\n        A new named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n    > var p1 = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n    > var p2 = p1.subtuple( 2 );\n    > p2.fields\n    [ 'z', 'w', 'v' ]\n    > p2[ 0 ]\n    0.0\n    > p2.z\n    0.0\n    > p2[ 1 ]\n    2.0\n    > p2.w\n    2.0\n    > p2[ 2 ]\n    -2.0\n    > p2.v\n    -2.0\n    > p2.length\n    3\n\n\ntuple.toJSON()\n    Serializes a tuple as JSON.\n\n    Returns\n    -------\n    obj: Object\n        A tuple JSON representation.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, -1.0, 0.0 ] );\n    > p.toJSON()\n    { 'x': 1.0, 'y': -1.0, 'z': 0.0 }\n\n\ntuple.toLocaleString( [locales[, options]] )\n    Serializes a tuple as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, -1.0, 0.0 ], 'int32' );\n    > p.toLocaleString()\n    '1,-1,0'\n\n\ntuple.toString()\n    Serializes a tuple as a string.\n\n    Returns\n    -------\n    str: string\n        A tuple string representation.\n\n    Examples\n    --------\n    > opts = { 'name': 'Point' };\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ], opts );\n    > var p = factory( [ 1.0, -1.0, 0.0 ] );\n    > p.toString()\n    'Point(x=1, y=-1, z=0)'\n\n\ntuple.values()\n    Returns an iterator for iterating over tuple elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over tuple elements.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > it = p.values();\n    > it.next().value\n    1.0\n    > it.next().value\n    -1.0\n    > it.next().done\n    true\n\n    See Also\n    --------\n    typedarray\n","NAN":"\nNAN\n    Double-precision floating-point NaN.\n\n    Examples\n    --------\n    > NAN\n    NaN\n\n    See Also\n    --------\n    FLOAT32_NAN\n","naryFunction":"\nnaryFunction( fcn, arity[, thisArg] )\n    Returns a function that applies a specified number of arguments to a\n    provided function.\n\n    The returned function *always* invokes the wrapped function with a specified\n    number of arguments, even when the returned function is provided fewer\n    arguments.\n\n    The value for the missing arguments is equal to `undefined`.\n\n    Parameters\n    ----------\n    fcn: Function\n        Input function.\n\n    arity: integer\n        Number of arguments.\n\n    thisArg: any (optional)\n        Function context.\n\n    Returns\n    -------\n    out: Function\n        Function wrapper.\n\n    Examples\n    --------\n    > function foo( a, b, c ) { return [ a, b, c ]; };\n    > var bar = naryFunction( foo, 2 );\n    > var out = bar( 1, 2, 3 )\n    [ 1, 2, undefined ]\n\n    See Also\n    --------\n    maskArguments, pickArguments\n","nativeClass":"\nnativeClass( value )\n    Returns a string value indicating a specification defined classification of\n    an object.\n\n    The function is *not* robust for ES2015+ environments. In ES2015+,\n    `Symbol.toStringTag` allows overriding the default description of an object.\n    While measures are taken to uncover the default description, such measures\n    can be thwarted. While this function remains useful for type-checking, be\n    aware that value impersonation is possible. Where possible, prefer functions\n    tailored to checking for particular value types, as specialized functions\n    are better equipped to address `Symbol.toStringTag`.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    out: string\n        String value indicating a specification defined classification of the\n        input value.\n\n    Examples\n    --------\n    > var str = nativeClass( 'a' )\n    '[object String]'\n    > str = nativeClass( 5 )\n    '[object Number]'\n    > function Beep(){};\n    > str = nativeClass( new Beep() )\n    '[object Object]'\n\n    See Also\n    --------\n    constructorName, typeOf\n","ndarray":"\nndarray( dtype, buffer, shape, strides, offset, order[, options] )\n    Returns an ndarray.\n\n    Parameters\n    ----------\n    dtype: string\n        Underlying data type.\n\n    buffer: ArrayLikeObject|TypedArray|Buffer\n        Data buffer. A data buffer must be an array-like object (i.e., have a\n        `length` property). For data buffers which are not indexed collections\n        (i.e., collections which cannot support direct index access, such as\n        `buffer[ index ]`; e.g., Complex64Array, Complex128Array, etc), a data\n        buffer should provide `#.get( idx )` and `#.set( v[, idx] )` methods.\n        Note that, for `set` methods, the value to set should be the first\n        argument, followed by the linear index, similar to the native typed\n        array `set` method.\n\n    shape: ArrayLikeObject<integer>\n        Array shape.\n\n    strides: ArrayLikeObject<integer>\n        Array strides.\n\n    offset: integer\n        Index offset.\n\n    order: string\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran-style).\n\n    options: Object (optional)\n        Options.\n\n    options.mode: string (optional)\n        Specifies how to handle indices which exceed array dimensions. If equal\n        to 'throw', an ndarray instance throws an error when an index exceeds\n        array dimensions. If equal to 'normalize', an ndarray instance\n        normalizes negative indices and throws an error when an index exceeds\n        array dimensions. If equal to 'wrap', an ndarray instance wraps around\n        indices exceeding array dimensions using modulo arithmetic. If equal to\n        'clamp', an ndarray instance sets an index exceeding array dimensions\n        to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n    options.submode: Array<string> (optional)\n        Specifies how to handle subscripts which exceed array dimensions. If a\n        mode for a corresponding dimension is equal to 'throw', an ndarray\n        instance throws an error when a subscript exceeds array dimensions. If\n        equal to 'normalize', an ndarray instance normalizes negative\n        subscripts and throws an error when a subscript exceeds array\n        dimensions. If equal to 'wrap', an ndarray instance wraps around\n        subscripts exceeding array dimensions using modulo arithmetic. If equal\n        to 'clamp', an ndarray instance sets a subscript exceeding array\n        dimensions to either `0` (minimum index) or the maximum index. If the\n        number of modes is fewer than the number of dimensions, the function\n        recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether an array should be read-only. Default: false.\n\n    Returns\n    -------\n    ndarray: ndarray\n        ndarray instance.\n\n    Examples\n    --------\n    // Create a new instance...\n    > var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\n    > var d = [ 2, 2 ]; // shape\n    > var s = [ 2, 1 ]; // strides\n    > var o = 0; // index offset\n    > var arr = ndarray( 'generic', b, d, s, o, 'row-major' )\n    <ndarray>\n\n    // Get an element using subscripts:\n    > var v = arr.get( 1, 1 )\n    4.0\n\n    // Get an element using a linear index:\n    > v = arr.iget( 3 )\n    4.0\n\n    // Set an element using subscripts:\n    > arr.set( 1, 1, 40.0 );\n    > arr.get( 1, 1 )\n    40.0\n\n    // Set an element using a linear index:\n    > arr.iset( 3, 99.0 );\n    > arr.get( 1, 1 )\n    99.0\n\n\nndarray.prototype.byteLength\n    Size (in bytes) of the array (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of the array.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.byteLength\n    32\n\n\nndarray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.BYTES_PER_ELEMENT\n    8\n\n\nndarray.prototype.data\n    Pointer to the underlying data buffer.\n\n    Returns\n    -------\n    buf: ArrayLikeObject|TypedArray|Buffer\n        Underlying data buffer.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var buf = arr.data\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n\nndarray.prototype.dtype\n    Underlying data type.\n\n    Returns\n    -------\n    dtype: string\n        Underlying data type.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var dt = arr.dtype\n    'float64'\n\n\nndarray.prototype.flags\n    Meta information, such as information concerning the memory layout of the\n    array.\n\n    Returns\n    -------\n    flags: Object\n        Info object.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var fl = arr.flags\n    {...}\n\n\nndarray.prototype.length\n    Length of the array (i.e., number of elements).\n\n    Returns\n    -------\n    len: integer\n        Array length.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var len = arr.length\n    4\n\n\nndarray.prototype.ndims\n    Number of dimensions.\n\n    Returns\n    -------\n    ndims: integer\n        Number of dimensions.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var n = arr.ndims\n    2\n\n\nndarray.prototype.offset\n    Index offset which specifies the buffer index at which to start iterating\n    over array elements.\n\n    Returns\n    -------\n    offset: integer\n        Index offset.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.offset\n    0\n\n\nndarray.prototype.order\n    Array order.\n\n    The array order is either row-major (C-style) or column-major (Fortran-\n    style).\n\n    Returns\n    -------\n    order: string\n        Array order.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var ord = arr.order\n    'row-major'\n\n\nndarray.prototype.shape\n    Array shape.\n\n    Returns\n    -------\n    shape: Array\n        Array shape.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sh = arr.shape\n    [ 2, 2 ]\n\n\nndarray.prototype.strides\n    Index strides which specify how to access data along corresponding array\n    dimensions.\n\n    Returns\n    -------\n    strides: Array\n        Index strides.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var st = arr.strides\n    [ 2, 1 ]\n\n\nndarray.prototype.get( ...idx )\n    Returns an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.get( 1, 1 )\n    4.0\n\n\nndarray.prototype.iget( idx )\n    Returns an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the input argument is ignored and, for clarity,\n    should not be provided.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.iget( 3 )\n    4.0\n\n\nndarray.prototype.set( ...idx, v )\n    Sets an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: ndarray\n        ndarray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > arr.set( 1, 1, -4.0 );\n    > arr.get( 1, 1 )\n    -4.0\n\n\nndarray.prototype.iset( idx, v )\n    Sets an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the first, and only, argument should be the\n    value to set.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: ndarray\n        ndarray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > arr.iset( 3, -4.0 );\n    > arr.iget( 3 )\n    -4.0\n\n\nndarray.prototype.toString()\n    Serializes an ndarray as a string.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    str: string\n        Serialized ndarray string.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toString()\n    '...'\n\n\nndarray.prototype.toJSON()\n    Serializes an ndarray as a JSON object.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toJSON()\n    {...}\n\n    See Also\n    --------\n    array, FancyArray\n","ndarray.prototype.byteLength":"\nndarray.prototype.byteLength\n    Size (in bytes) of the array (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of the array.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.byteLength\n    32","ndarray.prototype.BYTES_PER_ELEMENT":"\nndarray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.BYTES_PER_ELEMENT\n    8","ndarray.prototype.data":"\nndarray.prototype.data\n    Pointer to the underlying data buffer.\n\n    Returns\n    -------\n    buf: ArrayLikeObject|TypedArray|Buffer\n        Underlying data buffer.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var buf = arr.data\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]","ndarray.prototype.dtype":"\nndarray.prototype.dtype\n    Underlying data type.\n\n    Returns\n    -------\n    dtype: string\n        Underlying data type.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var dt = arr.dtype\n    'float64'","ndarray.prototype.flags":"\nndarray.prototype.flags\n    Meta information, such as information concerning the memory layout of the\n    array.\n\n    Returns\n    -------\n    flags: Object\n        Info object.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var fl = arr.flags\n    {...}","ndarray.prototype.length":"\nndarray.prototype.length\n    Length of the array (i.e., number of elements).\n\n    Returns\n    -------\n    len: integer\n        Array length.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var len = arr.length\n    4","ndarray.prototype.ndims":"\nndarray.prototype.ndims\n    Number of dimensions.\n\n    Returns\n    -------\n    ndims: integer\n        Number of dimensions.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var n = arr.ndims\n    2","ndarray.prototype.offset":"\nndarray.prototype.offset\n    Index offset which specifies the buffer index at which to start iterating\n    over array elements.\n\n    Returns\n    -------\n    offset: integer\n        Index offset.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.offset\n    0","ndarray.prototype.order":"\nndarray.prototype.order\n    Array order.\n\n    The array order is either row-major (C-style) or column-major (Fortran-\n    style).\n\n    Returns\n    -------\n    order: string\n        Array order.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var ord = arr.order\n    'row-major'","ndarray.prototype.shape":"\nndarray.prototype.shape\n    Array shape.\n\n    Returns\n    -------\n    shape: Array\n        Array shape.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sh = arr.shape\n    [ 2, 2 ]","ndarray.prototype.strides":"\nndarray.prototype.strides\n    Index strides which specify how to access data along corresponding array\n    dimensions.\n\n    Returns\n    -------\n    strides: Array\n        Index strides.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var st = arr.strides\n    [ 2, 1 ]","ndarray.prototype.get":"\nndarray.prototype.get( ...idx )\n    Returns an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.get( 1, 1 )\n    4.0","ndarray.prototype.iget":"\nndarray.prototype.iget( idx )\n    Returns an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the input argument is ignored and, for clarity,\n    should not be provided.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.iget( 3 )\n    4.0","ndarray.prototype.set":"\nndarray.prototype.set( ...idx, v )\n    Sets an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: ndarray\n        ndarray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > arr.set( 1, 1, -4.0 );\n    > arr.get( 1, 1 )\n    -4.0","ndarray.prototype.iset":"\nndarray.prototype.iset( idx, v )\n    Sets an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the first, and only, argument should be the\n    value to set.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: ndarray\n        ndarray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > arr.iset( 3, -4.0 );\n    > arr.iget( 3 )\n    -4.0","ndarray.prototype.toString":"\nndarray.prototype.toString()\n    Serializes an ndarray as a string.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    str: string\n        Serialized ndarray string.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toString()\n    '...'","ndarray.prototype.toJSON":"\nndarray.prototype.toJSON()\n    Serializes an ndarray as a JSON object.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toJSON()\n    {...}\n\n    See Also\n    --------\n    array, FancyArray","ndarray2array":"\nndarray2array( x )\n    Converts an ndarray to a generic array.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    Returns\n    -------\n    out: Array|Array<Array>\n        Generic array (which may include nested arrays).\n\n    Examples\n    --------\n    > var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > var out = ndarray2array( arr )\n    [ [ 1, 2 ], [ 3, 4 ] ]\n\n    See Also\n    --------\n    array, ndarray, ndarray2json\n","ndarray2fancy":"\nndarray2fancy( x[, options] )\n    Converts an ndarray to an object supporting fancy indexing.\n\n    An ndarray supporting fancy indexing is an ndarray which supports slicing\n    via indexing expressions for both retrieval and assignment.\n\n    A fancy ndarray can be consumed by any API which supports ndarray instances.\n\n    A fancy ndarray shares the *same* data as the provided input ndarray. Hence,\n    any mutations to the returned ndarray will affect the underlying input\n    ndarray and vice versa.\n\n    A fancy ndarray supports indexing using positive and negative integers (both\n    numeric literals and strings), Slice and MultiSlice instances, subsequence\n    expressions, mask ndarrays, boolean ndarrays, and integer ndarrays.\n\n    A fancy ndarray supports all properties and methods of the input ndarray,\n    and, thus, a fancy ndarray can be consumed by any API which supports\n    ndarray-like objects.\n\n    For operations returning a new ndarray (e.g., when slicing or invoking an\n    instance method), a fancy ndarray returns a new fancy ndarray having the\n    same configuration as specified by provided options.\n\n    Indexing expressions provide a convenient and powerful means for creating\n    and operating on ndarray views; however, their use does entail a performance\n    cost. Indexing expressions are best suited for interactive use and\n    scripting. For performance critical applications, prefer equivalent\n    functional APIs supporting ndarray instances.\n\n    Fancy ndarrays support broadcasting in which assigned scalars and ndarrays\n    are repeated (without additional memory allocation) to match the dimensions\n    of a target ndarray instance.\n\n    When assigning ndarrays to slices, the ndarray on the right-hand-side must\n    be broadcast-compatible with dimensions implied by the slice.\n\n    Fancy ndarrays support (mostly) safe casts (i.e., any cast which can be\n    performed without overflow or loss of precision, with the exception of\n    floating-point ndarrays which are also allowed to downcast from higher\n    precision to lower precision).\n\n    When attempting to perform an unsafe cast, fancy ndarrays will raise an\n    exception.\n\n    When assigning a real-valued scalar to a complex number ndarray, a fancy\n    ndarray will cast the real-valued scalar to a complex number argument having\n    an imaginary component equal to zero.\n\n    In older JavaScript environments which do not support Proxy objects, the use\n    of indexing expressions is not supported.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking. Default:\n        false.\n\n    options.cache: Object (optional)\n        Cache for resolving ndarray index objects. Must have a 'get' method\n        which accepts a single argument: a string identifier associated with an\n        ndarray index. If an ndarray index associated with a provided identifier\n        exists, the 'get' method should return an object having the following\n        properties:\n\n        - data: the underlying index ndarray.\n        - type: the index type. Must be either 'mask', 'bool', or 'int'.\n        - kind: the index kind. Must be either '', 'cartesian', or 'linear'.\n        - dtype: the data type of the underlying ndarray.\n\n        If an ndarray index is not associated with a provided identifier, the\n        'get' method should return `null`.\n\n        Default: `ndindex`.\n\n    Returns\n    -------\n    out: ndarray\n        Output ndarray supporting fancy indexing.\n\n    Examples\n    --------\n    // Create a normal ndarray...\n    > var b = [ 1.0, 2.0, 3.0, 4.0 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var x = ndarray( 'generic', b, d, s, o, 'row-major' );\n\n    // Convert to a fancy ndarray:\n    > var arr = ndarray2fancy( x );\n\n    // Get an element using subscripts:\n    > var v = arr.get( 1, 1 )\n    4.0\n\n    // Get an element using a linear index:\n    > v = arr.iget( 3 )\n    4.0\n\n    // Set an element using subscripts:\n    > arr.set( 1, 1, 40.0 );\n    > arr.get( 1, 1 )\n    40.0\n\n    // Set an element using a linear index:\n    > arr.iset( 3, 99.0 );\n    > arr.get( 1, 1 )\n    99.0\n\n\nndarray2fancy.factory( [options] )\n    Returns a function for converting an ndarray to an object supporting fancy\n    indexing.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking by default.\n        Default: false.\n\n    options.cache: Object (optional)\n        Cache for resolving ndarray index objects. Must have a 'get' method\n        which accepts a single argument: a string identifier associated with an\n        ndarray index. If an ndarray index associated with a provided identifier\n        exists, the 'get' method should return an object having the following\n        properties:\n\n        - data: the underlying index ndarray.\n        - type: the index type. Must be either 'mask', 'bool', or 'int'.\n        - kind: the index kind. Must be either '', 'cartesian', or 'linear'.\n        - dtype: the data type of the underlying ndarray.\n\n        If an ndarray index is not associated with a provided identifier, the\n        'get' method should return `null`.\n\n        Default: `ndindex`.\n\n    Returns\n    -------\n    fcn: Function\n        Function for converting an ndarray to an object supporting fancy\n        indexing.\n\n    Examples\n    --------\n    // Create a normal ndarray...\n    > var b = [ 1.0, 2.0, 3.0, 4.0 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var x = ndarray( 'generic', b, d, s, o, 'row-major' );\n\n    // Create a function for converting ndarrays to fancy ndarrays:\n    > var f = ndarray2fancy.factory();\n\n    // Convert the normal ndarray to a fancy ndarray:\n    > var y = f( x );\n\n\nndarray2fancy.idx( x[, options] )\n    Wraps a provided ndarray as an ndarray index object.\n\n    For documentation and usage, see `ndindex`.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.persist: boolean (optional)\n        Boolean indicating whether to continue persisting an index object after\n        first usage. Default: false.\n\n    options.kind: string (optional)\n        Specifies whether a provided ndarray is a specialized input ndarray\n        \"kind\". This option is only applicable for integer input ndarrays. Must\n        be one of the following:\n\n        - cartesian: a provided input ndarray contains Cartesian indices.\n        - linear: a provided input ndarray contains indices representing\n          locations in linear memory.\n\n        Default: ''.\n\n    Returns\n    -------\n    out: ndarrayIndex\n        ndarray index instance.\n\n    Examples\n    --------\n    > var opts = { 'dtype': 'int32' };\n    > var buf = new Int32Array( [ 1, 2, 3, 4 ] );\n    > var arr = array( buf, opts );\n    > var idx = ndarray2fancy.idx( arr );\n\n    See Also\n    --------\n    array2fancy, array, ndarray, FancyArray\n","ndarray2fancy.factory":"\nndarray2fancy.factory( [options] )\n    Returns a function for converting an ndarray to an object supporting fancy\n    indexing.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking by default.\n        Default: false.\n\n    options.cache: Object (optional)\n        Cache for resolving ndarray index objects. Must have a 'get' method\n        which accepts a single argument: a string identifier associated with an\n        ndarray index. If an ndarray index associated with a provided identifier\n        exists, the 'get' method should return an object having the following\n        properties:\n\n        - data: the underlying index ndarray.\n        - type: the index type. Must be either 'mask', 'bool', or 'int'.\n        - kind: the index kind. Must be either '', 'cartesian', or 'linear'.\n        - dtype: the data type of the underlying ndarray.\n\n        If an ndarray index is not associated with a provided identifier, the\n        'get' method should return `null`.\n\n        Default: `ndindex`.\n\n    Returns\n    -------\n    fcn: Function\n        Function for converting an ndarray to an object supporting fancy\n        indexing.\n\n    Examples\n    --------\n    // Create a normal ndarray...\n    > var b = [ 1.0, 2.0, 3.0, 4.0 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var x = ndarray( 'generic', b, d, s, o, 'row-major' );\n\n    // Create a function for converting ndarrays to fancy ndarrays:\n    > var f = ndarray2fancy.factory();\n\n    // Convert the normal ndarray to a fancy ndarray:\n    > var y = f( x );","ndarray2fancy.idx":"\nndarray2fancy.idx( x[, options] )\n    Wraps a provided ndarray as an ndarray index object.\n\n    For documentation and usage, see `ndindex`.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.persist: boolean (optional)\n        Boolean indicating whether to continue persisting an index object after\n        first usage. Default: false.\n\n    options.kind: string (optional)\n        Specifies whether a provided ndarray is a specialized input ndarray\n        \"kind\". This option is only applicable for integer input ndarrays. Must\n        be one of the following:\n\n        - cartesian: a provided input ndarray contains Cartesian indices.\n        - linear: a provided input ndarray contains indices representing\n          locations in linear memory.\n\n        Default: ''.\n\n    Returns\n    -------\n    out: ndarrayIndex\n        ndarray index instance.\n\n    Examples\n    --------\n    > var opts = { 'dtype': 'int32' };\n    > var buf = new Int32Array( [ 1, 2, 3, 4 ] );\n    > var arr = array( buf, opts );\n    > var idx = ndarray2fancy.idx( arr );\n\n    See Also\n    --------\n    array2fancy, array, ndarray, FancyArray","ndarray2json":"\nndarray2json( x )\n    Serializes an ndarray as a JSON object.\n\n    This function does *not* serialize data outside of the buffer region defined\n    by the ndarray view.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    Returns\n    -------\n    out: Object\n        JSON object.\n\n    Examples\n    --------\n    > var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > var out = ndarray2json( arr )\n    {...}\n\n    See Also\n    --------\n    array, ndarray, ndarray2array\n","ndarrayCastingModes":"\nndarrayCastingModes()\n    Returns a list of ndarray casting modes.\n\n    The output array contains the following modes:\n\n    - 'none': only allow casting between identical types.\n    - 'equiv': allow casting between identical and byte swapped types.\n    - 'safe': only allow \"safe\" casts.\n    - 'mostly-safe': allow \"safe\" casts and, for floating-point data types,\n      downcasts.\n    - 'same-kind': allow \"safe\" casts and casts within the same kind (e.g.,\n      between signed integers or between floats).\n    - 'unsafe': allow casting between all types (including between integers and\n      floats).\n\n    Returns\n    -------\n    out: Array<string>\n        List of ndarray casting modes.\n\n    Examples\n    --------\n    > var out = ndarrayCastingModes()\n    [ 'none', 'equiv', 'safe', 'mostly-safe', 'same-kind', 'unsafe' ]\n\n    See Also\n    --------\n    array, ndarray\n","ndarrayDataBuffer":"\nndarrayDataBuffer( x )\n    Returns the underlying data buffer of a provided ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Underlying data buffer.\n\n    Examples\n    --------\n    > var opts = { 'dtype': 'float64' };\n    > var out = ndarrayDataBuffer( ndzeros( [ 3, 3, 3 ], opts ) )\n    <Float64Array>\n\n    See Also\n    --------\n    array, ndarray, ndarrayDataType\n","ndarrayDataType":"\nndarrayDataType( x )\n    Returns the data type of a provided ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    Returns\n    -------\n    dt: string\n        Data type.\n\n    Examples\n    --------\n    > var opts = { 'dtype': 'float64' };\n    > var dt = ndarrayDataType( ndzeros( [ 3, 3, 3 ], opts ) )\n    'float64'\n\n    See Also\n    --------\n    array, ndarray, ndarrayDataTypes\n","ndarrayDataTypes":"\nndarrayDataTypes( [kind] )\n    Returns a list of ndarray data types.\n\n    When not provided a data type \"kind\", the function returns an array\n    containing the following data types:\n\n    - float32: single-precision floating-point numbers.\n    - float64: double-precision floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - complex128: double-precision complex floating-point numbers.\n    - bool: boolean values.\n    - generic: values of any type.\n    - int16: signed 16-bit integers.\n    - int32: signed 32-bit integers.\n    - int8: signed 8-bit integers.\n    - uint16: unsigned 16-bit integers.\n    - uint32: unsigned 32-bit integers.\n    - uint8: unsigned 8-bit integers.\n    - uint8c: unsigned clamped 8-bit integers.\n    - binary: binary.\n\n    The function supports the following data type \"kinds\":\n\n    - floating_point: floating-point data types.\n    - real_floating_point: real-valued floating-point data types.\n    - complex_floating_point: complex-valued floating-point data types.\n    - boolean: boolean data types.\n    - integer: integer data types.\n    - signed_integer: signed integer data types.\n    - unsigned_integer: unsigned integer data types.\n    - real: real-valued data types.\n    - numeric: numeric data types.\n    - typed: typed data types.\n    - all: all data types.\n\n    Additionally, the function supports extending the \"kinds\" listed above by\n    appending a '_and_generic' suffix to the kind name (e.g., real_and_generic).\n\n    Parameters\n    ----------\n    kind: string (optional)\n        Data type kind.\n\n    Returns\n    -------\n    out: Array<string>\n        List of ndarray data types.\n\n    Examples\n    --------\n    > var out = ndarrayDataTypes()\n    [...]\n    > out = ndarrayDataTypes( 'floating_point' )\n    [...]\n    > out = ndarrayDataTypes( 'floating_point_and_generic' )\n    [...]\n\n    See Also\n    --------\n    arrayDataTypes, array, ndarray, typedarrayDataTypes\n","ndarrayDispatch":"\nndarrayDispatch( fcns, types, data, nargs, nin, nout )\n    Returns an ndarray function interface which performs multiple dispatch.\n\n    An ndarray function interface has the following signature:\n\n      f( x, y, ... )\n\n    where\n\n    - x: ndarray.\n    - y: ndarray.\n    - ...: additional ndarrays.\n\n    The number of parameters is derived from `nargs`, the number of input\n    ndarrays is derived from `nin`, and the number of output ndarrays is derived\n    from `nout`.\n\n    Parameters\n    ----------\n    fcns: Function|ArrayLikeObject<Function>\n        List of ndarray functions. An ndarray function should have the following\n        signature:\n\n          f( arrays, data )\n\n        where\n\n        - arrays: array containing input and output ndarrays.\n        - data: ndarray function data (e.g., a callback).\n\n        For convenience, a single ndarray function may be provided which will be\n        invoked whenever the ndarray argument data types match a sequence of\n        types in `types`. Providing a single ndarray function is particularly\n        convenient for the case where, regardless of array data types,\n        traversing arrays remains the same, but the ndarray function `data`\n        differs (e.g., callbacks which differ based on the array data types).\n\n    types: ArrayLikeObject\n        One-dimensional list of ndarray argument data types.\n\n    data: ArrayLikeObject|null\n        ndarray function data (e.g., callbacks). If `null`, a returned ndarray\n        function interface does **not** provide a `data` argument to an invoked\n        ndarray function.\n\n    nargs: integer\n        Total number of ndarray function interface arguments.\n\n    nin: integer\n        Number of input ndarrays.\n\n    nout: integer\n        Number of output ndarrays.\n\n    Returns\n    -------\n    fcn: Function\n        ndarray function interface.\n\n    Examples\n    --------\n    // Define ndarray argument data types:\n    > var t = [ 'float64', 'float64', 'float32', 'float32' ];\n\n    // Define a list of ndarray function data (callbacks):\n    > var d = [ base.abs, base.absf ];\n\n    // Create an ndarray function interface for applying unary callbacks:\n    > var f = ndarrayDispatch( base.ndarrayUnary, t, d, 2, 1, 1 );\n\n    // Create an input ndarray:\n    > var xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var x = ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );\n\n    // Create an output ndarray:\n    > var ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var y = ndarray( 'float64', ybuf, [ 4 ], [ 1 ], 0, 'row-major' );\n\n    // Compute the element-wise absolute value:\n    > f( x, y );\n    > ybuf\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    See Also\n    --------\n    array, ndarray\n","ndarrayFlag":"\nndarrayFlag( x, name )\n    Returns a specified flag for a provided ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    name: string|symbol\n        Flag name.\n\n    Returns\n    -------\n    out: any\n        Flag value.\n\n    Examples\n    --------\n    > var out = ndarrayFlag( ndzeros( [ 3, 3, 3 ] ), 'READONLY' )\n    <boolean>\n\n    See Also\n    --------\n    array, ndarray, ndarrayFlags\n","ndarrayFlags":"\nndarrayFlags( x )\n    Returns the flags of a provided ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    Returns\n    -------\n    out: Object\n        Flags.\n\n    Examples\n    --------\n    > var out = ndarrayFlags( ndzeros( [ 3, 3, 3 ] ) )\n    {...}\n\n    See Also\n    --------\n    array, ndarray, ndarrayFlag\n","ndarrayIndexModes":"\nndarrayIndexModes()\n    Returns a list of ndarray index modes.\n\n    The output array contains the following modes:\n\n    - throw: specifies that a function should throw an error when an index is\n    outside a restricted interval.\n    - normalize: specifies that a function should normalize negative indices and\n    throw an error when an index is outside a restricted interval.\n    - wrap: specifies that a function should wrap around an index using modulo\n    arithmetic.\n    - clamp: specifies that a function should set an index less than zero to\n    zero (minimum index) and set an index greater than a maximum index value to\n    the maximum possible index.\n\n    Returns\n    -------\n    out: Array<string>\n        List of ndarray index modes.\n\n    Examples\n    --------\n    > var out = ndarrayIndexModes()\n    [ 'throw', 'normalize', 'clamp', 'wrap' ]\n\n    See Also\n    --------\n    array, ndarray\n","ndarraylike2ndarray":"\nndarraylike2ndarray( x[, options] )\n    Converts an ndarray-like object to an ndarray.\n\n    If provided a read-only ndarray, the function returns a read-only ndarray.\n\n    Parameters\n    ----------\n    x: ndarrayLike\n        Input ndarray-like object.\n\n    options: Object (optional)\n        Options.\n\n    options.mode: string (optional)\n        Specifies how to handle indices which exceed array dimensions. If equal\n        to 'throw', an ndarray instance throws an error when an index exceeds\n        array dimensions. If equal to 'normalize', an ndarray instance\n        normalizes negative indices and throws an error when an index exceeds\n        array dimensions. If equal to 'wrap', an ndarray instance wraps around\n        indices exceeding array dimensions using modulo arithmetic. If equal to\n        'clamp', an ndarray instance sets an index exceeding array dimensions\n        to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n    options.submode: Array<string> (optional)\n        Specifies how to handle subscripts which exceed array dimensions. If a\n        mode for a corresponding dimension is equal to 'throw', an ndarray\n        instance throws an error when a subscript exceeds array dimensions. If\n        equal to 'normalize', an ndarray instance normalizes negative\n        subscripts and throws an error when a subscript exceeds array\n        dimensions. If equal to 'wrap', an ndarray instance wraps around\n        subscripts exceeding array dimensions using modulo arithmetic. If equal\n        to 'clamp', an ndarray instance sets a subscript exceeding array\n        dimensions to either `0` (minimum index) or the maximum index. If the\n        number of modes is fewer than the number of dimensions, the function\n        recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether an array should be read-only.\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > var out = ndarraylike2ndarray( arr )\n    <ndarray>\n\n    See Also\n    --------\n    array, ndarray, ndemptyLike, ndzerosLike\n","ndarrayMinDataType":"\nndarrayMinDataType( value )\n    Returns the minimum ndarray data type of the closest \"kind\" necessary for\n    storing a provided scalar value.\n\n    The function does *not* provide precision guarantees for non-integer-valued\n    numbers. In other words, the function returns the smallest possible\n    floating-point (i.e., inexact) data type for storing numbers having\n    decimals.\n\n    Parameters\n    ----------\n    value: any\n        Scalar value.\n\n    Returns\n    -------\n    dt: string\n        ndarray data type.\n\n    Examples\n    --------\n    > var dt = ndarrayMinDataType( 3.141592653589793 )\n    'float32'\n    > dt = ndarrayMinDataType( 3 )\n    'uint8'\n    > dt = ndarrayMinDataType( -3 )\n    'int8'\n    > dt = ndarrayMinDataType( '-3' )\n    'generic'\n\n    See Also\n    --------\n    ndarrayDataTypes, ndarrayPromotionRules, ndarraySafeCasts\n","ndarrayMostlySafeCasts":"\nndarrayMostlySafeCasts( [dtype] )\n    Returns a list of ndarray data types to which a provided ndarray data type\n    can be safely cast and, for floating-point data types, can be downcast.\n\n    If not provided an ndarray data type, the function returns a casting table.\n\n    If provided an unrecognized ndarray data type, the function returns `null`.\n\n    Parameters\n    ----------\n    dtype: any (optional)\n        ndarray data type value.\n\n    Returns\n    -------\n    out: Object|Array<string>|null\n        ndarray data types to which a data type can be cast.\n\n    Examples\n    --------\n    > var out = ndarrayMostlySafeCasts( 'float32' )\n    <Array>\n\n    See Also\n    --------\n    ndarrayCastingModes, ndarrayDataTypes, ndarraySafeCasts, ndarraySameKindCasts\n","ndarrayNextDataType":"\nndarrayNextDataType( [dtype] )\n    Returns the next larger ndarray data type of the same kind.\n\n    If not provided a data type, the function returns a table.\n\n    If a data type does not have a next larger data type or the next larger type\n    is not supported, the function returns `-1`.\n\n    If provided an unrecognized data type, the function returns `null`.\n\n    Parameters\n    ----------\n    dtype: any (optional)\n        ndarray data type value.\n\n    Returns\n    -------\n    out: Object|string|integer|null\n        Next larger type(s).\n\n    Examples\n    --------\n    > var out = ndarrayNextDataType( 'float32' )\n    'float64'\n\n    See Also\n    --------\n    ndarrayDataTypes, ndarrayPromotionRules, ndarraySafeCasts\n","ndarrayOffset":"\nndarrayOffset( x )\n    Returns the index offset specifying the underlying buffer index of the first\n    iterated ndarray element.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    Returns\n    -------\n    n: integer\n        Index offset.\n\n    Examples\n    --------\n    > var n = ndarrayOffset( ndzeros( [ 3, 3, 3 ] ) )\n    0\n\n    See Also\n    --------\n    array, ndarray, ndarrayShape, ndarrayStrides\n","ndarrayOrder":"\nndarrayOrder( x )\n    Returns the layout order of a provided ndarray.\n\n    If unable to resolve a layout order, the function returns `null`.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    Returns\n    -------\n    out: string|null\n        Layout order.\n\n    Examples\n    --------\n    > var opts = { 'order': 'row-major' };\n    > var dt = ndarrayOrder( ndzeros( [ 3, 3, 3 ], opts ) )\n    'row-major'\n\n    See Also\n    --------\n    array, ndarray, ndarrayOrders, ndarrayShape, ndarrayStrides\n","ndarrayOrders":"\nndarrayOrders()\n    Returns a list of ndarray orders.\n\n    The output array contains the following orders:\n\n    - row-major: row-major (C-style) order.\n    - column-major: column-major (Fortran-style) order.\n\n    Returns\n    -------\n    out: Array<string>\n        List of ndarray orders.\n\n    Examples\n    --------\n    > var out = ndarrayOrders()\n    [ 'row-major', 'column-major' ]\n\n    See Also\n    --------\n    array, ndarray\n","ndarrayPromotionRules":"\nndarrayPromotionRules( [dtype1, dtype2] )\n    Returns the ndarray data type with the smallest size and closest \"kind\" to\n    which ndarray data types can be safely cast.\n\n    If not provided data types, the function returns a type promotion table.\n\n    If a data type to which data types can be safely cast does *not* exist (or\n    is not supported), the function returns `-1`.\n\n    If provided an unrecognized data type, the function returns `null`.\n\n    Parameters\n    ----------\n    dtype1: any (optional)\n        ndarray data type value.\n\n    dtype2: any (optional)\n        ndarray data type value.\n\n    Returns\n    -------\n    out: Object|string|integer|null\n        Promotion rule(s).\n\n    Examples\n    --------\n    > var out = ndarrayPromotionRules( 'float32', 'int32' )\n    'float64'\n\n    See Also\n    --------\n    ndarrayCastingModes, ndarrayDataTypes, ndarraySafeCasts\n","ndarraySafeCasts":"\nndarraySafeCasts( [dtype] )\n    Returns a list of ndarray data types to which a provided ndarray data type\n    can be safely cast.\n\n    If not provided an ndarray data type, the function returns a casting table.\n\n    If provided an unrecognized ndarray data type, the function returns `null`.\n\n    Parameters\n    ----------\n    dtype: any (optional)\n        ndarray data type value.\n\n    Returns\n    -------\n    out: Object|Array<string>|null\n        ndarray data types to which a data type can be safely cast.\n\n    Examples\n    --------\n    > var out = ndarraySafeCasts( 'float32' )\n    <Array>\n\n    See Also\n    --------\n    ndarrayCastingModes, ndarrayDataTypes, ndarraySameKindCasts\n","ndarraySameKindCasts":"\nndarraySameKindCasts( [dtype] )\n    Returns a list of ndarray data types to which a provided ndarray data type\n    can be safely cast or cast within the same \"kind\".\n\n    If not provided an ndarray data type, the function returns a casting table.\n\n    If provided an unrecognized ndarray data type, the function returns `null`.\n\n    Parameters\n    ----------\n    dtype: any (optional)\n        ndarray data type value.\n\n    Returns\n    -------\n    out: Object|Array<string>|null\n        ndarray data types to which a data type can be safely cast or cast\n        within the same \"kind\".\n\n    Examples\n    --------\n    > var out = ndarraySameKindCasts( 'float32' )\n    <Array>\n\n    See Also\n    --------\n    ndarrayCastingModes, ndarrayDataTypes, ndarraySafeCasts\n","ndarrayShape":"\nndarrayShape( x )\n    Returns the shape of a provided ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    Returns\n    -------\n    out: Array<integer>\n        Shape.\n\n    Examples\n    --------\n    > var out = ndarrayShape( ndzeros( [ 3, 3, 3 ] ) )\n    [ 3, 3, 3 ]\n\n    See Also\n    --------\n    array, ndarray, ndarrayOffset, ndarrayStrides\n","ndarrayStride":"\nndarrayStride( x, dim )\n    Returns the stride along a specified dimension for a provided ndarray.\n\n    A \"stride\" is the linear distance (i.e., number of elements) between\n    adjacent elements along a specified dimension.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    dim: integer\n        Dimension index. If less than zero, the index is resolved relative to\n        the last dimension, with the last dimension corresponding to the value\n        `-1`.\n\n    Returns\n    -------\n    out: integer\n        Stride.\n\n    Examples\n    --------\n    > var out = ndarrayStride( ndzeros( [ 3, 3, 3 ] ), 0 )\n    9\n\n    See Also\n    --------\n    array, ndarray, ndarrayOffset, ndarrayOrder, ndarrayShape, ndarrayStrides\n","ndarrayStrides":"\nndarrayStrides( x )\n    Returns the strides of a provided ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    Returns\n    -------\n    out: Array<integer>\n        Strides.\n\n    Examples\n    --------\n    > var out = ndarrayStrides( ndzeros( [ 3, 3, 3 ] ) )\n    [ 9, 3, 1 ]\n\n    See Also\n    --------\n    array, ndarray, ndarrayOffset, ndarrayOrder, ndarrayShape\n","ndat":"\nndat( x[, ...indices] )\n    Returns an ndarray element.\n\n    Negative indices are resolved relative to the last element along the\n    respective dimension, with the last element corresponding to `-1`.\n\n    If provided out-of-bounds indices, the function always returns `undefined`.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    indices: ...integer (optional)\n        Index arguments. The number of index arguments must equal the number of\n        dimensions.\n\n    Returns\n    -------\n    out: any\n        Element value.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > ndat( x, 0, 1 )\n    2\n    > ndat( x, 1, 0 )\n    3\n\n    See Also\n    --------\n    array, ndslice\n","ndempty":"\nndempty( shape[, options] )\n    Returns an uninitialized ndarray having a specified shape and data type.\n\n    In browser environments, the function always returns zero-filled ndarrays.\n\n    If `dtype` is 'generic', the function always returns a zero-filled ndarray.\n\n    For returned ndarrays whose underlying memory is *not* initialized, memory\n    contents are unknown and may contain *sensitive* data.\n\n    Parameters\n    ----------\n    shape: ArrayLikeObject<integer>|integer\n        Array shape.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Underlying data type. Default: 'float64'.\n\n    options.order: string (optional)\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran-style). Default: 'row-major'.\n\n    options.mode: string (optional)\n        Specifies how to handle indices which exceed array dimensions. If equal\n        to 'throw', an ndarray instance throws an error when an index exceeds\n        array dimensions. If equal to 'normalize', an ndarray instance\n        normalizes negative indices and throws an error when an index exceeds\n        array dimensions. If equal to 'wrap', an ndarray instance wraps around\n        indices exceeding array dimensions using modulo arithmetic. If equal to\n        'clamp', an ndarray instance sets an index exceeding array dimensions\n        to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n    options.submode: Array<string> (optional)\n        Specifies how to handle subscripts which exceed array dimensions. If a\n        mode for a corresponding dimension is equal to 'throw', an ndarray\n        instance throws an error when a subscript exceeds array dimensions. If\n        equal to 'normalize', an ndarray instance normalizes negative\n        subscripts and throws an error when a subscript exceeds array\n        dimensions. If equal to 'wrap', an ndarray instance wraps around\n        subscripts exceeding array dimensions using modulo arithmetic. If equal\n        to 'clamp', an ndarray instance sets a subscript exceeding array\n        dimensions to either `0` (minimum index) or the maximum index. If the\n        number of modes is fewer than the number of dimensions, the function\n        recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var arr = ndempty( [ 2, 2 ] )\n    <ndarray>\n    > var sh = arr.shape\n    [ 2, 2 ]\n    > var dt = arr.dtype\n    'float64'\n\n    See Also\n    --------\n    ndemptyLike, ndzeros\n","ndemptyLike":"\nndemptyLike( x[, options] )\n    Returns an uninitialized ndarray having the same shape and data type as a\n    provided input ndarray.\n\n    The function infers the following attributes from the input array:\n\n    - shape: array shape.\n    - dtype: underlying array data type.\n    - order: whether the array order is row-major (C-style) or column-major\n      (Fortran-style).\n\n    In browser environments, the function always returns zero-filled ndarrays.\n\n    If `dtype` is 'generic', the function always returns a zero-filled ndarray.\n\n    For returned ndarrays whose underlying memory is *not* initialized, memory\n    contents are unknown and may contain *sensitive* data.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    options: Object (optional)\n        Options.\n\n    options.shape: ArrayLikeObject<integer>|integer (optional)\n        Array shape. Overrides the input array's inferred shape.\n\n    options.dtype: string (optional)\n        Array data type. Overrides the input array's inferred data type.\n\n    options.order: string (optional)\n        Array order (either 'row-major' (C-style) or 'column-major' (Fortran-\n        style)). Overrides the input array's inferred order.\n\n    options.mode: string (optional)\n        Specifies how to handle indices which exceed array dimensions. If equal\n        to 'throw', an ndarray instance throws an error when an index exceeds\n        array dimensions. If equal to 'normalize', an ndarray instance\n        normalizes negative indices and throws an error when an index exceeds\n        array dimensions. If equal to 'wrap', an ndarray instance wraps around\n        indices exceeding array dimensions using modulo arithmetic. If equal to\n        'clamp', an ndarray instance sets an index exceeding array dimensions\n        to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n    options.submode: Array<string> (optional)\n        Specifies how to handle subscripts which exceed array dimensions. If a\n        mode for a corresponding dimension is equal to 'throw', an ndarray\n        instance throws an error when a subscript exceeds array dimensions. If\n        equal to 'normalize', an ndarray instance normalizes negative\n        subscripts and throws an error when a subscript exceeds array\n        dimensions. If equal to 'wrap', an ndarray instance wraps around\n        subscripts exceeding array dimensions using modulo arithmetic. If equal\n        to 'clamp', an ndarray instance sets a subscript exceeding array\n        dimensions to either `0` (minimum index) or the maximum index. If the\n        number of modes is fewer than the number of dimensions, the function\n        recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n    <ndarray>\n    > var sh = x.shape\n    [ 2, 2 ]\n    > var dt = x.dtype\n    'float64'\n    > var y = ndemptyLike( x )\n    <ndarray>\n    > sh = y.shape\n    [ 2, 2 ]\n    > dt = y.dtype\n    'float64'\n\n    See Also\n    --------\n    ndempty, ndzerosLike\n","ndfilter":"\nndfilter( x[, options], predicate[, thisArg] )\n    Returns a shallow copy of an ndarray containing only those elements which\n    pass a test implemented by a predicate function.\n\n    The predicate function is provided the following arguments:\n\n    - value: current array element.\n    - indices: current array element indices.\n    - arr: the input ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.dtype: string (optional)\n        Output ndarray data type. Overrides using the input array's inferred\n        data type.\n\n    options.order: string (optional)\n        Index iteration order. By default, the function iterates over elements\n        according to the layout order of the provided array. Accordingly, for\n        row-major input arrays, the last dimension indices increment fastest.\n        For column-major input arrays, the first dimension indices increment\n        fastest. To override the inferred order and ensure that indices\n        increment in a specific manner, regardless of the input array's layout\n        order, explicitly set the iteration order. Note, however, that iterating\n        according to an order which does not match that of the input array may,\n        in some circumstances, result in performance degradation due to cache\n        misses. Must be either 'row-major' or 'column-major'.\n\n    predicate: Function\n        Predicate function.\n\n    thisArg: any (optional)\n        Predicate function execution context.\n\n    Examples\n    --------\n    > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n    > function f( v ) { return v > 2.0; };\n    > var y = ndfilter( x, f );\n    > ndarray2array( y )\n    [ 3.0, 4.0 ]\n\n    See Also\n    --------\n    ndfilterMap, ndmap, ndreject, ndslice","ndfilterMap":"\nndfilterMap( x[, options], fcn[, thisArg] )\n    Filters and maps elements in an input ndarray to elements in a new output\n    ndarray according to a callback function.\n\n    The callback function is provided the following arguments:\n\n    - value: current array element.\n    - indices: current array element indices.\n    - arr: the input ndarray.\n\n    If a provided callback function returns `undefined`, the function skips the\n    respective ndarray element. If the callback function returns a value other\n    than `undefined`, the function stores the callback's return value in the\n    output ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.dtype: string (optional)\n        Output ndarray data type. Overrides using the input array's inferred\n        data type.\n\n    options.order: string (optional)\n        Index iteration order. By default, the function iterates over elements\n        according to the layout order of the provided array. Accordingly, for\n        row-major input arrays, the last dimension indices increment fastest.\n        For column-major input arrays, the first dimension indices increment\n        fastest. To override the inferred order and ensure that indices\n        increment in a specific manner, regardless of the input array's layout\n        order, explicitly set the iteration order. Note, however, that iterating\n        according to an order which does not match that of the input array may,\n        in some circumstances, result in performance degradation due to cache\n        misses. Must be either 'row-major' or 'column-major'.\n\n    fcn: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback function execution context.\n\n    Examples\n    --------\n    > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n    > function f( v ) { if ( v > 2.0 ) { return v * 10.0; } };\n    > var y = ndfilterMap( x, f );\n    > ndarray2array( y )\n    [ 30.0, 40.0 ]\n\n    See Also\n    --------\n    ndfilter, ndmap, ndreject, ndslice","ndforEach":"\nndforEach( x, fcn[, thisArg] )\n    Invokes a callback function once for each ndarray element.\n\n    The callback function is provided the following arguments:\n\n    - value: current array element.\n    - indices: current array element indices.\n    - arr: the input ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    fcn: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback function execution context.\n\n    Examples\n    --------\n    > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n    > function f( v ) { if ( v !== v ) { throw new Error( '...' ); } };\n    > ndforEach( x, f );\n\n    See Also\n    --------\n    ndmap","ndims":"\nndims( x )\n    Returns the number of ndarray dimensions.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    Returns\n    -------\n    n: integer\n        Number of dimensions.\n\n    Examples\n    --------\n    > var n = ndims( ndzeros( [ 3, 3, 3 ] ) )\n    3\n\n    See Also\n    --------\n    array, ndarray, numel, ndarrayShape\n","ndindex":"\nndindex( x[, options] )\n    Wraps a provided array as an ndarray index object.\n\n    ndarray index instances have no explicit functionality; however, they are\n    used by \"fancy\" ndarrays for element retrieval and assignment.\n\n    By default, an instance is invalidated and removed from an internal cache\n    immediately after a consumer resolves the underlying data associated with an\n    instance using the `get` static method. Immediate invalidation and cache\n    removal ensures that references to the underlying ndarray are not the source\n    of memory leaks.\n\n    Because instances leverage an internal cache implementing the Singleton\n    pattern, one must be sure to use the same constructor as consumers. If one\n    uses a different constructor, the consumer will *not* be able to resolve the\n    original wrapped ndarray, as the consumer will attempt to resolve an\n    instance in the wrong internal cache.\n\n    Because non-persisted instances are freed after first use, in order to avoid\n    holding onto memory and to allow garbage collection, one should avoid\n    scenarios in which an instance is never used.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.persist: boolean (optional)\n        Boolean indicating whether to continue persisting an index object after\n        first usage. Default: false.\n\n    options.kind: string (optional)\n        Specifies whether a provided ndarray is a specialized input ndarray\n        \"kind\". This option is only applicable for integer input ndarrays. Must\n        be one of the following:\n\n        - cartesian: a provided input ndarray contains Cartesian indices.\n        - linear: a provided input ndarray contains indices representing\n          locations in linear memory.\n\n        Default: ''.\n\n    Returns\n    -------\n    out: ndindex\n        Index instance.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n\n\nndindex.free( id )\n    Frees the instance associated with a provided identifier.\n\n    Parameters\n    ----------\n    id: string\n        Instance identifier.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an instance was successfully freed.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > ndindex.free( idx.id )\n    <boolean>\n\n\nndindex.get( id )\n    Returns the ndarray associated with the instance having a provided\n    identifier.\n\n    Parameters\n    ----------\n    id: string\n        Instance identifier.\n\n    Returns\n    -------\n    out: Object\n        Object containing ndarray data.\n\n    out.data: ndarray\n        The underlying ndarray associated with the provided identifier.\n\n    out.type: string\n        The type of ndarray index.\n\n    out.dtype: string\n        The data type of the underlying ndarray.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > ndindex.get( idx.id )\n    {...}\n\n\nndindex.cartesianIndex( x[, options] )\n    Returns an ndarray index containing Cartesian indices.\n\n    This is a convenience method for calling `ndindex` with `kind` set to\n    'cartesian'.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.persist: boolean (optional)\n        Boolean indicating whether to continue persisting an index object after\n        first usage. Default: false.\n\n    Returns\n    -------\n    out: ndindex\n        Index instance.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = ndindex.cartesianIndex( x );\n\n\nndindex.linearIndex( x[, options] )\n    Returns an ndarray index for indices representing locations in linear\n    memory.\n\n    This is a convenience method for calling `ndindex` with `kind` set to\n    'linear'.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.persist: boolean (optional)\n        Boolean indicating whether to continue persisting an index object after\n        first usage. Default: false.\n\n    Returns\n    -------\n    out: ndindex\n        Index instance.\n\n    Examples\n    --------\n    > var x = ndempty( [ 5 ], { 'dtype': 'int32' } );\n    > var idx = ndindex.linearIndex( x );\n\n\nndindex.prototype.data\n    Read-only property returning an ndarray view of the underlying index\n    ndarray.\n\n    Returns\n    -------\n    out: ndarray\n        Array data.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.data\n    <ndarray>\n\n\nndindex.prototype.dtype\n    Read-only property returning the underlying data type of the index ndarray.\n\n    Returns\n    -------\n    out: string\n        Array data type.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.dtype\n    'int32'\n\n\nndindex.prototype.id\n    Read-only property returning the unique identifier associated with an\n    instance.\n\n    Returns\n    -------\n    out: string\n        String identifier.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.id\n    <string>\n\n\nndindex.prototype.isCached\n    Read-only property returning a boolean indicating whether an ndarray index\n    is actively cached.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an ndarray index is actively cached.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.isCached\n    true\n\n\nndindex.prototype.kind\n    Read-only property returning the ndarray index kind.\n\n    Returns\n    -------\n    out: string\n        Index kind.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x, { 'kind': 'cartesian' } );\n    > idx.kind\n    'cartesian'\n\n\nndindex.prototype.type\n    Read-only property returning the ndarray index type.\n\n    Returns\n    -------\n    out: string\n        Index type.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.type\n    <string>\n\n\nndindex.prototype.toString()\n    Serializes an instance as a string.\n\n    Returns\n    -------\n    str: string\n        Serialized string.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.toString()\n    <string>\n\n\nndindex.prototype.toJSON()\n    Serializes an instance as a JSON object.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.toJSON()\n    { 'type': 'ndindex', ... }\n\n    See Also\n    --------\n    array, ndarray, FancyArray, ndslice, ndarray2fancy\n","ndindex.free":"\nndindex.free( id )\n    Frees the instance associated with a provided identifier.\n\n    Parameters\n    ----------\n    id: string\n        Instance identifier.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an instance was successfully freed.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > ndindex.free( idx.id )\n    <boolean>","ndindex.get":"\nndindex.get( id )\n    Returns the ndarray associated with the instance having a provided\n    identifier.\n\n    Parameters\n    ----------\n    id: string\n        Instance identifier.\n\n    Returns\n    -------\n    out: Object\n        Object containing ndarray data.\n\n    out.data: ndarray\n        The underlying ndarray associated with the provided identifier.\n\n    out.type: string\n        The type of ndarray index.\n\n    out.dtype: string\n        The data type of the underlying ndarray.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > ndindex.get( idx.id )\n    {...}","ndindex.cartesianIndex":"\nndindex.cartesianIndex( x[, options] )\n    Returns an ndarray index containing Cartesian indices.\n\n    This is a convenience method for calling `ndindex` with `kind` set to\n    'cartesian'.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.persist: boolean (optional)\n        Boolean indicating whether to continue persisting an index object after\n        first usage. Default: false.\n\n    Returns\n    -------\n    out: ndindex\n        Index instance.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = ndindex.cartesianIndex( x );","ndindex.linearIndex":"\nndindex.linearIndex( x[, options] )\n    Returns an ndarray index for indices representing locations in linear\n    memory.\n\n    This is a convenience method for calling `ndindex` with `kind` set to\n    'linear'.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.persist: boolean (optional)\n        Boolean indicating whether to continue persisting an index object after\n        first usage. Default: false.\n\n    Returns\n    -------\n    out: ndindex\n        Index instance.\n\n    Examples\n    --------\n    > var x = ndempty( [ 5 ], { 'dtype': 'int32' } );\n    > var idx = ndindex.linearIndex( x );","ndindex.prototype.data":"\nndindex.prototype.data\n    Read-only property returning an ndarray view of the underlying index\n    ndarray.\n\n    Returns\n    -------\n    out: ndarray\n        Array data.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.data\n    <ndarray>","ndindex.prototype.dtype":"\nndindex.prototype.dtype\n    Read-only property returning the underlying data type of the index ndarray.\n\n    Returns\n    -------\n    out: string\n        Array data type.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.dtype\n    'int32'","ndindex.prototype.id":"\nndindex.prototype.id\n    Read-only property returning the unique identifier associated with an\n    instance.\n\n    Returns\n    -------\n    out: string\n        String identifier.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.id\n    <string>","ndindex.prototype.isCached":"\nndindex.prototype.isCached\n    Read-only property returning a boolean indicating whether an ndarray index\n    is actively cached.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an ndarray index is actively cached.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.isCached\n    true","ndindex.prototype.kind":"\nndindex.prototype.kind\n    Read-only property returning the ndarray index kind.\n\n    Returns\n    -------\n    out: string\n        Index kind.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x, { 'kind': 'cartesian' } );\n    > idx.kind\n    'cartesian'","ndindex.prototype.type":"\nndindex.prototype.type\n    Read-only property returning the ndarray index type.\n\n    Returns\n    -------\n    out: string\n        Index type.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.type\n    <string>","ndindex.prototype.toString":"\nndindex.prototype.toString()\n    Serializes an instance as a string.\n\n    Returns\n    -------\n    str: string\n        Serialized string.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.toString()\n    <string>","ndindex.prototype.toJSON":"\nndindex.prototype.toJSON()\n    Serializes an instance as a JSON object.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.toJSON()\n    { 'type': 'ndindex', ... }\n\n    See Also\n    --------\n    array, ndarray, FancyArray, ndslice, ndarray2fancy","nditerColumnEntries":"\nnditerColumnEntries( x[, options] )\n    Returns an iterator which returns [index, column] pairs for each column in a\n    matrix (or stack of matrices).\n\n    Each returned index is a Cartesian index (i.e., an array of subscripts/\n    dimension indices). A dimension index equal to `null` indicates that all\n    values along the respective dimension are included in the returned ndarray.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    options: Object (optional)\n        Options.\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether returned ndarray views should be read-only.\n        If the input ndarray is read-only, setting this option to `false` raises\n        an exception. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > var it = nditerColumnEntries( x );\n    > var v = it.next().value;\n    > v[ 0 ]\n    [ null, 0 ]\n    > ndarray2array( v[ 1 ] )\n    [ 1, 3 ]\n    > v = it.next().value;\n    > v[ 0 ]\n    [ null, 1 ]\n    > ndarray2array( v[ 1 ] )\n    [ 2, 4 ]\n\n    See Also\n    --------\n    nditerColumns, nditerEntries, nditerRowEntries, ndslice\n","nditerColumns":"\nnditerColumns( x[, options] )\n    Returns an iterator which iterates over each column in a matrix (or stack of\n    matrices).\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray for which to create the iterator.\n\n    options: Object (optional)\n        Options.\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether returned ndarray views should be read-only.\n        If the input ndarray is read-only, setting this option to `false` raises\n        an exception. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > var it = nditerColumns( x );\n    > var v = it.next().value;\n    > ndarray2array( v )\n    [ 1, 3 ]\n    > v = it.next().value;\n    > ndarray2array( v )\n    [ 2, 4 ]\n\n    See Also\n    --------\n    nditerColumnEntries, nditerRows, ndslice\n","nditerEntries":"\nnditerEntries( x[, options] )\n    Returns an iterator which returns [index, value] pairs for each element in a\n    provided ndarray.\n\n    Each returned index is a Cartesian index (i.e., an array of subscripts/\n    dimension indices).\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    options: Object (optional)\n        Options.\n\n    options.order: string (optional)\n        Index iteration order. By default, the returned iterator returns values\n        according to the layout order of the provided array. Accordingly, for\n        row-major input arrays, the last dimension indices increment fastest.\n        For column-major input arrays, the first dimension indices increment\n        fastest. To override the inferred order and ensure that indices\n        increment in a specific manner, regardless of the input array's layout\n        order, explicitly set the iteration order. Note, however, that iterating\n        according to an order which does not match that of the input array may,\n        in some circumstances, result in performance degradation due to cache\n        misses. Must be either 'row-major' or 'column-major'.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > var it = nditerEntries( x );\n    > var v = it.next().value\n    [ [ 0, 0 ], 1 ]\n    > v = it.next().value\n    [ [ 0, 1 ], 2 ]\n\n    See Also\n    --------\n    ndarray, nditerIndices, nditerValues\n","nditerIndices":"\nnditerIndices( shape[, options] )\n    Returns an iterator which returns indices for use indexing into an ndarray\n    having a specified shape.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Input shape.\n\n    options: Object (optional)\n        Options.\n\n    options.order: string (optional)\n        Index iteration order. By default, the returned iterator iterates over\n        the last dimensions first, thus corresponding to iteration over\n        contiguous data stored in row-major order. Must be either 'row-major'\n        or 'column-major'.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > var it = nditerIndices( x.shape );\n    > var v = it.next().value\n    [ 0, 0 ]\n    > v = it.next().value\n    [ 0, 1 ]\n\n    See Also\n    --------\n    ndarray, nditerEntries, nditerValues\n","nditerInterleaveSubarrays":"\nnditerInterleaveSubarrays( arr, ndims )\n    Returns an iterator which iterates over interleaved subarrays.\n\n    For input ndarrays supporting read-only views, the function returns\n    *read-only* views of interleaved subarrays. As input ndarrays may be\n    broadcasted, a view is typically *not* contiguous. As more than one element\n    of a returned view may refer to the same memory location, writing to a view\n    may affect multiple elements. If you need to write to a subarray, copy the\n    subarray before attempting mutation.\n\n    The function throws an error if a provided broadcast-incompatible ndarrays.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    arr: ArrayLike<ndarray>\n        Input ndarrays. All ndarrays must be broadcast-compatible. After\n        broadcasting, each broadcasted input ndarray must have at least\n        `ndims+1` dimensions.\n\n    ndims: integer\n        Number of dimensions to stack after broadcasting.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n    > var it = nditerInterleaveSubarrays( [ x, x ], 2 );\n    > var v = it.next().value;\n    > ndarray2array( v )\n    [ [ 1, 2 ], [ 3, 4 ] ]\n\n    See Also\n    --------\n    nditerSubarrays, ndslice\n","nditerMatrices":"\nnditerMatrices( x[, options] )\n    Returns an iterator which iterates over each matrix in a stack of matrices.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray for which to create the iterator.\n\n    options: Object (optional)\n        Options.\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether returned ndarray views should be read-only.\n        If the input ndarray is read-only, setting this option to `false` raises\n        an exception. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n    > var it = nditerMatrices( x );\n    > var v = it.next().value;\n    > ndarray2array( v )\n    [ [ 1, 2 ], [ 3, 4 ] ]\n\n    See Also\n    --------\n    nditerColumns, nditerMatrixEntries, nditerRows, ndslice\n","nditerMatrixEntries":"\nnditerMatrixEntries( x[, options] )\n    Returns an iterator which returns [index, matrix] pairs for each matrix in a\n    stack of matrices.\n\n    Each returned index is a Cartesian index (i.e., an array of subscripts/\n    dimension indices). A dimension index equal to `null` indicates that all\n    values along the respective dimension are included in the returned ndarray.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    options: Object (optional)\n        Options.\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether returned ndarray views should be read-only.\n        If the input ndarray is read-only, setting this option to `false` raises\n        an exception. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n    > var it = nditerMatrixEntries( x );\n    > var v = it.next().value;\n    > v[ 0 ]\n    [ 0, null, null ]\n    > ndarray2array( v[ 1 ] )\n    [ [ 1, 2 ], [ 3, 4 ] ]\n\n    See Also\n    --------\n    nditerColumnEntries, nditerEntries, nditerMatrices, nditerRowEntries, ndslice\n","nditerRowEntries":"\nnditerRowEntries( x[, options] )\n    Returns an iterator which returns [index, row] pairs for each row in a\n    matrix (or stack of matrices).\n\n    Each returned index is a Cartesian index (i.e., an array of subscripts/\n    dimension indices). A dimension index equal to `null` indicates that all\n    values along the respective dimension are included in the returned ndarray.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    options: Object (optional)\n        Options.\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether returned ndarray views should be read-only.\n        If the input ndarray is read-only, setting this option to `false` raises\n        an exception. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > var it = nditerRowEntries( x );\n    > var v = it.next().value;\n    > v[ 0 ]\n    [ 0, null ]\n    > ndarray2array( v[ 1 ] )\n    [ 1, 2 ]\n    > v = it.next().value;\n    > v[ 0 ]\n    [ 1, null ]\n    > ndarray2array( v[ 1 ] )\n    [ 3, 4 ]\n\n    See Also\n    --------\n    nditerColumnEntries, nditerEntries, nditerRows, ndslice\n","nditerRows":"\nnditerRows( x[, options] )\n    Returns an iterator which iterates over each row in a matrix (or stack of\n    matrices).\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray for which to create the iterator.\n\n    options: Object (optional)\n        Options.\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether returned ndarray views should be read-only.\n        If the input ndarray is read-only, setting this option to `false` raises\n        an exception. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > var it = nditerRows( x );\n    > var v = it.next().value;\n    > ndarray2array( v )\n    [ 1, 2 ]\n    > v = it.next().value;\n    > ndarray2array( v )\n    [ 3, 4 ]\n\n    See Also\n    --------\n    nditerColumns, nditerRowEntries, ndslice\n","nditerSelectDimension":"\nnditerSelectDimension( x, dim[, options] )\n    Returns an iterator which iterates over each view along a specified\n    dimension.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray for which to create the iterator.\n\n    dim: integer\n        Dimension index. If less than zero, the index is resolved relative to\n        the last dimension, with the last dimension corresponding to the value\n        `-1`.\n\n    options: Object (optional)\n        Options.\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether returned ndarray views should be read-only.\n        If the input ndarray is read-only, setting this option to `false` raises\n        an exception. Default: true.\n\n    options.keepdim: boolean (optional)\n        Boolean indicating whether returned views should include the selected\n        dimension as a singleton dimension. Including the selected dimension as\n        a singleton dimension can be useful when wanting to ensure that returned\n        views remain broadcast compatible with the input ndarray. Default:\n        false.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n    > var it = nditerSelectDimension( x, 0 );\n    > var v = it.next().value;\n    > ndarray2array( v )\n    [ [ 1, 2 ], [ 3, 4 ] ]\n\n    See Also\n    --------\n    nditerColumns, nditerMatrices, nditerRows, ndslice\n","nditerStacks":"\nnditerStacks( x, dims[, options] )\n    Returns an iterator which iterates over each subarray in a stack of\n    subarrays according to a list of specified stack dimensions.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray for which to create the iterator. Must have at least\n        `dims.length+1` dimensions.\n\n    dims: Array<integer>\n        Indices of dimensions to stack. If a dimension index is less than zero,\n        the index is resolved relative to the last dimension, with the last\n        dimension corresponding to the value `-1`. The list of indices must be\n        unique and resolve to dimension indices sorted in ascending order.\n\n    options: Object (optional)\n        Options.\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether returned ndarray views should be read-only.\n        If the input ndarray is read-only, setting this option to `false` raises\n        an exception. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n    > var it = nditerStacks( x, [ 1, 2 ] );\n    > var v = it.next().value;\n    > ndarray2array( v )\n    [ [ 1, 2 ], [ 3, 4 ] ]\n\n    See Also\n    --------\n    nditerColumns, nditerMatrices, nditerRows, nditerSubarrays, ndslice\n","nditerSubarrays":"\nnditerSubarrays( x, ndims[, options] )\n    Returns an iterator which iterates over each subarray in a stack of\n    subarrays.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray for which to create the iterator. Must have at least\n        `ndims+1` dimensions.\n\n    ndims: integer\n        Number of dimensions to stack.\n\n    options: Object (optional)\n        Options.\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether returned ndarray views should be read-only.\n        If the input ndarray is read-only, setting this option to `false` raises\n        an exception. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n    > var it = nditerSubarrays( x, 2 );\n    > var v = it.next().value;\n    > ndarray2array( v )\n    [ [ 1, 2 ], [ 3, 4 ] ]\n\n    See Also\n    --------\n    nditerColumns, nditerMatrices, nditerRows, nditerStacks, ndslice\n","nditerValues":"\nnditerValues( x[, options] )\n    Returns an iterator which returns individual elements from a provided\n    ndarray.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    options: Object (optional)\n        Options.\n\n    options.order: string (optional)\n        Index iteration order. By default, the returned iterator returns values\n        according to the layout order of the provided array. Accordingly, for\n        row-major input arrays, the last dimension indices increment fastest.\n        For column-major input arrays, the first dimension indices increment\n        fastest. To override the inferred order and ensure that indices\n        increment in a specific manner, regardless of the input array's layout\n        order, explicitly set the iteration order. Note, however, that iterating\n        according to an order which does not match that of the input array may,\n        in some circumstances, result in performance degradation due to cache\n        misses. Must be either 'row-major' or 'column-major'.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > var it = nditerValues( x );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    ndarray, nditerEntries, nditerIndices\n","ndmap":"\nndmap( x[, options], fcn[, thisArg] )\n    Applies a callback function to elements in an input ndarray and assigns\n    results to elements in a new output ndarray.\n\n    The callback function is provided the following arguments:\n\n    - value: current array element.\n    - indices: current array element indices.\n    - arr: the input ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.dtype: string (optional)\n        Output ndarray data type. Overrides using the input array's inferred\n        data type.\n\n    fcn: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback function execution context.\n\n    Examples\n    --------\n    > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n    > function f( v ) { return v*10.0; };\n    > var y = ndmap( x, f );\n    > ndarray2array( y )\n    [ [ 10.0, 20.0 ], [ 30.0, 40.0 ] ]\n\n    See Also\n    --------\n    ndfilter, ndfilterMap, ndforEach, ndslice","ndreject":"\nndreject( x[, options], predicate[, thisArg] )\n    Returns a shallow copy of an ndarray containing only those elements which\n    fail a test implemented by a predicate function.\n\n    The predicate function is provided the following arguments:\n\n    - value: current array element.\n    - indices: current array element indices.\n    - arr: the input ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.dtype: string (optional)\n        Output ndarray data type. Overrides using the input array's inferred\n        data type.\n\n    options.order: string (optional)\n        Index iteration order. By default, the function iterates over elements\n        according to the layout order of the provided array. Accordingly, for\n        row-major input arrays, the last dimension indices increment fastest.\n        For column-major input arrays, the first dimension indices increment\n        fastest. To override the inferred order and ensure that indices\n        increment in a specific manner, regardless of the input array's layout\n        order, explicitly set the iteration order. Note, however, that iterating\n        according to an order which does not match that of the input array may,\n        in some circumstances, result in performance degradation due to cache\n        misses. Must be either 'row-major' or 'column-major'.\n\n    predicate: Function\n        Predicate function.\n\n    thisArg: any (optional)\n        Predicate function execution context.\n\n    Examples\n    --------\n    > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n    > function f( v ) { return v <= 2.0; };\n    > var y = ndreject( x, f );\n    > ndarray2array( y )\n    [ 3.0, 4.0 ]\n\n    See Also\n    --------\n    ndfilter, ndfilterMap, ndmap, ndslice","ndslice":"\nndslice( x, ...s[, options] )\n    Returns a read-only view of an input ndarray.\n\n    The function supports three (mutually exclusive) means of providing slice\n    arguments:\n\n    1. Providing a single MultiSlice object.\n    2. Providing a single array containing slice arguments.\n    3. Providing slice arguments as separate arguments.\n\n    An individual slice argument must be either a Slice, an integer, null, or\n    undefined.\n\n    In all cases, the number of slice dimensions must match the number of array\n    dimensions.\n\n    If providing a MultiSlice object or an array of slice arguments, no other\n    slice arguments should be provided.\n\n    Mixing function invocation styles (e.g., providing multiple MultiSlice\n    objects or providing an array of slice arguments followed by additional\n    slice arguments) is not supported.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    s: ...MultiSlice|Slice|null|undefined|integer|ArrayLike\n        Slice arguments.\n\n    options: Object (optional)\n        Options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking.\n        Default: true.\n\n    Returns\n    -------\n    out: ndarray\n        Output array view.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n    <ndarray>\n    > x.shape\n    [ 2, 2 ]\n    > var s = new MultiSlice( null, 1 )\n    <MultiSlice>\n    > var y = ndslice( x, s )\n    <ndarray>\n    > y.shape\n    [ 2 ]\n    > ndarray2array( y )\n    [ 2, 4 ]\n\n    See Also\n    --------\n    array, ndat, ndarray, ndsliceAssign, ndsliceDimension\n","ndsliceAssign":"\nndsliceAssign( x, y, ...s[, options] )\n    Assigns element values from a broadcasted input ndarray to corresponding\n    elements in an output ndarray view.\n\n    The function supports three (mutually exclusive) means of providing slice\n    arguments:\n\n    1. Providing a single MultiSlice object.\n    2. Providing a single array containing slice arguments.\n    3. Providing slice arguments as separate arguments.\n\n    An individual slice argument must be either a Slice, an integer, null, or\n    undefined.\n\n    In all cases, the number of slice dimensions must match the number of output\n    array dimensions.\n\n    If providing a MultiSlice object or an array of slice arguments, no other\n    slice arguments should be provided.\n\n    Mixing function invocation styles (e.g., providing multiple MultiSlice\n    objects or providing an array of slice arguments followed by additional\n    slice arguments) is not supported.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array. The input array must be broadcast compatible with the\n        output array view and must have a data type which can be safely cast to\n        the output array data type. Floating-point data types (both real and\n        complex) are allowed to downcast to a lower precision data type of the\n        same kind (e.g., element values from a 'float64' input array can be\n        assigned to corresponding elements in a 'float32' output array).\n\n    y: ndarray\n        Output array. The output array must be writable.\n\n    s: ...MultiSlice|Slice|null|undefined|integer|ArrayLike\n        Slice arguments.\n\n    options: Object (optional)\n        Options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking.\n        Default: true.\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var y = ndzeros( [ 2, 2 ] )\n    <ndarray>\n    > var x = scalar2ndarray( 3.0 )\n    <ndarray>\n    > var s = new MultiSlice( null, 1 )\n    <MultiSlice>\n    > var out = ndsliceAssign( x, y, s )\n    <ndarray>\n    > var bool = ( out === y )\n    true\n    > ndarray2array( y )\n    [ [ 0.0, 3.0 ], [ 0.0, 3.0 ] ]\n\n    See Also\n    --------\n    array, ndarray, ndslice\n","ndsliceDimension":"\nndsliceDimension( x, dim, slice[, options] )\n    Returns a read-only view of an input ndarray when sliced along a specified\n    dimension.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    dim: integer\n        Index of dimension to slice. If less than zero, the index is resolved\n        relative to the last dimension, with the last dimension corresponding to\n        the value `-1`.\n\n    slice: Slice|integer|null|undefined\n        Slice object or an integer. If provided `null` or `undefined`, the\n        returned view includes all elements along a specified dimension. If\n        provided an integer less than zero, the corresponding element along the\n        specified dimension is resolved relative to the last element along that\n        dimension. For negative integers, the last element corresponds to the\n        value `-1`.\n\n    options: Object (optional)\n        Options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking.\n        Default: true.\n\n    Returns\n    -------\n    out: ndarray\n        Output array view.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n    <ndarray>\n    > x.shape\n    [ 2, 2 ]\n    > var y = ndsliceDimension( x, 1, 1 )\n    <ndarray>\n    > y.shape\n    [ 2 ]\n    > ndarray2array( y )\n    [ 2, 4 ]\n\n    See Also\n    --------\n    array, ndarray, ndslice, ndsliceDimensionFrom, ndsliceDimensionTo\n","ndsliceDimensionFrom":"\nndsliceDimensionFrom( x, dim, start[, options] )\n    Returns a read-only shifted view of an input ndarray along a specified\n    dimension.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    dim: integer\n        Index of dimension to slice. If less than zero, the index is resolved\n        relative to the last dimension, with the last dimension corresponding to\n        the value `-1`.\n\n    start: integer\n        Starting index (inclusive). If less than zero, the corresponding element\n        along the specified dimension is resolved relative to the last element\n        along that dimension. For negative integers, the last element\n        corresponds to the value `-1`.\n\n    options: Object (optional)\n        Options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking.\n        Default: true.\n\n    Returns\n    -------\n    out: ndarray\n        Output array view.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n    <ndarray>\n    > x.shape\n    [ 2, 2 ]\n    > var y = ndsliceDimensionFrom( x, 1, 1 )\n    <ndarray>\n    > y.shape\n    [ 2, 1 ]\n    > ndarray2array( y )\n    [ [ 2 ], [ 4 ] ]\n\n    See Also\n    --------\n    array, ndarray, ndslice, ndsliceDimension, ndsliceDimensionTo, ndsliceFrom\n","ndsliceDimensionTo":"\nndsliceDimensionTo( x, dim, stop[, options] )\n    Returns a read-only truncated view of an input ndarray along a specified\n    dimension.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    dim: integer\n        Index of dimension to slice. If less than zero, the index is resolved\n        relative to the last dimension, with the last dimension corresponding to\n        the value `-1`.\n\n    stop: integer\n        Ending index (exclusive). If less than zero, the corresponding element\n        along the specified dimension is resolved relative to the last element\n        along that dimension. For negative integers, the last element\n        corresponds to the value `-1`.\n\n    options: Object (optional)\n        Options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking.\n        Default: true.\n\n    Returns\n    -------\n    out: ndarray\n        Output array view.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n    <ndarray>\n    > x.shape\n    [ 2, 2 ]\n    > var y = ndsliceDimensionTo( x, 1, 1 )\n    <ndarray>\n    > y.shape\n    [ 2, 1 ]\n    > ndarray2array( y )\n    [ [ 1 ], [ 3 ] ]\n\n    See Also\n    --------\n    array, ndarray, ndslice, ndsliceDimension, ndsliceDimensionFrom, ndsliceTo\n","ndsliceFrom":"\nndsliceFrom( x, ...start[, options] )\n    Returns a read-only shifted view of an input ndarray.\n\n    The function supports two (mutually exclusive) means of providing starting\n    indices:\n\n    1. Providing a single array containing start arguments.\n    2. Providing start arguments as separate arguments.\n\n    An individual start argument must be either an integer, null, or undefined.\n\n    In all cases, the number of start indices must match the number of array\n    dimensions.\n\n    If providing an array of start arguments, no other start arguments should be\n    provided.\n\n    Mixing function invocation styles (e.g., providing an array of start\n    arguments followed by additional start arguments) is not supported.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    start: ...null|void|integer\n        Starting indices (inclusive). If an element is either `null` or\n        `undefined`, the function returns a view containing all elements along\n        that dimension. A negative integer indicates to resolve a starting index\n        relative to the last element along a corresponding dimension, with the\n        last element having index `-1`.\n\n    options: Object (optional)\n        Options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking.\n        Default: true.\n\n    Returns\n    -------\n    out: ndarray\n        Output array view.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n    <ndarray>\n    > x.shape\n    [ 2, 2 ]\n    > var y = ndsliceFrom( x, 0, 1 )\n    <ndarray>\n    > y.shape\n    [ 2, 1 ]\n    > ndarray2array( y )\n    [ [ 2 ], [ 4 ] ]\n\n    See Also\n    --------\n    array, ndarray, ndslice, ndsliceDimensionFrom, ndsliceTo\n","ndsliceTo":"\nndsliceTo( x, ...stop[, options] )\n    Returns a read-only truncated view of an input ndarray.\n\n    The function supports two (mutually exclusive) means of providing ending\n    indices:\n\n    1. Providing a single array containing stop arguments.\n    2. Providing stop arguments as separate arguments.\n\n    An individual stop argument must be either an integer, null, or undefined.\n\n    In all cases, the number of stop indices must match the number of array\n    dimensions.\n\n    If providing an array of stop arguments, no other stop arguments should be\n    provided.\n\n    Mixing function invocation styles (e.g., providing an array of stop\n    arguments followed by additional stop arguments) is not supported.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    stop: ...null|void|integer\n        Ending indices (exclusive). If an ending index is either `null` or\n        `undefined`, the function returns a view containing all elements along\n        that dimension. A negative integer indicates to resolve an ending index\n        relative to the last element along a corresponding dimension, with the\n        last element having index `-1`.\n\n    options: Object (optional)\n        Options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking.\n        Default: true.\n\n    Returns\n    -------\n    out: ndarray\n        Output array view.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n    <ndarray>\n    > x.shape\n    [ 2, 2 ]\n    > var y = ndsliceTo( x, 1, 1 )\n    <ndarray>\n    > y.shape\n    [ 1, 1 ]\n    > ndarray2array( y )\n    [ [ 1 ] ]\n\n    See Also\n    --------\n    array, ndarray, ndslice, ndsliceDimensionTo, ndsliceFrom\n","ndzeros":"\nndzeros( shape[, options] )\n    Returns a zero-filled ndarray having a specified shape and data type.\n\n    Parameters\n    ----------\n    shape: ArrayLikeObject<integer>|integer\n        Array shape.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Underlying data type. Must be a numeric data type or \"generic\". Default:\n        'float64'.\n\n    options.order: string (optional)\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran-style). Default: 'row-major'.\n\n    options.mode: string (optional)\n        Specifies how to handle indices which exceed array dimensions. If equal\n        to 'throw', an ndarray instance throws an error when an index exceeds\n        array dimensions. If equal to 'normalize', an ndarray instance\n        normalizes negative indices and throws an error when an index exceeds\n        array dimensions. If equal to 'wrap', an ndarray instance wraps around\n        indices exceeding array dimensions using modulo arithmetic. If equal to\n        'clamp', an ndarray instance sets an index exceeding array dimensions\n        to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n    options.submode: Array<string> (optional)\n        Specifies how to handle subscripts which exceed array dimensions. If a\n        mode for a corresponding dimension is equal to 'throw', an ndarray\n        instance throws an error when a subscript exceeds array dimensions. If\n        equal to 'normalize', an ndarray instance normalizes negative\n        subscripts and throws an error when a subscript exceeds array\n        dimensions. If equal to 'wrap', an ndarray instance wraps around\n        subscripts exceeding array dimensions using modulo arithmetic. If equal\n        to 'clamp', an ndarray instance sets a subscript exceeding array\n        dimensions to either `0` (minimum index) or the maximum index. If the\n        number of modes is fewer than the number of dimensions, the function\n        recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether an array should be read-only. Default: false.\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var arr = ndzeros( [ 2, 2 ] )\n    <ndarray>\n    > var sh = arr.shape\n    [ 2, 2 ]\n    > var dt = arr.dtype\n    'float64'\n\n    See Also\n    --------\n    ndempty, ndzerosLike\n","ndzerosLike":"\nndzerosLike( x[, options] )\n    Returns a zero-filled ndarray having the same shape and data type as a\n    provided input ndarray.\n\n    The function infers the following attributes from the input array:\n\n    - shape: array shape.\n    - dtype: underlying array data type.\n    - order: whether the array order is row-major (C-style) or column-major\n      (Fortran-style).\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    options: Object (optional)\n        Options.\n\n    options.shape: ArrayLikeObject<integer>|integer (optional)\n        Array shape. Overrides the input array's inferred shape.\n\n    options.dtype: string (optional)\n        Array data type. Overrides the input array's inferred data type.\n\n    options.order: string (optional)\n        Array order (either 'row-major' (C-style) or 'column-major' (Fortran-\n        style)). Overrides the input array's inferred order.\n\n    options.mode: string (optional)\n        Specifies how to handle indices which exceed array dimensions. If equal\n        to 'throw', an ndarray instance throws an error when an index exceeds\n        array dimensions. If equal to 'normalize', an ndarray instance\n        normalizes negative indices and throws an error when an index exceeds\n        array dimensions. If equal to 'wrap', an ndarray instance wraps around\n        indices exceeding array dimensions using modulo arithmetic. If equal to\n        'clamp', an ndarray instance sets an index exceeding array dimensions\n        to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n    options.submode: Array<string> (optional)\n        Specifies how to handle subscripts which exceed array dimensions. If a\n        mode for a corresponding dimension is equal to 'throw', an ndarray\n        instance throws an error when a subscript exceeds array dimensions. If\n        equal to 'normalize', an ndarray instance normalizes negative\n        subscripts and throws an error when a subscript exceeds array\n        dimensions. If equal to 'wrap', an ndarray instance wraps around\n        subscripts exceeding array dimensions using modulo arithmetic. If equal\n        to 'clamp', an ndarray instance sets a subscript exceeding array\n        dimensions to either `0` (minimum index) or the maximum index. If the\n        number of modes is fewer than the number of dimensions, the function\n        recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether an array should be read-only. Default: false.\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n    <ndarray>\n    > var sh = x.shape\n    [ 2, 2 ]\n    > var dt = x.dtype\n    'float64'\n    > var y = ndzerosLike( x )\n    <ndarray>\n    > sh = y.shape\n    [ 2, 2 ]\n    > dt = y.dtype\n    'float64'\n\n    See Also\n    --------\n    ndemptyLike, ndzeros\n","nextGraphemeClusterBreak":"\nnextGraphemeClusterBreak( str[, fromIndex] )\n    Returns the next extended grapheme cluster break in a string after a\n    specified position.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    fromIndex: integer (optional)\n        Position. Default: 0.\n\n    Returns\n    -------\n    out: integer\n        Next extended grapheme cluster break position.\n\n    Examples\n    --------\n    > var out = nextGraphemeClusterBreak( 'last man standing', 4 )\n    5\n    > out = nextGraphemeClusterBreak( 'presidential election', 8 )\n    9\n    > out = nextGraphemeClusterBreak( 'अनुच्छेद', 1 )\n    3\n    > out = nextGraphemeClusterBreak( '🌷' )\n    -1\n\n    See Also\n    --------\n    numGraphemeClusters, prevGraphemeClusterBreak","nextTick":"\nnextTick( clbk[, ...args] )\n    Adds a callback to the \"next tick queue\".\n\n    The queue is fully drained after the current operation on the JavaScript\n    stack runs to completion and before the event loop is allowed to continue.\n\n    Parameters\n    ----------\n    clbk: Function\n        Callback to invoke.\n\n    ...args: any (optional)\n        Arguments to provide to the callback upon invocation.\n\n    Examples\n    --------\n    > function f() { console.log( 'beep' ); };\n    > nextTick( f )\n\n","NIGHTINGALES_ROSE":"\nNIGHTINGALES_ROSE()\n    Returns data for Nightingale's famous polar area diagram.\n\n    Returns\n    -------\n    out: Array<Object>\n        Nightingale's data.\n\n    Examples\n    --------\n    > var data = NIGHTINGALES_ROSE()\n    [{...}, {...}, ...]\n\n    References\n    ----------\n    - Nightingale, Florence. 1859. *A contribution to the sanitary history of\n    the British army during the late war with Russia*. London, United Kingdom:\n    John W. Parker and Son.<https://curiosity.lib.harvard.edu/contagion/\n    catalog/36-990101646750203941>.\n\n","NINF":"\nNINF\n    Double-precision floating-point negative infinity.\n\n    Examples\n    --------\n    > NINF\n    -Infinity\n\n    See Also\n    --------\n    FLOAT16_NINF, FLOAT32_NINF, PINF\n","NODE_VERSION":"\nNODE_VERSION\n    Node version.\n\n    Examples\n    --------\n    > NODE_VERSION\n    <string>\n\n","none":"\nnone( collection )\n    Tests whether all elements in a collection are falsy.\n\n    The function immediately returns upon encountering a truthy value.\n\n    If provided an empty collection, the function returns `true`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if all elements are falsy; otherwise, the\n        function returns `false`.\n\n    Examples\n    --------\n    > var arr = [ 0, 0, 0, 0, 0 ];\n    > var bool = none( arr )\n    true\n\n    See Also\n    --------\n    any, every, forEach, noneBy, some\n","noneBy":"\nnoneBy( collection, predicate[, thisArg ] )\n    Tests whether all elements in a collection fail a test implemented by a\n    predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    The function immediately returns upon encountering a truthy return value.\n\n    If provided an empty collection, the function returns `true`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns a falsy\n        value for all elements; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function negative( v ) { return ( v < 0 ); };\n    > var arr = [ 1, 2, 3, 4 ];\n    > var bool = noneBy( arr, negative )\n    true\n\n    See Also\n    --------\n    anyBy, everyBy, forEach, none, noneByRight, someBy\n","noneByAsync":"\nnoneByAsync( collection, [options,] predicate, done )\n    Tests whether all elements in a collection fail a test implemented by a\n    predicate function.\n\n    When invoked, the predicate function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If the\n    predicate function accepts two arguments, the predicate function is\n    provided:\n\n    - value\n    - next\n\n    If the predicate function accepts three arguments, the predicate function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other predicate function signature, the predicate function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - result: test result.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    The function immediately returns upon encountering a truthy `result` value\n    and calls the `done` callback with `null` as the first argument and `false`\n    as the second argument.\n\n    If all elements fail, the function calls the `done` callback with `null` as\n    the first argument and `true` as the second argument.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > noneByAsync( arr, predicate, done )\n    1000\n    2500\n    3000\n    true\n\n    // Limit number of concurrent invocations:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 3000, 2500, 1000 ];\n    > noneByAsync( arr, opts, predicate, done )\n    2500\n    3000\n    1000\n    true\n\n    // Process sequentially:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 3000, 2500, 1000 ];\n    > noneByAsync( arr, opts, predicate, done )\n    3000\n    2500\n    1000\n    true\n\n\nnoneByAsync.factory( [options,] predicate )\n    Returns a function which tests whether all elements in a collection fail a\n    test implemented by a predicate function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = noneByAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n\n    See Also\n    --------\n    anyByAsync, everyByAsync, forEachAsync, noneBy, noneByRightAsync, someByAsync\n","noneByAsync.factory":"\nnoneByAsync.factory( [options,] predicate )\n    Returns a function which tests whether all elements in a collection fail a\n    test implemented by a predicate function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = noneByAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n\n    See Also\n    --------\n    anyByAsync, everyByAsync, forEachAsync, noneBy, noneByRightAsync, someByAsync","noneByRight":"\nnoneByRight( collection, predicate[, thisArg ] )\n    Tests whether all elements in a collection fail a test implemented by a\n    predicate function, iterating from right to left.\n\n    The predicate function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    The function immediately returns upon encountering a truthy return value.\n\n    If provided an empty collection, the function returns `true`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns a falsy\n        value for all elements; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function positive( v ) { return ( v > 0 ); };\n    > var arr = [ -1, -2, -3, -4 ];\n    > var bool = noneByRight( arr, positive )\n    true\n\n    See Also\n    --------\n    anyByRight, everyByRight, forEachRight, none, noneBy, someByRight\n","noneByRightAsync":"\nnoneByRightAsync( collection, [options,] predicate, done )\n    Tests whether all elements in a collection fail a test implemented by a\n    predicate function, iterating from right to left.\n\n    When invoked, the predicate function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If the\n    predicate function accepts two arguments, the predicate function is\n    provided:\n\n    - value\n    - next\n\n    If the predicate function accepts three arguments, the predicate function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other predicate function signature, the predicate function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - result: test result.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    The function immediately returns upon encountering a truthy `result` value\n    and calls the `done` callback with `null` as the first argument and `false`\n    as the second argument.\n\n    If all elements fail, the function calls the `done` callback with `null` as\n    the first argument and `true` as the second argument.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > noneByRightAsync( arr, predicate, done )\n    1000\n    2500\n    3000\n    true\n\n    // Limit number of concurrent invocations:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 1000, 2500, 3000 ];\n    > noneByRightAsync( arr, opts, predicate, done )\n    2500\n    3000\n    1000\n    true\n\n    // Process sequentially:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 1000, 2500, 3000 ];\n    > noneByRightAsync( arr, opts, predicate, done )\n    3000\n    2500\n    1000\n    true\n\n\nnoneByRightAsync.factory( [options,] predicate )\n    Returns a function which tests whether all elements in a collection fail a\n    test implemented by a predicate function, iterating from right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = noneByRightAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n\n    See Also\n    --------\n    anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByAsync, noneByRight, someByRightAsync\n","noneByRightAsync.factory":"\nnoneByRightAsync.factory( [options,] predicate )\n    Returns a function which tests whether all elements in a collection fail a\n    test implemented by a predicate function, iterating from right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = noneByRightAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n\n    See Also\n    --------\n    anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByAsync, noneByRight, someByRightAsync","noneInBy":"\nnoneInBy( object, predicate[, thisArg ] )\n    Tests whether every property in an object fails a test implemented by a\n    predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: object value.\n    - key: object key.\n    - object: the input object.\n\n    The function immediately returns upon encountering a truthy return value.\n\n    If provided an empty object, the function returns `true`.\n\n    Parameters\n    ----------\n    object: Object\n        Input object over which to iterate.\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns a falsy\n        value for all properties; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function negative( v ) { return ( v < 0 ); };\n    > var obj = { 'a': 1, 'b': 2, 'c': 4 };\n    > var bool = noneInBy( obj, negative )\n    true\n\n    See Also\n    --------\n    anyInBy, everyInBy, forIn, noneBy, someInBy\n","nonEnumerableProperties":"\nnonEnumerableProperties( value )\n    Returns an array of an object's own non-enumerable property names and\n    symbols.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    props: Array\n        List of an object's own non-enumerable properties.\n\n    Examples\n    --------\n    > var obj = {};\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.writable = false;\n    > desc.value = 'boop';\n    > defineProperty( obj, 'beep', desc );\n    > var props = nonEnumerableProperties( obj )\n    [ 'beep' ]\n\n    See Also\n    --------\n    enumerableProperties, inheritedNonEnumerableProperties, nonEnumerablePropertiesIn, properties\n","nonEnumerablePropertiesIn":"\nnonEnumerablePropertiesIn( value )\n    Returns an array of an object's own and inherited non-enumerable property\n    names and symbols.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    props: Array\n        List of an object's own and inherited non-enumerable property names and\n        symbols.\n\n    Examples\n    --------\n    > var props = nonEnumerablePropertiesIn( [] )\n\n    See Also\n    --------\n    enumerablePropertiesIn, inheritedNonEnumerableProperties, nonEnumerableProperties, propertiesIn\n","nonEnumerablePropertyNames":"\nnonEnumerablePropertyNames( value )\n    Returns an array of an object's own non-enumerable property names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's own non-enumerable property names.\n\n    Examples\n    --------\n    > var obj = {};\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.writable = true;\n    > desc.value = 'boop';\n    > defineProperty( obj, 'beep', desc );\n    > var keys = nonEnumerablePropertyNames( obj )\n    e.g., [ 'beep', ... ]\n\n    See Also\n    --------\n    objectKeys, inheritedNonEnumerablePropertyNames, nonEnumerablePropertyNamesIn, nonEnumerablePropertySymbols, propertyNames\n","nonEnumerablePropertyNamesIn":"\nnonEnumerablePropertyNamesIn( value )\n    Returns an array of an object's own and inherited non-enumerable property\n    names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's own and inherited non-enumerable property names.\n\n    Examples\n    --------\n    > var obj = {};\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.writable = true;\n    > desc.value = 'boop';\n    > defineProperty( obj, 'beep', desc );\n    > var keys = nonEnumerablePropertyNamesIn( obj )\n    e.g., [ 'beep', ... ]\n\n    See Also\n    --------\n    keysIn, inheritedNonEnumerablePropertyNames, nonEnumerablePropertyNames, propertyNamesIn\n","nonEnumerablePropertySymbols":"\nnonEnumerablePropertySymbols( value )\n    Returns an array of an object's own non-enumerable symbol properties.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's own non-enumerable symbol properties.\n\n    Examples\n    --------\n    > var obj = {};\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.writable = true;\n    > desc.value = 'boop';\n    > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n    > defineProperty( obj, sym, desc );\n    > var symbols = nonEnumerablePropertySymbols( obj )\n\n    See Also\n    --------\n    enumerablePropertySymbols, inheritedNonEnumerablePropertySymbols, nonEnumerablePropertyNames, nonEnumerablePropertySymbolsIn, propertySymbols\n","nonEnumerablePropertySymbolsIn":"\nnonEnumerablePropertySymbolsIn( value )\n    Returns an array of an object's own and inherited non-enumerable symbol\n    properties.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's own and inherited non-enumerable symbol properties.\n\n    Examples\n    --------\n    > var obj = {};\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.writable = true;\n    > desc.value = 'boop';\n    > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n    > defineProperty( obj, sym, desc );\n    > var symbols = nonEnumerablePropertySymbolsIn( obj )\n\n    See Also\n    --------\n    enumerablePropertySymbolsIn, inheritedNonEnumerablePropertySymbols, nonEnumerablePropertyNamesIn, nonEnumerablePropertySymbols, propertySymbolsIn\n","noneOwnBy":"\nnoneOwnBy( object, predicate[, thisArg ] )\n    Tests whether every own property of an object fails a test implemented\n    by a predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: property value.\n    - index: property key.\n    - object: the input object.\n\n    The function immediately returns upon encountering a truthy return value.\n\n    If provided an empty object, the function returns `true`.\n\n    Parameters\n    ----------\n    object: Object\n        Input object.\n\n    predicate: Function\n        Test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns a falsy\n        value for all own properties; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function isUnderage( v ) { return ( v < 18 ); };\n    > var obj = { 'a': 11, 'b': 12, 'c': 22 };\n    > var bool = noneOwnBy( obj, isUnderage )\n    false\n\n    See Also\n    --------\n    anyOwnBy, everyOwnBy, forOwn, noneBy, someOwnBy\n","nonIndexKeys":"\nnonIndexKeys( obj )\n    Returns an array of an object's own enumerable property names which are not\n    integer indices.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    obj: any\n        Input value.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's own enumerable property names.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; this[0] = 3.14; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var keys = nonIndexKeys( obj )\n    e.g., [ 'beep' ]\n\n    See Also\n    --------\n    objectEntries, objectKeys, objectValues\n","noop":"\nnoop()\n    A function which does nothing.\n\n    Examples\n    --------\n    > noop();\n\n","now":"\nnow()\n    Returns the time in seconds since the epoch.\n\n    The Unix epoch is 00:00:00 UTC on 1 January 1970.\n\n    Returns\n    -------\n    out: integer\n        Time in seconds since the epoch.\n\n    Examples\n    --------\n    > var ts = now()\n    <number>\n\n","NUM_CPUS":"\nNUM_CPUS\n    Number of CPUs.\n\n    In browser environments, the number of CPUs is determined by querying the\n    hardware concurrency API.\n\n    In Node.js environments, the number of CPUs is determined via the `os`\n    module.\n\n    Examples\n    --------\n    > NUM_CPUS\n    <number>\n\n","num2words":"\nnum2words( value[, options] )\n    Converts a number to a word representation.\n\n    Parameters\n    ----------\n    value: integer\n        Input value.\n\n    options: Object (optional)\n        Options.\n\n    options.lang: string (optional)\n        Language code. Supported languages:\n\n        - en: English.\n        - de: German.\n\n        Default: `'en'`.\n\n    Returns\n    -------\n    out: string\n        Word representation of number.\n\n    Examples\n    --------\n    > var out = num2words( 123 )\n    'one hundred twenty-three'\n\n    > out = num2words( 16.31 )\n    'sixteen point three one'\n\n    > out = num2words( 123, { 'lang': 'de' } )\n    'einhundertdreiundzwanzig'\n\n","Number":"\nNumber( value )\n    Returns a Number object.\n\n    This constructor should be used sparingly. Always prefer number primitives.\n\n    Parameters\n    ----------\n    value: number\n        Value to wrap in a Number object.\n\n    Returns\n    -------\n    out: Number\n        Number object.\n\n    Examples\n    --------\n    > var v = new Number( 5 )\n    <Number>\n\n","numel":"\nnumel( x )\n    Returns the number of elements in an ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    Returns\n    -------\n    n: integer\n        Number of elements.\n\n    Examples\n    --------\n    > var n = numel( ndzeros( [ 3, 3, 3 ] ) )\n    27\n\n    See Also\n    --------\n    array, ndarray, numelDimension\n","numelDimension":"\nnumelDimension( x, dim )\n    Returns the size (i.e., number of elements) of a specified dimension for a\n    provided ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    dim: integer\n        Dimension index. If less than zero, the index is resolved relative to\n        the last dimension, with the last dimension corresponding to the value\n        `-1`.\n\n    Returns\n    -------\n    out: integer\n        Dimension size.\n\n    Examples\n    --------\n    > var out = numelDimension( ndzeros( [ 4, 2, 3 ] ), 0 )\n    4\n\n    See Also\n    --------\n    array, ndarray, numel\n","numGraphemeClusters":"\nnumGraphemeClusters( str )\n    Returns the number of grapheme clusters in a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Number of grapheme clusters.\n\n    Examples\n    --------\n    > var out = numGraphemeClusters( 'beep' )\n    4\n    > out = numGraphemeClusters( '🌷' )\n    1\n\n    See Also\n    --------\n    nextGraphemeClusterBreak\n","Object":"\nObject( value )\n    Returns an object.\n\n    If provided `null` or `undefined`, the function returns an empty object.\n\n    If provided an existing object, the function returns the input value\n    unchanged.\n\n    Otherwise, if provided any other value (e.g., a number, string, etc), the\n    function will return an object of the corresponding type.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    out: Object\n        Output object.\n\n    Examples\n    --------\n    > var o = new Object( null )\n    {}\n    > o = new Object( 5.0 )\n    <Number>\n    > o = new Object( 'beep' )\n    <String>\n\nObject.assign( target, ...sources )\n    Assigns enumerable and own properties from source objects to a target\n    object.\n\n    Parameters\n    ----------\n    target: Object\n        Target object.\n\n    sources: ...Object\n        Source objects.\n\n    Returns\n    -------\n    out: Object\n        Target object.\n\n    Examples\n    --------\n    > var o = Object.assign( {}, { 'a': 1 }, { 'b': 2 } )\n    { 'a': 1, 'b': 2 }\n\nObject.create( prototype, properties )\n    Creates a new object with a specified prototype object and properties.\n\n    Parameters\n    ----------\n    prototype: Object\n        Prototype object.\n\n    properties: Object\n        Properties object.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > var o = Object.create( {}, { 'a': { 'value': 1 } } )\n    { 'a': 1 }\n\nObject.defineProperties( obj, properties )\n    Defines properties for an object.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    properties: Object\n        Properties object.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.defineProperties( {}, { 'a': { 'value': 1 } } )\n    { 'a': 1 }\n\nObject.defineProperty( obj, key, descriptor )\n    Defines a property for an object.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    key: string\n        Property key.\n\n    descriptor: Object\n        Property descriptor.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.defineProperty( {}, 'a', {\n        'value': 1,\n        'enumerable': true,\n        'configurable': true,\n        'writable': false\n    })\n    { 'a': 1 }\n\nObject.entries( obj )\n    Returns an array of an object's own enumerable string-keyed property\n    [key, value] pairs.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Array\n        Array of [key, value] pairs.\n\n    Examples\n    --------\n    > var o = Object.entries( { 'a': 1, 'b': 2 } )\n    [ [ 'a', 1 ], [ 'b', 2 ] ]\n\nObject.freeze( obj )\n    Freezes an object.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.freeze( { 'a': 1 } )\n    { 'a': 1 }\n\nObject.getOwnPropertyDescriptor( obj, key )\n    Returns an object's own property descriptor.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    key: string\n        Property key.\n\n    Returns\n    -------\n    out: Object\n        Property descriptor.\n\n    Examples\n    --------\n    > var o = Object.getOwnPropertyDescriptor( { 'a': 1 }, 'a' )\n    { 'value': 1, 'enumerable': true, 'configurable': true, 'writable': true }\n\nObject.getOwnPropertyDescriptors( obj )\n    Returns an object's own property descriptors.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Object\n        Property descriptors.\n\n    Examples\n    --------\n    > var o = Object.getOwnPropertyDescriptors( { 'a': 1, 'b': 2 } )\n    {\n        'a': {\n            'value': 1,\n            'enumerable': true,\n            'configurable': true,\n            'writable': true\n        },\n        'b': {\n            'value': 2,\n            'enumerable': true,\n            'configurable': true,\n            'writable': true\n        }\n    }\n\nObject.getOwnPropertyNames( obj )\n    Returns an array of an object's own enumerable and non-enumerable\n    property names.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Array\n        Array of property names.\n\n    Examples\n    --------\n    > var o = Object.getOwnPropertyNames( { 'a': 1, 'b': 2 } )\n    [ 'a', 'b' ]\n\nObject.getOwnPropertySymbols( obj )\n    Returns an array of an object's own enumerable and non-enumerable\n    symbol property names.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Array\n        Array of symbol property names.\n\n    Examples\n    --------\n    > var o = Object.getOwnPropertySymbols( { 'a': 1, 'b': 2 } )\n    []\n\nObject.getPrototypeOf( obj )\n    Returns an object's prototype.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Object\n        Prototype.\n\n    Examples\n    --------\n    > var o = Object.getPrototypeOf( { 'a': 1, 'b': 2 } )\n    <Object>\n\nObject.hasOwn( obj, p )\n    Returns a boolean indicating whether an object has a property with the\n    specified name.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    p: string\n        Property name.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object has a property with the specified\n        name.\n\n    Examples\n    --------\n    > var o = Object.hasOwn( { 'a': 1, 'b': 2 }, 'a' )\n    true\n\nObject.is( value1, value2 )\n    Returns a boolean indicating whether two values are the same value.\n\n    Parameters\n    ----------\n    value1: any\n        First value.\n\n    value2: any\n        Second value.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether two values are the same value.\n\n    Examples\n    --------\n    > var o = Object.is( 1, 1 )\n    true\n    > var o = Object.is( 1, '1' )\n    false\n\nObject.isExtensible( obj )\n    Returns a boolean indicating whether an object is extensible.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object is extensible.\n\n    Examples\n    --------\n    > var o = Object.isExtensible( { 'a': 1 } )\n    true\n\nObject.isFrozen( obj )\n    Returns a boolean indicating whether an object is frozen.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object is frozen.\n\n    Examples\n    --------\n    > var o = Object.isFrozen( { 'a': 1 } )\n    false\n    > var o = Object.isFrozen( Object.freeze( { 'a': 1 } ) )\n    true\n\nObject.isSealed( obj )\n    Returns a boolean indicating whether an object is sealed.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object is sealed.\n\n    Examples\n    --------\n    > var o = Object.isSealed( { 'a': 1 } )\n    false\n    > var o = Object.isSealed( Object.seal( { 'a': 1 } ) )\n    true\n\nObject.keys( obj )\n    Returns an array of an object's own enumerable string-keyed property\n    names.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Array\n        Array of property names.\n\n    Examples\n    --------\n    > var o = Object.keys( { 'a': 1, 'b': 2 } )\n    [ 'a', 'b' ]\n\nObject.preventExtensions( obj )\n    Prevents the addition of new properties to an object.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.preventExtensions( { 'a': 1 } )\n    { 'a': 1 }\n    > o.b = 2;\n    > o\n    { 'a': 1 }\n\nObject.seal( obj )\n    Prevents the addition of new properties to an object and marks all\n    existing properties as non-configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.seal( { 'a': 1 } )\n    { 'a': 1 }\n    > o.b = 2;\n    > o\n    { 'a': 1 }\n    > delete o.a;\n    > o\n    { 'a': 1 }\n\nObject.setPrototypeOf( obj, proto )\n    Sets an object's prototype.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    proto: Object\n        Prototype.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.setPrototypeOf( { 'a': 1 }, { 'b': 2 } )\n    { 'a': 1 }\n    > o.b\n    2\n\nObject.values( obj )\n    Returns an array of an object's own enumerable property values.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Array\n        Array of property values.\n\n    Examples\n    --------\n    > var o = Object.values( { 'a': 1, 'b': 2 } )\n    [ 1, 2 ]\n\nObject.prototype.toLocaleString()\n    Returns a string representing the object.\n\n    Returns\n    -------\n    out: string\n        String representing the object.\n\n    Examples\n    --------\n    > var o = Object.prototype.toLocaleString.call( { 'a': 1, 'b': 2 } )\n    <string>\n\nObject.prototype.toString()\n    Returns a string representing the object.\n\n    Returns\n    -------\n    out: string\n        String representing the object.\n\n    Examples\n    --------\n    > var o = Object.prototype.toString.call( { 'a': 1, 'b': 2 } )\n    <string>\n\nObject.prototype.valueOf()\n    Returns the primitive value of the object.\n\n    Returns\n    -------\n    out: any\n        Primitive value of the object.\n\n    Examples\n    --------\n    > var o = Object.prototype.valueOf.call( { 'a': 1, 'b': 2 } )\n    {}\n\nObject.prototype.hasOwnProperty( p )\n    Returns a boolean indicating whether an object has a property with the\n    specified name.\n\n    Parameters\n    ----------\n    p: string\n        Property name.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object has a property with the specified\n        name.\n\n    Examples\n    --------\n    > var o = Object.prototype.hasOwnProperty.call( { 'a': 1, 'b': 2 }, 'a' )\n    true\n\nObject.prototype.isPrototypeOf( obj )\n    Returns a boolean indicating whether an object exists in another object's\n    prototype chain.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object exists in another object's\n        prototype chain.\n\n    Examples\n    --------\n    > var p = { 'a': 1 };\n    > var o = { '__proto__': p };\n    > var b = o.isPrototypeOf( p );\n    true\n\nObject.prototype.propertyIsEnumerable( p )\n    Returns a boolean indicating whether an object's property is enumerable.\n\n    Parameters\n    ----------\n    p: string\n        Property name.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object's property is enumerable.\n\n    Examples\n    --------\n    > var o = { 'a': 1, 'b': 2 };\n    > var bool = Object.prototype.propertyIsEnumerable.call( o, 'a' )\n    true\n\nObject.prototype.constructor\n    Property whose value is a reference to the constructor function that\n    created the instance object.\n\n    Examples\n    --------\n    > var o = new Object( null );\n    > var ctr = o.constructor;\n    <Object>\n\n","Object.assign":"\nObject.assign( target, ...sources )\n    Assigns enumerable and own properties from source objects to a target\n    object.\n\n    Parameters\n    ----------\n    target: Object\n        Target object.\n\n    sources: ...Object\n        Source objects.\n\n    Returns\n    -------\n    out: Object\n        Target object.\n\n    Examples\n    --------\n    > var o = Object.assign( {}, { 'a': 1 }, { 'b': 2 } )\n    { 'a': 1, 'b': 2 }","Object.create":"\nObject.create( prototype, properties )\n    Creates a new object with a specified prototype object and properties.\n\n    Parameters\n    ----------\n    prototype: Object\n        Prototype object.\n\n    properties: Object\n        Properties object.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > var o = Object.create( {}, { 'a': { 'value': 1 } } )\n    { 'a': 1 }","Object.defineProperties":"\nObject.defineProperties( obj, properties )\n    Defines properties for an object.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    properties: Object\n        Properties object.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.defineProperties( {}, { 'a': { 'value': 1 } } )\n    { 'a': 1 }","Object.defineProperty":"\nObject.defineProperty( obj, key, descriptor )\n    Defines a property for an object.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    key: string\n        Property key.\n\n    descriptor: Object\n        Property descriptor.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.defineProperty( {}, 'a', {\n        'value': 1,\n        'enumerable': true,\n        'configurable': true,\n        'writable': false\n    })\n    { 'a': 1 }","Object.entries":"\nObject.entries( obj )\n    Returns an array of an object's own enumerable string-keyed property\n    [key, value] pairs.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Array\n        Array of [key, value] pairs.\n\n    Examples\n    --------\n    > var o = Object.entries( { 'a': 1, 'b': 2 } )\n    [ [ 'a', 1 ], [ 'b', 2 ] ]","Object.freeze":"\nObject.freeze( obj )\n    Freezes an object.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.freeze( { 'a': 1 } )\n    { 'a': 1 }","Object.getOwnPropertyDescriptor":"\nObject.getOwnPropertyDescriptor( obj, key )\n    Returns an object's own property descriptor.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    key: string\n        Property key.\n\n    Returns\n    -------\n    out: Object\n        Property descriptor.\n\n    Examples\n    --------\n    > var o = Object.getOwnPropertyDescriptor( { 'a': 1 }, 'a' )\n    { 'value': 1, 'enumerable': true, 'configurable': true, 'writable': true }","Object.getOwnPropertyDescriptors":"\nObject.getOwnPropertyDescriptors( obj )\n    Returns an object's own property descriptors.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Object\n        Property descriptors.\n\n    Examples\n    --------\n    > var o = Object.getOwnPropertyDescriptors( { 'a': 1, 'b': 2 } )\n    {\n        'a': {\n            'value': 1,\n            'enumerable': true,\n            'configurable': true,\n            'writable': true\n        },\n        'b': {\n            'value': 2,\n            'enumerable': true,\n            'configurable': true,\n            'writable': true\n        }\n    }","Object.getOwnPropertyNames":"\nObject.getOwnPropertyNames( obj )\n    Returns an array of an object's own enumerable and non-enumerable\n    property names.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Array\n        Array of property names.\n\n    Examples\n    --------\n    > var o = Object.getOwnPropertyNames( { 'a': 1, 'b': 2 } )\n    [ 'a', 'b' ]","Object.getOwnPropertySymbols":"\nObject.getOwnPropertySymbols( obj )\n    Returns an array of an object's own enumerable and non-enumerable\n    symbol property names.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Array\n        Array of symbol property names.\n\n    Examples\n    --------\n    > var o = Object.getOwnPropertySymbols( { 'a': 1, 'b': 2 } )\n    []","Object.getPrototypeOf":"\nObject.getPrototypeOf( obj )\n    Returns an object's prototype.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Object\n        Prototype.\n\n    Examples\n    --------\n    > var o = Object.getPrototypeOf( { 'a': 1, 'b': 2 } )\n    <Object>","Object.hasOwn":"\nObject.hasOwn( obj, p )\n    Returns a boolean indicating whether an object has a property with the\n    specified name.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    p: string\n        Property name.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object has a property with the specified\n        name.\n\n    Examples\n    --------\n    > var o = Object.hasOwn( { 'a': 1, 'b': 2 }, 'a' )\n    true","Object.is":"\nObject.is( value1, value2 )\n    Returns a boolean indicating whether two values are the same value.\n\n    Parameters\n    ----------\n    value1: any\n        First value.\n\n    value2: any\n        Second value.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether two values are the same value.\n\n    Examples\n    --------\n    > var o = Object.is( 1, 1 )\n    true\n    > var o = Object.is( 1, '1' )\n    false","Object.isExtensible":"\nObject.isExtensible( obj )\n    Returns a boolean indicating whether an object is extensible.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object is extensible.\n\n    Examples\n    --------\n    > var o = Object.isExtensible( { 'a': 1 } )\n    true","Object.isFrozen":"\nObject.isFrozen( obj )\n    Returns a boolean indicating whether an object is frozen.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object is frozen.\n\n    Examples\n    --------\n    > var o = Object.isFrozen( { 'a': 1 } )\n    false\n    > var o = Object.isFrozen( Object.freeze( { 'a': 1 } ) )\n    true","Object.isSealed":"\nObject.isSealed( obj )\n    Returns a boolean indicating whether an object is sealed.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object is sealed.\n\n    Examples\n    --------\n    > var o = Object.isSealed( { 'a': 1 } )\n    false\n    > var o = Object.isSealed( Object.seal( { 'a': 1 } ) )\n    true","Object.keys":"\nObject.keys( obj )\n    Returns an array of an object's own enumerable string-keyed property\n    names.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Array\n        Array of property names.\n\n    Examples\n    --------\n    > var o = Object.keys( { 'a': 1, 'b': 2 } )\n    [ 'a', 'b' ]","Object.preventExtensions":"\nObject.preventExtensions( obj )\n    Prevents the addition of new properties to an object.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.preventExtensions( { 'a': 1 } )\n    { 'a': 1 }\n    > o.b = 2;\n    > o\n    { 'a': 1 }","Object.seal":"\nObject.seal( obj )\n    Prevents the addition of new properties to an object and marks all\n    existing properties as non-configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.seal( { 'a': 1 } )\n    { 'a': 1 }\n    > o.b = 2;\n    > o\n    { 'a': 1 }\n    > delete o.a;\n    > o\n    { 'a': 1 }","Object.setPrototypeOf":"\nObject.setPrototypeOf( obj, proto )\n    Sets an object's prototype.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    proto: Object\n        Prototype.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.setPrototypeOf( { 'a': 1 }, { 'b': 2 } )\n    { 'a': 1 }\n    > o.b\n    2","Object.values":"\nObject.values( obj )\n    Returns an array of an object's own enumerable property values.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Array\n        Array of property values.\n\n    Examples\n    --------\n    > var o = Object.values( { 'a': 1, 'b': 2 } )\n    [ 1, 2 ]","Object.prototype.toLocaleString":"\nObject.prototype.toLocaleString()\n    Returns a string representing the object.\n\n    Returns\n    -------\n    out: string\n        String representing the object.\n\n    Examples\n    --------\n    > var o = Object.prototype.toLocaleString.call( { 'a': 1, 'b': 2 } )\n    <string>","Object.prototype.toString":"\nObject.prototype.toString()\n    Returns a string representing the object.\n\n    Returns\n    -------\n    out: string\n        String representing the object.\n\n    Examples\n    --------\n    > var o = Object.prototype.toString.call( { 'a': 1, 'b': 2 } )\n    <string>","Object.prototype.valueOf":"\nObject.prototype.valueOf()\n    Returns the primitive value of the object.\n\n    Returns\n    -------\n    out: any\n        Primitive value of the object.\n\n    Examples\n    --------\n    > var o = Object.prototype.valueOf.call( { 'a': 1, 'b': 2 } )\n    {}","Object.prototype.hasOwnProperty":"\nObject.prototype.hasOwnProperty( p )\n    Returns a boolean indicating whether an object has a property with the\n    specified name.\n\n    Parameters\n    ----------\n    p: string\n        Property name.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object has a property with the specified\n        name.\n\n    Examples\n    --------\n    > var o = Object.prototype.hasOwnProperty.call( { 'a': 1, 'b': 2 }, 'a' )\n    true","Object.prototype.isPrototypeOf":"\nObject.prototype.isPrototypeOf( obj )\n    Returns a boolean indicating whether an object exists in another object's\n    prototype chain.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object exists in another object's\n        prototype chain.\n\n    Examples\n    --------\n    > var p = { 'a': 1 };\n    > var o = { '__proto__': p };\n    > var b = o.isPrototypeOf( p );\n    true","Object.prototype.propertyIsEnumerable":"\nObject.prototype.propertyIsEnumerable( p )\n    Returns a boolean indicating whether an object's property is enumerable.\n\n    Parameters\n    ----------\n    p: string\n        Property name.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object's property is enumerable.\n\n    Examples\n    --------\n    > var o = { 'a': 1, 'b': 2 };\n    > var bool = Object.prototype.propertyIsEnumerable.call( o, 'a' )\n    true","Object.prototype.constructor":"\nObject.prototype.constructor\n    Property whose value is a reference to the constructor function that\n    created the instance object.\n\n    Examples\n    --------\n    > var o = new Object( null );\n    > var ctr = o.constructor;\n    <Object>","objectEntries":"\nobjectEntries( obj )\n    Returns an array of an object's own enumerable property `[key, value]`\n    pairs.\n\n    Entry order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic return values.\n\n    Parameters\n    ----------\n    obj: ObjectLike\n        Input object.\n\n    Returns\n    -------\n    arr: Array\n        Array containing key-value pairs.\n\n    Examples\n    --------\n    > var obj = { 'beep': 'boop', 'foo': 'bar' };\n    > var entries = objectEntries( obj )\n    e.g., [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ]\n\n    See Also\n    --------\n    objectEntriesIn, objectFromEntries, objectKeys, objectValues\n","objectEntriesIn":"\nobjectEntriesIn( obj )\n    Returns an array of an object's own and inherited enumerable property\n    `[key, value]` pairs.\n\n    Entry order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic return values.\n\n    Parameters\n    ----------\n    obj: ObjectLike\n        Input object.\n\n    Returns\n    -------\n    arr: Array\n        Array containing key-value pairs.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var entries = objectEntriesIn( obj )\n    e.g., [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ]\n\n    See Also\n    --------\n    objectEntries, objectFromEntries, keysIn, objectValuesIn\n","objectFromEntries":"\nobjectFromEntries( entries )\n    Creates an object from an array of key-value pairs.\n\n    Parameters\n    ----------\n    entries: Array<Array>\n        Input object.\n\n    Returns\n    -------\n    out: Object\n        Object created from `[key, value]` pairs.\n\n    Examples\n    --------\n    > var entries = [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ];\n    > var obj = objectFromEntries( entries )\n    { 'beep': 'boop', 'foo': 'bar' }\n\n    See Also\n    --------\n    objectEntries\n","objectInverse":"\nobjectInverse( obj[, options] )\n    Inverts an object, such that keys become values and values become keys.\n\n    Beware when providing objects having values which are themselves objects.\n    The function relies on native object serialization (`#toString`) when\n    converting values to keys.\n\n    Insertion order is not guaranteed, as object key enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's keys, thus allowing for\n    deterministic inversion.\n\n    Parameters\n    ----------\n    obj: ObjectLike\n        Input object.\n\n    options: Object (optional)\n        Options.\n\n    options.duplicates: boolean (optional)\n        Boolean indicating whether to store keys mapped to duplicate values in\n        arrays. Default: `true`.\n\n    Returns\n    -------\n    out: Object\n        Inverted object.\n\n    Examples\n    --------\n    // Basic usage:\n    > var obj = { 'a': 'beep', 'b': 'boop' };\n    > var out = objectInverse( obj )\n    { 'beep': 'a', 'boop': 'b' }\n\n    // Duplicate values:\n    > obj = { 'a': 'beep', 'b': 'beep' };\n    > out = objectInverse( obj )\n    { 'beep': [ 'a', 'b' ] }\n\n    // Override duplicate values:\n    > obj = {};\n    > obj.a = 'beep';\n    > obj.b = 'boop';\n    > obj.c = 'beep';\n    > out = objectInverse( obj, { 'duplicates': false } )\n    { 'beep': 'c', 'boop': 'b' }\n\n    See Also\n    --------\n    objectInverseBy\n","objectInverseBy":"\nobjectInverseBy( obj, [options,] transform )\n    Inverts an object, such that keys become values and values become keys,\n    according to a transform function.\n\n    The transform function is provided three arguments:\n\n    - key: object key.\n    - value: object value corresponding to `key`.\n    - obj: the input object.\n\n    The value returned by a transform function should be a value which can be\n    serialized as an object key. Hence, beware when providing objects having\n    values which are themselves objects. The function relies on native object\n    serialization (`#toString`) when converting transform function return values\n    to keys.\n\n    Insertion order is not guaranteed, as object key enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's keys, thus allowing for\n    deterministic inversion.\n\n    Parameters\n    ----------\n    obj: ObjectLike\n        Input object.\n\n    options: Object (optional)\n        Options.\n\n    options.duplicates: boolean (optional)\n        Boolean indicating whether to store keys mapped to duplicate values in\n        arrays. Default: `true`.\n\n    transform: Function\n        Transform function.\n\n    Returns\n    -------\n    out: Object\n        Inverted object.\n\n    Examples\n    --------\n    // Basic usage:\n    > function transform( key, value ) { return key + value; };\n    > var obj = { 'a': 'beep', 'b': 'boop' };\n    > var out = objectInverseBy( obj, transform )\n    { 'abeep': 'a', 'bboop': 'b' }\n\n    // Duplicate values:\n    > function transform( key, value ) { return value; };\n    > obj = { 'a': 'beep', 'b': 'beep' };\n    > out = objectInverseBy( obj, transform )\n    { 'beep': [ 'a', 'b' ] }\n\n    // Override duplicate values:\n    > obj = {};\n    > obj.a = 'beep';\n    > obj.b = 'boop';\n    > obj.c = 'beep';\n    > out = objectInverseBy( obj, { 'duplicates': false }, transform )\n    { 'beep': 'c', 'boop': 'b' }\n\n    See Also\n    --------\n    objectInverse\n","objectKeys":"\nobjectKeys( value )\n    Returns an array of an object's own enumerable property names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's own enumerable property names.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var keys = objectKeys( obj )\n    [ 'beep' ]\n\n    See Also\n    --------\n    objectEntries, keysIn, nonIndexKeys, objectValues\n","objectValues":"\nobjectValues( obj )\n    Returns an array of an object's own enumerable property values.\n\n    Value order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    Parameters\n    ----------\n    obj: ObjectLike\n        Input object.\n\n    Returns\n    -------\n    values: Array\n        Value array.\n\n    Examples\n    --------\n    > var obj = { 'beep': 'boop', 'foo': 'bar' };\n    > var vals = objectValues( obj )\n    e.g., [ 'boop', 'bar' ]\n\n    See Also\n    --------\n    objectEntries, objectKeys\n","objectValuesIn":"\nobjectValuesIn( obj )\n    Returns an array of an object's own and inherited enumerable property\n    values.\n\n    Value order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    Parameters\n    ----------\n    obj: ObjectLike\n        Input object.\n\n    Returns\n    -------\n    values: Array\n        Value array.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var values = objectValuesIn( obj )\n    e.g., [ 'boop', 'bar' ]\n\n    See Also\n    --------\n    objectEntriesIn, keysIn, objectValues\n","omit":"\nomit( obj, keys )\n    Returns a partial object copy excluding specified keys.\n\n    The function returns a shallow copy.\n\n    The function ignores non-existent keys.\n\n    The function only copies own properties. Hence, the function never copies\n    inherited properties.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    keys: string|Array<string>\n        Keys to exclude.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > var obj1 = { 'a': 1, 'b': 2 };\n    > var obj2 = omit( obj1, 'b' )\n    { 'a': 1 }\n\n    See Also\n    --------\n    omitBy\n","omitBy":"\nomitBy( obj, predicate )\n    Returns a partial object copy excluding properties for which a predicate\n    returns a truthy value.\n\n    The function returns a shallow copy.\n\n    The function only copies own properties. Hence, the function never copies\n    inherited properties.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    predicate: Function\n        Predicate function.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > function predicate( key, value ) { return ( value > 1 ); };\n    > var obj1 = { 'a': 1, 'b': 2 };\n    > var obj2 = omitBy( obj1, predicate )\n    { 'a': 1 }\n\n    See Also\n    --------\n    omit\n","open":"\nopen( path[, flags[, mode]], clbk )\n    Asynchronously opens a file.\n\n    Some characters, such as <>:\"/\\|?*, are reserved under Windows.\n    Under NTFS, if the path contains a colon, Node.js will open a file system\n    stream.\n\n    Parameters\n    ----------\n    path: string|Buffer\n        Filename.\n\n    flags: string|number (optional)\n        File system flags. Default: 'r'.\n\n    mode: integer (optional)\n        File mode (permission and sticky bits). This sets the file mode, but\n        only if the file was created. On Windows, only the write permission can\n        be manipulated. Default: 0o666.\n\n    clbk: Function\n        Callback to invoke upon opening a file.\n\n    Examples\n    --------\n    > function onOpen( error, fd ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     } else {\n    ...         close.sync( fd );\n    ...     }\n    ... };\n    > open( './beep/boop.txt', onOpen );\n\n\nopen.sync( path[, flags[, mode]] )\n    Synchronously opens a file.\n\n    Parameters\n    ----------\n    path: string|Buffer\n        Filename.\n\n    flags: string|number (optional)\n        File system flags. Default: 'r'.\n\n    mode: integer (optional)\n        File mode (permission and sticky bits).  This sets the file mode, but\n        only if the file was created. On Windows, only the write permission can\n        be manipulated. Default: 0o666.\n\n    Returns\n    -------\n    fd: Error|integer\n        File descriptor.\n\n    Examples\n    --------\n    > var fd = open.sync( './beep/boop.txt' );\n    > if ( !isError( fd ) ) { close.sync( fd ); };\n\n    See Also\n    --------\n    close, exists, readFile\n","open.sync":"\nopen.sync( path[, flags[, mode]] )\n    Synchronously opens a file.\n\n    Parameters\n    ----------\n    path: string|Buffer\n        Filename.\n\n    flags: string|number (optional)\n        File system flags. Default: 'r'.\n\n    mode: integer (optional)\n        File mode (permission and sticky bits).  This sets the file mode, but\n        only if the file was created. On Windows, only the write permission can\n        be manipulated. Default: 0o666.\n\n    Returns\n    -------\n    fd: Error|integer\n        File descriptor.\n\n    Examples\n    --------\n    > var fd = open.sync( './beep/boop.txt' );\n    > if ( !isError( fd ) ) { close.sync( fd ); };\n\n    See Also\n    --------\n    close, exists, readFile","openURL":"\nopenURL( url )\n    Opens a URL in a user's default browser.\n\n    In a non-browser environment, the function returns an unreferenced child\n    process. In a browser environment, the function returns a reference to a\n    `window` object.\n\n    Parameters\n    ----------\n    url: string\n        URL to open.\n\n    Returns\n    -------\n    out: process|Window\n        Child process or `window` object.\n\n    Examples\n    --------\n    > var out = openURL( 'https://google.com' );\n\n","ordinalize":"\nordinalize( value[, options] )\n    Converts an integer to an ordinal string (e.g., `1st`, `2nd`, etc.).\n\n    Parameters\n    ----------\n    value: string|integer\n        Input value.\n\n    options: Object (optional)\n        Options.\n\n    options.lang: string (optional)\n        Language code. Supported languages:\n\n        - en: English.\n        - es: Spanish.\n        - fin: Finnish.\n        - fr: French.\n        - de: Dutch.\n        - it: Italian.\n        - pt: Portuguese.\n        - swe: Swedish.\n\n        Default: `'en'`.\n\n    options.suffixOnly: boolean (optional)\n        Boolean indicating whether to return only the suffix. Default: `false`.\n\n    options.gender: string (optional)\n       Grammatical gender (used if applicable); must be either 'masculine' or\n       'feminine'. Default: `'masculine'`.\n\n    Returns\n    -------\n    out: string\n        Ordinal string or suffix.\n\n    Examples\n    --------\n    > var out = ordinalize( '1' )\n    '1st'\n    > out = ordinalize( 2, { 'suffixOnly': true } )\n    'nd'\n    > out = ordinalize( '3', { 'lang': 'es' } )\n    '3º'\n\n","PACE_BOSTON_HOUSE_PRICES":"\nPACE_BOSTON_HOUSE_PRICES()\n    Returns a (corrected) dataset derived from information collected by the US\n    Census Service concerning housing in Boston, Massachusetts (1978).\n\n    The data consists of 21 attributes:\n\n    - obs: observation number.\n    - town: town name.\n    - town_id: town identifier.\n    - tract: tract identifier.\n    - lon: longitude.\n    - lat: latitude.\n    - medv: median value of owner-occupied homes in $1000's.\n    - cmedv: corrected median value of owner-occupied homes in $1000's.\n    - crim: per capita crime rate by town.\n    - zn: proportion of residential land zoned for lots over 25,000 square feet.\n    - indus: proportion of non-retail business acres per town.\n    - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise).\n    - nox: nitric oxides concentration (parts per 10 million).\n    - rm: average number of rooms per dwelling.\n    - age: proportion of owner-occupied units built prior to 1940.\n    - dis: weighted distances to five Boston employment centers.\n    - rad: index of accessibility to radial highways.\n    - tax: full-value property-tax rate per $10,000.\n    - ptratio: pupil-teacher ratio by town.\n    - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town.\n    - lstat: percent lower status of the population.\n\n    The dataset can be used to predict two dependent variables: 1) nitrous oxide\n    level and 2) median home value.\n\n    The median home value field seems to be censored at 50.00 (corresponding to\n    a median value of $50,000). Censoring is suggested by the fact that the\n    highest median value of exactly $50,000 is reported in 16 cases, while 15\n    cases have values between $40,000 and $50,000. Values are rounded to the\n    nearest hundred.\n\n    The dataset contains eight corrections to miscoded median values, as\n    documented by Gilley and Pace (1996).\n\n    The dataset augments the original dataset from Harrison and Rubinfeld (1978)\n    by including geo-referencing and spatial estimation for each observation.\n\n    Returns\n    -------\n    out: Array<Object>\n        Boston house prices.\n\n    Examples\n    --------\n    > var data = PACE_BOSTON_HOUSE_PRICES()\n    [ {...}, {...}, ... ]\n\n    References\n    ----------\n    - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n    the demand for clean air.\" _Journal of Environmental Economics and\n    Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n    - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n    Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n    doi:10.1006/jeem.1996.0052.\n    - Pace, R. Kelley, and Otis W. Gilley. 1997. \"Using the Spatial\n    Configuration of the Data to Improve Estimation.\" _The Journal of Real\n    Estate Finance and Economics_ 14 (3): 333–40. doi:10.1023/A:1007762613901.\n\n    See Also\n    --------\n    HARRISON_BOSTON_HOUSE_PRICES, HARRISON_BOSTON_HOUSE_PRICES_CORRECTED\n","pad":"\npad( str, len[, options] )\n    Pads a `string` such that the padded `string` has length `len`.\n\n    Any padding which does not evenly divide available space is trimmed such\n    that the returned string length is always `len`.\n\n    If `len < str.length`, the input string is trimmed.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    len: integer\n        Output string length.\n\n    options: Object (optional)\n        Options.\n\n    options.lpad: string (optional)\n        String used to left pad.\n\n    options.rpad: string (optional)\n        String used to right pad.\n\n    options.centerRight: boolean (optional)\n        Boolean indicating whether to center right in the event of a tie.\n        Default: `false` (i.e., center left).\n\n    Returns\n    -------\n    out: string\n        Padded string.\n\n    Examples\n    --------\n    // Standard usage:\n    > var out = pad( 'a', 5 )\n    'a    '\n\n    // Left pad:\n    > out = pad( 'a', 10, { 'lpad': 'b' } )\n    'bbbbbbbbba'\n\n    // Right pad:\n    > out = pad( 'a', 12, { 'rpad': 'b' } )\n    'abbbbbbbbbbb'\n\n    // Center an input string:\n    > var opts = { 'lpad': 'a', 'rpad': 'c' };\n    > out = pad( 'b', 11, opts )\n    'aaaaabccccc'\n\n    // Left center:\n    > opts.centerRight = false;\n    > out = pad( 'b', 10, opts )\n    'aaaabccccc'\n\n    // Right center:\n    > opts.centerRight = true;\n    > out = pad( 'b', 10, opts )\n    'aaaaabcccc'\n\n    // Output string always length `len`:\n    > opts = { 'lpad': 'boop', 'rpad': 'woot' };\n    > out = pad( 'beep', 10, opts )\n    'boobeepwoo'\n\n    // Pad right, trim right:\n    > out = pad( 'beep', 2 )\n    'be'\n\n    // Pad left, trim left:\n    > opts = { 'lpad': 'b' };\n    > out = pad( 'beep', 2, opts )\n    'ep'\n\n    // Pad both, trim both:\n    > opts = { 'lpad': '@', 'rpad': '!' };\n    > out = pad( 'beep', 2, opts )\n    'ee'\n\n    // Pad both, trim both starting from left:\n    > out = pad( 'abcdef', 3, opts )\n    'cde'\n\n    // Pad both, trim both starting from right:\n    > opts.centerRight = true;\n    > out = pad( 'abcdef', 3, opts )\n    'bcd'\n\n    See Also\n    --------\n    lpad, rpad\n","padjust":"\npadjust( pvals, method[, comparisons] )\n    Adjusts supplied p-values for multiple comparisons via a specified method.\n\n    The `method` parameter can be one of the following values:\n\n    - bh: Benjamini-Hochberg procedure controlling the False Discovery\n    Rate (FDR).\n    - bonferroni: Bonferroni correction fixing the family-wise error rate\n    by multiplying the p-values with the number of comparisons. The Bonferroni\n    correction is usually a too conservative adjustment compared to the others.\n    - by: Procedure by Benjamini & Yekutieli for controlling the False\n    Discovery Rate (FDR) under dependence.\n    - holm: Hommel's method controlling family-wise error rate. It is\n    uniformly more powerful than the Bonferroni correction.\n    - hommel: Hommel's method, which is valid when hypothesis tests are\n    independent. It is more expensive to compute than the other methods.\n\n    By default, the number of comparisons for which the p-values should be\n    corrected is equal to the number of provided p-values. Alternatively, it is\n    possible to set `comparisons` to a number greater than the length of\n    `pvals`. In that case, the methods assume `comparisons - pvals.length`\n    unobserved p-values that are greater than all observed p-values (for Holm's\n    method and the Bonferroni correction) or equal to `1` for the remaining\n    methods.\n\n    Parameters\n    ----------\n    pvals: Array<number>\n        P-values to be adjusted.\n\n    method: string\n        Correction method.\n\n    comparisons: integer (optional)\n        Number of comparisons. Default value: `pvals.length`.\n\n    Returns\n    -------\n    out: Array<number>\n        Array containing the corrected p-values.\n\n    Examples\n    --------\n    > var pvalues = [ 0.008, 0.03, 0.123, 0.6, 0.2 ];\n    > var out = padjust( pvalues, 'bh' )\n    [ 0.04, 0.075, ~0.205, 0.6, 0.25 ]\n\n    > out = padjust( pvalues, 'bonferroni' )\n    [ 0.04, 0.15, 0.615, 1.0, 1.0 ]\n\n    > out = padjust( pvalues, 'by' )\n    [ ~0.457, ~0.856, 1.0, 1.0, 1.0 ]\n\n    > out = padjust( pvalues, 'holm' )\n    [ 0.2, 0.6, 1.0, 1.0, 1.0 ]\n\n    > out = padjust( pvalues, 'hommel' )\n    [ 0.16, 0.6, 1.0, 1.0, 1.0 ]\n\n","papply":"\npapply( fcn, ...args )\n    Returns a function of smaller arity by partially applying arguments.\n\n    The implementation does not set the `length` property of the returned\n    function. Accordingly, the returned function `length` is always zero.\n\n    The evaluation context is always `null`.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to partially apply.\n\n    args: ...any\n        Arguments to partially apply.\n\n    Returns\n    -------\n    out: Function\n        Partially applied function.\n\n    Examples\n    --------\n    > function add( x, y ) { return x + y; };\n    > var add2 = papply( add, 2 );\n    > var sum = add2( 3 )\n    5\n\n    See Also\n    --------\n    papplyRight\n","papplyRight":"\npapplyRight( fcn, ...args )\n    Returns a function of smaller arity by partially applying arguments from the\n    right.\n\n    The implementation does not set the `length` property of the returned\n    function. Accordingly, the returned function `length` is always zero.\n\n    The evaluation context is always `null`.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to partially apply.\n\n    args: ...any\n        Arguments to partially apply.\n\n    Returns\n    -------\n    out: Function\n        Partially applied function.\n\n    Examples\n    --------\n    > function say( text, name ) { return text + ', ' + name + '.'; };\n    > var toGrace = papplyRight( say, 'Grace Hopper' );\n    > var str = toGrace( 'Hello' )\n    'Hello, Grace Hopper.'\n    > str = toGrace( 'Thank you' )\n    'Thank you, Grace Hopper.'\n\n    See Also\n    --------\n    papply\n","parallel":"\nparallel( files, [options,] clbk )\n    Executes scripts in parallel.\n\n    Relative file paths are resolved relative to the current working directory.\n\n    Ordered script output does not imply that scripts are executed in order. To\n    preserve script order, execute the scripts sequentially via some other\n    means.\n\n    Parameters\n    ----------\n    files: Array<string>\n        Script file paths.\n\n    options: Object (optional)\n        Options.\n\n    options.cmd: string (optional)\n        Executable file/command. Default: `'node'`.\n\n    options.concurrency: integer (optional)\n        Number of scripts to execute concurrently. Script concurrency cannot\n        exceed the number of scripts. By specifying a concurrency greater than\n        the number of workers, a worker may be executing more than `1` script at\n        any one time. While not likely to be advantageous for synchronous\n        scripts, setting a higher concurrency may be advantageous for scripts\n        performing asynchronous tasks. If the script concurrency is less than\n        the number of workers, the number of workers is reduced to match the\n        specified concurrency. Default: `options.workers`.\n\n    options.workers: integer (optional)\n        Number of workers. Default: number of CPUs minus `1`.\n\n    options.ordered: boolean (optional)\n        Boolean indicating whether to preserve the order of script output. By\n        default, the `stdio` output for each script is interleaved; i.e., the\n        `stdio` output from one script may be interleaved with the `stdio`\n        output from one or more other scripts. To preserve the `stdio` output\n        order for each script, set the `ordered` option to `true`. Default:\n        `false`.\n\n    options.uid: integer (optional)\n        Process user identity.\n\n    options.gid: integer (optional)\n        Process group identity.\n\n    options.maxBuffer: integer (optional)\n        Max child process `stdio` buffer size. This option is only applied when\n        `options.ordered = true`. Default: `200*1024*1024`.\n\n    clbk: Function\n        Callback to invoke after executing all scripts.\n\n    Examples\n    --------\n    > function done( error ) { if ( error ) { throw error; } };\n    > var files = [ './a.js', './b.js' ];\n    > parallel( files, done );\n\n    // Specify the number of workers:\n    > var opts = { 'workers': 8 };\n    > parallel( files, opts, done );\n\n","parseJSON":"\nparseJSON( str[, reviver] )\n    Attempts to parse a string as JSON.\n\n    Function behavior differs from `JSON.parse()` as follows:\n\n    - throws a `TypeError` if provided any value which is not a string.\n    - throws a `TypeError` if provided a `reviver` argument which is not a\n      function.\n    - returns, rather than throws, a `SyntaxError` if unable to parse a string\n      as JSON.\n\n    Parameters\n    ----------\n    str: string\n        String to parse.\n\n    reviver: Function (optional)\n        Transformation function.\n\n    Returns\n    -------\n    out: any|Error\n        Parsed value or an error.\n\n    Examples\n    --------\n    > var obj = parseJSON( '{\"beep\":\"boop\"}' )\n    { 'beep': 'boop' }\n\n    // Provide a reviver:\n    > function reviver( key, value ) {\n    ...     if ( key === '' ) { return value; }\n    ...     if ( key === 'beep' ) { return value; }\n    ... };\n    > var str = '{\"beep\":\"boop\",\"a\":\"b\"}';\n    > var out = parseJSON( str, reviver )\n    { 'beep': 'boop' }\n\n","pascalcase":"\npascalcase( str )\n    Converts a string to Pascal case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Pascal-cased string.\n\n    Examples\n    --------\n    > var out = pascalcase( 'Hello World!' )\n    'HelloWorld'\n    > out = pascalcase( 'beep boop' )\n    'BeepBoop'\n\n    See Also\n    --------\n    camelcase, constantcase, kebabcase, snakecase","PATH_DELIMITER":"\nPATH_DELIMITER\n    Platform-specific path delimiter.\n\n    Examples\n    --------\n    > PATH_DELIMITER\n    <string>\n\n    // POSIX environment:\n    > var path = '/usr/bin:/bin:/usr/sbin';\n    > var parts = path.split( PATH_DELIMITER )\n    [ '/usr/bin', '/bin', '/usr/sbin' ]\n\n    // Windows environment:\n    > path = 'C:\\\\Windows\\\\system32;C:\\\\Windows';\n    > parts = path.split( PATH_DELIMITER )\n    [ 'C:\\\\Windows\\system32', 'C:\\\\Windows' ]\n\n    See Also\n    --------\n    PATH_DELIMITER_POSIX, PATH_DELIMITER_WIN32\n","PATH_DELIMITER_POSIX":"\nPATH_DELIMITER_POSIX\n    POSIX path delimiter.\n\n    Examples\n    --------\n    > PATH_DELIMITER_POSIX\n    ':'\n    > var PATH = '/usr/bin:/bin:/usr/sbin:/sbin:/usr/local/bin';\n    > var paths = PATH.split( PATH_DELIMITER_POSIX )\n    [ '/usr/bin', '/bin', '/usr/sbin', '/sbin', '/usr/local/bin' ]\n\n    See Also\n    --------\n    PATH_DELIMITER, PATH_DELIMITER_WIN32\n","PATH_DELIMITER_WIN32":"\nPATH_DELIMITER_WIN32\n    Windows path delimiter.\n\n    Examples\n    --------\n    > PATH_DELIMITER_WIN32\n    ';'\n    > var PATH = 'C:\\\\Windows\\\\system32;C:\\\\Windows;C:\\\\Program Files\\\\node\\\\';\n    > var paths = PATH.split( PATH_DELIMITER_WIN32 )\n    [ 'C:\\\\Windows\\\\system32', 'C:\\\\Windows', 'C:\\\\Program Files\\\\node\\\\' ]\n\n    See Also\n    --------\n    PATH_DELIMITER, PATH_DELIMITER_POSIX\n","PATH_SEP":"\nPATH_SEP\n    Platform-specific path segment separator.\n\n    Examples\n    --------\n    > PATH_SEP\n    <string>\n\n    // Windows environment:\n    > var parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP )\n    [ 'foo', 'bar', 'baz' ]\n\n    // POSIX environment:\n    > parts = 'foo/bar/baz'.split( PATH_SEP )\n    [ 'foo', 'bar', 'baz' ]\n\n    See Also\n    --------\n    PATH_SEP_POSIX, PATH_SEP_WIN32\n","PATH_SEP_POSIX":"\nPATH_SEP_POSIX\n    POSIX path segment separator.\n\n    Examples\n    --------\n    > PATH_SEP_POSIX\n    '/'\n    > var parts = 'foo/bar/baz'.split( PATH_SEP_POSIX )\n    [ 'foo', 'bar', 'baz' ]\n\n    See Also\n    --------\n    PATH_SEP, PATH_SEP_WIN32\n","PATH_SEP_WIN32":"\nPATH_SEP_WIN32\n    Windows path segment separator.\n\n    Examples\n    --------\n    > PATH_SEP_WIN32\n    '\\\\'\n    > var parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP_WIN32 )\n    [ 'foo', 'bar', 'baz' ]\n\n    See Also\n    --------\n    PATH_SEP, PATH_SEP_POSIX\n","pcorrtest":"\npcorrtest( x, y[, options] )\n    Computes a Pearson product-moment correlation test between paired samples.\n\n    By default, the function performs a t-test for the null hypothesis that the\n    data in arrays or typed arrays `x` and `y` is not correlated. A test against\n    a different population correlation can be carried out by supplying the `rho`\n    option. In this case, a test using the Fisher's z transform is conducted.\n\n    The returned object comes with a `.print()` method which when invoked will\n    print a formatted output of the results of the hypothesis test.\n\n    Parameters\n    ----------\n    x: Array<number>\n        First data array.\n\n    y: Array<number>\n        Second data array.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Nnumber in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.alternative: string (optional)\n        Either `two-sided`, `less` or `greater`. Indicates whether the\n        alternative hypothesis is that `x` has a larger mean than `y`\n        (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n        the same (`two-sided`). Default: `'two-sided'`.\n\n    options.rho: number (optional)\n        Number denoting the correlation under the null hypothesis.\n        Default: `0`.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Used significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.ci: Array<number>\n        1-alpha confidence interval for the Pearson product-moment correlation\n        coefficient. The confidence interval is calculated using Fisher's\n        z-transform.\n\n    out.nullValue: number\n        Assumed correlation under H0 (equal to the supplied `rho` option).\n\n    out.alternative: string\n        Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n    out.method: string\n        Name of test.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    > var rho = 0.5;\n    > var x = new Array( 300 );\n    > var y = new Array( 300 );\n    > for ( var i = 0; i < 300; i++ ) {\n    ...    x[ i ] = base.random.normal( 0.0, 1.0 );\n    ...    y[ i ] = ( rho * x[ i ] ) + base.random.normal( 0.0,\n    ...    base.sqrt( 1.0 - (rho*rho) ) );\n    ... }\n    > var out = pcorrtest( x, y )\n    {\n        alpha: 0.05,\n        rejected: true,\n        pValue: 0,\n        statistic: 10.115805615994121,\n        ci: [ 0.4161679018930295, 0.5853122968949995 ],\n        alternative: 'two-sided',\n        method: 't-test for Pearson correlation coefficient',\n        nullValue: 0,\n        pcorr: 0.505582072355616,\n    }\n\n    // Print output:\n    > var table = out.print()\n    t-test for Pearson correlation coefficient\n\n    Alternative hypothesis: True correlation coefficient is not equal to 0\n\n        pValue: 0\n        statistic: 9.2106\n        95% confidence interval: [0.3776,0.5544]\n\n    Test Decision: Reject null in favor of alternative at 5% significance level\n\n","percentEncode":"\npercentEncode( str )\n    Percent-encodes a UTF-16 encoded string according to RFC 3986.\n\n    Parameters\n    ----------\n    str: string\n        UTF-16 encoded string.\n\n    Returns\n    -------\n    out: string\n        Percent-encoded string.\n\n    Examples\n    --------\n    > var out = percentEncode( '☃' )\n    '%E2%98%83'\n\n","PHI":"\nPHI\n    Golden ratio.\n\n    Examples\n    --------\n    > PHI\n    1.618033988749895\n\n","PI":"\nPI\n    The mathematical constant `π`.\n\n    Examples\n    --------\n    > PI\n    3.141592653589793\n\n    See Also\n    --------\n    TWO_PI\n","PI_SQUARED":"\nPI_SQUARED\n    Square of the mathematical constant `π`.\n\n    Examples\n    --------\n    > PI_SQUARED\n    9.869604401089358\n\n    See Also\n    --------\n    PI\n","pick":"\npick( obj, keys )\n    Returns a partial object copy containing only specified keys.\n\n    If a key does not exist as an own property in a source object, the key is\n    ignored.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    keys: string|Array<string>\n        Keys to copy.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > var obj1 = { 'a': 1, 'b': 2 };\n    > var obj2 = pick( obj1, 'b' )\n    { 'b': 2 }\n\n    See Also\n    --------\n    pickBy\n","pickArguments":"\npickArguments( fcn, indices[, thisArg] )\n    Returns a function that applies specified arguments to a provided function.\n\n    Parameters\n    ----------\n    fcn: Function\n        Input function.\n\n    indices: Array<integer>\n        Argument indices.\n\n    thisArg: any (optional)\n        Function context.\n\n    Returns\n    -------\n    out: Function\n        Function wrapper.\n\n    Examples\n    --------\n    > function foo( a, b ) { return [ a, b ]; };\n    > var bar = pickArguments( foo, [ 0, 2 ] );\n    > var out = bar( 1, 2, 3 )\n    [ 1, 3 ]\n\n    See Also\n    --------\n    reorderArguments, reverseArguments\n","pickBy":"\npickBy( obj, predicate )\n    Returns a partial object copy containing properties for which a predicate\n    returns a truthy value.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    predicate: Function\n        Predicate function.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > function predicate( key, value ) {\n    ...     return ( value > 1 );\n    ... };\n    > var obj1 = { 'a': 1, 'b': 2 };\n    > var obj2 = pickBy( obj1, predicate )\n    { 'b': 2 }\n\n    See Also\n    --------\n    pick\n","PINF":"\nPINF\n    Double-precision floating-point positive infinity.\n\n    Examples\n    --------\n    > PINF\n    Infinity\n\n    See Also\n    --------\n    NINF\n","pkg2alias":"\npkg2alias( pkg )\n    Returns the alias associated with a specified package name.\n\n    The function supports both internal and standalone package names.\n\n    Parameters\n    ----------\n    pkg: string\n        Package name.\n\n    Returns\n    -------\n    out: string|null\n        Alias.\n\n    Examples\n    --------\n    > var v = pkg2alias( '@stdlib/math/base/special/sin' )\n    <string>\n    > v = pkg2alias( '@stdlib/math-base-special-sin' )\n    <string>\n\n    See Also\n    --------\n    alias2pkg, aliases, pkg2related\n","pkg2related":"\npkg2related( pkg )\n    Returns package names related to a specified package name.\n\n    The function supports both internal and standalone package names.\n\n    Parameters\n    ----------\n    pkg: string\n        Package name.\n\n    Returns\n    -------\n    out: Array|null\n        Related package names.\n\n    Examples\n    --------\n    > var v = pkg2related( '@stdlib/math/base/special/sin' )\n    [...]\n    > v = pkg2related( '@stdlib/math-base-special-sin' )\n    [...]\n\n    See Also\n    --------\n    alias2related, aliases, pkg2alias\n","pkg2standalone":"\npkg2standalone( pkg )\n    Returns the standalone package name associated with a provided internal\n    package name.\n\n    Parameters\n    ----------\n    pkg: string\n        Package name.\n\n    Returns\n    -------\n    out: string|null\n        Standalone package name.\n\n    Examples\n    --------\n    > var v = pkg2standalone( '@stdlib/math/base/special/sin' )\n    '@stdlib/math-base-special-sin'\n\n    See Also\n    --------\n    alias2pkg, alias2standalone, aliases, pkg2alias, pkg2related\n","PLATFORM":"\nPLATFORM\n    Platform on which the current process is running.\n\n    Possible values:\n\n    - win32\n    - darwin\n    - linux\n    - freebsd\n    - sunos\n\n    Examples\n    --------\n    > PLATFORM\n    <string>\n\n    See Also\n    --------\n    ARCH\n","plot":"\nplot( [x, y,] [options] )\n    Returns a plot instance for creating 2-dimensional plots.\n\n    `x` and `y` arguments take precedence over `x` and `y` options.\n\n    Parameters\n    ----------\n    x: Array<Array>|Array<TypedArray> (optional)\n        An array of arrays containing x-coordinate values.\n\n    y: Array<Array>|Array<TypedArray> (optional)\n        An array of arrays containing y-coordinate values.\n\n    options: Object (optional)\n        Options.\n\n    options.autoRender: boolean (optional)\n        Boolean indicating whether to re-render on a 'change' event. Default:\n        false.\n\n    options.autoView: boolean (optional)\n        Boolean indicating whether to generate an updated view on a 'render'\n        event. Default: false.\n\n    options.colors: string|Array<string> (optional)\n        Data color(s). Default: 'category10'.\n\n    options.description: string (optional)\n        Plot description.\n\n    options.engine: string (optional)\n        Plot engine. Default: 'svg'.\n\n    options.height: number (optional)\n        Plot height (in pixels). Default: 400.\n\n    options.labels: Array|Array<string> (optional)\n        Data labels.\n\n    options.isDefined: Function (optional)\n        An accessor function indicating whether a datum is defined.\n\n    options.lineStyle: string|Array<string> (optional)\n        Data line style(s). Must be one of: '-', '--', ':', '-.', or 'none'.\n        Default: '-'.\n\n    options.lineOpacity: number|Array<number> (optional)\n        Data line opacity. Must be on the interval [0,1]. Default: 0.9.\n\n    options.lineWidth: integer|Array<integer> (optional)\n        Data line width (in pixels). Default: 2.\n\n    options.paddingBottom: integer (optional)\n        Bottom padding (in pixels). Default: 80.\n\n    options.paddingLeft: integer (optional)\n        Left padding (in pixels). Default: 90.\n\n    options.paddingRight: integer (optional)\n        Right padding (in pixels). Default: 20.\n\n    options.paddingTop: integer (optional)\n        Top padding (in pixels). Default: 80.\n\n    options.renderFormat: string (optional)\n        Plot render format. Must be one of 'vdom' or 'html'. Default: 'vdom'.\n\n    options.symbols: string|Array<string> (optional)\n        Data symbols. Must be one of 'closed-circle', 'open-circle', or 'none'.\n        Default: 'none'.\n\n    options.symbolsOpacity: number|Array<number> (optional)\n        Symbols opacity. Must be on the interval [0,1]. Default: 0.9.\n\n    options.symbolsSize: integer|Array<integer> (optional)\n        Symbols size (in pixels). Default: 6.\n\n    options.title: string (optional)\n        Plot title.\n\n    options.viewer: string (optional)\n        Plot viewer. Must be one of 'browser', 'terminal', 'stdout', 'window',\n        or 'none'. Default: 'none'.\n\n    options.width: number (optional)\n        Plot width (in pixels). Default: 400.\n\n    options.x: Array<Array>|Array<TypedArray> (optional)\n        x-coordinate values.\n\n    options.xAxisOrient: string (optional)\n        x-axis orientation. Must be either 'bottom' or 'top'. Default: 'bottom'.\n\n    options.xLabel: string (optional)\n        x-axis label. Default: 'x'.\n\n    options.xMax: number|null (optional)\n        Maximum value of the x-axis domain. If `null`, the maximum value is\n        calculated from the data. Default: null.\n\n    options.xMin: number|null (optional)\n        Minimum value of the x-axis domain. If `null`, the minimum value is\n        calculated from the data. Default: null.\n\n    options.xNumTicks: integer (optional)\n        Number of x-axis tick marks. Default: 5.\n\n    options.xRug: boolean|Array<boolean> (optional)\n        Boolean flag(s) indicating whether to render one or more rug plots along\n        the x-axis.\n\n    options.xRugOrient: string|Array<string> (optional)\n        x-axis rug plot orientation(s). Must be either 'bottom' or 'top'.\n        Default: 'bottom'.\n\n    options.xRugOpacity: number|Array<number> (optional)\n       x-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n    options.xRugSize: integer|Array<integer> (optional)\n       x-axis rug tick (tassel) size (in pixels). Default: 6.\n\n    options.xScale: string\n       x-axis scale. Default: 'linear'.\n\n    options.xTickFormat: string|null\n       x-axis tick format. Default: null.\n\n    options.y: Array<Array>|Array<TypedArray> (optional)\n        y-coordinate values.\n\n    options.yAxisOrient: string (optional)\n        x-axis orientation. Must be either 'left' or 'right'. Default: 'left'.\n\n    options.yLabel: string (optional)\n        y-axis label. Default: 'y'.\n\n    options.yMax: number|null (optional)\n        Maximum value of the y-axis domain. If `null`, the maximum value is\n        calculated from the data. Default: null.\n\n    options.yMin: number|null (optional)\n        Minimum value of the y-axis domain. If `null`, the minimum value is\n        calculated from the data. Default: null.\n\n    options.yNumTicks: integer (optional)\n        Number of x-axis tick marks. Default: 5.\n\n    options.yRug: boolean|Array<boolean> (optional)\n        Boolean flag(s) indicating whether to render one or more rug plots along\n        the y-axis.\n\n    options.yRugOrient: string|Array<string> (optional)\n        y-axis rug plot orientation(s). Must be either 'left' or 'right'.\n        Default: 'left'.\n\n    options.yRugOpacity: number|Array<number> (optional)\n       y-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n    options.yRugSize: integer|Array<integer> (optional)\n       y-axis rug tick (tassel) size (in pixels). Default: 6.\n\n    options.yScale: string\n       y-axis scale. Default: 'linear'.\n\n    options.yTickFormat: string|null\n       y-axis tick format. Default: null.\n\n    Returns\n    -------\n    plot: Plot\n        Plot instance.\n\n    plot.render()\n        Renders a plot as a virtual DOM tree.\n\n    plot.view( [viewer] )\n        Generates a plot view.\n\n    plot.x\n        x-coordinate values. An assigned value must be an array where each\n        element corresponds to a plotted dataset.\n\n    plot.y\n        y-coordinate values. An assigned value must be an array, where each\n        element corresponds to a plotted dataset.\n\n    plot.labels\n        Data labels. During plot creation, each plotted dataset is assigned a\n        label. If the number of labels is less than the number of plotted\n        datasets, labels are reused using modulo arithmetic.\n\n    plot.isDefined( d, i )\n        An accessor function which defines whether a datum is defined. This\n        accessor is used to define how missing values are encoded. The default\n        behavior is to ignore values which are `NaN`.\n\n    plot.colors\n        Data colors. To set the color all plotted datasets, provide a color\n        name. To specify the colors for each dataset, provide an array of\n        colors. During plot creation, each plotted dataset is assigned one of\n        the provided colors. If the number of colors is less than the number of\n        plotted datasets, colors are reused using modulo arithmetic. Lastly,\n        colors may also be specified by providing the name of a predefined color\n        scheme. The following schemes are supported: 'category10', 'category20',\n        'category20b', and 'category20c'.\n\n    plot.lineStyle\n        Data line style(s). The following line styles are supported: '-' (solid\n        line), '--' (dashed line), ':' (dotted line), '-.' (alternating dashes\n        and dots), and 'none' (no line). To specify the line style for each\n        dataset, provide an array of line styles. During plot creation, each\n        plotted dataset is assigned a line style. If the number of line styles\n        is less than the number of plotted datasets, line styles are reused\n        using modulo arithmetic.\n\n    plot.lineOpacity\n        Data line opacity, where an opacity of `0.0` make a line completely\n        transparent and an opacity of `1.0` makes a line completely opaque. To\n        specify the line opacity for each dataset, provide an array of\n        opacities. During plot creation, each plotted dataset is assigned an\n        opacity. If the number of opacities is less than the number of plotted\n        datasets, opacities are reused using modulo arithmetic.\n\n    plot.lineWidth\n        Data line width(s). To specify the line width for each dataset, provide\n        an array of widths. During plot creation, each plotted dataset is\n        assigned a line width. If the number of line widths is less than the\n        number of plotted datasets, line widths are reused using modulo\n        arithmetic.\n\n    plot.symbols\n        Data symbols. The following symbols are supported: 'closed-circle'\n        (closed circles), 'open-circle' (open circles), and 'none' (no symbols).\n        To specify the symbols used for each dataset, provide an array of\n        symbols. During plot creation, each plotted dataset is assigned a\n        symbol. If the number of symbols is less than the number of plotted\n        datasets, symbols are reused using modulo arithmetic.\n\n    plot.symbolSize\n        Symbols size. To specify the symbols size for each dataset, provide an\n        array of sizes. During plot creation, each plotted dataset is assigned\n        a symbols size. If the number of sizes is less than the number of\n        plotted datasets, sizes are reused using modulo arithmetic.\n\n    plot.symbolsOpacity\n        Symbols opacity, where an opacity of `0.0` makes a symbol completely\n        transparent and an opacity of `1.0` makes a symbol completely opaque. To\n        specify the opacity for each dataset, provide an array of opacities.\n        During plot creation, each plotted dataset is assigned an opacity. If\n        the number of opacities is less than the number of plotted datasets,\n        opacities are reused using modulo arithmetic.\n\n    plot.width\n        Plot width (in pixels).\n\n    plot.height\n        Plot height (in pixels).\n\n    plot.paddingLeft\n        Plot left padding (in pixels). Left padding is typically used to create\n        space for a left-oriented y-axis.\n\n    plot.paddingRight\n        Plot right padding (in pixels). Right padding is typically used to\n        create space for a right-oriented y-axis.\n\n    plot.paddingTop\n        Plot top padding (in pixels). Top padding is typically used to create\n        space for a title or top-oriented x-axis.\n\n    plot.paddingBottom\n        Plot bottom padding (in pixels). Bottom padding is typically used to\n        create space for a bottom-oriented x-axis.\n\n    plot.xMin\n        Minimum value of the x-axis domain. When retrieved, if the value has\n        been set to `null`, the returned value is computed from the `x` data.\n\n    plot.xMax\n        Maximum value of the x-axis domain. When retrieved, if the value has\n        been set to `null`, the returned value is computed from the `x` data.\n\n    plot.yMin\n        Minimum value of the y-axis domain. When retrieved, if the value has\n        been set to `null`, the returned value is computed from the `y` data.\n\n    plot.yMax\n        Maximum value of the y-axis domain. When retrieved, if the value has\n        been set to `null`, the returned value is computed from the `y` data.\n\n    plot.xScale\n        Scale function for mapping values to a coordinate along the x-axis. The\n        following `scales` are supported: 'linear' (linear scale) and 'time'\n        (time scale). When retrieved, the returned value is a scale function.\n\n    plot.yScale\n        Scale function for mapping values to a coordinate along the y-axis. The\n        following `scales` are supported: 'linear' (linear scale) and 'time'\n        (time scale). When retrieved, the returned value is a scale function.\n\n    plot.xTickFormat\n        x-axis tick format (e.g., '%H:%M'). When retrieved, if the value has not\n        been set to `null`, the returned value is a formatting function.\n\n    plot.yTickFormat\n        y-axis tick format (e.g., '%%'). When retrieved, if the value has not\n        been set to `null`, the returned value is a formatting function.\n\n    plot.xNumTicks\n        Number of x-axis tick marks. If the value is set to `null`, the number\n        of tick marks is computed internally.\n\n    plot.yNumTicks\n        Number of y-axis tick marks. If the value is set to `null`, the number\n        of tick marks is computed internally.\n\n    plot.xAxisOrient\n        x-axis orientation. The following orientations are supported: 'bottom'\n        and 'top'.\n\n    plot.yAxisOrient\n        y-axis orientation. The following orientations are supported: 'left' and\n        'right'.\n\n    plot.xRug\n        Boolean flag(s) indicating whether to display a rug plot along the x-\n        axis. To specify the flag for each dataset, provide an array of\n        booleans. During plot creation, each plotted dataset is assigned a flag.\n        If the number of flags is less than the number of plotted datasets,\n        flags are reused using modulo arithmetic.\n\n    plot.yRug\n        Boolean flag(s) indicating whether to display a rug plot along the y-\n        axis. To specify the flag for each dataset, provide an array of\n        booleans. During plot creation, each plotted dataset is assigned a flag.\n        If the number of flags is less than the number of plotted datasets,\n        flags are reused using modulo arithmetic.\n\n    plot.xRugOrient\n        x-axis rug orientation. The following orientations are supported:\n        'bottom' or 'top'. To specify the x-axis rug orientation for each\n        dataset, provide an array of orientations. During plot creation, each\n        plotted dataset is assigned an orientation. If the number of\n        orientations is less than the number of plotted datasets, orientations\n        are reused using modulo arithmetic.\n\n    plot.yRugOrient\n        y-axis rug orientation. The following orientations are supported: 'left'\n        or 'right'. To specify the y-axis rug orientation for each dataset,\n        provide an array of orientations. During plot creation, each plotted\n        dataset is assigned an orientation. If the number of orientations is\n        less than the number of plotted datasets, orientations are reused using\n        modulo arithmetic.\n\n    plot.xRugOpacity\n        x-axis rug opacity, where an opacity of `0.0` makes a rug completely\n        transparent and an opacity of `1.0` makes a rug completely opaque. To\n        specify the x-axis rug opacity for each dataset, provide an array of\n        opacities. During plot creation, each plotted dataset is assigned an\n        opacity. If the number of opacities is less than the number of plotted\n        datasets, opacities are reused using modulo arithmetic.\n\n    plot.yRugOpacity\n        y-axis rug opacity, where an opacity of `0.0` makes a rug completely\n        transparent and an opacity of `1.0` makes a rug completely opaque. To\n        specify the y-axis rug opacity for each dataset, provide an array of\n        opacities. During plot creation, each plotted dataset is assigned an\n        opacity. If the number of opacities is less than the number of plotted\n        datasets, opacities are reused using modulo arithmetic.\n\n    plot.xRugSize\n        x-axis rug tick (tassel) size. To specify the x-axis rug size for each\n        dataset, provide an array of sizes. During plot creation, each plotted\n        dataset is assigned a tick size. If the number of sizes is less than the\n        number of plotted datasets, sizes are reused using modulo arithmetic.\n\n    plot.yRugSize\n        y-axis rug tick (tassel) size. To specify the y-axis rug size for each\n        dataset, provide an array of sizes. During plot creation, each plotted\n        dataset is assigned a tick size. If the number of sizes is less than the\n        number of plotted datasets, sizes are reused using modulo arithmetic.\n\n    plot.description\n        Plot description.\n\n    plot.title\n        Plot title.\n\n    plot.xLabel\n        x-axis label.\n\n    plot.yLabel\n        y-axis label.\n\n    plot.engine\n        Plot rendering engine. The following engines are supported: 'svg'.\n\n    plot.renderFormat\n        Plot render format. The following formats are supported: 'vdom' and\n        'html'.\n\n    plot.autoRender\n        Rendering mode. If `true`, an instance renders on each 'change' event;\n        otherwise, rendering must be triggered manually.\n\n    plot.viewer\n        Plot viewer. The following viewers are supported: 'none', 'stdout',\n        'window', and 'browser'.\n\n    plot.autoView\n        Viewer mode. If `true`, an instance generates an updated view on each\n        'render' event; otherwise, generating a view must be triggered manually.\n\n    plot.graphWidth\n        Computed property corresponding to the expected graph width.\n\n    plot.graphHeight\n        Computed property corresponding to the expected graph height.\n\n    plot.xDomain\n        Computed property corresponding to the x-axis domain.\n\n    plot.yDomain\n        Computed property corresponding to the y-axis domain.\n\n    plot.xRange\n        Computed property corresponding to the x-axis range.\n\n    plot.yRange\n        Computed property correspond to the y-axis range.\n\n    plot.xPos\n        A function which maps values to x-axis coordinate values.\n\n    plot.yPos\n        A function which maps values to y-axis coordinate values.\n\n    Examples\n    --------\n    > var plot = plot()\n    <Plot>\n\n    // Provide plot data at instantiation:\n    > var x = [[0.10, 0.20, 0.30]];\n    > var y = [[0.52, 0.79, 0.64]];\n    > plot = plot( x, y )\n    <Plot>\n\n    See Also\n    --------\n    Plot\n","Plot":"\nPlot( [x, y,] [options] )\n    Returns a plot instance for creating 2-dimensional plots.\n\n    `x` and `y` arguments take precedence over `x` and `y` options.\n\n    Parameters\n    ----------\n    x: Array<Array>|Array<TypedArray> (optional)\n        An array of arrays containing x-coordinate values.\n\n    y: Array<Array>|Array<TypedArray> (optional)\n        An array of arrays containing y-coordinate values.\n\n    options: Object (optional)\n        Options.\n\n    options.autoRender: boolean (optional)\n        Boolean indicating whether to re-render on a 'change' event. Default:\n        false.\n\n    options.autoView: boolean (optional)\n        Boolean indicating whether to generate an updated view on a 'render'\n        event. Default: false.\n\n    options.colors: string|Array<string> (optional)\n        Data color(s). Default: 'category10'.\n\n    options.description: string (optional)\n        Plot description.\n\n    options.engine: string (optional)\n        Plot engine. Default: 'svg'.\n\n    options.height: number (optional)\n        Plot height (in pixels). Default: 400.\n\n    options.labels: Array|Array<string> (optional)\n        Data labels.\n\n    options.isDefined: Function (optional)\n        An accessor function indicating whether a datum is defined.\n\n    options.lineStyle: string|Array<string> (optional)\n        Data line style(s). Must be one of: '-', '--', ':', '-.', or 'none'.\n        Default: '-'.\n\n    options.lineOpacity: number|Array<number> (optional)\n        Data line opacity. Must be on the interval [0,1]. Default: 0.9.\n\n    options.lineWidth: integer|Array<integer> (optional)\n        Data line width (in pixels). Default: 2.\n\n    options.paddingBottom: integer (optional)\n        Bottom padding (in pixels). Default: 80.\n\n    options.paddingLeft: integer (optional)\n        Left padding (in pixels). Default: 90.\n\n    options.paddingRight: integer (optional)\n        Right padding (in pixels). Default: 20.\n\n    options.paddingTop: integer (optional)\n        Top padding (in pixels). Default: 80.\n\n    options.renderFormat: string (optional)\n        Plot render format. Must be one of 'vdom' or 'html'. Default: 'vdom'.\n\n    options.symbols: string|Array<string> (optional)\n        Data symbols. Must be one of 'closed-circle', 'open-circle', or 'none'.\n        Default: 'none'.\n\n    options.symbolsOpacity: number|Array<number> (optional)\n        Symbols opacity. Must be on the interval [0,1]. Default: 0.9.\n\n    options.symbolsSize: integer|Array<integer> (optional)\n        Symbols size (in pixels). Default: 6.\n\n    options.title: string (optional)\n        Plot title.\n\n    options.viewer: string (optional)\n        Plot viewer. Must be one of 'browser', 'terminal', 'stdout', 'window',\n        or 'none'. Default: 'none'.\n\n    options.width: number (optional)\n        Plot width (in pixels). Default: 400.\n\n    options.x: Array<Array>|Array<TypedArray> (optional)\n        x-coordinate values.\n\n    options.xAxisOrient: string (optional)\n        x-axis orientation. Must be either 'bottom' or 'top'. Default: 'bottom'.\n\n    options.xLabel: string (optional)\n        x-axis label. Default: 'x'.\n\n    options.xMax: number|null (optional)\n        Maximum value of the x-axis domain. If `null`, the maximum value is\n        calculated from the data. Default: null.\n\n    options.xMin: number|null (optional)\n        Minimum value of the x-axis domain. If `null`, the minimum value is\n        calculated from the data. Default: null.\n\n    options.xNumTicks: integer (optional)\n        Number of x-axis tick marks. Default: 5.\n\n    options.xRug: boolean|Array<boolean> (optional)\n        Boolean flag(s) indicating whether to render one or more rug plots along\n        the x-axis.\n\n    options.xRugOrient: string|Array<string> (optional)\n        x-axis rug plot orientation(s). Must be either 'bottom' or 'top'.\n        Default: 'bottom'.\n\n    options.xRugOpacity: number|Array<number> (optional)\n       x-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n    options.xRugSize: integer|Array<integer> (optional)\n       x-axis rug tick (tassel) size (in pixels). Default: 6.\n\n    options.xScale: string\n       x-axis scale. Default: 'linear'.\n\n    options.xTickFormat: string|null\n       x-axis tick format. Default: null.\n\n    options.y: Array<Array>|Array<TypedArray> (optional)\n        y-coordinate values.\n\n    options.yAxisOrient: string (optional)\n        x-axis orientation. Must be either 'left' or 'right'. Default: 'left'.\n\n    options.yLabel: string (optional)\n        y-axis label. Default: 'y'.\n\n    options.yMax: number|null (optional)\n        Maximum value of the y-axis domain. If `null`, the maximum value is\n        calculated from the data. Default: null.\n\n    options.yMin: number|null (optional)\n        Minimum value of the y-axis domain. If `null`, the minimum value is\n        calculated from the data. Default: null.\n\n    options.yNumTicks: integer (optional)\n        Number of x-axis tick marks. Default: 5.\n\n    options.yRug: boolean|Array<boolean> (optional)\n        Boolean flag(s) indicating whether to render one or more rug plots along\n        the y-axis.\n\n    options.yRugOrient: string|Array<string> (optional)\n        y-axis rug plot orientation(s). Must be either 'left' or 'right'.\n        Default: 'left'.\n\n    options.yRugOpacity: number|Array<number> (optional)\n       y-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n    options.yRugSize: integer|Array<integer> (optional)\n       y-axis rug tick (tassel) size (in pixels). Default: 6.\n\n    options.yScale: string\n       y-axis scale. Default: 'linear'.\n\n    options.yTickFormat: string|null\n       y-axis tick format. Default: null.\n\n    Returns\n    -------\n    plot: Plot\n        Plot instance.\n\n    plot.render()\n        Renders a plot as a virtual DOM tree.\n\n    plot.view( [viewer] )\n        Generates a plot view.\n\n    plot.x\n        x-coordinate values. An assigned value must be an array where each\n        element corresponds to a plotted dataset.\n\n    plot.y\n        y-coordinate values. An assigned value must be an array, where each\n        element corresponds to a plotted dataset.\n\n    plot.labels\n        Data labels. During plot creation, each plotted dataset is assigned a\n        label. If the number of labels is less than the number of plotted\n        datasets, labels are reused using modulo arithmetic.\n\n    plot.isDefined( d, i )\n        An accessor function which defines whether a datum is defined. This\n        accessor is used to define how missing values are encoded. The default\n        behavior is to ignore values which are `NaN`.\n\n    plot.colors\n        Data colors. To set the color all plotted datasets, provide a color\n        name. To specify the colors for each dataset, provide an array of\n        colors. During plot creation, each plotted dataset is assigned one of\n        the provided colors. If the number of colors is less than the number of\n        plotted datasets, colors are reused using modulo arithmetic. Lastly,\n        colors may also be specified by providing the name of a predefined color\n        scheme. The following schemes are supported: 'category10', 'category20',\n        'category20b', and 'category20c'.\n\n    plot.lineStyle\n        Data line style(s). The following line styles are supported: '-' (solid\n        line), '--' (dashed line), ':' (dotted line), '-.' (alternating dashes\n        and dots), and 'none' (no line). To specify the line style for each\n        dataset, provide an array of line styles. During plot creation, each\n        plotted dataset is assigned a line style. If the number of line styles\n        is less than the number of plotted datasets, line styles are reused\n        using modulo arithmetic.\n\n    plot.lineOpacity\n        Data line opacity, where an opacity of `0.0` make a line completely\n        transparent and an opacity of `1.0` makes a line completely opaque. To\n        specify the line opacity for each dataset, provide an array of\n        opacities. During plot creation, each plotted dataset is assigned an\n        opacity. If the number of opacities is less than the number of plotted\n        datasets, opacities are reused using modulo arithmetic.\n\n    plot.lineWidth\n        Data line width(s). To specify the line width for each dataset, provide\n        an array of widths. During plot creation, each plotted dataset is\n        assigned a line width. If the number of line widths is less than the\n        number of plotted datasets, line widths are reused using modulo\n        arithmetic.\n\n    plot.symbols\n        Data symbols. The following symbols are supported: 'closed-circle'\n        (closed circles), 'open-circle' (open circles), and 'none' (no symbols).\n        To specify the symbols used for each dataset, provide an array of\n        symbols. During plot creation, each plotted dataset is assigned a\n        symbol. If the number of symbols is less than the number of plotted\n        datasets, symbols are reused using modulo arithmetic.\n\n    plot.symbolSize\n        Symbols size. To specify the symbols size for each dataset, provide an\n        array of sizes. During plot creation, each plotted dataset is assigned\n        a symbols size. If the number of sizes is less than the number of\n        plotted datasets, sizes are reused using modulo arithmetic.\n\n    plot.symbolsOpacity\n        Symbols opacity, where an opacity of `0.0` makes a symbol completely\n        transparent and an opacity of `1.0` makes a symbol completely opaque. To\n        specify the opacity for each dataset, provide an array of opacities.\n        During plot creation, each plotted dataset is assigned an opacity. If\n        the number of opacities is less than the number of plotted datasets,\n        opacities are reused using modulo arithmetic.\n\n    plot.width\n        Plot width (in pixels).\n\n    plot.height\n        Plot height (in pixels).\n\n    plot.paddingLeft\n        Plot left padding (in pixels). Left padding is typically used to create\n        space for a left-oriented y-axis.\n\n    plot.paddingRight\n        Plot right padding (in pixels). Right padding is typically used to\n        create space for a right-oriented y-axis.\n\n    plot.paddingTop\n        Plot top padding (in pixels). Top padding is typically used to create\n        space for a title or top-oriented x-axis.\n\n    plot.paddingBottom\n        Plot bottom padding (in pixels). Bottom padding is typically used to\n        create space for a bottom-oriented x-axis.\n\n    plot.xMin\n        Minimum value of the x-axis domain. When retrieved, if the value has\n        been set to `null`, the returned value is computed from the `x` data.\n\n    plot.xMax\n        Maximum value of the x-axis domain. When retrieved, if the value has\n        been set to `null`, the returned value is computed from the `x` data.\n\n    plot.yMin\n        Minimum value of the y-axis domain. When retrieved, if the value has\n        been set to `null`, the returned value is computed from the `y` data.\n\n    plot.yMax\n        Maximum value of the y-axis domain. When retrieved, if the value has\n        been set to `null`, the returned value is computed from the `y` data.\n\n    plot.xScale\n        Scale function for mapping values to a coordinate along the x-axis. The\n        following `scales` are supported: 'linear' (linear scale) and 'time'\n        (time scale). When retrieved, the returned value is a scale function.\n\n    plot.yScale\n        Scale function for mapping values to a coordinate along the y-axis. The\n        following `scales` are supported: 'linear' (linear scale) and 'time'\n        (time scale). When retrieved, the returned value is a scale function.\n\n    plot.xTickFormat\n        x-axis tick format (e.g., '%H:%M'). When retrieved, if the value has not\n        been set to `null`, the returned value is a formatting function.\n\n    plot.yTickFormat\n        y-axis tick format (e.g., '%%'). When retrieved, if the value has not\n        been set to `null`, the returned value is a formatting function.\n\n    plot.xNumTicks\n        Number of x-axis tick marks. If the value is set to `null`, the number\n        of tick marks is computed internally.\n\n    plot.yNumTicks\n        Number of y-axis tick marks. If the value is set to `null`, the number\n        of tick marks is computed internally.\n\n    plot.xAxisOrient\n        x-axis orientation. The following orientations are supported: 'bottom'\n        and 'top'.\n\n    plot.yAxisOrient\n        y-axis orientation. The following orientations are supported: 'left' and\n        'right'.\n\n    plot.xRug\n        Boolean flag(s) indicating whether to display a rug plot along the x-\n        axis. To specify the flag for each dataset, provide an array of\n        booleans. During plot creation, each plotted dataset is assigned a flag.\n        If the number of flags is less than the number of plotted datasets,\n        flags are reused using modulo arithmetic.\n\n    plot.yRug\n        Boolean flag(s) indicating whether to display a rug plot along the y-\n        axis. To specify the flag for each dataset, provide an array of\n        booleans. During plot creation, each plotted dataset is assigned a flag.\n        If the number of flags is less than the number of plotted datasets,\n        flags are reused using modulo arithmetic.\n\n    plot.xRugOrient\n        x-axis rug orientation. The following orientations are supported:\n        'bottom' or 'top'. To specify the x-axis rug orientation for each\n        dataset, provide an array of orientations. During plot creation, each\n        plotted dataset is assigned an orientation. If the number of\n        orientations is less than the number of plotted datasets, orientations\n        are reused using modulo arithmetic.\n\n    plot.yRugOrient\n        y-axis rug orientation. The following orientations are supported: 'left'\n        or 'right'. To specify the y-axis rug orientation for each dataset,\n        provide an array of orientations. During plot creation, each plotted\n        dataset is assigned an orientation. If the number of orientations is\n        less than the number of plotted datasets, orientations are reused using\n        modulo arithmetic.\n\n    plot.xRugOpacity\n        x-axis rug opacity, where an opacity of `0.0` makes a rug completely\n        transparent and an opacity of `1.0` makes a rug completely opaque. To\n        specify the x-axis rug opacity for each dataset, provide an array of\n        opacities. During plot creation, each plotted dataset is assigned an\n        opacity. If the number of opacities is less than the number of plotted\n        datasets, opacities are reused using modulo arithmetic.\n\n    plot.yRugOpacity\n        y-axis rug opacity, where an opacity of `0.0` makes a rug completely\n        transparent and an opacity of `1.0` makes a rug completely opaque. To\n        specify the y-axis rug opacity for each dataset, provide an array of\n        opacities. During plot creation, each plotted dataset is assigned an\n        opacity. If the number of opacities is less than the number of plotted\n        datasets, opacities are reused using modulo arithmetic.\n\n    plot.xRugSize\n        x-axis rug tick (tassel) size. To specify the x-axis rug size for each\n        dataset, provide an array of sizes. During plot creation, each plotted\n        dataset is assigned a tick size. If the number of sizes is less than the\n        number of plotted datasets, sizes are reused using modulo arithmetic.\n\n    plot.yRugSize\n        y-axis rug tick (tassel) size. To specify the y-axis rug size for each\n        dataset, provide an array of sizes. During plot creation, each plotted\n        dataset is assigned a tick size. If the number of sizes is less than the\n        number of plotted datasets, sizes are reused using modulo arithmetic.\n\n    plot.description\n        Plot description.\n\n    plot.title\n        Plot title.\n\n    plot.xLabel\n        x-axis label.\n\n    plot.yLabel\n        y-axis label.\n\n    plot.engine\n        Plot rendering engine. The following engines are supported: 'svg'.\n\n    plot.renderFormat\n        Plot render format. The following formats are supported: 'vdom' and\n        'html'.\n\n    plot.autoRender\n        Rendering mode. If `true`, an instance renders on each 'change' event;\n        otherwise, rendering must be triggered manually.\n\n    plot.viewer\n        Plot viewer. The following viewers are supported: 'none', 'stdout',\n        'window', and 'browser'.\n\n    plot.autoView\n        Viewer mode. If `true`, an instance generates an updated view on each\n        'render' event; otherwise, generating a view must be triggered manually.\n\n    plot.graphWidth\n        Computed property corresponding to the expected graph width.\n\n    plot.graphHeight\n        Computed property corresponding to the expected graph height.\n\n    plot.xDomain\n        Computed property corresponding to the x-axis domain.\n\n    plot.yDomain\n        Computed property corresponding to the y-axis domain.\n\n    plot.xRange\n        Computed property corresponding to the x-axis range.\n\n    plot.yRange\n        Computed property correspond to the y-axis range.\n\n    plot.xPos\n        A function which maps values to x-axis coordinate values.\n\n    plot.yPos\n        A function which maps values to y-axis coordinate values.\n\n    Examples\n    --------\n    > var plot = Plot()\n    <Plot>\n\n    // Provide plot data at instantiation:\n    > var x = [[0.10, 0.20, 0.30]];\n    > var y = [[0.52, 0.79, 0.64]];\n    > plot = Plot( x, y )\n    <Plot>\n\n    See Also\n    --------\n    plot\n","pluck":"\npluck( arr, prop[, options] )\n    Extracts a property value from each element of an object array.\n\n    The function skips `null` and `undefined` array elements.\n\n    Extracted values are not cloned.\n\n    Parameters\n    ----------\n    arr: Array\n        Source array.\n\n    prop: string\n        Property to access.\n\n    options: Object (optional)\n        Options.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to return a new data structure. To mutate the\n        input data structure (e.g., when input values can be discarded or when\n        optimizing memory usage), set the `copy` option to `false`. Default:\n        true.\n\n    Returns\n    -------\n    out: Array\n        Destination array.\n\n    Examples\n    --------\n    > var arr = [\n    ...     { 'a': 1, 'b': 2 },\n    ...     { 'a': 0.5, 'b': 3 }\n    ... ];\n    > var out = pluck( arr, 'a' )\n    [ 1, 0.5 ]\n\n    > arr = [\n    ...     { 'a': 1, 'b': 2 },\n    ...     { 'a': 0.5, 'b': 3 }\n    ... ];\n    > out = pluck( arr, 'a', { 'copy': false } )\n    [ 1, 0.5 ]\n    > var bool = ( arr[ 0 ] === out[ 0 ] )\n    true\n\n    See Also\n    --------\n    deepPluck, pick\n","pop":"\npop( collection )\n    Removes and returns the last element of a collection.\n\n    The function returns an array with two elements: the shortened collection\n    and the removed element.\n\n    If the input collection is a typed array whose length is greater than `0`,\n    the first return value does not equal the input reference.\n\n    For purposes of generality, always treat the output collection as distinct\n    from the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        A collection. If the collection is an `Object`, the value should be\n        array-like.\n\n    Returns\n    -------\n    out: Array\n        Updated collection and the removed item.\n\n    Examples\n    --------\n    // Arrays:\n    > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > var out = pop( arr )\n    [ [ 1.0, 2.0, 3.0, 4.0 ], 5.0 ]\n\n    // Typed arrays:\n    > arr = new Float64Array( [ 1.0, 2.0 ] );\n    > out = pop( arr )\n    [ <Float64Array>[ 1.0 ], 2.0 ]\n\n    // Array-like object:\n    > arr = { 'length': 2, '0': 1.0, '1': 2.0 };\n    > out = pop( arr )\n    [ { 'length': 1, '0': 1.0 }, 2.0 ]\n\n    See Also\n    --------\n    push, shift, unshift\n","porterStemmer":"\nporterStemmer( word )\n    Extracts the stem of a given word.\n\n    Parameters\n    ----------\n    word: string\n        Input word.\n\n    Returns\n    -------\n    out: string\n        Word stem.\n\n    Examples\n    --------\n    > var out = porterStemmer( 'walking' )\n    'walk'\n    > out = porterStemmer( 'walked' )\n    'walk'\n    > out = porterStemmer( 'walks' )\n    'walk'\n    > out = porterStemmer( '' )\n    ''\n\n","prepend":"\nprepend( collection1, collection2 )\n    Adds the elements of one collection to the beginning of another collection.\n\n    If the input collection is a typed array, the output value does not equal\n    the input reference and the underlying `ArrayBuffer` may *not* be the same\n    as the `ArrayBuffer` belonging to the input view.\n\n    For purposes of generality, always treat the output collection as distinct\n    from the input collection.\n\n    Parameters\n    ----------\n    collection1: Array|TypedArray|Object\n        A collection. If the collection is an `Object`, the collection should be\n        array-like.\n\n    collection2: Array|TypedArray|Object\n        A collection containing the elements to add. If the collection is an\n        `Object`, the collection should be array-like.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Updated collection.\n\n    Examples\n    --------\n    // Arrays:\n    > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > arr = prepend( arr, [ 6.0, 7.0 ] )\n    [ 6.0, 7.0, 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Typed arrays:\n    > arr = new Float64Array( [ 1.0, 2.0 ] );\n    > arr = prepend( arr, [ 3.0, 4.0 ] )\n    <Float64Array>[ 3.0, 4.0, 1.0, 2.0 ]\n\n    // Array-like object:\n    > arr = { 'length': 1, '0': 1.0 };\n    > arr = prepend( arr, [ 2.0, 3.0 ] )\n    { 'length': 3, '0': 2.0, '1': 3.0, '2': 1.0 }\n\n    See Also\n    --------\n    append, unshift\n","prevGraphemeClusterBreak":"\nprevGraphemeClusterBreak( str[, fromIndex] )\n    Returns the previous extended grapheme cluster break in a string before a\n    specified position.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    fromIndex: integer (optional)\n        Position. Default: str.length-1.\n\n    Returns\n    -------\n    out: integer\n        Previous extended grapheme cluster break position.\n\n    Examples\n    --------\n    > var out = prevGraphemeClusterBreak( 'last man standing', 4 )\n    3\n    > out = prevGraphemeClusterBreak( 'presidential election', 8 )\n    7\n    > out = prevGraphemeClusterBreak( 'अनुच्छेद', 2 )\n    0\n    > out = prevGraphemeClusterBreak( '🌷', 1 )\n    -1\n\n    See Also\n    --------\n    numGraphemeClusters, nextGraphemeClusterBreak","PRIMES_100K":"\nPRIMES_100K()\n    Returns an array containing the first 100,000 prime numbers.\n\n    Returns\n    -------\n    out: Array<number>\n        List of primes.\n\n    Examples\n    --------\n    > var list = PRIMES_100K()\n    [ 2, 3, 5, ... ]\n\n    See Also\n    --------\n    iterPrimesSeq\n","properties":"\nproperties( value )\n    Returns an array of an object's own enumerable and non-enumerable property\n    names and symbols.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    props: Array\n        List of an object's own enumerable and non-enumerable properties.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var props = properties( obj )\n    [ 'beep' ]\n\n    See Also\n    --------\n    defineProperties, inheritedProperties, propertiesIn, propertyNames, propertySymbols\n","propertiesIn":"\npropertiesIn( value )\n    Returns an array of an object's own and inherited property names and\n    symbols.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    props: Array\n        List of an object's own and inherited property names and symbols.\n\n    Examples\n    --------\n    > var props = propertiesIn( [] )\n\n    See Also\n    --------\n    defineProperties, inheritedProperties, properties, propertyNamesIn, propertySymbolsIn\n","propertyDescriptor":"\npropertyDescriptor( value, property )\n    Returns a property descriptor for an object's own property.\n\n    If provided `null` or `undefined` or provided a non-existent property, the\n    function returns `null`.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    property: string|symbol\n        Property name.\n\n    Returns\n    -------\n    desc: Object|null\n        Property descriptor.\n\n    Examples\n    --------\n    > var obj = { 'a': 'b' };\n    > var desc = propertyDescriptor( obj, 'a' )\n    {...}\n\n    See Also\n    --------\n    hasOwnProp, defineProperty, propertyDescriptorIn, propertyDescriptors\n","propertyDescriptorIn":"\npropertyDescriptorIn( value, property )\n    Returns a property descriptor for an object's own or inherited property.\n\n    If provided `null` or `undefined` or provided a non-existent property, the\n    function returns `null`.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    property: string|symbol\n        Property name.\n\n    Returns\n    -------\n    desc: Object|null\n        Property descriptor.\n\n    Examples\n    --------\n    > var obj = { 'a': 'b' };\n    > var desc = propertyDescriptorIn( obj, 'a' )\n    {...}\n\n    See Also\n    --------\n    hasProp, defineProperty, propertyDescriptor, propertyDescriptorsIn\n","propertyDescriptors":"\npropertyDescriptors( value )\n    Returns an object's own property descriptors.\n\n    If provided `null` or `undefined`, the function returns an empty object.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    desc: Object\n        Property descriptors.\n\n    Examples\n    --------\n    > var obj = { 'a': 'b' };\n    > var desc = propertyDescriptors( obj )\n    { 'a': {...} }\n\n    See Also\n    --------\n    defineProperty, defineProperties, propertyDescriptor, propertyDescriptorsIn, propertyNames, propertySymbols\n","propertyDescriptorsIn":"\npropertyDescriptorsIn( value )\n    Returns an object's own and inherited property descriptors.\n\n    If provided `null` or `undefined`, the function returns an empty object.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    desc: Object\n        An object's own and inherited property descriptors.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var desc = propertyDescriptorsIn( obj )\n    { 'beep': {...}, 'foo': {...}, ... }\n\n    See Also\n    --------\n    defineProperties, propertyDescriptorIn, propertyDescriptors, propertyNamesIn, propertySymbolsIn\n","propertyNames":"\npropertyNames( value )\n    Returns an array of an object's own enumerable and non-enumerable property\n    names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's own enumerable and non-enumerable property names.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var keys = propertyNames( obj )\n    [ 'beep' ]\n\n    See Also\n    --------\n    objectKeys, nonEnumerablePropertyNames, propertyNamesIn, propertySymbols\n","propertyNamesIn":"\npropertyNamesIn( value )\n    Returns an array of an object's own and inherited enumerable and non-\n    enumerable property names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's own and inherited enumerable and non-enumerable\n        property names.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var keys = propertyNamesIn( obj )\n    e.g., [ 'beep', 'foo', ... ]\n\n    See Also\n    --------\n    objectKeys, nonEnumerablePropertyNamesIn, propertyNames, propertySymbolsIn\n","propertySymbols":"\npropertySymbols( value )\n    Returns an array of an object's own symbol properties.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's own symbol properties.\n\n    Examples\n    --------\n    > var s = propertySymbols( {} )\n\n    See Also\n    --------\n    propertyNames, propertySymbolsIn\n","propertySymbolsIn":"\npropertySymbolsIn( value )\n    Returns an array of an object's own and inherited symbol properties.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's own and inherited symbol properties.\n\n    Examples\n    --------\n    > var s = propertySymbolsIn( [] )\n\n    See Also\n    --------\n    propertyNamesIn, propertySymbols\n","Proxy":"\nProxy( target, handlers )\n    Returns a proxy object implementing custom behavior for specified object\n    operations.\n\n    The following \"traps\" are supported:\n\n    - getPrototypeOf( target )\n        Trap for `Object.getPrototypeOf()`. Can be used to intercept the\n        `instanceof` operator. The method must return an object or `null`.\n\n    - setPrototypeOf( target, prototype )\n        Trap for `Object.setPrototypeOf()`. The method must return a boolean\n        indicating if prototype successfully set.\n\n    - isExtensible( target )\n        Trap for `Object.isExtensible()`. The method must return a boolean.\n\n    - preventExtensions( target )\n        Trap for `Object.preventExtensions()`. The method must return a boolean.\n\n    - getOwnPropertyDescriptor( target, property )\n        Trap for `Object.getOwnPropertyDescriptor()`. The method must return an\n        object or `undefined`.\n\n    - defineProperty( target, property, descriptor )\n        Trap for `Object.defineProperty()`. The method must return a boolean\n        indicating whether the operation succeeded.\n\n    - has( target, property )\n        Trap for the `in` operator. The method must return a boolean.\n\n    - get( target, property, receiver )\n        Trap for retrieving property values. The method can return any value.\n\n    - set( target, property, value, receiver )\n        Trap for setting property values. The method should return a boolean\n        indicating whether assignment succeeded.\n\n    - deleteProperty( target, property )\n        Trap for the `delete` operator. The method must return a boolean\n        indicating whether operation succeeded.\n\n    - ownKeys( target )\n        Trap for `Object.keys`, `Object.getOwnPropertyNames()`, and\n        `Object.getOwnPropertySymbols()`. The method must return an enumerable\n        object.\n\n    - apply( target, thisArg, argumentsList )\n        Trap for a function call. The method can return any value.\n\n    - construct( target, argumentsList, newTarget )\n        Trap for the `new` operator. The method must return an object.\n\n    All traps are optional. If a trap is not defined, the default behavior is to\n    forward the operation to the target.\n\n    Parameters\n    ----------\n    target: Object\n        Object which the proxy virtualizes.\n\n    handlers: Object\n        Object whose properties are functions which define the behavior of the\n        proxy when performing operations.\n\n    Returns\n    -------\n    p: Object\n        Proxy object.\n\n    Examples\n    --------\n    > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n    > var h = { 'get': get };\n    > var p = new Proxy( {}, h );\n    > p.a = 3.14;\n    > p.a\n    6.28\n\n\nProxy.revocable( target, handlers )\n    Returns a revocable proxy object.\n\n    Parameters\n    ----------\n    target: Object\n        Object which the proxy virtualizes.\n\n    handlers: Object\n        Object whose properties are functions which define the behavior of the\n        proxy when performing operations.\n\n    Returns\n    -------\n    p: Object\n        Revocable proxy object.\n\n    p.proxy: Object\n        Proxy object.\n\n    p.revoke: Function\n        Invalidates a proxy, rendering a proxy object unusable.\n\n    Examples\n    --------\n    > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n    > var h = { 'get': get };\n    > var p = Proxy.revocable( {}, h );\n    > p.proxy.a = 3.14;\n    > p.proxy.a\n    6.28\n    > p.revoke();\n\n","Proxy.revocable":"\nProxy.revocable( target, handlers )\n    Returns a revocable proxy object.\n\n    Parameters\n    ----------\n    target: Object\n        Object which the proxy virtualizes.\n\n    handlers: Object\n        Object whose properties are functions which define the behavior of the\n        proxy when performing operations.\n\n    Returns\n    -------\n    p: Object\n        Revocable proxy object.\n\n    p.proxy: Object\n        Proxy object.\n\n    p.revoke: Function\n        Invalidates a proxy, rendering a proxy object unusable.\n\n    Examples\n    --------\n    > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n    > var h = { 'get': get };\n    > var p = Proxy.revocable( {}, h );\n    > p.proxy.a = 3.14;\n    > p.proxy.a\n    6.28\n    > p.revoke();","push":"\npush( collection, ...items )\n    Adds one or more elements to the end of a collection.\n\n    If the input collection is a typed array, the output value does not equal\n    the input reference and the underlying `ArrayBuffer` may *not* be the same\n    as the `ArrayBuffer` belonging to the input view.\n\n    For purposes of generality, always treat the output collection as distinct\n    from the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        A collection. If the collection is an `Object`, the collection should be\n        array-like.\n\n    items: ...any\n        Items to add.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Updated collection.\n\n    Examples\n    --------\n    // Arrays:\n    > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > arr = push( arr, 6.0, 7.0 )\n    [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]\n\n    // Typed arrays:\n    > arr = new Float64Array( [ 1.0, 2.0 ] );\n    > arr = push( arr, 3.0, 4.0 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Array-like object:\n    > arr = { 'length': 0 };\n    > arr = push( arr, 1.0, 2.0 )\n    { 'length': 2, '0': 1.0, '1': 2.0 }\n\n    See Also\n    --------\n    pop, shift, unshift\n","quarterOfYear":"\nquarterOfYear( [month] )\n    Returns the quarter of the year.\n\n    By default, the function returns the quarter of the year for the current\n    month in the current year (according to local time). To determine the\n    quarter for a particular month, provide either a month or a `Date`\n    object.\n\n    A `month` may be either a month's integer value, three letter abbreviation,\n    or full name (case insensitive).\n\n    Parameters\n    ----------\n    month: integer|string|Date (optional)\n        Month (or `Date`).\n\n    Returns\n    -------\n    out: integer\n        Quarter of the year.\n\n    Examples\n    --------\n    > var q = quarterOfYear( new Date() )\n    <number>\n    > q = quarterOfYear( 4 )\n    2\n    > q = quarterOfYear( 'June' )\n    2\n\n    // Other ways to supply month:\n    > q = quarterOfYear( 'April' )\n    2\n    > q = quarterOfYear( 'apr' )\n    2\n\n    See Also\n    --------\n    dayOfYear\n","random.array.arcsine":"\nrandom.array.arcsine( len, a, b[, options] )\n    Returns an array containing pseudorandom numbers drawn from an arcsine\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.arcsine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.arcsine.assign( a, b, out )\n    Fills an array with pseudorandom numbers drawn from an arcsine distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.arcsine.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.arcsine.factory( [a, b, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an arcsine distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.arcsine.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.arcsine.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.arcsine.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.arcsine.PRNG;\n\n\nrandom.array.arcsine.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.arcsine.seed;\n\n\nrandom.array.arcsine.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.arcsine.seedLength;\n\n\nrandom.array.arcsine.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.arcsine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.arcsine.state\n    <Uint32Array>\n\n    > out = random.array.arcsine( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.arcsine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.arcsine.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.arcsine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.arcsine.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.arcsine.stateLength;\n\n\nrandom.array.arcsine.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.arcsine.byteLength;\n\n    See Also\n    --------\n    base.random.arcsine, random.strided.arcsine\n","random.array.arcsine.assign":"\nrandom.array.arcsine.assign( a, b, out )\n    Fills an array with pseudorandom numbers drawn from an arcsine distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.arcsine.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.arcsine.factory":"\nrandom.array.arcsine.factory( [a, b, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an arcsine distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.arcsine.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.arcsine.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.arcsine.PRNG":"\nrandom.array.arcsine.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.arcsine.PRNG;","random.array.arcsine.seed":"\nrandom.array.arcsine.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.arcsine.seed;","random.array.arcsine.seedLength":"\nrandom.array.arcsine.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.arcsine.seedLength;","random.array.arcsine.state":"\nrandom.array.arcsine.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.arcsine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.arcsine.state\n    <Uint32Array>\n\n    > out = random.array.arcsine( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.arcsine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.arcsine.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.arcsine( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.arcsine.stateLength":"\nrandom.array.arcsine.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.arcsine.stateLength;","random.array.arcsine.byteLength":"\nrandom.array.arcsine.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.arcsine.byteLength;\n\n    See Also\n    --------\n    base.random.arcsine, random.strided.arcsine","random.array.bernoulli":"\nrandom.array.bernoulli( len, p[, options] )\n    Returns an array containing pseudorandom numbers drawn from a Bernoulli\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.bernoulli( 3, 0.5 )\n    <Float64Array>\n\n\nrandom.array.bernoulli.assign( p, out )\n    Fills an array with pseudorandom numbers drawn from a Bernoulli\n    distribution.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.bernoulli.assign( 0.5, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.bernoulli.factory( [p, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Bernoulli distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.bernoulli.factory();\n    > var out = fcn( 3, 0.5 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.bernoulli.factory( 0.5 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.bernoulli.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.bernoulli.PRNG;\n\n\nrandom.array.bernoulli.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.bernoulli.seed;\n\n\nrandom.array.bernoulli.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.bernoulli.seedLength;\n\n\nrandom.array.bernoulli.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.bernoulli( 3, 0.5 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.bernoulli.state\n    <Uint32Array>\n\n    > out = random.array.bernoulli( 3, 0.5 )\n    <Float64Array>\n    > out = random.array.bernoulli( 3, 0.5 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.bernoulli.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.bernoulli( 3, 0.5 )\n    <Float64Array>\n\n\nrandom.array.bernoulli.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.bernoulli.stateLength;\n\n\nrandom.array.bernoulli.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.bernoulli.byteLength;\n\n    See Also\n    --------\n    base.random.bernoulli, random.strided.bernoulli\n","random.array.bernoulli.assign":"\nrandom.array.bernoulli.assign( p, out )\n    Fills an array with pseudorandom numbers drawn from a Bernoulli\n    distribution.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.bernoulli.assign( 0.5, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.bernoulli.factory":"\nrandom.array.bernoulli.factory( [p, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Bernoulli distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.bernoulli.factory();\n    > var out = fcn( 3, 0.5 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.bernoulli.factory( 0.5 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.bernoulli.PRNG":"\nrandom.array.bernoulli.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.bernoulli.PRNG;","random.array.bernoulli.seed":"\nrandom.array.bernoulli.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.bernoulli.seed;","random.array.bernoulli.seedLength":"\nrandom.array.bernoulli.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.bernoulli.seedLength;","random.array.bernoulli.state":"\nrandom.array.bernoulli.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.bernoulli( 3, 0.5 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.bernoulli.state\n    <Uint32Array>\n\n    > out = random.array.bernoulli( 3, 0.5 )\n    <Float64Array>\n    > out = random.array.bernoulli( 3, 0.5 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.bernoulli.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.bernoulli( 3, 0.5 )\n    <Float64Array>","random.array.bernoulli.stateLength":"\nrandom.array.bernoulli.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.bernoulli.stateLength;","random.array.bernoulli.byteLength":"\nrandom.array.bernoulli.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.bernoulli.byteLength;\n\n    See Also\n    --------\n    base.random.bernoulli, random.strided.bernoulli","random.array.beta":"\nrandom.array.beta( len, alpha, beta[, options] )\n    Returns an array containing pseudorandom numbers drawn from a beta\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    alpha: number\n        First shape parameter.\n\n    beta: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.beta( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.beta.assign( alpha, beta, out )\n    Fills an array with pseudorandom numbers drawn from a beta distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        First shape parameter.\n\n    beta: number\n        Second shape parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.beta.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.beta.factory( [alpha, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a beta distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        First shape parameter.\n\n    beta: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.beta.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.beta.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.beta.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.beta.PRNG;\n\n\nrandom.array.beta.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.beta.seed;\n\n\nrandom.array.beta.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.beta.seedLength;\n\n\nrandom.array.beta.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.beta( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.beta.state\n    <Uint32Array>\n\n    > out = random.array.beta( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.beta( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.beta.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.beta( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.beta.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.beta.stateLength;\n\n\nrandom.array.beta.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.beta.byteLength;\n\n    See Also\n    --------\n    base.random.beta, random.strided.beta\n","random.array.beta.assign":"\nrandom.array.beta.assign( alpha, beta, out )\n    Fills an array with pseudorandom numbers drawn from a beta distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        First shape parameter.\n\n    beta: number\n        Second shape parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.beta.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.beta.factory":"\nrandom.array.beta.factory( [alpha, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a beta distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        First shape parameter.\n\n    beta: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.beta.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.beta.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.beta.PRNG":"\nrandom.array.beta.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.beta.PRNG;","random.array.beta.seed":"\nrandom.array.beta.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.beta.seed;","random.array.beta.seedLength":"\nrandom.array.beta.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.beta.seedLength;","random.array.beta.state":"\nrandom.array.beta.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.beta( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.beta.state\n    <Uint32Array>\n\n    > out = random.array.beta( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.beta( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.beta.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.beta( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.beta.stateLength":"\nrandom.array.beta.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.beta.stateLength;","random.array.beta.byteLength":"\nrandom.array.beta.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.beta.byteLength;\n\n    See Also\n    --------\n    base.random.beta, random.strided.beta","random.array.betaprime":"\nrandom.array.betaprime( len, alpha, beta[, options] )\n    Returns an array containing pseudorandom numbers drawn from a beta prime\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    alpha: number\n        First shape parameter.\n\n    beta: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.betaprime( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.betaprime.assign( alpha, beta, out )\n    Fills an array with pseudorandom numbers drawn from a beta prime\n    distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        First shape parameter.\n\n    beta: number\n        Second shape parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.betaprime.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.betaprime.factory( [alpha, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a beta prime distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        First shape parameter.\n\n    beta: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.betaprime.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.betaprime.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.betaprime.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.betaprime.PRNG;\n\n\nrandom.array.betaprime.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.betaprime.seed;\n\n\nrandom.array.betaprime.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.betaprime.seedLength;\n\n\nrandom.array.betaprime.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.betaprime( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.betaprime.state\n    <Uint32Array>\n\n    > out = random.array.betaprime( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.betaprime( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.betaprime.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.betaprime( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.betaprime.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.betaprime.stateLength;\n\n\nrandom.array.betaprime.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.betaprime.byteLength;\n\n    See Also\n    --------\n    base.random.betaprime, random.strided.betaprime\n","random.array.betaprime.assign":"\nrandom.array.betaprime.assign( alpha, beta, out )\n    Fills an array with pseudorandom numbers drawn from a beta prime\n    distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        First shape parameter.\n\n    beta: number\n        Second shape parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.betaprime.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.betaprime.factory":"\nrandom.array.betaprime.factory( [alpha, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a beta prime distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        First shape parameter.\n\n    beta: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.betaprime.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.betaprime.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.betaprime.PRNG":"\nrandom.array.betaprime.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.betaprime.PRNG;","random.array.betaprime.seed":"\nrandom.array.betaprime.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.betaprime.seed;","random.array.betaprime.seedLength":"\nrandom.array.betaprime.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.betaprime.seedLength;","random.array.betaprime.state":"\nrandom.array.betaprime.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.betaprime( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.betaprime.state\n    <Uint32Array>\n\n    > out = random.array.betaprime( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.betaprime( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.betaprime.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.betaprime( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.betaprime.stateLength":"\nrandom.array.betaprime.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.betaprime.stateLength;","random.array.betaprime.byteLength":"\nrandom.array.betaprime.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.betaprime.byteLength;\n\n    See Also\n    --------\n    base.random.betaprime, random.strided.betaprime","random.array.binomial":"\nrandom.array.binomial( len, n, p[, options] )\n    Returns an array containing pseudorandom numbers drawn from a binomial\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    n: number\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.binomial( 3, 17, 0.5 )\n    <Float64Array>\n\n\nrandom.array.binomial.assign( n, p, out )\n    Fills an array with pseudorandom numbers drawn from a binomial distribution.\n\n    Parameters\n    ----------\n    n: number\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.binomial.assign( 17, 0.5, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.binomial.factory( [n, p, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a binomial distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    n: number (optional)\n        Number of trials.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.binomial.factory();\n    > var out = fcn( 3, 17, 0.5 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.binomial.factory( 17, 0.5 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.binomial.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.binomial.PRNG;\n\n\nrandom.array.binomial.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.binomial.seed;\n\n\nrandom.array.binomial.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.binomial.seedLength;\n\n\nrandom.array.binomial.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.binomial( 3, 17, 0.5 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.binomial.state\n    <Uint32Array>\n\n    > out = random.array.binomial( 3, 17, 0.5 )\n    <Float64Array>\n    > out = random.array.binomial( 3, 17, 0.5 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.binomial.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.binomial( 3, 17, 0.5 )\n    <Float64Array>\n\n\nrandom.array.binomial.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.binomial.stateLength;\n\n\nrandom.array.binomial.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.binomial.byteLength;\n\n    See Also\n    --------\n    random.array.negativeBinomial, base.random.binomial\n","random.array.binomial.assign":"\nrandom.array.binomial.assign( n, p, out )\n    Fills an array with pseudorandom numbers drawn from a binomial distribution.\n\n    Parameters\n    ----------\n    n: number\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.binomial.assign( 17, 0.5, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.binomial.factory":"\nrandom.array.binomial.factory( [n, p, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a binomial distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    n: number (optional)\n        Number of trials.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.binomial.factory();\n    > var out = fcn( 3, 17, 0.5 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.binomial.factory( 17, 0.5 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.binomial.PRNG":"\nrandom.array.binomial.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.binomial.PRNG;","random.array.binomial.seed":"\nrandom.array.binomial.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.binomial.seed;","random.array.binomial.seedLength":"\nrandom.array.binomial.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.binomial.seedLength;","random.array.binomial.state":"\nrandom.array.binomial.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.binomial( 3, 17, 0.5 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.binomial.state\n    <Uint32Array>\n\n    > out = random.array.binomial( 3, 17, 0.5 )\n    <Float64Array>\n    > out = random.array.binomial( 3, 17, 0.5 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.binomial.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.binomial( 3, 17, 0.5 )\n    <Float64Array>","random.array.binomial.stateLength":"\nrandom.array.binomial.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.binomial.stateLength;","random.array.binomial.byteLength":"\nrandom.array.binomial.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.binomial.byteLength;\n\n    See Also\n    --------\n    random.array.negativeBinomial, base.random.binomial","random.array.cauchy":"\nrandom.array.cauchy( len, x0, gamma[, options] )\n    Returns an array containing pseudorandom numbers drawn from a Cauchy\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    x0: number\n        Location parameter.\n\n    gamma: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.cauchy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.cauchy.assign( x0, gamma, out )\n    Fills an array with pseudorandom numbers drawn from a Cauchy distribution.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    gamma: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.cauchy.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.cauchy.factory( [x0, gamma, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Cauchy distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    x0: number (optional)\n        Location parameter.\n\n    gamma: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.cauchy.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.cauchy.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.cauchy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.cauchy.PRNG;\n\n\nrandom.array.cauchy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.cauchy.seed;\n\n\nrandom.array.cauchy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.cauchy.seedLength;\n\n\nrandom.array.cauchy.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.cauchy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.cauchy.state\n    <Uint32Array>\n\n    > out = random.array.cauchy( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.cauchy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.cauchy.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.cauchy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.cauchy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.cauchy.stateLength;\n\n\nrandom.array.cauchy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.cauchy.byteLength;\n\n    See Also\n    --------\n    base.random.cauchy\n","random.array.cauchy.assign":"\nrandom.array.cauchy.assign( x0, gamma, out )\n    Fills an array with pseudorandom numbers drawn from a Cauchy distribution.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    gamma: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.cauchy.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.cauchy.factory":"\nrandom.array.cauchy.factory( [x0, gamma, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Cauchy distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    x0: number (optional)\n        Location parameter.\n\n    gamma: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.cauchy.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.cauchy.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.cauchy.PRNG":"\nrandom.array.cauchy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.cauchy.PRNG;","random.array.cauchy.seed":"\nrandom.array.cauchy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.cauchy.seed;","random.array.cauchy.seedLength":"\nrandom.array.cauchy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.cauchy.seedLength;","random.array.cauchy.state":"\nrandom.array.cauchy.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.cauchy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.cauchy.state\n    <Uint32Array>\n\n    > out = random.array.cauchy( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.cauchy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.cauchy.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.cauchy( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.cauchy.stateLength":"\nrandom.array.cauchy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.cauchy.stateLength;","random.array.cauchy.byteLength":"\nrandom.array.cauchy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.cauchy.byteLength;\n\n    See Also\n    --------\n    base.random.cauchy","random.array.chi":"\nrandom.array.chi( len, k[, options] )\n    Returns an array containing pseudorandom numbers drawn from a chi\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    k: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.chi( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.chi.assign( k, out )\n    Fills an array with pseudorandom numbers drawn from a chi distribution.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.chi.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.chi.factory( [k, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a chi distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.chi.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.chi.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.chi.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.chi.PRNG;\n\n\nrandom.array.chi.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.chi.seed;\n\n\nrandom.array.chi.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.chi.seedLength;\n\n\nrandom.array.chi.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.chi( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.chi.state\n    <Uint32Array>\n\n    > out = random.array.chi( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.chi( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.chi.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.chi( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.chi.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.chi.stateLength;\n\n\nrandom.array.chi.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.chi.byteLength;\n\n    See Also\n    --------\n    base.random.chi, random.strided.chi\n","random.array.chi.assign":"\nrandom.array.chi.assign( k, out )\n    Fills an array with pseudorandom numbers drawn from a chi distribution.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.chi.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.chi.factory":"\nrandom.array.chi.factory( [k, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a chi distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.chi.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.chi.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.chi.PRNG":"\nrandom.array.chi.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.chi.PRNG;","random.array.chi.seed":"\nrandom.array.chi.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.chi.seed;","random.array.chi.seedLength":"\nrandom.array.chi.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.chi.seedLength;","random.array.chi.state":"\nrandom.array.chi.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.chi( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.chi.state\n    <Uint32Array>\n\n    > out = random.array.chi( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.chi( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.chi.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.chi( 3, 2.0 )\n    <Float64Array>","random.array.chi.stateLength":"\nrandom.array.chi.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.chi.stateLength;","random.array.chi.byteLength":"\nrandom.array.chi.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.chi.byteLength;\n\n    See Also\n    --------\n    base.random.chi, random.strided.chi","random.array.chisquare":"\nrandom.array.chisquare( len, k[, options] )\n    Returns an array containing pseudorandom numbers drawn from a chi-square\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    k: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.chisquare( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.chisquare.assign( k, out )\n    Fills an array with pseudorandom numbers drawn from a chi-square\n    distribution.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.chisquare.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.chisquare.factory( [k, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a chi-square distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.chisquare.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.chisquare.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.chisquare.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.chisquare.PRNG;\n\n\nrandom.array.chisquare.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.chisquare.seed;\n\n\nrandom.array.chisquare.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.chisquare.seedLength;\n\n\nrandom.array.chisquare.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.chisquare( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.chisquare.state\n    <Uint32Array>\n\n    > out = random.array.chisquare( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.chisquare( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.chisquare.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.chisquare( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.chisquare.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.chisquare.stateLength;\n\n\nrandom.array.chisquare.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.chisquare.byteLength;\n\n    See Also\n    --------\n    base.random.chisquare, random.strided.chisquare\n","random.array.chisquare.assign":"\nrandom.array.chisquare.assign( k, out )\n    Fills an array with pseudorandom numbers drawn from a chi-square\n    distribution.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.chisquare.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.chisquare.factory":"\nrandom.array.chisquare.factory( [k, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a chi-square distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.chisquare.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.chisquare.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.chisquare.PRNG":"\nrandom.array.chisquare.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.chisquare.PRNG;","random.array.chisquare.seed":"\nrandom.array.chisquare.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.chisquare.seed;","random.array.chisquare.seedLength":"\nrandom.array.chisquare.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.chisquare.seedLength;","random.array.chisquare.state":"\nrandom.array.chisquare.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.chisquare( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.chisquare.state\n    <Uint32Array>\n\n    > out = random.array.chisquare( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.chisquare( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.chisquare.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.chisquare( 3, 2.0 )\n    <Float64Array>","random.array.chisquare.stateLength":"\nrandom.array.chisquare.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.chisquare.stateLength;","random.array.chisquare.byteLength":"\nrandom.array.chisquare.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.chisquare.byteLength;\n\n    See Also\n    --------\n    base.random.chisquare, random.strided.chisquare","random.array.cosine":"\nrandom.array.cosine( len, mu, s[, options] )\n    Returns an array containing pseudorandom numbers drawn from a raised cosine\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    mu: number\n        Mean.\n\n    s: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.cosine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.cosine.assign( mu, s, out )\n    Fills an array with pseudorandom numbers drawn from a raised cosine\n    distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Mean.\n\n    s: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.cosine.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.cosine.factory( [mu, s, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a raised cosine distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Mean.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.cosine.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.cosine.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.cosine.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.cosine.PRNG;\n\n\nrandom.array.cosine.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.cosine.seed;\n\n\nrandom.array.cosine.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.cosine.seedLength;\n\n\nrandom.array.cosine.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.cosine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.cosine.state\n    <Uint32Array>\n\n    > out = random.array.cosine( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.cosine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.cosine.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.cosine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.cosine.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.cosine.stateLength;\n\n\nrandom.array.cosine.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.cosine.byteLength;\n\n    See Also\n    --------\n    base.random.cosine, random.strided.cosine\n","random.array.cosine.assign":"\nrandom.array.cosine.assign( mu, s, out )\n    Fills an array with pseudorandom numbers drawn from a raised cosine\n    distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Mean.\n\n    s: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.cosine.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.cosine.factory":"\nrandom.array.cosine.factory( [mu, s, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a raised cosine distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Mean.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.cosine.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.cosine.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.cosine.PRNG":"\nrandom.array.cosine.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.cosine.PRNG;","random.array.cosine.seed":"\nrandom.array.cosine.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.cosine.seed;","random.array.cosine.seedLength":"\nrandom.array.cosine.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.cosine.seedLength;","random.array.cosine.state":"\nrandom.array.cosine.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.cosine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.cosine.state\n    <Uint32Array>\n\n    > out = random.array.cosine( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.cosine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.cosine.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.cosine( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.cosine.stateLength":"\nrandom.array.cosine.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.cosine.stateLength;","random.array.cosine.byteLength":"\nrandom.array.cosine.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.cosine.byteLength;\n\n    See Also\n    --------\n    base.random.cosine, random.strided.cosine","random.array.discreteUniform":"\nrandom.array.discreteUniform( len, a, b[, options] )\n    Returns an array containing pseudorandom numbers drawn from a discrete\n    uniform distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.discreteUniform( 3, -10, 10 )\n    <Float64Array>\n\n\nrandom.array.discreteUniform.assign( a, b, out )\n    Fills an array with pseudorandom numbers drawn from a discrete uniform\n    distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.discreteUniform.assign( -10, 10, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.discreteUniform.factory( [a, b, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a discrete uniform distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom integers. If provided, the `state` and `seed`\n        options are ignored. In order to seed the returned pseudorandom number\n        generator, one must seed the provided `prng` (assuming the provided\n        `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n        properties specifying the minimum and maximum possible pseudorandom\n        integers.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.discreteUniform.factory();\n    > var out = fcn( 3, -10, 10 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.discreteUniform.factory( -10, 10 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.discreteUniform.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.discreteUniform.PRNG;\n\n\nrandom.array.discreteUniform.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.discreteUniform.seed;\n\n\nrandom.array.discreteUniform.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.discreteUniform.seedLength;\n\n\nrandom.array.discreteUniform.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.discreteUniform( 3, -10, 10 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.discreteUniform.state\n    <Uint32Array>\n\n    > out = random.array.discreteUniform( 3, -10, 10 )\n    <Float64Array>\n    > out = random.array.discreteUniform( 3, -10, 10 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.discreteUniform.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.discreteUniform( 3, -10, 10 )\n    <Float64Array>\n\n\nrandom.array.discreteUniform.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.discreteUniform.stateLength;\n\n\nrandom.array.discreteUniform.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.discreteUniform.byteLength;\n\n    See Also\n    --------\n    random.array.uniform, base.random.discreteUniform, random.strided.discreteUniform\n","random.array.discreteUniform.assign":"\nrandom.array.discreteUniform.assign( a, b, out )\n    Fills an array with pseudorandom numbers drawn from a discrete uniform\n    distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.discreteUniform.assign( -10, 10, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.discreteUniform.factory":"\nrandom.array.discreteUniform.factory( [a, b, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a discrete uniform distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom integers. If provided, the `state` and `seed`\n        options are ignored. In order to seed the returned pseudorandom number\n        generator, one must seed the provided `prng` (assuming the provided\n        `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n        properties specifying the minimum and maximum possible pseudorandom\n        integers.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.discreteUniform.factory();\n    > var out = fcn( 3, -10, 10 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.discreteUniform.factory( -10, 10 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.discreteUniform.PRNG":"\nrandom.array.discreteUniform.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.discreteUniform.PRNG;","random.array.discreteUniform.seed":"\nrandom.array.discreteUniform.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.discreteUniform.seed;","random.array.discreteUniform.seedLength":"\nrandom.array.discreteUniform.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.discreteUniform.seedLength;","random.array.discreteUniform.state":"\nrandom.array.discreteUniform.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.discreteUniform( 3, -10, 10 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.discreteUniform.state\n    <Uint32Array>\n\n    > out = random.array.discreteUniform( 3, -10, 10 )\n    <Float64Array>\n    > out = random.array.discreteUniform( 3, -10, 10 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.discreteUniform.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.discreteUniform( 3, -10, 10 )\n    <Float64Array>","random.array.discreteUniform.stateLength":"\nrandom.array.discreteUniform.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.discreteUniform.stateLength;","random.array.discreteUniform.byteLength":"\nrandom.array.discreteUniform.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.discreteUniform.byteLength;\n\n    See Also\n    --------\n    random.array.uniform, base.random.discreteUniform, random.strided.discreteUniform","random.array.erlang":"\nrandom.array.erlang( len, k, lambda[, options] )\n    Returns an array containing pseudorandom numbers drawn from an Erlang\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    k: number\n        Shape parameter.\n\n    lambda: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.erlang( 3, 2, 5.0 )\n    <Float64Array>\n\n\nrandom.array.erlang.assign( k, lambda, out )\n    Fills an array with pseudorandom numbers drawn from an Erlang distribution.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    lambda: number\n        Rate parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.erlang.assign( 2, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.erlang.factory( [k, lambda, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an Erlang distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Shape parameter.\n\n    lambda: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.erlang.factory();\n    > var out = fcn( 3, 2, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.erlang.factory( 2, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.erlang.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.erlang.PRNG;\n\n\nrandom.array.erlang.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.erlang.seed;\n\n\nrandom.array.erlang.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.erlang.seedLength;\n\n\nrandom.array.erlang.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.erlang( 3, 2, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.erlang.state\n    <Uint32Array>\n\n    > out = random.array.erlang( 3, 2, 5.0 )\n    <Float64Array>\n    > out = random.array.erlang( 3, 2, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.erlang.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.erlang( 3, 2, 5.0 )\n    <Float64Array>\n\n\nrandom.array.erlang.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.erlang.stateLength;\n\n\nrandom.array.erlang.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.erlang.byteLength;\n\n    See Also\n    --------\n    base.random.erlang\n","random.array.erlang.assign":"\nrandom.array.erlang.assign( k, lambda, out )\n    Fills an array with pseudorandom numbers drawn from an Erlang distribution.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    lambda: number\n        Rate parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.erlang.assign( 2, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.erlang.factory":"\nrandom.array.erlang.factory( [k, lambda, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an Erlang distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Shape parameter.\n\n    lambda: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.erlang.factory();\n    > var out = fcn( 3, 2, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.erlang.factory( 2, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.erlang.PRNG":"\nrandom.array.erlang.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.erlang.PRNG;","random.array.erlang.seed":"\nrandom.array.erlang.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.erlang.seed;","random.array.erlang.seedLength":"\nrandom.array.erlang.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.erlang.seedLength;","random.array.erlang.state":"\nrandom.array.erlang.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.erlang( 3, 2, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.erlang.state\n    <Uint32Array>\n\n    > out = random.array.erlang( 3, 2, 5.0 )\n    <Float64Array>\n    > out = random.array.erlang( 3, 2, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.erlang.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.erlang( 3, 2, 5.0 )\n    <Float64Array>","random.array.erlang.stateLength":"\nrandom.array.erlang.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.erlang.stateLength;","random.array.erlang.byteLength":"\nrandom.array.erlang.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.erlang.byteLength;\n\n    See Also\n    --------\n    base.random.erlang","random.array.exponential":"\nrandom.array.exponential( len, lambda[, options] )\n    Returns an array containing pseudorandom numbers drawn from an exponential\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    lambda: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.exponential( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.exponential.assign( lambda, out )\n    Fills an array with pseudorandom numbers drawn from an exponential\n    distribution.\n\n    Parameters\n    ----------\n    lambda: number\n        Rate parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.exponential.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.exponential.factory( [lambda, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an exponential distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    lambda: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.exponential.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.exponential.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.exponential.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.exponential.PRNG;\n\n\nrandom.array.exponential.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.exponential.seed;\n\n\nrandom.array.exponential.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.exponential.seedLength;\n\n\nrandom.array.exponential.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.exponential( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.exponential.state\n    <Uint32Array>\n\n    > out = random.array.exponential( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.exponential( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.exponential.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.exponential( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.exponential.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.exponential.stateLength;\n\n\nrandom.array.exponential.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.exponential.byteLength;\n\n    See Also\n    --------\n    base.random.exponential, random.strided.exponential\n","random.array.exponential.assign":"\nrandom.array.exponential.assign( lambda, out )\n    Fills an array with pseudorandom numbers drawn from an exponential\n    distribution.\n\n    Parameters\n    ----------\n    lambda: number\n        Rate parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.exponential.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.exponential.factory":"\nrandom.array.exponential.factory( [lambda, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an exponential distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    lambda: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.exponential.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.exponential.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.exponential.PRNG":"\nrandom.array.exponential.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.exponential.PRNG;","random.array.exponential.seed":"\nrandom.array.exponential.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.exponential.seed;","random.array.exponential.seedLength":"\nrandom.array.exponential.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.exponential.seedLength;","random.array.exponential.state":"\nrandom.array.exponential.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.exponential( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.exponential.state\n    <Uint32Array>\n\n    > out = random.array.exponential( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.exponential( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.exponential.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.exponential( 3, 2.0 )\n    <Float64Array>","random.array.exponential.stateLength":"\nrandom.array.exponential.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.exponential.stateLength;","random.array.exponential.byteLength":"\nrandom.array.exponential.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.exponential.byteLength;\n\n    See Also\n    --------\n    base.random.exponential, random.strided.exponential","random.array.f":"\nrandom.array.f( len, d1, d2[, options] )\n    Returns an array containing pseudorandom numbers drawn from an F\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    d1: number\n        Degrees of freedom.\n\n    d2: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.f( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.f.assign( d1, d2, out )\n    Fills an array with pseudorandom numbers drawn from an F distribution.\n\n    Parameters\n    ----------\n    d1: number\n        Degrees of freedom.\n\n    d2: number\n        Degrees of freedom.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.f.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.f.factory( [d1, d2, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an F distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    d1: number (optional)\n        Degrees of freedom.\n\n    d2: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.f.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.f.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.f.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.f.PRNG;\n\n\nrandom.array.f.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.f.seed;\n\n\nrandom.array.f.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.f.seedLength;\n\n\nrandom.array.f.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.f( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.f.state\n    <Uint32Array>\n\n    > out = random.array.f( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.f( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.f.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.f( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.f.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.f.stateLength;\n\n\nrandom.array.f.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.f.byteLength;\n\n    See Also\n    --------\n    base.random.f\n","random.array.f.assign":"\nrandom.array.f.assign( d1, d2, out )\n    Fills an array with pseudorandom numbers drawn from an F distribution.\n\n    Parameters\n    ----------\n    d1: number\n        Degrees of freedom.\n\n    d2: number\n        Degrees of freedom.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.f.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.f.factory":"\nrandom.array.f.factory( [d1, d2, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an F distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    d1: number (optional)\n        Degrees of freedom.\n\n    d2: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.f.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.f.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.f.PRNG":"\nrandom.array.f.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.f.PRNG;","random.array.f.seed":"\nrandom.array.f.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.f.seed;","random.array.f.seedLength":"\nrandom.array.f.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.f.seedLength;","random.array.f.state":"\nrandom.array.f.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.f( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.f.state\n    <Uint32Array>\n\n    > out = random.array.f( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.f( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.f.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.f( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.f.stateLength":"\nrandom.array.f.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.f.stateLength;","random.array.f.byteLength":"\nrandom.array.f.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.f.byteLength;\n\n    See Also\n    --------\n    base.random.f","random.array.frechet":"\nrandom.array.frechet( len, alpha, s, m[, options] )\n    Returns an array containing pseudorandom numbers drawn from a Fréchet\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    alpha: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n\nrandom.array.frechet.assign( alpha, s, m, out )\n    Fills an array with pseudorandom numbers drawn from a Fréchet distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.frechet.assign( 2.0, 5.0, 3.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.frechet.factory( [alpha, s, m, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Fréchet distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        Shape parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    m: number (optional)\n        Location parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.frechet.factory();\n    > var out = fcn( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.frechet.factory( 2.0, 5.0, 3.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.frechet.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.frechet.PRNG;\n\n\nrandom.array.frechet.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.frechet.seed;\n\n\nrandom.array.frechet.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.frechet.seedLength;\n\n\nrandom.array.frechet.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.frechet.state\n    <Uint32Array>\n\n    > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n    > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.frechet.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n\nrandom.array.frechet.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.frechet.stateLength;\n\n\nrandom.array.frechet.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.frechet.byteLength;\n\n    See Also\n    --------\n    base.random.frechet\n","random.array.frechet.assign":"\nrandom.array.frechet.assign( alpha, s, m, out )\n    Fills an array with pseudorandom numbers drawn from a Fréchet distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.frechet.assign( 2.0, 5.0, 3.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.frechet.factory":"\nrandom.array.frechet.factory( [alpha, s, m, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Fréchet distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        Shape parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    m: number (optional)\n        Location parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.frechet.factory();\n    > var out = fcn( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.frechet.factory( 2.0, 5.0, 3.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.frechet.PRNG":"\nrandom.array.frechet.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.frechet.PRNG;","random.array.frechet.seed":"\nrandom.array.frechet.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.frechet.seed;","random.array.frechet.seedLength":"\nrandom.array.frechet.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.frechet.seedLength;","random.array.frechet.state":"\nrandom.array.frechet.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.frechet.state\n    <Uint32Array>\n\n    > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n    > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.frechet.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>","random.array.frechet.stateLength":"\nrandom.array.frechet.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.frechet.stateLength;","random.array.frechet.byteLength":"\nrandom.array.frechet.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.frechet.byteLength;\n\n    See Also\n    --------\n    base.random.frechet","random.array.gamma":"\nrandom.array.gamma( len, alpha, beta[, options] )\n    Returns an array containing pseudorandom numbers drawn from a gamma\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    alpha: number\n        Shape parameter.\n\n    beta: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.gamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.gamma.assign( alpha, beta, out )\n    Fills an array with pseudorandom numbers drawn from a gamma distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        Shape parameter.\n\n    beta: number\n        Rate parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.gamma.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.gamma.factory( [alpha, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a gamma distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        Shape parameter.\n\n    beta: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.gamma.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.gamma.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.gamma.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.gamma.PRNG;\n\n\nrandom.array.gamma.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.gamma.seed;\n\n\nrandom.array.gamma.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.gamma.seedLength;\n\n\nrandom.array.gamma.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.gamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.gamma.state\n    <Uint32Array>\n\n    > out = random.array.gamma( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.gamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.gamma.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.gamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.gamma.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.gamma.stateLength;\n\n\nrandom.array.gamma.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.gamma.byteLength;\n\n    See Also\n    --------\n    base.random.gamma, random.strided.gamma\n","random.array.gamma.assign":"\nrandom.array.gamma.assign( alpha, beta, out )\n    Fills an array with pseudorandom numbers drawn from a gamma distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        Shape parameter.\n\n    beta: number\n        Rate parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.gamma.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.gamma.factory":"\nrandom.array.gamma.factory( [alpha, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a gamma distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        Shape parameter.\n\n    beta: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.gamma.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.gamma.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.gamma.PRNG":"\nrandom.array.gamma.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.gamma.PRNG;","random.array.gamma.seed":"\nrandom.array.gamma.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.gamma.seed;","random.array.gamma.seedLength":"\nrandom.array.gamma.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.gamma.seedLength;","random.array.gamma.state":"\nrandom.array.gamma.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.gamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.gamma.state\n    <Uint32Array>\n\n    > out = random.array.gamma( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.gamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.gamma.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.gamma( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.gamma.stateLength":"\nrandom.array.gamma.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.gamma.stateLength;","random.array.gamma.byteLength":"\nrandom.array.gamma.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.gamma.byteLength;\n\n    See Also\n    --------\n    base.random.gamma, random.strided.gamma","random.array.geometric":"\nrandom.array.geometric( len, p[, options] )\n    Returns an array containing pseudorandom numbers drawn from a geometric\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.geometric( 3, 0.01 )\n    <Float64Array>\n\n\nrandom.array.geometric.assign( p, out )\n    Fills an array with pseudorandom numbers drawn from a geometric\n    distribution.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.geometric.assign( 0.01, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.geometric.factory( [p, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a geometric distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.geometric.factory();\n    > var out = fcn( 3, 0.01 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.geometric.factory( 0.01 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.geometric.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.geometric.PRNG;\n\n\nrandom.array.geometric.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.geometric.seed;\n\n\nrandom.array.geometric.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.geometric.seedLength;\n\n\nrandom.array.geometric.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.geometric( 3, 0.01 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.geometric.state\n    <Uint32Array>\n\n    > out = random.array.geometric( 3, 0.01 )\n    <Float64Array>\n    > out = random.array.geometric( 3, 0.01 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.geometric.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.geometric( 3, 0.01 )\n    <Float64Array>\n\n\nrandom.array.geometric.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.geometric.stateLength;\n\n\nrandom.array.geometric.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.geometric.byteLength;\n\n    See Also\n    --------\n    base.random.geometric, random.strided.geometric\n","random.array.geometric.assign":"\nrandom.array.geometric.assign( p, out )\n    Fills an array with pseudorandom numbers drawn from a geometric\n    distribution.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.geometric.assign( 0.01, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.geometric.factory":"\nrandom.array.geometric.factory( [p, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a geometric distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.geometric.factory();\n    > var out = fcn( 3, 0.01 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.geometric.factory( 0.01 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.geometric.PRNG":"\nrandom.array.geometric.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.geometric.PRNG;","random.array.geometric.seed":"\nrandom.array.geometric.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.geometric.seed;","random.array.geometric.seedLength":"\nrandom.array.geometric.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.geometric.seedLength;","random.array.geometric.state":"\nrandom.array.geometric.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.geometric( 3, 0.01 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.geometric.state\n    <Uint32Array>\n\n    > out = random.array.geometric( 3, 0.01 )\n    <Float64Array>\n    > out = random.array.geometric( 3, 0.01 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.geometric.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.geometric( 3, 0.01 )\n    <Float64Array>","random.array.geometric.stateLength":"\nrandom.array.geometric.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.geometric.stateLength;","random.array.geometric.byteLength":"\nrandom.array.geometric.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.geometric.byteLength;\n\n    See Also\n    --------\n    base.random.geometric, random.strided.geometric","random.array.gumbel":"\nrandom.array.gumbel( len, mu, beta[, options] )\n    Returns an array containing pseudorandom numbers drawn from a Gumbel\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    mu: number\n        Mean.\n\n    beta: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.gumbel( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.gumbel.assign( mu, beta, out )\n    Fills an array with pseudorandom numbers drawn from a Gumbel distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Mean.\n\n    beta: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.gumbel.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.gumbel.factory( [mu, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Gumbel distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Mean.\n\n    beta: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.gumbel.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.gumbel.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.gumbel.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.gumbel.PRNG;\n\n\nrandom.array.gumbel.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.gumbel.seed;\n\n\nrandom.array.gumbel.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.gumbel.seedLength;\n\n\nrandom.array.gumbel.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.gumbel( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.gumbel.state\n    <Uint32Array>\n\n    > out = random.array.gumbel( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.gumbel( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.gumbel.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.gumbel( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.gumbel.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.gumbel.stateLength;\n\n\nrandom.array.gumbel.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.gumbel.byteLength;\n\n    See Also\n    --------\n    base.random.gumbel\n","random.array.gumbel.assign":"\nrandom.array.gumbel.assign( mu, beta, out )\n    Fills an array with pseudorandom numbers drawn from a Gumbel distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Mean.\n\n    beta: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.gumbel.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.gumbel.factory":"\nrandom.array.gumbel.factory( [mu, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Gumbel distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Mean.\n\n    beta: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.gumbel.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.gumbel.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.gumbel.PRNG":"\nrandom.array.gumbel.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.gumbel.PRNG;","random.array.gumbel.seed":"\nrandom.array.gumbel.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.gumbel.seed;","random.array.gumbel.seedLength":"\nrandom.array.gumbel.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.gumbel.seedLength;","random.array.gumbel.state":"\nrandom.array.gumbel.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.gumbel( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.gumbel.state\n    <Uint32Array>\n\n    > out = random.array.gumbel( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.gumbel( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.gumbel.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.gumbel( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.gumbel.stateLength":"\nrandom.array.gumbel.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.gumbel.stateLength;","random.array.gumbel.byteLength":"\nrandom.array.gumbel.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.gumbel.byteLength;\n\n    See Also\n    --------\n    base.random.gumbel","random.array.hypergeometric":"\nrandom.array.hypergeometric( len, N, K, n[, options] )\n    Returns an array containing pseudorandom numbers drawn from a hypergeometric\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    N: number\n        Population size.\n\n    K: number\n        Subpopulation size.\n\n    n: number\n        Number of draws.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.hypergeometric( 3, 20, 10, 7 )\n    <Float64Array>\n\n\nrandom.array.hypergeometric.assign( N, K, n, out )\n    Fills an array with pseudorandom numbers drawn from a hypergeometric\n    distribution.\n\n    Parameters\n    ----------\n    N: number\n        Population size.\n\n    K: number\n        Subpopulation size.\n\n    n: number\n        Number of draws.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.hypergeometric.assign( 20, 10, 7, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.hypergeometric.factory( [N, K, n, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a hypergeometric distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    N: number (optional)\n        Population size.\n\n    K: number (optional)\n        Subpopulation size.\n\n    n: number (optional)\n        Number of draws.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.hypergeometric.factory();\n    > var out = fcn( 3, 20, 10, 7 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.hypergeometric.factory( 20, 10, 7 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.hypergeometric.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.hypergeometric.PRNG;\n\n\nrandom.array.hypergeometric.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.hypergeometric.seed;\n\n\nrandom.array.hypergeometric.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.hypergeometric.seedLength;\n\n\nrandom.array.hypergeometric.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.hypergeometric( 3, 20, 10, 7 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.hypergeometric.state\n    <Uint32Array>\n\n    > out = random.array.hypergeometric( 3, 20, 10, 7 )\n    <Float64Array>\n    > out = random.array.hypergeometric( 3, 20, 10, 7 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.hypergeometric.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.hypergeometric( 3, 20, 10, 7 )\n    <Float64Array>\n\n\nrandom.array.hypergeometric.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.hypergeometric.stateLength;\n\n\nrandom.array.hypergeometric.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.hypergeometric.byteLength;\n\n    See Also\n    --------\n    base.random.hypergeometric\n","random.array.hypergeometric.assign":"\nrandom.array.hypergeometric.assign( N, K, n, out )\n    Fills an array with pseudorandom numbers drawn from a hypergeometric\n    distribution.\n\n    Parameters\n    ----------\n    N: number\n        Population size.\n\n    K: number\n        Subpopulation size.\n\n    n: number\n        Number of draws.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.hypergeometric.assign( 20, 10, 7, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.hypergeometric.factory":"\nrandom.array.hypergeometric.factory( [N, K, n, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a hypergeometric distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    N: number (optional)\n        Population size.\n\n    K: number (optional)\n        Subpopulation size.\n\n    n: number (optional)\n        Number of draws.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.hypergeometric.factory();\n    > var out = fcn( 3, 20, 10, 7 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.hypergeometric.factory( 20, 10, 7 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.hypergeometric.PRNG":"\nrandom.array.hypergeometric.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.hypergeometric.PRNG;","random.array.hypergeometric.seed":"\nrandom.array.hypergeometric.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.hypergeometric.seed;","random.array.hypergeometric.seedLength":"\nrandom.array.hypergeometric.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.hypergeometric.seedLength;","random.array.hypergeometric.state":"\nrandom.array.hypergeometric.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.hypergeometric( 3, 20, 10, 7 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.hypergeometric.state\n    <Uint32Array>\n\n    > out = random.array.hypergeometric( 3, 20, 10, 7 )\n    <Float64Array>\n    > out = random.array.hypergeometric( 3, 20, 10, 7 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.hypergeometric.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.hypergeometric( 3, 20, 10, 7 )\n    <Float64Array>","random.array.hypergeometric.stateLength":"\nrandom.array.hypergeometric.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.hypergeometric.stateLength;","random.array.hypergeometric.byteLength":"\nrandom.array.hypergeometric.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.hypergeometric.byteLength;\n\n    See Also\n    --------\n    base.random.hypergeometric","random.array.invgamma":"\nrandom.array.invgamma( len, alpha, beta[, options] )\n    Returns an array containing pseudorandom numbers drawn from an inverse gamma\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    alpha: number\n        Shape parameter.\n\n    beta: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.invgamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.invgamma.assign( alpha, beta, out )\n    Fills an array with pseudorandom numbers drawn from an inverse gamma\n    distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        Shape parameter.\n\n    beta: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.invgamma.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.invgamma.factory( [alpha, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an inverse gamma distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        Shape parameter.\n\n    beta: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.invgamma.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.invgamma.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.invgamma.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.invgamma.PRNG;\n\n\nrandom.array.invgamma.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.invgamma.seed;\n\n\nrandom.array.invgamma.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.invgamma.seedLength;\n\n\nrandom.array.invgamma.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.invgamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.invgamma.state\n    <Uint32Array>\n\n    > out = random.array.invgamma( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.invgamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.invgamma.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.invgamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.invgamma.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.invgamma.stateLength;\n\n\nrandom.array.invgamma.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.invgamma.byteLength;\n\n    See Also\n    --------\n    base.random.invgamma, random.strided.invgamma\n","random.array.invgamma.assign":"\nrandom.array.invgamma.assign( alpha, beta, out )\n    Fills an array with pseudorandom numbers drawn from an inverse gamma\n    distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        Shape parameter.\n\n    beta: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.invgamma.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.invgamma.factory":"\nrandom.array.invgamma.factory( [alpha, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an inverse gamma distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        Shape parameter.\n\n    beta: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.invgamma.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.invgamma.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.invgamma.PRNG":"\nrandom.array.invgamma.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.invgamma.PRNG;","random.array.invgamma.seed":"\nrandom.array.invgamma.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.invgamma.seed;","random.array.invgamma.seedLength":"\nrandom.array.invgamma.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.invgamma.seedLength;","random.array.invgamma.state":"\nrandom.array.invgamma.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.invgamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.invgamma.state\n    <Uint32Array>\n\n    > out = random.array.invgamma( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.invgamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.invgamma.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.invgamma( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.invgamma.stateLength":"\nrandom.array.invgamma.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.invgamma.stateLength;","random.array.invgamma.byteLength":"\nrandom.array.invgamma.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.invgamma.byteLength;\n\n    See Also\n    --------\n    base.random.invgamma, random.strided.invgamma","random.array.kumaraswamy":"\nrandom.array.kumaraswamy( len, a, b[, options] )\n    Returns an array containing pseudorandom numbers drawn from Kumaraswamy's\n    double bounded distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.kumaraswamy.assign( a, b, out )\n    Fills an array with pseudorandom numbers drawn from Kumaraswamy's double\n    bounded distribution.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.kumaraswamy.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.kumaraswamy.factory( [a, b, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from Kumaraswamy's double bounded distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    a: number (optional)\n        First shape parameter.\n\n    b: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.kumaraswamy.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.kumaraswamy.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.kumaraswamy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.kumaraswamy.PRNG;\n\n\nrandom.array.kumaraswamy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.kumaraswamy.seed;\n\n\nrandom.array.kumaraswamy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.kumaraswamy.seedLength;\n\n\nrandom.array.kumaraswamy.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.kumaraswamy.state\n    <Uint32Array>\n\n    > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.kumaraswamy.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.kumaraswamy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.kumaraswamy.stateLength;\n\n\nrandom.array.kumaraswamy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.kumaraswamy.byteLength;\n\n    See Also\n    --------\n    base.random.kumaraswamy\n","random.array.kumaraswamy.assign":"\nrandom.array.kumaraswamy.assign( a, b, out )\n    Fills an array with pseudorandom numbers drawn from Kumaraswamy's double\n    bounded distribution.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.kumaraswamy.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.kumaraswamy.factory":"\nrandom.array.kumaraswamy.factory( [a, b, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from Kumaraswamy's double bounded distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    a: number (optional)\n        First shape parameter.\n\n    b: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.kumaraswamy.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.kumaraswamy.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.kumaraswamy.PRNG":"\nrandom.array.kumaraswamy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.kumaraswamy.PRNG;","random.array.kumaraswamy.seed":"\nrandom.array.kumaraswamy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.kumaraswamy.seed;","random.array.kumaraswamy.seedLength":"\nrandom.array.kumaraswamy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.kumaraswamy.seedLength;","random.array.kumaraswamy.state":"\nrandom.array.kumaraswamy.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.kumaraswamy.state\n    <Uint32Array>\n\n    > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.kumaraswamy.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.kumaraswamy.stateLength":"\nrandom.array.kumaraswamy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.kumaraswamy.stateLength;","random.array.kumaraswamy.byteLength":"\nrandom.array.kumaraswamy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.kumaraswamy.byteLength;\n\n    See Also\n    --------\n    base.random.kumaraswamy","random.array.laplace":"\nrandom.array.laplace( len, mu, b[, options] )\n    Returns an array containing pseudorandom numbers drawn from a Laplace\n    (double exponential) distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    mu: number\n        Mean.\n\n    b: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.laplace( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.laplace.assign( mu, b, out )\n    Fills an array with pseudorandom numbers drawn from a Laplace (double\n    exponential) distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Mean.\n\n    b: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.laplace.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.laplace.factory( [mu, b, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Laplace (double exponential) distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Mean.\n\n    b: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.laplace.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.laplace.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.laplace.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.laplace.PRNG;\n\n\nrandom.array.laplace.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.laplace.seed;\n\n\nrandom.array.laplace.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.laplace.seedLength;\n\n\nrandom.array.laplace.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.laplace( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.laplace.state\n    <Uint32Array>\n\n    > out = random.array.laplace( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.laplace( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.laplace.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.laplace( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.laplace.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.laplace.stateLength;\n\n\nrandom.array.laplace.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.laplace.byteLength;\n\n    See Also\n    --------\n    base.random.laplace\n","random.array.laplace.assign":"\nrandom.array.laplace.assign( mu, b, out )\n    Fills an array with pseudorandom numbers drawn from a Laplace (double\n    exponential) distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Mean.\n\n    b: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.laplace.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.laplace.factory":"\nrandom.array.laplace.factory( [mu, b, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Laplace (double exponential) distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Mean.\n\n    b: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.laplace.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.laplace.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.laplace.PRNG":"\nrandom.array.laplace.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.laplace.PRNG;","random.array.laplace.seed":"\nrandom.array.laplace.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.laplace.seed;","random.array.laplace.seedLength":"\nrandom.array.laplace.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.laplace.seedLength;","random.array.laplace.state":"\nrandom.array.laplace.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.laplace( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.laplace.state\n    <Uint32Array>\n\n    > out = random.array.laplace( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.laplace( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.laplace.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.laplace( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.laplace.stateLength":"\nrandom.array.laplace.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.laplace.stateLength;","random.array.laplace.byteLength":"\nrandom.array.laplace.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.laplace.byteLength;\n\n    See Also\n    --------\n    base.random.laplace","random.array.levy":"\nrandom.array.levy( len, mu, c[, options] )\n    Returns an array containing pseudorandom numbers drawn from a Lévy\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    mu: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.levy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.levy.assign( mu, c, out )\n    Fills an array with pseudorandom numbers drawn from a Lévy distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.levy.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.levy.factory( [mu, c, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Lévy distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Location parameter.\n\n    c: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.levy.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.levy.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.levy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.levy.PRNG;\n\n\nrandom.array.levy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.levy.seed;\n\n\nrandom.array.levy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.levy.seedLength;\n\n\nrandom.array.levy.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.levy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.levy.state\n    <Uint32Array>\n\n    > out = random.array.levy( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.levy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.levy.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.levy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.levy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.levy.stateLength;\n\n\nrandom.array.levy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.levy.byteLength;\n\n    See Also\n    --------\n    base.random.levy\n","random.array.levy.assign":"\nrandom.array.levy.assign( mu, c, out )\n    Fills an array with pseudorandom numbers drawn from a Lévy distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.levy.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.levy.factory":"\nrandom.array.levy.factory( [mu, c, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Lévy distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Location parameter.\n\n    c: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.levy.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.levy.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.levy.PRNG":"\nrandom.array.levy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.levy.PRNG;","random.array.levy.seed":"\nrandom.array.levy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.levy.seed;","random.array.levy.seedLength":"\nrandom.array.levy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.levy.seedLength;","random.array.levy.state":"\nrandom.array.levy.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.levy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.levy.state\n    <Uint32Array>\n\n    > out = random.array.levy( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.levy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.levy.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.levy( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.levy.stateLength":"\nrandom.array.levy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.levy.stateLength;","random.array.levy.byteLength":"\nrandom.array.levy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.levy.byteLength;\n\n    See Also\n    --------\n    base.random.levy","random.array.logistic":"\nrandom.array.logistic( len, mu, s[, options] )\n    Returns an array containing pseudorandom numbers drawn from a logistic\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    mu: number\n        Mean parameter.\n\n    s: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.logistic( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.logistic.assign( mu, s, out )\n    Fills an array with pseudorandom numbers drawn from a logistic distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Mean parameter.\n\n    s: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.logistic.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.logistic.factory( [mu, s, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a logistic distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Mean parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.logistic.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.logistic.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.logistic.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.logistic.PRNG;\n\n\nrandom.array.logistic.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.logistic.seed;\n\n\nrandom.array.logistic.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.logistic.seedLength;\n\n\nrandom.array.logistic.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.logistic( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.logistic.state\n    <Uint32Array>\n\n    > out = random.array.logistic( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.logistic( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.logistic.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.logistic( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.logistic.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.logistic.stateLength;\n\n\nrandom.array.logistic.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.logistic.byteLength;\n\n    See Also\n    --------\n    base.random.logistic\n","random.array.logistic.assign":"\nrandom.array.logistic.assign( mu, s, out )\n    Fills an array with pseudorandom numbers drawn from a logistic distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Mean parameter.\n\n    s: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.logistic.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.logistic.factory":"\nrandom.array.logistic.factory( [mu, s, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a logistic distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Mean parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.logistic.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.logistic.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.logistic.PRNG":"\nrandom.array.logistic.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.logistic.PRNG;","random.array.logistic.seed":"\nrandom.array.logistic.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.logistic.seed;","random.array.logistic.seedLength":"\nrandom.array.logistic.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.logistic.seedLength;","random.array.logistic.state":"\nrandom.array.logistic.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.logistic( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.logistic.state\n    <Uint32Array>\n\n    > out = random.array.logistic( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.logistic( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.logistic.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.logistic( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.logistic.stateLength":"\nrandom.array.logistic.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.logistic.stateLength;","random.array.logistic.byteLength":"\nrandom.array.logistic.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.logistic.byteLength;\n\n    See Also\n    --------\n    base.random.logistic","random.array.lognormal":"\nrandom.array.lognormal( len, mu, sigma[, options] )\n    Returns an array containing pseudorandom numbers drawn from a lognormal\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    mu: number\n        Location parameter.\n\n    sigma: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.lognormal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.lognormal.assign( mu, sigma, out )\n    Fills an array with pseudorandom numbers drawn from a lognormal\n    distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Location parameter.\n\n    sigma: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.lognormal.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.lognormal.factory( [mu, sigma, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a lognormal distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Location parameter.\n\n    sigma: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.lognormal.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.lognormal.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.lognormal.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.lognormal.PRNG;\n\n\nrandom.array.lognormal.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.lognormal.seed;\n\n\nrandom.array.lognormal.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.lognormal.seedLength;\n\n\nrandom.array.lognormal.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.lognormal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.lognormal.state\n    <Uint32Array>\n\n    > out = random.array.lognormal( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.lognormal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.lognormal.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.lognormal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.lognormal.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.lognormal.stateLength;\n\n\nrandom.array.lognormal.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.lognormal.byteLength;\n\n    See Also\n    --------\n    base.random.lognormal, random.strided.lognormal\n","random.array.lognormal.assign":"\nrandom.array.lognormal.assign( mu, sigma, out )\n    Fills an array with pseudorandom numbers drawn from a lognormal\n    distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Location parameter.\n\n    sigma: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.lognormal.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.lognormal.factory":"\nrandom.array.lognormal.factory( [mu, sigma, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a lognormal distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Location parameter.\n\n    sigma: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.lognormal.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.lognormal.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.lognormal.PRNG":"\nrandom.array.lognormal.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.lognormal.PRNG;","random.array.lognormal.seed":"\nrandom.array.lognormal.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.lognormal.seed;","random.array.lognormal.seedLength":"\nrandom.array.lognormal.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.lognormal.seedLength;","random.array.lognormal.state":"\nrandom.array.lognormal.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.lognormal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.lognormal.state\n    <Uint32Array>\n\n    > out = random.array.lognormal( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.lognormal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.lognormal.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.lognormal( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.lognormal.stateLength":"\nrandom.array.lognormal.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.lognormal.stateLength;","random.array.lognormal.byteLength":"\nrandom.array.lognormal.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.lognormal.byteLength;\n\n    See Also\n    --------\n    base.random.lognormal, random.strided.lognormal","random.array.minstd":"\nrandom.array.minstd( len[, options] )\n    Returns an array containing pseudorandom integers on the interval\n    `[1, 2147483646]`.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.minstd( 3 )\n    <Float64Array>\n\n\nrandom.array.minstd.normalized( len[, options] )\n    Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.minstd.normalized( 3 )\n    <Float64Array>\n\n\nrandom.array.minstd.factory( [options] )\n    Returns a function for creating arrays containing pseudorandom numbers\n    generated using a linear congruential pseudorandom number generator (LCG).\n\n    The returned function and its attached `normalized` method accept the\n    following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.idtype: string (optional)\n        Default output array data type when generating integers. Default:\n        'float64'.\n\n    options.ndtype: string (optional)\n        Default output array data type when generating normalized numbers.\n        Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.minstd.factory();\n    > var out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.minstd.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.minstd.PRNG;\n\n\nrandom.array.minstd.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.minstd.seed;\n\n\nrandom.array.minstd.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.minstd.seedLength;\n\n\nrandom.array.minstd.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.minstd( 3 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.minstd.state;\n\n    > out = random.array.minstd( 3 )\n    <Float64Array>\n    > out = random.array.minstd( 3 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.minstd.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.minstd( 3 )\n    <Float64Array>\n\n\nrandom.array.minstd.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.minstd.stateLength;\n\n\nrandom.array.minstd.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.minstd.byteLength;\n\n    See Also\n    --------\n    random.array.minstdShuffle, random.array.randu, base.random.minstd, random.strided.minstd\n","random.array.minstd.normalized":"\nrandom.array.minstd.normalized( len[, options] )\n    Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.minstd.normalized( 3 )\n    <Float64Array>","random.array.minstd.factory":"\nrandom.array.minstd.factory( [options] )\n    Returns a function for creating arrays containing pseudorandom numbers\n    generated using a linear congruential pseudorandom number generator (LCG).\n\n    The returned function and its attached `normalized` method accept the\n    following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.idtype: string (optional)\n        Default output array data type when generating integers. Default:\n        'float64'.\n\n    options.ndtype: string (optional)\n        Default output array data type when generating normalized numbers.\n        Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.minstd.factory();\n    > var out = fcn( 3 )\n    <Float64Array>","random.array.minstd.PRNG":"\nrandom.array.minstd.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.minstd.PRNG;","random.array.minstd.seed":"\nrandom.array.minstd.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.minstd.seed;","random.array.minstd.seedLength":"\nrandom.array.minstd.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.minstd.seedLength;","random.array.minstd.state":"\nrandom.array.minstd.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.minstd( 3 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.minstd.state;\n\n    > out = random.array.minstd( 3 )\n    <Float64Array>\n    > out = random.array.minstd( 3 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.minstd.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.minstd( 3 )\n    <Float64Array>","random.array.minstd.stateLength":"\nrandom.array.minstd.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.minstd.stateLength;","random.array.minstd.byteLength":"\nrandom.array.minstd.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.minstd.byteLength;\n\n    See Also\n    --------\n    random.array.minstdShuffle, random.array.randu, base.random.minstd, random.strided.minstd","random.array.minstdShuffle":"\nrandom.array.minstdShuffle( len[, options] )\n    Returns an array containing pseudorandom integers on the interval\n    `[1, 2147483646]`.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.minstdShuffle( 3 )\n    <Float64Array>\n\n\nrandom.array.minstdShuffle.normalized( len[, options] )\n    Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.minstdShuffle.normalized( 3 )\n    <Float64Array>\n\n\nrandom.array.minstdShuffle.factory( [options] )\n    Returns a function for creating arrays containing pseudorandom numbers\n    generated using a linear congruential pseudorandom number generator (LCG)\n    whose output is shuffled.\n\n    The returned function and its attached `normalized` method accept the\n    following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.idtype: string (optional)\n        Default output array data type when generating integers. Default:\n        'float64'.\n\n    options.ndtype: string (optional)\n        Default output array data type when generating normalized numbers.\n        Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.minstdShuffle.factory();\n    > var out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.minstdShuffle.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.minstdShuffle.PRNG;\n\n\nrandom.array.minstdShuffle.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.minstdShuffle.seed;\n\n\nrandom.array.minstdShuffle.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.minstdShuffle.seedLength;\n\n\nrandom.array.minstdShuffle.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.minstdShuffle( 3 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.minstdShuffle.state;\n\n    > out = random.array.minstdShuffle( 3 )\n    <Float64Array>\n    > out = random.array.minstdShuffle( 3 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.minstdShuffle.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.minstdShuffle( 3 )\n    <Float64Array>\n\n\nrandom.array.minstdShuffle.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.minstdShuffle.stateLength;\n\n\nrandom.array.minstdShuffle.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.minstdShuffle.byteLength;\n\n    See Also\n    --------\n    random.array.minstd, random.array.randu, base.random.minstdShuffle, random.strided.minstdShuffle\n","random.array.minstdShuffle.normalized":"\nrandom.array.minstdShuffle.normalized( len[, options] )\n    Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.minstdShuffle.normalized( 3 )\n    <Float64Array>","random.array.minstdShuffle.factory":"\nrandom.array.minstdShuffle.factory( [options] )\n    Returns a function for creating arrays containing pseudorandom numbers\n    generated using a linear congruential pseudorandom number generator (LCG)\n    whose output is shuffled.\n\n    The returned function and its attached `normalized` method accept the\n    following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.idtype: string (optional)\n        Default output array data type when generating integers. Default:\n        'float64'.\n\n    options.ndtype: string (optional)\n        Default output array data type when generating normalized numbers.\n        Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.minstdShuffle.factory();\n    > var out = fcn( 3 )\n    <Float64Array>","random.array.minstdShuffle.PRNG":"\nrandom.array.minstdShuffle.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.minstdShuffle.PRNG;","random.array.minstdShuffle.seed":"\nrandom.array.minstdShuffle.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.minstdShuffle.seed;","random.array.minstdShuffle.seedLength":"\nrandom.array.minstdShuffle.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.minstdShuffle.seedLength;","random.array.minstdShuffle.state":"\nrandom.array.minstdShuffle.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.minstdShuffle( 3 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.minstdShuffle.state;\n\n    > out = random.array.minstdShuffle( 3 )\n    <Float64Array>\n    > out = random.array.minstdShuffle( 3 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.minstdShuffle.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.minstdShuffle( 3 )\n    <Float64Array>","random.array.minstdShuffle.stateLength":"\nrandom.array.minstdShuffle.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.minstdShuffle.stateLength;","random.array.minstdShuffle.byteLength":"\nrandom.array.minstdShuffle.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.minstdShuffle.byteLength;\n\n    See Also\n    --------\n    random.array.minstd, random.array.randu, base.random.minstdShuffle, random.strided.minstdShuffle","random.array.mt19937":"\nrandom.array.mt19937( len[, options] )\n    Returns an array containing pseudorandom integers on the interval\n    `[0, 4294967295]`.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.mt19937( 3 )\n    <Float64Array>\n\n\nrandom.array.mt19937.normalized( len[, options] )\n    Returns an array containing pseudorandom numbers on the interval `[0, 1)`\n    with 53-bit precision.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.mt19937.normalized( 3 )\n    <Float64Array>\n\n\nrandom.array.mt19937.factory( [options] )\n    Returns a function for creating arrays containing pseudorandom numbers\n    generated using a 32-bit Mersenne Twister pseudorandom number generator.\n\n    The returned function and its attached `normalized` method accept the\n    following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.idtype: string (optional)\n        Default output array data type when generating integers. Default:\n        'float64'.\n\n    options.ndtype: string (optional)\n        Default output array data type when generating normalized numbers.\n        Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.mt19937.factory();\n    > var out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.mt19937.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.mt19937.PRNG;\n\n\nrandom.array.mt19937.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.mt19937.seed;\n\n\nrandom.array.mt19937.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.mt19937.seedLength;\n\n\nrandom.array.mt19937.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.mt19937( 3 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.mt19937.state;\n\n    > out = random.array.mt19937( 3 )\n    <Float64Array>\n    > out = random.array.mt19937( 3 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.mt19937.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.mt19937( 3 )\n    <Float64Array>\n\n\nrandom.array.mt19937.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.mt19937.stateLength;\n\n\nrandom.array.mt19937.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.mt19937.byteLength;\n\n    See Also\n    --------\n    random.array.randu, base.random.mt19937, random.strided.mt19937\n","random.array.mt19937.normalized":"\nrandom.array.mt19937.normalized( len[, options] )\n    Returns an array containing pseudorandom numbers on the interval `[0, 1)`\n    with 53-bit precision.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.mt19937.normalized( 3 )\n    <Float64Array>","random.array.mt19937.factory":"\nrandom.array.mt19937.factory( [options] )\n    Returns a function for creating arrays containing pseudorandom numbers\n    generated using a 32-bit Mersenne Twister pseudorandom number generator.\n\n    The returned function and its attached `normalized` method accept the\n    following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.idtype: string (optional)\n        Default output array data type when generating integers. Default:\n        'float64'.\n\n    options.ndtype: string (optional)\n        Default output array data type when generating normalized numbers.\n        Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.mt19937.factory();\n    > var out = fcn( 3 )\n    <Float64Array>","random.array.mt19937.PRNG":"\nrandom.array.mt19937.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.mt19937.PRNG;","random.array.mt19937.seed":"\nrandom.array.mt19937.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.mt19937.seed;","random.array.mt19937.seedLength":"\nrandom.array.mt19937.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.mt19937.seedLength;","random.array.mt19937.state":"\nrandom.array.mt19937.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.mt19937( 3 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.mt19937.state;\n\n    > out = random.array.mt19937( 3 )\n    <Float64Array>\n    > out = random.array.mt19937( 3 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.mt19937.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.mt19937( 3 )\n    <Float64Array>","random.array.mt19937.stateLength":"\nrandom.array.mt19937.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.mt19937.stateLength;","random.array.mt19937.byteLength":"\nrandom.array.mt19937.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.mt19937.byteLength;\n\n    See Also\n    --------\n    random.array.randu, base.random.mt19937, random.strided.mt19937","random.array.negativeBinomial":"\nrandom.array.negativeBinomial( len, r, p[, options] )\n    Returns an array containing pseudorandom numbers drawn from a negative\n    binomial distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.negativeBinomial( 3, 10, 0.5 )\n    <Float64Array>\n\n\nrandom.array.negativeBinomial.assign( r, p, out )\n    Fills an array with pseudorandom numbers drawn from a negative binomial\n    distribution.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.negativeBinomial.assign( 10, 0.5, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.negativeBinomial.factory( [r, p, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a negative binomial distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    r: number (optional)\n        Number of successes until experiment is stopped.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.negativeBinomial.factory();\n    > var out = fcn( 3, 10, 0.5 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.negativeBinomial.factory( 10, 0.5 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.negativeBinomial.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.negativeBinomial.PRNG;\n\n\nrandom.array.negativeBinomial.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.negativeBinomial.seed;\n\n\nrandom.array.negativeBinomial.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.negativeBinomial.seedLength;\n\n\nrandom.array.negativeBinomial.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.negativeBinomial( 3, 10, 0.5 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.negativeBinomial.state\n    <Uint32Array>\n\n    > out = random.array.negativeBinomial( 3, 10, 0.5 )\n    <Float64Array>\n    > out = random.array.negativeBinomial( 3, 10, 0.5 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.negativeBinomial.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.negativeBinomial( 3, 10, 0.5 )\n    <Float64Array>\n\n\nrandom.array.negativeBinomial.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.negativeBinomial.stateLength;\n\n\nrandom.array.negativeBinomial.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.negativeBinomial.byteLength;\n\n    See Also\n    --------\n    random.array.binomial, base.random.negativeBinomial\n","random.array.negativeBinomial.assign":"\nrandom.array.negativeBinomial.assign( r, p, out )\n    Fills an array with pseudorandom numbers drawn from a negative binomial\n    distribution.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.negativeBinomial.assign( 10, 0.5, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.negativeBinomial.factory":"\nrandom.array.negativeBinomial.factory( [r, p, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a negative binomial distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    r: number (optional)\n        Number of successes until experiment is stopped.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.negativeBinomial.factory();\n    > var out = fcn( 3, 10, 0.5 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.negativeBinomial.factory( 10, 0.5 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.negativeBinomial.PRNG":"\nrandom.array.negativeBinomial.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.negativeBinomial.PRNG;","random.array.negativeBinomial.seed":"\nrandom.array.negativeBinomial.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.negativeBinomial.seed;","random.array.negativeBinomial.seedLength":"\nrandom.array.negativeBinomial.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.negativeBinomial.seedLength;","random.array.negativeBinomial.state":"\nrandom.array.negativeBinomial.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.negativeBinomial( 3, 10, 0.5 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.negativeBinomial.state\n    <Uint32Array>\n\n    > out = random.array.negativeBinomial( 3, 10, 0.5 )\n    <Float64Array>\n    > out = random.array.negativeBinomial( 3, 10, 0.5 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.negativeBinomial.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.negativeBinomial( 3, 10, 0.5 )\n    <Float64Array>","random.array.negativeBinomial.stateLength":"\nrandom.array.negativeBinomial.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.negativeBinomial.stateLength;","random.array.negativeBinomial.byteLength":"\nrandom.array.negativeBinomial.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.negativeBinomial.byteLength;\n\n    See Also\n    --------\n    random.array.binomial, base.random.negativeBinomial","random.array.normal":"\nrandom.array.normal( len, mu, sigma[, options] )\n    Returns an array containing pseudorandom numbers drawn from a normal\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    mu: number\n        Mean.\n\n    sigma: number\n        Standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.normal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.normal.assign( mu, sigma, out )\n    Fills an array with pseudorandom numbers drawn from a normal distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Mean.\n\n    sigma: number\n        Standard deviation.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.normal.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.normal.factory( [mu, sigma, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a normal distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Mean.\n\n    sigma: number (optional)\n        Standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.normal.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.normal.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.normal.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.normal.PRNG;\n\n\nrandom.array.normal.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.normal.seed;\n\n\nrandom.array.normal.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.normal.seedLength;\n\n\nrandom.array.normal.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.normal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.normal.state\n    <Uint32Array>\n\n    > out = random.array.normal( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.normal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.normal.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.normal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.normal.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.normal.stateLength;\n\n\nrandom.array.normal.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.normal.byteLength;\n\n    See Also\n    --------\n    base.random.normal, random.strided.normal\n","random.array.normal.assign":"\nrandom.array.normal.assign( mu, sigma, out )\n    Fills an array with pseudorandom numbers drawn from a normal distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Mean.\n\n    sigma: number\n        Standard deviation.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.normal.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.normal.factory":"\nrandom.array.normal.factory( [mu, sigma, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a normal distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Mean.\n\n    sigma: number (optional)\n        Standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.normal.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.normal.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.normal.PRNG":"\nrandom.array.normal.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.normal.PRNG;","random.array.normal.seed":"\nrandom.array.normal.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.normal.seed;","random.array.normal.seedLength":"\nrandom.array.normal.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.normal.seedLength;","random.array.normal.state":"\nrandom.array.normal.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.normal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.normal.state\n    <Uint32Array>\n\n    > out = random.array.normal( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.normal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.normal.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.normal( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.normal.stateLength":"\nrandom.array.normal.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.normal.stateLength;","random.array.normal.byteLength":"\nrandom.array.normal.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.normal.byteLength;\n\n    See Also\n    --------\n    base.random.normal, random.strided.normal","random.array.pareto1":"\nrandom.array.pareto1( len, alpha, beta[, options] )\n    Returns an array containing pseudorandom numbers drawn from a Pareto (Type\n    I) distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    alpha: number\n        Shape parameter.\n\n    beta: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.pareto1( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.pareto1.assign( alpha, beta, out )\n    Fills an array with pseudorandom numbers drawn from a Pareto (Type I)\n    distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        Shape parameter.\n\n    beta: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.pareto1.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.pareto1.factory( [alpha, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Pareto (Type I) distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        Shape parameter.\n\n    beta: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.pareto1.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.pareto1.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.pareto1.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.pareto1.PRNG;\n\n\nrandom.array.pareto1.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.pareto1.seed;\n\n\nrandom.array.pareto1.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.pareto1.seedLength;\n\n\nrandom.array.pareto1.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.pareto1( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.pareto1.state\n    <Uint32Array>\n\n    > out = random.array.pareto1( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.pareto1( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.pareto1.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.pareto1( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.pareto1.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.pareto1.stateLength;\n\n\nrandom.array.pareto1.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.pareto1.byteLength;\n\n    See Also\n    --------\n    base.random.pareto1\n","random.array.pareto1.assign":"\nrandom.array.pareto1.assign( alpha, beta, out )\n    Fills an array with pseudorandom numbers drawn from a Pareto (Type I)\n    distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        Shape parameter.\n\n    beta: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.pareto1.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.pareto1.factory":"\nrandom.array.pareto1.factory( [alpha, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Pareto (Type I) distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        Shape parameter.\n\n    beta: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.pareto1.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.pareto1.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.pareto1.PRNG":"\nrandom.array.pareto1.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.pareto1.PRNG;","random.array.pareto1.seed":"\nrandom.array.pareto1.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.pareto1.seed;","random.array.pareto1.seedLength":"\nrandom.array.pareto1.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.pareto1.seedLength;","random.array.pareto1.state":"\nrandom.array.pareto1.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.pareto1( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.pareto1.state\n    <Uint32Array>\n\n    > out = random.array.pareto1( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.pareto1( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.pareto1.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.pareto1( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.pareto1.stateLength":"\nrandom.array.pareto1.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.pareto1.stateLength;","random.array.pareto1.byteLength":"\nrandom.array.pareto1.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.pareto1.byteLength;\n\n    See Also\n    --------\n    base.random.pareto1","random.array.poisson":"\nrandom.array.poisson( len, lambda[, options] )\n    Returns an array containing pseudorandom numbers drawn from a Poisson\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    lambda: number\n        Mean parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.poisson( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.poisson.assign( lambda, out )\n    Fills an array with pseudorandom numbers drawn from a Poisson distribution.\n\n    Parameters\n    ----------\n    lambda: number\n        Mean parameter.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.poisson.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.poisson.factory( [lambda, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Poisson distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    lambda: number (optional)\n        Mean parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.poisson.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.poisson.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.poisson.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.poisson.PRNG;\n\n\nrandom.array.poisson.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.poisson.seed;\n\n\nrandom.array.poisson.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.poisson.seedLength;\n\n\nrandom.array.poisson.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.poisson( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.poisson.state\n    <Uint32Array>\n\n    > out = random.array.poisson( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.poisson( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.poisson.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.poisson( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.poisson.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.poisson.stateLength;\n\n\nrandom.array.poisson.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.poisson.byteLength;\n\n    See Also\n    --------\n    base.random.poisson, random.strided.poisson\n","random.array.poisson.assign":"\nrandom.array.poisson.assign( lambda, out )\n    Fills an array with pseudorandom numbers drawn from a Poisson distribution.\n\n    Parameters\n    ----------\n    lambda: number\n        Mean parameter.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.poisson.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.poisson.factory":"\nrandom.array.poisson.factory( [lambda, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Poisson distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    lambda: number (optional)\n        Mean parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.poisson.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.poisson.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.poisson.PRNG":"\nrandom.array.poisson.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.poisson.PRNG;","random.array.poisson.seed":"\nrandom.array.poisson.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.poisson.seed;","random.array.poisson.seedLength":"\nrandom.array.poisson.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.poisson.seedLength;","random.array.poisson.state":"\nrandom.array.poisson.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.poisson( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.poisson.state\n    <Uint32Array>\n\n    > out = random.array.poisson( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.poisson( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.poisson.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.poisson( 3, 2.0 )\n    <Float64Array>","random.array.poisson.stateLength":"\nrandom.array.poisson.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.poisson.stateLength;","random.array.poisson.byteLength":"\nrandom.array.poisson.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.poisson.byteLength;\n\n    See Also\n    --------\n    base.random.poisson, random.strided.poisson","random.array.randu":"\nrandom.array.randu( len[, options] )\n    Returns an array containing uniformly distributed pseudorandom numbers\n    between 0 and 1.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.randu( 3 )\n    <Float64Array>\n\n\nrandom.array.randu.factory( [options] )\n    Returns a function for creating arrays containing uniformly distributed\n    pseudorandom numbers between 0 and 1.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: `'mt19937'`.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.randu.factory();\n    > var out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.randu.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.randu.PRNG;\n\n\nrandom.array.randu.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.randu.seed;\n\n\nrandom.array.randu.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.randu.seedLength;\n\n\nrandom.array.randu.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.randu( 3 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.randu.state;\n\n    > out = random.array.randu( 3 )\n    <Float64Array>\n    > out = random.array.randu( 3 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.randu.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.randu( 3 )\n    <Float64Array>\n\n\nrandom.array.randu.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.randu.stateLength;\n\n\nrandom.array.randu.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.randu.byteLength;\n\n    See Also\n    --------\n    random.array.uniform, base.random.randu, random.strided.randu\n","random.array.randu.factory":"\nrandom.array.randu.factory( [options] )\n    Returns a function for creating arrays containing uniformly distributed\n    pseudorandom numbers between 0 and 1.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: `'mt19937'`.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.randu.factory();\n    > var out = fcn( 3 )\n    <Float64Array>","random.array.randu.PRNG":"\nrandom.array.randu.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.randu.PRNG;","random.array.randu.seed":"\nrandom.array.randu.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.randu.seed;","random.array.randu.seedLength":"\nrandom.array.randu.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.randu.seedLength;","random.array.randu.state":"\nrandom.array.randu.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.randu( 3 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.randu.state;\n\n    > out = random.array.randu( 3 )\n    <Float64Array>\n    > out = random.array.randu( 3 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.randu.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.randu( 3 )\n    <Float64Array>","random.array.randu.stateLength":"\nrandom.array.randu.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.randu.stateLength;","random.array.randu.byteLength":"\nrandom.array.randu.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.randu.byteLength;\n\n    See Also\n    --------\n    random.array.uniform, base.random.randu, random.strided.randu","random.array.rayleigh":"\nrandom.array.rayleigh( len, sigma[, options] )\n    Returns an array containing pseudorandom numbers drawn from a Rayleigh\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    sigma: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.rayleigh( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.rayleigh.assign( sigma, out )\n    Fills an array with pseudorandom numbers drawn from a Rayleigh distribution.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.rayleigh.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.rayleigh.factory( [sigma, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Rayleigh distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    sigma: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.rayleigh.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.rayleigh.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.rayleigh.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.rayleigh.PRNG;\n\n\nrandom.array.rayleigh.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.rayleigh.seed;\n\n\nrandom.array.rayleigh.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.rayleigh.seedLength;\n\n\nrandom.array.rayleigh.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.rayleigh( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.rayleigh.state\n    <Uint32Array>\n\n    > out = random.array.rayleigh( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.rayleigh( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.rayleigh.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.rayleigh( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.rayleigh.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.rayleigh.stateLength;\n\n\nrandom.array.rayleigh.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.rayleigh.byteLength;\n\n    See Also\n    --------\n    base.random.rayleigh, random.strided.rayleigh\n","random.array.rayleigh.assign":"\nrandom.array.rayleigh.assign( sigma, out )\n    Fills an array with pseudorandom numbers drawn from a Rayleigh distribution.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.rayleigh.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.rayleigh.factory":"\nrandom.array.rayleigh.factory( [sigma, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Rayleigh distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    sigma: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.rayleigh.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.rayleigh.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.rayleigh.PRNG":"\nrandom.array.rayleigh.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.rayleigh.PRNG;","random.array.rayleigh.seed":"\nrandom.array.rayleigh.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.rayleigh.seed;","random.array.rayleigh.seedLength":"\nrandom.array.rayleigh.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.rayleigh.seedLength;","random.array.rayleigh.state":"\nrandom.array.rayleigh.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.rayleigh( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.rayleigh.state\n    <Uint32Array>\n\n    > out = random.array.rayleigh( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.rayleigh( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.rayleigh.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.rayleigh( 3, 2.0 )\n    <Float64Array>","random.array.rayleigh.stateLength":"\nrandom.array.rayleigh.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.rayleigh.stateLength;","random.array.rayleigh.byteLength":"\nrandom.array.rayleigh.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.rayleigh.byteLength;\n\n    See Also\n    --------\n    base.random.rayleigh, random.strided.rayleigh","random.array.t":"\nrandom.array.t( len, v[, options] )\n    Returns an array containing pseudorandom numbers drawn from a Student's t\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    v: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.t( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.t.assign( v, out )\n    Fills an array with pseudorandom numbers drawn from a Student's t\n    distribution.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.t.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.t.factory( [v, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Student's t distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    v: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.t.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.t.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.t.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.t.PRNG;\n\n\nrandom.array.t.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.t.seed;\n\n\nrandom.array.t.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.t.seedLength;\n\n\nrandom.array.t.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.t( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.t.state\n    <Uint32Array>\n\n    > out = random.array.t( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.t( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.t.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.t( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.t.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.t.stateLength;\n\n\nrandom.array.t.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.t.byteLength;\n\n    See Also\n    --------\n    base.random.t, random.strided.t\n","random.array.t.assign":"\nrandom.array.t.assign( v, out )\n    Fills an array with pseudorandom numbers drawn from a Student's t\n    distribution.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.t.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.t.factory":"\nrandom.array.t.factory( [v, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Student's t distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    v: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.t.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.t.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.t.PRNG":"\nrandom.array.t.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.t.PRNG;","random.array.t.seed":"\nrandom.array.t.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.t.seed;","random.array.t.seedLength":"\nrandom.array.t.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.t.seedLength;","random.array.t.state":"\nrandom.array.t.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.t( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.t.state\n    <Uint32Array>\n\n    > out = random.array.t( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.t( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.t.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.t( 3, 2.0 )\n    <Float64Array>","random.array.t.stateLength":"\nrandom.array.t.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.t.stateLength;","random.array.t.byteLength":"\nrandom.array.t.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.t.byteLength;\n\n    See Also\n    --------\n    base.random.t, random.strided.t","random.array.triangular":"\nrandom.array.triangular( len, a, b, c[, options] )\n    Returns an array containing pseudorandom numbers drawn from a triangular\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n\nrandom.array.triangular.assign( a, b, c, out )\n    Fills an array with pseudorandom numbers drawn from a triangular\n    distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.triangular.assign( 2.0, 5.0, 3.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.triangular.factory( [a, b, c, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a triangular distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    c: number (optional)\n        Mode.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.triangular.factory();\n    > var out = fcn( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.triangular.factory( 2.0, 5.0, 3.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.triangular.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.triangular.PRNG;\n\n\nrandom.array.triangular.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.triangular.seed;\n\n\nrandom.array.triangular.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.triangular.seedLength;\n\n\nrandom.array.triangular.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.triangular.state\n    <Uint32Array>\n\n    > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n    > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.triangular.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n\nrandom.array.triangular.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.triangular.stateLength;\n\n\nrandom.array.triangular.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.triangular.byteLength;\n\n    See Also\n    --------\n    base.random.triangular\n","random.array.triangular.assign":"\nrandom.array.triangular.assign( a, b, c, out )\n    Fills an array with pseudorandom numbers drawn from a triangular\n    distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.triangular.assign( 2.0, 5.0, 3.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.triangular.factory":"\nrandom.array.triangular.factory( [a, b, c, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a triangular distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    c: number (optional)\n        Mode.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.triangular.factory();\n    > var out = fcn( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.triangular.factory( 2.0, 5.0, 3.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.triangular.PRNG":"\nrandom.array.triangular.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.triangular.PRNG;","random.array.triangular.seed":"\nrandom.array.triangular.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.triangular.seed;","random.array.triangular.seedLength":"\nrandom.array.triangular.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.triangular.seedLength;","random.array.triangular.state":"\nrandom.array.triangular.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.triangular.state\n    <Uint32Array>\n\n    > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n    > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.triangular.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>","random.array.triangular.stateLength":"\nrandom.array.triangular.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.triangular.stateLength;","random.array.triangular.byteLength":"\nrandom.array.triangular.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.triangular.byteLength;\n\n    See Also\n    --------\n    base.random.triangular","random.array.uniform":"\nrandom.array.uniform( len, a, b[, options] )\n    Returns an array containing pseudorandom numbers drawn from a continuous\n    uniform distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.uniform( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.uniform.assign( a, b, out )\n    Fills an array with pseudorandom numbers drawn from a continuous uniform\n    distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.uniform.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.uniform.factory( [a, b, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a continuous uniform distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.uniform.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.uniform.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.uniform.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.uniform.PRNG;\n\n\nrandom.array.uniform.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.uniform.seed;\n\n\nrandom.array.uniform.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.uniform.seedLength;\n\n\nrandom.array.uniform.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.uniform( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.uniform.state\n    <Uint32Array>\n\n    > out = random.array.uniform( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.uniform( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.uniform.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.uniform( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.uniform.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.uniform.stateLength;\n\n\nrandom.array.uniform.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.uniform.byteLength;\n\n    See Also\n    --------\n    random.array.discreteUniform, base.random.uniform, random.strided.uniform\n","random.array.uniform.assign":"\nrandom.array.uniform.assign( a, b, out )\n    Fills an array with pseudorandom numbers drawn from a continuous uniform\n    distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.uniform.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.uniform.factory":"\nrandom.array.uniform.factory( [a, b, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a continuous uniform distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.uniform.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.uniform.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.uniform.PRNG":"\nrandom.array.uniform.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.uniform.PRNG;","random.array.uniform.seed":"\nrandom.array.uniform.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.uniform.seed;","random.array.uniform.seedLength":"\nrandom.array.uniform.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.uniform.seedLength;","random.array.uniform.state":"\nrandom.array.uniform.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.uniform( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.uniform.state\n    <Uint32Array>\n\n    > out = random.array.uniform( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.uniform( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.uniform.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.uniform( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.uniform.stateLength":"\nrandom.array.uniform.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.uniform.stateLength;","random.array.uniform.byteLength":"\nrandom.array.uniform.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.uniform.byteLength;\n\n    See Also\n    --------\n    random.array.discreteUniform, base.random.uniform, random.strided.uniform","random.array.weibull":"\nrandom.array.weibull( len, k, lambda[, options] )\n    Returns an array containing pseudorandom numbers drawn from a Weibull\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    k: number\n        Scale parameter.\n\n    lambda: number\n        Shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.weibull( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.weibull.assign( k, lambda, out )\n    Fills an array with pseudorandom numbers drawn from a Weibull distribution.\n\n    Parameters\n    ----------\n    k: number\n        Scale parameter.\n\n    lambda: number\n        Shape parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.weibull.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.weibull.factory( [k, lambda, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Weibull distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Scale parameter.\n\n    lambda: number (optional)\n        Shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.weibull.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.weibull.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.weibull.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.weibull.PRNG;\n\n\nrandom.array.weibull.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.weibull.seed;\n\n\nrandom.array.weibull.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.weibull.seedLength;\n\n\nrandom.array.weibull.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.weibull( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.weibull.state\n    <Uint32Array>\n\n    > out = random.array.weibull( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.weibull( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.weibull.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.weibull( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.weibull.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.weibull.stateLength;\n\n\nrandom.array.weibull.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.weibull.byteLength;\n\n    See Also\n    --------\n    base.random.weibull, random.strided.weibull\n","random.array.weibull.assign":"\nrandom.array.weibull.assign( k, lambda, out )\n    Fills an array with pseudorandom numbers drawn from a Weibull distribution.\n\n    Parameters\n    ----------\n    k: number\n        Scale parameter.\n\n    lambda: number\n        Shape parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.weibull.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.weibull.factory":"\nrandom.array.weibull.factory( [k, lambda, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Weibull distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Scale parameter.\n\n    lambda: number (optional)\n        Shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.weibull.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.weibull.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.weibull.PRNG":"\nrandom.array.weibull.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.weibull.PRNG;","random.array.weibull.seed":"\nrandom.array.weibull.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.weibull.seed;","random.array.weibull.seedLength":"\nrandom.array.weibull.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.weibull.seedLength;","random.array.weibull.state":"\nrandom.array.weibull.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.weibull( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.weibull.state\n    <Uint32Array>\n\n    > out = random.array.weibull( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.weibull( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.weibull.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.weibull( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.weibull.stateLength":"\nrandom.array.weibull.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.weibull.stateLength;","random.array.weibull.byteLength":"\nrandom.array.weibull.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.weibull.byteLength;\n\n    See Also\n    --------\n    base.random.weibull, random.strided.weibull","random.iterators.arcsine":"\nrandom.iterators.arcsine( a, b[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from an\n    arcsine distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.arcsine( 0.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.arcsine\n","random.iterators.bernoulli":"\nrandom.iterators.bernoulli( p[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Bernoulli distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.bernoulli( 0.3 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.bernoulli\n","random.iterators.beta":"\nrandom.iterators.beta( α, β[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    beta distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    The function throws an error if `α <= 0` or `β <= 0`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.beta( 1.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.beta\n","random.iterators.betaprime":"\nrandom.iterators.betaprime( α, β[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    beta prime distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    The function throws an error if `α <= 0` or `β <= 0`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.betaprime( 1.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.betaprime\n","random.iterators.binomial":"\nrandom.iterators.binomial( n, p[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    binomial distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.binomial( 10, 0.3 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.binomial\n","random.iterators.boxMuller":"\nrandom.iterators.boxMuller( [options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    standard normal distribution using the Box-Muller transform.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.boxMuller();\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.boxMuller\n","random.iterators.cauchy":"\nrandom.iterators.cauchy( x0, Ɣ[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Cauchy distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.seed: any\n        Pseudorandom number generator seed.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.cauchy( 0.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.cauchy\n","random.iterators.chi":"\nrandom.iterators.chi( k[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a chi\n    distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.chi( 1.5 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.chi\n","random.iterators.chisquare":"\nrandom.iterators.chisquare( k[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    chi-square distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.chisquare( 1.5 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.chisquare\n","random.iterators.cosine":"\nrandom.iterators.cosine( μ, s[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a raised\n    cosine distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.cosine( 0.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.cosine\n","random.iterators.discreteUniform":"\nrandom.iterators.discreteUniform( a, b[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    discrete uniform distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom integers. If provided, the `state` and `seed`\n        options are ignored. In order to seed the returned iterator, one must\n        seed the provided `prng` (assuming the provided `prng` is seedable). The\n        provided PRNG must have `MIN` and `MAX` properties specifying the\n        minimum and maximum possible pseudorandom integers.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.discreteUniform( 0, 3 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.discreteUniform\n","random.iterators.erlang":"\nrandom.iterators.erlang( k, λ[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from an Erlang\n    distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If `k` is not a positive integer or `λ <= 0`, the function throws an error.\n\n    Parameters\n    ----------\n    k: integer\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.erlang( 1, 1.5 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.erlang\n","random.iterators.exponential":"\nrandom.iterators.exponential( λ[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from an\n    exponential distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.exponential( 1.5 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.exponential\n","random.iterators.f":"\nrandom.iterators.f( d1, d2[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from an F\n    distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    The function throws an error if `d1 <= 0` or `d2 <= 0`.\n\n    Parameters\n    ----------\n    d1: number\n        Degrees of freedom.\n\n    d2: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.f( 1.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.f\n","random.iterators.frechet":"\nrandom.iterators.frechet( α, s, m[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Fréchet\n    distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    The function throws an error if `α <= 0` or `s <= 0`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.frechet( 1.0, 1.0, 0.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.frechet\n","random.iterators.gamma":"\nrandom.iterators.gamma( α, β[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a gamma\n    distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    The function throws an error if `α <= 0` or `β <= 0`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.gamma( 1.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.gamma\n","random.iterators.geometric":"\nrandom.iterators.geometric( p[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    geometric distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.geometric( 0.3 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.geometric\n","random.iterators.gumbel":"\nrandom.iterators.gumbel( μ, β[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Gumbel\n    distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.gumbel( 0.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.gumbel\n","random.iterators.hypergeometric":"\nrandom.iterators.hypergeometric( N, K, n[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    hypergeometric distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    `N`, `K`, and `n` must all be nonnegative integers; otherwise, the function\n    throws an error.\n\n    If `n > N` or `K > N`, the function throws an error.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.hypergeometric( 20, 10, 7 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.hypergeometric\n","random.iterators.improvedZiggurat":"\nrandom.iterators.improvedZiggurat( [options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    standard normal distribution using the Improved Ziggurat algorithm.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.improvedZiggurat();\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.improvedZiggurat\n","random.iterators.invgamma":"\nrandom.iterators.invgamma( α, β[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from an\n    inverse gamma distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    The function throws an error if `α <= 0` or `β <= 0`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.invgamma( 1.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.invgamma\n","random.iterators.kumaraswamy":"\nrandom.iterators.kumaraswamy( a, b[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Kumaraswamy's double bounded distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    The function throws an error if `a <= 0` or `b <= 0`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.kumaraswamy( 1.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.kumaraswamy\n","random.iterators.laplace":"\nrandom.iterators.laplace( μ, b[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Laplace\n    (double exponential) distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    b: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.laplace( 0.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.laplace\n","random.iterators.levy":"\nrandom.iterators.levy( μ, c[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Lévy\n    distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    c: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.levy( 0.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.levy\n","random.iterators.logistic":"\nrandom.iterators.logistic( μ, s[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    logistic distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    s: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.logistic( 0.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.logistic\n","random.iterators.lognormal":"\nrandom.iterators.lognormal( μ, σ[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    lognormal distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.lognormal( 0.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.lognormal\n","random.iterators.minstd":"\nrandom.iterators.minstd( [options] )\n    Returns an iterator for generating pseudorandom integers on the interval\n    `[1, 2147483646]`.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    This pseudorandom number generator (PRNG) is a linear congruential\n    pseudorandom number generator (LCG) based on Park and Miller.\n\n    The generator has a period of approximately `2.1e9`.\n\n    An LCG is fast and uses little memory. On the other hand, because the\n    generator is a simple LCG, the generator has recognized shortcomings. By\n    today's PRNG standards, the generator's period is relatively short. More\n    importantly, the \"randomness quality\" of the generator's output is lacking.\n    These defects make the generator unsuitable, for example, in Monte Carlo\n    simulations and in cryptographic applications.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing positive signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.seed: Int32Array\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer\n        Length of generator seed.\n\n    iterator.state: Int32Array\n        Generator state.\n\n    iterator.stateLength: integer\n        Length of generator state.\n\n    iterator.byteLength: integer\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.minstd();\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.minstd, random.iterators.minstdShuffle, random.iterators.mt19937, random.iterators.randi, random.iterators.randu\n","random.iterators.minstdShuffle":"\nrandom.iterators.minstdShuffle( [options] )\n    Returns an iterator for generating pseudorandom integers on the interval\n    `[1, 2147483646]`.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    This pseudorandom number generator (PRNG) is a linear congruential\n    pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n    Durham algorithm. The shuffle step considerably strengthens the \"randomness\n    quality\" of a simple LCG's output.\n\n    The generator has a period of approximately `2.1e9`.\n\n    An LCG is fast and uses little memory. On the other hand, because the\n    generator is a simple LCG, the generator has recognized shortcomings. By\n    today's PRNG standards, the generator's period is relatively short. In\n    general, this generator is unsuitable for Monte Carlo simulations and\n    cryptographic applications.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing positive signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.seed: Int32Array\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer\n        Length of generator seed.\n\n    iterator.state: Int32Array\n        Generator state.\n\n    iterator.stateLength: integer\n        Length of generator state.\n\n    iterator.byteLength: integer\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.minstdShuffle();\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.minstdShuffle, random.iterators.minstd, random.iterators.mt19937, random.iterators.randi, random.iterators.randu\n","random.iterators.mt19937":"\nrandom.iterators.mt19937( [options] )\n    Returns an iterator for generating pseudorandom integers on the interval\n    `[1, 4294967295]`.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    This pseudorandom number generator (PRNG) is a 32-bit Mersenne Twister\n    pseudorandom number generator.\n\n    The PRNG is *not* a cryptographically secure PRNG.\n\n    The PRNG has a period of 2^19937 - 1.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.seed: Uint32Array\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer\n        Length of generator seed.\n\n    iterator.state: Uint32Array\n        Generator state.\n\n    iterator.stateLength: integer\n        Length of generator state.\n\n    iterator.byteLength: integer\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.mt19937();\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.mt19937, random.iterators.minstd, random.iterators.minstdShuffle, random.iterators.randi, random.iterators.randu\n","random.iterators.negativeBinomial":"\nrandom.iterators.negativeBinomial( r, p[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    negative binomial distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.negativeBinomial( 10, 0.3 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.negativeBinomial\n","random.iterators.normal":"\nrandom.iterators.normal( μ, σ[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a normal\n    distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    σ: number\n        Standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.normal( 0.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.normal\n","random.iterators.pareto1":"\nrandom.iterators.pareto1( α, β[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Pareto\n    (Type I) distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    The function throws an error if `α <= 0` or `β <= 0`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.pareto1( 1.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.pareto1\n","random.iterators.poisson":"\nrandom.iterators.poisson( λ[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Poisson\n    distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    λ: number\n        Mean.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.poisson( 1.5 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.poisson\n","random.iterators.randi":"\nrandom.iterators.randi( [options] )\n    Create an iterator for generating pseudorandom numbers having integer\n    values.\n\n    The default underlying pseudorandom number generator (PRNG) *may* change in\n    the future. If exact reproducibility is required, either explicitly specify\n    a PRNG via the `name` option or use an underlying PRNG directly.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: `'mt19937'`.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: any\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer\n        Length of generator seed.\n\n    iterator.state: any\n        Generator state.\n\n    iterator.stateLength: integer\n        Length of generator state.\n\n    iterator.byteLength: integer\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.randi();\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.randi, random.iterators.randu\n","random.iterators.randn":"\nrandom.iterators.randn( [options] )\n    Create an iterator for generating pseudorandom numbers drawn from a standard\n    normal distribution.\n\n    The default underlying pseudorandom number generator (PRNG) *may* change in\n    the future. If exact reproducibility is required, either explicitly specify\n    a PRNG via the `name` option or use an underlying PRNG directly.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - improved-ziggurat: improved ziggurat method.\n        - box-muller: Box-Muller transform.\n\n        Default: `'improved-ziggurat'`.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.randn();\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.randn\n","random.iterators.randu":"\nrandom.iterators.randu( [options] )\n    Create an iterator for generating uniformly distributed pseudorandom numbers\n    between 0 and 1.\n\n    The default underlying pseudorandom number generator (PRNG) *may* change in\n    the future. If exact reproducibility is required, either explicitly specify\n    a PRNG via the `name` option or use an underlying PRNG directly.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: `'mt19937'`.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: any\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer\n        Length of generator seed.\n\n    iterator.state: any\n        Generator state.\n\n    iterator.stateLength: integer\n        Length of generator state.\n\n    iterator.byteLength: integer\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.randu();\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.randu, random.iterators.randi\n","random.iterators.rayleigh":"\nrandom.iterators.rayleigh( σ[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Rayleigh distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.rayleigh( 1.5 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.rayleigh\n","random.iterators.t":"\nrandom.iterators.t( v[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Student's t distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.t( 1.5 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.t\n","random.iterators.triangular":"\nrandom.iterators.triangular( a, b, c[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    triangular distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.triangular( 0.0, 1.0, 0.3 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.triangular\n","random.iterators.uniform":"\nrandom.iterators.uniform( a, b[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    continuous uniform distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.uniform( 0.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.uniform\n","random.iterators.weibull":"\nrandom.iterators.weibull( k, λ[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Weibull distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    The function throws an error if `k <= 0` or `λ <= 0`.\n\n    Parameters\n    ----------\n    k: number\n        Scale parameter.\n\n    λ: number\n        Shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.weibull( 1.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.weibull\n","random.streams.arcsine":"\nrandom.streams.arcsine( a, b[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from an\n    arcsine distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.arcsine( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.arcsine.factory( [a, b, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an arcsine distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.arcsine.factory( opts );\n\n\nrandom.streams.arcsine.objectMode( a, b[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an arcsine distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.arcsine.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.arcsine, random.iterators.arcsine\n","random.streams.arcsine.factory":"\nrandom.streams.arcsine.factory( [a, b, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an arcsine distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.arcsine.factory( opts );","random.streams.arcsine.objectMode":"\nrandom.streams.arcsine.objectMode( a, b[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an arcsine distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.arcsine.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.arcsine, random.iterators.arcsine","random.streams.bernoulli":"\nrandom.streams.bernoulli( p[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Bernoulli distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.bernoulli( 0.5, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.bernoulli.factory( [p, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Bernoulli distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.bernoulli.factory( opts );\n\n\nrandom.streams.bernoulli.objectMode( p[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Bernoulli distribution.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.bernoulli.objectMode( 0.3, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.bernoulli, random.iterators.bernoulli\n","random.streams.bernoulli.factory":"\nrandom.streams.bernoulli.factory( [p, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Bernoulli distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.bernoulli.factory( opts );","random.streams.bernoulli.objectMode":"\nrandom.streams.bernoulli.objectMode( p[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Bernoulli distribution.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.bernoulli.objectMode( 0.3, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.bernoulli, random.iterators.bernoulli","random.streams.beta":"\nrandom.streams.beta( α, β[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    beta distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.beta( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.beta.factory( [α, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a beta distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        First shape parameter.\n\n    β: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.beta.factory( opts );\n\n\nrandom.streams.beta.objectMode( α, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a beta distribution.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.beta.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.beta, random.iterators.beta\n","random.streams.beta.factory":"\nrandom.streams.beta.factory( [α, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a beta distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        First shape parameter.\n\n    β: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.beta.factory( opts );","random.streams.beta.objectMode":"\nrandom.streams.beta.objectMode( α, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a beta distribution.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.beta.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.beta, random.iterators.beta","random.streams.betaprime":"\nrandom.streams.betaprime( α, β[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    beta prime distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.betaprime( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.betaprime.factory( [α, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a beta prime distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        First shape parameter.\n\n    β: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.betaprime.factory( opts );\n\n\nrandom.streams.betaprime.objectMode( α, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a beta prime distribution.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.betaprime.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.betaprime, random.iterators.betaprime\n","random.streams.betaprime.factory":"\nrandom.streams.betaprime.factory( [α, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a beta prime distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        First shape parameter.\n\n    β: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.betaprime.factory( opts );","random.streams.betaprime.objectMode":"\nrandom.streams.betaprime.objectMode( α, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a beta prime distribution.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.betaprime.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.betaprime, random.iterators.betaprime","random.streams.binomial":"\nrandom.streams.binomial( n, p[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    binomial distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.binomial( 20, 0.5, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.binomial.factory( [n, p, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a binomial distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    n: integer (optional)\n        Number of trials.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.binomial.factory( opts );\n\n\nrandom.streams.binomial.objectMode( n, p[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a binomial distribution.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.binomial.objectMode( 20, 0.5, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.binomial, random.iterators.binomial\n","random.streams.binomial.factory":"\nrandom.streams.binomial.factory( [n, p, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a binomial distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    n: integer (optional)\n        Number of trials.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.binomial.factory( opts );","random.streams.binomial.objectMode":"\nrandom.streams.binomial.objectMode( n, p[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a binomial distribution.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.binomial.objectMode( 20, 0.5, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.binomial, random.iterators.binomial","random.streams.boxMuller":"\nrandom.streams.boxMuller( [options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    standard normal distribution using the Box-Muller transform.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.boxMuller( opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.boxMuller.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a standard normal distribution using the Box-Muller\n    transform.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.boxMuller.factory( opts );\n\n\nrandom.streams.boxMuller.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a standard normal distribution using the Box-Muller transform.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.boxMuller.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.boxMuller, random.iterators.boxMuller, random.streams.improvedZiggurat, random.streams.randn\n","random.streams.boxMuller.factory":"\nrandom.streams.boxMuller.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a standard normal distribution using the Box-Muller\n    transform.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.boxMuller.factory( opts );","random.streams.boxMuller.objectMode":"\nrandom.streams.boxMuller.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a standard normal distribution using the Box-Muller transform.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.boxMuller.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.boxMuller, random.iterators.boxMuller, random.streams.improvedZiggurat, random.streams.randn","random.streams.cauchy":"\nrandom.streams.cauchy( x0, γ[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Cauchy distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    γ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.cauchy( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.cauchy.factory( [x0, γ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Cauchy distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    x0: number (optional)\n        Location parameter.\n\n    γ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.cauchy.factory( opts );\n\n\nrandom.streams.cauchy.objectMode( x0, γ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Cauchy distribution.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    γ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.cauchy.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.cauchy, random.iterators.cauchy\n","random.streams.cauchy.factory":"\nrandom.streams.cauchy.factory( [x0, γ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Cauchy distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    x0: number (optional)\n        Location parameter.\n\n    γ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.cauchy.factory( opts );","random.streams.cauchy.objectMode":"\nrandom.streams.cauchy.objectMode( x0, γ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Cauchy distribution.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    γ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.cauchy.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.cauchy, random.iterators.cauchy","random.streams.chi":"\nrandom.streams.chi( k[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    chi distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.chi( 3.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.chi.factory( [k, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a chi distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.chi.factory( opts );\n\n\nrandom.streams.chi.objectMode( k[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a chi distribution.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.chi.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.chi, random.iterators.chi\n","random.streams.chi.factory":"\nrandom.streams.chi.factory( [k, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a chi distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.chi.factory( opts );","random.streams.chi.objectMode":"\nrandom.streams.chi.objectMode( k[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a chi distribution.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.chi.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.chi, random.iterators.chi","random.streams.chisquare":"\nrandom.streams.chisquare( k[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    chi-square distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.chisquare( 3.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.chisquare.factory( [k, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a chi-square distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.chisquare.factory( opts );\n\n\nrandom.streams.chisquare.objectMode( k[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a chi-square distribution.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.chisquare.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.chisquare, random.iterators.chisquare\n","random.streams.chisquare.factory":"\nrandom.streams.chisquare.factory( [k, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a chi-square distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.chisquare.factory( opts );","random.streams.chisquare.objectMode":"\nrandom.streams.chisquare.objectMode( k[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a chi-square distribution.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.chisquare.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.chisquare, random.iterators.chisquare","random.streams.cosine":"\nrandom.streams.cosine( μ, s[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    raised cosine distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.cosine( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.cosine.factory( [μ, s, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a raised cosine distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.cosine.factory( opts );\n\n\nrandom.streams.cosine.objectMode( μ, s[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a raised cosine distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.cosine.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.cosine, random.iterators.cosine\n","random.streams.cosine.factory":"\nrandom.streams.cosine.factory( [μ, s, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a raised cosine distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.cosine.factory( opts );","random.streams.cosine.objectMode":"\nrandom.streams.cosine.objectMode( μ, s[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a raised cosine distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.cosine.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.cosine, random.iterators.cosine","random.streams.discreteUniform":"\nrandom.streams.discreteUniform( a, b[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    discrete uniform distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.discreteUniform( 2, 5, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.discreteUniform.factory( [a, b, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a discrete uniform distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    a: integer (optional)\n        Minimum support.\n\n    b: integer (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.discreteUniform.factory( opts );\n\n\nrandom.streams.discreteUniform.objectMode( a, b[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a discrete uniform distribution.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.discreteUniform.objectMode( 2, 5, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.discreteUniform, random.iterators.discreteUniform\n","random.streams.discreteUniform.factory":"\nrandom.streams.discreteUniform.factory( [a, b, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a discrete uniform distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    a: integer (optional)\n        Minimum support.\n\n    b: integer (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.discreteUniform.factory( opts );","random.streams.discreteUniform.objectMode":"\nrandom.streams.discreteUniform.objectMode( a, b[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a discrete uniform distribution.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.discreteUniform.objectMode( 2, 5, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.discreteUniform, random.iterators.discreteUniform","random.streams.erlang":"\nrandom.streams.erlang( k, λ[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from an\n    Erlang distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    k: integer\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.erlang( 2, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.erlang.factory( [k, λ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an Erlang distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Shape parameter.\n\n    λ: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.erlang.factory( opts );\n\n\nrandom.streams.erlang.objectMode( k, λ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an Erlang distribution.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.erlang.objectMode( 2, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.erlang, random.iterators.erlang\n","random.streams.erlang.factory":"\nrandom.streams.erlang.factory( [k, λ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an Erlang distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Shape parameter.\n\n    λ: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.erlang.factory( opts );","random.streams.erlang.objectMode":"\nrandom.streams.erlang.objectMode( k, λ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an Erlang distribution.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.erlang.objectMode( 2, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.erlang, random.iterators.erlang","random.streams.exponential":"\nrandom.streams.exponential( λ[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from an\n    exponential distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.exponential( 3.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.exponential.factory( [λ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an exponential distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    λ: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.exponential.factory( opts );\n\n\nrandom.streams.exponential.objectMode( λ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an exponential distribution.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.exponential.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.exponential, random.iterators.exponential\n","random.streams.exponential.factory":"\nrandom.streams.exponential.factory( [λ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an exponential distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    λ: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.exponential.factory( opts );","random.streams.exponential.objectMode":"\nrandom.streams.exponential.objectMode( λ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an exponential distribution.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.exponential.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.exponential, random.iterators.exponential","random.streams.f":"\nrandom.streams.f( d1, d2[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from an\n    F distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    d1: number\n        Degrees of freedom.\n\n    d2: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.f( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.f.factory( [d1, d2, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an F distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    d1: number (optional)\n        Degrees of freedom.\n\n    d2: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.f.factory( opts );\n\n\nrandom.streams.f.objectMode( d1, d2[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an F distribution.\n\n    Parameters\n    ----------\n    d1: number\n        Degrees of freedom.\n\n    d2: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.f.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.f, random.iterators.f\n","random.streams.f.factory":"\nrandom.streams.f.factory( [d1, d2, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an F distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    d1: number (optional)\n        Degrees of freedom.\n\n    d2: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.f.factory( opts );","random.streams.f.objectMode":"\nrandom.streams.f.objectMode( d1, d2[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an F distribution.\n\n    Parameters\n    ----------\n    d1: number\n        Degrees of freedom.\n\n    d2: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.f.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.f, random.iterators.f","random.streams.frechet":"\nrandom.streams.frechet( α, s, m[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Fréchet distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.frechet( 2.0, 5.0, 3.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.frechet.factory( [α, s, m,][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Fréchet distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    m: number (optional)\n        Location parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.frechet.factory( opts );\n\n\nrandom.streams.frechet.objectMode( α, s, m[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Fréchet distribution.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.frechet.objectMode( 2.0, 5.0, 3.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.frechet, random.iterators.frechet\n","random.streams.frechet.factory":"\nrandom.streams.frechet.factory( [α, s, m,][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Fréchet distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    m: number (optional)\n        Location parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.frechet.factory( opts );","random.streams.frechet.objectMode":"\nrandom.streams.frechet.objectMode( α, s, m[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Fréchet distribution.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.frechet.objectMode( 2.0, 5.0, 3.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.frechet, random.iterators.frechet","random.streams.gamma":"\nrandom.streams.gamma( α, β[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    gamma distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.gamma( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.gamma.factory( [α, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a gamma distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.gamma.factory( opts );\n\n\nrandom.streams.gamma.objectMode( α, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a gamma distribution.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.gamma.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.gamma, random.iterators.gamma\n","random.streams.gamma.factory":"\nrandom.streams.gamma.factory( [α, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a gamma distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.gamma.factory( opts );","random.streams.gamma.objectMode":"\nrandom.streams.gamma.objectMode( α, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a gamma distribution.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.gamma.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.gamma, random.iterators.gamma","random.streams.geometric":"\nrandom.streams.geometric( p[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    geometric distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.geometric( 0.5, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.geometric.factory( [p, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a geometric distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.geometric.factory( opts );\n\n\nrandom.streams.geometric.objectMode( p[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a geometric distribution.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.geometric.objectMode( 0.3, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.geometric, random.iterators.geometric\n","random.streams.geometric.factory":"\nrandom.streams.geometric.factory( [p, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a geometric distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.geometric.factory( opts );","random.streams.geometric.objectMode":"\nrandom.streams.geometric.objectMode( p[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a geometric distribution.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.geometric.objectMode( 0.3, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.geometric, random.iterators.geometric","random.streams.gumbel":"\nrandom.streams.gumbel( μ, β[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Gumbel distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.gumbel( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.gumbel.factory( [μ, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Gumbel distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.gumbel.factory( opts );\n\n\nrandom.streams.gumbel.objectMode( μ, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Gumbel distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.gumbel.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.gumbel, random.iterators.gumbel\n","random.streams.gumbel.factory":"\nrandom.streams.gumbel.factory( [μ, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Gumbel distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.gumbel.factory( opts );","random.streams.gumbel.objectMode":"\nrandom.streams.gumbel.objectMode( μ, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Gumbel distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.gumbel.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.gumbel, random.iterators.gumbel","random.streams.hypergeometric":"\nrandom.streams.hypergeometric( N, K, n[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    hypergeometric distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.hypergeometric( 5, 3, 2, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.hypergeometric.factory( [N, K, n,][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a hypergeometric distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    N: integer (optional)\n        Population size.\n\n    K: integer (optional)\n        Subpopulation size.\n\n    n: integer (optional)\n        Number of draws.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.hypergeometric.factory( opts );\n\n\nrandom.streams.hypergeometric.objectMode( N, K, n[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a hypergeometric distribution.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.hypergeometric.objectMode( 5, 3, 2, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.hypergeometric, random.iterators.hypergeometric\n","random.streams.hypergeometric.factory":"\nrandom.streams.hypergeometric.factory( [N, K, n,][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a hypergeometric distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    N: integer (optional)\n        Population size.\n\n    K: integer (optional)\n        Subpopulation size.\n\n    n: integer (optional)\n        Number of draws.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.hypergeometric.factory( opts );","random.streams.hypergeometric.objectMode":"\nrandom.streams.hypergeometric.objectMode( N, K, n[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a hypergeometric distribution.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.hypergeometric.objectMode( 5, 3, 2, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.hypergeometric, random.iterators.hypergeometric","random.streams.improvedZiggurat":"\nrandom.streams.improvedZiggurat( [options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    standard normal distribution using the Improved Ziggurat algorithm.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.improvedZiggurat( opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.improvedZiggurat.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a standard normal distribution using the Improved\n    Ziggurat algorithm.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.improvedZiggurat.factory( opts );\n\n\nrandom.streams.improvedZiggurat.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a standard normal distribution using the Improved Ziggurat\n    algorithm.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.improvedZiggurat.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.improvedZiggurat, random.iterators.improvedZiggurat, random.streams.boxMuller, random.streams.randn\n","random.streams.improvedZiggurat.factory":"\nrandom.streams.improvedZiggurat.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a standard normal distribution using the Improved\n    Ziggurat algorithm.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.improvedZiggurat.factory( opts );","random.streams.improvedZiggurat.objectMode":"\nrandom.streams.improvedZiggurat.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a standard normal distribution using the Improved Ziggurat\n    algorithm.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.improvedZiggurat.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.improvedZiggurat, random.iterators.improvedZiggurat, random.streams.boxMuller, random.streams.randn","random.streams.invgamma":"\nrandom.streams.invgamma( α, β[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from an\n    inverse gamma distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.invgamma( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.invgamma.factory( [α, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an inverse gamma distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.invgamma.factory( opts );\n\n\nrandom.streams.invgamma.objectMode( α, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an inverse gamma distribution.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.invgamma.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.invgamma, random.iterators.invgamma\n","random.streams.invgamma.factory":"\nrandom.streams.invgamma.factory( [α, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an inverse gamma distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.invgamma.factory( opts );","random.streams.invgamma.objectMode":"\nrandom.streams.invgamma.objectMode( α, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an inverse gamma distribution.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.invgamma.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.invgamma, random.iterators.invgamma","random.streams.kumaraswamy":"\nrandom.streams.kumaraswamy( a, b[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Kumaraswamy's double bounded distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.kumaraswamy( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.kumaraswamy.factory( [a, b, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Kumaraswamy's double bounded distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        First shape parameter.\n\n    b: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.kumaraswamy.factory( opts );\n\n\nrandom.streams.kumaraswamy.objectMode( a, b[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Kumaraswamy's double bounded distribution.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.kumaraswamy.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.kumaraswamy, random.iterators.kumaraswamy\n","random.streams.kumaraswamy.factory":"\nrandom.streams.kumaraswamy.factory( [a, b, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Kumaraswamy's double bounded distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        First shape parameter.\n\n    b: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.kumaraswamy.factory( opts );","random.streams.kumaraswamy.objectMode":"\nrandom.streams.kumaraswamy.objectMode( a, b[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Kumaraswamy's double bounded distribution.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.kumaraswamy.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.kumaraswamy, random.iterators.kumaraswamy","random.streams.laplace":"\nrandom.streams.laplace( μ, b[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Laplace (double exponential) distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    b: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.laplace( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.laplace.factory( [μ, b, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Laplace (double exponential) distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    b: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.laplace.factory( opts );\n\n\nrandom.streams.laplace.objectMode( μ, b[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Laplace (double exponential) distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    b: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.laplace.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.laplace, random.iterators.laplace\n","random.streams.laplace.factory":"\nrandom.streams.laplace.factory( [μ, b, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Laplace (double exponential) distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    b: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.laplace.factory( opts );","random.streams.laplace.objectMode":"\nrandom.streams.laplace.objectMode( μ, b[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Laplace (double exponential) distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    b: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.laplace.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.laplace, random.iterators.laplace","random.streams.levy":"\nrandom.streams.levy( μ, c[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Lévy distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    c: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.levy( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.levy.factory( [μ, c, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Lévy distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    c: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.levy.factory( opts );\n\n\nrandom.streams.levy.objectMode( μ, c[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Lévy distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    c: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.levy.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.levy, random.iterators.levy\n","random.streams.levy.factory":"\nrandom.streams.levy.factory( [μ, c, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Lévy distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    c: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.levy.factory( opts );","random.streams.levy.objectMode":"\nrandom.streams.levy.objectMode( μ, c[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Lévy distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    c: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.levy.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.levy, random.iterators.levy","random.streams.logistic":"\nrandom.streams.logistic( μ, s[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    logistic distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    s: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.logistic( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.logistic.factory( [μ, s, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a logistic distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.logistic.factory( opts );\n\n\nrandom.streams.logistic.objectMode( μ, s[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a logistic distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    s: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.logistic.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.logistic, random.iterators.logistic\n","random.streams.logistic.factory":"\nrandom.streams.logistic.factory( [μ, s, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a logistic distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.logistic.factory( opts );","random.streams.logistic.objectMode":"\nrandom.streams.logistic.objectMode( μ, s[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a logistic distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    s: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.logistic.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.logistic, random.iterators.logistic","random.streams.lognormal":"\nrandom.streams.lognormal( μ, σ[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    lognormal distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.lognormal( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.lognormal.factory( [μ, σ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a lognormal distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter.\n\n    σ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.lognormal.factory( opts );\n\n\nrandom.streams.lognormal.objectMode( μ, σ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a lognormal distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.lognormal.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.lognormal, random.iterators.lognormal\n","random.streams.lognormal.factory":"\nrandom.streams.lognormal.factory( [μ, σ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a lognormal distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter.\n\n    σ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.lognormal.factory( opts );","random.streams.lognormal.objectMode":"\nrandom.streams.lognormal.objectMode( μ, σ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a lognormal distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.lognormal.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.lognormal, random.iterators.lognormal","random.streams.minstd":"\nrandom.streams.minstd( [options] )\n    Returns a readable stream for generating pseudorandom numbers on the\n    interval `[1, 2147483646]`.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    The underlying pseudorandom number generator (PRNG) is a linear congruential\n    pseudorandom number generator (LCG) based on Park and Miller.\n\n    The generator has a period of approximately `2.1e9`.\n\n    An LCG is fast and uses little memory. On the other hand, because the\n    generator is a simple LCG, the generator has recognized shortcomings. By\n    today's PRNG standards, the generator's period is relatively short. More\n    importantly, the \"randomness quality\" of the generator's output is lacking.\n    These defects make the generator unsuitable, for example, in Monte Carlo\n    simulations and in cryptographic applications.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.seed: Int32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Int32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.minstd( opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.minstd.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers on the interval `[1, 2147483646]`.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.minstd.factory( opts );\n\n\nrandom.streams.minstd.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    on the interval `[1, 2147483646]`.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.seed: Int32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Int32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.minstd.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.minstd, random.iterators.minstd, random.streams.minstdShuffle, random.streams.mt19937, random.streams.randi, random.streams.randu\n","random.streams.minstd.factory":"\nrandom.streams.minstd.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers on the interval `[1, 2147483646]`.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.minstd.factory( opts );","random.streams.minstd.objectMode":"\nrandom.streams.minstd.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    on the interval `[1, 2147483646]`.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.seed: Int32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Int32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.minstd.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.minstd, random.iterators.minstd, random.streams.minstdShuffle, random.streams.mt19937, random.streams.randi, random.streams.randu","random.streams.minstdShuffle":"\nrandom.streams.minstdShuffle( [options] )\n    Returns a readable stream for generating pseudorandom numbers on the\n    interval `[1, 2147483646]`.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    The underlying pseudorandom number generator (PRNG) is a linear congruential\n    pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n    Durham algorithm. The shuffle step considerably strengthens the \"randomness\n    quality\" of a simple LCG's output.\n\n    The generator has a period of approximately `2.1e9`.\n\n    An LCG is fast and uses little memory. On the other hand, because the\n    generator is a simple LCG, the generator has recognized shortcomings. By\n    today's PRNG standards, the generator's period is relatively short. In\n    general, this generator is unsuitable for Monte Carlo simulations and\n    cryptographic applications.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.seed: Int32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Int32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.minstdShuffle( opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.minstdShuffle.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers on the interval `[1, 2147483646]`.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.minstdShuffle.factory( opts );\n\n\nrandom.streams.minstdShuffle.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    on the interval `[1, 2147483646]`.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.seed: Int32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Int32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.minstdShuffle.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstd, random.streams.mt19937, random.streams.randi, random.streams.randu\n","random.streams.minstdShuffle.factory":"\nrandom.streams.minstdShuffle.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers on the interval `[1, 2147483646]`.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.minstdShuffle.factory( opts );","random.streams.minstdShuffle.objectMode":"\nrandom.streams.minstdShuffle.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    on the interval `[1, 2147483646]`.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.seed: Int32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Int32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.minstdShuffle.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstd, random.streams.mt19937, random.streams.randi, random.streams.randu","random.streams.mt19937":"\nrandom.streams.mt19937( [options] )\n    Returns a readable stream for generating pseudorandom numbers on the\n    interval `[1, 4294967295]`.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    The underlying pseudorandom number generator (PRNG) is a 32-bit Mersenne\n    Twister pseudorandom number generator.\n\n    The PRNG is *not* a cryptographically secure PRNG.\n\n    The PRNG has a period of 2^19937 - 1.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.mt19937( opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.mt19937.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers on the interval `[1, 4294967295]`.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.mt19937.factory( opts );\n\n\nrandom.streams.mt19937.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    on the interval `[1, 4294967295]`.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.mt19937.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.mt19937, random.iterators.mt19937, random.streams.minstd, random.streams.minstdShuffle, random.streams.randi, random.streams.randu\n","random.streams.mt19937.factory":"\nrandom.streams.mt19937.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers on the interval `[1, 4294967295]`.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.mt19937.factory( opts );","random.streams.mt19937.objectMode":"\nrandom.streams.mt19937.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    on the interval `[1, 4294967295]`.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.mt19937.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.mt19937, random.iterators.mt19937, random.streams.minstd, random.streams.minstdShuffle, random.streams.randi, random.streams.randu","random.streams.negativeBinomial":"\nrandom.streams.negativeBinomial( r, p[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    negative binomial distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.negativeBinomial( 20.0, 0.5, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.negativeBinomial.factory( [r, p, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a negative binomial distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    r: number (optional)\n        Number of successes until experiment is stopped.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.negativeBinomial.factory( opts );\n\n\nrandom.streams.negativeBinomial.objectMode( r, p[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a negative binomial distribution.\n\n    Parameters\n    ----------\n    r: integer\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.negativeBinomial.objectMode( 20.0, 0.5, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.negativeBinomial, random.iterators.negativeBinomial\n","random.streams.negativeBinomial.factory":"\nrandom.streams.negativeBinomial.factory( [r, p, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a negative binomial distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    r: number (optional)\n        Number of successes until experiment is stopped.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.negativeBinomial.factory( opts );","random.streams.negativeBinomial.objectMode":"\nrandom.streams.negativeBinomial.objectMode( r, p[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a negative binomial distribution.\n\n    Parameters\n    ----------\n    r: integer\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.negativeBinomial.objectMode( 20.0, 0.5, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.negativeBinomial, random.iterators.negativeBinomial","random.streams.normal":"\nrandom.streams.normal( μ, σ[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    normal distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    σ: number\n        Standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.normal( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.normal.factory( [μ, σ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a normal distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    σ: number (optional)\n        Standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.normal.factory( opts );\n\n\nrandom.streams.normal.objectMode( μ, σ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a normal distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    σ: number\n        Standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.normal.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.normal, random.iterators.normal\n","random.streams.normal.factory":"\nrandom.streams.normal.factory( [μ, σ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a normal distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    σ: number (optional)\n        Standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.normal.factory( opts );","random.streams.normal.objectMode":"\nrandom.streams.normal.objectMode( μ, σ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a normal distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    σ: number\n        Standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.normal.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.normal, random.iterators.normal","random.streams.pareto1":"\nrandom.streams.pareto1( α, β[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Pareto (Type I) distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.pareto1( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.pareto1.factory( [α, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Pareto (Type I) distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.pareto1.factory( opts );\n\n\nrandom.streams.pareto1.objectMode( α, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Pareto (Type I) distribution.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.pareto1.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.pareto1, random.iterators.pareto1\n","random.streams.pareto1.factory":"\nrandom.streams.pareto1.factory( [α, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Pareto (Type I) distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.pareto1.factory( opts );","random.streams.pareto1.objectMode":"\nrandom.streams.pareto1.objectMode( α, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Pareto (Type I) distribution.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.pareto1.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.pareto1, random.iterators.pareto1","random.streams.poisson":"\nrandom.streams.poisson( λ[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Poisson distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    λ: number\n        Mean.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.poisson( 3.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.poisson.factory( [λ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Poisson distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    λ: number (optional)\n        Mean.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.poisson.factory( opts );\n\n\nrandom.streams.poisson.objectMode( λ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Poisson distribution.\n\n    Parameters\n    ----------\n    λ: number\n        Mean.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.poisson.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.poisson, random.iterators.poisson\n","random.streams.poisson.factory":"\nrandom.streams.poisson.factory( [λ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Poisson distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    λ: number (optional)\n        Mean.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.poisson.factory( opts );","random.streams.poisson.objectMode":"\nrandom.streams.poisson.objectMode( λ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Poisson distribution.\n\n    Parameters\n    ----------\n    λ: number\n        Mean.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.poisson.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.poisson, random.iterators.poisson","random.streams.randi":"\nrandom.streams.randi( [options] )\n    Returns a readable stream for generating pseudorandom numbers having integer\n    values.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    The default underlying pseudorandom number generator (PRNG) *may* change in\n    the future. If exact reproducibility is required, either explicitly specify\n    a PRNG via the `name` option or use an underlying PRNG directly.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: any\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer\n        Length of generator seed.\n\n    stream.state: any\n        Generator state.\n\n    stream.stateLength: integer\n        Length of generator state.\n\n    stream.byteLength: integer\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.randi( opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.randi.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers having integer values.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.randi.factory( opts );\n\n\nrandom.streams.randi.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    having integer values.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: any\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer\n        Length of generator seed.\n\n    stream.state: any\n        Generator state.\n\n    stream.stateLength: integer\n        Length of generator state.\n\n    stream.byteLength: integer\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.randi.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.randi, random.iterators.randi, random.streams.randu\n","random.streams.randi.factory":"\nrandom.streams.randi.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers having integer values.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.randi.factory( opts );","random.streams.randi.objectMode":"\nrandom.streams.randi.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    having integer values.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: any\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer\n        Length of generator seed.\n\n    stream.state: any\n        Generator state.\n\n    stream.stateLength: integer\n        Length of generator state.\n\n    stream.byteLength: integer\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.randi.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.randi, random.iterators.randi, random.streams.randu","random.streams.randn":"\nrandom.streams.randn( [options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    standard normal distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    The default underlying pseudorandom number generator (PRNG) *may* change in\n    the future. If exact reproducibility is required, either explicitly specify\n    a PRNG via the `name` option or use an underlying PRNG directly.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - improved-ziggurat: improved ziggurat method.\n        - box-muller: Box-Muller transform.\n\n        Default: 'improved-ziggurat'.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.randn( opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.randn.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a standard normal distribution.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - improved-ziggurat: improved ziggurat method.\n        - box-muller: Box-Muller transform.\n\n        Default: 'improved-ziggurat'.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.randn.factory( opts );\n\n\nrandom.streams.randn.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a standard normal distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - improved-ziggurat: improved ziggurat method.\n        - box-muller: Box-Muller transform.\n\n        Default: 'improved-ziggurat'.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.randn.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.randn, random.iterators.randn, random.streams.boxMuller, random.streams.improvedZiggurat\n","random.streams.randn.factory":"\nrandom.streams.randn.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a standard normal distribution.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - improved-ziggurat: improved ziggurat method.\n        - box-muller: Box-Muller transform.\n\n        Default: 'improved-ziggurat'.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.randn.factory( opts );","random.streams.randn.objectMode":"\nrandom.streams.randn.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a standard normal distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - improved-ziggurat: improved ziggurat method.\n        - box-muller: Box-Muller transform.\n\n        Default: 'improved-ziggurat'.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.randn.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.randn, random.iterators.randn, random.streams.boxMuller, random.streams.improvedZiggurat","random.streams.randu":"\nrandom.streams.randu( [options] )\n    Returns a readable stream for generating uniformly distributed pseudorandom\n    numbers between 0 and 1.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    The default underlying pseudorandom number generator (PRNG) *may* change in\n    the future. If exact reproducibility is required, either explicitly specify\n    a PRNG via the `name` option or use an underlying PRNG directly.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: any\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer\n        Length of generator seed.\n\n    stream.state: any\n        Generator state.\n\n    stream.stateLength: integer\n        Length of generator state.\n\n    stream.byteLength: integer\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.randu( opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.randu.factory( [options] )\n    Returns a function for creating readable streams which generate uniformly\n    distributed pseudorandom numbers between 0 and 1.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.randu.factory( opts );\n\n\nrandom.streams.randu.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating uniformly distributed\n    pseudorandom numbers between 0 and 1.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: any\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer\n        Length of generator seed.\n\n    stream.state: any\n        Generator state.\n\n    stream.stateLength: integer\n        Length of generator state.\n\n    stream.byteLength: integer\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.randu.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.randu, random.iterators.randu, random.streams.randi\n","random.streams.randu.factory":"\nrandom.streams.randu.factory( [options] )\n    Returns a function for creating readable streams which generate uniformly\n    distributed pseudorandom numbers between 0 and 1.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.randu.factory( opts );","random.streams.randu.objectMode":"\nrandom.streams.randu.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating uniformly distributed\n    pseudorandom numbers between 0 and 1.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: any\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer\n        Length of generator seed.\n\n    stream.state: any\n        Generator state.\n\n    stream.stateLength: integer\n        Length of generator state.\n\n    stream.byteLength: integer\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.randu.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.randu, random.iterators.randu, random.streams.randi","random.streams.rayleigh":"\nrandom.streams.rayleigh( σ[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Rayleigh distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.rayleigh( 3.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.rayleigh.factory( [σ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Rayleigh distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    σ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.rayleigh.factory( opts );\n\n\nrandom.streams.rayleigh.objectMode( σ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Rayleigh distribution.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.rayleigh.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.rayleigh, random.iterators.rayleigh\n","random.streams.rayleigh.factory":"\nrandom.streams.rayleigh.factory( [σ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Rayleigh distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    σ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.rayleigh.factory( opts );","random.streams.rayleigh.objectMode":"\nrandom.streams.rayleigh.objectMode( σ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Rayleigh distribution.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.rayleigh.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.rayleigh, random.iterators.rayleigh","random.streams.t":"\nrandom.streams.t( v[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Student's t distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.t( 3.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.t.factory( [v, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Student's t distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    v: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.t.factory( opts );\n\n\nrandom.streams.t.objectMode( v[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Student's t distribution.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.t.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.t, random.iterators.t\n","random.streams.t.factory":"\nrandom.streams.t.factory( [v, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Student's t distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    v: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.t.factory( opts );","random.streams.t.objectMode":"\nrandom.streams.t.objectMode( v[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Student's t distribution.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.t.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.t, random.iterators.t","random.streams.triangular":"\nrandom.streams.triangular( a, b, c[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    triangular distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.triangular( 2.0, 5.0, 4.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.triangular.factory( [a, b, c, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a triangular distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    c: number (optional)\n        Mode.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.triangular.factory( opts );\n\n\nrandom.streams.triangular.objectMode( a, b, c[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a triangular distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.triangular.objectMode( 2.0, 5.0, 4.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.triangular, random.iterators.triangular\n","random.streams.triangular.factory":"\nrandom.streams.triangular.factory( [a, b, c, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a triangular distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    c: number (optional)\n        Mode.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.triangular.factory( opts );","random.streams.triangular.objectMode":"\nrandom.streams.triangular.objectMode( a, b, c[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a triangular distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.triangular.objectMode( 2.0, 5.0, 4.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.triangular, random.iterators.triangular","random.streams.uniform":"\nrandom.streams.uniform( a, b[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    uniform distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.uniform( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.uniform.factory( [a, b, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a uniform distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.uniform.factory( opts );\n\n\nrandom.streams.uniform.objectMode( a, b[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a uniform distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.uniform.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.uniform, random.iterators.uniform\n","random.streams.uniform.factory":"\nrandom.streams.uniform.factory( [a, b, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a uniform distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.uniform.factory( opts );","random.streams.uniform.objectMode":"\nrandom.streams.uniform.objectMode( a, b[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a uniform distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.uniform.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.uniform, random.iterators.uniform","random.streams.weibull":"\nrandom.streams.weibull( k, λ[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Weibull distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    k: number\n        Scale parameter.\n\n    λ: number\n        Shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.weibull( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.weibull.factory( [k, λ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Weibull distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Scale parameter.\n\n    λ: number (optional)\n        Shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.weibull.factory( opts );\n\n\nrandom.streams.weibull.objectMode( k, λ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Weibull distribution.\n\n    Parameters\n    ----------\n    k: number\n        Scale parameter.\n\n    λ: number\n        Shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.weibull.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.weibull, random.iterators.weibull\n","random.streams.weibull.factory":"\nrandom.streams.weibull.factory( [k, λ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Weibull distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Scale parameter.\n\n    λ: number (optional)\n        Shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.weibull.factory( opts );","random.streams.weibull.objectMode":"\nrandom.streams.weibull.objectMode( k, λ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Weibull distribution.\n\n    Parameters\n    ----------\n    k: number\n        Scale parameter.\n\n    λ: number\n        Shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.weibull.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.weibull, random.iterators.weibull","random.strided.arcsine":"\nrandom.strided.arcsine( N, a, sa, b, sb, out, so[, options] )\n    Fills a strided array with pseudorandom numbers drawn from an arcsine\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    a: ArrayLikeObject\n        Minimum support.\n\n    sa: integer\n        Index increment for `a`.\n\n    b: ArrayLikeObject\n        Maximum support.\n\n    sb: integer\n        Index increment for `b`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 0.0, 1.0, 5 );\n    > var b = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.arcsine( out.length, a, 1, b, 1, out, 1 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 0.0, 1.0, 6 );\n    > b = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.arcsine( 3, a, -2, b, 1, out, 1 )\n    [...]\n\n\nrandom.strided.arcsine.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from an arcsine\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    a: ArrayLikeObject\n        Minimum support.\n\n    sa: integer\n        Index increment for `a`.\n\n    oa: integer\n        Starting index for `a`.\n\n    b: ArrayLikeObject\n        Maximum support.\n\n    sb: integer\n        Index increment for `b`.\n\n    ob: integer\n        Starting index for `b`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 0.0, 1.0, 5 );\n    > var b = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.arcsine.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 0.0, 1.0, 6 );\n    > b = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.arcsine.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.arcsine, random.array.arcsine\n","random.strided.arcsine.ndarray":"\nrandom.strided.arcsine.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from an arcsine\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    a: ArrayLikeObject\n        Minimum support.\n\n    sa: integer\n        Index increment for `a`.\n\n    oa: integer\n        Starting index for `a`.\n\n    b: ArrayLikeObject\n        Maximum support.\n\n    sb: integer\n        Index increment for `b`.\n\n    ob: integer\n        Starting index for `b`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 0.0, 1.0, 5 );\n    > var b = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.arcsine.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 0.0, 1.0, 6 );\n    > b = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.arcsine.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.arcsine, random.array.arcsine","random.strided.bernoulli":"\nrandom.strided.bernoulli( N, p, sp, out, so )\n    Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    p: ArrayLikeObject\n        Success probability.\n\n    sp: integer\n        Index increment for `p`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.bernoulli.ndarray( N, p, sp, op, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    p: ArrayLikeObject\n        Success probability.\n\n    sp: integer\n        Index increment for `p`.\n\n    op: integer\n        Starting index for `p`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.bernoulli.ndarray( out.length, [ 0.5 ], 0, 0, out, 1, 0 )\n    [...]\n\n\nrandom.strided.bernoulli.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Bernoulli distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.bernoulli.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 0.5 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.bernoulli.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.bernoulli.PRNG;\n\n\nrandom.strided.bernoulli.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.bernoulli.seed;\n\n\nrandom.strided.bernoulli.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.bernoulli.seedLength;\n\n\nrandom.strided.bernoulli.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.bernoulli.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.bernoulli.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.bernoulli.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.bernoulli.stateLength;\n\n\nrandom.strided.bernoulli.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.bernoulli.byteLength;\n\n    See Also\n    --------\n    base.random.bernoulli, random.array.bernoulli\n","random.strided.bernoulli.ndarray":"\nrandom.strided.bernoulli.ndarray( N, p, sp, op, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    p: ArrayLikeObject\n        Success probability.\n\n    sp: integer\n        Index increment for `p`.\n\n    op: integer\n        Starting index for `p`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.bernoulli.ndarray( out.length, [ 0.5 ], 0, 0, out, 1, 0 )\n    [...]","random.strided.bernoulli.factory":"\nrandom.strided.bernoulli.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Bernoulli distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.bernoulli.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 0.5 ], 0, out, 1 )\n    [...]","random.strided.bernoulli.PRNG":"\nrandom.strided.bernoulli.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.bernoulli.PRNG;","random.strided.bernoulli.seed":"\nrandom.strided.bernoulli.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.bernoulli.seed;","random.strided.bernoulli.seedLength":"\nrandom.strided.bernoulli.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.bernoulli.seedLength;","random.strided.bernoulli.state":"\nrandom.strided.bernoulli.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.bernoulli.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.bernoulli.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n    [...]","random.strided.bernoulli.stateLength":"\nrandom.strided.bernoulli.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.bernoulli.stateLength;","random.strided.bernoulli.byteLength":"\nrandom.strided.bernoulli.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.bernoulli.byteLength;\n\n    See Also\n    --------\n    base.random.bernoulli, random.array.bernoulli","random.strided.beta":"\nrandom.strided.beta( N, alpha, sa, beta, sb, out, so[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a beta\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        First shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    beta: ArrayLikeObject\n        Second shape parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.beta( out.length, a, 1, b, 1, out, 1 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.beta( 3, a, -2, b, 1, out, 1 )\n    [...]\n\n\nrandom.strided.beta.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a beta\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        First shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    oa: integer\n        Starting index for `alpha`.\n\n    beta: ArrayLikeObject\n        Second shape parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    ob: integer\n        Starting index for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.beta.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.beta.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.beta, random.array.beta\n","random.strided.beta.ndarray":"\nrandom.strided.beta.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a beta\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        First shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    oa: integer\n        Starting index for `alpha`.\n\n    beta: ArrayLikeObject\n        Second shape parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    ob: integer\n        Starting index for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.beta.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.beta.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.beta, random.array.beta","random.strided.betaprime":"\nrandom.strided.betaprime( N, alpha, sa, beta, sb, out, so[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a beta prime\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        First shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    beta: ArrayLikeObject\n        Second shape parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.betaprime( out.length, a, 1, b, 1, out, 1 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.betaprime( 3, a, -2, b, 1, out, 1 )\n    [...]\n\n\nrandom.strided.betaprime.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a beta prime\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        First shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    oa: integer\n        Starting index for `alpha`.\n\n    beta: ArrayLikeObject\n        Second shape parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    ob: integer\n        Starting index for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.betaprime.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.betaprime.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.betaprime, random.array.betaprime\n","random.strided.betaprime.ndarray":"\nrandom.strided.betaprime.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a beta prime\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        First shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    oa: integer\n        Starting index for `alpha`.\n\n    beta: ArrayLikeObject\n        Second shape parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    ob: integer\n        Starting index for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.betaprime.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.betaprime.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.betaprime, random.array.betaprime","random.strided.chi":"\nrandom.strided.chi( N, k, sk, out, so )\n    Fills a strided array with pseudorandom numbers drawn from a chi\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    k: ArrayLikeObject\n        Degrees of freedom.\n\n    sk: integer\n        Index increment for `k`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.chi.ndarray( N, k, sk, ok, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a chi\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    k: ArrayLikeObject\n        Degrees of freedom.\n\n    sk: integer\n        Index increment for `k`.\n\n    ok: integer\n        Starting index for `k`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.chi.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]\n\n\nrandom.strided.chi.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a chi distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.chi.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.chi.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.chi.PRNG;\n\n\nrandom.strided.chi.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.chi.seed;\n\n\nrandom.strided.chi.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.chi.seedLength;\n\n\nrandom.strided.chi.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.chi.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.chi.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.chi.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.chi.stateLength;\n\n\nrandom.strided.chi.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.chi.byteLength;\n\n    See Also\n    --------\n    base.random.chi, random.array.chi\n","random.strided.chi.ndarray":"\nrandom.strided.chi.ndarray( N, k, sk, ok, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a chi\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    k: ArrayLikeObject\n        Degrees of freedom.\n\n    sk: integer\n        Index increment for `k`.\n\n    ok: integer\n        Starting index for `k`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.chi.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]","random.strided.chi.factory":"\nrandom.strided.chi.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a chi distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.chi.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.chi.PRNG":"\nrandom.strided.chi.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.chi.PRNG;","random.strided.chi.seed":"\nrandom.strided.chi.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.chi.seed;","random.strided.chi.seedLength":"\nrandom.strided.chi.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.chi.seedLength;","random.strided.chi.state":"\nrandom.strided.chi.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.chi.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.chi.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.chi.stateLength":"\nrandom.strided.chi.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.chi.stateLength;","random.strided.chi.byteLength":"\nrandom.strided.chi.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.chi.byteLength;\n\n    See Also\n    --------\n    base.random.chi, random.array.chi","random.strided.chisquare":"\nrandom.strided.chisquare( N, k, sk, out, so )\n    Fills a strided array with pseudorandom numbers drawn from a chi-square\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    k: ArrayLikeObject\n        Degrees of freedom.\n\n    sk: integer\n        Index increment for `k`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.chisquare.ndarray( N, k, sk, ok, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a chi-square\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    k: ArrayLikeObject\n        Degrees of freedom.\n\n    sk: integer\n        Index increment for `k`.\n\n    ok: integer\n        Starting index for `k`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.chisquare.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]\n\n\nrandom.strided.chisquare.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a chi-square distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.chisquare.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.chisquare.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.chisquare.PRNG;\n\n\nrandom.strided.chisquare.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.chisquare.seed;\n\n\nrandom.strided.chisquare.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.chisquare.seedLength;\n\n\nrandom.strided.chisquare.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.chisquare.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.chisquare.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.chisquare.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.chisquare.stateLength;\n\n\nrandom.strided.chisquare.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.chisquare.byteLength;\n\n    See Also\n    --------\n    base.random.chisquare, random.array.chisquare\n","random.strided.chisquare.ndarray":"\nrandom.strided.chisquare.ndarray( N, k, sk, ok, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a chi-square\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    k: ArrayLikeObject\n        Degrees of freedom.\n\n    sk: integer\n        Index increment for `k`.\n\n    ok: integer\n        Starting index for `k`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.chisquare.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]","random.strided.chisquare.factory":"\nrandom.strided.chisquare.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a chi-square distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.chisquare.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.chisquare.PRNG":"\nrandom.strided.chisquare.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.chisquare.PRNG;","random.strided.chisquare.seed":"\nrandom.strided.chisquare.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.chisquare.seed;","random.strided.chisquare.seedLength":"\nrandom.strided.chisquare.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.chisquare.seedLength;","random.strided.chisquare.state":"\nrandom.strided.chisquare.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.chisquare.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.chisquare.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.chisquare.stateLength":"\nrandom.strided.chisquare.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.chisquare.stateLength;","random.strided.chisquare.byteLength":"\nrandom.strided.chisquare.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.chisquare.byteLength;\n\n    See Also\n    --------\n    base.random.chisquare, random.array.chisquare","random.strided.cosine":"\nrandom.strided.cosine( N, mu, sm, s, ss, out, so[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a cosine\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mu: ArrayLikeObject\n        Mean.\n\n    sm: integer\n        Index increment for `mu`.\n\n    s: ArrayLikeObject\n        Scale parameter.\n\n    ss: integer\n        Index increment for `s`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var mu = linspace( 0.0, 1.0, 5 );\n    > var s = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.cosine( out.length, mu, 1, s, 1, out, 1 )\n    [...]\n\n    // Advanced indexing:\n    > mu = linspace( 0.0, 1.0, 6 );\n    > s = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.cosine( 3, mu, -2, s, 1, out, 1 )\n    [...]\n\n\nrandom.strided.cosine.ndarray( N, mu, sm, om, s, ss, os, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a cosine\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mu: ArrayLikeObject\n        Mean.\n\n    sm: integer\n        Index increment for `mu`.\n\n    om: integer\n        Starting index for `mu`.\n\n    s: ArrayLikeObject\n        Scale parameter.\n\n    ss: integer\n        Index increment for `s`.\n\n    os: integer\n        Starting index for `s`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var mu = linspace( 0.0, 1.0, 5 );\n    > var s = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.cosine.ndarray( out.length, mu, 1, 0, s, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > mu = linspace( 0.0, 1.0, 6 );\n    > s = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.cosine.ndarray( 3, mu, 2, 1, s, -1, s.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.cosine, random.array.cosine\n","random.strided.cosine.ndarray":"\nrandom.strided.cosine.ndarray( N, mu, sm, om, s, ss, os, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a cosine\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mu: ArrayLikeObject\n        Mean.\n\n    sm: integer\n        Index increment for `mu`.\n\n    om: integer\n        Starting index for `mu`.\n\n    s: ArrayLikeObject\n        Scale parameter.\n\n    ss: integer\n        Index increment for `s`.\n\n    os: integer\n        Starting index for `s`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var mu = linspace( 0.0, 1.0, 5 );\n    > var s = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.cosine.ndarray( out.length, mu, 1, 0, s, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > mu = linspace( 0.0, 1.0, 6 );\n    > s = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.cosine.ndarray( 3, mu, 2, 1, s, -1, s.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.cosine, random.array.cosine","random.strided.discreteUniform":"\nrandom.strided.discreteUniform( N, a, sa, b, sb, out, so[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a discrete\n    uniform distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    a: ArrayLikeObject\n        Minimum support.\n\n    sa: integer\n        Index increment for `a`.\n\n    b: ArrayLikeObject\n        Maximum support.\n\n    sb: integer\n        Index increment for `b`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = [ -10, -5, 0, 5, 10 ];\n    > var b = [ 20, 20, 20, 20, 20 ];\n    > var out = azeros( 5, 'generic' );\n    > random.strided.discreteUniform( out.length, a, 1, b, 1, out, 1 )\n    [...]\n\n    // Advanced indexing:\n    > a = [ -10, -5, 0, 5, 10, 15 ];\n    > b = [ 20, 20, 20, 20, 20, 20 ];\n    > out = azeros( 6, 'generic' );\n    > random.strided.discreteUniform( 3, a, -2, b, 1, out, 1 )\n    [...]\n\n\nrandom.strided.discreteUniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a discrete\n    uniform distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    a: ArrayLikeObject\n        Minimum support.\n\n    sa: integer\n        Index increment for `a`.\n\n    oa: integer\n        Starting index for `a`.\n\n    b: ArrayLikeObject\n        Maximum support.\n\n    sb: integer\n        Index increment for `b`.\n\n    ob: integer\n        Starting index for `b`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = [ -10, -5, 0, 5, 10 ];\n    > var b = [ 20, 20, 20, 20, 20 ];\n    > var out = azeros( 5, 'generic' );\n    > random.strided.discreteUniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = [ -10, -5, 0, 5, 10, 15 ];\n    > b = [ 20, 20, 20, 20, 20, 20 ];\n    > out = azeros( 6, 'generic' );\n    > random.strided.discreteUniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.discreteUniform, random.array.discreteUniform, random.strided.uniform\n","random.strided.discreteUniform.ndarray":"\nrandom.strided.discreteUniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a discrete\n    uniform distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    a: ArrayLikeObject\n        Minimum support.\n\n    sa: integer\n        Index increment for `a`.\n\n    oa: integer\n        Starting index for `a`.\n\n    b: ArrayLikeObject\n        Maximum support.\n\n    sb: integer\n        Index increment for `b`.\n\n    ob: integer\n        Starting index for `b`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = [ -10, -5, 0, 5, 10 ];\n    > var b = [ 20, 20, 20, 20, 20 ];\n    > var out = azeros( 5, 'generic' );\n    > random.strided.discreteUniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = [ -10, -5, 0, 5, 10, 15 ];\n    > b = [ 20, 20, 20, 20, 20, 20 ];\n    > out = azeros( 6, 'generic' );\n    > random.strided.discreteUniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.discreteUniform, random.array.discreteUniform, random.strided.uniform","random.strided.exponential":"\nrandom.strided.exponential( N, lambda, sl, out, so )\n    Fills a strided array with pseudorandom numbers drawn from an exponential\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    lambda: ArrayLikeObject\n        Rate parameter.\n\n    sl: integer\n        Index increment for `lambda`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.exponential.ndarray( N, lambda, sl, ol, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from an exponential\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    lambda: ArrayLikeObject\n        Rate parameter.\n\n    sl: integer\n        Index increment for `lambda`.\n\n    ol: integer\n        Starting index for `lambda`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.exponential.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]\n\n\nrandom.strided.exponential.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from an exponential distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.exponential.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.exponential.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.exponential.PRNG;\n\n\nrandom.strided.exponential.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.exponential.seed;\n\n\nrandom.strided.exponential.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.exponential.seedLength;\n\n\nrandom.strided.exponential.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.exponential.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.exponential.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.exponential.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.exponential.stateLength;\n\n\nrandom.strided.exponential.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.exponential.byteLength;\n\n    See Also\n    --------\n    base.random.exponential, random.array.exponential\n","random.strided.exponential.ndarray":"\nrandom.strided.exponential.ndarray( N, lambda, sl, ol, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from an exponential\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    lambda: ArrayLikeObject\n        Rate parameter.\n\n    sl: integer\n        Index increment for `lambda`.\n\n    ol: integer\n        Starting index for `lambda`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.exponential.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]","random.strided.exponential.factory":"\nrandom.strided.exponential.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from an exponential distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.exponential.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.exponential.PRNG":"\nrandom.strided.exponential.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.exponential.PRNG;","random.strided.exponential.seed":"\nrandom.strided.exponential.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.exponential.seed;","random.strided.exponential.seedLength":"\nrandom.strided.exponential.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.exponential.seedLength;","random.strided.exponential.state":"\nrandom.strided.exponential.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.exponential.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.exponential.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.exponential.stateLength":"\nrandom.strided.exponential.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.exponential.stateLength;","random.strided.exponential.byteLength":"\nrandom.strided.exponential.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.exponential.byteLength;\n\n    See Also\n    --------\n    base.random.exponential, random.array.exponential","random.strided.gamma":"\nrandom.strided.gamma( N, alpha, sa, beta, sb, out, so[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a gamma\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        Shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    beta: ArrayLikeObject\n        Rate parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.gamma( out.length, a, 1, b, 1, out, 1 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.gamma( 3, a, -2, b, 1, out, 1 )\n    [...]\n\n\nrandom.strided.gamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a gamma\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        Shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    oa: integer\n        Starting index for `alpha`.\n\n    beta: ArrayLikeObject\n        Rate parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    ob: integer\n        Starting index for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.gamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.gamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.gamma, random.array.gamma\n","random.strided.gamma.ndarray":"\nrandom.strided.gamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a gamma\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        Shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    oa: integer\n        Starting index for `alpha`.\n\n    beta: ArrayLikeObject\n        Rate parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    ob: integer\n        Starting index for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.gamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.gamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.gamma, random.array.gamma","random.strided.geometric":"\nrandom.strided.geometric( N, p, sp, out, so )\n    Fills a strided array with pseudorandom numbers drawn from a geometric\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    p: ArrayLikeObject\n        Success probability.\n\n    sp: integer\n        Index increment for `p`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.geometric.ndarray( N, p, sp, op, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a geometric\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    p: ArrayLikeObject\n        Success probability.\n\n    sp: integer\n        Index increment for `p`.\n\n    op: integer\n        Starting index for `p`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.geometric.ndarray( out.length, [ 0.01 ], 0, 0, out, 1, 0 )\n    [...]\n\n\nrandom.strided.geometric.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a geometric distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.geometric.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 0.01 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.geometric.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.geometric.PRNG;\n\n\nrandom.strided.geometric.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.geometric.seed;\n\n\nrandom.strided.geometric.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.geometric.seedLength;\n\n\nrandom.strided.geometric.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.geometric.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.geometric.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.geometric.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.geometric.stateLength;\n\n\nrandom.strided.geometric.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.geometric.byteLength;\n\n    See Also\n    --------\n    base.random.geometric, random.array.geometric\n","random.strided.geometric.ndarray":"\nrandom.strided.geometric.ndarray( N, p, sp, op, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a geometric\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    p: ArrayLikeObject\n        Success probability.\n\n    sp: integer\n        Index increment for `p`.\n\n    op: integer\n        Starting index for `p`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.geometric.ndarray( out.length, [ 0.01 ], 0, 0, out, 1, 0 )\n    [...]","random.strided.geometric.factory":"\nrandom.strided.geometric.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a geometric distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.geometric.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 0.01 ], 0, out, 1 )\n    [...]","random.strided.geometric.PRNG":"\nrandom.strided.geometric.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.geometric.PRNG;","random.strided.geometric.seed":"\nrandom.strided.geometric.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.geometric.seed;","random.strided.geometric.seedLength":"\nrandom.strided.geometric.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.geometric.seedLength;","random.strided.geometric.state":"\nrandom.strided.geometric.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.geometric.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.geometric.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n    [...]","random.strided.geometric.stateLength":"\nrandom.strided.geometric.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.geometric.stateLength;","random.strided.geometric.byteLength":"\nrandom.strided.geometric.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.geometric.byteLength;\n\n    See Also\n    --------\n    base.random.geometric, random.array.geometric","random.strided.invgamma":"\nrandom.strided.invgamma( N, alpha, sa, beta, sb, out, so[, options] )\n    Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        Shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    beta: ArrayLikeObject\n        Scale parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.invgamma( out.length, a, 1, b, 1, out, 1 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.invgamma( 3, a, -2, b, 1, out, 1 )\n    [...]\n\n\nrandom.strided.invgamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        Shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    oa: integer\n        Starting index for `alpha`.\n\n    beta: ArrayLikeObject\n        Scale parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    ob: integer\n        Starting index for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.invgamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.invgamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.invgamma, random.array.invgamma\n","random.strided.invgamma.ndarray":"\nrandom.strided.invgamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        Shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    oa: integer\n        Starting index for `alpha`.\n\n    beta: ArrayLikeObject\n        Scale parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    ob: integer\n        Starting index for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.invgamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.invgamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.invgamma, random.array.invgamma","random.strided.lognormal":"\nrandom.strided.lognormal( N, mu, sm, sigma, ss, out, so[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a lognormal\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mu: ArrayLikeObject\n        Location parameter.\n\n    sm: integer\n        Index increment for `mu`.\n\n    sigma: ArrayLikeObject\n        Scale parameter.\n\n    ss: integer\n        Index increment for `sigma`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var mu = linspace( 0.0, 1.0, 5 );\n    > var sigma = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.lognormal( out.length, mu, 1, sigma, 1, out, 1 )\n    [...]\n\n    // Advanced indexing:\n    > mu = linspace( 0.0, 1.0, 6 );\n    > sigma = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.lognormal( 3, mu, -2, sigma, 1, out, 1 )\n    [...]\n\n\nrandom.strided.lognormal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a lognormal\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mu: ArrayLikeObject\n        Location parameter.\n\n    sm: integer\n        Index increment for `mu`.\n\n    om: integer\n        Starting index for `mu`.\n\n    sigma: ArrayLikeObject\n        Scale parameter.\n\n    ss: integer\n        Index increment for `sigma`.\n\n    os: integer\n        Starting index for `sigma`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var mu = linspace( 0.0, 1.0, 5 );\n    > var sigma = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.lognormal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > mu = linspace( 0.0, 1.0, 6 );\n    > sigma = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.lognormal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.lognormal, random.array.lognormal\n","random.strided.lognormal.ndarray":"\nrandom.strided.lognormal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a lognormal\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mu: ArrayLikeObject\n        Location parameter.\n\n    sm: integer\n        Index increment for `mu`.\n\n    om: integer\n        Starting index for `mu`.\n\n    sigma: ArrayLikeObject\n        Scale parameter.\n\n    ss: integer\n        Index increment for `sigma`.\n\n    os: integer\n        Starting index for `sigma`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var mu = linspace( 0.0, 1.0, 5 );\n    > var sigma = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.lognormal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > mu = linspace( 0.0, 1.0, 6 );\n    > sigma = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.lognormal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.lognormal, random.array.lognormal","random.strided.minstd":"\nrandom.strided.minstd( N, out, so[, options] )\n    Fills a strided array with pseudorandom integers between 1 and 2147483646\n    (inclusive).\n\n    The `N` and stride parameters determine which elements in the provided\n    strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstd( out.length, out, 1 )\n    [...]\n\n\nrandom.strided.minstd.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom integers between 1 and 2147483646\n    (inclusive) using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstd.ndarray( out.length, out, 1, 0 )\n    [...]\n\n\nrandom.strided.minstd.normalized( N, out, so[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstd.normalized( out.length, out, 1 )\n    [...]\n\n\nrandom.strided.minstd.normalized.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1 using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstd.normalized.ndarray( out.length, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.minstd, random.array.minstd, random.strided.minstdShuffle, random.strided.randu\n","random.strided.minstd.ndarray":"\nrandom.strided.minstd.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom integers between 1 and 2147483646\n    (inclusive) using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstd.ndarray( out.length, out, 1, 0 )\n    [...]","random.strided.minstd.normalized":"\nrandom.strided.minstd.normalized( N, out, so[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstd.normalized( out.length, out, 1 )\n    [...]","random.strided.minstd.normalized.ndarray":"\nrandom.strided.minstd.normalized.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1 using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstd.normalized.ndarray( out.length, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.minstd, random.array.minstd, random.strided.minstdShuffle, random.strided.randu","random.strided.minstdShuffle":"\nrandom.strided.minstdShuffle( N, out, so[, options] )\n    Fills a strided array with pseudorandom integers between 1 and 2147483646\n    (inclusive).\n\n    The `N` and stride parameters determine which elements in the provided\n    strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstdShuffle( out.length, out, 1 )\n    [...]\n\n\nrandom.strided.minstdShuffle.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom integers between 1 and 2147483646\n    (inclusive) using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstdShuffle.ndarray( out.length, out, 1, 0 )\n    [...]\n\n\nrandom.strided.minstdShuffle.normalized( N, out, so[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstdShuffle.normalized( out.length, out, 1 )\n    [...]\n\n\nrandom.strided.minstdShuffle.normalized.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1 using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstdShuffle.normalized.ndarray( out.length, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.minstdShuffle, random.array.minstdShuffle, random.strided.minstd, random.strided.randu\n","random.strided.minstdShuffle.ndarray":"\nrandom.strided.minstdShuffle.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom integers between 1 and 2147483646\n    (inclusive) using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstdShuffle.ndarray( out.length, out, 1, 0 )\n    [...]","random.strided.minstdShuffle.normalized":"\nrandom.strided.minstdShuffle.normalized( N, out, so[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstdShuffle.normalized( out.length, out, 1 )\n    [...]","random.strided.minstdShuffle.normalized.ndarray":"\nrandom.strided.minstdShuffle.normalized.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1 using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstdShuffle.normalized.ndarray( out.length, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.minstdShuffle, random.array.minstdShuffle, random.strided.minstd, random.strided.randu","random.strided.mt19937":"\nrandom.strided.mt19937( N, out, so[, options] )\n    Fills a strided array with pseudorandom integers between 0 and 4294967295\n    (inclusive).\n\n    The `N` and stride parameters determine which elements in the provided\n    strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.mt19937( out.length, out, 1 )\n    [...]\n\n\nrandom.strided.mt19937.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom integers between 0 and 4294967295\n    (inclusive) using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.mt19937.ndarray( out.length, out, 1, 0 )\n    [...]\n\n\nrandom.strided.mt19937.normalized( N, out, so[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.mt19937.normalized( out.length, out, 1 )\n    [...]\n\n\nrandom.strided.mt19937.normalized.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1 using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.mt19937.normalized.ndarray( out.length, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.mt19937, random.array.mt19937, random.strided.randu\n","random.strided.mt19937.ndarray":"\nrandom.strided.mt19937.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom integers between 0 and 4294967295\n    (inclusive) using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.mt19937.ndarray( out.length, out, 1, 0 )\n    [...]","random.strided.mt19937.normalized":"\nrandom.strided.mt19937.normalized( N, out, so[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.mt19937.normalized( out.length, out, 1 )\n    [...]","random.strided.mt19937.normalized.ndarray":"\nrandom.strided.mt19937.normalized.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1 using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.mt19937.normalized.ndarray( out.length, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.mt19937, random.array.mt19937, random.strided.randu","random.strided.normal":"\nrandom.strided.normal( N, mu, sm, sigma, ss, out, so[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a normal\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mu: ArrayLikeObject\n        Mean.\n\n    sm: integer\n        Index increment for `mu`.\n\n    sigma: ArrayLikeObject\n        Standard deviation.\n\n    ss: integer\n        Index increment for `sigma`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var mu = linspace( 0.0, 1.0, 5 );\n    > var sigma = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.normal( out.length, mu, 1, sigma, 1, out, 1 )\n    [...]\n\n    // Advanced indexing:\n    > mu = linspace( 0.0, 1.0, 6 );\n    > sigma = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.normal( 3, mu, -2, sigma, 1, out, 1 )\n    [...]\n\n\nrandom.strided.normal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a normal\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mu: ArrayLikeObject\n        Mean.\n\n    sm: integer\n        Index increment for `mu`.\n\n    om: integer\n        Starting index for `mu`.\n\n    sigma: ArrayLikeObject\n        Standard deviation.\n\n    ss: integer\n        Index increment for `sigma`.\n\n    os: integer\n        Starting index for `sigma`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var mu = linspace( 0.0, 1.0, 5 );\n    > var sigma = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.normal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > mu = linspace( 0.0, 1.0, 6 );\n    > sigma = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.normal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.normal, random.array.normal\n","random.strided.normal.ndarray":"\nrandom.strided.normal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a normal\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mu: ArrayLikeObject\n        Mean.\n\n    sm: integer\n        Index increment for `mu`.\n\n    om: integer\n        Starting index for `mu`.\n\n    sigma: ArrayLikeObject\n        Standard deviation.\n\n    ss: integer\n        Index increment for `sigma`.\n\n    os: integer\n        Starting index for `sigma`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var mu = linspace( 0.0, 1.0, 5 );\n    > var sigma = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.normal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > mu = linspace( 0.0, 1.0, 6 );\n    > sigma = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.normal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.normal, random.array.normal","random.strided.poisson":"\nrandom.strided.poisson( N, lambda, sl, out, so )\n    Fills a strided array with pseudorandom numbers drawn from a Poisson\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    lambda: ArrayLikeObject\n        Mean parameter.\n\n    sl: integer\n        Index increment for `lambda`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.poisson.ndarray( N, lambda, sl, ol, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a Poisson\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    lambda: ArrayLikeObject\n        Mean parameter.\n\n    sl: integer\n        Index increment for `lambda`.\n\n    ol: integer\n        Starting index for `lambda`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.poisson.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]\n\n\nrandom.strided.poisson.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Poisson distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.poisson.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.poisson.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.poisson.PRNG;\n\n\nrandom.strided.poisson.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.poisson.seed;\n\n\nrandom.strided.poisson.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.poisson.seedLength;\n\n\nrandom.strided.poisson.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.poisson.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.poisson.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.poisson.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.poisson.stateLength;\n\n\nrandom.strided.poisson.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.poisson.byteLength;\n\n    See Also\n    --------\n    base.random.poisson, random.array.poisson\n","random.strided.poisson.ndarray":"\nrandom.strided.poisson.ndarray( N, lambda, sl, ol, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a Poisson\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    lambda: ArrayLikeObject\n        Mean parameter.\n\n    sl: integer\n        Index increment for `lambda`.\n\n    ol: integer\n        Starting index for `lambda`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.poisson.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]","random.strided.poisson.factory":"\nrandom.strided.poisson.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Poisson distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.poisson.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.poisson.PRNG":"\nrandom.strided.poisson.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.poisson.PRNG;","random.strided.poisson.seed":"\nrandom.strided.poisson.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.poisson.seed;","random.strided.poisson.seedLength":"\nrandom.strided.poisson.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.poisson.seedLength;","random.strided.poisson.state":"\nrandom.strided.poisson.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.poisson.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.poisson.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.poisson.stateLength":"\nrandom.strided.poisson.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.poisson.stateLength;","random.strided.poisson.byteLength":"\nrandom.strided.poisson.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.poisson.byteLength;\n\n    See Also\n    --------\n    base.random.poisson, random.array.poisson","random.strided.randu":"\nrandom.strided.randu( N, out, so[, options] )\n    Fills a strided array with uniformly distributed pseudorandom numbers\n    between 0 and 1.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: `'mt19937'`.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.randu( out.length, out, 1 )\n    [...]\n\n\nrandom.strided.randu.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with uniformly distributed pseudorandom numbers\n    between 0 and 1 using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: `'mt19937'`.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.randu.ndarray( out.length, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.randu, random.array.randu, random.strided.uniform\n","random.strided.randu.ndarray":"\nrandom.strided.randu.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with uniformly distributed pseudorandom numbers\n    between 0 and 1 using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: `'mt19937'`.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.randu.ndarray( out.length, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.randu, random.array.randu, random.strided.uniform","random.strided.rayleigh":"\nrandom.strided.rayleigh( N, sigma, ss, out, so )\n    Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sigma: ArrayLikeObject\n        Scale parameter.\n\n    ss: integer\n        Index increment for `sigma`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.rayleigh.ndarray( N, sigma, ss, os, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sigma: ArrayLikeObject\n        Scale parameter.\n\n    ss: integer\n        Index increment for `sigma`.\n\n    os: integer\n        Starting index for `sigma`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.rayleigh.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]\n\n\nrandom.strided.rayleigh.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Rayleigh distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.rayleigh.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.rayleigh.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.rayleigh.PRNG;\n\n\nrandom.strided.rayleigh.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.rayleigh.seed;\n\n\nrandom.strided.rayleigh.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.rayleigh.seedLength;\n\n\nrandom.strided.rayleigh.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.rayleigh.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.rayleigh.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.rayleigh.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.rayleigh.stateLength;\n\n\nrandom.strided.rayleigh.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.rayleigh.byteLength;\n\n    See Also\n    --------\n    base.random.rayleigh, random.array.rayleigh\n","random.strided.rayleigh.ndarray":"\nrandom.strided.rayleigh.ndarray( N, sigma, ss, os, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sigma: ArrayLikeObject\n        Scale parameter.\n\n    ss: integer\n        Index increment for `sigma`.\n\n    os: integer\n        Starting index for `sigma`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.rayleigh.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]","random.strided.rayleigh.factory":"\nrandom.strided.rayleigh.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Rayleigh distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.rayleigh.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.rayleigh.PRNG":"\nrandom.strided.rayleigh.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.rayleigh.PRNG;","random.strided.rayleigh.seed":"\nrandom.strided.rayleigh.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.rayleigh.seed;","random.strided.rayleigh.seedLength":"\nrandom.strided.rayleigh.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.rayleigh.seedLength;","random.strided.rayleigh.state":"\nrandom.strided.rayleigh.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.rayleigh.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.rayleigh.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.rayleigh.stateLength":"\nrandom.strided.rayleigh.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.rayleigh.stateLength;","random.strided.rayleigh.byteLength":"\nrandom.strided.rayleigh.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.rayleigh.byteLength;\n\n    See Also\n    --------\n    base.random.rayleigh, random.array.rayleigh","random.strided.t":"\nrandom.strided.t( N, v, sv, out, so )\n    Fills a strided array with pseudorandom numbers drawn from a Student's t-\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    v: ArrayLikeObject\n        Degrees of freedom.\n\n    sv: integer\n        Index increment for `v`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.t.ndarray( N, v, sv, ov, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a Student's t-\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    v: ArrayLikeObject\n        Degrees of freedom.\n\n    sv: integer\n        Index increment for `v`.\n\n    ov: integer\n        Starting index for `v`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.t.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]\n\n\nrandom.strided.t.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Student's t-distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.t.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.t.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.t.PRNG;\n\n\nrandom.strided.t.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.t.seed;\n\n\nrandom.strided.t.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.t.seedLength;\n\n\nrandom.strided.t.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.t.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.t.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.t.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.t.stateLength;\n\n\nrandom.strided.t.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.t.byteLength;\n\n    See Also\n    --------\n    base.random.t, random.array.t\n","random.strided.t.ndarray":"\nrandom.strided.t.ndarray( N, v, sv, ov, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a Student's t-\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    v: ArrayLikeObject\n        Degrees of freedom.\n\n    sv: integer\n        Index increment for `v`.\n\n    ov: integer\n        Starting index for `v`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.t.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]","random.strided.t.factory":"\nrandom.strided.t.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Student's t-distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.t.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.t.PRNG":"\nrandom.strided.t.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.t.PRNG;","random.strided.t.seed":"\nrandom.strided.t.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.t.seed;","random.strided.t.seedLength":"\nrandom.strided.t.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.t.seedLength;","random.strided.t.state":"\nrandom.strided.t.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.t.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.t.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.t.stateLength":"\nrandom.strided.t.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.t.stateLength;","random.strided.t.byteLength":"\nrandom.strided.t.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.t.byteLength;\n\n    See Also\n    --------\n    base.random.t, random.array.t","random.strided.uniform":"\nrandom.strided.uniform( N, a, sa, b, sb, out, so[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a continuous\n    uniform distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    a: ArrayLikeObject\n        Minimum support.\n\n    sa: integer\n        Index increment for `a`.\n\n    b: ArrayLikeObject\n        Maximum support.\n\n    sb: integer\n        Index increment for `b`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 0.0, 1.0, 5 );\n    > var b = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.uniform( out.length, a, 1, b, 1, out, 1 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 0.0, 1.0, 6 );\n    > b = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.uniform( 3, a, -2, b, 1, out, 1 )\n    [...]\n\n\nrandom.strided.uniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a continuous\n    uniform distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    a: ArrayLikeObject\n        Minimum support.\n\n    sa: integer\n        Index increment for `a`.\n\n    oa: integer\n        Starting index for `a`.\n\n    b: ArrayLikeObject\n        Maximum support.\n\n    sb: integer\n        Index increment for `b`.\n\n    ob: integer\n        Starting index for `b`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 0.0, 1.0, 5 );\n    > var b = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.uniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 0.0, 1.0, 6 );\n    > b = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.uniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.uniform, random.array.uniform, random.strided.discreteUniform\n","random.strided.uniform.ndarray":"\nrandom.strided.uniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a continuous\n    uniform distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    a: ArrayLikeObject\n        Minimum support.\n\n    sa: integer\n        Index increment for `a`.\n\n    oa: integer\n        Starting index for `a`.\n\n    b: ArrayLikeObject\n        Maximum support.\n\n    sb: integer\n        Index increment for `b`.\n\n    ob: integer\n        Starting index for `b`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 0.0, 1.0, 5 );\n    > var b = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.uniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 0.0, 1.0, 6 );\n    > b = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.uniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.uniform, random.array.uniform, random.strided.discreteUniform","random.strided.weibull":"\nrandom.strided.weibull( N, k, sk, lambda, sl, out, so[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a Weibull\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    k: ArrayLikeObject\n        Scale parameter.\n\n    sk: integer\n        Index increment for `k`.\n\n    lambda: ArrayLikeObject\n        Shape parameter.\n\n    sl: integer\n        Index increment for `lambda`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.weibull( out.length, a, 1, b, 1, out, 1 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.weibull( 3, a, -2, b, 1, out, 1 )\n    [...]\n\n\nrandom.strided.weibull.ndarray( N, k, sk, ok, lambda, sl, ol, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a Weibull\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    k: ArrayLikeObject\n        Scale parameter.\n\n    sk: integer\n        Index increment for `k`.\n\n    ok: integer\n        Starting index for `k`.\n\n    lambda: ArrayLikeObject\n        Shape parameter.\n\n    sl: integer\n        Index increment for `lambda`.\n\n    ol: integer\n        Starting index for `lambda`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.weibull.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.weibull.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.weibull, random.array.weibull\n","random.strided.weibull.ndarray":"\nrandom.strided.weibull.ndarray( N, k, sk, ok, lambda, sl, ol, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a Weibull\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    k: ArrayLikeObject\n        Scale parameter.\n\n    sk: integer\n        Index increment for `k`.\n\n    ok: integer\n        Starting index for `k`.\n\n    lambda: ArrayLikeObject\n        Shape parameter.\n\n    sl: integer\n        Index increment for `lambda`.\n\n    ol: integer\n        Starting index for `lambda`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.weibull.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.weibull.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.weibull, random.array.weibull","ranks":"\nranks( arr[, options] )\n    Computes the sample ranks for the values of an array-like object.\n\n    When all elements of the `array` are different, the ranks are uniquely\n    determined. When there are equal elements (called *ties*), the `method`\n    option determines how they are handled. The default, `'average'`, replaces\n    the ranks of the ties by their mean. Other possible options are `'min'` and\n    `'max'`, which replace the ranks of the ties by their minimum and maximum,\n    respectively. `'dense'` works like `'min'`, with the difference that the\n    next highest element after a tie is assigned the next smallest integer.\n    Finally, `ordinal` gives each element in `arr` a distinct rank, according to\n    the position they appear in.\n\n    The `missing` option is used to specify how to handle missing data.\n    By default, `NaN` or `null` are treated as missing values. `'last'`specifies\n    that missing values are placed last, `'first'` that the are assigned the\n    lowest ranks and `'remove'` means that they are removed from the array\n    before the ranks are calculated.\n\n    Parameters\n    ----------\n    arr: Array<number>\n        Input values.\n\n    options: Object (optional)\n        Function options.\n\n    options.method (optional)\n        Method name determining how ties are treated (`average`, `min`, `max`,\n        `dense`, or `ordinal`). Default: `'average'`.\n\n    options.missing (optional)\n        Determines where missing values go (`first`, `last`, or `remove`).\n        Default: `'last'`.\n\n    options.encoding (optional)\n        Array of values encoding missing values. Default: `[ null, NaN ]`.\n\n    Returns\n    -------\n    out: Array\n        Array containing the computed ranks for the elements of the input array.\n\n    Examples\n    --------\n    > var arr = [ 1.1, 2.0, 3.5, 0.0, 2.4 ] ;\n    > var out = ranks( arr )\n    [ 2, 3, 5, 1, 4 ]\n\n    // Ties are averaged:\n    > arr =  [ 2, 2, 1, 4, 3 ];\n    > out = ranks( arr )\n    [ 2.5, 2.5, 1, 5, 4 ]\n\n    // Missing values are placed last:\n    > arr = [ null, 2, 2, 1, 4, 3, NaN, NaN ];\n    > out = ranks( arr )\n    [ 6, 2.5, 2.5, 1, 5, 4, 7 ,8 ]\n\n","readDir":"\nreadDir( path, clbk )\n    Asynchronously reads the contents of a directory.\n\n    Parameters\n    ----------\n    path: string|Buffer\n        Directory path.\n\n    clbk: Function\n        Callback to invoke after reading directory contents.\n\n    Examples\n    --------\n    > function onRead( error, data ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     } else {\n    ...         console.log( data );\n    ...     }\n    ... };\n    > readDir( './beep/boop', onRead );\n\n\nreadDir.sync( path )\n    Synchronously reads the contents of a directory.\n\n    Parameters\n    ----------\n    path: string|Buffer\n        Directory path.\n\n    Returns\n    -------\n    out: Error|Array|Array<string>\n        Directory contents.\n\n    Examples\n    --------\n    > var out = readDir.sync( './beep/boop' );\n\n    See Also\n    --------\n    exists, readFile\n","readDir.sync":"\nreadDir.sync( path )\n    Synchronously reads the contents of a directory.\n\n    Parameters\n    ----------\n    path: string|Buffer\n        Directory path.\n\n    Returns\n    -------\n    out: Error|Array|Array<string>\n        Directory contents.\n\n    Examples\n    --------\n    > var out = readDir.sync( './beep/boop' );\n\n    See Also\n    --------\n    exists, readFile","readFile":"\nreadFile( file[, options], clbk )\n    Asynchronously reads the entire contents of a file.\n\n    If provided an encoding, the function returns a string. Otherwise, the\n    function returns a Buffer object.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. Default: null.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    clbk: Function\n        Callback to invoke upon reading file contents.\n\n    Examples\n    --------\n    > function onRead( error, data ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     } else {\n    ...         console.log( data );\n    ...     }\n    ... };\n    > readFile( './beep/boop.js', onRead );\n\n\nreadFile.sync( file[, options] )\n    Synchronously reads the entire contents of a file.\n\n    If provided an encoding, the function returns a string. Otherwise, the\n    function returns a Buffer object.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. Default: null.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    Returns\n    -------\n    out: Error|Buffer|string\n        File contents.\n\n    Examples\n    --------\n    > var out = readFile.sync( './beep/boop.js' );\n\n    See Also\n    --------\n    exists, open, readDir, readJSON, writeFile\n","readFile.sync":"\nreadFile.sync( file[, options] )\n    Synchronously reads the entire contents of a file.\n\n    If provided an encoding, the function returns a string. Otherwise, the\n    function returns a Buffer object.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. Default: null.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    Returns\n    -------\n    out: Error|Buffer|string\n        File contents.\n\n    Examples\n    --------\n    > var out = readFile.sync( './beep/boop.js' );\n\n    See Also\n    --------\n    exists, open, readDir, readJSON, writeFile","readFileList":"\nreadFileList( filepaths[, options], clbk )\n    Asynchronously reads the entire contents of each file in a file list.\n\n    If a provided an encoding, the function returns file contents as strings.\n    Otherwise, the function returns Buffer objects.\n\n    Each file is represented by an object with the following fields:\n\n    - file: file path.\n    - data: file contents as either a Buffer or string.\n\n    Parameters\n    ----------\n    filepaths: Array<string>\n        Filepaths.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. Default: null.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    clbk: Function\n        Callback to invoke upon reading file contents.\n\n    Examples\n    --------\n    > function onRead( error, data ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     } else {\n    ...         console.log( data );\n    ...     }\n    ... };\n    > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n    > readFileList( filepaths, onRead );\n\n\nreadFileList.sync( filepaths[, options] )\n    Synchronously reads the entire contents of each file in a file list.\n\n    If a provided an encoding, the function returns file contents as strings.\n    Otherwise, the function returns Buffer objects.\n\n    Parameters\n    ----------\n    filepaths: Array<string>\n        Filepaths.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. Default: null.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    Returns\n    -------\n    out: Error|Array|Array<string>\n        File contents.\n\n    out[ i ].file: string\n        File path.\n\n    out[ i ].data: Buffer|string\n        File contents.\n\n    Examples\n    --------\n    > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n    > var out = readFileList.sync( filepaths );\n\n","readFileList.sync":"\nreadFileList.sync( filepaths[, options] )\n    Synchronously reads the entire contents of each file in a file list.\n\n    If a provided an encoding, the function returns file contents as strings.\n    Otherwise, the function returns Buffer objects.\n\n    Parameters\n    ----------\n    filepaths: Array<string>\n        Filepaths.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. Default: null.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    Returns\n    -------\n    out: Error|Array|Array<string>\n        File contents.\n\n    out[ i ].file: string\n        File path.\n\n    out[ i ].data: Buffer|string\n        File contents.\n\n    Examples\n    --------\n    > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n    > var out = readFileList.sync( filepaths );","readJSON":"\nreadJSON( file[, options], clbk )\n    Asynchronously reads a file as JSON.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. If the encoding option is set to `utf8` and the file has a\n        UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n        attempting to parse as JSON. Default: null.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    options.reviver: Function (optional)\n        JSON transformation function.\n\n    clbk: Function\n        Callback to invoke upon reading file contents.\n\n    Examples\n    --------\n    > function onRead( error, data ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     } else {\n    ...         console.log( data );\n    ...     }\n    ... };\n    > readJSON( './beep/boop.json', onRead );\n\n\nreadJSON.sync( file[, options] )\n    Synchronously reads a file as JSON.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. If the encoding option is set to `utf8` and the file has a\n        UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n        attempting to parse as JSON. Default: null.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    options.reviver: Function (optional)\n        JSON transformation function.\n\n    Returns\n    -------\n    out: Error|JSON\n        File contents.\n\n    Examples\n    --------\n    > var out = readJSON.sync( './beep/boop.json' );\n\n    See Also\n    --------\n    readFile\n","readJSON.sync":"\nreadJSON.sync( file[, options] )\n    Synchronously reads a file as JSON.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. If the encoding option is set to `utf8` and the file has a\n        UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n        attempting to parse as JSON. Default: null.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    options.reviver: Function (optional)\n        JSON transformation function.\n\n    Returns\n    -------\n    out: Error|JSON\n        File contents.\n\n    Examples\n    --------\n    > var out = readJSON.sync( './beep/boop.json' );\n\n    See Also\n    --------\n    readFile","readWASM":"\nreadWASM( file[, options], clbk )\n    Asynchronously reads a file as WebAssembly.\n\n    The function returns file contents as a Uint8Array.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    options: Object (optional)\n        Options.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    clbk: Function\n        Callback to invoke upon reading file contents.\n\n    Examples\n    --------\n    > function onRead( error, data ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     } else {\n    ...         console.log( data );\n    ...     }\n    ... };\n    > readWASM( './beep/boop.wasm', onRead );\n\n\nreadWASM.sync( file[, options] )\n    Synchronously reads a file as WebAssembly.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    options: Object (optional)\n        Options.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    Returns\n    -------\n    out: Error|Uint8Array\n        File contents.\n\n    Examples\n    --------\n    > var out = readWASM.sync( './beep/boop.wasm' );\n\n    See Also\n    --------\n    readFile\n","readWASM.sync":"\nreadWASM.sync( file[, options] )\n    Synchronously reads a file as WebAssembly.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    options: Object (optional)\n        Options.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    Returns\n    -------\n    out: Error|Uint8Array\n        File contents.\n\n    Examples\n    --------\n    > var out = readWASM.sync( './beep/boop.wasm' );\n\n    See Also\n    --------\n    readFile","real":"\nreal( z )\n    Returns the real component of a double-precision complex floating-point\n    number.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    re: number\n        Real component.\n\n    Examples\n    --------\n    > var z = new Complex128( 5.0, 3.0 );\n    > var re = real( z )\n    5.0\n\n    See Also\n    --------\n    imag, reim\n","realarray":"\nrealarray( [dtype] )\n    Creates a typed array.\n\n    The function supports the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754).\n    - float32: single-precision floating-point numbers (IEEE 754).\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n\n    The default typed array data type is `float64`.\n\n    Parameters\n    ----------\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = realarray()\n    <Float64Array>\n    > arr = realarray( 'float32' )\n    <Float32Array>\n\n\nrealarray( length[, dtype] )\n    Returns a typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = realarray( 5 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n    > arr = realarray( 5, 'int32' )\n    <Int32Array>[ 0, 0, 0, 0, 0 ]\n\n\nrealarray( typedarray[, dtype] )\n    Creates a typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = realarray( [ 0.5, 0.5, 0.5 ] );\n    > var arr2 = realarray( arr1, 'float32' )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]\n\n\nrealarray( obj[, dtype] )\n    Creates a typed array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a typed array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 0.5, 0.5, 0.5 ];\n    > var arr2 = realarray( arr1, 'float32' )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]\n\n\nrealarray( buffer[, byteOffset[, length]][, dtype] )\n    Returns a typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 16 );\n    > var arr = realarray( buf, 0, 4, 'float32' )\n    <Float32Array>[ 0.0, 0.0, 0.0, 0.0 ]\n\n    See Also\n    --------\n    Float64Array, Float32Array, Int32Array, Uint32Array, Int16Array, Uint16Array, Int8Array, Uint8Array, Uint8ClampedArray\n","realarrayCtors":"\nrealarrayCtors( dtype )\n    Returns a typed array constructor.\n\n    The function returns constructors for the following data types:\n\n    - float32: single-precision floating-point numbers.\n    - float64: double-precision floating-point numbers.\n    - int16: signed 16-bit integers.\n    - int32: signed 32-bit integers.\n    - int8: signed 8-bit integers.\n    - uint16: unsigned 16-bit integers.\n    - uint32: unsigned 32-bit integers.\n    - uint8: unsigned 8-bit integers.\n    - uint8c: unsigned clamped 8-bit integers.\n\n    Parameters\n    ----------\n    dtype: string\n        Data type.\n\n    Returns\n    -------\n    out: Function|null\n        Typed array constructor.\n\n    Examples\n    --------\n    > var ctor = realarrayCtors( 'float64' )\n    <Function>\n    > ctor = realarrayCtors( 'float' )\n    null\n\n    See Also\n    --------\n    arrayCtors, complexarrayCtors\n","realarrayDataTypes":"\nrealarrayDataTypes()\n    Returns a list of typed array real-valued data types.\n\n    Returns\n    -------\n    out: Array<string>\n        List of typed array data types.\n\n    Examples\n    --------\n    > var out = realarrayDataTypes()\n    <Array>\n\n    See Also\n    --------\n    arrayDataTypes, complexarrayDataTypes\n","realf":"\nrealf( z )\n    Returns the real component of a single-precision complex floating-point\n    number.\n\n    Parameters\n    ----------\n    z: Complex64\n        Complex number.\n\n    Returns\n    -------\n    re: number\n        Real component.\n\n    Examples\n    --------\n    > var z = new Complex64( 5.0, 3.0 );\n    > var re = realf( z )\n    5.0\n\n    See Also\n    --------\n    imagf, real, reimf\n","realmax":"\nrealmax( dtype )\n    Returns the maximum finite value capable of being represented by a numeric\n    real type.\n\n    The following numeric real types are supported:\n\n    - float64: double-precision floating-point numbers.\n    - float32: single-precision floating-point numbers.\n    - float16: half-precision floating-point numbers.\n\n    Parameters\n    ----------\n    dtype: string\n        Numeric type.\n\n    Returns\n    -------\n    out: number\n        Maximum finite value.\n\n    Examples\n    --------\n    > var m = realmax( 'float16' )\n    65504.0\n    > m = realmax( 'float32' )\n    3.4028234663852886e+38\n\n    See Also\n    --------\n    realmin, typemax\n","realmin":"\nrealmin( dtype )\n    Returns the smallest positive normal value capable of being represented by a\n    numeric real type.\n\n    The following numeric real types are supported:\n\n    - float64: double-precision floating-point numbers.\n    - float32: single-precision floating-point numbers.\n    - float16: half-precision floating-point numbers.\n\n    Parameters\n    ----------\n    dtype: string\n        Numeric type.\n\n    Returns\n    -------\n    out: number\n        Smallest finite normal value.\n\n    Examples\n    --------\n    > var m = realmin( 'float16' )\n    0.00006103515625\n    > m = realmin( 'float32' )\n    1.1754943508222875e-38\n\n    See Also\n    --------\n    realmax, typemin\n","reBasename":"\nreBasename( [platform] )\n    Returns a regular expression to capture the last part of a path.\n\n    The regular expression is platform-dependent. If the current process is\n    running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n    `*.REGEXP_POSIX`.\n\n    Parameters\n    ----------\n    platform: string (optional)\n        Path platform (either `posix` or `win32`).\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reBasename()\n    <RegExp>\n    > var RE_POSIX = reBasename( 'posix' );\n    > var RE_WIN32 = reBasename( 'win32' );\n    > var str = RE.toString();\n    > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n    true\n\n\nreBasename.REGEXP\n    Regular expression to capture the last part of a POSIX path.\n\n    Examples\n    --------\n    > var RE = reBasename.REGEXP\n    <RegExp>\n\n\nreBasename.REGEXP_POSIX\n    Regular expression to capture the last part of a POSIX path.\n\n    Examples\n    --------\n    > var base = reBasename.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n    'index.js'\n\n\nreBasename.REGEXP_WIN32\n    Regular expression to capture the last part of a Windows path.\n\n    Examples\n    --------\n    > var base = reBasename.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    'index.js'\n\n    See Also\n    --------\n    reBasenamePosix, reBasenameWindows\n","reBasename.REGEXP":"\nreBasename.REGEXP\n    Regular expression to capture the last part of a POSIX path.\n\n    Examples\n    --------\n    > var RE = reBasename.REGEXP\n    <RegExp>","reBasename.REGEXP_POSIX":"\nreBasename.REGEXP_POSIX\n    Regular expression to capture the last part of a POSIX path.\n\n    Examples\n    --------\n    > var base = reBasename.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n    'index.js'","reBasename.REGEXP_WIN32":"\nreBasename.REGEXP_WIN32\n    Regular expression to capture the last part of a Windows path.\n\n    Examples\n    --------\n    > var base = reBasename.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    'index.js'\n\n    See Also\n    --------\n    reBasenamePosix, reBasenameWindows","reBasenamePosix":"\nreBasenamePosix()\n    Returns a regular expression to capture the last part of a POSIX path.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE_BASENAME_POSIX = reBasenamePosix();\n    > var base = RE_BASENAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n    'index.js'\n    > base = RE_BASENAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\n    '.gitignore'\n    > base = RE_BASENAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\n    'file.pdf'\n    > base = RE_BASENAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\n    'file'\n    > base = RE_BASENAME_POSIX.exec( 'index.js' )[ 1 ]\n    'index.js'\n    > base = RE_BASENAME_POSIX.exec( '.' )[ 1 ]\n    '.'\n    > base = RE_BASENAME_POSIX.exec( './' )[ 1 ]\n    '.'\n    > base = RE_BASENAME_POSIX.exec( '' )[ 1 ]\n    ''\n\n\nreBasenamePosix.REGEXP\n    Regular expression to capture the last part of a POSIX path.\n\n    Examples\n    --------\n    > var base = reBasenamePosix.REGEXP.exec( 'foo/bar/index.js' )[ 1 ]\n    'index.js'\n\n    See Also\n    --------\n    reBasename, reBasenameWindows\n","reBasenamePosix.REGEXP":"\nreBasenamePosix.REGEXP\n    Regular expression to capture the last part of a POSIX path.\n\n    Examples\n    --------\n    > var base = reBasenamePosix.REGEXP.exec( 'foo/bar/index.js' )[ 1 ]\n    'index.js'\n\n    See Also\n    --------\n    reBasename, reBasenameWindows","reBasenameWindows":"\nreBasenameWindows()\n    Returns a regular expression to capture the last part of a Windows path.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE_BASENAME_WINDOWS = reBasenameWindows();\n    > var base = RE_BASENAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    'index.js'\n    > base = RE_BASENAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n    '.gitignore'\n    > base = RE_BASENAME_WINDOWS.exec( 'foo\\\\file.pdf' )[ 1 ]\n    'file.pdf'\n    > base = RE_BASENAME_WINDOWS.exec( 'foo\\\\bar\\\\file' )[ 1 ]\n    'file'\n    > base = RE_BASENAME_WINDOWS.exec( 'index.js' )[ 1 ]\n    'index.js'\n    > base = RE_BASENAME_WINDOWS.exec( '.' )[ 1 ]\n    '.'\n    > base = RE_BASENAME_WINDOWS.exec( '' )[ 1 ]\n    ''\n\n\nreBasenameWindows.REGEXP\n    Regular expression to capture the last part of a Windows path.\n\n    Examples\n    --------\n    > var match = reBasenameWindows.REGEXP.exec( 'foo\\\\file.pdf' )[ 1 ]\n    'file.pdf'\n\n    See Also\n    --------\n    reBasename, reBasenamePosix\n","reBasenameWindows.REGEXP":"\nreBasenameWindows.REGEXP\n    Regular expression to capture the last part of a Windows path.\n\n    Examples\n    --------\n    > var match = reBasenameWindows.REGEXP.exec( 'foo\\\\file.pdf' )[ 1 ]\n    'file.pdf'\n\n    See Also\n    --------\n    reBasename, reBasenamePosix","reColorHexadecimal":"\nreColorHexadecimal( [mode] )\n    Returns a regular expression to match a hexadecimal color.\n\n    Parameters\n    ----------\n    mode: string (optional)\n        Color format (`full`, `shorthand`, or `either`).\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reColorHexadecimal();\n    > var bool = RE.test( 'ffffff' )\n    true\n    > bool = RE.test( '000' )\n    false\n    > bool = RE.test( 'beep' )\n    false\n\n\nreColorHexadecimal.REGEXP\n    Regular expression to match a full hexadecimal color.\n\n    Examples\n    --------\n    > var bool = reColorHexadecimal.REGEXP.test( 'ffffff' )\n    true\n    > bool = reColorHexadecimal.REGEXP.test( '000' )\n    false\n    > bool = reColorHexadecimal.REGEXP.test( 'beep' )\n    false\n\n\nreColorHexadecimal.REGEXP_SHORTHAND\n    Regular expression to match a shorthand hexadecimal color.\n\n    Examples\n    --------\n    > var bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'ffffff' )\n    false\n    > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( '000' )\n    true\n    > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'beep' )\n    false\n\n\nreColorHexadecimal.REGEXP_EITHER\n    Regular expression to match either a shorthand or full length hexadecimal\n    color.\n\n    Examples\n    --------\n    > var bool = reColorHexadecimal.REGEXP_EITHER.test( 'ffffff' )\n    true\n    > bool = reColorHexadecimal.REGEXP_EITHER.test( '000' )\n    true\n    > bool = reColorHexadecimal.REGEXP_EITHER.test( 'beep' )\n    false\n\n","reColorHexadecimal.REGEXP":"\nreColorHexadecimal.REGEXP\n    Regular expression to match a full hexadecimal color.\n\n    Examples\n    --------\n    > var bool = reColorHexadecimal.REGEXP.test( 'ffffff' )\n    true\n    > bool = reColorHexadecimal.REGEXP.test( '000' )\n    false\n    > bool = reColorHexadecimal.REGEXP.test( 'beep' )\n    false","reColorHexadecimal.REGEXP_SHORTHAND":"\nreColorHexadecimal.REGEXP_SHORTHAND\n    Regular expression to match a shorthand hexadecimal color.\n\n    Examples\n    --------\n    > var bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'ffffff' )\n    false\n    > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( '000' )\n    true\n    > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'beep' )\n    false","reColorHexadecimal.REGEXP_EITHER":"\nreColorHexadecimal.REGEXP_EITHER\n    Regular expression to match either a shorthand or full length hexadecimal\n    color.\n\n    Examples\n    --------\n    > var bool = reColorHexadecimal.REGEXP_EITHER.test( 'ffffff' )\n    true\n    > bool = reColorHexadecimal.REGEXP_EITHER.test( '000' )\n    true\n    > bool = reColorHexadecimal.REGEXP_EITHER.test( 'beep' )\n    false","reDecimalNumber":"\nreDecimalNumber( [options] )\n    Returns a regular expression to match a decimal number.\n\n    A leading digit is not required.\n\n    A decimal point and at least one trailing digit is required.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.flags: string (optional)\n        Regular expression flags. Default: ''.\n\n    options.capture: boolean (optional)\n        Boolean indicating whether to create a capture group for the match.\n        Default: false.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reDecimalNumber();\n    > var bool = RE.test( '1.234' )\n    true\n    > bool = RE.test( '-1.234' )\n    true\n    > bool = RE.test( '0.0' )\n    true\n    > bool = RE.test( '.0' )\n    true\n    > bool = RE.test( '0' )\n    false\n    > bool = RE.test( 'beep' )\n    false\n\n    // Create a RegExp to capture all decimal numbers:\n    > var re = reDecimalNumber({ 'flags': 'g' });\n    > var str = '1.234 5.6, 7.8';\n    > var out = str.match( re )\n    [ '1.234', '5.6', '7.8' ]\n\n\nreDecimalNumber.REGEXP\n    Regular expression to match a decimal number.\n\n    A leading digit is not required.\n\n    A decimal point and at least one trailing digit is required.\n\n    Examples\n    --------\n    > var RE = reDecimalNumber.REGEXP;\n    > var bool = RE.test( '1.234' )\n    true\n    > bool = RE.test( '-1.234' )\n    true\n\n\nreDecimalNumber.REGEXP_CAPTURE\n    Regular expression to capture a decimal number.\n\n    A leading digit is not required.\n\n    A decimal point and at least one trailing digit is required.\n\n    Examples\n    --------\n    > var RE = reDecimalNumber.REGEXP_CAPTURE;\n    > var str = '1.02';\n    > var out = replace( str, RE, '$1 x $1' )\n    '1.02 x 1.02'\n","reDecimalNumber.REGEXP":"\nreDecimalNumber.REGEXP\n    Regular expression to match a decimal number.\n\n    A leading digit is not required.\n\n    A decimal point and at least one trailing digit is required.\n\n    Examples\n    --------\n    > var RE = reDecimalNumber.REGEXP;\n    > var bool = RE.test( '1.234' )\n    true\n    > bool = RE.test( '-1.234' )\n    true","reDecimalNumber.REGEXP_CAPTURE":"\nreDecimalNumber.REGEXP_CAPTURE\n    Regular expression to capture a decimal number.\n\n    A leading digit is not required.\n\n    A decimal point and at least one trailing digit is required.\n\n    Examples\n    --------\n    > var RE = reDecimalNumber.REGEXP_CAPTURE;\n    > var str = '1.02';\n    > var out = replace( str, RE, '$1 x $1' )\n    '1.02 x 1.02'","reDirname":"\nreDirname( [platform] )\n    Returns a regular expression to capture a path dirname.\n\n    The regular expression is platform-dependent. If the current process is\n    running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n    `*.REGEXP_POSIX`.\n\n    Parameters\n    ----------\n    platform: string (optional)\n        Path platform (either `posix` or `win32`).\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reDirname()\n    <RegExp>\n    > var RE_POSIX = reDirname( 'posix' );\n    > var dir = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n    '/foo/bar'\n    > var RE_WIN32 = reDirname( 'win32' );\n    > dir = RE_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    'C:\\foo\\bar'\n    > var str = RE.toString();\n    > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n    true\n\n\nreDirname.REGEXP\n    Regular expression to capture a path dirname.\n\n    Examples\n    --------\n    > var RE = reDirname.REGEXP\n    <RegExp>\n\n\nreDirname.REGEXP_POSIX\n    Regular expression to capture a POSIX path dirname.\n\n    Examples\n    --------\n    > var dir = reDirname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n    '/foo/bar'\n\n\nreDirname.REGEXP_WIN32\n    Regular expression to capture a Windows path dirname.\n\n    Examples\n    --------\n    > var dir = reDirname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    'C:\\foo\\bar'\n\n    See Also\n    --------\n    reDirnamePosix, reDirnameWindows, dirname\n","reDirname.REGEXP":"\nreDirname.REGEXP\n    Regular expression to capture a path dirname.\n\n    Examples\n    --------\n    > var RE = reDirname.REGEXP\n    <RegExp>","reDirname.REGEXP_POSIX":"\nreDirname.REGEXP_POSIX\n    Regular expression to capture a POSIX path dirname.\n\n    Examples\n    --------\n    > var dir = reDirname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n    '/foo/bar'","reDirname.REGEXP_WIN32":"\nreDirname.REGEXP_WIN32\n    Regular expression to capture a Windows path dirname.\n\n    Examples\n    --------\n    > var dir = reDirname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    'C:\\foo\\bar'\n\n    See Also\n    --------\n    reDirnamePosix, reDirnameWindows, dirname","reDirnamePosix":"\nreDirnamePosix()\n    Returns a regular expression to capture a POSIX path dirname.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reDirnamePosix();\n    > var dir = RE.exec( '/foo/bar/index.js' )[ 1 ]\n    '/foo/bar'\n    > dir = RE.exec( './foo/bar/.gitignore' )[ 1 ]\n    './foo/bar'\n    > dir = RE.exec( 'foo/file.pdf' )[ 1 ]\n    'foo'\n    > dir = RE.exec( '/foo/bar/file' )[ 1 ]\n    '/foo/bar'\n    > dir = RE.exec( 'index.js' )[ 1 ]\n    ''\n    > dir = RE.exec( '.' )[ 1 ]\n    '.'\n    > dir = RE.exec( './' )[ 1 ]\n    '.'\n    > dir = RE.exec( '' )[ 1 ]\n    ''\n\n\nreDirnamePosix.REGEXP\n    Regular expression to capture a POSIX path dirname.\n\n    Examples\n    --------\n    > var ext = reDirnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n    '/foo/bar'\n\n    See Also\n    --------\n    reDirname, reDirnameWindows, dirname\n","reDirnamePosix.REGEXP":"\nreDirnamePosix.REGEXP\n    Regular expression to capture a POSIX path dirname.\n\n    Examples\n    --------\n    > var ext = reDirnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n    '/foo/bar'\n\n    See Also\n    --------\n    reDirname, reDirnameWindows, dirname","reDirnameWindows":"\nreDirnameWindows()\n    Returns a regular expression to capture a Windows path dirname.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reDirnameWindows();\n    > var dir = RE.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n    'foo\\bar'\n    > dir = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n    'C:\\foo\\bar'\n    > dir = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\n    'foo'\n    > dir = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\n    '\\foo\\bar'\n    > dir = RE.exec( 'index.js' )[ 1 ]\n    ''\n    > dir = RE.exec( '' )[ 1 ]\n    ''\n\n\nreDirnameWindows.REGEXP\n    Regular expression to capture a Windows path dirname.\n\n    Examples\n    --------\n    > var dir = reDirnameWindows.REGEXP.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n    'foo\\bar'\n\n    See Also\n    --------\n    reDirname, reDirnamePosix, dirname\n","reDirnameWindows.REGEXP":"\nreDirnameWindows.REGEXP\n    Regular expression to capture a Windows path dirname.\n\n    Examples\n    --------\n    > var dir = reDirnameWindows.REGEXP.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n    'foo\\bar'\n\n    See Also\n    --------\n    reDirname, reDirnamePosix, dirname","reduce":"\nreduce( arr, initial, reducer[, thisArg] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    When invoked, the reduction function is provided four arguments:\n\n    - accumulator: accumulated value.\n    - value: array element.\n    - index: element index.\n    - arr: input array.\n\n    If provided an empty array, the function returns the initial value.\n\n    When provided an ndarray, the function performs a reduction over the entire\n    input ndarray (i.e., higher-order ndarray dimensions are flattened to a\n    single-dimension).\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject|ndarray\n        Input array.\n\n    initial: any\n        Accumulator value used in the first invocation of the reduction\n        function.\n\n    reducer: Function\n        Function to invoke for each element in the input array.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: any\n        Accumulated result.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.add, 2 );\n    > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > var out = reduce( arr, 0.0, f )\n    21.0\n\n    // ndarray:\n    > arr = array( arr, { 'shape': [ 2, 3 ] } );\n    > out = reduce( arr, 0.0, f )\n    21.0\n\n    See Also\n    --------\n    forEach, map, reduceAsync, reduceRight\n","reduce2d":"\nreduce2d( arr, initial, reducer[, thisArg] )\n    Reduces the number of dimensions by one of a two-dimensional nested array by\n    applying a function against an accumulator and each element along the\n    innermost dimension and returning the accumulation results as a one-\n    dimensional array.\n\n    The applied function is provided the following arguments:\n\n    - accumulator: accumulated value.\n    - value: array element.\n    - indices: current array element indices.\n    - arr: input array.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject<ArrayLikeObject>\n        Input array of arrays.\n\n    initial: ArrayLikeObject\n        Initial values. Must have a length equal to the size of the outermost\n        input array dimension.\n\n    reducer: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array\n        Accumulation results.\n\n    Examples\n    --------\n    > var f = naryFunction( base.add, 2 );\n    > var arr = [ [ 1, 2, 3 ], [ 4, 5, 6 ] ];\n    > var out = reduce2d( arr, [ 0, 0 ], f )\n    [ 6, 15 ]\n\n    See Also\n    --------\n    map2d, reduce\n","reduceAsync":"\nreduceAsync( collection, initial, [options,] reducer, done )\n    Applies a function against an accumulator and each element in a collection\n    and returns the accumulated result.\n\n    When invoked, `reducer` is provided a maximum of five arguments:\n\n    - accumulator: accumulated value.\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If\n    `reducer` accepts three arguments, `reducer` is provided:\n\n    - accumulator\n    - value\n    - next\n\n    If `reducer` accepts four arguments, `reducer` is provided:\n\n    - accumulator\n    - value\n    - index\n    - next\n\n    For every other `reducer` signature, `reducer` is provided all five\n    arguments.\n\n    The `next` callback accepts two arguments:\n\n    - error: error argument.\n    - accumulator: accumulated value.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    If provided an empty collection, the function invokes the `done` callback\n    with the `initial` value as the second argument.\n\n    The function does not skip `undefined` elements.\n\n    When processing collection elements concurrently, *beware* of race\n    conditions when updating an accumulator. This is especially true when an\n    accumulator is a primitive (e.g., a number). In general, prefer object\n    accumulators.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    initial: any\n        Accumulator value used in the first invocation of the reduction\n        function.\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: true.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    reducer: Function\n        The function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function fcn( acc, value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         acc.sum += value;\n    ...         next( null, acc );\n    ...     }\n    ... };\n    > function done( error, acc ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( acc.sum );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > var acc = { 'sum': 0 };\n    > reduceAsync( arr, acc, fcn, done )\n    3000\n    2500\n    1000\n    6500\n\n    // Limit number of concurrent invocations:\n    > function fcn( acc, value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         acc.sum += value;\n    ...         next( null, acc );\n    ...     }\n    ... };\n    > function done( error, acc ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( acc.sum );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 3000, 2500, 1000 ];\n    > var acc = { 'sum': 0 };\n    > reduceAsync( arr, acc, opts, fcn, done )\n    2500\n    3000\n    1000\n    6500\n\n    // Process concurrently:\n    > function fcn( acc, value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         acc.sum += value;\n    ...         next( null, acc );\n    ...     }\n    ... };\n    > function done( error, acc ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( acc.sum );\n    ... };\n    > var opts = { 'series': false };\n    > var arr = [ 3000, 2500, 1000 ];\n    > var acc = { 'sum': 0 };\n    > reduceAsync( arr, acc, opts, fcn, done )\n    1000\n    2500\n    3000\n    6500\n\n\nreduceAsync.factory( [options,] fcn )\n    Returns a function which applies a function against an accumulator and each\n    element in a collection and returns the accumulated result.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: true.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function fcn( acc, value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         acc.sum += value;\n    ...         next( null, acc );\n    ...     }\n    ... };\n    > var opts = { 'series': false };\n    > var f = reduceAsync.factory( opts, fcn );\n    > function done( error, acc ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( acc.sum );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > var acc = { 'sum': 0 };\n    > f( arr, acc, done )\n    1000\n    2500\n    3000\n    6500\n    > acc = { 'sum': 0 };\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, acc, done )\n    1000\n    1500\n    2000\n    4500\n\n    See Also\n    --------\n    forEachAsync, reduce, reduceRightAsync\n","reduceAsync.factory":"\nreduceAsync.factory( [options,] fcn )\n    Returns a function which applies a function against an accumulator and each\n    element in a collection and returns the accumulated result.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: true.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function fcn( acc, value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         acc.sum += value;\n    ...         next( null, acc );\n    ...     }\n    ... };\n    > var opts = { 'series': false };\n    > var f = reduceAsync.factory( opts, fcn );\n    > function done( error, acc ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( acc.sum );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > var acc = { 'sum': 0 };\n    > f( arr, acc, done )\n    1000\n    2500\n    3000\n    6500\n    > acc = { 'sum': 0 };\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, acc, done )\n    1000\n    1500\n    2000\n    4500\n\n    See Also\n    --------\n    forEachAsync, reduce, reduceRightAsync","reduceRight":"\nreduceRight( arr, initial, reducer[, thisArg] )\n    Applies a function against an accumulator and each element in an array while\n    iterating from right to left and returns the accumulated result.\n\n    When invoked, the reduction function is provided four arguments:\n\n    - accumulator: accumulated value.\n    - value: array element.\n    - index: element index.\n    - arr: input array.\n\n    If provided an empty array, the function returns the initial value.\n\n    When provided an ndarray, the function performs a reduction over the entire\n    input ndarray (i.e., higher-order ndarray dimensions are flattened to a\n    single-dimension).\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject|ndarray\n        Input array.\n\n    initial: any\n        Accumulator value used in the first invocation of the reduction\n        function.\n\n    reducer: Function\n        Function to invoke for each element in the input array.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: any\n        Accumulated result.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.add, 2 );\n    > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > var out = reduceRight( arr, 0.0, f )\n    21.0\n\n    // ndarray:\n    > arr = array( arr, { 'shape': [ 2, 3 ] } );\n    > out = reduceRight( arr, 0.0, f )\n    21.0\n\n    See Also\n    --------\n    forEachRight, mapRight, reduce, reduceRightAsync\n","reduceRightAsync":"\nreduceRightAsync( collection, initial, [options,] reducer, done )\n    Applies a function against an accumulator and each element in a collection\n    and returns the accumulated result, iterating from right to left.\n\n    When invoked, `reducer` is provided a maximum of five arguments:\n\n    - accumulator: accumulated value.\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If\n    `reducer` accepts three arguments, `reducer` is provided:\n\n    - accumulator\n    - value\n    - next\n\n    If `reducer` accepts four arguments, `reducer` is provided:\n\n    - accumulator\n    - value\n    - index\n    - next\n\n    For every other `reducer` signature, `reducer` is provided all five\n    arguments.\n\n    The `next` callback accepts two arguments:\n\n    - error: error argument.\n    - accumulator: accumulated value.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    If provided an empty collection, the function invokes the `done` callback\n    with the `initial` value as the second argument.\n\n    The function does not skip `undefined` elements.\n\n    When processing collection elements concurrently, *beware* of race\n    conditions when updating an accumulator. This is especially true when an\n    accumulator is a primitive (e.g., a number). In general, prefer object\n    accumulators.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    initial: any\n        Accumulator value used in the first invocation of the reduction\n        function.\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: true.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    reducer: Function\n        The function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function fcn( acc, value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         acc.sum += value;\n    ...         next( null, acc );\n    ...     }\n    ... };\n    > function done( error, acc ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( acc.sum );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > var acc = { 'sum': 0 };\n    > reduceRightAsync( arr, acc, fcn, done )\n    3000\n    2500\n    1000\n    6500\n\n    // Limit number of concurrent invocations:\n    > function fcn( acc, value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         acc.sum += value;\n    ...         next( null, acc );\n    ...     }\n    ... };\n    > function done( error, acc ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( acc.sum );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 1000, 2500, 3000 ];\n    > var acc = { 'sum': 0 };\n    > reduceRightAsync( arr, acc, opts, fcn, done )\n    2500\n    3000\n    1000\n    6500\n\n    // Process concurrently:\n    > function fcn( acc, value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         acc.sum += value;\n    ...         next( null, acc );\n    ...     }\n    ... };\n    > function done( error, acc ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( acc.sum );\n    ... };\n    > var opts = { 'series': false };\n    > var arr = [ 1000, 2500, 3000 ];\n    > var acc = { 'sum': 0 };\n    > reduceRightAsync( arr, acc, opts, fcn, done )\n    1000\n    2500\n    3000\n    6500\n\n\nreduceRightAsync.factory( [options,] fcn )\n    Returns a function which applies a function against an accumulator and each\n    element in a collection and returns the accumulated result, iterating from\n    right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: true.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function fcn( acc, value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         acc.sum += value;\n    ...         next( null, acc );\n    ...     }\n    ... };\n    > var opts = { 'series': false };\n    > var f = reduceRightAsync.factory( opts, fcn );\n    > function done( error, acc ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( acc.sum );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > var acc = { 'sum': 0 };\n    > f( arr, acc, done )\n    1000\n    2500\n    3000\n    6500\n    > acc = { 'sum': 0 };\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, acc, done )\n    1000\n    1500\n    2000\n    4500\n\n    See Also\n    --------\n    forEachRightAsync, reduceAsync, reduceRight\n","reduceRightAsync.factory":"\nreduceRightAsync.factory( [options,] fcn )\n    Returns a function which applies a function against an accumulator and each\n    element in a collection and returns the accumulated result, iterating from\n    right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: true.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function fcn( acc, value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         acc.sum += value;\n    ...         next( null, acc );\n    ...     }\n    ... };\n    > var opts = { 'series': false };\n    > var f = reduceRightAsync.factory( opts, fcn );\n    > function done( error, acc ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( acc.sum );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > var acc = { 'sum': 0 };\n    > f( arr, acc, done )\n    1000\n    2500\n    3000\n    6500\n    > acc = { 'sum': 0 };\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, acc, done )\n    1000\n    1500\n    2000\n    4500\n\n    See Also\n    --------\n    forEachRightAsync, reduceAsync, reduceRight","reDurationString":"\nreDurationString()\n    Returns a regular expression to match a duration string.\n\n    A duration string is a string containing a sequence of time units. A time\n    unit is a nonnegative integer followed by a unit identifier. The following\n    unit identifiers are supported:\n\n    - d: days.\n    - h: hours.\n    - m: minutes.\n    - s: seconds.\n    - ms: milliseconds.\n\n    For example, the string `1m3s10ms` is a duration string containing three\n    time units: `1m` (1 minute), `3s` (3 seconds), and `10ms` (10 milliseconds).\n    The string `60m` is a duration string containing a single time unit: `60m`\n    (60 minutes). Time units must be supplied in descending order of magnitude\n    (i.e., days, hours, minutes, seconds, milliseconds).\n\n    Duration strings are case insensitive. For example, the string `1M3S10MS` is\n    equivalent to `1m3s10ms`.\n\n    The regular expression captures the following groups:\n\n    1. The days component.\n    2. The hours component.\n    3. The minutes component.\n    4. The seconds component.\n    5. The milliseconds component.\n\n    Returns\n    -------\n    re: RegExp: Regular expression\n        Regular expression to match a duration string.\n\n    Examples\n    --------\n    > var RE = reDurationString();\n    > var parts = RE.exec( '3d2ms' )\n    [...]\n    > parts = RE.exec( '4h3m20s' )\n    [...]\n\n\nreDurationString.REGEXP\n    Regular expression to match a duration string.\n\n    Examples\n    --------\n    > var bool = reDurationString.REGEXP.test( '3d2ms' )\n    true\n    > bool = reDurationString.REGEXP.test( 'foo' )\n    false\n","reDurationString.REGEXP":"\nreDurationString.REGEXP\n    Regular expression to match a duration string.\n\n    Examples\n    --------\n    > var bool = reDurationString.REGEXP.test( '3d2ms' )\n    true\n    > bool = reDurationString.REGEXP.test( 'foo' )\n    false","reEOL":"\nreEOL( [options] )\n    Regular expression to match a newline character sequence: /\\r?\\n/.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.flags: string (optional)\n        Regular expression flags. Default: ''.\n\n    options.capture: boolean (optional)\n        Boolean indicating whether to create a capture group for the match.\n        Default: false.\n\n    Returns\n    -------\n    regexp: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE_EOL = reEOL();\n    > var bool = RE_EOL.test( '\\n' )\n    true\n    > bool = RE_EOL.test( '\\r\\n' )\n    true\n    > bool = RE_EOL.test( '\\\\r\\\\n' )\n    false\n\nreEOL.REGEXP\n    Regular expression to match a newline character sequence: /\\r?\\n/.\n\n    Examples\n    --------\n    > var bool = reEOL.REGEXP.test( 'abc' )\n    false\n\nreEOL.REGEXP_CAPTURE\n    Regular expression to capture a newline character sequence: /\\r?\\n/.\n\n    Examples\n    --------\n    > var parts = reEOL.REGEXP_CAPTURE.exec( '\\n' )\n    [ '\\n', '\\n' ]\n\n","reEOL.REGEXP":"\nreEOL.REGEXP\n    Regular expression to match a newline character sequence: /\\r?\\n/.\n\n    Examples\n    --------\n    > var bool = reEOL.REGEXP.test( 'abc' )\n    false","reEOL.REGEXP_CAPTURE":"\nreEOL.REGEXP_CAPTURE\n    Regular expression to capture a newline character sequence: /\\r?\\n/.\n\n    Examples\n    --------\n    > var parts = reEOL.REGEXP_CAPTURE.exec( '\\n' )\n    [ '\\n', '\\n' ]","reExtendedLengthPath":"\nreExtendedLengthPath()\n    Returns a regular expression to test if a string is an extended-length path.\n\n    Extended-length paths are Windows paths which begin with `\\\\?\\`.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reExtendedLengthPath();\n    > var path = '\\\\\\\\?\\\\C:\\\\foo\\\\bar';\n    > var bool = RE.test( path )\n    true\n    > path = '\\\\\\\\?\\\\UNC\\\\server\\\\share';\n    > bool = RE.test( path )\n    true\n    > path = 'C:\\\\foo\\\\bar';\n    > bool = RE.test( path )\n    false\n    > path = '/c/foo/bar';\n    > bool = RE.test( path )\n    false\n    > path = '/foo/bar';\n    > bool = RE.test( path )\n    false\n\n\nreExtendedLengthPath.REGEXP\n    Regular expression to test if a string is an extended-length path.\n\n    Examples\n    --------\n    > var bool = reExtendedLengthPath.REGEXP.test( 'C:\\\\foo\\\\bar' )\n    false\n\n","reExtendedLengthPath.REGEXP":"\nreExtendedLengthPath.REGEXP\n    Regular expression to test if a string is an extended-length path.\n\n    Examples\n    --------\n    > var bool = reExtendedLengthPath.REGEXP.test( 'C:\\\\foo\\\\bar' )\n    false","reExtname":"\nreExtname( [platform] )\n    Returns a regular expression to capture a filename extension.\n\n    The regular expression is platform-dependent. If the current process is\n    running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n    `*.REGEXP_POSIX`.\n\n    Parameters\n    ----------\n    platform: string (optional)\n        Path platform (either `posix` or `win32`).\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reExtname()\n    <RegExp>\n    > var RE_POSIX = reExtname( 'posix' );\n    > var ext = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n    '.js'\n    > var RE_WIN32 = reExtname( 'win32' );\n    > ext = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    '.js'\n    > var str = RE.toString();\n    > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n    true\n\n\nreExtname.REGEXP\n    Regular expression to capture a filename extension.\n\n    Examples\n    --------\n    > var RE = reExtname.REGEXP\n    <RegExp>\n\n\nreExtname.REGEXP_POSIX\n    Regular expression to capture a POSIX filename extension.\n\n    Examples\n    --------\n    > var ext = reExtname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n    '.js'\n\n\nreExtname.REGEXP_WIN32\n    Regular expression to capture a Windows filename extension.\n\n    Examples\n    --------\n    > var ext = reExtname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    '.js'\n\n    See Also\n    --------\n    reExtnamePosix, reExtnameWindows, extname\n","reExtname.REGEXP":"\nreExtname.REGEXP\n    Regular expression to capture a filename extension.\n\n    Examples\n    --------\n    > var RE = reExtname.REGEXP\n    <RegExp>","reExtname.REGEXP_POSIX":"\nreExtname.REGEXP_POSIX\n    Regular expression to capture a POSIX filename extension.\n\n    Examples\n    --------\n    > var ext = reExtname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n    '.js'","reExtname.REGEXP_WIN32":"\nreExtname.REGEXP_WIN32\n    Regular expression to capture a Windows filename extension.\n\n    Examples\n    --------\n    > var ext = reExtname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    '.js'\n\n    See Also\n    --------\n    reExtnamePosix, reExtnameWindows, extname","reExtnamePosix":"\nreExtnamePosix\n    Returns a regular expression to capture a POSIX filename extension.\n\n    When executed against dotfile filenames (e.g., `.gitignore`), the regular\n    expression does not capture the basename as a filename extension.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reExtnamePosix();\n    > var ext = RE.exec( '/foo/bar/index.js' )[ 1 ]\n    '.js'\n    > ext = RE.exec( './foo/bar/.gitignore' )[ 1 ]\n    ''\n    > ext = RE.exec( 'foo/file.pdf' )[ 1 ]\n    '.pdf'\n    > ext = RE.exec( '/foo/bar/file' )[ 1 ]\n    ''\n    > ext = RE.exec( 'index.js' )[ 1 ]\n    '.js'\n    > ext = RE.exec( '.' )[ 1 ]\n    ''\n    > ext = RE.exec( './' )[ 1 ]\n    ''\n    > ext = RE.exec( '' )[ 1 ]\n    ''\n\n\nreExtnamePosix.REGEXP\n    Regular expression to capture a POSIX filename extension.\n\n    Examples\n    --------\n    > var ext = reExtnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n    '.js'\n\n    See Also\n    --------\n    reExtname, reExtnameWindows, extname\n","reExtnamePosix.REGEXP":"\nreExtnamePosix.REGEXP\n    Regular expression to capture a POSIX filename extension.\n\n    Examples\n    --------\n    > var ext = reExtnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n    '.js'\n\n    See Also\n    --------\n    reExtname, reExtnameWindows, extname","reExtnameWindows":"\nreExtnameWindows\n    Returns a regular expression to capture a Windows filename extension.\n\n    When executed against dotfile filenames (e.g., `.gitignore`), the regular\n    expression does not capture the basename as a filename extension.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reExtnameWindows();\n    > var ext = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    '.js'\n    > ext = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n    ''\n    > ext = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\n    '.pdf'\n    > ext = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\n    ''\n    > ext = RE.exec( 'beep\\\\boop.' )[ 1 ]\n    '.'\n    > ext = RE.exec( 'index.js' )[ 1 ]\n    '.js'\n    > ext = RE.exec( '' )[ 1 ]\n    ''\n\n\nreExtnameWindows.REGEXP\n    Regular expression to capture a Windows filename extension.\n\n    Examples\n    --------\n    > var ext = reExtnameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    '.js'\n\n    See Also\n    --------\n    reExtname, reExtnamePosix, extname\n","reExtnameWindows.REGEXP":"\nreExtnameWindows.REGEXP\n    Regular expression to capture a Windows filename extension.\n\n    Examples\n    --------\n    > var ext = reExtnameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    '.js'\n\n    See Also\n    --------\n    reExtname, reExtnamePosix, extname","reFilename":"\nreFilename( [platform] )\n    Regular expression to split a filename.\n\n    The regular expression is platform-dependent. If the current process is\n    running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n    `*.REGEXP_POSIX`.\n\n    Parameters\n    ----------\n    platform: string (optional)\n        Path platform (either `posix` or `win32`).\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reFilename()\n    <RegExp>\n    > var RE_POSIX = reFilename( 'posix' );\n    > var parts = RE_POSIX.exec( '/foo/bar/index.js' ).slice()\n    <Array>\n    > var RE_WIN32 = reFilename( 'win32' );\n    > parts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n    <Array>\n    > var str = RE.toString();\n    > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n    true\n\n\nreFilename.REGEXP\n    Regular expression to split a filename.\n\n    Examples\n    --------\n    > var RE = reFilename.REGEXP\n    <RegExp>\n\n\nreFilename.REGEXP_POSIX\n    Regular expression to split a POSIX filename.\n\n    When executed, the regular expression splits a POSIX filename into the\n    following parts:\n\n    - input value\n    - root\n    - dirname\n    - basename\n    - extname\n\n    Examples\n    --------\n    > var f = '/foo/bar/index.js';\n    > var parts = reFilename.REGEXP_POSIX.exec( f ).slice()\n    [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n\n\nreFilename.REGEXP_WIN32\n    Regular expression to split a Windows filename.\n\n    When executed, the regular expression splits a Windows filename into the\n    following parts:\n\n    - input value\n    - device\n    - slash\n    - dirname\n    - basename\n    - extname\n\n    Examples\n    --------\n    > var f = 'C:\\\\foo\\\\bar\\\\index.js';\n    > var parts = reFilename.REGEXP_WIN32.exec( f ).slice()\n    [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n    See Also\n    --------\n    reFilenamePosix, reFilenameWindows\n","reFilename.REGEXP":"\nreFilename.REGEXP\n    Regular expression to split a filename.\n\n    Examples\n    --------\n    > var RE = reFilename.REGEXP\n    <RegExp>","reFilename.REGEXP_POSIX":"\nreFilename.REGEXP_POSIX\n    Regular expression to split a POSIX filename.\n\n    When executed, the regular expression splits a POSIX filename into the\n    following parts:\n\n    - input value\n    - root\n    - dirname\n    - basename\n    - extname\n\n    Examples\n    --------\n    > var f = '/foo/bar/index.js';\n    > var parts = reFilename.REGEXP_POSIX.exec( f ).slice()\n    [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]","reFilename.REGEXP_WIN32":"\nreFilename.REGEXP_WIN32\n    Regular expression to split a Windows filename.\n\n    When executed, the regular expression splits a Windows filename into the\n    following parts:\n\n    - input value\n    - device\n    - slash\n    - dirname\n    - basename\n    - extname\n\n    Examples\n    --------\n    > var f = 'C:\\\\foo\\\\bar\\\\index.js';\n    > var parts = reFilename.REGEXP_WIN32.exec( f ).slice()\n    [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n    See Also\n    --------\n    reFilenamePosix, reFilenameWindows","reFilenamePosix":"\nreFilenamePosix()\n    Returns a regular expression to split a POSIX filename.\n\n    When executed, the regular expression splits a POSIX filename into the\n    following parts:\n\n    - input value\n    - root\n    - dirname\n    - basename\n    - extname\n\n    When executed against dotfile filenames (e.g., `.gitignore`), the regular\n    expression does not capture the basename as a filename extension.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reFilenamePosix();\n    > var parts = RE.exec( '/foo/bar/index.js' ).slice()\n    [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n    > parts = RE.exec( './foo/bar/.gitignore' ).slice()\n    [ './foo/bar/.gitignore', '', './foo/bar/', '.gitignore', '' ]\n    > parts = RE.exec( 'foo/file.pdf' ).slice()\n    [ 'foo/file.pdf', '', 'foo/', 'file.pdf', '.pdf' ]\n    > parts = RE.exec( '/foo/bar/file' ).slice()\n    [ '/foo/bar/file', '/', 'foo/bar/', 'file', '' ]\n    > parts = RE.exec( 'index.js' ).slice()\n    [ 'index.js', '', '', 'index.js', '.js' ]\n    > parts = RE.exec( '.' ).slice()\n    [ '.', '', '', '.', '' ]\n    > parts = RE.exec( './' ).slice()\n    [ './', '', ..., '.', '' ]\n    > parts = RE.exec( '' ).slice()\n    [ '', '', '', '', '' ]\n\n\nreFilenamePosix.REGEXP\n    Regular expression to split a POSIX filename.\n\n    Examples\n    --------\n    > var parts = reFilenamePosix.REGEXP.exec( '/foo/bar/index.js' ).slice()\n    [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n\n    See Also\n    --------\n    reFilename, reFilenameWindows\n","reFilenamePosix.REGEXP":"\nreFilenamePosix.REGEXP\n    Regular expression to split a POSIX filename.\n\n    Examples\n    --------\n    > var parts = reFilenamePosix.REGEXP.exec( '/foo/bar/index.js' ).slice()\n    [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n\n    See Also\n    --------\n    reFilename, reFilenameWindows","reFilenameWindows":"\nreFilenameWindows()\n    Returns a regular expression to split a Windows filename.\n\n    When executed, the regular expression splits a Windows filename into the\n    following parts:\n\n    - input value\n    - device\n    - slash\n    - dirname\n    - basename\n    - extname\n\n    When executed against dotfile filenames (e.g., `.gitignore`), the regular\n    expression does not capture the basename as a filename extension.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reFilenameWindows();\n    > var parts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n    [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n    > parts = RE.exec( '\\\\foo\\\\bar\\\\.gitignore' ).slice()\n    [ '\\\\foo\\\\bar\\\\.gitignore', '', '\\\\', 'foo\\\\bar\\\\', '.gitignore', '' ]\n    > parts = RE.exec( 'foo\\\\file.pdf' ).slice()\n    [ 'foo\\\\file.pdf', '', '', 'foo\\\\', 'file.pdf', '.pdf' ]\n    > parts = RE.exec( '\\\\foo\\\\bar\\\\file' ).slice()\n    [ '\\\\foo\\\\bar\\\\file', '', '\\\\', 'foo\\\\bar\\\\', 'file', '' ]\n    > parts = RE.exec( 'index.js' ).slice()\n    [ 'index.js', '', '', '', 'index.js', '.js' ]\n    > parts = RE.exec( '.' ).slice()\n    [ '.', '', '', '', '.', '' ]\n    > parts = RE.exec( './' ).slice()\n    [ './', '', ..., '.', '' ]\n    > parts = RE.exec( '' ).slice()\n    [ '', '', '', '', '', '' ]\n\n\nreFilenameWindows.REGEXP\n    Regular expression to split a Windows filename.\n\n    Examples\n    --------\n    > var parts = reFilenameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n    [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n    See Also\n    --------\n    reFilename, reFilenamePosix","reFilenameWindows.REGEXP":"\nreFilenameWindows.REGEXP\n    Regular expression to split a Windows filename.\n\n    Examples\n    --------\n    > var parts = reFilenameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n    [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n    See Also\n    --------\n    reFilename, reFilenamePosix","reFromString":"\nreFromString( str )\n    Parses a regular expression string and returns a new regular expression.\n\n    Provided strings should be properly escaped.\n\n    If unable to parse a string as a regular expression, the function returns\n    `null`.\n\n    Parameters\n    ----------\n    str: string\n        Regular expression string.\n\n    Returns\n    -------\n    out: RegExp|null\n        Regular expression or null.\n\n    Examples\n    --------\n    > var re = reFromString( '/beep/' )\n    /beep/\n    > re = reFromString( '/beep' )\n    null\n\n","reFunctionName":"\nreFunctionName()\n    Return a regular expression to capture a function name.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE_FUNCTION_NAME = reFunctionName();\n    > function beep() { return 'boop'; };\n    > var name = RE_FUNCTION_NAME.exec( beep.toString() )[ 1 ]\n    'beep'\n    > name = RE_FUNCTION_NAME.exec( function () {} )[ 1 ]\n    ''\n\n\nreFunctionName.REGEXP\n    Regular expression to capture a function name.\n\n    Examples\n    --------\n    > var str = reFunctionName.REGEXP.exec( Math.sqrt.toString() )[ 1 ]\n    'sqrt'\n\n    See Also\n    --------\n    functionName\n","reFunctionName.REGEXP":"\nreFunctionName.REGEXP\n    Regular expression to capture a function name.\n\n    Examples\n    --------\n    > var str = reFunctionName.REGEXP.exec( Math.sqrt.toString() )[ 1 ]\n    'sqrt'\n\n    See Also\n    --------\n    functionName","regexp2json":"\nregexp2json( re )\n    Returns a JSON representation of a regular expression.\n\n    Parameters\n    ----------\n    re: RegExp\n        Regular expression to serialize.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n        \n    out.type: string\n        Value type. The assigned value is always 'RegExp'.\n        \n    out.pattern: string\n        Regular expression pattern.\n        \n    out.flags: string\n        Regular expression flags.\n\n    Examples\n    --------\n    > var json = regexp2json( /ab+c/ )\n    {...}\n\n    See Also\n    --------\n    reviveRegExp    \n","reim":"\nreim( z )\n    Returns the real and imaginary components of a double-precision complex\n    floating-point number.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Float64Array\n        Array containing the real and imaginary components, respectively.\n\n    Examples\n    --------\n    > var z = new Complex128( 5.0, 3.0 );\n    > var out = reim( z )\n    <Float64Array>[ 5.0, 3.0 ]\n\n    See Also\n    --------\n    imag, real\n","reimf":"\nreimf( z )\n    Returns the real and imaginary components of a single-precision complex\n    floating-point number.\n\n    Parameters\n    ----------\n    z: Complex64\n        Complex number.\n\n    Returns\n    -------\n    out: Float32Array\n        Array containing the real and imaginary components, respectively.\n\n    Examples\n    --------\n    > var z = new Complex64( 5.0, 3.0 );\n    > var out = reimf( z )\n    <Float32Array>[ 5.0, 3.0 ]\n\n    See Also\n    --------\n    imagf, realf, reim\n","rejectArguments":"\nrejectArguments( fcn, predicate[, thisArg] )\n    Returns a function that applies arguments to a provided function according\n    to a predicate function.\n\n    Only those arguments in which the predicate function returns a falsy value\n    are applied to a provided function.\n\n    The predicate function is provided the following arguments:\n\n    - value: argument value.\n    - index: argument index.\n\n    Parameters\n    ----------\n    fcn: Function\n        Input function.\n\n    predicate: Function\n        Predicate function.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Function\n        Function wrapper.\n\n    Examples\n    --------\n    > function foo( a, b ) { return [ a, b ]; };\n    > function predicate( v ) { return ( v === 2 ); };\n    > var bar = rejectArguments( foo, predicate );\n    > var out = bar( 1, 2, 3 )\n    [ 1, 3 ]\n\n    See Also\n    --------\n    filterArguments, maskArguments\n","removeFirst":"\nremoveFirst( str[, n][, options] )\n    Removes the first character(s) of a `string`.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer (optional)\n        Number of characters to remove. Default: 1.\n\n    options: Object (optional)\n        Options.\n\n    options.mode: string (optional)\n        Type of characters to return. The following modes are supported:\n\n        - grapheme: grapheme clusters. Appropriate for strings containing visual\n          characters which can span multiple Unicode code points (e.g., emoji).\n        - code_point: Unicode code points. Appropriate for strings containing\n          visual characters which are comprised of more than one Unicode code\n          unit (e.g., ideographic symbols and punctuation and mathematical\n          alphanumerics).\n        - code_unit': UTF-16 code units. Appropriate for strings containing\n          visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n          common characters, such as those from the Latin, Greek, and Cyrillic\n          alphabets).\n\n        Default: 'grapheme'.\n\n    Returns\n    -------\n    out: string\n        Updated string.\n\n    Examples\n    --------\n    > var out = removeFirst( 'beep' )\n    'eep'\n    > out = removeFirst( 'Boop' )\n    'oop'\n    > out = removeFirst( 'foo bar', 4 )\n    'bar'\n\n    See Also\n    --------\n    removeLast\n","removeLast":"\nremoveLast( str[, n][, options] )\n    Removes the last character(s) of a `string`.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer (optional)\n        Number of characters to remove. Default: 1.\n\n    options: Object (optional)\n        Options.\n\n    options.mode: string (optional)\n        Type of characters to remove. The following modes are supported:\n\n        - grapheme: grapheme clusters. Appropriate for strings containing visual\n          characters which can span multiple Unicode code points (e.g., emoji).\n        - code_point: Unicode code points. Appropriate for strings containing\n          visual characters which are comprised of more than one Unicode code\n          unit (e.g., ideographic symbols and punctuation and mathematical\n          alphanumerics).\n        - code_unit': UTF-16 code units. Appropriate for strings containing\n          visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n          common characters, such as those from the Latin, Greek, and Cyrillic\n          alphabets).\n\n        Default: 'grapheme'.\n\n    Returns\n    -------\n    out: string\n        Updated string.\n\n    Examples\n    --------\n    > var out = removeLast( 'beep' )\n    'bee'\n    > out = removeLast( 'Boop' )\n    'Boo'\n    > out = removeLast( 'foo bar', 4 )\n    'foo'\n\n    See Also\n    --------\n    removeFirst\n","removePunctuation":"\nremovePunctuation( str )\n    Removes punctuation characters from a `string`.\n\n    The function removes the following characters:\n\n    - Apostrophe: `\n    - Braces : { }\n    - Brackets: [ ]\n    - Colon: :\n    - Comma: ,\n    - Exclamation Mark: !\n    - Fraction Slash: /\n    - Guillemets: < >\n    - Parentheses: ( )\n    - Period: .\n    - Semicolon: ;\n    - Tilde: ~\n    - Vertical Bar: |\n    - Question Mark: ?\n    - Quotation Marks: ' \"\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        String with punctuation characters removed.\n\n    Examples\n    --------\n    > var str = 'Sun Tzu said: \"A leader leads by example not by force.\"';\n    > var out = removePunctuation( str )\n    'Sun Tzu said A leader leads by example not by force'\n\n    > str = 'This function removes these characters: `{}[]:,!/<>().;~|?\\'\"';\n    > out = removePunctuation( str )\n    'This function removes these characters '\n\n","removeUTF8BOM":"\nremoveUTF8BOM( str )\n    Removes a UTF-8 byte order mark (BOM) from the beginning of a `string`.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        String with BOM removed.\n\n    Examples\n    --------\n    > var out = removeUTF8BOM( '\\ufeffbeep' )\n    'beep'\n\n","removeWords":"\nremoveWords( str, words[, ignoreCase] )\n    Removes all occurrences of the given words from a `string`.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    words: Array<string>\n        Array of words to be removed.\n\n    ignoreCase: boolean (optional)\n        Boolean indicating whether to perform a case-insensitive operation.\n        Default: `false`.\n\n    Returns\n    -------\n    out: string\n        String with words removed.\n\n    Examples\n    --------\n    > var out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ] )\n    'beep  Foo bar'\n\n    // Case-insensitive:\n    > out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ], true )\n    'beep   bar'\n\n","rename":"\nrename( oldPath, newPath, clbk )\n    Asynchronously renames a file.\n\n    The old path can specify a directory. In this case, the new path must either\n    not exist, or it must specify an empty directory.\n\n    The old pathname should not name an ancestor directory of the new pathname.\n\n    If the old path points to the pathname of a file that is not a directory,\n    the new path should not point to the pathname of a directory.\n\n    Write access permission is required for both the directory containing the\n    old path and the directory containing the new path.\n\n    If the link named by the new path exists, the new path is removed and the\n    old path is renamed to the new path. The link named by the new path will\n    remain visible to other threads throughout the renaming operation and refer\n    to either the file referred to by the new path or to the file referred to by\n    the old path before the operation began.\n\n    If the old path and the new path resolve to either the same existing\n    directory entry or to different directory entries for the same existing\n    file, no action is taken, and no error is returned.\n\n    If the old path points to a pathname of a symbolic link, the symbolic link\n    is renamed. If the new path points to a pathname of a symbolic link, the\n    symbolic link is removed.\n\n    If a link named by the new path exists and the file's link count becomes 0\n    when it is removed and no process has the file open, the space occupied by\n    the file is freed and the file is no longer accessible. If one or more\n    processes have the file open when the last link is removed, the link is\n    removed before the function returns, but the removal of file contents is\n    postponed until all references to the file are closed.\n\n    Parameters\n    ----------\n    oldPath: string|Buffer\n        Old path.\n\n    newPath: string|Buffer\n        New path.\n\n    clbk: Function\n        Callback to invoke upon renaming a file.\n\n    Examples\n    --------\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     }\n    ... };\n    > rename( './beep/boop.txt', './beep/foo.txt', done );\n\n\nrename.sync( oldPath, newPath )\n    Synchronously renames a file.\n\n    Parameters\n    ----------\n    oldPath: string|Buffer\n        Old path.\n\n    newPath: string|Buffer\n        New path.\n\n    Returns\n    -------\n    err: Error|null\n        Error object or null.\n\n    Examples\n    --------\n    > var err = rename.sync( './beep/boop.txt', './beep/foo.txt' );\n\n    See Also\n    --------\n    exists, readFile, writeFile, unlink\n","rename.sync":"\nrename.sync( oldPath, newPath )\n    Synchronously renames a file.\n\n    Parameters\n    ----------\n    oldPath: string|Buffer\n        Old path.\n\n    newPath: string|Buffer\n        New path.\n\n    Returns\n    -------\n    err: Error|null\n        Error object or null.\n\n    Examples\n    --------\n    > var err = rename.sync( './beep/boop.txt', './beep/foo.txt' );\n\n    See Also\n    --------\n    exists, readFile, writeFile, unlink","reNativeFunction":"\nreNativeFunction()\n    Returns a regular expression to match a native function.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reNativeFunction();\n    > var bool = RE.test( Date.toString() )\n    true\n    > bool = RE.test( (function noop() {}).toString() )\n    false\n\n\nreNativeFunction.REGEXP\n    Regular expression to match a native function.\n\n    Examples\n    --------\n    > var bool = reNativeFunction.REGEXP.test( Date.toString() )\n    true\n    > bool = reNativeFunction.REGEXP.test( (function noop() {}).toString() )\n    false\n\n    See Also\n    --------\n    reFunctionName, functionName\n","reNativeFunction.REGEXP":"\nreNativeFunction.REGEXP\n    Regular expression to match a native function.\n\n    Examples\n    --------\n    > var bool = reNativeFunction.REGEXP.test( Date.toString() )\n    true\n    > bool = reNativeFunction.REGEXP.test( (function noop() {}).toString() )\n    false\n\n    See Also\n    --------\n    reFunctionName, functionName","reorderArguments":"\nreorderArguments( fcn, indices[, thisArg] )\n    Returns a function that invokes a provided function with reordered\n    arguments.\n\n    Parameters\n    ----------\n    fcn: Function\n        Input function.\n\n    indices: Array<integer>\n        Argument indices.\n\n    thisArg: any (optional)\n        Function context.\n\n    Returns\n    -------\n    out: Function\n        Function with reordered arguments.\n\n    Examples\n    --------\n    > function foo( a, b, c ) { return [ a, b, c ]; };\n    > var bar = reorderArguments( foo, [ 2, 0, 1 ] );\n    > var out = bar( 1, 2, 3 )\n    [ 3, 1, 2 ]\n\n    See Also\n    --------\n    maskArguments, reverseArguments\n","repeat":"\nrepeat( str, n )\n    Repeats a string `n` times and returns the concatenated result.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of repetitions.\n\n    Returns\n    -------\n    out: string\n        Repeated string.\n\n    Examples\n    --------\n    > var out = repeat( 'a', 5 )\n    'aaaaa'\n    > out = repeat( '', 100 )\n    ''\n    > out = repeat( 'beep', 0 )\n    ''\n\n    See Also\n    --------\n    pad\n","replace":"\nreplace( str, search, newval )\n    Replaces search occurrences with a replacement string.\n\n    When provided a string as the search value, the function replaces *all*\n    occurrences. To remove only the first match, use a regular expression.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string|RegExp\n        Search expression.\n\n    newval: string|Function\n        Replacement value or function.\n\n    Returns\n    -------\n    out: string\n        String containing replacement(s).\n\n    Examples\n    --------\n    // Standard usage:\n    > var out = replace( 'beep', 'e', 'o' )\n    'boop'\n\n    // Replacer function:\n    > function replacer( match, p1 ) { return '/'+p1+'/'; };\n    > var str = 'Oranges and lemons';\n    > out = replace( str, /([^\\s]+)/gi, replacer )\n    '/Oranges/ /and/ /lemons/'\n\n    // Replace only first match:\n    > out = replace( 'beep', /e/, 'o' )\n    'boep'\n\n","replaceBefore":"\nreplaceBefore( str, search, replacement )\n    Replaces the substring before the first occurrence of a specified search\n    string. \n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search string.\n    \n    replacement: string\n        Replacement string.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var str = 'beep boop';\n    > var out = replaceBefore( str, ' ', 'foo' )\n    'foo boop'\n    > out = replaceBefore( str, 'o', 'foo' )\n    'foooop'\n\n","reRegExp":"\nreRegExp()\n    Returns a regular expression to parse a regular expression string.\n\n    Regular expression strings should be escaped.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reRegExp();\n    > var bool = RE.test( '/^beep$/' )\n    true\n    > bool = RE.test( '/boop' )\n    false\n\n    // Escape regular expression strings:\n    > bool = RE.test( '/^\\/([^\\/]+)\\/(.*)$/' )\n    false\n    > bool = RE.test( '/^\\\\/([^\\\\/]+)\\\\/(.*)$/' )\n    true\n\n\nreRegExp.REGEXP\n    Regular expression to parse a regular expression string.\n\n    Examples\n    --------\n    > var bool = reRegExp.REGEXP.test( '/^beep$/' )\n    true\n    > bool = reRegExp.REGEXP.test( '/boop' )\n    false\n\n    See Also\n    --------\n    reFromString\n","reRegExp.REGEXP":"\nreRegExp.REGEXP\n    Regular expression to parse a regular expression string.\n\n    Examples\n    --------\n    > var bool = reRegExp.REGEXP.test( '/^beep$/' )\n    true\n    > bool = reRegExp.REGEXP.test( '/boop' )\n    false\n\n    See Also\n    --------\n    reFromString","rescape":"\nrescape( str )\n    Escapes a regular expression string.\n\n    Parameters\n    ----------\n    str: string\n        Regular expression string.\n\n    Returns\n    -------\n    out: string\n        Escaped string.\n\n    Examples\n    --------\n    > var str = rescape( '[A-Z]*' )\n    '\\\\[A\\\\-Z\\\\]\\\\*'\n\n","reSemVer":"\nreSemVer()\n    Returns a regular expression to match a semantic version string.\n\n    Returns\n    -------\n    out: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE_SEMVER = reSemVer()\n    <RegExp>\n    > var bool = RE_SEMVER.test( '1.0.0' )\n    true\n    > bool = RE_SEMVER.test( '1.0.0-alpha.1' )\n    true\n    > bool = RE_SEMVER.test( 'abc' )\n    false\n    > bool = RE_SEMVER.test( '1.0.0-alpha.1+build.1' )\n    true\n\n\nreSemVer.REGEXP\n    Regular expression to match a semantic version string.\n\n    Examples\n    --------\n    > var bool = reSemVer.REGEXP.test( '1.0.0' )\n    true\n    > bool = reSemVer.REGEXP.test( '-1.0.0-alpha.1' )\n    false\n\n\n    See Also\n    --------\n    isSemVer","reSemVer.REGEXP":"\nreSemVer.REGEXP\n    Regular expression to match a semantic version string.\n\n    Examples\n    --------\n    > var bool = reSemVer.REGEXP.test( '1.0.0' )\n    true\n    > bool = reSemVer.REGEXP.test( '-1.0.0-alpha.1' )\n    false\n\n\n    See Also\n    --------\n    isSemVer","resolveParentPath":"\nresolveParentPath( path[, options], clbk )\n    Asynchronously resolves a path by walking parent directories.\n\n    If unable to resolve a path, the function returns `null` as the path result.\n\n    Parameters\n    ----------\n    path: string\n        Path to resolve.\n\n    options: Object (optional)\n        Options.\n\n    options.dir: string (optional)\n        Base directory from which to search. Default: current working directory.\n\n    clbk: Function\n        Callback to invoke after resolving a path.\n\n    Examples\n    --------\n    > function onPath( error, path ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     } else {\n    ...         console.log( path );\n    ...     }\n    ... };\n    > resolveParentPath( 'package.json', onPath );\n\n\nresolveParentPath.sync( path[, options] )\n    Synchronously resolves a path by walking parent directories.\n\n    Parameters\n    ----------\n    path: string\n        Path to resolve.\n\n    options: Object (optional)\n        Options.\n\n    options.dir: string (optional)\n        Base directory from which to search. Default: current working directory.\n\n    Returns\n    -------\n    out: string|null\n        Resolved path.\n\n    Examples\n    --------\n    > var out = resolveParentPath.sync( 'package.json' );\n\n    See Also\n    --------\n    resolveParentPathBy\n","resolveParentPath.sync":"\nresolveParentPath.sync( path[, options] )\n    Synchronously resolves a path by walking parent directories.\n\n    Parameters\n    ----------\n    path: string\n        Path to resolve.\n\n    options: Object (optional)\n        Options.\n\n    options.dir: string (optional)\n        Base directory from which to search. Default: current working directory.\n\n    Returns\n    -------\n    out: string|null\n        Resolved path.\n\n    Examples\n    --------\n    > var out = resolveParentPath.sync( 'package.json' );\n\n    See Also\n    --------\n    resolveParentPathBy","resolveParentPathBy":"\nresolveParentPathBy( path[, options], predicate, clbk )\n    Asynchronously resolves a path according to a predicate function by walking\n    parent directories.\n\n    When invoked, the predicate function is provided two arguments:\n\n    - path: a resolved path.\n    - next: a callback to be invoked after processing a resolved path.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - result: test result.\n\n    If a provided predicate function calls the `next` callback with a truthy\n    `error` argument, the function suspends execution and immediately calls the\n    `done` callback for subsequent `error` handling.\n\n    The function immediately returns upon encountering a non-falsy `result`\n    value and calls the `done` callback with `null` as the first argument and\n    the resolved path as the second argument.\n\n    If unable to resolve a path, the function returns `null` as the path result.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Parameters\n    ----------\n    path: string\n        Path to resolve.\n\n    options: Object (optional)\n        Options.\n\n    options.dir: string (optional)\n        Base directory from which to search. Default: current working directory.\n\n    predicate: Function\n        The test function to invoke for each resolved path.\n\n    clbk: Function\n        Callback to invoke after resolving a path.\n\n    Examples\n    --------\n    > function predicate( path, next ) {\n    ...     setTimeout( onTimeout, path );\n    ...     function onTimeout() {\n    ...         console.log( path );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function onPath( error, path ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     } else {\n    ...         console.log( path );\n    ...     }\n    ... };\n    > resolveParentPathBy( 'package.json', predicate, onPath );\n\n\nresolveParentPathBy.sync( path[, options], predicate )\n    Synchronously resolves a path according to a predicate function by walking\n    parent directories.\n\n    The predicate function is provided one argument:\n\n    - path: a resolved path.\n\n    The function immediately returns upon encountering a truthy return value.\n\n    If unable to resolve a path, the function returns `null` as the path result.\n\n    Parameters\n    ----------\n    path: string\n        Path to resolve.\n\n    options: Object (optional)\n        Options.\n\n    options.dir: string (optional)\n        Base directory from which to search. Default: current working directory.\n\n    predicate: Function\n        The test function to invoke for each resolved path.\n\n    Returns\n    -------\n    out: string|null\n        Resolved path.\n\n    Examples\n    --------\n    > function predicate() { return false; };\n    > var out = resolveParentPathBy.sync( 'package.json', predicate );\n\n    See Also\n    --------\n    resolveParentPath\n","resolveParentPathBy.sync":"\nresolveParentPathBy.sync( path[, options], predicate )\n    Synchronously resolves a path according to a predicate function by walking\n    parent directories.\n\n    The predicate function is provided one argument:\n\n    - path: a resolved path.\n\n    The function immediately returns upon encountering a truthy return value.\n\n    If unable to resolve a path, the function returns `null` as the path result.\n\n    Parameters\n    ----------\n    path: string\n        Path to resolve.\n\n    options: Object (optional)\n        Options.\n\n    options.dir: string (optional)\n        Base directory from which to search. Default: current working directory.\n\n    predicate: Function\n        The test function to invoke for each resolved path.\n\n    Returns\n    -------\n    out: string|null\n        Resolved path.\n\n    Examples\n    --------\n    > function predicate() { return false; };\n    > var out = resolveParentPathBy.sync( 'package.json', predicate );\n\n    See Also\n    --------\n    resolveParentPath","reUncPath":"\nreUncPath()\n    Return a regular expression to parse a UNC path.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reUncPath();\n    > var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\n    > var bool = RE.test( path )\n    true\n    > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\n    > bool = RE.test( path )\n    true\n    > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a';\n    > bool = RE.test( path )\n    true\n    > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz';\n    > bool = RE.test( path )\n    true\n    > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar';\n    > bool = RE.test( path )\n    true\n    > path = '\\\\\\\\server\\\\share\\\\foo';\n    > bool = RE.test( path )\n    true\n    > path = '\\\\\\\\server\\\\share';\n    > bool = RE.test( path )\n    true\n    > path = '\\\\\\\\server\\\\\\\\share';\n    > bool = RE.test( path )\n    false\n    > path = '\\\\\\\\\\\\\\\\server\\\\share';\n    > bool = RE.test( path )\n    false\n    > path = 'beep boop \\\\\\\\server\\\\share';\n    > bool = RE.test( path )\n    false\n    > path = '\\\\\\\\server';\n    > bool = RE.test( path )\n    false\n    > path = '\\\\';\n    > bool = RE.test( path )\n    false\n    > path = '';\n    > bool = RE.test( path )\n    false\n    > path = '\\\\\\\\server\\\\share\\\\';\n    > bool = RE.test( path )\n    false\n    > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:';\n    > bool = RE.test( path )\n    false\n    > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:';\n    > bool = RE.test( path )\n    false\n    > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::';\n    > bool = RE.test( path )\n    false\n    > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b:c';\n    > bool = RE.test( path )\n    false\n    > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\';\n    > bool = RE.test( path )\n    false\n    > path = '//server/share';\n    > bool = RE.test( path )\n    false\n    > path = '/foo/bar';\n    > bool = RE.test( path )\n    false\n    > path = 'foo/bar';\n    > bool = RE.test( path )\n    false\n    > path = './foo/bar';\n    > bool = RE.test( path )\n    false\n    > path = '/foo/../bar';\n    > bool = RE.test( path )\n    false\n\n\nreUncPath.REGEXP\n    Regular expression to parse a UNC path.\n\n    Examples\n    --------\n    > var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\n    > var bool = reUncPath.REGEXP.test( path )\n    true\n    > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\n    > bool = reUncPath.REGEXP.test( path )\n    true\n\n    See Also\n    --------\n    isUNCPath\n","reUncPath.REGEXP":"\nreUncPath.REGEXP\n    Regular expression to parse a UNC path.\n\n    Examples\n    --------\n    > var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\n    > var bool = reUncPath.REGEXP.test( path )\n    true\n    > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\n    > bool = reUncPath.REGEXP.test( path )\n    true\n\n    See Also\n    --------\n    isUNCPath","reUtf16SurrogatePair":"\nreUtf16SurrogatePair()\n    Returns a regular expression to match a UTF-16 surrogate pair.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reUtf16SurrogatePair();\n    > var bool = RE.test( 'abc\\uD800\\uDC00def' )\n    true\n    > bool = RE.test( 'abcdef' )\n    false\n\n\nreUtf16SurrogatePair.REGEXP\n    Regular expression to match a UTF-16 surrogate pair.\n\n    Examples\n    --------\n    > var RE = reUtf16SurrogatePair.REGEXP;\n    > var bool = RE.test( 'abc\\uD800\\uDC00def' )\n    true\n    > bool = RE.test( 'abcdef' )\n    false\n\n    See Also\n    --------\n    reUtf16UnpairedSurrogate","reUtf16SurrogatePair.REGEXP":"\nreUtf16SurrogatePair.REGEXP\n    Regular expression to match a UTF-16 surrogate pair.\n\n    Examples\n    --------\n    > var RE = reUtf16SurrogatePair.REGEXP;\n    > var bool = RE.test( 'abc\\uD800\\uDC00def' )\n    true\n    > bool = RE.test( 'abcdef' )\n    false\n\n    See Also\n    --------\n    reUtf16UnpairedSurrogate","reUtf16UnpairedSurrogate":"\nreUtf16UnpairedSurrogate()\n    Returns a regular expression to match an unpaired UTF-16 surrogate.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reUtf16UnpairedSurrogate();\n    > var bool = RE.test( 'abc' )\n    false\n    > bool = RE.test( '\\uD800' )\n    true\n\n\nreUtf16UnpairedSurrogate.REGEXP\n    Regular expression to match an unpaired UTF-16 surrogate.\n\n    Examples\n    --------\n    > var RE = reUtf16UnpairedSurrogate.REGEXP;\n    > var bool = RE.test( 'abc' )\n    false\n    > bool = RE.test( '\\uD800' )\n    true\n\n    See Also\n    --------\n    reUtf16SurrogatePair","reUtf16UnpairedSurrogate.REGEXP":"\nreUtf16UnpairedSurrogate.REGEXP\n    Regular expression to match an unpaired UTF-16 surrogate.\n\n    Examples\n    --------\n    > var RE = reUtf16UnpairedSurrogate.REGEXP;\n    > var bool = RE.test( 'abc' )\n    false\n    > bool = RE.test( '\\uD800' )\n    true\n\n    See Also\n    --------\n    reUtf16SurrogatePair","reverseArguments":"\nreverseArguments( fcn[, thisArg] )\n    Returns a function that invokes a provided function with arguments in\n    reverse order.\n\n    Parameters\n    ----------\n    fcn: Function\n        Input function.\n\n    thisArg: any (optional)\n        Function context.\n\n    Returns\n    -------\n    out: Function\n        Function with reversed arguments.\n\n    Examples\n    --------\n    > function foo( a, b, c ) { return [ a, b, c ]; };\n    > var bar = reverseArguments( foo );\n    > var out = bar( 1, 2, 3 )\n    [ 3, 2, 1 ]\n\n    See Also\n    --------\n    maskArguments, reorderArguments\n","reverseString":"\nreverseString( str[, options] )\n    Reverses a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    options: Object (optional)\n        Options.\n\n    options.mode: string (optional)\n        Type of characters to reverse. The following modes are supported:\n\n        - grapheme: grapheme clusters. Appropriate for strings containing visual\n          characters which can span multiple Unicode code points (e.g., emoji).\n        - code_point: Unicode code points. Appropriate for strings containing\n          visual characters which are comprised of more than one Unicode code\n          unit (e.g., ideographic symbols and punctuation and mathematical\n          alphanumerics).\n        - code_unit': UTF-16 code units. Appropriate for strings containing\n          visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n          common characters, such as those from the Latin, Greek, and Cyrillic\n          alphabets).\n\n        Default: 'grapheme'.\n\n    Returns\n    -------\n    out: string\n        Reversed string.\n\n    Examples\n    --------\n    > var out = reverseString( 'foo' )\n    'oof'\n    > out = reverseString( 'abcdef' )\n    'fedcba'\n\n","reviveBasePRNG":"\nreviveBasePRNG( key, value )\n    Revives a JSON-serialized pseudorandom number generator (PRNG).\n\n    Parameters\n    ----------\n    key: string\n        Key.\n\n    value: any\n        Value.\n\n    Returns\n    -------\n    out: any\n        Value or PRNG.\n\n    Examples\n    --------\n    > var str = JSON.stringify( base.random.mt19937 );\n    > var r = parseJSON( str, reviveBasePRNG )\n    <Function>\n\n","reviveBuffer":"\nreviveBuffer( key, value )\n    Revives a JSON-serialized Buffer.\n\n    The serialization format for a Buffer is an object having the following\n    fields:\n\n    - type: value type (Buffer).\n    - data: buffer data as an array of integers.\n\n    Parameters\n    ----------\n    key: string\n        Key.\n\n    value: any\n        Value.\n\n    Returns\n    -------\n    out: any\n        Value or Buffer.\n\n    Examples\n    --------\n    > var str = '{\"type\":\"Buffer\",\"data\":[5,3]}';\n    > var buf = parseJSON( str, reviveBuffer )\n    <Buffer>[ 5, 3 ]\n\n    See Also\n    --------\n    buffer2json\n","reviveComplex":"\nreviveComplex( key, value )\n    Revives a JSON-serialized complex number.\n\n    The serialization format for complex numbers is an object having the\n    following fields:\n\n    - type: complex number type (e.g., \"Complex128\", \"Complex64\").\n    - re: real component (number).\n    - im: imaginary component (number).\n\n    Parameters\n    ----------\n    key: string\n        Key.\n\n    value: any\n        Value.\n\n    Returns\n    -------\n    out: any\n        Value or complex number.\n\n    Examples\n    --------\n    > var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\n    > var z = parseJSON( str, reviveComplex )\n    <Complex128>\n\n    See Also\n    --------\n    Complex128, Complex64, reviveComplex128, reviveComplex64\n","reviveComplex64":"\nreviveComplex64( key, value )\n    Revives a JSON-serialized 64-bit complex number.\n\n    Parameters\n    ----------\n    key: string\n        Key.\n\n    value: any\n        Value.\n\n    Returns\n    -------\n    out: any\n        Value or complex number.\n\n    Examples\n    --------\n    > var str = '{\"type\":\"Complex64\",\"re\":5,\"im\":3}';\n    > var z = parseJSON( str, reviveComplex64 )\n    <Complex64>\n\n    See Also\n    --------\n    Complex64, reviveComplex128, reviveComplex\n","reviveComplex128":"\nreviveComplex128( key, value )\n    Revives a JSON-serialized 128-bit complex number.\n\n    Parameters\n    ----------\n    key: string\n        Key.\n\n    value: any\n        Value.\n\n    Returns\n    -------\n    out: any\n        Value or complex number.\n\n    Examples\n    --------\n    > var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\n    > var z = parseJSON( str, reviveComplex128 )\n    <Complex128>\n\n    See Also\n    --------\n    Complex128, reviveComplex64, reviveComplex\n","reviveError":"\nreviveError( key, value )\n    Revives a JSON-serialized error object.\n\n    The following built-in error types are supported:\n\n    - Error\n    - URIError\n    - ReferenceError\n    - SyntaxError\n    - RangeError\n    - EvalError\n    - TypeError\n\n    Parameters\n    ----------\n    key: string\n        Key.\n\n    value: any\n        Value.\n\n    Returns\n    -------\n    out: any\n        Value or error object.\n\n    Examples\n    --------\n    > var str = '{\"type\":\"TypeError\",\"message\":\"beep\"}';\n    > var err = JSON.parse( str, reviveError )\n    <TypeError>\n\n    See Also\n    --------\n    error2json\n","reviveRegExp":"\nreviveRegExp( key, value )\n    Revives a JSON-serialized regular expression.\n\n    The serialization format for a regular expression is an object having the\n    following fields:\n\n    - type: value type (RegExp).\n    - pattern: regular expression pattern.\n    - flags: regular expression flags.\n\n    Parameters\n    ----------\n    key: string\n        Key.\n\n    value: any\n        Value.\n\n    Returns\n    -------\n    out: any\n        Value or regular expression.\n\n    Examples\n    --------\n    > var str = '{\"type\":\"RegExp\",\"pattern\":\"ab+c\",\"flags\":\"\"}';\n    > var v = parseJSON( str, reviveRegExp )\n    <RegExp>\n\n    See Also\n    --------\n    regexp2json","reviveTypedArray":"\nreviveTypedArray( key, value )\n    Revives a JSON-serialized typed array.\n\n    The serialization format for typed array is an object having the following\n    fields:\n\n    - type: typed array type (e.g., \"Float64Array\", \"Int8Array\").\n    - data: typed array data as an array of numbers.\n\n    Parameters\n    ----------\n    key: string\n        Key.\n\n    value: any\n        Value.\n\n    Returns\n    -------\n    out: any\n        Value or typed array.\n\n    Examples\n    --------\n    > var str = '{\"type\":\"Float64Array\",\"data\":[5,3]}';\n    > var arr = parseJSON( str, reviveTypedArray )\n    <Float64Array>[ 5.0, 3.0 ]\n\n    See Also\n    --------\n    typedarray2json\n","reWhitespace":"\nreWhitespace( [options] )\n    Returns a regular expression to match a white space character.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.flags: string (optional)\n        Regular expression flags. Default: ''.\n\n    options.capture: boolean (optional)\n        Boolean indicating whether to wrap a regular expression matching a white\n        space character with a capture group. Default: false.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reWhitespace();\n    > var bool = RE.test( '\\n' )\n    true\n    > bool = RE.test( ' ' )\n    true\n    > bool = RE.test( 'a' )\n    false\n\n\nreWhitespace.REGEXP\n    Regular expression to match a white space character.\n\n    Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n    characters in the Unicode 9.0 character database.\n\n    Matches one related white space character without the Unicode character\n    property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n    of Unicode 3.2).\n\n    Examples\n    --------\n    > var RE = reWhitespace.REGEXP;\n    > var bool = RE.test( '\\n' )\n    true\n    > bool = RE.test( ' ' )\n    true\n    > bool = RE.test( 'a' )\n    false\n\n\nreWhitespace.REGEXP_CAPTURE\n    Regular expression to capture white space characters.\n\n    Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n    characters in the Unicode 9.0 character database.\n\n    Matches one related white space character without the Unicode character\n    property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n    of Unicode 3.2).\n\n    Examples\n    --------\n    > var RE = reWhitespace.REGEXP_CAPTURE;\n    > var str = 'Duplicate capture';\n    > var out = replace( str, RE, '$1$1' )\n    'Duplicate  capture'\n\n    See Also\n    --------\n    isWhitespace","reWhitespace.REGEXP":"\nreWhitespace.REGEXP\n    Regular expression to match a white space character.\n\n    Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n    characters in the Unicode 9.0 character database.\n\n    Matches one related white space character without the Unicode character\n    property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n    of Unicode 3.2).\n\n    Examples\n    --------\n    > var RE = reWhitespace.REGEXP;\n    > var bool = RE.test( '\\n' )\n    true\n    > bool = RE.test( ' ' )\n    true\n    > bool = RE.test( 'a' )\n    false","reWhitespace.REGEXP_CAPTURE":"\nreWhitespace.REGEXP_CAPTURE\n    Regular expression to capture white space characters.\n\n    Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n    characters in the Unicode 9.0 character database.\n\n    Matches one related white space character without the Unicode character\n    property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n    of Unicode 3.2).\n\n    Examples\n    --------\n    > var RE = reWhitespace.REGEXP_CAPTURE;\n    > var str = 'Duplicate capture';\n    > var out = replace( str, RE, '$1$1' )\n    'Duplicate  capture'\n\n    See Also\n    --------\n    isWhitespace","rpad":"\nrpad( str, len[, pad] )\n    Right pads a `string` such that the padded `string` has a length of at least\n    `len`.\n\n    An output string is not guaranteed to have a length of exactly `len`, but to\n    have a length of at least `len`. To generate a padded string having a length\n    equal to `len`, post-process a padded string by trimming off excess\n    characters.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    len: integer\n        Minimum string length.\n\n    pad: string (optional)\n        String used to pad. Default: ' '.\n\n    Returns\n    -------\n    out: string\n        Padded string.\n\n    Examples\n    --------\n    > var out = rpad( 'a', 5 )\n    'a    '\n    > out = rpad( 'beep', 10, 'p' )\n    'beeppppppp'\n    > out = rpad( 'beep', 12, 'boop' )\n    'beepboopboop'\n\n    See Also\n    --------\n    lpad, pad\n","rtrim":"\nrtrim( str )\n    Trims whitespace from the end of a string.\n\n    \"Whitespace\" is defined as the following characters:\n\n    - \\f\n    - \\n\n    - \\r\n    - \\t\n    - \\v\n    - \\u0020\n    - \\u00a0\n    - \\u1680\n    - \\u2000-\\u200a\n    - \\u2028\n    - \\u2029\n    - \\u202f\n    - \\u205f\n    - \\u3000\n    - \\ufeff\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Trimmed string.\n\n    Examples\n    --------\n    > var out = rtrim( ' \\t\\t\\n  Beep \\r\\n\\t  ' )\n    ' \\t\\t\\n  Beep'\n\n    See Also\n    --------\n    ltrim, trim\n","rtrimN":"\nrtrimN( str, n[, chars] )\n    Trims `n` characters from the end of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of characters to trim.\n\n    chars: Array<string>|string (optional)\n        Characters to trim. Default: whitespace characters.\n\n    Returns\n    -------\n    out: string\n        Trimmed string.\n\n    Examples\n    --------\n    > var out = rtrimN( '  abc  ', 2 )\n    '  abc'\n    > var out = rtrimN( '!!!abc!!!', 2, '!' )\n    '!!!abc!'\n\n    See Also\n    --------\n    ltrimN, trim","safeintmax":"\nsafeintmax( dtype )\n    Returns the maximum safe integer capable of being represented by a numeric\n    real type.\n\n    The following numeric real types are supported:\n\n    - float64: double-precision floating-point numbers.\n    - float32: single-precision floating-point numbers.\n    - float16: half-precision floating-point numbers.\n\n    Parameters\n    ----------\n    dtype: string\n        Numeric type.\n\n    Returns\n    -------\n    out: integer\n        Maximum safe integer.\n\n    Examples\n    --------\n    > var m = safeintmax( 'float16' )\n    2047\n    > m = safeintmax( 'float32' )\n    16777215\n\n    See Also\n    --------\n    safeintmin, realmax, typemax\n","safeintmin":"\nsafeintmin( dtype )\n    Returns the minimum safe integer capable of being represented by a numeric\n    real type.\n\n    The following numeric real types are supported:\n\n    - float64: double-precision floating-point numbers.\n    - float32: single-precision floating-point numbers.\n    - float16: half-precision floating-point numbers.\n\n    Parameters\n    ----------\n    dtype: string\n        Numeric type.\n\n    Returns\n    -------\n    out: integer\n        Minimum safe integer.\n\n    Examples\n    --------\n    > var m = safeintmin( 'float16' )\n    -2047\n    > m = safeintmin( 'float32' )\n    -16777215\n\n    See Also\n    --------\n    safeintmax, realmin, typemin\n","sample":"\nsample( x[, options] )\n    Samples elements from an array-like object.\n\n    Parameters\n    ----------\n    x: ArrayLike\n        Array-like object from which to sample.\n\n    options: Object (optional)\n        Options.\n\n    options.size: integer (optional)\n        Sample size. By default, the function returns an array having the same\n        length as `x`. Specify the `size` option to generate a sample of a\n        different size.\n\n    options.probs: Array<number> (optional)\n        Element probabilities. By default, the probability of sampling an\n        element is the same for all elements. To assign elements different\n        probabilities, set the `probs` option. The `probs` option must be a\n        numeric array consisting of nonnegative values which sum to one. When\n        sampling without replacement, note that the `probs` option denotes the\n        initial element probabilities which are then updated after each draw.\n\n    options.replace: boolean (optional)\n        Boolean indicating whether to sample with replacement. If the `replace`\n        option is set to `false`, the `size` option cannot be an integer larger\n        than the number of elements in `x`. Default: `true`.\n\n    Returns\n    -------\n    out: Array\n        Sample.\n\n    Examples\n    --------\n    > var out = sample( 'abc' )\n    e.g., [ 'a', 'a', 'b' ]\n    > out = sample( [ 3, 6, 9 ] )\n    e.g., [ 3, 9, 6 ]\n    > var bool = ( out.length === 3 )\n    true\n\n    > out = sample( [ 3, null, NaN, 'abc', function(){} ] )\n    e.g., [ 3, 'abc', null, 3, null ]\n\n    // Set sample size:\n    > out = sample( [ 3, 6, 9 ], { 'size': 10 } )\n    e.g., [ 6, 3, 9, 9, 9, 6, 9, 6, 9, 3 ]\n    > out = sample( [ 0, 1 ], { 'size': 20 } )\n    e.g., [ 0, 0, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 0 ]\n\n    // Draw without replacement:\n    > out = sample( [ 1, 2, 3, 4, 5, 6 ], { 'replace': false, 'size': 3 } )\n    e.g., [ 6, 1, 5 ]\n    > out = sample( [ 0, 1 ], { 'replace': false } )\n    e.g., [ 0, 1 ]\n\n    // Assigning non-uniform element probabilities:\n    > var x = [ 1, 2, 3, 4, 5, 6 ];\n    > var probs = [ 0.1, 0.1, 0.1, 0.1, 0.1, 0.5 ];\n    > out = sample( x, { 'probs': probs } )\n    e.g., [ 5, 6, 6, 5, 6, 4 ]\n    > out = sample( x, { 'probs': probs, 'size': 3, 'replace': false } )\n    e.g., [ 6, 4, 1 ]\n\n\nsample.factory( [pool, ][options] )\n    Returns a function to sample elements from an array-like object.\n\n    If provided an array-like object `pool`, the returned function will always\n    sample from the supplied object.\n\n    Parameters\n    ----------\n    pool: ArrayLike (optional)\n        Array-like object from which to sample.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer (optional)\n        Integer-valued seed.\n\n    options.size: integer (optional)\n        Sample size.\n\n    options.replace: boolean (optional)\n        Boolean indicating whether to sample with replacement. Default: `true`.\n\n    options.mutate: boolean (optional)\n        Boolean indicating whether to mutate the `pool` when sampling without\n        replacement. If a population from which to sample is provided, the\n        underlying `pool` remains by default constant for each function\n        invocation. To mutate the `pool` by permanently removing observations\n        when sampling without replacement, set the `mutate` option to `true`.\n        The returned function returns `null` after all population units are\n        exhausted. Default: `false`.\n\n    Returns\n    -------\n    fcn: Function\n        Function to sample elements from an array-like object.\n\n    Examples\n    --------\n    // Set a seed:\n    > var mysample = sample.factory({ 'seed': 232 } );\n    > var out = mysample( 'abcdefg' )\n    e.g., [ 'g', 'd', 'g', 'f', 'c', 'e', 'f' ]\n\n    // Provide `pool` and set a seed plus a default sample size:\n    > var pool = [ 1, 2, 3, 4, 5, 6 ];\n    > mysample = sample.factory( pool, { 'seed': 232, 'size': 2 } );\n    > out = mysample()\n    e.g., [ 6, 4 ]\n    > out = mysample()\n    e.g., [ 6, 5 ]\n\n    // Mutate the `pool`:\n    > var opts = { 'seed': 474, 'size': 3, 'mutate': true, 'replace': false };\n    > pool = [ 1, 2, 3, 4, 5, 6 ];\n    > mysample = sample.factory( pool, opts );\n    > out = mysample()\n    e.g., [ 4, 3, 6 ]\n    > out = mysample()\n    e.g., [ 1, 5, 2 ]\n    > out = mysample()\n    null\n\n    // Override default `size` parameter when invoking created function:\n    > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n    > out = mysample()\n    e.g., [ 1, 1 ]\n    > out = mysample({ 'size': 10 })\n    e.g, [ 0, 1, 1, 1, 0, 1, 0, 0, 1, 1 ]\n\n    // Sample with and without replacement:\n    > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n    > out = mysample()\n    e.g., [ 1, 1 ]\n    > out = mysample({ 'replace': false })\n    e.g., [ 0, 1 ] or [ 1, 0 ]\n    > out = mysample()\n    e.g., [ 1, 1 ]\n\n","sample.factory":"\nsample.factory( [pool, ][options] )\n    Returns a function to sample elements from an array-like object.\n\n    If provided an array-like object `pool`, the returned function will always\n    sample from the supplied object.\n\n    Parameters\n    ----------\n    pool: ArrayLike (optional)\n        Array-like object from which to sample.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer (optional)\n        Integer-valued seed.\n\n    options.size: integer (optional)\n        Sample size.\n\n    options.replace: boolean (optional)\n        Boolean indicating whether to sample with replacement. Default: `true`.\n\n    options.mutate: boolean (optional)\n        Boolean indicating whether to mutate the `pool` when sampling without\n        replacement. If a population from which to sample is provided, the\n        underlying `pool` remains by default constant for each function\n        invocation. To mutate the `pool` by permanently removing observations\n        when sampling without replacement, set the `mutate` option to `true`.\n        The returned function returns `null` after all population units are\n        exhausted. Default: `false`.\n\n    Returns\n    -------\n    fcn: Function\n        Function to sample elements from an array-like object.\n\n    Examples\n    --------\n    // Set a seed:\n    > var mysample = sample.factory({ 'seed': 232 } );\n    > var out = mysample( 'abcdefg' )\n    e.g., [ 'g', 'd', 'g', 'f', 'c', 'e', 'f' ]\n\n    // Provide `pool` and set a seed plus a default sample size:\n    > var pool = [ 1, 2, 3, 4, 5, 6 ];\n    > mysample = sample.factory( pool, { 'seed': 232, 'size': 2 } );\n    > out = mysample()\n    e.g., [ 6, 4 ]\n    > out = mysample()\n    e.g., [ 6, 5 ]\n\n    // Mutate the `pool`:\n    > var opts = { 'seed': 474, 'size': 3, 'mutate': true, 'replace': false };\n    > pool = [ 1, 2, 3, 4, 5, 6 ];\n    > mysample = sample.factory( pool, opts );\n    > out = mysample()\n    e.g., [ 4, 3, 6 ]\n    > out = mysample()\n    e.g., [ 1, 5, 2 ]\n    > out = mysample()\n    null\n\n    // Override default `size` parameter when invoking created function:\n    > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n    > out = mysample()\n    e.g., [ 1, 1 ]\n    > out = mysample({ 'size': 10 })\n    e.g, [ 0, 1, 1, 1, 0, 1, 0, 0, 1, 1 ]\n\n    // Sample with and without replacement:\n    > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n    > out = mysample()\n    e.g., [ 1, 1 ]\n    > out = mysample({ 'replace': false })\n    e.g., [ 0, 1 ] or [ 1, 0 ]\n    > out = mysample()\n    e.g., [ 1, 1 ]","SAVOY_STOPWORDS_FIN":"\nSAVOY_STOPWORDS_FIN()\n    Returns a list of Finnish stop words.\n\n    Returns\n    -------\n    out: Array<string>\n        List of stop words.\n\n    Examples\n    --------\n    > var list = SAVOY_STOPWORDS_FIN()\n    [ 'aiemmin', 'aika', 'aikaa', ... ]\n\n    References\n    ----------\n    - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n    <http://members.unine.ch/jacques.savoy/clef/>.\n\n","SAVOY_STOPWORDS_FR":"\nSAVOY_STOPWORDS_FR()\n    Returns a list of French stop words.\n\n    Returns\n    -------\n    out: Array<string>\n        List of stop words.\n\n    Examples\n    --------\n    > var list = SAVOY_STOPWORDS_FR()\n    [ 'a', 'à', 'â', 'abord', ... ]\n\n    References\n    ----------\n    - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n    <http://members.unine.ch/jacques.savoy/clef/>.\n\n","SAVOY_STOPWORDS_GER":"\nSAVOY_STOPWORDS_GER()\n    Returns a list of German stop words.\n\n    Returns\n    -------\n    out: Array<string>\n        List of stop words.\n\n    Examples\n    --------\n    > var list = SAVOY_STOPWORDS_GER()\n    [ 'a', 'ab', 'aber', 'ach', ... ]\n\n    References\n    ----------\n    - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n    <http://members.unine.ch/jacques.savoy/clef/>.\n\n","SAVOY_STOPWORDS_IT":"\nSAVOY_STOPWORDS_IT()\n    Returns a list of Italian stop words.\n\n    Returns\n    -------\n    out: Array<string>\n        List of stop words.\n\n    Examples\n    --------\n    > var list = SAVOY_STOPWORDS_IT()\n    [ 'a', 'abbastanza', 'accidenti', 'ad', ... ]\n\n    References\n    ----------\n    - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n    <http://members.unine.ch/jacques.savoy/clef/>.\n\n","SAVOY_STOPWORDS_POR":"\nSAVOY_STOPWORDS_POR()\n    Returns a list of Portuguese stop words.\n\n    Returns\n    -------\n    out: Array<string>\n        List of stop words.\n\n    Examples\n    --------\n    > var list = SAVOY_STOPWORDS_POR()\n    [ 'aiemmin', 'aika', 'aikaa', ... ]\n\n    References\n    ----------\n    - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n    <http://members.unine.ch/jacques.savoy/clef/>.\n\n","SAVOY_STOPWORDS_SP":"\nSAVOY_STOPWORDS_SP()\n    Returns a list of Spanish stop words.\n\n    Returns\n    -------\n    out: Array<string>\n        List of stop words.\n\n    Examples\n    --------\n    > var list = SAVOY_STOPWORDS_SP()\n    [ 'a', 'acuerdo', 'adelante', 'ademas', ... ]\n\n    References\n    ----------\n    - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n    <http://members.unine.ch/jacques.savoy/clef/>.\n\n","SAVOY_STOPWORDS_SWE":"\nSAVOY_STOPWORDS_SWE()\n    Returns a list of Swedish stop words.\n\n    Returns\n    -------\n    out: Array<string>\n        List of stop words.\n\n    Examples\n    --------\n    > var list = SAVOY_STOPWORDS_SWE()\n    [ 'aderton', 'adertonde', 'adjö', ... ]\n\n    References\n    ----------\n    - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n    <http://members.unine.ch/jacques.savoy/clef/>.\n\n","scalar2array":"\nscalar2array( value[, dtype] )\n    Returns a single-element array containing a provided scalar value.\n\n    If `value` is a number and `dtype` is a complex number data type, the\n    function returns a complex number array containing a complex number whose\n    real component equals the provided scalar value and whose imaginary\n    component is zero.\n\n    Parameters\n    ----------\n    value: any\n        Scalar value.\n\n    dtype: string (optional)\n        Data type. If not provided and `value`\n\n        - is a number, the default data type is the default real-valued\n          floating-point data type.\n        - is a boolean, the default data type is the default boolean data type.\n        - is a complex number object of a known complex data type, the data type\n          is the same as the provided value.\n        - is a complex number object of an unknown data type, the default data\n          type is the default complex-valued floating-point data type.\n        - is any other value type, the default data type is 'generic'.\n\n    Returns\n    -------\n    out: Array|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = scalar2array( 1.0 )\n    <Float64Array>[ 1.0 ]\n\n    See Also\n    --------\n    iterator2array\n","scalar2ndarray":"\nscalar2ndarray( value[, options] )\n    Returns a zero-dimensional ndarray containing a provided scalar value.\n\n    If `value` is a number and `options.dtype` is a complex number data type,\n    the function returns a zero-dimensional ndarray containing a complex number\n    whose real component equals the provided scalar value and whose imaginary\n    component is zero.\n\n    Parameters\n    ----------\n    value: any\n        Scalar value.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Data type. If not provided and `value`\n\n        - is a number, the default data type is the default real-valued\n          floating-point data type.\n        - is a boolean, the default data type is the default boolean data type.\n        - is a complex number object of a known complex data type, the data type\n          is the same as the provided value.\n        - is a complex number object of an unknown data type, the default data\n          type is the default complex-valued floating-point data type.\n        - is any other value type, the default data type is 'generic'.\n\n    options.order: string (optional)\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran-style). Default: 'row-major'.\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether an array should be read-only. Default: false.\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var x = scalar2ndarray( 1.0 )\n    <ndarray>\n    > var sh = x.shape\n    []\n    > var dt = x.dtype\n    'float64'\n    > var v = x.get()\n    1.0\n\n    See Also\n    --------\n    array, ndarray\n","sdot":"\nsdot( x, y[, dim] )\n    Computes the dot product of two single-precision floating-point vectors.\n\n    If provided at least one input array having more than one dimension, the\n    input arrays are broadcasted to a common shape.\n\n    For multi-dimensional input arrays, the function performs batched\n    computation, such that the function computes the dot product for each pair\n    of vectors in `x` and `y` according to the specified dimension index.\n\n    The size of the contracted dimension must be the same for both input arrays.\n\n    The function resolves the dimension index for which to compute the dot\n    product *before* broadcasting.\n\n    If provided empty vectors, the dot product is `0`.\n\n    Parameters\n    ----------\n    x: ndarray\n        First input array. Must have a 'float32' data type. Must have at least\n        one dimension and be broadcast-compatible with the second input array.\n\n    y: ndarray\n        Second input array. Must have a 'float32' data type. Must have at least\n        one dimension and be broadcast-compatible with the first input array.\n\n    dim: integer (optional)\n        Dimension index for which to compute the dot product. Must be a negative\n        integer. Negative indices are resolved relative to the last array\n        dimension, with the last dimension corresponding to `-1`. Default: -1.\n\n    Returns\n    -------\n    out: ndarray\n        The dot product. The output array has the same data type as the input\n        arrays and has a shape which is determined by broadcasting and excludes\n        the contracted dimension.\n\n    Examples\n    --------\n    > var xbuf = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var x = array( xbuf );\n    > var ybuf = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var y = array( ybuf );\n    > var z = sdot( x, y )\n    <ndarray>\n    > z.get()\n    -5.0\n\n    See Also\n    --------\n    base.strided.sdot, ddot, gdot\n","SECONDS_IN_DAY":"\nSECONDS_IN_DAY\n    Number of seconds in a day.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var days = 3.14;\n    > var secs = days * SECONDS_IN_DAY\n    271296\n\n","SECONDS_IN_HOUR":"\nSECONDS_IN_HOUR\n    Number of seconds in an hour.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var hrs = 3.14;\n    > var secs = hrs * SECONDS_IN_HOUR\n    11304\n\n","SECONDS_IN_MINUTE":"\nSECONDS_IN_MINUTE\n    Number of seconds in a minute.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies arising due to complications with time and dates.\n\n    Examples\n    --------\n    > var mins = 3.14;\n    > var secs = mins * SECONDS_IN_MINUTE\n    188.4\n\n","SECONDS_IN_WEEK":"\nSECONDS_IN_WEEK\n    Number of seconds in a week.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var wks = 3.14;\n    > var secs = wks * SECONDS_IN_WEEK\n    1899072\n\n","secondsInMonth":"\nsecondsInMonth( [month[, year]] )\n    Returns the number of seconds in a month.\n\n    By default, the function returns the number of seconds in the current month\n    of the current year (according to local time). To determine the number of\n    seconds for a particular month and year, provide `month` and `year`\n    arguments.\n\n    A `month` may be either a month's integer value, three letter abbreviation,\n    or full name (case insensitive).\n\n    The function's return value is a generalization and does **not** take into\n    account inaccuracies due to daylight savings conventions, crossing\n    timezones, or other complications with time and dates.\n\n    Parameters\n    ----------\n    month: string|Date|integer (optional)\n        Month.\n\n    year: integer (optional)\n        Year.\n\n    Returns\n    -------\n    out: integer\n        Seconds in a month.\n\n    Examples\n    --------\n    > var num = secondsInMonth()\n    <number>\n    > num = secondsInMonth( 2 )\n    <number>\n    > num = secondsInMonth( 2, 2016 )\n    2505600\n    > num = secondsInMonth( 2, 2017 )\n    2419200\n\n    // Other ways to supply month:\n    > num = secondsInMonth( 'feb', 2016 )\n    2505600\n    > num = secondsInMonth( 'february', 2016 )\n    2505600\n\n    See Also\n    --------\n    secondsInYear\n","secondsInYear":"\nsecondsInYear( [value] )\n    Returns the number of seconds in a year according to the Gregorian calendar.\n\n    By default, the function returns the number of seconds in the current year\n    (according to local time). To determine the number of seconds for a\n    particular year, provide either a year or a `Date` object.\n\n    The function's return value is a generalization and does **not** take into\n    account inaccuracies due to daylight savings conventions, crossing\n    timezones, or other complications with time and dates.\n\n    Parameters\n    ----------\n    value: integer|Date (optional)\n        Year or `Date` object.\n\n    Returns\n    -------\n    out: integer\n        Number of seconds in a year.\n\n    Examples\n    --------\n    > var num = secondsInYear()\n    <number>\n    > num = secondsInYear( 2016 )\n    31622400\n    > num = secondsInYear( 2017 )\n    31536000\n\n    See Also\n    --------\n    secondsInMonth\n","sentencize":"\nsentencize( str )\n    Splits a string into an array of sentences.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: Array\n        Array of sentences.\n\n    Examples\n    --------\n    > var out = sentencize( 'Hello Mrs. Maple, could you call me back?' )\n    [ 'Hello Mrs. Maple, could you call me back?' ]\n\n    > out = sentencize( 'Hello World! How are you?' )\n    [ 'Hello World!', 'How are you?' ]\n\n    See Also\n    --------\n    tokenize\n","seq2slice":"\nseq2slice( str, len, strict )\n    Converts a subsequence string to a Slice object.\n\n    A subsequence string has the following format:\n\n      <start>:<stop>:<increment>\n\n    If an increment is not specified, the default increment is one. An increment\n    of zero is not allowed.\n\n    The start index is inclusive.\n\n    The stop index is exclusive.\n\n    Both start and stop indices are optional. If not provided, the start and\n    stop indices default to index extremes. Which extremes correspond to which\n    index depends on whether the increment is positive or negative.\n\n    Both start and stop indices can be negative; in which case, the\n    corresponding index is resolved by subtracting the respective value from the\n    provided length.\n\n    Both start and stop indices can use the 'end' keyword (e.g., 'end-2::2',\n    'end-3:', etc), which supports basic subtraction and division.\n\n    The 'end' keyword resolves to the provided length. Thus, ':-1' is equivalent\n    to ':end-1', ':-2' is equivalent to ':end-2', and so on and so forth. The\n    exception is when performing a division operation when the increment is less\n    than zero; in which case, 'end' is equal to 'len-1' in order to preserve\n    user expectations when 'end/d' equals a whole number and slicing from right-\n    to-left. The result from a division operation is rounded down to the nearest\n    integer value.\n\n    In non-strict mode, the resolved slice start is clamped to the slice index\n    bounds [0, len).\n\n    In non-strict mode, Tte resolved slice end is upper bound clamped to the\n    provided length (i.e., one greater than the last possible index).\n\n    When the increment is negative, the resolved slice end value may be `null`,\n    thus indicating that a non-empty slice should include the first index.\n\n    The function ensures that results satisfy the convention that ':n' combined\n    with 'n:' is equivalent to ':' (i.e., selecting all elements).\n\n    When the provided length is zero, the function always returns a slice object\n    equivalent to '0:0:<increment>'.\n\n    Parameters\n    ----------\n    str: string\n        Subsequence string.\n\n    len: integer\n        Maximum number of elements allowed in the slice.\n\n    strict: boolean\n        Boolean indicating whether to enforce strict bounds checking.\n\n    Returns\n    -------\n    s: Slice\n        Slice instance.\n\n    Examples\n    --------\n    > var s = new seq2slice( '1:10', 10, false );\n    > s.start\n    1\n    > s.stop\n    10\n    > s.step\n    1\n    > s = new seq2slice( '2:5:2', 10, false );\n    > s.start\n    2\n    > s.stop\n    5\n    > s.step\n    2\n\n    See Also\n    --------\n    Slice\n","setConfigurableReadOnly":"\nsetConfigurableReadOnly( obj, prop, value )\n    Defines a configurable read-only property.\n\n    Configurable read-only properties are enumerable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    value: any\n        Value to set.\n\n    Examples\n    --------\n    > var obj = {};\n    > setConfigurableReadOnly( obj, 'foo', 'bar' );\n    > obj.foo = 'boop';\n    > obj\n    { 'foo': 'bar' }\n\n    See Also\n    --------\n    setConfigurableReadOnlyAccessor, setConfigurableReadWriteAccessor, defineProperty, setReadOnly\n","setConfigurableReadOnlyAccessor":"\nsetConfigurableReadOnlyAccessor( obj, prop, getter )\n    Defines a configurable read-only accessor.\n\n    Configurable read-only accessors are enumerable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    getter: Function\n        Get accessor.\n\n    Examples\n    --------\n    > var obj = {};\n    > function getter() { return 'bar'; };\n    > setConfigurableReadOnlyAccessor( obj, 'foo', getter );\n    > obj.foo\n    'bar'\n\n    See Also\n    --------\n    setConfigurableReadOnly, setConfigurableReadWriteAccessor, setConfigurableWriteOnlyAccessor, defineProperty, setReadOnlyAccessor\n","setConfigurableReadWriteAccessor":"\nsetConfigurableReadWriteAccessor( obj, prop, getter, setter )\n    Defines a configurable property having read-write accessors.\n\n    Configurable read-write accessors are enumerable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    getter: Function\n        Get accessor.\n\n    setter: Function\n        Set accessor.\n\n    Examples\n    --------\n    > var obj = {};\n    > var name = 'bar';\n    > function getter() { return name + ' foo'; };\n    > function setter( v ) { name = v; };\n    > setConfigurableReadWriteAccessor( obj, 'foo', getter, setter );\n    > obj.foo\n    'bar foo'\n    > obj.foo = 'beep';\n    > obj.foo\n    'beep foo'\n\n    See Also\n    --------\n    setConfigurableReadOnly, setConfigurableReadOnlyAccessor, setConfigurableWriteOnlyAccessor, defineProperty, setReadWriteAccessor\n","setConfigurableWriteOnlyAccessor":"\nsetConfigurableWriteOnlyAccessor( obj, prop, setter )\n    Defines a configurable write-only accessor.\n\n    Configurable write-only accessors are enumerable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    setter: Function\n        Set accessor.\n\n    Examples\n    --------\n    > var obj = {};\n    > var val = '';\n    > function setter( v ) { val = v; };\n    > setConfigurableWriteOnlyAccessor( obj, 'foo', setter );\n    > obj.foo = 'bar';\n    > val\n    'bar'\n\n    See Also\n    --------\n    setConfigurableReadOnly, setConfigurableReadOnlyAccessor, setConfigurableReadWriteAccessor, defineProperty, setWriteOnlyAccessor\n","setMemoizedConfigurableReadOnly":"\nsetMemoizedConfigurableReadOnly( obj, prop, fcn )\n    Defines a configurable memoized read-only object property.\n\n    Configurable read-only properties are enumerable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    fcn: Function\n        Synchronous function whose return value will be memoized and set as the\n        property value.\n\n    Examples\n    --------\n    > var obj = {};\n    > function foo() { return 'bar'; };\n    > setMemoizedConfigurableReadOnly( obj, 'foo', foo );\n    > obj.foo\n    'bar'\n\n    See Also\n    --------\n    setConfigurableReadOnly, setMemoizedReadOnly, setReadOnly\n","setMemoizedReadOnly":"\nsetMemoizedReadOnly( obj, prop, fcn )\n    Defines a memoized read-only object property.\n\n    Read-only properties are enumerable and non-configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    fcn: Function\n        Synchronous function whose return value will be memoized and set as the\n        property value.\n\n    Examples\n    --------\n    > var obj = {};\n    > function foo() { return 'bar'; };\n    > setMemoizedReadOnly( obj, 'foo', foo );\n    > obj.foo\n    'bar'\n\n    See Also\n    --------\n    defineMemoizedProperty, setReadOnly\n","setNonEnumerableProperty":"\nsetNonEnumerableProperty( obj, prop, value )\n    Defines a non-enumerable property.\n\n    Non-enumerable properties are writable and configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    value: any\n        Value to set.\n\n    Examples\n    --------\n    > var obj = {};\n    > setNonEnumerableProperty( obj, 'foo', 'bar' );\n    > obj.foo\n    'bar'\n    > objectKeys( obj )\n    []\n\n    See Also\n    --------\n    setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnly\n","setNonEnumerableReadOnly":"\nsetNonEnumerableReadOnly( obj, prop, value )\n    Defines a non-enumerable read-only property.\n\n    Non-enumerable read-only properties are non-configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    value: any\n        Value to set.\n\n    Examples\n    --------\n    > var obj = {};\n    > setNonEnumerableReadOnly( obj, 'foo', 'bar' );\n    > obj.foo = 'boop';\n    > obj\n    { 'foo': 'bar' }\n\n    See Also\n    --------\n    setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnly\n","setNonEnumerableReadOnlyAccessor":"\nsetNonEnumerableReadOnlyAccessor( obj, prop, getter )\n    Defines a non-enumerable read-only accessor.\n\n    Non-enumerable read-only accessors are non-configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    getter: Function\n        Get accessor.\n\n    Examples\n    --------\n    > var obj = {};\n    > function getter() { return 'bar'; };\n    > setNonEnumerableReadOnlyAccessor( obj, 'foo', getter );\n    > obj.foo\n    'bar'\n\n    See Also\n    --------\n    setNonEnumerableProperty, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnlyAccessor\n","setNonEnumerableReadWriteAccessor":"\nsetNonEnumerableReadWriteAccessor( obj, prop, getter, setter )\n    Defines a non-enumerable property having read-write accessors.\n\n    Non-enumerable read-write accessors are non-configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    getter: Function\n        Get accessor.\n\n    setter: Function\n        Set accessor.\n\n    Examples\n    --------\n    > var obj = {};\n    > var name = 'bar';\n    > function getter() { return name + ' foo'; };\n    > function setter( v ) { name = v; };\n    > setNonEnumerableReadWriteAccessor( obj, 'foo', getter, setter );\n    > obj.foo\n    'bar foo'\n    > obj.foo = 'beep';\n    > obj.foo\n    'beep foo'\n\n    See Also\n    --------\n    setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableWriteOnlyAccessor, setReadWriteAccessor\n","setNonEnumerableWriteOnlyAccessor":"\nsetNonEnumerableWriteOnlyAccessor( obj, prop, setter )\n    Defines a non-enumerable write-only accessor.\n\n    Non-enumerable write-only accessors are non-configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    setter: Function\n        Set accessor.\n\n    Examples\n    --------\n    > var obj = {};\n    > var val = '';\n    > function setter( v ) { val = v; };\n    > setNonEnumerableWriteOnlyAccessor( obj, 'foo', setter );\n    > obj.foo = 'bar';\n    > val\n    'bar'\n\n    See Also\n    --------\n    setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setWriteOnlyAccessor\n","setReadOnly":"\nsetReadOnly( obj, prop, value )\n    Defines a read-only property.\n\n    Read-only properties are enumerable and non-configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    value: any\n        Value to set.\n\n    Examples\n    --------\n    > var obj = {};\n    > setReadOnly( obj, 'foo', 'bar' );\n    > obj.foo = 'boop';\n    > obj\n    { 'foo': 'bar' }\n\n    See Also\n    --------\n    setReadOnlyAccessor, setReadWriteAccessor, setWriteOnlyAccessor\n","setReadOnlyAccessor":"\nsetReadOnlyAccessor( obj, prop, getter )\n    Defines a read-only accessor.\n\n    Read-only accessors are enumerable and non-configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    getter: Function\n        Get accessor.\n\n    Examples\n    --------\n    > var obj = {};\n    > function getter() { return 'bar'; };\n    > setReadOnlyAccessor( obj, 'foo', getter );\n    > obj.foo\n    'bar'\n\n    See Also\n    --------\n    setReadOnly, setReadWriteAccessor, setWriteOnlyAccessor\n","setReadWriteAccessor":"\nsetReadWriteAccessor( obj, prop, getter, setter )\n    Defines a property having read-write accessors.\n\n    Read-write accessors are enumerable and non-configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    getter: Function\n        Get accessor.\n\n    setter: Function\n        Set accessor.\n\n    Examples\n    --------\n    > var obj = {};\n    > var name = 'bar';\n    > function getter() { return name + ' foo'; };\n    > function setter( v ) { name = v; };\n    > setReadWriteAccessor( obj, 'foo', getter, setter );\n    > obj.foo\n    'bar foo'\n    > obj.foo = 'beep';\n    > obj.foo\n    'beep foo'\n\n    See Also\n    --------\n    setReadOnly, setReadOnlyAccessor, setWriteOnlyAccessor\n","setWriteOnlyAccessor":"\nsetWriteOnlyAccessor( obj, prop, setter )\n    Defines a write-only accessor.\n\n    Write-only accessors are enumerable and non-configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    setter: Function\n        Set accessor.\n\n    Examples\n    --------\n    > var obj = {};\n    > var val = '';\n    > function setter( v ) { val = v; };\n    > setWriteOnlyAccessor( obj, 'foo', setter );\n    > obj.foo = 'bar';\n    > val\n    'bar'\n\n    See Also\n    --------\n    setReadOnly, setReadOnlyAccessor, setReadWriteAccessor\n","SharedArrayBuffer":"\nSharedArrayBuffer( size )\n    Returns a shared array buffer having a specified number of bytes.\n\n    A shared array buffer behaves similarly to a non-shared array buffer, except\n    that a shared array buffer allows creating views of memory shared between\n    threads.\n\n    Buffer contents are initialized to 0.\n\n    If an environment does not support shared array buffers, the function throws\n    an error.\n\n    Parameters\n    ----------\n    size: integer\n        Number of bytes.\n\n    Returns\n    -------\n    out: SharedArrayBuffer\n        A shared array buffer.\n\n    Examples\n    --------\n    // Assuming an environment supports SharedArrayBuffers...\n    > var buf = new SharedArrayBuffer( 5 )\n    <SharedArrayBuffer>\n\n\nSharedArrayBuffer.length\n    Number of input arguments the constructor accepts.\n\n    Examples\n    --------\n    > SharedArrayBuffer.length\n    1\n\n\nSharedArrayBuffer.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the array buffer.\n\n    Examples\n    --------\n    // Assuming an environment supports SharedArrayBuffers...\n    > var buf = new SharedArrayBuffer( 5 );\n    > buf.byteLength\n    5\n\n\nSharedArrayBuffer.prototype.slice( [start[, end]] )\n    Copies the bytes of a shared array buffer to a new shared array buffer.\n\n    Parameters\n    ----------\n    start: integer (optional)\n        Index at which to start copying buffer contents (inclusive). If\n        negative, the index is relative to the end of the buffer.\n\n    end: integer (optional)\n        Index at which to stop copying buffer contents (exclusive). If negative,\n        the index is relative to the end of the buffer.\n\n    Returns\n    -------\n    out: SharedArrayBuffer\n        A new shared array buffer whose contents have been copied from the\n        calling shared array buffer.\n\n    Examples\n    --------\n    // Assuming an environment supports SharedArrayBuffers...\n    > var b1 = new SharedArrayBuffer( 10 );\n    > var b2 = b1.slice( 2, 6 );\n    > var bool = ( b1 === b2 )\n    false\n    > b2.byteLength\n    4\n\n    See Also\n    --------\n    Buffer, ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","SharedArrayBuffer.length":"\nSharedArrayBuffer.length\n    Number of input arguments the constructor accepts.\n\n    Examples\n    --------\n    > SharedArrayBuffer.length\n    1","SharedArrayBuffer.prototype.byteLength":"\nSharedArrayBuffer.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the array buffer.\n\n    Examples\n    --------\n    // Assuming an environment supports SharedArrayBuffers...\n    > var buf = new SharedArrayBuffer( 5 );\n    > buf.byteLength\n    5","SharedArrayBuffer.prototype.slice":"\nSharedArrayBuffer.prototype.slice( [start[, end]] )\n    Copies the bytes of a shared array buffer to a new shared array buffer.\n\n    Parameters\n    ----------\n    start: integer (optional)\n        Index at which to start copying buffer contents (inclusive). If\n        negative, the index is relative to the end of the buffer.\n\n    end: integer (optional)\n        Index at which to stop copying buffer contents (exclusive). If negative,\n        the index is relative to the end of the buffer.\n\n    Returns\n    -------\n    out: SharedArrayBuffer\n        A new shared array buffer whose contents have been copied from the\n        calling shared array buffer.\n\n    Examples\n    --------\n    // Assuming an environment supports SharedArrayBuffers...\n    > var b1 = new SharedArrayBuffer( 10 );\n    > var b2 = b1.slice( 2, 6 );\n    > var bool = ( b1 === b2 )\n    false\n    > b2.byteLength\n    4\n\n    See Also\n    --------\n    Buffer, ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","shift":"\nshift( collection )\n    Removes and returns the first element of a collection.\n\n    The function returns an array with two elements: the shortened collection\n    and the removed element.\n\n    If the input collection is a typed array whose length is greater than `0`,\n    the first return value does not equal the input reference.\n\n    For purposes of generality, always treat the output collection as distinct\n    from the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        A collection. If the collection is an `Object`, the value should be\n        array-like.\n\n    Returns\n    -------\n    out: Array\n        Updated collection and the removed item.\n\n    Examples\n    --------\n    // Arrays:\n    > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > var out = shift( arr )\n    [ [ 2.0, 3.0, 4.0, 5.0 ], 1.0 ]\n\n    // Typed arrays:\n    > arr = new Float64Array( [ 1.0, 2.0 ] );\n    > out = shift( arr )\n    [ <Float64Array>[ 2.0 ], 1.0 ]\n\n    // Array-like object:\n    > arr = { 'length': 2, '0': 1.0, '1': 2.0 };\n    > out = shift( arr )\n    [ { 'length': 1, '0': 2.0 }, 1.0 ]\n\n    See Also\n    --------\n    pop, push, unshift\n","shuffle":"\nshuffle( arr[, options] )\n    Shuffles elements of an array-like object.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Array-like object to shuffle.\n\n    options: Object (optional)\n        Options.\n\n    options.copy: string (optional)\n        String indicating whether to return a copy (`deep`,`shallow` or `none`).\n        Default: `'shallow'`.\n\n    Returns\n    -------\n    out: ArrayLike\n        Shuffled array-like object.\n\n    Examples\n    --------\n    > var data = [ 1, 2, 3 ];\n    > var out = shuffle( data )\n    e.g., [ 3, 1, 2 ]\n    > out = shuffle( data, { 'copy': 'none' } );\n    > var bool = ( data === out )\n    true\n\n\nshuffle.factory( [options] )\n    Returns a function to shuffle elements of array-like objects.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer (optional)\n        Integer-valued seed.\n\n    options.copy: string (optional)\n        String indicating whether to return a copy (`deep`,`shallow` or `none`).\n        Default: `'shallow'`.\n\n    Returns\n    -------\n    fcn: Function\n        Shuffle function.\n\n    Examples\n    --------\n    > var myshuffle = shuffle.factory();\n\n    // Set a seed:\n    > myshuffle = shuffle.factory({ 'seed': 239 });\n    > var arr = [ 0, 1, 2, 3, 4 ];\n    > var out = myshuffle( arr )\n    e.g., [ 3, 4, 1, 0, 2 ]\n\n    // Use a different copy strategy:\n    > myshuffle = shuffle.factory({ 'copy': 'none', 'seed': 867 });\n\n    // Created shuffle function mutates input array by default:\n    > arr = [ 1, 2, 3, 4, 5, 6 ];\n    > out = myshuffle( arr );\n    > var bool = ( arr === out )\n    true\n    // Default option can be overridden:\n    > arr = [ 1, 2, 3, 4 ];\n    > out = myshuffle( arr, { 'copy': 'shallow' } );\n    > bool = ( arr === out )\n    false\n\n    See Also\n    --------\n    sample\n","shuffle.factory":"\nshuffle.factory( [options] )\n    Returns a function to shuffle elements of array-like objects.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer (optional)\n        Integer-valued seed.\n\n    options.copy: string (optional)\n        String indicating whether to return a copy (`deep`,`shallow` or `none`).\n        Default: `'shallow'`.\n\n    Returns\n    -------\n    fcn: Function\n        Shuffle function.\n\n    Examples\n    --------\n    > var myshuffle = shuffle.factory();\n\n    // Set a seed:\n    > myshuffle = shuffle.factory({ 'seed': 239 });\n    > var arr = [ 0, 1, 2, 3, 4 ];\n    > var out = myshuffle( arr )\n    e.g., [ 3, 4, 1, 0, 2 ]\n\n    // Use a different copy strategy:\n    > myshuffle = shuffle.factory({ 'copy': 'none', 'seed': 867 });\n\n    // Created shuffle function mutates input array by default:\n    > arr = [ 1, 2, 3, 4, 5, 6 ];\n    > out = myshuffle( arr );\n    > var bool = ( arr === out )\n    true\n    // Default option can be overridden:\n    > arr = [ 1, 2, 3, 4 ];\n    > out = myshuffle( arr, { 'copy': 'shallow' } );\n    > bool = ( arr === out )\n    false\n\n    See Also\n    --------\n    sample","sizeOf":"\nsizeOf( dtype )\n    Returns the size (in bytes) of the canonical binary representation of a\n    specified numeric type.\n\n    The following numeric types are supported:\n\n    - float64: double-precision floating-point numbers.\n    - float32: single-precision floating-point numbers.\n    - float16: half-precision floating-point numbers.\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n    - complex128: 128-bit complex numbers.\n    - complex64: 64-bit complex numbers.\n\n    Parameters\n    ----------\n    dtype: string\n        Numeric type.\n\n    Returns\n    -------\n    out: number\n        Size (in bytes).\n\n    Examples\n    --------\n    > var s = sizeOf( 'int8' )\n    1\n    > s = sizeOf( 'uint32' )\n    4\n\n    See Also\n    --------\n    realmax, typemax\n","Slice":"\nSlice( [stop] )\n    Returns a Slice.\n\n    Parameters\n    ----------\n    stop: integer|null|undefined (optional)\n        Ending index (exclusive).\n\n    Returns\n    -------\n    s: Slice\n        Slice instance.\n\n    Examples\n    --------\n    > var s = new Slice();\n    > s = new Slice( 10 );\n\n\nSlice( start, stop[, step] )\n    Returns a Slice.\n\n    Parameters\n    ----------\n    start: integer|null|undefined\n        Starting index (inclusive).\n\n    stop: integer|null|undefined\n        Ending index (exclusive).\n\n    step: integer|null|undefined (optional)\n        Index increment. A numeric index increment argument should be a non-zero\n        integer value. Default: null.\n\n    Returns\n    -------\n    s: Slice\n        Slice instance.\n\n    Examples\n    --------\n    > var s = new Slice( 2, 10 );\n    > s = new Slice( 2, 10, 1 );\n\n\nSlice.prototype.start\n    Read-only property returning the starting slice index.\n\n    Returns\n    -------\n    start: integer|null\n        Starting index.\n\n    Examples\n    --------\n    > var s = new Slice( 10 );\n    > s.start\n    null\n    > s = new Slice( 2, 10 );\n    > s.start\n    2\n\n\nSlice.prototype.stop\n    Read-only property returning the ending slice index.\n\n    Returns\n    -------\n    stop: integer|null\n        Ending index.\n\n    Examples\n    --------\n    > var s = new Slice( 10 );\n    > s.stop\n    10\n    > s = new Slice( 2, 10 );\n    > s.stop\n    10\n\n\nSlice.prototype.step\n    Read-only property returning the index increment.\n\n    Returns\n    -------\n    step: integer|null\n        Index increment.\n\n    Examples\n    --------\n    > var s = new Slice( 10 );\n    > s.step\n    null\n    > s = new Slice( 2, 10 );\n    > s.step\n    null\n    > s = new Slice( 2, 10, 1 );\n    > s.step\n    1\n\n\nSlice.prototype.toString()\n    Serializes a Slice as a string.\n\n    Returns\n    -------\n    str: string\n        Serialized Slice string.\n\n    Examples\n    --------\n    > var s = new Slice( 10 );\n    > s.toString()\n    'Slice(null,10,null)'\n    > s = new Slice( 2, 10, 1 );\n    > s.toString()\n    'Slice(2,10,1)'\n\n\nSlice.prototype.toJSON()\n    Serializes a Slice as a JSON object.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var s = new Slice( 10 );\n    > s.toJSON()\n    { 'type': 'Slice', 'data': [ null, 10, null ] }\n    > s = new Slice( 2, 10, 1 );\n    > s.toJSON()\n    { 'type': 'Slice', 'data': [ 2, 10, 1 ] }\n\n    See Also\n    --------\n    ndarray, MultiSlice\n","Slice.prototype.start":"\nSlice.prototype.start\n    Read-only property returning the starting slice index.\n\n    Returns\n    -------\n    start: integer|null\n        Starting index.\n\n    Examples\n    --------\n    > var s = new Slice( 10 );\n    > s.start\n    null\n    > s = new Slice( 2, 10 );\n    > s.start\n    2","Slice.prototype.stop":"\nSlice.prototype.stop\n    Read-only property returning the ending slice index.\n\n    Returns\n    -------\n    stop: integer|null\n        Ending index.\n\n    Examples\n    --------\n    > var s = new Slice( 10 );\n    > s.stop\n    10\n    > s = new Slice( 2, 10 );\n    > s.stop\n    10","Slice.prototype.step":"\nSlice.prototype.step\n    Read-only property returning the index increment.\n\n    Returns\n    -------\n    step: integer|null\n        Index increment.\n\n    Examples\n    --------\n    > var s = new Slice( 10 );\n    > s.step\n    null\n    > s = new Slice( 2, 10 );\n    > s.step\n    null\n    > s = new Slice( 2, 10, 1 );\n    > s.step\n    1","Slice.prototype.toString":"\nSlice.prototype.toString()\n    Serializes a Slice as a string.\n\n    Returns\n    -------\n    str: string\n        Serialized Slice string.\n\n    Examples\n    --------\n    > var s = new Slice( 10 );\n    > s.toString()\n    'Slice(null,10,null)'\n    > s = new Slice( 2, 10, 1 );\n    > s.toString()\n    'Slice(2,10,1)'","Slice.prototype.toJSON":"\nSlice.prototype.toJSON()\n    Serializes a Slice as a JSON object.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var s = new Slice( 10 );\n    > s.toJSON()\n    { 'type': 'Slice', 'data': [ null, 10, null ] }\n    > s = new Slice( 2, 10, 1 );\n    > s.toJSON()\n    { 'type': 'Slice', 'data': [ 2, 10, 1 ] }\n\n    See Also\n    --------\n    ndarray, MultiSlice","snakecase":"\nsnakecase( str )\n    Converts a string to snake case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Snake-cased string.\n\n    Examples\n    --------\n    > var out = snakecase( 'Hello World!' )\n    'hello_world'\n    > out = snakecase( 'I am a tiny little teapot' )\n    'i_am_a_tiny_little_teapot'\n\n    See Also\n    --------\n    camelcase, constantcase, kebabcase, pascalcase","some":"\nsome( collection, n )\n    Tests whether at least `n` elements in a collection are truthy.\n\n    The function immediately returns upon finding `n` truthy elements.\n\n    If provided an empty collection, the function returns `false`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    n: number\n        Minimum number of truthy elements.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if a collection contains at least `n` truthy\n        elements; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > var arr = [ 0, 0, 1, 2, 3 ];\n    > var bool = some( arr, 3 )\n    true\n\n    See Also\n    --------\n    any, every, forEach, none, someBy\n","someBy":"\nsomeBy( collection, n, predicate[, thisArg ] )\n    Tests whether a collection contains at least `n` elements which pass a test\n    implemented by a predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    The function immediately returns upon finding `n` successful elements.\n\n    If provided an empty collection, the function returns `false`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    n: number\n        Minimum number of successful elements.\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if a collection contains at least `n`\n        successful elements; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function negative( v ) { return ( v < 0 ); };\n    > var arr = [ 1, 2, -3, 4, -1 ];\n    > var bool = someBy( arr, 2, negative )\n    true\n\n    See Also\n    --------\n    anyBy, everyBy, forEach, noneBy, someByAsync, someByRight\n","someByAsync":"\nsomeByAsync( collection, n, [options,] predicate, done )\n    Tests whether a collection contains at least `n` elements which pass a test\n    implemented by a predicate function.\n\n    When invoked, the predicate function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If the\n    predicate function accepts two arguments, the predicate function is\n    provided:\n\n    - value\n    - next\n\n    If the predicate function accepts three arguments, the predicate function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other predicate function signature, the predicate function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - result: test result.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    The function immediately returns upon receiving `n` non-falsy `result`\n    values and calls the `done` callback with `null` as the first argument and\n    `true` as the second argument.\n\n    If all elements fail, the function calls the `done` callback with `null`\n    as the first argument and `false` as the second argument.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    n: number\n        Minimum number of successful elements.\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > someByAsync( arr, 2, predicate, done )\n    1000\n    2500\n    3000\n    false\n\n    // Limit number of concurrent invocations:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 3000, 2500, 1000 ];\n    > someByAsync( arr, 2, opts, predicate, done )\n    2500\n    3000\n    1000\n    false\n\n    // Process sequentially:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 3000, 2500, 1000 ];\n    > someByAsync( arr, 2, opts, predicate, done )\n    3000\n    2500\n    1000\n    false\n\n\nsomeByAsync.factory( [options,] predicate )\n    Returns a function which tests whether a collection contains at least `n`\n    elements which pass a test implemented by a predicate function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = someByAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, 2, done )\n    3000\n    2500\n    1000\n    false\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, 2, done )\n    2000\n    1500\n    1000\n    false\n\n    See Also\n    --------\n    anyByAsync, everyByAsync, forEachAsync, noneByAsync, someBy, someByRightAsync\n","someByAsync.factory":"\nsomeByAsync.factory( [options,] predicate )\n    Returns a function which tests whether a collection contains at least `n`\n    elements which pass a test implemented by a predicate function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = someByAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, 2, done )\n    3000\n    2500\n    1000\n    false\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, 2, done )\n    2000\n    1500\n    1000\n    false\n\n    See Also\n    --------\n    anyByAsync, everyByAsync, forEachAsync, noneByAsync, someBy, someByRightAsync","someByRight":"\nsomeByRight( collection, n, predicate[, thisArg ] )\n    Tests whether a collection contains at least `n` elements which pass a test\n    implemented by a predicate function, iterating from right to left.\n\n    The predicate function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    The function immediately returns upon finding `n` successful elements.\n\n    If provided an empty collection, the function returns `false`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    n: number\n        Minimum number of successful elements.\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if a collection contains at least `n`\n        successful elements; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function negative( v ) { return ( v < 0 ); };\n    > var arr = [ -1, 1, -2, 3, 4 ];\n    > var bool = someByRight( arr, 2, negative )\n    true\n\n    See Also\n    --------\n    anyByRight, everyByRight, forEachRight, noneByRight, someBy, someByRightAsync\n","someByRightAsync":"\nsomeByRightAsync( collection, n, [options,] predicate, done )\n    Tests whether a collection contains at least `n` elements which pass a test\n    implemented by a predicate function, iterating from right to left.\n\n    When invoked, the predicate function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection value.\n\n    The actual number of provided arguments depends on function length. If the\n    predicate function accepts two arguments, the predicate function is\n    provided:\n\n    - value\n    - next\n\n    If the predicate function accepts three arguments, the predicate function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other predicate function signature, the predicate function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - result: test result.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    The function immediately returns upon receiving `n` non-falsy `result`\n    values and calls the `done` callback with `null` as the first argument and\n    `true` as the second argument.\n\n    If all elements fail, the function calls the `done` callback with `null`\n    as the first argument and `false` as the second argument.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    n: number\n        Minimum number of successful elements.\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > someByRightAsync( arr, 2, predicate, done )\n    1000\n    2500\n    3000\n    false\n\n    // Limit number of concurrent invocations:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 1000, 2500, 3000 ];\n    > someByRightAsync( arr, 2, opts, predicate, done )\n    2500\n    3000\n    1000\n    false\n\n    // Process sequentially:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 1000, 2500, 3000 ];\n    > someByRightAsync( arr, 2, opts, predicate, done )\n    3000\n    2500\n    1000\n    false\n\n\nsomeByRightAsync.factory( [options,] predicate )\n    Returns a function which tests whether a collection contains at least `n`\n    elements which pass a test implemented by a predicate function, iterating\n    from right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = someByRightAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, 2, done )\n    3000\n    2500\n    1000\n    false\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, 2, done )\n    2000\n    1500\n    1000\n    false\n\n    See Also\n    --------\n    anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByAsync, someByRight\n","someByRightAsync.factory":"\nsomeByRightAsync.factory( [options,] predicate )\n    Returns a function which tests whether a collection contains at least `n`\n    elements which pass a test implemented by a predicate function, iterating\n    from right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = someByRightAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, 2, done )\n    3000\n    2500\n    1000\n    false\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, 2, done )\n    2000\n    1500\n    1000\n    false\n\n    See Also\n    --------\n    anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByAsync, someByRight","someInBy":"\nsomeInBy( obj, n, predicate[, thisArg ] )\n    Tests whether an object contains at least `n` properties\n    (own and inherited) which pass a test\n    implemented by a predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: object value.\n    - key: object key.\n    - obj: the input object.\n\n    The function immediately returns upon finding `n` successful properties.\n\n    If provided an empty object, the function returns `false`.\n\n    Parameters\n    ----------\n    obj: Object\n        Input object over which to iterate.\n\n    n: number\n        Minimum number of successful properties.\n\n    predicate: Function\n        Test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if an object contains at least `n`\n        successful properties; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function negative( v ) { return ( v < 0 ); };\n    > var obj = { 'a': 1, 'b': 2, 'c': -3, 'd': 4, 'e': -1 };\n    > var bool = someInBy( obj, 2, negative )\n    true\n\n    See Also\n    --------\n    anyInBy, everyInBy, someBy, someOwnBy","someOwnBy":"\nsomeOwnBy( obj, n, predicate[, thisArg ] )\n    Tests whether some `own` properties of a provided object\n    satisfy a predicate function for at least `n` properties.\n\n    The predicate function is provided three arguments:\n\n    - value: object value.\n    - key: object key.\n    - obj: the input object.\n\n    The function immediately returns upon finding `n` successful properties.\n\n    If provided an empty object, the function returns `false`.\n\n    Parameters\n    ----------\n    obj: Object\n        Input object over which to iterate.\n\n    n: number\n        Minimum number of successful properties.\n\n    predicate: Function\n        Test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if an object's own properties satisfy a\n        predicate for at least `n` properties; otherwise, the function\n        returns `false`.\n\n    Examples\n    --------\n    > function negative( v ) { return ( v < 0 ); };\n    > var obj = { a: 1, b: 2, c: -3, d: 4, e: -1 };\n    > var bool = someOwnBy( obj, 2, negative )\n    true\n\n    See Also\n    --------\n    anyOwnBy, everyOwnBy, someBy, someInBy","SOTU":"\nSOTU( [options] )\n    Returns State of the Union (SOTU) addresses.\n\n    Each State of the Union address is represented by an object with the\n    following fields:\n\n    - year: speech year.\n    - name: President name.\n    - party: the President's political party.\n    - text: speech text.\n\n    The following political parties are recognized:\n\n    - Democratic\n    - Republican\n    - Democratic-Republican\n    - Federalist\n    - National Union\n    - Whig\n    - Whig & Democratic\n    - none\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.name: String|Array<string> (optional)\n        President name(s).\n\n    options.party: String|Array<string> (optional)\n        Political party (or parties).\n\n    options.year: integer|Array<integer> (optional)\n        Year(s).\n\n    options.range: Array<integer> (optional)\n        Two-element array specifying a year range.\n\n    Returns\n    -------\n    out: Array<Object>\n        State of the Union addresses.\n\n    Examples\n    --------\n    > var out = SOTU()\n    [ {...}, {...}, ... ]\n\n    // Retrieve addresses by one or more Presidents...\n    > var opts = { 'name': 'Barack Obama' };\n    > out = SOTU( opts )\n    [ {...}, {...}, ... ]\n\n    // Retrieve addresses by one or more political parties...\n    > opts = { 'party': [ 'Democratic', 'Federalist' ] };\n    > out = SOTU( opts )\n    [ {...}, {...}, ... ]\n\n    // Retrieve addresses from one or more years...\n    > opts = { 'year': [ 2008, 2009, 2011 ] };\n    > out = SOTU( opts )\n    [ {...}, {...}, {...} ]\n\n    // Retrieve addresses from a range of consecutive years...\n    > opts = { 'range': [ 2008, 2016 ] }\n    > out = SOTU( opts )\n    [ {...}, {...}, ... ]\n\n","SPACHE_REVISED":"\nSPACHE_REVISED()\n    Returns a list of simple American-English words (revised Spache).\n\n    Returns\n    -------\n    out: Array<string>\n        List of simple American-English words.\n\n    Examples\n    --------\n    > var list = SPACHE_REVISED()\n    [ 'a', 'able', 'about', 'above', ... ]\n\n    References\n    ----------\n    - Spache, George. 1953. \"A New Readability Formula for Primary-Grade Reading\n    Materials.\" *The Elementary School Journal* 53 (7): 410–13. doi:10.1086/\n    458513.\n    - Klare, George R. 1974. \"Assessing Readability.\" *Reading Research\n    Quarterly* 10 (1). Wiley, International Reading Association: 62–102.\n    <http://www.jstor.org/stable/747086>.\n    - Stone, Clarence R. 1956. \"Measuring Difficulty of Primary Reading\n    Material: A Constructive Criticism of Spache's Measure.\" *The Elementary\n    School Journal* 57 (1). University of Chicago Press: 36–41.\n    <http://www.jstor.org/stable/999700>.\n    - Perera, Katherine. 2012. \"The assessment of linguistic difficulty in\n    reading material.\" In *Linguistics and the Teacher*, edited by Ronald\n    Carter, 101–13. Routledge Library Editions: Education. Taylor & Francis.\n    <https://books.google.com/books?id=oNXFQ9Gn6XIC>.\n\n","SPAM_ASSASSIN":"\nSPAM_ASSASSIN()\n    Returns the Spam Assassin public mail corpus.\n\n    Each array element has the following fields:\n\n    - id: message id (relative to message group).\n    - group: message group.\n    - checksum: object containing checksum info.\n    - text: message text (including headers).\n\n    The message group may be one of the following:\n\n    - easy-ham-1: easier to detect non-spam e-mails (2500 messages).\n    - easy-ham-2: easier to detect non-spam e-mails collected at a later date\n      (1400 messages).\n    - hard-ham-1: harder to detect non-spam e-mails (250 messages).\n    - spam-1: spam e-mails (500 messages).\n    - spam-2: spam e-mails collected at a later date (1396 messages).\n\n    The checksum object contains the following fields:\n\n    - type: checksum type (e.g., MD5).\n    - value: checksum value.\n\n    Returns\n    -------\n    out: Array<Object>\n        Corpus.\n\n    Examples\n    --------\n    > var data = SPAM_ASSASSIN()\n    [ {...}, {...}, ... ]\n\n","SparklineBase":"\nSparklineBase( [data,] [options] )\n    Returns a Sparkline instance.\n\n    This constructor is a base Sparkline constructor from which constructors\n    tailored to generating particular types of Sparkline graphics should be\n    derived.\n\n    At a minimum, descendants should implement a private `_render()` method\n    which will be automatically invoked by the public `render()` method.\n\n    The `data` argument takes precedence over the `data` option.\n\n    Parameters\n    ----------\n    data: ArrayLike|ndarray (optional)\n        Sparkline data.\n\n    options: Object (optional)\n        Options.\n\n    options.autoRender: boolean (optional)\n        Boolean indicating whether to re-render on a 'change' event. Default:\n        false.\n\n    options.bufferSize: integer|null (optional)\n        Data buffer size. If provided, data is kept in a first-in first-out\n        (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n    options.data: ArrayLike|ndarray (optional)\n        Sparkline data.\n\n    options.description: string (optional)\n        Sparkline description.\n\n    options.isDefined: Function (optional)\n        An accessor function indicating whether a datum is defined.\n\n    options.label: string (optional)\n        Data label.\n\n    Returns\n    -------\n    sparkline: Sparkline\n        Sparkline instance.\n\n    sparkline.autoRender\n        Rendering mode. If `true`, an instance renders on each 'change' event;\n        otherwise, rendering must be triggered manually.\n\n    sparkline.bufferSize\n        Data buffer size.\n\n    sparkline.description\n        Sparkline description.\n\n    sparkline.data\n        Sparkline data.\n\n    sparkline.label\n        Data label.\n\n    sparkline.isDefined( d, i )\n        An accessor function which defines whether a datum is defined. This\n        accessor is used to define how missing values are encoded. The default\n        behavior is to ignore values which are `NaN`.\n\n    sparkline.render()\n        Renders a sparkline. This method calls `_render()` which must be\n        implemented by instances and child classes. The default behavior is\n        throw an error.\n\n    Examples\n    --------\n    > var sparkline = new SparklineBase()\n    <Sparkline>\n\n    // Provide sparkline data at instantiation:\n    > var data = [ 1, 2, 3 ];\n    > sparkline = new SparklineBase( data )\n    <Sparkline>\n\n    See Also\n    --------\n    plot, Plot, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeWinLossChartSparkline\n","sparsearray2iterator":"\nsparsearray2iterator( src[, mapFcn[, thisArg]] )\n    Returns an iterator which iterates over the elements of a sparse array-like\n    object.\n\n    The returned iterator skips elements which are undefined.\n\n    When invoked, an input function is provided three arguments:\n\n    - value: iterated value.\n    - index: iterated value index.\n    - src: source array-like object.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an array's `@@iterator` method, regardless of whether this method is\n    defined. To convert an array to an implementation defined iterator, invoke\n    this method directly.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Sparse array-like object from which to create the iterator.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = sparsearray2iterator( [ 1, , 3, 4 ] );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    3\n\n    See Also\n    --------\n    iterator2array, array2iterator, sparsearray2iteratorRight\n","sparsearray2iteratorRight":"\nsparsearray2iteratorRight( src[, mapFcn[, thisArg]] )\n    Returns an iterator which iterates from right to left over the elements of a\n    sparse array-like object.\n\n    The returned iterator skips elements which are undefined.\n\n    When invoked, an input function is provided three arguments:\n\n    - value: iterated value.\n    - index: iterated value index.\n    - src: source array-like object.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an array's `@@iterator` method, regardless of whether this method is\n    defined. To convert an array to an implementation defined iterator, invoke\n    this method directly.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Sparse array-like object from which to create the iterator.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = sparsearray2iteratorRight( [ 1, 2, , 4 ] );\n    > var v = it.next().value\n    4\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    iterator2array, array2iteratorRight, sparsearray2iterator\n","splitStream":"\nsplitStream( [options] )\n    Returns a transform stream which splits streamed data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Separator used to split streamed data. A separator may be either a\n        regular expression or a string. A separator which is a regular\n        expression containing a matching group will result in the separator\n        being retained in the output stream.Default: /\\r?\\n/.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.writableObjectMode: boolean (optional)\n        Specifies whether the writable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream.\n\n    Examples\n    --------\n    > var s = splitStream();\n    > s.write( 'a\\nb\\nc' );\n    > s.end();\n\n\nsplitStream.factory( [options] )\n    Returns a function for creating transform streams for splitting streamed\n    data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Separator used to split streamed data. A separator may be either a\n        regular expression or a string. A separator which is a regular\n        expression containing a matching group will result in the separator\n        being retained in the output stream. Default: /\\r?\\n/.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.writableObjectMode: boolean (optional)\n        Specifies whether the writable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    createStream: Function\n        Function for creating transform streams.\n\n    Examples\n    --------\n    > var opts = { 'highWaterMark': 64 };\n    > var createStream = splitStream.factory( opts );\n    > var s = createStream();\n    > s.write( 'a\\nb\\nc' );\n    > s.end();\n\n\nsplitStream.objectMode( [options] )\n    Returns an \"objectMode\" transform stream for splitting streamed data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Separator used to split streamed data. A separator may be either a\n        regular expression or a string. A separator which is a regular\n        expression containing a matching group will result in the separator\n        being retained in the output stream. Default: /\\r?\\n/.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.writableObjectMode: boolean (optional)\n        Specifies whether the writable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > var s = splitStream.objectMode();\n    > s.write( 'a\\nb\\c' );\n    > s.end();\n\n    See Also\n    --------\n    joinStream\n","splitStream.factory":"\nsplitStream.factory( [options] )\n    Returns a function for creating transform streams for splitting streamed\n    data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Separator used to split streamed data. A separator may be either a\n        regular expression or a string. A separator which is a regular\n        expression containing a matching group will result in the separator\n        being retained in the output stream. Default: /\\r?\\n/.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.writableObjectMode: boolean (optional)\n        Specifies whether the writable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    createStream: Function\n        Function for creating transform streams.\n\n    Examples\n    --------\n    > var opts = { 'highWaterMark': 64 };\n    > var createStream = splitStream.factory( opts );\n    > var s = createStream();\n    > s.write( 'a\\nb\\nc' );\n    > s.end();","splitStream.objectMode":"\nsplitStream.objectMode( [options] )\n    Returns an \"objectMode\" transform stream for splitting streamed data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Separator used to split streamed data. A separator may be either a\n        regular expression or a string. A separator which is a regular\n        expression containing a matching group will result in the separator\n        being retained in the output stream. Default: /\\r?\\n/.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.writableObjectMode: boolean (optional)\n        Specifies whether the writable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > var s = splitStream.objectMode();\n    > s.write( 'a\\nb\\c' );\n    > s.end();\n\n    See Also\n    --------\n    joinStream","SQRT_EPS":"\nSQRT_EPS\n    Square root of double-precision floating-point epsilon.\n\n    Examples\n    --------\n    > SQRT_EPS\n    0.14901161193847656e-7\n\n    See Also\n    --------\n    EPS\n","SQRT_HALF":"\nSQRT_HALF\n    Square root of `1/2`.\n\n    Examples\n    --------\n    > SQRT_HALF\n    0.7071067811865476\n\n    See Also\n    --------\n    LN_HALF\n","SQRT_HALF_PI":"\nSQRT_HALF_PI\n    Square root of the mathematical constant `π` divided by `2`.\n\n    Examples\n    --------\n    > SQRT_HALF_PI\n    1.2533141373155003\n\n    See Also\n    --------\n    PI\n","SQRT_PHI":"\nSQRT_PHI\n    Square root of the golden ratio.\n\n    Examples\n    --------\n    > SQRT_PHI\n    1.272019649514069\n\n    See Also\n    --------\n    PHI\n","SQRT_PI":"\nSQRT_PI\n    Square root of the mathematical constant `π`.\n\n    Examples\n    --------\n    > SQRT_PI\n    1.7724538509055160\n\n    See Also\n    --------\n    PI\n","SQRT_THREE":"\nSQRT_THREE\n    Square root of `3`.\n\n    Examples\n    --------\n    > SQRT_THREE\n    1.7320508075688772\n\n","SQRT_TWO":"\nSQRT_TWO\n    Square root of `2`.\n\n    Examples\n    --------\n    > SQRT_TWO\n    1.4142135623730951\n\n    See Also\n    --------\n    LN2\n","SQRT_TWO_PI":"\nSQRT_TWO_PI\n    Square root of the mathematical constant `π` times `2`.\n\n    Examples\n    --------\n    > SQRT_TWO_PI\n    2.5066282746310007\n\n    See Also\n    --------\n    TWO_PI\n","SSA_US_BIRTHS_2000_2014":"\nSSA_US_BIRTHS_2000_2014()\n    Returns US birth data from 2000 to 2014, as provided by the Social Security\n    Administration.\n\n    Returns\n    -------\n    out: Array<Object>\n        Birth data.\n\n    Examples\n    --------\n    > var data = SSA_US_BIRTHS_2000_2014()\n    [ {...}, ... ]\n\n    See Also\n    --------\n    CDC_NCHS_US_BIRTHS_1969_1988, CDC_NCHS_US_BIRTHS_1994_2003\n","sswap":"\nsswap( x, y[, dim] )\n    Interchanges two single-precision floating-point vectors.\n\n    For multi-dimensional input arrays, the function performs batched\n    computation, such that the function interchanges each pair of vectors in `x`\n    and `y` according to the specified dimension index.\n\n    Both input arrays must have the same shape.\n\n    Parameters\n    ----------\n    x: ndarray\n        First input array. Must have a 'float32' data type. Must have at least\n        one dimension and must have the same shape as the second input array.\n\n    y: ndarray\n        Second input array. Must have a 'float32' data type. Must have at least\n        one dimension and must have the same shape as the first input array.\n\n    dim: integer (optional)\n        Dimension index along which to interchange vectors. Must be a negative\n        integer. Negative indices are resolved relative to the last array\n        dimension, with the last dimension corresponding to `-1`. Default: -1.\n\n    Returns\n    -------\n    y: ndarray\n        The second input array `y`.\n\n    Examples\n    --------\n    > var x = array( new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n    > var y = array( new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n    > sswap( x, y );\n    > x.data\n    <Float32Array>[ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n    > y.data\n    <Float32Array>[ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n    See Also\n    --------\n    base.strided.sswap, dswap, gswap\n","Stack":"\nStack()\n    Stack constructor.\n\n    A stack is also referred to as a \"last-in-first-out\" queue.\n\n    Returns\n    -------\n    stack: Object\n        Stack data structure.\n\n    stack.clear: Function\n        Clears the stack.\n\n    stack.first: Function\n        Returns the \"newest\" stack value (i.e., the value which is \"first-out\").\n        If the stack is empty, the returned value is `undefined`.\n\n    stack.iterator: Function\n        Returns an iterator for iterating over a stack. If an environment\n        supports Symbol.iterator, the returned iterator is iterable. Note that,\n        in order to prevent confusion arising from stack mutation during\n        iteration, a returned iterator **always** iterates over a stack\n        \"snapshot\", which is defined as the list of stack elements at the time\n        of the method's invocation.\n\n    stack.last: Function\n        Returns the \"oldest\" stack value (i.e., the value which is \"last-out\").\n        If the stack is empty, the returned value is `undefined`.\n\n    stack.length: integer\n        Stack length.\n\n    stack.pop: Function\n        Removes and returns the current \"first-out\" value from the stack. If the\n        stack is empty, the returned value is `undefined`.\n\n    stack.push: Function\n        Adds a value to the stack.\n\n    stack.toArray: Function\n        Returns an array of stack values.\n\n    stack.toJSON: Function\n        Serializes a stack as JSON.\n\n    Examples\n    --------\n    > var s = Stack();\n    > s.push( 'foo' ).push( 'bar' );\n    > s.length\n    2\n    > s.pop()\n    'bar'\n    > s.length\n    1\n    > s.pop()\n    'foo'\n    > s.length\n    0\n\n    See Also\n    --------\n    FIFO\n","standalone2pkg":"\nstandalone2pkg( pkg )\n    Returns the internal package name associated with a provided standalone\n    package name.\n\n    Parameters\n    ----------\n    pkg: string\n        Standalone package name.\n\n    Returns\n    -------\n    out: string|null\n        Internal package name.\n\n    Examples\n    --------\n    > var v = standalone2pkg( '@stdlib/math-base-special-sin' )\n    '@stdlib/math/base/special/sin'\n\n    See Also\n    --------\n    alias2standalone, pkg2alias, pkg2standalone\n","STANDARD_CARD_DECK":"\nSTANDARD_CARD_DECK()\n    Returns a string array containing two or three letter abbreviations for each\n    card in a standard 52-card deck.\n\n    Abbreviation format: <card><suit>\n\n    Cards: A, 2, 3, 4, 5, 6, 7, 8, 9, 10, J, Q, K, where\n\n    - A: ace\n    - J: jack\n    - Q: queen\n    - K: king\n\n    Suit abbreviations:\n\n    - C: clubs\n    - D: diamonds\n    - H: hearts\n    - S: spades\n\n    Returns\n    -------\n    out: Array<string>\n        List of cards.\n\n    Examples\n    --------\n    > var list = STANDARD_CARD_DECK()\n    [ 'AC', '2C', '3C', ... ]\n\n","startcase":"\nstartcase( str )\n    Capitalizes the first letter of each word in an input string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        String containing words where each first letter is capitalized.\n\n    Examples\n    --------\n    > var out = startcase( 'beep boop' )\n    'Beep Boop'\n\n    See Also\n    --------\n    lowercase, uppercase\n","startsWith":"\nstartsWith( str, search[, position] )\n    Tests if a string starts with the characters of another string.\n\n    If provided an empty search string, the function always returns `true`.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search string.\n\n    position: integer (optional)\n        Position at which to start searching for `search`. If less than `0`, the\n        start position is determined relative to the end of the input string.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a string starts with the characters of\n        another string.\n\n    Examples\n    --------\n    > var bool = startsWith( 'Beep', 'Be' )\n    true\n    > bool = startsWith( 'Beep', 'ep' )\n    false\n    > bool = startsWith( 'Beep', 'ee', 1 )\n    true\n    > bool = startsWith( 'Beep', 'ee', -3 )\n    true\n    > bool = startsWith( 'Beep', '' )\n    true\n\n    See Also\n    --------\n    endsWith\n","STOPWORDS_EN":"\nSTOPWORDS_EN()\n    Returns a list of English stop words.\n\n    Returns\n    -------\n    out: Array<string>\n        List of stop words.\n\n    Examples\n    --------\n    > var list = STOPWORDS_EN()\n    [ 'a', 'about', 'above', 'across', ... ]\n\n","strided.abs":"\nstrided.abs( N, dtypeX, x, strideX, dtypeY, y, strideY )\n    Computes the absolute value for each element in a strided array `x` and\n    assigns the results to elements in a strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs( x.length, 'float64', x, 1, 'float64', y, 1 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs( 2, x, 2, y, -1 )\n    <Float64Array>[ 3.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.abs( 2, 'float64', x1, -2, 'float64', y1, 1 )\n    <Float64Array>[ 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nstrided.abs.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the absolute value for each element in a strided array `x` and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    strided.abs2, base.strided.dabs, base.strided.sabs\n","strided.abs.ndarray":"\nstrided.abs.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the absolute value for each element in a strided array `x` and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    strided.abs2, base.strided.dabs, base.strided.sabs","strided.abs2":"\nstrided.abs2( N, dtypeX, x, strideX, dtypeY, y, strideY )\n    Computes the squared absolute value for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs2( x.length, 'float64', x, 1, 'float64', y, 1 )\n    <Float64Array>[ 4.0, 1.0, 9.0, 25.0 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs2( 2, 'float64', x, 2, 'float64', y, -1 )\n    <Float64Array>[ 9.0, 4.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.abs2( 2, 'float64', x1, -2, 'float64', y1, 1 )\n    <Float64Array>[ 25.0, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 25.0, 1.0 ]\n\n\nstrided.abs2.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the squared absolute value for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs2.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 4.0, 1.0, 9.0, 25.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs2.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 25.0, 1.0 ]\n\n    See Also\n    --------\n    strided.abs, base.strided.dabs2, base.strided.sabs2\n","strided.abs2.ndarray":"\nstrided.abs2.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the squared absolute value for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs2.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 4.0, 1.0, 9.0, 25.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs2.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 25.0, 1.0 ]\n\n    See Also\n    --------\n    strided.abs, base.strided.dabs2, base.strided.sabs2","strided.abs2By":"\nstrided.abs2By( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the squared absolute value of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -1.0, -2.0, -3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.abs2By( x.length, x, 1, y, 1, clbk )\n    [ 1.0, 4.0, 9.0, 16.0 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.abs2By( 2, x, 2, y, -1, clbk )\n    [ 9.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.abs2By( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ 16.0, 4.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 16.0, 4.0 ]\n\n\nstrided.abs2By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the squared absolute value of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -1.0, -2.0, -3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.abs2By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 1.0, 4.0, 9.0, 16.0 ]\n\n    // Advanced indexing:\n    > x = [ -1.0, -2.0, -3.0, -4.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.abs2By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, 16.0, 4.0 ]\n\n    See Also\n    --------\n    strided.absBy, strided.abs2\n","strided.abs2By.ndarray":"\nstrided.abs2By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the squared absolute value of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -1.0, -2.0, -3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.abs2By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 1.0, 4.0, 9.0, 16.0 ]\n\n    // Advanced indexing:\n    > x = [ -1.0, -2.0, -3.0, -4.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.abs2By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, 16.0, 4.0 ]\n\n    See Also\n    --------\n    strided.absBy, strided.abs2","strided.absBy":"\nstrided.absBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the absolute value of each element retrieved from a strided input\n    array `x` via a callback function and assigns each result to an element in a\n    strided output array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v * 2.0; };\n    > strided.absBy( x.length, x, 1, y, 1, clbk )\n    [ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.absBy( 2, x, 2, y, -1, clbk )\n    [ 6.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.absBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ 8.0, 4.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 8.0, 4.0 ]\n\n\nstrided.absBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the absolute value of each element retrieved from a strided input\n    array `x` via a callback function and assigns each result to an element in a\n    strided output array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v * 2.0; };\n    > strided.absBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.absBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, 8.0, 4.0 ]\n\n    See Also\n    --------\n    strided.abs, strided.abs2By\n","strided.absBy.ndarray":"\nstrided.absBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the absolute value of each element retrieved from a strided input\n    array `x` via a callback function and assigns each result to an element in a\n    strided output array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v * 2.0; };\n    > strided.absBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.absBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, 8.0, 4.0 ]\n\n    See Also\n    --------\n    strided.abs, strided.abs2By","strided.acosBy":"\nstrided.acosBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the arccosine of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 0.707, 0.866, -0.707 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acosBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, ~0.786, ~0.524, ~2.356 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acosBy( 2, x, 2, y, -1, clbk )\n    [ ~0.524, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 0.707, 0.866, -0.707 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.acosBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~2.356, ~0.786 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~2.356, ~0.786 ]\n\n\nstrided.acosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the arccosine of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 0.707, 0.866, -0.707 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~0.786, ~0.524, ~2.356 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 0.707, 0.866, -0.707 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~2.356, ~0.786 ]\n\n","strided.acosBy.ndarray":"\nstrided.acosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the arccosine of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 0.707, 0.866, -0.707 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~0.786, ~0.524, ~2.356 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 0.707, 0.866, -0.707 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~2.356, ~0.786 ]","strided.acoshBy":"\nstrided.acoshBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the hyperbolic arccosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 1.5, 2.0, 2.5 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acoshBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, ~0.962, ~1.317, ~1.567 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acoshBy( 2, x, 2, y, -1, clbk )\n    [ ~1.317, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 1.5, 2.0, 2.5 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.acoshBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~1.567, ~0.962 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~1.567, ~0.962 ]\n\n\nstrided.acoshBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the hyperbolic arccosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 1.5, 2.0, 2.5 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acoshBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~0.962, ~1.317, ~1.567 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 1.5, 2.0, 2.5 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acoshBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~1.567, ~0.962 ]\n\n","strided.acoshBy.ndarray":"\nstrided.acoshBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the hyperbolic arccosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 1.5, 2.0, 2.5 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acoshBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~0.962, ~1.317, ~1.567 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 1.5, 2.0, 2.5 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acoshBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~1.567, ~0.962 ]","strided.acotBy":"\nstrided.acotBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the inverse cotangent of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -2.5, -1.5, -0.5, 0.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acotBy( x.length, x, 1, y, 1, clbk )\n    [ ~-0.381, ~-0.588, ~-1.107, ~1.571 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acotBy( 2, x, 2, y, -1, clbk )\n    [ ~-1.107, ~-0.381, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -2.5, -1.5, -0.5, 0.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.acotBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~1.571, ~-0.588 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~1.571, ~-0.588 ]\n\n\nstrided.acotBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse cotangent of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -2.5, -1.5, -0.5, 0.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acotBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ ~-0.381, ~-0.588, ~-1.107, ~1.571 ]\n\n    // Advanced indexing:\n    > x = [ -2.5, -1.5, -0.5, 0.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acotBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~1.571, ~-0.588 ]\n\n","strided.acotBy.ndarray":"\nstrided.acotBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse cotangent of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -2.5, -1.5, -0.5, 0.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acotBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ ~-0.381, ~-0.588, ~-1.107, ~1.571 ]\n\n    // Advanced indexing:\n    > x = [ -2.5, -1.5, -0.5, 0.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acotBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~1.571, ~-0.588 ]","strided.acothBy":"\nstrided.acothBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the inverse hyperbolic cotangent of each element retrieved from an\n    input strided array `x` via a callback function and assigns each result to\n    an element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -5.0, -4.0, -3.0, -1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acothBy( x.length, x, 1, y, 1, clbk )\n    [ ~-0.203, ~-0.255, ~-0.347, -Infinity ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acothBy( 2, x, 2, y, -1, clbk )\n    [ ~-0.347, ~-0.203, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -5.0, -4.0, -3.0, -1.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.acothBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ -Infinity, ~-0.255 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, -Infinity, ~-0.255 ]\n\n\nstrided.acothBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse hyperbolic cotangent of each element retrieved from an\n    input strided array `x` via a callback function and assigns each result to\n    an element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -5.0, -4.0, -3.0, -1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acothBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ ~-0.203, ~-0.255, ~-0.347, -Infinity ]\n\n    // Advanced indexing:\n    > x = [ -5.0, -4.0, -3.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acothBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, -Infinity, ~-0.255 ]\n\n","strided.acothBy.ndarray":"\nstrided.acothBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse hyperbolic cotangent of each element retrieved from an\n    input strided array `x` via a callback function and assigns each result to\n    an element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -5.0, -4.0, -3.0, -1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acothBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ ~-0.203, ~-0.255, ~-0.347, -Infinity ]\n\n    // Advanced indexing:\n    > x = [ -5.0, -4.0, -3.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acothBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, -Infinity, ~-0.255 ]","strided.acovercosBy":"\nstrided.acovercosBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the inverse coversed cosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acovercosBy( x.length, x, 1, y, 1, clbk )\n    [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acovercosBy( 2, x, 2, y, -1, clbk )\n    [ ~0.524, ~1.571, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, -1.57, -0.5, -1.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.acovercosBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ 0.0, ~-0.607 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, ~-0.607 ]\n\n\nstrided.acovercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse coversed cosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acovercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -1.57, -0.5, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acovercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, 0.0, ~-0.607 ]\n\n","strided.acovercosBy.ndarray":"\nstrided.acovercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse coversed cosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acovercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -1.57, -0.5, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acovercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, 0.0, ~-0.607 ]","strided.acoversinBy":"\nstrided.acoversinBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the inverse coversed sine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acoversinBy( x.length, x, 1, y, 1, clbk )\n    [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acoversinBy( 2, x, 2, y, -1, clbk )\n    [ ~0.524, ~1.571, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.acoversinBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ 0.0, ~-0.607 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, ~-0.607 ]\n\n\nstrided.acoversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse coversed sine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acoversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.57, 0.5, 1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acoversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, 0.0, ~-0.607 ]\n\n","strided.acoversinBy.ndarray":"\nstrided.acoversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse coversed sine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acoversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.57, 0.5, 1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acoversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, 0.0, ~-0.607 ]","strided.add":"\nstrided.add( N, dx, x, sx, dy, y, sy, dz, z, sz )\n    Adds each element in a strided array `x` to a corresponding element in a\n    strided array `y` and assigns the results to elements in a strided array\n    `z`.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dx: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    dy: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    dz: any\n        Data type for `z`.\n\n    z: ArrayLikeObject\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    Returns\n    -------\n    z: ArrayLikeObject\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var dt = 'float64';\n    > strided.add( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\n    <Float64Array>[ -1.0, 3.0, 6.0, -1.0 ]\n\n    // Using `N` and stride parameters:\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.add( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\n    <Float64Array>[ 1.0, 4.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > strided.add( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\n    <Float64Array>[ -2.0, 5.0 ]\n    > z0\n    <Float64Array>[ 0.0, 0.0, -2.0, 5.0 ]\n\n\nstrided.add.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n    Adds each element in a strided array `x` to a corresponding element in a\n    strided array `y` and assigns the results to elements in a strided array\n    `z` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dx: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    dy: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    dz: any\n        Data type for `z`.\n\n    z: ArrayLikeObject\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    Returns\n    -------\n    z: ArrayLikeObject\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var dt = 'float64';\n    > strided.add.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n    <Float64Array>[ -1.0, 3.0, 6.0, -1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.add.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n    <Float64Array>[ 0.0, 5.0, -2.0, 0.0 ]\n\n    See Also\n    --------\n    strided.mul, strided.sub\n","strided.add.ndarray":"\nstrided.add.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n    Adds each element in a strided array `x` to a corresponding element in a\n    strided array `y` and assigns the results to elements in a strided array\n    `z` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dx: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    dy: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    dz: any\n        Data type for `z`.\n\n    z: ArrayLikeObject\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    Returns\n    -------\n    z: ArrayLikeObject\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var dt = 'float64';\n    > strided.add.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n    <Float64Array>[ -1.0, 3.0, 6.0, -1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.add.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n    <Float64Array>[ 0.0, 5.0, -2.0, 0.0 ]\n\n    See Also\n    --------\n    strided.mul, strided.sub","strided.addBy":"\nstrided.addBy( N, x, sx, y, sy, z, sz, clbk[, thisArg] )\n    Performs element-wise addition of two strided arrays via a callback function\n    and assigns each result to an element in an output strided array.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided four arguments:\n\n    - values: input array elements.\n    - idx: iteration index.\n    - indices: strided array indices (offset + idx*stride).\n    - arrays: input and output arrays.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n    > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( values ) { return values; };\n    > strided.addBy( x.length, x, 1, y, 1, z, 1, clbk )\n    [ 12.0, 14.0, 16.0, 18.0 ]\n\n    // Using `N` and stride parameters:\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.addBy( 2, x, 2, y, -1, z, 1, clbk )\n    [ 13.0, 14.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\n    > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > strided.addBy( 2, x1, -2, y1, 1, z1, 1, clbk )\n    <Float64Array>[ 17.0, 16.0 ]\n    > z0\n    <Float64Array>[ 0.0, 0.0, 17.0, 16.0 ]\n\n\nstrided.addBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n    Performs element-wise addition of two strided arrays via a callback function\n    and assigns each result to an element in an output strided array using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n    > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( values ) { return values; };\n    > strided.addBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n    [ 12.0, 14.0, 16.0, 18.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0 ];\n    > y = [ 11.0, 12.0, 13.0, 14.0 ];\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > var oy = y.length - 1;\n    > var oz = z.length - 1;\n    > strided.addBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n    [ 0.0, 0.0, 17.0, 16.0 ]\n\n    See Also\n    --------\n    strided.add, strided.mulBy, strided.subBy\n","strided.addBy.ndarray":"\nstrided.addBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n    Performs element-wise addition of two strided arrays via a callback function\n    and assigns each result to an element in an output strided array using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n    > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( values ) { return values; };\n    > strided.addBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n    [ 12.0, 14.0, 16.0, 18.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0 ];\n    > y = [ 11.0, 12.0, 13.0, 14.0 ];\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > var oy = y.length - 1;\n    > var oz = z.length - 1;\n    > strided.addBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n    [ 0.0, 0.0, 17.0, 16.0 ]\n\n    See Also\n    --------\n    strided.add, strided.mulBy, strided.subBy","strided.ahavercosBy":"\nstrided.ahavercosBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the inverse half-value versed cosine of each element retrieved from\n    an input strided array `x` via a callback function and assigns each result\n    to an element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.ahavercosBy( x.length, x, 1, y, 1, clbk )\n    [ ~3.142, ~1.571, 0.0, ~2.094 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.ahavercosBy( 2, x, 2, y, -1, clbk )\n    [ 0.0, ~3.142, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 0.5, 1.0, 0.25 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.ahavercosBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~2.094, ~1.571 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~2.094, ~1.571 ]\n\n\nstrided.ahavercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse half-value versed cosine of each element retrieved from\n    an input strided array `x` via a callback function and assigns each result\n    to an element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.ahavercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ ~3.142, ~1.571, 0.0, ~2.094 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 0.5, 1.0, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.ahavercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~2.094, ~1.571 ]\n\n    See Also\n    --------\n    strided.ahaversinBy\n","strided.ahavercosBy.ndarray":"\nstrided.ahavercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse half-value versed cosine of each element retrieved from\n    an input strided array `x` via a callback function and assigns each result\n    to an element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.ahavercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ ~3.142, ~1.571, 0.0, ~2.094 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 0.5, 1.0, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.ahavercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~2.094, ~1.571 ]\n\n    See Also\n    --------\n    strided.ahaversinBy","strided.ahaversinBy":"\nstrided.ahaversinBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the inverse half-value versed sine of each element retrieved from\n    an input strided array `x` via a callback function and assigns each result\n    to an element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.ahaversinBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, ~1.571, ~3.142, ~1.047 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.ahaversinBy( 2, x, 2, y, -1, clbk )\n    [ ~3.142, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 0.5, 1.0, 0.25 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.ahaversinBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~1.047, ~1.571 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~1.047, ~1.571 ]\n\n\nstrided.ahaversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse half-value versed sine of each element retrieved from\n    an input strided array `x` via a callback function and assigns each result\n    to an element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.ahaversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~1.571, ~3.142, ~1.047 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 0.5, 1.0, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.ahaversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~1.047, ~1.571 ]\n\n    See Also\n    --------\n    strided.ahavercosBy\n","strided.ahaversinBy.ndarray":"\nstrided.ahaversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse half-value versed sine of each element retrieved from\n    an input strided array `x` via a callback function and assigns each result\n    to an element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.ahaversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~1.571, ~3.142, ~1.047 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 0.5, 1.0, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.ahaversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~1.047, ~1.571 ]\n\n    See Also\n    --------\n    strided.ahavercosBy","strided.asinBy":"\nstrided.asinBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the arcsine of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.asinBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, ~-0.524, ~1.571, ~-0.253 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.asinBy( 2, x, 2, y, -1, clbk )\n    [ ~1.571, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, -0.5, 1.0, -0.25 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.asinBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~-0.253, ~-0.524 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~-0.253, ~-0.524 ]\n\n\nstrided.asinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the arcsine of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.asinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~-0.524, ~1.571, ~-0.253 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -0.5, 1.0, -0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.asinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.253, ~-0.524 ]\n\n    See Also\n    --------\n    strided.asinhBy\n","strided.asinBy.ndarray":"\nstrided.asinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the arcsine of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.asinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~-0.524, ~1.571, ~-0.253 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -0.5, 1.0, -0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.asinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.253, ~-0.524 ]\n\n    See Also\n    --------\n    strided.asinhBy","strided.asinhBy":"\nstrided.asinhBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the hyperbolic arcsine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.0, 2.0, -2.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.asinhBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, 0.0, ~1.444, ~-1.444 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.asinhBy( 2, x, 2, y, -1, clbk )\n    [ ~1.444, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, -0.0, 2.0, -2.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.asinhBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~-1.444, 0.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~-1.444, 0.0 ]\n\n\nstrided.asinhBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the hyperbolic arcsine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.0, 2.0, -2.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.asinhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, 0.0, ~1.444, ~-1.444 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -0.0, 2.0, -2.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.asinhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-1.444, 0.0 ]\n\n    See Also\n    --------\n    strided.asinBy\n","strided.asinhBy.ndarray":"\nstrided.asinhBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the hyperbolic arcsine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.0, 2.0, -2.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.asinhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, 0.0, ~1.444, ~-1.444 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -0.0, 2.0, -2.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.asinhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-1.444, 0.0 ]\n\n    See Also\n    --------\n    strided.asinBy","strided.atanBy":"\nstrided.atanBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the arctangent of each element retrieved from an input strided\n    array `x` via a callback function and assigns each result to an element in\n    an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.5, 1.0, -1.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.atanBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, ~-0.464, ~0.785, ~-0.896 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.atanBy( 2, x, 2, y, -1, clbk )\n    [ ~0.785, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, -0.5, 1.0, -1.25 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.atanBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~-0.896, ~-0.464 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~-0.896, ~-0.464 ]\n\n\nstrided.atanBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the arctangent of each element retrieved from an input strided\n    array `x` via a callback function and assigns each result to an element in\n    an output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.5, 1.0, -1.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.atanBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~-0.464, ~0.785, ~-0.896 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -0.5, 1.0, -1.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.atanBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.896, ~-0.464 ]\n\n    See Also\n    --------\n    strided.atanhBy\n","strided.atanBy.ndarray":"\nstrided.atanBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the arctangent of each element retrieved from an input strided\n    array `x` via a callback function and assigns each result to an element in\n    an output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.5, 1.0, -1.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.atanBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~-0.464, ~0.785, ~-0.896 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -0.5, 1.0, -1.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.atanBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.896, ~-0.464 ]\n\n    See Also\n    --------\n    strided.atanhBy","strided.atanhBy":"\nstrided.atanhBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the hyperbolic arctangent of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.atanhBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, ~-0.549, Infinity, ~-0.255 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.atanhBy( 2, x, 2, y, -1, clbk )\n    [ Infinity, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, -0.5, 1.0, -0.25 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.atanhBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~-0.255, ~-0.549 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~-0.255, ~-0.549 ]\n\n\nstrided.atanhBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the hyperbolic arctangent of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.atanhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~-0.549, Infinity, ~-0.255 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -0.5, 1.0, -0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.atanhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.255, ~-0.549 ]\n\n    See Also\n    --------\n    strided.atanBy\n","strided.atanhBy.ndarray":"\nstrided.atanhBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the hyperbolic arctangent of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.atanhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~-0.549, Infinity, ~-0.255 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -0.5, 1.0, -0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.atanhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.255, ~-0.549 ]\n\n    See Also\n    --------\n    strided.atanBy","strided.avercosBy":"\nstrided.avercosBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the inverse versed cosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.avercosBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.avercosBy( 2, x, 2, y, -1, clbk )\n    [ ~1.047, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, -1.57, -0.5, -1.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.avercosBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~1.571, ~2.177 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~1.571, ~2.177 ]\n\n\nstrided.avercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse versed cosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.avercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -1.57, -0.5, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.avercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~1.571, ~2.177 ]\n\n","strided.avercosBy.ndarray":"\nstrided.avercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse versed cosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.avercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -1.57, -0.5, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.avercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~1.571, ~2.177 ]","strided.aversinBy":"\nstrided.aversinBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the inverse versed sine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.aversinBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.aversinBy( 2, x, 2, y, -1, clbk )\n    [ ~1.047, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.aversinBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~1.571, ~2.177 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~1.571, ~2.177 ]\n\n\nstrided.aversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse versed sine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.aversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.57, 0.5, 1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.aversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~1.571, ~2.177 ]\n\n","strided.aversinBy.ndarray":"\nstrided.aversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse versed sine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.aversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.57, 0.5, 1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.aversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~1.571, ~2.177 ]","strided.besselj0By":"\nstrided.besselj0By( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the Bessel function of the first kind of order zero for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.besselj0By( x.length, x, 1, y, 1, clbk )\n    [ 1.0, ~0.765, ~0.998, ~0.984 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.besselj0By( 2, x, 2, y, -1, clbk )\n    [ ~0.998, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.besselj0By( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~0.984, ~0.765 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~0.984, ~0.765 ]\n\n\nstrided.besselj0By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the Bessel function of the first kind of order zero for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.besselj0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 1.0, ~0.765, ~0.998, ~0.984 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.besselj0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~0.984, ~0.765 ]\n\n    See Also\n    --------\n    strided.besselj1By, strided.bessely0By, strided.bessely1By\n","strided.besselj0By.ndarray":"\nstrided.besselj0By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the Bessel function of the first kind of order zero for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.besselj0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 1.0, ~0.765, ~0.998, ~0.984 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.besselj0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~0.984, ~0.765 ]\n\n    See Also\n    --------\n    strided.besselj1By, strided.bessely0By, strided.bessely1By","strided.besselj1By":"\nstrided.besselj1By( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the Bessel function of the first kind of order one for each element\n    retrieved from an input strided array `x` via a callback function and\n    assigns each result to an element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.besselj1By( x.length, x, 1, y, 1, clbk )\n    [ 0.0, ~0.44, ~0.05, ~0.124 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.besselj1By( 2, x, 2, y, -1, clbk )\n    [ ~0.05, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.besselj1By( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~0.124, ~0.44 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~0.124, ~0.44 ]\n\n\nstrided.besselj1By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the Bessel function of the first kind of order one for each element\n    retrieved from an input strided array `x` via a callback function and\n    assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.besselj1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~0.44, ~0.05, ~0.124 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.besselj1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~0.124, ~0.44 ]\n\n    See Also\n    --------\n    strided.besselj0By, strided.bessely0By, strided.bessely1By\n","strided.besselj1By.ndarray":"\nstrided.besselj1By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the Bessel function of the first kind of order one for each element\n    retrieved from an input strided array `x` via a callback function and\n    assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.besselj1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~0.44, ~0.05, ~0.124 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.besselj1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~0.124, ~0.44 ]\n\n    See Also\n    --------\n    strided.besselj0By, strided.bessely0By, strided.bessely1By","strided.bessely0By":"\nstrided.bessely0By( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the Bessel function of the second kind of order zero for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.bessely0By( x.length, x, 1, y, 1, clbk )\n    [ -Infinity, ~0.088, ~-1.534, ~-0.932 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.bessely0By( 2, x, 2, y, -1, clbk )\n    [ ~-1.534, -Infinity, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.bessely0By( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~-0.932, ~0.088 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~-0.932, ~0.088 ]\n\n\nstrided.bessely0By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the Bessel function of the second kind of order zero for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.bessely0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ -Infinity, ~0.088, ~-1.534, ~-0.932 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.bessely0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.932, ~0.088 ]\n\n    See Also\n    --------\n    strided.besselj0By, strided.besselj1By, strided.bessely1By\n","strided.bessely0By.ndarray":"\nstrided.bessely0By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the Bessel function of the second kind of order zero for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.bessely0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ -Infinity, ~0.088, ~-1.534, ~-0.932 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.bessely0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.932, ~0.088 ]\n\n    See Also\n    --------\n    strided.besselj0By, strided.besselj1By, strided.bessely1By","strided.bessely1By":"\nstrided.bessely1By( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the Bessel function of the second kind of order one for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.bessely1By( x.length, x, 1, y, 1, clbk )\n    [ -Infinity, ~-0.781, ~-6.459, ~-2.704 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.bessely1By( 2, x, 2, y, -1, clbk )\n    [ ~-6.459, -Infinity, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.bessely1By( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~-2.704, ~-0.781 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~-2.704, ~-0.781 ]\n\n\nstrided.bessely1By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the Bessel function of the second kind of order one for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.bessely1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ -Infinity, ~-0.781, ~-6.459, ~-2.704 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.bessely1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-2.704, ~-0.781 ]\n\n    See Also\n    --------\n    strided.besselj0By, strided.besselj1By, strided.bessely0By\n","strided.bessely1By.ndarray":"\nstrided.bessely1By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the Bessel function of the second kind of order one for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.bessely1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ -Infinity, ~-0.781, ~-6.459, ~-2.704 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.bessely1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-2.704, ~-0.781 ]\n\n    See Also\n    --------\n    strided.besselj0By, strided.besselj1By, strided.bessely0By","strided.binetBy":"\nstrided.binetBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Evaluates Binet's formula extended to real numbers for each element\n    retrieved from an input strided array `x` via a callback function and\n    assigns each result to an element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.binetBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, 1.0, 1.0, 2.0 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.binetBy( 2, x, 2, y, -1, clbk )\n    [ 1.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.binetBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ 2.0, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 2.0, 1.0 ]\n\n\nstrided.binetBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Evaluates Binet's formula extended to real numbers for each element\n    retrieved from an input strided array `x` via a callback function and\n    assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.binetBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, 1.0, 1.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 2.0, 3.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.binetBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, 2.0, 1.0 ]\n\n","strided.binetBy.ndarray":"\nstrided.binetBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Evaluates Binet's formula extended to real numbers for each element\n    retrieved from an input strided array `x` via a callback function and\n    assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.binetBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, 1.0, 1.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 2.0, 3.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.binetBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, 2.0, 1.0 ]","strided.cbrt":"\nstrided.cbrt( N, dtypeX, x, strideX, dtypeY, y, strideY )\n    Computes the cube root of each element in a strided array `x` and assigns\n    the results to elements in a strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.cbrt( x.length, 'float64', x, 1, 'float64', y, 1 )\n    <Float64Array>[ 0.0, 1.0, 2.0, 3.0 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.cbrt( 2, 'float64', x, 2, 'float64', y, -1 )\n    <Float64Array>[ 2.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.cbrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\n    <Float64Array>[ 3.0, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n\nstrided.cbrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the cube root of each element in a strided array `x` and assigns\n    the results to elements in a strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.cbrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 0.0, 1.0, 2.0, 3.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.cbrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dcbrt, base.strided.scbrt, strided.sqrt\n","strided.cbrt.ndarray":"\nstrided.cbrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the cube root of each element in a strided array `x` and assigns\n    the results to elements in a strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.cbrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 0.0, 1.0, 2.0, 3.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.cbrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dcbrt, base.strided.scbrt, strided.sqrt","strided.cbrtBy":"\nstrided.cbrtBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the cube root of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 9.0, -27.0, 81.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.cbrtBy( x.length, x, 1, y, 1, clbk )\n    [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.cbrtBy( 2, x, 2, y, -1, clbk )\n    [ -3.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.cbrtBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~4.327, ~2.08 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~4.327, ~2.08 ]\n\n\nstrided.cbrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the cube root of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 9.0, -27.0, 81.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.cbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 9.0, -27.0, 81.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.cbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~4.327, ~2.08 ]\n\n    See Also\n    --------\n    strided.cbrt\n","strided.cbrtBy.ndarray":"\nstrided.cbrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the cube root of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 9.0, -27.0, 81.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.cbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 9.0, -27.0, 81.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.cbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~4.327, ~2.08 ]\n\n    See Also\n    --------\n    strided.cbrt","strided.ceil":"\nstrided.ceil( N, dtypeX, x, strideX, dtypeY, y, strideY )\n    Rounds each element in a strided array `x` toward positive infinity and\n    assigns the results to elements in a strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ceil( x.length, 'float64', x, 1, 'float64', y, 1 )\n    <Float64Array>[ 2.0, 3.0, -3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ceil( 2, 'float64', x, 2, 'float64', y, -1 )\n    <Float64Array>[ -3.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.ceil( 2, 'float64', x1, -2, 'float64', y1, 1 )\n    <Float64Array>[ 4.0, 3.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n\nstrided.ceil.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Rounds each element in a strided array `x` toward positive infinity and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ceil.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 2.0, 3.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ceil.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n    See Also\n    --------\n    base.strided.dceil, strided.floor, strided.trunc, base.strided.sceil\n","strided.ceil.ndarray":"\nstrided.ceil.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Rounds each element in a strided array `x` toward positive infinity and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ceil.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 2.0, 3.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ceil.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n    See Also\n    --------\n    base.strided.dceil, strided.floor, strided.trunc, base.strided.sceil","strided.cosBy":"\nstrided.cosBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the cosine for each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.cosBy( x.length, x, 1, y, 1, clbk )\n    [ 1.0, ~-1.0, ~-1.0, ~-0.839 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.cosBy( 2, x, 2, y, -1, clbk )\n    [ ~-1.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 3.14, -3.14, 10.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.cosBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~-0.839, ~-1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~-0.839, ~-1.0 ]\n\n\nstrided.cosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the cosine for each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.cosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 1.0, ~-1.0, ~-1.0, ~-0.839 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 3.14, -3.14, 10.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.cosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.839, ~-1.0 ]\n\n","strided.cosBy.ndarray":"\nstrided.cosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the cosine for each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.cosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 1.0, ~-1.0, ~-1.0, ~-0.839 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 3.14, -3.14, 10.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.cosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.839, ~-1.0 ]","strided.deg2rad":"\nstrided.deg2rad( N, dtypeX, x, strideX, dtypeY, y, strideY )\n    Converts each element in a strided array `x` from degrees to radians and\n    assigns the results to elements in a strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.deg2rad( x.length, 'float64', x, 1, 'float64', y, 1 )\n    <Float64Array>[ 0.0, ~0.524, ~0.785, ~1.571 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.deg2rad( 2, 'float64', x, 2, 'float64', y, -1 )\n    <Float64Array>[ ~0.785, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.deg2rad( 2, 'float64', x1, -2, 'float64', y1, 1 )\n    <Float64Array>[ ~1.571, ~0.524 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~1.571, ~0.524 ]\n\n\nstrided.deg2rad.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Converts each element in a strided array `x` from degrees to radians and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.deg2rad.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 0.0, ~0.524, ~0.785, ~1.571 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.deg2rad.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~1.571, ~0.524 ]\n\n    See Also\n    --------\n    base.strided.ddeg2rad, base.strided.sdeg2rad\n","strided.deg2rad.ndarray":"\nstrided.deg2rad.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Converts each element in a strided array `x` from degrees to radians and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.deg2rad.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 0.0, ~0.524, ~0.785, ~1.571 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.deg2rad.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~1.571, ~0.524 ]\n\n    See Also\n    --------\n    base.strided.ddeg2rad, base.strided.sdeg2rad","strided.dataTypes":"\nstrided.dataTypes()\n    Returns a list of strided array data types.\n\n    The output array contains the following data types:\n\n    - binary: binary.\n    - bool: boolean values.\n    - complex64: single-precision complex floating-point numbers.\n    - complex128: double-precision complex floating-point numbers.\n    - float32: single-precision floating-point numbers.\n    - float64: double-precision floating-point numbers.\n    - generic: values of any type.\n    - int16: signed 16-bit integers.\n    - int32: signed 32-bit integers.\n    - int8: signed 8-bit integers.\n    - uint16: unsigned 16-bit integers.\n    - uint32: unsigned 32-bit integers.\n    - uint8: unsigned 8-bit integers.\n    - uint8c: unsigned clamped 8-bit integers.\n\n    Returns\n    -------\n    out: Array<string>\n        List of strided array data types.\n\n    Examples\n    --------\n    > var out = strided.dataTypes()\n    <Array>\n\n","strided.dcbrtBy":"\nstrided.dcbrtBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the cube root of each element retrieved from an input double-\n    precision floating-point strided array via a callback function and assigns\n    each result to an element in an output double-precision floating-point\n    strided array.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - indices: strided array indices (offset + idx*stride).\n    - arrays: input and output arrays.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Float64Array\n        Destination array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > function clbk( v ) { return v; };\n    > strided.dcbrtBy( x.length, x, 1, y, 1, clbk )\n    <Float64Array>[ 1.0, ~2.08, -3.0, ~4.327 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.dcbrtBy( 2, x, 2, y, -1, clbk )\n    <Float64Array>[ -3.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.dcbrtBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~4.327, ~2.08 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~4.327, ~2.08 ]\n\n\nstrided.dcbrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the cube root of each element retrieved from an input double-\n    precision floating-point strided array via a callback function and assigns\n    each result to an element in an output double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - indices: strided array indices (offset + idx*stride).\n    - arrays: input and output arrays.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Float64Array\n        Destination array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > function clbk( v ) { return v; };\n    > strided.dcbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    <Float64Array>[ 1.0, ~2.08, -3.0, ~4.327 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.dcbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    <Float64Array>[ 0.0, 0.0, ~4.327, ~2.08 ]\n\n    See Also\n    --------\n    strided.cbrt\n","strided.dcbrtBy.ndarray":"\nstrided.dcbrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the cube root of each element retrieved from an input double-\n    precision floating-point strided array via a callback function and assigns\n    each result to an element in an output double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - indices: strided array indices (offset + idx*stride).\n    - arrays: input and output arrays.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Float64Array\n        Destination array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > function clbk( v ) { return v; };\n    > strided.dcbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    <Float64Array>[ 1.0, ~2.08, -3.0, ~4.327 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.dcbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    <Float64Array>[ 0.0, 0.0, ~4.327, ~2.08 ]\n\n    See Also\n    --------\n    strided.cbrt","strided.dispatch":"\nstrided.dispatch( fcns, types, data, nargs, nin, nout )\n    Returns a strided array function interface which performs multiple dispatch.\n\n    Without offsets, a strided array function interface has the following\n    signature:\n\n      f( N, dtypeX, x, strideX, dtypeY, y, strideY, ... )\n\n    where\n\n    - N: number of indexed elements.\n    - dtypeX: data type for `x`.\n    - x: strided array.\n    - strideX: index increment for `x`.\n    - dtypeY: data type for `y`.\n    - y: strided array.\n    - strideY: index increment for `y`.\n    - ...: additional strided arrays, data types, and associated strides.\n\n    The number of parameters is derived from `nargs`, the number of input\n    strided arrays is derived from `nin`, and the number of output strided\n    arrays is derived from `nout`.\n\n    Without offsets, the number of parameters must obey the following relation:\n\n      nargs = 3*(nout+nin) + 1\n\n    With offsets, the number of parameters must obey the following relation:\n\n      nargs = 4*(nout+nin) + 1\n\n    With offsets, a strided array function interface has the following\n    signature:\n\n      f( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY, ... )\n\n    where\n\n    - N: number of indexed elements.\n    - dtypeX: data type for `x`.\n    - x: strided array.\n    - strideX: index increment for `x`.\n    - offsetX: starting index for `x`.\n    - dtypeY: data type for `y`.\n    - y: strided array.\n    - strideY: index increment for `y`.\n    - offsetY: starting index for `y`.\n    - ...: additional strided arrays and associated data types, strides, and\n      offsets.\n\n    The choice of which strided array function interface to return depends on\n    the use case. The former is suitable for typed array views; while the latter\n    affords alternative indexing semantics more suitable for n-dimensional\n    arrays (ndarrays).\n\n    Parameters\n    ----------\n    fcns: Function|ArrayLikeObject<Function>\n        List of strided array functions. Without offsets, a strided array\n        function should have the following signature:\n\n          f( arrays, shape, strides, data )\n\n        where\n\n        - arrays: array containing strided input and output arrays.\n        - shape: array containing a single element, the number of indexed\n          elements.\n        - strides: array containing the stride lengths for the strided input and\n          output arrays.\n        - data: strided array function data (e.g., a callback).\n\n        With offsets, a strided array function should have the following\n        signature:\n\n          f( arrays, shape, strides, offsets, data )\n\n        where\n\n        - offsets: array containing the starting indices (i.e., index offsets)\n          for the strided input and output arrays.\n\n        For convenience, a single strided array function may be provided which\n        will be invoked whenever the strided array argument data types match a\n        sequence of types in `types`. Providing a single strided array function\n        is particularly convenient for the case where, regardless of array data\n        types, traversing arrays remains the same, but the strided array\n        function `data` differs (e.g., callbacks which differ based on the array\n        data types).\n\n    types: ArrayLikeObject\n        One-dimensional list of strided array argument data types.\n\n    data: ArrayLikeObject|null\n        Strided array function data (e.g., callbacks). If `null`, a returned\n        strided array function interface does **not** provide a `data` argument\n        to an invoked strided array function.\n\n    nargs: integer\n        Total number of strided array function interface arguments (including\n        data types, strides, and offsets).\n\n    nin: integer\n        Number of input strided arrays.\n\n    nout: integer\n        Number of output strided arrays.\n\n    Returns\n    -------\n    fcn: Function\n        Strided array function interface.\n\n    Examples\n    --------\n    // Define strided array argument data types:\n    > var t = [ 'float64', 'float64', 'float32', 'float32' ];\n\n    // Define a list of strided array function data (callbacks):\n    > var d = [ base.abs, base.absf ];\n\n    // Create a strided array function interface for applying unary callbacks:\n    > var f = strided.dispatch( base.strided.unary, t, d, 7, 1, 1 );\n\n    // Create an input strided array:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n    // Create an output strided array:\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n    // Compute the element-wise absolute value:\n    > f( x.length, 'float64', x, 1, 'float64', y, 1 );\n    > y\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Create a strided array function interface supporting offsets:\n    > f = strided.dispatch( base.strided.unary.ndarray, t, d, 9, 1, 1 );\n\n    // Create an input strided array:\n    > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n    // Create an output strided array:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n    // Compute the element-wise absolute value starting from the third element:\n    > f( 2, 'float64', x, 1, 2, 'float64', y, 1, 2 );\n    > y\n    <Float64Array>[ 0.0, 0.0, 3.0, 4.0 ]\n\n","strided.dispatchBy":"\nstrided.dispatchBy( fcns, types, data, nargs, nin, nout )\n    Returns a strided array function interface which accepts a callback function\n    and performs multiple dispatch.\n\n    Without offsets, a strided array function interface has the following\n    signature:\n\n      f( N, dx, x, sx, dy, y, sy, ..., clbk[, thisArg] )\n\n    where\n\n    - N: number of indexed elements.\n    - dx: data type for `x`.\n    - x: strided array.\n    - sx: index increment for `x`.\n    - dy: data type for `y`.\n    - y: strided array.\n    - sy: index increment for `y`.\n    - ...: additional strided arrays, data types, and associated strides.\n    - clbk: callback function.\n    - thisArg: callback function execution context.\n\n    The number of parameters is derived from `nargs`, the number of input\n    strided arrays is derived from `nin`, and the number of output strided\n    arrays is derived from `nout`.\n\n    Without offsets, the number of parameters must obey the following relation:\n\n      nargs = 3*(nout+nin) + 2\n\n    With offsets, the number of parameters must obey the following relation:\n\n      nargs = 4*(nout+nin) + 2\n\n    With offsets, a strided array function interface has the following\n    signature:\n\n      f( N, dx, x, sx, ox, dy, y, sy, oy, ..., clbk[, thisArg] )\n\n    where\n\n    - N: number of indexed elements.\n    - dx: data type for `x`.\n    - x: strided array.\n    - sx: index increment for `x`.\n    - ox: starting index for `x`.\n    - dy: data type for `y`.\n    - y: strided array.\n    - sy: index increment for `y`.\n    - oy: starting index for `y`.\n    - ...: additional strided arrays and associated data types, strides, and\n      offsets.\n    - clbk: callback function.\n    - thisArg: callback function execution context.\n\n    The choice of which strided array function interface to return depends on\n    the use case. The former is suitable for typed array views; while the latter\n    affords alternative indexing semantics more suitable for n-dimensional\n    arrays (ndarrays).\n\n    Parameters\n    ----------\n    fcns: Function|ArrayLikeObject<Function>\n        List of strided array functions. Without offsets, a strided array\n        function should have the following signature:\n\n          f( arrays, shape, strides, data, clbk, thisArg )\n\n        where\n\n        - arrays: array containing strided input and output arrays.\n        - shape: array containing a single element, the number of indexed\n          elements.\n        - strides: array containing the stride lengths for the strided input and\n          output arrays.\n        - data: strided array function data (e.g., a callback).\n        - clbk: callback function.\n        - thisArg: callback function execution context.\n\n        With offsets, a strided array function should have the following\n        signature:\n\n          f( arrays, shape, strides, offsets, data, clbk, thisArg )\n\n        where\n\n        - offsets: array containing the starting indices (i.e., index offsets)\n          for the strided input and output arrays.\n\n        For convenience, a single strided array function may be provided which\n        will be invoked whenever the strided array argument data types match a\n        sequence of types in `types`. Providing a single strided array function\n        is particularly convenient for the case where, regardless of array data\n        types, traversing arrays remains the same, but the strided array\n        function `data` differs (e.g., callbacks which differ based on the array\n        data types).\n\n    types: ArrayLikeObject\n        One-dimensional list of strided array argument data types.\n\n    data: ArrayLikeObject|null\n        Strided array function data (e.g., callbacks). If `null`, a returned\n        strided array function interface does **not** provide a `data` argument\n        to an invoked strided array function.\n\n    nargs: integer\n        Total number of strided array function interface arguments (including\n        data types, strides, offsets, and the callback function).\n\n    nin: integer\n        Number of input strided arrays.\n\n    nout: integer\n        Number of output strided arrays.\n\n    Returns\n    -------\n    fcn: Function\n        Strided array function interface.\n\n    Examples\n    --------\n    // Define strided array argument data types:\n    > var t = [ 'float64', 'float64', 'float32', 'float32' ];\n\n    // Define a list of strided array function data (callbacks):\n    > var d = [ base.abs, base.absf ];\n\n    // Create a strided array function interface for applying unary callbacks:\n    > var f = strided.dispatchBy( base.strided.unaryBy, t, d, 8, 1, 1 );\n\n    // Create an input strided array:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n    // Create an output strided array:\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n    // Compute the element-wise absolute value:\n    > f( x.length, 'float64', x, 1, 'float64', y, 1, base.identity );\n    > y\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Create a strided array function interface supporting offsets:\n    > f = strided.dispatchBy( base.strided.unary.ndarray, t, d, 10, 1, 1 );\n\n    // Create an input strided array:\n    > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n    // Create an output strided array:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n    // Compute the element-wise absolute value starting from the third element:\n    > f( 2, 'float64', x, 1, 2, 'float64', y, 1, 2, base.identity );\n    > y\n    <Float64Array>[ 0.0, 0.0, 3.0, 4.0 ]\n\n    See Also\n    --------\n    strided.dispatch\n","strided.floor":"\nstrided.floor( N, dtypeX, x, strideX, dtypeY, y, strideY )\n    Rounds each element in a strided array `x` toward negative infinity and\n    assigns the results to elements in a strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.floor( x.length, 'float64', x, 1, 'float64', y, 1 )\n    <Float64Array>[ -2.0, 2.0, -4.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.floor( 2, 'float64', x, 2, 'float64', y, -1 )\n    <Float64Array>[ -4.0, -2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.floor( 2, 'float64', x1, -2, 'float64', y1, 1 )\n    <Float64Array>[ 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nstrided.floor.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Rounds each element in a strided array `x` toward negative infinity and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.floor.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ -2.0, 2.0, -4.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.floor.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    strided.ceil, base.strided.dfloor, strided.trunc, base.strided.sfloor\n","strided.floor.ndarray":"\nstrided.floor.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Rounds each element in a strided array `x` toward negative infinity and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.floor.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ -2.0, 2.0, -4.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.floor.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    strided.ceil, base.strided.dfloor, strided.trunc, base.strided.sfloor","strided.inv":"\nstrided.inv( N, dtypeX, x, strideX, dtypeY, y, strideY )\n    Computes the multiplicative inverse for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.inv( x.length, 'float64', x, 1, 'float64', y, 1 )\n    <Float64Array>[ -0.05, -1.0, 0.5, 0.25 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.inv( 2, 'float64', x, 2, 'float64', y, -1 )\n    <Float64Array>[ 0.5, -0.05, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.inv( 2, 'float64', x1, -2, 'float64', y1, 1 )\n    <Float64Array>[ 0.25, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n\nstrided.inv.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the multiplicative inverse for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.inv.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ -0.05, -1.0, 0.5, 0.25 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.inv.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dinv, base.strided.sinv\n","strided.inv.ndarray":"\nstrided.inv.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the multiplicative inverse for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.inv.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ -0.05, -1.0, 0.5, 0.25 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.inv.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dinv, base.strided.sinv","strided.mul":"\nstrided.mul( N, dx, x, sx, dy, y, sy, dz, z, sz )\n    Multiplies each element in a strided array `x` to a corresponding element in\n    a strided array `y` and assigns the results to elements in a strided array\n    `z`.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dx: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    dy: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    dz: any\n        Data type for `z`.\n\n    z: ArrayLikeObject\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    Returns\n    -------\n    z: ArrayLikeObject\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var dt = 'float64';\n    > strided.mul( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\n    <Float64Array>[ -2.0, 2.0, 9.0, -20.0 ]\n\n    // Using `N` and stride parameters:\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.mul( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\n    <Float64Array>[ -6.0, 3.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > strided.mul( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\n    <Float64Array>[ -15.0, 4.0 ]\n    > z0\n    <Float64Array>[ 0.0, 0.0, -15.0, 4.0 ]\n\n\nstrided.mul.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n    Multiplies each element in a strided array `x` to a corresponding element in\n    a strided array `y` and assigns the results to elements in a strided array\n    `z` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dx: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    dy: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    dz: any\n        Data type for `z`.\n\n    z: ArrayLikeObject\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    Returns\n    -------\n    z: ArrayLikeObject\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var dt = 'float64';\n    > strided.mul.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n    <Float64Array>[ -2.0, 2.0, 9.0, -20.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.mul.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n    <Float64Array>[ 0.0, 4.0, -15.0, 0.0 ]\n\n    See Also\n    --------\n    strided.add, strided.sub\n","strided.mul.ndarray":"\nstrided.mul.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n    Multiplies each element in a strided array `x` to a corresponding element in\n    a strided array `y` and assigns the results to elements in a strided array\n    `z` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dx: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    dy: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    dz: any\n        Data type for `z`.\n\n    z: ArrayLikeObject\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    Returns\n    -------\n    z: ArrayLikeObject\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var dt = 'float64';\n    > strided.mul.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n    <Float64Array>[ -2.0, 2.0, 9.0, -20.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.mul.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n    <Float64Array>[ 0.0, 4.0, -15.0, 0.0 ]\n\n    See Also\n    --------\n    strided.add, strided.sub","strided.mulBy":"\nstrided.mulBy( N, x, sx, y, sy, z, sz, clbk[, thisArg] )\n    Performs element-wise multiplication of two strided arrays via a callback\n    function and assigns each result to an element in an output strided array.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided four arguments:\n\n    - values: input array elements.\n    - idx: iteration index.\n    - indices: strided array indices (offset + idx*stride).\n    - arrays: input and output arrays.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n    > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( values ) { return values; };\n    > strided.mulBy( x.length, x, 1, y, 1, z, 1, clbk )\n    [ 11.0, 24.0, 39.0, 56.0 ]\n\n    // Using `N` and stride parameters:\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.mulBy( 2, x, 2, y, -1, z, 1, clbk )\n    [ 12.0, 33.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\n    > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > strided.mulBy( 2, x1, -2, y1, 1, z1, 1, clbk )\n    <Float64Array>[ 52.0, 28.0 ]\n    > z0\n    <Float64Array>[ 0.0, 0.0, 52.0, 28.0 ]\n\n\nstrided.mulBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n    Performs element-wise multiplication of two strided arrays via a callback\n    function and assigns each result to an element in an output strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n    > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( values ) { return values; };\n    > strided.mulBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n    [ 11.0, 24.0, 39.0, 56.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0 ];\n    > y = [ 11.0, 12.0, 13.0, 14.0 ];\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > var oy = y.length - 1;\n    > var oz = z.length - 1;\n    > strided.mulBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n    [ 0.0, 0.0, 52.0, 28.0 ]\n\n    See Also\n    --------\n    strided.mul, strided.addBy, strided.subBy\n","strided.mulBy.ndarray":"\nstrided.mulBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n    Performs element-wise multiplication of two strided arrays via a callback\n    function and assigns each result to an element in an output strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n    > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( values ) { return values; };\n    > strided.mulBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n    [ 11.0, 24.0, 39.0, 56.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0 ];\n    > y = [ 11.0, 12.0, 13.0, 14.0 ];\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > var oy = y.length - 1;\n    > var oz = z.length - 1;\n    > strided.mulBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n    [ 0.0, 0.0, 52.0, 28.0 ]\n\n    See Also\n    --------\n    strided.mul, strided.addBy, strided.subBy","strided.ramp":"\nstrided.ramp( N, dtypeX, x, strideX, dtypeY, y, strideY )\n    Evaluates the ramp function for each element in a strided array `x` and\n    assigns the results to elements in a strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ramp( x.length, 'float64', x, 1, 'float64', y, 1 )\n    <Float64Array>[ 1.1, 2.5, 0.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ramp( 2, 'float64', x, 2, 'float64', y, -1 )\n    <Float64Array>[ 0.0, 1.1, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.ramp( 2, 'float64', x1, -2, 'float64', y1, 1 )\n    <Float64Array>[ 4.0, 2.5 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.5 ]\n\n\nstrided.ramp.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Evaluates the ramp function for each element in a strided array `x` and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ramp.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 1.1, 2.5, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ramp.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.5 ]\n\n    See Also\n    --------\n    base.strided.dramp, base.strided.sramp\n","strided.ramp.ndarray":"\nstrided.ramp.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Evaluates the ramp function for each element in a strided array `x` and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ramp.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 1.1, 2.5, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ramp.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.5 ]\n\n    See Also\n    --------\n    base.strided.dramp, base.strided.sramp","strided.rsqrt":"\nstrided.rsqrt( N, dtypeX, x, strideX, dtypeY, y, strideY )\n    Computes the reciprocal square root for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.rsqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\n    <Float64Array>[ Infinity, 0.5, ~0.333, ~0.289 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.rsqrt( 2, 'float64', x, 2, 'float64', y, -1 )\n    <Float64Array>[ ~0.333, Infinity, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.rsqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\n    <Float64Array>[ ~0.289, 0.5 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nstrided.rsqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the reciprocal square root for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.rsqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ Infinity, 0.5, ~0.333, ~0.289 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.rsqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n    See Also\n    --------\n    base.strided.drsqrt, strided.sqrt, base.strided.srsqrt\n","strided.rsqrt.ndarray":"\nstrided.rsqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the reciprocal square root for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.rsqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ Infinity, 0.5, ~0.333, ~0.289 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.rsqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n    See Also\n    --------\n    base.strided.drsqrt, strided.sqrt, base.strided.srsqrt","strided.sinBy":"\nstrided.sinBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the sine of each element retrieved from an input strided array `x`\n    via a callback function and assigns each result to an element in an output\n    strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.sinBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, ~0.002, ~-0.002, ~-0.544 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.sinBy( 2, x, 2, y, -1, clbk )\n    [ ~-0.002, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 3.14, -3.14, 10.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.sinBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~-0.544, ~0.002 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~-0.544, ~0.002 ]\n\n\nstrided.sinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the sine of each element retrieved from an input strided array `x`\n    via a callback function and assigns each result to an element in an output\n    strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.sinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~0.002, ~-0.002, ~-0.544 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 3.14, -3.14, 10.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.sinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.544, ~0.002 ]\n\n","strided.sinBy.ndarray":"\nstrided.sinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the sine of each element retrieved from an input strided array `x`\n    via a callback function and assigns each result to an element in an output\n    strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.sinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~0.002, ~-0.002, ~-0.544 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 3.14, -3.14, 10.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.sinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.544, ~0.002 ]","strided.sqrt":"\nstrided.sqrt( N, dtypeX, x, strideX, dtypeY, y, strideY )\n    Computes the principal square root for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.sqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\n    <Float64Array>[ 0.0, 2.0, 3.0, ~3.464 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.sqrt( 2, 'float64', x, 2, 'float64', y, -1 )\n    <Float64Array>[ 3.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.sqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\n    <Float64Array>[ ~3.464, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nstrided.sqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the principal square root for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.sqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 0.0, 2.0, 3.0, ~3.464 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.sqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n    See Also\n    --------\n    strided.cbrt, base.strided.dsqrt, strided.rsqrt, base.strided.ssqrt\n","strided.sqrt.ndarray":"\nstrided.sqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the principal square root for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.sqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 0.0, 2.0, 3.0, ~3.464 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.sqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n    See Also\n    --------\n    strided.cbrt, base.strided.dsqrt, strided.rsqrt, base.strided.ssqrt","strided.sqrtBy":"\nstrided.sqrtBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the principal square root for each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 122.0, 50.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.sqrtBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, 1.0, ~11.045, ~7.071 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.sqrtBy( 2, x, 2, y, -1, clbk )\n    [ ~11.045, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 1.0, 122.0, 50.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.sqrtBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~7.071, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~7.071, 1.0 ]\n\n\nstrided.sqrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the principal square root for each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 122.0, 50.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.sqrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, 1.0, ~11.045, ~7.071 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 122.0, 50.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.sqrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~7.071, 1.0 ]\n\n    See Also\n    --------\n    strided.sqrt\n","strided.sqrtBy.ndarray":"\nstrided.sqrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the principal square root for each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 122.0, 50.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.sqrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, 1.0, ~11.045, ~7.071 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 122.0, 50.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.sqrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~7.071, 1.0 ]\n\n    See Also\n    --------\n    strided.sqrt","strided.sub":"\nstrided.sub( N, dx, x, sx, dy, y, sy, dz, z, sz )\n    Subtracts each element in a strided array `x` to a corresponding element in\n    a strided array `y` and assigns the results to elements in a strided array\n    `z`.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dx: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    dy: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    dz: any\n        Data type for `z`.\n\n    z: ArrayLikeObject\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    Returns\n    -------\n    z: ArrayLikeObject\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var dt = 'float64';\n    > strided.sub( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\n    <Float64Array>[ -3.0, -1.0, 0.0, -9.0 ]\n\n    // Using `N` and stride parameters:\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.sub( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\n    <Float64Array>[ -5.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > strided.sub( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\n    <Float64Array>[ -8.0, -3.0 ]\n    > z0\n    <Float64Array>[ 0.0, 0.0, -8.0, -3.0 ]\n\n\nstrided.sub.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n    Subtracts each element in a strided array `x` to a corresponding element in\n    a strided array `y` and assigns the results to elements in a strided array\n    `z` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dx: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    dy: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    dz: any\n        Data type for `z`.\n\n    z: ArrayLikeObject\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    Returns\n    -------\n    z: ArrayLikeObject\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var dt = 'float64';\n    > strided.sub.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n    <Float64Array>[ -3.0, -1.0, 0.0, -9.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.sub.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n    <Float64Array>[ 0.0, -3.0, -8.0, 0.0 ]\n\n    See Also\n    --------\n    strided.add, strided.mul\n","strided.sub.ndarray":"\nstrided.sub.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n    Subtracts each element in a strided array `x` to a corresponding element in\n    a strided array `y` and assigns the results to elements in a strided array\n    `z` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dx: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    dy: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    dz: any\n        Data type for `z`.\n\n    z: ArrayLikeObject\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    Returns\n    -------\n    z: ArrayLikeObject\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var dt = 'float64';\n    > strided.sub.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n    <Float64Array>[ -3.0, -1.0, 0.0, -9.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.sub.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n    <Float64Array>[ 0.0, -3.0, -8.0, 0.0 ]\n\n    See Also\n    --------\n    strided.add, strided.mul","strided.subBy":"\nstrided.subBy( N, x, sx, y, sy, z, sz, clbk[, thisArg] )\n    Performs element-wise subtraction of two strided arrays via a callback\n    function and assigns each result to an element in an output strided array.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided four arguments:\n\n    - values: input array elements.\n    - idx: iteration index.\n    - indices: strided array indices (offset + idx*stride).\n    - arrays: input and output arrays.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 11.0, 12.0, 13.0, 14.0 ];\n    > var y = [ 8.0, 7.0, 6.0, 5.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( values ) { return values; };\n    > strided.subBy( x.length, x, 1, y, 1, z, 1, clbk )\n    [ 3.0, 5.0, 7.0, 9.0 ]\n\n    // Using `N` and stride parameters:\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.subBy( 2, x, 2, y, -1, z, 1, clbk )\n    [ 4.0, 5.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\n    > var y0 = new Float64Array( [ 8.0, 7.0, 6.0, 5.0 ] );\n    > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > strided.subBy( 2, x1, -2, y1, 1, z1, 1, clbk )\n    <Float64Array>[ 8.0, 7.0 ]\n    > z0\n    <Float64Array>[ 0.0, 0.0, 8.0, 7.0 ]\n\n\nstrided.subBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n    Performs element-wise subtraction of two strided arrays via a callback\n    function and assigns each result to an element in an output strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 11.0, 12.0, 13.0, 14.0 ];\n    > var y = [ 8.0, 7.0, 6.0, 5.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( values ) { return values; };\n    > strided.subBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n    [ 3.0, 5.0, 7.0, 9.0 ]\n\n    // Advanced indexing:\n    > x = [ 11.0, 12.0, 13.0, 14.0 ];\n    > y = [ 8.0, 7.0, 6.0, 5.0 ];\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > var oy = y.length - 1;\n    > var oz = z.length - 1;\n    > strided.subBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n    [ 0.0, 0.0, 8.0, 7.0 ]\n\n    See Also\n    --------\n    strided.sub, strided.addBy, strided.mulBy\n","strided.subBy.ndarray":"\nstrided.subBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n    Performs element-wise subtraction of two strided arrays via a callback\n    function and assigns each result to an element in an output strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 11.0, 12.0, 13.0, 14.0 ];\n    > var y = [ 8.0, 7.0, 6.0, 5.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( values ) { return values; };\n    > strided.subBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n    [ 3.0, 5.0, 7.0, 9.0 ]\n\n    // Advanced indexing:\n    > x = [ 11.0, 12.0, 13.0, 14.0 ];\n    > y = [ 8.0, 7.0, 6.0, 5.0 ];\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > var oy = y.length - 1;\n    > var oz = z.length - 1;\n    > strided.subBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n    [ 0.0, 0.0, 8.0, 7.0 ]\n\n    See Also\n    --------\n    strided.sub, strided.addBy, strided.mulBy","strided.trunc":"\nstrided.trunc( N, dtypeX, x, strideX, dtypeY, y, strideY )\n    Rounds each element in a strided array `x` toward zero and assigns the\n    results to elements in a strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.trunc( x.length, 'float64', x, 1, 'float64', y, 1 )\n    <Float64Array>[ 1.0, 2.0, -3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.trunc( 2, 'float64', x, 2, 'float64', y, -1 )\n    <Float64Array>[ -3.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.trunc( 2, 'float64', x1, -2, 'float64', y1, 1 )\n    <Float64Array>[ 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nstrided.trunc.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Rounds each element in a strided array `x` toward zero and assigns the\n    results to elements in a strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.trunc.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.trunc.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    strided.ceil, base.strided.dtrunc, strided.floor, base.strided.strunc\n","strided.trunc.ndarray":"\nstrided.trunc.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Rounds each element in a strided array `x` toward zero and assigns the\n    results to elements in a strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.trunc.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.trunc.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    strided.ceil, base.strided.dtrunc, strided.floor, base.strided.strunc","stridedarray2iterator":"\nstridedarray2iterator( N, src, stride, offset[, mapFcn[, thisArg]] )\n    Returns an iterator which iterates over elements of an array-like object\n    according to specified stride parameters.\n\n    When invoked, an input function is provided four arguments:\n\n    - value: iterated value.\n    - index: iterated value index.\n    - n: iteration count (zero-based).\n    - src: source array-like object.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an array's `@@iterator` method, regardless of whether this method is\n    defined. To convert an array to an implementation defined iterator, invoke\n    this method directly.\n\n    Parameters\n    ----------\n    N: integer\n        Number of values to iterate.\n\n    src: ArrayLikeObject\n        Array-like object from which to create the iterator.\n\n    stride: integer\n        Stride length.\n\n    offset: integer\n        Starting index.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = stridedarray2iterator( 2, [ 1, 2, 3, 4 ], -2, 3 );\n    > var v = it.next().value\n    4\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    iterator2array, array2iterator\n","stridedArrayStream":"\nstridedArrayStream( N, buffer, stride, offset[, options] )\n    Creates a readable stream from a strided array-like object.\n\n    In object mode, `null` is a reserved value. If an array contains `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or filter `null` values\n    prior to invocation.\n\n    In binary mode, if an array contains `undefined` values, the stream will\n    emit an error. Consider providing a custom serialization function or\n    filtering `undefined` values prior to invocation.\n\n    If a serialization function fails to return a string or Buffer, the stream\n    emits an error.\n\n    Parameters\n    ----------\n    N: integer\n        Number of values to stream.\n\n    buffer: ArrayLikeObject\n        Array-like object from which to create the stream.\n\n    stride: integer\n        Stride length.\n\n    offset: integer\n        Starting index.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing the stream.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize streamed\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var s = stridedArrayStream( 3, [ 1, 2, 3 ], 1, 0 );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nstridedArrayStream.factory( [options] )\n    Returns a function for creating readable streams from array-like objects.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing streaming.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize streamed\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = stridedArrayStream.factory( opts );\n\n\nstridedArrayStream.objectMode( N, buffer, stride, offset[, options] )\n    Returns an \"objectMode\" readable stream from a strided array-like object.\n\n    In object mode, `null` is a reserved value. If an array contains `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or filter `null` values\n    prior to invocation.\n\n    Parameters\n    ----------\n    N: integer\n        Number of values to stream.\n\n    buffer: ArrayLikeObject\n        Array-like object from which to create the stream.\n\n    stride: integer\n        Stride length.\n\n    offset: integer\n        Starting index.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before pausing streaming.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var s = stridedArrayStream.objectMode( 3, [ 1, 2, 3 ], 1, 0 );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    arrayStream\n","stridedArrayStream.factory":"\nstridedArrayStream.factory( [options] )\n    Returns a function for creating readable streams from array-like objects.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing streaming.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize streamed\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = stridedArrayStream.factory( opts );","stridedArrayStream.objectMode":"\nstridedArrayStream.objectMode( N, buffer, stride, offset[, options] )\n    Returns an \"objectMode\" readable stream from a strided array-like object.\n\n    In object mode, `null` is a reserved value. If an array contains `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or filter `null` values\n    prior to invocation.\n\n    Parameters\n    ----------\n    N: integer\n        Number of values to stream.\n\n    buffer: ArrayLikeObject\n        Array-like object from which to create the stream.\n\n    stride: integer\n        Stride length.\n\n    offset: integer\n        Starting index.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before pausing streaming.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var s = stridedArrayStream.objectMode( 3, [ 1, 2, 3 ], 1, 0 );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    arrayStream","string2buffer":"\nstring2buffer( str[, encoding] )\n    Allocates a buffer containing a provided string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    encoding: string (optional)\n        Character encoding. Default: 'utf8'.\n\n    Returns\n    -------\n    out: Buffer\n        Buffer instance.\n\n    Examples\n    --------\n    > var b = string2buffer( 'beep boop' )\n    <Buffer>\n    > b = string2buffer( '7468697320697320612074c3a97374', 'hex' );\n    > b.toString()\n    'this is a tést'\n\n    See Also\n    --------\n    Buffer, array2buffer, arraybuffer2buffer, copyBuffer\n","sub2ind":"\nsub2ind( shape, ...subscript[, options] )\n    Converts subscripts to a linear index.\n\n    Parameters\n    ----------\n    shape: ArrayLike\n        Array shape.\n\n    subscript: ...integer\n        Subscripts.\n\n    options: Object (optional)\n        Options.\n\n    options.order: string (optional)\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran style). Default: 'row-major'.\n\n    options.mode: string|Array<string> (optional)\n        Specifies how to handle subscripts which exceed array dimensions. If\n        equal to 'throw', the function throws an error when a subscript exceeds\n        array dimensions. If equal to 'normalize', the function normalizes\n        negative subscripts and throws an error when a subscript exceeds array\n        dimensions. If equal to 'wrap', the function wraps around subscripts\n        exceeding array dimensions using modulo arithmetic. If equal to\n        'clamp', the function sets subscripts exceeding array dimensions to\n        either `0` (minimum index) or the maximum index along a particular\n        dimension. If provided a mode array, each array element specifies the\n        mode for a corresponding array dimension. If provided fewer modes than\n        dimensions, the function recycles modes using modulo arithmetic.\n        Default: [ 'throw' ].\n\n    Returns\n    -------\n    idx: integer\n        Linear index.\n\n    Examples\n    --------\n    > var d = [ 3, 3, 3 ];\n    > var idx = sub2ind( d, 1, 2, 2 )\n    17\n\n    See Also\n    --------\n    array, ndarray, ind2sub\n","substringAfter":"\nsubstringAfter( str, search[, fromIndex] )\n    Returns the part of a string after a specified substring.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search string.\n\n    fromIndex: integer (optional)\n        Index from which to start the search. Default: `0`.\n\n    Returns\n    -------\n    out: string\n        Substring.\n\n    Examples\n    --------\n    > var out = substringAfter( 'Hello World!', 'World' )\n    '!'\n    > out = substringAfter( 'Hello World!', 'Hello ' )\n    'World!'\n    > out = substringAfter( 'Hello World!', 'l', 5 )\n    'd!'\n\n    See Also\n    --------\n    substringBefore, substringBeforeLast, substringAfterLast","substringAfterLast":"\nsubstringAfterLast( str, search[, fromIndex] )\n    Returns the part of a string after the last occurrence of a specified\n    substring.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search value.\n\n    fromIndex: integer (optional)\n        Index of last character to be considered beginning of a match.\n        Default: `str.length`.\n\n    Returns\n    -------\n    out: string\n        Substring.\n\n    Examples\n    --------\n    > var out = substringAfterLast( 'beep boop beep baz', 'beep' )\n    ' baz'\n    > out = substringAfterLast( 'Hello World!', 'Hello ' )\n    'World!'\n    > out = substringAfterLast( 'Hello World!', 'o', 5 )\n    ' World!'\n\n    See Also\n    --------\n    substringBefore, substringBeforeLast, substringAfter","substringBefore":"\nsubstringBefore( str, search )\n    Returns the part of a string before a specified substring.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search string.\n\n    Returns\n    -------\n    out: string\n        Substring.\n\n    Examples\n    --------\n    > var str = 'beep boop';\n    > var out = substringBefore( str, ' ' )\n    'beep'\n    > out = substringBefore( str, 'o' )\n    'beep b'\n\n    See Also\n    --------\n    substringBeforeLast, substringAfter, substringAfterLast","substringBeforeLast":"\nsubstringBeforeLast( str, search )\n    Returns the part of a string before the last occurrence of a specified\n    substring.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search value.\n\n    Returns\n    -------\n    out: string\n        Substring.\n\n    Examples\n    --------\n    > var str = 'Beep Boop Beep';\n    > var out = substringBeforeLast( str, 'Beep' )\n    'Beep Boop '\n    > out = substringBeforeLast( str, 'Boop' )\n    'Beep '\n\n    See Also\n    --------\n    substringBefore, substringAfter, substringAfterLast","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n    Returns a dataset consisting of labeled wireless sensor network data set\n    collected from a multi-hop wireless sensor network deployment using TelosB\n    motes.\n\n    Humidity and temperature measurements were collected at 5 second intervals\n    over a six hour period on July 10, 2010.\n\n    Temperature is in degrees Celsius.\n\n    Humidity is temperature corrected relative humidity, ranging from 0-100%.\n\n    The label '0' denotes normal data, and the label '1' denotes an introduced\n    event.\n\n    If a mote was an indoor sensor, the corresponding indicator is '1'. If a\n    mote was an outdoor sensor, the indoor indicator is '0'.\n\n    Returns\n    -------\n    out: Array<Object>\n        Sensor data.\n\n    Examples\n    --------\n    > var data = SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n    [{...}, {...}, ...]\n\n    References\n    ----------\n    - Suthaharan, Shan, Mohammed Alzahrani, Sutharshan Rajasegarar, Christopher\n    Leckie, and Marimuthu Palaniswami. 2010. \"Labelled data collection for\n    anomaly detection in wireless sensor networks.\" In _Proceedings of the Sixth\n    International Conference on Intelligent Sensors, Sensor Networks and\n    Information Processing (ISSNIP 2010)_. Brisbane, Australia: IEEE.\n\n    * If you use the data for publication or third party consumption, please\n    cite the listed reference.\n\n    See Also\n    --------\n    SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK\n","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n    Returns a dataset consisting of labeled wireless sensor network data set\n    collected from a simple single-hop wireless sensor network deployment using\n    TelosB motes.\n\n    Humidity and temperature measurements were collected at 5 second intervals\n    over a six hour period on May 9, 2010.\n\n    Temperature is in degrees Celsius.\n\n    Humidity is temperature corrected relative humidity, ranging from 0-100%.\n\n    The label '0' denotes normal data, and the label '1' denotes an introduced\n    event.\n\n    If a mote was an indoor sensor, the corresponding indicator is '1'. If a\n    mote was an outdoor sensor, the indoor indicator is '0'.\n\n    Returns\n    -------\n    out: Array<Object>\n        Sensor data.\n\n    Examples\n    --------\n    > var data = SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n    [{...}, {...}, ...]\n\n    References\n    ----------\n    - Suthaharan, Shan, Mohammed Alzahrani, Sutharshan Rajasegarar, Christopher\n    Leckie, and Marimuthu Palaniswami. 2010. \"Labelled data collection for\n    anomaly detection in wireless sensor networks.\" In _Proceedings of the Sixth\n    International Conference on Intelligent Sensors, Sensor Networks and\n    Information Processing (ISSNIP 2010)_. Brisbane, Australia: IEEE.\n\n    * If you use the data for publication or third party consumption, please\n    cite the listed reference.\n\n    See Also\n    --------\n    SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK\n","Symbol":"\nSymbol( [description] )\n    Returns a symbol.\n\n    Unlike conventional constructors, this function does **not** support the\n    `new` keyword.\n\n    This function is only supported in environments which support symbols.\n\n    Parameters\n    ----------\n    description: string (optional)\n        Symbol description which can be used for debugging but not to access the\n        symbol itself.\n\n    Returns\n    -------\n    out: symbol\n        Symbol.\n\n    Examples\n    --------\n    > var s = ( Symbol ) ? Symbol( 'beep' ) : null\n\n","tabulate":"\ntabulate( collection )\n    Generates a frequency table.\n\n    The table is an array of arrays where each sub-array corresponds to a unique\n    value in the input collection. Each sub-array is structured as follows:\n\n    - 0: unique value.\n    - 1: value count.\n    - 2: frequency percentage.\n\n    If provided an empty collection, the function returns an empty array.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection to tabulate. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    Returns\n    -------\n    out: Array<Array>|Array\n        Frequency table.\n\n    Examples\n    --------\n    > var collection = [ 'beep', 'boop', 'foo', 'beep' ];\n    > var out = tabulate( collection )\n    [ [ 'beep', 2, 0.5 ], [ 'boop', 1, 0.25 ], [ 'foo', 1, 0.25 ] ]\n\n    See Also\n    --------\n    countBy, groupBy, tabulateBy\n","tabulateBy":"\ntabulateBy( collection, [options,] indicator )\n    Generates a frequency table according to an indicator function.\n\n    When invoked, the indicator function is provided two arguments:\n\n    - value: collection value.\n    - index: collection index.\n\n    The table is an array of arrays where each sub-array corresponds to a unique\n    value in the input collection. Each sub-array is structured as follows:\n\n    - 0: unique value.\n    - 1: value count.\n    - 2: frequency percentage.\n\n    If provided an empty collection, the function returns an empty array.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection to tabulate. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Options.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    indicator: Function\n        Indicator function specifying how to categorize a collection element.\n\n    Returns\n    -------\n    out: Array<Array>|Array\n        Frequency table.\n\n    Examples\n    --------\n    > function indicator( value ) { return value[ 0 ]; };\n    > var collection = [ 'beep', 'boop', 'foo', 'beep' ];\n    > var out = tabulateBy( collection, indicator )\n    [ [ 'b', 3, 0.75 ], [ 'f', 1, 0.25 ] ]\n\n    See Also\n    --------\n    countBy, groupBy, tabulate\n","tabulateByAsync":"\ntabulateByAsync( collection, [options,] indicator, done )\n    Generates a frequency table according to an indicator function.\n\n    The table is an array of arrays where each sub-array corresponds to a unique\n    value in the input collection. Each sub-array is structured as follows:\n\n    - 0: unique value.\n    - 1: value count.\n    - 2: frequency percentage.\n\n    When invoked, the indicator function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If the\n    indicator function accepts two arguments, the indicator function is\n    provided:\n\n    - value\n    - next\n\n    If the indicator function accepts three arguments, the indicator function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other indicator function signature, the indicator function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - group: value group.\n\n    If an indicator function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    If provided an empty collection, the function calls the `done` callback with\n    an empty array as the second argument.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    indicator: Function\n        Indicator function specifying how to categorize a collection element.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000, 750 ];\n    > tabulateByAsync( arr, indicator, done )\n    750\n    1000\n    2500\n    3000\n    [ [ 'odd', 2, 0.5 ], [ 'even', 2, 0.5 ] ]\n\n    // Limit number of concurrent invocations:\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 3000, 2500, 1000, 750 ];\n    > tabulateByAsync( arr, opts, indicator, done )\n    2500\n    3000\n    1000\n    750\n    [ [ 'odd', 2, 0.5 ], [ 'even', 2, 0.5 ] ]\n\n    // Process sequentially:\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 3000, 2500, 1000, 750 ];\n    > tabulateByAsync( arr, opts, indicator, done )\n    3000\n    2500\n    1000\n    750\n    [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n\ntabulateByAsync.factory( [options,] indicator )\n    Returns a function which generates a frequency table according to an\n    indicator function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    indicator: Function\n        Indicator function specifying how to categorize a collection element.\n\n    Returns\n    -------\n    out: Function\n        A function which generates a frequency table according to an indicator\n        function.\n\n    Examples\n    --------\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = tabulateByAsync.factory( opts, indicator );\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000, 750 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    750\n    [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n    > arr = [ 2000, 1500, 1000, 750 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    750\n    [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n    See Also\n    --------\n    countByAsync, groupByAsync, tabulateBy\n","tabulateByAsync.factory":"\ntabulateByAsync.factory( [options,] indicator )\n    Returns a function which generates a frequency table according to an\n    indicator function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    indicator: Function\n        Indicator function specifying how to categorize a collection element.\n\n    Returns\n    -------\n    out: Function\n        A function which generates a frequency table according to an indicator\n        function.\n\n    Examples\n    --------\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = tabulateByAsync.factory( opts, indicator );\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000, 750 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    750\n    [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n    > arr = [ 2000, 1500, 1000, 750 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    750\n    [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n    See Also\n    --------\n    countByAsync, groupByAsync, tabulateBy","thunk":"\nthunk( fcn[, ...args] )\n    Returns a thunk.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to convert to a thunk.\n\n    args: ...any (optional)\n        Function arguments.\n\n    Returns\n    -------\n    out: Function\n        Thunk.\n\n    Examples\n    --------\n    > var fcn = thunk( base.add, 2, 3 );\n    > var v = fcn()\n    5\n    > v = fcn()\n    5\n\n","tic":"\ntic()\n    Returns a high-resolution time.\n\n    The returned array has the following format: `[seconds, nanoseconds]`.\n\n    Returns\n    -------\n    out: Array<integer>\n        High resolution time.\n\n    Examples\n    --------\n    > var t = tic()\n    [ <number>, <number> ]\n\n    See Also\n    --------\n    toc\n","timeit":"\ntimeit( code, [options,] clbk )\n    Times a snippet.\n\n    If the `asynchronous` option is set to `true`, the implementation assumes\n    that `before`, `after`, and `code` snippets are all asynchronous.\n    Accordingly, these snippets should invoke a `next( [error] )` callback\n    once complete. The implementation wraps the snippet within a function\n    accepting two arguments: `state` and `next`.\n\n    The `state` parameter is simply an empty object which allows the `before`,\n    `after`, and `code` snippets to share state.\n\n    Notes:\n\n    - Snippets always run in strict mode.\n    - Always verify results. Doing so prevents the compiler from performing dead\n      code elimination and other optimization techniques, which would render\n      timing results meaningless.\n    - Executed code is not sandboxed and has access to the global state. You are\n      strongly advised against timing untrusted code. To time untrusted code,\n      do so in an isolated environment (e.g., a separate process with restricted\n      access to both global state and the host environment).\n    - Wrapping asynchronous code does add overhead, but, in most cases, the\n      overhead should be negligible compared to the execution cost of the timed\n      snippet.\n    - When the `asynchronous` option is `true`, ensure that the main `code`\n      snippet is actually asynchronous. If a snippet releases the zalgo, an\n      error complaining about exceeding the maximum call stack size is highly\n      likely.\n    - While many benchmark frameworks calculate various statistics over raw\n      timing results (e.g., mean and standard deviation), do not do this.\n      Instead, consider the fastest time an approximate lower bound for how fast\n      an environment can execute a snippet. Slower times are more likely\n      attributable to other processes interfering with timing accuracy rather\n      than attributable to variability in JavaScript's speed. In which case, the\n      minimum time is most likely the only result of interest. When considering\n      all raw timing results, apply common sense rather than statistics.\n\n    Parameters\n    ----------\n    code: string\n         Snippet to time.\n\n    options: Object (optional)\n        Options.\n\n    options.before: string (optional)\n        Setup code. Default: `''`.\n\n    options.after: string (optional)\n        Cleanup code. Default: `''`.\n\n    options.iterations: integer|null (optional)\n        Number of iterations. If `null`, the number of iterations is determined\n        by trying successive powers of `10` until the total time is at least\n        `0.1` seconds. Default: `1e6`.\n\n    options.repeats: integer (optional)\n        Number of repeats. Default: `3`.\n\n    options.asynchronous: boolean (optional)\n        Boolean indicating whether a snippet is asynchronous. Default: `false`.\n\n    clbk: Function\n        Callback to invoke upon completion.\n\n    Examples\n    --------\n    > var code = 'var x = Math.pow( Math.random(), 3 );';\n    > code += 'if ( x !== x ) {';\n    > code += 'throw new Error( \\'Something went wrong.\\' );';\n    > code += '}';\n    > function done( error, results ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.dir( results );\n    ... };\n    > timeit( code, done )\n    e.g.,\n    {\n        \"iterations\": 1000000,\n        \"repeats\": 3,\n        \"min\": [ 0, 135734733 ],    // [seconds,nanoseconds]\n        \"elapsed\": 0.135734733,     // seconds\n        \"rate\": 7367311.062526641,  // iterations/second\n        \"times\": [                  // raw timing results\n            [ 0, 145641393 ],\n            [ 0, 135734733 ],\n            [ 0, 140462721 ]\n        ]\n    }\n\n","tmpdir":"\ntmpdir()\n    Returns the directory for storing temporary files.\n\n    Returns\n    -------\n    dir: string\n        Directory for temporary files.\n\n    Examples\n    --------\n    > var dir = tmpdir()\n    e.g., '/path/to/temporary/files/directory'\n\n    See Also\n    --------\n    configdir, homedir\n","toc":"\ntoc( time )\n    Returns a high-resolution time difference, where `time` is a two-element\n    array with format `[seconds, nanoseconds]`.\n\n    Similar to `time`, the returned array has format `[seconds, nanoseconds]`.\n\n    Parameters\n    ----------\n    time: Array<integer>\n        High-resolution time.\n\n    Returns\n    -------\n    out: Array<integer>\n        High resolution time difference.\n\n    Examples\n    --------\n    > var start = tic();\n    > var delta = toc( start )\n    [ <number>, <number> ]\n\n    See Also\n    --------\n    tic\n","tokenize":"\ntokenize( str[, keepWhitespace] )\n    Tokenizes a string.\n\n    To include whitespace characters (spaces, tabs, line breaks) in the output\n    array, set `keepWhitespace` to `true`.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    keepWhitespace: boolean (optional)\n        Boolean indicating whether whitespace characters should be returned as\n        part of the token array. Default: `false`.\n\n    Returns\n    -------\n    out: Array\n        Array of tokens.\n\n    Examples\n    --------\n    > var out = tokenize( 'Hello Mrs. Maple, could you call me back?' )\n    [ 'Hello', 'Mrs.', 'Maple', ',', 'could', 'you', 'call', 'me', 'back', '?' ]\n\n    > out = tokenize( 'Hello World!', true )\n    [ 'Hello', ' ', 'World', '!' ]\n\n","transformStream":"\ntransformStream( [options] )\n    Returns a transform stream.\n\n    If a transform function is not provided, the returned stream will be a\n    simple pass through stream.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.transform: Function (optional)\n        Callback to invoke upon receiving a new chunk.\n\n    options.flush: Function (optional)\n        Callback to invoke after receiving all chunks and prior to a stream\n        closing.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to decode strings into Buffer objects when writing.\n        Default: true.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream.\n\n    Examples\n    --------\n    > var s = transformStream();\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();\n\n\ntransformStream.factory( [options] )\n    Returns a function for creating transform streams.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to decode strings into Buffer objects when writing.\n        Default: true.\n\n    Returns\n    -------\n    createStream( transform[, flush] ): Function\n        Function for creating transform streams.\n\n    Examples\n    --------\n    > var opts = { 'highWaterMark': 64 };\n    > var createStream = transformStream.factory( opts );\n    > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n    > var s = createStream( fcn );\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();\n\n\ntransformStream.objectMode( [options] )\n    Returns an \"objectMode\" transform stream.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.transform: Function (optional)\n        Callback to invoke upon receiving a new chunk.\n\n    options.flush: Function (optional)\n        Callback to invoke after receiving all chunks and prior to a stream\n        closing.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to decode strings into Buffer objects when writing.\n        Default: true.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > var s = transformStream.objectMode();\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();\n\n\ntransformStream.ctor( [options] )\n    Returns a custom transform stream constructor.\n\n    If provided `transform` and `flush` options, these methods are bound to the\n    constructor prototype.\n\n    If not provided a transform function, the returned constructor creates\n    simple pass through streams.\n\n    The returned constructor accepts the same options as the constructor\n    factory, *except* for the `transform` and `flush` options, which are not\n    supported.\n\n    Any options provided to the constructor *override* options provided to the\n    constructor factory.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.transform: Function (optional)\n        Callback to invoke upon receiving a new chunk.\n\n    options.flush: Function (optional)\n        Callback to invoke after receiving all chunks and prior to a stream\n        closing.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to decode strings into Buffer objects when writing.\n        Default: true.\n\n    Returns\n    -------\n    ctor: Function\n        Custom transform stream constructor.\n\n    Examples\n    --------\n    > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n    > var opts = { 'highWaterMark': 64, 'transform': fcn };\n    > var customStream = transformStream.ctor( opts );\n    > var s = customStream();\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();\n\n","transformStream.factory":"\ntransformStream.factory( [options] )\n    Returns a function for creating transform streams.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to decode strings into Buffer objects when writing.\n        Default: true.\n\n    Returns\n    -------\n    createStream( transform[, flush] ): Function\n        Function for creating transform streams.\n\n    Examples\n    --------\n    > var opts = { 'highWaterMark': 64 };\n    > var createStream = transformStream.factory( opts );\n    > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n    > var s = createStream( fcn );\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();","transformStream.objectMode":"\ntransformStream.objectMode( [options] )\n    Returns an \"objectMode\" transform stream.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.transform: Function (optional)\n        Callback to invoke upon receiving a new chunk.\n\n    options.flush: Function (optional)\n        Callback to invoke after receiving all chunks and prior to a stream\n        closing.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to decode strings into Buffer objects when writing.\n        Default: true.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > var s = transformStream.objectMode();\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();","transformStream.ctor":"\ntransformStream.ctor( [options] )\n    Returns a custom transform stream constructor.\n\n    If provided `transform` and `flush` options, these methods are bound to the\n    constructor prototype.\n\n    If not provided a transform function, the returned constructor creates\n    simple pass through streams.\n\n    The returned constructor accepts the same options as the constructor\n    factory, *except* for the `transform` and `flush` options, which are not\n    supported.\n\n    Any options provided to the constructor *override* options provided to the\n    constructor factory.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.transform: Function (optional)\n        Callback to invoke upon receiving a new chunk.\n\n    options.flush: Function (optional)\n        Callback to invoke after receiving all chunks and prior to a stream\n        closing.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to decode strings into Buffer objects when writing.\n        Default: true.\n\n    Returns\n    -------\n    ctor: Function\n        Custom transform stream constructor.\n\n    Examples\n    --------\n    > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n    > var opts = { 'highWaterMark': 64, 'transform': fcn };\n    > var customStream = transformStream.ctor( opts );\n    > var s = customStream();\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();","trim":"\ntrim( str )\n    Trims whitespace from the beginning and end of a `string`.\n\n    \"Whitespace\" is defined as the following characters:\n\n    - \\f\n    - \\n\n    - \\r\n    - \\t\n    - \\v\n    - \\u0020\n    - \\u00a0\n    - \\u1680\n    - \\u2000-\\u200a\n    - \\u2028\n    - \\u2029\n    - \\u202f\n    - \\u205f\n    - \\u3000\n    - \\ufeff\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Trimmed string.\n\n    Examples\n    --------\n    > var out = trim( ' \\t\\t\\n  Beep \\r\\n\\t  ' )\n    'Beep'\n\n    See Also\n    --------\n    ltrim, pad, rtrim\n","truncate":"\ntruncate( str, len[, ending] )\n    Truncates a string to a specified length.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    len: integer\n        Output string length.\n\n    ending: string (optional)\n        Custom ending. Default: '...'.\n\n    Returns\n    -------\n    out: string\n        Truncated string.\n\n    Examples\n    --------\n    > var str = 'beep boop';\n    > var out = truncate( str, 5 )\n    'be...'\n\n    > out = truncate( str, 5, '|' )\n    'beep|'\n\n    See Also\n    --------\n    truncateMiddle","truncateMiddle":"\ntruncateMiddle( str, len[, seq] )\n    Truncates a string in the middle to a specified length.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    len: integer\n        Output string length.\n\n    seq: string (optional)\n        Custom replacement sequence. Default: '...'.\n\n    Returns\n    -------\n    out: string\n        Truncated string.\n\n    Examples\n    --------\n    > var str = 'beep boop';\n    > var out = truncateMiddle( str, 5 )\n    'b...p'\n\n    > out = truncateMiddle( str, 5, '|' )\n    'be|op'\n\n    See Also\n    --------\n    truncate","trycatch":"\ntrycatch( x, y )\n    If a function does not throw, returns the function return value; otherwise,\n    returns `y`.\n\n    Parameters\n    ----------\n    x: Function\n        Function to try invoking.\n\n    y: any\n        Value to return if a function throws an error.\n\n    Returns\n    -------\n    z: any\n        Either the return value of `x` or the provided argument `y`.\n\n    Examples\n    --------\n    > function x() {\n    ...     if ( base.random.randu() < 0.5 ) {\n    ...         throw new Error( 'beep' );\n    ...     }\n    ...     return 1.0;\n    ... };\n    > var z = trycatch( x, -1.0 )\n    <number>\n\n    See Also\n    --------\n    trycatchAsync, trythen\n","trycatchAsync":"\ntrycatchAsync( x, y, done )\n    If a function does not return an error, invokes a callback with the function\n    result; otherwise, invokes a callback with a value `y`.\n\n    A function `x` is provided a single argument:\n\n    - clbk: callback to invoke upon function completion.\n\n    The callback function accepts two arguments:\n\n    - error: error object.\n    - result: function result.\n\n    The `done` callback is invoked upon function completion and is provided two\n    arguments:\n\n    - error: error object.\n    - result: either the result of `x` or the provided argument `y`.\n\n    If `x` invokes `clbk` with an error argument, the function invokes the\n    `done` callback with both the error and the argument `y`.\n\n    If `x` does not invoke `clbk` with an error argument, the function invokes\n    the `done` callback with a first argument equal to `null` and the function\n    `result`.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Parameters\n    ----------\n    x: Function\n        Function to invoke.\n\n    y: any\n        Value to return if `x` returns an error.\n\n    done: Function\n        Callback to invoke upon completion.\n\n    Examples\n    --------\n    > function x( clbk ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         clbk( new Error( 'beep' ) );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         // process error...\n    ...     }\n    ...     console.log( result );\n    ... };\n    > trycatchAsync( x, 'boop', done )\n    'boop'\n\n    See Also\n    --------\n    trycatch, trythenAsync\n","tryFunction":"\ntryFunction( fcn[, thisArg] )\n    Wraps a function in a try/catch block.\n\n    If provided an asynchronous function, the returned function only traps\n    errors which occur during the current event loop tick.\n\n    If a function throws a literal, the literal is serialized as a string and\n    returned as an `Error` object.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to wrap.\n\n    thisArg: any (optional)\n        Function context.\n\n    Returns\n    -------\n    out: Function\n        Wrapped function.\n\n    Examples\n    --------\n    > function fcn() { throw new Error( 'beep boop' ); };\n    > var f = tryFunction( fcn );\n    > var out = f();\n    > out.message\n    'beep boop'\n\n","tryRequire":"\ntryRequire( id )\n    Wraps `require` in a `try/catch` block.\n\n    This function traps and returns any errors encountered when attempting to\n    require a module.\n\n    Use caution when attempting to resolve a relative path or a local module.\n    This function attempts to resolve a module from its current path. Thus, the\n    function is unable to resolve anything which is not along its search path.\n    For local requires, use an absolute file path.\n\n    Parameters\n    ----------\n    id: string\n        Module id.\n\n    Returns\n    -------\n    out: any|Error\n        Resolved module or an `Error`.\n\n    Examples\n    --------\n    > var out = tryRequire( '_unknown_module_id_' )\n    <Error>\n\n","trythen":"\ntrythen( x, y )\n    If a function does not throw, returns the function return value; otherwise,\n    returns the value returned by a second function `y`.\n\n    The function `y` is provided a single argument:\n\n    - error: the error thrown by `x`.\n\n    Parameters\n    ----------\n    x: Function\n        Function to try invoking.\n\n    y: Function\n        Function to invoke if an initial function throws an error.\n\n    Returns\n    -------\n    z: any\n        The return value of either `x` or `y`.\n\n    Examples\n    --------\n    > function x() {\n    ...     if ( base.random.randu() < 0.5 ) {\n    ...         throw new Error( 'beep' );\n    ...     }\n    ...     return 1.0;\n    ... };\n    > function y() {\n    ...     return -1.0;\n    ... };\n    > var z = trythen( x, y )\n    <number>\n\n    See Also\n    --------\n    trycatch, trythenAsync\n","trythenAsync":"\ntrythenAsync( x, y, done )\n    If a function does not return an error, invokes a callback with the function\n    result; otherwise, invokes a second function `y`.\n\n    A function `x` is provided a single argument:\n\n    - clbk: callback to invoke upon function completion.\n\n    The callback function accepts any number of arguments, with the first\n    argument reserved for providing an error.\n\n    If the error argument is falsy, the function invokes a `done` callback with\n    its first argument as `null` and all other provided arguments.\n\n    If the error argument is truthy, the function invokes a function `y`. The\n    number of arguments provided to `y` depends on the function's length. If `y`\n    is a unary function, `y` is provided a single argument:\n\n    - clbk: callback to invoke upon function completion.\n\n    Otherwise, `y` is provided two arguments:\n\n    - error: the error from `x`.\n    - clbk: callback to invoke upon function completion.\n\n    The callback function accepts any number of arguments, with the first\n    argument reserved for providing an error.\n\n    If the error argument is falsy, the `done` callback is invoked with its\n    first argument equal to `null` and all other arguments provided by `y`.\n\n    If the error argument is truthy, the `done` callback is invoked with only\n    the error argument provided by `y`.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Parameters\n    ----------\n    x: Function\n        Function to invoke.\n\n    y: Function\n        Function to invoke if `x` returns an error.\n\n    done: Function\n        Callback to invoke upon completion.\n\n    Examples\n    --------\n    > function x( clbk ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         clbk( new Error( 'beep' ) );\n    ...     }\n    ... };\n    > function y( clbk ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         clbk( null, 'boop' );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > trythenAsync( x, y, done )\n    'boop'\n\n    See Also\n    --------\n    trycatchAsync, trythen\n","ttest":"\nttest( x[, y][, options] )\n    Computes a one-sample or paired Student's t test.\n\n    When no `y` is supplied, the function performs a one-sample t-test for the\n    null hypothesis that the data in array or typed array `x` is drawn from a\n    normal distribution with mean zero and unknown variance.\n\n    When array or typed array `y` is supplied, the function tests whether the\n    differences `x - y` come from a normal distribution with mean zero and\n    unknown variance via the paired t-test.\n\n    The returned object comes with a `.print()` method which when invoked will\n    print a formatted output of the results of the hypothesis test.\n\n    Parameters\n    ----------\n    x: Array<number>\n        Data array.\n\n    y: Array<number> (optional)\n        Paired data array.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.alternative: string (optional)\n        Indicates whether the alternative hypothesis is that the mean of `x` is\n        larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n        `mu` (`two-sided`). Default: `'two-sided'`.\n\n    options.mu: number (optional)\n        Hypothesized true mean under the null hypothesis. Set this option to\n        test whether the data comes from a distribution with the specified `mu`.\n        Default: `0`.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Used significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.ci: Array<number>\n        1-alpha confidence interval for the mean.\n\n    out.nullValue: number\n        Assumed mean under H0 (or difference in means when `y` is supplied).\n\n    out.alternative: string\n        Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n    out.df: number\n        Degrees of freedom.\n\n    out.mean: number\n        Sample mean of `x` or `x - y`, respectively.\n\n    out.sd: number\n        Standard error of the mean.\n\n    out.method: string\n        Name of test.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    // One-sample t-test:\n    > var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 5776 } );\n    > var x = new Array( 100 );\n    > for ( var i = 0; i < x.length; i++ ) {\n    ...     x[ i ] = rnorm();\n    ... }\n    > var out = ttest( x )\n    {\n        rejected: false,\n        pValue: ~0.722,\n        statistic: ~0.357,\n        ci: [~-0.333,~0.479],\n        // ...\n    }\n\n    // Paired t-test:\n    > rnorm = base.random.normal.factory( 1.0, 2.0, { 'seed': 786 } );\n    > x = new Array( 100 );\n    > var y = new Array( 100 );\n    > for ( i = 0; i < x.length; i++ ) {\n    ...     x[ i ] = rnorm();\n    ...     y[ i ] = rnorm();\n    ... }\n    > out = ttest( x, y )\n    {\n        rejected: false,\n        pValue: ~0.191,\n        statistic: ~1.315,\n        ci: [ ~-0.196, ~0.964 ],\n        // ...\n    }\n\n    // Print formatted output:\n    > var table = out.print()\n    Paired t-test\n\n    Alternative hypothesis: True difference in means is not equal to 0\n\n        pValue: 0.1916\n        statistic: 1.3148\n        df: 99\n        95% confidence interval: [-0.1955,0.9635]\n\n    Test Decision: Fail to reject null in favor of alternative at 5%\n    significance level\n\n    // Choose custom significance level:\n    > var arr = [ 2, 4, 3, 1, 0 ];\n    > out = ttest( arr, { 'alpha': 0.01 } );\n    > table = out.print()\n    One-sample t-test\n\n    Alternative hypothesis: True mean is not equal to 0\n\n        pValue: 0.0474\n        statistic: 2.8284\n        df: 4\n        99% confidence interval: [-1.2556,5.2556]\n\n    Test Decision: Fail to reject null in favor of alternative at 1%\n    significance level\n\n    // Test for a mean equal to five:\n    > arr = [ 4, 4, 6, 6, 5 ];\n    > out = ttest( arr, { 'mu': 5 } )\n    {\n        rejected: false,\n        pValue: 1,\n        statistic: 0,\n        ci: [ ~3.758, ~6.242 ],\n        // ...\n    }\n\n    // Perform one-sided tests:\n    > arr = [ 4, 4, 6, 6, 5 ];\n    > out = ttest( arr, { 'alternative': 'less' } );\n    > table = out.print()\n    One-sample t-test\n\n    Alternative hypothesis: True mean is less than 0\n\n        pValue: 0.9998\n        statistic: 11.1803\n        df: 4\n        95% confidence interval: [-Infinity,5.9534]\n\n    Test Decision: Fail to reject null in favor of alternative at 5%\n    significance level\n\n    > out = ttest( arr, { 'alternative': 'greater' } );\n    > table = out.print()\n    One-sample t-test\n\n    Alternative hypothesis: True mean is greater than 0\n\n        pValue: 0.0002\n        statistic: 11.1803\n        df: 4\n        95% confidence interval: [4.0466,Infinity]\n\n    Test Decision: Reject null in favor of alternative at 5% significance level\n\n    See Also\n    --------\n    ttest2\n","ttest2":"\nttest2( x, y[, options] )\n    Computes a two-sample Student's t test.\n\n    By default, the function performs a two-sample t-test for the null\n    hypothesis that the data in arrays or typed arrays `x` and `y` is\n    independently drawn from normal distributions with equal means.\n\n    The returned object comes with a `.print()` method which when invoked will\n    print a formatted output of the results of the hypothesis test.\n\n    Parameters\n    ----------\n    x: Array<number>\n        First data array.\n\n    y: Array<number>\n        Second data array.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.alternative: string (optional)\n        Either `two-sided`, `less` or `greater`. Indicates whether the\n        alternative hypothesis is that `x` has a larger mean than `y`\n        (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n        the same (`two-sided`). Default: `'two-sided'`.\n\n    options.difference: number (optional)\n        Number denoting the difference in means under the null hypothesis.\n        Default: `0`.\n\n    options.variance: string (optional)\n        String indicating if the test should be conducted under the assumption\n        that the unknown variances of the normal distributions are `equal` or\n        `unequal`. As a default choice, the function carries out the Welch test\n        (using the Satterthwaite approximation for the degrees of freedom),\n        which does not have the requirement that the variances of the underlying\n        distributions are equal. If the equal variances assumption seems\n        warranted, set the option to `equal`. Default: `unequal`.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Used significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.ci: Array<number>\n        1-alpha confidence interval for the mean.\n\n    out.nullValue: number\n        Assumed difference in means under H0.\n\n    out.xmean: number\n        Sample mean of `x`.\n\n    out.ymean: number\n        Sample mean of `y`.\n\n    out.alternative: string\n        Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n    out.df: number\n        Degrees of freedom.\n\n    out.method: string\n        Name of test.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    // Student's sleep data:\n    > var x = [ 0.7, -1.6, -0.2, -1.2, -0.1, 3.4, 3.7, 0.8, 0.0, 2.0 ];\n    > var y = [ 1.9, 0.8, 1.1, 0.1, -0.1, 4.4, 5.5, 1.6, 4.6, 3.4 ];\n    > var out = ttest2( x, y )\n    {\n        rejected: false,\n        pValue: ~0.079,\n        statistic: ~-1.861,\n        ci: [ ~-3.365, ~0.205 ],\n        // ...\n    }\n\n    // Print table output:\n    > var table = out.print()\n    Welch two-sample t-test\n\n    Alternative hypothesis: True difference in means is not equal to 0\n\n        pValue: 0.0794\n        statistic: -1.8608\n        95% confidence interval: [-3.3655,0.2055]\n\n    Test Decision: Fail to reject null in favor of alternative at 5%\n    significance level\n\n    // Choose a different significance level than `0.05`:\n    > out = ttest2( x, y, { 'alpha': 0.1 } );\n    > table = out.print()\n    Welch two-sample t-test\n\n    Alternative hypothesis: True difference in means is not equal to 0\n\n        pValue: 0.0794\n        statistic: -1.8608\n        90% confidence interval: [-3.0534,-0.1066]\n\n    Test Decision: Reject null in favor of alternative at 10% significance level\n\n    // Perform one-sided tests:\n    > out = ttest2( x, y, { 'alternative': 'less' } );\n    > table = out.print()\n    Welch two-sample t-test\n\n    Alternative hypothesis: True difference in means is less than 0\n\n        pValue: 0.0397\n        statistic: -1.8608\n        df: 17.7765\n        95% confidence interval: [-Infinity,-0.1066]\n\n    Test Decision: Reject null in favor of alternative at 5% significance level\n\n    > out = ttest2( x, y, { 'alternative': 'greater' } );\n    > table = out.print()\n    Welch two-sample t-test\n\n    Alternative hypothesis: True difference in means is greater than 0\n\n        pValue: 0.9603\n        statistic: -1.8608\n        df: 17.7765\n        95% confidence interval: [-3.0534,Infinity]\n\n    Test Decision: Fail to reject null in favor of alternative at 5%\n    significance level\n\n    // Run tests with equal variances assumption:\n    > x = [ 2, 3, 1, 4 ];\n    > y = [ 1, 2, 3, 1, 2, 5, 3, 4 ];\n    > out = ttest2( x, y, { 'variance': 'equal' } );\n    > table = out.print()\n    Two-sample t-test\n\n    Alternative hypothesis: True difference in means is not equal to 0\n\n        pValue: 0.8848\n        statistic: -0.1486\n        df: 10\n        95% confidence interval: [-1.9996,1.7496]\n\n    Test Decision: Fail to reject null in favor of alternative at 5%\n    significance level\n\n    // Test for a difference in means besides zero:\n    > var rnorm = base.random.normal.factory({ 'seed': 372 } );\n    > x = new Array( 100 );\n    > for ( i = 0; i < x.length; i++ ) {\n    ...     x[ i ] = rnorm( 2.0, 3.0 );\n    ... }\n    > y = new Array( 100 );\n    > for ( i = 0; i < x.length; i++ ) {\n    ...     y[ i ] = rnorm( 1.0, 3.0 );\n    ... }\n    > out = ttest2( x, y, { 'difference': 1.0, 'variance': 'equal' } )\n    {\n        rejected: false,\n        pValue: ~0.642,\n        statistic: ~-0.466,\n        ci: [ ~-0.0455, ~1.646 ],\n        // ...\n    }\n\n    See Also\n    --------\n    ttest\n","TWO_PI":"\nTWO_PI\n    The mathematical constant `π` times `2`.\n\n    Examples\n    --------\n    > TWO_PI\n    6.283185307179586\n\n    See Also\n    --------\n    PI\n","typedarray":"\ntypedarray( [dtype] )\n    Creates a typed array.\n\n    Parameters\n    ----------\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = typedarray()\n    <Float64Array>\n    > arr = typedarray( 'float32' )\n    <Float32Array>\n\n\ntypedarray( length[, dtype] )\n    Returns a typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = typedarray( 5 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n    > arr = typedarray( 5, 'int32' )\n    <Int32Array>[ 0, 0, 0, 0, 0 ]\n\n\ntypedarray( typedarray[, dtype] )\n    Creates a typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = typedarray( [ 0.5, 0.5, 0.5 ] );\n    > var arr2 = typedarray( arr1, 'float32' )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]\n\n\ntypedarray( obj[, dtype] )\n    Creates a typed array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a typed array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 0.5, 0.5, 0.5 ];\n    > var arr2 = typedarray( arr1, 'float32' )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]\n\n\ntypedarray( buffer[, byteOffset[, length]][, dtype] )\n    Returns a typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 16 );\n    > var arr = typedarray( buf, 0, 4, 'float32' )\n    <Float32Array>[ 0.0, 0.0, 0.0, 0.0 ]\n\n    See Also\n    --------\n    Complex128Array, Complex64Array, Float64Array, Float32Array, Int32Array, Uint32Array, Int16Array, Uint16Array, Int8Array, Uint8Array, Uint8ClampedArray\n","typedarray2json":"\ntypedarray2json( arr )\n    Returns a JSON representation of a typed array.\n\n    The following typed array types are supported:\n\n    - Float64Array\n    - Float32Array\n    - Int32Array\n    - Uint32Array\n    - Int16Array\n    - Uint16Array\n    - Int8Array\n    - Uint8Array\n    - Uint8ClampedArray\n    - Complex64Array\n    - Complex128Array\n    - BooleanArray\n\n    The returned JSON object has the following properties:\n\n    - type: typed array type.\n    - data: typed array data as a generic array.\n\n    The implementation supports custom typed arrays and sets the `type` field to\n    the closest known typed array type.\n\n    Parameters\n    ----------\n    arr: TypedArray\n        Typed array to serialize.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 2 );\n    > arr[ 0 ] = 5.0;\n    > arr[ 1 ] = 3.0;\n    > var json = typedarray2json( arr )\n    { 'type': 'Float64Array', 'data': [ 5.0, 3.0 ] }\n\n    See Also\n    --------\n    reviveTypedArray\n","typedarrayCtors":"\ntypedarrayCtors( dtype )\n    Returns a typed array constructor.\n\n    The function returns constructors for the following data types:\n\n    - float32: single-precision floating-point numbers.\n    - float64: double-precision floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - complex128: double-precision complex floating-point numbers.\n    - bool: boolean values.\n    - int16: signed 16-bit integers.\n    - int32: signed 32-bit integers.\n    - int8: signed 8-bit integers.\n    - uint16: unsigned 16-bit integers.\n    - uint32: unsigned 32-bit integers.\n    - uint8: unsigned 8-bit integers.\n    - uint8c: unsigned clamped 8-bit integers.\n\n    Parameters\n    ----------\n    dtype: string\n        Data type.\n\n    Returns\n    -------\n    out: Function|null\n        Typed array constructor.\n\n    Examples\n    --------\n    > var ctor = typedarrayCtors( 'float64' )\n    <Function>\n    > ctor = typedarrayCtors( 'float' )\n    null\n\n    See Also\n    --------\n    arrayCtors\n","typedarrayDataTypes":"\ntypedarrayDataTypes()\n    Returns a list of typed array data types.\n\n    Returns\n    -------\n    out: Array<string>\n        List of typed array data types.\n\n    Examples\n    --------\n    > var out = typedarrayDataTypes()\n    <Array>\n\n    See Also\n    --------\n    arrayDataTypes, ndarrayDataTypes\n","typedarraypool":"\ntypedarraypool( [dtype] )\n    Returns an uninitialized typed array from a typed array memory pool.\n\n    Memory is **uninitialized**, which means that the contents of a returned\n    typed array may contain sensitive contents.\n\n    Parameters\n    ----------\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr = typedarraypool()\n    <Float64Array>[]\n    > arr = typedarraypool( 'float32' )\n    <Float32Array>[]\n\n\ntypedarraypool( length[, dtype] )\n    Returns an uninitialized typed array having a specified length from a typed\n    array memory pool.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr = typedarraypool( 5 )\n    <Float64Array>\n    > arr = typedarraypool( 5, 'int32' )\n    <Int32Array>\n\n\ntypedarraypool( typedarray[, dtype] )\n    Creates a pooled typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr1 = typedarraypool( [ 0.5, 0.5, 0.5 ] );\n    > var arr2 = typedarraypool( arr1, 'float32' )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool( obj[, dtype] )\n    Creates a pooled typed array from an array-like object.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object from which to generate a typed array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr1 = [ 0.5, 0.5, 0.5 ];\n    > var arr2 = typedarraypool( arr1, 'float32' )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.malloc( [dtype] )\n    Returns an uninitialized typed array from a typed array memory pool.\n\n    This method shares the same security vulnerabilities mentioned above.\n\n    Parameters\n    ----------\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr = typedarraypool.malloc()\n    <Float64Array>\n    > arr = typedarraypool.malloc( 'float32' )\n    <Float32Array>\n\n\ntypedarraypool.malloc( length[, dtype] )\n    Returns a typed array having a specified length from a typed array memory\n    pool.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr = typedarraypool.malloc( 5 )\n    <Float64Array>\n    > arr = typedarraypool.malloc( 5, 'int32' )\n    <Int32Array>\n\n\ntypedarraypool.malloc( typedarray[, dtype] )\n    Creates a pooled typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr1 = typedarraypool.malloc( [ 0.5, 0.5, 0.5 ] );\n    > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.malloc( obj[, dtype] )\n    Creates a pooled typed array from an array-like object.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object from which to generate a typed array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr1 = [ 0.5, 0.5, 0.5 ];\n    > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.calloc( [dtype] )\n    Returns a zero-initialized typed array from a typed array memory pool.\n\n    Parameters\n    ----------\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr = typedarraypool.calloc()\n    <Float64Array>[]\n    > arr = typedarraypool.calloc( 'float32' )\n    <Float32Array>[]\n\n\ntypedarraypool.calloc( length[, dtype] )\n    Returns a zero-initialized typed array having a specified length from a\n    typed array memory pool.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr = typedarraypool.calloc( 5 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n    > arr = typedarraypool.calloc( 5, 'int32' )\n    <Int32Array>[ 0, 0, 0, 0, 0 ]\n\n\ntypedarraypool.free( buf )\n    Frees a typed array or typed array buffer for use in a future allocation.\n\n    Parameters\n    ----------\n    buf: TypedArray|ArrayBuffer\n        Typed array or typed array buffer to free.\n\n    Examples\n    --------\n    > var arr = typedarraypool( 5 )\n    <Float64Array>\n    > typedarraypool.free( arr );\n\n\ntypedarraypool.clear()\n    Clears the typed array pool allowing garbage collection of previously\n    allocated (and currently free) array buffers.\n\n    Examples\n    --------\n    > var arr = typedarraypool( 5 )\n    <Float64Array>\n    > typedarraypool.free( arr );\n    > typedarraypool.clear();\n\n\ntypedarraypool.highWaterMark\n    Read-only property returning the pool's high water mark.\n\n    Once a high water mark is reached, typed array allocation fails.\n\n    Examples\n    --------\n    > typedarraypool.highWaterMark\n    <number>\n\n\ntypedarraypool.nbytes\n    Read-only property returning the total number of allocated bytes.\n\n    The returned value is the total accumulated value. Hence, anytime a pool\n    must allocate a new array buffer (i.e., more memory), the pool increments\n    this value.\n\n    The only time this value is decremented is when a pool is cleared.\n\n    This behavior means that, while allocated buffers which are never freed may,\n    in fact, be garbage collected, they continue to count against the high water\n    mark limit.\n\n    Accordingly, you should *always* free allocated buffers in order to prevent\n    the pool from believing that non-freed buffers are continually in use.\n\n    Examples\n    --------\n    > var arr = typedarraypool( 5 )\n    <Float64Array>\n    > typedarraypool.nbytes\n    <number>\n\n\ntypedarraypool.factory( [options] )\n    Creates a typed array pool.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.highWaterMark: integer (optional)\n        Maximum total memory (in bytes) which can be allocated.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating typed arrays from a typed array memory pool.\n\n    Examples\n    --------\n    > var pool = typedarraypool.factory();\n    > var arr1 = pool( 3, 'float64' )\n    <Float64Array>\n\n    See Also\n    --------\n    typedarray\n","typedarraypool.malloc":"\ntypedarraypool.malloc( [dtype] )\n    Returns an uninitialized typed array from a typed array memory pool.\n\n    This method shares the same security vulnerabilities mentioned above.\n\n    Parameters\n    ----------\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr = typedarraypool.malloc()\n    <Float64Array>\n    > arr = typedarraypool.malloc( 'float32' )\n    <Float32Array>typedarraypool.malloc( length[, dtype] )\n    Returns a typed array having a specified length from a typed array memory\n    pool.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr = typedarraypool.malloc( 5 )\n    <Float64Array>\n    > arr = typedarraypool.malloc( 5, 'int32' )\n    <Int32Array>typedarraypool.malloc( typedarray[, dtype] )\n    Creates a pooled typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr1 = typedarraypool.malloc( [ 0.5, 0.5, 0.5 ] );\n    > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]typedarraypool.malloc( obj[, dtype] )\n    Creates a pooled typed array from an array-like object.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object from which to generate a typed array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr1 = [ 0.5, 0.5, 0.5 ];\n    > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]","typedarraypool.calloc":"\ntypedarraypool.calloc( [dtype] )\n    Returns a zero-initialized typed array from a typed array memory pool.\n\n    Parameters\n    ----------\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr = typedarraypool.calloc()\n    <Float64Array>[]\n    > arr = typedarraypool.calloc( 'float32' )\n    <Float32Array>[]typedarraypool.calloc( length[, dtype] )\n    Returns a zero-initialized typed array having a specified length from a\n    typed array memory pool.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr = typedarraypool.calloc( 5 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n    > arr = typedarraypool.calloc( 5, 'int32' )\n    <Int32Array>[ 0, 0, 0, 0, 0 ]","typedarraypool.free":"\ntypedarraypool.free( buf )\n    Frees a typed array or typed array buffer for use in a future allocation.\n\n    Parameters\n    ----------\n    buf: TypedArray|ArrayBuffer\n        Typed array or typed array buffer to free.\n\n    Examples\n    --------\n    > var arr = typedarraypool( 5 )\n    <Float64Array>\n    > typedarraypool.free( arr );","typedarraypool.clear":"\ntypedarraypool.clear()\n    Clears the typed array pool allowing garbage collection of previously\n    allocated (and currently free) array buffers.\n\n    Examples\n    --------\n    > var arr = typedarraypool( 5 )\n    <Float64Array>\n    > typedarraypool.free( arr );\n    > typedarraypool.clear();","typedarraypool.highWaterMark":"\ntypedarraypool.highWaterMark\n    Read-only property returning the pool's high water mark.\n\n    Once a high water mark is reached, typed array allocation fails.\n\n    Examples\n    --------\n    > typedarraypool.highWaterMark\n    <number>","typedarraypool.nbytes":"\ntypedarraypool.nbytes\n    Read-only property returning the total number of allocated bytes.\n\n    The returned value is the total accumulated value. Hence, anytime a pool\n    must allocate a new array buffer (i.e., more memory), the pool increments\n    this value.\n\n    The only time this value is decremented is when a pool is cleared.\n\n    This behavior means that, while allocated buffers which are never freed may,\n    in fact, be garbage collected, they continue to count against the high water\n    mark limit.\n\n    Accordingly, you should *always* free allocated buffers in order to prevent\n    the pool from believing that non-freed buffers are continually in use.\n\n    Examples\n    --------\n    > var arr = typedarraypool( 5 )\n    <Float64Array>\n    > typedarraypool.nbytes\n    <number>","typedarraypool.factory":"\ntypedarraypool.factory( [options] )\n    Creates a typed array pool.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.highWaterMark: integer (optional)\n        Maximum total memory (in bytes) which can be allocated.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating typed arrays from a typed array memory pool.\n\n    Examples\n    --------\n    > var pool = typedarraypool.factory();\n    > var arr1 = pool( 3, 'float64' )\n    <Float64Array>\n\n    See Also\n    --------\n    typedarray","typemax":"\ntypemax( dtype )\n    Returns the maximum value of a specified numeric type.\n\n    The following numeric types are supported:\n\n    - float64: double-precision floating-point numbers.\n    - float32: single-precision floating-point numbers.\n    - float16: half-precision floating-point numbers.\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n\n    Parameters\n    ----------\n    dtype: string\n        Numeric type.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    > var m = typemax( 'int8' )\n    127\n    > m = typemax( 'uint32' )\n    4294967295\n\n    See Also\n    --------\n    realmax, typemin\n","typemin":"\ntypemin( dtype )\n    Returns the minimum value of a specified numeric type.\n\n    The following numeric types are supported:\n\n    - float64: double-precision floating-point numbers.\n    - float32: single-precision floating-point numbers.\n    - float16: half-precision floating-point numbers.\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n\n    Parameters\n    ----------\n    dtype: string\n        Numeric type.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    > var m = typemin( 'int8' )\n    -128\n    > m = typemin( 'uint32' )\n    0\n\n    See Also\n    --------\n    realmin, typemax\n","typeOf":"\ntypeOf( value )\n    Determines a value's type.\n\n    The following values are not natively provided in older JavaScript engines:\n\n    - Map\n    - Set\n    - WeakMap\n    - WeakSet\n    - Symbol\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    out: string\n        The value's type.\n\n    Examples\n    --------\n    // Built-ins:\n    > var t = typeOf( 'a' )\n    'string'\n    > t = typeOf( 5 )\n    'number'\n    > t = typeOf( NaN )\n    'number'\n    > t = typeOf( true )\n    'boolean'\n    > t = typeOf( false )\n    'boolean'\n    > t = typeOf( null )\n    'null'\n    > t = typeOf( undefined )\n    'undefined'\n    > t = typeOf( [] )\n    'array'\n    > t = typeOf( {} )\n    'object'\n    > t = typeOf( function noop() {} )\n    'function'\n    > t = typeOf( Symbol( 'beep' ) )\n    'symbol'\n    > t = typeOf( /.+/ )\n    'regexp'\n    > t = typeOf( new String( 'beep' ) )\n    'string'\n    > t = typeOf( new Number( 5 ) )\n    'number'\n    > t = typeOf( new Boolean( false ) )\n    'boolean'\n    > t = typeOf( new Array() )\n    'array'\n    > t = typeOf( new Object() )\n    'object'\n    > t = typeOf( new Int8Array( 10 ) )\n    'int8array'\n    > t = typeOf( new Uint8Array( 10 ) )\n    'uint8array'\n    > t = typeOf( new Uint8ClampedArray( 10 ) )\n    'uint8clampedarray'\n    > t = typeOf( new Int16Array( 10 ) )\n    'int16array'\n    > t = typeOf( new Uint16Array( 10 ) )\n    'uint16array'\n    > t = typeOf( new Int32Array( 10 ) )\n    'int32array'\n    > t = typeOf( new Uint32Array( 10 ) )\n    'uint32array'\n    > t = typeOf( new Float32Array( 10 ) )\n    'float32array'\n    > t = typeOf( new Float64Array( 10 ) )\n    'float64array'\n    > t = typeOf( new ArrayBuffer( 10 ) )\n    'arraybuffer'\n    > t = typeOf( new Date() )\n    'date'\n    > t = typeOf( new RegExp( '.+' ) )\n    'regexp'\n    > t = typeOf( new Map() )\n    'map'\n    > t = typeOf( new Set() )\n    'set'\n    > t = typeOf( new WeakMap() )\n    'weakmap'\n    > t = typeOf( new WeakSet() )\n    'weakset'\n    > t = typeOf( new Error( 'beep' ) )\n    'error'\n    > t = typeOf( new TypeError( 'beep' ) )\n    'typeerror'\n    > t = typeOf( new SyntaxError( 'beep' ) )\n    'syntaxerror'\n    > t = typeOf( new ReferenceError( 'beep' ) )\n    'referenceerror'\n    > t = typeOf( new URIError( 'beep' ) )\n    'urierror'\n    > t = typeOf( new RangeError( 'beep' ) )\n    'rangeerror'\n    > t = typeOf( new EvalError( 'beep' ) )\n    'evalerror'\n    > t = typeOf( Math )\n    'math'\n    > t = typeOf( JSON )\n    'json'\n\n    // Arguments object:\n    > function beep() { return arguments; };\n    > t = typeOf( beep() )\n    'arguments'\n\n    // Node.js Buffer object:\n    > t = typeOf( new Buffer( 10 ) )\n    'buffer'\n\n    // Custom constructor:\n    > function Person() { return this };\n    > t = typeOf( new Person() )\n    'person'\n\n    // Anonymous constructor:\n    > var Foo = function () { return this; };\n    > t = typeOf( new Foo() )\n    '' || 'foo'\n\n    See Also\n    --------\n    constructorName, nativeClass\n","UINT8_MAX":"\nUINT8_MAX\n    Maximum unsigned 8-bit integer.\n\n    The maximum unsigned 8-bit integer is given by `2^8 - 1`.\n\n    Examples\n    --------\n    > UINT8_MAX\n    255\n\n    See Also\n    --------\n    INT8_MAX\n","UINT8_NUM_BYTES":"\nUINT8_NUM_BYTES\n    Size (in bytes) of an 8-bit unsigned integer.\n\n    Examples\n    --------\n    > UINT8_NUM_BYTES\n    1\n\n    See Also\n    --------\n    INT8_NUM_BYTES, UINT16_NUM_BYTES, UINT32_NUM_BYTES\n","Uint8Array":"\nUint8Array()\n    A typed array constructor which returns a typed array representing an array\n    of 8-bit unsigned integers in the platform byte order.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array()\n    <Uint8Array>\n\n\nUint8Array( length )\n    Returns a typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( 5 )\n    <Uint8Array>[ 0, 0, 0, 0, 0 ]\n\n\nUint8Array( typedarray )\n    Creates a typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n    > var arr2 = new Uint8Array( arr1 )\n    <Uint8Array>[ 5, 5, 5 ]\n\n\nUint8Array( obj )\n    Creates a typed array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a typed array.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 5.0, 5.0, 5.0 ];\n    > var arr2 = new Uint8Array( arr1 )\n    <Uint8Array>[ 5, 5, 5 ]\n\n\nUint8Array( buffer[, byteOffset[, length]] )\n    Returns a typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 4 );\n    > var arr = new Uint8Array( buf, 0, 4 )\n    <Uint8Array>[ 0, 0, 0, 0 ]\n\n\nUint8Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Uint8Array.from( [ 1, 2 ], mapFcn )\n    <Uint8Array>[ 2, 4 ]\n\n\nUint8Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Uint8Array.of( 1, 2 )\n    <Uint8Array>[ 1, 2 ]\n\n\nUint8Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Uint8Array.BYTES_PER_ELEMENT\n    1\n\n\nUint8Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Uint8Array.name\n    'Uint8Array'\n\n\nUint8Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>\n\n\nUint8Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( 5 );\n    > arr.byteLength\n    5\n\n\nUint8Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( 5 );\n    > arr.byteOffset\n    0\n\n\nUint8Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    1\n\n\nUint8Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( 5 );\n    > arr.length\n    5\n\n\nUint8Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Uint8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2\n\n\nUint8Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true\n\n\nUint8Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false\n\n\nUint8Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Uint8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3\n\n\nUint8Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2\n\n\nUint8Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3\n\n\nUint8Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2\n\n\nUint8Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '\n\n\nUint8Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true\n\n\nUint8Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2\n\n\nUint8Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'\n\n\nUint8Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true\n\n\nUint8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3\n\n\nUint8Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Uint8Array>[ 2, 4, 6 ]\n\n\nUint8Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14\n\n\nUint8Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14\n\n\nUint8Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Uint8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] )\n    <Uint8Array>\n    > arr.reverse()\n    <Uint8Array>[ 3, 2, 1 ]\n\n\nUint8Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4\n\n\nUint8Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3\n\n\nUint8Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true\n\n\nUint8Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Uint8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Uint8Array>[ 0, 1, 1, 2, 2 ]\n\n\nUint8Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint8Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Uint8Array>[ 3, 4, 5 ]\n\n\nUint8Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'\n\n\nUint8Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'\n\n\nUint8Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8ClampedArray\n","Uint8Array.from":"\nUint8Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Uint8Array.from( [ 1, 2 ], mapFcn )\n    <Uint8Array>[ 2, 4 ]","Uint8Array.of":"\nUint8Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Uint8Array.of( 1, 2 )\n    <Uint8Array>[ 1, 2 ]","Uint8Array.BYTES_PER_ELEMENT":"\nUint8Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Uint8Array.BYTES_PER_ELEMENT\n    1","Uint8Array.name":"\nUint8Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Uint8Array.name\n    'Uint8Array'","Uint8Array.prototype.buffer":"\nUint8Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>","Uint8Array.prototype.byteLength":"\nUint8Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( 5 );\n    > arr.byteLength\n    5","Uint8Array.prototype.byteOffset":"\nUint8Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( 5 );\n    > arr.byteOffset\n    0","Uint8Array.prototype.BYTES_PER_ELEMENT":"\nUint8Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    1","Uint8Array.prototype.length":"\nUint8Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( 5 );\n    > arr.length\n    5","Uint8Array.prototype.copyWithin":"\nUint8Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Uint8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2","Uint8Array.prototype.entries":"\nUint8Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true","Uint8Array.prototype.every":"\nUint8Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false","Uint8Array.prototype.fill":"\nUint8Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Uint8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3","Uint8Array.prototype.filter":"\nUint8Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2","Uint8Array.prototype.find":"\nUint8Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3","Uint8Array.prototype.findIndex":"\nUint8Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2","Uint8Array.prototype.forEach":"\nUint8Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '","Uint8Array.prototype.includes":"\nUint8Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true","Uint8Array.prototype.indexOf":"\nUint8Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2","Uint8Array.prototype.join":"\nUint8Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'","Uint8Array.prototype.keys":"\nUint8Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true","Uint8Array.prototype.lastIndexOf":"\nUint8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3","Uint8Array.prototype.map":"\nUint8Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Uint8Array>[ 2, 4, 6 ]","Uint8Array.prototype.reduce":"\nUint8Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14","Uint8Array.prototype.reduceRight":"\nUint8Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14","Uint8Array.prototype.reverse":"\nUint8Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Uint8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] )\n    <Uint8Array>\n    > arr.reverse()\n    <Uint8Array>[ 3, 2, 1 ]","Uint8Array.prototype.set":"\nUint8Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4","Uint8Array.prototype.slice":"\nUint8Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3","Uint8Array.prototype.some":"\nUint8Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true","Uint8Array.prototype.sort":"\nUint8Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Uint8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Uint8Array>[ 0, 1, 1, 2, 2 ]","Uint8Array.prototype.subarray":"\nUint8Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint8Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Uint8Array>[ 3, 4, 5 ]","Uint8Array.prototype.toLocaleString":"\nUint8Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'","Uint8Array.prototype.toString":"\nUint8Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'","Uint8Array.prototype.values":"\nUint8Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8ClampedArray","Uint8ClampedArray":"\nUint8ClampedArray()\n    A typed array constructor which returns a typed array representing an array\n    of 8-bit unsigned integers in the platform byte order clamped to 0-255.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray()\n    <Uint8ClampedArray>\n\n\nUint8ClampedArray( length )\n    Returns a typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( 5 )\n    <Uint8ClampedArray>[ 0, 0, 0, 0, 0 ]\n\n\nUint8ClampedArray( typedarray )\n    Creates a typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n    > var arr2 = new Uint8ClampedArray( arr1 )\n    <Uint8ClampedArray>[ 5, 5, 5 ]\n\n\nUint8ClampedArray( obj )\n    Creates a typed array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a typed array.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 5.0, 5.0, 5.0 ];\n    > var arr2 = new Uint8ClampedArray( arr1 )\n    <Uint8ClampedArray>[ 5, 5, 5 ]\n\n\nUint8ClampedArray( buffer[, byteOffset[, length]] )\n    Returns a typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 4 );\n    > var arr = new Uint8ClampedArray( buf, 0, 4 )\n    <Uint8ClampedArray>[ 0, 0, 0, 0 ]\n\n\nUint8ClampedArray.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Uint8ClampedArray.from( [ 1, 2 ], mapFcn )\n    <Uint8ClampedArray>[ 2, 4 ]\n\n\nUint8ClampedArray.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Uint8ClampedArray.of( 1, 2 )\n    <Uint8ClampedArray>[ 1, 2 ]\n\n\nUint8ClampedArray.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Uint8ClampedArray.BYTES_PER_ELEMENT\n    1\n\n\nUint8ClampedArray.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Uint8ClampedArray.name\n    'Uint8ClampedArray'\n\n\nUint8ClampedArray.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( 5 );\n    > arr.buffer\n    <ArrayBuffer>\n\n\nUint8ClampedArray.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( 5 );\n    > arr.byteLength\n    5\n\n\nUint8ClampedArray.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( 5 );\n    > arr.byteOffset\n    0\n\n\nUint8ClampedArray.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( 5 );\n    > arr.BYTES_PER_ELEMENT\n    1\n\n\nUint8ClampedArray.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( 5 );\n    > arr.length\n    5\n\n\nUint8ClampedArray.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2\n\n\nUint8ClampedArray.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true\n\n\nUint8ClampedArray.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false\n\n\nUint8ClampedArray.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3\n\n\nUint8ClampedArray.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2\n\n\nUint8ClampedArray.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3\n\n\nUint8ClampedArray.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2\n\n\nUint8ClampedArray.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '\n\n\nUint8ClampedArray.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true\n\n\nUint8ClampedArray.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2\n\n\nUint8ClampedArray.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'\n\n\nUint8ClampedArray.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true\n\n\nUint8ClampedArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3\n\n\nUint8ClampedArray.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Uint8ClampedArray>[ 2, 4, 6 ]\n\n\nUint8ClampedArray.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14\n\n\nUint8ClampedArray.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14\n\n\nUint8ClampedArray.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] )\n    <Uint8ClampedArray>\n    > arr.reverse()\n    <Uint8ClampedArray>[ 3, 2, 1 ]\n\n\nUint8ClampedArray.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4\n\n\nUint8ClampedArray.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3\n\n\nUint8ClampedArray.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true\n\n\nUint8ClampedArray.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Uint8ClampedArray>[ 0, 1, 1, 2, 2 ]\n\n\nUint8ClampedArray.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Uint8ClampedArray>[ 3, 4, 5 ]\n\n\nUint8ClampedArray.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'\n\n\nUint8ClampedArray.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'\n\n\nUint8ClampedArray.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array\n","Uint8ClampedArray.from":"\nUint8ClampedArray.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Uint8ClampedArray.from( [ 1, 2 ], mapFcn )\n    <Uint8ClampedArray>[ 2, 4 ]","Uint8ClampedArray.of":"\nUint8ClampedArray.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Uint8ClampedArray.of( 1, 2 )\n    <Uint8ClampedArray>[ 1, 2 ]","Uint8ClampedArray.BYTES_PER_ELEMENT":"\nUint8ClampedArray.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Uint8ClampedArray.BYTES_PER_ELEMENT\n    1","Uint8ClampedArray.name":"\nUint8ClampedArray.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Uint8ClampedArray.name\n    'Uint8ClampedArray'","Uint8ClampedArray.prototype.buffer":"\nUint8ClampedArray.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( 5 );\n    > arr.buffer\n    <ArrayBuffer>","Uint8ClampedArray.prototype.byteLength":"\nUint8ClampedArray.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( 5 );\n    > arr.byteLength\n    5","Uint8ClampedArray.prototype.byteOffset":"\nUint8ClampedArray.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( 5 );\n    > arr.byteOffset\n    0","Uint8ClampedArray.prototype.BYTES_PER_ELEMENT":"\nUint8ClampedArray.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( 5 );\n    > arr.BYTES_PER_ELEMENT\n    1","Uint8ClampedArray.prototype.length":"\nUint8ClampedArray.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( 5 );\n    > arr.length\n    5","Uint8ClampedArray.prototype.copyWithin":"\nUint8ClampedArray.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2","Uint8ClampedArray.prototype.entries":"\nUint8ClampedArray.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true","Uint8ClampedArray.prototype.every":"\nUint8ClampedArray.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false","Uint8ClampedArray.prototype.fill":"\nUint8ClampedArray.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3","Uint8ClampedArray.prototype.filter":"\nUint8ClampedArray.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2","Uint8ClampedArray.prototype.find":"\nUint8ClampedArray.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3","Uint8ClampedArray.prototype.findIndex":"\nUint8ClampedArray.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2","Uint8ClampedArray.prototype.forEach":"\nUint8ClampedArray.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '","Uint8ClampedArray.prototype.includes":"\nUint8ClampedArray.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true","Uint8ClampedArray.prototype.indexOf":"\nUint8ClampedArray.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2","Uint8ClampedArray.prototype.join":"\nUint8ClampedArray.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'","Uint8ClampedArray.prototype.keys":"\nUint8ClampedArray.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true","Uint8ClampedArray.prototype.lastIndexOf":"\nUint8ClampedArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3","Uint8ClampedArray.prototype.map":"\nUint8ClampedArray.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Uint8ClampedArray>[ 2, 4, 6 ]","Uint8ClampedArray.prototype.reduce":"\nUint8ClampedArray.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14","Uint8ClampedArray.prototype.reduceRight":"\nUint8ClampedArray.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14","Uint8ClampedArray.prototype.reverse":"\nUint8ClampedArray.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] )\n    <Uint8ClampedArray>\n    > arr.reverse()\n    <Uint8ClampedArray>[ 3, 2, 1 ]","Uint8ClampedArray.prototype.set":"\nUint8ClampedArray.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4","Uint8ClampedArray.prototype.slice":"\nUint8ClampedArray.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3","Uint8ClampedArray.prototype.some":"\nUint8ClampedArray.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true","Uint8ClampedArray.prototype.sort":"\nUint8ClampedArray.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Uint8ClampedArray>[ 0, 1, 1, 2, 2 ]","Uint8ClampedArray.prototype.subarray":"\nUint8ClampedArray.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Uint8ClampedArray>[ 3, 4, 5 ]","Uint8ClampedArray.prototype.toLocaleString":"\nUint8ClampedArray.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'","Uint8ClampedArray.prototype.toString":"\nUint8ClampedArray.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'","Uint8ClampedArray.prototype.values":"\nUint8ClampedArray.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array","UINT16_MAX":"\nUINT16_MAX\n    Maximum unsigned 16-bit integer.\n\n    The maximum unsigned 16-bit integer is given by `2^16 - 1`.\n\n    Examples\n    --------\n    > UINT16_MAX\n    65535\n\n    See Also\n    --------\n    INT16_MAX\n","UINT16_NUM_BYTES":"\nUINT16_NUM_BYTES\n    Size (in bytes) of a 16-bit unsigned integer.\n\n    Examples\n    --------\n    > UINT16_NUM_BYTES\n    2\n\n    See Also\n    --------\n    INT16_NUM_BYTES, UINT32_NUM_BYTES, UINT8_NUM_BYTES\n","Uint16Array":"\nUint16Array()\n    A typed array constructor which returns a typed array representing an array\n    of 16-bit unsigned integers in the platform byte order.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array()\n    <Uint16Array>\n\n\nUint16Array( length )\n    Returns a typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( 5 )\n    <Uint16Array>[ 0, 0, 0, 0, 0 ]\n\n\nUint16Array( typedarray )\n    Creates a typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n    > var arr2 = new Uint16Array( arr1 )\n    <Uint16Array>[ 5, 5, 5 ]\n\n\nUint16Array( obj )\n    Creates a typed array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a typed array.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 5.0, 5.0, 5.0 ];\n    > var arr2 = new Uint16Array( arr1 )\n    <Uint16Array>[ 5, 5, 5 ]\n\n\nUint16Array( buffer[, byteOffset[, length]] )\n    Returns a typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 8 );\n    > var arr = new Uint16Array( buf, 0, 4 )\n    <Uint16Array>[ 0, 0, 0, 0 ]\n\n\nUint16Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Uint16Array.from( [ 1, 2 ], mapFcn )\n    <Uint16Array>[ 2, 4 ]\n\n\nUint16Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Uint16Array.of( 1, 2 )\n    <Uint16Array>[ 1, 2 ]\n\n\nUint16Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Uint16Array.BYTES_PER_ELEMENT\n    2\n\n\nUint16Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Uint16Array.name\n    'Uint16Array'\n\n\nUint16Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>\n\n\nUint16Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( 5 );\n    > arr.byteLength\n    10\n\n\nUint16Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( 5 );\n    > arr.byteOffset\n    0\n\n\nUint16Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    2\n\n\nUint16Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( 5 );\n    > arr.length\n    5\n\n\nUint16Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Uint16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2\n\n\nUint16Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true\n\n\nUint16Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false\n\n\nUint16Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Uint16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3\n\n\nUint16Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2\n\n\nUint16Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3\n\n\nUint16Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2\n\n\nUint16Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '\n\n\nUint16Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true\n\n\nUint16Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2\n\n\nUint16Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'\n\n\nUint16Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true\n\n\nUint16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3\n\n\nUint16Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Uint16Array>[ 2, 4, 6 ]\n\n\nUint16Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14\n\n\nUint16Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14\n\n\nUint16Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Uint16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] )\n    <Uint16Array>\n    > arr.reverse()\n    <Uint16Array>[ 3, 2, 1 ]\n\n\nUint16Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4\n\n\nUint16Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3\n\n\nUint16Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true\n\n\nUint16Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Uint16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Uint16Array>[ 0, 1, 1, 2, 2 ]\n\n\nUint16Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint16Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Uint16Array>[ 3, 4, 5 ]\n\n\nUint16Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'\n\n\nUint16Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'\n\n\nUint16Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Uint16Array.from":"\nUint16Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Uint16Array.from( [ 1, 2 ], mapFcn )\n    <Uint16Array>[ 2, 4 ]","Uint16Array.of":"\nUint16Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Uint16Array.of( 1, 2 )\n    <Uint16Array>[ 1, 2 ]","Uint16Array.BYTES_PER_ELEMENT":"\nUint16Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Uint16Array.BYTES_PER_ELEMENT\n    2","Uint16Array.name":"\nUint16Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Uint16Array.name\n    'Uint16Array'","Uint16Array.prototype.buffer":"\nUint16Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>","Uint16Array.prototype.byteLength":"\nUint16Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( 5 );\n    > arr.byteLength\n    10","Uint16Array.prototype.byteOffset":"\nUint16Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( 5 );\n    > arr.byteOffset\n    0","Uint16Array.prototype.BYTES_PER_ELEMENT":"\nUint16Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    2","Uint16Array.prototype.length":"\nUint16Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( 5 );\n    > arr.length\n    5","Uint16Array.prototype.copyWithin":"\nUint16Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Uint16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2","Uint16Array.prototype.entries":"\nUint16Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true","Uint16Array.prototype.every":"\nUint16Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false","Uint16Array.prototype.fill":"\nUint16Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Uint16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3","Uint16Array.prototype.filter":"\nUint16Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2","Uint16Array.prototype.find":"\nUint16Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3","Uint16Array.prototype.findIndex":"\nUint16Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2","Uint16Array.prototype.forEach":"\nUint16Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '","Uint16Array.prototype.includes":"\nUint16Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true","Uint16Array.prototype.indexOf":"\nUint16Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2","Uint16Array.prototype.join":"\nUint16Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'","Uint16Array.prototype.keys":"\nUint16Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true","Uint16Array.prototype.lastIndexOf":"\nUint16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3","Uint16Array.prototype.map":"\nUint16Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Uint16Array>[ 2, 4, 6 ]","Uint16Array.prototype.reduce":"\nUint16Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14","Uint16Array.prototype.reduceRight":"\nUint16Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14","Uint16Array.prototype.reverse":"\nUint16Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Uint16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] )\n    <Uint16Array>\n    > arr.reverse()\n    <Uint16Array>[ 3, 2, 1 ]","Uint16Array.prototype.set":"\nUint16Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4","Uint16Array.prototype.slice":"\nUint16Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3","Uint16Array.prototype.some":"\nUint16Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true","Uint16Array.prototype.sort":"\nUint16Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Uint16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Uint16Array>[ 0, 1, 1, 2, 2 ]","Uint16Array.prototype.subarray":"\nUint16Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint16Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Uint16Array>[ 3, 4, 5 ]","Uint16Array.prototype.toLocaleString":"\nUint16Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'","Uint16Array.prototype.toString":"\nUint16Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'","Uint16Array.prototype.values":"\nUint16Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint32Array, Uint8Array, Uint8ClampedArray","UINT32_MAX":"\nUINT32_MAX\n    Maximum unsigned 32-bit integer.\n\n    The maximum unsigned 32-bit integer is given by `2^32 - 1`.\n\n    Examples\n    --------\n    > UINT32_MAX\n    4294967295\n\n    See Also\n    --------\n    INT32_MAX\n","UINT32_NUM_BYTES":"\nUINT32_NUM_BYTES\n    Size (in bytes) of a 32-bit unsigned integer.\n\n    Examples\n    --------\n    > UINT32_NUM_BYTES\n    4\n\n    See Also\n    --------\n    INT32_NUM_BYTES, UINT16_NUM_BYTES, UINT8_NUM_BYTES\n","Uint32Array":"\nUint32Array()\n    A typed array constructor which returns a typed array representing an array\n    of 32-bit unsigned integers in the platform byte order.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array()\n    <Uint32Array>\n\n\nUint32Array( length )\n    Returns a typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( 5 )\n    <Uint32Array>[ 0, 0, 0, 0, 0 ]\n\n\nUint32Array( typedarray )\n    Creates a typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n    > var arr2 = new Uint32Array( arr1 )\n    <Uint32Array>[ 5, 5, 5 ]\n\n\nUint32Array( obj )\n    Creates a typed array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a typed array.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 5.0, 5.0, 5.0 ];\n    > var arr2 = new Uint32Array( arr1 )\n    <Uint32Array>[ 5, 5, 5 ]\n\n\nUint32Array( buffer[, byteOffset[, length]] )\n    Returns a typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 16 );\n    > var arr = new Uint32Array( buf, 0, 4 )\n    <Uint32Array>[ 0, 0, 0, 0 ]\n\n\nUint32Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Uint32Array.from( [ 1, 2 ], mapFcn )\n    <Uint32Array>[ 2, 4 ]\n\n\nUint32Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Uint32Array.of( 1, 2 )\n    <Uint32Array>[ 1, 2 ]\n\n\nUint32Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Uint32Array.BYTES_PER_ELEMENT\n    4\n\n\nUint32Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Uint32Array.name\n    'Uint32Array'\n\n\nUint32Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>\n\n\nUint32Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( 5 );\n    > arr.byteLength\n    20\n\n\nUint32Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( 5 );\n    > arr.byteOffset\n    0\n\n\nUint32Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    4\n\n\nUint32Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( 5 );\n    > arr.length\n    5\n\n\nUint32Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Uint32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2\n\n\nUint32Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true\n\n\nUint32Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false\n\n\nUint32Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Uint32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3\n\n\nUint32Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2\n\n\nUint32Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3\n\n\nUint32Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2\n\n\nUint32Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '\n\n\nUint32Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true\n\n\nUint32Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2\n\n\nUint32Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'\n\n\nUint32Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true\n\n\nUint32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3\n\n\nUint32Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Uint32Array>[ 2, 4, 6 ]\n\n\nUint32Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14\n\n\nUint32Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14\n\n\nUint32Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Uint32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] )\n    <Uint32Array>\n    > arr.reverse()\n    <Uint32Array>[ 3, 2, 1 ]\n\n\nUint32Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4\n\n\nUint32Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3\n\n\nUint32Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true\n\n\nUint32Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Uint32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Uint32Array>[ 0, 1, 1, 2, 2 ]\n\n\nUint32Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint32Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Uint32Array>[ 3, 4, 5 ]\n\n\nUint32Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'\n\n\nUint32Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'\n\n\nUint32Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint8Array, Uint8ClampedArray\n","Uint32Array.from":"\nUint32Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Uint32Array.from( [ 1, 2 ], mapFcn )\n    <Uint32Array>[ 2, 4 ]","Uint32Array.of":"\nUint32Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Uint32Array.of( 1, 2 )\n    <Uint32Array>[ 1, 2 ]","Uint32Array.BYTES_PER_ELEMENT":"\nUint32Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Uint32Array.BYTES_PER_ELEMENT\n    4","Uint32Array.name":"\nUint32Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Uint32Array.name\n    'Uint32Array'","Uint32Array.prototype.buffer":"\nUint32Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>","Uint32Array.prototype.byteLength":"\nUint32Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( 5 );\n    > arr.byteLength\n    20","Uint32Array.prototype.byteOffset":"\nUint32Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( 5 );\n    > arr.byteOffset\n    0","Uint32Array.prototype.BYTES_PER_ELEMENT":"\nUint32Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    4","Uint32Array.prototype.length":"\nUint32Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( 5 );\n    > arr.length\n    5","Uint32Array.prototype.copyWithin":"\nUint32Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Uint32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2","Uint32Array.prototype.entries":"\nUint32Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true","Uint32Array.prototype.every":"\nUint32Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false","Uint32Array.prototype.fill":"\nUint32Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Uint32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3","Uint32Array.prototype.filter":"\nUint32Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2","Uint32Array.prototype.find":"\nUint32Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3","Uint32Array.prototype.findIndex":"\nUint32Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2","Uint32Array.prototype.forEach":"\nUint32Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '","Uint32Array.prototype.includes":"\nUint32Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true","Uint32Array.prototype.indexOf":"\nUint32Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2","Uint32Array.prototype.join":"\nUint32Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'","Uint32Array.prototype.keys":"\nUint32Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true","Uint32Array.prototype.lastIndexOf":"\nUint32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3","Uint32Array.prototype.map":"\nUint32Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Uint32Array>[ 2, 4, 6 ]","Uint32Array.prototype.reduce":"\nUint32Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14","Uint32Array.prototype.reduceRight":"\nUint32Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14","Uint32Array.prototype.reverse":"\nUint32Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Uint32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] )\n    <Uint32Array>\n    > arr.reverse()\n    <Uint32Array>[ 3, 2, 1 ]","Uint32Array.prototype.set":"\nUint32Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4","Uint32Array.prototype.slice":"\nUint32Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3","Uint32Array.prototype.some":"\nUint32Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true","Uint32Array.prototype.sort":"\nUint32Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Uint32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Uint32Array>[ 0, 1, 1, 2, 2 ]","Uint32Array.prototype.subarray":"\nUint32Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint32Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Uint32Array>[ 3, 4, 5 ]","Uint32Array.prototype.toLocaleString":"\nUint32Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'","Uint32Array.prototype.toString":"\nUint32Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'","Uint32Array.prototype.values":"\nUint32Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint8Array, Uint8ClampedArray","umask":"\numask( [mask,] [options] )\n    Returns the current process mask, if not provided a mask; otherwise, sets\n    the process mask and returns the previous mask.\n\n    A mask is a set of bits, each of which restricts how its corresponding\n    permission is set for newly created files.\n\n    On POSIX platforms, each file has a set of attributes that control who can\n    read, write, or execute that file. Upon creating a file, file permissions\n    must be set to an initial setting. The process mask restricts those\n    permission settings.\n\n    If the mask contains a bit set to \"1\", the corresponding initial file\n    permission is disabled. If the mask contains a bit set to \"0\", the\n    corresponding permission is left to be determined by the requesting process\n    and the system.\n\n    The process mask is thus a filter that removes permissions as a file is\n    created; i.e., each bit set to a \"1\" removes its corresponding permission.\n\n    In octal representation, a mask is a four digit number, e.g., 0077,\n    comprised as follows:\n\n    - 0: special permissions (setuid, setgid, sticky bit)\n    - 0: (u)ser/owner permissions\n    - 7: (g)roup permissions\n    - 7: (o)thers/non-group permissions\n\n    Octal codes correspond to the following permissions:\n\n    - 0: read, write, execute\n    - 1: read, write\n    - 2: read, execute\n    - 3: read\n    - 4: write, execute\n    - 5: write\n    - 6: execute\n    - 7: no permissions\n\n    If provided fewer than four digits, the mask is left-padded with zeros.\n\n    Note, however, that only the last three digits (i.e., the file permissions\n    digits) of the mask are actually used when the mask is applied.\n\n    Permissions can be represented using the following symbolic form:\n\n        u=rwx,g=rwx,o=rwx\n\n    where\n\n    - u: user permissions\n    - g: group permissions\n    - o: other/non-group permissions\n    - r: read\n    - w: write\n    - x: execute\n\n    When setting permissions using symbolic notation, the function accepts a\n    mask expression of the form:\n\n        [<classes>]<operator><symbols>\n\n    where \"classes\" may be a combination of\n\n    - u: user\n    - g: group\n    - o: other/non-group\n    - a: all\n\n    \"symbols\" may be a combination of\n\n    - r: read\n    - w: write\n    - x: execute\n    - X: special execute\n    - s: setuid/gid on execution\n    - t: sticky\n\n    and \"operator\" may be one of\n\n    - +: enable\n    - -: disable\n    - =: enable specified and disable unspecified permissions\n\n    For example,\n\n    - u-w: disable user write permissions\n    - u+w: enable user write permissions\n    - u=w: enable user write permissions and disable user read and execute\n\n    To specify multiple changes, provide a comma-separated list of mask\n    expressions. For example,\n\n        u+rwx,g-x,o=r\n\n    would enable user read, write, and execute permissions, disable group\n    execute permissions, enable other read permissions, and disable other\n    write and execute permissions.\n\n    The `a` class indicates \"all\", which is the same as specifying \"ugo\". This\n    is the default class if a class is omitted when specifying permissions. For\n    example, `+x` is equivalent to `a+x` which is equivalent to `ugo+x` which\n    is equivalent to `u+x,g+x,o+x` and enables execution for all classes.\n\n    Parameters\n    ----------\n    mask: integer|string (optional)\n        Mask or mask expression. If the mask is a string, the mask is assumed to\n        be in symbolic notation.\n\n    options: Object (optional)\n        Options.\n\n    options.symbolic: boolean (optional)\n        Boolean indicating whether to return the mask using symbolic notation.\n\n    Returns\n    -------\n    mask: integer|string\n        Process mask. If provided a mask, the returned value is the previous\n        mask; otherwise, the returned value is the current process mask.\n\n    Examples\n    --------\n    > var mask = umask()\n    <number>\n    > mask = umask( { 'symbolic': true } )\n    <string>\n\n","uncapitalize":"\nuncapitalize( str )\n    Lowercases the first character of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Uncapitalized string.\n\n    Examples\n    --------\n    > var out = uncapitalize( 'Beep' )\n    'beep'\n    > out = uncapitalize( 'bOOp' )\n    'bOOp'\n\n    See Also\n    --------\n    capitalize, lowercase\n","uncapitalizeKeys":"\nuncapitalizeKeys( obj )\n    Converts the first letter of each object key to lowercase.\n\n    The function only transforms own properties. Hence, the function does not\n    transform inherited properties.\n\n    The function shallow copies key values.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > var obj = { 'AA': 1, 'BB': 2 };\n    > var out = uncapitalizeKeys( obj )\n    { 'aA': 1, 'bB': 2 }\n\n    See Also\n    --------\n    capitalizeKeys, lowercaseKeys\n","uncurry":"\nuncurry( fcn[, arity, ][thisArg] )\n    Transforms a curried function into a function invoked with multiple\n    arguments.\n\n    Parameters\n    ----------\n    fcn: Function\n        Curried function.\n\n    arity: integer (optional)\n        Number of parameters.\n\n    thisArg: any (optional)\n        Evaluation context.\n\n    Returns\n    -------\n    out: Function\n        Uncurried function.\n\n    Examples\n    --------\n    > function addX( x ) {\n    ...     return function addY( y ) {\n    ...         return x + y;\n    ...     };\n    ... };\n    > var fcn = uncurry( addX );\n    > var sum = fcn( 2, 3 )\n    5\n\n    // To enforce a fixed number of parameters, provide an `arity` argument:\n    > function add( x ) {\n    ...     return function add( y ) {\n    ...         return x + y;\n    ...     };\n    ... };\n    > fcn = uncurry( add, 2 );\n    > sum = fcn( 9 )\n    <Error>\n\n    // To specify an execution context, provide a `thisArg` argument:\n    > function addX( x ) {\n    ...     this.x = x;\n    ...     return addY;\n    ... };\n    > function addY( y ) {\n    ...     return this.x + y;\n    ... };\n    > fcn = uncurry( addX, {} );\n    > sum = fcn( 2, 3 )\n    5\n\n    See Also\n    --------\n    curry, uncurryRight\n","uncurryRight":"\nuncurryRight( fcn[, arity, ][thisArg] )\n    Transforms a curried function into a function invoked with multiple\n    arguments.\n\n    Provided arguments are applied starting from the right.\n\n    Parameters\n    ----------\n    fcn: Function\n        Curried function.\n\n    arity: integer (optional)\n        Number of parameters.\n\n    thisArg: any (optional)\n        Evaluation context.\n\n    Returns\n    -------\n    out: Function\n        Uncurried function.\n\n    Examples\n    --------\n    > function addX( x ) {\n    ...     return function addY( y ) {\n    ...         return x + y;\n    ...     };\n    ... };\n    > var fcn = uncurryRight( addX );\n    > var sum = fcn( 3, 2 )\n    5\n\n    // To enforce a fixed number of parameters, provide an `arity` argument:\n    > function add( y ) {\n    ...     return function add( x ) {\n    ...         return x + y;\n    ...     };\n    ... };\n    > fcn = uncurryRight( add, 2 );\n    > sum = fcn( 9 )\n    <Error>\n\n    // To specify an execution context, provide a `thisArg` argument:\n    > function addY( y ) {\n    ...     this.y = y;\n    ...     return addX;\n    ... };\n    > function addX( x ) {\n    ...     return x + this.y;\n    ... };\n    > fcn = uncurryRight( addY, {} );\n    > sum = fcn( 3, 2 )\n    5\n\n    See Also\n    --------\n    curry, curryRight, uncurry\n","UNICODE_MAX":"\nUNICODE_MAX\n    Maximum Unicode code point.\n\n    Examples\n    --------\n    > UNICODE_MAX\n    1114111\n\n    See Also\n    --------\n    UNICODE_MAX_BMP\n","UNICODE_MAX_BMP":"\nUNICODE_MAX_BMP\n    Maximum Unicode code point in the Basic Multilingual Plane (BMP).\n\n    Examples\n    --------\n    > UNICODE_MAX_BMP\n    65535\n\n    See Also\n    --------\n    UNICODE_MAX\n","UnicodeColumnChartSparkline":"\nUnicodeColumnChartSparkline( [data,] [options] )\n    Returns a sparkline column chart instance.\n\n    The `data` argument takes precedence over the `data` option.\n\n    Parameters\n    ----------\n    data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options: Object (optional)\n        Options.\n\n    options.autoRender: boolean (optional)\n        Boolean indicating whether to re-render on a 'change' event. Default:\n        false.\n\n    options.bufferSize: integer|null (optional)\n        Data buffer size. If provided, data is kept in a first-in first-out\n        (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n    options.data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options.description: string (optional)\n        Chart description.\n\n    options.infinities: boolean (optional)\n        Boolean indicating whether to encode infinite values. Default: false.\n\n    options.isDefined: Function (optional)\n        An accessor function indicating whether a datum is defined.\n\n    options.label: string (optional)\n        Data label.\n\n    options.yMax: number|null (optional)\n        Maximum value of the y-axis domain. If `null`, the value is computed\n        from the data. Default: null.\n\n    options.yMin: number|null (optional)\n        Minimum value of the y-axis domain. If `null`, the value is computed\n        from the data. Default: null.\n\n    Returns\n    -------\n    chart: ColumnChart\n        Column chart instance.\n\n    chart.autoRender\n        Rendering mode. If `true`, an instance renders on each 'change' event;\n        otherwise, rendering must be triggered manually.\n\n    chart.bufferSize\n        Data buffer size.\n\n    chart.description\n        Chart description.\n\n    chart.data\n        Chart data.\n\n    chart.label\n        Data label.\n\n    chart.infinities\n        Indicates whether to encode infinite values.\n\n    chart.isDefined( d, i )\n        An accessor function which defines whether a datum is defined. This\n        accessor is used to define how missing values are encoded. The default\n        behavior is to ignore values which are `NaN`.\n\n    chart.render()\n        Renders a column chart sparkline.\n\n    chart.yMax\n        Maximum value of the y-axis domain. If set to `null`, when accessed, the\n        returned value is computed from the data.\n\n    chart.yMin\n        Minimum value of the y-axis domain. If set to `null`, when accessed, the\n        returned value is computed from the data.\n\n    Examples\n    --------\n    > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n    > var chart = new UnicodeColumnChartSparkline( data );\n    > chart.render()\n    '▁█▅▃▆▆▅'\n\n    See Also\n    --------\n    plot, Plot, UnicodeSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeLineChartSparkline":"\nUnicodeLineChartSparkline( [data,] [options] )\n    Returns a sparkline line chart instance.\n\n    The `data` argument takes precedence over the `data` option.\n\n    Parameters\n    ----------\n    data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options: Object (optional)\n        Options.\n\n    options.autoRender: boolean (optional)\n        Boolean indicating whether to re-render on a 'change' event. Default:\n        false.\n\n    options.bufferSize: integer|null (optional)\n        Data buffer size. If provided, data is kept in a first-in first-out\n        (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n    options.data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options.description: string (optional)\n        Chart description.\n\n    options.infinities: boolean (optional)\n        Boolean indicating whether to encode infinite values. Default: false.\n\n    options.isDefined: Function (optional)\n        An accessor function indicating whether a datum is defined.\n\n    options.label: string (optional)\n        Data label.\n\n    options.yMax: number|null (optional)\n        Maximum value of the y-axis domain. If `null`, the value is computed\n        from the data. Default: null.\n\n    options.yMin: number|null (optional)\n        Minimum value of the y-axis domain. If `null`, the value is computed\n        from the data. Default: null.\n\n    Returns\n    -------\n    chart: LineChart\n        Line chart instance.\n\n    chart.autoRender\n        Rendering mode. If `true`, an instance renders on each 'change' event;\n        otherwise, rendering must be triggered manually.\n\n    chart.bufferSize\n        Data buffer size.\n\n    chart.description\n        Chart description.\n\n    chart.data\n        Chart data.\n\n    chart.label\n        Data label.\n\n    chart.infinities\n        Indicates whether to encode infinite values.\n\n    chart.isDefined( d, i )\n        An accessor function which defines whether a datum is defined. This\n        accessor is used to define how missing values are encoded. The default\n        behavior is to ignore values which are `NaN`.\n\n    chart.render()\n        Renders a line chart sparkline.\n\n    chart.yMax\n        Maximum value of the y-axis domain. If set to `null`, when accessed, the\n        returned value is computed from the data.\n\n    chart.yMin\n        Minimum value of the y-axis domain. If set to `null`, when accessed, the\n        returned value is computed from the data.\n\n    Examples\n    --------\n    > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n    > var chart = new UnicodeLineChartSparkline( data );\n    > chart.render()\n    '⡈⠑⠢⠔⠒⠒⠒'\n\n    See Also\n    --------\n    plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeSparkline":"\nUnicodeSparkline( [data,] [options] )\n    Returns a Unicode sparkline instance.\n\n    The following chart types are supported:\n\n    - column: column chart (e.g., ▃▆▂▄▁▅▅).\n    - line: line chart (e.g., ⡈⠑⠢⠔⠒⠒⠒).\n    - tristate: tristate chart (e.g., ▄▀──▀▄▄▀).\n    - up-down: up/down chart (e.g., ↓↑↑↑↑↓↓↑).\n    - win-loss: win/loss chart (e.g., ┌╵└┴╵╷╷╵).\n\n    The `data` argument takes precedence over the `data` option.\n\n    Parameters\n    ----------\n    data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options: Object (optional)\n        Options.\n\n    options.autoRender: boolean (optional)\n        Boolean indicating whether to re-render on a 'change' event. Default:\n        false.\n\n    options.bufferSize: integer|null (optional)\n        Data buffer size. If provided, data is kept in a first-in first-out\n        (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n    options.data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options.description: string (optional)\n        Chart description.\n\n    options.infinities: boolean (optional)\n        Boolean indicating whether to encode infinite values. Default: false.\n\n    options.isDefined: Function (optional)\n        An accessor function indicating whether a datum is defined.\n\n    options.label: string (optional)\n        Data label.\n\n    options.type: string (optional)\n        Chart type. Default: 'column'.\n\n    options.yMax: number|null (optional)\n        Maximum value of the y-axis domain. If `null`, the value is computed\n        from the data. Default: null.\n\n    options.yMin: number|null (optional)\n        Minimum value of the y-axis domain. If `null`, the value is computed\n        from the data. Default: null.\n\n    Returns\n    -------\n    chart: ColumnChart\n        Column chart instance.\n\n    chart.autoRender\n        Rendering mode. If `true`, an instance renders on each 'change' event;\n        otherwise, rendering must be triggered manually.\n\n    chart.bufferSize\n        Data buffer size.\n\n    chart.description\n        Chart description.\n\n    chart.data\n        Chart data.\n\n    chart.label\n        Data label.\n\n    chart.infinities\n        Indicates whether to encode infinite values.\n\n    chart.isDefined( d, i )\n        An accessor function which defines whether a datum is defined. This\n        accessor is used to define how missing values are encoded. The default\n        behavior is to ignore values which are `NaN`.\n\n    chart.render()\n        Renders a column chart sparkline.\n\n    chart.type\n        Chart type.\n\n    chart.yMax\n        Maximum value of the y-axis domain. If set to `null`, when accessed, the\n        returned value is computed from the data.\n\n    chart.yMin\n        Minimum value of the y-axis domain. If set to `null`, when accessed, the\n        returned value is computed from the data.\n\n    Examples\n    --------\n    > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n    > var chart = new UnicodeSparkline( data );\n    > chart.render()\n    '▁█▅▃▆▆▅'\n    > chart.type = 'line';\n    > chart.render()\n    '⡈⠑⠢⠔⠒⠒⠒'\n\n    See Also\n    --------\n    plot, Plot, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeTristateChartSparkline":"\nUnicodeTristateChartSparkline( [data,] [options] )\n    Returns a sparkline tristate chart instance.\n\n    In a tristate chart, negative values are encoded as lower blocks, positive\n    values are encoded as upper blocks, and values equal to zero are encoded as\n    middle lines.\n\n    The `data` argument takes precedence over the `data` option.\n\n    Parameters\n    ----------\n    data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options: Object (optional)\n        Options.\n\n    options.autoRender: boolean (optional)\n        Boolean indicating whether to re-render on a 'change' event. Default:\n        false.\n\n    options.bufferSize: integer|null (optional)\n        Data buffer size. If provided, data is kept in a first-in first-out\n        (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n    options.data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options.description: string (optional)\n        Chart description.\n\n    options.isDefined: Function (optional)\n        An accessor function indicating whether a datum is defined.\n\n    options.label: string (optional)\n        Data label.\n\n    Returns\n    -------\n    chart: TristateChart\n        Tristate chart instance.\n\n    chart.autoRender\n        Rendering mode. If `true`, an instance renders on each 'change' event;\n        otherwise, rendering must be triggered manually.\n\n    chart.bufferSize\n        Data buffer size.\n\n    chart.description\n        Chart description.\n\n    chart.data\n        Chart data.\n\n    chart.label\n        Data label.\n\n    chart.isDefined( d, i )\n        An accessor function which defines whether a datum is defined. This\n        accessor is used to define how missing values are encoded. The default\n        behavior is to ignore values which are `NaN`.\n\n    chart.render()\n        Renders a tristate chart sparkline.\n\n    Examples\n    --------\n    > var data = [ -1, 1, 0, 0, 1, -1, -1, 1 ];\n    > var chart = new UnicodeTristateChartSparkline( data );\n    > chart.render()\n    '▄▀──▀▄▄▀'\n\n    See Also\n    --------\n    plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeUpDownChartSparkline":"\nUnicodeUpDownChartSparkline( [data,] [options] )\n    Returns a sparkline up/down chart instance.\n\n    Glyphs:\n\n    | Value | Glyph |\n    |:-----:|:-----:|\n    |   1   |   ↑   |\n    |   -1  |   ↓   |\n\n    If provided any other value other than 1 or -1, the value is encoded as a\n    missing value.\n\n    The `data` argument takes precedence over the `data` option.\n\n    Parameters\n    ----------\n    data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options: Object (optional)\n        Options.\n\n    options.autoRender: boolean (optional)\n        Boolean indicating whether to re-render on a 'change' event. Default:\n        false.\n\n    options.bufferSize: integer|null (optional)\n        Data buffer size. If provided, data is kept in a first-in first-out\n        (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n    options.data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options.description: string (optional)\n        Chart description.\n\n    options.isDefined: Function (optional)\n        An accessor function indicating whether a datum is defined.\n\n    options.label: string (optional)\n        Data label.\n\n    Returns\n    -------\n    chart: UpDownChart\n        Chart instance.\n\n    chart.autoRender\n        Rendering mode. If `true`, an instance renders on each 'change' event;\n        otherwise, rendering must be triggered manually.\n\n    chart.bufferSize\n        Data buffer size.\n\n    chart.description\n        Chart description.\n\n    chart.data\n        Chart data.\n\n    chart.label\n        Data label.\n\n    chart.isDefined( d, i )\n        An accessor function which defines whether a datum is defined. This\n        accessor is used to define how missing values are encoded. The default\n        behavior is to ignore any values which are not 1 or -1.\n\n    chart.render()\n        Renders an up/down chart sparkline.\n\n    Examples\n    --------\n    > var data = [ -1, 1, 1, 1, 1, -1, -1, 1 ];\n    > var chart = new UnicodeUpDownChartSparkline( data );\n    > chart.render()\n    '↓↑↑↑↑↓↓↑'\n\n    See Also\n    --------\n    plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeWinLossChartSparkline":"\nUnicodeWinLossChartSparkline( [data,] [options] )\n    Returns a sparkline win/loss chart instance.\n\n    Glyphs:\n\n    | Value | Glyph |\n    |:-----:|:-----:|\n    |   1   |   ╵   |\n    |   -1  |   ╷   |\n    |   2   |   └   |\n    |   -2  |   ┌   |\n\n    If a `2` or `-2` is preceded by a `2` or `-2`,\n\n    | Value | Glyph |\n    |:-----:|:-----:|\n    |   2   |   ┴   |\n    |   -2  |   ┬   |\n\n    Based on the win/loss analogy,\n\n    - 1: win away\n    - 2: win at home\n    - -1: loss away\n    - -2: loss at home\n\n    If provided any value other than 1, -1, 2, or -2, the value is encoded as a\n    missing value.\n\n    The `data` argument takes precedence over the `data` option.\n\n    Parameters\n    ----------\n    data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options: Object (optional)\n        Options.\n\n    options.autoRender: boolean (optional)\n        Boolean indicating whether to re-render on a 'change' event. Default:\n        false.\n\n    options.bufferSize: integer|null (optional)\n        Data buffer size. If provided, data is kept in a first-in first-out\n        (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n    options.data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options.description: string (optional)\n        Chart description.\n\n    options.isDefined: Function (optional)\n        An accessor function indicating whether a datum is defined.\n\n    options.label: string (optional)\n        Data label.\n\n    Returns\n    -------\n    chart: WinLossChart\n        Chart instance.\n\n    chart.autoRender\n        Rendering mode. If `true`, an instance renders on each 'change' event;\n        otherwise, rendering must be triggered manually.\n\n    chart.bufferSize\n        Data buffer size.\n\n    chart.description\n        Chart description.\n\n    chart.data\n        Chart data.\n\n    chart.label\n        Data label.\n\n    chart.isDefined( d, i )\n        An accessor function which defines whether a datum is defined. This\n        accessor is used to define how missing values are encoded. The default\n        behavior is to ignore any values which are not 1, -1, 2, or -2.\n\n    chart.render()\n        Renders a win/loss chart sparkline.\n\n    Examples\n    --------\n    > var data = [ -2, 1, 2, 2, 1, -1, -1, 1 ];\n    > var chart = new UnicodeWinLossChartSparkline( data );\n    > chart.render()\n    '┌╵└┴╵╷╷╵'\n\n    See Also\n    --------\n    plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline\n","unlink":"\nunlink( path, clbk )\n    Asynchronously removes a directory entry.\n\n    If a provided path is a symbolic link, the function removes the symbolic\n    link named by the path and does not affect any file or directory named by\n    the contents of the symbolic link.\n\n    Otherwise, the function removes the link named by the provided path and\n    decrements the link count of the file referenced by the link.\n\n    When a file's link count becomes 0 and no process has the file open, the\n    space occupied by the file is freed and the file is no longer accessible.\n\n    If one or more processes have the file open when the last link is removed,\n    the link is removed before the function returns; however, the removal of\n    file contents is postponed until all references to the file are closed.\n\n    If the path refers to a socket, FIFO, or device, processes which have the\n    object open may continue to use it.\n\n    The path argument should *not* be a directory. To remove a directory, use\n    rmdir().\n\n    Parameters\n    ----------\n    path: string|Buffer|integer\n        Entry path.\n\n    clbk: Function\n        Callback to invoke upon removing an entry.\n\n    Examples\n    --------\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     }\n    ... };\n    > unlink( './beep/boop.txt', done );\n\n\nunlink.sync( path )\n    Synchronously removes a directory entry.\n\n   Parameters\n    ----------\n    path: string|Buffer|integer\n        Entry path.\n\n    Returns\n    -------\n    out: Error|null\n        Error object or null.\n\n    Examples\n    --------\n    > var out = unlink.sync( './beep/boop.txt' );\n\n    See Also\n    --------\n    exists\n","unlink.sync":"\nunlink.sync( path )\n    Synchronously removes a directory entry.\n\n   Parameters\n    ----------\n    path: string|Buffer|integer\n        Entry path.\n\n    Returns\n    -------\n    out: Error|null\n        Error object or null.\n\n    Examples\n    --------\n    > var out = unlink.sync( './beep/boop.txt' );\n\n    See Also\n    --------\n    exists","unshift":"\nunshift( collection, ...items )\n    Adds one or more elements to the beginning of a collection.\n\n    If the input collection is a typed array, the output value does not equal\n    the input reference and the underlying `ArrayBuffer` may *not* be the same\n    as the `ArrayBuffer` belonging to the input view.\n\n    For purposes of generality, always treat the output collection as distinct\n    from the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        A collection. If the collection is an `Object`, the collection should be\n        array-like.\n\n    items: ...any\n        Items to add.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Updated collection.\n\n    Examples\n    --------\n    // Arrays:\n    > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > arr = unshift( arr, 6.0, 7.0 )\n    [ 6.0, 7.0, 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Typed arrays:\n    > arr = new Float64Array( [ 1.0, 2.0 ] );\n    > arr = unshift( arr, 3.0, 4.0 )\n    <Float64Array>[ 3.0, 4.0, 1.0, 2.0 ]\n\n    // Array-like object:\n    > arr = { 'length': 1, '0': 1.0 };\n    > arr = unshift( arr, 2.0, 3.0 )\n    { 'length': 3, '0': 2.0, '1': 3.0, '2': 1.0 }\n\n    See Also\n    --------\n    pop, push, shift\n","until":"\nuntil( predicate, fcn[, thisArg] )\n    Invokes a function until a test condition is true.\n\n    When invoked, both the predicate function and the function to invoke are\n    provided a single argument:\n\n    - i: iteration number (starting from zero).\n\n    Parameters\n    ----------\n    predicate: Function\n        The predicate function which indicates whether to stop invoking a\n        function.\n\n    fcn: Function\n        The function to invoke.\n\n    thisArg: any (optional)\n        Execution context for the invoked function.\n\n    Examples\n    --------\n    > function predicate( i ) { return ( i >= 5 ); };\n    > function beep( i ) { console.log( 'boop: %d', i ); };\n    > until( predicate, beep )\n    boop: 0\n    boop: 1\n    boop: 2\n    boop: 3\n    boop: 4\n\n    See Also\n    --------\n    doUntil, doWhile, untilAsync, untilEach, whilst\n","untilAsync":"\nuntilAsync( predicate, fcn, done[, thisArg] )\n    Invokes a function until a test condition is true.\n\n    The predicate function is provided two arguments:\n\n    - i: iteration number (starting from zero).\n    - clbk: a callback indicating whether to invoke `fcn`.\n\n    The `clbk` function accepts two arguments:\n\n    - error: error argument.\n    - bool: test result.\n\n    If the test result is falsy, the function invokes `fcn`; otherwise, the\n    function invokes the `done` callback.\n\n    The function to invoke is provided two arguments:\n\n    - i: iteration number (starting from zero).\n    - next: a callback which must be invoked before proceeding to the next\n      iteration.\n\n    The first argument of the `next` callback is an `error` argument. If `fcn`\n    calls the `next` callback with a truthy `error` argument, the function\n    suspends execution and immediately calls the `done` callback for subsequent\n    `error` handling.\n\n    The `done` callback is invoked with an `error` argument and any arguments\n    passed to the final `next` callback.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Parameters\n    ----------\n    predicate: Function\n        The predicate function which indicates whether to continue invoking a\n        function.\n\n    fcn: Function\n        The function to invoke.\n\n    done: Function\n        Callback to invoke upon completion.\n\n    thisArg: any (optional)\n        Execution context for the invoked function.\n\n    Examples\n    --------\n    > function predicate( i, clbk ) { clbk( null, i >= 5 ); };\n    > function fcn( i, next ) {\n    ...     setTimeout( onTimeout, i );\n    ...     function onTimeout() {\n    ...         next( null, 'boop'+i );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > untilAsync( predicate, fcn, done )\n    boop: 4\n\n    See Also\n    --------\n    doUntilAsync, doWhileAsync, until, whileAsync\n","untilEach":"\nuntilEach( collection, predicate, fcn[, thisArg] )\n    Until a test condition is true, invokes a function for each element in a\n    collection.\n\n    When invoked, both the predicate function and the function to apply are\n    provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    predicate: Function\n        The predicate function which indicates whether to stop iterating over a\n        collection.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    thisArg: any (optional)\n        Execution context for the applied function.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function predicate( v ) { return v !== v; };\n    > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n    > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n    > untilEach( arr, predicate, logger )\n    0: 1\n    1: 2\n    2: 3\n    3: 4\n\n    See Also\n    --------\n    untilEachRight, whileEach\n","untilEachRight":"\nuntilEachRight( collection, predicate, fcn[, thisArg] )\n    Until a test condition is true, invokes a function for each element in a\n    collection, iterating from right to left.\n\n    When invoked, both the predicate function and the function to apply are\n    provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    predicate: Function\n        The predicate function which indicates whether to stop iterating over a\n        collection.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    thisArg: any (optional)\n        Execution context for the applied function.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function predicate( v ) { return v !== v; };\n    > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n    > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n    > untilEachRight( arr, predicate, logger )\n    5: 5\n    4: 4\n    3: 3\n    2: 2\n\n    See Also\n    --------\n    untilEach, whileEachRight\n","unzip":"\nunzip( arr[, idx] )\n    Unzips a zipped array (i.e., a nested array of tuples).\n\n    Parameters\n    ----------\n    arr: Array\n        Zipped array.\n\n    idx: Array<number> (optional)\n        Array of indices specifying which tuple elements to unzip.\n\n    Returns\n    -------\n    out: Array\n        Array of unzipped arrays.\n\n    Examples\n    --------\n    // Basic usage:\n    > var arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\n    > var out = unzip( arr )\n    [ [ 1, 2 ], [ 'a', 'b' ], [ 3, 4 ] ]\n\n    // Provide indices:\n    > arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\n    > out = unzip( arr, [ 0, 2 ] )\n    [ [ 1, 2 ], [ 3, 4 ] ]\n\n    See Also\n    --------\n    zip\n","uppercase":"\nuppercase( str )\n    Converts a string to uppercase.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Uppercase string.\n\n    Examples\n    --------\n    > var out = uppercase( 'bEEp' )\n    'BEEP'\n\n    See Also\n    --------\n    capitalize, lowercase\n","uppercaseKeys":"\nuppercaseKeys( obj )\n    Converts each object key to uppercase.\n\n    The function only transforms own properties. Hence, the function does not\n    transform inherited properties.\n\n    The function shallow copies key values.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > var obj = { 'a': 1, 'b': 2 };\n    > var out = uppercaseKeys( obj )\n    { 'A': 1, 'B': 2 }\n\n    See Also\n    --------\n    capitalizeKeys, lowercaseKeys\n","US_STATES_ABBR":"\nUS_STATES_ABBR()\n    Returns a list of US state two-letter abbreviations in alphabetical order\n    according to state name.\n\n    Returns\n    -------\n    out: Array<string>\n        List of US state two-letter abbreviations.\n\n    Examples\n    --------\n    > var list = US_STATES_ABBR()\n    [ 'AL', 'AK', 'AZ', 'AR', ... ]\n\n    See Also\n    --------\n    US_STATES_CAPITALS, US_STATES_NAMES\n","US_STATES_CAPITALS":"\nUS_STATES_CAPITALS()\n    Returns a list of US state capitals in alphabetical order according to state\n    name.\n\n    Returns\n    -------\n    out: Array<string>\n        List of US state capitals.\n\n    Examples\n    --------\n    > var list = US_STATES_CAPITALS()\n    [ 'Montgomery', 'Juneau', 'Phoenix', ... ]\n\n    See Also\n    --------\n    US_STATES_ABBR, US_STATES_CAPITALS_NAMES, US_STATES_NAMES, US_STATES_NAMES_CAPITALS\n","US_STATES_CAPITALS_NAMES":"\nUS_STATES_CAPITALS_NAMES()\n    Returns an object mapping US state capitals to state names.\n\n    Returns\n    -------\n    out: Object\n        An object mapping US state capitals to state names.\n\n    Examples\n    --------\n    > var out = US_STATES_CAPITALS_NAMES()\n    { 'Montgomery': 'Alabama', 'Juneau': 'Alaska', ... }\n\n    See Also\n    --------\n    US_STATES_CAPITALS, US_STATES_NAMES, US_STATES_NAMES_CAPITALS\n","US_STATES_NAMES":"\nUS_STATES_NAMES()\n    Returns a list of US state names in alphabetical order.\n\n    Returns\n    -------\n    out: Array<string>\n        List of US state names.\n\n    Examples\n    --------\n    > var list = US_STATES_NAMES()\n    [ 'Alabama', 'Alaska', 'Arizona', ... ]\n\n    See Also\n    --------\n    US_STATES_ABBR, US_STATES_CAPITALS, US_STATES_CAPITALS_NAMES, US_STATES_NAMES_CAPITALS\n","US_STATES_NAMES_CAPITALS":"\nUS_STATES_NAMES_CAPITALS()\n    Returns an object mapping US state names to state capitals.\n\n    Returns\n    -------\n    out: Object\n        An object mapping US state names to state capitals.\n\n    Examples\n    --------\n    > var out = US_STATES_NAMES_CAPITALS()\n    { 'Alabama': 'Montgomery', 'Alaska': 'Juneau', ... }\n\n    See Also\n    --------\n    US_STATES_CAPITALS, US_STATES_NAMES, US_STATES_NAMES_CAPITALS\n","utf16ToUTF8Array":"\nutf16ToUTF8Array( str )\n    Converts a UTF-16 encoded string to an array of integers using UTF-8\n    encoding.\n\n    The following byte sequences are used to represent a character. The sequence\n    depends on the code point:\n\n        0x00000000 - 0x0000007F:\n            0xxxxxxx\n\n        0x00000080 - 0x000007FF:\n            110xxxxx 10xxxxxx\n\n        0x00000800 - 0x0000FFFF:\n            1110xxxx 10xxxxxx 10xxxxxx\n\n        0x00010000 - 0x001FFFFF:\n            11110xxx 10xxxxxx 10xxxxxx 10xxxxxx\n\n    The `x` bit positions correspond to code point bits.\n\n    Only the shortest possible multi-byte sequence which can represent a code\n    point is used.\n\n    Parameters\n    ----------\n    str: string\n        UTF-16 encoded string.\n\n    Returns\n    -------\n    out: Array\n        Array of integers.\n\n    Examples\n    --------\n    > var str = '☃';\n    > var out = utf16ToUTF8Array( str )\n    [ 226, 152, 131 ]\n\n","vartest":"\nvartest( x, y[, options] )\n    Computes a two-sample F-test for equal variances.\n\n    The returned object comes with a `.print()` method which when invoked will\n    print a formatted output of the results of the hypothesis test.\n\n    Parameters\n    ----------\n    x: Array<number>\n        First data array.\n\n    y: Array<number>\n        Second data array.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.alternative: string (optional)\n        Either `two-sided`, `less` or `greater`.\n\n    options.ratio: number (optional)\n        Positive number denoting the ratio of the two population variances under\n        the null hypothesis. Default: `1`.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Used significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.ci: Array<number>\n        1-alpha confidence interval for the ratio of variances.\n\n    out.nullValue: number\n        Assumed ratio of variances under H0.\n\n    out.xvar: number\n        Sample variance of `x`.\n\n    out.yvar: number\n        Sample variance of `y`.\n\n    out.alternative: string\n        Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n    out.dfX: number\n        Numerator degrees of freedom.\n\n    out.dfY: number\n        Denominator degrees of freedom.\n\n    out.method: string\n        Name of test.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    > var x = [ 610, 610, 550, 590, 565, 570 ];\n    > var y = [ 560, 550, 580, 550, 560, 590, 550, 590 ];\n    > var out = vartest( x, y )\n    {\n        rejected: false,\n        pValue: ~0.399,\n        statistic: ~1.976,\n        ci: [ ~0.374, ~13.542 ],\n        // ...\n    }\n\n    // Print table output:\n    > var table = out.print()\n    F test for comparing two variances\n\n    Alternative hypothesis: True ratio in variances is not equal to 1\n\n        pValue: 0.3992\n        statistic: 1.976\n        variance of x: 617.5 (df of x: 5)\n        variance of y: 312.5 (df of y: 7)\n        95% confidence interval: [0.3739,13.5417]\n\n    Test Decision: Fail to reject null in favor of alternative at 5%\n    significance level\n\n    See Also\n    --------\n    bartlettTest\n","waterfall":"\nwaterfall( fcns, clbk[, thisArg] )\n    Executes functions in series, passing the results of one function as\n    arguments to the next function.\n\n    The last argument applied to each waterfall function is a callback. The\n    callback should be invoked upon a series function completion. The first\n    argument is reserved as an error argument (which can be `null`). Any results\n    which should be passed to the next function in the series should be provided\n    beginning with the second argument.\n\n    If any function calls the provided callback with a truthy `error` argument,\n    the waterfall suspends execution and immediately calls the completion\n    callback for subsequent error handling.\n\n    Execution is *not* guaranteed to be asynchronous. To ensure asynchrony, wrap\n    the completion callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Parameters\n    ----------\n    fcns: Array<Function>\n        Array of functions.\n\n    clbk: Function\n        Callback to invoke upon completion.\n\n    thisArg: any (optional)\n        Function context.\n\n    Examples\n    --------\n    > function foo( next ) { next( null, 'beep' ); };\n    > function bar( str, next ) { console.log( str ); next(); };\n    > function done( error ) { if ( error ) { throw error; } };\n    > var fcns = [ foo, bar ];\n    > waterfall( fcns, done );\n\n\nwaterfall.factory( fcns, clbk[, thisArg] )\n    Returns a reusable waterfall function.\n\n    Parameters\n    ----------\n    fcns: Array<Function>\n        Array of functions.\n\n    clbk: Function\n        Callback to invoke upon completion.\n\n    thisArg: any (optional)\n        Function context.\n\n    Returns\n    -------\n    fcn: Function\n        Waterfall function.\n\n    Examples\n    --------\n    > function foo( next ) { next( null, 'beep' ); };\n    > function bar( str, next ) { console.log( str ); next(); };\n    > function done( error ) { if ( error ) { throw error; } };\n    > var fcns = [ foo, bar ];\n    > var waterfall = waterfall.factory( fcns, done );\n    > waterfall();\n    > waterfall();\n    > waterfall();\n\n","waterfall.factory":"\nwaterfall.factory( fcns, clbk[, thisArg] )\n    Returns a reusable waterfall function.\n\n    Parameters\n    ----------\n    fcns: Array<Function>\n        Array of functions.\n\n    clbk: Function\n        Callback to invoke upon completion.\n\n    thisArg: any (optional)\n        Function context.\n\n    Returns\n    -------\n    fcn: Function\n        Waterfall function.\n\n    Examples\n    --------\n    > function foo( next ) { next( null, 'beep' ); };\n    > function bar( str, next ) { console.log( str ); next(); };\n    > function done( error ) { if ( error ) { throw error; } };\n    > var fcns = [ foo, bar ];\n    > var waterfall = waterfall.factory( fcns, done );\n    > waterfall();\n    > waterfall();\n    > waterfall();","WebAssemblyMemory":"\nWebAssemblyMemory( descriptor )\n    WebAssembly memory constructor.\n\n    Parameters\n    ----------\n    descriptor: Object\n        Memory descriptor object.\n\n    descriptor.initial: integer\n        Initial memory size in units of WebAssembly pages (i.e., 64KiB).\n\n    descriptor.maximum: integer (optional)\n        Maximum memory size in units of WebAssembly pages (i.e., 64KiB).\n\n    descriptor.shared: boolean (optional)\n        Boolean indicating whether the memory is shared. Default: false.\n\n    Returns\n    -------\n    out: Memory\n        WebAssembly memory instance.\n\n    Examples\n    --------\n    > var mem = new WebAssemblyMemory( { 'initial': 0 } )\n    <Memory>\n\n\nWebAssemblyMemory.prototype.buffer\n    Read-only property which returns the ArrayBuffer (or SharedArrayBuffer)\n    referenced by the memory instance.\n\n    Examples\n    --------\n    > var mem = new WebAssemblyMemory( { 'initial': 0 } );\n    > mem.buffer\n    <ArrayBuffer>\n\n\nWebAssemblyMemory.prototype.grow( delta )\n    Increases the size of the memory instance by a specified number of\n    WebAssembly pages (i.e., 64KiB).\n\n    Upon increasing the size, the previous ArrayBuffer is detached, thus\n    invalidating any typed arrays which were views over the previous\n    ArrayBuffer.\n\n    Detachment means that the previous ArrayBuffer byte length becomes zero, and\n    it no longer has bytes accessible to JavaScript.\n\n    ArrayBuffer detachment applies even when `delta` is zero.\n\n    Detachment only applies for non-shared memory instances. For a shared memory\n    instance, the initial buffer (which is a SharedArrayBuffer) will not become\n    detached and, instead, its length will not be updated.\n\n    Accesses to the `buffer` property after growing a SharedArrayBuffer will\n    yield a larger SharedArrayBuffer which may access a larger span of memory\n    than the buffer before growing memory.\n\n    Every SharedArrayBuffer accessed via the `buffer` property will always refer\n    to the start of the same memory address range and thus manipulate the same\n    data.\n\n    Parameters\n    ----------\n    delta: integer\n        Number of WebAssembly pages (i.e., 64KiB) by which to grow the\n        underlying memory.\n\n    Returns\n    -------\n    out: integer\n        Size of the previous memory (in units of pages).\n\n    Examples\n    --------\n    > var mem = new WebAssemblyMemory( { 'initial': 0 } );\n    > mem.grow( 1 )\n    <number>\n\n","WebAssemblyMemory.prototype.buffer":"\nWebAssemblyMemory.prototype.buffer\n    Read-only property which returns the ArrayBuffer (or SharedArrayBuffer)\n    referenced by the memory instance.\n\n    Examples\n    --------\n    > var mem = new WebAssemblyMemory( { 'initial': 0 } );\n    > mem.buffer\n    <ArrayBuffer>","WebAssemblyMemory.prototype.grow":"\nWebAssemblyMemory.prototype.grow( delta )\n    Increases the size of the memory instance by a specified number of\n    WebAssembly pages (i.e., 64KiB).\n\n    Upon increasing the size, the previous ArrayBuffer is detached, thus\n    invalidating any typed arrays which were views over the previous\n    ArrayBuffer.\n\n    Detachment means that the previous ArrayBuffer byte length becomes zero, and\n    it no longer has bytes accessible to JavaScript.\n\n    ArrayBuffer detachment applies even when `delta` is zero.\n\n    Detachment only applies for non-shared memory instances. For a shared memory\n    instance, the initial buffer (which is a SharedArrayBuffer) will not become\n    detached and, instead, its length will not be updated.\n\n    Accesses to the `buffer` property after growing a SharedArrayBuffer will\n    yield a larger SharedArrayBuffer which may access a larger span of memory\n    than the buffer before growing memory.\n\n    Every SharedArrayBuffer accessed via the `buffer` property will always refer\n    to the start of the same memory address range and thus manipulate the same\n    data.\n\n    Parameters\n    ----------\n    delta: integer\n        Number of WebAssembly pages (i.e., 64KiB) by which to grow the\n        underlying memory.\n\n    Returns\n    -------\n    out: integer\n        Size of the previous memory (in units of pages).\n\n    Examples\n    --------\n    > var mem = new WebAssemblyMemory( { 'initial': 0 } );\n    > mem.grow( 1 )\n    <number>","whileAsync":"\nwhileAsync( predicate, fcn, done[, thisArg] )\n    Invokes a function while a test condition is true.\n\n    The predicate function is provided two arguments:\n\n    - i: iteration number (starting from zero).\n    - clbk: a callback indicating whether to invoke `fcn`.\n\n    The `clbk` function accepts two arguments:\n\n    - error: error argument.\n    - bool: test result.\n\n    If the test result is truthy, the function invokes `fcn`; otherwise, the\n    function invokes the `done` callback.\n\n    The function to invoke is provided two arguments:\n\n    - i: iteration number (starting from zero).\n    - next: a callback which must be invoked before proceeding to the next\n      iteration.\n\n    The first argument of the `next` callback is an `error` argument. If `fcn`\n    calls the `next` callback with a truthy `error` argument, the function\n    suspends execution and immediately calls the `done` callback for subsequent\n    `error` handling.\n\n    The `done` callback is invoked with an `error` argument and any arguments\n    passed to the final `next` callback.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Parameters\n    ----------\n    predicate: Function\n        The predicate function which indicates whether to continue invoking a\n        function.\n\n    fcn: Function\n        The function to invoke.\n\n    done: Function\n        Callback to invoke upon completion.\n\n    thisArg: any (optional)\n        Execution context for the invoked function.\n\n    Examples\n    --------\n    > function predicate( i, clbk ) { clbk( null, i < 5 ); };\n    > function fcn( i, next ) {\n    ...     setTimeout( onTimeout, i );\n    ...     function onTimeout() {\n    ...         next( null, 'boop'+i );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > whileAsync( predicate, fcn, done )\n    boop: 4\n\n    See Also\n    --------\n    doUntilAsync, doWhileAsync, untilAsync, whilst\n","whileEach":"\nwhileEach( collection, predicate, fcn[, thisArg] )\n    While a test condition is true, invokes a function for each element in a\n    collection.\n\n    When invoked, both the predicate function and the function to apply are\n    provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    predicate: Function\n        The predicate function which indicates whether to continue iterating\n        over a collection.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    thisArg: any (optional)\n        Execution context for the applied function.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === v; };\n    > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n    > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n    > whileEach( arr, predicate, logger )\n    0: 1\n    1: 2\n    2: 3\n    3: 4\n\n    See Also\n    --------\n    untilEach, whileEachRight\n","whileEachRight":"\nwhileEachRight( collection, predicate, fcn[, thisArg] )\n    While a test condition is true, invokes a function for each element in a\n    collection, iterating from right to left.\n\n    When invoked, both the predicate function and the function to apply are\n    provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    predicate: Function\n        The predicate function which indicates whether to continue iterating\n        over a collection.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    thisArg: any (optional)\n        Execution context for the applied function.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === v; };\n    > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n    > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n    > whileEachRight( arr, predicate, logger )\n    5: 5\n    4: 4\n    3: 3\n    2: 2\n\n    See Also\n    --------\n    whileEach, untilEachRight\n","whilst":"\nwhilst( predicate, fcn[, thisArg] )\n    Invokes a function while a test condition is true.\n\n    When invoked, both the predicate function and the function to invoke are\n    provided a single argument:\n\n    - i: iteration number (starting from zero).\n\n    Parameters\n    ----------\n    predicate: Function\n        The predicate function which indicates whether to continue invoking a\n        function.\n\n    fcn: Function\n        The function to invoke.\n\n    thisArg: any (optional)\n        Execution context for the invoked function.\n\n    Examples\n    --------\n    > function predicate( i ) { return ( i < 5 ); };\n    > function beep( i ) { console.log( 'boop: %d', i ); };\n    > whilst( predicate, beep )\n    boop: 0\n    boop: 1\n    boop: 2\n    boop: 3\n    boop: 4\n\n    See Also\n    --------\n    doUntil, doWhile, until, whileAsync, whileEach\n","wilcoxon":"\nwilcoxon( x[, y][, options] )\n    Computes a one-sample or paired Wilcoxon signed rank test.\n\n    When no `y` is supplied, the function performs a one-sample  Wilcoxon signed\n    rank test for the null hypothesis that the data is drawn from a symmetric\n    distribution around zero.\n\n    When `y` is supplied, the function tests whether the\n    differences `x - y` come from a symmetric distribution around zero.\n\n    If `x` has less than fifty elements, an exact p-value is computed if there\n    are no zero values or ties. Otherwise, a normal approximation is used.\n\n    The returned object comes with a `.print()` method which when invoked will\n    print a formatted output of the results of the hypothesis test.\n\n    Parameters\n    ----------\n    x: Array<number>|TypedArray\n        Data array.\n\n    y: Array<number>|TypedArray (optional)\n        Paired data array.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.alternative: string (optional)\n        Indicates whether the alternative hypothesis is that the mean of `x` is\n        larger than `mu` (`greater`), smaller than `mu` (`less`), or equal to\n        `mu` (`two-sided`). Default: `'two-sided'`.\n\n    options.correction: boolean (optional)\n        Determines whether to apply continuity correction adjusting the Wilcoxon\n        rank statistic by 0.5 towards the mean when using the normal\n        approximation. Default: `true`.\n\n    options.exact: boolean (optional)\n        Determines whether to force use of the exact distribution instead of a\n        normal approximation when there are more than fifty data points.\n        Default: `false`.\n\n    options.mu: number (optional)\n        Hypothesized true location under the null hypothesis. Set this option to\n        test whether the data comes from a distribution with the specified `mu`.\n        Default: `0`.\n\n    options.zeroMethod: string (optional)\n        Method governing how zero-differences are handled (`pratt`, `wilcox`, or\n        `zsplit`). When set to `pratt`, differences of zero are used to\n        calculate ranks but their ranks are then dropped. When set to `wilcox`,\n        all zero-differences are discarded. When set to `zsplit`, differences of\n        zero are used to rank and their ranks are then split between positive\n        and negative ones. Default: `'wilcox'`.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Used significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.nullValue: number\n        Assumed location parameter under H0.\n\n    out.alternative: string\n        Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n    out.method: string\n        Name of test.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    // One-sample test:\n    > var arr = [ 6, 8, 14, 16, 23, 24, 28, 29, 41, -48, 49, 56, 60, -67, 75 ];\n    > var out = wilcoxon( x )\n    {\n        'rejected': true,\n        'alpha': 0.05,\n        'pValue': 0.04125976562499978,\n        'statistic': 96\n        // ...\n    }\n\n    // Paired test:\n    > runif = base.random.discreteUniform.factory( 1, 5, { 'seed': 786 });\n    > var x = new Array( 100 );\n    > var y = new Array( 100 );\n    > for ( i = 0; i < x.length; i++ ) {\n    ...     x[ i ] = runif();\n    ...     y[ i ] = runif();\n    ... }\n    > out = wilcoxon( x, y )\n    {\n        'rejected': false,\n        'alpha': 0.05,\n        'pValue': 0.21759090963694638,\n        'statistic': 2702.5,\n        // ...\n    }\n\n    // Print formatted output:\n    > var table = out.print()\n    Paired Wilcoxon signed rank test\n\n    Alternative hypothesis: Median of the difference `x - y` is not equal to 0\n\n        pValue: 0.2176\n        statistic: 2702.5\n\n    Test Decision: Fail to reject null in favor of alternative at 5% significance level\n\n\n    // Choose custom significance level:\n    > out = wilcoxon( arr, { 'alpha': 0.01 });\n    > table = out.print()\n    One-Sample Wilcoxon signed rank test\n\n    Alternative hypothesis: Median of `x` is not equal to 0\n\n        pValue: 0.0413\n        statistic: 96\n\n    Test Decision: Fail to reject null in favor of alternative at 1% significance level\n\n\n    // Test for a median equal to ten:\n    > out = wilcoxon( arr, { 'mu': 10 })\n    {\n        'rejected': false,\n        'alpha': 0.05,\n        'pValue': 0.11169650413134602,\n        'statistic': 88.5,\n        'nullValue': 10,\n        // ...\n    }\n\n    // Perform one-sided tests:\n    > out = wilcoxon( arr, { 'alternative': 'less' });\n    > table = out.print()\n    One-Sample Wilcoxon signed rank test\n\n    Alternative hypothesis: Median of `x` is less than 0\n\n        pValue: 0.9823\n        statistic: 96\n\n    Test Decision: Fail to reject null in favor of alternative at 5% significance level\n\n\n    > out = wilcoxon( arr, { 'alternative': 'greater' });\n    > table = out.print()\n    One-Sample Wilcoxon signed rank test\n\n    Alternative hypothesis: Median of `x` is greater than 0\n\n        pValue: 0.0206\n        statistic: 96\n\n    Test Decision: Reject null in favor of alternative at 5% significance level\n\n    See Also\n    --------\n    ttest, ztest\n","writableProperties":"\nwritableProperties( value )\n    Returns an array of an object's own writable property names and symbols.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    props: Array\n        List of an object's own writable properties.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var props = writableProperties( obj )\n    [ 'beep' ]\n\n    See Also\n    --------\n    inheritedWritableProperties, writablePropertiesIn, properties\n","writablePropertiesIn":"\nwritablePropertiesIn( value )\n    Returns an array of an object's own and inherited writable property names\n    and symbols.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    props: Array\n        List of an object's own and inherited writable property names and\n        symbols.\n\n    Examples\n    --------\n    > var props = writablePropertiesIn( [] )\n\n    See Also\n    --------\n    inheritedWritableProperties, writableProperties, propertiesIn\n","writablePropertyNames":"\nwritablePropertyNames( value )\n    Returns an array of an object's own writable property names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's own writable property names.\n\n    Examples\n    --------\n    > var obj = { 'a': 'b' };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = true;\n    > desc.writable = false;\n    > desc.value = 'boop';\n    > defineProperty( obj, 'beep', desc );\n    > var keys = writablePropertyNames( obj )\n    [ 'a' ]\n\n    See Also\n    --------\n    inheritedWritablePropertyNames, writableProperties, writablePropertyNamesIn, writablePropertySymbols, propertyNames\n","writablePropertyNamesIn":"\nwritablePropertyNamesIn( value )\n    Returns an array of an object's own and inherited writable property names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's own and inherited writable property names.\n\n    Examples\n    --------\n    > var obj = { 'a': 'b' };\n    > var desc = {};\n    > desc.configurable = true;\n    > desc.enumerable = true;\n    > desc.writable = false;\n    > desc.value = 'boop';\n    > defineProperty( obj, 'beep', desc );\n    > var keys = writablePropertyNamesIn( obj )\n    e.g., [ 'a', ... ]\n\n    See Also\n    --------\n    inheritedWritablePropertyNames, writablePropertiesIn, writablePropertyNames, writablePropertySymbolsIn, propertyNamesIn\n","writablePropertySymbols":"\nwritablePropertySymbols( value )\n    Returns an array of an object's own writable symbol properties.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's own writable symbol properties.\n\n    Examples\n    --------\n    > var obj = {};\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.writable = true;\n    > desc.value = 'boop';\n    > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n    > defineProperty( obj, sym, desc );\n    > var symbols = writablePropertySymbols( obj )\n\n    See Also\n    --------\n    inheritedWritablePropertySymbols, writableProperties, writablePropertyNames, writablePropertySymbolsIn, propertySymbols\n","writablePropertySymbolsIn":"\nwritablePropertySymbolsIn( value )\n    Returns an array of an object's own and inherited writable symbol\n    properties.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's own and inherited writable symbol properties.\n\n    Examples\n    --------\n    > var obj = {};\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.writable = true;\n    > desc.value = 'boop';\n    > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n    > defineProperty( obj, sym, desc );\n    > var symbols = writablePropertySymbolsIn( obj )\n\n    See Also\n    --------\n    inheritedWritablePropertySymbols, writablePropertiesIn, writablePropertyNamesIn, writablePropertySymbols, propertySymbolsIn\n","writeFile":"\nwriteFile( file, data[, options], clbk )\n    Asynchronously writes data to a file.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    data: string|Buffer\n        Data to write.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. The encoding option is ignored if the data argument is a\n        buffer. Default: 'utf8'.\n\n    options.flag: string (optional)\n        Flag. Default: 'w'.\n\n    options.mode: integer (optional)\n        Mode. Default: 0o666.\n\n    clbk: Function\n        Callback to invoke upon writing data to a file.\n\n    Examples\n    --------\n    > function onWrite( error ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     }\n    ... };\n    > writeFile( './beep/boop.txt', 'beep boop', onWrite );\n\n\nwriteFile.sync( file, data[, options] )\n    Synchronously writes data to a file.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    data: string|Buffer\n        Data to write.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. The encoding option is ignored if the data argument is a\n        buffer. Default: 'utf8'.\n\n    options.flag: string (optional)\n        Flag. Default: 'w'.\n\n    options.mode: integer (optional)\n        Mode. Default: 0o666.\n\n    Returns\n    -------\n    err: Error|null\n        Error object or null.\n\n    Examples\n    --------\n    > var err = writeFile.sync( './beep/boop.txt', 'beep boop' );\n\n    See Also\n    --------\n    exists, readFile\n","writeFile.sync":"\nwriteFile.sync( file, data[, options] )\n    Synchronously writes data to a file.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    data: string|Buffer\n        Data to write.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. The encoding option is ignored if the data argument is a\n        buffer. Default: 'utf8'.\n\n    options.flag: string (optional)\n        Flag. Default: 'w'.\n\n    options.mode: integer (optional)\n        Mode. Default: 0o666.\n\n    Returns\n    -------\n    err: Error|null\n        Error object or null.\n\n    Examples\n    --------\n    > var err = writeFile.sync( './beep/boop.txt', 'beep boop' );\n\n    See Also\n    --------\n    exists, readFile","zip":"\nzip( ...arr[, options] )\n    Generates array tuples from input arrays.\n\n    Parameters\n    ----------\n    arr: ...Array\n        Input arrays to be zipped.\n\n    options: Object (optional)\n        Options.\n\n    options.trunc: boolean (optional)\n        Boolean indicating whether to truncate arrays longer than the shortest\n        input array. Default: `true`.\n\n    options.fill: any (optional)\n        Fill value used for arrays of unequal length. Default: `null`.\n\n    options.arrays: boolean (optional)\n        Boolean indicating whether an input array should be interpreted as an\n        array of arrays to be zipped. Default: `false`.\n\n    Returns\n    -------\n    out: Array\n        Array of arrays.\n\n    Examples\n    --------\n    // Basic usage:\n    > var out = zip( [ 1, 2 ], [ 'a', 'b' ] )\n    [ [ 1, 'a' ], [ 2, 'b' ] ]\n\n    // Turn off truncation:\n    > var opts = { 'trunc': false };\n    > out = zip( [ 1, 2, 3 ], [ 'a', 'b' ], opts )\n    [ [ 1, 'a' ], [ 2, 'b' ], [ 3, null ] ]\n\n    See Also\n    --------\n    unzip\n","ztest":"\nztest( x, sigma[, options] )\n    Computes a one-sample z-test.\n\n    The function performs a one-sample z-test for the null hypothesis that the\n    data in array or typed array `x` is drawn from a normal distribution with\n    mean zero and standard deviation `sigma`.\n\n    The returned object comes with a `.print()` method which when invoked will\n    print a formatted output of the results of the hypothesis test.\n\n    Parameters\n    ----------\n    x: Array<number>\n        Data array.\n\n    sigma: number\n        Known standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.alternative: string (optional)\n        Indicates whether the alternative hypothesis is that the mean of `x` is\n        larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n        `mu` (`two-sided`). Default: `'two-sided'`.\n\n    options.mu: number (optional)\n        Hypothesized true mean under the null hypothesis. Set this option to\n        test whether the data comes from a distribution with the specified `mu`.\n        Default: `0`.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Used significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.ci: Array<number>\n        1-alpha confidence interval for mean.\n\n    out.nullValue: number\n        Assumed mean value under H0.\n\n    out.sd: number\n        Standard error.\n\n    out.alternative: string\n        Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n    out.method: string\n        Name of test (`One-Sample z-test`).\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    // One-sample z-test:\n    > var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 212 } );\n    > var x = new Array( 100 );\n    > for ( var i = 0; i < x.length; i++ ) {\n    ...     x[ i ] = rnorm();\n    ... }\n    > var out = ztest( x, 2.0 )\n    {\n        alpha: 0.05,\n        rejected: false,\n        pValue: ~0.180,\n        statistic: ~-1.34,\n        ci: [ ~-0.66, ~0.124 ],\n        ...\n    }\n\n    // Choose custom significance level and print output:\n    > arr = [ 2, 4, 3, 1, 0 ];\n    > out = ztest( arr, 2.0, { 'alpha': 0.01 } );\n    > table = out.print()\n    One-sample z-test\n\n    Alternative hypothesis: True mean is not equal to 0\n\n        pValue: 0.0253\n        statistic: 2.2361\n        99% confidence interval: [-0.3039,4.3039]\n\n    Test Decision: Fail to reject null in favor of alternative at 1%\n    significance level\n\n\n    // Test for a mean equal to five:\n    > var arr = [ 4, 4, 6, 6, 5 ];\n    > out = ztest( arr, 1.0, { 'mu': 5 } )\n    {\n        rejected: false,\n        pValue: 1,\n        statistic: 0,\n        ci: [ ~4.123, ~5.877 ],\n        // ...\n    }\n\n    // Perform one-sided tests:\n    > arr = [ 4, 4, 6, 6, 5 ];\n    > out = ztest( arr, 1.0, { 'alternative': 'less' } )\n    {\n        alpha: 0.05,\n        rejected: false,\n        pValue: 1,\n        statistic: 11.180339887498949,\n        ci: [ -Infinity, 5.735600904580115 ],\n        // ...\n    }\n    > out = ztest( arr, 1.0, { 'alternative': 'greater' } )\n    {\n        alpha: 0.05,\n        rejected: true,\n        pValue: 0,\n        statistic: 11.180339887498949,\n        ci: [ 4.264399095419885, Infinity ],\n        //...\n    }\n\n    See Also\n    --------\n    ztest2\n","ztest2":"\nztest2( x, y, sigmax, sigmay[, options] )\n    Computes a two-sample z-test.\n\n    By default, the function performs a two-sample z-test for the null\n    hypothesis that the data in arrays or typed arrays `x` and `y` is\n    independently drawn from normal distributions with equal means and known\n    standard deviations `sigmax` and `sigmay`.\n\n    The returned object comes with a `.print()` method which when invoked will\n    print a formatted output of the results of the hypothesis test.\n\n    Parameters\n    ----------\n    x: Array<number>\n        First data array.\n\n    y: Array<number>\n        Second data array.\n\n    sigmax: number\n        Known standard deviation of first group.\n\n    sigmay: number\n        Known standard deviation of second group.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.alternative: string (optional)\n        Either `two-sided`, `less` or `greater`. Indicates whether the\n        alternative hypothesis is that `x` has a larger mean than `y`\n        (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n        the same (`two-sided`). Default: `'two-sided'`.\n\n    options.difference: number (optional)\n        Number denoting the difference in means under the null hypothesis.\n        Default: `0`.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Used significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.ci: Array<number>\n        1-alpha confidence interval for the mean.\n\n    out.nullValue: number\n        Assumed difference in means under H0.\n\n    out.xmean: number\n        Sample mean of `x`.\n\n    out.ymean: number\n        Sample mean of `y`.\n\n    out.alternative: string\n        Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n    out.method: string\n        Name of test.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    // Drawn from Normal(0,2):\n    > var x = [ -0.21, 0.14, 1.65, 2.11, -1.86, -0.29, 1.48, 0.81, 0.86, 1.04 ];\n\n    // Drawn from Normal(1,2):\n    > var y = [ -1.53, -2.93, 2.34, -1.15, 2.7, -0.12, 4.22, 1.66, 3.43, 4.66 ];\n    > var out = ztest2( x, y, 2.0, 2.0 )\n    {\n        alpha: 0.05,\n        rejected: false,\n        pValue: ~0.398,\n        statistic: ~-0.844\n        ci: [ ~-2.508, ~0.988 ],\n        alternative: 'two-sided',\n        method: 'Two-sample z-test',\n        nullValue: 0,\n        xmean: ~0.573,\n        ymean: ~1.328\n    }\n\n    // Print table output:\n    > var table = out.print()\n    Two-sample z-test\n\n    Alternative hypothesis: True difference in means is not equal to 0\n\n        pValue: 0.3986\n        statistic: -0.8441\n        95% confidence interval: [-2.508,0.998]\n\n    Test Decision: Fail to reject null in favor of alternative at 5%\n    significance level\n\n    // Choose a different significance level than `0.05`:\n    > out = ztest2( x, y, 2.0, 2.0, { 'alpha': 0.4 } );\n    > table = out.print()\n    Two-sample z-test\n\n    Alternative hypothesis: True difference in means is not equal to 0\n\n        pValue: 0.3986\n        statistic: -0.8441\n        60% confidence interval: [-1.5078,-0.0022]\n\n    Test Decision: Reject null in favor of alternative at 40% significance level\n\n    // Perform one-sided tests:\n    > out = ztest2( x, y, 2.0, 2.0, { 'alternative': 'less' } );\n    > table = out.print()\n    Two-sample z-test\n\n    Alternative hypothesis: True difference in means is less than 0\n\n        pValue: 0.1993\n        statistic: -0.8441\n        95% confidence interval: [-Infinity,0.7162]\n\n    Test Decision: Fail to reject null in favor of alternative at 5%\n    significance level\n\n\n    > out = ztest2( x, y, 2.0, 2.0, { 'alternative': 'greater' } );\n    > table = out.print()\n    Two-sample z-test\n\n    Alternative hypothesis: True difference in means is greater than 0\n\n        pValue: 0.8007\n        statistic: -0.8441\n        95% confidence interval: [-2.2262,Infinity]\n\n    Test Decision: Fail to reject null in favor of alternative at 5%\n    significance level\n\n    // Test for a difference in means besides zero:\n    > var rnorm = base.random.normal.factory({ 'seed': 372 } );\n    > x = new Array( 100 );\n    > for ( i = 0; i < x.length; i++ ) {\n    ...     x[ i ] = rnorm( 2.0, 1.0 );\n    ... }\n    > y = new Array( 100 );\n    ... for ( i = 0; i < x.length; i++ ) {\n    ...     y[ i ] = rnorm( 0.0, 2.0 );\n    ... }\n    > out = ztest2( x, y, 1.0, 2.0, { 'difference': 2.0 } )\n    {\n        rejected: false,\n        pValue: ~0.35,\n        statistic: ~-0.935\n        ci: [ ~1.353, ~2.229 ],\n        // ...\n    }\n\n    See Also\n    --------\n    ztest\n"}
diff --git a/lib/node_modules/@stdlib/repl/info/data/data.csv b/lib/node_modules/@stdlib/repl/info/data/data.csv
index cb8d6c47900b..66d3e355ff10 100644
--- a/lib/node_modules/@stdlib/repl/info/data/data.csv
+++ b/lib/node_modules/@stdlib/repl/info/data/data.csv
@@ -1734,10 +1734,10 @@ base.strided.dmax,"\nbase.strided.dmax( N:integer, x:Float64Array, strideX:integ
 base.strided.dmax.ndarray,"\nbase.strided.dmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum value of a double-precision floating-point strided\n    array using alternative indexing semantics.\n"
 base.strided.dmaxabs,"\nbase.strided.dmaxabs( N:integer, x:Float64Array, strideX:integer )\n    Computes the maximum absolute value of a double-precision floating-point\n    strided array.\n"
 base.strided.dmaxabs.ndarray,"\nbase.strided.dmaxabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum absolute value of a double-precision floating-point\n    strided array using alternative indexing semantics.\n"
-base.strided.dmaxabssorted,"\nbase.strided.dmaxabssorted( N:integer, x:Float64Array, stride:integer )\n    Computes the maximum absolute value of a sorted double-precision floating-\n    point strided array.\n"
-base.strided.dmaxabssorted.ndarray,"\nbase.strided.dmaxabssorted.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the maximum absolute value of a sorted double-precision floating-\n    point strided array using alternative indexing semantics.\n"
-base.strided.dmaxsorted,"\nbase.strided.dmaxsorted( N:integer, x:Float64Array, stride:integer )\n    Computes the maximum value of a sorted double-precision floating-point\n    strided array.\n"
-base.strided.dmaxsorted.ndarray,"\nbase.strided.dmaxsorted.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the maximum value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n"
+base.strided.dmaxabssorted,"\nbase.strided.dmaxabssorted( N:integer, x:Float64Array, strideX:integer )\n    Computes the maximum absolute value of a sorted double-precision floating-\n    point strided array.\n"
+base.strided.dmaxabssorted.ndarray,"\nbase.strided.dmaxabssorted.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum absolute value of a sorted double-precision floating-\n    point strided array using alternative indexing semantics.\n"
+base.strided.dmaxsorted,"\nbase.strided.dmaxsorted( N:integer, x:Float64Array, strideX:integer )\n    Computes the maximum value of a sorted double-precision floating-point\n    strided array.\n"
+base.strided.dmaxsorted.ndarray,"\nbase.strided.dmaxsorted.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n"
 base.strided.dmean,"\nbase.strided.dmean( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array.\n"
 base.strided.dmean.ndarray,"\nbase.strided.dmean.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using alternative indexing semantics.\n"
 base.strided.dmeankbn,"\nbase.strided.dmeankbn( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm.\n"
@@ -1764,16 +1764,16 @@ base.strided.dmeanvarpn,"\nbase.strided.dmeanvarpn( N:integer, c:number, x:Float
 base.strided.dmeanvarpn.ndarray,"\nbase.strided.dmeanvarpn.ndarray( N:integer, c:number, x:Float64Array, \n  strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n  offsetOut:integer )\n    Computes the mean and variance of a double-precision floating-point strided\n    array using a two-pass algorithm and alternative indexing semantics.\n"
 base.strided.dmeanwd,"\nbase.strided.dmeanwd( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using Welford's algorithm.\n"
 base.strided.dmeanwd.ndarray,"\nbase.strided.dmeanwd.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n"
-base.strided.dmediansorted,"\nbase.strided.dmediansorted( N:integer, x:Float64Array, stride:integer )\n    Computes the median value of a sorted double-precision floating-point\n    strided array.\n"
-base.strided.dmediansorted.ndarray,"\nbase.strided.dmediansorted.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the median value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n"
+base.strided.dmediansorted,"\nbase.strided.dmediansorted( N:integer, x:Float64Array, strideX:integer )\n    Computes the median value of a sorted double-precision floating-point\n    strided array.\n"
+base.strided.dmediansorted.ndarray,"\nbase.strided.dmediansorted.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the median value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n"
 base.strided.dmidrange,"\nbase.strided.dmidrange( N:integer, x:Float64Array, strideX:integer )\n    Computes the mid-range of a double-precision floating-point strided array.\n"
 base.strided.dmidrange.ndarray,"\nbase.strided.dmidrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the mid-range of a double-precision floating-point strided array\n    using alternative indexing semantics.\n"
 base.strided.dmin,"\nbase.strided.dmin( N:integer, x:Float64Array, strideX:integer )\n    Computes the minimum value of a double-precision floating-point strided\n    array.\n"
 base.strided.dmin.ndarray,"\nbase.strided.dmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the minimum value of a double-precision floating-point strided\n    array using alternative indexing semantics.\n"
 base.strided.dminabs,"\nbase.strided.dminabs( N:integer, x:Float64Array, strideX:integer )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array.\n"
 base.strided.dminabs.ndarray,"\nbase.strided.dminabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array using alternative indexing semantics.\n"
-base.strided.dminsorted,"\nbase.strided.dminsorted( N:integer, x:Float64Array, stride:integer )\n    Computes the minimum value of a sorted double-precision floating-point\n    strided array.\n"
-base.strided.dminsorted.ndarray,"\nbase.strided.dminsorted.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the minimum value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n"
+base.strided.dminsorted,"\nbase.strided.dminsorted( N:integer, x:Float64Array, strideX:integer )\n    Computes the minimum value of a sorted double-precision floating-point\n    strided array.\n"
+base.strided.dminsorted.ndarray,"\nbase.strided.dminsorted.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the minimum value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n"
 base.strided.dmskabs,"\nbase.strided.dmskabs( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Computes the absolute value for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`.\n"
 base.strided.dmskabs.ndarray,"\nbase.strided.dmskabs.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n  sy:integer, oy:integer )\n    Computes the absolute value for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n"
 base.strided.dmskabs2,"\nbase.strided.dmskabs2( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Computes the squared absolute value for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point\n    strided array `y`.\n"
@@ -1968,12 +1968,12 @@ base.strided.dstdevwd,"\nbase.strided.dstdevwd( N:integer, correction:number, x:
 base.strided.dstdevwd.ndarray,"\nbase.strided.dstdevwd.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n"
 base.strided.dstdevyc,"\nbase.strided.dstdevyc( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer.\n"
 base.strided.dstdevyc.ndarray,"\nbase.strided.dstdevyc.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer and\n    alternative indexing semantics.\n"
-base.strided.dsum,"\nbase.strided.dsum( N:integer, x:Float64Array, stride:integer )\n    Computes the sum of double-precision floating-point strided array elements.\n"
-base.strided.dsum.ndarray,"\nbase.strided.dsum.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using alternative indexing semantics.\n"
+base.strided.dsum,"\nbase.strided.dsum( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of double-precision floating-point strided array elements.\n"
+base.strided.dsum.ndarray,"\nbase.strided.dsum.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using alternative indexing semantics.\n"
 base.strided.dsumkbn,"\nbase.strided.dsumkbn( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm.\n"
 base.strided.dsumkbn.ndarray,"\nbase.strided.dsumkbn.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n"
-base.strided.dsumkbn2,"\nbase.strided.dsumkbn2( N:integer, x:Float64Array, stride:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm.\n"
-base.strided.dsumkbn2.ndarray,"\nbase.strided.dsumkbn2.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n"
+base.strided.dsumkbn2,"\nbase.strided.dsumkbn2( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm.\n"
+base.strided.dsumkbn2.ndarray,"\nbase.strided.dsumkbn2.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n"
 base.strided.dsumors,"\nbase.strided.dsumors( N:integer, x:Float64Array, stride:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using ordinary recursive summation.\n"
 base.strided.dsumors.ndarray,"\nbase.strided.dsumors.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using ordinary recursive summation and alternative indexing semantics.\n"
 base.strided.dsumpw,"\nbase.strided.dsumpw( N:integer, x:Float64Array, stride:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using pairwise summation.\n"
@@ -2012,8 +2012,8 @@ base.strided.gapx,"\nbase.strided.gapx( N:integer, alpha:number, x:Array|TypedAr
 base.strided.gapx.ndarray,"\nbase.strided.gapx.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Adds a constant to each element in a strided array using alternative\n    indexing semantics.\n"
 base.strided.gapxsum,"\nbase.strided.gapxsum( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer )\n    Adds a constant to each strided array element and computes the sum.\n"
 base.strided.gapxsum.ndarray,"\nbase.strided.gapxsum.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Adds a constant to each strided array element and computes the sum using\n    alternative indexing semantics.\n"
-base.strided.gapxsumkbn,"\nbase.strided.gapxsumkbn( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer )\n    Adds a constant to each strided array element and computes the sum using an\n    improved Kahan–Babuška algorithm.\n"
-base.strided.gapxsumkbn.ndarray,"\nbase.strided.gapxsumkbn.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Adds a constant to each strided array element and computes the sum using an\n    improved Kahan–Babuška algorithm and alternative indexing semantics.\n"
+base.strided.gapxsumkbn,"\nbase.strided.gapxsumkbn( N:integer, alpha:number, x:Array|TypedArray, \n  strideX:integer )\n    Adds a scalar constant to each strided array element and computes the sum\n    using an improved Kahan–Babuška algorithm.\n"
+base.strided.gapxsumkbn.ndarray,"\nbase.strided.gapxsumkbn.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n  strideX:integer, offsetX:integer )\n    Adds a scalar constant to each strided array element and computes the sum\n    using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n"
 base.strided.gapxsumkbn2,"\nbase.strided.gapxsumkbn2( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer )\n    Adds a constant to each strided array element and computes the sum using a\n    second-order iterative Kahan–Babuška algorithm.\n"
 base.strided.gapxsumkbn2.ndarray,"\nbase.strided.gapxsumkbn2.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Adds a constant to each strided array element and computes the sum using a\n    second-order iterative Kahan–Babuška algorithm and alternative indexing\n    semantics.\n"
 base.strided.gapxsumors,"\nbase.strided.gapxsumors( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer )\n    Adds a constant to each strided array element and computes the sum using\n    ordinary recursive summation.\n"
@@ -2289,10 +2289,10 @@ base.strided.smax,"\nbase.strided.smax( N:integer, x:Float32Array, strideX:integ
 base.strided.smax.ndarray,"\nbase.strided.smax.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum value of a single-precision floating-point strided\n    array using alternative indexing semantics.\n"
 base.strided.smaxabs,"\nbase.strided.smaxabs( N:integer, x:Float32Array, strideX:integer )\n    Computes the maximum absolute value of a single-precision floating-point\n    strided array.\n"
 base.strided.smaxabs.ndarray,"\nbase.strided.smaxabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum absolute value of a single-precision floating-point\n    strided array using alternative indexing semantics.\n"
-base.strided.smaxabssorted,"\nbase.strided.smaxabssorted( N:integer, x:Float32Array, stride:integer )\n    Computes the maximum absolute value of a sorted single-precision floating-\n    point strided array.\n"
-base.strided.smaxabssorted.ndarray,"\nbase.strided.smaxabssorted.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the maximum absolute value of a sorted single-precision floating-\n    point strided array using alternative indexing semantics.\n"
-base.strided.smaxsorted,"\nbase.strided.smaxsorted( N:integer, x:Float32Array, stride:integer )\n    Computes the maximum value of a sorted single-precision floating-point\n    strided array.\n"
-base.strided.smaxsorted.ndarray,"\nbase.strided.smaxsorted.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the maximum value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n"
+base.strided.smaxabssorted,"\nbase.strided.smaxabssorted( N:integer, x:Float32Array, strideX:integer )\n    Computes the maximum absolute value of a sorted single-precision floating-\n    point strided array.\n"
+base.strided.smaxabssorted.ndarray,"\nbase.strided.smaxabssorted.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum absolute value of a sorted single-precision floating-\n    point strided array using alternative indexing semantics.\n"
+base.strided.smaxsorted,"\nbase.strided.smaxsorted( N:integer, x:Float32Array, strideX:integer )\n    Computes the maximum value of a sorted single-precision floating-point\n    strided array.\n"
+base.strided.smaxsorted.ndarray,"\nbase.strided.smaxsorted.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n"
 base.strided.smean,"\nbase.strided.smean( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array.\n"
 base.strided.smean.ndarray,"\nbase.strided.smean.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using alternative indexing semantics.\n"
 base.strided.smeankbn,"\nbase.strided.smeankbn( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm.\n"
diff --git a/lib/node_modules/@stdlib/repl/info/data/data.json b/lib/node_modules/@stdlib/repl/info/data/data.json
index f1fc5246902d..5586f874860c 100644
--- a/lib/node_modules/@stdlib/repl/info/data/data.json
+++ b/lib/node_modules/@stdlib/repl/info/data/data.json
@@ -1 +1 @@
-{"abs":"\nabs( x:ndarray|ArrayLikeObject|number[, options:Object] )\n    Computes the absolute value.\n","abs.assign":"\nabs.assign( x:ndarray|ArrayLikeObject, y:ndarray|ArrayLikeObject )\n    Computes the absolute value and assigns results to a provided output array.\n","acartesianPower":"\nacartesianPower( x:ArrayLikeObject, n:integer )\n    Returns the Cartesian power.\n","acartesianProduct":"\nacartesianProduct( x1:ArrayLikeObject, x2:ArrayLikeObject )\n    Returns the Cartesian product.\n","acartesianSquare":"\nacartesianSquare( x:ArrayLikeObject )\n    Returns the Cartesian square.\n","acronym":"\nacronym( str:string[, options:Object] )\n    Generates an acronym for a given string.\n","aempty":"\naempty( length:integer[, dtype:string] )\n    Creates an uninitialized array having a specified length.\n","aemptyLike":"\naemptyLike( x:TypedArray|Array[, dtype:string] )\n    Creates an uninitialized array having the same length and data type as a\n    provided input array.\n","AFINN_96":"\nAFINN_96()\n    Returns a list of English words rated for valence.\n","AFINN_111":"\nAFINN_111()\n    Returns a list of English words rated for valence.\n","afull":"\nafull( length:integer, value:any[, dtype:string] )\n    Returns a filled array having a specified length.\n","afullLike":"\nafullLike( x:TypedArray|Array[, dtype:string] )\n    Returns a filled array having the same length and data type as a provided\n    input array.\n","alias2pkg":"\nalias2pkg( alias:string )\n    Returns the package name associated with a provided alias.\n","alias2related":"\nalias2related( alias:string )\n    Returns aliases related to a specified alias.\n","alias2standalone":"\nalias2standalone( alias:string )\n    Returns the standalone package name associated with a provided alias.\n","aliases":"\naliases( [namespace:string] )\n    Returns a list of standard library aliases.\n","allocUnsafe":"\nallocUnsafe( size:integer )\n    Allocates a buffer having a specified number of bytes.\n","amskfilter":"\namskfilter( x:Array|TypedArray|Object, mask:Array|TypedArray|Object )\n    Returns a new array by applying a mask to a provided input array.\n","amskput":"\namskput( x:ArrayLikeObject, mask:ArrayLikeObject, values:ArrayLikeObject[, \n  options:Object] )\n    Replaces elements of an array with provided values according to a provided\n    mask array.\n","amskreject":"\namskreject( x:Array|TypedArray|Object, mask:Array|TypedArray|Object )\n    Returns a new array by applying a mask to a provided input array.\n","anans":"\nanans( length:integer[, dtype:string] )\n    Returns an array filled with NaNs and having a specified length.\n","anansLike":"\nanansLike( x:TypedArray|Array[, dtype:string] )\n    Returns an array filled with NaNs and having the same length and data type\n    as a provided input array.\n","anova1":"\nanova1( x:Array<number>, factor:Array[, options:Object] )\n    Performs a one-way analysis of variance.\n","ANSCOMBES_QUARTET":"\nANSCOMBES_QUARTET()\n    Returns Anscombe's quartet.\n","any":"\nany( collection:Array|TypedArray|Object )\n    Tests whether at least one element in a collection is truthy.\n","anyBy":"\nanyBy( collection:Array|TypedArray|Object, predicate:Function[, thisArg:any ] )\n    Tests whether at least one element in a collection passes a test implemented\n    by a predicate function.\n","anyByAsync":"\nanyByAsync( collection:Array|TypedArray|Object, [options:Object,] \n  predicate:Function, done:Function )\n    Tests whether at least one element in a collection passes a test implemented\n    by a predicate function.\n","anyByAsync.factory":"\nanyByAsync.factory( [options:Object,] predicate:Function )\n    Returns a function which tests whether at least one element in a collection\n    passes a test implemented by a predicate function.\n","anyByRight":"\nanyByRight( collection:Array|TypedArray|Object, predicate:Function[, \n  thisArg:any ] )\n    Tests whether at least one element in a collection passes a test implemented\n    by a predicate function, iterating from right to left.\n","anyByRightAsync":"\nanyByRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n  predicate:Function, done:Function )\n    Tests whether at least one element in a collection passes a test implemented\n    by a predicate function, iterating from right to left.\n","anyByRightAsync.factory":"\nanyByRightAsync.factory( [options:Object,] predicate:Function )\n    Returns a function which tests whether at least one element in a collection\n    passes a test implemented by a predicate function, iterating from right to\n    left.\n","anyInBy":"\nanyInBy( object:Object, predicate:Function[, thisArg:any ] )\n    Tests whether at least one value in an object passes a test implemented by\n    a predicate function.\n","anyOwnBy":"\nanyOwnBy( object:Object, predicate:Function[, thisArg:any ] )\n    Tests whether at least one own property of an object passes a\n    test implemented by a predicate function.\n","aones":"\naones( length:integer[, dtype:string] )\n    Returns an array filled with ones and having a specified length.\n","aonesLike":"\naonesLike( x:TypedArray|Array[, dtype:string] )\n    Returns an array filled with ones and having the same length and data type\n    as a provided input array.\n","aoneTo":"\naoneTo( n:integer[, dtype:string] )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from one.\n","aoneToLike":"\naoneToLike( x:TypedArray|Array[, dtype:string] )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from one and having the same length and data type as a provided\n    input array.\n","APERY":"\nAPERY\n    Apéry's constant.\n","aplace":"\naplace( x:ArrayLikeObject, mask:ArrayLikeObject, values:ArrayLikeObject[, \n  options:Object] )\n    Replaces elements of an array with provided values according to a provided\n    mask array.\n","append":"\nappend( collection1:Array|TypedArray|Object, \n  collection2:Array|TypedArray|Object )\n    Adds the elements of one collection to the end of another collection.\n","aput":"\naput( x:ArrayLikeObject, indices:ArrayLikeObject<integer>, \n  values:ArrayLikeObject[, options:Object] )\n    Replaces specified elements of an array with provided values.\n","ARCH":"\nARCH\n    Operating system CPU architecture for which the JavaScript runtime binary\n    was compiled.\n","argumentFunction":"\nargumentFunction( idx:integer )\n    Returns a function which always returns a specified argument.\n","ARGV":"\nARGV\n    An array containing command-line arguments passed when launching the calling\n    process.\n","array":"\narray( [buffer:Array|TypedArray|Buffer|ndarray,] [options:Object] )\n    Returns a multidimensional array.\n","array2buffer":"\narray2buffer( arr:Array<integer> )\n    Allocates a buffer using an octet array.\n","array2fancy":"\narray2fancy( x:Array|TypedArray|Object[, options:Object] )\n    Converts an array to an object supporting fancy indexing.\n","array2fancy.factory":"\narray2fancy.factory( [options:Object] )\n    Returns a function for converting an array to an object supporting fancy\n    indexing.\n","array2fancy.idx":"\narray2fancy.idx( x:Array|TypedArray|Object[, options:Object] )\n    Wraps a provided array as an array index object.\n","array2iterator":"\narray2iterator( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )\n    Returns an iterator which iterates over the elements of an array-like\n    object.\n","array2iteratorRight":"\narray2iteratorRight( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )\n    Returns an iterator which iterates from right to left over the elements of\n    an array-like object.\n","ArrayBuffer":"\nArrayBuffer( size:integer )\n    Returns an array buffer having a specified number of bytes.\n","ArrayBuffer.length":"\nArrayBuffer.length\n    Number of input arguments the constructor accepts.\n","ArrayBuffer.isView":"\nArrayBuffer.isView( arr:any )\n    Returns a boolean indicating if provided an array buffer view.\n","ArrayBuffer.prototype.byteLength":"\nArrayBuffer.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the array buffer.\n","ArrayBuffer.prototype.slice":"\nArrayBuffer.prototype.slice( [start:integer[, end:integer]] )\n    Copies the bytes of an array buffer to a new array buffer.\n","arraybuffer2buffer":"\narraybuffer2buffer( buf:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Allocates a buffer from an ArrayBuffer.\n","arrayCtors":"\narrayCtors( dtype:string )\n    Returns an array constructor.\n","arrayDataType":"\narrayDataType( array:any )\n    Returns the data type of an array.\n","arrayDataTypes":"\narrayDataTypes( [kind:string] )\n    Returns a list of array data types.\n","ArrayIndex":"\nArrayIndex( x:Array|TypedArray|Object[, options:Object] )\n    Wraps a provided array as an array index object.\n","ArrayIndex.free":"\nArrayIndex.free( id:string )\n    Frees the instance associated with a provided identifier.\n","ArrayIndex.get":"\nArrayIndex.get( id:string )\n    Returns the array associated with the instance having a provided identifier.\n","ArrayIndex.prototype.data":"\nArrayIndex.prototype.data\n    Read-only property returning the underlying index array.\n","ArrayIndex.prototype.dtype":"\nArrayIndex.prototype.dtype\n    Read-only property returning the underlying data type of the index array.\n","ArrayIndex.prototype.id":"\nArrayIndex.prototype.id\n    Read-only property returning the unique identifier associated with an\n    instance.\n","ArrayIndex.prototype.isCached":"\nArrayIndex.prototype.isCached\n    Read-only property returning a boolean indicating whether an array index is\n    actively cached.\n","ArrayIndex.prototype.type":"\nArrayIndex.prototype.type\n    Read-only property returning the array index type.\n","ArrayIndex.prototype.toString":"\nArrayIndex.prototype.toString()\n    Serializes an instance as a string.\n","ArrayIndex.prototype.toJSON":"\nArrayIndex.prototype.toJSON()\n    Serializes an instance as a JSON object.\n","arrayMinDataType":"\narrayMinDataType( value:any )\n    Returns the minimum array data type of the closest \"kind\" necessary for\n    storing a provided scalar value.\n","arrayMostlySafeCasts":"\narrayMostlySafeCasts( [dtype:any] )\n    Returns a list of array data types to which a provided array data type can\n    be safely cast and, for floating-point data types, can be downcast.\n","arrayNextDataType":"\narrayNextDataType( [dtype:string] )\n    Returns the next larger array data type of the same kind.\n","arrayPromotionRules":"\narrayPromotionRules( [dtype1:any, dtype2:any] )\n    Returns the array data type with the smallest size and closest \"kind\" to\n    which array data types can be safely cast.\n","arraySafeCasts":"\narraySafeCasts( [dtype:any] )\n    Returns a list of array data types to which a provided array data type can\n    be safely cast.\n","arraySameKindCasts":"\narraySameKindCasts( [dtype:any] )\n    Returns a list of array data types to which a provided array data type can\n    be safely cast or cast within the same \"kind\".\n","arrayShape":"\narrayShape( arr:ArrayLikeObject )\n    Determines array dimensions.\n","arrayStream":"\narrayStream( src:ArrayLikeObject[, options:Object] )\n    Creates a readable stream from an array-like object.\n","arrayStream.factory":"\narrayStream.factory( [options:Object] )\n    Returns a function for creating readable streams from array-like objects.\n","arrayStream.objectMode":"\narrayStream.objectMode( src:ArrayLikeObject[, options:Object] )\n    Returns an \"objectMode\" readable stream from an array-like object.\n","arrayview2iterator":"\narrayview2iterator( src:ArrayLikeObject[, begin:integer[, end:integer]][, \n  mapFcn:Function[, thisArg:any]] )\n    Returns an iterator which iterates over the elements of an array-like object\n    view.\n","arrayview2iteratorRight":"\narrayview2iteratorRight( src:ArrayLikeObject[, begin:integer[, end:integer]][, \n  mapFcn:Function[, thisArg:any]] )\n    Returns an iterator which iterates from right to left over the elements of\n    an array-like object view.\n","aslice":"\naslice( x:ArrayLikeObject[, start:integer[, end:integer]] )\n    Returns a shallow copy of a portion of an array.\n","AsyncIteratorSymbol":"\nAsyncIteratorSymbol\n    Async iterator symbol.\n","atake":"\natake( x:Array|TypedArray|Object, indices:ArrayLikeObject<integer>[, \n  options:Object] )\n    Takes elements from an array.\n","azeros":"\nazeros( length:integer[, dtype:string] )\n    Returns a zero-filled array having a specified length.\n","azerosLike":"\nazerosLike( x:TypedArray|Array[, dtype:string] )\n    Returns a zero-filled array having the same length and data type as a\n    provided input array.\n","azeroTo":"\nazeroTo( n:integer[, dtype:string] )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from zero.\n","azeroToLike":"\nazeroToLike( x:TypedArray|Array[, dtype:string] )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from zero and having the same length and data type as a provided\n    input array.\n","bartlettTest":"\nbartlettTest( ...x:Array[, options:Object] )\n    Computes Bartlett’s test for equal variances.\n","base.abs":"\nbase.abs( x:number )\n    Computes the absolute value of a double-precision floating-point number `x`.\n","base.abs2":"\nbase.abs2( x:number )\n    Computes the squared absolute value of a double-precision floating-point\n    `x`.\n","base.abs2f":"\nbase.abs2f( x:number )\n    Computes the squared absolute value of a single-precision floating-point\n    `x`.\n","base.absdiff":"\nbase.absdiff( x:number, y:number )\n    Computes the absolute difference.\n","base.absf":"\nbase.absf( x:number )\n    Computes the absolute value of a single-precision floating-point number `x`.\n","base.acartesianPower":"\nbase.acartesianPower( x:ArrayLikeObject, n:integer )\n    Returns the Cartesian power.\n","base.acartesianProduct":"\nbase.acartesianProduct( x1:ArrayLikeObject, x2:ArrayLikeObject )\n    Returns the Cartesian product.\n","base.acartesianSquare":"\nbase.acartesianSquare( x:ArrayLikeObject )\n    Returns the Cartesian square.\n","base.acos":"\nbase.acos( x:number )\n    Compute the arccosine of a double-precision floating-point number.\n","base.acosd":"\nbase.acosd( x:number )\n    Computes the arccosine (in degrees) of a double-precision floating-point \n    number.\n","base.acosf":"\nbase.acosf( x:number )\n    Computes the arccosine of a single-precision floating-point number.\n","base.acosh":"\nbase.acosh( x:number )\n    Computes the hyperbolic arccosine of a double-precision floating-point\n    number.\n","base.acot":"\nbase.acot( x:number )\n    Computes the inverse cotangent of a double-precision floating-point number.\n","base.acotd":"\nbase.acotd( x:number )\n    Computes the arccotangent (in degrees) of a double-precision floating-point\n    number.\n","base.acotf":"\nbase.acotf( x:number )\n    Computes the inverse cotangent of a single-precision floating-point number.\n","base.acoth":"\nbase.acoth( x:number )\n    Computes the inverse hyperbolic cotangent of a double-precision floating-\n    point number.\n","base.acovercos":"\nbase.acovercos( x:number )\n    Computes the inverse coversed cosine.\n","base.acoversin":"\nbase.acoversin( x:number )\n    Computes the inverse coversed sine.\n","base.acsc":"\nbase.acsc( x:number )\n    Computes the arccosecant of a number.\n","base.acscd":"\nbase.acscd( x:number )\n    Computes the arccosecant of (in degrees) a double-precision floating-point\n    number.\n","base.acscdf":"\nbase.acscdf( x:number )\n    Computes the arccosecant (in degrees) of a single-precision floating-point\n    number.\n","base.acscf":"\nbase.acscf( x:number )\n    Computes the arccosecant of a single-precision floating-point number.\n","base.acsch":"\nbase.acsch( x:number )\n    Computes the hyperbolic arccosecant of a number.\n","base.add":"\nbase.add( x:number, y:number )\n    Computes the sum of two double-precision floating-point numbers `x` and `y`.\n","base.add3":"\nbase.add3( x:number, y:number, z:number )\n    Computes the sum of three double-precision floating-point numbers.\n","base.add4":"\nbase.add4( x:number, y:number, z:number, w:number )\n    Computes the sum of four double-precision floating-point numbers.\n","base.add5":"\nbase.add5( x:number, y:number, z:number, w:number, u:number )\n    Computes the sum of five double-precision floating-point numbers.\n","base.addf":"\nbase.addf( x:number, y:number )\n    Computes the sum of two single-precision floating-point numbers `x` and `y`.\n","base.afilled":"\nbase.afilled( value:any, len:integer )\n    Returns a filled \"generic\" array.\n","base.afilled2d":"\nbase.afilled2d( value:any, shape:Array<integer> )\n    Returns a filled two-dimensional nested array.\n","base.afilled2dBy":"\nbase.afilled2dBy( shape:Array<integer>, clbk:Function[, thisArg:any] )\n    Returns a filled two-dimensional nested array according to a provided\n    callback function.\n","base.afilled3d":"\nbase.afilled3d( value:any, shape:Array<integer> )\n    Returns a filled three-dimensional nested array.\n","base.afilled3dBy":"\nbase.afilled3dBy( shape:Array<integer>, clbk:Function[, thisArg:any] )\n    Returns a filled three-dimensional nested array according to a provided\n    callback function.\n","base.afilled4d":"\nbase.afilled4d( value:any, shape:Array<integer> )\n    Returns a filled four-dimensional nested array.\n","base.afilled4dBy":"\nbase.afilled4dBy( shape:Array<integer>, clbk:Function[, thisArg:any] )\n    Returns a filled four-dimensional nested array according to a provided\n    callback function.\n","base.afilled5d":"\nbase.afilled5d( value:any, shape:Array<integer> )\n    Returns a filled five-dimensional nested array.\n","base.afilled5dBy":"\nbase.afilled5dBy( shape:Array<integer>, clbk:Function[, thisArg:any] )\n    Returns a filled five-dimensional nested array according to a provided\n    callback function.\n","base.afilledBy":"\nbase.afilledBy( len:integer, clbk:Function[, thisArg:any] )\n    Returns a filled \"generic\" array according to a provided callback function.\n","base.afillednd":"\nbase.afillednd( value:any, shape:Array<integer> )\n    Returns a filled n-dimensional nested array.\n","base.afilledndBy":"\nbase.afilledndBy( shape:Array<integer>, clbk:Function[, thisArg:any] )\n    Returns a filled n-dimensional nested array according to a callback\n    function.\n","base.afilter":"\nbase.afilter( x:Array|TypedArray|Object, predicate:Function[, thisArg:any] )\n    Returns a shallow copy of an array containing only those elements which pass\n    a test implemented by a predicate function.\n","base.afirst":"\nbase.afirst( arr:ArrayLikeObject )\n    Returns the first element of an array-like object.\n","base.aflatten":"\nbase.aflatten( x:Array, shape:Array<integer>, colexicographic:boolean )\n    Flattens an n-dimensional nested array.\n","base.aflatten.assign":"\nbase.aflatten.assign( x:Array, shape:Array<integer>, colexicographic:boolean, \n  out:Collection, stride:integer, offset:integer )\n    Flattens an n-dimensional nested array and assigns elements to a provided\n    output array.\n","base.aflatten2d":"\nbase.aflatten2d( x:Array, shape:Array<integer>, colexicographic:boolean )\n    Flattens a two-dimensional nested array.\n","base.aflatten2d.assign":"\nbase.aflatten2d.assign( x:Array, shape:Array<integer>, colexicographic:boolean, \n  out:Collection, stride:integer, offset:integer )\n    Flattens a two-dimensional nested array and assigns elements to a provided\n    output array.\n","base.aflatten2dBy":"\nbase.aflatten2dBy( x:Array, shape:Array<integer>, colex:boolean, \n  clbk:Function[, thisArg:any] )\n    Flattens a two-dimensional nested array according to a callback function.\n","base.aflatten2dBy.assign":"\nbase.aflatten2dBy.assign( x:Array, shape:Array<integer>, colex:boolean, \n  out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n    Flattens a two-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n","base.aflatten3d":"\nbase.aflatten3d( x:ArrayLikeObject, shape:Array<integer>, \n  colexicographic:boolean )\n    Flattens a three-dimensional nested array.\n","base.aflatten3d.assign":"\nbase.aflatten3d.assign( x:Array, shape:Array<integer>, colexicographic:boolean, \n  out:Collection, stride:integer, offset:integer )\n    Flattens a three-dimensional nested array and assigns elements to a provided\n    output array.\n","base.aflatten3dBy":"\nbase.aflatten3dBy( x:ArrayLikeObject, shape:Array<integer>, colex:boolean, \n  clbk:Function[, thisArg:any] )\n    Flattens a three-dimensional nested array according to a callback function.\n","base.aflatten3dBy.assign":"\nbase.aflatten3dBy.assign( x:Array, shape:Array<integer>, colex:boolean, \n  out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n    Flattens a three-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n","base.aflatten4d":"\nbase.aflatten4d( x:ArrayLikeObject, shape:Array<integer>, \n  colexicographic:boolean )\n    Flattens a four-dimensional nested array.\n","base.aflatten4d.assign":"\nbase.aflatten4d.assign( x:Array, shape:Array<integer>, colexicographic:boolean, \n  out:Collection, stride:integer, offset:integer )\n    Flattens a four-dimensional nested array and assigns elements to a provided\n    output array.\n","base.aflatten4dBy":"\nbase.aflatten4dBy( x:ArrayLikeObject, shape:Array<integer>, colex:boolean, \n  clbk:Function[, thisArg:any] )\n    Flattens a four-dimensional nested array according to a callback function.\n","base.aflatten4dBy.assign":"\nbase.aflatten4dBy.assign( x:Array, shape:Array<integer>, colex:boolean, \n  out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n    Flattens a four-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n","base.aflatten5d":"\nbase.aflatten5d( x:ArrayLikeObject, shape:Array<integer>, \n  colexicographic:boolean )\n    Flattens a five-dimensional nested array.\n","base.aflatten5d.assign":"\nbase.aflatten5d.assign( x:Array, shape:Array<integer>, colexicographic:boolean, \n  out:Collection, stride:integer, offset:integer )\n    Flattens a five-dimensional nested array and assigns elements to a provided\n    output array.\n","base.aflatten5dBy":"\nbase.aflatten5dBy( x:ArrayLikeObject, shape:Array<integer>, colex:boolean, \n  clbk:Function[, thisArg:any] )\n    Flattens a five-dimensional nested array according to a callback function.\n","base.aflatten5dBy.assign":"\nbase.aflatten5dBy.assign( x:Array, shape:Array<integer>, colex:boolean, \n  out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n    Flattens a five-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n","base.aflattenBy":"\nbase.aflattenBy( x:Array, shape:Array<integer>, colex:boolean, clbk:Function[, \n  thisArg:any] )\n    Flattens an n-dimensional nested array according to a callback function.\n","base.aflattenBy.assign":"\nbase.aflattenBy.assign( x:Array, shape:Array<integer>, colex:boolean, \n  out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n    Flattens an n-dimensional nested array according to a callback function and\n    assigns elements to a provided output array.\n","base.afliplr2d":"\nbase.afliplr2d( x:ArrayLikeObject )\n    Reverses the order of elements along the last dimension of a two-dimensional\n    nested input array.\n","base.afliplr3d":"\nbase.afliplr3d( x:ArrayLikeObject )\n    Reverses the order of elements along the last dimension of a three-\n    dimensional nested input array.\n","base.afliplr4d":"\nbase.afliplr4d( x:ArrayLikeObject )\n    Reverses the order of elements along the last dimension of a four-\n    dimensional nested input array.\n","base.afliplr5d":"\nbase.afliplr5d( x:ArrayLikeObject )\n    Reverses the order of elements along the last dimension of a five-\n    dimensional nested input array.\n","base.aflipud2d":"\nbase.aflipud2d( x:ArrayLikeObject )\n    Reverses the order of elements along the first dimension of a two-\n    dimensional nested input array.\n","base.aflipud3d":"\nbase.aflipud3d( x:ArrayLikeObject )\n    Reverses the order of elements along the second-to-last dimension of a\n    three-dimensional nested input array.\n","base.aflipud4d":"\nbase.aflipud4d( x:ArrayLikeObject )\n    Reverses the order of elements along the second-to-last dimension of a four-\n    dimensional nested input array.\n","base.aflipud5d":"\nbase.aflipud5d( x:ArrayLikeObject )\n    Reverses the order of elements along the second-to-last dimension of a five-\n    dimensional nested input array.\n","base.ahavercos":"\nbase.ahavercos( x:number )\n    Computes the inverse half-value versed cosine.\n","base.ahaversin":"\nbase.ahaversin( x:number )\n    Computes the inverse half-value versed sine.\n","base.altcase":"\nbase.altcase( str:string )\n    Converts a string to alternate case.\n","base.aones":"\nbase.aones( len:integer )\n    Returns a \"generic\" array filled with ones.\n","base.aones2d":"\nbase.aones2d( shape:Array<integer> )\n    Returns a two-dimensional nested array filled with ones.\n","base.aones3d":"\nbase.aones3d( shape:Array<integer> )\n    Returns a three-dimensional nested array filled with ones.\n","base.aones4d":"\nbase.aones4d( shape:Array<integer> )\n    Returns a four-dimensional nested array filled with ones.\n","base.aones5d":"\nbase.aones5d( shape:Array<integer> )\n    Returns a five-dimensional nested array filled with ones.\n","base.aonesnd":"\nbase.aonesnd( shape:Array<integer> )\n    Returns an n-dimensional nested array filled with ones.\n","base.aoneTo":"\nbase.aoneTo( n:number )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from one.\n","base.aoneTo.assign":"\nbase.aoneTo.assign( out:ArrayLikeObject, stride:integer, offset:integer )\n    Fills an array with linearly spaced numeric elements which increment by 1\n    starting from one.\n","base.args2multislice":"\nbase.args2multislice( args:Array<Slice|integer|null|undefined> )\n    Creates a MultiSlice object from a list of MultiSlice constructor arguments.\n","base.asec":"\nbase.asec( x:number )\n    Computes the inverse (arc) secant of a number.\n","base.asecd":"\nbase.asecd( x:number )\n    Computes the arcsecant (in degrees) of a double-precision floating-point\n    number.\n","base.asecdf":"\nbase.asecdf( x:number )\n    Computes the arcsecant (in degrees) of a single-precision floating-point\n    number.\n","base.asecf":"\nbase.asecf( x:number )\n    Computes the inverse (arc) secant of a single-precision\n    floating-point number.\n","base.asech":"\nbase.asech( x:number )\n    Computes the hyperbolic arcsecant of a number.\n","base.asin":"\nbase.asin( x:number )\n    Computes the arcsine of a double-precision floating-point number.\n","base.asind":"\nbase.asind( x:number )\n    Computes the arcsine (in degrees) of a double-precision floating-point\n    number.\n","base.asindf":"\nbase.asindf( x:number )\n    Computes the arcsine (in degrees) of a single-precision floating-point\n    number.\n","base.asinf":"\nbase.asinf( x:number )\n    Computes the arcsine of a single-precision floating-point number.\n","base.asinh":"\nbase.asinh( x:number )\n    Computes the hyperbolic arcsine of a double-precision floating-point number.\n","base.atan":"\nbase.atan( x:number )\n    Computes the arctangent of a double-precision floating-point number.\n","base.atan2":"\nbase.atan2( y:number, x:number )\n    Computes the angle in the plane (in radians) between the positive x-axis and\n    the ray from (0,0) to the point (x,y).\n","base.atand":"\nbase.atand( x:number )\n    Computes the arctangent (in degrees) of a double-precision floating-point\n    number.\n","base.atanf":"\nbase.atanf( x:number )\n    Computes the arctangent of a single-precision floating-point number.\n","base.atanh":"\nbase.atanh( x:number )\n    Computes the hyperbolic arctangent of a double-precision floating-point\n    number.\n","base.avercos":"\nbase.avercos( x:number )\n    Computes the inverse versed cosine.\n","base.aversin":"\nbase.aversin( x:number )\n    Computes the inverse versed sine.\n","base.azeros":"\nbase.azeros( len:integer )\n    Returns a zero-filled \"generic\" array.\n","base.azeros2d":"\nbase.azeros2d( shape:Array<integer> )\n    Returns a zero-filled two-dimensional nested array.\n","base.azeros3d":"\nbase.azeros3d( shape:Array<integer> )\n    Returns a zero-filled three-dimensional nested array.\n","base.azeros4d":"\nbase.azeros4d( shape:Array<integer> )\n    Returns a zero-filled four-dimensional nested array.\n","base.azeros5d":"\nbase.azeros5d( shape:Array<integer> )\n    Returns a zero-filled five-dimensional nested array.\n","base.azerosnd":"\nbase.azerosnd( shape:Array<integer> )\n    Returns a zero-filled n-dimensional nested array.\n","base.azeroTo":"\nbase.azeroTo( n:number )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from zero.\n","base.azeroTo.assign":"\nbase.azeroTo.assign( out:ArrayLikeObject, stride:integer, offset:integer )\n    Fills an array with linearly spaced numeric elements which increment by 1\n    starting from zero.\n","base.bernoulli":"\nbase.bernoulli( n:integer )\n    Computes the nth Bernoulli number.\n","base.besselj0":"\nbase.besselj0( x:number )\n    Computes the Bessel function of the first kind of order zero.\n","base.besselj1":"\nbase.besselj1( x:number )\n    Computes the Bessel function of the first kind of order one.\n","base.bessely0":"\nbase.bessely0( x:number )\n    Computes the Bessel function of the second kind of order zero.\n","base.bessely1":"\nbase.bessely1( x:number )\n    Computes the Bessel function of the second kind of order one.\n","base.beta":"\nbase.beta( x:number, y:number )\n    Evaluates the beta function.\n","base.betainc":"\nbase.betainc( x:number, a:number, b:number[, regularized:boolean[, \n  upper:boolean]] )\n    Computes the regularized incomplete beta function.\n","base.betaincinv":"\nbase.betaincinv( p:number, a:number, b:number[, upper:boolean] )\n    Computes the inverse of the lower incomplete beta function.\n","base.betaln":"\nbase.betaln( a:number, b:number )\n    Evaluates the natural logarithm of the beta function.\n","base.binet":"\nbase.binet( x:number )\n    Evaluates Binet's formula extended to real numbers.\n","base.binomcoef":"\nbase.binomcoef( n:integer, k:integer )\n    Computes the binomial coefficient of two integers.\n","base.binomcoefln":"\nbase.binomcoefln( n:integer, k:integer )\n    Computes the natural logarithm of the binomial coefficient of two integers.\n","base.boxcox":"\nbase.boxcox( x:number, lambda:number )\n    Computes a one-parameter Box-Cox transformation.\n","base.boxcox1p":"\nbase.boxcox1p( x:number, lambda:number )\n    Computes a one-parameter Box-Cox transformation of 1+x.\n","base.boxcox1pinv":"\nbase.boxcox1pinv( y:number, lambda:number )\n    Computes the inverse of a one-parameter Box-Cox transformation for 1+x.\n","base.boxcoxinv":"\nbase.boxcoxinv( y:number, lambda:number )\n    Computes the inverse of a one-parameter Box-Cox transformation.\n","base.cabs":"\nbase.cabs( z:Complex128 )\n    Computes the absolute value of a double-precision complex floating-point\n    number.\n","base.cabs2":"\nbase.cabs2( z:Complex128 )\n    Computes the squared absolute value of a double-precision complex floating-\n    point number.\n","base.cabs2f":"\nbase.cabs2f( z:Complex64 )\n    Computes the squared absolute value of a single-precision complex floating-\n    point number.\n","base.cabsf":"\nbase.cabsf( z:Complex64 )\n    Computes the absolute value of a single-precision complex floating-point\n    number.\n","base.cadd":"\nbase.cadd( z1:Complex128, z2:Complex128 )\n    Adds two double-precision complex floating-point numbers.\n","base.caddf":"\nbase.caddf( z1:Complex64, z2:Complex64 )\n    Adds two single-precision complex floating-point numbers.\n","base.camelcase":"\nbase.camelcase( str:string )\n    Converts a string to camel case.\n","base.capitalize":"\nbase.capitalize( str:string )\n    Capitalizes the first character in a string.\n","base.cbrt":"\nbase.cbrt( x:number )\n    Computes the cube root of a double-precision floating-point number.\n","base.cbrtf":"\nbase.cbrtf( x:number )\n    Computes the cube root of a single-precision floating-point number.\n","base.cceil":"\nbase.cceil( z:Complex128 )\n    Rounds each component of a double-precision complex floating-point number\n    toward positive infinity.\n","base.cceilf":"\nbase.cceilf( z:Complex64 )\n    Rounds a single-precision complex floating-point number toward positive\n    infinity.\n","base.cceiln":"\nbase.cceiln( z:Complex128, n:integer )\n    Rounds each component of a double-precision complex number to the nearest\n    multiple of `10^n` toward positive infinity.\n","base.ccis":"\nbase.ccis( z:Complex128 )\n    Evaluates the cis function for a double-precision complex floating-point\n    number.\n","base.cdiv":"\nbase.cdiv( z1:Complex128, z2:Complex128 )\n    Divides two double-precision complex floating-point numbers.\n","base.ceil":"\nbase.ceil( x:number )\n    Rounds a double-precision floating-point number toward positive infinity.\n","base.ceil2":"\nbase.ceil2( x:number )\n    Rounds a numeric value to the nearest power of two toward positive infinity.\n","base.ceil10":"\nbase.ceil10( x:number )\n    Rounds a numeric value to the nearest power of ten toward positive infinity.\n","base.ceilb":"\nbase.ceilb( x:number, n:integer, b:integer )\n    Rounds a numeric value to the nearest multiple of `b^n` toward positive\n    infinity.\n","base.ceilf":"\nbase.ceilf( x:number )\n    Rounds a single-precision floating-point number toward positive infinity.\n","base.ceiln":"\nbase.ceiln( x:number, n:integer )\n    Rounds a numeric value to the nearest multiple of `10^n` toward positive\n    infinity.\n","base.ceilsd":"\nbase.ceilsd( x:number, n:integer, b:integer )\n    Rounds a numeric value to the nearest number toward positive infinity with\n    `n` significant figures.\n","base.cexp":"\nbase.cexp( z:Complex128 )\n    Evaluates the exponential function for a double-precision complex floating-\n    point number.\n","base.cflipsign":"\nbase.cflipsign( z:Complex128, y:number )\n    Returns a double-precision complex floating-point number with the same\n    magnitude as `z` and the sign of `y*z`.\n","base.cflipsignf":"\nbase.cflipsignf( z:Complex64, y:number )\n    Returns a single-precision complex floating-point number with the same\n    magnitude as `z` and the sign of `y*z`.\n","base.cfloor":"\nbase.cfloor( z:Complex128 )\n    Rounds a double-precision complex floating-point number toward negative\n    infinity.\n","base.cfloorn":"\nbase.cfloorn( z:Complex128, n:integer )\n    Rounds each component of a double-precision complex floating-point number\n    to the nearest multiple of `10^n` toward negative infinity.\n","base.cidentity":"\nbase.cidentity( z:Complex128 )\n    Evaluates the identity function for a double-precision complex floating-\n    point number.\n","base.cidentityf":"\nbase.cidentityf( z:Complex64 )\n    Evaluates the identity function for a single-precision complex floating-\n    point number.\n","base.cinv":"\nbase.cinv( z:Complex128 )\n    Computes the inverse of a double-precision complex floating-point number.\n","base.clamp":"\nbase.clamp( v:number, min:number, max:number )\n    Restricts a double-precision floating-point number to a specified range.\n","base.clampf":"\nbase.clampf( v:number, min:number, max:number )\n    Restricts a single-precision floating-point number to a specified range.\n","base.cmul":"\nbase.cmul( z1:Complex128, z2:Complex128 )\n    Multiplies two double-precision complex floating-point numbers.\n","base.cmulf":"\nbase.cmulf( z1:Complex64, z2:Complex64 )\n    Multiplies two single-precision complex floating-point numbers.\n","base.cneg":"\nbase.cneg( z )\n    Negates a double-precision complex floating-point number.\n","base.cnegf":"\nbase.cnegf( z )\n    Negates a single-precision complex floating-point number.\n","base.codePointAt":"\nbase.codePointAt( str:string, idx:integer, backward:boolean )\n    Returns a Unicode code point from a string at a specified position.\n","base.constantcase":"\nbase.constantcase( str:string )\n    Converts a string to constant case.\n","base.continuedFraction":"\nbase.continuedFraction( generator:Function[, options:Object] )\n    Evaluates the continued fraction approximation for the supplied series\n    generator using the modified Lentz algorithm.\n","base.copysign":"\nbase.copysign( x:number, y:number )\n    Returns a double-precision floating-point number with the magnitude of `x`\n    and the sign of `y`.\n","base.copysignf":"\nbase.copysignf( x:number, y:number )\n    Returns a single-precision floating-point number with the magnitude of `x`\n    and the sign of `y`.\n","base.cos":"\nbase.cos( x:number )\n    Computes the cosine of a number.\n","base.cosd":"\nbase.cosd( x:number )\n    Computes the cosine of an angle measured in degrees.\n","base.cosh":"\nbase.cosh( x:number )\n    Computes the hyperbolic cosine of a double-precision floating-point number.\n","base.cosm1":"\nbase.cosm1( x:number )\n    Computes the cosine of a number minus one.\n","base.cospi":"\nbase.cospi( x:number )\n    Computes the value of `cos(πx)`.\n","base.cot":"\nbase.cot( x:number )\n    Computes the cotangent of a number.\n","base.cotd":"\nbase.cotd( x:number )\n    Computes the cotangent of an angle measured in degrees.\n","base.coth":"\nbase.coth( x:number )\n    Computes the hyperbolic cotangent of a number.\n","base.covercos":"\nbase.covercos( x:number )\n    Computes the coversed cosine.\n","base.coversin":"\nbase.coversin( x:number )\n    Computes the coversed sine.\n","base.cphase":"\nbase.cphase( z:Complex128 )\n    Computes the argument of a double-precision complex floating-point number\n    in radians.\n","base.cpolar":"\nbase.cpolar( z:Complex128 )\n    Returns the absolute value and phase of a double-precision complex\n    floating-point number.\n","base.cpolar.assign":"\nbase.cpolar.assign( z:Complex128, out:Array|TypedArray|Object, stride:integer, \n  offset:integer )\n    Returns the absolute value and phase of a double-precision complex\n    floating-point number and assigns results to a provided output array.\n","base.cround":"\nbase.cround( z:Complex128 )\n    Rounds each component of a double-precision complex floating-point number\n    to the nearest integer.\n","base.croundn":"\nbase.croundn( z:Complex128, n:integer )\n    Rounds each component of a double-precision complex floating-point number\n    to the nearest multiple of `10^n`.\n","base.csc":"\nbase.csc( x:number )\n    Computes the cosecant of a number.\n","base.cscd":"\nbase.cscd( x:number )\n    Computes the cosecant of a degree.\n","base.csch":"\nbase.csch( x:number )\n    Computes the hyperbolic cosecant of a number.\n","base.csignum":"\nbase.csignum( z:Complex128 )\n    Evaluates the signum function of a double-precision complex floating-point\n    number.\n","base.csub":"\nbase.csub( z1:Complex128, z2:Complex128 )\n    Subtracts two double-precision complex floating-point numbers.\n","base.csubf":"\nbase.csubf( z1:Complex64, z2:Complex64 )\n    Subtracts two single-precision complex floating-point numbers.\n","base.deg2rad":"\nbase.deg2rad( x:number )\n    Converts an angle from degrees to radians.\n","base.deg2radf":"\nbase.deg2radf( x:number )\n    Converts an angle from degrees to radians (single-precision).\n","base.digamma":"\nbase.digamma( x:number )\n    Evaluates the digamma function.\n","base.diracDelta":"\nbase.diracDelta( x:number )\n    Evaluates the Dirac delta function.\n","base.div":"\nbase.div( x:number, y:number )\n    Divides two double-precision floating-point numbers `x` and `y`.\n","base.divf":"\nbase.divf( x:number, y:number )\n    Divides two single-precision floating-point numbers `x` and `y`.\n","base.dotcase":"\nbase.dotcase( str:string )\n    Converts a string to dot case.\n","base.dists.arcsine.Arcsine":"\nbase.dists.arcsine.Arcsine( [a:number, b:number] )\n    Returns an arcsine distribution object.\n","base.dists.arcsine.cdf":"\nbase.dists.arcsine.cdf( x:number, a:number, b:number )\n    Evaluates the cumulative distribution function (CDF) for an arcsine\n    distribution with minimum support `a` and maximum support `b` at a value\n    `x`.\n","base.dists.arcsine.cdf.factory":"\nbase.dists.arcsine.cdf.factory( a:number, b:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an arcsine distribution with minimum support `a` and maximum support `b`.\n","base.dists.arcsine.entropy":"\nbase.dists.arcsine.entropy( a:number, b:number )\n    Returns the differential entropy of an arcsine distribution (in nats).\n","base.dists.arcsine.kurtosis":"\nbase.dists.arcsine.kurtosis( a:number, b:number )\n    Returns the excess kurtosis of an arcsine distribution.\n","base.dists.arcsine.logcdf":"\nbase.dists.arcsine.logcdf( x:number, a:number, b:number )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for an\n    arcsine distribution with minimum support `a` and maximum support `b` at a\n    value `x`.\n","base.dists.arcsine.logcdf.factory":"\nbase.dists.arcsine.logcdf.factory( a:number, b:number )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of an arcsine distribution with minimum support\n    `a` and maximum support `b`.\n","base.dists.arcsine.logpdf":"\nbase.dists.arcsine.logpdf( x:number, a:number, b:number )\n    Evaluates the logarithm of the probability density function (PDF) for an\n    arcsine distribution with minimum support `a` and maximum support `b` at a\n    value `x`.\n","base.dists.arcsine.logpdf.factory":"\nbase.dists.arcsine.logpdf.factory( a:number, b:number )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of an arcsine distribution with minimum support `a` and\n    maximum support `b`.\n","base.dists.arcsine.mean":"\nbase.dists.arcsine.mean( a:number, b:number )\n    Returns the expected value of an arcsine distribution.\n","base.dists.arcsine.median":"\nbase.dists.arcsine.median( a:number, b:number )\n    Returns the median of an arcsine distribution.\n","base.dists.arcsine.mode":"\nbase.dists.arcsine.mode( a:number, b:number )\n    Returns the mode of an arcsine distribution.\n","base.dists.arcsine.pdf":"\nbase.dists.arcsine.pdf( x:number, a:number, b:number )\n    Evaluates the probability density function (PDF) for an arcsine distribution\n    with minimum support `a` and maximum support `b` at a value `x`.\n","base.dists.arcsine.pdf.factory":"\nbase.dists.arcsine.pdf.factory( a:number, b:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    an arcsine distribution with minimum support `a` and maximum support `b`.\n","base.dists.arcsine.quantile":"\nbase.dists.arcsine.quantile( p:number, a:number, b:number )\n    Evaluates the quantile function for an arcsine distribution with minimum\n    support `a` and maximum support `b` at a probability `p`.\n","base.dists.arcsine.quantile.factory":"\nbase.dists.arcsine.quantile.factory( a:number, b:number )\n    Returns a function for evaluating the quantile function of an arcsine\n    distribution with minimum support `a` and maximum support `b`.\n","base.dists.arcsine.skewness":"\nbase.dists.arcsine.skewness( a:number, b:number )\n    Returns the skewness of an arcsine distribution.\n","base.dists.arcsine.stdev":"\nbase.dists.arcsine.stdev( a:number, b:number )\n    Returns the standard deviation of an arcsine distribution.\n","base.dists.arcsine.variance":"\nbase.dists.arcsine.variance( a:number, b:number )\n    Returns the variance of an arcsine distribution.\n","base.dists.bernoulli.Bernoulli":"\nbase.dists.bernoulli.Bernoulli( [p:number] )\n    Returns a Bernoulli distribution object.\n","base.dists.bernoulli.cdf":"\nbase.dists.bernoulli.cdf( x:number, p:number )\n    Evaluates the cumulative distribution function (CDF) for a Bernoulli\n    distribution with success probability `p` at a value `x`.\n","base.dists.bernoulli.cdf.factory":"\nbase.dists.bernoulli.cdf.factory( p:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.entropy":"\nbase.dists.bernoulli.entropy( p:number )\n    Returns the entropy of a Bernoulli distribution with success probability\n    `p` (in nats).\n","base.dists.bernoulli.kurtosis":"\nbase.dists.bernoulli.kurtosis( p:number )\n    Returns the excess kurtosis of a Bernoulli distribution with success\n    probability `p`.\n","base.dists.bernoulli.mean":"\nbase.dists.bernoulli.mean( p:number )\n    Returns the expected value of a Bernoulli distribution with success\n    probability `p`.\n","base.dists.bernoulli.median":"\nbase.dists.bernoulli.median( p:number )\n    Returns the median of a Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.mgf":"\nbase.dists.bernoulli.mgf( t:number, p:number )\n    Evaluates the moment-generating function (MGF) for a Bernoulli\n    distribution with success probability `p` at a value `t`.\n","base.dists.bernoulli.mgf.factory":"\nbase.dists.bernoulli.mgf.factory( p:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.mode":"\nbase.dists.bernoulli.mode( p:number )\n    Returns the mode of a Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.pmf":"\nbase.dists.bernoulli.pmf( x:number, p:number )\n    Evaluates the probability mass function (PMF) for a Bernoulli distribution\n    with success probability `p` at a value `x`.\n","base.dists.bernoulli.pmf.factory":"\nbase.dists.bernoulli.pmf.factory( p:number )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.quantile":"\nbase.dists.bernoulli.quantile( r:number, p:number )\n    Evaluates the quantile function for a Bernoulli distribution with success\n    probability `p` at a probability `r`.\n","base.dists.bernoulli.quantile.factory":"\nbase.dists.bernoulli.quantile.factory( p:number )\n    Returns a function for evaluating the quantile function of a Bernoulli\n    distribution with success probability `p`.\n","base.dists.bernoulli.skewness":"\nbase.dists.bernoulli.skewness( p:number )\n    Returns the skewness of a Bernoulli distribution with success probability\n    `p`.\n","base.dists.bernoulli.stdev":"\nbase.dists.bernoulli.stdev( p:number )\n    Returns the standard deviation of a Bernoulli distribution with success\n    probability `p`.\n","base.dists.bernoulli.variance":"\nbase.dists.bernoulli.variance( p:number )\n    Returns the variance of a Bernoulli distribution with success probability\n    `p`.\n","base.dists.beta.Beta":"\nbase.dists.beta.Beta( [α:number, β:number] )\n    Returns a beta distribution object.\n","base.dists.beta.cdf":"\nbase.dists.beta.cdf( x:number, α:number, β:number )\n    Evaluates the cumulative distribution function (CDF) for a beta distribution\n    with first shape parameter `α` and second shape parameter `β` at a value\n    `x`.\n","base.dists.beta.cdf.factory":"\nbase.dists.beta.cdf.factory( α:number, β:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a beta distribution with first shape parameter `α` and second shape\n    parameter `β`.\n","base.dists.beta.entropy":"\nbase.dists.beta.entropy( α:number, β:number )\n    Returns the differential entropy of a beta distribution.\n","base.dists.beta.kurtosis":"\nbase.dists.beta.kurtosis( α:number, β:number )\n    Returns the excess kurtosis of a beta distribution.\n","base.dists.beta.logcdf":"\nbase.dists.beta.logcdf( x:number, α:number, β:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a beta distribution with first shape parameter `α` and second\n    shape parameter `β` at a value `x`.\n","base.dists.beta.logcdf.factory":"\nbase.dists.beta.logcdf.factory( α:number, β:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a beta distribution with first shape\n    parameter `α` and second shape parameter `β`.\n","base.dists.beta.logpdf":"\nbase.dists.beta.logpdf( x:number, α:number, β:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a beta distribution with first shape parameter `α` and second shape\n    parameter `β` at a value `x`.\n","base.dists.beta.logpdf.factory":"\nbase.dists.beta.logpdf.factory( α:number, β:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a beta distribution with first shape parameter `α`\n    and second shape parameter `β`.\n","base.dists.beta.mean":"\nbase.dists.beta.mean( α:number, β:number )\n    Returns the expected value of a beta distribution.\n","base.dists.beta.median":"\nbase.dists.beta.median( α:number, β:number )\n    Returns the median of a beta distribution.\n","base.dists.beta.mgf":"\nbase.dists.beta.mgf( t:number, α:number, β:number )\n    Evaluates the moment-generating function (MGF) for a beta distribution with\n    first shape parameter `α` and second shape parameter `β` at a value `t`.\n","base.dists.beta.mgf.factory":"\nbase.dists.beta.mgf.factory( α:number, β:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    beta distribution with first shape parameter `α` and second shape parameter\n    `β`.\n","base.dists.beta.mode":"\nbase.dists.beta.mode( α:number, β:number )\n    Returns the mode of a beta distribution.\n","base.dists.beta.pdf":"\nbase.dists.beta.pdf( x:number, α:number, β:number )\n    Evaluates the probability density function (PDF) for a beta distribution\n    with first shape parameter `α` and second shape parameter `β` at a value\n    `x`.\n","base.dists.beta.pdf.factory":"\nbase.dists.beta.pdf.factory( α:number, β:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a beta distribution with first shape parameter `α` and second shape\n    parameter `β`.\n","base.dists.beta.quantile":"\nbase.dists.beta.quantile( p:number, α:number, β:number )\n    Evaluates the quantile function for a beta distribution with first shape\n    parameter `α` and second shape parameter `β` at a probability `p`.\n","base.dists.beta.quantile.factory":"\nbase.dists.beta.quantile.factory( α:number, β:number )\n    Returns a function for evaluating the quantile function of a beta\n    distribution with first shape parameter `α` and second shape parameter `β`.\n","base.dists.beta.skewness":"\nbase.dists.beta.skewness( α:number, β:number )\n    Returns the skewness of a beta distribution.\n","base.dists.beta.stdev":"\nbase.dists.beta.stdev( α:number, β:number )\n    Returns the standard deviation of a beta distribution.\n","base.dists.beta.variance":"\nbase.dists.beta.variance( α:number, β:number )\n    Returns the variance of a beta distribution.\n","base.dists.betaprime.BetaPrime":"\nbase.dists.betaprime.BetaPrime( [α:number, β:number] )\n    Returns a beta prime distribution object.\n","base.dists.betaprime.cdf":"\nbase.dists.betaprime.cdf( x:number, α:number, β:number )\n    Evaluates the cumulative distribution function (CDF) for a beta prime\n    distribution with first shape parameter `α` and second shape parameter `β`\n    at a value `x`.\n","base.dists.betaprime.cdf.factory":"\nbase.dists.betaprime.cdf.factory( α:number, β:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a beta prime distribution with first shape parameter `α` and second shape\n    parameter `β`.\n","base.dists.betaprime.kurtosis":"\nbase.dists.betaprime.kurtosis( α:number, β:number )\n    Returns the excess kurtosis of a beta prime distribution.\n","base.dists.betaprime.logcdf":"\nbase.dists.betaprime.logcdf( x:number, α:number, β:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a beta prime distribution with first shape parameter `α` and\n    second shape parameter `β` at a value `x`.\n","base.dists.betaprime.logcdf.factory":"\nbase.dists.betaprime.logcdf.factory( α:number, β:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a beta prime distribution with first shape\n    parameter `α` and second shape parameter `β`.\n","base.dists.betaprime.logpdf":"\nbase.dists.betaprime.logpdf( x:number, α:number, β:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a beta prime distribution with first shape parameter `α` and second\n    shape parameter `β` at a value `x`.\n","base.dists.betaprime.logpdf.factory":"\nbase.dists.betaprime.logpdf.factory( α:number, β:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a beta prime distribution with first shape\n    parameter `α` and second shape parameter `β`.\n","base.dists.betaprime.mean":"\nbase.dists.betaprime.mean( α:number, β:number )\n    Returns the expected value of a beta prime distribution.\n","base.dists.betaprime.mode":"\nbase.dists.betaprime.mode( α:number, β:number )\n    Returns the mode of a beta prime distribution.\n","base.dists.betaprime.pdf":"\nbase.dists.betaprime.pdf( x:number, α:number, β:number )\n    Evaluates the probability density function (PDF) for a beta prime\n    distribution  with first shape parameter `α` and second shape parameter `β`\n    at a value `x`.\n","base.dists.betaprime.pdf.factory":"\nbase.dists.betaprime.pdf.factory( α:number, β:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a beta prime distribution with first shape parameter `α` and second shape\n    parameter `β`.\n","base.dists.betaprime.quantile":"\nbase.dists.betaprime.quantile( p:number, α:number, β:number )\n    Evaluates the quantile function for a beta prime distribution with first\n    shape parameter `α` and second shape parameter `β` at a probability `p`.\n","base.dists.betaprime.quantile.factory":"\nbase.dists.betaprime.quantile.factory( α:number, β:number )\n    Returns a function for evaluating the quantile function of a beta prime\n    distribution with first shape parameter `α` and second shape parameter `β`.\n","base.dists.betaprime.skewness":"\nbase.dists.betaprime.skewness( α:number, β:number )\n    Returns the skewness of a beta prime distribution.\n","base.dists.betaprime.stdev":"\nbase.dists.betaprime.stdev( α:number, β:number )\n    Returns the standard deviation of a beta prime distribution.\n","base.dists.betaprime.variance":"\nbase.dists.betaprime.variance( α:number, β:number )\n    Returns the variance of a beta prime distribution.\n","base.dists.binomial.Binomial":"\nbase.dists.binomial.Binomial( [n:integer, p:number] )\n    Returns a binomial distribution object.\n","base.dists.binomial.cdf":"\nbase.dists.binomial.cdf( x:number, n:integer, p:number )\n    Evaluates the cumulative distribution function (CDF) for a binomial\n    distribution with number of trials `n` and success probability `p` at a\n    value `x`.\n","base.dists.binomial.cdf.factory":"\nbase.dists.binomial.cdf.factory( n:integer, p:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a binomial distribution with number of trials `n` and success probability\n    `p`.\n","base.dists.binomial.entropy":"\nbase.dists.binomial.entropy( n:integer, p:number )\n    Returns the entropy of a binomial distribution.\n","base.dists.binomial.kurtosis":"\nbase.dists.binomial.kurtosis( n:integer, p:number )\n    Returns the excess kurtosis of a binomial distribution.\n","base.dists.binomial.logpmf":"\nbase.dists.binomial.logpmf( x:number, n:integer, p:number )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    binomial distribution with number of trials `n` and success probability `p`\n    at a value `x`.\n","base.dists.binomial.logpmf.factory":"\nbase.dists.binomial.logpmf.factory( n:integer, p:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a binomial distribution with number of trials `n` and\n    success probability `p`.\n","base.dists.binomial.mean":"\nbase.dists.binomial.mean( n:integer, p:number )\n    Returns the expected value of a binomial distribution.\n","base.dists.binomial.median":"\nbase.dists.binomial.median( n:integer, p:number )\n    Returns the median of a binomial distribution.\n","base.dists.binomial.mgf":"\nbase.dists.binomial.mgf( t:number, n:integer, p:number )\n    Evaluates the moment-generating function (MGF) for a binomial distribution\n    with number of trials `n` and success probability `p` at a value `t`.\n","base.dists.binomial.mgf.factory":"\nbase.dists.binomial.mgf.factory( n:integer, p:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    binomial distribution with number of trials `n` and success probability `p`.\n","base.dists.binomial.mode":"\nbase.dists.binomial.mode( n:integer, p:number )\n    Returns the mode of a binomial distribution.\n","base.dists.binomial.pmf":"\nbase.dists.binomial.pmf( x:number, n:integer, p:number )\n    Evaluates the probability mass function (PMF) for a binomial distribution\n    with number of trials `n` and success probability `p` at a value `x`.\n","base.dists.binomial.pmf.factory":"\nbase.dists.binomial.pmf.factory( n:integer, p:number )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    binomial distribution with number of trials `n` and success probability `p`.\n","base.dists.binomial.quantile":"\nbase.dists.binomial.quantile( r:number, n:integer, p:number )\n    Evaluates the quantile function for a binomial distribution with number of\n    trials `n` and success probability `p` at a probability `r`.\n","base.dists.binomial.quantile.factory":"\nbase.dists.binomial.quantile.factory( n:integer, p:number )\n    Returns a function for evaluating the quantile function of a binomial\n    distribution with number of trials `n` and success probability `p`.\n","base.dists.binomial.skewness":"\nbase.dists.binomial.skewness( n:integer, p:number )\n    Returns the skewness of a binomial distribution.\n","base.dists.binomial.stdev":"\nbase.dists.binomial.stdev( n:integer, p:number )\n    Returns the standard deviation of a binomial distribution.\n","base.dists.binomial.variance":"\nbase.dists.binomial.variance( n:integer, p:number )\n    Returns the variance of a binomial distribution.\n","base.dists.cauchy.Cauchy":"\nbase.dists.cauchy.Cauchy( [x0:number, Ɣ:number] )\n    Returns a Cauchy distribution object.\n","base.dists.cauchy.cdf":"\nbase.dists.cauchy.cdf( x:number, x0:number, Ɣ:number )\n    Evaluates the cumulative distribution function (CDF) for a Cauchy\n    distribution with location parameter `x0` and scale parameter `Ɣ` at a value\n    `x`.\n","base.dists.cauchy.cdf.factory":"\nbase.dists.cauchy.cdf.factory( x0:number, Ɣ:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Cauchy distribution with location parameter `x0` and scale parameter\n    `Ɣ`.\n","base.dists.cauchy.entropy":"\nbase.dists.cauchy.entropy( x0:number, Ɣ:number )\n    Returns the differential entropy of a Cauchy distribution (in nats).\n","base.dists.cauchy.logcdf":"\nbase.dists.cauchy.logcdf( x:number, x0:number, Ɣ:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (logCDF) for a Cauchy distribution with location parameter `x0` and scale\n    parameter `Ɣ` at a value `x`.\n","base.dists.cauchy.logcdf.factory":"\nbase.dists.cauchy.logcdf.factory( x0:number, Ɣ:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (logCDF) of a Cauchy distribution with location\n    parameter `x0` and scale parameter `Ɣ`.\n","base.dists.cauchy.logpdf":"\nbase.dists.cauchy.logpdf( x:number, x0:number, Ɣ:number )\n    Evaluates the natural logarithm of the probability density function (logPDF)\n    for a Cauchy distribution with location parameter `x0` and scale parameter\n    `Ɣ` at a value `x`.\n","base.dists.cauchy.logpdf.factory":"\nbase.dists.cauchy.logpdf.factory( x0:number, Ɣ:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (logPDF) of a Cauchy distribution with location parameter\n    `x0` and scale parameter `Ɣ`.\n","base.dists.cauchy.median":"\nbase.dists.cauchy.median( x0:number, Ɣ:number )\n    Returns the median of a Cauchy distribution.\n","base.dists.cauchy.mode":"\nbase.dists.cauchy.mode( x0:number, Ɣ:number )\n    Returns the mode of a Cauchy distribution.\n","base.dists.cauchy.pdf":"\nbase.dists.cauchy.pdf( x:number, x0:number, Ɣ:number )\n    Evaluates the probability density function (PDF) for a Cauchy distribution\n    with location parameter `x0` and scale parameter `Ɣ` at a value `x`.\n","base.dists.cauchy.pdf.factory":"\nbase.dists.cauchy.pdf.factory( x0:number, Ɣ:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Cauchy distribution with location parameter `x0` and scale parameter `Ɣ`.\n","base.dists.cauchy.quantile":"\nbase.dists.cauchy.quantile( p:number, x0:number, Ɣ:number )\n    Evaluates the quantile function for a Cauchy distribution with location\n    parameter `x0`  and scale parameter `Ɣ` at a probability `p`.\n","base.dists.cauchy.quantile.factory":"\nbase.dists.cauchy.quantile.factory( x0:number, Ɣ:number )\n    Returns a function for evaluating the quantile function of a Cauchy\n    distribution with location parameter `x0` and scale parameter `Ɣ`.\n","base.dists.chi.cdf":"\nbase.dists.chi.cdf( x:number, k:number )\n    Evaluates the cumulative distribution function (CDF) for a chi distribution\n    with degrees of freedom `k` at a value `x`.\n","base.dists.chi.cdf.factory":"\nbase.dists.chi.cdf.factory( k:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a chi distribution with degrees of freedom `k`.\n","base.dists.chi.Chi":"\nbase.dists.chi.Chi( [k:number] )\n    Returns a chi distribution object.\n","base.dists.chi.entropy":"\nbase.dists.chi.entropy( k:number )\n    Returns the differential entropy of a chi distribution (in nats).\n","base.dists.chi.kurtosis":"\nbase.dists.chi.kurtosis( k:number )\n    Returns the excess kurtosis of a chi distribution.\n","base.dists.chi.logpdf":"\nbase.dists.chi.logpdf( x:number, k:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a chi distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chi.logpdf.factory":"\nbase.dists.chi.logpdf.factory( k:number )\n    Returns a function for evaluating the natural logarithm of the  probability\n    density function (PDF) of a chi distribution with degrees of freedom `k`.\n","base.dists.chi.mean":"\nbase.dists.chi.mean( k:number )\n    Returns the expected value of a chi distribution.\n","base.dists.chi.mode":"\nbase.dists.chi.mode( k:number )\n    Returns the mode of a chi distribution.\n","base.dists.chi.pdf":"\nbase.dists.chi.pdf( x:number, k:number )\n    Evaluates the probability density function (PDF) for a chi distribution with\n    degrees of freedom `k` at a value `x`.\n","base.dists.chi.pdf.factory":"\nbase.dists.chi.pdf.factory( k:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a chi distribution with degrees of freedom `k`.\n","base.dists.chi.quantile":"\nbase.dists.chi.quantile( p:number, k:number )\n    Evaluates the quantile function for a chi distribution with degrees of\n    freedom `k` at a probability `p`.\n","base.dists.chi.quantile.factory":"\nbase.dists.chi.quantile.factory( k:number )\n    Returns a function for evaluating the quantile function of a chi\n    distribution with degrees of freedom `k`.\n","base.dists.chi.skewness":"\nbase.dists.chi.skewness( k:number )\n    Returns the skewness of a chi distribution.\n","base.dists.chi.stdev":"\nbase.dists.chi.stdev( k:number )\n    Returns the standard deviation of a chi distribution.\n","base.dists.chi.variance":"\nbase.dists.chi.variance( k:number )\n    Returns the variance of a chi distribution.\n","base.dists.chisquare.cdf":"\nbase.dists.chisquare.cdf( x:number, k:number )\n    Evaluates the cumulative distribution function (CDF) for a chi-squared\n    distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chisquare.cdf.factory":"\nbase.dists.chisquare.cdf.factory( k:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a chi-squared distribution with degrees of freedom `k`.\n","base.dists.chisquare.ChiSquare":"\nbase.dists.chisquare.ChiSquare( [k:number] )\n    Returns a  chi-squared distribution object.\n","base.dists.chisquare.entropy":"\nbase.dists.chisquare.entropy( k:number )\n    Returns the differential entropy of a chi-squared distribution (in nats).\n","base.dists.chisquare.kurtosis":"\nbase.dists.chisquare.kurtosis( k:number )\n    Returns the excess kurtosis of a chi-squared distribution.\n","base.dists.chisquare.logpdf":"\nbase.dists.chisquare.logpdf( x:number, k:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a chi-squared distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chisquare.logpdf.factory":"\nbase.dists.chisquare.logpdf.factory( k:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a chi-squared distribution with degrees of freedom\n    `k`.\n","base.dists.chisquare.mean":"\nbase.dists.chisquare.mean( k:number )\n    Returns the expected value of a chi-squared distribution.\n","base.dists.chisquare.median":"\nbase.dists.chisquare.median( k:number )\n    Returns the median of a chi-squared distribution.\n","base.dists.chisquare.mgf":"\nbase.dists.chisquare.mgf( t:number, k:number )\n    Evaluates the moment-generating function (MGF) for a chi-squared\n    distribution with degrees of freedom `k` at a value `t`.\n","base.dists.chisquare.mgf.factory":"\nbase.dists.chisquare.mgf.factory( k:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    chi-squared distribution with degrees of freedom `k`.\n","base.dists.chisquare.mode":"\nbase.dists.chisquare.mode( k:number )\n    Returns the mode of a chi-squared distribution.\n","base.dists.chisquare.pdf":"\nbase.dists.chisquare.pdf( x:number, k:number )\n    Evaluates the probability density function (PDF) for a chi-squared\n    distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chisquare.pdf.factory":"\nbase.dists.chisquare.pdf.factory( k:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a chi-squared distribution with degrees of freedom `k`.\n","base.dists.chisquare.quantile":"\nbase.dists.chisquare.quantile( p:number, k:number )\n    Evaluates the quantile function for a chi-squared distribution with degrees\n    of freedom `k` at a probability `p`.\n","base.dists.chisquare.quantile.factory":"\nbase.dists.chisquare.quantile.factory( k:number )\n    Returns a function for evaluating the quantile function of a chi-squared\n    distribution with degrees of freedom `k`.\n","base.dists.chisquare.skewness":"\nbase.dists.chisquare.skewness( k:number )\n    Returns the skewness of a chi-squared distribution.\n","base.dists.chisquare.stdev":"\nbase.dists.chisquare.stdev( k:number )\n    Returns the standard deviation of a chi-squared distribution.\n","base.dists.chisquare.variance":"\nbase.dists.chisquare.variance( k:number )\n    Returns the variance of a chi-squared distribution.\n","base.dists.cosine.cdf":"\nbase.dists.cosine.cdf( x:number, μ:number, s:number )\n    Evaluates the cumulative distribution function (CDF) for a raised cosine\n    distribution with location parameter `μ` and scale parameter `s` at a value\n    `x`.\n","base.dists.cosine.cdf.factory":"\nbase.dists.cosine.cdf.factory( μ:number, s:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a raised cosine distribution with location parameter `μ` and scale\n    parameter `s`.\n","base.dists.cosine.Cosine":"\nbase.dists.cosine.Cosine( [μ:number, s:number] )\n    Returns a raised cosine distribution object.\n","base.dists.cosine.kurtosis":"\nbase.dists.cosine.kurtosis( μ:number, s:number )\n    Returns the excess kurtosis of a raised cosine distribution with location\n    parameter `μ` and scale parameter `s`.\n","base.dists.cosine.logcdf":"\nbase.dists.cosine.logcdf( x:number, μ:number, s:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a raised cosine distribution with location parameter `μ` and scale\n     parameter `s` at a value `x`.\n","base.dists.cosine.logcdf.factory":"\nbase.dists.cosine.logcdf.factory( μ:number, s:number )\n    Returns a function for evaluating the natural logarithm of the  cumulative\n    distribution function (CDF) of a raised cosine distribution with location\n    parameter `μ` and scale parameter `s`.\n","base.dists.cosine.logpdf":"\nbase.dists.cosine.logpdf( x:number, μ:number, s:number )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    raised cosine distribution with location parameter `μ` and scale parameter\n    `s` at a value `x`.\n","base.dists.cosine.logpdf.factory":"\nbase.dists.cosine.logpdf.factory( μ:number, s:number )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a raised cosine distribution with location parameter `μ`\n    and scale parameter `s`.\n","base.dists.cosine.mean":"\nbase.dists.cosine.mean( μ:number, s:number )\n    Returns the expected value of a raised cosine distribution with location\n    parameter `μ` and scale parameter `s`.\n","base.dists.cosine.median":"\nbase.dists.cosine.median( μ:number, s:number )\n    Returns the median of a raised cosine distribution with location parameter\n    `μ` and scale parameter `s`.\n","base.dists.cosine.mgf":"\nbase.dists.cosine.mgf( t:number, μ:number, s:number )\n    Evaluates the moment-generating function (MGF) for a raised cosine\n    distribution with location parameter `μ` and scale parameter `s` at a value\n    `t`.\n","base.dists.cosine.mgf.factory":"\nbase.dists.cosine.mgf.factory( μ:number, s:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    raised cosine distribution with location parameter `μ` and scale parameter\n    `s`.\n","base.dists.cosine.mode":"\nbase.dists.cosine.mode( μ:number, s:number )\n    Returns the mode of a raised cosine distribution with location parameter `μ`\n    and scale parameter `s`.\n","base.dists.cosine.pdf":"\nbase.dists.cosine.pdf( x:number, μ:number, s:number )\n    Evaluates the probability density function (PDF) for a raised cosine\n    distribution with location parameter `μ` and scale parameter `s` at a value\n    `x`.\n","base.dists.cosine.pdf.factory":"\nbase.dists.cosine.pdf.factory( μ:number, s:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a raised cosine distribution with location parameter `μ` and scale parameter\n    `s`.\n","base.dists.cosine.quantile":"\nbase.dists.cosine.quantile( p:number, μ:number, s:number )\n    Evaluates the quantile function for a raised cosine distribution with\n    location parameter `μ` and scale parameter `s` at a probability `p`.\n","base.dists.cosine.quantile.factory":"\nbase.dists.cosine.quantile.factory( μ:number, s:number )\n    Returns a function for evaluating the quantile function of a raised cosine\n    distribution with location parameter `μ` and scale parameter `s`.\n","base.dists.cosine.skewness":"\nbase.dists.cosine.skewness( μ:number, s:number )\n    Returns the skewness of a raised cosine distribution with location parameter\n    `μ` and scale parameter `s`.\n","base.dists.cosine.stdev":"\nbase.dists.cosine.stdev( μ:number, s:number )\n    Returns the standard deviation of a raised cosine distribution with location\n    parameter `μ` and scale parameter `s`.\n","base.dists.cosine.variance":"\nbase.dists.cosine.variance( μ:number, s:number )\n    Returns the variance of a raised cosine distribution with location parameter\n    `μ` and scale parameter `s`.\n","base.dists.degenerate.cdf":"\nbase.dists.degenerate.cdf( x:number, μ:number )\n    Evaluates the cumulative distribution function (CDF) for a degenerate\n    distribution with mean value `μ`.\n","base.dists.degenerate.cdf.factory":"\nbase.dists.degenerate.cdf.factory( μ:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a degenerate distribution centered at a provided mean value.\n","base.dists.degenerate.Degenerate":"\nbase.dists.degenerate.Degenerate( [μ:number] )\n    Returns a degenerate distribution object.\n","base.dists.degenerate.entropy":"\nbase.dists.degenerate.entropy( μ:number )\n    Returns the entropy of a degenerate distribution with constant value `μ`.\n","base.dists.degenerate.logcdf":"\nbase.dists.degenerate.logcdf( x:number, μ:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (logCDF) for a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logcdf.factory":"\nbase.dists.degenerate.logcdf.factory( μ:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (logCDF) of a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpdf":"\nbase.dists.degenerate.logpdf( x:number, μ:number )\n    Evaluates the natural logarithm of the probability density function (logPDF)\n    for a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpdf.factory":"\nbase.dists.degenerate.logpdf.factory( μ:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (logPDF) of a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpmf":"\nbase.dists.degenerate.logpmf( x:number, μ:number )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpmf.factory":"\nbase.dists.degenerate.logpmf.factory( μ:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a degenerate distribution with mean `μ`.\n","base.dists.degenerate.mean":"\nbase.dists.degenerate.mean( μ:number )\n    Returns the expected value of a degenerate distribution with constant value\n    `μ`.\n","base.dists.degenerate.median":"\nbase.dists.degenerate.median( μ:number )\n    Returns the median of a degenerate distribution with constant value `μ`.\n","base.dists.degenerate.mgf":"\nbase.dists.degenerate.mgf( x:number, μ:number )\n    Evaluates the moment-generating function (MGF) for a degenerate distribution\n    with mean `μ`.\n","base.dists.degenerate.mgf.factory":"\nbase.dists.degenerate.mgf.factory( μ:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    degenerate distribution with mean `μ`.\n","base.dists.degenerate.mode":"\nbase.dists.degenerate.mode( μ:number )\n    Returns the mode of a degenerate distribution with constant value `μ`.\n","base.dists.degenerate.pdf":"\nbase.dists.degenerate.pdf( x:number, μ:number )\n    Evaluates the probability density function (PDF) for a degenerate\n    distribution with mean `μ`.\n","base.dists.degenerate.pdf.factory":"\nbase.dists.degenerate.pdf.factory( μ:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a degenerate distribution with mean `μ`.\n","base.dists.degenerate.pmf":"\nbase.dists.degenerate.pmf( x:number, μ:number )\n    Evaluates the probability mass function (PMF) for a degenerate distribution\n    with mean `μ`.\n","base.dists.degenerate.pmf.factory":"\nbase.dists.degenerate.pmf.factory( μ:number )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    degenerate distribution with mean `μ`.\n","base.dists.degenerate.quantile":"\nbase.dists.degenerate.quantile( p:number, μ:number )\n    Evaluates the quantile function for a degenerate distribution with mean `μ`.\n","base.dists.degenerate.quantile.factory":"\nbase.dists.degenerate.quantile.factory( μ:number )\n    Returns a function for evaluating the quantile function of a degenerate\n    distribution with mean `μ`.\n","base.dists.degenerate.stdev":"\nbase.dists.degenerate.stdev( μ:number )\n    Returns the standard deviation of a degenerate distribution with constant\n    value `μ`.\n","base.dists.degenerate.variance":"\nbase.dists.degenerate.variance( μ:number )\n    Returns the variance of a degenerate distribution with constant value `μ`.\n","base.dists.discreteUniform.cdf":"\nbase.dists.discreteUniform.cdf( x:number, a:integer, b:integer )\n    Evaluates the cumulative distribution function (CDF) for a discrete uniform\n    distribution with minimum support `a` and maximum support `b` at a value\n    `x`.\n","base.dists.discreteUniform.cdf.factory":"\nbase.dists.discreteUniform.cdf.factory( a:integer, b:integer )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a discrete uniform distribution with minimum support `a` and maximum\n    support `b`.\n","base.dists.discreteUniform.DiscreteUniform":"\nbase.dists.discreteUniform.DiscreteUniform( [a:integer, b:integer] )\n    Returns a discrete uniform distribution object.\n","base.dists.discreteUniform.entropy":"\nbase.dists.discreteUniform.entropy( a:integer, b:integer )\n    Returns the entropy of a discrete uniform distribution.\n","base.dists.discreteUniform.kurtosis":"\nbase.dists.discreteUniform.kurtosis( a:integer, b:integer )\n    Returns the excess kurtosis of a discrete uniform distribution.\n","base.dists.discreteUniform.logcdf":"\nbase.dists.discreteUniform.logcdf( x:number, a:integer, b:integer )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a discrete uniform distribution with minimum support `a` and\n    maximum support `b` at a value `x`.\n","base.dists.discreteUniform.logcdf.factory":"\nbase.dists.discreteUniform.logcdf.factory( a:integer, b:integer )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a discrete uniform distribution with minimum\n    support `a` and maximum support `b`.\n","base.dists.discreteUniform.logpmf":"\nbase.dists.discreteUniform.logpmf( x:number, a:integer, b:integer )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    discrete uniform distribution with minimum support `a` and maximum support\n    `b` at a value `x`.\n","base.dists.discreteUniform.logpmf.factory":"\nbase.dists.discreteUniform.logpmf.factory( a:integer, b:integer )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a discrete uniform distribution with minimum support\n    `a` and maximum support `b`.\n","base.dists.discreteUniform.mean":"\nbase.dists.discreteUniform.mean( a:integer, b:integer )\n    Returns the expected value of a discrete uniform distribution.\n","base.dists.discreteUniform.median":"\nbase.dists.discreteUniform.median( a:integer, b:integer )\n    Returns the median of a discrete uniform distribution.\n","base.dists.discreteUniform.mgf":"\nbase.dists.discreteUniform.mgf( t:number, a:integer, b:integer )\n    Evaluates the moment-generating function (MGF) for a discrete uniform\n    distribution with minimum support `a` and maximum support `b` at a value\n    `t`.\n","base.dists.discreteUniform.mgf.factory":"\nbase.dists.discreteUniform.mgf.factory( a:integer, b:integer )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a discrete uniform distribution with minimum support `a` and maximum\n    support `b`.\n","base.dists.discreteUniform.pmf":"\nbase.dists.discreteUniform.pmf( x:number, a:integer, b:integer )\n    Evaluates the probability mass function (PMF) for a discrete uniform\n    distribution with minimum support `a` and maximum support `b` at a value\n    `x`.\n","base.dists.discreteUniform.pmf.factory":"\nbase.dists.discreteUniform.pmf.factory( a:integer, b:integer )\n    Returns a function for evaluating the probability mass function (PMF) of\n    a discrete uniform distribution with minimum support `a` and maximum support\n    `b`.\n","base.dists.discreteUniform.quantile":"\nbase.dists.discreteUniform.quantile( p:number, a:integer, b:integer )\n    Evaluates the quantile function for a discrete uniform distribution with\n    minimum support `a` and maximum support `b` at a probability `p`.\n","base.dists.discreteUniform.quantile.factory":"\nbase.dists.discreteUniform.quantile.factory( a:integer, b:integer )\n    Returns a function for evaluating the quantile function of a discrete\n    uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.discreteUniform.skewness":"\nbase.dists.discreteUniform.skewness( a:integer, b:integer )\n    Returns the skewness of a discrete uniform distribution.\n","base.dists.discreteUniform.stdev":"\nbase.dists.discreteUniform.stdev( a:integer, b:integer )\n    Returns the standard deviation of a discrete uniform distribution.\n","base.dists.discreteUniform.variance":"\nbase.dists.discreteUniform.variance( a:integer, b:integer )\n    Returns the variance of a discrete uniform distribution.\n","base.dists.erlang.cdf":"\nbase.dists.erlang.cdf( x:number, k:number, λ:number )\n    Evaluates the cumulative distribution function (CDF) for an Erlang\n    distribution with shape parameter `k` and rate parameter `λ` at a value\n    `x`.\n","base.dists.erlang.cdf.factory":"\nbase.dists.erlang.cdf.factory( k:number, λ:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.entropy":"\nbase.dists.erlang.entropy( k:integer, λ:number )\n    Returns the differential entropy of an Erlang distribution (in nats).\n","base.dists.erlang.Erlang":"\nbase.dists.erlang.Erlang( [k:number, λ:number] )\n    Returns an Erlang distribution object.\n","base.dists.erlang.kurtosis":"\nbase.dists.erlang.kurtosis( k:integer, λ:number )\n    Returns the excess kurtosis of an Erlang distribution.\n","base.dists.erlang.logpdf":"\nbase.dists.erlang.logpdf( x:number, k:number, λ:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for an Erlang distribution with shape parameter `k` and rate parameter `λ`\n    at a value `x`.\n","base.dists.erlang.logpdf.factory":"\nbase.dists.erlang.logpdf.factory( k:number, λ:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of an Erlang distribution with shape parameter `k`\n    and rate parameter `λ`.\n","base.dists.erlang.mean":"\nbase.dists.erlang.mean( k:integer, λ:number )\n    Returns the expected value of an Erlang distribution.\n","base.dists.erlang.mgf":"\nbase.dists.erlang.mgf( t:number, k:number, λ:number )\n    Evaluates the moment-generating function (MGF) for an Erlang distribution\n    with shape parameter `k` and rate parameter `λ` at a value `t`.\n","base.dists.erlang.mgf.factory":"\nbase.dists.erlang.mgf.factory( k:number, λ:number )\n    Returns a function for evaluating the moment-generating function (MGF) of an\n    Erlang distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.mode":"\nbase.dists.erlang.mode( k:integer, λ:number )\n    Returns the mode of an Erlang distribution.\n","base.dists.erlang.pdf":"\nbase.dists.erlang.pdf( x:number, k:number, λ:number )\n    Evaluates the probability density function (PDF) for an Erlang distribution\n    with shape parameter `k` and rate parameter `λ` at a value `x`.\n","base.dists.erlang.pdf.factory":"\nbase.dists.erlang.pdf.factory( k:number, λ:number )\n    Returns a function for evaluating the probability density function (PDF)\n    of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.quantile":"\nbase.dists.erlang.quantile( p:number, k:number, λ:number )\n    Evaluates the quantile function for an Erlang distribution with shape\n    parameter `k` and rate parameter `λ` at a probability `p`.\n","base.dists.erlang.quantile.factory":"\nbase.dists.erlang.quantile.factory( k:number, λ:number )\n    Returns a function for evaluating the quantile function of an Erlang\n    distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.skewness":"\nbase.dists.erlang.skewness( k:integer, λ:number )\n    Returns the skewness of an Erlang distribution.\n","base.dists.erlang.stdev":"\nbase.dists.erlang.stdev( k:integer, λ:number )\n    Returns the standard deviation of an Erlang distribution.\n","base.dists.erlang.variance":"\nbase.dists.erlang.variance( k:integer, λ:number )\n    Returns the variance of an Erlang distribution.\n","base.dists.exponential.cdf":"\nbase.dists.exponential.cdf( x:number, λ:number )\n    Evaluates the cumulative distribution function (CDF) for an exponential\n    distribution with rate parameter `λ` at a value `x`.\n","base.dists.exponential.cdf.factory":"\nbase.dists.exponential.cdf.factory( λ:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    for an exponential distribution with rate parameter `λ`.\n","base.dists.exponential.entropy":"\nbase.dists.exponential.entropy( λ:number )\n    Returns the differential entropy of an exponential distribution.\n","base.dists.exponential.Exponential":"\nbase.dists.exponential.Exponential( [λ:number] )\n    Returns an exponential distribution object.\n","base.dists.exponential.kurtosis":"\nbase.dists.exponential.kurtosis( λ:number )\n    Returns the excess kurtosis of an exponential distribution.\n","base.dists.exponential.logcdf":"\nbase.dists.exponential.logcdf( x:number, λ:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for an exponential distribution with rate parameter `λ` at a value\n    `x`.\n","base.dists.exponential.logcdf.factory":"\nbase.dists.exponential.logcdf.factory( λ:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) for an exponential distribution with rate\n    parameter `λ`.\n","base.dists.exponential.logpdf":"\nbase.dists.exponential.logpdf( x:number, λ:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for an exponential distribution with rate parameter `λ` at a value `x`.\n","base.dists.exponential.logpdf.factory":"\nbase.dists.exponential.logpdf.factory( λ:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) for an exponential distribution with rate parameter\n    `λ`.\n","base.dists.exponential.mean":"\nbase.dists.exponential.mean( λ:number )\n    Returns the expected value of an exponential distribution.\n","base.dists.exponential.median":"\nbase.dists.exponential.median( λ:number )\n    Returns the median of an exponential distribution.\n","base.dists.exponential.mgf":"\nbase.dists.exponential.mgf( t:number, λ:number )\n    Evaluates the moment-generating function (MGF) for an exponential\n    distribution with rate parameter `λ` at a value `t`.\n","base.dists.exponential.mgf.factory":"\nbase.dists.exponential.mgf.factory( λ:number )\n    Returns a function for evaluating the moment-generating function (MGF) for\n    an exponential distribution with rate parameter `λ`.\n","base.dists.exponential.mode":"\nbase.dists.exponential.mode( λ:number )\n    Returns the mode of an exponential distribution.\n","base.dists.exponential.pdf":"\nbase.dists.exponential.pdf( x:number, λ:number )\n    Evaluates the probability density function (PDF) for an exponential\n    distribution with rate parameter `λ` at a value `x`.\n","base.dists.exponential.pdf.factory":"\nbase.dists.exponential.pdf.factory( λ:number )\n    Returns a function for evaluating the probability density function (PDF)\n    for an exponential distribution with rate parameter `λ`.\n","base.dists.exponential.quantile":"\nbase.dists.exponential.quantile( p:number, λ:number )\n    Evaluates the quantile function for an exponential distribution with rate\n    parameter `λ` at a probability `p`.\n","base.dists.exponential.quantile.factory":"\nbase.dists.exponential.quantile.factory( λ:number )\n    Returns a function for evaluating the quantile function for an exponential\n    distribution with rate parameter `λ`.\n","base.dists.exponential.skewness":"\nbase.dists.exponential.skewness( λ:number )\n    Returns the skewness of an exponential distribution.\n","base.dists.exponential.stdev":"\nbase.dists.exponential.stdev( λ:number )\n    Returns the standard deviation of an exponential distribution.\n","base.dists.exponential.variance":"\nbase.dists.exponential.variance( λ:number )\n    Returns the variance of an exponential distribution.\n","base.dists.f.cdf":"\nbase.dists.f.cdf( x:number, d1:number, d2:number )\n    Evaluates the cumulative distribution function (CDF) for an F distribution\n    with numerator degrees of freedom `d1` and denominator degrees of freedom\n    `d2` at a value `x`.\n","base.dists.f.cdf.factory":"\nbase.dists.f.cdf.factory( d1:number, d2:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an F distribution with numerator degrees of freedom `d1` and denominator\n    degrees of freedom `d2`.\n","base.dists.f.entropy":"\nbase.dists.f.entropy( d1:number, d2:number )\n    Returns the differential entropy of an F distribution (in nats).\n","base.dists.f.F":"\nbase.dists.f.F( [d1:number, d2:number] )\n    Returns an F distribution object.\n","base.dists.f.kurtosis":"\nbase.dists.f.kurtosis( d1:number, d2:number )\n    Returns the excess kurtosis of an F distribution.\n","base.dists.f.mean":"\nbase.dists.f.mean( d1:number, d2:number )\n    Returns the expected value of an F distribution.\n","base.dists.f.mode":"\nbase.dists.f.mode( d1:number, d2:number )\n    Returns the mode of an F distribution.\n","base.dists.f.pdf":"\nbase.dists.f.pdf( x:number, d1:number, d2:number )\n    Evaluates the probability density function (PDF) for an F distribution with\n    numerator degrees of freedom `d1` and denominator degrees of freedom `d2` at\n    a value `x`.\n","base.dists.f.pdf.factory":"\nbase.dists.f.pdf.factory( d1:number, d2:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    an F distribution with numerator degrees of freedom `d1` and denominator\n    degrees of freedom `d2`.\n","base.dists.f.quantile":"\nbase.dists.f.quantile( p:number, d1:number, d2:number )\n    Evaluates the quantile function for an F distribution with numerator degrees\n    of freedom `d1` and denominator degrees of freedom `d2` at a probability\n    `p`.\n","base.dists.f.quantile.factory":"\nbase.dists.f.quantile.factory( d1:number, d2:number )\n    Returns a function for evaluating the quantile function of an F distribution\n    with numerator degrees of freedom `d1` and denominator degrees of freedom\n    `d2`.\n","base.dists.f.skewness":"\nbase.dists.f.skewness( d1:number, d2:number )\n    Returns the skewness of an F distribution.\n","base.dists.f.stdev":"\nbase.dists.f.stdev( d1:number, d2:number )\n    Returns the standard deviation of an F distribution.\n","base.dists.f.variance":"\nbase.dists.f.variance( d1:number, d2:number )\n    Returns the variance of an F distribution.\n","base.dists.frechet.cdf":"\nbase.dists.frechet.cdf( x:number, α:number, s:number, m:number )\n    Evaluates the cumulative distribution function (CDF) for a Fréchet\n    distribution with shape parameter `α`, scale parameter `s`, and location\n    `m`.\n","base.dists.frechet.cdf.factory":"\nbase.dists.frechet.cdf.factory( α:number, s:number, m:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n    location `m`.\n","base.dists.frechet.entropy":"\nbase.dists.frechet.entropy( α:number, s:number, m:number )\n    Returns the differential entropy of a Fréchet distribution with shape\n    parameter `α`, scale parameter `s`, and location `m` (in nats).\n","base.dists.frechet.Frechet":"\nbase.dists.frechet.Frechet( [α:number, s:number, m:number] )\n    Returns a Fréchet distribution object.\n","base.dists.frechet.kurtosis":"\nbase.dists.frechet.kurtosis( α:number, s:number, m:number )\n    Returns the excess kurtosis of a Fréchet distribution with shape parameter\n    `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.logcdf":"\nbase.dists.frechet.logcdf( x:number, α:number, s:number, m:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a Fréchet distribution with shape parameter `α`, scale parameter\n    `s`, and location `m`.\n","base.dists.frechet.logcdf.factory":"\nbase.dists.frechet.logcdf.factory( α:number, s:number, m:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Fréchet distribution with shape parameter\n    `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.logpdf":"\nbase.dists.frechet.logpdf( x:number, α:number, s:number, m:number )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n    location `m`.\n","base.dists.frechet.logpdf.factory":"\nbase.dists.frechet.logpdf.factory( α:number, s:number, m:number )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Fréchet distribution with shape parameter `α`, scale\n    parameter `s`, and location `m`.\n","base.dists.frechet.mean":"\nbase.dists.frechet.mean( α:number, s:number, m:number )\n    Returns the expected value of a Fréchet distribution with shape parameter\n    `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.median":"\nbase.dists.frechet.median( α:number, s:number, m:number )\n    Returns the median of a Fréchet distribution with shape parameter\n    `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.mode":"\nbase.dists.frechet.mode( α:number, s:number, m:number )\n    Returns the mode of a Fréchet distribution with shape parameter `α`, scale\n    parameter `s`, and location `m`.\n","base.dists.frechet.pdf":"\nbase.dists.frechet.pdf( x:number, α:number, s:number, m:number )\n    Evaluates the probability density function (PDF) for a Fréchet distribution\n    with shape parameter `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.pdf.factory":"\nbase.dists.frechet.pdf.factory( α:number, s:number, m:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n    location `m`.\n","base.dists.frechet.quantile":"\nbase.dists.frechet.quantile( p:number, α:number, s:number, m:number )\n    Evaluates the quantile function for a Fréchet distribution with shape\n    parameter `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.quantile.factory":"\nbase.dists.frechet.quantile.factory( α:number, s:number, m:number )\n    Returns a function for evaluating the quantile function of a Fréchet\n    distribution with shape parameter `α`, scale parameter `s`, and location\n    `m`.\n","base.dists.frechet.skewness":"\nbase.dists.frechet.skewness( α:number, s:number, m:number )\n    Returns the skewness of a Fréchet distribution with shape parameter `α`,\n    scale parameter `s`, and location `m`.\n","base.dists.frechet.stdev":"\nbase.dists.frechet.stdev( α:number, s:number, m:number )\n    Returns the standard deviation of a Fréchet distribution with shape\n    parameter `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.variance":"\nbase.dists.frechet.variance( α:number, s:number, m:number )\n    Returns the variance of a Fréchet distribution with shape parameter `α`,\n    scale parameter `s`, and location `m`.\n","base.dists.gamma.cdf":"\nbase.dists.gamma.cdf( x:number, α:number, β:number )\n    Evaluates the cumulative distribution function (CDF) for a gamma\n    distribution with shape parameter `α` and rate parameter `β` at a value `x`.\n","base.dists.gamma.cdf.factory":"\nbase.dists.gamma.cdf.factory( α:number, β:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a gamma distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.entropy":"\nbase.dists.gamma.entropy( α:number, β:number )\n    Returns the differential entropy of a gamma distribution.\n","base.dists.gamma.Gamma":"\nbase.dists.gamma.Gamma( [α:number, β:number] )\n    Returns a gamma distribution object.\n","base.dists.gamma.kurtosis":"\nbase.dists.gamma.kurtosis( α:number, β:number )\n    Returns the excess kurtosis of a gamma distribution.\n","base.dists.gamma.logcdf":"\nbase.dists.gamma.logcdf( x:number, α:number, β:number )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    gamma distribution with shape parameter `α` and rate parameter `β` at a\n    value `x`.\n","base.dists.gamma.logcdf.factory":"\nbase.dists.gamma.logcdf.factory( α:number, β:number )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a gamma distribution with shape parameter `α`\n    and rate parameter `β`.\n","base.dists.gamma.logpdf":"\nbase.dists.gamma.logpdf( x:number, α:number, β:number )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    gamma distribution with shape parameter `α` and rate parameter `β` at a\n    value `x`.\n","base.dists.gamma.logpdf.factory":"\nbase.dists.gamma.logpdf.factory( α:number, β:number )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a gamma distribution with shape parameter `α` and rate\n    parameter `β`.\n","base.dists.gamma.mean":"\nbase.dists.gamma.mean( α:number, β:number )\n    Returns the expected value of a gamma distribution.\n","base.dists.gamma.mgf":"\nbase.dists.gamma.mgf( t:number, α:number, β:number )\n    Evaluates the moment-generating function (MGF) for a gamma distribution with\n    shape parameter `α` and rate parameter `β` at a value `t`.\n","base.dists.gamma.mgf.factory":"\nbase.dists.gamma.mgf.factory( α:number, β:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    gamma distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.mode":"\nbase.dists.gamma.mode( α:number, β:number )\n    Returns the mode of a gamma distribution.\n","base.dists.gamma.pdf":"\nbase.dists.gamma.pdf( x:number, α:number, β:number )\n    Evaluates the probability density function (PDF) for a gamma distribution\n    with shape parameter `α` and rate parameter `β` at a value `x`.\n","base.dists.gamma.pdf.factory":"\nbase.dists.gamma.pdf.factory( α:number, β:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a gamma distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.quantile":"\nbase.dists.gamma.quantile( p:number, α:number, β:number )\n    Evaluates the quantile function for a gamma distribution with shape\n    parameter `α` and rate parameter `β` at a probability `p`.\n","base.dists.gamma.quantile.factory":"\nbase.dists.gamma.quantile.factory( α:number, β:number )\n    Returns a function for evaluating the quantile function of a gamma\n    distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.skewness":"\nbase.dists.gamma.skewness( α:number, β:number )\n    Returns the skewness of a gamma distribution.\n","base.dists.gamma.stdev":"\nbase.dists.gamma.stdev( α:number, β:number )\n    Returns the standard deviation of a gamma distribution.\n","base.dists.gamma.variance":"\nbase.dists.gamma.variance( α:number, β:number )\n    Returns the variance of a gamma distribution.\n","base.dists.geometric.cdf":"\nbase.dists.geometric.cdf( x:number, p:number )\n    Evaluates the cumulative distribution function (CDF) for a geometric\n    distribution with success probability `p` at a value `x`.\n","base.dists.geometric.cdf.factory":"\nbase.dists.geometric.cdf.factory( p:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a geometric distribution with success probability `p`.\n","base.dists.geometric.entropy":"\nbase.dists.geometric.entropy( p:number )\n    Returns the entropy of a geometric distribution with success probability\n    `p` (in nats).\n","base.dists.geometric.Geometric":"\nbase.dists.geometric.Geometric( [p:number] )\n    Returns a geometric distribution object.\n","base.dists.geometric.kurtosis":"\nbase.dists.geometric.kurtosis( p:number )\n    Returns the excess kurtosis of a geometric distribution with success\n    probability `p`.\n","base.dists.geometric.logcdf":"\nbase.dists.geometric.logcdf( x:number, p:number )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    geometric distribution with success probability `p` at a value `x`.\n","base.dists.geometric.logcdf.factory":"\nbase.dists.geometric.logcdf.factory( p:number )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a geometric distribution with success\n    probability `p`.\n","base.dists.geometric.logpmf":"\nbase.dists.geometric.logpmf( x:number, p:number )\n    Evaluates the logarithm of the probability mass function (PMF) for a\n    geometric distribution with success probability `p` at a value `x`.\n","base.dists.geometric.logpmf.factory":"\nbase.dists.geometric.logpmf.factory( p:number )\n    Returns a function for evaluating the logarithm of the probability mass\n    function (PMF) of a geometric distribution with success probability `p`.\n","base.dists.geometric.mean":"\nbase.dists.geometric.mean( p:number )\n    Returns the expected value of a geometric distribution with success\n    probability `p`.\n","base.dists.geometric.median":"\nbase.dists.geometric.median( p:number )\n    Returns the median of a geometric distribution with success probability `p`.\n","base.dists.geometric.mgf":"\nbase.dists.geometric.mgf( t:number, p:number )\n    Evaluates the moment-generating function (MGF) for a geometric\n    distribution with success probability `p` at a value `t`.\n","base.dists.geometric.mgf.factory":"\nbase.dists.geometric.mgf.factory( p:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    geometric distribution with success probability `p`.\n","base.dists.geometric.mode":"\nbase.dists.geometric.mode( p:number )\n    Returns the mode of a geometric distribution with success probability `p`.\n","base.dists.geometric.pmf":"\nbase.dists.geometric.pmf( x:number, p:number )\n    Evaluates the probability mass function (PMF) for a geometric distribution\n    with success probability `p` at a value `x`.\n","base.dists.geometric.pmf.factory":"\nbase.dists.geometric.pmf.factory( p:number )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    geometric distribution with success probability `p`.\n","base.dists.geometric.quantile":"\nbase.dists.geometric.quantile( r:number, p:number )\n    Evaluates the quantile function for a geometric distribution with success\n    probability `p` at a probability `r`.\n","base.dists.geometric.quantile.factory":"\nbase.dists.geometric.quantile.factory( p:number )\n    Returns a function for evaluating the quantile function of a geometric\n    distribution with success probability `p`.\n","base.dists.geometric.skewness":"\nbase.dists.geometric.skewness( p:number )\n    Returns the skewness of a geometric distribution with success probability\n    `p`.\n","base.dists.geometric.stdev":"\nbase.dists.geometric.stdev( p:number )\n    Returns the standard deviation of a geometric distribution with success\n    probability `p`.\n","base.dists.geometric.variance":"\nbase.dists.geometric.variance( p:number )\n    Returns the variance of a geometric distribution with success probability\n    `p`.\n","base.dists.gumbel.cdf":"\nbase.dists.gumbel.cdf( x:number, μ:number, β:number )\n    Evaluates the cumulative distribution function (CDF) for a Gumbel\n    distribution with location parameter `μ` and scale parameter `β` at a value\n    `x`.\n","base.dists.gumbel.cdf.factory":"\nbase.dists.gumbel.cdf.factory( μ:number, β:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Gumbel distribution with location parameter `μ` and scale parameter\n    `β`.\n","base.dists.gumbel.entropy":"\nbase.dists.gumbel.entropy( μ:number, β:number )\n    Returns the differential entropy of a Gumbel distribution with location\n    parameter `μ` and scale parameter `β` (in nats).\n","base.dists.gumbel.Gumbel":"\nbase.dists.gumbel.Gumbel( [μ:number, β:number] )\n    Returns a Gumbel distribution object.\n","base.dists.gumbel.kurtosis":"\nbase.dists.gumbel.kurtosis( μ:number, β:number )\n    Returns the excess kurtosis of a Gumbel distribution with location parameter\n    `μ` and scale parameter `β`.\n","base.dists.gumbel.logcdf":"\nbase.dists.gumbel.logcdf( x:number, μ:number, β:number )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n    value `x`.\n","base.dists.gumbel.logcdf.factory":"\nbase.dists.gumbel.logcdf.factory( μ:number, β:number )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Gumbel distribution with location parameter\n    `μ` and scale parameter `β`.\n","base.dists.gumbel.logpdf":"\nbase.dists.gumbel.logpdf( x:number, μ:number, β:number )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n    value `x`.\n","base.dists.gumbel.logpdf.factory":"\nbase.dists.gumbel.logpdf.factory( μ:number, β:number )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Gumbel distribution with location parameter `μ` and\n    scale parameter `β`.\n","base.dists.gumbel.mean":"\nbase.dists.gumbel.mean( μ:number, β:number )\n    Returns the expected value of a Gumbel distribution with location parameter\n    `μ` and scale parameter `β`.\n","base.dists.gumbel.median":"\nbase.dists.gumbel.median( μ:number, β:number )\n    Returns the median of a Gumbel distribution with location parameter `μ` and\n    scale parameter `β`.\n","base.dists.gumbel.mgf":"\nbase.dists.gumbel.mgf( t:number, μ:number, β:number )\n    Evaluates the moment-generating function (MGF) for a Gumbel distribution\n    with location parameter `μ` and scale parameter `β` at a value `t`.\n","base.dists.gumbel.mgf.factory":"\nbase.dists.gumbel.mgf.factory( μ:number, β:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Gumbel distribution with location parameter `μ` and scale parameter `β`.\n","base.dists.gumbel.mode":"\nbase.dists.gumbel.mode( μ:number, β:number )\n    Returns the mode of a Gumbel distribution with location parameter `μ` and\n    scale parameter `β`.\n","base.dists.gumbel.pdf":"\nbase.dists.gumbel.pdf( x:number, μ:number, β:number )\n    Evaluates the probability density function (PDF) for a Gumbel distribution\n    with location parameter `μ` and scale parameter `β` at a value `x`.\n","base.dists.gumbel.pdf.factory":"\nbase.dists.gumbel.pdf.factory( μ:number, β:number )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Gumbel distribution with location parameter `μ` and scale parameter\n    `β`.\n","base.dists.gumbel.quantile":"\nbase.dists.gumbel.quantile( p:number, μ:number, β:number )\n    Evaluates the quantile function for a Gumbel distribution with location\n    parameter `μ` and scale parameter `β` at a probability `p`.\n","base.dists.gumbel.quantile.factory":"\nbase.dists.gumbel.quantile.factory( μ:number, β:number )\n    Returns a function for evaluating the quantile function of a Gumbel\n    distribution with location parameter `μ` and scale parameter `β`.\n","base.dists.gumbel.skewness":"\nbase.dists.gumbel.skewness( μ:number, β:number )\n    Returns the skewness of a Gumbel distribution with location parameter `μ`\n    and scale parameter `β`.\n","base.dists.gumbel.stdev":"\nbase.dists.gumbel.stdev( μ:number, β:number )\n    Returns the standard deviation of a Gumbel distribution with location\n    parameter `μ` and scale parameter `β`.\n","base.dists.gumbel.variance":"\nbase.dists.gumbel.variance( μ:number, β:number )\n    Returns the variance of a Gumbel distribution with location parameter `μ`\n    and scale parameter `β`.\n","base.dists.hypergeometric.cdf":"\nbase.dists.hypergeometric.cdf( x:number, N:integer, K:integer, n:integer )\n    Evaluates the cumulative distribution function (CDF) for a hypergeometric\n    distribution with population size `N`, subpopulation size `K`, and number of\n    draws `n` at a value `x`.\n","base.dists.hypergeometric.cdf.factory":"\nbase.dists.hypergeometric.cdf.factory( N:integer, K:integer, n:integer )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a hypergeometric distribution with population size `N`, subpopulation\n    size `K`, and number of draws `n`.\n","base.dists.hypergeometric.Hypergeometric":"\nbase.dists.hypergeometric.Hypergeometric( [N:integer, K:integer, n:integer] )\n    Returns a hypergeometric distribution object.\n","base.dists.hypergeometric.kurtosis":"\nbase.dists.hypergeometric.kurtosis( N:integer, K:integer, n:integer )\n    Returns the excess kurtosis of a hypergeometric distribution.\n","base.dists.hypergeometric.logpmf":"\nbase.dists.hypergeometric.logpmf( x:number, N:integer, K:integer, n:integer )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    hypergeometric distribution with population size `N`, subpopulation size\n    `K`, and number of draws `n` at a value `x`.\n","base.dists.hypergeometric.logpmf.factory":"\nbase.dists.hypergeometric.logpmf.factory( N:integer, K:integer, n:integer )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a hypergeometric distribution with population size\n    `N`, subpopulation size `K`, and number of draws `n`.\n","base.dists.hypergeometric.mean":"\nbase.dists.hypergeometric.mean( N:integer, K:integer, n:integer )\n    Returns the expected value of a hypergeometric distribution.\n","base.dists.hypergeometric.mode":"\nbase.dists.hypergeometric.mode( N:integer, K:integer, n:integer )\n    Returns the mode of a hypergeometric distribution.\n","base.dists.hypergeometric.pmf":"\nbase.dists.hypergeometric.pmf( x:number, N:integer, K:integer, n:integer )\n    Evaluates the probability mass function (PMF) for a hypergeometric\n    distribution with population size `N`, subpopulation size `K`, and number of\n    draws `n` at a value `x`.\n","base.dists.hypergeometric.pmf.factory":"\nbase.dists.hypergeometric.pmf.factory( N:integer, K:integer, n:integer )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    hypergeometric distribution with population size `N`, subpopulation size\n    `K`, and number of draws `n`.\n","base.dists.hypergeometric.quantile":"\nbase.dists.hypergeometric.quantile( p:number, N:integer, K:integer, n:integer )\n    Evaluates the quantile function for a hypergeometric distribution with\n    population size `N`, subpopulation size `K`, and number of draws `n` at a\n    probability `p`.\n","base.dists.hypergeometric.quantile.factory":"\nbase.dists.hypergeometric.quantile.factory( N:integer, K:integer, n:integer )\n    Returns a function for evaluating the quantile function of a hypergeometric\n    distribution with population size `N`, subpopulation size `K`, and number of\n    draws `n`.\n","base.dists.hypergeometric.skewness":"\nbase.dists.hypergeometric.skewness( N:integer, K:integer, n:integer )\n    Returns the skewness of a hypergeometric distribution.\n","base.dists.hypergeometric.stdev":"\nbase.dists.hypergeometric.stdev( N:integer, K:integer, n:integer )\n    Returns the standard deviation of a hypergeometric distribution.\n","base.dists.hypergeometric.variance":"\nbase.dists.hypergeometric.variance( N:integer, K:integer, n:integer )\n    Returns the variance of a hypergeometric distribution.\n","base.dists.invgamma.cdf":"\nbase.dists.invgamma.cdf( x:number, α:number, β:number )\n    Evaluates the cumulative distribution function (CDF) for an inverse gamma\n    distribution with shape parameter `α` and scale parameter `β` at a value\n    `x`.\n","base.dists.invgamma.cdf.factory":"\nbase.dists.invgamma.cdf.factory( α:number, β:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an inverse gamma distribution with shape parameter `α` and scale\n    parameter `β`.\n","base.dists.invgamma.entropy":"\nbase.dists.invgamma.entropy( α:number, β:number )\n    Returns the differential entropy of an inverse gamma distribution.\n","base.dists.invgamma.InvGamma":"\nbase.dists.invgamma.InvGamma( [α:number, β:number] )\n    Returns an inverse gamma distribution object.\n","base.dists.invgamma.kurtosis":"\nbase.dists.invgamma.kurtosis( α:number, β:number )\n    Returns the excess kurtosis of an inverse gamma distribution.\n","base.dists.invgamma.logpdf":"\nbase.dists.invgamma.logpdf( x:number, α:number, β:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for an inverse gamma distribution with shape parameter `α` and scale\n    parameter `β` at a value `x`.\n","base.dists.invgamma.logpdf.factory":"\nbase.dists.invgamma.logpdf.factory( α:number, β:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) for an inverse gamma distribution with shape\n    parameter `α` and scale parameter `β`.\n","base.dists.invgamma.mean":"\nbase.dists.invgamma.mean( α:number, β:number )\n    Returns the expected value of an inverse gamma distribution.\n","base.dists.invgamma.mode":"\nbase.dists.invgamma.mode( α:number, β:number )\n    Returns the mode of an inverse gamma distribution.\n","base.dists.invgamma.pdf":"\nbase.dists.invgamma.pdf( x:number, α:number, β:number )\n    Evaluates the probability density function (PDF) for an inverse gamma\n    distribution with shape parameter `α` and scale parameter `β` at a value\n    `x`.\n","base.dists.invgamma.pdf.factory":"\nbase.dists.invgamma.pdf.factory( α:number, β:number )\n    Returns a function for evaluating the probability density function (PDF)\n    of an inverse gamma distribution with shape parameter `α` and scale\n    parameter `β`.\n","base.dists.invgamma.quantile":"\nbase.dists.invgamma.quantile( p:number, α:number, β:number )\n    Evaluates the quantile function for an inverse gamma distribution with shape\n    parameter `α` and scale parameter `β` at a probability `p`.\n","base.dists.invgamma.quantile.factory":"\nbase.dists.invgamma.quantile.factory( α:number, β:number )\n    Returns a function for evaluating the quantile function of an inverse gamma\n    distribution with shape parameter `α` and scale parameter `β`.\n","base.dists.invgamma.skewness":"\nbase.dists.invgamma.skewness( α:number, β:number )\n    Returns the skewness of an inverse gamma distribution.\n","base.dists.invgamma.stdev":"\nbase.dists.invgamma.stdev( α:number, β:number )\n    Returns the standard deviation of an inverse gamma distribution.\n","base.dists.invgamma.variance":"\nbase.dists.invgamma.variance( α:number, β:number )\n    Returns the variance of an inverse gamma distribution.\n","base.dists.kumaraswamy.cdf":"\nbase.dists.kumaraswamy.cdf( x:number, a:number, b:number )\n    Evaluates the cumulative distribution function (CDF) for Kumaraswamy's\n    double bounded distribution with first shape parameter `a` and second shape\n    parameter `b` at a value `x`.\n","base.dists.kumaraswamy.cdf.factory":"\nbase.dists.kumaraswamy.cdf.factory( a:number, b:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Kumaraswamy's double bounded distribution with first shape parameter\n    `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.Kumaraswamy":"\nbase.dists.kumaraswamy.Kumaraswamy( [a:number, b:number] )\n    Returns a Kumaraswamy's double bounded distribution object.\n","base.dists.kumaraswamy.kurtosis":"\nbase.dists.kumaraswamy.kurtosis( a:number, b:number )\n    Returns the excess kurtosis of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.logcdf":"\nbase.dists.kumaraswamy.logcdf( x:number, a:number, b:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for Kumaraswamy's double bounded distribution with first shape\n    parameter `a` and second shape parameter `b` at a value `x`.\n","base.dists.kumaraswamy.logcdf.factory":"\nbase.dists.kumaraswamy.logcdf.factory( a:number, b:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Kumaraswamy's double bounded distribution\n    with first shape parameter `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.logpdf":"\nbase.dists.kumaraswamy.logpdf( x:number, a:number, b:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for Kumaraswamy's double bounded distribution with first shape parameter `a`\n    and second shape parameter `b` at a value `x`.\n","base.dists.kumaraswamy.logpdf.factory":"\nbase.dists.kumaraswamy.logpdf.factory( a:number, b:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a Kumaraswamy's double bounded distribution with\n    first shape parameter `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.mean":"\nbase.dists.kumaraswamy.mean( a:number, b:number )\n    Returns the mean of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.median":"\nbase.dists.kumaraswamy.median( a:number, b:number )\n    Returns the median of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.mode":"\nbase.dists.kumaraswamy.mode( a:number, b:number )\n    Returns the mode of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.pdf":"\nbase.dists.kumaraswamy.pdf( x:number, a:number, b:number )\n    Evaluates the probability density function (PDF) for Kumaraswamy's double\n    bounded distribution with first shape parameter `a` and second shape\n    parameter `b` at a value `x`.\n","base.dists.kumaraswamy.pdf.factory":"\nbase.dists.kumaraswamy.pdf.factory( a:number, b:number )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Kumaraswamy's double bounded distribution with first shape parameter\n    `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.quantile":"\nbase.dists.kumaraswamy.quantile( p:number, a:number, b:number )\n    Evaluates the quantile function for a Kumaraswamy's double bounded\n    distribution with first shape parameter `a` and second shape parameter `b`\n    at a probability `p`.\n","base.dists.kumaraswamy.quantile.factory":"\nbase.dists.kumaraswamy.quantile.factory( a:number, b:number )\n    Returns a function for evaluating the quantile function of a Kumaraswamy's\n    double bounded distribution with first shape parameter `a` and second shape\n    parameter `b`.\n","base.dists.kumaraswamy.skewness":"\nbase.dists.kumaraswamy.skewness( a:number, b:number )\n    Returns the skewness of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.stdev":"\nbase.dists.kumaraswamy.stdev( a:number, b:number )\n    Returns the standard deviation of a Kumaraswamy's double bounded\n    distribution.\n","base.dists.kumaraswamy.variance":"\nbase.dists.kumaraswamy.variance( a:number, b:number )\n    Returns the variance of a Kumaraswamy's double bounded distribution.\n","base.dists.laplace.cdf":"\nbase.dists.laplace.cdf( x:number, μ:number, b:number )\n    Evaluates the cumulative distribution function (CDF) for a Laplace\n    distribution with scale parameter `b` and location parameter `μ` at a\n    value `x`.\n","base.dists.laplace.cdf.factory":"\nbase.dists.laplace.cdf.factory( μ:number, b:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Laplace distribution with scale parameter `b` and location parameter\n    `μ`.\n","base.dists.laplace.entropy":"\nbase.dists.laplace.entropy( μ:number, b:number )\n    Returns the differential entropy of a Laplace distribution with location\n    parameter `μ` and scale parameter `b`.\n","base.dists.laplace.kurtosis":"\nbase.dists.laplace.kurtosis( μ:number, b:number )\n    Returns the excess kurtosis of a Laplace distribution with location\n    parameter `μ` and scale parameter `b`.\n","base.dists.laplace.Laplace":"\nbase.dists.laplace.Laplace( [μ:number, b:number] )\n    Returns a Laplace distribution object.\n","base.dists.laplace.logcdf":"\nbase.dists.laplace.logcdf( x:number, μ:number, b:number )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    Laplace distribution with scale parameter `b` and location parameter `μ` at\n    a value `x`.\n","base.dists.laplace.logcdf.factory":"\nbase.dists.laplace.logcdf.factory( μ:number, b:number )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Laplace distribution with scale parameter\n    `b` and location parameter `μ`.\n","base.dists.laplace.logpdf":"\nbase.dists.laplace.logpdf( x:number, μ:number, b:number )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    Laplace distribution with scale parameter `b` and location parameter `μ` at\n    a value `x`.\n","base.dists.laplace.logpdf.factory":"\nbase.dists.laplace.logpdf.factory( μ:number, b:number )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Laplace distribution with scale parameter `b` and\n    location parameter `μ`.\n","base.dists.laplace.mean":"\nbase.dists.laplace.mean( μ:number, b:number )\n    Returns the expected value of a Laplace distribution with location parameter\n    `μ` and scale parameter `b`.\n","base.dists.laplace.median":"\nbase.dists.laplace.median( μ:number, b:number )\n    Returns the median of a Laplace distribution with location parameter `μ` and\n    scale parameter `b`.\n","base.dists.laplace.mgf":"\nbase.dists.laplace.mgf( t:number, μ:number, b:number )\n    Evaluates the moment-generating function (MGF) for a Laplace\n    distribution with scale parameter `b` and location parameter `μ` at a\n    value `t`.\n","base.dists.laplace.mgf.factory":"\nbase.dists.laplace.mgf.factory( μ:number, b:number )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a Laplace distribution with scale parameter `b` and location parameter\n    `μ`.\n","base.dists.laplace.mode":"\nbase.dists.laplace.mode( μ:number, b:number )\n    Returns the mode of a Laplace distribution with location parameter `μ` and\n    scale parameter `b`.\n","base.dists.laplace.pdf":"\nbase.dists.laplace.pdf( x:number, μ:number, b:number )\n    Evaluates the probability density function (PDF) for a Laplace\n    distribution with scale parameter `b` and location parameter `μ` at a\n    value `x`.\n","base.dists.laplace.pdf.factory":"\nbase.dists.laplace.pdf.factory( μ:number, b:number )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Laplace distribution with scale parameter `b` and location parameter\n    `μ`.\n","base.dists.laplace.quantile":"\nbase.dists.laplace.quantile( p:number, μ:number, b:number )\n    Evaluates the quantile function for a Laplace distribution with scale\n    parameter `b` and location parameter `μ` at a probability `p`.\n","base.dists.laplace.quantile.factory":"\nbase.dists.laplace.quantile.factory( μ:number, b:number )\n    Returns a function for evaluating the quantile function of a Laplace\n    distribution with scale parameter `b` and location parameter `μ`.\n","base.dists.laplace.skewness":"\nbase.dists.laplace.skewness( μ:number, b:number )\n    Returns the skewness of a Laplace distribution with location parameter `μ`\n    and scale parameter `b`.\n","base.dists.laplace.stdev":"\nbase.dists.laplace.stdev( μ:number, b:number )\n    Returns the standard deviation of a Laplace distribution with location\n    parameter `μ` and scale parameter `b`.\n","base.dists.laplace.variance":"\nbase.dists.laplace.variance( μ:number, b:number )\n    Returns the variance of a Laplace distribution with location parameter `μ`\n    and scale parameter `b`.\n","base.dists.levy.cdf":"\nbase.dists.levy.cdf( x:number, μ:number, c:number )\n    Evaluates the cumulative distribution function (CDF) for a Lévy distribution\n    with location parameter `μ` and scale parameter `c` at a value `x`.\n","base.dists.levy.cdf.factory":"\nbase.dists.levy.cdf.factory( μ:number, c:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Lévy distribution with location parameter `μ` and scale parameter `c`.\n","base.dists.levy.entropy":"\nbase.dists.levy.entropy( μ:number, c:number )\n    Returns the entropy of a Lévy distribution with location parameter `μ` and\n    scale parameter `c`.\n","base.dists.levy.Levy":"\nbase.dists.levy.Levy( [μ:number, c:number] )\n    Returns a Lévy distribution object.\n","base.dists.levy.logcdf":"\nbase.dists.levy.logcdf( x:number, μ:number, c:number )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    Lévy distribution with location parameter `μ` and scale parameter `c` at a\n    value `x`.\n","base.dists.levy.logcdf.factory":"\nbase.dists.levy.logcdf.factory( μ:number, c:number )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Lévy distribution with location parameter\n    `μ` and scale parameter `c`.\n","base.dists.levy.logpdf":"\nbase.dists.levy.logpdf( x:number, μ:number, c:number )\n    Evaluates the logarithm of the probability density function (PDF) for a Lévy\n    distribution with location parameter `μ` and scale parameter `c` at a value\n    `x`.\n","base.dists.levy.logpdf.factory":"\nbase.dists.levy.logpdf.factory( μ:number, c:number )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Lévy distribution with location parameter `μ` and scale\n    parameter `c`.\n","base.dists.levy.mean":"\nbase.dists.levy.mean( μ:number, c:number )\n    Returns the expected value of a Lévy distribution with location parameter\n    `μ` and scale parameter `c`.\n","base.dists.levy.median":"\nbase.dists.levy.median( μ:number, c:number )\n    Returns the median of a Lévy distribution with location parameter `μ` and\n    scale parameter `c`.\n","base.dists.levy.mode":"\nbase.dists.levy.mode( μ:number, c:number )\n    Returns the mode of a Lévy distribution with location parameter `μ` and\n    scale parameter `c`.\n","base.dists.levy.pdf":"\nbase.dists.levy.pdf( x:number, μ:number, c:number )\n    Evaluates the probability density function (PDF) for a Lévy distribution\n    with location parameter `μ` and scale parameter `c` at a value `x`.\n","base.dists.levy.pdf.factory":"\nbase.dists.levy.pdf.factory( μ:number, c:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Lévy distribution with location parameter `μ` and scale parameter `c`.\n","base.dists.levy.quantile":"\nbase.dists.levy.quantile( p:number, μ:number, c:number )\n    Evaluates the quantile function for a Lévy distribution with location\n    parameter `μ` and scale parameter `c` at a probability `p`.\n","base.dists.levy.quantile.factory":"\nbase.dists.levy.quantile.factory( μ:number, c:number )\n    Returns a function for evaluating the quantile function of a Lévy\n    distribution with location parameter `μ` and scale parameter `c`.\n","base.dists.levy.stdev":"\nbase.dists.levy.stdev( μ:number, c:number )\n    Returns the standard deviation of a Lévy distribution with location\n    parameter `μ` and scale parameter `c`.\n","base.dists.levy.variance":"\nbase.dists.levy.variance( μ:number, c:number )\n    Returns the variance of a Lévy distribution with location parameter `μ` and\n    scale parameter `c`.\n","base.dists.logistic.cdf":"\nbase.dists.logistic.cdf( x:number, μ:number, s:number )\n    Evaluates the cumulative distribution function (CDF) for a logistic\n    distribution with location parameter `μ` and scale parameter `s` at a value\n    `x`.\n","base.dists.logistic.cdf.factory":"\nbase.dists.logistic.cdf.factory( μ:number, s:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a logistic distribution with location parameter `μ` and scale parameter\n    `s`.\n","base.dists.logistic.entropy":"\nbase.dists.logistic.entropy( μ:number, s:number )\n    Returns the entropy of a logistic distribution with location parameter `μ`\n    and scale parameter `s`.\n","base.dists.logistic.kurtosis":"\nbase.dists.logistic.kurtosis( μ:number, s:number )\n    Returns the excess kurtosis of a logistic distribution with location\n    parameter `μ` and scale parameter `s`.\n","base.dists.logistic.logcdf":"\nbase.dists.logistic.logcdf( x:number, μ:number, s:number )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    logistic distribution with location parameter `μ` and scale parameter `s` at\n    a value `x`.\n","base.dists.logistic.logcdf.factory":"\nbase.dists.logistic.logcdf.factory( μ:number, s:number )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Logistic distribution with location\n    parameter `μ` and scale parameter `s`.\n","base.dists.logistic.Logistic":"\nbase.dists.logistic.Logistic( [μ:number, s:number] )\n    Returns a logistic distribution object.\n","base.dists.logistic.logpdf":"\nbase.dists.logistic.logpdf( x:number, μ:number, s:number )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    logistic distribution with location parameter `μ` and scale parameter `s` at\n    a value `x`.\n","base.dists.logistic.logpdf.factory":"\nbase.dists.logistic.logpdf.factory( μ:number, s:number )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Logistic distribution with location parameter `μ` and\n    scale parameter `s`.\n","base.dists.logistic.mean":"\nbase.dists.logistic.mean( μ:number, s:number )\n    Returns the expected value of a logistic distribution with location\n    parameter `μ` and scale parameter `s`.\n","base.dists.logistic.median":"\nbase.dists.logistic.median( μ:number, s:number )\n    Returns the median of a logistic distribution with location parameter `μ`\n    and scale parameter `s`.\n","base.dists.logistic.mgf":"\nbase.dists.logistic.mgf( t:number, μ:number, s:number )\n    Evaluates the moment-generating function (MGF) for a logistic distribution\n    with location parameter `μ` and scale parameter `s` at a value `t`.\n","base.dists.logistic.mgf.factory":"\nbase.dists.logistic.mgf.factory( μ:number, s:number )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a Logistic distribution with location parameter `μ` and scale parameter\n    `s`.\n","base.dists.logistic.mode":"\nbase.dists.logistic.mode( μ:number, s:number )\n    Returns the mode of a logistic distribution with location parameter `μ` and\n    scale parameter `s`.\n","base.dists.logistic.pdf":"\nbase.dists.logistic.pdf( x:number, μ:number, s:number )\n    Evaluates the probability density function (PDF) for a logistic distribution\n    with location parameter `μ` and scale parameter `s` at a value `x`.\n","base.dists.logistic.pdf.factory":"\nbase.dists.logistic.pdf.factory( μ:number, s:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Logistic distribution with location parameter `μ` and scale parameter `s`.\n","base.dists.logistic.quantile":"\nbase.dists.logistic.quantile( p:number, μ:number, s:number )\n    Evaluates the quantile function for a logistic distribution with location\n    parameter `μ` and scale parameter `s` at a probability `p`.\n","base.dists.logistic.quantile.factory":"\nbase.dists.logistic.quantile.factory( μ:number, s:number )\n    Returns a function for evaluating the quantile function of a logistic\n    distribution with location parameter `μ` and scale parameter `s`.\n","base.dists.logistic.skewness":"\nbase.dists.logistic.skewness( μ:number, s:number )\n    Returns the skewness of a logistic distribution with location parameter `μ`\n    and scale parameter `s`.\n","base.dists.logistic.stdev":"\nbase.dists.logistic.stdev( μ:number, s:number )\n    Returns the standard deviation of a logistic distribution with location\n    parameter `μ` and scale parameter `s`.\n","base.dists.logistic.variance":"\nbase.dists.logistic.variance( μ:number, s:number )\n    Returns the variance of a logistic distribution with location parameter `μ`\n    and scale parameter `s`.\n","base.dists.lognormal.cdf":"\nbase.dists.lognormal.cdf( x:number, μ:number, σ:number )\n    Evaluates the cumulative distribution function (CDF) for a lognormal\n    distribution with location parameter `μ` and scale parameter `σ` at a value\n    `x`.\n","base.dists.lognormal.cdf.factory":"\nbase.dists.lognormal.cdf.factory( μ:number, σ:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a lognormal distribution with location parameter `μ` and scale parameter\n    `σ`.\n","base.dists.lognormal.entropy":"\nbase.dists.lognormal.entropy( μ:number, σ:number )\n    Returns the differential entropy of a lognormal distribution with location\n    `μ` and scale `σ` (in nats).\n","base.dists.lognormal.kurtosis":"\nbase.dists.lognormal.kurtosis( μ:number, σ:number )\n    Returns the excess kurtosis of a lognormal distribution with location `μ`\n    and scale `σ`.\n","base.dists.lognormal.LogNormal":"\nbase.dists.lognormal.LogNormal( [μ:number, σ:number] )\n    Returns a lognormal distribution object.\n","base.dists.lognormal.logcdf":"\nbase.dists.lognormal.logcdf( x:number, μ:number, σ:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a lognormal distribution with mean `μ` and standard deviation `σ`\n    at a value `x`.\n","base.dists.lognormal.logcdf.factory":"\nbase.dists.lognormal.logcdf.factory( μ:number, σ:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a lognormal distribution with mean `μ` and\n    standard deviation `σ`.\n","base.dists.lognormal.logpdf":"\nbase.dists.lognormal.logpdf( x:number, μ:number, σ:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a lognormal distribution with location parameter `μ` and scale parameter\n    `σ` at a value `x`.\n","base.dists.lognormal.logpdf.factory":"\nbase.dists.lognormal.logpdf.factory( μ:number, σ:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a lognormal distribution with location parameter\n    `μ` and scale parameter `σ`.\n","base.dists.lognormal.mean":"\nbase.dists.lognormal.mean( μ:number, σ:number )\n    Returns the expected value of a lognormal distribution with location `μ` and\n    scale `σ`.\n","base.dists.lognormal.median":"\nbase.dists.lognormal.median( μ:number, σ:number )\n    Returns the median of a lognormal distribution with location `μ` and scale\n    `σ`.\n","base.dists.lognormal.mode":"\nbase.dists.lognormal.mode( μ:number, σ:number )\n    Returns the mode of a lognormal distribution with location `μ` and scale\n    `σ`.\n","base.dists.lognormal.pdf":"\nbase.dists.lognormal.pdf( x:number, μ:number, σ:number )\n    Evaluates the probability density function (PDF) for a lognormal\n    distribution with location parameter `μ` and scale parameter `σ` at a value\n    `x`.\n","base.dists.lognormal.pdf.factory":"\nbase.dists.lognormal.pdf.factory( μ:number, σ:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a lognormal distribution with location parameter `μ` and scale parameter\n    `σ`.\n","base.dists.lognormal.quantile":"\nbase.dists.lognormal.quantile( p:number, μ:number, σ:number )\n    Evaluates the quantile function for a lognormal distribution with location\n    parameter `μ` and scale parameter `σ` at a probability `p`.\n","base.dists.lognormal.quantile.factory":"\nbase.dists.lognormal.quantile.factory( μ:number, σ:number )\n    Returns a function for evaluating the quantile function of a lognormal\n    distribution with location parameter `μ` and scale parameter `σ`.\n","base.dists.lognormal.skewness":"\nbase.dists.lognormal.skewness( μ:number, σ:number )\n    Returns the skewness of a lognormal distribution with location `μ` and scale\n    `σ`.\n","base.dists.lognormal.stdev":"\nbase.dists.lognormal.stdev( μ:number, σ:number )\n    Returns the standard deviation of a lognormal distribution with location `μ`\n    and scale `σ`.\n","base.dists.lognormal.variance":"\nbase.dists.lognormal.variance( μ:number, σ:number )\n    Returns the variance of a lognormal distribution with location `μ` and scale\n    `σ`.\n","base.dists.negativeBinomial.cdf":"\nbase.dists.negativeBinomial.cdf( x:number, r:number, p:number )\n    Evaluates the cumulative distribution function (CDF) for a negative binomial\n    distribution with number of successes until experiment is stopped `r` and\n    success probability `p` at a value `x`.\n","base.dists.negativeBinomial.cdf.factory":"\nbase.dists.negativeBinomial.cdf.factory( r:number, p:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a negative binomial distribution with number of successes until\n    experiment is stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.kurtosis":"\nbase.dists.negativeBinomial.kurtosis( r:integer, p:number )\n    Returns the excess kurtosis of a negative binomial distribution.\n","base.dists.negativeBinomial.logpmf":"\nbase.dists.negativeBinomial.logpmf( x:number, r:number, p:number )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    negative binomial distribution with number of successes until experiment is\n    stopped `r` and success probability `p` at a value `x`.\n","base.dists.negativeBinomial.logpmf.factory":"\nbase.dists.negativeBinomial.logpmf.factory( r:number, p:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a negative binomial distribution with number of\n    successes until experiment is stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.mean":"\nbase.dists.negativeBinomial.mean( r:integer, p:number )\n    Returns the expected value of a negative binomial distribution.\n","base.dists.negativeBinomial.mgf":"\nbase.dists.negativeBinomial.mgf( x:number, r:number, p:number )\n    Evaluates the moment-generating function (MGF) for a negative binomial\n    distribution with number of successes until experiment is stopped `r` and\n    success probability `p` at a value `t`.\n","base.dists.negativeBinomial.mgf.factory":"\nbase.dists.negativeBinomial.mgf.factory( r:number, p:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    negative binomial distribution with number of successes until experiment is\n    stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.mode":"\nbase.dists.negativeBinomial.mode( r:integer, p:number )\n    Returns the mode of a negative binomial distribution.\n","base.dists.negativeBinomial.NegativeBinomial":"\nbase.dists.negativeBinomial.NegativeBinomial( [r:number, p:number] )\n    Returns a negative binomial distribution object.\n","base.dists.negativeBinomial.pmf":"\nbase.dists.negativeBinomial.pmf( x:number, r:number, p:number )\n    Evaluates the probability mass function (PMF) for a negative binomial\n    distribution with number of successes until experiment is stopped `r` and\n    success probability `p` at a value `x`.\n","base.dists.negativeBinomial.pmf.factory":"\nbase.dists.negativeBinomial.pmf.factory( r:number, p:number )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    negative binomial distribution with number of successes until experiment is\n    stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.quantile":"\nbase.dists.negativeBinomial.quantile( k:number, r:number, p:number )\n    Evaluates the quantile function for a negative binomial distribution with\n    number of successes until experiment is stopped `r` and success probability\n    `p` at a probability `k`.\n","base.dists.negativeBinomial.quantile.factory":"\nbase.dists.negativeBinomial.quantile.factory( r:number, p:number )\n    Returns a function for evaluating the quantile function of a negative\n    binomial distribution with number of successes until experiment is stopped\n    `r` and success probability `p`.\n","base.dists.negativeBinomial.skewness":"\nbase.dists.negativeBinomial.skewness( r:integer, p:number )\n    Returns the skewness of a negative binomial distribution.\n","base.dists.negativeBinomial.stdev":"\nbase.dists.negativeBinomial.stdev( r:integer, p:number )\n    Returns the standard deviation of a negative binomial distribution.\n","base.dists.negativeBinomial.variance":"\nbase.dists.negativeBinomial.variance( r:integer, p:number )\n    Returns the variance of a negative binomial distribution.\n","base.dists.normal.cdf":"\nbase.dists.normal.cdf( x:number, μ:number, σ:number )\n    Evaluates the cumulative distribution function (CDF) for a normal\n    distribution with mean `μ` and standard deviation `σ` at a value `x`.\n","base.dists.normal.cdf.factory":"\nbase.dists.normal.cdf.factory( μ:number, σ:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.entropy":"\nbase.dists.normal.entropy( μ:number, σ:number )\n    Returns the differential entropy of a normal distribution with mean `μ` and\n    standard deviation `σ`.\n","base.dists.normal.kurtosis":"\nbase.dists.normal.kurtosis( μ:number, σ:number )\n    Returns the excess kurtosis of a normal distribution with mean `μ` and\n    standard deviation `σ`.\n","base.dists.normal.logcdf":"\nbase.dists.normal.logcdf( x:number, μ:number, σ:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a normal distribution with mean `μ` and standard deviation `σ` at\n    a value `x`.\n","base.dists.normal.logcdf.factory":"\nbase.dists.normal.logcdf.factory( μ:number, σ:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a normal distribution with mean `μ` and\n    standard deviation `σ`.\n","base.dists.normal.logpdf":"\nbase.dists.normal.logpdf( x:number, μ:number, σ:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a normal distribution with mean `μ` and standard deviation `σ` at a\n    value `x`.\n","base.dists.normal.logpdf.factory":"\nbase.dists.normal.logpdf.factory( μ:number, σ:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a normal distribution with mean `μ` and standard\n    deviation `σ`.\n","base.dists.normal.mean":"\nbase.dists.normal.mean( μ:number, σ:number )\n    Returns the expected value of a normal distribution with mean `μ` and\n    standard deviation `σ`.\n","base.dists.normal.median":"\nbase.dists.normal.median( μ:number, σ:number )\n    Returns the median of a normal distribution with mean `μ` and standard\n    deviation `σ`.\n","base.dists.normal.mgf":"\nbase.dists.normal.mgf( x:number, μ:number, σ:number )\n    Evaluates the moment-generating function (MGF) for a normal distribution\n    with mean `μ` and standard deviation `σ` at a value `t`.\n","base.dists.normal.mgf.factory":"\nbase.dists.normal.mgf.factory( μ:number, σ:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.mode":"\nbase.dists.normal.mode( μ:number, σ:number )\n    Returns the mode of a normal distribution with mean `μ` and standard\n    deviation `σ`.\n","base.dists.normal.Normal":"\nbase.dists.normal.Normal( [μ:number, σ:number] )\n    Returns a normal distribution object.\n","base.dists.normal.pdf":"\nbase.dists.normal.pdf( x:number, μ:number, σ:number )\n    Evaluates the probability density function (PDF) for a normal distribution\n    with mean `μ` and standard deviation `σ` at a value `x`.\n","base.dists.normal.pdf.factory":"\nbase.dists.normal.pdf.factory( μ:number, σ:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.quantile":"\nbase.dists.normal.quantile( p:number, μ:number, σ:number )\n    Evaluates the quantile function for a normal distribution with mean `μ` and\n    standard deviation `σ` at a probability `p`.\n","base.dists.normal.quantile.factory":"\nbase.dists.normal.quantile.factory( μ:number, σ:number )\n    Returns a function for evaluating the quantile function\n    of a normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.skewness":"\nbase.dists.normal.skewness( μ:number, σ:number )\n    Returns the skewness of a normal distribution with mean `μ` and standard\n    deviation `σ`.\n","base.dists.normal.stdev":"\nbase.dists.normal.stdev( μ:number, σ:number )\n    Returns the standard deviation of a normal distribution with mean `μ` and\n    standard deviation `σ`.\n","base.dists.normal.variance":"\nbase.dists.normal.variance( μ:number, σ:number )\n    Returns the variance of a normal distribution with mean `μ` and standard\n    deviation `σ`.\n","base.dists.pareto1.cdf":"\nbase.dists.pareto1.cdf( x:number, α:number, β:number )\n    Evaluates the cumulative distribution function (CDF) for a Pareto (Type I)\n    distribution with shape parameter `α` and scale parameter `β` at a value\n    `x`.\n","base.dists.pareto1.cdf.factory":"\nbase.dists.pareto1.cdf.factory( α:number, β:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Pareto (Type I) distribution with shape parameter `α` and scale\n    parameter `β`.\n","base.dists.pareto1.entropy":"\nbase.dists.pareto1.entropy( α:number, β:number )\n    Returns the differential entropy of a Pareto (Type I) distribution\n    (in nats).\n","base.dists.pareto1.kurtosis":"\nbase.dists.pareto1.kurtosis( α:number, β:number )\n    Returns the excess kurtosis of a Pareto (Type I) distribution.\n","base.dists.pareto1.logcdf":"\nbase.dists.pareto1.logcdf( x:number, α:number, β:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a Pareto (Type I) distribution with shape parameter `α` and scale\n    parameter `β` at a value `x`.\n","base.dists.pareto1.logcdf.factory":"\nbase.dists.pareto1.logcdf.factory( α:number, β:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Pareto (Type I) distribution with shape\n    parameter `α` and scale parameter `β`.\n","base.dists.pareto1.logpdf":"\nbase.dists.pareto1.logpdf( x:number, α:number, β:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a Pareto (Type I) distribution with shape parameter `α` and scale\n    parameter `β` at a value `x`.\n","base.dists.pareto1.logpdf.factory":"\nbase.dists.pareto1.logpdf.factory( α:number, β:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a Pareto (Type I) distribution with shape\n    parameter `α` and scale parameter `β`.\n","base.dists.pareto1.mean":"\nbase.dists.pareto1.mean( α:number, β:number )\n    Returns the expected value of a Pareto (Type I) distribution.\n","base.dists.pareto1.median":"\nbase.dists.pareto1.median( α:number, β:number )\n    Returns the median of a Pareto (Type I) distribution.\n","base.dists.pareto1.mode":"\nbase.dists.pareto1.mode( α:number, β:number )\n    Returns the mode of a Pareto (Type I) distribution.\n","base.dists.pareto1.Pareto1":"\nbase.dists.pareto1.Pareto1( [α:number, β:number] )\n    Returns a Pareto (Type I) distribution object.\n","base.dists.pareto1.pdf":"\nbase.dists.pareto1.pdf( x:number, α:number, β:number )\n    Evaluates the probability density function (PDF) for a Pareto (Type I)\n    distribution with shape parameter `α` and scale parameter `β` at a value\n    `x`.\n","base.dists.pareto1.pdf.factory":"\nbase.dists.pareto1.pdf.factory( α:number, β:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Pareto (Type I) distribution with shape parameter `α` and scale parameter\n    `β`.\n","base.dists.pareto1.quantile":"\nbase.dists.pareto1.quantile( p:number, α:number, β:number )\n    Evaluates the quantile function for a Pareto (Type I) distribution with\n    shape parameter `α` and scale parameter `β` at a probability `p`.\n","base.dists.pareto1.quantile.factory":"\nbase.dists.pareto1.quantile.factory( α:number, β:number )\n    Returns a function for evaluating the quantile function of a Pareto (Type I)\n    distribution with shape parameter `α` and scale parameter `β`.\n","base.dists.pareto1.skewness":"\nbase.dists.pareto1.skewness( α:number, β:number )\n    Returns the skewness of a Pareto (Type I) distribution.\n","base.dists.pareto1.stdev":"\nbase.dists.pareto1.stdev( α:number, β:number )\n    Returns the standard deviation of a Pareto (Type I) distribution.\n","base.dists.pareto1.variance":"\nbase.dists.pareto1.variance( α:number, β:number )\n    Returns the variance of a Pareto (Type I) distribution.\n","base.dists.poisson.cdf":"\nbase.dists.poisson.cdf( x:number, λ:number )\n    Evaluates the cumulative distribution function (CDF) for a Poisson\n    distribution with mean parameter `λ` at a value `x`.\n","base.dists.poisson.cdf.factory":"\nbase.dists.poisson.cdf.factory( λ:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.entropy":"\nbase.dists.poisson.entropy( λ:number )\n    Returns the entropy of a Poisson distribution.\n","base.dists.poisson.kurtosis":"\nbase.dists.poisson.kurtosis( λ:number )\n    Returns the excess kurtosis of a Poisson distribution.\n","base.dists.poisson.logpmf":"\nbase.dists.poisson.logpmf( x:number, λ:number )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    Poisson distribution with mean parameter `λ` at a value `x`.\n","base.dists.poisson.logpmf.factory":"\nbase.dists.poisson.logpmf.factory( λ:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.mean":"\nbase.dists.poisson.mean( λ:number )\n    Returns the expected value of a Poisson distribution.\n","base.dists.poisson.median":"\nbase.dists.poisson.median( λ:number )\n    Returns the median of a Poisson distribution.\n","base.dists.poisson.mgf":"\nbase.dists.poisson.mgf( x:number, λ:number )\n    Evaluates the moment-generating function (MGF) for a Poisson distribution\n    with mean parameter `λ` at a value `x`.\n","base.dists.poisson.mgf.factory":"\nbase.dists.poisson.mgf.factory( λ:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.mode":"\nbase.dists.poisson.mode( λ:number )\n    Returns the mode of a Poisson distribution.\n","base.dists.poisson.pmf":"\nbase.dists.poisson.pmf( x:number, λ:number )\n    Evaluates the probability mass function (PMF) for a Poisson\n    distribution with mean parameter `λ` at a value `x`.\n","base.dists.poisson.pmf.factory":"\nbase.dists.poisson.pmf.factory( λ:number )\n    Returns a function for evaluating the probability mass function (PMF)\n    of a Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.Poisson":"\nbase.dists.poisson.Poisson( [λ:number] )\n    Returns a Poisson distribution object.\n","base.dists.poisson.quantile":"\nbase.dists.poisson.quantile( p:number, λ:number )\n    Evaluates the quantile function for a Poisson distribution with mean\n    parameter `λ` at a probability `p`.\n","base.dists.poisson.quantile.factory":"\nbase.dists.poisson.quantile.factory( λ:number )\n    Returns a function for evaluating the quantile function of a Poisson\n    distribution with mean parameter `λ`.\n","base.dists.poisson.skewness":"\nbase.dists.poisson.skewness( λ:number )\n    Returns the skewness of a Poisson distribution.\n","base.dists.poisson.stdev":"\nbase.dists.poisson.stdev( λ:number )\n    Returns the standard deviation of a Poisson distribution.\n","base.dists.poisson.variance":"\nbase.dists.poisson.variance( λ:number )\n    Returns the variance of a Poisson distribution.\n","base.dists.rayleigh.cdf":"\nbase.dists.rayleigh.cdf( x:number, sigma:number )\n    Evaluates the cumulative distribution function (CDF) for a Rayleigh\n    distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.cdf.factory":"\nbase.dists.rayleigh.cdf.factory( sigma:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.entropy":"\nbase.dists.rayleigh.entropy( σ:number )\n    Returns the differential entropy of a Rayleigh distribution.\n","base.dists.rayleigh.kurtosis":"\nbase.dists.rayleigh.kurtosis( σ:number )\n    Returns the excess kurtosis of a Rayleigh distribution.\n","base.dists.rayleigh.logcdf":"\nbase.dists.rayleigh.logcdf( x:number, sigma:number )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    Rayleigh distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.logcdf.factory":"\nbase.dists.rayleigh.logcdf.factory( sigma:number )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Rayleigh distribution with scale parameter\n    `sigma`.\n","base.dists.rayleigh.logpdf":"\nbase.dists.rayleigh.logpdf( x:number, sigma:number )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    Rayleigh distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.logpdf.factory":"\nbase.dists.rayleigh.logpdf.factory( sigma:number )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.mean":"\nbase.dists.rayleigh.mean( σ:number )\n    Returns the expected value of a Rayleigh distribution.\n","base.dists.rayleigh.median":"\nbase.dists.rayleigh.median( σ:number )\n    Returns the median of a Rayleigh distribution.\n","base.dists.rayleigh.mgf":"\nbase.dists.rayleigh.mgf( t:number, sigma:number )\n    Evaluates the moment-generating function (MGF) for a Rayleigh distribution\n    with scale parameter `sigma` at a value `t`.\n","base.dists.rayleigh.mgf.factory":"\nbase.dists.rayleigh.mgf.factory( sigma:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.mode":"\nbase.dists.rayleigh.mode( σ:number )\n    Returns the mode of a Rayleigh distribution.\n","base.dists.rayleigh.pdf":"\nbase.dists.rayleigh.pdf( x:number, sigma:number )\n    Evaluates the probability density function (PDF) for a Rayleigh\n    distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.pdf.factory":"\nbase.dists.rayleigh.pdf.factory( sigma:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.quantile":"\nbase.dists.rayleigh.quantile( p:number, sigma:number )\n    Evaluates the quantile function for a Rayleigh distribution with scale\n    parameter `sigma` at a probability `p`.\n","base.dists.rayleigh.quantile.factory":"\nbase.dists.rayleigh.quantile.factory( sigma:number )\n    Returns a function for evaluating the quantile function of a Rayleigh\n    distribution with scale parameter `sigma`.\n","base.dists.rayleigh.Rayleigh":"\nbase.dists.rayleigh.Rayleigh( [σ:number] )\n    Returns a Rayleigh distribution object.\n","base.dists.rayleigh.skewness":"\nbase.dists.rayleigh.skewness( σ:number )\n    Returns the skewness of a Rayleigh distribution.\n","base.dists.rayleigh.stdev":"\nbase.dists.rayleigh.stdev( σ:number )\n    Returns the standard deviation of a Rayleigh distribution.\n","base.dists.rayleigh.variance":"\nbase.dists.rayleigh.variance( σ:number )\n    Returns the variance of a Rayleigh distribution.\n","base.dists.signrank.cdf":"\nbase.dists.signrank.cdf( x:number, n:integer )\n    Evaluates the cumulative distribution function (CDF) for the distribution of\n    the Wilcoxon signed rank test statistic with `n` observations.\n","base.dists.signrank.cdf.factory":"\nbase.dists.signrank.cdf.factory( n:integer )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of the distribution of the Wilcoxon signed rank test statistic.\n","base.dists.signrank.pdf":"\nbase.dists.signrank.pdf( x:number, n:integer )\n    Evaluates the probability density function (PDF) for the distribution of\n    the Wilcoxon signed rank test statistic with `n` observations.\n","base.dists.signrank.pdf.factory":"\nbase.dists.signrank.pdf.factory( n:integer )\n    Returns a function for evaluating the probability density function (PDF)\n    of the distribution of the Wilcoxon signed rank test statistic.\n","base.dists.signrank.quantile":"\nbase.dists.signrank.quantile( p:number, n:integer )\n    Evaluates the quantile function for the Wilcoxon signed rank test statistic\n    with `n` observations at a probability `p`.\n","base.dists.signrank.quantile.factory":"\nbase.dists.signrank.quantile.factory( n:integer )\n    Returns a function for evaluating the quantile function of the Wilcoxon\n    signed rank test statistic with `n` observations.\n","base.dists.studentizedRange.cdf":"\nbase.dists.studentizedRange.cdf( x:number, r:number, v:number[, \n  nranges:integer] )\n    Evaluates the cumulative distribution function (CDF) of a studentized range\n    distribution.\n","base.dists.studentizedRange.cdf.factory":"\nbase.dists.studentizedRange.cdf.factory( r:number, v:number[, nranges:integer] )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a studentized range distribution.\n","base.dists.studentizedRange.quantile":"\nbase.dists.studentizedRange.quantile( p:number, r:number, v:number[, \n  nranges:integer] )\n    Evaluates the quantile function for a studentized range distribution.\n","base.dists.studentizedRange.quantile.factory":"\nbase.dists.studentizedRange.quantile.factory( r:number, v:number[, \n  nranges:integer] )\n    Returns a function for evaluating the quantile function of a studentized\n    range distribution.\n","base.dists.t.cdf":"\nbase.dists.t.cdf( x:number, v:number )\n    Evaluates the cumulative distribution function (CDF) for a Student's t\n    distribution with degrees of freedom `v` at a value `x`.\n","base.dists.t.cdf.factory":"\nbase.dists.t.cdf.factory( v:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Student's t distribution with degrees of freedom `v`.\n","base.dists.t.entropy":"\nbase.dists.t.entropy( v:number )\n    Returns the differential entropy of a Student's t distribution.\n","base.dists.t.kurtosis":"\nbase.dists.t.kurtosis( v:number )\n    Returns the excess kurtosis of a Student's t distribution.\n","base.dists.t.logcdf":"\nbase.dists.t.logcdf( x:number, v:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a Student's t distribution with degrees of freedom `v` at a value\n    `x`.\n","base.dists.t.logcdf.factory":"\nbase.dists.t.logcdf.factory( v:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Student's t distribution with degrees of\n    freedom `v`.\n","base.dists.t.logpdf":"\nbase.dists.t.logpdf( x:number, v:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a Student's t distribution with degrees of freedom `v` at a value `x`.\n","base.dists.t.logpdf.factory":"\nbase.dists.t.logpdf.factory( v:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a Student's t distribution with degrees of\n    freedom `v`.\n","base.dists.t.mean":"\nbase.dists.t.mean( v:number )\n    Returns the expected value of a Student's t distribution.\n","base.dists.t.median":"\nbase.dists.t.median( v:number )\n    Returns the median of a Student's t distribution.\n","base.dists.t.mode":"\nbase.dists.t.mode( v:number )\n    Returns the mode of a Student's t distribution.\n","base.dists.t.pdf":"\nbase.dists.t.pdf( x:number, v:number )\n    Evaluates the probability density function (PDF) for a Student's t\n    distribution with degrees of freedom `v` at a value `x`.\n","base.dists.t.pdf.factory":"\nbase.dists.t.pdf.factory( v:number )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Student's t distribution with degrees of freedom `v`.\n","base.dists.t.quantile":"\nbase.dists.t.quantile( p:number, v:number )\n    Evaluates the quantile function for a Student's t distribution with degrees\n    of freedom `v` at a probability `p`.\n","base.dists.t.quantile.factory":"\nbase.dists.t.quantile.factory( v:number )\n    Returns a function for evaluating the quantile function of a Student's t\n    distribution with degrees of freedom `v`.\n","base.dists.t.skewness":"\nbase.dists.t.skewness( v:number )\n    Returns the skewness of a Student's t distribution.\n","base.dists.t.stdev":"\nbase.dists.t.stdev( v:number )\n    Returns the standard deviation of a Student's t distribution.\n","base.dists.t.T":"\nbase.dists.t.T( [v:number] )\n    Returns a Student's t distribution object.\n","base.dists.t.variance":"\nbase.dists.t.variance( v:number )\n    Returns the variance of a Student's t distribution.\n","base.dists.triangular.cdf":"\nbase.dists.triangular.cdf( x:number, a:number, b:number, c:number )\n    Evaluates the cumulative distribution function (CDF) for a triangular\n    distribution with minimum support `a`, maximum support `b`, and mode `c` at\n    a value `x`.\n","base.dists.triangular.cdf.factory":"\nbase.dists.triangular.cdf.factory( a:number, b:number, c:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a triangular distribution with minimum support `a`, maximum support `b`,\n    and mode `c`.\n","base.dists.triangular.entropy":"\nbase.dists.triangular.entropy( a:number, b:number, c:number )\n    Returns the differential entropy of a triangular distribution (in nats).\n","base.dists.triangular.kurtosis":"\nbase.dists.triangular.kurtosis( a:number, b:number, c:number )\n    Returns the excess kurtosis of a triangular distribution.\n","base.dists.triangular.logcdf":"\nbase.dists.triangular.logcdf( x:number, a:number, b:number, c:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a triangular distribution with minimum support `a`, maximum\n    support `b`, and mode `c` at a value `x`.\n","base.dists.triangular.logcdf.factory":"\nbase.dists.triangular.logcdf.factory( a:number, b:number, c:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a triangular distribution with minimum\n    support `a`, maximum support `b`, and mode `c`.\n","base.dists.triangular.logpdf":"\nbase.dists.triangular.logpdf( x:number, a:number, b:number, c:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a triangular distribution with minimum support `a`, maximum support `b`,\n    and mode `c` at a value `x`.\n","base.dists.triangular.logpdf.factory":"\nbase.dists.triangular.logpdf.factory( a:number, b:number, c:number )\n    Returns a function for evaluating the natural logarithm of the  probability\n    density function (PDF) of a triangular distribution with minimum support\n    `a`, maximum support `b`, and mode `c`.\n","base.dists.triangular.mean":"\nbase.dists.triangular.mean( a:number, b:number, c:number )\n    Returns the expected value of a triangular distribution.\n","base.dists.triangular.median":"\nbase.dists.triangular.median( a:number, b:number, c:number )\n    Returns the median of a triangular distribution.\n","base.dists.triangular.mgf":"\nbase.dists.triangular.mgf( t:number, a:number, b:number, c:number )\n    Evaluates the moment-generating function (MGF) for a triangular distribution\n    with minimum support `a`, maximum support `b`, and mode `c` at a value `t`.\n","base.dists.triangular.mgf.factory":"\nbase.dists.triangular.mgf.factory( a:number, b:number, c:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    triangular distribution with minimum support `a`, maximum support `b`, and\n    mode `c`.\n","base.dists.triangular.mode":"\nbase.dists.triangular.mode( a:number, b:number, c:number )\n    Returns the mode of a triangular distribution.\n","base.dists.triangular.pdf":"\nbase.dists.triangular.pdf( x:number, a:number, b:number, c:number )\n    Evaluates the probability density function (PDF) for a triangular\n    distribution with minimum support `a`, maximum support `b`, and mode `c` at\n    a value `x`.\n","base.dists.triangular.pdf.factory":"\nbase.dists.triangular.pdf.factory( a:number, b:number, c:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a triangular distribution with minimum support `a`, maximum support `b`, and\n    mode `c`.\n","base.dists.triangular.quantile":"\nbase.dists.triangular.quantile( p:number, a:number, b:number, c:number )\n    Evaluates the quantile function for a triangular distribution with minimum\n    support `a`, maximum support `b`, and mode `c` at a value `x`.\n","base.dists.triangular.quantile.factory":"\nbase.dists.triangular.quantile.factory( a:number, b:number, c:number )\n    Returns a function for evaluating the quantile function of a triangular\n    distribution with minimum support `a`, maximum support `b`, and mode `c`.\n","base.dists.triangular.skewness":"\nbase.dists.triangular.skewness( a:number, b:number, c:number )\n    Returns the skewness of a triangular distribution.\n","base.dists.triangular.stdev":"\nbase.dists.triangular.stdev( a:number, b:number, c:number )\n    Returns the standard deviation of a triangular distribution.\n","base.dists.triangular.Triangular":"\nbase.dists.triangular.Triangular( [a:number, b:number, c:number] )\n    Returns a triangular distribution object.\n","base.dists.triangular.variance":"\nbase.dists.triangular.variance( a:number, b:number, c:number )\n    Returns the variance of a triangular distribution.\n","base.dists.uniform.cdf":"\nbase.dists.uniform.cdf( x:number, a:number, b:number )\n    Evaluates the cumulative distribution function (CDF) for a uniform\n    distribution with minimum support `a` and maximum support `b` at a value\n    `x`.\n","base.dists.uniform.cdf.factory":"\nbase.dists.uniform.cdf.factory( a:number, b:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.entropy":"\nbase.dists.uniform.entropy( a:number, b:number )\n    Returns the differential entropy of a uniform distribution.\n","base.dists.uniform.kurtosis":"\nbase.dists.uniform.kurtosis( a:number, b:number )\n    Returns the excess kurtosis of a uniform distribution.\n","base.dists.uniform.logcdf":"\nbase.dists.uniform.logcdf( x:number, a:number, b:number )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    uniform distribution with minimum support `a` and maximum support `b` at a\n    value `x`.\n","base.dists.uniform.logcdf.factory":"\nbase.dists.uniform.logcdf.factory( a:number, b:number )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a uniform distribution with minimum support\n    `a` and maximum support `b`.\n","base.dists.uniform.logpdf":"\nbase.dists.uniform.logpdf( x:number, a:number, b:number )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    uniform distribution with minimum support `a` and maximum support `b` at a\n    value `x`.\n","base.dists.uniform.logpdf.factory":"\nbase.dists.uniform.logpdf.factory( a:number, b:number )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a uniform distribution with minimum support `a` and\n    maximum support `b`.\n","base.dists.uniform.mean":"\nbase.dists.uniform.mean( a:number, b:number )\n    Returns the expected value of a uniform distribution.\n","base.dists.uniform.median":"\nbase.dists.uniform.median( a:number, b:number )\n    Returns the median of a uniform distribution.\n","base.dists.uniform.mgf":"\nbase.dists.uniform.mgf( t:number, a:number, b:number )\n    Evaluates the moment-generating function (MGF) for a uniform\n    distribution with minimum support `a` and maximum support `b` at a value\n    `t`.\n","base.dists.uniform.mgf.factory":"\nbase.dists.uniform.mgf.factory( a:number, b:number )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.pdf":"\nbase.dists.uniform.pdf( x:number, a:number, b:number )\n    Evaluates the probability density function (PDF) for a uniform distribution\n    with minimum support `a` and maximum support `b` at a value `x`.\n","base.dists.uniform.pdf.factory":"\nbase.dists.uniform.pdf.factory( a:number, b:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.quantile":"\nbase.dists.uniform.quantile( p:number, a:number, b:number )\n    Evaluates the quantile function for a uniform distribution with minimum\n    support `a` and maximum support `b` at a probability `p`.\n","base.dists.uniform.quantile.factory":"\nbase.dists.uniform.quantile.factory( a:number, b:number )\n    Returns a function for evaluating the quantile function of a uniform\n    distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.skewness":"\nbase.dists.uniform.skewness( a:number, b:number )\n    Returns the skewness of a uniform distribution.\n","base.dists.uniform.stdev":"\nbase.dists.uniform.stdev( a:number, b:number )\n    Returns the standard deviation of a uniform distribution.\n","base.dists.uniform.Uniform":"\nbase.dists.uniform.Uniform( [a:number, b:number] )\n    Returns a uniform distribution object.\n","base.dists.uniform.variance":"\nbase.dists.uniform.variance( a:number, b:number )\n    Returns the variance of a uniform distribution.\n","base.dists.weibull.cdf":"\nbase.dists.weibull.cdf( x:number, k:number, λ:number )\n    Evaluates the cumulative distribution function (CDF) for a Weibull\n    distribution with shape parameter `k` and scale parameter `λ` at a value\n    `x`.\n","base.dists.weibull.cdf.factory":"\nbase.dists.weibull.cdf.factory( k:number, λ:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n","base.dists.weibull.entropy":"\nbase.dists.weibull.entropy( k:number, λ:number )\n    Returns the differential entropy of a Weibull distribution (in nats).\n","base.dists.weibull.kurtosis":"\nbase.dists.weibull.kurtosis( k:number, λ:number )\n    Returns the excess kurtosis of a Weibull distribution.\n","base.dists.weibull.logcdf":"\nbase.dists.weibull.logcdf( x:number, k:number, λ:number )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n    value `x`.\n","base.dists.weibull.logcdf.factory":"\nbase.dists.weibull.logcdf.factory( k:number, λ:number)\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Weibull distribution with scale parameter\n    `λ` and shape parameter `k`.\n","base.dists.weibull.logpdf":"\nbase.dists.weibull.logpdf( x:number, k:number, λ:number )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n    value `x`.\n","base.dists.weibull.logpdf.factory":"\nbase.dists.weibull.logpdf.factory( k:number, λ:number )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Weibull distribution with shape parameter `k` and scale\n    parameter `λ`.\n","base.dists.weibull.mean":"\nbase.dists.weibull.mean( k:number, λ:number )\n    Returns the expected value of a Weibull distribution.\n","base.dists.weibull.median":"\nbase.dists.weibull.median( k:number, λ:number )\n    Returns the median of a Weibull distribution.\n","base.dists.weibull.mgf":"\nbase.dists.weibull.mgf( x:number, k:number, λ:number )\n    Evaluates the moment-generating function (MGF) for a Weibull distribution\n    with shape parameter `k` and scale parameter `λ` at a value `t`.\n","base.dists.weibull.mgf.factory":"\nbase.dists.weibull.mgf.factory( k:number, λ:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Weibull distribution with shape parameter `k` and scale parameter `λ`.\n","base.dists.weibull.mode":"\nbase.dists.weibull.mode( k:number, λ:number )\n    Returns the mode of a Weibull distribution.\n","base.dists.weibull.pdf":"\nbase.dists.weibull.pdf( x:number, k:number, λ:number )\n    Evaluates the probability density function (PDF) for a Weibull distribution\n    with shape parameter `k` and scale parameter `λ` at a value `x`.\n","base.dists.weibull.pdf.factory":"\nbase.dists.weibull.pdf.factory( k:number, λ:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n","base.dists.weibull.quantile":"\nbase.dists.weibull.quantile( p:number, k:number, λ:number )\n    Evaluates the quantile function for a Weibull distribution with scale\n    parameter `k` and shape parameter `λ` at a probability `p`.\n","base.dists.weibull.quantile.factory":"\nbase.dists.weibull.quantile.factory( k:number, λ:number )\n    Returns a function for evaluating the quantile function of a Weibull\n    distribution with scale parameter `k` and shape parameter `λ`.\n","base.dists.weibull.skewness":"\nbase.dists.weibull.skewness( k:number, λ:number )\n    Returns the skewness of a Weibull distribution.\n","base.dists.weibull.stdev":"\nbase.dists.weibull.stdev( k:number, λ:number )\n    Returns the standard deviation of a Weibull distribution.\n","base.dists.weibull.variance":"\nbase.dists.weibull.variance( k:number, λ:number )\n    Returns the variance of a Weibull distribution.\n","base.dists.weibull.Weibull":"\nbase.dists.weibull.Weibull( [k:number, λ:number] )\n    Returns a Weibull distribution object.\n","base.ellipe":"\nbase.ellipe( m:number )\n    Computes the complete elliptic integral of the second kind.\n","base.ellipj":"\nbase.ellipj( u:number, m:number )\n    Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n    amplitude am.\n","base.ellipj.assign":"\nbase.ellipj.assign( u:number, m:number, out:Array|TypedArray|Object, \n  stride:integer, offset:integer )\n    Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n    amplitude am and assigns results to a provided output array.\n","base.ellipj.sn":"\nbase.ellipj.sn( u:number, m:number )\n    Computes the Jacobi elliptic function sn.\n","base.ellipj.cn":"\nbase.ellipj.cn( u:number, m:number )\n    Computes the Jacobi elliptic functions cn.\n","base.ellipj.dn":"\nbase.ellipj.dn( u:number, m:number )\n    Computes the Jacobi elliptic function dn.\n","base.ellipj.am":"\nbase.ellipj.am( u:number, m:number )\n    Computes the Jacobi amplitude am.\n","base.ellipk":"\nbase.ellipk( m:number )\n    Computes the complete elliptic integral of the first kind.\n","base.endsWith":"\nbase.endsWith( str:string, search:string, len:integer )\n    Tests if a string ends with the characters of another string.\n","base.epsdiff":"\nbase.epsdiff( x:number, y:number[, scale:string|Function] )\n    Computes the relative difference of two real numbers in units of double-\n    precision floating-point epsilon.\n","base.erf":"\nbase.erf( x:number )\n    Evaluates the error function.\n","base.erfc":"\nbase.erfc( x:number )\n    Evaluates the complementary error function.\n","base.erfcinv":"\nbase.erfcinv( x:number )\n    Evaluates the inverse complementary error function.\n","base.erfcx":"\nbase.erfcx( x:number )\n    Evaluates the scaled complementary error function.\n","base.erfinv":"\nbase.erfinv( x:number )\n    Evaluates the inverse error function.\n","base.eta":"\nbase.eta( s:number )\n    Evaluates the Dirichlet eta function for a double-precision\n    floating-point number `s`.\n","base.evalpoly":"\nbase.evalpoly( c:Array<number>, x:number )\n    Evaluates a polynomial using double-precision floating-point arithmetic.\n","base.evalpoly.factory":"\nbase.evalpoly.factory( c:Array<number> )\n    Returns a function for evaluating a polynomial using double-precision\n    floating-point arithmetic.\n","base.evalrational":"\nbase.evalrational( P:Array<number>, Q:Array<number>, x:number )\n    Evaluates a rational function using double-precision floating-point\n    arithmetic.\n","base.evalrational.factory":"\nbase.evalrational.factory( P:Array<number>, Q:Array<number> )\n    Returns a function for evaluating a rational function using double-precision\n    floating-point arithmetic.\n","base.exp":"\nbase.exp( x:number )\n    Evaluates the natural exponential function.\n","base.exp2":"\nbase.exp2( x:number )\n    Evaluates the base 2 exponential function.\n","base.exp10":"\nbase.exp10( x:number )\n    Evaluates the base 10 exponential function.\n","base.expit":"\nbase.expit( x:number )\n    Evaluates the standard logistic function.\n","base.expm1":"\nbase.expm1( x:number )\n    Computes `exp(x)-1`, where `exp(x)` is the natural exponential function.\n","base.expm1rel":"\nbase.expm1rel( x:number )\n    Relative error exponential.\n","base.exponent":"\nbase.exponent( x:number )\n    Returns an integer corresponding to the unbiased exponent of a double-\n    precision floating-point number.\n","base.exponentf":"\nbase.exponentf( x:float )\n    Returns an integer corresponding to the unbiased exponent of a single-\n    precision floating-point number.\n","base.factorial":"\nbase.factorial( x:number )\n    Evaluates the factorial of `x`.\n","base.factorial2":"\nbase.factorial2( n:number )\n    Evaluates the double factorial of `n`.\n","base.factorialln":"\nbase.factorialln( x:number )\n    Evaluates the natural logarithm of the factorial of `x`.\n","base.fallingFactorial":"\nbase.fallingFactorial( x:number, n:integer )\n    Computes the falling factorial of `x` and `n`.\n","base.fibonacci":"\nbase.fibonacci( n:integer )\n    Computes the nth Fibonacci number.\n","base.fibonacciIndex":"\nbase.fibonacciIndex( F:integer )\n    Computes the Fibonacci number index.\n","base.fibpoly":"\nbase.fibpoly( n:integer, x:number )\n    Evaluates a Fibonacci polynomial.\n","base.fibpoly.factory":"\nbase.fibpoly.factory( n:integer )\n    Returns a function for evaluating a Fibonacci polynomial.\n","base.firstCodePoint":"\nbase.firstCodePoint( str:string, n:integer )\n    Returns the first `n` Unicode code points of a string.\n","base.firstCodeUnit":"\nbase.firstCodeUnit( str:string, n:integer )\n    Returns the first `n` UTF-16 code units of a string.\n","base.firstGraphemeCluster":"\nbase.firstGraphemeCluster( str:string, n:integer )\n    Returns the first `n` grapheme clusters (i.e., user-perceived characters) of\n    a string.\n","base.flipsign":"\nbase.flipsign( x:number, y:number )\n    Returns a double-precision floating-point number with the magnitude of `x`\n    and the sign of `x*y`.\n","base.flipsignf":"\nbase.flipsignf( x:number, y:number )\n    Returns a single-precision floating-point number with the magnitude of `x`\n    and the sign of `x*y`.\n","base.float32ToInt32":"\nbase.float32ToInt32( x:float )\n    Converts a single-precision floating-point number to a signed 32-bit\n    integer.\n","base.float32ToUint32":"\nbase.float32ToUint32( x:float )\n    Converts a single-precision floating-point number to a unsigned 32-bit\n    integer.\n","base.float64ToFloat32":"\nbase.float64ToFloat32( x:number )\n    Converts a double-precision floating-point number to the nearest single-\n    precision floating-point number.\n","base.float64ToInt32":"\nbase.float64ToInt32( x:number )\n    Converts a double-precision floating-point number to a signed 32-bit\n    integer.\n","base.float64ToInt64Bytes":"\nbase.float64ToInt64Bytes( x:integer )\n    Converts an integer-valued double-precision floating-point number to a\n    signed 64-bit integer byte array according to host byte order (endianness).\n","base.float64ToInt64Bytes.assign":"\nbase.float64ToInt64Bytes.assign( x:integer, out:Array|TypedArray|Object, \n  stride:integer, offset:integer )\n    Converts an integer-valued double-precision floating-point number to a\n    signed 64-bit integer byte array according to host byte order (endianness)\n    and assigns results to a provided output array.\n","base.float64ToUint32":"\nbase.float64ToUint32( x:number )\n    Converts a double-precision floating-point number to a unsigned 32-bit\n    integer.\n","base.floor":"\nbase.floor( x:number )\n    Rounds a double-precision floating-point number toward negative infinity.\n","base.floor2":"\nbase.floor2( x:number )\n    Rounds a numeric value to the nearest power of two toward negative infinity.\n","base.floor10":"\nbase.floor10( x:number )\n    Rounds a numeric value to the nearest power of ten toward negative infinity.\n","base.floorb":"\nbase.floorb( x:number, n:integer, b:integer )\n    Rounds a numeric value to the nearest multiple of `b^n` toward negative\n    infinity.\n","base.floorf":"\nbase.floorf( x:number )\n    Rounds a single-precision floating-point number toward negative infinity.\n","base.floorn":"\nbase.floorn( x:number, n:integer )\n    Rounds a double-precision floating-point number to the nearest multiple of\n    `10^n` toward negative infinity.\n","base.floorsd":"\nbase.floorsd( x:number, n:integer, b:integer )\n    Rounds a numeric value to the nearest number toward negative infinity with\n    `n` significant figures.\n","base.forEachChar":"\nbase.forEachChar( str:string, clbk:Function[, thisArg:any] )\n    Invokes a function for each UTF-16 code unit in a string.\n","base.forEachCodePoint":"\nbase.forEachCodePoint( str:string, clbk:Function[, thisArg:any] )\n    Invokes a function for each Unicode code point in a string.\n","base.forEachCodePointRight":"\nbase.forEachCodePointRight( str:string, clbk:Function[, thisArg:any] )\n    Invokes a function for each Unicode code point in a string, iterating from\n    right to left.\n","base.forEachGraphemeCluster":"\nbase.forEachGraphemeCluster( str:string, clbk:Function[, thisArg:any] )\n    Invokes a function for each grapheme cluster (i.e., user-perceived\n    character) in a string.\n","base.forEachRight":"\nbase.forEachRight( str:string, clbk:Function[, thisArg:any] )\n    Invokes a function for each UTF-16 code unit in a string, iterating from\n    right to left.\n","base.formatInterpolate":"\nbase.formatInterpolate( tokens:Array, ...args:any )\n    Generate string from a token array by interpolating values.\n","base.formatTokenize":"\nbase.formatTokenize( str:string )\n    Tokenize a string into an array of string parts and format identifier\n    objects.\n","base.fresnel":"\nbase.fresnel( x:number )\n    Computes the Fresnel integrals S(x) and C(x).\n","base.fresnel.assign":"\nbase.fresnel.assign( x:number, out:Array<number>, stride:integer, \n  offset:integer )\n    Computes the Fresnel integrals S(x) and C(x) and assigns results to a\n    provided output array.\n","base.fresnelc":"\nbase.fresnelc( x:number )\n    Computes the Fresnel integral C(x).\n","base.fresnels":"\nbase.fresnels( x:number )\n    Computes the Fresnel integral S(x).\n","base.frexp":"\nbase.frexp( x:number )\n    Splits a double-precision floating-point number into a normalized fraction\n    and an integer power of two.\n","base.frexp.assign":"\nbase.frexp.assign( x:number, out:Array<number>, stride:integer, offset:integer )\n    Splits a double-precision floating-point number into a normalized fraction\n    and an integer power of two and assigns results to a provided output array.\n","base.fromBinaryString":"\nbase.fromBinaryString( bstr:string )\n    Creates a double-precision floating-point number from a literal bit\n    representation.\n","base.fromBinaryStringf":"\nbase.fromBinaryStringf( bstr:string )\n    Creates a single-precision floating-point number from an IEEE 754 literal\n    bit representation.\n","base.fromBinaryStringUint8":"\nbase.fromBinaryStringUint8( bstr:string )\n    Creates an unsigned 8-bit integer from a literal bit representation.\n","base.fromBinaryStringUint16":"\nbase.fromBinaryStringUint16( bstr:string )\n    Creates an unsigned 16-bit integer from a literal bit representation.\n","base.fromBinaryStringUint32":"\nbase.fromBinaryStringUint32( bstr:string )\n    Creates an unsigned 32-bit integer from a literal bit representation.\n","base.fromInt64Bytes":"\nbase.fromInt64Bytes( bytes:Array|TypedArray|Object, stride:integer, \n  offset:integer )\n    Converts a signed 64-bit integer byte array to a double-precision floating-\n    point number.\n","base.fromWordf":"\nbase.fromWordf( word:integer )\n    Creates a single-precision floating-point number from an unsigned integer\n    corresponding to an IEEE 754 binary representation.\n","base.fromWords":"\nbase.fromWords( high:integer, low:integer )\n    Creates a double-precision floating-point number from a higher order word\n    (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n","base.gamma":"\nbase.gamma( x:number )\n    Evaluates the gamma function.\n","base.gamma1pm1":"\nbase.gamma1pm1( x:number )\n    Computes `gamma(x+1) - 1` without cancellation errors, where `gamma(x)` is\n    the gamma function.\n","base.gammaDeltaRatio":"\nbase.gammaDeltaRatio( z:number, delta:number )\n    Computes the ratio of two gamma functions.\n","base.gammainc":"\nbase.gammainc( x:number, s:number[, regularized:boolean[, upper:boolean]] )\n    Computes the regularized incomplete gamma function.\n","base.gammaincinv":"\nbase.gammaincinv( p:number, a:number[, upper:boolean] )\n    Computes the inverse of the lower incomplete gamma function.\n","base.gammaLanczosSum":"\nbase.gammaLanczosSum( x:number )\n    Calculates the Lanczos sum for the approximation of the gamma function.\n","base.gammaLanczosSumExpGScaled":"\nbase.gammaLanczosSumExpGScaled( x:number )\n    Calculates the scaled Lanczos sum for the approximation of the gamma\n    function.\n","base.gammaln":"\nbase.gammaln( x:number )\n    Evaluates the natural logarithm of the gamma function.\n","base.gammasgn":"\nbase.gammasgn( x:number )\n    Computes the sign of the gamma function.\n","base.gcd":"\nbase.gcd( a:integer, b:integer )\n    Computes the greatest common divisor (gcd).\n","base.getHighWord":"\nbase.getHighWord( x:number )\n    Returns an unsigned 32-bit integer corresponding to the more significant 32\n    bits of a double-precision floating-point number.\n","base.getLowWord":"\nbase.getLowWord( x:number )\n    Returns an unsigned 32-bit integer corresponding to the less significant 32\n    bits of a double-precision floating-point number.\n","base.hacovercos":"\nbase.hacovercos( x:number )\n    Computes the half-value coversed cosine.\n","base.hacoversin":"\nbase.hacoversin( x:number )\n    Computes the half-value coversed sine.\n","base.havercos":"\nbase.havercos( x:number )\n    Computes the half-value versed cosine.\n","base.haversin":"\nbase.haversin( x:number )\n    Computes the half-value versed sine.\n","base.headercase":"\nbase.headercase( str:string )\n    Converts a string to HTTP header case.\n","base.heaviside":"\nbase.heaviside( x:number[, continuity:string] )\n    Evaluates the Heaviside function.\n","base.hermitepoly":"\nbase.hermitepoly( n:integer, x:number )\n    Evaluates a physicist's Hermite polynomial.\n","base.hermitepoly.factory":"\nbase.hermitepoly.factory( n:integer )\n    Returns a function for evaluating a physicist's Hermite polynomial.\n","base.hypot":"\nbase.hypot( x:number, y:number )\n    Computes the hypotenuse avoiding overflow and underflow.\n","base.hypotf":"\nbase.hypotf( x:number, y:number )\n    Computes the hypotenuse avoiding overflow and underflow (single-precision).\n","base.identity":"\nbase.identity( x:number )\n    Evaluates the identity function for a double-precision floating-point number\n    `x`.\n","base.identityf":"\nbase.identityf( x:number )\n    Evaluates the identity function for a single-precision floating-point number\n    `x`.\n","base.imul":"\nbase.imul( a:integer, b:integer )\n    Performs C-like multiplication of two signed 32-bit integers.\n","base.imuldw":"\nbase.imuldw( a:integer, b:integer )\n    Multiplies two signed 32-bit integers and returns an array of two signed 32-\n    bit integers which represents the signed 64-bit integer product.\n","base.imuldw.assign":"\nbase.imuldw.assign( a:integer, b:integer, out:Array|TypedArray|Object, \n  stride:integer, offset:integer )\n    Multiplies two signed 32-bit integers and assigns results representing the\n    signed 64-bit integer product to a provided output array.\n","base.int2slice":"\nbase.int2slice( value:integer, max:integer, strict:boolean )\n    Converts an integer to a Slice object.\n","base.int32ToUint32":"\nbase.int32ToUint32( x:integer )\n    Converts a signed 32-bit integer to an unsigned 32-bit integer.\n","base.inv":"\nbase.inv( x:number )\n    Computes the multiplicative inverse of a double-precision floating-point\n    number `x`.\n","base.invcase":"\nbase.invcase( str:string )\n    Converts a string to inverse case.\n","base.invf":"\nbase.invf( x:number )\n    Computes the multiplicative inverse of a single-precision floating-point\n    number `x`.\n","base.isComposite":"\nbase.isComposite( x:number )\n    Tests if a number is composite.\n","base.isCoprime":"\nbase.isCoprime( a:number, b:number )\n    Tests if two numbers are coprime.\n","base.isEven":"\nbase.isEven( x:number )\n    Tests if a finite numeric value is an even number.\n","base.isEvenInt32":"\nbase.isEvenInt32( x:integer )\n    Tests if a 32-bit integer is even.\n","base.isFinite":"\nbase.isFinite( x:number )\n    Tests if a double-precision floating-point numeric value is finite.\n","base.isFinitef":"\nbase.isFinitef( x:number )\n    Tests if a single-precision floating-point numeric value is finite.\n","base.isInfinite":"\nbase.isInfinite( x:number )\n    Tests if a double-precision floating-point numeric value is infinite.\n","base.isInfinitef":"\nbase.isInfinitef( x:number )\n    Tests if a single-precision floating-point numeric value is infinite.\n","base.isInteger":"\nbase.isInteger( x:number )\n    Tests if a finite double-precision floating-point number is an integer.\n","base.isnan":"\nbase.isnan( x:number )\n     Tests if a double-precision floating-point numeric value is `NaN`.\n","base.isnanf":"\nbase.isnanf( x:number )\n     Tests if a single-precision floating-point numeric value is `NaN`.\n","base.isNegativeFinite":"\nbase.isNegativeFinite( x:number )\n    Tests if a double-precision floating-point numeric value is a negative\n    finite number.\n","base.isNegativeInteger":"\nbase.isNegativeInteger( x:number )\n    Tests if a finite double-precision floating-point number is a negative\n    integer.\n","base.isNegativeZero":"\nbase.isNegativeZero( x:number )\n    Tests if a double-precision floating-point numeric value is negative zero.\n","base.isNegativeZerof":"\nbase.isNegativeZerof( x:number )\n    Tests if a single-precision floating-point numeric value is negative zero.\n","base.isNonNegativeFinite":"\nbase.isNonNegativeFinite( x:number )\n    Tests if a double-precision floating-point numeric value is a nonnegative\n    finite number.\n","base.isNonNegativeInteger":"\nbase.isNonNegativeInteger( x:number )\n    Tests if a finite double-precision floating-point number is a nonnegative\n    integer.\n","base.isNonPositiveFinite":"\nbase.isNonPositiveFinite( x:number )\n    Tests if a double-precision floating-point numeric value is a nonpositive\n    finite number.\n","base.isNonPositiveInteger":"\nbase.isNonPositiveInteger( x:number )\n    Tests if a finite double-precision floating-point number is a nonpositive\n    integer.\n","base.isOdd":"\nbase.isOdd( x:number )\n    Tests if a finite numeric value is an odd number.\n","base.isOddInt32":"\nbase.isOddInt32( x:integer )\n    Tests if a 32-bit integer is odd.\n","base.isPositiveFinite":"\nbase.isPositiveFinite( x:number )\n    Tests if a double-precision floating-point numeric value is a positive\n    finite number.\n","base.isPositiveInteger":"\nbase.isPositiveInteger( x:number )\n    Tests if a finite double-precision floating-point number is a positive\n    integer.\n","base.isPositiveZero":"\nbase.isPositiveZero( x:number )\n    Tests if a double-precision floating-point numeric value is positive zero.\n","base.isPositiveZerof":"\nbase.isPositiveZerof( x:number )\n    Tests if a single-precision floating-point numeric value is positive zero.\n","base.isPow2Uint32":"\nbase.isPow2Uint32( x:integer )\n    Tests whether an unsigned integer is a power of 2.\n","base.isPrime":"\nbase.isPrime( x:number )\n    Tests if a number is prime.\n","base.isProbability":"\nbase.isProbability( x:number )\n    Tests if a double-precision floating-point number value is a probability.\n","base.isSafeInteger":"\nbase.isSafeInteger( x:number )\n    Tests if a finite double-precision floating-point number is a safe integer.\n","base.kebabcase":"\nbase.kebabcase( str:string )\n    Converts a string to kebab case.\n","base.kernelBetainc":"\nbase.kernelBetainc( x:number, a:number, b:number, regularized:boolean, \n  upper:boolean )\n    Computes the kernel function for the regularized incomplete beta function.\n","base.kernelBetainc.assign":"\nbase.kernelBetainc.assign( x:number, a:number, b:number, regularized:boolean, \n  upper:boolean, out:Array|TypedArray|Object, stride:integer, offset:integer )\n    Computes the kernel function for the regularized incomplete beta function.\n","base.kernelBetaincinv":"\nbase.kernelBetaincinv( a:number, b:number, p:number, q:number )\n    Computes the inverse of the lower incomplete beta function.\n","base.kernelCos":"\nbase.kernelCos( x:number, y:number )\n    Computes the cosine of a double-precision floating-point number on the\n    interval [-π/4, π/4].\n","base.kernelLog1p":"\nbase.kernelLog1p( f:number )\n    Computes `log(1+f) - f` for `1+f` in ~[sqrt(2)/2, sqrt(2)].\n","base.kernelSin":"\nbase.kernelSin( x:number, y:number )\n    Computes the sine of a double-precision floating-point number on [-π/4,π/4].\n","base.kernelTan":"\nbase.kernelTan( x:number, y:number, k:integer )\n    Computes the tangent of a double-precision floating-point number on the\n    interval [-π/4, π/4].\n","base.kroneckerDelta":"\nbase.kroneckerDelta( i:number, j:number )\n    Evaluates the Kronecker delta.\n","base.kroneckerDeltaf":"\nbase.kroneckerDeltaf( i:number, j:number )\n    Evaluates the Kronecker delta (single-precision).\n","base.labs":"\nbase.labs( x:integer )\n    Computes an absolute value of a signed 32-bit integer in two's complement\n    format.\n","base.last":"\nbase.last( str:string, n:integer )\n    Returns the last `n` UTF-16 code units of a string.\n","base.lastCodePoint":"\nbase.lastCodePoint( str:string, n:integer )\n    Returns the last `n` Unicode code points of a string.\n","base.lastGraphemeCluster":"\nbase.lastGraphemeCluster( str:string, n:integer )\n    Returns the last `n` grapheme clusters (i.e., user-perceived characters) of\n    a string.\n","base.lcm":"\nbase.lcm( a:integer, b:integer )\n    Computes the least common multiple (lcm).\n","base.ldexp":"\nbase.ldexp( frac:number, exp:number )\n    Multiplies a double-precision floating-point number by an integer power of\n    two; i.e., `x = frac * 2^exp`.\n","base.leftPad":"\nbase.leftPad( str:string, len:integer, pad:string )\n    Left pads a string such that the padded string has a length of at least\n    `len`.\n","base.leftTrim":"\nbase.leftTrim( str:string )\n    Trims whitespace from the beginning of a string.\n","base.ln":"\nbase.ln( x:number )\n    Evaluates the natural logarithm of a double-precision floating-point number.\n","base.log":"\nbase.log( x:number, b:number )\n    Computes the base `b` logarithm of a double-precision floating-point number.\n","base.log1mexp":"\nbase.log1mexp( x:number )\n    Evaluates the natural logarithm of `1-exp(-|x|)`.\n","base.log1p":"\nbase.log1p( x:number )\n    Evaluates the natural logarithm of `1+x`.\n","base.log1pexp":"\nbase.log1pexp( x:number )\n    Evaluates the natural logarithm of `1+exp(x)`.\n","base.log1pmx":"\nbase.log1pmx( x:number )\n    Evaluates `ln(1+x) - x`.\n","base.log2":"\nbase.log2( x:number )\n    Evaluates the binary logarithm (base two).\n","base.log10":"\nbase.log10( x:number )\n    Evaluates the common logarithm (base 10).\n","base.logaddexp":"\nbase.logaddexp( x:number, y:number )\n    Computes the natural logarithm of `exp(x) + exp(y)`.\n","base.logit":"\nbase.logit( p:number )\n    Evaluates the logit function.\n","base.lowercase":"\nbase.lowercase( str:string )\n    Converts a string to lowercase.\n","base.lucas":"\nbase.lucas( n:integer )\n    Computes the nth Lucas number.\n","base.lucaspoly":"\nbase.lucaspoly( n:integer, x:number )\n    Evaluates a Lucas polynomial.\n","base.lucaspoly.factory":"\nbase.lucaspoly.factory( n:integer )\n    Returns a function for evaluating a Lucas polynomial.\n","base.max":"\nbase.max( x:number, y:number )\n    Returns the maximum value.\n","base.maxabs":"\nbase.maxabs( x:number, y:number )\n    Returns the maximum absolute value.\n","base.maxabsn":"\nbase.maxabsn( [x:number[, y:number[, ...args:number]]] )\n    Returns the maximum absolute value.\n","base.maxn":"\nbase.maxn( [x:number[, y:number[, ...args:number]]] )\n    Returns the maximum value.\n","base.min":"\nbase.min( x:number, y:number )\n    Returns the minimum value.\n","base.minabs":"\nbase.minabs( x:number, y:number )\n    Returns the minimum absolute value.\n","base.minabsn":"\nbase.minabsn( [x:number[, y:number[, ...args:number]]] )\n    Returns the minimum absolute value.\n","base.minmax":"\nbase.minmax( x:number, y:number )\n    Returns the minimum and maximum values.\n","base.minmax.assign":"\nbase.minmax.assign( x:number, y:number, out:Array|TypedArray|Object, \n  stride:integer, offset:integer )\n    Returns the minimum and maximum values and assigns results to a provided\n    output array.\n","base.minmaxabs":"\nbase.minmaxabs( x:number, y:number )\n    Returns the minimum and maximum absolute values.\n","base.minmaxabs.assign":"\nbase.minmaxabs.assign( x:number, y:number, out:Array|TypedArray|Object, \n  stride:integer, offset:integer )\n    Returns the minimum and maximum absolute values.\n","base.minmaxabsn":"\nbase.minmaxabsn( [x:number[, y:number[, ...args:number]]] )\n    Returns the minimum and maximum absolute values.\n","base.minmaxabsn.assign":"\nbase.minmaxabsn.assign( [x:number[, y:number[, ...args:number]]], \n  out:Array|TypedArray|Object, stride:integer, offset:integer )\n    Returns the minimum and maximum absolute values.\n","base.minmaxn":"\nbase.minmaxn( [x:number[, y:number[, ...args:number]]] )\n    Returns the minimum and maximum values.\n","base.minmaxn.assign":"\nbase.minmaxn.assign( [x:number[, y:number[, ...args:number]]], \n  out:Array|TypedArray|Object, stride:integer, offset:integer )\n    Returns the minimum and maximum values and assigns results to a provided\n    output array.\n","base.minn":"\nbase.minn( [x:number[, y:number[, ...args:number]]] )\n    Returns the minimum value.\n","base.modf":"\nbase.modf( x:number )\n    Decomposes a double-precision floating-point number into integral and\n    fractional parts, each having the same type and sign as the input value.\n","base.modf.assign":"\nbase.modf.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n  offset:integer )\n    Decomposes a double-precision floating-point number into integral and\n    fractional parts, each having the same type and sign as the input value,\n    and assigns results to a provided output array.\n","base.mul":"\nbase.mul( x:number, y:number )\n    Multiplies two double-precision floating-point numbers `x` and `y`.\n","base.mulf":"\nbase.mulf( x:number, y:number )\n    Multiplies two single-precision floating-point numbers `x` and `y`.\n","base.ndarray":"\nbase.ndarray( dtype:string, buffer:ArrayLikeObject|TypedArray|Buffer, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  offset:integer, order:string )\n    Returns an ndarray.\n","base.ndarray.prototype.byteLength":"\nbase.ndarray.prototype.byteLength\n    Size (in bytes) of the array (if known).\n","base.ndarray.prototype.BYTES_PER_ELEMENT":"\nbase.ndarray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element (if known).\n","base.ndarray.prototype.data":"\nbase.ndarray.prototype.data\n    Pointer to the underlying data buffer.\n","base.ndarray.prototype.dtype":"\nbase.ndarray.prototype.dtype\n    Underlying data type.\n","base.ndarray.prototype.flags":"\nbase.ndarray.prototype.flags\n    Meta information, such as information concerning the memory layout of the\n    array.\n","base.ndarray.prototype.length":"\nbase.ndarray.prototype.length\n    Length of the array (i.e., number of elements).\n","base.ndarray.prototype.ndims":"\nbase.ndarray.prototype.ndims\n    Number of dimensions.\n","base.ndarray.prototype.offset":"\nbase.ndarray.prototype.offset\n    Index offset which specifies the buffer index at which to start iterating\n    over array elements.\n","base.ndarray.prototype.order: string":"\nbase.ndarray.prototype.order: string\n    Array order.\n","base.ndarray.prototype.shape":"\nbase.ndarray.prototype.shape\n    Array shape.\n","base.ndarray.prototype.strides":"\nbase.ndarray.prototype.strides\n    Index strides which specify how to access data along corresponding array\n    dimensions.\n","base.ndarray.prototype.get":"\nbase.ndarray.prototype.get( ...idx:integer )\n    Returns an array element specified according to provided subscripts.\n","base.ndarray.prototype.iget":"\nbase.ndarray.prototype.iget( idx:integer )\n    Returns an array element located at a specified linear index.\n","base.ndarray.prototype.set":"\nbase.ndarray.prototype.set( ...idx:integer, v:any )\n    Sets an array element specified according to provided subscripts.\n","base.ndarray.prototype.iset":"\nbase.ndarray.prototype.iset( idx:integer, v:any )\n    Sets an array element located at a specified linear index.\n","base.ndarray.prototype.toString":"\nbase.ndarray.prototype.toString()\n    Serializes an ndarray as a string.\n","base.ndarray.prototype.toJSON":"\nbase.ndarray.prototype.toJSON()\n    Serializes an ndarray as a JSON object.\n","base.ndarrayUnary":"\nbase.ndarrayUnary( arrays:ArrayLikeObject<ndarray>, fcn:Function )\n    Applies a unary callback to elements in an input ndarray and assigns results\n    to elements in an output ndarray.\n","base.ndzeros":"\nbase.ndzeros( dtype:string, shape:ArrayLikeObject<integer>, order:string )\n    Returns a zero-filled ndarray having a specified shape and data type.\n","base.ndzerosLike":"\nbase.ndzerosLike( x:ndarray )\n    Returns a zero-filled ndarray having the same shape and data type as a\n    provided input ndarray.\n","base.negafibonacci":"\nbase.negafibonacci( n:integer )\n    Computes the nth negaFibonacci number.\n","base.negalucas":"\nbase.negalucas( n:integer )\n    Computes the nth negaLucas number.\n","base.nonfibonacci":"\nbase.nonfibonacci( n:integer )\n    Computes the nth non-Fibonacci number.\n","base.normalize":"\nbase.normalize( x:number )\n    Returns a normal number and exponent satisfying `x = y * 2^exp` as an array.\n","base.normalize.assign":"\nbase.normalize.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n  offset:integer )\n    Returns a normal number and exponent satisfying `x = y * 2^exp` and assigns\n    results to a provided output array.\n","base.normalizef":"\nbase.normalizef( x:float )\n    Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` as\n    an array.\n","base.normalizef.assign":"\nbase.normalizef.assign( x:float, out:Array|TypedArray|Object, stride:integer, \n  offset:integer )\n    Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` and\n    assigns results to a provided output array.\n","base.normalizeSlice":"\nbase.normalizeSlice( slice:Slice, len:integer, strict:boolean )\n    Returns a normalized Slice object.\n","base.normhermitepoly":"\nbase.normhermitepoly( n:integer, x:number )\n    Evaluates a normalized Hermite polynomial using double-precision floating-\n    point arithmetic.\n","base.normhermitepoly.factory":"\nbase.normhermitepoly.factory( n:integer )\n    Returns a function for evaluating a normalized Hermite polynomial using\n    double-precision floating-point arithmetic.\n","base.pascalcase":"\nbase.pascalcase( str:string )\n    Converts a string to Pascal case.\n","base.pdiff":"\nbase.pdiff( x:number, y:number )\n    Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n    returns `0`.\n","base.pdifff":"\nbase.pdifff( x:number, y:number )\n    Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n    returns `0`.\n","base.percentEncode":"\nbase.percentEncode( str:string )\n    Percent-encodes a UTF-16 encoded string according to RFC 3986.\n","base.polygamma":"\nbase.polygamma( n:integer, x:number )\n    Evaluates the polygamma function of order `n`; i.e., the (n+1)th derivative\n    of the natural logarithm of the gamma function.\n","base.pow":"\nbase.pow( b:number, x:number )\n    Evaluates the exponential function `bˣ`.\n","base.powm1":"\nbase.powm1( b:number, x:number )\n    Evaluates `bˣ - 1`.\n","base.rad2deg":"\nbase.rad2deg( x:number )\n    Converts an angle from radians to degrees.\n","base.rad2degf":"\nbase.rad2degf( x:number )\n    Converts an angle from radians to degrees (single-precision).\n","base.ramp":"\nbase.ramp( x:number )\n    Evaluates the ramp function.\n","base.rampf":"\nbase.rampf( x:number )\n    Evaluates the ramp function (single-precision).\n","base.random.arcsine":"\nbase.random.arcsine( a:number, b:number )\n    Returns a pseudorandom number drawn from an arcsine distribution.\n","base.random.arcsine.factory":"\nbase.random.arcsine.factory( [a:number, b:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an arcsine distribution.\n","base.random.arcsine.NAME":"\nbase.random.arcsine.NAME\n    Generator name.\n","base.random.arcsine.PRNG":"\nbase.random.arcsine.PRNG\n    Underlying pseudorandom number generator.\n","base.random.arcsine.seed":"\nbase.random.arcsine.seed\n    Pseudorandom number generator seed.\n","base.random.arcsine.seedLength":"\nbase.random.arcsine.seedLength\n    Length of generator seed.\n","base.random.arcsine.state":"\nbase.random.arcsine.state\n    Generator state.\n","base.random.arcsine.stateLength":"\nbase.random.arcsine.stateLength\n    Length of generator state.\n","base.random.arcsine.byteLength":"\nbase.random.arcsine.byteLength\n    Size (in bytes) of generator state.\n","base.random.arcsine.toJSON":"\nbase.random.arcsine.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.bernoulli":"\nbase.random.bernoulli( p:number )\n    Returns a pseudorandom number drawn from a Bernoulli distribution.\n","base.random.bernoulli.factory":"\nbase.random.bernoulli.factory( [p:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Bernoulli distribution.\n","base.random.bernoulli.NAME":"\nbase.random.bernoulli.NAME\n    Generator name.\n","base.random.bernoulli.PRNG":"\nbase.random.bernoulli.PRNG\n    Underlying pseudorandom number generator.\n","base.random.bernoulli.seed":"\nbase.random.bernoulli.seed\n    Pseudorandom number generator seed.\n","base.random.bernoulli.seedLength":"\nbase.random.bernoulli.seedLength\n    Length of generator seed.\n","base.random.bernoulli.state":"\nbase.random.bernoulli.state\n    Generator state.\n","base.random.bernoulli.stateLength":"\nbase.random.bernoulli.stateLength\n    Length of generator state.\n","base.random.bernoulli.byteLength":"\nbase.random.bernoulli.byteLength\n    Size (in bytes) of generator state.\n","base.random.bernoulli.toJSON":"\nbase.random.bernoulli.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.beta":"\nbase.random.beta( α:number, β:number )\n    Returns a pseudorandom number drawn from a beta distribution.\n","base.random.beta.factory":"\nbase.random.beta.factory( [α:number, β:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a beta distribution.\n","base.random.beta.NAME":"\nbase.random.beta.NAME\n    Generator name.\n","base.random.beta.PRNG":"\nbase.random.beta.PRNG\n    Underlying pseudorandom number generator.\n","base.random.beta.seed":"\nbase.random.beta.seed\n    Pseudorandom number generator seed.\n","base.random.beta.seedLength":"\nbase.random.beta.seedLength\n    Length of generator seed.\n","base.random.beta.state":"\nbase.random.beta.state\n    Generator state.\n","base.random.beta.stateLength":"\nbase.random.beta.stateLength\n    Length of generator state.\n","base.random.beta.byteLength":"\nbase.random.beta.byteLength\n    Size (in bytes) of generator state.\n","base.random.beta.toJSON":"\nbase.random.beta.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.betaprime":"\nbase.random.betaprime( α:number, β:number )\n    Returns a pseudorandom number drawn from a beta prime distribution.\n","base.random.betaprime.factory":"\nbase.random.betaprime.factory( [α:number, β:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a beta prime distribution.\n","base.random.betaprime.NAME":"\nbase.random.betaprime.NAME\n    Generator name.\n","base.random.betaprime.PRNG":"\nbase.random.betaprime.PRNG\n    Underlying pseudorandom number generator.\n","base.random.betaprime.seed":"\nbase.random.betaprime.seed\n    Pseudorandom number generator seed.\n","base.random.betaprime.seedLength":"\nbase.random.betaprime.seedLength\n    Length of generator seed.\n","base.random.betaprime.state":"\nbase.random.betaprime.state\n    Generator state.\n","base.random.betaprime.stateLength":"\nbase.random.betaprime.stateLength\n    Length of generator state.\n","base.random.betaprime.byteLength":"\nbase.random.betaprime.byteLength\n    Size (in bytes) of generator state.\n","base.random.betaprime.toJSON":"\nbase.random.betaprime.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.binomial":"\nbase.random.binomial( n:integer, p:number )\n    Returns a pseudorandom number drawn from a binomial distribution.\n","base.random.binomial.factory":"\nbase.random.binomial.factory( [n:integer, p:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a binomial distribution.\n","base.random.binomial.NAME":"\nbase.random.binomial.NAME\n    Generator name.\n","base.random.binomial.PRNG":"\nbase.random.binomial.PRNG\n    Underlying pseudorandom number generator.\n","base.random.binomial.seed":"\nbase.random.binomial.seed\n    Pseudorandom number generator seed.\n","base.random.binomial.seedLength":"\nbase.random.binomial.seedLength\n    Length of generator seed.\n","base.random.binomial.state":"\nbase.random.binomial.state\n    Generator state.\n","base.random.binomial.stateLength":"\nbase.random.binomial.stateLength\n    Length of generator state.\n","base.random.binomial.byteLength":"\nbase.random.binomial.byteLength\n    Size of generator state.\n","base.random.binomial.toJSON":"\nbase.random.binomial.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.boxMuller":"\nbase.random.boxMuller()\n    Returns a pseudorandom number drawn from a standard normal distribution.\n","base.random.boxMuller.factory":"\nbase.random.boxMuller.factory( [options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a standard normal distribution.\n","base.random.boxMuller.NAME":"\nbase.random.boxMuller.NAME\n    Generator name.\n","base.random.boxMuller.PRNG":"\nbase.random.boxMuller.PRNG\n    Underlying pseudorandom number generator.\n","base.random.boxMuller.seed":"\nbase.random.boxMuller.seed\n    Pseudorandom number generator seed.\n","base.random.boxMuller.seedLength":"\nbase.random.boxMuller.seedLength\n    Length of generator seed.\n","base.random.boxMuller.state":"\nbase.random.boxMuller.state\n    Generator state.\n","base.random.boxMuller.stateLength":"\nbase.random.boxMuller.stateLength\n    Length of generator state.\n","base.random.boxMuller.byteLength":"\nbase.random.boxMuller.byteLength\n    Size (in bytes) of generator state.\n","base.random.boxMuller.toJSON":"\nbase.random.boxMuller.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.cauchy":"\nbase.random.cauchy( x0:number, Ɣ:number )\n    Returns a pseudorandom number drawn from a Cauchy distribution.\n","base.random.cauchy.factory":"\nbase.random.cauchy.factory( [x0:number, Ɣ:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Cauchy distribution.\n","base.random.cauchy.NAME":"\nbase.random.cauchy.NAME\n    Generator name.\n","base.random.cauchy.PRNG":"\nbase.random.cauchy.PRNG\n    Underlying pseudorandom number generator.\n","base.random.cauchy.seed":"\nbase.random.cauchy.seed\n    Pseudorandom number generator seed.\n","base.random.cauchy.seedLength":"\nbase.random.cauchy.seedLength\n    Length of generator seed.\n","base.random.cauchy.state":"\nbase.random.cauchy.state\n    Generator state.\n","base.random.cauchy.stateLength":"\nbase.random.cauchy.stateLength\n    Length of generator state.\n","base.random.cauchy.byteLength":"\nbase.random.cauchy.byteLength\n    Size (in bytes) of generator state.\n","base.random.cauchy.toJSON":"\nbase.random.cauchy.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.chi":"\nbase.random.chi( k:number )\n    Returns a pseudorandom number drawn from a chi distribution.\n","base.random.chi.factory":"\nbase.random.chi.factory( [k:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a chi distribution.\n","base.random.chi.NAME":"\nbase.random.chi.NAME\n    Generator name.\n","base.random.chi.PRNG":"\nbase.random.chi.PRNG\n    Underlying pseudorandom number generator.\n","base.random.chi.seed":"\nbase.random.chi.seed\n    Pseudorandom number generator seed.\n","base.random.chi.seedLength":"\nbase.random.chi.seedLength\n    Length of generator seed.\n","base.random.chi.state":"\nbase.random.chi.state\n    Generator state.\n","base.random.chi.stateLength":"\nbase.random.chi.stateLength\n    Length of generator state.\n","base.random.chi.byteLength":"\nbase.random.chi.byteLength\n    Size (in bytes) of generator state.\n","base.random.chi.toJSON":"\nbase.random.chi.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.chisquare":"\nbase.random.chisquare( k:number )\n    Returns a pseudorandom number drawn from a chi-square distribution.\n","base.random.chisquare.factory":"\nbase.random.chisquare.factory( [k:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a chi-square distribution.\n","base.random.chisquare.NAME":"\nbase.random.chisquare.NAME\n    Generator name.\n","base.random.chisquare.PRNG":"\nbase.random.chisquare.PRNG\n    Underlying pseudorandom number generator.\n","base.random.chisquare.seed":"\nbase.random.chisquare.seed\n    Pseudorandom number generator seed.\n","base.random.chisquare.seedLength":"\nbase.random.chisquare.seedLength\n    Length of generator seed.\n","base.random.chisquare.state":"\nbase.random.chisquare.state\n    Generator state.\n","base.random.chisquare.stateLength":"\nbase.random.chisquare.stateLength\n    Length of generator state.\n","base.random.chisquare.byteLength":"\nbase.random.chisquare.byteLength\n    Size (in bytes) of generator state.\n","base.random.chisquare.toJSON":"\nbase.random.chisquare.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.cosine":"\nbase.random.cosine( μ:number, s:number )\n    Returns a pseudorandom number drawn from a raised cosine distribution.\n","base.random.cosine.factory":"\nbase.random.cosine.factory( [μ:number, s:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a raised cosine distribution.\n","base.random.cosine.NAME":"\nbase.random.cosine.NAME\n    Generator name.\n","base.random.cosine.PRNG":"\nbase.random.cosine.PRNG\n    Underlying pseudorandom number generator.\n","base.random.cosine.seed":"\nbase.random.cosine.seed\n    Pseudorandom number generator seed.\n","base.random.cosine.seedLength":"\nbase.random.cosine.seedLength\n    Length of generator seed.\n","base.random.cosine.state":"\nbase.random.cosine.state\n    Generator state.\n","base.random.cosine.stateLength":"\nbase.random.cosine.stateLength\n    Length of generator state.\n","base.random.cosine.byteLength":"\nbase.random.cosine.byteLength\n    Size (in bytes) of generator state.\n","base.random.cosine.toJSON":"\nbase.random.cosine.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.discreteUniform":"\nbase.random.discreteUniform( a:integer, b:integer )\n    Returns a pseudorandom number drawn from a discrete uniform distribution.\n","base.random.discreteUniform.factory":"\nbase.random.discreteUniform.factory( [a:integer, b:integer, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a discrete uniform distribution.\n","base.random.discreteUniform.NAME":"\nbase.random.discreteUniform.NAME\n    Generator name.\n","base.random.discreteUniform.PRNG":"\nbase.random.discreteUniform.PRNG\n    Underlying pseudorandom number generator.\n","base.random.discreteUniform.seed":"\nbase.random.discreteUniform.seed\n    Pseudorandom number generator seed.\n","base.random.discreteUniform.seedLength":"\nbase.random.discreteUniform.seedLength\n    Length of generator seed.\n","base.random.discreteUniform.state":"\nbase.random.discreteUniform.state\n    Generator state.\n","base.random.discreteUniform.stateLength":"\nbase.random.discreteUniform.stateLength\n    Length of generator state.\n","base.random.discreteUniform.byteLength":"\nbase.random.discreteUniform.byteLength\n    Size (in bytes) of generator state.\n","base.random.discreteUniform.toJSON":"\nbase.random.discreteUniform.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.erlang":"\nbase.random.erlang( k:integer, λ:number )\n    Returns a pseudorandom number drawn from an Erlang distribution.\n","base.random.erlang.factory":"\nbase.random.erlang.factory( [k:integer, λ:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an Erlang distribution.\n","base.random.erlang.NAME":"\nbase.random.erlang.NAME\n    Generator name.\n","base.random.erlang.PRNG":"\nbase.random.erlang.PRNG\n    Underlying pseudorandom number generator.\n","base.random.erlang.seed":"\nbase.random.erlang.seed\n    Pseudorandom number generator seed.\n","base.random.erlang.seedLength":"\nbase.random.erlang.seedLength\n    Length of generator seed.\n","base.random.erlang.state":"\nbase.random.erlang.state\n    Generator state.\n","base.random.erlang.stateLength":"\nbase.random.erlang.stateLength\n    Length of generator state.\n","base.random.erlang.byteLength":"\nbase.random.erlang.byteLength\n    Size (in bytes) of generator state.\n","base.random.erlang.toJSON":"\nbase.random.erlang.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.exponential":"\nbase.random.exponential( λ:number )\n    Returns a pseudorandom number drawn from an exponential distribution.\n","base.random.exponential.factory":"\nbase.random.exponential.factory( [λ:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an exponential distribution.\n","base.random.exponential.NAME":"\nbase.random.exponential.NAME\n    Generator name.\n","base.random.exponential.PRNG":"\nbase.random.exponential.PRNG\n    Underlying pseudorandom number generator.\n","base.random.exponential.seed":"\nbase.random.exponential.seed\n    Pseudorandom number generator seed.\n","base.random.exponential.seedLength":"\nbase.random.exponential.seedLength\n    Length of generator seed.\n","base.random.exponential.state":"\nbase.random.exponential.state\n    Generator state.\n","base.random.exponential.stateLength":"\nbase.random.exponential.stateLength\n    Length of generator state.\n","base.random.exponential.byteLength":"\nbase.random.exponential.byteLength\n    Size (in bytes) of generator state.\n","base.random.exponential.toJSON":"\nbase.random.exponential.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.f":"\nbase.random.f( d1:number, d2:number )\n    Returns a pseudorandom number drawn from an F distribution.\n","base.random.f.factory":"\nbase.random.f.factory( [d1:number, d2:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an F distribution.\n","base.random.f.NAME":"\nbase.random.f.NAME\n    Generator name.\n","base.random.f.PRNG":"\nbase.random.f.PRNG\n    Underlying pseudorandom number generator.\n","base.random.f.seed":"\nbase.random.f.seed\n    Pseudorandom number generator seed.\n","base.random.f.seedLength":"\nbase.random.f.seedLength\n    Length of generator seed.\n","base.random.f.state":"\nbase.random.f.state\n    Generator state.\n","base.random.f.stateLength":"\nbase.random.f.stateLength\n    Length of generator state.\n","base.random.f.byteLength":"\nbase.random.f.byteLength\n    Size (in bytes) of generator state.\n","base.random.f.toJSON":"\nbase.random.f.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.frechet":"\nbase.random.frechet( α:number, s:number, m:number )\n    Returns a pseudorandom number drawn from a Fréchet distribution.\n","base.random.frechet.factory":"\nbase.random.frechet.factory( [α:number, s:number, m:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a triangular distribution.\n","base.random.frechet.NAME":"\nbase.random.frechet.NAME\n    Generator name.\n","base.random.frechet.PRNG":"\nbase.random.frechet.PRNG\n    Underlying pseudorandom number generator.\n","base.random.frechet.seed":"\nbase.random.frechet.seed\n    Pseudorandom number generator seed.\n","base.random.frechet.seedLength":"\nbase.random.frechet.seedLength\n    Length of generator seed.\n","base.random.frechet.state":"\nbase.random.frechet.state\n    Generator state.\n","base.random.frechet.stateLength":"\nbase.random.frechet.stateLength\n    Length of generator state.\n","base.random.frechet.byteLength":"\nbase.random.frechet.byteLength\n    Size (in bytes) of generator state.\n","base.random.frechet.toJSON":"\nbase.random.frechet.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.gamma":"\nbase.random.gamma( α:number, β:number )\n    Returns a pseudorandom number drawn from a gamma distribution.\n","base.random.gamma.factory":"\nbase.random.gamma.factory( [α:number, β:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a gamma distribution.\n","base.random.gamma.NAME":"\nbase.random.gamma.NAME\n    Generator name.\n","base.random.gamma.PRNG":"\nbase.random.gamma.PRNG\n    Underlying pseudorandom number generator.\n","base.random.gamma.seed":"\nbase.random.gamma.seed\n    Pseudorandom number generator seed.\n","base.random.gamma.seedLength":"\nbase.random.gamma.seedLength\n    Length of generator seed.\n","base.random.gamma.state":"\nbase.random.gamma.state\n    Generator state.\n","base.random.gamma.stateLength":"\nbase.random.gamma.stateLength\n    Length of generator state.\n","base.random.gamma.byteLength":"\nbase.random.gamma.byteLength\n    Size of generator state.\n","base.random.gamma.toJSON":"\nbase.random.gamma.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.geometric":"\nbase.random.geometric( p:number )\n    Returns a pseudorandom number drawn from a geometric distribution.\n","base.random.geometric.factory":"\nbase.random.geometric.factory( [p:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a geometric distribution.\n","base.random.geometric.NAME":"\nbase.random.geometric.NAME\n    Generator name.\n","base.random.geometric.PRNG":"\nbase.random.geometric.PRNG\n    Underlying pseudorandom number generator.\n","base.random.geometric.seed":"\nbase.random.geometric.seed\n    Pseudorandom number generator seed.\n","base.random.geometric.seedLength":"\nbase.random.geometric.seedLength\n    Length of generator seed.\n","base.random.geometric.state":"\nbase.random.geometric.state\n    Generator state.\n","base.random.geometric.stateLength":"\nbase.random.geometric.stateLength\n    Length of generator state.\n","base.random.geometric.byteLength":"\nbase.random.geometric.byteLength\n    Size (in bytes) of generator state.\n","base.random.geometric.toJSON":"\nbase.random.geometric.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.gumbel":"\nbase.random.gumbel( μ:number, β:number )\n    Returns a pseudorandom number drawn from a Gumbel distribution.\n","base.random.gumbel.factory":"\nbase.random.gumbel.factory( [μ:number, β:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Gumbel distribution.\n","base.random.gumbel.NAME":"\nbase.random.gumbel.NAME\n    Generator name.\n","base.random.gumbel.PRNG":"\nbase.random.gumbel.PRNG\n    Underlying pseudorandom number generator.\n","base.random.gumbel.seed":"\nbase.random.gumbel.seed\n    Pseudorandom number generator seed.\n","base.random.gumbel.seedLength":"\nbase.random.gumbel.seedLength\n    Length of generator seed.\n","base.random.gumbel.state":"\nbase.random.gumbel.state\n    Generator state.\n","base.random.gumbel.stateLength":"\nbase.random.gumbel.stateLength\n    Length of generator state.\n","base.random.gumbel.byteLength":"\nbase.random.gumbel.byteLength\n    Size (in bytes) of generator state.\n","base.random.gumbel.toJSON":"\nbase.random.gumbel.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.hypergeometric":"\nbase.random.hypergeometric( N:integer, K:integer, n:integer )\n    Returns a pseudorandom number drawn from a hypergeometric distribution.\n","base.random.hypergeometric.factory":"\nbase.random.hypergeometric.factory( [N:integer, K:integer, n:integer, ]\n  [options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a hypergeometric distribution.\n","base.random.hypergeometric.NAME":"\nbase.random.hypergeometric.NAME\n    Generator name.\n","base.random.hypergeometric.PRNG":"\nbase.random.hypergeometric.PRNG\n    Underlying pseudorandom number generator.\n","base.random.hypergeometric.seed":"\nbase.random.hypergeometric.seed\n    Pseudorandom number generator seed.\n","base.random.hypergeometric.seedLength":"\nbase.random.hypergeometric.seedLength\n    Length of generator seed.\n","base.random.hypergeometric.state":"\nbase.random.hypergeometric.state\n    Generator state.\n","base.random.hypergeometric.stateLength":"\nbase.random.hypergeometric.stateLength\n    Length of generator state.\n","base.random.hypergeometric.byteLength":"\nbase.random.hypergeometric.byteLength\n    Size (in bytes) of generator state.\n","base.random.hypergeometric.toJSON":"\nbase.random.hypergeometric.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.improvedZiggurat":"\nbase.random.improvedZiggurat()\n    Returns a pseudorandom number drawn from a standard normal distribution.\n","base.random.improvedZiggurat.factory":"\nbase.random.improvedZiggurat.factory( [options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a standard normal distribution.\n","base.random.improvedZiggurat.NAME":"\nbase.random.improvedZiggurat.NAME\n    Generator name.\n","base.random.improvedZiggurat.PRNG":"\nbase.random.improvedZiggurat.PRNG\n    Underlying pseudorandom number generator.\n","base.random.improvedZiggurat.seed":"\nbase.random.improvedZiggurat.seed\n    Pseudorandom number generator seed.\n","base.random.improvedZiggurat.seedLength":"\nbase.random.improvedZiggurat.seedLength\n    Length of generator seed.\n","base.random.improvedZiggurat.state":"\nbase.random.improvedZiggurat.state\n    Generator state.\n","base.random.improvedZiggurat.stateLength":"\nbase.random.improvedZiggurat.stateLength\n    Length of generator state.\n","base.random.improvedZiggurat.byteLength":"\nbase.random.improvedZiggurat.byteLength\n    Size (in bytes) of generator state.\n","base.random.improvedZiggurat.toJSON":"\nbase.random.improvedZiggurat.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.invgamma":"\nbase.random.invgamma( α:number, β:number )\n    Returns a pseudorandom number drawn from an inverse gamma distribution.\n","base.random.invgamma.factory":"\nbase.random.invgamma.factory( [α:number, β:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an inverse gamma distribution.\n","base.random.invgamma.NAME":"\nbase.random.invgamma.NAME\n    Generator name.\n","base.random.invgamma.PRNG":"\nbase.random.invgamma.PRNG\n    Underlying pseudorandom number generator.\n","base.random.invgamma.seed":"\nbase.random.invgamma.seed\n    Pseudorandom number generator seed.\n","base.random.invgamma.seedLength":"\nbase.random.invgamma.seedLength\n    Length of generator seed.\n","base.random.invgamma.state":"\nbase.random.invgamma.state\n    Generator state.\n","base.random.invgamma.stateLength":"\nbase.random.invgamma.stateLength\n    Length of generator state.\n","base.random.invgamma.byteLength":"\nbase.random.invgamma.byteLength\n    Size of generator state.\n","base.random.invgamma.toJSON":"\nbase.random.invgamma.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.kumaraswamy":"\nbase.random.kumaraswamy( a:number, b:number )\n    Returns a pseudorandom number drawn from Kumaraswamy's double bounded\n    distribution.\n","base.random.kumaraswamy.factory":"\nbase.random.kumaraswamy.factory( [a:number, b:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from Kumaraswamy's double bounded distribution.\n","base.random.kumaraswamy.NAME":"\nbase.random.kumaraswamy.NAME\n    Generator name.\n","base.random.kumaraswamy.PRNG":"\nbase.random.kumaraswamy.PRNG\n    Underlying pseudorandom number generator.\n","base.random.kumaraswamy.seed":"\nbase.random.kumaraswamy.seed\n    Pseudorandom number generator seed.\n","base.random.kumaraswamy.seedLength":"\nbase.random.kumaraswamy.seedLength\n    Length of generator seed.\n","base.random.kumaraswamy.state":"\nbase.random.kumaraswamy.state\n    Generator state.\n","base.random.kumaraswamy.stateLength":"\nbase.random.kumaraswamy.stateLength\n    Length of generator state.\n","base.random.kumaraswamy.byteLength":"\nbase.random.kumaraswamy.byteLength\n    Size (in bytes) of generator state.\n","base.random.kumaraswamy.toJSON":"\nbase.random.kumaraswamy.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.laplace":"\nbase.random.laplace( μ:number, b:number )\n    Returns a pseudorandom number drawn from a Laplace distribution.\n","base.random.laplace.factory":"\nbase.random.laplace.factory( [μ:number, b:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Laplace distribution.\n","base.random.laplace.NAME":"\nbase.random.laplace.NAME\n    Generator name.\n","base.random.laplace.PRNG":"\nbase.random.laplace.PRNG\n    Underlying pseudorandom number generator.\n","base.random.laplace.seed":"\nbase.random.laplace.seed\n    Pseudorandom number generator seed.\n","base.random.laplace.seedLength":"\nbase.random.laplace.seedLength\n    Length of generator seed.\n","base.random.laplace.state":"\nbase.random.laplace.state\n    Generator state.\n","base.random.laplace.stateLength":"\nbase.random.laplace.stateLength\n    Length of generator state.\n","base.random.laplace.byteLength":"\nbase.random.laplace.byteLength\n    Size (in bytes) of generator state.\n","base.random.laplace.toJSON":"\nbase.random.laplace.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.levy":"\nbase.random.levy( μ:number, c:number )\n    Returns a pseudorandom number drawn from a Lévy distribution.\n","base.random.levy.factory":"\nbase.random.levy.factory( [μ:number, c:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Lévy distribution.\n","base.random.levy.NAME":"\nbase.random.levy.NAME\n    Generator name.\n","base.random.levy.PRNG":"\nbase.random.levy.PRNG\n    Underlying pseudorandom number generator.\n","base.random.levy.seed":"\nbase.random.levy.seed\n    Pseudorandom number generator seed.\n","base.random.levy.seedLength":"\nbase.random.levy.seedLength\n    Length of generator seed.\n","base.random.levy.state":"\nbase.random.levy.state\n    Generator state.\n","base.random.levy.stateLength":"\nbase.random.levy.stateLength\n    Length of generator state.\n","base.random.levy.byteLength":"\nbase.random.levy.byteLength\n    Size (in bytes) of generator state.\n","base.random.levy.toJSON":"\nbase.random.levy.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.logistic":"\nbase.random.logistic( μ:number, s:number )\n    Returns a pseudorandom number drawn from a logistic distribution.\n","base.random.logistic.factory":"\nbase.random.logistic.factory( [μ:number, s:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a logistic distribution.\n","base.random.logistic.NAME":"\nbase.random.logistic.NAME\n    Generator name.\n","base.random.logistic.PRNG":"\nbase.random.logistic.PRNG\n    Underlying pseudorandom number generator.\n","base.random.logistic.seed":"\nbase.random.logistic.seed\n    Pseudorandom number generator seed.\n","base.random.logistic.seedLength":"\nbase.random.logistic.seedLength\n    Length of generator seed.\n","base.random.logistic.state":"\nbase.random.logistic.state\n    Generator state.\n","base.random.logistic.stateLength":"\nbase.random.logistic.stateLength\n    Length of generator state.\n","base.random.logistic.byteLength":"\nbase.random.logistic.byteLength\n    Size (in bytes) of generator state.\n","base.random.logistic.toJSON":"\nbase.random.logistic.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.lognormal":"\nbase.random.lognormal( μ:number, σ:number )\n    Returns a pseudorandom number drawn from a lognormal distribution.\n","base.random.lognormal.factory":"\nbase.random.lognormal.factory( [μ:number, σ:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a lognormal distribution.\n","base.random.lognormal.NAME":"\nbase.random.lognormal.NAME\n    Generator name.\n","base.random.lognormal.PRNG":"\nbase.random.lognormal.PRNG\n    Underlying pseudorandom number generator.\n","base.random.lognormal.seed":"\nbase.random.lognormal.seed\n    Pseudorandom number generator seed.\n","base.random.lognormal.seedLength":"\nbase.random.lognormal.seedLength\n    Length of generator seed.\n","base.random.lognormal.state":"\nbase.random.lognormal.state\n    Generator state.\n","base.random.lognormal.stateLength":"\nbase.random.lognormal.stateLength\n    Length of generator state.\n","base.random.lognormal.byteLength":"\nbase.random.lognormal.byteLength\n    Size (in bytes) of generator state.\n","base.random.lognormal.toJSON":"\nbase.random.lognormal.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.minstd":"\nbase.random.minstd()\n    Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n","base.random.minstd.normalized":"\nbase.random.minstd.normalized()\n    Returns a pseudorandom number on the interval `[0,1)`.\n","base.random.minstd.factory":"\nbase.random.minstd.factory( [options:Object] )\n    Returns a linear congruential pseudorandom number generator (LCG).\n","base.random.minstd.NAME":"\nbase.random.minstd.NAME\n    Generator name.\n","base.random.minstd.MIN":"\nbase.random.minstd.MIN\n    Minimum possible value.\n","base.random.minstd.MAX":"\nbase.random.minstd.MAX\n    Maximum possible value.\n","base.random.minstd.seed":"\nbase.random.minstd.seed\n    Pseudorandom number generator seed.\n","base.random.minstd.seedLength":"\nbase.random.minstd.seedLength\n    Length of generator seed.\n","base.random.minstd.state":"\nbase.random.minstd.state\n    Generator state.\n","base.random.minstd.stateLength":"\nbase.random.minstd.stateLength\n    Length of generator state.\n","base.random.minstd.byteLength":"\nbase.random.minstd.byteLength\n    Size (in bytes) of generator state.\n","base.random.minstd.toJSON":"\nbase.random.minstd.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.minstdShuffle":"\nbase.random.minstdShuffle()\n    Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n","base.random.minstdShuffle.normalized":"\nbase.random.minstdShuffle.normalized()\n    Returns a pseudorandom number on the interval `[0,1)`.\n","base.random.minstdShuffle.factory":"\nbase.random.minstdShuffle.factory( [options:Object] )\n    Returns a linear congruential pseudorandom number generator (LCG) whose\n    output is shuffled.\n","base.random.minstdShuffle.NAME":"\nbase.random.minstdShuffle.NAME\n    Generator name.\n","base.random.minstdShuffle.MIN":"\nbase.random.minstdShuffle.MIN\n    Minimum possible value.\n","base.random.minstdShuffle.MAX":"\nbase.random.minstdShuffle.MAX\n    Maximum possible value.\n","base.random.minstdShuffle.seed":"\nbase.random.minstdShuffle.seed\n    Pseudorandom number generator seed.\n","base.random.minstdShuffle.seedLength":"\nbase.random.minstdShuffle.seedLength\n    Length of generator seed.\n","base.random.minstdShuffle.state":"\nbase.random.minstdShuffle.state\n    Generator state.\n","base.random.minstdShuffle.stateLength":"\nbase.random.minstdShuffle.stateLength\n    Length of generator state.\n","base.random.minstdShuffle.byteLength":"\nbase.random.minstdShuffle.byteLength\n    Size (in bytes) of generator state.\n","base.random.minstdShuffle.toJSON":"\nbase.random.minstdShuffle.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.mt19937":"\nbase.random.mt19937()\n    Returns a pseudorandom integer on the interval `[0, 4294967295]`.\n","base.random.mt19937.normalized":"\nbase.random.mt19937.normalized()\n    Returns a pseudorandom number on the interval `[0,1)` with 53-bit precision.\n","base.random.mt19937.factory":"\nbase.random.mt19937.factory( [options:Object] )\n    Returns a 32-bit Mersenne Twister pseudorandom number generator.\n","base.random.mt19937.NAME":"\nbase.random.mt19937.NAME\n    Generator name.\n","base.random.mt19937.MIN":"\nbase.random.mt19937.MIN\n    Minimum possible value.\n","base.random.mt19937.MAX":"\nbase.random.mt19937.MAX\n    Maximum possible value.\n","base.random.mt19937.seed":"\nbase.random.mt19937.seed\n    Pseudorandom number generator seed.\n","base.random.mt19937.seedLength":"\nbase.random.mt19937.seedLength\n    Length of generator seed.\n","base.random.mt19937.state":"\nbase.random.mt19937.state\n    Generator state.\n","base.random.mt19937.stateLength":"\nbase.random.mt19937.stateLength\n    Length of generator state.\n","base.random.mt19937.byteLength":"\nbase.random.mt19937.byteLength\n    Size (in bytes) of generator state.\n","base.random.mt19937.toJSON":"\nbase.random.mt19937.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.negativeBinomial":"\nbase.random.negativeBinomial( r:number, p:number )\n    Returns a pseudorandom number drawn from a negative binomial distribution.\n","base.random.negativeBinomial.factory":"\nbase.random.negativeBinomial.factory( [r:number, p:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a negative binomial distribution.\n","base.random.negativeBinomial.NAME":"\nbase.random.negativeBinomial.NAME\n    Generator name.\n","base.random.negativeBinomial.PRNG":"\nbase.random.negativeBinomial.PRNG\n    Underlying pseudorandom number generator.\n","base.random.negativeBinomial.seed":"\nbase.random.negativeBinomial.seed\n    Pseudorandom number generator seed.\n","base.random.negativeBinomial.seedLength":"\nbase.random.negativeBinomial.seedLength\n    Length of generator seed.\n","base.random.negativeBinomial.state":"\nbase.random.negativeBinomial.state\n    Generator state.\n","base.random.negativeBinomial.stateLength":"\nbase.random.negativeBinomial.stateLength\n    Length of generator state.\n","base.random.negativeBinomial.byteLength":"\nbase.random.negativeBinomial.byteLength\n    Size (in bytes) of generator state.\n","base.random.negativeBinomial.toJSON":"\nbase.random.negativeBinomial.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.normal":"\nbase.random.normal( μ:number, σ:number )\n    Returns a pseudorandom number drawn from a normal distribution.\n","base.random.normal.factory":"\nbase.random.normal.factory( [μ:number, σ:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a normal distribution.\n","base.random.normal.NAME":"\nbase.random.normal.NAME\n    Generator name.\n","base.random.normal.PRNG":"\nbase.random.normal.PRNG\n    Underlying pseudorandom number generator.\n","base.random.normal.seed":"\nbase.random.normal.seed\n    Pseudorandom number generator seed.\n","base.random.normal.seedLength":"\nbase.random.normal.seedLength\n    Length of generator seed.\n","base.random.normal.state":"\nbase.random.normal.state\n    Generator state.\n","base.random.normal.stateLength":"\nbase.random.normal.stateLength\n    Length of generator state.\n","base.random.normal.byteLength":"\nbase.random.normal.byteLength\n    Size of generator state.\n","base.random.normal.toJSON":"\nbase.random.normal.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.pareto1":"\nbase.random.pareto1( α:number, β:number )\n    Returns a pseudorandom number drawn from a Pareto (Type I) distribution.\n","base.random.pareto1.factory":"\nbase.random.pareto1.factory( [α:number, β:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Pareto (Type I) distribution.\n","base.random.pareto1.NAME":"\nbase.random.pareto1.NAME\n    Generator name.\n","base.random.pareto1.PRNG":"\nbase.random.pareto1.PRNG\n    Underlying pseudorandom number generator.\n","base.random.pareto1.seed":"\nbase.random.pareto1.seed\n    Pseudorandom number generator seed.\n","base.random.pareto1.seedLength":"\nbase.random.pareto1.seedLength\n    Length of generator seed.\n","base.random.pareto1.state":"\nbase.random.pareto1.state\n    Generator state.\n","base.random.pareto1.stateLength":"\nbase.random.pareto1.stateLength\n    Length of generator state.\n","base.random.pareto1.byteLength":"\nbase.random.pareto1.byteLength\n    Size (in bytes) of generator state.\n","base.random.pareto1.toJSON":"\nbase.random.pareto1.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.poisson":"\nbase.random.poisson( λ:number )\n    Returns a pseudorandom number drawn from a Poisson distribution.\n","base.random.poisson.factory":"\nbase.random.poisson.factory( [λ:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Poisson distribution.\n","base.random.poisson.NAME":"\nbase.random.poisson.NAME\n    Generator name.\n","base.random.poisson.PRNG":"\nbase.random.poisson.PRNG\n    Underlying pseudorandom number generator.\n","base.random.poisson.seed":"\nbase.random.poisson.seed\n    Pseudorandom number generator seed.\n","base.random.poisson.seedLength":"\nbase.random.poisson.seedLength\n    Length of generator seed.\n","base.random.poisson.state":"\nbase.random.poisson.state\n    Generator state.\n","base.random.poisson.stateLength":"\nbase.random.poisson.stateLength\n    Length of generator state.\n","base.random.poisson.byteLength":"\nbase.random.poisson.byteLength\n    Size (in bytes) of generator state.\n","base.random.poisson.toJSON":"\nbase.random.poisson.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.randi":"\nbase.random.randi()\n    Returns a pseudorandom number having an integer value.\n","base.random.randi.factory":"\nbase.random.randi.factory( [options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers having integer values.\n","base.random.randi.NAME":"\nbase.random.randi.NAME\n    Generator name.\n","base.random.randi.PRNG":"\nbase.random.randi.PRNG\n    Underlying pseudorandom number generator.\n","base.random.randi.MIN":"\nbase.random.randi.MIN\n    Minimum possible value (specific to underlying PRNG).\n","base.random.randi.MAX":"\nbase.random.randi.MAX\n    Maximum possible value (specific to underlying PRNG).\n","base.random.randi.seed":"\nbase.random.randi.seed\n    Pseudorandom number generator seed.\n","base.random.randi.seedLength":"\nbase.random.randi.seedLength\n    Length of generator seed.\n","base.random.randi.state":"\nbase.random.randi.state\n    Generator state.\n","base.random.randi.stateLength":"\nbase.random.randi.stateLength\n    Length of generator state.\n","base.random.randi.byteLength":"\nbase.random.randi.byteLength\n    Size (in bytes) of generator state.\n","base.random.randi.toJSON":"\nbase.random.randi.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.randn":"\nbase.random.randn()\n    Returns a pseudorandom number drawn from a standard normal distribution.\n","base.random.randn.factory":"\nbase.random.randn.factory( [options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a standard normal distribution.\n","base.random.randn.NAME":"\nbase.random.randn.NAME\n    Generator name.\n","base.random.randn.PRNG":"\nbase.random.randn.PRNG\n    Underlying pseudorandom number generator.\n","base.random.randn.seed":"\nbase.random.randn.seed\n    Pseudorandom number generator seed.\n","base.random.randn.seedLength":"\nbase.random.randn.seedLength\n    Length of generator seed.\n","base.random.randn.state":"\nbase.random.randn.state\n    Generator state.\n","base.random.randn.stateLength":"\nbase.random.randn.stateLength\n    Length of generator state.\n","base.random.randn.byteLength":"\nbase.random.randn.byteLength\n    Size (in bytes) of generator state.\n","base.random.randn.toJSON":"\nbase.random.randn.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.randu":"\nbase.random.randu()\n    Returns a pseudorandom number drawn from a uniform distribution.\n","base.random.randu.factory":"\nbase.random.randu.factory( [options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a uniform distribution.\n","base.random.randu.NAME":"\nbase.random.randu.NAME\n    Generator name.\n","base.random.randu.PRNG":"\nbase.random.randu.PRNG\n    Underlying pseudorandom number generator.\n","base.random.randu.MIN":"\nbase.random.randu.MIN\n    Minimum possible value (specific to underlying PRNG).\n","base.random.randu.MAX":"\nbase.random.randu.MAX\n    Maximum possible value (specific to underlying PRNG).\n","base.random.randu.seed":"\nbase.random.randu.seed\n    Pseudorandom number generator seed.\n","base.random.randu.seedLength":"\nbase.random.randu.seedLength\n    Length of generator seed.\n","base.random.randu.state":"\nbase.random.randu.state\n    Generator state.\n","base.random.randu.stateLength":"\nbase.random.randu.stateLength\n    Length of generator state.\n","base.random.randu.byteLength":"\nbase.random.randu.byteLength\n    Size (in bytes) of generator state.\n","base.random.randu.toJSON":"\nbase.random.randu.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.rayleigh":"\nbase.random.rayleigh( σ:number )\n    Returns a pseudorandom number drawn from a Rayleigh distribution.\n","base.random.rayleigh.factory":"\nbase.random.rayleigh.factory( [σ:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Rayleigh distribution.\n","base.random.rayleigh.NAME":"\nbase.random.rayleigh.NAME\n    Generator name.\n","base.random.rayleigh.PRNG":"\nbase.random.rayleigh.PRNG\n    Underlying pseudorandom number generator.\n","base.random.rayleigh.seed":"\nbase.random.rayleigh.seed\n    Pseudorandom number generator seed.\n","base.random.rayleigh.seedLength":"\nbase.random.rayleigh.seedLength\n    Length of generator seed.\n","base.random.rayleigh.state":"\nbase.random.rayleigh.state\n    Generator state.\n","base.random.rayleigh.stateLength":"\nbase.random.rayleigh.stateLength\n    Length of generator state.\n","base.random.rayleigh.byteLength":"\nbase.random.rayleigh.byteLength\n    Size (in bytes) of generator state.\n","base.random.rayleigh.toJSON":"\nbase.random.rayleigh.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.t":"\nbase.random.t( v:number )\n    Returns a pseudorandom number drawn from a Student's t distribution.\n","base.random.t.factory":"\nbase.random.t.factory( [v:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Student's t distribution.\n","base.random.t.NAME":"\nbase.random.t.NAME\n    Generator name.\n","base.random.t.PRNG":"\nbase.random.t.PRNG\n    Underlying pseudorandom number generator.\n","base.random.t.seed":"\nbase.random.t.seed\n    Pseudorandom number generator seed.\n","base.random.t.seedLength":"\nbase.random.t.seedLength\n    Length of generator seed.\n","base.random.t.state":"\nbase.random.t.state\n    Generator state.\n","base.random.t.stateLength":"\nbase.random.t.stateLength\n    Length of generator state.\n","base.random.t.byteLength":"\nbase.random.t.byteLength\n    Size (in bytes) of generator state.\n","base.random.t.toJSON":"\nbase.random.t.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.triangular":"\nbase.random.triangular( a:number, b:number, c:number )\n    Returns a pseudorandom number drawn from a triangular distribution.\n","base.random.triangular.factory":"\nbase.random.triangular.factory( [a:number, b:number, c:number, ]\n  [options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a triangular distribution.\n","base.random.triangular.NAME":"\nbase.random.triangular.NAME\n    Generator name.\n","base.random.triangular.PRNG":"\nbase.random.triangular.PRNG\n    Underlying pseudorandom number generator.\n","base.random.triangular.seed":"\nbase.random.triangular.seed\n    Pseudorandom number generator seed.\n","base.random.triangular.seedLength":"\nbase.random.triangular.seedLength\n    Length of generator seed.\n","base.random.triangular.state":"\nbase.random.triangular.state\n    Generator state.\n","base.random.triangular.stateLength":"\nbase.random.triangular.stateLength\n    Length of generator state.\n","base.random.triangular.byteLength":"\nbase.random.triangular.byteLength\n    Size (in bytes) of generator state.\n","base.random.triangular.toJSON":"\nbase.random.triangular.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.uniform":"\nbase.random.uniform( a:number, b:number )\n    Returns a pseudorandom number drawn from a continuous uniform distribution.\n","base.random.uniform.factory":"\nbase.random.uniform.factory( [a:number, b:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a continuous uniform distribution.\n","base.random.uniform.NAME":"\nbase.random.uniform.NAME\n    Generator name.\n","base.random.uniform.PRNG":"\nbase.random.uniform.PRNG\n    Underlying pseudorandom number generator.\n","base.random.uniform.seed":"\nbase.random.uniform.seed\n    Pseudorandom number generator seed.\n","base.random.uniform.seedLength":"\nbase.random.uniform.seedLength\n    Length of generator seed.\n","base.random.uniform.state":"\nbase.random.uniform.state\n    Generator state.\n","base.random.uniform.stateLength":"\nbase.random.uniform.stateLength\n    Length of generator state.\n","base.random.uniform.byteLength":"\nbase.random.uniform.byteLength\n    Size (in bytes) of generator state.\n","base.random.uniform.toJSON":"\nbase.random.uniform.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.weibull":"\nbase.random.weibull( k:number, λ:number )\n    Returns a pseudorandom number drawn from a Weibull distribution.\n","base.random.weibull.factory":"\nbase.random.weibull.factory( [k:number, λ:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Weibull distribution.\n","base.random.weibull.NAME":"\nbase.random.weibull.NAME\n    Generator name.\n","base.random.weibull.PRNG":"\nbase.random.weibull.PRNG\n    Underlying pseudorandom number generator.\n","base.random.weibull.seed":"\nbase.random.weibull.seed\n    Pseudorandom number generator seed.\n","base.random.weibull.seedLength":"\nbase.random.weibull.seedLength\n    Length of generator seed.\n","base.random.weibull.state":"\nbase.random.weibull.state\n    Generator state.\n","base.random.weibull.stateLength":"\nbase.random.weibull.stateLength\n    Length of generator state.\n","base.random.weibull.byteLength":"\nbase.random.weibull.byteLength\n    Size (in bytes) of generator state.\n","base.random.weibull.toJSON":"\nbase.random.weibull.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.rcbrt":"\nbase.rcbrt( x:number )\n    Computes the reciprocal cube root of a double-precision floating-point\n    number.\n","base.rcbrtf":"\nbase.rcbrtf( x:number )\n    Computes the reciprocal cube root of a single-precision floating-point\n    number.\n","base.reldiff":"\nbase.reldiff( x:number, y:number[, scale:string|Function] )\n    Computes the relative difference of two real numbers.\n","base.removeFirst":"\nbase.removeFirst( str:string, n:integer )\n    Removes the first `n` UTF-16 code units of a string.\n","base.removeFirstCodePoint":"\nbase.removeFirstCodePoint( str:string, n:integer )\n    Removes the first `n` Unicode code points of a string.\n","base.removeFirstGraphemeCluster":"\nbase.removeFirstGraphemeCluster( str:string, n:integer )\n    Removes the first `n` grapheme clusters (i.e., user-perceived characters)\n    of a string.\n","base.removeLast":"\nbase.removeLast( str:string, n:integer )\n    Removes the last `n` UTF-16 code units of a string.\n","base.removeLastCodePoint":"\nbase.removeLastCodePoint( str:string, n:integer )\n    Removes the last `n` Unicode code points of a string.\n","base.removeLastGraphemeCluster":"\nbase.removeLastGraphemeCluster( str:string, n:integer )\n    Removes the last `n` grapheme clusters (i.e., user-perceived characters)\n    of a string.\n","base.rempio2":"\nbase.rempio2( x:number, y:Array|TypedArray|Object )\n    Computes `x - nπ/2 = r`.\n","base.repeat":"\nbase.repeat( str:string, n:integer )\n    Repeats a string `n` times and returns the concatenated result.\n","base.replace":"\nbase.replace( str:string, search:RegExp, newval:string|Function )\n    Replaces search occurrences with a replacement string.\n","base.replaceAfter":"\nbase.replaceAfter( str:string, search:string, replacement:string, \n  fromIndex:integer )\n    Replaces the substring after the first occurrence of a specified search\n    string.\n","base.replaceAfterLast":"\nbase.replaceAfterLast( str:string, search:string, replacement:string, \n  fromIndex:integer )\n    Replaces the substring after the last occurrence of a specified search\n    string.\n","base.replaceBefore":"\nbase.replaceBefore( str:string, search:string, replacement:string, \n  fromIndex:integer )\n    Replaces the substring before the first occurrence of a specified search\n    string.\n","base.replaceBeforeLast":"\nbase.replaceBeforeLast( str:string, search:string, replacement:string, \n  fromIndex:integer )\n    Replaces the substring before the last occurrence of a specified search\n    string.\n","base.reverse":"\nbase.reverse( str:string )\n    Reverses the UTF-16 code units of a string.\n","base.reverseCodePoints":"\nbase.reverseCodePoints( str:string )\n    Reverses the Unicode code points of a string.\n","base.reverseGraphemeClusters":"\nbase.reverseGraphemeClusters( str:string )\n    Reverses the grapheme clusters (i.e., user-perceived characters) of a\n    string.\n","base.rightPad":"\nbase.rightPad( str:string, len:integer, pad:string )\n    Right pads a string such that the padded string has a length of at least\n    `len`.\n","base.rightTrim":"\nbase.rightTrim( str:string )\n    Trims whitespace from the end of a string.\n","base.risingFactorial":"\nbase.risingFactorial( x:number, n:integer )\n    Computes the rising factorial of `x` and `n`.\n","base.rotl32":"\nbase.rotl32( x:integer, shift:integer )\n    Performs a bitwise rotation to the left.\n","base.rotr32":"\nbase.rotr32( x:integer, shift:integer )\n    Performs a bitwise rotation to the right.\n","base.round":"\nbase.round( x:number )\n    Rounds a numeric value to the nearest integer.\n","base.round2":"\nbase.round2( x:number )\n    Rounds a numeric value to the nearest power of two on a linear scale.\n","base.round10":"\nbase.round10( x:number )\n    Rounds a numeric value to the nearest power of ten on a linear scale.\n","base.roundb":"\nbase.roundb( x:number, n:integer, b:integer )\n    Rounds a numeric value to the nearest multiple of `b^n` on a linear scale.\n","base.roundn":"\nbase.roundn( x:number, n:integer )\n    Rounds a numeric value to the nearest multiple of `10^n`.\n","base.roundsd":"\nbase.roundsd( x:number, n:integer[, b:integer] )\n    Rounds a numeric value to the nearest number with `n` significant figures.\n","base.rsqrt":"\nbase.rsqrt( x:number )\n    Computes the reciprocal square root of a double-precision floating-point\n    number.\n","base.rsqrtf":"\nbase.rsqrtf( x:number )\n    Computes the reciprocal square root of a single-precision floating-point\n    number.\n","base.sargs2multislice":"\nbase.sargs2multislice( str:string )\n    Creates a MultiSlice object from a comma-separated list of string-serialized\n    MultiSlice constructor arguments.\n","base.scalar2ndarray":"\nbase.scalar2ndarray( value:any, dtype:string, order:string )\n    Returns a zero-dimensional ndarray containing a provided scalar value.\n","base.secd":"\nbase.secd( x:number )\n    Computes the secant of an angle measured in degrees.\n","base.seq2multislice":"\nbase.seq2multislice( str:string, shape:Array<integer>, strict:boolean )\n    Converts a multidimensional subsequence string to a MultiSlice object.\n","base.seq2slice":"\nbase.seq2slice( str:string, len:integer, strict:boolean )\n    Converts a subsequence string to a Slice object.\n","base.setHighWord":"\nbase.setHighWord( x:number, high:integer )\n    Sets the more significant 32 bits of a double-precision floating-point\n    number.\n","base.setLowWord":"\nbase.setLowWord( x:number, low:integer )\n    Sets the less significant 32 bits of a double-precision floating-point\n    number.\n","base.sici":"\nbase.sici( x:number )\n    Computes the sine and cosine integrals.\n","base.sici.assign":"\nbase.sici.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n  offset:integer )\n    Computes the sine and cosine integrals and assigns results to a provided\n    output array.\n","base.signbit":"\nbase.signbit( x:number )\n    Returns a boolean indicating if the sign bit is on (true) or off (false).\n","base.signbitf":"\nbase.signbitf( x:float )\n    Returns a boolean indicating if the sign bit is on (true) or off (false).\n","base.significandf":"\nbase.significandf( x:float )\n    Returns an integer corresponding to the significand of a single-precision\n    floating-point number.\n","base.signum":"\nbase.signum( x:number )\n    Evaluates the signum function for a double-precision floating-point number.\n","base.signumf":"\nbase.signumf( x:number )\n    Evaluates the signum function for a single-precision floating-point number.\n","base.sin":"\nbase.sin( x:number )\n    Computes the sine of a number.\n","base.sinc":"\nbase.sinc( x:number )\n    Computes the normalized cardinal sine of a number.\n","base.sincos":"\nbase.sincos( x:number )\n    Simultaneously computes the sine and cosine of a number.\n\nbase.sincos( x:number, out:Array|TypedArray|Object, stride:integer, \n  offset:integer )\n    Simultaneously computes the sine and cosine of a number and assigns\n    results to a provided output array.\n","base.sincospi":"\nbase.sincospi( x:number )\n    Simultaneously computes the sine and cosine of a number times π.\n","base.sincospi.assign":"\nbase.sincospi.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n  offset:integer )\n    Simultaneously computes the sine and cosine of a number times π and\n    assigns results to a provided output array.\n","base.sinh":"\nbase.sinh( x:number )\n    Computes the hyperbolic sine of a double-precision floating-point number.\n","base.sinpi":"\nbase.sinpi( x:number )\n    Computes the value of `sin(πx)`.\n","base.slice2seq":"\nbase.slice2seq( slice:Slice )\n    Converts a Slice object to a subsequence string.\n","base.sliceLength":"\nbase.sliceLength( slice:Slice )\n    Returns the number of elements in a normalized slice.\n","base.sliceNonReducedDimensions":"\nbase.sliceNonReducedDimensions( slice:MultiSlice )\n    Returns a list of non-reduced dimensions in an un-normalized multi-slice.\n","base.sliceReducedDimensions":"\nbase.sliceReducedDimensions( slice:MultiSlice )\n    Returns a list of reduced dimensions in an un-normalized multi-slice.\n","base.sliceShape":"\nbase.sliceShape( slice:MultiSlice )\n    Returns the shape of a normalized multi-slice.\n","base.snakecase":"\nbase.snakecase( str:string )\n    Converts a string to snake case.\n","base.spence":"\nbase.spence( x:number )\n    Evaluates Spence's function, which is also known as the dilogarithm.\n","base.sqrt":"\nbase.sqrt( x:number )\n    Computes the principal square root of a double-precision floating-point\n    number.\n","base.sqrt1pm1":"\nbase.sqrt1pm1( x:number )\n    Computes the principal square root of `1+x` minus one.\n","base.sqrtf":"\nbase.sqrtf( x:number )\n    Computes the principal square root of a single-precision floating-point\n    number.\n","base.sqrtpi":"\nbase.sqrtpi( x:number )\n    Computes the principal square root of the product of π and a positive\n    double-precision floating-point number.\n","base.startcase":"\nbase.startcase( str:string )\n    Capitalizes the first letter of each word in an input string.\n","base.startsWith":"\nbase.startsWith( str:string, search:string, position:integer )\n    Tests if a string starts with the characters of another string.\n","base.stickycase":"\nbase.stickycase( str[, p] )\n    Converts a string to sticky case.\n","base.strided.binary":"\nbase.strided.binary( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  fcn:Function )\n    Applies a binary callback to strided input array elements and assigns\n    results to elements in a strided output array.\n","base.strided.binary.ndarray":"\nbase.strided.binary.ndarray( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  offsets:ArrayLikeObject<integer>, fcn:Function )\n    Applies a binary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n","base.strided.binaryDtypeSignatures":"\nbase.strided.binaryDtypeSignatures( dtypes1:ArrayLike<any>, \n  dtypes2:ArrayLike<any>, dtypes3:ArrayLike<any>[, options:Object] )\n    Generates a list of binary interface signatures from strided array data\n    types.\n","base.strided.binarySignatureCallbacks":"\nbase.strided.binarySignatureCallbacks( table:Object, signatures:ArrayLike<any> )\n    Assigns callbacks to binary interfaces according to type promotion rules.\n","base.strided.ccopy":"\nbase.strided.ccopy( N:integer, x:Complex64Array, strideX:integer, \n  y:Complex64Array, strideY:integer )\n    Copies values from one complex single-precision floating-point vector to\n    another complex single-precision floating-point vector.\n","base.strided.ccopy.ndarray":"\nbase.strided.ccopy.ndarray( N:integer, x:Complex64Array, strideX:integer, \n  offsetX:integer, y:Complex64Array, strideY:integer, offsetY:integer )\n    Copies values from one complex single-precision floating-point vector to\n    another complex single-precision floating-point vector using alternative\n    indexing semantics.\n","base.strided.cmap":"\nbase.strided.cmap( N:integer, x:Complex64Array, strideX:integer, \n  y:Complex64Array, strideY:integer, fcn:Function )\n    Applies a unary function to a single-precision complex floating-point\n    strided input array and assigns results to a single-precision complex\n    floating-point strided output array.\n","base.strided.cmap.ndarray":"\nbase.strided.cmap.ndarray( N:integer, x:Complex64Array, strideX:integer, \n  offsetX:integer, y:Complex64Array, strideY:integer, offsetY:integer, \n  fcn:Function )\n    Applies a unary function to a single-precision complex floating-point\n    strided input array and assigns results to a single-precision complex\n    floating-point strided output array using alternative indexing semantics.\n","base.strided.cswap":"\nbase.strided.cswap( N:integer, x:Complex64Array, strideX:integer, \n  y:Complex64Array, strideY:integer )\n    Interchanges two complex single-precision floating-point vectors.\n","base.strided.cswap.ndarray":"\nbase.strided.cswap.ndarray( N:integer, x:Complex64Array, strideX:integer, \n  offsetX:integer, y:Complex64Array, strideY:integer, offsetY:integer )\n    Interchanges two complex single-precision floating-point vectors using\n    alternative indexing semantics.\n","base.strided.cumax":"\nbase.strided.cumax( N:integer, x:Array|TypedArray, strideX:integer, \n  y:Array|TypedArray, strideY:integer )\n    Computes the cumulative maximum of a strided array.\n","base.strided.cumax.ndarray":"\nbase.strided.cumax.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n  offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n    Computes the cumulative maximum of a strided array using alternative\n    indexing semantics.\n","base.strided.cumaxabs":"\nbase.strided.cumaxabs( N:integer, x:Array|TypedArray, strideX:integer, \n  y:Array|TypedArray, strideY:integer )\n    Computes the cumulative maximum absolute value of a strided array.\n","base.strided.cumaxabs.ndarray":"\nbase.strided.cumaxabs.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n  offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n    Computes the cumulative maximum absolute value of a strided array using\n    alternative indexing semantics.\n","base.strided.cumin":"\nbase.strided.cumin( N:integer, x:Array|TypedArray, strideX:integer, \n  y:Array|TypedArray, strideY:integer )\n    Computes the cumulative minimum of a strided array.\n","base.strided.cumin.ndarray":"\nbase.strided.cumin.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n  offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n    Computes the cumulative minimum of a strided array using alternative\n    indexing semantics.\n","base.strided.cuminabs":"\nbase.strided.cuminabs( N:integer, x:Array|TypedArray, strideX:integer, \n  y:Array|TypedArray, strideY:integer )\n    Computes the cumulative minimum absolute value of a strided array.\n","base.strided.cuminabs.ndarray":"\nbase.strided.cuminabs.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n  offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n    Computes the cumulative minimum absolute value of a strided array using\n    alternative indexing semantics.\n","base.strided.dabs":"\nbase.strided.dabs( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n  strideY:integer )\n    Computes the absolute value for each element in a double-precision floating-\n    point strided array `x` and assigns the results to elements in a double-\n    precision floating-point strided array `y`.\n","base.strided.dabs.ndarray":"\nbase.strided.dabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Computes the absolute value for each element in a double-precision floating-\n    point strided array `x` and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.dabs2":"\nbase.strided.dabs2( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n  strideY:integer )\n    Computes the squared absolute value for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y`.\n","base.strided.dabs2.ndarray":"\nbase.strided.dabs2.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Computes the squared absolute value for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.dapx":"\nbase.strided.dapx( N:integer, alpha:number, x:Float64Array, strideX:integer )\n    Adds a scalar constant to each element in a double-precision floating-point\n    strided array.\n","base.strided.dapx.ndarray":"\nbase.strided.dapx.ndarray( N:integer, alpha:number, x:Float64Array, \n  strideX:integer, offsetX:integer )\n    Adds a scalar constant to each element in a double-precision floating-point\n    strided array using alternative indexing semantics.\n","base.strided.dapxsum":"\nbase.strided.dapxsum( N:integer, alpha:number, x:Float64Array, strideX:integer )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum.\n","base.strided.dapxsum.ndarray":"\nbase.strided.dapxsum.ndarray( N:integer, alpha:number, x:Float64Array, \n  strideX:integer, offsetX:integer )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using alternative indexing semantics.\n","base.strided.dapxsumkbn":"\nbase.strided.dapxsumkbn( N:integer, alpha:number, x:Float64Array, \n  strideX:integer )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using an improved Kahan–Babuška\n    algorithm.\n","base.strided.dapxsumkbn.ndarray":"\nbase.strided.dapxsumkbn.ndarray( N:integer, alpha:number, x:Float64Array, \n  strideX:integer, offsetX:integer )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using an improved Kahan–Babuška\n    algorithm and alternative indexing semantics.\n","base.strided.dapxsumkbn2":"\nbase.strided.dapxsumkbn2( N:integer, alpha:number, x:Float64Array, \n  strideX:integer )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using a second-order iterative\n    Kahan–Babuška algorithm.\n","base.strided.dapxsumkbn2.ndarray":"\nbase.strided.dapxsumkbn2.ndarray( N:integer, alpha:number, x:Float64Array, \n  strideX:integer, offsetX:integer )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using a second-order iterative\n    Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.dapxsumors":"\nbase.strided.dapxsumors( N:integer, alpha:number, x:Float64Array, \n  strideX:integer )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using ordinary recursive summation.\n","base.strided.dapxsumors.ndarray":"\nbase.strided.dapxsumors.ndarray( N:integer, alpha:number, x:Float64Array, \n  strideX:integer, offsetX:integer )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using ordinary recursive summation\n    and alternative indexing semantics.\n","base.strided.dapxsumpw":"\nbase.strided.dapxsumpw( N:integer, alpha:number, x:Float64Array, \n  strideX:integer )\n    Adds a scalar constant to each double-precision floating-point strided array\n    element and computes the sum using pairwise summation.\n","base.strided.dapxsumpw.ndarray":"\nbase.strided.dapxsumpw.ndarray( N:integer, alpha:number, x:Float64Array, \n  strideX:integer, offsetX:integer )\n    Adds a constant to each double-precision floating-point strided array\n    element and computes the sum using pairwise summation and alternative\n    indexing semantics.\n","base.strided.dasum":"\nbase.strided.dasum( N:integer, x:Float64Array, stride:integer )\n    Computes the sum of the absolute values.\n","base.strided.dasum.ndarray":"\nbase.strided.dasum.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the sum of absolute values using alternative indexing semantics.\n","base.strided.dasumpw":"\nbase.strided.dasumpw( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements using pairwise summation.\n","base.strided.dasumpw.ndarray":"\nbase.strided.dasumpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements using pairwise summation and alternative\n    indexing semantics.\n","base.strided.daxpy":"\nbase.strided.daxpy( N:integer, alpha:number, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n","base.strided.daxpy.ndarray":"\nbase.strided.daxpy.ndarray( N:integer, alpha:number, x:Float64Array, \n  strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n  offsetY:integer )\n    Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n    using alternative indexing semantics.\n","base.strided.dcbrt":"\nbase.strided.dcbrt( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n  strideY:integer )\n    Computes the cube root of each element in a double-precision floating-point\n    strided array `x` and assigns the results to elements in a double-precision\n    floating-point strided array `y`.\n","base.strided.dcbrt.ndarray":"\nbase.strided.dcbrt.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Computes the cube root of each element in a double-precision floating-point\n    strided array `x` and assigns the results to elements in a double-precision\n    floating-point strided array `y` using alternative indexing semantics.\n","base.strided.dceil":"\nbase.strided.dceil( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n  strideY:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward positive infinity and assigns the results to elements in a double-\n    precision floating-point strided array `y`.\n","base.strided.dceil.ndarray":"\nbase.strided.dceil.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward positive infinity and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.dcopy":"\nbase.strided.dcopy( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n  strideY:integer )\n    Copies values from `x` into `y`.\n","base.strided.dcopy.ndarray":"\nbase.strided.dcopy.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Copies values from `x` into `y` using alternative indexing semantics.\n","base.strided.dcumax":"\nbase.strided.dcumax( N:integer, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Computes the cumulative maximum of double-precision floating-point strided\n    array elements.\n","base.strided.dcumax.ndarray":"\nbase.strided.dcumax.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Computes the cumulative maximum of double-precision floating-point strided\n    array elements using alternative indexing semantics.\n","base.strided.dcumaxabs":"\nbase.strided.dcumaxabs( N:integer, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Computes the cumulative maximum absolute value of double-precision floating-\n    point strided array elements.\n","base.strided.dcumaxabs.ndarray":"\nbase.strided.dcumaxabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Computes the cumulative maximum absolute value of double-precision floating-\n    point strided array elements using alternative indexing semantics.\n","base.strided.dcumin":"\nbase.strided.dcumin( N:integer, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Computes the cumulative minimum of double-precision floating-point strided\n    array elements.\n","base.strided.dcumin.ndarray":"\nbase.strided.dcumin.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Computes the cumulative minimum of double-precision floating-point strided\n    array elements using alternative indexing semantics.\n","base.strided.dcuminabs":"\nbase.strided.dcuminabs( N:integer, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Computes the cumulative minimum absolute value of double-precision floating-\n    point strided array elements.\n","base.strided.dcuminabs.ndarray":"\nbase.strided.dcuminabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Computes the cumulative minimum absolute value of double-precision floating-\n    point strided array elements using alternative indexing semantics.\n","base.strided.dcusum":"\nbase.strided.dcusum( N:integer, sum:number, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements.\n","base.strided.dcusum.ndarray":"\nbase.strided.dcusum.ndarray( N:integer, sum:number, x:Float64Array, \n  strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using alternative indexing semantics.\n","base.strided.dcusumkbn":"\nbase.strided.dcusumkbn( N:integer, sum:number, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using an improved Kahan–Babuška algorithm.\n","base.strided.dcusumkbn.ndarray":"\nbase.strided.dcusumkbn.ndarray( N:integer, sum:number, x:Float64Array, \n  strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n","base.strided.dcusumkbn2":"\nbase.strided.dcusumkbn2( N:integer, sum:number, x:Float64Array, \n  strideX:integer, y:Float64Array, strideY:integer )\n    Computes the cumulative sum of double-precision floating-point strided\n    array elements using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.dcusumkbn2.ndarray":"\nbase.strided.dcusumkbn2.ndarray( N:integer, sum:number, x:Float64Array, \n  strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of double-precision floating-point strided\n    array elements using a second-order iterative Kahan–Babuška algorithm and\n    alternative indexing semantics.\n","base.strided.dcusumors":"\nbase.strided.dcusumors( N:integer, sum:number, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using ordinary recursive summation.\n","base.strided.dcusumors.ndarray":"\nbase.strided.dcusumors.ndarray( N:integer, sum:number, x:Float64Array, \n  strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using ordinary recursive summation and alternative indexing\n    semantics.\n","base.strided.dcusumpw":"\nbase.strided.dcusumpw( N:integer, sum:number, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using pairwise summation.\n","base.strided.dcusumpw.ndarray":"\nbase.strided.dcusumpw.ndarray( N:integer, sum:number, x:Float64Array, \n  strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using pairwise summation and alternative indexing semantics.\n","base.strided.ddeg2rad":"\nbase.strided.ddeg2rad( N:integer, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Converts each element in a double-precision floating-point strided array `x`\n    from degrees to radians and assigns the results to elements in a double-\n    precision floating-point strided array `y`.\n","base.strided.ddeg2rad.ndarray":"\nbase.strided.ddeg2rad.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Converts each element in a double-precision floating-point strided array `x`\n    from degrees to radians and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.ddot":"\nbase.strided.ddot( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n  strideY:integer )\n    Computes the dot product of two double-precision floating-point vectors.\n","base.strided.ddot.ndarray":"\nbase.strided.ddot.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Computes the dot product of two double-precision floating-point vectors\n    using alternative indexing semantics.\n","base.strided.dfill":"\nbase.strided.dfill( N:integer, alpha:number, x:Float64Array, strideX:integer )\n    Fills a double-precision floating-point strided array with a specified\n    scalar value.\n","base.strided.dfill.ndarray":"\nbase.strided.dfill.ndarray( N:integer, alpha:number, x:Float64Array, \n  strideX:integer, offsetX:integer )\n    Fills a double-precision floating-point strided array with a specified\n    scalar value using alternative indexing semantics.\n","base.strided.dfloor":"\nbase.strided.dfloor( N:integer, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward negative infinity and assigns the results to elements in a double-\n    precision floating-point strided array `y`.\n","base.strided.dfloor.ndarray":"\nbase.strided.dfloor.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward negative infinity and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.dinv":"\nbase.strided.dinv( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n  strideY:integer )\n    Computes the multiplicative inverse for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y`.\n","base.strided.dinv.ndarray":"\nbase.strided.dinv.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Computes the multiplicative inverse for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.dmap":"\nbase.strided.dmap( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n  strideY:integer, fcn:Function )\n    Applies a unary function to a double-precision floating-point strided input\n    array and assigns results to a double-precision floating-point strided\n    output array.\n","base.strided.dmap.ndarray":"\nbase.strided.dmap.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer, \n  fcn:Function )\n    Applies a unary function to a double-precision floating-point strided input\n    array and assigns results to a double-precision floating-point strided\n    output array using alternative indexing semantics.\n","base.strided.dmap2":"\nbase.strided.dmap2( N:integer, x:Float64Array, sx:integer, y:Float64Array, \n  sy:integer, z:Float64Array, sz:integer, fcn:Function )\n    Applies a binary function to double-precision floating-point strided input\n    arrays and assigns results to a double-precision floating-point strided\n    output array.\n","base.strided.dmap2.ndarray":"\nbase.strided.dmap2.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, \n  y:Float64Array, sy:integer, oy:integer, z:Float64Array, sz:integer, \n  oz:integer, fcn:Function )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array using alternative indexing semantics.\n","base.strided.dmax":"\nbase.strided.dmax( N:integer, x:Float64Array, strideX:integer )\n    Computes the maximum value of a double-precision floating-point strided\n    array.\n","base.strided.dmax.ndarray":"\nbase.strided.dmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum value of a double-precision floating-point strided\n    array using alternative indexing semantics.\n","base.strided.dmaxabs":"\nbase.strided.dmaxabs( N:integer, x:Float64Array, strideX:integer )\n    Computes the maximum absolute value of a double-precision floating-point\n    strided array.\n","base.strided.dmaxabs.ndarray":"\nbase.strided.dmaxabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum absolute value of a double-precision floating-point\n    strided array using alternative indexing semantics.\n","base.strided.dmaxabssorted":"\nbase.strided.dmaxabssorted( N:integer, x:Float64Array, stride:integer )\n    Computes the maximum absolute value of a sorted double-precision floating-\n    point strided array.\n","base.strided.dmaxabssorted.ndarray":"\nbase.strided.dmaxabssorted.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the maximum absolute value of a sorted double-precision floating-\n    point strided array using alternative indexing semantics.\n","base.strided.dmaxsorted":"\nbase.strided.dmaxsorted( N:integer, x:Float64Array, stride:integer )\n    Computes the maximum value of a sorted double-precision floating-point\n    strided array.\n","base.strided.dmaxsorted.ndarray":"\nbase.strided.dmaxsorted.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the maximum value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n","base.strided.dmean":"\nbase.strided.dmean( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array.\n","base.strided.dmean.ndarray":"\nbase.strided.dmean.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using alternative indexing semantics.\n","base.strided.dmeankbn":"\nbase.strided.dmeankbn( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm.\n","base.strided.dmeankbn.ndarray":"\nbase.strided.dmeankbn.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n","base.strided.dmeankbn2":"\nbase.strided.dmeankbn2( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.dmeankbn2.ndarray":"\nbase.strided.dmeankbn2.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n","base.strided.dmeanli":"\nbase.strided.dmeanli( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm.\n","base.strided.dmeanli.ndarray":"\nbase.strided.dmeanli.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n","base.strided.dmeanlipw":"\nbase.strided.dmeanlipw( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm with pairwise summation.\n","base.strided.dmeanlipw.ndarray":"\nbase.strided.dmeanlipw.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm with pairwise summation and\n    alternative indexing semantics.\n","base.strided.dmeanors":"\nbase.strided.dmeanors( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using ordinary recursive summation.\n","base.strided.dmeanors.ndarray":"\nbase.strided.dmeanors.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using ordinary recursive summation and alternative indexing semantics.\n","base.strided.dmeanpn":"\nbase.strided.dmeanpn( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a two-pass error correction algorithm.\n","base.strided.dmeanpn.ndarray":"\nbase.strided.dmeanpn.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a two-pass error correction algorithm and alternative indexing\n    semantics.\n","base.strided.dmeanpw":"\nbase.strided.dmeanpw( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using pairwise summation.\n","base.strided.dmeanpw.ndarray":"\nbase.strided.dmeanpw.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using pairwise summation and alternative indexing semantics.\n","base.strided.dmeanstdev":"\nbase.strided.dmeanstdev( N:integer, c:number, x:Float64Array, strideX:integer, \n  out:Float64Array, strideOut:integer )\n    Computes the mean and standard deviation of a double-precision floating-\n    point strided array.\n","base.strided.dmeanstdev.ndarray":"\nbase.strided.dmeanstdev.ndarray( N:integer, c:number, x:Float64Array, \n  strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n  offsetOut:integer )\n    Computes the mean and standard deviation of a double-precision floating-\n    point strided array using alternative indexing semantics.\n","base.strided.dmeanstdevpn":"\nbase.strided.dmeanstdevpn( N:integer, c:number, x:Float64Array, \n  strideX:integer, out:Float64Array, strideOut:integer )\n    Computes the mean and standard deviation of a double-precision floating-\n    point strided array using a two-pass algorithm.\n","base.strided.dmeanstdevpn.ndarray":"\nbase.strided.dmeanstdevpn.ndarray( N:integer, c:number, x:Float64Array, \n  strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n  offsetOut:integer )\n    Computes the mean and standard deviation of a double-precision floating-\n    point strided array using a two-pass algorithm and alternative indexing\n    semantics.\n","base.strided.dmeanvar":"\nbase.strided.dmeanvar( N:integer, c:number, x:Float64Array, strideX:integer, \n  out:Float64Array, strideOut:integer )\n    Computes the mean and variance of a double-precision floating-point strided\n    array.\n","base.strided.dmeanvar.ndarray":"\nbase.strided.dmeanvar.ndarray( N:integer, c:number, x:Float64Array, \n  strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n  offsetOut:integer )\n    Computes the mean and variance of a double-precision floating-point strided\n    array using alternative indexing semantics.\n","base.strided.dmeanvarpn":"\nbase.strided.dmeanvarpn( N:integer, c:number, x:Float64Array, strideX:integer, \n  out:Float64Array, strideOut:integer )\n    Computes the mean and variance of a double-precision floating-point strided\n    array using a two-pass algorithm.\n","base.strided.dmeanvarpn.ndarray":"\nbase.strided.dmeanvarpn.ndarray( N:integer, c:number, x:Float64Array, \n  strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n  offsetOut:integer )\n    Computes the mean and variance of a double-precision floating-point strided\n    array using a two-pass algorithm and alternative indexing semantics.\n","base.strided.dmeanwd":"\nbase.strided.dmeanwd( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using Welford's algorithm.\n","base.strided.dmeanwd.ndarray":"\nbase.strided.dmeanwd.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n","base.strided.dmediansorted":"\nbase.strided.dmediansorted( N:integer, x:Float64Array, stride:integer )\n    Computes the median value of a sorted double-precision floating-point\n    strided array.\n","base.strided.dmediansorted.ndarray":"\nbase.strided.dmediansorted.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the median value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n","base.strided.dmidrange":"\nbase.strided.dmidrange( N:integer, x:Float64Array, strideX:integer )\n    Computes the mid-range of a double-precision floating-point strided array.\n","base.strided.dmidrange.ndarray":"\nbase.strided.dmidrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the mid-range of a double-precision floating-point strided array\n    using alternative indexing semantics.\n","base.strided.dmin":"\nbase.strided.dmin( N:integer, x:Float64Array, strideX:integer )\n    Computes the minimum value of a double-precision floating-point strided\n    array.\n","base.strided.dmin.ndarray":"\nbase.strided.dmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the minimum value of a double-precision floating-point strided\n    array using alternative indexing semantics.\n","base.strided.dminabs":"\nbase.strided.dminabs( N:integer, x:Float64Array, strideX:integer )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array.\n","base.strided.dminabs.ndarray":"\nbase.strided.dminabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array using alternative indexing semantics.\n","base.strided.dminsorted":"\nbase.strided.dminsorted( N:integer, x:Float64Array, stride:integer )\n    Computes the minimum value of a sorted double-precision floating-point\n    strided array.\n","base.strided.dminsorted.ndarray":"\nbase.strided.dminsorted.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the minimum value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n","base.strided.dmskabs":"\nbase.strided.dmskabs( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Computes the absolute value for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskabs.ndarray":"\nbase.strided.dmskabs.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n  sy:integer, oy:integer )\n    Computes the absolute value for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n","base.strided.dmskabs2":"\nbase.strided.dmskabs2( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Computes the squared absolute value for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point\n    strided array `y`.\n","base.strided.dmskabs2.ndarray":"\nbase.strided.dmskabs2.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n  sy:integer, oy:integer )\n    Computes the squared absolute value for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point\n    strided array `y` using alternative indexing semantics.\n","base.strided.dmskcbrt":"\nbase.strided.dmskcbrt( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Computes the cube root for each element in a double-precision floating-point\n    strided array `x` according to a strided mask array and assigns the results\n    to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskcbrt.ndarray":"\nbase.strided.dmskcbrt.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n  sy:integer, oy:integer )\n    Computes the cube root for each element in a double-precision floating-point\n    strided array `x` according to a strided mask array and assigns the results\n    to elements in a double-precision floating-point strided array `y` using\n    alternative indexing semantics.\n","base.strided.dmskceil":"\nbase.strided.dmskceil( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward positive infinity according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskceil.ndarray":"\nbase.strided.dmskceil.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n  sy:integer, oy:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward positive infinity according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n","base.strided.dmskdeg2rad":"\nbase.strided.dmskdeg2rad( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Converts each element in a double-precision floating-point strided array `x`\n    from degrees to radians according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskdeg2rad.ndarray":"\nbase.strided.dmskdeg2rad.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n  sy:integer, oy:integer )\n    Converts each element in a double-precision floating-point strided array `x`\n    from degrees to radians according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n","base.strided.dmskfloor":"\nbase.strided.dmskfloor( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward negative infinity according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskfloor.ndarray":"\nbase.strided.dmskfloor.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n  sy:integer, oy:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward negative infinity according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n","base.strided.dmskinv":"\nbase.strided.dmskinv( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Computes the multiplicative inverse for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y`.\n","base.strided.dmskinv.ndarray":"\nbase.strided.dmskinv.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n  sy:integer, oy:integer )\n    Computes the multiplicative inverse for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y` using alternative indexing semantics.\n","base.strided.dmskmap":"\nbase.strided.dmskmap( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer, fcn:Function )\n    Applies a unary function to a double-precision floating-point strided input\n    array according to a strided mask array and assigns results to a double-\n    precision floating-point strided output array.\n","base.strided.dmskmap.ndarray":"\nbase.strided.dmskmap.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Uint8Array, sm:integer, om:integer, y:Float64Array, sy:integer, \n  oy:integer, fcn:Function )\n    Applies a unary function to a double-precision floating-point strided input\n    array according to a strided mask array and assigns results to a double-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n","base.strided.dmskmap2":"\nbase.strided.dmskmap2( N:integer, x:Float64Array, sx:integer, y:Float64Array, \n  sy:integer, m:Uint8Array, sm:integer, z:Float64Array, sz:integer, \n  fcn:Function )\n    Applies a binary function to double-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a double-\n    precision floating-point strided output array.\n","base.strided.dmskmap2.ndarray":"\nbase.strided.dmskmap2.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, y:Float64Array, sy:integer, oy:integer, m:Uint8Array, sm:integer, \n  om:integer, z:Float64Array, sz:integer, oz:integer, fcn:Function )\n    Applies a binary function to double-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a double-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n","base.strided.dmskmax":"\nbase.strided.dmskmax( N:integer, x:Float64Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask.\n","base.strided.dmskmax.ndarray":"\nbase.strided.dmskmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n","base.strided.dmskmin":"\nbase.strided.dmskmin( N:integer, x:Float64Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask.\n","base.strided.dmskmin.ndarray":"\nbase.strided.dmskmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n","base.strided.dmskramp":"\nbase.strided.dmskramp( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Evaluates the ramp function for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskramp.ndarray":"\nbase.strided.dmskramp.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n  sy:integer, oy:integer )\n    Evaluates the ramp function for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n","base.strided.dmskrange":"\nbase.strided.dmskrange( N:integer, x:Float64Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the range of a double-precision floating-point strided array\n    according to a mask.\n","base.strided.dmskrange.ndarray":"\nbase.strided.dmskrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the range of a double-precision floating-point strided array\n    according to a mask and using alternative indexing semantics.\n","base.strided.dmskrsqrt":"\nbase.strided.dmskrsqrt( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Computes the reciprocal square root for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y`.\n","base.strided.dmskrsqrt.ndarray":"\nbase.strided.dmskrsqrt.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n  sy:integer, oy:integer )\n    Computes the reciprocal square root for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y` using alternative indexing semantics.\n","base.strided.dmsksqrt":"\nbase.strided.dmsksqrt( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Computes the principal square root for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y`.\n","base.strided.dmsksqrt.ndarray":"\nbase.strided.dmsksqrt.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n  sy:integer, oy:integer )\n    Computes the principal square root for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y` using alternative indexing semantics.\n","base.strided.dmsktrunc":"\nbase.strided.dmsktrunc( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward zero according to a strided mask array and assigns the results to\n    elements in a double-precision floating-point strided array `y`.\n","base.strided.dmsktrunc.ndarray":"\nbase.strided.dmsktrunc.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n  sy:integer, oy:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward zero according to a strided mask array and assigns the results to\n    elements in a double-precision floating-point strided array `y` using\n    alternative indexing semantics.\n","base.strided.dnanasum":"\nbase.strided.dnanasum( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements, ignoring `NaN` values.\n","base.strided.dnanasum.ndarray":"\nbase.strided.dnanasum.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements, ignoring `NaN` values and using alternative\n    indexing semantics.\n","base.strided.dnanasumors":"\nbase.strided.dnanasumors( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements, ignoring `NaN` values and using ordinary\n    recursive summation.\n","base.strided.dnanasumors.ndarray":"\nbase.strided.dnanasumors.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements, ignoring `NaN` values and using ordinary\n    recursive summation alternative indexing semantics.\n","base.strided.dnanmax":"\nbase.strided.dnanmax( N:integer, x:Float64Array, strideX:integer )\n    Computes the maximum value of a double-precision floating-point strided\n    array, ignoring `NaN` values.\n","base.strided.dnanmax.ndarray":"\nbase.strided.dnanmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum value of a double-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanmaxabs":"\nbase.strided.dnanmaxabs( N:integer, x:Float64Array, strideX:integer )\n    Computes the maximum absolute value of a double-precision floating-point\n    strided array, ignoring `NaN` values.\n","base.strided.dnanmaxabs.ndarray":"\nbase.strided.dnanmaxabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum absolute value of a double-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n","base.strided.dnanmean":"\nbase.strided.dnanmean( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values.\n","base.strided.dnanmean.ndarray":"\nbase.strided.dnanmean.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanmeanors":"\nbase.strided.dnanmeanors( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.dnanmeanors.ndarray":"\nbase.strided.dnanmeanors.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation and\n    alternative indexing semantics.\n","base.strided.dnanmeanpn":"\nbase.strided.dnanmeanpn( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction\n    algorithm.\n","base.strided.dnanmeanpn.ndarray":"\nbase.strided.dnanmeanpn.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction algorithm\n    and alternative indexing semantics.\n","base.strided.dnanmeanpw":"\nbase.strided.dnanmeanpw( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using pairwise summation.\n","base.strided.dnanmeanpw.ndarray":"\nbase.strided.dnanmeanpw.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using pairwise summation and alternative\n    indexing semantics.\n","base.strided.dnanmeanwd":"\nbase.strided.dnanmeanwd( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, using Welford's algorithm and ignoring `NaN` values.\n","base.strided.dnanmeanwd.ndarray":"\nbase.strided.dnanmeanwd.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n","base.strided.dnanmin":"\nbase.strided.dnanmin( N:integer, x:Float64Array, strideX:integer )\n    Computes the minimum value of a double-precision floating-point strided\n    array, ignoring `NaN` values.\n","base.strided.dnanmin.ndarray":"\nbase.strided.dnanmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the minimum value of a double-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanminabs":"\nbase.strided.dnanminabs( N:integer, x:Float64Array, strideX:integer )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array, ignoring `NaN` values.\n","base.strided.dnanminabs.ndarray":"\nbase.strided.dnanminabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n","base.strided.dnanmskmax":"\nbase.strided.dnanmskmax( N:integer, x:Float64Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask, ignoring `NaN` values.\n","base.strided.dnanmskmax.ndarray":"\nbase.strided.dnanmskmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n","base.strided.dnanmskmin":"\nbase.strided.dnanmskmin( N:integer, x:Float64Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask, ignoring `NaN` values.\n","base.strided.dnanmskmin.ndarray":"\nbase.strided.dnanmskmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n","base.strided.dnanmskrange":"\nbase.strided.dnanmskrange( N:integer, x:Float64Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the range of a double-precision floating-point strided array\n    according to a mask, ignoring `NaN` values.\n","base.strided.dnanmskrange.ndarray":"\nbase.strided.dnanmskrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the range of a double-precision floating-point strided array\n    according to a mask, ignoring `NaN` values and using alternative indexing\n    semantics.\n","base.strided.dnannsum":"\nbase.strided.dnannsum( N:integer, x:Float64Array, strideX:integer, \n  out:Float64Array, strideOut:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values.\n","base.strided.dnannsum.ndarray":"\nbase.strided.dnannsum.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnannsumkbn":"\nbase.strided.dnannsumkbn( N:integer, x:Float64Array, strideX:integer, \n  out:Float64Array, strideOut:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n","base.strided.dnannsumkbn.ndarray":"\nbase.strided.dnannsumkbn.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n","base.strided.dnannsumkbn2":"\nbase.strided.dnannsumkbn2( N:integer, x:Float64Array, strideX:integer, \n  out:Float64Array, strideOut:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm.\n","base.strided.dnannsumkbn2.ndarray":"\nbase.strided.dnannsumkbn2.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n","base.strided.dnannsumors":"\nbase.strided.dnannsumors( N:integer, x:Float64Array, strideX:integer, \n  out:Float64Array, strideOut:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.dnannsumors.ndarray":"\nbase.strided.dnannsumors.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation and alternative\n    indexing semantics.\n","base.strided.dnannsumpw":"\nbase.strided.dnannsumpw( N:integer, x:Float64Array, strideX:integer, \n  out:Float64Array, strideOut:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation.\n","base.strided.dnannsumpw.ndarray":"\nbase.strided.dnannsumpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation and alternative indexing\n    semantics.\n","base.strided.dnanrange":"\nbase.strided.dnanrange( N:integer, x:Float64Array, strideX:integer )\n    Computes the range of a double-precision floating-point strided array,\n    ignoring `NaN` values.\n","base.strided.dnanrange.ndarray":"\nbase.strided.dnanrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the range of a double-precision floating-point strided array,\n    ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanstdev":"\nbase.strided.dnanstdev( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values.\n","base.strided.dnanstdev.ndarray":"\nbase.strided.dnanstdev.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanstdevch":"\nbase.strided.dnanstdevch( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.dnanstdevch.ndarray":"\nbase.strided.dnanstdevch.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n","base.strided.dnanstdevpn":"\nbase.strided.dnanstdevpn( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.dnanstdevpn.ndarray":"\nbase.strided.dnanstdevpn.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n","base.strided.dnanstdevtk":"\nbase.strided.dnanstdevtk( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.dnanstdevtk.ndarray":"\nbase.strided.dnanstdevtk.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n","base.strided.dnanstdevwd":"\nbase.strided.dnanstdevwd( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using Welford's algorithm.\n","base.strided.dnanstdevwd.ndarray":"\nbase.strided.dnanstdevwd.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n","base.strided.dnanstdevyc":"\nbase.strided.dnanstdevyc( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass algorithm proposed by\n    Youngs and Cramer.\n","base.strided.dnanstdevyc.ndarray":"\nbase.strided.dnanstdevyc.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass algorithm proposed by\n    Youngs and Cramer and alternative indexing semantics.\n","base.strided.dnansum":"\nbase.strided.dnansum( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values.\n","base.strided.dnansum.ndarray":"\nbase.strided.dnansum.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnansumkbn":"\nbase.strided.dnansumkbn( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n","base.strided.dnansumkbn.ndarray":"\nbase.strided.dnansumkbn.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n","base.strided.dnansumkbn2":"\nbase.strided.dnansumkbn2( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm.\n","base.strided.dnansumkbn2.ndarray":"\nbase.strided.dnansumkbn2.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n","base.strided.dnansumors":"\nbase.strided.dnansumors( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.dnansumors.ndarray":"\nbase.strided.dnansumors.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation and alternative\n    indexing semantics.\n","base.strided.dnansumpw":"\nbase.strided.dnansumpw( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation.\n","base.strided.dnansumpw.ndarray":"\nbase.strided.dnansumpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation and alternative indexing\n    semantics.\n","base.strided.dnanvariance":"\nbase.strided.dnanvariance( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values.\n","base.strided.dnanvariance.ndarray":"\nbase.strided.dnanvariance.ndarray( N:integer, correction:number, \n  x:Float64Array, stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanvariancech":"\nbase.strided.dnanvariancech( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.dnanvariancech.ndarray":"\nbase.strided.dnanvariancech.ndarray( N:integer, correction:number, \n  x:Float64Array, stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n","base.strided.dnanvariancepn":"\nbase.strided.dnanvariancepn( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.dnanvariancepn.ndarray":"\nbase.strided.dnanvariancepn.ndarray( N:integer, correction:number, \n  x:Float64Array, stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n","base.strided.dnanvariancetk":"\nbase.strided.dnanvariancetk( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.dnanvariancetk.ndarray":"\nbase.strided.dnanvariancetk.ndarray( N:integer, correction:number, \n  x:Float64Array, stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n","base.strided.dnanvariancewd":"\nbase.strided.dnanvariancewd( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using Welford's algorithm.\n","base.strided.dnanvariancewd.ndarray":"\nbase.strided.dnanvariancewd.ndarray( N:integer, correction:number, \n  x:Float64Array, stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using Welford's algorithm and alternative indexing\n    semantics.\n","base.strided.dnanvarianceyc":"\nbase.strided.dnanvarianceyc( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n    Cramer.\n","base.strided.dnanvarianceyc.ndarray":"\nbase.strided.dnanvarianceyc.ndarray( N:integer, correction:number, \n  x:Float64Array, stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n    Cramer and alternative indexing semantics.\n","base.strided.dnrm2":"\nbase.strided.dnrm2( N:integer, x:Float64Array, stride:integer )\n    Computes the L2-norm of a double-precision floating-point vector.\n","base.strided.dnrm2.ndarray":"\nbase.strided.dnrm2.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the L2-norm of a double-precision floating-point vector using\n    alternative indexing semantics.\n","base.strided.dramp":"\nbase.strided.dramp( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n  strideY:integer )\n    Evaluates the ramp function for each element in a double-precision floating-\n    point strided array `x` and assigns the results to elements in a double-\n    precision floating-point strided array `y`.\n","base.strided.dramp.ndarray":"\nbase.strided.dramp.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Evaluates the ramp function for each element in a double-precision floating-\n    point strided array `x` and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.drange":"\nbase.strided.drange( N:integer, x:Float64Array, strideX:integer )\n    Computes the range of a double-precision floating-point strided array.\n","base.strided.drange.ndarray":"\nbase.strided.drange.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the range of a double-precision floating-point strided array using\n    alternative indexing semantics.\n","base.strided.drev":"\nbase.strided.drev( N:integer, x:Float64Array, strideX:integer )\n    Reverses a double-precision floating-point strided array in-place.\n","base.strided.drev.ndarray":"\nbase.strided.drev.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Reverses a double-precision floating-point strided array in-place using\n    alternative indexing semantics.\n","base.strided.drsqrt":"\nbase.strided.drsqrt( N:integer, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Computes the reciprocal square root for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y`.\n","base.strided.drsqrt.ndarray":"\nbase.strided.drsqrt.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Computes the reciprocal square root for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.dsapxsum":"\nbase.strided.dsapxsum( N:integer, alpha:number, x:Float32Array, \n  strideX:integer )\n    Adds a scalar constant to each single-precision floating-point strided array\n    element, and computes the sum using extended accumulation and returning\n    an extended precision result.\n","base.strided.dsapxsum.ndarray":"\nbase.strided.dsapxsum.ndarray( N:integer, alpha:number, x:Float32Array, \n  strideX:integer, offsetX:integer )\n    Adds a scalar constant to each single-precision floating-point strided array\n    element, and computes the sum using pairwise summation with extended\n    accumulation and alternative indexing semantics and returning an extended\n    precision result.\n","base.strided.dsapxsumpw":"\nbase.strided.dsapxsumpw( N:integer, alpha:number, x:Float32Array, \n  strideX:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element, and computes the sum using pairwise summation with extended\n    accumulation and returning an extended precision result.\n","base.strided.dsapxsumpw.ndarray":"\nbase.strided.dsapxsumpw.ndarray( N:integer, alpha:number, x:Float32Array, \n  strideX:integer, offsetX:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element, and computes the sum using pairwise summation with extended\n    accumulation and alternative indexing semantics and returning an extended\n    precision result.\n","base.strided.dscal":"\nbase.strided.dscal( N:integer, alpha:number, x:Float64Array, stride:integer )\n    Multiplies a double-precision floating-point vector `x` by a constant\n    `alpha`.\n","base.strided.dscal.ndarray":"\nbase.strided.dscal.ndarray( N:integer, alpha:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Multiplies a double-precision floating-point vector `x` by a constant\n    `alpha` using alternative indexing semantics.\n","base.strided.dsdot":"\nbase.strided.dsdot( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer )\n    Computes the dot product of two single-precision floating-point vectors with\n    extended accumulation and result.\n","base.strided.dsdot.ndarray":"\nbase.strided.dsdot.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the dot product of two single-precision floating-point vectors\n    using alternative indexing semantics and with extended accumulation and\n    result.\n","base.strided.dsem":"\nbase.strided.dsem( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array.\n","base.strided.dsem.ndarray":"\nbase.strided.dsem.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using alternative indexing semantics.\n","base.strided.dsemch":"\nbase.strided.dsemch( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass trial mean algorithm.\n","base.strided.dsemch.ndarray":"\nbase.strided.dsemch.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass trial mean algorithm and alternative\n    indexing semantics.\n","base.strided.dsempn":"\nbase.strided.dsempn( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a two-pass algorithm.\n","base.strided.dsempn.ndarray":"\nbase.strided.dsempn.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a two-pass algorithm and alternative indexing\n    semantics.\n","base.strided.dsemtk":"\nbase.strided.dsemtk( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass textbook algorithm.\n","base.strided.dsemtk.ndarray":"\nbase.strided.dsemtk.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass textbook algorithm and alternative\n    indexing semantics.\n","base.strided.dsemwd":"\nbase.strided.dsemwd( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using Welford's algorithm.\n","base.strided.dsemwd.ndarray":"\nbase.strided.dsemwd.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using Welford's algorithm and alternative indexing\n    semantics.\n","base.strided.dsemyc":"\nbase.strided.dsemyc( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass algorithm proposed by Youngs and\n    Cramer.\n","base.strided.dsemyc.ndarray":"\nbase.strided.dsemyc.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass algorithm proposed by Youngs and Cramer\n    and alternative indexing semantics.\n","base.strided.dsmean":"\nbase.strided.dsmean( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using extended accumulation and returning an extended precision\n    result.\n","base.strided.dsmean.ndarray":"\nbase.strided.dsmean.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using extended accumulation and alternative indexing semantics and\n    returning an extended precision result.\n","base.strided.dsmeanors":"\nbase.strided.dsmeanors( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation with extended accumulation and\n    returning an extended precision result.\n","base.strided.dsmeanors.ndarray":"\nbase.strided.dsmeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation with extended accumulation and\n    alternative indexing semantics and returning an extended precision result.\n","base.strided.dsmeanpn":"\nbase.strided.dsmeanpn( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a two-pass error correction algorithm with extended accumulation\n    and returning an extended precision result.\n","base.strided.dsmeanpn.ndarray":"\nbase.strided.dsmeanpn.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a two-pass error correction algorithm with extended accumulation\n    and alternative indexing semantics and returning an extended precision\n    result.\n","base.strided.dsmeanpw":"\nbase.strided.dsmeanpw( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using pairwise summation with extended accumulation and returning an\n    extended precision result.\n","base.strided.dsmeanpw.ndarray":"\nbase.strided.dsmeanpw.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using pairwise summation with extended accumulation and alternative\n    indexing semantics and returning an extended precision result.\n","base.strided.dsmeanwd":"\nbase.strided.dsmeanwd( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using Welford's algorithm with extended accumulation and returning an\n    extended precision result.\n","base.strided.dsmeanwd.ndarray":"\nbase.strided.dsmeanwd.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using Welford's algorithm with extended accumulation and alternative\n    indexing semantics and returning an extended precision result.\n","base.strided.dsnanmean":"\nbase.strided.dsnanmean( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values, using extended accumulation, and returning an\n    extended precision result.\n","base.strided.dsnanmean.ndarray":"\nbase.strided.dsnanmean.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using extended accumulation and alternative\n    indexing semantics.\n","base.strided.dsnanmeanors":"\nbase.strided.dsnanmeanors( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values, using ordinary recursive summation with\n    extended accumulation, and returning an extended precision result.\n","base.strided.dsnanmeanors.ndarray":"\nbase.strided.dsnanmeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation with\n    extended accumulation and alternative indexing semantics.\n","base.strided.dsnanmeanpn":"\nbase.strided.dsnanmeanpn( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values, using a two-pass error correction algorithm\n    with extended accumulation, and returning an extended precision result.\n","base.strided.dsnanmeanpn.ndarray":"\nbase.strided.dsnanmeanpn.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction algorithm\n    with extended accumulation and alternative indexing semantics.\n","base.strided.dsnanmeanwd":"\nbase.strided.dsnanmeanwd( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values, using Welford's algorithm with extended\n    accumulation, and returning an extended precision result.\n","base.strided.dsnanmeanwd.ndarray":"\nbase.strided.dsnanmeanwd.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm with extended\n    accumulation and alternative indexing semantics.\n","base.strided.dsnannsumors":"\nbase.strided.dsnannsumors( N:integer, x:Float32Array, strideX:integer, \n  out:Float64Array, strideOut:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using ordinary recursive summation with extended\n    accumulation, and returning an extended precision result.\n","base.strided.dsnannsumors.ndarray":"\nbase.strided.dsnannsumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using ordinary recursive summation with extended\n    accumulation and alternative indexing semantics, and returning an extended\n    precision result.\n","base.strided.dsnansum":"\nbase.strided.dsnansum( N:integer, x:Float32Array, strideX:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using extended accumulation, and returning an\n    extended precision result.\n","base.strided.dsnansum.ndarray":"\nbase.strided.dsnansum.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using extended accumulation and alternative\n    indexing semantics, and returning an extended precision result.\n","base.strided.dsnansumors":"\nbase.strided.dsnansumors( N:integer, x:Float32Array, strideX:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using ordinary recursive summation with extended\n    accumulation, and returning an extended precision result.\n","base.strided.dsnansumors.ndarray":"\nbase.strided.dsnansumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation with extended\n    accumulation and alternative indexing semantics, and returning an extended\n    precision result.\n","base.strided.dsnansumpw":"\nbase.strided.dsnansumpw( N:integer, x:Float32Array, strideX:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using pairwise summation with extended accumulation,\n    and returning an extended precision result.\n","base.strided.dsnansumpw.ndarray":"\nbase.strided.dsnansumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using pairwise summation with extended accumulation\n    and alternative indexing semantics, and returning an extended precision\n    result.\n","base.strided.dsort2hp":"\nbase.strided.dsort2hp( N:integer, order:number, x:Float64Array, \n  strideX:integer, y:Float64Array, strideY:integer )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using heapsort.\n","base.strided.dsort2hp.ndarray":"\nbase.strided.dsort2hp.ndarray( N:integer, order:number, x:Float64Array, \n  strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n  offsetY:integer )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using heapsort and alternative\n    indexing semantics.\n","base.strided.dsort2ins":"\nbase.strided.dsort2ins( N:integer, order:number, x:Float64Array, \n  strideX:integer, y:Float64Array, strideY:integer )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using insertion sort.\n","base.strided.dsort2ins.ndarray":"\nbase.strided.dsort2ins.ndarray( N:integer, order:number, x:Float64Array, \n  strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n  offsetY:integer )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using insertion sort and\n    alternative indexing semantics.\n","base.strided.dsort2sh":"\nbase.strided.dsort2sh( N:integer, order:number, x:Float64Array, \n  strideX:integer, y:Float64Array, strideY:integer )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using Shellsort.\n","base.strided.dsort2sh.ndarray":"\nbase.strided.dsort2sh.ndarray( N:integer, order:number, x:Float64Array, \n  strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n  offsetY:integer )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using Shellsort and alternative\n    indexing semantics.\n","base.strided.dsorthp":"\nbase.strided.dsorthp( N:integer, order:number, x:Float64Array, stride:integer )\n    Sorts a double-precision floating-point strided array using heapsort.\n","base.strided.dsorthp.ndarray":"\nbase.strided.dsorthp.ndarray( N:integer, order:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Sorts a double-precision floating-point strided array using heapsort and\n    alternative indexing semantics.\n","base.strided.dsortins":"\nbase.strided.dsortins( N:integer, order:number, x:Float64Array, stride:integer )\n    Sorts a double-precision floating-point strided array using insertion sort.\n","base.strided.dsortins.ndarray":"\nbase.strided.dsortins.ndarray( N:integer, order:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Sorts a double-precision floating-point strided array using insertion sort\n    and alternative indexing semantics.\n","base.strided.dsortsh":"\nbase.strided.dsortsh( N:integer, order:number, x:Float64Array, stride:integer )\n    Sorts a double-precision floating-point strided array using Shellsort.\n","base.strided.dsortsh.ndarray":"\nbase.strided.dsortsh.ndarray( N:integer, order:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Sorts a double-precision floating-point strided array using Shellsort and\n    alternative indexing semantics.\n","base.strided.dsqrt":"\nbase.strided.dsqrt( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n  strideY:integer )\n    Computes the principal square root for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y`.\n","base.strided.dsqrt.ndarray":"\nbase.strided.dsqrt.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Computes the principal square root for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.dssum":"\nbase.strided.dssum( N:integer, x:Float32Array, strideX:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using extended accumulation and returning an extended precision result.\n","base.strided.dssum.ndarray":"\nbase.strided.dssum.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using extended accumulation and alternative indexing semantics and returning\n    an extended precision result.\n","base.strided.dssumors":"\nbase.strided.dssumors( N:integer, x:Float32Array, strideX:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using ordinary recursive summation with extended accumulation and returning\n    an extended precision result.\n","base.strided.dssumors.ndarray":"\nbase.strided.dssumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using ordinary recursive summation with extended accumulation and\n    alternative indexing semantics and returning an extended precision result.\n","base.strided.dssumpw":"\nbase.strided.dssumpw( N:integer, x:Float32Array, strideX:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation with extended accumulation and returning an\n    extended precision result.\n","base.strided.dssumpw.ndarray":"\nbase.strided.dssumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation with extended accumulation and alternative indexing\n    semantics and returning an extended precision result.\n","base.strided.dstdev":"\nbase.strided.dstdev( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array.\n","base.strided.dstdev.ndarray":"\nbase.strided.dstdev.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using alternative indexing semantics.\n","base.strided.dstdevch":"\nbase.strided.dstdevch( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm.\n","base.strided.dstdevch.ndarray":"\nbase.strided.dstdevch.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n","base.strided.dstdevpn":"\nbase.strided.dstdevpn( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a two-pass algorithm.\n","base.strided.dstdevpn.ndarray":"\nbase.strided.dstdevpn.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a two-pass algorithm and alternative indexing semantics.\n","base.strided.dstdevtk":"\nbase.strided.dstdevtk( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass textbook algorithm.\n","base.strided.dstdevtk.ndarray":"\nbase.strided.dstdevtk.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass textbook algorithm and alternative indexing\n    semantics.\n","base.strided.dstdevwd":"\nbase.strided.dstdevwd( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using Welford's algorithm.\n","base.strided.dstdevwd.ndarray":"\nbase.strided.dstdevwd.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n","base.strided.dstdevyc":"\nbase.strided.dstdevyc( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.dstdevyc.ndarray":"\nbase.strided.dstdevyc.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer and\n    alternative indexing semantics.\n","base.strided.dsum":"\nbase.strided.dsum( N:integer, x:Float64Array, stride:integer )\n    Computes the sum of double-precision floating-point strided array elements.\n","base.strided.dsum.ndarray":"\nbase.strided.dsum.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using alternative indexing semantics.\n","base.strided.dsumkbn":"\nbase.strided.dsumkbn( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm.\n","base.strided.dsumkbn.ndarray":"\nbase.strided.dsumkbn.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n","base.strided.dsumkbn2":"\nbase.strided.dsumkbn2( N:integer, x:Float64Array, stride:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.dsumkbn2.ndarray":"\nbase.strided.dsumkbn2.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n","base.strided.dsumors":"\nbase.strided.dsumors( N:integer, x:Float64Array, stride:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using ordinary recursive summation.\n","base.strided.dsumors.ndarray":"\nbase.strided.dsumors.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using ordinary recursive summation and alternative indexing semantics.\n","base.strided.dsumpw":"\nbase.strided.dsumpw( N:integer, x:Float64Array, stride:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using pairwise summation.\n","base.strided.dsumpw.ndarray":"\nbase.strided.dsumpw.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using pairwise summation and alternative indexing semantics.\n","base.strided.dsvariance":"\nbase.strided.dsvariance( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using extended accumulation and returning an extended precision result.\n","base.strided.dsvariance.ndarray":"\nbase.strided.dsvariance.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using extended accumulation and alternative indexing semantics and\n    returning an extended precision result.\n","base.strided.dsvariancepn":"\nbase.strided.dsvariancepn( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using a two-pass algorithm with extended accumulation and returning an\n    extended precision result.\n","base.strided.dsvariancepn.ndarray":"\nbase.strided.dsvariancepn.ndarray( N:integer, correction:number, \n  x:Float32Array, stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using a two-pass algorithm with extended accumulation and alternative\n    indexing semantics and returning an extended precision result.\n","base.strided.dswap":"\nbase.strided.dswap( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n  strideY:integer )\n    Interchanges two double-precision floating-point vectors.\n","base.strided.dswap.ndarray":"\nbase.strided.dswap.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Interchanges two double-precision floating-point vectors using alternative\n    indexing semantics.\n","base.strided.dtrunc":"\nbase.strided.dtrunc( N:integer, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward zero and assigns the results to elements in a double-precision\n    floating-point strided array `y`.\n","base.strided.dtrunc.ndarray":"\nbase.strided.dtrunc.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward zero and assigns the results to elements in a double-precision\n    floating-point strided array `y` using alternative indexing semantics.\n","base.strided.dtypeEnum2Str":"\nbase.strided.dtypeEnum2Str( dtype:integer )\n    Returns the data type string associated with a strided array data type\n    enumeration constant.\n","base.strided.dtypeResolveEnum":"\nbase.strided.dtypeResolveEnum( dtype:any )\n    Returns the enumeration constant associated with a supported strided array\n    data type value.\n","base.strided.dtypeResolveStr":"\nbase.strided.dtypeResolveStr( dtype:any )\n    Returns the data type string associated with a supported data type value.\n","base.strided.dtypeStr2Enum":"\nbase.strided.dtypeStr2Enum( dtype:string )\n    Returns the enumeration constant associated with a strided array data type\n    string.\n","base.strided.dvariance":"\nbase.strided.dvariance( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array.\n","base.strided.dvariance.ndarray":"\nbase.strided.dvariance.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using alternative indexing semantics.\n","base.strided.dvariancech":"\nbase.strided.dvariancech( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass trial mean algorithm.\n","base.strided.dvariancech.ndarray":"\nbase.strided.dvariancech.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.dvariancepn":"\nbase.strided.dvariancepn( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using a two-pass algorithm.\n","base.strided.dvariancepn.ndarray":"\nbase.strided.dvariancepn.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using a two-pass algorithm and alternative indexing semantics.\n","base.strided.dvariancetk":"\nbase.strided.dvariancetk( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass textbook algorithm.\n","base.strided.dvariancetk.ndarray":"\nbase.strided.dvariancetk.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.dvariancewd":"\nbase.strided.dvariancewd( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using Welford's algorithm.\n","base.strided.dvariancewd.ndarray":"\nbase.strided.dvariancewd.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using Welford's algorithm and alternative indexing semantics.\n","base.strided.dvarianceyc":"\nbase.strided.dvarianceyc( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.dvarianceyc.ndarray":"\nbase.strided.dvarianceyc.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass algorithm proposed by Youngs and Cramer and alternative\n    indexing semantics.\n","base.strided.dvarm":"\nbase.strided.dvarm( N:integer, mean:number, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean.\n","base.strided.dvarm.ndarray":"\nbase.strided.dvarm.ndarray( N:integer, mean:number, correction:number, \n  x:Float64Array, stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using alternative indexing semantics.\n","base.strided.dvarmpn":"\nbase.strided.dvarmpn( N:integer, mean:number, correction:number, \n  x:Float64Array, stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using Neely's correction algorithm.\n","base.strided.dvarmpn.ndarray":"\nbase.strided.dvarmpn.ndarray( N:integer, mean:number, correction:number, \n  x:Float64Array, stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using Neely's correction algorithm and alternative\n    indexing semantics.\n","base.strided.dvarmtk":"\nbase.strided.dvarmtk( N:integer, mean:number, correction:number, \n  x:Float64Array, stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using a one-pass textbook algorithm.\n","base.strided.dvarmtk.ndarray":"\nbase.strided.dvarmtk.ndarray( N:integer, mean:number, correction:number, \n  x:Float64Array, stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n","base.strided.gapx":"\nbase.strided.gapx( N:integer, alpha:number, x:Array|TypedArray, stride:integer )\n    Adds a constant to each element in a strided array.\n","base.strided.gapx.ndarray":"\nbase.strided.gapx.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Adds a constant to each element in a strided array using alternative\n    indexing semantics.\n","base.strided.gapxsum":"\nbase.strided.gapxsum( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer )\n    Adds a constant to each strided array element and computes the sum.\n","base.strided.gapxsum.ndarray":"\nbase.strided.gapxsum.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Adds a constant to each strided array element and computes the sum using\n    alternative indexing semantics.\n","base.strided.gapxsumkbn":"\nbase.strided.gapxsumkbn( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer )\n    Adds a constant to each strided array element and computes the sum using an\n    improved Kahan–Babuška algorithm.\n","base.strided.gapxsumkbn.ndarray":"\nbase.strided.gapxsumkbn.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Adds a constant to each strided array element and computes the sum using an\n    improved Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gapxsumkbn2":"\nbase.strided.gapxsumkbn2( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer )\n    Adds a constant to each strided array element and computes the sum using a\n    second-order iterative Kahan–Babuška algorithm.\n","base.strided.gapxsumkbn2.ndarray":"\nbase.strided.gapxsumkbn2.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Adds a constant to each strided array element and computes the sum using a\n    second-order iterative Kahan–Babuška algorithm and alternative indexing\n    semantics.\n","base.strided.gapxsumors":"\nbase.strided.gapxsumors( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer )\n    Adds a constant to each strided array element and computes the sum using\n    ordinary recursive summation.\n","base.strided.gapxsumors.ndarray":"\nbase.strided.gapxsumors.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Adds a constant to each strided array element and computes the sum using\n    ordinary recursive summation and alternative indexing semantics.\n","base.strided.gapxsumpw":"\nbase.strided.gapxsumpw( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer )\n    Adds a constant to each strided array element and computes the sum using\n    pairwise summation.\n","base.strided.gapxsumpw.ndarray":"\nbase.strided.gapxsumpw.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Adds a constant to each strided array element and computes the sum using\n    pairwise summation and alternative indexing semantics.\n","base.strided.gasum":"\nbase.strided.gasum( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of the absolute values.\n","base.strided.gasum.ndarray":"\nbase.strided.gasum.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the sum of absolute values using alternative indexing semantics.\n","base.strided.gasumpw":"\nbase.strided.gasumpw( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of absolute values (L1 norm) of strided array elements\n    using pairwise summation.\n","base.strided.gasumpw.ndarray":"\nbase.strided.gasumpw.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the sum of absolute values (L1 norm) of strided array elements\n    using pairwise summation and alternative indexing semantics.\n","base.strided.gaxpy":"\nbase.strided.gaxpy( N:integer, alpha:number, x:Array|TypedArray, \n  strideX:integer, y:Array|TypedArray, strideY:integer )\n    Multiplies `x` by a constant `alpha` and adds the result to `y`.\n","base.strided.gaxpy.ndarray":"\nbase.strided.gaxpy.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n  strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n  offsetY:integer )\n    Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n    alternative indexing semantics.\n","base.strided.gcopy":"\nbase.strided.gcopy( N:integer, x:ArrayLikeObject, strideX:integer, \n  y:ArrayLikeObject, strideY:integer )\n    Copies values from `x` into `y`.\n","base.strided.gcopy.ndarray":"\nbase.strided.gcopy.ndarray( N:integer, x:ArrayLikeObject, strideX:integer, \n  offsetX:integer, y:ArrayLikeObject, strideY:integer, offsetY:integer )\n    Copies values from `x` into `y` using alternative indexing semantics.\n","base.strided.gcusum":"\nbase.strided.gcusum( N:integer, sum:number, x:Array|TypedArray, \n  strideX:integer, y:Array|TypedArray, strideY:integer )\n    Computes the cumulative sum of strided array elements.\n","base.strided.gcusum.ndarray":"\nbase.strided.gcusum.ndarray( N:integer, sum:number, x:Array|TypedArray, \n  strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of strided array elements using alternative\n    indexing semantics.\n","base.strided.gcusumkbn":"\nbase.strided.gcusumkbn( N:integer, sum:number, x:Array|TypedArray, \n  strideX:integer, y:Array|TypedArray, strideY:integer )\n    Computes the cumulative sum of strided array elements using an improved\n    Kahan–Babuška algorithm.\n","base.strided.gcusumkbn.ndarray":"\nbase.strided.gcusumkbn.ndarray( N:integer, sum:number, x:Array|TypedArray, \n  strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of strided array elements using an improved\n    Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gcusumkbn2":"\nbase.strided.gcusumkbn2( N:integer, sum:number, x:Array|TypedArray, \n  strideX:integer, y:Array|TypedArray, strideY:integer )\n    Computes the cumulative sum of strided array elements using a second-order\n    iterative Kahan–Babuška algorithm.\n","base.strided.gcusumkbn2.ndarray":"\nbase.strided.gcusumkbn2.ndarray( N:integer, sum:number, x:Array|TypedArray, \n  strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of strided array elements using a second-order\n    iterative Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gcusumors":"\nbase.strided.gcusumors( N:integer, sum:number, x:Array|TypedArray, \n  strideX:integer, y:Array|TypedArray, strideY:integer )\n    Computes the cumulative sum of strided array elements using ordinary\n    recursive summation.\n","base.strided.gcusumors.ndarray":"\nbase.strided.gcusumors.ndarray( N:integer, sum:number, x:Array|TypedArray, \n  strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of strided array elements using ordinary\n    recursive summation and alternative indexing semantics.\n","base.strided.gcusumpw":"\nbase.strided.gcusumpw( N:integer, sum:number, x:Array|TypedArray, \n  strideX:integer, y:Array|TypedArray, strideY:integer )\n    Computes the cumulative sum of strided array elements using pairwise\n    summation.\n","base.strided.gcusumpw.ndarray":"\nbase.strided.gcusumpw.ndarray( N:integer, sum:number, x:Array|TypedArray, \n  strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of strided array elements using pairwise\n    summation and alternative indexing semantics.\n","base.strided.gdot":"\nbase.strided.gdot( N:integer, x:Array|TypedArray, strideX:integer, \n  y:Array|TypedArray, strideY:integer )\n    Computes the dot product of two vectors.\n","base.strided.gdot.ndarray":"\nbase.strided.gdot.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n  offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n    Computes the dot product of two vectors using alternative indexing\n    semantics.\n","base.strided.gfill":"\nbase.strided.gfill( N:integer, alpha:any, x:ArrayLikeObject, stride:integer )\n    Fills a strided array with a specified scalar value.\n","base.strided.gfill.ndarray":"\nbase.strided.gfill.ndarray( N:integer, alpha:any, x:ArrayLikeObject, \n  stride:integer, offset:integer )\n    Fills a strided array with a specified scalar value using alternative\n    indexing semantics.\n","base.strided.gfillBy":"\nbase.strided.gfillBy( N:integer, x:ArrayLikeObject, stride:integer, \n  clbk:Function[, thisArg:any] )\n    Fills a strided array according to a provided callback function.\n","base.strided.gfillBy.ndarray":"\nbase.strided.gfillBy.ndarray( N:integer, x:ArrayLikeObject, stride:integer, \n  offset:integer, clbk:Function[, thisArg:any] )\n    Fills a strided array according to a provided callback function and using\n    alternative indexing semantics.\n","base.strided.gnannsumkbn":"\nbase.strided.gnannsumkbn( N:integer, x:Array|TypedArray, strideX:integer, \n  out:Array|TypedArray, strideOut:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    an improved Kahan–Babuška algorithm.\n","base.strided.gnannsumkbn.ndarray":"\nbase.strided.gnannsumkbn.ndarray( N:integer, x:Array|TypedArray, \n  strideX:integer, offsetX:integer, out:Array|TypedArray, strideOut:integer, \n  offsetOut:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    an improved Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gnansum":"\nbase.strided.gnansum( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values.\n","base.strided.gnansum.ndarray":"\nbase.strided.gnansum.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    alternative indexing semantics.\n","base.strided.gnansumkbn":"\nbase.strided.gnansumkbn( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    an improved Kahan–Babuška algorithm.\n","base.strided.gnansumkbn.ndarray":"\nbase.strided.gnansumkbn.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    an improved Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gnansumkbn2":"\nbase.strided.gnansumkbn2( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    a second-order iterative Kahan–Babuška algorithm.\n","base.strided.gnansumkbn2.ndarray":"\nbase.strided.gnansumkbn2.ndarray( N:integer, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    a second-order iterative Kahan–Babuška algorithm and alternative indexing\n    semantics.\n","base.strided.gnansumors":"\nbase.strided.gnansumors( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    ordinary recursive summation.\n","base.strided.gnansumors.ndarray":"\nbase.strided.gnansumors.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    ordinary recursive summation and alternative indexing semantics.\n","base.strided.gnansumpw":"\nbase.strided.gnansumpw( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values and\n    pairwise summation.\n","base.strided.gnansumpw.ndarray":"\nbase.strided.gnansumpw.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    pairwise summation and alternative indexing semantics.\n","base.strided.gnrm2":"\nbase.strided.gnrm2( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the L2-norm of a vector.\n","base.strided.gnrm2.ndarray":"\nbase.strided.gnrm2.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the L2-norm of a vector using alternative indexing semantics.\n","base.strided.grev":"\nbase.strided.grev( N:integer, x:ArrayLikeObject, stride:integer )\n    Reverses a strided array in-place.\n","base.strided.grev.ndarray":"\nbase.strided.grev.ndarray( N:integer, x:ArrayLikeObject, stride:integer, \n  offset:integer )\n    Reverses a strided array in-place using alternative indexing semantics.\n","base.strided.gscal":"\nbase.strided.gscal( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer )\n    Multiplies a vector `x` by a constant `alpha`.\n","base.strided.gscal.ndarray":"\nbase.strided.gscal.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Multiplies `x` by a constant `alpha` using alternative indexing semantics.\n","base.strided.gsort2hp":"\nbase.strided.gsort2hp( N:integer, order:number, x:Array|TypedArray, \n  strideX:integer, y:Array|TypedArray, strideY:integer )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using heapsort.\n","base.strided.gsort2hp.ndarray":"\nbase.strided.gsort2hp.ndarray( N:integer, order:number, x:Array|TypedArray, \n  strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n  offsetY:integer )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using heapsort and alternative indexing semantics.\n","base.strided.gsort2ins":"\nbase.strided.gsort2ins( N:integer, order:number, x:Array|TypedArray, \n  strideX:integer, y:Array|TypedArray, strideY:integer )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using insertion sort.\n","base.strided.gsort2ins.ndarray":"\nbase.strided.gsort2ins.ndarray( N:integer, order:number, x:Array|TypedArray, \n  strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n  offsetY:integer )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using insertion sort and alternative indexing semantics.\n","base.strided.gsort2sh":"\nbase.strided.gsort2sh( N:integer, order:number, x:Array|TypedArray, \n  strideX:integer, y:Array|TypedArray, strideY:integer )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using Shellsort.\n","base.strided.gsort2sh.ndarray":"\nbase.strided.gsort2sh.ndarray( N:integer, order:number, x:Array|TypedArray, \n  strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n  offsetY:integer )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using Shellsort and alternative indexing semantics.\n","base.strided.gsorthp":"\nbase.strided.gsorthp( N:integer, order:number, x:Array|TypedArray, \n  stride:integer )\n    Sorts a strided array using heapsort.\n","base.strided.gsorthp.ndarray":"\nbase.strided.gsorthp.ndarray( N:integer, order:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Sorts a strided array using heapsort and alternative indexing semantics.\n","base.strided.gsortins":"\nbase.strided.gsortins( N:integer, order:number, x:Array|TypedArray, \n  stride:integer )\n    Sorts a strided array using insertion sort.\n","base.strided.gsortins.ndarray":"\nbase.strided.gsortins.ndarray( N:integer, order:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Sorts a strided array using insertion sort and alternative indexing\n    semantics.\n","base.strided.gsortsh":"\nbase.strided.gsortsh( N:integer, order:number, x:Array|TypedArray, \n  stride:integer )\n    Sorts a strided array using Shellsort.\n","base.strided.gsortsh.ndarray":"\nbase.strided.gsortsh.ndarray( N:integer, order:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Sorts a strided array using Shellsort and alternative indexing semantics.\n","base.strided.gsum":"\nbase.strided.gsum( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of strided array elements.\n","base.strided.gsum.ndarray":"\nbase.strided.gsum.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the sum of strided array elements using alternative indexing\n    semantics.\n","base.strided.gsumkbn":"\nbase.strided.gsumkbn( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of strided array elements using an improved Kahan–Babuška\n    algorithm.\n","base.strided.gsumkbn.ndarray":"\nbase.strided.gsumkbn.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the sum of strided array elements using an improved Kahan–Babuška\n    algorithm and alternative indexing semantics.\n","base.strided.gsumkbn2":"\nbase.strided.gsumkbn2( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of strided array elements using a second-order iterative\n    Kahan–Babuška algorithm.\n","base.strided.gsumkbn2.ndarray":"\nbase.strided.gsumkbn2.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the sum of strided array elements using a second-order iterative\n    Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gsumors":"\nbase.strided.gsumors( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of strided array elements using ordinary recursive\n    summation.\n","base.strided.gsumors.ndarray":"\nbase.strided.gsumors.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the sum of strided array elements using ordinary recursive\n    summation and alternative indexing semantics.\n","base.strided.gsumpw":"\nbase.strided.gsumpw( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of strided array elements using pairwise summation.\n","base.strided.gsumpw.ndarray":"\nbase.strided.gsumpw.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the sum of strided array elements using pairwise summation and\n    alternative indexing semantics.\n","base.strided.gswap":"\nbase.strided.gswap( N:integer, x:ArrayLikeObject, strideX:integer, \n  y:ArrayLikeObject, strideY:integer )\n    Interchanges vectors `x` and `y`.\n","base.strided.gswap.ndarray":"\nbase.strided.gswap.ndarray( N:integer, x:ArrayLikeObject, strideX:integer, \n  offsetX:integer, y:ArrayLikeObject, strideY:integer, offsetY:integer )\n    Interchanges vectors `x` and `y` using alternative indexing semantics.\n","base.strided.mapBy":"\nbase.strided.mapBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, fcn:Function, clbk:Function[, \n  thisArg:any] )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array.\n","base.strided.mapBy.ndarray":"\nbase.strided.mapBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, fcn:Function, \n  clbk:Function[, thisArg:any] )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array using alternative indexing semantics.\n","base.strided.mapBy2":"\nbase.strided.mapBy2( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, \n  fcn:Function, clbk:Function[, thisArg:any] )\n    Applies a binary function to each pair of elements retrieved from strided\n    input arrays according to a callback function and assigns results to a\n    strided output array.\n","base.strided.mapBy2.ndarray":"\nbase.strided.mapBy2.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  z:Array|TypedArray|Object, sz:integer, oz:integer, fcn:Function, \n  clbk:Function[, thisArg:any] )\n    Applies a binary function to each pair of elements retrieved from strided\n    input arrays according to a callback function and assigns results to a\n    strided output array using alternative indexing semantics.\n","base.strided.max":"\nbase.strided.max( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the maximum value of a strided array.\n","base.strided.max.ndarray":"\nbase.strided.max.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the maximum value of a strided array using alternative indexing\n    semantics.\n","base.strided.maxabs":"\nbase.strided.maxabs( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the maximum absolute value of a strided array.\n","base.strided.maxabs.ndarray":"\nbase.strided.maxabs.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the maximum absolute value of a strided array using alternative\n    indexing semantics.\n","base.strided.maxBy":"\nbase.strided.maxBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n  clbk:Function[, thisArg:any] )\n    Calculates the maximum value of a strided array via a callback function.\n","base.strided.maxBy.ndarray":"\nbase.strided.maxBy.ndarray( N:integer, x:Array|TypedArray|Object, \n  stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n    Calculates the maximum value of a strided array via a callback function and\n    using alternative indexing semantics.\n","base.strided.maxsorted":"\nbase.strided.maxsorted( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the maximum value of a sorted strided array.\n","base.strided.maxsorted.ndarray":"\nbase.strided.maxsorted.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the maximum value of a sorted strided array using alternative\n    indexing semantics.\n","base.strided.maxViewBufferIndex":"\nbase.strided.maxViewBufferIndex( N:integer, stride:integer, offset:integer )\n    Returns the maximum accessible index based on a set of provided strided\n    array parameters.\n","base.strided.mean":"\nbase.strided.mean( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the arithmetic mean of a strided array.\n","base.strided.mean.ndarray":"\nbase.strided.mean.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a strided array using alternative indexing\n    semantics.\n","base.strided.meankbn":"\nbase.strided.meankbn( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the arithmetic mean of a strided array using an improved Kahan–\n    Babuška algorithm.\n","base.strided.meankbn.ndarray":"\nbase.strided.meankbn.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a strided array using an improved Kahan–\n    Babuška algorithm and alternative indexing semantics.\n","base.strided.meankbn2":"\nbase.strided.meankbn2( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the arithmetic mean of a strided array using a second-order\n    iterative Kahan–Babuška algorithm.\n","base.strided.meankbn2.ndarray":"\nbase.strided.meankbn2.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a strided array using a second-order\n    iterative Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.meanors":"\nbase.strided.meanors( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the arithmetic mean of a strided array using ordinary recursive\n    summation.\n","base.strided.meanors.ndarray":"\nbase.strided.meanors.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a strided array using ordinary recursive\n    summation and alternative indexing semantics.\n","base.strided.meanpn":"\nbase.strided.meanpn( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the arithmetic mean of a strided array using a two-pass error\n    correction algorithm.\n","base.strided.meanpn.ndarray":"\nbase.strided.meanpn.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a strided array using a two-pass error\n    correction algorithm and alternative indexing semantics.\n","base.strided.meanpw":"\nbase.strided.meanpw( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the arithmetic mean of a strided array using pairwise summation.\n","base.strided.meanpw.ndarray":"\nbase.strided.meanpw.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a strided array using pairwise summation and\n    alternative indexing semantics.\n","base.strided.meanwd":"\nbase.strided.meanwd( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the arithmetic mean of a strided array using Welford's algorithm.\n","base.strided.meanwd.ndarray":"\nbase.strided.meanwd.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a strided array using Welford's algorithm\n    and alternative indexing semantics.\n","base.strided.mediansorted":"\nbase.strided.mediansorted( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the median value of a sorted strided array.\n","base.strided.mediansorted.ndarray":"\nbase.strided.mediansorted.ndarray( N:integer, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Computes the median value of a sorted strided array using alternative\n    indexing semantics.\n","base.strided.metaDataProps":"\nbase.strided.metaDataProps( meta:Object, dtypes:ArrayLikeObject, \n  obj:Object|Function, bool:boolean )\n    Defines non-enumerable read-only properties which expose strided array\n    function meta data.\n","base.strided.min":"\nbase.strided.min( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the minimum value of a strided array.\n","base.strided.min.ndarray":"\nbase.strided.min.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the minimum value of a strided array using alternative indexing\n    semantics.\n","base.strided.minabs":"\nbase.strided.minabs( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the minimum absolute value of a strided array.\n","base.strided.minabs.ndarray":"\nbase.strided.minabs.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the minimum absolute value of a strided array using alternative\n    indexing semantics.\n","base.strided.minBy":"\nbase.strided.minBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n  clbk:Function[, thisArg:any] )\n    Calculates the minimum value of a strided array via a callback function.\n","base.strided.minBy.ndarray":"\nbase.strided.minBy.ndarray( N:integer, x:Array|TypedArray|Object, \n  stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n    Calculates the minimum value of a strided array via a callback function and\n    using alternative indexing semantics.\n","base.strided.minsorted":"\nbase.strided.minsorted( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the minimum value of a sorted strided array.\n","base.strided.minsorted.ndarray":"\nbase.strided.minsorted.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the minimum value of a sorted strided array using alternative\n    indexing semantics.\n","base.strided.minViewBufferIndex":"\nbase.strided.minViewBufferIndex( N:integer, stride:integer, offset:integer )\n    Returns the minimum accessible index based on a set of provided strided\n    array parameters.\n","base.strided.mskmax":"\nbase.strided.mskmax( N:integer, x:Array|TypedArray, strideX:integer, \n  mask:Array|TypedArray, strideMask:integer )\n    Computes the maximum value of a strided array according to a mask.\n","base.strided.mskmax.ndarray":"\nbase.strided.mskmax.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n  offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n  offsetMask:integer )\n    Computes the maximum value of a strided array according to a mask and using\n    alternative indexing semantics.\n","base.strided.mskmin":"\nbase.strided.mskmin( N:integer, x:Array|TypedArray, strideX:integer, \n  mask:Array|TypedArray, strideMask:integer )\n    Computes the minimum value of a strided array according to a mask.\n","base.strided.mskmin.ndarray":"\nbase.strided.mskmin.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n  offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n  offsetMask:integer )\n    Computes the minimum value of a strided array according to a mask and using\n    alternative indexing semantics.\n","base.strided.mskrange":"\nbase.strided.mskrange( N:integer, x:Array|TypedArray, strideX:integer, \n  mask:Array|TypedArray, strideMask:integer )\n    Computes the range of a strided array according to a mask.\n","base.strided.mskrange.ndarray":"\nbase.strided.mskrange.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n  offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n  offsetMask:integer )\n    Computes the range of a strided array according to a mask and using\n    alternative indexing semantics.\n","base.strided.mskunary":"\nbase.strided.mskunary( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  fcn:Function )\n    Applies a unary callback to elements in a strided input array according to\n    elements in a strided mask array and assigns results to elements in a\n    strided output array.\n","base.strided.mskunary.ndarray":"\nbase.strided.mskunary.ndarray( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  offsets:ArrayLikeObject<integer>, fcn:Function )\n    Applies a unary callback to elements in a strided input array according to\n    elements in a strided mask array, and assigns results to elements in a\n    strided output array using alternative indexing semantics.\n","base.strided.mskunaryDtypeSignatures":"\nbase.strided.mskunaryDtypeSignatures( dtypes1:ArrayLike<any>, \n  dtypes2:ArrayLike<any>[, options:Object] )\n    Generates a list of masked unary interface signatures from strided array\n    data types.\n","base.strided.mskunarySignatureCallbacks":"\nbase.strided.mskunarySignatureCallbacks( table:Object, \n  signatures:ArrayLike<any> )\n    Assigns callbacks to masked unary interfaces according to type promotion\n    rules.\n","base.strided.nanmax":"\nbase.strided.nanmax( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the maximum value of a strided array, ignoring `NaN` values.\n","base.strided.nanmax.ndarray":"\nbase.strided.nanmax.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the maximum value of a strided array, ignoring `NaN` values and\n    using alternative indexing semantics.\n","base.strided.nanmaxabs":"\nbase.strided.nanmaxabs( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the maximum absolute value of a strided array, ignoring `NaN`\n    values.\n","base.strided.nanmaxabs.ndarray":"\nbase.strided.nanmaxabs.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the maximum absolute value of a strided array, ignoring `NaN`\n    values and using alternative indexing semantics.\n","base.strided.nanmaxBy":"\nbase.strided.nanmaxBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n  clbk:Function[, thisArg:any] )\n    Calculates the maximum value of a strided array via a callback function,\n    ignoring `NaN` values.\n","base.strided.nanmaxBy.ndarray":"\nbase.strided.nanmaxBy.ndarray( N:integer, x:Array|TypedArray|Object, \n  stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n    Calculates the maximum value of a strided array via a callback function,\n    ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.nanmean":"\nbase.strided.nanmean( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values.\n","base.strided.nanmean.ndarray":"\nbase.strided.nanmean.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using alternative indexing semantics.\n","base.strided.nanmeanors":"\nbase.strided.nanmeanors( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using ordinary recursive summation.\n","base.strided.nanmeanors.ndarray":"\nbase.strided.nanmeanors.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using ordinary recursive summation and alternative indexing semantics.\n","base.strided.nanmeanpn":"\nbase.strided.nanmeanpn( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using a two-pass error correction algorithm.\n","base.strided.nanmeanpn.ndarray":"\nbase.strided.nanmeanpn.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using a two-pass error correction algorithm and alternative indexing\n    semantics.\n","base.strided.nanmeanwd":"\nbase.strided.nanmeanwd( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using Welford's algorithm.\n","base.strided.nanmeanwd.ndarray":"\nbase.strided.nanmeanwd.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using Welford's algorithm and alternative indexing semantics.\n","base.strided.nanmin":"\nbase.strided.nanmin( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the minimum value of a strided array, ignoring `NaN` values.\n","base.strided.nanmin.ndarray":"\nbase.strided.nanmin.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the minimum value of a strided array, ignoring `NaN` values and\n    using alternative indexing semantics.\n","base.strided.nanminabs":"\nbase.strided.nanminabs( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the minimum absolute value of a strided array, ignoring `NaN`\n    values.\n","base.strided.nanminabs.ndarray":"\nbase.strided.nanminabs.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the minimum absolute value of a strided array, ignoring `NaN`\n    values and using alternative indexing semantics.\n","base.strided.nanminBy":"\nbase.strided.nanminBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n  clbk:Function[, thisArg:any] )\n    Calculates the minimum value of a strided array via a callback function,\n    ignoring `NaN` values.\n","base.strided.nanminBy.ndarray":"\nbase.strided.nanminBy.ndarray( N:integer, x:Array|TypedArray|Object, \n  stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n    Calculates the minimum value of a strided array via a callback function,\n    ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.nanmskmax":"\nbase.strided.nanmskmax( N:integer, x:Array|TypedArray, strideX:integer, \n  mask:Array|TypedArray, strideMask:integer )\n    Computes the maximum value of a strided array according to a mask and\n    ignoring `NaN` values.\n","base.strided.nanmskmax.ndarray":"\nbase.strided.nanmskmax.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n  offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n  offsetMask:integer )\n    Computes the maximum value of a strided array according to a mask,\n    ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.nanmskmin":"\nbase.strided.nanmskmin( N:integer, x:Array|TypedArray, strideX:integer, \n  mask:Array|TypedArray, strideMask:integer )\n    Computes the minimum value of a strided array according to a mask and\n    ignoring `NaN` values.\n","base.strided.nanmskmin.ndarray":"\nbase.strided.nanmskmin.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n  offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n  offsetMask:integer )\n    Computes the minimum value of a strided array according to a mask, ignoring\n    `NaN` values and using alternative indexing semantics.\n","base.strided.nanmskrange":"\nbase.strided.nanmskrange( N:integer, x:Array|TypedArray, strideX:integer, \n  mask:Array|TypedArray, strideMask:integer )\n    Computes the range of a strided array according to a mask and ignoring `NaN`\n    values.\n","base.strided.nanmskrange.ndarray":"\nbase.strided.nanmskrange.ndarray( N:integer, x:Array|TypedArray, \n  strideX:integer, offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n  offsetMask:integer )\n    Computes the range of a strided array according to a mask, ignoring `NaN`\n    values and using alternative indexing semantics.\n","base.strided.nanrange":"\nbase.strided.nanrange( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the range of a strided array, ignoring `NaN` values.\n","base.strided.nanrange.ndarray":"\nbase.strided.nanrange.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the range of a strided array, ignoring `NaN` values and using\n    alternative indexing semantics.\n","base.strided.nanrangeBy":"\nbase.strided.nanrangeBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n  clbk:Function[, thisArg:any] )\n    Calculates the range of a strided array via a callback function, ignoring\n    `NaN` values.\n","base.strided.nanrangeBy.ndarray":"\nbase.strided.nanrangeBy.ndarray( N:integer, x:Array|TypedArray|Object, \n  stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n    Calculates the range of a strided array via a callback function, ignoring\n    `NaN` values and using alternative indexing semantics.\n","base.strided.nanstdev":"\nbase.strided.nanstdev( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values.\n","base.strided.nanstdev.ndarray":"\nbase.strided.nanstdev.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using alternative indexing semantics.\n","base.strided.nanstdevch":"\nbase.strided.nanstdevch( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass trial mean algorithm.\n","base.strided.nanstdevch.ndarray":"\nbase.strided.nanstdevch.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.nanstdevpn":"\nbase.strided.nanstdevpn( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a two-pass algorithm.\n","base.strided.nanstdevpn.ndarray":"\nbase.strided.nanstdevpn.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a two-pass algorithm and alternative indexing semantics.\n","base.strided.nanstdevtk":"\nbase.strided.nanstdevtk( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass textbook algorithm.\n","base.strided.nanstdevtk.ndarray":"\nbase.strided.nanstdevtk.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.nanstdevwd":"\nbase.strided.nanstdevwd( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using Welford's algorithm.\n","base.strided.nanstdevwd.ndarray":"\nbase.strided.nanstdevwd.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using Welford's algorithm and alternative indexing semantics.\n","base.strided.nanstdevyc":"\nbase.strided.nanstdevyc( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.nanstdevyc.ndarray":"\nbase.strided.nanstdevyc.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass algorithm proposed by Youngs and Cramer and alternative\n    indexing semantics.\n","base.strided.nanvariance":"\nbase.strided.nanvariance( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array ignoring `NaN` values.\n","base.strided.nanvariance.ndarray":"\nbase.strided.nanvariance.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using\n    alternative indexing semantics.\n","base.strided.nanvariancech":"\nbase.strided.nanvariancech( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass trial mean algorithm.\n","base.strided.nanvariancech.ndarray":"\nbase.strided.nanvariancech.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.nanvariancepn":"\nbase.strided.nanvariancepn( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    two-pass algorithm.\n","base.strided.nanvariancepn.ndarray":"\nbase.strided.nanvariancepn.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    two-pass algorithm and alternative indexing semantics.\n","base.strided.nanvariancetk":"\nbase.strided.nanvariancetk( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass textbook algorithm.\n","base.strided.nanvariancetk.ndarray":"\nbase.strided.nanvariancetk.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.nanvariancewd":"\nbase.strided.nanvariancewd( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using\n    Welford's algorithm.\n","base.strided.nanvariancewd.ndarray":"\nbase.strided.nanvariancewd.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using\n    Welford's algorithm and alternative indexing semantics.\n","base.strided.nanvarianceyc":"\nbase.strided.nanvarianceyc( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.nanvarianceyc.ndarray":"\nbase.strided.nanvarianceyc.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass algorithm proposed by Youngs and Cramer and alternative indexing\n    semantics.\n","base.strided.nullary":"\nbase.strided.nullary( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  fcn:Function )\n    Applies a nullary callback and assigns results to elements in a strided\n    output array.\n","base.strided.nullary.ndarray":"\nbase.strided.nullary.ndarray( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  offsets:ArrayLikeObject<integer>, fcn:Function )\n    Applies a nullary callback and assigns results to elements in a strided\n    output array using alternative indexing semantics.\n","base.strided.offsetView":"\nbase.strided.offsetView( x:TypedArray, offset:integer )\n    Returns a typed array view having the same data type as a provided input\n    typed array and starting at a specified index offset.\n","base.strided.quaternary":"\nbase.strided.quaternary( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  fcn:Function )\n    Applies a quaternary callback to strided input array elements and assigns\n    results to elements in a strided output array.\n","base.strided.quaternary.ndarray":"\nbase.strided.quaternary.ndarray( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  offsets:ArrayLikeObject<integer>, fcn:Function )\n    Applies a quaternary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n","base.strided.quinary":"\nbase.strided.quinary( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  fcn:Function )\n    Applies a quinary callback to strided input array elements and assigns\n    results to elements in a strided output array.\n","base.strided.quinary.ndarray":"\nbase.strided.quinary.ndarray( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  offsets:ArrayLikeObject<integer>, fcn:Function )\n    Applies a quinary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n","base.strided.range":"\nbase.strided.range( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the range of a strided array.\n","base.strided.range.ndarray":"\nbase.strided.range.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the range of a strided array using alternative indexing semantics.\n","base.strided.rangeBy":"\nbase.strided.rangeBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n  clbk:Function[, thisArg:any] )\n    Calculates the range of a strided array via a callback function.\n","base.strided.rangeBy.ndarray":"\nbase.strided.rangeBy.ndarray( N:integer, x:Array|TypedArray|Object, \n  stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n    Calculates the range of a strided array via a callback function and using\n    alternative indexing semantics.\n","base.strided.reinterpretComplex":"\nbase.strided.reinterpretComplex( x:Complex128Array|Complex64Array, \n  offset:integer )\n    Returns a real-valued floating-point array view of a complex-valued\n    floating-point array having the same precision.\n","base.strided.reinterpretComplex64":"\nbase.strided.reinterpretComplex64( x:Complex64Array, offset:integer )\n    Returns a Float32Array view of a Complex64Array.\n","base.strided.reinterpretComplex128":"\nbase.strided.reinterpretComplex128( x:Complex128Array, offset:integer )\n    Returns a Float64Array view of a Complex128Array.\n","base.strided.sabs":"\nbase.strided.sabs( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer )\n    Computes the absolute value for each element in a single-precision floating-\n    point strided array `x` and assigns the results to elements in a single-\n    precision floating-point strided array `y`.\n","base.strided.sabs.ndarray":"\nbase.strided.sabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the absolute value for each element in a single-precision floating-\n    point strided array `x` and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.sabs2":"\nbase.strided.sabs2( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer )\n    Computes the squared absolute value for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y`.\n","base.strided.sabs2.ndarray":"\nbase.strided.sabs2.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the squared absolute value for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.sapx":"\nbase.strided.sapx( N:integer, alpha:number, x:Float32Array, stride:integer )\n    Adds a constant to each element in a single-precision floating-point strided\n    array.\n","base.strided.sapx.ndarray":"\nbase.strided.sapx.ndarray( N:integer, alpha:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Adds a constant to each element in a single-precision floating-point strided\n    array using alternative indexing semantics.\n","base.strided.sapxsum":"\nbase.strided.sapxsum( N:integer, alpha:number, x:Float32Array, stride:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum.\n","base.strided.sapxsum.ndarray":"\nbase.strided.sapxsum.ndarray( N:integer, alpha:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using alternative indexing semantics.\n","base.strided.sapxsumkbn":"\nbase.strided.sapxsumkbn( N:integer, alpha:number, x:Float32Array, \n  stride:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using an improved Kahan–Babuška algorithm.\n","base.strided.sapxsumkbn.ndarray":"\nbase.strided.sapxsumkbn.ndarray( N:integer, alpha:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n","base.strided.sapxsumkbn2":"\nbase.strided.sapxsumkbn2( N:integer, alpha:number, x:Float32Array, \n  stride:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using a second-order iterative Kahan–Babuška\n    algorithm.\n","base.strided.sapxsumkbn2.ndarray":"\nbase.strided.sapxsumkbn2.ndarray( N:integer, alpha:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n","base.strided.sapxsumors":"\nbase.strided.sapxsumors( N:integer, alpha:number, x:Float32Array, \n  stride:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using ordinary recursive summation.\n","base.strided.sapxsumors.ndarray":"\nbase.strided.sapxsumors.ndarray( N:integer, alpha:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using ordinary recursive summation and\n    alternative indexing semantics.\n","base.strided.sapxsumpw":"\nbase.strided.sapxsumpw( N:integer, alpha:number, x:Float32Array, \n  stride:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using pairwise summation.\n","base.strided.sapxsumpw.ndarray":"\nbase.strided.sapxsumpw.ndarray( N:integer, alpha:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using pairwise summation and alternative\n    indexing semantics.\n","base.strided.sasum":"\nbase.strided.sasum( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of the absolute values.\n","base.strided.sasum.ndarray":"\nbase.strided.sasum.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of absolute values using alternative indexing semantics.\n","base.strided.sasumpw":"\nbase.strided.sasumpw( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of absolute values (L1 norm) of single-precision floating-\n    point strided array elements using pairwise summation.\n","base.strided.sasumpw.ndarray":"\nbase.strided.sasumpw.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of absolute values (L1 norm) of single-precision floating-\n    point strided array elements using pairwise summation and alternative\n    indexing semantics.\n","base.strided.saxpy":"\nbase.strided.saxpy( N:integer, alpha:number, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n","base.strided.saxpy.ndarray":"\nbase.strided.saxpy.ndarray( N:integer, alpha:number, x:Float32Array, \n  strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n  offsetY:integer )\n    Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n    using alternative indexing semantics.\n","base.strided.scbrt":"\nbase.strided.scbrt( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer )\n    Computes the cube root of each element in a single-precision floating-point \n    strided array `x` and assigns the results to elements in a single-precision \n    floating-point strided array `y`.\n","base.strided.scbrt.ndarray":"\nbase.strided.scbrt.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the cube root of each element in a single-precision floating-point \n    strided array `x` and assigns the results to elements in a single-precision \n    floating-point strided array `y` using alternative indexing semantics.\n","base.strided.sceil":"\nbase.strided.sceil( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward positive infinity and assigns the results to elements in a single-\n    precision floating-point strided array `y`.\n","base.strided.sceil.ndarray":"\nbase.strided.sceil.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward positive infinity and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.scopy":"\nbase.strided.scopy( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer )\n    Copies values from `x` into `y`.\n","base.strided.scopy.ndarray":"\nbase.strided.scopy.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Copies values from `x` into `y` using alternative indexing semantics.\n","base.strided.scumax":"\nbase.strided.scumax( N:integer, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Computes the cumulative maximum of single-precision floating-point strided\n    array elements.\n","base.strided.scumax.ndarray":"\nbase.strided.scumax.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the cumulative maximum of single-precision floating-point strided\n    array elements using alternative indexing semantics.\n","base.strided.scumaxabs":"\nbase.strided.scumaxabs( N:integer, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Computes the cumulative maximum absolute value of single-precision floating-\n    point strided array elements.\n","base.strided.scumaxabs.ndarray":"\nbase.strided.scumaxabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the cumulative maximum absolute value of single-precision floating-\n    point strided array elements using alternative indexing semantics.\n","base.strided.scumin":"\nbase.strided.scumin( N:integer, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Computes the cumulative minimum of single-precision floating-point strided\n    array elements.\n","base.strided.scumin.ndarray":"\nbase.strided.scumin.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the cumulative minimum of single-precision floating-point strided\n    array elements using alternative indexing semantics.\n","base.strided.scuminabs":"\nbase.strided.scuminabs( N:integer, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Computes the cumulative minimum absolute value of single-precision floating-\n    point strided array elements.\n","base.strided.scuminabs.ndarray":"\nbase.strided.scuminabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the cumulative minimum absolute value of single-precision floating-\n    point strided array elements using alternative indexing semantics.\n","base.strided.scusum":"\nbase.strided.scusum( N:integer, sum:number, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements.\n","base.strided.scusum.ndarray":"\nbase.strided.scusum.ndarray( N:integer, sum:number, x:Float32Array, \n  strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using alternative indexing semantics.\n","base.strided.scusumkbn":"\nbase.strided.scusumkbn( N:integer, sum:number, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using an improved Kahan–Babuška algorithm.\n","base.strided.scusumkbn.ndarray":"\nbase.strided.scusumkbn.ndarray( N:integer, sum:number, x:Float32Array, \n  strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n","base.strided.scusumkbn2":"\nbase.strided.scusumkbn2( N:integer, sum:number, x:Float32Array, \n  strideX:integer, y:Float32Array, strideY:integer )\n    Computes the cumulative sum of single-precision floating-point strided \n    array elements using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.scusumkbn2.ndarray":"\nbase.strided.scusumkbn2.ndarray( N:integer, sum:number, x:Float32Array, \n  strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of single-precision floating-point strided\n    array elements using a second-order iterative Kahan–Babuška algorithm and\n    alternative indexing semantics.\n","base.strided.scusumors":"\nbase.strided.scusumors( N:integer, sum:number, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using ordinary recursive summation.\n","base.strided.scusumors.ndarray":"\nbase.strided.scusumors.ndarray( N:integer, sum:number, x:Float32Array, \n  strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using ordinary recursive summation and alternative indexing\n    semantics.\n","base.strided.scusumpw":"\nbase.strided.scusumpw( N:integer, sum:number, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using pairwise summation.\n","base.strided.scusumpw.ndarray":"\nbase.strided.scusumpw.ndarray( N:integer, sum:number, x:Float32Array, \n  strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using pairwise summation and alternative indexing semantics.\n","base.strided.sdeg2rad":"\nbase.strided.sdeg2rad( N:integer, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Converts each element in a single-precision floating-point strided array `x`\n    from degrees to radians and assigns the results to elements in a single-\n    precision floating-point strided array `y`.\n","base.strided.sdeg2rad.ndarray":"\nbase.strided.sdeg2rad.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Converts each element in a single-precision floating-point strided array `x`\n    from degrees to radians and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.sdot":"\nbase.strided.sdot( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer )\n    Computes the dot product of two single-precision floating-point vectors.\n","base.strided.sdot.ndarray":"\nbase.strided.sdot.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the dot product of two single-precision floating-point vectors\n    using alternative indexing semantics.\n","base.strided.sdsapxsum":"\nbase.strided.sdsapxsum( N:integer, alpha:number, x:Float32Array, \n  stride:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using extended accumulation.\n","base.strided.sdsapxsum.ndarray":"\nbase.strided.sdsapxsum.ndarray( N:integer, alpha:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using extended accumulation and alternative\n    indexing semantics.\n","base.strided.sdsapxsumpw":"\nbase.strided.sdsapxsumpw( N:integer, alpha:number, x:Float32Array, \n  stride:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using pairwise summation with extended\n    accumulation.\n","base.strided.sdsapxsumpw.ndarray":"\nbase.strided.sdsapxsumpw.ndarray( N:integer, alpha:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using pairwise summation with extended\n    accumulation and alternative indexing semantics.\n","base.strided.sdsdot":"\nbase.strided.sdsdot( N:integer, scalar:number, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Computes the dot product of two single-precision floating-point vectors with\n    extended accumulation.\n","base.strided.sdsdot.ndarray":"\nbase.strided.sdsdot.ndarray( N:integer, scalar:number, x:Float32Array, \n  strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n  offsetY:integer )\n    Computes the dot product of two single-precision floating-point vectors\n    using alternative indexing semantics and with extended accumulation.\n","base.strided.sdsmean":"\nbase.strided.sdsmean( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using extended accumulation.\n","base.strided.sdsmean.ndarray":"\nbase.strided.sdsmean.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using extended accumulation and alternative indexing semantics.\n","base.strided.sdsmeanors":"\nbase.strided.sdsmeanors( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation with extended accumulation.\n","base.strided.sdsmeanors.ndarray":"\nbase.strided.sdsmeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation with extended accumulation and\n    alternative indexing semantics.\n","base.strided.sdsnanmean":"\nbase.strided.sdsnanmean( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using extended accumulation.\n","base.strided.sdsnanmean.ndarray":"\nbase.strided.sdsnanmean.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using extended accumulation and alternative\n    indexing semantics.\n","base.strided.sdsnanmeanors":"\nbase.strided.sdsnanmeanors( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation with\n    extended accumulation.\n","base.strided.sdsnanmeanors.ndarray":"\nbase.strided.sdsnanmeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation with\n    extended accumulation and alternative indexing semantics.\n","base.strided.sdsnansum":"\nbase.strided.sdsnansum( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of single-precision floating-point strided array\n    elements, ignore `NaN` values and using extended accumulation.\n","base.strided.sdsnansum.ndarray":"\nbase.strided.sdsnansum.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using extended accumulation and alternative\n    indexing semantics.\n","base.strided.sdsnansumpw":"\nbase.strided.sdsnansumpw( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation with extended\n    accumulation.\n","base.strided.sdsnansumpw.ndarray":"\nbase.strided.sdsnansumpw.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation with extended\n    accumulation and alternative indexing semantics.\n","base.strided.sdssum":"\nbase.strided.sdssum( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using extended accumulation.\n","base.strided.sdssum.ndarray":"\nbase.strided.sdssum.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using extended accumulation and alternative indexing semantics.\n","base.strided.sdssumpw":"\nbase.strided.sdssumpw( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation with extended accumulation.\n","base.strided.sdssumpw.ndarray":"\nbase.strided.sdssumpw.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation with extended accumulation and alternative indexing\n    semantics.\n","base.strided.sfill":"\nbase.strided.sfill( N:integer, alpha:number, x:Float32Array, strideX:integer )\n    Fills a single-precision floating-point strided array with a specified\n    scalar value.\n","base.strided.sfill.ndarray":"\nbase.strided.sfill.ndarray( N:integer, alpha:number, x:Float32Array, \n  strideX:integer, offsetX:integer )\n    Fills a single-precision floating-point strided array with a specified\n    scalar value using alternative indexing semantics.\n","base.strided.sfloor":"\nbase.strided.sfloor( N:integer, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward negative infinity and assigns the results to elements in a single-\n    precision floating-point strided array `y`.\n","base.strided.sfloor.ndarray":"\nbase.strided.sfloor.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward negative infinity and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.sinv":"\nbase.strided.sinv( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer )\n    Computes the multiplicative inverse for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y`.\n","base.strided.sinv.ndarray":"\nbase.strided.sinv.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the multiplicative inverse for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.smap":"\nbase.strided.smap( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer, fcn:Function )\n    Applies a unary function to a single-precision floating-point strided input\n    array and assigns results to a single-precision floating-point strided\n    output array.\n","base.strided.smap.ndarray":"\nbase.strided.smap.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer, \n  fcn:Function )\n    Applies a unary function to a single-precision floating-point strided input\n    array and assigns results to a single-precision floating-point strided\n    output array using alternative indexing semantics.\n","base.strided.smap2":"\nbase.strided.smap2( N:integer, x:Float32Array, sx:integer, y:Float32Array, \n  sy:integer, z:Float32Array, sz:integer, fcn:Function )\n    Applies a binary function to single-precision floating-point strided input\n    arrays and assigns results to a single-precision floating-point strided\n    output array.\n","base.strided.smap2.ndarray":"\nbase.strided.smap2.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, \n  y:Float32Array, sy:integer, oy:integer, z:Float32Array, sz:integer, \n  oz:integer, fcn:Function )\n    Applies a binary function to single-precision floating-point strided input\n    arrays and assigns results to a single-precision floating-point strided\n    output array using alternative indexing semantics.\n","base.strided.smax":"\nbase.strided.smax( N:integer, x:Float32Array, strideX:integer )\n    Computes the maximum value of a single-precision floating-point strided\n    array.\n","base.strided.smax.ndarray":"\nbase.strided.smax.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum value of a single-precision floating-point strided\n    array using alternative indexing semantics.\n","base.strided.smaxabs":"\nbase.strided.smaxabs( N:integer, x:Float32Array, strideX:integer )\n    Computes the maximum absolute value of a single-precision floating-point\n    strided array.\n","base.strided.smaxabs.ndarray":"\nbase.strided.smaxabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum absolute value of a single-precision floating-point\n    strided array using alternative indexing semantics.\n","base.strided.smaxabssorted":"\nbase.strided.smaxabssorted( N:integer, x:Float32Array, stride:integer )\n    Computes the maximum absolute value of a sorted single-precision floating-\n    point strided array.\n","base.strided.smaxabssorted.ndarray":"\nbase.strided.smaxabssorted.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the maximum absolute value of a sorted single-precision floating-\n    point strided array using alternative indexing semantics.\n","base.strided.smaxsorted":"\nbase.strided.smaxsorted( N:integer, x:Float32Array, stride:integer )\n    Computes the maximum value of a sorted single-precision floating-point\n    strided array.\n","base.strided.smaxsorted.ndarray":"\nbase.strided.smaxsorted.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the maximum value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n","base.strided.smean":"\nbase.strided.smean( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array.\n","base.strided.smean.ndarray":"\nbase.strided.smean.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using alternative indexing semantics.\n","base.strided.smeankbn":"\nbase.strided.smeankbn( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm.\n","base.strided.smeankbn.ndarray":"\nbase.strided.smeankbn.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n","base.strided.smeankbn2":"\nbase.strided.smeankbn2( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.smeankbn2.ndarray":"\nbase.strided.smeankbn2.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n","base.strided.smeanli":"\nbase.strided.smeanli( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm.\n","base.strided.smeanli.ndarray":"\nbase.strided.smeanli.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n","base.strided.smeanlipw":"\nbase.strided.smeanlipw( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm with pairwise summation.\n","base.strided.smeanlipw.ndarray":"\nbase.strided.smeanlipw.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm with pairwise summation and\n    alternative indexing semantics.\n","base.strided.smeanors":"\nbase.strided.smeanors( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation.\n","base.strided.smeanors.ndarray":"\nbase.strided.smeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation and alternative indexing semantics.\n","base.strided.smeanpn":"\nbase.strided.smeanpn( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a two-pass error correction algorithm.\n","base.strided.smeanpn.ndarray":"\nbase.strided.smeanpn.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a two-pass error correction algorithm and alternative indexing\n    semantics.\n","base.strided.smeanpw":"\nbase.strided.smeanpw( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using pairwise summation.\n","base.strided.smeanpw.ndarray":"\nbase.strided.smeanpw.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using pairwise summation and alternative indexing semantics.\n","base.strided.smeanwd":"\nbase.strided.smeanwd( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using Welford's algorithm.\n","base.strided.smeanwd.ndarray":"\nbase.strided.smeanwd.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n","base.strided.smediansorted":"\nbase.strided.smediansorted( N:integer, x:Float32Array, stride:integer )\n    Computes the median value of a sorted single-precision floating-point\n    strided array.\n","base.strided.smediansorted.ndarray":"\nbase.strided.smediansorted.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the median value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n","base.strided.smidrange":"\nbase.strided.smidrange( N:integer, x:Float32Array, strideX:integer )\n    Computes the mid-range of a single-precision floating-point strided array.\n","base.strided.smidrange.ndarray":"\nbase.strided.smidrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the mid-range of a single-precision floating-point strided array\n    using alternative indexing semantics.\n","base.strided.smin":"\nbase.strided.smin( N:integer, x:Float32Array, strideX:integer )\n    Computes the minimum value of a single-precision floating-point strided\n    array.\n","base.strided.smin.ndarray":"\nbase.strided.smin.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the minimum value of a single-precision floating-point strided\n    array using alternative indexing semantics.\n","base.strided.sminabs":"\nbase.strided.sminabs( N:integer, x:Float32Array, strideX:integer )\n    Computes the minimum absolute value of a single-precision floating-point\n    strided array.\n","base.strided.sminabs.ndarray":"\nbase.strided.sminabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the minimum absolute value of a single-precision floating-point\n    strided array using alternative indexing semantics.\n","base.strided.sminsorted":"\nbase.strided.sminsorted( N:integer, x:Float32Array, stride:integer )\n    Computes the minimum value of a sorted single-precision floating-point\n    strided array.\n","base.strided.sminsorted.ndarray":"\nbase.strided.sminsorted.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the minimum value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n","base.strided.smskabs":"\nbase.strided.smskabs( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Computes the absolute value for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskabs.ndarray":"\nbase.strided.smskabs.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n  sy:integer, oy:integer )\n    Computes the absolute value for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n","base.strided.smskabs2":"\nbase.strided.smskabs2( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Computes the squared absolute value for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point\n    strided array `y`.\n","base.strided.smskabs2.ndarray":"\nbase.strided.smskabs2.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n  sy:integer, oy:integer )\n    Computes the squared absolute value for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point\n    strided array `y` using alternative indexing semantics.\n","base.strided.smskcbrt":"\nbase.strided.smskcbrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Computes the cube root for each element in a single-precision floating-point\n    strided array `x` according to a strided mask array and assigns the results\n    to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskcbrt.ndarray":"\nbase.strided.smskcbrt.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n  sy:integer, oy:integer )\n    Computes the cube root for each element in a single-precision floating-point\n    strided array `x` according to a strided mask array and assigns the results\n    to elements in a single-precision floating-point strided array `y` using\n    alternative indexing semantics.\n","base.strided.smskceil":"\nbase.strided.smskceil( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward positive infinity according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskceil.ndarray":"\nbase.strided.smskceil.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n  sy:integer, oy:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward positive infinity according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n","base.strided.smskdeg2rad":"\nbase.strided.smskdeg2rad( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Converts each element in a single-precision floating-point strided array `x`\n    from degrees to radians according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskdeg2rad.ndarray":"\nbase.strided.smskdeg2rad.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n  sy:integer, oy:integer )\n    Converts each element in a single-precision floating-point strided array `x`\n    from degrees to radians according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n","base.strided.smskfloor":"\nbase.strided.smskfloor( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward negative infinity according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskfloor.ndarray":"\nbase.strided.smskfloor.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n  sy:integer, oy:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward negative infinity according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n","base.strided.smskinv":"\nbase.strided.smskinv( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Computes the multiplicative inverse for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y`.\n","base.strided.smskinv.ndarray":"\nbase.strided.smskinv.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n  sy:integer, oy:integer )\n    Computes the multiplicative inverse for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y` using alternative indexing semantics.\n","base.strided.smskmap":"\nbase.strided.smskmap( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer, fcn:Function )\n    Applies a unary function to a single-precision floating-point strided input\n    array according to a strided mask array and assigns results to a single-\n    precision floating-point strided output array.\n","base.strided.smskmap.ndarray":"\nbase.strided.smskmap.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Uint8Array, sm:integer, om:integer, y:Float32Array, sy:integer, \n  oy:integer, fcn:Function )\n    Applies a unary function to a single-precision floating-point strided input\n    array according to a strided mask array and assigns results to a single-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n","base.strided.smskmap2":"\nbase.strided.smskmap2( N:integer, x:Float32Array, sx:integer, y:Float32Array, \n  sy:integer, m:Uint8Array, sm:integer, z:Float32Array, sz:integer, \n  fcn:Function )\n    Applies a binary function to single-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a single-\n    precision floating-point strided output array.\n","base.strided.smskmap2.ndarray":"\nbase.strided.smskmap2.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, y:Float32Array, sy:integer, oy:integer, m:Uint8Array, sm:integer, \n  om:integer, z:Float32Array, sz:integer, oz:integer, fcn:Function )\n    Applies a binary function to single-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a single-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n","base.strided.smskmax":"\nbase.strided.smskmax( N:integer, x:Float32Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask.\n","base.strided.smskmax.ndarray":"\nbase.strided.smskmax.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n","base.strided.smskmin":"\nbase.strided.smskmin( N:integer, x:Float32Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask.\n","base.strided.smskmin.ndarray":"\nbase.strided.smskmin.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n","base.strided.smskramp":"\nbase.strided.smskramp( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Evaluates the ramp function for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskramp.ndarray":"\nbase.strided.smskramp.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n  sy:integer, oy:integer )\n    Evaluates the ramp function for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n","base.strided.smskrange":"\nbase.strided.smskrange( N:integer, x:Float32Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask.\n","base.strided.smskrange.ndarray":"\nbase.strided.smskrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask and using alternative indexing semantics.\n","base.strided.smskrsqrt":"\nbase.strided.smskrsqrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Computes the reciprocal square root for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y`.\n","base.strided.smskrsqrt.ndarray":"\nbase.strided.smskrsqrt.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n  sy:integer, oy:integer )\n    Computes the reciprocal square root for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y` using alternative indexing semantics.\n","base.strided.smsksqrt":"\nbase.strided.smsksqrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Computes the principal square root for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y`.\n","base.strided.smsksqrt.ndarray":"\nbase.strided.smsksqrt.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n  sy:integer, oy:integer )\n    Computes the principal square root for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y` using alternative indexing semantics.\n","base.strided.smsktrunc":"\nbase.strided.smsktrunc( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward zero according to a strided mask array and assigns the results to\n    elements in a single-precision floating-point strided array `y`.\n","base.strided.smsktrunc.ndarray":"\nbase.strided.smsktrunc.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n  sy:integer, oy:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward zero according to a strided mask array and assigns the results to\n    elements in a single-precision floating-point strided array `y` using\n    alternative indexing semantics.\n","base.strided.snanmax":"\nbase.strided.snanmax( N:integer, x:Float32Array, strideX:integer )\n    Computes the maximum value of a single-precision floating-point strided\n    array, ignoring `NaN` values.\n","base.strided.snanmax.ndarray":"\nbase.strided.snanmax.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum value of a single-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanmaxabs":"\nbase.strided.snanmaxabs( N:integer, x:Float32Array, strideX:integer )\n    Computes the maximum absolute value of a single-precision floating-point\n    strided array, ignoring `NaN` values.\n","base.strided.snanmaxabs.ndarray":"\nbase.strided.snanmaxabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum absolute value of a single-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n","base.strided.snanmean":"\nbase.strided.snanmean( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values.\n","base.strided.snanmean.ndarray":"\nbase.strided.snanmean.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanmeanors":"\nbase.strided.snanmeanors( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.snanmeanors.ndarray":"\nbase.strided.snanmeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation and\n    alternative indexing semantics.\n","base.strided.snanmeanpn":"\nbase.strided.snanmeanpn( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction\n    algorithm.\n","base.strided.snanmeanpn.ndarray":"\nbase.strided.snanmeanpn.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction algorithm\n    and alternative indexing semantics.\n","base.strided.snanmeanwd":"\nbase.strided.snanmeanwd( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm.\n","base.strided.snanmeanwd.ndarray":"\nbase.strided.snanmeanwd.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n","base.strided.snanmin":"\nbase.strided.snanmin( N:integer, x:Float32Array, strideX:integer )\n    Computes the minimum value of a single-precision floating-point strided\n    array, ignoring `NaN` values.\n","base.strided.snanmin.ndarray":"\nbase.strided.snanmin.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the minimum value of a single-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanminabs":"\nbase.strided.snanminabs( N:integer, x:Float32Array, strideX:integer )\n    Computes the minimum absolute value of a single-precision floating-point\n    strided array, ignoring `NaN` values.\n","base.strided.snanminabs.ndarray":"\nbase.strided.snanminabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the minimum absolute value of a single-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n","base.strided.snanmskmax":"\nbase.strided.snanmskmax( N:integer, x:Float32Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask, ignoring `NaN` values.\n","base.strided.snanmskmax.ndarray":"\nbase.strided.snanmskmax.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n","base.strided.snanmskmin":"\nbase.strided.snanmskmin( N:integer, x:Float32Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask, ignoring `NaN` values.\n","base.strided.snanmskmin.ndarray":"\nbase.strided.snanmskmin.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n","base.strided.snanmskrange":"\nbase.strided.snanmskrange( N:integer, x:Float32Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask, ignoring `NaN` values.\n","base.strided.snanmskrange.ndarray":"\nbase.strided.snanmskrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask, ignoring `NaN` values and using alternative indexing\n    semantics.\n","base.strided.snanrange":"\nbase.strided.snanrange( N:integer, x:Float32Array, strideX:integer )\n    Computes the range of a single-precision floating-point strided array,\n    ignoring `NaN` values.\n","base.strided.snanrange.ndarray":"\nbase.strided.snanrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the range of a single-precision floating-point strided array,\n    ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanstdev":"\nbase.strided.snanstdev( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values.\n","base.strided.snanstdev.ndarray":"\nbase.strided.snanstdev.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and alternative indexing semantics.\n","base.strided.snanstdevch":"\nbase.strided.snanstdevch( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.snanstdevch.ndarray":"\nbase.strided.snanstdevch.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n","base.strided.snanstdevpn":"\nbase.strided.snanstdevpn( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.snanstdevpn.ndarray":"\nbase.strided.snanstdevpn.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n","base.strided.snanstdevtk":"\nbase.strided.snanstdevtk( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.snanstdevtk.ndarray":"\nbase.strided.snanstdevtk.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n","base.strided.snanstdevwd":"\nbase.strided.snanstdevwd( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using Welford's algorithm.\n","base.strided.snanstdevwd.ndarray":"\nbase.strided.snanstdevwd.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n","base.strided.snanstdevyc":"\nbase.strided.snanstdevyc( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass algorithm proposed by\n    Youngs and Cramer.\n","base.strided.snanstdevyc.ndarray":"\nbase.strided.snanstdevyc.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass algorithm proposed by\n    Youngs and Cramer and alternative indexing semantics.\n","base.strided.snansum":"\nbase.strided.snansum( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values.\n","base.strided.snansum.ndarray":"\nbase.strided.snansum.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snansumkbn":"\nbase.strided.snansumkbn( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n","base.strided.snansumkbn.ndarray":"\nbase.strided.snansumkbn.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n","base.strided.snansumkbn2":"\nbase.strided.snansumkbn2( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm.\n","base.strided.snansumkbn2.ndarray":"\nbase.strided.snansumkbn2.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n","base.strided.snansumors":"\nbase.strided.snansumors( N:integer, x:Float32Array, strideX:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.snansumors.ndarray":"\nbase.strided.snansumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation and alternative\n    indexing semantics.\n","base.strided.snansumpw":"\nbase.strided.snansumpw( N:integer, x:Float32Array, strideX:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation.\n","base.strided.snansumpw.ndarray":"\nbase.strided.snansumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation and alternative indexing\n    semantics.\n","base.strided.snanvariance":"\nbase.strided.snanvariance( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values.\n","base.strided.snanvariance.ndarray":"\nbase.strided.snanvariance.ndarray( N:integer, correction:number, \n  x:Float32Array, stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanvariancech":"\nbase.strided.snanvariancech( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.snanvariancech.ndarray":"\nbase.strided.snanvariancech.ndarray( N:integer, correction:number, \n  x:Float32Array, stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n","base.strided.snanvariancepn":"\nbase.strided.snanvariancepn( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.snanvariancepn.ndarray":"\nbase.strided.snanvariancepn.ndarray( N:integer, correction:number, \n  x:Float32Array, stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n","base.strided.snanvariancetk":"\nbase.strided.snanvariancetk( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.snanvariancetk.ndarray":"\nbase.strided.snanvariancetk.ndarray( N:integer, correction:number, \n  x:Float32Array, stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n","base.strided.snanvariancewd":"\nbase.strided.snanvariancewd( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using Welford's algorithm.\n","base.strided.snanvariancewd.ndarray":"\nbase.strided.snanvariancewd.ndarray( N:integer, correction:number, \n  x:Float32Array, stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using Welford's algorithm and alternative indexing\n    semantics.\n","base.strided.snanvarianceyc":"\nbase.strided.snanvarianceyc( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n    Cramer.\n","base.strided.snanvarianceyc.ndarray":"\nbase.strided.snanvarianceyc.ndarray( N:integer, correction:number, \n  x:Float32Array, stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n    Cramer and alternative indexing semantics.\n","base.strided.snrm2":"\nbase.strided.snrm2( N:integer, x:Float32Array, stride:integer )\n    Computes the L2-norm of a single-precision floating-point vector.\n","base.strided.snrm2.ndarray":"\nbase.strided.snrm2.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the L2-norm of a single-precision floating-point vector using\n    alternative indexing semantics.\n","base.strided.sramp":"\nbase.strided.sramp( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer )\n    Evaluates the ramp function for each element in a single-precision floating-\n    point strided array `x` and assigns the results to elements in a single-\n    precision floating-point strided array `y`.\n","base.strided.sramp.ndarray":"\nbase.strided.sramp.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Evaluates the ramp function for each element in a single-precision floating-\n    point strided array `x` and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.srange":"\nbase.strided.srange( N:integer, x:Float32Array, strideX:integer )\n    Computes the range of a single-precision floating-point strided array.\n","base.strided.srange.ndarray":"\nbase.strided.srange.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the range of a single-precision floating-point strided array using\n    alternative indexing semantics.\n","base.strided.srev":"\nbase.strided.srev( N:integer, x:Float32Array, stride:integer )\n    Reverses a single-precision floating-point strided array in-place.\n","base.strided.srev.ndarray":"\nbase.strided.srev.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Reverses a single-precision floating-point strided array in-place using\n    alternative indexing semantics.\n","base.strided.srsqrt":"\nbase.strided.srsqrt( N:integer, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Computes the reciprocal square root for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y`.\n","base.strided.srsqrt.ndarray":"\nbase.strided.srsqrt.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the reciprocal square root for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.sscal":"\nbase.strided.sscal( N:integer, alpha:number, x:Float32Array, stride:integer )\n    Multiplies a single-precision floating-point vector `x` by a constant\n    `alpha`.\n","base.strided.sscal.ndarray":"\nbase.strided.sscal.ndarray( N:integer, alpha:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Multiplies a single-precision floating-point vector `x` by a constant\n    `alpha` using alternative indexing semantics.\n","base.strided.ssort2hp":"\nbase.strided.ssort2hp( N:integer, order:number, x:Float32Array, \n  strideX:integer, y:Float32Array, strideY:integer )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using heapsort.\n","base.strided.ssort2hp.ndarray":"\nbase.strided.ssort2hp.ndarray( N:integer, order:number, x:Float32Array, \n  strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n  offsetY:integer )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using heapsort and alternative\n    indexing semantics.\n","base.strided.ssort2ins":"\nbase.strided.ssort2ins( N:integer, order:number, x:Float32Array, \n  strideX:integer, y:Float32Array, strideY:integer )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using insertion sort.\n","base.strided.ssort2ins.ndarray":"\nbase.strided.ssort2ins.ndarray( N:integer, order:number, x:Float32Array, \n  strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n  offsetY:integer )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using insertion sort and\n    alternative indexing semantics.\n","base.strided.ssort2sh":"\nbase.strided.ssort2sh( N:integer, order:number, x:Float32Array, \n  strideX:integer, y:Float32Array, strideY:integer )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using Shellsort.\n","base.strided.ssort2sh.ndarray":"\nbase.strided.ssort2sh.ndarray( N:integer, order:number, x:Float32Array, \n  strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n  offsetY:integer )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using Shellsort and alternative\n    indexing semantics.\n","base.strided.ssorthp":"\nbase.strided.ssorthp( N:integer, order:number, x:Float32Array, stride:integer )\n    Sorts a single-precision floating-point strided array using heapsort.\n","base.strided.ssorthp.ndarray":"\nbase.strided.ssorthp.ndarray( N:integer, order:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Sorts a single-precision floating-point strided array using heapsort and\n    alternative indexing semantics.\n","base.strided.ssortins":"\nbase.strided.ssortins( N:integer, order:number, x:Float32Array, stride:integer )\n    Sorts a single-precision floating-point strided array using insertion sort.\n","base.strided.ssortins.ndarray":"\nbase.strided.ssortins.ndarray( N:integer, order:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Sorts a single-precision floating-point strided array using insertion sort\n    and alternative indexing semantics.\n","base.strided.ssortsh":"\nbase.strided.ssortsh( N:integer, order:number, x:Float32Array, stride:integer )\n    Sorts a single-precision floating-point strided array using Shellsort.\n","base.strided.ssortsh.ndarray":"\nbase.strided.ssortsh.ndarray( N:integer, order:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Sorts a single-precision floating-point strided array using Shellsort and\n    alternative indexing semantics.\n","base.strided.ssqrt":"\nbase.strided.ssqrt( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer )\n    Computes the principal square root for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y`.\n","base.strided.ssqrt.ndarray":"\nbase.strided.ssqrt.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the principal square root for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.sstdev":"\nbase.strided.sstdev( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array.\n","base.strided.sstdev.ndarray":"\nbase.strided.sstdev.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using alternative indexing semantics.\n","base.strided.sstdevch":"\nbase.strided.sstdevch( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm.\n","base.strided.sstdevch.ndarray":"\nbase.strided.sstdevch.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n","base.strided.sstdevpn":"\nbase.strided.sstdevpn( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a two-pass algorithm.\n","base.strided.sstdevpn.ndarray":"\nbase.strided.sstdevpn.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a two-pass algorithm and alternative indexing semantics.\n","base.strided.sstdevtk":"\nbase.strided.sstdevtk( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass textbook algorithm.\n","base.strided.sstdevtk.ndarray":"\nbase.strided.sstdevtk.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass textbook algorithm and alternative indexing\n    semantics.\n","base.strided.sstdevwd":"\nbase.strided.sstdevwd( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using Welford's algorithm.\n","base.strided.sstdevwd.ndarray":"\nbase.strided.sstdevwd.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n","base.strided.sstdevyc":"\nbase.strided.sstdevyc( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.sstdevyc.ndarray":"\nbase.strided.sstdevyc.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer and\n    alternative indexing semantics.\n","base.strided.ssum":"\nbase.strided.ssum( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of single-precision floating-point strided array elements.\n","base.strided.ssum.ndarray":"\nbase.strided.ssum.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using alternative indexing semantics.\n","base.strided.ssumkbn":"\nbase.strided.ssumkbn( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm.\n","base.strided.ssumkbn.ndarray":"\nbase.strided.ssumkbn.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n","base.strided.ssumkbn2":"\nbase.strided.ssumkbn2( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.ssumkbn2.ndarray":"\nbase.strided.ssumkbn2.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n","base.strided.ssumors":"\nbase.strided.ssumors( N:integer, x:Float32Array, strideX:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using ordinary recursive summation.\n","base.strided.ssumors.ndarray":"\nbase.strided.ssumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using ordinary recursive summation and alternative indexing semantics.\n","base.strided.ssumpw":"\nbase.strided.ssumpw( N:integer, x:Float32Array, strideX:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation.\n","base.strided.ssumpw.ndarray":"\nbase.strided.ssumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation and alternative indexing semantics.\n","base.strided.sswap":"\nbase.strided.sswap( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer )\n    Interchanges two single-precision floating-point vectors.\n","base.strided.sswap.ndarray":"\nbase.strided.sswap.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Interchanges two single-precision floating-point vectors using alternative\n    indexing semantics.\n","base.strided.stdev":"\nbase.strided.stdev( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array.\n","base.strided.stdev.ndarray":"\nbase.strided.stdev.ndarray( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a strided array using alternative\n    indexing semantics.\n","base.strided.stdevch":"\nbase.strided.stdevch( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array using a one-pass trial\n    mean algorithm.\n","base.strided.stdevch.ndarray":"\nbase.strided.stdevch.ndarray( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a strided array using a one-pass trial\n    mean algorithm and alternative indexing semantics.\n","base.strided.stdevpn":"\nbase.strided.stdevpn( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array using a two-pass\n    algorithm.\n","base.strided.stdevpn.ndarray":"\nbase.strided.stdevpn.ndarray( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a strided array using a two-pass\n    algorithm and alternative indexing semantics.\n","base.strided.stdevtk":"\nbase.strided.stdevtk( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array using a one-pass textbook\n    algorithm.\n","base.strided.stdevtk.ndarray":"\nbase.strided.stdevtk.ndarray( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a strided array using a one-pass textbook\n    algorithm and alternative indexing semantics.\n","base.strided.stdevwd":"\nbase.strided.stdevwd( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array using Welford's\n    algorithm.\n","base.strided.stdevwd.ndarray":"\nbase.strided.stdevwd.ndarray( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a strided array using Welford's algorithm\n    and alternative indexing semantics.\n","base.strided.stdevyc":"\nbase.strided.stdevyc( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array using a one-pass\n    algorithm proposed by Youngs and Cramer.\n","base.strided.stdevyc.ndarray":"\nbase.strided.stdevyc.ndarray( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a strided array using a one-pass\n    algorithm proposed by Youngs and Cramer and alternative indexing semantics.\n","base.strided.strunc":"\nbase.strided.strunc( N:integer, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward zero and assigns the results to elements in a single-precision\n    floating-point strided array `y`.\n","base.strided.strunc.ndarray":"\nbase.strided.strunc.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward zero and assigns the results to elements in a single-precision\n    floating-point strided array `y` using alternative indexing semantics.\n","base.strided.svariance":"\nbase.strided.svariance( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array.\n","base.strided.svariance.ndarray":"\nbase.strided.svariance.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using alternative indexing semantics.\n","base.strided.svariancech":"\nbase.strided.svariancech( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass trial mean algorithm.\n","base.strided.svariancech.ndarray":"\nbase.strided.svariancech.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.svariancepn":"\nbase.strided.svariancepn( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using a two-pass algorithm.\n","base.strided.svariancepn.ndarray":"\nbase.strided.svariancepn.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using a two-pass algorithm and alternative indexing semantics.\n","base.strided.svariancetk":"\nbase.strided.svariancetk( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass textbook algorithm.\n","base.strided.svariancetk.ndarray":"\nbase.strided.svariancetk.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.svariancewd":"\nbase.strided.svariancewd( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using Welford's algorithm.\n","base.strided.svariancewd.ndarray":"\nbase.strided.svariancewd.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using Welford's algorithm and alternative indexing semantics.\n","base.strided.svarianceyc":"\nbase.strided.svarianceyc( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.svarianceyc.ndarray":"\nbase.strided.svarianceyc.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass algorithm proposed by Youngs and Cramer and alternative\n    indexing semantics.\n","base.strided.ternary":"\nbase.strided.ternary( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  fcn:Function )\n    Applies a ternary callback to strided input array elements and assigns\n    results to elements in a strided output array.\n","base.strided.ternary.ndarray":"\nbase.strided.ternary.ndarray( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  offsets:ArrayLikeObject<integer>, fcn:Function )\n    Applies a ternary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n","base.strided.unary":"\nbase.strided.unary( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  fcn:Function )\n    Applies a unary callback to elements in a strided input array and assigns\n    results to elements in a strided output array.\n","base.strided.unary.ndarray":"\nbase.strided.unary.ndarray( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  offsets:ArrayLikeObject<integer>, fcn:Function )\n    Applies a unary callback to elements in a strided input array and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n","base.strided.unaryBy":"\nbase.strided.unaryBy( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  fcn:Function, clbk:Function[, thisArg:any] )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array.\n","base.strided.unaryBy.ndarray":"\nbase.strided.unaryBy.ndarray( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  offsets:ArrayLikeObject<integer>, fcn:Function, clbk:Function[, thisArg:any] )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array using alternative indexing semantics.\n","base.strided.unaryDtypeSignatures":"\nbase.strided.unaryDtypeSignatures( dtypes1:ArrayLike<any>, \n  dtypes2:ArrayLike<any>[, options:Object] )\n    Generates a list of unary interface signatures from strided array data\n    types.\n","base.strided.unarySignatureCallbacks":"\nbase.strided.unarySignatureCallbacks( table:Object, signatures:ArrayLike<any> )\n    Assigns callbacks to unary interfaces according to type promotion rules.\n","base.strided.variance":"\nbase.strided.variance( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array.\n","base.strided.variance.ndarray":"\nbase.strided.variance.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array using alternative indexing\n    semantics.\n","base.strided.variancech":"\nbase.strided.variancech( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array using a one-pass trial mean\n    algorithm.\n","base.strided.variancech.ndarray":"\nbase.strided.variancech.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array using a one-pass trial mean\n    algorithm and alternative indexing semantics.\n","base.strided.variancepn":"\nbase.strided.variancepn( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array using a two-pass algorithm.\n","base.strided.variancepn.ndarray":"\nbase.strided.variancepn.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array using a two-pass algorithm and\n    alternative indexing semantics.\n","base.strided.variancetk":"\nbase.strided.variancetk( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array using a one-pass textbook\n    algorithm.\n","base.strided.variancetk.ndarray":"\nbase.strided.variancetk.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array using a one-pass textbook algorithm\n    and alternative indexing semantics.\n","base.strided.variancewd":"\nbase.strided.variancewd( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array using Welford's algorithm.\n","base.strided.variancewd.ndarray":"\nbase.strided.variancewd.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array using Welford's algorithm and\n    alternative indexing semantics.\n","base.strided.varianceyc":"\nbase.strided.varianceyc( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array using a one-pass algorithm proposed\n    by Youngs and Cramer.\n","base.strided.varianceyc.ndarray":"\nbase.strided.varianceyc.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array using a one-pass algorithm proposed\n    by Youngs and Cramer and alternative indexing semantics.\n","base.strided.zmap":"\nbase.strided.zmap( N:integer, x:Complex128Array, strideX:integer, \n  y:Complex128Array, strideY:integer, fcn:Function )\n    Applies a unary function to a double-precision complex floating-point\n    strided input array and assigns results to a double-precision complex\n    floating-point strided output array.\n","base.strided.zmap.ndarray":"\nbase.strided.zmap.ndarray( N:integer, x:Complex128Array, strideX:integer, \n  offsetX:integer, y:Complex128Array, strideY:integer, offsetY:integer, \n  fcn:Function )\n    Applies a unary function to a double-precision complex floating-point\n    strided input array and assigns results to a double-precision complex\n    floating-point strided output array using alternative indexing semantics.\n","base.str2multislice":"\nbase.str2multislice( str:string )\n    Parses a string-serialized MultiSlice object.\n","base.str2slice":"\nbase.str2slice( str:string )\n    Parses a string-serialized Slice object.\n","base.sub":"\nbase.sub( x:number, y:number )\n    Subtracts two double-precision floating-point numbers `x` and `y`.\n","base.subf":"\nbase.subf( x:number, y:number )\n    Subtracts two single-precision floating-point numbers `x` and `y`.\n","base.sumSeries":"\nbase.sumSeries( generator:Function[, options:Object] )\n    Sum the elements of the series given by the supplied function.\n","base.tan":"\nbase.tan( x:number )\n    Computes the tangent of a number.\n","base.tand":"\nbase.tand( x:number )\n    Computes the tangent of an angle measured in degrees.\n","base.tanh":"\nbase.tanh( x:number )\n    Computes the hyperbolic tangent of a double-precision floating-point number.\n","base.toBinaryString":"\nbase.toBinaryString( x:number )\n    Returns a string giving the literal bit representation of a double-precision\n    floating-point number.\n","base.toBinaryStringf":"\nbase.toBinaryStringf( x:float )\n    Returns a string giving the literal bit representation of a single-precision\n    floating-point number.\n","base.toBinaryStringUint8":"\nbase.toBinaryStringUint8( x:integer )\n    Returns a string giving the literal bit representation of an unsigned 8-bit\n    integer.\n","base.toBinaryStringUint16":"\nbase.toBinaryStringUint16( x:integer )\n    Returns a string giving the literal bit representation of an unsigned 16-bit\n    integer.\n","base.toBinaryStringUint32":"\nbase.toBinaryStringUint32( x:integer )\n    Returns a string giving the literal bit representation of an unsigned 32-bit\n    integer.\n","base.toWordf":"\nbase.toWordf( x:float )\n    Returns an unsigned 32-bit integer corresponding to the IEEE 754 binary\n    representation of a single-precision floating-point number.\n","base.toWords":"\nbase.toWords( x:number )\n    Splits a double-precision floating-point number into a higher order word\n    (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n","base.toWords.assign":"\nbase.toWords.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n  offset:integer )\n    Splits a double-precision floating-point number into a higher order word\n    (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer)\n    and assigns results to a provided output array.\n","base.transpose":"\nbase.transpose( x:ndarray )\n    Transposes a matrix (or a stack of matrices).\n","base.tribonacci":"\nbase.tribonacci( n:integer )\n    Computes the nth Tribonacci number.\n","base.trigamma":"\nbase.trigamma( x:number )\n    Evaluates the trigamma function.\n","base.trim":"\nbase.trim( str:string )\n    Trims whitespace from the beginning and end of a `string`.\n","base.trunc":"\nbase.trunc( x:number )\n    Rounds a double-precision floating-point number toward zero.\n","base.trunc2":"\nbase.trunc2( x:number )\n    Rounds a numeric value to the nearest power of two toward zero.\n","base.trunc10":"\nbase.trunc10( x:number )\n    Rounds a numeric value to the nearest power of ten toward zero.\n","base.truncateMiddle":"\nbase.truncateMiddle( str:string, len:integer, seq:string )\n    Truncates the middle UTF-16 code units of a string to return a string\n    having a specified length.\n","base.truncb":"\nbase.truncb( x:number, n:integer, b:integer )\n    Rounds a numeric value to the nearest multiple of `b^n` toward zero.\n","base.truncf":"\nbase.truncf( x:number )\n    Rounds a single-precision floating-point number toward zero.\n","base.truncn":"\nbase.truncn( x:number, n:integer )\n    Rounds a numeric value to the nearest multiple of `10^n` toward zero.\n","base.truncsd":"\nbase.truncsd( x:number, n:integer, b:integer )\n    Rounds a numeric value to the nearest number toward zero with `n`\n    significant figures.\n","base.uint32ToInt32":"\nbase.uint32ToInt32( x:integer )\n    Converts an unsigned 32-bit integer to a signed 32-bit integer.\n","base.umul":"\nbase.umul( a:integer, b:integer )\n    Performs C-like multiplication of two unsigned 32-bit integers.\n","base.umuldw":"\nbase.umuldw( a:integer, b:integer )\n    Multiplies two unsigned 32-bit integers and returns an array of two unsigned\n    32-bit integers which represents the unsigned 64-bit integer product.\n","base.umuldw.assign":"\nbase.umuldw.assign( a:integer, b:integer, out:Array|TypedArray|Object, \n  stride:integer, offset:integer )\n    Multiplies two unsigned 32-bit integers and assigns results representing\n    the unsigned 64-bit integer product to a provided output array.\n","base.uncapitalize":"\nbase.uncapitalize( str:string )\n    Lowercases the first character of a string.\n","base.uppercase":"\nbase.uppercase( str:string )\n    Converts a string to uppercase.\n","base.vercos":"\nbase.vercos( x:number )\n    Computes the versed cosine.\n","base.versin":"\nbase.versin( x:number )\n    Computes the versed sine.\n","base.wrap":"\nbase.wrap( v:number, min:number, max:number )\n    Wraps a value on the half-open interval `[min,max)`.\n","base.xlog1py":"\nbase.xlog1py( x:number, y:number )\n    Computes `x * ln(y+1)` so that the result is `0` if `x = 0`.\n","base.xlogy":"\nbase.xlogy( x:number, y:number )\n    Computes `x * ln(y)` so that the result is `0` if `x = 0`.\n","base.zeta":"\nbase.zeta( s:number )\n    Evaluates the Riemann zeta function as a function of a real variable `s`.\n","BERNDT_CPS_WAGES_1985":"\nBERNDT_CPS_WAGES_1985()\n    Returns a random sample of 534 workers from the Current Population Survey\n    (CPS) from 1985, including their wages and and other characteristics.\n","bifurcate":"\nbifurcate( collection:Array|TypedArray|Object, [options:Object,] \n  filter:Array|TypedArray|Object )\n    Splits values into two groups.\n","bifurcateBy":"\nbifurcateBy( collection:Array|TypedArray|Object, [options:Object,] \n  predicate:Function )\n    Splits values into two groups according to a predicate function.\n","bifurcateByAsync":"\nbifurcateByAsync( collection:Array|TypedArray|Object, [options:Object,] \n  predicate:Function, done:Function )\n    Splits values into two groups according to a predicate function.\n","bifurcateByAsync.factory":"\nbifurcateByAsync.factory( [options:Object,] predicate:Function )\n    Returns a function which splits values into two groups according to an\n    predicate function.\n","bifurcateIn":"\nbifurcateIn( obj:Object|Array|TypedArray, [options:Object,] predicate:Function )\n    Splits values into two groups according to a predicate function.\n","bifurcateOwn":"\nbifurcateOwn( obj:Object|Array|TypedArray, [options:Object,] \n  predicate:Function )\n    Splits values into two groups according to a predicate function.\n","BigInt":"\nBigInt( value:integer|string )\n    Returns a BigInt.\n","binomialTest":"\nbinomialTest( x:(number|Array[, n:Array<number>][, options:Object] )\n    Computes an exact test for the success probability in a Bernoulli\n    experiment.\n","Boolean":"\nBoolean( value:any )\n    Returns a boolean.\n","Boolean.prototype.toString":"\nBoolean.prototype.toString()\n    Returns a string representing the `Boolean` object.\n","Boolean.prototype.valueOf":"\nBoolean.prototype.valueOf()\n    Returns the primitive value of a `Boolean` object.\n","BooleanArray":"\nBooleanArray()\n    A Boolean array.\n\nBooleanArray( length:integer )\n    Creates a boolean array having a specified length.\n\nBooleanArray( booleanarray:BooleanArray )\n    Creates a boolean array from another boolean array.\n\nBooleanArray( typedarray:TypedArray )\n    Creates a boolean array from a typed array.\n\nBooleanArray( obj:Object )\n    Creates a boolean array from an array-like object or iterable.\n\nBooleanArray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a boolean array view of an ArrayBuffer.\n","BooleanArray.from":"\nBooleanArray.from( src:ArrayLike|Iterable[, clbk:Function[, thisArg:Any]] )\n    Creates a new boolean array from an array-like object or an iterable.\n","BooleanArray.of":"\nBooleanArray.of( element0:bool[, element1:bool[, ...elementN:bool]] )\n    Creates a new boolean array from a variable number of arguments.\n","BooleanArray.BYTES_PER_ELEMENT":"\nBooleanArray.BYTES_PER_ELEMENT\n    The size of each array element in bytes.\n","BooleanArray.name":"\nBooleanArray.name\n    Typed array constructor name.\n","BooleanArray.prototype.buffer":"\nBooleanArray.prototype.buffer\n    Pointer to the underlying data buffer.\n","BooleanArray.prototype.byteLength":"\nBooleanArray.prototype.byteLength\n    Size of the array in bytes.\n","BooleanArray.prototype.byteOffset":"\nBooleanArray.prototype.byteOffset\n    Offset (in bytes) of the array from the start of its underlying\n    ArrayBuffer.\n","BooleanArray.prototype.BYTES_PER_ELEMENT":"\nBooleanArray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element.\n","BooleanArray.prototype.length":"\nBooleanArray.prototype.length\n    The number of array elements.\n","BooleanArray.prototype.at":"\nBooleanArray.prototype.at( i:integer )\n    Returns an array element located at integer position (index) `i`, with\n    support for noth nonnegative and negative integer positions.\n","BooleanArray.prototype.copyWithin":"\nBooleanArray.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","BooleanArray.prototype.entries":"\nBooleanArray.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","BooleanArray.prototype.every":"\nBooleanArray.prototype.every( predicate:Function[, thisArg:Any] )\n    Returns a boolean indicating whether all elements in the array pass a test.\n","BooleanArray.prototype.fill":"\nBooleanArray.prototype.fill( value:boolean[, start:integer[, end:integer]] )\n    Returns a modified typed array filled with a fill value.\n","BooleanArray.prototype.filter":"\nBooleanArray.prototype.filter( predicate:Function[, thisArg:Any] )\n    Returns a new array containing the elements of an array which pass a test\n    implemented by a predicate function.\n","BooleanArray.prototype.find":"\nBooleanArray.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first element in an array for which a predicate function returns\n    a truthy value.\n","BooleanArray.prototype.findIndex":"\nBooleanArray.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first element in an array for which a predicate\n    function returns a truthy value.\n","BooleanArray.prototype.findLast":"\nBooleanArray.prototype.findLast( predicate:Function[, thisArg:Any] )\n    Returns the last element in an array for which a predicate function returns\n    a truthy value.\n","BooleanArray.prototype.findLastIndex":"\nBooleanArray.prototype.findLastIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the last element in an array for which a predicate\n    function returns a truthy value.\n","BooleanArray.prototype.forEach":"\nBooleanArray.prototype.forEach( clbk:Function[, thisArg:Any] )\n    Invokes a function once for each array element.\n","BooleanArray.prototype.get":"\nBooleanArray.prototype.get( i:integer )\n    Returns an array element located at integer position (index) `i`.\n","BooleanArray.prototype.includes":"\nBooleanArray.prototype.includes( searchElement:boolean[, fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a provided value.\n","BooleanArray.prototype.indexOf":"\nBooleanArray.prototype.indexOf( searchElement:boolean[, fromIndex:integer] )\n    Returns the first index at which a given element can be found.\n","BooleanArray.prototype.join":"\nBooleanArray.prototype.join( [separator:string] )\n    Returns a new string by concatenating all array elements separated by a\n    separator string.\n","BooleanArray.prototype.keys":"\nBooleanArray.prototype.keys()\n    Returns an iterator for iterating over each index key in a typed array.\n","BooleanArray.prototype.lastIndexOf":"\nBooleanArray.prototype.lastIndexOf( searchElement:boolean[, fromIndex:integer] )\n    Returns the last index at which a given element can be found.\n","BooleanArray.prototype.map":"\nBooleanArray.prototype.map( clbk:Function[, thisArg:Any] )\n    Returns a new array with each element being the result of a provided\n    callback function.\n","BooleanArray.prototype.reduce":"\nBooleanArray.prototype.reduce( reducerFn:Function[, initialValue:any] )\n    Applies a provided function to each element of the array, in order, passing\n    in the return value from the calculation on the preceding element and\n    returning the accumulated result upon completion.\n","BooleanArray.prototype.reduceRight":"\nBooleanArray.prototype.reduceRight( reducerFn:Function[, initialValue:any] )\n    Applies a provided function to each element of the array, in reverse order,\n    passing in the return value from the calculation on the preceding element\n    and returning the accumulated result upon completion.\n","BooleanArray.prototype.reverse":"\nBooleanArray.prototype.reverse()\n    Reverses the array *in-place*.\n","BooleanArray.prototype.set":"\nBooleanArray.prototype.set( v:bool|BooleanArray|ArrayLikeObject[, i:integer] )\n    Sets one or more array elements.\n","BooleanArray.prototype.slice":"\nBooleanArray.prototype.slice( [start:integer[, end:integer]] )\n    Copies a portion of a typed array to a new typed array.\n","BooleanArray.prototype.some":"\nBooleanArray.prototype.some( predicate:Function[, thisArg:Any] )\n    Returns a boolean indicating whether at least one element passes a test.\n","BooleanArray.prototype.sort":"\nBooleanArray.prototype.sort( [compareFunction:Function] )\n    Sorts an array in-place.\n","BooleanArray.prototype.subarray":"\nBooleanArray.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array view over the same underlying `ArrayBuffer` and\n    with the same underlying data type as the host array.\n","BooleanArray.prototype.toLocaleString":"\nBooleanArray.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n","BooleanArray.prototype.toReversed":"\nBooleanArray.prototype.toReversed()\n    Returns a new typed array containing the elements in reversed order.\n","BooleanArray.prototype.toSorted":"\nBooleanArray.prototype.toSorted( [compareFunction:Function] )\n    Returns a new typed array containing the elements in sorted order.\n","BooleanArray.prototype.toString":"\nBooleanArray.prototype.toString()\n    Serializes an array as a string.\n","BooleanArray.prototype.values":"\nBooleanArray.prototype.values()\n    Returns an iterator for iterating over each value in a typed array.\n","BooleanArray.prototype.with":"\nBooleanArray.prototype.with( index, value )\n    Returns a new typed array with the element at a provided index replaced\n    with a provided value.\n","broadcastArray":"\nbroadcastArray( x:ndarray, shape:ArrayLikeObject )\n    Broadcasts an ndarray to a specified shape.\n","broadcastArrays":"\nbroadcastArrays( ...arrays:ndarray|ArrayLikeObject<ndarray> )\n    Broadcasts ndarrays to a common shape.\n","Buffer":"\nBuffer\n\nBuffer( size:integer )\n    Allocates a buffer having a specified number of bytes.\n\nBuffer( buffer:Buffer )\n    Copies buffer data to a new Buffer instance.\n\nBuffer( array:Array )\n    Allocates a buffer using an array of octets.\n\nBuffer( str:string[, encoding:string] )\n    Allocates a buffer containing a provided string.\n","buffer2json":"\nbuffer2json( buffer:Buffer )\n    Returns a JSON representation of a buffer.\n","BYTE_ORDER":"\nBYTE_ORDER\n    Platform byte order.\n","camelcase":"\ncamelcase( str:string )\n    Converts a string to camel case.\n","capitalize":"\ncapitalize( str:string )\n    Capitalizes the first character in a string.\n","capitalizeKeys":"\ncapitalizeKeys( obj:Object )\n    Converts the first letter of each object key to uppercase.\n","CATALAN":"\nCATALAN\n    Catalan's constant.\n","CBRT_EPS":"\nCBRT_EPS\n    Cube root of double-precision floating-point epsilon.\n","CDC_NCHS_US_BIRTHS_1969_1988":"\nCDC_NCHS_US_BIRTHS_1969_1988()\n    Returns US birth data from 1969 to 1988, as provided by the Center for\n    Disease Control and Prevention's National Center for Health Statistics.\n","CDC_NCHS_US_BIRTHS_1994_2003":"\nCDC_NCHS_US_BIRTHS_1994_2003()\n    Returns US birth data from 1994 to 2003, as provided by the Center for\n    Disease Control and Prevention's National Center for Health Statistics.\n","CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013":"\nCDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n    Returns US infant mortality data, by race, from 1915 to 2013, as provided by\n    the Center for Disease Control and Prevention's National Center for Health\n    Statistics.\n","chdir":"\nchdir( path:string )\n    Changes the current working directory.\n","chi2gof":"\nchi2gof( x:ndarray|Array|TypedArray, y:ndarray|Array|TypedArray|string[, \n  ...args:number][, options:Object] )\n    Performs a chi-square goodness-of-fit test.\n","chi2test":"\nchi2test( x:ndarray|Array[, options:Object] )\n    Performs a chi-square independence test.\n","circarray2iterator":"\ncircarray2iterator( src:ArrayLikeObject[, options:Object][, mapFcn:Function[, \n  thisArg:any]] )\n    Returns an iterator which repeatedly iterates over the elements of an array-\n    like object.\n","circularArrayStream":"\ncircularArrayStream( src:ArrayLikeObject[, options:Object] )\n    Creates a readable stream from an array-like object which repeatedly\n    iterates over the provided value's elements.\n","circularArrayStream.factory":"\ncircularArrayStream.factory( [options:Object] )\n    Returns a function for creating readable streams from array-like objects\n    which repeatedly iterate over the elements of provided values.\n","circularArrayStream.objectMode":"\ncircularArrayStream.objectMode( src:ArrayLikeObject[, options:Object] )\n    Returns an \"objectMode\" readable stream from an array-like object which\n    repeatedly iterates over a provided value's elements.\n","CircularBuffer":"\nCircularBuffer( buffer:integer|ArrayLike )\n    Circular buffer constructor.\n","CircularBuffer.prototype.clear":"\nCircularBuffer.prototype.clear()\n    Clears a buffer.\n","CircularBuffer.prototype.count":"\nCircularBuffer.prototype.count\n    Read-only property returning the number of elements currently in the buffer.\n","CircularBuffer.prototype.full":"\nCircularBuffer.prototype.full\n    Read-only property returning a boolean indicating whether a circular buffer\n    is full.\n","CircularBuffer.prototype.iterator":"\nCircularBuffer.prototype.iterator( [niters:integer] )\n    Returns an iterator for iterating over a circular buffer.\n","CircularBuffer.prototype.length":"\nCircularBuffer.prototype.length\n    Read-only property returning the buffer length (i.e., capacity).\n","CircularBuffer.prototype.push":"\nCircularBuffer.prototype.push( value:any )\n    Adds a value to a circular buffer.\n","CircularBuffer.prototype.toArray":"\nCircularBuffer.prototype.toArray()\n    Returns an array of circular buffer values.\n","CircularBuffer.prototype.toJSON":"\nCircularBuffer.prototype.toJSON()\n    Serializes a circular buffer as JSON.\n","close":"\nclose( fd:integer, clbk:Function )\n    Asynchronously closes a file descriptor, so that the file descriptor no\n    longer refers to any file and may be reused.\n","close.sync":"\nclose.sync( fd:integer )\n    Synchronously closes a file descriptor.\n","CMUDICT":"\nCMUDICT( [options:Object] )\n    Returns datasets from the Carnegie Mellon Pronouncing Dictionary (CMUdict).\n","codePointAt":"\ncodePointAt( str:string, idx:integer[, backward:boolean] )\n    Returns a Unicode code point from a string at a specified position.\n","commonKeys":"\ncommonKeys( obj1:any, obj2:any[, ...obj:any] )\n    Returns the common own property names of two or more objects.\n","commonKeysIn":"\ncommonKeysIn( obj1:any, obj2:any[, ...obj:any] )\n    Returns the common own and inherited property names of two or more objects.\n","complex":"\ncomplex( real:number, imag:number[, dtype:string] )\n    Creates a complex number.\n","Complex64":"\nComplex64( real:number, imag:number )\n    64-bit complex number constructor.\n","Complex64.BYTES_PER_ELEMENT":"\nComplex64.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n","Complex64.prototype.BYTES_PER_ELEMENT":"\nComplex64.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n","Complex64.prototype.byteLength":"\nComplex64.prototype.byteLength\n    Length (in bytes) of a complex number.\n","COMPLEX64_NAN":"\nCOMPLEX64_NAN\n    Canonical single-precision complex floating-point NaN.\n","COMPLEX64_NUM_BYTES":"\nCOMPLEX64_NUM_BYTES\n    Size (in bytes) of a 64-bit complex number.\n","COMPLEX64_ZERO":"\nCOMPLEX64_ZERO\n    Single-precision complex floating-point zero.\n","Complex64Array":"\nComplex64Array()\n    A 64-bit complex number array.\n\nComplex64Array( length:integer )\n    Creates a 64-bit complex number array having a specified length.\n\nComplex64Array( complexarray:Complex64Array )\n    Creates a 64-bit complex number array from another complex number array.\n\nComplex64Array( typedarray:TypedArray )\n    Creates a 64-bit complex number array from a typed array\n    containing interleaved real and imaginary components.\n\nComplex64Array( obj:Object )\n    Creates a 64-bit complex number array from an array-like object or iterable.\n\nComplex64Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a 64-bit complex number array view of an ArrayBuffer.\n","Complex64Array.from":"\nComplex64Array.from( src:ArrayLike|Iterable[, clbk:Function[, thisArg:Any]] )\n    Creates a new 64-bit complex number array from an array-like object or an\n    iterable.\n","Complex64Array.of":"\nComplex64Array.of( element0:number[, element1:number[, ...elementN:number]] )\n    Creates a new 64-bit complex number array from a variable number of\n    arguments.\n","Complex64Array.BYTES_PER_ELEMENT":"\nComplex64Array.BYTES_PER_ELEMENT\n    The size of each array element in bytes.\n","Complex64Array.name":"\nComplex64Array.name\n    Typed array constructor name.\n","Complex64Array.prototype.buffer":"\nComplex64Array.prototype.buffer\n    Pointer to the underlying data buffer.\n","Complex64Array.prototype.byteLength":"\nComplex64Array.prototype.byteLength\n    Length of the array in bytes.\n","Complex64Array.prototype.byteOffset":"\nComplex64Array.prototype.byteOffset\n    Offset (in bytes) of the array from the start of its underlying\n    ArrayBuffer.\n","Complex64Array.prototype.BYTES_PER_ELEMENT":"\nComplex64Array.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element.\n","Complex64Array.prototype.length":"\nComplex64Array.prototype.length\n    The number of array elements.\n","Complex64Array.prototype.at":"\nComplex64Array.prototype.at( i:integer )\n    Returns an array element located at integer position (index) `i`, with\n    support for noth nonnegative and negative integer positions.\n","Complex64Array.prototype.copyWithin":"\nComplex64Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","Complex64Array.prototype.entries":"\nComplex64Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","Complex64Array.prototype.every":"\nComplex64Array.prototype.every( predicate:Function[, thisArg:Any] )\n    Returns a boolean indicating whether all elements in the array pass a test.\n","Complex64Array.prototype.fill":"\nComplex64Array.prototype.fill( value:Complex64[, start:integer[, end:integer]] )\n    Returns a modified typed array filled with a fill value.\n","Complex64Array.prototype.filter":"\nComplex64Array.prototype.filter( predicate:Function[, thisArg:Any] )\n    Returns a new array containing the elements of an array which pass a test\n    implemented by a predicate function.\n","Complex64Array.prototype.find":"\nComplex64Array.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first element in an array for which a predicate function\n    returns a truthy value.\n","Complex64Array.prototype.findIndex":"\nComplex64Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first element in an array for which a predicate\n    function returns a truthy value.\n","Complex64Array.prototype.findLast":"\nComplex64Array.prototype.findLast( predicate:Function[, thisArg:Any] )\n    Returns the last element in an array for which a predicate function returns\n    a truthy value.\n","Complex64Array.prototype.findLastIndex":"\nComplex64Array.prototype.findLastIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the last element in an array for which a predicate\n    function returns a truthy value.\n","Complex64Array.prototype.forEach":"\nComplex64Array.prototype.forEach( clbk:Function[, thisArg:Any] )\n    Invokes a function once for each array element.\n","Complex64Array.prototype.get":"\nComplex64Array.prototype.get( i:integer )\n    Returns an array element located at integer position (index) `i`.\n","Complex64Array.prototype.includes":"\nComplex64Array.prototype.includes( searchElement:Complex64[, \n  fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a provided value.\n","Complex64Array.prototype.indexOf":"\nComplex64Array.prototype.indexOf( searchElement:Complex64[, fromIndex:integer] )\n    Returns the first index at which a given element can be found.\n","Complex64Array.prototype.join":"\nComplex64Array.prototype.join( [separator:string] )\n    Returns a new string by concatenating all array elements separated by a\n    separator string.\n","Complex64Array.prototype.keys":"\nComplex64Array.prototype.keys()\n    Returns an iterator for iterating over each index key in a typed array.\n","Complex64Array.prototype.lastIndexOf":"\nComplex64Array.prototype.lastIndexOf( searchElement:Complex64[, \n  fromIndex:integer] )\n    Returns the last index at which a given element can be found.\n","Complex64Array.prototype.map":"\nComplex64Array.prototype.map( clbk:Function[, thisArg:Any] )\n    Returns a new array with each element being the result of a provided\n    callback function.\n","Complex64Array.prototype.reduce":"\nComplex64Array.prototype.reduce( reducerFn:Function[, initialValue:any] )\n    Applies a provided function to each element of the array, in order, passing\n    in the return value from the calculation on the preceding element and\n    returning the accumulated result upon completion.\n","Complex64Array.prototype.reduceRight":"\nComplex64Array.prototype.reduceRight( reducerFn:Function[, initialValue:any] )\n    Applies a provided function to each element of the array, in reverse order,\n    passing in the return value from the calculation on the preceding element\n    and returning the accumulated result upon completion.\n","Complex64Array.prototype.reverse":"\nComplex64Array.prototype.reverse()\n    Reverses the array *in-place*.\n","Complex64Array.prototype.set":"\nComplex64Array.prototype.set( z:Complex64|Complex64Array|ArrayLikeObject[, \n  i:integer] )\n    Sets one or more array elements.\n","Complex64Array.prototype.slice":"\nComplex64Array.prototype.slice( [start:integer[, end:integer]] )\n    Copies a portion of a typed array to a new typed array.\n","Complex64Array.prototype.some":"\nComplex64Array.prototype.some( predicate[, thisArg] )\n    Returns a boolean indicating whether at least one element passes a test.\n","Complex64Array.prototype.sort":"\nComplex64Array.prototype.sort( compareFunction:Function )\n    Sorts an array in-place.\n","Complex64Array.prototype.subarray":"\nComplex64Array.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array view over the same underlying `ArrayBuffer` and\n    with the same underlying data type as the host array.\n","Complex64Array.prototype.toLocaleString":"\nComplex64Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n","Complex64Array.prototype.toReversed":"\nComplex64Array.prototype.toReversed()\n    Returns a new typed array containing the elements in reversed order.\n","Complex64Array.prototype.toSorted":"\nComplex64Array.prototype.toSorted( compareFcn:Function )\n    Returns a new typed array containing the elements in sorted order.\n","Complex64Array.prototype.toString":"\nComplex64Array.prototype.toString()\n    Serializes an array as a string.\n","Complex64Array.prototype.values":"\nComplex64Array.prototype.values()\n    Returns an iterator for iterating over each value in a typed array.\n","Complex64Array.prototype.with":"\nComplex64Array.prototype.with( index, value )\n    Returns a new typed array with the element at a provided index replaced\n    with a provided value.\n","Complex128":"\nComplex128( real:number, imag:number )\n    128-bit complex number constructor.\n","Complex128.BYTES_PER_ELEMENT":"\nComplex128.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n","Complex128.prototype.BYTES_PER_ELEMENT":"\nComplex128.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n","Complex128.prototype.byteLength":"\nComplex128.prototype.byteLength\n    Length (in bytes) of a complex number.\n","COMPLEX128_NAN":"\nCOMPLEX128_NAN\n    Canonical double-precision complex floating-point NaN.\n","COMPLEX128_NUM_BYTES":"\nCOMPLEX128_NUM_BYTES\n    Size (in bytes) of a 128-bit complex number.\n","COMPLEX128_ZERO":"\nCOMPLEX128_ZERO\n    Double-precision complex floating-point zero.\n","Complex128Array":"\nComplex128Array()\n    A 128-bit complex number array.\n\nComplex128Array( length:integer )\n    Creates a 128-bit complex number array having a specified length.\n\nComplex128Array( complexarray:Complex128Array )\n    Creates a 64-bit complex number array from another complex number array.\n\nComplex128Array( typedarray:TypedArray )\n    Creates a 128-bit complex number array from a typed array\n    containing interleaved real and imaginary components.\n\nComplex128Array( obj:Object )\n    Creates a 128-bit complex number array from an array-like object or \n    iterable.\n\nComplex128Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a 128-bit complex number array view of an ArrayBuffer.\n","Complex128Array.from":"\nComplex128Array.from( src:ArrayLike|Iterable[, clbk:Function[, thisArg:Any]] )\n    Creates a new 128-bit complex number array from an array-like object or an\n    iterable.\n","Complex128Array.of":"\nComplex128Array.of( element0:number|ComplexLike[, \n  element1:number |ComplexLike[, ...elementN:number|ComplexLike]] )\n    Creates a new 128-bit complex number array from a variable number of\n    arguments.\n","Complex128Array.BYTES_PER_ELEMENT":"\nComplex128Array.BYTES_PER_ELEMENT\n    The size of each array element in bytes.\n","Complex128Array.name":"\nComplex128Array.name\n    Typed array constructor name.\n","Complex128Array.prototype.buffer":"\nComplex128Array.prototype.buffer\n    Pointer to the underlying data buffer.\n","Complex128Array.prototype.byteLength":"\nComplex128Array.prototype.byteLength\n    Length of the array in bytes.\n","Complex128Array.prototype.byteOffset":"\nComplex128Array.prototype.byteOffset\n    Offset (in bytes) of the array from the start of its underlying\n    ArrayBuffer.\n","Complex128Array.prototype.BYTES_PER_ELEMENT":"\nComplex128Array.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element.\n","Complex128Array.prototype.length":"\nComplex128Array.prototype.length\n    The number of array elements.\n","Complex128Array.prototype.at":"\nComplex128Array.prototype.at( i:integer )\n    Returns an array element located at integer position (index) `i`, with\n    support for both nonnegative and negative integer positions.\n","Complex128Array.prototype.copyWithin":"\nComplex128Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","Complex128Array.prototype.entries":"\nComplex128Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","Complex128Array.prototype.every":"\nComplex128Array.prototype.every( predicate:Function[, thisArg:Any] )\n    Returns a boolean indicating whether all elements in the array pass a test.\n","Complex128Array.prototype.fill":"\nComplex128Array.prototype.fill( value:Complex128[, start:integer[, \n  end:integer]] )\n    Returns a modified typed array filled with a fill value.\n","Complex128Array.prototype.filter":"\nComplex128Array.prototype.filter( predicate:Function[, thisArg:Any] )\n    Returns a new array containing the elements of an array which pass a test\n    implemented by a predicate function.\n","Complex128Array.prototype.find":"\nComplex128Array.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first element in an array for which a predicate function\n    returns a truthy value.\n","Complex128Array.prototype.findIndex":"\nComplex128Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first element in an array for which a predicate\n    function returns a truthy value.\n","Complex128Array.prototype.findLast":"\nComplex128Array.prototype.findLast( predicate:Function[, thisArg:Any] )\n    Returns the last element in an array for which a predicate function returns\n    a truthy value.\n","Complex128Array.prototype.findLastIndex":"\nComplex128Array.prototype.findLastIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the last element in an array for which a predicate\n    function returns a truthy value.\n","Complex128Array.prototype.forEach":"\nComplex128Array.prototype.forEach( clbk:Function[, thisArg:Any] )\n    Invokes a function once for each array element.\n","Complex128Array.prototype.get":"\nComplex128Array.prototype.get( i:integer )\n    Returns an array element located at integer position (index) `i`.\n","Complex128Array.prototype.includes":"\nComplex128Array.prototype.includes( searchElement:Complex128[, \n  fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a provided value.\n","Complex128Array.prototype.indexOf":"\nComplex128Array.prototype.indexOf( searchElement:Complex128[, \n  fromIndex:integer] )\n    Returns the first index at which a given element can be found.\n","Complex128Array.prototype.join":"\nComplex128Array.prototype.join( [separator:string] )\n    Returns a new string by concatenating all array elements separated by a\n    separator string.\n","Complex128Array.prototype.keys":"\nComplex128Array.prototype.keys()\n    Returns an iterator for iterating over each index key in a typed array.\n","Complex128Array.prototype.lastIndexOf":"\nComplex128Array.prototype.lastIndexOf( searchElement:Complex128[, \n  fromIndex:integer] )\n    Returns the last index at which a given element can be found.\n","Complex128Array.prototype.map":"\nComplex128Array.prototype.map( clbk:Function[, thisArg:Any] )\n    Returns a new array with each element being the result of a provided\n    callback function.\n","Complex128Array.prototype.reduce":"\nComplex128Array.prototype.reduce( reducerFn:Function[, initialValue:any] )\n    Applies a provided function to each element of the array, in order, passing\n    in the return value from the calculation on the preceding element and\n    returning the accumulated result upon completion.\n","Complex128Array.prototype.reduceRight":"\nComplex128Array.prototype.reduceRight( reducerFn:Function[, initialValue:any] )\n    Applies a provided function to each element of the array, in reverse order,\n    passing in the return value from the calculation on the preceding element\n    and returning the accumulated result upon completion.\n","Complex128Array.prototype.reverse":"\nComplex128Array.prototype.reverse()\n    Reverses the array *in-place*.\n","Complex128Array.prototype.set":"\nComplex128Array.prototype.set( z:Complex128|Complex128Array|ArrayLikeObject[, \n  i:integer] )\n    Sets one or more array elements.\n","Complex128Array.prototype.slice":"\nComplex128Array.prototype.slice( [start:integer[, end:integer]] )\n    Copies a portion of a typed array to a new typed array.\n","Complex128Array.prototype.some":"\nComplex128Array.prototype.some( predicate[, thisArg] )\n    Returns a boolean indicating whether at least one element passes a test.\n","Complex128Array.prototype.sort":"\nComplex128Array.prototype.sort( compareFunction:Function )\n    Sorts an array in-place.\n","Complex128Array.prototype.subarray":"\nComplex128Array.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array view over the same underlying `ArrayBuffer` and\n    with the same underlying data type as the host array.\n","Complex128Array.prototype.toLocaleString":"\nComplex128Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n","Complex128Array.prototype.toReversed":"\nComplex128Array.prototype.toReversed()\n    Returns a new typed array containing the elements in reversed order.\n","Complex128Array.prototype.toSorted":"\nComplex128Array.prototype.toSorted( compareFcn:Function )\n    Returns a new typed array containing the elements in sorted order.\n","Complex128Array.prototype.toString":"\nComplex128Array.prototype.toString()\n    Serializes an array as a string.\n","Complex128Array.prototype.values":"\nComplex128Array.prototype.values()\n    Returns an iterator for iterating over each value in a typed array.\n","Complex128Array.prototype.with":"\nComplex128Array.prototype.with( index, value )\n    Returns a new typed array with the element at a provided index replaced\n    with a provided value.\n","complexarray":"\ncomplexarray( [dtype:string] )\n    Creates a complex typed array.\n\ncomplexarray( length:integer[, dtype:string] )\n    Returns a complex number typed array having a specified length.\n\ncomplexarray( complexarray:ComplexArray[, dtype:string] )\n    Creates a complex number typed array from another complex number typed\n    array.\n\ncomplexarray( obj:Object[, dtype:string] )\n    Creates a complex number typed array from an array-like object or iterable.\n\ncomplexarray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n  dtype:string] )\n    Returns a complex number typed array view of an ArrayBuffer.\n","complexarrayCtors":"\ncomplexarrayCtors( dtype:string )\n    Returns a complex typed array constructor.\n","complexarrayDataTypes":"\ncomplexarrayDataTypes()\n    Returns a list of complex typed array data types.\n","complexCtors":"\ncomplexCtors( dtype:string )\n    Returns a complex number constructor.\n","complexDataType":"\ncomplexDataType( value:any )\n    Returns the data type of a complex number object.\n","complexDataTypes":"\ncomplexDataTypes()\n    Returns a list of complex number data types.\n","complexPromotionRules":"\ncomplexPromotionRules( [dtype1:string, dtype2:string] )\n    Returns the complex number data type with the smallest size and closest\n    \"kind\" to which data types can be safely cast.\n","compose":"\ncompose( ...f:Function )\n    Function composition.\n","composeAsync":"\ncomposeAsync( ...f:Function )\n    Function composition.\n","configdir":"\nconfigdir( [p:string] )\n    Returns a directory for user-specific configuration files.\n","conj":"\nconj( z:Complex128 )\n    Returns the complex conjugate of a double-precision complex floating-point\n    number.\n","conjf":"\nconjf( z:Complex64 )\n    Returns the complex conjugate of a single-precision complex floating-point\n    number.\n","constantcase":"\nconstantcase( str:string )\n    Converts a string to constant case.\n","constantFunction":"\nconstantFunction( val:any )\n    Creates a function which always returns the same value.\n","constantStream":"\nconstantStream( value:string|Buffer|Uint8Array|any[, options:Object] )\n    Returns a readable stream which always streams the same value.\n","constantStream.factory":"\nconstantStream.factory( [value:string|Buffer|Uint8Array|any, ][options:Object] )\n    Returns a function for creating readable streams which always stream the\n    same value.\n","constantStream.objectMode":"\nconstantStream.objectMode( value:any[, options:Object] )\n    Returns an \"objectMode\" readable stream which always streams the same value.\n","constructorName":"\nconstructorName( val:any )\n    Determines the name of a value's constructor.\n","contains":"\ncontains( val:ArrayLike, searchValue:any[, position:integer] )\n    Tests if an array-like value contains a search value.\n","convertArray":"\nconvertArray( arr:ArrayLikeObject, dtype:string )\n    Converts an input array to an array of a different data type.\n","convertArraySame":"\nconvertArraySame( x:ArrayLikeObject, y:Array|TypedArray )\n    Converts an input array to the same data type as a second input array.\n","convertPath":"\nconvertPath( from:string, to:string )\n    Converts between POSIX and Windows paths.\n","copy":"\ncopy( value:any[, level:integer] )\n    Copy or deep clone a value to an arbitrary depth.\n","copyBuffer":"\ncopyBuffer( buffer:Buffer )\n    Copies buffer data to a new Buffer instance.\n","countBy":"\ncountBy( collection:Array|TypedArray|Object, [options:Object,] \n  indicator:Function )\n    Groups values according to an indicator function and returns group counts.\n","countByAsync":"\ncountByAsync( collection:Array|TypedArray|Object, [options:Object,] \n  indicator:Function, done:Function )\n    Groups values according to an indicator function and returns group counts.\n","countByAsync.factory":"\ncountByAsync.factory( [options:Object,] indicator:Function )\n    Returns a function which groups values according to an indicator function\n    and returns group counts.\n","currentYear":"\ncurrentYear()\n    Returns the current year.\n","curry":"\ncurry( fcn:Function[, arity:integer][, thisArg:any] )\n    Transforms a function into a sequence of functions each accepting a single\n    argument.\n","curryRight":"\ncurryRight( fcn:Function[, arity:integer][, thisArg:any] )\n    Transforms a function into a sequence of functions each accepting a single\n    argument.\n","cwd":"\ncwd()\n    Returns the current working directory.\n","DALE_CHALL_NEW":"\nDALE_CHALL_NEW()\n    Returns a list of familiar English words.\n","datasets":"\ndatasets( name:string[, options:Object] )\n    Returns a dataset.\n","DataView":"\nDataView( buffer:ArrayBuffer|SharedArrayBuffer[, byteOffset:integer[, \n  byteLength:integer]] )\n    Returns a data view representing a provided array buffer.\n","DataView.prototype.buffer":"\nDataView.prototype.buffer\n    Read-only property which returns the underyling array buffer.\n","DataView.prototype.byteLength":"\nDataView.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the view.\n","DataView.prototype.byteOffset":"\nDataView.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the view to the\n    start of the underlying array buffer.\n","datespace":"\ndatespace( start:number, stop:number[, length:integer][ , options:Object] )\n    Generates an array of linearly spaced dates.\n","dayOfQuarter":"\ndayOfQuarter( [month:string|integer|Date[, day:integer, year:integer]] )\n    Returns the day of the quarter.\n","dayOfYear":"\ndayOfYear( [month:string|integer|Date[, day:integer, year:integer]] )\n    Returns the day of the year.\n","daysInMonth":"\ndaysInMonth( [month:string|integer|Date[, year:integer]] )\n    Returns the number of days in a month.\n","daysInYear":"\ndaysInYear( [value:integer|Date] )\n    Returns the number of days in a year according to the Gregorian calendar.\n","ddot":"\nddot( x:ndarray, y:ndarray[, dim:integer] )\n    Computes the dot product of two double-precision floating-point vectors.\n","debugSinkStream":"\ndebugSinkStream( [options:Object,] [clbk:Function] )\n    Returns a writable stream for debugging stream pipelines.\n","debugSinkStream.factory":"\ndebugSinkStream.factory( [options:Object] )\n    Returns a function for creating writable streams for debugging stream\n    pipelines.\n","debugSinkStream.objectMode":"\ndebugSinkStream.objectMode( [options:Object,] [clbk:Function] )\n    Returns an \"objectMode\" writable stream for debugging stream pipelines.\n","debugStream":"\ndebugStream( [options:Object,] [clbk:Function] )\n    Returns a transform stream for debugging stream pipelines.\n","debugStream.factory":"\ndebugStream.factory( [options:Object] )\n    Returns a function for creating transform streams for debugging stream\n    pipelines.\n","debugStream.objectMode":"\ndebugStream.objectMode( [options:Object,] [clbk:Function] )\n    Returns an \"objectMode\" transform stream for debugging stream pipelines.\n","decorateAfter":"\ndecorateAfter( fcn:Function, arity:integer, after:Function[, thisArg:any] )\n    Decorates a provided function such that the function's return value is\n    provided as an argument to another function.\n","decorateAfter.factory":"\ndecorateAfter.factory( fcn:Function, arity:integer, after:Function[, \n  thisArg:any] )\n    Uses code generation to decorate a provided function such that the\n    function's return value is provided as an argument to another function.\n","deepEqual":"\ndeepEqual( a:any, b:any )\n    Tests for deep equality between two values.\n","deepGet":"\ndeepGet( obj:ObjectLike, path:string|Array[, options:Object] )\n    Returns a nested property value.\n","deepGet.factory":"\ndeepGet.factory( path:string|Array[, options:Object] )\n    Creates a reusable deep get function.\n","deepHasOwnProp":"\ndeepHasOwnProp( value:any, path:string|Array[, options:Object] )\n    Returns a boolean indicating whether an object contains a nested key path.\n","deepHasOwnProp.factory":"\ndeepHasOwnProp.factory( path:string|Array[, options:Object] )\n    Returns a function which tests whether an object contains a nested key path.\n","deepHasProp":"\ndeepHasProp( value:any, path:string|Array[, options:Object] )\n    Returns a boolean indicating whether an object contains a nested key path,\n    either own or inherited.\n","deepHasProp.factory":"\ndeepHasProp.factory( path:string|Array[, options:Object] )\n    Returns a function which tests whether an object contains a nested key path,\n    either own or inherited.\n","deepPluck":"\ndeepPluck( arr:Array, path:string|Array[, options:Object] )\n    Extracts a nested property value from each element of an object array.\n","deepSet":"\ndeepSet( obj:ObjectLike, path:string|Array, value:any[, options:Object] )\n    Sets a nested property value.\n","deepSet.factory":"\ndeepSet.factory( path:string|Array[, options:Object] )\n    Creates a reusable deep set function.\n","defineMemoizedProperty":"\ndefineMemoizedProperty( obj:Object, prop:string|symbol, descriptor:Object )\n    Defines a memoized object property.\n","defineProperties":"\ndefineProperties( obj:Object, properties:Object )\n    Defines (and/or modifies) object properties.\n","defineProperty":"\ndefineProperty( obj:Object, prop:string|symbol, descriptor:Object )\n    Defines (or modifies) an object property.\n","dirname":"\ndirname( path:string )\n    Returns a directory name.\n","dotcase":"\ndotcase( str:string )\n    Converts a string to dot case.\n","DoublyLinkedList":"\nDoublyLinkedList()\n    Doubly linked list constructor.\n","doUntil":"\ndoUntil( fcn:Function, predicate:Function[, thisArg:any] )\n    Invokes a function until a test condition is true.\n","doUntilAsync":"\ndoUntilAsync( fcn:Function, predicate:Function, done:Function[, thisArg:any] )\n    Invokes a function until a test condition is true.\n","doUntilEach":"\ndoUntilEach( collection:Array|TypedArray|Object, fcn:Function, \n  predicate:Function[, thisArg:any] )\n    Until a test condition is true, invokes a function for each element in a\n    collection.\n","doUntilEachRight":"\ndoUntilEachRight( collection:Array|TypedArray|Object, fcn:Function, \n  predicate:Function[, thisArg:any] )\n    Until a test condition is true, invokes a function for each element in a\n    collection, iterating from right to left.\n","doWhile":"\ndoWhile( fcn:Function, predicate:Function[, thisArg:any] )\n    Invokes a function while a test condition is true.\n","doWhileAsync":"\ndoWhileAsync( fcn:Function, predicate:Function, done:Function[, thisArg:any] )\n    Invokes a function while a test condition is true.\n","doWhileEach":"\ndoWhileEach( collection:Array|TypedArray|Object, fcn:Function, \n  predicate:Function[, thisArg:any] )\n    While a test condition is true, invokes a function for each element in a\n    collection.\n","doWhileEachRight":"\ndoWhileEachRight( collection:Array|TypedArray|Object, fcn:Function, \n  predicate:Function[, thisArg:any] )\n    While a test condition is true, invokes a function for each element in a\n    collection, iterating from right to left.\n","dswap":"\ndswap( x:ndarray, y:ndarray[, dim:integer] )\n    Interchanges two double-precision floating-point vectors.\n","E":"\nE\n    Euler's number.\n","EMOJI":"\nEMOJI()\n    Returns an emoji database.\n","EMOJI_CODE_PICTO":"\nEMOJI_CODE_PICTO()\n    Returns an object mapping emoji codes to pictographs.\n","EMOJI_PICTO_CODE":"\nEMOJI_PICTO_CODE()\n    Returns an object mapping emoji pictographs to codes.\n","emptyStream":"\nemptyStream( [options:Object] )\n    Returns an \"empty\" readable stream.\n","emptyStream.factory":"\nemptyStream.factory( [options:Object] )\n    Returns a function for creating empty readable streams.\n","emptyStream.objectMode":"\nemptyStream.objectMode()\n    Returns an \"objectMode\" empty readable stream.\n","endsWith":"\nendsWith( str:string, search:string[, len:integer] )\n    Tests if a string ends with the characters of another string.\n","enumerableProperties":"\nenumerableProperties( value:any )\n    Returns an array of an object's own enumerable property names and symbols.\n","enumerablePropertiesIn":"\nenumerablePropertiesIn( value:any )\n    Returns an array of an object's own and inherited enumerable property names\n    and symbols.\n","enumerablePropertySymbols":"\nenumerablePropertySymbols( value:any )\n    Returns an array of an object's own enumerable symbol properties.\n","enumerablePropertySymbolsIn":"\nenumerablePropertySymbolsIn( value:any )\n    Returns an array of an object's own and inherited enumerable symbol\n    properties.\n","ENV":"\nENV\n    An object containing the user environment.\n","EPS":"\nEPS\n    Difference between one and the smallest value greater than one that can be\n    represented as a double-precision floating-point number.\n","error2json":"\nerror2json( error:Error )\n    Returns a JSON representation of an error object.\n","EULERGAMMA":"\nEULERGAMMA\n    The Euler-Mascheroni constant.\n","every":"\nevery( collection:Array|TypedArray|Object )\n    Tests whether all elements in a collection are truthy.\n","everyBy":"\neveryBy( collection:Array|TypedArray|Object, predicate:Function[, \n  thisArg:any ] )\n    Tests whether all elements in a collection pass a test implemented by a\n    predicate function.\n","everyByAsync":"\neveryByAsync( collection:Array|TypedArray|Object, [options:Object,] \n  predicate:Function, done:Function )\n    Tests whether all elements in a collection pass a test implemented by a\n    predicate function.\n","everyByAsync.factory":"\neveryByAsync.factory( [options:Object,] predicate:Function )\n    Returns a function which tests whether all elements in a collection pass a\n    test implemented by a predicate function.\n","everyByRight":"\neveryByRight( collection:Array|TypedArray|Object, predicate:Function[, \n  thisArg:any ] )\n    Tests whether all elements in a collection pass a test implemented by a\n    predicate function, iterating from right to left.\n","everyByRightAsync":"\neveryByRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n  predicate:Function, done:Function )\n    Tests whether all elements in a collection pass a test implemented by a\n    predicate function, iterating from right to left.\n","everyByRightAsync.factory":"\neveryByRightAsync.factory( [options:Object,] predicate:Function )\n    Returns a function which tests whether all elements in a collection pass a\n    test implemented by a predicate function, iterating from right to left.\n","everyInBy":"\neveryInBy( object:Object, predicate:Function[, thisArg:any ] )\n   Test whether all properties (own and inherited) of an object pass a\n   test implemented by a predicate function.\n","everyOwnBy":"\neveryOwnBy( object:Object, predicate:Function[, thisArg:any ] )\n    Tests whether every own property of an object pass a test implemented by a\n    predicate function.\n","evil":"\nevil( str:string )\n    Alias for `eval` global.\n","EXEC_PATH":"\nEXEC_PATH\n    Absolute pathname of the executable which started the current Node.js\n    process.\n","exists":"\nexists( path:string|Buffer, clbk:Function )\n    Asynchronously tests whether a path exists on the filesystem.\n","exists.sync":"\nexists.sync( path:string|Buffer )\n    Synchronously tests whether a path exists on the filesystem.\n","expandAcronyms":"\nexpandAcronyms( str:string )\n    Expands acronyms in a string.\n","expandContractions":"\nexpandContractions( str:string )\n    Expands all contractions to their formal equivalents.\n","extname":"\nextname( filename:string )\n    Returns a filename extension.\n","FancyArray":"\nFancyArray( dtype:string, buffer:ArrayLikeObject|TypedArray|Buffer, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  offset:integer, order:string[, options:Object] )\n    Returns a FancyArray instance.\n","FancyArray.prototype.byteLength":"\nFancyArray.prototype.byteLength\n    Size (in bytes) of the array (if known).\n","FancyArray.prototype.BYTES_PER_ELEMENT":"\nFancyArray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element (if known).\n","FancyArray.prototype.data":"\nFancyArray.prototype.data\n    Pointer to the underlying data buffer.\n","FancyArray.prototype.dtype":"\nFancyArray.prototype.dtype\n    Underlying data type.\n","FancyArray.prototype.flags":"\nFancyArray.prototype.flags\n    Meta information, such as information concerning the memory layout of the\n    array.\n","FancyArray.prototype.length":"\nFancyArray.prototype.length\n    Length of the array (i.e., number of elements).\n","FancyArray.prototype.ndims":"\nFancyArray.prototype.ndims\n    Number of dimensions.\n","FancyArray.prototype.offset":"\nFancyArray.prototype.offset\n    Index offset which specifies the buffer index at which to start iterating\n    over array elements.\n","FancyArray.prototype.order":"\nFancyArray.prototype.order\n    Array order.\n","FancyArray.prototype.shape":"\nFancyArray.prototype.shape\n    Array shape.\n","FancyArray.prototype.strides":"\nFancyArray.prototype.strides\n    Index strides which specify how to access data along corresponding array\n    dimensions.\n","FancyArray.prototype.get":"\nFancyArray.prototype.get( ...idx:integer )\n    Returns an array element specified according to provided subscripts.\n","FancyArray.prototype.iget":"\nFancyArray.prototype.iget( idx:integer )\n    Returns an array element located at a specified linear index.\n","FancyArray.prototype.set":"\nFancyArray.prototype.set( ...idx:integer, v:any )\n    Sets an array element specified according to provided subscripts.\n","FancyArray.prototype.iset":"\nFancyArray.prototype.iset( idx:integer, v:any )\n    Sets an array element located at a specified linear index.\n","FancyArray.prototype.toString":"\nFancyArray.prototype.toString()\n    Serializes a FancyArray as a string.\n","FancyArray.prototype.toJSON":"\nFancyArray.prototype.toJSON()\n    Serializes a FancyArray as a JSON object.\n","fastmath.abs":"\nfastmath.abs( x:number )\n    Computes an absolute value.\n","fastmath.acosh":"\nfastmath.acosh( x:number )\n    Computes the hyperbolic arccosine of a number.\n","fastmath.ampbm":"\nfastmath.ampbm( x:number, y:number )\n    Computes the hypotenuse using the alpha max plus beta min algorithm.\n","fastmath.ampbm.factory":"\nfastmath.ampbm.factory( alpha:number, beta:number, [nonnegative:boolean[, \n  ints:boolean]] )\n    Returns a function to compute a hypotenuse using the alpha max plus beta min\n    algorithm.\n","fastmath.asinh":"\nfastmath.asinh( x:number )\n    Computes the hyperbolic arcsine of a number.\n","fastmath.atanh":"\nfastmath.atanh( x:number )\n    Computes the hyperbolic arctangent of a number.\n","fastmath.hypot":"\nfastmath.hypot( x:number, y:number )\n    Computes the hypotenuse.\n","fastmath.log2Uint32":"\nfastmath.log2Uint32( x:uinteger )\n    Returns an approximate binary logarithm (base two) of an unsigned 32-bit\n    integer `x`.\n","fastmath.max":"\nfastmath.max( x:number, y:number )\n    Returns the maximum value.\n","fastmath.min":"\nfastmath.min( x:number, y:number )\n    Returns the minimum value.\n","fastmath.powint":"\nfastmath.powint( x:number, y:integer )\n    Evaluates the exponential function given a signed 32-bit integer exponent.\n","fastmath.sqrtUint32":"\nfastmath.sqrtUint32( x:uinteger )\n    Returns an approximate square root of an unsigned 32-bit integer `x`.\n","FEMALE_FIRST_NAMES_EN":"\nFEMALE_FIRST_NAMES_EN()\n    Returns a list of common female first names in English speaking countries.\n","FIFO":"\nFIFO()\n    First-in-first-out (FIFO) queue constructor.\n","filledarray":"\nfilledarray( [dtype:string] )\n    Creates a filled array.\n\nfilledarray( value:any, length:integer[, dtype:string] )\n    Returns a filled array having a specified length.\n\nfilledarray( value:any, array:ArrayLikeObject[, dtype:string] )\n    Creates a filled array from another array (or array-like object).\n\nfilledarray( value:any, iterable:Iterable[, dtype:string] )\n    Creates a filled array from an iterable.\n\nfilledarray( value:any, buffer:ArrayBuffer[, byteOffset:integer[, \n  length:integer]][, dtype:string] )\n    Returns a filled typed array view of an ArrayBuffer.\n","filledarrayBy":"\nfilledarrayBy( [dtype:string] )\n    Creates a filled array.\n\nfilledarrayBy( length:integer[, dtype:string], clbk:Function[, thisArg:any] )\n    Returns a filled array according to a provided callback function and having\n    a specified length.\n\nfilledarrayBy( array:ArrayLikeObject[, dtype:string], clbk:Function[, \n  thisArg:any] )\n    Creates a filled array from another array (or array-like object) according\n    to a provided callback function.\n\nfilledarrayBy( iterable:Iterable[, dtype:string], clbk:Function[, thisArg:any] )\n    Creates a filled array from an iterable according to a provided callback\n    function.\n\nfilledarrayBy( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n  dtype:string], clbk:Function[, thisArg:any] )\n    Returns a filled typed array view of an ArrayBuffer according to a provided\n    callback function.\n","filterArguments":"\nfilterArguments( fcn:Function, predicate:Function[, thisArg:any] )\n    Returns a function that applies arguments to a provided function according\n    to a predicate function.\n","find":"\nfind( arr:Array|TypedArray|string, [options:Object,] clbk:Function )\n    Finds elements in an array-like object that satisfy a test condition.\n","firstChar":"\nfirstChar( str:string[, n:integer][, options:Object] )\n    Returns the first character(s) of a string.\n","FIVETHIRTYEIGHT_FFQ":"\nFIVETHIRTYEIGHT_FFQ()\n    Returns FiveThirtyEight reader responses to a food frequency questionnaire\n    (FFQ).\n","flattenArray":"\nflattenArray( arr:ArrayLikeObject[, options:Object] )\n    Flattens an array.\n","flattenArray.factory":"\nflattenArray.factory( dims:ArrayLike<integer>[, options:Object] )\n    Returns a function for flattening arrays having specified dimensions.\n","flattenObject":"\nflattenObject( obj:ObjectLike[, options:Object] )\n    Flattens an object.\n","flattenObject.factory":"\nflattenObject.factory( [options:Object] )\n    Returns a function to flatten an object.\n","flignerTest":"\nflignerTest( ...x:Array[, options:Object] )\n    Computes the Fligner-Killeen test for equal variances.\n","FLOAT_WORD_ORDER":"\nFLOAT_WORD_ORDER\n    Platform float word order.\n","FLOAT16_CBRT_EPS":"\nFLOAT16_CBRT_EPS\n    Cube root of half-precision floating-point epsilon.\n","FLOAT16_EPS":"\nFLOAT16_EPS\n    Difference between one and the smallest value greater than one that can be\n    represented as a half-precision floating-point number.\n","FLOAT16_EXPONENT_BIAS":"\nFLOAT16_EXPONENT_BIAS\n    The bias of a half-precision floating-point number's exponent.\n","FLOAT16_MAX":"\nFLOAT16_MAX\n    Maximum half-precision floating-point number.\n","FLOAT16_MAX_SAFE_INTEGER":"\nFLOAT16_MAX_SAFE_INTEGER\n    Maximum safe half-precision floating-point integer.\n","FLOAT16_MIN_SAFE_INTEGER":"\nFLOAT16_MIN_SAFE_INTEGER\n    Minimum safe half-precision floating-point integer.\n","FLOAT16_NINF":"\nFLOAT16_NINF\n    Half-precision floating-point negative infinity.\n","FLOAT16_NUM_BYTES":"\nFLOAT16_NUM_BYTES\n    Size (in bytes) of a half-precision floating-point number.\n","FLOAT16_PINF":"\nFLOAT16_PINF\n    Half-precision floating-point positive infinity.\n","FLOAT16_PRECISION":"\nFLOAT16_PRECISION\n    Effective number of bits in the significand of a half-precision floating-\n    point number.\n","FLOAT16_SMALLEST_NORMAL":"\nFLOAT16_SMALLEST_NORMAL\n    Smallest positive normalized half-precision floating-point number.\n","FLOAT16_SMALLEST_SUBNORMAL":"\nFLOAT16_SMALLEST_SUBNORMAL\n    Smallest positive denormalized half-precision floating-point number.\n","FLOAT16_SQRT_EPS":"\nFLOAT16_SQRT_EPS\n    Square root of half-precision floating-point epsilon.\n","FLOAT32_ABS_MASK":"\nFLOAT32_ABS_MASK\n    Mask for excluding the sign bit of a single-precision floating-point number.\n","FLOAT32_CBRT_EPS":"\nFLOAT32_CBRT_EPS\n    Cube root of single-precision floating-point epsilon.\n","FLOAT32_E":"\nFLOAT32_E\n    Euler's number.\n","FLOAT32_EPS":"\nFLOAT32_EPS\n    Difference between one and the smallest value greater than one that can be\n    represented as a single-precision floating-point number.\n","FLOAT32_EXPONENT_BIAS":"\nFLOAT32_EXPONENT_BIAS\n    The bias of a single-precision floating-point number's exponent.\n","FLOAT32_EXPONENT_MASK":"\nFLOAT32_EXPONENT_MASK\n    Mask for the exponent of a single-precision floating-point number.\n","FLOAT32_FOURTH_PI":"\nFLOAT32_FOURTH_PI\n    One fourth times the mathematical constant `π`.\n","FLOAT32_HALF_LN_TWO":"\nFLOAT32_HALF_LN_TWO\n    One half times the natural logarithm of 2 as a single-precision\n    floating-point number.\n","FLOAT32_HALF_PI":"\nFLOAT32_HALF_PI\n    One half times the mathematical constant `π`.\n","FLOAT32_LN_HALF":"\nFLOAT32_LN_HALF\n    Natural logarithm of `1/2` as a single-precision floating-point number.\n","FLOAT32_LN_PI":"\nFLOAT32_LN_PI\n    Natural logarithm of the mathematical constant `π` as a single-precision\n    floating-point number.\n","FLOAT32_LN_TEN":"\nFLOAT32_LN_TEN\n    Natural logarithm of `10` as a single-precision floating-point number.\n","FLOAT32_LN_TWO":"\nFLOAT32_LN_TWO\n    Natural logarithm of `2` as a single-precision floating-point number.\n","FLOAT32_MAX":"\nFLOAT32_MAX\n    Maximum single-precision floating-point number.\n","FLOAT32_MAX_BASE2_EXPONENT":"\nFLOAT32_MAX_BASE2_EXPONENT\n    The maximum biased base 2 exponent for a single-precision floating-point\n    number.\n","FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL\n    The maximum biased base 2 exponent for a subnormal single-precision\n    floating-point number.\n","FLOAT32_MAX_BASE10_EXPONENT":"\nFLOAT32_MAX_BASE10_EXPONENT\n    The maximum base 10 exponent for a single-precision floating-point number.\n","FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL\n    The maximum base 10 exponent for a subnormal single-precision floating-point\n    number.\n","FLOAT32_MAX_SAFE_FIBONACCI":"\nFLOAT32_MAX_SAFE_FIBONACCI\n    Maximum safe Fibonacci number when stored in single-precision floating-point\n    format.\n","FLOAT32_MAX_SAFE_INTEGER":"\nFLOAT32_MAX_SAFE_INTEGER\n    Maximum safe single-precision floating-point integer.\n","FLOAT32_MAX_SAFE_NTH_FACTORIAL":"\nFLOAT32_MAX_SAFE_NTH_FACTORIAL\n    Maximum safe nth factorial when stored in single-precision floating-\n    point format.\n","FLOAT32_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT32_MAX_SAFE_NTH_FIBONACCI\n    Maximum safe nth Fibonacci number when stored in single-precision floating-\n    point format.\n","FLOAT32_MAX_SAFE_NTH_LUCAS":"\nFLOAT32_MAX_SAFE_NTH_LUCAS\n    Maximum safe nth Lucas number when stored in single-precision floating-point\n    format.\n","FLOAT32_MIN_BASE2_EXPONENT":"\nFLOAT32_MIN_BASE2_EXPONENT\n    The minimum biased base 2 exponent for a normalized single-precision\n    floating-point number.\n","FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL\n    The minimum biased base 2 exponent for a subnormal single-precision\n    floating-point number.\n","FLOAT32_MIN_BASE10_EXPONENT":"\nFLOAT32_MIN_BASE10_EXPONENT\n    The minimum base 10 exponent for a normal single-precision floating-\n    point number.\n","FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL\n    The minimum base 10 exponent for a subnormal single-precision floating-\n    point number.\n","FLOAT32_MIN_SAFE_INTEGER":"\nFLOAT32_MIN_SAFE_INTEGER\n    Minimum safe single-precision floating-point integer.\n","FLOAT32_NAN":"\nFLOAT32_NAN\n    Single-precision floating-point NaN.\n","FLOAT32_NINF":"\nFLOAT32_NINF\n    Single-precision floating-point negative infinity.\n","FLOAT32_NUM_BYTES":"\nFLOAT32_NUM_BYTES\n    Size (in bytes) of a single-precision floating-point number.\n","FLOAT32_PHI":"\nFLOAT32_PHI\n    Golden ratio.\n","FLOAT32_PI":"\nFLOAT32_PI\n    The mathematical constant `π`.\n","FLOAT32_PINF":"\nFLOAT32_PINF\n    Single-precision floating-point positive infinity.\n","FLOAT32_PRECISION":"\nFLOAT32_PRECISION\n    Effective number of bits in the significand of a single-precision floating-\n    point number.\n","FLOAT32_SIGN_MASK":"\nFLOAT32_SIGN_MASK\n    Mask for the sign bit of a single-precision floating-point number.\n","FLOAT32_SIGNIFICAND_MASK":"\nFLOAT32_SIGNIFICAND_MASK\n    Mask for the significand of a single-precision floating-point number.\n","FLOAT32_SMALLEST_NORMAL":"\nFLOAT32_SMALLEST_NORMAL\n    Smallest positive normalized single-precision floating-point number.\n","FLOAT32_SMALLEST_SUBNORMAL":"\nFLOAT32_SMALLEST_SUBNORMAL\n    Smallest positive denormalized single-precision floating-point number.\n","FLOAT32_SQRT_EPS":"\nFLOAT32_SQRT_EPS\n    Square root of single-precision floating-point epsilon.\n","FLOAT32_SQRT_HALF":"\nFLOAT32_SQRT_HALF\n    Square root of `1/2` as a single-precision floating-point number.\n","FLOAT32_SQRT_HALF_PI":"\nFLOAT32_SQRT_HALF_PI\n    Square root of `π` divided by `2` as a single-precision \n    floating-point number.\n","FLOAT32_SQRT_PHI":"\nFLOAT32_SQRT_PHI\n    Square root of the golden ratio as a single-precision floating-point number.\n","FLOAT32_SQRT_PI":"\nFLOAT32_SQRT_PI\n    Square root of the mathematical constant `π` as a single-precision\n    floating-point number.\n","FLOAT32_SQRT_THREE":"\nFLOAT32_SQRT_THREE\n    Square root of `3` as a single-precision floating-point number.\n","FLOAT32_SQRT_TWO":"\nFLOAT32_SQRT_TWO\n    Square root of `2` as a single-precision floating-point number.\n","FLOAT32_SQRT_TWO_PI":"\nFLOAT32_SQRT_TWO_PI\n    Square root of the `π` times `2` as single-precision floating-point number.\n","FLOAT32_TWO_PI":"\nFLOAT32_TWO_PI\n    The mathematical constant `π` times `2`.\n","Float32Array":"\nFloat32Array()\n    A typed array constructor which returns a typed array representing an array\n    of single-precision floating-point numbers in the platform byte order.\n\nFloat32Array( length:integer )\n    Returns a typed array having a specified length.\n\nFloat32Array( typedarray:TypedArray )\n    Creates a typed array from another typed array.\n\nFloat32Array( obj:Object )\n    Creates a typed array from an array-like object or iterable.\n\nFloat32Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a typed array view of an ArrayBuffer.\n","Float32Array.from":"\nFloat32Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n    Creates a new typed array from an array-like object or an iterable.\n","Float32Array.of":"\nFloat32Array.of( element0:number[, element1:number[, ...elementN:number]] )\n    Creates a new typed array from a variable number of arguments.\n","Float32Array.BYTES_PER_ELEMENT":"\nFloat32Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Float32Array.name":"\nFloat32Array.name\n    Typed array constructor name.\n","Float32Array.prototype.buffer":"\nFloat32Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n","Float32Array.prototype.byteLength":"\nFloat32Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n","Float32Array.prototype.byteOffset":"\nFloat32Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n","Float32Array.prototype.BYTES_PER_ELEMENT":"\nFloat32Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Float32Array.prototype.length":"\nFloat32Array.prototype.length\n    Read-only property which returns the number of view elements.\n","Float32Array.prototype.copyWithin":"\nFloat32Array.prototype.copyWithin( target:integer, start:integer[, \n  end:integer] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","Float32Array.prototype.entries":"\nFloat32Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","Float32Array.prototype.every":"\nFloat32Array.prototype.every( predicate:Function[, thisArg:Any] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n","Float32Array.prototype.fill":"\nFloat32Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n","Float32Array.prototype.filter":"\nFloat32Array.prototype.filter( predicate:Function[, thisArg:Any] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n","Float32Array.prototype.find":"\nFloat32Array.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n","Float32Array.prototype.findIndex":"\nFloat32Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n","Float32Array.prototype.forEach":"\nFloat32Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n    Invokes a callback for each array element.\n","Float32Array.prototype.includes":"\nFloat32Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a search element.\n","Float32Array.prototype.indexOf":"\nFloat32Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n","Float32Array.prototype.join":"\nFloat32Array.prototype.join( [separator:string] )\n    Serializes an array by joining all array elements as a string.\n","Float32Array.prototype.keys":"\nFloat32Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n","Float32Array.prototype.lastIndexOf":"\nFloat32Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n","Float32Array.prototype.map":"\nFloat32Array.prototype.map( fcn:Function[, thisArg:Any] )\n    Maps each array element to an element in a new typed array.\n","Float32Array.prototype.reduce":"\nFloat32Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n","Float32Array.prototype.reduceRight":"\nFloat32Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n","Float32Array.prototype.reverse":"\nFloat32Array.prototype.reverse()\n    Reverses an array *in-place*.\n","Float32Array.prototype.set":"\nFloat32Array.prototype.set( arr:ArrayLike[, offset:integer] )\n    Sets array elements.\n","Float32Array.prototype.slice":"\nFloat32Array.prototype.slice( [begin:integer[, end:integer]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n","Float32Array.prototype.some":"\nFloat32Array.prototype.some( predicate:Function[, thisArg:Any] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n","Float32Array.prototype.sort":"\nFloat32Array.prototype.sort( [compareFunction:Function] )\n    Sorts an array *in-place*.\n","Float32Array.prototype.subarray":"\nFloat32Array.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n","Float32Array.prototype.toLocaleString":"\nFloat32Array.prototype.toLocaleString( [locales:string|Array[, \n  options:Object]] )\n    Serializes an array as a locale-specific string.\n","Float32Array.prototype.toString":"\nFloat32Array.prototype.toString()\n    Serializes an array as a string.\n","Float32Array.prototype.values":"\nFloat32Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n","FLOAT64_EXPONENT_BIAS":"\nFLOAT64_EXPONENT_BIAS\n    The bias of a double-precision floating-point number's exponent.\n","FLOAT64_HIGH_WORD_ABS_MASK":"\nFLOAT64_HIGH_WORD_ABS_MASK\n    High word mask for excluding the sign bit of a double-precision floating-\n    point number.\n","FLOAT64_HIGH_WORD_EXPONENT_MASK":"\nFLOAT64_HIGH_WORD_EXPONENT_MASK\n    High word mask for the exponent of a double-precision floating-point number.\n","FLOAT64_HIGH_WORD_SIGN_MASK":"\nFLOAT64_HIGH_WORD_SIGN_MASK\n    High word mask for the sign bit of a double-precision floating-point number.\n","FLOAT64_HIGH_WORD_SIGNIFICAND_MASK":"\nFLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n    High word mask for the significand of a double-precision floating-point\n    number.\n","FLOAT64_MAX":"\nFLOAT64_MAX\n    Maximum double-precision floating-point number.\n","FLOAT64_MAX_BASE2_EXPONENT":"\nFLOAT64_MAX_BASE2_EXPONENT\n    The maximum biased base 2 exponent for a double-precision floating-point\n    number.\n","FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n    The maximum biased base 2 exponent for a subnormal double-precision\n    floating-point number.\n","FLOAT64_MAX_BASE10_EXPONENT":"\nFLOAT64_MAX_BASE10_EXPONENT\n    The maximum base 10 exponent for a double-precision floating-point number.\n","FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n    The maximum base 10 exponent for a subnormal double-precision floating-point\n    number.\n","FLOAT64_MAX_LN":"\nFLOAT64_MAX_LN\n    Natural logarithm of the maximum double-precision floating-point number.\n","FLOAT64_MAX_SAFE_FIBONACCI":"\nFLOAT64_MAX_SAFE_FIBONACCI\n    Maximum safe Fibonacci number when stored in double-precision floating-point\n    format.\n","FLOAT64_MAX_SAFE_INTEGER":"\nFLOAT64_MAX_SAFE_INTEGER\n    Maximum safe double-precision floating-point integer.\n","FLOAT64_MAX_SAFE_LUCAS":"\nFLOAT64_MAX_SAFE_LUCAS\n    Maximum safe Lucas number when stored in double-precision floating-point\n    format.\n","FLOAT64_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT64_MAX_SAFE_NTH_FIBONACCI\n    Maximum safe nth Fibonacci number when stored in double-precision floating-\n    point format.\n","FLOAT64_MAX_SAFE_NTH_LUCAS":"\nFLOAT64_MAX_SAFE_NTH_LUCAS\n    Maximum safe nth Lucas number when stored in double-precision floating-point\n    format.\n","FLOAT64_MIN_BASE2_EXPONENT":"\nFLOAT64_MIN_BASE2_EXPONENT\n    The minimum biased base 2 exponent for a normalized double-precision\n    floating-point number.\n","FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n    The minimum biased base 2 exponent for a subnormal double-precision\n    floating-point number.\n","FLOAT64_MIN_BASE10_EXPONENT":"\nFLOAT64_MIN_BASE10_EXPONENT\n    The minimum base 10 exponent for a normalized double-precision floating-\n    point number.\n","FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n    The minimum base 10 exponent for a subnormal double-precision floating-\n    point number.\n","FLOAT64_MIN_LN":"\nFLOAT64_MIN_LN\n    Natural logarithm of the smallest normalized double-precision floating-point\n    number.\n","FLOAT64_MIN_SAFE_INTEGER":"\nFLOAT64_MIN_SAFE_INTEGER\n    Minimum safe double-precision floating-point integer.\n","FLOAT64_NUM_BYTES":"\nFLOAT64_NUM_BYTES\n    Size (in bytes) of a double-precision floating-point number.\n","FLOAT64_PRECISION":"\nFLOAT64_PRECISION\n    Effective number of bits in the significand of a double-precision floating-\n    point number.\n","FLOAT64_SMALLEST_NORMAL":"\nFLOAT64_SMALLEST_NORMAL\n    Smallest positive normalized double-precision floating-point number.\n","FLOAT64_SMALLEST_SUBNORMAL":"\nFLOAT64_SMALLEST_SUBNORMAL\n    Smallest positive denormalized double-precision floating-point number.\n","Float64Array":"\nFloat64Array()\n    A typed array constructor which returns a typed array representing an array\n    of double-precision floating-point numbers in the platform byte order.\n\nFloat64Array( length:integer )\n    Returns a typed array having a specified length.\n\nFloat64Array( typedarray:TypedArray )\n    Creates a typed array from another typed array.\n\nFloat64Array( obj:Object )\n    Creates a typed array from an array-like object or iterable.\n\nFloat64Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a typed array view of an ArrayBuffer.\n","Float64Array.from":"\nFloat64Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n    Creates a new typed array from an array-like object or an iterable.\n","Float64Array.of":"\nFloat64Array.of( element0:number[, element1:number[, ...elementN:number]] )\n    Creates a new typed array from a variable number of arguments.\n","Float64Array.BYTES_PER_ELEMENT":"\nFloat64Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Float64Array.name":"\nFloat64Array.name\n    Typed array constructor name.\n","Float64Array.prototype.buffer":"\nFloat64Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n","Float64Array.prototype.byteLength":"\nFloat64Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n","Float64Array.prototype.byteOffset":"\nFloat64Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n","Float64Array.prototype.BYTES_PER_ELEMENT":"\nFloat64Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Float64Array.prototype.length":"\nFloat64Array.prototype.length\n    Read-only property which returns the number of view elements.\n","Float64Array.prototype.copyWithin":"\nFloat64Array.prototype.copyWithin( target:integer, start:integer[, \n  end:integer] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","Float64Array.prototype.entries":"\nFloat64Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","Float64Array.prototype.every":"\nFloat64Array.prototype.every( predicate:Function[, thisArg:Any] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n","Float64Array.prototype.fill":"\nFloat64Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n","Float64Array.prototype.filter":"\nFloat64Array.prototype.filter( predicate:Function[, thisArg:Any] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n","Float64Array.prototype.find":"\nFloat64Array.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n","Float64Array.prototype.findIndex":"\nFloat64Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n","Float64Array.prototype.forEach":"\nFloat64Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n    Invokes a callback for each array element.\n","Float64Array.prototype.includes":"\nFloat64Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a search element.\n","Float64Array.prototype.indexOf":"\nFloat64Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n","Float64Array.prototype.join":"\nFloat64Array.prototype.join( [separator:string] )\n    Serializes an array by joining all array elements as a string.\n","Float64Array.prototype.keys":"\nFloat64Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n","Float64Array.prototype.lastIndexOf":"\nFloat64Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n","Float64Array.prototype.map":"\nFloat64Array.prototype.map( fcn:Function[, thisArg:Any] )\n    Maps each array element to an element in a new typed array.\n","Float64Array.prototype.reduce":"\nFloat64Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n","Float64Array.prototype.reduceRight":"\nFloat64Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n","Float64Array.prototype.reverse":"\nFloat64Array.prototype.reverse()\n    Reverses an array *in-place*.\n","Float64Array.prototype.set":"\nFloat64Array.prototype.set( arr:ArrayLike[, offset:integer] )\n    Sets array elements.\n","Float64Array.prototype.slice":"\nFloat64Array.prototype.slice( [begin:integer[, end:integer]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n","Float64Array.prototype.some":"\nFloat64Array.prototype.some( predicate:Function[, thisArg:Any] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n","Float64Array.prototype.sort":"\nFloat64Array.prototype.sort( [compareFunction:Function] )\n    Sorts an array *in-place*.\n","Float64Array.prototype.subarray":"\nFloat64Array.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n","Float64Array.prototype.toLocaleString":"\nFloat64Array.prototype.toLocaleString( [locales:string|Array[, \n  options:Object]] )\n    Serializes an array as a locale-specific string.\n","Float64Array.prototype.toString":"\nFloat64Array.prototype.toString()\n    Serializes an array as a string.\n","Float64Array.prototype.values":"\nFloat64Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n","forEach":"\nforEach( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n    Invokes a function for each element in a collection.\n","forEachAsync":"\nforEachAsync( collection:Array|TypedArray|Object, [options:Object,] \n  fcn:Function, done:Function )\n    Invokes a function once for each element in a collection.\n","forEachAsync.factory":"\nforEachAsync.factory( [options:Object,] fcn:Function )\n    Returns a function which invokes a function once for each element in a\n    collection.\n","forEachChar":"\nforEachChar( str:string, [options:Object,] clbk:Function[, thisArg:any] )\n    Invokes a function for each character in a string.\n","forEachRight":"\nforEachRight( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n    Invokes a function for each element in a collection, iterating from right to\n    left.\n","forEachRightAsync":"\nforEachRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n  fcn:Function, done:Function )\n    Invokes a function once for each element in a collection, iterating from\n    right to left.\n","forEachRightAsync.factory":"\nforEachRightAsync.factory( [options:Object,] fcn:Function )\n    Returns a function which invokes a function once for each element in a\n    collection, iterating from right to left.\n","forIn":"\nforIn( obj:Object, fcn:Function[, thisArg:any] )\n    Invokes a function for each own and inherited enumerable property of an\n    object.\n","format":"\nformat( str:string, ...args:any )\n    Insert supplied variable values into a format string.\n","forOwn":"\nforOwn( obj:Object, fcn:Function[, thisArg:any] )\n    Invokes a function for each own enumerable property of an object.\n","FOURTH_PI":"\nFOURTH_PI\n    One fourth times the mathematical constant `π`.\n","FOURTH_ROOT_EPS":"\nFOURTH_ROOT_EPS\n    Fourth root of double-precision floating-point epsilon.\n","FRB_SF_WAGE_RIGIDITY":"\nFRB_SF_WAGE_RIGIDITY()\n    Returns wage rates for U.S. workers that have not changed jobs within the\n    year.\n","fromCodePoint":"\nfromCodePoint( ...pt:integer )\n    Creates a string from a sequence of Unicode code points.\n","Function":"\nFunction( [...argNames:any,] body:string )\n    Returns a Function object.\n","Function.prototype.apply":"\nFunction.prototype.apply( thisArg:any, args:Array )\n    Calls a function with a given `this` value and arguments provided as an\n    array (or array-like object).\n","Function.prototype.call":"\nFunction.prototype.call( thisArg:any, ...args:any )\n    Calls a function with a given `this` value and arguments provided\n    individually.\n","Function.prototype.bind":"\nFunction.prototype.bind( thisArg:any, ...args:any )\n    Creates a new function which, when called, has its `this` keyword set to the\n    provided value, with a given sequence of arguments preceding any provided\n    when the new function is called.\n","Function.prototype.toString":"\nFunction.prototype.toString()\n    Returns a string representation of the function.\n","Function.prototype.length":"\nFunction.prototype.length\n    The number of arguments expected by the function.\n","Function.prototype.name":"\nFunction.prototype.name\n    The name of the function.\n","Function.prototype.prototype":"\nFunction.prototype.prototype\n    The prototype of the function.\n","function2string":"\nfunction2string( fcn:Function )\n    Returns a string representing the source code of a provided function.\n","functionName":"\nfunctionName( fcn:Function )\n    Returns the name of a function.\n","functionSequence":"\nfunctionSequence( ...fcn:Function )\n    Returns a pipeline function.\n","functionSequenceAsync":"\nfunctionSequenceAsync( ...fcn:Function )\n    Returns a pipeline function.\n","GAMMA_LANCZOS_G":"\nGAMMA_LANCZOS_G\n    Arbitrary constant `g` to be used in Lanczos approximation functions.\n","gdot":"\ngdot( x:ndarray|ArrayLikeObject, y:ndarray|ArrayLikeObject )\n    Computes the dot product of two vectors.\n","getegid":"\ngetegid()\n    Returns the effective numeric group identity of the calling process.\n","geteuid":"\ngeteuid()\n    Returns the effective numeric user identity of the calling process.\n","getgid":"\ngetgid()\n    Returns the numeric group identity of the calling process.\n","getGlobal":"\ngetGlobal( [codegen:boolean] )\n    Returns the global object.\n","getPrototypeOf":"\ngetPrototypeOf( value:any )\n    Returns the prototype of a provided object.\n","getuid":"\ngetuid()\n    Returns the numeric user identity of the calling process.\n","GLAISHER":"\nGLAISHER\n    Glaisher-Kinkelin constant.\n","graphemeClusters2iterator":"\ngraphemeClusters2iterator( src:string[, mapFcn:Function[, thisArg:any]] )\n    Returns an iterator which iterates over each grapheme cluster in a string.\n","graphemeClusters2iteratorRight":"\ngraphemeClusters2iteratorRight( src:string[, mapFcn:Function[, thisArg:any]] )\n    Returns an iterator which iterates from right to left over each grapheme\n    cluster in a string.\n","group":"\ngroup( collection:Array|TypedArray|Object, [options:Object,] \n  groups:Array|TypedArray|Object )\n    Groups values as arrays associated with distinct keys.\n","groupBy":"\ngroupBy( collection:Array|TypedArray|Object, [options:Object,] \n  indicator:Function )\n    Groups values according to an indicator function.\n","groupByAsync":"\ngroupByAsync( collection:Array|TypedArray|Object, [options:Object,] \n  indicator:Function, done:Function )\n    Groups values according to an indicator function.\n","groupByAsync.factory":"\ngroupByAsync.factory( [options:Object,] indicator:Function )\n    Returns a function which groups values according to an indicator function.\n","groupIn":"\ngroupIn( obj:Object|Array|TypedArray, [options:Object,] indicator:Function )\n    Group values according to an indicator function.\n","groupOwn":"\ngroupOwn( obj:Object|Array|TypedArray, [options:Object,] indicator:Function )\n    Group values according to an indicator function.\n","gswap":"\ngswap( x:ndarray|ArrayLikeObject, y:ndarray|ArrayLikeObject )\n    Interchanges two vectors.\n","HALF_LN2":"\nHALF_LN2\n    One half times the natural logarithm of `2`.\n","HALF_PI":"\nHALF_PI\n    One half times the mathematical constant `π`.\n","HARRISON_BOSTON_HOUSE_PRICES":"\nHARRISON_BOSTON_HOUSE_PRICES()\n    Returns a dataset derived from information collected by the US Census\n    Service concerning housing in Boston, Massachusetts (1978).\n","HARRISON_BOSTON_HOUSE_PRICES_CORRECTED":"\nHARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n    Returns a (corrected) dataset derived from information collected by the US\n    Census Service concerning housing in Boston, Massachusetts (1978).\n","hasArrayBufferSupport":"\nhasArrayBufferSupport()\n    Tests for native `ArrayBuffer` support.\n","hasArrowFunctionSupport":"\nhasArrowFunctionSupport()\n    Tests whether an environment supports native arrow functions.\n","hasAsyncAwaitSupport":"\nhasAsyncAwaitSupport()\n    Tests for native `async`/`await` support.\n","hasAsyncIteratorSymbolSupport":"\nhasAsyncIteratorSymbolSupport()\n    Tests for native `Symbol.asyncIterator` support.\n","hasAtobSupport":"\nhasAtobSupport()\n    Tests for native `atob` support.\n","hasBigInt64ArraySupport":"\nhasBigInt64ArraySupport()\n    Tests for native `BigInt64Array` support.\n","hasBigIntSupport":"\nhasBigIntSupport()\n    Tests for native `BigInt` support.\n","hasBigUint64ArraySupport":"\nhasBigUint64ArraySupport()\n    Tests for native `BigUint64Array` support.\n","hasBtoaSupport":"\nhasBtoaSupport()\n    Tests for native `btoa` support.\n","hasClassSupport":"\nhasClassSupport()\n    Tests for native `class` support.\n","hasDataViewSupport":"\nhasDataViewSupport()\n    Tests for native `DataView` support.\n","hasDefinePropertiesSupport":"\nhasDefinePropertiesSupport()\n    Tests for `Object.defineProperties` support.\n","hasDefinePropertySupport":"\nhasDefinePropertySupport()\n    Tests for `Object.defineProperty` support.\n","hasFloat32ArraySupport":"\nhasFloat32ArraySupport()\n    Tests for native `Float32Array` support.\n","hasFloat64ArraySupport":"\nhasFloat64ArraySupport()\n    Tests for native `Float64Array` support.\n","hasFunctionNameSupport":"\nhasFunctionNameSupport()\n    Tests for native function `name` support.\n","hasGeneratorSupport":"\nhasGeneratorSupport()\n    Tests whether an environment supports native generator functions.\n","hasGlobalThisSupport":"\nhasGlobalThisSupport()\n    Tests for `globalThis` support.\n","hasInt8ArraySupport":"\nhasInt8ArraySupport()\n    Tests for native `Int8Array` support.\n","hasInt16ArraySupport":"\nhasInt16ArraySupport()\n    Tests for native `Int16Array` support.\n","hasInt32ArraySupport":"\nhasInt32ArraySupport()\n    Tests for native `Int32Array` support.\n","hasIteratorSymbolSupport":"\nhasIteratorSymbolSupport()\n    Tests for native `Symbol.iterator` support.\n","hasMapSupport":"\nhasMapSupport()\n    Tests for native `Map` support.\n","hasNodeBufferSupport":"\nhasNodeBufferSupport()\n    Tests for native `Buffer` support.\n","hasOwnProp":"\nhasOwnProp( value:any, property:any )\n    Tests if an object has a specified property.\n","hasProp":"\nhasProp( value:any, property:any )\n    Tests if an object has a specified property, either own or inherited.\n","hasProxySupport":"\nhasProxySupport()\n    Tests whether an environment has native `Proxy` support.\n","hasSetSupport":"\nhasSetSupport()\n    Tests for native `Set` support.\n","hasSharedArrayBufferSupport":"\nhasSharedArrayBufferSupport()\n    Tests for native `SharedArrayBuffer` support.\n","hasSymbolSupport":"\nhasSymbolSupport()\n    Tests for native `Symbol` support.\n","hasToStringTagSupport":"\nhasToStringTagSupport()\n    Tests for native `toStringTag` support.\n","hasUint8ArraySupport":"\nhasUint8ArraySupport()\n    Tests for native `Uint8Array` support.\n","hasUint8ClampedArraySupport":"\nhasUint8ClampedArraySupport()\n    Tests for native `Uint8ClampedArray` support.\n","hasUint16ArraySupport":"\nhasUint16ArraySupport()\n    Tests for native `Uint16Array` support.\n","hasUint32ArraySupport":"\nhasUint32ArraySupport()\n    Tests for native `Uint32Array` support.\n","hasUTF16SurrogatePairAt":"\nhasUTF16SurrogatePairAt( str:string, pos:integer )\n    Tests if a position in a string marks the start of a UTF-16 surrogate pair.\n","hasWeakMapSupport":"\nhasWeakMapSupport()\n    Tests for native `WeakMap` support.\n","hasWeakSetSupport":"\nhasWeakSetSupport()\n    Tests for native `WeakSet` support.\n","hasWebAssemblySupport":"\nhasWebAssemblySupport()\n    Tests for native WebAssembly support.\n","headercase":"\nheadercase( str:string )\n    Converts a string to HTTP header case.\n","HERNDON_VENUS_SEMIDIAMETERS":"\nHERNDON_VENUS_SEMIDIAMETERS()\n    Returns fifteen observations of the vertical semidiameter of Venus, made by\n    Lieutenant Herndon, with the meridian circle at Washington, in the year\n    1846.\n","homedir":"\nhomedir()\n    Returns the current user's home directory.\n","HOURS_IN_DAY":"\nHOURS_IN_DAY\n    Number of hours in a day.\n","HOURS_IN_WEEK":"\nHOURS_IN_WEEK\n    Number of hours in a week.\n","hoursInMonth":"\nhoursInMonth( [month:string|Date|integer[, year:integer]] )\n    Returns the number of hours in a month.\n","hoursInYear":"\nhoursInYear( [value:integer|Date] )\n    Returns the number of hours in a year according to the Gregorian calendar.\n","httpServer":"\nhttpServer( [options:Object,] [requestListener:Function] )\n    Returns a function to create an HTTP server.\n","identity":"\nidentity( x:any )\n    Identity function.\n","ifelse":"\nifelse( bool:boolean, x:any, y:any )\n    If a condition is truthy, returns `x`; otherwise, returns `y`.\n","ifelseAsync":"\nifelseAsync( predicate:Function, x:any, y:any, done:Function )\n    If a predicate function returns a truthy value, returns `x`; otherwise,\n    returns `y`.\n","ifthen":"\nifthen( bool:boolean, x:Function, y:Function )\n    If a condition is truthy, invoke `x`; otherwise, invoke `y`.\n","ifthenAsync":"\nifthenAsync( predicate:Function, x:Function, y:Function, done:Function )\n    If a predicate function returns a truthy value, invokes `x`; otherwise,\n    invokes `y`.\n","imag":"\nimag( z:Complex128 )\n    Returns the imaginary component of a double-precision complex floating-point\n    number.\n","imagf":"\nimagf( z:Complex64 )\n    Returns the imaginary component of a single-precision complex floating-point\n    number.\n","IMG_ACANTHUS_MOLLIS":"\nIMG_ACANTHUS_MOLLIS()\n    Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n    print *Acanthus mollis*.\n","IMG_AIRPLANE_FROM_ABOVE":"\nIMG_AIRPLANE_FROM_ABOVE()\n    Returns a `Buffer` containing image data of Fédèle Azari's gelatin silver\n    print of an airplane, viewed from above looking down.\n","IMG_ALLIUM_OREOPHILUM":"\nIMG_ALLIUM_OREOPHILUM()\n    Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n    print *Allium ostrowskianum*.\n","IMG_BLACK_CANYON":"\nIMG_BLACK_CANYON()\n    Returns a `Buffer` containing image data of Timothy H. O'Sullivan's albumen\n    silver print *Black Cañon, Colorado River, From Camp 8, Looking Above*.\n","IMG_DUST_BOWL_HOME":"\nIMG_DUST_BOWL_HOME()\n    Returns a `Buffer` containing image data of Dorothea Lange's gelatin silver\n    print of an abandoned Dust Bowl home.\n","IMG_FRENCH_ALPINE_LANDSCAPE":"\nIMG_FRENCH_ALPINE_LANDSCAPE()\n    Returns a `Buffer` containing image data of Adolphe Braun's carbon print of\n    a French alpine landscape.\n","IMG_LOCOMOTION_HOUSE_CAT":"\nIMG_LOCOMOTION_HOUSE_CAT()\n    Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n    collotype of a house cat (24 views).\n","IMG_LOCOMOTION_NUDE_MALE":"\nIMG_LOCOMOTION_NUDE_MALE()\n    Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n    collotype of a nude male moving in place (48 views).\n","IMG_MARCH_PASTORAL":"\nIMG_MARCH_PASTORAL()\n    Returns a `Buffer` containing image data of Peter Henry Emerson's\n    photogravure of sheep in a pastoral setting.\n","IMG_NAGASAKI_BOATS":"\nIMG_NAGASAKI_BOATS()\n    Returns a `Buffer` containing image data of Felice Beato's albumen silver\n    print of boats in a river in Nagasaki.\n","incrapcorr":"\nincrapcorr( [mx:number, my:number] )\n    Returns an accumulator function which incrementally computes the absolute\n    value of the sample Pearson product-moment correlation coefficient.\n","incrBinaryClassification":"\nincrBinaryClassification( N:integer[, options:Object] )\n    Returns an accumulator function which incrementally performs binary\n    classification using stochastic gradient descent (SGD).\n","incrcount":"\nincrcount()\n    Returns an accumulator function which incrementally updates a count.\n","incrcovariance":"\nincrcovariance( [mx:number, my:number] )\n    Returns an accumulator function which incrementally computes an unbiased\n    sample covariance.\n","incrcovmat":"\nincrcovmat( out:integer|ndarray[, means:ndarray] )\n    Returns an accumulator function which incrementally computes an unbiased\n    sample covariance matrix.\n","incrcv":"\nincrcv( [mean:number] )\n    Returns an accumulator function which incrementally computes the coefficient\n    of variation (CV).\n","increwmean":"\nincrewmean( α:number )\n    Returns an accumulator function which incrementally computes an\n    exponentially weighted mean, where α is a smoothing factor between 0 and 1.\n","increwstdev":"\nincrewstdev( α:number )\n    Returns an accumulator function which incrementally computes an\n    exponentially weighted standard deviation, where α is a smoothing factor\n    between 0 and 1.\n","increwvariance":"\nincrewvariance( α:number )\n    Returns an accumulator function which incrementally computes an\n    exponentially weighted variance, where α is a smoothing factor between 0 and\n    1.\n","incrgmean":"\nincrgmean()\n    Returns an accumulator function which incrementally computes a geometric\n    mean.\n","incrgrubbs":"\nincrgrubbs( [options:Object] )\n    Returns an accumulator function which incrementally performs Grubbs' test\n    for detecting outliers.\n","incrhmean":"\nincrhmean()\n    Returns an accumulator function which incrementally computes a harmonic\n    mean.\n","incrkmeans":"\nincrkmeans( k:integer|ndarray[, ndims:integer][, options:Object] )\n    Returns an accumulator function which incrementally partitions data into `k`\n    clusters.\n","incrkurtosis":"\nincrkurtosis()\n    Returns an accumulator function which incrementally computes a corrected\n    sample excess kurtosis.\n","incrmaape":"\nincrmaape()\n    Returns an accumulator function which incrementally computes the mean\n    arctangent absolute percentage error (MAAPE).\n","incrmae":"\nincrmae()\n    Returns an accumulator function which incrementally computes the mean\n    absolute error (MAE).\n","incrmapcorr":"\nincrmapcorr( W:integer[, mx:number, my:number] )\n    Returns an accumulator function which incrementally computes a moving\n    sample absolute Pearson product-moment correlation coefficient.\n","incrmape":"\nincrmape()\n    Returns an accumulator function which incrementally computes the mean\n    absolute percentage error (MAPE).\n","incrmax":"\nincrmax()\n    Returns an accumulator function which incrementally computes a maximum\n    value.\n","incrmaxabs":"\nincrmaxabs()\n    Returns an accumulator function which incrementally computes a maximum\n    absolute value.\n","incrmcovariance":"\nincrmcovariance( W:integer[, mx:number, my:number] )\n    Returns an accumulator function which incrementally computes a moving\n    unbiased sample covariance.\n","incrmcv":"\nincrmcv( W:integer[, mean:number] )\n    Returns an accumulator function which incrementally computes a moving\n    coefficient of variation (CV).\n","incrmda":"\nincrmda()\n    Returns an accumulator function which incrementally computes the mean\n    directional accuracy (MDA).\n","incrme":"\nincrme()\n    Returns an accumulator function which incrementally computes the mean error\n    (ME).\n","incrmean":"\nincrmean()\n    Returns an accumulator function which incrementally computes an arithmetic\n    mean.\n","incrmeanabs":"\nincrmeanabs()\n    Returns an accumulator function which incrementally computes an arithmetic\n    mean of absolute values.\n","incrmeanabs2":"\nincrmeanabs2()\n    Returns an accumulator function which incrementally computes an arithmetic\n    mean of squared absolute values.\n","incrmeanstdev":"\nincrmeanstdev( [out:Array|TypedArray] )\n    Returns an accumulator function which incrementally computes an arithmetic\n    mean and corrected sample standard deviation.\n","incrmeanvar":"\nincrmeanvar( [out:Array|TypedArray] )\n    Returns an accumulator function which incrementally computes an arithmetic\n    mean and unbiased sample variance.\n","incrmgmean":"\nincrmgmean( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    geometric mean.\n","incrmgrubbs":"\nincrmgrubbs( W:integer[, options:Object] )\n    Returns an accumulator function which incrementally performs a moving\n    Grubbs' test for detecting outliers.\n","incrmhmean":"\nincrmhmean( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    harmonic mean.\n","incrmidrange":"\nincrmidrange()\n    Returns an accumulator function which incrementally computes a mid-range.\n","incrmin":"\nincrmin()\n    Returns an accumulator function which incrementally computes a minimum\n    value.\n","incrminabs":"\nincrminabs()\n    Returns an accumulator function which incrementally computes a minimum\n    absolute value.\n","incrminmax":"\nincrminmax( [out:Array|TypedArray] )\n    Returns an accumulator function which incrementally computes a minimum and\n    maximum.\n","incrminmaxabs":"\nincrminmaxabs( [out:Array|TypedArray] )\n    Returns an accumulator function which incrementally computes a minimum and\n    maximum absolute value.\n","incrmmaape":"\nincrmmaape( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    mean arctangent absolute percentage error (MAAPE).\n","incrmmae":"\nincrmmae( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    mean absolute error (MAE).\n","incrmmape":"\nincrmmape( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    mean absolute percentage error (MAPE).\n","incrmmax":"\nincrmmax( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    maximum value.\n","incrmmaxabs":"\nincrmmaxabs( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    maximum absolute value.\n","incrmmda":"\nincrmmda( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    mean directional accuracy (MDA).\n","incrmme":"\nincrmme( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    mean error (ME).\n","incrmmean":"\nincrmmean( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    arithmetic mean.\n","incrmmeanabs":"\nincrmmeanabs( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    arithmetic mean of absolute values.\n","incrmmeanabs2":"\nincrmmeanabs2( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    arithmetic mean of squared absolute values.\n","incrmmeanstdev":"\nincrmmeanstdev( [out:Array|TypedArray,] W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    arithmetic mean and corrected sample standard deviation.\n","incrmmeanvar":"\nincrmmeanvar( [out:Array|TypedArray,] W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    arithmetic mean and unbiased sample variance.\n","incrmmidrange":"\nincrmmidrange( W:integer )\n    Returns an accumulator function which incrementally computes a moving mid-\n    range.\n","incrmmin":"\nincrmmin( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    minimum value.\n","incrmminabs":"\nincrmminabs( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    minimum absolute value.\n","incrmminmax":"\nincrmminmax( [out:Array|TypedArray,] W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    minimum and maximum.\n","incrmminmaxabs":"\nincrmminmaxabs( [out:Array|TypedArray,] W:integer )\n    Returns an accumulator function which incrementally computes moving minimum\n    and maximum absolute values.\n","incrmmpe":"\nincrmmpe( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    mean percentage error (MPE).\n","incrmmse":"\nincrmmse( W:integer )\n    Returns an accumulator function which incrementally computes a moving mean\n    squared error (MSE).\n","incrmpcorr":"\nincrmpcorr( W:integer[, mx:number, my:number] )\n    Returns an accumulator function which incrementally computes a moving\n    sample Pearson product-moment correlation coefficient.\n","incrmpcorr2":"\nincrmpcorr2( W:integer[, mx:number, my:number] )\n    Returns an accumulator function which incrementally computes a moving\n    squared sample Pearson product-moment correlation coefficient.\n","incrmpcorrdist":"\nincrmpcorrdist( W:integer[, mx:number, my:number] )\n    Returns an accumulator function which incrementally computes a moving\n    sample Pearson product-moment correlation distance.\n","incrmpe":"\nincrmpe()\n    Returns an accumulator function which incrementally computes the mean\n    percentage error (MPE).\n","incrmprod":"\nincrmprod( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    product.\n","incrmrange":"\nincrmrange( W:integer )\n    Returns an accumulator function which incrementally computes a moving range.\n","incrmrmse":"\nincrmrmse( W:integer )\n    Returns an accumulator function which incrementally computes a moving root\n    mean squared error (RMSE).\n","incrmrss":"\nincrmrss( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    residual sum of squares (RSS).\n","incrmse":"\nincrmse()\n    Returns an accumulator function which incrementally computes the mean\n    squared error (MSE).\n","incrmstdev":"\nincrmstdev( W:integer[, mean:number] )\n    Returns an accumulator function which incrementally computes a moving\n    corrected sample standard deviation.\n","incrmsum":"\nincrmsum( W:integer )\n    Returns an accumulator function which incrementally computes a moving sum.\n","incrmsumabs":"\nincrmsumabs( W:integer )\n    Returns an accumulator function which incrementally computes a moving sum of\n    absolute values.\n","incrmsumabs2":"\nincrmsumabs2( W:integer )\n    Returns an accumulator function which incrementally computes a moving sum of\n    squared absolute values.\n","incrmsummary":"\nincrmsummary( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    statistical summary.\n","incrmsumprod":"\nincrmsumprod( W:integer )\n    Returns an accumulator function which incrementally computes a moving sum of\n    products.\n","incrmvariance":"\nincrmvariance( W:integer[, mean:number] )\n    Returns an accumulator function which incrementally computes a moving\n    unbiased sample variance.\n","incrmvmr":"\nincrmvmr( W:integer[, mean:number] )\n    Returns an accumulator function which incrementally computes a moving\n    variance-to-mean (VMR).\n","incrnancount":"\nincrnancount()\n    Returns an accumulator function which incrementally updates a count,\n    ignoring `NaN` values.\n","incrnansum":"\nincrnansum()\n    Returns an accumulator function which incrementally computes a sum, ignoring\n    `NaN` values.\n","incrnansumabs":"\nincrnansumabs()\n    Returns an accumulator function which incrementally computes a sum of\n    absolute values, ignoring NaN values.\n","incrnansumabs2":"\nincrnansumabs2()\n    Returns an accumulator function which incrementally computes a sum of\n    squared absolute values, ignoring NaN values.\n","incrpcorr":"\nincrpcorr( [mx:number, my:number] )\n    Returns an accumulator function which incrementally computes a sample\n    Pearson product-moment correlation coefficient.\n","incrpcorr2":"\nincrpcorr2( [mx:number, my:number] )\n    Returns an accumulator function which incrementally computes the squared\n    sample Pearson product-moment correlation coefficient.\n","incrpcorrdist":"\nincrpcorrdist( [mx:number, my:number] )\n    Returns an accumulator function which incrementally computes a sample\n    Pearson product-moment correlation distance.\n","incrpcorrdistmat":"\nincrpcorrdistmat( out:integer|ndarray[, means:ndarray] )\n    Returns an accumulator function which incrementally computes a sample\n    Pearson product-moment correlation distance matrix.\n","incrpcorrmat":"\nincrpcorrmat( out:integer|ndarray[, means:ndarray] )\n    Returns an accumulator function which incrementally computes a sample\n    Pearson product-moment correlation matrix.\n","incrprod":"\nincrprod()\n    Returns an accumulator function which incrementally computes a product.\n","incrrange":"\nincrrange()\n    Returns an accumulator function which incrementally computes a range.\n","incrrmse":"\nincrrmse()\n    Returns an accumulator function which incrementally computes the root mean\n    squared error (RMSE).\n","incrrss":"\nincrrss()\n    Returns an accumulator function which incrementally computes the residual\n    sum of squares (RSS).\n","incrskewness":"\nincrskewness()\n    Returns an accumulator function which incrementally computes a corrected\n    sample skewness.\n","incrspace":"\nincrspace( start:number, stop:number[, increment:number] )\n    Generates a linearly spaced numeric array using a provided increment.\n","incrstdev":"\nincrstdev( [mean:number] )\n    Returns an accumulator function which incrementally computes a corrected\n    sample standard deviation.\n","incrsum":"\nincrsum()\n    Returns an accumulator function which incrementally computes a sum.\n","incrsumabs":"\nincrsumabs()\n    Returns an accumulator function which incrementally computes a sum of\n    absolute values.\n","incrsumabs2":"\nincrsumabs2()\n    Returns an accumulator function which incrementally computes a sum of\n    squared absolute values.\n","incrsummary":"\nincrsummary()\n    Returns an accumulator function which incrementally computes a statistical\n    summary.\n","incrsumprod":"\nincrsumprod()\n    Returns an accumulator function which incrementally computes a sum of\n    products.\n","incrvariance":"\nincrvariance( [mean:number] )\n    Returns an accumulator function which incrementally computes an unbiased\n    sample variance.\n","incrvmr":"\nincrvmr( [mean:number] )\n    Returns an accumulator function which incrementally computes a variance-to-\n    mean ratio (VMR).\n","incrwmean":"\nincrwmean()\n    Returns an accumulator function which incrementally computes a weighted\n    arithmetic mean.\n","ind2sub":"\nind2sub( shape:ArrayLike, idx:integer[, options:Object] )\n    Converts a linear index to an array of subscripts.\n","ind2sub.assign":"\nind2sub.assign( shape:ArrayLike, idx:integer[, options:Object], \n  out:Array|TypedArray|Object )\n    Converts a linear index to an array of subscripts and assigns results to a\n    provided output array.\n","indexOf":"\nindexOf( arr:ArrayLike, searchElement:any[, fromIndex:integer] )\n    Returns the first index at which a given element can be found.\n","inherit":"\ninherit( ctor:Object|Function, superCtor:Object|Function )\n    Prototypical inheritance by replacing the prototype of one constructor with\n    the prototype of another constructor.\n","inheritedEnumerableProperties":"\ninheritedEnumerableProperties( value:any[, level:integer] )\n    Returns an array of an object's inherited enumerable property names and\n    symbols.\n","inheritedEnumerablePropertySymbols":"\ninheritedEnumerablePropertySymbols( value:any[, level:integer] )\n    Returns an array of an object's inherited enumerable symbol properties.\n","inheritedKeys":"\ninheritedKeys( value:any[, level:integer] )\n    Returns an array of an object's inherited enumerable property names.\n","inheritedNonEnumerableProperties":"\ninheritedNonEnumerableProperties( value:any[, level:integer] )\n    Returns an array of an object's inherited non-enumerable property names and\n    symbols.\n","inheritedNonEnumerablePropertyNames":"\ninheritedNonEnumerablePropertyNames( value:any[, level:integer] )\n    Returns an array of an object's inherited non-enumerable property names.\n","inheritedNonEnumerablePropertySymbols":"\ninheritedNonEnumerablePropertySymbols( value:any[, level:integer] )\n    Returns an array of an object's inherited non-enumerable symbol properties.\n","inheritedProperties":"\ninheritedProperties( value:any[, level:integer] )\n    Returns an array of an object's inherited property names and symbols.\n","inheritedPropertyDescriptor":"\ninheritedPropertyDescriptor( value:any, property:string|symbol[, \n  level:integer] )\n    Returns a property descriptor for an object's inherited property.\n","inheritedPropertyDescriptors":"\ninheritedPropertyDescriptors( value:any[, level:integer] )\n    Returns an object's inherited property descriptors.\n","inheritedPropertyNames":"\ninheritedPropertyNames( value:any[, level:integer] )\n    Returns an array of an object's inherited enumerable and non-enumerable\n    property names.\n","inheritedPropertySymbols":"\ninheritedPropertySymbols( value:any[, level:integer] )\n    Returns an array of an object's inherited symbol properties.\n","inheritedWritableProperties":"\ninheritedWritableProperties( value:any[, level:integer] )\n    Returns an array of an object's inherited writable property names and\n    symbols.\n","inheritedWritablePropertyNames":"\ninheritedWritablePropertyNames( value:any[, level:integer] )\n    Returns an array of an object's inherited writable property names.\n","inheritedWritablePropertySymbols":"\ninheritedWritablePropertySymbols( value:any[, level:integer] )\n    Returns an array of an object's inherited writable symbol properties.\n","inmap":"\ninmap( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n    Invokes a function for each element in a collection and updates the\n    collection in-place.\n","inmapAsync":"\ninmapAsync( collection:Array|TypedArray|Object, [options:Object,] fcn:Function, \n  done:Function )\n    Invokes a function once for each element in a collection and updates a\n    collection in-place.\n","inmapAsync.factory":"\ninmapAsync.factory( [options:Object,] fcn:Function )\n    Returns a function which invokes a function once for each element in a\n    collection and updates a collection in-place.\n","inmapRight":"\ninmapRight( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n    Invokes a function for each element in a collection and updates the\n    collection in-place, iterating from right to left.\n","inmapRightAsync":"\ninmapRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n  fcn:Function, done:Function )\n    Invokes a function once for each element in a collection and updates a\n    collection in-place, iterating from right to left.\n","inmapRightAsync.factory":"\ninmapRightAsync.factory( [options:Object,] fcn:Function )\n    Returns a function which invokes a function once for each element in a\n    collection and updates a collection in-place, iterating from right to left.\n","inspectSinkStream":"\ninspectSinkStream( [options:Object,] clbk:Function )\n    Returns a writable stream for inspecting stream data.\n","inspectSinkStream.factory":"\ninspectSinkStream.factory( [options:Object] )\n    Returns a function for creating writable streams for inspecting stream data.\n","inspectSinkStream.objectMode":"\ninspectSinkStream.objectMode( [options:Object,] clbk:Function )\n    Returns an \"objectMode\" writable stream for inspecting stream data.\n","inspectStream":"\ninspectStream( [options:Object,] clbk:Function )\n    Returns a transform stream for inspecting stream data.\n","inspectStream.factory":"\ninspectStream.factory( [options:Object] )\n    Returns a function for creating transform streams for inspecting stream\n    data.\n","inspectStream.objectMode":"\ninspectStream.objectMode( [options:Object,] clbk:Function )\n    Returns an \"objectMode\" transform stream for inspecting stream data.\n","instanceOf":"\ninstanceOf( value:any, constructor:Function )\n    Tests whether a value has in its prototype chain a specified constructor as\n    a prototype property.\n","INT8_MAX":"\nINT8_MAX\n    Maximum signed 8-bit integer.\n","INT8_MIN":"\nINT8_MIN\n    Minimum signed 8-bit integer.\n","INT8_NUM_BYTES":"\nINT8_NUM_BYTES\n    Size (in bytes) of an 8-bit signed integer.\n","Int8Array":"\nInt8Array()\n    A typed array constructor which returns a typed array representing an array\n    of twos-complement 8-bit signed integers in the platform byte order.\n\nInt8Array( length:integer )\n    Returns a typed array having a specified length.\n\nInt8Array( typedarray:TypedArray )\n    Creates a typed array from another typed array.\n\nInt8Array( obj:Object )\n    Creates a typed array from an array-like object or iterable.\n\nInt8Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a typed array view of an ArrayBuffer.\n","Int8Array.from":"\nInt8Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n    Creates a new typed array from an array-like object or an iterable.\n","Int8Array.of":"\nInt8Array.of( element0:number[, element1:number[, ...elementN:number]] )\n    Creates a new typed array from a variable number of arguments.\n","Int8Array.BYTES_PER_ELEMENT":"\nInt8Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Int8Array.name":"\nInt8Array.name\n    Typed array constructor name.\n","Int8Array.prototype.buffer":"\nInt8Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n","Int8Array.prototype.byteLength":"\nInt8Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n","Int8Array.prototype.byteOffset":"\nInt8Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n","Int8Array.prototype.BYTES_PER_ELEMENT":"\nInt8Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Int8Array.prototype.length":"\nInt8Array.prototype.length\n    Read-only property which returns the number of view elements.\n","Int8Array.prototype.copyWithin":"\nInt8Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","Int8Array.prototype.entries":"\nInt8Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","Int8Array.prototype.every":"\nInt8Array.prototype.every( predicate:Function[, thisArg:Any] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n","Int8Array.prototype.fill":"\nInt8Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n","Int8Array.prototype.filter":"\nInt8Array.prototype.filter( predicate:Function[, thisArg:Any] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n","Int8Array.prototype.find":"\nInt8Array.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n","Int8Array.prototype.findIndex":"\nInt8Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n","Int8Array.prototype.forEach":"\nInt8Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n    Invokes a callback for each array element.\n","Int8Array.prototype.includes":"\nInt8Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a search element.\n","Int8Array.prototype.indexOf":"\nInt8Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n","Int8Array.prototype.join":"\nInt8Array.prototype.join( [separator:string] )\n    Serializes an array by joining all array elements as a string.\n","Int8Array.prototype.keys":"\nInt8Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n","Int8Array.prototype.lastIndexOf":"\nInt8Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n","Int8Array.prototype.map":"\nInt8Array.prototype.map( fcn:Function[, thisArg:Any] )\n    Maps each array element to an element in a new typed array.\n","Int8Array.prototype.reduce":"\nInt8Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n","Int8Array.prototype.reduceRight":"\nInt8Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n","Int8Array.prototype.reverse":"\nInt8Array.prototype.reverse()\n    Reverses an array *in-place*.\n","Int8Array.prototype.set":"\nInt8Array.prototype.set( arr:ArrayLike[, offset:integer] )\n    Sets array elements.\n","Int8Array.prototype.slice":"\nInt8Array.prototype.slice( [begin:integer[, end:integer]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n","Int8Array.prototype.some":"\nInt8Array.prototype.some( predicate:Function[, thisArg:Any] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n","Int8Array.prototype.sort":"\nInt8Array.prototype.sort( [compareFunction:Function] )\n    Sorts an array *in-place*.\n","Int8Array.prototype.subarray":"\nInt8Array.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n","Int8Array.prototype.toLocaleString":"\nInt8Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n    Serializes an array as a locale-specific string.\n","Int8Array.prototype.toString":"\nInt8Array.prototype.toString()\n    Serializes an array as a string.\n","Int8Array.prototype.values":"\nInt8Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n","INT16_MAX":"\nINT16_MAX\n    Maximum signed 16-bit integer.\n","INT16_MIN":"\nINT16_MIN\n    Minimum signed 16-bit integer.\n","INT16_NUM_BYTES":"\nINT16_NUM_BYTES\n    Size (in bytes) of a 16-bit signed integer.\n","Int16Array":"\nInt16Array()\n    A typed array constructor which returns a typed array representing an array\n    of twos-complement 16-bit signed integers in the platform byte order.\n\nInt16Array( length:integer )\n    Returns a typed array having a specified length.\n\nInt16Array( typedarray:TypedArray )\n    Creates a typed array from another typed array.\n\nInt16Array( obj:Object )\n    Creates a typed array from an array-like object or iterable.\n\nInt16Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a typed array view of an ArrayBuffer.\n","Int16Array.from":"\nInt16Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n    Creates a new typed array from an array-like object or an iterable.\n","Int16Array.of":"\nInt16Array.of( element0:number[, element1:number[, ...elementN:number]] )\n    Creates a new typed array from a variable number of arguments.\n","Int16Array.BYTES_PER_ELEMENT":"\nInt16Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Int16Array.name":"\nInt16Array.name\n    Typed array constructor name.\n","Int16Array.prototype.buffer":"\nInt16Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n","Int16Array.prototype.byteLength":"\nInt16Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n","Int16Array.prototype.byteOffset":"\nInt16Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n","Int16Array.prototype.BYTES_PER_ELEMENT":"\nInt16Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Int16Array.prototype.length":"\nInt16Array.prototype.length\n    Read-only property which returns the number of view elements.\n","Int16Array.prototype.copyWithin":"\nInt16Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","Int16Array.prototype.entries":"\nInt16Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","Int16Array.prototype.every":"\nInt16Array.prototype.every( predicate:Function[, thisArg:Any] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n","Int16Array.prototype.fill":"\nInt16Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n","Int16Array.prototype.filter":"\nInt16Array.prototype.filter( predicate:Function[, thisArg:Any] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n","Int16Array.prototype.find":"\nInt16Array.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n","Int16Array.prototype.findIndex":"\nInt16Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n","Int16Array.prototype.forEach":"\nInt16Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n    Invokes a callback for each array element.\n","Int16Array.prototype.includes":"\nInt16Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a search element.\n","Int16Array.prototype.indexOf":"\nInt16Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n","Int16Array.prototype.join":"\nInt16Array.prototype.join( [separator:string] )\n    Serializes an array by joining all array elements as a string.\n","Int16Array.prototype.keys":"\nInt16Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n","Int16Array.prototype.lastIndexOf":"\nInt16Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n","Int16Array.prototype.map":"\nInt16Array.prototype.map( fcn:Function[, thisArg:Any] )\n    Maps each array element to an element in a new typed array.\n","Int16Array.prototype.reduce":"\nInt16Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n","Int16Array.prototype.reduceRight":"\nInt16Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n","Int16Array.prototype.reverse":"\nInt16Array.prototype.reverse()\n    Reverses an array *in-place*.\n","Int16Array.prototype.set":"\nInt16Array.prototype.set( arr:ArrayLike[, offset:integer] )\n    Sets array elements.\n","Int16Array.prototype.slice":"\nInt16Array.prototype.slice( [begin:integer[, end:integer]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n","Int16Array.prototype.some":"\nInt16Array.prototype.some( predicate:Function[, thisArg:Any] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n","Int16Array.prototype.sort":"\nInt16Array.prototype.sort( [compareFunction:Function] )\n    Sorts an array *in-place*.\n","Int16Array.prototype.subarray":"\nInt16Array.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n","Int16Array.prototype.toLocaleString":"\nInt16Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n    Serializes an array as a locale-specific string.\n","Int16Array.prototype.toString":"\nInt16Array.prototype.toString()\n    Serializes an array as a string.\n","Int16Array.prototype.values":"\nInt16Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n","INT32_MAX":"\nINT32_MAX\n    Maximum signed 32-bit integer.\n","INT32_MIN":"\nINT32_MIN\n    Minimum signed 32-bit integer.\n","INT32_NUM_BYTES":"\nINT32_NUM_BYTES\n    Size (in bytes) of a 32-bit signed integer.\n","Int32Array":"\nInt32Array()\n    A typed array constructor which returns a typed array representing an array\n    of twos-complement 32-bit signed integers in the platform byte order.\n\nInt32Array( length:integer )\n    Returns a typed array having a specified length.\n\nInt32Array( typedarray:TypedArray )\n    Creates a typed array from another typed array.\n\nInt32Array( obj:Object )\n    Creates a typed array from an array-like object or iterable.\n\nInt32Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a typed array view of an ArrayBuffer.\n","Int32Array.from":"\nInt32Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n    Creates a new typed array from an array-like object or an iterable.\n","Int32Array.of":"\nInt32Array.of( element0:number[, element1:number[, ...elementN:number]] )\n    Creates a new typed array from a variable number of arguments.\n","Int32Array.BYTES_PER_ELEMENT":"\nInt32Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Int32Array.name":"\nInt32Array.name\n    Typed array constructor name.\n","Int32Array.prototype.buffer":"\nInt32Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n","Int32Array.prototype.byteLength":"\nInt32Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n","Int32Array.prototype.byteOffset":"\nInt32Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n","Int32Array.prototype.BYTES_PER_ELEMENT":"\nInt32Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Int32Array.prototype.length":"\nInt32Array.prototype.length\n    Read-only property which returns the number of view elements.\n","Int32Array.prototype.copyWithin":"\nInt32Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","Int32Array.prototype.entries":"\nInt32Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","Int32Array.prototype.every":"\nInt32Array.prototype.every( predicate:Function[, thisArg:Any] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n","Int32Array.prototype.fill":"\nInt32Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n","Int32Array.prototype.filter":"\nInt32Array.prototype.filter( predicate:Function[, thisArg:Any] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n","Int32Array.prototype.find":"\nInt32Array.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n","Int32Array.prototype.findIndex":"\nInt32Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n","Int32Array.prototype.forEach":"\nInt32Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n    Invokes a callback for each array element.\n","Int32Array.prototype.includes":"\nInt32Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a search element.\n","Int32Array.prototype.indexOf":"\nInt32Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n","Int32Array.prototype.join":"\nInt32Array.prototype.join( [separator:string] )\n    Serializes an array by joining all array elements as a string.\n","Int32Array.prototype.keys":"\nInt32Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n","Int32Array.prototype.lastIndexOf":"\nInt32Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n","Int32Array.prototype.map":"\nInt32Array.prototype.map( fcn:Function[, thisArg:Any] )\n    Maps each array element to an element in a new typed array.\n","Int32Array.prototype.reduce":"\nInt32Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n","Int32Array.prototype.reduceRight":"\nInt32Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n","Int32Array.prototype.reverse":"\nInt32Array.prototype.reverse()\n    Reverses an array *in-place*.\n","Int32Array.prototype.set":"\nInt32Array.prototype.set( arr:ArrayLike[, offset:integer] )\n    Sets array elements.\n","Int32Array.prototype.slice":"\nInt32Array.prototype.slice( [begin:integer[, end:integer]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n","Int32Array.prototype.some":"\nInt32Array.prototype.some( predicate:Function[, thisArg:Any] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n","Int32Array.prototype.sort":"\nInt32Array.prototype.sort( [compareFunction:Function] )\n    Sorts an array *in-place*.\n","Int32Array.prototype.subarray":"\nInt32Array.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n","Int32Array.prototype.toLocaleString":"\nInt32Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n    Serializes an array as a locale-specific string.\n","Int32Array.prototype.toString":"\nInt32Array.prototype.toString()\n    Serializes an array as a string.\n","Int32Array.prototype.values":"\nInt32Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n","IS_BIG_ENDIAN":"\nIS_BIG_ENDIAN\n    Boolean indicating if the environment is big endian.\n","IS_BROWSER":"\nIS_BROWSER\n    Boolean indicating if the runtime is a web browser.\n","IS_DARWIN":"\nIS_DARWIN\n    Boolean indicating if the current process is running on Darwin.\n","IS_DOCKER":"\nIS_DOCKER\n    Boolean indicating if the process is running in a Docker container.\n","IS_ELECTRON":"\nIS_ELECTRON\n    Boolean indicating if the runtime is Electron.\n","IS_ELECTRON_MAIN":"\nIS_ELECTRON_MAIN\n    Boolean indicating if the runtime is the main Electron process.\n","IS_ELECTRON_RENDERER":"\nIS_ELECTRON_RENDERER\n    Boolean indicating if the runtime is the Electron renderer process.\n","IS_LITTLE_ENDIAN":"\nIS_LITTLE_ENDIAN\n    Boolean indicating if the environment is little endian.\n","IS_MOBILE":"\nIS_MOBILE\n    Boolean indicating if the current environment is a mobile device.\n","IS_NODE":"\nIS_NODE\n    Boolean indicating if the runtime is Node.js.\n","IS_TOUCH_DEVICE":"\nIS_TOUCH_DEVICE\n    Boolean indicating if the current environment is a touch device.\n","IS_WEB_WORKER":"\nIS_WEB_WORKER\n    Boolean indicating if the runtime is a web worker.\n","IS_WINDOWS":"\nIS_WINDOWS\n    Boolean indicating if the current process is running on Windows.\n","isAbsoluteHttpURI":"\nisAbsoluteHttpURI( value:any )\n    Tests whether a value is an absolute HTTP(S) URI.\n","isAbsolutePath":"\nisAbsolutePath( value:any )\n    Tests if a value is an absolute path.\n","isAbsolutePath.posix":"\nisAbsolutePath.posix( value:any )\n    Tests if a value is a POSIX absolute path.\n","isAbsolutePath.win32":"\nisAbsolutePath.win32( value:any )\n    Tests if a value is a Windows absolute path.\n","isAbsoluteURI":"\nisAbsoluteURI( value:any )\n    Tests whether a value is an absolute URI.\n","isAccessorArray":"\nisAccessorArray( value:any )\n    Tests if a value is an array-like object supporting the accessor (get/set)\n    protocol.\n","isAccessorProperty":"\nisAccessorProperty( value:any, property:any )\n    Tests if an object's own property has an accessor descriptor.\n","isAccessorPropertyIn":"\nisAccessorPropertyIn( value:any, property:any )\n    Tests if an object's own or inherited property has an accessor descriptor.\n","isAlphagram":"\nisAlphagram( value:any )\n    Tests if a value is an alphagram (i.e., a sequence of characters arranged in\n    alphabetical order).\n","isAlphaNumeric":"\nisAlphaNumeric( str:string )\n    Tests whether a string contains only alphanumeric characters.\n","isAnagram":"\nisAnagram( str:string, value:any )\n    Tests if a value is an anagram.\n","isArguments":"\nisArguments( value:any )\n    Tests if a value is an arguments object.\n","isArray":"\nisArray( value:any )\n    Tests if a value is an array.\n","isArrayArray":"\nisArrayArray( value:any )\n    Tests if a value is an array of arrays.\n","isArrayBuffer":"\nisArrayBuffer( value:any )\n    Tests if a value is an ArrayBuffer.\n","isArrayBufferView":"\nisArrayBufferView( value:any )\n    Tests if a value is a `ArrayBuffer` view.\n","isArrayLength":"\nisArrayLength( value:any )\n    Tests if a value is a valid array length.\n","isArrayLike":"\nisArrayLike( value:any )\n    Tests if a value is array-like.\n","isArrayLikeObject":"\nisArrayLikeObject( value:any )\n    Tests if a value is an array-like object.\n","isArrowFunction":"\nisArrowFunction( value:any )\n    Tests if a value is an arrow function.\n","isASCII":"\nisASCII( str:string )\n    Tests whether a character belongs to the ASCII character set and whether\n    this is true for all characters in a provided string.\n","isBetween":"\nisBetween( value:any, a:any, b:any[, left:string, right:string] )\n    Tests if a value is between two values.\n","isBetweenArray":"\nisBetweenArray( value:any, a:any, b:any[, left:string, right:string] )\n    Tests if a value is an array-like object where every element is between two\n    values.\n","isBigInt":"\nisBigInt( value:any )\n    Tests if a value is a BigInt.\n","isBigInt64Array":"\nisBigInt64Array( value:any )\n    Tests if a value is a BigInt64Array.\n","isBigUint64Array":"\nisBigUint64Array( value:any )\n    Tests if a value is a BigUint64Array.\n","isBinaryString":"\nisBinaryString( value:any )\n    Tests if a value is a binary string.\n","isBlankString":"\nisBlankString( value:any )\n    Tests if a value is a blank string (i.e., an empty string or a string\n    consisting only of whitespace characters).\n","isBoolean":"\nisBoolean( value:any )\n    Tests if a value is a boolean.\n","isBoolean.isPrimitive":"\nisBoolean.isPrimitive( value:any )\n    Tests if a value is a boolean primitive.\n","isBoolean.isObject":"\nisBoolean.isObject( value:any )\n    Tests if a value is a boolean object.\n","isBooleanArray":"\nisBooleanArray( value:any )\n    Tests if a value is an array-like object of booleans.\n","isBooleanArray.primitives":"\nisBooleanArray.primitives( value:any )\n    Tests if a value is an array-like object containing only boolean primitives.\n","isBooleanArray.objects":"\nisBooleanArray.objects( value:any )\n    Tests if a value is an array-like object containing only Boolean objects.\n","isBoxedPrimitive":"\nisBoxedPrimitive( value:any )\n    Tests if a value is a JavaScript boxed primitive.\n","isBuffer":"\nisBuffer( value:any )\n    Tests if a value is a Buffer instance.\n","isCamelcase":"\nisCamelcase( value:any )\n    Tests if a value is a camelcase string.\n","isCapitalized":"\nisCapitalized( value:any )\n    Tests if a value is a string having an uppercase first character.\n","isCentrosymmetricMatrix":"\nisCentrosymmetricMatrix( value:any )\n    Tests if a value is a matrix which is symmetric about its center.\n","isCircular":"\nisCircular( value:any )\n    Tests if an object-like value contains a circular reference.\n","isCircularArray":"\nisCircularArray( value:any )\n    Tests if a value is an array containing a circular reference.\n","isCircularPlainObject":"\nisCircularPlainObject( value:any )\n    Tests if a value is a plain object containing a circular reference.\n","isClass":"\nisClass( value:any )\n    Tests if a value is a class.\n","isCollection":"\nisCollection( value:any )\n    Tests if a value is a collection.\n","isComplex":"\nisComplex( value:any )\n    Tests if a value is a 64-bit or 128-bit complex number.\n","isComplex64":"\nisComplex64( value:any )\n    Tests if a value is a 64-bit complex number.\n","isComplex64Array":"\nisComplex64Array( value:any )\n    Tests if a value is a Complex64Array.\n","isComplex64MatrixLike":"\nisComplex64MatrixLike( value:any )\n    Tests if a value is a 2-dimensional ndarray-like object containing single-\n    precision complex floating-point numbers.\n","isComplex64ndarrayLike":"\nisComplex64ndarrayLike( value:any )\n    Tests if a value is an ndarray-like object containing single-precision\n    complex floating-point numbers.\n","isComplex64VectorLike":"\nisComplex64VectorLike( value:any )\n    Tests if a value is a 1-dimensional ndarray-like object containing single-\n    precision complex floating-point numbers.\n","isComplex128":"\nisComplex128( value:any )\n    Tests if a value is a 128-bit complex number.\n","isComplex128Array":"\nisComplex128Array( value:any )\n    Tests if a value is a Complex128Array.\n","isComplex128MatrixLike":"\nisComplex128MatrixLike( value:any )\n    Tests if a value is a 2-dimensional ndarray-like object containing double-\n    precision complex floating-point numbers.\n","isComplex128ndarrayLike":"\nisComplex128ndarrayLike( value:any )\n    Tests if a value is an ndarray-like object containing double-precision\n    complex floating-point numbers.\n","isComplex128VectorLike":"\nisComplex128VectorLike( value:any )\n    Tests if a value is a 1-dimensional ndarray-like object containing double-\n    precision complex floating-point numbers.\n","isComplexLike":"\nisComplexLike( value:any )\n    Tests if a value is a complex number-like object.\n","isComplexTypedArray":"\nisComplexTypedArray( value:any )\n    Tests if a value is a complex typed array.\n","isComplexTypedArrayLike":"\nisComplexTypedArrayLike( value:any )\n    Tests if a value is complex-typed-array-like.\n","isComposite":"\nisComposite( value:any )\n    Tests if a value is a composite number.\n","isComposite.isPrimitive":"\nisComposite.isPrimitive( value:any )\n    Tests if a value is a number primitive which is a composite number.\n","isComposite.isObject":"\nisComposite.isObject( value:any )\n    Tests if a value is a number object having a value which is a composite\n    number.\n","isConfigurableProperty":"\nisConfigurableProperty( value:any, property:any )\n    Tests if an object's own property is configurable.\n","isConfigurablePropertyIn":"\nisConfigurablePropertyIn( value:any, property:any )\n    Tests if an object's own or inherited property is configurable.\n","isConstantcase":"\nisConstantcase( value:any )\n    Tests if a value is a constantcase string.\n","isCubeNumber":"\nisCubeNumber( value:any )\n    Tests if a value is a cube number.\n","isCubeNumber.isPrimitive":"\nisCubeNumber.isPrimitive( value:any )\n    Tests if a value is a number primitive which is a cube number.\n","isCubeNumber.isObject":"\nisCubeNumber.isObject( value:any )\n    Tests if a value is a number object having a value which is a cube number.\n","isCurrentYear":"\nisCurrentYear( value:any )\n    Tests if a value is the current year.\n","isDataProperty":"\nisDataProperty( value:any, property:any )\n    Tests if an object's own property has a data descriptor.\n","isDataPropertyIn":"\nisDataPropertyIn( value:any, property:any )\n    Tests if an object's own or inherited property has a data descriptor.\n","isDataView":"\nisDataView( value:any )\n    Tests if a value is a DataView.\n","isDateObject":"\nisDateObject( value:any )\n    Tests if a value is a Date object.\n","isDateObjectArray":"\nisDateObjectArray( value:any )\n    Tests if a value is an array-like object containing only Date objects.\n","isDigitString":"\nisDigitString( str:string )\n    Tests whether a string contains only numeric digits.\n","isDomainName":"\nisDomainName( value:any )\n    Tests if a value is a domain name.\n","isDurationString":"\nisDurationString( value:any )\n    Tests if a value is a duration string.\n","isEmailAddress":"\nisEmailAddress( value:any )\n    Tests if a value is an email address.\n","isEmptyArray":"\nisEmptyArray( value:any )\n    Tests if a value is an empty array.\n","isEmptyArrayLikeObject":"\nisEmptyArrayLikeObject( value:any )\n    Tests if a value is an empty array-like object.\n","isEmptyCollection":"\nisEmptyCollection( value:any )\n    Tests if a value is an empty collection.\n","isEmptyObject":"\nisEmptyObject( value:any )\n    Tests if a value is an empty object.\n","isEmptyString":"\nisEmptyString( value:any )\n    Tests if a value is an empty string.\n","isEmptyString.isPrimitive":"\nisEmptyString.isPrimitive( value:any )\n    Tests if a value is an empty string primitive.\n","isEmptyString.isObject":"\nisEmptyString.isObject( value:any )\n    Tests if a value is an empty `String` object.\n","isEnumerableProperty":"\nisEnumerableProperty( value:any, property:any )\n    Tests if an object's own property is enumerable.\n","isEnumerablePropertyIn":"\nisEnumerablePropertyIn( value:any, property:any )\n    Tests if an object's own or inherited property is enumerable.\n","isEqualArray":"\nisEqualArray( v1:any, v2:any )\n    Tests if two arguments are both generic arrays and have equal values.\n","isError":"\nisError( value:any )\n    Tests if a value is an Error object.\n","isEvalError":"\nisEvalError( value:any )\n    Tests if a value is an EvalError object.\n","isEven":"\nisEven( value:any )\n    Tests if a value is an even number.\n","isEven.isPrimitive":"\nisEven.isPrimitive( value:any )\n    Tests if a value is a number primitive that is an even number.\n","isEven.isObject":"\nisEven.isObject( value:any )\n    Tests if a value is a number object that is an even number.\n","isFalsy":"\nisFalsy( value:any )\n    Tests if a value is a value which translates to `false` when evaluated in a\n    boolean context.\n","isFalsyArray":"\nisFalsyArray( value:any )\n    Tests if a value is an array-like object containing only falsy values.\n","isFinite":"\nisFinite( value:any )\n    Tests if a value is a finite number.\n","isFinite.isPrimitive":"\nisFinite.isPrimitive( value:any )\n    Tests if a value is a number primitive having a finite value.\n","isFinite.isObject":"\nisFinite.isObject( value:any )\n    Tests if a value is a number object having a finite value.\n","isFiniteArray":"\nisFiniteArray( value:any )\n    Tests if a value is an array-like object of finite numbers.\n","isFiniteArray.primitives":"\nisFiniteArray.primitives( value:any )\n    Tests if a value is an array-like object containing only primitive finite\n    numbers.\n","isFiniteArray.objects":"\nisFiniteArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having finite values.\n","isFloat32Array":"\nisFloat32Array( value:any )\n    Tests if a value is a Float32Array.\n","isFloat32MatrixLike":"\nisFloat32MatrixLike( value:any )\n    Tests if a value is a 2-dimensional ndarray-like object containing single-\n    precision floating-point numbers.\n","isFloat32ndarrayLike":"\nisFloat32ndarrayLike( value:any )\n    Tests if a value is an ndarray-like object containing single-precision\n    floating-point numbers.\n","isFloat32VectorLike":"\nisFloat32VectorLike( value:any )\n    Tests if a value is a 1-dimensional ndarray-like object containing single-\n    precision floating-point numbers.\n","isFloat64Array":"\nisFloat64Array( value:any )\n    Tests if a value is a Float64Array.\n","isFloat64MatrixLike":"\nisFloat64MatrixLike( value:any )\n    Tests if a value is a 2-dimensional ndarray-like object containing double-\n    precision floating-point numbers.\n","isFloat64ndarrayLike":"\nisFloat64ndarrayLike( value:any )\n    Tests if a value is an ndarray-like object containing double-precision\n    floating-point numbers.\n","isFloat64VectorLike":"\nisFloat64VectorLike( value:any )\n    Tests if a value is a 1-dimensional ndarray-like object containing double-\n    precision floating-point numbers.\n","isFunction":"\nisFunction( value:any )\n    Tests if a value is a function.\n","isFunctionArray":"\nisFunctionArray( value:any )\n    Tests if a value is an array-like object containing only functions.\n","isGeneratorObject":"\nisGeneratorObject( value:any )\n    Tests if a value is a generator object.\n","isGeneratorObjectLike":"\nisGeneratorObjectLike( value:any )\n    Tests if a value is generator object-like.\n","isgzipBuffer":"\nisgzipBuffer( value:any )\n    Tests if a value is a gzip buffer.\n","isHexString":"\nisHexString( str:string )\n    Tests whether a string contains only hexadecimal digits.\n","isInfinite":"\nisInfinite( value:any )\n    Tests if a value is an infinite number.\n","isInfinite.isPrimitive":"\nisInfinite.isPrimitive( value:any )\n    Tests if a value is a number primitive having an infinite value.\n","isInfinite.isObject":"\nisInfinite.isObject( value:any )\n    Tests if a value is a number object having an infinite value.\n","isInheritedProperty":"\nisInheritedProperty( value:any, property:any )\n    Tests if an object has an inherited property.\n","isInt8Array":"\nisInt8Array( value:any )\n    Tests if a value is an Int8Array.\n","isInt16Array":"\nisInt16Array( value:any )\n    Tests if a value is an Int16Array.\n","isInt32Array":"\nisInt32Array( value:any )\n    Tests if a value is an Int32Array.\n","isInteger":"\nisInteger( value:any )\n    Tests if a value is an integer.\n","isInteger.isPrimitive":"\nisInteger.isPrimitive( value:any )\n    Tests if a value is a number primitive having an integer value.\n","isInteger.isObject":"\nisInteger.isObject( value:any )\n    Tests if a value is a number object having an integer value.\n","isIntegerArray":"\nisIntegerArray( value:any )\n    Tests if a value is an array-like object of integer values.\n","isIntegerArray.primitives":"\nisIntegerArray.primitives( value:any )\n    Tests if a value is an array-like object containing only primitive integer\n    values.\n","isIntegerArray.objects":"\nisIntegerArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having integer values.\n","isIterableLike":"\nisIterableLike( value:any )\n    Tests if a value is iterable-like.\n","isIteratorLike":"\nisIteratorLike( value:any )\n    Tests if a value is iterator-like.\n","isJSON":"\nisJSON( value:any )\n    Tests if a value is a parseable JSON string.\n","isKebabcase":"\nisKebabcase( value:any )\n    Tests if a value is a string in kebab case.\n","isLeapYear":"\nisLeapYear( value:any )\n    Tests whether a value corresponds to a leap year in the Gregorian calendar.\n","isLocalhost":"\nisLocalhost( value:any )\n    Tests whether a value is a localhost hostname.\n","isLowercase":"\nisLowercase( value:any )\n    Tests if a value is a lowercase string.\n","isMatrixLike":"\nisMatrixLike( value:any )\n    Tests if a value is a 2-dimensional ndarray-like object.\n","isMethod":"\nisMethod( value:any, property:any )\n    Tests if an object has a specified method name.\n","isMethodIn":"\nisMethodIn( value:any, property:any )\n    Tests if an object has a specified method name, either own or inherited.\n","isMultiSlice":"\nisMultiSlice( value:any )\n    Tests if a value is a MultiSlice object.\n","isNamedTypedTupleLike":"\nisNamedTypedTupleLike( value:any )\n    Tests if a value is named typed tuple-like.\n","isnan":"\nisnan( value:any )\n    Tests if a value is NaN.\n","isnan.isPrimitive":"\nisnan.isPrimitive( value:any )\n    Tests if a value is a NaN number primitive.\n","isnan.isObject":"\nisnan.isObject( value:any )\n    Tests if a value is a number object having a value of NaN.\n","isNaNArray":"\nisNaNArray( value:any )\n    Tests if a value is an array-like object containing only NaN values.\n","isNaNArray.primitives":"\nisNaNArray.primitives( value:any )\n    Tests if a value is an array-like object containing only primitive NaN\n    values.\n","isNaNArray.objects":"\nisNaNArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having NaN values.\n","isNativeFunction":"\nisNativeFunction( value:any )\n    Tests if a value is a native function.\n","isndarrayLike":"\nisndarrayLike( value:any )\n    Tests if a value is ndarray-like.\n","isndarrayLikeWithDataType":"\nisndarrayLikeWithDataType( value:any, dtype:any )\n    Tests if a value is an ndarray-like object having a specified data type.\n","isNegativeFinite":"\nisNegativeFinite( value:any )\n    Tests if a value is a finite negative number.\n","isNegativeFinite.isPrimitive":"\nisNegativeFinite.isPrimitive( value:any )\n    Tests if a value is a number primitive having a finite negative value.\n","isNegativeFinite.isObject":"\nisNegativeFinite.isObject( value:any )\n    Tests if a value is a number object having a finite negative value.\n","isNegativeInteger":"\nisNegativeInteger( value:any )\n    Tests if a value is a negative integer.\n","isNegativeInteger.isPrimitive":"\nisNegativeInteger.isPrimitive( value:any )\n    Tests if a value is a number primitive having a negative integer value.\n","isNegativeInteger.isObject":"\nisNegativeInteger.isObject( value:any )\n    Tests if a value is a number object having a negative integer value.\n","isNegativeIntegerArray":"\nisNegativeIntegerArray( value:any )\n    Tests if a value is an array-like object containing only negative integers.\n","isNegativeIntegerArray.primitives":"\nisNegativeIntegerArray.primitives( value:any )\n    Tests if a value is an array-like object containing only negative primitive\n    integer values.\n","isNegativeIntegerArray.objects":"\nisNegativeIntegerArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having negative integer values.\n","isNegativeNumber":"\nisNegativeNumber( value:any )\n    Tests if a value is a negative number.\n","isNegativeNumber.isPrimitive":"\nisNegativeNumber.isPrimitive( value:any )\n    Tests if a value is a number primitive having a negative value.\n","isNegativeNumber.isObject":"\nisNegativeNumber.isObject( value:any )\n    Tests if a value is a number object having a negative value.\n","isNegativeNumberArray":"\nisNegativeNumberArray( value:any )\n    Tests if a value is an array-like object containing only negative numbers.\n","isNegativeNumberArray.primitives":"\nisNegativeNumberArray.primitives( value:any )\n    Tests if a value is an array-like object containing only primitive negative\n    numbers.\n","isNegativeNumberArray.objects":"\nisNegativeNumberArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having negative number values.\n","isNegativeZero":"\nisNegativeZero( value:any )\n    Tests if a value is negative zero.\n","isNegativeZero.isPrimitive":"\nisNegativeZero.isPrimitive( value:any )\n    Tests if a value is a number primitive equal to negative zero.\n","isNegativeZero.isObject":"\nisNegativeZero.isObject( value:any )\n    Tests if a value is a number object having a value equal to negative zero.\n","isNodeBuiltin":"\nisNodeBuiltin( str:string )\n    Tests whether a string matches a Node.js built-in module name.\n","isNodeDuplexStreamLike":"\nisNodeDuplexStreamLike( value:any )\n    Tests if a value is Node duplex stream-like.\n","isNodeReadableStreamLike":"\nisNodeReadableStreamLike( value:any )\n    Tests if a value is Node readable stream-like.\n","isNodeREPL":"\nisNodeREPL()\n    Returns a boolean indicating if running in a Node.js REPL environment.\n","isNodeStreamLike":"\nisNodeStreamLike( value:any )\n    Tests if a value is Node stream-like.\n","isNodeTransformStreamLike":"\nisNodeTransformStreamLike( value:any )\n    Tests if a value is Node transform stream-like.\n","isNodeWritableStreamLike":"\nisNodeWritableStreamLike( value:any )\n    Tests if a value is Node writable stream-like.\n","isNonConfigurableProperty":"\nisNonConfigurableProperty( value:any, property:any )\n    Tests if an object's own property is non-configurable.\n","isNonConfigurablePropertyIn":"\nisNonConfigurablePropertyIn( value:any, property:any )\n    Tests if an object's own or inherited property is non-configurable.\n","isNonEnumerableProperty":"\nisNonEnumerableProperty( value:any, property:any )\n    Tests if an object's own property is non-enumerable.\n","isNonEnumerablePropertyIn":"\nisNonEnumerablePropertyIn( value:any, property:any )\n    Tests if an object's own or inherited property is non-enumerable.\n","isNonNegativeFinite":"\nisNonNegativeFinite( value:any )\n    Tests if a value is a nonnegative finite number.\n","isNonNegativeFinite.isPrimitive":"\nisNonNegativeFinite.isPrimitive( value:any )\n    Tests if a value is a number primitive having a nonnegative finite value.\n","isNonNegativeFinite.isObject":"\nisNonNegativeFinite.isObject( value:any )\n    Tests if a value is a number object having a nonnegative finite value.\n","isNonNegativeInteger":"\nisNonNegativeInteger( value:any )\n    Tests if a value is a nonnegative integer.\n","isNonNegativeInteger.isPrimitive":"\nisNonNegativeInteger.isPrimitive( value:any )\n    Tests if a value is a number primitive having a nonnegative integer value.\n","isNonNegativeInteger.isObject":"\nisNonNegativeInteger.isObject( value:any )\n    Tests if a value is a number object having a nonnegative integer value.\n","isNonNegativeIntegerArray":"\nisNonNegativeIntegerArray( value:any )\n    Tests if a value is an array-like object containing only nonnegative\n    integers.\n","isNonNegativeIntegerArray.primitives":"\nisNonNegativeIntegerArray.primitives( value:any )\n    Tests if a value is an array-like object containing only nonnegative\n    primitive integer values.\n","isNonNegativeIntegerArray.objects":"\nisNonNegativeIntegerArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having nonnegative integer values.\n","isNonNegativeNumber":"\nisNonNegativeNumber( value:any )\n    Tests if a value is a nonnegative number.\n","isNonNegativeNumber.isPrimitive":"\nisNonNegativeNumber.isPrimitive( value:any )\n    Tests if a value is a number primitive having a nonnegative value.\n","isNonNegativeNumber.isObject":"\nisNonNegativeNumber.isObject( value:any )\n    Tests if a value is a number object having a nonnegative value.\n","isNonNegativeNumberArray":"\nisNonNegativeNumberArray( value:any )\n    Tests if a value is an array-like object containing only nonnegative\n    numbers.\n","isNonNegativeNumberArray.primitives":"\nisNonNegativeNumberArray.primitives( value:any )\n    Tests if a value is an array-like object containing only primitive\n    nonnegative numbers.\n","isNonNegativeNumberArray.objects":"\nisNonNegativeNumberArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having nonnegative number values.\n","isNonPositiveFinite":"\nisNonPositiveFinite( value:any )\n    Tests if a value is a nonpositive finite number.\n","isNonPositiveFinite.isPrimitive":"\nisNonPositiveFinite.isPrimitive( value:any )\n    Tests if a value is a number primitive having a nonpositive finite value.\n","isNonPositiveFinite.isObject":"\nisNonPositiveFinite.isObject( value:any )\n    Tests if a value is a number object having a nonpositive finite value.\n","isNonPositiveInteger":"\nisNonPositiveInteger( value:any )\n    Tests if a value is a nonpositive integer.\n","isNonPositiveInteger.isPrimitive":"\nisNonPositiveInteger.isPrimitive( value:any )\n    Tests if a value is a number primitive having a nonpositive integer value.\n","isNonPositiveInteger.isObject":"\nisNonPositiveInteger.isObject( value:any )\n    Tests if a value is a number object having a nonpositive integer value.\n","isNonPositiveIntegerArray":"\nisNonPositiveIntegerArray( value:any )\n    Tests if a value is an array-like object containing only nonpositive\n    integers.\n","isNonPositiveIntegerArray.primitives":"\nisNonPositiveIntegerArray.primitives( value:any )\n    Tests if a value is an array-like object containing only nonpositive\n    primitive integer values.\n","isNonPositiveIntegerArray.objects":"\nisNonPositiveIntegerArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having nonpositive integer values.\n","isNonPositiveNumber":"\nisNonPositiveNumber( value:any )\n    Tests if a value is a nonpositive number.\n","isNonPositiveNumber.isPrimitive":"\nisNonPositiveNumber.isPrimitive( value:any )\n    Tests if a value is a number primitive having a nonpositive value.\n","isNonPositiveNumber.isObject":"\nisNonPositiveNumber.isObject( value:any )\n    Tests if a value is a number object having a nonpositive value.\n","isNonPositiveNumberArray":"\nisNonPositiveNumberArray( value:any )\n    Tests if a value is an array-like object containing only nonpositive\n    numbers.\n","isNonPositiveNumberArray.primitives":"\nisNonPositiveNumberArray.primitives( value:any )\n    Tests if a value is an array-like object containing only primitive\n    nonpositive numbers.\n","isNonPositiveNumberArray.objects":"\nisNonPositiveNumberArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having nonpositive number values.\n","isNonSymmetricMatrix":"\nisNonSymmetricMatrix( value:any )\n    Tests if a value is a non-symmetric matrix.\n","isNull":"\nisNull( value:any )\n    Tests if a value is null.\n","isNullArray":"\nisNullArray( value:any )\n    Tests if a value is an array-like object containing only null values.\n","isNumber":"\nisNumber( value:any )\n    Tests if a value is a number.\n","isNumber.isPrimitive":"\nisNumber.isPrimitive( value:any )\n    Tests if a value is a number primitive.\n","isNumber.isObject":"\nisNumber.isObject( value:any )\n    Tests if a value is a `Number` object.\n","isNumberArray":"\nisNumberArray( value:any )\n    Tests if a value is an array-like object containing only numbers.\n","isNumberArray.primitives":"\nisNumberArray.primitives( value:any )\n    Tests if a value is an array-like object containing only number primitives.\n","isNumberArray.objects":"\nisNumberArray.objects( value:any )\n    Tests if a value is an array-like object containing only `Number` objects.\n","isNumericArray":"\nisNumericArray( value:any )\n    Tests if a value is a numeric array.\n","isObject":"\nisObject( value:any )\n    Tests if a value is an object; e.g., `{}`.\n","isObjectArray":"\nisObjectArray( value:any )\n    Tests if a value is an array-like object containing only objects.\n","isObjectLike":"\nisObjectLike( value:any )\n    Tests if a value is object-like.\n","isOdd":"\nisOdd( value:any )\n    Tests if a value is an odd number.\n","isOdd.isPrimitive":"\nisOdd.isPrimitive( value:any )\n    Tests if a value is a number primitive that is an odd number.\n","isOdd.isObject":"\nisOdd.isObject( value:any )\n    Tests if a value is a number object that has an odd number value.\n","isoWeeksInYear":"\nisoWeeksInYear( [year:integer] )\n    Returns the number of ISO weeks in a year according to the Gregorian\n    calendar.\n","isPascalcase":"\nisPascalcase( value:any )\n    Tests if a value is a string in Pascal case.\n","isPersymmetricMatrix":"\nisPersymmetricMatrix( value:any )\n    Tests if a value is a square matrix which is symmetric about its\n    antidiagonal.\n","isPlainObject":"\nisPlainObject( value:any )\n    Tests if a value is a plain object.\n","isPlainObjectArray":"\nisPlainObjectArray( value:any )\n    Tests if a value is an array-like object containing only plain objects.\n","isPositiveFinite":"\nisPositiveFinite( value:any )\n    Tests if a value is a positive finite number.\n","isPositiveFinite.isPrimitive":"\nisPositiveFinite.isPrimitive( value:any )\n    Tests if a value is a number primitive having a positive finite value.\n","isPositiveFinite.isObject":"\nisPositiveFinite.isObject( value:any )\n    Tests if a value is a number object having a positive finite value.\n","isPositiveInteger":"\nisPositiveInteger( value:any )\n    Tests if a value is a positive integer.\n","isPositiveInteger.isPrimitive":"\nisPositiveInteger.isPrimitive( value:any )\n    Tests if a value is a number primitive having a positive integer value.\n","isPositiveInteger.isObject":"\nisPositiveInteger.isObject( value:any )\n    Tests if a value is a number object having a positive integer value.\n","isPositiveIntegerArray":"\nisPositiveIntegerArray( value:any )\n    Tests if a value is an array-like object containing only positive integers.\n","isPositiveIntegerArray.primitives":"\nisPositiveIntegerArray.primitives( value:any )\n    Tests if a value is an array-like object containing only positive primitive\n    integer values.\n","isPositiveIntegerArray.objects":"\nisPositiveIntegerArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having positive integer values.\n","isPositiveNumber":"\nisPositiveNumber( value:any )\n    Tests if a value is a positive number.\n","isPositiveNumber.isPrimitive":"\nisPositiveNumber.isPrimitive( value:any )\n    Tests if a value is a number primitive having a positive value.\n","isPositiveNumber.isObject":"\nisPositiveNumber.isObject( value:any )\n    Tests if a value is a number object having a positive value.\n","isPositiveNumberArray":"\nisPositiveNumberArray( value:any )\n    Tests if a value is an array-like object containing only positive numbers.\n","isPositiveNumberArray.primitives":"\nisPositiveNumberArray.primitives( value:any )\n    Tests if a value is an array-like object containing only positive primitive\n    number values.\n","isPositiveNumberArray.objects":"\nisPositiveNumberArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having positive values.\n","isPositiveZero":"\nisPositiveZero( value:any )\n    Tests if a value is positive zero.\n","isPositiveZero.isPrimitive":"\nisPositiveZero.isPrimitive( value:any )\n    Tests if a value is a number primitive equal to positive zero.\n","isPositiveZero.isObject":"\nisPositiveZero.isObject( value:any )\n    Tests if a value is a number object having a value equal to positive zero.\n","isPrime":"\nisPrime( value:any )\n    Tests if a value is a prime number.\n","isPrime.isPrimitive":"\nisPrime.isPrimitive( value:any )\n    Tests if a value is a number primitive which is a prime number.\n","isPrime.isObject":"\nisPrime.isObject( value:any )\n    Tests if a value is a number object having a value which is a prime number.\n","isPrimitive":"\nisPrimitive( value:any )\n    Tests if a value is a JavaScript primitive.\n","isPrimitiveArray":"\nisPrimitiveArray( value:any )\n    Tests if a value is an array-like object containing only JavaScript\n    primitives.\n","isPRNGLike":"\nisPRNGLike( value:any )\n    Tests if a value is PRNG-like.\n","isProbability":"\nisProbability( value:any )\n    Tests if a value is a probability.\n","isProbability.isPrimitive":"\nisProbability.isPrimitive( value:any )\n    Tests if a value is a number primitive which is a probability.\n","isProbability.isObject":"\nisProbability.isObject( value:any )\n    Tests if a value is a number object having a value which is a probability.\n","isProbabilityArray":"\nisProbabilityArray( value:any )\n    Tests if a value is an array-like object containing only probabilities.\n","isProbabilityArray.primitives":"\nisProbabilityArray.primitives( value:any )\n    Tests if a value is an array-like object containing only primitive\n    probabilities.\n","isProbabilityArray.objects":"\nisProbabilityArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having probability values.\n","isPropertyKey":"\nisPropertyKey( value:any )\n    Tests whether a value is a property key.\n","isPrototypeOf":"\nisPrototypeOf( value:any, proto:Object|Function )\n    Tests if an object's prototype chain contains a provided prototype.\n","isRaggedNestedArray":"\nisRaggedNestedArray( value:any )\n    Tests if a value is a ragged nested array. \n","isRangeError":"\nisRangeError( value:any )\n    Tests if a value is a RangeError object.\n","isReadableProperty":"\nisReadableProperty( value:any, property:any )\n    Tests if an object's own property is readable.\n","isReadablePropertyIn":"\nisReadablePropertyIn( value:any, property:any )\n    Tests if an object's own or inherited property is readable.\n","isReadOnlyProperty":"\nisReadOnlyProperty( value:any, property:any )\n    Tests if an object's own property is read-only.\n","isReadOnlyPropertyIn":"\nisReadOnlyPropertyIn( value:any, property:any )\n    Tests if an object's own or inherited property is read-only.\n","isReadWriteProperty":"\nisReadWriteProperty( value:any, property:any )\n    Tests if an object's own property is readable and writable.\n","isReadWritePropertyIn":"\nisReadWritePropertyIn( value:any, property:any )\n    Tests if an object's own or inherited property is readable and writable.\n","isReferenceError":"\nisReferenceError( value:any )\n    Tests if a value is a ReferenceError object.\n","isRegExp":"\nisRegExp( value:any )\n    Tests if a value is a regular expression.\n","isRegExpString":"\nisRegExpString( value:any )\n    Tests if a value is a regular expression string.\n","isRelativePath":"\nisRelativePath( value:any )\n    Tests if a value is a relative path.\n","isRelativePath.posix":"\nisRelativePath.posix( value:any )\n    Tests if a value is a POSIX relative path.\n","isRelativePath.win32":"\nisRelativePath.win32( value:any )\n    Tests if a value is a Windows relative path.\n","isRelativeURI":"\nisRelativeURI( value:any )\n    Tests whether a value is a relative URI.\n","isSafeInteger":"\nisSafeInteger( value:any )\n    Tests if a value is a safe integer.\n","isSafeInteger.isPrimitive":"\nisSafeInteger.isPrimitive( value:any )\n    Tests if a value is a number primitive having a safe integer value.\n","isSafeInteger.isObject":"\nisSafeInteger.isObject( value:any )\n    Tests if a value is a `Number` object having a safe integer value.\n","isSafeIntegerArray":"\nisSafeIntegerArray( value:any )\n    Tests if a value is an array-like object containing only safe integers.\n","isSafeIntegerArray.primitives":"\nisSafeIntegerArray.primitives( value:any )\n    Tests if a value is an array-like object containing only primitive safe\n    integer values.\n","isSafeIntegerArray.objects":"\nisSafeIntegerArray.objects( value:any )\n    Tests if a value is an array-like object containing only `Number` objects\n    having safe integer values.\n","isSameArray":"\nisSameArray( v1:any, v2:any )\n    Tests if two arguments are both generic arrays and have the same values.\n","isSameArrayLike":"\nisSameArrayLike( v1:any, v2:any )\n    Tests if two arguments are both array-like and have the same values.\n","isSameComplex64":"\nisSameComplex64( v1:any, v2:any )\n    Tests if two arguments are both single-precision complex floating-point\n    numbers and have the same value.\n","isSameComplex64Array":"\nisSameComplex64Array( v1:any, v2:any )\n    Tests if two arguments are both Complex64Arrays and have the same values.\n","isSameComplex128":"\nisSameComplex128( v1:any, v2:any )\n    Tests if two arguments are both double-precision complex floating-point\n    numbers and have the same value.\n","isSameComplex128Array":"\nisSameComplex128Array( v1:any, v2:any )\n    Tests if two arguments are both Complex128Arrays and have the same values.\n","isSameDateObject":"\nisSameDateObject( d1, d2 )\n    Tests if two values are both Date objects corresponding \n    to the same date and time.\n","isSameFloat32Array":"\nisSameFloat32Array( v1:any, v2:any )\n    Tests if two arguments are both Float32Arrays and have the same values.\n","isSameFloat64Array":"\nisSameFloat64Array( v1:any, v2:any )\n    Tests if two arguments are both Float64Arrays and have the same values.\n","isSameNativeClass":"\nisSameNativeClass( a:any, b:any )\n    Tests if two arguments have the same native class.\n","isSameType":"\nisSameType( a:any, b:any )\n    Tests if two arguments have the same type.\n","isSameValue":"\nisSameValue( a:any, b:any )\n    Tests if two arguments are the same value.\n","isSameValueZero":"\nisSameValueZero( a:any, b:any )\n    Tests if two arguments are the same value.\n","isSemVer":"\nisSemVer( value:any )\n    Tests if a value is a semantic version string.\n","isSharedArrayBuffer":"\nisSharedArrayBuffer( value:any )\n    Tests if a value is a SharedArrayBuffer.\n","isSkewCentrosymmetricMatrix":"\nisSkewCentrosymmetricMatrix( value:any )\n    Tests if a value is a skew-centrosymmetric matrix.\n","isSkewPersymmetricMatrix":"\nisSkewPersymmetricMatrix( value:any )\n    Tests if a value is a skew-persymmetric matrix.\n","isSkewSymmetricMatrix":"\nisSkewSymmetricMatrix( value:any )\n    Tests if a value is a skew-symmetric (or antisymmetric) matrix.\n","isSlice":"\nisSlice( value:any )\n    Tests if a value is a Slice object.\n","isSnakecase":"\nisSnakecase( value:any )\n    Tests if a value is a string in snake case.\n","isSquareMatrix":"\nisSquareMatrix( value:any )\n    Tests if a value is a 2-dimensional ndarray-like object having equal\n    dimensions.\n","isSquareNumber":"\nisSquareNumber( value:any )\n    Tests if a value is a square number.\n","isSquareNumber.isPrimitive":"\nisSquareNumber.isPrimitive( value:any )\n    Tests if a value is a number primitive which is a square number.\n","isSquareNumber.isObject":"\nisSquareNumber.isObject( value:any )\n    Tests if a value is a number object having a value which is a square number.\n","isSquareTriangularNumber":"\nisSquareTriangularNumber( value:any )\n    Tests if a value is a square triangular number.\n","isSquareTriangularNumber.isPrimitive":"\nisSquareTriangularNumber.isPrimitive( value:any )\n    Tests if a value is a number primitive which is a square triangular number.\n","isSquareTriangularNumber.isObject":"\nisSquareTriangularNumber.isObject( value:any )\n    Tests if a value is a number object having a value which is a square\n    triangular number.\n","isStartcase":"\nisStartcase( value:any )\n    Tests if a value is a startcase string.\n","isStrictEqual":"\nisStrictEqual( a:any, b:any )\n    Tests if two arguments are strictly equal.\n","isString":"\nisString( value:any )\n    Tests if a value is a string.\n","isString.isPrimitive":"\nisString.isPrimitive( value:any )\n    Tests if a value is a string primitive.\n","isString.isObject":"\nisString.isObject( value:any )\n    Tests if a value is a `String` object.\n","isStringArray":"\nisStringArray( value:any )\n    Tests if a value is an array of strings.\n","isStringArray.primitives":"\nisStringArray.primitives( value:any )\n    Tests if a value is an array containing only string primitives.\n","isStringArray.objects":"\nisStringArray.objects( value:any )\n    Tests if a value is an array containing only `String` objects.\n","isSymbol":"\nisSymbol( value:any )\n    Tests if a value is a symbol.\n","isSymbolArray":"\nisSymbolArray( value:any )\n    Tests if a value is an array-like object containing only symbols.\n","isSymbolArray.primitives":"\nisSymbolArray.primitives( value:any )\n    Tests if a value is an array-like object containing only `symbol`\n    primitives.\n","isSymbolArray.objects":"\nisSymbolArray.objects( value:any )\n    Tests if a value is an array-like object containing only `Symbol`\n    objects.\n","isSymmetricMatrix":"\nisSymmetricMatrix( value:any )\n    Tests if a value is a square matrix which equals its transpose.\n","isSyntaxError":"\nisSyntaxError( value:any )\n    Tests if a value is a SyntaxError object.\n","isTriangularNumber":"\nisTriangularNumber( value:any )\n    Tests if a value is a triangular number.\n","isTriangularNumber.isPrimitive":"\nisTriangularNumber.isPrimitive( value:any )\n    Tests if a value is a number primitive which is a triangular number.\n","isTriangularNumber.isObject":"\nisTriangularNumber.isObject( value:any )\n    Tests if a value is a number object having a value which is a triangular\n    number.\n","isTruthy":"\nisTruthy( value:any )\n    Tests if a value is a value which translates to `true` when evaluated in a\n    boolean context.\n","isTruthyArray":"\nisTruthyArray( value:any )\n    Tests if a value is an array-like object containing only truthy values.\n","isTypedArray":"\nisTypedArray( value:any )\n    Tests if a value is a typed array.\n","isTypedArrayLength":"\nisTypedArrayLength( value:any )\n    Tests if a value is a valid typed array length.\n","isTypedArrayLike":"\nisTypedArrayLike( value:any )\n    Tests if a value is typed-array-like.\n","isTypeError":"\nisTypeError( value:any )\n    Tests if a value is a TypeError object.\n","isUint8Array":"\nisUint8Array( value:any )\n    Tests if a value is a Uint8Array.\n","isUint8ClampedArray":"\nisUint8ClampedArray( value:any )\n    Tests if a value is a Uint8ClampedArray.\n","isUint16Array":"\nisUint16Array( value:any )\n    Tests if a value is a Uint16Array.\n","isUint32Array":"\nisUint32Array( value:any )\n    Tests if a value is a Uint32Array.\n","isUNCPath":"\nisUNCPath( value:any )\n    Tests if a value is a UNC path.\n","isUndefined":"\nisUndefined( value:any )\n    Tests if a value is undefined.\n","isUndefinedOrNull":"\nisUndefinedOrNull( value:any )\n    Tests if a value is undefined or null.\n","isUnityProbabilityArray":"\nisUnityProbabilityArray( value:any )\n    Tests if a value is an array of probabilities that sum to one.\n","isUppercase":"\nisUppercase( value:any )\n    Tests if a value is an uppercase string.\n","isURI":"\nisURI( value:any )\n    Tests if a value is a URI.\n","isURIError":"\nisURIError( value:any )\n    Tests if a value is a URIError object.\n","isVectorLike":"\nisVectorLike( value:any )\n    Tests if a value is a 1-dimensional ndarray-like object.\n","isWebAssemblyMemory":"\nisWebAssemblyMemory( value:any )\n    Tests if a value is a WebAssembly memory instance.\n","isWellFormedString":"\nisWellFormedString( str:any )\n    Tests if a string is well-formed.\n","isWellFormedString.isPrimitive":"\nisWellFormedString.isPrimitive( str:any )\n    Tests if a string is a well-formed string primitive.\n","isWellFormedString.isObject":"\nisWellFormedString.isObject( str:any )\n    Tests if a string is a well-formed string object.\n","isWhitespace":"\nisWhitespace( str:string )\n    Tests whether a string contains only white space characters.\n","isWritableProperty":"\nisWritableProperty( value:any, property:any )\n    Tests if an object's own property is writable.\n","isWritablePropertyIn":"\nisWritablePropertyIn( value:any, property:any )\n    Tests if an object's own or inherited property is writable.\n","isWriteOnlyProperty":"\nisWriteOnlyProperty( value:any, property:any )\n    Tests if an object's own property is write-only.\n","isWriteOnlyPropertyIn":"\nisWriteOnlyPropertyIn( value:any, property:any )\n    Tests if an object's own or inherited property is write-only.\n","iterAbs":"\niterAbs( iterator:Object )\n    Returns an iterator which iteratively computes the absolute value.\n","iterAbs2":"\niterAbs2( iterator:Object )\n    Returns an iterator which iteratively computes the squared absolute value.\n","iterAcos":"\niterAcos( iterator:Object )\n    Returns an iterator which iteratively computes the arccosine.\n","iterAcosh":"\niterAcosh( iterator:Object )\n    Returns an iterator which iteratively computes the hyperbolic arccosine.\n","iterAcot":"\niterAcot( iterator:Object )\n    Returns an iterator which iteratively computes the inverse cotangent.\n","iterAcoth":"\niterAcoth( iterator:Object )\n    Returns an iterator which iteratively computes the inverse hyperbolic\n    cotangent.\n","iterAcovercos":"\niterAcovercos( iterator:Object )\n    Returns an iterator which iteratively computes the inverse coversed cosine.\n","iterAcoversin":"\niterAcoversin( iterator:Object )\n    Returns an iterator which iteratively computes the inverse coversed sine.\n","iterAdd":"\niterAdd( iter0:Object, ...iterator:Object )\n    Returns an iterator which performs element-wise addition of two or more\n    iterators.\n","iterAdvance":"\niterAdvance( iterator:Object[, n:integer] )\n    Advances an entire iterator.\n","iterAhavercos":"\niterAhavercos( iterator:Object )\n    Returns an iterator which iteratively computes the inverse half-value versed\n    cosine.\n","iterAhaversin":"\niterAhaversin( iterator:Object )\n    Returns an iterator which iteratively computes the inverse half-value versed\n    sine.\n","iterAny":"\niterAny( iterator:Object )\n    Tests whether at least one iterated value is truthy.\n","iterAnyBy":"\niterAnyBy( iterator:Object, predicate:Function[, thisArg:any ] )\n    Tests whether at least one iterated value passes a test implemented by a\n    predicate function.\n","iterAsin":"\niterAsin( iterator:Object )\n    Returns an iterator which iteratively computes the arcsine.\n","iterAsinh":"\niterAsinh( iterator:Object )\n    Returns an iterator which iteratively computes the hyperbolic arcsine.\n","iterAtan":"\niterAtan( iterator:Object )\n    Returns an iterator which iteratively computes the arctangent.\n","iterAtan2":"\niterAtan2( y:Object|number, x:Object|number )\n    Returns an iterator which iteratively computes the angle in the plane (in\n    radians) between the positive x-axis and the ray from (0,0) to the point\n    (x,y).\n","iterAtanh":"\niterAtanh( iterator:Object )\n    Returns an iterator which iteratively computes the hyperbolic arctangent.\n","iterator2array":"\niterator2array( iterator:Object[, out:ArrayLikeObject][, mapFcn:Function[, \n  thisArg:any]] )\n    Creates (or fills) an array from an iterator.\n","iterator2arrayview":"\niterator2arrayview( iterator:Object, dest:ArrayLikeObject[, begin:integer[, \n  end:integer]][, mapFcn:Function[, thisArg:any]] )\n    Fills an array-like object view with values returned from an iterator.\n","iterator2arrayviewRight":"\niterator2arrayviewRight( iterator:Object, dest:ArrayLikeObject[, \n  begin:integer[, end:integer]][, mapFcn:Function[, thisArg:any]] )\n    Fills an array-like object view from right to left with values returned from\n    an iterator.\n","iteratorStream":"\niteratorStream( iterator:Object[, options:Object] )\n    Creates a readable stream from an iterator.\n","iteratorStream.factory":"\niteratorStream.factory( [options:Object] )\n    Returns a function for creating readable streams from iterators.\n","iteratorStream.objectMode":"\niteratorStream.objectMode( iterator:Object[, options:Object] )\n    Returns an \"objectMode\" readable stream from an iterator.\n","IteratorSymbol":"\nIteratorSymbol\n    Iterator symbol.\n","iterAvercos":"\niterAvercos( iterator:Object )\n    Returns an iterator which iteratively computes the inverse versed cosine.\n","iterAversin":"\niterAversin( iterator:Object )\n    Returns an iterator which iteratively computes the inverse versed sine.\n","iterawgn":"\niterawgn( iterator:Object, sigma:number[, options:Object] )\n    Returns an iterator which introduces additive white Gaussian noise (AWGN)\n    with standard deviation `sigma`.\n","iterawln":"\niterawln( iterator:Object, sigma:number[, options:Object] )\n    Returns an iterator which introduces additive white Laplacian noise (AWLN)\n    with standard deviation `sigma`.\n","iterawun":"\niterawun( iterator:Object, sigma:number[, options:Object] )\n    Returns an iterator which introduces additive white uniform noise (AWUN)\n    with standard deviation `sigma`.\n","iterBartlettHannPulse":"\niterBartlettHannPulse( [options:Object] )\n    Returns an iterator which generates a Bartlett-Hann pulse waveform.\n","iterBartlettPulse":"\niterBartlettPulse( [options:Object] )\n    Returns an iterator which generates a Bartlett pulse waveform.\n","iterBesselj0":"\niterBesselj0( iterator:Object )\n    Returns an iterator which iteratively evaluates the Bessel function of the\n    first kind of order zero.\n","iterBesselj1":"\niterBesselj1( iterator:Object )\n    Returns an iterator which iteratively evaluates the Bessel function of the\n    first kind of order one.\n","iterBessely0":"\niterBessely0( iterator:Object )\n    Returns an iterator which iteratively evaluates the Bessel function of the\n    second kind of order zero.\n","iterBessely1":"\niterBessely1( iterator:Object )\n    Returns an iterator which iteratively evaluates the Bessel function of the\n    second kind of order one.\n","iterBeta":"\niterBeta( x:Object|number, y:Object|number )\n    Returns an iterator which iteratively evaluates the beta function.\n","iterBetaln":"\niterBetaln( x:Object|number, y:Object|number )\n    Returns an iterator which iteratively evaluates the natural logarithm of the\n    beta function.\n","iterBinet":"\niterBinet( iterator:Object )\n    Returns an iterator which iteratively evaluates Binet's formula extended to\n    real numbers.\n","iterCbrt":"\niterCbrt( iterator:Object )\n    Returns an iterator which iteratively computes the cube root.\n","iterCeil":"\niterCeil( iterator:Object )\n    Returns an iterator which rounds each iterated value toward positive\n    infinity.\n","iterCeil2":"\niterCeil2( iterator:Object )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    two toward positive infinity.\n","iterCeil10":"\niterCeil10( iterator:Object )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    10 toward positive infinity.\n","iterCompositesSeq":"\niterCompositesSeq( [options:Object] )\n    Returns an iterator which generates a sequence of composite numbers.\n","iterConcat":"\niterConcat( iter0:Object, ...iterator:Object )\n    Returns an iterator which iterates over the values of two or more iterators.\n","iterConstant":"\niterConstant( value:any[, options:Object] )\n    Returns an iterator which always returns the same value.\n","iterContinuedFraction":"\niterContinuedFraction( iterator:Object[, options:Object] )\n    Evaluates the terms of a continued fraction.\n","iterContinuedFractionSeq":"\niterContinuedFractionSeq( x:number[, options:Object] )\n    Returns an iterator which generates a list of all continued fraction terms\n    which can be obtained given the precision of `x`.\n","iterCos":"\niterCos( iterator:Object )\n    Returns an iterator which iteratively computes the cosine.\n","iterCosh":"\niterCosh( iterator:Object )\n    Returns an iterator which iteratively computes the hyperbolic cosine.\n","iterCosineWave":"\niterCosineWave( [options:Object] )\n    Returns an iterator which generates a cosine wave.\n","iterCosm1":"\niterCosm1( iterator:Object )\n    Returns an iterator which iteratively computes `cos(x) - 1`.\n","iterCospi":"\niterCospi( iterator:Object )\n    Returns an iterator which computes the cosine of each iterated value times\n    π.\n","iterCounter":"\niterCounter( iterator:Object )\n    Returns an iterator which iteratively computes the number of iterated\n    values.\n","iterCovercos":"\niterCovercos( iterator:Object )\n    Returns an iterator which iteratively computes the coversed cosine.\n","iterCoversin":"\niterCoversin( iterator:Object )\n    Returns an iterator which iteratively computes the coversed sine.\n","iterCubesSeq":"\niterCubesSeq( [options:Object] )\n    Returns an iterator which generates a sequence of cubes.\n","itercugmean":"\nitercugmean( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative geometric mean.\n","itercuhmean":"\nitercuhmean( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative harmonic mean.\n","itercumax":"\nitercumax( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative maximum value.\n","itercumaxabs":"\nitercumaxabs( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative maximum absolute\n    value.\n","itercumean":"\nitercumean( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative arithmetic mean.\n","itercumeanabs":"\nitercumeanabs( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative arithmetic mean\n    of absolute values.\n","itercumeanabs2":"\nitercumeanabs2( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative arithmetic mean\n    of squared absolute values.\n","itercumidrange":"\nitercumidrange( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative mid-range.\n","itercumin":"\nitercumin( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative minimum value.\n","itercuminabs":"\nitercuminabs( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative minimum absolute\n    value.\n","itercuprod":"\nitercuprod( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative product.\n","itercurange":"\nitercurange( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative range.\n","itercusum":"\nitercusum( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative sum.\n","itercusumabs":"\nitercusumabs( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative sum of absolute\n    values.\n","itercusumabs2":"\nitercusumabs2( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative sum of squared\n    absolute values.\n","iterDatespace":"\niterDatespace( start:integer|string|Date, stop:integer|string|Date[, \n  N:integer][, options:Object] )\n    Returns an iterator which returns evenly spaced dates over a specified\n    interval.\n","iterDedupe":"\niterDedupe( iterator:Object[, limit:integer] )\n    Returns an iterator which removes consecutive duplicated values.\n","iterDedupeBy":"\niterDedupeBy( iterator:Object, [limit:integer,] fcn:Function )\n    Returns an iterator which removes consecutive values that resolve to the\n    same value according to a provided function.\n","iterDeg2rad":"\niterDeg2rad( iterator:Object )\n    Returns an iterator which iteratively converts an angle from degrees to\n    radians.\n","iterDigamma":"\niterDigamma( iterator:Object )\n    Returns an iterator which iteratively evaluates the digamma function.\n","iterDiracComb":"\niterDiracComb( [options:Object] )\n    Returns an iterator which generates a Dirac comb.\n","iterDiracDelta":"\niterDiracDelta( iterator:Object )\n    Returns an iterator which iteratively evaluates the Dirac delta function.\n","iterDivide":"\niterDivide( iter0:Object, ...iterator:Object )\n    Returns an iterator which performs element-wise division of two or more\n    iterators.\n","iterDoWhileEach":"\niterDoWhileEach( iterator:Object, predicate:Function, fcn:Function[, \n  thisArg:any] )\n    Returns an iterator which invokes a function for each iterated value before\n    returning the iterated value until either a predicate function returns false\n    or the iterator has iterated over all values.\n","iterEllipe":"\niterEllipe( iterator:Object )\n    Returns an iterator which iteratively computes the complete elliptic\n    integral of the second kind.\n","iterEllipk":"\niterEllipk( iterator:Object )\n    Returns an iterator which iteratively computes the complete elliptic\n    integral of the first kind.\n","iterEmpty":"\niterEmpty()\n    Returns an empty iterator.\n","iterErf":"\niterErf( iterator:Object )\n    Returns an iterator which iteratively evaluates the error function.\n","iterErfc":"\niterErfc( iterator:Object )\n    Returns an iterator which iteratively evaluates the complementary error\n    function.\n","iterErfcinv":"\niterErfcinv( iterator:Object )\n    Returns an iterator which iteratively evaluates the inverse complementary\n    error function.\n","iterErfinv":"\niterErfinv( iterator:Object )\n    Returns an iterator which iteratively evaluates the inverse error function.\n","iterEta":"\niterEta( iterator:Object )\n    Returns an iterator which iteratively evaluates the Dirichlet eta function.\n","iterEvenIntegersSeq":"\niterEvenIntegersSeq( [options:Object] )\n    Returns an iterator which generates an interleaved sequence of even\n    integers.\n","iterEvery":"\niterEvery( iterator:Object )\n    Tests whether all iterated values are truthy.\n","iterEveryBy":"\niterEveryBy( iterator:Object, predicate:Function[, thisArg:any ] )\n    Tests whether every iterated value passes a test implemented by a predicate\n    function.\n","iterExp":"\niterExp( iterator:Object )\n    Returns an iterator which iteratively evaluates the natural exponential\n    function.\n","iterExp2":"\niterExp2( iterator:Object )\n    Returns an iterator which iteratively evaluates the base `2` exponential\n    function.\n","iterExp10":"\niterExp10( iterator:Object )\n    Returns an iterator which iteratively evaluates the base `10` exponential\n    function.\n","iterExpit":"\niterExpit( iterator:Object )\n    Returns an iterator which iteratively evaluates the standard logistic\n    function.\n","iterExpm1":"\niterExpm1( iterator:Object )\n    Returns an iterator which iteratively computes `exp(x) - 1`.\n","iterExpm1rel":"\niterExpm1rel( iterator:Object )\n    Returns an iterator which iteratively evaluates the relative error\n    exponential.\n","iterFactorial":"\niterFactorial( iterator:Object )\n    Returns an iterator which iteratively evaluates the factorial function.\n","iterFactorialln":"\niterFactorialln( iterator:Object )\n    Returns an iterator which iteratively evaluates the natural logarithm of the\n    factorial function.\n","iterFactorialsSeq":"\niterFactorialsSeq( [options:Object] )\n    Returns an iterator which generates a sequence of factorials.\n","iterFibonacciSeq":"\niterFibonacciSeq( [options:Object] )\n    Returns an iterator which generates a Fibonacci sequence.\n","iterFifthPowersSeq":"\niterFifthPowersSeq( [options:Object] )\n    Returns an iterator which generates a sequence of fifth powers.\n","iterFill":"\niterFill( iterator:Object, value:any[, begin:integer[, end:integer]] )\n    Returns an iterator which replaces all values from a provided iterator from\n    a start index to an end index with a static value.\n","iterFilter":"\niterFilter( iterator:Object, predicate:Function[, thisArg:any] )\n    Returns an iterator which filters a provided iterator's values according to\n    a predicate function.\n","iterFilterMap":"\niterFilterMap( iterator:Object, fcn:Function[, thisArg:any] )\n    Returns an iterator which both filters and maps a provided iterator's\n    values.\n","iterFirst":"\niterFirst( iterator:Object )\n    Returns the first iterated value.\n","iterFlatTopPulse":"\niterFlatTopPulse( [options:Object] )\n    Returns an iterator which generates a flat top pulse waveform.\n","iterFloor":"\niterFloor( iterator:Object )\n    Returns an iterator which rounds each iterated value toward negative\n    infinity.\n","iterFloor2":"\niterFloor2( iterator:Object )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    two toward negative infinity.\n","iterFloor10":"\niterFloor10( iterator:Object )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    10 toward negative infinity.\n","iterFlow":"\niterFlow( methods:Object )\n    Returns a fluent interface iterator constructor with a customized prototype\n    based on provided methods.\n","iterForEach":"\niterForEach( iterator:Object, fcn:Function[, thisArg:any] )\n    Returns an iterator which invokes a function for each iterated value before\n    returning the iterated value.\n","iterFourthPowersSeq":"\niterFourthPowersSeq( [options:Object] )\n    Returns an iterator which generates a sequence of fourth powers.\n","iterFresnelc":"\niterFresnelc( iterator:Object )\n    Returns an iterator which iteratively computes the Fresnel integral C(x).\n","iterFresnels":"\niterFresnels( iterator:Object )\n    Returns an iterator which iteratively computes the Fresnel integral S(x).\n","iterGamma":"\niterGamma( iterator:Object )\n    Returns an iterator which iteratively evaluates the gamma function.\n","iterGamma1pm1":"\niterGamma1pm1( iterator:Object )\n    Returns an iterator which iteratively computes `gamma(x+1) - 1` without\n    cancellation errors for small `x`.\n","iterGammaln":"\niterGammaln( iterator:Object )\n    Returns an iterator which iteratively evaluates the natural logarithm of the\n    gamma function.\n","iterHacovercos":"\niterHacovercos( iterator:Object )\n    Returns an iterator which iteratively computes the half-value coversed\n    cosine.\n","iterHacoversin":"\niterHacoversin( iterator:Object )\n    Returns an iterator which iteratively computes the half-value coversed sine.\n","iterHannPulse":"\niterHannPulse( [options:Object] )\n    Returns an iterator which generates a Hann pulse waveform.\n","iterHavercos":"\niterHavercos( iterator:Object )\n    Returns an iterator which iteratively computes the half-value versed cosine.\n","iterHaversin":"\niterHaversin( iterator:Object )\n    Returns an iterator which iteratively computes the half-value versed sine.\n","iterHead":"\niterHead( iterator:Object, n:integer )\n    Returns an iterator which returns the first `n` values of a provided\n    iterator.\n","iterIncrspace":"\niterIncrspace( start:number, stop:number[, increment:number] )\n    Returns an iterator which returns evenly spaced numbers according to a\n    specified increment.\n","iterIntegersSeq":"\niterIntegersSeq( [options:Object] )\n    Returns an iterator which generates an interleaved integer sequence.\n","iterIntersection":"\niterIntersection( iter0:Object, ...iterator:Object )\n    Returns an iterator which returns the intersection of two or more iterators.\n","iterIntersectionByHash":"\niterIntersectionByHash( iter0:Object, ...iterator:Object, hashFcn:Function[, \n  thisArg:any] )\n    Returns an iterator which returns the intersection of two or more iterators\n    according to a hash function.\n","iterInv":"\niterInv( iterator:Object )\n    Returns an iterator which iteratively computes the multiplicative inverse.\n","iterLanczosPulse":"\niterLanczosPulse( [options:Object] )\n    Returns an iterator which generates a Lanczos pulse waveform.\n","iterLast":"\niterLast( iterator:Object )\n    Consumes an entire iterator and returns the last iterated value.\n","iterLength":"\niterLength( iterator:Object )\n    Consumes an entire iterator and returns the number of iterated values.\n","iterLinspace":"\niterLinspace( start:number, stop:number[, N:integer] )\n    Returns an iterator which returns evenly spaced numbers over a specified\n    interval.\n","iterLn":"\niterLn( iterator:Object )\n    Returns an iterator which iteratively evaluates the natural logarithm.\n","iterLog":"\niterLog( x:Object|number, b:Object|number )\n    Returns an iterator which iteratively computes the base `b` logarithm.\n","iterLog1mexp":"\niterLog1mexp( iterator:Object )\n    Returns an iterator which iteratively evaluates the natural logarithm of\n    `1-exp(-|x|)`.\n","iterLog1p":"\niterLog1p( iterator:Object )\n    Returns an iterator which iteratively evaluates the natural logarithm of\n    `1+x`.\n","iterLog1pexp":"\niterLog1pexp( iterator:Object )\n    Returns an iterator which iteratively evaluates the natural logarithm of\n    `1+exp(x)`.\n","iterLog2":"\niterLog2( iterator:Object )\n    Returns an iterator which iteratively evaluates the binary logarithm.\n","iterLog10":"\niterLog10( iterator:Object )\n    Returns an iterator which iteratively evaluates the common logarithm\n    (logarithm with base 10).\n","iterLogit":"\niterLogit( iterator:Object )\n    Returns an iterator which iteratively evaluates the logit function.\n","iterLogspace":"\niterLogspace( start:number, stop:number[, N:integer][, options:Object] )\n    Returns an iterator which returns evenly spaced numbers on a log scale.\n","iterLucasSeq":"\niterLucasSeq( [options:Object] )\n    Returns an iterator which generates a Lucas sequence.\n","iterMap":"\niterMap( iterator:Object, fcn:Function[, thisArg:any] )\n    Returns an iterator which invokes a function for each iterated value.\n","iterMapN":"\niterMapN( iter0:Object, ...iterator:Object, fcn:Function[, thisArg:any] )\n    Returns an iterator which transforms iterated values from two or more\n    iterators by applying the iterated values as arguments to a provided\n    function.\n","itermax":"\nitermax( iterator:Object )\n    Computes the maximum value of all iterated values.\n","itermaxabs":"\nitermaxabs( iterator:Object )\n    Computes the maximum absolute value of all iterated values.\n","itermean":"\nitermean( iterator:Object )\n    Computes an arithmetic mean over all iterated values.\n","itermeanabs":"\nitermeanabs( iterator:Object )\n    Computes an arithmetic mean of absolute values for all iterated values.\n","itermeanabs2":"\nitermeanabs2( iterator:Object )\n    Computes an arithmetic mean of squared absolute values for all iterated\n    values.\n","itermidrange":"\nitermidrange( iterator:Object )\n    Computes the mid-range of all iterated values.\n","itermin":"\nitermin( iterator:Object )\n    Computes the minimum value of all iterated values.\n","iterminabs":"\niterminabs( iterator:Object )\n    Computes the minimum absolute value of all iterated values.\n","itermmax":"\nitermmax( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving maximum value.\n","itermmaxabs":"\nitermmaxabs( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving maximum absolute\n    value.\n","itermmean":"\nitermmean( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving arithmetic mean.\n","itermmeanabs":"\nitermmeanabs( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving arithmetic mean of\n    absolute values.\n","itermmeanabs2":"\nitermmeanabs2( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving arithmetic mean of\n    squared absolute values.\n","itermmidrange":"\nitermmidrange( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving mid-range.\n","itermmin":"\nitermmin( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving minimum value.\n","itermminabs":"\nitermminabs( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving minimum absolute\n    value.\n","iterMod":"\niterMod( iter0:Object, ...iterator:Object )\n    Returns an iterator which performs an element-wise modulo operation of two\n    or more iterators.\n","itermprod":"\nitermprod( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving product.\n","itermrange":"\nitermrange( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving range.\n","itermsum":"\nitermsum( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving sum.\n","itermsumabs":"\nitermsumabs( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving sum of absolute\n    values.\n","itermsumabs2":"\nitermsumabs2( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving sum of squared\n    absolute values.\n","iterMultiply":"\niterMultiply( iter0:Object, ...iterator:Object )\n    Returns an iterator which performs element-wise multiplication of two or\n    more iterators.\n","iterNegaFibonacciSeq":"\niterNegaFibonacciSeq( [options:Object] )\n    Returns an iterator which generates a negaFibonacci sequence.\n","iterNegaLucasSeq":"\niterNegaLucasSeq( [options:Object] )\n    Returns an iterator which generates a negaLucas sequence.\n","iterNegativeEvenIntegersSeq":"\niterNegativeEvenIntegersSeq( [options:Object] )\n    Returns an iterator which generates a sequence of negative even integers.\n","iterNegativeIntegersSeq":"\niterNegativeIntegersSeq( [options:Object] )\n    Returns an iterator which generates a negative integer sequence.\n","iterNegativeOddIntegersSeq":"\niterNegativeOddIntegersSeq( [options:Object] )\n    Returns an iterator which generates a sequence of negative odd integers.\n","iterNone":"\niterNone( iterator:Object )\n    Tests whether all iterated values are falsy.\n","iterNoneBy":"\niterNoneBy( iterator:Object, predicate:Function[, thisArg:any ] )\n    Tests whether every iterated value fails a test implemented by a predicate\n    function.\n","iterNonFibonacciSeq":"\niterNonFibonacciSeq( [options:Object] )\n    Returns an iterator which generates a non-Fibonacci integer sequence.\n","iterNonNegativeEvenIntegersSeq":"\niterNonNegativeEvenIntegersSeq( [options:Object] )\n    Returns an iterator which generates a sequence of nonnegative even integers.\n","iterNonNegativeIntegersSeq":"\niterNonNegativeIntegersSeq( [options:Object] )\n    Returns an iterator which generates a nonnegative integer sequence.\n","iterNonPositiveEvenIntegersSeq":"\niterNonPositiveEvenIntegersSeq( [options:Object] )\n    Returns an iterator which generates a sequence of nonpositive even integers.\n","iterNonPositiveIntegersSeq":"\niterNonPositiveIntegersSeq( [options:Object] )\n    Returns an iterator which generates a nonpositive integer sequence.\n","iterNonSquaresSeq":"\niterNonSquaresSeq( [options:Object] )\n    Returns an iterator which generates a sequence of nonsquares.\n","iterNth":"\niterNth( iterator:Object, n:integer )\n    Returns the nth iterated value.\n","iterOddIntegersSeq":"\niterOddIntegersSeq( [options:Object] )\n    Returns an iterator which generates an interleaved sequence of odd integers.\n","iterPeriodicSinc":"\niterPeriodicSinc( n:integer[, options:Object] )\n    Returns an iterator which generates a periodic sinc waveform.\n","iterPipeline":"\niterPipeline( iterFcn:Function|Array[, ...iterFcn:Function] )\n    Returns an iterator pipeline.\n","iterPop":"\niterPop( iterator:Object[, clbk:Function[, thisArg:any]] )\n    Returns an iterator which skips the last value of a provided iterator.\n","iterPositiveEvenIntegersSeq":"\niterPositiveEvenIntegersSeq( [options:Object] )\n    Returns an iterator which generates a sequence of positive even integers.\n","iterPositiveIntegersSeq":"\niterPositiveIntegersSeq( [options:Object] )\n    Returns an iterator which generates a positive integer sequence.\n","iterPositiveOddIntegersSeq":"\niterPositiveOddIntegersSeq( [options:Object] )\n    Returns an iterator which generates a sequence of positive odd integers.\n","iterPow":"\niterPow( base:Object|number, exponent:Object|number )\n    Returns an iterator which iteratively evaluates the exponential function.\n","iterPrimesSeq":"\niterPrimesSeq( [options:Object] )\n    Returns an iterator which generates a sequence of prime numbers.\n","iterprod":"\niterprod( iterator:Object )\n    Computes the product of all iterated values.\n","iterPulse":"\niterPulse( [options:Object] )\n    Returns an iterator which generates a pulse waveform.\n","iterPush":"\niterPush( iterator:Object, ...items:any )\n    Returns an iterator which appends additional values to the end of a provided\n    iterator.\n","iterRad2deg":"\niterRad2deg( iterator:Object )\n    Returns an iterator which iteratively converts an angle from radians to\n    degrees.\n","iterRamp":"\niterRamp( iterator:Object )\n    Returns an iterator which iteratively evaluates the ramp function.\n","iterrange":"\niterrange( iterator:Object )\n    Computes the range of all iterated values.\n","iterReject":"\niterReject( iterator:Object, predicate:Function[, thisArg:any] )\n    Returns an iterator which rejects a provided iterator's values according to\n    a predicate function.\n","iterReplicate":"\niterReplicate( iterator:Object, n:integer )\n    Returns an iterator which replicates each iterated value `n` times.\n","iterReplicateBy":"\niterReplicateBy( iterator:Object, fcn:Function[, thisArg:any] )\n    Returns an iterator which replicates each iterated value according to a\n    provided function.\n","iterRound":"\niterRound( iterator:Object )\n    Returns an iterator which rounds each iterated value to the nearest integer.\n","iterRound2":"\niterRound2( iterator:Object )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    two on a linear scale.\n","iterRound10":"\niterRound10( iterator:Object )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    10 on a linear scale.\n","iterRsqrt":"\niterRsqrt( iterator:Object )\n    Returns an iterator which iteratively computes the reciprocal (inverse)\n    square root.\n","iterSawtoothWave":"\niterSawtoothWave( [options:Object] )\n    Returns an iterator which generates a sawtooth wave.\n","iterShift":"\niterShift( iterator:Object[, clbk:Function[, thisArg:any]] )\n    Returns an iterator which skips the first value of a provided iterator.\n","iterSignum":"\niterSignum( iterator:Object )\n    Returns an iterator which iteratively evaluates the signum function.\n","iterSin":"\niterSin( iterator:Object )\n    Returns an iterator which iteratively computes the sine.\n","iterSinc":"\niterSinc( iterator:Object )\n    Returns an iterator which iteratively computes the normalized cardinal sine.\n","iterSineWave":"\niterSineWave( [options:Object] )\n    Returns an iterator which generates a sine wave.\n","iterSinh":"\niterSinh( iterator:Object )\n    Returns an iterator which iteratively evaluates the hyperbolic sine.\n","iterSinpi":"\niterSinpi( iterator:Object )\n    Returns an iterator which computes the sine of each iterated value times π.\n","iterSlice":"\niterSlice( iterator:Object[, begin:integer[, end:integer]] )\n    Returns an iterator which returns a subsequence of iterated values from a\n    provided iterator.\n","iterSome":"\niterSome( iterator:Object, n:number )\n    Tests whether at least `n` iterated values are truthy.\n","iterSomeBy":"\niterSomeBy( iterator:Object, n:integer, predicate:Function[, thisArg:any ] )\n    Tests whether at least `n` iterated values pass a test implemented by a\n    predicate function.\n","iterSpence":"\niterSpence( iterator:Object )\n    Returns an iterator which iteratively evaluates Spence's function.\n","iterSqrt":"\niterSqrt( iterator:Object )\n    Returns an iterator which iteratively computes the principal square root.\n","iterSqrt1pm1":"\niterSqrt1pm1( iterator:Object )\n    Returns an iterator which iteratively computes `sqrt(1+x) - 1` more \n    accurately for small `x`.\n","iterSquaredTriangularSeq":"\niterSquaredTriangularSeq( [options:Object] )\n    Returns an iterator which generates a sequence of squared triangular\n    numbers.\n","iterSquaresSeq":"\niterSquaresSeq( [options:Object] )\n    Returns an iterator which generates a sequence of squares.\n","iterSquareWave":"\niterSquareWave( [options:Object] )\n    Returns an iterator which generates a square wave.\n","iterstdev":"\niterstdev( iterator:Object[, mean:number] )\n    Computes a correct sample standard deviation over all iterated values.\n","iterStep":"\niterStep( start:number, increment:number[, N:number] )\n    Returns an iterator which returns a sequence of numbers according to a\n    specified increment.\n","iterStrided":"\niterStrided( iterator:Object, stride:integer[, offset:integer[, \n  eager:boolean]] )\n    Returns an iterator which steps by a specified amount.\n","iterStridedBy":"\niterStridedBy( iterator:Object, fcn:Function[, offset:integer[, \n  eager:boolean]][, thisArg:any] )\n    Returns an iterator which steps according to a provided callback function.\n","iterSubtract":"\niterSubtract( iter0:Object, ...iterator:Object )\n    Returns an iterator which performs element-wise subtraction of two or more\n    iterators.\n","itersum":"\nitersum( iterator:Object )\n    Computes the sum of all iterated values.\n","itersumabs":"\nitersumabs( iterator:Object )\n    Computes the sum of absolute values for all iterated values.\n","itersumabs2":"\nitersumabs2( iterator:Object )\n    Computes the sum of squared absolute values for all iterated values.\n","iterTan":"\niterTan( iterator:Object )\n    Returns an iterator which iteratively evaluates the tangent.\n","iterTanh":"\niterTanh( iterator:Object )\n    Returns an iterator which iteratively evaluates the hyperbolic tangent.\n","iterThunk":"\niterThunk( iterFcn:Function[, ...args:any] )\n    Returns an iterator \"thunk\".\n","iterTriangleWave":"\niterTriangleWave( [options:Object] )\n    Returns an iterator which generates a triangle wave.\n","iterTriangularSeq":"\niterTriangularSeq( [options:Object] )\n    Returns an iterator which generates a sequence of triangular numbers.\n","iterTribonnaciSeq":"\niterTribonnaciSeq( [options:Object] )\n    Returns an iterator which generates a Tribonacci sequence.\n    \n    The returned iterator can only generate the first 64 Tribonacci numbers, as\n    larger Tribonacci numbers cannot be safely represented in double-precision\n    floating-point format.\n","iterTrigamma":"\niterTrigamma( iterator:Object )\n    Returns an iterator which iteratively evaluates the trigamma function.\n","iterTrunc":"\niterTrunc( iterator:Object )\n    Returns an iterator which rounds each iterated value toward zero.\n","iterTrunc2":"\niterTrunc2( iterator:Object )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    two toward zero.\n","iterTrunc10":"\niterTrunc10( iterator:Object )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    10 toward zero.\n","iterUnion":"\niterUnion( iter0:Object, ...iterator:Object )\n    Returns an iterator which returns the union of two or more iterators.\n","iterUnique":"\niterUnique( iterator:Object )\n    Returns an iterator which returns unique values.\n","iterUniqueBy":"\niterUniqueBy( iterator:Object, predicate:Function[, thisArg:any] )\n    Returns an iterator which returns unique values according to a predicate\n    function.\n","iterUniqueByHash":"\niterUniqueByHash( iterator:Object, hashFcn:Function[, thisArg:any] )\n    Returns an iterator which returns unique values according to a hash\n    function.\n","iterUnitspace":"\niterUnitspace( start:number[, stop:number] )\n    Returns an iterator which returns numbers incremented by one.\n","iterUnshift":"\niterUnshift( iterator:Object, ...items:any )\n    Returns an iterator which prepends values to the beginning of a provided\n    iterator.\n","iterUntilEach":"\niterUntilEach( iterator:Object, predicate:Function, fcn:Function[, \n  thisArg:any] )\n    Returns an iterator which invokes a function for each iterated value before\n    returning the iterated value until either a predicate function returns true\n    or the iterator has iterated over all values.\n","itervariance":"\nitervariance( iterator:Object[, mean:number] )\n    Computes an unbiased sample variance over all iterated values.\n","iterVercos":"\niterVercos( iterator:Object )\n    Returns an iterator which iteratively computes the versed cosine.\n","iterVersin":"\niterVersin( iterator:Object )\n    Returns an iterator which iteratively computes the versed sine.\n","iterWhileEach":"\niterWhileEach( iterator:Object, predicate:Function, fcn:Function[, \n  thisArg:any] )\n    Returns an iterator which invokes a function for each iterated value before\n    returning the iterated value until either a predicate function returns false\n    or the iterator has iterated over all values.\n","iterZeta":"\niterZeta( iterator:Object )\n    Returns an iterator which iteratively evaluates the Riemann zeta function.\n","joinStream":"\njoinStream( [options:Object] )\n    Returns a transform stream which joins streamed data.\n","joinStream.factory":"\njoinStream.factory( [options:Object] )\n    Returns a function for creating transform streams for joined streamed data.\n","joinStream.objectMode":"\njoinStream.objectMode( [options:Object] )\n    Returns an \"objectMode\" transform stream for joining streamed data.\n","kde2d":"\nkde2d( x:Array<number>, y:Array<number>[, options:Object] )\n    Two-dimensional kernel density estimation.\n","kebabcase":"\nkebabcase( str:string )\n    Converts a string to kebab case.\n","keyBy":"\nkeyBy( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n    Converts a collection to an object whose keys are determined by a provided\n    function and whose values are the collection values.\n","keyByRight":"\nkeyByRight( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n    Converts a collection to an object whose keys are determined by a provided\n    function and whose values are the collection values, iterating from right to\n    left.\n","keysIn":"\nkeysIn( obj:any )\n    Returns an array of an object's own and inherited enumerable property\n    names.\n","kruskalTest":"\nkruskalTest( ...x:Array[, options:Object] )\n    Computes the Kruskal-Wallis test for equal medians.\n","kstest":"\nkstest( x:Array<number>, y:Function|string[, ...params:number][, \n  options:Object] )\n    Computes a Kolmogorov-Smirnov goodness-of-fit test.\n","last":"\nlast( str:string[, n:integer][, options:Object] )\n    Returns the last character(s) of a string.\n","leveneTest":"\nleveneTest( x:Array<number>[, ...y:Array<number>[, options:Object]] )\n    Computes Levene's test for equal variances.\n","LinkedList":"\nLinkedList()\n    Linked list constructor.\n","linspace":"\nlinspace( start:number|ComplexLike, stop:number|ComplexLike, length:integer[, \n  options:Object] )\n    Generates a linearly spaced array over a specified interval.\n","linspace.assign":"\nlinspace.assign( start:number|ComplexLike, stop:number|ComplexLike, \n  out:ArrayLikeObject[, options:Object] )\n    Generates a linearly spaced sequence over a specified interval and assigns\n    the results to a provided output array.\n","LIU_NEGATIVE_OPINION_WORDS_EN":"\nLIU_NEGATIVE_OPINION_WORDS_EN()\n    Returns a list of negative opinion words.\n","LIU_POSITIVE_OPINION_WORDS_EN":"\nLIU_POSITIVE_OPINION_WORDS_EN()\n    Returns a list of positive opinion words.\n","LN_HALF":"\nLN_HALF\n    Natural logarithm of `1/2`.\n","LN_PI":"\nLN_PI\n    Natural logarithm of the mathematical constant `π`.\n","LN_SQRT_TWO_PI":"\nLN_SQRT_TWO_PI\n    Natural logarithm of the square root of `2π`.\n","LN_TWO_PI":"\nLN_TWO_PI\n    Natural logarithm of `2π`.\n","LN2":"\nLN2\n    Natural logarithm of `2`.\n","LN10":"\nLN10\n    Natural logarithm of `10`.\n","LOG2E":"\nLOG2E\n    Base 2 logarithm of Euler's number.\n","LOG10E":"\nLOG10E\n    Base 10 logarithm of Euler's number.\n","logspace":"\nlogspace( a:number, b:number[, length:integer] )\n    Generates a logarithmically spaced numeric array between `10^a` and `10^b`.\n","lowercase":"\nlowercase( str:string )\n    Converts a string to lowercase.\n","lowercaseKeys":"\nlowercaseKeys( obj:Object )\n    Converts each object key to lowercase.\n","lowess":"\nlowess( x:Array<number>, y:Array<number>[, options:Object] )\n    Locally-weighted polynomial regression via the LOWESS algorithm.\n","lpad":"\nlpad( str:string, len:integer[, pad:string] )\n    Left pads a string such that the padded string has a length of at least\n    `len`.\n","ltrim":"\nltrim( str:string )\n    Trims whitespace from the beginning of a string.\n","ltrimN":"\nltrimN( str:string, n:integer[, chars:Array|string] )\n    Trims `n` characters from the beginning of a string.\n","MALE_FIRST_NAMES_EN":"\nMALE_FIRST_NAMES_EN()\n    Returns a list of common male first names in English speaking countries.\n","map":"\nmap( arr:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n    Applies a function to each element in an array and assigns the result to an\n    element in a new array.\n","map.assign":"\nmap.assign( arr:ArrayLikeObject|ndarray, out:ArrayLikeObject|ndarray, \n  fcn:Function[, thisArg:any] )\n    Applies a function to each element in an array and assigns the result to an\n    element in an output array.\n","map2":"\nmap2( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, fcn:Function[, \n  thisArg:any] )\n    Applies a function to elements in two input arrays and assigns the results\n    to a new array.\n","map2.assign":"\nmap2.assign( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, \n  out:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n    Applies a function to elements in two input arrays and assigns the results\n    to an output array.\n","map2d":"\nmap2d( arr:ArrayLikeObject<ArrayLikeObject>, fcn:Function[, thisArg:any] )\n    Applies a function to each nested element in an array of arrays and assigns\n    the result to a nested element in a new array of arrays.\n","map2Right":"\nmap2Right( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, fcn:Function[, \n  thisArg:any] )\n    Applies a function to elements in two input arrays while iterating from\n    right to left and assigns the results to a new array.\n","map2Right.assign":"\nmap2Right.assign( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, \n  out:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n    Applies a function to elements in two input arrays while iterating from\n    right to left and assigns the results to an output array.\n","map3d":"\nmap3d( arr:ArrayLikeObject<ArrayLikeObject<ArrayLikeObject>>, fcn:Function[, \n  thisArg:any] )\n    Applies a function to each nested element in a three-dimensional nested\n    array and assigns the result to a nested element in a new three-dimensional\n    nested array.\n","map4d":"\nmap4d( arr:ArrayLikeObject<ArrayLikeObject>, fcn:Function[, thisArg:any] )\n    Applies a function to each nested element in a four-dimensional nested array\n    and assigns the result to a nested element in a new four-dimensional nested\n    array.\n","map5d":"\nmap5d( arr:ArrayLikeObject<ArrayLikeObject>, fcn:Function[, thisArg:any] )\n    Applies a function to each nested element in a five-dimensional nested array\n    and assigns the result to a nested element in a new five-dimensional nested\n    array.\n","mapArguments":"\nmapArguments( fcn:Function, clbk:Function[, thisArg:any] )\n    Returns a function that applies arguments to a provided function after\n    transforming arguments according to a callback function.\n","mapFun":"\nmapFun( fcn:Function, n:integer[, thisArg:any] )\n    Invokes a function `n` times and returns an array of accumulated function\n    return values.\n","mapFunAsync":"\nmapFunAsync( fcn:Function, n:integer, [options:Object,] done:Function )\n    Invokes a function `n` times and returns an array of accumulated function\n    return values.\n","mapFunAsync.factory":"\nmapFunAsync.factory( [options:Object,] fcn:Function )\n    Returns a function which invokes a function `n` times and returns an array\n    of accumulated function return values.\n","mapKeys":"\nmapKeys( obj:Object, transform:Function )\n    Maps keys from one object to a new object having the same values.\n","mapKeysAsync":"\nmapKeysAsync( obj:Object, [options:Object,] transform:Function, done:Function )\n    Maps keys from one object to a new object having the same values.\n","mapKeysAsync.factory":"\nmapKeysAsync.factory( [options:Object,] transform:Function )\n    Returns a function which maps keys from one object to a new object having\n    the same values.\n","mapReduce":"\nmapReduce( arr:ArrayLikeObject|ndarray, initial:any, mapper:Function, \n  reducer:Function[, thisArg:any] )\n    Performs a map-reduce operation for each element in an array and returns the\n    accumulated result.\n","mapReduceRight":"\nmapReduceRight( arr:ArrayLikeObject|ndarray, initial:any, mapper:Function, \n  reducer:Function[, thisArg:any] )\n    Performs a map-reduce operation for each element in an array while iterating\n    from right to left and returns the accumulated result.\n","mapRight":"\nmapRight( arr:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n    Applies a function to each element in an array and assigns the result to an\n    element in a new array, iterating from right to left.\n","mapRight.assign":"\nmapRight.assign( arr:ArrayLikeObject|ndarray, out:ArrayLikeObject|ndarray, \n  fcn:Function[, thisArg:any] )\n    Applies a function to each element in an array and assigns the result to an\n    element in an output array, iterating from right to left.\n","mapValues":"\nmapValues( obj:Object, transform:Function )\n    Maps values from one object to a new object having the same keys.\n","mapValuesAsync":"\nmapValuesAsync( obj:Object, [options:Object,] transform:Function, \n  done:Function )\n    Maps values from one object to a new object having the same keys.\n","mapValuesAsync.factory":"\nmapValuesAsync.factory( [options:Object,] transform:Function )\n    Returns a function which maps values from one object to a new object having\n    the same keys.\n","maskArguments":"\nmaskArguments( fcn:Function, mask:ArrayLikeObject[, thisArg:any] )\n    Returns a function that applies arguments to a provided function according\n    to a specified mask.\n","MAX_ARRAY_LENGTH":"\nMAX_ARRAY_LENGTH\n    Maximum length for a generic array.\n","MAX_TYPED_ARRAY_LENGTH":"\nMAX_TYPED_ARRAY_LENGTH\n    Maximum length for a typed array.\n","maybeBroadcastArray":"\nmaybeBroadcastArray( x:ndarray, shape:ArrayLikeObject )\n    Broadcasts an ndarray to a specified shape if and only if the specified\n    shape differs from the provided ndarray's shape.\n","maybeBroadcastArrays":"\nmaybeBroadcastArrays( ...arrays:ndarray|ArrayLikeObject<ndarray> )\n    Broadcasts ndarrays to a common shape.\n","memoize":"\nmemoize( fcn:Function[, hashFunction:Function] )\n    Returns a memoized function.\n","merge":"\nmerge( target:Object, ...source:Object )\n    Merges objects into a target object.\n","merge.factory":"\nmerge.factory( options:Object )\n    Returns a function for merging and extending objects.\n","MILLISECONDS_IN_DAY":"\nMILLISECONDS_IN_DAY\n    Number of milliseconds in a day.\n","MILLISECONDS_IN_HOUR":"\nMILLISECONDS_IN_HOUR\n    Number of milliseconds in an hour.\n","MILLISECONDS_IN_MINUTE":"\nMILLISECONDS_IN_MINUTE\n    Number of milliseconds in a minute.\n","MILLISECONDS_IN_SECOND":"\nMILLISECONDS_IN_SECOND\n    Number of milliseconds in a second.\n","MILLISECONDS_IN_WEEK":"\nMILLISECONDS_IN_WEEK\n    Number of milliseconds in a week.\n","MINARD_NAPOLEONS_MARCH":"\nMINARD_NAPOLEONS_MARCH( [options:Object] )\n    Returns data for Charles Joseph Minard's cartographic depiction of\n    Napoleon's Russian campaign of 1812.\n","MINUTES_IN_DAY":"\nMINUTES_IN_DAY\n    Number of minutes in a day.\n","MINUTES_IN_HOUR":"\nMINUTES_IN_HOUR\n    Number of minutes in an hour.\n","MINUTES_IN_WEEK":"\nMINUTES_IN_WEEK\n    Number of minutes in a week.\n","minutesInMonth":"\nminutesInMonth( [month:string|Date|integer[, year:integer]] )\n    Returns the number of minutes in a month.\n","minutesInYear":"\nminutesInYear( [value:integer|Date] )\n    Returns the number of minutes in a year according to the Gregorian calendar.\n","MOBY_DICK":"\nMOBY_DICK()\n    Returns the text of Moby Dick by Herman Melville.\n","MONTH_NAMES_EN":"\nMONTH_NAMES_EN()\n    Returns a list of month names (English).\n","MONTHS_IN_YEAR":"\nMONTHS_IN_YEAR\n    Number of months in a year.\n","moveProperty":"\nmoveProperty( source:Object, prop:string, target:Object )\n    Moves a property from one object to another object.\n","MultiSlice":"\nMultiSlice( ...slice )\n    Returns a multi-slice.\n","MultiSlice.prototype.ndims":"\nMultiSlice.prototype.ndims\n    Read-only property returning the number of slice dimensions.\n","MultiSlice.prototype.data":"\nMultiSlice.prototype.data\n    Read-only property returning the slice data.\n","MultiSlice.prototype.toString":"\nMultiSlice.prototype.toString()\n    Serializes a multi-slice as a string.\n","MultiSlice.prototype.toJSON":"\nMultiSlice.prototype.toJSON()\n    Serializes a multi-slice as a JSON object.\n","namedtypedtuple":"\nnamedtypedtuple( fields:Array<string>[, options:Object] )\n    Returns a named typed tuple factory.\n","NAN":"\nNAN\n    Double-precision floating-point NaN.\n","naryFunction":"\nnaryFunction( fcn:Function, arity:integer[, thisArg:any] )\n    Returns a function that applies a specified number of arguments to a\n    provided function.\n","nativeClass":"\nnativeClass( value:any )\n    Returns a string value indicating a specification defined classification of\n    an object.\n","ndarray":"\nndarray( dtype:string, buffer:ArrayLikeObject|TypedArray|Buffer, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  offset:integer, order:string[, options:Object] )\n    Returns an ndarray.\n","ndarray.prototype.byteLength":"\nndarray.prototype.byteLength\n    Size (in bytes) of the array (if known).\n","ndarray.prototype.BYTES_PER_ELEMENT":"\nndarray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element (if known).\n","ndarray.prototype.data":"\nndarray.prototype.data\n    Pointer to the underlying data buffer.\n","ndarray.prototype.dtype":"\nndarray.prototype.dtype\n    Underlying data type.\n","ndarray.prototype.flags":"\nndarray.prototype.flags\n    Meta information, such as information concerning the memory layout of the\n    array.\n","ndarray.prototype.length":"\nndarray.prototype.length\n    Length of the array (i.e., number of elements).\n","ndarray.prototype.ndims":"\nndarray.prototype.ndims\n    Number of dimensions.\n","ndarray.prototype.offset":"\nndarray.prototype.offset\n    Index offset which specifies the buffer index at which to start iterating\n    over array elements.\n","ndarray.prototype.order":"\nndarray.prototype.order\n    Array order.\n","ndarray.prototype.shape":"\nndarray.prototype.shape\n    Array shape.\n","ndarray.prototype.strides":"\nndarray.prototype.strides\n    Index strides which specify how to access data along corresponding array\n    dimensions.\n","ndarray.prototype.get":"\nndarray.prototype.get( ...idx:integer )\n    Returns an array element specified according to provided subscripts.\n","ndarray.prototype.iget":"\nndarray.prototype.iget( idx:integer )\n    Returns an array element located at a specified linear index.\n","ndarray.prototype.set":"\nndarray.prototype.set( ...idx:integer, v:any )\n    Sets an array element specified according to provided subscripts.\n","ndarray.prototype.iset":"\nndarray.prototype.iset( idx:integer, v:any )\n    Sets an array element located at a specified linear index.\n","ndarray.prototype.toString":"\nndarray.prototype.toString()\n    Serializes an ndarray as a string.\n","ndarray.prototype.toJSON":"\nndarray.prototype.toJSON()\n    Serializes an ndarray as a JSON object.\n","ndarray2array":"\nndarray2array( x:ndarray )\n    Converts an ndarray to a generic array.\n","ndarray2fancy":"\nndarray2fancy( x:ndarray[, options:Object] )\n    Converts an ndarray to an object supporting fancy indexing.\n","ndarray2fancy.factory":"\nndarray2fancy.factory( [options:Object] )\n    Returns a function for converting an ndarray to an object supporting fancy\n    indexing.\n","ndarray2fancy.idx":"\nndarray2fancy.idx( x:ndarray[, options:Object] )\n    Wraps a provided ndarray as an ndarray index object.\n","ndarray2json":"\nndarray2json( x:ndarray )\n    Serializes an ndarray as a JSON object.\n","ndarrayCastingModes":"\nndarrayCastingModes()\n    Returns a list of ndarray casting modes.\n","ndarrayDataBuffer":"\nndarrayDataBuffer( x:ndarray )\n    Returns the underlying data buffer of a provided ndarray.\n","ndarrayDataType":"\nndarrayDataType( x:ndarray )\n    Returns the data type of a provided ndarray.\n","ndarrayDataTypes":"\nndarrayDataTypes( [kind:string] )\n    Returns a list of ndarray data types.\n","ndarrayDispatch":"\nndarrayDispatch( fcns:Function|ArrayLikeObject<Function>, \n  types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, \n  nout:integer )\n    Returns an ndarray function interface which performs multiple dispatch.\n","ndarrayFlag":"\nndarrayFlag( x:ndarray, name:string|symbol )\n    Returns a specified flag for a provided ndarray.\n","ndarrayFlags":"\nndarrayFlags( x:ndarray )\n    Returns the flags of a provided ndarray.\n","ndarrayIndexModes":"\nndarrayIndexModes()\n    Returns a list of ndarray index modes.\n","ndarraylike2ndarray":"\nndarraylike2ndarray( x:ndarrayLike[, options:Object] )\n    Converts an ndarray-like object to an ndarray.\n","ndarrayMinDataType":"\nndarrayMinDataType( value:any )\n    Returns the minimum ndarray data type of the closest \"kind\" necessary for\n    storing a provided scalar value.\n","ndarrayMostlySafeCasts":"\nndarrayMostlySafeCasts( [dtype:any] )\n    Returns a list of ndarray data types to which a provided ndarray data type\n    can be safely cast and, for floating-point data types, can be downcast.\n","ndarrayNextDataType":"\nndarrayNextDataType( [dtype:any] )\n    Returns the next larger ndarray data type of the same kind.\n","ndarrayOffset":"\nndarrayOffset( x:ndarray )\n    Returns the index offset specifying the underlying buffer index of the first\n    iterated ndarray element.\n","ndarrayOrder":"\nndarrayOrder( x:ndarray )\n    Returns the layout order of a provided ndarray.\n","ndarrayOrders":"\nndarrayOrders()\n    Returns a list of ndarray orders.\n","ndarrayPromotionRules":"\nndarrayPromotionRules( [dtype1:any, dtype2:any] )\n    Returns the ndarray data type with the smallest size and closest \"kind\" to\n    which ndarray data types can be safely cast.\n","ndarraySafeCasts":"\nndarraySafeCasts( [dtype:any] )\n    Returns a list of ndarray data types to which a provided ndarray data type\n    can be safely cast.\n","ndarraySameKindCasts":"\nndarraySameKindCasts( [dtype:any] )\n    Returns a list of ndarray data types to which a provided ndarray data type\n    can be safely cast or cast within the same \"kind\".\n","ndarrayShape":"\nndarrayShape( x:ndarray )\n    Returns the shape of a provided ndarray.\n","ndarrayStride":"\nndarrayStride( x:ndarray, dim:integer )\n    Returns the stride along a specified dimension for a provided ndarray.\n","ndarrayStrides":"\nndarrayStrides( x:ndarray )\n    Returns the strides of a provided ndarray.\n","ndat":"\nndat( x:ndarray[, ...indices:integer] )\n    Returns an ndarray element.\n","ndempty":"\nndempty( shape:ArrayLikeObject<integer>|integer[, options:Object] )\n    Returns an uninitialized ndarray having a specified shape and data type.\n","ndemptyLike":"\nndemptyLike( x:ndarray[, options:Object] )\n    Returns an uninitialized ndarray having the same shape and data type as a\n    provided input ndarray.\n","ndfilter":"\nndfilter( x:ndarray[, options:Object], predicate:Function[, thisArg:any] )\n    Returns a shallow copy of an ndarray containing only those elements which\n    pass a test implemented by a predicate function.\n","ndfilterMap":"\nndfilterMap( x:ndarray[, options:Object], fcn:Function[, thisArg:any] )\n    Filters and maps elements in an input ndarray to elements in a new output\n    ndarray according to a callback function.\n","ndforEach":"\nndforEach( x:ndarray, fcn:Function[, thisArg:any] )\n    Invokes a callback function once for each ndarray element.\n","ndims":"\nndims( x:ndarray )\n    Returns the number of ndarray dimensions.\n","ndindex":"\nndindex( x:ndarray[, options:Object] )\n    Wraps a provided array as an ndarray index object.\n","ndindex.free":"\nndindex.free( id:string )\n    Frees the instance associated with a provided identifier.\n","ndindex.get":"\nndindex.get( id:string )\n    Returns the ndarray associated with the instance having a provided\n    identifier.\n","ndindex.cartesianIndex":"\nndindex.cartesianIndex( x:ndarray[, options:Object] )\n    Returns an ndarray index containing Cartesian indices.\n","ndindex.linearIndex":"\nndindex.linearIndex( x:ndarray[, options:Object] )\n    Returns an ndarray index for indices representing locations in linear\n    memory.\n","ndindex.prototype.data":"\nndindex.prototype.data\n    Read-only property returning an ndarray view of the underlying index\n    ndarray.\n","ndindex.prototype.dtype":"\nndindex.prototype.dtype\n    Read-only property returning the underlying data type of the index ndarray.\n","ndindex.prototype.id":"\nndindex.prototype.id\n    Read-only property returning the unique identifier associated with an\n    instance.\n","ndindex.prototype.isCached":"\nndindex.prototype.isCached\n    Read-only property returning a boolean indicating whether an ndarray index\n    is actively cached.\n","ndindex.prototype.kind":"\nndindex.prototype.kind\n    Read-only property returning the ndarray index kind.\n","ndindex.prototype.type":"\nndindex.prototype.type\n    Read-only property returning the ndarray index type.\n","ndindex.prototype.toString":"\nndindex.prototype.toString()\n    Serializes an instance as a string.\n","ndindex.prototype.toJSON":"\nndindex.prototype.toJSON()\n    Serializes an instance as a JSON object.\n","nditerColumnEntries":"\nnditerColumnEntries( x:ndarray[, options:Object] )\n    Returns an iterator which returns [index, column] pairs for each column in a\n    matrix (or stack of matrices).\n","nditerColumns":"\nnditerColumns( x:ndarray[, options:Object] )\n    Returns an iterator which iterates over each column in a matrix (or stack of\n    matrices).\n","nditerEntries":"\nnditerEntries( x:ndarray[, options:Object] )\n    Returns an iterator which returns [index, value] pairs for each element in a\n    provided ndarray.\n","nditerIndices":"\nnditerIndices( shape:Array<integer>[, options:Object] )\n    Returns an iterator which returns indices for use indexing into an ndarray\n    having a specified shape.\n","nditerInterleaveSubarrays":"\nnditerInterleaveSubarrays( arr:ArrayLike<ndarray>, ndims:integer )\n    Returns an iterator which iterates over interleaved subarrays.\n","nditerMatrices":"\nnditerMatrices( x:ndarray[, options:Object] )\n    Returns an iterator which iterates over each matrix in a stack of matrices.\n","nditerMatrixEntries":"\nnditerMatrixEntries( x:ndarray[, options:Object] )\n    Returns an iterator which returns [index, matrix] pairs for each matrix in a\n    stack of matrices.\n","nditerRowEntries":"\nnditerRowEntries( x:ndarray[, options:Object] )\n    Returns an iterator which returns [index, row] pairs for each row in a\n    matrix (or stack of matrices).\n","nditerRows":"\nnditerRows( x:ndarray[, options:Object] )\n    Returns an iterator which iterates over each row in a matrix (or stack of\n    matrices).\n","nditerSelectDimension":"\nnditerSelectDimension( x:ndarray, dim:integer[, options:Object] )\n    Returns an iterator which iterates over each view along a specified\n    dimension.\n","nditerStacks":"\nnditerStacks( x:ndarray, dims:Array<integer>[, options:Object] )\n    Returns an iterator which iterates over each subarray in a stack of\n    subarrays according to a list of specified stack dimensions.\n","nditerSubarrays":"\nnditerSubarrays( x:ndarray, ndims:integer[, options:Object] )\n    Returns an iterator which iterates over each subarray in a stack of\n    subarrays.\n","nditerValues":"\nnditerValues( x:ndarray[, options:Object] )\n    Returns an iterator which returns individual elements from a provided\n    ndarray.\n","ndmap":"\nndmap( x:ndarray[, options:Object], fcn:Function[, thisArg:any] )\n    Applies a callback function to elements in an input ndarray and assigns\n    results to elements in a new output ndarray.\n","ndreject":"\nndreject( x:ndarray[, options:Object], predicate:Function[, thisArg:any] )\n    Returns a shallow copy of an ndarray containing only those elements which\n    fail a test implemented by a predicate function.\n","ndslice":"\nndslice( x:ndarray, ...s:MultiSlice|Slice|null|undefined|integer|ArrayLike[, \n  options:Object] )\n    Returns a read-only view of an input ndarray.\n","ndsliceAssign":"\nndsliceAssign( x:ndarray, y:ndarray, \n  ...s:MultiSlice|Slice|null|undefined|integer|ArrayLike[, options:Object] )\n    Assigns element values from a broadcasted input ndarray to corresponding\n    elements in an output ndarray view.\n","ndsliceDimension":"\nndsliceDimension( x:ndarray, dim:integer, slice:Slice|integer|null|undefined[, \n  options:Object] )\n    Returns a read-only view of an input ndarray when sliced along a specified\n    dimension.\n","ndsliceDimensionFrom":"\nndsliceDimensionFrom( x:ndarray, dim:integer, start:integer[, options:Object] )\n    Returns a read-only shifted view of an input ndarray along a specified\n    dimension.\n","ndsliceDimensionTo":"\nndsliceDimensionTo( x:ndarray, dim:integer, stop:integer[, options:Object] )\n    Returns a read-only truncated view of an input ndarray along a specified\n    dimension.\n","ndsliceFrom":"\nndsliceFrom( x:ndarray, ...start:null|void|integer[, options:Object] )\n    Returns a read-only shifted view of an input ndarray.\n","ndsliceTo":"\nndsliceTo( x:ndarray, ...stop:null|void|integer[, options:Object] )\n    Returns a read-only truncated view of an input ndarray.\n","ndzeros":"\nndzeros( shape:ArrayLikeObject<integer>|integer[, options:Object] )\n    Returns a zero-filled ndarray having a specified shape and data type.\n","ndzerosLike":"\nndzerosLike( x:ndarray[, options:Object] )\n    Returns a zero-filled ndarray having the same shape and data type as a\n    provided input ndarray.\n","nextGraphemeClusterBreak":"\nnextGraphemeClusterBreak( str:string[, fromIndex:integer] )\n    Returns the next extended grapheme cluster break in a string after a\n    specified position.\n","nextTick":"\nnextTick( clbk[, ...args] )\n    Adds a callback to the \"next tick queue\".\n","NIGHTINGALES_ROSE":"\nNIGHTINGALES_ROSE()\n    Returns data for Nightingale's famous polar area diagram.\n","NINF":"\nNINF\n    Double-precision floating-point negative infinity.\n","NODE_VERSION":"\nNODE_VERSION\n    Node version.\n","none":"\nnone( collection:Array|TypedArray|Object )\n    Tests whether all elements in a collection are falsy.\n","noneBy":"\nnoneBy( collection:Array|TypedArray|Object, predicate:Function[, thisArg:any ] )\n    Tests whether all elements in a collection fail a test implemented by a\n    predicate function.\n","noneByAsync":"\nnoneByAsync( collection:Array|TypedArray|Object, [options:Object,] \n  predicate:Function, done:Function )\n    Tests whether all elements in a collection fail a test implemented by a\n    predicate function.\n","noneByAsync.factory":"\nnoneByAsync.factory( [options:Object,] predicate:Function )\n    Returns a function which tests whether all elements in a collection fail a\n    test implemented by a predicate function.\n","noneByRight":"\nnoneByRight( collection:Array|TypedArray|Object, predicate:Function[, \n  thisArg:any ] )\n    Tests whether all elements in a collection fail a test implemented by a\n    predicate function, iterating from right to left.\n","noneByRightAsync":"\nnoneByRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n  predicate:Function, done:Function )\n    Tests whether all elements in a collection fail a test implemented by a\n    predicate function, iterating from right to left.\n","noneByRightAsync.factory":"\nnoneByRightAsync.factory( [options:Object,] predicate:Function )\n    Returns a function which tests whether all elements in a collection fail a\n    test implemented by a predicate function, iterating from right to left.\n","noneInBy":"\nnoneInBy( object:Object, predicate:Function[, thisArg:any ] )\n    Tests whether every property in an object fails a test implemented by a\n    predicate function.\n","nonEnumerableProperties":"\nnonEnumerableProperties( value:any )\n    Returns an array of an object's own non-enumerable property names and\n    symbols.\n","nonEnumerablePropertiesIn":"\nnonEnumerablePropertiesIn( value:any )\n    Returns an array of an object's own and inherited non-enumerable property\n    names and symbols.\n","nonEnumerablePropertyNames":"\nnonEnumerablePropertyNames( value:any )\n    Returns an array of an object's own non-enumerable property names.\n","nonEnumerablePropertyNamesIn":"\nnonEnumerablePropertyNamesIn( value:any )\n    Returns an array of an object's own and inherited non-enumerable property\n    names.\n","nonEnumerablePropertySymbols":"\nnonEnumerablePropertySymbols( value:any )\n    Returns an array of an object's own non-enumerable symbol properties.\n","nonEnumerablePropertySymbolsIn":"\nnonEnumerablePropertySymbolsIn( value:any )\n    Returns an array of an object's own and inherited non-enumerable symbol\n    properties.\n","noneOwnBy":"\nnoneOwnBy( object:Object, predicate:Function[, thisArg:any ] )\n    Tests whether every own property of an object fails a test implemented\n    by a predicate function.\n","nonIndexKeys":"\nnonIndexKeys( obj:any )\n    Returns an array of an object's own enumerable property names which are not\n    integer indices.\n","noop":"\nnoop()\n    A function which does nothing.\n","now":"\nnow()\n    Returns the time in seconds since the epoch.\n","NUM_CPUS":"\nNUM_CPUS\n    Number of CPUs.\n","num2words":"\nnum2words( value:integer[, options:Object] )\n    Converts a number to a word representation.\n","Number":"\nNumber( value:number )\n    Returns a Number object.\n","numel":"\nnumel( x:ndarray )\n    Returns the number of elements in an ndarray.\n","numelDimension":"\nnumelDimension( x:ndarray, dim:integer )\n    Returns the size (i.e., number of elements) of a specified dimension for a\n    provided ndarray.\n","numGraphemeClusters":"\nnumGraphemeClusters( str:string )\n    Returns the number of grapheme clusters in a string.\n","Object":"\nObject( value:any )\n    Returns an object.\n","Object.assign":"\nObject.assign( target:Object, ...sources:Object )\n    Assigns enumerable and own properties from source objects to a target\n    object.\n","Object.create":"\nObject.create( prototype:Object, properties:Object )\n    Creates a new object with a specified prototype object and properties.\n","Object.defineProperties":"\nObject.defineProperties( obj:Object, properties:Object )\n    Defines properties for an object.\n","Object.defineProperty":"\nObject.defineProperty( obj:Object, key:string, descriptor:Object )\n    Defines a property for an object.\n","Object.entries":"\nObject.entries( obj:Object )\n    Returns an array of an object's own enumerable string-keyed property\n    [key, value] pairs.\n","Object.freeze":"\nObject.freeze( obj:Object )\n    Freezes an object.\n","Object.getOwnPropertyDescriptor":"\nObject.getOwnPropertyDescriptor( obj:Object, key:string )\n    Returns an object's own property descriptor.\n","Object.getOwnPropertyDescriptors":"\nObject.getOwnPropertyDescriptors( obj:Object )\n    Returns an object's own property descriptors.\n","Object.getOwnPropertyNames":"\nObject.getOwnPropertyNames( obj:Object )\n    Returns an array of an object's own enumerable and non-enumerable\n    property names.\n","Object.getOwnPropertySymbols":"\nObject.getOwnPropertySymbols( obj:Object )\n    Returns an array of an object's own enumerable and non-enumerable\n    symbol property names.\n","Object.getPrototypeOf":"\nObject.getPrototypeOf( obj:Object )\n    Returns an object's prototype.\n","Object.hasOwn":"\nObject.hasOwn( obj:Object, p:string )\n    Returns a boolean indicating whether an object has a property with the\n    specified name.\n","Object.is":"\nObject.is( value1:any, value2:any )\n    Returns a boolean indicating whether two values are the same value.\n","Object.isExtensible":"\nObject.isExtensible( obj:Object )\n    Returns a boolean indicating whether an object is extensible.\n","Object.isFrozen":"\nObject.isFrozen( obj:Object )\n    Returns a boolean indicating whether an object is frozen.\n","Object.isSealed":"\nObject.isSealed( obj:Object )\n    Returns a boolean indicating whether an object is sealed.\n","Object.keys":"\nObject.keys( obj:Object )\n    Returns an array of an object's own enumerable string-keyed property\n    names.\n","Object.preventExtensions":"\nObject.preventExtensions( obj:Object )\n    Prevents the addition of new properties to an object.\n","Object.seal":"\nObject.seal( obj:Object )\n    Prevents the addition of new properties to an object and marks all\n    existing properties as non-configurable.\n","Object.setPrototypeOf":"\nObject.setPrototypeOf( obj:Object, proto:Object )\n    Sets an object's prototype.\n","Object.values":"\nObject.values( obj:Object )\n    Returns an array of an object's own enumerable property values.\n","Object.prototype.toLocaleString":"\nObject.prototype.toLocaleString()\n    Returns a string representing the object.\n","Object.prototype.toString":"\nObject.prototype.toString()\n    Returns a string representing the object.\n","Object.prototype.valueOf":"\nObject.prototype.valueOf()\n    Returns the primitive value of the object.\n","Object.prototype.hasOwnProperty":"\nObject.prototype.hasOwnProperty( p:string )\n    Returns a boolean indicating whether an object has a property with the\n    specified name.\n","Object.prototype.isPrototypeOf":"\nObject.prototype.isPrototypeOf( obj:Object )\n    Returns a boolean indicating whether an object exists in another object's\n    prototype chain.\n","Object.prototype.propertyIsEnumerable":"\nObject.prototype.propertyIsEnumerable( p:string )\n    Returns a boolean indicating whether an object's property is enumerable.\n","Object.prototype.constructor":"\nObject.prototype.constructor\n    Property whose value is a reference to the constructor function that\n    created the instance object.\n","objectEntries":"\nobjectEntries( obj:ObjectLike )\n    Returns an array of an object's own enumerable property `[key, value]`\n    pairs.\n","objectEntriesIn":"\nobjectEntriesIn( obj:ObjectLike )\n    Returns an array of an object's own and inherited enumerable property\n    `[key, value]` pairs.\n","objectFromEntries":"\nobjectFromEntries( entries:Array<Array> )\n    Creates an object from an array of key-value pairs.\n","objectInverse":"\nobjectInverse( obj:ObjectLike[, options:Object] )\n    Inverts an object, such that keys become values and values become keys.\n","objectInverseBy":"\nobjectInverseBy( obj:ObjectLike, [options:Object,] transform:Function )\n    Inverts an object, such that keys become values and values become keys,\n    according to a transform function.\n","objectKeys":"\nobjectKeys( value:any )\n    Returns an array of an object's own enumerable property names.\n","objectValues":"\nobjectValues( obj:ObjectLike )\n    Returns an array of an object's own enumerable property values.\n","objectValuesIn":"\nobjectValuesIn( obj:ObjectLike )\n    Returns an array of an object's own and inherited enumerable property\n    values.\n","omit":"\nomit( obj:Object, keys:string|Array )\n    Returns a partial object copy excluding specified keys.\n","omitBy":"\nomitBy( obj:Object, predicate:Function )\n    Returns a partial object copy excluding properties for which a predicate\n    returns a truthy value.\n","open":"\nopen( path:string|Buffer[, flags:string|number[, mode:integer]], clbk:Function )\n    Asynchronously opens a file.\n","open.sync":"\nopen.sync( path:string|Buffer[, flags:string|number[, mode:integer]] )\n    Synchronously opens a file.\n","openURL":"\nopenURL( url:string )\n    Opens a URL in a user's default browser.\n","ordinalize":"\nordinalize( value:string|integer[, options:Object] )\n    Converts an integer to an ordinal string (e.g., `1st`, `2nd`, etc.).\n","PACE_BOSTON_HOUSE_PRICES":"\nPACE_BOSTON_HOUSE_PRICES()\n    Returns a (corrected) dataset derived from information collected by the US\n    Census Service concerning housing in Boston, Massachusetts (1978).\n","pad":"\npad( str:string, len:integer[, options:Object] )\n    Pads a `string` such that the padded `string` has length `len`.\n","padjust":"\npadjust( pvals:Array<number>, method:string[, comparisons:integer] )\n    Adjusts supplied p-values for multiple comparisons via a specified method.\n","papply":"\npapply( fcn:Function, ...args:any )\n    Returns a function of smaller arity by partially applying arguments.\n","papplyRight":"\npapplyRight( fcn:Function, ...args:any )\n    Returns a function of smaller arity by partially applying arguments from the\n    right.\n","parallel":"\nparallel( files:Array<string>, [options:Object,] clbk:Function )\n    Executes scripts in parallel.\n","parseJSON":"\nparseJSON( str:string[, reviver:Function] )\n    Attempts to parse a string as JSON.\n","pascalcase":"\npascalcase( str:string )\n    Converts a string to Pascal case.\n","PATH_DELIMITER":"\nPATH_DELIMITER\n    Platform-specific path delimiter.\n","PATH_DELIMITER_POSIX":"\nPATH_DELIMITER_POSIX\n    POSIX path delimiter.\n","PATH_DELIMITER_WIN32":"\nPATH_DELIMITER_WIN32\n    Windows path delimiter.\n","PATH_SEP":"\nPATH_SEP\n    Platform-specific path segment separator.\n","PATH_SEP_POSIX":"\nPATH_SEP_POSIX\n    POSIX path segment separator.\n","PATH_SEP_WIN32":"\nPATH_SEP_WIN32\n    Windows path segment separator.\n","pcorrtest":"\npcorrtest( x:Array<number>, y:Array<number>[, options:Object] )\n    Computes a Pearson product-moment correlation test between paired samples.\n","percentEncode":"\npercentEncode( str:string )\n    Percent-encodes a UTF-16 encoded string according to RFC 3986.\n","PHI":"\nPHI\n    Golden ratio.\n","PI":"\nPI\n    The mathematical constant `π`.\n","PI_SQUARED":"\nPI_SQUARED\n    Square of the mathematical constant `π`.\n","pick":"\npick( obj:Object, keys:string|Array )\n    Returns a partial object copy containing only specified keys.\n","pickArguments":"\npickArguments( fcn:Function, indices:Array<integer>[, thisArg:any] )\n    Returns a function that applies specified arguments to a provided function.\n","pickBy":"\npickBy( obj:Object, predicate:Function )\n    Returns a partial object copy containing properties for which a predicate\n    returns a truthy value.\n","PINF":"\nPINF\n    Double-precision floating-point positive infinity.\n","pkg2alias":"\npkg2alias( pkg:string )\n    Returns the alias associated with a specified package name.\n","pkg2related":"\npkg2related( pkg:string )\n    Returns package names related to a specified package name.\n","pkg2standalone":"\npkg2standalone( pkg:string )\n    Returns the standalone package name associated with a provided internal\n    package name.\n","PLATFORM":"\nPLATFORM\n    Platform on which the current process is running.\n","plot":"\nplot( [x:Array|Array, y:Array|Array,] [options:Object] )\n    Returns a plot instance for creating 2-dimensional plots.\n","Plot":"\nPlot( [x:Array|Array, y:Array|Array,] [options:Object] )\n    Returns a plot instance for creating 2-dimensional plots.\n","pluck":"\npluck( arr:Array, prop:string[, options:Object] )\n    Extracts a property value from each element of an object array.\n","pop":"\npop( collection:Array|TypedArray|Object )\n    Removes and returns the last element of a collection.\n","porterStemmer":"\nporterStemmer( word:string )\n    Extracts the stem of a given word.\n","prepend":"\nprepend( collection1:Array|TypedArray|Object, \n  collection2:Array|TypedArray|Object )\n    Adds the elements of one collection to the beginning of another collection.\n","prevGraphemeClusterBreak":"\nprevGraphemeClusterBreak( str:string[, fromIndex:integer] )\n    Returns the previous extended grapheme cluster break in a string before a\n    specified position.\n","PRIMES_100K":"\nPRIMES_100K()\n    Returns an array containing the first 100,000 prime numbers.\n","properties":"\nproperties( value:any )\n    Returns an array of an object's own enumerable and non-enumerable property\n    names and symbols.\n","propertiesIn":"\npropertiesIn( value:any )\n    Returns an array of an object's own and inherited property names and\n    symbols.\n","propertyDescriptor":"\npropertyDescriptor( value:any, property:string|symbol )\n    Returns a property descriptor for an object's own property.\n","propertyDescriptorIn":"\npropertyDescriptorIn( value:any, property:string|symbol )\n    Returns a property descriptor for an object's own or inherited property.\n","propertyDescriptors":"\npropertyDescriptors( value:any )\n    Returns an object's own property descriptors.\n","propertyDescriptorsIn":"\npropertyDescriptorsIn( value:any )\n    Returns an object's own and inherited property descriptors.\n","propertyNames":"\npropertyNames( value:any )\n    Returns an array of an object's own enumerable and non-enumerable property\n    names.\n","propertyNamesIn":"\npropertyNamesIn( value:any )\n    Returns an array of an object's own and inherited enumerable and non-\n    enumerable property names.\n","propertySymbols":"\npropertySymbols( value:any )\n    Returns an array of an object's own symbol properties.\n","propertySymbolsIn":"\npropertySymbolsIn( value:any )\n    Returns an array of an object's own and inherited symbol properties.\n","Proxy":"\nProxy( target:Object, handlers:Object )\n    Returns a proxy object implementing custom behavior for specified object\n    operations.\n","Proxy.revocable":"\nProxy.revocable( target:Object, handlers:Object )\n    Returns a revocable proxy object.\n","push":"\npush( collection:Array|TypedArray|Object, ...items:any )\n    Adds one or more elements to the end of a collection.\n","quarterOfYear":"\nquarterOfYear( [month:integer|string|Date] )\n    Returns the quarter of the year.\n","random.array.arcsine":"\nrandom.array.arcsine( len:integer, a:number, b:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from an arcsine\n    distribution.\n","random.array.arcsine.assign":"\nrandom.array.arcsine.assign( a:number, b:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from an arcsine distribution.\n","random.array.arcsine.factory":"\nrandom.array.arcsine.factory( [a:number, b:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an arcsine distribution.\n","random.array.arcsine.PRNG":"\nrandom.array.arcsine.PRNG\n    Underlying pseudorandom number generator.\n","random.array.arcsine.seed":"\nrandom.array.arcsine.seed\n    Pseudorandom number generator seed.\n","random.array.arcsine.seedLength":"\nrandom.array.arcsine.seedLength\n    Length of generator seed.\n","random.array.arcsine.state":"\nrandom.array.arcsine.state\n    Generator state.\n","random.array.arcsine.stateLength":"\nrandom.array.arcsine.stateLength\n    Length of generator state.\n","random.array.arcsine.byteLength":"\nrandom.array.arcsine.byteLength\n    Size (in bytes) of generator state.\n","random.array.bernoulli":"\nrandom.array.bernoulli( len:integer, p:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a Bernoulli\n    distribution.\n","random.array.bernoulli.assign":"\nrandom.array.bernoulli.assign( p:number, out:Array|TypedArray )\n    Fills an array with pseudorandom numbers drawn from a Bernoulli\n    distribution.\n","random.array.bernoulli.factory":"\nrandom.array.bernoulli.factory( [p:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Bernoulli distribution.\n","random.array.bernoulli.PRNG":"\nrandom.array.bernoulli.PRNG\n    Underlying pseudorandom number generator.\n","random.array.bernoulli.seed":"\nrandom.array.bernoulli.seed\n    Pseudorandom number generator seed.\n","random.array.bernoulli.seedLength":"\nrandom.array.bernoulli.seedLength\n    Length of generator seed.\n","random.array.bernoulli.state":"\nrandom.array.bernoulli.state\n    Generator state.\n","random.array.bernoulli.stateLength":"\nrandom.array.bernoulli.stateLength\n    Length of generator state.\n","random.array.bernoulli.byteLength":"\nrandom.array.bernoulli.byteLength\n    Size (in bytes) of generator state.\n","random.array.beta":"\nrandom.array.beta( len:integer, alpha:number, beta:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a beta\n    distribution.\n","random.array.beta.assign":"\nrandom.array.beta.assign( alpha:number, beta:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a beta distribution.\n","random.array.beta.factory":"\nrandom.array.beta.factory( [alpha:number, beta:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a beta distribution.\n","random.array.beta.PRNG":"\nrandom.array.beta.PRNG\n    Underlying pseudorandom number generator.\n","random.array.beta.seed":"\nrandom.array.beta.seed\n    Pseudorandom number generator seed.\n","random.array.beta.seedLength":"\nrandom.array.beta.seedLength\n    Length of generator seed.\n","random.array.beta.state":"\nrandom.array.beta.state\n    Generator state.\n","random.array.beta.stateLength":"\nrandom.array.beta.stateLength\n    Length of generator state.\n","random.array.beta.byteLength":"\nrandom.array.beta.byteLength\n    Size (in bytes) of generator state.\n","random.array.betaprime":"\nrandom.array.betaprime( len:integer, alpha:number, beta:number[, \n  options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a beta prime\n    distribution.\n","random.array.betaprime.assign":"\nrandom.array.betaprime.assign( alpha:number, beta:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a beta prime\n    distribution.\n","random.array.betaprime.factory":"\nrandom.array.betaprime.factory( [alpha:number, beta:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a beta prime distribution.\n","random.array.betaprime.PRNG":"\nrandom.array.betaprime.PRNG\n    Underlying pseudorandom number generator.\n","random.array.betaprime.seed":"\nrandom.array.betaprime.seed\n    Pseudorandom number generator seed.\n","random.array.betaprime.seedLength":"\nrandom.array.betaprime.seedLength\n    Length of generator seed.\n","random.array.betaprime.state":"\nrandom.array.betaprime.state\n    Generator state.\n","random.array.betaprime.stateLength":"\nrandom.array.betaprime.stateLength\n    Length of generator state.\n","random.array.betaprime.byteLength":"\nrandom.array.betaprime.byteLength\n    Size (in bytes) of generator state.\n","random.array.binomial":"\nrandom.array.binomial( len:integer, n:number, p:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a binomial\n    distribution.\n","random.array.binomial.assign":"\nrandom.array.binomial.assign( n:number, p:number, out:Array|TypedArray )\n    Fills an array with pseudorandom numbers drawn from a binomial distribution.\n","random.array.binomial.factory":"\nrandom.array.binomial.factory( [n:number, p:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a binomial distribution.\n","random.array.binomial.PRNG":"\nrandom.array.binomial.PRNG\n    Underlying pseudorandom number generator.\n","random.array.binomial.seed":"\nrandom.array.binomial.seed\n    Pseudorandom number generator seed.\n","random.array.binomial.seedLength":"\nrandom.array.binomial.seedLength\n    Length of generator seed.\n","random.array.binomial.state":"\nrandom.array.binomial.state\n    Generator state.\n","random.array.binomial.stateLength":"\nrandom.array.binomial.stateLength\n    Length of generator state.\n","random.array.binomial.byteLength":"\nrandom.array.binomial.byteLength\n    Size (in bytes) of generator state.\n","random.array.cauchy":"\nrandom.array.cauchy( len:integer, x0:number, gamma:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a Cauchy\n    distribution.\n","random.array.cauchy.assign":"\nrandom.array.cauchy.assign( x0:number, gamma:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a Cauchy distribution.\n","random.array.cauchy.factory":"\nrandom.array.cauchy.factory( [x0:number, gamma:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Cauchy distribution.\n","random.array.cauchy.PRNG":"\nrandom.array.cauchy.PRNG\n    Underlying pseudorandom number generator.\n","random.array.cauchy.seed":"\nrandom.array.cauchy.seed\n    Pseudorandom number generator seed.\n","random.array.cauchy.seedLength":"\nrandom.array.cauchy.seedLength\n    Length of generator seed.\n","random.array.cauchy.state":"\nrandom.array.cauchy.state\n    Generator state.\n","random.array.cauchy.stateLength":"\nrandom.array.cauchy.stateLength\n    Length of generator state.\n","random.array.cauchy.byteLength":"\nrandom.array.cauchy.byteLength\n    Size (in bytes) of generator state.\n","random.array.chi":"\nrandom.array.chi( len:integer, k:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a chi\n    distribution.\n","random.array.chi.assign":"\nrandom.array.chi.assign( k:number, out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a chi distribution.\n","random.array.chi.factory":"\nrandom.array.chi.factory( [k:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a chi distribution.\n","random.array.chi.PRNG":"\nrandom.array.chi.PRNG\n    Underlying pseudorandom number generator.\n","random.array.chi.seed":"\nrandom.array.chi.seed\n    Pseudorandom number generator seed.\n","random.array.chi.seedLength":"\nrandom.array.chi.seedLength\n    Length of generator seed.\n","random.array.chi.state":"\nrandom.array.chi.state\n    Generator state.\n","random.array.chi.stateLength":"\nrandom.array.chi.stateLength\n    Length of generator state.\n","random.array.chi.byteLength":"\nrandom.array.chi.byteLength\n    Size (in bytes) of generator state.\n","random.array.chisquare":"\nrandom.array.chisquare( len:integer, k:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a chi-square\n    distribution.\n","random.array.chisquare.assign":"\nrandom.array.chisquare.assign( k:number, out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a chi-square\n    distribution.\n","random.array.chisquare.factory":"\nrandom.array.chisquare.factory( [k:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a chi-square distribution.\n","random.array.chisquare.PRNG":"\nrandom.array.chisquare.PRNG\n    Underlying pseudorandom number generator.\n","random.array.chisquare.seed":"\nrandom.array.chisquare.seed\n    Pseudorandom number generator seed.\n","random.array.chisquare.seedLength":"\nrandom.array.chisquare.seedLength\n    Length of generator seed.\n","random.array.chisquare.state":"\nrandom.array.chisquare.state\n    Generator state.\n","random.array.chisquare.stateLength":"\nrandom.array.chisquare.stateLength\n    Length of generator state.\n","random.array.chisquare.byteLength":"\nrandom.array.chisquare.byteLength\n    Size (in bytes) of generator state.\n","random.array.cosine":"\nrandom.array.cosine( len:integer, mu:number, s:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a raised cosine\n    distribution.\n","random.array.cosine.assign":"\nrandom.array.cosine.assign( mu:number, s:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a raised cosine\n    distribution.\n","random.array.cosine.factory":"\nrandom.array.cosine.factory( [mu:number, s:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a raised cosine distribution.\n","random.array.cosine.PRNG":"\nrandom.array.cosine.PRNG\n    Underlying pseudorandom number generator.\n","random.array.cosine.seed":"\nrandom.array.cosine.seed\n    Pseudorandom number generator seed.\n","random.array.cosine.seedLength":"\nrandom.array.cosine.seedLength\n    Length of generator seed.\n","random.array.cosine.state":"\nrandom.array.cosine.state\n    Generator state.\n","random.array.cosine.stateLength":"\nrandom.array.cosine.stateLength\n    Length of generator state.\n","random.array.cosine.byteLength":"\nrandom.array.cosine.byteLength\n    Size (in bytes) of generator state.\n","random.array.discreteUniform":"\nrandom.array.discreteUniform( len:integer, a:number, b:number[, \n  options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a discrete\n    uniform distribution.\n","random.array.discreteUniform.assign":"\nrandom.array.discreteUniform.assign( a:number, b:number, out:Array|TypedArray )\n    Fills an array with pseudorandom numbers drawn from a discrete uniform\n    distribution.\n","random.array.discreteUniform.factory":"\nrandom.array.discreteUniform.factory( [a:number, b:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a discrete uniform distribution.\n","random.array.discreteUniform.PRNG":"\nrandom.array.discreteUniform.PRNG\n    Underlying pseudorandom number generator.\n","random.array.discreteUniform.seed":"\nrandom.array.discreteUniform.seed\n    Pseudorandom number generator seed.\n","random.array.discreteUniform.seedLength":"\nrandom.array.discreteUniform.seedLength\n    Length of generator seed.\n","random.array.discreteUniform.state":"\nrandom.array.discreteUniform.state\n    Generator state.\n","random.array.discreteUniform.stateLength":"\nrandom.array.discreteUniform.stateLength\n    Length of generator state.\n","random.array.discreteUniform.byteLength":"\nrandom.array.discreteUniform.byteLength\n    Size (in bytes) of generator state.\n","random.array.erlang":"\nrandom.array.erlang( len:integer, k:number, lambda:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from an Erlang\n    distribution.\n","random.array.erlang.assign":"\nrandom.array.erlang.assign( k:number, lambda:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from an Erlang distribution.\n","random.array.erlang.factory":"\nrandom.array.erlang.factory( [k:number, lambda:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an Erlang distribution.\n","random.array.erlang.PRNG":"\nrandom.array.erlang.PRNG\n    Underlying pseudorandom number generator.\n","random.array.erlang.seed":"\nrandom.array.erlang.seed\n    Pseudorandom number generator seed.\n","random.array.erlang.seedLength":"\nrandom.array.erlang.seedLength\n    Length of generator seed.\n","random.array.erlang.state":"\nrandom.array.erlang.state\n    Generator state.\n","random.array.erlang.stateLength":"\nrandom.array.erlang.stateLength\n    Length of generator state.\n","random.array.erlang.byteLength":"\nrandom.array.erlang.byteLength\n    Size (in bytes) of generator state.\n","random.array.exponential":"\nrandom.array.exponential( len:integer, lambda:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from an exponential\n    distribution.\n","random.array.exponential.assign":"\nrandom.array.exponential.assign( lambda:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from an exponential\n    distribution.\n","random.array.exponential.factory":"\nrandom.array.exponential.factory( [lambda:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an exponential distribution.\n","random.array.exponential.PRNG":"\nrandom.array.exponential.PRNG\n    Underlying pseudorandom number generator.\n","random.array.exponential.seed":"\nrandom.array.exponential.seed\n    Pseudorandom number generator seed.\n","random.array.exponential.seedLength":"\nrandom.array.exponential.seedLength\n    Length of generator seed.\n","random.array.exponential.state":"\nrandom.array.exponential.state\n    Generator state.\n","random.array.exponential.stateLength":"\nrandom.array.exponential.stateLength\n    Length of generator state.\n","random.array.exponential.byteLength":"\nrandom.array.exponential.byteLength\n    Size (in bytes) of generator state.\n","random.array.f":"\nrandom.array.f( len:integer, d1:number, d2:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from an F\n    distribution.\n","random.array.f.assign":"\nrandom.array.f.assign( d1:number, d2:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from an F distribution.\n","random.array.f.factory":"\nrandom.array.f.factory( [d1:number, d2:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an F distribution.\n","random.array.f.PRNG":"\nrandom.array.f.PRNG\n    Underlying pseudorandom number generator.\n","random.array.f.seed":"\nrandom.array.f.seed\n    Pseudorandom number generator seed.\n","random.array.f.seedLength":"\nrandom.array.f.seedLength\n    Length of generator seed.\n","random.array.f.state":"\nrandom.array.f.state\n    Generator state.\n","random.array.f.stateLength":"\nrandom.array.f.stateLength\n    Length of generator state.\n","random.array.f.byteLength":"\nrandom.array.f.byteLength\n    Size (in bytes) of generator state.\n","random.array.frechet":"\nrandom.array.frechet( len:integer, alpha:number, s:number, m:number[, \n  options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a Fréchet\n    distribution.\n","random.array.frechet.assign":"\nrandom.array.frechet.assign( alpha:number, s:number, m:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a Fréchet distribution.\n","random.array.frechet.factory":"\nrandom.array.frechet.factory( [alpha:number, s:number, m:number, ]\n  [options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Fréchet distribution.\n","random.array.frechet.PRNG":"\nrandom.array.frechet.PRNG\n    Underlying pseudorandom number generator.\n","random.array.frechet.seed":"\nrandom.array.frechet.seed\n    Pseudorandom number generator seed.\n","random.array.frechet.seedLength":"\nrandom.array.frechet.seedLength\n    Length of generator seed.\n","random.array.frechet.state":"\nrandom.array.frechet.state\n    Generator state.\n","random.array.frechet.stateLength":"\nrandom.array.frechet.stateLength\n    Length of generator state.\n","random.array.frechet.byteLength":"\nrandom.array.frechet.byteLength\n    Size (in bytes) of generator state.\n","random.array.gamma":"\nrandom.array.gamma( len:integer, alpha:number, beta:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a gamma\n    distribution.\n","random.array.gamma.assign":"\nrandom.array.gamma.assign( alpha:number, beta:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a gamma distribution.\n","random.array.gamma.factory":"\nrandom.array.gamma.factory( [alpha:number, beta:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a gamma distribution.\n","random.array.gamma.PRNG":"\nrandom.array.gamma.PRNG\n    Underlying pseudorandom number generator.\n","random.array.gamma.seed":"\nrandom.array.gamma.seed\n    Pseudorandom number generator seed.\n","random.array.gamma.seedLength":"\nrandom.array.gamma.seedLength\n    Length of generator seed.\n","random.array.gamma.state":"\nrandom.array.gamma.state\n    Generator state.\n","random.array.gamma.stateLength":"\nrandom.array.gamma.stateLength\n    Length of generator state.\n","random.array.gamma.byteLength":"\nrandom.array.gamma.byteLength\n    Size (in bytes) of generator state.\n","random.array.geometric":"\nrandom.array.geometric( len:integer, p:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a geometric\n    distribution.\n","random.array.geometric.assign":"\nrandom.array.geometric.assign( p:number, out:Array|TypedArray )\n    Fills an array with pseudorandom numbers drawn from a geometric\n    distribution.\n","random.array.geometric.factory":"\nrandom.array.geometric.factory( [p:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a geometric distribution.\n","random.array.geometric.PRNG":"\nrandom.array.geometric.PRNG\n    Underlying pseudorandom number generator.\n","random.array.geometric.seed":"\nrandom.array.geometric.seed\n    Pseudorandom number generator seed.\n","random.array.geometric.seedLength":"\nrandom.array.geometric.seedLength\n    Length of generator seed.\n","random.array.geometric.state":"\nrandom.array.geometric.state\n    Generator state.\n","random.array.geometric.stateLength":"\nrandom.array.geometric.stateLength\n    Length of generator state.\n","random.array.geometric.byteLength":"\nrandom.array.geometric.byteLength\n    Size (in bytes) of generator state.\n","random.array.gumbel":"\nrandom.array.gumbel( len:integer, mu:number, beta:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a Gumbel\n    distribution.\n","random.array.gumbel.assign":"\nrandom.array.gumbel.assign( mu:number, beta:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a Gumbel distribution.\n","random.array.gumbel.factory":"\nrandom.array.gumbel.factory( [mu:number, beta:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Gumbel distribution.\n","random.array.gumbel.PRNG":"\nrandom.array.gumbel.PRNG\n    Underlying pseudorandom number generator.\n","random.array.gumbel.seed":"\nrandom.array.gumbel.seed\n    Pseudorandom number generator seed.\n","random.array.gumbel.seedLength":"\nrandom.array.gumbel.seedLength\n    Length of generator seed.\n","random.array.gumbel.state":"\nrandom.array.gumbel.state\n    Generator state.\n","random.array.gumbel.stateLength":"\nrandom.array.gumbel.stateLength\n    Length of generator state.\n","random.array.gumbel.byteLength":"\nrandom.array.gumbel.byteLength\n    Size (in bytes) of generator state.\n","random.array.hypergeometric":"\nrandom.array.hypergeometric( len:integer, N:number, K:number, n:number[, \n  options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a hypergeometric\n    distribution.\n","random.array.hypergeometric.assign":"\nrandom.array.hypergeometric.assign( N:number, K:number, n:number, \n  out:Array|TypedArray )\n    Fills an array with pseudorandom numbers drawn from a hypergeometric\n    distribution.\n","random.array.hypergeometric.factory":"\nrandom.array.hypergeometric.factory( [N:number, K:number, n:number, ]\n  [options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a hypergeometric distribution.\n","random.array.hypergeometric.PRNG":"\nrandom.array.hypergeometric.PRNG\n    Underlying pseudorandom number generator.\n","random.array.hypergeometric.seed":"\nrandom.array.hypergeometric.seed\n    Pseudorandom number generator seed.\n","random.array.hypergeometric.seedLength":"\nrandom.array.hypergeometric.seedLength\n    Length of generator seed.\n","random.array.hypergeometric.state":"\nrandom.array.hypergeometric.state\n    Generator state.\n","random.array.hypergeometric.stateLength":"\nrandom.array.hypergeometric.stateLength\n    Length of generator state.\n","random.array.hypergeometric.byteLength":"\nrandom.array.hypergeometric.byteLength\n    Size (in bytes) of generator state.\n","random.array.invgamma":"\nrandom.array.invgamma( len:integer, alpha:number, beta:number[, \n  options:Object] )\n    Returns an array containing pseudorandom numbers drawn from an inverse gamma\n    distribution.\n","random.array.invgamma.assign":"\nrandom.array.invgamma.assign( alpha:number, beta:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from an inverse gamma\n    distribution.\n","random.array.invgamma.factory":"\nrandom.array.invgamma.factory( [alpha:number, beta:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an inverse gamma distribution.\n","random.array.invgamma.PRNG":"\nrandom.array.invgamma.PRNG\n    Underlying pseudorandom number generator.\n","random.array.invgamma.seed":"\nrandom.array.invgamma.seed\n    Pseudorandom number generator seed.\n","random.array.invgamma.seedLength":"\nrandom.array.invgamma.seedLength\n    Length of generator seed.\n","random.array.invgamma.state":"\nrandom.array.invgamma.state\n    Generator state.\n","random.array.invgamma.stateLength":"\nrandom.array.invgamma.stateLength\n    Length of generator state.\n","random.array.invgamma.byteLength":"\nrandom.array.invgamma.byteLength\n    Size (in bytes) of generator state.\n","random.array.kumaraswamy":"\nrandom.array.kumaraswamy( len:integer, a:number, b:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from Kumaraswamy's\n    double bounded distribution.\n","random.array.kumaraswamy.assign":"\nrandom.array.kumaraswamy.assign( a:number, b:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from Kumaraswamy's double\n    bounded distribution.\n","random.array.kumaraswamy.factory":"\nrandom.array.kumaraswamy.factory( [a:number, b:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from Kumaraswamy's double bounded distribution.\n","random.array.kumaraswamy.PRNG":"\nrandom.array.kumaraswamy.PRNG\n    Underlying pseudorandom number generator.\n","random.array.kumaraswamy.seed":"\nrandom.array.kumaraswamy.seed\n    Pseudorandom number generator seed.\n","random.array.kumaraswamy.seedLength":"\nrandom.array.kumaraswamy.seedLength\n    Length of generator seed.\n","random.array.kumaraswamy.state":"\nrandom.array.kumaraswamy.state\n    Generator state.\n","random.array.kumaraswamy.stateLength":"\nrandom.array.kumaraswamy.stateLength\n    Length of generator state.\n","random.array.kumaraswamy.byteLength":"\nrandom.array.kumaraswamy.byteLength\n    Size (in bytes) of generator state.\n","random.array.laplace":"\nrandom.array.laplace( len:integer, mu:number, b:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a Laplace\n    (double exponential) distribution.\n","random.array.laplace.assign":"\nrandom.array.laplace.assign( mu:number, b:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a Laplace (double\n    exponential) distribution.\n","random.array.laplace.factory":"\nrandom.array.laplace.factory( [mu:number, b:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Laplace (double exponential) distribution.\n","random.array.laplace.PRNG":"\nrandom.array.laplace.PRNG\n    Underlying pseudorandom number generator.\n","random.array.laplace.seed":"\nrandom.array.laplace.seed\n    Pseudorandom number generator seed.\n","random.array.laplace.seedLength":"\nrandom.array.laplace.seedLength\n    Length of generator seed.\n","random.array.laplace.state":"\nrandom.array.laplace.state\n    Generator state.\n","random.array.laplace.stateLength":"\nrandom.array.laplace.stateLength\n    Length of generator state.\n","random.array.laplace.byteLength":"\nrandom.array.laplace.byteLength\n    Size (in bytes) of generator state.\n","random.array.levy":"\nrandom.array.levy( len:integer, mu:number, c:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a Lévy\n    distribution.\n","random.array.levy.assign":"\nrandom.array.levy.assign( mu:number, c:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a Lévy distribution.\n","random.array.levy.factory":"\nrandom.array.levy.factory( [mu:number, c:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Lévy distribution.\n","random.array.levy.PRNG":"\nrandom.array.levy.PRNG\n    Underlying pseudorandom number generator.\n","random.array.levy.seed":"\nrandom.array.levy.seed\n    Pseudorandom number generator seed.\n","random.array.levy.seedLength":"\nrandom.array.levy.seedLength\n    Length of generator seed.\n","random.array.levy.state":"\nrandom.array.levy.state\n    Generator state.\n","random.array.levy.stateLength":"\nrandom.array.levy.stateLength\n    Length of generator state.\n","random.array.levy.byteLength":"\nrandom.array.levy.byteLength\n    Size (in bytes) of generator state.\n","random.array.logistic":"\nrandom.array.logistic( len:integer, mu:number, s:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a logistic\n    distribution.\n","random.array.logistic.assign":"\nrandom.array.logistic.assign( mu:number, s:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a logistic distribution.\n","random.array.logistic.factory":"\nrandom.array.logistic.factory( [mu:number, s:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a logistic distribution.\n","random.array.logistic.PRNG":"\nrandom.array.logistic.PRNG\n    Underlying pseudorandom number generator.\n","random.array.logistic.seed":"\nrandom.array.logistic.seed\n    Pseudorandom number generator seed.\n","random.array.logistic.seedLength":"\nrandom.array.logistic.seedLength\n    Length of generator seed.\n","random.array.logistic.state":"\nrandom.array.logistic.state\n    Generator state.\n","random.array.logistic.stateLength":"\nrandom.array.logistic.stateLength\n    Length of generator state.\n","random.array.logistic.byteLength":"\nrandom.array.logistic.byteLength\n    Size (in bytes) of generator state.\n","random.array.lognormal":"\nrandom.array.lognormal( len:integer, mu:number, sigma:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a lognormal\n    distribution.\n","random.array.lognormal.assign":"\nrandom.array.lognormal.assign( mu:number, sigma:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a lognormal\n    distribution.\n","random.array.lognormal.factory":"\nrandom.array.lognormal.factory( [mu:number, sigma:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a lognormal distribution.\n","random.array.lognormal.PRNG":"\nrandom.array.lognormal.PRNG\n    Underlying pseudorandom number generator.\n","random.array.lognormal.seed":"\nrandom.array.lognormal.seed\n    Pseudorandom number generator seed.\n","random.array.lognormal.seedLength":"\nrandom.array.lognormal.seedLength\n    Length of generator seed.\n","random.array.lognormal.state":"\nrandom.array.lognormal.state\n    Generator state.\n","random.array.lognormal.stateLength":"\nrandom.array.lognormal.stateLength\n    Length of generator state.\n","random.array.lognormal.byteLength":"\nrandom.array.lognormal.byteLength\n    Size (in bytes) of generator state.\n","random.array.minstd":"\nrandom.array.minstd( len:integer[, options:Object] )\n    Returns an array containing pseudorandom integers on the interval\n    `[1, 2147483646]`.\n","random.array.minstd.normalized":"\nrandom.array.minstd.normalized( len:integer[, options:Object] )\n    Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n","random.array.minstd.factory":"\nrandom.array.minstd.factory( [options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers\n    generated using a linear congruential pseudorandom number generator (LCG).\n","random.array.minstd.PRNG":"\nrandom.array.minstd.PRNG\n    Underlying pseudorandom number generator.\n","random.array.minstd.seed":"\nrandom.array.minstd.seed\n    Pseudorandom number generator seed.\n","random.array.minstd.seedLength":"\nrandom.array.minstd.seedLength\n    Length of generator seed.\n","random.array.minstd.state":"\nrandom.array.minstd.state\n    Generator state.\n","random.array.minstd.stateLength":"\nrandom.array.minstd.stateLength\n    Length of generator state.\n","random.array.minstd.byteLength":"\nrandom.array.minstd.byteLength\n    Size (in bytes) of generator state.\n","random.array.minstdShuffle":"\nrandom.array.minstdShuffle( len:integer[, options:Object] )\n    Returns an array containing pseudorandom integers on the interval\n    `[1, 2147483646]`.\n","random.array.minstdShuffle.normalized":"\nrandom.array.minstdShuffle.normalized( len:integer[, options:Object] )\n    Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n","random.array.minstdShuffle.factory":"\nrandom.array.minstdShuffle.factory( [options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers\n    generated using a linear congruential pseudorandom number generator (LCG)\n    whose output is shuffled.\n","random.array.minstdShuffle.PRNG":"\nrandom.array.minstdShuffle.PRNG\n    Underlying pseudorandom number generator.\n","random.array.minstdShuffle.seed":"\nrandom.array.minstdShuffle.seed\n    Pseudorandom number generator seed.\n","random.array.minstdShuffle.seedLength":"\nrandom.array.minstdShuffle.seedLength\n    Length of generator seed.\n","random.array.minstdShuffle.state":"\nrandom.array.minstdShuffle.state\n    Generator state.\n","random.array.minstdShuffle.stateLength":"\nrandom.array.minstdShuffle.stateLength\n    Length of generator state.\n","random.array.minstdShuffle.byteLength":"\nrandom.array.minstdShuffle.byteLength\n    Size (in bytes) of generator state.\n","random.array.mt19937":"\nrandom.array.mt19937( len:integer[, options:Object] )\n    Returns an array containing pseudorandom integers on the interval\n    `[0, 4294967295]`.\n","random.array.mt19937.normalized":"\nrandom.array.mt19937.normalized( len:integer[, options:Object] )\n    Returns an array containing pseudorandom numbers on the interval `[0, 1)`\n    with 53-bit precision.\n","random.array.mt19937.factory":"\nrandom.array.mt19937.factory( [options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers\n    generated using a 32-bit Mersenne Twister pseudorandom number generator.\n","random.array.mt19937.PRNG":"\nrandom.array.mt19937.PRNG\n    Underlying pseudorandom number generator.\n","random.array.mt19937.seed":"\nrandom.array.mt19937.seed\n    Pseudorandom number generator seed.\n","random.array.mt19937.seedLength":"\nrandom.array.mt19937.seedLength\n    Length of generator seed.\n","random.array.mt19937.state":"\nrandom.array.mt19937.state\n    Generator state.\n","random.array.mt19937.stateLength":"\nrandom.array.mt19937.stateLength\n    Length of generator state.\n","random.array.mt19937.byteLength":"\nrandom.array.mt19937.byteLength\n    Size (in bytes) of generator state.\n","random.array.negativeBinomial":"\nrandom.array.negativeBinomial( len:integer, r:number, p:number[, \n  options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a negative\n    binomial distribution.\n","random.array.negativeBinomial.assign":"\nrandom.array.negativeBinomial.assign( r:number, p:number, out:Array|TypedArray )\n    Fills an array with pseudorandom numbers drawn from a negative binomial\n    distribution.\n","random.array.negativeBinomial.factory":"\nrandom.array.negativeBinomial.factory( [r:number, p:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a negative binomial distribution.\n","random.array.negativeBinomial.PRNG":"\nrandom.array.negativeBinomial.PRNG\n    Underlying pseudorandom number generator.\n","random.array.negativeBinomial.seed":"\nrandom.array.negativeBinomial.seed\n    Pseudorandom number generator seed.\n","random.array.negativeBinomial.seedLength":"\nrandom.array.negativeBinomial.seedLength\n    Length of generator seed.\n","random.array.negativeBinomial.state":"\nrandom.array.negativeBinomial.state\n    Generator state.\n","random.array.negativeBinomial.stateLength":"\nrandom.array.negativeBinomial.stateLength\n    Length of generator state.\n","random.array.negativeBinomial.byteLength":"\nrandom.array.negativeBinomial.byteLength\n    Size (in bytes) of generator state.\n","random.array.normal":"\nrandom.array.normal( len:integer, mu:number, sigma:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a normal\n    distribution.\n","random.array.normal.assign":"\nrandom.array.normal.assign( mu:number, sigma:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a normal distribution.\n","random.array.normal.factory":"\nrandom.array.normal.factory( [mu:number, sigma:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a normal distribution.\n","random.array.normal.PRNG":"\nrandom.array.normal.PRNG\n    Underlying pseudorandom number generator.\n","random.array.normal.seed":"\nrandom.array.normal.seed\n    Pseudorandom number generator seed.\n","random.array.normal.seedLength":"\nrandom.array.normal.seedLength\n    Length of generator seed.\n","random.array.normal.state":"\nrandom.array.normal.state\n    Generator state.\n","random.array.normal.stateLength":"\nrandom.array.normal.stateLength\n    Length of generator state.\n","random.array.normal.byteLength":"\nrandom.array.normal.byteLength\n    Size (in bytes) of generator state.\n","random.array.pareto1":"\nrandom.array.pareto1( len:integer, alpha:number, beta:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a Pareto (Type\n    I) distribution.\n","random.array.pareto1.assign":"\nrandom.array.pareto1.assign( alpha:number, beta:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a Pareto (Type I)\n    distribution.\n","random.array.pareto1.factory":"\nrandom.array.pareto1.factory( [alpha:number, beta:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Pareto (Type I) distribution.\n","random.array.pareto1.PRNG":"\nrandom.array.pareto1.PRNG\n    Underlying pseudorandom number generator.\n","random.array.pareto1.seed":"\nrandom.array.pareto1.seed\n    Pseudorandom number generator seed.\n","random.array.pareto1.seedLength":"\nrandom.array.pareto1.seedLength\n    Length of generator seed.\n","random.array.pareto1.state":"\nrandom.array.pareto1.state\n    Generator state.\n","random.array.pareto1.stateLength":"\nrandom.array.pareto1.stateLength\n    Length of generator state.\n","random.array.pareto1.byteLength":"\nrandom.array.pareto1.byteLength\n    Size (in bytes) of generator state.\n","random.array.poisson":"\nrandom.array.poisson( len:integer, lambda:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a Poisson\n    distribution.\n","random.array.poisson.assign":"\nrandom.array.poisson.assign( lambda:number, out:Array|TypedArray )\n    Fills an array with pseudorandom numbers drawn from a Poisson distribution.\n","random.array.poisson.factory":"\nrandom.array.poisson.factory( [lambda:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Poisson distribution.\n","random.array.poisson.PRNG":"\nrandom.array.poisson.PRNG\n    Underlying pseudorandom number generator.\n","random.array.poisson.seed":"\nrandom.array.poisson.seed\n    Pseudorandom number generator seed.\n","random.array.poisson.seedLength":"\nrandom.array.poisson.seedLength\n    Length of generator seed.\n","random.array.poisson.state":"\nrandom.array.poisson.state\n    Generator state.\n","random.array.poisson.stateLength":"\nrandom.array.poisson.stateLength\n    Length of generator state.\n","random.array.poisson.byteLength":"\nrandom.array.poisson.byteLength\n    Size (in bytes) of generator state.\n","random.array.randu":"\nrandom.array.randu( len:integer[, options:Object] )\n    Returns an array containing uniformly distributed pseudorandom numbers\n    between 0 and 1.\n","random.array.randu.factory":"\nrandom.array.randu.factory( [options:Object] )\n    Returns a function for creating arrays containing uniformly distributed\n    pseudorandom numbers between 0 and 1.\n","random.array.randu.PRNG":"\nrandom.array.randu.PRNG\n    Underlying pseudorandom number generator.\n","random.array.randu.seed":"\nrandom.array.randu.seed\n    Pseudorandom number generator seed.\n","random.array.randu.seedLength":"\nrandom.array.randu.seedLength\n    Length of generator seed.\n","random.array.randu.state":"\nrandom.array.randu.state\n    Generator state.\n","random.array.randu.stateLength":"\nrandom.array.randu.stateLength\n    Length of generator state.\n","random.array.randu.byteLength":"\nrandom.array.randu.byteLength\n    Size (in bytes) of generator state.\n","random.array.rayleigh":"\nrandom.array.rayleigh( len:integer, sigma:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a Rayleigh\n    distribution.\n","random.array.rayleigh.assign":"\nrandom.array.rayleigh.assign( sigma:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a Rayleigh distribution.\n","random.array.rayleigh.factory":"\nrandom.array.rayleigh.factory( [sigma:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Rayleigh distribution.\n","random.array.rayleigh.PRNG":"\nrandom.array.rayleigh.PRNG\n    Underlying pseudorandom number generator.\n","random.array.rayleigh.seed":"\nrandom.array.rayleigh.seed\n    Pseudorandom number generator seed.\n","random.array.rayleigh.seedLength":"\nrandom.array.rayleigh.seedLength\n    Length of generator seed.\n","random.array.rayleigh.state":"\nrandom.array.rayleigh.state\n    Generator state.\n","random.array.rayleigh.stateLength":"\nrandom.array.rayleigh.stateLength\n    Length of generator state.\n","random.array.rayleigh.byteLength":"\nrandom.array.rayleigh.byteLength\n    Size (in bytes) of generator state.\n","random.array.t":"\nrandom.array.t( len:integer, v:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a Student's t\n    distribution.\n","random.array.t.assign":"\nrandom.array.t.assign( v:number, out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a Student's t\n    distribution.\n","random.array.t.factory":"\nrandom.array.t.factory( [v:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Student's t distribution.\n","random.array.t.PRNG":"\nrandom.array.t.PRNG\n    Underlying pseudorandom number generator.\n","random.array.t.seed":"\nrandom.array.t.seed\n    Pseudorandom number generator seed.\n","random.array.t.seedLength":"\nrandom.array.t.seedLength\n    Length of generator seed.\n","random.array.t.state":"\nrandom.array.t.state\n    Generator state.\n","random.array.t.stateLength":"\nrandom.array.t.stateLength\n    Length of generator state.\n","random.array.t.byteLength":"\nrandom.array.t.byteLength\n    Size (in bytes) of generator state.\n","random.array.triangular":"\nrandom.array.triangular( len:integer, a:number, b:number, c:number[, \n  options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a triangular\n    distribution.\n","random.array.triangular.assign":"\nrandom.array.triangular.assign( a:number, b:number, c:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a triangular\n    distribution.\n","random.array.triangular.factory":"\nrandom.array.triangular.factory( [a:number, b:number, c:number, ]\n  [options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a triangular distribution.\n","random.array.triangular.PRNG":"\nrandom.array.triangular.PRNG\n    Underlying pseudorandom number generator.\n","random.array.triangular.seed":"\nrandom.array.triangular.seed\n    Pseudorandom number generator seed.\n","random.array.triangular.seedLength":"\nrandom.array.triangular.seedLength\n    Length of generator seed.\n","random.array.triangular.state":"\nrandom.array.triangular.state\n    Generator state.\n","random.array.triangular.stateLength":"\nrandom.array.triangular.stateLength\n    Length of generator state.\n","random.array.triangular.byteLength":"\nrandom.array.triangular.byteLength\n    Size (in bytes) of generator state.\n","random.array.uniform":"\nrandom.array.uniform( len:integer, a:number, b:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a continuous\n    uniform distribution.\n","random.array.uniform.assign":"\nrandom.array.uniform.assign( a:number, b:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a continuous uniform\n    distribution.\n","random.array.uniform.factory":"\nrandom.array.uniform.factory( [a:number, b:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a continuous uniform distribution.\n","random.array.uniform.PRNG":"\nrandom.array.uniform.PRNG\n    Underlying pseudorandom number generator.\n","random.array.uniform.seed":"\nrandom.array.uniform.seed\n    Pseudorandom number generator seed.\n","random.array.uniform.seedLength":"\nrandom.array.uniform.seedLength\n    Length of generator seed.\n","random.array.uniform.state":"\nrandom.array.uniform.state\n    Generator state.\n","random.array.uniform.stateLength":"\nrandom.array.uniform.stateLength\n    Length of generator state.\n","random.array.uniform.byteLength":"\nrandom.array.uniform.byteLength\n    Size (in bytes) of generator state.\n","random.array.weibull":"\nrandom.array.weibull( len:integer, k:number, lambda:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a Weibull\n    distribution.\n","random.array.weibull.assign":"\nrandom.array.weibull.assign( k:number, lambda:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a Weibull distribution.\n","random.array.weibull.factory":"\nrandom.array.weibull.factory( [k:number, lambda:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Weibull distribution.\n","random.array.weibull.PRNG":"\nrandom.array.weibull.PRNG\n    Underlying pseudorandom number generator.\n","random.array.weibull.seed":"\nrandom.array.weibull.seed\n    Pseudorandom number generator seed.\n","random.array.weibull.seedLength":"\nrandom.array.weibull.seedLength\n    Length of generator seed.\n","random.array.weibull.state":"\nrandom.array.weibull.state\n    Generator state.\n","random.array.weibull.stateLength":"\nrandom.array.weibull.stateLength\n    Length of generator state.\n","random.array.weibull.byteLength":"\nrandom.array.weibull.byteLength\n    Size (in bytes) of generator state.\n","random.iterators.arcsine":"\nrandom.iterators.arcsine( a:number, b:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from an\n    arcsine distribution.\n","random.iterators.bernoulli":"\nrandom.iterators.bernoulli( p:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Bernoulli distribution.\n","random.iterators.beta":"\nrandom.iterators.beta( α:number, β:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    beta distribution.\n","random.iterators.betaprime":"\nrandom.iterators.betaprime( α:number, β:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    beta prime distribution.\n","random.iterators.binomial":"\nrandom.iterators.binomial( n:integer, p:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    binomial distribution.\n","random.iterators.boxMuller":"\nrandom.iterators.boxMuller( [options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    standard normal distribution using the Box-Muller transform.\n","random.iterators.cauchy":"\nrandom.iterators.cauchy( x0:number, Ɣ:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Cauchy distribution.\n","random.iterators.chi":"\nrandom.iterators.chi( k:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a chi\n    distribution.\n","random.iterators.chisquare":"\nrandom.iterators.chisquare( k:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    chi-square distribution.\n","random.iterators.cosine":"\nrandom.iterators.cosine( μ:number, s:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a raised\n    cosine distribution.\n","random.iterators.discreteUniform":"\nrandom.iterators.discreteUniform( a:integer, b:integer[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    discrete uniform distribution.\n","random.iterators.erlang":"\nrandom.iterators.erlang( k:integer, λ:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from an Erlang\n    distribution.\n","random.iterators.exponential":"\nrandom.iterators.exponential( λ:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from an\n    exponential distribution.\n","random.iterators.f":"\nrandom.iterators.f( d1:number, d2:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from an F\n    distribution.\n","random.iterators.frechet":"\nrandom.iterators.frechet( α:number, s:number, m:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Fréchet\n    distribution.\n","random.iterators.gamma":"\nrandom.iterators.gamma( α:number, β:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a gamma\n    distribution.\n","random.iterators.geometric":"\nrandom.iterators.geometric( p:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    geometric distribution.\n","random.iterators.gumbel":"\nrandom.iterators.gumbel( μ:number, β:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Gumbel\n    distribution.\n","random.iterators.hypergeometric":"\nrandom.iterators.hypergeometric( N:integer, K:integer, n:integer[, \n  options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    hypergeometric distribution.\n","random.iterators.improvedZiggurat":"\nrandom.iterators.improvedZiggurat( [options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    standard normal distribution using the Improved Ziggurat algorithm.\n","random.iterators.invgamma":"\nrandom.iterators.invgamma( α:number, β:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from an\n    inverse gamma distribution.\n","random.iterators.kumaraswamy":"\nrandom.iterators.kumaraswamy( a:number, b:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Kumaraswamy's double bounded distribution.\n","random.iterators.laplace":"\nrandom.iterators.laplace( μ:number, b:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Laplace\n    (double exponential) distribution.\n","random.iterators.levy":"\nrandom.iterators.levy( μ:number, c:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Lévy\n    distribution.\n","random.iterators.logistic":"\nrandom.iterators.logistic( μ:number, s:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    logistic distribution.\n","random.iterators.lognormal":"\nrandom.iterators.lognormal( μ:number, σ:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    lognormal distribution.\n","random.iterators.minstd":"\nrandom.iterators.minstd( [options:Object] )\n    Returns an iterator for generating pseudorandom integers on the interval\n    `[1, 2147483646]`.\n","random.iterators.minstdShuffle":"\nrandom.iterators.minstdShuffle( [options:Object] )\n    Returns an iterator for generating pseudorandom integers on the interval\n    `[1, 2147483646]`.\n","random.iterators.mt19937":"\nrandom.iterators.mt19937( [options:Object] )\n    Returns an iterator for generating pseudorandom integers on the interval\n    `[1, 4294967295]`.\n","random.iterators.negativeBinomial":"\nrandom.iterators.negativeBinomial( r:number, p:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    negative binomial distribution.\n","random.iterators.normal":"\nrandom.iterators.normal( μ:number, σ:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a normal\n    distribution.\n","random.iterators.pareto1":"\nrandom.iterators.pareto1( α:number, β:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Pareto\n    (Type I) distribution.\n","random.iterators.poisson":"\nrandom.iterators.poisson( λ:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Poisson\n    distribution.\n","random.iterators.randi":"\nrandom.iterators.randi( [options:Object] )\n    Create an iterator for generating pseudorandom numbers having integer\n    values.\n","random.iterators.randn":"\nrandom.iterators.randn( [options:Object] )\n    Create an iterator for generating pseudorandom numbers drawn from a standard\n    normal distribution.\n","random.iterators.randu":"\nrandom.iterators.randu( [options:Object] )\n    Create an iterator for generating uniformly distributed pseudorandom numbers\n    between 0 and 1.\n","random.iterators.rayleigh":"\nrandom.iterators.rayleigh( σ:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Rayleigh distribution.\n","random.iterators.t":"\nrandom.iterators.t( v:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Student's t distribution.\n","random.iterators.triangular":"\nrandom.iterators.triangular( a:number, b:number, c:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    triangular distribution.\n","random.iterators.uniform":"\nrandom.iterators.uniform( a:number, b:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    continuous uniform distribution.\n","random.iterators.weibull":"\nrandom.iterators.weibull( k:number, λ:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Weibull distribution.\n","random.streams.arcsine":"\nrandom.streams.arcsine( a:number, b:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from an\n    arcsine distribution.\n","random.streams.arcsine.factory":"\nrandom.streams.arcsine.factory( [a:number, b:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an arcsine distribution.\n","random.streams.arcsine.objectMode":"\nrandom.streams.arcsine.objectMode( a:number, b:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an arcsine distribution.\n","random.streams.bernoulli":"\nrandom.streams.bernoulli( p:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Bernoulli distribution.\n","random.streams.bernoulli.factory":"\nrandom.streams.bernoulli.factory( [p:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Bernoulli distribution.\n","random.streams.bernoulli.objectMode":"\nrandom.streams.bernoulli.objectMode( p:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Bernoulli distribution.\n","random.streams.beta":"\nrandom.streams.beta( α:number, β:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    beta distribution.\n","random.streams.beta.factory":"\nrandom.streams.beta.factory( [α:number, β:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a beta distribution.\n","random.streams.beta.objectMode":"\nrandom.streams.beta.objectMode( α:number, β:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a beta distribution.\n","random.streams.betaprime":"\nrandom.streams.betaprime( α:number, β:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    beta prime distribution.\n","random.streams.betaprime.factory":"\nrandom.streams.betaprime.factory( [α:number, β:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a beta prime distribution.\n","random.streams.betaprime.objectMode":"\nrandom.streams.betaprime.objectMode( α:number, β:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a beta prime distribution.\n","random.streams.binomial":"\nrandom.streams.binomial( n:integer, p:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    binomial distribution.\n","random.streams.binomial.factory":"\nrandom.streams.binomial.factory( [n:integer, p:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a binomial distribution.\n","random.streams.binomial.objectMode":"\nrandom.streams.binomial.objectMode( n:integer, p:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a binomial distribution.\n","random.streams.boxMuller":"\nrandom.streams.boxMuller( [options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    standard normal distribution using the Box-Muller transform.\n","random.streams.boxMuller.factory":"\nrandom.streams.boxMuller.factory( [options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a standard normal distribution using the Box-Muller\n    transform.\n","random.streams.boxMuller.objectMode":"\nrandom.streams.boxMuller.objectMode( [options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a standard normal distribution using the Box-Muller transform.\n","random.streams.cauchy":"\nrandom.streams.cauchy( x0:number, γ:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Cauchy distribution.\n","random.streams.cauchy.factory":"\nrandom.streams.cauchy.factory( [x0:number, γ:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Cauchy distribution.\n","random.streams.cauchy.objectMode":"\nrandom.streams.cauchy.objectMode( x0:number, γ:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Cauchy distribution.\n","random.streams.chi":"\nrandom.streams.chi( k:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    chi distribution.\n","random.streams.chi.factory":"\nrandom.streams.chi.factory( [k:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a chi distribution.\n","random.streams.chi.objectMode":"\nrandom.streams.chi.objectMode( k:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a chi distribution.\n","random.streams.chisquare":"\nrandom.streams.chisquare( k:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    chi-square distribution.\n","random.streams.chisquare.factory":"\nrandom.streams.chisquare.factory( [k:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a chi-square distribution.\n","random.streams.chisquare.objectMode":"\nrandom.streams.chisquare.objectMode( k:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a chi-square distribution.\n","random.streams.cosine":"\nrandom.streams.cosine( μ:number, s:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    raised cosine distribution.\n","random.streams.cosine.factory":"\nrandom.streams.cosine.factory( [μ:number, s:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a raised cosine distribution.\n","random.streams.cosine.objectMode":"\nrandom.streams.cosine.objectMode( μ:number, s:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a raised cosine distribution.\n","random.streams.discreteUniform":"\nrandom.streams.discreteUniform( a:integer, b:integer[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    discrete uniform distribution.\n","random.streams.discreteUniform.factory":"\nrandom.streams.discreteUniform.factory( [a:integer, b:integer, ]\n  [options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a discrete uniform distribution.\n","random.streams.discreteUniform.objectMode":"\nrandom.streams.discreteUniform.objectMode( a:integer, b:integer[, \n  options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a discrete uniform distribution.\n","random.streams.erlang":"\nrandom.streams.erlang( k:integer, λ:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from an\n    Erlang distribution.\n","random.streams.erlang.factory":"\nrandom.streams.erlang.factory( [k:number, λ:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an Erlang distribution.\n","random.streams.erlang.objectMode":"\nrandom.streams.erlang.objectMode( k:number, λ:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an Erlang distribution.\n","random.streams.exponential":"\nrandom.streams.exponential( λ:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from an\n    exponential distribution.\n","random.streams.exponential.factory":"\nrandom.streams.exponential.factory( [λ:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an exponential distribution.\n","random.streams.exponential.objectMode":"\nrandom.streams.exponential.objectMode( λ:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an exponential distribution.\n","random.streams.f":"\nrandom.streams.f( d1:number, d2:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from an\n    F distribution.\n","random.streams.f.factory":"\nrandom.streams.f.factory( [d1:number, d2:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an F distribution.\n","random.streams.f.objectMode":"\nrandom.streams.f.objectMode( d1:number, d2:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an F distribution.\n","random.streams.frechet":"\nrandom.streams.frechet( α:number, s:number, m:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Fréchet distribution.\n","random.streams.frechet.factory":"\nrandom.streams.frechet.factory( [α:number, s:number, m:number,]\n  [options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Fréchet distribution.\n","random.streams.frechet.objectMode":"\nrandom.streams.frechet.objectMode( α:number, s:number, m:number[, \n  options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Fréchet distribution.\n","random.streams.gamma":"\nrandom.streams.gamma( α:number, β:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    gamma distribution.\n","random.streams.gamma.factory":"\nrandom.streams.gamma.factory( [α:number, β:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a gamma distribution.\n","random.streams.gamma.objectMode":"\nrandom.streams.gamma.objectMode( α:number, β:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a gamma distribution.\n","random.streams.geometric":"\nrandom.streams.geometric( p:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    geometric distribution.\n","random.streams.geometric.factory":"\nrandom.streams.geometric.factory( [p:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a geometric distribution.\n","random.streams.geometric.objectMode":"\nrandom.streams.geometric.objectMode( p:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a geometric distribution.\n","random.streams.gumbel":"\nrandom.streams.gumbel( μ:number, β:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Gumbel distribution.\n","random.streams.gumbel.factory":"\nrandom.streams.gumbel.factory( [μ:number, β:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Gumbel distribution.\n","random.streams.gumbel.objectMode":"\nrandom.streams.gumbel.objectMode( μ:number, β:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Gumbel distribution.\n","random.streams.hypergeometric":"\nrandom.streams.hypergeometric( N:integer, K:integer, n:integer[, \n  options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    hypergeometric distribution.\n","random.streams.hypergeometric.factory":"\nrandom.streams.hypergeometric.factory( [N:integer, K:integer, n:integer,]\n  [options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a hypergeometric distribution.\n","random.streams.hypergeometric.objectMode":"\nrandom.streams.hypergeometric.objectMode( N:integer, K:integer, n:integer[, \n  options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a hypergeometric distribution.\n","random.streams.improvedZiggurat":"\nrandom.streams.improvedZiggurat( [options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    standard normal distribution using the Improved Ziggurat algorithm.\n","random.streams.improvedZiggurat.factory":"\nrandom.streams.improvedZiggurat.factory( [options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a standard normal distribution using the Improved\n    Ziggurat algorithm.\n","random.streams.improvedZiggurat.objectMode":"\nrandom.streams.improvedZiggurat.objectMode( [options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a standard normal distribution using the Improved Ziggurat\n    algorithm.\n","random.streams.invgamma":"\nrandom.streams.invgamma( α:number, β:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from an\n    inverse gamma distribution.\n","random.streams.invgamma.factory":"\nrandom.streams.invgamma.factory( [α:number, β:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an inverse gamma distribution.\n","random.streams.invgamma.objectMode":"\nrandom.streams.invgamma.objectMode( α:number, β:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an inverse gamma distribution.\n","random.streams.kumaraswamy":"\nrandom.streams.kumaraswamy( a:number, b:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Kumaraswamy's double bounded distribution.\n","random.streams.kumaraswamy.factory":"\nrandom.streams.kumaraswamy.factory( [a:number, b:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Kumaraswamy's double bounded distribution.\n","random.streams.kumaraswamy.objectMode":"\nrandom.streams.kumaraswamy.objectMode( a:number, b:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Kumaraswamy's double bounded distribution.\n","random.streams.laplace":"\nrandom.streams.laplace( μ:number, b:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Laplace (double exponential) distribution.\n","random.streams.laplace.factory":"\nrandom.streams.laplace.factory( [μ:number, b:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Laplace (double exponential) distribution.\n","random.streams.laplace.objectMode":"\nrandom.streams.laplace.objectMode( μ:number, b:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Laplace (double exponential) distribution.\n","random.streams.levy":"\nrandom.streams.levy( μ:number, c:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Lévy distribution.\n","random.streams.levy.factory":"\nrandom.streams.levy.factory( [μ:number, c:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Lévy distribution.\n","random.streams.levy.objectMode":"\nrandom.streams.levy.objectMode( μ:number, c:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Lévy distribution.\n","random.streams.logistic":"\nrandom.streams.logistic( μ:number, s:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    logistic distribution.\n","random.streams.logistic.factory":"\nrandom.streams.logistic.factory( [μ:number, s:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a logistic distribution.\n","random.streams.logistic.objectMode":"\nrandom.streams.logistic.objectMode( μ:number, s:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a logistic distribution.\n","random.streams.lognormal":"\nrandom.streams.lognormal( μ:number, σ:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    lognormal distribution.\n","random.streams.lognormal.factory":"\nrandom.streams.lognormal.factory( [μ:number, σ:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a lognormal distribution.\n","random.streams.lognormal.objectMode":"\nrandom.streams.lognormal.objectMode( μ:number, σ:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a lognormal distribution.\n","random.streams.minstd":"\nrandom.streams.minstd( [options:Object] )\n    Returns a readable stream for generating pseudorandom numbers on the\n    interval `[1, 2147483646]`.\n","random.streams.minstd.factory":"\nrandom.streams.minstd.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers on the interval `[1, 2147483646]`.\n","random.streams.minstd.objectMode":"\nrandom.streams.minstd.objectMode( [options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    on the interval `[1, 2147483646]`.\n","random.streams.minstdShuffle":"\nrandom.streams.minstdShuffle( [options:Object] )\n    Returns a readable stream for generating pseudorandom numbers on the\n    interval `[1, 2147483646]`.\n","random.streams.minstdShuffle.factory":"\nrandom.streams.minstdShuffle.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers on the interval `[1, 2147483646]`.\n","random.streams.minstdShuffle.objectMode":"\nrandom.streams.minstdShuffle.objectMode( [options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    on the interval `[1, 2147483646]`.\n","random.streams.mt19937":"\nrandom.streams.mt19937( [options:Object] )\n    Returns a readable stream for generating pseudorandom numbers on the\n    interval `[1, 4294967295]`.\n","random.streams.mt19937.factory":"\nrandom.streams.mt19937.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers on the interval `[1, 4294967295]`.\n","random.streams.mt19937.objectMode":"\nrandom.streams.mt19937.objectMode( [options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    on the interval `[1, 4294967295]`.\n","random.streams.negativeBinomial":"\nrandom.streams.negativeBinomial( r:number, p:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    negative binomial distribution.\n","random.streams.negativeBinomial.factory":"\nrandom.streams.negativeBinomial.factory( [r:number, p:number, ]\n  [options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a negative binomial distribution.\n","random.streams.negativeBinomial.objectMode":"\nrandom.streams.negativeBinomial.objectMode( r:integer, p:number[, \n  options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a negative binomial distribution.\n","random.streams.normal":"\nrandom.streams.normal( μ:number, σ:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    normal distribution.\n","random.streams.normal.factory":"\nrandom.streams.normal.factory( [μ:number, σ:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a normal distribution.\n","random.streams.normal.objectMode":"\nrandom.streams.normal.objectMode( μ:number, σ:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a normal distribution.\n","random.streams.pareto1":"\nrandom.streams.pareto1( α:number, β:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Pareto (Type I) distribution.\n","random.streams.pareto1.factory":"\nrandom.streams.pareto1.factory( [α:number, β:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Pareto (Type I) distribution.\n","random.streams.pareto1.objectMode":"\nrandom.streams.pareto1.objectMode( α:number, β:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Pareto (Type I) distribution.\n","random.streams.poisson":"\nrandom.streams.poisson( λ:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Poisson distribution.\n","random.streams.poisson.factory":"\nrandom.streams.poisson.factory( [λ:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Poisson distribution.\n","random.streams.poisson.objectMode":"\nrandom.streams.poisson.objectMode( λ:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Poisson distribution.\n","random.streams.randi":"\nrandom.streams.randi( [options:Object] )\n    Returns a readable stream for generating pseudorandom numbers having integer\n    values.\n","random.streams.randi.factory":"\nrandom.streams.randi.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers having integer values.\n","random.streams.randi.objectMode":"\nrandom.streams.randi.objectMode( [options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    having integer values.\n","random.streams.randn":"\nrandom.streams.randn( [options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    standard normal distribution.\n","random.streams.randn.factory":"\nrandom.streams.randn.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a standard normal distribution.\n","random.streams.randn.objectMode":"\nrandom.streams.randn.objectMode( [options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a standard normal distribution.\n","random.streams.randu":"\nrandom.streams.randu( [options:Object] )\n    Returns a readable stream for generating uniformly distributed pseudorandom\n    numbers between 0 and 1.\n","random.streams.randu.factory":"\nrandom.streams.randu.factory( [options] )\n    Returns a function for creating readable streams which generate uniformly\n    distributed pseudorandom numbers between 0 and 1.\n","random.streams.randu.objectMode":"\nrandom.streams.randu.objectMode( [options:Object] )\n    Returns an \"objectMode\" readable stream for generating uniformly distributed\n    pseudorandom numbers between 0 and 1.\n","random.streams.rayleigh":"\nrandom.streams.rayleigh( σ:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Rayleigh distribution.\n","random.streams.rayleigh.factory":"\nrandom.streams.rayleigh.factory( [σ:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Rayleigh distribution.\n","random.streams.rayleigh.objectMode":"\nrandom.streams.rayleigh.objectMode( σ:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Rayleigh distribution.\n","random.streams.t":"\nrandom.streams.t( v:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Student's t distribution.\n","random.streams.t.factory":"\nrandom.streams.t.factory( [v:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Student's t distribution.\n","random.streams.t.objectMode":"\nrandom.streams.t.objectMode( v:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Student's t distribution.\n","random.streams.triangular":"\nrandom.streams.triangular( a:number, b:number, c:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    triangular distribution.\n","random.streams.triangular.factory":"\nrandom.streams.triangular.factory( [a:number, b:number, c:number, ]\n  [options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a triangular distribution.\n","random.streams.triangular.objectMode":"\nrandom.streams.triangular.objectMode( a:number, b:number, c:number[, \n  options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a triangular distribution.\n","random.streams.uniform":"\nrandom.streams.uniform( a:number, b:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    uniform distribution.\n","random.streams.uniform.factory":"\nrandom.streams.uniform.factory( [a:number, b:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a uniform distribution.\n","random.streams.uniform.objectMode":"\nrandom.streams.uniform.objectMode( a:number, b:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a uniform distribution.\n","random.streams.weibull":"\nrandom.streams.weibull( k:number, λ:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Weibull distribution.\n","random.streams.weibull.factory":"\nrandom.streams.weibull.factory( [k:number, λ:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Weibull distribution.\n","random.streams.weibull.objectMode":"\nrandom.streams.weibull.objectMode( k:number, λ:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Weibull distribution.\n","random.strided.arcsine":"\nrandom.strided.arcsine( N:integer, a:ArrayLikeObject, sa:integer, \n  b:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from an arcsine\n    distribution.\n","random.strided.arcsine.ndarray":"\nrandom.strided.arcsine.ndarray( N:integer, a:ArrayLikeObject, sa:integer, \n  oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, \n  so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from an arcsine\n    distribution using alternative indexing semantics.\n","random.strided.bernoulli":"\nrandom.strided.bernoulli( N:integer, p:ArrayLikeObject, sp:integer, \n  out:ArrayLikeObject, so:integer )\n    Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n    distribution.\n","random.strided.bernoulli.ndarray":"\nrandom.strided.bernoulli.ndarray( N:integer, p:ArrayLikeObject, sp:integer, \n  op:integer, out:ArrayLikeObject, so:integer, oo:integer )\n    Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n    distribution using alternative indexing semantics.\n","random.strided.bernoulli.factory":"\nrandom.strided.bernoulli.factory( [options:Object] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Bernoulli distribution.\n","random.strided.bernoulli.PRNG":"\nrandom.strided.bernoulli.PRNG\n    Underlying pseudorandom number generator.\n","random.strided.bernoulli.seed":"\nrandom.strided.bernoulli.seed\n    Pseudorandom number generator seed.\n","random.strided.bernoulli.seedLength":"\nrandom.strided.bernoulli.seedLength\n    Length of generator seed.\n","random.strided.bernoulli.state":"\nrandom.strided.bernoulli.state\n    Generator state.\n","random.strided.bernoulli.stateLength":"\nrandom.strided.bernoulli.stateLength\n    Length of generator state.\n","random.strided.bernoulli.byteLength":"\nrandom.strided.bernoulli.byteLength\n    Size (in bytes) of generator state.\n","random.strided.beta":"\nrandom.strided.beta( N:integer, alpha:ArrayLikeObject, sa:integer, \n  beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a beta\n    distribution.\n","random.strided.beta.ndarray":"\nrandom.strided.beta.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n  oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n  out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a beta\n    distribution using alternative indexing semantics.\n","random.strided.betaprime":"\nrandom.strided.betaprime( N:integer, alpha:ArrayLikeObject, sa:integer, \n  beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a beta prime\n    distribution.\n","random.strided.betaprime.ndarray":"\nrandom.strided.betaprime.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n  oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n  out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a beta prime\n    distribution using alternative indexing semantics.\n","random.strided.chi":"\nrandom.strided.chi( N:integer, k:ArrayLikeObject, sk:integer, \n  out:ArrayLikeObject, so:integer )\n    Fills a strided array with pseudorandom numbers drawn from a chi\n    distribution.\n","random.strided.chi.ndarray":"\nrandom.strided.chi.ndarray( N:integer, k:ArrayLikeObject, sk:integer, \n  ok:integer, out:ArrayLikeObject, so:integer, oo:integer )\n    Fills a strided array with pseudorandom numbers drawn from a chi\n    distribution using alternative indexing semantics.\n","random.strided.chi.factory":"\nrandom.strided.chi.factory( [options:Object] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a chi distribution.\n","random.strided.chi.PRNG":"\nrandom.strided.chi.PRNG\n    Underlying pseudorandom number generator.\n","random.strided.chi.seed":"\nrandom.strided.chi.seed\n    Pseudorandom number generator seed.\n","random.strided.chi.seedLength":"\nrandom.strided.chi.seedLength\n    Length of generator seed.\n","random.strided.chi.state":"\nrandom.strided.chi.state\n    Generator state.\n","random.strided.chi.stateLength":"\nrandom.strided.chi.stateLength\n    Length of generator state.\n","random.strided.chi.byteLength":"\nrandom.strided.chi.byteLength\n    Size (in bytes) of generator state.\n","random.strided.chisquare":"\nrandom.strided.chisquare( N:integer, k:ArrayLikeObject, sk:integer, \n  out:ArrayLikeObject, so:integer )\n    Fills a strided array with pseudorandom numbers drawn from a chi-square\n    distribution.\n","random.strided.chisquare.ndarray":"\nrandom.strided.chisquare.ndarray( N:integer, k:ArrayLikeObject, sk:integer, \n  ok:integer, out:ArrayLikeObject, so:integer, oo:integer )\n    Fills a strided array with pseudorandom numbers drawn from a chi-square\n    distribution using alternative indexing semantics.\n","random.strided.chisquare.factory":"\nrandom.strided.chisquare.factory( [options:Object] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a chi-square distribution.\n","random.strided.chisquare.PRNG":"\nrandom.strided.chisquare.PRNG\n    Underlying pseudorandom number generator.\n","random.strided.chisquare.seed":"\nrandom.strided.chisquare.seed\n    Pseudorandom number generator seed.\n","random.strided.chisquare.seedLength":"\nrandom.strided.chisquare.seedLength\n    Length of generator seed.\n","random.strided.chisquare.state":"\nrandom.strided.chisquare.state\n    Generator state.\n","random.strided.chisquare.stateLength":"\nrandom.strided.chisquare.stateLength\n    Length of generator state.\n","random.strided.chisquare.byteLength":"\nrandom.strided.chisquare.byteLength\n    Size (in bytes) of generator state.\n","random.strided.cosine":"\nrandom.strided.cosine( N:integer, mu:ArrayLikeObject, sm:integer, \n  s:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a cosine\n    distribution.\n","random.strided.cosine.ndarray":"\nrandom.strided.cosine.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, \n  om:integer, s:ArrayLikeObject, ss:integer, os:integer, out:ArrayLikeObject, \n  so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a cosine\n    distribution using alternative indexing semantics.\n","random.strided.discreteUniform":"\nrandom.strided.discreteUniform( N:integer, a:ArrayLikeObject, sa:integer, \n  b:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a discrete\n    uniform distribution.\n","random.strided.discreteUniform.ndarray":"\nrandom.strided.discreteUniform.ndarray( N:integer, a:ArrayLikeObject, \n  sa:integer, oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, \n  out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a discrete\n    uniform distribution using alternative indexing semantics.\n","random.strided.exponential":"\nrandom.strided.exponential( N:integer, lambda:ArrayLikeObject, sl:integer, \n  out:ArrayLikeObject, so:integer )\n    Fills a strided array with pseudorandom numbers drawn from an exponential\n    distribution.\n","random.strided.exponential.ndarray":"\nrandom.strided.exponential.ndarray( N:integer, lambda:ArrayLikeObject, \n  sl:integer, ol:integer, out:ArrayLikeObject, so:integer, oo:integer )\n    Fills a strided array with pseudorandom numbers drawn from an exponential\n    distribution using alternative indexing semantics.\n","random.strided.exponential.factory":"\nrandom.strided.exponential.factory( [options:Object] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from an exponential distribution.\n","random.strided.exponential.PRNG":"\nrandom.strided.exponential.PRNG\n    Underlying pseudorandom number generator.\n","random.strided.exponential.seed":"\nrandom.strided.exponential.seed\n    Pseudorandom number generator seed.\n","random.strided.exponential.seedLength":"\nrandom.strided.exponential.seedLength\n    Length of generator seed.\n","random.strided.exponential.state":"\nrandom.strided.exponential.state\n    Generator state.\n","random.strided.exponential.stateLength":"\nrandom.strided.exponential.stateLength\n    Length of generator state.\n","random.strided.exponential.byteLength":"\nrandom.strided.exponential.byteLength\n    Size (in bytes) of generator state.\n","random.strided.gamma":"\nrandom.strided.gamma( N:integer, alpha:ArrayLikeObject, sa:integer, \n  beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a gamma\n    distribution.\n","random.strided.gamma.ndarray":"\nrandom.strided.gamma.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n  oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n  out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a gamma\n    distribution using alternative indexing semantics.\n","random.strided.geometric":"\nrandom.strided.geometric( N:integer, p:ArrayLikeObject, sp:integer, \n  out:ArrayLikeObject, so:integer )\n    Fills a strided array with pseudorandom numbers drawn from a geometric\n    distribution.\n","random.strided.geometric.ndarray":"\nrandom.strided.geometric.ndarray( N:integer, p:ArrayLikeObject, sp:integer, \n  op:integer, out:ArrayLikeObject, so:integer, oo:integer )\n    Fills a strided array with pseudorandom numbers drawn from a geometric\n    distribution using alternative indexing semantics.\n","random.strided.geometric.factory":"\nrandom.strided.geometric.factory( [options:Object] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a geometric distribution.\n","random.strided.geometric.PRNG":"\nrandom.strided.geometric.PRNG\n    Underlying pseudorandom number generator.\n","random.strided.geometric.seed":"\nrandom.strided.geometric.seed\n    Pseudorandom number generator seed.\n","random.strided.geometric.seedLength":"\nrandom.strided.geometric.seedLength\n    Length of generator seed.\n","random.strided.geometric.state":"\nrandom.strided.geometric.state\n    Generator state.\n","random.strided.geometric.stateLength":"\nrandom.strided.geometric.stateLength\n    Length of generator state.\n","random.strided.geometric.byteLength":"\nrandom.strided.geometric.byteLength\n    Size (in bytes) of generator state.\n","random.strided.invgamma":"\nrandom.strided.invgamma( N:integer, alpha:ArrayLikeObject, sa:integer, \n  beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n    distribution.\n","random.strided.invgamma.ndarray":"\nrandom.strided.invgamma.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n  oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n  out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n    distribution using alternative indexing semantics.\n","random.strided.lognormal":"\nrandom.strided.lognormal( N:integer, mu:ArrayLikeObject, sm:integer, \n  sigma:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a lognormal\n    distribution.\n","random.strided.lognormal.ndarray":"\nrandom.strided.lognormal.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, \n  om:integer, sigma:ArrayLikeObject, ss:integer, os:integer, \n  out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a lognormal\n    distribution using alternative indexing semantics.\n","random.strided.minstd":"\nrandom.strided.minstd( N:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom integers between 1 and 2147483646\n    (inclusive).\n","random.strided.minstd.ndarray":"\nrandom.strided.minstd.ndarray( N:integer, out:ArrayLikeObject, so:integer, \n  oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom integers between 1 and 2147483646\n    (inclusive) using alternative indexing semantics.\n","random.strided.minstd.normalized":"\nrandom.strided.minstd.normalized( N:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers between 0 and 1.\n","random.strided.minstd.normalized.ndarray":"\nrandom.strided.minstd.normalized.ndarray( N:integer, out:ArrayLikeObject, \n  so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers between 0 and 1 using\n    alternative indexing semantics.\n","random.strided.minstdShuffle":"\nrandom.strided.minstdShuffle( N:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom integers between 1 and 2147483646\n    (inclusive).\n","random.strided.minstdShuffle.ndarray":"\nrandom.strided.minstdShuffle.ndarray( N:integer, out:ArrayLikeObject, \n  so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom integers between 1 and 2147483646\n    (inclusive) using alternative indexing semantics.\n","random.strided.minstdShuffle.normalized":"\nrandom.strided.minstdShuffle.normalized( N:integer, out:ArrayLikeObject, \n  so:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers between 0 and 1.\n","random.strided.minstdShuffle.normalized.ndarray":"\nrandom.strided.minstdShuffle.normalized.ndarray( N:integer, \n  out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers between 0 and 1 using\n    alternative indexing semantics.\n","random.strided.mt19937":"\nrandom.strided.mt19937( N:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom integers between 0 and 4294967295\n    (inclusive).\n","random.strided.mt19937.ndarray":"\nrandom.strided.mt19937.ndarray( N:integer, out:ArrayLikeObject, so:integer, \n  oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom integers between 0 and 4294967295\n    (inclusive) using alternative indexing semantics.\n","random.strided.mt19937.normalized":"\nrandom.strided.mt19937.normalized( N:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers between 0 and 1.\n","random.strided.mt19937.normalized.ndarray":"\nrandom.strided.mt19937.normalized.ndarray( N:integer, out:ArrayLikeObject, \n  so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers between 0 and 1 using\n    alternative indexing semantics.\n","random.strided.normal":"\nrandom.strided.normal( N:integer, mu:ArrayLikeObject, sm:integer, \n  sigma:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a normal\n    distribution.\n","random.strided.normal.ndarray":"\nrandom.strided.normal.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, \n  om:integer, sigma:ArrayLikeObject, ss:integer, os:integer, \n  out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a normal\n    distribution using alternative indexing semantics.\n","random.strided.poisson":"\nrandom.strided.poisson( N:integer, lambda:ArrayLikeObject, sl:integer, \n  out:ArrayLikeObject, so:integer )\n    Fills a strided array with pseudorandom numbers drawn from a Poisson\n    distribution.\n","random.strided.poisson.ndarray":"\nrandom.strided.poisson.ndarray( N:integer, lambda:ArrayLikeObject, sl:integer, \n  ol:integer, out:ArrayLikeObject, so:integer, oo:integer )\n    Fills a strided array with pseudorandom numbers drawn from a Poisson\n    distribution using alternative indexing semantics.\n","random.strided.poisson.factory":"\nrandom.strided.poisson.factory( [options:Object] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Poisson distribution.\n","random.strided.poisson.PRNG":"\nrandom.strided.poisson.PRNG\n    Underlying pseudorandom number generator.\n","random.strided.poisson.seed":"\nrandom.strided.poisson.seed\n    Pseudorandom number generator seed.\n","random.strided.poisson.seedLength":"\nrandom.strided.poisson.seedLength\n    Length of generator seed.\n","random.strided.poisson.state":"\nrandom.strided.poisson.state\n    Generator state.\n","random.strided.poisson.stateLength":"\nrandom.strided.poisson.stateLength\n    Length of generator state.\n","random.strided.poisson.byteLength":"\nrandom.strided.poisson.byteLength\n    Size (in bytes) of generator state.\n","random.strided.randu":"\nrandom.strided.randu( N:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with uniformly distributed pseudorandom numbers\n    between 0 and 1.\n","random.strided.randu.ndarray":"\nrandom.strided.randu.ndarray( N:integer, out:ArrayLikeObject, so:integer, \n  oo:integer[, options:Object] )\n    Fills a strided array with uniformly distributed pseudorandom numbers\n    between 0 and 1 using alternative indexing semantics.\n","random.strided.rayleigh":"\nrandom.strided.rayleigh( N:integer, sigma:ArrayLikeObject, ss:integer, \n  out:ArrayLikeObject, so:integer )\n    Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n    distribution.\n","random.strided.rayleigh.ndarray":"\nrandom.strided.rayleigh.ndarray( N:integer, sigma:ArrayLikeObject, ss:integer, \n  os:integer, out:ArrayLikeObject, so:integer, oo:integer )\n    Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n    distribution using alternative indexing semantics.\n","random.strided.rayleigh.factory":"\nrandom.strided.rayleigh.factory( [options:Object] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Rayleigh distribution.\n","random.strided.rayleigh.PRNG":"\nrandom.strided.rayleigh.PRNG\n    Underlying pseudorandom number generator.\n","random.strided.rayleigh.seed":"\nrandom.strided.rayleigh.seed\n    Pseudorandom number generator seed.\n","random.strided.rayleigh.seedLength":"\nrandom.strided.rayleigh.seedLength\n    Length of generator seed.\n","random.strided.rayleigh.state":"\nrandom.strided.rayleigh.state\n    Generator state.\n","random.strided.rayleigh.stateLength":"\nrandom.strided.rayleigh.stateLength\n    Length of generator state.\n","random.strided.rayleigh.byteLength":"\nrandom.strided.rayleigh.byteLength\n    Size (in bytes) of generator state.\n","random.strided.t":"\nrandom.strided.t( N:integer, v:ArrayLikeObject, sv:integer, \n  out:ArrayLikeObject, so:integer )\n    Fills a strided array with pseudorandom numbers drawn from a Student's t-\n    distribution.\n","random.strided.t.ndarray":"\nrandom.strided.t.ndarray( N:integer, v:ArrayLikeObject, sv:integer, ov:integer, \n  out:ArrayLikeObject, so:integer, oo:integer )\n    Fills a strided array with pseudorandom numbers drawn from a Student's t-\n    distribution using alternative indexing semantics.\n","random.strided.t.factory":"\nrandom.strided.t.factory( [options:Object] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Student's t-distribution.\n","random.strided.t.PRNG":"\nrandom.strided.t.PRNG\n    Underlying pseudorandom number generator.\n","random.strided.t.seed":"\nrandom.strided.t.seed\n    Pseudorandom number generator seed.\n","random.strided.t.seedLength":"\nrandom.strided.t.seedLength\n    Length of generator seed.\n","random.strided.t.state":"\nrandom.strided.t.state\n    Generator state.\n","random.strided.t.stateLength":"\nrandom.strided.t.stateLength\n    Length of generator state.\n","random.strided.t.byteLength":"\nrandom.strided.t.byteLength\n    Size (in bytes) of generator state.\n","random.strided.uniform":"\nrandom.strided.uniform( N:integer, a:ArrayLikeObject, sa:integer, \n  b:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a continuous\n    uniform distribution.\n","random.strided.uniform.ndarray":"\nrandom.strided.uniform.ndarray( N:integer, a:ArrayLikeObject, sa:integer, \n  oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, \n  so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a continuous\n    uniform distribution using alternative indexing semantics.\n","random.strided.weibull":"\nrandom.strided.weibull( N:integer, k:ArrayLikeObject, sk:integer, \n  lambda:ArrayLikeObject, sl:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a Weibull\n    distribution.\n","random.strided.weibull.ndarray":"\nrandom.strided.weibull.ndarray( N:integer, k:ArrayLikeObject, sk:integer, \n  ok:integer, lambda:ArrayLikeObject, sl:integer, ol:integer, \n  out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a Weibull\n    distribution using alternative indexing semantics.\n","ranks":"\nranks( arr:Array<number>[, options:Object] )\n    Computes the sample ranks for the values of an array-like object.\n","readDir":"\nreadDir( path:string|Buffer, clbk:Function )\n    Asynchronously reads the contents of a directory.\n","readDir.sync":"\nreadDir.sync( path:string|Buffer )\n    Synchronously reads the contents of a directory.\n","readFile":"\nreadFile( file:string|Buffer|integer[, options:Object|string], clbk:Function )\n    Asynchronously reads the entire contents of a file.\n","readFile.sync":"\nreadFile.sync( file:string|Buffer|integer[, options:Object|string] )\n    Synchronously reads the entire contents of a file.\n","readFileList":"\nreadFileList( filepaths:Array<string>[, options:Object|string], clbk:Function )\n    Asynchronously reads the entire contents of each file in a file list.\n","readFileList.sync":"\nreadFileList.sync( filepaths:Array<string>[, options:Object|string] )\n    Synchronously reads the entire contents of each file in a file list.\n","readJSON":"\nreadJSON( file:string|Buffer|integer[, options:Object|string], clbk:Function )\n    Asynchronously reads a file as JSON.\n","readJSON.sync":"\nreadJSON.sync( file:string|Buffer|integer[, options:Object|string] )\n    Synchronously reads a file as JSON.\n","readWASM":"\nreadWASM( file:string|Buffer|integer[, options:Object], clbk:Function )\n    Asynchronously reads a file as WebAssembly.\n","readWASM.sync":"\nreadWASM.sync( file:string|Buffer|integer[, options:Object] )\n    Synchronously reads a file as WebAssembly.\n","real":"\nreal( z:Complex128 )\n    Returns the real component of a double-precision complex floating-point\n    number.\n","realarray":"\nrealarray( [dtype:string] )\n    Creates a typed array.\n\nrealarray( length:integer[, dtype:string] )\n    Returns a typed array having a specified length.\n\nrealarray( typedarray:TypedArray[, dtype:string] )\n    Creates a typed array from another typed array.\n\nrealarray( obj:Object[, dtype:string] )\n    Creates a typed array from an array-like object or iterable.\n\nrealarray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n  dtype:string] )\n    Returns a typed array view of an ArrayBuffer.\n","realarrayCtors":"\nrealarrayCtors( dtype:string )\n    Returns a typed array constructor.\n","realarrayDataTypes":"\nrealarrayDataTypes()\n    Returns a list of typed array real-valued data types.\n","realf":"\nrealf( z:Complex64 )\n    Returns the real component of a single-precision complex floating-point\n    number.\n","realmax":"\nrealmax( dtype:string )\n    Returns the maximum finite value capable of being represented by a numeric\n    real type.\n","realmin":"\nrealmin( dtype:string )\n    Returns the smallest positive normal value capable of being represented by a\n    numeric real type.\n","reBasename":"\nreBasename( [platform:string] )\n    Returns a regular expression to capture the last part of a path.\n","reBasename.REGEXP":"\nreBasename.REGEXP\n    Regular expression to capture the last part of a POSIX path.\n","reBasename.REGEXP_POSIX":"\nreBasename.REGEXP_POSIX\n    Regular expression to capture the last part of a POSIX path.\n","reBasename.REGEXP_WIN32":"\nreBasename.REGEXP_WIN32\n    Regular expression to capture the last part of a Windows path.\n","reBasenamePosix":"\nreBasenamePosix()\n    Returns a regular expression to capture the last part of a POSIX path.\n","reBasenamePosix.REGEXP":"\nreBasenamePosix.REGEXP\n    Regular expression to capture the last part of a POSIX path.\n","reBasenameWindows":"\nreBasenameWindows()\n    Returns a regular expression to capture the last part of a Windows path.\n","reBasenameWindows.REGEXP":"\nreBasenameWindows.REGEXP\n    Regular expression to capture the last part of a Windows path.\n","reColorHexadecimal":"\nreColorHexadecimal( [mode:string] )\n    Returns a regular expression to match a hexadecimal color.\n","reColorHexadecimal.REGEXP":"\nreColorHexadecimal.REGEXP\n    Regular expression to match a full hexadecimal color.\n","reColorHexadecimal.REGEXP_SHORTHAND":"\nreColorHexadecimal.REGEXP_SHORTHAND\n    Regular expression to match a shorthand hexadecimal color.\n","reColorHexadecimal.REGEXP_EITHER":"\nreColorHexadecimal.REGEXP_EITHER\n    Regular expression to match either a shorthand or full length hexadecimal\n    color.\n","reDecimalNumber":"\nreDecimalNumber( [options:Object] )\n    Returns a regular expression to match a decimal number.\n","reDecimalNumber.REGEXP":"\nreDecimalNumber.REGEXP\n    Regular expression to match a decimal number.\n","reDecimalNumber.REGEXP_CAPTURE":"\nreDecimalNumber.REGEXP_CAPTURE\n    Regular expression to capture a decimal number.\n","reDirname":"\nreDirname( [platform:string] )\n    Returns a regular expression to capture a path dirname.\n","reDirname.REGEXP":"\nreDirname.REGEXP\n    Regular expression to capture a path dirname.\n","reDirname.REGEXP_POSIX":"\nreDirname.REGEXP_POSIX\n    Regular expression to capture a POSIX path dirname.\n","reDirname.REGEXP_WIN32":"\nreDirname.REGEXP_WIN32\n    Regular expression to capture a Windows path dirname.\n","reDirnamePosix":"\nreDirnamePosix()\n    Returns a regular expression to capture a POSIX path dirname.\n","reDirnamePosix.REGEXP":"\nreDirnamePosix.REGEXP\n    Regular expression to capture a POSIX path dirname.\n","reDirnameWindows":"\nreDirnameWindows()\n    Returns a regular expression to capture a Windows path dirname.\n","reDirnameWindows.REGEXP":"\nreDirnameWindows.REGEXP\n    Regular expression to capture a Windows path dirname.\n","reduce":"\nreduce( arr:ArrayLikeObject|ndarray, initial:any, reducer:Function[, \n  thisArg:any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n","reduce2d":"\nreduce2d( arr:ArrayLikeObject<ArrayLikeObject>, initial:ArrayLikeObject, \n  reducer:Function[, thisArg:any] )\n    Reduces the number of dimensions by one of a two-dimensional nested array by\n    applying a function against an accumulator and each element along the\n    innermost dimension and returning the accumulation results as a one-\n    dimensional array.\n","reduceAsync":"\nreduceAsync( collection:Array|TypedArray|Object, initial:any, [options:Object,] \n  reducer:Function, done:Function )\n    Applies a function against an accumulator and each element in a collection\n    and returns the accumulated result.\n","reduceAsync.factory":"\nreduceAsync.factory( [options:Object,] fcn:Function )\n    Returns a function which applies a function against an accumulator and each\n    element in a collection and returns the accumulated result.\n","reduceRight":"\nreduceRight( arr:ArrayLikeObject|ndarray, initial:any, reducer:Function[, \n  thisArg:any] )\n    Applies a function against an accumulator and each element in an array while\n    iterating from right to left and returns the accumulated result.\n","reduceRightAsync":"\nreduceRightAsync( collection:Array|TypedArray|Object, initial:any, \n  [options:Object,] reducer:Function, done:Function )\n    Applies a function against an accumulator and each element in a collection\n    and returns the accumulated result, iterating from right to left.\n","reduceRightAsync.factory":"\nreduceRightAsync.factory( [options:Object,] fcn:Function )\n    Returns a function which applies a function against an accumulator and each\n    element in a collection and returns the accumulated result, iterating from\n    right to left.\n","reDurationString":"\nreDurationString()\n    Returns a regular expression to match a duration string.\n","reDurationString.REGEXP":"\nreDurationString.REGEXP\n    Regular expression to match a duration string.\n","reEOL":"\nreEOL( [options:Object] )\n    Regular expression to match a newline character sequence: /\\r?\\n/.\n","reEOL.REGEXP":"\nreEOL.REGEXP\n    Regular expression to match a newline character sequence: /\\r?\\n/.\n","reEOL.REGEXP_CAPTURE":"\nreEOL.REGEXP_CAPTURE\n    Regular expression to capture a newline character sequence: /\\r?\\n/.\n","reExtendedLengthPath":"\nreExtendedLengthPath()\n    Returns a regular expression to test if a string is an extended-length path.\n","reExtendedLengthPath.REGEXP":"\nreExtendedLengthPath.REGEXP\n    Regular expression to test if a string is an extended-length path.\n","reExtname":"\nreExtname( [platform:string] )\n    Returns a regular expression to capture a filename extension.\n","reExtname.REGEXP":"\nreExtname.REGEXP\n    Regular expression to capture a filename extension.\n","reExtname.REGEXP_POSIX":"\nreExtname.REGEXP_POSIX\n    Regular expression to capture a POSIX filename extension.\n","reExtname.REGEXP_WIN32":"\nreExtname.REGEXP_WIN32\n    Regular expression to capture a Windows filename extension.\n","reExtnamePosix":"\nreExtnamePosix\n    Returns a regular expression to capture a POSIX filename extension.\n","reExtnamePosix.REGEXP":"\nreExtnamePosix.REGEXP\n    Regular expression to capture a POSIX filename extension.\n","reExtnameWindows":"\nreExtnameWindows\n    Returns a regular expression to capture a Windows filename extension.\n","reExtnameWindows.REGEXP":"\nreExtnameWindows.REGEXP\n    Regular expression to capture a Windows filename extension.\n","reFilename":"\nreFilename( [platform:string] )\n    Regular expression to split a filename.\n","reFilename.REGEXP":"\nreFilename.REGEXP\n    Regular expression to split a filename.\n","reFilename.REGEXP_POSIX":"\nreFilename.REGEXP_POSIX\n    Regular expression to split a POSIX filename.\n","reFilename.REGEXP_WIN32":"\nreFilename.REGEXP_WIN32\n    Regular expression to split a Windows filename.\n","reFilenamePosix":"\nreFilenamePosix()\n    Returns a regular expression to split a POSIX filename.\n","reFilenamePosix.REGEXP":"\nreFilenamePosix.REGEXP\n    Regular expression to split a POSIX filename.\n","reFilenameWindows":"\nreFilenameWindows()\n    Returns a regular expression to split a Windows filename.\n","reFilenameWindows.REGEXP":"\nreFilenameWindows.REGEXP\n    Regular expression to split a Windows filename.\n","reFromString":"\nreFromString( str:string )\n    Parses a regular expression string and returns a new regular expression.\n","reFunctionName":"\nreFunctionName()\n    Return a regular expression to capture a function name.\n","reFunctionName.REGEXP":"\nreFunctionName.REGEXP\n    Regular expression to capture a function name.\n","regexp2json":"\nregexp2json( re:RegExp )\n    Returns a JSON representation of a regular expression.\n","reim":"\nreim( z:Complex128 )\n    Returns the real and imaginary components of a double-precision complex\n    floating-point number.\n","reimf":"\nreimf( z:Complex64 )\n    Returns the real and imaginary components of a single-precision complex\n    floating-point number.\n","rejectArguments":"\nrejectArguments( fcn:Function, predicate:Function[, thisArg:any] )\n    Returns a function that applies arguments to a provided function according\n    to a predicate function.\n","removeFirst":"\nremoveFirst( str:string[, n:integer][, options:Object] )\n    Removes the first character(s) of a `string`.\n","removeLast":"\nremoveLast( str:string[, n:integer][, options:Object] )\n    Removes the last character(s) of a `string`.\n","removePunctuation":"\nremovePunctuation( str:string )\n    Removes punctuation characters from a `string`.\n","removeUTF8BOM":"\nremoveUTF8BOM( str:string )\n    Removes a UTF-8 byte order mark (BOM) from the beginning of a `string`.\n","removeWords":"\nremoveWords( str:string, words:Array<string>[, ignoreCase:boolean] )\n    Removes all occurrences of the given words from a `string`.\n","rename":"\nrename( oldPath:string|Buffer, newPath:string|Buffer, clbk:Function )\n    Asynchronously renames a file.\n","rename.sync":"\nrename.sync( oldPath:string|Buffer, newPath:string|Buffer )\n    Synchronously renames a file.\n","reNativeFunction":"\nreNativeFunction()\n    Returns a regular expression to match a native function.\n","reNativeFunction.REGEXP":"\nreNativeFunction.REGEXP\n    Regular expression to match a native function.\n","reorderArguments":"\nreorderArguments( fcn:Function, indices:Array<integer>[, thisArg:any] )\n    Returns a function that invokes a provided function with reordered\n    arguments.\n","repeat":"\nrepeat( str:string, n:integer )\n    Repeats a string `n` times and returns the concatenated result.\n","replace":"\nreplace( str:string, search:string|RegExp, newval:string|Function )\n    Replaces search occurrences with a replacement string.\n","replaceBefore":"\nreplaceBefore( str, search, replacement )\n    Replaces the substring before the first occurrence of a specified search\n    string. \n","reRegExp":"\nreRegExp()\n    Returns a regular expression to parse a regular expression string.\n","reRegExp.REGEXP":"\nreRegExp.REGEXP\n    Regular expression to parse a regular expression string.\n","rescape":"\nrescape( str:string )\n    Escapes a regular expression string.\n","reSemVer":"\nreSemVer()\n    Returns a regular expression to match a semantic version string.\n","reSemVer.REGEXP":"\nreSemVer.REGEXP\n    Regular expression to match a semantic version string.\n","resolveParentPath":"\nresolveParentPath( path:string[, options:Object], clbk:Function )\n    Asynchronously resolves a path by walking parent directories.\n","resolveParentPath.sync":"\nresolveParentPath.sync( path:string[, options:Object] )\n    Synchronously resolves a path by walking parent directories.\n","resolveParentPathBy":"\nresolveParentPathBy( path:string[, options:Object], predicate:Function, \n  clbk:Function )\n    Asynchronously resolves a path according to a predicate function by walking\n    parent directories.\n","resolveParentPathBy.sync":"\nresolveParentPathBy.sync( path:string[, options:Object], predicate:Function )\n    Synchronously resolves a path according to a predicate function by walking\n    parent directories.\n","reUncPath":"\nreUncPath()\n    Return a regular expression to parse a UNC path.\n","reUncPath.REGEXP":"\nreUncPath.REGEXP\n    Regular expression to parse a UNC path.\n","reUtf16SurrogatePair":"\nreUtf16SurrogatePair()\n    Returns a regular expression to match a UTF-16 surrogate pair.\n","reUtf16SurrogatePair.REGEXP":"\nreUtf16SurrogatePair.REGEXP\n    Regular expression to match a UTF-16 surrogate pair.\n","reUtf16UnpairedSurrogate":"\nreUtf16UnpairedSurrogate()\n    Returns a regular expression to match an unpaired UTF-16 surrogate.\n","reUtf16UnpairedSurrogate.REGEXP":"\nreUtf16UnpairedSurrogate.REGEXP\n    Regular expression to match an unpaired UTF-16 surrogate.\n","reverseArguments":"\nreverseArguments( fcn:Function[, thisArg:any] )\n    Returns a function that invokes a provided function with arguments in\n    reverse order.\n","reverseString":"\nreverseString( str:string[, options:Object] )\n    Reverses a string.\n","reviveBasePRNG":"\nreviveBasePRNG( key:string, value:any )\n    Revives a JSON-serialized pseudorandom number generator (PRNG).\n","reviveBuffer":"\nreviveBuffer( key:string, value:any )\n    Revives a JSON-serialized Buffer.\n","reviveComplex":"\nreviveComplex( key:string, value:any )\n    Revives a JSON-serialized complex number.\n","reviveComplex64":"\nreviveComplex64( key:string, value:any )\n    Revives a JSON-serialized 64-bit complex number.\n","reviveComplex128":"\nreviveComplex128( key:string, value:any )\n    Revives a JSON-serialized 128-bit complex number.\n","reviveError":"\nreviveError( key:string, value:any )\n    Revives a JSON-serialized error object.\n","reviveRegExp":"\nreviveRegExp( key:string, value:any )\n    Revives a JSON-serialized regular expression.\n","reviveTypedArray":"\nreviveTypedArray( key:string, value:any )\n    Revives a JSON-serialized typed array.\n","reWhitespace":"\nreWhitespace( [options:Object] )\n    Returns a regular expression to match a white space character.\n","reWhitespace.REGEXP":"\nreWhitespace.REGEXP\n    Regular expression to match a white space character.\n","reWhitespace.REGEXP_CAPTURE":"\nreWhitespace.REGEXP_CAPTURE\n    Regular expression to capture white space characters.\n","rpad":"\nrpad( str:string, len:integer[, pad:string] )\n    Right pads a `string` such that the padded `string` has a length of at least\n    `len`.\n","rtrim":"\nrtrim( str:string )\n    Trims whitespace from the end of a string.\n","rtrimN":"\nrtrimN( str:string, n:integer[, chars:Array|string] )\n    Trims `n` characters from the end of a string.\n","safeintmax":"\nsafeintmax( dtype:string )\n    Returns the maximum safe integer capable of being represented by a numeric\n    real type.\n","safeintmin":"\nsafeintmin( dtype:string )\n    Returns the minimum safe integer capable of being represented by a numeric\n    real type.\n","sample":"\nsample( x:ArrayLike[, options:Object] )\n    Samples elements from an array-like object.\n","sample.factory":"\nsample.factory( [pool:ArrayLike, ][options:Object] )\n    Returns a function to sample elements from an array-like object.\n","SAVOY_STOPWORDS_FIN":"\nSAVOY_STOPWORDS_FIN()\n    Returns a list of Finnish stop words.\n","SAVOY_STOPWORDS_FR":"\nSAVOY_STOPWORDS_FR()\n    Returns a list of French stop words.\n","SAVOY_STOPWORDS_GER":"\nSAVOY_STOPWORDS_GER()\n    Returns a list of German stop words.\n","SAVOY_STOPWORDS_IT":"\nSAVOY_STOPWORDS_IT()\n    Returns a list of Italian stop words.\n","SAVOY_STOPWORDS_POR":"\nSAVOY_STOPWORDS_POR()\n    Returns a list of Portuguese stop words.\n","SAVOY_STOPWORDS_SP":"\nSAVOY_STOPWORDS_SP()\n    Returns a list of Spanish stop words.\n","SAVOY_STOPWORDS_SWE":"\nSAVOY_STOPWORDS_SWE()\n    Returns a list of Swedish stop words.\n","scalar2array":"\nscalar2array( value:any[, dtype:string] )\n    Returns a single-element array containing a provided scalar value.\n","scalar2ndarray":"\nscalar2ndarray( value:any[, options:Object] )\n    Returns a zero-dimensional ndarray containing a provided scalar value.\n","sdot":"\nsdot( x:ndarray, y:ndarray[, dim:integer] )\n    Computes the dot product of two single-precision floating-point vectors.\n","SECONDS_IN_DAY":"\nSECONDS_IN_DAY\n    Number of seconds in a day.\n","SECONDS_IN_HOUR":"\nSECONDS_IN_HOUR\n    Number of seconds in an hour.\n","SECONDS_IN_MINUTE":"\nSECONDS_IN_MINUTE\n    Number of seconds in a minute.\n","SECONDS_IN_WEEK":"\nSECONDS_IN_WEEK\n    Number of seconds in a week.\n","secondsInMonth":"\nsecondsInMonth( [month:string|Date|integer[, year:integer]] )\n    Returns the number of seconds in a month.\n","secondsInYear":"\nsecondsInYear( [value:integer|Date] )\n    Returns the number of seconds in a year according to the Gregorian calendar.\n","sentencize":"\nsentencize( str:string )\n    Splits a string into an array of sentences.\n","seq2slice":"\nseq2slice( str:string, len:integer, strict:boolean )\n    Converts a subsequence string to a Slice object.\n","setConfigurableReadOnly":"\nsetConfigurableReadOnly( obj:Object, prop:string|symbol, value:any )\n    Defines a configurable read-only property.\n","setConfigurableReadOnlyAccessor":"\nsetConfigurableReadOnlyAccessor( obj:Object, prop:string|symbol, \n  getter:Function )\n    Defines a configurable read-only accessor.\n","setConfigurableReadWriteAccessor":"\nsetConfigurableReadWriteAccessor( obj:Object, prop:string|symbol, \n  getter:Function, setter:Function )\n    Defines a configurable property having read-write accessors.\n","setConfigurableWriteOnlyAccessor":"\nsetConfigurableWriteOnlyAccessor( obj:Object, prop:string|symbol, \n  setter:Function )\n    Defines a configurable write-only accessor.\n","setMemoizedConfigurableReadOnly":"\nsetMemoizedConfigurableReadOnly( obj:Object, prop:string|symbol, fcn:Function )\n    Defines a configurable memoized read-only object property.\n","setMemoizedReadOnly":"\nsetMemoizedReadOnly( obj:Object, prop:string|symbol, fcn:Function )\n    Defines a memoized read-only object property.\n","setNonEnumerableProperty":"\nsetNonEnumerableProperty( obj:Object, prop:string|symbol, value:any )\n    Defines a non-enumerable property.\n","setNonEnumerableReadOnly":"\nsetNonEnumerableReadOnly( obj:Object, prop:string|symbol, value:any )\n    Defines a non-enumerable read-only property.\n","setNonEnumerableReadOnlyAccessor":"\nsetNonEnumerableReadOnlyAccessor( obj:Object, prop:string|symbol, \n  getter:Function )\n    Defines a non-enumerable read-only accessor.\n","setNonEnumerableReadWriteAccessor":"\nsetNonEnumerableReadWriteAccessor( obj:Object, prop:string|symbol, \n  getter:Function, setter:Function )\n    Defines a non-enumerable property having read-write accessors.\n","setNonEnumerableWriteOnlyAccessor":"\nsetNonEnumerableWriteOnlyAccessor( obj:Object, prop:string|symbol, \n  setter:Function )\n    Defines a non-enumerable write-only accessor.\n","setReadOnly":"\nsetReadOnly( obj:Object, prop:string|symbol, value:any )\n    Defines a read-only property.\n","setReadOnlyAccessor":"\nsetReadOnlyAccessor( obj:Object, prop:string|symbol, getter:Function )\n    Defines a read-only accessor.\n","setReadWriteAccessor":"\nsetReadWriteAccessor( obj:Object, prop:string|symbol, getter:Function, \n  setter:Function )\n    Defines a property having read-write accessors.\n","setWriteOnlyAccessor":"\nsetWriteOnlyAccessor( obj:Object, prop:string|symbol, setter:Function )\n    Defines a write-only accessor.\n","SharedArrayBuffer":"\nSharedArrayBuffer( size:integer )\n    Returns a shared array buffer having a specified number of bytes.\n","SharedArrayBuffer.length":"\nSharedArrayBuffer.length\n    Number of input arguments the constructor accepts.\n","SharedArrayBuffer.prototype.byteLength":"\nSharedArrayBuffer.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the array buffer.\n","SharedArrayBuffer.prototype.slice":"\nSharedArrayBuffer.prototype.slice( [start:integer[, end:integer]] )\n    Copies the bytes of a shared array buffer to a new shared array buffer.\n","shift":"\nshift( collection:Array|TypedArray|Object )\n    Removes and returns the first element of a collection.\n","shuffle":"\nshuffle( arr:ArrayLike[, options:Object] )\n    Shuffles elements of an array-like object.\n","shuffle.factory":"\nshuffle.factory( [options:Object] )\n    Returns a function to shuffle elements of array-like objects.\n","sizeOf":"\nsizeOf( dtype:string )\n    Returns the size (in bytes) of the canonical binary representation of a\n    specified numeric type.\n","Slice":"\nSlice( [stop:integer|null|undefined] )\n    Returns a Slice.\n\nSlice( start:integer|null|undefined, stop:integer|null|undefined[, \n  step:integer|null|undefined] )\n    Returns a Slice.\n","Slice.prototype.start":"\nSlice.prototype.start\n    Read-only property returning the starting slice index.\n","Slice.prototype.stop":"\nSlice.prototype.stop\n    Read-only property returning the ending slice index.\n","Slice.prototype.step":"\nSlice.prototype.step\n    Read-only property returning the index increment.\n","Slice.prototype.toString":"\nSlice.prototype.toString()\n    Serializes a Slice as a string.\n","Slice.prototype.toJSON":"\nSlice.prototype.toJSON()\n    Serializes a Slice as a JSON object.\n","snakecase":"\nsnakecase( str:string )\n    Converts a string to snake case.\n","some":"\nsome( collection:Array|TypedArray|Object, n:number )\n    Tests whether at least `n` elements in a collection are truthy.\n","someBy":"\nsomeBy( collection:Array|TypedArray|Object, n:number, predicate:Function[, \n  thisArg:any ] )\n    Tests whether a collection contains at least `n` elements which pass a test\n    implemented by a predicate function.\n","someByAsync":"\nsomeByAsync( collection:Array|TypedArray|Object, n:number, [options:Object,] \n  predicate:Function, done:Function )\n    Tests whether a collection contains at least `n` elements which pass a test\n    implemented by a predicate function.\n","someByAsync.factory":"\nsomeByAsync.factory( [options:Object,] predicate:Function )\n    Returns a function which tests whether a collection contains at least `n`\n    elements which pass a test implemented by a predicate function.\n","someByRight":"\nsomeByRight( collection:Array|TypedArray|Object, n:number, predicate:Function[, \n  thisArg:any ] )\n    Tests whether a collection contains at least `n` elements which pass a test\n    implemented by a predicate function, iterating from right to left.\n","someByRightAsync":"\nsomeByRightAsync( collection:Array|TypedArray|Object, n:number, \n  [options:Object,] predicate:Function, done:Function )\n    Tests whether a collection contains at least `n` elements which pass a test\n    implemented by a predicate function, iterating from right to left.\n","someByRightAsync.factory":"\nsomeByRightAsync.factory( [options:Object,] predicate:Function )\n    Returns a function which tests whether a collection contains at least `n`\n    elements which pass a test implemented by a predicate function, iterating\n    from right to left.\n","someInBy":"\nsomeInBy( obj:Object, n:number, predicate:Function[, thisArg:any ] )\n    Tests whether an object contains at least `n` properties\n    (own and inherited) which pass a test\n    implemented by a predicate function.\n","someOwnBy":"\nsomeOwnBy( obj:Object, n:number, predicate:Function[, thisArg:any ] )\n    Tests whether some `own` properties of a provided object\n    satisfy a predicate function for at least `n` properties.\n","SOTU":"\nSOTU( [options:Object] )\n    Returns State of the Union (SOTU) addresses.\n","SPACHE_REVISED":"\nSPACHE_REVISED()\n    Returns a list of simple American-English words (revised Spache).\n","SPAM_ASSASSIN":"\nSPAM_ASSASSIN()\n    Returns the Spam Assassin public mail corpus.\n","SparklineBase":"\nSparklineBase( [data:ArrayLike|ndarray,] [options:Object] )\n    Returns a Sparkline instance.\n","sparsearray2iterator":"\nsparsearray2iterator( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )\n    Returns an iterator which iterates over the elements of a sparse array-like\n    object.\n","sparsearray2iteratorRight":"\nsparsearray2iteratorRight( src:ArrayLikeObject[, mapFcn:Function[, \n  thisArg:any]] )\n    Returns an iterator which iterates from right to left over the elements of a\n    sparse array-like object.\n","splitStream":"\nsplitStream( [options:Object] )\n    Returns a transform stream which splits streamed data.\n","splitStream.factory":"\nsplitStream.factory( [options:Object] )\n    Returns a function for creating transform streams for splitting streamed\n    data.\n","splitStream.objectMode":"\nsplitStream.objectMode( [options:Object] )\n    Returns an \"objectMode\" transform stream for splitting streamed data.\n","SQRT_EPS":"\nSQRT_EPS\n    Square root of double-precision floating-point epsilon.\n","SQRT_HALF":"\nSQRT_HALF\n    Square root of `1/2`.\n","SQRT_HALF_PI":"\nSQRT_HALF_PI\n    Square root of the mathematical constant `π` divided by `2`.\n","SQRT_PHI":"\nSQRT_PHI\n    Square root of the golden ratio.\n","SQRT_PI":"\nSQRT_PI\n    Square root of the mathematical constant `π`.\n","SQRT_THREE":"\nSQRT_THREE\n    Square root of `3`.\n","SQRT_TWO":"\nSQRT_TWO\n    Square root of `2`.\n","SQRT_TWO_PI":"\nSQRT_TWO_PI\n    Square root of the mathematical constant `π` times `2`.\n","SSA_US_BIRTHS_2000_2014":"\nSSA_US_BIRTHS_2000_2014()\n    Returns US birth data from 2000 to 2014, as provided by the Social Security\n    Administration.\n","sswap":"\nsswap( x:ndarray, y:ndarray[, dim:integer] )\n    Interchanges two single-precision floating-point vectors.\n","Stack":"\nStack()\n    Stack constructor.\n","standalone2pkg":"\nstandalone2pkg( pkg:string )\n    Returns the internal package name associated with a provided standalone\n    package name.\n","STANDARD_CARD_DECK":"\nSTANDARD_CARD_DECK()\n    Returns a string array containing two or three letter abbreviations for each\n    card in a standard 52-card deck.\n","startcase":"\nstartcase( str:string )\n    Capitalizes the first letter of each word in an input string.\n","startsWith":"\nstartsWith( str:string, search:string[, position:integer] )\n    Tests if a string starts with the characters of another string.\n","STOPWORDS_EN":"\nSTOPWORDS_EN()\n    Returns a list of English stop words.\n","strided.abs":"\nstrided.abs( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  dtypeY:any, y:ArrayLikeObject, strideY:integer )\n    Computes the absolute value for each element in a strided array `x` and\n    assigns the results to elements in a strided array `y`.\n","strided.abs.ndarray":"\nstrided.abs.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, \n  offsetY:integer )\n    Computes the absolute value for each element in a strided array `x` and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n","strided.abs2":"\nstrided.abs2( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  dtypeY:any, y:ArrayLikeObject, strideY:integer )\n    Computes the squared absolute value for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y`.\n","strided.abs2.ndarray":"\nstrided.abs2.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n  strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n  strideY:integer, offsetY:integer )\n    Computes the squared absolute value for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n","strided.abs2By":"\nstrided.abs2By( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the squared absolute value of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n","strided.abs2By.ndarray":"\nstrided.abs2By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the squared absolute value of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing semantics.\n","strided.absBy":"\nstrided.absBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the absolute value of each element retrieved from a strided input\n    array `x` via a callback function and assigns each result to an element in a\n    strided output array `y`.\n","strided.absBy.ndarray":"\nstrided.absBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the absolute value of each element retrieved from a strided input\n    array `x` via a callback function and assigns each result to an element in a\n    strided output array `y` using alternative indexing semantics.\n","strided.acosBy":"\nstrided.acosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the arccosine of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y`.\n","strided.acosBy.ndarray":"\nstrided.acosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the arccosine of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n","strided.acoshBy":"\nstrided.acoshBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the hyperbolic arccosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n","strided.acoshBy.ndarray":"\nstrided.acoshBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the hyperbolic arccosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n","strided.acotBy":"\nstrided.acotBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the inverse cotangent of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n","strided.acotBy.ndarray":"\nstrided.acotBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the inverse cotangent of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n","strided.acothBy":"\nstrided.acothBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the inverse hyperbolic cotangent of each element retrieved from an\n    input strided array `x` via a callback function and assigns each result to\n    an element in an output strided array `y`.\n","strided.acothBy.ndarray":"\nstrided.acothBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the inverse hyperbolic cotangent of each element retrieved from an\n    input strided array `x` via a callback function and assigns each result to\n    an element in an output strided array `y` using alternative indexing\n    semantics.\n","strided.acovercosBy":"\nstrided.acovercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the inverse coversed cosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n","strided.acovercosBy.ndarray":"\nstrided.acovercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the inverse coversed cosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n","strided.acoversinBy":"\nstrided.acoversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the inverse coversed sine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n","strided.acoversinBy.ndarray":"\nstrided.acoversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the inverse coversed sine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n","strided.add":"\nstrided.add( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, \n  y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )\n    Adds each element in a strided array `x` to a corresponding element in a\n    strided array `y` and assigns the results to elements in a strided array\n    `z`.\n","strided.add.ndarray":"\nstrided.add.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, \n  ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, \n  z:ArrayLikeObject, sz:integer, oz:integer )\n    Adds each element in a strided array `x` to a corresponding element in a\n    strided array `y` and assigns the results to elements in a strided array\n    `z` using alternative indexing semantics.\n","strided.addBy":"\nstrided.addBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, \n  clbk:Function[, thisArg:any] )\n    Performs element-wise addition of two strided arrays via a callback function\n    and assigns each result to an element in an output strided array.\n","strided.addBy.ndarray":"\nstrided.addBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, \n  thisArg:any] )\n    Performs element-wise addition of two strided arrays via a callback function\n    and assigns each result to an element in an output strided array using\n    alternative indexing semantics.\n","strided.ahavercosBy":"\nstrided.ahavercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the inverse half-value versed cosine of each element retrieved from\n    an input strided array `x` via a callback function and assigns each result\n    to an element in an output strided array `y`.\n","strided.ahavercosBy.ndarray":"\nstrided.ahavercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the inverse half-value versed cosine of each element retrieved from\n    an input strided array `x` via a callback function and assigns each result\n    to an element in an output strided array `y` using alternative indexing\n    semantics.\n","strided.ahaversinBy":"\nstrided.ahaversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the inverse half-value versed sine of each element retrieved from\n    an input strided array `x` via a callback function and assigns each result\n    to an element in an output strided array `y`.\n","strided.ahaversinBy.ndarray":"\nstrided.ahaversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the inverse half-value versed sine of each element retrieved from\n    an input strided array `x` via a callback function and assigns each result\n    to an element in an output strided array `y` using alternative indexing\n    semantics.\n","strided.asinBy":"\nstrided.asinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the arcsine of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y`.\n","strided.asinBy.ndarray":"\nstrided.asinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the arcsine of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n","strided.asinhBy":"\nstrided.asinhBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the hyperbolic arcsine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n","strided.asinhBy.ndarray":"\nstrided.asinhBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the hyperbolic arcsine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n","strided.atanBy":"\nstrided.atanBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the arctangent of each element retrieved from an input strided\n    array `x` via a callback function and assigns each result to an element in\n    an output strided array `y`.\n","strided.atanBy.ndarray":"\nstrided.atanBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the arctangent of each element retrieved from an input strided\n    array `x` via a callback function and assigns each result to an element in\n    an output strided array `y` using alternative indexing semantics.\n","strided.atanhBy":"\nstrided.atanhBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the hyperbolic arctangent of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n","strided.atanhBy.ndarray":"\nstrided.atanhBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the hyperbolic arctangent of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n","strided.avercosBy":"\nstrided.avercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the inverse versed cosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n","strided.avercosBy.ndarray":"\nstrided.avercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the inverse versed cosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n","strided.aversinBy":"\nstrided.aversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the inverse versed sine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n","strided.aversinBy.ndarray":"\nstrided.aversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the inverse versed sine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n","strided.besselj0By":"\nstrided.besselj0By( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the Bessel function of the first kind of order zero for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y`.\n","strided.besselj0By.ndarray":"\nstrided.besselj0By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the Bessel function of the first kind of order zero for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n","strided.besselj1By":"\nstrided.besselj1By( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the Bessel function of the first kind of order one for each element\n    retrieved from an input strided array `x` via a callback function and\n    assigns each result to an element in an output strided array `y`.\n","strided.besselj1By.ndarray":"\nstrided.besselj1By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the Bessel function of the first kind of order one for each element\n    retrieved from an input strided array `x` via a callback function and\n    assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n","strided.bessely0By":"\nstrided.bessely0By( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the Bessel function of the second kind of order zero for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y`.\n","strided.bessely0By.ndarray":"\nstrided.bessely0By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the Bessel function of the second kind of order zero for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n","strided.bessely1By":"\nstrided.bessely1By( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the Bessel function of the second kind of order one for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y`.\n","strided.bessely1By.ndarray":"\nstrided.bessely1By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the Bessel function of the second kind of order one for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n","strided.binetBy":"\nstrided.binetBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Evaluates Binet's formula extended to real numbers for each element\n    retrieved from an input strided array `x` via a callback function and\n    assigns each result to an element in an output strided array `y`.\n","strided.binetBy.ndarray":"\nstrided.binetBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Evaluates Binet's formula extended to real numbers for each element\n    retrieved from an input strided array `x` via a callback function and\n    assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n","strided.cbrt":"\nstrided.cbrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  dtypeY:any, y:ArrayLikeObject, strideY:integer )\n    Computes the cube root of each element in a strided array `x` and assigns\n    the results to elements in a strided array `y`.\n","strided.cbrt.ndarray":"\nstrided.cbrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n  strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n  strideY:integer, offsetY:integer )\n    Computes the cube root of each element in a strided array `x` and assigns\n    the results to elements in a strided array `y` using alternative indexing\n    semantics.\n","strided.cbrtBy":"\nstrided.cbrtBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the cube root of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y`.\n","strided.cbrtBy.ndarray":"\nstrided.cbrtBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the cube root of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n","strided.ceil":"\nstrided.ceil( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  dtypeY:any, y:ArrayLikeObject, strideY:integer )\n    Rounds each element in a strided array `x` toward positive infinity and\n    assigns the results to elements in a strided array `y`.\n","strided.ceil.ndarray":"\nstrided.ceil.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n  strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n  strideY:integer, offsetY:integer )\n    Rounds each element in a strided array `x` toward positive infinity and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n","strided.cosBy":"\nstrided.cosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the cosine for each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y`.\n","strided.cosBy.ndarray":"\nstrided.cosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the cosine for each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n","strided.deg2rad":"\nstrided.deg2rad( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  dtypeY:any, y:ArrayLikeObject, strideY:integer )\n    Converts each element in a strided array `x` from degrees to radians and\n    assigns the results to elements in a strided array `y`.\n","strided.deg2rad.ndarray":"\nstrided.deg2rad.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n  strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n  strideY:integer, offsetY:integer )\n    Converts each element in a strided array `x` from degrees to radians and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n","strided.dataTypes":"\nstrided.dataTypes()\n    Returns a list of strided array data types.\n","strided.dcbrtBy":"\nstrided.dcbrtBy( N:integer, x:Float64Array, sx:integer, y:Float64Array, \n  sy:integer, clbk:Function[, thisArg:any] )\n    Computes the cube root of each element retrieved from an input double-\n    precision floating-point strided array via a callback function and assigns\n    each result to an element in an output double-precision floating-point\n    strided array.\n","strided.dcbrtBy.ndarray":"\nstrided.dcbrtBy.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, \n  y:Float64Array, sy:integer, oy:integer, clbk:Function[, thisArg:any] )\n    Computes the cube root of each element retrieved from an input double-\n    precision floating-point strided array via a callback function and assigns\n    each result to an element in an output double-precision floating-point\n    strided array using alternative indexing semantics.\n","strided.dispatch":"\nstrided.dispatch( fcns:Function|ArrayLikeObject<Function>, \n  types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, \n  nout:integer )\n    Returns a strided array function interface which performs multiple dispatch.\n","strided.dispatchBy":"\nstrided.dispatchBy( fcns:Function|ArrayLikeObject<Function>, \n  types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, \n  nout:integer )\n    Returns a strided array function interface which accepts a callback function\n    and performs multiple dispatch.\n","strided.floor":"\nstrided.floor( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  dtypeY:any, y:ArrayLikeObject, strideY:integer )\n    Rounds each element in a strided array `x` toward negative infinity and\n    assigns the results to elements in a strided array `y`.\n","strided.floor.ndarray":"\nstrided.floor.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n  strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n  strideY:integer, offsetY:integer )\n    Rounds each element in a strided array `x` toward negative infinity and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n","strided.inv":"\nstrided.inv( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  dtypeY:any, y:ArrayLikeObject, strideY:integer )\n    Computes the multiplicative inverse for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y`.\n","strided.inv.ndarray":"\nstrided.inv.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, \n  offsetY:integer )\n    Computes the multiplicative inverse for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n","strided.mul":"\nstrided.mul( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, \n  y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )\n    Multiplies each element in a strided array `x` to a corresponding element in\n    a strided array `y` and assigns the results to elements in a strided array\n    `z`.\n","strided.mul.ndarray":"\nstrided.mul.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, \n  ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, \n  z:ArrayLikeObject, sz:integer, oz:integer )\n    Multiplies each element in a strided array `x` to a corresponding element in\n    a strided array `y` and assigns the results to elements in a strided array\n    `z` using alternative indexing semantics.\n","strided.mulBy":"\nstrided.mulBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, \n  clbk:Function[, thisArg:any] )\n    Performs element-wise multiplication of two strided arrays via a callback\n    function and assigns each result to an element in an output strided array.\n","strided.mulBy.ndarray":"\nstrided.mulBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, \n  thisArg:any] )\n    Performs element-wise multiplication of two strided arrays via a callback\n    function and assigns each result to an element in an output strided array\n    using alternative indexing semantics.\n","strided.ramp":"\nstrided.ramp( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  dtypeY:any, y:ArrayLikeObject, strideY:integer )\n    Evaluates the ramp function for each element in a strided array `x` and\n    assigns the results to elements in a strided array `y`.\n","strided.ramp.ndarray":"\nstrided.ramp.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n  strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n  strideY:integer, offsetY:integer )\n    Evaluates the ramp function for each element in a strided array `x` and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n","strided.rsqrt":"\nstrided.rsqrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  dtypeY:any, y:ArrayLikeObject, strideY:integer )\n    Computes the reciprocal square root for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y`.\n","strided.rsqrt.ndarray":"\nstrided.rsqrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n  strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n  strideY:integer, offsetY:integer )\n    Computes the reciprocal square root for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n","strided.sinBy":"\nstrided.sinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the sine of each element retrieved from an input strided array `x`\n    via a callback function and assigns each result to an element in an output\n    strided array `y`.\n","strided.sinBy.ndarray":"\nstrided.sinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the sine of each element retrieved from an input strided array `x`\n    via a callback function and assigns each result to an element in an output\n    strided array `y` using alternative indexing semantics.\n","strided.sqrt":"\nstrided.sqrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  dtypeY:any, y:ArrayLikeObject, strideY:integer )\n    Computes the principal square root for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y`.\n","strided.sqrt.ndarray":"\nstrided.sqrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n  strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n  strideY:integer, offsetY:integer )\n    Computes the principal square root for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n","strided.sqrtBy":"\nstrided.sqrtBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the principal square root for each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n","strided.sqrtBy.ndarray":"\nstrided.sqrtBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the principal square root for each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing semantics.\n","strided.sub":"\nstrided.sub( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, \n  y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )\n    Subtracts each element in a strided array `x` to a corresponding element in\n    a strided array `y` and assigns the results to elements in a strided array\n    `z`.\n","strided.sub.ndarray":"\nstrided.sub.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, \n  ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, \n  z:ArrayLikeObject, sz:integer, oz:integer )\n    Subtracts each element in a strided array `x` to a corresponding element in\n    a strided array `y` and assigns the results to elements in a strided array\n    `z` using alternative indexing semantics.\n","strided.subBy":"\nstrided.subBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, \n  clbk:Function[, thisArg:any] )\n    Performs element-wise subtraction of two strided arrays via a callback\n    function and assigns each result to an element in an output strided array.\n","strided.subBy.ndarray":"\nstrided.subBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, \n  thisArg:any] )\n    Performs element-wise subtraction of two strided arrays via a callback\n    function and assigns each result to an element in an output strided array\n    using alternative indexing semantics.\n","strided.trunc":"\nstrided.trunc( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  dtypeY:any, y:ArrayLikeObject, strideY:integer )\n    Rounds each element in a strided array `x` toward zero and assigns the\n    results to elements in a strided array `y`.\n","strided.trunc.ndarray":"\nstrided.trunc.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n  strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n  strideY:integer, offsetY:integer )\n    Rounds each element in a strided array `x` toward zero and assigns the\n    results to elements in a strided array `y` using alternative indexing\n    semantics.\n","stridedarray2iterator":"\nstridedarray2iterator( N:integer, src:ArrayLikeObject, stride:integer, \n  offset:integer[, mapFcn:Function[, thisArg:any]] )\n    Returns an iterator which iterates over elements of an array-like object\n    according to specified stride parameters.\n","stridedArrayStream":"\nstridedArrayStream( N:integer, buffer:ArrayLikeObject, stride:integer, \n  offset:integer[, options:Object] )\n    Creates a readable stream from a strided array-like object.\n","stridedArrayStream.factory":"\nstridedArrayStream.factory( [options:Object] )\n    Returns a function for creating readable streams from array-like objects.\n","stridedArrayStream.objectMode":"\nstridedArrayStream.objectMode( N:integer, buffer:ArrayLikeObject, \n  stride:integer, offset:integer[, options:Object] )\n    Returns an \"objectMode\" readable stream from a strided array-like object.\n","string2buffer":"\nstring2buffer( str:string[, encoding:string] )\n    Allocates a buffer containing a provided string.\n","sub2ind":"\nsub2ind( shape:ArrayLike, ...subscript:integer[, options:Object] )\n    Converts subscripts to a linear index.\n","substringAfter":"\nsubstringAfter( str:string, search:string[, fromIndex:integer] )\n    Returns the part of a string after a specified substring.\n","substringAfterLast":"\nsubstringAfterLast( str:string, search:string[, fromIndex:integer] )\n    Returns the part of a string after the last occurrence of a specified\n    substring.\n","substringBefore":"\nsubstringBefore( str:string, search:string )\n    Returns the part of a string before a specified substring.\n","substringBeforeLast":"\nsubstringBeforeLast( str:string, search:string )\n    Returns the part of a string before the last occurrence of a specified\n    substring.\n","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n    Returns a dataset consisting of labeled wireless sensor network data set\n    collected from a multi-hop wireless sensor network deployment using TelosB\n    motes.\n","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n    Returns a dataset consisting of labeled wireless sensor network data set\n    collected from a simple single-hop wireless sensor network deployment using\n    TelosB motes.\n","Symbol":"\nSymbol( [description:string] )\n    Returns a symbol.\n","tabulate":"\ntabulate( collection:Array|TypedArray|Object )\n    Generates a frequency table.\n","tabulateBy":"\ntabulateBy( collection:Array|TypedArray|Object, [options:Object,] \n  indicator:Function )\n    Generates a frequency table according to an indicator function.\n","tabulateByAsync":"\ntabulateByAsync( collection:Array|TypedArray|Object, [options:Object,] \n  indicator:Function, done:Function )\n    Generates a frequency table according to an indicator function.\n","tabulateByAsync.factory":"\ntabulateByAsync.factory( [options:Object,] indicator:Function )\n    Returns a function which generates a frequency table according to an\n    indicator function.\n","thunk":"\nthunk( fcn:Function[, ...args:any] )\n    Returns a thunk.\n","tic":"\ntic()\n    Returns a high-resolution time.\n","timeit":"\ntimeit( code:string, [options:Object,] clbk:Function )\n    Times a snippet.\n","tmpdir":"\ntmpdir()\n    Returns the directory for storing temporary files.\n","toc":"\ntoc( time:Array<integer> )\n    Returns a high-resolution time difference, where `time` is a two-element\n    array with format `[seconds, nanoseconds]`.\n","tokenize":"\ntokenize( str:string[, keepWhitespace:boolean] )\n    Tokenizes a string.\n","transformStream":"\ntransformStream( [options:Object] )\n    Returns a transform stream.\n","transformStream.factory":"\ntransformStream.factory( [options:Object] )\n    Returns a function for creating transform streams.\n","transformStream.objectMode":"\ntransformStream.objectMode( [options:Object] )\n    Returns an \"objectMode\" transform stream.\n","transformStream.ctor":"\ntransformStream.ctor( [options:Object] )\n    Returns a custom transform stream constructor.\n","trim":"\ntrim( str:string )\n    Trims whitespace from the beginning and end of a `string`.\n","truncate":"\ntruncate( str:string, len:integer[, ending:string] )\n    Truncates a string to a specified length.\n","truncateMiddle":"\ntruncateMiddle( str:string, len:integer[, seq:string] )\n    Truncates a string in the middle to a specified length.\n","trycatch":"\ntrycatch( x:Function, y:any )\n    If a function does not throw, returns the function return value; otherwise,\n    returns `y`.\n","trycatchAsync":"\ntrycatchAsync( x:Function, y:any, done:Function )\n    If a function does not return an error, invokes a callback with the function\n    result; otherwise, invokes a callback with a value `y`.\n","tryFunction":"\ntryFunction( fcn:Function[, thisArg:any] )\n    Wraps a function in a try/catch block.\n","tryRequire":"\ntryRequire( id:string )\n    Wraps `require` in a `try/catch` block.\n","trythen":"\ntrythen( x:Function, y:Function )\n    If a function does not throw, returns the function return value; otherwise,\n    returns the value returned by a second function `y`.\n","trythenAsync":"\ntrythenAsync( x:Function, y:Function, done:Function )\n    If a function does not return an error, invokes a callback with the function\n    result; otherwise, invokes a second function `y`.\n","ttest":"\nttest( x:Array<number>[, y:Array<number>][, options:Object] )\n    Computes a one-sample or paired Student's t test.\n","ttest2":"\nttest2( x:Array<number>, y:Array<number>[, options:Object] )\n    Computes a two-sample Student's t test.\n","TWO_PI":"\nTWO_PI\n    The mathematical constant `π` times `2`.\n","typedarray":"\ntypedarray( [dtype:string] )\n    Creates a typed array.\n\ntypedarray( length:integer[, dtype:string] )\n    Returns a typed array having a specified length.\n\ntypedarray( typedarray:TypedArray[, dtype:string] )\n    Creates a typed array from another typed array.\n\ntypedarray( obj:Object[, dtype:string] )\n    Creates a typed array from an array-like object or iterable.\n\ntypedarray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n  dtype:string] )\n    Returns a typed array view of an ArrayBuffer.\n","typedarray2json":"\ntypedarray2json( arr:TypedArray )\n    Returns a JSON representation of a typed array.\n","typedarrayCtors":"\ntypedarrayCtors( dtype:string )\n    Returns a typed array constructor.\n","typedarrayDataTypes":"\ntypedarrayDataTypes()\n    Returns a list of typed array data types.\n","typedarraypool":"\ntypedarraypool( [dtype:string] )\n    Returns an uninitialized typed array from a typed array memory pool.\n\ntypedarraypool( length:integer[, dtype:string] )\n    Returns an uninitialized typed array having a specified length from a typed\n    array memory pool.\n\ntypedarraypool( typedarray:TypedArray[, dtype:string] )\n    Creates a pooled typed array from another typed array.\n\ntypedarraypool( obj:Object[, dtype:string] )\n    Creates a pooled typed array from an array-like object.\n","typedarraypool.malloc":"\ntypedarraypool.malloc( [dtype:string] )\n    Returns an uninitialized typed array from a typed array memory pool.\n\ntypedarraypool.malloc( length:integer[, dtype:string] )\n    Returns a typed array having a specified length from a typed array memory\n    pool.\n\ntypedarraypool.malloc( typedarray:TypedArray[, dtype:string] )\n    Creates a pooled typed array from another typed array.\n\ntypedarraypool.malloc( obj:Object[, dtype:string] )\n    Creates a pooled typed array from an array-like object.\n","typedarraypool.calloc":"\ntypedarraypool.calloc( [dtype:string] )\n    Returns a zero-initialized typed array from a typed array memory pool.\n\ntypedarraypool.calloc( length:integer[, dtype:string] )\n    Returns a zero-initialized typed array having a specified length from a\n    typed array memory pool.\n","typedarraypool.free":"\ntypedarraypool.free( buf:TypedArray|ArrayBuffer )\n    Frees a typed array or typed array buffer for use in a future allocation.\n","typedarraypool.clear":"\ntypedarraypool.clear()\n    Clears the typed array pool allowing garbage collection of previously\n    allocated (and currently free) array buffers.\n","typedarraypool.highWaterMark":"\ntypedarraypool.highWaterMark\n    Read-only property returning the pool's high water mark.\n","typedarraypool.nbytes":"\ntypedarraypool.nbytes\n    Read-only property returning the total number of allocated bytes.\n","typedarraypool.factory":"\ntypedarraypool.factory( [options:Object] )\n    Creates a typed array pool.\n","typemax":"\ntypemax( dtype:string )\n    Returns the maximum value of a specified numeric type.\n","typemin":"\ntypemin( dtype:string )\n    Returns the minimum value of a specified numeric type.\n","typeOf":"\ntypeOf( value:any )\n    Determines a value's type.\n","UINT8_MAX":"\nUINT8_MAX\n    Maximum unsigned 8-bit integer.\n","UINT8_NUM_BYTES":"\nUINT8_NUM_BYTES\n    Size (in bytes) of an 8-bit unsigned integer.\n","Uint8Array":"\nUint8Array()\n    A typed array constructor which returns a typed array representing an array\n    of 8-bit unsigned integers in the platform byte order.\n\nUint8Array( length:integer )\n    Returns a typed array having a specified length.\n\nUint8Array( typedarray:TypedArray )\n    Creates a typed array from another typed array.\n\nUint8Array( obj:Object )\n    Creates a typed array from an array-like object or iterable.\n\nUint8Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a typed array view of an ArrayBuffer.\n","Uint8Array.from":"\nUint8Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n    Creates a new typed array from an array-like object or an iterable.\n","Uint8Array.of":"\nUint8Array.of( element0:number[, element1:number[, ...elementN:number]] )\n    Creates a new typed array from a variable number of arguments.\n","Uint8Array.BYTES_PER_ELEMENT":"\nUint8Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Uint8Array.name":"\nUint8Array.name\n    Typed array constructor name.\n","Uint8Array.prototype.buffer":"\nUint8Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n","Uint8Array.prototype.byteLength":"\nUint8Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n","Uint8Array.prototype.byteOffset":"\nUint8Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n","Uint8Array.prototype.BYTES_PER_ELEMENT":"\nUint8Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Uint8Array.prototype.length":"\nUint8Array.prototype.length\n    Read-only property which returns the number of view elements.\n","Uint8Array.prototype.copyWithin":"\nUint8Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint8Array.prototype.entries":"\nUint8Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","Uint8Array.prototype.every":"\nUint8Array.prototype.every( predicate:Function[, thisArg:Any] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n","Uint8Array.prototype.fill":"\nUint8Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n","Uint8Array.prototype.filter":"\nUint8Array.prototype.filter( predicate:Function[, thisArg:Any] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n","Uint8Array.prototype.find":"\nUint8Array.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n","Uint8Array.prototype.findIndex":"\nUint8Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n","Uint8Array.prototype.forEach":"\nUint8Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n    Invokes a callback for each array element.\n","Uint8Array.prototype.includes":"\nUint8Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a search element.\n","Uint8Array.prototype.indexOf":"\nUint8Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n","Uint8Array.prototype.join":"\nUint8Array.prototype.join( [separator:string] )\n    Serializes an array by joining all array elements as a string.\n","Uint8Array.prototype.keys":"\nUint8Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n","Uint8Array.prototype.lastIndexOf":"\nUint8Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n","Uint8Array.prototype.map":"\nUint8Array.prototype.map( fcn:Function[, thisArg:Any] )\n    Maps each array element to an element in a new typed array.\n","Uint8Array.prototype.reduce":"\nUint8Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n","Uint8Array.prototype.reduceRight":"\nUint8Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n","Uint8Array.prototype.reverse":"\nUint8Array.prototype.reverse()\n    Reverses an array *in-place*.\n","Uint8Array.prototype.set":"\nUint8Array.prototype.set( arr:ArrayLike[, offset:integer] )\n    Sets array elements.\n","Uint8Array.prototype.slice":"\nUint8Array.prototype.slice( [begin:integer[, end:integer]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n","Uint8Array.prototype.some":"\nUint8Array.prototype.some( predicate:Function[, thisArg:Any] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n","Uint8Array.prototype.sort":"\nUint8Array.prototype.sort( [compareFunction:Function] )\n    Sorts an array *in-place*.\n","Uint8Array.prototype.subarray":"\nUint8Array.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n","Uint8Array.prototype.toLocaleString":"\nUint8Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n    Serializes an array as a locale-specific string.\n","Uint8Array.prototype.toString":"\nUint8Array.prototype.toString()\n    Serializes an array as a string.\n","Uint8Array.prototype.values":"\nUint8Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n","Uint8ClampedArray":"\nUint8ClampedArray()\n    A typed array constructor which returns a typed array representing an array\n    of 8-bit unsigned integers in the platform byte order clamped to 0-255.\n\nUint8ClampedArray( length:integer )\n    Returns a typed array having a specified length.\n\nUint8ClampedArray( typedarray:TypedArray )\n    Creates a typed array from another typed array.\n\nUint8ClampedArray( obj:Object )\n    Creates a typed array from an array-like object or iterable.\n\nUint8ClampedArray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a typed array view of an ArrayBuffer.\n","Uint8ClampedArray.from":"\nUint8ClampedArray.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n    Creates a new typed array from an array-like object or an iterable.\n","Uint8ClampedArray.of":"\nUint8ClampedArray.of( element0:number[, element1:number[, ...elementN:number]] )\n    Creates a new typed array from a variable number of arguments.\n","Uint8ClampedArray.BYTES_PER_ELEMENT":"\nUint8ClampedArray.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Uint8ClampedArray.name":"\nUint8ClampedArray.name\n    Typed array constructor name.\n","Uint8ClampedArray.prototype.buffer":"\nUint8ClampedArray.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n","Uint8ClampedArray.prototype.byteLength":"\nUint8ClampedArray.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n","Uint8ClampedArray.prototype.byteOffset":"\nUint8ClampedArray.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n","Uint8ClampedArray.prototype.BYTES_PER_ELEMENT":"\nUint8ClampedArray.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Uint8ClampedArray.prototype.length":"\nUint8ClampedArray.prototype.length\n    Read-only property which returns the number of view elements.\n","Uint8ClampedArray.prototype.copyWithin":"\nUint8ClampedArray.prototype.copyWithin( target:integer, start:integer[, \n  end:integer] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint8ClampedArray.prototype.entries":"\nUint8ClampedArray.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","Uint8ClampedArray.prototype.every":"\nUint8ClampedArray.prototype.every( predicate:Function[, thisArg:Any] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n","Uint8ClampedArray.prototype.fill":"\nUint8ClampedArray.prototype.fill( value:number[, start:integer[, end:integer]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n","Uint8ClampedArray.prototype.filter":"\nUint8ClampedArray.prototype.filter( predicate:Function[, thisArg:Any] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n","Uint8ClampedArray.prototype.find":"\nUint8ClampedArray.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n","Uint8ClampedArray.prototype.findIndex":"\nUint8ClampedArray.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n","Uint8ClampedArray.prototype.forEach":"\nUint8ClampedArray.prototype.forEach( fcn:Function[, thisArg:Any] )\n    Invokes a callback for each array element.\n","Uint8ClampedArray.prototype.includes":"\nUint8ClampedArray.prototype.includes( searchElement:number[, \n  fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a search element.\n","Uint8ClampedArray.prototype.indexOf":"\nUint8ClampedArray.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n","Uint8ClampedArray.prototype.join":"\nUint8ClampedArray.prototype.join( [separator:string] )\n    Serializes an array by joining all array elements as a string.\n","Uint8ClampedArray.prototype.keys":"\nUint8ClampedArray.prototype.keys()\n    Returns an iterator for iterating over array keys.\n","Uint8ClampedArray.prototype.lastIndexOf":"\nUint8ClampedArray.prototype.lastIndexOf( searchElement:number[, \n  fromIndex:integer] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n","Uint8ClampedArray.prototype.map":"\nUint8ClampedArray.prototype.map( fcn:Function[, thisArg:Any] )\n    Maps each array element to an element in a new typed array.\n","Uint8ClampedArray.prototype.reduce":"\nUint8ClampedArray.prototype.reduce( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n","Uint8ClampedArray.prototype.reduceRight":"\nUint8ClampedArray.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n","Uint8ClampedArray.prototype.reverse":"\nUint8ClampedArray.prototype.reverse()\n    Reverses an array *in-place*.\n","Uint8ClampedArray.prototype.set":"\nUint8ClampedArray.prototype.set( arr:ArrayLike[, offset:integer] )\n    Sets array elements.\n","Uint8ClampedArray.prototype.slice":"\nUint8ClampedArray.prototype.slice( [begin:integer[, end:integer]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n","Uint8ClampedArray.prototype.some":"\nUint8ClampedArray.prototype.some( predicate:Function[, thisArg:Any] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n","Uint8ClampedArray.prototype.sort":"\nUint8ClampedArray.prototype.sort( [compareFunction:Function] )\n    Sorts an array *in-place*.\n","Uint8ClampedArray.prototype.subarray":"\nUint8ClampedArray.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n","Uint8ClampedArray.prototype.toLocaleString":"\nUint8ClampedArray.prototype.toLocaleString( [locales:string|Array[, \n  options:Object]] )\n    Serializes an array as a locale-specific string.\n","Uint8ClampedArray.prototype.toString":"\nUint8ClampedArray.prototype.toString()\n    Serializes an array as a string.\n","Uint8ClampedArray.prototype.values":"\nUint8ClampedArray.prototype.values()\n    Returns an iterator for iterating over array elements.\n","UINT16_MAX":"\nUINT16_MAX\n    Maximum unsigned 16-bit integer.\n","UINT16_NUM_BYTES":"\nUINT16_NUM_BYTES\n    Size (in bytes) of a 16-bit unsigned integer.\n","Uint16Array":"\nUint16Array()\n    A typed array constructor which returns a typed array representing an array\n    of 16-bit unsigned integers in the platform byte order.\n\nUint16Array( length:integer )\n    Returns a typed array having a specified length.\n\nUint16Array( typedarray:TypedArray )\n    Creates a typed array from another typed array.\n\nUint16Array( obj:Object )\n    Creates a typed array from an array-like object or iterable.\n\nUint16Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a typed array view of an ArrayBuffer.\n","Uint16Array.from":"\nUint16Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n    Creates a new typed array from an array-like object or an iterable.\n","Uint16Array.of":"\nUint16Array.of( element0:number[, element1:number[, ...elementN:number]] )\n    Creates a new typed array from a variable number of arguments.\n","Uint16Array.BYTES_PER_ELEMENT":"\nUint16Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Uint16Array.name":"\nUint16Array.name\n    Typed array constructor name.\n","Uint16Array.prototype.buffer":"\nUint16Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n","Uint16Array.prototype.byteLength":"\nUint16Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n","Uint16Array.prototype.byteOffset":"\nUint16Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n","Uint16Array.prototype.BYTES_PER_ELEMENT":"\nUint16Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Uint16Array.prototype.length":"\nUint16Array.prototype.length\n    Read-only property which returns the number of view elements.\n","Uint16Array.prototype.copyWithin":"\nUint16Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint16Array.prototype.entries":"\nUint16Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","Uint16Array.prototype.every":"\nUint16Array.prototype.every( predicate:Function[, thisArg:Any] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n","Uint16Array.prototype.fill":"\nUint16Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n","Uint16Array.prototype.filter":"\nUint16Array.prototype.filter( predicate:Function[, thisArg:Any] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n","Uint16Array.prototype.find":"\nUint16Array.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n","Uint16Array.prototype.findIndex":"\nUint16Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n","Uint16Array.prototype.forEach":"\nUint16Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n    Invokes a callback for each array element.\n","Uint16Array.prototype.includes":"\nUint16Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a search element.\n","Uint16Array.prototype.indexOf":"\nUint16Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n","Uint16Array.prototype.join":"\nUint16Array.prototype.join( [separator:string] )\n    Serializes an array by joining all array elements as a string.\n","Uint16Array.prototype.keys":"\nUint16Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n","Uint16Array.prototype.lastIndexOf":"\nUint16Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n","Uint16Array.prototype.map":"\nUint16Array.prototype.map( fcn:Function[, thisArg:Any] )\n    Maps each array element to an element in a new typed array.\n","Uint16Array.prototype.reduce":"\nUint16Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n","Uint16Array.prototype.reduceRight":"\nUint16Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n","Uint16Array.prototype.reverse":"\nUint16Array.prototype.reverse()\n    Reverses an array *in-place*.\n","Uint16Array.prototype.set":"\nUint16Array.prototype.set( arr:ArrayLike[, offset:integer] )\n    Sets array elements.\n","Uint16Array.prototype.slice":"\nUint16Array.prototype.slice( [begin:integer[, end:integer]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n","Uint16Array.prototype.some":"\nUint16Array.prototype.some( predicate:Function[, thisArg:Any] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n","Uint16Array.prototype.sort":"\nUint16Array.prototype.sort( [compareFunction:Function] )\n    Sorts an array *in-place*.\n","Uint16Array.prototype.subarray":"\nUint16Array.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n","Uint16Array.prototype.toLocaleString":"\nUint16Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n    Serializes an array as a locale-specific string.\n","Uint16Array.prototype.toString":"\nUint16Array.prototype.toString()\n    Serializes an array as a string.\n","Uint16Array.prototype.values":"\nUint16Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n","UINT32_MAX":"\nUINT32_MAX\n    Maximum unsigned 32-bit integer.\n","UINT32_NUM_BYTES":"\nUINT32_NUM_BYTES\n    Size (in bytes) of a 32-bit unsigned integer.\n","Uint32Array":"\nUint32Array()\n    A typed array constructor which returns a typed array representing an array\n    of 32-bit unsigned integers in the platform byte order.\n\nUint32Array( length:integer )\n    Returns a typed array having a specified length.\n\nUint32Array( typedarray:TypedArray )\n    Creates a typed array from another typed array.\n\nUint32Array( obj:Object )\n    Creates a typed array from an array-like object or iterable.\n\nUint32Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a typed array view of an ArrayBuffer.\n","Uint32Array.from":"\nUint32Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n    Creates a new typed array from an array-like object or an iterable.\n","Uint32Array.of":"\nUint32Array.of( element0:number[, element1:number[, ...elementN:number]] )\n    Creates a new typed array from a variable number of arguments.\n","Uint32Array.BYTES_PER_ELEMENT":"\nUint32Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Uint32Array.name":"\nUint32Array.name\n    Typed array constructor name.\n","Uint32Array.prototype.buffer":"\nUint32Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n","Uint32Array.prototype.byteLength":"\nUint32Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n","Uint32Array.prototype.byteOffset":"\nUint32Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n","Uint32Array.prototype.BYTES_PER_ELEMENT":"\nUint32Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Uint32Array.prototype.length":"\nUint32Array.prototype.length\n    Read-only property which returns the number of view elements.\n","Uint32Array.prototype.copyWithin":"\nUint32Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint32Array.prototype.entries":"\nUint32Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","Uint32Array.prototype.every":"\nUint32Array.prototype.every( predicate:Function[, thisArg:Any] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n","Uint32Array.prototype.fill":"\nUint32Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n","Uint32Array.prototype.filter":"\nUint32Array.prototype.filter( predicate:Function[, thisArg:Any] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n","Uint32Array.prototype.find":"\nUint32Array.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n","Uint32Array.prototype.findIndex":"\nUint32Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n","Uint32Array.prototype.forEach":"\nUint32Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n    Invokes a callback for each array element.\n","Uint32Array.prototype.includes":"\nUint32Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a search element.\n","Uint32Array.prototype.indexOf":"\nUint32Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n","Uint32Array.prototype.join":"\nUint32Array.prototype.join( [separator:string] )\n    Serializes an array by joining all array elements as a string.\n","Uint32Array.prototype.keys":"\nUint32Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n","Uint32Array.prototype.lastIndexOf":"\nUint32Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n","Uint32Array.prototype.map":"\nUint32Array.prototype.map( fcn:Function[, thisArg:Any] )\n    Maps each array element to an element in a new typed array.\n","Uint32Array.prototype.reduce":"\nUint32Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n","Uint32Array.prototype.reduceRight":"\nUint32Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n","Uint32Array.prototype.reverse":"\nUint32Array.prototype.reverse()\n    Reverses an array *in-place*.\n","Uint32Array.prototype.set":"\nUint32Array.prototype.set( arr:ArrayLike[, offset:integer] )\n    Sets array elements.\n","Uint32Array.prototype.slice":"\nUint32Array.prototype.slice( [begin:integer[, end:integer]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n","Uint32Array.prototype.some":"\nUint32Array.prototype.some( predicate:Function[, thisArg:Any] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n","Uint32Array.prototype.sort":"\nUint32Array.prototype.sort( [compareFunction:Function] )\n    Sorts an array *in-place*.\n","Uint32Array.prototype.subarray":"\nUint32Array.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n","Uint32Array.prototype.toLocaleString":"\nUint32Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n    Serializes an array as a locale-specific string.\n","Uint32Array.prototype.toString":"\nUint32Array.prototype.toString()\n    Serializes an array as a string.\n","Uint32Array.prototype.values":"\nUint32Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n","umask":"\numask( [mask:integer|string,] [options:Object] )\n    Returns the current process mask, if not provided a mask; otherwise, sets\n    the process mask and returns the previous mask.\n","uncapitalize":"\nuncapitalize( str:string )\n    Lowercases the first character of a string.\n","uncapitalizeKeys":"\nuncapitalizeKeys( obj:Object )\n    Converts the first letter of each object key to lowercase.\n","uncurry":"\nuncurry( fcn:Function[, arity:integer, ][thisArg:any] )\n    Transforms a curried function into a function invoked with multiple\n    arguments.\n","uncurryRight":"\nuncurryRight( fcn:Function[, arity:integer, ][thisArg:any] )\n    Transforms a curried function into a function invoked with multiple\n    arguments.\n","UNICODE_MAX":"\nUNICODE_MAX\n    Maximum Unicode code point.\n","UNICODE_MAX_BMP":"\nUNICODE_MAX_BMP\n    Maximum Unicode code point in the Basic Multilingual Plane (BMP).\n","UnicodeColumnChartSparkline":"\nUnicodeColumnChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n    Returns a sparkline column chart instance.\n","UnicodeLineChartSparkline":"\nUnicodeLineChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n    Returns a sparkline line chart instance.\n","UnicodeSparkline":"\nUnicodeSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n    Returns a Unicode sparkline instance.\n","UnicodeTristateChartSparkline":"\nUnicodeTristateChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n    Returns a sparkline tristate chart instance.\n","UnicodeUpDownChartSparkline":"\nUnicodeUpDownChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n    Returns a sparkline up/down chart instance.\n","UnicodeWinLossChartSparkline":"\nUnicodeWinLossChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n    Returns a sparkline win/loss chart instance.\n","unlink":"\nunlink( path:string|Buffer|integer, clbk:Function )\n    Asynchronously removes a directory entry.\n","unlink.sync":"\nunlink.sync( path:string|Buffer|integer )\n    Synchronously removes a directory entry.\n","unshift":"\nunshift( collection:Array|TypedArray|Object, ...items:any )\n    Adds one or more elements to the beginning of a collection.\n","until":"\nuntil( predicate:Function, fcn:Function[, thisArg:any] )\n    Invokes a function until a test condition is true.\n","untilAsync":"\nuntilAsync( predicate:Function, fcn:Function, done:Function[, thisArg:any] )\n    Invokes a function until a test condition is true.\n","untilEach":"\nuntilEach( collection:Array|TypedArray|Object, predicate:Function, \n  fcn:Function[, thisArg:any] )\n    Until a test condition is true, invokes a function for each element in a\n    collection.\n","untilEachRight":"\nuntilEachRight( collection:Array|TypedArray|Object, predicate:Function, \n  fcn:Function[, thisArg:any] )\n    Until a test condition is true, invokes a function for each element in a\n    collection, iterating from right to left.\n","unzip":"\nunzip( arr:Array[, idx:Array<number>] )\n    Unzips a zipped array (i.e., a nested array of tuples).\n","uppercase":"\nuppercase( str:string )\n    Converts a string to uppercase.\n","uppercaseKeys":"\nuppercaseKeys( obj:Object )\n    Converts each object key to uppercase.\n","US_STATES_ABBR":"\nUS_STATES_ABBR()\n    Returns a list of US state two-letter abbreviations in alphabetical order\n    according to state name.\n","US_STATES_CAPITALS":"\nUS_STATES_CAPITALS()\n    Returns a list of US state capitals in alphabetical order according to state\n    name.\n","US_STATES_CAPITALS_NAMES":"\nUS_STATES_CAPITALS_NAMES()\n    Returns an object mapping US state capitals to state names.\n","US_STATES_NAMES":"\nUS_STATES_NAMES()\n    Returns a list of US state names in alphabetical order.\n","US_STATES_NAMES_CAPITALS":"\nUS_STATES_NAMES_CAPITALS()\n    Returns an object mapping US state names to state capitals.\n","utf16ToUTF8Array":"\nutf16ToUTF8Array( str:string )\n    Converts a UTF-16 encoded string to an array of integers using UTF-8\n    encoding.\n","vartest":"\nvartest( x:Array<number>, y:Array<number>[, options:Object] )\n    Computes a two-sample F-test for equal variances.\n","waterfall":"\nwaterfall( fcns:Array<Function>, clbk:Function[, thisArg:any] )\n    Executes functions in series, passing the results of one function as\n    arguments to the next function.\n","waterfall.factory":"\nwaterfall.factory( fcns:Array<Function>, clbk:Function[, thisArg:any] )\n    Returns a reusable waterfall function.\n","WebAssemblyMemory":"\nWebAssemblyMemory( descriptor:Object )\n    WebAssembly memory constructor.\n","WebAssemblyMemory.prototype.buffer":"\nWebAssemblyMemory.prototype.buffer\n    Read-only property which returns the ArrayBuffer (or SharedArrayBuffer)\n    referenced by the memory instance.\n","WebAssemblyMemory.prototype.grow":"\nWebAssemblyMemory.prototype.grow( delta:integer )\n    Increases the size of the memory instance by a specified number of\n    WebAssembly pages (i.e., 64KiB).\n","whileAsync":"\nwhileAsync( predicate:Function, fcn:Function, done:Function[, thisArg:any] )\n    Invokes a function while a test condition is true.\n","whileEach":"\nwhileEach( collection:Array|TypedArray|Object, predicate:Function, \n  fcn:Function[, thisArg:any] )\n    While a test condition is true, invokes a function for each element in a\n    collection.\n","whileEachRight":"\nwhileEachRight( collection:Array|TypedArray|Object, predicate:Function, \n  fcn:Function[, thisArg:any] )\n    While a test condition is true, invokes a function for each element in a\n    collection, iterating from right to left.\n","whilst":"\nwhilst( predicate:Function, fcn:Function[, thisArg:any] )\n    Invokes a function while a test condition is true.\n","wilcoxon":"\nwilcoxon( x:Array|TypedArray[, y:Array|TypedArray][, options:Object] )\n    Computes a one-sample or paired Wilcoxon signed rank test.\n","writableProperties":"\nwritableProperties( value:any )\n    Returns an array of an object's own writable property names and symbols.\n","writablePropertiesIn":"\nwritablePropertiesIn( value:any )\n    Returns an array of an object's own and inherited writable property names\n    and symbols.\n","writablePropertyNames":"\nwritablePropertyNames( value:any )\n    Returns an array of an object's own writable property names.\n","writablePropertyNamesIn":"\nwritablePropertyNamesIn( value:any )\n    Returns an array of an object's own and inherited writable property names.\n","writablePropertySymbols":"\nwritablePropertySymbols( value:any )\n    Returns an array of an object's own writable symbol properties.\n","writablePropertySymbolsIn":"\nwritablePropertySymbolsIn( value:any )\n    Returns an array of an object's own and inherited writable symbol\n    properties.\n","writeFile":"\nwriteFile( file:string|Buffer|integer, data:string|Buffer[, \n  options:Object|string], clbk:Function )\n    Asynchronously writes data to a file.\n","writeFile.sync":"\nwriteFile.sync( file:string|Buffer|integer, data:string|Buffer[, \n  options:Object|string] )\n    Synchronously writes data to a file.\n","zip":"\nzip( ...arr:Array[, options:Object] )\n    Generates array tuples from input arrays.\n","ztest":"\nztest( x:Array<number>, sigma:number[, options:Object] )\n    Computes a one-sample z-test.\n","ztest2":"\nztest2( x:Array<number>, y:Array<number>, sigmax:number, sigmay:number[, \n  options:Object] )\n    Computes a two-sample z-test.\n"}
+{"abs":"\nabs( x:ndarray|ArrayLikeObject|number[, options:Object] )\n    Computes the absolute value.\n","abs.assign":"\nabs.assign( x:ndarray|ArrayLikeObject, y:ndarray|ArrayLikeObject )\n    Computes the absolute value and assigns results to a provided output array.\n","acartesianPower":"\nacartesianPower( x:ArrayLikeObject, n:integer )\n    Returns the Cartesian power.\n","acartesianProduct":"\nacartesianProduct( x1:ArrayLikeObject, x2:ArrayLikeObject )\n    Returns the Cartesian product.\n","acartesianSquare":"\nacartesianSquare( x:ArrayLikeObject )\n    Returns the Cartesian square.\n","acronym":"\nacronym( str:string[, options:Object] )\n    Generates an acronym for a given string.\n","aempty":"\naempty( length:integer[, dtype:string] )\n    Creates an uninitialized array having a specified length.\n","aemptyLike":"\naemptyLike( x:TypedArray|Array[, dtype:string] )\n    Creates an uninitialized array having the same length and data type as a\n    provided input array.\n","AFINN_96":"\nAFINN_96()\n    Returns a list of English words rated for valence.\n","AFINN_111":"\nAFINN_111()\n    Returns a list of English words rated for valence.\n","afull":"\nafull( length:integer, value:any[, dtype:string] )\n    Returns a filled array having a specified length.\n","afullLike":"\nafullLike( x:TypedArray|Array[, dtype:string] )\n    Returns a filled array having the same length and data type as a provided\n    input array.\n","alias2pkg":"\nalias2pkg( alias:string )\n    Returns the package name associated with a provided alias.\n","alias2related":"\nalias2related( alias:string )\n    Returns aliases related to a specified alias.\n","alias2standalone":"\nalias2standalone( alias:string )\n    Returns the standalone package name associated with a provided alias.\n","aliases":"\naliases( [namespace:string] )\n    Returns a list of standard library aliases.\n","allocUnsafe":"\nallocUnsafe( size:integer )\n    Allocates a buffer having a specified number of bytes.\n","amskfilter":"\namskfilter( x:Array|TypedArray|Object, mask:Array|TypedArray|Object )\n    Returns a new array by applying a mask to a provided input array.\n","amskput":"\namskput( x:ArrayLikeObject, mask:ArrayLikeObject, values:ArrayLikeObject[, \n  options:Object] )\n    Replaces elements of an array with provided values according to a provided\n    mask array.\n","amskreject":"\namskreject( x:Array|TypedArray|Object, mask:Array|TypedArray|Object )\n    Returns a new array by applying a mask to a provided input array.\n","anans":"\nanans( length:integer[, dtype:string] )\n    Returns an array filled with NaNs and having a specified length.\n","anansLike":"\nanansLike( x:TypedArray|Array[, dtype:string] )\n    Returns an array filled with NaNs and having the same length and data type\n    as a provided input array.\n","anova1":"\nanova1( x:Array<number>, factor:Array[, options:Object] )\n    Performs a one-way analysis of variance.\n","ANSCOMBES_QUARTET":"\nANSCOMBES_QUARTET()\n    Returns Anscombe's quartet.\n","any":"\nany( collection:Array|TypedArray|Object )\n    Tests whether at least one element in a collection is truthy.\n","anyBy":"\nanyBy( collection:Array|TypedArray|Object, predicate:Function[, thisArg:any ] )\n    Tests whether at least one element in a collection passes a test implemented\n    by a predicate function.\n","anyByAsync":"\nanyByAsync( collection:Array|TypedArray|Object, [options:Object,] \n  predicate:Function, done:Function )\n    Tests whether at least one element in a collection passes a test implemented\n    by a predicate function.\n","anyByAsync.factory":"\nanyByAsync.factory( [options:Object,] predicate:Function )\n    Returns a function which tests whether at least one element in a collection\n    passes a test implemented by a predicate function.\n","anyByRight":"\nanyByRight( collection:Array|TypedArray|Object, predicate:Function[, \n  thisArg:any ] )\n    Tests whether at least one element in a collection passes a test implemented\n    by a predicate function, iterating from right to left.\n","anyByRightAsync":"\nanyByRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n  predicate:Function, done:Function )\n    Tests whether at least one element in a collection passes a test implemented\n    by a predicate function, iterating from right to left.\n","anyByRightAsync.factory":"\nanyByRightAsync.factory( [options:Object,] predicate:Function )\n    Returns a function which tests whether at least one element in a collection\n    passes a test implemented by a predicate function, iterating from right to\n    left.\n","anyInBy":"\nanyInBy( object:Object, predicate:Function[, thisArg:any ] )\n    Tests whether at least one value in an object passes a test implemented by\n    a predicate function.\n","anyOwnBy":"\nanyOwnBy( object:Object, predicate:Function[, thisArg:any ] )\n    Tests whether at least one own property of an object passes a\n    test implemented by a predicate function.\n","aones":"\naones( length:integer[, dtype:string] )\n    Returns an array filled with ones and having a specified length.\n","aonesLike":"\naonesLike( x:TypedArray|Array[, dtype:string] )\n    Returns an array filled with ones and having the same length and data type\n    as a provided input array.\n","aoneTo":"\naoneTo( n:integer[, dtype:string] )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from one.\n","aoneToLike":"\naoneToLike( x:TypedArray|Array[, dtype:string] )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from one and having the same length and data type as a provided\n    input array.\n","APERY":"\nAPERY\n    Apéry's constant.\n","aplace":"\naplace( x:ArrayLikeObject, mask:ArrayLikeObject, values:ArrayLikeObject[, \n  options:Object] )\n    Replaces elements of an array with provided values according to a provided\n    mask array.\n","append":"\nappend( collection1:Array|TypedArray|Object, \n  collection2:Array|TypedArray|Object )\n    Adds the elements of one collection to the end of another collection.\n","aput":"\naput( x:ArrayLikeObject, indices:ArrayLikeObject<integer>, \n  values:ArrayLikeObject[, options:Object] )\n    Replaces specified elements of an array with provided values.\n","ARCH":"\nARCH\n    Operating system CPU architecture for which the JavaScript runtime binary\n    was compiled.\n","argumentFunction":"\nargumentFunction( idx:integer )\n    Returns a function which always returns a specified argument.\n","ARGV":"\nARGV\n    An array containing command-line arguments passed when launching the calling\n    process.\n","array":"\narray( [buffer:Array|TypedArray|Buffer|ndarray,] [options:Object] )\n    Returns a multidimensional array.\n","array2buffer":"\narray2buffer( arr:Array<integer> )\n    Allocates a buffer using an octet array.\n","array2fancy":"\narray2fancy( x:Array|TypedArray|Object[, options:Object] )\n    Converts an array to an object supporting fancy indexing.\n","array2fancy.factory":"\narray2fancy.factory( [options:Object] )\n    Returns a function for converting an array to an object supporting fancy\n    indexing.\n","array2fancy.idx":"\narray2fancy.idx( x:Array|TypedArray|Object[, options:Object] )\n    Wraps a provided array as an array index object.\n","array2iterator":"\narray2iterator( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )\n    Returns an iterator which iterates over the elements of an array-like\n    object.\n","array2iteratorRight":"\narray2iteratorRight( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )\n    Returns an iterator which iterates from right to left over the elements of\n    an array-like object.\n","ArrayBuffer":"\nArrayBuffer( size:integer )\n    Returns an array buffer having a specified number of bytes.\n","ArrayBuffer.length":"\nArrayBuffer.length\n    Number of input arguments the constructor accepts.\n","ArrayBuffer.isView":"\nArrayBuffer.isView( arr:any )\n    Returns a boolean indicating if provided an array buffer view.\n","ArrayBuffer.prototype.byteLength":"\nArrayBuffer.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the array buffer.\n","ArrayBuffer.prototype.slice":"\nArrayBuffer.prototype.slice( [start:integer[, end:integer]] )\n    Copies the bytes of an array buffer to a new array buffer.\n","arraybuffer2buffer":"\narraybuffer2buffer( buf:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Allocates a buffer from an ArrayBuffer.\n","arrayCtors":"\narrayCtors( dtype:string )\n    Returns an array constructor.\n","arrayDataType":"\narrayDataType( array:any )\n    Returns the data type of an array.\n","arrayDataTypes":"\narrayDataTypes( [kind:string] )\n    Returns a list of array data types.\n","ArrayIndex":"\nArrayIndex( x:Array|TypedArray|Object[, options:Object] )\n    Wraps a provided array as an array index object.\n","ArrayIndex.free":"\nArrayIndex.free( id:string )\n    Frees the instance associated with a provided identifier.\n","ArrayIndex.get":"\nArrayIndex.get( id:string )\n    Returns the array associated with the instance having a provided identifier.\n","ArrayIndex.prototype.data":"\nArrayIndex.prototype.data\n    Read-only property returning the underlying index array.\n","ArrayIndex.prototype.dtype":"\nArrayIndex.prototype.dtype\n    Read-only property returning the underlying data type of the index array.\n","ArrayIndex.prototype.id":"\nArrayIndex.prototype.id\n    Read-only property returning the unique identifier associated with an\n    instance.\n","ArrayIndex.prototype.isCached":"\nArrayIndex.prototype.isCached\n    Read-only property returning a boolean indicating whether an array index is\n    actively cached.\n","ArrayIndex.prototype.type":"\nArrayIndex.prototype.type\n    Read-only property returning the array index type.\n","ArrayIndex.prototype.toString":"\nArrayIndex.prototype.toString()\n    Serializes an instance as a string.\n","ArrayIndex.prototype.toJSON":"\nArrayIndex.prototype.toJSON()\n    Serializes an instance as a JSON object.\n","arrayMinDataType":"\narrayMinDataType( value:any )\n    Returns the minimum array data type of the closest \"kind\" necessary for\n    storing a provided scalar value.\n","arrayMostlySafeCasts":"\narrayMostlySafeCasts( [dtype:any] )\n    Returns a list of array data types to which a provided array data type can\n    be safely cast and, for floating-point data types, can be downcast.\n","arrayNextDataType":"\narrayNextDataType( [dtype:string] )\n    Returns the next larger array data type of the same kind.\n","arrayPromotionRules":"\narrayPromotionRules( [dtype1:any, dtype2:any] )\n    Returns the array data type with the smallest size and closest \"kind\" to\n    which array data types can be safely cast.\n","arraySafeCasts":"\narraySafeCasts( [dtype:any] )\n    Returns a list of array data types to which a provided array data type can\n    be safely cast.\n","arraySameKindCasts":"\narraySameKindCasts( [dtype:any] )\n    Returns a list of array data types to which a provided array data type can\n    be safely cast or cast within the same \"kind\".\n","arrayShape":"\narrayShape( arr:ArrayLikeObject )\n    Determines array dimensions.\n","arrayStream":"\narrayStream( src:ArrayLikeObject[, options:Object] )\n    Creates a readable stream from an array-like object.\n","arrayStream.factory":"\narrayStream.factory( [options:Object] )\n    Returns a function for creating readable streams from array-like objects.\n","arrayStream.objectMode":"\narrayStream.objectMode( src:ArrayLikeObject[, options:Object] )\n    Returns an \"objectMode\" readable stream from an array-like object.\n","arrayview2iterator":"\narrayview2iterator( src:ArrayLikeObject[, begin:integer[, end:integer]][, \n  mapFcn:Function[, thisArg:any]] )\n    Returns an iterator which iterates over the elements of an array-like object\n    view.\n","arrayview2iteratorRight":"\narrayview2iteratorRight( src:ArrayLikeObject[, begin:integer[, end:integer]][, \n  mapFcn:Function[, thisArg:any]] )\n    Returns an iterator which iterates from right to left over the elements of\n    an array-like object view.\n","aslice":"\naslice( x:ArrayLikeObject[, start:integer[, end:integer]] )\n    Returns a shallow copy of a portion of an array.\n","AsyncIteratorSymbol":"\nAsyncIteratorSymbol\n    Async iterator symbol.\n","atake":"\natake( x:Array|TypedArray|Object, indices:ArrayLikeObject<integer>[, \n  options:Object] )\n    Takes elements from an array.\n","azeros":"\nazeros( length:integer[, dtype:string] )\n    Returns a zero-filled array having a specified length.\n","azerosLike":"\nazerosLike( x:TypedArray|Array[, dtype:string] )\n    Returns a zero-filled array having the same length and data type as a\n    provided input array.\n","azeroTo":"\nazeroTo( n:integer[, dtype:string] )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from zero.\n","azeroToLike":"\nazeroToLike( x:TypedArray|Array[, dtype:string] )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from zero and having the same length and data type as a provided\n    input array.\n","bartlettTest":"\nbartlettTest( ...x:Array[, options:Object] )\n    Computes Bartlett’s test for equal variances.\n","base.abs":"\nbase.abs( x:number )\n    Computes the absolute value of a double-precision floating-point number `x`.\n","base.abs2":"\nbase.abs2( x:number )\n    Computes the squared absolute value of a double-precision floating-point\n    `x`.\n","base.abs2f":"\nbase.abs2f( x:number )\n    Computes the squared absolute value of a single-precision floating-point\n    `x`.\n","base.absdiff":"\nbase.absdiff( x:number, y:number )\n    Computes the absolute difference.\n","base.absf":"\nbase.absf( x:number )\n    Computes the absolute value of a single-precision floating-point number `x`.\n","base.acartesianPower":"\nbase.acartesianPower( x:ArrayLikeObject, n:integer )\n    Returns the Cartesian power.\n","base.acartesianProduct":"\nbase.acartesianProduct( x1:ArrayLikeObject, x2:ArrayLikeObject )\n    Returns the Cartesian product.\n","base.acartesianSquare":"\nbase.acartesianSquare( x:ArrayLikeObject )\n    Returns the Cartesian square.\n","base.acos":"\nbase.acos( x:number )\n    Compute the arccosine of a double-precision floating-point number.\n","base.acosd":"\nbase.acosd( x:number )\n    Computes the arccosine (in degrees) of a double-precision floating-point \n    number.\n","base.acosf":"\nbase.acosf( x:number )\n    Computes the arccosine of a single-precision floating-point number.\n","base.acosh":"\nbase.acosh( x:number )\n    Computes the hyperbolic arccosine of a double-precision floating-point\n    number.\n","base.acot":"\nbase.acot( x:number )\n    Computes the inverse cotangent of a double-precision floating-point number.\n","base.acotd":"\nbase.acotd( x:number )\n    Computes the arccotangent (in degrees) of a double-precision floating-point\n    number.\n","base.acotf":"\nbase.acotf( x:number )\n    Computes the inverse cotangent of a single-precision floating-point number.\n","base.acoth":"\nbase.acoth( x:number )\n    Computes the inverse hyperbolic cotangent of a double-precision floating-\n    point number.\n","base.acovercos":"\nbase.acovercos( x:number )\n    Computes the inverse coversed cosine.\n","base.acoversin":"\nbase.acoversin( x:number )\n    Computes the inverse coversed sine.\n","base.acsc":"\nbase.acsc( x:number )\n    Computes the arccosecant of a number.\n","base.acscd":"\nbase.acscd( x:number )\n    Computes the arccosecant of (in degrees) a double-precision floating-point\n    number.\n","base.acscdf":"\nbase.acscdf( x:number )\n    Computes the arccosecant (in degrees) of a single-precision floating-point\n    number.\n","base.acscf":"\nbase.acscf( x:number )\n    Computes the arccosecant of a single-precision floating-point number.\n","base.acsch":"\nbase.acsch( x:number )\n    Computes the hyperbolic arccosecant of a number.\n","base.add":"\nbase.add( x:number, y:number )\n    Computes the sum of two double-precision floating-point numbers `x` and `y`.\n","base.add3":"\nbase.add3( x:number, y:number, z:number )\n    Computes the sum of three double-precision floating-point numbers.\n","base.add4":"\nbase.add4( x:number, y:number, z:number, w:number )\n    Computes the sum of four double-precision floating-point numbers.\n","base.add5":"\nbase.add5( x:number, y:number, z:number, w:number, u:number )\n    Computes the sum of five double-precision floating-point numbers.\n","base.addf":"\nbase.addf( x:number, y:number )\n    Computes the sum of two single-precision floating-point numbers `x` and `y`.\n","base.afilled":"\nbase.afilled( value:any, len:integer )\n    Returns a filled \"generic\" array.\n","base.afilled2d":"\nbase.afilled2d( value:any, shape:Array<integer> )\n    Returns a filled two-dimensional nested array.\n","base.afilled2dBy":"\nbase.afilled2dBy( shape:Array<integer>, clbk:Function[, thisArg:any] )\n    Returns a filled two-dimensional nested array according to a provided\n    callback function.\n","base.afilled3d":"\nbase.afilled3d( value:any, shape:Array<integer> )\n    Returns a filled three-dimensional nested array.\n","base.afilled3dBy":"\nbase.afilled3dBy( shape:Array<integer>, clbk:Function[, thisArg:any] )\n    Returns a filled three-dimensional nested array according to a provided\n    callback function.\n","base.afilled4d":"\nbase.afilled4d( value:any, shape:Array<integer> )\n    Returns a filled four-dimensional nested array.\n","base.afilled4dBy":"\nbase.afilled4dBy( shape:Array<integer>, clbk:Function[, thisArg:any] )\n    Returns a filled four-dimensional nested array according to a provided\n    callback function.\n","base.afilled5d":"\nbase.afilled5d( value:any, shape:Array<integer> )\n    Returns a filled five-dimensional nested array.\n","base.afilled5dBy":"\nbase.afilled5dBy( shape:Array<integer>, clbk:Function[, thisArg:any] )\n    Returns a filled five-dimensional nested array according to a provided\n    callback function.\n","base.afilledBy":"\nbase.afilledBy( len:integer, clbk:Function[, thisArg:any] )\n    Returns a filled \"generic\" array according to a provided callback function.\n","base.afillednd":"\nbase.afillednd( value:any, shape:Array<integer> )\n    Returns a filled n-dimensional nested array.\n","base.afilledndBy":"\nbase.afilledndBy( shape:Array<integer>, clbk:Function[, thisArg:any] )\n    Returns a filled n-dimensional nested array according to a callback\n    function.\n","base.afilter":"\nbase.afilter( x:Array|TypedArray|Object, predicate:Function[, thisArg:any] )\n    Returns a shallow copy of an array containing only those elements which pass\n    a test implemented by a predicate function.\n","base.afirst":"\nbase.afirst( arr:ArrayLikeObject )\n    Returns the first element of an array-like object.\n","base.aflatten":"\nbase.aflatten( x:Array, shape:Array<integer>, colexicographic:boolean )\n    Flattens an n-dimensional nested array.\n","base.aflatten.assign":"\nbase.aflatten.assign( x:Array, shape:Array<integer>, colexicographic:boolean, \n  out:Collection, stride:integer, offset:integer )\n    Flattens an n-dimensional nested array and assigns elements to a provided\n    output array.\n","base.aflatten2d":"\nbase.aflatten2d( x:Array, shape:Array<integer>, colexicographic:boolean )\n    Flattens a two-dimensional nested array.\n","base.aflatten2d.assign":"\nbase.aflatten2d.assign( x:Array, shape:Array<integer>, colexicographic:boolean, \n  out:Collection, stride:integer, offset:integer )\n    Flattens a two-dimensional nested array and assigns elements to a provided\n    output array.\n","base.aflatten2dBy":"\nbase.aflatten2dBy( x:Array, shape:Array<integer>, colex:boolean, \n  clbk:Function[, thisArg:any] )\n    Flattens a two-dimensional nested array according to a callback function.\n","base.aflatten2dBy.assign":"\nbase.aflatten2dBy.assign( x:Array, shape:Array<integer>, colex:boolean, \n  out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n    Flattens a two-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n","base.aflatten3d":"\nbase.aflatten3d( x:ArrayLikeObject, shape:Array<integer>, \n  colexicographic:boolean )\n    Flattens a three-dimensional nested array.\n","base.aflatten3d.assign":"\nbase.aflatten3d.assign( x:Array, shape:Array<integer>, colexicographic:boolean, \n  out:Collection, stride:integer, offset:integer )\n    Flattens a three-dimensional nested array and assigns elements to a provided\n    output array.\n","base.aflatten3dBy":"\nbase.aflatten3dBy( x:ArrayLikeObject, shape:Array<integer>, colex:boolean, \n  clbk:Function[, thisArg:any] )\n    Flattens a three-dimensional nested array according to a callback function.\n","base.aflatten3dBy.assign":"\nbase.aflatten3dBy.assign( x:Array, shape:Array<integer>, colex:boolean, \n  out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n    Flattens a three-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n","base.aflatten4d":"\nbase.aflatten4d( x:ArrayLikeObject, shape:Array<integer>, \n  colexicographic:boolean )\n    Flattens a four-dimensional nested array.\n","base.aflatten4d.assign":"\nbase.aflatten4d.assign( x:Array, shape:Array<integer>, colexicographic:boolean, \n  out:Collection, stride:integer, offset:integer )\n    Flattens a four-dimensional nested array and assigns elements to a provided\n    output array.\n","base.aflatten4dBy":"\nbase.aflatten4dBy( x:ArrayLikeObject, shape:Array<integer>, colex:boolean, \n  clbk:Function[, thisArg:any] )\n    Flattens a four-dimensional nested array according to a callback function.\n","base.aflatten4dBy.assign":"\nbase.aflatten4dBy.assign( x:Array, shape:Array<integer>, colex:boolean, \n  out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n    Flattens a four-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n","base.aflatten5d":"\nbase.aflatten5d( x:ArrayLikeObject, shape:Array<integer>, \n  colexicographic:boolean )\n    Flattens a five-dimensional nested array.\n","base.aflatten5d.assign":"\nbase.aflatten5d.assign( x:Array, shape:Array<integer>, colexicographic:boolean, \n  out:Collection, stride:integer, offset:integer )\n    Flattens a five-dimensional nested array and assigns elements to a provided\n    output array.\n","base.aflatten5dBy":"\nbase.aflatten5dBy( x:ArrayLikeObject, shape:Array<integer>, colex:boolean, \n  clbk:Function[, thisArg:any] )\n    Flattens a five-dimensional nested array according to a callback function.\n","base.aflatten5dBy.assign":"\nbase.aflatten5dBy.assign( x:Array, shape:Array<integer>, colex:boolean, \n  out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n    Flattens a five-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n","base.aflattenBy":"\nbase.aflattenBy( x:Array, shape:Array<integer>, colex:boolean, clbk:Function[, \n  thisArg:any] )\n    Flattens an n-dimensional nested array according to a callback function.\n","base.aflattenBy.assign":"\nbase.aflattenBy.assign( x:Array, shape:Array<integer>, colex:boolean, \n  out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n    Flattens an n-dimensional nested array according to a callback function and\n    assigns elements to a provided output array.\n","base.afliplr2d":"\nbase.afliplr2d( x:ArrayLikeObject )\n    Reverses the order of elements along the last dimension of a two-dimensional\n    nested input array.\n","base.afliplr3d":"\nbase.afliplr3d( x:ArrayLikeObject )\n    Reverses the order of elements along the last dimension of a three-\n    dimensional nested input array.\n","base.afliplr4d":"\nbase.afliplr4d( x:ArrayLikeObject )\n    Reverses the order of elements along the last dimension of a four-\n    dimensional nested input array.\n","base.afliplr5d":"\nbase.afliplr5d( x:ArrayLikeObject )\n    Reverses the order of elements along the last dimension of a five-\n    dimensional nested input array.\n","base.aflipud2d":"\nbase.aflipud2d( x:ArrayLikeObject )\n    Reverses the order of elements along the first dimension of a two-\n    dimensional nested input array.\n","base.aflipud3d":"\nbase.aflipud3d( x:ArrayLikeObject )\n    Reverses the order of elements along the second-to-last dimension of a\n    three-dimensional nested input array.\n","base.aflipud4d":"\nbase.aflipud4d( x:ArrayLikeObject )\n    Reverses the order of elements along the second-to-last dimension of a four-\n    dimensional nested input array.\n","base.aflipud5d":"\nbase.aflipud5d( x:ArrayLikeObject )\n    Reverses the order of elements along the second-to-last dimension of a five-\n    dimensional nested input array.\n","base.ahavercos":"\nbase.ahavercos( x:number )\n    Computes the inverse half-value versed cosine.\n","base.ahaversin":"\nbase.ahaversin( x:number )\n    Computes the inverse half-value versed sine.\n","base.altcase":"\nbase.altcase( str:string )\n    Converts a string to alternate case.\n","base.aones":"\nbase.aones( len:integer )\n    Returns a \"generic\" array filled with ones.\n","base.aones2d":"\nbase.aones2d( shape:Array<integer> )\n    Returns a two-dimensional nested array filled with ones.\n","base.aones3d":"\nbase.aones3d( shape:Array<integer> )\n    Returns a three-dimensional nested array filled with ones.\n","base.aones4d":"\nbase.aones4d( shape:Array<integer> )\n    Returns a four-dimensional nested array filled with ones.\n","base.aones5d":"\nbase.aones5d( shape:Array<integer> )\n    Returns a five-dimensional nested array filled with ones.\n","base.aonesnd":"\nbase.aonesnd( shape:Array<integer> )\n    Returns an n-dimensional nested array filled with ones.\n","base.aoneTo":"\nbase.aoneTo( n:number )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from one.\n","base.aoneTo.assign":"\nbase.aoneTo.assign( out:ArrayLikeObject, stride:integer, offset:integer )\n    Fills an array with linearly spaced numeric elements which increment by 1\n    starting from one.\n","base.args2multislice":"\nbase.args2multislice( args:Array<Slice|integer|null|undefined> )\n    Creates a MultiSlice object from a list of MultiSlice constructor arguments.\n","base.asec":"\nbase.asec( x:number )\n    Computes the inverse (arc) secant of a number.\n","base.asecd":"\nbase.asecd( x:number )\n    Computes the arcsecant (in degrees) of a double-precision floating-point\n    number.\n","base.asecdf":"\nbase.asecdf( x:number )\n    Computes the arcsecant (in degrees) of a single-precision floating-point\n    number.\n","base.asecf":"\nbase.asecf( x:number )\n    Computes the inverse (arc) secant of a single-precision\n    floating-point number.\n","base.asech":"\nbase.asech( x:number )\n    Computes the hyperbolic arcsecant of a number.\n","base.asin":"\nbase.asin( x:number )\n    Computes the arcsine of a double-precision floating-point number.\n","base.asind":"\nbase.asind( x:number )\n    Computes the arcsine (in degrees) of a double-precision floating-point\n    number.\n","base.asindf":"\nbase.asindf( x:number )\n    Computes the arcsine (in degrees) of a single-precision floating-point\n    number.\n","base.asinf":"\nbase.asinf( x:number )\n    Computes the arcsine of a single-precision floating-point number.\n","base.asinh":"\nbase.asinh( x:number )\n    Computes the hyperbolic arcsine of a double-precision floating-point number.\n","base.atan":"\nbase.atan( x:number )\n    Computes the arctangent of a double-precision floating-point number.\n","base.atan2":"\nbase.atan2( y:number, x:number )\n    Computes the angle in the plane (in radians) between the positive x-axis and\n    the ray from (0,0) to the point (x,y).\n","base.atand":"\nbase.atand( x:number )\n    Computes the arctangent (in degrees) of a double-precision floating-point\n    number.\n","base.atanf":"\nbase.atanf( x:number )\n    Computes the arctangent of a single-precision floating-point number.\n","base.atanh":"\nbase.atanh( x:number )\n    Computes the hyperbolic arctangent of a double-precision floating-point\n    number.\n","base.avercos":"\nbase.avercos( x:number )\n    Computes the inverse versed cosine.\n","base.aversin":"\nbase.aversin( x:number )\n    Computes the inverse versed sine.\n","base.azeros":"\nbase.azeros( len:integer )\n    Returns a zero-filled \"generic\" array.\n","base.azeros2d":"\nbase.azeros2d( shape:Array<integer> )\n    Returns a zero-filled two-dimensional nested array.\n","base.azeros3d":"\nbase.azeros3d( shape:Array<integer> )\n    Returns a zero-filled three-dimensional nested array.\n","base.azeros4d":"\nbase.azeros4d( shape:Array<integer> )\n    Returns a zero-filled four-dimensional nested array.\n","base.azeros5d":"\nbase.azeros5d( shape:Array<integer> )\n    Returns a zero-filled five-dimensional nested array.\n","base.azerosnd":"\nbase.azerosnd( shape:Array<integer> )\n    Returns a zero-filled n-dimensional nested array.\n","base.azeroTo":"\nbase.azeroTo( n:number )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from zero.\n","base.azeroTo.assign":"\nbase.azeroTo.assign( out:ArrayLikeObject, stride:integer, offset:integer )\n    Fills an array with linearly spaced numeric elements which increment by 1\n    starting from zero.\n","base.bernoulli":"\nbase.bernoulli( n:integer )\n    Computes the nth Bernoulli number.\n","base.besselj0":"\nbase.besselj0( x:number )\n    Computes the Bessel function of the first kind of order zero.\n","base.besselj1":"\nbase.besselj1( x:number )\n    Computes the Bessel function of the first kind of order one.\n","base.bessely0":"\nbase.bessely0( x:number )\n    Computes the Bessel function of the second kind of order zero.\n","base.bessely1":"\nbase.bessely1( x:number )\n    Computes the Bessel function of the second kind of order one.\n","base.beta":"\nbase.beta( x:number, y:number )\n    Evaluates the beta function.\n","base.betainc":"\nbase.betainc( x:number, a:number, b:number[, regularized:boolean[, \n  upper:boolean]] )\n    Computes the regularized incomplete beta function.\n","base.betaincinv":"\nbase.betaincinv( p:number, a:number, b:number[, upper:boolean] )\n    Computes the inverse of the lower incomplete beta function.\n","base.betaln":"\nbase.betaln( a:number, b:number )\n    Evaluates the natural logarithm of the beta function.\n","base.binet":"\nbase.binet( x:number )\n    Evaluates Binet's formula extended to real numbers.\n","base.binomcoef":"\nbase.binomcoef( n:integer, k:integer )\n    Computes the binomial coefficient of two integers.\n","base.binomcoefln":"\nbase.binomcoefln( n:integer, k:integer )\n    Computes the natural logarithm of the binomial coefficient of two integers.\n","base.boxcox":"\nbase.boxcox( x:number, lambda:number )\n    Computes a one-parameter Box-Cox transformation.\n","base.boxcox1p":"\nbase.boxcox1p( x:number, lambda:number )\n    Computes a one-parameter Box-Cox transformation of 1+x.\n","base.boxcox1pinv":"\nbase.boxcox1pinv( y:number, lambda:number )\n    Computes the inverse of a one-parameter Box-Cox transformation for 1+x.\n","base.boxcoxinv":"\nbase.boxcoxinv( y:number, lambda:number )\n    Computes the inverse of a one-parameter Box-Cox transformation.\n","base.cabs":"\nbase.cabs( z:Complex128 )\n    Computes the absolute value of a double-precision complex floating-point\n    number.\n","base.cabs2":"\nbase.cabs2( z:Complex128 )\n    Computes the squared absolute value of a double-precision complex floating-\n    point number.\n","base.cabs2f":"\nbase.cabs2f( z:Complex64 )\n    Computes the squared absolute value of a single-precision complex floating-\n    point number.\n","base.cabsf":"\nbase.cabsf( z:Complex64 )\n    Computes the absolute value of a single-precision complex floating-point\n    number.\n","base.cadd":"\nbase.cadd( z1:Complex128, z2:Complex128 )\n    Adds two double-precision complex floating-point numbers.\n","base.caddf":"\nbase.caddf( z1:Complex64, z2:Complex64 )\n    Adds two single-precision complex floating-point numbers.\n","base.camelcase":"\nbase.camelcase( str:string )\n    Converts a string to camel case.\n","base.capitalize":"\nbase.capitalize( str:string )\n    Capitalizes the first character in a string.\n","base.cbrt":"\nbase.cbrt( x:number )\n    Computes the cube root of a double-precision floating-point number.\n","base.cbrtf":"\nbase.cbrtf( x:number )\n    Computes the cube root of a single-precision floating-point number.\n","base.cceil":"\nbase.cceil( z:Complex128 )\n    Rounds each component of a double-precision complex floating-point number\n    toward positive infinity.\n","base.cceilf":"\nbase.cceilf( z:Complex64 )\n    Rounds a single-precision complex floating-point number toward positive\n    infinity.\n","base.cceiln":"\nbase.cceiln( z:Complex128, n:integer )\n    Rounds each component of a double-precision complex number to the nearest\n    multiple of `10^n` toward positive infinity.\n","base.ccis":"\nbase.ccis( z:Complex128 )\n    Evaluates the cis function for a double-precision complex floating-point\n    number.\n","base.cdiv":"\nbase.cdiv( z1:Complex128, z2:Complex128 )\n    Divides two double-precision complex floating-point numbers.\n","base.ceil":"\nbase.ceil( x:number )\n    Rounds a double-precision floating-point number toward positive infinity.\n","base.ceil2":"\nbase.ceil2( x:number )\n    Rounds a numeric value to the nearest power of two toward positive infinity.\n","base.ceil10":"\nbase.ceil10( x:number )\n    Rounds a numeric value to the nearest power of ten toward positive infinity.\n","base.ceilb":"\nbase.ceilb( x:number, n:integer, b:integer )\n    Rounds a numeric value to the nearest multiple of `b^n` toward positive\n    infinity.\n","base.ceilf":"\nbase.ceilf( x:number )\n    Rounds a single-precision floating-point number toward positive infinity.\n","base.ceiln":"\nbase.ceiln( x:number, n:integer )\n    Rounds a numeric value to the nearest multiple of `10^n` toward positive\n    infinity.\n","base.ceilsd":"\nbase.ceilsd( x:number, n:integer, b:integer )\n    Rounds a numeric value to the nearest number toward positive infinity with\n    `n` significant figures.\n","base.cexp":"\nbase.cexp( z:Complex128 )\n    Evaluates the exponential function for a double-precision complex floating-\n    point number.\n","base.cflipsign":"\nbase.cflipsign( z:Complex128, y:number )\n    Returns a double-precision complex floating-point number with the same\n    magnitude as `z` and the sign of `y*z`.\n","base.cflipsignf":"\nbase.cflipsignf( z:Complex64, y:number )\n    Returns a single-precision complex floating-point number with the same\n    magnitude as `z` and the sign of `y*z`.\n","base.cfloor":"\nbase.cfloor( z:Complex128 )\n    Rounds a double-precision complex floating-point number toward negative\n    infinity.\n","base.cfloorn":"\nbase.cfloorn( z:Complex128, n:integer )\n    Rounds each component of a double-precision complex floating-point number\n    to the nearest multiple of `10^n` toward negative infinity.\n","base.cidentity":"\nbase.cidentity( z:Complex128 )\n    Evaluates the identity function for a double-precision complex floating-\n    point number.\n","base.cidentityf":"\nbase.cidentityf( z:Complex64 )\n    Evaluates the identity function for a single-precision complex floating-\n    point number.\n","base.cinv":"\nbase.cinv( z:Complex128 )\n    Computes the inverse of a double-precision complex floating-point number.\n","base.clamp":"\nbase.clamp( v:number, min:number, max:number )\n    Restricts a double-precision floating-point number to a specified range.\n","base.clampf":"\nbase.clampf( v:number, min:number, max:number )\n    Restricts a single-precision floating-point number to a specified range.\n","base.cmul":"\nbase.cmul( z1:Complex128, z2:Complex128 )\n    Multiplies two double-precision complex floating-point numbers.\n","base.cmulf":"\nbase.cmulf( z1:Complex64, z2:Complex64 )\n    Multiplies two single-precision complex floating-point numbers.\n","base.cneg":"\nbase.cneg( z )\n    Negates a double-precision complex floating-point number.\n","base.cnegf":"\nbase.cnegf( z )\n    Negates a single-precision complex floating-point number.\n","base.codePointAt":"\nbase.codePointAt( str:string, idx:integer, backward:boolean )\n    Returns a Unicode code point from a string at a specified position.\n","base.constantcase":"\nbase.constantcase( str:string )\n    Converts a string to constant case.\n","base.continuedFraction":"\nbase.continuedFraction( generator:Function[, options:Object] )\n    Evaluates the continued fraction approximation for the supplied series\n    generator using the modified Lentz algorithm.\n","base.copysign":"\nbase.copysign( x:number, y:number )\n    Returns a double-precision floating-point number with the magnitude of `x`\n    and the sign of `y`.\n","base.copysignf":"\nbase.copysignf( x:number, y:number )\n    Returns a single-precision floating-point number with the magnitude of `x`\n    and the sign of `y`.\n","base.cos":"\nbase.cos( x:number )\n    Computes the cosine of a number.\n","base.cosd":"\nbase.cosd( x:number )\n    Computes the cosine of an angle measured in degrees.\n","base.cosh":"\nbase.cosh( x:number )\n    Computes the hyperbolic cosine of a double-precision floating-point number.\n","base.cosm1":"\nbase.cosm1( x:number )\n    Computes the cosine of a number minus one.\n","base.cospi":"\nbase.cospi( x:number )\n    Computes the value of `cos(πx)`.\n","base.cot":"\nbase.cot( x:number )\n    Computes the cotangent of a number.\n","base.cotd":"\nbase.cotd( x:number )\n    Computes the cotangent of an angle measured in degrees.\n","base.coth":"\nbase.coth( x:number )\n    Computes the hyperbolic cotangent of a number.\n","base.covercos":"\nbase.covercos( x:number )\n    Computes the coversed cosine.\n","base.coversin":"\nbase.coversin( x:number )\n    Computes the coversed sine.\n","base.cphase":"\nbase.cphase( z:Complex128 )\n    Computes the argument of a double-precision complex floating-point number\n    in radians.\n","base.cpolar":"\nbase.cpolar( z:Complex128 )\n    Returns the absolute value and phase of a double-precision complex\n    floating-point number.\n","base.cpolar.assign":"\nbase.cpolar.assign( z:Complex128, out:Array|TypedArray|Object, stride:integer, \n  offset:integer )\n    Returns the absolute value and phase of a double-precision complex\n    floating-point number and assigns results to a provided output array.\n","base.cround":"\nbase.cround( z:Complex128 )\n    Rounds each component of a double-precision complex floating-point number\n    to the nearest integer.\n","base.croundn":"\nbase.croundn( z:Complex128, n:integer )\n    Rounds each component of a double-precision complex floating-point number\n    to the nearest multiple of `10^n`.\n","base.csc":"\nbase.csc( x:number )\n    Computes the cosecant of a number.\n","base.cscd":"\nbase.cscd( x:number )\n    Computes the cosecant of a degree.\n","base.csch":"\nbase.csch( x:number )\n    Computes the hyperbolic cosecant of a number.\n","base.csignum":"\nbase.csignum( z:Complex128 )\n    Evaluates the signum function of a double-precision complex floating-point\n    number.\n","base.csub":"\nbase.csub( z1:Complex128, z2:Complex128 )\n    Subtracts two double-precision complex floating-point numbers.\n","base.csubf":"\nbase.csubf( z1:Complex64, z2:Complex64 )\n    Subtracts two single-precision complex floating-point numbers.\n","base.deg2rad":"\nbase.deg2rad( x:number )\n    Converts an angle from degrees to radians.\n","base.deg2radf":"\nbase.deg2radf( x:number )\n    Converts an angle from degrees to radians (single-precision).\n","base.digamma":"\nbase.digamma( x:number )\n    Evaluates the digamma function.\n","base.diracDelta":"\nbase.diracDelta( x:number )\n    Evaluates the Dirac delta function.\n","base.div":"\nbase.div( x:number, y:number )\n    Divides two double-precision floating-point numbers `x` and `y`.\n","base.divf":"\nbase.divf( x:number, y:number )\n    Divides two single-precision floating-point numbers `x` and `y`.\n","base.dotcase":"\nbase.dotcase( str:string )\n    Converts a string to dot case.\n","base.dists.arcsine.Arcsine":"\nbase.dists.arcsine.Arcsine( [a:number, b:number] )\n    Returns an arcsine distribution object.\n","base.dists.arcsine.cdf":"\nbase.dists.arcsine.cdf( x:number, a:number, b:number )\n    Evaluates the cumulative distribution function (CDF) for an arcsine\n    distribution with minimum support `a` and maximum support `b` at a value\n    `x`.\n","base.dists.arcsine.cdf.factory":"\nbase.dists.arcsine.cdf.factory( a:number, b:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an arcsine distribution with minimum support `a` and maximum support `b`.\n","base.dists.arcsine.entropy":"\nbase.dists.arcsine.entropy( a:number, b:number )\n    Returns the differential entropy of an arcsine distribution (in nats).\n","base.dists.arcsine.kurtosis":"\nbase.dists.arcsine.kurtosis( a:number, b:number )\n    Returns the excess kurtosis of an arcsine distribution.\n","base.dists.arcsine.logcdf":"\nbase.dists.arcsine.logcdf( x:number, a:number, b:number )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for an\n    arcsine distribution with minimum support `a` and maximum support `b` at a\n    value `x`.\n","base.dists.arcsine.logcdf.factory":"\nbase.dists.arcsine.logcdf.factory( a:number, b:number )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of an arcsine distribution with minimum support\n    `a` and maximum support `b`.\n","base.dists.arcsine.logpdf":"\nbase.dists.arcsine.logpdf( x:number, a:number, b:number )\n    Evaluates the logarithm of the probability density function (PDF) for an\n    arcsine distribution with minimum support `a` and maximum support `b` at a\n    value `x`.\n","base.dists.arcsine.logpdf.factory":"\nbase.dists.arcsine.logpdf.factory( a:number, b:number )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of an arcsine distribution with minimum support `a` and\n    maximum support `b`.\n","base.dists.arcsine.mean":"\nbase.dists.arcsine.mean( a:number, b:number )\n    Returns the expected value of an arcsine distribution.\n","base.dists.arcsine.median":"\nbase.dists.arcsine.median( a:number, b:number )\n    Returns the median of an arcsine distribution.\n","base.dists.arcsine.mode":"\nbase.dists.arcsine.mode( a:number, b:number )\n    Returns the mode of an arcsine distribution.\n","base.dists.arcsine.pdf":"\nbase.dists.arcsine.pdf( x:number, a:number, b:number )\n    Evaluates the probability density function (PDF) for an arcsine distribution\n    with minimum support `a` and maximum support `b` at a value `x`.\n","base.dists.arcsine.pdf.factory":"\nbase.dists.arcsine.pdf.factory( a:number, b:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    an arcsine distribution with minimum support `a` and maximum support `b`.\n","base.dists.arcsine.quantile":"\nbase.dists.arcsine.quantile( p:number, a:number, b:number )\n    Evaluates the quantile function for an arcsine distribution with minimum\n    support `a` and maximum support `b` at a probability `p`.\n","base.dists.arcsine.quantile.factory":"\nbase.dists.arcsine.quantile.factory( a:number, b:number )\n    Returns a function for evaluating the quantile function of an arcsine\n    distribution with minimum support `a` and maximum support `b`.\n","base.dists.arcsine.skewness":"\nbase.dists.arcsine.skewness( a:number, b:number )\n    Returns the skewness of an arcsine distribution.\n","base.dists.arcsine.stdev":"\nbase.dists.arcsine.stdev( a:number, b:number )\n    Returns the standard deviation of an arcsine distribution.\n","base.dists.arcsine.variance":"\nbase.dists.arcsine.variance( a:number, b:number )\n    Returns the variance of an arcsine distribution.\n","base.dists.bernoulli.Bernoulli":"\nbase.dists.bernoulli.Bernoulli( [p:number] )\n    Returns a Bernoulli distribution object.\n","base.dists.bernoulli.cdf":"\nbase.dists.bernoulli.cdf( x:number, p:number )\n    Evaluates the cumulative distribution function (CDF) for a Bernoulli\n    distribution with success probability `p` at a value `x`.\n","base.dists.bernoulli.cdf.factory":"\nbase.dists.bernoulli.cdf.factory( p:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.entropy":"\nbase.dists.bernoulli.entropy( p:number )\n    Returns the entropy of a Bernoulli distribution with success probability\n    `p` (in nats).\n","base.dists.bernoulli.kurtosis":"\nbase.dists.bernoulli.kurtosis( p:number )\n    Returns the excess kurtosis of a Bernoulli distribution with success\n    probability `p`.\n","base.dists.bernoulli.mean":"\nbase.dists.bernoulli.mean( p:number )\n    Returns the expected value of a Bernoulli distribution with success\n    probability `p`.\n","base.dists.bernoulli.median":"\nbase.dists.bernoulli.median( p:number )\n    Returns the median of a Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.mgf":"\nbase.dists.bernoulli.mgf( t:number, p:number )\n    Evaluates the moment-generating function (MGF) for a Bernoulli\n    distribution with success probability `p` at a value `t`.\n","base.dists.bernoulli.mgf.factory":"\nbase.dists.bernoulli.mgf.factory( p:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.mode":"\nbase.dists.bernoulli.mode( p:number )\n    Returns the mode of a Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.pmf":"\nbase.dists.bernoulli.pmf( x:number, p:number )\n    Evaluates the probability mass function (PMF) for a Bernoulli distribution\n    with success probability `p` at a value `x`.\n","base.dists.bernoulli.pmf.factory":"\nbase.dists.bernoulli.pmf.factory( p:number )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.quantile":"\nbase.dists.bernoulli.quantile( r:number, p:number )\n    Evaluates the quantile function for a Bernoulli distribution with success\n    probability `p` at a probability `r`.\n","base.dists.bernoulli.quantile.factory":"\nbase.dists.bernoulli.quantile.factory( p:number )\n    Returns a function for evaluating the quantile function of a Bernoulli\n    distribution with success probability `p`.\n","base.dists.bernoulli.skewness":"\nbase.dists.bernoulli.skewness( p:number )\n    Returns the skewness of a Bernoulli distribution with success probability\n    `p`.\n","base.dists.bernoulli.stdev":"\nbase.dists.bernoulli.stdev( p:number )\n    Returns the standard deviation of a Bernoulli distribution with success\n    probability `p`.\n","base.dists.bernoulli.variance":"\nbase.dists.bernoulli.variance( p:number )\n    Returns the variance of a Bernoulli distribution with success probability\n    `p`.\n","base.dists.beta.Beta":"\nbase.dists.beta.Beta( [α:number, β:number] )\n    Returns a beta distribution object.\n","base.dists.beta.cdf":"\nbase.dists.beta.cdf( x:number, α:number, β:number )\n    Evaluates the cumulative distribution function (CDF) for a beta distribution\n    with first shape parameter `α` and second shape parameter `β` at a value\n    `x`.\n","base.dists.beta.cdf.factory":"\nbase.dists.beta.cdf.factory( α:number, β:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a beta distribution with first shape parameter `α` and second shape\n    parameter `β`.\n","base.dists.beta.entropy":"\nbase.dists.beta.entropy( α:number, β:number )\n    Returns the differential entropy of a beta distribution.\n","base.dists.beta.kurtosis":"\nbase.dists.beta.kurtosis( α:number, β:number )\n    Returns the excess kurtosis of a beta distribution.\n","base.dists.beta.logcdf":"\nbase.dists.beta.logcdf( x:number, α:number, β:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a beta distribution with first shape parameter `α` and second\n    shape parameter `β` at a value `x`.\n","base.dists.beta.logcdf.factory":"\nbase.dists.beta.logcdf.factory( α:number, β:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a beta distribution with first shape\n    parameter `α` and second shape parameter `β`.\n","base.dists.beta.logpdf":"\nbase.dists.beta.logpdf( x:number, α:number, β:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a beta distribution with first shape parameter `α` and second shape\n    parameter `β` at a value `x`.\n","base.dists.beta.logpdf.factory":"\nbase.dists.beta.logpdf.factory( α:number, β:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a beta distribution with first shape parameter `α`\n    and second shape parameter `β`.\n","base.dists.beta.mean":"\nbase.dists.beta.mean( α:number, β:number )\n    Returns the expected value of a beta distribution.\n","base.dists.beta.median":"\nbase.dists.beta.median( α:number, β:number )\n    Returns the median of a beta distribution.\n","base.dists.beta.mgf":"\nbase.dists.beta.mgf( t:number, α:number, β:number )\n    Evaluates the moment-generating function (MGF) for a beta distribution with\n    first shape parameter `α` and second shape parameter `β` at a value `t`.\n","base.dists.beta.mgf.factory":"\nbase.dists.beta.mgf.factory( α:number, β:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    beta distribution with first shape parameter `α` and second shape parameter\n    `β`.\n","base.dists.beta.mode":"\nbase.dists.beta.mode( α:number, β:number )\n    Returns the mode of a beta distribution.\n","base.dists.beta.pdf":"\nbase.dists.beta.pdf( x:number, α:number, β:number )\n    Evaluates the probability density function (PDF) for a beta distribution\n    with first shape parameter `α` and second shape parameter `β` at a value\n    `x`.\n","base.dists.beta.pdf.factory":"\nbase.dists.beta.pdf.factory( α:number, β:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a beta distribution with first shape parameter `α` and second shape\n    parameter `β`.\n","base.dists.beta.quantile":"\nbase.dists.beta.quantile( p:number, α:number, β:number )\n    Evaluates the quantile function for a beta distribution with first shape\n    parameter `α` and second shape parameter `β` at a probability `p`.\n","base.dists.beta.quantile.factory":"\nbase.dists.beta.quantile.factory( α:number, β:number )\n    Returns a function for evaluating the quantile function of a beta\n    distribution with first shape parameter `α` and second shape parameter `β`.\n","base.dists.beta.skewness":"\nbase.dists.beta.skewness( α:number, β:number )\n    Returns the skewness of a beta distribution.\n","base.dists.beta.stdev":"\nbase.dists.beta.stdev( α:number, β:number )\n    Returns the standard deviation of a beta distribution.\n","base.dists.beta.variance":"\nbase.dists.beta.variance( α:number, β:number )\n    Returns the variance of a beta distribution.\n","base.dists.betaprime.BetaPrime":"\nbase.dists.betaprime.BetaPrime( [α:number, β:number] )\n    Returns a beta prime distribution object.\n","base.dists.betaprime.cdf":"\nbase.dists.betaprime.cdf( x:number, α:number, β:number )\n    Evaluates the cumulative distribution function (CDF) for a beta prime\n    distribution with first shape parameter `α` and second shape parameter `β`\n    at a value `x`.\n","base.dists.betaprime.cdf.factory":"\nbase.dists.betaprime.cdf.factory( α:number, β:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a beta prime distribution with first shape parameter `α` and second shape\n    parameter `β`.\n","base.dists.betaprime.kurtosis":"\nbase.dists.betaprime.kurtosis( α:number, β:number )\n    Returns the excess kurtosis of a beta prime distribution.\n","base.dists.betaprime.logcdf":"\nbase.dists.betaprime.logcdf( x:number, α:number, β:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a beta prime distribution with first shape parameter `α` and\n    second shape parameter `β` at a value `x`.\n","base.dists.betaprime.logcdf.factory":"\nbase.dists.betaprime.logcdf.factory( α:number, β:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a beta prime distribution with first shape\n    parameter `α` and second shape parameter `β`.\n","base.dists.betaprime.logpdf":"\nbase.dists.betaprime.logpdf( x:number, α:number, β:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a beta prime distribution with first shape parameter `α` and second\n    shape parameter `β` at a value `x`.\n","base.dists.betaprime.logpdf.factory":"\nbase.dists.betaprime.logpdf.factory( α:number, β:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a beta prime distribution with first shape\n    parameter `α` and second shape parameter `β`.\n","base.dists.betaprime.mean":"\nbase.dists.betaprime.mean( α:number, β:number )\n    Returns the expected value of a beta prime distribution.\n","base.dists.betaprime.mode":"\nbase.dists.betaprime.mode( α:number, β:number )\n    Returns the mode of a beta prime distribution.\n","base.dists.betaprime.pdf":"\nbase.dists.betaprime.pdf( x:number, α:number, β:number )\n    Evaluates the probability density function (PDF) for a beta prime\n    distribution  with first shape parameter `α` and second shape parameter `β`\n    at a value `x`.\n","base.dists.betaprime.pdf.factory":"\nbase.dists.betaprime.pdf.factory( α:number, β:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a beta prime distribution with first shape parameter `α` and second shape\n    parameter `β`.\n","base.dists.betaprime.quantile":"\nbase.dists.betaprime.quantile( p:number, α:number, β:number )\n    Evaluates the quantile function for a beta prime distribution with first\n    shape parameter `α` and second shape parameter `β` at a probability `p`.\n","base.dists.betaprime.quantile.factory":"\nbase.dists.betaprime.quantile.factory( α:number, β:number )\n    Returns a function for evaluating the quantile function of a beta prime\n    distribution with first shape parameter `α` and second shape parameter `β`.\n","base.dists.betaprime.skewness":"\nbase.dists.betaprime.skewness( α:number, β:number )\n    Returns the skewness of a beta prime distribution.\n","base.dists.betaprime.stdev":"\nbase.dists.betaprime.stdev( α:number, β:number )\n    Returns the standard deviation of a beta prime distribution.\n","base.dists.betaprime.variance":"\nbase.dists.betaprime.variance( α:number, β:number )\n    Returns the variance of a beta prime distribution.\n","base.dists.binomial.Binomial":"\nbase.dists.binomial.Binomial( [n:integer, p:number] )\n    Returns a binomial distribution object.\n","base.dists.binomial.cdf":"\nbase.dists.binomial.cdf( x:number, n:integer, p:number )\n    Evaluates the cumulative distribution function (CDF) for a binomial\n    distribution with number of trials `n` and success probability `p` at a\n    value `x`.\n","base.dists.binomial.cdf.factory":"\nbase.dists.binomial.cdf.factory( n:integer, p:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a binomial distribution with number of trials `n` and success probability\n    `p`.\n","base.dists.binomial.entropy":"\nbase.dists.binomial.entropy( n:integer, p:number )\n    Returns the entropy of a binomial distribution.\n","base.dists.binomial.kurtosis":"\nbase.dists.binomial.kurtosis( n:integer, p:number )\n    Returns the excess kurtosis of a binomial distribution.\n","base.dists.binomial.logpmf":"\nbase.dists.binomial.logpmf( x:number, n:integer, p:number )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    binomial distribution with number of trials `n` and success probability `p`\n    at a value `x`.\n","base.dists.binomial.logpmf.factory":"\nbase.dists.binomial.logpmf.factory( n:integer, p:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a binomial distribution with number of trials `n` and\n    success probability `p`.\n","base.dists.binomial.mean":"\nbase.dists.binomial.mean( n:integer, p:number )\n    Returns the expected value of a binomial distribution.\n","base.dists.binomial.median":"\nbase.dists.binomial.median( n:integer, p:number )\n    Returns the median of a binomial distribution.\n","base.dists.binomial.mgf":"\nbase.dists.binomial.mgf( t:number, n:integer, p:number )\n    Evaluates the moment-generating function (MGF) for a binomial distribution\n    with number of trials `n` and success probability `p` at a value `t`.\n","base.dists.binomial.mgf.factory":"\nbase.dists.binomial.mgf.factory( n:integer, p:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    binomial distribution with number of trials `n` and success probability `p`.\n","base.dists.binomial.mode":"\nbase.dists.binomial.mode( n:integer, p:number )\n    Returns the mode of a binomial distribution.\n","base.dists.binomial.pmf":"\nbase.dists.binomial.pmf( x:number, n:integer, p:number )\n    Evaluates the probability mass function (PMF) for a binomial distribution\n    with number of trials `n` and success probability `p` at a value `x`.\n","base.dists.binomial.pmf.factory":"\nbase.dists.binomial.pmf.factory( n:integer, p:number )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    binomial distribution with number of trials `n` and success probability `p`.\n","base.dists.binomial.quantile":"\nbase.dists.binomial.quantile( r:number, n:integer, p:number )\n    Evaluates the quantile function for a binomial distribution with number of\n    trials `n` and success probability `p` at a probability `r`.\n","base.dists.binomial.quantile.factory":"\nbase.dists.binomial.quantile.factory( n:integer, p:number )\n    Returns a function for evaluating the quantile function of a binomial\n    distribution with number of trials `n` and success probability `p`.\n","base.dists.binomial.skewness":"\nbase.dists.binomial.skewness( n:integer, p:number )\n    Returns the skewness of a binomial distribution.\n","base.dists.binomial.stdev":"\nbase.dists.binomial.stdev( n:integer, p:number )\n    Returns the standard deviation of a binomial distribution.\n","base.dists.binomial.variance":"\nbase.dists.binomial.variance( n:integer, p:number )\n    Returns the variance of a binomial distribution.\n","base.dists.cauchy.Cauchy":"\nbase.dists.cauchy.Cauchy( [x0:number, Ɣ:number] )\n    Returns a Cauchy distribution object.\n","base.dists.cauchy.cdf":"\nbase.dists.cauchy.cdf( x:number, x0:number, Ɣ:number )\n    Evaluates the cumulative distribution function (CDF) for a Cauchy\n    distribution with location parameter `x0` and scale parameter `Ɣ` at a value\n    `x`.\n","base.dists.cauchy.cdf.factory":"\nbase.dists.cauchy.cdf.factory( x0:number, Ɣ:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Cauchy distribution with location parameter `x0` and scale parameter\n    `Ɣ`.\n","base.dists.cauchy.entropy":"\nbase.dists.cauchy.entropy( x0:number, Ɣ:number )\n    Returns the differential entropy of a Cauchy distribution (in nats).\n","base.dists.cauchy.logcdf":"\nbase.dists.cauchy.logcdf( x:number, x0:number, Ɣ:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (logCDF) for a Cauchy distribution with location parameter `x0` and scale\n    parameter `Ɣ` at a value `x`.\n","base.dists.cauchy.logcdf.factory":"\nbase.dists.cauchy.logcdf.factory( x0:number, Ɣ:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (logCDF) of a Cauchy distribution with location\n    parameter `x0` and scale parameter `Ɣ`.\n","base.dists.cauchy.logpdf":"\nbase.dists.cauchy.logpdf( x:number, x0:number, Ɣ:number )\n    Evaluates the natural logarithm of the probability density function (logPDF)\n    for a Cauchy distribution with location parameter `x0` and scale parameter\n    `Ɣ` at a value `x`.\n","base.dists.cauchy.logpdf.factory":"\nbase.dists.cauchy.logpdf.factory( x0:number, Ɣ:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (logPDF) of a Cauchy distribution with location parameter\n    `x0` and scale parameter `Ɣ`.\n","base.dists.cauchy.median":"\nbase.dists.cauchy.median( x0:number, Ɣ:number )\n    Returns the median of a Cauchy distribution.\n","base.dists.cauchy.mode":"\nbase.dists.cauchy.mode( x0:number, Ɣ:number )\n    Returns the mode of a Cauchy distribution.\n","base.dists.cauchy.pdf":"\nbase.dists.cauchy.pdf( x:number, x0:number, Ɣ:number )\n    Evaluates the probability density function (PDF) for a Cauchy distribution\n    with location parameter `x0` and scale parameter `Ɣ` at a value `x`.\n","base.dists.cauchy.pdf.factory":"\nbase.dists.cauchy.pdf.factory( x0:number, Ɣ:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Cauchy distribution with location parameter `x0` and scale parameter `Ɣ`.\n","base.dists.cauchy.quantile":"\nbase.dists.cauchy.quantile( p:number, x0:number, Ɣ:number )\n    Evaluates the quantile function for a Cauchy distribution with location\n    parameter `x0`  and scale parameter `Ɣ` at a probability `p`.\n","base.dists.cauchy.quantile.factory":"\nbase.dists.cauchy.quantile.factory( x0:number, Ɣ:number )\n    Returns a function for evaluating the quantile function of a Cauchy\n    distribution with location parameter `x0` and scale parameter `Ɣ`.\n","base.dists.chi.cdf":"\nbase.dists.chi.cdf( x:number, k:number )\n    Evaluates the cumulative distribution function (CDF) for a chi distribution\n    with degrees of freedom `k` at a value `x`.\n","base.dists.chi.cdf.factory":"\nbase.dists.chi.cdf.factory( k:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a chi distribution with degrees of freedom `k`.\n","base.dists.chi.Chi":"\nbase.dists.chi.Chi( [k:number] )\n    Returns a chi distribution object.\n","base.dists.chi.entropy":"\nbase.dists.chi.entropy( k:number )\n    Returns the differential entropy of a chi distribution (in nats).\n","base.dists.chi.kurtosis":"\nbase.dists.chi.kurtosis( k:number )\n    Returns the excess kurtosis of a chi distribution.\n","base.dists.chi.logpdf":"\nbase.dists.chi.logpdf( x:number, k:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a chi distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chi.logpdf.factory":"\nbase.dists.chi.logpdf.factory( k:number )\n    Returns a function for evaluating the natural logarithm of the  probability\n    density function (PDF) of a chi distribution with degrees of freedom `k`.\n","base.dists.chi.mean":"\nbase.dists.chi.mean( k:number )\n    Returns the expected value of a chi distribution.\n","base.dists.chi.mode":"\nbase.dists.chi.mode( k:number )\n    Returns the mode of a chi distribution.\n","base.dists.chi.pdf":"\nbase.dists.chi.pdf( x:number, k:number )\n    Evaluates the probability density function (PDF) for a chi distribution with\n    degrees of freedom `k` at a value `x`.\n","base.dists.chi.pdf.factory":"\nbase.dists.chi.pdf.factory( k:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a chi distribution with degrees of freedom `k`.\n","base.dists.chi.quantile":"\nbase.dists.chi.quantile( p:number, k:number )\n    Evaluates the quantile function for a chi distribution with degrees of\n    freedom `k` at a probability `p`.\n","base.dists.chi.quantile.factory":"\nbase.dists.chi.quantile.factory( k:number )\n    Returns a function for evaluating the quantile function of a chi\n    distribution with degrees of freedom `k`.\n","base.dists.chi.skewness":"\nbase.dists.chi.skewness( k:number )\n    Returns the skewness of a chi distribution.\n","base.dists.chi.stdev":"\nbase.dists.chi.stdev( k:number )\n    Returns the standard deviation of a chi distribution.\n","base.dists.chi.variance":"\nbase.dists.chi.variance( k:number )\n    Returns the variance of a chi distribution.\n","base.dists.chisquare.cdf":"\nbase.dists.chisquare.cdf( x:number, k:number )\n    Evaluates the cumulative distribution function (CDF) for a chi-squared\n    distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chisquare.cdf.factory":"\nbase.dists.chisquare.cdf.factory( k:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a chi-squared distribution with degrees of freedom `k`.\n","base.dists.chisquare.ChiSquare":"\nbase.dists.chisquare.ChiSquare( [k:number] )\n    Returns a  chi-squared distribution object.\n","base.dists.chisquare.entropy":"\nbase.dists.chisquare.entropy( k:number )\n    Returns the differential entropy of a chi-squared distribution (in nats).\n","base.dists.chisquare.kurtosis":"\nbase.dists.chisquare.kurtosis( k:number )\n    Returns the excess kurtosis of a chi-squared distribution.\n","base.dists.chisquare.logpdf":"\nbase.dists.chisquare.logpdf( x:number, k:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a chi-squared distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chisquare.logpdf.factory":"\nbase.dists.chisquare.logpdf.factory( k:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a chi-squared distribution with degrees of freedom\n    `k`.\n","base.dists.chisquare.mean":"\nbase.dists.chisquare.mean( k:number )\n    Returns the expected value of a chi-squared distribution.\n","base.dists.chisquare.median":"\nbase.dists.chisquare.median( k:number )\n    Returns the median of a chi-squared distribution.\n","base.dists.chisquare.mgf":"\nbase.dists.chisquare.mgf( t:number, k:number )\n    Evaluates the moment-generating function (MGF) for a chi-squared\n    distribution with degrees of freedom `k` at a value `t`.\n","base.dists.chisquare.mgf.factory":"\nbase.dists.chisquare.mgf.factory( k:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    chi-squared distribution with degrees of freedom `k`.\n","base.dists.chisquare.mode":"\nbase.dists.chisquare.mode( k:number )\n    Returns the mode of a chi-squared distribution.\n","base.dists.chisquare.pdf":"\nbase.dists.chisquare.pdf( x:number, k:number )\n    Evaluates the probability density function (PDF) for a chi-squared\n    distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chisquare.pdf.factory":"\nbase.dists.chisquare.pdf.factory( k:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a chi-squared distribution with degrees of freedom `k`.\n","base.dists.chisquare.quantile":"\nbase.dists.chisquare.quantile( p:number, k:number )\n    Evaluates the quantile function for a chi-squared distribution with degrees\n    of freedom `k` at a probability `p`.\n","base.dists.chisquare.quantile.factory":"\nbase.dists.chisquare.quantile.factory( k:number )\n    Returns a function for evaluating the quantile function of a chi-squared\n    distribution with degrees of freedom `k`.\n","base.dists.chisquare.skewness":"\nbase.dists.chisquare.skewness( k:number )\n    Returns the skewness of a chi-squared distribution.\n","base.dists.chisquare.stdev":"\nbase.dists.chisquare.stdev( k:number )\n    Returns the standard deviation of a chi-squared distribution.\n","base.dists.chisquare.variance":"\nbase.dists.chisquare.variance( k:number )\n    Returns the variance of a chi-squared distribution.\n","base.dists.cosine.cdf":"\nbase.dists.cosine.cdf( x:number, μ:number, s:number )\n    Evaluates the cumulative distribution function (CDF) for a raised cosine\n    distribution with location parameter `μ` and scale parameter `s` at a value\n    `x`.\n","base.dists.cosine.cdf.factory":"\nbase.dists.cosine.cdf.factory( μ:number, s:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a raised cosine distribution with location parameter `μ` and scale\n    parameter `s`.\n","base.dists.cosine.Cosine":"\nbase.dists.cosine.Cosine( [μ:number, s:number] )\n    Returns a raised cosine distribution object.\n","base.dists.cosine.kurtosis":"\nbase.dists.cosine.kurtosis( μ:number, s:number )\n    Returns the excess kurtosis of a raised cosine distribution with location\n    parameter `μ` and scale parameter `s`.\n","base.dists.cosine.logcdf":"\nbase.dists.cosine.logcdf( x:number, μ:number, s:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a raised cosine distribution with location parameter `μ` and scale\n     parameter `s` at a value `x`.\n","base.dists.cosine.logcdf.factory":"\nbase.dists.cosine.logcdf.factory( μ:number, s:number )\n    Returns a function for evaluating the natural logarithm of the  cumulative\n    distribution function (CDF) of a raised cosine distribution with location\n    parameter `μ` and scale parameter `s`.\n","base.dists.cosine.logpdf":"\nbase.dists.cosine.logpdf( x:number, μ:number, s:number )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    raised cosine distribution with location parameter `μ` and scale parameter\n    `s` at a value `x`.\n","base.dists.cosine.logpdf.factory":"\nbase.dists.cosine.logpdf.factory( μ:number, s:number )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a raised cosine distribution with location parameter `μ`\n    and scale parameter `s`.\n","base.dists.cosine.mean":"\nbase.dists.cosine.mean( μ:number, s:number )\n    Returns the expected value of a raised cosine distribution with location\n    parameter `μ` and scale parameter `s`.\n","base.dists.cosine.median":"\nbase.dists.cosine.median( μ:number, s:number )\n    Returns the median of a raised cosine distribution with location parameter\n    `μ` and scale parameter `s`.\n","base.dists.cosine.mgf":"\nbase.dists.cosine.mgf( t:number, μ:number, s:number )\n    Evaluates the moment-generating function (MGF) for a raised cosine\n    distribution with location parameter `μ` and scale parameter `s` at a value\n    `t`.\n","base.dists.cosine.mgf.factory":"\nbase.dists.cosine.mgf.factory( μ:number, s:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    raised cosine distribution with location parameter `μ` and scale parameter\n    `s`.\n","base.dists.cosine.mode":"\nbase.dists.cosine.mode( μ:number, s:number )\n    Returns the mode of a raised cosine distribution with location parameter `μ`\n    and scale parameter `s`.\n","base.dists.cosine.pdf":"\nbase.dists.cosine.pdf( x:number, μ:number, s:number )\n    Evaluates the probability density function (PDF) for a raised cosine\n    distribution with location parameter `μ` and scale parameter `s` at a value\n    `x`.\n","base.dists.cosine.pdf.factory":"\nbase.dists.cosine.pdf.factory( μ:number, s:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a raised cosine distribution with location parameter `μ` and scale parameter\n    `s`.\n","base.dists.cosine.quantile":"\nbase.dists.cosine.quantile( p:number, μ:number, s:number )\n    Evaluates the quantile function for a raised cosine distribution with\n    location parameter `μ` and scale parameter `s` at a probability `p`.\n","base.dists.cosine.quantile.factory":"\nbase.dists.cosine.quantile.factory( μ:number, s:number )\n    Returns a function for evaluating the quantile function of a raised cosine\n    distribution with location parameter `μ` and scale parameter `s`.\n","base.dists.cosine.skewness":"\nbase.dists.cosine.skewness( μ:number, s:number )\n    Returns the skewness of a raised cosine distribution with location parameter\n    `μ` and scale parameter `s`.\n","base.dists.cosine.stdev":"\nbase.dists.cosine.stdev( μ:number, s:number )\n    Returns the standard deviation of a raised cosine distribution with location\n    parameter `μ` and scale parameter `s`.\n","base.dists.cosine.variance":"\nbase.dists.cosine.variance( μ:number, s:number )\n    Returns the variance of a raised cosine distribution with location parameter\n    `μ` and scale parameter `s`.\n","base.dists.degenerate.cdf":"\nbase.dists.degenerate.cdf( x:number, μ:number )\n    Evaluates the cumulative distribution function (CDF) for a degenerate\n    distribution with mean value `μ`.\n","base.dists.degenerate.cdf.factory":"\nbase.dists.degenerate.cdf.factory( μ:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a degenerate distribution centered at a provided mean value.\n","base.dists.degenerate.Degenerate":"\nbase.dists.degenerate.Degenerate( [μ:number] )\n    Returns a degenerate distribution object.\n","base.dists.degenerate.entropy":"\nbase.dists.degenerate.entropy( μ:number )\n    Returns the entropy of a degenerate distribution with constant value `μ`.\n","base.dists.degenerate.logcdf":"\nbase.dists.degenerate.logcdf( x:number, μ:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (logCDF) for a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logcdf.factory":"\nbase.dists.degenerate.logcdf.factory( μ:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (logCDF) of a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpdf":"\nbase.dists.degenerate.logpdf( x:number, μ:number )\n    Evaluates the natural logarithm of the probability density function (logPDF)\n    for a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpdf.factory":"\nbase.dists.degenerate.logpdf.factory( μ:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (logPDF) of a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpmf":"\nbase.dists.degenerate.logpmf( x:number, μ:number )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpmf.factory":"\nbase.dists.degenerate.logpmf.factory( μ:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a degenerate distribution with mean `μ`.\n","base.dists.degenerate.mean":"\nbase.dists.degenerate.mean( μ:number )\n    Returns the expected value of a degenerate distribution with constant value\n    `μ`.\n","base.dists.degenerate.median":"\nbase.dists.degenerate.median( μ:number )\n    Returns the median of a degenerate distribution with constant value `μ`.\n","base.dists.degenerate.mgf":"\nbase.dists.degenerate.mgf( x:number, μ:number )\n    Evaluates the moment-generating function (MGF) for a degenerate distribution\n    with mean `μ`.\n","base.dists.degenerate.mgf.factory":"\nbase.dists.degenerate.mgf.factory( μ:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    degenerate distribution with mean `μ`.\n","base.dists.degenerate.mode":"\nbase.dists.degenerate.mode( μ:number )\n    Returns the mode of a degenerate distribution with constant value `μ`.\n","base.dists.degenerate.pdf":"\nbase.dists.degenerate.pdf( x:number, μ:number )\n    Evaluates the probability density function (PDF) for a degenerate\n    distribution with mean `μ`.\n","base.dists.degenerate.pdf.factory":"\nbase.dists.degenerate.pdf.factory( μ:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a degenerate distribution with mean `μ`.\n","base.dists.degenerate.pmf":"\nbase.dists.degenerate.pmf( x:number, μ:number )\n    Evaluates the probability mass function (PMF) for a degenerate distribution\n    with mean `μ`.\n","base.dists.degenerate.pmf.factory":"\nbase.dists.degenerate.pmf.factory( μ:number )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    degenerate distribution with mean `μ`.\n","base.dists.degenerate.quantile":"\nbase.dists.degenerate.quantile( p:number, μ:number )\n    Evaluates the quantile function for a degenerate distribution with mean `μ`.\n","base.dists.degenerate.quantile.factory":"\nbase.dists.degenerate.quantile.factory( μ:number )\n    Returns a function for evaluating the quantile function of a degenerate\n    distribution with mean `μ`.\n","base.dists.degenerate.stdev":"\nbase.dists.degenerate.stdev( μ:number )\n    Returns the standard deviation of a degenerate distribution with constant\n    value `μ`.\n","base.dists.degenerate.variance":"\nbase.dists.degenerate.variance( μ:number )\n    Returns the variance of a degenerate distribution with constant value `μ`.\n","base.dists.discreteUniform.cdf":"\nbase.dists.discreteUniform.cdf( x:number, a:integer, b:integer )\n    Evaluates the cumulative distribution function (CDF) for a discrete uniform\n    distribution with minimum support `a` and maximum support `b` at a value\n    `x`.\n","base.dists.discreteUniform.cdf.factory":"\nbase.dists.discreteUniform.cdf.factory( a:integer, b:integer )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a discrete uniform distribution with minimum support `a` and maximum\n    support `b`.\n","base.dists.discreteUniform.DiscreteUniform":"\nbase.dists.discreteUniform.DiscreteUniform( [a:integer, b:integer] )\n    Returns a discrete uniform distribution object.\n","base.dists.discreteUniform.entropy":"\nbase.dists.discreteUniform.entropy( a:integer, b:integer )\n    Returns the entropy of a discrete uniform distribution.\n","base.dists.discreteUniform.kurtosis":"\nbase.dists.discreteUniform.kurtosis( a:integer, b:integer )\n    Returns the excess kurtosis of a discrete uniform distribution.\n","base.dists.discreteUniform.logcdf":"\nbase.dists.discreteUniform.logcdf( x:number, a:integer, b:integer )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a discrete uniform distribution with minimum support `a` and\n    maximum support `b` at a value `x`.\n","base.dists.discreteUniform.logcdf.factory":"\nbase.dists.discreteUniform.logcdf.factory( a:integer, b:integer )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a discrete uniform distribution with minimum\n    support `a` and maximum support `b`.\n","base.dists.discreteUniform.logpmf":"\nbase.dists.discreteUniform.logpmf( x:number, a:integer, b:integer )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    discrete uniform distribution with minimum support `a` and maximum support\n    `b` at a value `x`.\n","base.dists.discreteUniform.logpmf.factory":"\nbase.dists.discreteUniform.logpmf.factory( a:integer, b:integer )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a discrete uniform distribution with minimum support\n    `a` and maximum support `b`.\n","base.dists.discreteUniform.mean":"\nbase.dists.discreteUniform.mean( a:integer, b:integer )\n    Returns the expected value of a discrete uniform distribution.\n","base.dists.discreteUniform.median":"\nbase.dists.discreteUniform.median( a:integer, b:integer )\n    Returns the median of a discrete uniform distribution.\n","base.dists.discreteUniform.mgf":"\nbase.dists.discreteUniform.mgf( t:number, a:integer, b:integer )\n    Evaluates the moment-generating function (MGF) for a discrete uniform\n    distribution with minimum support `a` and maximum support `b` at a value\n    `t`.\n","base.dists.discreteUniform.mgf.factory":"\nbase.dists.discreteUniform.mgf.factory( a:integer, b:integer )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a discrete uniform distribution with minimum support `a` and maximum\n    support `b`.\n","base.dists.discreteUniform.pmf":"\nbase.dists.discreteUniform.pmf( x:number, a:integer, b:integer )\n    Evaluates the probability mass function (PMF) for a discrete uniform\n    distribution with minimum support `a` and maximum support `b` at a value\n    `x`.\n","base.dists.discreteUniform.pmf.factory":"\nbase.dists.discreteUniform.pmf.factory( a:integer, b:integer )\n    Returns a function for evaluating the probability mass function (PMF) of\n    a discrete uniform distribution with minimum support `a` and maximum support\n    `b`.\n","base.dists.discreteUniform.quantile":"\nbase.dists.discreteUniform.quantile( p:number, a:integer, b:integer )\n    Evaluates the quantile function for a discrete uniform distribution with\n    minimum support `a` and maximum support `b` at a probability `p`.\n","base.dists.discreteUniform.quantile.factory":"\nbase.dists.discreteUniform.quantile.factory( a:integer, b:integer )\n    Returns a function for evaluating the quantile function of a discrete\n    uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.discreteUniform.skewness":"\nbase.dists.discreteUniform.skewness( a:integer, b:integer )\n    Returns the skewness of a discrete uniform distribution.\n","base.dists.discreteUniform.stdev":"\nbase.dists.discreteUniform.stdev( a:integer, b:integer )\n    Returns the standard deviation of a discrete uniform distribution.\n","base.dists.discreteUniform.variance":"\nbase.dists.discreteUniform.variance( a:integer, b:integer )\n    Returns the variance of a discrete uniform distribution.\n","base.dists.erlang.cdf":"\nbase.dists.erlang.cdf( x:number, k:number, λ:number )\n    Evaluates the cumulative distribution function (CDF) for an Erlang\n    distribution with shape parameter `k` and rate parameter `λ` at a value\n    `x`.\n","base.dists.erlang.cdf.factory":"\nbase.dists.erlang.cdf.factory( k:number, λ:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.entropy":"\nbase.dists.erlang.entropy( k:integer, λ:number )\n    Returns the differential entropy of an Erlang distribution (in nats).\n","base.dists.erlang.Erlang":"\nbase.dists.erlang.Erlang( [k:number, λ:number] )\n    Returns an Erlang distribution object.\n","base.dists.erlang.kurtosis":"\nbase.dists.erlang.kurtosis( k:integer, λ:number )\n    Returns the excess kurtosis of an Erlang distribution.\n","base.dists.erlang.logpdf":"\nbase.dists.erlang.logpdf( x:number, k:number, λ:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for an Erlang distribution with shape parameter `k` and rate parameter `λ`\n    at a value `x`.\n","base.dists.erlang.logpdf.factory":"\nbase.dists.erlang.logpdf.factory( k:number, λ:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of an Erlang distribution with shape parameter `k`\n    and rate parameter `λ`.\n","base.dists.erlang.mean":"\nbase.dists.erlang.mean( k:integer, λ:number )\n    Returns the expected value of an Erlang distribution.\n","base.dists.erlang.mgf":"\nbase.dists.erlang.mgf( t:number, k:number, λ:number )\n    Evaluates the moment-generating function (MGF) for an Erlang distribution\n    with shape parameter `k` and rate parameter `λ` at a value `t`.\n","base.dists.erlang.mgf.factory":"\nbase.dists.erlang.mgf.factory( k:number, λ:number )\n    Returns a function for evaluating the moment-generating function (MGF) of an\n    Erlang distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.mode":"\nbase.dists.erlang.mode( k:integer, λ:number )\n    Returns the mode of an Erlang distribution.\n","base.dists.erlang.pdf":"\nbase.dists.erlang.pdf( x:number, k:number, λ:number )\n    Evaluates the probability density function (PDF) for an Erlang distribution\n    with shape parameter `k` and rate parameter `λ` at a value `x`.\n","base.dists.erlang.pdf.factory":"\nbase.dists.erlang.pdf.factory( k:number, λ:number )\n    Returns a function for evaluating the probability density function (PDF)\n    of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.quantile":"\nbase.dists.erlang.quantile( p:number, k:number, λ:number )\n    Evaluates the quantile function for an Erlang distribution with shape\n    parameter `k` and rate parameter `λ` at a probability `p`.\n","base.dists.erlang.quantile.factory":"\nbase.dists.erlang.quantile.factory( k:number, λ:number )\n    Returns a function for evaluating the quantile function of an Erlang\n    distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.skewness":"\nbase.dists.erlang.skewness( k:integer, λ:number )\n    Returns the skewness of an Erlang distribution.\n","base.dists.erlang.stdev":"\nbase.dists.erlang.stdev( k:integer, λ:number )\n    Returns the standard deviation of an Erlang distribution.\n","base.dists.erlang.variance":"\nbase.dists.erlang.variance( k:integer, λ:number )\n    Returns the variance of an Erlang distribution.\n","base.dists.exponential.cdf":"\nbase.dists.exponential.cdf( x:number, λ:number )\n    Evaluates the cumulative distribution function (CDF) for an exponential\n    distribution with rate parameter `λ` at a value `x`.\n","base.dists.exponential.cdf.factory":"\nbase.dists.exponential.cdf.factory( λ:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    for an exponential distribution with rate parameter `λ`.\n","base.dists.exponential.entropy":"\nbase.dists.exponential.entropy( λ:number )\n    Returns the differential entropy of an exponential distribution.\n","base.dists.exponential.Exponential":"\nbase.dists.exponential.Exponential( [λ:number] )\n    Returns an exponential distribution object.\n","base.dists.exponential.kurtosis":"\nbase.dists.exponential.kurtosis( λ:number )\n    Returns the excess kurtosis of an exponential distribution.\n","base.dists.exponential.logcdf":"\nbase.dists.exponential.logcdf( x:number, λ:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for an exponential distribution with rate parameter `λ` at a value\n    `x`.\n","base.dists.exponential.logcdf.factory":"\nbase.dists.exponential.logcdf.factory( λ:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) for an exponential distribution with rate\n    parameter `λ`.\n","base.dists.exponential.logpdf":"\nbase.dists.exponential.logpdf( x:number, λ:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for an exponential distribution with rate parameter `λ` at a value `x`.\n","base.dists.exponential.logpdf.factory":"\nbase.dists.exponential.logpdf.factory( λ:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) for an exponential distribution with rate parameter\n    `λ`.\n","base.dists.exponential.mean":"\nbase.dists.exponential.mean( λ:number )\n    Returns the expected value of an exponential distribution.\n","base.dists.exponential.median":"\nbase.dists.exponential.median( λ:number )\n    Returns the median of an exponential distribution.\n","base.dists.exponential.mgf":"\nbase.dists.exponential.mgf( t:number, λ:number )\n    Evaluates the moment-generating function (MGF) for an exponential\n    distribution with rate parameter `λ` at a value `t`.\n","base.dists.exponential.mgf.factory":"\nbase.dists.exponential.mgf.factory( λ:number )\n    Returns a function for evaluating the moment-generating function (MGF) for\n    an exponential distribution with rate parameter `λ`.\n","base.dists.exponential.mode":"\nbase.dists.exponential.mode( λ:number )\n    Returns the mode of an exponential distribution.\n","base.dists.exponential.pdf":"\nbase.dists.exponential.pdf( x:number, λ:number )\n    Evaluates the probability density function (PDF) for an exponential\n    distribution with rate parameter `λ` at a value `x`.\n","base.dists.exponential.pdf.factory":"\nbase.dists.exponential.pdf.factory( λ:number )\n    Returns a function for evaluating the probability density function (PDF)\n    for an exponential distribution with rate parameter `λ`.\n","base.dists.exponential.quantile":"\nbase.dists.exponential.quantile( p:number, λ:number )\n    Evaluates the quantile function for an exponential distribution with rate\n    parameter `λ` at a probability `p`.\n","base.dists.exponential.quantile.factory":"\nbase.dists.exponential.quantile.factory( λ:number )\n    Returns a function for evaluating the quantile function for an exponential\n    distribution with rate parameter `λ`.\n","base.dists.exponential.skewness":"\nbase.dists.exponential.skewness( λ:number )\n    Returns the skewness of an exponential distribution.\n","base.dists.exponential.stdev":"\nbase.dists.exponential.stdev( λ:number )\n    Returns the standard deviation of an exponential distribution.\n","base.dists.exponential.variance":"\nbase.dists.exponential.variance( λ:number )\n    Returns the variance of an exponential distribution.\n","base.dists.f.cdf":"\nbase.dists.f.cdf( x:number, d1:number, d2:number )\n    Evaluates the cumulative distribution function (CDF) for an F distribution\n    with numerator degrees of freedom `d1` and denominator degrees of freedom\n    `d2` at a value `x`.\n","base.dists.f.cdf.factory":"\nbase.dists.f.cdf.factory( d1:number, d2:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an F distribution with numerator degrees of freedom `d1` and denominator\n    degrees of freedom `d2`.\n","base.dists.f.entropy":"\nbase.dists.f.entropy( d1:number, d2:number )\n    Returns the differential entropy of an F distribution (in nats).\n","base.dists.f.F":"\nbase.dists.f.F( [d1:number, d2:number] )\n    Returns an F distribution object.\n","base.dists.f.kurtosis":"\nbase.dists.f.kurtosis( d1:number, d2:number )\n    Returns the excess kurtosis of an F distribution.\n","base.dists.f.mean":"\nbase.dists.f.mean( d1:number, d2:number )\n    Returns the expected value of an F distribution.\n","base.dists.f.mode":"\nbase.dists.f.mode( d1:number, d2:number )\n    Returns the mode of an F distribution.\n","base.dists.f.pdf":"\nbase.dists.f.pdf( x:number, d1:number, d2:number )\n    Evaluates the probability density function (PDF) for an F distribution with\n    numerator degrees of freedom `d1` and denominator degrees of freedom `d2` at\n    a value `x`.\n","base.dists.f.pdf.factory":"\nbase.dists.f.pdf.factory( d1:number, d2:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    an F distribution with numerator degrees of freedom `d1` and denominator\n    degrees of freedom `d2`.\n","base.dists.f.quantile":"\nbase.dists.f.quantile( p:number, d1:number, d2:number )\n    Evaluates the quantile function for an F distribution with numerator degrees\n    of freedom `d1` and denominator degrees of freedom `d2` at a probability\n    `p`.\n","base.dists.f.quantile.factory":"\nbase.dists.f.quantile.factory( d1:number, d2:number )\n    Returns a function for evaluating the quantile function of an F distribution\n    with numerator degrees of freedom `d1` and denominator degrees of freedom\n    `d2`.\n","base.dists.f.skewness":"\nbase.dists.f.skewness( d1:number, d2:number )\n    Returns the skewness of an F distribution.\n","base.dists.f.stdev":"\nbase.dists.f.stdev( d1:number, d2:number )\n    Returns the standard deviation of an F distribution.\n","base.dists.f.variance":"\nbase.dists.f.variance( d1:number, d2:number )\n    Returns the variance of an F distribution.\n","base.dists.frechet.cdf":"\nbase.dists.frechet.cdf( x:number, α:number, s:number, m:number )\n    Evaluates the cumulative distribution function (CDF) for a Fréchet\n    distribution with shape parameter `α`, scale parameter `s`, and location\n    `m`.\n","base.dists.frechet.cdf.factory":"\nbase.dists.frechet.cdf.factory( α:number, s:number, m:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n    location `m`.\n","base.dists.frechet.entropy":"\nbase.dists.frechet.entropy( α:number, s:number, m:number )\n    Returns the differential entropy of a Fréchet distribution with shape\n    parameter `α`, scale parameter `s`, and location `m` (in nats).\n","base.dists.frechet.Frechet":"\nbase.dists.frechet.Frechet( [α:number, s:number, m:number] )\n    Returns a Fréchet distribution object.\n","base.dists.frechet.kurtosis":"\nbase.dists.frechet.kurtosis( α:number, s:number, m:number )\n    Returns the excess kurtosis of a Fréchet distribution with shape parameter\n    `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.logcdf":"\nbase.dists.frechet.logcdf( x:number, α:number, s:number, m:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a Fréchet distribution with shape parameter `α`, scale parameter\n    `s`, and location `m`.\n","base.dists.frechet.logcdf.factory":"\nbase.dists.frechet.logcdf.factory( α:number, s:number, m:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Fréchet distribution with shape parameter\n    `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.logpdf":"\nbase.dists.frechet.logpdf( x:number, α:number, s:number, m:number )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n    location `m`.\n","base.dists.frechet.logpdf.factory":"\nbase.dists.frechet.logpdf.factory( α:number, s:number, m:number )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Fréchet distribution with shape parameter `α`, scale\n    parameter `s`, and location `m`.\n","base.dists.frechet.mean":"\nbase.dists.frechet.mean( α:number, s:number, m:number )\n    Returns the expected value of a Fréchet distribution with shape parameter\n    `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.median":"\nbase.dists.frechet.median( α:number, s:number, m:number )\n    Returns the median of a Fréchet distribution with shape parameter\n    `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.mode":"\nbase.dists.frechet.mode( α:number, s:number, m:number )\n    Returns the mode of a Fréchet distribution with shape parameter `α`, scale\n    parameter `s`, and location `m`.\n","base.dists.frechet.pdf":"\nbase.dists.frechet.pdf( x:number, α:number, s:number, m:number )\n    Evaluates the probability density function (PDF) for a Fréchet distribution\n    with shape parameter `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.pdf.factory":"\nbase.dists.frechet.pdf.factory( α:number, s:number, m:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n    location `m`.\n","base.dists.frechet.quantile":"\nbase.dists.frechet.quantile( p:number, α:number, s:number, m:number )\n    Evaluates the quantile function for a Fréchet distribution with shape\n    parameter `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.quantile.factory":"\nbase.dists.frechet.quantile.factory( α:number, s:number, m:number )\n    Returns a function for evaluating the quantile function of a Fréchet\n    distribution with shape parameter `α`, scale parameter `s`, and location\n    `m`.\n","base.dists.frechet.skewness":"\nbase.dists.frechet.skewness( α:number, s:number, m:number )\n    Returns the skewness of a Fréchet distribution with shape parameter `α`,\n    scale parameter `s`, and location `m`.\n","base.dists.frechet.stdev":"\nbase.dists.frechet.stdev( α:number, s:number, m:number )\n    Returns the standard deviation of a Fréchet distribution with shape\n    parameter `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.variance":"\nbase.dists.frechet.variance( α:number, s:number, m:number )\n    Returns the variance of a Fréchet distribution with shape parameter `α`,\n    scale parameter `s`, and location `m`.\n","base.dists.gamma.cdf":"\nbase.dists.gamma.cdf( x:number, α:number, β:number )\n    Evaluates the cumulative distribution function (CDF) for a gamma\n    distribution with shape parameter `α` and rate parameter `β` at a value `x`.\n","base.dists.gamma.cdf.factory":"\nbase.dists.gamma.cdf.factory( α:number, β:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a gamma distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.entropy":"\nbase.dists.gamma.entropy( α:number, β:number )\n    Returns the differential entropy of a gamma distribution.\n","base.dists.gamma.Gamma":"\nbase.dists.gamma.Gamma( [α:number, β:number] )\n    Returns a gamma distribution object.\n","base.dists.gamma.kurtosis":"\nbase.dists.gamma.kurtosis( α:number, β:number )\n    Returns the excess kurtosis of a gamma distribution.\n","base.dists.gamma.logcdf":"\nbase.dists.gamma.logcdf( x:number, α:number, β:number )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    gamma distribution with shape parameter `α` and rate parameter `β` at a\n    value `x`.\n","base.dists.gamma.logcdf.factory":"\nbase.dists.gamma.logcdf.factory( α:number, β:number )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a gamma distribution with shape parameter `α`\n    and rate parameter `β`.\n","base.dists.gamma.logpdf":"\nbase.dists.gamma.logpdf( x:number, α:number, β:number )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    gamma distribution with shape parameter `α` and rate parameter `β` at a\n    value `x`.\n","base.dists.gamma.logpdf.factory":"\nbase.dists.gamma.logpdf.factory( α:number, β:number )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a gamma distribution with shape parameter `α` and rate\n    parameter `β`.\n","base.dists.gamma.mean":"\nbase.dists.gamma.mean( α:number, β:number )\n    Returns the expected value of a gamma distribution.\n","base.dists.gamma.mgf":"\nbase.dists.gamma.mgf( t:number, α:number, β:number )\n    Evaluates the moment-generating function (MGF) for a gamma distribution with\n    shape parameter `α` and rate parameter `β` at a value `t`.\n","base.dists.gamma.mgf.factory":"\nbase.dists.gamma.mgf.factory( α:number, β:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    gamma distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.mode":"\nbase.dists.gamma.mode( α:number, β:number )\n    Returns the mode of a gamma distribution.\n","base.dists.gamma.pdf":"\nbase.dists.gamma.pdf( x:number, α:number, β:number )\n    Evaluates the probability density function (PDF) for a gamma distribution\n    with shape parameter `α` and rate parameter `β` at a value `x`.\n","base.dists.gamma.pdf.factory":"\nbase.dists.gamma.pdf.factory( α:number, β:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a gamma distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.quantile":"\nbase.dists.gamma.quantile( p:number, α:number, β:number )\n    Evaluates the quantile function for a gamma distribution with shape\n    parameter `α` and rate parameter `β` at a probability `p`.\n","base.dists.gamma.quantile.factory":"\nbase.dists.gamma.quantile.factory( α:number, β:number )\n    Returns a function for evaluating the quantile function of a gamma\n    distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.skewness":"\nbase.dists.gamma.skewness( α:number, β:number )\n    Returns the skewness of a gamma distribution.\n","base.dists.gamma.stdev":"\nbase.dists.gamma.stdev( α:number, β:number )\n    Returns the standard deviation of a gamma distribution.\n","base.dists.gamma.variance":"\nbase.dists.gamma.variance( α:number, β:number )\n    Returns the variance of a gamma distribution.\n","base.dists.geometric.cdf":"\nbase.dists.geometric.cdf( x:number, p:number )\n    Evaluates the cumulative distribution function (CDF) for a geometric\n    distribution with success probability `p` at a value `x`.\n","base.dists.geometric.cdf.factory":"\nbase.dists.geometric.cdf.factory( p:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a geometric distribution with success probability `p`.\n","base.dists.geometric.entropy":"\nbase.dists.geometric.entropy( p:number )\n    Returns the entropy of a geometric distribution with success probability\n    `p` (in nats).\n","base.dists.geometric.Geometric":"\nbase.dists.geometric.Geometric( [p:number] )\n    Returns a geometric distribution object.\n","base.dists.geometric.kurtosis":"\nbase.dists.geometric.kurtosis( p:number )\n    Returns the excess kurtosis of a geometric distribution with success\n    probability `p`.\n","base.dists.geometric.logcdf":"\nbase.dists.geometric.logcdf( x:number, p:number )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    geometric distribution with success probability `p` at a value `x`.\n","base.dists.geometric.logcdf.factory":"\nbase.dists.geometric.logcdf.factory( p:number )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a geometric distribution with success\n    probability `p`.\n","base.dists.geometric.logpmf":"\nbase.dists.geometric.logpmf( x:number, p:number )\n    Evaluates the logarithm of the probability mass function (PMF) for a\n    geometric distribution with success probability `p` at a value `x`.\n","base.dists.geometric.logpmf.factory":"\nbase.dists.geometric.logpmf.factory( p:number )\n    Returns a function for evaluating the logarithm of the probability mass\n    function (PMF) of a geometric distribution with success probability `p`.\n","base.dists.geometric.mean":"\nbase.dists.geometric.mean( p:number )\n    Returns the expected value of a geometric distribution with success\n    probability `p`.\n","base.dists.geometric.median":"\nbase.dists.geometric.median( p:number )\n    Returns the median of a geometric distribution with success probability `p`.\n","base.dists.geometric.mgf":"\nbase.dists.geometric.mgf( t:number, p:number )\n    Evaluates the moment-generating function (MGF) for a geometric\n    distribution with success probability `p` at a value `t`.\n","base.dists.geometric.mgf.factory":"\nbase.dists.geometric.mgf.factory( p:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    geometric distribution with success probability `p`.\n","base.dists.geometric.mode":"\nbase.dists.geometric.mode( p:number )\n    Returns the mode of a geometric distribution with success probability `p`.\n","base.dists.geometric.pmf":"\nbase.dists.geometric.pmf( x:number, p:number )\n    Evaluates the probability mass function (PMF) for a geometric distribution\n    with success probability `p` at a value `x`.\n","base.dists.geometric.pmf.factory":"\nbase.dists.geometric.pmf.factory( p:number )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    geometric distribution with success probability `p`.\n","base.dists.geometric.quantile":"\nbase.dists.geometric.quantile( r:number, p:number )\n    Evaluates the quantile function for a geometric distribution with success\n    probability `p` at a probability `r`.\n","base.dists.geometric.quantile.factory":"\nbase.dists.geometric.quantile.factory( p:number )\n    Returns a function for evaluating the quantile function of a geometric\n    distribution with success probability `p`.\n","base.dists.geometric.skewness":"\nbase.dists.geometric.skewness( p:number )\n    Returns the skewness of a geometric distribution with success probability\n    `p`.\n","base.dists.geometric.stdev":"\nbase.dists.geometric.stdev( p:number )\n    Returns the standard deviation of a geometric distribution with success\n    probability `p`.\n","base.dists.geometric.variance":"\nbase.dists.geometric.variance( p:number )\n    Returns the variance of a geometric distribution with success probability\n    `p`.\n","base.dists.gumbel.cdf":"\nbase.dists.gumbel.cdf( x:number, μ:number, β:number )\n    Evaluates the cumulative distribution function (CDF) for a Gumbel\n    distribution with location parameter `μ` and scale parameter `β` at a value\n    `x`.\n","base.dists.gumbel.cdf.factory":"\nbase.dists.gumbel.cdf.factory( μ:number, β:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Gumbel distribution with location parameter `μ` and scale parameter\n    `β`.\n","base.dists.gumbel.entropy":"\nbase.dists.gumbel.entropy( μ:number, β:number )\n    Returns the differential entropy of a Gumbel distribution with location\n    parameter `μ` and scale parameter `β` (in nats).\n","base.dists.gumbel.Gumbel":"\nbase.dists.gumbel.Gumbel( [μ:number, β:number] )\n    Returns a Gumbel distribution object.\n","base.dists.gumbel.kurtosis":"\nbase.dists.gumbel.kurtosis( μ:number, β:number )\n    Returns the excess kurtosis of a Gumbel distribution with location parameter\n    `μ` and scale parameter `β`.\n","base.dists.gumbel.logcdf":"\nbase.dists.gumbel.logcdf( x:number, μ:number, β:number )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n    value `x`.\n","base.dists.gumbel.logcdf.factory":"\nbase.dists.gumbel.logcdf.factory( μ:number, β:number )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Gumbel distribution with location parameter\n    `μ` and scale parameter `β`.\n","base.dists.gumbel.logpdf":"\nbase.dists.gumbel.logpdf( x:number, μ:number, β:number )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n    value `x`.\n","base.dists.gumbel.logpdf.factory":"\nbase.dists.gumbel.logpdf.factory( μ:number, β:number )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Gumbel distribution with location parameter `μ` and\n    scale parameter `β`.\n","base.dists.gumbel.mean":"\nbase.dists.gumbel.mean( μ:number, β:number )\n    Returns the expected value of a Gumbel distribution with location parameter\n    `μ` and scale parameter `β`.\n","base.dists.gumbel.median":"\nbase.dists.gumbel.median( μ:number, β:number )\n    Returns the median of a Gumbel distribution with location parameter `μ` and\n    scale parameter `β`.\n","base.dists.gumbel.mgf":"\nbase.dists.gumbel.mgf( t:number, μ:number, β:number )\n    Evaluates the moment-generating function (MGF) for a Gumbel distribution\n    with location parameter `μ` and scale parameter `β` at a value `t`.\n","base.dists.gumbel.mgf.factory":"\nbase.dists.gumbel.mgf.factory( μ:number, β:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Gumbel distribution with location parameter `μ` and scale parameter `β`.\n","base.dists.gumbel.mode":"\nbase.dists.gumbel.mode( μ:number, β:number )\n    Returns the mode of a Gumbel distribution with location parameter `μ` and\n    scale parameter `β`.\n","base.dists.gumbel.pdf":"\nbase.dists.gumbel.pdf( x:number, μ:number, β:number )\n    Evaluates the probability density function (PDF) for a Gumbel distribution\n    with location parameter `μ` and scale parameter `β` at a value `x`.\n","base.dists.gumbel.pdf.factory":"\nbase.dists.gumbel.pdf.factory( μ:number, β:number )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Gumbel distribution with location parameter `μ` and scale parameter\n    `β`.\n","base.dists.gumbel.quantile":"\nbase.dists.gumbel.quantile( p:number, μ:number, β:number )\n    Evaluates the quantile function for a Gumbel distribution with location\n    parameter `μ` and scale parameter `β` at a probability `p`.\n","base.dists.gumbel.quantile.factory":"\nbase.dists.gumbel.quantile.factory( μ:number, β:number )\n    Returns a function for evaluating the quantile function of a Gumbel\n    distribution with location parameter `μ` and scale parameter `β`.\n","base.dists.gumbel.skewness":"\nbase.dists.gumbel.skewness( μ:number, β:number )\n    Returns the skewness of a Gumbel distribution with location parameter `μ`\n    and scale parameter `β`.\n","base.dists.gumbel.stdev":"\nbase.dists.gumbel.stdev( μ:number, β:number )\n    Returns the standard deviation of a Gumbel distribution with location\n    parameter `μ` and scale parameter `β`.\n","base.dists.gumbel.variance":"\nbase.dists.gumbel.variance( μ:number, β:number )\n    Returns the variance of a Gumbel distribution with location parameter `μ`\n    and scale parameter `β`.\n","base.dists.hypergeometric.cdf":"\nbase.dists.hypergeometric.cdf( x:number, N:integer, K:integer, n:integer )\n    Evaluates the cumulative distribution function (CDF) for a hypergeometric\n    distribution with population size `N`, subpopulation size `K`, and number of\n    draws `n` at a value `x`.\n","base.dists.hypergeometric.cdf.factory":"\nbase.dists.hypergeometric.cdf.factory( N:integer, K:integer, n:integer )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a hypergeometric distribution with population size `N`, subpopulation\n    size `K`, and number of draws `n`.\n","base.dists.hypergeometric.Hypergeometric":"\nbase.dists.hypergeometric.Hypergeometric( [N:integer, K:integer, n:integer] )\n    Returns a hypergeometric distribution object.\n","base.dists.hypergeometric.kurtosis":"\nbase.dists.hypergeometric.kurtosis( N:integer, K:integer, n:integer )\n    Returns the excess kurtosis of a hypergeometric distribution.\n","base.dists.hypergeometric.logpmf":"\nbase.dists.hypergeometric.logpmf( x:number, N:integer, K:integer, n:integer )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    hypergeometric distribution with population size `N`, subpopulation size\n    `K`, and number of draws `n` at a value `x`.\n","base.dists.hypergeometric.logpmf.factory":"\nbase.dists.hypergeometric.logpmf.factory( N:integer, K:integer, n:integer )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a hypergeometric distribution with population size\n    `N`, subpopulation size `K`, and number of draws `n`.\n","base.dists.hypergeometric.mean":"\nbase.dists.hypergeometric.mean( N:integer, K:integer, n:integer )\n    Returns the expected value of a hypergeometric distribution.\n","base.dists.hypergeometric.mode":"\nbase.dists.hypergeometric.mode( N:integer, K:integer, n:integer )\n    Returns the mode of a hypergeometric distribution.\n","base.dists.hypergeometric.pmf":"\nbase.dists.hypergeometric.pmf( x:number, N:integer, K:integer, n:integer )\n    Evaluates the probability mass function (PMF) for a hypergeometric\n    distribution with population size `N`, subpopulation size `K`, and number of\n    draws `n` at a value `x`.\n","base.dists.hypergeometric.pmf.factory":"\nbase.dists.hypergeometric.pmf.factory( N:integer, K:integer, n:integer )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    hypergeometric distribution with population size `N`, subpopulation size\n    `K`, and number of draws `n`.\n","base.dists.hypergeometric.quantile":"\nbase.dists.hypergeometric.quantile( p:number, N:integer, K:integer, n:integer )\n    Evaluates the quantile function for a hypergeometric distribution with\n    population size `N`, subpopulation size `K`, and number of draws `n` at a\n    probability `p`.\n","base.dists.hypergeometric.quantile.factory":"\nbase.dists.hypergeometric.quantile.factory( N:integer, K:integer, n:integer )\n    Returns a function for evaluating the quantile function of a hypergeometric\n    distribution with population size `N`, subpopulation size `K`, and number of\n    draws `n`.\n","base.dists.hypergeometric.skewness":"\nbase.dists.hypergeometric.skewness( N:integer, K:integer, n:integer )\n    Returns the skewness of a hypergeometric distribution.\n","base.dists.hypergeometric.stdev":"\nbase.dists.hypergeometric.stdev( N:integer, K:integer, n:integer )\n    Returns the standard deviation of a hypergeometric distribution.\n","base.dists.hypergeometric.variance":"\nbase.dists.hypergeometric.variance( N:integer, K:integer, n:integer )\n    Returns the variance of a hypergeometric distribution.\n","base.dists.invgamma.cdf":"\nbase.dists.invgamma.cdf( x:number, α:number, β:number )\n    Evaluates the cumulative distribution function (CDF) for an inverse gamma\n    distribution with shape parameter `α` and scale parameter `β` at a value\n    `x`.\n","base.dists.invgamma.cdf.factory":"\nbase.dists.invgamma.cdf.factory( α:number, β:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an inverse gamma distribution with shape parameter `α` and scale\n    parameter `β`.\n","base.dists.invgamma.entropy":"\nbase.dists.invgamma.entropy( α:number, β:number )\n    Returns the differential entropy of an inverse gamma distribution.\n","base.dists.invgamma.InvGamma":"\nbase.dists.invgamma.InvGamma( [α:number, β:number] )\n    Returns an inverse gamma distribution object.\n","base.dists.invgamma.kurtosis":"\nbase.dists.invgamma.kurtosis( α:number, β:number )\n    Returns the excess kurtosis of an inverse gamma distribution.\n","base.dists.invgamma.logpdf":"\nbase.dists.invgamma.logpdf( x:number, α:number, β:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for an inverse gamma distribution with shape parameter `α` and scale\n    parameter `β` at a value `x`.\n","base.dists.invgamma.logpdf.factory":"\nbase.dists.invgamma.logpdf.factory( α:number, β:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) for an inverse gamma distribution with shape\n    parameter `α` and scale parameter `β`.\n","base.dists.invgamma.mean":"\nbase.dists.invgamma.mean( α:number, β:number )\n    Returns the expected value of an inverse gamma distribution.\n","base.dists.invgamma.mode":"\nbase.dists.invgamma.mode( α:number, β:number )\n    Returns the mode of an inverse gamma distribution.\n","base.dists.invgamma.pdf":"\nbase.dists.invgamma.pdf( x:number, α:number, β:number )\n    Evaluates the probability density function (PDF) for an inverse gamma\n    distribution with shape parameter `α` and scale parameter `β` at a value\n    `x`.\n","base.dists.invgamma.pdf.factory":"\nbase.dists.invgamma.pdf.factory( α:number, β:number )\n    Returns a function for evaluating the probability density function (PDF)\n    of an inverse gamma distribution with shape parameter `α` and scale\n    parameter `β`.\n","base.dists.invgamma.quantile":"\nbase.dists.invgamma.quantile( p:number, α:number, β:number )\n    Evaluates the quantile function for an inverse gamma distribution with shape\n    parameter `α` and scale parameter `β` at a probability `p`.\n","base.dists.invgamma.quantile.factory":"\nbase.dists.invgamma.quantile.factory( α:number, β:number )\n    Returns a function for evaluating the quantile function of an inverse gamma\n    distribution with shape parameter `α` and scale parameter `β`.\n","base.dists.invgamma.skewness":"\nbase.dists.invgamma.skewness( α:number, β:number )\n    Returns the skewness of an inverse gamma distribution.\n","base.dists.invgamma.stdev":"\nbase.dists.invgamma.stdev( α:number, β:number )\n    Returns the standard deviation of an inverse gamma distribution.\n","base.dists.invgamma.variance":"\nbase.dists.invgamma.variance( α:number, β:number )\n    Returns the variance of an inverse gamma distribution.\n","base.dists.kumaraswamy.cdf":"\nbase.dists.kumaraswamy.cdf( x:number, a:number, b:number )\n    Evaluates the cumulative distribution function (CDF) for Kumaraswamy's\n    double bounded distribution with first shape parameter `a` and second shape\n    parameter `b` at a value `x`.\n","base.dists.kumaraswamy.cdf.factory":"\nbase.dists.kumaraswamy.cdf.factory( a:number, b:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Kumaraswamy's double bounded distribution with first shape parameter\n    `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.Kumaraswamy":"\nbase.dists.kumaraswamy.Kumaraswamy( [a:number, b:number] )\n    Returns a Kumaraswamy's double bounded distribution object.\n","base.dists.kumaraswamy.kurtosis":"\nbase.dists.kumaraswamy.kurtosis( a:number, b:number )\n    Returns the excess kurtosis of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.logcdf":"\nbase.dists.kumaraswamy.logcdf( x:number, a:number, b:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for Kumaraswamy's double bounded distribution with first shape\n    parameter `a` and second shape parameter `b` at a value `x`.\n","base.dists.kumaraswamy.logcdf.factory":"\nbase.dists.kumaraswamy.logcdf.factory( a:number, b:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Kumaraswamy's double bounded distribution\n    with first shape parameter `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.logpdf":"\nbase.dists.kumaraswamy.logpdf( x:number, a:number, b:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for Kumaraswamy's double bounded distribution with first shape parameter `a`\n    and second shape parameter `b` at a value `x`.\n","base.dists.kumaraswamy.logpdf.factory":"\nbase.dists.kumaraswamy.logpdf.factory( a:number, b:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a Kumaraswamy's double bounded distribution with\n    first shape parameter `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.mean":"\nbase.dists.kumaraswamy.mean( a:number, b:number )\n    Returns the mean of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.median":"\nbase.dists.kumaraswamy.median( a:number, b:number )\n    Returns the median of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.mode":"\nbase.dists.kumaraswamy.mode( a:number, b:number )\n    Returns the mode of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.pdf":"\nbase.dists.kumaraswamy.pdf( x:number, a:number, b:number )\n    Evaluates the probability density function (PDF) for Kumaraswamy's double\n    bounded distribution with first shape parameter `a` and second shape\n    parameter `b` at a value `x`.\n","base.dists.kumaraswamy.pdf.factory":"\nbase.dists.kumaraswamy.pdf.factory( a:number, b:number )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Kumaraswamy's double bounded distribution with first shape parameter\n    `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.quantile":"\nbase.dists.kumaraswamy.quantile( p:number, a:number, b:number )\n    Evaluates the quantile function for a Kumaraswamy's double bounded\n    distribution with first shape parameter `a` and second shape parameter `b`\n    at a probability `p`.\n","base.dists.kumaraswamy.quantile.factory":"\nbase.dists.kumaraswamy.quantile.factory( a:number, b:number )\n    Returns a function for evaluating the quantile function of a Kumaraswamy's\n    double bounded distribution with first shape parameter `a` and second shape\n    parameter `b`.\n","base.dists.kumaraswamy.skewness":"\nbase.dists.kumaraswamy.skewness( a:number, b:number )\n    Returns the skewness of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.stdev":"\nbase.dists.kumaraswamy.stdev( a:number, b:number )\n    Returns the standard deviation of a Kumaraswamy's double bounded\n    distribution.\n","base.dists.kumaraswamy.variance":"\nbase.dists.kumaraswamy.variance( a:number, b:number )\n    Returns the variance of a Kumaraswamy's double bounded distribution.\n","base.dists.laplace.cdf":"\nbase.dists.laplace.cdf( x:number, μ:number, b:number )\n    Evaluates the cumulative distribution function (CDF) for a Laplace\n    distribution with scale parameter `b` and location parameter `μ` at a\n    value `x`.\n","base.dists.laplace.cdf.factory":"\nbase.dists.laplace.cdf.factory( μ:number, b:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Laplace distribution with scale parameter `b` and location parameter\n    `μ`.\n","base.dists.laplace.entropy":"\nbase.dists.laplace.entropy( μ:number, b:number )\n    Returns the differential entropy of a Laplace distribution with location\n    parameter `μ` and scale parameter `b`.\n","base.dists.laplace.kurtosis":"\nbase.dists.laplace.kurtosis( μ:number, b:number )\n    Returns the excess kurtosis of a Laplace distribution with location\n    parameter `μ` and scale parameter `b`.\n","base.dists.laplace.Laplace":"\nbase.dists.laplace.Laplace( [μ:number, b:number] )\n    Returns a Laplace distribution object.\n","base.dists.laplace.logcdf":"\nbase.dists.laplace.logcdf( x:number, μ:number, b:number )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    Laplace distribution with scale parameter `b` and location parameter `μ` at\n    a value `x`.\n","base.dists.laplace.logcdf.factory":"\nbase.dists.laplace.logcdf.factory( μ:number, b:number )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Laplace distribution with scale parameter\n    `b` and location parameter `μ`.\n","base.dists.laplace.logpdf":"\nbase.dists.laplace.logpdf( x:number, μ:number, b:number )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    Laplace distribution with scale parameter `b` and location parameter `μ` at\n    a value `x`.\n","base.dists.laplace.logpdf.factory":"\nbase.dists.laplace.logpdf.factory( μ:number, b:number )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Laplace distribution with scale parameter `b` and\n    location parameter `μ`.\n","base.dists.laplace.mean":"\nbase.dists.laplace.mean( μ:number, b:number )\n    Returns the expected value of a Laplace distribution with location parameter\n    `μ` and scale parameter `b`.\n","base.dists.laplace.median":"\nbase.dists.laplace.median( μ:number, b:number )\n    Returns the median of a Laplace distribution with location parameter `μ` and\n    scale parameter `b`.\n","base.dists.laplace.mgf":"\nbase.dists.laplace.mgf( t:number, μ:number, b:number )\n    Evaluates the moment-generating function (MGF) for a Laplace\n    distribution with scale parameter `b` and location parameter `μ` at a\n    value `t`.\n","base.dists.laplace.mgf.factory":"\nbase.dists.laplace.mgf.factory( μ:number, b:number )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a Laplace distribution with scale parameter `b` and location parameter\n    `μ`.\n","base.dists.laplace.mode":"\nbase.dists.laplace.mode( μ:number, b:number )\n    Returns the mode of a Laplace distribution with location parameter `μ` and\n    scale parameter `b`.\n","base.dists.laplace.pdf":"\nbase.dists.laplace.pdf( x:number, μ:number, b:number )\n    Evaluates the probability density function (PDF) for a Laplace\n    distribution with scale parameter `b` and location parameter `μ` at a\n    value `x`.\n","base.dists.laplace.pdf.factory":"\nbase.dists.laplace.pdf.factory( μ:number, b:number )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Laplace distribution with scale parameter `b` and location parameter\n    `μ`.\n","base.dists.laplace.quantile":"\nbase.dists.laplace.quantile( p:number, μ:number, b:number )\n    Evaluates the quantile function for a Laplace distribution with scale\n    parameter `b` and location parameter `μ` at a probability `p`.\n","base.dists.laplace.quantile.factory":"\nbase.dists.laplace.quantile.factory( μ:number, b:number )\n    Returns a function for evaluating the quantile function of a Laplace\n    distribution with scale parameter `b` and location parameter `μ`.\n","base.dists.laplace.skewness":"\nbase.dists.laplace.skewness( μ:number, b:number )\n    Returns the skewness of a Laplace distribution with location parameter `μ`\n    and scale parameter `b`.\n","base.dists.laplace.stdev":"\nbase.dists.laplace.stdev( μ:number, b:number )\n    Returns the standard deviation of a Laplace distribution with location\n    parameter `μ` and scale parameter `b`.\n","base.dists.laplace.variance":"\nbase.dists.laplace.variance( μ:number, b:number )\n    Returns the variance of a Laplace distribution with location parameter `μ`\n    and scale parameter `b`.\n","base.dists.levy.cdf":"\nbase.dists.levy.cdf( x:number, μ:number, c:number )\n    Evaluates the cumulative distribution function (CDF) for a Lévy distribution\n    with location parameter `μ` and scale parameter `c` at a value `x`.\n","base.dists.levy.cdf.factory":"\nbase.dists.levy.cdf.factory( μ:number, c:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Lévy distribution with location parameter `μ` and scale parameter `c`.\n","base.dists.levy.entropy":"\nbase.dists.levy.entropy( μ:number, c:number )\n    Returns the entropy of a Lévy distribution with location parameter `μ` and\n    scale parameter `c`.\n","base.dists.levy.Levy":"\nbase.dists.levy.Levy( [μ:number, c:number] )\n    Returns a Lévy distribution object.\n","base.dists.levy.logcdf":"\nbase.dists.levy.logcdf( x:number, μ:number, c:number )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    Lévy distribution with location parameter `μ` and scale parameter `c` at a\n    value `x`.\n","base.dists.levy.logcdf.factory":"\nbase.dists.levy.logcdf.factory( μ:number, c:number )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Lévy distribution with location parameter\n    `μ` and scale parameter `c`.\n","base.dists.levy.logpdf":"\nbase.dists.levy.logpdf( x:number, μ:number, c:number )\n    Evaluates the logarithm of the probability density function (PDF) for a Lévy\n    distribution with location parameter `μ` and scale parameter `c` at a value\n    `x`.\n","base.dists.levy.logpdf.factory":"\nbase.dists.levy.logpdf.factory( μ:number, c:number )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Lévy distribution with location parameter `μ` and scale\n    parameter `c`.\n","base.dists.levy.mean":"\nbase.dists.levy.mean( μ:number, c:number )\n    Returns the expected value of a Lévy distribution with location parameter\n    `μ` and scale parameter `c`.\n","base.dists.levy.median":"\nbase.dists.levy.median( μ:number, c:number )\n    Returns the median of a Lévy distribution with location parameter `μ` and\n    scale parameter `c`.\n","base.dists.levy.mode":"\nbase.dists.levy.mode( μ:number, c:number )\n    Returns the mode of a Lévy distribution with location parameter `μ` and\n    scale parameter `c`.\n","base.dists.levy.pdf":"\nbase.dists.levy.pdf( x:number, μ:number, c:number )\n    Evaluates the probability density function (PDF) for a Lévy distribution\n    with location parameter `μ` and scale parameter `c` at a value `x`.\n","base.dists.levy.pdf.factory":"\nbase.dists.levy.pdf.factory( μ:number, c:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Lévy distribution with location parameter `μ` and scale parameter `c`.\n","base.dists.levy.quantile":"\nbase.dists.levy.quantile( p:number, μ:number, c:number )\n    Evaluates the quantile function for a Lévy distribution with location\n    parameter `μ` and scale parameter `c` at a probability `p`.\n","base.dists.levy.quantile.factory":"\nbase.dists.levy.quantile.factory( μ:number, c:number )\n    Returns a function for evaluating the quantile function of a Lévy\n    distribution with location parameter `μ` and scale parameter `c`.\n","base.dists.levy.stdev":"\nbase.dists.levy.stdev( μ:number, c:number )\n    Returns the standard deviation of a Lévy distribution with location\n    parameter `μ` and scale parameter `c`.\n","base.dists.levy.variance":"\nbase.dists.levy.variance( μ:number, c:number )\n    Returns the variance of a Lévy distribution with location parameter `μ` and\n    scale parameter `c`.\n","base.dists.logistic.cdf":"\nbase.dists.logistic.cdf( x:number, μ:number, s:number )\n    Evaluates the cumulative distribution function (CDF) for a logistic\n    distribution with location parameter `μ` and scale parameter `s` at a value\n    `x`.\n","base.dists.logistic.cdf.factory":"\nbase.dists.logistic.cdf.factory( μ:number, s:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a logistic distribution with location parameter `μ` and scale parameter\n    `s`.\n","base.dists.logistic.entropy":"\nbase.dists.logistic.entropy( μ:number, s:number )\n    Returns the entropy of a logistic distribution with location parameter `μ`\n    and scale parameter `s`.\n","base.dists.logistic.kurtosis":"\nbase.dists.logistic.kurtosis( μ:number, s:number )\n    Returns the excess kurtosis of a logistic distribution with location\n    parameter `μ` and scale parameter `s`.\n","base.dists.logistic.logcdf":"\nbase.dists.logistic.logcdf( x:number, μ:number, s:number )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    logistic distribution with location parameter `μ` and scale parameter `s` at\n    a value `x`.\n","base.dists.logistic.logcdf.factory":"\nbase.dists.logistic.logcdf.factory( μ:number, s:number )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Logistic distribution with location\n    parameter `μ` and scale parameter `s`.\n","base.dists.logistic.Logistic":"\nbase.dists.logistic.Logistic( [μ:number, s:number] )\n    Returns a logistic distribution object.\n","base.dists.logistic.logpdf":"\nbase.dists.logistic.logpdf( x:number, μ:number, s:number )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    logistic distribution with location parameter `μ` and scale parameter `s` at\n    a value `x`.\n","base.dists.logistic.logpdf.factory":"\nbase.dists.logistic.logpdf.factory( μ:number, s:number )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Logistic distribution with location parameter `μ` and\n    scale parameter `s`.\n","base.dists.logistic.mean":"\nbase.dists.logistic.mean( μ:number, s:number )\n    Returns the expected value of a logistic distribution with location\n    parameter `μ` and scale parameter `s`.\n","base.dists.logistic.median":"\nbase.dists.logistic.median( μ:number, s:number )\n    Returns the median of a logistic distribution with location parameter `μ`\n    and scale parameter `s`.\n","base.dists.logistic.mgf":"\nbase.dists.logistic.mgf( t:number, μ:number, s:number )\n    Evaluates the moment-generating function (MGF) for a logistic distribution\n    with location parameter `μ` and scale parameter `s` at a value `t`.\n","base.dists.logistic.mgf.factory":"\nbase.dists.logistic.mgf.factory( μ:number, s:number )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a Logistic distribution with location parameter `μ` and scale parameter\n    `s`.\n","base.dists.logistic.mode":"\nbase.dists.logistic.mode( μ:number, s:number )\n    Returns the mode of a logistic distribution with location parameter `μ` and\n    scale parameter `s`.\n","base.dists.logistic.pdf":"\nbase.dists.logistic.pdf( x:number, μ:number, s:number )\n    Evaluates the probability density function (PDF) for a logistic distribution\n    with location parameter `μ` and scale parameter `s` at a value `x`.\n","base.dists.logistic.pdf.factory":"\nbase.dists.logistic.pdf.factory( μ:number, s:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Logistic distribution with location parameter `μ` and scale parameter `s`.\n","base.dists.logistic.quantile":"\nbase.dists.logistic.quantile( p:number, μ:number, s:number )\n    Evaluates the quantile function for a logistic distribution with location\n    parameter `μ` and scale parameter `s` at a probability `p`.\n","base.dists.logistic.quantile.factory":"\nbase.dists.logistic.quantile.factory( μ:number, s:number )\n    Returns a function for evaluating the quantile function of a logistic\n    distribution with location parameter `μ` and scale parameter `s`.\n","base.dists.logistic.skewness":"\nbase.dists.logistic.skewness( μ:number, s:number )\n    Returns the skewness of a logistic distribution with location parameter `μ`\n    and scale parameter `s`.\n","base.dists.logistic.stdev":"\nbase.dists.logistic.stdev( μ:number, s:number )\n    Returns the standard deviation of a logistic distribution with location\n    parameter `μ` and scale parameter `s`.\n","base.dists.logistic.variance":"\nbase.dists.logistic.variance( μ:number, s:number )\n    Returns the variance of a logistic distribution with location parameter `μ`\n    and scale parameter `s`.\n","base.dists.lognormal.cdf":"\nbase.dists.lognormal.cdf( x:number, μ:number, σ:number )\n    Evaluates the cumulative distribution function (CDF) for a lognormal\n    distribution with location parameter `μ` and scale parameter `σ` at a value\n    `x`.\n","base.dists.lognormal.cdf.factory":"\nbase.dists.lognormal.cdf.factory( μ:number, σ:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a lognormal distribution with location parameter `μ` and scale parameter\n    `σ`.\n","base.dists.lognormal.entropy":"\nbase.dists.lognormal.entropy( μ:number, σ:number )\n    Returns the differential entropy of a lognormal distribution with location\n    `μ` and scale `σ` (in nats).\n","base.dists.lognormal.kurtosis":"\nbase.dists.lognormal.kurtosis( μ:number, σ:number )\n    Returns the excess kurtosis of a lognormal distribution with location `μ`\n    and scale `σ`.\n","base.dists.lognormal.LogNormal":"\nbase.dists.lognormal.LogNormal( [μ:number, σ:number] )\n    Returns a lognormal distribution object.\n","base.dists.lognormal.logcdf":"\nbase.dists.lognormal.logcdf( x:number, μ:number, σ:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a lognormal distribution with mean `μ` and standard deviation `σ`\n    at a value `x`.\n","base.dists.lognormal.logcdf.factory":"\nbase.dists.lognormal.logcdf.factory( μ:number, σ:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a lognormal distribution with mean `μ` and\n    standard deviation `σ`.\n","base.dists.lognormal.logpdf":"\nbase.dists.lognormal.logpdf( x:number, μ:number, σ:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a lognormal distribution with location parameter `μ` and scale parameter\n    `σ` at a value `x`.\n","base.dists.lognormal.logpdf.factory":"\nbase.dists.lognormal.logpdf.factory( μ:number, σ:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a lognormal distribution with location parameter\n    `μ` and scale parameter `σ`.\n","base.dists.lognormal.mean":"\nbase.dists.lognormal.mean( μ:number, σ:number )\n    Returns the expected value of a lognormal distribution with location `μ` and\n    scale `σ`.\n","base.dists.lognormal.median":"\nbase.dists.lognormal.median( μ:number, σ:number )\n    Returns the median of a lognormal distribution with location `μ` and scale\n    `σ`.\n","base.dists.lognormal.mode":"\nbase.dists.lognormal.mode( μ:number, σ:number )\n    Returns the mode of a lognormal distribution with location `μ` and scale\n    `σ`.\n","base.dists.lognormal.pdf":"\nbase.dists.lognormal.pdf( x:number, μ:number, σ:number )\n    Evaluates the probability density function (PDF) for a lognormal\n    distribution with location parameter `μ` and scale parameter `σ` at a value\n    `x`.\n","base.dists.lognormal.pdf.factory":"\nbase.dists.lognormal.pdf.factory( μ:number, σ:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a lognormal distribution with location parameter `μ` and scale parameter\n    `σ`.\n","base.dists.lognormal.quantile":"\nbase.dists.lognormal.quantile( p:number, μ:number, σ:number )\n    Evaluates the quantile function for a lognormal distribution with location\n    parameter `μ` and scale parameter `σ` at a probability `p`.\n","base.dists.lognormal.quantile.factory":"\nbase.dists.lognormal.quantile.factory( μ:number, σ:number )\n    Returns a function for evaluating the quantile function of a lognormal\n    distribution with location parameter `μ` and scale parameter `σ`.\n","base.dists.lognormal.skewness":"\nbase.dists.lognormal.skewness( μ:number, σ:number )\n    Returns the skewness of a lognormal distribution with location `μ` and scale\n    `σ`.\n","base.dists.lognormal.stdev":"\nbase.dists.lognormal.stdev( μ:number, σ:number )\n    Returns the standard deviation of a lognormal distribution with location `μ`\n    and scale `σ`.\n","base.dists.lognormal.variance":"\nbase.dists.lognormal.variance( μ:number, σ:number )\n    Returns the variance of a lognormal distribution with location `μ` and scale\n    `σ`.\n","base.dists.negativeBinomial.cdf":"\nbase.dists.negativeBinomial.cdf( x:number, r:number, p:number )\n    Evaluates the cumulative distribution function (CDF) for a negative binomial\n    distribution with number of successes until experiment is stopped `r` and\n    success probability `p` at a value `x`.\n","base.dists.negativeBinomial.cdf.factory":"\nbase.dists.negativeBinomial.cdf.factory( r:number, p:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a negative binomial distribution with number of successes until\n    experiment is stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.kurtosis":"\nbase.dists.negativeBinomial.kurtosis( r:integer, p:number )\n    Returns the excess kurtosis of a negative binomial distribution.\n","base.dists.negativeBinomial.logpmf":"\nbase.dists.negativeBinomial.logpmf( x:number, r:number, p:number )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    negative binomial distribution with number of successes until experiment is\n    stopped `r` and success probability `p` at a value `x`.\n","base.dists.negativeBinomial.logpmf.factory":"\nbase.dists.negativeBinomial.logpmf.factory( r:number, p:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a negative binomial distribution with number of\n    successes until experiment is stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.mean":"\nbase.dists.negativeBinomial.mean( r:integer, p:number )\n    Returns the expected value of a negative binomial distribution.\n","base.dists.negativeBinomial.mgf":"\nbase.dists.negativeBinomial.mgf( x:number, r:number, p:number )\n    Evaluates the moment-generating function (MGF) for a negative binomial\n    distribution with number of successes until experiment is stopped `r` and\n    success probability `p` at a value `t`.\n","base.dists.negativeBinomial.mgf.factory":"\nbase.dists.negativeBinomial.mgf.factory( r:number, p:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    negative binomial distribution with number of successes until experiment is\n    stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.mode":"\nbase.dists.negativeBinomial.mode( r:integer, p:number )\n    Returns the mode of a negative binomial distribution.\n","base.dists.negativeBinomial.NegativeBinomial":"\nbase.dists.negativeBinomial.NegativeBinomial( [r:number, p:number] )\n    Returns a negative binomial distribution object.\n","base.dists.negativeBinomial.pmf":"\nbase.dists.negativeBinomial.pmf( x:number, r:number, p:number )\n    Evaluates the probability mass function (PMF) for a negative binomial\n    distribution with number of successes until experiment is stopped `r` and\n    success probability `p` at a value `x`.\n","base.dists.negativeBinomial.pmf.factory":"\nbase.dists.negativeBinomial.pmf.factory( r:number, p:number )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    negative binomial distribution with number of successes until experiment is\n    stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.quantile":"\nbase.dists.negativeBinomial.quantile( k:number, r:number, p:number )\n    Evaluates the quantile function for a negative binomial distribution with\n    number of successes until experiment is stopped `r` and success probability\n    `p` at a probability `k`.\n","base.dists.negativeBinomial.quantile.factory":"\nbase.dists.negativeBinomial.quantile.factory( r:number, p:number )\n    Returns a function for evaluating the quantile function of a negative\n    binomial distribution with number of successes until experiment is stopped\n    `r` and success probability `p`.\n","base.dists.negativeBinomial.skewness":"\nbase.dists.negativeBinomial.skewness( r:integer, p:number )\n    Returns the skewness of a negative binomial distribution.\n","base.dists.negativeBinomial.stdev":"\nbase.dists.negativeBinomial.stdev( r:integer, p:number )\n    Returns the standard deviation of a negative binomial distribution.\n","base.dists.negativeBinomial.variance":"\nbase.dists.negativeBinomial.variance( r:integer, p:number )\n    Returns the variance of a negative binomial distribution.\n","base.dists.normal.cdf":"\nbase.dists.normal.cdf( x:number, μ:number, σ:number )\n    Evaluates the cumulative distribution function (CDF) for a normal\n    distribution with mean `μ` and standard deviation `σ` at a value `x`.\n","base.dists.normal.cdf.factory":"\nbase.dists.normal.cdf.factory( μ:number, σ:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.entropy":"\nbase.dists.normal.entropy( μ:number, σ:number )\n    Returns the differential entropy of a normal distribution with mean `μ` and\n    standard deviation `σ`.\n","base.dists.normal.kurtosis":"\nbase.dists.normal.kurtosis( μ:number, σ:number )\n    Returns the excess kurtosis of a normal distribution with mean `μ` and\n    standard deviation `σ`.\n","base.dists.normal.logcdf":"\nbase.dists.normal.logcdf( x:number, μ:number, σ:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a normal distribution with mean `μ` and standard deviation `σ` at\n    a value `x`.\n","base.dists.normal.logcdf.factory":"\nbase.dists.normal.logcdf.factory( μ:number, σ:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a normal distribution with mean `μ` and\n    standard deviation `σ`.\n","base.dists.normal.logpdf":"\nbase.dists.normal.logpdf( x:number, μ:number, σ:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a normal distribution with mean `μ` and standard deviation `σ` at a\n    value `x`.\n","base.dists.normal.logpdf.factory":"\nbase.dists.normal.logpdf.factory( μ:number, σ:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a normal distribution with mean `μ` and standard\n    deviation `σ`.\n","base.dists.normal.mean":"\nbase.dists.normal.mean( μ:number, σ:number )\n    Returns the expected value of a normal distribution with mean `μ` and\n    standard deviation `σ`.\n","base.dists.normal.median":"\nbase.dists.normal.median( μ:number, σ:number )\n    Returns the median of a normal distribution with mean `μ` and standard\n    deviation `σ`.\n","base.dists.normal.mgf":"\nbase.dists.normal.mgf( x:number, μ:number, σ:number )\n    Evaluates the moment-generating function (MGF) for a normal distribution\n    with mean `μ` and standard deviation `σ` at a value `t`.\n","base.dists.normal.mgf.factory":"\nbase.dists.normal.mgf.factory( μ:number, σ:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.mode":"\nbase.dists.normal.mode( μ:number, σ:number )\n    Returns the mode of a normal distribution with mean `μ` and standard\n    deviation `σ`.\n","base.dists.normal.Normal":"\nbase.dists.normal.Normal( [μ:number, σ:number] )\n    Returns a normal distribution object.\n","base.dists.normal.pdf":"\nbase.dists.normal.pdf( x:number, μ:number, σ:number )\n    Evaluates the probability density function (PDF) for a normal distribution\n    with mean `μ` and standard deviation `σ` at a value `x`.\n","base.dists.normal.pdf.factory":"\nbase.dists.normal.pdf.factory( μ:number, σ:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.quantile":"\nbase.dists.normal.quantile( p:number, μ:number, σ:number )\n    Evaluates the quantile function for a normal distribution with mean `μ` and\n    standard deviation `σ` at a probability `p`.\n","base.dists.normal.quantile.factory":"\nbase.dists.normal.quantile.factory( μ:number, σ:number )\n    Returns a function for evaluating the quantile function\n    of a normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.skewness":"\nbase.dists.normal.skewness( μ:number, σ:number )\n    Returns the skewness of a normal distribution with mean `μ` and standard\n    deviation `σ`.\n","base.dists.normal.stdev":"\nbase.dists.normal.stdev( μ:number, σ:number )\n    Returns the standard deviation of a normal distribution with mean `μ` and\n    standard deviation `σ`.\n","base.dists.normal.variance":"\nbase.dists.normal.variance( μ:number, σ:number )\n    Returns the variance of a normal distribution with mean `μ` and standard\n    deviation `σ`.\n","base.dists.pareto1.cdf":"\nbase.dists.pareto1.cdf( x:number, α:number, β:number )\n    Evaluates the cumulative distribution function (CDF) for a Pareto (Type I)\n    distribution with shape parameter `α` and scale parameter `β` at a value\n    `x`.\n","base.dists.pareto1.cdf.factory":"\nbase.dists.pareto1.cdf.factory( α:number, β:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Pareto (Type I) distribution with shape parameter `α` and scale\n    parameter `β`.\n","base.dists.pareto1.entropy":"\nbase.dists.pareto1.entropy( α:number, β:number )\n    Returns the differential entropy of a Pareto (Type I) distribution\n    (in nats).\n","base.dists.pareto1.kurtosis":"\nbase.dists.pareto1.kurtosis( α:number, β:number )\n    Returns the excess kurtosis of a Pareto (Type I) distribution.\n","base.dists.pareto1.logcdf":"\nbase.dists.pareto1.logcdf( x:number, α:number, β:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a Pareto (Type I) distribution with shape parameter `α` and scale\n    parameter `β` at a value `x`.\n","base.dists.pareto1.logcdf.factory":"\nbase.dists.pareto1.logcdf.factory( α:number, β:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Pareto (Type I) distribution with shape\n    parameter `α` and scale parameter `β`.\n","base.dists.pareto1.logpdf":"\nbase.dists.pareto1.logpdf( x:number, α:number, β:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a Pareto (Type I) distribution with shape parameter `α` and scale\n    parameter `β` at a value `x`.\n","base.dists.pareto1.logpdf.factory":"\nbase.dists.pareto1.logpdf.factory( α:number, β:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a Pareto (Type I) distribution with shape\n    parameter `α` and scale parameter `β`.\n","base.dists.pareto1.mean":"\nbase.dists.pareto1.mean( α:number, β:number )\n    Returns the expected value of a Pareto (Type I) distribution.\n","base.dists.pareto1.median":"\nbase.dists.pareto1.median( α:number, β:number )\n    Returns the median of a Pareto (Type I) distribution.\n","base.dists.pareto1.mode":"\nbase.dists.pareto1.mode( α:number, β:number )\n    Returns the mode of a Pareto (Type I) distribution.\n","base.dists.pareto1.Pareto1":"\nbase.dists.pareto1.Pareto1( [α:number, β:number] )\n    Returns a Pareto (Type I) distribution object.\n","base.dists.pareto1.pdf":"\nbase.dists.pareto1.pdf( x:number, α:number, β:number )\n    Evaluates the probability density function (PDF) for a Pareto (Type I)\n    distribution with shape parameter `α` and scale parameter `β` at a value\n    `x`.\n","base.dists.pareto1.pdf.factory":"\nbase.dists.pareto1.pdf.factory( α:number, β:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Pareto (Type I) distribution with shape parameter `α` and scale parameter\n    `β`.\n","base.dists.pareto1.quantile":"\nbase.dists.pareto1.quantile( p:number, α:number, β:number )\n    Evaluates the quantile function for a Pareto (Type I) distribution with\n    shape parameter `α` and scale parameter `β` at a probability `p`.\n","base.dists.pareto1.quantile.factory":"\nbase.dists.pareto1.quantile.factory( α:number, β:number )\n    Returns a function for evaluating the quantile function of a Pareto (Type I)\n    distribution with shape parameter `α` and scale parameter `β`.\n","base.dists.pareto1.skewness":"\nbase.dists.pareto1.skewness( α:number, β:number )\n    Returns the skewness of a Pareto (Type I) distribution.\n","base.dists.pareto1.stdev":"\nbase.dists.pareto1.stdev( α:number, β:number )\n    Returns the standard deviation of a Pareto (Type I) distribution.\n","base.dists.pareto1.variance":"\nbase.dists.pareto1.variance( α:number, β:number )\n    Returns the variance of a Pareto (Type I) distribution.\n","base.dists.poisson.cdf":"\nbase.dists.poisson.cdf( x:number, λ:number )\n    Evaluates the cumulative distribution function (CDF) for a Poisson\n    distribution with mean parameter `λ` at a value `x`.\n","base.dists.poisson.cdf.factory":"\nbase.dists.poisson.cdf.factory( λ:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.entropy":"\nbase.dists.poisson.entropy( λ:number )\n    Returns the entropy of a Poisson distribution.\n","base.dists.poisson.kurtosis":"\nbase.dists.poisson.kurtosis( λ:number )\n    Returns the excess kurtosis of a Poisson distribution.\n","base.dists.poisson.logpmf":"\nbase.dists.poisson.logpmf( x:number, λ:number )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    Poisson distribution with mean parameter `λ` at a value `x`.\n","base.dists.poisson.logpmf.factory":"\nbase.dists.poisson.logpmf.factory( λ:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.mean":"\nbase.dists.poisson.mean( λ:number )\n    Returns the expected value of a Poisson distribution.\n","base.dists.poisson.median":"\nbase.dists.poisson.median( λ:number )\n    Returns the median of a Poisson distribution.\n","base.dists.poisson.mgf":"\nbase.dists.poisson.mgf( x:number, λ:number )\n    Evaluates the moment-generating function (MGF) for a Poisson distribution\n    with mean parameter `λ` at a value `x`.\n","base.dists.poisson.mgf.factory":"\nbase.dists.poisson.mgf.factory( λ:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.mode":"\nbase.dists.poisson.mode( λ:number )\n    Returns the mode of a Poisson distribution.\n","base.dists.poisson.pmf":"\nbase.dists.poisson.pmf( x:number, λ:number )\n    Evaluates the probability mass function (PMF) for a Poisson\n    distribution with mean parameter `λ` at a value `x`.\n","base.dists.poisson.pmf.factory":"\nbase.dists.poisson.pmf.factory( λ:number )\n    Returns a function for evaluating the probability mass function (PMF)\n    of a Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.Poisson":"\nbase.dists.poisson.Poisson( [λ:number] )\n    Returns a Poisson distribution object.\n","base.dists.poisson.quantile":"\nbase.dists.poisson.quantile( p:number, λ:number )\n    Evaluates the quantile function for a Poisson distribution with mean\n    parameter `λ` at a probability `p`.\n","base.dists.poisson.quantile.factory":"\nbase.dists.poisson.quantile.factory( λ:number )\n    Returns a function for evaluating the quantile function of a Poisson\n    distribution with mean parameter `λ`.\n","base.dists.poisson.skewness":"\nbase.dists.poisson.skewness( λ:number )\n    Returns the skewness of a Poisson distribution.\n","base.dists.poisson.stdev":"\nbase.dists.poisson.stdev( λ:number )\n    Returns the standard deviation of a Poisson distribution.\n","base.dists.poisson.variance":"\nbase.dists.poisson.variance( λ:number )\n    Returns the variance of a Poisson distribution.\n","base.dists.rayleigh.cdf":"\nbase.dists.rayleigh.cdf( x:number, sigma:number )\n    Evaluates the cumulative distribution function (CDF) for a Rayleigh\n    distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.cdf.factory":"\nbase.dists.rayleigh.cdf.factory( sigma:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.entropy":"\nbase.dists.rayleigh.entropy( σ:number )\n    Returns the differential entropy of a Rayleigh distribution.\n","base.dists.rayleigh.kurtosis":"\nbase.dists.rayleigh.kurtosis( σ:number )\n    Returns the excess kurtosis of a Rayleigh distribution.\n","base.dists.rayleigh.logcdf":"\nbase.dists.rayleigh.logcdf( x:number, sigma:number )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    Rayleigh distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.logcdf.factory":"\nbase.dists.rayleigh.logcdf.factory( sigma:number )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Rayleigh distribution with scale parameter\n    `sigma`.\n","base.dists.rayleigh.logpdf":"\nbase.dists.rayleigh.logpdf( x:number, sigma:number )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    Rayleigh distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.logpdf.factory":"\nbase.dists.rayleigh.logpdf.factory( sigma:number )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.mean":"\nbase.dists.rayleigh.mean( σ:number )\n    Returns the expected value of a Rayleigh distribution.\n","base.dists.rayleigh.median":"\nbase.dists.rayleigh.median( σ:number )\n    Returns the median of a Rayleigh distribution.\n","base.dists.rayleigh.mgf":"\nbase.dists.rayleigh.mgf( t:number, sigma:number )\n    Evaluates the moment-generating function (MGF) for a Rayleigh distribution\n    with scale parameter `sigma` at a value `t`.\n","base.dists.rayleigh.mgf.factory":"\nbase.dists.rayleigh.mgf.factory( sigma:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.mode":"\nbase.dists.rayleigh.mode( σ:number )\n    Returns the mode of a Rayleigh distribution.\n","base.dists.rayleigh.pdf":"\nbase.dists.rayleigh.pdf( x:number, sigma:number )\n    Evaluates the probability density function (PDF) for a Rayleigh\n    distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.pdf.factory":"\nbase.dists.rayleigh.pdf.factory( sigma:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.quantile":"\nbase.dists.rayleigh.quantile( p:number, sigma:number )\n    Evaluates the quantile function for a Rayleigh distribution with scale\n    parameter `sigma` at a probability `p`.\n","base.dists.rayleigh.quantile.factory":"\nbase.dists.rayleigh.quantile.factory( sigma:number )\n    Returns a function for evaluating the quantile function of a Rayleigh\n    distribution with scale parameter `sigma`.\n","base.dists.rayleigh.Rayleigh":"\nbase.dists.rayleigh.Rayleigh( [σ:number] )\n    Returns a Rayleigh distribution object.\n","base.dists.rayleigh.skewness":"\nbase.dists.rayleigh.skewness( σ:number )\n    Returns the skewness of a Rayleigh distribution.\n","base.dists.rayleigh.stdev":"\nbase.dists.rayleigh.stdev( σ:number )\n    Returns the standard deviation of a Rayleigh distribution.\n","base.dists.rayleigh.variance":"\nbase.dists.rayleigh.variance( σ:number )\n    Returns the variance of a Rayleigh distribution.\n","base.dists.signrank.cdf":"\nbase.dists.signrank.cdf( x:number, n:integer )\n    Evaluates the cumulative distribution function (CDF) for the distribution of\n    the Wilcoxon signed rank test statistic with `n` observations.\n","base.dists.signrank.cdf.factory":"\nbase.dists.signrank.cdf.factory( n:integer )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of the distribution of the Wilcoxon signed rank test statistic.\n","base.dists.signrank.pdf":"\nbase.dists.signrank.pdf( x:number, n:integer )\n    Evaluates the probability density function (PDF) for the distribution of\n    the Wilcoxon signed rank test statistic with `n` observations.\n","base.dists.signrank.pdf.factory":"\nbase.dists.signrank.pdf.factory( n:integer )\n    Returns a function for evaluating the probability density function (PDF)\n    of the distribution of the Wilcoxon signed rank test statistic.\n","base.dists.signrank.quantile":"\nbase.dists.signrank.quantile( p:number, n:integer )\n    Evaluates the quantile function for the Wilcoxon signed rank test statistic\n    with `n` observations at a probability `p`.\n","base.dists.signrank.quantile.factory":"\nbase.dists.signrank.quantile.factory( n:integer )\n    Returns a function for evaluating the quantile function of the Wilcoxon\n    signed rank test statistic with `n` observations.\n","base.dists.studentizedRange.cdf":"\nbase.dists.studentizedRange.cdf( x:number, r:number, v:number[, \n  nranges:integer] )\n    Evaluates the cumulative distribution function (CDF) of a studentized range\n    distribution.\n","base.dists.studentizedRange.cdf.factory":"\nbase.dists.studentizedRange.cdf.factory( r:number, v:number[, nranges:integer] )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a studentized range distribution.\n","base.dists.studentizedRange.quantile":"\nbase.dists.studentizedRange.quantile( p:number, r:number, v:number[, \n  nranges:integer] )\n    Evaluates the quantile function for a studentized range distribution.\n","base.dists.studentizedRange.quantile.factory":"\nbase.dists.studentizedRange.quantile.factory( r:number, v:number[, \n  nranges:integer] )\n    Returns a function for evaluating the quantile function of a studentized\n    range distribution.\n","base.dists.t.cdf":"\nbase.dists.t.cdf( x:number, v:number )\n    Evaluates the cumulative distribution function (CDF) for a Student's t\n    distribution with degrees of freedom `v` at a value `x`.\n","base.dists.t.cdf.factory":"\nbase.dists.t.cdf.factory( v:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Student's t distribution with degrees of freedom `v`.\n","base.dists.t.entropy":"\nbase.dists.t.entropy( v:number )\n    Returns the differential entropy of a Student's t distribution.\n","base.dists.t.kurtosis":"\nbase.dists.t.kurtosis( v:number )\n    Returns the excess kurtosis of a Student's t distribution.\n","base.dists.t.logcdf":"\nbase.dists.t.logcdf( x:number, v:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a Student's t distribution with degrees of freedom `v` at a value\n    `x`.\n","base.dists.t.logcdf.factory":"\nbase.dists.t.logcdf.factory( v:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Student's t distribution with degrees of\n    freedom `v`.\n","base.dists.t.logpdf":"\nbase.dists.t.logpdf( x:number, v:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a Student's t distribution with degrees of freedom `v` at a value `x`.\n","base.dists.t.logpdf.factory":"\nbase.dists.t.logpdf.factory( v:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a Student's t distribution with degrees of\n    freedom `v`.\n","base.dists.t.mean":"\nbase.dists.t.mean( v:number )\n    Returns the expected value of a Student's t distribution.\n","base.dists.t.median":"\nbase.dists.t.median( v:number )\n    Returns the median of a Student's t distribution.\n","base.dists.t.mode":"\nbase.dists.t.mode( v:number )\n    Returns the mode of a Student's t distribution.\n","base.dists.t.pdf":"\nbase.dists.t.pdf( x:number, v:number )\n    Evaluates the probability density function (PDF) for a Student's t\n    distribution with degrees of freedom `v` at a value `x`.\n","base.dists.t.pdf.factory":"\nbase.dists.t.pdf.factory( v:number )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Student's t distribution with degrees of freedom `v`.\n","base.dists.t.quantile":"\nbase.dists.t.quantile( p:number, v:number )\n    Evaluates the quantile function for a Student's t distribution with degrees\n    of freedom `v` at a probability `p`.\n","base.dists.t.quantile.factory":"\nbase.dists.t.quantile.factory( v:number )\n    Returns a function for evaluating the quantile function of a Student's t\n    distribution with degrees of freedom `v`.\n","base.dists.t.skewness":"\nbase.dists.t.skewness( v:number )\n    Returns the skewness of a Student's t distribution.\n","base.dists.t.stdev":"\nbase.dists.t.stdev( v:number )\n    Returns the standard deviation of a Student's t distribution.\n","base.dists.t.T":"\nbase.dists.t.T( [v:number] )\n    Returns a Student's t distribution object.\n","base.dists.t.variance":"\nbase.dists.t.variance( v:number )\n    Returns the variance of a Student's t distribution.\n","base.dists.triangular.cdf":"\nbase.dists.triangular.cdf( x:number, a:number, b:number, c:number )\n    Evaluates the cumulative distribution function (CDF) for a triangular\n    distribution with minimum support `a`, maximum support `b`, and mode `c` at\n    a value `x`.\n","base.dists.triangular.cdf.factory":"\nbase.dists.triangular.cdf.factory( a:number, b:number, c:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a triangular distribution with minimum support `a`, maximum support `b`,\n    and mode `c`.\n","base.dists.triangular.entropy":"\nbase.dists.triangular.entropy( a:number, b:number, c:number )\n    Returns the differential entropy of a triangular distribution (in nats).\n","base.dists.triangular.kurtosis":"\nbase.dists.triangular.kurtosis( a:number, b:number, c:number )\n    Returns the excess kurtosis of a triangular distribution.\n","base.dists.triangular.logcdf":"\nbase.dists.triangular.logcdf( x:number, a:number, b:number, c:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a triangular distribution with minimum support `a`, maximum\n    support `b`, and mode `c` at a value `x`.\n","base.dists.triangular.logcdf.factory":"\nbase.dists.triangular.logcdf.factory( a:number, b:number, c:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a triangular distribution with minimum\n    support `a`, maximum support `b`, and mode `c`.\n","base.dists.triangular.logpdf":"\nbase.dists.triangular.logpdf( x:number, a:number, b:number, c:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a triangular distribution with minimum support `a`, maximum support `b`,\n    and mode `c` at a value `x`.\n","base.dists.triangular.logpdf.factory":"\nbase.dists.triangular.logpdf.factory( a:number, b:number, c:number )\n    Returns a function for evaluating the natural logarithm of the  probability\n    density function (PDF) of a triangular distribution with minimum support\n    `a`, maximum support `b`, and mode `c`.\n","base.dists.triangular.mean":"\nbase.dists.triangular.mean( a:number, b:number, c:number )\n    Returns the expected value of a triangular distribution.\n","base.dists.triangular.median":"\nbase.dists.triangular.median( a:number, b:number, c:number )\n    Returns the median of a triangular distribution.\n","base.dists.triangular.mgf":"\nbase.dists.triangular.mgf( t:number, a:number, b:number, c:number )\n    Evaluates the moment-generating function (MGF) for a triangular distribution\n    with minimum support `a`, maximum support `b`, and mode `c` at a value `t`.\n","base.dists.triangular.mgf.factory":"\nbase.dists.triangular.mgf.factory( a:number, b:number, c:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    triangular distribution with minimum support `a`, maximum support `b`, and\n    mode `c`.\n","base.dists.triangular.mode":"\nbase.dists.triangular.mode( a:number, b:number, c:number )\n    Returns the mode of a triangular distribution.\n","base.dists.triangular.pdf":"\nbase.dists.triangular.pdf( x:number, a:number, b:number, c:number )\n    Evaluates the probability density function (PDF) for a triangular\n    distribution with minimum support `a`, maximum support `b`, and mode `c` at\n    a value `x`.\n","base.dists.triangular.pdf.factory":"\nbase.dists.triangular.pdf.factory( a:number, b:number, c:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a triangular distribution with minimum support `a`, maximum support `b`, and\n    mode `c`.\n","base.dists.triangular.quantile":"\nbase.dists.triangular.quantile( p:number, a:number, b:number, c:number )\n    Evaluates the quantile function for a triangular distribution with minimum\n    support `a`, maximum support `b`, and mode `c` at a value `x`.\n","base.dists.triangular.quantile.factory":"\nbase.dists.triangular.quantile.factory( a:number, b:number, c:number )\n    Returns a function for evaluating the quantile function of a triangular\n    distribution with minimum support `a`, maximum support `b`, and mode `c`.\n","base.dists.triangular.skewness":"\nbase.dists.triangular.skewness( a:number, b:number, c:number )\n    Returns the skewness of a triangular distribution.\n","base.dists.triangular.stdev":"\nbase.dists.triangular.stdev( a:number, b:number, c:number )\n    Returns the standard deviation of a triangular distribution.\n","base.dists.triangular.Triangular":"\nbase.dists.triangular.Triangular( [a:number, b:number, c:number] )\n    Returns a triangular distribution object.\n","base.dists.triangular.variance":"\nbase.dists.triangular.variance( a:number, b:number, c:number )\n    Returns the variance of a triangular distribution.\n","base.dists.uniform.cdf":"\nbase.dists.uniform.cdf( x:number, a:number, b:number )\n    Evaluates the cumulative distribution function (CDF) for a uniform\n    distribution with minimum support `a` and maximum support `b` at a value\n    `x`.\n","base.dists.uniform.cdf.factory":"\nbase.dists.uniform.cdf.factory( a:number, b:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.entropy":"\nbase.dists.uniform.entropy( a:number, b:number )\n    Returns the differential entropy of a uniform distribution.\n","base.dists.uniform.kurtosis":"\nbase.dists.uniform.kurtosis( a:number, b:number )\n    Returns the excess kurtosis of a uniform distribution.\n","base.dists.uniform.logcdf":"\nbase.dists.uniform.logcdf( x:number, a:number, b:number )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    uniform distribution with minimum support `a` and maximum support `b` at a\n    value `x`.\n","base.dists.uniform.logcdf.factory":"\nbase.dists.uniform.logcdf.factory( a:number, b:number )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a uniform distribution with minimum support\n    `a` and maximum support `b`.\n","base.dists.uniform.logpdf":"\nbase.dists.uniform.logpdf( x:number, a:number, b:number )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    uniform distribution with minimum support `a` and maximum support `b` at a\n    value `x`.\n","base.dists.uniform.logpdf.factory":"\nbase.dists.uniform.logpdf.factory( a:number, b:number )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a uniform distribution with minimum support `a` and\n    maximum support `b`.\n","base.dists.uniform.mean":"\nbase.dists.uniform.mean( a:number, b:number )\n    Returns the expected value of a uniform distribution.\n","base.dists.uniform.median":"\nbase.dists.uniform.median( a:number, b:number )\n    Returns the median of a uniform distribution.\n","base.dists.uniform.mgf":"\nbase.dists.uniform.mgf( t:number, a:number, b:number )\n    Evaluates the moment-generating function (MGF) for a uniform\n    distribution with minimum support `a` and maximum support `b` at a value\n    `t`.\n","base.dists.uniform.mgf.factory":"\nbase.dists.uniform.mgf.factory( a:number, b:number )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.pdf":"\nbase.dists.uniform.pdf( x:number, a:number, b:number )\n    Evaluates the probability density function (PDF) for a uniform distribution\n    with minimum support `a` and maximum support `b` at a value `x`.\n","base.dists.uniform.pdf.factory":"\nbase.dists.uniform.pdf.factory( a:number, b:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.quantile":"\nbase.dists.uniform.quantile( p:number, a:number, b:number )\n    Evaluates the quantile function for a uniform distribution with minimum\n    support `a` and maximum support `b` at a probability `p`.\n","base.dists.uniform.quantile.factory":"\nbase.dists.uniform.quantile.factory( a:number, b:number )\n    Returns a function for evaluating the quantile function of a uniform\n    distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.skewness":"\nbase.dists.uniform.skewness( a:number, b:number )\n    Returns the skewness of a uniform distribution.\n","base.dists.uniform.stdev":"\nbase.dists.uniform.stdev( a:number, b:number )\n    Returns the standard deviation of a uniform distribution.\n","base.dists.uniform.Uniform":"\nbase.dists.uniform.Uniform( [a:number, b:number] )\n    Returns a uniform distribution object.\n","base.dists.uniform.variance":"\nbase.dists.uniform.variance( a:number, b:number )\n    Returns the variance of a uniform distribution.\n","base.dists.weibull.cdf":"\nbase.dists.weibull.cdf( x:number, k:number, λ:number )\n    Evaluates the cumulative distribution function (CDF) for a Weibull\n    distribution with shape parameter `k` and scale parameter `λ` at a value\n    `x`.\n","base.dists.weibull.cdf.factory":"\nbase.dists.weibull.cdf.factory( k:number, λ:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n","base.dists.weibull.entropy":"\nbase.dists.weibull.entropy( k:number, λ:number )\n    Returns the differential entropy of a Weibull distribution (in nats).\n","base.dists.weibull.kurtosis":"\nbase.dists.weibull.kurtosis( k:number, λ:number )\n    Returns the excess kurtosis of a Weibull distribution.\n","base.dists.weibull.logcdf":"\nbase.dists.weibull.logcdf( x:number, k:number, λ:number )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n    value `x`.\n","base.dists.weibull.logcdf.factory":"\nbase.dists.weibull.logcdf.factory( k:number, λ:number)\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Weibull distribution with scale parameter\n    `λ` and shape parameter `k`.\n","base.dists.weibull.logpdf":"\nbase.dists.weibull.logpdf( x:number, k:number, λ:number )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n    value `x`.\n","base.dists.weibull.logpdf.factory":"\nbase.dists.weibull.logpdf.factory( k:number, λ:number )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Weibull distribution with shape parameter `k` and scale\n    parameter `λ`.\n","base.dists.weibull.mean":"\nbase.dists.weibull.mean( k:number, λ:number )\n    Returns the expected value of a Weibull distribution.\n","base.dists.weibull.median":"\nbase.dists.weibull.median( k:number, λ:number )\n    Returns the median of a Weibull distribution.\n","base.dists.weibull.mgf":"\nbase.dists.weibull.mgf( x:number, k:number, λ:number )\n    Evaluates the moment-generating function (MGF) for a Weibull distribution\n    with shape parameter `k` and scale parameter `λ` at a value `t`.\n","base.dists.weibull.mgf.factory":"\nbase.dists.weibull.mgf.factory( k:number, λ:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Weibull distribution with shape parameter `k` and scale parameter `λ`.\n","base.dists.weibull.mode":"\nbase.dists.weibull.mode( k:number, λ:number )\n    Returns the mode of a Weibull distribution.\n","base.dists.weibull.pdf":"\nbase.dists.weibull.pdf( x:number, k:number, λ:number )\n    Evaluates the probability density function (PDF) for a Weibull distribution\n    with shape parameter `k` and scale parameter `λ` at a value `x`.\n","base.dists.weibull.pdf.factory":"\nbase.dists.weibull.pdf.factory( k:number, λ:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n","base.dists.weibull.quantile":"\nbase.dists.weibull.quantile( p:number, k:number, λ:number )\n    Evaluates the quantile function for a Weibull distribution with scale\n    parameter `k` and shape parameter `λ` at a probability `p`.\n","base.dists.weibull.quantile.factory":"\nbase.dists.weibull.quantile.factory( k:number, λ:number )\n    Returns a function for evaluating the quantile function of a Weibull\n    distribution with scale parameter `k` and shape parameter `λ`.\n","base.dists.weibull.skewness":"\nbase.dists.weibull.skewness( k:number, λ:number )\n    Returns the skewness of a Weibull distribution.\n","base.dists.weibull.stdev":"\nbase.dists.weibull.stdev( k:number, λ:number )\n    Returns the standard deviation of a Weibull distribution.\n","base.dists.weibull.variance":"\nbase.dists.weibull.variance( k:number, λ:number )\n    Returns the variance of a Weibull distribution.\n","base.dists.weibull.Weibull":"\nbase.dists.weibull.Weibull( [k:number, λ:number] )\n    Returns a Weibull distribution object.\n","base.ellipe":"\nbase.ellipe( m:number )\n    Computes the complete elliptic integral of the second kind.\n","base.ellipj":"\nbase.ellipj( u:number, m:number )\n    Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n    amplitude am.\n","base.ellipj.assign":"\nbase.ellipj.assign( u:number, m:number, out:Array|TypedArray|Object, \n  stride:integer, offset:integer )\n    Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n    amplitude am and assigns results to a provided output array.\n","base.ellipj.sn":"\nbase.ellipj.sn( u:number, m:number )\n    Computes the Jacobi elliptic function sn.\n","base.ellipj.cn":"\nbase.ellipj.cn( u:number, m:number )\n    Computes the Jacobi elliptic functions cn.\n","base.ellipj.dn":"\nbase.ellipj.dn( u:number, m:number )\n    Computes the Jacobi elliptic function dn.\n","base.ellipj.am":"\nbase.ellipj.am( u:number, m:number )\n    Computes the Jacobi amplitude am.\n","base.ellipk":"\nbase.ellipk( m:number )\n    Computes the complete elliptic integral of the first kind.\n","base.endsWith":"\nbase.endsWith( str:string, search:string, len:integer )\n    Tests if a string ends with the characters of another string.\n","base.epsdiff":"\nbase.epsdiff( x:number, y:number[, scale:string|Function] )\n    Computes the relative difference of two real numbers in units of double-\n    precision floating-point epsilon.\n","base.erf":"\nbase.erf( x:number )\n    Evaluates the error function.\n","base.erfc":"\nbase.erfc( x:number )\n    Evaluates the complementary error function.\n","base.erfcinv":"\nbase.erfcinv( x:number )\n    Evaluates the inverse complementary error function.\n","base.erfcx":"\nbase.erfcx( x:number )\n    Evaluates the scaled complementary error function.\n","base.erfinv":"\nbase.erfinv( x:number )\n    Evaluates the inverse error function.\n","base.eta":"\nbase.eta( s:number )\n    Evaluates the Dirichlet eta function for a double-precision\n    floating-point number `s`.\n","base.evalpoly":"\nbase.evalpoly( c:Array<number>, x:number )\n    Evaluates a polynomial using double-precision floating-point arithmetic.\n","base.evalpoly.factory":"\nbase.evalpoly.factory( c:Array<number> )\n    Returns a function for evaluating a polynomial using double-precision\n    floating-point arithmetic.\n","base.evalrational":"\nbase.evalrational( P:Array<number>, Q:Array<number>, x:number )\n    Evaluates a rational function using double-precision floating-point\n    arithmetic.\n","base.evalrational.factory":"\nbase.evalrational.factory( P:Array<number>, Q:Array<number> )\n    Returns a function for evaluating a rational function using double-precision\n    floating-point arithmetic.\n","base.exp":"\nbase.exp( x:number )\n    Evaluates the natural exponential function.\n","base.exp2":"\nbase.exp2( x:number )\n    Evaluates the base 2 exponential function.\n","base.exp10":"\nbase.exp10( x:number )\n    Evaluates the base 10 exponential function.\n","base.expit":"\nbase.expit( x:number )\n    Evaluates the standard logistic function.\n","base.expm1":"\nbase.expm1( x:number )\n    Computes `exp(x)-1`, where `exp(x)` is the natural exponential function.\n","base.expm1rel":"\nbase.expm1rel( x:number )\n    Relative error exponential.\n","base.exponent":"\nbase.exponent( x:number )\n    Returns an integer corresponding to the unbiased exponent of a double-\n    precision floating-point number.\n","base.exponentf":"\nbase.exponentf( x:float )\n    Returns an integer corresponding to the unbiased exponent of a single-\n    precision floating-point number.\n","base.factorial":"\nbase.factorial( x:number )\n    Evaluates the factorial of `x`.\n","base.factorial2":"\nbase.factorial2( n:number )\n    Evaluates the double factorial of `n`.\n","base.factorialln":"\nbase.factorialln( x:number )\n    Evaluates the natural logarithm of the factorial of `x`.\n","base.fallingFactorial":"\nbase.fallingFactorial( x:number, n:integer )\n    Computes the falling factorial of `x` and `n`.\n","base.fibonacci":"\nbase.fibonacci( n:integer )\n    Computes the nth Fibonacci number.\n","base.fibonacciIndex":"\nbase.fibonacciIndex( F:integer )\n    Computes the Fibonacci number index.\n","base.fibpoly":"\nbase.fibpoly( n:integer, x:number )\n    Evaluates a Fibonacci polynomial.\n","base.fibpoly.factory":"\nbase.fibpoly.factory( n:integer )\n    Returns a function for evaluating a Fibonacci polynomial.\n","base.firstCodePoint":"\nbase.firstCodePoint( str:string, n:integer )\n    Returns the first `n` Unicode code points of a string.\n","base.firstCodeUnit":"\nbase.firstCodeUnit( str:string, n:integer )\n    Returns the first `n` UTF-16 code units of a string.\n","base.firstGraphemeCluster":"\nbase.firstGraphemeCluster( str:string, n:integer )\n    Returns the first `n` grapheme clusters (i.e., user-perceived characters) of\n    a string.\n","base.flipsign":"\nbase.flipsign( x:number, y:number )\n    Returns a double-precision floating-point number with the magnitude of `x`\n    and the sign of `x*y`.\n","base.flipsignf":"\nbase.flipsignf( x:number, y:number )\n    Returns a single-precision floating-point number with the magnitude of `x`\n    and the sign of `x*y`.\n","base.float32ToInt32":"\nbase.float32ToInt32( x:float )\n    Converts a single-precision floating-point number to a signed 32-bit\n    integer.\n","base.float32ToUint32":"\nbase.float32ToUint32( x:float )\n    Converts a single-precision floating-point number to a unsigned 32-bit\n    integer.\n","base.float64ToFloat32":"\nbase.float64ToFloat32( x:number )\n    Converts a double-precision floating-point number to the nearest single-\n    precision floating-point number.\n","base.float64ToInt32":"\nbase.float64ToInt32( x:number )\n    Converts a double-precision floating-point number to a signed 32-bit\n    integer.\n","base.float64ToInt64Bytes":"\nbase.float64ToInt64Bytes( x:integer )\n    Converts an integer-valued double-precision floating-point number to a\n    signed 64-bit integer byte array according to host byte order (endianness).\n","base.float64ToInt64Bytes.assign":"\nbase.float64ToInt64Bytes.assign( x:integer, out:Array|TypedArray|Object, \n  stride:integer, offset:integer )\n    Converts an integer-valued double-precision floating-point number to a\n    signed 64-bit integer byte array according to host byte order (endianness)\n    and assigns results to a provided output array.\n","base.float64ToUint32":"\nbase.float64ToUint32( x:number )\n    Converts a double-precision floating-point number to a unsigned 32-bit\n    integer.\n","base.floor":"\nbase.floor( x:number )\n    Rounds a double-precision floating-point number toward negative infinity.\n","base.floor2":"\nbase.floor2( x:number )\n    Rounds a numeric value to the nearest power of two toward negative infinity.\n","base.floor10":"\nbase.floor10( x:number )\n    Rounds a numeric value to the nearest power of ten toward negative infinity.\n","base.floorb":"\nbase.floorb( x:number, n:integer, b:integer )\n    Rounds a numeric value to the nearest multiple of `b^n` toward negative\n    infinity.\n","base.floorf":"\nbase.floorf( x:number )\n    Rounds a single-precision floating-point number toward negative infinity.\n","base.floorn":"\nbase.floorn( x:number, n:integer )\n    Rounds a double-precision floating-point number to the nearest multiple of\n    `10^n` toward negative infinity.\n","base.floorsd":"\nbase.floorsd( x:number, n:integer, b:integer )\n    Rounds a numeric value to the nearest number toward negative infinity with\n    `n` significant figures.\n","base.forEachChar":"\nbase.forEachChar( str:string, clbk:Function[, thisArg:any] )\n    Invokes a function for each UTF-16 code unit in a string.\n","base.forEachCodePoint":"\nbase.forEachCodePoint( str:string, clbk:Function[, thisArg:any] )\n    Invokes a function for each Unicode code point in a string.\n","base.forEachCodePointRight":"\nbase.forEachCodePointRight( str:string, clbk:Function[, thisArg:any] )\n    Invokes a function for each Unicode code point in a string, iterating from\n    right to left.\n","base.forEachGraphemeCluster":"\nbase.forEachGraphemeCluster( str:string, clbk:Function[, thisArg:any] )\n    Invokes a function for each grapheme cluster (i.e., user-perceived\n    character) in a string.\n","base.forEachRight":"\nbase.forEachRight( str:string, clbk:Function[, thisArg:any] )\n    Invokes a function for each UTF-16 code unit in a string, iterating from\n    right to left.\n","base.formatInterpolate":"\nbase.formatInterpolate( tokens:Array, ...args:any )\n    Generate string from a token array by interpolating values.\n","base.formatTokenize":"\nbase.formatTokenize( str:string )\n    Tokenize a string into an array of string parts and format identifier\n    objects.\n","base.fresnel":"\nbase.fresnel( x:number )\n    Computes the Fresnel integrals S(x) and C(x).\n","base.fresnel.assign":"\nbase.fresnel.assign( x:number, out:Array<number>, stride:integer, \n  offset:integer )\n    Computes the Fresnel integrals S(x) and C(x) and assigns results to a\n    provided output array.\n","base.fresnelc":"\nbase.fresnelc( x:number )\n    Computes the Fresnel integral C(x).\n","base.fresnels":"\nbase.fresnels( x:number )\n    Computes the Fresnel integral S(x).\n","base.frexp":"\nbase.frexp( x:number )\n    Splits a double-precision floating-point number into a normalized fraction\n    and an integer power of two.\n","base.frexp.assign":"\nbase.frexp.assign( x:number, out:Array<number>, stride:integer, offset:integer )\n    Splits a double-precision floating-point number into a normalized fraction\n    and an integer power of two and assigns results to a provided output array.\n","base.fromBinaryString":"\nbase.fromBinaryString( bstr:string )\n    Creates a double-precision floating-point number from a literal bit\n    representation.\n","base.fromBinaryStringf":"\nbase.fromBinaryStringf( bstr:string )\n    Creates a single-precision floating-point number from an IEEE 754 literal\n    bit representation.\n","base.fromBinaryStringUint8":"\nbase.fromBinaryStringUint8( bstr:string )\n    Creates an unsigned 8-bit integer from a literal bit representation.\n","base.fromBinaryStringUint16":"\nbase.fromBinaryStringUint16( bstr:string )\n    Creates an unsigned 16-bit integer from a literal bit representation.\n","base.fromBinaryStringUint32":"\nbase.fromBinaryStringUint32( bstr:string )\n    Creates an unsigned 32-bit integer from a literal bit representation.\n","base.fromInt64Bytes":"\nbase.fromInt64Bytes( bytes:Array|TypedArray|Object, stride:integer, \n  offset:integer )\n    Converts a signed 64-bit integer byte array to a double-precision floating-\n    point number.\n","base.fromWordf":"\nbase.fromWordf( word:integer )\n    Creates a single-precision floating-point number from an unsigned integer\n    corresponding to an IEEE 754 binary representation.\n","base.fromWords":"\nbase.fromWords( high:integer, low:integer )\n    Creates a double-precision floating-point number from a higher order word\n    (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n","base.gamma":"\nbase.gamma( x:number )\n    Evaluates the gamma function.\n","base.gamma1pm1":"\nbase.gamma1pm1( x:number )\n    Computes `gamma(x+1) - 1` without cancellation errors, where `gamma(x)` is\n    the gamma function.\n","base.gammaDeltaRatio":"\nbase.gammaDeltaRatio( z:number, delta:number )\n    Computes the ratio of two gamma functions.\n","base.gammainc":"\nbase.gammainc( x:number, s:number[, regularized:boolean[, upper:boolean]] )\n    Computes the regularized incomplete gamma function.\n","base.gammaincinv":"\nbase.gammaincinv( p:number, a:number[, upper:boolean] )\n    Computes the inverse of the lower incomplete gamma function.\n","base.gammaLanczosSum":"\nbase.gammaLanczosSum( x:number )\n    Calculates the Lanczos sum for the approximation of the gamma function.\n","base.gammaLanczosSumExpGScaled":"\nbase.gammaLanczosSumExpGScaled( x:number )\n    Calculates the scaled Lanczos sum for the approximation of the gamma\n    function.\n","base.gammaln":"\nbase.gammaln( x:number )\n    Evaluates the natural logarithm of the gamma function.\n","base.gammasgn":"\nbase.gammasgn( x:number )\n    Computes the sign of the gamma function.\n","base.gcd":"\nbase.gcd( a:integer, b:integer )\n    Computes the greatest common divisor (gcd).\n","base.getHighWord":"\nbase.getHighWord( x:number )\n    Returns an unsigned 32-bit integer corresponding to the more significant 32\n    bits of a double-precision floating-point number.\n","base.getLowWord":"\nbase.getLowWord( x:number )\n    Returns an unsigned 32-bit integer corresponding to the less significant 32\n    bits of a double-precision floating-point number.\n","base.hacovercos":"\nbase.hacovercos( x:number )\n    Computes the half-value coversed cosine.\n","base.hacoversin":"\nbase.hacoversin( x:number )\n    Computes the half-value coversed sine.\n","base.havercos":"\nbase.havercos( x:number )\n    Computes the half-value versed cosine.\n","base.haversin":"\nbase.haversin( x:number )\n    Computes the half-value versed sine.\n","base.headercase":"\nbase.headercase( str:string )\n    Converts a string to HTTP header case.\n","base.heaviside":"\nbase.heaviside( x:number[, continuity:string] )\n    Evaluates the Heaviside function.\n","base.hermitepoly":"\nbase.hermitepoly( n:integer, x:number )\n    Evaluates a physicist's Hermite polynomial.\n","base.hermitepoly.factory":"\nbase.hermitepoly.factory( n:integer )\n    Returns a function for evaluating a physicist's Hermite polynomial.\n","base.hypot":"\nbase.hypot( x:number, y:number )\n    Computes the hypotenuse avoiding overflow and underflow.\n","base.hypotf":"\nbase.hypotf( x:number, y:number )\n    Computes the hypotenuse avoiding overflow and underflow (single-precision).\n","base.identity":"\nbase.identity( x:number )\n    Evaluates the identity function for a double-precision floating-point number\n    `x`.\n","base.identityf":"\nbase.identityf( x:number )\n    Evaluates the identity function for a single-precision floating-point number\n    `x`.\n","base.imul":"\nbase.imul( a:integer, b:integer )\n    Performs C-like multiplication of two signed 32-bit integers.\n","base.imuldw":"\nbase.imuldw( a:integer, b:integer )\n    Multiplies two signed 32-bit integers and returns an array of two signed 32-\n    bit integers which represents the signed 64-bit integer product.\n","base.imuldw.assign":"\nbase.imuldw.assign( a:integer, b:integer, out:Array|TypedArray|Object, \n  stride:integer, offset:integer )\n    Multiplies two signed 32-bit integers and assigns results representing the\n    signed 64-bit integer product to a provided output array.\n","base.int2slice":"\nbase.int2slice( value:integer, max:integer, strict:boolean )\n    Converts an integer to a Slice object.\n","base.int32ToUint32":"\nbase.int32ToUint32( x:integer )\n    Converts a signed 32-bit integer to an unsigned 32-bit integer.\n","base.inv":"\nbase.inv( x:number )\n    Computes the multiplicative inverse of a double-precision floating-point\n    number `x`.\n","base.invcase":"\nbase.invcase( str:string )\n    Converts a string to inverse case.\n","base.invf":"\nbase.invf( x:number )\n    Computes the multiplicative inverse of a single-precision floating-point\n    number `x`.\n","base.isComposite":"\nbase.isComposite( x:number )\n    Tests if a number is composite.\n","base.isCoprime":"\nbase.isCoprime( a:number, b:number )\n    Tests if two numbers are coprime.\n","base.isEven":"\nbase.isEven( x:number )\n    Tests if a finite numeric value is an even number.\n","base.isEvenInt32":"\nbase.isEvenInt32( x:integer )\n    Tests if a 32-bit integer is even.\n","base.isFinite":"\nbase.isFinite( x:number )\n    Tests if a double-precision floating-point numeric value is finite.\n","base.isFinitef":"\nbase.isFinitef( x:number )\n    Tests if a single-precision floating-point numeric value is finite.\n","base.isInfinite":"\nbase.isInfinite( x:number )\n    Tests if a double-precision floating-point numeric value is infinite.\n","base.isInfinitef":"\nbase.isInfinitef( x:number )\n    Tests if a single-precision floating-point numeric value is infinite.\n","base.isInteger":"\nbase.isInteger( x:number )\n    Tests if a finite double-precision floating-point number is an integer.\n","base.isnan":"\nbase.isnan( x:number )\n     Tests if a double-precision floating-point numeric value is `NaN`.\n","base.isnanf":"\nbase.isnanf( x:number )\n     Tests if a single-precision floating-point numeric value is `NaN`.\n","base.isNegativeFinite":"\nbase.isNegativeFinite( x:number )\n    Tests if a double-precision floating-point numeric value is a negative\n    finite number.\n","base.isNegativeInteger":"\nbase.isNegativeInteger( x:number )\n    Tests if a finite double-precision floating-point number is a negative\n    integer.\n","base.isNegativeZero":"\nbase.isNegativeZero( x:number )\n    Tests if a double-precision floating-point numeric value is negative zero.\n","base.isNegativeZerof":"\nbase.isNegativeZerof( x:number )\n    Tests if a single-precision floating-point numeric value is negative zero.\n","base.isNonNegativeFinite":"\nbase.isNonNegativeFinite( x:number )\n    Tests if a double-precision floating-point numeric value is a nonnegative\n    finite number.\n","base.isNonNegativeInteger":"\nbase.isNonNegativeInteger( x:number )\n    Tests if a finite double-precision floating-point number is a nonnegative\n    integer.\n","base.isNonPositiveFinite":"\nbase.isNonPositiveFinite( x:number )\n    Tests if a double-precision floating-point numeric value is a nonpositive\n    finite number.\n","base.isNonPositiveInteger":"\nbase.isNonPositiveInteger( x:number )\n    Tests if a finite double-precision floating-point number is a nonpositive\n    integer.\n","base.isOdd":"\nbase.isOdd( x:number )\n    Tests if a finite numeric value is an odd number.\n","base.isOddInt32":"\nbase.isOddInt32( x:integer )\n    Tests if a 32-bit integer is odd.\n","base.isPositiveFinite":"\nbase.isPositiveFinite( x:number )\n    Tests if a double-precision floating-point numeric value is a positive\n    finite number.\n","base.isPositiveInteger":"\nbase.isPositiveInteger( x:number )\n    Tests if a finite double-precision floating-point number is a positive\n    integer.\n","base.isPositiveZero":"\nbase.isPositiveZero( x:number )\n    Tests if a double-precision floating-point numeric value is positive zero.\n","base.isPositiveZerof":"\nbase.isPositiveZerof( x:number )\n    Tests if a single-precision floating-point numeric value is positive zero.\n","base.isPow2Uint32":"\nbase.isPow2Uint32( x:integer )\n    Tests whether an unsigned integer is a power of 2.\n","base.isPrime":"\nbase.isPrime( x:number )\n    Tests if a number is prime.\n","base.isProbability":"\nbase.isProbability( x:number )\n    Tests if a double-precision floating-point number value is a probability.\n","base.isSafeInteger":"\nbase.isSafeInteger( x:number )\n    Tests if a finite double-precision floating-point number is a safe integer.\n","base.kebabcase":"\nbase.kebabcase( str:string )\n    Converts a string to kebab case.\n","base.kernelBetainc":"\nbase.kernelBetainc( x:number, a:number, b:number, regularized:boolean, \n  upper:boolean )\n    Computes the kernel function for the regularized incomplete beta function.\n","base.kernelBetainc.assign":"\nbase.kernelBetainc.assign( x:number, a:number, b:number, regularized:boolean, \n  upper:boolean, out:Array|TypedArray|Object, stride:integer, offset:integer )\n    Computes the kernel function for the regularized incomplete beta function.\n","base.kernelBetaincinv":"\nbase.kernelBetaincinv( a:number, b:number, p:number, q:number )\n    Computes the inverse of the lower incomplete beta function.\n","base.kernelCos":"\nbase.kernelCos( x:number, y:number )\n    Computes the cosine of a double-precision floating-point number on the\n    interval [-π/4, π/4].\n","base.kernelLog1p":"\nbase.kernelLog1p( f:number )\n    Computes `log(1+f) - f` for `1+f` in ~[sqrt(2)/2, sqrt(2)].\n","base.kernelSin":"\nbase.kernelSin( x:number, y:number )\n    Computes the sine of a double-precision floating-point number on [-π/4,π/4].\n","base.kernelTan":"\nbase.kernelTan( x:number, y:number, k:integer )\n    Computes the tangent of a double-precision floating-point number on the\n    interval [-π/4, π/4].\n","base.kroneckerDelta":"\nbase.kroneckerDelta( i:number, j:number )\n    Evaluates the Kronecker delta.\n","base.kroneckerDeltaf":"\nbase.kroneckerDeltaf( i:number, j:number )\n    Evaluates the Kronecker delta (single-precision).\n","base.labs":"\nbase.labs( x:integer )\n    Computes an absolute value of a signed 32-bit integer in two's complement\n    format.\n","base.last":"\nbase.last( str:string, n:integer )\n    Returns the last `n` UTF-16 code units of a string.\n","base.lastCodePoint":"\nbase.lastCodePoint( str:string, n:integer )\n    Returns the last `n` Unicode code points of a string.\n","base.lastGraphemeCluster":"\nbase.lastGraphemeCluster( str:string, n:integer )\n    Returns the last `n` grapheme clusters (i.e., user-perceived characters) of\n    a string.\n","base.lcm":"\nbase.lcm( a:integer, b:integer )\n    Computes the least common multiple (lcm).\n","base.ldexp":"\nbase.ldexp( frac:number, exp:number )\n    Multiplies a double-precision floating-point number by an integer power of\n    two; i.e., `x = frac * 2^exp`.\n","base.leftPad":"\nbase.leftPad( str:string, len:integer, pad:string )\n    Left pads a string such that the padded string has a length of at least\n    `len`.\n","base.leftTrim":"\nbase.leftTrim( str:string )\n    Trims whitespace from the beginning of a string.\n","base.ln":"\nbase.ln( x:number )\n    Evaluates the natural logarithm of a double-precision floating-point number.\n","base.log":"\nbase.log( x:number, b:number )\n    Computes the base `b` logarithm of a double-precision floating-point number.\n","base.log1mexp":"\nbase.log1mexp( x:number )\n    Evaluates the natural logarithm of `1-exp(-|x|)`.\n","base.log1p":"\nbase.log1p( x:number )\n    Evaluates the natural logarithm of `1+x`.\n","base.log1pexp":"\nbase.log1pexp( x:number )\n    Evaluates the natural logarithm of `1+exp(x)`.\n","base.log1pmx":"\nbase.log1pmx( x:number )\n    Evaluates `ln(1+x) - x`.\n","base.log2":"\nbase.log2( x:number )\n    Evaluates the binary logarithm (base two).\n","base.log10":"\nbase.log10( x:number )\n    Evaluates the common logarithm (base 10).\n","base.logaddexp":"\nbase.logaddexp( x:number, y:number )\n    Computes the natural logarithm of `exp(x) + exp(y)`.\n","base.logit":"\nbase.logit( p:number )\n    Evaluates the logit function.\n","base.lowercase":"\nbase.lowercase( str:string )\n    Converts a string to lowercase.\n","base.lucas":"\nbase.lucas( n:integer )\n    Computes the nth Lucas number.\n","base.lucaspoly":"\nbase.lucaspoly( n:integer, x:number )\n    Evaluates a Lucas polynomial.\n","base.lucaspoly.factory":"\nbase.lucaspoly.factory( n:integer )\n    Returns a function for evaluating a Lucas polynomial.\n","base.max":"\nbase.max( x:number, y:number )\n    Returns the maximum value.\n","base.maxabs":"\nbase.maxabs( x:number, y:number )\n    Returns the maximum absolute value.\n","base.maxabsn":"\nbase.maxabsn( [x:number[, y:number[, ...args:number]]] )\n    Returns the maximum absolute value.\n","base.maxn":"\nbase.maxn( [x:number[, y:number[, ...args:number]]] )\n    Returns the maximum value.\n","base.min":"\nbase.min( x:number, y:number )\n    Returns the minimum value.\n","base.minabs":"\nbase.minabs( x:number, y:number )\n    Returns the minimum absolute value.\n","base.minabsn":"\nbase.minabsn( [x:number[, y:number[, ...args:number]]] )\n    Returns the minimum absolute value.\n","base.minmax":"\nbase.minmax( x:number, y:number )\n    Returns the minimum and maximum values.\n","base.minmax.assign":"\nbase.minmax.assign( x:number, y:number, out:Array|TypedArray|Object, \n  stride:integer, offset:integer )\n    Returns the minimum and maximum values and assigns results to a provided\n    output array.\n","base.minmaxabs":"\nbase.minmaxabs( x:number, y:number )\n    Returns the minimum and maximum absolute values.\n","base.minmaxabs.assign":"\nbase.minmaxabs.assign( x:number, y:number, out:Array|TypedArray|Object, \n  stride:integer, offset:integer )\n    Returns the minimum and maximum absolute values.\n","base.minmaxabsn":"\nbase.minmaxabsn( [x:number[, y:number[, ...args:number]]] )\n    Returns the minimum and maximum absolute values.\n","base.minmaxabsn.assign":"\nbase.minmaxabsn.assign( [x:number[, y:number[, ...args:number]]], \n  out:Array|TypedArray|Object, stride:integer, offset:integer )\n    Returns the minimum and maximum absolute values.\n","base.minmaxn":"\nbase.minmaxn( [x:number[, y:number[, ...args:number]]] )\n    Returns the minimum and maximum values.\n","base.minmaxn.assign":"\nbase.minmaxn.assign( [x:number[, y:number[, ...args:number]]], \n  out:Array|TypedArray|Object, stride:integer, offset:integer )\n    Returns the minimum and maximum values and assigns results to a provided\n    output array.\n","base.minn":"\nbase.minn( [x:number[, y:number[, ...args:number]]] )\n    Returns the minimum value.\n","base.modf":"\nbase.modf( x:number )\n    Decomposes a double-precision floating-point number into integral and\n    fractional parts, each having the same type and sign as the input value.\n","base.modf.assign":"\nbase.modf.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n  offset:integer )\n    Decomposes a double-precision floating-point number into integral and\n    fractional parts, each having the same type and sign as the input value,\n    and assigns results to a provided output array.\n","base.mul":"\nbase.mul( x:number, y:number )\n    Multiplies two double-precision floating-point numbers `x` and `y`.\n","base.mulf":"\nbase.mulf( x:number, y:number )\n    Multiplies two single-precision floating-point numbers `x` and `y`.\n","base.ndarray":"\nbase.ndarray( dtype:string, buffer:ArrayLikeObject|TypedArray|Buffer, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  offset:integer, order:string )\n    Returns an ndarray.\n","base.ndarray.prototype.byteLength":"\nbase.ndarray.prototype.byteLength\n    Size (in bytes) of the array (if known).\n","base.ndarray.prototype.BYTES_PER_ELEMENT":"\nbase.ndarray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element (if known).\n","base.ndarray.prototype.data":"\nbase.ndarray.prototype.data\n    Pointer to the underlying data buffer.\n","base.ndarray.prototype.dtype":"\nbase.ndarray.prototype.dtype\n    Underlying data type.\n","base.ndarray.prototype.flags":"\nbase.ndarray.prototype.flags\n    Meta information, such as information concerning the memory layout of the\n    array.\n","base.ndarray.prototype.length":"\nbase.ndarray.prototype.length\n    Length of the array (i.e., number of elements).\n","base.ndarray.prototype.ndims":"\nbase.ndarray.prototype.ndims\n    Number of dimensions.\n","base.ndarray.prototype.offset":"\nbase.ndarray.prototype.offset\n    Index offset which specifies the buffer index at which to start iterating\n    over array elements.\n","base.ndarray.prototype.order: string":"\nbase.ndarray.prototype.order: string\n    Array order.\n","base.ndarray.prototype.shape":"\nbase.ndarray.prototype.shape\n    Array shape.\n","base.ndarray.prototype.strides":"\nbase.ndarray.prototype.strides\n    Index strides which specify how to access data along corresponding array\n    dimensions.\n","base.ndarray.prototype.get":"\nbase.ndarray.prototype.get( ...idx:integer )\n    Returns an array element specified according to provided subscripts.\n","base.ndarray.prototype.iget":"\nbase.ndarray.prototype.iget( idx:integer )\n    Returns an array element located at a specified linear index.\n","base.ndarray.prototype.set":"\nbase.ndarray.prototype.set( ...idx:integer, v:any )\n    Sets an array element specified according to provided subscripts.\n","base.ndarray.prototype.iset":"\nbase.ndarray.prototype.iset( idx:integer, v:any )\n    Sets an array element located at a specified linear index.\n","base.ndarray.prototype.toString":"\nbase.ndarray.prototype.toString()\n    Serializes an ndarray as a string.\n","base.ndarray.prototype.toJSON":"\nbase.ndarray.prototype.toJSON()\n    Serializes an ndarray as a JSON object.\n","base.ndarrayUnary":"\nbase.ndarrayUnary( arrays:ArrayLikeObject<ndarray>, fcn:Function )\n    Applies a unary callback to elements in an input ndarray and assigns results\n    to elements in an output ndarray.\n","base.ndzeros":"\nbase.ndzeros( dtype:string, shape:ArrayLikeObject<integer>, order:string )\n    Returns a zero-filled ndarray having a specified shape and data type.\n","base.ndzerosLike":"\nbase.ndzerosLike( x:ndarray )\n    Returns a zero-filled ndarray having the same shape and data type as a\n    provided input ndarray.\n","base.negafibonacci":"\nbase.negafibonacci( n:integer )\n    Computes the nth negaFibonacci number.\n","base.negalucas":"\nbase.negalucas( n:integer )\n    Computes the nth negaLucas number.\n","base.nonfibonacci":"\nbase.nonfibonacci( n:integer )\n    Computes the nth non-Fibonacci number.\n","base.normalize":"\nbase.normalize( x:number )\n    Returns a normal number and exponent satisfying `x = y * 2^exp` as an array.\n","base.normalize.assign":"\nbase.normalize.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n  offset:integer )\n    Returns a normal number and exponent satisfying `x = y * 2^exp` and assigns\n    results to a provided output array.\n","base.normalizef":"\nbase.normalizef( x:float )\n    Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` as\n    an array.\n","base.normalizef.assign":"\nbase.normalizef.assign( x:float, out:Array|TypedArray|Object, stride:integer, \n  offset:integer )\n    Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` and\n    assigns results to a provided output array.\n","base.normalizeSlice":"\nbase.normalizeSlice( slice:Slice, len:integer, strict:boolean )\n    Returns a normalized Slice object.\n","base.normhermitepoly":"\nbase.normhermitepoly( n:integer, x:number )\n    Evaluates a normalized Hermite polynomial using double-precision floating-\n    point arithmetic.\n","base.normhermitepoly.factory":"\nbase.normhermitepoly.factory( n:integer )\n    Returns a function for evaluating a normalized Hermite polynomial using\n    double-precision floating-point arithmetic.\n","base.pascalcase":"\nbase.pascalcase( str:string )\n    Converts a string to Pascal case.\n","base.pdiff":"\nbase.pdiff( x:number, y:number )\n    Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n    returns `0`.\n","base.pdifff":"\nbase.pdifff( x:number, y:number )\n    Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n    returns `0`.\n","base.percentEncode":"\nbase.percentEncode( str:string )\n    Percent-encodes a UTF-16 encoded string according to RFC 3986.\n","base.polygamma":"\nbase.polygamma( n:integer, x:number )\n    Evaluates the polygamma function of order `n`; i.e., the (n+1)th derivative\n    of the natural logarithm of the gamma function.\n","base.pow":"\nbase.pow( b:number, x:number )\n    Evaluates the exponential function `bˣ`.\n","base.powm1":"\nbase.powm1( b:number, x:number )\n    Evaluates `bˣ - 1`.\n","base.rad2deg":"\nbase.rad2deg( x:number )\n    Converts an angle from radians to degrees.\n","base.rad2degf":"\nbase.rad2degf( x:number )\n    Converts an angle from radians to degrees (single-precision).\n","base.ramp":"\nbase.ramp( x:number )\n    Evaluates the ramp function.\n","base.rampf":"\nbase.rampf( x:number )\n    Evaluates the ramp function (single-precision).\n","base.random.arcsine":"\nbase.random.arcsine( a:number, b:number )\n    Returns a pseudorandom number drawn from an arcsine distribution.\n","base.random.arcsine.factory":"\nbase.random.arcsine.factory( [a:number, b:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an arcsine distribution.\n","base.random.arcsine.NAME":"\nbase.random.arcsine.NAME\n    Generator name.\n","base.random.arcsine.PRNG":"\nbase.random.arcsine.PRNG\n    Underlying pseudorandom number generator.\n","base.random.arcsine.seed":"\nbase.random.arcsine.seed\n    Pseudorandom number generator seed.\n","base.random.arcsine.seedLength":"\nbase.random.arcsine.seedLength\n    Length of generator seed.\n","base.random.arcsine.state":"\nbase.random.arcsine.state\n    Generator state.\n","base.random.arcsine.stateLength":"\nbase.random.arcsine.stateLength\n    Length of generator state.\n","base.random.arcsine.byteLength":"\nbase.random.arcsine.byteLength\n    Size (in bytes) of generator state.\n","base.random.arcsine.toJSON":"\nbase.random.arcsine.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.bernoulli":"\nbase.random.bernoulli( p:number )\n    Returns a pseudorandom number drawn from a Bernoulli distribution.\n","base.random.bernoulli.factory":"\nbase.random.bernoulli.factory( [p:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Bernoulli distribution.\n","base.random.bernoulli.NAME":"\nbase.random.bernoulli.NAME\n    Generator name.\n","base.random.bernoulli.PRNG":"\nbase.random.bernoulli.PRNG\n    Underlying pseudorandom number generator.\n","base.random.bernoulli.seed":"\nbase.random.bernoulli.seed\n    Pseudorandom number generator seed.\n","base.random.bernoulli.seedLength":"\nbase.random.bernoulli.seedLength\n    Length of generator seed.\n","base.random.bernoulli.state":"\nbase.random.bernoulli.state\n    Generator state.\n","base.random.bernoulli.stateLength":"\nbase.random.bernoulli.stateLength\n    Length of generator state.\n","base.random.bernoulli.byteLength":"\nbase.random.bernoulli.byteLength\n    Size (in bytes) of generator state.\n","base.random.bernoulli.toJSON":"\nbase.random.bernoulli.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.beta":"\nbase.random.beta( α:number, β:number )\n    Returns a pseudorandom number drawn from a beta distribution.\n","base.random.beta.factory":"\nbase.random.beta.factory( [α:number, β:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a beta distribution.\n","base.random.beta.NAME":"\nbase.random.beta.NAME\n    Generator name.\n","base.random.beta.PRNG":"\nbase.random.beta.PRNG\n    Underlying pseudorandom number generator.\n","base.random.beta.seed":"\nbase.random.beta.seed\n    Pseudorandom number generator seed.\n","base.random.beta.seedLength":"\nbase.random.beta.seedLength\n    Length of generator seed.\n","base.random.beta.state":"\nbase.random.beta.state\n    Generator state.\n","base.random.beta.stateLength":"\nbase.random.beta.stateLength\n    Length of generator state.\n","base.random.beta.byteLength":"\nbase.random.beta.byteLength\n    Size (in bytes) of generator state.\n","base.random.beta.toJSON":"\nbase.random.beta.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.betaprime":"\nbase.random.betaprime( α:number, β:number )\n    Returns a pseudorandom number drawn from a beta prime distribution.\n","base.random.betaprime.factory":"\nbase.random.betaprime.factory( [α:number, β:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a beta prime distribution.\n","base.random.betaprime.NAME":"\nbase.random.betaprime.NAME\n    Generator name.\n","base.random.betaprime.PRNG":"\nbase.random.betaprime.PRNG\n    Underlying pseudorandom number generator.\n","base.random.betaprime.seed":"\nbase.random.betaprime.seed\n    Pseudorandom number generator seed.\n","base.random.betaprime.seedLength":"\nbase.random.betaprime.seedLength\n    Length of generator seed.\n","base.random.betaprime.state":"\nbase.random.betaprime.state\n    Generator state.\n","base.random.betaprime.stateLength":"\nbase.random.betaprime.stateLength\n    Length of generator state.\n","base.random.betaprime.byteLength":"\nbase.random.betaprime.byteLength\n    Size (in bytes) of generator state.\n","base.random.betaprime.toJSON":"\nbase.random.betaprime.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.binomial":"\nbase.random.binomial( n:integer, p:number )\n    Returns a pseudorandom number drawn from a binomial distribution.\n","base.random.binomial.factory":"\nbase.random.binomial.factory( [n:integer, p:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a binomial distribution.\n","base.random.binomial.NAME":"\nbase.random.binomial.NAME\n    Generator name.\n","base.random.binomial.PRNG":"\nbase.random.binomial.PRNG\n    Underlying pseudorandom number generator.\n","base.random.binomial.seed":"\nbase.random.binomial.seed\n    Pseudorandom number generator seed.\n","base.random.binomial.seedLength":"\nbase.random.binomial.seedLength\n    Length of generator seed.\n","base.random.binomial.state":"\nbase.random.binomial.state\n    Generator state.\n","base.random.binomial.stateLength":"\nbase.random.binomial.stateLength\n    Length of generator state.\n","base.random.binomial.byteLength":"\nbase.random.binomial.byteLength\n    Size of generator state.\n","base.random.binomial.toJSON":"\nbase.random.binomial.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.boxMuller":"\nbase.random.boxMuller()\n    Returns a pseudorandom number drawn from a standard normal distribution.\n","base.random.boxMuller.factory":"\nbase.random.boxMuller.factory( [options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a standard normal distribution.\n","base.random.boxMuller.NAME":"\nbase.random.boxMuller.NAME\n    Generator name.\n","base.random.boxMuller.PRNG":"\nbase.random.boxMuller.PRNG\n    Underlying pseudorandom number generator.\n","base.random.boxMuller.seed":"\nbase.random.boxMuller.seed\n    Pseudorandom number generator seed.\n","base.random.boxMuller.seedLength":"\nbase.random.boxMuller.seedLength\n    Length of generator seed.\n","base.random.boxMuller.state":"\nbase.random.boxMuller.state\n    Generator state.\n","base.random.boxMuller.stateLength":"\nbase.random.boxMuller.stateLength\n    Length of generator state.\n","base.random.boxMuller.byteLength":"\nbase.random.boxMuller.byteLength\n    Size (in bytes) of generator state.\n","base.random.boxMuller.toJSON":"\nbase.random.boxMuller.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.cauchy":"\nbase.random.cauchy( x0:number, Ɣ:number )\n    Returns a pseudorandom number drawn from a Cauchy distribution.\n","base.random.cauchy.factory":"\nbase.random.cauchy.factory( [x0:number, Ɣ:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Cauchy distribution.\n","base.random.cauchy.NAME":"\nbase.random.cauchy.NAME\n    Generator name.\n","base.random.cauchy.PRNG":"\nbase.random.cauchy.PRNG\n    Underlying pseudorandom number generator.\n","base.random.cauchy.seed":"\nbase.random.cauchy.seed\n    Pseudorandom number generator seed.\n","base.random.cauchy.seedLength":"\nbase.random.cauchy.seedLength\n    Length of generator seed.\n","base.random.cauchy.state":"\nbase.random.cauchy.state\n    Generator state.\n","base.random.cauchy.stateLength":"\nbase.random.cauchy.stateLength\n    Length of generator state.\n","base.random.cauchy.byteLength":"\nbase.random.cauchy.byteLength\n    Size (in bytes) of generator state.\n","base.random.cauchy.toJSON":"\nbase.random.cauchy.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.chi":"\nbase.random.chi( k:number )\n    Returns a pseudorandom number drawn from a chi distribution.\n","base.random.chi.factory":"\nbase.random.chi.factory( [k:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a chi distribution.\n","base.random.chi.NAME":"\nbase.random.chi.NAME\n    Generator name.\n","base.random.chi.PRNG":"\nbase.random.chi.PRNG\n    Underlying pseudorandom number generator.\n","base.random.chi.seed":"\nbase.random.chi.seed\n    Pseudorandom number generator seed.\n","base.random.chi.seedLength":"\nbase.random.chi.seedLength\n    Length of generator seed.\n","base.random.chi.state":"\nbase.random.chi.state\n    Generator state.\n","base.random.chi.stateLength":"\nbase.random.chi.stateLength\n    Length of generator state.\n","base.random.chi.byteLength":"\nbase.random.chi.byteLength\n    Size (in bytes) of generator state.\n","base.random.chi.toJSON":"\nbase.random.chi.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.chisquare":"\nbase.random.chisquare( k:number )\n    Returns a pseudorandom number drawn from a chi-square distribution.\n","base.random.chisquare.factory":"\nbase.random.chisquare.factory( [k:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a chi-square distribution.\n","base.random.chisquare.NAME":"\nbase.random.chisquare.NAME\n    Generator name.\n","base.random.chisquare.PRNG":"\nbase.random.chisquare.PRNG\n    Underlying pseudorandom number generator.\n","base.random.chisquare.seed":"\nbase.random.chisquare.seed\n    Pseudorandom number generator seed.\n","base.random.chisquare.seedLength":"\nbase.random.chisquare.seedLength\n    Length of generator seed.\n","base.random.chisquare.state":"\nbase.random.chisquare.state\n    Generator state.\n","base.random.chisquare.stateLength":"\nbase.random.chisquare.stateLength\n    Length of generator state.\n","base.random.chisquare.byteLength":"\nbase.random.chisquare.byteLength\n    Size (in bytes) of generator state.\n","base.random.chisquare.toJSON":"\nbase.random.chisquare.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.cosine":"\nbase.random.cosine( μ:number, s:number )\n    Returns a pseudorandom number drawn from a raised cosine distribution.\n","base.random.cosine.factory":"\nbase.random.cosine.factory( [μ:number, s:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a raised cosine distribution.\n","base.random.cosine.NAME":"\nbase.random.cosine.NAME\n    Generator name.\n","base.random.cosine.PRNG":"\nbase.random.cosine.PRNG\n    Underlying pseudorandom number generator.\n","base.random.cosine.seed":"\nbase.random.cosine.seed\n    Pseudorandom number generator seed.\n","base.random.cosine.seedLength":"\nbase.random.cosine.seedLength\n    Length of generator seed.\n","base.random.cosine.state":"\nbase.random.cosine.state\n    Generator state.\n","base.random.cosine.stateLength":"\nbase.random.cosine.stateLength\n    Length of generator state.\n","base.random.cosine.byteLength":"\nbase.random.cosine.byteLength\n    Size (in bytes) of generator state.\n","base.random.cosine.toJSON":"\nbase.random.cosine.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.discreteUniform":"\nbase.random.discreteUniform( a:integer, b:integer )\n    Returns a pseudorandom number drawn from a discrete uniform distribution.\n","base.random.discreteUniform.factory":"\nbase.random.discreteUniform.factory( [a:integer, b:integer, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a discrete uniform distribution.\n","base.random.discreteUniform.NAME":"\nbase.random.discreteUniform.NAME\n    Generator name.\n","base.random.discreteUniform.PRNG":"\nbase.random.discreteUniform.PRNG\n    Underlying pseudorandom number generator.\n","base.random.discreteUniform.seed":"\nbase.random.discreteUniform.seed\n    Pseudorandom number generator seed.\n","base.random.discreteUniform.seedLength":"\nbase.random.discreteUniform.seedLength\n    Length of generator seed.\n","base.random.discreteUniform.state":"\nbase.random.discreteUniform.state\n    Generator state.\n","base.random.discreteUniform.stateLength":"\nbase.random.discreteUniform.stateLength\n    Length of generator state.\n","base.random.discreteUniform.byteLength":"\nbase.random.discreteUniform.byteLength\n    Size (in bytes) of generator state.\n","base.random.discreteUniform.toJSON":"\nbase.random.discreteUniform.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.erlang":"\nbase.random.erlang( k:integer, λ:number )\n    Returns a pseudorandom number drawn from an Erlang distribution.\n","base.random.erlang.factory":"\nbase.random.erlang.factory( [k:integer, λ:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an Erlang distribution.\n","base.random.erlang.NAME":"\nbase.random.erlang.NAME\n    Generator name.\n","base.random.erlang.PRNG":"\nbase.random.erlang.PRNG\n    Underlying pseudorandom number generator.\n","base.random.erlang.seed":"\nbase.random.erlang.seed\n    Pseudorandom number generator seed.\n","base.random.erlang.seedLength":"\nbase.random.erlang.seedLength\n    Length of generator seed.\n","base.random.erlang.state":"\nbase.random.erlang.state\n    Generator state.\n","base.random.erlang.stateLength":"\nbase.random.erlang.stateLength\n    Length of generator state.\n","base.random.erlang.byteLength":"\nbase.random.erlang.byteLength\n    Size (in bytes) of generator state.\n","base.random.erlang.toJSON":"\nbase.random.erlang.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.exponential":"\nbase.random.exponential( λ:number )\n    Returns a pseudorandom number drawn from an exponential distribution.\n","base.random.exponential.factory":"\nbase.random.exponential.factory( [λ:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an exponential distribution.\n","base.random.exponential.NAME":"\nbase.random.exponential.NAME\n    Generator name.\n","base.random.exponential.PRNG":"\nbase.random.exponential.PRNG\n    Underlying pseudorandom number generator.\n","base.random.exponential.seed":"\nbase.random.exponential.seed\n    Pseudorandom number generator seed.\n","base.random.exponential.seedLength":"\nbase.random.exponential.seedLength\n    Length of generator seed.\n","base.random.exponential.state":"\nbase.random.exponential.state\n    Generator state.\n","base.random.exponential.stateLength":"\nbase.random.exponential.stateLength\n    Length of generator state.\n","base.random.exponential.byteLength":"\nbase.random.exponential.byteLength\n    Size (in bytes) of generator state.\n","base.random.exponential.toJSON":"\nbase.random.exponential.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.f":"\nbase.random.f( d1:number, d2:number )\n    Returns a pseudorandom number drawn from an F distribution.\n","base.random.f.factory":"\nbase.random.f.factory( [d1:number, d2:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an F distribution.\n","base.random.f.NAME":"\nbase.random.f.NAME\n    Generator name.\n","base.random.f.PRNG":"\nbase.random.f.PRNG\n    Underlying pseudorandom number generator.\n","base.random.f.seed":"\nbase.random.f.seed\n    Pseudorandom number generator seed.\n","base.random.f.seedLength":"\nbase.random.f.seedLength\n    Length of generator seed.\n","base.random.f.state":"\nbase.random.f.state\n    Generator state.\n","base.random.f.stateLength":"\nbase.random.f.stateLength\n    Length of generator state.\n","base.random.f.byteLength":"\nbase.random.f.byteLength\n    Size (in bytes) of generator state.\n","base.random.f.toJSON":"\nbase.random.f.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.frechet":"\nbase.random.frechet( α:number, s:number, m:number )\n    Returns a pseudorandom number drawn from a Fréchet distribution.\n","base.random.frechet.factory":"\nbase.random.frechet.factory( [α:number, s:number, m:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a triangular distribution.\n","base.random.frechet.NAME":"\nbase.random.frechet.NAME\n    Generator name.\n","base.random.frechet.PRNG":"\nbase.random.frechet.PRNG\n    Underlying pseudorandom number generator.\n","base.random.frechet.seed":"\nbase.random.frechet.seed\n    Pseudorandom number generator seed.\n","base.random.frechet.seedLength":"\nbase.random.frechet.seedLength\n    Length of generator seed.\n","base.random.frechet.state":"\nbase.random.frechet.state\n    Generator state.\n","base.random.frechet.stateLength":"\nbase.random.frechet.stateLength\n    Length of generator state.\n","base.random.frechet.byteLength":"\nbase.random.frechet.byteLength\n    Size (in bytes) of generator state.\n","base.random.frechet.toJSON":"\nbase.random.frechet.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.gamma":"\nbase.random.gamma( α:number, β:number )\n    Returns a pseudorandom number drawn from a gamma distribution.\n","base.random.gamma.factory":"\nbase.random.gamma.factory( [α:number, β:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a gamma distribution.\n","base.random.gamma.NAME":"\nbase.random.gamma.NAME\n    Generator name.\n","base.random.gamma.PRNG":"\nbase.random.gamma.PRNG\n    Underlying pseudorandom number generator.\n","base.random.gamma.seed":"\nbase.random.gamma.seed\n    Pseudorandom number generator seed.\n","base.random.gamma.seedLength":"\nbase.random.gamma.seedLength\n    Length of generator seed.\n","base.random.gamma.state":"\nbase.random.gamma.state\n    Generator state.\n","base.random.gamma.stateLength":"\nbase.random.gamma.stateLength\n    Length of generator state.\n","base.random.gamma.byteLength":"\nbase.random.gamma.byteLength\n    Size of generator state.\n","base.random.gamma.toJSON":"\nbase.random.gamma.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.geometric":"\nbase.random.geometric( p:number )\n    Returns a pseudorandom number drawn from a geometric distribution.\n","base.random.geometric.factory":"\nbase.random.geometric.factory( [p:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a geometric distribution.\n","base.random.geometric.NAME":"\nbase.random.geometric.NAME\n    Generator name.\n","base.random.geometric.PRNG":"\nbase.random.geometric.PRNG\n    Underlying pseudorandom number generator.\n","base.random.geometric.seed":"\nbase.random.geometric.seed\n    Pseudorandom number generator seed.\n","base.random.geometric.seedLength":"\nbase.random.geometric.seedLength\n    Length of generator seed.\n","base.random.geometric.state":"\nbase.random.geometric.state\n    Generator state.\n","base.random.geometric.stateLength":"\nbase.random.geometric.stateLength\n    Length of generator state.\n","base.random.geometric.byteLength":"\nbase.random.geometric.byteLength\n    Size (in bytes) of generator state.\n","base.random.geometric.toJSON":"\nbase.random.geometric.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.gumbel":"\nbase.random.gumbel( μ:number, β:number )\n    Returns a pseudorandom number drawn from a Gumbel distribution.\n","base.random.gumbel.factory":"\nbase.random.gumbel.factory( [μ:number, β:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Gumbel distribution.\n","base.random.gumbel.NAME":"\nbase.random.gumbel.NAME\n    Generator name.\n","base.random.gumbel.PRNG":"\nbase.random.gumbel.PRNG\n    Underlying pseudorandom number generator.\n","base.random.gumbel.seed":"\nbase.random.gumbel.seed\n    Pseudorandom number generator seed.\n","base.random.gumbel.seedLength":"\nbase.random.gumbel.seedLength\n    Length of generator seed.\n","base.random.gumbel.state":"\nbase.random.gumbel.state\n    Generator state.\n","base.random.gumbel.stateLength":"\nbase.random.gumbel.stateLength\n    Length of generator state.\n","base.random.gumbel.byteLength":"\nbase.random.gumbel.byteLength\n    Size (in bytes) of generator state.\n","base.random.gumbel.toJSON":"\nbase.random.gumbel.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.hypergeometric":"\nbase.random.hypergeometric( N:integer, K:integer, n:integer )\n    Returns a pseudorandom number drawn from a hypergeometric distribution.\n","base.random.hypergeometric.factory":"\nbase.random.hypergeometric.factory( [N:integer, K:integer, n:integer, ]\n  [options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a hypergeometric distribution.\n","base.random.hypergeometric.NAME":"\nbase.random.hypergeometric.NAME\n    Generator name.\n","base.random.hypergeometric.PRNG":"\nbase.random.hypergeometric.PRNG\n    Underlying pseudorandom number generator.\n","base.random.hypergeometric.seed":"\nbase.random.hypergeometric.seed\n    Pseudorandom number generator seed.\n","base.random.hypergeometric.seedLength":"\nbase.random.hypergeometric.seedLength\n    Length of generator seed.\n","base.random.hypergeometric.state":"\nbase.random.hypergeometric.state\n    Generator state.\n","base.random.hypergeometric.stateLength":"\nbase.random.hypergeometric.stateLength\n    Length of generator state.\n","base.random.hypergeometric.byteLength":"\nbase.random.hypergeometric.byteLength\n    Size (in bytes) of generator state.\n","base.random.hypergeometric.toJSON":"\nbase.random.hypergeometric.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.improvedZiggurat":"\nbase.random.improvedZiggurat()\n    Returns a pseudorandom number drawn from a standard normal distribution.\n","base.random.improvedZiggurat.factory":"\nbase.random.improvedZiggurat.factory( [options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a standard normal distribution.\n","base.random.improvedZiggurat.NAME":"\nbase.random.improvedZiggurat.NAME\n    Generator name.\n","base.random.improvedZiggurat.PRNG":"\nbase.random.improvedZiggurat.PRNG\n    Underlying pseudorandom number generator.\n","base.random.improvedZiggurat.seed":"\nbase.random.improvedZiggurat.seed\n    Pseudorandom number generator seed.\n","base.random.improvedZiggurat.seedLength":"\nbase.random.improvedZiggurat.seedLength\n    Length of generator seed.\n","base.random.improvedZiggurat.state":"\nbase.random.improvedZiggurat.state\n    Generator state.\n","base.random.improvedZiggurat.stateLength":"\nbase.random.improvedZiggurat.stateLength\n    Length of generator state.\n","base.random.improvedZiggurat.byteLength":"\nbase.random.improvedZiggurat.byteLength\n    Size (in bytes) of generator state.\n","base.random.improvedZiggurat.toJSON":"\nbase.random.improvedZiggurat.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.invgamma":"\nbase.random.invgamma( α:number, β:number )\n    Returns a pseudorandom number drawn from an inverse gamma distribution.\n","base.random.invgamma.factory":"\nbase.random.invgamma.factory( [α:number, β:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an inverse gamma distribution.\n","base.random.invgamma.NAME":"\nbase.random.invgamma.NAME\n    Generator name.\n","base.random.invgamma.PRNG":"\nbase.random.invgamma.PRNG\n    Underlying pseudorandom number generator.\n","base.random.invgamma.seed":"\nbase.random.invgamma.seed\n    Pseudorandom number generator seed.\n","base.random.invgamma.seedLength":"\nbase.random.invgamma.seedLength\n    Length of generator seed.\n","base.random.invgamma.state":"\nbase.random.invgamma.state\n    Generator state.\n","base.random.invgamma.stateLength":"\nbase.random.invgamma.stateLength\n    Length of generator state.\n","base.random.invgamma.byteLength":"\nbase.random.invgamma.byteLength\n    Size of generator state.\n","base.random.invgamma.toJSON":"\nbase.random.invgamma.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.kumaraswamy":"\nbase.random.kumaraswamy( a:number, b:number )\n    Returns a pseudorandom number drawn from Kumaraswamy's double bounded\n    distribution.\n","base.random.kumaraswamy.factory":"\nbase.random.kumaraswamy.factory( [a:number, b:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from Kumaraswamy's double bounded distribution.\n","base.random.kumaraswamy.NAME":"\nbase.random.kumaraswamy.NAME\n    Generator name.\n","base.random.kumaraswamy.PRNG":"\nbase.random.kumaraswamy.PRNG\n    Underlying pseudorandom number generator.\n","base.random.kumaraswamy.seed":"\nbase.random.kumaraswamy.seed\n    Pseudorandom number generator seed.\n","base.random.kumaraswamy.seedLength":"\nbase.random.kumaraswamy.seedLength\n    Length of generator seed.\n","base.random.kumaraswamy.state":"\nbase.random.kumaraswamy.state\n    Generator state.\n","base.random.kumaraswamy.stateLength":"\nbase.random.kumaraswamy.stateLength\n    Length of generator state.\n","base.random.kumaraswamy.byteLength":"\nbase.random.kumaraswamy.byteLength\n    Size (in bytes) of generator state.\n","base.random.kumaraswamy.toJSON":"\nbase.random.kumaraswamy.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.laplace":"\nbase.random.laplace( μ:number, b:number )\n    Returns a pseudorandom number drawn from a Laplace distribution.\n","base.random.laplace.factory":"\nbase.random.laplace.factory( [μ:number, b:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Laplace distribution.\n","base.random.laplace.NAME":"\nbase.random.laplace.NAME\n    Generator name.\n","base.random.laplace.PRNG":"\nbase.random.laplace.PRNG\n    Underlying pseudorandom number generator.\n","base.random.laplace.seed":"\nbase.random.laplace.seed\n    Pseudorandom number generator seed.\n","base.random.laplace.seedLength":"\nbase.random.laplace.seedLength\n    Length of generator seed.\n","base.random.laplace.state":"\nbase.random.laplace.state\n    Generator state.\n","base.random.laplace.stateLength":"\nbase.random.laplace.stateLength\n    Length of generator state.\n","base.random.laplace.byteLength":"\nbase.random.laplace.byteLength\n    Size (in bytes) of generator state.\n","base.random.laplace.toJSON":"\nbase.random.laplace.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.levy":"\nbase.random.levy( μ:number, c:number )\n    Returns a pseudorandom number drawn from a Lévy distribution.\n","base.random.levy.factory":"\nbase.random.levy.factory( [μ:number, c:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Lévy distribution.\n","base.random.levy.NAME":"\nbase.random.levy.NAME\n    Generator name.\n","base.random.levy.PRNG":"\nbase.random.levy.PRNG\n    Underlying pseudorandom number generator.\n","base.random.levy.seed":"\nbase.random.levy.seed\n    Pseudorandom number generator seed.\n","base.random.levy.seedLength":"\nbase.random.levy.seedLength\n    Length of generator seed.\n","base.random.levy.state":"\nbase.random.levy.state\n    Generator state.\n","base.random.levy.stateLength":"\nbase.random.levy.stateLength\n    Length of generator state.\n","base.random.levy.byteLength":"\nbase.random.levy.byteLength\n    Size (in bytes) of generator state.\n","base.random.levy.toJSON":"\nbase.random.levy.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.logistic":"\nbase.random.logistic( μ:number, s:number )\n    Returns a pseudorandom number drawn from a logistic distribution.\n","base.random.logistic.factory":"\nbase.random.logistic.factory( [μ:number, s:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a logistic distribution.\n","base.random.logistic.NAME":"\nbase.random.logistic.NAME\n    Generator name.\n","base.random.logistic.PRNG":"\nbase.random.logistic.PRNG\n    Underlying pseudorandom number generator.\n","base.random.logistic.seed":"\nbase.random.logistic.seed\n    Pseudorandom number generator seed.\n","base.random.logistic.seedLength":"\nbase.random.logistic.seedLength\n    Length of generator seed.\n","base.random.logistic.state":"\nbase.random.logistic.state\n    Generator state.\n","base.random.logistic.stateLength":"\nbase.random.logistic.stateLength\n    Length of generator state.\n","base.random.logistic.byteLength":"\nbase.random.logistic.byteLength\n    Size (in bytes) of generator state.\n","base.random.logistic.toJSON":"\nbase.random.logistic.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.lognormal":"\nbase.random.lognormal( μ:number, σ:number )\n    Returns a pseudorandom number drawn from a lognormal distribution.\n","base.random.lognormal.factory":"\nbase.random.lognormal.factory( [μ:number, σ:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a lognormal distribution.\n","base.random.lognormal.NAME":"\nbase.random.lognormal.NAME\n    Generator name.\n","base.random.lognormal.PRNG":"\nbase.random.lognormal.PRNG\n    Underlying pseudorandom number generator.\n","base.random.lognormal.seed":"\nbase.random.lognormal.seed\n    Pseudorandom number generator seed.\n","base.random.lognormal.seedLength":"\nbase.random.lognormal.seedLength\n    Length of generator seed.\n","base.random.lognormal.state":"\nbase.random.lognormal.state\n    Generator state.\n","base.random.lognormal.stateLength":"\nbase.random.lognormal.stateLength\n    Length of generator state.\n","base.random.lognormal.byteLength":"\nbase.random.lognormal.byteLength\n    Size (in bytes) of generator state.\n","base.random.lognormal.toJSON":"\nbase.random.lognormal.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.minstd":"\nbase.random.minstd()\n    Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n","base.random.minstd.normalized":"\nbase.random.minstd.normalized()\n    Returns a pseudorandom number on the interval `[0,1)`.\n","base.random.minstd.factory":"\nbase.random.minstd.factory( [options:Object] )\n    Returns a linear congruential pseudorandom number generator (LCG).\n","base.random.minstd.NAME":"\nbase.random.minstd.NAME\n    Generator name.\n","base.random.minstd.MIN":"\nbase.random.minstd.MIN\n    Minimum possible value.\n","base.random.minstd.MAX":"\nbase.random.minstd.MAX\n    Maximum possible value.\n","base.random.minstd.seed":"\nbase.random.minstd.seed\n    Pseudorandom number generator seed.\n","base.random.minstd.seedLength":"\nbase.random.minstd.seedLength\n    Length of generator seed.\n","base.random.minstd.state":"\nbase.random.minstd.state\n    Generator state.\n","base.random.minstd.stateLength":"\nbase.random.minstd.stateLength\n    Length of generator state.\n","base.random.minstd.byteLength":"\nbase.random.minstd.byteLength\n    Size (in bytes) of generator state.\n","base.random.minstd.toJSON":"\nbase.random.minstd.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.minstdShuffle":"\nbase.random.minstdShuffle()\n    Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n","base.random.minstdShuffle.normalized":"\nbase.random.minstdShuffle.normalized()\n    Returns a pseudorandom number on the interval `[0,1)`.\n","base.random.minstdShuffle.factory":"\nbase.random.minstdShuffle.factory( [options:Object] )\n    Returns a linear congruential pseudorandom number generator (LCG) whose\n    output is shuffled.\n","base.random.minstdShuffle.NAME":"\nbase.random.minstdShuffle.NAME\n    Generator name.\n","base.random.minstdShuffle.MIN":"\nbase.random.minstdShuffle.MIN\n    Minimum possible value.\n","base.random.minstdShuffle.MAX":"\nbase.random.minstdShuffle.MAX\n    Maximum possible value.\n","base.random.minstdShuffle.seed":"\nbase.random.minstdShuffle.seed\n    Pseudorandom number generator seed.\n","base.random.minstdShuffle.seedLength":"\nbase.random.minstdShuffle.seedLength\n    Length of generator seed.\n","base.random.minstdShuffle.state":"\nbase.random.minstdShuffle.state\n    Generator state.\n","base.random.minstdShuffle.stateLength":"\nbase.random.minstdShuffle.stateLength\n    Length of generator state.\n","base.random.minstdShuffle.byteLength":"\nbase.random.minstdShuffle.byteLength\n    Size (in bytes) of generator state.\n","base.random.minstdShuffle.toJSON":"\nbase.random.minstdShuffle.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.mt19937":"\nbase.random.mt19937()\n    Returns a pseudorandom integer on the interval `[0, 4294967295]`.\n","base.random.mt19937.normalized":"\nbase.random.mt19937.normalized()\n    Returns a pseudorandom number on the interval `[0,1)` with 53-bit precision.\n","base.random.mt19937.factory":"\nbase.random.mt19937.factory( [options:Object] )\n    Returns a 32-bit Mersenne Twister pseudorandom number generator.\n","base.random.mt19937.NAME":"\nbase.random.mt19937.NAME\n    Generator name.\n","base.random.mt19937.MIN":"\nbase.random.mt19937.MIN\n    Minimum possible value.\n","base.random.mt19937.MAX":"\nbase.random.mt19937.MAX\n    Maximum possible value.\n","base.random.mt19937.seed":"\nbase.random.mt19937.seed\n    Pseudorandom number generator seed.\n","base.random.mt19937.seedLength":"\nbase.random.mt19937.seedLength\n    Length of generator seed.\n","base.random.mt19937.state":"\nbase.random.mt19937.state\n    Generator state.\n","base.random.mt19937.stateLength":"\nbase.random.mt19937.stateLength\n    Length of generator state.\n","base.random.mt19937.byteLength":"\nbase.random.mt19937.byteLength\n    Size (in bytes) of generator state.\n","base.random.mt19937.toJSON":"\nbase.random.mt19937.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.negativeBinomial":"\nbase.random.negativeBinomial( r:number, p:number )\n    Returns a pseudorandom number drawn from a negative binomial distribution.\n","base.random.negativeBinomial.factory":"\nbase.random.negativeBinomial.factory( [r:number, p:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a negative binomial distribution.\n","base.random.negativeBinomial.NAME":"\nbase.random.negativeBinomial.NAME\n    Generator name.\n","base.random.negativeBinomial.PRNG":"\nbase.random.negativeBinomial.PRNG\n    Underlying pseudorandom number generator.\n","base.random.negativeBinomial.seed":"\nbase.random.negativeBinomial.seed\n    Pseudorandom number generator seed.\n","base.random.negativeBinomial.seedLength":"\nbase.random.negativeBinomial.seedLength\n    Length of generator seed.\n","base.random.negativeBinomial.state":"\nbase.random.negativeBinomial.state\n    Generator state.\n","base.random.negativeBinomial.stateLength":"\nbase.random.negativeBinomial.stateLength\n    Length of generator state.\n","base.random.negativeBinomial.byteLength":"\nbase.random.negativeBinomial.byteLength\n    Size (in bytes) of generator state.\n","base.random.negativeBinomial.toJSON":"\nbase.random.negativeBinomial.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.normal":"\nbase.random.normal( μ:number, σ:number )\n    Returns a pseudorandom number drawn from a normal distribution.\n","base.random.normal.factory":"\nbase.random.normal.factory( [μ:number, σ:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a normal distribution.\n","base.random.normal.NAME":"\nbase.random.normal.NAME\n    Generator name.\n","base.random.normal.PRNG":"\nbase.random.normal.PRNG\n    Underlying pseudorandom number generator.\n","base.random.normal.seed":"\nbase.random.normal.seed\n    Pseudorandom number generator seed.\n","base.random.normal.seedLength":"\nbase.random.normal.seedLength\n    Length of generator seed.\n","base.random.normal.state":"\nbase.random.normal.state\n    Generator state.\n","base.random.normal.stateLength":"\nbase.random.normal.stateLength\n    Length of generator state.\n","base.random.normal.byteLength":"\nbase.random.normal.byteLength\n    Size of generator state.\n","base.random.normal.toJSON":"\nbase.random.normal.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.pareto1":"\nbase.random.pareto1( α:number, β:number )\n    Returns a pseudorandom number drawn from a Pareto (Type I) distribution.\n","base.random.pareto1.factory":"\nbase.random.pareto1.factory( [α:number, β:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Pareto (Type I) distribution.\n","base.random.pareto1.NAME":"\nbase.random.pareto1.NAME\n    Generator name.\n","base.random.pareto1.PRNG":"\nbase.random.pareto1.PRNG\n    Underlying pseudorandom number generator.\n","base.random.pareto1.seed":"\nbase.random.pareto1.seed\n    Pseudorandom number generator seed.\n","base.random.pareto1.seedLength":"\nbase.random.pareto1.seedLength\n    Length of generator seed.\n","base.random.pareto1.state":"\nbase.random.pareto1.state\n    Generator state.\n","base.random.pareto1.stateLength":"\nbase.random.pareto1.stateLength\n    Length of generator state.\n","base.random.pareto1.byteLength":"\nbase.random.pareto1.byteLength\n    Size (in bytes) of generator state.\n","base.random.pareto1.toJSON":"\nbase.random.pareto1.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.poisson":"\nbase.random.poisson( λ:number )\n    Returns a pseudorandom number drawn from a Poisson distribution.\n","base.random.poisson.factory":"\nbase.random.poisson.factory( [λ:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Poisson distribution.\n","base.random.poisson.NAME":"\nbase.random.poisson.NAME\n    Generator name.\n","base.random.poisson.PRNG":"\nbase.random.poisson.PRNG\n    Underlying pseudorandom number generator.\n","base.random.poisson.seed":"\nbase.random.poisson.seed\n    Pseudorandom number generator seed.\n","base.random.poisson.seedLength":"\nbase.random.poisson.seedLength\n    Length of generator seed.\n","base.random.poisson.state":"\nbase.random.poisson.state\n    Generator state.\n","base.random.poisson.stateLength":"\nbase.random.poisson.stateLength\n    Length of generator state.\n","base.random.poisson.byteLength":"\nbase.random.poisson.byteLength\n    Size (in bytes) of generator state.\n","base.random.poisson.toJSON":"\nbase.random.poisson.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.randi":"\nbase.random.randi()\n    Returns a pseudorandom number having an integer value.\n","base.random.randi.factory":"\nbase.random.randi.factory( [options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers having integer values.\n","base.random.randi.NAME":"\nbase.random.randi.NAME\n    Generator name.\n","base.random.randi.PRNG":"\nbase.random.randi.PRNG\n    Underlying pseudorandom number generator.\n","base.random.randi.MIN":"\nbase.random.randi.MIN\n    Minimum possible value (specific to underlying PRNG).\n","base.random.randi.MAX":"\nbase.random.randi.MAX\n    Maximum possible value (specific to underlying PRNG).\n","base.random.randi.seed":"\nbase.random.randi.seed\n    Pseudorandom number generator seed.\n","base.random.randi.seedLength":"\nbase.random.randi.seedLength\n    Length of generator seed.\n","base.random.randi.state":"\nbase.random.randi.state\n    Generator state.\n","base.random.randi.stateLength":"\nbase.random.randi.stateLength\n    Length of generator state.\n","base.random.randi.byteLength":"\nbase.random.randi.byteLength\n    Size (in bytes) of generator state.\n","base.random.randi.toJSON":"\nbase.random.randi.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.randn":"\nbase.random.randn()\n    Returns a pseudorandom number drawn from a standard normal distribution.\n","base.random.randn.factory":"\nbase.random.randn.factory( [options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a standard normal distribution.\n","base.random.randn.NAME":"\nbase.random.randn.NAME\n    Generator name.\n","base.random.randn.PRNG":"\nbase.random.randn.PRNG\n    Underlying pseudorandom number generator.\n","base.random.randn.seed":"\nbase.random.randn.seed\n    Pseudorandom number generator seed.\n","base.random.randn.seedLength":"\nbase.random.randn.seedLength\n    Length of generator seed.\n","base.random.randn.state":"\nbase.random.randn.state\n    Generator state.\n","base.random.randn.stateLength":"\nbase.random.randn.stateLength\n    Length of generator state.\n","base.random.randn.byteLength":"\nbase.random.randn.byteLength\n    Size (in bytes) of generator state.\n","base.random.randn.toJSON":"\nbase.random.randn.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.randu":"\nbase.random.randu()\n    Returns a pseudorandom number drawn from a uniform distribution.\n","base.random.randu.factory":"\nbase.random.randu.factory( [options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a uniform distribution.\n","base.random.randu.NAME":"\nbase.random.randu.NAME\n    Generator name.\n","base.random.randu.PRNG":"\nbase.random.randu.PRNG\n    Underlying pseudorandom number generator.\n","base.random.randu.MIN":"\nbase.random.randu.MIN\n    Minimum possible value (specific to underlying PRNG).\n","base.random.randu.MAX":"\nbase.random.randu.MAX\n    Maximum possible value (specific to underlying PRNG).\n","base.random.randu.seed":"\nbase.random.randu.seed\n    Pseudorandom number generator seed.\n","base.random.randu.seedLength":"\nbase.random.randu.seedLength\n    Length of generator seed.\n","base.random.randu.state":"\nbase.random.randu.state\n    Generator state.\n","base.random.randu.stateLength":"\nbase.random.randu.stateLength\n    Length of generator state.\n","base.random.randu.byteLength":"\nbase.random.randu.byteLength\n    Size (in bytes) of generator state.\n","base.random.randu.toJSON":"\nbase.random.randu.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.rayleigh":"\nbase.random.rayleigh( σ:number )\n    Returns a pseudorandom number drawn from a Rayleigh distribution.\n","base.random.rayleigh.factory":"\nbase.random.rayleigh.factory( [σ:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Rayleigh distribution.\n","base.random.rayleigh.NAME":"\nbase.random.rayleigh.NAME\n    Generator name.\n","base.random.rayleigh.PRNG":"\nbase.random.rayleigh.PRNG\n    Underlying pseudorandom number generator.\n","base.random.rayleigh.seed":"\nbase.random.rayleigh.seed\n    Pseudorandom number generator seed.\n","base.random.rayleigh.seedLength":"\nbase.random.rayleigh.seedLength\n    Length of generator seed.\n","base.random.rayleigh.state":"\nbase.random.rayleigh.state\n    Generator state.\n","base.random.rayleigh.stateLength":"\nbase.random.rayleigh.stateLength\n    Length of generator state.\n","base.random.rayleigh.byteLength":"\nbase.random.rayleigh.byteLength\n    Size (in bytes) of generator state.\n","base.random.rayleigh.toJSON":"\nbase.random.rayleigh.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.t":"\nbase.random.t( v:number )\n    Returns a pseudorandom number drawn from a Student's t distribution.\n","base.random.t.factory":"\nbase.random.t.factory( [v:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Student's t distribution.\n","base.random.t.NAME":"\nbase.random.t.NAME\n    Generator name.\n","base.random.t.PRNG":"\nbase.random.t.PRNG\n    Underlying pseudorandom number generator.\n","base.random.t.seed":"\nbase.random.t.seed\n    Pseudorandom number generator seed.\n","base.random.t.seedLength":"\nbase.random.t.seedLength\n    Length of generator seed.\n","base.random.t.state":"\nbase.random.t.state\n    Generator state.\n","base.random.t.stateLength":"\nbase.random.t.stateLength\n    Length of generator state.\n","base.random.t.byteLength":"\nbase.random.t.byteLength\n    Size (in bytes) of generator state.\n","base.random.t.toJSON":"\nbase.random.t.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.triangular":"\nbase.random.triangular( a:number, b:number, c:number )\n    Returns a pseudorandom number drawn from a triangular distribution.\n","base.random.triangular.factory":"\nbase.random.triangular.factory( [a:number, b:number, c:number, ]\n  [options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a triangular distribution.\n","base.random.triangular.NAME":"\nbase.random.triangular.NAME\n    Generator name.\n","base.random.triangular.PRNG":"\nbase.random.triangular.PRNG\n    Underlying pseudorandom number generator.\n","base.random.triangular.seed":"\nbase.random.triangular.seed\n    Pseudorandom number generator seed.\n","base.random.triangular.seedLength":"\nbase.random.triangular.seedLength\n    Length of generator seed.\n","base.random.triangular.state":"\nbase.random.triangular.state\n    Generator state.\n","base.random.triangular.stateLength":"\nbase.random.triangular.stateLength\n    Length of generator state.\n","base.random.triangular.byteLength":"\nbase.random.triangular.byteLength\n    Size (in bytes) of generator state.\n","base.random.triangular.toJSON":"\nbase.random.triangular.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.uniform":"\nbase.random.uniform( a:number, b:number )\n    Returns a pseudorandom number drawn from a continuous uniform distribution.\n","base.random.uniform.factory":"\nbase.random.uniform.factory( [a:number, b:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a continuous uniform distribution.\n","base.random.uniform.NAME":"\nbase.random.uniform.NAME\n    Generator name.\n","base.random.uniform.PRNG":"\nbase.random.uniform.PRNG\n    Underlying pseudorandom number generator.\n","base.random.uniform.seed":"\nbase.random.uniform.seed\n    Pseudorandom number generator seed.\n","base.random.uniform.seedLength":"\nbase.random.uniform.seedLength\n    Length of generator seed.\n","base.random.uniform.state":"\nbase.random.uniform.state\n    Generator state.\n","base.random.uniform.stateLength":"\nbase.random.uniform.stateLength\n    Length of generator state.\n","base.random.uniform.byteLength":"\nbase.random.uniform.byteLength\n    Size (in bytes) of generator state.\n","base.random.uniform.toJSON":"\nbase.random.uniform.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.weibull":"\nbase.random.weibull( k:number, λ:number )\n    Returns a pseudorandom number drawn from a Weibull distribution.\n","base.random.weibull.factory":"\nbase.random.weibull.factory( [k:number, λ:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Weibull distribution.\n","base.random.weibull.NAME":"\nbase.random.weibull.NAME\n    Generator name.\n","base.random.weibull.PRNG":"\nbase.random.weibull.PRNG\n    Underlying pseudorandom number generator.\n","base.random.weibull.seed":"\nbase.random.weibull.seed\n    Pseudorandom number generator seed.\n","base.random.weibull.seedLength":"\nbase.random.weibull.seedLength\n    Length of generator seed.\n","base.random.weibull.state":"\nbase.random.weibull.state\n    Generator state.\n","base.random.weibull.stateLength":"\nbase.random.weibull.stateLength\n    Length of generator state.\n","base.random.weibull.byteLength":"\nbase.random.weibull.byteLength\n    Size (in bytes) of generator state.\n","base.random.weibull.toJSON":"\nbase.random.weibull.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.rcbrt":"\nbase.rcbrt( x:number )\n    Computes the reciprocal cube root of a double-precision floating-point\n    number.\n","base.rcbrtf":"\nbase.rcbrtf( x:number )\n    Computes the reciprocal cube root of a single-precision floating-point\n    number.\n","base.reldiff":"\nbase.reldiff( x:number, y:number[, scale:string|Function] )\n    Computes the relative difference of two real numbers.\n","base.removeFirst":"\nbase.removeFirst( str:string, n:integer )\n    Removes the first `n` UTF-16 code units of a string.\n","base.removeFirstCodePoint":"\nbase.removeFirstCodePoint( str:string, n:integer )\n    Removes the first `n` Unicode code points of a string.\n","base.removeFirstGraphemeCluster":"\nbase.removeFirstGraphemeCluster( str:string, n:integer )\n    Removes the first `n` grapheme clusters (i.e., user-perceived characters)\n    of a string.\n","base.removeLast":"\nbase.removeLast( str:string, n:integer )\n    Removes the last `n` UTF-16 code units of a string.\n","base.removeLastCodePoint":"\nbase.removeLastCodePoint( str:string, n:integer )\n    Removes the last `n` Unicode code points of a string.\n","base.removeLastGraphemeCluster":"\nbase.removeLastGraphemeCluster( str:string, n:integer )\n    Removes the last `n` grapheme clusters (i.e., user-perceived characters)\n    of a string.\n","base.rempio2":"\nbase.rempio2( x:number, y:Array|TypedArray|Object )\n    Computes `x - nπ/2 = r`.\n","base.repeat":"\nbase.repeat( str:string, n:integer )\n    Repeats a string `n` times and returns the concatenated result.\n","base.replace":"\nbase.replace( str:string, search:RegExp, newval:string|Function )\n    Replaces search occurrences with a replacement string.\n","base.replaceAfter":"\nbase.replaceAfter( str:string, search:string, replacement:string, \n  fromIndex:integer )\n    Replaces the substring after the first occurrence of a specified search\n    string.\n","base.replaceAfterLast":"\nbase.replaceAfterLast( str:string, search:string, replacement:string, \n  fromIndex:integer )\n    Replaces the substring after the last occurrence of a specified search\n    string.\n","base.replaceBefore":"\nbase.replaceBefore( str:string, search:string, replacement:string, \n  fromIndex:integer )\n    Replaces the substring before the first occurrence of a specified search\n    string.\n","base.replaceBeforeLast":"\nbase.replaceBeforeLast( str:string, search:string, replacement:string, \n  fromIndex:integer )\n    Replaces the substring before the last occurrence of a specified search\n    string.\n","base.reverse":"\nbase.reverse( str:string )\n    Reverses the UTF-16 code units of a string.\n","base.reverseCodePoints":"\nbase.reverseCodePoints( str:string )\n    Reverses the Unicode code points of a string.\n","base.reverseGraphemeClusters":"\nbase.reverseGraphemeClusters( str:string )\n    Reverses the grapheme clusters (i.e., user-perceived characters) of a\n    string.\n","base.rightPad":"\nbase.rightPad( str:string, len:integer, pad:string )\n    Right pads a string such that the padded string has a length of at least\n    `len`.\n","base.rightTrim":"\nbase.rightTrim( str:string )\n    Trims whitespace from the end of a string.\n","base.risingFactorial":"\nbase.risingFactorial( x:number, n:integer )\n    Computes the rising factorial of `x` and `n`.\n","base.rotl32":"\nbase.rotl32( x:integer, shift:integer )\n    Performs a bitwise rotation to the left.\n","base.rotr32":"\nbase.rotr32( x:integer, shift:integer )\n    Performs a bitwise rotation to the right.\n","base.round":"\nbase.round( x:number )\n    Rounds a numeric value to the nearest integer.\n","base.round2":"\nbase.round2( x:number )\n    Rounds a numeric value to the nearest power of two on a linear scale.\n","base.round10":"\nbase.round10( x:number )\n    Rounds a numeric value to the nearest power of ten on a linear scale.\n","base.roundb":"\nbase.roundb( x:number, n:integer, b:integer )\n    Rounds a numeric value to the nearest multiple of `b^n` on a linear scale.\n","base.roundn":"\nbase.roundn( x:number, n:integer )\n    Rounds a numeric value to the nearest multiple of `10^n`.\n","base.roundsd":"\nbase.roundsd( x:number, n:integer[, b:integer] )\n    Rounds a numeric value to the nearest number with `n` significant figures.\n","base.rsqrt":"\nbase.rsqrt( x:number )\n    Computes the reciprocal square root of a double-precision floating-point\n    number.\n","base.rsqrtf":"\nbase.rsqrtf( x:number )\n    Computes the reciprocal square root of a single-precision floating-point\n    number.\n","base.sargs2multislice":"\nbase.sargs2multislice( str:string )\n    Creates a MultiSlice object from a comma-separated list of string-serialized\n    MultiSlice constructor arguments.\n","base.scalar2ndarray":"\nbase.scalar2ndarray( value:any, dtype:string, order:string )\n    Returns a zero-dimensional ndarray containing a provided scalar value.\n","base.secd":"\nbase.secd( x:number )\n    Computes the secant of an angle measured in degrees.\n","base.seq2multislice":"\nbase.seq2multislice( str:string, shape:Array<integer>, strict:boolean )\n    Converts a multidimensional subsequence string to a MultiSlice object.\n","base.seq2slice":"\nbase.seq2slice( str:string, len:integer, strict:boolean )\n    Converts a subsequence string to a Slice object.\n","base.setHighWord":"\nbase.setHighWord( x:number, high:integer )\n    Sets the more significant 32 bits of a double-precision floating-point\n    number.\n","base.setLowWord":"\nbase.setLowWord( x:number, low:integer )\n    Sets the less significant 32 bits of a double-precision floating-point\n    number.\n","base.sici":"\nbase.sici( x:number )\n    Computes the sine and cosine integrals.\n","base.sici.assign":"\nbase.sici.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n  offset:integer )\n    Computes the sine and cosine integrals and assigns results to a provided\n    output array.\n","base.signbit":"\nbase.signbit( x:number )\n    Returns a boolean indicating if the sign bit is on (true) or off (false).\n","base.signbitf":"\nbase.signbitf( x:float )\n    Returns a boolean indicating if the sign bit is on (true) or off (false).\n","base.significandf":"\nbase.significandf( x:float )\n    Returns an integer corresponding to the significand of a single-precision\n    floating-point number.\n","base.signum":"\nbase.signum( x:number )\n    Evaluates the signum function for a double-precision floating-point number.\n","base.signumf":"\nbase.signumf( x:number )\n    Evaluates the signum function for a single-precision floating-point number.\n","base.sin":"\nbase.sin( x:number )\n    Computes the sine of a number.\n","base.sinc":"\nbase.sinc( x:number )\n    Computes the normalized cardinal sine of a number.\n","base.sincos":"\nbase.sincos( x:number )\n    Simultaneously computes the sine and cosine of a number.\n\nbase.sincos( x:number, out:Array|TypedArray|Object, stride:integer, \n  offset:integer )\n    Simultaneously computes the sine and cosine of a number and assigns\n    results to a provided output array.\n","base.sincospi":"\nbase.sincospi( x:number )\n    Simultaneously computes the sine and cosine of a number times π.\n","base.sincospi.assign":"\nbase.sincospi.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n  offset:integer )\n    Simultaneously computes the sine and cosine of a number times π and\n    assigns results to a provided output array.\n","base.sinh":"\nbase.sinh( x:number )\n    Computes the hyperbolic sine of a double-precision floating-point number.\n","base.sinpi":"\nbase.sinpi( x:number )\n    Computes the value of `sin(πx)`.\n","base.slice2seq":"\nbase.slice2seq( slice:Slice )\n    Converts a Slice object to a subsequence string.\n","base.sliceLength":"\nbase.sliceLength( slice:Slice )\n    Returns the number of elements in a normalized slice.\n","base.sliceNonReducedDimensions":"\nbase.sliceNonReducedDimensions( slice:MultiSlice )\n    Returns a list of non-reduced dimensions in an un-normalized multi-slice.\n","base.sliceReducedDimensions":"\nbase.sliceReducedDimensions( slice:MultiSlice )\n    Returns a list of reduced dimensions in an un-normalized multi-slice.\n","base.sliceShape":"\nbase.sliceShape( slice:MultiSlice )\n    Returns the shape of a normalized multi-slice.\n","base.snakecase":"\nbase.snakecase( str:string )\n    Converts a string to snake case.\n","base.spence":"\nbase.spence( x:number )\n    Evaluates Spence's function, which is also known as the dilogarithm.\n","base.sqrt":"\nbase.sqrt( x:number )\n    Computes the principal square root of a double-precision floating-point\n    number.\n","base.sqrt1pm1":"\nbase.sqrt1pm1( x:number )\n    Computes the principal square root of `1+x` minus one.\n","base.sqrtf":"\nbase.sqrtf( x:number )\n    Computes the principal square root of a single-precision floating-point\n    number.\n","base.sqrtpi":"\nbase.sqrtpi( x:number )\n    Computes the principal square root of the product of π and a positive\n    double-precision floating-point number.\n","base.startcase":"\nbase.startcase( str:string )\n    Capitalizes the first letter of each word in an input string.\n","base.startsWith":"\nbase.startsWith( str:string, search:string, position:integer )\n    Tests if a string starts with the characters of another string.\n","base.stickycase":"\nbase.stickycase( str[, p] )\n    Converts a string to sticky case.\n","base.strided.binary":"\nbase.strided.binary( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  fcn:Function )\n    Applies a binary callback to strided input array elements and assigns\n    results to elements in a strided output array.\n","base.strided.binary.ndarray":"\nbase.strided.binary.ndarray( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  offsets:ArrayLikeObject<integer>, fcn:Function )\n    Applies a binary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n","base.strided.binaryDtypeSignatures":"\nbase.strided.binaryDtypeSignatures( dtypes1:ArrayLike<any>, \n  dtypes2:ArrayLike<any>, dtypes3:ArrayLike<any>[, options:Object] )\n    Generates a list of binary interface signatures from strided array data\n    types.\n","base.strided.binarySignatureCallbacks":"\nbase.strided.binarySignatureCallbacks( table:Object, signatures:ArrayLike<any> )\n    Assigns callbacks to binary interfaces according to type promotion rules.\n","base.strided.ccopy":"\nbase.strided.ccopy( N:integer, x:Complex64Array, strideX:integer, \n  y:Complex64Array, strideY:integer )\n    Copies values from one complex single-precision floating-point vector to\n    another complex single-precision floating-point vector.\n","base.strided.ccopy.ndarray":"\nbase.strided.ccopy.ndarray( N:integer, x:Complex64Array, strideX:integer, \n  offsetX:integer, y:Complex64Array, strideY:integer, offsetY:integer )\n    Copies values from one complex single-precision floating-point vector to\n    another complex single-precision floating-point vector using alternative\n    indexing semantics.\n","base.strided.cmap":"\nbase.strided.cmap( N:integer, x:Complex64Array, strideX:integer, \n  y:Complex64Array, strideY:integer, fcn:Function )\n    Applies a unary function to a single-precision complex floating-point\n    strided input array and assigns results to a single-precision complex\n    floating-point strided output array.\n","base.strided.cmap.ndarray":"\nbase.strided.cmap.ndarray( N:integer, x:Complex64Array, strideX:integer, \n  offsetX:integer, y:Complex64Array, strideY:integer, offsetY:integer, \n  fcn:Function )\n    Applies a unary function to a single-precision complex floating-point\n    strided input array and assigns results to a single-precision complex\n    floating-point strided output array using alternative indexing semantics.\n","base.strided.cswap":"\nbase.strided.cswap( N:integer, x:Complex64Array, strideX:integer, \n  y:Complex64Array, strideY:integer )\n    Interchanges two complex single-precision floating-point vectors.\n","base.strided.cswap.ndarray":"\nbase.strided.cswap.ndarray( N:integer, x:Complex64Array, strideX:integer, \n  offsetX:integer, y:Complex64Array, strideY:integer, offsetY:integer )\n    Interchanges two complex single-precision floating-point vectors using\n    alternative indexing semantics.\n","base.strided.cumax":"\nbase.strided.cumax( N:integer, x:Array|TypedArray, strideX:integer, \n  y:Array|TypedArray, strideY:integer )\n    Computes the cumulative maximum of a strided array.\n","base.strided.cumax.ndarray":"\nbase.strided.cumax.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n  offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n    Computes the cumulative maximum of a strided array using alternative\n    indexing semantics.\n","base.strided.cumaxabs":"\nbase.strided.cumaxabs( N:integer, x:Array|TypedArray, strideX:integer, \n  y:Array|TypedArray, strideY:integer )\n    Computes the cumulative maximum absolute value of a strided array.\n","base.strided.cumaxabs.ndarray":"\nbase.strided.cumaxabs.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n  offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n    Computes the cumulative maximum absolute value of a strided array using\n    alternative indexing semantics.\n","base.strided.cumin":"\nbase.strided.cumin( N:integer, x:Array|TypedArray, strideX:integer, \n  y:Array|TypedArray, strideY:integer )\n    Computes the cumulative minimum of a strided array.\n","base.strided.cumin.ndarray":"\nbase.strided.cumin.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n  offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n    Computes the cumulative minimum of a strided array using alternative\n    indexing semantics.\n","base.strided.cuminabs":"\nbase.strided.cuminabs( N:integer, x:Array|TypedArray, strideX:integer, \n  y:Array|TypedArray, strideY:integer )\n    Computes the cumulative minimum absolute value of a strided array.\n","base.strided.cuminabs.ndarray":"\nbase.strided.cuminabs.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n  offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n    Computes the cumulative minimum absolute value of a strided array using\n    alternative indexing semantics.\n","base.strided.dabs":"\nbase.strided.dabs( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n  strideY:integer )\n    Computes the absolute value for each element in a double-precision floating-\n    point strided array `x` and assigns the results to elements in a double-\n    precision floating-point strided array `y`.\n","base.strided.dabs.ndarray":"\nbase.strided.dabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Computes the absolute value for each element in a double-precision floating-\n    point strided array `x` and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.dabs2":"\nbase.strided.dabs2( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n  strideY:integer )\n    Computes the squared absolute value for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y`.\n","base.strided.dabs2.ndarray":"\nbase.strided.dabs2.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Computes the squared absolute value for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.dapx":"\nbase.strided.dapx( N:integer, alpha:number, x:Float64Array, strideX:integer )\n    Adds a scalar constant to each element in a double-precision floating-point\n    strided array.\n","base.strided.dapx.ndarray":"\nbase.strided.dapx.ndarray( N:integer, alpha:number, x:Float64Array, \n  strideX:integer, offsetX:integer )\n    Adds a scalar constant to each element in a double-precision floating-point\n    strided array using alternative indexing semantics.\n","base.strided.dapxsum":"\nbase.strided.dapxsum( N:integer, alpha:number, x:Float64Array, strideX:integer )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum.\n","base.strided.dapxsum.ndarray":"\nbase.strided.dapxsum.ndarray( N:integer, alpha:number, x:Float64Array, \n  strideX:integer, offsetX:integer )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using alternative indexing semantics.\n","base.strided.dapxsumkbn":"\nbase.strided.dapxsumkbn( N:integer, alpha:number, x:Float64Array, \n  strideX:integer )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using an improved Kahan–Babuška\n    algorithm.\n","base.strided.dapxsumkbn.ndarray":"\nbase.strided.dapxsumkbn.ndarray( N:integer, alpha:number, x:Float64Array, \n  strideX:integer, offsetX:integer )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using an improved Kahan–Babuška\n    algorithm and alternative indexing semantics.\n","base.strided.dapxsumkbn2":"\nbase.strided.dapxsumkbn2( N:integer, alpha:number, x:Float64Array, \n  strideX:integer )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using a second-order iterative\n    Kahan–Babuška algorithm.\n","base.strided.dapxsumkbn2.ndarray":"\nbase.strided.dapxsumkbn2.ndarray( N:integer, alpha:number, x:Float64Array, \n  strideX:integer, offsetX:integer )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using a second-order iterative\n    Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.dapxsumors":"\nbase.strided.dapxsumors( N:integer, alpha:number, x:Float64Array, \n  strideX:integer )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using ordinary recursive summation.\n","base.strided.dapxsumors.ndarray":"\nbase.strided.dapxsumors.ndarray( N:integer, alpha:number, x:Float64Array, \n  strideX:integer, offsetX:integer )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using ordinary recursive summation\n    and alternative indexing semantics.\n","base.strided.dapxsumpw":"\nbase.strided.dapxsumpw( N:integer, alpha:number, x:Float64Array, \n  strideX:integer )\n    Adds a scalar constant to each double-precision floating-point strided array\n    element and computes the sum using pairwise summation.\n","base.strided.dapxsumpw.ndarray":"\nbase.strided.dapxsumpw.ndarray( N:integer, alpha:number, x:Float64Array, \n  strideX:integer, offsetX:integer )\n    Adds a constant to each double-precision floating-point strided array\n    element and computes the sum using pairwise summation and alternative\n    indexing semantics.\n","base.strided.dasum":"\nbase.strided.dasum( N:integer, x:Float64Array, stride:integer )\n    Computes the sum of the absolute values.\n","base.strided.dasum.ndarray":"\nbase.strided.dasum.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the sum of absolute values using alternative indexing semantics.\n","base.strided.dasumpw":"\nbase.strided.dasumpw( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements using pairwise summation.\n","base.strided.dasumpw.ndarray":"\nbase.strided.dasumpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements using pairwise summation and alternative\n    indexing semantics.\n","base.strided.daxpy":"\nbase.strided.daxpy( N:integer, alpha:number, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n","base.strided.daxpy.ndarray":"\nbase.strided.daxpy.ndarray( N:integer, alpha:number, x:Float64Array, \n  strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n  offsetY:integer )\n    Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n    using alternative indexing semantics.\n","base.strided.dcbrt":"\nbase.strided.dcbrt( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n  strideY:integer )\n    Computes the cube root of each element in a double-precision floating-point\n    strided array `x` and assigns the results to elements in a double-precision\n    floating-point strided array `y`.\n","base.strided.dcbrt.ndarray":"\nbase.strided.dcbrt.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Computes the cube root of each element in a double-precision floating-point\n    strided array `x` and assigns the results to elements in a double-precision\n    floating-point strided array `y` using alternative indexing semantics.\n","base.strided.dceil":"\nbase.strided.dceil( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n  strideY:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward positive infinity and assigns the results to elements in a double-\n    precision floating-point strided array `y`.\n","base.strided.dceil.ndarray":"\nbase.strided.dceil.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward positive infinity and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.dcopy":"\nbase.strided.dcopy( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n  strideY:integer )\n    Copies values from `x` into `y`.\n","base.strided.dcopy.ndarray":"\nbase.strided.dcopy.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Copies values from `x` into `y` using alternative indexing semantics.\n","base.strided.dcumax":"\nbase.strided.dcumax( N:integer, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Computes the cumulative maximum of double-precision floating-point strided\n    array elements.\n","base.strided.dcumax.ndarray":"\nbase.strided.dcumax.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Computes the cumulative maximum of double-precision floating-point strided\n    array elements using alternative indexing semantics.\n","base.strided.dcumaxabs":"\nbase.strided.dcumaxabs( N:integer, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Computes the cumulative maximum absolute value of double-precision floating-\n    point strided array elements.\n","base.strided.dcumaxabs.ndarray":"\nbase.strided.dcumaxabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Computes the cumulative maximum absolute value of double-precision floating-\n    point strided array elements using alternative indexing semantics.\n","base.strided.dcumin":"\nbase.strided.dcumin( N:integer, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Computes the cumulative minimum of double-precision floating-point strided\n    array elements.\n","base.strided.dcumin.ndarray":"\nbase.strided.dcumin.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Computes the cumulative minimum of double-precision floating-point strided\n    array elements using alternative indexing semantics.\n","base.strided.dcuminabs":"\nbase.strided.dcuminabs( N:integer, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Computes the cumulative minimum absolute value of double-precision floating-\n    point strided array elements.\n","base.strided.dcuminabs.ndarray":"\nbase.strided.dcuminabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Computes the cumulative minimum absolute value of double-precision floating-\n    point strided array elements using alternative indexing semantics.\n","base.strided.dcusum":"\nbase.strided.dcusum( N:integer, sum:number, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements.\n","base.strided.dcusum.ndarray":"\nbase.strided.dcusum.ndarray( N:integer, sum:number, x:Float64Array, \n  strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using alternative indexing semantics.\n","base.strided.dcusumkbn":"\nbase.strided.dcusumkbn( N:integer, sum:number, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using an improved Kahan–Babuška algorithm.\n","base.strided.dcusumkbn.ndarray":"\nbase.strided.dcusumkbn.ndarray( N:integer, sum:number, x:Float64Array, \n  strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n","base.strided.dcusumkbn2":"\nbase.strided.dcusumkbn2( N:integer, sum:number, x:Float64Array, \n  strideX:integer, y:Float64Array, strideY:integer )\n    Computes the cumulative sum of double-precision floating-point strided\n    array elements using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.dcusumkbn2.ndarray":"\nbase.strided.dcusumkbn2.ndarray( N:integer, sum:number, x:Float64Array, \n  strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of double-precision floating-point strided\n    array elements using a second-order iterative Kahan–Babuška algorithm and\n    alternative indexing semantics.\n","base.strided.dcusumors":"\nbase.strided.dcusumors( N:integer, sum:number, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using ordinary recursive summation.\n","base.strided.dcusumors.ndarray":"\nbase.strided.dcusumors.ndarray( N:integer, sum:number, x:Float64Array, \n  strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using ordinary recursive summation and alternative indexing\n    semantics.\n","base.strided.dcusumpw":"\nbase.strided.dcusumpw( N:integer, sum:number, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using pairwise summation.\n","base.strided.dcusumpw.ndarray":"\nbase.strided.dcusumpw.ndarray( N:integer, sum:number, x:Float64Array, \n  strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using pairwise summation and alternative indexing semantics.\n","base.strided.ddeg2rad":"\nbase.strided.ddeg2rad( N:integer, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Converts each element in a double-precision floating-point strided array `x`\n    from degrees to radians and assigns the results to elements in a double-\n    precision floating-point strided array `y`.\n","base.strided.ddeg2rad.ndarray":"\nbase.strided.ddeg2rad.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Converts each element in a double-precision floating-point strided array `x`\n    from degrees to radians and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.ddot":"\nbase.strided.ddot( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n  strideY:integer )\n    Computes the dot product of two double-precision floating-point vectors.\n","base.strided.ddot.ndarray":"\nbase.strided.ddot.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Computes the dot product of two double-precision floating-point vectors\n    using alternative indexing semantics.\n","base.strided.dfill":"\nbase.strided.dfill( N:integer, alpha:number, x:Float64Array, strideX:integer )\n    Fills a double-precision floating-point strided array with a specified\n    scalar value.\n","base.strided.dfill.ndarray":"\nbase.strided.dfill.ndarray( N:integer, alpha:number, x:Float64Array, \n  strideX:integer, offsetX:integer )\n    Fills a double-precision floating-point strided array with a specified\n    scalar value using alternative indexing semantics.\n","base.strided.dfloor":"\nbase.strided.dfloor( N:integer, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward negative infinity and assigns the results to elements in a double-\n    precision floating-point strided array `y`.\n","base.strided.dfloor.ndarray":"\nbase.strided.dfloor.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward negative infinity and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.dinv":"\nbase.strided.dinv( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n  strideY:integer )\n    Computes the multiplicative inverse for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y`.\n","base.strided.dinv.ndarray":"\nbase.strided.dinv.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Computes the multiplicative inverse for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.dmap":"\nbase.strided.dmap( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n  strideY:integer, fcn:Function )\n    Applies a unary function to a double-precision floating-point strided input\n    array and assigns results to a double-precision floating-point strided\n    output array.\n","base.strided.dmap.ndarray":"\nbase.strided.dmap.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer, \n  fcn:Function )\n    Applies a unary function to a double-precision floating-point strided input\n    array and assigns results to a double-precision floating-point strided\n    output array using alternative indexing semantics.\n","base.strided.dmap2":"\nbase.strided.dmap2( N:integer, x:Float64Array, sx:integer, y:Float64Array, \n  sy:integer, z:Float64Array, sz:integer, fcn:Function )\n    Applies a binary function to double-precision floating-point strided input\n    arrays and assigns results to a double-precision floating-point strided\n    output array.\n","base.strided.dmap2.ndarray":"\nbase.strided.dmap2.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, \n  y:Float64Array, sy:integer, oy:integer, z:Float64Array, sz:integer, \n  oz:integer, fcn:Function )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array using alternative indexing semantics.\n","base.strided.dmax":"\nbase.strided.dmax( N:integer, x:Float64Array, strideX:integer )\n    Computes the maximum value of a double-precision floating-point strided\n    array.\n","base.strided.dmax.ndarray":"\nbase.strided.dmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum value of a double-precision floating-point strided\n    array using alternative indexing semantics.\n","base.strided.dmaxabs":"\nbase.strided.dmaxabs( N:integer, x:Float64Array, strideX:integer )\n    Computes the maximum absolute value of a double-precision floating-point\n    strided array.\n","base.strided.dmaxabs.ndarray":"\nbase.strided.dmaxabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum absolute value of a double-precision floating-point\n    strided array using alternative indexing semantics.\n","base.strided.dmaxabssorted":"\nbase.strided.dmaxabssorted( N:integer, x:Float64Array, strideX:integer )\n    Computes the maximum absolute value of a sorted double-precision floating-\n    point strided array.\n","base.strided.dmaxabssorted.ndarray":"\nbase.strided.dmaxabssorted.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum absolute value of a sorted double-precision floating-\n    point strided array using alternative indexing semantics.\n","base.strided.dmaxsorted":"\nbase.strided.dmaxsorted( N:integer, x:Float64Array, strideX:integer )\n    Computes the maximum value of a sorted double-precision floating-point\n    strided array.\n","base.strided.dmaxsorted.ndarray":"\nbase.strided.dmaxsorted.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n","base.strided.dmean":"\nbase.strided.dmean( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array.\n","base.strided.dmean.ndarray":"\nbase.strided.dmean.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using alternative indexing semantics.\n","base.strided.dmeankbn":"\nbase.strided.dmeankbn( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm.\n","base.strided.dmeankbn.ndarray":"\nbase.strided.dmeankbn.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n","base.strided.dmeankbn2":"\nbase.strided.dmeankbn2( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.dmeankbn2.ndarray":"\nbase.strided.dmeankbn2.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n","base.strided.dmeanli":"\nbase.strided.dmeanli( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm.\n","base.strided.dmeanli.ndarray":"\nbase.strided.dmeanli.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n","base.strided.dmeanlipw":"\nbase.strided.dmeanlipw( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm with pairwise summation.\n","base.strided.dmeanlipw.ndarray":"\nbase.strided.dmeanlipw.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm with pairwise summation and\n    alternative indexing semantics.\n","base.strided.dmeanors":"\nbase.strided.dmeanors( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using ordinary recursive summation.\n","base.strided.dmeanors.ndarray":"\nbase.strided.dmeanors.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using ordinary recursive summation and alternative indexing semantics.\n","base.strided.dmeanpn":"\nbase.strided.dmeanpn( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a two-pass error correction algorithm.\n","base.strided.dmeanpn.ndarray":"\nbase.strided.dmeanpn.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a two-pass error correction algorithm and alternative indexing\n    semantics.\n","base.strided.dmeanpw":"\nbase.strided.dmeanpw( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using pairwise summation.\n","base.strided.dmeanpw.ndarray":"\nbase.strided.dmeanpw.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using pairwise summation and alternative indexing semantics.\n","base.strided.dmeanstdev":"\nbase.strided.dmeanstdev( N:integer, c:number, x:Float64Array, strideX:integer, \n  out:Float64Array, strideOut:integer )\n    Computes the mean and standard deviation of a double-precision floating-\n    point strided array.\n","base.strided.dmeanstdev.ndarray":"\nbase.strided.dmeanstdev.ndarray( N:integer, c:number, x:Float64Array, \n  strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n  offsetOut:integer )\n    Computes the mean and standard deviation of a double-precision floating-\n    point strided array using alternative indexing semantics.\n","base.strided.dmeanstdevpn":"\nbase.strided.dmeanstdevpn( N:integer, c:number, x:Float64Array, \n  strideX:integer, out:Float64Array, strideOut:integer )\n    Computes the mean and standard deviation of a double-precision floating-\n    point strided array using a two-pass algorithm.\n","base.strided.dmeanstdevpn.ndarray":"\nbase.strided.dmeanstdevpn.ndarray( N:integer, c:number, x:Float64Array, \n  strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n  offsetOut:integer )\n    Computes the mean and standard deviation of a double-precision floating-\n    point strided array using a two-pass algorithm and alternative indexing\n    semantics.\n","base.strided.dmeanvar":"\nbase.strided.dmeanvar( N:integer, c:number, x:Float64Array, strideX:integer, \n  out:Float64Array, strideOut:integer )\n    Computes the mean and variance of a double-precision floating-point strided\n    array.\n","base.strided.dmeanvar.ndarray":"\nbase.strided.dmeanvar.ndarray( N:integer, c:number, x:Float64Array, \n  strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n  offsetOut:integer )\n    Computes the mean and variance of a double-precision floating-point strided\n    array using alternative indexing semantics.\n","base.strided.dmeanvarpn":"\nbase.strided.dmeanvarpn( N:integer, c:number, x:Float64Array, strideX:integer, \n  out:Float64Array, strideOut:integer )\n    Computes the mean and variance of a double-precision floating-point strided\n    array using a two-pass algorithm.\n","base.strided.dmeanvarpn.ndarray":"\nbase.strided.dmeanvarpn.ndarray( N:integer, c:number, x:Float64Array, \n  strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n  offsetOut:integer )\n    Computes the mean and variance of a double-precision floating-point strided\n    array using a two-pass algorithm and alternative indexing semantics.\n","base.strided.dmeanwd":"\nbase.strided.dmeanwd( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using Welford's algorithm.\n","base.strided.dmeanwd.ndarray":"\nbase.strided.dmeanwd.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n","base.strided.dmediansorted":"\nbase.strided.dmediansorted( N:integer, x:Float64Array, strideX:integer )\n    Computes the median value of a sorted double-precision floating-point\n    strided array.\n","base.strided.dmediansorted.ndarray":"\nbase.strided.dmediansorted.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the median value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n","base.strided.dmidrange":"\nbase.strided.dmidrange( N:integer, x:Float64Array, strideX:integer )\n    Computes the mid-range of a double-precision floating-point strided array.\n","base.strided.dmidrange.ndarray":"\nbase.strided.dmidrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the mid-range of a double-precision floating-point strided array\n    using alternative indexing semantics.\n","base.strided.dmin":"\nbase.strided.dmin( N:integer, x:Float64Array, strideX:integer )\n    Computes the minimum value of a double-precision floating-point strided\n    array.\n","base.strided.dmin.ndarray":"\nbase.strided.dmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the minimum value of a double-precision floating-point strided\n    array using alternative indexing semantics.\n","base.strided.dminabs":"\nbase.strided.dminabs( N:integer, x:Float64Array, strideX:integer )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array.\n","base.strided.dminabs.ndarray":"\nbase.strided.dminabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array using alternative indexing semantics.\n","base.strided.dminsorted":"\nbase.strided.dminsorted( N:integer, x:Float64Array, strideX:integer )\n    Computes the minimum value of a sorted double-precision floating-point\n    strided array.\n","base.strided.dminsorted.ndarray":"\nbase.strided.dminsorted.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the minimum value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n","base.strided.dmskabs":"\nbase.strided.dmskabs( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Computes the absolute value for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskabs.ndarray":"\nbase.strided.dmskabs.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n  sy:integer, oy:integer )\n    Computes the absolute value for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n","base.strided.dmskabs2":"\nbase.strided.dmskabs2( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Computes the squared absolute value for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point\n    strided array `y`.\n","base.strided.dmskabs2.ndarray":"\nbase.strided.dmskabs2.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n  sy:integer, oy:integer )\n    Computes the squared absolute value for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point\n    strided array `y` using alternative indexing semantics.\n","base.strided.dmskcbrt":"\nbase.strided.dmskcbrt( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Computes the cube root for each element in a double-precision floating-point\n    strided array `x` according to a strided mask array and assigns the results\n    to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskcbrt.ndarray":"\nbase.strided.dmskcbrt.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n  sy:integer, oy:integer )\n    Computes the cube root for each element in a double-precision floating-point\n    strided array `x` according to a strided mask array and assigns the results\n    to elements in a double-precision floating-point strided array `y` using\n    alternative indexing semantics.\n","base.strided.dmskceil":"\nbase.strided.dmskceil( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward positive infinity according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskceil.ndarray":"\nbase.strided.dmskceil.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n  sy:integer, oy:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward positive infinity according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n","base.strided.dmskdeg2rad":"\nbase.strided.dmskdeg2rad( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Converts each element in a double-precision floating-point strided array `x`\n    from degrees to radians according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskdeg2rad.ndarray":"\nbase.strided.dmskdeg2rad.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n  sy:integer, oy:integer )\n    Converts each element in a double-precision floating-point strided array `x`\n    from degrees to radians according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n","base.strided.dmskfloor":"\nbase.strided.dmskfloor( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward negative infinity according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskfloor.ndarray":"\nbase.strided.dmskfloor.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n  sy:integer, oy:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward negative infinity according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n","base.strided.dmskinv":"\nbase.strided.dmskinv( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Computes the multiplicative inverse for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y`.\n","base.strided.dmskinv.ndarray":"\nbase.strided.dmskinv.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n  sy:integer, oy:integer )\n    Computes the multiplicative inverse for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y` using alternative indexing semantics.\n","base.strided.dmskmap":"\nbase.strided.dmskmap( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer, fcn:Function )\n    Applies a unary function to a double-precision floating-point strided input\n    array according to a strided mask array and assigns results to a double-\n    precision floating-point strided output array.\n","base.strided.dmskmap.ndarray":"\nbase.strided.dmskmap.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Uint8Array, sm:integer, om:integer, y:Float64Array, sy:integer, \n  oy:integer, fcn:Function )\n    Applies a unary function to a double-precision floating-point strided input\n    array according to a strided mask array and assigns results to a double-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n","base.strided.dmskmap2":"\nbase.strided.dmskmap2( N:integer, x:Float64Array, sx:integer, y:Float64Array, \n  sy:integer, m:Uint8Array, sm:integer, z:Float64Array, sz:integer, \n  fcn:Function )\n    Applies a binary function to double-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a double-\n    precision floating-point strided output array.\n","base.strided.dmskmap2.ndarray":"\nbase.strided.dmskmap2.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, y:Float64Array, sy:integer, oy:integer, m:Uint8Array, sm:integer, \n  om:integer, z:Float64Array, sz:integer, oz:integer, fcn:Function )\n    Applies a binary function to double-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a double-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n","base.strided.dmskmax":"\nbase.strided.dmskmax( N:integer, x:Float64Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask.\n","base.strided.dmskmax.ndarray":"\nbase.strided.dmskmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n","base.strided.dmskmin":"\nbase.strided.dmskmin( N:integer, x:Float64Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask.\n","base.strided.dmskmin.ndarray":"\nbase.strided.dmskmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n","base.strided.dmskramp":"\nbase.strided.dmskramp( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Evaluates the ramp function for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskramp.ndarray":"\nbase.strided.dmskramp.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n  sy:integer, oy:integer )\n    Evaluates the ramp function for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n","base.strided.dmskrange":"\nbase.strided.dmskrange( N:integer, x:Float64Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the range of a double-precision floating-point strided array\n    according to a mask.\n","base.strided.dmskrange.ndarray":"\nbase.strided.dmskrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the range of a double-precision floating-point strided array\n    according to a mask and using alternative indexing semantics.\n","base.strided.dmskrsqrt":"\nbase.strided.dmskrsqrt( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Computes the reciprocal square root for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y`.\n","base.strided.dmskrsqrt.ndarray":"\nbase.strided.dmskrsqrt.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n  sy:integer, oy:integer )\n    Computes the reciprocal square root for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y` using alternative indexing semantics.\n","base.strided.dmsksqrt":"\nbase.strided.dmsksqrt( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Computes the principal square root for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y`.\n","base.strided.dmsksqrt.ndarray":"\nbase.strided.dmsksqrt.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n  sy:integer, oy:integer )\n    Computes the principal square root for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y` using alternative indexing semantics.\n","base.strided.dmsktrunc":"\nbase.strided.dmsktrunc( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward zero according to a strided mask array and assigns the results to\n    elements in a double-precision floating-point strided array `y`.\n","base.strided.dmsktrunc.ndarray":"\nbase.strided.dmsktrunc.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n  sy:integer, oy:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward zero according to a strided mask array and assigns the results to\n    elements in a double-precision floating-point strided array `y` using\n    alternative indexing semantics.\n","base.strided.dnanasum":"\nbase.strided.dnanasum( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements, ignoring `NaN` values.\n","base.strided.dnanasum.ndarray":"\nbase.strided.dnanasum.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements, ignoring `NaN` values and using alternative\n    indexing semantics.\n","base.strided.dnanasumors":"\nbase.strided.dnanasumors( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements, ignoring `NaN` values and using ordinary\n    recursive summation.\n","base.strided.dnanasumors.ndarray":"\nbase.strided.dnanasumors.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements, ignoring `NaN` values and using ordinary\n    recursive summation alternative indexing semantics.\n","base.strided.dnanmax":"\nbase.strided.dnanmax( N:integer, x:Float64Array, strideX:integer )\n    Computes the maximum value of a double-precision floating-point strided\n    array, ignoring `NaN` values.\n","base.strided.dnanmax.ndarray":"\nbase.strided.dnanmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum value of a double-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanmaxabs":"\nbase.strided.dnanmaxabs( N:integer, x:Float64Array, strideX:integer )\n    Computes the maximum absolute value of a double-precision floating-point\n    strided array, ignoring `NaN` values.\n","base.strided.dnanmaxabs.ndarray":"\nbase.strided.dnanmaxabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum absolute value of a double-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n","base.strided.dnanmean":"\nbase.strided.dnanmean( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values.\n","base.strided.dnanmean.ndarray":"\nbase.strided.dnanmean.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanmeanors":"\nbase.strided.dnanmeanors( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.dnanmeanors.ndarray":"\nbase.strided.dnanmeanors.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation and\n    alternative indexing semantics.\n","base.strided.dnanmeanpn":"\nbase.strided.dnanmeanpn( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction\n    algorithm.\n","base.strided.dnanmeanpn.ndarray":"\nbase.strided.dnanmeanpn.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction algorithm\n    and alternative indexing semantics.\n","base.strided.dnanmeanpw":"\nbase.strided.dnanmeanpw( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using pairwise summation.\n","base.strided.dnanmeanpw.ndarray":"\nbase.strided.dnanmeanpw.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using pairwise summation and alternative\n    indexing semantics.\n","base.strided.dnanmeanwd":"\nbase.strided.dnanmeanwd( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, using Welford's algorithm and ignoring `NaN` values.\n","base.strided.dnanmeanwd.ndarray":"\nbase.strided.dnanmeanwd.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n","base.strided.dnanmin":"\nbase.strided.dnanmin( N:integer, x:Float64Array, strideX:integer )\n    Computes the minimum value of a double-precision floating-point strided\n    array, ignoring `NaN` values.\n","base.strided.dnanmin.ndarray":"\nbase.strided.dnanmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the minimum value of a double-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanminabs":"\nbase.strided.dnanminabs( N:integer, x:Float64Array, strideX:integer )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array, ignoring `NaN` values.\n","base.strided.dnanminabs.ndarray":"\nbase.strided.dnanminabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n","base.strided.dnanmskmax":"\nbase.strided.dnanmskmax( N:integer, x:Float64Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask, ignoring `NaN` values.\n","base.strided.dnanmskmax.ndarray":"\nbase.strided.dnanmskmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n","base.strided.dnanmskmin":"\nbase.strided.dnanmskmin( N:integer, x:Float64Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask, ignoring `NaN` values.\n","base.strided.dnanmskmin.ndarray":"\nbase.strided.dnanmskmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n","base.strided.dnanmskrange":"\nbase.strided.dnanmskrange( N:integer, x:Float64Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the range of a double-precision floating-point strided array\n    according to a mask, ignoring `NaN` values.\n","base.strided.dnanmskrange.ndarray":"\nbase.strided.dnanmskrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the range of a double-precision floating-point strided array\n    according to a mask, ignoring `NaN` values and using alternative indexing\n    semantics.\n","base.strided.dnannsum":"\nbase.strided.dnannsum( N:integer, x:Float64Array, strideX:integer, \n  out:Float64Array, strideOut:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values.\n","base.strided.dnannsum.ndarray":"\nbase.strided.dnannsum.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnannsumkbn":"\nbase.strided.dnannsumkbn( N:integer, x:Float64Array, strideX:integer, \n  out:Float64Array, strideOut:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n","base.strided.dnannsumkbn.ndarray":"\nbase.strided.dnannsumkbn.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n","base.strided.dnannsumkbn2":"\nbase.strided.dnannsumkbn2( N:integer, x:Float64Array, strideX:integer, \n  out:Float64Array, strideOut:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm.\n","base.strided.dnannsumkbn2.ndarray":"\nbase.strided.dnannsumkbn2.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n","base.strided.dnannsumors":"\nbase.strided.dnannsumors( N:integer, x:Float64Array, strideX:integer, \n  out:Float64Array, strideOut:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.dnannsumors.ndarray":"\nbase.strided.dnannsumors.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation and alternative\n    indexing semantics.\n","base.strided.dnannsumpw":"\nbase.strided.dnannsumpw( N:integer, x:Float64Array, strideX:integer, \n  out:Float64Array, strideOut:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation.\n","base.strided.dnannsumpw.ndarray":"\nbase.strided.dnannsumpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation and alternative indexing\n    semantics.\n","base.strided.dnanrange":"\nbase.strided.dnanrange( N:integer, x:Float64Array, strideX:integer )\n    Computes the range of a double-precision floating-point strided array,\n    ignoring `NaN` values.\n","base.strided.dnanrange.ndarray":"\nbase.strided.dnanrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the range of a double-precision floating-point strided array,\n    ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanstdev":"\nbase.strided.dnanstdev( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values.\n","base.strided.dnanstdev.ndarray":"\nbase.strided.dnanstdev.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanstdevch":"\nbase.strided.dnanstdevch( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.dnanstdevch.ndarray":"\nbase.strided.dnanstdevch.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n","base.strided.dnanstdevpn":"\nbase.strided.dnanstdevpn( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.dnanstdevpn.ndarray":"\nbase.strided.dnanstdevpn.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n","base.strided.dnanstdevtk":"\nbase.strided.dnanstdevtk( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.dnanstdevtk.ndarray":"\nbase.strided.dnanstdevtk.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n","base.strided.dnanstdevwd":"\nbase.strided.dnanstdevwd( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using Welford's algorithm.\n","base.strided.dnanstdevwd.ndarray":"\nbase.strided.dnanstdevwd.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n","base.strided.dnanstdevyc":"\nbase.strided.dnanstdevyc( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass algorithm proposed by\n    Youngs and Cramer.\n","base.strided.dnanstdevyc.ndarray":"\nbase.strided.dnanstdevyc.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass algorithm proposed by\n    Youngs and Cramer and alternative indexing semantics.\n","base.strided.dnansum":"\nbase.strided.dnansum( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values.\n","base.strided.dnansum.ndarray":"\nbase.strided.dnansum.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnansumkbn":"\nbase.strided.dnansumkbn( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n","base.strided.dnansumkbn.ndarray":"\nbase.strided.dnansumkbn.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n","base.strided.dnansumkbn2":"\nbase.strided.dnansumkbn2( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm.\n","base.strided.dnansumkbn2.ndarray":"\nbase.strided.dnansumkbn2.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n","base.strided.dnansumors":"\nbase.strided.dnansumors( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.dnansumors.ndarray":"\nbase.strided.dnansumors.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation and alternative\n    indexing semantics.\n","base.strided.dnansumpw":"\nbase.strided.dnansumpw( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation.\n","base.strided.dnansumpw.ndarray":"\nbase.strided.dnansumpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation and alternative indexing\n    semantics.\n","base.strided.dnanvariance":"\nbase.strided.dnanvariance( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values.\n","base.strided.dnanvariance.ndarray":"\nbase.strided.dnanvariance.ndarray( N:integer, correction:number, \n  x:Float64Array, stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanvariancech":"\nbase.strided.dnanvariancech( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.dnanvariancech.ndarray":"\nbase.strided.dnanvariancech.ndarray( N:integer, correction:number, \n  x:Float64Array, stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n","base.strided.dnanvariancepn":"\nbase.strided.dnanvariancepn( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.dnanvariancepn.ndarray":"\nbase.strided.dnanvariancepn.ndarray( N:integer, correction:number, \n  x:Float64Array, stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n","base.strided.dnanvariancetk":"\nbase.strided.dnanvariancetk( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.dnanvariancetk.ndarray":"\nbase.strided.dnanvariancetk.ndarray( N:integer, correction:number, \n  x:Float64Array, stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n","base.strided.dnanvariancewd":"\nbase.strided.dnanvariancewd( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using Welford's algorithm.\n","base.strided.dnanvariancewd.ndarray":"\nbase.strided.dnanvariancewd.ndarray( N:integer, correction:number, \n  x:Float64Array, stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using Welford's algorithm and alternative indexing\n    semantics.\n","base.strided.dnanvarianceyc":"\nbase.strided.dnanvarianceyc( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n    Cramer.\n","base.strided.dnanvarianceyc.ndarray":"\nbase.strided.dnanvarianceyc.ndarray( N:integer, correction:number, \n  x:Float64Array, stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n    Cramer and alternative indexing semantics.\n","base.strided.dnrm2":"\nbase.strided.dnrm2( N:integer, x:Float64Array, stride:integer )\n    Computes the L2-norm of a double-precision floating-point vector.\n","base.strided.dnrm2.ndarray":"\nbase.strided.dnrm2.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the L2-norm of a double-precision floating-point vector using\n    alternative indexing semantics.\n","base.strided.dramp":"\nbase.strided.dramp( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n  strideY:integer )\n    Evaluates the ramp function for each element in a double-precision floating-\n    point strided array `x` and assigns the results to elements in a double-\n    precision floating-point strided array `y`.\n","base.strided.dramp.ndarray":"\nbase.strided.dramp.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Evaluates the ramp function for each element in a double-precision floating-\n    point strided array `x` and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.drange":"\nbase.strided.drange( N:integer, x:Float64Array, strideX:integer )\n    Computes the range of a double-precision floating-point strided array.\n","base.strided.drange.ndarray":"\nbase.strided.drange.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the range of a double-precision floating-point strided array using\n    alternative indexing semantics.\n","base.strided.drev":"\nbase.strided.drev( N:integer, x:Float64Array, strideX:integer )\n    Reverses a double-precision floating-point strided array in-place.\n","base.strided.drev.ndarray":"\nbase.strided.drev.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Reverses a double-precision floating-point strided array in-place using\n    alternative indexing semantics.\n","base.strided.drsqrt":"\nbase.strided.drsqrt( N:integer, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Computes the reciprocal square root for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y`.\n","base.strided.drsqrt.ndarray":"\nbase.strided.drsqrt.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Computes the reciprocal square root for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.dsapxsum":"\nbase.strided.dsapxsum( N:integer, alpha:number, x:Float32Array, \n  strideX:integer )\n    Adds a scalar constant to each single-precision floating-point strided array\n    element, and computes the sum using extended accumulation and returning\n    an extended precision result.\n","base.strided.dsapxsum.ndarray":"\nbase.strided.dsapxsum.ndarray( N:integer, alpha:number, x:Float32Array, \n  strideX:integer, offsetX:integer )\n    Adds a scalar constant to each single-precision floating-point strided array\n    element, and computes the sum using pairwise summation with extended\n    accumulation and alternative indexing semantics and returning an extended\n    precision result.\n","base.strided.dsapxsumpw":"\nbase.strided.dsapxsumpw( N:integer, alpha:number, x:Float32Array, \n  strideX:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element, and computes the sum using pairwise summation with extended\n    accumulation and returning an extended precision result.\n","base.strided.dsapxsumpw.ndarray":"\nbase.strided.dsapxsumpw.ndarray( N:integer, alpha:number, x:Float32Array, \n  strideX:integer, offsetX:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element, and computes the sum using pairwise summation with extended\n    accumulation and alternative indexing semantics and returning an extended\n    precision result.\n","base.strided.dscal":"\nbase.strided.dscal( N:integer, alpha:number, x:Float64Array, stride:integer )\n    Multiplies a double-precision floating-point vector `x` by a constant\n    `alpha`.\n","base.strided.dscal.ndarray":"\nbase.strided.dscal.ndarray( N:integer, alpha:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Multiplies a double-precision floating-point vector `x` by a constant\n    `alpha` using alternative indexing semantics.\n","base.strided.dsdot":"\nbase.strided.dsdot( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer )\n    Computes the dot product of two single-precision floating-point vectors with\n    extended accumulation and result.\n","base.strided.dsdot.ndarray":"\nbase.strided.dsdot.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the dot product of two single-precision floating-point vectors\n    using alternative indexing semantics and with extended accumulation and\n    result.\n","base.strided.dsem":"\nbase.strided.dsem( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array.\n","base.strided.dsem.ndarray":"\nbase.strided.dsem.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using alternative indexing semantics.\n","base.strided.dsemch":"\nbase.strided.dsemch( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass trial mean algorithm.\n","base.strided.dsemch.ndarray":"\nbase.strided.dsemch.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass trial mean algorithm and alternative\n    indexing semantics.\n","base.strided.dsempn":"\nbase.strided.dsempn( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a two-pass algorithm.\n","base.strided.dsempn.ndarray":"\nbase.strided.dsempn.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a two-pass algorithm and alternative indexing\n    semantics.\n","base.strided.dsemtk":"\nbase.strided.dsemtk( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass textbook algorithm.\n","base.strided.dsemtk.ndarray":"\nbase.strided.dsemtk.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass textbook algorithm and alternative\n    indexing semantics.\n","base.strided.dsemwd":"\nbase.strided.dsemwd( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using Welford's algorithm.\n","base.strided.dsemwd.ndarray":"\nbase.strided.dsemwd.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using Welford's algorithm and alternative indexing\n    semantics.\n","base.strided.dsemyc":"\nbase.strided.dsemyc( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass algorithm proposed by Youngs and\n    Cramer.\n","base.strided.dsemyc.ndarray":"\nbase.strided.dsemyc.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass algorithm proposed by Youngs and Cramer\n    and alternative indexing semantics.\n","base.strided.dsmean":"\nbase.strided.dsmean( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using extended accumulation and returning an extended precision\n    result.\n","base.strided.dsmean.ndarray":"\nbase.strided.dsmean.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using extended accumulation and alternative indexing semantics and\n    returning an extended precision result.\n","base.strided.dsmeanors":"\nbase.strided.dsmeanors( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation with extended accumulation and\n    returning an extended precision result.\n","base.strided.dsmeanors.ndarray":"\nbase.strided.dsmeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation with extended accumulation and\n    alternative indexing semantics and returning an extended precision result.\n","base.strided.dsmeanpn":"\nbase.strided.dsmeanpn( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a two-pass error correction algorithm with extended accumulation\n    and returning an extended precision result.\n","base.strided.dsmeanpn.ndarray":"\nbase.strided.dsmeanpn.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a two-pass error correction algorithm with extended accumulation\n    and alternative indexing semantics and returning an extended precision\n    result.\n","base.strided.dsmeanpw":"\nbase.strided.dsmeanpw( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using pairwise summation with extended accumulation and returning an\n    extended precision result.\n","base.strided.dsmeanpw.ndarray":"\nbase.strided.dsmeanpw.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using pairwise summation with extended accumulation and alternative\n    indexing semantics and returning an extended precision result.\n","base.strided.dsmeanwd":"\nbase.strided.dsmeanwd( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using Welford's algorithm with extended accumulation and returning an\n    extended precision result.\n","base.strided.dsmeanwd.ndarray":"\nbase.strided.dsmeanwd.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using Welford's algorithm with extended accumulation and alternative\n    indexing semantics and returning an extended precision result.\n","base.strided.dsnanmean":"\nbase.strided.dsnanmean( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values, using extended accumulation, and returning an\n    extended precision result.\n","base.strided.dsnanmean.ndarray":"\nbase.strided.dsnanmean.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using extended accumulation and alternative\n    indexing semantics.\n","base.strided.dsnanmeanors":"\nbase.strided.dsnanmeanors( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values, using ordinary recursive summation with\n    extended accumulation, and returning an extended precision result.\n","base.strided.dsnanmeanors.ndarray":"\nbase.strided.dsnanmeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation with\n    extended accumulation and alternative indexing semantics.\n","base.strided.dsnanmeanpn":"\nbase.strided.dsnanmeanpn( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values, using a two-pass error correction algorithm\n    with extended accumulation, and returning an extended precision result.\n","base.strided.dsnanmeanpn.ndarray":"\nbase.strided.dsnanmeanpn.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction algorithm\n    with extended accumulation and alternative indexing semantics.\n","base.strided.dsnanmeanwd":"\nbase.strided.dsnanmeanwd( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values, using Welford's algorithm with extended\n    accumulation, and returning an extended precision result.\n","base.strided.dsnanmeanwd.ndarray":"\nbase.strided.dsnanmeanwd.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm with extended\n    accumulation and alternative indexing semantics.\n","base.strided.dsnannsumors":"\nbase.strided.dsnannsumors( N:integer, x:Float32Array, strideX:integer, \n  out:Float64Array, strideOut:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using ordinary recursive summation with extended\n    accumulation, and returning an extended precision result.\n","base.strided.dsnannsumors.ndarray":"\nbase.strided.dsnannsumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using ordinary recursive summation with extended\n    accumulation and alternative indexing semantics, and returning an extended\n    precision result.\n","base.strided.dsnansum":"\nbase.strided.dsnansum( N:integer, x:Float32Array, strideX:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using extended accumulation, and returning an\n    extended precision result.\n","base.strided.dsnansum.ndarray":"\nbase.strided.dsnansum.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using extended accumulation and alternative\n    indexing semantics, and returning an extended precision result.\n","base.strided.dsnansumors":"\nbase.strided.dsnansumors( N:integer, x:Float32Array, strideX:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using ordinary recursive summation with extended\n    accumulation, and returning an extended precision result.\n","base.strided.dsnansumors.ndarray":"\nbase.strided.dsnansumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation with extended\n    accumulation and alternative indexing semantics, and returning an extended\n    precision result.\n","base.strided.dsnansumpw":"\nbase.strided.dsnansumpw( N:integer, x:Float32Array, strideX:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using pairwise summation with extended accumulation,\n    and returning an extended precision result.\n","base.strided.dsnansumpw.ndarray":"\nbase.strided.dsnansumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using pairwise summation with extended accumulation\n    and alternative indexing semantics, and returning an extended precision\n    result.\n","base.strided.dsort2hp":"\nbase.strided.dsort2hp( N:integer, order:number, x:Float64Array, \n  strideX:integer, y:Float64Array, strideY:integer )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using heapsort.\n","base.strided.dsort2hp.ndarray":"\nbase.strided.dsort2hp.ndarray( N:integer, order:number, x:Float64Array, \n  strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n  offsetY:integer )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using heapsort and alternative\n    indexing semantics.\n","base.strided.dsort2ins":"\nbase.strided.dsort2ins( N:integer, order:number, x:Float64Array, \n  strideX:integer, y:Float64Array, strideY:integer )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using insertion sort.\n","base.strided.dsort2ins.ndarray":"\nbase.strided.dsort2ins.ndarray( N:integer, order:number, x:Float64Array, \n  strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n  offsetY:integer )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using insertion sort and\n    alternative indexing semantics.\n","base.strided.dsort2sh":"\nbase.strided.dsort2sh( N:integer, order:number, x:Float64Array, \n  strideX:integer, y:Float64Array, strideY:integer )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using Shellsort.\n","base.strided.dsort2sh.ndarray":"\nbase.strided.dsort2sh.ndarray( N:integer, order:number, x:Float64Array, \n  strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n  offsetY:integer )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using Shellsort and alternative\n    indexing semantics.\n","base.strided.dsorthp":"\nbase.strided.dsorthp( N:integer, order:number, x:Float64Array, stride:integer )\n    Sorts a double-precision floating-point strided array using heapsort.\n","base.strided.dsorthp.ndarray":"\nbase.strided.dsorthp.ndarray( N:integer, order:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Sorts a double-precision floating-point strided array using heapsort and\n    alternative indexing semantics.\n","base.strided.dsortins":"\nbase.strided.dsortins( N:integer, order:number, x:Float64Array, stride:integer )\n    Sorts a double-precision floating-point strided array using insertion sort.\n","base.strided.dsortins.ndarray":"\nbase.strided.dsortins.ndarray( N:integer, order:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Sorts a double-precision floating-point strided array using insertion sort\n    and alternative indexing semantics.\n","base.strided.dsortsh":"\nbase.strided.dsortsh( N:integer, order:number, x:Float64Array, stride:integer )\n    Sorts a double-precision floating-point strided array using Shellsort.\n","base.strided.dsortsh.ndarray":"\nbase.strided.dsortsh.ndarray( N:integer, order:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Sorts a double-precision floating-point strided array using Shellsort and\n    alternative indexing semantics.\n","base.strided.dsqrt":"\nbase.strided.dsqrt( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n  strideY:integer )\n    Computes the principal square root for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y`.\n","base.strided.dsqrt.ndarray":"\nbase.strided.dsqrt.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Computes the principal square root for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.dssum":"\nbase.strided.dssum( N:integer, x:Float32Array, strideX:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using extended accumulation and returning an extended precision result.\n","base.strided.dssum.ndarray":"\nbase.strided.dssum.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using extended accumulation and alternative indexing semantics and returning\n    an extended precision result.\n","base.strided.dssumors":"\nbase.strided.dssumors( N:integer, x:Float32Array, strideX:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using ordinary recursive summation with extended accumulation and returning\n    an extended precision result.\n","base.strided.dssumors.ndarray":"\nbase.strided.dssumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using ordinary recursive summation with extended accumulation and\n    alternative indexing semantics and returning an extended precision result.\n","base.strided.dssumpw":"\nbase.strided.dssumpw( N:integer, x:Float32Array, strideX:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation with extended accumulation and returning an\n    extended precision result.\n","base.strided.dssumpw.ndarray":"\nbase.strided.dssumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation with extended accumulation and alternative indexing\n    semantics and returning an extended precision result.\n","base.strided.dstdev":"\nbase.strided.dstdev( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array.\n","base.strided.dstdev.ndarray":"\nbase.strided.dstdev.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using alternative indexing semantics.\n","base.strided.dstdevch":"\nbase.strided.dstdevch( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm.\n","base.strided.dstdevch.ndarray":"\nbase.strided.dstdevch.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n","base.strided.dstdevpn":"\nbase.strided.dstdevpn( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a two-pass algorithm.\n","base.strided.dstdevpn.ndarray":"\nbase.strided.dstdevpn.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a two-pass algorithm and alternative indexing semantics.\n","base.strided.dstdevtk":"\nbase.strided.dstdevtk( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass textbook algorithm.\n","base.strided.dstdevtk.ndarray":"\nbase.strided.dstdevtk.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass textbook algorithm and alternative indexing\n    semantics.\n","base.strided.dstdevwd":"\nbase.strided.dstdevwd( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using Welford's algorithm.\n","base.strided.dstdevwd.ndarray":"\nbase.strided.dstdevwd.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n","base.strided.dstdevyc":"\nbase.strided.dstdevyc( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.dstdevyc.ndarray":"\nbase.strided.dstdevyc.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer and\n    alternative indexing semantics.\n","base.strided.dsum":"\nbase.strided.dsum( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of double-precision floating-point strided array elements.\n","base.strided.dsum.ndarray":"\nbase.strided.dsum.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using alternative indexing semantics.\n","base.strided.dsumkbn":"\nbase.strided.dsumkbn( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm.\n","base.strided.dsumkbn.ndarray":"\nbase.strided.dsumkbn.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n","base.strided.dsumkbn2":"\nbase.strided.dsumkbn2( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.dsumkbn2.ndarray":"\nbase.strided.dsumkbn2.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n","base.strided.dsumors":"\nbase.strided.dsumors( N:integer, x:Float64Array, stride:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using ordinary recursive summation.\n","base.strided.dsumors.ndarray":"\nbase.strided.dsumors.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using ordinary recursive summation and alternative indexing semantics.\n","base.strided.dsumpw":"\nbase.strided.dsumpw( N:integer, x:Float64Array, stride:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using pairwise summation.\n","base.strided.dsumpw.ndarray":"\nbase.strided.dsumpw.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using pairwise summation and alternative indexing semantics.\n","base.strided.dsvariance":"\nbase.strided.dsvariance( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using extended accumulation and returning an extended precision result.\n","base.strided.dsvariance.ndarray":"\nbase.strided.dsvariance.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using extended accumulation and alternative indexing semantics and\n    returning an extended precision result.\n","base.strided.dsvariancepn":"\nbase.strided.dsvariancepn( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using a two-pass algorithm with extended accumulation and returning an\n    extended precision result.\n","base.strided.dsvariancepn.ndarray":"\nbase.strided.dsvariancepn.ndarray( N:integer, correction:number, \n  x:Float32Array, stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using a two-pass algorithm with extended accumulation and alternative\n    indexing semantics and returning an extended precision result.\n","base.strided.dswap":"\nbase.strided.dswap( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n  strideY:integer )\n    Interchanges two double-precision floating-point vectors.\n","base.strided.dswap.ndarray":"\nbase.strided.dswap.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Interchanges two double-precision floating-point vectors using alternative\n    indexing semantics.\n","base.strided.dtrunc":"\nbase.strided.dtrunc( N:integer, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward zero and assigns the results to elements in a double-precision\n    floating-point strided array `y`.\n","base.strided.dtrunc.ndarray":"\nbase.strided.dtrunc.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward zero and assigns the results to elements in a double-precision\n    floating-point strided array `y` using alternative indexing semantics.\n","base.strided.dtypeEnum2Str":"\nbase.strided.dtypeEnum2Str( dtype:integer )\n    Returns the data type string associated with a strided array data type\n    enumeration constant.\n","base.strided.dtypeResolveEnum":"\nbase.strided.dtypeResolveEnum( dtype:any )\n    Returns the enumeration constant associated with a supported strided array\n    data type value.\n","base.strided.dtypeResolveStr":"\nbase.strided.dtypeResolveStr( dtype:any )\n    Returns the data type string associated with a supported data type value.\n","base.strided.dtypeStr2Enum":"\nbase.strided.dtypeStr2Enum( dtype:string )\n    Returns the enumeration constant associated with a strided array data type\n    string.\n","base.strided.dvariance":"\nbase.strided.dvariance( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array.\n","base.strided.dvariance.ndarray":"\nbase.strided.dvariance.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using alternative indexing semantics.\n","base.strided.dvariancech":"\nbase.strided.dvariancech( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass trial mean algorithm.\n","base.strided.dvariancech.ndarray":"\nbase.strided.dvariancech.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.dvariancepn":"\nbase.strided.dvariancepn( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using a two-pass algorithm.\n","base.strided.dvariancepn.ndarray":"\nbase.strided.dvariancepn.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using a two-pass algorithm and alternative indexing semantics.\n","base.strided.dvariancetk":"\nbase.strided.dvariancetk( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass textbook algorithm.\n","base.strided.dvariancetk.ndarray":"\nbase.strided.dvariancetk.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.dvariancewd":"\nbase.strided.dvariancewd( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using Welford's algorithm.\n","base.strided.dvariancewd.ndarray":"\nbase.strided.dvariancewd.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using Welford's algorithm and alternative indexing semantics.\n","base.strided.dvarianceyc":"\nbase.strided.dvarianceyc( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.dvarianceyc.ndarray":"\nbase.strided.dvarianceyc.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass algorithm proposed by Youngs and Cramer and alternative\n    indexing semantics.\n","base.strided.dvarm":"\nbase.strided.dvarm( N:integer, mean:number, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean.\n","base.strided.dvarm.ndarray":"\nbase.strided.dvarm.ndarray( N:integer, mean:number, correction:number, \n  x:Float64Array, stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using alternative indexing semantics.\n","base.strided.dvarmpn":"\nbase.strided.dvarmpn( N:integer, mean:number, correction:number, \n  x:Float64Array, stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using Neely's correction algorithm.\n","base.strided.dvarmpn.ndarray":"\nbase.strided.dvarmpn.ndarray( N:integer, mean:number, correction:number, \n  x:Float64Array, stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using Neely's correction algorithm and alternative\n    indexing semantics.\n","base.strided.dvarmtk":"\nbase.strided.dvarmtk( N:integer, mean:number, correction:number, \n  x:Float64Array, stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using a one-pass textbook algorithm.\n","base.strided.dvarmtk.ndarray":"\nbase.strided.dvarmtk.ndarray( N:integer, mean:number, correction:number, \n  x:Float64Array, stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n","base.strided.gapx":"\nbase.strided.gapx( N:integer, alpha:number, x:Array|TypedArray, stride:integer )\n    Adds a constant to each element in a strided array.\n","base.strided.gapx.ndarray":"\nbase.strided.gapx.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Adds a constant to each element in a strided array using alternative\n    indexing semantics.\n","base.strided.gapxsum":"\nbase.strided.gapxsum( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer )\n    Adds a constant to each strided array element and computes the sum.\n","base.strided.gapxsum.ndarray":"\nbase.strided.gapxsum.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Adds a constant to each strided array element and computes the sum using\n    alternative indexing semantics.\n","base.strided.gapxsumkbn":"\nbase.strided.gapxsumkbn( N:integer, alpha:number, x:Array|TypedArray, \n  strideX:integer )\n    Adds a scalar constant to each strided array element and computes the sum\n    using an improved Kahan–Babuška algorithm.\n","base.strided.gapxsumkbn.ndarray":"\nbase.strided.gapxsumkbn.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n  strideX:integer, offsetX:integer )\n    Adds a scalar constant to each strided array element and computes the sum\n    using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n","base.strided.gapxsumkbn2":"\nbase.strided.gapxsumkbn2( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer )\n    Adds a constant to each strided array element and computes the sum using a\n    second-order iterative Kahan–Babuška algorithm.\n","base.strided.gapxsumkbn2.ndarray":"\nbase.strided.gapxsumkbn2.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Adds a constant to each strided array element and computes the sum using a\n    second-order iterative Kahan–Babuška algorithm and alternative indexing\n    semantics.\n","base.strided.gapxsumors":"\nbase.strided.gapxsumors( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer )\n    Adds a constant to each strided array element and computes the sum using\n    ordinary recursive summation.\n","base.strided.gapxsumors.ndarray":"\nbase.strided.gapxsumors.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Adds a constant to each strided array element and computes the sum using\n    ordinary recursive summation and alternative indexing semantics.\n","base.strided.gapxsumpw":"\nbase.strided.gapxsumpw( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer )\n    Adds a constant to each strided array element and computes the sum using\n    pairwise summation.\n","base.strided.gapxsumpw.ndarray":"\nbase.strided.gapxsumpw.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Adds a constant to each strided array element and computes the sum using\n    pairwise summation and alternative indexing semantics.\n","base.strided.gasum":"\nbase.strided.gasum( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of the absolute values.\n","base.strided.gasum.ndarray":"\nbase.strided.gasum.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the sum of absolute values using alternative indexing semantics.\n","base.strided.gasumpw":"\nbase.strided.gasumpw( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of absolute values (L1 norm) of strided array elements\n    using pairwise summation.\n","base.strided.gasumpw.ndarray":"\nbase.strided.gasumpw.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the sum of absolute values (L1 norm) of strided array elements\n    using pairwise summation and alternative indexing semantics.\n","base.strided.gaxpy":"\nbase.strided.gaxpy( N:integer, alpha:number, x:Array|TypedArray, \n  strideX:integer, y:Array|TypedArray, strideY:integer )\n    Multiplies `x` by a constant `alpha` and adds the result to `y`.\n","base.strided.gaxpy.ndarray":"\nbase.strided.gaxpy.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n  strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n  offsetY:integer )\n    Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n    alternative indexing semantics.\n","base.strided.gcopy":"\nbase.strided.gcopy( N:integer, x:ArrayLikeObject, strideX:integer, \n  y:ArrayLikeObject, strideY:integer )\n    Copies values from `x` into `y`.\n","base.strided.gcopy.ndarray":"\nbase.strided.gcopy.ndarray( N:integer, x:ArrayLikeObject, strideX:integer, \n  offsetX:integer, y:ArrayLikeObject, strideY:integer, offsetY:integer )\n    Copies values from `x` into `y` using alternative indexing semantics.\n","base.strided.gcusum":"\nbase.strided.gcusum( N:integer, sum:number, x:Array|TypedArray, \n  strideX:integer, y:Array|TypedArray, strideY:integer )\n    Computes the cumulative sum of strided array elements.\n","base.strided.gcusum.ndarray":"\nbase.strided.gcusum.ndarray( N:integer, sum:number, x:Array|TypedArray, \n  strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of strided array elements using alternative\n    indexing semantics.\n","base.strided.gcusumkbn":"\nbase.strided.gcusumkbn( N:integer, sum:number, x:Array|TypedArray, \n  strideX:integer, y:Array|TypedArray, strideY:integer )\n    Computes the cumulative sum of strided array elements using an improved\n    Kahan–Babuška algorithm.\n","base.strided.gcusumkbn.ndarray":"\nbase.strided.gcusumkbn.ndarray( N:integer, sum:number, x:Array|TypedArray, \n  strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of strided array elements using an improved\n    Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gcusumkbn2":"\nbase.strided.gcusumkbn2( N:integer, sum:number, x:Array|TypedArray, \n  strideX:integer, y:Array|TypedArray, strideY:integer )\n    Computes the cumulative sum of strided array elements using a second-order\n    iterative Kahan–Babuška algorithm.\n","base.strided.gcusumkbn2.ndarray":"\nbase.strided.gcusumkbn2.ndarray( N:integer, sum:number, x:Array|TypedArray, \n  strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of strided array elements using a second-order\n    iterative Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gcusumors":"\nbase.strided.gcusumors( N:integer, sum:number, x:Array|TypedArray, \n  strideX:integer, y:Array|TypedArray, strideY:integer )\n    Computes the cumulative sum of strided array elements using ordinary\n    recursive summation.\n","base.strided.gcusumors.ndarray":"\nbase.strided.gcusumors.ndarray( N:integer, sum:number, x:Array|TypedArray, \n  strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of strided array elements using ordinary\n    recursive summation and alternative indexing semantics.\n","base.strided.gcusumpw":"\nbase.strided.gcusumpw( N:integer, sum:number, x:Array|TypedArray, \n  strideX:integer, y:Array|TypedArray, strideY:integer )\n    Computes the cumulative sum of strided array elements using pairwise\n    summation.\n","base.strided.gcusumpw.ndarray":"\nbase.strided.gcusumpw.ndarray( N:integer, sum:number, x:Array|TypedArray, \n  strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of strided array elements using pairwise\n    summation and alternative indexing semantics.\n","base.strided.gdot":"\nbase.strided.gdot( N:integer, x:Array|TypedArray, strideX:integer, \n  y:Array|TypedArray, strideY:integer )\n    Computes the dot product of two vectors.\n","base.strided.gdot.ndarray":"\nbase.strided.gdot.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n  offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n    Computes the dot product of two vectors using alternative indexing\n    semantics.\n","base.strided.gfill":"\nbase.strided.gfill( N:integer, alpha:any, x:ArrayLikeObject, stride:integer )\n    Fills a strided array with a specified scalar value.\n","base.strided.gfill.ndarray":"\nbase.strided.gfill.ndarray( N:integer, alpha:any, x:ArrayLikeObject, \n  stride:integer, offset:integer )\n    Fills a strided array with a specified scalar value using alternative\n    indexing semantics.\n","base.strided.gfillBy":"\nbase.strided.gfillBy( N:integer, x:ArrayLikeObject, stride:integer, \n  clbk:Function[, thisArg:any] )\n    Fills a strided array according to a provided callback function.\n","base.strided.gfillBy.ndarray":"\nbase.strided.gfillBy.ndarray( N:integer, x:ArrayLikeObject, stride:integer, \n  offset:integer, clbk:Function[, thisArg:any] )\n    Fills a strided array according to a provided callback function and using\n    alternative indexing semantics.\n","base.strided.gnannsumkbn":"\nbase.strided.gnannsumkbn( N:integer, x:Array|TypedArray, strideX:integer, \n  out:Array|TypedArray, strideOut:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    an improved Kahan–Babuška algorithm.\n","base.strided.gnannsumkbn.ndarray":"\nbase.strided.gnannsumkbn.ndarray( N:integer, x:Array|TypedArray, \n  strideX:integer, offsetX:integer, out:Array|TypedArray, strideOut:integer, \n  offsetOut:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    an improved Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gnansum":"\nbase.strided.gnansum( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values.\n","base.strided.gnansum.ndarray":"\nbase.strided.gnansum.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    alternative indexing semantics.\n","base.strided.gnansumkbn":"\nbase.strided.gnansumkbn( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    an improved Kahan–Babuška algorithm.\n","base.strided.gnansumkbn.ndarray":"\nbase.strided.gnansumkbn.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    an improved Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gnansumkbn2":"\nbase.strided.gnansumkbn2( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    a second-order iterative Kahan–Babuška algorithm.\n","base.strided.gnansumkbn2.ndarray":"\nbase.strided.gnansumkbn2.ndarray( N:integer, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    a second-order iterative Kahan–Babuška algorithm and alternative indexing\n    semantics.\n","base.strided.gnansumors":"\nbase.strided.gnansumors( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    ordinary recursive summation.\n","base.strided.gnansumors.ndarray":"\nbase.strided.gnansumors.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    ordinary recursive summation and alternative indexing semantics.\n","base.strided.gnansumpw":"\nbase.strided.gnansumpw( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values and\n    pairwise summation.\n","base.strided.gnansumpw.ndarray":"\nbase.strided.gnansumpw.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    pairwise summation and alternative indexing semantics.\n","base.strided.gnrm2":"\nbase.strided.gnrm2( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the L2-norm of a vector.\n","base.strided.gnrm2.ndarray":"\nbase.strided.gnrm2.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the L2-norm of a vector using alternative indexing semantics.\n","base.strided.grev":"\nbase.strided.grev( N:integer, x:ArrayLikeObject, stride:integer )\n    Reverses a strided array in-place.\n","base.strided.grev.ndarray":"\nbase.strided.grev.ndarray( N:integer, x:ArrayLikeObject, stride:integer, \n  offset:integer )\n    Reverses a strided array in-place using alternative indexing semantics.\n","base.strided.gscal":"\nbase.strided.gscal( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer )\n    Multiplies a vector `x` by a constant `alpha`.\n","base.strided.gscal.ndarray":"\nbase.strided.gscal.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Multiplies `x` by a constant `alpha` using alternative indexing semantics.\n","base.strided.gsort2hp":"\nbase.strided.gsort2hp( N:integer, order:number, x:Array|TypedArray, \n  strideX:integer, y:Array|TypedArray, strideY:integer )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using heapsort.\n","base.strided.gsort2hp.ndarray":"\nbase.strided.gsort2hp.ndarray( N:integer, order:number, x:Array|TypedArray, \n  strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n  offsetY:integer )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using heapsort and alternative indexing semantics.\n","base.strided.gsort2ins":"\nbase.strided.gsort2ins( N:integer, order:number, x:Array|TypedArray, \n  strideX:integer, y:Array|TypedArray, strideY:integer )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using insertion sort.\n","base.strided.gsort2ins.ndarray":"\nbase.strided.gsort2ins.ndarray( N:integer, order:number, x:Array|TypedArray, \n  strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n  offsetY:integer )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using insertion sort and alternative indexing semantics.\n","base.strided.gsort2sh":"\nbase.strided.gsort2sh( N:integer, order:number, x:Array|TypedArray, \n  strideX:integer, y:Array|TypedArray, strideY:integer )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using Shellsort.\n","base.strided.gsort2sh.ndarray":"\nbase.strided.gsort2sh.ndarray( N:integer, order:number, x:Array|TypedArray, \n  strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n  offsetY:integer )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using Shellsort and alternative indexing semantics.\n","base.strided.gsorthp":"\nbase.strided.gsorthp( N:integer, order:number, x:Array|TypedArray, \n  stride:integer )\n    Sorts a strided array using heapsort.\n","base.strided.gsorthp.ndarray":"\nbase.strided.gsorthp.ndarray( N:integer, order:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Sorts a strided array using heapsort and alternative indexing semantics.\n","base.strided.gsortins":"\nbase.strided.gsortins( N:integer, order:number, x:Array|TypedArray, \n  stride:integer )\n    Sorts a strided array using insertion sort.\n","base.strided.gsortins.ndarray":"\nbase.strided.gsortins.ndarray( N:integer, order:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Sorts a strided array using insertion sort and alternative indexing\n    semantics.\n","base.strided.gsortsh":"\nbase.strided.gsortsh( N:integer, order:number, x:Array|TypedArray, \n  stride:integer )\n    Sorts a strided array using Shellsort.\n","base.strided.gsortsh.ndarray":"\nbase.strided.gsortsh.ndarray( N:integer, order:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Sorts a strided array using Shellsort and alternative indexing semantics.\n","base.strided.gsum":"\nbase.strided.gsum( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of strided array elements.\n","base.strided.gsum.ndarray":"\nbase.strided.gsum.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the sum of strided array elements using alternative indexing\n    semantics.\n","base.strided.gsumkbn":"\nbase.strided.gsumkbn( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of strided array elements using an improved Kahan–Babuška\n    algorithm.\n","base.strided.gsumkbn.ndarray":"\nbase.strided.gsumkbn.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the sum of strided array elements using an improved Kahan–Babuška\n    algorithm and alternative indexing semantics.\n","base.strided.gsumkbn2":"\nbase.strided.gsumkbn2( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of strided array elements using a second-order iterative\n    Kahan–Babuška algorithm.\n","base.strided.gsumkbn2.ndarray":"\nbase.strided.gsumkbn2.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the sum of strided array elements using a second-order iterative\n    Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gsumors":"\nbase.strided.gsumors( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of strided array elements using ordinary recursive\n    summation.\n","base.strided.gsumors.ndarray":"\nbase.strided.gsumors.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the sum of strided array elements using ordinary recursive\n    summation and alternative indexing semantics.\n","base.strided.gsumpw":"\nbase.strided.gsumpw( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of strided array elements using pairwise summation.\n","base.strided.gsumpw.ndarray":"\nbase.strided.gsumpw.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the sum of strided array elements using pairwise summation and\n    alternative indexing semantics.\n","base.strided.gswap":"\nbase.strided.gswap( N:integer, x:ArrayLikeObject, strideX:integer, \n  y:ArrayLikeObject, strideY:integer )\n    Interchanges vectors `x` and `y`.\n","base.strided.gswap.ndarray":"\nbase.strided.gswap.ndarray( N:integer, x:ArrayLikeObject, strideX:integer, \n  offsetX:integer, y:ArrayLikeObject, strideY:integer, offsetY:integer )\n    Interchanges vectors `x` and `y` using alternative indexing semantics.\n","base.strided.mapBy":"\nbase.strided.mapBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, fcn:Function, clbk:Function[, \n  thisArg:any] )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array.\n","base.strided.mapBy.ndarray":"\nbase.strided.mapBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, fcn:Function, \n  clbk:Function[, thisArg:any] )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array using alternative indexing semantics.\n","base.strided.mapBy2":"\nbase.strided.mapBy2( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, \n  fcn:Function, clbk:Function[, thisArg:any] )\n    Applies a binary function to each pair of elements retrieved from strided\n    input arrays according to a callback function and assigns results to a\n    strided output array.\n","base.strided.mapBy2.ndarray":"\nbase.strided.mapBy2.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  z:Array|TypedArray|Object, sz:integer, oz:integer, fcn:Function, \n  clbk:Function[, thisArg:any] )\n    Applies a binary function to each pair of elements retrieved from strided\n    input arrays according to a callback function and assigns results to a\n    strided output array using alternative indexing semantics.\n","base.strided.max":"\nbase.strided.max( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the maximum value of a strided array.\n","base.strided.max.ndarray":"\nbase.strided.max.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the maximum value of a strided array using alternative indexing\n    semantics.\n","base.strided.maxabs":"\nbase.strided.maxabs( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the maximum absolute value of a strided array.\n","base.strided.maxabs.ndarray":"\nbase.strided.maxabs.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the maximum absolute value of a strided array using alternative\n    indexing semantics.\n","base.strided.maxBy":"\nbase.strided.maxBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n  clbk:Function[, thisArg:any] )\n    Calculates the maximum value of a strided array via a callback function.\n","base.strided.maxBy.ndarray":"\nbase.strided.maxBy.ndarray( N:integer, x:Array|TypedArray|Object, \n  stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n    Calculates the maximum value of a strided array via a callback function and\n    using alternative indexing semantics.\n","base.strided.maxsorted":"\nbase.strided.maxsorted( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the maximum value of a sorted strided array.\n","base.strided.maxsorted.ndarray":"\nbase.strided.maxsorted.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the maximum value of a sorted strided array using alternative\n    indexing semantics.\n","base.strided.maxViewBufferIndex":"\nbase.strided.maxViewBufferIndex( N:integer, stride:integer, offset:integer )\n    Returns the maximum accessible index based on a set of provided strided\n    array parameters.\n","base.strided.mean":"\nbase.strided.mean( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the arithmetic mean of a strided array.\n","base.strided.mean.ndarray":"\nbase.strided.mean.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a strided array using alternative indexing\n    semantics.\n","base.strided.meankbn":"\nbase.strided.meankbn( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the arithmetic mean of a strided array using an improved Kahan–\n    Babuška algorithm.\n","base.strided.meankbn.ndarray":"\nbase.strided.meankbn.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a strided array using an improved Kahan–\n    Babuška algorithm and alternative indexing semantics.\n","base.strided.meankbn2":"\nbase.strided.meankbn2( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the arithmetic mean of a strided array using a second-order\n    iterative Kahan–Babuška algorithm.\n","base.strided.meankbn2.ndarray":"\nbase.strided.meankbn2.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a strided array using a second-order\n    iterative Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.meanors":"\nbase.strided.meanors( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the arithmetic mean of a strided array using ordinary recursive\n    summation.\n","base.strided.meanors.ndarray":"\nbase.strided.meanors.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a strided array using ordinary recursive\n    summation and alternative indexing semantics.\n","base.strided.meanpn":"\nbase.strided.meanpn( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the arithmetic mean of a strided array using a two-pass error\n    correction algorithm.\n","base.strided.meanpn.ndarray":"\nbase.strided.meanpn.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a strided array using a two-pass error\n    correction algorithm and alternative indexing semantics.\n","base.strided.meanpw":"\nbase.strided.meanpw( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the arithmetic mean of a strided array using pairwise summation.\n","base.strided.meanpw.ndarray":"\nbase.strided.meanpw.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a strided array using pairwise summation and\n    alternative indexing semantics.\n","base.strided.meanwd":"\nbase.strided.meanwd( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the arithmetic mean of a strided array using Welford's algorithm.\n","base.strided.meanwd.ndarray":"\nbase.strided.meanwd.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a strided array using Welford's algorithm\n    and alternative indexing semantics.\n","base.strided.mediansorted":"\nbase.strided.mediansorted( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the median value of a sorted strided array.\n","base.strided.mediansorted.ndarray":"\nbase.strided.mediansorted.ndarray( N:integer, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Computes the median value of a sorted strided array using alternative\n    indexing semantics.\n","base.strided.metaDataProps":"\nbase.strided.metaDataProps( meta:Object, dtypes:ArrayLikeObject, \n  obj:Object|Function, bool:boolean )\n    Defines non-enumerable read-only properties which expose strided array\n    function meta data.\n","base.strided.min":"\nbase.strided.min( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the minimum value of a strided array.\n","base.strided.min.ndarray":"\nbase.strided.min.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the minimum value of a strided array using alternative indexing\n    semantics.\n","base.strided.minabs":"\nbase.strided.minabs( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the minimum absolute value of a strided array.\n","base.strided.minabs.ndarray":"\nbase.strided.minabs.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the minimum absolute value of a strided array using alternative\n    indexing semantics.\n","base.strided.minBy":"\nbase.strided.minBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n  clbk:Function[, thisArg:any] )\n    Calculates the minimum value of a strided array via a callback function.\n","base.strided.minBy.ndarray":"\nbase.strided.minBy.ndarray( N:integer, x:Array|TypedArray|Object, \n  stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n    Calculates the minimum value of a strided array via a callback function and\n    using alternative indexing semantics.\n","base.strided.minsorted":"\nbase.strided.minsorted( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the minimum value of a sorted strided array.\n","base.strided.minsorted.ndarray":"\nbase.strided.minsorted.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the minimum value of a sorted strided array using alternative\n    indexing semantics.\n","base.strided.minViewBufferIndex":"\nbase.strided.minViewBufferIndex( N:integer, stride:integer, offset:integer )\n    Returns the minimum accessible index based on a set of provided strided\n    array parameters.\n","base.strided.mskmax":"\nbase.strided.mskmax( N:integer, x:Array|TypedArray, strideX:integer, \n  mask:Array|TypedArray, strideMask:integer )\n    Computes the maximum value of a strided array according to a mask.\n","base.strided.mskmax.ndarray":"\nbase.strided.mskmax.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n  offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n  offsetMask:integer )\n    Computes the maximum value of a strided array according to a mask and using\n    alternative indexing semantics.\n","base.strided.mskmin":"\nbase.strided.mskmin( N:integer, x:Array|TypedArray, strideX:integer, \n  mask:Array|TypedArray, strideMask:integer )\n    Computes the minimum value of a strided array according to a mask.\n","base.strided.mskmin.ndarray":"\nbase.strided.mskmin.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n  offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n  offsetMask:integer )\n    Computes the minimum value of a strided array according to a mask and using\n    alternative indexing semantics.\n","base.strided.mskrange":"\nbase.strided.mskrange( N:integer, x:Array|TypedArray, strideX:integer, \n  mask:Array|TypedArray, strideMask:integer )\n    Computes the range of a strided array according to a mask.\n","base.strided.mskrange.ndarray":"\nbase.strided.mskrange.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n  offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n  offsetMask:integer )\n    Computes the range of a strided array according to a mask and using\n    alternative indexing semantics.\n","base.strided.mskunary":"\nbase.strided.mskunary( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  fcn:Function )\n    Applies a unary callback to elements in a strided input array according to\n    elements in a strided mask array and assigns results to elements in a\n    strided output array.\n","base.strided.mskunary.ndarray":"\nbase.strided.mskunary.ndarray( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  offsets:ArrayLikeObject<integer>, fcn:Function )\n    Applies a unary callback to elements in a strided input array according to\n    elements in a strided mask array, and assigns results to elements in a\n    strided output array using alternative indexing semantics.\n","base.strided.mskunaryDtypeSignatures":"\nbase.strided.mskunaryDtypeSignatures( dtypes1:ArrayLike<any>, \n  dtypes2:ArrayLike<any>[, options:Object] )\n    Generates a list of masked unary interface signatures from strided array\n    data types.\n","base.strided.mskunarySignatureCallbacks":"\nbase.strided.mskunarySignatureCallbacks( table:Object, \n  signatures:ArrayLike<any> )\n    Assigns callbacks to masked unary interfaces according to type promotion\n    rules.\n","base.strided.nanmax":"\nbase.strided.nanmax( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the maximum value of a strided array, ignoring `NaN` values.\n","base.strided.nanmax.ndarray":"\nbase.strided.nanmax.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the maximum value of a strided array, ignoring `NaN` values and\n    using alternative indexing semantics.\n","base.strided.nanmaxabs":"\nbase.strided.nanmaxabs( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the maximum absolute value of a strided array, ignoring `NaN`\n    values.\n","base.strided.nanmaxabs.ndarray":"\nbase.strided.nanmaxabs.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the maximum absolute value of a strided array, ignoring `NaN`\n    values and using alternative indexing semantics.\n","base.strided.nanmaxBy":"\nbase.strided.nanmaxBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n  clbk:Function[, thisArg:any] )\n    Calculates the maximum value of a strided array via a callback function,\n    ignoring `NaN` values.\n","base.strided.nanmaxBy.ndarray":"\nbase.strided.nanmaxBy.ndarray( N:integer, x:Array|TypedArray|Object, \n  stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n    Calculates the maximum value of a strided array via a callback function,\n    ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.nanmean":"\nbase.strided.nanmean( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values.\n","base.strided.nanmean.ndarray":"\nbase.strided.nanmean.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using alternative indexing semantics.\n","base.strided.nanmeanors":"\nbase.strided.nanmeanors( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using ordinary recursive summation.\n","base.strided.nanmeanors.ndarray":"\nbase.strided.nanmeanors.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using ordinary recursive summation and alternative indexing semantics.\n","base.strided.nanmeanpn":"\nbase.strided.nanmeanpn( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using a two-pass error correction algorithm.\n","base.strided.nanmeanpn.ndarray":"\nbase.strided.nanmeanpn.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using a two-pass error correction algorithm and alternative indexing\n    semantics.\n","base.strided.nanmeanwd":"\nbase.strided.nanmeanwd( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using Welford's algorithm.\n","base.strided.nanmeanwd.ndarray":"\nbase.strided.nanmeanwd.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using Welford's algorithm and alternative indexing semantics.\n","base.strided.nanmin":"\nbase.strided.nanmin( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the minimum value of a strided array, ignoring `NaN` values.\n","base.strided.nanmin.ndarray":"\nbase.strided.nanmin.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the minimum value of a strided array, ignoring `NaN` values and\n    using alternative indexing semantics.\n","base.strided.nanminabs":"\nbase.strided.nanminabs( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the minimum absolute value of a strided array, ignoring `NaN`\n    values.\n","base.strided.nanminabs.ndarray":"\nbase.strided.nanminabs.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the minimum absolute value of a strided array, ignoring `NaN`\n    values and using alternative indexing semantics.\n","base.strided.nanminBy":"\nbase.strided.nanminBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n  clbk:Function[, thisArg:any] )\n    Calculates the minimum value of a strided array via a callback function,\n    ignoring `NaN` values.\n","base.strided.nanminBy.ndarray":"\nbase.strided.nanminBy.ndarray( N:integer, x:Array|TypedArray|Object, \n  stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n    Calculates the minimum value of a strided array via a callback function,\n    ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.nanmskmax":"\nbase.strided.nanmskmax( N:integer, x:Array|TypedArray, strideX:integer, \n  mask:Array|TypedArray, strideMask:integer )\n    Computes the maximum value of a strided array according to a mask and\n    ignoring `NaN` values.\n","base.strided.nanmskmax.ndarray":"\nbase.strided.nanmskmax.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n  offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n  offsetMask:integer )\n    Computes the maximum value of a strided array according to a mask,\n    ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.nanmskmin":"\nbase.strided.nanmskmin( N:integer, x:Array|TypedArray, strideX:integer, \n  mask:Array|TypedArray, strideMask:integer )\n    Computes the minimum value of a strided array according to a mask and\n    ignoring `NaN` values.\n","base.strided.nanmskmin.ndarray":"\nbase.strided.nanmskmin.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n  offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n  offsetMask:integer )\n    Computes the minimum value of a strided array according to a mask, ignoring\n    `NaN` values and using alternative indexing semantics.\n","base.strided.nanmskrange":"\nbase.strided.nanmskrange( N:integer, x:Array|TypedArray, strideX:integer, \n  mask:Array|TypedArray, strideMask:integer )\n    Computes the range of a strided array according to a mask and ignoring `NaN`\n    values.\n","base.strided.nanmskrange.ndarray":"\nbase.strided.nanmskrange.ndarray( N:integer, x:Array|TypedArray, \n  strideX:integer, offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n  offsetMask:integer )\n    Computes the range of a strided array according to a mask, ignoring `NaN`\n    values and using alternative indexing semantics.\n","base.strided.nanrange":"\nbase.strided.nanrange( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the range of a strided array, ignoring `NaN` values.\n","base.strided.nanrange.ndarray":"\nbase.strided.nanrange.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the range of a strided array, ignoring `NaN` values and using\n    alternative indexing semantics.\n","base.strided.nanrangeBy":"\nbase.strided.nanrangeBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n  clbk:Function[, thisArg:any] )\n    Calculates the range of a strided array via a callback function, ignoring\n    `NaN` values.\n","base.strided.nanrangeBy.ndarray":"\nbase.strided.nanrangeBy.ndarray( N:integer, x:Array|TypedArray|Object, \n  stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n    Calculates the range of a strided array via a callback function, ignoring\n    `NaN` values and using alternative indexing semantics.\n","base.strided.nanstdev":"\nbase.strided.nanstdev( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values.\n","base.strided.nanstdev.ndarray":"\nbase.strided.nanstdev.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using alternative indexing semantics.\n","base.strided.nanstdevch":"\nbase.strided.nanstdevch( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass trial mean algorithm.\n","base.strided.nanstdevch.ndarray":"\nbase.strided.nanstdevch.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.nanstdevpn":"\nbase.strided.nanstdevpn( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a two-pass algorithm.\n","base.strided.nanstdevpn.ndarray":"\nbase.strided.nanstdevpn.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a two-pass algorithm and alternative indexing semantics.\n","base.strided.nanstdevtk":"\nbase.strided.nanstdevtk( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass textbook algorithm.\n","base.strided.nanstdevtk.ndarray":"\nbase.strided.nanstdevtk.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.nanstdevwd":"\nbase.strided.nanstdevwd( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using Welford's algorithm.\n","base.strided.nanstdevwd.ndarray":"\nbase.strided.nanstdevwd.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using Welford's algorithm and alternative indexing semantics.\n","base.strided.nanstdevyc":"\nbase.strided.nanstdevyc( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.nanstdevyc.ndarray":"\nbase.strided.nanstdevyc.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass algorithm proposed by Youngs and Cramer and alternative\n    indexing semantics.\n","base.strided.nanvariance":"\nbase.strided.nanvariance( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array ignoring `NaN` values.\n","base.strided.nanvariance.ndarray":"\nbase.strided.nanvariance.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using\n    alternative indexing semantics.\n","base.strided.nanvariancech":"\nbase.strided.nanvariancech( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass trial mean algorithm.\n","base.strided.nanvariancech.ndarray":"\nbase.strided.nanvariancech.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.nanvariancepn":"\nbase.strided.nanvariancepn( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    two-pass algorithm.\n","base.strided.nanvariancepn.ndarray":"\nbase.strided.nanvariancepn.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    two-pass algorithm and alternative indexing semantics.\n","base.strided.nanvariancetk":"\nbase.strided.nanvariancetk( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass textbook algorithm.\n","base.strided.nanvariancetk.ndarray":"\nbase.strided.nanvariancetk.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.nanvariancewd":"\nbase.strided.nanvariancewd( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using\n    Welford's algorithm.\n","base.strided.nanvariancewd.ndarray":"\nbase.strided.nanvariancewd.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using\n    Welford's algorithm and alternative indexing semantics.\n","base.strided.nanvarianceyc":"\nbase.strided.nanvarianceyc( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.nanvarianceyc.ndarray":"\nbase.strided.nanvarianceyc.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass algorithm proposed by Youngs and Cramer and alternative indexing\n    semantics.\n","base.strided.nullary":"\nbase.strided.nullary( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  fcn:Function )\n    Applies a nullary callback and assigns results to elements in a strided\n    output array.\n","base.strided.nullary.ndarray":"\nbase.strided.nullary.ndarray( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  offsets:ArrayLikeObject<integer>, fcn:Function )\n    Applies a nullary callback and assigns results to elements in a strided\n    output array using alternative indexing semantics.\n","base.strided.offsetView":"\nbase.strided.offsetView( x:TypedArray, offset:integer )\n    Returns a typed array view having the same data type as a provided input\n    typed array and starting at a specified index offset.\n","base.strided.quaternary":"\nbase.strided.quaternary( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  fcn:Function )\n    Applies a quaternary callback to strided input array elements and assigns\n    results to elements in a strided output array.\n","base.strided.quaternary.ndarray":"\nbase.strided.quaternary.ndarray( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  offsets:ArrayLikeObject<integer>, fcn:Function )\n    Applies a quaternary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n","base.strided.quinary":"\nbase.strided.quinary( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  fcn:Function )\n    Applies a quinary callback to strided input array elements and assigns\n    results to elements in a strided output array.\n","base.strided.quinary.ndarray":"\nbase.strided.quinary.ndarray( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  offsets:ArrayLikeObject<integer>, fcn:Function )\n    Applies a quinary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n","base.strided.range":"\nbase.strided.range( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the range of a strided array.\n","base.strided.range.ndarray":"\nbase.strided.range.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the range of a strided array using alternative indexing semantics.\n","base.strided.rangeBy":"\nbase.strided.rangeBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n  clbk:Function[, thisArg:any] )\n    Calculates the range of a strided array via a callback function.\n","base.strided.rangeBy.ndarray":"\nbase.strided.rangeBy.ndarray( N:integer, x:Array|TypedArray|Object, \n  stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n    Calculates the range of a strided array via a callback function and using\n    alternative indexing semantics.\n","base.strided.reinterpretComplex":"\nbase.strided.reinterpretComplex( x:Complex128Array|Complex64Array, \n  offset:integer )\n    Returns a real-valued floating-point array view of a complex-valued\n    floating-point array having the same precision.\n","base.strided.reinterpretComplex64":"\nbase.strided.reinterpretComplex64( x:Complex64Array, offset:integer )\n    Returns a Float32Array view of a Complex64Array.\n","base.strided.reinterpretComplex128":"\nbase.strided.reinterpretComplex128( x:Complex128Array, offset:integer )\n    Returns a Float64Array view of a Complex128Array.\n","base.strided.sabs":"\nbase.strided.sabs( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer )\n    Computes the absolute value for each element in a single-precision floating-\n    point strided array `x` and assigns the results to elements in a single-\n    precision floating-point strided array `y`.\n","base.strided.sabs.ndarray":"\nbase.strided.sabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the absolute value for each element in a single-precision floating-\n    point strided array `x` and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.sabs2":"\nbase.strided.sabs2( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer )\n    Computes the squared absolute value for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y`.\n","base.strided.sabs2.ndarray":"\nbase.strided.sabs2.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the squared absolute value for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.sapx":"\nbase.strided.sapx( N:integer, alpha:number, x:Float32Array, stride:integer )\n    Adds a constant to each element in a single-precision floating-point strided\n    array.\n","base.strided.sapx.ndarray":"\nbase.strided.sapx.ndarray( N:integer, alpha:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Adds a constant to each element in a single-precision floating-point strided\n    array using alternative indexing semantics.\n","base.strided.sapxsum":"\nbase.strided.sapxsum( N:integer, alpha:number, x:Float32Array, stride:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum.\n","base.strided.sapxsum.ndarray":"\nbase.strided.sapxsum.ndarray( N:integer, alpha:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using alternative indexing semantics.\n","base.strided.sapxsumkbn":"\nbase.strided.sapxsumkbn( N:integer, alpha:number, x:Float32Array, \n  stride:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using an improved Kahan–Babuška algorithm.\n","base.strided.sapxsumkbn.ndarray":"\nbase.strided.sapxsumkbn.ndarray( N:integer, alpha:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n","base.strided.sapxsumkbn2":"\nbase.strided.sapxsumkbn2( N:integer, alpha:number, x:Float32Array, \n  stride:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using a second-order iterative Kahan–Babuška\n    algorithm.\n","base.strided.sapxsumkbn2.ndarray":"\nbase.strided.sapxsumkbn2.ndarray( N:integer, alpha:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n","base.strided.sapxsumors":"\nbase.strided.sapxsumors( N:integer, alpha:number, x:Float32Array, \n  stride:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using ordinary recursive summation.\n","base.strided.sapxsumors.ndarray":"\nbase.strided.sapxsumors.ndarray( N:integer, alpha:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using ordinary recursive summation and\n    alternative indexing semantics.\n","base.strided.sapxsumpw":"\nbase.strided.sapxsumpw( N:integer, alpha:number, x:Float32Array, \n  stride:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using pairwise summation.\n","base.strided.sapxsumpw.ndarray":"\nbase.strided.sapxsumpw.ndarray( N:integer, alpha:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using pairwise summation and alternative\n    indexing semantics.\n","base.strided.sasum":"\nbase.strided.sasum( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of the absolute values.\n","base.strided.sasum.ndarray":"\nbase.strided.sasum.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of absolute values using alternative indexing semantics.\n","base.strided.sasumpw":"\nbase.strided.sasumpw( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of absolute values (L1 norm) of single-precision floating-\n    point strided array elements using pairwise summation.\n","base.strided.sasumpw.ndarray":"\nbase.strided.sasumpw.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of absolute values (L1 norm) of single-precision floating-\n    point strided array elements using pairwise summation and alternative\n    indexing semantics.\n","base.strided.saxpy":"\nbase.strided.saxpy( N:integer, alpha:number, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n","base.strided.saxpy.ndarray":"\nbase.strided.saxpy.ndarray( N:integer, alpha:number, x:Float32Array, \n  strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n  offsetY:integer )\n    Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n    using alternative indexing semantics.\n","base.strided.scbrt":"\nbase.strided.scbrt( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer )\n    Computes the cube root of each element in a single-precision floating-point \n    strided array `x` and assigns the results to elements in a single-precision \n    floating-point strided array `y`.\n","base.strided.scbrt.ndarray":"\nbase.strided.scbrt.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the cube root of each element in a single-precision floating-point \n    strided array `x` and assigns the results to elements in a single-precision \n    floating-point strided array `y` using alternative indexing semantics.\n","base.strided.sceil":"\nbase.strided.sceil( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward positive infinity and assigns the results to elements in a single-\n    precision floating-point strided array `y`.\n","base.strided.sceil.ndarray":"\nbase.strided.sceil.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward positive infinity and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.scopy":"\nbase.strided.scopy( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer )\n    Copies values from `x` into `y`.\n","base.strided.scopy.ndarray":"\nbase.strided.scopy.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Copies values from `x` into `y` using alternative indexing semantics.\n","base.strided.scumax":"\nbase.strided.scumax( N:integer, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Computes the cumulative maximum of single-precision floating-point strided\n    array elements.\n","base.strided.scumax.ndarray":"\nbase.strided.scumax.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the cumulative maximum of single-precision floating-point strided\n    array elements using alternative indexing semantics.\n","base.strided.scumaxabs":"\nbase.strided.scumaxabs( N:integer, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Computes the cumulative maximum absolute value of single-precision floating-\n    point strided array elements.\n","base.strided.scumaxabs.ndarray":"\nbase.strided.scumaxabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the cumulative maximum absolute value of single-precision floating-\n    point strided array elements using alternative indexing semantics.\n","base.strided.scumin":"\nbase.strided.scumin( N:integer, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Computes the cumulative minimum of single-precision floating-point strided\n    array elements.\n","base.strided.scumin.ndarray":"\nbase.strided.scumin.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the cumulative minimum of single-precision floating-point strided\n    array elements using alternative indexing semantics.\n","base.strided.scuminabs":"\nbase.strided.scuminabs( N:integer, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Computes the cumulative minimum absolute value of single-precision floating-\n    point strided array elements.\n","base.strided.scuminabs.ndarray":"\nbase.strided.scuminabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the cumulative minimum absolute value of single-precision floating-\n    point strided array elements using alternative indexing semantics.\n","base.strided.scusum":"\nbase.strided.scusum( N:integer, sum:number, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements.\n","base.strided.scusum.ndarray":"\nbase.strided.scusum.ndarray( N:integer, sum:number, x:Float32Array, \n  strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using alternative indexing semantics.\n","base.strided.scusumkbn":"\nbase.strided.scusumkbn( N:integer, sum:number, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using an improved Kahan–Babuška algorithm.\n","base.strided.scusumkbn.ndarray":"\nbase.strided.scusumkbn.ndarray( N:integer, sum:number, x:Float32Array, \n  strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n","base.strided.scusumkbn2":"\nbase.strided.scusumkbn2( N:integer, sum:number, x:Float32Array, \n  strideX:integer, y:Float32Array, strideY:integer )\n    Computes the cumulative sum of single-precision floating-point strided \n    array elements using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.scusumkbn2.ndarray":"\nbase.strided.scusumkbn2.ndarray( N:integer, sum:number, x:Float32Array, \n  strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of single-precision floating-point strided\n    array elements using a second-order iterative Kahan–Babuška algorithm and\n    alternative indexing semantics.\n","base.strided.scusumors":"\nbase.strided.scusumors( N:integer, sum:number, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using ordinary recursive summation.\n","base.strided.scusumors.ndarray":"\nbase.strided.scusumors.ndarray( N:integer, sum:number, x:Float32Array, \n  strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using ordinary recursive summation and alternative indexing\n    semantics.\n","base.strided.scusumpw":"\nbase.strided.scusumpw( N:integer, sum:number, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using pairwise summation.\n","base.strided.scusumpw.ndarray":"\nbase.strided.scusumpw.ndarray( N:integer, sum:number, x:Float32Array, \n  strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using pairwise summation and alternative indexing semantics.\n","base.strided.sdeg2rad":"\nbase.strided.sdeg2rad( N:integer, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Converts each element in a single-precision floating-point strided array `x`\n    from degrees to radians and assigns the results to elements in a single-\n    precision floating-point strided array `y`.\n","base.strided.sdeg2rad.ndarray":"\nbase.strided.sdeg2rad.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Converts each element in a single-precision floating-point strided array `x`\n    from degrees to radians and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.sdot":"\nbase.strided.sdot( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer )\n    Computes the dot product of two single-precision floating-point vectors.\n","base.strided.sdot.ndarray":"\nbase.strided.sdot.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the dot product of two single-precision floating-point vectors\n    using alternative indexing semantics.\n","base.strided.sdsapxsum":"\nbase.strided.sdsapxsum( N:integer, alpha:number, x:Float32Array, \n  stride:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using extended accumulation.\n","base.strided.sdsapxsum.ndarray":"\nbase.strided.sdsapxsum.ndarray( N:integer, alpha:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using extended accumulation and alternative\n    indexing semantics.\n","base.strided.sdsapxsumpw":"\nbase.strided.sdsapxsumpw( N:integer, alpha:number, x:Float32Array, \n  stride:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using pairwise summation with extended\n    accumulation.\n","base.strided.sdsapxsumpw.ndarray":"\nbase.strided.sdsapxsumpw.ndarray( N:integer, alpha:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using pairwise summation with extended\n    accumulation and alternative indexing semantics.\n","base.strided.sdsdot":"\nbase.strided.sdsdot( N:integer, scalar:number, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Computes the dot product of two single-precision floating-point vectors with\n    extended accumulation.\n","base.strided.sdsdot.ndarray":"\nbase.strided.sdsdot.ndarray( N:integer, scalar:number, x:Float32Array, \n  strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n  offsetY:integer )\n    Computes the dot product of two single-precision floating-point vectors\n    using alternative indexing semantics and with extended accumulation.\n","base.strided.sdsmean":"\nbase.strided.sdsmean( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using extended accumulation.\n","base.strided.sdsmean.ndarray":"\nbase.strided.sdsmean.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using extended accumulation and alternative indexing semantics.\n","base.strided.sdsmeanors":"\nbase.strided.sdsmeanors( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation with extended accumulation.\n","base.strided.sdsmeanors.ndarray":"\nbase.strided.sdsmeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation with extended accumulation and\n    alternative indexing semantics.\n","base.strided.sdsnanmean":"\nbase.strided.sdsnanmean( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using extended accumulation.\n","base.strided.sdsnanmean.ndarray":"\nbase.strided.sdsnanmean.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using extended accumulation and alternative\n    indexing semantics.\n","base.strided.sdsnanmeanors":"\nbase.strided.sdsnanmeanors( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation with\n    extended accumulation.\n","base.strided.sdsnanmeanors.ndarray":"\nbase.strided.sdsnanmeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation with\n    extended accumulation and alternative indexing semantics.\n","base.strided.sdsnansum":"\nbase.strided.sdsnansum( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of single-precision floating-point strided array\n    elements, ignore `NaN` values and using extended accumulation.\n","base.strided.sdsnansum.ndarray":"\nbase.strided.sdsnansum.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using extended accumulation and alternative\n    indexing semantics.\n","base.strided.sdsnansumpw":"\nbase.strided.sdsnansumpw( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation with extended\n    accumulation.\n","base.strided.sdsnansumpw.ndarray":"\nbase.strided.sdsnansumpw.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation with extended\n    accumulation and alternative indexing semantics.\n","base.strided.sdssum":"\nbase.strided.sdssum( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using extended accumulation.\n","base.strided.sdssum.ndarray":"\nbase.strided.sdssum.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using extended accumulation and alternative indexing semantics.\n","base.strided.sdssumpw":"\nbase.strided.sdssumpw( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation with extended accumulation.\n","base.strided.sdssumpw.ndarray":"\nbase.strided.sdssumpw.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation with extended accumulation and alternative indexing\n    semantics.\n","base.strided.sfill":"\nbase.strided.sfill( N:integer, alpha:number, x:Float32Array, strideX:integer )\n    Fills a single-precision floating-point strided array with a specified\n    scalar value.\n","base.strided.sfill.ndarray":"\nbase.strided.sfill.ndarray( N:integer, alpha:number, x:Float32Array, \n  strideX:integer, offsetX:integer )\n    Fills a single-precision floating-point strided array with a specified\n    scalar value using alternative indexing semantics.\n","base.strided.sfloor":"\nbase.strided.sfloor( N:integer, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward negative infinity and assigns the results to elements in a single-\n    precision floating-point strided array `y`.\n","base.strided.sfloor.ndarray":"\nbase.strided.sfloor.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward negative infinity and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.sinv":"\nbase.strided.sinv( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer )\n    Computes the multiplicative inverse for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y`.\n","base.strided.sinv.ndarray":"\nbase.strided.sinv.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the multiplicative inverse for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.smap":"\nbase.strided.smap( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer, fcn:Function )\n    Applies a unary function to a single-precision floating-point strided input\n    array and assigns results to a single-precision floating-point strided\n    output array.\n","base.strided.smap.ndarray":"\nbase.strided.smap.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer, \n  fcn:Function )\n    Applies a unary function to a single-precision floating-point strided input\n    array and assigns results to a single-precision floating-point strided\n    output array using alternative indexing semantics.\n","base.strided.smap2":"\nbase.strided.smap2( N:integer, x:Float32Array, sx:integer, y:Float32Array, \n  sy:integer, z:Float32Array, sz:integer, fcn:Function )\n    Applies a binary function to single-precision floating-point strided input\n    arrays and assigns results to a single-precision floating-point strided\n    output array.\n","base.strided.smap2.ndarray":"\nbase.strided.smap2.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, \n  y:Float32Array, sy:integer, oy:integer, z:Float32Array, sz:integer, \n  oz:integer, fcn:Function )\n    Applies a binary function to single-precision floating-point strided input\n    arrays and assigns results to a single-precision floating-point strided\n    output array using alternative indexing semantics.\n","base.strided.smax":"\nbase.strided.smax( N:integer, x:Float32Array, strideX:integer )\n    Computes the maximum value of a single-precision floating-point strided\n    array.\n","base.strided.smax.ndarray":"\nbase.strided.smax.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum value of a single-precision floating-point strided\n    array using alternative indexing semantics.\n","base.strided.smaxabs":"\nbase.strided.smaxabs( N:integer, x:Float32Array, strideX:integer )\n    Computes the maximum absolute value of a single-precision floating-point\n    strided array.\n","base.strided.smaxabs.ndarray":"\nbase.strided.smaxabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum absolute value of a single-precision floating-point\n    strided array using alternative indexing semantics.\n","base.strided.smaxabssorted":"\nbase.strided.smaxabssorted( N:integer, x:Float32Array, strideX:integer )\n    Computes the maximum absolute value of a sorted single-precision floating-\n    point strided array.\n","base.strided.smaxabssorted.ndarray":"\nbase.strided.smaxabssorted.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum absolute value of a sorted single-precision floating-\n    point strided array using alternative indexing semantics.\n","base.strided.smaxsorted":"\nbase.strided.smaxsorted( N:integer, x:Float32Array, strideX:integer )\n    Computes the maximum value of a sorted single-precision floating-point\n    strided array.\n","base.strided.smaxsorted.ndarray":"\nbase.strided.smaxsorted.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n","base.strided.smean":"\nbase.strided.smean( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array.\n","base.strided.smean.ndarray":"\nbase.strided.smean.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using alternative indexing semantics.\n","base.strided.smeankbn":"\nbase.strided.smeankbn( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm.\n","base.strided.smeankbn.ndarray":"\nbase.strided.smeankbn.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n","base.strided.smeankbn2":"\nbase.strided.smeankbn2( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.smeankbn2.ndarray":"\nbase.strided.smeankbn2.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n","base.strided.smeanli":"\nbase.strided.smeanli( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm.\n","base.strided.smeanli.ndarray":"\nbase.strided.smeanli.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n","base.strided.smeanlipw":"\nbase.strided.smeanlipw( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm with pairwise summation.\n","base.strided.smeanlipw.ndarray":"\nbase.strided.smeanlipw.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm with pairwise summation and\n    alternative indexing semantics.\n","base.strided.smeanors":"\nbase.strided.smeanors( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation.\n","base.strided.smeanors.ndarray":"\nbase.strided.smeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation and alternative indexing semantics.\n","base.strided.smeanpn":"\nbase.strided.smeanpn( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a two-pass error correction algorithm.\n","base.strided.smeanpn.ndarray":"\nbase.strided.smeanpn.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a two-pass error correction algorithm and alternative indexing\n    semantics.\n","base.strided.smeanpw":"\nbase.strided.smeanpw( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using pairwise summation.\n","base.strided.smeanpw.ndarray":"\nbase.strided.smeanpw.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using pairwise summation and alternative indexing semantics.\n","base.strided.smeanwd":"\nbase.strided.smeanwd( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using Welford's algorithm.\n","base.strided.smeanwd.ndarray":"\nbase.strided.smeanwd.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n","base.strided.smediansorted":"\nbase.strided.smediansorted( N:integer, x:Float32Array, stride:integer )\n    Computes the median value of a sorted single-precision floating-point\n    strided array.\n","base.strided.smediansorted.ndarray":"\nbase.strided.smediansorted.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the median value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n","base.strided.smidrange":"\nbase.strided.smidrange( N:integer, x:Float32Array, strideX:integer )\n    Computes the mid-range of a single-precision floating-point strided array.\n","base.strided.smidrange.ndarray":"\nbase.strided.smidrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the mid-range of a single-precision floating-point strided array\n    using alternative indexing semantics.\n","base.strided.smin":"\nbase.strided.smin( N:integer, x:Float32Array, strideX:integer )\n    Computes the minimum value of a single-precision floating-point strided\n    array.\n","base.strided.smin.ndarray":"\nbase.strided.smin.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the minimum value of a single-precision floating-point strided\n    array using alternative indexing semantics.\n","base.strided.sminabs":"\nbase.strided.sminabs( N:integer, x:Float32Array, strideX:integer )\n    Computes the minimum absolute value of a single-precision floating-point\n    strided array.\n","base.strided.sminabs.ndarray":"\nbase.strided.sminabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the minimum absolute value of a single-precision floating-point\n    strided array using alternative indexing semantics.\n","base.strided.sminsorted":"\nbase.strided.sminsorted( N:integer, x:Float32Array, stride:integer )\n    Computes the minimum value of a sorted single-precision floating-point\n    strided array.\n","base.strided.sminsorted.ndarray":"\nbase.strided.sminsorted.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the minimum value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n","base.strided.smskabs":"\nbase.strided.smskabs( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Computes the absolute value for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskabs.ndarray":"\nbase.strided.smskabs.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n  sy:integer, oy:integer )\n    Computes the absolute value for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n","base.strided.smskabs2":"\nbase.strided.smskabs2( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Computes the squared absolute value for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point\n    strided array `y`.\n","base.strided.smskabs2.ndarray":"\nbase.strided.smskabs2.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n  sy:integer, oy:integer )\n    Computes the squared absolute value for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point\n    strided array `y` using alternative indexing semantics.\n","base.strided.smskcbrt":"\nbase.strided.smskcbrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Computes the cube root for each element in a single-precision floating-point\n    strided array `x` according to a strided mask array and assigns the results\n    to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskcbrt.ndarray":"\nbase.strided.smskcbrt.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n  sy:integer, oy:integer )\n    Computes the cube root for each element in a single-precision floating-point\n    strided array `x` according to a strided mask array and assigns the results\n    to elements in a single-precision floating-point strided array `y` using\n    alternative indexing semantics.\n","base.strided.smskceil":"\nbase.strided.smskceil( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward positive infinity according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskceil.ndarray":"\nbase.strided.smskceil.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n  sy:integer, oy:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward positive infinity according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n","base.strided.smskdeg2rad":"\nbase.strided.smskdeg2rad( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Converts each element in a single-precision floating-point strided array `x`\n    from degrees to radians according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskdeg2rad.ndarray":"\nbase.strided.smskdeg2rad.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n  sy:integer, oy:integer )\n    Converts each element in a single-precision floating-point strided array `x`\n    from degrees to radians according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n","base.strided.smskfloor":"\nbase.strided.smskfloor( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward negative infinity according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskfloor.ndarray":"\nbase.strided.smskfloor.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n  sy:integer, oy:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward negative infinity according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n","base.strided.smskinv":"\nbase.strided.smskinv( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Computes the multiplicative inverse for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y`.\n","base.strided.smskinv.ndarray":"\nbase.strided.smskinv.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n  sy:integer, oy:integer )\n    Computes the multiplicative inverse for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y` using alternative indexing semantics.\n","base.strided.smskmap":"\nbase.strided.smskmap( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer, fcn:Function )\n    Applies a unary function to a single-precision floating-point strided input\n    array according to a strided mask array and assigns results to a single-\n    precision floating-point strided output array.\n","base.strided.smskmap.ndarray":"\nbase.strided.smskmap.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Uint8Array, sm:integer, om:integer, y:Float32Array, sy:integer, \n  oy:integer, fcn:Function )\n    Applies a unary function to a single-precision floating-point strided input\n    array according to a strided mask array and assigns results to a single-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n","base.strided.smskmap2":"\nbase.strided.smskmap2( N:integer, x:Float32Array, sx:integer, y:Float32Array, \n  sy:integer, m:Uint8Array, sm:integer, z:Float32Array, sz:integer, \n  fcn:Function )\n    Applies a binary function to single-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a single-\n    precision floating-point strided output array.\n","base.strided.smskmap2.ndarray":"\nbase.strided.smskmap2.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, y:Float32Array, sy:integer, oy:integer, m:Uint8Array, sm:integer, \n  om:integer, z:Float32Array, sz:integer, oz:integer, fcn:Function )\n    Applies a binary function to single-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a single-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n","base.strided.smskmax":"\nbase.strided.smskmax( N:integer, x:Float32Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask.\n","base.strided.smskmax.ndarray":"\nbase.strided.smskmax.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n","base.strided.smskmin":"\nbase.strided.smskmin( N:integer, x:Float32Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask.\n","base.strided.smskmin.ndarray":"\nbase.strided.smskmin.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n","base.strided.smskramp":"\nbase.strided.smskramp( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Evaluates the ramp function for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskramp.ndarray":"\nbase.strided.smskramp.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n  sy:integer, oy:integer )\n    Evaluates the ramp function for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n","base.strided.smskrange":"\nbase.strided.smskrange( N:integer, x:Float32Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask.\n","base.strided.smskrange.ndarray":"\nbase.strided.smskrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask and using alternative indexing semantics.\n","base.strided.smskrsqrt":"\nbase.strided.smskrsqrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Computes the reciprocal square root for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y`.\n","base.strided.smskrsqrt.ndarray":"\nbase.strided.smskrsqrt.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n  sy:integer, oy:integer )\n    Computes the reciprocal square root for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y` using alternative indexing semantics.\n","base.strided.smsksqrt":"\nbase.strided.smsksqrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Computes the principal square root for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y`.\n","base.strided.smsksqrt.ndarray":"\nbase.strided.smsksqrt.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n  sy:integer, oy:integer )\n    Computes the principal square root for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y` using alternative indexing semantics.\n","base.strided.smsktrunc":"\nbase.strided.smsktrunc( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward zero according to a strided mask array and assigns the results to\n    elements in a single-precision floating-point strided array `y`.\n","base.strided.smsktrunc.ndarray":"\nbase.strided.smsktrunc.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n  sy:integer, oy:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward zero according to a strided mask array and assigns the results to\n    elements in a single-precision floating-point strided array `y` using\n    alternative indexing semantics.\n","base.strided.snanmax":"\nbase.strided.snanmax( N:integer, x:Float32Array, strideX:integer )\n    Computes the maximum value of a single-precision floating-point strided\n    array, ignoring `NaN` values.\n","base.strided.snanmax.ndarray":"\nbase.strided.snanmax.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum value of a single-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanmaxabs":"\nbase.strided.snanmaxabs( N:integer, x:Float32Array, strideX:integer )\n    Computes the maximum absolute value of a single-precision floating-point\n    strided array, ignoring `NaN` values.\n","base.strided.snanmaxabs.ndarray":"\nbase.strided.snanmaxabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum absolute value of a single-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n","base.strided.snanmean":"\nbase.strided.snanmean( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values.\n","base.strided.snanmean.ndarray":"\nbase.strided.snanmean.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanmeanors":"\nbase.strided.snanmeanors( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.snanmeanors.ndarray":"\nbase.strided.snanmeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation and\n    alternative indexing semantics.\n","base.strided.snanmeanpn":"\nbase.strided.snanmeanpn( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction\n    algorithm.\n","base.strided.snanmeanpn.ndarray":"\nbase.strided.snanmeanpn.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction algorithm\n    and alternative indexing semantics.\n","base.strided.snanmeanwd":"\nbase.strided.snanmeanwd( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm.\n","base.strided.snanmeanwd.ndarray":"\nbase.strided.snanmeanwd.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n","base.strided.snanmin":"\nbase.strided.snanmin( N:integer, x:Float32Array, strideX:integer )\n    Computes the minimum value of a single-precision floating-point strided\n    array, ignoring `NaN` values.\n","base.strided.snanmin.ndarray":"\nbase.strided.snanmin.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the minimum value of a single-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanminabs":"\nbase.strided.snanminabs( N:integer, x:Float32Array, strideX:integer )\n    Computes the minimum absolute value of a single-precision floating-point\n    strided array, ignoring `NaN` values.\n","base.strided.snanminabs.ndarray":"\nbase.strided.snanminabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the minimum absolute value of a single-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n","base.strided.snanmskmax":"\nbase.strided.snanmskmax( N:integer, x:Float32Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask, ignoring `NaN` values.\n","base.strided.snanmskmax.ndarray":"\nbase.strided.snanmskmax.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n","base.strided.snanmskmin":"\nbase.strided.snanmskmin( N:integer, x:Float32Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask, ignoring `NaN` values.\n","base.strided.snanmskmin.ndarray":"\nbase.strided.snanmskmin.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n","base.strided.snanmskrange":"\nbase.strided.snanmskrange( N:integer, x:Float32Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask, ignoring `NaN` values.\n","base.strided.snanmskrange.ndarray":"\nbase.strided.snanmskrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask, ignoring `NaN` values and using alternative indexing\n    semantics.\n","base.strided.snanrange":"\nbase.strided.snanrange( N:integer, x:Float32Array, strideX:integer )\n    Computes the range of a single-precision floating-point strided array,\n    ignoring `NaN` values.\n","base.strided.snanrange.ndarray":"\nbase.strided.snanrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the range of a single-precision floating-point strided array,\n    ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanstdev":"\nbase.strided.snanstdev( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values.\n","base.strided.snanstdev.ndarray":"\nbase.strided.snanstdev.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and alternative indexing semantics.\n","base.strided.snanstdevch":"\nbase.strided.snanstdevch( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.snanstdevch.ndarray":"\nbase.strided.snanstdevch.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n","base.strided.snanstdevpn":"\nbase.strided.snanstdevpn( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.snanstdevpn.ndarray":"\nbase.strided.snanstdevpn.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n","base.strided.snanstdevtk":"\nbase.strided.snanstdevtk( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.snanstdevtk.ndarray":"\nbase.strided.snanstdevtk.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n","base.strided.snanstdevwd":"\nbase.strided.snanstdevwd( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using Welford's algorithm.\n","base.strided.snanstdevwd.ndarray":"\nbase.strided.snanstdevwd.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n","base.strided.snanstdevyc":"\nbase.strided.snanstdevyc( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass algorithm proposed by\n    Youngs and Cramer.\n","base.strided.snanstdevyc.ndarray":"\nbase.strided.snanstdevyc.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass algorithm proposed by\n    Youngs and Cramer and alternative indexing semantics.\n","base.strided.snansum":"\nbase.strided.snansum( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values.\n","base.strided.snansum.ndarray":"\nbase.strided.snansum.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snansumkbn":"\nbase.strided.snansumkbn( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n","base.strided.snansumkbn.ndarray":"\nbase.strided.snansumkbn.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n","base.strided.snansumkbn2":"\nbase.strided.snansumkbn2( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm.\n","base.strided.snansumkbn2.ndarray":"\nbase.strided.snansumkbn2.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n","base.strided.snansumors":"\nbase.strided.snansumors( N:integer, x:Float32Array, strideX:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.snansumors.ndarray":"\nbase.strided.snansumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation and alternative\n    indexing semantics.\n","base.strided.snansumpw":"\nbase.strided.snansumpw( N:integer, x:Float32Array, strideX:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation.\n","base.strided.snansumpw.ndarray":"\nbase.strided.snansumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation and alternative indexing\n    semantics.\n","base.strided.snanvariance":"\nbase.strided.snanvariance( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values.\n","base.strided.snanvariance.ndarray":"\nbase.strided.snanvariance.ndarray( N:integer, correction:number, \n  x:Float32Array, stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanvariancech":"\nbase.strided.snanvariancech( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.snanvariancech.ndarray":"\nbase.strided.snanvariancech.ndarray( N:integer, correction:number, \n  x:Float32Array, stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n","base.strided.snanvariancepn":"\nbase.strided.snanvariancepn( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.snanvariancepn.ndarray":"\nbase.strided.snanvariancepn.ndarray( N:integer, correction:number, \n  x:Float32Array, stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n","base.strided.snanvariancetk":"\nbase.strided.snanvariancetk( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.snanvariancetk.ndarray":"\nbase.strided.snanvariancetk.ndarray( N:integer, correction:number, \n  x:Float32Array, stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n","base.strided.snanvariancewd":"\nbase.strided.snanvariancewd( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using Welford's algorithm.\n","base.strided.snanvariancewd.ndarray":"\nbase.strided.snanvariancewd.ndarray( N:integer, correction:number, \n  x:Float32Array, stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using Welford's algorithm and alternative indexing\n    semantics.\n","base.strided.snanvarianceyc":"\nbase.strided.snanvarianceyc( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n    Cramer.\n","base.strided.snanvarianceyc.ndarray":"\nbase.strided.snanvarianceyc.ndarray( N:integer, correction:number, \n  x:Float32Array, stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n    Cramer and alternative indexing semantics.\n","base.strided.snrm2":"\nbase.strided.snrm2( N:integer, x:Float32Array, stride:integer )\n    Computes the L2-norm of a single-precision floating-point vector.\n","base.strided.snrm2.ndarray":"\nbase.strided.snrm2.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the L2-norm of a single-precision floating-point vector using\n    alternative indexing semantics.\n","base.strided.sramp":"\nbase.strided.sramp( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer )\n    Evaluates the ramp function for each element in a single-precision floating-\n    point strided array `x` and assigns the results to elements in a single-\n    precision floating-point strided array `y`.\n","base.strided.sramp.ndarray":"\nbase.strided.sramp.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Evaluates the ramp function for each element in a single-precision floating-\n    point strided array `x` and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.srange":"\nbase.strided.srange( N:integer, x:Float32Array, strideX:integer )\n    Computes the range of a single-precision floating-point strided array.\n","base.strided.srange.ndarray":"\nbase.strided.srange.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the range of a single-precision floating-point strided array using\n    alternative indexing semantics.\n","base.strided.srev":"\nbase.strided.srev( N:integer, x:Float32Array, stride:integer )\n    Reverses a single-precision floating-point strided array in-place.\n","base.strided.srev.ndarray":"\nbase.strided.srev.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Reverses a single-precision floating-point strided array in-place using\n    alternative indexing semantics.\n","base.strided.srsqrt":"\nbase.strided.srsqrt( N:integer, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Computes the reciprocal square root for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y`.\n","base.strided.srsqrt.ndarray":"\nbase.strided.srsqrt.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the reciprocal square root for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.sscal":"\nbase.strided.sscal( N:integer, alpha:number, x:Float32Array, stride:integer )\n    Multiplies a single-precision floating-point vector `x` by a constant\n    `alpha`.\n","base.strided.sscal.ndarray":"\nbase.strided.sscal.ndarray( N:integer, alpha:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Multiplies a single-precision floating-point vector `x` by a constant\n    `alpha` using alternative indexing semantics.\n","base.strided.ssort2hp":"\nbase.strided.ssort2hp( N:integer, order:number, x:Float32Array, \n  strideX:integer, y:Float32Array, strideY:integer )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using heapsort.\n","base.strided.ssort2hp.ndarray":"\nbase.strided.ssort2hp.ndarray( N:integer, order:number, x:Float32Array, \n  strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n  offsetY:integer )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using heapsort and alternative\n    indexing semantics.\n","base.strided.ssort2ins":"\nbase.strided.ssort2ins( N:integer, order:number, x:Float32Array, \n  strideX:integer, y:Float32Array, strideY:integer )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using insertion sort.\n","base.strided.ssort2ins.ndarray":"\nbase.strided.ssort2ins.ndarray( N:integer, order:number, x:Float32Array, \n  strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n  offsetY:integer )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using insertion sort and\n    alternative indexing semantics.\n","base.strided.ssort2sh":"\nbase.strided.ssort2sh( N:integer, order:number, x:Float32Array, \n  strideX:integer, y:Float32Array, strideY:integer )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using Shellsort.\n","base.strided.ssort2sh.ndarray":"\nbase.strided.ssort2sh.ndarray( N:integer, order:number, x:Float32Array, \n  strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n  offsetY:integer )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using Shellsort and alternative\n    indexing semantics.\n","base.strided.ssorthp":"\nbase.strided.ssorthp( N:integer, order:number, x:Float32Array, stride:integer )\n    Sorts a single-precision floating-point strided array using heapsort.\n","base.strided.ssorthp.ndarray":"\nbase.strided.ssorthp.ndarray( N:integer, order:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Sorts a single-precision floating-point strided array using heapsort and\n    alternative indexing semantics.\n","base.strided.ssortins":"\nbase.strided.ssortins( N:integer, order:number, x:Float32Array, stride:integer )\n    Sorts a single-precision floating-point strided array using insertion sort.\n","base.strided.ssortins.ndarray":"\nbase.strided.ssortins.ndarray( N:integer, order:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Sorts a single-precision floating-point strided array using insertion sort\n    and alternative indexing semantics.\n","base.strided.ssortsh":"\nbase.strided.ssortsh( N:integer, order:number, x:Float32Array, stride:integer )\n    Sorts a single-precision floating-point strided array using Shellsort.\n","base.strided.ssortsh.ndarray":"\nbase.strided.ssortsh.ndarray( N:integer, order:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Sorts a single-precision floating-point strided array using Shellsort and\n    alternative indexing semantics.\n","base.strided.ssqrt":"\nbase.strided.ssqrt( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer )\n    Computes the principal square root for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y`.\n","base.strided.ssqrt.ndarray":"\nbase.strided.ssqrt.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the principal square root for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.sstdev":"\nbase.strided.sstdev( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array.\n","base.strided.sstdev.ndarray":"\nbase.strided.sstdev.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using alternative indexing semantics.\n","base.strided.sstdevch":"\nbase.strided.sstdevch( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm.\n","base.strided.sstdevch.ndarray":"\nbase.strided.sstdevch.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n","base.strided.sstdevpn":"\nbase.strided.sstdevpn( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a two-pass algorithm.\n","base.strided.sstdevpn.ndarray":"\nbase.strided.sstdevpn.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a two-pass algorithm and alternative indexing semantics.\n","base.strided.sstdevtk":"\nbase.strided.sstdevtk( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass textbook algorithm.\n","base.strided.sstdevtk.ndarray":"\nbase.strided.sstdevtk.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass textbook algorithm and alternative indexing\n    semantics.\n","base.strided.sstdevwd":"\nbase.strided.sstdevwd( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using Welford's algorithm.\n","base.strided.sstdevwd.ndarray":"\nbase.strided.sstdevwd.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n","base.strided.sstdevyc":"\nbase.strided.sstdevyc( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.sstdevyc.ndarray":"\nbase.strided.sstdevyc.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer and\n    alternative indexing semantics.\n","base.strided.ssum":"\nbase.strided.ssum( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of single-precision floating-point strided array elements.\n","base.strided.ssum.ndarray":"\nbase.strided.ssum.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using alternative indexing semantics.\n","base.strided.ssumkbn":"\nbase.strided.ssumkbn( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm.\n","base.strided.ssumkbn.ndarray":"\nbase.strided.ssumkbn.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n","base.strided.ssumkbn2":"\nbase.strided.ssumkbn2( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.ssumkbn2.ndarray":"\nbase.strided.ssumkbn2.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n","base.strided.ssumors":"\nbase.strided.ssumors( N:integer, x:Float32Array, strideX:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using ordinary recursive summation.\n","base.strided.ssumors.ndarray":"\nbase.strided.ssumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using ordinary recursive summation and alternative indexing semantics.\n","base.strided.ssumpw":"\nbase.strided.ssumpw( N:integer, x:Float32Array, strideX:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation.\n","base.strided.ssumpw.ndarray":"\nbase.strided.ssumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation and alternative indexing semantics.\n","base.strided.sswap":"\nbase.strided.sswap( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer )\n    Interchanges two single-precision floating-point vectors.\n","base.strided.sswap.ndarray":"\nbase.strided.sswap.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Interchanges two single-precision floating-point vectors using alternative\n    indexing semantics.\n","base.strided.stdev":"\nbase.strided.stdev( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array.\n","base.strided.stdev.ndarray":"\nbase.strided.stdev.ndarray( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a strided array using alternative\n    indexing semantics.\n","base.strided.stdevch":"\nbase.strided.stdevch( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array using a one-pass trial\n    mean algorithm.\n","base.strided.stdevch.ndarray":"\nbase.strided.stdevch.ndarray( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a strided array using a one-pass trial\n    mean algorithm and alternative indexing semantics.\n","base.strided.stdevpn":"\nbase.strided.stdevpn( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array using a two-pass\n    algorithm.\n","base.strided.stdevpn.ndarray":"\nbase.strided.stdevpn.ndarray( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a strided array using a two-pass\n    algorithm and alternative indexing semantics.\n","base.strided.stdevtk":"\nbase.strided.stdevtk( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array using a one-pass textbook\n    algorithm.\n","base.strided.stdevtk.ndarray":"\nbase.strided.stdevtk.ndarray( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a strided array using a one-pass textbook\n    algorithm and alternative indexing semantics.\n","base.strided.stdevwd":"\nbase.strided.stdevwd( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array using Welford's\n    algorithm.\n","base.strided.stdevwd.ndarray":"\nbase.strided.stdevwd.ndarray( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a strided array using Welford's algorithm\n    and alternative indexing semantics.\n","base.strided.stdevyc":"\nbase.strided.stdevyc( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array using a one-pass\n    algorithm proposed by Youngs and Cramer.\n","base.strided.stdevyc.ndarray":"\nbase.strided.stdevyc.ndarray( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a strided array using a one-pass\n    algorithm proposed by Youngs and Cramer and alternative indexing semantics.\n","base.strided.strunc":"\nbase.strided.strunc( N:integer, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward zero and assigns the results to elements in a single-precision\n    floating-point strided array `y`.\n","base.strided.strunc.ndarray":"\nbase.strided.strunc.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward zero and assigns the results to elements in a single-precision\n    floating-point strided array `y` using alternative indexing semantics.\n","base.strided.svariance":"\nbase.strided.svariance( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array.\n","base.strided.svariance.ndarray":"\nbase.strided.svariance.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using alternative indexing semantics.\n","base.strided.svariancech":"\nbase.strided.svariancech( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass trial mean algorithm.\n","base.strided.svariancech.ndarray":"\nbase.strided.svariancech.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.svariancepn":"\nbase.strided.svariancepn( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using a two-pass algorithm.\n","base.strided.svariancepn.ndarray":"\nbase.strided.svariancepn.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using a two-pass algorithm and alternative indexing semantics.\n","base.strided.svariancetk":"\nbase.strided.svariancetk( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass textbook algorithm.\n","base.strided.svariancetk.ndarray":"\nbase.strided.svariancetk.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.svariancewd":"\nbase.strided.svariancewd( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using Welford's algorithm.\n","base.strided.svariancewd.ndarray":"\nbase.strided.svariancewd.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using Welford's algorithm and alternative indexing semantics.\n","base.strided.svarianceyc":"\nbase.strided.svarianceyc( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.svarianceyc.ndarray":"\nbase.strided.svarianceyc.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass algorithm proposed by Youngs and Cramer and alternative\n    indexing semantics.\n","base.strided.ternary":"\nbase.strided.ternary( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  fcn:Function )\n    Applies a ternary callback to strided input array elements and assigns\n    results to elements in a strided output array.\n","base.strided.ternary.ndarray":"\nbase.strided.ternary.ndarray( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  offsets:ArrayLikeObject<integer>, fcn:Function )\n    Applies a ternary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n","base.strided.unary":"\nbase.strided.unary( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  fcn:Function )\n    Applies a unary callback to elements in a strided input array and assigns\n    results to elements in a strided output array.\n","base.strided.unary.ndarray":"\nbase.strided.unary.ndarray( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  offsets:ArrayLikeObject<integer>, fcn:Function )\n    Applies a unary callback to elements in a strided input array and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n","base.strided.unaryBy":"\nbase.strided.unaryBy( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  fcn:Function, clbk:Function[, thisArg:any] )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array.\n","base.strided.unaryBy.ndarray":"\nbase.strided.unaryBy.ndarray( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  offsets:ArrayLikeObject<integer>, fcn:Function, clbk:Function[, thisArg:any] )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array using alternative indexing semantics.\n","base.strided.unaryDtypeSignatures":"\nbase.strided.unaryDtypeSignatures( dtypes1:ArrayLike<any>, \n  dtypes2:ArrayLike<any>[, options:Object] )\n    Generates a list of unary interface signatures from strided array data\n    types.\n","base.strided.unarySignatureCallbacks":"\nbase.strided.unarySignatureCallbacks( table:Object, signatures:ArrayLike<any> )\n    Assigns callbacks to unary interfaces according to type promotion rules.\n","base.strided.variance":"\nbase.strided.variance( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array.\n","base.strided.variance.ndarray":"\nbase.strided.variance.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array using alternative indexing\n    semantics.\n","base.strided.variancech":"\nbase.strided.variancech( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array using a one-pass trial mean\n    algorithm.\n","base.strided.variancech.ndarray":"\nbase.strided.variancech.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array using a one-pass trial mean\n    algorithm and alternative indexing semantics.\n","base.strided.variancepn":"\nbase.strided.variancepn( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array using a two-pass algorithm.\n","base.strided.variancepn.ndarray":"\nbase.strided.variancepn.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array using a two-pass algorithm and\n    alternative indexing semantics.\n","base.strided.variancetk":"\nbase.strided.variancetk( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array using a one-pass textbook\n    algorithm.\n","base.strided.variancetk.ndarray":"\nbase.strided.variancetk.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array using a one-pass textbook algorithm\n    and alternative indexing semantics.\n","base.strided.variancewd":"\nbase.strided.variancewd( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array using Welford's algorithm.\n","base.strided.variancewd.ndarray":"\nbase.strided.variancewd.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array using Welford's algorithm and\n    alternative indexing semantics.\n","base.strided.varianceyc":"\nbase.strided.varianceyc( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array using a one-pass algorithm proposed\n    by Youngs and Cramer.\n","base.strided.varianceyc.ndarray":"\nbase.strided.varianceyc.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array using a one-pass algorithm proposed\n    by Youngs and Cramer and alternative indexing semantics.\n","base.strided.zmap":"\nbase.strided.zmap( N:integer, x:Complex128Array, strideX:integer, \n  y:Complex128Array, strideY:integer, fcn:Function )\n    Applies a unary function to a double-precision complex floating-point\n    strided input array and assigns results to a double-precision complex\n    floating-point strided output array.\n","base.strided.zmap.ndarray":"\nbase.strided.zmap.ndarray( N:integer, x:Complex128Array, strideX:integer, \n  offsetX:integer, y:Complex128Array, strideY:integer, offsetY:integer, \n  fcn:Function )\n    Applies a unary function to a double-precision complex floating-point\n    strided input array and assigns results to a double-precision complex\n    floating-point strided output array using alternative indexing semantics.\n","base.str2multislice":"\nbase.str2multislice( str:string )\n    Parses a string-serialized MultiSlice object.\n","base.str2slice":"\nbase.str2slice( str:string )\n    Parses a string-serialized Slice object.\n","base.sub":"\nbase.sub( x:number, y:number )\n    Subtracts two double-precision floating-point numbers `x` and `y`.\n","base.subf":"\nbase.subf( x:number, y:number )\n    Subtracts two single-precision floating-point numbers `x` and `y`.\n","base.sumSeries":"\nbase.sumSeries( generator:Function[, options:Object] )\n    Sum the elements of the series given by the supplied function.\n","base.tan":"\nbase.tan( x:number )\n    Computes the tangent of a number.\n","base.tand":"\nbase.tand( x:number )\n    Computes the tangent of an angle measured in degrees.\n","base.tanh":"\nbase.tanh( x:number )\n    Computes the hyperbolic tangent of a double-precision floating-point number.\n","base.toBinaryString":"\nbase.toBinaryString( x:number )\n    Returns a string giving the literal bit representation of a double-precision\n    floating-point number.\n","base.toBinaryStringf":"\nbase.toBinaryStringf( x:float )\n    Returns a string giving the literal bit representation of a single-precision\n    floating-point number.\n","base.toBinaryStringUint8":"\nbase.toBinaryStringUint8( x:integer )\n    Returns a string giving the literal bit representation of an unsigned 8-bit\n    integer.\n","base.toBinaryStringUint16":"\nbase.toBinaryStringUint16( x:integer )\n    Returns a string giving the literal bit representation of an unsigned 16-bit\n    integer.\n","base.toBinaryStringUint32":"\nbase.toBinaryStringUint32( x:integer )\n    Returns a string giving the literal bit representation of an unsigned 32-bit\n    integer.\n","base.toWordf":"\nbase.toWordf( x:float )\n    Returns an unsigned 32-bit integer corresponding to the IEEE 754 binary\n    representation of a single-precision floating-point number.\n","base.toWords":"\nbase.toWords( x:number )\n    Splits a double-precision floating-point number into a higher order word\n    (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n","base.toWords.assign":"\nbase.toWords.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n  offset:integer )\n    Splits a double-precision floating-point number into a higher order word\n    (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer)\n    and assigns results to a provided output array.\n","base.transpose":"\nbase.transpose( x:ndarray )\n    Transposes a matrix (or a stack of matrices).\n","base.tribonacci":"\nbase.tribonacci( n:integer )\n    Computes the nth Tribonacci number.\n","base.trigamma":"\nbase.trigamma( x:number )\n    Evaluates the trigamma function.\n","base.trim":"\nbase.trim( str:string )\n    Trims whitespace from the beginning and end of a `string`.\n","base.trunc":"\nbase.trunc( x:number )\n    Rounds a double-precision floating-point number toward zero.\n","base.trunc2":"\nbase.trunc2( x:number )\n    Rounds a numeric value to the nearest power of two toward zero.\n","base.trunc10":"\nbase.trunc10( x:number )\n    Rounds a numeric value to the nearest power of ten toward zero.\n","base.truncateMiddle":"\nbase.truncateMiddle( str:string, len:integer, seq:string )\n    Truncates the middle UTF-16 code units of a string to return a string\n    having a specified length.\n","base.truncb":"\nbase.truncb( x:number, n:integer, b:integer )\n    Rounds a numeric value to the nearest multiple of `b^n` toward zero.\n","base.truncf":"\nbase.truncf( x:number )\n    Rounds a single-precision floating-point number toward zero.\n","base.truncn":"\nbase.truncn( x:number, n:integer )\n    Rounds a numeric value to the nearest multiple of `10^n` toward zero.\n","base.truncsd":"\nbase.truncsd( x:number, n:integer, b:integer )\n    Rounds a numeric value to the nearest number toward zero with `n`\n    significant figures.\n","base.uint32ToInt32":"\nbase.uint32ToInt32( x:integer )\n    Converts an unsigned 32-bit integer to a signed 32-bit integer.\n","base.umul":"\nbase.umul( a:integer, b:integer )\n    Performs C-like multiplication of two unsigned 32-bit integers.\n","base.umuldw":"\nbase.umuldw( a:integer, b:integer )\n    Multiplies two unsigned 32-bit integers and returns an array of two unsigned\n    32-bit integers which represents the unsigned 64-bit integer product.\n","base.umuldw.assign":"\nbase.umuldw.assign( a:integer, b:integer, out:Array|TypedArray|Object, \n  stride:integer, offset:integer )\n    Multiplies two unsigned 32-bit integers and assigns results representing\n    the unsigned 64-bit integer product to a provided output array.\n","base.uncapitalize":"\nbase.uncapitalize( str:string )\n    Lowercases the first character of a string.\n","base.uppercase":"\nbase.uppercase( str:string )\n    Converts a string to uppercase.\n","base.vercos":"\nbase.vercos( x:number )\n    Computes the versed cosine.\n","base.versin":"\nbase.versin( x:number )\n    Computes the versed sine.\n","base.wrap":"\nbase.wrap( v:number, min:number, max:number )\n    Wraps a value on the half-open interval `[min,max)`.\n","base.xlog1py":"\nbase.xlog1py( x:number, y:number )\n    Computes `x * ln(y+1)` so that the result is `0` if `x = 0`.\n","base.xlogy":"\nbase.xlogy( x:number, y:number )\n    Computes `x * ln(y)` so that the result is `0` if `x = 0`.\n","base.zeta":"\nbase.zeta( s:number )\n    Evaluates the Riemann zeta function as a function of a real variable `s`.\n","BERNDT_CPS_WAGES_1985":"\nBERNDT_CPS_WAGES_1985()\n    Returns a random sample of 534 workers from the Current Population Survey\n    (CPS) from 1985, including their wages and and other characteristics.\n","bifurcate":"\nbifurcate( collection:Array|TypedArray|Object, [options:Object,] \n  filter:Array|TypedArray|Object )\n    Splits values into two groups.\n","bifurcateBy":"\nbifurcateBy( collection:Array|TypedArray|Object, [options:Object,] \n  predicate:Function )\n    Splits values into two groups according to a predicate function.\n","bifurcateByAsync":"\nbifurcateByAsync( collection:Array|TypedArray|Object, [options:Object,] \n  predicate:Function, done:Function )\n    Splits values into two groups according to a predicate function.\n","bifurcateByAsync.factory":"\nbifurcateByAsync.factory( [options:Object,] predicate:Function )\n    Returns a function which splits values into two groups according to an\n    predicate function.\n","bifurcateIn":"\nbifurcateIn( obj:Object|Array|TypedArray, [options:Object,] predicate:Function )\n    Splits values into two groups according to a predicate function.\n","bifurcateOwn":"\nbifurcateOwn( obj:Object|Array|TypedArray, [options:Object,] \n  predicate:Function )\n    Splits values into two groups according to a predicate function.\n","BigInt":"\nBigInt( value:integer|string )\n    Returns a BigInt.\n","binomialTest":"\nbinomialTest( x:(number|Array[, n:Array<number>][, options:Object] )\n    Computes an exact test for the success probability in a Bernoulli\n    experiment.\n","Boolean":"\nBoolean( value:any )\n    Returns a boolean.\n","Boolean.prototype.toString":"\nBoolean.prototype.toString()\n    Returns a string representing the `Boolean` object.\n","Boolean.prototype.valueOf":"\nBoolean.prototype.valueOf()\n    Returns the primitive value of a `Boolean` object.\n","BooleanArray":"\nBooleanArray()\n    A Boolean array.\n\nBooleanArray( length:integer )\n    Creates a boolean array having a specified length.\n\nBooleanArray( booleanarray:BooleanArray )\n    Creates a boolean array from another boolean array.\n\nBooleanArray( typedarray:TypedArray )\n    Creates a boolean array from a typed array.\n\nBooleanArray( obj:Object )\n    Creates a boolean array from an array-like object or iterable.\n\nBooleanArray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a boolean array view of an ArrayBuffer.\n","BooleanArray.from":"\nBooleanArray.from( src:ArrayLike|Iterable[, clbk:Function[, thisArg:Any]] )\n    Creates a new boolean array from an array-like object or an iterable.\n","BooleanArray.of":"\nBooleanArray.of( element0:bool[, element1:bool[, ...elementN:bool]] )\n    Creates a new boolean array from a variable number of arguments.\n","BooleanArray.BYTES_PER_ELEMENT":"\nBooleanArray.BYTES_PER_ELEMENT\n    The size of each array element in bytes.\n","BooleanArray.name":"\nBooleanArray.name\n    Typed array constructor name.\n","BooleanArray.prototype.buffer":"\nBooleanArray.prototype.buffer\n    Pointer to the underlying data buffer.\n","BooleanArray.prototype.byteLength":"\nBooleanArray.prototype.byteLength\n    Size of the array in bytes.\n","BooleanArray.prototype.byteOffset":"\nBooleanArray.prototype.byteOffset\n    Offset (in bytes) of the array from the start of its underlying\n    ArrayBuffer.\n","BooleanArray.prototype.BYTES_PER_ELEMENT":"\nBooleanArray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element.\n","BooleanArray.prototype.length":"\nBooleanArray.prototype.length\n    The number of array elements.\n","BooleanArray.prototype.at":"\nBooleanArray.prototype.at( i:integer )\n    Returns an array element located at integer position (index) `i`, with\n    support for noth nonnegative and negative integer positions.\n","BooleanArray.prototype.copyWithin":"\nBooleanArray.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","BooleanArray.prototype.entries":"\nBooleanArray.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","BooleanArray.prototype.every":"\nBooleanArray.prototype.every( predicate:Function[, thisArg:Any] )\n    Returns a boolean indicating whether all elements in the array pass a test.\n","BooleanArray.prototype.fill":"\nBooleanArray.prototype.fill( value:boolean[, start:integer[, end:integer]] )\n    Returns a modified typed array filled with a fill value.\n","BooleanArray.prototype.filter":"\nBooleanArray.prototype.filter( predicate:Function[, thisArg:Any] )\n    Returns a new array containing the elements of an array which pass a test\n    implemented by a predicate function.\n","BooleanArray.prototype.find":"\nBooleanArray.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first element in an array for which a predicate function returns\n    a truthy value.\n","BooleanArray.prototype.findIndex":"\nBooleanArray.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first element in an array for which a predicate\n    function returns a truthy value.\n","BooleanArray.prototype.findLast":"\nBooleanArray.prototype.findLast( predicate:Function[, thisArg:Any] )\n    Returns the last element in an array for which a predicate function returns\n    a truthy value.\n","BooleanArray.prototype.findLastIndex":"\nBooleanArray.prototype.findLastIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the last element in an array for which a predicate\n    function returns a truthy value.\n","BooleanArray.prototype.forEach":"\nBooleanArray.prototype.forEach( clbk:Function[, thisArg:Any] )\n    Invokes a function once for each array element.\n","BooleanArray.prototype.get":"\nBooleanArray.prototype.get( i:integer )\n    Returns an array element located at integer position (index) `i`.\n","BooleanArray.prototype.includes":"\nBooleanArray.prototype.includes( searchElement:boolean[, fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a provided value.\n","BooleanArray.prototype.indexOf":"\nBooleanArray.prototype.indexOf( searchElement:boolean[, fromIndex:integer] )\n    Returns the first index at which a given element can be found.\n","BooleanArray.prototype.join":"\nBooleanArray.prototype.join( [separator:string] )\n    Returns a new string by concatenating all array elements separated by a\n    separator string.\n","BooleanArray.prototype.keys":"\nBooleanArray.prototype.keys()\n    Returns an iterator for iterating over each index key in a typed array.\n","BooleanArray.prototype.lastIndexOf":"\nBooleanArray.prototype.lastIndexOf( searchElement:boolean[, fromIndex:integer] )\n    Returns the last index at which a given element can be found.\n","BooleanArray.prototype.map":"\nBooleanArray.prototype.map( clbk:Function[, thisArg:Any] )\n    Returns a new array with each element being the result of a provided\n    callback function.\n","BooleanArray.prototype.reduce":"\nBooleanArray.prototype.reduce( reducerFn:Function[, initialValue:any] )\n    Applies a provided function to each element of the array, in order, passing\n    in the return value from the calculation on the preceding element and\n    returning the accumulated result upon completion.\n","BooleanArray.prototype.reduceRight":"\nBooleanArray.prototype.reduceRight( reducerFn:Function[, initialValue:any] )\n    Applies a provided function to each element of the array, in reverse order,\n    passing in the return value from the calculation on the preceding element\n    and returning the accumulated result upon completion.\n","BooleanArray.prototype.reverse":"\nBooleanArray.prototype.reverse()\n    Reverses the array *in-place*.\n","BooleanArray.prototype.set":"\nBooleanArray.prototype.set( v:bool|BooleanArray|ArrayLikeObject[, i:integer] )\n    Sets one or more array elements.\n","BooleanArray.prototype.slice":"\nBooleanArray.prototype.slice( [start:integer[, end:integer]] )\n    Copies a portion of a typed array to a new typed array.\n","BooleanArray.prototype.some":"\nBooleanArray.prototype.some( predicate:Function[, thisArg:Any] )\n    Returns a boolean indicating whether at least one element passes a test.\n","BooleanArray.prototype.sort":"\nBooleanArray.prototype.sort( [compareFunction:Function] )\n    Sorts an array in-place.\n","BooleanArray.prototype.subarray":"\nBooleanArray.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array view over the same underlying `ArrayBuffer` and\n    with the same underlying data type as the host array.\n","BooleanArray.prototype.toLocaleString":"\nBooleanArray.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n","BooleanArray.prototype.toReversed":"\nBooleanArray.prototype.toReversed()\n    Returns a new typed array containing the elements in reversed order.\n","BooleanArray.prototype.toSorted":"\nBooleanArray.prototype.toSorted( [compareFunction:Function] )\n    Returns a new typed array containing the elements in sorted order.\n","BooleanArray.prototype.toString":"\nBooleanArray.prototype.toString()\n    Serializes an array as a string.\n","BooleanArray.prototype.values":"\nBooleanArray.prototype.values()\n    Returns an iterator for iterating over each value in a typed array.\n","BooleanArray.prototype.with":"\nBooleanArray.prototype.with( index, value )\n    Returns a new typed array with the element at a provided index replaced\n    with a provided value.\n","broadcastArray":"\nbroadcastArray( x:ndarray, shape:ArrayLikeObject )\n    Broadcasts an ndarray to a specified shape.\n","broadcastArrays":"\nbroadcastArrays( ...arrays:ndarray|ArrayLikeObject<ndarray> )\n    Broadcasts ndarrays to a common shape.\n","Buffer":"\nBuffer\n\nBuffer( size:integer )\n    Allocates a buffer having a specified number of bytes.\n\nBuffer( buffer:Buffer )\n    Copies buffer data to a new Buffer instance.\n\nBuffer( array:Array )\n    Allocates a buffer using an array of octets.\n\nBuffer( str:string[, encoding:string] )\n    Allocates a buffer containing a provided string.\n","buffer2json":"\nbuffer2json( buffer:Buffer )\n    Returns a JSON representation of a buffer.\n","BYTE_ORDER":"\nBYTE_ORDER\n    Platform byte order.\n","camelcase":"\ncamelcase( str:string )\n    Converts a string to camel case.\n","capitalize":"\ncapitalize( str:string )\n    Capitalizes the first character in a string.\n","capitalizeKeys":"\ncapitalizeKeys( obj:Object )\n    Converts the first letter of each object key to uppercase.\n","CATALAN":"\nCATALAN\n    Catalan's constant.\n","CBRT_EPS":"\nCBRT_EPS\n    Cube root of double-precision floating-point epsilon.\n","CDC_NCHS_US_BIRTHS_1969_1988":"\nCDC_NCHS_US_BIRTHS_1969_1988()\n    Returns US birth data from 1969 to 1988, as provided by the Center for\n    Disease Control and Prevention's National Center for Health Statistics.\n","CDC_NCHS_US_BIRTHS_1994_2003":"\nCDC_NCHS_US_BIRTHS_1994_2003()\n    Returns US birth data from 1994 to 2003, as provided by the Center for\n    Disease Control and Prevention's National Center for Health Statistics.\n","CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013":"\nCDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n    Returns US infant mortality data, by race, from 1915 to 2013, as provided by\n    the Center for Disease Control and Prevention's National Center for Health\n    Statistics.\n","chdir":"\nchdir( path:string )\n    Changes the current working directory.\n","chi2gof":"\nchi2gof( x:ndarray|Array|TypedArray, y:ndarray|Array|TypedArray|string[, \n  ...args:number][, options:Object] )\n    Performs a chi-square goodness-of-fit test.\n","chi2test":"\nchi2test( x:ndarray|Array[, options:Object] )\n    Performs a chi-square independence test.\n","circarray2iterator":"\ncircarray2iterator( src:ArrayLikeObject[, options:Object][, mapFcn:Function[, \n  thisArg:any]] )\n    Returns an iterator which repeatedly iterates over the elements of an array-\n    like object.\n","circularArrayStream":"\ncircularArrayStream( src:ArrayLikeObject[, options:Object] )\n    Creates a readable stream from an array-like object which repeatedly\n    iterates over the provided value's elements.\n","circularArrayStream.factory":"\ncircularArrayStream.factory( [options:Object] )\n    Returns a function for creating readable streams from array-like objects\n    which repeatedly iterate over the elements of provided values.\n","circularArrayStream.objectMode":"\ncircularArrayStream.objectMode( src:ArrayLikeObject[, options:Object] )\n    Returns an \"objectMode\" readable stream from an array-like object which\n    repeatedly iterates over a provided value's elements.\n","CircularBuffer":"\nCircularBuffer( buffer:integer|ArrayLike )\n    Circular buffer constructor.\n","CircularBuffer.prototype.clear":"\nCircularBuffer.prototype.clear()\n    Clears a buffer.\n","CircularBuffer.prototype.count":"\nCircularBuffer.prototype.count\n    Read-only property returning the number of elements currently in the buffer.\n","CircularBuffer.prototype.full":"\nCircularBuffer.prototype.full\n    Read-only property returning a boolean indicating whether a circular buffer\n    is full.\n","CircularBuffer.prototype.iterator":"\nCircularBuffer.prototype.iterator( [niters:integer] )\n    Returns an iterator for iterating over a circular buffer.\n","CircularBuffer.prototype.length":"\nCircularBuffer.prototype.length\n    Read-only property returning the buffer length (i.e., capacity).\n","CircularBuffer.prototype.push":"\nCircularBuffer.prototype.push( value:any )\n    Adds a value to a circular buffer.\n","CircularBuffer.prototype.toArray":"\nCircularBuffer.prototype.toArray()\n    Returns an array of circular buffer values.\n","CircularBuffer.prototype.toJSON":"\nCircularBuffer.prototype.toJSON()\n    Serializes a circular buffer as JSON.\n","close":"\nclose( fd:integer, clbk:Function )\n    Asynchronously closes a file descriptor, so that the file descriptor no\n    longer refers to any file and may be reused.\n","close.sync":"\nclose.sync( fd:integer )\n    Synchronously closes a file descriptor.\n","CMUDICT":"\nCMUDICT( [options:Object] )\n    Returns datasets from the Carnegie Mellon Pronouncing Dictionary (CMUdict).\n","codePointAt":"\ncodePointAt( str:string, idx:integer[, backward:boolean] )\n    Returns a Unicode code point from a string at a specified position.\n","commonKeys":"\ncommonKeys( obj1:any, obj2:any[, ...obj:any] )\n    Returns the common own property names of two or more objects.\n","commonKeysIn":"\ncommonKeysIn( obj1:any, obj2:any[, ...obj:any] )\n    Returns the common own and inherited property names of two or more objects.\n","complex":"\ncomplex( real:number, imag:number[, dtype:string] )\n    Creates a complex number.\n","Complex64":"\nComplex64( real:number, imag:number )\n    64-bit complex number constructor.\n","Complex64.BYTES_PER_ELEMENT":"\nComplex64.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n","Complex64.prototype.BYTES_PER_ELEMENT":"\nComplex64.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n","Complex64.prototype.byteLength":"\nComplex64.prototype.byteLength\n    Length (in bytes) of a complex number.\n","COMPLEX64_NAN":"\nCOMPLEX64_NAN\n    Canonical single-precision complex floating-point NaN.\n","COMPLEX64_NUM_BYTES":"\nCOMPLEX64_NUM_BYTES\n    Size (in bytes) of a 64-bit complex number.\n","COMPLEX64_ZERO":"\nCOMPLEX64_ZERO\n    Single-precision complex floating-point zero.\n","Complex64Array":"\nComplex64Array()\n    A 64-bit complex number array.\n\nComplex64Array( length:integer )\n    Creates a 64-bit complex number array having a specified length.\n\nComplex64Array( complexarray:Complex64Array )\n    Creates a 64-bit complex number array from another complex number array.\n\nComplex64Array( typedarray:TypedArray )\n    Creates a 64-bit complex number array from a typed array\n    containing interleaved real and imaginary components.\n\nComplex64Array( obj:Object )\n    Creates a 64-bit complex number array from an array-like object or iterable.\n\nComplex64Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a 64-bit complex number array view of an ArrayBuffer.\n","Complex64Array.from":"\nComplex64Array.from( src:ArrayLike|Iterable[, clbk:Function[, thisArg:Any]] )\n    Creates a new 64-bit complex number array from an array-like object or an\n    iterable.\n","Complex64Array.of":"\nComplex64Array.of( element0:number[, element1:number[, ...elementN:number]] )\n    Creates a new 64-bit complex number array from a variable number of\n    arguments.\n","Complex64Array.BYTES_PER_ELEMENT":"\nComplex64Array.BYTES_PER_ELEMENT\n    The size of each array element in bytes.\n","Complex64Array.name":"\nComplex64Array.name\n    Typed array constructor name.\n","Complex64Array.prototype.buffer":"\nComplex64Array.prototype.buffer\n    Pointer to the underlying data buffer.\n","Complex64Array.prototype.byteLength":"\nComplex64Array.prototype.byteLength\n    Length of the array in bytes.\n","Complex64Array.prototype.byteOffset":"\nComplex64Array.prototype.byteOffset\n    Offset (in bytes) of the array from the start of its underlying\n    ArrayBuffer.\n","Complex64Array.prototype.BYTES_PER_ELEMENT":"\nComplex64Array.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element.\n","Complex64Array.prototype.length":"\nComplex64Array.prototype.length\n    The number of array elements.\n","Complex64Array.prototype.at":"\nComplex64Array.prototype.at( i:integer )\n    Returns an array element located at integer position (index) `i`, with\n    support for noth nonnegative and negative integer positions.\n","Complex64Array.prototype.copyWithin":"\nComplex64Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","Complex64Array.prototype.entries":"\nComplex64Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","Complex64Array.prototype.every":"\nComplex64Array.prototype.every( predicate:Function[, thisArg:Any] )\n    Returns a boolean indicating whether all elements in the array pass a test.\n","Complex64Array.prototype.fill":"\nComplex64Array.prototype.fill( value:Complex64[, start:integer[, end:integer]] )\n    Returns a modified typed array filled with a fill value.\n","Complex64Array.prototype.filter":"\nComplex64Array.prototype.filter( predicate:Function[, thisArg:Any] )\n    Returns a new array containing the elements of an array which pass a test\n    implemented by a predicate function.\n","Complex64Array.prototype.find":"\nComplex64Array.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first element in an array for which a predicate function\n    returns a truthy value.\n","Complex64Array.prototype.findIndex":"\nComplex64Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first element in an array for which a predicate\n    function returns a truthy value.\n","Complex64Array.prototype.findLast":"\nComplex64Array.prototype.findLast( predicate:Function[, thisArg:Any] )\n    Returns the last element in an array for which a predicate function returns\n    a truthy value.\n","Complex64Array.prototype.findLastIndex":"\nComplex64Array.prototype.findLastIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the last element in an array for which a predicate\n    function returns a truthy value.\n","Complex64Array.prototype.forEach":"\nComplex64Array.prototype.forEach( clbk:Function[, thisArg:Any] )\n    Invokes a function once for each array element.\n","Complex64Array.prototype.get":"\nComplex64Array.prototype.get( i:integer )\n    Returns an array element located at integer position (index) `i`.\n","Complex64Array.prototype.includes":"\nComplex64Array.prototype.includes( searchElement:Complex64[, \n  fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a provided value.\n","Complex64Array.prototype.indexOf":"\nComplex64Array.prototype.indexOf( searchElement:Complex64[, fromIndex:integer] )\n    Returns the first index at which a given element can be found.\n","Complex64Array.prototype.join":"\nComplex64Array.prototype.join( [separator:string] )\n    Returns a new string by concatenating all array elements separated by a\n    separator string.\n","Complex64Array.prototype.keys":"\nComplex64Array.prototype.keys()\n    Returns an iterator for iterating over each index key in a typed array.\n","Complex64Array.prototype.lastIndexOf":"\nComplex64Array.prototype.lastIndexOf( searchElement:Complex64[, \n  fromIndex:integer] )\n    Returns the last index at which a given element can be found.\n","Complex64Array.prototype.map":"\nComplex64Array.prototype.map( clbk:Function[, thisArg:Any] )\n    Returns a new array with each element being the result of a provided\n    callback function.\n","Complex64Array.prototype.reduce":"\nComplex64Array.prototype.reduce( reducerFn:Function[, initialValue:any] )\n    Applies a provided function to each element of the array, in order, passing\n    in the return value from the calculation on the preceding element and\n    returning the accumulated result upon completion.\n","Complex64Array.prototype.reduceRight":"\nComplex64Array.prototype.reduceRight( reducerFn:Function[, initialValue:any] )\n    Applies a provided function to each element of the array, in reverse order,\n    passing in the return value from the calculation on the preceding element\n    and returning the accumulated result upon completion.\n","Complex64Array.prototype.reverse":"\nComplex64Array.prototype.reverse()\n    Reverses the array *in-place*.\n","Complex64Array.prototype.set":"\nComplex64Array.prototype.set( z:Complex64|Complex64Array|ArrayLikeObject[, \n  i:integer] )\n    Sets one or more array elements.\n","Complex64Array.prototype.slice":"\nComplex64Array.prototype.slice( [start:integer[, end:integer]] )\n    Copies a portion of a typed array to a new typed array.\n","Complex64Array.prototype.some":"\nComplex64Array.prototype.some( predicate[, thisArg] )\n    Returns a boolean indicating whether at least one element passes a test.\n","Complex64Array.prototype.sort":"\nComplex64Array.prototype.sort( compareFunction:Function )\n    Sorts an array in-place.\n","Complex64Array.prototype.subarray":"\nComplex64Array.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array view over the same underlying `ArrayBuffer` and\n    with the same underlying data type as the host array.\n","Complex64Array.prototype.toLocaleString":"\nComplex64Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n","Complex64Array.prototype.toReversed":"\nComplex64Array.prototype.toReversed()\n    Returns a new typed array containing the elements in reversed order.\n","Complex64Array.prototype.toSorted":"\nComplex64Array.prototype.toSorted( compareFcn:Function )\n    Returns a new typed array containing the elements in sorted order.\n","Complex64Array.prototype.toString":"\nComplex64Array.prototype.toString()\n    Serializes an array as a string.\n","Complex64Array.prototype.values":"\nComplex64Array.prototype.values()\n    Returns an iterator for iterating over each value in a typed array.\n","Complex64Array.prototype.with":"\nComplex64Array.prototype.with( index, value )\n    Returns a new typed array with the element at a provided index replaced\n    with a provided value.\n","Complex128":"\nComplex128( real:number, imag:number )\n    128-bit complex number constructor.\n","Complex128.BYTES_PER_ELEMENT":"\nComplex128.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n","Complex128.prototype.BYTES_PER_ELEMENT":"\nComplex128.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n","Complex128.prototype.byteLength":"\nComplex128.prototype.byteLength\n    Length (in bytes) of a complex number.\n","COMPLEX128_NAN":"\nCOMPLEX128_NAN\n    Canonical double-precision complex floating-point NaN.\n","COMPLEX128_NUM_BYTES":"\nCOMPLEX128_NUM_BYTES\n    Size (in bytes) of a 128-bit complex number.\n","COMPLEX128_ZERO":"\nCOMPLEX128_ZERO\n    Double-precision complex floating-point zero.\n","Complex128Array":"\nComplex128Array()\n    A 128-bit complex number array.\n\nComplex128Array( length:integer )\n    Creates a 128-bit complex number array having a specified length.\n\nComplex128Array( complexarray:Complex128Array )\n    Creates a 64-bit complex number array from another complex number array.\n\nComplex128Array( typedarray:TypedArray )\n    Creates a 128-bit complex number array from a typed array\n    containing interleaved real and imaginary components.\n\nComplex128Array( obj:Object )\n    Creates a 128-bit complex number array from an array-like object or \n    iterable.\n\nComplex128Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a 128-bit complex number array view of an ArrayBuffer.\n","Complex128Array.from":"\nComplex128Array.from( src:ArrayLike|Iterable[, clbk:Function[, thisArg:Any]] )\n    Creates a new 128-bit complex number array from an array-like object or an\n    iterable.\n","Complex128Array.of":"\nComplex128Array.of( element0:number|ComplexLike[, \n  element1:number |ComplexLike[, ...elementN:number|ComplexLike]] )\n    Creates a new 128-bit complex number array from a variable number of\n    arguments.\n","Complex128Array.BYTES_PER_ELEMENT":"\nComplex128Array.BYTES_PER_ELEMENT\n    The size of each array element in bytes.\n","Complex128Array.name":"\nComplex128Array.name\n    Typed array constructor name.\n","Complex128Array.prototype.buffer":"\nComplex128Array.prototype.buffer\n    Pointer to the underlying data buffer.\n","Complex128Array.prototype.byteLength":"\nComplex128Array.prototype.byteLength\n    Length of the array in bytes.\n","Complex128Array.prototype.byteOffset":"\nComplex128Array.prototype.byteOffset\n    Offset (in bytes) of the array from the start of its underlying\n    ArrayBuffer.\n","Complex128Array.prototype.BYTES_PER_ELEMENT":"\nComplex128Array.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element.\n","Complex128Array.prototype.length":"\nComplex128Array.prototype.length\n    The number of array elements.\n","Complex128Array.prototype.at":"\nComplex128Array.prototype.at( i:integer )\n    Returns an array element located at integer position (index) `i`, with\n    support for both nonnegative and negative integer positions.\n","Complex128Array.prototype.copyWithin":"\nComplex128Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","Complex128Array.prototype.entries":"\nComplex128Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","Complex128Array.prototype.every":"\nComplex128Array.prototype.every( predicate:Function[, thisArg:Any] )\n    Returns a boolean indicating whether all elements in the array pass a test.\n","Complex128Array.prototype.fill":"\nComplex128Array.prototype.fill( value:Complex128[, start:integer[, \n  end:integer]] )\n    Returns a modified typed array filled with a fill value.\n","Complex128Array.prototype.filter":"\nComplex128Array.prototype.filter( predicate:Function[, thisArg:Any] )\n    Returns a new array containing the elements of an array which pass a test\n    implemented by a predicate function.\n","Complex128Array.prototype.find":"\nComplex128Array.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first element in an array for which a predicate function\n    returns a truthy value.\n","Complex128Array.prototype.findIndex":"\nComplex128Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first element in an array for which a predicate\n    function returns a truthy value.\n","Complex128Array.prototype.findLast":"\nComplex128Array.prototype.findLast( predicate:Function[, thisArg:Any] )\n    Returns the last element in an array for which a predicate function returns\n    a truthy value.\n","Complex128Array.prototype.findLastIndex":"\nComplex128Array.prototype.findLastIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the last element in an array for which a predicate\n    function returns a truthy value.\n","Complex128Array.prototype.forEach":"\nComplex128Array.prototype.forEach( clbk:Function[, thisArg:Any] )\n    Invokes a function once for each array element.\n","Complex128Array.prototype.get":"\nComplex128Array.prototype.get( i:integer )\n    Returns an array element located at integer position (index) `i`.\n","Complex128Array.prototype.includes":"\nComplex128Array.prototype.includes( searchElement:Complex128[, \n  fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a provided value.\n","Complex128Array.prototype.indexOf":"\nComplex128Array.prototype.indexOf( searchElement:Complex128[, \n  fromIndex:integer] )\n    Returns the first index at which a given element can be found.\n","Complex128Array.prototype.join":"\nComplex128Array.prototype.join( [separator:string] )\n    Returns a new string by concatenating all array elements separated by a\n    separator string.\n","Complex128Array.prototype.keys":"\nComplex128Array.prototype.keys()\n    Returns an iterator for iterating over each index key in a typed array.\n","Complex128Array.prototype.lastIndexOf":"\nComplex128Array.prototype.lastIndexOf( searchElement:Complex128[, \n  fromIndex:integer] )\n    Returns the last index at which a given element can be found.\n","Complex128Array.prototype.map":"\nComplex128Array.prototype.map( clbk:Function[, thisArg:Any] )\n    Returns a new array with each element being the result of a provided\n    callback function.\n","Complex128Array.prototype.reduce":"\nComplex128Array.prototype.reduce( reducerFn:Function[, initialValue:any] )\n    Applies a provided function to each element of the array, in order, passing\n    in the return value from the calculation on the preceding element and\n    returning the accumulated result upon completion.\n","Complex128Array.prototype.reduceRight":"\nComplex128Array.prototype.reduceRight( reducerFn:Function[, initialValue:any] )\n    Applies a provided function to each element of the array, in reverse order,\n    passing in the return value from the calculation on the preceding element\n    and returning the accumulated result upon completion.\n","Complex128Array.prototype.reverse":"\nComplex128Array.prototype.reverse()\n    Reverses the array *in-place*.\n","Complex128Array.prototype.set":"\nComplex128Array.prototype.set( z:Complex128|Complex128Array|ArrayLikeObject[, \n  i:integer] )\n    Sets one or more array elements.\n","Complex128Array.prototype.slice":"\nComplex128Array.prototype.slice( [start:integer[, end:integer]] )\n    Copies a portion of a typed array to a new typed array.\n","Complex128Array.prototype.some":"\nComplex128Array.prototype.some( predicate[, thisArg] )\n    Returns a boolean indicating whether at least one element passes a test.\n","Complex128Array.prototype.sort":"\nComplex128Array.prototype.sort( compareFunction:Function )\n    Sorts an array in-place.\n","Complex128Array.prototype.subarray":"\nComplex128Array.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array view over the same underlying `ArrayBuffer` and\n    with the same underlying data type as the host array.\n","Complex128Array.prototype.toLocaleString":"\nComplex128Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n","Complex128Array.prototype.toReversed":"\nComplex128Array.prototype.toReversed()\n    Returns a new typed array containing the elements in reversed order.\n","Complex128Array.prototype.toSorted":"\nComplex128Array.prototype.toSorted( compareFcn:Function )\n    Returns a new typed array containing the elements in sorted order.\n","Complex128Array.prototype.toString":"\nComplex128Array.prototype.toString()\n    Serializes an array as a string.\n","Complex128Array.prototype.values":"\nComplex128Array.prototype.values()\n    Returns an iterator for iterating over each value in a typed array.\n","Complex128Array.prototype.with":"\nComplex128Array.prototype.with( index, value )\n    Returns a new typed array with the element at a provided index replaced\n    with a provided value.\n","complexarray":"\ncomplexarray( [dtype:string] )\n    Creates a complex typed array.\n\ncomplexarray( length:integer[, dtype:string] )\n    Returns a complex number typed array having a specified length.\n\ncomplexarray( complexarray:ComplexArray[, dtype:string] )\n    Creates a complex number typed array from another complex number typed\n    array.\n\ncomplexarray( obj:Object[, dtype:string] )\n    Creates a complex number typed array from an array-like object or iterable.\n\ncomplexarray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n  dtype:string] )\n    Returns a complex number typed array view of an ArrayBuffer.\n","complexarrayCtors":"\ncomplexarrayCtors( dtype:string )\n    Returns a complex typed array constructor.\n","complexarrayDataTypes":"\ncomplexarrayDataTypes()\n    Returns a list of complex typed array data types.\n","complexCtors":"\ncomplexCtors( dtype:string )\n    Returns a complex number constructor.\n","complexDataType":"\ncomplexDataType( value:any )\n    Returns the data type of a complex number object.\n","complexDataTypes":"\ncomplexDataTypes()\n    Returns a list of complex number data types.\n","complexPromotionRules":"\ncomplexPromotionRules( [dtype1:string, dtype2:string] )\n    Returns the complex number data type with the smallest size and closest\n    \"kind\" to which data types can be safely cast.\n","compose":"\ncompose( ...f:Function )\n    Function composition.\n","composeAsync":"\ncomposeAsync( ...f:Function )\n    Function composition.\n","configdir":"\nconfigdir( [p:string] )\n    Returns a directory for user-specific configuration files.\n","conj":"\nconj( z:Complex128 )\n    Returns the complex conjugate of a double-precision complex floating-point\n    number.\n","conjf":"\nconjf( z:Complex64 )\n    Returns the complex conjugate of a single-precision complex floating-point\n    number.\n","constantcase":"\nconstantcase( str:string )\n    Converts a string to constant case.\n","constantFunction":"\nconstantFunction( val:any )\n    Creates a function which always returns the same value.\n","constantStream":"\nconstantStream( value:string|Buffer|Uint8Array|any[, options:Object] )\n    Returns a readable stream which always streams the same value.\n","constantStream.factory":"\nconstantStream.factory( [value:string|Buffer|Uint8Array|any, ][options:Object] )\n    Returns a function for creating readable streams which always stream the\n    same value.\n","constantStream.objectMode":"\nconstantStream.objectMode( value:any[, options:Object] )\n    Returns an \"objectMode\" readable stream which always streams the same value.\n","constructorName":"\nconstructorName( val:any )\n    Determines the name of a value's constructor.\n","contains":"\ncontains( val:ArrayLike, searchValue:any[, position:integer] )\n    Tests if an array-like value contains a search value.\n","convertArray":"\nconvertArray( arr:ArrayLikeObject, dtype:string )\n    Converts an input array to an array of a different data type.\n","convertArraySame":"\nconvertArraySame( x:ArrayLikeObject, y:Array|TypedArray )\n    Converts an input array to the same data type as a second input array.\n","convertPath":"\nconvertPath( from:string, to:string )\n    Converts between POSIX and Windows paths.\n","copy":"\ncopy( value:any[, level:integer] )\n    Copy or deep clone a value to an arbitrary depth.\n","copyBuffer":"\ncopyBuffer( buffer:Buffer )\n    Copies buffer data to a new Buffer instance.\n","countBy":"\ncountBy( collection:Array|TypedArray|Object, [options:Object,] \n  indicator:Function )\n    Groups values according to an indicator function and returns group counts.\n","countByAsync":"\ncountByAsync( collection:Array|TypedArray|Object, [options:Object,] \n  indicator:Function, done:Function )\n    Groups values according to an indicator function and returns group counts.\n","countByAsync.factory":"\ncountByAsync.factory( [options:Object,] indicator:Function )\n    Returns a function which groups values according to an indicator function\n    and returns group counts.\n","currentYear":"\ncurrentYear()\n    Returns the current year.\n","curry":"\ncurry( fcn:Function[, arity:integer][, thisArg:any] )\n    Transforms a function into a sequence of functions each accepting a single\n    argument.\n","curryRight":"\ncurryRight( fcn:Function[, arity:integer][, thisArg:any] )\n    Transforms a function into a sequence of functions each accepting a single\n    argument.\n","cwd":"\ncwd()\n    Returns the current working directory.\n","DALE_CHALL_NEW":"\nDALE_CHALL_NEW()\n    Returns a list of familiar English words.\n","datasets":"\ndatasets( name:string[, options:Object] )\n    Returns a dataset.\n","DataView":"\nDataView( buffer:ArrayBuffer|SharedArrayBuffer[, byteOffset:integer[, \n  byteLength:integer]] )\n    Returns a data view representing a provided array buffer.\n","DataView.prototype.buffer":"\nDataView.prototype.buffer\n    Read-only property which returns the underyling array buffer.\n","DataView.prototype.byteLength":"\nDataView.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the view.\n","DataView.prototype.byteOffset":"\nDataView.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the view to the\n    start of the underlying array buffer.\n","datespace":"\ndatespace( start:number, stop:number[, length:integer][ , options:Object] )\n    Generates an array of linearly spaced dates.\n","dayOfQuarter":"\ndayOfQuarter( [month:string|integer|Date[, day:integer, year:integer]] )\n    Returns the day of the quarter.\n","dayOfYear":"\ndayOfYear( [month:string|integer|Date[, day:integer, year:integer]] )\n    Returns the day of the year.\n","daysInMonth":"\ndaysInMonth( [month:string|integer|Date[, year:integer]] )\n    Returns the number of days in a month.\n","daysInYear":"\ndaysInYear( [value:integer|Date] )\n    Returns the number of days in a year according to the Gregorian calendar.\n","ddot":"\nddot( x:ndarray, y:ndarray[, dim:integer] )\n    Computes the dot product of two double-precision floating-point vectors.\n","debugSinkStream":"\ndebugSinkStream( [options:Object,] [clbk:Function] )\n    Returns a writable stream for debugging stream pipelines.\n","debugSinkStream.factory":"\ndebugSinkStream.factory( [options:Object] )\n    Returns a function for creating writable streams for debugging stream\n    pipelines.\n","debugSinkStream.objectMode":"\ndebugSinkStream.objectMode( [options:Object,] [clbk:Function] )\n    Returns an \"objectMode\" writable stream for debugging stream pipelines.\n","debugStream":"\ndebugStream( [options:Object,] [clbk:Function] )\n    Returns a transform stream for debugging stream pipelines.\n","debugStream.factory":"\ndebugStream.factory( [options:Object] )\n    Returns a function for creating transform streams for debugging stream\n    pipelines.\n","debugStream.objectMode":"\ndebugStream.objectMode( [options:Object,] [clbk:Function] )\n    Returns an \"objectMode\" transform stream for debugging stream pipelines.\n","decorateAfter":"\ndecorateAfter( fcn:Function, arity:integer, after:Function[, thisArg:any] )\n    Decorates a provided function such that the function's return value is\n    provided as an argument to another function.\n","decorateAfter.factory":"\ndecorateAfter.factory( fcn:Function, arity:integer, after:Function[, \n  thisArg:any] )\n    Uses code generation to decorate a provided function such that the\n    function's return value is provided as an argument to another function.\n","deepEqual":"\ndeepEqual( a:any, b:any )\n    Tests for deep equality between two values.\n","deepGet":"\ndeepGet( obj:ObjectLike, path:string|Array[, options:Object] )\n    Returns a nested property value.\n","deepGet.factory":"\ndeepGet.factory( path:string|Array[, options:Object] )\n    Creates a reusable deep get function.\n","deepHasOwnProp":"\ndeepHasOwnProp( value:any, path:string|Array[, options:Object] )\n    Returns a boolean indicating whether an object contains a nested key path.\n","deepHasOwnProp.factory":"\ndeepHasOwnProp.factory( path:string|Array[, options:Object] )\n    Returns a function which tests whether an object contains a nested key path.\n","deepHasProp":"\ndeepHasProp( value:any, path:string|Array[, options:Object] )\n    Returns a boolean indicating whether an object contains a nested key path,\n    either own or inherited.\n","deepHasProp.factory":"\ndeepHasProp.factory( path:string|Array[, options:Object] )\n    Returns a function which tests whether an object contains a nested key path,\n    either own or inherited.\n","deepPluck":"\ndeepPluck( arr:Array, path:string|Array[, options:Object] )\n    Extracts a nested property value from each element of an object array.\n","deepSet":"\ndeepSet( obj:ObjectLike, path:string|Array, value:any[, options:Object] )\n    Sets a nested property value.\n","deepSet.factory":"\ndeepSet.factory( path:string|Array[, options:Object] )\n    Creates a reusable deep set function.\n","defineMemoizedProperty":"\ndefineMemoizedProperty( obj:Object, prop:string|symbol, descriptor:Object )\n    Defines a memoized object property.\n","defineProperties":"\ndefineProperties( obj:Object, properties:Object )\n    Defines (and/or modifies) object properties.\n","defineProperty":"\ndefineProperty( obj:Object, prop:string|symbol, descriptor:Object )\n    Defines (or modifies) an object property.\n","dirname":"\ndirname( path:string )\n    Returns a directory name.\n","dotcase":"\ndotcase( str:string )\n    Converts a string to dot case.\n","DoublyLinkedList":"\nDoublyLinkedList()\n    Doubly linked list constructor.\n","doUntil":"\ndoUntil( fcn:Function, predicate:Function[, thisArg:any] )\n    Invokes a function until a test condition is true.\n","doUntilAsync":"\ndoUntilAsync( fcn:Function, predicate:Function, done:Function[, thisArg:any] )\n    Invokes a function until a test condition is true.\n","doUntilEach":"\ndoUntilEach( collection:Array|TypedArray|Object, fcn:Function, \n  predicate:Function[, thisArg:any] )\n    Until a test condition is true, invokes a function for each element in a\n    collection.\n","doUntilEachRight":"\ndoUntilEachRight( collection:Array|TypedArray|Object, fcn:Function, \n  predicate:Function[, thisArg:any] )\n    Until a test condition is true, invokes a function for each element in a\n    collection, iterating from right to left.\n","doWhile":"\ndoWhile( fcn:Function, predicate:Function[, thisArg:any] )\n    Invokes a function while a test condition is true.\n","doWhileAsync":"\ndoWhileAsync( fcn:Function, predicate:Function, done:Function[, thisArg:any] )\n    Invokes a function while a test condition is true.\n","doWhileEach":"\ndoWhileEach( collection:Array|TypedArray|Object, fcn:Function, \n  predicate:Function[, thisArg:any] )\n    While a test condition is true, invokes a function for each element in a\n    collection.\n","doWhileEachRight":"\ndoWhileEachRight( collection:Array|TypedArray|Object, fcn:Function, \n  predicate:Function[, thisArg:any] )\n    While a test condition is true, invokes a function for each element in a\n    collection, iterating from right to left.\n","dswap":"\ndswap( x:ndarray, y:ndarray[, dim:integer] )\n    Interchanges two double-precision floating-point vectors.\n","E":"\nE\n    Euler's number.\n","EMOJI":"\nEMOJI()\n    Returns an emoji database.\n","EMOJI_CODE_PICTO":"\nEMOJI_CODE_PICTO()\n    Returns an object mapping emoji codes to pictographs.\n","EMOJI_PICTO_CODE":"\nEMOJI_PICTO_CODE()\n    Returns an object mapping emoji pictographs to codes.\n","emptyStream":"\nemptyStream( [options:Object] )\n    Returns an \"empty\" readable stream.\n","emptyStream.factory":"\nemptyStream.factory( [options:Object] )\n    Returns a function for creating empty readable streams.\n","emptyStream.objectMode":"\nemptyStream.objectMode()\n    Returns an \"objectMode\" empty readable stream.\n","endsWith":"\nendsWith( str:string, search:string[, len:integer] )\n    Tests if a string ends with the characters of another string.\n","enumerableProperties":"\nenumerableProperties( value:any )\n    Returns an array of an object's own enumerable property names and symbols.\n","enumerablePropertiesIn":"\nenumerablePropertiesIn( value:any )\n    Returns an array of an object's own and inherited enumerable property names\n    and symbols.\n","enumerablePropertySymbols":"\nenumerablePropertySymbols( value:any )\n    Returns an array of an object's own enumerable symbol properties.\n","enumerablePropertySymbolsIn":"\nenumerablePropertySymbolsIn( value:any )\n    Returns an array of an object's own and inherited enumerable symbol\n    properties.\n","ENV":"\nENV\n    An object containing the user environment.\n","EPS":"\nEPS\n    Difference between one and the smallest value greater than one that can be\n    represented as a double-precision floating-point number.\n","error2json":"\nerror2json( error:Error )\n    Returns a JSON representation of an error object.\n","EULERGAMMA":"\nEULERGAMMA\n    The Euler-Mascheroni constant.\n","every":"\nevery( collection:Array|TypedArray|Object )\n    Tests whether all elements in a collection are truthy.\n","everyBy":"\neveryBy( collection:Array|TypedArray|Object, predicate:Function[, \n  thisArg:any ] )\n    Tests whether all elements in a collection pass a test implemented by a\n    predicate function.\n","everyByAsync":"\neveryByAsync( collection:Array|TypedArray|Object, [options:Object,] \n  predicate:Function, done:Function )\n    Tests whether all elements in a collection pass a test implemented by a\n    predicate function.\n","everyByAsync.factory":"\neveryByAsync.factory( [options:Object,] predicate:Function )\n    Returns a function which tests whether all elements in a collection pass a\n    test implemented by a predicate function.\n","everyByRight":"\neveryByRight( collection:Array|TypedArray|Object, predicate:Function[, \n  thisArg:any ] )\n    Tests whether all elements in a collection pass a test implemented by a\n    predicate function, iterating from right to left.\n","everyByRightAsync":"\neveryByRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n  predicate:Function, done:Function )\n    Tests whether all elements in a collection pass a test implemented by a\n    predicate function, iterating from right to left.\n","everyByRightAsync.factory":"\neveryByRightAsync.factory( [options:Object,] predicate:Function )\n    Returns a function which tests whether all elements in a collection pass a\n    test implemented by a predicate function, iterating from right to left.\n","everyInBy":"\neveryInBy( object:Object, predicate:Function[, thisArg:any ] )\n   Test whether all properties (own and inherited) of an object pass a\n   test implemented by a predicate function.\n","everyOwnBy":"\neveryOwnBy( object:Object, predicate:Function[, thisArg:any ] )\n    Tests whether every own property of an object pass a test implemented by a\n    predicate function.\n","evil":"\nevil( str:string )\n    Alias for `eval` global.\n","EXEC_PATH":"\nEXEC_PATH\n    Absolute pathname of the executable which started the current Node.js\n    process.\n","exists":"\nexists( path:string|Buffer, clbk:Function )\n    Asynchronously tests whether a path exists on the filesystem.\n","exists.sync":"\nexists.sync( path:string|Buffer )\n    Synchronously tests whether a path exists on the filesystem.\n","expandAcronyms":"\nexpandAcronyms( str:string )\n    Expands acronyms in a string.\n","expandContractions":"\nexpandContractions( str:string )\n    Expands all contractions to their formal equivalents.\n","extname":"\nextname( filename:string )\n    Returns a filename extension.\n","FancyArray":"\nFancyArray( dtype:string, buffer:ArrayLikeObject|TypedArray|Buffer, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  offset:integer, order:string[, options:Object] )\n    Returns a FancyArray instance.\n","FancyArray.prototype.byteLength":"\nFancyArray.prototype.byteLength\n    Size (in bytes) of the array (if known).\n","FancyArray.prototype.BYTES_PER_ELEMENT":"\nFancyArray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element (if known).\n","FancyArray.prototype.data":"\nFancyArray.prototype.data\n    Pointer to the underlying data buffer.\n","FancyArray.prototype.dtype":"\nFancyArray.prototype.dtype\n    Underlying data type.\n","FancyArray.prototype.flags":"\nFancyArray.prototype.flags\n    Meta information, such as information concerning the memory layout of the\n    array.\n","FancyArray.prototype.length":"\nFancyArray.prototype.length\n    Length of the array (i.e., number of elements).\n","FancyArray.prototype.ndims":"\nFancyArray.prototype.ndims\n    Number of dimensions.\n","FancyArray.prototype.offset":"\nFancyArray.prototype.offset\n    Index offset which specifies the buffer index at which to start iterating\n    over array elements.\n","FancyArray.prototype.order":"\nFancyArray.prototype.order\n    Array order.\n","FancyArray.prototype.shape":"\nFancyArray.prototype.shape\n    Array shape.\n","FancyArray.prototype.strides":"\nFancyArray.prototype.strides\n    Index strides which specify how to access data along corresponding array\n    dimensions.\n","FancyArray.prototype.get":"\nFancyArray.prototype.get( ...idx:integer )\n    Returns an array element specified according to provided subscripts.\n","FancyArray.prototype.iget":"\nFancyArray.prototype.iget( idx:integer )\n    Returns an array element located at a specified linear index.\n","FancyArray.prototype.set":"\nFancyArray.prototype.set( ...idx:integer, v:any )\n    Sets an array element specified according to provided subscripts.\n","FancyArray.prototype.iset":"\nFancyArray.prototype.iset( idx:integer, v:any )\n    Sets an array element located at a specified linear index.\n","FancyArray.prototype.toString":"\nFancyArray.prototype.toString()\n    Serializes a FancyArray as a string.\n","FancyArray.prototype.toJSON":"\nFancyArray.prototype.toJSON()\n    Serializes a FancyArray as a JSON object.\n","fastmath.abs":"\nfastmath.abs( x:number )\n    Computes an absolute value.\n","fastmath.acosh":"\nfastmath.acosh( x:number )\n    Computes the hyperbolic arccosine of a number.\n","fastmath.ampbm":"\nfastmath.ampbm( x:number, y:number )\n    Computes the hypotenuse using the alpha max plus beta min algorithm.\n","fastmath.ampbm.factory":"\nfastmath.ampbm.factory( alpha:number, beta:number, [nonnegative:boolean[, \n  ints:boolean]] )\n    Returns a function to compute a hypotenuse using the alpha max plus beta min\n    algorithm.\n","fastmath.asinh":"\nfastmath.asinh( x:number )\n    Computes the hyperbolic arcsine of a number.\n","fastmath.atanh":"\nfastmath.atanh( x:number )\n    Computes the hyperbolic arctangent of a number.\n","fastmath.hypot":"\nfastmath.hypot( x:number, y:number )\n    Computes the hypotenuse.\n","fastmath.log2Uint32":"\nfastmath.log2Uint32( x:uinteger )\n    Returns an approximate binary logarithm (base two) of an unsigned 32-bit\n    integer `x`.\n","fastmath.max":"\nfastmath.max( x:number, y:number )\n    Returns the maximum value.\n","fastmath.min":"\nfastmath.min( x:number, y:number )\n    Returns the minimum value.\n","fastmath.powint":"\nfastmath.powint( x:number, y:integer )\n    Evaluates the exponential function given a signed 32-bit integer exponent.\n","fastmath.sqrtUint32":"\nfastmath.sqrtUint32( x:uinteger )\n    Returns an approximate square root of an unsigned 32-bit integer `x`.\n","FEMALE_FIRST_NAMES_EN":"\nFEMALE_FIRST_NAMES_EN()\n    Returns a list of common female first names in English speaking countries.\n","FIFO":"\nFIFO()\n    First-in-first-out (FIFO) queue constructor.\n","filledarray":"\nfilledarray( [dtype:string] )\n    Creates a filled array.\n\nfilledarray( value:any, length:integer[, dtype:string] )\n    Returns a filled array having a specified length.\n\nfilledarray( value:any, array:ArrayLikeObject[, dtype:string] )\n    Creates a filled array from another array (or array-like object).\n\nfilledarray( value:any, iterable:Iterable[, dtype:string] )\n    Creates a filled array from an iterable.\n\nfilledarray( value:any, buffer:ArrayBuffer[, byteOffset:integer[, \n  length:integer]][, dtype:string] )\n    Returns a filled typed array view of an ArrayBuffer.\n","filledarrayBy":"\nfilledarrayBy( [dtype:string] )\n    Creates a filled array.\n\nfilledarrayBy( length:integer[, dtype:string], clbk:Function[, thisArg:any] )\n    Returns a filled array according to a provided callback function and having\n    a specified length.\n\nfilledarrayBy( array:ArrayLikeObject[, dtype:string], clbk:Function[, \n  thisArg:any] )\n    Creates a filled array from another array (or array-like object) according\n    to a provided callback function.\n\nfilledarrayBy( iterable:Iterable[, dtype:string], clbk:Function[, thisArg:any] )\n    Creates a filled array from an iterable according to a provided callback\n    function.\n\nfilledarrayBy( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n  dtype:string], clbk:Function[, thisArg:any] )\n    Returns a filled typed array view of an ArrayBuffer according to a provided\n    callback function.\n","filterArguments":"\nfilterArguments( fcn:Function, predicate:Function[, thisArg:any] )\n    Returns a function that applies arguments to a provided function according\n    to a predicate function.\n","find":"\nfind( arr:Array|TypedArray|string, [options:Object,] clbk:Function )\n    Finds elements in an array-like object that satisfy a test condition.\n","firstChar":"\nfirstChar( str:string[, n:integer][, options:Object] )\n    Returns the first character(s) of a string.\n","FIVETHIRTYEIGHT_FFQ":"\nFIVETHIRTYEIGHT_FFQ()\n    Returns FiveThirtyEight reader responses to a food frequency questionnaire\n    (FFQ).\n","flattenArray":"\nflattenArray( arr:ArrayLikeObject[, options:Object] )\n    Flattens an array.\n","flattenArray.factory":"\nflattenArray.factory( dims:ArrayLike<integer>[, options:Object] )\n    Returns a function for flattening arrays having specified dimensions.\n","flattenObject":"\nflattenObject( obj:ObjectLike[, options:Object] )\n    Flattens an object.\n","flattenObject.factory":"\nflattenObject.factory( [options:Object] )\n    Returns a function to flatten an object.\n","flignerTest":"\nflignerTest( ...x:Array[, options:Object] )\n    Computes the Fligner-Killeen test for equal variances.\n","FLOAT_WORD_ORDER":"\nFLOAT_WORD_ORDER\n    Platform float word order.\n","FLOAT16_CBRT_EPS":"\nFLOAT16_CBRT_EPS\n    Cube root of half-precision floating-point epsilon.\n","FLOAT16_EPS":"\nFLOAT16_EPS\n    Difference between one and the smallest value greater than one that can be\n    represented as a half-precision floating-point number.\n","FLOAT16_EXPONENT_BIAS":"\nFLOAT16_EXPONENT_BIAS\n    The bias of a half-precision floating-point number's exponent.\n","FLOAT16_MAX":"\nFLOAT16_MAX\n    Maximum half-precision floating-point number.\n","FLOAT16_MAX_SAFE_INTEGER":"\nFLOAT16_MAX_SAFE_INTEGER\n    Maximum safe half-precision floating-point integer.\n","FLOAT16_MIN_SAFE_INTEGER":"\nFLOAT16_MIN_SAFE_INTEGER\n    Minimum safe half-precision floating-point integer.\n","FLOAT16_NINF":"\nFLOAT16_NINF\n    Half-precision floating-point negative infinity.\n","FLOAT16_NUM_BYTES":"\nFLOAT16_NUM_BYTES\n    Size (in bytes) of a half-precision floating-point number.\n","FLOAT16_PINF":"\nFLOAT16_PINF\n    Half-precision floating-point positive infinity.\n","FLOAT16_PRECISION":"\nFLOAT16_PRECISION\n    Effective number of bits in the significand of a half-precision floating-\n    point number.\n","FLOAT16_SMALLEST_NORMAL":"\nFLOAT16_SMALLEST_NORMAL\n    Smallest positive normalized half-precision floating-point number.\n","FLOAT16_SMALLEST_SUBNORMAL":"\nFLOAT16_SMALLEST_SUBNORMAL\n    Smallest positive denormalized half-precision floating-point number.\n","FLOAT16_SQRT_EPS":"\nFLOAT16_SQRT_EPS\n    Square root of half-precision floating-point epsilon.\n","FLOAT32_ABS_MASK":"\nFLOAT32_ABS_MASK\n    Mask for excluding the sign bit of a single-precision floating-point number.\n","FLOAT32_CBRT_EPS":"\nFLOAT32_CBRT_EPS\n    Cube root of single-precision floating-point epsilon.\n","FLOAT32_E":"\nFLOAT32_E\n    Euler's number.\n","FLOAT32_EPS":"\nFLOAT32_EPS\n    Difference between one and the smallest value greater than one that can be\n    represented as a single-precision floating-point number.\n","FLOAT32_EXPONENT_BIAS":"\nFLOAT32_EXPONENT_BIAS\n    The bias of a single-precision floating-point number's exponent.\n","FLOAT32_EXPONENT_MASK":"\nFLOAT32_EXPONENT_MASK\n    Mask for the exponent of a single-precision floating-point number.\n","FLOAT32_FOURTH_PI":"\nFLOAT32_FOURTH_PI\n    One fourth times the mathematical constant `π`.\n","FLOAT32_HALF_LN_TWO":"\nFLOAT32_HALF_LN_TWO\n    One half times the natural logarithm of 2 as a single-precision\n    floating-point number.\n","FLOAT32_HALF_PI":"\nFLOAT32_HALF_PI\n    One half times the mathematical constant `π`.\n","FLOAT32_LN_HALF":"\nFLOAT32_LN_HALF\n    Natural logarithm of `1/2` as a single-precision floating-point number.\n","FLOAT32_LN_PI":"\nFLOAT32_LN_PI\n    Natural logarithm of the mathematical constant `π` as a single-precision\n    floating-point number.\n","FLOAT32_LN_TEN":"\nFLOAT32_LN_TEN\n    Natural logarithm of `10` as a single-precision floating-point number.\n","FLOAT32_LN_TWO":"\nFLOAT32_LN_TWO\n    Natural logarithm of `2` as a single-precision floating-point number.\n","FLOAT32_MAX":"\nFLOAT32_MAX\n    Maximum single-precision floating-point number.\n","FLOAT32_MAX_BASE2_EXPONENT":"\nFLOAT32_MAX_BASE2_EXPONENT\n    The maximum biased base 2 exponent for a single-precision floating-point\n    number.\n","FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL\n    The maximum biased base 2 exponent for a subnormal single-precision\n    floating-point number.\n","FLOAT32_MAX_BASE10_EXPONENT":"\nFLOAT32_MAX_BASE10_EXPONENT\n    The maximum base 10 exponent for a single-precision floating-point number.\n","FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL\n    The maximum base 10 exponent for a subnormal single-precision floating-point\n    number.\n","FLOAT32_MAX_SAFE_FIBONACCI":"\nFLOAT32_MAX_SAFE_FIBONACCI\n    Maximum safe Fibonacci number when stored in single-precision floating-point\n    format.\n","FLOAT32_MAX_SAFE_INTEGER":"\nFLOAT32_MAX_SAFE_INTEGER\n    Maximum safe single-precision floating-point integer.\n","FLOAT32_MAX_SAFE_NTH_FACTORIAL":"\nFLOAT32_MAX_SAFE_NTH_FACTORIAL\n    Maximum safe nth factorial when stored in single-precision floating-\n    point format.\n","FLOAT32_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT32_MAX_SAFE_NTH_FIBONACCI\n    Maximum safe nth Fibonacci number when stored in single-precision floating-\n    point format.\n","FLOAT32_MAX_SAFE_NTH_LUCAS":"\nFLOAT32_MAX_SAFE_NTH_LUCAS\n    Maximum safe nth Lucas number when stored in single-precision floating-point\n    format.\n","FLOAT32_MIN_BASE2_EXPONENT":"\nFLOAT32_MIN_BASE2_EXPONENT\n    The minimum biased base 2 exponent for a normalized single-precision\n    floating-point number.\n","FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL\n    The minimum biased base 2 exponent for a subnormal single-precision\n    floating-point number.\n","FLOAT32_MIN_BASE10_EXPONENT":"\nFLOAT32_MIN_BASE10_EXPONENT\n    The minimum base 10 exponent for a normal single-precision floating-\n    point number.\n","FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL\n    The minimum base 10 exponent for a subnormal single-precision floating-\n    point number.\n","FLOAT32_MIN_SAFE_INTEGER":"\nFLOAT32_MIN_SAFE_INTEGER\n    Minimum safe single-precision floating-point integer.\n","FLOAT32_NAN":"\nFLOAT32_NAN\n    Single-precision floating-point NaN.\n","FLOAT32_NINF":"\nFLOAT32_NINF\n    Single-precision floating-point negative infinity.\n","FLOAT32_NUM_BYTES":"\nFLOAT32_NUM_BYTES\n    Size (in bytes) of a single-precision floating-point number.\n","FLOAT32_PHI":"\nFLOAT32_PHI\n    Golden ratio.\n","FLOAT32_PI":"\nFLOAT32_PI\n    The mathematical constant `π`.\n","FLOAT32_PINF":"\nFLOAT32_PINF\n    Single-precision floating-point positive infinity.\n","FLOAT32_PRECISION":"\nFLOAT32_PRECISION\n    Effective number of bits in the significand of a single-precision floating-\n    point number.\n","FLOAT32_SIGN_MASK":"\nFLOAT32_SIGN_MASK\n    Mask for the sign bit of a single-precision floating-point number.\n","FLOAT32_SIGNIFICAND_MASK":"\nFLOAT32_SIGNIFICAND_MASK\n    Mask for the significand of a single-precision floating-point number.\n","FLOAT32_SMALLEST_NORMAL":"\nFLOAT32_SMALLEST_NORMAL\n    Smallest positive normalized single-precision floating-point number.\n","FLOAT32_SMALLEST_SUBNORMAL":"\nFLOAT32_SMALLEST_SUBNORMAL\n    Smallest positive denormalized single-precision floating-point number.\n","FLOAT32_SQRT_EPS":"\nFLOAT32_SQRT_EPS\n    Square root of single-precision floating-point epsilon.\n","FLOAT32_SQRT_HALF":"\nFLOAT32_SQRT_HALF\n    Square root of `1/2` as a single-precision floating-point number.\n","FLOAT32_SQRT_HALF_PI":"\nFLOAT32_SQRT_HALF_PI\n    Square root of `π` divided by `2` as a single-precision \n    floating-point number.\n","FLOAT32_SQRT_PHI":"\nFLOAT32_SQRT_PHI\n    Square root of the golden ratio as a single-precision floating-point number.\n","FLOAT32_SQRT_PI":"\nFLOAT32_SQRT_PI\n    Square root of the mathematical constant `π` as a single-precision\n    floating-point number.\n","FLOAT32_SQRT_THREE":"\nFLOAT32_SQRT_THREE\n    Square root of `3` as a single-precision floating-point number.\n","FLOAT32_SQRT_TWO":"\nFLOAT32_SQRT_TWO\n    Square root of `2` as a single-precision floating-point number.\n","FLOAT32_SQRT_TWO_PI":"\nFLOAT32_SQRT_TWO_PI\n    Square root of the `π` times `2` as single-precision floating-point number.\n","FLOAT32_TWO_PI":"\nFLOAT32_TWO_PI\n    The mathematical constant `π` times `2`.\n","Float32Array":"\nFloat32Array()\n    A typed array constructor which returns a typed array representing an array\n    of single-precision floating-point numbers in the platform byte order.\n\nFloat32Array( length:integer )\n    Returns a typed array having a specified length.\n\nFloat32Array( typedarray:TypedArray )\n    Creates a typed array from another typed array.\n\nFloat32Array( obj:Object )\n    Creates a typed array from an array-like object or iterable.\n\nFloat32Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a typed array view of an ArrayBuffer.\n","Float32Array.from":"\nFloat32Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n    Creates a new typed array from an array-like object or an iterable.\n","Float32Array.of":"\nFloat32Array.of( element0:number[, element1:number[, ...elementN:number]] )\n    Creates a new typed array from a variable number of arguments.\n","Float32Array.BYTES_PER_ELEMENT":"\nFloat32Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Float32Array.name":"\nFloat32Array.name\n    Typed array constructor name.\n","Float32Array.prototype.buffer":"\nFloat32Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n","Float32Array.prototype.byteLength":"\nFloat32Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n","Float32Array.prototype.byteOffset":"\nFloat32Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n","Float32Array.prototype.BYTES_PER_ELEMENT":"\nFloat32Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Float32Array.prototype.length":"\nFloat32Array.prototype.length\n    Read-only property which returns the number of view elements.\n","Float32Array.prototype.copyWithin":"\nFloat32Array.prototype.copyWithin( target:integer, start:integer[, \n  end:integer] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","Float32Array.prototype.entries":"\nFloat32Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","Float32Array.prototype.every":"\nFloat32Array.prototype.every( predicate:Function[, thisArg:Any] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n","Float32Array.prototype.fill":"\nFloat32Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n","Float32Array.prototype.filter":"\nFloat32Array.prototype.filter( predicate:Function[, thisArg:Any] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n","Float32Array.prototype.find":"\nFloat32Array.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n","Float32Array.prototype.findIndex":"\nFloat32Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n","Float32Array.prototype.forEach":"\nFloat32Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n    Invokes a callback for each array element.\n","Float32Array.prototype.includes":"\nFloat32Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a search element.\n","Float32Array.prototype.indexOf":"\nFloat32Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n","Float32Array.prototype.join":"\nFloat32Array.prototype.join( [separator:string] )\n    Serializes an array by joining all array elements as a string.\n","Float32Array.prototype.keys":"\nFloat32Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n","Float32Array.prototype.lastIndexOf":"\nFloat32Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n","Float32Array.prototype.map":"\nFloat32Array.prototype.map( fcn:Function[, thisArg:Any] )\n    Maps each array element to an element in a new typed array.\n","Float32Array.prototype.reduce":"\nFloat32Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n","Float32Array.prototype.reduceRight":"\nFloat32Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n","Float32Array.prototype.reverse":"\nFloat32Array.prototype.reverse()\n    Reverses an array *in-place*.\n","Float32Array.prototype.set":"\nFloat32Array.prototype.set( arr:ArrayLike[, offset:integer] )\n    Sets array elements.\n","Float32Array.prototype.slice":"\nFloat32Array.prototype.slice( [begin:integer[, end:integer]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n","Float32Array.prototype.some":"\nFloat32Array.prototype.some( predicate:Function[, thisArg:Any] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n","Float32Array.prototype.sort":"\nFloat32Array.prototype.sort( [compareFunction:Function] )\n    Sorts an array *in-place*.\n","Float32Array.prototype.subarray":"\nFloat32Array.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n","Float32Array.prototype.toLocaleString":"\nFloat32Array.prototype.toLocaleString( [locales:string|Array[, \n  options:Object]] )\n    Serializes an array as a locale-specific string.\n","Float32Array.prototype.toString":"\nFloat32Array.prototype.toString()\n    Serializes an array as a string.\n","Float32Array.prototype.values":"\nFloat32Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n","FLOAT64_EXPONENT_BIAS":"\nFLOAT64_EXPONENT_BIAS\n    The bias of a double-precision floating-point number's exponent.\n","FLOAT64_HIGH_WORD_ABS_MASK":"\nFLOAT64_HIGH_WORD_ABS_MASK\n    High word mask for excluding the sign bit of a double-precision floating-\n    point number.\n","FLOAT64_HIGH_WORD_EXPONENT_MASK":"\nFLOAT64_HIGH_WORD_EXPONENT_MASK\n    High word mask for the exponent of a double-precision floating-point number.\n","FLOAT64_HIGH_WORD_SIGN_MASK":"\nFLOAT64_HIGH_WORD_SIGN_MASK\n    High word mask for the sign bit of a double-precision floating-point number.\n","FLOAT64_HIGH_WORD_SIGNIFICAND_MASK":"\nFLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n    High word mask for the significand of a double-precision floating-point\n    number.\n","FLOAT64_MAX":"\nFLOAT64_MAX\n    Maximum double-precision floating-point number.\n","FLOAT64_MAX_BASE2_EXPONENT":"\nFLOAT64_MAX_BASE2_EXPONENT\n    The maximum biased base 2 exponent for a double-precision floating-point\n    number.\n","FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n    The maximum biased base 2 exponent for a subnormal double-precision\n    floating-point number.\n","FLOAT64_MAX_BASE10_EXPONENT":"\nFLOAT64_MAX_BASE10_EXPONENT\n    The maximum base 10 exponent for a double-precision floating-point number.\n","FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n    The maximum base 10 exponent for a subnormal double-precision floating-point\n    number.\n","FLOAT64_MAX_LN":"\nFLOAT64_MAX_LN\n    Natural logarithm of the maximum double-precision floating-point number.\n","FLOAT64_MAX_SAFE_FIBONACCI":"\nFLOAT64_MAX_SAFE_FIBONACCI\n    Maximum safe Fibonacci number when stored in double-precision floating-point\n    format.\n","FLOAT64_MAX_SAFE_INTEGER":"\nFLOAT64_MAX_SAFE_INTEGER\n    Maximum safe double-precision floating-point integer.\n","FLOAT64_MAX_SAFE_LUCAS":"\nFLOAT64_MAX_SAFE_LUCAS\n    Maximum safe Lucas number when stored in double-precision floating-point\n    format.\n","FLOAT64_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT64_MAX_SAFE_NTH_FIBONACCI\n    Maximum safe nth Fibonacci number when stored in double-precision floating-\n    point format.\n","FLOAT64_MAX_SAFE_NTH_LUCAS":"\nFLOAT64_MAX_SAFE_NTH_LUCAS\n    Maximum safe nth Lucas number when stored in double-precision floating-point\n    format.\n","FLOAT64_MIN_BASE2_EXPONENT":"\nFLOAT64_MIN_BASE2_EXPONENT\n    The minimum biased base 2 exponent for a normalized double-precision\n    floating-point number.\n","FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n    The minimum biased base 2 exponent for a subnormal double-precision\n    floating-point number.\n","FLOAT64_MIN_BASE10_EXPONENT":"\nFLOAT64_MIN_BASE10_EXPONENT\n    The minimum base 10 exponent for a normalized double-precision floating-\n    point number.\n","FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n    The minimum base 10 exponent for a subnormal double-precision floating-\n    point number.\n","FLOAT64_MIN_LN":"\nFLOAT64_MIN_LN\n    Natural logarithm of the smallest normalized double-precision floating-point\n    number.\n","FLOAT64_MIN_SAFE_INTEGER":"\nFLOAT64_MIN_SAFE_INTEGER\n    Minimum safe double-precision floating-point integer.\n","FLOAT64_NUM_BYTES":"\nFLOAT64_NUM_BYTES\n    Size (in bytes) of a double-precision floating-point number.\n","FLOAT64_PRECISION":"\nFLOAT64_PRECISION\n    Effective number of bits in the significand of a double-precision floating-\n    point number.\n","FLOAT64_SMALLEST_NORMAL":"\nFLOAT64_SMALLEST_NORMAL\n    Smallest positive normalized double-precision floating-point number.\n","FLOAT64_SMALLEST_SUBNORMAL":"\nFLOAT64_SMALLEST_SUBNORMAL\n    Smallest positive denormalized double-precision floating-point number.\n","Float64Array":"\nFloat64Array()\n    A typed array constructor which returns a typed array representing an array\n    of double-precision floating-point numbers in the platform byte order.\n\nFloat64Array( length:integer )\n    Returns a typed array having a specified length.\n\nFloat64Array( typedarray:TypedArray )\n    Creates a typed array from another typed array.\n\nFloat64Array( obj:Object )\n    Creates a typed array from an array-like object or iterable.\n\nFloat64Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a typed array view of an ArrayBuffer.\n","Float64Array.from":"\nFloat64Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n    Creates a new typed array from an array-like object or an iterable.\n","Float64Array.of":"\nFloat64Array.of( element0:number[, element1:number[, ...elementN:number]] )\n    Creates a new typed array from a variable number of arguments.\n","Float64Array.BYTES_PER_ELEMENT":"\nFloat64Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Float64Array.name":"\nFloat64Array.name\n    Typed array constructor name.\n","Float64Array.prototype.buffer":"\nFloat64Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n","Float64Array.prototype.byteLength":"\nFloat64Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n","Float64Array.prototype.byteOffset":"\nFloat64Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n","Float64Array.prototype.BYTES_PER_ELEMENT":"\nFloat64Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Float64Array.prototype.length":"\nFloat64Array.prototype.length\n    Read-only property which returns the number of view elements.\n","Float64Array.prototype.copyWithin":"\nFloat64Array.prototype.copyWithin( target:integer, start:integer[, \n  end:integer] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","Float64Array.prototype.entries":"\nFloat64Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","Float64Array.prototype.every":"\nFloat64Array.prototype.every( predicate:Function[, thisArg:Any] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n","Float64Array.prototype.fill":"\nFloat64Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n","Float64Array.prototype.filter":"\nFloat64Array.prototype.filter( predicate:Function[, thisArg:Any] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n","Float64Array.prototype.find":"\nFloat64Array.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n","Float64Array.prototype.findIndex":"\nFloat64Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n","Float64Array.prototype.forEach":"\nFloat64Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n    Invokes a callback for each array element.\n","Float64Array.prototype.includes":"\nFloat64Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a search element.\n","Float64Array.prototype.indexOf":"\nFloat64Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n","Float64Array.prototype.join":"\nFloat64Array.prototype.join( [separator:string] )\n    Serializes an array by joining all array elements as a string.\n","Float64Array.prototype.keys":"\nFloat64Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n","Float64Array.prototype.lastIndexOf":"\nFloat64Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n","Float64Array.prototype.map":"\nFloat64Array.prototype.map( fcn:Function[, thisArg:Any] )\n    Maps each array element to an element in a new typed array.\n","Float64Array.prototype.reduce":"\nFloat64Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n","Float64Array.prototype.reduceRight":"\nFloat64Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n","Float64Array.prototype.reverse":"\nFloat64Array.prototype.reverse()\n    Reverses an array *in-place*.\n","Float64Array.prototype.set":"\nFloat64Array.prototype.set( arr:ArrayLike[, offset:integer] )\n    Sets array elements.\n","Float64Array.prototype.slice":"\nFloat64Array.prototype.slice( [begin:integer[, end:integer]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n","Float64Array.prototype.some":"\nFloat64Array.prototype.some( predicate:Function[, thisArg:Any] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n","Float64Array.prototype.sort":"\nFloat64Array.prototype.sort( [compareFunction:Function] )\n    Sorts an array *in-place*.\n","Float64Array.prototype.subarray":"\nFloat64Array.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n","Float64Array.prototype.toLocaleString":"\nFloat64Array.prototype.toLocaleString( [locales:string|Array[, \n  options:Object]] )\n    Serializes an array as a locale-specific string.\n","Float64Array.prototype.toString":"\nFloat64Array.prototype.toString()\n    Serializes an array as a string.\n","Float64Array.prototype.values":"\nFloat64Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n","forEach":"\nforEach( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n    Invokes a function for each element in a collection.\n","forEachAsync":"\nforEachAsync( collection:Array|TypedArray|Object, [options:Object,] \n  fcn:Function, done:Function )\n    Invokes a function once for each element in a collection.\n","forEachAsync.factory":"\nforEachAsync.factory( [options:Object,] fcn:Function )\n    Returns a function which invokes a function once for each element in a\n    collection.\n","forEachChar":"\nforEachChar( str:string, [options:Object,] clbk:Function[, thisArg:any] )\n    Invokes a function for each character in a string.\n","forEachRight":"\nforEachRight( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n    Invokes a function for each element in a collection, iterating from right to\n    left.\n","forEachRightAsync":"\nforEachRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n  fcn:Function, done:Function )\n    Invokes a function once for each element in a collection, iterating from\n    right to left.\n","forEachRightAsync.factory":"\nforEachRightAsync.factory( [options:Object,] fcn:Function )\n    Returns a function which invokes a function once for each element in a\n    collection, iterating from right to left.\n","forIn":"\nforIn( obj:Object, fcn:Function[, thisArg:any] )\n    Invokes a function for each own and inherited enumerable property of an\n    object.\n","format":"\nformat( str:string, ...args:any )\n    Insert supplied variable values into a format string.\n","forOwn":"\nforOwn( obj:Object, fcn:Function[, thisArg:any] )\n    Invokes a function for each own enumerable property of an object.\n","FOURTH_PI":"\nFOURTH_PI\n    One fourth times the mathematical constant `π`.\n","FOURTH_ROOT_EPS":"\nFOURTH_ROOT_EPS\n    Fourth root of double-precision floating-point epsilon.\n","FRB_SF_WAGE_RIGIDITY":"\nFRB_SF_WAGE_RIGIDITY()\n    Returns wage rates for U.S. workers that have not changed jobs within the\n    year.\n","fromCodePoint":"\nfromCodePoint( ...pt:integer )\n    Creates a string from a sequence of Unicode code points.\n","Function":"\nFunction( [...argNames:any,] body:string )\n    Returns a Function object.\n","Function.prototype.apply":"\nFunction.prototype.apply( thisArg:any, args:Array )\n    Calls a function with a given `this` value and arguments provided as an\n    array (or array-like object).\n","Function.prototype.call":"\nFunction.prototype.call( thisArg:any, ...args:any )\n    Calls a function with a given `this` value and arguments provided\n    individually.\n","Function.prototype.bind":"\nFunction.prototype.bind( thisArg:any, ...args:any )\n    Creates a new function which, when called, has its `this` keyword set to the\n    provided value, with a given sequence of arguments preceding any provided\n    when the new function is called.\n","Function.prototype.toString":"\nFunction.prototype.toString()\n    Returns a string representation of the function.\n","Function.prototype.length":"\nFunction.prototype.length\n    The number of arguments expected by the function.\n","Function.prototype.name":"\nFunction.prototype.name\n    The name of the function.\n","Function.prototype.prototype":"\nFunction.prototype.prototype\n    The prototype of the function.\n","function2string":"\nfunction2string( fcn:Function )\n    Returns a string representing the source code of a provided function.\n","functionName":"\nfunctionName( fcn:Function )\n    Returns the name of a function.\n","functionSequence":"\nfunctionSequence( ...fcn:Function )\n    Returns a pipeline function.\n","functionSequenceAsync":"\nfunctionSequenceAsync( ...fcn:Function )\n    Returns a pipeline function.\n","GAMMA_LANCZOS_G":"\nGAMMA_LANCZOS_G\n    Arbitrary constant `g` to be used in Lanczos approximation functions.\n","gdot":"\ngdot( x:ndarray|ArrayLikeObject, y:ndarray|ArrayLikeObject )\n    Computes the dot product of two vectors.\n","getegid":"\ngetegid()\n    Returns the effective numeric group identity of the calling process.\n","geteuid":"\ngeteuid()\n    Returns the effective numeric user identity of the calling process.\n","getgid":"\ngetgid()\n    Returns the numeric group identity of the calling process.\n","getGlobal":"\ngetGlobal( [codegen:boolean] )\n    Returns the global object.\n","getPrototypeOf":"\ngetPrototypeOf( value:any )\n    Returns the prototype of a provided object.\n","getuid":"\ngetuid()\n    Returns the numeric user identity of the calling process.\n","GLAISHER":"\nGLAISHER\n    Glaisher-Kinkelin constant.\n","graphemeClusters2iterator":"\ngraphemeClusters2iterator( src:string[, mapFcn:Function[, thisArg:any]] )\n    Returns an iterator which iterates over each grapheme cluster in a string.\n","graphemeClusters2iteratorRight":"\ngraphemeClusters2iteratorRight( src:string[, mapFcn:Function[, thisArg:any]] )\n    Returns an iterator which iterates from right to left over each grapheme\n    cluster in a string.\n","group":"\ngroup( collection:Array|TypedArray|Object, [options:Object,] \n  groups:Array|TypedArray|Object )\n    Groups values as arrays associated with distinct keys.\n","groupBy":"\ngroupBy( collection:Array|TypedArray|Object, [options:Object,] \n  indicator:Function )\n    Groups values according to an indicator function.\n","groupByAsync":"\ngroupByAsync( collection:Array|TypedArray|Object, [options:Object,] \n  indicator:Function, done:Function )\n    Groups values according to an indicator function.\n","groupByAsync.factory":"\ngroupByAsync.factory( [options:Object,] indicator:Function )\n    Returns a function which groups values according to an indicator function.\n","groupIn":"\ngroupIn( obj:Object|Array|TypedArray, [options:Object,] indicator:Function )\n    Group values according to an indicator function.\n","groupOwn":"\ngroupOwn( obj:Object|Array|TypedArray, [options:Object,] indicator:Function )\n    Group values according to an indicator function.\n","gswap":"\ngswap( x:ndarray|ArrayLikeObject, y:ndarray|ArrayLikeObject )\n    Interchanges two vectors.\n","HALF_LN2":"\nHALF_LN2\n    One half times the natural logarithm of `2`.\n","HALF_PI":"\nHALF_PI\n    One half times the mathematical constant `π`.\n","HARRISON_BOSTON_HOUSE_PRICES":"\nHARRISON_BOSTON_HOUSE_PRICES()\n    Returns a dataset derived from information collected by the US Census\n    Service concerning housing in Boston, Massachusetts (1978).\n","HARRISON_BOSTON_HOUSE_PRICES_CORRECTED":"\nHARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n    Returns a (corrected) dataset derived from information collected by the US\n    Census Service concerning housing in Boston, Massachusetts (1978).\n","hasArrayBufferSupport":"\nhasArrayBufferSupport()\n    Tests for native `ArrayBuffer` support.\n","hasArrowFunctionSupport":"\nhasArrowFunctionSupport()\n    Tests whether an environment supports native arrow functions.\n","hasAsyncAwaitSupport":"\nhasAsyncAwaitSupport()\n    Tests for native `async`/`await` support.\n","hasAsyncIteratorSymbolSupport":"\nhasAsyncIteratorSymbolSupport()\n    Tests for native `Symbol.asyncIterator` support.\n","hasAtobSupport":"\nhasAtobSupport()\n    Tests for native `atob` support.\n","hasBigInt64ArraySupport":"\nhasBigInt64ArraySupport()\n    Tests for native `BigInt64Array` support.\n","hasBigIntSupport":"\nhasBigIntSupport()\n    Tests for native `BigInt` support.\n","hasBigUint64ArraySupport":"\nhasBigUint64ArraySupport()\n    Tests for native `BigUint64Array` support.\n","hasBtoaSupport":"\nhasBtoaSupport()\n    Tests for native `btoa` support.\n","hasClassSupport":"\nhasClassSupport()\n    Tests for native `class` support.\n","hasDataViewSupport":"\nhasDataViewSupport()\n    Tests for native `DataView` support.\n","hasDefinePropertiesSupport":"\nhasDefinePropertiesSupport()\n    Tests for `Object.defineProperties` support.\n","hasDefinePropertySupport":"\nhasDefinePropertySupport()\n    Tests for `Object.defineProperty` support.\n","hasFloat32ArraySupport":"\nhasFloat32ArraySupport()\n    Tests for native `Float32Array` support.\n","hasFloat64ArraySupport":"\nhasFloat64ArraySupport()\n    Tests for native `Float64Array` support.\n","hasFunctionNameSupport":"\nhasFunctionNameSupport()\n    Tests for native function `name` support.\n","hasGeneratorSupport":"\nhasGeneratorSupport()\n    Tests whether an environment supports native generator functions.\n","hasGlobalThisSupport":"\nhasGlobalThisSupport()\n    Tests for `globalThis` support.\n","hasInt8ArraySupport":"\nhasInt8ArraySupport()\n    Tests for native `Int8Array` support.\n","hasInt16ArraySupport":"\nhasInt16ArraySupport()\n    Tests for native `Int16Array` support.\n","hasInt32ArraySupport":"\nhasInt32ArraySupport()\n    Tests for native `Int32Array` support.\n","hasIteratorSymbolSupport":"\nhasIteratorSymbolSupport()\n    Tests for native `Symbol.iterator` support.\n","hasMapSupport":"\nhasMapSupport()\n    Tests for native `Map` support.\n","hasNodeBufferSupport":"\nhasNodeBufferSupport()\n    Tests for native `Buffer` support.\n","hasOwnProp":"\nhasOwnProp( value:any, property:any )\n    Tests if an object has a specified property.\n","hasProp":"\nhasProp( value:any, property:any )\n    Tests if an object has a specified property, either own or inherited.\n","hasProxySupport":"\nhasProxySupport()\n    Tests whether an environment has native `Proxy` support.\n","hasSetSupport":"\nhasSetSupport()\n    Tests for native `Set` support.\n","hasSharedArrayBufferSupport":"\nhasSharedArrayBufferSupport()\n    Tests for native `SharedArrayBuffer` support.\n","hasSymbolSupport":"\nhasSymbolSupport()\n    Tests for native `Symbol` support.\n","hasToStringTagSupport":"\nhasToStringTagSupport()\n    Tests for native `toStringTag` support.\n","hasUint8ArraySupport":"\nhasUint8ArraySupport()\n    Tests for native `Uint8Array` support.\n","hasUint8ClampedArraySupport":"\nhasUint8ClampedArraySupport()\n    Tests for native `Uint8ClampedArray` support.\n","hasUint16ArraySupport":"\nhasUint16ArraySupport()\n    Tests for native `Uint16Array` support.\n","hasUint32ArraySupport":"\nhasUint32ArraySupport()\n    Tests for native `Uint32Array` support.\n","hasUTF16SurrogatePairAt":"\nhasUTF16SurrogatePairAt( str:string, pos:integer )\n    Tests if a position in a string marks the start of a UTF-16 surrogate pair.\n","hasWeakMapSupport":"\nhasWeakMapSupport()\n    Tests for native `WeakMap` support.\n","hasWeakSetSupport":"\nhasWeakSetSupport()\n    Tests for native `WeakSet` support.\n","hasWebAssemblySupport":"\nhasWebAssemblySupport()\n    Tests for native WebAssembly support.\n","headercase":"\nheadercase( str:string )\n    Converts a string to HTTP header case.\n","HERNDON_VENUS_SEMIDIAMETERS":"\nHERNDON_VENUS_SEMIDIAMETERS()\n    Returns fifteen observations of the vertical semidiameter of Venus, made by\n    Lieutenant Herndon, with the meridian circle at Washington, in the year\n    1846.\n","homedir":"\nhomedir()\n    Returns the current user's home directory.\n","HOURS_IN_DAY":"\nHOURS_IN_DAY\n    Number of hours in a day.\n","HOURS_IN_WEEK":"\nHOURS_IN_WEEK\n    Number of hours in a week.\n","hoursInMonth":"\nhoursInMonth( [month:string|Date|integer[, year:integer]] )\n    Returns the number of hours in a month.\n","hoursInYear":"\nhoursInYear( [value:integer|Date] )\n    Returns the number of hours in a year according to the Gregorian calendar.\n","httpServer":"\nhttpServer( [options:Object,] [requestListener:Function] )\n    Returns a function to create an HTTP server.\n","identity":"\nidentity( x:any )\n    Identity function.\n","ifelse":"\nifelse( bool:boolean, x:any, y:any )\n    If a condition is truthy, returns `x`; otherwise, returns `y`.\n","ifelseAsync":"\nifelseAsync( predicate:Function, x:any, y:any, done:Function )\n    If a predicate function returns a truthy value, returns `x`; otherwise,\n    returns `y`.\n","ifthen":"\nifthen( bool:boolean, x:Function, y:Function )\n    If a condition is truthy, invoke `x`; otherwise, invoke `y`.\n","ifthenAsync":"\nifthenAsync( predicate:Function, x:Function, y:Function, done:Function )\n    If a predicate function returns a truthy value, invokes `x`; otherwise,\n    invokes `y`.\n","imag":"\nimag( z:Complex128 )\n    Returns the imaginary component of a double-precision complex floating-point\n    number.\n","imagf":"\nimagf( z:Complex64 )\n    Returns the imaginary component of a single-precision complex floating-point\n    number.\n","IMG_ACANTHUS_MOLLIS":"\nIMG_ACANTHUS_MOLLIS()\n    Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n    print *Acanthus mollis*.\n","IMG_AIRPLANE_FROM_ABOVE":"\nIMG_AIRPLANE_FROM_ABOVE()\n    Returns a `Buffer` containing image data of Fédèle Azari's gelatin silver\n    print of an airplane, viewed from above looking down.\n","IMG_ALLIUM_OREOPHILUM":"\nIMG_ALLIUM_OREOPHILUM()\n    Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n    print *Allium ostrowskianum*.\n","IMG_BLACK_CANYON":"\nIMG_BLACK_CANYON()\n    Returns a `Buffer` containing image data of Timothy H. O'Sullivan's albumen\n    silver print *Black Cañon, Colorado River, From Camp 8, Looking Above*.\n","IMG_DUST_BOWL_HOME":"\nIMG_DUST_BOWL_HOME()\n    Returns a `Buffer` containing image data of Dorothea Lange's gelatin silver\n    print of an abandoned Dust Bowl home.\n","IMG_FRENCH_ALPINE_LANDSCAPE":"\nIMG_FRENCH_ALPINE_LANDSCAPE()\n    Returns a `Buffer` containing image data of Adolphe Braun's carbon print of\n    a French alpine landscape.\n","IMG_LOCOMOTION_HOUSE_CAT":"\nIMG_LOCOMOTION_HOUSE_CAT()\n    Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n    collotype of a house cat (24 views).\n","IMG_LOCOMOTION_NUDE_MALE":"\nIMG_LOCOMOTION_NUDE_MALE()\n    Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n    collotype of a nude male moving in place (48 views).\n","IMG_MARCH_PASTORAL":"\nIMG_MARCH_PASTORAL()\n    Returns a `Buffer` containing image data of Peter Henry Emerson's\n    photogravure of sheep in a pastoral setting.\n","IMG_NAGASAKI_BOATS":"\nIMG_NAGASAKI_BOATS()\n    Returns a `Buffer` containing image data of Felice Beato's albumen silver\n    print of boats in a river in Nagasaki.\n","incrapcorr":"\nincrapcorr( [mx:number, my:number] )\n    Returns an accumulator function which incrementally computes the absolute\n    value of the sample Pearson product-moment correlation coefficient.\n","incrBinaryClassification":"\nincrBinaryClassification( N:integer[, options:Object] )\n    Returns an accumulator function which incrementally performs binary\n    classification using stochastic gradient descent (SGD).\n","incrcount":"\nincrcount()\n    Returns an accumulator function which incrementally updates a count.\n","incrcovariance":"\nincrcovariance( [mx:number, my:number] )\n    Returns an accumulator function which incrementally computes an unbiased\n    sample covariance.\n","incrcovmat":"\nincrcovmat( out:integer|ndarray[, means:ndarray] )\n    Returns an accumulator function which incrementally computes an unbiased\n    sample covariance matrix.\n","incrcv":"\nincrcv( [mean:number] )\n    Returns an accumulator function which incrementally computes the coefficient\n    of variation (CV).\n","increwmean":"\nincrewmean( α:number )\n    Returns an accumulator function which incrementally computes an\n    exponentially weighted mean, where α is a smoothing factor between 0 and 1.\n","increwstdev":"\nincrewstdev( α:number )\n    Returns an accumulator function which incrementally computes an\n    exponentially weighted standard deviation, where α is a smoothing factor\n    between 0 and 1.\n","increwvariance":"\nincrewvariance( α:number )\n    Returns an accumulator function which incrementally computes an\n    exponentially weighted variance, where α is a smoothing factor between 0 and\n    1.\n","incrgmean":"\nincrgmean()\n    Returns an accumulator function which incrementally computes a geometric\n    mean.\n","incrgrubbs":"\nincrgrubbs( [options:Object] )\n    Returns an accumulator function which incrementally performs Grubbs' test\n    for detecting outliers.\n","incrhmean":"\nincrhmean()\n    Returns an accumulator function which incrementally computes a harmonic\n    mean.\n","incrkmeans":"\nincrkmeans( k:integer|ndarray[, ndims:integer][, options:Object] )\n    Returns an accumulator function which incrementally partitions data into `k`\n    clusters.\n","incrkurtosis":"\nincrkurtosis()\n    Returns an accumulator function which incrementally computes a corrected\n    sample excess kurtosis.\n","incrmaape":"\nincrmaape()\n    Returns an accumulator function which incrementally computes the mean\n    arctangent absolute percentage error (MAAPE).\n","incrmae":"\nincrmae()\n    Returns an accumulator function which incrementally computes the mean\n    absolute error (MAE).\n","incrmapcorr":"\nincrmapcorr( W:integer[, mx:number, my:number] )\n    Returns an accumulator function which incrementally computes a moving\n    sample absolute Pearson product-moment correlation coefficient.\n","incrmape":"\nincrmape()\n    Returns an accumulator function which incrementally computes the mean\n    absolute percentage error (MAPE).\n","incrmax":"\nincrmax()\n    Returns an accumulator function which incrementally computes a maximum\n    value.\n","incrmaxabs":"\nincrmaxabs()\n    Returns an accumulator function which incrementally computes a maximum\n    absolute value.\n","incrmcovariance":"\nincrmcovariance( W:integer[, mx:number, my:number] )\n    Returns an accumulator function which incrementally computes a moving\n    unbiased sample covariance.\n","incrmcv":"\nincrmcv( W:integer[, mean:number] )\n    Returns an accumulator function which incrementally computes a moving\n    coefficient of variation (CV).\n","incrmda":"\nincrmda()\n    Returns an accumulator function which incrementally computes the mean\n    directional accuracy (MDA).\n","incrme":"\nincrme()\n    Returns an accumulator function which incrementally computes the mean error\n    (ME).\n","incrmean":"\nincrmean()\n    Returns an accumulator function which incrementally computes an arithmetic\n    mean.\n","incrmeanabs":"\nincrmeanabs()\n    Returns an accumulator function which incrementally computes an arithmetic\n    mean of absolute values.\n","incrmeanabs2":"\nincrmeanabs2()\n    Returns an accumulator function which incrementally computes an arithmetic\n    mean of squared absolute values.\n","incrmeanstdev":"\nincrmeanstdev( [out:Array|TypedArray] )\n    Returns an accumulator function which incrementally computes an arithmetic\n    mean and corrected sample standard deviation.\n","incrmeanvar":"\nincrmeanvar( [out:Array|TypedArray] )\n    Returns an accumulator function which incrementally computes an arithmetic\n    mean and unbiased sample variance.\n","incrmgmean":"\nincrmgmean( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    geometric mean.\n","incrmgrubbs":"\nincrmgrubbs( W:integer[, options:Object] )\n    Returns an accumulator function which incrementally performs a moving\n    Grubbs' test for detecting outliers.\n","incrmhmean":"\nincrmhmean( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    harmonic mean.\n","incrmidrange":"\nincrmidrange()\n    Returns an accumulator function which incrementally computes a mid-range.\n","incrmin":"\nincrmin()\n    Returns an accumulator function which incrementally computes a minimum\n    value.\n","incrminabs":"\nincrminabs()\n    Returns an accumulator function which incrementally computes a minimum\n    absolute value.\n","incrminmax":"\nincrminmax( [out:Array|TypedArray] )\n    Returns an accumulator function which incrementally computes a minimum and\n    maximum.\n","incrminmaxabs":"\nincrminmaxabs( [out:Array|TypedArray] )\n    Returns an accumulator function which incrementally computes a minimum and\n    maximum absolute value.\n","incrmmaape":"\nincrmmaape( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    mean arctangent absolute percentage error (MAAPE).\n","incrmmae":"\nincrmmae( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    mean absolute error (MAE).\n","incrmmape":"\nincrmmape( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    mean absolute percentage error (MAPE).\n","incrmmax":"\nincrmmax( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    maximum value.\n","incrmmaxabs":"\nincrmmaxabs( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    maximum absolute value.\n","incrmmda":"\nincrmmda( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    mean directional accuracy (MDA).\n","incrmme":"\nincrmme( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    mean error (ME).\n","incrmmean":"\nincrmmean( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    arithmetic mean.\n","incrmmeanabs":"\nincrmmeanabs( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    arithmetic mean of absolute values.\n","incrmmeanabs2":"\nincrmmeanabs2( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    arithmetic mean of squared absolute values.\n","incrmmeanstdev":"\nincrmmeanstdev( [out:Array|TypedArray,] W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    arithmetic mean and corrected sample standard deviation.\n","incrmmeanvar":"\nincrmmeanvar( [out:Array|TypedArray,] W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    arithmetic mean and unbiased sample variance.\n","incrmmidrange":"\nincrmmidrange( W:integer )\n    Returns an accumulator function which incrementally computes a moving mid-\n    range.\n","incrmmin":"\nincrmmin( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    minimum value.\n","incrmminabs":"\nincrmminabs( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    minimum absolute value.\n","incrmminmax":"\nincrmminmax( [out:Array|TypedArray,] W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    minimum and maximum.\n","incrmminmaxabs":"\nincrmminmaxabs( [out:Array|TypedArray,] W:integer )\n    Returns an accumulator function which incrementally computes moving minimum\n    and maximum absolute values.\n","incrmmpe":"\nincrmmpe( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    mean percentage error (MPE).\n","incrmmse":"\nincrmmse( W:integer )\n    Returns an accumulator function which incrementally computes a moving mean\n    squared error (MSE).\n","incrmpcorr":"\nincrmpcorr( W:integer[, mx:number, my:number] )\n    Returns an accumulator function which incrementally computes a moving\n    sample Pearson product-moment correlation coefficient.\n","incrmpcorr2":"\nincrmpcorr2( W:integer[, mx:number, my:number] )\n    Returns an accumulator function which incrementally computes a moving\n    squared sample Pearson product-moment correlation coefficient.\n","incrmpcorrdist":"\nincrmpcorrdist( W:integer[, mx:number, my:number] )\n    Returns an accumulator function which incrementally computes a moving\n    sample Pearson product-moment correlation distance.\n","incrmpe":"\nincrmpe()\n    Returns an accumulator function which incrementally computes the mean\n    percentage error (MPE).\n","incrmprod":"\nincrmprod( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    product.\n","incrmrange":"\nincrmrange( W:integer )\n    Returns an accumulator function which incrementally computes a moving range.\n","incrmrmse":"\nincrmrmse( W:integer )\n    Returns an accumulator function which incrementally computes a moving root\n    mean squared error (RMSE).\n","incrmrss":"\nincrmrss( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    residual sum of squares (RSS).\n","incrmse":"\nincrmse()\n    Returns an accumulator function which incrementally computes the mean\n    squared error (MSE).\n","incrmstdev":"\nincrmstdev( W:integer[, mean:number] )\n    Returns an accumulator function which incrementally computes a moving\n    corrected sample standard deviation.\n","incrmsum":"\nincrmsum( W:integer )\n    Returns an accumulator function which incrementally computes a moving sum.\n","incrmsumabs":"\nincrmsumabs( W:integer )\n    Returns an accumulator function which incrementally computes a moving sum of\n    absolute values.\n","incrmsumabs2":"\nincrmsumabs2( W:integer )\n    Returns an accumulator function which incrementally computes a moving sum of\n    squared absolute values.\n","incrmsummary":"\nincrmsummary( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    statistical summary.\n","incrmsumprod":"\nincrmsumprod( W:integer )\n    Returns an accumulator function which incrementally computes a moving sum of\n    products.\n","incrmvariance":"\nincrmvariance( W:integer[, mean:number] )\n    Returns an accumulator function which incrementally computes a moving\n    unbiased sample variance.\n","incrmvmr":"\nincrmvmr( W:integer[, mean:number] )\n    Returns an accumulator function which incrementally computes a moving\n    variance-to-mean (VMR).\n","incrnancount":"\nincrnancount()\n    Returns an accumulator function which incrementally updates a count,\n    ignoring `NaN` values.\n","incrnansum":"\nincrnansum()\n    Returns an accumulator function which incrementally computes a sum, ignoring\n    `NaN` values.\n","incrnansumabs":"\nincrnansumabs()\n    Returns an accumulator function which incrementally computes a sum of\n    absolute values, ignoring NaN values.\n","incrnansumabs2":"\nincrnansumabs2()\n    Returns an accumulator function which incrementally computes a sum of\n    squared absolute values, ignoring NaN values.\n","incrpcorr":"\nincrpcorr( [mx:number, my:number] )\n    Returns an accumulator function which incrementally computes a sample\n    Pearson product-moment correlation coefficient.\n","incrpcorr2":"\nincrpcorr2( [mx:number, my:number] )\n    Returns an accumulator function which incrementally computes the squared\n    sample Pearson product-moment correlation coefficient.\n","incrpcorrdist":"\nincrpcorrdist( [mx:number, my:number] )\n    Returns an accumulator function which incrementally computes a sample\n    Pearson product-moment correlation distance.\n","incrpcorrdistmat":"\nincrpcorrdistmat( out:integer|ndarray[, means:ndarray] )\n    Returns an accumulator function which incrementally computes a sample\n    Pearson product-moment correlation distance matrix.\n","incrpcorrmat":"\nincrpcorrmat( out:integer|ndarray[, means:ndarray] )\n    Returns an accumulator function which incrementally computes a sample\n    Pearson product-moment correlation matrix.\n","incrprod":"\nincrprod()\n    Returns an accumulator function which incrementally computes a product.\n","incrrange":"\nincrrange()\n    Returns an accumulator function which incrementally computes a range.\n","incrrmse":"\nincrrmse()\n    Returns an accumulator function which incrementally computes the root mean\n    squared error (RMSE).\n","incrrss":"\nincrrss()\n    Returns an accumulator function which incrementally computes the residual\n    sum of squares (RSS).\n","incrskewness":"\nincrskewness()\n    Returns an accumulator function which incrementally computes a corrected\n    sample skewness.\n","incrspace":"\nincrspace( start:number, stop:number[, increment:number] )\n    Generates a linearly spaced numeric array using a provided increment.\n","incrstdev":"\nincrstdev( [mean:number] )\n    Returns an accumulator function which incrementally computes a corrected\n    sample standard deviation.\n","incrsum":"\nincrsum()\n    Returns an accumulator function which incrementally computes a sum.\n","incrsumabs":"\nincrsumabs()\n    Returns an accumulator function which incrementally computes a sum of\n    absolute values.\n","incrsumabs2":"\nincrsumabs2()\n    Returns an accumulator function which incrementally computes a sum of\n    squared absolute values.\n","incrsummary":"\nincrsummary()\n    Returns an accumulator function which incrementally computes a statistical\n    summary.\n","incrsumprod":"\nincrsumprod()\n    Returns an accumulator function which incrementally computes a sum of\n    products.\n","incrvariance":"\nincrvariance( [mean:number] )\n    Returns an accumulator function which incrementally computes an unbiased\n    sample variance.\n","incrvmr":"\nincrvmr( [mean:number] )\n    Returns an accumulator function which incrementally computes a variance-to-\n    mean ratio (VMR).\n","incrwmean":"\nincrwmean()\n    Returns an accumulator function which incrementally computes a weighted\n    arithmetic mean.\n","ind2sub":"\nind2sub( shape:ArrayLike, idx:integer[, options:Object] )\n    Converts a linear index to an array of subscripts.\n","ind2sub.assign":"\nind2sub.assign( shape:ArrayLike, idx:integer[, options:Object], \n  out:Array|TypedArray|Object )\n    Converts a linear index to an array of subscripts and assigns results to a\n    provided output array.\n","indexOf":"\nindexOf( arr:ArrayLike, searchElement:any[, fromIndex:integer] )\n    Returns the first index at which a given element can be found.\n","inherit":"\ninherit( ctor:Object|Function, superCtor:Object|Function )\n    Prototypical inheritance by replacing the prototype of one constructor with\n    the prototype of another constructor.\n","inheritedEnumerableProperties":"\ninheritedEnumerableProperties( value:any[, level:integer] )\n    Returns an array of an object's inherited enumerable property names and\n    symbols.\n","inheritedEnumerablePropertySymbols":"\ninheritedEnumerablePropertySymbols( value:any[, level:integer] )\n    Returns an array of an object's inherited enumerable symbol properties.\n","inheritedKeys":"\ninheritedKeys( value:any[, level:integer] )\n    Returns an array of an object's inherited enumerable property names.\n","inheritedNonEnumerableProperties":"\ninheritedNonEnumerableProperties( value:any[, level:integer] )\n    Returns an array of an object's inherited non-enumerable property names and\n    symbols.\n","inheritedNonEnumerablePropertyNames":"\ninheritedNonEnumerablePropertyNames( value:any[, level:integer] )\n    Returns an array of an object's inherited non-enumerable property names.\n","inheritedNonEnumerablePropertySymbols":"\ninheritedNonEnumerablePropertySymbols( value:any[, level:integer] )\n    Returns an array of an object's inherited non-enumerable symbol properties.\n","inheritedProperties":"\ninheritedProperties( value:any[, level:integer] )\n    Returns an array of an object's inherited property names and symbols.\n","inheritedPropertyDescriptor":"\ninheritedPropertyDescriptor( value:any, property:string|symbol[, \n  level:integer] )\n    Returns a property descriptor for an object's inherited property.\n","inheritedPropertyDescriptors":"\ninheritedPropertyDescriptors( value:any[, level:integer] )\n    Returns an object's inherited property descriptors.\n","inheritedPropertyNames":"\ninheritedPropertyNames( value:any[, level:integer] )\n    Returns an array of an object's inherited enumerable and non-enumerable\n    property names.\n","inheritedPropertySymbols":"\ninheritedPropertySymbols( value:any[, level:integer] )\n    Returns an array of an object's inherited symbol properties.\n","inheritedWritableProperties":"\ninheritedWritableProperties( value:any[, level:integer] )\n    Returns an array of an object's inherited writable property names and\n    symbols.\n","inheritedWritablePropertyNames":"\ninheritedWritablePropertyNames( value:any[, level:integer] )\n    Returns an array of an object's inherited writable property names.\n","inheritedWritablePropertySymbols":"\ninheritedWritablePropertySymbols( value:any[, level:integer] )\n    Returns an array of an object's inherited writable symbol properties.\n","inmap":"\ninmap( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n    Invokes a function for each element in a collection and updates the\n    collection in-place.\n","inmapAsync":"\ninmapAsync( collection:Array|TypedArray|Object, [options:Object,] fcn:Function, \n  done:Function )\n    Invokes a function once for each element in a collection and updates a\n    collection in-place.\n","inmapAsync.factory":"\ninmapAsync.factory( [options:Object,] fcn:Function )\n    Returns a function which invokes a function once for each element in a\n    collection and updates a collection in-place.\n","inmapRight":"\ninmapRight( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n    Invokes a function for each element in a collection and updates the\n    collection in-place, iterating from right to left.\n","inmapRightAsync":"\ninmapRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n  fcn:Function, done:Function )\n    Invokes a function once for each element in a collection and updates a\n    collection in-place, iterating from right to left.\n","inmapRightAsync.factory":"\ninmapRightAsync.factory( [options:Object,] fcn:Function )\n    Returns a function which invokes a function once for each element in a\n    collection and updates a collection in-place, iterating from right to left.\n","inspectSinkStream":"\ninspectSinkStream( [options:Object,] clbk:Function )\n    Returns a writable stream for inspecting stream data.\n","inspectSinkStream.factory":"\ninspectSinkStream.factory( [options:Object] )\n    Returns a function for creating writable streams for inspecting stream data.\n","inspectSinkStream.objectMode":"\ninspectSinkStream.objectMode( [options:Object,] clbk:Function )\n    Returns an \"objectMode\" writable stream for inspecting stream data.\n","inspectStream":"\ninspectStream( [options:Object,] clbk:Function )\n    Returns a transform stream for inspecting stream data.\n","inspectStream.factory":"\ninspectStream.factory( [options:Object] )\n    Returns a function for creating transform streams for inspecting stream\n    data.\n","inspectStream.objectMode":"\ninspectStream.objectMode( [options:Object,] clbk:Function )\n    Returns an \"objectMode\" transform stream for inspecting stream data.\n","instanceOf":"\ninstanceOf( value:any, constructor:Function )\n    Tests whether a value has in its prototype chain a specified constructor as\n    a prototype property.\n","INT8_MAX":"\nINT8_MAX\n    Maximum signed 8-bit integer.\n","INT8_MIN":"\nINT8_MIN\n    Minimum signed 8-bit integer.\n","INT8_NUM_BYTES":"\nINT8_NUM_BYTES\n    Size (in bytes) of an 8-bit signed integer.\n","Int8Array":"\nInt8Array()\n    A typed array constructor which returns a typed array representing an array\n    of twos-complement 8-bit signed integers in the platform byte order.\n\nInt8Array( length:integer )\n    Returns a typed array having a specified length.\n\nInt8Array( typedarray:TypedArray )\n    Creates a typed array from another typed array.\n\nInt8Array( obj:Object )\n    Creates a typed array from an array-like object or iterable.\n\nInt8Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a typed array view of an ArrayBuffer.\n","Int8Array.from":"\nInt8Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n    Creates a new typed array from an array-like object or an iterable.\n","Int8Array.of":"\nInt8Array.of( element0:number[, element1:number[, ...elementN:number]] )\n    Creates a new typed array from a variable number of arguments.\n","Int8Array.BYTES_PER_ELEMENT":"\nInt8Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Int8Array.name":"\nInt8Array.name\n    Typed array constructor name.\n","Int8Array.prototype.buffer":"\nInt8Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n","Int8Array.prototype.byteLength":"\nInt8Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n","Int8Array.prototype.byteOffset":"\nInt8Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n","Int8Array.prototype.BYTES_PER_ELEMENT":"\nInt8Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Int8Array.prototype.length":"\nInt8Array.prototype.length\n    Read-only property which returns the number of view elements.\n","Int8Array.prototype.copyWithin":"\nInt8Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","Int8Array.prototype.entries":"\nInt8Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","Int8Array.prototype.every":"\nInt8Array.prototype.every( predicate:Function[, thisArg:Any] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n","Int8Array.prototype.fill":"\nInt8Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n","Int8Array.prototype.filter":"\nInt8Array.prototype.filter( predicate:Function[, thisArg:Any] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n","Int8Array.prototype.find":"\nInt8Array.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n","Int8Array.prototype.findIndex":"\nInt8Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n","Int8Array.prototype.forEach":"\nInt8Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n    Invokes a callback for each array element.\n","Int8Array.prototype.includes":"\nInt8Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a search element.\n","Int8Array.prototype.indexOf":"\nInt8Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n","Int8Array.prototype.join":"\nInt8Array.prototype.join( [separator:string] )\n    Serializes an array by joining all array elements as a string.\n","Int8Array.prototype.keys":"\nInt8Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n","Int8Array.prototype.lastIndexOf":"\nInt8Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n","Int8Array.prototype.map":"\nInt8Array.prototype.map( fcn:Function[, thisArg:Any] )\n    Maps each array element to an element in a new typed array.\n","Int8Array.prototype.reduce":"\nInt8Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n","Int8Array.prototype.reduceRight":"\nInt8Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n","Int8Array.prototype.reverse":"\nInt8Array.prototype.reverse()\n    Reverses an array *in-place*.\n","Int8Array.prototype.set":"\nInt8Array.prototype.set( arr:ArrayLike[, offset:integer] )\n    Sets array elements.\n","Int8Array.prototype.slice":"\nInt8Array.prototype.slice( [begin:integer[, end:integer]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n","Int8Array.prototype.some":"\nInt8Array.prototype.some( predicate:Function[, thisArg:Any] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n","Int8Array.prototype.sort":"\nInt8Array.prototype.sort( [compareFunction:Function] )\n    Sorts an array *in-place*.\n","Int8Array.prototype.subarray":"\nInt8Array.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n","Int8Array.prototype.toLocaleString":"\nInt8Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n    Serializes an array as a locale-specific string.\n","Int8Array.prototype.toString":"\nInt8Array.prototype.toString()\n    Serializes an array as a string.\n","Int8Array.prototype.values":"\nInt8Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n","INT16_MAX":"\nINT16_MAX\n    Maximum signed 16-bit integer.\n","INT16_MIN":"\nINT16_MIN\n    Minimum signed 16-bit integer.\n","INT16_NUM_BYTES":"\nINT16_NUM_BYTES\n    Size (in bytes) of a 16-bit signed integer.\n","Int16Array":"\nInt16Array()\n    A typed array constructor which returns a typed array representing an array\n    of twos-complement 16-bit signed integers in the platform byte order.\n\nInt16Array( length:integer )\n    Returns a typed array having a specified length.\n\nInt16Array( typedarray:TypedArray )\n    Creates a typed array from another typed array.\n\nInt16Array( obj:Object )\n    Creates a typed array from an array-like object or iterable.\n\nInt16Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a typed array view of an ArrayBuffer.\n","Int16Array.from":"\nInt16Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n    Creates a new typed array from an array-like object or an iterable.\n","Int16Array.of":"\nInt16Array.of( element0:number[, element1:number[, ...elementN:number]] )\n    Creates a new typed array from a variable number of arguments.\n","Int16Array.BYTES_PER_ELEMENT":"\nInt16Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Int16Array.name":"\nInt16Array.name\n    Typed array constructor name.\n","Int16Array.prototype.buffer":"\nInt16Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n","Int16Array.prototype.byteLength":"\nInt16Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n","Int16Array.prototype.byteOffset":"\nInt16Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n","Int16Array.prototype.BYTES_PER_ELEMENT":"\nInt16Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Int16Array.prototype.length":"\nInt16Array.prototype.length\n    Read-only property which returns the number of view elements.\n","Int16Array.prototype.copyWithin":"\nInt16Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","Int16Array.prototype.entries":"\nInt16Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","Int16Array.prototype.every":"\nInt16Array.prototype.every( predicate:Function[, thisArg:Any] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n","Int16Array.prototype.fill":"\nInt16Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n","Int16Array.prototype.filter":"\nInt16Array.prototype.filter( predicate:Function[, thisArg:Any] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n","Int16Array.prototype.find":"\nInt16Array.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n","Int16Array.prototype.findIndex":"\nInt16Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n","Int16Array.prototype.forEach":"\nInt16Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n    Invokes a callback for each array element.\n","Int16Array.prototype.includes":"\nInt16Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a search element.\n","Int16Array.prototype.indexOf":"\nInt16Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n","Int16Array.prototype.join":"\nInt16Array.prototype.join( [separator:string] )\n    Serializes an array by joining all array elements as a string.\n","Int16Array.prototype.keys":"\nInt16Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n","Int16Array.prototype.lastIndexOf":"\nInt16Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n","Int16Array.prototype.map":"\nInt16Array.prototype.map( fcn:Function[, thisArg:Any] )\n    Maps each array element to an element in a new typed array.\n","Int16Array.prototype.reduce":"\nInt16Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n","Int16Array.prototype.reduceRight":"\nInt16Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n","Int16Array.prototype.reverse":"\nInt16Array.prototype.reverse()\n    Reverses an array *in-place*.\n","Int16Array.prototype.set":"\nInt16Array.prototype.set( arr:ArrayLike[, offset:integer] )\n    Sets array elements.\n","Int16Array.prototype.slice":"\nInt16Array.prototype.slice( [begin:integer[, end:integer]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n","Int16Array.prototype.some":"\nInt16Array.prototype.some( predicate:Function[, thisArg:Any] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n","Int16Array.prototype.sort":"\nInt16Array.prototype.sort( [compareFunction:Function] )\n    Sorts an array *in-place*.\n","Int16Array.prototype.subarray":"\nInt16Array.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n","Int16Array.prototype.toLocaleString":"\nInt16Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n    Serializes an array as a locale-specific string.\n","Int16Array.prototype.toString":"\nInt16Array.prototype.toString()\n    Serializes an array as a string.\n","Int16Array.prototype.values":"\nInt16Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n","INT32_MAX":"\nINT32_MAX\n    Maximum signed 32-bit integer.\n","INT32_MIN":"\nINT32_MIN\n    Minimum signed 32-bit integer.\n","INT32_NUM_BYTES":"\nINT32_NUM_BYTES\n    Size (in bytes) of a 32-bit signed integer.\n","Int32Array":"\nInt32Array()\n    A typed array constructor which returns a typed array representing an array\n    of twos-complement 32-bit signed integers in the platform byte order.\n\nInt32Array( length:integer )\n    Returns a typed array having a specified length.\n\nInt32Array( typedarray:TypedArray )\n    Creates a typed array from another typed array.\n\nInt32Array( obj:Object )\n    Creates a typed array from an array-like object or iterable.\n\nInt32Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a typed array view of an ArrayBuffer.\n","Int32Array.from":"\nInt32Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n    Creates a new typed array from an array-like object or an iterable.\n","Int32Array.of":"\nInt32Array.of( element0:number[, element1:number[, ...elementN:number]] )\n    Creates a new typed array from a variable number of arguments.\n","Int32Array.BYTES_PER_ELEMENT":"\nInt32Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Int32Array.name":"\nInt32Array.name\n    Typed array constructor name.\n","Int32Array.prototype.buffer":"\nInt32Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n","Int32Array.prototype.byteLength":"\nInt32Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n","Int32Array.prototype.byteOffset":"\nInt32Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n","Int32Array.prototype.BYTES_PER_ELEMENT":"\nInt32Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Int32Array.prototype.length":"\nInt32Array.prototype.length\n    Read-only property which returns the number of view elements.\n","Int32Array.prototype.copyWithin":"\nInt32Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","Int32Array.prototype.entries":"\nInt32Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","Int32Array.prototype.every":"\nInt32Array.prototype.every( predicate:Function[, thisArg:Any] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n","Int32Array.prototype.fill":"\nInt32Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n","Int32Array.prototype.filter":"\nInt32Array.prototype.filter( predicate:Function[, thisArg:Any] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n","Int32Array.prototype.find":"\nInt32Array.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n","Int32Array.prototype.findIndex":"\nInt32Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n","Int32Array.prototype.forEach":"\nInt32Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n    Invokes a callback for each array element.\n","Int32Array.prototype.includes":"\nInt32Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a search element.\n","Int32Array.prototype.indexOf":"\nInt32Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n","Int32Array.prototype.join":"\nInt32Array.prototype.join( [separator:string] )\n    Serializes an array by joining all array elements as a string.\n","Int32Array.prototype.keys":"\nInt32Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n","Int32Array.prototype.lastIndexOf":"\nInt32Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n","Int32Array.prototype.map":"\nInt32Array.prototype.map( fcn:Function[, thisArg:Any] )\n    Maps each array element to an element in a new typed array.\n","Int32Array.prototype.reduce":"\nInt32Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n","Int32Array.prototype.reduceRight":"\nInt32Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n","Int32Array.prototype.reverse":"\nInt32Array.prototype.reverse()\n    Reverses an array *in-place*.\n","Int32Array.prototype.set":"\nInt32Array.prototype.set( arr:ArrayLike[, offset:integer] )\n    Sets array elements.\n","Int32Array.prototype.slice":"\nInt32Array.prototype.slice( [begin:integer[, end:integer]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n","Int32Array.prototype.some":"\nInt32Array.prototype.some( predicate:Function[, thisArg:Any] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n","Int32Array.prototype.sort":"\nInt32Array.prototype.sort( [compareFunction:Function] )\n    Sorts an array *in-place*.\n","Int32Array.prototype.subarray":"\nInt32Array.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n","Int32Array.prototype.toLocaleString":"\nInt32Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n    Serializes an array as a locale-specific string.\n","Int32Array.prototype.toString":"\nInt32Array.prototype.toString()\n    Serializes an array as a string.\n","Int32Array.prototype.values":"\nInt32Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n","IS_BIG_ENDIAN":"\nIS_BIG_ENDIAN\n    Boolean indicating if the environment is big endian.\n","IS_BROWSER":"\nIS_BROWSER\n    Boolean indicating if the runtime is a web browser.\n","IS_DARWIN":"\nIS_DARWIN\n    Boolean indicating if the current process is running on Darwin.\n","IS_DOCKER":"\nIS_DOCKER\n    Boolean indicating if the process is running in a Docker container.\n","IS_ELECTRON":"\nIS_ELECTRON\n    Boolean indicating if the runtime is Electron.\n","IS_ELECTRON_MAIN":"\nIS_ELECTRON_MAIN\n    Boolean indicating if the runtime is the main Electron process.\n","IS_ELECTRON_RENDERER":"\nIS_ELECTRON_RENDERER\n    Boolean indicating if the runtime is the Electron renderer process.\n","IS_LITTLE_ENDIAN":"\nIS_LITTLE_ENDIAN\n    Boolean indicating if the environment is little endian.\n","IS_MOBILE":"\nIS_MOBILE\n    Boolean indicating if the current environment is a mobile device.\n","IS_NODE":"\nIS_NODE\n    Boolean indicating if the runtime is Node.js.\n","IS_TOUCH_DEVICE":"\nIS_TOUCH_DEVICE\n    Boolean indicating if the current environment is a touch device.\n","IS_WEB_WORKER":"\nIS_WEB_WORKER\n    Boolean indicating if the runtime is a web worker.\n","IS_WINDOWS":"\nIS_WINDOWS\n    Boolean indicating if the current process is running on Windows.\n","isAbsoluteHttpURI":"\nisAbsoluteHttpURI( value:any )\n    Tests whether a value is an absolute HTTP(S) URI.\n","isAbsolutePath":"\nisAbsolutePath( value:any )\n    Tests if a value is an absolute path.\n","isAbsolutePath.posix":"\nisAbsolutePath.posix( value:any )\n    Tests if a value is a POSIX absolute path.\n","isAbsolutePath.win32":"\nisAbsolutePath.win32( value:any )\n    Tests if a value is a Windows absolute path.\n","isAbsoluteURI":"\nisAbsoluteURI( value:any )\n    Tests whether a value is an absolute URI.\n","isAccessorArray":"\nisAccessorArray( value:any )\n    Tests if a value is an array-like object supporting the accessor (get/set)\n    protocol.\n","isAccessorProperty":"\nisAccessorProperty( value:any, property:any )\n    Tests if an object's own property has an accessor descriptor.\n","isAccessorPropertyIn":"\nisAccessorPropertyIn( value:any, property:any )\n    Tests if an object's own or inherited property has an accessor descriptor.\n","isAlphagram":"\nisAlphagram( value:any )\n    Tests if a value is an alphagram (i.e., a sequence of characters arranged in\n    alphabetical order).\n","isAlphaNumeric":"\nisAlphaNumeric( str:string )\n    Tests whether a string contains only alphanumeric characters.\n","isAnagram":"\nisAnagram( str:string, value:any )\n    Tests if a value is an anagram.\n","isArguments":"\nisArguments( value:any )\n    Tests if a value is an arguments object.\n","isArray":"\nisArray( value:any )\n    Tests if a value is an array.\n","isArrayArray":"\nisArrayArray( value:any )\n    Tests if a value is an array of arrays.\n","isArrayBuffer":"\nisArrayBuffer( value:any )\n    Tests if a value is an ArrayBuffer.\n","isArrayBufferView":"\nisArrayBufferView( value:any )\n    Tests if a value is a `ArrayBuffer` view.\n","isArrayLength":"\nisArrayLength( value:any )\n    Tests if a value is a valid array length.\n","isArrayLike":"\nisArrayLike( value:any )\n    Tests if a value is array-like.\n","isArrayLikeObject":"\nisArrayLikeObject( value:any )\n    Tests if a value is an array-like object.\n","isArrowFunction":"\nisArrowFunction( value:any )\n    Tests if a value is an arrow function.\n","isASCII":"\nisASCII( str:string )\n    Tests whether a character belongs to the ASCII character set and whether\n    this is true for all characters in a provided string.\n","isBetween":"\nisBetween( value:any, a:any, b:any[, left:string, right:string] )\n    Tests if a value is between two values.\n","isBetweenArray":"\nisBetweenArray( value:any, a:any, b:any[, left:string, right:string] )\n    Tests if a value is an array-like object where every element is between two\n    values.\n","isBigInt":"\nisBigInt( value:any )\n    Tests if a value is a BigInt.\n","isBigInt64Array":"\nisBigInt64Array( value:any )\n    Tests if a value is a BigInt64Array.\n","isBigUint64Array":"\nisBigUint64Array( value:any )\n    Tests if a value is a BigUint64Array.\n","isBinaryString":"\nisBinaryString( value:any )\n    Tests if a value is a binary string.\n","isBlankString":"\nisBlankString( value:any )\n    Tests if a value is a blank string (i.e., an empty string or a string\n    consisting only of whitespace characters).\n","isBoolean":"\nisBoolean( value:any )\n    Tests if a value is a boolean.\n","isBoolean.isPrimitive":"\nisBoolean.isPrimitive( value:any )\n    Tests if a value is a boolean primitive.\n","isBoolean.isObject":"\nisBoolean.isObject( value:any )\n    Tests if a value is a boolean object.\n","isBooleanArray":"\nisBooleanArray( value:any )\n    Tests if a value is an array-like object of booleans.\n","isBooleanArray.primitives":"\nisBooleanArray.primitives( value:any )\n    Tests if a value is an array-like object containing only boolean primitives.\n","isBooleanArray.objects":"\nisBooleanArray.objects( value:any )\n    Tests if a value is an array-like object containing only Boolean objects.\n","isBoxedPrimitive":"\nisBoxedPrimitive( value:any )\n    Tests if a value is a JavaScript boxed primitive.\n","isBuffer":"\nisBuffer( value:any )\n    Tests if a value is a Buffer instance.\n","isCamelcase":"\nisCamelcase( value:any )\n    Tests if a value is a camelcase string.\n","isCapitalized":"\nisCapitalized( value:any )\n    Tests if a value is a string having an uppercase first character.\n","isCentrosymmetricMatrix":"\nisCentrosymmetricMatrix( value:any )\n    Tests if a value is a matrix which is symmetric about its center.\n","isCircular":"\nisCircular( value:any )\n    Tests if an object-like value contains a circular reference.\n","isCircularArray":"\nisCircularArray( value:any )\n    Tests if a value is an array containing a circular reference.\n","isCircularPlainObject":"\nisCircularPlainObject( value:any )\n    Tests if a value is a plain object containing a circular reference.\n","isClass":"\nisClass( value:any )\n    Tests if a value is a class.\n","isCollection":"\nisCollection( value:any )\n    Tests if a value is a collection.\n","isComplex":"\nisComplex( value:any )\n    Tests if a value is a 64-bit or 128-bit complex number.\n","isComplex64":"\nisComplex64( value:any )\n    Tests if a value is a 64-bit complex number.\n","isComplex64Array":"\nisComplex64Array( value:any )\n    Tests if a value is a Complex64Array.\n","isComplex64MatrixLike":"\nisComplex64MatrixLike( value:any )\n    Tests if a value is a 2-dimensional ndarray-like object containing single-\n    precision complex floating-point numbers.\n","isComplex64ndarrayLike":"\nisComplex64ndarrayLike( value:any )\n    Tests if a value is an ndarray-like object containing single-precision\n    complex floating-point numbers.\n","isComplex64VectorLike":"\nisComplex64VectorLike( value:any )\n    Tests if a value is a 1-dimensional ndarray-like object containing single-\n    precision complex floating-point numbers.\n","isComplex128":"\nisComplex128( value:any )\n    Tests if a value is a 128-bit complex number.\n","isComplex128Array":"\nisComplex128Array( value:any )\n    Tests if a value is a Complex128Array.\n","isComplex128MatrixLike":"\nisComplex128MatrixLike( value:any )\n    Tests if a value is a 2-dimensional ndarray-like object containing double-\n    precision complex floating-point numbers.\n","isComplex128ndarrayLike":"\nisComplex128ndarrayLike( value:any )\n    Tests if a value is an ndarray-like object containing double-precision\n    complex floating-point numbers.\n","isComplex128VectorLike":"\nisComplex128VectorLike( value:any )\n    Tests if a value is a 1-dimensional ndarray-like object containing double-\n    precision complex floating-point numbers.\n","isComplexLike":"\nisComplexLike( value:any )\n    Tests if a value is a complex number-like object.\n","isComplexTypedArray":"\nisComplexTypedArray( value:any )\n    Tests if a value is a complex typed array.\n","isComplexTypedArrayLike":"\nisComplexTypedArrayLike( value:any )\n    Tests if a value is complex-typed-array-like.\n","isComposite":"\nisComposite( value:any )\n    Tests if a value is a composite number.\n","isComposite.isPrimitive":"\nisComposite.isPrimitive( value:any )\n    Tests if a value is a number primitive which is a composite number.\n","isComposite.isObject":"\nisComposite.isObject( value:any )\n    Tests if a value is a number object having a value which is a composite\n    number.\n","isConfigurableProperty":"\nisConfigurableProperty( value:any, property:any )\n    Tests if an object's own property is configurable.\n","isConfigurablePropertyIn":"\nisConfigurablePropertyIn( value:any, property:any )\n    Tests if an object's own or inherited property is configurable.\n","isConstantcase":"\nisConstantcase( value:any )\n    Tests if a value is a constantcase string.\n","isCubeNumber":"\nisCubeNumber( value:any )\n    Tests if a value is a cube number.\n","isCubeNumber.isPrimitive":"\nisCubeNumber.isPrimitive( value:any )\n    Tests if a value is a number primitive which is a cube number.\n","isCubeNumber.isObject":"\nisCubeNumber.isObject( value:any )\n    Tests if a value is a number object having a value which is a cube number.\n","isCurrentYear":"\nisCurrentYear( value:any )\n    Tests if a value is the current year.\n","isDataProperty":"\nisDataProperty( value:any, property:any )\n    Tests if an object's own property has a data descriptor.\n","isDataPropertyIn":"\nisDataPropertyIn( value:any, property:any )\n    Tests if an object's own or inherited property has a data descriptor.\n","isDataView":"\nisDataView( value:any )\n    Tests if a value is a DataView.\n","isDateObject":"\nisDateObject( value:any )\n    Tests if a value is a Date object.\n","isDateObjectArray":"\nisDateObjectArray( value:any )\n    Tests if a value is an array-like object containing only Date objects.\n","isDigitString":"\nisDigitString( str:string )\n    Tests whether a string contains only numeric digits.\n","isDomainName":"\nisDomainName( value:any )\n    Tests if a value is a domain name.\n","isDurationString":"\nisDurationString( value:any )\n    Tests if a value is a duration string.\n","isEmailAddress":"\nisEmailAddress( value:any )\n    Tests if a value is an email address.\n","isEmptyArray":"\nisEmptyArray( value:any )\n    Tests if a value is an empty array.\n","isEmptyArrayLikeObject":"\nisEmptyArrayLikeObject( value:any )\n    Tests if a value is an empty array-like object.\n","isEmptyCollection":"\nisEmptyCollection( value:any )\n    Tests if a value is an empty collection.\n","isEmptyObject":"\nisEmptyObject( value:any )\n    Tests if a value is an empty object.\n","isEmptyString":"\nisEmptyString( value:any )\n    Tests if a value is an empty string.\n","isEmptyString.isPrimitive":"\nisEmptyString.isPrimitive( value:any )\n    Tests if a value is an empty string primitive.\n","isEmptyString.isObject":"\nisEmptyString.isObject( value:any )\n    Tests if a value is an empty `String` object.\n","isEnumerableProperty":"\nisEnumerableProperty( value:any, property:any )\n    Tests if an object's own property is enumerable.\n","isEnumerablePropertyIn":"\nisEnumerablePropertyIn( value:any, property:any )\n    Tests if an object's own or inherited property is enumerable.\n","isEqualArray":"\nisEqualArray( v1:any, v2:any )\n    Tests if two arguments are both generic arrays and have equal values.\n","isError":"\nisError( value:any )\n    Tests if a value is an Error object.\n","isEvalError":"\nisEvalError( value:any )\n    Tests if a value is an EvalError object.\n","isEven":"\nisEven( value:any )\n    Tests if a value is an even number.\n","isEven.isPrimitive":"\nisEven.isPrimitive( value:any )\n    Tests if a value is a number primitive that is an even number.\n","isEven.isObject":"\nisEven.isObject( value:any )\n    Tests if a value is a number object that is an even number.\n","isFalsy":"\nisFalsy( value:any )\n    Tests if a value is a value which translates to `false` when evaluated in a\n    boolean context.\n","isFalsyArray":"\nisFalsyArray( value:any )\n    Tests if a value is an array-like object containing only falsy values.\n","isFinite":"\nisFinite( value:any )\n    Tests if a value is a finite number.\n","isFinite.isPrimitive":"\nisFinite.isPrimitive( value:any )\n    Tests if a value is a number primitive having a finite value.\n","isFinite.isObject":"\nisFinite.isObject( value:any )\n    Tests if a value is a number object having a finite value.\n","isFiniteArray":"\nisFiniteArray( value:any )\n    Tests if a value is an array-like object of finite numbers.\n","isFiniteArray.primitives":"\nisFiniteArray.primitives( value:any )\n    Tests if a value is an array-like object containing only primitive finite\n    numbers.\n","isFiniteArray.objects":"\nisFiniteArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having finite values.\n","isFloat32Array":"\nisFloat32Array( value:any )\n    Tests if a value is a Float32Array.\n","isFloat32MatrixLike":"\nisFloat32MatrixLike( value:any )\n    Tests if a value is a 2-dimensional ndarray-like object containing single-\n    precision floating-point numbers.\n","isFloat32ndarrayLike":"\nisFloat32ndarrayLike( value:any )\n    Tests if a value is an ndarray-like object containing single-precision\n    floating-point numbers.\n","isFloat32VectorLike":"\nisFloat32VectorLike( value:any )\n    Tests if a value is a 1-dimensional ndarray-like object containing single-\n    precision floating-point numbers.\n","isFloat64Array":"\nisFloat64Array( value:any )\n    Tests if a value is a Float64Array.\n","isFloat64MatrixLike":"\nisFloat64MatrixLike( value:any )\n    Tests if a value is a 2-dimensional ndarray-like object containing double-\n    precision floating-point numbers.\n","isFloat64ndarrayLike":"\nisFloat64ndarrayLike( value:any )\n    Tests if a value is an ndarray-like object containing double-precision\n    floating-point numbers.\n","isFloat64VectorLike":"\nisFloat64VectorLike( value:any )\n    Tests if a value is a 1-dimensional ndarray-like object containing double-\n    precision floating-point numbers.\n","isFunction":"\nisFunction( value:any )\n    Tests if a value is a function.\n","isFunctionArray":"\nisFunctionArray( value:any )\n    Tests if a value is an array-like object containing only functions.\n","isGeneratorObject":"\nisGeneratorObject( value:any )\n    Tests if a value is a generator object.\n","isGeneratorObjectLike":"\nisGeneratorObjectLike( value:any )\n    Tests if a value is generator object-like.\n","isgzipBuffer":"\nisgzipBuffer( value:any )\n    Tests if a value is a gzip buffer.\n","isHexString":"\nisHexString( str:string )\n    Tests whether a string contains only hexadecimal digits.\n","isInfinite":"\nisInfinite( value:any )\n    Tests if a value is an infinite number.\n","isInfinite.isPrimitive":"\nisInfinite.isPrimitive( value:any )\n    Tests if a value is a number primitive having an infinite value.\n","isInfinite.isObject":"\nisInfinite.isObject( value:any )\n    Tests if a value is a number object having an infinite value.\n","isInheritedProperty":"\nisInheritedProperty( value:any, property:any )\n    Tests if an object has an inherited property.\n","isInt8Array":"\nisInt8Array( value:any )\n    Tests if a value is an Int8Array.\n","isInt16Array":"\nisInt16Array( value:any )\n    Tests if a value is an Int16Array.\n","isInt32Array":"\nisInt32Array( value:any )\n    Tests if a value is an Int32Array.\n","isInteger":"\nisInteger( value:any )\n    Tests if a value is an integer.\n","isInteger.isPrimitive":"\nisInteger.isPrimitive( value:any )\n    Tests if a value is a number primitive having an integer value.\n","isInteger.isObject":"\nisInteger.isObject( value:any )\n    Tests if a value is a number object having an integer value.\n","isIntegerArray":"\nisIntegerArray( value:any )\n    Tests if a value is an array-like object of integer values.\n","isIntegerArray.primitives":"\nisIntegerArray.primitives( value:any )\n    Tests if a value is an array-like object containing only primitive integer\n    values.\n","isIntegerArray.objects":"\nisIntegerArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having integer values.\n","isIterableLike":"\nisIterableLike( value:any )\n    Tests if a value is iterable-like.\n","isIteratorLike":"\nisIteratorLike( value:any )\n    Tests if a value is iterator-like.\n","isJSON":"\nisJSON( value:any )\n    Tests if a value is a parseable JSON string.\n","isKebabcase":"\nisKebabcase( value:any )\n    Tests if a value is a string in kebab case.\n","isLeapYear":"\nisLeapYear( value:any )\n    Tests whether a value corresponds to a leap year in the Gregorian calendar.\n","isLocalhost":"\nisLocalhost( value:any )\n    Tests whether a value is a localhost hostname.\n","isLowercase":"\nisLowercase( value:any )\n    Tests if a value is a lowercase string.\n","isMatrixLike":"\nisMatrixLike( value:any )\n    Tests if a value is a 2-dimensional ndarray-like object.\n","isMethod":"\nisMethod( value:any, property:any )\n    Tests if an object has a specified method name.\n","isMethodIn":"\nisMethodIn( value:any, property:any )\n    Tests if an object has a specified method name, either own or inherited.\n","isMultiSlice":"\nisMultiSlice( value:any )\n    Tests if a value is a MultiSlice object.\n","isNamedTypedTupleLike":"\nisNamedTypedTupleLike( value:any )\n    Tests if a value is named typed tuple-like.\n","isnan":"\nisnan( value:any )\n    Tests if a value is NaN.\n","isnan.isPrimitive":"\nisnan.isPrimitive( value:any )\n    Tests if a value is a NaN number primitive.\n","isnan.isObject":"\nisnan.isObject( value:any )\n    Tests if a value is a number object having a value of NaN.\n","isNaNArray":"\nisNaNArray( value:any )\n    Tests if a value is an array-like object containing only NaN values.\n","isNaNArray.primitives":"\nisNaNArray.primitives( value:any )\n    Tests if a value is an array-like object containing only primitive NaN\n    values.\n","isNaNArray.objects":"\nisNaNArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having NaN values.\n","isNativeFunction":"\nisNativeFunction( value:any )\n    Tests if a value is a native function.\n","isndarrayLike":"\nisndarrayLike( value:any )\n    Tests if a value is ndarray-like.\n","isndarrayLikeWithDataType":"\nisndarrayLikeWithDataType( value:any, dtype:any )\n    Tests if a value is an ndarray-like object having a specified data type.\n","isNegativeFinite":"\nisNegativeFinite( value:any )\n    Tests if a value is a finite negative number.\n","isNegativeFinite.isPrimitive":"\nisNegativeFinite.isPrimitive( value:any )\n    Tests if a value is a number primitive having a finite negative value.\n","isNegativeFinite.isObject":"\nisNegativeFinite.isObject( value:any )\n    Tests if a value is a number object having a finite negative value.\n","isNegativeInteger":"\nisNegativeInteger( value:any )\n    Tests if a value is a negative integer.\n","isNegativeInteger.isPrimitive":"\nisNegativeInteger.isPrimitive( value:any )\n    Tests if a value is a number primitive having a negative integer value.\n","isNegativeInteger.isObject":"\nisNegativeInteger.isObject( value:any )\n    Tests if a value is a number object having a negative integer value.\n","isNegativeIntegerArray":"\nisNegativeIntegerArray( value:any )\n    Tests if a value is an array-like object containing only negative integers.\n","isNegativeIntegerArray.primitives":"\nisNegativeIntegerArray.primitives( value:any )\n    Tests if a value is an array-like object containing only negative primitive\n    integer values.\n","isNegativeIntegerArray.objects":"\nisNegativeIntegerArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having negative integer values.\n","isNegativeNumber":"\nisNegativeNumber( value:any )\n    Tests if a value is a negative number.\n","isNegativeNumber.isPrimitive":"\nisNegativeNumber.isPrimitive( value:any )\n    Tests if a value is a number primitive having a negative value.\n","isNegativeNumber.isObject":"\nisNegativeNumber.isObject( value:any )\n    Tests if a value is a number object having a negative value.\n","isNegativeNumberArray":"\nisNegativeNumberArray( value:any )\n    Tests if a value is an array-like object containing only negative numbers.\n","isNegativeNumberArray.primitives":"\nisNegativeNumberArray.primitives( value:any )\n    Tests if a value is an array-like object containing only primitive negative\n    numbers.\n","isNegativeNumberArray.objects":"\nisNegativeNumberArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having negative number values.\n","isNegativeZero":"\nisNegativeZero( value:any )\n    Tests if a value is negative zero.\n","isNegativeZero.isPrimitive":"\nisNegativeZero.isPrimitive( value:any )\n    Tests if a value is a number primitive equal to negative zero.\n","isNegativeZero.isObject":"\nisNegativeZero.isObject( value:any )\n    Tests if a value is a number object having a value equal to negative zero.\n","isNodeBuiltin":"\nisNodeBuiltin( str:string )\n    Tests whether a string matches a Node.js built-in module name.\n","isNodeDuplexStreamLike":"\nisNodeDuplexStreamLike( value:any )\n    Tests if a value is Node duplex stream-like.\n","isNodeReadableStreamLike":"\nisNodeReadableStreamLike( value:any )\n    Tests if a value is Node readable stream-like.\n","isNodeREPL":"\nisNodeREPL()\n    Returns a boolean indicating if running in a Node.js REPL environment.\n","isNodeStreamLike":"\nisNodeStreamLike( value:any )\n    Tests if a value is Node stream-like.\n","isNodeTransformStreamLike":"\nisNodeTransformStreamLike( value:any )\n    Tests if a value is Node transform stream-like.\n","isNodeWritableStreamLike":"\nisNodeWritableStreamLike( value:any )\n    Tests if a value is Node writable stream-like.\n","isNonConfigurableProperty":"\nisNonConfigurableProperty( value:any, property:any )\n    Tests if an object's own property is non-configurable.\n","isNonConfigurablePropertyIn":"\nisNonConfigurablePropertyIn( value:any, property:any )\n    Tests if an object's own or inherited property is non-configurable.\n","isNonEnumerableProperty":"\nisNonEnumerableProperty( value:any, property:any )\n    Tests if an object's own property is non-enumerable.\n","isNonEnumerablePropertyIn":"\nisNonEnumerablePropertyIn( value:any, property:any )\n    Tests if an object's own or inherited property is non-enumerable.\n","isNonNegativeFinite":"\nisNonNegativeFinite( value:any )\n    Tests if a value is a nonnegative finite number.\n","isNonNegativeFinite.isPrimitive":"\nisNonNegativeFinite.isPrimitive( value:any )\n    Tests if a value is a number primitive having a nonnegative finite value.\n","isNonNegativeFinite.isObject":"\nisNonNegativeFinite.isObject( value:any )\n    Tests if a value is a number object having a nonnegative finite value.\n","isNonNegativeInteger":"\nisNonNegativeInteger( value:any )\n    Tests if a value is a nonnegative integer.\n","isNonNegativeInteger.isPrimitive":"\nisNonNegativeInteger.isPrimitive( value:any )\n    Tests if a value is a number primitive having a nonnegative integer value.\n","isNonNegativeInteger.isObject":"\nisNonNegativeInteger.isObject( value:any )\n    Tests if a value is a number object having a nonnegative integer value.\n","isNonNegativeIntegerArray":"\nisNonNegativeIntegerArray( value:any )\n    Tests if a value is an array-like object containing only nonnegative\n    integers.\n","isNonNegativeIntegerArray.primitives":"\nisNonNegativeIntegerArray.primitives( value:any )\n    Tests if a value is an array-like object containing only nonnegative\n    primitive integer values.\n","isNonNegativeIntegerArray.objects":"\nisNonNegativeIntegerArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having nonnegative integer values.\n","isNonNegativeNumber":"\nisNonNegativeNumber( value:any )\n    Tests if a value is a nonnegative number.\n","isNonNegativeNumber.isPrimitive":"\nisNonNegativeNumber.isPrimitive( value:any )\n    Tests if a value is a number primitive having a nonnegative value.\n","isNonNegativeNumber.isObject":"\nisNonNegativeNumber.isObject( value:any )\n    Tests if a value is a number object having a nonnegative value.\n","isNonNegativeNumberArray":"\nisNonNegativeNumberArray( value:any )\n    Tests if a value is an array-like object containing only nonnegative\n    numbers.\n","isNonNegativeNumberArray.primitives":"\nisNonNegativeNumberArray.primitives( value:any )\n    Tests if a value is an array-like object containing only primitive\n    nonnegative numbers.\n","isNonNegativeNumberArray.objects":"\nisNonNegativeNumberArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having nonnegative number values.\n","isNonPositiveFinite":"\nisNonPositiveFinite( value:any )\n    Tests if a value is a nonpositive finite number.\n","isNonPositiveFinite.isPrimitive":"\nisNonPositiveFinite.isPrimitive( value:any )\n    Tests if a value is a number primitive having a nonpositive finite value.\n","isNonPositiveFinite.isObject":"\nisNonPositiveFinite.isObject( value:any )\n    Tests if a value is a number object having a nonpositive finite value.\n","isNonPositiveInteger":"\nisNonPositiveInteger( value:any )\n    Tests if a value is a nonpositive integer.\n","isNonPositiveInteger.isPrimitive":"\nisNonPositiveInteger.isPrimitive( value:any )\n    Tests if a value is a number primitive having a nonpositive integer value.\n","isNonPositiveInteger.isObject":"\nisNonPositiveInteger.isObject( value:any )\n    Tests if a value is a number object having a nonpositive integer value.\n","isNonPositiveIntegerArray":"\nisNonPositiveIntegerArray( value:any )\n    Tests if a value is an array-like object containing only nonpositive\n    integers.\n","isNonPositiveIntegerArray.primitives":"\nisNonPositiveIntegerArray.primitives( value:any )\n    Tests if a value is an array-like object containing only nonpositive\n    primitive integer values.\n","isNonPositiveIntegerArray.objects":"\nisNonPositiveIntegerArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having nonpositive integer values.\n","isNonPositiveNumber":"\nisNonPositiveNumber( value:any )\n    Tests if a value is a nonpositive number.\n","isNonPositiveNumber.isPrimitive":"\nisNonPositiveNumber.isPrimitive( value:any )\n    Tests if a value is a number primitive having a nonpositive value.\n","isNonPositiveNumber.isObject":"\nisNonPositiveNumber.isObject( value:any )\n    Tests if a value is a number object having a nonpositive value.\n","isNonPositiveNumberArray":"\nisNonPositiveNumberArray( value:any )\n    Tests if a value is an array-like object containing only nonpositive\n    numbers.\n","isNonPositiveNumberArray.primitives":"\nisNonPositiveNumberArray.primitives( value:any )\n    Tests if a value is an array-like object containing only primitive\n    nonpositive numbers.\n","isNonPositiveNumberArray.objects":"\nisNonPositiveNumberArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having nonpositive number values.\n","isNonSymmetricMatrix":"\nisNonSymmetricMatrix( value:any )\n    Tests if a value is a non-symmetric matrix.\n","isNull":"\nisNull( value:any )\n    Tests if a value is null.\n","isNullArray":"\nisNullArray( value:any )\n    Tests if a value is an array-like object containing only null values.\n","isNumber":"\nisNumber( value:any )\n    Tests if a value is a number.\n","isNumber.isPrimitive":"\nisNumber.isPrimitive( value:any )\n    Tests if a value is a number primitive.\n","isNumber.isObject":"\nisNumber.isObject( value:any )\n    Tests if a value is a `Number` object.\n","isNumberArray":"\nisNumberArray( value:any )\n    Tests if a value is an array-like object containing only numbers.\n","isNumberArray.primitives":"\nisNumberArray.primitives( value:any )\n    Tests if a value is an array-like object containing only number primitives.\n","isNumberArray.objects":"\nisNumberArray.objects( value:any )\n    Tests if a value is an array-like object containing only `Number` objects.\n","isNumericArray":"\nisNumericArray( value:any )\n    Tests if a value is a numeric array.\n","isObject":"\nisObject( value:any )\n    Tests if a value is an object; e.g., `{}`.\n","isObjectArray":"\nisObjectArray( value:any )\n    Tests if a value is an array-like object containing only objects.\n","isObjectLike":"\nisObjectLike( value:any )\n    Tests if a value is object-like.\n","isOdd":"\nisOdd( value:any )\n    Tests if a value is an odd number.\n","isOdd.isPrimitive":"\nisOdd.isPrimitive( value:any )\n    Tests if a value is a number primitive that is an odd number.\n","isOdd.isObject":"\nisOdd.isObject( value:any )\n    Tests if a value is a number object that has an odd number value.\n","isoWeeksInYear":"\nisoWeeksInYear( [year:integer] )\n    Returns the number of ISO weeks in a year according to the Gregorian\n    calendar.\n","isPascalcase":"\nisPascalcase( value:any )\n    Tests if a value is a string in Pascal case.\n","isPersymmetricMatrix":"\nisPersymmetricMatrix( value:any )\n    Tests if a value is a square matrix which is symmetric about its\n    antidiagonal.\n","isPlainObject":"\nisPlainObject( value:any )\n    Tests if a value is a plain object.\n","isPlainObjectArray":"\nisPlainObjectArray( value:any )\n    Tests if a value is an array-like object containing only plain objects.\n","isPositiveFinite":"\nisPositiveFinite( value:any )\n    Tests if a value is a positive finite number.\n","isPositiveFinite.isPrimitive":"\nisPositiveFinite.isPrimitive( value:any )\n    Tests if a value is a number primitive having a positive finite value.\n","isPositiveFinite.isObject":"\nisPositiveFinite.isObject( value:any )\n    Tests if a value is a number object having a positive finite value.\n","isPositiveInteger":"\nisPositiveInteger( value:any )\n    Tests if a value is a positive integer.\n","isPositiveInteger.isPrimitive":"\nisPositiveInteger.isPrimitive( value:any )\n    Tests if a value is a number primitive having a positive integer value.\n","isPositiveInteger.isObject":"\nisPositiveInteger.isObject( value:any )\n    Tests if a value is a number object having a positive integer value.\n","isPositiveIntegerArray":"\nisPositiveIntegerArray( value:any )\n    Tests if a value is an array-like object containing only positive integers.\n","isPositiveIntegerArray.primitives":"\nisPositiveIntegerArray.primitives( value:any )\n    Tests if a value is an array-like object containing only positive primitive\n    integer values.\n","isPositiveIntegerArray.objects":"\nisPositiveIntegerArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having positive integer values.\n","isPositiveNumber":"\nisPositiveNumber( value:any )\n    Tests if a value is a positive number.\n","isPositiveNumber.isPrimitive":"\nisPositiveNumber.isPrimitive( value:any )\n    Tests if a value is a number primitive having a positive value.\n","isPositiveNumber.isObject":"\nisPositiveNumber.isObject( value:any )\n    Tests if a value is a number object having a positive value.\n","isPositiveNumberArray":"\nisPositiveNumberArray( value:any )\n    Tests if a value is an array-like object containing only positive numbers.\n","isPositiveNumberArray.primitives":"\nisPositiveNumberArray.primitives( value:any )\n    Tests if a value is an array-like object containing only positive primitive\n    number values.\n","isPositiveNumberArray.objects":"\nisPositiveNumberArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having positive values.\n","isPositiveZero":"\nisPositiveZero( value:any )\n    Tests if a value is positive zero.\n","isPositiveZero.isPrimitive":"\nisPositiveZero.isPrimitive( value:any )\n    Tests if a value is a number primitive equal to positive zero.\n","isPositiveZero.isObject":"\nisPositiveZero.isObject( value:any )\n    Tests if a value is a number object having a value equal to positive zero.\n","isPrime":"\nisPrime( value:any )\n    Tests if a value is a prime number.\n","isPrime.isPrimitive":"\nisPrime.isPrimitive( value:any )\n    Tests if a value is a number primitive which is a prime number.\n","isPrime.isObject":"\nisPrime.isObject( value:any )\n    Tests if a value is a number object having a value which is a prime number.\n","isPrimitive":"\nisPrimitive( value:any )\n    Tests if a value is a JavaScript primitive.\n","isPrimitiveArray":"\nisPrimitiveArray( value:any )\n    Tests if a value is an array-like object containing only JavaScript\n    primitives.\n","isPRNGLike":"\nisPRNGLike( value:any )\n    Tests if a value is PRNG-like.\n","isProbability":"\nisProbability( value:any )\n    Tests if a value is a probability.\n","isProbability.isPrimitive":"\nisProbability.isPrimitive( value:any )\n    Tests if a value is a number primitive which is a probability.\n","isProbability.isObject":"\nisProbability.isObject( value:any )\n    Tests if a value is a number object having a value which is a probability.\n","isProbabilityArray":"\nisProbabilityArray( value:any )\n    Tests if a value is an array-like object containing only probabilities.\n","isProbabilityArray.primitives":"\nisProbabilityArray.primitives( value:any )\n    Tests if a value is an array-like object containing only primitive\n    probabilities.\n","isProbabilityArray.objects":"\nisProbabilityArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having probability values.\n","isPropertyKey":"\nisPropertyKey( value:any )\n    Tests whether a value is a property key.\n","isPrototypeOf":"\nisPrototypeOf( value:any, proto:Object|Function )\n    Tests if an object's prototype chain contains a provided prototype.\n","isRaggedNestedArray":"\nisRaggedNestedArray( value:any )\n    Tests if a value is a ragged nested array. \n","isRangeError":"\nisRangeError( value:any )\n    Tests if a value is a RangeError object.\n","isReadableProperty":"\nisReadableProperty( value:any, property:any )\n    Tests if an object's own property is readable.\n","isReadablePropertyIn":"\nisReadablePropertyIn( value:any, property:any )\n    Tests if an object's own or inherited property is readable.\n","isReadOnlyProperty":"\nisReadOnlyProperty( value:any, property:any )\n    Tests if an object's own property is read-only.\n","isReadOnlyPropertyIn":"\nisReadOnlyPropertyIn( value:any, property:any )\n    Tests if an object's own or inherited property is read-only.\n","isReadWriteProperty":"\nisReadWriteProperty( value:any, property:any )\n    Tests if an object's own property is readable and writable.\n","isReadWritePropertyIn":"\nisReadWritePropertyIn( value:any, property:any )\n    Tests if an object's own or inherited property is readable and writable.\n","isReferenceError":"\nisReferenceError( value:any )\n    Tests if a value is a ReferenceError object.\n","isRegExp":"\nisRegExp( value:any )\n    Tests if a value is a regular expression.\n","isRegExpString":"\nisRegExpString( value:any )\n    Tests if a value is a regular expression string.\n","isRelativePath":"\nisRelativePath( value:any )\n    Tests if a value is a relative path.\n","isRelativePath.posix":"\nisRelativePath.posix( value:any )\n    Tests if a value is a POSIX relative path.\n","isRelativePath.win32":"\nisRelativePath.win32( value:any )\n    Tests if a value is a Windows relative path.\n","isRelativeURI":"\nisRelativeURI( value:any )\n    Tests whether a value is a relative URI.\n","isSafeInteger":"\nisSafeInteger( value:any )\n    Tests if a value is a safe integer.\n","isSafeInteger.isPrimitive":"\nisSafeInteger.isPrimitive( value:any )\n    Tests if a value is a number primitive having a safe integer value.\n","isSafeInteger.isObject":"\nisSafeInteger.isObject( value:any )\n    Tests if a value is a `Number` object having a safe integer value.\n","isSafeIntegerArray":"\nisSafeIntegerArray( value:any )\n    Tests if a value is an array-like object containing only safe integers.\n","isSafeIntegerArray.primitives":"\nisSafeIntegerArray.primitives( value:any )\n    Tests if a value is an array-like object containing only primitive safe\n    integer values.\n","isSafeIntegerArray.objects":"\nisSafeIntegerArray.objects( value:any )\n    Tests if a value is an array-like object containing only `Number` objects\n    having safe integer values.\n","isSameArray":"\nisSameArray( v1:any, v2:any )\n    Tests if two arguments are both generic arrays and have the same values.\n","isSameArrayLike":"\nisSameArrayLike( v1:any, v2:any )\n    Tests if two arguments are both array-like and have the same values.\n","isSameComplex64":"\nisSameComplex64( v1:any, v2:any )\n    Tests if two arguments are both single-precision complex floating-point\n    numbers and have the same value.\n","isSameComplex64Array":"\nisSameComplex64Array( v1:any, v2:any )\n    Tests if two arguments are both Complex64Arrays and have the same values.\n","isSameComplex128":"\nisSameComplex128( v1:any, v2:any )\n    Tests if two arguments are both double-precision complex floating-point\n    numbers and have the same value.\n","isSameComplex128Array":"\nisSameComplex128Array( v1:any, v2:any )\n    Tests if two arguments are both Complex128Arrays and have the same values.\n","isSameDateObject":"\nisSameDateObject( d1, d2 )\n    Tests if two values are both Date objects corresponding \n    to the same date and time.\n","isSameFloat32Array":"\nisSameFloat32Array( v1:any, v2:any )\n    Tests if two arguments are both Float32Arrays and have the same values.\n","isSameFloat64Array":"\nisSameFloat64Array( v1:any, v2:any )\n    Tests if two arguments are both Float64Arrays and have the same values.\n","isSameNativeClass":"\nisSameNativeClass( a:any, b:any )\n    Tests if two arguments have the same native class.\n","isSameType":"\nisSameType( a:any, b:any )\n    Tests if two arguments have the same type.\n","isSameValue":"\nisSameValue( a:any, b:any )\n    Tests if two arguments are the same value.\n","isSameValueZero":"\nisSameValueZero( a:any, b:any )\n    Tests if two arguments are the same value.\n","isSemVer":"\nisSemVer( value:any )\n    Tests if a value is a semantic version string.\n","isSharedArrayBuffer":"\nisSharedArrayBuffer( value:any )\n    Tests if a value is a SharedArrayBuffer.\n","isSkewCentrosymmetricMatrix":"\nisSkewCentrosymmetricMatrix( value:any )\n    Tests if a value is a skew-centrosymmetric matrix.\n","isSkewPersymmetricMatrix":"\nisSkewPersymmetricMatrix( value:any )\n    Tests if a value is a skew-persymmetric matrix.\n","isSkewSymmetricMatrix":"\nisSkewSymmetricMatrix( value:any )\n    Tests if a value is a skew-symmetric (or antisymmetric) matrix.\n","isSlice":"\nisSlice( value:any )\n    Tests if a value is a Slice object.\n","isSnakecase":"\nisSnakecase( value:any )\n    Tests if a value is a string in snake case.\n","isSquareMatrix":"\nisSquareMatrix( value:any )\n    Tests if a value is a 2-dimensional ndarray-like object having equal\n    dimensions.\n","isSquareNumber":"\nisSquareNumber( value:any )\n    Tests if a value is a square number.\n","isSquareNumber.isPrimitive":"\nisSquareNumber.isPrimitive( value:any )\n    Tests if a value is a number primitive which is a square number.\n","isSquareNumber.isObject":"\nisSquareNumber.isObject( value:any )\n    Tests if a value is a number object having a value which is a square number.\n","isSquareTriangularNumber":"\nisSquareTriangularNumber( value:any )\n    Tests if a value is a square triangular number.\n","isSquareTriangularNumber.isPrimitive":"\nisSquareTriangularNumber.isPrimitive( value:any )\n    Tests if a value is a number primitive which is a square triangular number.\n","isSquareTriangularNumber.isObject":"\nisSquareTriangularNumber.isObject( value:any )\n    Tests if a value is a number object having a value which is a square\n    triangular number.\n","isStartcase":"\nisStartcase( value:any )\n    Tests if a value is a startcase string.\n","isStrictEqual":"\nisStrictEqual( a:any, b:any )\n    Tests if two arguments are strictly equal.\n","isString":"\nisString( value:any )\n    Tests if a value is a string.\n","isString.isPrimitive":"\nisString.isPrimitive( value:any )\n    Tests if a value is a string primitive.\n","isString.isObject":"\nisString.isObject( value:any )\n    Tests if a value is a `String` object.\n","isStringArray":"\nisStringArray( value:any )\n    Tests if a value is an array of strings.\n","isStringArray.primitives":"\nisStringArray.primitives( value:any )\n    Tests if a value is an array containing only string primitives.\n","isStringArray.objects":"\nisStringArray.objects( value:any )\n    Tests if a value is an array containing only `String` objects.\n","isSymbol":"\nisSymbol( value:any )\n    Tests if a value is a symbol.\n","isSymbolArray":"\nisSymbolArray( value:any )\n    Tests if a value is an array-like object containing only symbols.\n","isSymbolArray.primitives":"\nisSymbolArray.primitives( value:any )\n    Tests if a value is an array-like object containing only `symbol`\n    primitives.\n","isSymbolArray.objects":"\nisSymbolArray.objects( value:any )\n    Tests if a value is an array-like object containing only `Symbol`\n    objects.\n","isSymmetricMatrix":"\nisSymmetricMatrix( value:any )\n    Tests if a value is a square matrix which equals its transpose.\n","isSyntaxError":"\nisSyntaxError( value:any )\n    Tests if a value is a SyntaxError object.\n","isTriangularNumber":"\nisTriangularNumber( value:any )\n    Tests if a value is a triangular number.\n","isTriangularNumber.isPrimitive":"\nisTriangularNumber.isPrimitive( value:any )\n    Tests if a value is a number primitive which is a triangular number.\n","isTriangularNumber.isObject":"\nisTriangularNumber.isObject( value:any )\n    Tests if a value is a number object having a value which is a triangular\n    number.\n","isTruthy":"\nisTruthy( value:any )\n    Tests if a value is a value which translates to `true` when evaluated in a\n    boolean context.\n","isTruthyArray":"\nisTruthyArray( value:any )\n    Tests if a value is an array-like object containing only truthy values.\n","isTypedArray":"\nisTypedArray( value:any )\n    Tests if a value is a typed array.\n","isTypedArrayLength":"\nisTypedArrayLength( value:any )\n    Tests if a value is a valid typed array length.\n","isTypedArrayLike":"\nisTypedArrayLike( value:any )\n    Tests if a value is typed-array-like.\n","isTypeError":"\nisTypeError( value:any )\n    Tests if a value is a TypeError object.\n","isUint8Array":"\nisUint8Array( value:any )\n    Tests if a value is a Uint8Array.\n","isUint8ClampedArray":"\nisUint8ClampedArray( value:any )\n    Tests if a value is a Uint8ClampedArray.\n","isUint16Array":"\nisUint16Array( value:any )\n    Tests if a value is a Uint16Array.\n","isUint32Array":"\nisUint32Array( value:any )\n    Tests if a value is a Uint32Array.\n","isUNCPath":"\nisUNCPath( value:any )\n    Tests if a value is a UNC path.\n","isUndefined":"\nisUndefined( value:any )\n    Tests if a value is undefined.\n","isUndefinedOrNull":"\nisUndefinedOrNull( value:any )\n    Tests if a value is undefined or null.\n","isUnityProbabilityArray":"\nisUnityProbabilityArray( value:any )\n    Tests if a value is an array of probabilities that sum to one.\n","isUppercase":"\nisUppercase( value:any )\n    Tests if a value is an uppercase string.\n","isURI":"\nisURI( value:any )\n    Tests if a value is a URI.\n","isURIError":"\nisURIError( value:any )\n    Tests if a value is a URIError object.\n","isVectorLike":"\nisVectorLike( value:any )\n    Tests if a value is a 1-dimensional ndarray-like object.\n","isWebAssemblyMemory":"\nisWebAssemblyMemory( value:any )\n    Tests if a value is a WebAssembly memory instance.\n","isWellFormedString":"\nisWellFormedString( str:any )\n    Tests if a string is well-formed.\n","isWellFormedString.isPrimitive":"\nisWellFormedString.isPrimitive( str:any )\n    Tests if a string is a well-formed string primitive.\n","isWellFormedString.isObject":"\nisWellFormedString.isObject( str:any )\n    Tests if a string is a well-formed string object.\n","isWhitespace":"\nisWhitespace( str:string )\n    Tests whether a string contains only white space characters.\n","isWritableProperty":"\nisWritableProperty( value:any, property:any )\n    Tests if an object's own property is writable.\n","isWritablePropertyIn":"\nisWritablePropertyIn( value:any, property:any )\n    Tests if an object's own or inherited property is writable.\n","isWriteOnlyProperty":"\nisWriteOnlyProperty( value:any, property:any )\n    Tests if an object's own property is write-only.\n","isWriteOnlyPropertyIn":"\nisWriteOnlyPropertyIn( value:any, property:any )\n    Tests if an object's own or inherited property is write-only.\n","iterAbs":"\niterAbs( iterator:Object )\n    Returns an iterator which iteratively computes the absolute value.\n","iterAbs2":"\niterAbs2( iterator:Object )\n    Returns an iterator which iteratively computes the squared absolute value.\n","iterAcos":"\niterAcos( iterator:Object )\n    Returns an iterator which iteratively computes the arccosine.\n","iterAcosh":"\niterAcosh( iterator:Object )\n    Returns an iterator which iteratively computes the hyperbolic arccosine.\n","iterAcot":"\niterAcot( iterator:Object )\n    Returns an iterator which iteratively computes the inverse cotangent.\n","iterAcoth":"\niterAcoth( iterator:Object )\n    Returns an iterator which iteratively computes the inverse hyperbolic\n    cotangent.\n","iterAcovercos":"\niterAcovercos( iterator:Object )\n    Returns an iterator which iteratively computes the inverse coversed cosine.\n","iterAcoversin":"\niterAcoversin( iterator:Object )\n    Returns an iterator which iteratively computes the inverse coversed sine.\n","iterAdd":"\niterAdd( iter0:Object, ...iterator:Object )\n    Returns an iterator which performs element-wise addition of two or more\n    iterators.\n","iterAdvance":"\niterAdvance( iterator:Object[, n:integer] )\n    Advances an entire iterator.\n","iterAhavercos":"\niterAhavercos( iterator:Object )\n    Returns an iterator which iteratively computes the inverse half-value versed\n    cosine.\n","iterAhaversin":"\niterAhaversin( iterator:Object )\n    Returns an iterator which iteratively computes the inverse half-value versed\n    sine.\n","iterAny":"\niterAny( iterator:Object )\n    Tests whether at least one iterated value is truthy.\n","iterAnyBy":"\niterAnyBy( iterator:Object, predicate:Function[, thisArg:any ] )\n    Tests whether at least one iterated value passes a test implemented by a\n    predicate function.\n","iterAsin":"\niterAsin( iterator:Object )\n    Returns an iterator which iteratively computes the arcsine.\n","iterAsinh":"\niterAsinh( iterator:Object )\n    Returns an iterator which iteratively computes the hyperbolic arcsine.\n","iterAtan":"\niterAtan( iterator:Object )\n    Returns an iterator which iteratively computes the arctangent.\n","iterAtan2":"\niterAtan2( y:Object|number, x:Object|number )\n    Returns an iterator which iteratively computes the angle in the plane (in\n    radians) between the positive x-axis and the ray from (0,0) to the point\n    (x,y).\n","iterAtanh":"\niterAtanh( iterator:Object )\n    Returns an iterator which iteratively computes the hyperbolic arctangent.\n","iterator2array":"\niterator2array( iterator:Object[, out:ArrayLikeObject][, mapFcn:Function[, \n  thisArg:any]] )\n    Creates (or fills) an array from an iterator.\n","iterator2arrayview":"\niterator2arrayview( iterator:Object, dest:ArrayLikeObject[, begin:integer[, \n  end:integer]][, mapFcn:Function[, thisArg:any]] )\n    Fills an array-like object view with values returned from an iterator.\n","iterator2arrayviewRight":"\niterator2arrayviewRight( iterator:Object, dest:ArrayLikeObject[, \n  begin:integer[, end:integer]][, mapFcn:Function[, thisArg:any]] )\n    Fills an array-like object view from right to left with values returned from\n    an iterator.\n","iteratorStream":"\niteratorStream( iterator:Object[, options:Object] )\n    Creates a readable stream from an iterator.\n","iteratorStream.factory":"\niteratorStream.factory( [options:Object] )\n    Returns a function for creating readable streams from iterators.\n","iteratorStream.objectMode":"\niteratorStream.objectMode( iterator:Object[, options:Object] )\n    Returns an \"objectMode\" readable stream from an iterator.\n","IteratorSymbol":"\nIteratorSymbol\n    Iterator symbol.\n","iterAvercos":"\niterAvercos( iterator:Object )\n    Returns an iterator which iteratively computes the inverse versed cosine.\n","iterAversin":"\niterAversin( iterator:Object )\n    Returns an iterator which iteratively computes the inverse versed sine.\n","iterawgn":"\niterawgn( iterator:Object, sigma:number[, options:Object] )\n    Returns an iterator which introduces additive white Gaussian noise (AWGN)\n    with standard deviation `sigma`.\n","iterawln":"\niterawln( iterator:Object, sigma:number[, options:Object] )\n    Returns an iterator which introduces additive white Laplacian noise (AWLN)\n    with standard deviation `sigma`.\n","iterawun":"\niterawun( iterator:Object, sigma:number[, options:Object] )\n    Returns an iterator which introduces additive white uniform noise (AWUN)\n    with standard deviation `sigma`.\n","iterBartlettHannPulse":"\niterBartlettHannPulse( [options:Object] )\n    Returns an iterator which generates a Bartlett-Hann pulse waveform.\n","iterBartlettPulse":"\niterBartlettPulse( [options:Object] )\n    Returns an iterator which generates a Bartlett pulse waveform.\n","iterBesselj0":"\niterBesselj0( iterator:Object )\n    Returns an iterator which iteratively evaluates the Bessel function of the\n    first kind of order zero.\n","iterBesselj1":"\niterBesselj1( iterator:Object )\n    Returns an iterator which iteratively evaluates the Bessel function of the\n    first kind of order one.\n","iterBessely0":"\niterBessely0( iterator:Object )\n    Returns an iterator which iteratively evaluates the Bessel function of the\n    second kind of order zero.\n","iterBessely1":"\niterBessely1( iterator:Object )\n    Returns an iterator which iteratively evaluates the Bessel function of the\n    second kind of order one.\n","iterBeta":"\niterBeta( x:Object|number, y:Object|number )\n    Returns an iterator which iteratively evaluates the beta function.\n","iterBetaln":"\niterBetaln( x:Object|number, y:Object|number )\n    Returns an iterator which iteratively evaluates the natural logarithm of the\n    beta function.\n","iterBinet":"\niterBinet( iterator:Object )\n    Returns an iterator which iteratively evaluates Binet's formula extended to\n    real numbers.\n","iterCbrt":"\niterCbrt( iterator:Object )\n    Returns an iterator which iteratively computes the cube root.\n","iterCeil":"\niterCeil( iterator:Object )\n    Returns an iterator which rounds each iterated value toward positive\n    infinity.\n","iterCeil2":"\niterCeil2( iterator:Object )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    two toward positive infinity.\n","iterCeil10":"\niterCeil10( iterator:Object )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    10 toward positive infinity.\n","iterCompositesSeq":"\niterCompositesSeq( [options:Object] )\n    Returns an iterator which generates a sequence of composite numbers.\n","iterConcat":"\niterConcat( iter0:Object, ...iterator:Object )\n    Returns an iterator which iterates over the values of two or more iterators.\n","iterConstant":"\niterConstant( value:any[, options:Object] )\n    Returns an iterator which always returns the same value.\n","iterContinuedFraction":"\niterContinuedFraction( iterator:Object[, options:Object] )\n    Evaluates the terms of a continued fraction.\n","iterContinuedFractionSeq":"\niterContinuedFractionSeq( x:number[, options:Object] )\n    Returns an iterator which generates a list of all continued fraction terms\n    which can be obtained given the precision of `x`.\n","iterCos":"\niterCos( iterator:Object )\n    Returns an iterator which iteratively computes the cosine.\n","iterCosh":"\niterCosh( iterator:Object )\n    Returns an iterator which iteratively computes the hyperbolic cosine.\n","iterCosineWave":"\niterCosineWave( [options:Object] )\n    Returns an iterator which generates a cosine wave.\n","iterCosm1":"\niterCosm1( iterator:Object )\n    Returns an iterator which iteratively computes `cos(x) - 1`.\n","iterCospi":"\niterCospi( iterator:Object )\n    Returns an iterator which computes the cosine of each iterated value times\n    π.\n","iterCounter":"\niterCounter( iterator:Object )\n    Returns an iterator which iteratively computes the number of iterated\n    values.\n","iterCovercos":"\niterCovercos( iterator:Object )\n    Returns an iterator which iteratively computes the coversed cosine.\n","iterCoversin":"\niterCoversin( iterator:Object )\n    Returns an iterator which iteratively computes the coversed sine.\n","iterCubesSeq":"\niterCubesSeq( [options:Object] )\n    Returns an iterator which generates a sequence of cubes.\n","itercugmean":"\nitercugmean( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative geometric mean.\n","itercuhmean":"\nitercuhmean( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative harmonic mean.\n","itercumax":"\nitercumax( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative maximum value.\n","itercumaxabs":"\nitercumaxabs( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative maximum absolute\n    value.\n","itercumean":"\nitercumean( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative arithmetic mean.\n","itercumeanabs":"\nitercumeanabs( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative arithmetic mean\n    of absolute values.\n","itercumeanabs2":"\nitercumeanabs2( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative arithmetic mean\n    of squared absolute values.\n","itercumidrange":"\nitercumidrange( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative mid-range.\n","itercumin":"\nitercumin( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative minimum value.\n","itercuminabs":"\nitercuminabs( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative minimum absolute\n    value.\n","itercuprod":"\nitercuprod( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative product.\n","itercurange":"\nitercurange( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative range.\n","itercusum":"\nitercusum( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative sum.\n","itercusumabs":"\nitercusumabs( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative sum of absolute\n    values.\n","itercusumabs2":"\nitercusumabs2( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative sum of squared\n    absolute values.\n","iterDatespace":"\niterDatespace( start:integer|string|Date, stop:integer|string|Date[, \n  N:integer][, options:Object] )\n    Returns an iterator which returns evenly spaced dates over a specified\n    interval.\n","iterDedupe":"\niterDedupe( iterator:Object[, limit:integer] )\n    Returns an iterator which removes consecutive duplicated values.\n","iterDedupeBy":"\niterDedupeBy( iterator:Object, [limit:integer,] fcn:Function )\n    Returns an iterator which removes consecutive values that resolve to the\n    same value according to a provided function.\n","iterDeg2rad":"\niterDeg2rad( iterator:Object )\n    Returns an iterator which iteratively converts an angle from degrees to\n    radians.\n","iterDigamma":"\niterDigamma( iterator:Object )\n    Returns an iterator which iteratively evaluates the digamma function.\n","iterDiracComb":"\niterDiracComb( [options:Object] )\n    Returns an iterator which generates a Dirac comb.\n","iterDiracDelta":"\niterDiracDelta( iterator:Object )\n    Returns an iterator which iteratively evaluates the Dirac delta function.\n","iterDivide":"\niterDivide( iter0:Object, ...iterator:Object )\n    Returns an iterator which performs element-wise division of two or more\n    iterators.\n","iterDoWhileEach":"\niterDoWhileEach( iterator:Object, predicate:Function, fcn:Function[, \n  thisArg:any] )\n    Returns an iterator which invokes a function for each iterated value before\n    returning the iterated value until either a predicate function returns false\n    or the iterator has iterated over all values.\n","iterEllipe":"\niterEllipe( iterator:Object )\n    Returns an iterator which iteratively computes the complete elliptic\n    integral of the second kind.\n","iterEllipk":"\niterEllipk( iterator:Object )\n    Returns an iterator which iteratively computes the complete elliptic\n    integral of the first kind.\n","iterEmpty":"\niterEmpty()\n    Returns an empty iterator.\n","iterErf":"\niterErf( iterator:Object )\n    Returns an iterator which iteratively evaluates the error function.\n","iterErfc":"\niterErfc( iterator:Object )\n    Returns an iterator which iteratively evaluates the complementary error\n    function.\n","iterErfcinv":"\niterErfcinv( iterator:Object )\n    Returns an iterator which iteratively evaluates the inverse complementary\n    error function.\n","iterErfinv":"\niterErfinv( iterator:Object )\n    Returns an iterator which iteratively evaluates the inverse error function.\n","iterEta":"\niterEta( iterator:Object )\n    Returns an iterator which iteratively evaluates the Dirichlet eta function.\n","iterEvenIntegersSeq":"\niterEvenIntegersSeq( [options:Object] )\n    Returns an iterator which generates an interleaved sequence of even\n    integers.\n","iterEvery":"\niterEvery( iterator:Object )\n    Tests whether all iterated values are truthy.\n","iterEveryBy":"\niterEveryBy( iterator:Object, predicate:Function[, thisArg:any ] )\n    Tests whether every iterated value passes a test implemented by a predicate\n    function.\n","iterExp":"\niterExp( iterator:Object )\n    Returns an iterator which iteratively evaluates the natural exponential\n    function.\n","iterExp2":"\niterExp2( iterator:Object )\n    Returns an iterator which iteratively evaluates the base `2` exponential\n    function.\n","iterExp10":"\niterExp10( iterator:Object )\n    Returns an iterator which iteratively evaluates the base `10` exponential\n    function.\n","iterExpit":"\niterExpit( iterator:Object )\n    Returns an iterator which iteratively evaluates the standard logistic\n    function.\n","iterExpm1":"\niterExpm1( iterator:Object )\n    Returns an iterator which iteratively computes `exp(x) - 1`.\n","iterExpm1rel":"\niterExpm1rel( iterator:Object )\n    Returns an iterator which iteratively evaluates the relative error\n    exponential.\n","iterFactorial":"\niterFactorial( iterator:Object )\n    Returns an iterator which iteratively evaluates the factorial function.\n","iterFactorialln":"\niterFactorialln( iterator:Object )\n    Returns an iterator which iteratively evaluates the natural logarithm of the\n    factorial function.\n","iterFactorialsSeq":"\niterFactorialsSeq( [options:Object] )\n    Returns an iterator which generates a sequence of factorials.\n","iterFibonacciSeq":"\niterFibonacciSeq( [options:Object] )\n    Returns an iterator which generates a Fibonacci sequence.\n","iterFifthPowersSeq":"\niterFifthPowersSeq( [options:Object] )\n    Returns an iterator which generates a sequence of fifth powers.\n","iterFill":"\niterFill( iterator:Object, value:any[, begin:integer[, end:integer]] )\n    Returns an iterator which replaces all values from a provided iterator from\n    a start index to an end index with a static value.\n","iterFilter":"\niterFilter( iterator:Object, predicate:Function[, thisArg:any] )\n    Returns an iterator which filters a provided iterator's values according to\n    a predicate function.\n","iterFilterMap":"\niterFilterMap( iterator:Object, fcn:Function[, thisArg:any] )\n    Returns an iterator which both filters and maps a provided iterator's\n    values.\n","iterFirst":"\niterFirst( iterator:Object )\n    Returns the first iterated value.\n","iterFlatTopPulse":"\niterFlatTopPulse( [options:Object] )\n    Returns an iterator which generates a flat top pulse waveform.\n","iterFloor":"\niterFloor( iterator:Object )\n    Returns an iterator which rounds each iterated value toward negative\n    infinity.\n","iterFloor2":"\niterFloor2( iterator:Object )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    two toward negative infinity.\n","iterFloor10":"\niterFloor10( iterator:Object )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    10 toward negative infinity.\n","iterFlow":"\niterFlow( methods:Object )\n    Returns a fluent interface iterator constructor with a customized prototype\n    based on provided methods.\n","iterForEach":"\niterForEach( iterator:Object, fcn:Function[, thisArg:any] )\n    Returns an iterator which invokes a function for each iterated value before\n    returning the iterated value.\n","iterFourthPowersSeq":"\niterFourthPowersSeq( [options:Object] )\n    Returns an iterator which generates a sequence of fourth powers.\n","iterFresnelc":"\niterFresnelc( iterator:Object )\n    Returns an iterator which iteratively computes the Fresnel integral C(x).\n","iterFresnels":"\niterFresnels( iterator:Object )\n    Returns an iterator which iteratively computes the Fresnel integral S(x).\n","iterGamma":"\niterGamma( iterator:Object )\n    Returns an iterator which iteratively evaluates the gamma function.\n","iterGamma1pm1":"\niterGamma1pm1( iterator:Object )\n    Returns an iterator which iteratively computes `gamma(x+1) - 1` without\n    cancellation errors for small `x`.\n","iterGammaln":"\niterGammaln( iterator:Object )\n    Returns an iterator which iteratively evaluates the natural logarithm of the\n    gamma function.\n","iterHacovercos":"\niterHacovercos( iterator:Object )\n    Returns an iterator which iteratively computes the half-value coversed\n    cosine.\n","iterHacoversin":"\niterHacoversin( iterator:Object )\n    Returns an iterator which iteratively computes the half-value coversed sine.\n","iterHannPulse":"\niterHannPulse( [options:Object] )\n    Returns an iterator which generates a Hann pulse waveform.\n","iterHavercos":"\niterHavercos( iterator:Object )\n    Returns an iterator which iteratively computes the half-value versed cosine.\n","iterHaversin":"\niterHaversin( iterator:Object )\n    Returns an iterator which iteratively computes the half-value versed sine.\n","iterHead":"\niterHead( iterator:Object, n:integer )\n    Returns an iterator which returns the first `n` values of a provided\n    iterator.\n","iterIncrspace":"\niterIncrspace( start:number, stop:number[, increment:number] )\n    Returns an iterator which returns evenly spaced numbers according to a\n    specified increment.\n","iterIntegersSeq":"\niterIntegersSeq( [options:Object] )\n    Returns an iterator which generates an interleaved integer sequence.\n","iterIntersection":"\niterIntersection( iter0:Object, ...iterator:Object )\n    Returns an iterator which returns the intersection of two or more iterators.\n","iterIntersectionByHash":"\niterIntersectionByHash( iter0:Object, ...iterator:Object, hashFcn:Function[, \n  thisArg:any] )\n    Returns an iterator which returns the intersection of two or more iterators\n    according to a hash function.\n","iterInv":"\niterInv( iterator:Object )\n    Returns an iterator which iteratively computes the multiplicative inverse.\n","iterLanczosPulse":"\niterLanczosPulse( [options:Object] )\n    Returns an iterator which generates a Lanczos pulse waveform.\n","iterLast":"\niterLast( iterator:Object )\n    Consumes an entire iterator and returns the last iterated value.\n","iterLength":"\niterLength( iterator:Object )\n    Consumes an entire iterator and returns the number of iterated values.\n","iterLinspace":"\niterLinspace( start:number, stop:number[, N:integer] )\n    Returns an iterator which returns evenly spaced numbers over a specified\n    interval.\n","iterLn":"\niterLn( iterator:Object )\n    Returns an iterator which iteratively evaluates the natural logarithm.\n","iterLog":"\niterLog( x:Object|number, b:Object|number )\n    Returns an iterator which iteratively computes the base `b` logarithm.\n","iterLog1mexp":"\niterLog1mexp( iterator:Object )\n    Returns an iterator which iteratively evaluates the natural logarithm of\n    `1-exp(-|x|)`.\n","iterLog1p":"\niterLog1p( iterator:Object )\n    Returns an iterator which iteratively evaluates the natural logarithm of\n    `1+x`.\n","iterLog1pexp":"\niterLog1pexp( iterator:Object )\n    Returns an iterator which iteratively evaluates the natural logarithm of\n    `1+exp(x)`.\n","iterLog2":"\niterLog2( iterator:Object )\n    Returns an iterator which iteratively evaluates the binary logarithm.\n","iterLog10":"\niterLog10( iterator:Object )\n    Returns an iterator which iteratively evaluates the common logarithm\n    (logarithm with base 10).\n","iterLogit":"\niterLogit( iterator:Object )\n    Returns an iterator which iteratively evaluates the logit function.\n","iterLogspace":"\niterLogspace( start:number, stop:number[, N:integer][, options:Object] )\n    Returns an iterator which returns evenly spaced numbers on a log scale.\n","iterLucasSeq":"\niterLucasSeq( [options:Object] )\n    Returns an iterator which generates a Lucas sequence.\n","iterMap":"\niterMap( iterator:Object, fcn:Function[, thisArg:any] )\n    Returns an iterator which invokes a function for each iterated value.\n","iterMapN":"\niterMapN( iter0:Object, ...iterator:Object, fcn:Function[, thisArg:any] )\n    Returns an iterator which transforms iterated values from two or more\n    iterators by applying the iterated values as arguments to a provided\n    function.\n","itermax":"\nitermax( iterator:Object )\n    Computes the maximum value of all iterated values.\n","itermaxabs":"\nitermaxabs( iterator:Object )\n    Computes the maximum absolute value of all iterated values.\n","itermean":"\nitermean( iterator:Object )\n    Computes an arithmetic mean over all iterated values.\n","itermeanabs":"\nitermeanabs( iterator:Object )\n    Computes an arithmetic mean of absolute values for all iterated values.\n","itermeanabs2":"\nitermeanabs2( iterator:Object )\n    Computes an arithmetic mean of squared absolute values for all iterated\n    values.\n","itermidrange":"\nitermidrange( iterator:Object )\n    Computes the mid-range of all iterated values.\n","itermin":"\nitermin( iterator:Object )\n    Computes the minimum value of all iterated values.\n","iterminabs":"\niterminabs( iterator:Object )\n    Computes the minimum absolute value of all iterated values.\n","itermmax":"\nitermmax( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving maximum value.\n","itermmaxabs":"\nitermmaxabs( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving maximum absolute\n    value.\n","itermmean":"\nitermmean( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving arithmetic mean.\n","itermmeanabs":"\nitermmeanabs( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving arithmetic mean of\n    absolute values.\n","itermmeanabs2":"\nitermmeanabs2( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving arithmetic mean of\n    squared absolute values.\n","itermmidrange":"\nitermmidrange( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving mid-range.\n","itermmin":"\nitermmin( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving minimum value.\n","itermminabs":"\nitermminabs( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving minimum absolute\n    value.\n","iterMod":"\niterMod( iter0:Object, ...iterator:Object )\n    Returns an iterator which performs an element-wise modulo operation of two\n    or more iterators.\n","itermprod":"\nitermprod( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving product.\n","itermrange":"\nitermrange( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving range.\n","itermsum":"\nitermsum( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving sum.\n","itermsumabs":"\nitermsumabs( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving sum of absolute\n    values.\n","itermsumabs2":"\nitermsumabs2( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving sum of squared\n    absolute values.\n","iterMultiply":"\niterMultiply( iter0:Object, ...iterator:Object )\n    Returns an iterator which performs element-wise multiplication of two or\n    more iterators.\n","iterNegaFibonacciSeq":"\niterNegaFibonacciSeq( [options:Object] )\n    Returns an iterator which generates a negaFibonacci sequence.\n","iterNegaLucasSeq":"\niterNegaLucasSeq( [options:Object] )\n    Returns an iterator which generates a negaLucas sequence.\n","iterNegativeEvenIntegersSeq":"\niterNegativeEvenIntegersSeq( [options:Object] )\n    Returns an iterator which generates a sequence of negative even integers.\n","iterNegativeIntegersSeq":"\niterNegativeIntegersSeq( [options:Object] )\n    Returns an iterator which generates a negative integer sequence.\n","iterNegativeOddIntegersSeq":"\niterNegativeOddIntegersSeq( [options:Object] )\n    Returns an iterator which generates a sequence of negative odd integers.\n","iterNone":"\niterNone( iterator:Object )\n    Tests whether all iterated values are falsy.\n","iterNoneBy":"\niterNoneBy( iterator:Object, predicate:Function[, thisArg:any ] )\n    Tests whether every iterated value fails a test implemented by a predicate\n    function.\n","iterNonFibonacciSeq":"\niterNonFibonacciSeq( [options:Object] )\n    Returns an iterator which generates a non-Fibonacci integer sequence.\n","iterNonNegativeEvenIntegersSeq":"\niterNonNegativeEvenIntegersSeq( [options:Object] )\n    Returns an iterator which generates a sequence of nonnegative even integers.\n","iterNonNegativeIntegersSeq":"\niterNonNegativeIntegersSeq( [options:Object] )\n    Returns an iterator which generates a nonnegative integer sequence.\n","iterNonPositiveEvenIntegersSeq":"\niterNonPositiveEvenIntegersSeq( [options:Object] )\n    Returns an iterator which generates a sequence of nonpositive even integers.\n","iterNonPositiveIntegersSeq":"\niterNonPositiveIntegersSeq( [options:Object] )\n    Returns an iterator which generates a nonpositive integer sequence.\n","iterNonSquaresSeq":"\niterNonSquaresSeq( [options:Object] )\n    Returns an iterator which generates a sequence of nonsquares.\n","iterNth":"\niterNth( iterator:Object, n:integer )\n    Returns the nth iterated value.\n","iterOddIntegersSeq":"\niterOddIntegersSeq( [options:Object] )\n    Returns an iterator which generates an interleaved sequence of odd integers.\n","iterPeriodicSinc":"\niterPeriodicSinc( n:integer[, options:Object] )\n    Returns an iterator which generates a periodic sinc waveform.\n","iterPipeline":"\niterPipeline( iterFcn:Function|Array[, ...iterFcn:Function] )\n    Returns an iterator pipeline.\n","iterPop":"\niterPop( iterator:Object[, clbk:Function[, thisArg:any]] )\n    Returns an iterator which skips the last value of a provided iterator.\n","iterPositiveEvenIntegersSeq":"\niterPositiveEvenIntegersSeq( [options:Object] )\n    Returns an iterator which generates a sequence of positive even integers.\n","iterPositiveIntegersSeq":"\niterPositiveIntegersSeq( [options:Object] )\n    Returns an iterator which generates a positive integer sequence.\n","iterPositiveOddIntegersSeq":"\niterPositiveOddIntegersSeq( [options:Object] )\n    Returns an iterator which generates a sequence of positive odd integers.\n","iterPow":"\niterPow( base:Object|number, exponent:Object|number )\n    Returns an iterator which iteratively evaluates the exponential function.\n","iterPrimesSeq":"\niterPrimesSeq( [options:Object] )\n    Returns an iterator which generates a sequence of prime numbers.\n","iterprod":"\niterprod( iterator:Object )\n    Computes the product of all iterated values.\n","iterPulse":"\niterPulse( [options:Object] )\n    Returns an iterator which generates a pulse waveform.\n","iterPush":"\niterPush( iterator:Object, ...items:any )\n    Returns an iterator which appends additional values to the end of a provided\n    iterator.\n","iterRad2deg":"\niterRad2deg( iterator:Object )\n    Returns an iterator which iteratively converts an angle from radians to\n    degrees.\n","iterRamp":"\niterRamp( iterator:Object )\n    Returns an iterator which iteratively evaluates the ramp function.\n","iterrange":"\niterrange( iterator:Object )\n    Computes the range of all iterated values.\n","iterReject":"\niterReject( iterator:Object, predicate:Function[, thisArg:any] )\n    Returns an iterator which rejects a provided iterator's values according to\n    a predicate function.\n","iterReplicate":"\niterReplicate( iterator:Object, n:integer )\n    Returns an iterator which replicates each iterated value `n` times.\n","iterReplicateBy":"\niterReplicateBy( iterator:Object, fcn:Function[, thisArg:any] )\n    Returns an iterator which replicates each iterated value according to a\n    provided function.\n","iterRound":"\niterRound( iterator:Object )\n    Returns an iterator which rounds each iterated value to the nearest integer.\n","iterRound2":"\niterRound2( iterator:Object )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    two on a linear scale.\n","iterRound10":"\niterRound10( iterator:Object )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    10 on a linear scale.\n","iterRsqrt":"\niterRsqrt( iterator:Object )\n    Returns an iterator which iteratively computes the reciprocal (inverse)\n    square root.\n","iterSawtoothWave":"\niterSawtoothWave( [options:Object] )\n    Returns an iterator which generates a sawtooth wave.\n","iterShift":"\niterShift( iterator:Object[, clbk:Function[, thisArg:any]] )\n    Returns an iterator which skips the first value of a provided iterator.\n","iterSignum":"\niterSignum( iterator:Object )\n    Returns an iterator which iteratively evaluates the signum function.\n","iterSin":"\niterSin( iterator:Object )\n    Returns an iterator which iteratively computes the sine.\n","iterSinc":"\niterSinc( iterator:Object )\n    Returns an iterator which iteratively computes the normalized cardinal sine.\n","iterSineWave":"\niterSineWave( [options:Object] )\n    Returns an iterator which generates a sine wave.\n","iterSinh":"\niterSinh( iterator:Object )\n    Returns an iterator which iteratively evaluates the hyperbolic sine.\n","iterSinpi":"\niterSinpi( iterator:Object )\n    Returns an iterator which computes the sine of each iterated value times π.\n","iterSlice":"\niterSlice( iterator:Object[, begin:integer[, end:integer]] )\n    Returns an iterator which returns a subsequence of iterated values from a\n    provided iterator.\n","iterSome":"\niterSome( iterator:Object, n:number )\n    Tests whether at least `n` iterated values are truthy.\n","iterSomeBy":"\niterSomeBy( iterator:Object, n:integer, predicate:Function[, thisArg:any ] )\n    Tests whether at least `n` iterated values pass a test implemented by a\n    predicate function.\n","iterSpence":"\niterSpence( iterator:Object )\n    Returns an iterator which iteratively evaluates Spence's function.\n","iterSqrt":"\niterSqrt( iterator:Object )\n    Returns an iterator which iteratively computes the principal square root.\n","iterSqrt1pm1":"\niterSqrt1pm1( iterator:Object )\n    Returns an iterator which iteratively computes `sqrt(1+x) - 1` more \n    accurately for small `x`.\n","iterSquaredTriangularSeq":"\niterSquaredTriangularSeq( [options:Object] )\n    Returns an iterator which generates a sequence of squared triangular\n    numbers.\n","iterSquaresSeq":"\niterSquaresSeq( [options:Object] )\n    Returns an iterator which generates a sequence of squares.\n","iterSquareWave":"\niterSquareWave( [options:Object] )\n    Returns an iterator which generates a square wave.\n","iterstdev":"\niterstdev( iterator:Object[, mean:number] )\n    Computes a correct sample standard deviation over all iterated values.\n","iterStep":"\niterStep( start:number, increment:number[, N:number] )\n    Returns an iterator which returns a sequence of numbers according to a\n    specified increment.\n","iterStrided":"\niterStrided( iterator:Object, stride:integer[, offset:integer[, \n  eager:boolean]] )\n    Returns an iterator which steps by a specified amount.\n","iterStridedBy":"\niterStridedBy( iterator:Object, fcn:Function[, offset:integer[, \n  eager:boolean]][, thisArg:any] )\n    Returns an iterator which steps according to a provided callback function.\n","iterSubtract":"\niterSubtract( iter0:Object, ...iterator:Object )\n    Returns an iterator which performs element-wise subtraction of two or more\n    iterators.\n","itersum":"\nitersum( iterator:Object )\n    Computes the sum of all iterated values.\n","itersumabs":"\nitersumabs( iterator:Object )\n    Computes the sum of absolute values for all iterated values.\n","itersumabs2":"\nitersumabs2( iterator:Object )\n    Computes the sum of squared absolute values for all iterated values.\n","iterTan":"\niterTan( iterator:Object )\n    Returns an iterator which iteratively evaluates the tangent.\n","iterTanh":"\niterTanh( iterator:Object )\n    Returns an iterator which iteratively evaluates the hyperbolic tangent.\n","iterThunk":"\niterThunk( iterFcn:Function[, ...args:any] )\n    Returns an iterator \"thunk\".\n","iterTriangleWave":"\niterTriangleWave( [options:Object] )\n    Returns an iterator which generates a triangle wave.\n","iterTriangularSeq":"\niterTriangularSeq( [options:Object] )\n    Returns an iterator which generates a sequence of triangular numbers.\n","iterTribonnaciSeq":"\niterTribonnaciSeq( [options:Object] )\n    Returns an iterator which generates a Tribonacci sequence.\n    \n    The returned iterator can only generate the first 64 Tribonacci numbers, as\n    larger Tribonacci numbers cannot be safely represented in double-precision\n    floating-point format.\n","iterTrigamma":"\niterTrigamma( iterator:Object )\n    Returns an iterator which iteratively evaluates the trigamma function.\n","iterTrunc":"\niterTrunc( iterator:Object )\n    Returns an iterator which rounds each iterated value toward zero.\n","iterTrunc2":"\niterTrunc2( iterator:Object )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    two toward zero.\n","iterTrunc10":"\niterTrunc10( iterator:Object )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    10 toward zero.\n","iterUnion":"\niterUnion( iter0:Object, ...iterator:Object )\n    Returns an iterator which returns the union of two or more iterators.\n","iterUnique":"\niterUnique( iterator:Object )\n    Returns an iterator which returns unique values.\n","iterUniqueBy":"\niterUniqueBy( iterator:Object, predicate:Function[, thisArg:any] )\n    Returns an iterator which returns unique values according to a predicate\n    function.\n","iterUniqueByHash":"\niterUniqueByHash( iterator:Object, hashFcn:Function[, thisArg:any] )\n    Returns an iterator which returns unique values according to a hash\n    function.\n","iterUnitspace":"\niterUnitspace( start:number[, stop:number] )\n    Returns an iterator which returns numbers incremented by one.\n","iterUnshift":"\niterUnshift( iterator:Object, ...items:any )\n    Returns an iterator which prepends values to the beginning of a provided\n    iterator.\n","iterUntilEach":"\niterUntilEach( iterator:Object, predicate:Function, fcn:Function[, \n  thisArg:any] )\n    Returns an iterator which invokes a function for each iterated value before\n    returning the iterated value until either a predicate function returns true\n    or the iterator has iterated over all values.\n","itervariance":"\nitervariance( iterator:Object[, mean:number] )\n    Computes an unbiased sample variance over all iterated values.\n","iterVercos":"\niterVercos( iterator:Object )\n    Returns an iterator which iteratively computes the versed cosine.\n","iterVersin":"\niterVersin( iterator:Object )\n    Returns an iterator which iteratively computes the versed sine.\n","iterWhileEach":"\niterWhileEach( iterator:Object, predicate:Function, fcn:Function[, \n  thisArg:any] )\n    Returns an iterator which invokes a function for each iterated value before\n    returning the iterated value until either a predicate function returns false\n    or the iterator has iterated over all values.\n","iterZeta":"\niterZeta( iterator:Object )\n    Returns an iterator which iteratively evaluates the Riemann zeta function.\n","joinStream":"\njoinStream( [options:Object] )\n    Returns a transform stream which joins streamed data.\n","joinStream.factory":"\njoinStream.factory( [options:Object] )\n    Returns a function for creating transform streams for joined streamed data.\n","joinStream.objectMode":"\njoinStream.objectMode( [options:Object] )\n    Returns an \"objectMode\" transform stream for joining streamed data.\n","kde2d":"\nkde2d( x:Array<number>, y:Array<number>[, options:Object] )\n    Two-dimensional kernel density estimation.\n","kebabcase":"\nkebabcase( str:string )\n    Converts a string to kebab case.\n","keyBy":"\nkeyBy( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n    Converts a collection to an object whose keys are determined by a provided\n    function and whose values are the collection values.\n","keyByRight":"\nkeyByRight( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n    Converts a collection to an object whose keys are determined by a provided\n    function and whose values are the collection values, iterating from right to\n    left.\n","keysIn":"\nkeysIn( obj:any )\n    Returns an array of an object's own and inherited enumerable property\n    names.\n","kruskalTest":"\nkruskalTest( ...x:Array[, options:Object] )\n    Computes the Kruskal-Wallis test for equal medians.\n","kstest":"\nkstest( x:Array<number>, y:Function|string[, ...params:number][, \n  options:Object] )\n    Computes a Kolmogorov-Smirnov goodness-of-fit test.\n","last":"\nlast( str:string[, n:integer][, options:Object] )\n    Returns the last character(s) of a string.\n","leveneTest":"\nleveneTest( x:Array<number>[, ...y:Array<number>[, options:Object]] )\n    Computes Levene's test for equal variances.\n","LinkedList":"\nLinkedList()\n    Linked list constructor.\n","linspace":"\nlinspace( start:number|ComplexLike, stop:number|ComplexLike, length:integer[, \n  options:Object] )\n    Generates a linearly spaced array over a specified interval.\n","linspace.assign":"\nlinspace.assign( start:number|ComplexLike, stop:number|ComplexLike, \n  out:ArrayLikeObject[, options:Object] )\n    Generates a linearly spaced sequence over a specified interval and assigns\n    the results to a provided output array.\n","LIU_NEGATIVE_OPINION_WORDS_EN":"\nLIU_NEGATIVE_OPINION_WORDS_EN()\n    Returns a list of negative opinion words.\n","LIU_POSITIVE_OPINION_WORDS_EN":"\nLIU_POSITIVE_OPINION_WORDS_EN()\n    Returns a list of positive opinion words.\n","LN_HALF":"\nLN_HALF\n    Natural logarithm of `1/2`.\n","LN_PI":"\nLN_PI\n    Natural logarithm of the mathematical constant `π`.\n","LN_SQRT_TWO_PI":"\nLN_SQRT_TWO_PI\n    Natural logarithm of the square root of `2π`.\n","LN_TWO_PI":"\nLN_TWO_PI\n    Natural logarithm of `2π`.\n","LN2":"\nLN2\n    Natural logarithm of `2`.\n","LN10":"\nLN10\n    Natural logarithm of `10`.\n","LOG2E":"\nLOG2E\n    Base 2 logarithm of Euler's number.\n","LOG10E":"\nLOG10E\n    Base 10 logarithm of Euler's number.\n","logspace":"\nlogspace( a:number, b:number[, length:integer] )\n    Generates a logarithmically spaced numeric array between `10^a` and `10^b`.\n","lowercase":"\nlowercase( str:string )\n    Converts a string to lowercase.\n","lowercaseKeys":"\nlowercaseKeys( obj:Object )\n    Converts each object key to lowercase.\n","lowess":"\nlowess( x:Array<number>, y:Array<number>[, options:Object] )\n    Locally-weighted polynomial regression via the LOWESS algorithm.\n","lpad":"\nlpad( str:string, len:integer[, pad:string] )\n    Left pads a string such that the padded string has a length of at least\n    `len`.\n","ltrim":"\nltrim( str:string )\n    Trims whitespace from the beginning of a string.\n","ltrimN":"\nltrimN( str:string, n:integer[, chars:Array|string] )\n    Trims `n` characters from the beginning of a string.\n","MALE_FIRST_NAMES_EN":"\nMALE_FIRST_NAMES_EN()\n    Returns a list of common male first names in English speaking countries.\n","map":"\nmap( arr:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n    Applies a function to each element in an array and assigns the result to an\n    element in a new array.\n","map.assign":"\nmap.assign( arr:ArrayLikeObject|ndarray, out:ArrayLikeObject|ndarray, \n  fcn:Function[, thisArg:any] )\n    Applies a function to each element in an array and assigns the result to an\n    element in an output array.\n","map2":"\nmap2( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, fcn:Function[, \n  thisArg:any] )\n    Applies a function to elements in two input arrays and assigns the results\n    to a new array.\n","map2.assign":"\nmap2.assign( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, \n  out:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n    Applies a function to elements in two input arrays and assigns the results\n    to an output array.\n","map2d":"\nmap2d( arr:ArrayLikeObject<ArrayLikeObject>, fcn:Function[, thisArg:any] )\n    Applies a function to each nested element in an array of arrays and assigns\n    the result to a nested element in a new array of arrays.\n","map2Right":"\nmap2Right( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, fcn:Function[, \n  thisArg:any] )\n    Applies a function to elements in two input arrays while iterating from\n    right to left and assigns the results to a new array.\n","map2Right.assign":"\nmap2Right.assign( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, \n  out:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n    Applies a function to elements in two input arrays while iterating from\n    right to left and assigns the results to an output array.\n","map3d":"\nmap3d( arr:ArrayLikeObject<ArrayLikeObject<ArrayLikeObject>>, fcn:Function[, \n  thisArg:any] )\n    Applies a function to each nested element in a three-dimensional nested\n    array and assigns the result to a nested element in a new three-dimensional\n    nested array.\n","map4d":"\nmap4d( arr:ArrayLikeObject<ArrayLikeObject>, fcn:Function[, thisArg:any] )\n    Applies a function to each nested element in a four-dimensional nested array\n    and assigns the result to a nested element in a new four-dimensional nested\n    array.\n","map5d":"\nmap5d( arr:ArrayLikeObject<ArrayLikeObject>, fcn:Function[, thisArg:any] )\n    Applies a function to each nested element in a five-dimensional nested array\n    and assigns the result to a nested element in a new five-dimensional nested\n    array.\n","mapArguments":"\nmapArguments( fcn:Function, clbk:Function[, thisArg:any] )\n    Returns a function that applies arguments to a provided function after\n    transforming arguments according to a callback function.\n","mapFun":"\nmapFun( fcn:Function, n:integer[, thisArg:any] )\n    Invokes a function `n` times and returns an array of accumulated function\n    return values.\n","mapFunAsync":"\nmapFunAsync( fcn:Function, n:integer, [options:Object,] done:Function )\n    Invokes a function `n` times and returns an array of accumulated function\n    return values.\n","mapFunAsync.factory":"\nmapFunAsync.factory( [options:Object,] fcn:Function )\n    Returns a function which invokes a function `n` times and returns an array\n    of accumulated function return values.\n","mapKeys":"\nmapKeys( obj:Object, transform:Function )\n    Maps keys from one object to a new object having the same values.\n","mapKeysAsync":"\nmapKeysAsync( obj:Object, [options:Object,] transform:Function, done:Function )\n    Maps keys from one object to a new object having the same values.\n","mapKeysAsync.factory":"\nmapKeysAsync.factory( [options:Object,] transform:Function )\n    Returns a function which maps keys from one object to a new object having\n    the same values.\n","mapReduce":"\nmapReduce( arr:ArrayLikeObject|ndarray, initial:any, mapper:Function, \n  reducer:Function[, thisArg:any] )\n    Performs a map-reduce operation for each element in an array and returns the\n    accumulated result.\n","mapReduceRight":"\nmapReduceRight( arr:ArrayLikeObject|ndarray, initial:any, mapper:Function, \n  reducer:Function[, thisArg:any] )\n    Performs a map-reduce operation for each element in an array while iterating\n    from right to left and returns the accumulated result.\n","mapRight":"\nmapRight( arr:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n    Applies a function to each element in an array and assigns the result to an\n    element in a new array, iterating from right to left.\n","mapRight.assign":"\nmapRight.assign( arr:ArrayLikeObject|ndarray, out:ArrayLikeObject|ndarray, \n  fcn:Function[, thisArg:any] )\n    Applies a function to each element in an array and assigns the result to an\n    element in an output array, iterating from right to left.\n","mapValues":"\nmapValues( obj:Object, transform:Function )\n    Maps values from one object to a new object having the same keys.\n","mapValuesAsync":"\nmapValuesAsync( obj:Object, [options:Object,] transform:Function, \n  done:Function )\n    Maps values from one object to a new object having the same keys.\n","mapValuesAsync.factory":"\nmapValuesAsync.factory( [options:Object,] transform:Function )\n    Returns a function which maps values from one object to a new object having\n    the same keys.\n","maskArguments":"\nmaskArguments( fcn:Function, mask:ArrayLikeObject[, thisArg:any] )\n    Returns a function that applies arguments to a provided function according\n    to a specified mask.\n","MAX_ARRAY_LENGTH":"\nMAX_ARRAY_LENGTH\n    Maximum length for a generic array.\n","MAX_TYPED_ARRAY_LENGTH":"\nMAX_TYPED_ARRAY_LENGTH\n    Maximum length for a typed array.\n","maybeBroadcastArray":"\nmaybeBroadcastArray( x:ndarray, shape:ArrayLikeObject )\n    Broadcasts an ndarray to a specified shape if and only if the specified\n    shape differs from the provided ndarray's shape.\n","maybeBroadcastArrays":"\nmaybeBroadcastArrays( ...arrays:ndarray|ArrayLikeObject<ndarray> )\n    Broadcasts ndarrays to a common shape.\n","memoize":"\nmemoize( fcn:Function[, hashFunction:Function] )\n    Returns a memoized function.\n","merge":"\nmerge( target:Object, ...source:Object )\n    Merges objects into a target object.\n","merge.factory":"\nmerge.factory( options:Object )\n    Returns a function for merging and extending objects.\n","MILLISECONDS_IN_DAY":"\nMILLISECONDS_IN_DAY\n    Number of milliseconds in a day.\n","MILLISECONDS_IN_HOUR":"\nMILLISECONDS_IN_HOUR\n    Number of milliseconds in an hour.\n","MILLISECONDS_IN_MINUTE":"\nMILLISECONDS_IN_MINUTE\n    Number of milliseconds in a minute.\n","MILLISECONDS_IN_SECOND":"\nMILLISECONDS_IN_SECOND\n    Number of milliseconds in a second.\n","MILLISECONDS_IN_WEEK":"\nMILLISECONDS_IN_WEEK\n    Number of milliseconds in a week.\n","MINARD_NAPOLEONS_MARCH":"\nMINARD_NAPOLEONS_MARCH( [options:Object] )\n    Returns data for Charles Joseph Minard's cartographic depiction of\n    Napoleon's Russian campaign of 1812.\n","MINUTES_IN_DAY":"\nMINUTES_IN_DAY\n    Number of minutes in a day.\n","MINUTES_IN_HOUR":"\nMINUTES_IN_HOUR\n    Number of minutes in an hour.\n","MINUTES_IN_WEEK":"\nMINUTES_IN_WEEK\n    Number of minutes in a week.\n","minutesInMonth":"\nminutesInMonth( [month:string|Date|integer[, year:integer]] )\n    Returns the number of minutes in a month.\n","minutesInYear":"\nminutesInYear( [value:integer|Date] )\n    Returns the number of minutes in a year according to the Gregorian calendar.\n","MOBY_DICK":"\nMOBY_DICK()\n    Returns the text of Moby Dick by Herman Melville.\n","MONTH_NAMES_EN":"\nMONTH_NAMES_EN()\n    Returns a list of month names (English).\n","MONTHS_IN_YEAR":"\nMONTHS_IN_YEAR\n    Number of months in a year.\n","moveProperty":"\nmoveProperty( source:Object, prop:string, target:Object )\n    Moves a property from one object to another object.\n","MultiSlice":"\nMultiSlice( ...slice )\n    Returns a multi-slice.\n","MultiSlice.prototype.ndims":"\nMultiSlice.prototype.ndims\n    Read-only property returning the number of slice dimensions.\n","MultiSlice.prototype.data":"\nMultiSlice.prototype.data\n    Read-only property returning the slice data.\n","MultiSlice.prototype.toString":"\nMultiSlice.prototype.toString()\n    Serializes a multi-slice as a string.\n","MultiSlice.prototype.toJSON":"\nMultiSlice.prototype.toJSON()\n    Serializes a multi-slice as a JSON object.\n","namedtypedtuple":"\nnamedtypedtuple( fields:Array<string>[, options:Object] )\n    Returns a named typed tuple factory.\n","NAN":"\nNAN\n    Double-precision floating-point NaN.\n","naryFunction":"\nnaryFunction( fcn:Function, arity:integer[, thisArg:any] )\n    Returns a function that applies a specified number of arguments to a\n    provided function.\n","nativeClass":"\nnativeClass( value:any )\n    Returns a string value indicating a specification defined classification of\n    an object.\n","ndarray":"\nndarray( dtype:string, buffer:ArrayLikeObject|TypedArray|Buffer, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  offset:integer, order:string[, options:Object] )\n    Returns an ndarray.\n","ndarray.prototype.byteLength":"\nndarray.prototype.byteLength\n    Size (in bytes) of the array (if known).\n","ndarray.prototype.BYTES_PER_ELEMENT":"\nndarray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element (if known).\n","ndarray.prototype.data":"\nndarray.prototype.data\n    Pointer to the underlying data buffer.\n","ndarray.prototype.dtype":"\nndarray.prototype.dtype\n    Underlying data type.\n","ndarray.prototype.flags":"\nndarray.prototype.flags\n    Meta information, such as information concerning the memory layout of the\n    array.\n","ndarray.prototype.length":"\nndarray.prototype.length\n    Length of the array (i.e., number of elements).\n","ndarray.prototype.ndims":"\nndarray.prototype.ndims\n    Number of dimensions.\n","ndarray.prototype.offset":"\nndarray.prototype.offset\n    Index offset which specifies the buffer index at which to start iterating\n    over array elements.\n","ndarray.prototype.order":"\nndarray.prototype.order\n    Array order.\n","ndarray.prototype.shape":"\nndarray.prototype.shape\n    Array shape.\n","ndarray.prototype.strides":"\nndarray.prototype.strides\n    Index strides which specify how to access data along corresponding array\n    dimensions.\n","ndarray.prototype.get":"\nndarray.prototype.get( ...idx:integer )\n    Returns an array element specified according to provided subscripts.\n","ndarray.prototype.iget":"\nndarray.prototype.iget( idx:integer )\n    Returns an array element located at a specified linear index.\n","ndarray.prototype.set":"\nndarray.prototype.set( ...idx:integer, v:any )\n    Sets an array element specified according to provided subscripts.\n","ndarray.prototype.iset":"\nndarray.prototype.iset( idx:integer, v:any )\n    Sets an array element located at a specified linear index.\n","ndarray.prototype.toString":"\nndarray.prototype.toString()\n    Serializes an ndarray as a string.\n","ndarray.prototype.toJSON":"\nndarray.prototype.toJSON()\n    Serializes an ndarray as a JSON object.\n","ndarray2array":"\nndarray2array( x:ndarray )\n    Converts an ndarray to a generic array.\n","ndarray2fancy":"\nndarray2fancy( x:ndarray[, options:Object] )\n    Converts an ndarray to an object supporting fancy indexing.\n","ndarray2fancy.factory":"\nndarray2fancy.factory( [options:Object] )\n    Returns a function for converting an ndarray to an object supporting fancy\n    indexing.\n","ndarray2fancy.idx":"\nndarray2fancy.idx( x:ndarray[, options:Object] )\n    Wraps a provided ndarray as an ndarray index object.\n","ndarray2json":"\nndarray2json( x:ndarray )\n    Serializes an ndarray as a JSON object.\n","ndarrayCastingModes":"\nndarrayCastingModes()\n    Returns a list of ndarray casting modes.\n","ndarrayDataBuffer":"\nndarrayDataBuffer( x:ndarray )\n    Returns the underlying data buffer of a provided ndarray.\n","ndarrayDataType":"\nndarrayDataType( x:ndarray )\n    Returns the data type of a provided ndarray.\n","ndarrayDataTypes":"\nndarrayDataTypes( [kind:string] )\n    Returns a list of ndarray data types.\n","ndarrayDispatch":"\nndarrayDispatch( fcns:Function|ArrayLikeObject<Function>, \n  types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, \n  nout:integer )\n    Returns an ndarray function interface which performs multiple dispatch.\n","ndarrayFlag":"\nndarrayFlag( x:ndarray, name:string|symbol )\n    Returns a specified flag for a provided ndarray.\n","ndarrayFlags":"\nndarrayFlags( x:ndarray )\n    Returns the flags of a provided ndarray.\n","ndarrayIndexModes":"\nndarrayIndexModes()\n    Returns a list of ndarray index modes.\n","ndarraylike2ndarray":"\nndarraylike2ndarray( x:ndarrayLike[, options:Object] )\n    Converts an ndarray-like object to an ndarray.\n","ndarrayMinDataType":"\nndarrayMinDataType( value:any )\n    Returns the minimum ndarray data type of the closest \"kind\" necessary for\n    storing a provided scalar value.\n","ndarrayMostlySafeCasts":"\nndarrayMostlySafeCasts( [dtype:any] )\n    Returns a list of ndarray data types to which a provided ndarray data type\n    can be safely cast and, for floating-point data types, can be downcast.\n","ndarrayNextDataType":"\nndarrayNextDataType( [dtype:any] )\n    Returns the next larger ndarray data type of the same kind.\n","ndarrayOffset":"\nndarrayOffset( x:ndarray )\n    Returns the index offset specifying the underlying buffer index of the first\n    iterated ndarray element.\n","ndarrayOrder":"\nndarrayOrder( x:ndarray )\n    Returns the layout order of a provided ndarray.\n","ndarrayOrders":"\nndarrayOrders()\n    Returns a list of ndarray orders.\n","ndarrayPromotionRules":"\nndarrayPromotionRules( [dtype1:any, dtype2:any] )\n    Returns the ndarray data type with the smallest size and closest \"kind\" to\n    which ndarray data types can be safely cast.\n","ndarraySafeCasts":"\nndarraySafeCasts( [dtype:any] )\n    Returns a list of ndarray data types to which a provided ndarray data type\n    can be safely cast.\n","ndarraySameKindCasts":"\nndarraySameKindCasts( [dtype:any] )\n    Returns a list of ndarray data types to which a provided ndarray data type\n    can be safely cast or cast within the same \"kind\".\n","ndarrayShape":"\nndarrayShape( x:ndarray )\n    Returns the shape of a provided ndarray.\n","ndarrayStride":"\nndarrayStride( x:ndarray, dim:integer )\n    Returns the stride along a specified dimension for a provided ndarray.\n","ndarrayStrides":"\nndarrayStrides( x:ndarray )\n    Returns the strides of a provided ndarray.\n","ndat":"\nndat( x:ndarray[, ...indices:integer] )\n    Returns an ndarray element.\n","ndempty":"\nndempty( shape:ArrayLikeObject<integer>|integer[, options:Object] )\n    Returns an uninitialized ndarray having a specified shape and data type.\n","ndemptyLike":"\nndemptyLike( x:ndarray[, options:Object] )\n    Returns an uninitialized ndarray having the same shape and data type as a\n    provided input ndarray.\n","ndfilter":"\nndfilter( x:ndarray[, options:Object], predicate:Function[, thisArg:any] )\n    Returns a shallow copy of an ndarray containing only those elements which\n    pass a test implemented by a predicate function.\n","ndfilterMap":"\nndfilterMap( x:ndarray[, options:Object], fcn:Function[, thisArg:any] )\n    Filters and maps elements in an input ndarray to elements in a new output\n    ndarray according to a callback function.\n","ndforEach":"\nndforEach( x:ndarray, fcn:Function[, thisArg:any] )\n    Invokes a callback function once for each ndarray element.\n","ndims":"\nndims( x:ndarray )\n    Returns the number of ndarray dimensions.\n","ndindex":"\nndindex( x:ndarray[, options:Object] )\n    Wraps a provided array as an ndarray index object.\n","ndindex.free":"\nndindex.free( id:string )\n    Frees the instance associated with a provided identifier.\n","ndindex.get":"\nndindex.get( id:string )\n    Returns the ndarray associated with the instance having a provided\n    identifier.\n","ndindex.cartesianIndex":"\nndindex.cartesianIndex( x:ndarray[, options:Object] )\n    Returns an ndarray index containing Cartesian indices.\n","ndindex.linearIndex":"\nndindex.linearIndex( x:ndarray[, options:Object] )\n    Returns an ndarray index for indices representing locations in linear\n    memory.\n","ndindex.prototype.data":"\nndindex.prototype.data\n    Read-only property returning an ndarray view of the underlying index\n    ndarray.\n","ndindex.prototype.dtype":"\nndindex.prototype.dtype\n    Read-only property returning the underlying data type of the index ndarray.\n","ndindex.prototype.id":"\nndindex.prototype.id\n    Read-only property returning the unique identifier associated with an\n    instance.\n","ndindex.prototype.isCached":"\nndindex.prototype.isCached\n    Read-only property returning a boolean indicating whether an ndarray index\n    is actively cached.\n","ndindex.prototype.kind":"\nndindex.prototype.kind\n    Read-only property returning the ndarray index kind.\n","ndindex.prototype.type":"\nndindex.prototype.type\n    Read-only property returning the ndarray index type.\n","ndindex.prototype.toString":"\nndindex.prototype.toString()\n    Serializes an instance as a string.\n","ndindex.prototype.toJSON":"\nndindex.prototype.toJSON()\n    Serializes an instance as a JSON object.\n","nditerColumnEntries":"\nnditerColumnEntries( x:ndarray[, options:Object] )\n    Returns an iterator which returns [index, column] pairs for each column in a\n    matrix (or stack of matrices).\n","nditerColumns":"\nnditerColumns( x:ndarray[, options:Object] )\n    Returns an iterator which iterates over each column in a matrix (or stack of\n    matrices).\n","nditerEntries":"\nnditerEntries( x:ndarray[, options:Object] )\n    Returns an iterator which returns [index, value] pairs for each element in a\n    provided ndarray.\n","nditerIndices":"\nnditerIndices( shape:Array<integer>[, options:Object] )\n    Returns an iterator which returns indices for use indexing into an ndarray\n    having a specified shape.\n","nditerInterleaveSubarrays":"\nnditerInterleaveSubarrays( arr:ArrayLike<ndarray>, ndims:integer )\n    Returns an iterator which iterates over interleaved subarrays.\n","nditerMatrices":"\nnditerMatrices( x:ndarray[, options:Object] )\n    Returns an iterator which iterates over each matrix in a stack of matrices.\n","nditerMatrixEntries":"\nnditerMatrixEntries( x:ndarray[, options:Object] )\n    Returns an iterator which returns [index, matrix] pairs for each matrix in a\n    stack of matrices.\n","nditerRowEntries":"\nnditerRowEntries( x:ndarray[, options:Object] )\n    Returns an iterator which returns [index, row] pairs for each row in a\n    matrix (or stack of matrices).\n","nditerRows":"\nnditerRows( x:ndarray[, options:Object] )\n    Returns an iterator which iterates over each row in a matrix (or stack of\n    matrices).\n","nditerSelectDimension":"\nnditerSelectDimension( x:ndarray, dim:integer[, options:Object] )\n    Returns an iterator which iterates over each view along a specified\n    dimension.\n","nditerStacks":"\nnditerStacks( x:ndarray, dims:Array<integer>[, options:Object] )\n    Returns an iterator which iterates over each subarray in a stack of\n    subarrays according to a list of specified stack dimensions.\n","nditerSubarrays":"\nnditerSubarrays( x:ndarray, ndims:integer[, options:Object] )\n    Returns an iterator which iterates over each subarray in a stack of\n    subarrays.\n","nditerValues":"\nnditerValues( x:ndarray[, options:Object] )\n    Returns an iterator which returns individual elements from a provided\n    ndarray.\n","ndmap":"\nndmap( x:ndarray[, options:Object], fcn:Function[, thisArg:any] )\n    Applies a callback function to elements in an input ndarray and assigns\n    results to elements in a new output ndarray.\n","ndreject":"\nndreject( x:ndarray[, options:Object], predicate:Function[, thisArg:any] )\n    Returns a shallow copy of an ndarray containing only those elements which\n    fail a test implemented by a predicate function.\n","ndslice":"\nndslice( x:ndarray, ...s:MultiSlice|Slice|null|undefined|integer|ArrayLike[, \n  options:Object] )\n    Returns a read-only view of an input ndarray.\n","ndsliceAssign":"\nndsliceAssign( x:ndarray, y:ndarray, \n  ...s:MultiSlice|Slice|null|undefined|integer|ArrayLike[, options:Object] )\n    Assigns element values from a broadcasted input ndarray to corresponding\n    elements in an output ndarray view.\n","ndsliceDimension":"\nndsliceDimension( x:ndarray, dim:integer, slice:Slice|integer|null|undefined[, \n  options:Object] )\n    Returns a read-only view of an input ndarray when sliced along a specified\n    dimension.\n","ndsliceDimensionFrom":"\nndsliceDimensionFrom( x:ndarray, dim:integer, start:integer[, options:Object] )\n    Returns a read-only shifted view of an input ndarray along a specified\n    dimension.\n","ndsliceDimensionTo":"\nndsliceDimensionTo( x:ndarray, dim:integer, stop:integer[, options:Object] )\n    Returns a read-only truncated view of an input ndarray along a specified\n    dimension.\n","ndsliceFrom":"\nndsliceFrom( x:ndarray, ...start:null|void|integer[, options:Object] )\n    Returns a read-only shifted view of an input ndarray.\n","ndsliceTo":"\nndsliceTo( x:ndarray, ...stop:null|void|integer[, options:Object] )\n    Returns a read-only truncated view of an input ndarray.\n","ndzeros":"\nndzeros( shape:ArrayLikeObject<integer>|integer[, options:Object] )\n    Returns a zero-filled ndarray having a specified shape and data type.\n","ndzerosLike":"\nndzerosLike( x:ndarray[, options:Object] )\n    Returns a zero-filled ndarray having the same shape and data type as a\n    provided input ndarray.\n","nextGraphemeClusterBreak":"\nnextGraphemeClusterBreak( str:string[, fromIndex:integer] )\n    Returns the next extended grapheme cluster break in a string after a\n    specified position.\n","nextTick":"\nnextTick( clbk[, ...args] )\n    Adds a callback to the \"next tick queue\".\n","NIGHTINGALES_ROSE":"\nNIGHTINGALES_ROSE()\n    Returns data for Nightingale's famous polar area diagram.\n","NINF":"\nNINF\n    Double-precision floating-point negative infinity.\n","NODE_VERSION":"\nNODE_VERSION\n    Node version.\n","none":"\nnone( collection:Array|TypedArray|Object )\n    Tests whether all elements in a collection are falsy.\n","noneBy":"\nnoneBy( collection:Array|TypedArray|Object, predicate:Function[, thisArg:any ] )\n    Tests whether all elements in a collection fail a test implemented by a\n    predicate function.\n","noneByAsync":"\nnoneByAsync( collection:Array|TypedArray|Object, [options:Object,] \n  predicate:Function, done:Function )\n    Tests whether all elements in a collection fail a test implemented by a\n    predicate function.\n","noneByAsync.factory":"\nnoneByAsync.factory( [options:Object,] predicate:Function )\n    Returns a function which tests whether all elements in a collection fail a\n    test implemented by a predicate function.\n","noneByRight":"\nnoneByRight( collection:Array|TypedArray|Object, predicate:Function[, \n  thisArg:any ] )\n    Tests whether all elements in a collection fail a test implemented by a\n    predicate function, iterating from right to left.\n","noneByRightAsync":"\nnoneByRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n  predicate:Function, done:Function )\n    Tests whether all elements in a collection fail a test implemented by a\n    predicate function, iterating from right to left.\n","noneByRightAsync.factory":"\nnoneByRightAsync.factory( [options:Object,] predicate:Function )\n    Returns a function which tests whether all elements in a collection fail a\n    test implemented by a predicate function, iterating from right to left.\n","noneInBy":"\nnoneInBy( object:Object, predicate:Function[, thisArg:any ] )\n    Tests whether every property in an object fails a test implemented by a\n    predicate function.\n","nonEnumerableProperties":"\nnonEnumerableProperties( value:any )\n    Returns an array of an object's own non-enumerable property names and\n    symbols.\n","nonEnumerablePropertiesIn":"\nnonEnumerablePropertiesIn( value:any )\n    Returns an array of an object's own and inherited non-enumerable property\n    names and symbols.\n","nonEnumerablePropertyNames":"\nnonEnumerablePropertyNames( value:any )\n    Returns an array of an object's own non-enumerable property names.\n","nonEnumerablePropertyNamesIn":"\nnonEnumerablePropertyNamesIn( value:any )\n    Returns an array of an object's own and inherited non-enumerable property\n    names.\n","nonEnumerablePropertySymbols":"\nnonEnumerablePropertySymbols( value:any )\n    Returns an array of an object's own non-enumerable symbol properties.\n","nonEnumerablePropertySymbolsIn":"\nnonEnumerablePropertySymbolsIn( value:any )\n    Returns an array of an object's own and inherited non-enumerable symbol\n    properties.\n","noneOwnBy":"\nnoneOwnBy( object:Object, predicate:Function[, thisArg:any ] )\n    Tests whether every own property of an object fails a test implemented\n    by a predicate function.\n","nonIndexKeys":"\nnonIndexKeys( obj:any )\n    Returns an array of an object's own enumerable property names which are not\n    integer indices.\n","noop":"\nnoop()\n    A function which does nothing.\n","now":"\nnow()\n    Returns the time in seconds since the epoch.\n","NUM_CPUS":"\nNUM_CPUS\n    Number of CPUs.\n","num2words":"\nnum2words( value:integer[, options:Object] )\n    Converts a number to a word representation.\n","Number":"\nNumber( value:number )\n    Returns a Number object.\n","numel":"\nnumel( x:ndarray )\n    Returns the number of elements in an ndarray.\n","numelDimension":"\nnumelDimension( x:ndarray, dim:integer )\n    Returns the size (i.e., number of elements) of a specified dimension for a\n    provided ndarray.\n","numGraphemeClusters":"\nnumGraphemeClusters( str:string )\n    Returns the number of grapheme clusters in a string.\n","Object":"\nObject( value:any )\n    Returns an object.\n","Object.assign":"\nObject.assign( target:Object, ...sources:Object )\n    Assigns enumerable and own properties from source objects to a target\n    object.\n","Object.create":"\nObject.create( prototype:Object, properties:Object )\n    Creates a new object with a specified prototype object and properties.\n","Object.defineProperties":"\nObject.defineProperties( obj:Object, properties:Object )\n    Defines properties for an object.\n","Object.defineProperty":"\nObject.defineProperty( obj:Object, key:string, descriptor:Object )\n    Defines a property for an object.\n","Object.entries":"\nObject.entries( obj:Object )\n    Returns an array of an object's own enumerable string-keyed property\n    [key, value] pairs.\n","Object.freeze":"\nObject.freeze( obj:Object )\n    Freezes an object.\n","Object.getOwnPropertyDescriptor":"\nObject.getOwnPropertyDescriptor( obj:Object, key:string )\n    Returns an object's own property descriptor.\n","Object.getOwnPropertyDescriptors":"\nObject.getOwnPropertyDescriptors( obj:Object )\n    Returns an object's own property descriptors.\n","Object.getOwnPropertyNames":"\nObject.getOwnPropertyNames( obj:Object )\n    Returns an array of an object's own enumerable and non-enumerable\n    property names.\n","Object.getOwnPropertySymbols":"\nObject.getOwnPropertySymbols( obj:Object )\n    Returns an array of an object's own enumerable and non-enumerable\n    symbol property names.\n","Object.getPrototypeOf":"\nObject.getPrototypeOf( obj:Object )\n    Returns an object's prototype.\n","Object.hasOwn":"\nObject.hasOwn( obj:Object, p:string )\n    Returns a boolean indicating whether an object has a property with the\n    specified name.\n","Object.is":"\nObject.is( value1:any, value2:any )\n    Returns a boolean indicating whether two values are the same value.\n","Object.isExtensible":"\nObject.isExtensible( obj:Object )\n    Returns a boolean indicating whether an object is extensible.\n","Object.isFrozen":"\nObject.isFrozen( obj:Object )\n    Returns a boolean indicating whether an object is frozen.\n","Object.isSealed":"\nObject.isSealed( obj:Object )\n    Returns a boolean indicating whether an object is sealed.\n","Object.keys":"\nObject.keys( obj:Object )\n    Returns an array of an object's own enumerable string-keyed property\n    names.\n","Object.preventExtensions":"\nObject.preventExtensions( obj:Object )\n    Prevents the addition of new properties to an object.\n","Object.seal":"\nObject.seal( obj:Object )\n    Prevents the addition of new properties to an object and marks all\n    existing properties as non-configurable.\n","Object.setPrototypeOf":"\nObject.setPrototypeOf( obj:Object, proto:Object )\n    Sets an object's prototype.\n","Object.values":"\nObject.values( obj:Object )\n    Returns an array of an object's own enumerable property values.\n","Object.prototype.toLocaleString":"\nObject.prototype.toLocaleString()\n    Returns a string representing the object.\n","Object.prototype.toString":"\nObject.prototype.toString()\n    Returns a string representing the object.\n","Object.prototype.valueOf":"\nObject.prototype.valueOf()\n    Returns the primitive value of the object.\n","Object.prototype.hasOwnProperty":"\nObject.prototype.hasOwnProperty( p:string )\n    Returns a boolean indicating whether an object has a property with the\n    specified name.\n","Object.prototype.isPrototypeOf":"\nObject.prototype.isPrototypeOf( obj:Object )\n    Returns a boolean indicating whether an object exists in another object's\n    prototype chain.\n","Object.prototype.propertyIsEnumerable":"\nObject.prototype.propertyIsEnumerable( p:string )\n    Returns a boolean indicating whether an object's property is enumerable.\n","Object.prototype.constructor":"\nObject.prototype.constructor\n    Property whose value is a reference to the constructor function that\n    created the instance object.\n","objectEntries":"\nobjectEntries( obj:ObjectLike )\n    Returns an array of an object's own enumerable property `[key, value]`\n    pairs.\n","objectEntriesIn":"\nobjectEntriesIn( obj:ObjectLike )\n    Returns an array of an object's own and inherited enumerable property\n    `[key, value]` pairs.\n","objectFromEntries":"\nobjectFromEntries( entries:Array<Array> )\n    Creates an object from an array of key-value pairs.\n","objectInverse":"\nobjectInverse( obj:ObjectLike[, options:Object] )\n    Inverts an object, such that keys become values and values become keys.\n","objectInverseBy":"\nobjectInverseBy( obj:ObjectLike, [options:Object,] transform:Function )\n    Inverts an object, such that keys become values and values become keys,\n    according to a transform function.\n","objectKeys":"\nobjectKeys( value:any )\n    Returns an array of an object's own enumerable property names.\n","objectValues":"\nobjectValues( obj:ObjectLike )\n    Returns an array of an object's own enumerable property values.\n","objectValuesIn":"\nobjectValuesIn( obj:ObjectLike )\n    Returns an array of an object's own and inherited enumerable property\n    values.\n","omit":"\nomit( obj:Object, keys:string|Array )\n    Returns a partial object copy excluding specified keys.\n","omitBy":"\nomitBy( obj:Object, predicate:Function )\n    Returns a partial object copy excluding properties for which a predicate\n    returns a truthy value.\n","open":"\nopen( path:string|Buffer[, flags:string|number[, mode:integer]], clbk:Function )\n    Asynchronously opens a file.\n","open.sync":"\nopen.sync( path:string|Buffer[, flags:string|number[, mode:integer]] )\n    Synchronously opens a file.\n","openURL":"\nopenURL( url:string )\n    Opens a URL in a user's default browser.\n","ordinalize":"\nordinalize( value:string|integer[, options:Object] )\n    Converts an integer to an ordinal string (e.g., `1st`, `2nd`, etc.).\n","PACE_BOSTON_HOUSE_PRICES":"\nPACE_BOSTON_HOUSE_PRICES()\n    Returns a (corrected) dataset derived from information collected by the US\n    Census Service concerning housing in Boston, Massachusetts (1978).\n","pad":"\npad( str:string, len:integer[, options:Object] )\n    Pads a `string` such that the padded `string` has length `len`.\n","padjust":"\npadjust( pvals:Array<number>, method:string[, comparisons:integer] )\n    Adjusts supplied p-values for multiple comparisons via a specified method.\n","papply":"\npapply( fcn:Function, ...args:any )\n    Returns a function of smaller arity by partially applying arguments.\n","papplyRight":"\npapplyRight( fcn:Function, ...args:any )\n    Returns a function of smaller arity by partially applying arguments from the\n    right.\n","parallel":"\nparallel( files:Array<string>, [options:Object,] clbk:Function )\n    Executes scripts in parallel.\n","parseJSON":"\nparseJSON( str:string[, reviver:Function] )\n    Attempts to parse a string as JSON.\n","pascalcase":"\npascalcase( str:string )\n    Converts a string to Pascal case.\n","PATH_DELIMITER":"\nPATH_DELIMITER\n    Platform-specific path delimiter.\n","PATH_DELIMITER_POSIX":"\nPATH_DELIMITER_POSIX\n    POSIX path delimiter.\n","PATH_DELIMITER_WIN32":"\nPATH_DELIMITER_WIN32\n    Windows path delimiter.\n","PATH_SEP":"\nPATH_SEP\n    Platform-specific path segment separator.\n","PATH_SEP_POSIX":"\nPATH_SEP_POSIX\n    POSIX path segment separator.\n","PATH_SEP_WIN32":"\nPATH_SEP_WIN32\n    Windows path segment separator.\n","pcorrtest":"\npcorrtest( x:Array<number>, y:Array<number>[, options:Object] )\n    Computes a Pearson product-moment correlation test between paired samples.\n","percentEncode":"\npercentEncode( str:string )\n    Percent-encodes a UTF-16 encoded string according to RFC 3986.\n","PHI":"\nPHI\n    Golden ratio.\n","PI":"\nPI\n    The mathematical constant `π`.\n","PI_SQUARED":"\nPI_SQUARED\n    Square of the mathematical constant `π`.\n","pick":"\npick( obj:Object, keys:string|Array )\n    Returns a partial object copy containing only specified keys.\n","pickArguments":"\npickArguments( fcn:Function, indices:Array<integer>[, thisArg:any] )\n    Returns a function that applies specified arguments to a provided function.\n","pickBy":"\npickBy( obj:Object, predicate:Function )\n    Returns a partial object copy containing properties for which a predicate\n    returns a truthy value.\n","PINF":"\nPINF\n    Double-precision floating-point positive infinity.\n","pkg2alias":"\npkg2alias( pkg:string )\n    Returns the alias associated with a specified package name.\n","pkg2related":"\npkg2related( pkg:string )\n    Returns package names related to a specified package name.\n","pkg2standalone":"\npkg2standalone( pkg:string )\n    Returns the standalone package name associated with a provided internal\n    package name.\n","PLATFORM":"\nPLATFORM\n    Platform on which the current process is running.\n","plot":"\nplot( [x:Array|Array, y:Array|Array,] [options:Object] )\n    Returns a plot instance for creating 2-dimensional plots.\n","Plot":"\nPlot( [x:Array|Array, y:Array|Array,] [options:Object] )\n    Returns a plot instance for creating 2-dimensional plots.\n","pluck":"\npluck( arr:Array, prop:string[, options:Object] )\n    Extracts a property value from each element of an object array.\n","pop":"\npop( collection:Array|TypedArray|Object )\n    Removes and returns the last element of a collection.\n","porterStemmer":"\nporterStemmer( word:string )\n    Extracts the stem of a given word.\n","prepend":"\nprepend( collection1:Array|TypedArray|Object, \n  collection2:Array|TypedArray|Object )\n    Adds the elements of one collection to the beginning of another collection.\n","prevGraphemeClusterBreak":"\nprevGraphemeClusterBreak( str:string[, fromIndex:integer] )\n    Returns the previous extended grapheme cluster break in a string before a\n    specified position.\n","PRIMES_100K":"\nPRIMES_100K()\n    Returns an array containing the first 100,000 prime numbers.\n","properties":"\nproperties( value:any )\n    Returns an array of an object's own enumerable and non-enumerable property\n    names and symbols.\n","propertiesIn":"\npropertiesIn( value:any )\n    Returns an array of an object's own and inherited property names and\n    symbols.\n","propertyDescriptor":"\npropertyDescriptor( value:any, property:string|symbol )\n    Returns a property descriptor for an object's own property.\n","propertyDescriptorIn":"\npropertyDescriptorIn( value:any, property:string|symbol )\n    Returns a property descriptor for an object's own or inherited property.\n","propertyDescriptors":"\npropertyDescriptors( value:any )\n    Returns an object's own property descriptors.\n","propertyDescriptorsIn":"\npropertyDescriptorsIn( value:any )\n    Returns an object's own and inherited property descriptors.\n","propertyNames":"\npropertyNames( value:any )\n    Returns an array of an object's own enumerable and non-enumerable property\n    names.\n","propertyNamesIn":"\npropertyNamesIn( value:any )\n    Returns an array of an object's own and inherited enumerable and non-\n    enumerable property names.\n","propertySymbols":"\npropertySymbols( value:any )\n    Returns an array of an object's own symbol properties.\n","propertySymbolsIn":"\npropertySymbolsIn( value:any )\n    Returns an array of an object's own and inherited symbol properties.\n","Proxy":"\nProxy( target:Object, handlers:Object )\n    Returns a proxy object implementing custom behavior for specified object\n    operations.\n","Proxy.revocable":"\nProxy.revocable( target:Object, handlers:Object )\n    Returns a revocable proxy object.\n","push":"\npush( collection:Array|TypedArray|Object, ...items:any )\n    Adds one or more elements to the end of a collection.\n","quarterOfYear":"\nquarterOfYear( [month:integer|string|Date] )\n    Returns the quarter of the year.\n","random.array.arcsine":"\nrandom.array.arcsine( len:integer, a:number, b:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from an arcsine\n    distribution.\n","random.array.arcsine.assign":"\nrandom.array.arcsine.assign( a:number, b:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from an arcsine distribution.\n","random.array.arcsine.factory":"\nrandom.array.arcsine.factory( [a:number, b:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an arcsine distribution.\n","random.array.arcsine.PRNG":"\nrandom.array.arcsine.PRNG\n    Underlying pseudorandom number generator.\n","random.array.arcsine.seed":"\nrandom.array.arcsine.seed\n    Pseudorandom number generator seed.\n","random.array.arcsine.seedLength":"\nrandom.array.arcsine.seedLength\n    Length of generator seed.\n","random.array.arcsine.state":"\nrandom.array.arcsine.state\n    Generator state.\n","random.array.arcsine.stateLength":"\nrandom.array.arcsine.stateLength\n    Length of generator state.\n","random.array.arcsine.byteLength":"\nrandom.array.arcsine.byteLength\n    Size (in bytes) of generator state.\n","random.array.bernoulli":"\nrandom.array.bernoulli( len:integer, p:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a Bernoulli\n    distribution.\n","random.array.bernoulli.assign":"\nrandom.array.bernoulli.assign( p:number, out:Array|TypedArray )\n    Fills an array with pseudorandom numbers drawn from a Bernoulli\n    distribution.\n","random.array.bernoulli.factory":"\nrandom.array.bernoulli.factory( [p:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Bernoulli distribution.\n","random.array.bernoulli.PRNG":"\nrandom.array.bernoulli.PRNG\n    Underlying pseudorandom number generator.\n","random.array.bernoulli.seed":"\nrandom.array.bernoulli.seed\n    Pseudorandom number generator seed.\n","random.array.bernoulli.seedLength":"\nrandom.array.bernoulli.seedLength\n    Length of generator seed.\n","random.array.bernoulli.state":"\nrandom.array.bernoulli.state\n    Generator state.\n","random.array.bernoulli.stateLength":"\nrandom.array.bernoulli.stateLength\n    Length of generator state.\n","random.array.bernoulli.byteLength":"\nrandom.array.bernoulli.byteLength\n    Size (in bytes) of generator state.\n","random.array.beta":"\nrandom.array.beta( len:integer, alpha:number, beta:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a beta\n    distribution.\n","random.array.beta.assign":"\nrandom.array.beta.assign( alpha:number, beta:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a beta distribution.\n","random.array.beta.factory":"\nrandom.array.beta.factory( [alpha:number, beta:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a beta distribution.\n","random.array.beta.PRNG":"\nrandom.array.beta.PRNG\n    Underlying pseudorandom number generator.\n","random.array.beta.seed":"\nrandom.array.beta.seed\n    Pseudorandom number generator seed.\n","random.array.beta.seedLength":"\nrandom.array.beta.seedLength\n    Length of generator seed.\n","random.array.beta.state":"\nrandom.array.beta.state\n    Generator state.\n","random.array.beta.stateLength":"\nrandom.array.beta.stateLength\n    Length of generator state.\n","random.array.beta.byteLength":"\nrandom.array.beta.byteLength\n    Size (in bytes) of generator state.\n","random.array.betaprime":"\nrandom.array.betaprime( len:integer, alpha:number, beta:number[, \n  options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a beta prime\n    distribution.\n","random.array.betaprime.assign":"\nrandom.array.betaprime.assign( alpha:number, beta:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a beta prime\n    distribution.\n","random.array.betaprime.factory":"\nrandom.array.betaprime.factory( [alpha:number, beta:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a beta prime distribution.\n","random.array.betaprime.PRNG":"\nrandom.array.betaprime.PRNG\n    Underlying pseudorandom number generator.\n","random.array.betaprime.seed":"\nrandom.array.betaprime.seed\n    Pseudorandom number generator seed.\n","random.array.betaprime.seedLength":"\nrandom.array.betaprime.seedLength\n    Length of generator seed.\n","random.array.betaprime.state":"\nrandom.array.betaprime.state\n    Generator state.\n","random.array.betaprime.stateLength":"\nrandom.array.betaprime.stateLength\n    Length of generator state.\n","random.array.betaprime.byteLength":"\nrandom.array.betaprime.byteLength\n    Size (in bytes) of generator state.\n","random.array.binomial":"\nrandom.array.binomial( len:integer, n:number, p:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a binomial\n    distribution.\n","random.array.binomial.assign":"\nrandom.array.binomial.assign( n:number, p:number, out:Array|TypedArray )\n    Fills an array with pseudorandom numbers drawn from a binomial distribution.\n","random.array.binomial.factory":"\nrandom.array.binomial.factory( [n:number, p:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a binomial distribution.\n","random.array.binomial.PRNG":"\nrandom.array.binomial.PRNG\n    Underlying pseudorandom number generator.\n","random.array.binomial.seed":"\nrandom.array.binomial.seed\n    Pseudorandom number generator seed.\n","random.array.binomial.seedLength":"\nrandom.array.binomial.seedLength\n    Length of generator seed.\n","random.array.binomial.state":"\nrandom.array.binomial.state\n    Generator state.\n","random.array.binomial.stateLength":"\nrandom.array.binomial.stateLength\n    Length of generator state.\n","random.array.binomial.byteLength":"\nrandom.array.binomial.byteLength\n    Size (in bytes) of generator state.\n","random.array.cauchy":"\nrandom.array.cauchy( len:integer, x0:number, gamma:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a Cauchy\n    distribution.\n","random.array.cauchy.assign":"\nrandom.array.cauchy.assign( x0:number, gamma:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a Cauchy distribution.\n","random.array.cauchy.factory":"\nrandom.array.cauchy.factory( [x0:number, gamma:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Cauchy distribution.\n","random.array.cauchy.PRNG":"\nrandom.array.cauchy.PRNG\n    Underlying pseudorandom number generator.\n","random.array.cauchy.seed":"\nrandom.array.cauchy.seed\n    Pseudorandom number generator seed.\n","random.array.cauchy.seedLength":"\nrandom.array.cauchy.seedLength\n    Length of generator seed.\n","random.array.cauchy.state":"\nrandom.array.cauchy.state\n    Generator state.\n","random.array.cauchy.stateLength":"\nrandom.array.cauchy.stateLength\n    Length of generator state.\n","random.array.cauchy.byteLength":"\nrandom.array.cauchy.byteLength\n    Size (in bytes) of generator state.\n","random.array.chi":"\nrandom.array.chi( len:integer, k:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a chi\n    distribution.\n","random.array.chi.assign":"\nrandom.array.chi.assign( k:number, out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a chi distribution.\n","random.array.chi.factory":"\nrandom.array.chi.factory( [k:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a chi distribution.\n","random.array.chi.PRNG":"\nrandom.array.chi.PRNG\n    Underlying pseudorandom number generator.\n","random.array.chi.seed":"\nrandom.array.chi.seed\n    Pseudorandom number generator seed.\n","random.array.chi.seedLength":"\nrandom.array.chi.seedLength\n    Length of generator seed.\n","random.array.chi.state":"\nrandom.array.chi.state\n    Generator state.\n","random.array.chi.stateLength":"\nrandom.array.chi.stateLength\n    Length of generator state.\n","random.array.chi.byteLength":"\nrandom.array.chi.byteLength\n    Size (in bytes) of generator state.\n","random.array.chisquare":"\nrandom.array.chisquare( len:integer, k:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a chi-square\n    distribution.\n","random.array.chisquare.assign":"\nrandom.array.chisquare.assign( k:number, out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a chi-square\n    distribution.\n","random.array.chisquare.factory":"\nrandom.array.chisquare.factory( [k:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a chi-square distribution.\n","random.array.chisquare.PRNG":"\nrandom.array.chisquare.PRNG\n    Underlying pseudorandom number generator.\n","random.array.chisquare.seed":"\nrandom.array.chisquare.seed\n    Pseudorandom number generator seed.\n","random.array.chisquare.seedLength":"\nrandom.array.chisquare.seedLength\n    Length of generator seed.\n","random.array.chisquare.state":"\nrandom.array.chisquare.state\n    Generator state.\n","random.array.chisquare.stateLength":"\nrandom.array.chisquare.stateLength\n    Length of generator state.\n","random.array.chisquare.byteLength":"\nrandom.array.chisquare.byteLength\n    Size (in bytes) of generator state.\n","random.array.cosine":"\nrandom.array.cosine( len:integer, mu:number, s:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a raised cosine\n    distribution.\n","random.array.cosine.assign":"\nrandom.array.cosine.assign( mu:number, s:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a raised cosine\n    distribution.\n","random.array.cosine.factory":"\nrandom.array.cosine.factory( [mu:number, s:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a raised cosine distribution.\n","random.array.cosine.PRNG":"\nrandom.array.cosine.PRNG\n    Underlying pseudorandom number generator.\n","random.array.cosine.seed":"\nrandom.array.cosine.seed\n    Pseudorandom number generator seed.\n","random.array.cosine.seedLength":"\nrandom.array.cosine.seedLength\n    Length of generator seed.\n","random.array.cosine.state":"\nrandom.array.cosine.state\n    Generator state.\n","random.array.cosine.stateLength":"\nrandom.array.cosine.stateLength\n    Length of generator state.\n","random.array.cosine.byteLength":"\nrandom.array.cosine.byteLength\n    Size (in bytes) of generator state.\n","random.array.discreteUniform":"\nrandom.array.discreteUniform( len:integer, a:number, b:number[, \n  options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a discrete\n    uniform distribution.\n","random.array.discreteUniform.assign":"\nrandom.array.discreteUniform.assign( a:number, b:number, out:Array|TypedArray )\n    Fills an array with pseudorandom numbers drawn from a discrete uniform\n    distribution.\n","random.array.discreteUniform.factory":"\nrandom.array.discreteUniform.factory( [a:number, b:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a discrete uniform distribution.\n","random.array.discreteUniform.PRNG":"\nrandom.array.discreteUniform.PRNG\n    Underlying pseudorandom number generator.\n","random.array.discreteUniform.seed":"\nrandom.array.discreteUniform.seed\n    Pseudorandom number generator seed.\n","random.array.discreteUniform.seedLength":"\nrandom.array.discreteUniform.seedLength\n    Length of generator seed.\n","random.array.discreteUniform.state":"\nrandom.array.discreteUniform.state\n    Generator state.\n","random.array.discreteUniform.stateLength":"\nrandom.array.discreteUniform.stateLength\n    Length of generator state.\n","random.array.discreteUniform.byteLength":"\nrandom.array.discreteUniform.byteLength\n    Size (in bytes) of generator state.\n","random.array.erlang":"\nrandom.array.erlang( len:integer, k:number, lambda:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from an Erlang\n    distribution.\n","random.array.erlang.assign":"\nrandom.array.erlang.assign( k:number, lambda:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from an Erlang distribution.\n","random.array.erlang.factory":"\nrandom.array.erlang.factory( [k:number, lambda:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an Erlang distribution.\n","random.array.erlang.PRNG":"\nrandom.array.erlang.PRNG\n    Underlying pseudorandom number generator.\n","random.array.erlang.seed":"\nrandom.array.erlang.seed\n    Pseudorandom number generator seed.\n","random.array.erlang.seedLength":"\nrandom.array.erlang.seedLength\n    Length of generator seed.\n","random.array.erlang.state":"\nrandom.array.erlang.state\n    Generator state.\n","random.array.erlang.stateLength":"\nrandom.array.erlang.stateLength\n    Length of generator state.\n","random.array.erlang.byteLength":"\nrandom.array.erlang.byteLength\n    Size (in bytes) of generator state.\n","random.array.exponential":"\nrandom.array.exponential( len:integer, lambda:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from an exponential\n    distribution.\n","random.array.exponential.assign":"\nrandom.array.exponential.assign( lambda:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from an exponential\n    distribution.\n","random.array.exponential.factory":"\nrandom.array.exponential.factory( [lambda:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an exponential distribution.\n","random.array.exponential.PRNG":"\nrandom.array.exponential.PRNG\n    Underlying pseudorandom number generator.\n","random.array.exponential.seed":"\nrandom.array.exponential.seed\n    Pseudorandom number generator seed.\n","random.array.exponential.seedLength":"\nrandom.array.exponential.seedLength\n    Length of generator seed.\n","random.array.exponential.state":"\nrandom.array.exponential.state\n    Generator state.\n","random.array.exponential.stateLength":"\nrandom.array.exponential.stateLength\n    Length of generator state.\n","random.array.exponential.byteLength":"\nrandom.array.exponential.byteLength\n    Size (in bytes) of generator state.\n","random.array.f":"\nrandom.array.f( len:integer, d1:number, d2:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from an F\n    distribution.\n","random.array.f.assign":"\nrandom.array.f.assign( d1:number, d2:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from an F distribution.\n","random.array.f.factory":"\nrandom.array.f.factory( [d1:number, d2:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an F distribution.\n","random.array.f.PRNG":"\nrandom.array.f.PRNG\n    Underlying pseudorandom number generator.\n","random.array.f.seed":"\nrandom.array.f.seed\n    Pseudorandom number generator seed.\n","random.array.f.seedLength":"\nrandom.array.f.seedLength\n    Length of generator seed.\n","random.array.f.state":"\nrandom.array.f.state\n    Generator state.\n","random.array.f.stateLength":"\nrandom.array.f.stateLength\n    Length of generator state.\n","random.array.f.byteLength":"\nrandom.array.f.byteLength\n    Size (in bytes) of generator state.\n","random.array.frechet":"\nrandom.array.frechet( len:integer, alpha:number, s:number, m:number[, \n  options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a Fréchet\n    distribution.\n","random.array.frechet.assign":"\nrandom.array.frechet.assign( alpha:number, s:number, m:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a Fréchet distribution.\n","random.array.frechet.factory":"\nrandom.array.frechet.factory( [alpha:number, s:number, m:number, ]\n  [options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Fréchet distribution.\n","random.array.frechet.PRNG":"\nrandom.array.frechet.PRNG\n    Underlying pseudorandom number generator.\n","random.array.frechet.seed":"\nrandom.array.frechet.seed\n    Pseudorandom number generator seed.\n","random.array.frechet.seedLength":"\nrandom.array.frechet.seedLength\n    Length of generator seed.\n","random.array.frechet.state":"\nrandom.array.frechet.state\n    Generator state.\n","random.array.frechet.stateLength":"\nrandom.array.frechet.stateLength\n    Length of generator state.\n","random.array.frechet.byteLength":"\nrandom.array.frechet.byteLength\n    Size (in bytes) of generator state.\n","random.array.gamma":"\nrandom.array.gamma( len:integer, alpha:number, beta:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a gamma\n    distribution.\n","random.array.gamma.assign":"\nrandom.array.gamma.assign( alpha:number, beta:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a gamma distribution.\n","random.array.gamma.factory":"\nrandom.array.gamma.factory( [alpha:number, beta:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a gamma distribution.\n","random.array.gamma.PRNG":"\nrandom.array.gamma.PRNG\n    Underlying pseudorandom number generator.\n","random.array.gamma.seed":"\nrandom.array.gamma.seed\n    Pseudorandom number generator seed.\n","random.array.gamma.seedLength":"\nrandom.array.gamma.seedLength\n    Length of generator seed.\n","random.array.gamma.state":"\nrandom.array.gamma.state\n    Generator state.\n","random.array.gamma.stateLength":"\nrandom.array.gamma.stateLength\n    Length of generator state.\n","random.array.gamma.byteLength":"\nrandom.array.gamma.byteLength\n    Size (in bytes) of generator state.\n","random.array.geometric":"\nrandom.array.geometric( len:integer, p:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a geometric\n    distribution.\n","random.array.geometric.assign":"\nrandom.array.geometric.assign( p:number, out:Array|TypedArray )\n    Fills an array with pseudorandom numbers drawn from a geometric\n    distribution.\n","random.array.geometric.factory":"\nrandom.array.geometric.factory( [p:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a geometric distribution.\n","random.array.geometric.PRNG":"\nrandom.array.geometric.PRNG\n    Underlying pseudorandom number generator.\n","random.array.geometric.seed":"\nrandom.array.geometric.seed\n    Pseudorandom number generator seed.\n","random.array.geometric.seedLength":"\nrandom.array.geometric.seedLength\n    Length of generator seed.\n","random.array.geometric.state":"\nrandom.array.geometric.state\n    Generator state.\n","random.array.geometric.stateLength":"\nrandom.array.geometric.stateLength\n    Length of generator state.\n","random.array.geometric.byteLength":"\nrandom.array.geometric.byteLength\n    Size (in bytes) of generator state.\n","random.array.gumbel":"\nrandom.array.gumbel( len:integer, mu:number, beta:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a Gumbel\n    distribution.\n","random.array.gumbel.assign":"\nrandom.array.gumbel.assign( mu:number, beta:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a Gumbel distribution.\n","random.array.gumbel.factory":"\nrandom.array.gumbel.factory( [mu:number, beta:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Gumbel distribution.\n","random.array.gumbel.PRNG":"\nrandom.array.gumbel.PRNG\n    Underlying pseudorandom number generator.\n","random.array.gumbel.seed":"\nrandom.array.gumbel.seed\n    Pseudorandom number generator seed.\n","random.array.gumbel.seedLength":"\nrandom.array.gumbel.seedLength\n    Length of generator seed.\n","random.array.gumbel.state":"\nrandom.array.gumbel.state\n    Generator state.\n","random.array.gumbel.stateLength":"\nrandom.array.gumbel.stateLength\n    Length of generator state.\n","random.array.gumbel.byteLength":"\nrandom.array.gumbel.byteLength\n    Size (in bytes) of generator state.\n","random.array.hypergeometric":"\nrandom.array.hypergeometric( len:integer, N:number, K:number, n:number[, \n  options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a hypergeometric\n    distribution.\n","random.array.hypergeometric.assign":"\nrandom.array.hypergeometric.assign( N:number, K:number, n:number, \n  out:Array|TypedArray )\n    Fills an array with pseudorandom numbers drawn from a hypergeometric\n    distribution.\n","random.array.hypergeometric.factory":"\nrandom.array.hypergeometric.factory( [N:number, K:number, n:number, ]\n  [options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a hypergeometric distribution.\n","random.array.hypergeometric.PRNG":"\nrandom.array.hypergeometric.PRNG\n    Underlying pseudorandom number generator.\n","random.array.hypergeometric.seed":"\nrandom.array.hypergeometric.seed\n    Pseudorandom number generator seed.\n","random.array.hypergeometric.seedLength":"\nrandom.array.hypergeometric.seedLength\n    Length of generator seed.\n","random.array.hypergeometric.state":"\nrandom.array.hypergeometric.state\n    Generator state.\n","random.array.hypergeometric.stateLength":"\nrandom.array.hypergeometric.stateLength\n    Length of generator state.\n","random.array.hypergeometric.byteLength":"\nrandom.array.hypergeometric.byteLength\n    Size (in bytes) of generator state.\n","random.array.invgamma":"\nrandom.array.invgamma( len:integer, alpha:number, beta:number[, \n  options:Object] )\n    Returns an array containing pseudorandom numbers drawn from an inverse gamma\n    distribution.\n","random.array.invgamma.assign":"\nrandom.array.invgamma.assign( alpha:number, beta:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from an inverse gamma\n    distribution.\n","random.array.invgamma.factory":"\nrandom.array.invgamma.factory( [alpha:number, beta:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an inverse gamma distribution.\n","random.array.invgamma.PRNG":"\nrandom.array.invgamma.PRNG\n    Underlying pseudorandom number generator.\n","random.array.invgamma.seed":"\nrandom.array.invgamma.seed\n    Pseudorandom number generator seed.\n","random.array.invgamma.seedLength":"\nrandom.array.invgamma.seedLength\n    Length of generator seed.\n","random.array.invgamma.state":"\nrandom.array.invgamma.state\n    Generator state.\n","random.array.invgamma.stateLength":"\nrandom.array.invgamma.stateLength\n    Length of generator state.\n","random.array.invgamma.byteLength":"\nrandom.array.invgamma.byteLength\n    Size (in bytes) of generator state.\n","random.array.kumaraswamy":"\nrandom.array.kumaraswamy( len:integer, a:number, b:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from Kumaraswamy's\n    double bounded distribution.\n","random.array.kumaraswamy.assign":"\nrandom.array.kumaraswamy.assign( a:number, b:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from Kumaraswamy's double\n    bounded distribution.\n","random.array.kumaraswamy.factory":"\nrandom.array.kumaraswamy.factory( [a:number, b:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from Kumaraswamy's double bounded distribution.\n","random.array.kumaraswamy.PRNG":"\nrandom.array.kumaraswamy.PRNG\n    Underlying pseudorandom number generator.\n","random.array.kumaraswamy.seed":"\nrandom.array.kumaraswamy.seed\n    Pseudorandom number generator seed.\n","random.array.kumaraswamy.seedLength":"\nrandom.array.kumaraswamy.seedLength\n    Length of generator seed.\n","random.array.kumaraswamy.state":"\nrandom.array.kumaraswamy.state\n    Generator state.\n","random.array.kumaraswamy.stateLength":"\nrandom.array.kumaraswamy.stateLength\n    Length of generator state.\n","random.array.kumaraswamy.byteLength":"\nrandom.array.kumaraswamy.byteLength\n    Size (in bytes) of generator state.\n","random.array.laplace":"\nrandom.array.laplace( len:integer, mu:number, b:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a Laplace\n    (double exponential) distribution.\n","random.array.laplace.assign":"\nrandom.array.laplace.assign( mu:number, b:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a Laplace (double\n    exponential) distribution.\n","random.array.laplace.factory":"\nrandom.array.laplace.factory( [mu:number, b:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Laplace (double exponential) distribution.\n","random.array.laplace.PRNG":"\nrandom.array.laplace.PRNG\n    Underlying pseudorandom number generator.\n","random.array.laplace.seed":"\nrandom.array.laplace.seed\n    Pseudorandom number generator seed.\n","random.array.laplace.seedLength":"\nrandom.array.laplace.seedLength\n    Length of generator seed.\n","random.array.laplace.state":"\nrandom.array.laplace.state\n    Generator state.\n","random.array.laplace.stateLength":"\nrandom.array.laplace.stateLength\n    Length of generator state.\n","random.array.laplace.byteLength":"\nrandom.array.laplace.byteLength\n    Size (in bytes) of generator state.\n","random.array.levy":"\nrandom.array.levy( len:integer, mu:number, c:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a Lévy\n    distribution.\n","random.array.levy.assign":"\nrandom.array.levy.assign( mu:number, c:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a Lévy distribution.\n","random.array.levy.factory":"\nrandom.array.levy.factory( [mu:number, c:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Lévy distribution.\n","random.array.levy.PRNG":"\nrandom.array.levy.PRNG\n    Underlying pseudorandom number generator.\n","random.array.levy.seed":"\nrandom.array.levy.seed\n    Pseudorandom number generator seed.\n","random.array.levy.seedLength":"\nrandom.array.levy.seedLength\n    Length of generator seed.\n","random.array.levy.state":"\nrandom.array.levy.state\n    Generator state.\n","random.array.levy.stateLength":"\nrandom.array.levy.stateLength\n    Length of generator state.\n","random.array.levy.byteLength":"\nrandom.array.levy.byteLength\n    Size (in bytes) of generator state.\n","random.array.logistic":"\nrandom.array.logistic( len:integer, mu:number, s:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a logistic\n    distribution.\n","random.array.logistic.assign":"\nrandom.array.logistic.assign( mu:number, s:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a logistic distribution.\n","random.array.logistic.factory":"\nrandom.array.logistic.factory( [mu:number, s:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a logistic distribution.\n","random.array.logistic.PRNG":"\nrandom.array.logistic.PRNG\n    Underlying pseudorandom number generator.\n","random.array.logistic.seed":"\nrandom.array.logistic.seed\n    Pseudorandom number generator seed.\n","random.array.logistic.seedLength":"\nrandom.array.logistic.seedLength\n    Length of generator seed.\n","random.array.logistic.state":"\nrandom.array.logistic.state\n    Generator state.\n","random.array.logistic.stateLength":"\nrandom.array.logistic.stateLength\n    Length of generator state.\n","random.array.logistic.byteLength":"\nrandom.array.logistic.byteLength\n    Size (in bytes) of generator state.\n","random.array.lognormal":"\nrandom.array.lognormal( len:integer, mu:number, sigma:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a lognormal\n    distribution.\n","random.array.lognormal.assign":"\nrandom.array.lognormal.assign( mu:number, sigma:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a lognormal\n    distribution.\n","random.array.lognormal.factory":"\nrandom.array.lognormal.factory( [mu:number, sigma:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a lognormal distribution.\n","random.array.lognormal.PRNG":"\nrandom.array.lognormal.PRNG\n    Underlying pseudorandom number generator.\n","random.array.lognormal.seed":"\nrandom.array.lognormal.seed\n    Pseudorandom number generator seed.\n","random.array.lognormal.seedLength":"\nrandom.array.lognormal.seedLength\n    Length of generator seed.\n","random.array.lognormal.state":"\nrandom.array.lognormal.state\n    Generator state.\n","random.array.lognormal.stateLength":"\nrandom.array.lognormal.stateLength\n    Length of generator state.\n","random.array.lognormal.byteLength":"\nrandom.array.lognormal.byteLength\n    Size (in bytes) of generator state.\n","random.array.minstd":"\nrandom.array.minstd( len:integer[, options:Object] )\n    Returns an array containing pseudorandom integers on the interval\n    `[1, 2147483646]`.\n","random.array.minstd.normalized":"\nrandom.array.minstd.normalized( len:integer[, options:Object] )\n    Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n","random.array.minstd.factory":"\nrandom.array.minstd.factory( [options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers\n    generated using a linear congruential pseudorandom number generator (LCG).\n","random.array.minstd.PRNG":"\nrandom.array.minstd.PRNG\n    Underlying pseudorandom number generator.\n","random.array.minstd.seed":"\nrandom.array.minstd.seed\n    Pseudorandom number generator seed.\n","random.array.minstd.seedLength":"\nrandom.array.minstd.seedLength\n    Length of generator seed.\n","random.array.minstd.state":"\nrandom.array.minstd.state\n    Generator state.\n","random.array.minstd.stateLength":"\nrandom.array.minstd.stateLength\n    Length of generator state.\n","random.array.minstd.byteLength":"\nrandom.array.minstd.byteLength\n    Size (in bytes) of generator state.\n","random.array.minstdShuffle":"\nrandom.array.minstdShuffle( len:integer[, options:Object] )\n    Returns an array containing pseudorandom integers on the interval\n    `[1, 2147483646]`.\n","random.array.minstdShuffle.normalized":"\nrandom.array.minstdShuffle.normalized( len:integer[, options:Object] )\n    Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n","random.array.minstdShuffle.factory":"\nrandom.array.minstdShuffle.factory( [options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers\n    generated using a linear congruential pseudorandom number generator (LCG)\n    whose output is shuffled.\n","random.array.minstdShuffle.PRNG":"\nrandom.array.minstdShuffle.PRNG\n    Underlying pseudorandom number generator.\n","random.array.minstdShuffle.seed":"\nrandom.array.minstdShuffle.seed\n    Pseudorandom number generator seed.\n","random.array.minstdShuffle.seedLength":"\nrandom.array.minstdShuffle.seedLength\n    Length of generator seed.\n","random.array.minstdShuffle.state":"\nrandom.array.minstdShuffle.state\n    Generator state.\n","random.array.minstdShuffle.stateLength":"\nrandom.array.minstdShuffle.stateLength\n    Length of generator state.\n","random.array.minstdShuffle.byteLength":"\nrandom.array.minstdShuffle.byteLength\n    Size (in bytes) of generator state.\n","random.array.mt19937":"\nrandom.array.mt19937( len:integer[, options:Object] )\n    Returns an array containing pseudorandom integers on the interval\n    `[0, 4294967295]`.\n","random.array.mt19937.normalized":"\nrandom.array.mt19937.normalized( len:integer[, options:Object] )\n    Returns an array containing pseudorandom numbers on the interval `[0, 1)`\n    with 53-bit precision.\n","random.array.mt19937.factory":"\nrandom.array.mt19937.factory( [options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers\n    generated using a 32-bit Mersenne Twister pseudorandom number generator.\n","random.array.mt19937.PRNG":"\nrandom.array.mt19937.PRNG\n    Underlying pseudorandom number generator.\n","random.array.mt19937.seed":"\nrandom.array.mt19937.seed\n    Pseudorandom number generator seed.\n","random.array.mt19937.seedLength":"\nrandom.array.mt19937.seedLength\n    Length of generator seed.\n","random.array.mt19937.state":"\nrandom.array.mt19937.state\n    Generator state.\n","random.array.mt19937.stateLength":"\nrandom.array.mt19937.stateLength\n    Length of generator state.\n","random.array.mt19937.byteLength":"\nrandom.array.mt19937.byteLength\n    Size (in bytes) of generator state.\n","random.array.negativeBinomial":"\nrandom.array.negativeBinomial( len:integer, r:number, p:number[, \n  options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a negative\n    binomial distribution.\n","random.array.negativeBinomial.assign":"\nrandom.array.negativeBinomial.assign( r:number, p:number, out:Array|TypedArray )\n    Fills an array with pseudorandom numbers drawn from a negative binomial\n    distribution.\n","random.array.negativeBinomial.factory":"\nrandom.array.negativeBinomial.factory( [r:number, p:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a negative binomial distribution.\n","random.array.negativeBinomial.PRNG":"\nrandom.array.negativeBinomial.PRNG\n    Underlying pseudorandom number generator.\n","random.array.negativeBinomial.seed":"\nrandom.array.negativeBinomial.seed\n    Pseudorandom number generator seed.\n","random.array.negativeBinomial.seedLength":"\nrandom.array.negativeBinomial.seedLength\n    Length of generator seed.\n","random.array.negativeBinomial.state":"\nrandom.array.negativeBinomial.state\n    Generator state.\n","random.array.negativeBinomial.stateLength":"\nrandom.array.negativeBinomial.stateLength\n    Length of generator state.\n","random.array.negativeBinomial.byteLength":"\nrandom.array.negativeBinomial.byteLength\n    Size (in bytes) of generator state.\n","random.array.normal":"\nrandom.array.normal( len:integer, mu:number, sigma:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a normal\n    distribution.\n","random.array.normal.assign":"\nrandom.array.normal.assign( mu:number, sigma:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a normal distribution.\n","random.array.normal.factory":"\nrandom.array.normal.factory( [mu:number, sigma:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a normal distribution.\n","random.array.normal.PRNG":"\nrandom.array.normal.PRNG\n    Underlying pseudorandom number generator.\n","random.array.normal.seed":"\nrandom.array.normal.seed\n    Pseudorandom number generator seed.\n","random.array.normal.seedLength":"\nrandom.array.normal.seedLength\n    Length of generator seed.\n","random.array.normal.state":"\nrandom.array.normal.state\n    Generator state.\n","random.array.normal.stateLength":"\nrandom.array.normal.stateLength\n    Length of generator state.\n","random.array.normal.byteLength":"\nrandom.array.normal.byteLength\n    Size (in bytes) of generator state.\n","random.array.pareto1":"\nrandom.array.pareto1( len:integer, alpha:number, beta:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a Pareto (Type\n    I) distribution.\n","random.array.pareto1.assign":"\nrandom.array.pareto1.assign( alpha:number, beta:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a Pareto (Type I)\n    distribution.\n","random.array.pareto1.factory":"\nrandom.array.pareto1.factory( [alpha:number, beta:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Pareto (Type I) distribution.\n","random.array.pareto1.PRNG":"\nrandom.array.pareto1.PRNG\n    Underlying pseudorandom number generator.\n","random.array.pareto1.seed":"\nrandom.array.pareto1.seed\n    Pseudorandom number generator seed.\n","random.array.pareto1.seedLength":"\nrandom.array.pareto1.seedLength\n    Length of generator seed.\n","random.array.pareto1.state":"\nrandom.array.pareto1.state\n    Generator state.\n","random.array.pareto1.stateLength":"\nrandom.array.pareto1.stateLength\n    Length of generator state.\n","random.array.pareto1.byteLength":"\nrandom.array.pareto1.byteLength\n    Size (in bytes) of generator state.\n","random.array.poisson":"\nrandom.array.poisson( len:integer, lambda:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a Poisson\n    distribution.\n","random.array.poisson.assign":"\nrandom.array.poisson.assign( lambda:number, out:Array|TypedArray )\n    Fills an array with pseudorandom numbers drawn from a Poisson distribution.\n","random.array.poisson.factory":"\nrandom.array.poisson.factory( [lambda:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Poisson distribution.\n","random.array.poisson.PRNG":"\nrandom.array.poisson.PRNG\n    Underlying pseudorandom number generator.\n","random.array.poisson.seed":"\nrandom.array.poisson.seed\n    Pseudorandom number generator seed.\n","random.array.poisson.seedLength":"\nrandom.array.poisson.seedLength\n    Length of generator seed.\n","random.array.poisson.state":"\nrandom.array.poisson.state\n    Generator state.\n","random.array.poisson.stateLength":"\nrandom.array.poisson.stateLength\n    Length of generator state.\n","random.array.poisson.byteLength":"\nrandom.array.poisson.byteLength\n    Size (in bytes) of generator state.\n","random.array.randu":"\nrandom.array.randu( len:integer[, options:Object] )\n    Returns an array containing uniformly distributed pseudorandom numbers\n    between 0 and 1.\n","random.array.randu.factory":"\nrandom.array.randu.factory( [options:Object] )\n    Returns a function for creating arrays containing uniformly distributed\n    pseudorandom numbers between 0 and 1.\n","random.array.randu.PRNG":"\nrandom.array.randu.PRNG\n    Underlying pseudorandom number generator.\n","random.array.randu.seed":"\nrandom.array.randu.seed\n    Pseudorandom number generator seed.\n","random.array.randu.seedLength":"\nrandom.array.randu.seedLength\n    Length of generator seed.\n","random.array.randu.state":"\nrandom.array.randu.state\n    Generator state.\n","random.array.randu.stateLength":"\nrandom.array.randu.stateLength\n    Length of generator state.\n","random.array.randu.byteLength":"\nrandom.array.randu.byteLength\n    Size (in bytes) of generator state.\n","random.array.rayleigh":"\nrandom.array.rayleigh( len:integer, sigma:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a Rayleigh\n    distribution.\n","random.array.rayleigh.assign":"\nrandom.array.rayleigh.assign( sigma:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a Rayleigh distribution.\n","random.array.rayleigh.factory":"\nrandom.array.rayleigh.factory( [sigma:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Rayleigh distribution.\n","random.array.rayleigh.PRNG":"\nrandom.array.rayleigh.PRNG\n    Underlying pseudorandom number generator.\n","random.array.rayleigh.seed":"\nrandom.array.rayleigh.seed\n    Pseudorandom number generator seed.\n","random.array.rayleigh.seedLength":"\nrandom.array.rayleigh.seedLength\n    Length of generator seed.\n","random.array.rayleigh.state":"\nrandom.array.rayleigh.state\n    Generator state.\n","random.array.rayleigh.stateLength":"\nrandom.array.rayleigh.stateLength\n    Length of generator state.\n","random.array.rayleigh.byteLength":"\nrandom.array.rayleigh.byteLength\n    Size (in bytes) of generator state.\n","random.array.t":"\nrandom.array.t( len:integer, v:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a Student's t\n    distribution.\n","random.array.t.assign":"\nrandom.array.t.assign( v:number, out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a Student's t\n    distribution.\n","random.array.t.factory":"\nrandom.array.t.factory( [v:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Student's t distribution.\n","random.array.t.PRNG":"\nrandom.array.t.PRNG\n    Underlying pseudorandom number generator.\n","random.array.t.seed":"\nrandom.array.t.seed\n    Pseudorandom number generator seed.\n","random.array.t.seedLength":"\nrandom.array.t.seedLength\n    Length of generator seed.\n","random.array.t.state":"\nrandom.array.t.state\n    Generator state.\n","random.array.t.stateLength":"\nrandom.array.t.stateLength\n    Length of generator state.\n","random.array.t.byteLength":"\nrandom.array.t.byteLength\n    Size (in bytes) of generator state.\n","random.array.triangular":"\nrandom.array.triangular( len:integer, a:number, b:number, c:number[, \n  options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a triangular\n    distribution.\n","random.array.triangular.assign":"\nrandom.array.triangular.assign( a:number, b:number, c:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a triangular\n    distribution.\n","random.array.triangular.factory":"\nrandom.array.triangular.factory( [a:number, b:number, c:number, ]\n  [options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a triangular distribution.\n","random.array.triangular.PRNG":"\nrandom.array.triangular.PRNG\n    Underlying pseudorandom number generator.\n","random.array.triangular.seed":"\nrandom.array.triangular.seed\n    Pseudorandom number generator seed.\n","random.array.triangular.seedLength":"\nrandom.array.triangular.seedLength\n    Length of generator seed.\n","random.array.triangular.state":"\nrandom.array.triangular.state\n    Generator state.\n","random.array.triangular.stateLength":"\nrandom.array.triangular.stateLength\n    Length of generator state.\n","random.array.triangular.byteLength":"\nrandom.array.triangular.byteLength\n    Size (in bytes) of generator state.\n","random.array.uniform":"\nrandom.array.uniform( len:integer, a:number, b:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a continuous\n    uniform distribution.\n","random.array.uniform.assign":"\nrandom.array.uniform.assign( a:number, b:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a continuous uniform\n    distribution.\n","random.array.uniform.factory":"\nrandom.array.uniform.factory( [a:number, b:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a continuous uniform distribution.\n","random.array.uniform.PRNG":"\nrandom.array.uniform.PRNG\n    Underlying pseudorandom number generator.\n","random.array.uniform.seed":"\nrandom.array.uniform.seed\n    Pseudorandom number generator seed.\n","random.array.uniform.seedLength":"\nrandom.array.uniform.seedLength\n    Length of generator seed.\n","random.array.uniform.state":"\nrandom.array.uniform.state\n    Generator state.\n","random.array.uniform.stateLength":"\nrandom.array.uniform.stateLength\n    Length of generator state.\n","random.array.uniform.byteLength":"\nrandom.array.uniform.byteLength\n    Size (in bytes) of generator state.\n","random.array.weibull":"\nrandom.array.weibull( len:integer, k:number, lambda:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a Weibull\n    distribution.\n","random.array.weibull.assign":"\nrandom.array.weibull.assign( k:number, lambda:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a Weibull distribution.\n","random.array.weibull.factory":"\nrandom.array.weibull.factory( [k:number, lambda:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Weibull distribution.\n","random.array.weibull.PRNG":"\nrandom.array.weibull.PRNG\n    Underlying pseudorandom number generator.\n","random.array.weibull.seed":"\nrandom.array.weibull.seed\n    Pseudorandom number generator seed.\n","random.array.weibull.seedLength":"\nrandom.array.weibull.seedLength\n    Length of generator seed.\n","random.array.weibull.state":"\nrandom.array.weibull.state\n    Generator state.\n","random.array.weibull.stateLength":"\nrandom.array.weibull.stateLength\n    Length of generator state.\n","random.array.weibull.byteLength":"\nrandom.array.weibull.byteLength\n    Size (in bytes) of generator state.\n","random.iterators.arcsine":"\nrandom.iterators.arcsine( a:number, b:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from an\n    arcsine distribution.\n","random.iterators.bernoulli":"\nrandom.iterators.bernoulli( p:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Bernoulli distribution.\n","random.iterators.beta":"\nrandom.iterators.beta( α:number, β:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    beta distribution.\n","random.iterators.betaprime":"\nrandom.iterators.betaprime( α:number, β:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    beta prime distribution.\n","random.iterators.binomial":"\nrandom.iterators.binomial( n:integer, p:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    binomial distribution.\n","random.iterators.boxMuller":"\nrandom.iterators.boxMuller( [options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    standard normal distribution using the Box-Muller transform.\n","random.iterators.cauchy":"\nrandom.iterators.cauchy( x0:number, Ɣ:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Cauchy distribution.\n","random.iterators.chi":"\nrandom.iterators.chi( k:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a chi\n    distribution.\n","random.iterators.chisquare":"\nrandom.iterators.chisquare( k:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    chi-square distribution.\n","random.iterators.cosine":"\nrandom.iterators.cosine( μ:number, s:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a raised\n    cosine distribution.\n","random.iterators.discreteUniform":"\nrandom.iterators.discreteUniform( a:integer, b:integer[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    discrete uniform distribution.\n","random.iterators.erlang":"\nrandom.iterators.erlang( k:integer, λ:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from an Erlang\n    distribution.\n","random.iterators.exponential":"\nrandom.iterators.exponential( λ:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from an\n    exponential distribution.\n","random.iterators.f":"\nrandom.iterators.f( d1:number, d2:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from an F\n    distribution.\n","random.iterators.frechet":"\nrandom.iterators.frechet( α:number, s:number, m:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Fréchet\n    distribution.\n","random.iterators.gamma":"\nrandom.iterators.gamma( α:number, β:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a gamma\n    distribution.\n","random.iterators.geometric":"\nrandom.iterators.geometric( p:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    geometric distribution.\n","random.iterators.gumbel":"\nrandom.iterators.gumbel( μ:number, β:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Gumbel\n    distribution.\n","random.iterators.hypergeometric":"\nrandom.iterators.hypergeometric( N:integer, K:integer, n:integer[, \n  options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    hypergeometric distribution.\n","random.iterators.improvedZiggurat":"\nrandom.iterators.improvedZiggurat( [options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    standard normal distribution using the Improved Ziggurat algorithm.\n","random.iterators.invgamma":"\nrandom.iterators.invgamma( α:number, β:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from an\n    inverse gamma distribution.\n","random.iterators.kumaraswamy":"\nrandom.iterators.kumaraswamy( a:number, b:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Kumaraswamy's double bounded distribution.\n","random.iterators.laplace":"\nrandom.iterators.laplace( μ:number, b:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Laplace\n    (double exponential) distribution.\n","random.iterators.levy":"\nrandom.iterators.levy( μ:number, c:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Lévy\n    distribution.\n","random.iterators.logistic":"\nrandom.iterators.logistic( μ:number, s:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    logistic distribution.\n","random.iterators.lognormal":"\nrandom.iterators.lognormal( μ:number, σ:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    lognormal distribution.\n","random.iterators.minstd":"\nrandom.iterators.minstd( [options:Object] )\n    Returns an iterator for generating pseudorandom integers on the interval\n    `[1, 2147483646]`.\n","random.iterators.minstdShuffle":"\nrandom.iterators.minstdShuffle( [options:Object] )\n    Returns an iterator for generating pseudorandom integers on the interval\n    `[1, 2147483646]`.\n","random.iterators.mt19937":"\nrandom.iterators.mt19937( [options:Object] )\n    Returns an iterator for generating pseudorandom integers on the interval\n    `[1, 4294967295]`.\n","random.iterators.negativeBinomial":"\nrandom.iterators.negativeBinomial( r:number, p:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    negative binomial distribution.\n","random.iterators.normal":"\nrandom.iterators.normal( μ:number, σ:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a normal\n    distribution.\n","random.iterators.pareto1":"\nrandom.iterators.pareto1( α:number, β:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Pareto\n    (Type I) distribution.\n","random.iterators.poisson":"\nrandom.iterators.poisson( λ:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Poisson\n    distribution.\n","random.iterators.randi":"\nrandom.iterators.randi( [options:Object] )\n    Create an iterator for generating pseudorandom numbers having integer\n    values.\n","random.iterators.randn":"\nrandom.iterators.randn( [options:Object] )\n    Create an iterator for generating pseudorandom numbers drawn from a standard\n    normal distribution.\n","random.iterators.randu":"\nrandom.iterators.randu( [options:Object] )\n    Create an iterator for generating uniformly distributed pseudorandom numbers\n    between 0 and 1.\n","random.iterators.rayleigh":"\nrandom.iterators.rayleigh( σ:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Rayleigh distribution.\n","random.iterators.t":"\nrandom.iterators.t( v:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Student's t distribution.\n","random.iterators.triangular":"\nrandom.iterators.triangular( a:number, b:number, c:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    triangular distribution.\n","random.iterators.uniform":"\nrandom.iterators.uniform( a:number, b:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    continuous uniform distribution.\n","random.iterators.weibull":"\nrandom.iterators.weibull( k:number, λ:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Weibull distribution.\n","random.streams.arcsine":"\nrandom.streams.arcsine( a:number, b:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from an\n    arcsine distribution.\n","random.streams.arcsine.factory":"\nrandom.streams.arcsine.factory( [a:number, b:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an arcsine distribution.\n","random.streams.arcsine.objectMode":"\nrandom.streams.arcsine.objectMode( a:number, b:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an arcsine distribution.\n","random.streams.bernoulli":"\nrandom.streams.bernoulli( p:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Bernoulli distribution.\n","random.streams.bernoulli.factory":"\nrandom.streams.bernoulli.factory( [p:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Bernoulli distribution.\n","random.streams.bernoulli.objectMode":"\nrandom.streams.bernoulli.objectMode( p:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Bernoulli distribution.\n","random.streams.beta":"\nrandom.streams.beta( α:number, β:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    beta distribution.\n","random.streams.beta.factory":"\nrandom.streams.beta.factory( [α:number, β:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a beta distribution.\n","random.streams.beta.objectMode":"\nrandom.streams.beta.objectMode( α:number, β:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a beta distribution.\n","random.streams.betaprime":"\nrandom.streams.betaprime( α:number, β:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    beta prime distribution.\n","random.streams.betaprime.factory":"\nrandom.streams.betaprime.factory( [α:number, β:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a beta prime distribution.\n","random.streams.betaprime.objectMode":"\nrandom.streams.betaprime.objectMode( α:number, β:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a beta prime distribution.\n","random.streams.binomial":"\nrandom.streams.binomial( n:integer, p:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    binomial distribution.\n","random.streams.binomial.factory":"\nrandom.streams.binomial.factory( [n:integer, p:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a binomial distribution.\n","random.streams.binomial.objectMode":"\nrandom.streams.binomial.objectMode( n:integer, p:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a binomial distribution.\n","random.streams.boxMuller":"\nrandom.streams.boxMuller( [options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    standard normal distribution using the Box-Muller transform.\n","random.streams.boxMuller.factory":"\nrandom.streams.boxMuller.factory( [options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a standard normal distribution using the Box-Muller\n    transform.\n","random.streams.boxMuller.objectMode":"\nrandom.streams.boxMuller.objectMode( [options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a standard normal distribution using the Box-Muller transform.\n","random.streams.cauchy":"\nrandom.streams.cauchy( x0:number, γ:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Cauchy distribution.\n","random.streams.cauchy.factory":"\nrandom.streams.cauchy.factory( [x0:number, γ:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Cauchy distribution.\n","random.streams.cauchy.objectMode":"\nrandom.streams.cauchy.objectMode( x0:number, γ:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Cauchy distribution.\n","random.streams.chi":"\nrandom.streams.chi( k:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    chi distribution.\n","random.streams.chi.factory":"\nrandom.streams.chi.factory( [k:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a chi distribution.\n","random.streams.chi.objectMode":"\nrandom.streams.chi.objectMode( k:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a chi distribution.\n","random.streams.chisquare":"\nrandom.streams.chisquare( k:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    chi-square distribution.\n","random.streams.chisquare.factory":"\nrandom.streams.chisquare.factory( [k:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a chi-square distribution.\n","random.streams.chisquare.objectMode":"\nrandom.streams.chisquare.objectMode( k:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a chi-square distribution.\n","random.streams.cosine":"\nrandom.streams.cosine( μ:number, s:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    raised cosine distribution.\n","random.streams.cosine.factory":"\nrandom.streams.cosine.factory( [μ:number, s:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a raised cosine distribution.\n","random.streams.cosine.objectMode":"\nrandom.streams.cosine.objectMode( μ:number, s:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a raised cosine distribution.\n","random.streams.discreteUniform":"\nrandom.streams.discreteUniform( a:integer, b:integer[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    discrete uniform distribution.\n","random.streams.discreteUniform.factory":"\nrandom.streams.discreteUniform.factory( [a:integer, b:integer, ]\n  [options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a discrete uniform distribution.\n","random.streams.discreteUniform.objectMode":"\nrandom.streams.discreteUniform.objectMode( a:integer, b:integer[, \n  options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a discrete uniform distribution.\n","random.streams.erlang":"\nrandom.streams.erlang( k:integer, λ:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from an\n    Erlang distribution.\n","random.streams.erlang.factory":"\nrandom.streams.erlang.factory( [k:number, λ:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an Erlang distribution.\n","random.streams.erlang.objectMode":"\nrandom.streams.erlang.objectMode( k:number, λ:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an Erlang distribution.\n","random.streams.exponential":"\nrandom.streams.exponential( λ:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from an\n    exponential distribution.\n","random.streams.exponential.factory":"\nrandom.streams.exponential.factory( [λ:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an exponential distribution.\n","random.streams.exponential.objectMode":"\nrandom.streams.exponential.objectMode( λ:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an exponential distribution.\n","random.streams.f":"\nrandom.streams.f( d1:number, d2:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from an\n    F distribution.\n","random.streams.f.factory":"\nrandom.streams.f.factory( [d1:number, d2:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an F distribution.\n","random.streams.f.objectMode":"\nrandom.streams.f.objectMode( d1:number, d2:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an F distribution.\n","random.streams.frechet":"\nrandom.streams.frechet( α:number, s:number, m:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Fréchet distribution.\n","random.streams.frechet.factory":"\nrandom.streams.frechet.factory( [α:number, s:number, m:number,]\n  [options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Fréchet distribution.\n","random.streams.frechet.objectMode":"\nrandom.streams.frechet.objectMode( α:number, s:number, m:number[, \n  options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Fréchet distribution.\n","random.streams.gamma":"\nrandom.streams.gamma( α:number, β:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    gamma distribution.\n","random.streams.gamma.factory":"\nrandom.streams.gamma.factory( [α:number, β:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a gamma distribution.\n","random.streams.gamma.objectMode":"\nrandom.streams.gamma.objectMode( α:number, β:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a gamma distribution.\n","random.streams.geometric":"\nrandom.streams.geometric( p:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    geometric distribution.\n","random.streams.geometric.factory":"\nrandom.streams.geometric.factory( [p:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a geometric distribution.\n","random.streams.geometric.objectMode":"\nrandom.streams.geometric.objectMode( p:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a geometric distribution.\n","random.streams.gumbel":"\nrandom.streams.gumbel( μ:number, β:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Gumbel distribution.\n","random.streams.gumbel.factory":"\nrandom.streams.gumbel.factory( [μ:number, β:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Gumbel distribution.\n","random.streams.gumbel.objectMode":"\nrandom.streams.gumbel.objectMode( μ:number, β:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Gumbel distribution.\n","random.streams.hypergeometric":"\nrandom.streams.hypergeometric( N:integer, K:integer, n:integer[, \n  options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    hypergeometric distribution.\n","random.streams.hypergeometric.factory":"\nrandom.streams.hypergeometric.factory( [N:integer, K:integer, n:integer,]\n  [options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a hypergeometric distribution.\n","random.streams.hypergeometric.objectMode":"\nrandom.streams.hypergeometric.objectMode( N:integer, K:integer, n:integer[, \n  options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a hypergeometric distribution.\n","random.streams.improvedZiggurat":"\nrandom.streams.improvedZiggurat( [options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    standard normal distribution using the Improved Ziggurat algorithm.\n","random.streams.improvedZiggurat.factory":"\nrandom.streams.improvedZiggurat.factory( [options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a standard normal distribution using the Improved\n    Ziggurat algorithm.\n","random.streams.improvedZiggurat.objectMode":"\nrandom.streams.improvedZiggurat.objectMode( [options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a standard normal distribution using the Improved Ziggurat\n    algorithm.\n","random.streams.invgamma":"\nrandom.streams.invgamma( α:number, β:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from an\n    inverse gamma distribution.\n","random.streams.invgamma.factory":"\nrandom.streams.invgamma.factory( [α:number, β:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an inverse gamma distribution.\n","random.streams.invgamma.objectMode":"\nrandom.streams.invgamma.objectMode( α:number, β:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an inverse gamma distribution.\n","random.streams.kumaraswamy":"\nrandom.streams.kumaraswamy( a:number, b:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Kumaraswamy's double bounded distribution.\n","random.streams.kumaraswamy.factory":"\nrandom.streams.kumaraswamy.factory( [a:number, b:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Kumaraswamy's double bounded distribution.\n","random.streams.kumaraswamy.objectMode":"\nrandom.streams.kumaraswamy.objectMode( a:number, b:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Kumaraswamy's double bounded distribution.\n","random.streams.laplace":"\nrandom.streams.laplace( μ:number, b:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Laplace (double exponential) distribution.\n","random.streams.laplace.factory":"\nrandom.streams.laplace.factory( [μ:number, b:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Laplace (double exponential) distribution.\n","random.streams.laplace.objectMode":"\nrandom.streams.laplace.objectMode( μ:number, b:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Laplace (double exponential) distribution.\n","random.streams.levy":"\nrandom.streams.levy( μ:number, c:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Lévy distribution.\n","random.streams.levy.factory":"\nrandom.streams.levy.factory( [μ:number, c:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Lévy distribution.\n","random.streams.levy.objectMode":"\nrandom.streams.levy.objectMode( μ:number, c:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Lévy distribution.\n","random.streams.logistic":"\nrandom.streams.logistic( μ:number, s:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    logistic distribution.\n","random.streams.logistic.factory":"\nrandom.streams.logistic.factory( [μ:number, s:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a logistic distribution.\n","random.streams.logistic.objectMode":"\nrandom.streams.logistic.objectMode( μ:number, s:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a logistic distribution.\n","random.streams.lognormal":"\nrandom.streams.lognormal( μ:number, σ:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    lognormal distribution.\n","random.streams.lognormal.factory":"\nrandom.streams.lognormal.factory( [μ:number, σ:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a lognormal distribution.\n","random.streams.lognormal.objectMode":"\nrandom.streams.lognormal.objectMode( μ:number, σ:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a lognormal distribution.\n","random.streams.minstd":"\nrandom.streams.minstd( [options:Object] )\n    Returns a readable stream for generating pseudorandom numbers on the\n    interval `[1, 2147483646]`.\n","random.streams.minstd.factory":"\nrandom.streams.minstd.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers on the interval `[1, 2147483646]`.\n","random.streams.minstd.objectMode":"\nrandom.streams.minstd.objectMode( [options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    on the interval `[1, 2147483646]`.\n","random.streams.minstdShuffle":"\nrandom.streams.minstdShuffle( [options:Object] )\n    Returns a readable stream for generating pseudorandom numbers on the\n    interval `[1, 2147483646]`.\n","random.streams.minstdShuffle.factory":"\nrandom.streams.minstdShuffle.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers on the interval `[1, 2147483646]`.\n","random.streams.minstdShuffle.objectMode":"\nrandom.streams.minstdShuffle.objectMode( [options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    on the interval `[1, 2147483646]`.\n","random.streams.mt19937":"\nrandom.streams.mt19937( [options:Object] )\n    Returns a readable stream for generating pseudorandom numbers on the\n    interval `[1, 4294967295]`.\n","random.streams.mt19937.factory":"\nrandom.streams.mt19937.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers on the interval `[1, 4294967295]`.\n","random.streams.mt19937.objectMode":"\nrandom.streams.mt19937.objectMode( [options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    on the interval `[1, 4294967295]`.\n","random.streams.negativeBinomial":"\nrandom.streams.negativeBinomial( r:number, p:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    negative binomial distribution.\n","random.streams.negativeBinomial.factory":"\nrandom.streams.negativeBinomial.factory( [r:number, p:number, ]\n  [options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a negative binomial distribution.\n","random.streams.negativeBinomial.objectMode":"\nrandom.streams.negativeBinomial.objectMode( r:integer, p:number[, \n  options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a negative binomial distribution.\n","random.streams.normal":"\nrandom.streams.normal( μ:number, σ:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    normal distribution.\n","random.streams.normal.factory":"\nrandom.streams.normal.factory( [μ:number, σ:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a normal distribution.\n","random.streams.normal.objectMode":"\nrandom.streams.normal.objectMode( μ:number, σ:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a normal distribution.\n","random.streams.pareto1":"\nrandom.streams.pareto1( α:number, β:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Pareto (Type I) distribution.\n","random.streams.pareto1.factory":"\nrandom.streams.pareto1.factory( [α:number, β:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Pareto (Type I) distribution.\n","random.streams.pareto1.objectMode":"\nrandom.streams.pareto1.objectMode( α:number, β:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Pareto (Type I) distribution.\n","random.streams.poisson":"\nrandom.streams.poisson( λ:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Poisson distribution.\n","random.streams.poisson.factory":"\nrandom.streams.poisson.factory( [λ:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Poisson distribution.\n","random.streams.poisson.objectMode":"\nrandom.streams.poisson.objectMode( λ:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Poisson distribution.\n","random.streams.randi":"\nrandom.streams.randi( [options:Object] )\n    Returns a readable stream for generating pseudorandom numbers having integer\n    values.\n","random.streams.randi.factory":"\nrandom.streams.randi.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers having integer values.\n","random.streams.randi.objectMode":"\nrandom.streams.randi.objectMode( [options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    having integer values.\n","random.streams.randn":"\nrandom.streams.randn( [options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    standard normal distribution.\n","random.streams.randn.factory":"\nrandom.streams.randn.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a standard normal distribution.\n","random.streams.randn.objectMode":"\nrandom.streams.randn.objectMode( [options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a standard normal distribution.\n","random.streams.randu":"\nrandom.streams.randu( [options:Object] )\n    Returns a readable stream for generating uniformly distributed pseudorandom\n    numbers between 0 and 1.\n","random.streams.randu.factory":"\nrandom.streams.randu.factory( [options] )\n    Returns a function for creating readable streams which generate uniformly\n    distributed pseudorandom numbers between 0 and 1.\n","random.streams.randu.objectMode":"\nrandom.streams.randu.objectMode( [options:Object] )\n    Returns an \"objectMode\" readable stream for generating uniformly distributed\n    pseudorandom numbers between 0 and 1.\n","random.streams.rayleigh":"\nrandom.streams.rayleigh( σ:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Rayleigh distribution.\n","random.streams.rayleigh.factory":"\nrandom.streams.rayleigh.factory( [σ:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Rayleigh distribution.\n","random.streams.rayleigh.objectMode":"\nrandom.streams.rayleigh.objectMode( σ:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Rayleigh distribution.\n","random.streams.t":"\nrandom.streams.t( v:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Student's t distribution.\n","random.streams.t.factory":"\nrandom.streams.t.factory( [v:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Student's t distribution.\n","random.streams.t.objectMode":"\nrandom.streams.t.objectMode( v:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Student's t distribution.\n","random.streams.triangular":"\nrandom.streams.triangular( a:number, b:number, c:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    triangular distribution.\n","random.streams.triangular.factory":"\nrandom.streams.triangular.factory( [a:number, b:number, c:number, ]\n  [options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a triangular distribution.\n","random.streams.triangular.objectMode":"\nrandom.streams.triangular.objectMode( a:number, b:number, c:number[, \n  options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a triangular distribution.\n","random.streams.uniform":"\nrandom.streams.uniform( a:number, b:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    uniform distribution.\n","random.streams.uniform.factory":"\nrandom.streams.uniform.factory( [a:number, b:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a uniform distribution.\n","random.streams.uniform.objectMode":"\nrandom.streams.uniform.objectMode( a:number, b:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a uniform distribution.\n","random.streams.weibull":"\nrandom.streams.weibull( k:number, λ:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Weibull distribution.\n","random.streams.weibull.factory":"\nrandom.streams.weibull.factory( [k:number, λ:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Weibull distribution.\n","random.streams.weibull.objectMode":"\nrandom.streams.weibull.objectMode( k:number, λ:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Weibull distribution.\n","random.strided.arcsine":"\nrandom.strided.arcsine( N:integer, a:ArrayLikeObject, sa:integer, \n  b:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from an arcsine\n    distribution.\n","random.strided.arcsine.ndarray":"\nrandom.strided.arcsine.ndarray( N:integer, a:ArrayLikeObject, sa:integer, \n  oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, \n  so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from an arcsine\n    distribution using alternative indexing semantics.\n","random.strided.bernoulli":"\nrandom.strided.bernoulli( N:integer, p:ArrayLikeObject, sp:integer, \n  out:ArrayLikeObject, so:integer )\n    Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n    distribution.\n","random.strided.bernoulli.ndarray":"\nrandom.strided.bernoulli.ndarray( N:integer, p:ArrayLikeObject, sp:integer, \n  op:integer, out:ArrayLikeObject, so:integer, oo:integer )\n    Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n    distribution using alternative indexing semantics.\n","random.strided.bernoulli.factory":"\nrandom.strided.bernoulli.factory( [options:Object] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Bernoulli distribution.\n","random.strided.bernoulli.PRNG":"\nrandom.strided.bernoulli.PRNG\n    Underlying pseudorandom number generator.\n","random.strided.bernoulli.seed":"\nrandom.strided.bernoulli.seed\n    Pseudorandom number generator seed.\n","random.strided.bernoulli.seedLength":"\nrandom.strided.bernoulli.seedLength\n    Length of generator seed.\n","random.strided.bernoulli.state":"\nrandom.strided.bernoulli.state\n    Generator state.\n","random.strided.bernoulli.stateLength":"\nrandom.strided.bernoulli.stateLength\n    Length of generator state.\n","random.strided.bernoulli.byteLength":"\nrandom.strided.bernoulli.byteLength\n    Size (in bytes) of generator state.\n","random.strided.beta":"\nrandom.strided.beta( N:integer, alpha:ArrayLikeObject, sa:integer, \n  beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a beta\n    distribution.\n","random.strided.beta.ndarray":"\nrandom.strided.beta.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n  oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n  out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a beta\n    distribution using alternative indexing semantics.\n","random.strided.betaprime":"\nrandom.strided.betaprime( N:integer, alpha:ArrayLikeObject, sa:integer, \n  beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a beta prime\n    distribution.\n","random.strided.betaprime.ndarray":"\nrandom.strided.betaprime.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n  oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n  out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a beta prime\n    distribution using alternative indexing semantics.\n","random.strided.chi":"\nrandom.strided.chi( N:integer, k:ArrayLikeObject, sk:integer, \n  out:ArrayLikeObject, so:integer )\n    Fills a strided array with pseudorandom numbers drawn from a chi\n    distribution.\n","random.strided.chi.ndarray":"\nrandom.strided.chi.ndarray( N:integer, k:ArrayLikeObject, sk:integer, \n  ok:integer, out:ArrayLikeObject, so:integer, oo:integer )\n    Fills a strided array with pseudorandom numbers drawn from a chi\n    distribution using alternative indexing semantics.\n","random.strided.chi.factory":"\nrandom.strided.chi.factory( [options:Object] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a chi distribution.\n","random.strided.chi.PRNG":"\nrandom.strided.chi.PRNG\n    Underlying pseudorandom number generator.\n","random.strided.chi.seed":"\nrandom.strided.chi.seed\n    Pseudorandom number generator seed.\n","random.strided.chi.seedLength":"\nrandom.strided.chi.seedLength\n    Length of generator seed.\n","random.strided.chi.state":"\nrandom.strided.chi.state\n    Generator state.\n","random.strided.chi.stateLength":"\nrandom.strided.chi.stateLength\n    Length of generator state.\n","random.strided.chi.byteLength":"\nrandom.strided.chi.byteLength\n    Size (in bytes) of generator state.\n","random.strided.chisquare":"\nrandom.strided.chisquare( N:integer, k:ArrayLikeObject, sk:integer, \n  out:ArrayLikeObject, so:integer )\n    Fills a strided array with pseudorandom numbers drawn from a chi-square\n    distribution.\n","random.strided.chisquare.ndarray":"\nrandom.strided.chisquare.ndarray( N:integer, k:ArrayLikeObject, sk:integer, \n  ok:integer, out:ArrayLikeObject, so:integer, oo:integer )\n    Fills a strided array with pseudorandom numbers drawn from a chi-square\n    distribution using alternative indexing semantics.\n","random.strided.chisquare.factory":"\nrandom.strided.chisquare.factory( [options:Object] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a chi-square distribution.\n","random.strided.chisquare.PRNG":"\nrandom.strided.chisquare.PRNG\n    Underlying pseudorandom number generator.\n","random.strided.chisquare.seed":"\nrandom.strided.chisquare.seed\n    Pseudorandom number generator seed.\n","random.strided.chisquare.seedLength":"\nrandom.strided.chisquare.seedLength\n    Length of generator seed.\n","random.strided.chisquare.state":"\nrandom.strided.chisquare.state\n    Generator state.\n","random.strided.chisquare.stateLength":"\nrandom.strided.chisquare.stateLength\n    Length of generator state.\n","random.strided.chisquare.byteLength":"\nrandom.strided.chisquare.byteLength\n    Size (in bytes) of generator state.\n","random.strided.cosine":"\nrandom.strided.cosine( N:integer, mu:ArrayLikeObject, sm:integer, \n  s:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a cosine\n    distribution.\n","random.strided.cosine.ndarray":"\nrandom.strided.cosine.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, \n  om:integer, s:ArrayLikeObject, ss:integer, os:integer, out:ArrayLikeObject, \n  so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a cosine\n    distribution using alternative indexing semantics.\n","random.strided.discreteUniform":"\nrandom.strided.discreteUniform( N:integer, a:ArrayLikeObject, sa:integer, \n  b:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a discrete\n    uniform distribution.\n","random.strided.discreteUniform.ndarray":"\nrandom.strided.discreteUniform.ndarray( N:integer, a:ArrayLikeObject, \n  sa:integer, oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, \n  out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a discrete\n    uniform distribution using alternative indexing semantics.\n","random.strided.exponential":"\nrandom.strided.exponential( N:integer, lambda:ArrayLikeObject, sl:integer, \n  out:ArrayLikeObject, so:integer )\n    Fills a strided array with pseudorandom numbers drawn from an exponential\n    distribution.\n","random.strided.exponential.ndarray":"\nrandom.strided.exponential.ndarray( N:integer, lambda:ArrayLikeObject, \n  sl:integer, ol:integer, out:ArrayLikeObject, so:integer, oo:integer )\n    Fills a strided array with pseudorandom numbers drawn from an exponential\n    distribution using alternative indexing semantics.\n","random.strided.exponential.factory":"\nrandom.strided.exponential.factory( [options:Object] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from an exponential distribution.\n","random.strided.exponential.PRNG":"\nrandom.strided.exponential.PRNG\n    Underlying pseudorandom number generator.\n","random.strided.exponential.seed":"\nrandom.strided.exponential.seed\n    Pseudorandom number generator seed.\n","random.strided.exponential.seedLength":"\nrandom.strided.exponential.seedLength\n    Length of generator seed.\n","random.strided.exponential.state":"\nrandom.strided.exponential.state\n    Generator state.\n","random.strided.exponential.stateLength":"\nrandom.strided.exponential.stateLength\n    Length of generator state.\n","random.strided.exponential.byteLength":"\nrandom.strided.exponential.byteLength\n    Size (in bytes) of generator state.\n","random.strided.gamma":"\nrandom.strided.gamma( N:integer, alpha:ArrayLikeObject, sa:integer, \n  beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a gamma\n    distribution.\n","random.strided.gamma.ndarray":"\nrandom.strided.gamma.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n  oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n  out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a gamma\n    distribution using alternative indexing semantics.\n","random.strided.geometric":"\nrandom.strided.geometric( N:integer, p:ArrayLikeObject, sp:integer, \n  out:ArrayLikeObject, so:integer )\n    Fills a strided array with pseudorandom numbers drawn from a geometric\n    distribution.\n","random.strided.geometric.ndarray":"\nrandom.strided.geometric.ndarray( N:integer, p:ArrayLikeObject, sp:integer, \n  op:integer, out:ArrayLikeObject, so:integer, oo:integer )\n    Fills a strided array with pseudorandom numbers drawn from a geometric\n    distribution using alternative indexing semantics.\n","random.strided.geometric.factory":"\nrandom.strided.geometric.factory( [options:Object] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a geometric distribution.\n","random.strided.geometric.PRNG":"\nrandom.strided.geometric.PRNG\n    Underlying pseudorandom number generator.\n","random.strided.geometric.seed":"\nrandom.strided.geometric.seed\n    Pseudorandom number generator seed.\n","random.strided.geometric.seedLength":"\nrandom.strided.geometric.seedLength\n    Length of generator seed.\n","random.strided.geometric.state":"\nrandom.strided.geometric.state\n    Generator state.\n","random.strided.geometric.stateLength":"\nrandom.strided.geometric.stateLength\n    Length of generator state.\n","random.strided.geometric.byteLength":"\nrandom.strided.geometric.byteLength\n    Size (in bytes) of generator state.\n","random.strided.invgamma":"\nrandom.strided.invgamma( N:integer, alpha:ArrayLikeObject, sa:integer, \n  beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n    distribution.\n","random.strided.invgamma.ndarray":"\nrandom.strided.invgamma.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n  oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n  out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n    distribution using alternative indexing semantics.\n","random.strided.lognormal":"\nrandom.strided.lognormal( N:integer, mu:ArrayLikeObject, sm:integer, \n  sigma:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a lognormal\n    distribution.\n","random.strided.lognormal.ndarray":"\nrandom.strided.lognormal.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, \n  om:integer, sigma:ArrayLikeObject, ss:integer, os:integer, \n  out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a lognormal\n    distribution using alternative indexing semantics.\n","random.strided.minstd":"\nrandom.strided.minstd( N:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom integers between 1 and 2147483646\n    (inclusive).\n","random.strided.minstd.ndarray":"\nrandom.strided.minstd.ndarray( N:integer, out:ArrayLikeObject, so:integer, \n  oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom integers between 1 and 2147483646\n    (inclusive) using alternative indexing semantics.\n","random.strided.minstd.normalized":"\nrandom.strided.minstd.normalized( N:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers between 0 and 1.\n","random.strided.minstd.normalized.ndarray":"\nrandom.strided.minstd.normalized.ndarray( N:integer, out:ArrayLikeObject, \n  so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers between 0 and 1 using\n    alternative indexing semantics.\n","random.strided.minstdShuffle":"\nrandom.strided.minstdShuffle( N:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom integers between 1 and 2147483646\n    (inclusive).\n","random.strided.minstdShuffle.ndarray":"\nrandom.strided.minstdShuffle.ndarray( N:integer, out:ArrayLikeObject, \n  so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom integers between 1 and 2147483646\n    (inclusive) using alternative indexing semantics.\n","random.strided.minstdShuffle.normalized":"\nrandom.strided.minstdShuffle.normalized( N:integer, out:ArrayLikeObject, \n  so:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers between 0 and 1.\n","random.strided.minstdShuffle.normalized.ndarray":"\nrandom.strided.minstdShuffle.normalized.ndarray( N:integer, \n  out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers between 0 and 1 using\n    alternative indexing semantics.\n","random.strided.mt19937":"\nrandom.strided.mt19937( N:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom integers between 0 and 4294967295\n    (inclusive).\n","random.strided.mt19937.ndarray":"\nrandom.strided.mt19937.ndarray( N:integer, out:ArrayLikeObject, so:integer, \n  oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom integers between 0 and 4294967295\n    (inclusive) using alternative indexing semantics.\n","random.strided.mt19937.normalized":"\nrandom.strided.mt19937.normalized( N:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers between 0 and 1.\n","random.strided.mt19937.normalized.ndarray":"\nrandom.strided.mt19937.normalized.ndarray( N:integer, out:ArrayLikeObject, \n  so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers between 0 and 1 using\n    alternative indexing semantics.\n","random.strided.normal":"\nrandom.strided.normal( N:integer, mu:ArrayLikeObject, sm:integer, \n  sigma:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a normal\n    distribution.\n","random.strided.normal.ndarray":"\nrandom.strided.normal.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, \n  om:integer, sigma:ArrayLikeObject, ss:integer, os:integer, \n  out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a normal\n    distribution using alternative indexing semantics.\n","random.strided.poisson":"\nrandom.strided.poisson( N:integer, lambda:ArrayLikeObject, sl:integer, \n  out:ArrayLikeObject, so:integer )\n    Fills a strided array with pseudorandom numbers drawn from a Poisson\n    distribution.\n","random.strided.poisson.ndarray":"\nrandom.strided.poisson.ndarray( N:integer, lambda:ArrayLikeObject, sl:integer, \n  ol:integer, out:ArrayLikeObject, so:integer, oo:integer )\n    Fills a strided array with pseudorandom numbers drawn from a Poisson\n    distribution using alternative indexing semantics.\n","random.strided.poisson.factory":"\nrandom.strided.poisson.factory( [options:Object] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Poisson distribution.\n","random.strided.poisson.PRNG":"\nrandom.strided.poisson.PRNG\n    Underlying pseudorandom number generator.\n","random.strided.poisson.seed":"\nrandom.strided.poisson.seed\n    Pseudorandom number generator seed.\n","random.strided.poisson.seedLength":"\nrandom.strided.poisson.seedLength\n    Length of generator seed.\n","random.strided.poisson.state":"\nrandom.strided.poisson.state\n    Generator state.\n","random.strided.poisson.stateLength":"\nrandom.strided.poisson.stateLength\n    Length of generator state.\n","random.strided.poisson.byteLength":"\nrandom.strided.poisson.byteLength\n    Size (in bytes) of generator state.\n","random.strided.randu":"\nrandom.strided.randu( N:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with uniformly distributed pseudorandom numbers\n    between 0 and 1.\n","random.strided.randu.ndarray":"\nrandom.strided.randu.ndarray( N:integer, out:ArrayLikeObject, so:integer, \n  oo:integer[, options:Object] )\n    Fills a strided array with uniformly distributed pseudorandom numbers\n    between 0 and 1 using alternative indexing semantics.\n","random.strided.rayleigh":"\nrandom.strided.rayleigh( N:integer, sigma:ArrayLikeObject, ss:integer, \n  out:ArrayLikeObject, so:integer )\n    Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n    distribution.\n","random.strided.rayleigh.ndarray":"\nrandom.strided.rayleigh.ndarray( N:integer, sigma:ArrayLikeObject, ss:integer, \n  os:integer, out:ArrayLikeObject, so:integer, oo:integer )\n    Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n    distribution using alternative indexing semantics.\n","random.strided.rayleigh.factory":"\nrandom.strided.rayleigh.factory( [options:Object] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Rayleigh distribution.\n","random.strided.rayleigh.PRNG":"\nrandom.strided.rayleigh.PRNG\n    Underlying pseudorandom number generator.\n","random.strided.rayleigh.seed":"\nrandom.strided.rayleigh.seed\n    Pseudorandom number generator seed.\n","random.strided.rayleigh.seedLength":"\nrandom.strided.rayleigh.seedLength\n    Length of generator seed.\n","random.strided.rayleigh.state":"\nrandom.strided.rayleigh.state\n    Generator state.\n","random.strided.rayleigh.stateLength":"\nrandom.strided.rayleigh.stateLength\n    Length of generator state.\n","random.strided.rayleigh.byteLength":"\nrandom.strided.rayleigh.byteLength\n    Size (in bytes) of generator state.\n","random.strided.t":"\nrandom.strided.t( N:integer, v:ArrayLikeObject, sv:integer, \n  out:ArrayLikeObject, so:integer )\n    Fills a strided array with pseudorandom numbers drawn from a Student's t-\n    distribution.\n","random.strided.t.ndarray":"\nrandom.strided.t.ndarray( N:integer, v:ArrayLikeObject, sv:integer, ov:integer, \n  out:ArrayLikeObject, so:integer, oo:integer )\n    Fills a strided array with pseudorandom numbers drawn from a Student's t-\n    distribution using alternative indexing semantics.\n","random.strided.t.factory":"\nrandom.strided.t.factory( [options:Object] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Student's t-distribution.\n","random.strided.t.PRNG":"\nrandom.strided.t.PRNG\n    Underlying pseudorandom number generator.\n","random.strided.t.seed":"\nrandom.strided.t.seed\n    Pseudorandom number generator seed.\n","random.strided.t.seedLength":"\nrandom.strided.t.seedLength\n    Length of generator seed.\n","random.strided.t.state":"\nrandom.strided.t.state\n    Generator state.\n","random.strided.t.stateLength":"\nrandom.strided.t.stateLength\n    Length of generator state.\n","random.strided.t.byteLength":"\nrandom.strided.t.byteLength\n    Size (in bytes) of generator state.\n","random.strided.uniform":"\nrandom.strided.uniform( N:integer, a:ArrayLikeObject, sa:integer, \n  b:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a continuous\n    uniform distribution.\n","random.strided.uniform.ndarray":"\nrandom.strided.uniform.ndarray( N:integer, a:ArrayLikeObject, sa:integer, \n  oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, \n  so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a continuous\n    uniform distribution using alternative indexing semantics.\n","random.strided.weibull":"\nrandom.strided.weibull( N:integer, k:ArrayLikeObject, sk:integer, \n  lambda:ArrayLikeObject, sl:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a Weibull\n    distribution.\n","random.strided.weibull.ndarray":"\nrandom.strided.weibull.ndarray( N:integer, k:ArrayLikeObject, sk:integer, \n  ok:integer, lambda:ArrayLikeObject, sl:integer, ol:integer, \n  out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a Weibull\n    distribution using alternative indexing semantics.\n","ranks":"\nranks( arr:Array<number>[, options:Object] )\n    Computes the sample ranks for the values of an array-like object.\n","readDir":"\nreadDir( path:string|Buffer, clbk:Function )\n    Asynchronously reads the contents of a directory.\n","readDir.sync":"\nreadDir.sync( path:string|Buffer )\n    Synchronously reads the contents of a directory.\n","readFile":"\nreadFile( file:string|Buffer|integer[, options:Object|string], clbk:Function )\n    Asynchronously reads the entire contents of a file.\n","readFile.sync":"\nreadFile.sync( file:string|Buffer|integer[, options:Object|string] )\n    Synchronously reads the entire contents of a file.\n","readFileList":"\nreadFileList( filepaths:Array<string>[, options:Object|string], clbk:Function )\n    Asynchronously reads the entire contents of each file in a file list.\n","readFileList.sync":"\nreadFileList.sync( filepaths:Array<string>[, options:Object|string] )\n    Synchronously reads the entire contents of each file in a file list.\n","readJSON":"\nreadJSON( file:string|Buffer|integer[, options:Object|string], clbk:Function )\n    Asynchronously reads a file as JSON.\n","readJSON.sync":"\nreadJSON.sync( file:string|Buffer|integer[, options:Object|string] )\n    Synchronously reads a file as JSON.\n","readWASM":"\nreadWASM( file:string|Buffer|integer[, options:Object], clbk:Function )\n    Asynchronously reads a file as WebAssembly.\n","readWASM.sync":"\nreadWASM.sync( file:string|Buffer|integer[, options:Object] )\n    Synchronously reads a file as WebAssembly.\n","real":"\nreal( z:Complex128 )\n    Returns the real component of a double-precision complex floating-point\n    number.\n","realarray":"\nrealarray( [dtype:string] )\n    Creates a typed array.\n\nrealarray( length:integer[, dtype:string] )\n    Returns a typed array having a specified length.\n\nrealarray( typedarray:TypedArray[, dtype:string] )\n    Creates a typed array from another typed array.\n\nrealarray( obj:Object[, dtype:string] )\n    Creates a typed array from an array-like object or iterable.\n\nrealarray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n  dtype:string] )\n    Returns a typed array view of an ArrayBuffer.\n","realarrayCtors":"\nrealarrayCtors( dtype:string )\n    Returns a typed array constructor.\n","realarrayDataTypes":"\nrealarrayDataTypes()\n    Returns a list of typed array real-valued data types.\n","realf":"\nrealf( z:Complex64 )\n    Returns the real component of a single-precision complex floating-point\n    number.\n","realmax":"\nrealmax( dtype:string )\n    Returns the maximum finite value capable of being represented by a numeric\n    real type.\n","realmin":"\nrealmin( dtype:string )\n    Returns the smallest positive normal value capable of being represented by a\n    numeric real type.\n","reBasename":"\nreBasename( [platform:string] )\n    Returns a regular expression to capture the last part of a path.\n","reBasename.REGEXP":"\nreBasename.REGEXP\n    Regular expression to capture the last part of a POSIX path.\n","reBasename.REGEXP_POSIX":"\nreBasename.REGEXP_POSIX\n    Regular expression to capture the last part of a POSIX path.\n","reBasename.REGEXP_WIN32":"\nreBasename.REGEXP_WIN32\n    Regular expression to capture the last part of a Windows path.\n","reBasenamePosix":"\nreBasenamePosix()\n    Returns a regular expression to capture the last part of a POSIX path.\n","reBasenamePosix.REGEXP":"\nreBasenamePosix.REGEXP\n    Regular expression to capture the last part of a POSIX path.\n","reBasenameWindows":"\nreBasenameWindows()\n    Returns a regular expression to capture the last part of a Windows path.\n","reBasenameWindows.REGEXP":"\nreBasenameWindows.REGEXP\n    Regular expression to capture the last part of a Windows path.\n","reColorHexadecimal":"\nreColorHexadecimal( [mode:string] )\n    Returns a regular expression to match a hexadecimal color.\n","reColorHexadecimal.REGEXP":"\nreColorHexadecimal.REGEXP\n    Regular expression to match a full hexadecimal color.\n","reColorHexadecimal.REGEXP_SHORTHAND":"\nreColorHexadecimal.REGEXP_SHORTHAND\n    Regular expression to match a shorthand hexadecimal color.\n","reColorHexadecimal.REGEXP_EITHER":"\nreColorHexadecimal.REGEXP_EITHER\n    Regular expression to match either a shorthand or full length hexadecimal\n    color.\n","reDecimalNumber":"\nreDecimalNumber( [options:Object] )\n    Returns a regular expression to match a decimal number.\n","reDecimalNumber.REGEXP":"\nreDecimalNumber.REGEXP\n    Regular expression to match a decimal number.\n","reDecimalNumber.REGEXP_CAPTURE":"\nreDecimalNumber.REGEXP_CAPTURE\n    Regular expression to capture a decimal number.\n","reDirname":"\nreDirname( [platform:string] )\n    Returns a regular expression to capture a path dirname.\n","reDirname.REGEXP":"\nreDirname.REGEXP\n    Regular expression to capture a path dirname.\n","reDirname.REGEXP_POSIX":"\nreDirname.REGEXP_POSIX\n    Regular expression to capture a POSIX path dirname.\n","reDirname.REGEXP_WIN32":"\nreDirname.REGEXP_WIN32\n    Regular expression to capture a Windows path dirname.\n","reDirnamePosix":"\nreDirnamePosix()\n    Returns a regular expression to capture a POSIX path dirname.\n","reDirnamePosix.REGEXP":"\nreDirnamePosix.REGEXP\n    Regular expression to capture a POSIX path dirname.\n","reDirnameWindows":"\nreDirnameWindows()\n    Returns a regular expression to capture a Windows path dirname.\n","reDirnameWindows.REGEXP":"\nreDirnameWindows.REGEXP\n    Regular expression to capture a Windows path dirname.\n","reduce":"\nreduce( arr:ArrayLikeObject|ndarray, initial:any, reducer:Function[, \n  thisArg:any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n","reduce2d":"\nreduce2d( arr:ArrayLikeObject<ArrayLikeObject>, initial:ArrayLikeObject, \n  reducer:Function[, thisArg:any] )\n    Reduces the number of dimensions by one of a two-dimensional nested array by\n    applying a function against an accumulator and each element along the\n    innermost dimension and returning the accumulation results as a one-\n    dimensional array.\n","reduceAsync":"\nreduceAsync( collection:Array|TypedArray|Object, initial:any, [options:Object,] \n  reducer:Function, done:Function )\n    Applies a function against an accumulator and each element in a collection\n    and returns the accumulated result.\n","reduceAsync.factory":"\nreduceAsync.factory( [options:Object,] fcn:Function )\n    Returns a function which applies a function against an accumulator and each\n    element in a collection and returns the accumulated result.\n","reduceRight":"\nreduceRight( arr:ArrayLikeObject|ndarray, initial:any, reducer:Function[, \n  thisArg:any] )\n    Applies a function against an accumulator and each element in an array while\n    iterating from right to left and returns the accumulated result.\n","reduceRightAsync":"\nreduceRightAsync( collection:Array|TypedArray|Object, initial:any, \n  [options:Object,] reducer:Function, done:Function )\n    Applies a function against an accumulator and each element in a collection\n    and returns the accumulated result, iterating from right to left.\n","reduceRightAsync.factory":"\nreduceRightAsync.factory( [options:Object,] fcn:Function )\n    Returns a function which applies a function against an accumulator and each\n    element in a collection and returns the accumulated result, iterating from\n    right to left.\n","reDurationString":"\nreDurationString()\n    Returns a regular expression to match a duration string.\n","reDurationString.REGEXP":"\nreDurationString.REGEXP\n    Regular expression to match a duration string.\n","reEOL":"\nreEOL( [options:Object] )\n    Regular expression to match a newline character sequence: /\\r?\\n/.\n","reEOL.REGEXP":"\nreEOL.REGEXP\n    Regular expression to match a newline character sequence: /\\r?\\n/.\n","reEOL.REGEXP_CAPTURE":"\nreEOL.REGEXP_CAPTURE\n    Regular expression to capture a newline character sequence: /\\r?\\n/.\n","reExtendedLengthPath":"\nreExtendedLengthPath()\n    Returns a regular expression to test if a string is an extended-length path.\n","reExtendedLengthPath.REGEXP":"\nreExtendedLengthPath.REGEXP\n    Regular expression to test if a string is an extended-length path.\n","reExtname":"\nreExtname( [platform:string] )\n    Returns a regular expression to capture a filename extension.\n","reExtname.REGEXP":"\nreExtname.REGEXP\n    Regular expression to capture a filename extension.\n","reExtname.REGEXP_POSIX":"\nreExtname.REGEXP_POSIX\n    Regular expression to capture a POSIX filename extension.\n","reExtname.REGEXP_WIN32":"\nreExtname.REGEXP_WIN32\n    Regular expression to capture a Windows filename extension.\n","reExtnamePosix":"\nreExtnamePosix\n    Returns a regular expression to capture a POSIX filename extension.\n","reExtnamePosix.REGEXP":"\nreExtnamePosix.REGEXP\n    Regular expression to capture a POSIX filename extension.\n","reExtnameWindows":"\nreExtnameWindows\n    Returns a regular expression to capture a Windows filename extension.\n","reExtnameWindows.REGEXP":"\nreExtnameWindows.REGEXP\n    Regular expression to capture a Windows filename extension.\n","reFilename":"\nreFilename( [platform:string] )\n    Regular expression to split a filename.\n","reFilename.REGEXP":"\nreFilename.REGEXP\n    Regular expression to split a filename.\n","reFilename.REGEXP_POSIX":"\nreFilename.REGEXP_POSIX\n    Regular expression to split a POSIX filename.\n","reFilename.REGEXP_WIN32":"\nreFilename.REGEXP_WIN32\n    Regular expression to split a Windows filename.\n","reFilenamePosix":"\nreFilenamePosix()\n    Returns a regular expression to split a POSIX filename.\n","reFilenamePosix.REGEXP":"\nreFilenamePosix.REGEXP\n    Regular expression to split a POSIX filename.\n","reFilenameWindows":"\nreFilenameWindows()\n    Returns a regular expression to split a Windows filename.\n","reFilenameWindows.REGEXP":"\nreFilenameWindows.REGEXP\n    Regular expression to split a Windows filename.\n","reFromString":"\nreFromString( str:string )\n    Parses a regular expression string and returns a new regular expression.\n","reFunctionName":"\nreFunctionName()\n    Return a regular expression to capture a function name.\n","reFunctionName.REGEXP":"\nreFunctionName.REGEXP\n    Regular expression to capture a function name.\n","regexp2json":"\nregexp2json( re:RegExp )\n    Returns a JSON representation of a regular expression.\n","reim":"\nreim( z:Complex128 )\n    Returns the real and imaginary components of a double-precision complex\n    floating-point number.\n","reimf":"\nreimf( z:Complex64 )\n    Returns the real and imaginary components of a single-precision complex\n    floating-point number.\n","rejectArguments":"\nrejectArguments( fcn:Function, predicate:Function[, thisArg:any] )\n    Returns a function that applies arguments to a provided function according\n    to a predicate function.\n","removeFirst":"\nremoveFirst( str:string[, n:integer][, options:Object] )\n    Removes the first character(s) of a `string`.\n","removeLast":"\nremoveLast( str:string[, n:integer][, options:Object] )\n    Removes the last character(s) of a `string`.\n","removePunctuation":"\nremovePunctuation( str:string )\n    Removes punctuation characters from a `string`.\n","removeUTF8BOM":"\nremoveUTF8BOM( str:string )\n    Removes a UTF-8 byte order mark (BOM) from the beginning of a `string`.\n","removeWords":"\nremoveWords( str:string, words:Array<string>[, ignoreCase:boolean] )\n    Removes all occurrences of the given words from a `string`.\n","rename":"\nrename( oldPath:string|Buffer, newPath:string|Buffer, clbk:Function )\n    Asynchronously renames a file.\n","rename.sync":"\nrename.sync( oldPath:string|Buffer, newPath:string|Buffer )\n    Synchronously renames a file.\n","reNativeFunction":"\nreNativeFunction()\n    Returns a regular expression to match a native function.\n","reNativeFunction.REGEXP":"\nreNativeFunction.REGEXP\n    Regular expression to match a native function.\n","reorderArguments":"\nreorderArguments( fcn:Function, indices:Array<integer>[, thisArg:any] )\n    Returns a function that invokes a provided function with reordered\n    arguments.\n","repeat":"\nrepeat( str:string, n:integer )\n    Repeats a string `n` times and returns the concatenated result.\n","replace":"\nreplace( str:string, search:string|RegExp, newval:string|Function )\n    Replaces search occurrences with a replacement string.\n","replaceBefore":"\nreplaceBefore( str, search, replacement )\n    Replaces the substring before the first occurrence of a specified search\n    string. \n","reRegExp":"\nreRegExp()\n    Returns a regular expression to parse a regular expression string.\n","reRegExp.REGEXP":"\nreRegExp.REGEXP\n    Regular expression to parse a regular expression string.\n","rescape":"\nrescape( str:string )\n    Escapes a regular expression string.\n","reSemVer":"\nreSemVer()\n    Returns a regular expression to match a semantic version string.\n","reSemVer.REGEXP":"\nreSemVer.REGEXP\n    Regular expression to match a semantic version string.\n","resolveParentPath":"\nresolveParentPath( path:string[, options:Object], clbk:Function )\n    Asynchronously resolves a path by walking parent directories.\n","resolveParentPath.sync":"\nresolveParentPath.sync( path:string[, options:Object] )\n    Synchronously resolves a path by walking parent directories.\n","resolveParentPathBy":"\nresolveParentPathBy( path:string[, options:Object], predicate:Function, \n  clbk:Function )\n    Asynchronously resolves a path according to a predicate function by walking\n    parent directories.\n","resolveParentPathBy.sync":"\nresolveParentPathBy.sync( path:string[, options:Object], predicate:Function )\n    Synchronously resolves a path according to a predicate function by walking\n    parent directories.\n","reUncPath":"\nreUncPath()\n    Return a regular expression to parse a UNC path.\n","reUncPath.REGEXP":"\nreUncPath.REGEXP\n    Regular expression to parse a UNC path.\n","reUtf16SurrogatePair":"\nreUtf16SurrogatePair()\n    Returns a regular expression to match a UTF-16 surrogate pair.\n","reUtf16SurrogatePair.REGEXP":"\nreUtf16SurrogatePair.REGEXP\n    Regular expression to match a UTF-16 surrogate pair.\n","reUtf16UnpairedSurrogate":"\nreUtf16UnpairedSurrogate()\n    Returns a regular expression to match an unpaired UTF-16 surrogate.\n","reUtf16UnpairedSurrogate.REGEXP":"\nreUtf16UnpairedSurrogate.REGEXP\n    Regular expression to match an unpaired UTF-16 surrogate.\n","reverseArguments":"\nreverseArguments( fcn:Function[, thisArg:any] )\n    Returns a function that invokes a provided function with arguments in\n    reverse order.\n","reverseString":"\nreverseString( str:string[, options:Object] )\n    Reverses a string.\n","reviveBasePRNG":"\nreviveBasePRNG( key:string, value:any )\n    Revives a JSON-serialized pseudorandom number generator (PRNG).\n","reviveBuffer":"\nreviveBuffer( key:string, value:any )\n    Revives a JSON-serialized Buffer.\n","reviveComplex":"\nreviveComplex( key:string, value:any )\n    Revives a JSON-serialized complex number.\n","reviveComplex64":"\nreviveComplex64( key:string, value:any )\n    Revives a JSON-serialized 64-bit complex number.\n","reviveComplex128":"\nreviveComplex128( key:string, value:any )\n    Revives a JSON-serialized 128-bit complex number.\n","reviveError":"\nreviveError( key:string, value:any )\n    Revives a JSON-serialized error object.\n","reviveRegExp":"\nreviveRegExp( key:string, value:any )\n    Revives a JSON-serialized regular expression.\n","reviveTypedArray":"\nreviveTypedArray( key:string, value:any )\n    Revives a JSON-serialized typed array.\n","reWhitespace":"\nreWhitespace( [options:Object] )\n    Returns a regular expression to match a white space character.\n","reWhitespace.REGEXP":"\nreWhitespace.REGEXP\n    Regular expression to match a white space character.\n","reWhitespace.REGEXP_CAPTURE":"\nreWhitespace.REGEXP_CAPTURE\n    Regular expression to capture white space characters.\n","rpad":"\nrpad( str:string, len:integer[, pad:string] )\n    Right pads a `string` such that the padded `string` has a length of at least\n    `len`.\n","rtrim":"\nrtrim( str:string )\n    Trims whitespace from the end of a string.\n","rtrimN":"\nrtrimN( str:string, n:integer[, chars:Array|string] )\n    Trims `n` characters from the end of a string.\n","safeintmax":"\nsafeintmax( dtype:string )\n    Returns the maximum safe integer capable of being represented by a numeric\n    real type.\n","safeintmin":"\nsafeintmin( dtype:string )\n    Returns the minimum safe integer capable of being represented by a numeric\n    real type.\n","sample":"\nsample( x:ArrayLike[, options:Object] )\n    Samples elements from an array-like object.\n","sample.factory":"\nsample.factory( [pool:ArrayLike, ][options:Object] )\n    Returns a function to sample elements from an array-like object.\n","SAVOY_STOPWORDS_FIN":"\nSAVOY_STOPWORDS_FIN()\n    Returns a list of Finnish stop words.\n","SAVOY_STOPWORDS_FR":"\nSAVOY_STOPWORDS_FR()\n    Returns a list of French stop words.\n","SAVOY_STOPWORDS_GER":"\nSAVOY_STOPWORDS_GER()\n    Returns a list of German stop words.\n","SAVOY_STOPWORDS_IT":"\nSAVOY_STOPWORDS_IT()\n    Returns a list of Italian stop words.\n","SAVOY_STOPWORDS_POR":"\nSAVOY_STOPWORDS_POR()\n    Returns a list of Portuguese stop words.\n","SAVOY_STOPWORDS_SP":"\nSAVOY_STOPWORDS_SP()\n    Returns a list of Spanish stop words.\n","SAVOY_STOPWORDS_SWE":"\nSAVOY_STOPWORDS_SWE()\n    Returns a list of Swedish stop words.\n","scalar2array":"\nscalar2array( value:any[, dtype:string] )\n    Returns a single-element array containing a provided scalar value.\n","scalar2ndarray":"\nscalar2ndarray( value:any[, options:Object] )\n    Returns a zero-dimensional ndarray containing a provided scalar value.\n","sdot":"\nsdot( x:ndarray, y:ndarray[, dim:integer] )\n    Computes the dot product of two single-precision floating-point vectors.\n","SECONDS_IN_DAY":"\nSECONDS_IN_DAY\n    Number of seconds in a day.\n","SECONDS_IN_HOUR":"\nSECONDS_IN_HOUR\n    Number of seconds in an hour.\n","SECONDS_IN_MINUTE":"\nSECONDS_IN_MINUTE\n    Number of seconds in a minute.\n","SECONDS_IN_WEEK":"\nSECONDS_IN_WEEK\n    Number of seconds in a week.\n","secondsInMonth":"\nsecondsInMonth( [month:string|Date|integer[, year:integer]] )\n    Returns the number of seconds in a month.\n","secondsInYear":"\nsecondsInYear( [value:integer|Date] )\n    Returns the number of seconds in a year according to the Gregorian calendar.\n","sentencize":"\nsentencize( str:string )\n    Splits a string into an array of sentences.\n","seq2slice":"\nseq2slice( str:string, len:integer, strict:boolean )\n    Converts a subsequence string to a Slice object.\n","setConfigurableReadOnly":"\nsetConfigurableReadOnly( obj:Object, prop:string|symbol, value:any )\n    Defines a configurable read-only property.\n","setConfigurableReadOnlyAccessor":"\nsetConfigurableReadOnlyAccessor( obj:Object, prop:string|symbol, \n  getter:Function )\n    Defines a configurable read-only accessor.\n","setConfigurableReadWriteAccessor":"\nsetConfigurableReadWriteAccessor( obj:Object, prop:string|symbol, \n  getter:Function, setter:Function )\n    Defines a configurable property having read-write accessors.\n","setConfigurableWriteOnlyAccessor":"\nsetConfigurableWriteOnlyAccessor( obj:Object, prop:string|symbol, \n  setter:Function )\n    Defines a configurable write-only accessor.\n","setMemoizedConfigurableReadOnly":"\nsetMemoizedConfigurableReadOnly( obj:Object, prop:string|symbol, fcn:Function )\n    Defines a configurable memoized read-only object property.\n","setMemoizedReadOnly":"\nsetMemoizedReadOnly( obj:Object, prop:string|symbol, fcn:Function )\n    Defines a memoized read-only object property.\n","setNonEnumerableProperty":"\nsetNonEnumerableProperty( obj:Object, prop:string|symbol, value:any )\n    Defines a non-enumerable property.\n","setNonEnumerableReadOnly":"\nsetNonEnumerableReadOnly( obj:Object, prop:string|symbol, value:any )\n    Defines a non-enumerable read-only property.\n","setNonEnumerableReadOnlyAccessor":"\nsetNonEnumerableReadOnlyAccessor( obj:Object, prop:string|symbol, \n  getter:Function )\n    Defines a non-enumerable read-only accessor.\n","setNonEnumerableReadWriteAccessor":"\nsetNonEnumerableReadWriteAccessor( obj:Object, prop:string|symbol, \n  getter:Function, setter:Function )\n    Defines a non-enumerable property having read-write accessors.\n","setNonEnumerableWriteOnlyAccessor":"\nsetNonEnumerableWriteOnlyAccessor( obj:Object, prop:string|symbol, \n  setter:Function )\n    Defines a non-enumerable write-only accessor.\n","setReadOnly":"\nsetReadOnly( obj:Object, prop:string|symbol, value:any )\n    Defines a read-only property.\n","setReadOnlyAccessor":"\nsetReadOnlyAccessor( obj:Object, prop:string|symbol, getter:Function )\n    Defines a read-only accessor.\n","setReadWriteAccessor":"\nsetReadWriteAccessor( obj:Object, prop:string|symbol, getter:Function, \n  setter:Function )\n    Defines a property having read-write accessors.\n","setWriteOnlyAccessor":"\nsetWriteOnlyAccessor( obj:Object, prop:string|symbol, setter:Function )\n    Defines a write-only accessor.\n","SharedArrayBuffer":"\nSharedArrayBuffer( size:integer )\n    Returns a shared array buffer having a specified number of bytes.\n","SharedArrayBuffer.length":"\nSharedArrayBuffer.length\n    Number of input arguments the constructor accepts.\n","SharedArrayBuffer.prototype.byteLength":"\nSharedArrayBuffer.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the array buffer.\n","SharedArrayBuffer.prototype.slice":"\nSharedArrayBuffer.prototype.slice( [start:integer[, end:integer]] )\n    Copies the bytes of a shared array buffer to a new shared array buffer.\n","shift":"\nshift( collection:Array|TypedArray|Object )\n    Removes and returns the first element of a collection.\n","shuffle":"\nshuffle( arr:ArrayLike[, options:Object] )\n    Shuffles elements of an array-like object.\n","shuffle.factory":"\nshuffle.factory( [options:Object] )\n    Returns a function to shuffle elements of array-like objects.\n","sizeOf":"\nsizeOf( dtype:string )\n    Returns the size (in bytes) of the canonical binary representation of a\n    specified numeric type.\n","Slice":"\nSlice( [stop:integer|null|undefined] )\n    Returns a Slice.\n\nSlice( start:integer|null|undefined, stop:integer|null|undefined[, \n  step:integer|null|undefined] )\n    Returns a Slice.\n","Slice.prototype.start":"\nSlice.prototype.start\n    Read-only property returning the starting slice index.\n","Slice.prototype.stop":"\nSlice.prototype.stop\n    Read-only property returning the ending slice index.\n","Slice.prototype.step":"\nSlice.prototype.step\n    Read-only property returning the index increment.\n","Slice.prototype.toString":"\nSlice.prototype.toString()\n    Serializes a Slice as a string.\n","Slice.prototype.toJSON":"\nSlice.prototype.toJSON()\n    Serializes a Slice as a JSON object.\n","snakecase":"\nsnakecase( str:string )\n    Converts a string to snake case.\n","some":"\nsome( collection:Array|TypedArray|Object, n:number )\n    Tests whether at least `n` elements in a collection are truthy.\n","someBy":"\nsomeBy( collection:Array|TypedArray|Object, n:number, predicate:Function[, \n  thisArg:any ] )\n    Tests whether a collection contains at least `n` elements which pass a test\n    implemented by a predicate function.\n","someByAsync":"\nsomeByAsync( collection:Array|TypedArray|Object, n:number, [options:Object,] \n  predicate:Function, done:Function )\n    Tests whether a collection contains at least `n` elements which pass a test\n    implemented by a predicate function.\n","someByAsync.factory":"\nsomeByAsync.factory( [options:Object,] predicate:Function )\n    Returns a function which tests whether a collection contains at least `n`\n    elements which pass a test implemented by a predicate function.\n","someByRight":"\nsomeByRight( collection:Array|TypedArray|Object, n:number, predicate:Function[, \n  thisArg:any ] )\n    Tests whether a collection contains at least `n` elements which pass a test\n    implemented by a predicate function, iterating from right to left.\n","someByRightAsync":"\nsomeByRightAsync( collection:Array|TypedArray|Object, n:number, \n  [options:Object,] predicate:Function, done:Function )\n    Tests whether a collection contains at least `n` elements which pass a test\n    implemented by a predicate function, iterating from right to left.\n","someByRightAsync.factory":"\nsomeByRightAsync.factory( [options:Object,] predicate:Function )\n    Returns a function which tests whether a collection contains at least `n`\n    elements which pass a test implemented by a predicate function, iterating\n    from right to left.\n","someInBy":"\nsomeInBy( obj:Object, n:number, predicate:Function[, thisArg:any ] )\n    Tests whether an object contains at least `n` properties\n    (own and inherited) which pass a test\n    implemented by a predicate function.\n","someOwnBy":"\nsomeOwnBy( obj:Object, n:number, predicate:Function[, thisArg:any ] )\n    Tests whether some `own` properties of a provided object\n    satisfy a predicate function for at least `n` properties.\n","SOTU":"\nSOTU( [options:Object] )\n    Returns State of the Union (SOTU) addresses.\n","SPACHE_REVISED":"\nSPACHE_REVISED()\n    Returns a list of simple American-English words (revised Spache).\n","SPAM_ASSASSIN":"\nSPAM_ASSASSIN()\n    Returns the Spam Assassin public mail corpus.\n","SparklineBase":"\nSparklineBase( [data:ArrayLike|ndarray,] [options:Object] )\n    Returns a Sparkline instance.\n","sparsearray2iterator":"\nsparsearray2iterator( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )\n    Returns an iterator which iterates over the elements of a sparse array-like\n    object.\n","sparsearray2iteratorRight":"\nsparsearray2iteratorRight( src:ArrayLikeObject[, mapFcn:Function[, \n  thisArg:any]] )\n    Returns an iterator which iterates from right to left over the elements of a\n    sparse array-like object.\n","splitStream":"\nsplitStream( [options:Object] )\n    Returns a transform stream which splits streamed data.\n","splitStream.factory":"\nsplitStream.factory( [options:Object] )\n    Returns a function for creating transform streams for splitting streamed\n    data.\n","splitStream.objectMode":"\nsplitStream.objectMode( [options:Object] )\n    Returns an \"objectMode\" transform stream for splitting streamed data.\n","SQRT_EPS":"\nSQRT_EPS\n    Square root of double-precision floating-point epsilon.\n","SQRT_HALF":"\nSQRT_HALF\n    Square root of `1/2`.\n","SQRT_HALF_PI":"\nSQRT_HALF_PI\n    Square root of the mathematical constant `π` divided by `2`.\n","SQRT_PHI":"\nSQRT_PHI\n    Square root of the golden ratio.\n","SQRT_PI":"\nSQRT_PI\n    Square root of the mathematical constant `π`.\n","SQRT_THREE":"\nSQRT_THREE\n    Square root of `3`.\n","SQRT_TWO":"\nSQRT_TWO\n    Square root of `2`.\n","SQRT_TWO_PI":"\nSQRT_TWO_PI\n    Square root of the mathematical constant `π` times `2`.\n","SSA_US_BIRTHS_2000_2014":"\nSSA_US_BIRTHS_2000_2014()\n    Returns US birth data from 2000 to 2014, as provided by the Social Security\n    Administration.\n","sswap":"\nsswap( x:ndarray, y:ndarray[, dim:integer] )\n    Interchanges two single-precision floating-point vectors.\n","Stack":"\nStack()\n    Stack constructor.\n","standalone2pkg":"\nstandalone2pkg( pkg:string )\n    Returns the internal package name associated with a provided standalone\n    package name.\n","STANDARD_CARD_DECK":"\nSTANDARD_CARD_DECK()\n    Returns a string array containing two or three letter abbreviations for each\n    card in a standard 52-card deck.\n","startcase":"\nstartcase( str:string )\n    Capitalizes the first letter of each word in an input string.\n","startsWith":"\nstartsWith( str:string, search:string[, position:integer] )\n    Tests if a string starts with the characters of another string.\n","STOPWORDS_EN":"\nSTOPWORDS_EN()\n    Returns a list of English stop words.\n","strided.abs":"\nstrided.abs( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  dtypeY:any, y:ArrayLikeObject, strideY:integer )\n    Computes the absolute value for each element in a strided array `x` and\n    assigns the results to elements in a strided array `y`.\n","strided.abs.ndarray":"\nstrided.abs.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, \n  offsetY:integer )\n    Computes the absolute value for each element in a strided array `x` and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n","strided.abs2":"\nstrided.abs2( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  dtypeY:any, y:ArrayLikeObject, strideY:integer )\n    Computes the squared absolute value for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y`.\n","strided.abs2.ndarray":"\nstrided.abs2.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n  strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n  strideY:integer, offsetY:integer )\n    Computes the squared absolute value for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n","strided.abs2By":"\nstrided.abs2By( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the squared absolute value of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n","strided.abs2By.ndarray":"\nstrided.abs2By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the squared absolute value of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing semantics.\n","strided.absBy":"\nstrided.absBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the absolute value of each element retrieved from a strided input\n    array `x` via a callback function and assigns each result to an element in a\n    strided output array `y`.\n","strided.absBy.ndarray":"\nstrided.absBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the absolute value of each element retrieved from a strided input\n    array `x` via a callback function and assigns each result to an element in a\n    strided output array `y` using alternative indexing semantics.\n","strided.acosBy":"\nstrided.acosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the arccosine of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y`.\n","strided.acosBy.ndarray":"\nstrided.acosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the arccosine of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n","strided.acoshBy":"\nstrided.acoshBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the hyperbolic arccosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n","strided.acoshBy.ndarray":"\nstrided.acoshBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the hyperbolic arccosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n","strided.acotBy":"\nstrided.acotBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the inverse cotangent of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n","strided.acotBy.ndarray":"\nstrided.acotBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the inverse cotangent of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n","strided.acothBy":"\nstrided.acothBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the inverse hyperbolic cotangent of each element retrieved from an\n    input strided array `x` via a callback function and assigns each result to\n    an element in an output strided array `y`.\n","strided.acothBy.ndarray":"\nstrided.acothBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the inverse hyperbolic cotangent of each element retrieved from an\n    input strided array `x` via a callback function and assigns each result to\n    an element in an output strided array `y` using alternative indexing\n    semantics.\n","strided.acovercosBy":"\nstrided.acovercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the inverse coversed cosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n","strided.acovercosBy.ndarray":"\nstrided.acovercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the inverse coversed cosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n","strided.acoversinBy":"\nstrided.acoversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the inverse coversed sine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n","strided.acoversinBy.ndarray":"\nstrided.acoversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the inverse coversed sine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n","strided.add":"\nstrided.add( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, \n  y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )\n    Adds each element in a strided array `x` to a corresponding element in a\n    strided array `y` and assigns the results to elements in a strided array\n    `z`.\n","strided.add.ndarray":"\nstrided.add.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, \n  ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, \n  z:ArrayLikeObject, sz:integer, oz:integer )\n    Adds each element in a strided array `x` to a corresponding element in a\n    strided array `y` and assigns the results to elements in a strided array\n    `z` using alternative indexing semantics.\n","strided.addBy":"\nstrided.addBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, \n  clbk:Function[, thisArg:any] )\n    Performs element-wise addition of two strided arrays via a callback function\n    and assigns each result to an element in an output strided array.\n","strided.addBy.ndarray":"\nstrided.addBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, \n  thisArg:any] )\n    Performs element-wise addition of two strided arrays via a callback function\n    and assigns each result to an element in an output strided array using\n    alternative indexing semantics.\n","strided.ahavercosBy":"\nstrided.ahavercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the inverse half-value versed cosine of each element retrieved from\n    an input strided array `x` via a callback function and assigns each result\n    to an element in an output strided array `y`.\n","strided.ahavercosBy.ndarray":"\nstrided.ahavercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the inverse half-value versed cosine of each element retrieved from\n    an input strided array `x` via a callback function and assigns each result\n    to an element in an output strided array `y` using alternative indexing\n    semantics.\n","strided.ahaversinBy":"\nstrided.ahaversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the inverse half-value versed sine of each element retrieved from\n    an input strided array `x` via a callback function and assigns each result\n    to an element in an output strided array `y`.\n","strided.ahaversinBy.ndarray":"\nstrided.ahaversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the inverse half-value versed sine of each element retrieved from\n    an input strided array `x` via a callback function and assigns each result\n    to an element in an output strided array `y` using alternative indexing\n    semantics.\n","strided.asinBy":"\nstrided.asinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the arcsine of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y`.\n","strided.asinBy.ndarray":"\nstrided.asinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the arcsine of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n","strided.asinhBy":"\nstrided.asinhBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the hyperbolic arcsine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n","strided.asinhBy.ndarray":"\nstrided.asinhBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the hyperbolic arcsine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n","strided.atanBy":"\nstrided.atanBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the arctangent of each element retrieved from an input strided\n    array `x` via a callback function and assigns each result to an element in\n    an output strided array `y`.\n","strided.atanBy.ndarray":"\nstrided.atanBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the arctangent of each element retrieved from an input strided\n    array `x` via a callback function and assigns each result to an element in\n    an output strided array `y` using alternative indexing semantics.\n","strided.atanhBy":"\nstrided.atanhBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the hyperbolic arctangent of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n","strided.atanhBy.ndarray":"\nstrided.atanhBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the hyperbolic arctangent of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n","strided.avercosBy":"\nstrided.avercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the inverse versed cosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n","strided.avercosBy.ndarray":"\nstrided.avercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the inverse versed cosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n","strided.aversinBy":"\nstrided.aversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the inverse versed sine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n","strided.aversinBy.ndarray":"\nstrided.aversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the inverse versed sine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n","strided.besselj0By":"\nstrided.besselj0By( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the Bessel function of the first kind of order zero for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y`.\n","strided.besselj0By.ndarray":"\nstrided.besselj0By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the Bessel function of the first kind of order zero for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n","strided.besselj1By":"\nstrided.besselj1By( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the Bessel function of the first kind of order one for each element\n    retrieved from an input strided array `x` via a callback function and\n    assigns each result to an element in an output strided array `y`.\n","strided.besselj1By.ndarray":"\nstrided.besselj1By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the Bessel function of the first kind of order one for each element\n    retrieved from an input strided array `x` via a callback function and\n    assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n","strided.bessely0By":"\nstrided.bessely0By( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the Bessel function of the second kind of order zero for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y`.\n","strided.bessely0By.ndarray":"\nstrided.bessely0By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the Bessel function of the second kind of order zero for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n","strided.bessely1By":"\nstrided.bessely1By( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the Bessel function of the second kind of order one for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y`.\n","strided.bessely1By.ndarray":"\nstrided.bessely1By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the Bessel function of the second kind of order one for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n","strided.binetBy":"\nstrided.binetBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Evaluates Binet's formula extended to real numbers for each element\n    retrieved from an input strided array `x` via a callback function and\n    assigns each result to an element in an output strided array `y`.\n","strided.binetBy.ndarray":"\nstrided.binetBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Evaluates Binet's formula extended to real numbers for each element\n    retrieved from an input strided array `x` via a callback function and\n    assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n","strided.cbrt":"\nstrided.cbrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  dtypeY:any, y:ArrayLikeObject, strideY:integer )\n    Computes the cube root of each element in a strided array `x` and assigns\n    the results to elements in a strided array `y`.\n","strided.cbrt.ndarray":"\nstrided.cbrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n  strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n  strideY:integer, offsetY:integer )\n    Computes the cube root of each element in a strided array `x` and assigns\n    the results to elements in a strided array `y` using alternative indexing\n    semantics.\n","strided.cbrtBy":"\nstrided.cbrtBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the cube root of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y`.\n","strided.cbrtBy.ndarray":"\nstrided.cbrtBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the cube root of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n","strided.ceil":"\nstrided.ceil( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  dtypeY:any, y:ArrayLikeObject, strideY:integer )\n    Rounds each element in a strided array `x` toward positive infinity and\n    assigns the results to elements in a strided array `y`.\n","strided.ceil.ndarray":"\nstrided.ceil.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n  strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n  strideY:integer, offsetY:integer )\n    Rounds each element in a strided array `x` toward positive infinity and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n","strided.cosBy":"\nstrided.cosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the cosine for each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y`.\n","strided.cosBy.ndarray":"\nstrided.cosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the cosine for each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n","strided.deg2rad":"\nstrided.deg2rad( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  dtypeY:any, y:ArrayLikeObject, strideY:integer )\n    Converts each element in a strided array `x` from degrees to radians and\n    assigns the results to elements in a strided array `y`.\n","strided.deg2rad.ndarray":"\nstrided.deg2rad.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n  strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n  strideY:integer, offsetY:integer )\n    Converts each element in a strided array `x` from degrees to radians and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n","strided.dataTypes":"\nstrided.dataTypes()\n    Returns a list of strided array data types.\n","strided.dcbrtBy":"\nstrided.dcbrtBy( N:integer, x:Float64Array, sx:integer, y:Float64Array, \n  sy:integer, clbk:Function[, thisArg:any] )\n    Computes the cube root of each element retrieved from an input double-\n    precision floating-point strided array via a callback function and assigns\n    each result to an element in an output double-precision floating-point\n    strided array.\n","strided.dcbrtBy.ndarray":"\nstrided.dcbrtBy.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, \n  y:Float64Array, sy:integer, oy:integer, clbk:Function[, thisArg:any] )\n    Computes the cube root of each element retrieved from an input double-\n    precision floating-point strided array via a callback function and assigns\n    each result to an element in an output double-precision floating-point\n    strided array using alternative indexing semantics.\n","strided.dispatch":"\nstrided.dispatch( fcns:Function|ArrayLikeObject<Function>, \n  types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, \n  nout:integer )\n    Returns a strided array function interface which performs multiple dispatch.\n","strided.dispatchBy":"\nstrided.dispatchBy( fcns:Function|ArrayLikeObject<Function>, \n  types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, \n  nout:integer )\n    Returns a strided array function interface which accepts a callback function\n    and performs multiple dispatch.\n","strided.floor":"\nstrided.floor( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  dtypeY:any, y:ArrayLikeObject, strideY:integer )\n    Rounds each element in a strided array `x` toward negative infinity and\n    assigns the results to elements in a strided array `y`.\n","strided.floor.ndarray":"\nstrided.floor.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n  strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n  strideY:integer, offsetY:integer )\n    Rounds each element in a strided array `x` toward negative infinity and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n","strided.inv":"\nstrided.inv( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  dtypeY:any, y:ArrayLikeObject, strideY:integer )\n    Computes the multiplicative inverse for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y`.\n","strided.inv.ndarray":"\nstrided.inv.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, \n  offsetY:integer )\n    Computes the multiplicative inverse for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n","strided.mul":"\nstrided.mul( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, \n  y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )\n    Multiplies each element in a strided array `x` to a corresponding element in\n    a strided array `y` and assigns the results to elements in a strided array\n    `z`.\n","strided.mul.ndarray":"\nstrided.mul.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, \n  ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, \n  z:ArrayLikeObject, sz:integer, oz:integer )\n    Multiplies each element in a strided array `x` to a corresponding element in\n    a strided array `y` and assigns the results to elements in a strided array\n    `z` using alternative indexing semantics.\n","strided.mulBy":"\nstrided.mulBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, \n  clbk:Function[, thisArg:any] )\n    Performs element-wise multiplication of two strided arrays via a callback\n    function and assigns each result to an element in an output strided array.\n","strided.mulBy.ndarray":"\nstrided.mulBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, \n  thisArg:any] )\n    Performs element-wise multiplication of two strided arrays via a callback\n    function and assigns each result to an element in an output strided array\n    using alternative indexing semantics.\n","strided.ramp":"\nstrided.ramp( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  dtypeY:any, y:ArrayLikeObject, strideY:integer )\n    Evaluates the ramp function for each element in a strided array `x` and\n    assigns the results to elements in a strided array `y`.\n","strided.ramp.ndarray":"\nstrided.ramp.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n  strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n  strideY:integer, offsetY:integer )\n    Evaluates the ramp function for each element in a strided array `x` and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n","strided.rsqrt":"\nstrided.rsqrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  dtypeY:any, y:ArrayLikeObject, strideY:integer )\n    Computes the reciprocal square root for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y`.\n","strided.rsqrt.ndarray":"\nstrided.rsqrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n  strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n  strideY:integer, offsetY:integer )\n    Computes the reciprocal square root for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n","strided.sinBy":"\nstrided.sinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the sine of each element retrieved from an input strided array `x`\n    via a callback function and assigns each result to an element in an output\n    strided array `y`.\n","strided.sinBy.ndarray":"\nstrided.sinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the sine of each element retrieved from an input strided array `x`\n    via a callback function and assigns each result to an element in an output\n    strided array `y` using alternative indexing semantics.\n","strided.sqrt":"\nstrided.sqrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  dtypeY:any, y:ArrayLikeObject, strideY:integer )\n    Computes the principal square root for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y`.\n","strided.sqrt.ndarray":"\nstrided.sqrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n  strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n  strideY:integer, offsetY:integer )\n    Computes the principal square root for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n","strided.sqrtBy":"\nstrided.sqrtBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the principal square root for each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n","strided.sqrtBy.ndarray":"\nstrided.sqrtBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the principal square root for each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing semantics.\n","strided.sub":"\nstrided.sub( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, \n  y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )\n    Subtracts each element in a strided array `x` to a corresponding element in\n    a strided array `y` and assigns the results to elements in a strided array\n    `z`.\n","strided.sub.ndarray":"\nstrided.sub.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, \n  ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, \n  z:ArrayLikeObject, sz:integer, oz:integer )\n    Subtracts each element in a strided array `x` to a corresponding element in\n    a strided array `y` and assigns the results to elements in a strided array\n    `z` using alternative indexing semantics.\n","strided.subBy":"\nstrided.subBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, \n  clbk:Function[, thisArg:any] )\n    Performs element-wise subtraction of two strided arrays via a callback\n    function and assigns each result to an element in an output strided array.\n","strided.subBy.ndarray":"\nstrided.subBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, \n  thisArg:any] )\n    Performs element-wise subtraction of two strided arrays via a callback\n    function and assigns each result to an element in an output strided array\n    using alternative indexing semantics.\n","strided.trunc":"\nstrided.trunc( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  dtypeY:any, y:ArrayLikeObject, strideY:integer )\n    Rounds each element in a strided array `x` toward zero and assigns the\n    results to elements in a strided array `y`.\n","strided.trunc.ndarray":"\nstrided.trunc.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n  strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n  strideY:integer, offsetY:integer )\n    Rounds each element in a strided array `x` toward zero and assigns the\n    results to elements in a strided array `y` using alternative indexing\n    semantics.\n","stridedarray2iterator":"\nstridedarray2iterator( N:integer, src:ArrayLikeObject, stride:integer, \n  offset:integer[, mapFcn:Function[, thisArg:any]] )\n    Returns an iterator which iterates over elements of an array-like object\n    according to specified stride parameters.\n","stridedArrayStream":"\nstridedArrayStream( N:integer, buffer:ArrayLikeObject, stride:integer, \n  offset:integer[, options:Object] )\n    Creates a readable stream from a strided array-like object.\n","stridedArrayStream.factory":"\nstridedArrayStream.factory( [options:Object] )\n    Returns a function for creating readable streams from array-like objects.\n","stridedArrayStream.objectMode":"\nstridedArrayStream.objectMode( N:integer, buffer:ArrayLikeObject, \n  stride:integer, offset:integer[, options:Object] )\n    Returns an \"objectMode\" readable stream from a strided array-like object.\n","string2buffer":"\nstring2buffer( str:string[, encoding:string] )\n    Allocates a buffer containing a provided string.\n","sub2ind":"\nsub2ind( shape:ArrayLike, ...subscript:integer[, options:Object] )\n    Converts subscripts to a linear index.\n","substringAfter":"\nsubstringAfter( str:string, search:string[, fromIndex:integer] )\n    Returns the part of a string after a specified substring.\n","substringAfterLast":"\nsubstringAfterLast( str:string, search:string[, fromIndex:integer] )\n    Returns the part of a string after the last occurrence of a specified\n    substring.\n","substringBefore":"\nsubstringBefore( str:string, search:string )\n    Returns the part of a string before a specified substring.\n","substringBeforeLast":"\nsubstringBeforeLast( str:string, search:string )\n    Returns the part of a string before the last occurrence of a specified\n    substring.\n","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n    Returns a dataset consisting of labeled wireless sensor network data set\n    collected from a multi-hop wireless sensor network deployment using TelosB\n    motes.\n","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n    Returns a dataset consisting of labeled wireless sensor network data set\n    collected from a simple single-hop wireless sensor network deployment using\n    TelosB motes.\n","Symbol":"\nSymbol( [description:string] )\n    Returns a symbol.\n","tabulate":"\ntabulate( collection:Array|TypedArray|Object )\n    Generates a frequency table.\n","tabulateBy":"\ntabulateBy( collection:Array|TypedArray|Object, [options:Object,] \n  indicator:Function )\n    Generates a frequency table according to an indicator function.\n","tabulateByAsync":"\ntabulateByAsync( collection:Array|TypedArray|Object, [options:Object,] \n  indicator:Function, done:Function )\n    Generates a frequency table according to an indicator function.\n","tabulateByAsync.factory":"\ntabulateByAsync.factory( [options:Object,] indicator:Function )\n    Returns a function which generates a frequency table according to an\n    indicator function.\n","thunk":"\nthunk( fcn:Function[, ...args:any] )\n    Returns a thunk.\n","tic":"\ntic()\n    Returns a high-resolution time.\n","timeit":"\ntimeit( code:string, [options:Object,] clbk:Function )\n    Times a snippet.\n","tmpdir":"\ntmpdir()\n    Returns the directory for storing temporary files.\n","toc":"\ntoc( time:Array<integer> )\n    Returns a high-resolution time difference, where `time` is a two-element\n    array with format `[seconds, nanoseconds]`.\n","tokenize":"\ntokenize( str:string[, keepWhitespace:boolean] )\n    Tokenizes a string.\n","transformStream":"\ntransformStream( [options:Object] )\n    Returns a transform stream.\n","transformStream.factory":"\ntransformStream.factory( [options:Object] )\n    Returns a function for creating transform streams.\n","transformStream.objectMode":"\ntransformStream.objectMode( [options:Object] )\n    Returns an \"objectMode\" transform stream.\n","transformStream.ctor":"\ntransformStream.ctor( [options:Object] )\n    Returns a custom transform stream constructor.\n","trim":"\ntrim( str:string )\n    Trims whitespace from the beginning and end of a `string`.\n","truncate":"\ntruncate( str:string, len:integer[, ending:string] )\n    Truncates a string to a specified length.\n","truncateMiddle":"\ntruncateMiddle( str:string, len:integer[, seq:string] )\n    Truncates a string in the middle to a specified length.\n","trycatch":"\ntrycatch( x:Function, y:any )\n    If a function does not throw, returns the function return value; otherwise,\n    returns `y`.\n","trycatchAsync":"\ntrycatchAsync( x:Function, y:any, done:Function )\n    If a function does not return an error, invokes a callback with the function\n    result; otherwise, invokes a callback with a value `y`.\n","tryFunction":"\ntryFunction( fcn:Function[, thisArg:any] )\n    Wraps a function in a try/catch block.\n","tryRequire":"\ntryRequire( id:string )\n    Wraps `require` in a `try/catch` block.\n","trythen":"\ntrythen( x:Function, y:Function )\n    If a function does not throw, returns the function return value; otherwise,\n    returns the value returned by a second function `y`.\n","trythenAsync":"\ntrythenAsync( x:Function, y:Function, done:Function )\n    If a function does not return an error, invokes a callback with the function\n    result; otherwise, invokes a second function `y`.\n","ttest":"\nttest( x:Array<number>[, y:Array<number>][, options:Object] )\n    Computes a one-sample or paired Student's t test.\n","ttest2":"\nttest2( x:Array<number>, y:Array<number>[, options:Object] )\n    Computes a two-sample Student's t test.\n","TWO_PI":"\nTWO_PI\n    The mathematical constant `π` times `2`.\n","typedarray":"\ntypedarray( [dtype:string] )\n    Creates a typed array.\n\ntypedarray( length:integer[, dtype:string] )\n    Returns a typed array having a specified length.\n\ntypedarray( typedarray:TypedArray[, dtype:string] )\n    Creates a typed array from another typed array.\n\ntypedarray( obj:Object[, dtype:string] )\n    Creates a typed array from an array-like object or iterable.\n\ntypedarray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n  dtype:string] )\n    Returns a typed array view of an ArrayBuffer.\n","typedarray2json":"\ntypedarray2json( arr:TypedArray )\n    Returns a JSON representation of a typed array.\n","typedarrayCtors":"\ntypedarrayCtors( dtype:string )\n    Returns a typed array constructor.\n","typedarrayDataTypes":"\ntypedarrayDataTypes()\n    Returns a list of typed array data types.\n","typedarraypool":"\ntypedarraypool( [dtype:string] )\n    Returns an uninitialized typed array from a typed array memory pool.\n\ntypedarraypool( length:integer[, dtype:string] )\n    Returns an uninitialized typed array having a specified length from a typed\n    array memory pool.\n\ntypedarraypool( typedarray:TypedArray[, dtype:string] )\n    Creates a pooled typed array from another typed array.\n\ntypedarraypool( obj:Object[, dtype:string] )\n    Creates a pooled typed array from an array-like object.\n","typedarraypool.malloc":"\ntypedarraypool.malloc( [dtype:string] )\n    Returns an uninitialized typed array from a typed array memory pool.\n\ntypedarraypool.malloc( length:integer[, dtype:string] )\n    Returns a typed array having a specified length from a typed array memory\n    pool.\n\ntypedarraypool.malloc( typedarray:TypedArray[, dtype:string] )\n    Creates a pooled typed array from another typed array.\n\ntypedarraypool.malloc( obj:Object[, dtype:string] )\n    Creates a pooled typed array from an array-like object.\n","typedarraypool.calloc":"\ntypedarraypool.calloc( [dtype:string] )\n    Returns a zero-initialized typed array from a typed array memory pool.\n\ntypedarraypool.calloc( length:integer[, dtype:string] )\n    Returns a zero-initialized typed array having a specified length from a\n    typed array memory pool.\n","typedarraypool.free":"\ntypedarraypool.free( buf:TypedArray|ArrayBuffer )\n    Frees a typed array or typed array buffer for use in a future allocation.\n","typedarraypool.clear":"\ntypedarraypool.clear()\n    Clears the typed array pool allowing garbage collection of previously\n    allocated (and currently free) array buffers.\n","typedarraypool.highWaterMark":"\ntypedarraypool.highWaterMark\n    Read-only property returning the pool's high water mark.\n","typedarraypool.nbytes":"\ntypedarraypool.nbytes\n    Read-only property returning the total number of allocated bytes.\n","typedarraypool.factory":"\ntypedarraypool.factory( [options:Object] )\n    Creates a typed array pool.\n","typemax":"\ntypemax( dtype:string )\n    Returns the maximum value of a specified numeric type.\n","typemin":"\ntypemin( dtype:string )\n    Returns the minimum value of a specified numeric type.\n","typeOf":"\ntypeOf( value:any )\n    Determines a value's type.\n","UINT8_MAX":"\nUINT8_MAX\n    Maximum unsigned 8-bit integer.\n","UINT8_NUM_BYTES":"\nUINT8_NUM_BYTES\n    Size (in bytes) of an 8-bit unsigned integer.\n","Uint8Array":"\nUint8Array()\n    A typed array constructor which returns a typed array representing an array\n    of 8-bit unsigned integers in the platform byte order.\n\nUint8Array( length:integer )\n    Returns a typed array having a specified length.\n\nUint8Array( typedarray:TypedArray )\n    Creates a typed array from another typed array.\n\nUint8Array( obj:Object )\n    Creates a typed array from an array-like object or iterable.\n\nUint8Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a typed array view of an ArrayBuffer.\n","Uint8Array.from":"\nUint8Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n    Creates a new typed array from an array-like object or an iterable.\n","Uint8Array.of":"\nUint8Array.of( element0:number[, element1:number[, ...elementN:number]] )\n    Creates a new typed array from a variable number of arguments.\n","Uint8Array.BYTES_PER_ELEMENT":"\nUint8Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Uint8Array.name":"\nUint8Array.name\n    Typed array constructor name.\n","Uint8Array.prototype.buffer":"\nUint8Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n","Uint8Array.prototype.byteLength":"\nUint8Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n","Uint8Array.prototype.byteOffset":"\nUint8Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n","Uint8Array.prototype.BYTES_PER_ELEMENT":"\nUint8Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Uint8Array.prototype.length":"\nUint8Array.prototype.length\n    Read-only property which returns the number of view elements.\n","Uint8Array.prototype.copyWithin":"\nUint8Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint8Array.prototype.entries":"\nUint8Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","Uint8Array.prototype.every":"\nUint8Array.prototype.every( predicate:Function[, thisArg:Any] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n","Uint8Array.prototype.fill":"\nUint8Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n","Uint8Array.prototype.filter":"\nUint8Array.prototype.filter( predicate:Function[, thisArg:Any] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n","Uint8Array.prototype.find":"\nUint8Array.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n","Uint8Array.prototype.findIndex":"\nUint8Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n","Uint8Array.prototype.forEach":"\nUint8Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n    Invokes a callback for each array element.\n","Uint8Array.prototype.includes":"\nUint8Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a search element.\n","Uint8Array.prototype.indexOf":"\nUint8Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n","Uint8Array.prototype.join":"\nUint8Array.prototype.join( [separator:string] )\n    Serializes an array by joining all array elements as a string.\n","Uint8Array.prototype.keys":"\nUint8Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n","Uint8Array.prototype.lastIndexOf":"\nUint8Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n","Uint8Array.prototype.map":"\nUint8Array.prototype.map( fcn:Function[, thisArg:Any] )\n    Maps each array element to an element in a new typed array.\n","Uint8Array.prototype.reduce":"\nUint8Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n","Uint8Array.prototype.reduceRight":"\nUint8Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n","Uint8Array.prototype.reverse":"\nUint8Array.prototype.reverse()\n    Reverses an array *in-place*.\n","Uint8Array.prototype.set":"\nUint8Array.prototype.set( arr:ArrayLike[, offset:integer] )\n    Sets array elements.\n","Uint8Array.prototype.slice":"\nUint8Array.prototype.slice( [begin:integer[, end:integer]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n","Uint8Array.prototype.some":"\nUint8Array.prototype.some( predicate:Function[, thisArg:Any] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n","Uint8Array.prototype.sort":"\nUint8Array.prototype.sort( [compareFunction:Function] )\n    Sorts an array *in-place*.\n","Uint8Array.prototype.subarray":"\nUint8Array.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n","Uint8Array.prototype.toLocaleString":"\nUint8Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n    Serializes an array as a locale-specific string.\n","Uint8Array.prototype.toString":"\nUint8Array.prototype.toString()\n    Serializes an array as a string.\n","Uint8Array.prototype.values":"\nUint8Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n","Uint8ClampedArray":"\nUint8ClampedArray()\n    A typed array constructor which returns a typed array representing an array\n    of 8-bit unsigned integers in the platform byte order clamped to 0-255.\n\nUint8ClampedArray( length:integer )\n    Returns a typed array having a specified length.\n\nUint8ClampedArray( typedarray:TypedArray )\n    Creates a typed array from another typed array.\n\nUint8ClampedArray( obj:Object )\n    Creates a typed array from an array-like object or iterable.\n\nUint8ClampedArray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a typed array view of an ArrayBuffer.\n","Uint8ClampedArray.from":"\nUint8ClampedArray.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n    Creates a new typed array from an array-like object or an iterable.\n","Uint8ClampedArray.of":"\nUint8ClampedArray.of( element0:number[, element1:number[, ...elementN:number]] )\n    Creates a new typed array from a variable number of arguments.\n","Uint8ClampedArray.BYTES_PER_ELEMENT":"\nUint8ClampedArray.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Uint8ClampedArray.name":"\nUint8ClampedArray.name\n    Typed array constructor name.\n","Uint8ClampedArray.prototype.buffer":"\nUint8ClampedArray.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n","Uint8ClampedArray.prototype.byteLength":"\nUint8ClampedArray.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n","Uint8ClampedArray.prototype.byteOffset":"\nUint8ClampedArray.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n","Uint8ClampedArray.prototype.BYTES_PER_ELEMENT":"\nUint8ClampedArray.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Uint8ClampedArray.prototype.length":"\nUint8ClampedArray.prototype.length\n    Read-only property which returns the number of view elements.\n","Uint8ClampedArray.prototype.copyWithin":"\nUint8ClampedArray.prototype.copyWithin( target:integer, start:integer[, \n  end:integer] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint8ClampedArray.prototype.entries":"\nUint8ClampedArray.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","Uint8ClampedArray.prototype.every":"\nUint8ClampedArray.prototype.every( predicate:Function[, thisArg:Any] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n","Uint8ClampedArray.prototype.fill":"\nUint8ClampedArray.prototype.fill( value:number[, start:integer[, end:integer]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n","Uint8ClampedArray.prototype.filter":"\nUint8ClampedArray.prototype.filter( predicate:Function[, thisArg:Any] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n","Uint8ClampedArray.prototype.find":"\nUint8ClampedArray.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n","Uint8ClampedArray.prototype.findIndex":"\nUint8ClampedArray.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n","Uint8ClampedArray.prototype.forEach":"\nUint8ClampedArray.prototype.forEach( fcn:Function[, thisArg:Any] )\n    Invokes a callback for each array element.\n","Uint8ClampedArray.prototype.includes":"\nUint8ClampedArray.prototype.includes( searchElement:number[, \n  fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a search element.\n","Uint8ClampedArray.prototype.indexOf":"\nUint8ClampedArray.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n","Uint8ClampedArray.prototype.join":"\nUint8ClampedArray.prototype.join( [separator:string] )\n    Serializes an array by joining all array elements as a string.\n","Uint8ClampedArray.prototype.keys":"\nUint8ClampedArray.prototype.keys()\n    Returns an iterator for iterating over array keys.\n","Uint8ClampedArray.prototype.lastIndexOf":"\nUint8ClampedArray.prototype.lastIndexOf( searchElement:number[, \n  fromIndex:integer] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n","Uint8ClampedArray.prototype.map":"\nUint8ClampedArray.prototype.map( fcn:Function[, thisArg:Any] )\n    Maps each array element to an element in a new typed array.\n","Uint8ClampedArray.prototype.reduce":"\nUint8ClampedArray.prototype.reduce( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n","Uint8ClampedArray.prototype.reduceRight":"\nUint8ClampedArray.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n","Uint8ClampedArray.prototype.reverse":"\nUint8ClampedArray.prototype.reverse()\n    Reverses an array *in-place*.\n","Uint8ClampedArray.prototype.set":"\nUint8ClampedArray.prototype.set( arr:ArrayLike[, offset:integer] )\n    Sets array elements.\n","Uint8ClampedArray.prototype.slice":"\nUint8ClampedArray.prototype.slice( [begin:integer[, end:integer]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n","Uint8ClampedArray.prototype.some":"\nUint8ClampedArray.prototype.some( predicate:Function[, thisArg:Any] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n","Uint8ClampedArray.prototype.sort":"\nUint8ClampedArray.prototype.sort( [compareFunction:Function] )\n    Sorts an array *in-place*.\n","Uint8ClampedArray.prototype.subarray":"\nUint8ClampedArray.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n","Uint8ClampedArray.prototype.toLocaleString":"\nUint8ClampedArray.prototype.toLocaleString( [locales:string|Array[, \n  options:Object]] )\n    Serializes an array as a locale-specific string.\n","Uint8ClampedArray.prototype.toString":"\nUint8ClampedArray.prototype.toString()\n    Serializes an array as a string.\n","Uint8ClampedArray.prototype.values":"\nUint8ClampedArray.prototype.values()\n    Returns an iterator for iterating over array elements.\n","UINT16_MAX":"\nUINT16_MAX\n    Maximum unsigned 16-bit integer.\n","UINT16_NUM_BYTES":"\nUINT16_NUM_BYTES\n    Size (in bytes) of a 16-bit unsigned integer.\n","Uint16Array":"\nUint16Array()\n    A typed array constructor which returns a typed array representing an array\n    of 16-bit unsigned integers in the platform byte order.\n\nUint16Array( length:integer )\n    Returns a typed array having a specified length.\n\nUint16Array( typedarray:TypedArray )\n    Creates a typed array from another typed array.\n\nUint16Array( obj:Object )\n    Creates a typed array from an array-like object or iterable.\n\nUint16Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a typed array view of an ArrayBuffer.\n","Uint16Array.from":"\nUint16Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n    Creates a new typed array from an array-like object or an iterable.\n","Uint16Array.of":"\nUint16Array.of( element0:number[, element1:number[, ...elementN:number]] )\n    Creates a new typed array from a variable number of arguments.\n","Uint16Array.BYTES_PER_ELEMENT":"\nUint16Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Uint16Array.name":"\nUint16Array.name\n    Typed array constructor name.\n","Uint16Array.prototype.buffer":"\nUint16Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n","Uint16Array.prototype.byteLength":"\nUint16Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n","Uint16Array.prototype.byteOffset":"\nUint16Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n","Uint16Array.prototype.BYTES_PER_ELEMENT":"\nUint16Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Uint16Array.prototype.length":"\nUint16Array.prototype.length\n    Read-only property which returns the number of view elements.\n","Uint16Array.prototype.copyWithin":"\nUint16Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint16Array.prototype.entries":"\nUint16Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","Uint16Array.prototype.every":"\nUint16Array.prototype.every( predicate:Function[, thisArg:Any] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n","Uint16Array.prototype.fill":"\nUint16Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n","Uint16Array.prototype.filter":"\nUint16Array.prototype.filter( predicate:Function[, thisArg:Any] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n","Uint16Array.prototype.find":"\nUint16Array.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n","Uint16Array.prototype.findIndex":"\nUint16Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n","Uint16Array.prototype.forEach":"\nUint16Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n    Invokes a callback for each array element.\n","Uint16Array.prototype.includes":"\nUint16Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a search element.\n","Uint16Array.prototype.indexOf":"\nUint16Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n","Uint16Array.prototype.join":"\nUint16Array.prototype.join( [separator:string] )\n    Serializes an array by joining all array elements as a string.\n","Uint16Array.prototype.keys":"\nUint16Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n","Uint16Array.prototype.lastIndexOf":"\nUint16Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n","Uint16Array.prototype.map":"\nUint16Array.prototype.map( fcn:Function[, thisArg:Any] )\n    Maps each array element to an element in a new typed array.\n","Uint16Array.prototype.reduce":"\nUint16Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n","Uint16Array.prototype.reduceRight":"\nUint16Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n","Uint16Array.prototype.reverse":"\nUint16Array.prototype.reverse()\n    Reverses an array *in-place*.\n","Uint16Array.prototype.set":"\nUint16Array.prototype.set( arr:ArrayLike[, offset:integer] )\n    Sets array elements.\n","Uint16Array.prototype.slice":"\nUint16Array.prototype.slice( [begin:integer[, end:integer]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n","Uint16Array.prototype.some":"\nUint16Array.prototype.some( predicate:Function[, thisArg:Any] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n","Uint16Array.prototype.sort":"\nUint16Array.prototype.sort( [compareFunction:Function] )\n    Sorts an array *in-place*.\n","Uint16Array.prototype.subarray":"\nUint16Array.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n","Uint16Array.prototype.toLocaleString":"\nUint16Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n    Serializes an array as a locale-specific string.\n","Uint16Array.prototype.toString":"\nUint16Array.prototype.toString()\n    Serializes an array as a string.\n","Uint16Array.prototype.values":"\nUint16Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n","UINT32_MAX":"\nUINT32_MAX\n    Maximum unsigned 32-bit integer.\n","UINT32_NUM_BYTES":"\nUINT32_NUM_BYTES\n    Size (in bytes) of a 32-bit unsigned integer.\n","Uint32Array":"\nUint32Array()\n    A typed array constructor which returns a typed array representing an array\n    of 32-bit unsigned integers in the platform byte order.\n\nUint32Array( length:integer )\n    Returns a typed array having a specified length.\n\nUint32Array( typedarray:TypedArray )\n    Creates a typed array from another typed array.\n\nUint32Array( obj:Object )\n    Creates a typed array from an array-like object or iterable.\n\nUint32Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a typed array view of an ArrayBuffer.\n","Uint32Array.from":"\nUint32Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n    Creates a new typed array from an array-like object or an iterable.\n","Uint32Array.of":"\nUint32Array.of( element0:number[, element1:number[, ...elementN:number]] )\n    Creates a new typed array from a variable number of arguments.\n","Uint32Array.BYTES_PER_ELEMENT":"\nUint32Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Uint32Array.name":"\nUint32Array.name\n    Typed array constructor name.\n","Uint32Array.prototype.buffer":"\nUint32Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n","Uint32Array.prototype.byteLength":"\nUint32Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n","Uint32Array.prototype.byteOffset":"\nUint32Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n","Uint32Array.prototype.BYTES_PER_ELEMENT":"\nUint32Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Uint32Array.prototype.length":"\nUint32Array.prototype.length\n    Read-only property which returns the number of view elements.\n","Uint32Array.prototype.copyWithin":"\nUint32Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint32Array.prototype.entries":"\nUint32Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","Uint32Array.prototype.every":"\nUint32Array.prototype.every( predicate:Function[, thisArg:Any] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n","Uint32Array.prototype.fill":"\nUint32Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n","Uint32Array.prototype.filter":"\nUint32Array.prototype.filter( predicate:Function[, thisArg:Any] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n","Uint32Array.prototype.find":"\nUint32Array.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n","Uint32Array.prototype.findIndex":"\nUint32Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n","Uint32Array.prototype.forEach":"\nUint32Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n    Invokes a callback for each array element.\n","Uint32Array.prototype.includes":"\nUint32Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a search element.\n","Uint32Array.prototype.indexOf":"\nUint32Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n","Uint32Array.prototype.join":"\nUint32Array.prototype.join( [separator:string] )\n    Serializes an array by joining all array elements as a string.\n","Uint32Array.prototype.keys":"\nUint32Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n","Uint32Array.prototype.lastIndexOf":"\nUint32Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n","Uint32Array.prototype.map":"\nUint32Array.prototype.map( fcn:Function[, thisArg:Any] )\n    Maps each array element to an element in a new typed array.\n","Uint32Array.prototype.reduce":"\nUint32Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n","Uint32Array.prototype.reduceRight":"\nUint32Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n","Uint32Array.prototype.reverse":"\nUint32Array.prototype.reverse()\n    Reverses an array *in-place*.\n","Uint32Array.prototype.set":"\nUint32Array.prototype.set( arr:ArrayLike[, offset:integer] )\n    Sets array elements.\n","Uint32Array.prototype.slice":"\nUint32Array.prototype.slice( [begin:integer[, end:integer]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n","Uint32Array.prototype.some":"\nUint32Array.prototype.some( predicate:Function[, thisArg:Any] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n","Uint32Array.prototype.sort":"\nUint32Array.prototype.sort( [compareFunction:Function] )\n    Sorts an array *in-place*.\n","Uint32Array.prototype.subarray":"\nUint32Array.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n","Uint32Array.prototype.toLocaleString":"\nUint32Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n    Serializes an array as a locale-specific string.\n","Uint32Array.prototype.toString":"\nUint32Array.prototype.toString()\n    Serializes an array as a string.\n","Uint32Array.prototype.values":"\nUint32Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n","umask":"\numask( [mask:integer|string,] [options:Object] )\n    Returns the current process mask, if not provided a mask; otherwise, sets\n    the process mask and returns the previous mask.\n","uncapitalize":"\nuncapitalize( str:string )\n    Lowercases the first character of a string.\n","uncapitalizeKeys":"\nuncapitalizeKeys( obj:Object )\n    Converts the first letter of each object key to lowercase.\n","uncurry":"\nuncurry( fcn:Function[, arity:integer, ][thisArg:any] )\n    Transforms a curried function into a function invoked with multiple\n    arguments.\n","uncurryRight":"\nuncurryRight( fcn:Function[, arity:integer, ][thisArg:any] )\n    Transforms a curried function into a function invoked with multiple\n    arguments.\n","UNICODE_MAX":"\nUNICODE_MAX\n    Maximum Unicode code point.\n","UNICODE_MAX_BMP":"\nUNICODE_MAX_BMP\n    Maximum Unicode code point in the Basic Multilingual Plane (BMP).\n","UnicodeColumnChartSparkline":"\nUnicodeColumnChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n    Returns a sparkline column chart instance.\n","UnicodeLineChartSparkline":"\nUnicodeLineChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n    Returns a sparkline line chart instance.\n","UnicodeSparkline":"\nUnicodeSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n    Returns a Unicode sparkline instance.\n","UnicodeTristateChartSparkline":"\nUnicodeTristateChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n    Returns a sparkline tristate chart instance.\n","UnicodeUpDownChartSparkline":"\nUnicodeUpDownChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n    Returns a sparkline up/down chart instance.\n","UnicodeWinLossChartSparkline":"\nUnicodeWinLossChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n    Returns a sparkline win/loss chart instance.\n","unlink":"\nunlink( path:string|Buffer|integer, clbk:Function )\n    Asynchronously removes a directory entry.\n","unlink.sync":"\nunlink.sync( path:string|Buffer|integer )\n    Synchronously removes a directory entry.\n","unshift":"\nunshift( collection:Array|TypedArray|Object, ...items:any )\n    Adds one or more elements to the beginning of a collection.\n","until":"\nuntil( predicate:Function, fcn:Function[, thisArg:any] )\n    Invokes a function until a test condition is true.\n","untilAsync":"\nuntilAsync( predicate:Function, fcn:Function, done:Function[, thisArg:any] )\n    Invokes a function until a test condition is true.\n","untilEach":"\nuntilEach( collection:Array|TypedArray|Object, predicate:Function, \n  fcn:Function[, thisArg:any] )\n    Until a test condition is true, invokes a function for each element in a\n    collection.\n","untilEachRight":"\nuntilEachRight( collection:Array|TypedArray|Object, predicate:Function, \n  fcn:Function[, thisArg:any] )\n    Until a test condition is true, invokes a function for each element in a\n    collection, iterating from right to left.\n","unzip":"\nunzip( arr:Array[, idx:Array<number>] )\n    Unzips a zipped array (i.e., a nested array of tuples).\n","uppercase":"\nuppercase( str:string )\n    Converts a string to uppercase.\n","uppercaseKeys":"\nuppercaseKeys( obj:Object )\n    Converts each object key to uppercase.\n","US_STATES_ABBR":"\nUS_STATES_ABBR()\n    Returns a list of US state two-letter abbreviations in alphabetical order\n    according to state name.\n","US_STATES_CAPITALS":"\nUS_STATES_CAPITALS()\n    Returns a list of US state capitals in alphabetical order according to state\n    name.\n","US_STATES_CAPITALS_NAMES":"\nUS_STATES_CAPITALS_NAMES()\n    Returns an object mapping US state capitals to state names.\n","US_STATES_NAMES":"\nUS_STATES_NAMES()\n    Returns a list of US state names in alphabetical order.\n","US_STATES_NAMES_CAPITALS":"\nUS_STATES_NAMES_CAPITALS()\n    Returns an object mapping US state names to state capitals.\n","utf16ToUTF8Array":"\nutf16ToUTF8Array( str:string )\n    Converts a UTF-16 encoded string to an array of integers using UTF-8\n    encoding.\n","vartest":"\nvartest( x:Array<number>, y:Array<number>[, options:Object] )\n    Computes a two-sample F-test for equal variances.\n","waterfall":"\nwaterfall( fcns:Array<Function>, clbk:Function[, thisArg:any] )\n    Executes functions in series, passing the results of one function as\n    arguments to the next function.\n","waterfall.factory":"\nwaterfall.factory( fcns:Array<Function>, clbk:Function[, thisArg:any] )\n    Returns a reusable waterfall function.\n","WebAssemblyMemory":"\nWebAssemblyMemory( descriptor:Object )\n    WebAssembly memory constructor.\n","WebAssemblyMemory.prototype.buffer":"\nWebAssemblyMemory.prototype.buffer\n    Read-only property which returns the ArrayBuffer (or SharedArrayBuffer)\n    referenced by the memory instance.\n","WebAssemblyMemory.prototype.grow":"\nWebAssemblyMemory.prototype.grow( delta:integer )\n    Increases the size of the memory instance by a specified number of\n    WebAssembly pages (i.e., 64KiB).\n","whileAsync":"\nwhileAsync( predicate:Function, fcn:Function, done:Function[, thisArg:any] )\n    Invokes a function while a test condition is true.\n","whileEach":"\nwhileEach( collection:Array|TypedArray|Object, predicate:Function, \n  fcn:Function[, thisArg:any] )\n    While a test condition is true, invokes a function for each element in a\n    collection.\n","whileEachRight":"\nwhileEachRight( collection:Array|TypedArray|Object, predicate:Function, \n  fcn:Function[, thisArg:any] )\n    While a test condition is true, invokes a function for each element in a\n    collection, iterating from right to left.\n","whilst":"\nwhilst( predicate:Function, fcn:Function[, thisArg:any] )\n    Invokes a function while a test condition is true.\n","wilcoxon":"\nwilcoxon( x:Array|TypedArray[, y:Array|TypedArray][, options:Object] )\n    Computes a one-sample or paired Wilcoxon signed rank test.\n","writableProperties":"\nwritableProperties( value:any )\n    Returns an array of an object's own writable property names and symbols.\n","writablePropertiesIn":"\nwritablePropertiesIn( value:any )\n    Returns an array of an object's own and inherited writable property names\n    and symbols.\n","writablePropertyNames":"\nwritablePropertyNames( value:any )\n    Returns an array of an object's own writable property names.\n","writablePropertyNamesIn":"\nwritablePropertyNamesIn( value:any )\n    Returns an array of an object's own and inherited writable property names.\n","writablePropertySymbols":"\nwritablePropertySymbols( value:any )\n    Returns an array of an object's own writable symbol properties.\n","writablePropertySymbolsIn":"\nwritablePropertySymbolsIn( value:any )\n    Returns an array of an object's own and inherited writable symbol\n    properties.\n","writeFile":"\nwriteFile( file:string|Buffer|integer, data:string|Buffer[, \n  options:Object|string], clbk:Function )\n    Asynchronously writes data to a file.\n","writeFile.sync":"\nwriteFile.sync( file:string|Buffer|integer, data:string|Buffer[, \n  options:Object|string] )\n    Synchronously writes data to a file.\n","zip":"\nzip( ...arr:Array[, options:Object] )\n    Generates array tuples from input arrays.\n","ztest":"\nztest( x:Array<number>, sigma:number[, options:Object] )\n    Computes a one-sample z-test.\n","ztest2":"\nztest2( x:Array<number>, y:Array<number>, sigmax:number, sigmay:number[, \n  options:Object] )\n    Computes a two-sample z-test.\n"}
diff --git a/lib/node_modules/@stdlib/repl/signature/data/data.csv b/lib/node_modules/@stdlib/repl/signature/data/data.csv
index 04f473f6110e..ff7316e2b5c4 100644
--- a/lib/node_modules/@stdlib/repl/signature/data/data.csv
+++ b/lib/node_modules/@stdlib/repl/signature/data/data.csv
@@ -1735,10 +1735,10 @@ base.strided.dmax,"base.strided.dmax( N, x, strideX )"
 base.strided.dmax.ndarray,"base.strided.dmax.ndarray( N, x, strideX, offsetX )"
 base.strided.dmaxabs,"base.strided.dmaxabs( N, x, strideX )"
 base.strided.dmaxabs.ndarray,"base.strided.dmaxabs.ndarray( N, x, strideX, offsetX )"
-base.strided.dmaxabssorted,"base.strided.dmaxabssorted( N, x, stride )"
-base.strided.dmaxabssorted.ndarray,"base.strided.dmaxabssorted.ndarray( N, x, stride, offset )"
-base.strided.dmaxsorted,"base.strided.dmaxsorted( N, x, stride )"
-base.strided.dmaxsorted.ndarray,"base.strided.dmaxsorted.ndarray( N, x, stride, offset )"
+base.strided.dmaxabssorted,"base.strided.dmaxabssorted( N, x, strideX )"
+base.strided.dmaxabssorted.ndarray,"base.strided.dmaxabssorted.ndarray( N, x, strideX, offsetX )"
+base.strided.dmaxsorted,"base.strided.dmaxsorted( N, x, strideX )"
+base.strided.dmaxsorted.ndarray,"base.strided.dmaxsorted.ndarray( N, x, strideX, offsetX )"
 base.strided.dmean,"base.strided.dmean( N, x, stride )"
 base.strided.dmean.ndarray,"base.strided.dmean.ndarray( N, x, stride, offset )"
 base.strided.dmeankbn,"base.strided.dmeankbn( N, x, stride )"
@@ -1765,16 +1765,16 @@ base.strided.dmeanvarpn,"base.strided.dmeanvarpn( N, c, x, strideX, out, strideO
 base.strided.dmeanvarpn.ndarray,"base.strided.dmeanvarpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )"
 base.strided.dmeanwd,"base.strided.dmeanwd( N, x, stride )"
 base.strided.dmeanwd.ndarray,"base.strided.dmeanwd.ndarray( N, x, stride, offset )"
-base.strided.dmediansorted,"base.strided.dmediansorted( N, x, stride )"
-base.strided.dmediansorted.ndarray,"base.strided.dmediansorted.ndarray( N, x, stride, offset )"
+base.strided.dmediansorted,"base.strided.dmediansorted( N, x, strideX )"
+base.strided.dmediansorted.ndarray,"base.strided.dmediansorted.ndarray( N, x, strideX, offsetX )"
 base.strided.dmidrange,"base.strided.dmidrange( N, x, strideX )"
 base.strided.dmidrange.ndarray,"base.strided.dmidrange.ndarray( N, x, strideX, offsetX )"
 base.strided.dmin,"base.strided.dmin( N, x, strideX )"
 base.strided.dmin.ndarray,"base.strided.dmin.ndarray( N, x, strideX, offsetX )"
 base.strided.dminabs,"base.strided.dminabs( N, x, strideX )"
 base.strided.dminabs.ndarray,"base.strided.dminabs.ndarray( N, x, strideX, offsetX )"
-base.strided.dminsorted,"base.strided.dminsorted( N, x, stride )"
-base.strided.dminsorted.ndarray,"base.strided.dminsorted.ndarray( N, x, stride, offset )"
+base.strided.dminsorted,"base.strided.dminsorted( N, x, strideX )"
+base.strided.dminsorted.ndarray,"base.strided.dminsorted.ndarray( N, x, strideX, offsetX )"
 base.strided.dmskabs,"base.strided.dmskabs( N, x, sx, m, sm, y, sy )"
 base.strided.dmskabs.ndarray,"base.strided.dmskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )"
 base.strided.dmskabs2,"base.strided.dmskabs2( N, x, sx, m, sm, y, sy )"
@@ -1969,12 +1969,12 @@ base.strided.dstdevwd,"base.strided.dstdevwd( N, correction, x, stride )"
 base.strided.dstdevwd.ndarray,"base.strided.dstdevwd.ndarray( N, correction, x, stride, offset )"
 base.strided.dstdevyc,"base.strided.dstdevyc( N, correction, x, stride )"
 base.strided.dstdevyc.ndarray,"base.strided.dstdevyc.ndarray( N, correction, x, stride, offset )"
-base.strided.dsum,"base.strided.dsum( N, x, stride )"
-base.strided.dsum.ndarray,"base.strided.dsum.ndarray( N, x, stride, offset )"
+base.strided.dsum,"base.strided.dsum( N, x, strideX )"
+base.strided.dsum.ndarray,"base.strided.dsum.ndarray( N, x, strideX, offsetX )"
 base.strided.dsumkbn,"base.strided.dsumkbn( N, x, strideX )"
 base.strided.dsumkbn.ndarray,"base.strided.dsumkbn.ndarray( N, x, strideX, offsetX )"
-base.strided.dsumkbn2,"base.strided.dsumkbn2( N, x, stride )"
-base.strided.dsumkbn2.ndarray,"base.strided.dsumkbn2.ndarray( N, x, stride, offset )"
+base.strided.dsumkbn2,"base.strided.dsumkbn2( N, x, strideX )"
+base.strided.dsumkbn2.ndarray,"base.strided.dsumkbn2.ndarray( N, x, strideX, offsetX )"
 base.strided.dsumors,"base.strided.dsumors( N, x, stride )"
 base.strided.dsumors.ndarray,"base.strided.dsumors.ndarray( N, x, stride, offset )"
 base.strided.dsumpw,"base.strided.dsumpw( N, x, stride )"
@@ -2013,8 +2013,8 @@ base.strided.gapx,"base.strided.gapx( N, alpha, x, stride )"
 base.strided.gapx.ndarray,"base.strided.gapx.ndarray( N, alpha, x, stride, offset )"
 base.strided.gapxsum,"base.strided.gapxsum( N, alpha, x, stride )"
 base.strided.gapxsum.ndarray,"base.strided.gapxsum.ndarray( N, alpha, x, stride, offset )"
-base.strided.gapxsumkbn,"base.strided.gapxsumkbn( N, alpha, x, stride )"
-base.strided.gapxsumkbn.ndarray,"base.strided.gapxsumkbn.ndarray( N, alpha, x, stride, offset )"
+base.strided.gapxsumkbn,"base.strided.gapxsumkbn( N, alpha, x, strideX )"
+base.strided.gapxsumkbn.ndarray,"base.strided.gapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )"
 base.strided.gapxsumkbn2,"base.strided.gapxsumkbn2( N, alpha, x, stride )"
 base.strided.gapxsumkbn2.ndarray,"base.strided.gapxsumkbn2.ndarray( N, alpha, x, stride, offset )"
 base.strided.gapxsumors,"base.strided.gapxsumors( N, alpha, x, stride )"
@@ -2290,10 +2290,10 @@ base.strided.smax,"base.strided.smax( N, x, strideX )"
 base.strided.smax.ndarray,"base.strided.smax.ndarray( N, x, strideX, offsetX )"
 base.strided.smaxabs,"base.strided.smaxabs( N, x, strideX )"
 base.strided.smaxabs.ndarray,"base.strided.smaxabs.ndarray( N, x, strideX, offsetX )"
-base.strided.smaxabssorted,"base.strided.smaxabssorted( N, x, stride )"
-base.strided.smaxabssorted.ndarray,"base.strided.smaxabssorted.ndarray( N, x, stride, offset )"
-base.strided.smaxsorted,"base.strided.smaxsorted( N, x, stride )"
-base.strided.smaxsorted.ndarray,"base.strided.smaxsorted.ndarray( N, x, stride, offset )"
+base.strided.smaxabssorted,"base.strided.smaxabssorted( N, x, strideX )"
+base.strided.smaxabssorted.ndarray,"base.strided.smaxabssorted.ndarray( N, x, strideX, offsetX )"
+base.strided.smaxsorted,"base.strided.smaxsorted( N, x, strideX )"
+base.strided.smaxsorted.ndarray,"base.strided.smaxsorted.ndarray( N, x, strideX, offsetX )"
 base.strided.smean,"base.strided.smean( N, x, stride )"
 base.strided.smean.ndarray,"base.strided.smean.ndarray( N, x, stride, offset )"
 base.strided.smeankbn,"base.strided.smeankbn( N, x, stride )"
diff --git a/lib/node_modules/@stdlib/repl/signature/data/data.json b/lib/node_modules/@stdlib/repl/signature/data/data.json
index 5774c63cff49..9928c058303a 100644
--- a/lib/node_modules/@stdlib/repl/signature/data/data.json
+++ b/lib/node_modules/@stdlib/repl/signature/data/data.json
@@ -1 +1 @@
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)"],["isFunction","isFunction( value )"],["isFunctionArray","isFunctionArray( value )"],["isGeneratorObject","isGeneratorObject( value )"],["isGeneratorObjectLike","isGeneratorObjectLike( value )"],["isgzipBuffer","isgzipBuffer( value )"],["isHexString","isHexString( str )"],["isInfinite","isInfinite( value )"],["isInfinite.isPrimitive","isInfinite.isPrimitive( value )"],["isInfinite.isObject","isInfinite.isObject( value )"],["isInheritedProperty","isInheritedProperty( value, property )"],["isInt8Array","isInt8Array( value )"],["isInt16Array","isInt16Array( value )"],["isInt32Array","isInt32Array( value )"],["isInteger","isInteger( value )"],["isInteger.isPrimitive","isInteger.isPrimitive( value )"],["isInteger.isObject","isInteger.isObject( value )"],["isIntegerArray","isIntegerArray( value )"],["isIntegerArray.primitives","isIntegerArray.primitives( value )"],["isIntegerArray.objects","isIntegerArray.objects( value )"],["isIterableLike","isIterableLike( value )"],["isIteratorLike","isIteratorLike( value )"],["isJSON","isJSON( value )"],["isKebabcase","isKebabcase( value )"],["isLeapYear","isLeapYear( value )"],["isLocalhost","isLocalhost( value )"],["isLowercase","isLowercase( value )"],["isMatrixLike","isMatrixLike( value )"],["isMethod","isMethod( value, property )"],["isMethodIn","isMethodIn( value, property )"],["isMultiSlice","isMultiSlice( value )"],["isNamedTypedTupleLike","isNamedTypedTupleLike( value )"],["isnan","isnan( value )"],["isnan.isPrimitive","isnan.isPrimitive( value )"],["isnan.isObject","isnan.isObject( value )"],["isNaNArray","isNaNArray( value )"],["isNaNArray.primitives","isNaNArray.primitives( value )"],["isNaNArray.objects","isNaNArray.objects( value )"],["isNativeFunction","isNativeFunction( value )"],["isndarrayLike","isndarrayLike( value )"],["isndarrayLikeWithDataType","isndarrayLikeWithDataType( value, dtype )"],["isNegativeFinite","isNegativeFinite( value 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value )"],["isNegativeZero.isPrimitive","isNegativeZero.isPrimitive( value )"],["isNegativeZero.isObject","isNegativeZero.isObject( value )"],["isNodeBuiltin","isNodeBuiltin( str )"],["isNodeDuplexStreamLike","isNodeDuplexStreamLike( value )"],["isNodeReadableStreamLike","isNodeReadableStreamLike( value )"],["isNodeREPL","isNodeREPL()"],["isNodeStreamLike","isNodeStreamLike( value )"],["isNodeTransformStreamLike","isNodeTransformStreamLike( value )"],["isNodeWritableStreamLike","isNodeWritableStreamLike( value )"],["isNonConfigurableProperty","isNonConfigurableProperty( value, property )"],["isNonConfigurablePropertyIn","isNonConfigurablePropertyIn( value, property )"],["isNonEnumerableProperty","isNonEnumerableProperty( value, property )"],["isNonEnumerablePropertyIn","isNonEnumerablePropertyIn( value, property )"],["isNonNegativeFinite","isNonNegativeFinite( value )"],["isNonNegativeFinite.isPrimitive","isNonNegativeFinite.isPrimitive( value 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)"],["isPersymmetricMatrix","isPersymmetricMatrix( value )"],["isPlainObject","isPlainObject( value )"],["isPlainObjectArray","isPlainObjectArray( value )"],["isPositiveFinite","isPositiveFinite( value )"],["isPositiveFinite.isPrimitive","isPositiveFinite.isPrimitive( value )"],["isPositiveFinite.isObject","isPositiveFinite.isObject( value )"],["isPositiveInteger","isPositiveInteger( value )"],["isPositiveInteger.isPrimitive","isPositiveInteger.isPrimitive( value )"],["isPositiveInteger.isObject","isPositiveInteger.isObject( value )"],["isPositiveIntegerArray","isPositiveIntegerArray( value )"],["isPositiveIntegerArray.primitives","isPositiveIntegerArray.primitives( value )"],["isPositiveIntegerArray.objects","isPositiveIntegerArray.objects( value )"],["isPositiveNumber","isPositiveNumber( value )"],["isPositiveNumber.isPrimitive","isPositiveNumber.isPrimitive( value )"],["isPositiveNumber.isObject","isPositiveNumber.isObject( value )"],["isPositiveNumberArray","isPositiveNumberArray( value )"],["isPositiveNumberArray.primitives","isPositiveNumberArray.primitives( value )"],["isPositiveNumberArray.objects","isPositiveNumberArray.objects( value )"],["isPositiveZero","isPositiveZero( value )"],["isPositiveZero.isPrimitive","isPositiveZero.isPrimitive( value )"],["isPositiveZero.isObject","isPositiveZero.isObject( value )"],["isPrime","isPrime( value )"],["isPrime.isPrimitive","isPrime.isPrimitive( value )"],["isPrime.isObject","isPrime.isObject( value )"],["isPrimitive","isPrimitive( value )"],["isPrimitiveArray","isPrimitiveArray( value )"],["isPRNGLike","isPRNGLike( value )"],["isProbability","isProbability( value )"],["isProbability.isPrimitive","isProbability.isPrimitive( value )"],["isProbability.isObject","isProbability.isObject( value )"],["isProbabilityArray","isProbabilityArray( value )"],["isProbabilityArray.primitives","isProbabilityArray.primitives( value )"],["isProbabilityArray.objects","isProbabilityArray.objects( value )"],["isPropertyKey","isPropertyKey( value )"],["isPrototypeOf","isPrototypeOf( value, proto )"],["isRaggedNestedArray","isRaggedNestedArray( value )"],["isRangeError","isRangeError( value )"],["isReadableProperty","isReadableProperty( value, property )"],["isReadablePropertyIn","isReadablePropertyIn( value, property )"],["isReadOnlyProperty","isReadOnlyProperty( value, property )"],["isReadOnlyPropertyIn","isReadOnlyPropertyIn( value, property )"],["isReadWriteProperty","isReadWriteProperty( value, property )"],["isReadWritePropertyIn","isReadWritePropertyIn( value, property )"],["isReferenceError","isReferenceError( value )"],["isRegExp","isRegExp( value )"],["isRegExpString","isRegExpString( value )"],["isRelativePath","isRelativePath( value )"],["isRelativePath.posix","isRelativePath.posix( value )"],["isRelativePath.win32","isRelativePath.win32( value )"],["isRelativeURI","isRelativeURI( value )"],["isSafeInteger","isSafeInteger( value )"],["isSafeInteger.isPrimitive","isSafeInteger.isPrimitive( value )"],["isSafeInteger.isObject","isSafeInteger.isObject( value )"],["isSafeIntegerArray","isSafeIntegerArray( value )"],["isSafeIntegerArray.primitives","isSafeIntegerArray.primitives( value )"],["isSafeIntegerArray.objects","isSafeIntegerArray.objects( value )"],["isSameArray","isSameArray( v1, v2 )"],["isSameArrayLike","isSameArrayLike( v1, v2 )"],["isSameComplex64","isSameComplex64( v1, v2 )"],["isSameComplex64Array","isSameComplex64Array( v1, v2 )"],["isSameComplex128","isSameComplex128( v1, v2 )"],["isSameComplex128Array","isSameComplex128Array( v1, v2 )"],["isSameDateObject","isSameDateObject( d1, d2 )"],["isSameFloat32Array","isSameFloat32Array( v1, v2 )"],["isSameFloat64Array","isSameFloat64Array( v1, v2 )"],["isSameNativeClass","isSameNativeClass( a, b )"],["isSameType","isSameType( a, b )"],["isSameValue","isSameValue( a, b )"],["isSameValueZero","isSameValueZero( a, b )"],["isSemVer","isSemVer( value )"],["isSharedArrayBuffer","isSharedArrayBuffer( value )"],["isSkewCentrosymmetricMatrix","isSkewCentrosymmetricMatrix( value )"],["isSkewPersymmetricMatrix","isSkewPersymmetricMatrix( value )"],["isSkewSymmetricMatrix","isSkewSymmetricMatrix( value )"],["isSlice","isSlice( value )"],["isSnakecase","isSnakecase( value )"],["isSquareMatrix","isSquareMatrix( value )"],["isSquareNumber","isSquareNumber( value )"],["isSquareNumber.isPrimitive","isSquareNumber.isPrimitive( value )"],["isSquareNumber.isObject","isSquareNumber.isObject( value )"],["isSquareTriangularNumber","isSquareTriangularNumber( value )"],["isSquareTriangularNumber.isPrimitive","isSquareTriangularNumber.isPrimitive( value )"],["isSquareTriangularNumber.isObject","isSquareTriangularNumber.isObject( value )"],["isStartcase","isStartcase( value )"],["isStrictEqual","isStrictEqual( a, b )"],["isString","isString( value )"],["isString.isPrimitive","isString.isPrimitive( value )"],["isString.isObject","isString.isObject( value )"],["isStringArray","isStringArray( value )"],["isStringArray.primitives","isStringArray.primitives( value )"],["isStringArray.objects","isStringArray.objects( value )"],["isSymbol","isSymbol( value )"],["isSymbolArray","isSymbolArray( value )"],["isSymbolArray.primitives","isSymbolArray.primitives( value )"],["isSymbolArray.objects","isSymbolArray.objects( value )"],["isSymmetricMatrix","isSymmetricMatrix( value )"],["isSyntaxError","isSyntaxError( value )"],["isTriangularNumber","isTriangularNumber( value )"],["isTriangularNumber.isPrimitive","isTriangularNumber.isPrimitive( value )"],["isTriangularNumber.isObject","isTriangularNumber.isObject( value )"],["isTruthy","isTruthy( value )"],["isTruthyArray","isTruthyArray( value )"],["isTypedArray","isTypedArray( value )"],["isTypedArrayLength","isTypedArrayLength( value )"],["isTypedArrayLike","isTypedArrayLike( value )"],["isTypeError","isTypeError( value )"],["isUint8Array","isUint8Array( value )"],["isUint8ClampedArray","isUint8ClampedArray( value )"],["isUint16Array","isUint16Array( value )"],["isUint32Array","isUint32Array( value )"],["isUNCPath","isUNCPath( value )"],["isUndefined","isUndefined( value )"],["isUndefinedOrNull","isUndefinedOrNull( value )"],["isUnityProbabilityArray","isUnityProbabilityArray( value )"],["isUppercase","isUppercase( value )"],["isURI","isURI( value )"],["isURIError","isURIError( value )"],["isVectorLike","isVectorLike( value )"],["isWebAssemblyMemory","isWebAssemblyMemory( value )"],["isWellFormedString","isWellFormedString( str )"],["isWellFormedString.isPrimitive","isWellFormedString.isPrimitive( str )"],["isWellFormedString.isObject","isWellFormedString.isObject( str )"],["isWhitespace","isWhitespace( str )"],["isWritableProperty","isWritableProperty( value, property )"],["isWritablePropertyIn","isWritablePropertyIn( value, property )"],["isWriteOnlyProperty","isWriteOnlyProperty( value, property )"],["isWriteOnlyPropertyIn","isWriteOnlyPropertyIn( value, property )"],["iterAbs","iterAbs( iterator )"],["iterAbs2","iterAbs2( iterator )"],["iterAcos","iterAcos( iterator )"],["iterAcosh","iterAcosh( iterator )"],["iterAcot","iterAcot( iterator )"],["iterAcoth","iterAcoth( iterator )"],["iterAcovercos","iterAcovercos( iterator )"],["iterAcoversin","iterAcoversin( iterator )"],["iterAdd","iterAdd( iter0, ...iterator )"],["iterAdvance","iterAdvance( iterator[, n] )"],["iterAhavercos","iterAhavercos( iterator )"],["iterAhaversin","iterAhaversin( iterator )"],["iterAny","iterAny( iterator )"],["iterAnyBy","iterAnyBy( iterator, predicate[, thisArg ] )"],["iterAsin","iterAsin( iterator )"],["iterAsinh","iterAsinh( iterator )"],["iterAtan","iterAtan( iterator )"],["iterAtan2","iterAtan2( y, x )"],["iterAtanh","iterAtanh( iterator )"],["iterator2array","iterator2array( iterator[, out][, mapFcn[, thisArg]] )"],["iterator2arrayview","iterator2arrayview( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )"],["iterator2arrayviewRight","iterator2arrayviewRight( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )"],["iteratorStream","iteratorStream( iterator[, options] )"],["iteratorStream.factory","iteratorStream.factory( [options] )"],["iteratorStream.objectMode","iteratorStream.objectMode( iterator[, options] )"],["IteratorSymbol","IteratorSymbol"],["iterAvercos","iterAvercos( iterator )"],["iterAversin","iterAversin( iterator )"],["iterawgn","iterawgn( iterator, sigma[, options] )"],["iterawln","iterawln( iterator, sigma[, options] )"],["iterawun","iterawun( iterator, sigma[, options] )"],["iterBartlettHannPulse","iterBartlettHannPulse( [options] )"],["iterBartlettPulse","iterBartlettPulse( [options] )"],["iterBesselj0","iterBesselj0( iterator )"],["iterBesselj1","iterBesselj1( iterator )"],["iterBessely0","iterBessely0( iterator )"],["iterBessely1","iterBessely1( iterator )"],["iterBeta","iterBeta( x, y )"],["iterBetaln","iterBetaln( x, y )"],["iterBinet","iterBinet( iterator )"],["iterCbrt","iterCbrt( iterator )"],["iterCeil","iterCeil( iterator )"],["iterCeil2","iterCeil2( iterator )"],["iterCeil10","iterCeil10( iterator )"],["iterCompositesSeq","iterCompositesSeq( [options] )"],["iterConcat","iterConcat( iter0, ...iterator )"],["iterConstant","iterConstant( value[, options] )"],["iterContinuedFraction","iterContinuedFraction( iterator[, options] )"],["iterContinuedFractionSeq","iterContinuedFractionSeq( x[, options] )"],["iterCos","iterCos( iterator )"],["iterCosh","iterCosh( iterator )"],["iterCosineWave","iterCosineWave( [options] )"],["iterCosm1","iterCosm1( iterator )"],["iterCospi","iterCospi( iterator )"],["iterCounter","iterCounter( iterator )"],["iterCovercos","iterCovercos( iterator )"],["iterCoversin","iterCoversin( iterator )"],["iterCubesSeq","iterCubesSeq( [options] )"],["itercugmean","itercugmean( iterator )"],["itercuhmean","itercuhmean( iterator )"],["itercumax","itercumax( iterator )"],["itercumaxabs","itercumaxabs( iterator )"],["itercumean","itercumean( iterator )"],["itercumeanabs","itercumeanabs( iterator )"],["itercumeanabs2","itercumeanabs2( iterator )"],["itercumidrange","itercumidrange( iterator )"],["itercumin","itercumin( iterator )"],["itercuminabs","itercuminabs( iterator )"],["itercuprod","itercuprod( iterator )"],["itercurange","itercurange( iterator )"],["itercusum","itercusum( iterator )"],["itercusumabs","itercusumabs( iterator )"],["itercusumabs2","itercusumabs2( iterator )"],["iterDatespace","iterDatespace( start, stop[, N][, options] )"],["iterDedupe","iterDedupe( iterator[, limit] )"],["iterDedupeBy","iterDedupeBy( iterator, [limit,] fcn )"],["iterDeg2rad","iterDeg2rad( iterator )"],["iterDigamma","iterDigamma( iterator )"],["iterDiracComb","iterDiracComb( [options] )"],["iterDiracDelta","iterDiracDelta( iterator )"],["iterDivide","iterDivide( iter0, ...iterator )"],["iterDoWhileEach","iterDoWhileEach( iterator, predicate, fcn[, thisArg] )"],["iterEllipe","iterEllipe( iterator )"],["iterEllipk","iterEllipk( iterator )"],["iterEmpty","iterEmpty()"],["iterErf","iterErf( iterator )"],["iterErfc","iterErfc( iterator )"],["iterErfcinv","iterErfcinv( iterator )"],["iterErfinv","iterErfinv( iterator )"],["iterEta","iterEta( iterator )"],["iterEvenIntegersSeq","iterEvenIntegersSeq( [options] )"],["iterEvery","iterEvery( iterator )"],["iterEveryBy","iterEveryBy( iterator, predicate[, thisArg ] )"],["iterExp","iterExp( iterator )"],["iterExp2","iterExp2( iterator )"],["iterExp10","iterExp10( iterator )"],["iterExpit","iterExpit( iterator )"],["iterExpm1","iterExpm1( iterator )"],["iterExpm1rel","iterExpm1rel( iterator )"],["iterFactorial","iterFactorial( iterator )"],["iterFactorialln","iterFactorialln( iterator )"],["iterFactorialsSeq","iterFactorialsSeq( [options] )"],["iterFibonacciSeq","iterFibonacciSeq( [options] )"],["iterFifthPowersSeq","iterFifthPowersSeq( [options] )"],["iterFill","iterFill( iterator, value[, begin[, end]] )"],["iterFilter","iterFilter( iterator, predicate[, thisArg] )"],["iterFilterMap","iterFilterMap( iterator, fcn[, thisArg] )"],["iterFirst","iterFirst( iterator )"],["iterFlatTopPulse","iterFlatTopPulse( [options] )"],["iterFloor","iterFloor( iterator )"],["iterFloor2","iterFloor2( iterator )"],["iterFloor10","iterFloor10( iterator )"],["iterFlow","iterFlow( methods )"],["iterForEach","iterForEach( iterator, fcn[, thisArg] )"],["iterFourthPowersSeq","iterFourthPowersSeq( [options] )"],["iterFresnelc","iterFresnelc( iterator )"],["iterFresnels","iterFresnels( iterator )"],["iterGamma","iterGamma( iterator )"],["iterGamma1pm1","iterGamma1pm1( iterator )"],["iterGammaln","iterGammaln( iterator )"],["iterHacovercos","iterHacovercos( iterator )"],["iterHacoversin","iterHacoversin( iterator )"],["iterHannPulse","iterHannPulse( [options] )"],["iterHavercos","iterHavercos( iterator )"],["iterHaversin","iterHaversin( iterator )"],["iterHead","iterHead( iterator, n )"],["iterIncrspace","iterIncrspace( start, stop[, increment] )"],["iterIntegersSeq","iterIntegersSeq( [options] )"],["iterIntersection","iterIntersection( iter0, ...iterator )"],["iterIntersectionByHash","iterIntersectionByHash( iter0, ...iterator, hashFcn[, thisArg] )"],["iterInv","iterInv( iterator )"],["iterLanczosPulse","iterLanczosPulse( [options] )"],["iterLast","iterLast( iterator )"],["iterLength","iterLength( iterator )"],["iterLinspace","iterLinspace( start, stop[, N] )"],["iterLn","iterLn( iterator )"],["iterLog","iterLog( x, b )"],["iterLog1mexp","iterLog1mexp( iterator )"],["iterLog1p","iterLog1p( iterator )"],["iterLog1pexp","iterLog1pexp( iterator )"],["iterLog2","iterLog2( iterator )"],["iterLog10","iterLog10( iterator )"],["iterLogit","iterLogit( iterator )"],["iterLogspace","iterLogspace( start, stop[, N][, options] )"],["iterLucasSeq","iterLucasSeq( [options] )"],["iterMap","iterMap( iterator, fcn[, thisArg] )"],["iterMapN","iterMapN( iter0, ...iterator, fcn[, thisArg] )"],["itermax","itermax( iterator )"],["itermaxabs","itermaxabs( iterator )"],["itermean","itermean( iterator )"],["itermeanabs","itermeanabs( iterator )"],["itermeanabs2","itermeanabs2( iterator )"],["itermidrange","itermidrange( iterator )"],["itermin","itermin( iterator )"],["iterminabs","iterminabs( iterator )"],["itermmax","itermmax( iterator, W )"],["itermmaxabs","itermmaxabs( iterator, W )"],["itermmean","itermmean( iterator, W )"],["itermmeanabs","itermmeanabs( iterator, W )"],["itermmeanabs2","itermmeanabs2( iterator, W )"],["itermmidrange","itermmidrange( iterator, W )"],["itermmin","itermmin( iterator, W )"],["itermminabs","itermminabs( iterator, W )"],["iterMod","iterMod( iter0, ...iterator )"],["itermprod","itermprod( iterator, W )"],["itermrange","itermrange( iterator, W )"],["itermsum","itermsum( iterator, W )"],["itermsumabs","itermsumabs( iterator, W )"],["itermsumabs2","itermsumabs2( iterator, W )"],["iterMultiply","iterMultiply( iter0, ...iterator )"],["iterNegaFibonacciSeq","iterNegaFibonacciSeq( [options] )"],["iterNegaLucasSeq","iterNegaLucasSeq( [options] )"],["iterNegativeEvenIntegersSeq","iterNegativeEvenIntegersSeq( [options] )"],["iterNegativeIntegersSeq","iterNegativeIntegersSeq( [options] )"],["iterNegativeOddIntegersSeq","iterNegativeOddIntegersSeq( [options] )"],["iterNone","iterNone( iterator )"],["iterNoneBy","iterNoneBy( iterator, predicate[, thisArg ] )"],["iterNonFibonacciSeq","iterNonFibonacciSeq( [options] )"],["iterNonNegativeEvenIntegersSeq","iterNonNegativeEvenIntegersSeq( [options] )"],["iterNonNegativeIntegersSeq","iterNonNegativeIntegersSeq( [options] )"],["iterNonPositiveEvenIntegersSeq","iterNonPositiveEvenIntegersSeq( [options] )"],["iterNonPositiveIntegersSeq","iterNonPositiveIntegersSeq( [options] )"],["iterNonSquaresSeq","iterNonSquaresSeq( [options] )"],["iterNth","iterNth( iterator, n )"],["iterOddIntegersSeq","iterOddIntegersSeq( [options] )"],["iterPeriodicSinc","iterPeriodicSinc( n[, options] )"],["iterPipeline","iterPipeline( iterFcn[, ...iterFcn] )"],["iterPop","iterPop( iterator[, clbk[, thisArg]] )"],["iterPositiveEvenIntegersSeq","iterPositiveEvenIntegersSeq( [options] )"],["iterPositiveIntegersSeq","iterPositiveIntegersSeq( [options] )"],["iterPositiveOddIntegersSeq","iterPositiveOddIntegersSeq( [options] )"],["iterPow","iterPow( base, exponent )"],["iterPrimesSeq","iterPrimesSeq( [options] )"],["iterprod","iterprod( iterator )"],["iterPulse","iterPulse( [options] )"],["iterPush","iterPush( iterator, ...items )"],["iterRad2deg","iterRad2deg( iterator )"],["iterRamp","iterRamp( iterator )"],["iterrange","iterrange( iterator )"],["iterReject","iterReject( iterator, predicate[, thisArg] )"],["iterReplicate","iterReplicate( iterator, n )"],["iterReplicateBy","iterReplicateBy( iterator, fcn[, thisArg] )"],["iterRound","iterRound( iterator )"],["iterRound2","iterRound2( iterator )"],["iterRound10","iterRound10( iterator )"],["iterRsqrt","iterRsqrt( iterator 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fcn[, offset[, eager]][, thisArg] )"],["iterSubtract","iterSubtract( iter0, ...iterator )"],["itersum","itersum( iterator )"],["itersumabs","itersumabs( iterator )"],["itersumabs2","itersumabs2( iterator )"],["iterTan","iterTan( iterator )"],["iterTanh","iterTanh( iterator )"],["iterThunk","iterThunk( iterFcn[, ...args] )"],["iterTriangleWave","iterTriangleWave( [options] )"],["iterTriangularSeq","iterTriangularSeq( [options] )"],["iterTribonnaciSeq","iterTribonnaciSeq( [options] )"],["iterTrigamma","iterTrigamma( iterator )"],["iterTrunc","iterTrunc( iterator )"],["iterTrunc2","iterTrunc2( iterator )"],["iterTrunc10","iterTrunc10( iterator )"],["iterUnion","iterUnion( iter0, ...iterator )"],["iterUnique","iterUnique( iterator )"],["iterUniqueBy","iterUniqueBy( iterator, predicate[, thisArg] )"],["iterUniqueByHash","iterUniqueByHash( iterator, hashFcn[, thisArg] )"],["iterUnitspace","iterUnitspace( start[, stop] )"],["iterUnshift","iterUnshift( iterator, ...items 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dim[, options] )"],["nditerStacks","nditerStacks( x, dims[, options] )"],["nditerSubarrays","nditerSubarrays( x, ndims[, options] )"],["nditerValues","nditerValues( x[, options] )"],["ndmap","ndmap( x[, options], fcn[, thisArg] )"],["ndreject","ndreject( x[, options], predicate[, thisArg] )"],["ndslice","ndslice( x, ...s[, options] )"],["ndsliceAssign","ndsliceAssign( x, y, ...s[, options] )"],["ndsliceDimension","ndsliceDimension( x, dim, slice[, options] )"],["ndsliceDimensionFrom","ndsliceDimensionFrom( x, dim, start[, options] )"],["ndsliceDimensionTo","ndsliceDimensionTo( x, dim, stop[, options] )"],["ndsliceFrom","ndsliceFrom( x, ...start[, options] )"],["ndsliceTo","ndsliceTo( x, ...stop[, options] )"],["ndzeros","ndzeros( shape[, options] )"],["ndzerosLike","ndzerosLike( x[, options] )"],["nextGraphemeClusterBreak","nextGraphemeClusterBreak( str[, fromIndex] )"],["nextTick","nextTick( clbk[, ...args] 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prop, value )"],["setNonEnumerableReadOnly","setNonEnumerableReadOnly( obj, prop, value )"],["setNonEnumerableReadOnlyAccessor","setNonEnumerableReadOnlyAccessor( obj, prop, getter )"],["setNonEnumerableReadWriteAccessor","setNonEnumerableReadWriteAccessor( obj, prop, getter, setter )"],["setNonEnumerableWriteOnlyAccessor","setNonEnumerableWriteOnlyAccessor( obj, prop, setter )"],["setReadOnly","setReadOnly( obj, prop, value )"],["setReadOnlyAccessor","setReadOnlyAccessor( obj, prop, getter )"],["setReadWriteAccessor","setReadWriteAccessor( obj, prop, getter, setter )"],["setWriteOnlyAccessor","setWriteOnlyAccessor( obj, prop, setter )"],["SharedArrayBuffer","SharedArrayBuffer( size )"],["SharedArrayBuffer.length","SharedArrayBuffer.length"],["SharedArrayBuffer.prototype.byteLength","SharedArrayBuffer.prototype.byteLength"],["SharedArrayBuffer.prototype.slice","SharedArrayBuffer.prototype.slice( [start[, end]] )"],["shift","shift( collection )"],["shuffle","shuffle( arr[, options] 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obj, n, predicate[, thisArg ] )"],["SOTU","SOTU( [options] )"],["SPACHE_REVISED","SPACHE_REVISED()"],["SPAM_ASSASSIN","SPAM_ASSASSIN()"],["SparklineBase","SparklineBase( [data,] [options] )"],["sparsearray2iterator","sparsearray2iterator( src[, mapFcn[, thisArg]] )"],["sparsearray2iteratorRight","sparsearray2iteratorRight( src[, mapFcn[, thisArg]] )"],["splitStream","splitStream( [options] )"],["splitStream.factory","splitStream.factory( [options] )"],["splitStream.objectMode","splitStream.objectMode( [options] )"],["SQRT_EPS","SQRT_EPS"],["SQRT_HALF","SQRT_HALF"],["SQRT_HALF_PI","SQRT_HALF_PI"],["SQRT_PHI","SQRT_PHI"],["SQRT_PI","SQRT_PI"],["SQRT_THREE","SQRT_THREE"],["SQRT_TWO","SQRT_TWO"],["SQRT_TWO_PI","SQRT_TWO_PI"],["SSA_US_BIRTHS_2000_2014","SSA_US_BIRTHS_2000_2014()"],["sswap","sswap( x, y[, dim] )"],["Stack","Stack()"],["standalone2pkg","standalone2pkg( pkg )"],["STANDARD_CARD_DECK","STANDARD_CARD_DECK()"],["startcase","startcase( str )"],["startsWith","startsWith( str, search[, position] )"],["STOPWORDS_EN","STOPWORDS_EN()"],["strided.abs","strided.abs( N, dtypeX, x, strideX, dtypeY, y, strideY )"],["strided.abs.ndarray","strided.abs.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )"],["strided.abs2","strided.abs2( N, dtypeX, x, strideX, dtypeY, y, strideY )"],["strided.abs2.ndarray","strided.abs2.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )"],["strided.abs2By","strided.abs2By( N, x, sx, y, sy, clbk[, thisArg] )"],["strided.abs2By.ndarray","strided.abs2By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )"],["strided.absBy","strided.absBy( N, x, sx, y, sy, clbk[, thisArg] )"],["strided.absBy.ndarray","strided.absBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )"],["strided.acosBy","strided.acosBy( N, x, sx, y, sy, clbk[, thisArg] )"],["strided.acosBy.ndarray","strided.acosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )"],["strided.acoshBy","strided.acoshBy( N, x, sx, y, sy, clbk[, thisArg] 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strideX, offsetX, dtypeY, y, strideY, offsetY )"],["strided.inv","strided.inv( N, dtypeX, x, strideX, dtypeY, y, strideY )"],["strided.inv.ndarray","strided.inv.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )"],["strided.mul","strided.mul( N, dx, x, sx, dy, y, sy, dz, z, sz )"],["strided.mul.ndarray","strided.mul.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )"],["strided.mulBy","strided.mulBy( N, x, sx, y, sy, z, sz, clbk[, thisArg] )"],["strided.mulBy.ndarray","strided.mulBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )"],["strided.ramp","strided.ramp( N, dtypeX, x, strideX, dtypeY, y, strideY )"],["strided.ramp.ndarray","strided.ramp.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )"],["strided.rsqrt","strided.rsqrt( N, dtypeX, x, strideX, dtypeY, y, strideY )"],["strided.rsqrt.ndarray","strided.rsqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )"],["strided.sinBy","strided.sinBy( N, x, sx, y, sy, clbk[, thisArg] )"],["strided.sinBy.ndarray","strided.sinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )"],["strided.sqrt","strided.sqrt( N, dtypeX, x, strideX, dtypeY, y, strideY )"],["strided.sqrt.ndarray","strided.sqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )"],["strided.sqrtBy","strided.sqrtBy( N, x, sx, y, sy, clbk[, thisArg] )"],["strided.sqrtBy.ndarray","strided.sqrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )"],["strided.sub","strided.sub( N, dx, x, sx, dy, y, sy, dz, z, sz )"],["strided.sub.ndarray","strided.sub.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )"],["strided.subBy","strided.subBy( N, x, sx, y, sy, z, sz, clbk[, thisArg] )"],["strided.subBy.ndarray","strided.subBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )"],["strided.trunc","strided.trunc( N, dtypeX, x, strideX, dtypeY, y, strideY )"],["strided.trunc.ndarray","strided.trunc.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )"],["stridedarray2iterator","stridedarray2iterator( N, src, stride, offset[, mapFcn[, thisArg]] )"],["stridedArrayStream","stridedArrayStream( N, buffer, stride, offset[, options] )"],["stridedArrayStream.factory","stridedArrayStream.factory( [options] )"],["stridedArrayStream.objectMode","stridedArrayStream.objectMode( N, buffer, stride, offset[, options] )"],["string2buffer","string2buffer( str[, encoding] )"],["sub2ind","sub2ind( shape, ...subscript[, options] )"],["substringAfter","substringAfter( str, search[, fromIndex] )"],["substringAfterLast","substringAfterLast( str, search[, fromIndex] )"],["substringBefore","substringBefore( str, search )"],["substringBeforeLast","substringBeforeLast( str, search )"],["SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()"],["SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()"],["Symbol","Symbol( [description] )"],["tabulate","tabulate( collection 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)"],["trythenAsync","trythenAsync( x, y, done )"],["ttest","ttest( x[, y][, options] )"],["ttest2","ttest2( x, y[, options] )"],["TWO_PI","TWO_PI"],["typedarray","typedarray( [dtype] )"],["typedarray","typedarray( length[, dtype] )"],["typedarray","typedarray( typedarray[, dtype] )"],["typedarray","typedarray( obj[, dtype] )"],["typedarray","typedarray( buffer[, byteOffset[, length]][, dtype] )"],["typedarray2json","typedarray2json( arr )"],["typedarrayCtors","typedarrayCtors( dtype )"],["typedarrayDataTypes","typedarrayDataTypes()"],["typedarraypool","typedarraypool( [dtype] )"],["typedarraypool","typedarraypool( length[, dtype] )"],["typedarraypool","typedarraypool( typedarray[, dtype] )"],["typedarraypool","typedarraypool( obj[, dtype] )"],["typedarraypool.malloc","typedarraypool.malloc( [dtype] )"],["typedarraypool.malloc","typedarraypool.malloc( length[, dtype] )"],["typedarraypool.malloc","typedarraypool.malloc( typedarray[, dtype] )"],["typedarraypool.malloc","typedarraypool.malloc( obj[, dtype] )"],["typedarraypool.calloc","typedarraypool.calloc( [dtype] )"],["typedarraypool.calloc","typedarraypool.calloc( length[, dtype] )"],["typedarraypool.free","typedarraypool.free( buf )"],["typedarraypool.clear","typedarraypool.clear()"],["typedarraypool.highWaterMark","typedarraypool.highWaterMark"],["typedarraypool.nbytes","typedarraypool.nbytes"],["typedarraypool.factory","typedarraypool.factory( [options] )"],["typemax","typemax( dtype )"],["typemin","typemin( dtype )"],["typeOf","typeOf( value )"],["UINT8_MAX","UINT8_MAX"],["UINT8_NUM_BYTES","UINT8_NUM_BYTES"],["Uint8Array","Uint8Array()"],["Uint8Array","Uint8Array( length )"],["Uint8Array","Uint8Array( typedarray )"],["Uint8Array","Uint8Array( obj )"],["Uint8Array","Uint8Array( buffer[, byteOffset[, length]] )"],["Uint8Array.from","Uint8Array.from( src[, map[, thisArg]] )"],["Uint8Array.of","Uint8Array.of( element0[, element1[, ...elementN]] )"],["Uint8Array.BYTES_PER_ELEMENT","Uint8Array.BYTES_PER_ELEMENT"],["Uint8Array.name","Uint8Array.name"],["Uint8Array.prototype.buffer","Uint8Array.prototype.buffer"],["Uint8Array.prototype.byteLength","Uint8Array.prototype.byteLength"],["Uint8Array.prototype.byteOffset","Uint8Array.prototype.byteOffset"],["Uint8Array.prototype.BYTES_PER_ELEMENT","Uint8Array.prototype.BYTES_PER_ELEMENT"],["Uint8Array.prototype.length","Uint8Array.prototype.length"],["Uint8Array.prototype.copyWithin","Uint8Array.prototype.copyWithin( target, start[, end] )"],["Uint8Array.prototype.entries","Uint8Array.prototype.entries()"],["Uint8Array.prototype.every","Uint8Array.prototype.every( predicate[, thisArg] )"],["Uint8Array.prototype.fill","Uint8Array.prototype.fill( value[, start[, end]] )"],["Uint8Array.prototype.filter","Uint8Array.prototype.filter( predicate[, thisArg] )"],["Uint8Array.prototype.find","Uint8Array.prototype.find( predicate[, thisArg] )"],["Uint8Array.prototype.findIndex","Uint8Array.prototype.findIndex( predicate[, thisArg] )"],["Uint8Array.prototype.forEach","Uint8Array.prototype.forEach( fcn[, thisArg] )"],["Uint8Array.prototype.includes","Uint8Array.prototype.includes( searchElement[, fromIndex] )"],["Uint8Array.prototype.indexOf","Uint8Array.prototype.indexOf( searchElement[, fromIndex] )"],["Uint8Array.prototype.join","Uint8Array.prototype.join( [separator] )"],["Uint8Array.prototype.keys","Uint8Array.prototype.keys()"],["Uint8Array.prototype.lastIndexOf","Uint8Array.prototype.lastIndexOf( searchElement[, fromIndex] )"],["Uint8Array.prototype.map","Uint8Array.prototype.map( fcn[, thisArg] )"],["Uint8Array.prototype.reduce","Uint8Array.prototype.reduce( fcn[, initialValue] )"],["Uint8Array.prototype.reduceRight","Uint8Array.prototype.reduceRight( fcn[, initialValue] )"],["Uint8Array.prototype.reverse","Uint8Array.prototype.reverse()"],["Uint8Array.prototype.set","Uint8Array.prototype.set( arr[, offset] )"],["Uint8Array.prototype.slice","Uint8Array.prototype.slice( [begin[, end]] )"],["Uint8Array.prototype.some","Uint8Array.prototype.some( predicate[, thisArg] )"],["Uint8Array.prototype.sort","Uint8Array.prototype.sort( [compareFunction] )"],["Uint8Array.prototype.subarray","Uint8Array.prototype.subarray( [begin[, end]] )"],["Uint8Array.prototype.toLocaleString","Uint8Array.prototype.toLocaleString( [locales[, options]] )"],["Uint8Array.prototype.toString","Uint8Array.prototype.toString()"],["Uint8Array.prototype.values","Uint8Array.prototype.values()"],["Uint8ClampedArray","Uint8ClampedArray()"],["Uint8ClampedArray","Uint8ClampedArray( length )"],["Uint8ClampedArray","Uint8ClampedArray( typedarray )"],["Uint8ClampedArray","Uint8ClampedArray( obj )"],["Uint8ClampedArray","Uint8ClampedArray( buffer[, byteOffset[, length]] )"],["Uint8ClampedArray.from","Uint8ClampedArray.from( src[, map[, thisArg]] )"],["Uint8ClampedArray.of","Uint8ClampedArray.of( element0[, element1[, ...elementN]] )"],["Uint8ClampedArray.BYTES_PER_ELEMENT","Uint8ClampedArray.BYTES_PER_ELEMENT"],["Uint8ClampedArray.name","Uint8ClampedArray.name"],["Uint8ClampedArray.prototype.buffer","Uint8ClampedArray.prototype.buffer"],["Uint8ClampedArray.prototype.byteLength","Uint8ClampedArray.prototype.byteLength"],["Uint8ClampedArray.prototype.byteOffset","Uint8ClampedArray.prototype.byteOffset"],["Uint8ClampedArray.prototype.BYTES_PER_ELEMENT","Uint8ClampedArray.prototype.BYTES_PER_ELEMENT"],["Uint8ClampedArray.prototype.length","Uint8ClampedArray.prototype.length"],["Uint8ClampedArray.prototype.copyWithin","Uint8ClampedArray.prototype.copyWithin( target, start[, end] )"],["Uint8ClampedArray.prototype.entries","Uint8ClampedArray.prototype.entries()"],["Uint8ClampedArray.prototype.every","Uint8ClampedArray.prototype.every( predicate[, thisArg] )"],["Uint8ClampedArray.prototype.fill","Uint8ClampedArray.prototype.fill( value[, start[, end]] )"],["Uint8ClampedArray.prototype.filter","Uint8ClampedArray.prototype.filter( predicate[, thisArg] )"],["Uint8ClampedArray.prototype.find","Uint8ClampedArray.prototype.find( predicate[, thisArg] )"],["Uint8ClampedArray.prototype.findIndex","Uint8ClampedArray.prototype.findIndex( predicate[, thisArg] )"],["Uint8ClampedArray.prototype.forEach","Uint8ClampedArray.prototype.forEach( fcn[, thisArg] )"],["Uint8ClampedArray.prototype.includes","Uint8ClampedArray.prototype.includes( searchElement[, fromIndex] )"],["Uint8ClampedArray.prototype.indexOf","Uint8ClampedArray.prototype.indexOf( searchElement[, fromIndex] )"],["Uint8ClampedArray.prototype.join","Uint8ClampedArray.prototype.join( [separator] )"],["Uint8ClampedArray.prototype.keys","Uint8ClampedArray.prototype.keys()"],["Uint8ClampedArray.prototype.lastIndexOf","Uint8ClampedArray.prototype.lastIndexOf( searchElement[, fromIndex] )"],["Uint8ClampedArray.prototype.map","Uint8ClampedArray.prototype.map( fcn[, thisArg] )"],["Uint8ClampedArray.prototype.reduce","Uint8ClampedArray.prototype.reduce( fcn[, initialValue] )"],["Uint8ClampedArray.prototype.reduceRight","Uint8ClampedArray.prototype.reduceRight( fcn[, initialValue] )"],["Uint8ClampedArray.prototype.reverse","Uint8ClampedArray.prototype.reverse()"],["Uint8ClampedArray.prototype.set","Uint8ClampedArray.prototype.set( arr[, offset] )"],["Uint8ClampedArray.prototype.slice","Uint8ClampedArray.prototype.slice( [begin[, end]] )"],["Uint8ClampedArray.prototype.some","Uint8ClampedArray.prototype.some( predicate[, thisArg] )"],["Uint8ClampedArray.prototype.sort","Uint8ClampedArray.prototype.sort( [compareFunction] )"],["Uint8ClampedArray.prototype.subarray","Uint8ClampedArray.prototype.subarray( [begin[, end]] )"],["Uint8ClampedArray.prototype.toLocaleString","Uint8ClampedArray.prototype.toLocaleString( [locales[, options]] )"],["Uint8ClampedArray.prototype.toString","Uint8ClampedArray.prototype.toString()"],["Uint8ClampedArray.prototype.values","Uint8ClampedArray.prototype.values()"],["UINT16_MAX","UINT16_MAX"],["UINT16_NUM_BYTES","UINT16_NUM_BYTES"],["Uint16Array","Uint16Array()"],["Uint16Array","Uint16Array( length )"],["Uint16Array","Uint16Array( typedarray )"],["Uint16Array","Uint16Array( obj )"],["Uint16Array","Uint16Array( buffer[, byteOffset[, length]] )"],["Uint16Array.from","Uint16Array.from( src[, map[, thisArg]] )"],["Uint16Array.of","Uint16Array.of( element0[, element1[, ...elementN]] )"],["Uint16Array.BYTES_PER_ELEMENT","Uint16Array.BYTES_PER_ELEMENT"],["Uint16Array.name","Uint16Array.name"],["Uint16Array.prototype.buffer","Uint16Array.prototype.buffer"],["Uint16Array.prototype.byteLength","Uint16Array.prototype.byteLength"],["Uint16Array.prototype.byteOffset","Uint16Array.prototype.byteOffset"],["Uint16Array.prototype.BYTES_PER_ELEMENT","Uint16Array.prototype.BYTES_PER_ELEMENT"],["Uint16Array.prototype.length","Uint16Array.prototype.length"],["Uint16Array.prototype.copyWithin","Uint16Array.prototype.copyWithin( target, start[, end] )"],["Uint16Array.prototype.entries","Uint16Array.prototype.entries()"],["Uint16Array.prototype.every","Uint16Array.prototype.every( predicate[, thisArg] )"],["Uint16Array.prototype.fill","Uint16Array.prototype.fill( value[, start[, end]] )"],["Uint16Array.prototype.filter","Uint16Array.prototype.filter( predicate[, thisArg] )"],["Uint16Array.prototype.find","Uint16Array.prototype.find( predicate[, thisArg] )"],["Uint16Array.prototype.findIndex","Uint16Array.prototype.findIndex( predicate[, thisArg] )"],["Uint16Array.prototype.forEach","Uint16Array.prototype.forEach( fcn[, thisArg] )"],["Uint16Array.prototype.includes","Uint16Array.prototype.includes( searchElement[, fromIndex] )"],["Uint16Array.prototype.indexOf","Uint16Array.prototype.indexOf( searchElement[, fromIndex] )"],["Uint16Array.prototype.join","Uint16Array.prototype.join( [separator] )"],["Uint16Array.prototype.keys","Uint16Array.prototype.keys()"],["Uint16Array.prototype.lastIndexOf","Uint16Array.prototype.lastIndexOf( searchElement[, fromIndex] )"],["Uint16Array.prototype.map","Uint16Array.prototype.map( fcn[, thisArg] )"],["Uint16Array.prototype.reduce","Uint16Array.prototype.reduce( fcn[, initialValue] )"],["Uint16Array.prototype.reduceRight","Uint16Array.prototype.reduceRight( fcn[, initialValue] )"],["Uint16Array.prototype.reverse","Uint16Array.prototype.reverse()"],["Uint16Array.prototype.set","Uint16Array.prototype.set( arr[, offset] )"],["Uint16Array.prototype.slice","Uint16Array.prototype.slice( [begin[, end]] )"],["Uint16Array.prototype.some","Uint16Array.prototype.some( predicate[, thisArg] )"],["Uint16Array.prototype.sort","Uint16Array.prototype.sort( [compareFunction] )"],["Uint16Array.prototype.subarray","Uint16Array.prototype.subarray( [begin[, end]] )"],["Uint16Array.prototype.toLocaleString","Uint16Array.prototype.toLocaleString( [locales[, options]] )"],["Uint16Array.prototype.toString","Uint16Array.prototype.toString()"],["Uint16Array.prototype.values","Uint16Array.prototype.values()"],["UINT32_MAX","UINT32_MAX"],["UINT32_NUM_BYTES","UINT32_NUM_BYTES"],["Uint32Array","Uint32Array()"],["Uint32Array","Uint32Array( length )"],["Uint32Array","Uint32Array( typedarray )"],["Uint32Array","Uint32Array( obj )"],["Uint32Array","Uint32Array( buffer[, byteOffset[, length]] )"],["Uint32Array.from","Uint32Array.from( src[, map[, thisArg]] )"],["Uint32Array.of","Uint32Array.of( element0[, element1[, ...elementN]] )"],["Uint32Array.BYTES_PER_ELEMENT","Uint32Array.BYTES_PER_ELEMENT"],["Uint32Array.name","Uint32Array.name"],["Uint32Array.prototype.buffer","Uint32Array.prototype.buffer"],["Uint32Array.prototype.byteLength","Uint32Array.prototype.byteLength"],["Uint32Array.prototype.byteOffset","Uint32Array.prototype.byteOffset"],["Uint32Array.prototype.BYTES_PER_ELEMENT","Uint32Array.prototype.BYTES_PER_ELEMENT"],["Uint32Array.prototype.length","Uint32Array.prototype.length"],["Uint32Array.prototype.copyWithin","Uint32Array.prototype.copyWithin( target, start[, end] )"],["Uint32Array.prototype.entries","Uint32Array.prototype.entries()"],["Uint32Array.prototype.every","Uint32Array.prototype.every( predicate[, thisArg] )"],["Uint32Array.prototype.fill","Uint32Array.prototype.fill( value[, start[, end]] )"],["Uint32Array.prototype.filter","Uint32Array.prototype.filter( predicate[, thisArg] )"],["Uint32Array.prototype.find","Uint32Array.prototype.find( predicate[, thisArg] )"],["Uint32Array.prototype.findIndex","Uint32Array.prototype.findIndex( predicate[, thisArg] )"],["Uint32Array.prototype.forEach","Uint32Array.prototype.forEach( fcn[, thisArg] )"],["Uint32Array.prototype.includes","Uint32Array.prototype.includes( searchElement[, fromIndex] )"],["Uint32Array.prototype.indexOf","Uint32Array.prototype.indexOf( searchElement[, fromIndex] )"],["Uint32Array.prototype.join","Uint32Array.prototype.join( [separator] )"],["Uint32Array.prototype.keys","Uint32Array.prototype.keys()"],["Uint32Array.prototype.lastIndexOf","Uint32Array.prototype.lastIndexOf( searchElement[, fromIndex] )"],["Uint32Array.prototype.map","Uint32Array.prototype.map( fcn[, thisArg] )"],["Uint32Array.prototype.reduce","Uint32Array.prototype.reduce( fcn[, initialValue] )"],["Uint32Array.prototype.reduceRight","Uint32Array.prototype.reduceRight( fcn[, initialValue] )"],["Uint32Array.prototype.reverse","Uint32Array.prototype.reverse()"],["Uint32Array.prototype.set","Uint32Array.prototype.set( arr[, offset] )"],["Uint32Array.prototype.slice","Uint32Array.prototype.slice( [begin[, end]] )"],["Uint32Array.prototype.some","Uint32Array.prototype.some( predicate[, thisArg] )"],["Uint32Array.prototype.sort","Uint32Array.prototype.sort( [compareFunction] )"],["Uint32Array.prototype.subarray","Uint32Array.prototype.subarray( [begin[, end]] )"],["Uint32Array.prototype.toLocaleString","Uint32Array.prototype.toLocaleString( [locales[, options]] )"],["Uint32Array.prototype.toString","Uint32Array.prototype.toString()"],["Uint32Array.prototype.values","Uint32Array.prototype.values()"],["umask","umask( [mask,] [options] )"],["uncapitalize","uncapitalize( str )"],["uncapitalizeKeys","uncapitalizeKeys( obj )"],["uncurry","uncurry( fcn[, arity, ][thisArg] )"],["uncurryRight","uncurryRight( fcn[, arity, ][thisArg] )"],["UNICODE_MAX","UNICODE_MAX"],["UNICODE_MAX_BMP","UNICODE_MAX_BMP"],["UnicodeColumnChartSparkline","UnicodeColumnChartSparkline( [data,] [options] )"],["UnicodeLineChartSparkline","UnicodeLineChartSparkline( [data,] [options] )"],["UnicodeSparkline","UnicodeSparkline( [data,] [options] )"],["UnicodeTristateChartSparkline","UnicodeTristateChartSparkline( [data,] [options] )"],["UnicodeUpDownChartSparkline","UnicodeUpDownChartSparkline( [data,] [options] )"],["UnicodeWinLossChartSparkline","UnicodeWinLossChartSparkline( [data,] [options] )"],["unlink","unlink( path, clbk )"],["unlink.sync","unlink.sync( path )"],["unshift","unshift( collection, ...items )"],["until","until( predicate, fcn[, thisArg] )"],["untilAsync","untilAsync( predicate, fcn, done[, thisArg] )"],["untilEach","untilEach( collection, predicate, fcn[, thisArg] )"],["untilEachRight","untilEachRight( collection, predicate, fcn[, thisArg] )"],["unzip","unzip( arr[, idx] )"],["uppercase","uppercase( str )"],["uppercaseKeys","uppercaseKeys( obj )"],["US_STATES_ABBR","US_STATES_ABBR()"],["US_STATES_CAPITALS","US_STATES_CAPITALS()"],["US_STATES_CAPITALS_NAMES","US_STATES_CAPITALS_NAMES()"],["US_STATES_NAMES","US_STATES_NAMES()"],["US_STATES_NAMES_CAPITALS","US_STATES_NAMES_CAPITALS()"],["utf16ToUTF8Array","utf16ToUTF8Array( str )"],["vartest","vartest( x, y[, options] )"],["waterfall","waterfall( fcns, clbk[, thisArg] )"],["waterfall.factory","waterfall.factory( fcns, clbk[, thisArg] )"],["WebAssemblyMemory","WebAssemblyMemory( descriptor )"],["WebAssemblyMemory.prototype.buffer","WebAssemblyMemory.prototype.buffer"],["WebAssemblyMemory.prototype.grow","WebAssemblyMemory.prototype.grow( delta )"],["whileAsync","whileAsync( predicate, fcn, done[, thisArg] )"],["whileEach","whileEach( collection, predicate, fcn[, thisArg] )"],["whileEachRight","whileEachRight( collection, predicate, fcn[, thisArg] )"],["whilst","whilst( predicate, fcn[, thisArg] )"],["wilcoxon","wilcoxon( x[, y][, options] )"],["writableProperties","writableProperties( value )"],["writablePropertiesIn","writablePropertiesIn( value )"],["writablePropertyNames","writablePropertyNames( value )"],["writablePropertyNamesIn","writablePropertyNamesIn( value )"],["writablePropertySymbols","writablePropertySymbols( value )"],["writablePropertySymbolsIn","writablePropertySymbolsIn( value )"],["writeFile","writeFile( file, data[, options], clbk )"],["writeFile.sync","writeFile.sync( file, data[, options] )"],["zip","zip( ...arr[, options] )"],["ztest","ztest( x, sigma[, options] )"],["ztest2","ztest2( x, y, sigmax, sigmay[, options] )"]]
+[["abs","abs( x[, options] )"],["abs.assign","abs.assign( x, y )"],["acartesianPower","acartesianPower( x, n )"],["acartesianProduct","acartesianProduct( x1, x2 )"],["acartesianSquare","acartesianSquare( x )"],["acronym","acronym( str[, options] )"],["aempty","aempty( length[, dtype] )"],["aemptyLike","aemptyLike( x[, dtype] )"],["AFINN_96","AFINN_96()"],["AFINN_111","AFINN_111()"],["afull","afull( length, value[, dtype] )"],["afullLike","afullLike( x[, dtype] )"],["alias2pkg","alias2pkg( alias )"],["alias2related","alias2related( alias )"],["alias2standalone","alias2standalone( alias )"],["aliases","aliases( [namespace] )"],["allocUnsafe","allocUnsafe( size )"],["amskfilter","amskfilter( x, mask )"],["amskput","amskput( x, mask, values[, options] )"],["amskreject","amskreject( x, mask )"],["anans","anans( length[, dtype] )"],["anansLike","anansLike( x[, dtype] )"],["anova1","anova1( x, factor[, options] )"],["ANSCOMBES_QUARTET","ANSCOMBES_QUARTET()"],["any","any( collection )"],["anyBy","anyBy( collection, predicate[, thisArg ] )"],["anyByAsync","anyByAsync( collection, [options,] predicate, done )"],["anyByAsync.factory","anyByAsync.factory( [options,] predicate )"],["anyByRight","anyByRight( collection, predicate[, thisArg ] )"],["anyByRightAsync","anyByRightAsync( collection, [options,] predicate, done )"],["anyByRightAsync.factory","anyByRightAsync.factory( [options,] predicate )"],["anyInBy","anyInBy( object, predicate[, thisArg ] )"],["anyOwnBy","anyOwnBy( object, predicate[, thisArg ] )"],["aones","aones( length[, dtype] )"],["aonesLike","aonesLike( x[, dtype] )"],["aoneTo","aoneTo( n[, dtype] )"],["aoneToLike","aoneToLike( x[, dtype] )"],["APERY","APERY"],["aplace","aplace( x, mask, values[, options] )"],["append","append( collection1, collection2 )"],["aput","aput( x, indices, values[, options] )"],["ARCH","ARCH"],["argumentFunction","argumentFunction( idx )"],["ARGV","ARGV"],["array","array( [buffer,] [options] )"],["array2buffer","array2buffer( arr )"],["array2fancy","array2fancy( x[, options] )"],["array2fancy.factory","array2fancy.factory( [options] )"],["array2fancy.idx","array2fancy.idx( x[, options] )"],["array2iterator","array2iterator( src[, mapFcn[, thisArg]] )"],["array2iteratorRight","array2iteratorRight( src[, mapFcn[, thisArg]] )"],["ArrayBuffer","ArrayBuffer( size )"],["ArrayBuffer.length","ArrayBuffer.length"],["ArrayBuffer.isView","ArrayBuffer.isView( arr )"],["ArrayBuffer.prototype.byteLength","ArrayBuffer.prototype.byteLength"],["ArrayBuffer.prototype.slice","ArrayBuffer.prototype.slice( [start[, end]] )"],["arraybuffer2buffer","arraybuffer2buffer( buf[, byteOffset[, length]] )"],["arrayCtors","arrayCtors( dtype )"],["arrayDataType","arrayDataType( array )"],["arrayDataTypes","arrayDataTypes( [kind] )"],["ArrayIndex","ArrayIndex( x[, options] )"],["ArrayIndex.free","ArrayIndex.free( id )"],["ArrayIndex.get","ArrayIndex.get( id )"],["ArrayIndex.prototype.data","ArrayIndex.prototype.data"],["ArrayIndex.prototype.dtype","ArrayIndex.prototype.dtype"],["ArrayIndex.prototype.id","ArrayIndex.prototype.id"],["ArrayIndex.prototype.isCached","ArrayIndex.prototype.isCached"],["ArrayIndex.prototype.type","ArrayIndex.prototype.type"],["ArrayIndex.prototype.toString","ArrayIndex.prototype.toString()"],["ArrayIndex.prototype.toJSON","ArrayIndex.prototype.toJSON()"],["arrayMinDataType","arrayMinDataType( value )"],["arrayMostlySafeCasts","arrayMostlySafeCasts( [dtype] )"],["arrayNextDataType","arrayNextDataType( [dtype] )"],["arrayPromotionRules","arrayPromotionRules( [dtype1, dtype2] )"],["arraySafeCasts","arraySafeCasts( [dtype] )"],["arraySameKindCasts","arraySameKindCasts( [dtype] )"],["arrayShape","arrayShape( arr )"],["arrayStream","arrayStream( src[, options] )"],["arrayStream.factory","arrayStream.factory( [options] )"],["arrayStream.objectMode","arrayStream.objectMode( src[, options] )"],["arrayview2iterator","arrayview2iterator( src[, begin[, end]][, mapFcn[, thisArg]] )"],["arrayview2iteratorRight","arrayview2iteratorRight( src[, begin[, end]][, mapFcn[, thisArg]] )"],["aslice","aslice( x[, start[, end]] )"],["AsyncIteratorSymbol","AsyncIteratorSymbol"],["atake","atake( x, indices[, options] )"],["azeros","azeros( length[, dtype] )"],["azerosLike","azerosLike( x[, dtype] )"],["azeroTo","azeroTo( n[, dtype] )"],["azeroToLike","azeroToLike( x[, dtype] )"],["bartlettTest","bartlettTest( ...x[, options] )"],["base.abs","base.abs( x )"],["base.abs2","base.abs2( x )"],["base.abs2f","base.abs2f( x )"],["base.absdiff","base.absdiff( x, y )"],["base.absf","base.absf( x )"],["base.acartesianPower","base.acartesianPower( x, n )"],["base.acartesianProduct","base.acartesianProduct( x1, x2 )"],["base.acartesianSquare","base.acartesianSquare( x )"],["base.acos","base.acos( x )"],["base.acosd","base.acosd( x )"],["base.acosf","base.acosf( x )"],["base.acosh","base.acosh( x )"],["base.acot","base.acot( x )"],["base.acotd","base.acotd( x )"],["base.acotf","base.acotf( x )"],["base.acoth","base.acoth( x )"],["base.acovercos","base.acovercos( x )"],["base.acoversin","base.acoversin( x )"],["base.acsc","base.acsc( x )"],["base.acscd","base.acscd( x )"],["base.acscdf","base.acscdf( x )"],["base.acscf","base.acscf( x )"],["base.acsch","base.acsch( x )"],["base.add","base.add( x, y )"],["base.add3","base.add3( x, y, z )"],["base.add4","base.add4( x, y, z, w )"],["base.add5","base.add5( x, y, z, w, u )"],["base.addf","base.addf( x, y )"],["base.afilled","base.afilled( value, len )"],["base.afilled2d","base.afilled2d( value, shape )"],["base.afilled2dBy","base.afilled2dBy( shape, clbk[, thisArg] )"],["base.afilled3d","base.afilled3d( value, shape )"],["base.afilled3dBy","base.afilled3dBy( shape, clbk[, thisArg] )"],["base.afilled4d","base.afilled4d( value, shape )"],["base.afilled4dBy","base.afilled4dBy( shape, clbk[, thisArg] 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value )"],["isPositiveNumberArray.primitives","isPositiveNumberArray.primitives( value )"],["isPositiveNumberArray.objects","isPositiveNumberArray.objects( value )"],["isPositiveZero","isPositiveZero( value )"],["isPositiveZero.isPrimitive","isPositiveZero.isPrimitive( value )"],["isPositiveZero.isObject","isPositiveZero.isObject( value )"],["isPrime","isPrime( value )"],["isPrime.isPrimitive","isPrime.isPrimitive( value )"],["isPrime.isObject","isPrime.isObject( value )"],["isPrimitive","isPrimitive( value )"],["isPrimitiveArray","isPrimitiveArray( value )"],["isPRNGLike","isPRNGLike( value )"],["isProbability","isProbability( value )"],["isProbability.isPrimitive","isProbability.isPrimitive( value )"],["isProbability.isObject","isProbability.isObject( value )"],["isProbabilityArray","isProbabilityArray( value )"],["isProbabilityArray.primitives","isProbabilityArray.primitives( value )"],["isProbabilityArray.objects","isProbabilityArray.objects( value 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)"],["isUint8ClampedArray","isUint8ClampedArray( value )"],["isUint16Array","isUint16Array( value )"],["isUint32Array","isUint32Array( value )"],["isUNCPath","isUNCPath( value )"],["isUndefined","isUndefined( value )"],["isUndefinedOrNull","isUndefinedOrNull( value )"],["isUnityProbabilityArray","isUnityProbabilityArray( value )"],["isUppercase","isUppercase( value )"],["isURI","isURI( value )"],["isURIError","isURIError( value )"],["isVectorLike","isVectorLike( value )"],["isWebAssemblyMemory","isWebAssemblyMemory( value )"],["isWellFormedString","isWellFormedString( str )"],["isWellFormedString.isPrimitive","isWellFormedString.isPrimitive( str )"],["isWellFormedString.isObject","isWellFormedString.isObject( str )"],["isWhitespace","isWhitespace( str )"],["isWritableProperty","isWritableProperty( value, property )"],["isWritablePropertyIn","isWritablePropertyIn( value, property )"],["isWriteOnlyProperty","isWriteOnlyProperty( value, property 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mapFcn[, thisArg]] )"],["iterator2arrayviewRight","iterator2arrayviewRight( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )"],["iteratorStream","iteratorStream( iterator[, options] )"],["iteratorStream.factory","iteratorStream.factory( [options] )"],["iteratorStream.objectMode","iteratorStream.objectMode( iterator[, options] )"],["IteratorSymbol","IteratorSymbol"],["iterAvercos","iterAvercos( iterator )"],["iterAversin","iterAversin( iterator )"],["iterawgn","iterawgn( iterator, sigma[, options] )"],["iterawln","iterawln( iterator, sigma[, options] )"],["iterawun","iterawun( iterator, sigma[, options] )"],["iterBartlettHannPulse","iterBartlettHannPulse( [options] )"],["iterBartlettPulse","iterBartlettPulse( [options] )"],["iterBesselj0","iterBesselj0( iterator )"],["iterBesselj1","iterBesselj1( iterator )"],["iterBessely0","iterBessely0( iterator )"],["iterBessely1","iterBessely1( iterator )"],["iterBeta","iterBeta( x, y )"],["iterBetaln","iterBetaln( x, y )"],["iterBinet","iterBinet( iterator )"],["iterCbrt","iterCbrt( iterator )"],["iterCeil","iterCeil( iterator )"],["iterCeil2","iterCeil2( iterator )"],["iterCeil10","iterCeil10( iterator )"],["iterCompositesSeq","iterCompositesSeq( [options] )"],["iterConcat","iterConcat( iter0, ...iterator )"],["iterConstant","iterConstant( value[, options] )"],["iterContinuedFraction","iterContinuedFraction( iterator[, options] )"],["iterContinuedFractionSeq","iterContinuedFractionSeq( x[, options] )"],["iterCos","iterCos( iterator )"],["iterCosh","iterCosh( iterator )"],["iterCosineWave","iterCosineWave( [options] )"],["iterCosm1","iterCosm1( iterator )"],["iterCospi","iterCospi( iterator )"],["iterCounter","iterCounter( iterator )"],["iterCovercos","iterCovercos( iterator )"],["iterCoversin","iterCoversin( iterator )"],["iterCubesSeq","iterCubesSeq( [options] )"],["itercugmean","itercugmean( iterator )"],["itercuhmean","itercuhmean( iterator )"],["itercumax","itercumax( iterator )"],["itercumaxabs","itercumaxabs( iterator )"],["itercumean","itercumean( iterator )"],["itercumeanabs","itercumeanabs( iterator )"],["itercumeanabs2","itercumeanabs2( iterator )"],["itercumidrange","itercumidrange( iterator )"],["itercumin","itercumin( iterator )"],["itercuminabs","itercuminabs( iterator )"],["itercuprod","itercuprod( iterator )"],["itercurange","itercurange( iterator )"],["itercusum","itercusum( iterator )"],["itercusumabs","itercusumabs( iterator )"],["itercusumabs2","itercusumabs2( iterator )"],["iterDatespace","iterDatespace( start, stop[, N][, options] )"],["iterDedupe","iterDedupe( iterator[, limit] )"],["iterDedupeBy","iterDedupeBy( iterator, [limit,] fcn )"],["iterDeg2rad","iterDeg2rad( iterator )"],["iterDigamma","iterDigamma( iterator )"],["iterDiracComb","iterDiracComb( [options] )"],["iterDiracDelta","iterDiracDelta( iterator )"],["iterDivide","iterDivide( iter0, ...iterator )"],["iterDoWhileEach","iterDoWhileEach( iterator, predicate, fcn[, thisArg] )"],["iterEllipe","iterEllipe( iterator )"],["iterEllipk","iterEllipk( iterator )"],["iterEmpty","iterEmpty()"],["iterErf","iterErf( iterator )"],["iterErfc","iterErfc( iterator )"],["iterErfcinv","iterErfcinv( iterator )"],["iterErfinv","iterErfinv( iterator )"],["iterEta","iterEta( iterator )"],["iterEvenIntegersSeq","iterEvenIntegersSeq( [options] )"],["iterEvery","iterEvery( iterator )"],["iterEveryBy","iterEveryBy( iterator, predicate[, thisArg ] )"],["iterExp","iterExp( iterator )"],["iterExp2","iterExp2( iterator )"],["iterExp10","iterExp10( iterator )"],["iterExpit","iterExpit( iterator )"],["iterExpm1","iterExpm1( iterator )"],["iterExpm1rel","iterExpm1rel( iterator )"],["iterFactorial","iterFactorial( iterator )"],["iterFactorialln","iterFactorialln( iterator )"],["iterFactorialsSeq","iterFactorialsSeq( [options] )"],["iterFibonacciSeq","iterFibonacciSeq( [options] )"],["iterFifthPowersSeq","iterFifthPowersSeq( [options] )"],["iterFill","iterFill( iterator, value[, begin[, end]] )"],["iterFilter","iterFilter( iterator, predicate[, thisArg] )"],["iterFilterMap","iterFilterMap( iterator, fcn[, thisArg] )"],["iterFirst","iterFirst( iterator )"],["iterFlatTopPulse","iterFlatTopPulse( [options] )"],["iterFloor","iterFloor( iterator )"],["iterFloor2","iterFloor2( iterator )"],["iterFloor10","iterFloor10( iterator )"],["iterFlow","iterFlow( methods )"],["iterForEach","iterForEach( iterator, fcn[, thisArg] )"],["iterFourthPowersSeq","iterFourthPowersSeq( [options] )"],["iterFresnelc","iterFresnelc( iterator )"],["iterFresnels","iterFresnels( iterator )"],["iterGamma","iterGamma( iterator )"],["iterGamma1pm1","iterGamma1pm1( iterator )"],["iterGammaln","iterGammaln( iterator )"],["iterHacovercos","iterHacovercos( iterator )"],["iterHacoversin","iterHacoversin( iterator )"],["iterHannPulse","iterHannPulse( [options] )"],["iterHavercos","iterHavercos( iterator )"],["iterHaversin","iterHaversin( iterator )"],["iterHead","iterHead( iterator, n )"],["iterIncrspace","iterIncrspace( start, stop[, increment] )"],["iterIntegersSeq","iterIntegersSeq( [options] )"],["iterIntersection","iterIntersection( iter0, ...iterator )"],["iterIntersectionByHash","iterIntersectionByHash( iter0, ...iterator, hashFcn[, thisArg] )"],["iterInv","iterInv( iterator )"],["iterLanczosPulse","iterLanczosPulse( [options] )"],["iterLast","iterLast( iterator )"],["iterLength","iterLength( iterator )"],["iterLinspace","iterLinspace( start, stop[, N] )"],["iterLn","iterLn( iterator )"],["iterLog","iterLog( x, b )"],["iterLog1mexp","iterLog1mexp( iterator )"],["iterLog1p","iterLog1p( iterator )"],["iterLog1pexp","iterLog1pexp( iterator )"],["iterLog2","iterLog2( iterator )"],["iterLog10","iterLog10( iterator )"],["iterLogit","iterLogit( iterator )"],["iterLogspace","iterLogspace( start, stop[, N][, options] )"],["iterLucasSeq","iterLucasSeq( [options] )"],["iterMap","iterMap( iterator, fcn[, thisArg] )"],["iterMapN","iterMapN( iter0, ...iterator, fcn[, thisArg] )"],["itermax","itermax( iterator )"],["itermaxabs","itermaxabs( iterator )"],["itermean","itermean( iterator )"],["itermeanabs","itermeanabs( iterator )"],["itermeanabs2","itermeanabs2( iterator )"],["itermidrange","itermidrange( iterator )"],["itermin","itermin( iterator )"],["iterminabs","iterminabs( iterator )"],["itermmax","itermmax( iterator, W )"],["itermmaxabs","itermmaxabs( iterator, W )"],["itermmean","itermmean( iterator, W )"],["itermmeanabs","itermmeanabs( iterator, W )"],["itermmeanabs2","itermmeanabs2( iterator, W )"],["itermmidrange","itermmidrange( iterator, W )"],["itermmin","itermmin( iterator, W )"],["itermminabs","itermminabs( iterator, W )"],["iterMod","iterMod( iter0, ...iterator )"],["itermprod","itermprod( iterator, W )"],["itermrange","itermrange( iterator, W )"],["itermsum","itermsum( iterator, W )"],["itermsumabs","itermsumabs( iterator, W )"],["itermsumabs2","itermsumabs2( iterator, W )"],["iterMultiply","iterMultiply( iter0, ...iterator )"],["iterNegaFibonacciSeq","iterNegaFibonacciSeq( [options] )"],["iterNegaLucasSeq","iterNegaLucasSeq( [options] )"],["iterNegativeEvenIntegersSeq","iterNegativeEvenIntegersSeq( [options] )"],["iterNegativeIntegersSeq","iterNegativeIntegersSeq( [options] )"],["iterNegativeOddIntegersSeq","iterNegativeOddIntegersSeq( [options] )"],["iterNone","iterNone( iterator )"],["iterNoneBy","iterNoneBy( iterator, predicate[, thisArg ] )"],["iterNonFibonacciSeq","iterNonFibonacciSeq( [options] )"],["iterNonNegativeEvenIntegersSeq","iterNonNegativeEvenIntegersSeq( [options] )"],["iterNonNegativeIntegersSeq","iterNonNegativeIntegersSeq( [options] )"],["iterNonPositiveEvenIntegersSeq","iterNonPositiveEvenIntegersSeq( [options] )"],["iterNonPositiveIntegersSeq","iterNonPositiveIntegersSeq( [options] )"],["iterNonSquaresSeq","iterNonSquaresSeq( [options] )"],["iterNth","iterNth( iterator, n )"],["iterOddIntegersSeq","iterOddIntegersSeq( [options] )"],["iterPeriodicSinc","iterPeriodicSinc( n[, options] )"],["iterPipeline","iterPipeline( iterFcn[, ...iterFcn] )"],["iterPop","iterPop( iterator[, clbk[, thisArg]] )"],["iterPositiveEvenIntegersSeq","iterPositiveEvenIntegersSeq( [options] )"],["iterPositiveIntegersSeq","iterPositiveIntegersSeq( [options] )"],["iterPositiveOddIntegersSeq","iterPositiveOddIntegersSeq( [options] )"],["iterPow","iterPow( base, exponent )"],["iterPrimesSeq","iterPrimesSeq( [options] )"],["iterprod","iterprod( iterator )"],["iterPulse","iterPulse( [options] )"],["iterPush","iterPush( iterator, ...items )"],["iterRad2deg","iterRad2deg( iterator )"],["iterRamp","iterRamp( iterator )"],["iterrange","iterrange( iterator )"],["iterReject","iterReject( iterator, predicate[, thisArg] )"],["iterReplicate","iterReplicate( iterator, n )"],["iterReplicateBy","iterReplicateBy( iterator, fcn[, thisArg] )"],["iterRound","iterRound( iterator )"],["iterRound2","iterRound2( iterator )"],["iterRound10","iterRound10( iterator )"],["iterRsqrt","iterRsqrt( iterator )"],["iterSawtoothWave","iterSawtoothWave( [options] )"],["iterShift","iterShift( iterator[, clbk[, thisArg]] )"],["iterSignum","iterSignum( iterator )"],["iterSin","iterSin( iterator )"],["iterSinc","iterSinc( iterator )"],["iterSineWave","iterSineWave( [options] )"],["iterSinh","iterSinh( iterator )"],["iterSinpi","iterSinpi( iterator )"],["iterSlice","iterSlice( iterator[, begin[, end]] )"],["iterSome","iterSome( iterator, n )"],["iterSomeBy","iterSomeBy( iterator, n, predicate[, thisArg ] )"],["iterSpence","iterSpence( iterator )"],["iterSqrt","iterSqrt( iterator )"],["iterSqrt1pm1","iterSqrt1pm1( iterator )"],["iterSquaredTriangularSeq","iterSquaredTriangularSeq( [options] )"],["iterSquaresSeq","iterSquaresSeq( [options] )"],["iterSquareWave","iterSquareWave( [options] )"],["iterstdev","iterstdev( iterator[, mean] )"],["iterStep","iterStep( start, increment[, N] )"],["iterStrided","iterStrided( iterator, stride[, offset[, eager]] )"],["iterStridedBy","iterStridedBy( iterator, fcn[, offset[, eager]][, thisArg] )"],["iterSubtract","iterSubtract( iter0, ...iterator )"],["itersum","itersum( iterator )"],["itersumabs","itersumabs( iterator )"],["itersumabs2","itersumabs2( iterator )"],["iterTan","iterTan( iterator )"],["iterTanh","iterTanh( iterator )"],["iterThunk","iterThunk( iterFcn[, ...args] )"],["iterTriangleWave","iterTriangleWave( [options] )"],["iterTriangularSeq","iterTriangularSeq( [options] )"],["iterTribonnaciSeq","iterTribonnaciSeq( [options] )"],["iterTrigamma","iterTrigamma( iterator )"],["iterTrunc","iterTrunc( iterator )"],["iterTrunc2","iterTrunc2( iterator )"],["iterTrunc10","iterTrunc10( iterator )"],["iterUnion","iterUnion( iter0, ...iterator )"],["iterUnique","iterUnique( iterator )"],["iterUniqueBy","iterUniqueBy( iterator, predicate[, thisArg] )"],["iterUniqueByHash","iterUniqueByHash( iterator, hashFcn[, thisArg] )"],["iterUnitspace","iterUnitspace( start[, stop] )"],["iterUnshift","iterUnshift( iterator, ...items 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)"],["Uint8Array.prototype.slice","Uint8Array.prototype.slice( [begin[, end]] )"],["Uint8Array.prototype.some","Uint8Array.prototype.some( predicate[, thisArg] )"],["Uint8Array.prototype.sort","Uint8Array.prototype.sort( [compareFunction] )"],["Uint8Array.prototype.subarray","Uint8Array.prototype.subarray( [begin[, end]] )"],["Uint8Array.prototype.toLocaleString","Uint8Array.prototype.toLocaleString( [locales[, options]] )"],["Uint8Array.prototype.toString","Uint8Array.prototype.toString()"],["Uint8Array.prototype.values","Uint8Array.prototype.values()"],["Uint8ClampedArray","Uint8ClampedArray()"],["Uint8ClampedArray","Uint8ClampedArray( length )"],["Uint8ClampedArray","Uint8ClampedArray( typedarray )"],["Uint8ClampedArray","Uint8ClampedArray( obj )"],["Uint8ClampedArray","Uint8ClampedArray( buffer[, byteOffset[, length]] )"],["Uint8ClampedArray.from","Uint8ClampedArray.from( src[, map[, thisArg]] )"],["Uint8ClampedArray.of","Uint8ClampedArray.of( element0[, element1[, ...elementN]] )"],["Uint8ClampedArray.BYTES_PER_ELEMENT","Uint8ClampedArray.BYTES_PER_ELEMENT"],["Uint8ClampedArray.name","Uint8ClampedArray.name"],["Uint8ClampedArray.prototype.buffer","Uint8ClampedArray.prototype.buffer"],["Uint8ClampedArray.prototype.byteLength","Uint8ClampedArray.prototype.byteLength"],["Uint8ClampedArray.prototype.byteOffset","Uint8ClampedArray.prototype.byteOffset"],["Uint8ClampedArray.prototype.BYTES_PER_ELEMENT","Uint8ClampedArray.prototype.BYTES_PER_ELEMENT"],["Uint8ClampedArray.prototype.length","Uint8ClampedArray.prototype.length"],["Uint8ClampedArray.prototype.copyWithin","Uint8ClampedArray.prototype.copyWithin( target, start[, end] )"],["Uint8ClampedArray.prototype.entries","Uint8ClampedArray.prototype.entries()"],["Uint8ClampedArray.prototype.every","Uint8ClampedArray.prototype.every( predicate[, thisArg] )"],["Uint8ClampedArray.prototype.fill","Uint8ClampedArray.prototype.fill( value[, start[, end]] )"],["Uint8ClampedArray.prototype.filter","Uint8ClampedArray.prototype.filter( predicate[, thisArg] )"],["Uint8ClampedArray.prototype.find","Uint8ClampedArray.prototype.find( predicate[, thisArg] )"],["Uint8ClampedArray.prototype.findIndex","Uint8ClampedArray.prototype.findIndex( predicate[, thisArg] )"],["Uint8ClampedArray.prototype.forEach","Uint8ClampedArray.prototype.forEach( fcn[, thisArg] )"],["Uint8ClampedArray.prototype.includes","Uint8ClampedArray.prototype.includes( searchElement[, fromIndex] )"],["Uint8ClampedArray.prototype.indexOf","Uint8ClampedArray.prototype.indexOf( searchElement[, fromIndex] )"],["Uint8ClampedArray.prototype.join","Uint8ClampedArray.prototype.join( [separator] )"],["Uint8ClampedArray.prototype.keys","Uint8ClampedArray.prototype.keys()"],["Uint8ClampedArray.prototype.lastIndexOf","Uint8ClampedArray.prototype.lastIndexOf( searchElement[, fromIndex] )"],["Uint8ClampedArray.prototype.map","Uint8ClampedArray.prototype.map( fcn[, thisArg] )"],["Uint8ClampedArray.prototype.reduce","Uint8ClampedArray.prototype.reduce( fcn[, initialValue] )"],["Uint8ClampedArray.prototype.reduceRight","Uint8ClampedArray.prototype.reduceRight( fcn[, initialValue] )"],["Uint8ClampedArray.prototype.reverse","Uint8ClampedArray.prototype.reverse()"],["Uint8ClampedArray.prototype.set","Uint8ClampedArray.prototype.set( arr[, offset] )"],["Uint8ClampedArray.prototype.slice","Uint8ClampedArray.prototype.slice( [begin[, end]] )"],["Uint8ClampedArray.prototype.some","Uint8ClampedArray.prototype.some( predicate[, thisArg] )"],["Uint8ClampedArray.prototype.sort","Uint8ClampedArray.prototype.sort( [compareFunction] )"],["Uint8ClampedArray.prototype.subarray","Uint8ClampedArray.prototype.subarray( [begin[, end]] )"],["Uint8ClampedArray.prototype.toLocaleString","Uint8ClampedArray.prototype.toLocaleString( [locales[, options]] )"],["Uint8ClampedArray.prototype.toString","Uint8ClampedArray.prototype.toString()"],["Uint8ClampedArray.prototype.values","Uint8ClampedArray.prototype.values()"],["UINT16_MAX","UINT16_MAX"],["UINT16_NUM_BYTES","UINT16_NUM_BYTES"],["Uint16Array","Uint16Array()"],["Uint16Array","Uint16Array( length )"],["Uint16Array","Uint16Array( typedarray )"],["Uint16Array","Uint16Array( obj )"],["Uint16Array","Uint16Array( buffer[, byteOffset[, length]] )"],["Uint16Array.from","Uint16Array.from( src[, map[, thisArg]] )"],["Uint16Array.of","Uint16Array.of( element0[, element1[, ...elementN]] )"],["Uint16Array.BYTES_PER_ELEMENT","Uint16Array.BYTES_PER_ELEMENT"],["Uint16Array.name","Uint16Array.name"],["Uint16Array.prototype.buffer","Uint16Array.prototype.buffer"],["Uint16Array.prototype.byteLength","Uint16Array.prototype.byteLength"],["Uint16Array.prototype.byteOffset","Uint16Array.prototype.byteOffset"],["Uint16Array.prototype.BYTES_PER_ELEMENT","Uint16Array.prototype.BYTES_PER_ELEMENT"],["Uint16Array.prototype.length","Uint16Array.prototype.length"],["Uint16Array.prototype.copyWithin","Uint16Array.prototype.copyWithin( target, start[, end] )"],["Uint16Array.prototype.entries","Uint16Array.prototype.entries()"],["Uint16Array.prototype.every","Uint16Array.prototype.every( predicate[, thisArg] )"],["Uint16Array.prototype.fill","Uint16Array.prototype.fill( value[, start[, end]] )"],["Uint16Array.prototype.filter","Uint16Array.prototype.filter( predicate[, thisArg] )"],["Uint16Array.prototype.find","Uint16Array.prototype.find( predicate[, thisArg] )"],["Uint16Array.prototype.findIndex","Uint16Array.prototype.findIndex( predicate[, thisArg] )"],["Uint16Array.prototype.forEach","Uint16Array.prototype.forEach( fcn[, thisArg] )"],["Uint16Array.prototype.includes","Uint16Array.prototype.includes( searchElement[, fromIndex] )"],["Uint16Array.prototype.indexOf","Uint16Array.prototype.indexOf( searchElement[, fromIndex] )"],["Uint16Array.prototype.join","Uint16Array.prototype.join( [separator] )"],["Uint16Array.prototype.keys","Uint16Array.prototype.keys()"],["Uint16Array.prototype.lastIndexOf","Uint16Array.prototype.lastIndexOf( searchElement[, fromIndex] )"],["Uint16Array.prototype.map","Uint16Array.prototype.map( fcn[, thisArg] )"],["Uint16Array.prototype.reduce","Uint16Array.prototype.reduce( fcn[, initialValue] )"],["Uint16Array.prototype.reduceRight","Uint16Array.prototype.reduceRight( fcn[, initialValue] )"],["Uint16Array.prototype.reverse","Uint16Array.prototype.reverse()"],["Uint16Array.prototype.set","Uint16Array.prototype.set( arr[, offset] )"],["Uint16Array.prototype.slice","Uint16Array.prototype.slice( [begin[, end]] )"],["Uint16Array.prototype.some","Uint16Array.prototype.some( predicate[, thisArg] )"],["Uint16Array.prototype.sort","Uint16Array.prototype.sort( [compareFunction] )"],["Uint16Array.prototype.subarray","Uint16Array.prototype.subarray( [begin[, end]] )"],["Uint16Array.prototype.toLocaleString","Uint16Array.prototype.toLocaleString( [locales[, options]] )"],["Uint16Array.prototype.toString","Uint16Array.prototype.toString()"],["Uint16Array.prototype.values","Uint16Array.prototype.values()"],["UINT32_MAX","UINT32_MAX"],["UINT32_NUM_BYTES","UINT32_NUM_BYTES"],["Uint32Array","Uint32Array()"],["Uint32Array","Uint32Array( length )"],["Uint32Array","Uint32Array( typedarray )"],["Uint32Array","Uint32Array( obj )"],["Uint32Array","Uint32Array( buffer[, byteOffset[, length]] )"],["Uint32Array.from","Uint32Array.from( src[, map[, thisArg]] )"],["Uint32Array.of","Uint32Array.of( element0[, element1[, ...elementN]] )"],["Uint32Array.BYTES_PER_ELEMENT","Uint32Array.BYTES_PER_ELEMENT"],["Uint32Array.name","Uint32Array.name"],["Uint32Array.prototype.buffer","Uint32Array.prototype.buffer"],["Uint32Array.prototype.byteLength","Uint32Array.prototype.byteLength"],["Uint32Array.prototype.byteOffset","Uint32Array.prototype.byteOffset"],["Uint32Array.prototype.BYTES_PER_ELEMENT","Uint32Array.prototype.BYTES_PER_ELEMENT"],["Uint32Array.prototype.length","Uint32Array.prototype.length"],["Uint32Array.prototype.copyWithin","Uint32Array.prototype.copyWithin( target, start[, end] )"],["Uint32Array.prototype.entries","Uint32Array.prototype.entries()"],["Uint32Array.prototype.every","Uint32Array.prototype.every( predicate[, thisArg] )"],["Uint32Array.prototype.fill","Uint32Array.prototype.fill( value[, start[, end]] )"],["Uint32Array.prototype.filter","Uint32Array.prototype.filter( predicate[, thisArg] )"],["Uint32Array.prototype.find","Uint32Array.prototype.find( predicate[, thisArg] )"],["Uint32Array.prototype.findIndex","Uint32Array.prototype.findIndex( predicate[, thisArg] )"],["Uint32Array.prototype.forEach","Uint32Array.prototype.forEach( fcn[, thisArg] )"],["Uint32Array.prototype.includes","Uint32Array.prototype.includes( searchElement[, fromIndex] )"],["Uint32Array.prototype.indexOf","Uint32Array.prototype.indexOf( searchElement[, fromIndex] )"],["Uint32Array.prototype.join","Uint32Array.prototype.join( [separator] )"],["Uint32Array.prototype.keys","Uint32Array.prototype.keys()"],["Uint32Array.prototype.lastIndexOf","Uint32Array.prototype.lastIndexOf( searchElement[, fromIndex] )"],["Uint32Array.prototype.map","Uint32Array.prototype.map( fcn[, thisArg] )"],["Uint32Array.prototype.reduce","Uint32Array.prototype.reduce( fcn[, initialValue] )"],["Uint32Array.prototype.reduceRight","Uint32Array.prototype.reduceRight( fcn[, initialValue] )"],["Uint32Array.prototype.reverse","Uint32Array.prototype.reverse()"],["Uint32Array.prototype.set","Uint32Array.prototype.set( arr[, offset] )"],["Uint32Array.prototype.slice","Uint32Array.prototype.slice( [begin[, end]] )"],["Uint32Array.prototype.some","Uint32Array.prototype.some( predicate[, thisArg] )"],["Uint32Array.prototype.sort","Uint32Array.prototype.sort( [compareFunction] )"],["Uint32Array.prototype.subarray","Uint32Array.prototype.subarray( [begin[, end]] )"],["Uint32Array.prototype.toLocaleString","Uint32Array.prototype.toLocaleString( [locales[, options]] )"],["Uint32Array.prototype.toString","Uint32Array.prototype.toString()"],["Uint32Array.prototype.values","Uint32Array.prototype.values()"],["umask","umask( [mask,] [options] )"],["uncapitalize","uncapitalize( str )"],["uncapitalizeKeys","uncapitalizeKeys( obj )"],["uncurry","uncurry( fcn[, arity, ][thisArg] )"],["uncurryRight","uncurryRight( fcn[, arity, ][thisArg] )"],["UNICODE_MAX","UNICODE_MAX"],["UNICODE_MAX_BMP","UNICODE_MAX_BMP"],["UnicodeColumnChartSparkline","UnicodeColumnChartSparkline( [data,] [options] )"],["UnicodeLineChartSparkline","UnicodeLineChartSparkline( [data,] [options] )"],["UnicodeSparkline","UnicodeSparkline( [data,] [options] )"],["UnicodeTristateChartSparkline","UnicodeTristateChartSparkline( [data,] [options] )"],["UnicodeUpDownChartSparkline","UnicodeUpDownChartSparkline( [data,] [options] )"],["UnicodeWinLossChartSparkline","UnicodeWinLossChartSparkline( [data,] [options] )"],["unlink","unlink( path, clbk )"],["unlink.sync","unlink.sync( path )"],["unshift","unshift( collection, ...items )"],["until","until( predicate, fcn[, thisArg] )"],["untilAsync","untilAsync( predicate, fcn, done[, thisArg] )"],["untilEach","untilEach( collection, predicate, fcn[, thisArg] )"],["untilEachRight","untilEachRight( collection, predicate, fcn[, thisArg] )"],["unzip","unzip( arr[, idx] )"],["uppercase","uppercase( str )"],["uppercaseKeys","uppercaseKeys( obj )"],["US_STATES_ABBR","US_STATES_ABBR()"],["US_STATES_CAPITALS","US_STATES_CAPITALS()"],["US_STATES_CAPITALS_NAMES","US_STATES_CAPITALS_NAMES()"],["US_STATES_NAMES","US_STATES_NAMES()"],["US_STATES_NAMES_CAPITALS","US_STATES_NAMES_CAPITALS()"],["utf16ToUTF8Array","utf16ToUTF8Array( str )"],["vartest","vartest( x, y[, options] )"],["waterfall","waterfall( fcns, clbk[, thisArg] )"],["waterfall.factory","waterfall.factory( fcns, clbk[, thisArg] )"],["WebAssemblyMemory","WebAssemblyMemory( descriptor )"],["WebAssemblyMemory.prototype.buffer","WebAssemblyMemory.prototype.buffer"],["WebAssemblyMemory.prototype.grow","WebAssemblyMemory.prototype.grow( delta )"],["whileAsync","whileAsync( predicate, fcn, done[, thisArg] )"],["whileEach","whileEach( collection, predicate, fcn[, thisArg] )"],["whileEachRight","whileEachRight( collection, predicate, fcn[, thisArg] )"],["whilst","whilst( predicate, fcn[, thisArg] )"],["wilcoxon","wilcoxon( x[, y][, options] )"],["writableProperties","writableProperties( value )"],["writablePropertiesIn","writablePropertiesIn( value )"],["writablePropertyNames","writablePropertyNames( value )"],["writablePropertyNamesIn","writablePropertyNamesIn( value )"],["writablePropertySymbols","writablePropertySymbols( value )"],["writablePropertySymbolsIn","writablePropertySymbolsIn( value )"],["writeFile","writeFile( file, data[, options], clbk )"],["writeFile.sync","writeFile.sync( file, data[, options] )"],["zip","zip( ...arr[, options] )"],["ztest","ztest( x, sigma[, options] )"],["ztest2","ztest2( x, y, sigmax, sigmay[, options] )"]]
diff --git a/lib/node_modules/@stdlib/repl/typed-signature/data/data.csv b/lib/node_modules/@stdlib/repl/typed-signature/data/data.csv
index 349c10c9e3b3..4815c0210dc2 100644
--- a/lib/node_modules/@stdlib/repl/typed-signature/data/data.csv
+++ b/lib/node_modules/@stdlib/repl/typed-signature/data/data.csv
@@ -1735,10 +1735,10 @@ base.strided.dmax,"base.strided.dmax( N:integer, x:Float64Array, strideX:integer
 base.strided.dmax.ndarray,"base.strided.dmax.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )"
 base.strided.dmaxabs,"base.strided.dmaxabs( N:integer, x:Float64Array, strideX:integer )"
 base.strided.dmaxabs.ndarray,"base.strided.dmaxabs.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )"
-base.strided.dmaxabssorted,"base.strided.dmaxabssorted( N:integer, x:Float64Array, stride:integer )"
-base.strided.dmaxabssorted.ndarray,"base.strided.dmaxabssorted.ndarray( N:integer, x:Float64Array, stride:integer, offset:integer )"
-base.strided.dmaxsorted,"base.strided.dmaxsorted( N:integer, x:Float64Array, stride:integer )"
-base.strided.dmaxsorted.ndarray,"base.strided.dmaxsorted.ndarray( N:integer, x:Float64Array, stride:integer, offset:integer )"
+base.strided.dmaxabssorted,"base.strided.dmaxabssorted( N:integer, x:Float64Array, strideX:integer )"
+base.strided.dmaxabssorted.ndarray,"base.strided.dmaxabssorted.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )"
+base.strided.dmaxsorted,"base.strided.dmaxsorted( N:integer, x:Float64Array, strideX:integer )"
+base.strided.dmaxsorted.ndarray,"base.strided.dmaxsorted.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )"
 base.strided.dmean,"base.strided.dmean( N:integer, x:Float64Array, stride:integer )"
 base.strided.dmean.ndarray,"base.strided.dmean.ndarray( N:integer, x:Float64Array, stride:integer, offset:integer )"
 base.strided.dmeankbn,"base.strided.dmeankbn( N:integer, x:Float64Array, stride:integer )"
@@ -1765,16 +1765,16 @@ base.strided.dmeanvarpn,"base.strided.dmeanvarpn( N:integer, c:number, x:Float64
 base.strided.dmeanvarpn.ndarray,"base.strided.dmeanvarpn.ndarray( N:integer, c:number, x:Float64Array, strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )"
 base.strided.dmeanwd,"base.strided.dmeanwd( N:integer, x:Float64Array, stride:integer )"
 base.strided.dmeanwd.ndarray,"base.strided.dmeanwd.ndarray( N:integer, x:Float64Array, stride:integer, offset:integer )"
-base.strided.dmediansorted,"base.strided.dmediansorted( N:integer, x:Float64Array, stride:integer )"
-base.strided.dmediansorted.ndarray,"base.strided.dmediansorted.ndarray( N:integer, x:Float64Array, stride:integer, offset:integer )"
+base.strided.dmediansorted,"base.strided.dmediansorted( N:integer, x:Float64Array, strideX:integer )"
+base.strided.dmediansorted.ndarray,"base.strided.dmediansorted.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )"
 base.strided.dmidrange,"base.strided.dmidrange( N:integer, x:Float64Array, strideX:integer )"
 base.strided.dmidrange.ndarray,"base.strided.dmidrange.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )"
 base.strided.dmin,"base.strided.dmin( N:integer, x:Float64Array, strideX:integer )"
 base.strided.dmin.ndarray,"base.strided.dmin.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )"
 base.strided.dminabs,"base.strided.dminabs( N:integer, x:Float64Array, strideX:integer )"
 base.strided.dminabs.ndarray,"base.strided.dminabs.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )"
-base.strided.dminsorted,"base.strided.dminsorted( N:integer, x:Float64Array, stride:integer )"
-base.strided.dminsorted.ndarray,"base.strided.dminsorted.ndarray( N:integer, x:Float64Array, stride:integer, offset:integer )"
+base.strided.dminsorted,"base.strided.dminsorted( N:integer, x:Float64Array, strideX:integer )"
+base.strided.dminsorted.ndarray,"base.strided.dminsorted.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )"
 base.strided.dmskabs,"base.strided.dmskabs( N:integer, x:Float64Array, sx:integer, m:Uint8Array, sm:integer, y:Float64Array, sy:integer )"
 base.strided.dmskabs.ndarray,"base.strided.dmskabs.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, sy:integer, oy:integer )"
 base.strided.dmskabs2,"base.strided.dmskabs2( N:integer, x:Float64Array, sx:integer, m:Uint8Array, sm:integer, y:Float64Array, sy:integer )"
@@ -1969,12 +1969,12 @@ base.strided.dstdevwd,"base.strided.dstdevwd( N:integer, correction:number, x:Fl
 base.strided.dstdevwd.ndarray,"base.strided.dstdevwd.ndarray( N:integer, correction:number, x:Float64Array, stride:integer, offset:integer )"
 base.strided.dstdevyc,"base.strided.dstdevyc( N:integer, correction:number, x:Float64Array, stride:integer )"
 base.strided.dstdevyc.ndarray,"base.strided.dstdevyc.ndarray( N:integer, correction:number, x:Float64Array, stride:integer, offset:integer )"
-base.strided.dsum,"base.strided.dsum( N:integer, x:Float64Array, stride:integer )"
-base.strided.dsum.ndarray,"base.strided.dsum.ndarray( N:integer, x:Float64Array, stride:integer, offset:integer )"
+base.strided.dsum,"base.strided.dsum( N:integer, x:Float64Array, strideX:integer )"
+base.strided.dsum.ndarray,"base.strided.dsum.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )"
 base.strided.dsumkbn,"base.strided.dsumkbn( N:integer, x:Float64Array, strideX:integer )"
 base.strided.dsumkbn.ndarray,"base.strided.dsumkbn.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )"
-base.strided.dsumkbn2,"base.strided.dsumkbn2( N:integer, x:Float64Array, stride:integer )"
-base.strided.dsumkbn2.ndarray,"base.strided.dsumkbn2.ndarray( N:integer, x:Float64Array, stride:integer, offset:integer )"
+base.strided.dsumkbn2,"base.strided.dsumkbn2( N:integer, x:Float64Array, strideX:integer )"
+base.strided.dsumkbn2.ndarray,"base.strided.dsumkbn2.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )"
 base.strided.dsumors,"base.strided.dsumors( N:integer, x:Float64Array, stride:integer )"
 base.strided.dsumors.ndarray,"base.strided.dsumors.ndarray( N:integer, x:Float64Array, stride:integer, offset:integer )"
 base.strided.dsumpw,"base.strided.dsumpw( N:integer, x:Float64Array, stride:integer )"
@@ -2013,8 +2013,8 @@ base.strided.gapx,"base.strided.gapx( N:integer, alpha:number, x:Array|TypedArra
 base.strided.gapx.ndarray,"base.strided.gapx.ndarray( N:integer, alpha:number, x:Array|TypedArray, stride:integer, offset:integer )"
 base.strided.gapxsum,"base.strided.gapxsum( N:integer, alpha:number, x:Array|TypedArray, stride:integer )"
 base.strided.gapxsum.ndarray,"base.strided.gapxsum.ndarray( N:integer, alpha:number, x:Array|TypedArray, stride:integer, offset:integer )"
-base.strided.gapxsumkbn,"base.strided.gapxsumkbn( N:integer, alpha:number, x:Array|TypedArray, stride:integer )"
-base.strided.gapxsumkbn.ndarray,"base.strided.gapxsumkbn.ndarray( N:integer, alpha:number, x:Array|TypedArray, stride:integer, offset:integer )"
+base.strided.gapxsumkbn,"base.strided.gapxsumkbn( N:integer, alpha:number, x:Array|TypedArray, strideX:integer )"
+base.strided.gapxsumkbn.ndarray,"base.strided.gapxsumkbn.ndarray( N:integer, alpha:number, x:Array|TypedArray, strideX:integer, offsetX:integer )"
 base.strided.gapxsumkbn2,"base.strided.gapxsumkbn2( N:integer, alpha:number, x:Array|TypedArray, stride:integer )"
 base.strided.gapxsumkbn2.ndarray,"base.strided.gapxsumkbn2.ndarray( N:integer, alpha:number, x:Array|TypedArray, stride:integer, offset:integer )"
 base.strided.gapxsumors,"base.strided.gapxsumors( N:integer, alpha:number, x:Array|TypedArray, stride:integer )"
@@ -2290,10 +2290,10 @@ base.strided.smax,"base.strided.smax( N:integer, x:Float32Array, strideX:integer
 base.strided.smax.ndarray,"base.strided.smax.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"
 base.strided.smaxabs,"base.strided.smaxabs( N:integer, x:Float32Array, strideX:integer )"
 base.strided.smaxabs.ndarray,"base.strided.smaxabs.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"
-base.strided.smaxabssorted,"base.strided.smaxabssorted( N:integer, x:Float32Array, stride:integer )"
-base.strided.smaxabssorted.ndarray,"base.strided.smaxabssorted.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )"
-base.strided.smaxsorted,"base.strided.smaxsorted( N:integer, x:Float32Array, stride:integer )"
-base.strided.smaxsorted.ndarray,"base.strided.smaxsorted.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )"
+base.strided.smaxabssorted,"base.strided.smaxabssorted( N:integer, x:Float32Array, strideX:integer )"
+base.strided.smaxabssorted.ndarray,"base.strided.smaxabssorted.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"
+base.strided.smaxsorted,"base.strided.smaxsorted( N:integer, x:Float32Array, strideX:integer )"
+base.strided.smaxsorted.ndarray,"base.strided.smaxsorted.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"
 base.strided.smean,"base.strided.smean( N:integer, x:Float32Array, stride:integer )"
 base.strided.smean.ndarray,"base.strided.smean.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )"
 base.strided.smeankbn,"base.strided.smeankbn( N:integer, x:Float32Array, stride:integer )"
diff --git a/lib/node_modules/@stdlib/repl/typed-signature/data/data.json b/lib/node_modules/@stdlib/repl/typed-signature/data/data.json
index 977c61334136..43bfbef6bad3 100644
--- a/lib/node_modules/@stdlib/repl/typed-signature/data/data.json
+++ b/lib/node_modules/@stdlib/repl/typed-signature/data/data.json
@@ -1 +1 @@
-[["abs","abs( x:ndarray|ArrayLikeObject|number[, options:Object] )"],["abs.assign","abs.assign( x:ndarray|ArrayLikeObject, y:ndarray|ArrayLikeObject )"],["acartesianPower","acartesianPower( x:ArrayLikeObject, n:integer )"],["acartesianProduct","acartesianProduct( x1:ArrayLikeObject, x2:ArrayLikeObject )"],["acartesianSquare","acartesianSquare( x:ArrayLikeObject )"],["acronym","acronym( str:string[, options:Object] )"],["aempty","aempty( length:integer[, dtype:string] )"],["aemptyLike","aemptyLike( x:TypedArray|Array[, dtype:string] )"],["AFINN_96","AFINN_96()"],["AFINN_111","AFINN_111()"],["afull","afull( length:integer, value:any[, dtype:string] )"],["afullLike","afullLike( x:TypedArray|Array[, dtype:string] )"],["alias2pkg","alias2pkg( alias:string )"],["alias2related","alias2related( alias:string )"],["alias2standalone","alias2standalone( alias:string )"],["aliases","aliases( [namespace:string] )"],["allocUnsafe","allocUnsafe( size:integer )"],["amskfilter","amskfilter( 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offset:integer )"],["base.strided.smeanwd","base.strided.smeanwd( N:integer, x:Float32Array, stride:integer )"],["base.strided.smeanwd.ndarray","base.strided.smeanwd.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )"],["base.strided.smediansorted","base.strided.smediansorted( N:integer, x:Float32Array, stride:integer )"],["base.strided.smediansorted.ndarray","base.strided.smediansorted.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )"],["base.strided.smidrange","base.strided.smidrange( N:integer, x:Float32Array, strideX:integer )"],["base.strided.smidrange.ndarray","base.strided.smidrange.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.smin","base.strided.smin( N:integer, x:Float32Array, strideX:integer )"],["base.strided.smin.ndarray","base.strided.smin.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.sminabs","base.strided.sminabs( N:integer, x:Float32Array, strideX:integer )"],["base.strided.sminabs.ndarray","base.strided.sminabs.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.sminsorted","base.strided.sminsorted( N:integer, x:Float32Array, stride:integer )"],["base.strided.sminsorted.ndarray","base.strided.sminsorted.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )"],["base.strided.smskabs","base.strided.smskabs( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskabs.ndarray","base.strided.smskabs.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskabs2","base.strided.smskabs2( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskabs2.ndarray","base.strided.smskabs2.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskcbrt","base.strided.smskcbrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskcbrt.ndarray","base.strided.smskcbrt.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskceil","base.strided.smskceil( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskceil.ndarray","base.strided.smskceil.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskdeg2rad","base.strided.smskdeg2rad( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskdeg2rad.ndarray","base.strided.smskdeg2rad.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskfloor","base.strided.smskfloor( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskfloor.ndarray","base.strided.smskfloor.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskinv","base.strided.smskinv( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskinv.ndarray","base.strided.smskinv.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskmap","base.strided.smskmap( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer, fcn:Function )"],["base.strided.smskmap.ndarray","base.strided.smskmap.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Uint8Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer, fcn:Function )"],["base.strided.smskmap2","base.strided.smskmap2( N:integer, x:Float32Array, sx:integer, y:Float32Array, sy:integer, m:Uint8Array, sm:integer, z:Float32Array, sz:integer, fcn:Function )"],["base.strided.smskmap2.ndarray","base.strided.smskmap2.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, y:Float32Array, sy:integer, oy:integer, m:Uint8Array, sm:integer, om:integer, z:Float32Array, sz:integer, oz:integer, fcn:Function )"],["base.strided.smskmax","base.strided.smskmax( N:integer, x:Float32Array, strideX:integer, mask:Uint8Array, strideMask:integer )"],["base.strided.smskmax.ndarray","base.strided.smskmax.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )"],["base.strided.smskmin","base.strided.smskmin( N:integer, x:Float32Array, strideX:integer, mask:Uint8Array, strideMask:integer )"],["base.strided.smskmin.ndarray","base.strided.smskmin.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )"],["base.strided.smskramp","base.strided.smskramp( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskramp.ndarray","base.strided.smskramp.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskrange","base.strided.smskrange( N:integer, x:Float32Array, strideX:integer, mask:Uint8Array, strideMask:integer )"],["base.strided.smskrange.ndarray","base.strided.smskrange.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )"],["base.strided.smskrsqrt","base.strided.smskrsqrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskrsqrt.ndarray","base.strided.smskrsqrt.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smsksqrt","base.strided.smsksqrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smsksqrt.ndarray","base.strided.smsksqrt.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smsktrunc","base.strided.smsktrunc( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smsktrunc.ndarray","base.strided.smsktrunc.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.snanmax","base.strided.snanmax( N:integer, x:Float32Array, strideX:integer )"],["base.strided.snanmax.ndarray","base.strided.snanmax.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.snanmaxabs","base.strided.snanmaxabs( N:integer, x:Float32Array, strideX:integer )"],["base.strided.snanmaxabs.ndarray","base.strided.snanmaxabs.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.snanmean","base.strided.snanmean( N:integer, x:Float32Array, stride:integer )"],["base.strided.snanmean.ndarray","base.strided.snanmean.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )"],["base.strided.snanmeanors","base.strided.snanmeanors( N:integer, x:Float32Array, stride:integer )"],["base.strided.snanmeanors.ndarray","base.strided.snanmeanors.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer 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value:any )"],["isPositiveNumberArray","isPositiveNumberArray( value:any )"],["isPositiveNumberArray.primitives","isPositiveNumberArray.primitives( value:any )"],["isPositiveNumberArray.objects","isPositiveNumberArray.objects( value:any )"],["isPositiveZero","isPositiveZero( value:any )"],["isPositiveZero.isPrimitive","isPositiveZero.isPrimitive( value:any )"],["isPositiveZero.isObject","isPositiveZero.isObject( value:any )"],["isPrime","isPrime( value:any )"],["isPrime.isPrimitive","isPrime.isPrimitive( value:any )"],["isPrime.isObject","isPrime.isObject( value:any )"],["isPrimitive","isPrimitive( value:any )"],["isPrimitiveArray","isPrimitiveArray( value:any )"],["isPRNGLike","isPRNGLike( value:any )"],["isProbability","isProbability( value:any )"],["isProbability.isPrimitive","isProbability.isPrimitive( value:any )"],["isProbability.isObject","isProbability.isObject( value:any )"],["isProbabilityArray","isProbabilityArray( value:any 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value:any )"],["isRelativePath.posix","isRelativePath.posix( value:any )"],["isRelativePath.win32","isRelativePath.win32( value:any )"],["isRelativeURI","isRelativeURI( value:any )"],["isSafeInteger","isSafeInteger( value:any )"],["isSafeInteger.isPrimitive","isSafeInteger.isPrimitive( value:any )"],["isSafeInteger.isObject","isSafeInteger.isObject( value:any )"],["isSafeIntegerArray","isSafeIntegerArray( value:any )"],["isSafeIntegerArray.primitives","isSafeIntegerArray.primitives( value:any )"],["isSafeIntegerArray.objects","isSafeIntegerArray.objects( value:any )"],["isSameArray","isSameArray( v1:any, v2:any )"],["isSameArrayLike","isSameArrayLike( v1:any, v2:any )"],["isSameComplex64","isSameComplex64( v1:any, v2:any )"],["isSameComplex64Array","isSameComplex64Array( v1:any, v2:any )"],["isSameComplex128","isSameComplex128( v1:any, v2:any )"],["isSameComplex128Array","isSameComplex128Array( v1:any, v2:any )"],["isSameDateObject","isSameDateObject( d1, d2 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)"],["isURIError","isURIError( value:any )"],["isVectorLike","isVectorLike( value:any )"],["isWebAssemblyMemory","isWebAssemblyMemory( value:any )"],["isWellFormedString","isWellFormedString( str:any )"],["isWellFormedString.isPrimitive","isWellFormedString.isPrimitive( str:any )"],["isWellFormedString.isObject","isWellFormedString.isObject( str:any )"],["isWhitespace","isWhitespace( str:string )"],["isWritableProperty","isWritableProperty( value:any, property:any )"],["isWritablePropertyIn","isWritablePropertyIn( value:any, property:any )"],["isWriteOnlyProperty","isWriteOnlyProperty( value:any, property:any )"],["isWriteOnlyPropertyIn","isWriteOnlyPropertyIn( value:any, property:any )"],["iterAbs","iterAbs( iterator:Object )"],["iterAbs2","iterAbs2( iterator:Object )"],["iterAcos","iterAcos( iterator:Object )"],["iterAcosh","iterAcosh( iterator:Object )"],["iterAcot","iterAcot( iterator:Object )"],["iterAcoth","iterAcoth( iterator:Object )"],["iterAcovercos","iterAcovercos( iterator:Object )"],["iterAcoversin","iterAcoversin( iterator:Object )"],["iterAdd","iterAdd( iter0:Object, ...iterator:Object )"],["iterAdvance","iterAdvance( iterator:Object[, n:integer] )"],["iterAhavercos","iterAhavercos( iterator:Object )"],["iterAhaversin","iterAhaversin( iterator:Object )"],["iterAny","iterAny( iterator:Object )"],["iterAnyBy","iterAnyBy( iterator:Object, predicate:Function[, thisArg:any ] )"],["iterAsin","iterAsin( iterator:Object )"],["iterAsinh","iterAsinh( iterator:Object )"],["iterAtan","iterAtan( iterator:Object )"],["iterAtan2","iterAtan2( y:Object|number, x:Object|number )"],["iterAtanh","iterAtanh( iterator:Object )"],["iterator2array","iterator2array( iterator:Object[, out:ArrayLikeObject][, mapFcn:Function[, thisArg:any]] )"],["iterator2arrayview","iterator2arrayview( iterator:Object, dest:ArrayLikeObject[, begin:integer[, end:integer]][, mapFcn:Function[, thisArg:any]] )"],["iterator2arrayviewRight","iterator2arrayviewRight( iterator:Object, dest:ArrayLikeObject[, begin:integer[, end:integer]][, mapFcn:Function[, thisArg:any]] )"],["iteratorStream","iteratorStream( iterator:Object[, options:Object] )"],["iteratorStream.factory","iteratorStream.factory( [options:Object] )"],["iteratorStream.objectMode","iteratorStream.objectMode( iterator:Object[, options:Object] )"],["IteratorSymbol","IteratorSymbol"],["iterAvercos","iterAvercos( iterator:Object )"],["iterAversin","iterAversin( iterator:Object )"],["iterawgn","iterawgn( iterator:Object, sigma:number[, options:Object] )"],["iterawln","iterawln( iterator:Object, sigma:number[, options:Object] )"],["iterawun","iterawun( iterator:Object, sigma:number[, options:Object] )"],["iterBartlettHannPulse","iterBartlettHannPulse( [options:Object] )"],["iterBartlettPulse","iterBartlettPulse( [options:Object] )"],["iterBesselj0","iterBesselj0( iterator:Object )"],["iterBesselj1","iterBesselj1( iterator:Object )"],["iterBessely0","iterBessely0( iterator:Object 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)"],["iterCounter","iterCounter( iterator:Object )"],["iterCovercos","iterCovercos( iterator:Object )"],["iterCoversin","iterCoversin( iterator:Object )"],["iterCubesSeq","iterCubesSeq( [options:Object] )"],["itercugmean","itercugmean( iterator:Object )"],["itercuhmean","itercuhmean( iterator:Object )"],["itercumax","itercumax( iterator:Object )"],["itercumaxabs","itercumaxabs( iterator:Object )"],["itercumean","itercumean( iterator:Object )"],["itercumeanabs","itercumeanabs( iterator:Object )"],["itercumeanabs2","itercumeanabs2( iterator:Object )"],["itercumidrange","itercumidrange( iterator:Object )"],["itercumin","itercumin( iterator:Object )"],["itercuminabs","itercuminabs( iterator:Object )"],["itercuprod","itercuprod( iterator:Object )"],["itercurange","itercurange( iterator:Object )"],["itercusum","itercusum( iterator:Object )"],["itercusumabs","itercusumabs( iterator:Object )"],["itercusumabs2","itercusumabs2( iterator:Object )"],["iterDatespace","iterDatespace( start:integer|string|Date, stop:integer|string|Date[, N:integer][, options:Object] )"],["iterDedupe","iterDedupe( iterator:Object[, limit:integer] )"],["iterDedupeBy","iterDedupeBy( iterator:Object, [limit:integer,] fcn:Function )"],["iterDeg2rad","iterDeg2rad( iterator:Object )"],["iterDigamma","iterDigamma( iterator:Object )"],["iterDiracComb","iterDiracComb( [options:Object] )"],["iterDiracDelta","iterDiracDelta( iterator:Object )"],["iterDivide","iterDivide( iter0:Object, ...iterator:Object )"],["iterDoWhileEach","iterDoWhileEach( iterator:Object, predicate:Function, fcn:Function[, thisArg:any] )"],["iterEllipe","iterEllipe( iterator:Object )"],["iterEllipk","iterEllipk( iterator:Object )"],["iterEmpty","iterEmpty()"],["iterErf","iterErf( iterator:Object )"],["iterErfc","iterErfc( iterator:Object )"],["iterErfcinv","iterErfcinv( iterator:Object )"],["iterErfinv","iterErfinv( iterator:Object )"],["iterEta","iterEta( iterator:Object )"],["iterEvenIntegersSeq","iterEvenIntegersSeq( [options:Object] )"],["iterEvery","iterEvery( iterator:Object )"],["iterEveryBy","iterEveryBy( iterator:Object, predicate:Function[, thisArg:any ] )"],["iterExp","iterExp( iterator:Object )"],["iterExp2","iterExp2( iterator:Object )"],["iterExp10","iterExp10( iterator:Object )"],["iterExpit","iterExpit( iterator:Object )"],["iterExpm1","iterExpm1( iterator:Object )"],["iterExpm1rel","iterExpm1rel( iterator:Object )"],["iterFactorial","iterFactorial( iterator:Object )"],["iterFactorialln","iterFactorialln( iterator:Object )"],["iterFactorialsSeq","iterFactorialsSeq( [options:Object] )"],["iterFibonacciSeq","iterFibonacciSeq( [options:Object] )"],["iterFifthPowersSeq","iterFifthPowersSeq( [options:Object] )"],["iterFill","iterFill( iterator:Object, value:any[, begin:integer[, end:integer]] )"],["iterFilter","iterFilter( iterator:Object, predicate:Function[, thisArg:any] )"],["iterFilterMap","iterFilterMap( iterator:Object, fcn:Function[, thisArg:any] )"],["iterFirst","iterFirst( iterator:Object )"],["iterFlatTopPulse","iterFlatTopPulse( [options:Object] )"],["iterFloor","iterFloor( iterator:Object )"],["iterFloor2","iterFloor2( iterator:Object )"],["iterFloor10","iterFloor10( iterator:Object )"],["iterFlow","iterFlow( methods:Object )"],["iterForEach","iterForEach( iterator:Object, fcn:Function[, thisArg:any] )"],["iterFourthPowersSeq","iterFourthPowersSeq( [options:Object] )"],["iterFresnelc","iterFresnelc( iterator:Object )"],["iterFresnels","iterFresnels( iterator:Object )"],["iterGamma","iterGamma( iterator:Object )"],["iterGamma1pm1","iterGamma1pm1( iterator:Object )"],["iterGammaln","iterGammaln( iterator:Object )"],["iterHacovercos","iterHacovercos( iterator:Object )"],["iterHacoversin","iterHacoversin( iterator:Object )"],["iterHannPulse","iterHannPulse( [options:Object] )"],["iterHavercos","iterHavercos( iterator:Object )"],["iterHaversin","iterHaversin( iterator:Object )"],["iterHead","iterHead( iterator:Object, n:integer )"],["iterIncrspace","iterIncrspace( start:number, stop:number[, increment:number] )"],["iterIntegersSeq","iterIntegersSeq( [options:Object] )"],["iterIntersection","iterIntersection( iter0:Object, ...iterator:Object )"],["iterIntersectionByHash","iterIntersectionByHash( iter0:Object, ...iterator:Object, hashFcn:Function[, thisArg:any] )"],["iterInv","iterInv( iterator:Object )"],["iterLanczosPulse","iterLanczosPulse( [options:Object] )"],["iterLast","iterLast( iterator:Object )"],["iterLength","iterLength( iterator:Object )"],["iterLinspace","iterLinspace( start:number, stop:number[, N:integer] )"],["iterLn","iterLn( iterator:Object )"],["iterLog","iterLog( x:Object|number, b:Object|number )"],["iterLog1mexp","iterLog1mexp( iterator:Object )"],["iterLog1p","iterLog1p( iterator:Object )"],["iterLog1pexp","iterLog1pexp( iterator:Object )"],["iterLog2","iterLog2( iterator:Object )"],["iterLog10","iterLog10( iterator:Object )"],["iterLogit","iterLogit( iterator:Object )"],["iterLogspace","iterLogspace( start:number, stop:number[, N:integer][, options:Object] )"],["iterLucasSeq","iterLucasSeq( [options:Object] )"],["iterMap","iterMap( iterator:Object, fcn:Function[, thisArg:any] )"],["iterMapN","iterMapN( iter0:Object, ...iterator:Object, fcn:Function[, thisArg:any] )"],["itermax","itermax( iterator:Object )"],["itermaxabs","itermaxabs( iterator:Object )"],["itermean","itermean( iterator:Object )"],["itermeanabs","itermeanabs( iterator:Object )"],["itermeanabs2","itermeanabs2( iterator:Object )"],["itermidrange","itermidrange( iterator:Object )"],["itermin","itermin( iterator:Object )"],["iterminabs","iterminabs( iterator:Object )"],["itermmax","itermmax( iterator:Object, W:integer )"],["itermmaxabs","itermmaxabs( iterator:Object, W:integer )"],["itermmean","itermmean( iterator:Object, W:integer )"],["itermmeanabs","itermmeanabs( iterator:Object, W:integer )"],["itermmeanabs2","itermmeanabs2( iterator:Object, W:integer )"],["itermmidrange","itermmidrange( iterator:Object, W:integer )"],["itermmin","itermmin( iterator:Object, W:integer )"],["itermminabs","itermminabs( iterator:Object, W:integer )"],["iterMod","iterMod( iter0:Object, ...iterator:Object )"],["itermprod","itermprod( iterator:Object, W:integer )"],["itermrange","itermrange( iterator:Object, W:integer )"],["itermsum","itermsum( iterator:Object, W:integer )"],["itermsumabs","itermsumabs( iterator:Object, W:integer )"],["itermsumabs2","itermsumabs2( iterator:Object, W:integer )"],["iterMultiply","iterMultiply( iter0:Object, ...iterator:Object )"],["iterNegaFibonacciSeq","iterNegaFibonacciSeq( [options:Object] )"],["iterNegaLucasSeq","iterNegaLucasSeq( [options:Object] )"],["iterNegativeEvenIntegersSeq","iterNegativeEvenIntegersSeq( [options:Object] )"],["iterNegativeIntegersSeq","iterNegativeIntegersSeq( [options:Object] )"],["iterNegativeOddIntegersSeq","iterNegativeOddIntegersSeq( [options:Object] )"],["iterNone","iterNone( iterator:Object )"],["iterNoneBy","iterNoneBy( iterator:Object, predicate:Function[, thisArg:any ] )"],["iterNonFibonacciSeq","iterNonFibonacciSeq( [options:Object] )"],["iterNonNegativeEvenIntegersSeq","iterNonNegativeEvenIntegersSeq( [options:Object] )"],["iterNonNegativeIntegersSeq","iterNonNegativeIntegersSeq( [options:Object] )"],["iterNonPositiveEvenIntegersSeq","iterNonPositiveEvenIntegersSeq( [options:Object] )"],["iterNonPositiveIntegersSeq","iterNonPositiveIntegersSeq( [options:Object] )"],["iterNonSquaresSeq","iterNonSquaresSeq( [options:Object] )"],["iterNth","iterNth( iterator:Object, n:integer )"],["iterOddIntegersSeq","iterOddIntegersSeq( [options:Object] )"],["iterPeriodicSinc","iterPeriodicSinc( n:integer[, options:Object] )"],["iterPipeline","iterPipeline( iterFcn:Function|Array[, ...iterFcn:Function] )"],["iterPop","iterPop( iterator:Object[, clbk:Function[, thisArg:any]] )"],["iterPositiveEvenIntegersSeq","iterPositiveEvenIntegersSeq( [options:Object] )"],["iterPositiveIntegersSeq","iterPositiveIntegersSeq( [options:Object] )"],["iterPositiveOddIntegersSeq","iterPositiveOddIntegersSeq( [options:Object] )"],["iterPow","iterPow( base:Object|number, exponent:Object|number )"],["iterPrimesSeq","iterPrimesSeq( [options:Object] )"],["iterprod","iterprod( iterator:Object )"],["iterPulse","iterPulse( [options:Object] )"],["iterPush","iterPush( iterator:Object, ...items:any )"],["iterRad2deg","iterRad2deg( iterator:Object )"],["iterRamp","iterRamp( iterator:Object )"],["iterrange","iterrange( iterator:Object )"],["iterReject","iterReject( iterator:Object, predicate:Function[, thisArg:any] )"],["iterReplicate","iterReplicate( iterator:Object, n:integer )"],["iterReplicateBy","iterReplicateBy( iterator:Object, fcn:Function[, thisArg:any] )"],["iterRound","iterRound( iterator:Object )"],["iterRound2","iterRound2( iterator:Object )"],["iterRound10","iterRound10( iterator:Object )"],["iterRsqrt","iterRsqrt( iterator:Object )"],["iterSawtoothWave","iterSawtoothWave( [options:Object] )"],["iterShift","iterShift( iterator:Object[, clbk:Function[, thisArg:any]] )"],["iterSignum","iterSignum( iterator:Object )"],["iterSin","iterSin( iterator:Object )"],["iterSinc","iterSinc( iterator:Object )"],["iterSineWave","iterSineWave( [options:Object] )"],["iterSinh","iterSinh( iterator:Object )"],["iterSinpi","iterSinpi( iterator:Object )"],["iterSlice","iterSlice( iterator:Object[, begin:integer[, end:integer]] )"],["iterSome","iterSome( iterator:Object, n:number )"],["iterSomeBy","iterSomeBy( iterator:Object, n:integer, predicate:Function[, thisArg:any ] )"],["iterSpence","iterSpence( iterator:Object )"],["iterSqrt","iterSqrt( iterator:Object )"],["iterSqrt1pm1","iterSqrt1pm1( iterator:Object )"],["iterSquaredTriangularSeq","iterSquaredTriangularSeq( [options:Object] )"],["iterSquaresSeq","iterSquaresSeq( [options:Object] )"],["iterSquareWave","iterSquareWave( [options:Object] )"],["iterstdev","iterstdev( iterator:Object[, mean:number] )"],["iterStep","iterStep( start:number, increment:number[, N:number] )"],["iterStrided","iterStrided( iterator:Object, stride:integer[, offset:integer[, eager:boolean]] )"],["iterStridedBy","iterStridedBy( iterator:Object, fcn:Function[, offset:integer[, eager:boolean]][, thisArg:any] )"],["iterSubtract","iterSubtract( iter0:Object, ...iterator:Object )"],["itersum","itersum( iterator:Object )"],["itersumabs","itersumabs( iterator:Object )"],["itersumabs2","itersumabs2( iterator:Object )"],["iterTan","iterTan( iterator:Object )"],["iterTanh","iterTanh( iterator:Object )"],["iterThunk","iterThunk( iterFcn:Function[, ...args:any] )"],["iterTriangleWave","iterTriangleWave( [options:Object] )"],["iterTriangularSeq","iterTriangularSeq( [options:Object] )"],["iterTribonnaciSeq","iterTribonnaciSeq( [options:Object] )"],["iterTrigamma","iterTrigamma( iterator:Object )"],["iterTrunc","iterTrunc( iterator:Object )"],["iterTrunc2","iterTrunc2( iterator:Object )"],["iterTrunc10","iterTrunc10( iterator:Object )"],["iterUnion","iterUnion( iter0:Object, ...iterator:Object )"],["iterUnique","iterUnique( iterator:Object )"],["iterUniqueBy","iterUniqueBy( iterator:Object, predicate:Function[, thisArg:any] )"],["iterUniqueByHash","iterUniqueByHash( iterator:Object, hashFcn:Function[, thisArg:any] )"],["iterUnitspace","iterUnitspace( start:number[, stop:number] )"],["iterUnshift","iterUnshift( iterator:Object, ...items:any )"],["iterUntilEach","iterUntilEach( iterator:Object, predicate:Function, fcn:Function[, thisArg:any] )"],["itervariance","itervariance( iterator:Object[, mean:number] )"],["iterVercos","iterVercos( iterator:Object )"],["iterVersin","iterVersin( iterator:Object )"],["iterWhileEach","iterWhileEach( iterator:Object, predicate:Function, fcn:Function[, thisArg:any] )"],["iterZeta","iterZeta( iterator:Object )"],["joinStream","joinStream( [options:Object] )"],["joinStream.factory","joinStream.factory( [options:Object] )"],["joinStream.objectMode","joinStream.objectMode( [options:Object] )"],["kde2d","kde2d( x:Array<number>, y:Array<number>[, options:Object] )"],["kebabcase","kebabcase( str:string )"],["keyBy","keyBy( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )"],["keyByRight","keyByRight( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )"],["keysIn","keysIn( obj:any )"],["kruskalTest","kruskalTest( ...x:Array[, options:Object] )"],["kstest","kstest( x:Array<number>, y:Function|string[, ...params:number][, options:Object] )"],["last","last( str:string[, n:integer][, options:Object] )"],["leveneTest","leveneTest( x:Array<number>[, ...y:Array<number>[, options:Object]] )"],["LinkedList","LinkedList()"],["linspace","linspace( start:number|ComplexLike, stop:number|ComplexLike, length:integer[, options:Object] )"],["linspace.assign","linspace.assign( start:number|ComplexLike, stop:number|ComplexLike, out:ArrayLikeObject[, options:Object] )"],["LIU_NEGATIVE_OPINION_WORDS_EN","LIU_NEGATIVE_OPINION_WORDS_EN()"],["LIU_POSITIVE_OPINION_WORDS_EN","LIU_POSITIVE_OPINION_WORDS_EN()"],["LN_HALF","LN_HALF"],["LN_PI","LN_PI"],["LN_SQRT_TWO_PI","LN_SQRT_TWO_PI"],["LN_TWO_PI","LN_TWO_PI"],["LN2","LN2"],["LN10","LN10"],["LOG2E","LOG2E"],["LOG10E","LOG10E"],["logspace","logspace( a:number, b:number[, length:integer] )"],["lowercase","lowercase( str:string )"],["lowercaseKeys","lowercaseKeys( obj:Object )"],["lowess","lowess( x:Array<number>, y:Array<number>[, options:Object] )"],["lpad","lpad( str:string, len:integer[, pad:string] )"],["ltrim","ltrim( str:string )"],["ltrimN","ltrimN( str:string, n:integer[, chars:Array|string] )"],["MALE_FIRST_NAMES_EN","MALE_FIRST_NAMES_EN()"],["map","map( arr:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )"],["map.assign","map.assign( arr:ArrayLikeObject|ndarray, out:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )"],["map2","map2( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )"],["map2.assign","map2.assign( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, out:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )"],["map2d","map2d( arr:ArrayLikeObject<ArrayLikeObject>, fcn:Function[, thisArg:any] )"],["map2Right","map2Right( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )"],["map2Right.assign","map2Right.assign( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, out:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )"],["map3d","map3d( arr:ArrayLikeObject<ArrayLikeObject<ArrayLikeObject>>, fcn:Function[, thisArg:any] )"],["map4d","map4d( arr:ArrayLikeObject<ArrayLikeObject>, fcn:Function[, thisArg:any] )"],["map5d","map5d( arr:ArrayLikeObject<ArrayLikeObject>, fcn:Function[, thisArg:any] )"],["mapArguments","mapArguments( fcn:Function, clbk:Function[, thisArg:any] )"],["mapFun","mapFun( fcn:Function, n:integer[, thisArg:any] )"],["mapFunAsync","mapFunAsync( fcn:Function, n:integer, [options:Object,] done:Function )"],["mapFunAsync.factory","mapFunAsync.factory( [options:Object,] fcn:Function )"],["mapKeys","mapKeys( obj:Object, transform:Function )"],["mapKeysAsync","mapKeysAsync( obj:Object, [options:Object,] transform:Function, done:Function )"],["mapKeysAsync.factory","mapKeysAsync.factory( [options:Object,] transform:Function )"],["mapReduce","mapReduce( arr:ArrayLikeObject|ndarray, initial:any, mapper:Function, reducer:Function[, thisArg:any] )"],["mapReduceRight","mapReduceRight( arr:ArrayLikeObject|ndarray, initial:any, mapper:Function, reducer:Function[, thisArg:any] )"],["mapRight","mapRight( arr:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )"],["mapRight.assign","mapRight.assign( arr:ArrayLikeObject|ndarray, out:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )"],["mapValues","mapValues( obj:Object, transform:Function )"],["mapValuesAsync","mapValuesAsync( obj:Object, [options:Object,] transform:Function, done:Function )"],["mapValuesAsync.factory","mapValuesAsync.factory( [options:Object,] transform:Function )"],["maskArguments","maskArguments( fcn:Function, mask:ArrayLikeObject[, thisArg:any] )"],["MAX_ARRAY_LENGTH","MAX_ARRAY_LENGTH"],["MAX_TYPED_ARRAY_LENGTH","MAX_TYPED_ARRAY_LENGTH"],["maybeBroadcastArray","maybeBroadcastArray( x:ndarray, shape:ArrayLikeObject )"],["maybeBroadcastArrays","maybeBroadcastArrays( ...arrays:ndarray|ArrayLikeObject<ndarray> )"],["memoize","memoize( fcn:Function[, hashFunction:Function] )"],["merge","merge( target:Object, ...source:Object )"],["merge.factory","merge.factory( options:Object )"],["MILLISECONDS_IN_DAY","MILLISECONDS_IN_DAY"],["MILLISECONDS_IN_HOUR","MILLISECONDS_IN_HOUR"],["MILLISECONDS_IN_MINUTE","MILLISECONDS_IN_MINUTE"],["MILLISECONDS_IN_SECOND","MILLISECONDS_IN_SECOND"],["MILLISECONDS_IN_WEEK","MILLISECONDS_IN_WEEK"],["MINARD_NAPOLEONS_MARCH","MINARD_NAPOLEONS_MARCH( [options:Object] )"],["MINUTES_IN_DAY","MINUTES_IN_DAY"],["MINUTES_IN_HOUR","MINUTES_IN_HOUR"],["MINUTES_IN_WEEK","MINUTES_IN_WEEK"],["minutesInMonth","minutesInMonth( [month:string|Date|integer[, year:integer]] )"],["minutesInYear","minutesInYear( [value:integer|Date] )"],["MOBY_DICK","MOBY_DICK()"],["MONTH_NAMES_EN","MONTH_NAMES_EN()"],["MONTHS_IN_YEAR","MONTHS_IN_YEAR"],["moveProperty","moveProperty( source:Object, prop:string, target:Object )"],["MultiSlice","MultiSlice( ...slice )"],["MultiSlice.prototype.ndims","MultiSlice.prototype.ndims"],["MultiSlice.prototype.data","MultiSlice.prototype.data"],["MultiSlice.prototype.toString","MultiSlice.prototype.toString()"],["MultiSlice.prototype.toJSON","MultiSlice.prototype.toJSON()"],["namedtypedtuple","namedtypedtuple( fields:Array<string>[, options:Object] )"],["NAN","NAN"],["naryFunction","naryFunction( fcn:Function, arity:integer[, thisArg:any] )"],["nativeClass","nativeClass( value:any )"],["ndarray","ndarray( dtype:string, buffer:ArrayLikeObject|TypedArray|Buffer, shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, offset:integer, order:string[, options:Object] )"],["ndarray.prototype.byteLength","ndarray.prototype.byteLength"],["ndarray.prototype.BYTES_PER_ELEMENT","ndarray.prototype.BYTES_PER_ELEMENT"],["ndarray.prototype.data","ndarray.prototype.data"],["ndarray.prototype.dtype","ndarray.prototype.dtype"],["ndarray.prototype.flags","ndarray.prototype.flags"],["ndarray.prototype.length","ndarray.prototype.length"],["ndarray.prototype.ndims","ndarray.prototype.ndims"],["ndarray.prototype.offset","ndarray.prototype.offset"],["ndarray.prototype.order","ndarray.prototype.order"],["ndarray.prototype.shape","ndarray.prototype.shape"],["ndarray.prototype.strides","ndarray.prototype.strides"],["ndarray.prototype.get","ndarray.prototype.get( ...idx:integer )"],["ndarray.prototype.iget","ndarray.prototype.iget( idx:integer )"],["ndarray.prototype.set","ndarray.prototype.set( ...idx:integer, v:any )"],["ndarray.prototype.iset","ndarray.prototype.iset( idx:integer, v:any )"],["ndarray.prototype.toString","ndarray.prototype.toString()"],["ndarray.prototype.toJSON","ndarray.prototype.toJSON()"],["ndarray2array","ndarray2array( x:ndarray )"],["ndarray2fancy","ndarray2fancy( x:ndarray[, options:Object] )"],["ndarray2fancy.factory","ndarray2fancy.factory( [options:Object] )"],["ndarray2fancy.idx","ndarray2fancy.idx( x:ndarray[, options:Object] )"],["ndarray2json","ndarray2json( x:ndarray )"],["ndarrayCastingModes","ndarrayCastingModes()"],["ndarrayDataBuffer","ndarrayDataBuffer( x:ndarray )"],["ndarrayDataType","ndarrayDataType( x:ndarray )"],["ndarrayDataTypes","ndarrayDataTypes( [kind:string] )"],["ndarrayDispatch","ndarrayDispatch( fcns:Function|ArrayLikeObject<Function>, types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, nout:integer )"],["ndarrayFlag","ndarrayFlag( x:ndarray, name:string|symbol )"],["ndarrayFlags","ndarrayFlags( x:ndarray )"],["ndarrayIndexModes","ndarrayIndexModes()"],["ndarraylike2ndarray","ndarraylike2ndarray( x:ndarrayLike[, options:Object] )"],["ndarrayMinDataType","ndarrayMinDataType( value:any )"],["ndarrayMostlySafeCasts","ndarrayMostlySafeCasts( [dtype:any] )"],["ndarrayNextDataType","ndarrayNextDataType( [dtype:any] )"],["ndarrayOffset","ndarrayOffset( x:ndarray )"],["ndarrayOrder","ndarrayOrder( x:ndarray )"],["ndarrayOrders","ndarrayOrders()"],["ndarrayPromotionRules","ndarrayPromotionRules( [dtype1:any, dtype2:any] )"],["ndarraySafeCasts","ndarraySafeCasts( [dtype:any] )"],["ndarraySameKindCasts","ndarraySameKindCasts( [dtype:any] )"],["ndarrayShape","ndarrayShape( x:ndarray )"],["ndarrayStride","ndarrayStride( x:ndarray, dim:integer )"],["ndarrayStrides","ndarrayStrides( x:ndarray )"],["ndat","ndat( x:ndarray[, ...indices:integer] )"],["ndempty","ndempty( shape:ArrayLikeObject<integer>|integer[, options:Object] )"],["ndemptyLike","ndemptyLike( x:ndarray[, options:Object] )"],["ndfilter","ndfilter( x:ndarray[, options:Object], predicate:Function[, thisArg:any] )"],["ndfilterMap","ndfilterMap( x:ndarray[, options:Object], fcn:Function[, thisArg:any] )"],["ndforEach","ndforEach( x:ndarray, fcn:Function[, thisArg:any] )"],["ndims","ndims( x:ndarray )"],["ndindex","ndindex( x:ndarray[, options:Object] )"],["ndindex.free","ndindex.free( id:string )"],["ndindex.get","ndindex.get( id:string )"],["ndindex.cartesianIndex","ndindex.cartesianIndex( x:ndarray[, options:Object] )"],["ndindex.linearIndex","ndindex.linearIndex( x:ndarray[, options:Object] )"],["ndindex.prototype.data","ndindex.prototype.data"],["ndindex.prototype.dtype","ndindex.prototype.dtype"],["ndindex.prototype.id","ndindex.prototype.id"],["ndindex.prototype.isCached","ndindex.prototype.isCached"],["ndindex.prototype.kind","ndindex.prototype.kind"],["ndindex.prototype.type","ndindex.prototype.type"],["ndindex.prototype.toString","ndindex.prototype.toString()"],["ndindex.prototype.toJSON","ndindex.prototype.toJSON()"],["nditerColumnEntries","nditerColumnEntries( x:ndarray[, options:Object] )"],["nditerColumns","nditerColumns( x:ndarray[, options:Object] )"],["nditerEntries","nditerEntries( x:ndarray[, options:Object] )"],["nditerIndices","nditerIndices( shape:Array<integer>[, options:Object] )"],["nditerInterleaveSubarrays","nditerInterleaveSubarrays( arr:ArrayLike<ndarray>, ndims:integer )"],["nditerMatrices","nditerMatrices( x:ndarray[, options:Object] )"],["nditerMatrixEntries","nditerMatrixEntries( x:ndarray[, options:Object] )"],["nditerRowEntries","nditerRowEntries( x:ndarray[, options:Object] )"],["nditerRows","nditerRows( x:ndarray[, options:Object] )"],["nditerSelectDimension","nditerSelectDimension( x:ndarray, dim:integer[, options:Object] )"],["nditerStacks","nditerStacks( x:ndarray, dims:Array<integer>[, options:Object] )"],["nditerSubarrays","nditerSubarrays( x:ndarray, ndims:integer[, options:Object] )"],["nditerValues","nditerValues( x:ndarray[, options:Object] )"],["ndmap","ndmap( x:ndarray[, options:Object], fcn:Function[, thisArg:any] )"],["ndreject","ndreject( x:ndarray[, options:Object], predicate:Function[, thisArg:any] )"],["ndslice","ndslice( x:ndarray, ...s:MultiSlice|Slice|null|undefined|integer|ArrayLike[, options:Object] )"],["ndsliceAssign","ndsliceAssign( x:ndarray, y:ndarray, ...s:MultiSlice|Slice|null|undefined|integer|ArrayLike[, options:Object] )"],["ndsliceDimension","ndsliceDimension( x:ndarray, dim:integer, slice:Slice|integer|null|undefined[, options:Object] )"],["ndsliceDimensionFrom","ndsliceDimensionFrom( x:ndarray, dim:integer, start:integer[, options:Object] )"],["ndsliceDimensionTo","ndsliceDimensionTo( x:ndarray, dim:integer, stop:integer[, options:Object] )"],["ndsliceFrom","ndsliceFrom( x:ndarray, ...start:null|void|integer[, options:Object] )"],["ndsliceTo","ndsliceTo( x:ndarray, ...stop:null|void|integer[, options:Object] )"],["ndzeros","ndzeros( shape:ArrayLikeObject<integer>|integer[, options:Object] )"],["ndzerosLike","ndzerosLike( x:ndarray[, options:Object] )"],["nextGraphemeClusterBreak","nextGraphemeClusterBreak( str:string[, fromIndex:integer] )"],["nextTick","nextTick( clbk[, ...args] )"],["NIGHTINGALES_ROSE","NIGHTINGALES_ROSE()"],["NINF","NINF"],["NODE_VERSION","NODE_VERSION"],["none","none( collection:Array|TypedArray|Object )"],["noneBy","noneBy( collection:Array|TypedArray|Object, predicate:Function[, thisArg:any ] )"],["noneByAsync","noneByAsync( collection:Array|TypedArray|Object, [options:Object,] predicate:Function, done:Function )"],["noneByAsync.factory","noneByAsync.factory( [options:Object,] predicate:Function )"],["noneByRight","noneByRight( collection:Array|TypedArray|Object, predicate:Function[, thisArg:any ] )"],["noneByRightAsync","noneByRightAsync( collection:Array|TypedArray|Object, [options:Object,] predicate:Function, done:Function )"],["noneByRightAsync.factory","noneByRightAsync.factory( [options:Object,] predicate:Function )"],["noneInBy","noneInBy( object:Object, predicate:Function[, thisArg:any ] )"],["nonEnumerableProperties","nonEnumerableProperties( value:any )"],["nonEnumerablePropertiesIn","nonEnumerablePropertiesIn( value:any )"],["nonEnumerablePropertyNames","nonEnumerablePropertyNames( value:any )"],["nonEnumerablePropertyNamesIn","nonEnumerablePropertyNamesIn( value:any )"],["nonEnumerablePropertySymbols","nonEnumerablePropertySymbols( value:any )"],["nonEnumerablePropertySymbolsIn","nonEnumerablePropertySymbolsIn( value:any )"],["noneOwnBy","noneOwnBy( object:Object, predicate:Function[, thisArg:any ] )"],["nonIndexKeys","nonIndexKeys( obj:any )"],["noop","noop()"],["now","now()"],["NUM_CPUS","NUM_CPUS"],["num2words","num2words( value:integer[, options:Object] )"],["Number","Number( value:number )"],["numel","numel( x:ndarray )"],["numelDimension","numelDimension( x:ndarray, dim:integer )"],["numGraphemeClusters","numGraphemeClusters( str:string )"],["Object","Object( value:any )"],["Object.assign","Object.assign( target:Object, ...sources:Object )"],["Object.create","Object.create( prototype:Object, properties:Object )"],["Object.defineProperties","Object.defineProperties( obj:Object, properties:Object )"],["Object.defineProperty","Object.defineProperty( obj:Object, key:string, descriptor:Object )"],["Object.entries","Object.entries( obj:Object )"],["Object.freeze","Object.freeze( obj:Object )"],["Object.getOwnPropertyDescriptor","Object.getOwnPropertyDescriptor( obj:Object, key:string )"],["Object.getOwnPropertyDescriptors","Object.getOwnPropertyDescriptors( obj:Object )"],["Object.getOwnPropertyNames","Object.getOwnPropertyNames( obj:Object )"],["Object.getOwnPropertySymbols","Object.getOwnPropertySymbols( obj:Object )"],["Object.getPrototypeOf","Object.getPrototypeOf( obj:Object )"],["Object.hasOwn","Object.hasOwn( obj:Object, p:string )"],["Object.is","Object.is( value1:any, value2:any )"],["Object.isExtensible","Object.isExtensible( obj:Object )"],["Object.isFrozen","Object.isFrozen( obj:Object )"],["Object.isSealed","Object.isSealed( obj:Object )"],["Object.keys","Object.keys( obj:Object )"],["Object.preventExtensions","Object.preventExtensions( obj:Object )"],["Object.seal","Object.seal( obj:Object )"],["Object.setPrototypeOf","Object.setPrototypeOf( obj:Object, proto:Object )"],["Object.values","Object.values( obj:Object )"],["Object.prototype.toLocaleString","Object.prototype.toLocaleString()"],["Object.prototype.toString","Object.prototype.toString()"],["Object.prototype.valueOf","Object.prototype.valueOf()"],["Object.prototype.hasOwnProperty","Object.prototype.hasOwnProperty( p:string )"],["Object.prototype.isPrototypeOf","Object.prototype.isPrototypeOf( obj:Object )"],["Object.prototype.propertyIsEnumerable","Object.prototype.propertyIsEnumerable( p:string )"],["Object.prototype.constructor","Object.prototype.constructor"],["objectEntries","objectEntries( obj:ObjectLike )"],["objectEntriesIn","objectEntriesIn( obj:ObjectLike )"],["objectFromEntries","objectFromEntries( entries:Array<Array> )"],["objectInverse","objectInverse( obj:ObjectLike[, options:Object] )"],["objectInverseBy","objectInverseBy( obj:ObjectLike, [options:Object,] transform:Function )"],["objectKeys","objectKeys( value:any )"],["objectValues","objectValues( obj:ObjectLike )"],["objectValuesIn","objectValuesIn( obj:ObjectLike )"],["omit","omit( obj:Object, keys:string|Array )"],["omitBy","omitBy( obj:Object, predicate:Function )"],["open","open( path:string|Buffer[, flags:string|number[, mode:integer]], clbk:Function )"],["open.sync","open.sync( path:string|Buffer[, flags:string|number[, mode:integer]] )"],["openURL","openURL( url:string )"],["ordinalize","ordinalize( value:string|integer[, options:Object] )"],["PACE_BOSTON_HOUSE_PRICES","PACE_BOSTON_HOUSE_PRICES()"],["pad","pad( str:string, len:integer[, options:Object] )"],["padjust","padjust( pvals:Array<number>, method:string[, comparisons:integer] )"],["papply","papply( fcn:Function, ...args:any )"],["papplyRight","papplyRight( fcn:Function, ...args:any )"],["parallel","parallel( files:Array<string>, [options:Object,] clbk:Function )"],["parseJSON","parseJSON( str:string[, reviver:Function] )"],["pascalcase","pascalcase( str:string 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)"],["random.strided.minstd.normalized.ndarray","random.strided.minstd.normalized.ndarray( N:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.minstdShuffle","random.strided.minstdShuffle( N:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.minstdShuffle.ndarray","random.strided.minstdShuffle.ndarray( N:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.minstdShuffle.normalized","random.strided.minstdShuffle.normalized( N:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.minstdShuffle.normalized.ndarray","random.strided.minstdShuffle.normalized.ndarray( N:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.mt19937","random.strided.mt19937( N:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.mt19937.ndarray","random.strided.mt19937.ndarray( N:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.mt19937.normalized","random.strided.mt19937.normalized( N:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.mt19937.normalized.ndarray","random.strided.mt19937.normalized.ndarray( N:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.normal","random.strided.normal( N:integer, mu:ArrayLikeObject, sm:integer, sigma:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.normal.ndarray","random.strided.normal.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, om:integer, sigma:ArrayLikeObject, ss:integer, os:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.poisson","random.strided.poisson( N:integer, lambda:ArrayLikeObject, sl:integer, out:ArrayLikeObject, so:integer )"],["random.strided.poisson.ndarray","random.strided.poisson.ndarray( N:integer, lambda:ArrayLikeObject, sl:integer, ol:integer, out:ArrayLikeObject, so:integer, oo:integer )"],["random.strided.poisson.factory","random.strided.poisson.factory( [options:Object] )"],["random.strided.poisson.PRNG","random.strided.poisson.PRNG"],["random.strided.poisson.seed","random.strided.poisson.seed"],["random.strided.poisson.seedLength","random.strided.poisson.seedLength"],["random.strided.poisson.state","random.strided.poisson.state"],["random.strided.poisson.stateLength","random.strided.poisson.stateLength"],["random.strided.poisson.byteLength","random.strided.poisson.byteLength"],["random.strided.randu","random.strided.randu( N:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.randu.ndarray","random.strided.randu.ndarray( N:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.rayleigh","random.strided.rayleigh( N:integer, sigma:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer 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options:Object] )"],["random.strided.weibull.ndarray","random.strided.weibull.ndarray( N:integer, k:ArrayLikeObject, sk:integer, ok:integer, lambda:ArrayLikeObject, sl:integer, ol:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["ranks","ranks( arr:Array<number>[, options:Object] )"],["readDir","readDir( path:string|Buffer, clbk:Function )"],["readDir.sync","readDir.sync( path:string|Buffer )"],["readFile","readFile( file:string|Buffer|integer[, options:Object|string], clbk:Function )"],["readFile.sync","readFile.sync( file:string|Buffer|integer[, options:Object|string] )"],["readFileList","readFileList( filepaths:Array<string>[, options:Object|string], clbk:Function )"],["readFileList.sync","readFileList.sync( filepaths:Array<string>[, options:Object|string] )"],["readJSON","readJSON( file:string|Buffer|integer[, options:Object|string], clbk:Function )"],["readJSON.sync","readJSON.sync( file:string|Buffer|integer[, options:Object|string] 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done:Function )"],["reduceRightAsync.factory","reduceRightAsync.factory( [options:Object,] fcn:Function )"],["reDurationString","reDurationString()"],["reDurationString.REGEXP","reDurationString.REGEXP"],["reEOL","reEOL( [options:Object] )"],["reEOL.REGEXP","reEOL.REGEXP"],["reEOL.REGEXP_CAPTURE","reEOL.REGEXP_CAPTURE"],["reExtendedLengthPath","reExtendedLengthPath()"],["reExtendedLengthPath.REGEXP","reExtendedLengthPath.REGEXP"],["reExtname","reExtname( [platform:string] )"],["reExtname.REGEXP","reExtname.REGEXP"],["reExtname.REGEXP_POSIX","reExtname.REGEXP_POSIX"],["reExtname.REGEXP_WIN32","reExtname.REGEXP_WIN32"],["reExtnamePosix","reExtnamePosix"],["reExtnamePosix.REGEXP","reExtnamePosix.REGEXP"],["reExtnameWindows","reExtnameWindows"],["reExtnameWindows.REGEXP","reExtnameWindows.REGEXP"],["reFilename","reFilename( [platform:string] 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ignoreCase:boolean] )"],["rename","rename( oldPath:string|Buffer, newPath:string|Buffer, clbk:Function )"],["rename.sync","rename.sync( oldPath:string|Buffer, newPath:string|Buffer )"],["reNativeFunction","reNativeFunction()"],["reNativeFunction.REGEXP","reNativeFunction.REGEXP"],["reorderArguments","reorderArguments( fcn:Function, indices:Array<integer>[, thisArg:any] )"],["repeat","repeat( str:string, n:integer )"],["replace","replace( str:string, search:string|RegExp, newval:string|Function )"],["replaceBefore","replaceBefore( str, search, replacement )"],["reRegExp","reRegExp()"],["reRegExp.REGEXP","reRegExp.REGEXP"],["rescape","rescape( str:string )"],["reSemVer","reSemVer()"],["reSemVer.REGEXP","reSemVer.REGEXP"],["resolveParentPath","resolveParentPath( path:string[, options:Object], clbk:Function )"],["resolveParentPath.sync","resolveParentPath.sync( path:string[, options:Object] )"],["resolveParentPathBy","resolveParentPathBy( path:string[, options:Object], predicate:Function, clbk:Function )"],["resolveParentPathBy.sync","resolveParentPathBy.sync( path:string[, options:Object], predicate:Function )"],["reUncPath","reUncPath()"],["reUncPath.REGEXP","reUncPath.REGEXP"],["reUtf16SurrogatePair","reUtf16SurrogatePair()"],["reUtf16SurrogatePair.REGEXP","reUtf16SurrogatePair.REGEXP"],["reUtf16UnpairedSurrogate","reUtf16UnpairedSurrogate()"],["reUtf16UnpairedSurrogate.REGEXP","reUtf16UnpairedSurrogate.REGEXP"],["reverseArguments","reverseArguments( fcn:Function[, thisArg:any] )"],["reverseString","reverseString( str:string[, options:Object] )"],["reviveBasePRNG","reviveBasePRNG( key:string, value:any )"],["reviveBuffer","reviveBuffer( key:string, value:any )"],["reviveComplex","reviveComplex( key:string, value:any )"],["reviveComplex64","reviveComplex64( key:string, value:any )"],["reviveComplex128","reviveComplex128( key:string, value:any )"],["reviveError","reviveError( key:string, value:any )"],["reviveRegExp","reviveRegExp( key:string, value:any 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)"],["SQRT_EPS","SQRT_EPS"],["SQRT_HALF","SQRT_HALF"],["SQRT_HALF_PI","SQRT_HALF_PI"],["SQRT_PHI","SQRT_PHI"],["SQRT_PI","SQRT_PI"],["SQRT_THREE","SQRT_THREE"],["SQRT_TWO","SQRT_TWO"],["SQRT_TWO_PI","SQRT_TWO_PI"],["SSA_US_BIRTHS_2000_2014","SSA_US_BIRTHS_2000_2014()"],["sswap","sswap( x:ndarray, y:ndarray[, dim:integer] )"],["Stack","Stack()"],["standalone2pkg","standalone2pkg( pkg:string )"],["STANDARD_CARD_DECK","STANDARD_CARD_DECK()"],["startcase","startcase( str:string )"],["startsWith","startsWith( str:string, search:string[, position:integer] )"],["STOPWORDS_EN","STOPWORDS_EN()"],["strided.abs","strided.abs( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.abs.ndarray","strided.abs.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.abs2","strided.abs2( N:integer, dtypeX:any, x:ArrayLikeObject, 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clbk:Function[, thisArg:any] )"],["strided.acothBy","strided.acothBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.acothBy.ndarray","strided.acothBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.acovercosBy","strided.acovercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.acovercosBy.ndarray","strided.acovercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.acoversinBy","strided.acoversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.acoversinBy.ndarray","strided.acoversinBy.ndarray( 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)"],["strided.ahavercosBy","strided.ahavercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.ahavercosBy.ndarray","strided.ahavercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.ahaversinBy","strided.ahaversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.ahaversinBy.ndarray","strided.ahaversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.asinBy","strided.asinBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.asinBy.ndarray","strided.asinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.asinhBy","strided.asinhBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.asinhBy.ndarray","strided.asinhBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.atanBy","strided.atanBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.atanBy.ndarray","strided.atanBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.atanhBy","strided.atanhBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.atanhBy.ndarray","strided.atanhBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.avercosBy","strided.avercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.avercosBy.ndarray","strided.avercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.aversinBy","strided.aversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.aversinBy.ndarray","strided.aversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.besselj0By","strided.besselj0By( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.besselj0By.ndarray","strided.besselj0By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.besselj1By","strided.besselj1By( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.besselj1By.ndarray","strided.besselj1By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.bessely0By","strided.bessely0By( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.bessely0By.ndarray","strided.bessely0By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.bessely1By","strided.bessely1By( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.bessely1By.ndarray","strided.bessely1By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.binetBy","strided.binetBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.binetBy.ndarray","strided.binetBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.cbrt","strided.cbrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.cbrt.ndarray","strided.cbrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.cbrtBy","strided.cbrtBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.cbrtBy.ndarray","strided.cbrtBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.ceil","strided.ceil( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.ceil.ndarray","strided.ceil.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.cosBy","strided.cosBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.cosBy.ndarray","strided.cosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.deg2rad","strided.deg2rad( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.deg2rad.ndarray","strided.deg2rad.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.dataTypes","strided.dataTypes()"],["strided.dcbrtBy","strided.dcbrtBy( N:integer, x:Float64Array, sx:integer, y:Float64Array, sy:integer, clbk:Function[, thisArg:any] )"],["strided.dcbrtBy.ndarray","strided.dcbrtBy.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, y:Float64Array, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.dispatch","strided.dispatch( fcns:Function|ArrayLikeObject<Function>, types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, nout:integer )"],["strided.dispatchBy","strided.dispatchBy( fcns:Function|ArrayLikeObject<Function>, types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, nout:integer )"],["strided.floor","strided.floor( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.floor.ndarray","strided.floor.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.inv","strided.inv( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.inv.ndarray","strided.inv.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.mul","strided.mul( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )"],["strided.mul.ndarray","strided.mul.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, z:ArrayLikeObject, sz:integer, oz:integer )"],["strided.mulBy","strided.mulBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, clbk:Function[, thisArg:any] )"],["strided.mulBy.ndarray","strided.mulBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, thisArg:any] )"],["strided.ramp","strided.ramp( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.ramp.ndarray","strided.ramp.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.rsqrt","strided.rsqrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.rsqrt.ndarray","strided.rsqrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.sinBy","strided.sinBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.sinBy.ndarray","strided.sinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.sqrt","strided.sqrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.sqrt.ndarray","strided.sqrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.sqrtBy","strided.sqrtBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.sqrtBy.ndarray","strided.sqrtBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.sub","strided.sub( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )"],["strided.sub.ndarray","strided.sub.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, z:ArrayLikeObject, sz:integer, oz:integer )"],["strided.subBy","strided.subBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, clbk:Function[, thisArg:any] )"],["strided.subBy.ndarray","strided.subBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, thisArg:any] )"],["strided.trunc","strided.trunc( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.trunc.ndarray","strided.trunc.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["stridedarray2iterator","stridedarray2iterator( N:integer, src:ArrayLikeObject, stride:integer, offset:integer[, mapFcn:Function[, thisArg:any]] )"],["stridedArrayStream","stridedArrayStream( N:integer, buffer:ArrayLikeObject, stride:integer, offset:integer[, options:Object] )"],["stridedArrayStream.factory","stridedArrayStream.factory( [options:Object] )"],["stridedArrayStream.objectMode","stridedArrayStream.objectMode( N:integer, buffer:ArrayLikeObject, stride:integer, offset:integer[, options:Object] )"],["string2buffer","string2buffer( str:string[, encoding:string] )"],["sub2ind","sub2ind( shape:ArrayLike, ...subscript:integer[, options:Object] )"],["substringAfter","substringAfter( str:string, search:string[, fromIndex:integer] )"],["substringAfterLast","substringAfterLast( str:string, search:string[, fromIndex:integer] )"],["substringBefore","substringBefore( str:string, search:string )"],["substringBeforeLast","substringBeforeLast( str:string, search:string )"],["SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()"],["SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()"],["Symbol","Symbol( [description:string] )"],["tabulate","tabulate( collection:Array|TypedArray|Object )"],["tabulateBy","tabulateBy( collection:Array|TypedArray|Object, [options:Object,] indicator:Function )"],["tabulateByAsync","tabulateByAsync( collection:Array|TypedArray|Object, [options:Object,] indicator:Function, done:Function )"],["tabulateByAsync.factory","tabulateByAsync.factory( [options:Object,] indicator:Function )"],["thunk","thunk( fcn:Function[, ...args:any] )"],["tic","tic()"],["timeit","timeit( code:string, [options:Object,] clbk:Function )"],["tmpdir","tmpdir()"],["toc","toc( time:Array<integer> )"],["tokenize","tokenize( str:string[, keepWhitespace:boolean] )"],["transformStream","transformStream( [options:Object] )"],["transformStream.factory","transformStream.factory( [options:Object] )"],["transformStream.objectMode","transformStream.objectMode( [options:Object] )"],["transformStream.ctor","transformStream.ctor( [options:Object] )"],["trim","trim( str:string )"],["truncate","truncate( str:string, len:integer[, ending:string] )"],["truncateMiddle","truncateMiddle( str:string, len:integer[, seq:string] )"],["trycatch","trycatch( x:Function, y:any )"],["trycatchAsync","trycatchAsync( x:Function, y:any, done:Function )"],["tryFunction","tryFunction( fcn:Function[, thisArg:any] )"],["tryRequire","tryRequire( id:string )"],["trythen","trythen( x:Function, y:Function )"],["trythenAsync","trythenAsync( x:Function, y:Function, done:Function )"],["ttest","ttest( x:Array<number>[, y:Array<number>][, options:Object] )"],["ttest2","ttest2( x:Array<number>, y:Array<number>[, options:Object] )"],["TWO_PI","TWO_PI"],["typedarray","typedarray( [dtype:string] )"],["typedarray","typedarray( length:integer[, dtype:string] )"],["typedarray","typedarray( typedarray:TypedArray[, dtype:string] )"],["typedarray","typedarray( obj:Object[, dtype:string] )"],["typedarray","typedarray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, dtype:string] )"],["typedarray2json","typedarray2json( arr:TypedArray )"],["typedarrayCtors","typedarrayCtors( dtype:string )"],["typedarrayDataTypes","typedarrayDataTypes()"],["typedarraypool","typedarraypool( [dtype:string] )"],["typedarraypool","typedarraypool( length:integer[, dtype:string] )"],["typedarraypool","typedarraypool( typedarray:TypedArray[, dtype:string] )"],["typedarraypool","typedarraypool( obj:Object[, dtype:string] )"],["typedarraypool.malloc","typedarraypool.malloc( [dtype:string] )"],["typedarraypool.malloc","typedarraypool.malloc( length:integer[, dtype:string] )"],["typedarraypool.malloc","typedarraypool.malloc( typedarray:TypedArray[, dtype:string] )"],["typedarraypool.malloc","typedarraypool.malloc( obj:Object[, dtype:string] )"],["typedarraypool.calloc","typedarraypool.calloc( [dtype:string] )"],["typedarraypool.calloc","typedarraypool.calloc( length:integer[, dtype:string] )"],["typedarraypool.free","typedarraypool.free( buf:TypedArray|ArrayBuffer )"],["typedarraypool.clear","typedarraypool.clear()"],["typedarraypool.highWaterMark","typedarraypool.highWaterMark"],["typedarraypool.nbytes","typedarraypool.nbytes"],["typedarraypool.factory","typedarraypool.factory( [options:Object] )"],["typemax","typemax( dtype:string )"],["typemin","typemin( dtype:string )"],["typeOf","typeOf( value:any )"],["UINT8_MAX","UINT8_MAX"],["UINT8_NUM_BYTES","UINT8_NUM_BYTES"],["Uint8Array","Uint8Array()"],["Uint8Array","Uint8Array( length:integer )"],["Uint8Array","Uint8Array( typedarray:TypedArray )"],["Uint8Array","Uint8Array( obj:Object )"],["Uint8Array","Uint8Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )"],["Uint8Array.from","Uint8Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )"],["Uint8Array.of","Uint8Array.of( element0:number[, element1:number[, ...elementN:number]] )"],["Uint8Array.BYTES_PER_ELEMENT","Uint8Array.BYTES_PER_ELEMENT"],["Uint8Array.name","Uint8Array.name"],["Uint8Array.prototype.buffer","Uint8Array.prototype.buffer"],["Uint8Array.prototype.byteLength","Uint8Array.prototype.byteLength"],["Uint8Array.prototype.byteOffset","Uint8Array.prototype.byteOffset"],["Uint8Array.prototype.BYTES_PER_ELEMENT","Uint8Array.prototype.BYTES_PER_ELEMENT"],["Uint8Array.prototype.length","Uint8Array.prototype.length"],["Uint8Array.prototype.copyWithin","Uint8Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )"],["Uint8Array.prototype.entries","Uint8Array.prototype.entries()"],["Uint8Array.prototype.every","Uint8Array.prototype.every( predicate:Function[, thisArg:Any] )"],["Uint8Array.prototype.fill","Uint8Array.prototype.fill( value:number[, start:integer[, end:integer]] )"],["Uint8Array.prototype.filter","Uint8Array.prototype.filter( predicate:Function[, thisArg:Any] )"],["Uint8Array.prototype.find","Uint8Array.prototype.find( predicate:Function[, thisArg:Any] )"],["Uint8Array.prototype.findIndex","Uint8Array.prototype.findIndex( predicate:Function[, thisArg:Any] )"],["Uint8Array.prototype.forEach","Uint8Array.prototype.forEach( fcn:Function[, thisArg:Any] )"],["Uint8Array.prototype.includes","Uint8Array.prototype.includes( searchElement:number[, fromIndex:integer] )"],["Uint8Array.prototype.indexOf","Uint8Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )"],["Uint8Array.prototype.join","Uint8Array.prototype.join( [separator:string] )"],["Uint8Array.prototype.keys","Uint8Array.prototype.keys()"],["Uint8Array.prototype.lastIndexOf","Uint8Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )"],["Uint8Array.prototype.map","Uint8Array.prototype.map( fcn:Function[, thisArg:Any] )"],["Uint8Array.prototype.reduce","Uint8Array.prototype.reduce( fcn:Function[, initialValue:Any] )"],["Uint8Array.prototype.reduceRight","Uint8Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )"],["Uint8Array.prototype.reverse","Uint8Array.prototype.reverse()"],["Uint8Array.prototype.set","Uint8Array.prototype.set( arr:ArrayLike[, offset:integer] )"],["Uint8Array.prototype.slice","Uint8Array.prototype.slice( [begin:integer[, end:integer]] )"],["Uint8Array.prototype.some","Uint8Array.prototype.some( predicate:Function[, thisArg:Any] )"],["Uint8Array.prototype.sort","Uint8Array.prototype.sort( [compareFunction:Function] )"],["Uint8Array.prototype.subarray","Uint8Array.prototype.subarray( [begin:integer[, end:integer]] )"],["Uint8Array.prototype.toLocaleString","Uint8Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )"],["Uint8Array.prototype.toString","Uint8Array.prototype.toString()"],["Uint8Array.prototype.values","Uint8Array.prototype.values()"],["Uint8ClampedArray","Uint8ClampedArray()"],["Uint8ClampedArray","Uint8ClampedArray( length:integer )"],["Uint8ClampedArray","Uint8ClampedArray( typedarray:TypedArray )"],["Uint8ClampedArray","Uint8ClampedArray( obj:Object )"],["Uint8ClampedArray","Uint8ClampedArray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )"],["Uint8ClampedArray.from","Uint8ClampedArray.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )"],["Uint8ClampedArray.of","Uint8ClampedArray.of( element0:number[, element1:number[, ...elementN:number]] )"],["Uint8ClampedArray.BYTES_PER_ELEMENT","Uint8ClampedArray.BYTES_PER_ELEMENT"],["Uint8ClampedArray.name","Uint8ClampedArray.name"],["Uint8ClampedArray.prototype.buffer","Uint8ClampedArray.prototype.buffer"],["Uint8ClampedArray.prototype.byteLength","Uint8ClampedArray.prototype.byteLength"],["Uint8ClampedArray.prototype.byteOffset","Uint8ClampedArray.prototype.byteOffset"],["Uint8ClampedArray.prototype.BYTES_PER_ELEMENT","Uint8ClampedArray.prototype.BYTES_PER_ELEMENT"],["Uint8ClampedArray.prototype.length","Uint8ClampedArray.prototype.length"],["Uint8ClampedArray.prototype.copyWithin","Uint8ClampedArray.prototype.copyWithin( target:integer, start:integer[, end:integer] )"],["Uint8ClampedArray.prototype.entries","Uint8ClampedArray.prototype.entries()"],["Uint8ClampedArray.prototype.every","Uint8ClampedArray.prototype.every( predicate:Function[, thisArg:Any] )"],["Uint8ClampedArray.prototype.fill","Uint8ClampedArray.prototype.fill( value:number[, start:integer[, end:integer]] )"],["Uint8ClampedArray.prototype.filter","Uint8ClampedArray.prototype.filter( predicate:Function[, thisArg:Any] )"],["Uint8ClampedArray.prototype.find","Uint8ClampedArray.prototype.find( predicate:Function[, thisArg:Any] )"],["Uint8ClampedArray.prototype.findIndex","Uint8ClampedArray.prototype.findIndex( predicate:Function[, thisArg:Any] )"],["Uint8ClampedArray.prototype.forEach","Uint8ClampedArray.prototype.forEach( fcn:Function[, thisArg:Any] )"],["Uint8ClampedArray.prototype.includes","Uint8ClampedArray.prototype.includes( searchElement:number[, fromIndex:integer] )"],["Uint8ClampedArray.prototype.indexOf","Uint8ClampedArray.prototype.indexOf( searchElement:number[, fromIndex:integer] )"],["Uint8ClampedArray.prototype.join","Uint8ClampedArray.prototype.join( [separator:string] )"],["Uint8ClampedArray.prototype.keys","Uint8ClampedArray.prototype.keys()"],["Uint8ClampedArray.prototype.lastIndexOf","Uint8ClampedArray.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )"],["Uint8ClampedArray.prototype.map","Uint8ClampedArray.prototype.map( fcn:Function[, thisArg:Any] )"],["Uint8ClampedArray.prototype.reduce","Uint8ClampedArray.prototype.reduce( fcn:Function[, initialValue:Any] )"],["Uint8ClampedArray.prototype.reduceRight","Uint8ClampedArray.prototype.reduceRight( fcn:Function[, initialValue:Any] )"],["Uint8ClampedArray.prototype.reverse","Uint8ClampedArray.prototype.reverse()"],["Uint8ClampedArray.prototype.set","Uint8ClampedArray.prototype.set( arr:ArrayLike[, offset:integer] )"],["Uint8ClampedArray.prototype.slice","Uint8ClampedArray.prototype.slice( [begin:integer[, end:integer]] )"],["Uint8ClampedArray.prototype.some","Uint8ClampedArray.prototype.some( predicate:Function[, thisArg:Any] )"],["Uint8ClampedArray.prototype.sort","Uint8ClampedArray.prototype.sort( [compareFunction:Function] )"],["Uint8ClampedArray.prototype.subarray","Uint8ClampedArray.prototype.subarray( [begin:integer[, end:integer]] )"],["Uint8ClampedArray.prototype.toLocaleString","Uint8ClampedArray.prototype.toLocaleString( [locales:string|Array[, options:Object]] )"],["Uint8ClampedArray.prototype.toString","Uint8ClampedArray.prototype.toString()"],["Uint8ClampedArray.prototype.values","Uint8ClampedArray.prototype.values()"],["UINT16_MAX","UINT16_MAX"],["UINT16_NUM_BYTES","UINT16_NUM_BYTES"],["Uint16Array","Uint16Array()"],["Uint16Array","Uint16Array( length:integer )"],["Uint16Array","Uint16Array( typedarray:TypedArray )"],["Uint16Array","Uint16Array( obj:Object )"],["Uint16Array","Uint16Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )"],["Uint16Array.from","Uint16Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )"],["Uint16Array.of","Uint16Array.of( element0:number[, element1:number[, ...elementN:number]] )"],["Uint16Array.BYTES_PER_ELEMENT","Uint16Array.BYTES_PER_ELEMENT"],["Uint16Array.name","Uint16Array.name"],["Uint16Array.prototype.buffer","Uint16Array.prototype.buffer"],["Uint16Array.prototype.byteLength","Uint16Array.prototype.byteLength"],["Uint16Array.prototype.byteOffset","Uint16Array.prototype.byteOffset"],["Uint16Array.prototype.BYTES_PER_ELEMENT","Uint16Array.prototype.BYTES_PER_ELEMENT"],["Uint16Array.prototype.length","Uint16Array.prototype.length"],["Uint16Array.prototype.copyWithin","Uint16Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )"],["Uint16Array.prototype.entries","Uint16Array.prototype.entries()"],["Uint16Array.prototype.every","Uint16Array.prototype.every( predicate:Function[, thisArg:Any] )"],["Uint16Array.prototype.fill","Uint16Array.prototype.fill( value:number[, start:integer[, end:integer]] )"],["Uint16Array.prototype.filter","Uint16Array.prototype.filter( predicate:Function[, thisArg:Any] )"],["Uint16Array.prototype.find","Uint16Array.prototype.find( predicate:Function[, thisArg:Any] )"],["Uint16Array.prototype.findIndex","Uint16Array.prototype.findIndex( predicate:Function[, thisArg:Any] )"],["Uint16Array.prototype.forEach","Uint16Array.prototype.forEach( fcn:Function[, thisArg:Any] )"],["Uint16Array.prototype.includes","Uint16Array.prototype.includes( searchElement:number[, fromIndex:integer] )"],["Uint16Array.prototype.indexOf","Uint16Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )"],["Uint16Array.prototype.join","Uint16Array.prototype.join( [separator:string] )"],["Uint16Array.prototype.keys","Uint16Array.prototype.keys()"],["Uint16Array.prototype.lastIndexOf","Uint16Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )"],["Uint16Array.prototype.map","Uint16Array.prototype.map( fcn:Function[, thisArg:Any] )"],["Uint16Array.prototype.reduce","Uint16Array.prototype.reduce( fcn:Function[, initialValue:Any] )"],["Uint16Array.prototype.reduceRight","Uint16Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )"],["Uint16Array.prototype.reverse","Uint16Array.prototype.reverse()"],["Uint16Array.prototype.set","Uint16Array.prototype.set( arr:ArrayLike[, offset:integer] )"],["Uint16Array.prototype.slice","Uint16Array.prototype.slice( [begin:integer[, end:integer]] )"],["Uint16Array.prototype.some","Uint16Array.prototype.some( predicate:Function[, thisArg:Any] )"],["Uint16Array.prototype.sort","Uint16Array.prototype.sort( [compareFunction:Function] )"],["Uint16Array.prototype.subarray","Uint16Array.prototype.subarray( [begin:integer[, end:integer]] )"],["Uint16Array.prototype.toLocaleString","Uint16Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )"],["Uint16Array.prototype.toString","Uint16Array.prototype.toString()"],["Uint16Array.prototype.values","Uint16Array.prototype.values()"],["UINT32_MAX","UINT32_MAX"],["UINT32_NUM_BYTES","UINT32_NUM_BYTES"],["Uint32Array","Uint32Array()"],["Uint32Array","Uint32Array( length:integer )"],["Uint32Array","Uint32Array( typedarray:TypedArray )"],["Uint32Array","Uint32Array( obj:Object )"],["Uint32Array","Uint32Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )"],["Uint32Array.from","Uint32Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )"],["Uint32Array.of","Uint32Array.of( element0:number[, element1:number[, ...elementN:number]] )"],["Uint32Array.BYTES_PER_ELEMENT","Uint32Array.BYTES_PER_ELEMENT"],["Uint32Array.name","Uint32Array.name"],["Uint32Array.prototype.buffer","Uint32Array.prototype.buffer"],["Uint32Array.prototype.byteLength","Uint32Array.prototype.byteLength"],["Uint32Array.prototype.byteOffset","Uint32Array.prototype.byteOffset"],["Uint32Array.prototype.BYTES_PER_ELEMENT","Uint32Array.prototype.BYTES_PER_ELEMENT"],["Uint32Array.prototype.length","Uint32Array.prototype.length"],["Uint32Array.prototype.copyWithin","Uint32Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )"],["Uint32Array.prototype.entries","Uint32Array.prototype.entries()"],["Uint32Array.prototype.every","Uint32Array.prototype.every( predicate:Function[, thisArg:Any] )"],["Uint32Array.prototype.fill","Uint32Array.prototype.fill( value:number[, start:integer[, end:integer]] )"],["Uint32Array.prototype.filter","Uint32Array.prototype.filter( predicate:Function[, thisArg:Any] )"],["Uint32Array.prototype.find","Uint32Array.prototype.find( predicate:Function[, thisArg:Any] )"],["Uint32Array.prototype.findIndex","Uint32Array.prototype.findIndex( predicate:Function[, thisArg:Any] )"],["Uint32Array.prototype.forEach","Uint32Array.prototype.forEach( fcn:Function[, thisArg:Any] )"],["Uint32Array.prototype.includes","Uint32Array.prototype.includes( searchElement:number[, fromIndex:integer] )"],["Uint32Array.prototype.indexOf","Uint32Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )"],["Uint32Array.prototype.join","Uint32Array.prototype.join( [separator:string] )"],["Uint32Array.prototype.keys","Uint32Array.prototype.keys()"],["Uint32Array.prototype.lastIndexOf","Uint32Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )"],["Uint32Array.prototype.map","Uint32Array.prototype.map( fcn:Function[, thisArg:Any] )"],["Uint32Array.prototype.reduce","Uint32Array.prototype.reduce( fcn:Function[, initialValue:Any] )"],["Uint32Array.prototype.reduceRight","Uint32Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )"],["Uint32Array.prototype.reverse","Uint32Array.prototype.reverse()"],["Uint32Array.prototype.set","Uint32Array.prototype.set( arr:ArrayLike[, offset:integer] )"],["Uint32Array.prototype.slice","Uint32Array.prototype.slice( [begin:integer[, end:integer]] )"],["Uint32Array.prototype.some","Uint32Array.prototype.some( predicate:Function[, thisArg:Any] )"],["Uint32Array.prototype.sort","Uint32Array.prototype.sort( [compareFunction:Function] )"],["Uint32Array.prototype.subarray","Uint32Array.prototype.subarray( [begin:integer[, end:integer]] )"],["Uint32Array.prototype.toLocaleString","Uint32Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )"],["Uint32Array.prototype.toString","Uint32Array.prototype.toString()"],["Uint32Array.prototype.values","Uint32Array.prototype.values()"],["umask","umask( [mask:integer|string,] [options:Object] )"],["uncapitalize","uncapitalize( str:string )"],["uncapitalizeKeys","uncapitalizeKeys( obj:Object )"],["uncurry","uncurry( fcn:Function[, arity:integer, ][thisArg:any] )"],["uncurryRight","uncurryRight( fcn:Function[, arity:integer, ][thisArg:any] )"],["UNICODE_MAX","UNICODE_MAX"],["UNICODE_MAX_BMP","UNICODE_MAX_BMP"],["UnicodeColumnChartSparkline","UnicodeColumnChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )"],["UnicodeLineChartSparkline","UnicodeLineChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )"],["UnicodeSparkline","UnicodeSparkline( [data:ArrayLike|ndarray,] [options:Object] )"],["UnicodeTristateChartSparkline","UnicodeTristateChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )"],["UnicodeUpDownChartSparkline","UnicodeUpDownChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )"],["UnicodeWinLossChartSparkline","UnicodeWinLossChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )"],["unlink","unlink( path:string|Buffer|integer, clbk:Function )"],["unlink.sync","unlink.sync( path:string|Buffer|integer )"],["unshift","unshift( collection:Array|TypedArray|Object, ...items:any )"],["until","until( predicate:Function, fcn:Function[, thisArg:any] )"],["untilAsync","untilAsync( predicate:Function, fcn:Function, done:Function[, thisArg:any] )"],["untilEach","untilEach( collection:Array|TypedArray|Object, predicate:Function, fcn:Function[, thisArg:any] )"],["untilEachRight","untilEachRight( collection:Array|TypedArray|Object, predicate:Function, fcn:Function[, thisArg:any] )"],["unzip","unzip( arr:Array[, idx:Array<number>] )"],["uppercase","uppercase( str:string )"],["uppercaseKeys","uppercaseKeys( obj:Object )"],["US_STATES_ABBR","US_STATES_ABBR()"],["US_STATES_CAPITALS","US_STATES_CAPITALS()"],["US_STATES_CAPITALS_NAMES","US_STATES_CAPITALS_NAMES()"],["US_STATES_NAMES","US_STATES_NAMES()"],["US_STATES_NAMES_CAPITALS","US_STATES_NAMES_CAPITALS()"],["utf16ToUTF8Array","utf16ToUTF8Array( str:string )"],["vartest","vartest( x:Array<number>, y:Array<number>[, options:Object] )"],["waterfall","waterfall( fcns:Array<Function>, clbk:Function[, thisArg:any] )"],["waterfall.factory","waterfall.factory( fcns:Array<Function>, clbk:Function[, thisArg:any] )"],["WebAssemblyMemory","WebAssemblyMemory( descriptor:Object )"],["WebAssemblyMemory.prototype.buffer","WebAssemblyMemory.prototype.buffer"],["WebAssemblyMemory.prototype.grow","WebAssemblyMemory.prototype.grow( delta:integer )"],["whileAsync","whileAsync( predicate:Function, fcn:Function, done:Function[, thisArg:any] )"],["whileEach","whileEach( collection:Array|TypedArray|Object, predicate:Function, fcn:Function[, thisArg:any] )"],["whileEachRight","whileEachRight( collection:Array|TypedArray|Object, predicate:Function, fcn:Function[, thisArg:any] )"],["whilst","whilst( predicate:Function, fcn:Function[, thisArg:any] )"],["wilcoxon","wilcoxon( x:Array|TypedArray[, y:Array|TypedArray][, options:Object] )"],["writableProperties","writableProperties( value:any )"],["writablePropertiesIn","writablePropertiesIn( value:any )"],["writablePropertyNames","writablePropertyNames( value:any )"],["writablePropertyNamesIn","writablePropertyNamesIn( value:any )"],["writablePropertySymbols","writablePropertySymbols( value:any )"],["writablePropertySymbolsIn","writablePropertySymbolsIn( value:any )"],["writeFile","writeFile( file:string|Buffer|integer, data:string|Buffer[, options:Object|string], clbk:Function )"],["writeFile.sync","writeFile.sync( file:string|Buffer|integer, data:string|Buffer[, options:Object|string] )"],["zip","zip( ...arr:Array[, options:Object] )"],["ztest","ztest( x:Array<number>, sigma:number[, options:Object] )"],["ztest2","ztest2( x:Array<number>, y:Array<number>, sigmax:number, sigmay:number[, options:Object] )"]]
+[["abs","abs( x:ndarray|ArrayLikeObject|number[, options:Object] )"],["abs.assign","abs.assign( x:ndarray|ArrayLikeObject, y:ndarray|ArrayLikeObject )"],["acartesianPower","acartesianPower( x:ArrayLikeObject, n:integer )"],["acartesianProduct","acartesianProduct( x1:ArrayLikeObject, x2:ArrayLikeObject )"],["acartesianSquare","acartesianSquare( x:ArrayLikeObject )"],["acronym","acronym( str:string[, options:Object] )"],["aempty","aempty( length:integer[, dtype:string] )"],["aemptyLike","aemptyLike( x:TypedArray|Array[, dtype:string] )"],["AFINN_96","AFINN_96()"],["AFINN_111","AFINN_111()"],["afull","afull( length:integer, value:any[, dtype:string] )"],["afullLike","afullLike( x:TypedArray|Array[, dtype:string] )"],["alias2pkg","alias2pkg( alias:string )"],["alias2related","alias2related( alias:string )"],["alias2standalone","alias2standalone( alias:string )"],["aliases","aliases( [namespace:string] )"],["allocUnsafe","allocUnsafe( size:integer )"],["amskfilter","amskfilter( x:Array|TypedArray|Object, mask:Array|TypedArray|Object )"],["amskput","amskput( x:ArrayLikeObject, mask:ArrayLikeObject, values:ArrayLikeObject[, options:Object] )"],["amskreject","amskreject( x:Array|TypedArray|Object, mask:Array|TypedArray|Object )"],["anans","anans( length:integer[, dtype:string] )"],["anansLike","anansLike( x:TypedArray|Array[, dtype:string] )"],["anova1","anova1( x:Array<number>, factor:Array[, options:Object] )"],["ANSCOMBES_QUARTET","ANSCOMBES_QUARTET()"],["any","any( collection:Array|TypedArray|Object )"],["anyBy","anyBy( collection:Array|TypedArray|Object, predicate:Function[, thisArg:any ] )"],["anyByAsync","anyByAsync( collection:Array|TypedArray|Object, [options:Object,] predicate:Function, done:Function )"],["anyByAsync.factory","anyByAsync.factory( [options:Object,] predicate:Function )"],["anyByRight","anyByRight( collection:Array|TypedArray|Object, predicate:Function[, thisArg:any ] )"],["anyByRightAsync","anyByRightAsync( collection:Array|TypedArray|Object, [options:Object,] predicate:Function, done:Function )"],["anyByRightAsync.factory","anyByRightAsync.factory( [options:Object,] predicate:Function )"],["anyInBy","anyInBy( object:Object, predicate:Function[, thisArg:any ] )"],["anyOwnBy","anyOwnBy( object:Object, predicate:Function[, thisArg:any ] )"],["aones","aones( length:integer[, dtype:string] )"],["aonesLike","aonesLike( x:TypedArray|Array[, dtype:string] )"],["aoneTo","aoneTo( n:integer[, dtype:string] )"],["aoneToLike","aoneToLike( x:TypedArray|Array[, dtype:string] )"],["APERY","APERY"],["aplace","aplace( x:ArrayLikeObject, mask:ArrayLikeObject, values:ArrayLikeObject[, options:Object] )"],["append","append( collection1:Array|TypedArray|Object, collection2:Array|TypedArray|Object )"],["aput","aput( x:ArrayLikeObject, indices:ArrayLikeObject<integer>, values:ArrayLikeObject[, options:Object] )"],["ARCH","ARCH"],["argumentFunction","argumentFunction( idx:integer )"],["ARGV","ARGV"],["array","array( [buffer:Array|TypedArray|Buffer|ndarray,] [options:Object] )"],["array2buffer","array2buffer( arr:Array<integer> )"],["array2fancy","array2fancy( x:Array|TypedArray|Object[, options:Object] )"],["array2fancy.factory","array2fancy.factory( [options:Object] )"],["array2fancy.idx","array2fancy.idx( x:Array|TypedArray|Object[, options:Object] )"],["array2iterator","array2iterator( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )"],["array2iteratorRight","array2iteratorRight( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )"],["ArrayBuffer","ArrayBuffer( size:integer )"],["ArrayBuffer.length","ArrayBuffer.length"],["ArrayBuffer.isView","ArrayBuffer.isView( arr:any )"],["ArrayBuffer.prototype.byteLength","ArrayBuffer.prototype.byteLength"],["ArrayBuffer.prototype.slice","ArrayBuffer.prototype.slice( [start:integer[, end:integer]] )"],["arraybuffer2buffer","arraybuffer2buffer( buf:ArrayBuffer[, byteOffset:integer[, length:integer]] 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)"],["base.strided.dmeanwd.ndarray","base.strided.dmeanwd.ndarray( N:integer, x:Float64Array, stride:integer, offset:integer )"],["base.strided.dmediansorted","base.strided.dmediansorted( N:integer, x:Float64Array, strideX:integer )"],["base.strided.dmediansorted.ndarray","base.strided.dmediansorted.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )"],["base.strided.dmidrange","base.strided.dmidrange( N:integer, x:Float64Array, strideX:integer )"],["base.strided.dmidrange.ndarray","base.strided.dmidrange.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )"],["base.strided.dmin","base.strided.dmin( N:integer, x:Float64Array, strideX:integer )"],["base.strided.dmin.ndarray","base.strided.dmin.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )"],["base.strided.dminabs","base.strided.dminabs( N:integer, x:Float64Array, strideX:integer )"],["base.strided.dminabs.ndarray","base.strided.dminabs.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )"],["base.strided.dminsorted","base.strided.dminsorted( N:integer, x:Float64Array, strideX:integer )"],["base.strided.dminsorted.ndarray","base.strided.dminsorted.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )"],["base.strided.dmskabs","base.strided.dmskabs( N:integer, x:Float64Array, sx:integer, m:Uint8Array, sm:integer, y:Float64Array, sy:integer )"],["base.strided.dmskabs.ndarray","base.strided.dmskabs.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, sy:integer, oy:integer )"],["base.strided.dmskabs2","base.strided.dmskabs2( N:integer, x:Float64Array, sx:integer, m:Uint8Array, sm:integer, y:Float64Array, sy:integer )"],["base.strided.dmskabs2.ndarray","base.strided.dmskabs2.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, sy:integer, oy:integer )"],["base.strided.dmskcbrt","base.strided.dmskcbrt( N:integer, x:Float64Array, sx:integer, m:Uint8Array, sm:integer, y:Float64Array, sy:integer )"],["base.strided.dmskcbrt.ndarray","base.strided.dmskcbrt.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, sy:integer, oy:integer )"],["base.strided.dmskceil","base.strided.dmskceil( N:integer, x:Float64Array, sx:integer, m:Uint8Array, sm:integer, y:Float64Array, sy:integer )"],["base.strided.dmskceil.ndarray","base.strided.dmskceil.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, sy:integer, oy:integer )"],["base.strided.dmskdeg2rad","base.strided.dmskdeg2rad( N:integer, x:Float64Array, sx:integer, m:Uint8Array, sm:integer, y:Float64Array, sy:integer )"],["base.strided.dmskdeg2rad.ndarray","base.strided.dmskdeg2rad.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, sy:integer, oy:integer )"],["base.strided.dmskfloor","base.strided.dmskfloor( N:integer, x:Float64Array, sx:integer, m:Uint8Array, sm:integer, y:Float64Array, sy:integer )"],["base.strided.dmskfloor.ndarray","base.strided.dmskfloor.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, sy:integer, oy:integer )"],["base.strided.dmskinv","base.strided.dmskinv( N:integer, x:Float64Array, sx:integer, m:Uint8Array, sm:integer, y:Float64Array, sy:integer )"],["base.strided.dmskinv.ndarray","base.strided.dmskinv.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, sy:integer, oy:integer )"],["base.strided.dmskmap","base.strided.dmskmap( N:integer, x:Float64Array, sx:integer, m:Uint8Array, sm:integer, y:Float64Array, sy:integer, fcn:Function )"],["base.strided.dmskmap.ndarray","base.strided.dmskmap.ndarray( N:integer, x:Float64Array, 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strideX:integer )"],["base.strided.sminabs.ndarray","base.strided.sminabs.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.sminsorted","base.strided.sminsorted( N:integer, x:Float32Array, stride:integer )"],["base.strided.sminsorted.ndarray","base.strided.sminsorted.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )"],["base.strided.smskabs","base.strided.smskabs( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskabs.ndarray","base.strided.smskabs.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskabs2","base.strided.smskabs2( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskabs2.ndarray","base.strided.smskabs2.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskcbrt","base.strided.smskcbrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskcbrt.ndarray","base.strided.smskcbrt.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskceil","base.strided.smskceil( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskceil.ndarray","base.strided.smskceil.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskdeg2rad","base.strided.smskdeg2rad( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskdeg2rad.ndarray","base.strided.smskdeg2rad.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskfloor","base.strided.smskfloor( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskfloor.ndarray","base.strided.smskfloor.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskinv","base.strided.smskinv( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskinv.ndarray","base.strided.smskinv.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskmap","base.strided.smskmap( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer, fcn:Function )"],["base.strided.smskmap.ndarray","base.strided.smskmap.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Uint8Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer, fcn:Function )"],["base.strided.smskmap2","base.strided.smskmap2( N:integer, x:Float32Array, sx:integer, y:Float32Array, sy:integer, m:Uint8Array, sm:integer, z:Float32Array, sz:integer, fcn:Function )"],["base.strided.smskmap2.ndarray","base.strided.smskmap2.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, y:Float32Array, sy:integer, oy:integer, m:Uint8Array, sm:integer, om:integer, z:Float32Array, sz:integer, oz:integer, fcn:Function )"],["base.strided.smskmax","base.strided.smskmax( N:integer, x:Float32Array, strideX:integer, mask:Uint8Array, strideMask:integer )"],["base.strided.smskmax.ndarray","base.strided.smskmax.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )"],["base.strided.smskmin","base.strided.smskmin( N:integer, x:Float32Array, strideX:integer, mask:Uint8Array, strideMask:integer )"],["base.strided.smskmin.ndarray","base.strided.smskmin.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )"],["base.strided.smskramp","base.strided.smskramp( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskramp.ndarray","base.strided.smskramp.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskrange","base.strided.smskrange( N:integer, x:Float32Array, strideX:integer, mask:Uint8Array, strideMask:integer )"],["base.strided.smskrange.ndarray","base.strided.smskrange.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )"],["base.strided.smskrsqrt","base.strided.smskrsqrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskrsqrt.ndarray","base.strided.smskrsqrt.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smsksqrt","base.strided.smsksqrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smsksqrt.ndarray","base.strided.smsksqrt.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smsktrunc","base.strided.smsktrunc( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smsktrunc.ndarray","base.strided.smsktrunc.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.snanmax","base.strided.snanmax( N:integer, x:Float32Array, strideX:integer )"],["base.strided.snanmax.ndarray","base.strided.snanmax.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.snanmaxabs","base.strided.snanmaxabs( N:integer, x:Float32Array, strideX:integer )"],["base.strided.snanmaxabs.ndarray","base.strided.snanmaxabs.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.snanmean","base.strided.snanmean( N:integer, x:Float32Array, stride:integer )"],["base.strided.snanmean.ndarray","base.strided.snanmean.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )"],["base.strided.snanmeanors","base.strided.snanmeanors( N:integer, x:Float32Array, stride:integer )"],["base.strided.snanmeanors.ndarray","base.strided.snanmeanors.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )"],["base.strided.snanmeanpn","base.strided.snanmeanpn( N:integer, x:Float32Array, stride:integer )"],["base.strided.snanmeanpn.ndarray","base.strided.snanmeanpn.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )"],["base.strided.snanmeanwd","base.strided.snanmeanwd( N:integer, x:Float32Array, stride:integer )"],["base.strided.snanmeanwd.ndarray","base.strided.snanmeanwd.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )"],["base.strided.snanmin","base.strided.snanmin( N:integer, x:Float32Array, strideX:integer )"],["base.strided.snanmin.ndarray","base.strided.snanmin.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.snanminabs","base.strided.snanminabs( N:integer, x:Float32Array, strideX:integer )"],["base.strided.snanminabs.ndarray","base.strided.snanminabs.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.snanmskmax","base.strided.snanmskmax( N:integer, x:Float32Array, strideX:integer, mask:Uint8Array, strideMask:integer )"],["base.strided.snanmskmax.ndarray","base.strided.snanmskmax.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )"],["base.strided.snanmskmin","base.strided.snanmskmin( N:integer, x:Float32Array, strideX:integer, mask:Uint8Array, strideMask:integer )"],["base.strided.snanmskmin.ndarray","base.strided.snanmskmin.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )"],["base.strided.snanmskrange","base.strided.snanmskrange( N:integer, x:Float32Array, strideX:integer, mask:Uint8Array, strideMask:integer )"],["base.strided.snanmskrange.ndarray","base.strided.snanmskrange.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )"],["base.strided.snanrange","base.strided.snanrange( N:integer, x:Float32Array, strideX:integer )"],["base.strided.snanrange.ndarray","base.strided.snanrange.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.snanstdev","base.strided.snanstdev( N:integer, correction:number, x:Float32Array, stride:integer )"],["base.strided.snanstdev.ndarray","base.strided.snanstdev.ndarray( N:integer, correction:number, x:Float32Array, stride:integer, offset:integer )"],["base.strided.snanstdevch","base.strided.snanstdevch( N:integer, correction:number, x:Float32Array, stride:integer )"],["base.strided.snanstdevch.ndarray","base.strided.snanstdevch.ndarray( N:integer, correction:number, x:Float32Array, stride:integer, offset:integer )"],["base.strided.snanstdevpn","base.strided.snanstdevpn( N:integer, correction:number, x:Float32Array, stride:integer )"],["base.strided.snanstdevpn.ndarray","base.strided.snanstdevpn.ndarray( N:integer, correction:number, x:Float32Array, stride:integer, offset:integer )"],["base.strided.snanstdevtk","base.strided.snanstdevtk( N:integer, correction:number, x:Float32Array, stride:integer )"],["base.strided.snanstdevtk.ndarray","base.strided.snanstdevtk.ndarray( N:integer, correction:number, x:Float32Array, stride:integer, offset:integer )"],["base.strided.snanstdevwd","base.strided.snanstdevwd( N:integer, correction:number, x:Float32Array, stride:integer )"],["base.strided.snanstdevwd.ndarray","base.strided.snanstdevwd.ndarray( N:integer, correction:number, x:Float32Array, stride:integer, offset:integer )"],["base.strided.snanstdevyc","base.strided.snanstdevyc( N:integer, correction:number, x:Float32Array, stride:integer )"],["base.strided.snanstdevyc.ndarray","base.strided.snanstdevyc.ndarray( N:integer, correction:number, x:Float32Array, stride:integer, offset:integer )"],["base.strided.snansum","base.strided.snansum( N:integer, x:Float32Array, stride:integer )"],["base.strided.snansum.ndarray","base.strided.snansum.ndarray( N:integer, 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)"],["isNonPositiveFinite.isObject","isNonPositiveFinite.isObject( value:any )"],["isNonPositiveInteger","isNonPositiveInteger( value:any )"],["isNonPositiveInteger.isPrimitive","isNonPositiveInteger.isPrimitive( value:any )"],["isNonPositiveInteger.isObject","isNonPositiveInteger.isObject( value:any )"],["isNonPositiveIntegerArray","isNonPositiveIntegerArray( value:any )"],["isNonPositiveIntegerArray.primitives","isNonPositiveIntegerArray.primitives( value:any )"],["isNonPositiveIntegerArray.objects","isNonPositiveIntegerArray.objects( value:any )"],["isNonPositiveNumber","isNonPositiveNumber( value:any )"],["isNonPositiveNumber.isPrimitive","isNonPositiveNumber.isPrimitive( value:any )"],["isNonPositiveNumber.isObject","isNonPositiveNumber.isObject( value:any )"],["isNonPositiveNumberArray","isNonPositiveNumberArray( value:any )"],["isNonPositiveNumberArray.primitives","isNonPositiveNumberArray.primitives( value:any 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)"],["isPersymmetricMatrix","isPersymmetricMatrix( value:any )"],["isPlainObject","isPlainObject( value:any )"],["isPlainObjectArray","isPlainObjectArray( value:any )"],["isPositiveFinite","isPositiveFinite( value:any )"],["isPositiveFinite.isPrimitive","isPositiveFinite.isPrimitive( value:any )"],["isPositiveFinite.isObject","isPositiveFinite.isObject( value:any )"],["isPositiveInteger","isPositiveInteger( value:any )"],["isPositiveInteger.isPrimitive","isPositiveInteger.isPrimitive( value:any )"],["isPositiveInteger.isObject","isPositiveInteger.isObject( value:any )"],["isPositiveIntegerArray","isPositiveIntegerArray( value:any )"],["isPositiveIntegerArray.primitives","isPositiveIntegerArray.primitives( value:any )"],["isPositiveIntegerArray.objects","isPositiveIntegerArray.objects( value:any )"],["isPositiveNumber","isPositiveNumber( value:any )"],["isPositiveNumber.isPrimitive","isPositiveNumber.isPrimitive( value:any )"],["isPositiveNumber.isObject","isPositiveNumber.isObject( value:any )"],["isPositiveNumberArray","isPositiveNumberArray( value:any )"],["isPositiveNumberArray.primitives","isPositiveNumberArray.primitives( value:any )"],["isPositiveNumberArray.objects","isPositiveNumberArray.objects( value:any )"],["isPositiveZero","isPositiveZero( value:any )"],["isPositiveZero.isPrimitive","isPositiveZero.isPrimitive( value:any )"],["isPositiveZero.isObject","isPositiveZero.isObject( value:any )"],["isPrime","isPrime( value:any )"],["isPrime.isPrimitive","isPrime.isPrimitive( value:any )"],["isPrime.isObject","isPrime.isObject( value:any )"],["isPrimitive","isPrimitive( value:any )"],["isPrimitiveArray","isPrimitiveArray( value:any )"],["isPRNGLike","isPRNGLike( value:any )"],["isProbability","isProbability( value:any )"],["isProbability.isPrimitive","isProbability.isPrimitive( value:any )"],["isProbability.isObject","isProbability.isObject( value:any )"],["isProbabilityArray","isProbabilityArray( value:any )"],["isProbabilityArray.primitives","isProbabilityArray.primitives( value:any )"],["isProbabilityArray.objects","isProbabilityArray.objects( value:any )"],["isPropertyKey","isPropertyKey( value:any )"],["isPrototypeOf","isPrototypeOf( value:any, proto:Object|Function )"],["isRaggedNestedArray","isRaggedNestedArray( value:any )"],["isRangeError","isRangeError( value:any )"],["isReadableProperty","isReadableProperty( value:any, property:any )"],["isReadablePropertyIn","isReadablePropertyIn( value:any, property:any )"],["isReadOnlyProperty","isReadOnlyProperty( value:any, property:any )"],["isReadOnlyPropertyIn","isReadOnlyPropertyIn( value:any, property:any )"],["isReadWriteProperty","isReadWriteProperty( value:any, property:any )"],["isReadWritePropertyIn","isReadWritePropertyIn( value:any, property:any )"],["isReferenceError","isReferenceError( value:any )"],["isRegExp","isRegExp( value:any )"],["isRegExpString","isRegExpString( value:any )"],["isRelativePath","isRelativePath( value:any )"],["isRelativePath.posix","isRelativePath.posix( value:any )"],["isRelativePath.win32","isRelativePath.win32( value:any )"],["isRelativeURI","isRelativeURI( value:any )"],["isSafeInteger","isSafeInteger( value:any )"],["isSafeInteger.isPrimitive","isSafeInteger.isPrimitive( value:any )"],["isSafeInteger.isObject","isSafeInteger.isObject( value:any )"],["isSafeIntegerArray","isSafeIntegerArray( value:any )"],["isSafeIntegerArray.primitives","isSafeIntegerArray.primitives( value:any )"],["isSafeIntegerArray.objects","isSafeIntegerArray.objects( value:any )"],["isSameArray","isSameArray( v1:any, v2:any )"],["isSameArrayLike","isSameArrayLike( v1:any, v2:any )"],["isSameComplex64","isSameComplex64( v1:any, v2:any )"],["isSameComplex64Array","isSameComplex64Array( v1:any, v2:any )"],["isSameComplex128","isSameComplex128( v1:any, v2:any )"],["isSameComplex128Array","isSameComplex128Array( v1:any, v2:any )"],["isSameDateObject","isSameDateObject( d1, d2 )"],["isSameFloat32Array","isSameFloat32Array( v1:any, v2:any )"],["isSameFloat64Array","isSameFloat64Array( v1:any, v2:any )"],["isSameNativeClass","isSameNativeClass( a:any, b:any )"],["isSameType","isSameType( a:any, b:any )"],["isSameValue","isSameValue( a:any, b:any )"],["isSameValueZero","isSameValueZero( a:any, b:any )"],["isSemVer","isSemVer( value:any )"],["isSharedArrayBuffer","isSharedArrayBuffer( value:any )"],["isSkewCentrosymmetricMatrix","isSkewCentrosymmetricMatrix( value:any )"],["isSkewPersymmetricMatrix","isSkewPersymmetricMatrix( value:any )"],["isSkewSymmetricMatrix","isSkewSymmetricMatrix( value:any )"],["isSlice","isSlice( value:any )"],["isSnakecase","isSnakecase( value:any )"],["isSquareMatrix","isSquareMatrix( value:any )"],["isSquareNumber","isSquareNumber( value:any )"],["isSquareNumber.isPrimitive","isSquareNumber.isPrimitive( value:any )"],["isSquareNumber.isObject","isSquareNumber.isObject( value:any )"],["isSquareTriangularNumber","isSquareTriangularNumber( value:any )"],["isSquareTriangularNumber.isPrimitive","isSquareTriangularNumber.isPrimitive( value:any )"],["isSquareTriangularNumber.isObject","isSquareTriangularNumber.isObject( value:any )"],["isStartcase","isStartcase( value:any )"],["isStrictEqual","isStrictEqual( a:any, b:any )"],["isString","isString( value:any )"],["isString.isPrimitive","isString.isPrimitive( value:any )"],["isString.isObject","isString.isObject( value:any )"],["isStringArray","isStringArray( value:any )"],["isStringArray.primitives","isStringArray.primitives( value:any )"],["isStringArray.objects","isStringArray.objects( value:any )"],["isSymbol","isSymbol( value:any )"],["isSymbolArray","isSymbolArray( value:any )"],["isSymbolArray.primitives","isSymbolArray.primitives( value:any )"],["isSymbolArray.objects","isSymbolArray.objects( value:any )"],["isSymmetricMatrix","isSymmetricMatrix( value:any )"],["isSyntaxError","isSyntaxError( value:any )"],["isTriangularNumber","isTriangularNumber( value:any )"],["isTriangularNumber.isPrimitive","isTriangularNumber.isPrimitive( value:any )"],["isTriangularNumber.isObject","isTriangularNumber.isObject( value:any )"],["isTruthy","isTruthy( value:any )"],["isTruthyArray","isTruthyArray( value:any )"],["isTypedArray","isTypedArray( value:any )"],["isTypedArrayLength","isTypedArrayLength( value:any )"],["isTypedArrayLike","isTypedArrayLike( value:any )"],["isTypeError","isTypeError( value:any )"],["isUint8Array","isUint8Array( value:any )"],["isUint8ClampedArray","isUint8ClampedArray( value:any )"],["isUint16Array","isUint16Array( value:any )"],["isUint32Array","isUint32Array( value:any )"],["isUNCPath","isUNCPath( value:any )"],["isUndefined","isUndefined( value:any )"],["isUndefinedOrNull","isUndefinedOrNull( value:any )"],["isUnityProbabilityArray","isUnityProbabilityArray( value:any )"],["isUppercase","isUppercase( value:any )"],["isURI","isURI( value:any )"],["isURIError","isURIError( value:any )"],["isVectorLike","isVectorLike( value:any )"],["isWebAssemblyMemory","isWebAssemblyMemory( value:any )"],["isWellFormedString","isWellFormedString( str:any )"],["isWellFormedString.isPrimitive","isWellFormedString.isPrimitive( str:any )"],["isWellFormedString.isObject","isWellFormedString.isObject( str:any )"],["isWhitespace","isWhitespace( str:string )"],["isWritableProperty","isWritableProperty( value:any, property:any )"],["isWritablePropertyIn","isWritablePropertyIn( value:any, property:any )"],["isWriteOnlyProperty","isWriteOnlyProperty( value:any, property:any )"],["isWriteOnlyPropertyIn","isWriteOnlyPropertyIn( value:any, property:any )"],["iterAbs","iterAbs( iterator:Object )"],["iterAbs2","iterAbs2( iterator:Object )"],["iterAcos","iterAcos( iterator:Object )"],["iterAcosh","iterAcosh( iterator:Object )"],["iterAcot","iterAcot( iterator:Object )"],["iterAcoth","iterAcoth( iterator:Object )"],["iterAcovercos","iterAcovercos( iterator:Object )"],["iterAcoversin","iterAcoversin( iterator:Object )"],["iterAdd","iterAdd( iter0:Object, ...iterator:Object )"],["iterAdvance","iterAdvance( iterator:Object[, n:integer] )"],["iterAhavercos","iterAhavercos( iterator:Object )"],["iterAhaversin","iterAhaversin( iterator:Object )"],["iterAny","iterAny( iterator:Object )"],["iterAnyBy","iterAnyBy( iterator:Object, predicate:Function[, thisArg:any ] )"],["iterAsin","iterAsin( iterator:Object )"],["iterAsinh","iterAsinh( iterator:Object )"],["iterAtan","iterAtan( iterator:Object )"],["iterAtan2","iterAtan2( y:Object|number, x:Object|number )"],["iterAtanh","iterAtanh( iterator:Object )"],["iterator2array","iterator2array( iterator:Object[, out:ArrayLikeObject][, mapFcn:Function[, thisArg:any]] )"],["iterator2arrayview","iterator2arrayview( iterator:Object, dest:ArrayLikeObject[, begin:integer[, end:integer]][, mapFcn:Function[, thisArg:any]] )"],["iterator2arrayviewRight","iterator2arrayviewRight( iterator:Object, dest:ArrayLikeObject[, begin:integer[, end:integer]][, mapFcn:Function[, thisArg:any]] )"],["iteratorStream","iteratorStream( iterator:Object[, options:Object] )"],["iteratorStream.factory","iteratorStream.factory( [options:Object] )"],["iteratorStream.objectMode","iteratorStream.objectMode( iterator:Object[, options:Object] )"],["IteratorSymbol","IteratorSymbol"],["iterAvercos","iterAvercos( iterator:Object )"],["iterAversin","iterAversin( iterator:Object )"],["iterawgn","iterawgn( iterator:Object, sigma:number[, options:Object] )"],["iterawln","iterawln( iterator:Object, sigma:number[, options:Object] )"],["iterawun","iterawun( iterator:Object, sigma:number[, options:Object] )"],["iterBartlettHannPulse","iterBartlettHannPulse( [options:Object] )"],["iterBartlettPulse","iterBartlettPulse( [options:Object] )"],["iterBesselj0","iterBesselj0( iterator:Object )"],["iterBesselj1","iterBesselj1( iterator:Object )"],["iterBessely0","iterBessely0( iterator:Object )"],["iterBessely1","iterBessely1( iterator:Object )"],["iterBeta","iterBeta( x:Object|number, y:Object|number )"],["iterBetaln","iterBetaln( x:Object|number, y:Object|number )"],["iterBinet","iterBinet( iterator:Object )"],["iterCbrt","iterCbrt( iterator:Object )"],["iterCeil","iterCeil( iterator:Object )"],["iterCeil2","iterCeil2( iterator:Object )"],["iterCeil10","iterCeil10( iterator:Object )"],["iterCompositesSeq","iterCompositesSeq( [options:Object] )"],["iterConcat","iterConcat( iter0:Object, ...iterator:Object )"],["iterConstant","iterConstant( value:any[, options:Object] )"],["iterContinuedFraction","iterContinuedFraction( iterator:Object[, options:Object] )"],["iterContinuedFractionSeq","iterContinuedFractionSeq( x:number[, options:Object] )"],["iterCos","iterCos( iterator:Object )"],["iterCosh","iterCosh( iterator:Object )"],["iterCosineWave","iterCosineWave( [options:Object] )"],["iterCosm1","iterCosm1( iterator:Object )"],["iterCospi","iterCospi( iterator:Object )"],["iterCounter","iterCounter( iterator:Object )"],["iterCovercos","iterCovercos( iterator:Object )"],["iterCoversin","iterCoversin( iterator:Object )"],["iterCubesSeq","iterCubesSeq( [options:Object] )"],["itercugmean","itercugmean( iterator:Object )"],["itercuhmean","itercuhmean( iterator:Object )"],["itercumax","itercumax( iterator:Object )"],["itercumaxabs","itercumaxabs( iterator:Object )"],["itercumean","itercumean( iterator:Object )"],["itercumeanabs","itercumeanabs( iterator:Object )"],["itercumeanabs2","itercumeanabs2( iterator:Object )"],["itercumidrange","itercumidrange( iterator:Object )"],["itercumin","itercumin( iterator:Object )"],["itercuminabs","itercuminabs( iterator:Object )"],["itercuprod","itercuprod( iterator:Object )"],["itercurange","itercurange( iterator:Object )"],["itercusum","itercusum( iterator:Object )"],["itercusumabs","itercusumabs( iterator:Object )"],["itercusumabs2","itercusumabs2( iterator:Object )"],["iterDatespace","iterDatespace( start:integer|string|Date, stop:integer|string|Date[, N:integer][, options:Object] )"],["iterDedupe","iterDedupe( iterator:Object[, limit:integer] )"],["iterDedupeBy","iterDedupeBy( iterator:Object, [limit:integer,] fcn:Function )"],["iterDeg2rad","iterDeg2rad( iterator:Object )"],["iterDigamma","iterDigamma( iterator:Object )"],["iterDiracComb","iterDiracComb( [options:Object] )"],["iterDiracDelta","iterDiracDelta( iterator:Object )"],["iterDivide","iterDivide( iter0:Object, ...iterator:Object )"],["iterDoWhileEach","iterDoWhileEach( iterator:Object, predicate:Function, fcn:Function[, thisArg:any] )"],["iterEllipe","iterEllipe( iterator:Object )"],["iterEllipk","iterEllipk( iterator:Object )"],["iterEmpty","iterEmpty()"],["iterErf","iterErf( iterator:Object )"],["iterErfc","iterErfc( iterator:Object )"],["iterErfcinv","iterErfcinv( iterator:Object )"],["iterErfinv","iterErfinv( iterator:Object )"],["iterEta","iterEta( iterator:Object )"],["iterEvenIntegersSeq","iterEvenIntegersSeq( [options:Object] )"],["iterEvery","iterEvery( iterator:Object )"],["iterEveryBy","iterEveryBy( iterator:Object, predicate:Function[, thisArg:any ] )"],["iterExp","iterExp( iterator:Object )"],["iterExp2","iterExp2( iterator:Object )"],["iterExp10","iterExp10( iterator:Object )"],["iterExpit","iterExpit( iterator:Object )"],["iterExpm1","iterExpm1( iterator:Object )"],["iterExpm1rel","iterExpm1rel( iterator:Object )"],["iterFactorial","iterFactorial( iterator:Object )"],["iterFactorialln","iterFactorialln( iterator:Object )"],["iterFactorialsSeq","iterFactorialsSeq( [options:Object] )"],["iterFibonacciSeq","iterFibonacciSeq( [options:Object] )"],["iterFifthPowersSeq","iterFifthPowersSeq( [options:Object] )"],["iterFill","iterFill( iterator:Object, value:any[, begin:integer[, end:integer]] )"],["iterFilter","iterFilter( iterator:Object, predicate:Function[, thisArg:any] )"],["iterFilterMap","iterFilterMap( iterator:Object, fcn:Function[, thisArg:any] )"],["iterFirst","iterFirst( iterator:Object )"],["iterFlatTopPulse","iterFlatTopPulse( [options:Object] )"],["iterFloor","iterFloor( iterator:Object )"],["iterFloor2","iterFloor2( iterator:Object )"],["iterFloor10","iterFloor10( iterator:Object )"],["iterFlow","iterFlow( methods:Object )"],["iterForEach","iterForEach( iterator:Object, fcn:Function[, thisArg:any] )"],["iterFourthPowersSeq","iterFourthPowersSeq( [options:Object] )"],["iterFresnelc","iterFresnelc( iterator:Object )"],["iterFresnels","iterFresnels( iterator:Object )"],["iterGamma","iterGamma( iterator:Object )"],["iterGamma1pm1","iterGamma1pm1( iterator:Object )"],["iterGammaln","iterGammaln( iterator:Object )"],["iterHacovercos","iterHacovercos( iterator:Object )"],["iterHacoversin","iterHacoversin( iterator:Object )"],["iterHannPulse","iterHannPulse( [options:Object] )"],["iterHavercos","iterHavercos( iterator:Object )"],["iterHaversin","iterHaversin( iterator:Object )"],["iterHead","iterHead( iterator:Object, n:integer )"],["iterIncrspace","iterIncrspace( start:number, stop:number[, increment:number] )"],["iterIntegersSeq","iterIntegersSeq( [options:Object] )"],["iterIntersection","iterIntersection( iter0:Object, ...iterator:Object )"],["iterIntersectionByHash","iterIntersectionByHash( iter0:Object, ...iterator:Object, hashFcn:Function[, thisArg:any] )"],["iterInv","iterInv( iterator:Object )"],["iterLanczosPulse","iterLanczosPulse( [options:Object] )"],["iterLast","iterLast( iterator:Object )"],["iterLength","iterLength( iterator:Object )"],["iterLinspace","iterLinspace( start:number, stop:number[, N:integer] )"],["iterLn","iterLn( iterator:Object )"],["iterLog","iterLog( x:Object|number, b:Object|number )"],["iterLog1mexp","iterLog1mexp( iterator:Object )"],["iterLog1p","iterLog1p( iterator:Object )"],["iterLog1pexp","iterLog1pexp( iterator:Object )"],["iterLog2","iterLog2( iterator:Object )"],["iterLog10","iterLog10( iterator:Object )"],["iterLogit","iterLogit( iterator:Object )"],["iterLogspace","iterLogspace( start:number, stop:number[, N:integer][, options:Object] )"],["iterLucasSeq","iterLucasSeq( [options:Object] )"],["iterMap","iterMap( iterator:Object, fcn:Function[, thisArg:any] )"],["iterMapN","iterMapN( iter0:Object, ...iterator:Object, fcn:Function[, thisArg:any] )"],["itermax","itermax( iterator:Object )"],["itermaxabs","itermaxabs( iterator:Object )"],["itermean","itermean( iterator:Object )"],["itermeanabs","itermeanabs( iterator:Object )"],["itermeanabs2","itermeanabs2( iterator:Object )"],["itermidrange","itermidrange( iterator:Object )"],["itermin","itermin( iterator:Object )"],["iterminabs","iterminabs( iterator:Object )"],["itermmax","itermmax( iterator:Object, W:integer )"],["itermmaxabs","itermmaxabs( iterator:Object, W:integer )"],["itermmean","itermmean( iterator:Object, W:integer )"],["itermmeanabs","itermmeanabs( iterator:Object, W:integer )"],["itermmeanabs2","itermmeanabs2( iterator:Object, W:integer )"],["itermmidrange","itermmidrange( iterator:Object, W:integer )"],["itermmin","itermmin( iterator:Object, W:integer )"],["itermminabs","itermminabs( iterator:Object, W:integer )"],["iterMod","iterMod( iter0:Object, ...iterator:Object )"],["itermprod","itermprod( iterator:Object, W:integer )"],["itermrange","itermrange( iterator:Object, W:integer )"],["itermsum","itermsum( iterator:Object, W:integer )"],["itermsumabs","itermsumabs( iterator:Object, W:integer )"],["itermsumabs2","itermsumabs2( iterator:Object, W:integer )"],["iterMultiply","iterMultiply( iter0:Object, ...iterator:Object )"],["iterNegaFibonacciSeq","iterNegaFibonacciSeq( [options:Object] )"],["iterNegaLucasSeq","iterNegaLucasSeq( [options:Object] )"],["iterNegativeEvenIntegersSeq","iterNegativeEvenIntegersSeq( [options:Object] )"],["iterNegativeIntegersSeq","iterNegativeIntegersSeq( [options:Object] )"],["iterNegativeOddIntegersSeq","iterNegativeOddIntegersSeq( [options:Object] )"],["iterNone","iterNone( iterator:Object )"],["iterNoneBy","iterNoneBy( iterator:Object, predicate:Function[, thisArg:any ] )"],["iterNonFibonacciSeq","iterNonFibonacciSeq( [options:Object] )"],["iterNonNegativeEvenIntegersSeq","iterNonNegativeEvenIntegersSeq( [options:Object] )"],["iterNonNegativeIntegersSeq","iterNonNegativeIntegersSeq( [options:Object] )"],["iterNonPositiveEvenIntegersSeq","iterNonPositiveEvenIntegersSeq( [options:Object] )"],["iterNonPositiveIntegersSeq","iterNonPositiveIntegersSeq( [options:Object] )"],["iterNonSquaresSeq","iterNonSquaresSeq( [options:Object] )"],["iterNth","iterNth( iterator:Object, n:integer )"],["iterOddIntegersSeq","iterOddIntegersSeq( [options:Object] )"],["iterPeriodicSinc","iterPeriodicSinc( n:integer[, options:Object] )"],["iterPipeline","iterPipeline( iterFcn:Function|Array[, ...iterFcn:Function] )"],["iterPop","iterPop( iterator:Object[, clbk:Function[, thisArg:any]] )"],["iterPositiveEvenIntegersSeq","iterPositiveEvenIntegersSeq( [options:Object] )"],["iterPositiveIntegersSeq","iterPositiveIntegersSeq( [options:Object] )"],["iterPositiveOddIntegersSeq","iterPositiveOddIntegersSeq( [options:Object] )"],["iterPow","iterPow( base:Object|number, exponent:Object|number )"],["iterPrimesSeq","iterPrimesSeq( [options:Object] )"],["iterprod","iterprod( iterator:Object )"],["iterPulse","iterPulse( [options:Object] )"],["iterPush","iterPush( iterator:Object, ...items:any )"],["iterRad2deg","iterRad2deg( iterator:Object )"],["iterRamp","iterRamp( iterator:Object )"],["iterrange","iterrange( iterator:Object )"],["iterReject","iterReject( iterator:Object, predicate:Function[, thisArg:any] )"],["iterReplicate","iterReplicate( iterator:Object, n:integer )"],["iterReplicateBy","iterReplicateBy( iterator:Object, fcn:Function[, thisArg:any] )"],["iterRound","iterRound( iterator:Object )"],["iterRound2","iterRound2( iterator:Object )"],["iterRound10","iterRound10( iterator:Object )"],["iterRsqrt","iterRsqrt( iterator:Object )"],["iterSawtoothWave","iterSawtoothWave( [options:Object] )"],["iterShift","iterShift( iterator:Object[, clbk:Function[, thisArg:any]] )"],["iterSignum","iterSignum( iterator:Object )"],["iterSin","iterSin( iterator:Object )"],["iterSinc","iterSinc( iterator:Object )"],["iterSineWave","iterSineWave( [options:Object] )"],["iterSinh","iterSinh( iterator:Object )"],["iterSinpi","iterSinpi( iterator:Object )"],["iterSlice","iterSlice( iterator:Object[, begin:integer[, end:integer]] )"],["iterSome","iterSome( iterator:Object, n:number )"],["iterSomeBy","iterSomeBy( iterator:Object, n:integer, predicate:Function[, thisArg:any ] )"],["iterSpence","iterSpence( iterator:Object )"],["iterSqrt","iterSqrt( iterator:Object )"],["iterSqrt1pm1","iterSqrt1pm1( iterator:Object )"],["iterSquaredTriangularSeq","iterSquaredTriangularSeq( [options:Object] )"],["iterSquaresSeq","iterSquaresSeq( [options:Object] )"],["iterSquareWave","iterSquareWave( [options:Object] )"],["iterstdev","iterstdev( iterator:Object[, mean:number] )"],["iterStep","iterStep( start:number, increment:number[, N:number] )"],["iterStrided","iterStrided( iterator:Object, stride:integer[, offset:integer[, eager:boolean]] )"],["iterStridedBy","iterStridedBy( iterator:Object, fcn:Function[, offset:integer[, eager:boolean]][, thisArg:any] )"],["iterSubtract","iterSubtract( iter0:Object, ...iterator:Object )"],["itersum","itersum( iterator:Object )"],["itersumabs","itersumabs( iterator:Object )"],["itersumabs2","itersumabs2( iterator:Object )"],["iterTan","iterTan( iterator:Object )"],["iterTanh","iterTanh( iterator:Object )"],["iterThunk","iterThunk( iterFcn:Function[, ...args:any] )"],["iterTriangleWave","iterTriangleWave( [options:Object] )"],["iterTriangularSeq","iterTriangularSeq( [options:Object] )"],["iterTribonnaciSeq","iterTribonnaciSeq( [options:Object] )"],["iterTrigamma","iterTrigamma( iterator:Object )"],["iterTrunc","iterTrunc( iterator:Object )"],["iterTrunc2","iterTrunc2( iterator:Object 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out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.discreteUniform.ndarray","random.strided.discreteUniform.ndarray( N:integer, a:ArrayLikeObject, sa:integer, oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.exponential","random.strided.exponential( N:integer, lambda:ArrayLikeObject, sl:integer, out:ArrayLikeObject, so:integer )"],["random.strided.exponential.ndarray","random.strided.exponential.ndarray( N:integer, lambda:ArrayLikeObject, sl:integer, ol:integer, out:ArrayLikeObject, so:integer, oo:integer )"],["random.strided.exponential.factory","random.strided.exponential.factory( [options:Object] 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clbk:Function )"],["resolveParentPathBy.sync","resolveParentPathBy.sync( path:string[, options:Object], predicate:Function )"],["reUncPath","reUncPath()"],["reUncPath.REGEXP","reUncPath.REGEXP"],["reUtf16SurrogatePair","reUtf16SurrogatePair()"],["reUtf16SurrogatePair.REGEXP","reUtf16SurrogatePair.REGEXP"],["reUtf16UnpairedSurrogate","reUtf16UnpairedSurrogate()"],["reUtf16UnpairedSurrogate.REGEXP","reUtf16UnpairedSurrogate.REGEXP"],["reverseArguments","reverseArguments( fcn:Function[, thisArg:any] )"],["reverseString","reverseString( str:string[, options:Object] )"],["reviveBasePRNG","reviveBasePRNG( key:string, value:any )"],["reviveBuffer","reviveBuffer( key:string, value:any )"],["reviveComplex","reviveComplex( key:string, value:any )"],["reviveComplex64","reviveComplex64( key:string, value:any )"],["reviveComplex128","reviveComplex128( key:string, value:any )"],["reviveError","reviveError( key:string, value:any )"],["reviveRegExp","reviveRegExp( key:string, value:any 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setter:Function )"],["setMemoizedConfigurableReadOnly","setMemoizedConfigurableReadOnly( obj:Object, prop:string|symbol, fcn:Function )"],["setMemoizedReadOnly","setMemoizedReadOnly( obj:Object, prop:string|symbol, fcn:Function )"],["setNonEnumerableProperty","setNonEnumerableProperty( obj:Object, prop:string|symbol, value:any )"],["setNonEnumerableReadOnly","setNonEnumerableReadOnly( obj:Object, prop:string|symbol, value:any )"],["setNonEnumerableReadOnlyAccessor","setNonEnumerableReadOnlyAccessor( obj:Object, prop:string|symbol, getter:Function )"],["setNonEnumerableReadWriteAccessor","setNonEnumerableReadWriteAccessor( obj:Object, prop:string|symbol, getter:Function, setter:Function )"],["setNonEnumerableWriteOnlyAccessor","setNonEnumerableWriteOnlyAccessor( obj:Object, prop:string|symbol, setter:Function )"],["setReadOnly","setReadOnly( obj:Object, prop:string|symbol, value:any )"],["setReadOnlyAccessor","setReadOnlyAccessor( obj:Object, prop:string|symbol, getter:Function 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)"],["strided.ahavercosBy","strided.ahavercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.ahavercosBy.ndarray","strided.ahavercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.ahaversinBy","strided.ahaversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.ahaversinBy.ndarray","strided.ahaversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.asinBy","strided.asinBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.asinBy.ndarray","strided.asinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.asinhBy","strided.asinhBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.asinhBy.ndarray","strided.asinhBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.atanBy","strided.atanBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.atanBy.ndarray","strided.atanBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.atanhBy","strided.atanhBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.atanhBy.ndarray","strided.atanhBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.avercosBy","strided.avercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.avercosBy.ndarray","strided.avercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.aversinBy","strided.aversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.aversinBy.ndarray","strided.aversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.besselj0By","strided.besselj0By( N:integer, 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sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.bessely1By","strided.bessely1By( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.bessely1By.ndarray","strided.bessely1By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.binetBy","strided.binetBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.binetBy.ndarray","strided.binetBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.cbrt","strided.cbrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.cbrt.ndarray","strided.cbrt.ndarray( N:integer, dtypeX:any, 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)"],["strided.cosBy.ndarray","strided.cosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.deg2rad","strided.deg2rad( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.deg2rad.ndarray","strided.deg2rad.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.dataTypes","strided.dataTypes()"],["strided.dcbrtBy","strided.dcbrtBy( N:integer, x:Float64Array, sx:integer, y:Float64Array, sy:integer, clbk:Function[, thisArg:any] )"],["strided.dcbrtBy.ndarray","strided.dcbrtBy.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, y:Float64Array, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.dispatch","strided.dispatch( fcns:Function|ArrayLikeObject<Function>, 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)"],["stridedArrayStream.objectMode","stridedArrayStream.objectMode( N:integer, buffer:ArrayLikeObject, stride:integer, offset:integer[, options:Object] )"],["string2buffer","string2buffer( str:string[, encoding:string] )"],["sub2ind","sub2ind( shape:ArrayLike, ...subscript:integer[, options:Object] )"],["substringAfter","substringAfter( str:string, search:string[, fromIndex:integer] )"],["substringAfterLast","substringAfterLast( str:string, search:string[, fromIndex:integer] )"],["substringBefore","substringBefore( str:string, search:string )"],["substringBeforeLast","substringBeforeLast( str:string, search:string )"],["SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()"],["SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()"],["Symbol","Symbol( [description:string] )"],["tabulate","tabulate( collection:Array|TypedArray|Object )"],["tabulateBy","tabulateBy( collection:Array|TypedArray|Object, [options:Object,] indicator:Function 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[dtype:string] )"],["typedarraypool","typedarraypool( length:integer[, dtype:string] )"],["typedarraypool","typedarraypool( typedarray:TypedArray[, dtype:string] )"],["typedarraypool","typedarraypool( obj:Object[, dtype:string] )"],["typedarraypool.malloc","typedarraypool.malloc( [dtype:string] )"],["typedarraypool.malloc","typedarraypool.malloc( length:integer[, dtype:string] )"],["typedarraypool.malloc","typedarraypool.malloc( typedarray:TypedArray[, dtype:string] )"],["typedarraypool.malloc","typedarraypool.malloc( obj:Object[, dtype:string] )"],["typedarraypool.calloc","typedarraypool.calloc( [dtype:string] )"],["typedarraypool.calloc","typedarraypool.calloc( length:integer[, dtype:string] )"],["typedarraypool.free","typedarraypool.free( buf:TypedArray|ArrayBuffer )"],["typedarraypool.clear","typedarraypool.clear()"],["typedarraypool.highWaterMark","typedarraypool.highWaterMark"],["typedarraypool.nbytes","typedarraypool.nbytes"],["typedarraypool.factory","typedarraypool.factory( [options:Object] )"],["typemax","typemax( dtype:string )"],["typemin","typemin( dtype:string )"],["typeOf","typeOf( value:any )"],["UINT8_MAX","UINT8_MAX"],["UINT8_NUM_BYTES","UINT8_NUM_BYTES"],["Uint8Array","Uint8Array()"],["Uint8Array","Uint8Array( length:integer )"],["Uint8Array","Uint8Array( typedarray:TypedArray )"],["Uint8Array","Uint8Array( obj:Object )"],["Uint8Array","Uint8Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )"],["Uint8Array.from","Uint8Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )"],["Uint8Array.of","Uint8Array.of( element0:number[, element1:number[, ...elementN:number]] 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predicate:Function[, thisArg:Any] )"],["Uint8Array.prototype.findIndex","Uint8Array.prototype.findIndex( predicate:Function[, thisArg:Any] )"],["Uint8Array.prototype.forEach","Uint8Array.prototype.forEach( fcn:Function[, thisArg:Any] )"],["Uint8Array.prototype.includes","Uint8Array.prototype.includes( searchElement:number[, fromIndex:integer] )"],["Uint8Array.prototype.indexOf","Uint8Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )"],["Uint8Array.prototype.join","Uint8Array.prototype.join( [separator:string] )"],["Uint8Array.prototype.keys","Uint8Array.prototype.keys()"],["Uint8Array.prototype.lastIndexOf","Uint8Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )"],["Uint8Array.prototype.map","Uint8Array.prototype.map( fcn:Function[, thisArg:Any] )"],["Uint8Array.prototype.reduce","Uint8Array.prototype.reduce( fcn:Function[, initialValue:Any] )"],["Uint8Array.prototype.reduceRight","Uint8Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )"],["Uint8Array.prototype.reverse","Uint8Array.prototype.reverse()"],["Uint8Array.prototype.set","Uint8Array.prototype.set( arr:ArrayLike[, offset:integer] )"],["Uint8Array.prototype.slice","Uint8Array.prototype.slice( [begin:integer[, end:integer]] )"],["Uint8Array.prototype.some","Uint8Array.prototype.some( predicate:Function[, thisArg:Any] )"],["Uint8Array.prototype.sort","Uint8Array.prototype.sort( [compareFunction:Function] )"],["Uint8Array.prototype.subarray","Uint8Array.prototype.subarray( [begin:integer[, end:integer]] )"],["Uint8Array.prototype.toLocaleString","Uint8Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )"],["Uint8Array.prototype.toString","Uint8Array.prototype.toString()"],["Uint8Array.prototype.values","Uint8Array.prototype.values()"],["Uint8ClampedArray","Uint8ClampedArray()"],["Uint8ClampedArray","Uint8ClampedArray( length:integer )"],["Uint8ClampedArray","Uint8ClampedArray( typedarray:TypedArray )"],["Uint8ClampedArray","Uint8ClampedArray( obj:Object )"],["Uint8ClampedArray","Uint8ClampedArray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )"],["Uint8ClampedArray.from","Uint8ClampedArray.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )"],["Uint8ClampedArray.of","Uint8ClampedArray.of( element0:number[, element1:number[, ...elementN:number]] )"],["Uint8ClampedArray.BYTES_PER_ELEMENT","Uint8ClampedArray.BYTES_PER_ELEMENT"],["Uint8ClampedArray.name","Uint8ClampedArray.name"],["Uint8ClampedArray.prototype.buffer","Uint8ClampedArray.prototype.buffer"],["Uint8ClampedArray.prototype.byteLength","Uint8ClampedArray.prototype.byteLength"],["Uint8ClampedArray.prototype.byteOffset","Uint8ClampedArray.prototype.byteOffset"],["Uint8ClampedArray.prototype.BYTES_PER_ELEMENT","Uint8ClampedArray.prototype.BYTES_PER_ELEMENT"],["Uint8ClampedArray.prototype.length","Uint8ClampedArray.prototype.length"],["Uint8ClampedArray.prototype.copyWithin","Uint8ClampedArray.prototype.copyWithin( target:integer, start:integer[, end:integer] )"],["Uint8ClampedArray.prototype.entries","Uint8ClampedArray.prototype.entries()"],["Uint8ClampedArray.prototype.every","Uint8ClampedArray.prototype.every( predicate:Function[, thisArg:Any] )"],["Uint8ClampedArray.prototype.fill","Uint8ClampedArray.prototype.fill( value:number[, start:integer[, end:integer]] )"],["Uint8ClampedArray.prototype.filter","Uint8ClampedArray.prototype.filter( predicate:Function[, thisArg:Any] )"],["Uint8ClampedArray.prototype.find","Uint8ClampedArray.prototype.find( predicate:Function[, thisArg:Any] )"],["Uint8ClampedArray.prototype.findIndex","Uint8ClampedArray.prototype.findIndex( predicate:Function[, thisArg:Any] )"],["Uint8ClampedArray.prototype.forEach","Uint8ClampedArray.prototype.forEach( fcn:Function[, thisArg:Any] )"],["Uint8ClampedArray.prototype.includes","Uint8ClampedArray.prototype.includes( searchElement:number[, fromIndex:integer] )"],["Uint8ClampedArray.prototype.indexOf","Uint8ClampedArray.prototype.indexOf( searchElement:number[, fromIndex:integer] )"],["Uint8ClampedArray.prototype.join","Uint8ClampedArray.prototype.join( [separator:string] )"],["Uint8ClampedArray.prototype.keys","Uint8ClampedArray.prototype.keys()"],["Uint8ClampedArray.prototype.lastIndexOf","Uint8ClampedArray.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )"],["Uint8ClampedArray.prototype.map","Uint8ClampedArray.prototype.map( fcn:Function[, thisArg:Any] )"],["Uint8ClampedArray.prototype.reduce","Uint8ClampedArray.prototype.reduce( fcn:Function[, initialValue:Any] )"],["Uint8ClampedArray.prototype.reduceRight","Uint8ClampedArray.prototype.reduceRight( fcn:Function[, initialValue:Any] )"],["Uint8ClampedArray.prototype.reverse","Uint8ClampedArray.prototype.reverse()"],["Uint8ClampedArray.prototype.set","Uint8ClampedArray.prototype.set( arr:ArrayLike[, offset:integer] )"],["Uint8ClampedArray.prototype.slice","Uint8ClampedArray.prototype.slice( [begin:integer[, end:integer]] )"],["Uint8ClampedArray.prototype.some","Uint8ClampedArray.prototype.some( predicate:Function[, thisArg:Any] )"],["Uint8ClampedArray.prototype.sort","Uint8ClampedArray.prototype.sort( [compareFunction:Function] )"],["Uint8ClampedArray.prototype.subarray","Uint8ClampedArray.prototype.subarray( [begin:integer[, end:integer]] )"],["Uint8ClampedArray.prototype.toLocaleString","Uint8ClampedArray.prototype.toLocaleString( [locales:string|Array[, options:Object]] )"],["Uint8ClampedArray.prototype.toString","Uint8ClampedArray.prototype.toString()"],["Uint8ClampedArray.prototype.values","Uint8ClampedArray.prototype.values()"],["UINT16_MAX","UINT16_MAX"],["UINT16_NUM_BYTES","UINT16_NUM_BYTES"],["Uint16Array","Uint16Array()"],["Uint16Array","Uint16Array( length:integer )"],["Uint16Array","Uint16Array( typedarray:TypedArray )"],["Uint16Array","Uint16Array( obj:Object )"],["Uint16Array","Uint16Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )"],["Uint16Array.from","Uint16Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )"],["Uint16Array.of","Uint16Array.of( element0:number[, element1:number[, ...elementN:number]] )"],["Uint16Array.BYTES_PER_ELEMENT","Uint16Array.BYTES_PER_ELEMENT"],["Uint16Array.name","Uint16Array.name"],["Uint16Array.prototype.buffer","Uint16Array.prototype.buffer"],["Uint16Array.prototype.byteLength","Uint16Array.prototype.byteLength"],["Uint16Array.prototype.byteOffset","Uint16Array.prototype.byteOffset"],["Uint16Array.prototype.BYTES_PER_ELEMENT","Uint16Array.prototype.BYTES_PER_ELEMENT"],["Uint16Array.prototype.length","Uint16Array.prototype.length"],["Uint16Array.prototype.copyWithin","Uint16Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )"],["Uint16Array.prototype.entries","Uint16Array.prototype.entries()"],["Uint16Array.prototype.every","Uint16Array.prototype.every( predicate:Function[, thisArg:Any] )"],["Uint16Array.prototype.fill","Uint16Array.prototype.fill( value:number[, start:integer[, end:integer]] )"],["Uint16Array.prototype.filter","Uint16Array.prototype.filter( predicate:Function[, thisArg:Any] )"],["Uint16Array.prototype.find","Uint16Array.prototype.find( predicate:Function[, thisArg:Any] )"],["Uint16Array.prototype.findIndex","Uint16Array.prototype.findIndex( predicate:Function[, thisArg:Any] )"],["Uint16Array.prototype.forEach","Uint16Array.prototype.forEach( fcn:Function[, thisArg:Any] )"],["Uint16Array.prototype.includes","Uint16Array.prototype.includes( searchElement:number[, fromIndex:integer] )"],["Uint16Array.prototype.indexOf","Uint16Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )"],["Uint16Array.prototype.join","Uint16Array.prototype.join( [separator:string] )"],["Uint16Array.prototype.keys","Uint16Array.prototype.keys()"],["Uint16Array.prototype.lastIndexOf","Uint16Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )"],["Uint16Array.prototype.map","Uint16Array.prototype.map( fcn:Function[, thisArg:Any] )"],["Uint16Array.prototype.reduce","Uint16Array.prototype.reduce( fcn:Function[, initialValue:Any] )"],["Uint16Array.prototype.reduceRight","Uint16Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )"],["Uint16Array.prototype.reverse","Uint16Array.prototype.reverse()"],["Uint16Array.prototype.set","Uint16Array.prototype.set( arr:ArrayLike[, offset:integer] )"],["Uint16Array.prototype.slice","Uint16Array.prototype.slice( [begin:integer[, end:integer]] )"],["Uint16Array.prototype.some","Uint16Array.prototype.some( predicate:Function[, thisArg:Any] )"],["Uint16Array.prototype.sort","Uint16Array.prototype.sort( [compareFunction:Function] )"],["Uint16Array.prototype.subarray","Uint16Array.prototype.subarray( [begin:integer[, end:integer]] )"],["Uint16Array.prototype.toLocaleString","Uint16Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )"],["Uint16Array.prototype.toString","Uint16Array.prototype.toString()"],["Uint16Array.prototype.values","Uint16Array.prototype.values()"],["UINT32_MAX","UINT32_MAX"],["UINT32_NUM_BYTES","UINT32_NUM_BYTES"],["Uint32Array","Uint32Array()"],["Uint32Array","Uint32Array( length:integer )"],["Uint32Array","Uint32Array( typedarray:TypedArray )"],["Uint32Array","Uint32Array( obj:Object )"],["Uint32Array","Uint32Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )"],["Uint32Array.from","Uint32Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )"],["Uint32Array.of","Uint32Array.of( element0:number[, element1:number[, ...elementN:number]] )"],["Uint32Array.BYTES_PER_ELEMENT","Uint32Array.BYTES_PER_ELEMENT"],["Uint32Array.name","Uint32Array.name"],["Uint32Array.prototype.buffer","Uint32Array.prototype.buffer"],["Uint32Array.prototype.byteLength","Uint32Array.prototype.byteLength"],["Uint32Array.prototype.byteOffset","Uint32Array.prototype.byteOffset"],["Uint32Array.prototype.BYTES_PER_ELEMENT","Uint32Array.prototype.BYTES_PER_ELEMENT"],["Uint32Array.prototype.length","Uint32Array.prototype.length"],["Uint32Array.prototype.copyWithin","Uint32Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )"],["Uint32Array.prototype.entries","Uint32Array.prototype.entries()"],["Uint32Array.prototype.every","Uint32Array.prototype.every( predicate:Function[, thisArg:Any] )"],["Uint32Array.prototype.fill","Uint32Array.prototype.fill( value:number[, start:integer[, end:integer]] )"],["Uint32Array.prototype.filter","Uint32Array.prototype.filter( predicate:Function[, thisArg:Any] )"],["Uint32Array.prototype.find","Uint32Array.prototype.find( predicate:Function[, thisArg:Any] )"],["Uint32Array.prototype.findIndex","Uint32Array.prototype.findIndex( predicate:Function[, thisArg:Any] )"],["Uint32Array.prototype.forEach","Uint32Array.prototype.forEach( fcn:Function[, thisArg:Any] )"],["Uint32Array.prototype.includes","Uint32Array.prototype.includes( searchElement:number[, fromIndex:integer] )"],["Uint32Array.prototype.indexOf","Uint32Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )"],["Uint32Array.prototype.join","Uint32Array.prototype.join( [separator:string] )"],["Uint32Array.prototype.keys","Uint32Array.prototype.keys()"],["Uint32Array.prototype.lastIndexOf","Uint32Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )"],["Uint32Array.prototype.map","Uint32Array.prototype.map( fcn:Function[, thisArg:Any] )"],["Uint32Array.prototype.reduce","Uint32Array.prototype.reduce( fcn:Function[, initialValue:Any] )"],["Uint32Array.prototype.reduceRight","Uint32Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )"],["Uint32Array.prototype.reverse","Uint32Array.prototype.reverse()"],["Uint32Array.prototype.set","Uint32Array.prototype.set( arr:ArrayLike[, offset:integer] )"],["Uint32Array.prototype.slice","Uint32Array.prototype.slice( [begin:integer[, end:integer]] )"],["Uint32Array.prototype.some","Uint32Array.prototype.some( predicate:Function[, thisArg:Any] )"],["Uint32Array.prototype.sort","Uint32Array.prototype.sort( [compareFunction:Function] )"],["Uint32Array.prototype.subarray","Uint32Array.prototype.subarray( [begin:integer[, end:integer]] )"],["Uint32Array.prototype.toLocaleString","Uint32Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )"],["Uint32Array.prototype.toString","Uint32Array.prototype.toString()"],["Uint32Array.prototype.values","Uint32Array.prototype.values()"],["umask","umask( [mask:integer|string,] [options:Object] )"],["uncapitalize","uncapitalize( str:string )"],["uncapitalizeKeys","uncapitalizeKeys( obj:Object )"],["uncurry","uncurry( fcn:Function[, arity:integer, ][thisArg:any] )"],["uncurryRight","uncurryRight( fcn:Function[, arity:integer, ][thisArg:any] )"],["UNICODE_MAX","UNICODE_MAX"],["UNICODE_MAX_BMP","UNICODE_MAX_BMP"],["UnicodeColumnChartSparkline","UnicodeColumnChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )"],["UnicodeLineChartSparkline","UnicodeLineChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )"],["UnicodeSparkline","UnicodeSparkline( [data:ArrayLike|ndarray,] [options:Object] )"],["UnicodeTristateChartSparkline","UnicodeTristateChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )"],["UnicodeUpDownChartSparkline","UnicodeUpDownChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )"],["UnicodeWinLossChartSparkline","UnicodeWinLossChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )"],["unlink","unlink( path:string|Buffer|integer, clbk:Function )"],["unlink.sync","unlink.sync( path:string|Buffer|integer )"],["unshift","unshift( collection:Array|TypedArray|Object, ...items:any )"],["until","until( predicate:Function, fcn:Function[, thisArg:any] )"],["untilAsync","untilAsync( predicate:Function, fcn:Function, done:Function[, thisArg:any] )"],["untilEach","untilEach( collection:Array|TypedArray|Object, predicate:Function, fcn:Function[, thisArg:any] )"],["untilEachRight","untilEachRight( collection:Array|TypedArray|Object, predicate:Function, fcn:Function[, thisArg:any] )"],["unzip","unzip( arr:Array[, idx:Array<number>] )"],["uppercase","uppercase( str:string )"],["uppercaseKeys","uppercaseKeys( obj:Object )"],["US_STATES_ABBR","US_STATES_ABBR()"],["US_STATES_CAPITALS","US_STATES_CAPITALS()"],["US_STATES_CAPITALS_NAMES","US_STATES_CAPITALS_NAMES()"],["US_STATES_NAMES","US_STATES_NAMES()"],["US_STATES_NAMES_CAPITALS","US_STATES_NAMES_CAPITALS()"],["utf16ToUTF8Array","utf16ToUTF8Array( str:string )"],["vartest","vartest( x:Array<number>, y:Array<number>[, options:Object] )"],["waterfall","waterfall( fcns:Array<Function>, clbk:Function[, thisArg:any] )"],["waterfall.factory","waterfall.factory( fcns:Array<Function>, clbk:Function[, thisArg:any] )"],["WebAssemblyMemory","WebAssemblyMemory( descriptor:Object )"],["WebAssemblyMemory.prototype.buffer","WebAssemblyMemory.prototype.buffer"],["WebAssemblyMemory.prototype.grow","WebAssemblyMemory.prototype.grow( delta:integer )"],["whileAsync","whileAsync( predicate:Function, fcn:Function, done:Function[, thisArg:any] )"],["whileEach","whileEach( collection:Array|TypedArray|Object, predicate:Function, fcn:Function[, thisArg:any] )"],["whileEachRight","whileEachRight( collection:Array|TypedArray|Object, predicate:Function, fcn:Function[, thisArg:any] )"],["whilst","whilst( predicate:Function, fcn:Function[, thisArg:any] )"],["wilcoxon","wilcoxon( x:Array|TypedArray[, y:Array|TypedArray][, options:Object] )"],["writableProperties","writableProperties( value:any )"],["writablePropertiesIn","writablePropertiesIn( value:any )"],["writablePropertyNames","writablePropertyNames( value:any )"],["writablePropertyNamesIn","writablePropertyNamesIn( value:any )"],["writablePropertySymbols","writablePropertySymbols( value:any )"],["writablePropertySymbolsIn","writablePropertySymbolsIn( value:any )"],["writeFile","writeFile( file:string|Buffer|integer, data:string|Buffer[, options:Object|string], clbk:Function )"],["writeFile.sync","writeFile.sync( file:string|Buffer|integer, data:string|Buffer[, options:Object|string] )"],["zip","zip( ...arr:Array[, options:Object] )"],["ztest","ztest( x:Array<number>, sigma:number[, options:Object] )"],["ztest2","ztest2( x:Array<number>, y:Array<number>, sigmax:number, sigmay:number[, options:Object] )"]]

From 960b084f1a4daa0f8ae95dc6fa6b7c72a5342b43 Mon Sep 17 00:00:00 2001
From: stdlib-bot <82920195+stdlib-bot@users.noreply.github.com>
Date: Thu, 2 Jan 2025 19:31:07 -0800
Subject: [PATCH 57/87] feat: update namespace TypeScript declarations

PR-URL: https://github.com/stdlib-js/stdlib/pull/4487

Co-authored-by: Philipp Burckhardt <pburckhardt@outlook.com>
Reviewed-by: Philipp Burckhardt <pburckhardt@outlook.com>
Signed-off-by: stdlib-bot <82920195+stdlib-bot@users.noreply.github.com>
---
 .../@stdlib/blas/ext/base/docs/types/index.d.ts      | 12 ++++++------
 .../@stdlib/stats/base/docs/types/index.d.ts         | 10 +++++-----
 2 files changed, 11 insertions(+), 11 deletions(-)

diff --git a/lib/node_modules/@stdlib/blas/ext/base/docs/types/index.d.ts b/lib/node_modules/@stdlib/blas/ext/base/docs/types/index.d.ts
index f3eac464da8f..03b759a054cd 100644
--- a/lib/node_modules/@stdlib/blas/ext/base/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/blas/ext/base/docs/types/index.d.ts
@@ -1370,7 +1370,7 @@ interface Namespace {
 	*
 	* @param N - number of indexed elements
 	* @param x - input array
-	* @param stride - stride length
+	* @param strideX - stride length
 	* @returns sum
 	*
 	* @example
@@ -1490,12 +1490,12 @@ interface Namespace {
 	gapxsum: typeof gapxsum;
 
 	/**
-	* Adds a constant to each strided array element and computes the sum using an improved Kahan–Babuška algorithm.
+	* Adds a scalar constant to each strided array element and computes the sum using an improved Kahan–Babuška algorithm.
 	*
 	* @param N - number of indexed elements
-	* @param alpha - constant
+	* @param alpha - scalar constant
 	* @param x - input array
-	* @param stride - stride length
+	* @param strideX - stride length
 	* @returns sum
 	*
 	* @example
@@ -1636,9 +1636,9 @@ interface Namespace {
 	* @param N - number of indexed elements
 	* @param sum - initial sum
 	* @param x - input array
-	* @param strideX - `x` stride length
+	* @param strideX - stride length for `x`
 	* @param y - output array
-	* @param strideY - `y` stride length
+	* @param strideY - stride length for `y`
 	* @returns output array
 	*
 	* @example
diff --git a/lib/node_modules/@stdlib/stats/base/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/docs/types/index.d.ts
index f29e2223adb3..d760f9e8b9b2 100644
--- a/lib/node_modules/@stdlib/stats/base/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/docs/types/index.d.ts
@@ -529,7 +529,7 @@ interface Namespace {
 	*
 	* @param N - number of indexed elements
 	* @param x - sorted input array
-	* @param stride - stride length
+	* @param strideX - stride length
 	* @returns maximum absolute value
 	*
 	* @example
@@ -555,7 +555,7 @@ interface Namespace {
 	*
 	* @param N - number of indexed elements
 	* @param x - sorted input array
-	* @param stride - stride length
+	* @param strideX - stride length
 	* @returns maximum value
 	*
 	* @example
@@ -939,7 +939,7 @@ interface Namespace {
 	*
 	* @param N - number of indexed elements
 	* @param x - sorted input array
-	* @param stride - stride length
+	* @param strideX - stride length
 	* @returns median value
 	*
 	* @example
@@ -1043,7 +1043,7 @@ interface Namespace {
 	*
 	* @param N - number of indexed elements
 	* @param x - sorted input array
-	* @param stride - stride length
+	* @param strideX - stride length
 	* @returns minimum value
 	*
 	* @example
@@ -4261,7 +4261,7 @@ interface Namespace {
 	*
 	* @param N - number of indexed elements
 	* @param x - sorted input array
-	* @param stride - stride length
+	* @param strideX - stride length
 	* @returns maximum value
 	*
 	* @example

From 810f68ab9df619907d134931431014c543aeabda Mon Sep 17 00:00:00 2001
From: JoyBoy <144602492+0PrashantYadav0@users.noreply.github.com>
Date: Fri, 3 Jan 2025 09:01:56 +0530
Subject: [PATCH 58/87] feat: add C implementation for
 `stats/base/dists/rayleigh/median`

PR-URL: https://github.com/stdlib-js/stdlib/pull/4027
Closes: https://github.com/stdlib-js/stdlib/issues/3804

Co-authored-by: Philipp Burckhardt <pburckhardt@outlook.com>
Co-authored-by: stdlib-bot <noreply@stdlib.io>
Reviewed-by: Philipp Burckhardt <pburckhardt@outlook.com>
Signed-off-by: Philipp Burckhardt <pburckhardt@outlook.com>
---
 .../base/dists/rayleigh/median/README.md      |  95 +++++++++-
 .../rayleigh/median/benchmark/benchmark.js    |  11 +-
 .../median/benchmark/benchmark.native.js      |  68 +++++++
 .../rayleigh/median/benchmark/c/Makefile      | 146 +++++++++++++++
 .../rayleigh/median/benchmark/c/benchmark.c   | 139 ++++++++++++++
 .../base/dists/rayleigh/median/binding.gyp    | 170 ++++++++++++++++++
 .../dists/rayleigh/median/examples/c/Makefile | 146 +++++++++++++++
 .../rayleigh/median/examples/c/example.c      |  38 ++++
 .../base/dists/rayleigh/median/include.gypi   |  53 ++++++
 .../stdlib/stats/base/dists/rayleigh/median.h |  38 ++++
 .../base/dists/rayleigh/median/lib/native.js  |  58 ++++++
 .../base/dists/rayleigh/median/manifest.json  |  83 +++++++++
 .../base/dists/rayleigh/median/package.json   |   3 +
 .../base/dists/rayleigh/median/src/Makefile   |  70 ++++++++
 .../base/dists/rayleigh/median/src/addon.c    |  23 +++
 .../base/dists/rayleigh/median/src/main.c     |  39 ++++
 .../dists/rayleigh/median/test/test.native.js |  92 ++++++++++
 17 files changed, 1268 insertions(+), 4 deletions(-)
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/benchmark/benchmark.native.js
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/benchmark/c/Makefile
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/benchmark/c/benchmark.c
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/binding.gyp
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/examples/c/Makefile
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/examples/c/example.c
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/include.gypi
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/include/stdlib/stats/base/dists/rayleigh/median.h
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/lib/native.js
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/manifest.json
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/src/Makefile
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/src/addon.c
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/src/main.c
 create mode 100644 lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/test/test.native.js

diff --git a/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/README.md b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/README.md
index 07db6a790b4a..66851a14b5b7 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/README.md
+++ b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/README.md
@@ -59,8 +59,7 @@ var median = require( '@stdlib/stats/base/dists/rayleigh/median' );
 
 #### median( sigma )
 
-Returns the [median][median] of a [Rayleigh][rayleigh-distribution] distribution with scale 
-parameter `sigma`.
+Returns the [median][median] of a [Rayleigh][rayleigh-distribution] distribution with scale parameter `sigma`.
 
 ```javascript
 var y = median( 9.0 );
@@ -119,6 +118,98 @@ for ( i = 0; i < 10; i++ ) {
 
 <!-- /.examples -->
 
+<!-- C interface documentation. -->
+
+* * *
+
+<section class="c">
+
+## C APIs
+
+<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<!-- C usage documentation. -->
+
+<section class="usage">
+
+### Usage
+
+```c
+#include "stdlib/stats/base/dists/rayleigh/median.h"
+```
+
+#### stdlib_base_dists_rayleigh_median( sigma )
+
+Returns the [median][median] of a [Rayleigh][rayleigh-distribution] distribution with scale parameter `sigma`.
+
+```c
+double out = stdlib_base_dists_rayleigh_median( 9.0 );
+// returns ~10.595
+```
+
+The function accepts the following arguments:
+
+-   **sigma**: `[in] double` scale parameter.
+
+```c
+double stdlib_base_dists_rayleigh_median( const double sigma );
+```
+
+</section>
+
+<!-- /.usage -->
+
+<!-- C API usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="notes">
+
+</section>
+
+<!-- /.notes -->
+
+<!-- C API usage examples. -->
+
+<section class="examples">
+
+### Examples
+
+```c
+#include "stdlib/stats/base/dists/rayleigh/median.h"
+#include <stdlib.h>
+#include <stdio.h>
+
+static double random_uniform( const double min, const double max ) {
+    double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
+    return min + ( v*(max-min) );
+}
+
+int main( void ) {
+    double sigma;
+    double y;
+    int i;
+
+    for ( i = 0; i < 25; i++ ) {
+        sigma = random_uniform( 0.0, 20.0 );
+        y = stdlib_base_dists_rayleigh_median( sigma );
+        printf( "σ: %lf, Median(X;σ): %lf\n", sigma, y );
+    }
+}
+```
+
+</section>
+
+<!-- /.examples -->
+
+</section>
+
+<!-- /.c -->
+
 <!-- Section to include cited references. If references are included, add a horizontal rule *before* the section. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
 
 <section class="references">
diff --git a/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/benchmark/benchmark.js
index d4301399c8a4..49af404e2d80 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/benchmark/benchmark.js
+++ b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/benchmark/benchmark.js
@@ -21,6 +21,7 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
+var Float64Array = require( '@stdlib/array/float64' );
 var randu = require( '@stdlib/random/base/randu' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var EPS = require( '@stdlib/constants/float64/eps' );
@@ -32,13 +33,19 @@ var median = require( './../lib' );
 
 bench( pkg, function benchmark( b ) {
 	var sigma;
+	var len;
 	var y;
 	var i;
 
+	len = 100;
+	sigma = new Float64Array( len );
+	for ( i = 0; i < len; i++ ) {
+		sigma[ i ] = ( randu() * 20.0 ) + EPS;
+	}
+
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		sigma = ( randu()*20.0 ) + EPS;
-		y = median( sigma );
+		y = median( sigma[ i % len ] );
 		if ( isnan( y ) ) {
 			b.fail( 'should not return NaN' );
 		}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/benchmark/benchmark.native.js
new file mode 100644
index 000000000000..b65c5add32cd
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/benchmark/benchmark.native.js
@@ -0,0 +1,68 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var resolve = require( 'path' ).resolve;
+var bench = require( '@stdlib/bench' );
+var Float64Array = require( '@stdlib/array/float64' );
+var tryRequire = require( '@stdlib/utils/try-require' );
+var randu = require( '@stdlib/random/base/randu' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var EPS = require( '@stdlib/constants/float64/eps' );
+var pkg = require( './../package.json' ).name;
+
+
+// VARIABLES //
+
+var median = tryRequire( resolve( __dirname, './../lib/native.js' ) );
+var opts = {
+	'skip': ( median instanceof Error )
+};
+
+
+// MAIN //
+
+bench( pkg+'::native', opts, function benchmark( b ) {
+	var sigma;
+	var len;
+	var y;
+	var i;
+
+	len = 100;
+	sigma = new Float64Array( len );
+	for ( i = 0; i < len; i++ ) {
+		sigma[ i ] = ( randu() * 20.0 ) + EPS;
+	}
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		y = median( sigma[ i % len ] );
+		if ( isnan( y ) ) {
+			b.fail( 'should not return NaN' );
+		}
+	}
+	b.toc();
+	if ( isnan( y ) ) {
+		b.fail( 'should not return NaN' );
+	}
+	b.pass( 'benchmark finished' );
+	b.end();
+});
diff --git a/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/benchmark/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/benchmark/c/Makefile
new file mode 100644
index 000000000000..a4bd7b38fd74
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/benchmark/c/Makefile
@@ -0,0 +1,146 @@
+#/
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#/
+
+# VARIABLES #
+
+ifndef VERBOSE
+	QUIET := @
+else
+	QUIET :=
+endif
+
+# Determine the OS ([1][1], [2][2]).
+#
+# [1]: https://en.wikipedia.org/wiki/Uname#Examples
+# [2]: http://stackoverflow.com/a/27776822/2225624
+OS ?= $(shell uname)
+ifneq (, $(findstring MINGW,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring MSYS,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring CYGWIN,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring Windows_NT,$(OS)))
+	OS := WINNT
+endif
+endif
+endif
+endif
+
+# Define the program used for compiling C source files:
+ifdef C_COMPILER
+	CC := $(C_COMPILER)
+else
+	CC := gcc
+endif
+
+# Define the command-line options when compiling C files:
+CFLAGS ?= \
+	-std=c99 \
+	-O3 \
+	-Wall \
+	-pedantic
+
+# Determine whether to generate position independent code ([1][1], [2][2]).
+#
+# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options
+# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option
+ifeq ($(OS), WINNT)
+	fPIC ?=
+else
+	fPIC ?= -fPIC
+endif
+
+# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`):
+INCLUDE ?=
+
+# List of source files:
+SOURCE_FILES ?=
+
+# List of libraries (e.g., `-lopenblas -lpthread`):
+LIBRARIES ?=
+
+# List of library paths (e.g., `-L /foo/bar -L /beep/boop`):
+LIBPATH ?=
+
+# List of C targets:
+c_targets := benchmark.out
+
+
+# RULES #
+
+#/
+# Compiles source files.
+#
+# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`)
+# @param {string} [CFLAGS] - C compiler options
+# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`)
+# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`)
+# @param {string} [SOURCE_FILES] - list of source files
+# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`)
+# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`)
+#
+# @example
+# make
+#
+# @example
+# make all
+#/
+all: $(c_targets)
+
+.PHONY: all
+
+#/
+# Compiles C source files.
+#
+# @private
+# @param {string} CC - C compiler (e.g., `gcc`)
+# @param {string} CFLAGS - C compiler options
+# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`)
+# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`)
+# @param {string} SOURCE_FILES - list of source files
+# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`)
+# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`)
+#/
+$(c_targets): %.out: %.c
+	$(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES)
+
+#/
+# Runs compiled benchmarks.
+#
+# @example
+# make run
+#/
+run: $(c_targets)
+	$(QUIET) ./$<
+
+.PHONY: run
+
+#/
+# Removes generated files.
+#
+# @example
+# make clean
+#/
+clean:
+	$(QUIET) -rm -f *.o *.out
+
+.PHONY: clean
diff --git a/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/benchmark/c/benchmark.c b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/benchmark/c/benchmark.c
new file mode 100644
index 000000000000..aeaabda65d2c
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/benchmark/c/benchmark.c
@@ -0,0 +1,139 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/dists/rayleigh/median.h"
+#include "stdlib/constants/float64/eps.h"
+#include <stdlib.h>
+#include <stdio.h>
+#include <math.h>
+#include <time.h>
+#include <sys/time.h>
+
+#define NAME "rayleigh-median"
+#define ITERATIONS 1000000
+#define REPEATS 3
+
+/**
+* Prints the TAP version.
+*/
+static void print_version( void ) {
+	printf( "TAP version 13\n" );
+}
+
+/**
+* Prints the TAP summary.
+*
+* @param total     total number of tests
+* @param passing   total number of passing tests
+*/
+static void print_summary( int total, int passing ) {
+	printf( "#\n" );
+	printf( "1..%d\n", total ); // TAP plan
+	printf( "# total %d\n", total );
+	printf( "# pass  %d\n", passing );
+	printf( "#\n" );
+	printf( "# ok\n" );
+}
+
+/**
+* Prints benchmarks results.
+*
+* @param elapsed   elapsed time in seconds
+*/
+static void print_results( double elapsed ) {
+	double rate = (double)ITERATIONS / elapsed;
+	printf( "  ---\n" );
+	printf( "  iterations: %d\n", ITERATIONS );
+	printf( "  elapsed: %0.9f\n", elapsed );
+	printf( "  rate: %0.9f\n", rate );
+	printf( "  ...\n" );
+}
+
+/**
+* Returns a clock time.
+*
+* @return clock time
+*/
+static double tic( void ) {
+	struct timeval now;
+	gettimeofday( &now, NULL );
+	return (double)now.tv_sec + (double)now.tv_usec/1.0e6;
+}
+
+/**
+* Generates a random number on the interval [min,max).
+*
+* @param min    minimum value (inclusive)
+* @param max    maximum value (exclusive)
+* @return       random number
+*/
+static double random_uniform( const double min, const double max ) {
+	double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
+	return min + ( v*(max-min) );
+}
+
+/**
+* Runs a benchmark.
+*
+* @return elapsed time in seconds
+*/
+static double benchmark( void ) {
+	double elapsed;
+	double sigma[ 100 ];
+	double y;
+	double t;
+	int i;
+
+	for ( i = 0; i < 100; i++ ) {
+		sigma[ i ] = random_uniform( 0.0, 20.0 ) + STDLIB_CONSTANT_FLOAT64_EPS;
+	}
+
+	t = tic();
+	for ( i = 0; i < ITERATIONS; i++ ) {
+		y = stdlib_base_dists_rayleigh_median( sigma[ i % 100 ] );
+		if ( y != y ) {
+			printf( "should not return NaN\n" );
+			break;
+		}
+	}
+	elapsed = tic() - t;
+	if ( y != y ) {
+		printf( "should not return NaN\n" );
+	}
+	return elapsed;
+}
+
+/**
+* Main execution sequence.
+*/
+int main( void ) {
+	double elapsed;
+	int i;
+
+	// Use the current time to seed the random number generator:
+	srand( time( NULL ) );
+
+	print_version();
+	for ( i = 0; i < REPEATS; i++ ) {
+		printf( "# c::%s\n", NAME );
+		elapsed = benchmark();
+		print_results( elapsed );
+		printf( "ok %d benchmark finished\n", i+1 );
+	}
+	print_summary( REPEATS, REPEATS );
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/binding.gyp b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/binding.gyp
new file mode 100644
index 000000000000..68a1ca11d160
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/binding.gyp
@@ -0,0 +1,170 @@
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# A `.gyp` file for building a Node.js native add-on.
+#
+# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md
+# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md
+{
+  # List of files to include in this file:
+  'includes': [
+    './include.gypi',
+  ],
+
+  # Define variables to be used throughout the configuration for all targets:
+  'variables': {
+    # Target name should match the add-on export name:
+    'addon_target_name%': 'addon',
+
+    # Set variables based on the host OS:
+    'conditions': [
+      [
+        'OS=="win"',
+        {
+          # Define the object file suffix:
+          'obj': 'obj',
+        },
+        {
+          # Define the object file suffix:
+          'obj': 'o',
+        }
+      ], # end condition (OS=="win")
+    ], # end conditions
+  }, # end variables
+
+  # Define compile targets:
+  'targets': [
+
+    # Target to generate an add-on:
+    {
+      # The target name should match the add-on export name:
+      'target_name': '<(addon_target_name)',
+
+      # Define dependencies:
+      'dependencies': [],
+
+      # Define directories which contain relevant include headers:
+      'include_dirs': [
+        # Local include directory:
+        '<@(include_dirs)',
+      ],
+
+      # List of source files:
+      'sources': [
+        '<@(src_files)',
+      ],
+
+      # Settings which should be applied when a target's object files are used as linker input:
+      'link_settings': {
+        # Define libraries:
+        'libraries': [
+          '<@(libraries)',
+        ],
+
+        # Define library directories:
+        'library_dirs': [
+          '<@(library_dirs)',
+        ],
+      },
+
+      # C/C++ compiler flags:
+      'cflags': [
+        # Enable commonly used warning options:
+        '-Wall',
+
+        # Aggressive optimization:
+        '-O3',
+      ],
+
+      # C specific compiler flags:
+      'cflags_c': [
+        # Specify the C standard to which a program is expected to conform:
+        '-std=c99',
+      ],
+
+      # C++ specific compiler flags:
+      'cflags_cpp': [
+        # Specify the C++ standard to which a program is expected to conform:
+        '-std=c++11',
+      ],
+
+      # Linker flags:
+      'ldflags': [],
+
+      # Apply conditions based on the host OS:
+      'conditions': [
+        [
+          'OS=="mac"',
+          {
+            # Linker flags:
+            'ldflags': [
+              '-undefined dynamic_lookup',
+              '-Wl,-no-pie',
+              '-Wl,-search_paths_first',
+            ],
+          },
+        ], # end condition (OS=="mac")
+        [
+          'OS!="win"',
+          {
+            # C/C++ flags:
+            'cflags': [
+              # Generate platform-independent code:
+              '-fPIC',
+            ],
+          },
+        ], # end condition (OS!="win")
+      ], # end conditions
+    }, # end target <(addon_target_name)
+
+    # Target to copy a generated add-on to a standard location:
+    {
+      'target_name': 'copy_addon',
+
+      # Declare that the output of this target is not linked:
+      'type': 'none',
+
+      # Define dependencies:
+      'dependencies': [
+        # Require that the add-on be generated before building this target:
+        '<(addon_target_name)',
+      ],
+
+      # Define a list of actions:
+      'actions': [
+        {
+          'action_name': 'copy_addon',
+          'message': 'Copying addon...',
+
+          # Explicitly list the inputs in the command-line invocation below:
+          'inputs': [],
+
+          # Declare the expected outputs:
+          'outputs': [
+            '<(addon_output_dir)/<(addon_target_name).node',
+          ],
+
+          # Define the command-line invocation:
+          'action': [
+            'cp',
+            '<(PRODUCT_DIR)/<(addon_target_name).node',
+            '<(addon_output_dir)/<(addon_target_name).node',
+          ],
+        },
+      ], # end actions
+    }, # end target copy_addon
+  ], # end targets
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/examples/c/Makefile b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/examples/c/Makefile
new file mode 100644
index 000000000000..25ced822f96a
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/examples/c/Makefile
@@ -0,0 +1,146 @@
+#/
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#/
+
+# VARIABLES #
+
+ifndef VERBOSE
+	QUIET := @
+else
+	QUIET :=
+endif
+
+# Determine the OS ([1][1], [2][2]).
+#
+# [1]: https://en.wikipedia.org/wiki/Uname#Examples
+# [2]: http://stackoverflow.com/a/27776822/2225624
+OS ?= $(shell uname)
+ifneq (, $(findstring MINGW,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring MSYS,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring CYGWIN,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring Windows_NT,$(OS)))
+	OS := WINNT
+endif
+endif
+endif
+endif
+
+# Define the program used for compiling C source files:
+ifdef C_COMPILER
+	CC := $(C_COMPILER)
+else
+	CC := gcc
+endif
+
+# Define the command-line options when compiling C files:
+CFLAGS ?= \
+	-std=c99 \
+	-O3 \
+	-Wall \
+	-pedantic
+
+# Determine whether to generate position independent code ([1][1], [2][2]).
+#
+# [1]: https://gcc.gnu.org/onlinedocs/gcc/Code-Gen-Options.html#Code-Gen-Options
+# [2]: http://stackoverflow.com/questions/5311515/gcc-fpic-option
+ifeq ($(OS), WINNT)
+	fPIC ?=
+else
+	fPIC ?= -fPIC
+endif
+
+# List of includes (e.g., `-I /foo/bar -I /beep/boop/include`):
+INCLUDE ?=
+
+# List of source files:
+SOURCE_FILES ?=
+
+# List of libraries (e.g., `-lopenblas -lpthread`):
+LIBRARIES ?=
+
+# List of library paths (e.g., `-L /foo/bar -L /beep/boop`):
+LIBPATH ?=
+
+# List of C targets:
+c_targets := example.out
+
+
+# RULES #
+
+#/
+# Compiles source files.
+#
+# @param {string} [C_COMPILER] - C compiler (e.g., `gcc`)
+# @param {string} [CFLAGS] - C compiler options
+# @param {(string|void)} [fPIC] - compiler flag determining whether to generate position independent code (e.g., `-fPIC`)
+# @param {string} [INCLUDE] - list of includes (e.g., `-I /foo/bar -I /beep/boop/include`)
+# @param {string} [SOURCE_FILES] - list of source files
+# @param {string} [LIBPATH] - list of library paths (e.g., `-L /foo/bar -L /beep/boop`)
+# @param {string} [LIBRARIES] - list of libraries (e.g., `-lopenblas -lpthread`)
+#
+# @example
+# make
+#
+# @example
+# make all
+#/
+all: $(c_targets)
+
+.PHONY: all
+
+#/
+# Compiles C source files.
+#
+# @private
+# @param {string} CC - C compiler (e.g., `gcc`)
+# @param {string} CFLAGS - C compiler options
+# @param {(string|void)} fPIC - compiler flag determining whether to generate position independent code (e.g., `-fPIC`)
+# @param {string} INCLUDE - list of includes (e.g., `-I /foo/bar`)
+# @param {string} SOURCE_FILES - list of source files
+# @param {string} LIBPATH - list of library paths (e.g., `-L /foo/bar`)
+# @param {string} LIBRARIES - list of libraries (e.g., `-lopenblas`)
+#/
+$(c_targets): %.out: %.c
+	$(QUIET) $(CC) $(CFLAGS) $(fPIC) $(INCLUDE) -o $@ $(SOURCE_FILES) $< $(LIBPATH) -lm $(LIBRARIES)
+
+#/
+# Runs compiled examples.
+#
+# @example
+# make run
+#/
+run: $(c_targets)
+	$(QUIET) ./$<
+
+.PHONY: run
+
+#/
+# Removes generated files.
+#
+# @example
+# make clean
+#/
+clean:
+	$(QUIET) -rm -f *.o *.out
+
+.PHONY: clean
diff --git a/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/examples/c/example.c
new file mode 100644
index 000000000000..9829c1e36bf6
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/examples/c/example.c
@@ -0,0 +1,38 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/dists/rayleigh/median.h"
+#include <stdlib.h>
+#include <stdio.h>
+
+static double random_uniform( const double min, const double max ) {
+	double v = (double)rand() / ( (double)RAND_MAX + 1.0 );
+	return min + ( v*(max-min) );
+}
+
+int main( void ) {
+	double sigma;
+	double y;
+	int i;
+
+	for ( i = 0; i < 25; i++ ) {
+		sigma = random_uniform( 0.0, 20.0 );
+		y = stdlib_base_dists_rayleigh_median( sigma );
+		printf( "σ: %lf, Median(X;σ): %lf\n", sigma, y );
+	}
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/include.gypi b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/include.gypi
new file mode 100644
index 000000000000..ecfaf82a3279
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/include.gypi
@@ -0,0 +1,53 @@
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# A GYP include file for building a Node.js native add-on.
+#
+# Main documentation:
+#
+# [1]: https://gyp.gsrc.io/docs/InputFormatReference.md
+# [2]: https://gyp.gsrc.io/docs/UserDocumentation.md
+{
+  # Define variables to be used throughout the configuration for all targets:
+  'variables': {
+    # Source directory:
+    'src_dir': './src',
+
+    # Include directories:
+    'include_dirs': [
+      '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).include; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
+    ],
+
+    # Add-on destination directory:
+    'addon_output_dir': './src',
+
+    # Source files:
+    'src_files': [
+      '<(src_dir)/addon.c',
+      '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).src; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
+    ],
+
+    # Library dependencies:
+    'libraries': [
+      '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).libraries; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
+    ],
+
+    # Library directories:
+    'library_dirs': [
+      '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).libpath; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
+    ],
+  }, # end variables
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/include/stdlib/stats/base/dists/rayleigh/median.h b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/include/stdlib/stats/base/dists/rayleigh/median.h
new file mode 100644
index 000000000000..56c224c425d2
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/include/stdlib/stats/base/dists/rayleigh/median.h
@@ -0,0 +1,38 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#ifndef STDLIB_STATS_BASE_DISTS_RAYLEIGH_MEDIAN_H
+#define STDLIB_STATS_BASE_DISTS_RAYLEIGH_MEDIAN_H
+
+/*
+* If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler.
+*/
+#ifdef __cplusplus
+extern "C" {
+#endif
+
+/**
+* Returns the median of a Rayleigh distribution.
+*/
+double stdlib_base_dists_rayleigh_median( const double sigma );
+
+#ifdef __cplusplus
+}
+#endif
+
+#endif // !STDLIB_STATS_BASE_DISTS_RAYLEIGH_MEDIAN_H
diff --git a/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/lib/native.js b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/lib/native.js
new file mode 100644
index 000000000000..1bd85ca8f168
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/lib/native.js
@@ -0,0 +1,58 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var addon = require( './../src/addon.node' );
+
+
+// MAIN //
+
+/**
+* Returns the median of a Rayleigh distribution.
+*
+* @private
+* @param {NonNegativeNumber} sigma - scale parameter
+* @returns {NonNegativeNumber} median
+*
+* @example
+* var v = median( 9.0 );
+* // returns ~10.597
+*
+* @example
+* var v = median( 2.0 );
+* // returns ~2.355
+*
+* @example
+* var v = median( -0.2 );
+* // returns NaN
+*
+* @example
+* var v = median( NaN );
+* // returns NaN
+*/
+function median( sigma ) {
+	return addon( sigma );
+}
+
+
+// EXPORTS //
+
+module.exports = median;
diff --git a/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/manifest.json b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/manifest.json
new file mode 100644
index 000000000000..b1717d6b3d58
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/manifest.json
@@ -0,0 +1,83 @@
+{
+  "options": {
+    "task": "build",
+    "wasm": false
+  },
+  "fields": [
+    {
+      "field": "src",
+      "resolve": true,
+      "relative": true
+    },
+    {
+      "field": "include",
+      "resolve": true,
+      "relative": true
+    },
+    {
+      "field": "libraries",
+      "resolve": false,
+      "relative": false
+    },
+    {
+      "field": "libpath",
+      "resolve": true,
+      "relative": false
+    }
+  ],
+  "confs": [
+    {
+      "task": "build",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/math/base/napi/unary",
+        "@stdlib/math/base/assert/is-nan",
+        "@stdlib/constants/float64/ln-two",
+        "@stdlib/math/base/special/sqrt"
+      ]
+    },
+    {
+      "task": "benchmark",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/math/base/assert/is-nan",
+        "@stdlib/constants/float64/ln-two",
+        "@stdlib/constants/float64/eps",
+        "@stdlib/math/base/special/sqrt"
+      ]
+    },
+    {
+      "task": "examples",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/math/base/assert/is-nan",
+        "@stdlib/constants/float64/ln-two",
+        "@stdlib/math/base/special/sqrt"
+      ]
+    }
+  ]
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/package.json b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/package.json
index a84b1ae7073c..be394b09f8e6 100644
--- a/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/package.json
+++ b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/package.json
@@ -14,11 +14,14 @@
     }
   ],
   "main": "./lib",
+  "gypfile": true,
   "directories": {
     "benchmark": "./benchmark",
     "doc": "./docs",
     "example": "./examples",
+    "include": "./include",
     "lib": "./lib",
+    "src": "./src",
     "test": "./test"
   },
   "types": "./docs/types",
diff --git a/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/src/Makefile b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/src/Makefile
new file mode 100644
index 000000000000..7733b6180cb4
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/src/Makefile
@@ -0,0 +1,70 @@
+#/
+# @license Apache-2.0
+#
+# Copyright (c) 2025 The Stdlib Authors.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+#/
+
+# VARIABLES #
+
+ifndef VERBOSE
+	QUIET := @
+else
+	QUIET :=
+endif
+
+# Determine the OS ([1][1], [2][2]).
+#
+# [1]: https://en.wikipedia.org/wiki/Uname#Examples
+# [2]: http://stackoverflow.com/a/27776822/2225624
+OS ?= $(shell uname)
+ifneq (, $(findstring MINGW,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring MSYS,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring CYGWIN,$(OS)))
+	OS := WINNT
+else
+ifneq (, $(findstring Windows_NT,$(OS)))
+	OS := WINNT
+endif
+endif
+endif
+endif
+
+
+# RULES #
+
+#/
+# Removes generated files for building an add-on.
+#
+# @example
+# make clean-addon
+#/
+clean-addon:
+	$(QUIET) -rm -f *.o *.node
+
+.PHONY: clean-addon
+
+#/
+# Removes generated files.
+#
+# @example
+# make clean
+#/
+clean: clean-addon
+
+.PHONY: clean
diff --git a/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/src/addon.c b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/src/addon.c
new file mode 100644
index 000000000000..f1f06e3c1781
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/src/addon.c
@@ -0,0 +1,23 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/dists/rayleigh/median.h"
+#include "stdlib/math/base/napi/unary.h"
+
+// cppcheck-suppress shadowFunction
+STDLIB_MATH_BASE_NAPI_MODULE_D_D( stdlib_base_dists_rayleigh_median )
diff --git a/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/src/main.c b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/src/main.c
new file mode 100644
index 000000000000..750f996b1edc
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/src/main.c
@@ -0,0 +1,39 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/dists/rayleigh/median.h"
+#include "stdlib/math/base/assert/is_nan.h"
+#include "stdlib/math/base/special/sqrt.h"
+#include "stdlib/constants/float64/ln_two.h"
+
+/**
+* Returns the median of a Rayleigh distribution.
+*
+* @param sigma    scale parameter
+* @return         median
+*
+* @example
+* double y = stdlib_base_dists_rayleigh_median( 9.0 );
+* // returns ~10.595
+*/
+double stdlib_base_dists_rayleigh_median( const double sigma ) {
+	if ( stdlib_base_is_nan( sigma ) || sigma < 0 ) {
+		return 0.0 / 0.0; // NaN
+	}
+	return sigma * stdlib_base_sqrt( 2.0 * STDLIB_CONSTANT_FLOAT64_LN2 );
+}
diff --git a/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/test/test.native.js b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/test/test.native.js
new file mode 100644
index 000000000000..91d43670c030
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/dists/rayleigh/median/test/test.native.js
@@ -0,0 +1,92 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var resolve = require( 'path' ).resolve;
+var tape = require( 'tape' );
+var tryRequire = require( '@stdlib/utils/try-require' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var abs = require( '@stdlib/math/base/special/abs' );
+var NINF = require( '@stdlib/constants/float64/ninf' );
+var EPS = require( '@stdlib/constants/float64/eps' );
+
+
+// VARIABLES //
+
+var median = tryRequire( resolve( __dirname, './../lib/native.js' ) );
+var opts = {
+	'skip': ( median instanceof Error )
+};
+
+
+// FIXTURES //
+
+var data = require( './fixtures/julia/data.json' );
+
+
+// TESTS //
+
+tape( 'main export is a function', opts, function test( t ) {
+	t.ok( true, __filename );
+	t.strictEqual( typeof median, 'function', 'main export is a function' );
+	t.end();
+});
+
+tape( 'if provided `NaN` for `sigma`, the function returns `NaN`', opts, function test( t ) {
+	var result = median( NaN );
+	t.equal( isnan( result ), true, 'returns NaN' );
+	t.end();
+});
+
+tape( 'if provided a scale `sigma` that is not a nonnegative number, the function returns `NaN`', opts, function test( t ) {
+	var result;
+
+	result = median( -1.0 );
+	t.equal( isnan( result ), true, 'returns NaN' );
+
+	result = median( NINF );
+	t.equal( isnan( result ), true, 'returns NaN' );
+
+	t.end();
+});
+
+tape( 'the function returns the median of a Rayleigh distribution', opts, function test( t ) {
+	var expected;
+	var delta;
+	var sigma;
+	var tol;
+	var i;
+	var y;
+
+	expected = data.expected;
+	sigma = data.sigma;
+	for ( i = 0; i < expected.length; i++ ) {
+		y = median( sigma[i] );
+		if ( y === expected[i] ) {
+			t.equal( y, expected[i], 'sigma: '+sigma[i]+', y: '+y+', expected: '+expected[i] );
+		} else {
+			delta = abs( y - expected[ i ] );
+			tol = 1.0 * EPS * abs( expected[ i ] );
+			t.ok( delta <= tol, 'within tolerance. sigma: '+sigma[i]+'. y: '+y+'. E: '+expected[ i ]+'. Δ: '+delta+'. tol: '+tol+'.' );
+		}
+	}
+	t.end();
+});

From 1c1a28204d476c724fb9d4c69cfd6da42a915582 Mon Sep 17 00:00:00 2001
From: stdlib-bot <82920195+stdlib-bot@users.noreply.github.com>
Date: Thu, 2 Jan 2025 19:35:09 -0800
Subject: [PATCH 59/87] docs: update namespace table of contents

PR-URL: https://github.com/stdlib-js/stdlib/pull/4489

Reviewed-by: Philipp Burckhardt <pburckhardt@outlook.com>
Signed-off-by: stdlib-bot <82920195+stdlib-bot@users.noreply.github.com>
---
 lib/node_modules/@stdlib/blas/ext/base/README.md |  4 ++--
 lib/node_modules/@stdlib/stats/base/README.md    | 10 +++++-----
 2 files changed, 7 insertions(+), 7 deletions(-)

diff --git a/lib/node_modules/@stdlib/blas/ext/base/README.md b/lib/node_modules/@stdlib/blas/ext/base/README.md
index 3d13ca4e0660..93833964c9e6 100644
--- a/lib/node_modules/@stdlib/blas/ext/base/README.md
+++ b/lib/node_modules/@stdlib/blas/ext/base/README.md
@@ -86,12 +86,12 @@ var ns = extblas;
 -   <span class="signature">[`dssumpw( N, x, strideX )`][@stdlib/blas/ext/base/dssumpw]</span><span class="delimiter">: </span><span class="description">calculate the sum of single-precision floating-point strided array elements using pairwise summation with extended accumulation and returning an extended precision result.</span>
 -   <span class="signature">[`dsum( N, x, strideX )`][@stdlib/blas/ext/base/dsum]</span><span class="delimiter">: </span><span class="description">calculate the sum of double-precision floating-point strided array elements.</span>
 -   <span class="signature">[`dsumkbn( N, x, strideX )`][@stdlib/blas/ext/base/dsumkbn]</span><span class="delimiter">: </span><span class="description">calculate the sum of double-precision floating-point strided array elements using an improved Kahan–Babuška algorithm.</span>
--   <span class="signature">[`dsumkbn2( N, x, stride )`][@stdlib/blas/ext/base/dsumkbn2]</span><span class="delimiter">: </span><span class="description">calculate the sum of double-precision floating-point strided array elements using a second-order iterative Kahan–Babuška algorithm.</span>
+-   <span class="signature">[`dsumkbn2( N, x, strideX )`][@stdlib/blas/ext/base/dsumkbn2]</span><span class="delimiter">: </span><span class="description">calculate the sum of double-precision floating-point strided array elements using a second-order iterative Kahan–Babuška algorithm.</span>
 -   <span class="signature">[`dsumors( N, x, stride )`][@stdlib/blas/ext/base/dsumors]</span><span class="delimiter">: </span><span class="description">calculate the sum of double-precision floating-point strided array elements using ordinary recursive summation.</span>
 -   <span class="signature">[`dsumpw( N, x, stride )`][@stdlib/blas/ext/base/dsumpw]</span><span class="delimiter">: </span><span class="description">calculate the sum of double-precision floating-point strided array elements using pairwise summation.</span>
 -   <span class="signature">[`gapx( N, alpha, x, stride )`][@stdlib/blas/ext/base/gapx]</span><span class="delimiter">: </span><span class="description">add a constant to each element in a strided array.</span>
 -   <span class="signature">[`gapxsum( N, alpha, x, stride )`][@stdlib/blas/ext/base/gapxsum]</span><span class="delimiter">: </span><span class="description">add a constant to each strided array element and compute the sum.</span>
--   <span class="signature">[`gapxsumkbn( N, alpha, x, stride )`][@stdlib/blas/ext/base/gapxsumkbn]</span><span class="delimiter">: </span><span class="description">add a constant to each strided array element and compute the sum using an improved Kahan–Babuška algorithm.</span>
+-   <span class="signature">[`gapxsumkbn( N, alpha, x, strideX )`][@stdlib/blas/ext/base/gapxsumkbn]</span><span class="delimiter">: </span><span class="description">add a scalar constant to each strided array element and compute the sum using an improved Kahan–Babuška algorithm.</span>
 -   <span class="signature">[`gapxsumkbn2( N, alpha, x, stride )`][@stdlib/blas/ext/base/gapxsumkbn2]</span><span class="delimiter">: </span><span class="description">add a constant to each strided array element and compute the sum using a second-order iterative Kahan–Babuška algorithm.</span>
 -   <span class="signature">[`gapxsumors( N, alpha, x, stride )`][@stdlib/blas/ext/base/gapxsumors]</span><span class="delimiter">: </span><span class="description">add a constant to each strided array element and compute the sum using ordinary recursive summation.</span>
 -   <span class="signature">[`gapxsumpw( N, alpha, x, stride )`][@stdlib/blas/ext/base/gapxsumpw]</span><span class="delimiter">: </span><span class="description">add a constant to each strided array element and compute the sum using pairwise summation.</span>
diff --git a/lib/node_modules/@stdlib/stats/base/README.md b/lib/node_modules/@stdlib/stats/base/README.md
index a885eb9f0a1b..b0fb0ebfb3f8 100644
--- a/lib/node_modules/@stdlib/stats/base/README.md
+++ b/lib/node_modules/@stdlib/stats/base/README.md
@@ -67,8 +67,8 @@ The namespace contains the following statistical functions:
 -   <span class="signature">[`dcuminabs( N, x, strideX, y, strideY )`][@stdlib/stats/base/dcuminabs]</span><span class="delimiter">: </span><span class="description">calculate the cumulative minimum absolute value of double-precision floating-point strided array elements.</span>
 -   <span class="signature">[`dmax( N, x, strideX )`][@stdlib/stats/base/dmax]</span><span class="delimiter">: </span><span class="description">calculate the maximum value of a double-precision floating-point strided array.</span>
 -   <span class="signature">[`dmaxabs( N, x, strideX )`][@stdlib/stats/base/dmaxabs]</span><span class="delimiter">: </span><span class="description">calculate the maximum absolute value of a double-precision floating-point strided array.</span>
--   <span class="signature">[`dmaxabssorted( N, x, stride )`][@stdlib/stats/base/dmaxabssorted]</span><span class="delimiter">: </span><span class="description">calculate the maximum absolute value of a sorted double-precision floating-point strided array.</span>
--   <span class="signature">[`dmaxsorted( N, x, stride )`][@stdlib/stats/base/dmaxsorted]</span><span class="delimiter">: </span><span class="description">calculate the maximum value of a sorted double-precision floating-point strided array.</span>
+-   <span class="signature">[`dmaxabssorted( N, x, strideX )`][@stdlib/stats/base/dmaxabssorted]</span><span class="delimiter">: </span><span class="description">calculate the maximum absolute value of a sorted double-precision floating-point strided array.</span>
+-   <span class="signature">[`dmaxsorted( N, x, strideX )`][@stdlib/stats/base/dmaxsorted]</span><span class="delimiter">: </span><span class="description">calculate the maximum value of a sorted double-precision floating-point strided array.</span>
 -   <span class="signature">[`dmean( N, x, stride )`][@stdlib/stats/base/dmean]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array.</span>
 -   <span class="signature">[`dmeankbn( N, x, stride )`][@stdlib/stats/base/dmeankbn]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array using an improved Kahan–Babuška algorithm.</span>
 -   <span class="signature">[`dmeankbn2( N, x, stride )`][@stdlib/stats/base/dmeankbn2]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array using a second-order iterative Kahan–Babuška algorithm.</span>
@@ -82,11 +82,11 @@ The namespace contains the following statistical functions:
 -   <span class="signature">[`dmeanvar( N, correction, x, strideX, out, strideOut )`][@stdlib/stats/base/dmeanvar]</span><span class="delimiter">: </span><span class="description">calculate the mean and variance of a double-precision floating-point strided array.</span>
 -   <span class="signature">[`dmeanvarpn( N, correction, x, strideX, out, strideOut )`][@stdlib/stats/base/dmeanvarpn]</span><span class="delimiter">: </span><span class="description">calculate the mean and variance of a double-precision floating-point strided array using a two-pass algorithm.</span>
 -   <span class="signature">[`dmeanwd( N, x, stride )`][@stdlib/stats/base/dmeanwd]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array using Welford's algorithm.</span>
--   <span class="signature">[`dmediansorted( N, x, stride )`][@stdlib/stats/base/dmediansorted]</span><span class="delimiter">: </span><span class="description">calculate the median value of a sorted double-precision floating-point strided array.</span>
+-   <span class="signature">[`dmediansorted( N, x, strideX )`][@stdlib/stats/base/dmediansorted]</span><span class="delimiter">: </span><span class="description">calculate the median value of a sorted double-precision floating-point strided array.</span>
 -   <span class="signature">[`dmidrange( N, x, strideX )`][@stdlib/stats/base/dmidrange]</span><span class="delimiter">: </span><span class="description">calculate the mid-range of a double-precision floating-point strided array.</span>
 -   <span class="signature">[`dmin( N, x, strideX )`][@stdlib/stats/base/dmin]</span><span class="delimiter">: </span><span class="description">calculate the minimum value of a double-precision floating-point strided array.</span>
 -   <span class="signature">[`dminabs( N, x, strideX )`][@stdlib/stats/base/dminabs]</span><span class="delimiter">: </span><span class="description">calculate the minimum absolute value of a double-precision floating-point strided array.</span>
--   <span class="signature">[`dminsorted( N, x, stride )`][@stdlib/stats/base/dminsorted]</span><span class="delimiter">: </span><span class="description">calculate the minimum value of a sorted double-precision floating-point strided array.</span>
+-   <span class="signature">[`dminsorted( N, x, strideX )`][@stdlib/stats/base/dminsorted]</span><span class="delimiter">: </span><span class="description">calculate the minimum value of a sorted double-precision floating-point strided array.</span>
 -   <span class="signature">[`dmskmax( N, x, strideX, mask, strideMask )`][@stdlib/stats/base/dmskmax]</span><span class="delimiter">: </span><span class="description">calculate the maximum value of a double-precision floating-point strided array according to a mask.</span>
 -   <span class="signature">[`dmskmin( N, x, strideX, mask, strideMask )`][@stdlib/stats/base/dmskmin]</span><span class="delimiter">: </span><span class="description">calculate the minimum value of a double-precision floating-point strided array according to a mask.</span>
 -   <span class="signature">[`dmskrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/base/dmskrange]</span><span class="delimiter">: </span><span class="description">calculate the range of a double-precision floating-point strided array according to a mask.</span>
@@ -206,7 +206,7 @@ The namespace contains the following statistical functions:
 -   <span class="signature">[`sdsnanmeanors( N, x, stride )`][@stdlib/stats/base/sdsnanmeanors]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array, ignoring `NaN` values and using ordinary recursive summation with extended accumulation.</span>
 -   <span class="signature">[`smax( N, x, strideX )`][@stdlib/stats/base/smax]</span><span class="delimiter">: </span><span class="description">calculate the maximum value of a single-precision floating-point strided array.</span>
 -   <span class="signature">[`smaxabs( N, x, strideX )`][@stdlib/stats/base/smaxabs]</span><span class="delimiter">: </span><span class="description">calculate the maximum absolute value of a single-precision floating-point strided array.</span>
--   <span class="signature">[`smaxabssorted( N, x, stride )`][@stdlib/stats/base/smaxabssorted]</span><span class="delimiter">: </span><span class="description">calculate the maximum absolute value of a sorted single-precision floating-point strided array.</span>
+-   <span class="signature">[`smaxabssorted( N, x, strideX )`][@stdlib/stats/base/smaxabssorted]</span><span class="delimiter">: </span><span class="description">calculate the maximum absolute value of a sorted single-precision floating-point strided array.</span>
 -   <span class="signature">[`smaxsorted( N, x, stride )`][@stdlib/stats/base/smaxsorted]</span><span class="delimiter">: </span><span class="description">calculate the maximum value of a sorted single-precision floating-point strided array.</span>
 -   <span class="signature">[`smean( N, x, stride )`][@stdlib/stats/base/smean]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array.</span>
 -   <span class="signature">[`smeankbn( N, x, stride )`][@stdlib/stats/base/smeankbn]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array using an improved Kahan–Babuška algorithm.</span>

From 16d5a84d32d879fc3986cac561c4c53f2f8b5b7c Mon Sep 17 00:00:00 2001
From: stdlib-bot <82920195+stdlib-bot@users.noreply.github.com>
Date: Thu, 2 Jan 2025 20:31:49 -0800
Subject: [PATCH 60/87] docs: update list of contributors

PR-URL: https://github.com/stdlib-js/stdlib/pull/4486
Reviewed-by: Athan Reines <kgryte@gmail.com>
---
 CONTRIBUTORS | 1 +
 1 file changed, 1 insertion(+)

diff --git a/CONTRIBUTORS b/CONTRIBUTORS
index 173c07b086cb..a5f7abac3c23 100644
--- a/CONTRIBUTORS
+++ b/CONTRIBUTORS
@@ -27,6 +27,7 @@ Daniel Killenberger <daniel.killenberger@gmail.com>
 Daniel Yu <40680511+Daniel777y@users.noreply.github.com>
 Debashis Maharana <debashismaharana7854@gmail.com>
 Desh Deepak Kant <118960904+DeshDeepakKant@users.noreply.github.com>
+Dhruv/ <154677013+DhruvArvindSingh@users.noreply.github.com>
 Divyansh Seth <59174836+sethdivyansh@users.noreply.github.com>
 Dominic Lim <46486515+domlimm@users.noreply.github.com>
 Dominik Moritz <domoritz@gmail.com>

From 03e10eda6eb87cdb8de7ca638eaf662838d59b05 Mon Sep 17 00:00:00 2001
From: Athan Reines <kgryte@gmail.com>
Date: Thu, 2 Jan 2025 22:15:06 -0800
Subject: [PATCH 61/87] refactor: move variable declaration

---
type: pre_commit_static_analysis_report
description: Results of running static analysis checks when committing changes.
report:
  - task: lint_filenames
    status: passed
  - task: lint_editorconfig
    status: passed
  - task: lint_markdown
    status: na
  - task: lint_package_json
    status: na
  - task: lint_repl_help
    status: na
  - task: lint_javascript_src
    status: na
  - task: lint_javascript_cli
    status: na
  - task: lint_javascript_examples
    status: na
  - task: lint_javascript_tests
    status: na
  - task: lint_javascript_benchmarks
    status: na
  - task: lint_python
    status: na
  - task: lint_r
    status: na
  - task: lint_c_src
    status: passed
  - task: lint_c_examples
    status: na
  - task: lint_c_benchmarks
    status: na
  - task: lint_c_tests_fixtures
    status: na
  - task: lint_shell
    status: na
  - task: lint_typescript_declarations
    status: na
  - task: lint_typescript_tests
    status: na
  - task: lint_license_headers
    status: passed
---

---
type: pre_push_report
description: Results of running various checks prior to pushing changes.
report:
  - task: run_javascript_examples
    status: na
  - task: run_c_examples
    status: na
  - task: run_cpp_examples
    status: na
  - task: run_javascript_readme_examples
    status: na
  - task: run_c_benchmarks
    status: na
  - task: run_cpp_benchmarks
    status: na
  - task: run_fortran_benchmarks
    status: na
  - task: run_javascript_benchmarks
    status: na
  - task: run_julia_benchmarks
    status: na
  - task: run_python_benchmarks
    status: na
  - task: run_r_benchmarks
    status: na
  - task: run_javascript_tests
    status: na
---
---
 lib/node_modules/@stdlib/random/base/uniform/src/main.c | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/lib/node_modules/@stdlib/random/base/uniform/src/main.c b/lib/node_modules/@stdlib/random/base/uniform/src/main.c
index 5863ac6c95a4..a60cdea01ce1 100644
--- a/lib/node_modules/@stdlib/random/base/uniform/src/main.c
+++ b/lib/node_modules/@stdlib/random/base/uniform/src/main.c
@@ -62,10 +62,10 @@
 * stdlib_base_random_randu_free( randu, -10.0, 10.0 );
 */
 double stdlib_base_random_uniform( struct BasePRNGObject *randu, const double a, const double b ) {
+	double r;
 	if ( randu == NULL ) {
 		return 0.0 / 0.0; // NaN
 	}
-	double r;
 	randu->prng->normalized( randu, &r );
 	return ( b*r ) + ( (1.0-r)*a );
 }

From fc7a7b8891ab4ae92103f87ce8aa7a5b696d8ea0 Mon Sep 17 00:00:00 2001
From: Athan Reines <kgryte@gmail.com>
Date: Thu, 2 Jan 2025 22:21:58 -0800
Subject: [PATCH 62/87] chore: update copyright years

---
 tools/snippets/README.md                                   | 2 +-
 tools/snippets/benchmark/benchmark.async.js                | 2 +-
 tools/snippets/benchmark/benchmark.js                      | 2 +-
 tools/snippets/benchmark/benchmark.length.js               | 2 +-
 tools/snippets/benchmark/benchmark.native.js               | 2 +-
 tools/snippets/benchmark/benchmark.wasm.js                 | 2 +-
 tools/snippets/benchmark/c/Makefile                        | 2 +-
 tools/snippets/benchmark/c/benchmark.c                     | 2 +-
 tools/snippets/benchmark/c/cephes/Makefile                 | 2 +-
 tools/snippets/benchmark/c/cephes/benchmark.c              | 2 +-
 tools/snippets/benchmark/c/native/Makefile                 | 2 +-
 tools/snippets/benchmark/c/native/benchmark.c              | 2 +-
 tools/snippets/benchmark/c/native/benchmark.length.c       | 2 +-
 tools/snippets/benchmark/cpp/boost/Makefile                | 2 +-
 tools/snippets/benchmark/cpp/boost/benchmark.cpp           | 2 +-
 tools/snippets/benchmark/fortran/Makefile                  | 2 +-
 tools/snippets/benchmark/fortran/benchmark.f               | 2 +-
 tools/snippets/benchmark/fortran/native/Makefile           | 2 +-
 tools/snippets/benchmark/fortran/native/benchmark.f        | 2 +-
 tools/snippets/benchmark/fortran/native/benchmark.length.f | 2 +-
 tools/snippets/benchmark/julia/benchmark.jl                | 2 +-
 tools/snippets/benchmark/python/benchmark.py               | 2 +-
 tools/snippets/benchmark/python/numpy/benchmark.py         | 2 +-
 tools/snippets/benchmark/python/scipy/benchmark.py         | 2 +-
 tools/snippets/benchmark/r/benchmark.R                     | 2 +-
 tools/snippets/bin/cli                                     | 2 +-
 tools/snippets/bin/cli_stdin                               | 2 +-
 tools/snippets/examples/index.js                           | 2 +-
 tools/snippets/include/stdlib/todo.h                       | 2 +-
 tools/snippets/lib/index.js                                | 2 +-
 tools/snippets/lib/main.js                                 | 2 +-
 tools/snippets/lib/validate.js                             | 2 +-
 tools/snippets/src/Makefile                                | 2 +-
 tools/snippets/src/addon.c                                 | 2 +-
 tools/snippets/src/main.c                                  | 2 +-
 tools/snippets/test/fixtures/c/cephes/Makefile             | 2 +-
 tools/snippets/test/fixtures/c/cephes/runner.c             | 2 +-
 tools/snippets/test/fixtures/cpp/boost/Makefile            | 2 +-
 tools/snippets/test/fixtures/cpp/boost/runner.cpp          | 2 +-
 tools/snippets/test/fixtures/julia/runner.jl               | 2 +-
 tools/snippets/test/fixtures/python/runner.py              | 2 +-
 tools/snippets/test/fixtures/r/runner.R                    | 2 +-
 tools/snippets/test/fixtures/stdin_error.js.txt            | 2 +-
 tools/snippets/test/test.cli.js                            | 2 +-
 tools/snippets/test/test.js                                | 2 +-
 tools/snippets/test/test.native.js                         | 2 +-
 tools/snippets/test/test.stdin_cli.js                      | 2 +-
 tools/snippets/test/test.validate.js                       | 2 +-
 48 files changed, 48 insertions(+), 48 deletions(-)

diff --git a/tools/snippets/README.md b/tools/snippets/README.md
index ded745b95c94..93db27a11734 100644
--- a/tools/snippets/README.md
+++ b/tools/snippets/README.md
@@ -2,7 +2,7 @@
 
 @license Apache-2.0
 
-Copyright (c) 2024 The Stdlib Authors.
+Copyright (c) 2025 The Stdlib Authors.
 
 Licensed under the Apache License, Version 2.0 (the "License");
 you may not use this file except in compliance with the License.
diff --git a/tools/snippets/benchmark/benchmark.async.js b/tools/snippets/benchmark/benchmark.async.js
index 688b12040791..d48d05f30de6 100644
--- a/tools/snippets/benchmark/benchmark.async.js
+++ b/tools/snippets/benchmark/benchmark.async.js
@@ -1,7 +1,7 @@
 /**
 * @license Apache-2.0
 *
-* Copyright (c) 2024 The Stdlib Authors.
+* Copyright (c) 2025 The Stdlib Authors.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
diff --git a/tools/snippets/benchmark/benchmark.js b/tools/snippets/benchmark/benchmark.js
index 767e4a019e1b..0c646ddcf267 100644
--- a/tools/snippets/benchmark/benchmark.js
+++ b/tools/snippets/benchmark/benchmark.js
@@ -1,7 +1,7 @@
 /**
 * @license Apache-2.0
 *
-* Copyright (c) 2024 The Stdlib Authors.
+* Copyright (c) 2025 The Stdlib Authors.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
diff --git a/tools/snippets/benchmark/benchmark.length.js b/tools/snippets/benchmark/benchmark.length.js
index c20dc91d9af5..813c02f29b45 100644
--- a/tools/snippets/benchmark/benchmark.length.js
+++ b/tools/snippets/benchmark/benchmark.length.js
@@ -1,7 +1,7 @@
 /**
 * @license Apache-2.0
 *
-* Copyright (c) 2024 The Stdlib Authors.
+* Copyright (c) 2025 The Stdlib Authors.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
diff --git a/tools/snippets/benchmark/benchmark.native.js b/tools/snippets/benchmark/benchmark.native.js
index 2f1daf9c0103..69b035a857c8 100644
--- a/tools/snippets/benchmark/benchmark.native.js
+++ b/tools/snippets/benchmark/benchmark.native.js
@@ -1,7 +1,7 @@
 /**
 * @license Apache-2.0
 *
-* Copyright (c) 2024 The Stdlib Authors.
+* Copyright (c) 2025 The Stdlib Authors.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
diff --git a/tools/snippets/benchmark/benchmark.wasm.js b/tools/snippets/benchmark/benchmark.wasm.js
index 2c18bfec696f..66165f7620dd 100644
--- a/tools/snippets/benchmark/benchmark.wasm.js
+++ b/tools/snippets/benchmark/benchmark.wasm.js
@@ -1,7 +1,7 @@
 /**
 * @license Apache-2.0
 *
-* Copyright (c) 2024 The Stdlib Authors.
+* Copyright (c) 2025 The Stdlib Authors.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
diff --git a/tools/snippets/benchmark/c/Makefile b/tools/snippets/benchmark/c/Makefile
index 88cbd1bb8a1b..635d877081d5 100644
--- a/tools/snippets/benchmark/c/Makefile
+++ b/tools/snippets/benchmark/c/Makefile
@@ -1,7 +1,7 @@
 #/
 # @license Apache-2.0
 #
-# Copyright (c) 2024 The Stdlib Authors.
+# Copyright (c) 2025 The Stdlib Authors.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
diff --git a/tools/snippets/benchmark/c/benchmark.c b/tools/snippets/benchmark/c/benchmark.c
index 0f52b6d27280..9670a2d0bdf1 100644
--- a/tools/snippets/benchmark/c/benchmark.c
+++ b/tools/snippets/benchmark/c/benchmark.c
@@ -1,7 +1,7 @@
 /**
 * @license Apache-2.0
 *
-* Copyright (c) 2024 The Stdlib Authors.
+* Copyright (c) 2025 The Stdlib Authors.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
diff --git a/tools/snippets/benchmark/c/cephes/Makefile b/tools/snippets/benchmark/c/cephes/Makefile
index 35b7d7c26ebd..c103e646f7a5 100644
--- a/tools/snippets/benchmark/c/cephes/Makefile
+++ b/tools/snippets/benchmark/c/cephes/Makefile
@@ -1,7 +1,7 @@
 #/
 # @license Apache-2.0
 #
-# Copyright (c) 2024 The Stdlib Authors.
+# Copyright (c) 2025 The Stdlib Authors.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
diff --git a/tools/snippets/benchmark/c/cephes/benchmark.c b/tools/snippets/benchmark/c/cephes/benchmark.c
index c579e9733466..c29256b2a648 100644
--- a/tools/snippets/benchmark/c/cephes/benchmark.c
+++ b/tools/snippets/benchmark/c/cephes/benchmark.c
@@ -1,7 +1,7 @@
 /**
 * @license Apache-2.0
 *
-* Copyright (c) 2024 The Stdlib Authors.
+* Copyright (c) 2025 The Stdlib Authors.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
diff --git a/tools/snippets/benchmark/c/native/Makefile b/tools/snippets/benchmark/c/native/Makefile
index 5d06a4714f91..100043f4054b 100644
--- a/tools/snippets/benchmark/c/native/Makefile
+++ b/tools/snippets/benchmark/c/native/Makefile
@@ -1,7 +1,7 @@
 #/
 # @license Apache-2.0
 #
-# Copyright (c) 2024 The Stdlib Authors.
+# Copyright (c) 2025 The Stdlib Authors.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
diff --git a/tools/snippets/benchmark/c/native/benchmark.c b/tools/snippets/benchmark/c/native/benchmark.c
index 9a5435c130b4..11c517a70543 100644
--- a/tools/snippets/benchmark/c/native/benchmark.c
+++ b/tools/snippets/benchmark/c/native/benchmark.c
@@ -1,7 +1,7 @@
 /**
 * @license Apache-2.0
 *
-* Copyright (c) 2024 The Stdlib Authors.
+* Copyright (c) 2025 The Stdlib Authors.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
diff --git a/tools/snippets/benchmark/c/native/benchmark.length.c b/tools/snippets/benchmark/c/native/benchmark.length.c
index 3cd3cc770c9a..daf9fa34caf2 100644
--- a/tools/snippets/benchmark/c/native/benchmark.length.c
+++ b/tools/snippets/benchmark/c/native/benchmark.length.c
@@ -1,7 +1,7 @@
 /**
 * @license Apache-2.0
 *
-* Copyright (c) 2024 The Stdlib Authors.
+* Copyright (c) 2025 The Stdlib Authors.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
diff --git a/tools/snippets/benchmark/cpp/boost/Makefile b/tools/snippets/benchmark/cpp/boost/Makefile
index eff50bbce3ae..a8582cd67345 100644
--- a/tools/snippets/benchmark/cpp/boost/Makefile
+++ b/tools/snippets/benchmark/cpp/boost/Makefile
@@ -1,7 +1,7 @@
 #/
 # @license Apache-2.0
 #
-# Copyright (c) 2024 The Stdlib Authors.
+# Copyright (c) 2025 The Stdlib Authors.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
diff --git a/tools/snippets/benchmark/cpp/boost/benchmark.cpp b/tools/snippets/benchmark/cpp/boost/benchmark.cpp
index 5b687c5d7d73..0bdd0a9db2b9 100644
--- a/tools/snippets/benchmark/cpp/boost/benchmark.cpp
+++ b/tools/snippets/benchmark/cpp/boost/benchmark.cpp
@@ -1,7 +1,7 @@
 /**
 * @license Apache-2.0
 *
-* Copyright (c) 2024 The Stdlib Authors.
+* Copyright (c) 2025 The Stdlib Authors.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
diff --git a/tools/snippets/benchmark/fortran/Makefile b/tools/snippets/benchmark/fortran/Makefile
index feb4fdc606fd..fc211b649ce3 100644
--- a/tools/snippets/benchmark/fortran/Makefile
+++ b/tools/snippets/benchmark/fortran/Makefile
@@ -1,7 +1,7 @@
 #/
 # @license Apache-2.0
 #
-# Copyright (c) 2024 The Stdlib Authors.
+# Copyright (c) 2025 The Stdlib Authors.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
diff --git a/tools/snippets/benchmark/fortran/benchmark.f b/tools/snippets/benchmark/fortran/benchmark.f
index 42a7abd4ff06..f8dedc5357d3 100644
--- a/tools/snippets/benchmark/fortran/benchmark.f
+++ b/tools/snippets/benchmark/fortran/benchmark.f
@@ -1,7 +1,7 @@
 !>
 ! @license Apache-2.0
 !
-! Copyright (c) 2024 The Stdlib Authors.
+! Copyright (c) 2025 The Stdlib Authors.
 !
 ! Licensed under the Apache License, Version 2.0 (the "License");
 ! you may not use this file except in compliance with the License.
diff --git a/tools/snippets/benchmark/fortran/native/Makefile b/tools/snippets/benchmark/fortran/native/Makefile
index 85ccfc26080b..56b2cdf9ee54 100644
--- a/tools/snippets/benchmark/fortran/native/Makefile
+++ b/tools/snippets/benchmark/fortran/native/Makefile
@@ -1,7 +1,7 @@
 #/
 # @license Apache-2.0
 #
-# Copyright (c) 2024 The Stdlib Authors.
+# Copyright (c) 2025 The Stdlib Authors.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
diff --git a/tools/snippets/benchmark/fortran/native/benchmark.f b/tools/snippets/benchmark/fortran/native/benchmark.f
index f4b943f0a3c3..48431d53f97d 100644
--- a/tools/snippets/benchmark/fortran/native/benchmark.f
+++ b/tools/snippets/benchmark/fortran/native/benchmark.f
@@ -1,7 +1,7 @@
 !>
 ! @license Apache-2.0
 !
-! Copyright (c) 2024 The Stdlib Authors.
+! Copyright (c) 2025 The Stdlib Authors.
 !
 ! Licensed under the Apache License, Version 2.0 (the "License");
 ! you may not use this file except in compliance with the License.
diff --git a/tools/snippets/benchmark/fortran/native/benchmark.length.f b/tools/snippets/benchmark/fortran/native/benchmark.length.f
index 00e5b68f52f2..df4e16c50a33 100644
--- a/tools/snippets/benchmark/fortran/native/benchmark.length.f
+++ b/tools/snippets/benchmark/fortran/native/benchmark.length.f
@@ -1,7 +1,7 @@
 !>
 ! @license Apache-2.0
 !
-! Copyright (c) 2024 The Stdlib Authors.
+! Copyright (c) 2025 The Stdlib Authors.
 !
 ! Licensed under the Apache License, Version 2.0 (the "License");
 ! you may not use this file except in compliance with the License.
diff --git a/tools/snippets/benchmark/julia/benchmark.jl b/tools/snippets/benchmark/julia/benchmark.jl
index c548c9413f41..5187008d5728 100755
--- a/tools/snippets/benchmark/julia/benchmark.jl
+++ b/tools/snippets/benchmark/julia/benchmark.jl
@@ -2,7 +2,7 @@
 #
 # @license Apache-2.0
 #
-# Copyright (c) 2024 The Stdlib Authors.
+# Copyright (c) 2025 The Stdlib Authors.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
diff --git a/tools/snippets/benchmark/python/benchmark.py b/tools/snippets/benchmark/python/benchmark.py
index eb5cf28fa92d..c7f6e4ec38e8 100644
--- a/tools/snippets/benchmark/python/benchmark.py
+++ b/tools/snippets/benchmark/python/benchmark.py
@@ -2,7 +2,7 @@
 #
 # @license Apache-2.0
 #
-# Copyright (c) 2024 The Stdlib Authors.
+# Copyright (c) 2025 The Stdlib Authors.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
diff --git a/tools/snippets/benchmark/python/numpy/benchmark.py b/tools/snippets/benchmark/python/numpy/benchmark.py
index 268a0eee08e2..260b5f1c68e9 100755
--- a/tools/snippets/benchmark/python/numpy/benchmark.py
+++ b/tools/snippets/benchmark/python/numpy/benchmark.py
@@ -2,7 +2,7 @@
 #
 # @license Apache-2.0
 #
-# Copyright (c) 2024 The Stdlib Authors.
+# Copyright (c) 2025 The Stdlib Authors.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
diff --git a/tools/snippets/benchmark/python/scipy/benchmark.py b/tools/snippets/benchmark/python/scipy/benchmark.py
index ade2520d5494..275d4da40e7c 100755
--- a/tools/snippets/benchmark/python/scipy/benchmark.py
+++ b/tools/snippets/benchmark/python/scipy/benchmark.py
@@ -2,7 +2,7 @@
 #
 # @license Apache-2.0
 #
-# Copyright (c) 2024 The Stdlib Authors.
+# Copyright (c) 2025 The Stdlib Authors.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
diff --git a/tools/snippets/benchmark/r/benchmark.R b/tools/snippets/benchmark/r/benchmark.R
index 5940cf1ea4e3..0245788e590d 100755
--- a/tools/snippets/benchmark/r/benchmark.R
+++ b/tools/snippets/benchmark/r/benchmark.R
@@ -2,7 +2,7 @@
 #
 # @license Apache-2.0
 #
-# Copyright (c) 2024 The Stdlib Authors.
+# Copyright (c) 2025 The Stdlib Authors.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
diff --git a/tools/snippets/bin/cli b/tools/snippets/bin/cli
index d737111a54a0..7c1b87fb8167 100755
--- a/tools/snippets/bin/cli
+++ b/tools/snippets/bin/cli
@@ -3,7 +3,7 @@
 /**
 * @license Apache-2.0
 *
-* Copyright (c) 2024 The Stdlib Authors.
+* Copyright (c) 2025 The Stdlib Authors.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
diff --git a/tools/snippets/bin/cli_stdin b/tools/snippets/bin/cli_stdin
index eb98a704ec02..44868f9cab59 100644
--- a/tools/snippets/bin/cli_stdin
+++ b/tools/snippets/bin/cli_stdin
@@ -3,7 +3,7 @@
 /**
 * @license Apache-2.0
 *
-* Copyright (c) 2024 The Stdlib Authors.
+* Copyright (c) 2025 The Stdlib Authors.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
diff --git a/tools/snippets/examples/index.js b/tools/snippets/examples/index.js
index f9c9747b9f6b..a9e69ac28ea0 100644
--- a/tools/snippets/examples/index.js
+++ b/tools/snippets/examples/index.js
@@ -1,7 +1,7 @@
 /**
 * @license Apache-2.0
 *
-* Copyright (c) 2024 The Stdlib Authors.
+* Copyright (c) 2025 The Stdlib Authors.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
diff --git a/tools/snippets/include/stdlib/todo.h b/tools/snippets/include/stdlib/todo.h
index afbd6e5b3a27..6b834781571c 100644
--- a/tools/snippets/include/stdlib/todo.h
+++ b/tools/snippets/include/stdlib/todo.h
@@ -1,7 +1,7 @@
 /**
 * @license Apache-2.0
 *
-* Copyright (c) 2024 The Stdlib Authors.
+* Copyright (c) 2025 The Stdlib Authors.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
diff --git a/tools/snippets/lib/index.js b/tools/snippets/lib/index.js
index d328dae487a2..d553da142c86 100644
--- a/tools/snippets/lib/index.js
+++ b/tools/snippets/lib/index.js
@@ -1,7 +1,7 @@
 /**
 * @license Apache-2.0
 *
-* Copyright (c) 2024 The Stdlib Authors.
+* Copyright (c) 2025 The Stdlib Authors.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
diff --git a/tools/snippets/lib/main.js b/tools/snippets/lib/main.js
index 19673be4ca8a..be644cf0fca6 100644
--- a/tools/snippets/lib/main.js
+++ b/tools/snippets/lib/main.js
@@ -1,7 +1,7 @@
 /**
 * @license Apache-2.0
 *
-* Copyright (c) 2024 The Stdlib Authors.
+* Copyright (c) 2025 The Stdlib Authors.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
diff --git a/tools/snippets/lib/validate.js b/tools/snippets/lib/validate.js
index 95cd9fbe5d27..6078bd3fb5fe 100644
--- a/tools/snippets/lib/validate.js
+++ b/tools/snippets/lib/validate.js
@@ -1,7 +1,7 @@
 /**
 * @license Apache-2.0
 *
-* Copyright (c) 2024 The Stdlib Authors.
+* Copyright (c) 2025 The Stdlib Authors.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
diff --git a/tools/snippets/src/Makefile b/tools/snippets/src/Makefile
index bcf18aa46655..7733b6180cb4 100644
--- a/tools/snippets/src/Makefile
+++ b/tools/snippets/src/Makefile
@@ -1,7 +1,7 @@
 #/
 # @license Apache-2.0
 #
-# Copyright (c) 2024 The Stdlib Authors.
+# Copyright (c) 2025 The Stdlib Authors.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
diff --git a/tools/snippets/src/addon.c b/tools/snippets/src/addon.c
index 4a2388fb907a..a158f045f84d 100644
--- a/tools/snippets/src/addon.c
+++ b/tools/snippets/src/addon.c
@@ -1,7 +1,7 @@
 /**
 * @license Apache-2.0
 *
-* Copyright (c) 2024 The Stdlib Authors.
+* Copyright (c) 2025 The Stdlib Authors.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
diff --git a/tools/snippets/src/main.c b/tools/snippets/src/main.c
index ace6bc92f41f..24f0765d71e4 100644
--- a/tools/snippets/src/main.c
+++ b/tools/snippets/src/main.c
@@ -1,7 +1,7 @@
 /**
 * @license Apache-2.0
 *
-* Copyright (c) 2024 The Stdlib Authors.
+* Copyright (c) 2025 The Stdlib Authors.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
diff --git a/tools/snippets/test/fixtures/c/cephes/Makefile b/tools/snippets/test/fixtures/c/cephes/Makefile
index ee252738689e..fd3f30129594 100644
--- a/tools/snippets/test/fixtures/c/cephes/Makefile
+++ b/tools/snippets/test/fixtures/c/cephes/Makefile
@@ -1,7 +1,7 @@
 #/
 # @license Apache-2.0
 #
-# Copyright (c) 2024 The Stdlib Authors.
+# Copyright (c) 2025 The Stdlib Authors.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
diff --git a/tools/snippets/test/fixtures/c/cephes/runner.c b/tools/snippets/test/fixtures/c/cephes/runner.c
index 1b76e91fabb9..2ef820d96629 100644
--- a/tools/snippets/test/fixtures/c/cephes/runner.c
+++ b/tools/snippets/test/fixtures/c/cephes/runner.c
@@ -1,7 +1,7 @@
 /**
 * @license Apache-2.0
 *
-* Copyright (c) 2024 The Stdlib Authors.
+* Copyright (c) 2025 The Stdlib Authors.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
diff --git a/tools/snippets/test/fixtures/cpp/boost/Makefile b/tools/snippets/test/fixtures/cpp/boost/Makefile
index 8ba5f7c629bd..94874eb7a405 100644
--- a/tools/snippets/test/fixtures/cpp/boost/Makefile
+++ b/tools/snippets/test/fixtures/cpp/boost/Makefile
@@ -1,7 +1,7 @@
 #/
 # @license Apache-2.0
 #
-# Copyright (c) 2024 The Stdlib Authors.
+# Copyright (c) 2025 The Stdlib Authors.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
diff --git a/tools/snippets/test/fixtures/cpp/boost/runner.cpp b/tools/snippets/test/fixtures/cpp/boost/runner.cpp
index c32d421a8b36..d91cebe5e6a1 100644
--- a/tools/snippets/test/fixtures/cpp/boost/runner.cpp
+++ b/tools/snippets/test/fixtures/cpp/boost/runner.cpp
@@ -1,7 +1,7 @@
 /**
 * @license Apache-2.0
 *
-* Copyright (c) 2024 The Stdlib Authors.
+* Copyright (c) 2025 The Stdlib Authors.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
diff --git a/tools/snippets/test/fixtures/julia/runner.jl b/tools/snippets/test/fixtures/julia/runner.jl
index 1025b93a7e4f..74aff7d3c714 100644
--- a/tools/snippets/test/fixtures/julia/runner.jl
+++ b/tools/snippets/test/fixtures/julia/runner.jl
@@ -2,7 +2,7 @@
 #
 # @license Apache-2.0
 #
-# Copyright (c) 2024 The Stdlib Authors.
+# Copyright (c) 2025 The Stdlib Authors.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
diff --git a/tools/snippets/test/fixtures/python/runner.py b/tools/snippets/test/fixtures/python/runner.py
index 45119f27f677..5acb4c6d301f 100644
--- a/tools/snippets/test/fixtures/python/runner.py
+++ b/tools/snippets/test/fixtures/python/runner.py
@@ -2,7 +2,7 @@
 #
 # @license Apache-2.0
 #
-# Copyright (c) 2024 The Stdlib Authors.
+# Copyright (c) 2025 The Stdlib Authors.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
diff --git a/tools/snippets/test/fixtures/r/runner.R b/tools/snippets/test/fixtures/r/runner.R
index 2cd3bc9136d9..e1e4d755118d 100644
--- a/tools/snippets/test/fixtures/r/runner.R
+++ b/tools/snippets/test/fixtures/r/runner.R
@@ -2,7 +2,7 @@
 #
 # @license Apache-2.0
 #
-# Copyright (c) 2024 The Stdlib Authors.
+# Copyright (c) 2025 The Stdlib Authors.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
diff --git a/tools/snippets/test/fixtures/stdin_error.js.txt b/tools/snippets/test/fixtures/stdin_error.js.txt
index c7e3c506a96b..7b3cc56df0fa 100644
--- a/tools/snippets/test/fixtures/stdin_error.js.txt
+++ b/tools/snippets/test/fixtures/stdin_error.js.txt
@@ -1,7 +1,7 @@
 /**
 * @license Apache-2.0
 *
-* Copyright (c) 2024 The Stdlib Authors.
+* Copyright (c) 2025 The Stdlib Authors.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
diff --git a/tools/snippets/test/test.cli.js b/tools/snippets/test/test.cli.js
index 2f3d7d270a21..61e11e246eee 100644
--- a/tools/snippets/test/test.cli.js
+++ b/tools/snippets/test/test.cli.js
@@ -1,7 +1,7 @@
 /**
 * @license Apache-2.0
 *
-* Copyright (c) 2024 The Stdlib Authors.
+* Copyright (c) 2025 The Stdlib Authors.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
diff --git a/tools/snippets/test/test.js b/tools/snippets/test/test.js
index 5e23e37197f1..ab6b7d018893 100644
--- a/tools/snippets/test/test.js
+++ b/tools/snippets/test/test.js
@@ -1,7 +1,7 @@
 /**
 * @license Apache-2.0
 *
-* Copyright (c) 2024 The Stdlib Authors.
+* Copyright (c) 2025 The Stdlib Authors.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
diff --git a/tools/snippets/test/test.native.js b/tools/snippets/test/test.native.js
index d51b9c47be00..b46ab66277c6 100644
--- a/tools/snippets/test/test.native.js
+++ b/tools/snippets/test/test.native.js
@@ -1,7 +1,7 @@
 /**
 * @license Apache-2.0
 *
-* Copyright (c) 2024 The Stdlib Authors.
+* Copyright (c) 2025 The Stdlib Authors.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
diff --git a/tools/snippets/test/test.stdin_cli.js b/tools/snippets/test/test.stdin_cli.js
index 1ec83225f144..c9bd774e929d 100644
--- a/tools/snippets/test/test.stdin_cli.js
+++ b/tools/snippets/test/test.stdin_cli.js
@@ -1,7 +1,7 @@
 /**
 * @license Apache-2.0
 *
-* Copyright (c) 2024 The Stdlib Authors.
+* Copyright (c) 2025 The Stdlib Authors.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
diff --git a/tools/snippets/test/test.validate.js b/tools/snippets/test/test.validate.js
index 12bd75f8d7ab..c4bedccaee84 100644
--- a/tools/snippets/test/test.validate.js
+++ b/tools/snippets/test/test.validate.js
@@ -1,7 +1,7 @@
 /**
 * @license Apache-2.0
 *
-* Copyright (c) 2024 The Stdlib Authors.
+* Copyright (c) 2025 The Stdlib Authors.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.

From 3a15881b47c16c763e00a5f7cab4a1ae97e416b3 Mon Sep 17 00:00:00 2001
From: Athan Reines <kgryte@gmail.com>
Date: Thu, 2 Jan 2025 22:22:42 -0800
Subject: [PATCH 63/87] chore: update copyright year

---
type: pre_commit_static_analysis_report
description: Results of running static analysis checks when committing changes.
report:
  - task: lint_filenames
    status: passed
  - task: lint_editorconfig
    status: passed
  - task: lint_markdown
    status: passed
  - task: lint_package_json
    status: na
  - task: lint_repl_help
    status: na
  - task: lint_javascript_src
    status: na
  - task: lint_javascript_cli
    status: na
  - task: lint_javascript_examples
    status: na
  - task: lint_javascript_tests
    status: na
  - task: lint_javascript_benchmarks
    status: na
  - task: lint_python
    status: na
  - task: lint_r
    status: na
  - task: lint_c_src
    status: na
  - task: lint_c_examples
    status: na
  - task: lint_c_benchmarks
    status: na
  - task: lint_c_tests_fixtures
    status: na
  - task: lint_shell
    status: na
  - task: lint_typescript_declarations
    status: na
  - task: lint_typescript_tests
    status: na
  - task: lint_license_headers
    status: passed
---
---
 README.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/README.md b/README.md
index 98d0d1ce7fa2..f4bdc0ae926c 100644
--- a/README.md
+++ b/README.md
@@ -611,7 +611,7 @@ See [LICENSE][stdlib-license].
 
 ## Copyright
 
-Copyright © 2016-2024. The Stdlib [Authors][stdlib-authors].
+Copyright © 2016-2025. The Stdlib [Authors][stdlib-authors].
 
 </section>
 

From fb26ebe1c006de31d2bb8603f1fe0d21171f9601 Mon Sep 17 00:00:00 2001
From: Athan Reines <kgryte@gmail.com>
Date: Thu, 2 Jan 2025 22:22:59 -0800
Subject: [PATCH 64/87] chore: update copyright year

---
type: pre_commit_static_analysis_report
description: Results of running static analysis checks when committing changes.
report:
  - task: lint_filenames
    status: passed
  - task: lint_editorconfig
    status: passed
  - task: lint_markdown
    status: na
  - task: lint_package_json
    status: na
  - task: lint_repl_help
    status: na
  - task: lint_javascript_src
    status: na
  - task: lint_javascript_cli
    status: na
  - task: lint_javascript_examples
    status: na
  - task: lint_javascript_tests
    status: na
  - task: lint_javascript_benchmarks
    status: na
  - task: lint_python
    status: na
  - task: lint_r
    status: na
  - task: lint_c_src
    status: na
  - task: lint_c_examples
    status: na
  - task: lint_c_benchmarks
    status: na
  - task: lint_c_tests_fixtures
    status: na
  - task: lint_shell
    status: na
  - task: lint_typescript_declarations
    status: na
  - task: lint_typescript_tests
    status: na
  - task: lint_license_headers
    status: passed
---

---
type: pre_push_report
description: Results of running various checks prior to pushing changes.
report:
  - task: run_javascript_examples
    status: passed
  - task: run_c_examples
    status: na
  - task: run_cpp_examples
    status: na
  - task: run_javascript_readme_examples
    status: failed
---
---
 NOTICE | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/NOTICE b/NOTICE
index e6e7482f21fd..cbd3a299d947 100644
--- a/NOTICE
+++ b/NOTICE
@@ -1 +1 @@
-Copyright (c) 2016-2024 The Stdlib Authors.
+Copyright (c) 2016-2025 The Stdlib Authors.

From 82d1f24ef99db3f49a22b2f48d3efae1c8123a46 Mon Sep 17 00:00:00 2001
From: Athan Reines <kgryte@gmail.com>
Date: Thu, 2 Jan 2025 22:36:23 -0800
Subject: [PATCH 65/87] chore: update mailmap

---
type: pre_commit_static_analysis_report
description: Results of running static analysis checks when committing changes.
report:
  - task: lint_filenames
    status: passed
  - task: lint_editorconfig
    status: passed
  - task: lint_markdown
    status: na
  - task: lint_package_json
    status: na
  - task: lint_repl_help
    status: na
  - task: lint_javascript_src
    status: na
  - task: lint_javascript_cli
    status: na
  - task: lint_javascript_examples
    status: na
  - task: lint_javascript_tests
    status: na
  - task: lint_javascript_benchmarks
    status: na
  - task: lint_python
    status: na
  - task: lint_r
    status: na
  - task: lint_c_src
    status: na
  - task: lint_c_examples
    status: na
  - task: lint_c_benchmarks
    status: na
  - task: lint_c_tests_fixtures
    status: na
  - task: lint_shell
    status: na
  - task: lint_typescript_declarations
    status: na
  - task: lint_typescript_tests
    status: na
  - task: lint_license_headers
    status: passed
---

---
type: pre_push_report
description: Results of running various checks prior to pushing changes.
report:
  - task: run_javascript_examples
    status: na
  - task: run_c_examples
    status: na
  - task: run_cpp_examples
    status: na
  - task: run_javascript_readme_examples
    status: na
  - task: run_c_benchmarks
    status: na
  - task: run_cpp_benchmarks
    status: na
  - task: run_fortran_benchmarks
    status: na
  - task: run_javascript_benchmarks
    status: na
  - task: run_julia_benchmarks
    status: na
  - task: run_python_benchmarks
    status: na
  - task: run_r_benchmarks
    status: na
  - task: run_javascript_tests
    status: na
---
---
 .mailmap | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/.mailmap b/.mailmap
index 3593db50775e..2e21b2b6a037 100644
--- a/.mailmap
+++ b/.mailmap
@@ -52,6 +52,9 @@ Chinmay Joshi <86140365+JawHawk@users.noreply.github.com> Chinmay J
 Debashis Maharana <debashismaharana7854@gmail.com> <145602692+DevMhrn@users.noreply.github.com>
 Debashis Maharana <debashismaharana7854@gmail.com> DebashisMaharana
 
+Dhruv Arvind Singh <154677013+DhruvArvindSingh@users.noreply.github.com> DhruvArvindSingh
+Dhruv Arvind Singh <154677013+DhruvArvindSingh@users.noreply.github.com> Dhruv/
+
 Dorrin Sotoudeh <dorrinsotoudeh123@gmail.com> <59933477+dorrin-sot@users.noreply.github.com>
 Dorrin Sotoudeh <dorrinsotoudeh123@gmail.com> dorrin-sot
 

From cf5c6b20df701881c5b4a252403ea69c08f1982f Mon Sep 17 00:00:00 2001
From: Athan Reines <kgryte@gmail.com>
Date: Thu, 2 Jan 2025 23:37:37 -0800
Subject: [PATCH 66/87] chore: update mailmap

---
type: pre_commit_static_analysis_report
description: Results of running static analysis checks when committing changes.
report:
  - task: lint_filenames
    status: passed
  - task: lint_editorconfig
    status: passed
  - task: lint_markdown
    status: na
  - task: lint_package_json
    status: na
  - task: lint_repl_help
    status: na
  - task: lint_javascript_src
    status: na
  - task: lint_javascript_cli
    status: na
  - task: lint_javascript_examples
    status: na
  - task: lint_javascript_tests
    status: na
  - task: lint_javascript_benchmarks
    status: na
  - task: lint_python
    status: na
  - task: lint_r
    status: na
  - task: lint_c_src
    status: na
  - task: lint_c_examples
    status: na
  - task: lint_c_benchmarks
    status: na
  - task: lint_c_tests_fixtures
    status: na
  - task: lint_shell
    status: na
  - task: lint_typescript_declarations
    status: na
  - task: lint_typescript_tests
    status: na
  - task: lint_license_headers
    status: passed
---
---
 .mailmap | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/.mailmap b/.mailmap
index 2e21b2b6a037..8d87c73f6c33 100644
--- a/.mailmap
+++ b/.mailmap
@@ -219,6 +219,9 @@ Vaibhav Patel <98279986+noobCoderVP@users.noreply.github.com> ProCoderVP
 Varad Gupta <varadgupta21@gmail.com> <114755221+vr-varad@users.noreply.github.com>
 Varad Gupta <varadgupta21@gmail.com> vr-varad
 
+Vivek Maurya <vm8118134@gmail.com> <155618190+vivekmaurya001@users.noreply.github.com>
+Vivek Maurya <vm8118134@gmail.com> vivekmaurya001
+
 # Y
 
 Yaswanth Kosuru <116426380+yaswanthkosuru@users.noreply.github.com> yaswanth

From d9f4811979ca3428b880bac2a8f06c6f908d51a5 Mon Sep 17 00:00:00 2001
From: Neeraj Pathak <neerajrpathak710@gmail.com>
Date: Fri, 3 Jan 2025 12:09:54 +0530
Subject: [PATCH 67/87] feat: add C `ndarray` interface and refactor
 implementation for `stats/base/dnanmeanwd`

PR-URL: https://github.com/stdlib-js/stdlib/pull/4251
Co-authored-by: Athan Reines <kgryte@gmail.com>
Reviewed-by: Athan Reines <kgryte@gmail.com>
---
 .../@stdlib/stats/base/dnanmeanwd/README.md   | 148 +++++++++++++++---
 .../base/dnanmeanwd/benchmark/benchmark.js    |  30 ++--
 .../dnanmeanwd/benchmark/benchmark.native.js  |  30 ++--
 .../dnanmeanwd/benchmark/benchmark.ndarray.js |  30 ++--
 .../benchmark/benchmark.ndarray.native.js     |  30 ++--
 .../dnanmeanwd/benchmark/c/benchmark.length.c |  54 ++++++-
 .../stats/base/dnanmeanwd/docs/repl.txt       |  34 ++--
 .../base/dnanmeanwd/docs/types/index.d.ts     |  12 +-
 .../base/dnanmeanwd/examples/c/example.c      |   9 +-
 .../include/stdlib/stats/base/dnanmeanwd.h    |   9 +-
 .../stats/base/dnanmeanwd/lib/dnanmeanwd.js   |  45 ++----
 .../base/dnanmeanwd/lib/dnanmeanwd.native.js  |   9 +-
 .../stats/base/dnanmeanwd/lib/index.js        |   7 +-
 .../stats/base/dnanmeanwd/lib/ndarray.js      |  18 +--
 .../base/dnanmeanwd/lib/ndarray.native.js     |  20 +--
 .../stats/base/dnanmeanwd/manifest.json       |  50 ++++--
 .../@stdlib/stats/base/dnanmeanwd/src/addon.c |  28 +++-
 .../dnanmeanwd/src/{dnanmeanwd.c => main.c}   |  46 ++++--
 .../base/dnanmeanwd/test/test.dnanmeanwd.js   |  13 +-
 .../dnanmeanwd/test/test.dnanmeanwd.native.js |  13 +-
 .../base/dnanmeanwd/test/test.ndarray.js      |  13 +-
 .../dnanmeanwd/test/test.ndarray.native.js    |  13 +-
 22 files changed, 409 insertions(+), 252 deletions(-)
 rename lib/node_modules/@stdlib/stats/base/dnanmeanwd/src/{dnanmeanwd.c => main.c} (62%)

diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/README.md b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/README.md
index 8392e1999459..2ee2d1fb9649 100644
--- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/README.md
+++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/README.md
@@ -51,7 +51,7 @@ The [arithmetic mean][arithmetic-mean] is defined as
 var dnanmeanwd = require( '@stdlib/stats/base/dnanmeanwd' );
 ```
 
-#### dnanmeanwd( N, x, stride )
+#### dnanmeanwd( N, x, strideX )
 
 Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-point strided array `x`, using Welford's algorithm and ignoring `NaN` values.
 
@@ -59,9 +59,8 @@ Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-p
 var Float64Array = require( '@stdlib/array/float64' );
 
 var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
-var N = x.length;
 
-var v = dnanmeanwd( N, x, 1 );
+var v = dnanmeanwd( x.length, x, 1 );
 // returns ~0.3333
 ```
 
@@ -69,18 +68,16 @@ The function has the following parameters:
 
 -   **N**: number of indexed elements.
 -   **x**: input [`Float64Array`][@stdlib/array/float64].
--   **stride**: index increment for `x`.
+-   **strideX**: index increment for `x`.
 
-The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`,
+The `N` and stride parameters determine which elements in the stride array are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`,
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0, NaN ] );
-var N = floor( x.length / 2 );
 
-var v = dnanmeanwd( N, x, 2 );
+var v = dnanmeanwd( 4, x, 2 );
 // returns 1.25
 ```
 
@@ -90,18 +87,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ] );
 var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
 
-var N = floor( x0.length / 2 );
-
-var v = dnanmeanwd( N, x1, 2 );
+var v = dnanmeanwd( 4, x1, 2 );
 // returns 1.25
 ```
 
-#### dnanmeanwd.ndarray( N, x, stride, offset )
+#### dnanmeanwd.ndarray( N, x, strideX, offsetX )
 
 Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-point strided array, ignoring `NaN` values and using Welford's algorithm and alternative indexing semantics.
 
@@ -109,26 +103,23 @@ Computes the [arithmetic mean][arithmetic-mean] of a double-precision floating-p
 var Float64Array = require( '@stdlib/array/float64' );
 
 var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
-var N = x.length;
 
-var v = dnanmeanwd.ndarray( N, x, 1, 0 );
+var v = dnanmeanwd.ndarray( x.length, x, 1, 0 );
 // returns ~0.33333
 ```
 
 The function has the following additional parameters:
 
--   **offset**: starting index for `x`.
+-   **offsetX**: starting index for `x`.
 
-While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the [arithmetic mean][arithmetic-mean] for every other value in `x` starting from the second value
+While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the [arithmetic mean][arithmetic-mean] for every other element in `x` starting from the second element
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ] );
-var N = floor( x.length / 2 );
 
-var v = dnanmeanwd.ndarray( N, x, 2, 1 );
+var v = dnanmeanwd.ndarray( 4, x, 2, 1 );
 // returns 1.25
 ```
 
@@ -180,6 +171,123 @@ console.log( v );
 
 <!-- /.examples -->
 
+<!-- C interface documentation. -->
+
+* * *
+
+<section class="c">
+
+## C APIs
+
+<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<!-- C usage documentation. -->
+
+<section class="usage">
+
+### Usage
+
+```c
+#include "stdlib/stats/base/dnanmeanwd.h"
+```
+
+#### stdlib_strided_dnanmeanwd( N, \*X, strideX )
+
+Computes the arithmetic mean of a double-precision floating-point strided array `x`, using Welford's algorithm and ignoring `NaN` values.
+
+```c
+const double x[] = { 1.0, 2.0, 0.0/0.0, 3.0, 0.0/0.0, 4.0, 5.0, 6.0, 0.0/0.0, 7.0, 8.0, 0.0/0.0 };
+
+double v = stdlib_strided_dnanmeanwd( 6, x, 2 );
+// returns 1.25
+```
+
+The function accepts the following arguments:
+
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **X**: `[in] double*` input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+
+```c
+double stdlib_strided_dnanmeanwd( const CBLAS_INT N, const double *X, const CBLAS_INT strideX );
+```
+
+#### stdlib_strided_dnanmeanwd_ndarray( N, \*X, strideX, offsetX )
+
+Computes the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values and using Welford's algorithm and alternative indexing semantics.
+
+```c
+const double x[] = { 1.0, 2.0, 0.0/0.0, 3.0, 0.0/0.0, 4.0, 5.0, 6.0, 0.0/0.0, 7.0, 8.0, 0.0/0.0 };
+
+double v = stdlib_strided_dnanmeanwd_ndarray( 6, x, 2, 0 );
+// returns 1.25
+```
+
+The function accepts the following arguments:
+
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **X**: `[in] double*` input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+-   **offsetX**: `[in] CBLAS_INT` starting index for `X`.
+
+```c
+double stdlib_strided_dnanmeanwd_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX );
+```
+
+</section>
+
+<!-- /.usage -->
+
+<!-- C API usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="notes">
+
+</section>
+
+<!-- /.notes -->
+
+<!-- C API usage examples. -->
+
+<section class="examples">
+
+### Examples
+
+```c
+#include "stdlib/stats/base/dnanmeanwd.h"
+#include <stdio.h>
+
+int main( void ) {
+    // Create a strided array:
+    const double x[] = { 1.0, 2.0, 0.0/0.0, 3.0, 0.0/0.0, 4.0, 5.0, 6.0, 0.0/0.0, 7.0, 8.0, 0.0/0.0 };
+
+    // Specify the number of elements:
+    const int N = 6;
+
+    // Specify the stride length:
+    const int strideX = 2;
+
+    // Compute the arithmetic mean:
+    double v = stdlib_strided_dnanmeanwd( N, x, strideX );
+
+    // Print the result:
+    printf( "mean: %lf\n", v );
+}
+```
+
+</section>
+
+<!-- /.examples -->
+
+</section>
+
+<!-- /.c -->
+
 * * *
 
 <section class="references">
diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/benchmark/benchmark.js
index 725749785047..5b3d7bd98e6f 100644
--- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/benchmark/benchmark.js
+++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/benchmark/benchmark.js
@@ -21,16 +21,30 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/base/uniform' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
+var filledarrayBy = require( '@stdlib/array/filled-by' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float64Array = require( '@stdlib/array/float64' );
 var pkg = require( './../package.json' ).name;
 var dnanmeanwd = require( './../lib/dnanmeanwd.js' );
 
 
 // FUNCTIONS //
 
+/**
+* Returns a random value or `NaN`.
+*
+* @private
+* @returns {number} random number or `NaN`
+*/
+function rand() {
+	if ( bernoulli( 0.2 ) ) {
+		return NaN;
+	}
+	return uniform( -10.0, 10.0 );
+}
+
 /**
 * Creates a benchmark function.
 *
@@ -39,17 +53,7 @@ var dnanmeanwd = require( './../lib/dnanmeanwd.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float64Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		if ( randu() < 0.2 ) {
-			x[ i ] = NaN;
-		} else {
-			x[ i ] = ( randu()*20.0 ) - 10.0;
-		}
-	}
+	var x = filledarrayBy( len, 'float64', rand );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/benchmark/benchmark.native.js
index 49d5321307e9..45aaba61cc4c 100644
--- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/benchmark/benchmark.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/benchmark/benchmark.native.js
@@ -22,10 +22,11 @@
 
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/base/uniform' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
+var filledarrayBy = require( '@stdlib/array/filled-by' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float64Array = require( '@stdlib/array/float64' );
 var tryRequire = require( '@stdlib/utils/try-require' );
 var pkg = require( './../package.json' ).name;
 
@@ -40,6 +41,19 @@ var opts = {
 
 // FUNCTIONS //
 
+/**
+* Returns a random value or `NaN`.
+*
+* @private
+* @returns {number} random number or `NaN`
+*/
+function rand() {
+	if ( bernoulli( 0.2 ) ) {
+		return NaN;
+	}
+	return uniform( -10.0, 10.0 );
+}
+
 /**
 * Creates a benchmark function.
 *
@@ -48,17 +62,7 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float64Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		if ( randu() < 0.2 ) {
-			x[ i ] = NaN;
-		} else {
-			x[ i ] = ( randu()*20.0 ) - 10.0;
-		}
-	}
+	var x = filledarrayBy( len, 'float64', rand );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/benchmark/benchmark.ndarray.js
index f2e9d31a0fc1..c22b93247335 100644
--- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/benchmark/benchmark.ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/benchmark/benchmark.ndarray.js
@@ -21,16 +21,30 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/base/uniform' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
+var filledarrayBy = require( '@stdlib/array/filled-by' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float64Array = require( '@stdlib/array/float64' );
 var pkg = require( './../package.json' ).name;
 var dnanmeanwd = require( './../lib/ndarray.js' );
 
 
 // FUNCTIONS //
 
+/**
+* Returns a random value or `NaN`.
+*
+* @private
+* @returns {number} random number or `NaN`
+*/
+function rand() {
+	if ( bernoulli( 0.2 ) ) {
+		return NaN;
+	}
+	return uniform( -10.0, 10.0 );
+}
+
 /**
 * Creates a benchmark function.
 *
@@ -39,17 +53,7 @@ var dnanmeanwd = require( './../lib/ndarray.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float64Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		if ( randu() < 0.2 ) {
-			x[ i ] = NaN;
-		} else {
-			x[ i ] = ( randu()*20.0 ) - 10.0;
-		}
-	}
+	var x = filledarrayBy( len, 'float64', rand );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/benchmark/benchmark.ndarray.native.js
index a62fc15c5406..77bdfc9108e7 100644
--- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/benchmark/benchmark.ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/benchmark/benchmark.ndarray.native.js
@@ -22,10 +22,11 @@
 
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
+var uniform = require( '@stdlib/random/base/uniform' );
+var bernoulli = require( '@stdlib/random/base/bernoulli' );
+var filledarrayBy = require( '@stdlib/array/filled-by' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float64Array = require( '@stdlib/array/float64' );
 var tryRequire = require( '@stdlib/utils/try-require' );
 var pkg = require( './../package.json' ).name;
 
@@ -40,6 +41,19 @@ var opts = {
 
 // FUNCTIONS //
 
+/**
+* Returns a random value or `NaN`.
+*
+* @private
+* @returns {number} random number or `NaN`
+*/
+function rand() {
+	if ( bernoulli( 0.2 ) ) {
+		return NaN;
+	}
+	return uniform( -10.0, 10.0 );
+}
+
 /**
 * Creates a benchmark function.
 *
@@ -48,17 +62,7 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float64Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		if ( randu() < 0.2 ) {
-			x[ i ] = NaN;
-		} else {
-			x[ i ] = ( randu()*20.0 ) - 10.0;
-		}
-	}
+	var x = filledarrayBy( len, 'float64', rand );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/benchmark/c/benchmark.length.c
index 3dce6d5a6c7f..7876ee3ceac5 100644
--- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/benchmark/c/benchmark.length.c
+++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/benchmark/c/benchmark.length.c
@@ -94,7 +94,7 @@ static double rand_double( void ) {
 * @param len          array length
 * @return             elapsed time in seconds
 */
-static double benchmark( int iterations, int len ) {
+static double benchmark1( int iterations, int len ) {
 	double elapsed;
 	double x[ len ];
 	double v;
@@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) {
 	v = 0.0;
 	t = tic();
 	for ( i = 0; i < iterations; i++ ) {
+		// cppcheck-suppress uninitvar
 		v = stdlib_strided_dnanmeanwd( len, x, 1 );
 		if ( v != v ) {
 			printf( "should not return NaN\n" );
@@ -120,6 +121,44 @@ static double benchmark( int iterations, int len ) {
 	return elapsed;
 }
 
+/**
+* Runs a benchmark.
+*
+* @param iterations   number of iterations
+* @param len          array length
+* @return             elapsed time in seconds
+*/
+static double benchmark2( int iterations, int len ) {
+	double elapsed;
+	double x[ len ];
+	double v;
+	double t;
+	int i;
+
+	for ( i = 0; i < len; i++ ) {
+		if ( rand_double() < 0.2 ) {
+			x[ i ] = 0.0 / 0.0; // NaN
+		} else {
+			x[ i ] = ( rand_double() * 20000.0 ) - 10000.0;
+		}
+	}
+	v = 0.0;
+	t = tic();
+	for ( i = 0; i < iterations; i++ ) {
+		// cppcheck-suppress uninitvar
+		v = stdlib_strided_dnanmeanwd_ndarray( len, x, 1, 0 );
+		if ( v != v ) {
+			printf( "should not return NaN\n" );
+			break;
+		}
+	}
+	elapsed = tic() - t;
+	if ( v != v ) {
+		printf( "should not return NaN\n" );
+	}
+	return elapsed;
+}
+
 /**
 * Main execution sequence.
 */
@@ -142,7 +181,18 @@ int main( void ) {
 		for ( j = 0; j < REPEATS; j++ ) {
 			count += 1;
 			printf( "# c::%s:len=%d\n", NAME, len );
-			elapsed = benchmark( iter, len );
+			elapsed = benchmark1( iter, len );
+			print_results( iter, elapsed );
+			printf( "ok %d benchmark finished\n", count );
+		}
+	}
+	for ( i = MIN; i <= MAX; i++ ) {
+		len = pow( 10, i );
+		iter = ITERATIONS / pow( 10, i-1 );
+		for ( j = 0; j < REPEATS; j++ ) {
+			count += 1;
+			printf( "# c::%s:ndarray:len=%d\n", NAME, len );
+			elapsed = benchmark2( iter, len );
 			print_results( iter, elapsed );
 			printf( "ok %d benchmark finished\n", count );
 		}
diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/docs/repl.txt
index 33f938b1969d..9a707a6850a8 100644
--- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/docs/repl.txt
+++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/docs/repl.txt
@@ -1,10 +1,10 @@
 
-{{alias}}( N, x, stride )
+{{alias}}( N, x, strideX )
     Computes the arithmetic mean of a double-precision floating-point strided
     array, using Welford's algorithm and ignoring `NaN` values.
 
-    The `N` and `stride` parameters determine which elements in `x` are accessed
-    at runtime.
+    The `N` and stride parameters determine which elements in the strided array
+    are accessed at runtime.
 
     Indexing is relative to the first index. To introduce an offset, use a typed
     array view.
@@ -21,8 +21,8 @@
     x: Float64Array
         Input array.
 
-    stride: integer
-        Index increment.
+    strideX: integer
+        Stride length.
 
     Returns
     -------
@@ -36,28 +36,25 @@
     > {{alias}}( x.length, x, 1 )
     ~0.3333
 
-    // Using `N` and `stride` parameters:
+    // Using `N` and stride parameters:
     > x = new {{alias:@stdlib/array/float64}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > var stride = 2;
-    > {{alias}}( N, x, stride )
+    > {{alias}}( 3, x, 2 )
     ~0.3333
 
     // Using view offsets:
     > var x0 = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );
     > var x1 = new {{alias:@stdlib/array/float64}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );
-    > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );
-    > stride = 2;
-    > {{alias}}( N, x1, stride )
+    > {{alias}}( 3, x1, 2 )
     ~-0.3333
 
-{{alias}}.ndarray( N, x, stride, offset )
+
+{{alias}}.ndarray( N, x, strideX, offsetX )
     Computes the arithmetic mean of a double-precision floating-point strided
     array, ignoring `NaN` values and using Welford's algorithm and alternative
     indexing semantics.
 
     While typed array views mandate a view offset based on the underlying
-    buffer, the `offset` parameter supports indexing semantics based on a
+    buffer, the offset parameter supports indexing semantics based on a
     starting index.
 
     Parameters
@@ -68,10 +65,10 @@
     x: Float64Array
         Input array.
 
-    stride: integer
-        Index increment.
+    strideX: integer
+        Stride length.
 
-    offset: integer
+    offsetX: integer
         Starting index.
 
     Returns
@@ -88,8 +85,7 @@
 
     // Using offset parameter:
     > var x = new {{alias:@stdlib/array/float64}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > {{alias}}.ndarray( N, x, 2, 1 )
+    > {{alias}}.ndarray( 3, x, 2, 1 )
     ~-0.3333
 
     See Also
diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/docs/types/index.d.ts
index d674d840c966..9c5697ea52ca 100644
--- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/docs/types/index.d.ts
@@ -27,7 +27,7 @@ interface Routine {
 	*
 	* @param N - number of indexed elements
 	* @param x - input array
-	* @param stride - stride length
+	* @param strideX - stride length
 	* @returns arithmetic mean
 	*
 	* @example
@@ -38,15 +38,15 @@ interface Routine {
 	* var v = dnanmeanwd( x.length, x, 1 );
 	* // returns ~0.3333
 	*/
-	( N: number, x: Float64Array, stride: number ): number;
+	( N: number, x: Float64Array, strideX: number ): number;
 
 	/**
 	* Computes the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values and using Welford's algorithm and alternative indexing semantics.
 	*
 	* @param N - number of indexed elements
 	* @param x - input array
-	* @param stride - stride length
-	* @param offset - starting index
+	* @param strideX - stride length
+	* @param offsetX - starting index
 	* @returns arithmetic mean
 	*
 	* @example
@@ -57,7 +57,7 @@ interface Routine {
 	* var v = dnanmeanwd.ndarray( x.length, x, 1, 0 );
 	* // returns ~0.3333
 	*/
-	ndarray( N: number, x: Float64Array, stride: number, offset: number ): number;
+	ndarray( N: number, x: Float64Array, strideX: number, offsetX: number ): number;
 }
 
 /**
@@ -65,7 +65,7 @@ interface Routine {
 *
 * @param N - number of indexed elements
 * @param x - input array
-* @param stride - stride length
+* @param strideX - stride length
 * @returns arithmetic mean
 *
 * @example
diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/examples/c/example.c
index 03e6af11ea32..8d795c27ee78 100644
--- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/examples/c/example.c
+++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/examples/c/example.c
@@ -17,21 +17,20 @@
 */
 
 #include "stdlib/stats/base/dnanmeanwd.h"
-#include <stdint.h>
 #include <stdio.h>
 
 int main( void ) {
 	// Create a strided array:
-	double x[] = { 1.0, 2.0, 0.0/0.0, 3.0, 0.0/0.0, 4.0, 5.0, 6.0, 0.0/0.0, 7.0, 8.0, 0.0/0.0 };
+	const double x[] = { 1.0, 2.0, 0.0/0.0, 3.0, 0.0/0.0, 4.0, 5.0, 6.0, 0.0/0.0, 7.0, 8.0, 0.0/0.0 };
 
 	// Specify the number of elements:
-	int64_t N = 6;
+	const int N = 6;
 
 	// Specify the stride length:
-	int64_t stride = 2;
+	const int strideX = 2;
 
 	// Compute the arithmetic mean:
-	double v = stdlib_strided_dnanmeanwd( N, x, stride );
+	double v = stdlib_strided_dnanmeanwd( N, x, strideX );
 
 	// Print the result:
 	printf( "mean: %lf\n", v );
diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/include/stdlib/stats/base/dnanmeanwd.h b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/include/stdlib/stats/base/dnanmeanwd.h
index aefd7c9a8c10..8cbe79514434 100644
--- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/include/stdlib/stats/base/dnanmeanwd.h
+++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/include/stdlib/stats/base/dnanmeanwd.h
@@ -19,7 +19,7 @@
 #ifndef STDLIB_STATS_BASE_DNANMEANWD_H
 #define STDLIB_STATS_BASE_DNANMEANWD_H
 
-#include <stdint.h>
+#include "stdlib/blas/base/shared.h"
 
 /*
 * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler.
@@ -31,7 +31,12 @@ extern "C" {
 /**
 * Computes the arithmetic mean of a double-precision floating-point strided array, using Welford's algorithm and ignoring `NaN` values.
 */
-double stdlib_strided_dnanmeanwd( const int64_t N, const double *X, const int64_t stride );
+double API_SUFFIX(stdlib_strided_dnanmeanwd)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX );
+
+/**
+* Computes the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values and using Welford's algorithm and alternative indexing semantics.
+*/
+double API_SUFFIX(stdlib_strided_dnanmeanwd_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX );
 
 #ifdef __cplusplus
 }
diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/lib/dnanmeanwd.js b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/lib/dnanmeanwd.js
index a258c5ddbb53..26f73054c35b 100644
--- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/lib/dnanmeanwd.js
+++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/lib/dnanmeanwd.js
@@ -18,6 +18,12 @@
 
 'use strict';
 
+// MODULES //
+
+var stride2offset = require( '@stdlib/strided/base/stride2offset' );
+var ndarray = require( './ndarray.js' );
+
+
 // MAIN //
 
 /**
@@ -43,50 +49,19 @@
 *
 * @param {PositiveInteger} N - number of indexed elements
 * @param {Float64Array} x - input array
-* @param {integer} stride - stride length
+* @param {integer} strideX - stride length
 * @returns {number} arithmetic mean
 *
 * @example
 * var Float64Array = require( '@stdlib/array/float64' );
 *
 * var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
-* var N = x.length;
 *
-* var v = dnanmeanwd( N, x, 1 );
+* var v = dnanmeanwd( x.length, x, 1 );
 * // returns ~0.3333
 */
-function dnanmeanwd( N, x, stride ) {
-	var mu;
-	var ix;
-	var v;
-	var n;
-	var i;
-
-	if ( N <= 0 ) {
-		return NaN;
-	}
-	if ( N === 1 || stride === 0 ) {
-		return x[ 0 ];
-	}
-	if ( stride < 0 ) {
-		ix = (1-N) * stride;
-	} else {
-		ix = 0;
-	}
-	mu = 0.0;
-	n = 0;
-	for ( i = 0; i < N; i++ ) {
-		v = x[ ix ];
-		if ( v === v ) {
-			n += 1;
-			mu += ( v-mu ) / n;
-		}
-		ix += stride;
-	}
-	if ( n === 0 ) {
-		return NaN;
-	}
-	return mu;
+function dnanmeanwd( N, x, strideX ) {
+	return ndarray( N, x, strideX, stride2offset( N, strideX ) );
 }
 
 
diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/lib/dnanmeanwd.native.js b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/lib/dnanmeanwd.native.js
index 453518fe3e67..758ec4ccd4f5 100644
--- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/lib/dnanmeanwd.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/lib/dnanmeanwd.native.js
@@ -30,20 +30,19 @@ var addon = require( './../src/addon.node' );
 *
 * @param {PositiveInteger} N - number of indexed elements
 * @param {Float64Array} x - input array
-* @param {integer} stride - stride length
+* @param {integer} strideX - stride length
 * @returns {number} arithmetic mean
 *
 * @example
 * var Float64Array = require( '@stdlib/array/float64' );
 *
 * var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
-* var N = x.length;
 *
-* var v = dnanmeanwd( N, x, 1 );
+* var v = dnanmeanwd( x.length, x, 1 );
 * // returns ~0.3333
 */
-function dnanmeanwd( N, x, stride ) {
-	return addon( N, x, stride );
+function dnanmeanwd( N, x, strideX ) {
+	return addon( N, x, strideX );
 }
 
 
diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/lib/index.js b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/lib/index.js
index 9bf3e4eb75e7..9f251ed36e80 100644
--- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/lib/index.js
+++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/lib/index.js
@@ -28,20 +28,17 @@
 * var dnanmeanwd = require( '@stdlib/stats/base/dnanmeanwd' );
 *
 * var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
-* var N = 3;
 *
-* var v = dnanmeanwd( N, x, 1 );
+* var v = dnanmeanwd( x.length, x, 1 );
 * // returns ~0.3333
 *
 * @example
 * var Float64Array = require( '@stdlib/array/float64' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 * var dnanmeanwd = require( '@stdlib/stats/base/dnanmeanwd' );
 *
 * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ] );
-* var N = floor( x.length / 2 );
 *
-* var v = dnanmeanwd.ndarray( N, x, 2, 1 );
+* var v = dnanmeanwd.ndarray( 4, x, 2, 1 );
 * // returns 1.25
 */
 
diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/lib/ndarray.js
index 3f76936b2e87..4beb52be8514 100644
--- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/lib/ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/lib/ndarray.js
@@ -43,21 +43,19 @@
 *
 * @param {PositiveInteger} N - number of indexed elements
 * @param {Float64Array} x - input array
-* @param {integer} stride - stride length
-* @param {NonNegativeInteger} offset - starting index
+* @param {integer} strideX - stride length
+* @param {NonNegativeInteger} offsetX - starting index
 * @returns {number} arithmetic mean
 *
 * @example
 * var Float64Array = require( '@stdlib/array/float64' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 *
 * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ] );
-* var N = floor( x.length / 2 );
 *
-* var v = dnanmeanwd( N, x, 2, 1 );
+* var v = dnanmeanwd( 4, x, 2, 1 );
 * // returns 1.25
 */
-function dnanmeanwd( N, x, stride, offset ) {
+function dnanmeanwd( N, x, strideX, offsetX ) {
 	var mu;
 	var ix;
 	var v;
@@ -67,10 +65,10 @@ function dnanmeanwd( N, x, stride, offset ) {
 	if ( N <= 0 ) {
 		return NaN;
 	}
-	if ( N === 1 || stride === 0 ) {
-		return x[ offset ];
+	if ( N === 1 || strideX === 0 ) {
+		return x[ offsetX ];
 	}
-	ix = offset;
+	ix = offsetX;
 	mu = 0.0;
 	n = 0;
 	for ( i = 0; i < N; i++ ) {
@@ -79,7 +77,7 @@ function dnanmeanwd( N, x, stride, offset ) {
 			n += 1;
 			mu += ( v-mu ) / n;
 		}
-		ix += stride;
+		ix += strideX;
 	}
 	if ( n === 0 ) {
 		return NaN;
diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/lib/ndarray.native.js
index 3acbd37309a2..b10036df551d 100644
--- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/lib/ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/lib/ndarray.native.js
@@ -20,8 +20,7 @@
 
 // MODULES //
 
-var Float64Array = require( '@stdlib/array/float64' );
-var addon = require( './dnanmeanwd.native.js' );
+var addon = require( './../src/addon.node' );
 
 
 // MAIN //
@@ -31,27 +30,20 @@ var addon = require( './dnanmeanwd.native.js' );
 *
 * @param {PositiveInteger} N - number of indexed elements
 * @param {Float64Array} x - input array
-* @param {integer} stride - stride length
-* @param {NonNegativeInteger} offset - starting index
+* @param {integer} strideX - stride length
+* @param {NonNegativeInteger} offsetX - starting index
 * @returns {number} arithmetic mean
 *
 * @example
 * var Float64Array = require( '@stdlib/array/float64' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 *
 * var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0, NaN ] );
-* var N = floor( x.length / 2 );
 *
-* var v = dnanmeanwd( N, x, 2, 1 );
+* var v = dnanmeanwd( 4, x, 2, 1 );
 * // returns 1.25
 */
-function dnanmeanwd( N, x, stride, offset ) {
-	var view;
-	if ( stride < 0 ) {
-		offset += (N-1) * stride;
-	}
-	view = new Float64Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len
-	return addon( N, view, stride );
+function dnanmeanwd( N, x, strideX, offsetX ) {
+	return addon.ndarray( N, x, strideX, offsetX );
 }
 
 
diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/manifest.json b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/manifest.json
index 8bdb968d02e5..99aaf0c4da72 100644
--- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/manifest.json
+++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/manifest.json
@@ -1,6 +1,7 @@
 {
   "options": {
-    "task":"build"
+    "task": "build",
+    "wasm": false
   },
   "fields": [
     {
@@ -27,17 +28,18 @@
   "confs": [
     {
       "task": "build",
+      "wasm": false,
       "src": [
-        "./src/dnanmeanwd.c"
+        "./src/main.c"
       ],
       "include": [
         "./include"
       ],
-      "libraries": [
-        "-lm"
-      ],
+      "libraries": [],
       "libpath": [],
       "dependencies": [
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset",
         "@stdlib/napi/export",
         "@stdlib/napi/argv",
         "@stdlib/napi/argv-int64",
@@ -47,31 +49,51 @@
     },
     {
       "task": "benchmark",
+      "wasm": false,
       "src": [
-        "./src/dnanmeanwd.c"
+        "./src/main.c"
       ],
       "include": [
         "./include"
       ],
-      "libraries": [
-        "-lm"
-      ],
+      "libraries": [],
       "libpath": [],
-      "dependencies": []
+      "dependencies": [
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset"
+      ]
     },
     {
       "task": "examples",
+      "wasm": false,
       "src": [
-        "./src/dnanmeanwd.c"
+        "./src/main.c"
       ],
       "include": [
         "./include"
       ],
-      "libraries": [
-        "-lm"
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset"
+      ]
+    },
+    {
+      "task": "",
+      "wasm": true,
+      "src": [
+        "./src/main.c"
       ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
       "libpath": [],
-      "dependencies": []
+      "dependencies": [
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset"
+      ]
     }
   ]
 }
diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/src/addon.c b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/src/addon.c
index 89c2a60995db..222f988aead4 100644
--- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/src/addon.c
+++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/src/addon.c
@@ -17,12 +17,11 @@
 */
 
 #include "stdlib/stats/base/dnanmeanwd.h"
+#include "stdlib/napi/export.h"
 #include "stdlib/napi/argv.h"
 #include "stdlib/napi/argv_int64.h"
 #include "stdlib/napi/argv_strided_float64array.h"
 #include "stdlib/napi/create_double.h"
-#include "stdlib/napi/export.h"
-#include <node_api.h>
 
 /**
 * Receives JavaScript callback invocation data.
@@ -34,10 +33,27 @@
 static napi_value addon( napi_env env, napi_callback_info info ) {
 	STDLIB_NAPI_ARGV( env, info, argv, argc, 3 );
 	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
-	STDLIB_NAPI_ARGV_INT64( env, stride, argv, 2 );
-	STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, stride, argv, 1 );
-	STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dnanmeanwd( N, X, stride ), v );
+	STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dnanmeanwd( N, X, strideX ), v );
+	return v;
+}
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon_method( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 4 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 );
+	STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT64ARRAY( env, X, N, strideX, argv, 1 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, stdlib_strided_dnanmeanwd_ndarray( N, X, strideX, offsetX ), v );
 	return v;
 }
 
-STDLIB_NAPI_MODULE_EXPORT_FCN( addon )
+STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method )
diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/src/dnanmeanwd.c b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/src/main.c
similarity index 62%
rename from lib/node_modules/@stdlib/stats/base/dnanmeanwd/src/dnanmeanwd.c
rename to lib/node_modules/@stdlib/stats/base/dnanmeanwd/src/main.c
index ba1d54d3a05f..a0a7c9c37e73 100644
--- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/src/dnanmeanwd.c
+++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/src/main.c
@@ -1,7 +1,7 @@
 /**
 * @license Apache-2.0
 *
-* Copyright (c) 2020 The Stdlib Authors.
+* Copyright (c) 2025 The Stdlib Authors.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
@@ -17,6 +17,8 @@
 */
 
 #include "stdlib/stats/base/dnanmeanwd.h"
+#include "stdlib/blas/base/shared.h"
+#include "stdlib/strided/base/stride2offset.h"
 #include <stdint.h>
 
 /**
@@ -40,29 +42,39 @@
 * -   Welford, B. P. 1962. "Note on a Method for Calculating Corrected Sums of Squares and Products." _Technometrics_ 4 (3). Taylor & Francis: 419–20. doi:[10.1080/00401706.1962.10490022](https://doi.org/10.1080/00401706.1962.10490022).
 * -   van Reeken, A. J. 1968. "Letters to the Editor: Dealing with Neely's Algorithms." _Communications of the ACM_ 11 (3): 149–50. doi:[10.1145/362929.362961](https://doi.org/10.1145/362929.362961).
 *
-* @param N       number of indexed elements
-* @param X       input array
-* @param stride  stride length
-* @return        output value
+* @param N        number of indexed elements
+* @param X        input array
+* @param strideX  stride length
+* @return         output value
 */
-double stdlib_strided_dnanmeanwd( const int64_t N, const double *X, const int64_t stride ) {
-	int64_t ix;
-	int64_t i;
-	int64_t n;
+double API_SUFFIX(stdlib_strided_dnanmeanwd)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX ) {
+	const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX );
+	return API_SUFFIX(stdlib_strided_dnanmeanwd_ndarray)( N, X, strideX, ox );
+}
+
+/**
+* Computes the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values and using Welford's algorithm and alternative indexing semantics.
+*
+* @param N        number of indexed elements
+* @param X        input array
+* @param strideX  stride length
+* @param offsetX  starting index for X
+* @return         output value
+*/
+double API_SUFFIX(stdlib_strided_dnanmeanwd_ndarray)( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) {
+	CBLAS_INT ix;
+	CBLAS_INT i;
+	CBLAS_INT n;
 	double mu;
 	double v;
 
 	if ( N <= 0 ) {
 		return 0.0 / 0.0; // NaN
 	}
-	if ( N == 1 || stride == 0 ) {
-		return X[ 0 ];
-	}
-	if ( stride < 0 ) {
-		ix = (1-N) * stride;
-	} else {
-		ix = 0;
+	if ( N == 1 || strideX == 0 ) {
+		return X[ offsetX ];
 	}
+	ix = offsetX;
 	mu = 0.0;
 	n = 0;
 	for ( i = 0; i < N; i++ ) {
@@ -71,7 +83,7 @@ double stdlib_strided_dnanmeanwd( const int64_t N, const double *X, const int64_
 			n += 1;
 			mu += ( v-mu ) / (double)n;
 		}
-		ix += stride;
+		ix += strideX;
 	}
 	if ( n == 0 ) {
 		return 0.0 / 0.0; // NaN;
diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.dnanmeanwd.js b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.dnanmeanwd.js
index 8d3e5c441607..baed8323682c 100644
--- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.dnanmeanwd.js
+++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.dnanmeanwd.js
@@ -21,7 +21,6 @@
 // MODULES //
 
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var Float64Array = require( '@stdlib/array/float64' );
 var dnanmeanwd = require( './../lib/dnanmeanwd.js' );
@@ -90,7 +89,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 });
 
 tape( 'the function supports a `stride` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -106,15 +104,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) {
 		NaN   // 4
 	]);
 
-	N = floor( x.length / 2 );
-	v = dnanmeanwd( N, x, 2 );
+	v = dnanmeanwd( 4, x, 2 );
 
 	t.strictEqual( v, 1.25, 'returns expected value' );
 	t.end();
 });
 
 tape( 'the function supports a negative `stride` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -130,8 +126,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t )
 		NaN   // 0
 	]);
 
-	N = floor( x.length / 2 );
-	v = dnanmeanwd( N, x, -2 );
+	v = dnanmeanwd( 4, x, -2 );
 
 	t.strictEqual( v, 1.25, 'returns expected value' );
 	t.end();
@@ -152,7 +147,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f
 tape( 'the function supports view offsets', function test( t ) {
 	var x0;
 	var x1;
-	var N;
 	var v;
 
 	x0 = new Float64Array([
@@ -169,9 +163,8 @@ tape( 'the function supports view offsets', function test( t ) {
 	]);
 
 	x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
-	N = floor(x1.length / 2);
 
-	v = dnanmeanwd( N, x1, 2 );
+	v = dnanmeanwd( 5, x1, 2 );
 	t.strictEqual( v, 1.25, 'returns expected value' );
 
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.dnanmeanwd.native.js b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.dnanmeanwd.native.js
index 86d88d56366d..cf5754b12d8e 100644
--- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.dnanmeanwd.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.dnanmeanwd.native.js
@@ -22,7 +22,6 @@
 
 var resolve = require( 'path' ).resolve;
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var Float64Array = require( '@stdlib/array/float64' );
 var tryRequire = require( '@stdlib/utils/try-require' );
@@ -181,7 +180,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 });
 
 tape( 'the function supports a `stride` parameter', opts, function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -197,15 +195,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) {
 		NaN   // 4
 	]);
 
-	N = floor( x.length / 2 );
-	v = dnanmeanwd( N, x, 2 );
+	v = dnanmeanwd( 4, x, 2 );
 
 	t.strictEqual( v, 1.25, 'returns expected value' );
 	t.end();
 });
 
 tape( 'the function supports a negative `stride` parameter', opts, function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -221,8 +217,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test
 		NaN   // 0
 	]);
 
-	N = floor( x.length / 2 );
-	v = dnanmeanwd( N, x, -2 );
+	v = dnanmeanwd( 4, x, -2 );
 
 	t.strictEqual( v, 1.25, 'returns expected value' );
 	t.end();
@@ -243,7 +238,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f
 tape( 'the function supports view offsets', opts, function test( t ) {
 	var x0;
 	var x1;
-	var N;
 	var v;
 
 	x0 = new Float64Array([
@@ -260,9 +254,8 @@ tape( 'the function supports view offsets', opts, function test( t ) {
 	]);
 
 	x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
-	N = floor(x1.length / 2);
 
-	v = dnanmeanwd( N, x1, 2 );
+	v = dnanmeanwd( 5, x1, 2 );
 	t.strictEqual( v, 1.25, 'returns expected value' );
 
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.ndarray.js
index 7dd106806e3e..a911e86e95c7 100644
--- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.ndarray.js
@@ -21,7 +21,6 @@
 // MODULES //
 
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var Float64Array = require( '@stdlib/array/float64' );
 var dnanmeanwd = require( './../lib/ndarray.js' );
@@ -90,7 +89,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 });
 
 tape( 'the function supports a `stride` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -106,15 +104,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) {
 		NaN   // 4
 	]);
 
-	N = floor( x.length / 2 );
-	v = dnanmeanwd( N, x, 2, 0 );
+	v = dnanmeanwd( 4, x, 2, 0 );
 
 	t.strictEqual( v, 1.25, 'returns expected value' );
 	t.end();
 });
 
 tape( 'the function supports a negative `stride` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -130,8 +126,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t )
 		NaN   // 0
 	]);
 
-	N = floor( x.length / 2 );
-	v = dnanmeanwd( N, x, -2, 6 );
+	v = dnanmeanwd( 4, x, -2, 6 );
 
 	t.strictEqual( v, 1.25, 'returns expected value' );
 	t.end();
@@ -150,7 +145,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f
 });
 
 tape( 'the function supports an `offset` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -166,9 +160,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) {
 		NaN,
 		NaN   // 4
 	]);
-	N = floor( x.length / 2 );
 
-	v = dnanmeanwd( N, x, 2, 1 );
+	v = dnanmeanwd( 5, x, 2, 1 );
 	t.strictEqual( v, 1.25, 'returns expected value' );
 
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.ndarray.native.js
index b6e78c8c14ab..574982c528a2 100644
--- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.ndarray.native.js
@@ -22,7 +22,6 @@
 
 var resolve = require( 'path' ).resolve;
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnan = require( '@stdlib/math/base/assert/is-nan' );
 var Float64Array = require( '@stdlib/array/float64' );
 var tryRequire = require( '@stdlib/utils/try-require' );
@@ -99,7 +98,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 });
 
 tape( 'the function supports a `stride` parameter', opts, function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -115,15 +113,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) {
 		NaN   // 4
 	]);
 
-	N = floor( x.length / 2 );
-	v = dnanmeanwd( N, x, 2, 0 );
+	v = dnanmeanwd( 4, x, 2, 0 );
 
 	t.strictEqual( v, 1.25, 'returns expected value' );
 	t.end();
 });
 
 tape( 'the function supports a negative `stride` parameter', opts, function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -139,8 +135,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test
 		NaN   // 0
 	]);
 
-	N = floor( x.length / 2 );
-	v = dnanmeanwd( N, x, -2, 6 );
+	v = dnanmeanwd( 4, x, -2, 6 );
 
 	t.strictEqual( v, 1.25, 'returns expected value' );
 	t.end();
@@ -159,7 +154,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f
 });
 
 tape( 'the function supports an `offset` parameter', opts, function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -175,9 +169,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) {
 		NaN,
 		NaN   // 4
 	]);
-	N = floor( x.length / 2 );
 
-	v = dnanmeanwd( N, x, 2, 1 );
+	v = dnanmeanwd( 5, x, 2, 1 );
 	t.strictEqual( v, 1.25, 'returns expected value' );
 
 	t.end();

From 1a97dfaa12cad0dee6a967372391f2d797598c7b Mon Sep 17 00:00:00 2001
From: Vivek maurya <155618190+vivekmaurya001@users.noreply.github.com>
Date: Fri, 3 Jan 2025 13:08:39 +0530
Subject: [PATCH 68/87] refactor: update `math/base/assert/is-even` to follow
 latest project conventions

PR-URL: https://github.com/stdlib-js/stdlib/pull/4183
Co-authored-by: Athan Reines <kgryte@gmail.com>
Reviewed-by: Athan Reines <kgryte@gmail.com>
---
 .../assert/is-even/benchmark/benchmark.js     | 10 +--
 .../is-even/benchmark/benchmark.native.js     | 10 +--
 .../is-even/benchmark/c/native/benchmark.c    |  9 ++-
 .../math/base/assert/is-even/manifest.json    | 41 +++++++++++-
 .../math/base/assert/is-even/src/addon.c      | 64 +++----------------
 5 files changed, 67 insertions(+), 67 deletions(-)

diff --git a/lib/node_modules/@stdlib/math/base/assert/is-even/benchmark/benchmark.js b/lib/node_modules/@stdlib/math/base/assert/is-even/benchmark/benchmark.js
index 5c2a4932dffa..0ea52481252f 100644
--- a/lib/node_modules/@stdlib/math/base/assert/is-even/benchmark/benchmark.js
+++ b/lib/node_modules/@stdlib/math/base/assert/is-even/benchmark/benchmark.js
@@ -21,8 +21,7 @@
 // MODULES //
 
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
-var round = require( '@stdlib/math/base/special/round' );
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
 var isBoolean = require( '@stdlib/assert/is-boolean' ).isPrimitive;
 var pkg = require( './../package.json' ).name;
 var isEven = require( './../lib' );
@@ -31,14 +30,17 @@ var isEven = require( './../lib' );
 // MAIN //
 
 bench( pkg, function benchmark( b ) {
+	var len;
 	var x;
 	var y;
 	var i;
 
+	len = 100;
+	x = discreteUniform( len, 0, 1000 );
+
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		x = round( (randu()*1.0e7) - 5.0e6 );
-		y = isEven( x );
+		y = isEven( x[ i % len ] );
 		if ( typeof y !== 'boolean' ) {
 			b.fail( 'should return a boolean' );
 		}
diff --git a/lib/node_modules/@stdlib/math/base/assert/is-even/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/math/base/assert/is-even/benchmark/benchmark.native.js
index da205aada595..b95bed88186f 100644
--- a/lib/node_modules/@stdlib/math/base/assert/is-even/benchmark/benchmark.native.js
+++ b/lib/node_modules/@stdlib/math/base/assert/is-even/benchmark/benchmark.native.js
@@ -22,8 +22,7 @@
 
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
-var randu = require( '@stdlib/random/base/randu' );
-var round = require( '@stdlib/math/base/special/round' );
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
 var isBoolean = require( '@stdlib/assert/is-boolean' ).isPrimitive;
 var tryRequire = require( '@stdlib/utils/try-require' );
 var pkg = require( './../package.json' ).name;
@@ -40,14 +39,17 @@ var opts = {
 // MAIN //
 
 bench( pkg+'::native', opts, function benchmark( b ) {
+	var len;
 	var x;
 	var y;
 	var i;
 
+	len = 100;
+	x = discreteUniform( len, 0, 1000 );
+
 	b.tic();
 	for ( i = 0; i < b.iterations; i++ ) {
-		x = round( (randu()*1.0e7) - 5.0e6 );
-		y = isEven( x );
+		y = isEven( x[ i % len ] );
 		if ( typeof y !== 'boolean' ) {
 			b.fail( 'should return a boolean' );
 		}
diff --git a/lib/node_modules/@stdlib/math/base/assert/is-even/benchmark/c/native/benchmark.c b/lib/node_modules/@stdlib/math/base/assert/is-even/benchmark/c/native/benchmark.c
index 5605d32ba184..7e0075a0d8a8 100644
--- a/lib/node_modules/@stdlib/math/base/assert/is-even/benchmark/c/native/benchmark.c
+++ b/lib/node_modules/@stdlib/math/base/assert/is-even/benchmark/c/native/benchmark.c
@@ -92,15 +92,18 @@ static double rand_double( void ) {
 */
 static double benchmark( void ) {
 	double elapsed;
-	double x;
+	double x[ 100 ];
 	double t;
 	bool b;
 	int i;
 
+	for ( i = 0; i < 100; i++ ) {
+		x[ i ] = round( (rand_double()*200.0) - 100.0 );
+	}
+
 	t = tic();
 	for ( i = 0; i < ITERATIONS; i++ ) {
-		x = ( rand_double() * 200.0 ) - 100.0;
-		b = stdlib_base_is_even( x );
+		b = stdlib_base_is_even( x[ i%100 ] );
 		if ( b != true && b != false ) {
 			printf( "should return either true or false\n" );
 			break;
diff --git a/lib/node_modules/@stdlib/math/base/assert/is-even/manifest.json b/lib/node_modules/@stdlib/math/base/assert/is-even/manifest.json
index 33756e256dcf..accca2c07be0 100644
--- a/lib/node_modules/@stdlib/math/base/assert/is-even/manifest.json
+++ b/lib/node_modules/@stdlib/math/base/assert/is-even/manifest.json
@@ -1,5 +1,7 @@
 {
-  "options": {},
+  "options": {
+    "task": "build"
+  },
   "fields": [
     {
       "field": "src",
@@ -24,6 +26,43 @@
   ],
   "confs": [
     {
+      "task": "build",
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [
+        "-lm"
+      ],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/math/base/assert/is-integer",
+        "@stdlib/napi/export",
+        "@stdlib/napi/argv",
+        "@stdlib/napi/argv-double",
+        "@stdlib/napi/create-int32"
+      ]
+    },
+    {
+      "task": "benchmark",
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [
+        "-lm"
+      ],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/math/base/assert/is-integer"
+      ]
+    },
+    {
+      "task": "examples",
       "src": [
         "./src/main.c"
       ],
diff --git a/lib/node_modules/@stdlib/math/base/assert/is-even/src/addon.c b/lib/node_modules/@stdlib/math/base/assert/is-even/src/addon.c
index 85642e403244..b496a218e026 100644
--- a/lib/node_modules/@stdlib/math/base/assert/is-even/src/addon.c
+++ b/lib/node_modules/@stdlib/math/base/assert/is-even/src/addon.c
@@ -17,9 +17,12 @@
 */
 
 #include "stdlib/math/base/assert/is_even.h"
+#include "stdlib/napi/argv.h"
+#include "stdlib/napi/argv_double.h"
+#include "stdlib/napi/create_int32.h"
+#include "stdlib/napi/export.h"
 #include <node_api.h>
 #include <stdint.h>
-#include <assert.h>
 
 /**
 * Receives JavaScript callback invocation data.
@@ -29,60 +32,11 @@
 * @return       Node-API value
 */
 static napi_value addon( napi_env env, napi_callback_info info ) {
-	napi_status status;
-
-	// Get callback arguments:
-	size_t argc = 1;
-	napi_value argv[ 1 ];
-	status = napi_get_cb_info( env, info, &argc, argv, NULL, NULL );
-	assert( status == napi_ok );
-
-	// Check whether we were provided the correct number of arguments:
-	if ( argc < 1 ) {
-		status = napi_throw_error( env, NULL, "invalid invocation. Insufficient arguments." );
-		assert( status == napi_ok );
-		return NULL;
-	}
-	if ( argc > 1 ) {
-		status = napi_throw_error( env, NULL, "invalid invocation. Too many arguments." );
-		assert( status == napi_ok );
-		return NULL;
-	}
-
-	napi_valuetype vtype0;
-	status = napi_typeof( env, argv[ 0 ], &vtype0 );
-	assert( status == napi_ok );
-	if ( vtype0 != napi_number ) {
-		status = napi_throw_type_error( env, NULL, "invalid argument. First argument must be a number." );
-		assert( status == napi_ok );
-		return NULL;
-	}
-
-	double x;
-	status = napi_get_value_double( env, argv[ 0 ], &x );
-	assert( status == napi_ok );
-
-	bool result = stdlib_base_is_even( x );
-
-	napi_value v;
-	status = napi_create_int32( env, (int32_t)result, &v );
-	assert( status == napi_ok );
-
-	return v;
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 1 );
+	STDLIB_NAPI_ARGV_DOUBLE( env, x, argv, 0 );
+	STDLIB_NAPI_CREATE_INT32( env, (int32_t)stdlib_base_is_even( x ), out );
+	return out;
 }
 
-/**
-* Initializes a Node-API module.
-*
-* @param env      environment under which the function is invoked
-* @param exports  exports object
-* @return         main export
-*/
-static napi_value init( napi_env env, napi_value exports ) {
-	napi_value fcn;
-	napi_status status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, addon, NULL, &fcn );
-	assert( status == napi_ok );
-	return fcn;
-}
+STDLIB_NAPI_MODULE_EXPORT_FCN( addon )
 
-NAPI_MODULE( NODE_GYP_MODULE_NAME, init )

From d2fc4576989007259ef556e663e8a26502fb61c5 Mon Sep 17 00:00:00 2001
From: Dhruv/ <154677013+DhruvArvindSingh@users.noreply.github.com>
Date: Sat, 4 Jan 2025 01:59:08 +0530
Subject: [PATCH 69/87] refactor: update `stats/base/snanstdevch` native addon
 from C++ to C

PR-URL: https://github.com/stdlib-js/stdlib/pull/4470
Reviewed-by: Athan Reines <kgryte@gmail.com>
---
 .../stats/base/snanstdevch/include.gypi       |   2 +-
 .../stats/base/snanstdevch/manifest.json      |  43 +++++-
 .../stats/base/snanstdevch/src/addon.c        |  45 ++++++
 .../stats/base/snanstdevch/src/addon.cpp      | 130 ------------------
 4 files changed, 88 insertions(+), 132 deletions(-)
 create mode 100644 lib/node_modules/@stdlib/stats/base/snanstdevch/src/addon.c
 delete mode 100644 lib/node_modules/@stdlib/stats/base/snanstdevch/src/addon.cpp

diff --git a/lib/node_modules/@stdlib/stats/base/snanstdevch/include.gypi b/lib/node_modules/@stdlib/stats/base/snanstdevch/include.gypi
index 868c5c12e852..26476a8c2655 100644
--- a/lib/node_modules/@stdlib/stats/base/snanstdevch/include.gypi
+++ b/lib/node_modules/@stdlib/stats/base/snanstdevch/include.gypi
@@ -36,7 +36,7 @@
 
     # Source files:
     'src_files': [
-      '<(src_dir)/addon.cpp',
+      '<(src_dir)/addon.c',
       '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).src; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
     ],
 
diff --git a/lib/node_modules/@stdlib/stats/base/snanstdevch/manifest.json b/lib/node_modules/@stdlib/stats/base/snanstdevch/manifest.json
index 34cc378c2b14..914273dfe691 100644
--- a/lib/node_modules/@stdlib/stats/base/snanstdevch/manifest.json
+++ b/lib/node_modules/@stdlib/stats/base/snanstdevch/manifest.json
@@ -1,5 +1,7 @@
 {
-  "options": {},
+  "options": {
+    "task": "build"
+  },
   "fields": [
     {
       "field": "src",
@@ -24,6 +26,45 @@
   ],
   "confs": [
     {
+      "task": "build",
+      "src": [
+        "./src/snanstdevch.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [
+        "-lm"
+      ],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/napi/export",
+        "@stdlib/napi/argv",
+        "@stdlib/napi/argv-int64",
+        "@stdlib/napi/argv-float",
+        "@stdlib/napi/argv-strided-float32array",
+        "@stdlib/stats/base/snanvariancech",
+        "@stdlib/napi/create-double"
+      ]
+    },
+    {
+      "task": "benchmark",
+      "src": [
+        "./src/snanstdevch.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [
+        "-lm"
+      ],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/stats/base/snanvariancech"
+      ]
+    },
+    {
+      "task": "examples",
       "src": [
         "./src/snanstdevch.c"
       ],
diff --git a/lib/node_modules/@stdlib/stats/base/snanstdevch/src/addon.c b/lib/node_modules/@stdlib/stats/base/snanstdevch/src/addon.c
new file mode 100644
index 000000000000..2021633fbf97
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/snanstdevch/src/addon.c
@@ -0,0 +1,45 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/snanstdevch.h"
+#include "stdlib/napi/export.h"
+#include "stdlib/napi/argv.h"
+#include "stdlib/napi/argv_int64.h"
+#include "stdlib/napi/argv_strided_float32array.h"
+#include "stdlib/napi/argv_float.h"
+#include "stdlib/napi/create_double.h"
+#include <node_api.h>
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 4 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_FLOAT( env, correction, argv, 1 );
+	STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 2 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_snanstdevch( N, correction, X, stride ), v );
+	return v;
+}
+
+STDLIB_NAPI_MODULE_EXPORT_FCN( addon )
diff --git a/lib/node_modules/@stdlib/stats/base/snanstdevch/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/snanstdevch/src/addon.cpp
deleted file mode 100644
index ff8de9c5c6d6..000000000000
--- a/lib/node_modules/@stdlib/stats/base/snanstdevch/src/addon.cpp
+++ /dev/null
@@ -1,130 +0,0 @@
-/**
-* @license Apache-2.0
-*
-* Copyright (c) 2020 The Stdlib Authors.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-*    http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-
-#include "stdlib/stats/base/snanstdevch.h"
-#include <node_api.h>
-#include <stdint.h>
-#include <stdlib.h>
-#include <stdbool.h>
-#include <assert.h>
-
-/**
-* Add-on namespace.
-*/
-namespace stdlib_stats_base_snanstdevch {
-
-	/**
-	* Computes the standard deviation of a single-precision floating-point strided array ignoring `NaN` values and using a one-pass trial mean algorithm.
-	*
-	* ## Notes
-	*
-	* -   When called from JavaScript, the function expects four arguments:
-	*
-	*     -   `N`: number of indexed elements
-	*     -   `correction`: degrees of freedom adjustment
-	*     -   `X`: input array
-	*     -   `stride`: stride length
-	*/
-	napi_value node_snanstdevch( napi_env env, napi_callback_info info ) {
-		napi_status status;
-
-		size_t argc = 4;
-		napi_value argv[ 4 ];
-		status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr );
-		assert( status == napi_ok );
-
-		if ( argc < 4 ) {
-			napi_throw_error( env, nullptr, "invalid invocation. Must provide 4 arguments." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype0;
-		status = napi_typeof( env, argv[ 0 ], &vtype0 );
-		assert( status == napi_ok );
-		if ( vtype0 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype1;
-		status = napi_typeof( env, argv[ 1 ], &vtype1 );
-		assert( status == napi_ok );
-		if ( vtype1 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." );
-			return nullptr;
-		}
-
-		bool res;
-		status = napi_is_typedarray( env, argv[ 2 ], &res );
-		assert( status == napi_ok );
-		if ( res == false ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype3;
-		status = napi_typeof( env, argv[ 3 ], &vtype3 );
-		assert( status == napi_ok );
-		if ( vtype3 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." );
-			return nullptr;
-		}
-
-		int64_t N;
-		status = napi_get_value_int64( env, argv[ 0 ], &N );
-		assert( status == napi_ok );
-
-		double correction;
-		status = napi_get_value_double( env, argv[ 1 ], &correction );
-		assert( status == napi_ok );
-
-		int64_t stride;
-		status = napi_get_value_int64( env, argv[ 3 ], &stride );
-		assert( status == napi_ok );
-
-		napi_typedarray_type vtype2;
-		size_t xlen;
-		void *X;
-		status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr );
-		assert( status == napi_ok );
-		if ( vtype2 != napi_float32_array ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." );
-			return nullptr;
-		}
-		if ( (N-1)*llabs(stride) >= (int64_t)xlen ) {
-			napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." );
-			return nullptr;
-		}
-
-		napi_value v;
-		status = napi_create_double( env, (double)stdlib_strided_snanstdevch( N, (float)correction, (float *)X, stride ), &v );
-		assert( status == napi_ok );
-
-		return v;
-	}
-
-	napi_value Init( napi_env env, napi_value exports ) {
-		napi_status status;
-		napi_value fcn;
-		status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_snanstdevch, NULL, &fcn );
-		assert( status == napi_ok );
-		return fcn;
-	}
-
-	NAPI_MODULE( NODE_GYP_MODULE_NAME, Init )
-} // end namespace stdlib_stats_base_snanstdevch

From 64a5d93971ef49adef45146bd07eeb21b2922632 Mon Sep 17 00:00:00 2001
From: Dhruv/ <154677013+DhruvArvindSingh@users.noreply.github.com>
Date: Sat, 4 Jan 2025 02:00:18 +0530
Subject: [PATCH 70/87] refactor: update `stats/base/snanstdevwd` native addon
 from C++ to C

PR-URL: https://github.com/stdlib-js/stdlib/pull/4473
Reviewed-by: Athan Reines <kgryte@gmail.com>
---
 .../stats/base/snanstdevwd/include.gypi       |   2 +-
 .../stats/base/snanstdevwd/manifest.json      |  43 +++++-
 .../stats/base/snanstdevwd/src/addon.c        |  45 ++++++
 .../stats/base/snanstdevwd/src/addon.cpp      | 130 ------------------
 4 files changed, 88 insertions(+), 132 deletions(-)
 create mode 100644 lib/node_modules/@stdlib/stats/base/snanstdevwd/src/addon.c
 delete mode 100644 lib/node_modules/@stdlib/stats/base/snanstdevwd/src/addon.cpp

diff --git a/lib/node_modules/@stdlib/stats/base/snanstdevwd/include.gypi b/lib/node_modules/@stdlib/stats/base/snanstdevwd/include.gypi
index 868c5c12e852..26476a8c2655 100644
--- a/lib/node_modules/@stdlib/stats/base/snanstdevwd/include.gypi
+++ b/lib/node_modules/@stdlib/stats/base/snanstdevwd/include.gypi
@@ -36,7 +36,7 @@
 
     # Source files:
     'src_files': [
-      '<(src_dir)/addon.cpp',
+      '<(src_dir)/addon.c',
       '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).src; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
     ],
 
diff --git a/lib/node_modules/@stdlib/stats/base/snanstdevwd/manifest.json b/lib/node_modules/@stdlib/stats/base/snanstdevwd/manifest.json
index 2951f4643505..6a91361fc23d 100644
--- a/lib/node_modules/@stdlib/stats/base/snanstdevwd/manifest.json
+++ b/lib/node_modules/@stdlib/stats/base/snanstdevwd/manifest.json
@@ -1,5 +1,7 @@
 {
-  "options": {},
+  "options": {
+    "task": "build"
+  },
   "fields": [
     {
       "field": "src",
@@ -24,6 +26,45 @@
   ],
   "confs": [
     {
+      "task": "build",
+      "src": [
+        "./src/snanstdevwd.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [
+        "-lm"
+      ],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/napi/export",
+        "@stdlib/napi/argv",
+        "@stdlib/napi/argv-int64",
+        "@stdlib/napi/argv-float",
+        "@stdlib/napi/argv-strided-float32array",
+        "@stdlib/stats/base/snanvariancewd",
+        "@stdlib/napi/create-double"
+      ]
+    },
+    {
+      "task": "benchmark",
+      "src": [
+        "./src/snanstdevwd.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [
+        "-lm"
+      ],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/stats/base/snanvariancewd"
+      ]
+    },
+    {
+      "task": "examples",
       "src": [
         "./src/snanstdevwd.c"
       ],
diff --git a/lib/node_modules/@stdlib/stats/base/snanstdevwd/src/addon.c b/lib/node_modules/@stdlib/stats/base/snanstdevwd/src/addon.c
new file mode 100644
index 000000000000..e5709d9f7278
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/snanstdevwd/src/addon.c
@@ -0,0 +1,45 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/snanstdevwd.h"
+#include "stdlib/napi/export.h"
+#include "stdlib/napi/argv.h"
+#include "stdlib/napi/argv_int64.h"
+#include "stdlib/napi/argv_float.h"
+#include "stdlib/napi/argv_strided_float32array.h"
+#include "stdlib/napi/create_double.h"
+#include <node_api.h>
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 4 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_FLOAT( env, correction, argv, 1 );
+	STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 2 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_snanstdevwd( N, correction, X, stride ), v );
+	return v;
+}
+
+STDLIB_NAPI_MODULE_EXPORT_FCN( addon )
diff --git a/lib/node_modules/@stdlib/stats/base/snanstdevwd/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/snanstdevwd/src/addon.cpp
deleted file mode 100644
index 1da417d16c69..000000000000
--- a/lib/node_modules/@stdlib/stats/base/snanstdevwd/src/addon.cpp
+++ /dev/null
@@ -1,130 +0,0 @@
-/**
-* @license Apache-2.0
-*
-* Copyright (c) 2020 The Stdlib Authors.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-*    http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-
-#include "stdlib/stats/base/snanstdevwd.h"
-#include <node_api.h>
-#include <stdint.h>
-#include <stdlib.h>
-#include <stdbool.h>
-#include <assert.h>
-
-/**
-* Add-on namespace.
-*/
-namespace stdlib_stats_base_snanstdevwd {
-
-	/**
-	* Computes the standard deviation of a single-precision floating-point strided array ignoring `NaN` values and using Welford's algorithm.
-	*
-	* ## Notes
-	*
-	* -   When called from JavaScript, the function expects four arguments:
-	*
-	*     -   `N`: number of indexed elements
-	*     -   `correction`: degrees of freedom adjustment
-	*     -   `X`: input array
-	*     -   `stride`: stride length
-	*/
-	napi_value node_snanstdevwd( napi_env env, napi_callback_info info ) {
-		napi_status status;
-
-		size_t argc = 4;
-		napi_value argv[ 4 ];
-		status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr );
-		assert( status == napi_ok );
-
-		if ( argc < 4 ) {
-			napi_throw_error( env, nullptr, "invalid invocation. Must provide 4 arguments." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype0;
-		status = napi_typeof( env, argv[ 0 ], &vtype0 );
-		assert( status == napi_ok );
-		if ( vtype0 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype1;
-		status = napi_typeof( env, argv[ 1 ], &vtype1 );
-		assert( status == napi_ok );
-		if ( vtype1 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." );
-			return nullptr;
-		}
-
-		bool res;
-		status = napi_is_typedarray( env, argv[ 2 ], &res );
-		assert( status == napi_ok );
-		if ( res == false ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype3;
-		status = napi_typeof( env, argv[ 3 ], &vtype3 );
-		assert( status == napi_ok );
-		if ( vtype3 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." );
-			return nullptr;
-		}
-
-		int64_t N;
-		status = napi_get_value_int64( env, argv[ 0 ], &N );
-		assert( status == napi_ok );
-
-		double correction;
-		status = napi_get_value_double( env, argv[ 1 ], &correction );
-		assert( status == napi_ok );
-
-		int64_t stride;
-		status = napi_get_value_int64( env, argv[ 3 ], &stride );
-		assert( status == napi_ok );
-
-		napi_typedarray_type vtype2;
-		size_t xlen;
-		void *X;
-		status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr );
-		assert( status == napi_ok );
-		if ( vtype2 != napi_float32_array ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." );
-			return nullptr;
-		}
-		if ( (N-1)*llabs(stride) >= (int64_t)xlen ) {
-			napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." );
-			return nullptr;
-		}
-
-		napi_value v;
-		status = napi_create_double( env, (double)stdlib_strided_snanstdevwd( N, (float)correction, (float *)X, stride ), &v );
-		assert( status == napi_ok );
-
-		return v;
-	}
-
-	napi_value Init( napi_env env, napi_value exports ) {
-		napi_status status;
-		napi_value fcn;
-		status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_snanstdevwd, NULL, &fcn );
-		assert( status == napi_ok );
-		return fcn;
-	}
-
-	NAPI_MODULE( NODE_GYP_MODULE_NAME, Init )
-} // end namespace stdlib_stats_base_snanstdevwd

From e04b98e4c09e3aa7d4b35193dab677ac3e6bafb1 Mon Sep 17 00:00:00 2001
From: Dhruv/ <154677013+DhruvArvindSingh@users.noreply.github.com>
Date: Sat, 4 Jan 2025 02:01:43 +0530
Subject: [PATCH 71/87] refactor: update `stats/base/snanvariancewd` native
 addon from C++ to C

PR-URL: https://github.com/stdlib-js/stdlib/pull/4504
Reviewed-by: Athan Reines <kgryte@gmail.com>
---
 .../stats/base/snanvariancewd/include.gypi    |   2 +-
 .../stats/base/snanvariancewd/manifest.json   |  40 +++++-
 .../stats/base/snanvariancewd/src/addon.c     |  45 ++++++
 .../stats/base/snanvariancewd/src/addon.cpp   | 130 ------------------
 4 files changed, 85 insertions(+), 132 deletions(-)
 create mode 100644 lib/node_modules/@stdlib/stats/base/snanvariancewd/src/addon.c
 delete mode 100644 lib/node_modules/@stdlib/stats/base/snanvariancewd/src/addon.cpp

diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancewd/include.gypi b/lib/node_modules/@stdlib/stats/base/snanvariancewd/include.gypi
index 868c5c12e852..26476a8c2655 100644
--- a/lib/node_modules/@stdlib/stats/base/snanvariancewd/include.gypi
+++ b/lib/node_modules/@stdlib/stats/base/snanvariancewd/include.gypi
@@ -36,7 +36,7 @@
 
     # Source files:
     'src_files': [
-      '<(src_dir)/addon.cpp',
+      '<(src_dir)/addon.c',
       '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).src; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
     ],
 
diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancewd/manifest.json b/lib/node_modules/@stdlib/stats/base/snanvariancewd/manifest.json
index b58d3eebb989..9ff9b43cb370 100644
--- a/lib/node_modules/@stdlib/stats/base/snanvariancewd/manifest.json
+++ b/lib/node_modules/@stdlib/stats/base/snanvariancewd/manifest.json
@@ -1,5 +1,7 @@
 {
-  "options": {},
+  "options": {
+    "task": "build"
+  },
   "fields": [
     {
       "field": "src",
@@ -24,6 +26,42 @@
   ],
   "confs": [
     {
+      "task": "build",
+      "src": [
+        "./src/snanvariancewd.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [
+        "-lm"
+      ],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/napi/export",
+        "@stdlib/napi/argv",
+        "@stdlib/napi/argv-int64",
+        "@stdlib/napi/argv-float",
+        "@stdlib/napi/argv-strided-float32array",
+        "@stdlib/napi/create-double"
+      ]
+    },
+    {
+      "task": "benchmark",
+      "src": [
+        "./src/snanvariancewd.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [
+        "-lm"
+      ],
+      "libpath": [],
+      "dependencies": []
+    },
+    {
+      "task": "examples",
       "src": [
         "./src/snanvariancewd.c"
       ],
diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancewd/src/addon.c b/lib/node_modules/@stdlib/stats/base/snanvariancewd/src/addon.c
new file mode 100644
index 000000000000..97c658d45c95
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/snanvariancewd/src/addon.c
@@ -0,0 +1,45 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/snanvariancewd.h"
+#include "stdlib/napi/export.h"
+#include "stdlib/napi/argv.h"
+#include "stdlib/napi/argv_int64.h"
+#include "stdlib/napi/argv_float.h"
+#include "stdlib/napi/argv_strided_float32array.h"
+#include "stdlib/napi/create_double.h"
+#include <node_api.h>
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 4 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_FLOAT( env, correction, argv, 1 );
+	STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 2 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_snanvariancewd( N, correction, X, stride ), v );
+	return v;
+}
+
+STDLIB_NAPI_MODULE_EXPORT_FCN( addon )
diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancewd/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/snanvariancewd/src/addon.cpp
deleted file mode 100644
index 7903326e673f..000000000000
--- a/lib/node_modules/@stdlib/stats/base/snanvariancewd/src/addon.cpp
+++ /dev/null
@@ -1,130 +0,0 @@
-/**
-* @license Apache-2.0
-*
-* Copyright (c) 2020 The Stdlib Authors.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-*    http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-
-#include "stdlib/stats/base/snanvariancewd.h"
-#include <node_api.h>
-#include <stdint.h>
-#include <stdlib.h>
-#include <stdbool.h>
-#include <assert.h>
-
-/**
-* Add-on namespace.
-*/
-namespace stdlib_stats_base_snanvariancewd {
-
-	/**
-	* Computes the variance of a single-precision floating-point strided array ignoring `NaN` values and using Welford's algorithm.
-	*
-	* ## Notes
-	*
-	* -   When called from JavaScript, the function expects four arguments:
-	*
-	*     -   `N`: number of indexed elements
-	*     -   `correction`: degrees of freedom adjustment
-	*     -   `X`: input array
-	*     -   `stride`: stride length
-	*/
-	napi_value node_snanvariancewd( napi_env env, napi_callback_info info ) {
-		napi_status status;
-
-		size_t argc = 4;
-		napi_value argv[ 4 ];
-		status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr );
-		assert( status == napi_ok );
-
-		if ( argc < 4 ) {
-			napi_throw_error( env, nullptr, "invalid invocation. Must provide 4 arguments." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype0;
-		status = napi_typeof( env, argv[ 0 ], &vtype0 );
-		assert( status == napi_ok );
-		if ( vtype0 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype1;
-		status = napi_typeof( env, argv[ 1 ], &vtype1 );
-		assert( status == napi_ok );
-		if ( vtype1 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." );
-			return nullptr;
-		}
-
-		bool res;
-		status = napi_is_typedarray( env, argv[ 2 ], &res );
-		assert( status == napi_ok );
-		if ( res == false ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype3;
-		status = napi_typeof( env, argv[ 3 ], &vtype3 );
-		assert( status == napi_ok );
-		if ( vtype3 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." );
-			return nullptr;
-		}
-
-		int64_t N;
-		status = napi_get_value_int64( env, argv[ 0 ], &N );
-		assert( status == napi_ok );
-
-		double correction;
-		status = napi_get_value_double( env, argv[ 1 ], &correction );
-		assert( status == napi_ok );
-
-		int64_t stride;
-		status = napi_get_value_int64( env, argv[ 3 ], &stride );
-		assert( status == napi_ok );
-
-		napi_typedarray_type vtype2;
-		size_t xlen;
-		void *X;
-		status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr );
-		assert( status == napi_ok );
-		if ( vtype2 != napi_float32_array ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." );
-			return nullptr;
-		}
-		if ( (N-1)*llabs(stride) >= (int64_t)xlen ) {
-			napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." );
-			return nullptr;
-		}
-
-		napi_value v;
-		status = napi_create_double( env, (double)stdlib_strided_snanvariancewd( N, (float)correction, (float *)X, stride ), &v );
-		assert( status == napi_ok );
-
-		return v;
-	}
-
-	napi_value Init( napi_env env, napi_value exports ) {
-		napi_status status;
-		napi_value fcn;
-		status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_snanvariancewd, NULL, &fcn );
-		assert( status == napi_ok );
-		return fcn;
-	}
-
-	NAPI_MODULE( NODE_GYP_MODULE_NAME, Init )
-} // end namespace stdlib_stats_base_snanvariancewd

From d9ddb96dd041404d7d7cf59e3f25cdb284621e6e Mon Sep 17 00:00:00 2001
From: Dhruv/ <154677013+DhruvArvindSingh@users.noreply.github.com>
Date: Sat, 4 Jan 2025 02:02:59 +0530
Subject: [PATCH 72/87] refactor: update `stats/base/snanvariancetk` native
 addon from C++ to C

PR-URL: https://github.com/stdlib-js/stdlib/pull/4505
Reviewed-by: Athan Reines <kgryte@gmail.com>
---
 .../stats/base/snanvariancetk/include.gypi    |   2 +-
 .../stats/base/snanvariancetk/manifest.json   |  41 +++++-
 .../stats/base/snanvariancetk/src/addon.c     |  45 ++++++
 .../stats/base/snanvariancetk/src/addon.cpp   | 130 ------------------
 4 files changed, 86 insertions(+), 132 deletions(-)
 create mode 100644 lib/node_modules/@stdlib/stats/base/snanvariancetk/src/addon.c
 delete mode 100644 lib/node_modules/@stdlib/stats/base/snanvariancetk/src/addon.cpp

diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancetk/include.gypi b/lib/node_modules/@stdlib/stats/base/snanvariancetk/include.gypi
index 868c5c12e852..26476a8c2655 100644
--- a/lib/node_modules/@stdlib/stats/base/snanvariancetk/include.gypi
+++ b/lib/node_modules/@stdlib/stats/base/snanvariancetk/include.gypi
@@ -36,7 +36,7 @@
 
     # Source files:
     'src_files': [
-      '<(src_dir)/addon.cpp',
+      '<(src_dir)/addon.c',
       '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).src; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
     ],
 
diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancetk/manifest.json b/lib/node_modules/@stdlib/stats/base/snanvariancetk/manifest.json
index 05cc73770f2e..f8a15e9e4331 100644
--- a/lib/node_modules/@stdlib/stats/base/snanvariancetk/manifest.json
+++ b/lib/node_modules/@stdlib/stats/base/snanvariancetk/manifest.json
@@ -1,5 +1,7 @@
 {
-  "options": {},
+  "options": {
+    "task": "build"
+  },
   "fields": [
     {
       "field": "src",
@@ -24,6 +26,43 @@
   ],
   "confs": [
     {
+      "task": "build",
+      "src": [
+        "./src/snanvariancetk.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [
+        "-lm"
+      ],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/napi/export",
+        "@stdlib/napi/argv",
+        "@stdlib/napi/argv-int64",
+        "@stdlib/napi/argv-float",
+        "@stdlib/napi/argv-strided-float32array",
+        "@stdlib/napi/create-double"
+      ]
+    },
+    {
+      "task": "benchmark",
+      "src": [
+        "./src/snanvariancetk.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [
+        "-lm"
+      ],
+      "libpath": [],
+      "dependencies": [
+      ]
+    },
+    {
+      "task": "examples",
       "src": [
         "./src/snanvariancetk.c"
       ],
diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancetk/src/addon.c b/lib/node_modules/@stdlib/stats/base/snanvariancetk/src/addon.c
new file mode 100644
index 000000000000..9019b78789e3
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/snanvariancetk/src/addon.c
@@ -0,0 +1,45 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/snanvariancetk.h"
+#include "stdlib/napi/export.h"
+#include "stdlib/napi/argv.h"
+#include "stdlib/napi/argv_int64.h"
+#include "stdlib/napi/argv_float.h"
+#include "stdlib/napi/argv_strided_float32array.h"
+#include "stdlib/napi/create_double.h"
+#include <node_api.h>
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 4 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_FLOAT( env, correction, argv, 1 );
+	STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 2 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_snanvariancetk( N, correction, X, stride ), v );
+	return v;
+}
+
+STDLIB_NAPI_MODULE_EXPORT_FCN( addon )
diff --git a/lib/node_modules/@stdlib/stats/base/snanvariancetk/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/snanvariancetk/src/addon.cpp
deleted file mode 100644
index d3c973cef0e7..000000000000
--- a/lib/node_modules/@stdlib/stats/base/snanvariancetk/src/addon.cpp
+++ /dev/null
@@ -1,130 +0,0 @@
-/**
-* @license Apache-2.0
-*
-* Copyright (c) 2020 The Stdlib Authors.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-*    http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-
-#include "stdlib/stats/base/snanvariancetk.h"
-#include <node_api.h>
-#include <stdint.h>
-#include <stdlib.h>
-#include <stdbool.h>
-#include <assert.h>
-
-/**
-* Add-on namespace.
-*/
-namespace stdlib_stats_base_snanvariancetk {
-
-	/**
-	* Computes the variance of a single-precision floating-point strided array ignoring `NaN` values and using a one-pass textbook algorithm.
-	*
-	* ## Notes
-	*
-	* -   When called from JavaScript, the function expects four arguments:
-	*
-	*     -   `N`: number of indexed elements
-	*     -   `correction`: degrees of freedom adjustment
-	*     -   `X`: input array
-	*     -   `stride`: stride length
-	*/
-	napi_value node_snanvariancetk( napi_env env, napi_callback_info info ) {
-		napi_status status;
-
-		size_t argc = 4;
-		napi_value argv[ 4 ];
-		status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr );
-		assert( status == napi_ok );
-
-		if ( argc < 4 ) {
-			napi_throw_error( env, nullptr, "invalid invocation. Must provide 4 arguments." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype0;
-		status = napi_typeof( env, argv[ 0 ], &vtype0 );
-		assert( status == napi_ok );
-		if ( vtype0 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype1;
-		status = napi_typeof( env, argv[ 1 ], &vtype1 );
-		assert( status == napi_ok );
-		if ( vtype1 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." );
-			return nullptr;
-		}
-
-		bool res;
-		status = napi_is_typedarray( env, argv[ 2 ], &res );
-		assert( status == napi_ok );
-		if ( res == false ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype3;
-		status = napi_typeof( env, argv[ 3 ], &vtype3 );
-		assert( status == napi_ok );
-		if ( vtype3 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." );
-			return nullptr;
-		}
-
-		int64_t N;
-		status = napi_get_value_int64( env, argv[ 0 ], &N );
-		assert( status == napi_ok );
-
-		double correction;
-		status = napi_get_value_double( env, argv[ 1 ], &correction );
-		assert( status == napi_ok );
-
-		int64_t stride;
-		status = napi_get_value_int64( env, argv[ 3 ], &stride );
-		assert( status == napi_ok );
-
-		napi_typedarray_type vtype2;
-		size_t xlen;
-		void *X;
-		status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr );
-		assert( status == napi_ok );
-		if ( vtype2 != napi_float32_array ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." );
-			return nullptr;
-		}
-		if ( (N-1)*llabs(stride) >= (int64_t)xlen ) {
-			napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." );
-			return nullptr;
-		}
-
-		napi_value v;
-		status = napi_create_double( env, (double)stdlib_strided_snanvariancetk( N, (float)correction, (float *)X, stride ), &v );
-		assert( status == napi_ok );
-
-		return v;
-	}
-
-	napi_value Init( napi_env env, napi_value exports ) {
-		napi_status status;
-		napi_value fcn;
-		status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_snanvariancetk, NULL, &fcn );
-		assert( status == napi_ok );
-		return fcn;
-	}
-
-	NAPI_MODULE( NODE_GYP_MODULE_NAME, Init )
-} // end namespace stdlib_stats_base_snanvariancetk

From aa4b857746d4a8aa7aa76b18ed1f38a343bf79df Mon Sep 17 00:00:00 2001
From: Dhruv/ <154677013+DhruvArvindSingh@users.noreply.github.com>
Date: Sat, 4 Jan 2025 02:04:27 +0530
Subject: [PATCH 73/87] refactor: update `stats/base/sstdev` native addon from
 C++ to C

PR-URL: https://github.com/stdlib-js/stdlib/pull/4507
Reviewed-by: Athan Reines <kgryte@gmail.com>
---
 .../@stdlib/stats/base/sstdev/include.gypi    |   2 +-
 .../@stdlib/stats/base/sstdev/manifest.json   |  43 +++++-
 .../@stdlib/stats/base/sstdev/src/addon.c     |  45 ++++++
 .../@stdlib/stats/base/sstdev/src/addon.cpp   | 130 ------------------
 4 files changed, 88 insertions(+), 132 deletions(-)
 create mode 100644 lib/node_modules/@stdlib/stats/base/sstdev/src/addon.c
 delete mode 100644 lib/node_modules/@stdlib/stats/base/sstdev/src/addon.cpp

diff --git a/lib/node_modules/@stdlib/stats/base/sstdev/include.gypi b/lib/node_modules/@stdlib/stats/base/sstdev/include.gypi
index 868c5c12e852..26476a8c2655 100644
--- a/lib/node_modules/@stdlib/stats/base/sstdev/include.gypi
+++ b/lib/node_modules/@stdlib/stats/base/sstdev/include.gypi
@@ -36,7 +36,7 @@
 
     # Source files:
     'src_files': [
-      '<(src_dir)/addon.cpp',
+      '<(src_dir)/addon.c',
       '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).src; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
     ],
 
diff --git a/lib/node_modules/@stdlib/stats/base/sstdev/manifest.json b/lib/node_modules/@stdlib/stats/base/sstdev/manifest.json
index 993a3bb08359..1be2c722efaa 100644
--- a/lib/node_modules/@stdlib/stats/base/sstdev/manifest.json
+++ b/lib/node_modules/@stdlib/stats/base/sstdev/manifest.json
@@ -1,5 +1,7 @@
 {
-  "options": {},
+  "options": {
+    "task": "build"
+  },
   "fields": [
     {
       "field": "src",
@@ -24,6 +26,45 @@
   ],
   "confs": [
     {
+      "task": "build",
+      "src": [
+        "./src/sstdev.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [
+        "-lm"
+      ],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/napi/export",
+        "@stdlib/napi/argv",
+        "@stdlib/napi/argv-int64",
+        "@stdlib/napi/argv-float",
+        "@stdlib/napi/argv-strided-float32array",
+        "@stdlib/stats/base/sstdevpn",
+        "@stdlib/napi/create-double"
+      ]
+    },
+    {
+      "task": "benchmark",
+      "src": [
+        "./src/sstdev.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [
+        "-lm"
+      ],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/stats/base/sstdevpn"
+      ]
+    },
+    {
+      "task": "examples",
       "src": [
         "./src/sstdev.c"
       ],
diff --git a/lib/node_modules/@stdlib/stats/base/sstdev/src/addon.c b/lib/node_modules/@stdlib/stats/base/sstdev/src/addon.c
new file mode 100644
index 000000000000..4f07cd243d9c
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/sstdev/src/addon.c
@@ -0,0 +1,45 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/sstdev.h"
+#include "stdlib/napi/export.h"
+#include "stdlib/napi/argv.h"
+#include "stdlib/napi/argv_int64.h"
+#include "stdlib/napi/argv_float.h"
+#include "stdlib/napi/argv_strided_float32array.h"
+#include "stdlib/napi/create_double.h"
+#include <node_api.h>
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 4 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_FLOAT( env, correction, argv, 1 );
+	STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 2 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_sstdev( N, correction, X, stride ), v );
+	return v;
+}
+
+STDLIB_NAPI_MODULE_EXPORT_FCN( addon )
diff --git a/lib/node_modules/@stdlib/stats/base/sstdev/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/sstdev/src/addon.cpp
deleted file mode 100644
index 3bd3a912050e..000000000000
--- a/lib/node_modules/@stdlib/stats/base/sstdev/src/addon.cpp
+++ /dev/null
@@ -1,130 +0,0 @@
-/**
-* @license Apache-2.0
-*
-* Copyright (c) 2020 The Stdlib Authors.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-*    http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-
-#include "stdlib/stats/base/sstdev.h"
-#include <node_api.h>
-#include <stdint.h>
-#include <stdlib.h>
-#include <stdbool.h>
-#include <assert.h>
-
-/**
-* Add-on namespace.
-*/
-namespace stdlib_stats_base_sstdev {
-
-	/**
-	* Computes the standard deviation of a single-precision floating-point strided array.
-	*
-	* ## Notes
-	*
-	* -   When called from JavaScript, the function expects four arguments:
-	*
-	*     -   `N`: number of indexed elements
-	*     -   `correction`: degrees of freedom adjustment
-	*     -   `X`: input array
-	*     -   `stride`: stride length
-	*/
-	napi_value node_sstdev( napi_env env, napi_callback_info info ) {
-		napi_status status;
-
-		size_t argc = 4;
-		napi_value argv[ 4 ];
-		status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr );
-		assert( status == napi_ok );
-
-		if ( argc < 4 ) {
-			napi_throw_error( env, nullptr, "invalid invocation. Must provide 4 arguments." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype0;
-		status = napi_typeof( env, argv[ 0 ], &vtype0 );
-		assert( status == napi_ok );
-		if ( vtype0 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype1;
-		status = napi_typeof( env, argv[ 1 ], &vtype1 );
-		assert( status == napi_ok );
-		if ( vtype1 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." );
-			return nullptr;
-		}
-
-		bool res;
-		status = napi_is_typedarray( env, argv[ 2 ], &res );
-		assert( status == napi_ok );
-		if ( res == false ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype3;
-		status = napi_typeof( env, argv[ 3 ], &vtype3 );
-		assert( status == napi_ok );
-		if ( vtype3 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." );
-			return nullptr;
-		}
-
-		int64_t N;
-		status = napi_get_value_int64( env, argv[ 0 ], &N );
-		assert( status == napi_ok );
-
-		double correction;
-		status = napi_get_value_double( env, argv[ 1 ], &correction );
-		assert( status == napi_ok );
-
-		int64_t stride;
-		status = napi_get_value_int64( env, argv[ 3 ], &stride );
-		assert( status == napi_ok );
-
-		napi_typedarray_type vtype2;
-		size_t xlen;
-		void *X;
-		status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr );
-		assert( status == napi_ok );
-		if ( vtype2 != napi_float32_array ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." );
-			return nullptr;
-		}
-		if ( (N-1)*llabs(stride) >= (int64_t)xlen ) {
-			napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." );
-			return nullptr;
-		}
-
-		napi_value v;
-		status = napi_create_double( env, (double)stdlib_strided_sstdev( N, (float)correction, (float *)X, stride ), &v );
-		assert( status == napi_ok );
-
-		return v;
-	}
-
-	napi_value Init( napi_env env, napi_value exports ) {
-		napi_status status;
-		napi_value fcn;
-		status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_sstdev, NULL, &fcn );
-		assert( status == napi_ok );
-		return fcn;
-	}
-
-	NAPI_MODULE( NODE_GYP_MODULE_NAME, Init )
-} // end namespace stdlib_stats_base_sstdev

From d11fe8d72c3d987750761f13a340dd3cc21bdbcf Mon Sep 17 00:00:00 2001
From: Dhruv/ <154677013+DhruvArvindSingh@users.noreply.github.com>
Date: Sat, 4 Jan 2025 02:06:00 +0530
Subject: [PATCH 74/87] refactor: update `stats/base/sstdevpn` native addon
 from C++ to C

PR-URL: https://github.com/stdlib-js/stdlib/pull/4509
Reviewed-by: Athan Reines <kgryte@gmail.com>
---
 .../@stdlib/stats/base/sstdevpn/include.gypi  |   2 +-
 .../@stdlib/stats/base/sstdevpn/manifest.json |  43 +++++-
 .../@stdlib/stats/base/sstdevpn/src/addon.c   |  45 ++++++
 .../@stdlib/stats/base/sstdevpn/src/addon.cpp | 130 ------------------
 4 files changed, 88 insertions(+), 132 deletions(-)
 create mode 100644 lib/node_modules/@stdlib/stats/base/sstdevpn/src/addon.c
 delete mode 100644 lib/node_modules/@stdlib/stats/base/sstdevpn/src/addon.cpp

diff --git a/lib/node_modules/@stdlib/stats/base/sstdevpn/include.gypi b/lib/node_modules/@stdlib/stats/base/sstdevpn/include.gypi
index 868c5c12e852..26476a8c2655 100644
--- a/lib/node_modules/@stdlib/stats/base/sstdevpn/include.gypi
+++ b/lib/node_modules/@stdlib/stats/base/sstdevpn/include.gypi
@@ -36,7 +36,7 @@
 
     # Source files:
     'src_files': [
-      '<(src_dir)/addon.cpp',
+      '<(src_dir)/addon.c',
       '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).src; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
     ],
 
diff --git a/lib/node_modules/@stdlib/stats/base/sstdevpn/manifest.json b/lib/node_modules/@stdlib/stats/base/sstdevpn/manifest.json
index 275dba8e56f7..054ff3c2f85c 100644
--- a/lib/node_modules/@stdlib/stats/base/sstdevpn/manifest.json
+++ b/lib/node_modules/@stdlib/stats/base/sstdevpn/manifest.json
@@ -1,5 +1,7 @@
 {
-  "options": {},
+  "options": {
+    "task": "build"
+  },
   "fields": [
     {
       "field": "src",
@@ -24,6 +26,45 @@
   ],
   "confs": [
     {
+      "task": "build",
+      "src": [
+        "./src/sstdevpn.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [
+        "-lm"
+      ],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/napi/export",
+        "@stdlib/napi/argv",
+        "@stdlib/napi/argv-int64",
+        "@stdlib/napi/argv-float",
+        "@stdlib/napi/argv-strided-float32array",
+        "@stdlib/stats/base/svariancepn",
+        "@stdlib/napi/create-double"
+      ]
+    },
+    {
+      "task": "benchmark",
+      "src": [
+        "./src/sstdevpn.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [
+        "-lm"
+      ],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/stats/base/svariancepn"
+      ]
+    },
+    {
+      "task": "examples",
       "src": [
         "./src/sstdevpn.c"
       ],
diff --git a/lib/node_modules/@stdlib/stats/base/sstdevpn/src/addon.c b/lib/node_modules/@stdlib/stats/base/sstdevpn/src/addon.c
new file mode 100644
index 000000000000..552c639215ed
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/sstdevpn/src/addon.c
@@ -0,0 +1,45 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/sstdevpn.h"
+#include "stdlib/napi/export.h"
+#include "stdlib/napi/argv.h"
+#include "stdlib/napi/argv_int64.h"
+#include "stdlib/napi/argv_float.h"
+#include "stdlib/napi/argv_strided_float32array.h"
+#include "stdlib/napi/create_double.h"
+#include <node_api.h>
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 4 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_FLOAT( env, correction, argv, 1 );
+	STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 2 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_sstdevpn( N, correction, X, stride ), v );
+	return v;
+}
+
+STDLIB_NAPI_MODULE_EXPORT_FCN( addon )
diff --git a/lib/node_modules/@stdlib/stats/base/sstdevpn/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/sstdevpn/src/addon.cpp
deleted file mode 100644
index a1e51a8fb99a..000000000000
--- a/lib/node_modules/@stdlib/stats/base/sstdevpn/src/addon.cpp
+++ /dev/null
@@ -1,130 +0,0 @@
-/**
-* @license Apache-2.0
-*
-* Copyright (c) 2020 The Stdlib Authors.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-*    http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-
-#include "stdlib/stats/base/sstdevpn.h"
-#include <node_api.h>
-#include <stdint.h>
-#include <stdlib.h>
-#include <stdbool.h>
-#include <assert.h>
-
-/**
-* Add-on namespace.
-*/
-namespace stdlib_stats_base_sstdevpn {
-
-	/**
-	* Computes the standard deviation of a single-precision floating-point strided array using a two-pass algorithm.
-	*
-	* ## Notes
-	*
-	* -   When called from JavaScript, the function expects four arguments:
-	*
-	*     -   `N`: number of indexed elements
-	*     -   `correction`: degrees of freedom adjustment
-	*     -   `X`: input array
-	*     -   `stride`: stride length
-	*/
-	napi_value node_sstdevpn( napi_env env, napi_callback_info info ) {
-		napi_status status;
-
-		size_t argc = 4;
-		napi_value argv[ 4 ];
-		status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr );
-		assert( status == napi_ok );
-
-		if ( argc < 4 ) {
-			napi_throw_error( env, nullptr, "invalid invocation. Must provide 4 arguments." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype0;
-		status = napi_typeof( env, argv[ 0 ], &vtype0 );
-		assert( status == napi_ok );
-		if ( vtype0 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype1;
-		status = napi_typeof( env, argv[ 1 ], &vtype1 );
-		assert( status == napi_ok );
-		if ( vtype1 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." );
-			return nullptr;
-		}
-
-		bool res;
-		status = napi_is_typedarray( env, argv[ 2 ], &res );
-		assert( status == napi_ok );
-		if ( res == false ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype3;
-		status = napi_typeof( env, argv[ 3 ], &vtype3 );
-		assert( status == napi_ok );
-		if ( vtype3 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." );
-			return nullptr;
-		}
-
-		int64_t N;
-		status = napi_get_value_int64( env, argv[ 0 ], &N );
-		assert( status == napi_ok );
-
-		double correction;
-		status = napi_get_value_double( env, argv[ 1 ], &correction );
-		assert( status == napi_ok );
-
-		int64_t stride;
-		status = napi_get_value_int64( env, argv[ 3 ], &stride );
-		assert( status == napi_ok );
-
-		napi_typedarray_type vtype2;
-		size_t xlen;
-		void *X;
-		status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr );
-		assert( status == napi_ok );
-		if ( vtype2 != napi_float32_array ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." );
-			return nullptr;
-		}
-		if ( (N-1)*llabs(stride) >= (int64_t)xlen ) {
-			napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." );
-			return nullptr;
-		}
-
-		napi_value v;
-		status = napi_create_double( env, (double)stdlib_strided_sstdevpn( N, (float)correction, (float *)X, stride ), &v );
-		assert( status == napi_ok );
-
-		return v;
-	}
-
-	napi_value Init( napi_env env, napi_value exports ) {
-		napi_status status;
-		napi_value fcn;
-		status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_sstdevpn, NULL, &fcn );
-		assert( status == napi_ok );
-		return fcn;
-	}
-
-	NAPI_MODULE( NODE_GYP_MODULE_NAME, Init )
-} // end namespace stdlib_stats_base_sstdevpn

From 6c99f7d5f2e06b7bad035507e3595e732719fa7d Mon Sep 17 00:00:00 2001
From: Dhruv/ <154677013+DhruvArvindSingh@users.noreply.github.com>
Date: Sat, 4 Jan 2025 02:07:07 +0530
Subject: [PATCH 75/87] refactor: update `stats/base/snanvarianceyc` native
 addon from C++ to C

PR-URL: https://github.com/stdlib-js/stdlib/pull/4511
Reviewed-by: Athan Reines <kgryte@gmail.com>
---
 .../stats/base/snanvarianceyc/include.gypi    |   2 +-
 .../stats/base/snanvarianceyc/manifest.json   |  40 +++++-
 .../stats/base/snanvarianceyc/src/addon.c     |  45 ++++++
 .../stats/base/snanvarianceyc/src/addon.cpp   | 130 ------------------
 4 files changed, 85 insertions(+), 132 deletions(-)
 create mode 100644 lib/node_modules/@stdlib/stats/base/snanvarianceyc/src/addon.c
 delete mode 100644 lib/node_modules/@stdlib/stats/base/snanvarianceyc/src/addon.cpp

diff --git a/lib/node_modules/@stdlib/stats/base/snanvarianceyc/include.gypi b/lib/node_modules/@stdlib/stats/base/snanvarianceyc/include.gypi
index 868c5c12e852..26476a8c2655 100644
--- a/lib/node_modules/@stdlib/stats/base/snanvarianceyc/include.gypi
+++ b/lib/node_modules/@stdlib/stats/base/snanvarianceyc/include.gypi
@@ -36,7 +36,7 @@
 
     # Source files:
     'src_files': [
-      '<(src_dir)/addon.cpp',
+      '<(src_dir)/addon.c',
       '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).src; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
     ],
 
diff --git a/lib/node_modules/@stdlib/stats/base/snanvarianceyc/manifest.json b/lib/node_modules/@stdlib/stats/base/snanvarianceyc/manifest.json
index 9a17ed1bb885..bb20b350f5ee 100644
--- a/lib/node_modules/@stdlib/stats/base/snanvarianceyc/manifest.json
+++ b/lib/node_modules/@stdlib/stats/base/snanvarianceyc/manifest.json
@@ -1,5 +1,7 @@
 {
-  "options": {},
+  "options": {
+    "task": "build"
+  },
   "fields": [
     {
       "field": "src",
@@ -24,6 +26,42 @@
   ],
   "confs": [
     {
+      "task": "build",
+      "src": [
+        "./src/snanvarianceyc.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [
+        "-lm"
+      ],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/napi/export",
+        "@stdlib/napi/argv",
+        "@stdlib/napi/argv-int64",
+        "@stdlib/napi/argv-float",
+        "@stdlib/napi/argv-strided-float32array",
+        "@stdlib/napi/create-double"
+      ]
+    },
+    {
+      "task": "benchmark",
+      "src": [
+        "./src/snanvarianceyc.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [
+        "-lm"
+      ],
+      "libpath": [],
+      "dependencies": []
+    },
+    {
+      "task": "examples",
       "src": [
         "./src/snanvarianceyc.c"
       ],
diff --git a/lib/node_modules/@stdlib/stats/base/snanvarianceyc/src/addon.c b/lib/node_modules/@stdlib/stats/base/snanvarianceyc/src/addon.c
new file mode 100644
index 000000000000..d1257fb8dfe7
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/snanvarianceyc/src/addon.c
@@ -0,0 +1,45 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/snanvarianceyc.h"
+#include "stdlib/napi/export.h"
+#include "stdlib/napi/argv.h"
+#include "stdlib/napi/argv_int64.h"
+#include "stdlib/napi/argv_float.h"
+#include "stdlib/napi/argv_strided_float32array.h"
+#include "stdlib/napi/create_double.h"
+#include <node_api.h>
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 4 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_FLOAT( env, correction, argv, 1 );
+	STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 2 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_snanvarianceyc( N, correction, X, stride ), v );
+	return v;
+}
+
+STDLIB_NAPI_MODULE_EXPORT_FCN( addon )
diff --git a/lib/node_modules/@stdlib/stats/base/snanvarianceyc/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/snanvarianceyc/src/addon.cpp
deleted file mode 100644
index 3cc800e7bbbe..000000000000
--- a/lib/node_modules/@stdlib/stats/base/snanvarianceyc/src/addon.cpp
+++ /dev/null
@@ -1,130 +0,0 @@
-/**
-* @license Apache-2.0
-*
-* Copyright (c) 2020 The Stdlib Authors.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-*    http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-
-#include "stdlib/stats/base/snanvarianceyc.h"
-#include <node_api.h>
-#include <stdint.h>
-#include <stdlib.h>
-#include <stdbool.h>
-#include <assert.h>
-
-/**
-* Add-on namespace.
-*/
-namespace stdlib_stats_base_snanvarianceyc {
-
-	/**
-	* Computes the variance of a single-precision floating-point strided array ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and Cramer.
-	*
-	* ## Notes
-	*
-	* -   When called from JavaScript, the function expects four arguments:
-	*
-	*     -   `N`: number of indexed elements
-	*     -   `correction`: degrees of freedom adjustment
-	*     -   `X`: input array
-	*     -   `stride`: stride length
-	*/
-	napi_value node_snanvarianceyc( napi_env env, napi_callback_info info ) {
-		napi_status status;
-
-		size_t argc = 4;
-		napi_value argv[ 4 ];
-		status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr );
-		assert( status == napi_ok );
-
-		if ( argc < 4 ) {
-			napi_throw_error( env, nullptr, "invalid invocation. Must provide 4 arguments." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype0;
-		status = napi_typeof( env, argv[ 0 ], &vtype0 );
-		assert( status == napi_ok );
-		if ( vtype0 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype1;
-		status = napi_typeof( env, argv[ 1 ], &vtype1 );
-		assert( status == napi_ok );
-		if ( vtype1 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." );
-			return nullptr;
-		}
-
-		bool res;
-		status = napi_is_typedarray( env, argv[ 2 ], &res );
-		assert( status == napi_ok );
-		if ( res == false ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype3;
-		status = napi_typeof( env, argv[ 3 ], &vtype3 );
-		assert( status == napi_ok );
-		if ( vtype3 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." );
-			return nullptr;
-		}
-
-		int64_t N;
-		status = napi_get_value_int64( env, argv[ 0 ], &N );
-		assert( status == napi_ok );
-
-		double correction;
-		status = napi_get_value_double( env, argv[ 1 ], &correction );
-		assert( status == napi_ok );
-
-		int64_t stride;
-		status = napi_get_value_int64( env, argv[ 3 ], &stride );
-		assert( status == napi_ok );
-
-		napi_typedarray_type vtype2;
-		size_t xlen;
-		void *X;
-		status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr );
-		assert( status == napi_ok );
-		if ( vtype2 != napi_float32_array ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." );
-			return nullptr;
-		}
-		if ( (N-1)*llabs(stride) >= (int64_t)xlen ) {
-			napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." );
-			return nullptr;
-		}
-
-		napi_value v;
-		status = napi_create_double( env, (double)stdlib_strided_snanvarianceyc( N, (float)correction, (float *)X, stride ), &v );
-		assert( status == napi_ok );
-
-		return v;
-	}
-
-	napi_value Init( napi_env env, napi_value exports ) {
-		napi_status status;
-		napi_value fcn;
-		status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_snanvarianceyc, NULL, &fcn );
-		assert( status == napi_ok );
-		return fcn;
-	}
-
-	NAPI_MODULE( NODE_GYP_MODULE_NAME, Init )
-} // end namespace stdlib_stats_base_snanvarianceyc

From 32e6c57271021df8a78dc8441cb71ef2f5bb5c84 Mon Sep 17 00:00:00 2001
From: Dhruv/ <154677013+DhruvArvindSingh@users.noreply.github.com>
Date: Sat, 4 Jan 2025 02:09:31 +0530
Subject: [PATCH 76/87] refactor: update `stats/base/sstdevch` native addon
 from C++ to C

PR-URL: https://github.com/stdlib-js/stdlib/pull/4508
Reviewed-by: Athan Reines <kgryte@gmail.com>
---
 .../@stdlib/stats/base/sstdevch/include.gypi  |   2 +-
 .../@stdlib/stats/base/sstdevch/manifest.json |  43 +++++-
 .../@stdlib/stats/base/sstdevch/src/addon.c   |  45 ++++++
 .../@stdlib/stats/base/sstdevch/src/addon.cpp | 130 ------------------
 4 files changed, 88 insertions(+), 132 deletions(-)
 create mode 100644 lib/node_modules/@stdlib/stats/base/sstdevch/src/addon.c
 delete mode 100644 lib/node_modules/@stdlib/stats/base/sstdevch/src/addon.cpp

diff --git a/lib/node_modules/@stdlib/stats/base/sstdevch/include.gypi b/lib/node_modules/@stdlib/stats/base/sstdevch/include.gypi
index 868c5c12e852..26476a8c2655 100644
--- a/lib/node_modules/@stdlib/stats/base/sstdevch/include.gypi
+++ b/lib/node_modules/@stdlib/stats/base/sstdevch/include.gypi
@@ -36,7 +36,7 @@
 
     # Source files:
     'src_files': [
-      '<(src_dir)/addon.cpp',
+      '<(src_dir)/addon.c',
       '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).src; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
     ],
 
diff --git a/lib/node_modules/@stdlib/stats/base/sstdevch/manifest.json b/lib/node_modules/@stdlib/stats/base/sstdevch/manifest.json
index a093653896c5..53509c94f6c5 100644
--- a/lib/node_modules/@stdlib/stats/base/sstdevch/manifest.json
+++ b/lib/node_modules/@stdlib/stats/base/sstdevch/manifest.json
@@ -1,5 +1,7 @@
 {
-  "options": {},
+  "options": {
+    "task": "build"
+  },
   "fields": [
     {
       "field": "src",
@@ -24,6 +26,45 @@
   ],
   "confs": [
     {
+      "task": "build",
+      "src": [
+        "./src/sstdevch.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [
+        "-lm"
+      ],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/napi/export",
+        "@stdlib/napi/argv",
+        "@stdlib/napi/argv-int64",
+        "@stdlib/napi/argv-float",
+        "@stdlib/napi/argv-strided-float32array",
+        "@stdlib/stats/base/svariancech",
+        "@stdlib/napi/create-double"
+      ]
+    },
+    {
+      "task": "benchmark",
+      "src": [
+        "./src/sstdevch.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [
+        "-lm"
+      ],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/stats/base/svariancech"
+      ]
+    },
+    {
+      "task": "examples",
       "src": [
         "./src/sstdevch.c"
       ],
diff --git a/lib/node_modules/@stdlib/stats/base/sstdevch/src/addon.c b/lib/node_modules/@stdlib/stats/base/sstdevch/src/addon.c
new file mode 100644
index 000000000000..343a5102efd0
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/sstdevch/src/addon.c
@@ -0,0 +1,45 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/sstdevch.h"
+#include "stdlib/napi/export.h"
+#include "stdlib/napi/argv.h"
+#include "stdlib/napi/argv_int64.h"
+#include "stdlib/napi/argv_float.h"
+#include "stdlib/napi/argv_strided_float32array.h"
+#include "stdlib/napi/create_double.h"
+#include <node_api.h>
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 4 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_FLOAT( env, correction, argv, 1 );
+	STDLIB_NAPI_ARGV_INT64( env, stride, argv, 3 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, stride, argv, 2 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_sstdevch( N, correction, X, stride ), v );
+	return v;
+}
+
+STDLIB_NAPI_MODULE_EXPORT_FCN( addon )
diff --git a/lib/node_modules/@stdlib/stats/base/sstdevch/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/sstdevch/src/addon.cpp
deleted file mode 100644
index c8c2266b7b4e..000000000000
--- a/lib/node_modules/@stdlib/stats/base/sstdevch/src/addon.cpp
+++ /dev/null
@@ -1,130 +0,0 @@
-/**
-* @license Apache-2.0
-*
-* Copyright (c) 2020 The Stdlib Authors.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-*    http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-
-#include "stdlib/stats/base/sstdevch.h"
-#include <node_api.h>
-#include <stdint.h>
-#include <stdlib.h>
-#include <stdbool.h>
-#include <assert.h>
-
-/**
-* Add-on namespace.
-*/
-namespace stdlib_stats_base_sstdevch {
-
-	/**
-	* Computes the standard deviation of a single-precision floating-point strided array using a one-pass trial mean algorithm.
-	*
-	* ## Notes
-	*
-	* -   When called from JavaScript, the function expects four arguments:
-	*
-	*     -   `N`: number of indexed elements
-	*     -   `correction`: degrees of freedom adjustment
-	*     -   `X`: input array
-	*     -   `stride`: stride length
-	*/
-	napi_value node_sstdevch( napi_env env, napi_callback_info info ) {
-		napi_status status;
-
-		size_t argc = 4;
-		napi_value argv[ 4 ];
-		status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr );
-		assert( status == napi_ok );
-
-		if ( argc < 4 ) {
-			napi_throw_error( env, nullptr, "invalid invocation. Must provide 4 arguments." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype0;
-		status = napi_typeof( env, argv[ 0 ], &vtype0 );
-		assert( status == napi_ok );
-		if ( vtype0 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype1;
-		status = napi_typeof( env, argv[ 1 ], &vtype1 );
-		assert( status == napi_ok );
-		if ( vtype1 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a number." );
-			return nullptr;
-		}
-
-		bool res;
-		status = napi_is_typedarray( env, argv[ 2 ], &res );
-		assert( status == napi_ok );
-		if ( res == false ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype3;
-		status = napi_typeof( env, argv[ 3 ], &vtype3 );
-		assert( status == napi_ok );
-		if ( vtype3 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Fourth argument must be a number." );
-			return nullptr;
-		}
-
-		int64_t N;
-		status = napi_get_value_int64( env, argv[ 0 ], &N );
-		assert( status == napi_ok );
-
-		double correction;
-		status = napi_get_value_double( env, argv[ 1 ], &correction );
-		assert( status == napi_ok );
-
-		int64_t stride;
-		status = napi_get_value_int64( env, argv[ 3 ], &stride );
-		assert( status == napi_ok );
-
-		napi_typedarray_type vtype2;
-		size_t xlen;
-		void *X;
-		status = napi_get_typedarray_info( env, argv[ 2 ], &vtype2, &xlen, &X, nullptr, nullptr );
-		assert( status == napi_ok );
-		if ( vtype2 != napi_float32_array ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a Float32Array." );
-			return nullptr;
-		}
-		if ( (N-1)*llabs(stride) >= (int64_t)xlen ) {
-			napi_throw_range_error( env, nullptr, "invalid argument. Third argument has insufficient elements based on the associated stride and the number of indexed elements." );
-			return nullptr;
-		}
-
-		napi_value v;
-		status = napi_create_double( env, (double)stdlib_strided_sstdevch( N, (float)correction, (float *)X, stride ), &v );
-		assert( status == napi_ok );
-
-		return v;
-	}
-
-	napi_value Init( napi_env env, napi_value exports ) {
-		napi_status status;
-		napi_value fcn;
-		status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_sstdevch, NULL, &fcn );
-		assert( status == napi_ok );
-		return fcn;
-	}
-
-	NAPI_MODULE( NODE_GYP_MODULE_NAME, Init )
-} // end namespace stdlib_stats_base_sstdevch

From 0fbd4596fbe9387a58689ed4b0b45b7d9c9abb69 Mon Sep 17 00:00:00 2001
From: Athan Reines <kgryte@gmail.com>
Date: Fri, 3 Jan 2025 13:10:33 -0800
Subject: [PATCH 77/87] docs: fix examples

---
type: pre_commit_static_analysis_report
description: Results of running static analysis checks when committing changes.
report:
  - task: lint_filenames
    status: passed
  - task: lint_editorconfig
    status: passed
  - task: lint_markdown
    status: passed
  - task: lint_package_json
    status: na
  - task: lint_repl_help
    status: na
  - task: lint_javascript_src
    status: na
  - task: lint_javascript_cli
    status: na
  - task: lint_javascript_examples
    status: na
  - task: lint_javascript_tests
    status: na
  - task: lint_javascript_benchmarks
    status: na
  - task: lint_python
    status: na
  - task: lint_r
    status: na
  - task: lint_c_src
    status: na
  - task: lint_c_examples
    status: na
  - task: lint_c_benchmarks
    status: na
  - task: lint_c_tests_fixtures
    status: na
  - task: lint_shell
    status: na
  - task: lint_typescript_declarations
    status: na
  - task: lint_typescript_tests
    status: na
  - task: lint_license_headers
    status: passed
---
---
 lib/node_modules/@stdlib/stats/base/dnanmeanwd/README.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/README.md b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/README.md
index 2ee2d1fb9649..dbc9169c65f4 100644
--- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/README.md
+++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/README.md
@@ -205,7 +205,7 @@ Computes the arithmetic mean of a double-precision floating-point strided array
 const double x[] = { 1.0, 2.0, 0.0/0.0, 3.0, 0.0/0.0, 4.0, 5.0, 6.0, 0.0/0.0, 7.0, 8.0, 0.0/0.0 };
 
 double v = stdlib_strided_dnanmeanwd( 6, x, 2 );
-// returns 1.25
+// returns ~4.67
 ```
 
 The function accepts the following arguments:
@@ -226,7 +226,7 @@ Computes the arithmetic mean of a double-precision floating-point strided array,
 const double x[] = { 1.0, 2.0, 0.0/0.0, 3.0, 0.0/0.0, 4.0, 5.0, 6.0, 0.0/0.0, 7.0, 8.0, 0.0/0.0 };
 
 double v = stdlib_strided_dnanmeanwd_ndarray( 6, x, 2, 0 );
-// returns 1.25
+// returns ~4.67
 ```
 
 The function accepts the following arguments:

From 58275a47eb7c5f2f5f476ccd4346f86cf811cbd1 Mon Sep 17 00:00:00 2001
From: Athan Reines <kgryte@gmail.com>
Date: Fri, 3 Jan 2025 13:11:48 -0800
Subject: [PATCH 78/87] test: fix arguments

---
type: pre_commit_static_analysis_report
description: Results of running static analysis checks when committing changes.
report:
  - task: lint_filenames
    status: passed
  - task: lint_editorconfig
    status: passed
  - task: lint_markdown
    status: na
  - task: lint_package_json
    status: na
  - task: lint_repl_help
    status: na
  - task: lint_javascript_src
    status: na
  - task: lint_javascript_cli
    status: na
  - task: lint_javascript_examples
    status: na
  - task: lint_javascript_tests
    status: passed
  - task: lint_javascript_benchmarks
    status: na
  - task: lint_python
    status: na
  - task: lint_r
    status: na
  - task: lint_c_src
    status: na
  - task: lint_c_examples
    status: na
  - task: lint_c_benchmarks
    status: na
  - task: lint_c_tests_fixtures
    status: na
  - task: lint_shell
    status: na
  - task: lint_typescript_declarations
    status: na
  - task: lint_typescript_tests
    status: na
  - task: lint_license_headers
    status: passed
---

---
type: pre_push_report
description: Results of running various checks prior to pushing changes.
report:
  - task: run_javascript_examples
    status: na
  - task: run_c_examples
    status: na
  - task: run_cpp_examples
    status: na
  - task: run_javascript_readme_examples
    status: passed
  - task: run_c_benchmarks
    status: na
  - task: run_cpp_benchmarks
    status: na
  - task: run_fortran_benchmarks
    status: na
  - task: run_javascript_benchmarks
    status: na
  - task: run_julia_benchmarks
    status: na
  - task: run_python_benchmarks
    status: na
  - task: run_r_benchmarks
    status: na
  - task: run_javascript_tests
    status: passed
---
---
 .../@stdlib/stats/base/dnanmeanwd/test/test.dnanmeanwd.js     | 4 ++--
 .../stats/base/dnanmeanwd/test/test.dnanmeanwd.native.js      | 4 ++--
 .../@stdlib/stats/base/dnanmeanwd/test/test.ndarray.js        | 4 ++--
 .../@stdlib/stats/base/dnanmeanwd/test/test.ndarray.native.js | 4 ++--
 4 files changed, 8 insertions(+), 8 deletions(-)

diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.dnanmeanwd.js b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.dnanmeanwd.js
index baed8323682c..5d8dfac2ea9e 100644
--- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.dnanmeanwd.js
+++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.dnanmeanwd.js
@@ -104,7 +104,7 @@ tape( 'the function supports a `stride` parameter', function test( t ) {
 		NaN   // 4
 	]);
 
-	v = dnanmeanwd( 4, x, 2 );
+	v = dnanmeanwd( 5, x, 2 );
 
 	t.strictEqual( v, 1.25, 'returns expected value' );
 	t.end();
@@ -126,7 +126,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t )
 		NaN   // 0
 	]);
 
-	v = dnanmeanwd( 4, x, -2 );
+	v = dnanmeanwd( 5, x, -2 );
 
 	t.strictEqual( v, 1.25, 'returns expected value' );
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.dnanmeanwd.native.js b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.dnanmeanwd.native.js
index cf5754b12d8e..ccad2611f919 100644
--- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.dnanmeanwd.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.dnanmeanwd.native.js
@@ -195,7 +195,7 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) {
 		NaN   // 4
 	]);
 
-	v = dnanmeanwd( 4, x, 2 );
+	v = dnanmeanwd( 5, x, 2 );
 
 	t.strictEqual( v, 1.25, 'returns expected value' );
 	t.end();
@@ -217,7 +217,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test
 		NaN   // 0
 	]);
 
-	v = dnanmeanwd( 4, x, -2 );
+	v = dnanmeanwd( 5, x, -2 );
 
 	t.strictEqual( v, 1.25, 'returns expected value' );
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.ndarray.js
index a911e86e95c7..fe56b5994118 100644
--- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.ndarray.js
@@ -104,7 +104,7 @@ tape( 'the function supports a `stride` parameter', function test( t ) {
 		NaN   // 4
 	]);
 
-	v = dnanmeanwd( 4, x, 2, 0 );
+	v = dnanmeanwd( 5, x, 2, 0 );
 
 	t.strictEqual( v, 1.25, 'returns expected value' );
 	t.end();
@@ -126,7 +126,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t )
 		NaN   // 0
 	]);
 
-	v = dnanmeanwd( 4, x, -2, 6 );
+	v = dnanmeanwd( 5, x, -2, 8 );
 
 	t.strictEqual( v, 1.25, 'returns expected value' );
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.ndarray.native.js
index 574982c528a2..3160f0db750f 100644
--- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/test/test.ndarray.native.js
@@ -113,7 +113,7 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) {
 		NaN   // 4
 	]);
 
-	v = dnanmeanwd( 4, x, 2, 0 );
+	v = dnanmeanwd( 5, x, 2, 0 );
 
 	t.strictEqual( v, 1.25, 'returns expected value' );
 	t.end();
@@ -135,7 +135,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test
 		NaN   // 0
 	]);
 
-	v = dnanmeanwd( 4, x, -2, 6 );
+	v = dnanmeanwd( 5, x, -2, 8 );
 
 	t.strictEqual( v, 1.25, 'returns expected value' );
 	t.end();

From 78cb140c3e18ab53936a12de4072c7a18f6f777c Mon Sep 17 00:00:00 2001
From: Aayush Khanna <96649223+aayush0325@users.noreply.github.com>
Date: Sat, 4 Jan 2025 02:44:49 +0530
Subject: [PATCH 79/87] chore: remove unused header in `stats/base/dnanmeanwd`

PR-URL: https://github.com/stdlib-js/stdlib/pull/4497
Reviewed-by: Athan Reines <kgryte@gmail.com>
---
 lib/node_modules/@stdlib/stats/base/dnanmeanwd/README.md  | 2 +-
 lib/node_modules/@stdlib/stats/base/dnanmeanwd/src/main.c | 1 -
 2 files changed, 1 insertion(+), 2 deletions(-)

diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/README.md b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/README.md
index dbc9169c65f4..2bc5dd63a3d8 100644
--- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/README.md
+++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/README.md
@@ -70,7 +70,7 @@ The function has the following parameters:
 -   **x**: input [`Float64Array`][@stdlib/array/float64].
 -   **strideX**: index increment for `x`.
 
-The `N` and stride parameters determine which elements in the stride array are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`,
+The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the [arithmetic mean][arithmetic-mean] of every other element in `x`,
 
 ```javascript
 var Float64Array = require( '@stdlib/array/float64' );
diff --git a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/src/main.c b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/src/main.c
index a0a7c9c37e73..45806c5705d1 100644
--- a/lib/node_modules/@stdlib/stats/base/dnanmeanwd/src/main.c
+++ b/lib/node_modules/@stdlib/stats/base/dnanmeanwd/src/main.c
@@ -19,7 +19,6 @@
 #include "stdlib/stats/base/dnanmeanwd.h"
 #include "stdlib/blas/base/shared.h"
 #include "stdlib/strided/base/stride2offset.h"
-#include <stdint.h>
 
 /**
 * Computes the arithmetic mean of a double-precision floating-point strided array, using Welford's algorithm and ignoring `NaN` values.

From 59ab5bed4887460a52712946309411645b5809ad Mon Sep 17 00:00:00 2001
From: Aayush Khanna <96649223+aayush0325@users.noreply.github.com>
Date: Sat, 4 Jan 2025 02:56:16 +0530
Subject: [PATCH 80/87] feat: add C ndarray interface and refactor
 implementation for `stats/base/sminsorted`

PR-URL: https://github.com/stdlib-js/stdlib/pull/4492
Reviewed-by: Athan Reines <kgryte@gmail.com>
Co-authored-by: stdlib-bot <82920195+stdlib-bot@users.noreply.github.com>
---
 .../@stdlib/stats/base/sminsorted/README.md   | 164 ++++++++++++++----
 .../base/sminsorted/benchmark/benchmark.js    |  17 +-
 .../sminsorted/benchmark/benchmark.native.js  |  13 +-
 .../sminsorted/benchmark/benchmark.ndarray.js |  17 +-
 .../benchmark/benchmark.ndarray.native.js     |  13 +-
 .../sminsorted/benchmark/c/benchmark.length.c |  54 +++++-
 .../stats/base/sminsorted/docs/repl.txt       |  32 ++--
 .../base/sminsorted/docs/types/index.d.ts     |  12 +-
 .../base/sminsorted/examples/c/example.c      |   9 +-
 .../stats/base/sminsorted/examples/index.js   |  13 +-
 .../stats/base/sminsorted/include.gypi        |   2 +-
 .../include/stdlib/stats/base/sminsorted.h    |   9 +-
 .../stats/base/sminsorted/lib/index.js        |   7 +-
 .../stats/base/sminsorted/lib/ndarray.js      |  16 +-
 .../base/sminsorted/lib/ndarray.native.js     |  20 +--
 .../stats/base/sminsorted/lib/sminsorted.js   |  41 +----
 .../base/sminsorted/lib/sminsorted.native.js  |   9 +-
 .../stats/base/sminsorted/manifest.json       |  74 +++++++-
 .../@stdlib/stats/base/sminsorted/src/addon.c |  60 +++++++
 .../stats/base/sminsorted/src/addon.cpp       | 117 -------------
 .../sminsorted/src/{sminsorted.c => main.c}   |  38 ++--
 .../base/sminsorted/test/test.ndarray.js      |  15 +-
 .../sminsorted/test/test.ndarray.native.js    |  15 +-
 .../base/sminsorted/test/test.sminsorted.js   |  13 +-
 .../sminsorted/test/test.sminsorted.native.js |  13 +-
 25 files changed, 441 insertions(+), 352 deletions(-)
 create mode 100644 lib/node_modules/@stdlib/stats/base/sminsorted/src/addon.c
 delete mode 100644 lib/node_modules/@stdlib/stats/base/sminsorted/src/addon.cpp
 rename lib/node_modules/@stdlib/stats/base/sminsorted/src/{sminsorted.c => main.c} (54%)

diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/README.md b/lib/node_modules/@stdlib/stats/base/sminsorted/README.md
index 2d988bb3a57e..0b8552e30be4 100644
--- a/lib/node_modules/@stdlib/stats/base/sminsorted/README.md
+++ b/lib/node_modules/@stdlib/stats/base/sminsorted/README.md
@@ -36,7 +36,7 @@ limitations under the License.
 var sminsorted = require( '@stdlib/stats/base/sminsorted' );
 ```
 
-#### sminsorted( N, x, stride )
+#### sminsorted( N, x, strideX )
 
 Computes the minimum value of a sorted single-precision floating-point strided array `x`.
 
@@ -44,15 +44,13 @@ Computes the minimum value of a sorted single-precision floating-point strided a
 var Float32Array = require( '@stdlib/array/float32' );
 
 var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );
-var N = x.length;
 
-var v = sminsorted( N, x, 1 );
+var v = sminsorted( x.length, x, 1 );
 // returns 1.0
 
 x = new Float32Array( [ 3.0, 2.0, 1.0 ] );
-N = x.length;
 
-v = sminsorted( N, x, 1 );
+v = sminsorted( x.length, x, 1 );
 // returns 1.0
 ```
 
@@ -60,18 +58,16 @@ The function has the following parameters:
 
 -   **N**: number of indexed elements.
 -   **x**: sorted input [`Float32Array`][@stdlib/array/float32].
--   **stride**: index increment for `x`.
+-   **strideX**: index increment for `x`.
 
-The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the minimum value of every other element in `x`,
+The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the minimum value of every other element in `x`,
 
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x = new Float32Array( [ 1.0, 2.0, 2.0, -7.0, 3.0, 3.0, 4.0, 2.0 ] );
-var N = floor( x.length / 2 );
 
-var v = sminsorted( N, x, 2 );
+var v = sminsorted( 4, x, 2 );
 // returns 1.0
 ```
 
@@ -81,18 +77,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [
 
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x0 = new Float32Array( [ 2.0, 1.0, 2.0, 2.0, -2.0, 2.0, 3.0, 4.0 ] );
 var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
 
-var N = floor( x0.length / 2 );
-
-var v = sminsorted( N, x1, 2 );
+var v = sminsorted( 4, x1, 2 );
 // returns 1.0
 ```
 
-#### sminsorted.ndarray( N, x, stride, offset )
+#### sminsorted.ndarray( N, x, strideX, offsetX )
 
 Computes the minimum value of a sorted single-precision floating-point strided array using alternative indexing semantics.
 
@@ -100,26 +93,23 @@ Computes the minimum value of a sorted single-precision floating-point strided a
 var Float32Array = require( '@stdlib/array/float32' );
 
 var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );
-var N = x.length;
 
-var v = sminsorted.ndarray( N, x, 1, 0 );
+var v = sminsorted.ndarray( x.length, x, 1, 0 );
 // returns 1.0
 ```
 
 The function has the following additional parameters:
 
--   **offset**: starting index for `x`.
+-   **offsetX**: starting index for `x`.
 
-While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the minimum value for every other value in `x` starting from the second value
+While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the minimum value for every other element in `x` starting from the second element
 
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x = new Float32Array( [ 2.0, 1.0, 2.0, 2.0, -2.0, 2.0, 3.0, 4.0 ] );
-var N = floor( x.length / 2 );
 
-var v = sminsorted.ndarray( N, x, 2, 1 );
+var v = sminsorted.ndarray( 4, x, 2, 1 );
 // returns 1.0
 ```
 
@@ -145,16 +135,13 @@ var v = sminsorted.ndarray( N, x, 2, 1 );
 <!-- eslint no-undef: "error" -->
 
 ```javascript
-var Float32Array = require( '@stdlib/array/float32' );
+var linspace = require( '@stdlib/array/linspace' );
 var sminsorted = require( '@stdlib/stats/base/sminsorted' );
 
-var x;
-var i;
-
-x = new Float32Array( 10 );
-for ( i = 0; i < x.length; i++ ) {
-    x[ i ] = i - 5.0;
-}
+var options = {
+    'dtype': 'float32'
+};
+var x = linspace( -5.0, 5.0, 10, options );
 console.log( x );
 
 var v = sminsorted( x.length, x, 1 );
@@ -165,6 +152,123 @@ console.log( v );
 
 <!-- /.examples -->
 
+<!-- C interface documentation. -->
+
+* * *
+
+<section class="c">
+
+## C APIs
+
+<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<!-- C usage documentation. -->
+
+<section class="usage">
+
+### Usage
+
+```c
+#include "stdlib/stats/base/sminsorted.h"
+```
+
+#### stdlib_strided_sminsorted( N, \*X, strideX )
+
+Computes the minimum value of a sorted single-precision floating-point strided array.
+
+```c
+const float x[] = { 1.0f, 2.0f, 3.0f };
+
+float v = stdlib_strided_sminsorted( 3, x, 1 );
+// returns 1.0f
+```
+
+The function accepts the following arguments:
+
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **X**: `[in] float*` input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+
+```c
+float stdlib_strided_sminsorted( const CBLAS_INT N, const float *X, const CBLAS_INT strideX );
+```
+
+#### stdlib_strided_sminsorted_ndarray( N, \*X, strideX, offsetX )
+
+Computes the minimum value of a sorted single-precision floating-point strided array using alternative indexing semantics.
+
+```c
+const float x[] = { 1.0f, 2.0f, 3.0f };
+
+float v = stdlib_strided_sminsorted_ndarray( 3, x, 1, 0 );
+// returns 1.0f
+```
+
+The function accepts the following arguments:
+
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **X**: `[in] float*` input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+-   **offsetX**: `[in] CBLAS_INT` starting index for `X`.
+
+```c
+float stdlib_strided_sminsorted_ndarray( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX );
+```
+
+</section>
+
+<!-- /.usage -->
+
+<!-- C API usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="notes">
+
+</section>
+
+<!-- /.notes -->
+
+<!-- C API usage examples. -->
+
+<section class="examples">
+
+### Examples
+
+```c
+#include "stdlib/stats/base/sminsorted.h"
+#include <stdio.h>
+
+int main( void ) {
+    // Create a strided array:
+    const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f };
+
+    // Specify the number of elements:
+    const int N = 4;
+
+    // Specify the stride length:
+    const int strideX = 2;
+
+    // Compute the minimum value:
+    float v = stdlib_strided_sminsorted( N, x, strideX );
+
+    // Print the result:
+    printf( "min: %f\n", v );
+}
+```
+
+</section>
+
+<!-- /.examples -->
+
+</section>
+
+<!-- /.c -->
+
 <!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
 
 <section class="related">
diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/sminsorted/benchmark/benchmark.js
index 89ed34128746..dbe64cce9803 100644
--- a/lib/node_modules/@stdlib/stats/base/sminsorted/benchmark/benchmark.js
+++ b/lib/node_modules/@stdlib/stats/base/sminsorted/benchmark/benchmark.js
@@ -22,12 +22,19 @@
 
 var bench = require( '@stdlib/bench' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
+var linspace = require( '@stdlib/array/linspace' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float32Array = require( '@stdlib/array/float32' );
 var pkg = require( './../package.json' ).name;
 var sminsorted = require( './../lib/sminsorted.js' );
 
 
+// VARIABLES //
+
+var options = {
+	'dtype': 'float32'
+};
+
+
 // FUNCTIONS //
 
 /**
@@ -38,13 +45,7 @@ var sminsorted = require( './../lib/sminsorted.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float32Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = i;
-	}
+	var x = linspace( -len/2, len/2, len, options );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/sminsorted/benchmark/benchmark.native.js
index 46d041cfe1e6..2ae34f28c2cf 100644
--- a/lib/node_modules/@stdlib/stats/base/sminsorted/benchmark/benchmark.native.js
+++ b/lib/node_modules/@stdlib/stats/base/sminsorted/benchmark/benchmark.native.js
@@ -23,8 +23,8 @@
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
+var linspace = require( '@stdlib/array/linspace' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float32Array = require( '@stdlib/array/float32' );
 var tryRequire = require( '@stdlib/utils/try-require' );
 var pkg = require( './../package.json' ).name;
 
@@ -35,6 +35,9 @@ var sminsorted = tryRequire( resolve( __dirname, './../lib/sminsorted.native.js'
 var opts = {
 	'skip': ( sminsorted instanceof Error )
 };
+var options = {
+	'dtype': 'float32'
+};
 
 
 // FUNCTIONS //
@@ -47,13 +50,7 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float32Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = i;
-	}
+	var x = linspace( -len/2, len/2, len, options );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/sminsorted/benchmark/benchmark.ndarray.js
index 47374c1da0f8..48c1e0a7bcde 100644
--- a/lib/node_modules/@stdlib/stats/base/sminsorted/benchmark/benchmark.ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/sminsorted/benchmark/benchmark.ndarray.js
@@ -22,12 +22,19 @@
 
 var bench = require( '@stdlib/bench' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
+var linspace = require( '@stdlib/array/linspace' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float32Array = require( '@stdlib/array/float32' );
 var pkg = require( './../package.json' ).name;
 var sminsorted = require( './../lib/ndarray.js' );
 
 
+// VARIABLES //
+
+var options = {
+	'dtype': 'float32'
+};
+
+
 // FUNCTIONS //
 
 /**
@@ -38,13 +45,7 @@ var sminsorted = require( './../lib/ndarray.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float32Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = i;
-	}
+	var x = linspace( -len/2, len/2, len, options );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/sminsorted/benchmark/benchmark.ndarray.native.js
index c26c3b438aa8..433e57b181b9 100644
--- a/lib/node_modules/@stdlib/stats/base/sminsorted/benchmark/benchmark.ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/sminsorted/benchmark/benchmark.ndarray.native.js
@@ -23,8 +23,8 @@
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
+var linspace = require( '@stdlib/array/linspace' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float32Array = require( '@stdlib/array/float32' );
 var tryRequire = require( '@stdlib/utils/try-require' );
 var pkg = require( './../package.json' ).name;
 
@@ -35,6 +35,9 @@ var sminsorted = tryRequire( resolve( __dirname, './../lib/ndarray.native.js' )
 var opts = {
 	'skip': ( sminsorted instanceof Error )
 };
+var options = {
+	'dtype': 'float32'
+};
 
 
 // FUNCTIONS //
@@ -47,13 +50,7 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float32Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = i;
-	}
+	var x = linspace( -len/2, len/2, len, options );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/sminsorted/benchmark/c/benchmark.length.c
index 871fc4baf5d5..a78f92e4d87d 100644
--- a/lib/node_modules/@stdlib/stats/base/sminsorted/benchmark/c/benchmark.length.c
+++ b/lib/node_modules/@stdlib/stats/base/sminsorted/benchmark/c/benchmark.length.c
@@ -82,9 +82,9 @@ static double tic( void ) {
 *
 * @return random number
 */
-static double rand_double( void ) {
+static float rand_float( void ) {
 	int r = rand();
-	return (double)r / ( (double)RAND_MAX + 1.0 );
+	return (float)r / ( (float)RAND_MAX + 1.0f );
 }
 
 /**
@@ -94,7 +94,7 @@ static double rand_double( void ) {
 * @param len          array length
 * @return             elapsed time in seconds
 */
-static double benchmark( int iterations, int len ) {
+static double benchmark1( int iterations, int len ) {
 	double elapsed;
 	float x[ len ];
 	float v;
@@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) {
 	v = 0.0f;
 	t = tic();
 	for ( i = 0; i < iterations; i++ ) {
+		// cppcheck-suppress uninitvar
 		v = stdlib_strided_sminsorted( len, x, 1 );
 		if ( v != v ) {
 			printf( "should not return NaN\n" );
@@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) {
 	return elapsed;
 }
 
+/**
+* Runs a benchmark.
+*
+* @param iterations   number of iterations
+* @param len          array length
+* @return             elapsed time in seconds
+*/
+static double benchmark2( int iterations, int len ) {
+	double elapsed;
+	float x[ len ];
+	float v;
+	double t;
+	int i;
+
+	for ( i = 0; i < len; i++ ) {
+		x[ i ] = i;
+	}
+	v = 0.0f;
+	t = tic();
+	for ( i = 0; i < iterations; i++ ) {
+		// cppcheck-suppress uninitvar
+		v = stdlib_strided_sminsorted_ndarray( len, x, 1, 0 );
+		if ( v != v ) {
+			printf( "should not return NaN\n" );
+			break;
+		}
+	}
+	elapsed = tic() - t;
+	if ( v != v ) {
+		printf( "should not return NaN\n" );
+	}
+	return elapsed;
+}
+
 /**
 * Main execution sequence.
 */
@@ -142,7 +177,18 @@ int main( void ) {
 		for ( j = 0; j < REPEATS; j++ ) {
 			count += 1;
 			printf( "# c::%s:len=%d\n", NAME, len );
-			elapsed = benchmark( iter, len );
+			elapsed = benchmark1( iter, len );
+			print_results( iter, elapsed );
+			printf( "ok %d benchmark finished\n", count );
+		}
+	}
+	for ( i = MIN; i <= MAX; i++ ) {
+		len = pow( 10, i );
+		iter = ITERATIONS;
+		for ( j = 0; j < REPEATS; j++ ) {
+			count += 1;
+			printf( "# c::%s:ndarray:len=%d\n", NAME, len );
+			elapsed = benchmark2( iter, len );
 			print_results( iter, elapsed );
 			printf( "ok %d benchmark finished\n", count );
 		}
diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/sminsorted/docs/repl.txt
index 24308e8dbbc9..1e883deb38a5 100644
--- a/lib/node_modules/@stdlib/stats/base/sminsorted/docs/repl.txt
+++ b/lib/node_modules/@stdlib/stats/base/sminsorted/docs/repl.txt
@@ -1,13 +1,13 @@
 
-{{alias}}( N, x, stride )
+{{alias}}( N, x, strideX )
     Computes the minimum value of a sorted single-precision floating-point
     strided array.
 
     The input strided array must be sorted in either strictly ascending or
     descending order.
 
-    The `N` and `stride` parameters determine which elements in `x` are accessed
-    at runtime.
+    The `N` and stride parameters determine which elements in the strided array
+    are accessed at runtime.
 
     Indexing is relative to the first index. To introduce an offset, use a typed
     array view.
@@ -22,8 +22,8 @@
     x: Float32Array
         Sorted input array.
 
-    stride: integer
-        Index increment.
+    strideX: integer
+        Stride Length.
 
     Returns
     -------
@@ -37,22 +37,19 @@
     > {{alias}}( x.length, x, 1 )
     1.0
 
-    // Using `N` and `stride` parameters:
+    // Using `N` and stride parameters:
     > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > var stride = 2;
-    > {{alias}}( N, x, stride )
+    > {{alias}}( 3, x, 2 )
     -2.0
 
     // Using view offsets:
     > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );
     > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );
-    > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );
-    > stride = 2;
-    > {{alias}}( N, x1, stride )
+    > {{alias}}( 3, x1, 2 )
     -2.0
 
-{{alias}}.ndarray( N, x, stride, offset )
+
+{{alias}}.ndarray( N, x, strideX, offsetX )
     Computes the minimum value of a sorted single-precision floating-point
     strided array using alternative indexing semantics.
 
@@ -68,10 +65,10 @@
     x: Float32Array
         Sorted input array.
 
-    stride: integer
-        Index increment.
+    strideX: integer
+        Stride Length.
 
-    offset: integer
+    offsetX: integer
         Starting index.
 
     Returns
@@ -88,8 +85,7 @@
 
     // Using offset parameter:
     > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > {{alias}}.ndarray( N, x, 2, 1 )
+    > {{alias}}.ndarray( 3, x, 2, 1 )
     -2.0
 
     See Also
diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/sminsorted/docs/types/index.d.ts
index b31aac869805..8309813835b3 100644
--- a/lib/node_modules/@stdlib/stats/base/sminsorted/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/sminsorted/docs/types/index.d.ts
@@ -27,7 +27,7 @@ interface Routine {
 	*
 	* @param N - number of indexed elements
 	* @param x - sorted input array
-	* @param stride - stride length
+	* @param strideX - stride length
 	* @returns minimum value
 	*
 	* @example
@@ -38,15 +38,15 @@ interface Routine {
 	* var v = sminsorted( x.length, x, 1 );
 	* // returns 1.0
 	*/
-	( N: number, x: Float32Array, stride: number ): number;
+	( N: number, x: Float32Array, strideX: number ): number;
 
 	/**
 	* Computes the minimum value of a sorted single-precision floating-point strided array using alternative indexing semantics.
 	*
 	* @param N - number of indexed elements
 	* @param x - sorted input array
-	* @param stride - stride length
-	* @param offset - starting index
+	* @param strideX - stride length
+	* @param offsetX - starting index
 	* @returns minimum value
 	*
 	* @example
@@ -57,7 +57,7 @@ interface Routine {
 	* var v = sminsorted.ndarray( x.length, x, 1, 0 );
 	* // returns 1.0
 	*/
-	ndarray( N: number, x: Float32Array, stride: number, offset: number ): number;
+	ndarray( N: number, x: Float32Array, strideX: number, offsetX: number ): number;
 }
 
 /**
@@ -65,7 +65,7 @@ interface Routine {
 *
 * @param N - number of indexed elements
 * @param x - sorted input array
-* @param stride - stride length
+* @param strideX - stride length
 * @returns minimum value
 *
 * @example
diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/sminsorted/examples/c/example.c
index 960eadf4538b..7ba730cd529f 100644
--- a/lib/node_modules/@stdlib/stats/base/sminsorted/examples/c/example.c
+++ b/lib/node_modules/@stdlib/stats/base/sminsorted/examples/c/example.c
@@ -17,21 +17,20 @@
 */
 
 #include "stdlib/stats/base/sminsorted.h"
-#include <stdint.h>
 #include <stdio.h>
 
 int main( void ) {
 	// Create a strided array:
-	float x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 };
+	const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f };
 
 	// Specify the number of elements:
-	int64_t N = 4;
+	const int N = 4;
 
 	// Specify the stride length:
-	int64_t stride = 2;
+	const int strideX = 2;
 
 	// Compute the minimum value:
-	float v = stdlib_strided_sminsorted( N, x, stride );
+	float v = stdlib_strided_sminsorted( N, x, strideX );
 
 	// Print the result:
 	printf( "min: %f\n", v );
diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/examples/index.js b/lib/node_modules/@stdlib/stats/base/sminsorted/examples/index.js
index 3365c9442ffd..6ff2f407fbf1 100644
--- a/lib/node_modules/@stdlib/stats/base/sminsorted/examples/index.js
+++ b/lib/node_modules/@stdlib/stats/base/sminsorted/examples/index.js
@@ -18,16 +18,13 @@
 
 'use strict';
 
-var Float32Array = require( '@stdlib/array/float32' );
+var linspace = require( '@stdlib/array/linspace' );
 var sminsorted = require( './../lib' );
 
-var x;
-var i;
-
-x = new Float32Array( 10 );
-for ( i = 0; i < x.length; i++ ) {
-	x[ i ] = i - 5.0;
-}
+var options = {
+	'dtype': 'float32'
+};
+var x = linspace( -5.0, 5.0, 10, options );
 console.log( x );
 
 var v = sminsorted( x.length, x, 1 );
diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/include.gypi b/lib/node_modules/@stdlib/stats/base/sminsorted/include.gypi
index 868c5c12e852..26476a8c2655 100644
--- a/lib/node_modules/@stdlib/stats/base/sminsorted/include.gypi
+++ b/lib/node_modules/@stdlib/stats/base/sminsorted/include.gypi
@@ -36,7 +36,7 @@
 
     # Source files:
     'src_files': [
-      '<(src_dir)/addon.cpp',
+      '<(src_dir)/addon.c',
       '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).src; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
     ],
 
diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/include/stdlib/stats/base/sminsorted.h b/lib/node_modules/@stdlib/stats/base/sminsorted/include/stdlib/stats/base/sminsorted.h
index 17939458ee10..19120f7e665e 100644
--- a/lib/node_modules/@stdlib/stats/base/sminsorted/include/stdlib/stats/base/sminsorted.h
+++ b/lib/node_modules/@stdlib/stats/base/sminsorted/include/stdlib/stats/base/sminsorted.h
@@ -19,7 +19,7 @@
 #ifndef STDLIB_STATS_BASE_SMINSORTED_H
 #define STDLIB_STATS_BASE_SMINSORTED_H
 
-#include <stdint.h>
+#include "stdlib/blas/base/shared.h"
 
 /*
 * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler.
@@ -31,7 +31,12 @@ extern "C" {
 /**
 * Computes the minimum value of a sorted single-precision floating-point strided array.
 */
-float stdlib_strided_sminsorted( const int64_t N, const float *X, const int64_t stride );
+float API_SUFFIX(stdlib_strided_sminsorted)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX );
+
+/**
+* Computes the minimum value of a sorted single-precision floating-point strided array using alternative indexing semantics.
+*/
+float API_SUFFIX(stdlib_strided_sminsorted_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX );
 
 #ifdef __cplusplus
 }
diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/lib/index.js b/lib/node_modules/@stdlib/stats/base/sminsorted/lib/index.js
index 30ca8ac6db06..4f073370b4b0 100644
--- a/lib/node_modules/@stdlib/stats/base/sminsorted/lib/index.js
+++ b/lib/node_modules/@stdlib/stats/base/sminsorted/lib/index.js
@@ -28,20 +28,17 @@
 * var sminsorted = require( '@stdlib/stats/base/sminsorted' );
 *
 * var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );
-* var N = x.length;
 *
-* var v = sminsorted( N, x, 1 );
+* var v = sminsorted( x.length, x, 1 );
 * // returns 1.0
 *
 * @example
 * var Float32Array = require( '@stdlib/array/float32' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 * var sminsorted = require( '@stdlib/stats/base/sminsorted' );
 *
 * var x = new Float32Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
-* var N = floor( x.length / 2 );
 *
-* var v = sminsorted.ndarray( N, x, 2, 1 );
+* var v = sminsorted.ndarray( 4, x, 2, 1 );
 * // returns -3.0
 */
 
diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/sminsorted/lib/ndarray.js
index da4cf5058734..157f1015f56b 100644
--- a/lib/node_modules/@stdlib/stats/base/sminsorted/lib/ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/sminsorted/lib/ndarray.js
@@ -31,32 +31,30 @@ var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' );
 *
 * @param {PositiveInteger} N - number of indexed elements
 * @param {Float32Array} x - sorted input array
-* @param {integer} stride - stride length
-* @param {NonNegativeInteger} offset - starting index
+* @param {integer} strideX - stride length
+* @param {NonNegativeInteger} offsetX - starting index
 * @returns {number} minimum value
 *
 * @example
 * var Float32Array = require( '@stdlib/array/float32' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 *
 * var x = new Float32Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
-* var N = floor( x.length / 2 );
 *
-* var v = sminsorted( N, x, 2, 1 );
+* var v = sminsorted( 4, x, 2, 1 );
 * // returns -3.0
 */
-function sminsorted( N, x, stride, offset ) {
+function sminsorted( N, x, strideX, offsetX ) {
 	var v1;
 	var v2;
 
 	if ( N <= 0 ) {
 		return NaN;
 	}
-	if ( N === 1 || stride === 0 ) {
+	if ( N === 1 || strideX === 0 ) {
 		return x[ 0 ];
 	}
-	v1 = x[ offset ];
-	v2 = x[ offset + ((N-1)*stride) ];
+	v1 = x[ offsetX ];
+	v2 = x[ offsetX + ((N-1)*strideX) ];
 	if ( isnanf( v1 ) || isnanf( v2 ) ) {
 		return NaN;
 	}
diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/sminsorted/lib/ndarray.native.js
index 7c64eb780966..a592bf398e2c 100644
--- a/lib/node_modules/@stdlib/stats/base/sminsorted/lib/ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/sminsorted/lib/ndarray.native.js
@@ -20,8 +20,7 @@
 
 // MODULES //
 
-var Float32Array = require( '@stdlib/array/float32' );
-var addon = require( './sminsorted.native.js' );
+var addon = require( './../src/addon.node' );
 
 
 // MAIN //
@@ -31,27 +30,20 @@ var addon = require( './sminsorted.native.js' );
 *
 * @param {PositiveInteger} N - number of indexed elements
 * @param {Float32Array} x - sorted input array
-* @param {integer} stride - stride length
-* @param {NonNegativeInteger} offset - starting index
+* @param {integer} strideX - stride length
+* @param {NonNegativeInteger} offsetX - starting index
 * @returns {number} minimum value
 *
 * @example
 * var Float32Array = require( '@stdlib/array/float32' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 *
 * var x = new Float32Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
-* var N = floor( x.length / 2 );
 *
-* var v = sminsorted( N, x, 2, 1 );
+* var v = sminsorted( 4, x, 2, 1 );
 * // returns -3.0
 */
-function sminsorted( N, x, stride, offset ) {
-	var view;
-	if ( stride < 0 ) {
-		offset += (N-1) * stride;
-	}
-	view = new Float32Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len
-	return addon( N, view, stride );
+function sminsorted( N, x, strideX, offsetX ) {
+	return addon.ndarray( N, x, strideX, offsetX );
 }
 
 
diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/lib/sminsorted.js b/lib/node_modules/@stdlib/stats/base/sminsorted/lib/sminsorted.js
index 787df41ce295..38047d3b7932 100644
--- a/lib/node_modules/@stdlib/stats/base/sminsorted/lib/sminsorted.js
+++ b/lib/node_modules/@stdlib/stats/base/sminsorted/lib/sminsorted.js
@@ -20,8 +20,8 @@
 
 // MODULES //
 
-var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
-var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' );
+var stride2offset = require( '@stdlib/strided/base/stride2offset' );
+var ndarray = require( './ndarray.js' );
 
 
 // MAIN //
@@ -31,48 +31,19 @@ var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' );
 *
 * @param {PositiveInteger} N - number of indexed elements
 * @param {Float32Array} x - sorted input array
-* @param {integer} stride - stride length
+* @param {integer} strideX - stride length
 * @returns {number} minimum value
 *
 * @example
 * var Float32Array = require( '@stdlib/array/float32' );
 *
 * var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );
-* var N = x.length;
 *
-* var v = sminsorted( N, x, 1 );
+* var v = sminsorted( x.length, x, 1 );
 * // returns 1.0
 */
-function sminsorted( N, x, stride ) {
-	var v1;
-	var v2;
-
-	if ( N <= 0 ) {
-		return NaN;
-	}
-	if ( N === 1 || stride === 0 ) {
-		return x[ 0 ];
-	}
-	if ( stride < 0 ) {
-		v1 = x[ (1-N) * stride ];
-		v2 = x[ 0 ];
-	} else {
-		v1 = x[ 0 ];
-		v2 = x[ (N-1) * stride ];
-	}
-	if ( isnanf( v1 ) || isnanf( v2 ) ) {
-		return NaN;
-	}
-	if ( v1 === v2 ) {
-		if ( isNegativeZerof( v1 ) || isNegativeZerof( v2 ) ) {
-			return -0.0;
-		}
-		return v1;
-	}
-	if ( v1 < v2 ) {
-		return v1;
-	}
-	return v2;
+function sminsorted( N, x, strideX ) {
+	return ndarray( N, x, strideX, stride2offset( N, strideX ) );
 }
 
 
diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/lib/sminsorted.native.js b/lib/node_modules/@stdlib/stats/base/sminsorted/lib/sminsorted.native.js
index 21c3a7138274..203035ca0b28 100644
--- a/lib/node_modules/@stdlib/stats/base/sminsorted/lib/sminsorted.native.js
+++ b/lib/node_modules/@stdlib/stats/base/sminsorted/lib/sminsorted.native.js
@@ -30,20 +30,19 @@ var addon = require( './../src/addon.node' );
 *
 * @param {PositiveInteger} N - number of indexed elements
 * @param {Float32Array} x - sorted input array
-* @param {integer} stride - stride length
+* @param {integer} strideX - stride length
 * @returns {number} minimum value
 *
 * @example
 * var Float32Array = require( '@stdlib/array/float32' );
 *
 * var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );
-* var N = x.length;
 *
-* var v = sminsorted( N, x, 1 );
+* var v = sminsorted( x.length, x, 1 );
 * // returns 1.0
 */
-function sminsorted( N, x, stride ) {
-	return addon( N, x, stride );
+function sminsorted( N, x, strideX ) {
+	return addon( N, x, strideX );
 }
 
 
diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/manifest.json b/lib/node_modules/@stdlib/stats/base/sminsorted/manifest.json
index dd2eadc21a8c..5cd4cc1df6c7 100644
--- a/lib/node_modules/@stdlib/stats/base/sminsorted/manifest.json
+++ b/lib/node_modules/@stdlib/stats/base/sminsorted/manifest.json
@@ -1,5 +1,8 @@
 {
-  "options": {},
+  "options": {
+    "task": "build",
+    "wasm": false
+  },
   "fields": [
     {
       "field": "src",
@@ -24,19 +27,80 @@
   ],
   "confs": [
     {
+      "task": "build",
+      "wasm": false,
       "src": [
-        "./src/sminsorted.c"
+        "./src/main.c"
       ],
       "include": [
         "./include"
       ],
-      "libraries": [
-        "-lm"
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/math/base/assert/is-nanf",
+        "@stdlib/math/base/assert/is-negative-zerof",
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset",
+        "@stdlib/napi/export",
+        "@stdlib/napi/argv",
+        "@stdlib/napi/argv-int64",
+        "@stdlib/napi/argv-strided-float32array",
+        "@stdlib/napi/create-double"
+      ]
+    },
+    {
+      "task": "benchmark",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/math/base/assert/is-nanf",
+        "@stdlib/math/base/assert/is-negative-zerof",
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset"
+      ]
+    },
+    {
+      "task": "examples",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/math/base/assert/is-nanf",
+        "@stdlib/math/base/assert/is-negative-zerof",
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset"
+      ]
+    },
+    {
+      "task": "",
+      "wasm": true,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
       ],
+      "libraries": [],
       "libpath": [],
       "dependencies": [
         "@stdlib/math/base/assert/is-nanf",
-        "@stdlib/math/base/assert/is-negative-zerof"
+        "@stdlib/math/base/assert/is-negative-zerof",
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset"
       ]
     }
   ]
diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/src/addon.c b/lib/node_modules/@stdlib/stats/base/sminsorted/src/addon.c
new file mode 100644
index 000000000000..ed151bc8e5d4
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/sminsorted/src/addon.c
@@ -0,0 +1,60 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/sminsorted.h"
+#include "stdlib/napi/export.h"
+#include "stdlib/napi/argv.h"
+#include "stdlib/napi/argv_int64.h"
+#include "stdlib/napi/argv_strided_float32array.h"
+#include "stdlib/napi/create_double.h"
+#include <node_api.h>
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 3 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_sminsorted( N, X, strideX ), v );
+	return v;
+}
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon_method( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 4 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 );
+	STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_sminsorted_ndarray( N, X, strideX, offsetX ), v );
+	return v;
+}
+
+STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method )
diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/sminsorted/src/addon.cpp
deleted file mode 100644
index 6a69ec5a76b3..000000000000
--- a/lib/node_modules/@stdlib/stats/base/sminsorted/src/addon.cpp
+++ /dev/null
@@ -1,117 +0,0 @@
-/**
-* @license Apache-2.0
-*
-* Copyright (c) 2020 The Stdlib Authors.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-*    http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-
-#include "stdlib/stats/base/sminsorted.h"
-#include <node_api.h>
-#include <stdint.h>
-#include <stdlib.h>
-#include <stdbool.h>
-#include <assert.h>
-
-/**
-* Add-on namespace.
-*/
-namespace stdlib_stats_base_sminsorted {
-
-	/**
-	* Computes the minimum value of a sorted single-precision floating-point strided array.
-	*
-	* ## Notes
-	*
-	* -   When called from JavaScript, the function expects three arguments:
-	*
-	*     -   `N`: number of indexed elements
-	*     -   `X`: sorted input array
-	*     -   `stride`: stride length
-	*/
-	napi_value node_sminsorted( napi_env env, napi_callback_info info ) {
-		napi_status status;
-
-		size_t argc = 3;
-		napi_value argv[ 3 ];
-		status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr );
-		assert( status == napi_ok );
-
-		if ( argc < 3 ) {
-			napi_throw_error( env, nullptr, "invalid invocation. Must provide 3 arguments." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype0;
-		status = napi_typeof( env, argv[ 0 ], &vtype0 );
-		assert( status == napi_ok );
-		if ( vtype0 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." );
-			return nullptr;
-		}
-
-		bool res;
-		status = napi_is_typedarray( env, argv[ 1 ], &res );
-		assert( status == napi_ok );
-		if ( res == false ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype2;
-		status = napi_typeof( env, argv[ 2 ], &vtype2 );
-		assert( status == napi_ok );
-		if ( vtype2 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." );
-			return nullptr;
-		}
-
-		int64_t N;
-		status = napi_get_value_int64( env, argv[ 0 ], &N );
-		assert( status == napi_ok );
-
-		int64_t stride;
-		status = napi_get_value_int64( env, argv[ 2 ], &stride );
-		assert( status == napi_ok );
-
-		napi_typedarray_type vtype1;
-		size_t xlen;
-		void *X;
-		status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr );
-		assert( status == napi_ok );
-		if ( vtype1 != napi_float32_array ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." );
-			return nullptr;
-		}
-		if ( (N-1)*llabs(stride) >= (int64_t)xlen ) {
-			napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." );
-			return nullptr;
-		}
-
-		napi_value v;
-		status = napi_create_double( env, (double)stdlib_strided_sminsorted( N, (float *)X, stride ), &v );
-		assert( status == napi_ok );
-
-		return v;
-	}
-
-	napi_value Init( napi_env env, napi_value exports ) {
-		napi_status status;
-		napi_value fcn;
-		status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_sminsorted, NULL, &fcn );
-		assert( status == napi_ok );
-		return fcn;
-	}
-
-	NAPI_MODULE( NODE_GYP_MODULE_NAME, Init )
-} // end namespace stdlib_stats_base_sminsorted
diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/src/sminsorted.c b/lib/node_modules/@stdlib/stats/base/sminsorted/src/main.c
similarity index 54%
rename from lib/node_modules/@stdlib/stats/base/sminsorted/src/sminsorted.c
rename to lib/node_modules/@stdlib/stats/base/sminsorted/src/main.c
index 010e8b4fecf3..5141b7d0bd7b 100644
--- a/lib/node_modules/@stdlib/stats/base/sminsorted/src/sminsorted.c
+++ b/lib/node_modules/@stdlib/stats/base/sminsorted/src/main.c
@@ -19,33 +19,43 @@
 #include "stdlib/stats/base/sminsorted.h"
 #include "stdlib/math/base/assert/is_nanf.h"
 #include "stdlib/math/base/assert/is_negative_zerof.h"
-#include <stdint.h>
+#include "stdlib/blas/base/shared.h"
+#include "stdlib/strided/base/stride2offset.h"
 
 /**
 * Computes the minimum value of a sorted single-precision floating-point strided array.
 *
-* @param N       number of indexed elements
-* @param X       sorted input array
-* @param stride  stride length
-* @return        output value
+* @param N        number of indexed elements
+* @param X        sorted input array
+* @param strideX  stride length
+* @return         output value
 */
-float stdlib_strided_sminsorted( const int64_t N, const float *X, const int64_t stride ) {
+float API_SUFFIX(stdlib_strided_sminsorted)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX ) {
+	const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX );
+	return API_SUFFIX(stdlib_strided_sminsorted_ndarray)( N, X, strideX, ox );
+}
+
+/**
+* Computes the minimum value of a sorted single-precision floating-point strided array using alternative indexing semantics.
+*
+* @param N        number of indexed elements
+* @param X        sorted input array
+* @param strideX  stride length
+* @param offsetX  starting index for X
+* @return         output value
+*/
+float API_SUFFIX(stdlib_strided_sminsorted_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) {
 	float v1;
 	float v2;
 
 	if ( N <= 0 ) {
 		return 0.0f / 0.0f; // NaN
 	}
-	if ( N == 1 || stride == 0 ) {
+	if ( N == 1 || strideX == 0 ) {
 		return X[ 0 ];
 	}
-	if ( stride < 0 ) {
-		v1 = X[ (1-N) * stride ];
-		v2 = X[ 0 ];
-	} else {
-		v1 = X[ 0 ];
-		v2 = X[ (N-1) * stride ];
-	}
+	v1 = X[ offsetX ];
+	v2 = X[ ( (N-1)*strideX ) + offsetX ];
 	if ( stdlib_base_is_nanf( v1 ) || stdlib_base_is_nanf( v2 ) ) {
 		return 0.0f / 0.0f; // NaN
 	}
diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/sminsorted/test/test.ndarray.js
index 957da06a2064..b04416da13d8 100644
--- a/lib/node_modules/@stdlib/stats/base/sminsorted/test/test.ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/sminsorted/test/test.ndarray.js
@@ -21,7 +21,6 @@
 // MODULES //
 
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
 var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' );
 var Float32Array = require( '@stdlib/array/float32' );
@@ -116,7 +115,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 });
 
 tape( 'the function supports a `stride` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -125,21 +123,19 @@ tape( 'the function supports a `stride` parameter', function test( t ) {
 		2.0,
 		2.0,  // 1
 		-7.0,
-		3.0, // 2
+		3.0,  // 2
 		3.0,
 		4.0,  // 3
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = sminsorted( N, x, 2, 0 );
+	v = sminsorted( 4, x, 2, 0 );
 
 	t.strictEqual( v, 1.0, 'returns expected value' );
 	t.end();
 });
 
 tape( 'the function supports a negative `stride` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -154,8 +150,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t )
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = sminsorted( N, x, -2, 6 );
+	v = sminsorted( 4, x, -2, 6 );
 
 	t.strictEqual( v, 1.0, 'returns expected value' );
 	t.end();
@@ -174,7 +169,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f
 });
 
 tape( 'the function supports an `offset` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -188,9 +182,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) {
 		3.0,
 		4.0   // 3
 	]);
-	N = floor( x.length / 2 );
 
-	v = sminsorted( N, x, 2, 1 );
+	v = sminsorted( 4, x, 2, 1 );
 	t.strictEqual( v, 1.0, 'returns expected value' );
 
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/sminsorted/test/test.ndarray.native.js
index 63b639f20159..31a8b7596f9c 100644
--- a/lib/node_modules/@stdlib/stats/base/sminsorted/test/test.ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/sminsorted/test/test.ndarray.native.js
@@ -22,7 +22,6 @@
 
 var resolve = require( 'path' ).resolve;
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
 var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' );
 var Float32Array = require( '@stdlib/array/float32' );
@@ -125,7 +124,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 });
 
 tape( 'the function supports a `stride` parameter', opts, function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -134,21 +132,19 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) {
 		2.0,
 		2.0,  // 1
 		-7.0,
-		3.0, // 2
+		3.0,  // 2
 		3.0,
 		4.0,  // 3
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = sminsorted( N, x, 2, 0 );
+	v = sminsorted( 4, x, 2, 0 );
 
 	t.strictEqual( v, 1.0, 'returns expected value' );
 	t.end();
 });
 
 tape( 'the function supports a negative `stride` parameter', opts, function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -163,8 +159,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = sminsorted( N, x, -2, 6 );
+	v = sminsorted( 4, x, -2, 6 );
 
 	t.strictEqual( v, 1.0, 'returns expected value' );
 	t.end();
@@ -183,7 +178,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f
 });
 
 tape( 'the function supports an `offset` parameter', opts, function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -197,9 +191,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) {
 		3.0,
 		4.0   // 3
 	]);
-	N = floor( x.length / 2 );
 
-	v = sminsorted( N, x, 2, 1 );
+	v = sminsorted( 4, x, 2, 1 );
 	t.strictEqual( v, 1.0, 'returns expected value' );
 
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/test/test.sminsorted.js b/lib/node_modules/@stdlib/stats/base/sminsorted/test/test.sminsorted.js
index 1335e2c4c2b5..8dcf5387c212 100644
--- a/lib/node_modules/@stdlib/stats/base/sminsorted/test/test.sminsorted.js
+++ b/lib/node_modules/@stdlib/stats/base/sminsorted/test/test.sminsorted.js
@@ -21,7 +21,6 @@
 // MODULES //
 
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
 var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' );
 var Float32Array = require( '@stdlib/array/float32' );
@@ -116,7 +115,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 });
 
 tape( 'the function supports a `stride` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -131,15 +129,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) {
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = sminsorted( N, x, 2 );
+	v = sminsorted( 4, x, 2 );
 
 	t.strictEqual( v, 1.0, 'returns expected value' );
 	t.end();
 });
 
 tape( 'the function supports a negative `stride` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -154,8 +150,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t )
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = sminsorted( N, x, -2 );
+	v = sminsorted( 4, x, -2 );
 
 	t.strictEqual( v, 1.0, 'returns expected value' );
 	t.end();
@@ -176,7 +171,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f
 tape( 'the function supports view offsets', function test( t ) {
 	var x0;
 	var x1;
-	var N;
 	var v;
 
 	x0 = new Float32Array([
@@ -192,9 +186,8 @@ tape( 'the function supports view offsets', function test( t ) {
 	]);
 
 	x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
-	N = floor(x1.length / 2);
 
-	v = sminsorted( N, x1, 2 );
+	v = sminsorted( 4, x1, 2 );
 	t.strictEqual( v, 1.0, 'returns expected value' );
 
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/sminsorted/test/test.sminsorted.native.js b/lib/node_modules/@stdlib/stats/base/sminsorted/test/test.sminsorted.native.js
index 5ce498094816..56d2100968ad 100644
--- a/lib/node_modules/@stdlib/stats/base/sminsorted/test/test.sminsorted.native.js
+++ b/lib/node_modules/@stdlib/stats/base/sminsorted/test/test.sminsorted.native.js
@@ -22,7 +22,6 @@
 
 var resolve = require( 'path' ).resolve;
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
 var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' );
 var Float32Array = require( '@stdlib/array/float32' );
@@ -125,7 +124,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 });
 
 tape( 'the function supports a `stride` parameter', opts, function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -140,15 +138,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) {
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = sminsorted( N, x, 2 );
+	v = sminsorted( 4, x, 2 );
 
 	t.strictEqual( v, 1.0, 'returns expected value' );
 	t.end();
 });
 
 tape( 'the function supports a negative `stride` parameter', opts, function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -163,8 +159,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = sminsorted( N, x, -2 );
+	v = sminsorted( 4, x, -2 );
 
 	t.strictEqual( v, 1.0, 'returns expected value' );
 	t.end();
@@ -185,7 +180,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f
 tape( 'the function supports view offsets', opts, function test( t ) {
 	var x0;
 	var x1;
-	var N;
 	var v;
 
 	x0 = new Float32Array([
@@ -201,9 +195,8 @@ tape( 'the function supports view offsets', opts, function test( t ) {
 	]);
 
 	x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
-	N = floor(x1.length / 2);
 
-	v = sminsorted( N, x1, 2 );
+	v = sminsorted( 4, x1, 2 );
 	t.strictEqual( v, 1.0, 'returns expected value' );
 
 	t.end();

From bcae23ba678b106da4d9935afe6f15f8cf7e1778 Mon Sep 17 00:00:00 2001
From: Aayush Khanna <96649223+aayush0325@users.noreply.github.com>
Date: Sat, 4 Jan 2025 03:34:31 +0530
Subject: [PATCH 81/87] feat: add C ndarray interface and refactor
 implementation for `stats/base/smediansorted`

PR-URL: https://github.com/stdlib-js/stdlib/pull/4490
Co-authored-by: Athan Reines <kgryte@gmail.com>
Reviewed-by: Athan Reines <kgryte@gmail.com>
---
 .../stats/base/smediansorted/README.md        | 156 +++++++++++++++---
 .../base/smediansorted/benchmark/benchmark.js |  17 +-
 .../benchmark/benchmark.native.js             |  13 +-
 .../benchmark/benchmark.ndarray.js            |  17 +-
 .../benchmark/benchmark.ndarray.native.js     |  13 +-
 .../benchmark/c/benchmark.length.c            |  54 +++++-
 .../stats/base/smediansorted/docs/repl.txt    |  26 ++-
 .../base/smediansorted/docs/types/index.d.ts  |  12 +-
 .../base/smediansorted/examples/c/example.c   |   9 +-
 .../base/smediansorted/examples/index.js      |  13 +-
 .../stats/base/smediansorted/include.gypi     |   2 +-
 .../include/stdlib/stats/base/smediansorted.h |   9 +-
 .../stats/base/smediansorted/lib/index.js     |   4 +-
 .../stats/base/smediansorted/lib/ndarray.js   |  14 +-
 .../base/smediansorted/lib/ndarray.native.js  |  20 +--
 .../base/smediansorted/lib/smediansorted.js   |  29 +---
 .../smediansorted/lib/smediansorted.native.js |   6 +-
 .../stats/base/smediansorted/manifest.json    |  69 +++++++-
 .../stats/base/smediansorted/src/addon.c      |  60 +++++++
 .../stats/base/smediansorted/src/addon.cpp    | 117 -------------
 .../stats/base/smediansorted/src/main.c       |  58 +++++++
 .../base/smediansorted/src/smediansorted.c    |  49 ------
 .../base/smediansorted/test/test.ndarray.js   |  13 +-
 .../smediansorted/test/test.ndarray.native.js |  13 +-
 .../smediansorted/test/test.smediansorted.js  |  13 +-
 .../test/test.smediansorted.native.js         |  13 +-
 26 files changed, 459 insertions(+), 360 deletions(-)
 create mode 100644 lib/node_modules/@stdlib/stats/base/smediansorted/src/addon.c
 delete mode 100644 lib/node_modules/@stdlib/stats/base/smediansorted/src/addon.cpp
 create mode 100644 lib/node_modules/@stdlib/stats/base/smediansorted/src/main.c
 delete mode 100644 lib/node_modules/@stdlib/stats/base/smediansorted/src/smediansorted.c

diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/README.md b/lib/node_modules/@stdlib/stats/base/smediansorted/README.md
index a1445f4a465a..dcae19495563 100644
--- a/lib/node_modules/@stdlib/stats/base/smediansorted/README.md
+++ b/lib/node_modules/@stdlib/stats/base/smediansorted/README.md
@@ -36,7 +36,7 @@ limitations under the License.
 var smediansorted = require( '@stdlib/stats/base/smediansorted' );
 ```
 
-#### smediansorted( N, x, stride )
+#### smediansorted( N, x, strideX )
 
 Computes the median value of a sorted single-precision floating-point strided array `x`.
 
@@ -56,18 +56,16 @@ The function has the following parameters:
 
 -   **N**: number of indexed elements.
 -   **x**: sorted input [`Float32Array`][@stdlib/array/float32].
--   **stride**: index increment for `x`.
+-   **strideX**: stride length for `x`.
 
-The `N` and `stride` parameters determine which elements in `x` are accessed at runtime. For example, to compute the median value of every other element in `x`,
+The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the median value of every other element in `x`,
 
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x = new Float32Array( [ 1.0, 2.0, 2.0, -7.0, 3.0, 3.0, 4.0, 2.0 ] );
-var N = floor( x.length / 2 );
 
-var v = smediansorted( N, x, 2 );
+var v = smediansorted( 4, x, 2 );
 // returns 2.5
 ```
 
@@ -77,18 +75,15 @@ Note that indexing is relative to the first index. To introduce an offset, use [
 
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x0 = new Float32Array( [ 2.0, 1.0, 2.0, 2.0, -2.0, 2.0, 3.0, 4.0 ] );
 var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
 
-var N = floor( x0.length / 2 );
-
-var v = smediansorted( N, x1, 2 );
+var v = smediansorted( 4, x1, 2 );
 // returns 2.0
 ```
 
-#### smediansorted.ndarray( N, x, stride, offset )
+#### smediansorted.ndarray( N, x, strideX, offsetX )
 
 Computes the median value of a sorted single-precision floating-point strided array using alternative indexing semantics.
 
@@ -96,9 +91,8 @@ Computes the median value of a sorted single-precision floating-point strided ar
 var Float32Array = require( '@stdlib/array/float32' );
 
 var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );
-var N = x.length;
 
-var v = smediansorted.ndarray( N, x, 1, 0 );
+var v = smediansorted.ndarray( x.length, x, 1, 0 );
 // returns 2.0
 ```
 
@@ -106,16 +100,14 @@ The function has the following additional parameters:
 
 -   **offset**: starting index for `x`.
 
-While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying `buffer`, the `offset` parameter supports indexing semantics based on a starting index. For example, to calculate the median value for every other value in `x` starting from the second value
+While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to calculate the median value for every other element in `x` starting from the second element
 
 ```javascript
 var Float32Array = require( '@stdlib/array/float32' );
-var floor = require( '@stdlib/math/base/special/floor' );
 
 var x = new Float32Array( [ 2.0, 1.0, 2.0, 2.0, -2.0, 2.0, 3.0, 4.0 ] );
-var N = floor( x.length / 2 );
 
-var v = smediansorted.ndarray( N, x, 2, 1 );
+var v = smediansorted.ndarray( 4, x, 2, 1 );
 // returns 2.0
 ```
 
@@ -141,16 +133,13 @@ var v = smediansorted.ndarray( N, x, 2, 1 );
 <!-- eslint no-undef: "error" -->
 
 ```javascript
-var Float32Array = require( '@stdlib/array/float32' );
+var linspace = require( '@stdlib/array/linspace' );
 var smediansorted = require( '@stdlib/stats/base/smediansorted' );
 
-var x;
-var i;
-
-x = new Float32Array( 10 );
-for ( i = 0; i < x.length; i++ ) {
-    x[ i ] = i - 5.0;
-}
+var options = {
+    'dtype': 'float32'
+};
+var x = linspace( -5.0, 5.0, 10, options );
 console.log( x );
 
 var v = smediansorted( x.length, x, 1 );
@@ -161,6 +150,123 @@ console.log( v );
 
 <!-- /.examples -->
 
+<!-- C interface documentation. -->
+
+* * *
+
+<section class="c">
+
+## C APIs
+
+<!-- Section to include introductory text. Make sure to keep an empty line after the intro `section` element and another before the `/section` close. -->
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<!-- C usage documentation. -->
+
+<section class="usage">
+
+### Usage
+
+```c
+#include "stdlib/stats/base/smediansorted.h"
+```
+
+#### stdlib_strided_smediansorted( N, \*X, strideX )
+
+Computes the median value of a sorted single-precision floating-point strided array.
+
+```c
+const float x[] = { 1.0f, 2.0f, 3.0f };
+
+float v = stdlib_strided_smediansorted( 3, x, 1 );
+// returns 2.0f
+```
+
+The function accepts the following arguments:
+
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **X**: `[in] float*` input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+
+```c
+float stdlib_strided_smediansorted( const CBLAS_INT N, const float *X, const CBLAS_INT strideX );
+```
+
+#### stdlib_strided_smediansorted_ndarray( N, \*X, strideX, offsetX )
+
+Computes the median value of a sorted single-precision floating-point strided array using alternative indexing semantics.
+
+```c
+const float x[] = { 1.0f, 2.0f, 3.0f };
+
+float v = stdlib_strided_smediansorted_ndarray( 3, x, 1, 0 );
+// returns 2.0f
+```
+
+The function accepts the following arguments:
+
+-   **N**: `[in] CBLAS_INT` number of indexed elements.
+-   **X**: `[in] float*` input array.
+-   **strideX**: `[in] CBLAS_INT` stride length for `X`.
+-   **offsetX**: `[in] CBLAS_INT` starting index for `X`.
+
+```c
+float stdlib_strided_smediansorted_ndarray( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX );
+```
+
+</section>
+
+<!-- /.usage -->
+
+<!-- C API usage notes. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="notes">
+
+</section>
+
+<!-- /.notes -->
+
+<!-- C API usage examples. -->
+
+<section class="examples">
+
+### Examples
+
+```c
+#include "stdlib/stats/base/smediansorted.h"
+#include <stdio.h>
+
+int main( void ) {
+    // Create a strided array:
+    const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f };
+
+    // Specify the number of elements:
+    const int N = 4;
+
+    // Specify the stride length:
+    const int strideX = 2;
+
+    // Compute the median value:
+    float v = stdlib_strided_smediansorted( N, x, strideX );
+
+    // Print the result:
+    printf( "median: %f\n", v );
+}
+```
+
+</section>
+
+<!-- /.examples -->
+
+</section>
+
+<!-- /.c -->
+
 <!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
 
 <section class="related">
diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/benchmark/benchmark.js b/lib/node_modules/@stdlib/stats/base/smediansorted/benchmark/benchmark.js
index aa0d2b00e3dc..49eb9f882fe4 100644
--- a/lib/node_modules/@stdlib/stats/base/smediansorted/benchmark/benchmark.js
+++ b/lib/node_modules/@stdlib/stats/base/smediansorted/benchmark/benchmark.js
@@ -22,12 +22,19 @@
 
 var bench = require( '@stdlib/bench' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
+var linspace = require( '@stdlib/array/linspace' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float32Array = require( '@stdlib/array/float32' );
 var pkg = require( './../package.json' ).name;
 var smediansorted = require( './../lib/smediansorted.js' );
 
 
+// VARIABLES //
+
+var options = {
+	'dtype': 'float32'
+};
+
+
 // FUNCTIONS //
 
 /**
@@ -38,13 +45,7 @@ var smediansorted = require( './../lib/smediansorted.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float32Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = i;
-	}
+	var x = linspace( -len/2, len/2, len, options );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/benchmark/benchmark.native.js b/lib/node_modules/@stdlib/stats/base/smediansorted/benchmark/benchmark.native.js
index 44e26264be5b..44f95e1af499 100644
--- a/lib/node_modules/@stdlib/stats/base/smediansorted/benchmark/benchmark.native.js
+++ b/lib/node_modules/@stdlib/stats/base/smediansorted/benchmark/benchmark.native.js
@@ -23,8 +23,8 @@
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
+var linspace = require( '@stdlib/array/linspace' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float32Array = require( '@stdlib/array/float32' );
 var tryRequire = require( '@stdlib/utils/try-require' );
 var pkg = require( './../package.json' ).name;
 
@@ -35,6 +35,9 @@ var smediansorted = tryRequire( resolve( __dirname, './../lib/smediansorted.nati
 var opts = {
 	'skip': ( smediansorted instanceof Error )
 };
+var options = {
+	'dtype': 'float32'
+};
 
 
 // FUNCTIONS //
@@ -47,13 +50,7 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float32Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = i;
-	}
+	var x = linspace( -len/2, len/2, len, options );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/benchmark/benchmark.ndarray.js b/lib/node_modules/@stdlib/stats/base/smediansorted/benchmark/benchmark.ndarray.js
index d0dec1cbc22e..12620874edb7 100644
--- a/lib/node_modules/@stdlib/stats/base/smediansorted/benchmark/benchmark.ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/smediansorted/benchmark/benchmark.ndarray.js
@@ -22,12 +22,19 @@
 
 var bench = require( '@stdlib/bench' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
+var linspace = require( '@stdlib/array/linspace' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float32Array = require( '@stdlib/array/float32' );
 var pkg = require( './../package.json' ).name;
 var smediansorted = require( './../lib/ndarray.js' );
 
 
+// VARIABLES //
+
+var options = {
+	'dtype': 'float32'
+};
+
+
 // FUNCTIONS //
 
 /**
@@ -38,13 +45,7 @@ var smediansorted = require( './../lib/ndarray.js' );
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float32Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = i;
-	}
+	var x = linspace( -len/2, len/2, len, options );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/benchmark/benchmark.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/smediansorted/benchmark/benchmark.ndarray.native.js
index 9e992b40939f..1c75037ae063 100644
--- a/lib/node_modules/@stdlib/stats/base/smediansorted/benchmark/benchmark.ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/smediansorted/benchmark/benchmark.ndarray.native.js
@@ -23,8 +23,8 @@
 var resolve = require( 'path' ).resolve;
 var bench = require( '@stdlib/bench' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
+var linspace = require( '@stdlib/array/linspace' );
 var pow = require( '@stdlib/math/base/special/pow' );
-var Float32Array = require( '@stdlib/array/float32' );
 var tryRequire = require( '@stdlib/utils/try-require' );
 var pkg = require( './../package.json' ).name;
 
@@ -35,6 +35,9 @@ var smediansorted = tryRequire( resolve( __dirname, './../lib/ndarray.native.js'
 var opts = {
 	'skip': ( smediansorted instanceof Error )
 };
+var options = {
+	'dtype': 'float32'
+};
 
 
 // FUNCTIONS //
@@ -47,13 +50,7 @@ var opts = {
 * @returns {Function} benchmark function
 */
 function createBenchmark( len ) {
-	var x;
-	var i;
-
-	x = new Float32Array( len );
-	for ( i = 0; i < x.length; i++ ) {
-		x[ i ] = i;
-	}
+	var x = linspace( -len/2, len/2, len, options );
 	return benchmark;
 
 	function benchmark( b ) {
diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/benchmark/c/benchmark.length.c b/lib/node_modules/@stdlib/stats/base/smediansorted/benchmark/c/benchmark.length.c
index e0b375995782..c7c02d5582b7 100644
--- a/lib/node_modules/@stdlib/stats/base/smediansorted/benchmark/c/benchmark.length.c
+++ b/lib/node_modules/@stdlib/stats/base/smediansorted/benchmark/c/benchmark.length.c
@@ -82,9 +82,9 @@ static double tic( void ) {
 *
 * @return random number
 */
-static double rand_double( void ) {
+static float rand_float( void ) {
 	int r = rand();
-	return (double)r / ( (double)RAND_MAX + 1.0 );
+	return (float)r / ( (float)RAND_MAX + 1.0f );
 }
 
 /**
@@ -94,7 +94,7 @@ static double rand_double( void ) {
 * @param len          array length
 * @return             elapsed time in seconds
 */
-static double benchmark( int iterations, int len ) {
+static double benchmark1( int iterations, int len ) {
 	double elapsed;
 	float x[ len ];
 	float v;
@@ -107,6 +107,7 @@ static double benchmark( int iterations, int len ) {
 	v = 0.0f;
 	t = tic();
 	for ( i = 0; i < iterations; i++ ) {
+		// cppcheck-suppress uninitvar
 		v = stdlib_strided_smediansorted( len, x, 1 );
 		if ( v != v ) {
 			printf( "should not return NaN\n" );
@@ -120,6 +121,40 @@ static double benchmark( int iterations, int len ) {
 	return elapsed;
 }
 
+/**
+* Runs a benchmark.
+*
+* @param iterations   number of iterations
+* @param len          array length
+* @return             elapsed time in seconds
+*/
+static double benchmark2( int iterations, int len ) {
+	double elapsed;
+	float x[ len ];
+	float v;
+	double t;
+	int i;
+
+	for ( i = 0; i < len; i++ ) {
+		x[ i ] = i;
+	}
+	v = 0.0f;
+	t = tic();
+	for ( i = 0; i < iterations; i++ ) {
+		// cppcheck-suppress uninitvar
+		v = stdlib_strided_smediansorted_ndarray( len, x, 1, 0 );
+		if ( v != v ) {
+			printf( "should not return NaN\n" );
+			break;
+		}
+	}
+	elapsed = tic() - t;
+	if ( v != v ) {
+		printf( "should not return NaN\n" );
+	}
+	return elapsed;
+}
+
 /**
 * Main execution sequence.
 */
@@ -142,7 +177,18 @@ int main( void ) {
 		for ( j = 0; j < REPEATS; j++ ) {
 			count += 1;
 			printf( "# c::%s:len=%d\n", NAME, len );
-			elapsed = benchmark( iter, len );
+			elapsed = benchmark1( iter, len );
+			print_results( iter, elapsed );
+			printf( "ok %d benchmark finished\n", count );
+		}
+	}
+	for ( i = MIN; i <= MAX; i++ ) {
+		len = pow( 10, i );
+		iter = ITERATIONS;
+		for ( j = 0; j < REPEATS; j++ ) {
+			count += 1;
+			printf( "# c::%s:ndarray:len=%d\n", NAME, len );
+			elapsed = benchmark2( iter, len );
 			print_results( iter, elapsed );
 			printf( "ok %d benchmark finished\n", count );
 		}
diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/docs/repl.txt b/lib/node_modules/@stdlib/stats/base/smediansorted/docs/repl.txt
index 3f60345acbca..2ac1f6be73a4 100644
--- a/lib/node_modules/@stdlib/stats/base/smediansorted/docs/repl.txt
+++ b/lib/node_modules/@stdlib/stats/base/smediansorted/docs/repl.txt
@@ -1,13 +1,13 @@
 
-{{alias}}( N, x, stride )
+{{alias}}( N, x, strideX )
     Computes the median value of a sorted single-precision floating-point
     strided array.
 
     The input strided array must be sorted in either strictly ascending or
     descending order.
 
-    The `N` and `stride` parameters determine which elements in `x` are accessed
-    at runtime.
+    The `N` and stride parameters determine which elements in the strided array
+    are accessed at runtime.
 
     Indexing is relative to the first index. To introduce an offset, use a typed
     array view.
@@ -22,7 +22,7 @@
     x: Float32Array
         Sorted input array.
 
-    stride: integer
+    strideX: integer
         Index increment.
 
     Returns
@@ -37,20 +37,19 @@
     > {{alias}}( x.length, x, 1 )
     2.0
 
-    // Using `N` and `stride` parameters:
+    // Using `N` and stride parameters:
     > x = new {{alias:@stdlib/array/float32}}( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > {{alias}}( N, x, 2 )
+    > {{alias}}( 3, x, 2 )
     1.0
 
     // Using view offsets:
     > var x0 = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );
     > var x1 = new {{alias:@stdlib/array/float32}}( x0.buffer, x0.BYTES_PER_ELEMENT*1 );
-    > N = {{alias:@stdlib/math/base/special/floor}}( x0.length / 2 );
-    > {{alias}}( N, x1, 2 )
+    > {{alias}}( 3, x1, 2 )
     2.0
 
-{{alias}}.ndarray( N, x, stride, offset )
+
+{{alias}}.ndarray( N, x, strideX, offsetX )
     Computes the median value of a sorted single-precision floating-point
     strided array using alternative indexing semantics.
 
@@ -66,10 +65,10 @@
     x: Float32Array
         Sorted input array.
 
-    stride: integer
+    strideX: integer
         Index increment.
 
-    offset: integer
+    offsetX: integer
         Starting index.
 
     Returns
@@ -86,8 +85,7 @@
 
     // Using offset parameter:
     > var x = new {{alias:@stdlib/array/float32}}( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );
-    > var N = {{alias:@stdlib/math/base/special/floor}}( x.length / 2 );
-    > {{alias}}.ndarray( N, x, 2, 1 )
+    > {{alias}}.ndarray( 3, x, 2, 1 )
     2.0
 
     See Also
diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/smediansorted/docs/types/index.d.ts
index 948b796c94c9..e1ec1dd684eb 100644
--- a/lib/node_modules/@stdlib/stats/base/smediansorted/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/smediansorted/docs/types/index.d.ts
@@ -27,7 +27,7 @@ interface Routine {
 	*
 	* @param N - number of indexed elements
 	* @param x - sorted input array
-	* @param stride - stride length
+	* @param strideX - stride length
 	* @returns median value
 	*
 	* @example
@@ -38,15 +38,15 @@ interface Routine {
 	* var v = smediansorted( x.length, x, 1 );
 	* // returns 2.0
 	*/
-	( N: number, x: Float32Array, stride: number ): number;
+	( N: number, x: Float32Array, strideX: number ): number;
 
 	/**
 	* Computes the median value of a sorted single-precision floating-point strided array using alternative indexing semantics.
 	*
 	* @param N - number of indexed elements
 	* @param x - sorted input array
-	* @param stride - stride length
-	* @param offset - starting index
+	* @param strideX - stride length
+	* @param offsetX - starting index
 	* @returns median value
 	*
 	* @example
@@ -57,7 +57,7 @@ interface Routine {
 	* var v = smediansorted.ndarray( x.length, x, 1, 0 );
 	* // returns 2.0
 	*/
-	ndarray( N: number, x: Float32Array, stride: number, offset: number ): number;
+	ndarray( N: number, x: Float32Array, strideX: number, offsetX: number ): number;
 }
 
 /**
@@ -65,7 +65,7 @@ interface Routine {
 *
 * @param N - number of indexed elements
 * @param x - sorted input array
-* @param stride - stride length
+* @param strideX - stride length
 * @returns median value
 *
 * @example
diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/examples/c/example.c b/lib/node_modules/@stdlib/stats/base/smediansorted/examples/c/example.c
index 727a623326a9..52975dfde647 100644
--- a/lib/node_modules/@stdlib/stats/base/smediansorted/examples/c/example.c
+++ b/lib/node_modules/@stdlib/stats/base/smediansorted/examples/c/example.c
@@ -17,21 +17,20 @@
 */
 
 #include "stdlib/stats/base/smediansorted.h"
-#include <stdint.h>
 #include <stdio.h>
 
 int main( void ) {
 	// Create a strided array:
-	float x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 };
+	const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f };
 
 	// Specify the number of elements:
-	int64_t N = 4;
+	const int N = 4;
 
 	// Specify the stride length:
-	int64_t stride = 2;
+	const int strideX = 2;
 
 	// Compute the median value:
-	float v = stdlib_strided_smediansorted( N, x, stride );
+	float v = stdlib_strided_smediansorted( N, x, strideX );
 
 	// Print the result:
 	printf( "median: %f\n", v );
diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/examples/index.js b/lib/node_modules/@stdlib/stats/base/smediansorted/examples/index.js
index f2e77652484e..c463db67f1c7 100644
--- a/lib/node_modules/@stdlib/stats/base/smediansorted/examples/index.js
+++ b/lib/node_modules/@stdlib/stats/base/smediansorted/examples/index.js
@@ -18,16 +18,13 @@
 
 'use strict';
 
-var Float32Array = require( '@stdlib/array/float32' );
+var linspace = require( '@stdlib/array/linspace' );
 var smediansorted = require( './../lib' );
 
-var x;
-var i;
-
-x = new Float32Array( 10 );
-for ( i = 0; i < x.length; i++ ) {
-	x[ i ] = i - 5.0;
-}
+var options = {
+	'dtype': 'float32'
+};
+var x = linspace( -5.0, 5.0, 10, options );
 console.log( x );
 
 var v = smediansorted( x.length, x, 1 );
diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/include.gypi b/lib/node_modules/@stdlib/stats/base/smediansorted/include.gypi
index 868c5c12e852..26476a8c2655 100644
--- a/lib/node_modules/@stdlib/stats/base/smediansorted/include.gypi
+++ b/lib/node_modules/@stdlib/stats/base/smediansorted/include.gypi
@@ -36,7 +36,7 @@
 
     # Source files:
     'src_files': [
-      '<(src_dir)/addon.cpp',
+      '<(src_dir)/addon.c',
       '<!@(node -e "var arr = require(\'@stdlib/utils/library-manifest\')(\'./manifest.json\',{},{\'basedir\':process.cwd(),\'paths\':\'posix\'}).src; for ( var i = 0; i < arr.length; i++ ) { console.log( arr[ i ] ); }")',
     ],
 
diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/include/stdlib/stats/base/smediansorted.h b/lib/node_modules/@stdlib/stats/base/smediansorted/include/stdlib/stats/base/smediansorted.h
index 63a193017af9..c6d4b5a3eb84 100644
--- a/lib/node_modules/@stdlib/stats/base/smediansorted/include/stdlib/stats/base/smediansorted.h
+++ b/lib/node_modules/@stdlib/stats/base/smediansorted/include/stdlib/stats/base/smediansorted.h
@@ -19,7 +19,7 @@
 #ifndef STDLIB_STATS_BASE_SMEDIANSORTED_H
 #define STDLIB_STATS_BASE_SMEDIANSORTED_H
 
-#include <stdint.h>
+#include "stdlib/blas/base/shared.h"
 
 /*
 * If C++, prevent name mangling so that the compiler emits a binary file having undecorated names, thus mirroring the behavior of a C compiler.
@@ -31,7 +31,12 @@ extern "C" {
 /**
 * Computes the median value of a sorted single-precision floating-point strided array.
 */
-float stdlib_strided_smediansorted( const int64_t N, const float *X, const int64_t stride );
+float API_SUFFIX(stdlib_strided_smediansorted)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX );
+
+/**
+* Computes the median value of a sorted single-precision floating-point strided array using alternative indexing semantics.
+*/
+float API_SUFFIX(stdlib_strided_smediansorted_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX );
 
 #ifdef __cplusplus
 }
diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/lib/index.js b/lib/node_modules/@stdlib/stats/base/smediansorted/lib/index.js
index c3c940d36aec..b72bc656d954 100644
--- a/lib/node_modules/@stdlib/stats/base/smediansorted/lib/index.js
+++ b/lib/node_modules/@stdlib/stats/base/smediansorted/lib/index.js
@@ -34,13 +34,11 @@
 *
 * @example
 * var Float32Array = require( '@stdlib/array/float32' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 * var smediansorted = require( '@stdlib/stats/base/smediansorted' );
 *
 * var x = new Float32Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
-* var N = floor( x.length / 2 );
 *
-* var v = smediansorted.ndarray( N, x, 2, 1 );
+* var v = smediansorted.ndarray( 4, x, 2, 1 );
 * // returns 0.0
 */
 
diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/lib/ndarray.js b/lib/node_modules/@stdlib/stats/base/smediansorted/lib/ndarray.js
index 6afedb060092..ea4df53a4263 100644
--- a/lib/node_modules/@stdlib/stats/base/smediansorted/lib/ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/smediansorted/lib/ndarray.js
@@ -31,21 +31,19 @@ var floor = require( '@stdlib/math/base/special/floor' );
 *
 * @param {PositiveInteger} N - number of indexed elements
 * @param {Float32Array} x - sorted input array
-* @param {integer} stride - stride length
-* @param {NonNegativeInteger} offset - starting index
+* @param {integer} strideX - stride length
+* @param {NonNegativeInteger} offsetX - starting index
 * @returns {number} median value
 *
 * @example
 * var Float32Array = require( '@stdlib/array/float32' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 *
 * var x = new Float32Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
-* var N = floor( x.length / 2 );
 *
-* var v = smediansorted( N, x, 2, 1 );
+* var v = smediansorted( 4, x, 2, 1 );
 * // returns 0.0
 */
-function smediansorted( N, x, stride, offset ) {
+function smediansorted( N, x, strideX, offsetX ) {
 	var n;
 	var m;
 
@@ -56,10 +54,10 @@ function smediansorted( N, x, stride, offset ) {
 	m = floor( n );
 	if ( n === m ) {
 		// Even number of elements...
-		return float64ToFloat32( float64ToFloat32( x[ offset+(m*stride) ] + x[ offset+((m-1)*stride) ] ) / 2.0 ); // eslint-disable-line max-len
+		return float64ToFloat32( float64ToFloat32( x[ offsetX+(m*strideX) ] + x[ offsetX+((m-1)*strideX) ] ) / 2.0 ); // eslint-disable-line max-len
 	}
 	// Odd number of elements...
-	return x[ offset+(m*stride) ];
+	return x[ offsetX+(m*strideX) ];
 }
 
 
diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/lib/ndarray.native.js b/lib/node_modules/@stdlib/stats/base/smediansorted/lib/ndarray.native.js
index da59286ed6e6..1e1454676234 100644
--- a/lib/node_modules/@stdlib/stats/base/smediansorted/lib/ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/smediansorted/lib/ndarray.native.js
@@ -20,8 +20,7 @@
 
 // MODULES //
 
-var Float32Array = require( '@stdlib/array/float32' );
-var addon = require( './smediansorted.native.js' );
+var addon = require( './../src/addon.node' );
 
 
 // MAIN //
@@ -31,27 +30,20 @@ var addon = require( './smediansorted.native.js' );
 *
 * @param {PositiveInteger} N - number of indexed elements
 * @param {Float32Array} x - sorted input array
-* @param {integer} stride - stride length
-* @param {NonNegativeInteger} offset - starting index
+* @param {integer} strideX - stride length
+* @param {NonNegativeInteger} offsetX - starting index
 * @returns {number} median value
 *
 * @example
 * var Float32Array = require( '@stdlib/array/float32' );
-* var floor = require( '@stdlib/math/base/special/floor' );
 *
 * var x = new Float32Array( [ 2.0, -3.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
-* var N = floor( x.length / 2 );
 *
-* var v = smediansorted( N, x, 2, 1 );
+* var v = smediansorted( 4, x, 2, 1 );
 * // returns 0.0
 */
-function smediansorted( N, x, stride, offset ) {
-	var view;
-	if ( stride < 0 ) {
-		offset += (N-1) * stride;
-	}
-	view = new Float32Array( x.buffer, x.byteOffset+(x.BYTES_PER_ELEMENT*offset), x.length-offset ); // eslint-disable-line max-len
-	return addon( N, view, stride );
+function smediansorted( N, x, strideX, offsetX ) {
+	return addon.ndarray( N, x, strideX, offsetX );
 }
 
 
diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/lib/smediansorted.js b/lib/node_modules/@stdlib/stats/base/smediansorted/lib/smediansorted.js
index c484afcbf35d..ae926ae41a23 100644
--- a/lib/node_modules/@stdlib/stats/base/smediansorted/lib/smediansorted.js
+++ b/lib/node_modules/@stdlib/stats/base/smediansorted/lib/smediansorted.js
@@ -20,8 +20,8 @@
 
 // MODULES //
 
-var float64ToFloat32 = require( '@stdlib/number/float64/base/to-float32' );
-var floor = require( '@stdlib/math/base/special/floor' );
+var stride2offset = require( '@stdlib/strided/base/stride2offset' );
+var ndarray = require( './ndarray.js' );
 
 
 // MAIN //
@@ -31,7 +31,7 @@ var floor = require( '@stdlib/math/base/special/floor' );
 *
 * @param {PositiveInteger} N - number of indexed elements
 * @param {Float32Array} x - sorted input array
-* @param {integer} stride - stride length
+* @param {integer} strideX - stride length
 * @returns {number} median value
 *
 * @example
@@ -42,27 +42,8 @@ var floor = require( '@stdlib/math/base/special/floor' );
 * var v = smediansorted( x.length, x, 1 );
 * // returns 2.0
 */
-function smediansorted( N, x, stride ) {
-	var offset;
-	var n;
-	var m;
-
-	if ( N <= 0 ) {
-		return NaN;
-	}
-	if ( stride < 0 ) {
-		offset = (1-N) * stride;
-	} else {
-		offset = 0;
-	}
-	n = N / 2;
-	m = floor( n );
-	if ( n === m ) {
-		// Even number of elements...
-		return float64ToFloat32( float64ToFloat32( x[ offset+(m*stride) ] + x[ offset+((m-1)*stride) ] ) / 2.0 ); // eslint-disable-line max-len
-	}
-	// Odd number of elements...
-	return x[ offset+(m*stride) ];
+function smediansorted( N, x, strideX ) {
+	return ndarray( N, x, strideX, stride2offset( N, strideX ) );
 }
 
 
diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/lib/smediansorted.native.js b/lib/node_modules/@stdlib/stats/base/smediansorted/lib/smediansorted.native.js
index b378fc6d03d3..de6698ed0efe 100644
--- a/lib/node_modules/@stdlib/stats/base/smediansorted/lib/smediansorted.native.js
+++ b/lib/node_modules/@stdlib/stats/base/smediansorted/lib/smediansorted.native.js
@@ -30,7 +30,7 @@ var addon = require( './../src/addon.node' );
 *
 * @param {PositiveInteger} N - number of indexed elements
 * @param {Float32Array} x - sorted input array
-* @param {integer} stride - stride length
+* @param {integer} strideX - stride length
 * @returns {number} median value
 *
 * @example
@@ -41,8 +41,8 @@ var addon = require( './../src/addon.node' );
 * var v = smediansorted( x.length, x, 1 );
 * // returns 2.0
 */
-function smediansorted( N, x, stride ) {
-	return addon( N, x, stride );
+function smediansorted( N, x, strideX ) {
+	return addon( N, x, strideX );
 }
 
 
diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/manifest.json b/lib/node_modules/@stdlib/stats/base/smediansorted/manifest.json
index d8255d672b93..7a0fdb1d890b 100644
--- a/lib/node_modules/@stdlib/stats/base/smediansorted/manifest.json
+++ b/lib/node_modules/@stdlib/stats/base/smediansorted/manifest.json
@@ -1,5 +1,8 @@
 {
-  "options": {},
+  "options": {
+    "task": "build",
+    "wasm": false
+  },
   "fields": [
     {
       "field": "src",
@@ -24,17 +27,73 @@
   ],
   "confs": [
     {
+      "task": "build",
+      "wasm": false,
       "src": [
-        "./src/smediansorted.c"
+        "./src/main.c"
       ],
       "include": [
         "./include"
       ],
-      "libraries": [
-        "-lm"
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset",
+        "@stdlib/napi/export",
+        "@stdlib/napi/argv",
+        "@stdlib/napi/argv-int64",
+        "@stdlib/napi/argv-strided-float32array",
+        "@stdlib/napi/create-double"
+      ]
+    },
+    {
+      "task": "benchmark",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset"
+      ]
+    },
+    {
+      "task": "examples",
+      "wasm": false,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
+      ],
+      "libraries": [],
+      "libpath": [],
+      "dependencies": [
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset"
+      ]
+    },
+    {
+      "task": "",
+      "wasm": true,
+      "src": [
+        "./src/main.c"
+      ],
+      "include": [
+        "./include"
       ],
+      "libraries": [],
       "libpath": [],
-      "dependencies": []
+      "dependencies": [
+        "@stdlib/blas/base/shared",
+        "@stdlib/strided/base/stride2offset"
+      ]
     }
   ]
 }
diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/src/addon.c b/lib/node_modules/@stdlib/stats/base/smediansorted/src/addon.c
new file mode 100644
index 000000000000..4aa30bbb8d48
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/smediansorted/src/addon.c
@@ -0,0 +1,60 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/smediansorted.h"
+#include "stdlib/napi/export.h"
+#include "stdlib/napi/argv.h"
+#include "stdlib/napi/argv_int64.h"
+#include "stdlib/napi/argv_strided_float32array.h"
+#include "stdlib/napi/create_double.h"
+#include <node_api.h>
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 3 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_smediansorted( N, X, strideX ), v );
+	return v;
+}
+
+/**
+* Receives JavaScript callback invocation data.
+*
+* @param env    environment under which the function is invoked
+* @param info   callback data
+* @return       Node-API value
+*/
+static napi_value addon_method( napi_env env, napi_callback_info info ) {
+	STDLIB_NAPI_ARGV( env, info, argv, argc, 4 );
+	STDLIB_NAPI_ARGV_INT64( env, N, argv, 0 );
+	STDLIB_NAPI_ARGV_INT64( env, strideX, argv, 2 );
+	STDLIB_NAPI_ARGV_INT64( env, offsetX, argv, 3 );
+	STDLIB_NAPI_ARGV_STRIDED_FLOAT32ARRAY( env, X, N, strideX, argv, 1 );
+	STDLIB_NAPI_CREATE_DOUBLE( env, (double)stdlib_strided_smediansorted_ndarray( N, X, strideX, offsetX ), v );
+	return v;
+}
+
+STDLIB_NAPI_MODULE_EXPORT_FCN_WITH_METHOD( addon, "ndarray", addon_method )
diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/src/addon.cpp b/lib/node_modules/@stdlib/stats/base/smediansorted/src/addon.cpp
deleted file mode 100644
index 47845c16d2b2..000000000000
--- a/lib/node_modules/@stdlib/stats/base/smediansorted/src/addon.cpp
+++ /dev/null
@@ -1,117 +0,0 @@
-/**
-* @license Apache-2.0
-*
-* Copyright (c) 2020 The Stdlib Authors.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-*    http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-
-#include "stdlib/stats/base/smediansorted.h"
-#include <node_api.h>
-#include <stdint.h>
-#include <stdlib.h>
-#include <stdbool.h>
-#include <assert.h>
-
-/**
-* Add-on namespace.
-*/
-namespace stdlib_stats_base_smediansorted {
-
-	/**
-	* Computes the median value of a sorted single-precision floating-point strided array.
-	*
-	* ## Notes
-	*
-	* -   When called from JavaScript, the function expects three arguments:
-	*
-	*     -   `N`: number of indexed elements
-	*     -   `X`: sorted input array
-	*     -   `stride`: stride length
-	*/
-	napi_value node_smediansorted( napi_env env, napi_callback_info info ) {
-		napi_status status;
-
-		size_t argc = 3;
-		napi_value argv[ 3 ];
-		status = napi_get_cb_info( env, info, &argc, argv, nullptr, nullptr );
-		assert( status == napi_ok );
-
-		if ( argc < 3 ) {
-			napi_throw_error( env, nullptr, "invalid invocation. Must provide 3 arguments." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype0;
-		status = napi_typeof( env, argv[ 0 ], &vtype0 );
-		assert( status == napi_ok );
-		if ( vtype0 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. First argument must be a number." );
-			return nullptr;
-		}
-
-		bool res;
-		status = napi_is_typedarray( env, argv[ 1 ], &res );
-		assert( status == napi_ok );
-		if ( res == false ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." );
-			return nullptr;
-		}
-
-		napi_valuetype vtype2;
-		status = napi_typeof( env, argv[ 2 ], &vtype2 );
-		assert( status == napi_ok );
-		if ( vtype2 != napi_number ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Third argument must be a number." );
-			return nullptr;
-		}
-
-		int64_t N;
-		status = napi_get_value_int64( env, argv[ 0 ], &N );
-		assert( status == napi_ok );
-
-		int64_t stride;
-		status = napi_get_value_int64( env, argv[ 2 ], &stride );
-		assert( status == napi_ok );
-
-		napi_typedarray_type vtype1;
-		size_t xlen;
-		void *X;
-		status = napi_get_typedarray_info( env, argv[ 1 ], &vtype1, &xlen, &X, nullptr, nullptr );
-		assert( status == napi_ok );
-		if ( vtype1 != napi_float32_array ) {
-			napi_throw_type_error( env, nullptr, "invalid argument. Second argument must be a Float32Array." );
-			return nullptr;
-		}
-		if ( (N-1)*llabs(stride) >= (int64_t)xlen ) {
-			napi_throw_range_error( env, nullptr, "invalid argument. Second argument has insufficient elements based on the associated stride and the number of indexed elements." );
-			return nullptr;
-		}
-
-		napi_value v;
-		status = napi_create_double( env, (double)stdlib_strided_smediansorted( N, (float *)X, stride ), &v );
-		assert( status == napi_ok );
-
-		return v;
-	}
-
-	napi_value Init( napi_env env, napi_value exports ) {
-		napi_status status;
-		napi_value fcn;
-		status = napi_create_function( env, "exports", NAPI_AUTO_LENGTH, node_smediansorted, NULL, &fcn );
-		assert( status == napi_ok );
-		return fcn;
-	}
-
-	NAPI_MODULE( NODE_GYP_MODULE_NAME, Init )
-} // end namespace stdlib_stats_base_smediansorted
diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/src/main.c b/lib/node_modules/@stdlib/stats/base/smediansorted/src/main.c
new file mode 100644
index 000000000000..300fd23956ce
--- /dev/null
+++ b/lib/node_modules/@stdlib/stats/base/smediansorted/src/main.c
@@ -0,0 +1,58 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+#include "stdlib/stats/base/smediansorted.h"
+#include "stdlib/blas/base/shared.h"
+#include "stdlib/strided/base/stride2offset.h"
+
+/**
+* Computes the median value of a sorted single-precision floating-point strided array.
+*
+* @param N        number of indexed elements
+* @param X        sorted input array
+* @param strideX  stride length
+* @return         output value
+*/
+float API_SUFFIX(stdlib_strided_smediansorted)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX ) {
+	const CBLAS_INT ox = stdlib_strided_stride2offset( N, strideX );
+	return API_SUFFIX(stdlib_strided_smediansorted_ndarray)( N, X, strideX, ox );
+}
+
+/**
+* Computes the median value of a sorted single-precision floating-point strided array using alternative indexing semantics.
+*
+* @param N        number of indexed elements
+* @param X        sorted input array
+* @param strideX  stride length
+* @param offsetX  starting index for X
+* @return         output value
+*/
+float API_SUFFIX(stdlib_strided_smediansorted_ndarray)( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX ) {
+	CBLAS_INT n;
+
+	if ( N <= 0 ) {
+		return 0.0f / 0.0f; // NaN
+	}
+	n = N >> 1;
+	if ( N & 1 ) {
+		// Odd number of elements...
+		return X[ offsetX + ( n * strideX )  ];
+	}
+	// Even number of elements...
+	return ( X[ offsetX + ( n * strideX ) ] + X[ offsetX+( ( n - 1 ) * strideX ) ] ) / 2.0f;
+}
diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/src/smediansorted.c b/lib/node_modules/@stdlib/stats/base/smediansorted/src/smediansorted.c
deleted file mode 100644
index aba34b158855..000000000000
--- a/lib/node_modules/@stdlib/stats/base/smediansorted/src/smediansorted.c
+++ /dev/null
@@ -1,49 +0,0 @@
-/**
-* @license Apache-2.0
-*
-* Copyright (c) 2020 The Stdlib Authors.
-*
-* Licensed under the Apache License, Version 2.0 (the "License");
-* you may not use this file except in compliance with the License.
-* You may obtain a copy of the License at
-*
-*    http://www.apache.org/licenses/LICENSE-2.0
-*
-* Unless required by applicable law or agreed to in writing, software
-* distributed under the License is distributed on an "AS IS" BASIS,
-* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-* See the License for the specific language governing permissions and
-* limitations under the License.
-*/
-
-#include "stdlib/stats/base/smediansorted.h"
-#include <stdint.h>
-
-/**
-* Computes the median value of a sorted single-precision floating-point strided array.
-*
-* @param N       number of indexed elements
-* @param X       sorted input array
-* @param stride  stride length
-* @return        output value
-*/
-float stdlib_strided_smediansorted( const int64_t N, const float *X, const int64_t stride ) {
-	int64_t offset;
-	int64_t n;
-
-	if ( N <= 0 ) {
-		return 0.0f/0.0f; // NaN
-	}
-	if ( stride < 0 ) {
-		offset = (1-N) * stride;
-	} else {
-		offset = 0;
-	}
-	n = N >> 1;
-	if ( N & 1 ) {
-		// Odd number of elements...
-		return X[ offset+(n*stride) ];
-	}
-	// Even number of elements...
-	return ( X[ offset+(n*stride) ] + X[ offset+((n-1)*stride) ] ) / 2.0f;
-}
diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/test/test.ndarray.js b/lib/node_modules/@stdlib/stats/base/smediansorted/test/test.ndarray.js
index 13c6c2f675f5..23f6d6cf609d 100644
--- a/lib/node_modules/@stdlib/stats/base/smediansorted/test/test.ndarray.js
+++ b/lib/node_modules/@stdlib/stats/base/smediansorted/test/test.ndarray.js
@@ -21,7 +21,6 @@
 // MODULES //
 
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
 var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' );
 var Float32Array = require( '@stdlib/array/float32' );
@@ -120,7 +119,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 });
 
 tape( 'the function supports a `stride` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -135,15 +133,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) {
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = smediansorted( N, x, 2, 0 );
+	v = smediansorted( 4, x, 2, 0 );
 
 	t.strictEqual( v, 2.5, 'returns expected value' );
 	t.end();
 });
 
 tape( 'the function supports a negative `stride` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -158,8 +154,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t )
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = smediansorted( N, x, -2, 6 );
+	v = smediansorted( 4, x, -2, 6 );
 
 	t.strictEqual( v, 2.5, 'returns expected value' );
 	t.end();
@@ -178,7 +173,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f
 });
 
 tape( 'the function supports an `offset` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -192,9 +186,8 @@ tape( 'the function supports an `offset` parameter', function test( t ) {
 		3.0,
 		4.0   // 3
 	]);
-	N = floor( x.length / 2 );
 
-	v = smediansorted( N, x, 2, 1 );
+	v = smediansorted( 4, x, 2, 1 );
 	t.strictEqual( v, 2.5, 'returns expected value' );
 
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/test/test.ndarray.native.js b/lib/node_modules/@stdlib/stats/base/smediansorted/test/test.ndarray.native.js
index 23124fe66745..090c33c8fd3b 100644
--- a/lib/node_modules/@stdlib/stats/base/smediansorted/test/test.ndarray.native.js
+++ b/lib/node_modules/@stdlib/stats/base/smediansorted/test/test.ndarray.native.js
@@ -22,7 +22,6 @@
 
 var resolve = require( 'path' ).resolve;
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
 var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' );
 var Float32Array = require( '@stdlib/array/float32' );
@@ -129,7 +128,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 });
 
 tape( 'the function supports a `stride` parameter', opts, function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -144,15 +142,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) {
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = smediansorted( N, x, 2, 0 );
+	v = smediansorted( 4, x, 2, 0 );
 
 	t.strictEqual( v, 2.5, 'returns expected value' );
 	t.end();
 });
 
 tape( 'the function supports a negative `stride` parameter', opts, function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -167,8 +163,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = smediansorted( N, x, -2, 6 );
+	v = smediansorted( 4, x, -2, 6 );
 
 	t.strictEqual( v, 2.5, 'returns expected value' );
 	t.end();
@@ -187,7 +182,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f
 });
 
 tape( 'the function supports an `offset` parameter', opts, function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -201,9 +195,8 @@ tape( 'the function supports an `offset` parameter', opts, function test( t ) {
 		3.0,
 		4.0   // 3
 	]);
-	N = floor( x.length / 2 );
 
-	v = smediansorted( N, x, 2, 1 );
+	v = smediansorted( 4, x, 2, 1 );
 	t.strictEqual( v, 2.5, 'returns expected value' );
 
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/test/test.smediansorted.js b/lib/node_modules/@stdlib/stats/base/smediansorted/test/test.smediansorted.js
index 36f903a3dee2..6c564c924f00 100644
--- a/lib/node_modules/@stdlib/stats/base/smediansorted/test/test.smediansorted.js
+++ b/lib/node_modules/@stdlib/stats/base/smediansorted/test/test.smediansorted.js
@@ -21,7 +21,6 @@
 // MODULES //
 
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
 var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' );
 var Float32Array = require( '@stdlib/array/float32' );
@@ -120,7 +119,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 });
 
 tape( 'the function supports a `stride` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -135,15 +133,13 @@ tape( 'the function supports a `stride` parameter', function test( t ) {
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = smediansorted( N, x, 2 );
+	v = smediansorted( 4, x, 2 );
 
 	t.strictEqual( v, 2.5, 'returns expected value' );
 	t.end();
 });
 
 tape( 'the function supports a negative `stride` parameter', function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -158,8 +154,7 @@ tape( 'the function supports a negative `stride` parameter', function test( t )
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = smediansorted( N, x, -2 );
+	v = smediansorted( 4, x, -2 );
 
 	t.strictEqual( v, 2.5, 'returns expected value' );
 	t.end();
@@ -180,7 +175,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f
 tape( 'the function supports view offsets', function test( t ) {
 	var x0;
 	var x1;
-	var N;
 	var v;
 
 	x0 = new Float32Array([
@@ -196,9 +190,8 @@ tape( 'the function supports view offsets', function test( t ) {
 	]);
 
 	x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
-	N = floor(x1.length / 2);
 
-	v = smediansorted( N, x1, 2 );
+	v = smediansorted( 4, x1, 2 );
 	t.strictEqual( v, 2.5, 'returns expected value' );
 
 	t.end();
diff --git a/lib/node_modules/@stdlib/stats/base/smediansorted/test/test.smediansorted.native.js b/lib/node_modules/@stdlib/stats/base/smediansorted/test/test.smediansorted.native.js
index 66d42f1c0fb6..0f2b394a2422 100644
--- a/lib/node_modules/@stdlib/stats/base/smediansorted/test/test.smediansorted.native.js
+++ b/lib/node_modules/@stdlib/stats/base/smediansorted/test/test.smediansorted.native.js
@@ -22,7 +22,6 @@
 
 var resolve = require( 'path' ).resolve;
 var tape = require( 'tape' );
-var floor = require( '@stdlib/math/base/special/floor' );
 var isnanf = require( '@stdlib/math/base/assert/is-nanf' );
 var isNegativeZerof = require( '@stdlib/math/base/assert/is-negative-zerof' );
 var Float32Array = require( '@stdlib/array/float32' );
@@ -129,7 +128,6 @@ tape( 'if provided an `N` parameter equal to `1`, the function returns the first
 });
 
 tape( 'the function supports a `stride` parameter', opts, function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -144,15 +142,13 @@ tape( 'the function supports a `stride` parameter', opts, function test( t ) {
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = smediansorted( N, x, 2 );
+	v = smediansorted( 4, x, 2 );
 
 	t.strictEqual( v, 2.5, 'returns expected value' );
 	t.end();
 });
 
 tape( 'the function supports a negative `stride` parameter', opts, function test( t ) {
-	var N;
 	var x;
 	var v;
 
@@ -167,8 +163,7 @@ tape( 'the function supports a negative `stride` parameter', opts, function test
 		2.0
 	]);
 
-	N = floor( x.length / 2 );
-	v = smediansorted( N, x, -2 );
+	v = smediansorted( 4, x, -2 );
 
 	t.strictEqual( v, 2.5, 'returns expected value' );
 	t.end();
@@ -189,7 +184,6 @@ tape( 'if provided a `stride` parameter equal to `0`, the function returns the f
 tape( 'the function supports view offsets', opts, function test( t ) {
 	var x0;
 	var x1;
-	var N;
 	var v;
 
 	x0 = new Float32Array([
@@ -205,9 +199,8 @@ tape( 'the function supports view offsets', opts, function test( t ) {
 	]);
 
 	x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
-	N = floor(x1.length / 2);
 
-	v = smediansorted( N, x1, 2 );
+	v = smediansorted( 4, x1, 2 );
 	t.strictEqual( v, 2.5, 'returns expected value' );
 
 	t.end();

From 15b212e161aa45d40467257610c33d3604824cec Mon Sep 17 00:00:00 2001
From: stdlib-bot <82920195+stdlib-bot@users.noreply.github.com>
Date: Fri, 3 Jan 2025 19:10:09 -0800
Subject: [PATCH 82/87] docs: update related packages sections

PR-URL: https://github.com/stdlib-js/stdlib/pull/4517

Reviewed-by: Philipp Burckhardt <pburckhardt@outlook.com>
---
 .../float32/max-safe-nth-fibonacci/README.md         |  8 ++++++++
 .../@stdlib/math/base/special/cceilf/README.md       |  2 +-
 .../@stdlib/math/base/special/gammasgn/README.md     |  6 ++++++
 .../strided/base/dtype-resolve-enum/README.md        | 12 ++++++++++++
 4 files changed, 27 insertions(+), 1 deletion(-)

diff --git a/lib/node_modules/@stdlib/constants/float32/max-safe-nth-fibonacci/README.md b/lib/node_modules/@stdlib/constants/float32/max-safe-nth-fibonacci/README.md
index bdafa9622fb3..0a6edf628998 100644
--- a/lib/node_modules/@stdlib/constants/float32/max-safe-nth-fibonacci/README.md
+++ b/lib/node_modules/@stdlib/constants/float32/max-safe-nth-fibonacci/README.md
@@ -148,6 +148,12 @@ Macro for the maximum [safe][safe-integers] nth [Fibonacci number][fibonacci-num
 
 <section class="related">
 
+* * *
+
+## See Also
+
+-   <span class="package-name">[`@stdlib/constants/float64/max-safe-nth-fibonacci`][@stdlib/constants/float64/max-safe-nth-fibonacci]</span><span class="delimiter">: </span><span class="description">maximum safe nth Fibonacci number when stored in double-precision floating-point format.</span>
+
 </section>
 
 <!-- /.related -->
@@ -164,6 +170,8 @@ Macro for the maximum [safe][safe-integers] nth [Fibonacci number][fibonacci-num
 
 <!-- <related-links> -->
 
+[@stdlib/constants/float64/max-safe-nth-fibonacci]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/constants/float64/max-safe-nth-fibonacci
+
 <!-- </related-links> -->
 
 </section>
diff --git a/lib/node_modules/@stdlib/math/base/special/cceilf/README.md b/lib/node_modules/@stdlib/math/base/special/cceilf/README.md
index a7c08ee41be0..99b848325ca5 100644
--- a/lib/node_modules/@stdlib/math/base/special/cceilf/README.md
+++ b/lib/node_modules/@stdlib/math/base/special/cceilf/README.md
@@ -176,7 +176,7 @@ int main( void ) {
 
 ## See Also
 
--   <span class="package-name">[`@stdlib/math/base/special/cceil`][@stdlib/math/base/special/cceil]</span><span class="delimiter">: </span><span class="description">round a double-precision complex floating-point number toward positive infinity.</span>
+-   <span class="package-name">[`@stdlib/math/base/special/cceil`][@stdlib/math/base/special/cceil]</span><span class="delimiter">: </span><span class="description">round each component of a double-precision complex floating-point number toward positive infinity.</span>
 
 </section>
 
diff --git a/lib/node_modules/@stdlib/math/base/special/gammasgn/README.md b/lib/node_modules/@stdlib/math/base/special/gammasgn/README.md
index 1b4954820b2a..40135d3a8aaa 100644
--- a/lib/node_modules/@stdlib/math/base/special/gammasgn/README.md
+++ b/lib/node_modules/@stdlib/math/base/special/gammasgn/README.md
@@ -201,6 +201,12 @@ int main( void ) {
 
 <section class="related">
 
+* * *
+
+## See Also
+
+-   <span class="package-name">[`@stdlib/math/base/special/gamma`][@stdlib/math/base/special/gamma]</span><span class="delimiter">: </span><span class="description">gamma function.</span>
+
 </section>
 
 <!-- /.related -->
diff --git a/lib/node_modules/@stdlib/strided/base/dtype-resolve-enum/README.md b/lib/node_modules/@stdlib/strided/base/dtype-resolve-enum/README.md
index 51ddecccbcf4..25c144bfae2a 100644
--- a/lib/node_modules/@stdlib/strided/base/dtype-resolve-enum/README.md
+++ b/lib/node_modules/@stdlib/strided/base/dtype-resolve-enum/README.md
@@ -129,6 +129,12 @@ v = resolve( 'uint8' );
 
 <section class="related">
 
+* * *
+
+## See Also
+
+-   <span class="package-name">[`@stdlib/strided/base/dtype-resolve-str`][@stdlib/strided/base/dtype-resolve-str]</span><span class="delimiter">: </span><span class="description">return the data type string associated with a supported strided array data type value.</span>
+
 </section>
 
 <!-- /.related -->
@@ -137,6 +143,12 @@ v = resolve( 'uint8' );
 
 <section class="links">
 
+<!-- <related-links> -->
+
+[@stdlib/strided/base/dtype-resolve-str]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/strided/base/dtype-resolve-str
+
+<!-- </related-links> -->
+
 </section>
 
 <!-- /.links -->

From 3f8d07ac5632e95b98b7ad572fa108c96baeed4e Mon Sep 17 00:00:00 2001
From: stdlib-bot <82920195+stdlib-bot@users.noreply.github.com>
Date: Fri, 3 Jan 2025 19:10:51 -0800
Subject: [PATCH 83/87] docs: update namespace table of contents

PR-URL: https://github.com/stdlib-js/stdlib/pull/4520

Reviewed-by: Philipp Burckhardt <pburckhardt@outlook.com>
Signed-off-by: stdlib-bot <82920195+stdlib-bot@users.noreply.github.com>
---
 lib/node_modules/@stdlib/stats/base/README.md | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/lib/node_modules/@stdlib/stats/base/README.md b/lib/node_modules/@stdlib/stats/base/README.md
index b0fb0ebfb3f8..4c24763dbda5 100644
--- a/lib/node_modules/@stdlib/stats/base/README.md
+++ b/lib/node_modules/@stdlib/stats/base/README.md
@@ -96,7 +96,7 @@ The namespace contains the following statistical functions:
 -   <span class="signature">[`dnanmeanors( N, x, stride )`][@stdlib/stats/base/dnanmeanors]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values and using ordinary recursive summation.</span>
 -   <span class="signature">[`dnanmeanpn( N, x, stride )`][@stdlib/stats/base/dnanmeanpn]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values and using a two-pass error correction algorithm.</span>
 -   <span class="signature">[`dnanmeanpw( N, x, stride )`][@stdlib/stats/base/dnanmeanpw]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array, ignoring `NaN` values and using pairwise summation.</span>
--   <span class="signature">[`dnanmeanwd( N, x, stride )`][@stdlib/stats/base/dnanmeanwd]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array, using Welford's algorithm and ignoring `NaN` values.</span>
+-   <span class="signature">[`dnanmeanwd( N, x, strideX )`][@stdlib/stats/base/dnanmeanwd]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a double-precision floating-point strided array, using Welford's algorithm and ignoring `NaN` values.</span>
 -   <span class="signature">[`dnanmin( N, x, strideX )`][@stdlib/stats/base/dnanmin]</span><span class="delimiter">: </span><span class="description">calculate the minimum value of a double-precision floating-point strided array, ignoring `NaN` values.</span>
 -   <span class="signature">[`dnanminabs( N, x, strideX )`][@stdlib/stats/base/dnanminabs]</span><span class="delimiter">: </span><span class="description">calculate the minimum absolute value of a double-precision floating-point strided array, ignoring `NaN` values.</span>
 -   <span class="signature">[`dnanmskmax( N, x, strideX, mask, strideMask )`][@stdlib/stats/base/dnanmskmax]</span><span class="delimiter">: </span><span class="description">calculate the maximum value of a double-precision floating-point strided array according to a mask, ignoring `NaN` values.</span>
@@ -217,11 +217,11 @@ The namespace contains the following statistical functions:
 -   <span class="signature">[`smeanpn( N, x, stride )`][@stdlib/stats/base/smeanpn]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array using a two-pass error correction algorithm.</span>
 -   <span class="signature">[`smeanpw( N, x, stride )`][@stdlib/stats/base/smeanpw]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array using pairwise summation.</span>
 -   <span class="signature">[`smeanwd( N, x, stride )`][@stdlib/stats/base/smeanwd]</span><span class="delimiter">: </span><span class="description">calculate the arithmetic mean of a single-precision floating-point strided array using Welford's algorithm.</span>
--   <span class="signature">[`smediansorted( N, x, stride )`][@stdlib/stats/base/smediansorted]</span><span class="delimiter">: </span><span class="description">calculate the median value of a sorted single-precision floating-point strided array.</span>
+-   <span class="signature">[`smediansorted( N, x, strideX )`][@stdlib/stats/base/smediansorted]</span><span class="delimiter">: </span><span class="description">calculate the median value of a sorted single-precision floating-point strided array.</span>
 -   <span class="signature">[`smidrange( N, x, strideX )`][@stdlib/stats/base/smidrange]</span><span class="delimiter">: </span><span class="description">calculate the mid-range of a single-precision floating-point strided array.</span>
 -   <span class="signature">[`smin( N, x, strideX )`][@stdlib/stats/base/smin]</span><span class="delimiter">: </span><span class="description">calculate the minimum value of a single-precision floating-point strided array.</span>
 -   <span class="signature">[`sminabs( N, x, strideX )`][@stdlib/stats/base/sminabs]</span><span class="delimiter">: </span><span class="description">calculate the minimum absolute value of a single-precision floating-point strided array.</span>
--   <span class="signature">[`sminsorted( N, x, stride )`][@stdlib/stats/base/sminsorted]</span><span class="delimiter">: </span><span class="description">calculate the minimum value of a sorted single-precision floating-point strided array.</span>
+-   <span class="signature">[`sminsorted( N, x, strideX )`][@stdlib/stats/base/sminsorted]</span><span class="delimiter">: </span><span class="description">calculate the minimum value of a sorted single-precision floating-point strided array.</span>
 -   <span class="signature">[`smskmax( N, x, strideX, mask, strideMask )`][@stdlib/stats/base/smskmax]</span><span class="delimiter">: </span><span class="description">calculate the maximum value of a single-precision floating-point strided array according to a mask.</span>
 -   <span class="signature">[`smskmin( N, x, strideX, mask, strideMask )`][@stdlib/stats/base/smskmin]</span><span class="delimiter">: </span><span class="description">calculate the minimum value of a single-precision floating-point strided array according to a mask.</span>
 -   <span class="signature">[`smskrange( N, x, strideX, mask, strideMask )`][@stdlib/stats/base/smskrange]</span><span class="delimiter">: </span><span class="description">calculate the range of a single-precision floating-point strided array according to a mask.</span>

From 69da34e1f93dab2ed698c89092db3d794aed2646 Mon Sep 17 00:00:00 2001
From: stdlib-bot <82920195+stdlib-bot@users.noreply.github.com>
Date: Fri, 3 Jan 2025 19:11:31 -0800
Subject: [PATCH 84/87] docs: update list of contributors

PR-URL: https://github.com/stdlib-js/stdlib/pull/4516

Co-authored-by: Philipp Burckhardt <pburckhardt@outlook.com>
Reviewed-by: Philipp Burckhardt <pburckhardt@outlook.com>
Signed-off-by: stdlib-bot <82920195+stdlib-bot@users.noreply.github.com>
---
 CONTRIBUTORS | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/CONTRIBUTORS b/CONTRIBUTORS
index a5f7abac3c23..440aba13e081 100644
--- a/CONTRIBUTORS
+++ b/CONTRIBUTORS
@@ -27,7 +27,7 @@ Daniel Killenberger <daniel.killenberger@gmail.com>
 Daniel Yu <40680511+Daniel777y@users.noreply.github.com>
 Debashis Maharana <debashismaharana7854@gmail.com>
 Desh Deepak Kant <118960904+DeshDeepakKant@users.noreply.github.com>
-Dhruv/ <154677013+DhruvArvindSingh@users.noreply.github.com>
+Dhruv Arvind Singh <154677013+DhruvArvindSingh@users.noreply.github.com>
 Divyansh Seth <59174836+sethdivyansh@users.noreply.github.com>
 Dominic Lim <46486515+domlimm@users.noreply.github.com>
 Dominik Moritz <domoritz@gmail.com>
@@ -118,7 +118,7 @@ UtkershBasnet <119008923+UtkershBasnet@users.noreply.github.com>
 Vaibhav Patel <98279986+noobCoderVP@users.noreply.github.com>
 Varad Gupta <varadgupta21@gmail.com>
 Vinit Pandit <106718914+MeastroZI@users.noreply.github.com>
-Vivek maurya <155618190+vivekmaurya001@users.noreply.github.com>
+Vivek Maurya <vm8118134@gmail.com>
 Xiaochuan Ye <tap91624@gmail.com>
 Yaswanth Kosuru <116426380+yaswanthkosuru@users.noreply.github.com>
 Yernar Yergaziyev <yernar.yergaziyev@erg.kz>

From 0b2e74a578a4f2e6af6655d254e13036e3dd68a8 Mon Sep 17 00:00:00 2001
From: stdlib-bot <82920195+stdlib-bot@users.noreply.github.com>
Date: Fri, 3 Jan 2025 19:12:01 -0800
Subject: [PATCH 85/87] feat: update namespace TypeScript declarations

PR-URL: https://github.com/stdlib-js/stdlib/pull/4518

Co-authored-by: Philipp Burckhardt <pburckhardt@outlook.com>
Reviewed-by: Philipp Burckhardt <pburckhardt@outlook.com>
Signed-off-by: stdlib-bot <82920195+stdlib-bot@users.noreply.github.com>
---
 lib/node_modules/@stdlib/stats/base/docs/types/index.d.ts | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/lib/node_modules/@stdlib/stats/base/docs/types/index.d.ts b/lib/node_modules/@stdlib/stats/base/docs/types/index.d.ts
index d760f9e8b9b2..0df7486ac432 100644
--- a/lib/node_modules/@stdlib/stats/base/docs/types/index.d.ts
+++ b/lib/node_modules/@stdlib/stats/base/docs/types/index.d.ts
@@ -1321,7 +1321,7 @@ interface Namespace {
 	*
 	* @param N - number of indexed elements
 	* @param x - input array
-	* @param stride - stride length
+	* @param strideX - stride length
 	* @returns arithmetic mean
 	*
 	* @example
@@ -4521,7 +4521,7 @@ interface Namespace {
 	*
 	* @param N - number of indexed elements
 	* @param x - sorted input array
-	* @param stride - stride length
+	* @param strideX - stride length
 	* @returns median value
 	*
 	* @example
@@ -4625,7 +4625,7 @@ interface Namespace {
 	*
 	* @param N - number of indexed elements
 	* @param x - sorted input array
-	* @param stride - stride length
+	* @param strideX - stride length
 	* @returns minimum value
 	*
 	* @example

From 83b6c343c6bbd3a369901e5689dd3e17c992d345 Mon Sep 17 00:00:00 2001
From: stdlib-bot <82920195+stdlib-bot@users.noreply.github.com>
Date: Fri, 3 Jan 2025 19:12:48 -0800
Subject: [PATCH 86/87] docs: update REPL namespace documentation

PR-URL: https://github.com/stdlib-js/stdlib/pull/4519

Reviewed-by: Philipp Burckhardt <pburckhardt@outlook.com>
Signed-off-by: stdlib-bot <82920195+stdlib-bot@users.noreply.github.com>
---
 .../@stdlib/repl/code-blocks/data/data.csv           | 12 ++++++------
 .../@stdlib/repl/code-blocks/data/data.json          |  2 +-
 lib/node_modules/@stdlib/repl/data/contributor.json  |  2 +-
 lib/node_modules/@stdlib/repl/help/data/data.csv     | 12 ++++++------
 lib/node_modules/@stdlib/repl/help/data/data.json    |  2 +-
 lib/node_modules/@stdlib/repl/info/data/data.csv     | 12 ++++++------
 lib/node_modules/@stdlib/repl/info/data/data.json    |  2 +-
 .../@stdlib/repl/signature/data/data.csv             | 12 ++++++------
 .../@stdlib/repl/signature/data/data.json            |  2 +-
 .../@stdlib/repl/typed-signature/data/data.csv       | 12 ++++++------
 .../@stdlib/repl/typed-signature/data/data.json      |  2 +-
 11 files changed, 36 insertions(+), 36 deletions(-)

diff --git a/lib/node_modules/@stdlib/repl/code-blocks/data/data.csv b/lib/node_modules/@stdlib/repl/code-blocks/data/data.csv
index af85e78a0e0b..2a03b9b97c8b 100644
--- a/lib/node_modules/@stdlib/repl/code-blocks/data/data.csv
+++ b/lib/node_modules/@stdlib/repl/code-blocks/data/data.csv
@@ -1822,8 +1822,8 @@ base.strided.dnanmeanpn,"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nb
 base.strided.dnanmeanpn.ndarray,"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmeanpn.ndarray( N, x, 2, 1 )\n"
 base.strided.dnanmeanpw,"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmeanpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmeanpw( N, x1, stride )\n"
 base.strided.dnanmeanpw.ndarray,"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmeanpw.ndarray( N, x, 2, 1 )\n"
-base.strided.dnanmeanwd,"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanwd( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmeanwd( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmeanwd( N, x1, stride )\n"
-base.strided.dnanmeanwd.ndarray,"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmeanwd.ndarray( N, x, 2, 1 )\n"
+base.strided.dnanmeanwd,"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanwd( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanmeanwd( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmeanwd( 3, x1, 2 )\n"
+base.strided.dnanmeanwd.ndarray,"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanmeanwd.ndarray( 3, x, 2, 1 )\n"
 base.strided.dnanmin,"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmin( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanmin( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmin( 3, x1, 2 )\n"
 base.strided.dnanmin.ndarray,"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanmin.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanmin.ndarray( 3, x, 2, 1 )\n"
 base.strided.dnanminabs,"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanminabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanminabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanminabs( 3, x1, 2 )\n"
@@ -2311,16 +2311,16 @@ base.strided.smeanpw,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.stri
 base.strided.smeanpw.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanpw.ndarray( N, x, 2, 1 )\n"
 base.strided.smeanwd,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanwd( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanwd( N, x1, stride )\n"
 base.strided.smeanwd.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanwd.ndarray( N, x, 2, 1 )\n"
-base.strided.smediansorted,"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smediansorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smediansorted( N, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.smediansorted( N, x1, 2 )\n"
-base.strided.smediansorted.ndarray,"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smediansorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smediansorted.ndarray( N, x, 2, 1 )\n"
+base.strided.smediansorted,"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smediansorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smediansorted( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smediansorted( 3, x1, 2 )\n"
+base.strided.smediansorted.ndarray,"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smediansorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.smediansorted.ndarray( 3, x, 2, 1 )\n"
 base.strided.smidrange,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smidrange( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smidrange( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smidrange( 3, x1, 2 )\n"
 base.strided.smidrange.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smidrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smidrange.ndarray( 3, x, 2, 1 )\n"
 base.strided.smin,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smin( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smin( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smin( 3, x1, 2 )\n"
 base.strided.smin.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smin.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smin.ndarray( 3, x, 2, 1 )\n"
 base.strided.sminabs,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sminabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sminabs( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sminabs( 3, x1, 2 )\n"
 base.strided.sminabs.ndarray,"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sminabs.ndarray( 3, x, 2, 1 )\n"
-base.strided.sminsorted,"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.sminsorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sminsorted( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sminsorted( N, x1, stride )\n"
-base.strided.sminsorted.ndarray,"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.sminsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sminsorted.ndarray( N, x, 2, 1 )\n"
+base.strided.sminsorted,"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.sminsorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sminsorted( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sminsorted( 3, x1, 2 )\n"
+base.strided.sminsorted.ndarray,"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.sminsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.sminsorted.ndarray( 3, x, 2, 1 )\n"
 base.strided.smskabs,"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskabs( 2, x1, -2, m1, -2, y1, 1 )\ny0\n"
 base.strided.smskabs.ndarray,"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n"
 base.strided.smskabs2,"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskabs2( 2, x1, -2, m1, -2, y1, 1 )\ny0\n"
diff --git a/lib/node_modules/@stdlib/repl/code-blocks/data/data.json b/lib/node_modules/@stdlib/repl/code-blocks/data/data.json
index 9ecb3be283bf..fd6bd0c9a7d6 100644
--- a/lib/node_modules/@stdlib/repl/code-blocks/data/data.json
+++ b/lib/node_modules/@stdlib/repl/code-blocks/data/data.json
@@ -1 +1 @@
-{"abs":"var y = abs( -1.0 )\nvar x = new Float64Array( [ -1.0, -2.0 ] );\ny = abs( x )\nx = [ -1.0, -2.0 ];\ny = abs( x )\nx = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] );\ny = abs( x )\ny.get( 0, 1 )\n","abs.assign":"var x = new Float64Array( [ -1.0, -2.0 ] );\nvar y = new Float64Array( x.length );\nvar out = abs.assign( x, y )\nvar bool = ( out === y )\nx = [ -1.0, -2.0 ];\ny = [ 0.0, 0.0 ];\nout = abs.assign( x, y )\nbool = ( out === y )\nx = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] );\ny = array( [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ] );\nout = abs.assign( x, y )\nout.get( 0, 1 )\nbool = ( out === y )\n","acartesianPower":"var x = [ 1, 2 ];\nvar out = acartesianPower( x, 2 )\n","acartesianProduct":"var x1 = [ 1, 2 ];\nvar x2 = [ 3, 4 ];\nvar out = acartesianProduct( x1, x2 )\n","acartesianSquare":"var out = acartesianSquare( [ 1, 2 ] )\n","acronym":"var out = acronym( 'the quick brown fox' )\nout = acronym( 'Hard-boiled eggs' )\n","aempty":"var arr = aempty( 2 )\narr = aempty( 2, 'float32' )\n","aemptyLike":"var x = new Float64Array( 2 );\nvar arr = aemptyLike( x )\narr = aemptyLike( x, 'float32' )\n","AFINN_96":"var list = AFINN_96()\n","AFINN_111":"var list = AFINN_111()\n","afull":"var arr = afull( 2, 1.0 )\narr = afull( 2, 1.0, 'float32' )\n","afullLike":"var x = new Float64Array( 2 );\nvar y = afullLike( x, 1.0 )\ny = afullLike( x, 1.0, 'float32' )\n","alias2pkg":"var v = alias2pkg( 'base.sin' )\n","alias2related":"var v = alias2related( 'base.sin' )\n","alias2standalone":"var v = alias2standalone( 'base.sin' )\n","aliases":"var o = aliases()\no = aliases( '@stdlib/math/base/special' )\n","allocUnsafe":"var buf = allocUnsafe( 100 )\n","amskfilter":"var x = [ 1, 2, 3, 4 ];\nvar y = amskfilter( x, [ 0, 1, 0, 1 ] )\n","amskput":"var x = [ 1, 2, 3, 4 ];\nvar out = amskput( x, [ 1, 0, 1, 0 ], [ 20, 40 ] )\nvar bool = ( out === x )\n","amskreject":"var x = [ 1, 2, 3, 4 ];\nvar y = amskreject( x, [ 0, 1, 0, 1 ] )\n","anans":"var arr = anans( 2 )\narr = anans( 2, 'float32' )\n","anansLike":"var x = new Float64Array( 2 );\nvar y = anansLike( x )\ny = anansLike( x, 'float32' )\n","anova1":"var x = [1, 3, 5, 2, 4, 6, 8, 7, 10, 11, 12, 15];\nvar f = [\n 'control', 'treatA', 'treatB', 'treatC', 'control',\n 'treatA', 'treatB', 'treatC', 'control', 'treatA', 'treatB', 'treatC'\n ];\nvar out = anova1( x, f )\n","ANSCOMBES_QUARTET":"var d = ANSCOMBES_QUARTET()\n","any":"var arr = [ 0, 0, 0, 0, 1 ];\nvar bool = any( arr )\n","anyBy":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ 1, 2, 3, 4, -1 ];\nvar bool = anyBy( arr, negative )\n","anyByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nanyByAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nanyByAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nanyByAsync( arr, opts, predicate, done )\n","anyByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = anyByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","anyByRight":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ -1, 1, 2, 3, 4 ];\nvar bool = anyByRight( arr, negative )\n","anyByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nanyByRightAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nanyByRightAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nanyByRightAsync( arr, opts, predicate, done )\n","anyByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = anyByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","anyInBy":"function isNegative(value) { return value < 0 }\nvar obj = { a: 1, b: -2, c: 3, d: 4 }\nvar result = anyInBy(obj, isNegative)\n","anyOwnBy":"function positive( v ) { return ( v > 0 ); };\nvar obj = { 'a': -1, 'b': 2, 'c': -3 };\nvar bool = anyOwnBy( obj, positive )\n","aones":"var arr = aones( 2 )\narr = aones( 2, 'float32' )\n","aonesLike":"var x = new Float64Array( 2 );\nvar y = aonesLike( x )\ny = aonesLike( x, 'float32' )\n","aoneTo":"var arr = aoneTo( 2 )\narr = aoneTo( 2, 'float32' )\n","aoneToLike":"var arr = aoneToLike( [ 0, 0 ] )\narr = aoneToLike( [ 0, 0 ], 'float32' )\n","APERY":"APERY\n","aplace":"var x = [ 1, 2, 3, 4 ];\nvar out = aplace( x, [ 0, 1, 0, 1 ], [ 20, 40 ] )\nvar bool = ( out === x )\n","append":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = append( arr, [ 6.0, 7.0 ] )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = append( arr, [ 3.0, 4.0 ] )\narr = { 'length': 0 };\narr = append( arr, [ 1.0, 2.0 ] )\n","aput":"var x = [ 1, 2, 3, 4 ];\nvar out = aput( x, [ 1, 3 ], [ 20, 40 ] )\nvar bool = ( out === x )\n","ARCH":"ARCH\n","argumentFunction":"var argn = argumentFunction( 1 );\nvar v = argn( 3.14, -3.14, 0.0 )\nv = argn( -1.0, -0.0, 1.0 )\nv = argn( 'beep', 'boop', 'bop' )\nv = argn( 'beep' )\n","ARGV":"var execPath = ARGV[ 0 ]\n","array":"var arr = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","array2buffer":"var buf = array2buffer( [ 1, 2, 3, 4 ] )\n","array2fancy":"var y = array2fancy( [ 1, 2, 3, 4 ] );\ny[ '1::2' ]\ny[ '::-1' ]\n","array2fancy.factory":"var f = array2fancy.factory();\nvar y = f( [ 1, 2, 3, 4 ] );\ny[ '1::2' ]\ny[ '::-1' ]\n","array2fancy.idx":"var idx = array2fancy.idx( [ 1, 2, 3, 4 ] );\n","array2iterator":"var it = array2iterator( [ 1, 2, 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","array2iteratorRight":"var it = array2iteratorRight( [ 1, 2, 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","ArrayBuffer":"var buf = new ArrayBuffer( 5 )\n","ArrayBuffer.length":"ArrayBuffer.length\n","ArrayBuffer.isView":"var arr = new Float64Array( 10 );\nArrayBuffer.isView( arr )\n","ArrayBuffer.prototype.byteLength":"var buf = new ArrayBuffer( 5 );\nbuf.byteLength\n","ArrayBuffer.prototype.slice":"var b1 = new ArrayBuffer( 10 );\nvar b2 = b1.slice( 2, 6 );\nvar bool = ( b1 === b2 )\nb2.byteLength\n","arraybuffer2buffer":"var ab = new ArrayBuffer( 10 )\nvar buf = arraybuffer2buffer( ab )\nvar len = buf.length\nbuf = arraybuffer2buffer( ab, 2, 6 )\nlen = buf.length\n","arrayCtors":"var ctor = arrayCtors( 'float64' )\nctor = arrayCtors( 'float' )\n","arrayDataType":"var arr = new Float64Array( 10 );\nvar dt = arrayDataType( arr )\ndt = arrayDataType( 'beep' )\n","arrayDataTypes":"var out = arrayDataTypes()\nout = arrayDataTypes( 'floating_point' )\nout = arrayDataTypes( 'floating_point_and_generic' )\n","ArrayIndex":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n","ArrayIndex.free":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nArrayIndex.free( idx.id )\n","ArrayIndex.get":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nArrayIndex.get( idx.id )\n","ArrayIndex.prototype.data":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.data\n","ArrayIndex.prototype.dtype":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.dtype\n","ArrayIndex.prototype.id":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.id\n","ArrayIndex.prototype.isCached":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.isCached\n","ArrayIndex.prototype.type":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.type\n","ArrayIndex.prototype.toString":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.toString()\n","ArrayIndex.prototype.toJSON":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.toJSON()\n","arrayMinDataType":"var dt = arrayMinDataType( 3.141592653589793 )\ndt = arrayMinDataType( 3 )\ndt = arrayMinDataType( -3 )\ndt = arrayMinDataType( '-3' )\n","arrayMostlySafeCasts":"var out = arrayMostlySafeCasts( 'float32' )\n","arrayNextDataType":"var out = arrayNextDataType( 'float32' )\n","arrayPromotionRules":"var out = arrayPromotionRules( 'float32', 'int32' )\n","arraySafeCasts":"var out = arraySafeCasts( 'float32' )\n","arraySameKindCasts":"var out = arraySameKindCasts( 'float32' )\n","arrayShape":"var out = arrayShape( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n","arrayStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar s = arrayStream( [ 1, 2, 3 ] );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","arrayStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = arrayStream.factory( opts );\n","arrayStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar s = arrayStream.objectMode( [ 1, 2, 3 ] );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","arrayview2iterator":"var it = arrayview2iterator( [ 1, 2, 3, 4 ], 1, 3 );\nvar v = it.next().value\nv = it.next().value\n","arrayview2iteratorRight":"var it = arrayview2iteratorRight( [ 1, 2, 3, 4 ], 1, 3 );\nvar v = it.next().value\nv = it.next().value\n","aslice":"var out = aslice( [ 1, 2, 3, 4 ] )\nout = aslice( [ 1, 2, 3, 4 ], 1 )\nout = aslice( [ 1, 2, 3, 4 ], 1, 3 )\n","AsyncIteratorSymbol":"var s = AsyncIteratorSymbol\n","atake":"var x = [ 1, 2, 3, 4 ];\nvar y = atake( x, [ 1, 3 ] )\n","azeros":"var arr = azeros( 2 )\narr = azeros( 2, 'float32' )\n","azerosLike":"var x = new Float64Array( 2 );\nvar y = azerosLike( x )\ny = azerosLike( x, 'float32' )\n","azeroTo":"var arr = azeroTo( 2 )\narr = azeroTo( 2, 'float32' )\n","azeroToLike":"var arr = azeroToLike( [ 0, 0 ] )\narr = azeroToLike( [ 0, 0 ], 'float32' )\n","bartlettTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = bartlettTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = bartlettTest( arr, { 'groups': groups } )\n","base.abs":"var y = base.abs( -1.0 )\ny = base.abs( 2.0 )\ny = base.abs( 0.0 )\ny = base.abs( -0.0 )\ny = base.abs( NaN )\n","base.abs2":"var y = base.abs2( -1.0 )\ny = base.abs2( 2.0 )\ny = base.abs2( 0.0 )\ny = base.abs2( -0.0 )\ny = base.abs2( NaN )\n","base.abs2f":"var y = base.abs2f( -1.0 )\ny = base.abs2f( 2.0 )\ny = base.abs2f( 0.0 )\ny = base.abs2f( -0.0 )\ny = base.abs2f( NaN )\n","base.absdiff":"var d = base.absdiff( 2.0, 5.0 )\nd = base.absdiff( -1.0, 3.14 )\nd = base.absdiff( 10.1, -2.05 )\nd = base.absdiff( -0.0, 0.0 )\nd = base.absdiff( NaN, 5.0 )\nd = base.absdiff( PINF, NINF )\nd = base.absdiff( PINF, PINF )\n","base.absf":"var y = base.absf( -1.0 )\ny = base.absf( 2.0 )\ny = base.absf( 0.0 )\ny = base.absf( -0.0 )\ny = base.absf( NaN )\n","base.acartesianPower":"var x = [ 1, 2 ];\nvar out = base.acartesianPower( x, 2 )\n","base.acartesianProduct":"var x1 = [ 1, 2 ];\nvar x2 = [ 3, 4 ];\nvar out = base.acartesianProduct( x1, x2 )\n","base.acartesianSquare":"var x = [ 1, 2 ];\nvar out = base.acartesianSquare( x )\n","base.acos":"var y = base.acos( 1.0 )\ny = base.acos( 0.707 )\ny = base.acos( NaN )\n","base.acosd":"var y = base.acosd( 0.0 )\ny = base.acosd( PI/6.0 )\ny = base.acosd( NaN )\n","base.acosf":"var y = base.acosf( 1.0 )\ny = base.acosf( 0.707 )\ny = base.acosf( NaN )\n","base.acosh":"var y = base.acosh( 1.0 )\ny = base.acosh( 2.0 )\ny = base.acosh( NaN )\n","base.acot":"var y = base.acot( 2.0 )\ny = base.acot( 0.0 )\ny = base.acot( 0.5 )\ny = base.acot( 1.0 )\ny = base.acot( NaN )\n","base.acotd":"var y = base.acotd( 0.0 )\ny = base.acotd( PI/6.0 )\ny = base.acotd( NaN )\n","base.acotf":"var y = base.acotf( 2.0 )\ny = base.acotf( 0.0 )\ny = base.acotf( 0.5 )\ny = base.acotf( 1.0 )\ny = base.acotf( NaN )\n","base.acoth":"var y = base.acoth( 2.0 )\ny = base.acoth( 0.0 )\ny = base.acoth( 0.5 )\ny = base.acoth( 1.0 )\ny = base.acoth( NaN )\n","base.acovercos":"var y = base.acovercos( -1.5 )\ny = base.acovercos( -0.0 )\n","base.acoversin":"var y = base.acoversin( 1.5 )\ny = base.acoversin( 0.0 )\n","base.acsc":"var y = base.acsc( 1.0 )\ny = base.acsc( PI )\ny = base.acsc( -PI )\ny = base.acsc( NaN )\n","base.acscd":"var y = base.acscd( 0.0 )\ny = base.acscd( PI/6.0 )\ny = base.acscd( 1 )\ny = base.acscd( NaN )\n","base.acscdf":"var y = base.acscdf( 0.0 )\ny = base.acscdf( 3.1415927410125732 / 6.0 )\ny = base.acscdf( 1.0 )\ny = base.acscdf( NaN )\n","base.acscf":"var y = base.acscf( 1.0 )\ny = base.acscf( 3.141592653589793 )\ny = base.acscf( -3.141592653589793 )\ny = base.acscf( NaN )\n","base.acsch":"var y = base.acsch( 0.0 )\ny = base.acsch( -1.0 )\ny = base.acsch( NaN )\n","base.add":"var v = base.add( -1.0, 5.0 )\nv = base.add( 2.0, 5.0 )\nv = base.add( 0.0, 5.0 )\nv = base.add( -0.0, 0.0 )\nv = base.add( NaN, NaN )\n","base.add3":"var v = base.add3( -1.0, 5.0, 2.0 )\nv = base.add3( 2.0, 5.0, 2.0 )\nv = base.add3( 0.0, 5.0, 2.0 )\nv = base.add3( -0.0, 0.0, -0.0 )\nv = base.add3( NaN, NaN, NaN )\n","base.add4":"var v = base.add4( -1.0, 5.0, 2.0, -3.0 )\nv = base.add4( 2.0, 5.0, 2.0, -3.0 )\nv = base.add4( 0.0, 5.0, 2.0, -3.0 )\nv = base.add4( -0.0, 0.0, -0.0, -0.0 )\nv = base.add4( NaN, NaN, NaN, NaN )\n","base.add5":"var v = base.add5( -1.0, 5.0, 2.0, -3.0, 4.0 )\nv = base.add5( 2.0, 5.0, 2.0, -3.0, 4.0 )\nv = base.add5( 0.0, 5.0, 2.0, -3.0, 4.0 )\nv = base.add5( -0.0, 0.0, -0.0, -0.0, -0.0 )\nv = base.add5( NaN, NaN, NaN, NaN, NaN )\n","base.addf":"var v = base.addf( -1.0, 5.0 )\nv = base.addf( 2.0, 5.0 )\nv = base.addf( 0.0, 5.0 )\nv = base.addf( -0.0, 0.0 )\nv = base.addf( NaN, NaN )\n","base.afilled":"var out = base.afilled( 0.0, 3 )\n","base.afilled2d":"var out = base.afilled2d( 0.0, [ 1, 3 ] )\n","base.afilled2dBy":"function clbk() { return 1.0; };\nvar out = base.afilled2dBy( [ 1, 3 ], clbk )\n","base.afilled3d":"var out = base.afilled3d( 0.0, [ 1, 1, 3 ] )\n","base.afilled3dBy":"function clbk() { return 1.0; };\nvar out = base.afilled3dBy( [ 1, 1, 3 ], clbk )\n","base.afilled4d":"var out = base.afilled4d( 0.0, [ 1, 1, 1, 3 ] )\n","base.afilled4dBy":"function clbk() { return 1.0; };\nvar out = base.afilled4dBy( [ 1, 1, 1, 3 ], clbk )\n","base.afilled5d":"var out = base.afilled5d( 0.0, [ 1, 1, 1, 1, 3 ] )\n","base.afilled5dBy":"function clbk() { return 1.0; };\nvar out = base.afilled5dBy( [ 1, 1, 1, 1, 3 ], clbk )\n","base.afilledBy":"function clbk() { return 1.0; };\nvar out = base.afilledBy( 3, clbk )\n","base.afillednd":"var out = base.afillednd( 0.0, [ 1, 3 ] )\n","base.afilledndBy":"function clbk() { return 1.0; };\nvar out = base.afilledndBy( [ 1, 3 ], clbk )\n","base.afilter":"function f( v ) { return ( v > 0 ); };\nvar x = [ 1, -2, -3, 4 ];\nvar out = base.afilter( x, f )\n","base.afirst":"var out = base.afirst( [ 1, 2, 3 ] )\n","base.aflatten":"var x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = base.aflatten( x, [ 2, 2 ], false )\nout = base.aflatten( x, [ 2, 2 ], true )\n","base.aflatten.assign":"var x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten.assign( x, [ 2, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten.assign( x, [ 2, 2 ], true, out, 1, 0 );\nout\n","base.aflatten2d":"var x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = base.aflatten2d( x, [ 2, 2 ], false )\nout = base.aflatten2d( x, [ 2, 2 ], true )\n","base.aflatten2d.assign":"var x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten2d.assign( x, [ 2, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten2d.assign( x, [ 2, 2 ], true, out, 1, 0 );\nout\n","base.aflatten2dBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = base.aflatten2dBy( x, [ 2, 2 ], false, fcn )\nout = base.aflatten2dBy( x, [ 2, 2 ], true, fcn )\n","base.aflatten2dBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten2dBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten2dBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\nout\n","base.aflatten3d":"var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\nvar out = base.aflatten3d( x, [ 2, 1, 2 ], false )\nout = base.aflatten3d( x, [ 2, 1, 2 ], true )\n","base.aflatten3d.assign":"var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten3d.assign( x, [ 2, 1, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten3d.assign( x, [ 2, 1, 2 ], true, out, 1, 0 );\nout\n","base.aflatten3dBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\nvar out = base.aflatten3dBy( x, [ 2, 1, 2 ], false, fcn )\nout = base.aflatten3dBy( x, [ 2, 1, 2 ], true, fcn )\n","base.aflatten3dBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten3dBy.assign( x, [ 2, 1, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten3dBy.assign( x, [ 2, 1, 2 ], true, out, 1, 0, fcn );\nout\n","base.aflatten4d":"var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\nvar out = base.aflatten4d( x, [ 2, 1, 1, 2 ], false )\nout = base.aflatten4d( x, [ 2, 1, 1, 2 ], true )\n","base.aflatten4d.assign":"var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten4d.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0 );\nout\n","base.aflatten4dBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\nvar out = base.aflatten4dBy( x, [ 2, 1, 1, 2 ], false, fcn )\nout = base.aflatten4dBy( x, [ 2, 1, 1, 2 ], true, fcn )\n","base.aflatten4dBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0, fcn );\nout\n","base.aflatten5d":"var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\nvar out = base.aflatten5d( x, [ 2, 1, 1, 1, 2 ], false )\nout = base.aflatten5d( x, [ 2, 1, 1, 1, 2 ], true )\n","base.aflatten5d.assign":"var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0 );\nout\n","base.aflatten5dBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\nvar out = base.aflatten5dBy( x, [ 2, 1, 1, 1, 2 ], false, fcn )\nout = base.aflatten5dBy( x, [ 2, 1, 1, 1, 2 ], true, fcn )\n","base.aflatten5dBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0, fcn );\nout\n","base.aflattenBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = base.aflattenBy( x, [ 2, 2 ], false, fcn )\nout = base.aflattenBy( x, [ 2, 2 ], true, fcn )\n","base.aflattenBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflattenBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflattenBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\nout\n","base.afliplr2d":"var out = base.afliplr2d( [ [ 1, 2 ], [ 3, 4 ] ] )\n","base.afliplr3d":"var out = base.afliplr3d( [ [ [ 1, 2 ], [ 3, 4 ] ] ] )\n","base.afliplr4d":"var out = base.afliplr4d( [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] )\n","base.afliplr5d":"var out = base.afliplr5d( [ [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] ] )\n","base.aflipud2d":"var out = base.aflipud2d( [ [ 1, 2 ], [ 3, 4 ] ] )\n","base.aflipud3d":"var out = base.aflipud3d( [ [ [ 1, 2 ], [ 3, 4 ] ] ] )\n","base.aflipud4d":"var out = base.aflipud4d( [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] )\n","base.aflipud5d":"var out = base.aflipud5d( [ [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] ] )\n","base.ahavercos":"var y = base.ahavercos( 0.5 )\ny = base.ahavercos( 0.0 )\n","base.ahaversin":"var y = base.ahaversin( 0.5 )\ny = base.ahaversin( 0.0 )\n","base.altcase":"var out = base.altcase( 'Hello World!' )\nout = base.altcase( 'I am a tiny little teapot' )\n","base.aones":"var out = base.aones( 3 )\n","base.aones2d":"var out = base.aones2d( [ 1, 3 ] )\n","base.aones3d":"var out = base.aones3d( [ 1, 1, 3 ] )\n","base.aones4d":"var out = base.aones4d( [ 1, 1, 1, 3 ] )\n","base.aones5d":"var out = base.aones5d( [ 1, 1, 1, 1, 3 ] )\n","base.aonesnd":"var out = base.aonesnd( [ 1, 3 ] )\n","base.aoneTo":"var arr = base.aoneTo( 6 )\n","base.aoneTo.assign":"var out = [ 0, 0, 0, 0, 0, 0 ];\nbase.aoneTo.assign( out, -1, out.length-1 );\nout\n","base.args2multislice":"var args = [ null, null, null ];\nvar s = new base.args2multislice( args );\ns.data\nargs = [ 10, new Slice( 0, 10, 1 ), null ];\ns = new base.args2multislice( args );\ns.data\n","base.asec":"var y = base.asec( 1.0 )\ny = base.asec( 2.0 )\ny = base.asec( NaN )\n","base.asecd":"var y = base.asecd( 0.0 )\ny = base.asecd( 2 )\ny = base.asecd( NaN )\n","base.asecdf":"var y = base.asecdf( 2.0 )\ny = base.asecdf( 0.0 )\ny = base.asecdf( NaN )\n","base.asecf":"var y = base.asecf( 1.0 )\ny = base.asecf( 2.0 )\ny = base.asecf( NaN )\n","base.asech":"var y = base.asech( 1.0 )\ny = base.asech( 0.5 )\ny = base.asech( NaN )\n","base.asin":"var y = base.asin( 0.0 )\ny = base.asin( -PI/6.0 )\ny = base.asin( NaN )\n","base.asind":"var y = base.asind( 0.0 )\ny = base.asind( PI / 6.0 )\ny = base.asind( NaN )\n","base.asindf":"var y = base.asindf( 0.0 )\ny = base.asindf( 3.1415927410125732 / 6.0 )\ny = base.asindf( NaN )\n","base.asinf":"var y = base.asinf( 0.0 )\ny = base.asinf( -3.14/6.0 )\ny = base.asinf( NaN )\n","base.asinh":"var y = base.asinh( 0.0 )\ny = base.asinh( 2.0 )\ny = base.asinh( -2.0 )\ny = base.asinh( NaN )\ny = base.asinh( NINF )\ny = base.asinh( PINF )\n","base.atan":"var y = base.atan( 0.0 )\ny = base.atan( -PI/2.0 )\ny = base.atan( PI/2.0 )\ny = base.atan( NaN )\n","base.atan2":"var v = base.atan2( 2.0, 2.0 )\nv = base.atan2( 6.0, 2.0 )\nv = base.atan2( -1.0, -1.0 )\nv = base.atan2( 3.0, 0.0 )\nv = base.atan2( -2.0, 0.0 )\nv = base.atan2( 0.0, 0.0 )\nv = base.atan2( 3.0, NaN )\nv = base.atan2( NaN, 2.0 )\n","base.atand":"var y = base.atand( 0.0 )\ny = base.atand( PI/6.0 )\ny = base.atand( NaN )\n","base.atanf":"var y = base.atanf( 0.0 )\ny = base.atanf( -3.14/4.0 )\ny = base.atanf( 3.14/4.0 )\ny = base.atanf( NaN )\n","base.atanh":"var y = base.atanh( 0.0 )\ny = base.atanh( 0.9 )\ny = base.atanh( 1.0 )\ny = base.atanh( -1.0 )\ny = base.atanh( NaN )\n","base.avercos":"var y = base.avercos( -1.5 )\ny = base.avercos( -0.0 )\n","base.aversin":"var y = base.aversin( 1.5 )\ny = base.aversin( 0.0 )\n","base.azeros":"var out = base.azeros( 3 )\n","base.azeros2d":"var out = base.azeros2d( [ 1, 3 ] )\n","base.azeros3d":"var out = base.azeros3d( [ 1, 1, 3 ] )\n","base.azeros4d":"var out = base.azeros4d( [ 1, 1, 1, 3 ] )\n","base.azeros5d":"var out = base.azeros5d( [ 1, 1, 1, 1, 3 ] )\n","base.azerosnd":"var out = base.azerosnd( [ 1, 3 ] )\n","base.azeroTo":"var arr = base.azeroTo( 6 )\n","base.azeroTo.assign":"var out = [ 0, 0, 0, 0, 0, 0 ];\nbase.azeroTo.assign( out, -1, out.length-1 );\nout\n","base.bernoulli":"var y = base.bernoulli( 0 )\ny = base.bernoulli( 1 )\ny = base.bernoulli( 2 )\ny = base.bernoulli( 3 )\ny = base.bernoulli( 4 )\ny = base.bernoulli( 5 )\ny = base.bernoulli( 20 )\ny = base.bernoulli( 260 )\ny = base.bernoulli( 262 )\ny = base.bernoulli( NaN )\n","base.besselj0":"var y = base.besselj0( 0.0 )\ny = base.besselj0( 1.0 )\ny = base.besselj0( PINF )\ny = base.besselj0( NINF )\ny = base.besselj0( NaN )\n","base.besselj1":"var y = base.besselj1( 0.0 )\ny = base.besselj1( 1.0 )\ny = base.besselj1( PINF )\ny = base.besselj1( NINF )\ny = base.besselj1( NaN )\n","base.bessely0":"var y = base.bessely0( 0.0 )\ny = base.bessely0( 1.0 )\ny = base.bessely0( -1.0 )\ny = base.bessely0( PINF )\ny = base.bessely0( NINF )\ny = base.bessely0( NaN )\n","base.bessely1":"var y = base.bessely1( 0.0 )\ny = base.bessely1( 1.0 )\ny = base.bessely1( -1.0 )\ny = base.bessely1( PINF )\ny = base.bessely1( NINF )\ny = base.bessely1( NaN )\n","base.beta":"var v = base.beta( 0.0, 0.5 )\nv = base.beta( 1.0, 1.0 )\nv = base.beta( -1.0, 2.0 )\nv = base.beta( 5.0, 0.2 )\nv = base.beta( 4.0, 1.0 )\nv = base.beta( NaN, 2.0 )\n","base.betainc":"var y = base.betainc( 0.5, 2.0, 2.0 )\ny = base.betainc( 0.5, 2.0, 2.0, false )\ny = base.betainc( 0.2, 1.0, 2.0 )\ny = base.betainc( 0.2, 1.0, 2.0, true, true )\ny = base.betainc( NaN, 1.0, 1.0 )\ny = base.betainc( 0.8, NaN, 1.0 )\ny = base.betainc( 0.8, 1.0, NaN )\ny = base.betainc( 1.5, 1.0, 1.0 )\ny = base.betainc( -0.5, 1.0, 1.0 )\ny = base.betainc( 0.5, -2.0, 2.0 )\ny = base.betainc( 0.5, 2.0, -2.0 )\n","base.betaincinv":"var y = base.betaincinv( 0.2, 3.0, 3.0 )\ny = base.betaincinv( 0.4, 3.0, 3.0 )\ny = base.betaincinv( 0.4, 3.0, 3.0, true )\ny = base.betaincinv( 0.4, 1.0, 6.0 )\ny = base.betaincinv( 0.8, 1.0, 6.0 )\ny = base.betaincinv( NaN, 1.0, 1.0 )\ny = base.betaincinv( 0.5, NaN, 1.0 )\ny = base.betaincinv( 0.5, 1.0, NaN )\ny = base.betaincinv( 1.2, 1.0, 1.0 )\ny = base.betaincinv( -0.5, 1.0, 1.0 )\ny = base.betaincinv( 0.5, -2.0, 2.0 )\ny = base.betaincinv( 0.5, 0.0, 2.0 )\ny = base.betaincinv( 0.5, 2.0, -2.0 )\ny = base.betaincinv( 0.5, 2.0, 0.0 )\n","base.betaln":"var v = base.betaln( 0.0, 0.0 )\nv = base.betaln( 1.0, 1.0 )\nv = base.betaln( -1.0, 2.0 )\nv = base.betaln( 5.0, 0.2 )\nv = base.betaln( 4.0, 1.0 )\nv = base.betaln( NaN, 2.0 )\n","base.binet":"var y = base.binet( 0.0 )\ny = base.binet( 1.0 )\ny = base.binet( 2.0 )\ny = base.binet( 3.0 )\ny = base.binet( 4.0 )\ny = base.binet( 5.0 )\ny = base.binet( NaN )\n","base.binomcoef":"var v = base.binomcoef( 8, 2 )\nv = base.binomcoef( 0, 0 )\nv = base.binomcoef( -4, 2 )\nv = base.binomcoef( 5, 3 )\nv = base.binomcoef( NaN, 3 )\nv = base.binomcoef( 5, NaN )\nv = base.binomcoef( NaN, NaN )\n","base.binomcoefln":"var v = base.binomcoefln( 8, 2 )\nv = base.binomcoefln( 0, 0 )\nv = base.binomcoefln( -4, 2 )\nv = base.binomcoefln( 88, 3 )\nv = base.binomcoefln( NaN, 3 )\nv = base.binomcoefln( 5, NaN )\nv = base.binomcoefln( NaN, NaN )\n","base.boxcox":"var v = base.boxcox( 1.0, 2.5 )\nv = base.boxcox( 4.0, 2.5 )\nv = base.boxcox( 10.0, 2.5 )\nv = base.boxcox( 2.0, 0.0 )\nv = base.boxcox( -1.0, 2.5 )\nv = base.boxcox( 0.0, -1.0 )\n","base.boxcox1p":"var v =  base.boxcox1p( 1.0, 2.5 )\nv = base.boxcox1p( 4.0, 2.5 )\nv = base.boxcox1p( 10.0, 2.5 )\nv = base.boxcox1p( 2.0, 0.0 )\nv = base.boxcox1p( -1.0, 2.5 )\nv = base.boxcox1p( 0.0, -1.0 )\nv = base.boxcox1p( -1.0, -1.0 )\n","base.boxcox1pinv":"var v = base.boxcox1pinv( 1.0, 2.5 )\nv = base.boxcox1pinv( 4.0, 2.5 )\nv = base.boxcox1pinv( 10.0, 2.5 )\nv = base.boxcox1pinv( 2.0, 0.0 )\nv = base.boxcox1pinv( -1.0, 2.5 )\nv = base.boxcox1pinv( 0.0, -1.0 )\nv = base.boxcox1pinv( 1.0, NaN )\nv = base.boxcox1pinv( NaN, 3.1 )\n","base.boxcoxinv":"var v = base.boxcoxinv( 1.0, 2.5 )\nv = base.boxcoxinv( 4.0, 2.5 )\nv = base.boxcoxinv( 10.0, 2.5 )\nv = base.boxcoxinv( 2.0, 0.0 )\nv = base.boxcoxinv( -1.0, 2.5 )\nv = base.boxcoxinv( 0.0, -1.0 )\nv = base.boxcoxinv( 1.0, NaN )\nv = base.boxcoxinv( NaN, 3.1 )\n","base.cabs":"var y = base.cabs( new Complex128( 5.0, 3.0 ) )\n","base.cabs2":"var y = base.cabs2( new Complex128( 5.0, 3.0 ) )\n","base.cabs2f":"var y = base.cabs2f( new Complex64( 5.0, 3.0 ) )\n","base.cabsf":"var y = base.cabsf( new Complex64( 5.0, 3.0 ) )\n","base.cadd":"var z = new Complex128( 5.0, 3.0 )\nvar out = base.cadd( z, z )\nvar re = real( out )\nvar im = imag( out )\n","base.caddf":"var z = new Complex64( 5.0, 3.0 )\nvar out = base.caddf( z, z )\nvar re = realf( out )\nvar im = imagf( out )\n","base.camelcase":"var out = base.camelcase( 'Hello World!' )\nout = base.camelcase( 'beep boop' )\n","base.capitalize":"var out = base.capitalize( 'beep' )\nout = base.capitalize( 'Boop' )\n","base.cbrt":"var y = base.cbrt( 64.0 )\ny = base.cbrt( 27.0 )\ny = base.cbrt( 0.0 )\ny = base.cbrt( -0.0 )\ny = base.cbrt( -9.0 )\ny = base.cbrt( NaN )\n","base.cbrtf":"var y = base.cbrtf( 64.0 )\ny = base.cbrtf( 27.0 )\ny = base.cbrtf( 0.0 )\ny = base.cbrtf( -0.0 )\ny = base.cbrtf( -9.0 )\ny = base.cbrtf( NaN )\n","base.cceil":"var v = base.cceil( new Complex128( -1.5, 2.5 ) )\nvar re = real( v )\nvar im = imag( v )\n","base.cceilf":"var v = base.cceilf( new Complex64( -1.5, 2.5 ) )\nvar re = realf( v )\nvar im = imagf( v )\n","base.cceiln":"var out = base.cceiln( new Complex128( 5.555, -3.333 ), -2 )\nvar re = real( out )\nvar im = imag( out )\n","base.ccis":"var y = base.ccis( new Complex128( 0.0, 0.0 ) )\nvar re = real( y )\nvar im = imag( y )\ny = base.ccis( new Complex128( 1.0, 0.0 ) )\nre = real( y )\nim = imag( y )\n","base.cdiv":"var z1 = new Complex128( -13.0, -1.0 )\nvar z2 = new Complex128( -2.0, 1.0 )\nvar y = base.cdiv( z1, z2 )\nvar re = real( y )\nvar im = imag( y )\n","base.ceil":"var y = base.ceil( 3.14 )\ny = base.ceil( -4.2 )\ny = base.ceil( -4.6 )\ny = base.ceil( 9.5 )\ny = base.ceil( -0.0 )\n","base.ceil2":"var y = base.ceil2( 3.14 )\ny = base.ceil2( -4.2 )\ny = base.ceil2( -4.6 )\ny = base.ceil2( 9.5 )\ny = base.ceil2( 13.0 )\ny = base.ceil2( -13.0 )\ny = base.ceil2( -0.0 )\n","base.ceil10":"var y = base.ceil10( 3.14 )\ny = base.ceil10( -4.2 )\ny = base.ceil10( -4.6 )\ny = base.ceil10( 9.5 )\ny = base.ceil10( 13.0 )\ny = base.ceil10( -13.0 )\ny = base.ceil10( -0.0 )\n","base.ceilb":"var y = base.ceilb( 3.14159, -4, 10 )\ny = base.ceilb( 3.14159, 0, 2 )\ny = base.ceilb( 5.0, 1, 2 )\n","base.ceilf":"var y = base.ceilf( 3.14 )\ny = base.ceilf( -4.2 )\ny = base.ceilf( -4.6 )\ny = base.ceilf( 9.5 )\ny = base.ceilf( -0.0 )\n","base.ceiln":"var y = base.ceiln( 3.14159, -2 )\ny = base.ceiln( 3.14159, 0 )\ny = base.ceiln( 12368.0, 3 )\n","base.ceilsd":"var y = base.ceilsd( 3.14159, 5, 10 )\ny = base.ceilsd( 3.14159, 1, 10 )\ny = base.ceilsd( 12368.0, 2, 10 )\ny = base.ceilsd( 0.0313, 2, 2 )\n","base.cexp":"var y = base.cexp( new Complex128( 0.0, 0.0 ) )\nvar re = real( y )\nvar im = imag( y )\ny = base.cexp( new Complex128( 0.0, 1.0 ) )\nre = real( y )\nim = imag( y )\n","base.cflipsign":"var v = base.cflipsign( new Complex128( -4.2, 5.5 ), -9.0 )\nvar re = real( v )\nvar im = imag( v )\n","base.cflipsignf":"var v = base.cflipsignf( new Complex64( -4.0, 5.0 ), -9.0 )\nvar re = realf( v )\nvar im = imagf( v )\n","base.cfloor":"var v = base.cfloor( new Complex128( 5.5, 3.3 ) )\nvar re = real( v )\nvar im = imag( v )\n","base.cfloorn":"var v = base.cfloorn( new Complex128( 5.555, -3.333 ), -2 )\nvar re = real( v )\nvar im = imag( v )\n","base.cidentity":"var v = base.cidentity( new Complex128( -1.0, 2.0 ) )\nvar re = real( v )\nvar img = imag( v )\n","base.cidentityf":"var v = base.cidentityf( new Complex64( -1.0, 2.0 ) )\nvar re = realf( v )\nvar img = imagf( v )\n","base.cinv":"var v = base.cinv( new Complex128( 2.0, 4.0 ) )\nvar re = real( v )\nvar im = imag( v )\n","base.clamp":"var y = base.clamp( 3.14, 0.0, 5.0 )\ny = base.clamp( -3.14, 0.0, 5.0 )\ny = base.clamp( 3.14, 0.0, 3.0 )\ny = base.clamp( -0.0, 0.0, 5.0 )\ny = base.clamp( 0.0, -3.14, -0.0 )\ny = base.clamp( NaN, 0.0, 5.0 )\n","base.clampf":"var y = base.clampf( 3.14, 0.0, 5.0 )\ny = base.clampf( -3.14, 0.0, 5.0 )\ny = base.clampf( 3.14, 0.0, 3.0 )\ny = base.clampf( -0.0, 0.0, 5.0 )\ny = base.clampf( 0.0, -3.14, -0.0 )\ny = base.clampf( NaN, 0.0, 5.0 )\n","base.cmul":"var z1 = new Complex128( 5.0, 3.0 )\nvar z2 = new Complex128( -2.0, 1.0 )\nvar out = base.cmul( z1, z2 )\nvar re = real( out )\nvar im = imag( out )\n","base.cmulf":"var z1 = new Complex64( 5.0, 3.0 )\nvar z2 = new Complex64( -2.0, 1.0 )\nvar out = base.cmulf( z1, z2 )\nvar re = realf( out )\nvar im = imagf( out )\n","base.cneg":"var z = new Complex128( -4.2, 5.5 )\nvar v = base.cneg( z )\nvar re = real( v )\nvar im = imag( v )\n","base.cnegf":"var z = new Complex64( -4.0, 5.0 )\nvar v = base.cnegf( z )\nvar re = realf( v )\nvar im = imagf( v )\n","base.codePointAt":"var out = base.codePointAt( 'last man standing', 4, false )\nout = base.codePointAt( 'presidential election', 8, true )\nout = base.codePointAt( 'अनुच्छेद', 2, false )\nout = base.codePointAt( '🌷', 1, true )\n","base.constantcase":"var out = base.constantcase( 'Hello World!' )\nout = base.constantcase( 'I am a tiny little teapot' )\n","base.continuedFraction":"function closure() {\nvar i = 0;\nreturn function() {\n    i += 1;\n    return [ i, i ];\n};\n };\nvar gen = closure();\nvar out = base.continuedFraction( gen )\nfunction* generator() {\n var i = 0;\n while ( true ) {\n     i += 1;\n     yield [ i, i ];\n }\n };\ngen = generator();\nout = base.continuedFraction( gen )\nout = base.continuedFraction( generator(), { 'keep': true } )\nout = base.continuedFraction( generator(), { 'maxIter': 10 } )\nout = base.continuedFraction( generator(), { 'tolerance': 1e-1 } )\n","base.copysign":"var z = base.copysign( -3.14, 10.0 )\nz = base.copysign( 3.14, -1.0 )\nz = base.copysign( 1.0, -0.0 )\nz = base.copysign( -3.14, -0.0 )\nz = base.copysign( -0.0, 1.0 )\n","base.copysignf":"var z = base.copysignf( -3.0, 10.0 )\nz = base.copysignf( 3.0, -1.0 )\nz = base.copysignf( 1.0, -0.0 )\nz = base.copysignf( -3.0, -0.0 )\nz = base.copysignf( -0.0, 1.0 )\n","base.cos":"var y = base.cos( 0.0 )\ny = base.cos( PI/4.0 )\ny = base.cos( -PI/6.0 )\ny = base.cos( NaN )\n","base.cosd":"var y = base.cosd( 0.0 )\ny = base.cosd( 90.0 )\ny = base.cosd( 60.0 )\ny = base.cosd( NaN )\n","base.cosh":"var y = base.cosh( 0.0 )\ny = base.cosh( 2.0 )\ny = base.cosh( -2.0 )\ny = base.cosh( NaN )\n","base.cosm1":"var y = base.cosm1( 0.0 )\ny = base.cosm1( PI/4.0 )\ny = base.cosm1( -PI/6.0 )\ny = base.cosm1( NaN )\n","base.cospi":"var y = base.cospi( 0.0 )\ny = base.cospi( 0.5 )\ny = base.cospi( 0.1 )\ny = base.cospi( NaN )\n","base.cot":"var y = base.cot( 0.0 )\ny = base.cot( -PI/4.0 )\ny = base.cot( PI/4.0 )\ny = base.cot( NaN )\n","base.cotd":"var y = base.cotd( 0.0 )\ny = base.cotd( 90.0 )\ny = base.cotd( 60.0 )\ny = base.cotd( NaN )\n","base.coth":"var y = base.coth( 0.0 )\ny = base.coth( -0.0 )\ny = base.coth( 2.0 )\ny = base.coth( -2.0 )\ny = base.coth( +Infinity )\ny = base.coth( -Infinity )\ny = base.coth( NaN )\n","base.covercos":"var y = base.covercos( 3.14 )\ny = base.covercos( -4.2 )\ny = base.covercos( -4.6 )\ny = base.covercos( 9.5 )\ny = base.covercos( -0.0 )\n","base.coversin":"var y = base.coversin( 3.14 )\ny = base.coversin( -4.2 )\ny = base.coversin( -4.6 )\ny = base.coversin( 9.5 )\ny = base.coversin( -0.0 )\n","base.cphase":"var phi = base.cphase( new Complex128( 5.0, 3.0 ) )\n","base.cpolar":"var out = base.cpolar( new Complex128( 5.0, 3.0 ) )\n","base.cpolar.assign":"var out = new Float64Array( 2 );\nvar v = base.cpolar.assign( new Complex128( 5.0, 3.0 ), out, 1, 0 )\nvar bool = ( v === out )\n","base.cround":"var v = base.cround( new Complex128( 5.5, 3.3 ) )\nvar re = real( v )\nvar im = imag( v )\n","base.croundn":"var v = base.croundn( new Complex128( 5.555, -3.336 ), -2 )\nvar re = real( v )\nvar im = imag( v )\n","base.csc":"var y = base.csc( 0.0 )\ny = base.csc( PI/2.0 )\ny = base.csc( -PI/6.0 )\ny = base.csc( NaN )\n","base.cscd":"var y = base.cscd( 1.0 )\ny = base.cscd( PI )\ny = base.cscd( -PI )\ny = base.cscd( NaN )\n","base.csch":"var y = base.csch( +0.0 )\nvar y = base.csch( -0.0 )\nvar y = base.csch( +Infinity )\nvar y = base.csch( -Infinity )\ny = base.csch( 2.0 )\ny = base.csch( -2.0 )\ny = base.csch( NaN )\n","base.csignum":"var v = base.csignum( new Complex128( -4.2, 5.5 ) )\nvar re = real( v )\nvar im = imag( v )\n","base.csub":"var z1 = new Complex128( 5.0, 3.0 )\nvar z2 = new Complex128( -2.0, 1.0 )\nvar out = base.csub( z1, z2 )\nvar re = real( out )\nvar im = imag( out )\n","base.csubf":"var z1 = new Complex64( 5.0, 3.0 )\nvar z2 = new Complex64( -2.0, 1.0 )\nvar out = base.csubf( z1, z2 )\nvar re = realf( out )\nvar im = imagf( out )\n","base.deg2rad":"var r = base.deg2rad( 90.0 )\nr = base.deg2rad( -45.0 )\nr = base.deg2rad( NaN )\n","base.deg2radf":"var r = base.deg2radf( 90.0 )\nr = base.deg2radf( -45.0 )\nr = base.deg2radf( NaN )\n","base.digamma":"var y = base.digamma( -2.5 )\ny = base.digamma( 1.0 )\ny = base.digamma( 10.0 )\ny = base.digamma( NaN )\ny = base.digamma( -1.0 )\n","base.diracDelta":"var y = base.diracDelta( 3.14 )\ny = base.diracDelta( 0.0 )\n","base.div":"var v = base.div( -1.0, 5.0 )\nv = base.div( 2.0, 5.0 )\nv = base.div( 0.0, 5.0 )\nv = base.div( -0.0, 5.0 )\nv = base.div( NaN, NaN )\n","base.divf":"var v = base.divf( -1.0, 5.0 )\nv = base.divf( 2.0, 5.0 )\nv = base.divf( 0.0, 5.0 )\nv = base.divf( -0.0, 5.0 )\nv = base.divf( NaN, NaN )\n","base.dotcase":"var out = base.dotcase( 'Hello World!' )\nout = base.dotcase( 'I am a tiny little teapot' )\n","base.dists.arcsine.Arcsine":"var arcsine = base.dists.arcsine.Arcsine( 0.0, 1.0 );\narcsine.a\narcsine.b\narcsine.entropy\narcsine.kurtosis\narcsine.mean\narcsine.median\narcsine.mode\narcsine.skewness\narcsine.stdev\narcsine.variance\narcsine.cdf( 0.8 )\narcsine.logcdf( 0.8 )\narcsine.logpdf( 0.4 )\narcsine.pdf( 0.8 )\narcsine.quantile( 0.8 )\n","base.dists.arcsine.cdf":"var y = base.dists.arcsine.cdf( 9.0, 0.0, 10.0 )\ny = base.dists.arcsine.cdf( 0.5, 0.0, 2.0 )\ny = base.dists.arcsine.cdf( PINF, 2.0, 4.0 )\ny = base.dists.arcsine.cdf( NINF, 2.0, 4.0 )\ny = base.dists.arcsine.cdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.cdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.cdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.cdf( 2.0, 1.0, 0.0 )\n","base.dists.arcsine.cdf.factory":"var mycdf = base.dists.arcsine.cdf.factory( 0.0, 10.0 );\nvar y = mycdf( 0.5 )\ny = mycdf( 8.0 )\n","base.dists.arcsine.entropy":"var v = base.dists.arcsine.entropy( 0.0, 1.0 )\nv = base.dists.arcsine.entropy( 4.0, 12.0 )\nv = base.dists.arcsine.entropy( 2.0, 8.0 )\n","base.dists.arcsine.kurtosis":"var v = base.dists.arcsine.kurtosis( 0.0, 1.0 )\nv = base.dists.arcsine.kurtosis( 4.0, 12.0 )\nv = base.dists.arcsine.kurtosis( 2.0, 8.0 )\n","base.dists.arcsine.logcdf":"var y = base.dists.arcsine.logcdf( 9.0, 0.0, 10.0 )\ny = base.dists.arcsine.logcdf( 0.5, 0.0, 2.0 )\ny = base.dists.arcsine.logcdf( PINF, 2.0, 4.0 )\ny = base.dists.arcsine.logcdf( NINF, 2.0, 4.0 )\ny = base.dists.arcsine.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.logcdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.logcdf( 2.0, 1.0, 0.0 )\n","base.dists.arcsine.logcdf.factory":"var mylogcdf = base.dists.arcsine.logcdf.factory( 0.0, 10.0 );\nvar y = mylogcdf( 0.5 )\ny = mylogcdf( 8.0 )\n","base.dists.arcsine.logpdf":"var y = base.dists.arcsine.logpdf( 2.0, 0.0, 4.0 )\ny = base.dists.arcsine.logpdf( 5.0, 0.0, 4.0 )\ny = base.dists.arcsine.logpdf( 0.25, 0.0, 1.0 )\ny = base.dists.arcsine.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.logpdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.logpdf( 2.0, 3.0, 1.0 )\n","base.dists.arcsine.logpdf.factory":"var mylogPDF = base.dists.arcsine.logpdf.factory( 6.0, 7.0 );\nvar y = mylogPDF( 7.0 )\ny = mylogPDF( 5.0 )\n","base.dists.arcsine.mean":"var v = base.dists.arcsine.mean( 0.0, 1.0 )\nv = base.dists.arcsine.mean( 4.0, 12.0 )\nv = base.dists.arcsine.mean( 2.0, 8.0 )\n","base.dists.arcsine.median":"var v = base.dists.arcsine.median( 0.0, 1.0 )\nv = base.dists.arcsine.median( 4.0, 12.0 )\nv = base.dists.arcsine.median( 2.0, 8.0 )\n","base.dists.arcsine.mode":"var v = base.dists.arcsine.mode( 0.0, 1.0 )\nv = base.dists.arcsine.mode( 4.0, 12.0 )\nv = base.dists.arcsine.mode( 2.0, 8.0 )\n","base.dists.arcsine.pdf":"var y = base.dists.arcsine.pdf( 2.0, 0.0, 4.0 )\ny = base.dists.arcsine.pdf( 5.0, 0.0, 4.0 )\ny = base.dists.arcsine.pdf( 0.25, 0.0, 1.0 )\ny = base.dists.arcsine.pdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.pdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.pdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.pdf( 2.0, 3.0, 1.0 )\n","base.dists.arcsine.pdf.factory":"var myPDF = base.dists.arcsine.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 7.0 )\ny = myPDF( 5.0 )\n","base.dists.arcsine.quantile":"var y = base.dists.arcsine.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( 0.5, 0.0, 10.0 )\ny = base.dists.arcsine.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.quantile( 0.0, 0.0, NaN )\ny = base.dists.arcsine.quantile( 0.5, 2.0, 1.0 )\n","base.dists.arcsine.quantile.factory":"var myQuantile = base.dists.arcsine.quantile.factory( 0.0, 4.0 );\nvar y = myQuantile( 0.8 )\n","base.dists.arcsine.skewness":"var v = base.dists.arcsine.skewness( 0.0, 1.0 )\nv = base.dists.arcsine.skewness( 4.0, 12.0 )\nv = base.dists.arcsine.skewness( 2.0, 8.0 )\n","base.dists.arcsine.stdev":"var v = base.dists.arcsine.stdev( 0.0, 1.0 )\nv = base.dists.arcsine.stdev( 4.0, 12.0 )\nv = base.dists.arcsine.stdev( 2.0, 8.0 )\n","base.dists.arcsine.variance":"var v = base.dists.arcsine.variance( 0.0, 1.0 )\nv = base.dists.arcsine.variance( 4.0, 12.0 )\nv = base.dists.arcsine.variance( 2.0, 8.0 )\n","base.dists.bernoulli.Bernoulli":"var bernoulli = base.dists.bernoulli.Bernoulli( 0.6 );\nbernoulli.p\nbernoulli.entropy\nbernoulli.kurtosis\nbernoulli.mean\nbernoulli.median\nbernoulli.skewness\nbernoulli.stdev\nbernoulli.variance\nbernoulli.cdf( 0.5 )\nbernoulli.mgf( 3.0 )\nbernoulli.pmf( 0.0 )\nbernoulli.quantile( 0.7 )\n","base.dists.bernoulli.cdf":"var y = base.dists.bernoulli.cdf( 0.5, 0.5 )\ny = base.dists.bernoulli.cdf( 0.8, 0.1 )\ny = base.dists.bernoulli.cdf( -1.0, 0.4 )\ny = base.dists.bernoulli.cdf( 1.5, 0.4 )\ny = base.dists.bernoulli.cdf( NaN, 0.5 )\ny = base.dists.bernoulli.cdf( 0.0, NaN )\ny = base.dists.bernoulli.cdf( 2.0, 1.4 )\n","base.dists.bernoulli.cdf.factory":"var mycdf = base.dists.bernoulli.cdf.factory( 0.5 );\nvar y = mycdf( 3.0 )\ny = mycdf( 0.7 )\n","base.dists.bernoulli.entropy":"var v = base.dists.bernoulli.entropy( 0.1 )\nv = base.dists.bernoulli.entropy( 0.5 )\n","base.dists.bernoulli.kurtosis":"var v = base.dists.bernoulli.kurtosis( 0.1 )\nv = base.dists.bernoulli.kurtosis( 0.5 )\n","base.dists.bernoulli.mean":"var v = base.dists.bernoulli.mean( 0.1 )\nv = base.dists.bernoulli.mean( 0.5 )\n","base.dists.bernoulli.median":"var v = base.dists.bernoulli.median( 0.1 )\nv = base.dists.bernoulli.median( 0.8 )\n","base.dists.bernoulli.mgf":"var y = base.dists.bernoulli.mgf( 0.2, 0.5 )\ny = base.dists.bernoulli.mgf( 0.4, 0.5 )\ny = base.dists.bernoulli.mgf( NaN, 0.0 )\ny = base.dists.bernoulli.mgf( 0.0, NaN )\ny = base.dists.bernoulli.mgf( -2.0, -1.0 )\ny = base.dists.bernoulli.mgf( 0.2, 2.0 )\n","base.dists.bernoulli.mgf.factory":"var mymgf = base.dists.bernoulli.mgf.factory( 0.8 );\nvar y = mymgf( -0.2 )\n","base.dists.bernoulli.mode":"var v = base.dists.bernoulli.mode( 0.1 )\nv = base.dists.bernoulli.mode( 0.8 )\n","base.dists.bernoulli.pmf":"var y = base.dists.bernoulli.pmf( 1.0, 0.3 )\ny = base.dists.bernoulli.pmf( 0.0, 0.7 )\ny = base.dists.bernoulli.pmf( -1.0, 0.5 )\ny = base.dists.bernoulli.pmf( 0.0, NaN )\ny = base.dists.bernoulli.pmf( NaN, 0.5 )\ny = base.dists.bernoulli.pmf( 0.0, 1.5 )\n","base.dists.bernoulli.pmf.factory":"var mypmf = base.dists.bernoulli.pmf.factory( 0.5 );\nvar y = mypmf( 1.0 )\ny = mypmf( 0.0 )\n","base.dists.bernoulli.quantile":"var y = base.dists.bernoulli.quantile( 0.8, 0.4 )\ny = base.dists.bernoulli.quantile( 0.5, 0.4 )\ny = base.dists.bernoulli.quantile( 0.9, 0.1 )\ny = base.dists.bernoulli.quantile( -0.2, 0.1 )\ny = base.dists.bernoulli.quantile( NaN, 0.8 )\ny = base.dists.bernoulli.quantile( 0.4, NaN )\ny = base.dists.bernoulli.quantile( 0.5, -1.0 )\ny = base.dists.bernoulli.quantile( 0.5, 1.5 )\n","base.dists.bernoulli.quantile.factory":"var myquantile = base.dists.bernoulli.quantile.factory( 0.4 );\nvar y = myquantile( 0.4 )\ny = myquantile( 0.8 )\ny = myquantile( 1.0 )\n","base.dists.bernoulli.skewness":"var v = base.dists.bernoulli.skewness( 0.1 )\nv = base.dists.bernoulli.skewness( 0.5 )\n","base.dists.bernoulli.stdev":"var v = base.dists.bernoulli.stdev( 0.1 )\nv = base.dists.bernoulli.stdev( 0.5 )\n","base.dists.bernoulli.variance":"var v = base.dists.bernoulli.variance( 0.1 )\nv = base.dists.bernoulli.variance( 0.5 )\n","base.dists.beta.Beta":"var beta = base.dists.beta.Beta( 1.0, 1.0 );\nbeta.alpha\nbeta.beta\nbeta.entropy\nbeta.kurtosis\nbeta.mean\nbeta.median\nbeta.mode\nbeta.skewness\nbeta.stdev\nbeta.variance\nbeta.cdf( 0.8 )\nbeta.logcdf( 0.8 )\nbeta.logpdf( 1.0 )\nbeta.mgf( 3.14 )\nbeta.pdf( 1.0 )\nbeta.quantile( 0.8 )\n","base.dists.beta.cdf":"var y = base.dists.beta.cdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.cdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.cdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.cdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.cdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.cdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.beta.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.beta.cdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.cdf( 0.0, NaN, 1.0 )\ny = base.dists.beta.cdf( 0.0, 1.0, NaN )\n","base.dists.beta.cdf.factory":"var mycdf = base.dists.beta.cdf.factory( 0.5, 0.5 );\nvar y = mycdf( 0.8 )\ny = mycdf( 0.3 )\n","base.dists.beta.entropy":"var v = base.dists.beta.entropy( 1.0, 1.0 )\nv = base.dists.beta.entropy( 4.0, 12.0 )\nv = base.dists.beta.entropy( 8.0, 2.0 )\nv = base.dists.beta.entropy( 1.0, -0.1 )\nv = base.dists.beta.entropy( -0.1, 1.0 )\nv = base.dists.beta.entropy( 2.0, NaN )\nv = base.dists.beta.entropy( NaN, 2.0 )\n","base.dists.beta.kurtosis":"var v = base.dists.beta.kurtosis( 1.0, 1.0 )\nv = base.dists.beta.kurtosis( 4.0, 12.0 )\nv = base.dists.beta.kurtosis( 8.0, 2.0 )\nv = base.dists.beta.kurtosis( 1.0, -0.1 )\nv = base.dists.beta.kurtosis( -0.1, 1.0 )\nv = base.dists.beta.kurtosis( 2.0, NaN )\nv = base.dists.beta.kurtosis( NaN, 2.0 )\n","base.dists.beta.logcdf":"var y = base.dists.beta.logcdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.logcdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.logcdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.logcdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.logcdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.logcdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.beta.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.beta.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.beta.logcdf( 0.0, 1.0, NaN )\n","base.dists.beta.logcdf.factory":"var mylogcdf = base.dists.beta.logcdf.factory( 0.5, 0.5 );\nvar y = mylogcdf( 0.8 )\ny = mylogcdf( 0.3 )\n","base.dists.beta.logpdf":"var y = base.dists.beta.logpdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.logpdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.logpdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.logpdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.logpdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.logpdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.logpdf( 0.5, -1.0, 0.5 )\ny = base.dists.beta.logpdf( 0.5, 0.5, -1.0 )\ny = base.dists.beta.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.logpdf( 0.5, NaN, 1.0 )\ny = base.dists.beta.logpdf( 0.5, 1.0, NaN )\n","base.dists.beta.logpdf.factory":"var mylogpdf = base.dists.beta.logpdf.factory( 0.5, 0.5 );\nvar y = mylogpdf( 0.8 )\ny = mylogpdf( 0.3 )\n","base.dists.beta.mean":"var v = base.dists.beta.mean( 1.0, 1.0 )\nv = base.dists.beta.mean( 4.0, 12.0 )\nv = base.dists.beta.mean( 8.0, 2.0 )\n","base.dists.beta.median":"var v = base.dists.beta.median( 1.0, 1.0 )\nv = base.dists.beta.median( 4.0, 12.0 )\nv = base.dists.beta.median( 8.0, 2.0 )\nv = base.dists.beta.median( 1.0, -0.1 )\nv = base.dists.beta.median( -0.1, 1.0 )\nv = base.dists.beta.median( 2.0, NaN )\nv = base.dists.beta.median( NaN, 2.0 )\n","base.dists.beta.mgf":"var y = base.dists.beta.mgf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.mgf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.mgf( 3.0, 2.0, 2.0 )\ny = base.dists.beta.mgf( -0.8, 4.0, 4.0 )\ny = base.dists.beta.mgf( NaN, 1.0, 1.0 )\ny = base.dists.beta.mgf( 0.0, NaN, 1.0 )\ny = base.dists.beta.mgf( 0.0, 1.0, NaN )\ny = base.dists.beta.mgf( 2.0, -1.0, 0.5 )\ny = base.dists.beta.mgf( 2.0, 0.0, 0.5 )\ny = base.dists.beta.mgf( 2.0, 0.5, -1.0 )\ny = base.dists.beta.mgf( 2.0, 0.5, 0.0 )\n","base.dists.beta.mgf.factory":"var myMGF = base.dists.beta.mgf.factory( 0.5, 0.5 );\nvar y = myMGF( 0.8 )\ny = myMGF( 0.3 )\n","base.dists.beta.mode":"var v = base.dists.beta.mode( 4.0, 12.0 )\nv = base.dists.beta.mode( 8.0, 2.0 )\nv = base.dists.beta.mode( 1.0, 1.0 )\n","base.dists.beta.pdf":"var y = base.dists.beta.pdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.pdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.pdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.pdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.pdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.pdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.pdf( 0.5, -1.0, 0.5 )\ny = base.dists.beta.pdf( 0.5, 0.5, -1.0 )\ny = base.dists.beta.pdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.pdf( 0.5, NaN, 1.0 )\ny = base.dists.beta.pdf( 0.5, 1.0, NaN )\n","base.dists.beta.pdf.factory":"var mypdf = base.dists.beta.pdf.factory( 0.5, 0.5 );\nvar y = mypdf( 0.8 )\ny = mypdf( 0.3 )\n","base.dists.beta.quantile":"var y = base.dists.beta.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.beta.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.beta.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.beta.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.beta.quantile( NaN, 1.0, 1.0 )\ny = base.dists.beta.quantile( 0.5, NaN, 1.0 )\ny = base.dists.beta.quantile( 0.5, 1.0, NaN )\ny = base.dists.beta.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.beta.quantile( 0.5, 1.0, -1.0 )\n","base.dists.beta.quantile.factory":"var myquantile = base.dists.beta.quantile.factory( 2.0, 2.0 );\ny = myquantile( 0.8 )\ny = myquantile( 0.4 )\n","base.dists.beta.skewness":"var v = base.dists.beta.skewness( 1.0, 1.0 )\nv = base.dists.beta.skewness( 4.0, 12.0 )\nv = base.dists.beta.skewness( 8.0, 2.0 )\nv = base.dists.beta.skewness( 1.0, -0.1 )\nv = base.dists.beta.skewness( -0.1, 1.0 )\nv = base.dists.beta.skewness( 2.0, NaN )\nv = base.dists.beta.skewness( NaN, 2.0 )\n","base.dists.beta.stdev":"var v = base.dists.beta.stdev( 1.0, 1.0 )\nv = base.dists.beta.stdev( 4.0, 12.0 )\nv = base.dists.beta.stdev( 8.0, 2.0 )\nv = base.dists.beta.stdev( 1.0, -0.1 )\nv = base.dists.beta.stdev( -0.1, 1.0 )\nv = base.dists.beta.stdev( 2.0, NaN )\nv = base.dists.beta.stdev( NaN, 2.0 )\n","base.dists.beta.variance":"var v = base.dists.beta.variance( 1.0, 1.0 )\nv = base.dists.beta.variance( 4.0, 12.0 )\nv = base.dists.beta.variance( 8.0, 2.0 )\nv = base.dists.beta.variance( 1.0, -0.1 )\nv = base.dists.beta.variance( -0.1, 1.0 )\nv = base.dists.beta.variance( 2.0, NaN )\nv = base.dists.beta.variance( NaN, 2.0 )\n","base.dists.betaprime.BetaPrime":"var betaprime = base.dists.betaprime.BetaPrime( 6.0, 5.0 );\nbetaprime.alpha\nbetaprime.beta\nbetaprime.kurtosis\nbetaprime.mean\nbetaprime.mode\nbetaprime.skewness\nbetaprime.stdev\nbetaprime.variance\nbetaprime.cdf( 0.8 )\nbetaprime.logcdf( 0.8 )\nbetaprime.logpdf( 1.0 )\nbetaprime.pdf( 1.0 )\nbetaprime.quantile( 0.8 )\n","base.dists.betaprime.cdf":"var y = base.dists.betaprime.cdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.cdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.cdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.cdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.cdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.betaprime.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.betaprime.cdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.cdf( 0.0, NaN, 1.0 )\ny = base.dists.betaprime.cdf( 0.0, 1.0, NaN )\n","base.dists.betaprime.cdf.factory":"var mycdf = base.dists.betaprime.cdf.factory( 0.5, 0.5 );\nvar y = mycdf( 0.8 )\ny = mycdf( 0.3 )\n","base.dists.betaprime.kurtosis":"var v = base.dists.betaprime.kurtosis( 2.0, 6.0 )\nv = base.dists.betaprime.kurtosis( 4.0, 12.0 )\nv = base.dists.betaprime.kurtosis( 8.0, 6.0 )\nv = base.dists.betaprime.kurtosis( 1.0, 2.8 )\nv = base.dists.betaprime.kurtosis( 1.0, -0.1 )\nv = base.dists.betaprime.kurtosis( -0.1, 5.0 )\nv = base.dists.betaprime.kurtosis( 2.0, NaN )\nv = base.dists.betaprime.kurtosis( NaN, 6.0 )\n","base.dists.betaprime.logcdf":"var y = base.dists.betaprime.logcdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.logcdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.logcdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.logcdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.logcdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.betaprime.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.betaprime.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.betaprime.logcdf( 0.0, 1.0, NaN )\n","base.dists.betaprime.logcdf.factory":"var mylogcdf = base.dists.betaprime.logcdf.factory( 0.5, 0.5 );\nvar y = mylogcdf( 0.8 )\ny = mylogcdf( 0.3 )\n","base.dists.betaprime.logpdf":"var y = base.dists.betaprime.logpdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.logpdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.logpdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.logpdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.logpdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.logpdf( 0.5, -1.0, 0.5 )\ny = base.dists.betaprime.logpdf( 0.5, 0.5, -1.0 )\ny = base.dists.betaprime.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.logpdf( 0.5, NaN, 1.0 )\ny = base.dists.betaprime.logpdf( 0.5, 1.0, NaN )\n","base.dists.betaprime.logpdf.factory":"var mylogpdf = base.dists.betaprime.logpdf.factory( 0.5, 0.5 );\nvar y = mylogpdf( 0.8 )\ny = mylogpdf( 0.3 )\n","base.dists.betaprime.mean":"var v = base.dists.betaprime.mean( 1.0, 2.0 )\nv = base.dists.betaprime.mean( 4.0, 12.0 )\nv = base.dists.betaprime.mean( 8.0, 2.0 )\n","base.dists.betaprime.mode":"var v = base.dists.betaprime.mode( 1.0, 2.0 )\nv = base.dists.betaprime.mode( 4.0, 12.0 )\nv = base.dists.betaprime.mode( 8.0, 2.0 )\n","base.dists.betaprime.pdf":"var y = base.dists.betaprime.pdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.pdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.pdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.pdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.pdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.pdf( 0.5, -1.0, 0.5 )\ny = base.dists.betaprime.pdf( 0.5, 0.5, -1.0 )\ny = base.dists.betaprime.pdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.pdf( 0.5, NaN, 1.0 )\ny = base.dists.betaprime.pdf( 0.5, 1.0, NaN )\n","base.dists.betaprime.pdf.factory":"var mypdf = base.dists.betaprime.pdf.factory( 0.5, 0.5 );\nvar y = mypdf( 0.8 )\ny = mypdf( 0.3 )\n","base.dists.betaprime.quantile":"var y = base.dists.betaprime.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.betaprime.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.betaprime.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.betaprime.quantile( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, NaN, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, 1.0, NaN )\ny = base.dists.betaprime.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, 1.0, -1.0 )\n","base.dists.betaprime.quantile.factory":"var myQuantile = base.dists.betaprime.quantile.factory( 2.0, 2.0 );\ny = myQuantile( 0.8 )\ny = myQuantile( 0.4 )\n","base.dists.betaprime.skewness":"var v = base.dists.betaprime.skewness( 2.0, 4.0 )\nv = base.dists.betaprime.skewness( 4.0, 12.0 )\nv = base.dists.betaprime.skewness( 8.0, 4.0 )\nv = base.dists.betaprime.skewness( 1.0, 2.8 )\nv = base.dists.betaprime.skewness( 1.0, -0.1 )\nv = base.dists.betaprime.skewness( -0.1, 4.0 )\nv = base.dists.betaprime.skewness( 2.0, NaN )\nv = base.dists.betaprime.skewness( NaN, 4.0 )\n","base.dists.betaprime.stdev":"var v = base.dists.betaprime.stdev( 1.0, 2.5 )\nv = base.dists.betaprime.stdev( 4.0, 12.0 )\nv = base.dists.betaprime.stdev( 8.0, 2.5 )\nv = base.dists.betaprime.stdev( 8.0, 1.0 )\nv = base.dists.betaprime.stdev( 1.0, -0.1 )\nv = base.dists.betaprime.stdev( -0.1, 3.0 )\nv = base.dists.betaprime.stdev( 2.0, NaN )\nv = base.dists.betaprime.stdev( NaN, 3.0 )\n","base.dists.betaprime.variance":"var v = base.dists.betaprime.variance( 1.0, 2.5 )\nv = base.dists.betaprime.variance( 4.0, 12.0 )\nv = base.dists.betaprime.variance( 8.0, 2.5 )\nv = base.dists.betaprime.variance( 8.0, 1.0 )\nv = base.dists.betaprime.variance( 1.0, -0.1 )\nv = base.dists.betaprime.variance( -0.1, 3.0 )\nv = base.dists.betaprime.variance( 2.0, NaN )\nv = base.dists.betaprime.variance( NaN, 3.0 )\n","base.dists.binomial.Binomial":"var binomial = base.dists.binomial.Binomial( 8, 0.5 );\nbinomial.n\nbinomial.p\nbinomial.kurtosis\nbinomial.mean\nbinomial.median\nbinomial.mode\nbinomial.skewness\nbinomial.stdev\nbinomial.variance\nbinomial.cdf( 2.9 )\nbinomial.logpmf( 3.0 )\nbinomial.mgf( 0.2 )\nbinomial.pmf( 3.0 )\nbinomial.quantile( 0.8 )\n","base.dists.binomial.cdf":"var y = base.dists.binomial.cdf( 3.0, 20, 0.2 )\ny = base.dists.binomial.cdf( 21.0, 20, 0.2 )\ny = base.dists.binomial.cdf( 5.0, 10, 0.4 )\ny = base.dists.binomial.cdf( 0.0, 10, 0.4 )\ny = base.dists.binomial.cdf( NaN, 20, 0.5 )\ny = base.dists.binomial.cdf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.cdf( 0.0, 20, NaN )\ny = base.dists.binomial.cdf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.cdf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.cdf( 2.0, 20, -1.0 )\ny = base.dists.binomial.cdf( 2.0, 20, 1.5 )\n","base.dists.binomial.cdf.factory":"var mycdf = base.dists.binomial.cdf.factory( 10, 0.5 );\nvar y = mycdf( 3.0 )\ny = mycdf( 1.0 )\n","base.dists.binomial.entropy":"var v = base.dists.binomial.entropy( 100, 0.1 )\nv = base.dists.binomial.entropy( 20, 0.5 )\nv = base.dists.binomial.entropy( 10.3, 0.5 )\nv = base.dists.binomial.entropy( 20, 1.1 )\nv = base.dists.binomial.entropy( 20, NaN )\n","base.dists.binomial.kurtosis":"var v = base.dists.binomial.kurtosis( 100, 0.1 )\nv = base.dists.binomial.kurtosis( 20, 0.5 )\nv = base.dists.binomial.kurtosis( 10.3, 0.5 )\nv = base.dists.binomial.kurtosis( 20, 1.1 )\nv = base.dists.binomial.kurtosis( 20, NaN )\n","base.dists.binomial.logpmf":"var y = base.dists.binomial.logpmf( 3.0, 20, 0.2 )\ny = base.dists.binomial.logpmf( 21.0, 20, 0.2 )\ny = base.dists.binomial.logpmf( 5.0, 10, 0.4 )\ny = base.dists.binomial.logpmf( 0.0, 10, 0.4 )\ny = base.dists.binomial.logpmf( NaN, 20, 0.5 )\ny = base.dists.binomial.logpmf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.logpmf( 0.0, 20, NaN )\ny = base.dists.binomial.logpmf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.logpmf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.logpmf( 2.0, 20, -1.0 )\ny = base.dists.binomial.logpmf( 2.0, 20, 1.5 )\n","base.dists.binomial.logpmf.factory":"var mylogpmf = base.dists.binomial.logpmf.factory( 10, 0.5 );\nvar y = mylogpmf( 3.0 )\ny = mylogpmf( 5.0 )\n","base.dists.binomial.mean":"var v = base.dists.binomial.mean( 100, 0.1 )\nv = base.dists.binomial.mean( 20, 0.5 )\nv = base.dists.binomial.mean( 10.3, 0.5 )\nv = base.dists.binomial.mean( 20, 1.1 )\nv = base.dists.binomial.mean( 20, NaN )\n","base.dists.binomial.median":"var v = base.dists.binomial.median( 100, 0.1 )\nv = base.dists.binomial.median( 20, 0.5 )\nv = base.dists.binomial.median( 10.3, 0.5 )\nv = base.dists.binomial.median( 20, 1.1 )\nv = base.dists.binomial.median( 20, NaN )\n","base.dists.binomial.mgf":"var y = base.dists.binomial.mgf( 0.5, 20, 0.2 )\ny = base.dists.binomial.mgf( 5.0, 20, 0.2 )\ny = base.dists.binomial.mgf( 0.9, 10, 0.4 )\ny = base.dists.binomial.mgf( 0.0, 10, 0.4 )\ny = base.dists.binomial.mgf( NaN, 20, 0.5 )\ny = base.dists.binomial.mgf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.mgf( 0.0, 20, NaN )\ny = base.dists.binomial.mgf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.mgf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.mgf( 2.0, 20, -1.0 )\ny = base.dists.binomial.mgf( 2.0, 20, 1.5 )\n","base.dists.binomial.mgf.factory":"var myMGF = base.dists.binomial.mgf.factory( 10, 0.5 );\nvar y = myMGF( 0.3 )\n","base.dists.binomial.mode":"var v = base.dists.binomial.mode( 100, 0.1 )\nv = base.dists.binomial.mode( 20, 0.5 )\nv = base.dists.binomial.mode( 10.3, 0.5 )\nv = base.dists.binomial.mode( 20, 1.1 )\nv = base.dists.binomial.mode( 20, NaN )\n","base.dists.binomial.pmf":"var y = base.dists.binomial.pmf( 3.0, 20, 0.2 )\ny = base.dists.binomial.pmf( 21.0, 20, 0.2 )\ny = base.dists.binomial.pmf( 5.0, 10, 0.4 )\ny = base.dists.binomial.pmf( 0.0, 10, 0.4 )\ny = base.dists.binomial.pmf( NaN, 20, 0.5 )\ny = base.dists.binomial.pmf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.pmf( 0.0, 20, NaN )\ny = base.dists.binomial.pmf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.pmf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.pmf( 2.0, 20, -1.0 )\ny = base.dists.binomial.pmf( 2.0, 20, 1.5 )\n","base.dists.binomial.pmf.factory":"var mypmf = base.dists.binomial.pmf.factory( 10, 0.5 );\nvar y = mypmf( 3.0 )\ny = mypmf( 5.0 )\n","base.dists.binomial.quantile":"var y = base.dists.binomial.quantile( 0.4, 20, 0.2 )\ny = base.dists.binomial.quantile( 0.8, 20, 0.2 )\ny = base.dists.binomial.quantile( 0.5, 10, 0.4 )\ny = base.dists.binomial.quantile( 0.0, 10, 0.4 )\ny = base.dists.binomial.quantile( 1.0, 10, 0.4 )\ny = base.dists.binomial.quantile( NaN, 20, 0.5 )\ny = base.dists.binomial.quantile( 0.2, NaN, 0.5 )\ny = base.dists.binomial.quantile( 0.2, 20, NaN )\ny = base.dists.binomial.quantile( 0.5, 1.5, 0.5 )\ny = base.dists.binomial.quantile( 0.5, -2.0, 0.5 )\ny = base.dists.binomial.quantile( 0.5, 20, -1.0 )\ny = base.dists.binomial.quantile( 0.5, 20, 1.5 )\n","base.dists.binomial.quantile.factory":"var myquantile = base.dists.binomial.quantile.factory( 10, 0.5 );\nvar y = myquantile( 0.1 )\ny = myquantile( 0.9 )\n","base.dists.binomial.skewness":"var v = base.dists.binomial.skewness( 100, 0.1 )\nv = base.dists.binomial.skewness( 20, 0.5 )\nv = base.dists.binomial.skewness( 10.3, 0.5 )\nv = base.dists.binomial.skewness( 20, 1.1 )\nv = base.dists.binomial.skewness( 20, NaN )\n","base.dists.binomial.stdev":"var v = base.dists.binomial.stdev( 100, 0.1 )\nv = base.dists.binomial.stdev( 20, 0.5 )\nv = base.dists.binomial.stdev( 10.3, 0.5 )\nv = base.dists.binomial.stdev( 20, 1.1 )\nv = base.dists.binomial.stdev( 20, NaN )\n","base.dists.binomial.variance":"var v = base.dists.binomial.variance( 100, 0.1 )\nv = base.dists.binomial.variance( 20, 0.5 )\nv = base.dists.binomial.variance( 10.3, 0.5 )\nv = base.dists.binomial.variance( 20, 1.1 )\nv = base.dists.binomial.variance( 20, NaN )\n","base.dists.cauchy.Cauchy":"var cauchy = base.dists.cauchy.Cauchy( 0.0, 1.0 );\ncauchy.x0\ncauchy.gamma\ncauchy.entropy\ncauchy.median\ncauchy.mode\ncauchy.cdf( 0.8 )\ncauchy.logcdf( 1.0 )\ncauchy.logpdf( 1.0 )\ncauchy.pdf( 1.0 )\ncauchy.quantile( 0.8 )\n","base.dists.cauchy.cdf":"var y = base.dists.cauchy.cdf( 4.0, 0.0, 2.0 )\ny = base.dists.cauchy.cdf( 1.0, 0.0, 2.0 )\ny = base.dists.cauchy.cdf( 1.0, 3.0, 2.0 )\ny = base.dists.cauchy.cdf( NaN, 0.0, 2.0 )\ny = base.dists.cauchy.cdf( 1.0, 2.0, NaN )\ny = base.dists.cauchy.cdf( 1.0, NaN, 3.0 )\n","base.dists.cauchy.cdf.factory":"var myCDF = base.dists.cauchy.cdf.factory( 1.5, 3.0 );\nvar y = myCDF( 1.0 )\n","base.dists.cauchy.entropy":"var v = base.dists.cauchy.entropy( 10.0, 7.0 )\nv = base.dists.cauchy.entropy( 22.0, 0.5 )\nv = base.dists.cauchy.entropy( 10.3, -0.5 )\n","base.dists.cauchy.logcdf":"var y = base.dists.cauchy.logcdf( 4.0, 0.0, 2.0 )\ny = base.dists.cauchy.logcdf( 1.0, 0.0, 2.0 )\ny = base.dists.cauchy.logcdf( 1.0, 3.0, 2.0 )\ny = base.dists.cauchy.logcdf( NaN, 0.0, 2.0 )\ny = base.dists.cauchy.logcdf( 1.0, 2.0, NaN )\ny = base.dists.cauchy.logcdf( 1.0, NaN, 3.0 )\n","base.dists.cauchy.logcdf.factory":"var mylogCDF = base.dists.cauchy.logcdf.factory( 1.5, 3.0 );\nvar y = mylogCDF( 1.0 )\n","base.dists.cauchy.logpdf":"var y = base.dists.cauchy.logpdf( 2.0, 1.0, 1.0 )\ny = base.dists.cauchy.logpdf( 4.0, 3.0, 0.1 )\ny = base.dists.cauchy.logpdf( 4.0, 3.0, 3.0 )\ny = base.dists.cauchy.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.cauchy.logpdf( 2.0, NaN, 1.0 )\ny = base.dists.cauchy.logpdf( 2.0, 1.0, NaN )\ny = base.dists.cauchy.logpdf( 2.0, 1.0, -2.0 )\n","base.dists.cauchy.logpdf.factory":"var mylogPDF = base.dists.cauchy.logpdf.factory( 10.0, 2.0 );\nvar y = mylogPDF( 10.0 )\n","base.dists.cauchy.median":"var v = base.dists.cauchy.median( 10.0, 5.0 )\nv = base.dists.cauchy.median( 7.0, 0.5 )\nv = base.dists.cauchy.median( 10.3, -0.5 )\n","base.dists.cauchy.mode":"var v = base.dists.cauchy.mode( 10.0, 5.0 )\nv = base.dists.cauchy.mode( 7.0, 0.5 )\nv = base.dists.cauchy.mode( 10.3, -0.5 )\n","base.dists.cauchy.pdf":"var y = base.dists.cauchy.pdf( 2.0, 1.0, 1.0 )\ny = base.dists.cauchy.pdf( 4.0, 3.0, 0.1 )\ny = base.dists.cauchy.pdf( 4.0, 3.0, 3.0 )\ny = base.dists.cauchy.pdf( NaN, 1.0, 1.0 )\ny = base.dists.cauchy.pdf( 2.0, NaN, 1.0 )\ny = base.dists.cauchy.pdf( 2.0, 1.0, NaN )\ny = base.dists.cauchy.pdf( 2.0, 1.0, -2.0 )\n","base.dists.cauchy.pdf.factory":"var myPDF = base.dists.cauchy.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\n","base.dists.cauchy.quantile":"var y = base.dists.cauchy.quantile( 0.3, 2.0, 2.0 )\ny = base.dists.cauchy.quantile( 0.8, 10, 2.0 )\ny = base.dists.cauchy.quantile( 0.1, 10.0, 2.0 )\ny = base.dists.cauchy.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.cauchy.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.cauchy.quantile( NaN, 0.0, 1.0 )\ny = base.dists.cauchy.quantile( 0.0, NaN, 1.0 )\ny = base.dists.cauchy.quantile( 0.0, 0.0, NaN )\ny = base.dists.cauchy.quantile( 0.5, 0.0, -1.0 )\n","base.dists.cauchy.quantile.factory":"var myQuantile = base.dists.cauchy.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.chi.cdf":"var y = base.dists.chi.cdf( 2.0, 3.0 )\ny = base.dists.chi.cdf( 1.0, 0.5 )\ny = base.dists.chi.cdf( -1.0, 4.0 )\ny = base.dists.chi.cdf( NaN, 1.0 )\ny = base.dists.chi.cdf( 0.0, NaN )\ny = base.dists.chi.cdf( 2.0, -1.0 )\ny = base.dists.chi.cdf( 2.0, 0.0 )\ny = base.dists.chi.cdf( -2.0, 0.0 )\ny = base.dists.chi.cdf( 0.0, 0.0 )\n","base.dists.chi.cdf.factory":"var mycdf = base.dists.chi.cdf.factory( 1.0 );\nvar y = mycdf( 2.0 )\ny = mycdf( 1.2 )\n","base.dists.chi.Chi":"var chi = base.dists.chi.Chi( 6.0 );\nchi.k\nchi.entropy\nchi.kurtosis\nchi.mean\nchi.mode\nchi.skewness\nchi.stdev\nchi.variance\nchi.cdf( 1.0 )\nchi.logpdf( 1.5 )\nchi.pdf( 1.5 )\nchi.quantile( 0.5 )\n","base.dists.chi.entropy":"var v = base.dists.chi.entropy( 11.0 )\nv = base.dists.chi.entropy( 1.5 )\n","base.dists.chi.kurtosis":"var v = base.dists.chi.kurtosis( 9.0 )\nv = base.dists.chi.kurtosis( 1.5 )\n","base.dists.chi.logpdf":"var y = base.dists.chi.logpdf( 0.3, 4.0 )\ny = base.dists.chi.logpdf( 0.7, 0.7 )\ny = base.dists.chi.logpdf( -1.0, 0.5 )\ny = base.dists.chi.logpdf( 0.0, NaN )\ny = base.dists.chi.logpdf( NaN, 2.0 )\ny = base.dists.chi.logpdf( 2.0, -1.0 )\ny = base.dists.chi.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.chi.logpdf( 0.0, 0.0, 2.0 )\n","base.dists.chi.logpdf.factory":"var mylogPDF = base.dists.chi.logpdf.factory( 6.0 );\nvar y = mylogPDF( 3.0 )\n","base.dists.chi.mean":"var v = base.dists.chi.mean( 11.0 )\nv = base.dists.chi.mean( 4.5 )\n","base.dists.chi.mode":"var v = base.dists.chi.mode( 11.0 )\nv = base.dists.chi.mode( 1.5 )\n","base.dists.chi.pdf":"var y = base.dists.chi.pdf( 0.3, 4.0 )\ny = base.dists.chi.pdf( 0.7, 0.7 )\ny = base.dists.chi.pdf( -1.0, 0.5 )\ny = base.dists.chi.pdf( 0.0, NaN )\ny = base.dists.chi.pdf( NaN, 2.0 )\ny = base.dists.chi.pdf( 2.0, -1.0 )\ny = base.dists.chi.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.chi.pdf( 0.0, 0.0, 2.0 )\n","base.dists.chi.pdf.factory":"var myPDF = base.dists.chi.pdf.factory( 6.0 );\nvar y = myPDF( 3.0 )\n","base.dists.chi.quantile":"var y = base.dists.chi.quantile( 0.8, 1.0 )\ny = base.dists.chi.quantile( 0.5, 4.0 )\ny = base.dists.chi.quantile( 0.8, 0.1 )\ny = base.dists.chi.quantile( -0.2, 0.5 )\ny = base.dists.chi.quantile( 1.1, 0.5 )\ny = base.dists.chi.quantile( NaN, 1.0 )\ny = base.dists.chi.quantile( 0.0, NaN )\ny = base.dists.chi.quantile( 0.5, -1.0 )\ny = base.dists.chi.quantile( 0.3, 0.0 )\ny = base.dists.chi.quantile( 0.9, 0.0 )\n","base.dists.chi.quantile.factory":"var myquantile = base.dists.chi.quantile.factory( 2.0 );\nvar y = myquantile( 0.3 )\ny = myquantile( 0.7 )\n","base.dists.chi.skewness":"var v = base.dists.chi.skewness( 11.0 )\nv = base.dists.chi.skewness( 1.5 )\n","base.dists.chi.stdev":"var v = base.dists.chi.stdev( 11.0 )\nv = base.dists.chi.stdev( 1.5 )\n","base.dists.chi.variance":"var v = base.dists.chi.variance( 11.0 )\nv = base.dists.chi.variance( 1.5 )\n","base.dists.chisquare.cdf":"var y = base.dists.chisquare.cdf( 2.0, 3.0 )\ny = base.dists.chisquare.cdf( 1.0, 0.5 )\ny = base.dists.chisquare.cdf( -1.0, 4.0 )\ny = base.dists.chisquare.cdf( NaN, 1.0 )\ny = base.dists.chisquare.cdf( 0.0, NaN )\ny = base.dists.chisquare.cdf( 2.0, -1.0 )\ny = base.dists.chisquare.cdf( 2.0, 0.0 )\ny = base.dists.chisquare.cdf( -2.0, 0.0 )\ny = base.dists.chisquare.cdf( 0.0, 0.0 )\n","base.dists.chisquare.cdf.factory":"var mycdf = base.dists.chisquare.cdf.factory( 1.0 );\nvar y = mycdf( 2.0 )\ny = mycdf( 1.2 )\n","base.dists.chisquare.ChiSquare":"var chisquare = base.dists.chisquare.ChiSquare( 6.0 );\nchisquare.k\nchisquare.entropy\nchisquare.kurtosis\nchisquare.mean\nchisquare.median\nchisquare.mode\nchisquare.skewness\nchisquare.stdev\nchisquare.variance\nchisquare.cdf( 3.0 )\nchisquare.mgf( 0.2 )\nchisquare.pdf( 1.5 )\nchisquare.quantile( 0.5 )\n","base.dists.chisquare.entropy":"var v = base.dists.chisquare.entropy( 11.0 )\nv = base.dists.chisquare.entropy( 1.5 )\n","base.dists.chisquare.kurtosis":"var v = base.dists.chisquare.kurtosis( 9.0 )\nv = base.dists.chisquare.kurtosis( 1.5 )\n","base.dists.chisquare.logpdf":"var y = base.dists.chisquare.logpdf( 0.3, 4.0 )\ny = base.dists.chisquare.logpdf( 0.7, 0.7 )\ny = base.dists.chisquare.logpdf( -1.0, 0.5 )\ny = base.dists.chisquare.logpdf( 0.0, NaN )\ny = base.dists.chisquare.logpdf( NaN, 2.0 )\ny = base.dists.chisquare.logpdf( 2.0, -1.0 )\ny = base.dists.chisquare.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.chisquare.logpdf( 0.0, 0.0, 2.0 )\n","base.dists.chisquare.logpdf.factory":"var myLogPDF = base.dists.chisquare.logpdf.factory( 6.0 );\nvar y = myLogPDF( 3.0 )\n","base.dists.chisquare.mean":"var v = base.dists.chisquare.mean( 11.0 )\nv = base.dists.chisquare.mean( 4.5 )\n","base.dists.chisquare.median":"var k = base.dists.chisquare.median( 9.0 )\nk = base.dists.chisquare.median( 2.0 )\n","base.dists.chisquare.mgf":"var y = base.dists.chisquare.mgf( 0.4, 2 )\ny = base.dists.chisquare.mgf( -1.0, 5.0 )\ny = base.dists.chisquare.mgf( 0.0, 10.0 )\n","base.dists.chisquare.mgf.factory":"var mymgf = base.dists.chisquare.mgf.factory( 1.0 );\nvar y = mymgf( 0.2 )\ny = mymgf( 0.4 )\n","base.dists.chisquare.mode":"var v = base.dists.chisquare.mode( 11.0 )\nv = base.dists.chisquare.mode( 1.5 )\n","base.dists.chisquare.pdf":"var y = base.dists.chisquare.pdf( 0.3, 4.0 )\ny = base.dists.chisquare.pdf( 0.7, 0.7 )\ny = base.dists.chisquare.pdf( -1.0, 0.5 )\ny = base.dists.chisquare.pdf( 0.0, NaN )\ny = base.dists.chisquare.pdf( NaN, 2.0 )\ny = base.dists.chisquare.pdf( 2.0, -1.0 )\ny = base.dists.chisquare.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.chisquare.pdf( 0.0, 0.0, 2.0 )\n","base.dists.chisquare.pdf.factory":"var myPDF = base.dists.chisquare.pdf.factory( 6.0 );\nvar y = myPDF( 3.0 )\n","base.dists.chisquare.quantile":"var y = base.dists.chisquare.quantile( 0.8, 1.0 )\ny = base.dists.chisquare.quantile( 0.5, 4.0 )\ny = base.dists.chisquare.quantile( 0.8, 0.1 )\ny = base.dists.chisquare.quantile( -0.2, 0.5 )\ny = base.dists.chisquare.quantile( 1.1, 0.5 )\ny = base.dists.chisquare.quantile( NaN, 1.0 )\ny = base.dists.chisquare.quantile( 0.0, NaN )\ny = base.dists.chisquare.quantile( 0.5, -1.0 )\ny = base.dists.chisquare.quantile( 0.3, 0.0 )\ny = base.dists.chisquare.quantile( 0.9, 0.0 )\n","base.dists.chisquare.quantile.factory":"var myquantile = base.dists.chisquare.quantile.factory( 2.0 );\nvar y = myquantile( 0.3 )\ny = myquantile( 0.7 )\n","base.dists.chisquare.skewness":"var v = base.dists.chisquare.skewness( 11.0 )\nv = base.dists.chisquare.skewness( 1.5 )\n","base.dists.chisquare.stdev":"var v = base.dists.chisquare.stdev( 11.0 )\nv = base.dists.chisquare.stdev( 1.5 )\n","base.dists.chisquare.variance":"var v = base.dists.chisquare.variance( 11.0 )\nv = base.dists.chisquare.variance( 1.5 )\n","base.dists.cosine.cdf":"var y = base.dists.cosine.cdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.cdf( 9.0, 10.0, 3.0 )\ny = base.dists.cosine.cdf( 2.0, 0.0, NaN )\ny = base.dists.cosine.cdf( 2.0, NaN, 1.0 )\ny = base.dists.cosine.cdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.cdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.cdf( 8.0, 8.0, 0.0 )\ny = base.dists.cosine.cdf( 10.0, 8.0, 0.0 )\n","base.dists.cosine.cdf.factory":"var mycdf = base.dists.cosine.cdf.factory( 3.0, 1.5 );\nvar y = mycdf( 1.9 )\n","base.dists.cosine.Cosine":"var cosine = base.dists.cosine.Cosine( -2.0, 3.0 );\ncosine.mu\ncosine.s\ncosine.kurtosis\ncosine.mean\ncosine.median\ncosine.mode\ncosine.skewness\ncosine.stdev\ncosine.variance\ncosine.cdf( 0.5 )\ncosine.logcdf( 0.5 )\ncosine.logpdf( -1.0 )\ncosine.mgf( 0.2 )\ncosine.pdf( -2.0 )\ncosine.quantile( 0.9 )\n","base.dists.cosine.kurtosis":"var y = base.dists.cosine.kurtosis( 0.0, 1.0 )\ny = base.dists.cosine.kurtosis( 4.0, 2.0 )\ny = base.dists.cosine.kurtosis( NaN, 1.0 )\ny = base.dists.cosine.kurtosis( 0.0, NaN )\ny = base.dists.cosine.kurtosis( 0.0, 0.0 )\n","base.dists.cosine.logcdf":"var y = base.dists.cosine.logcdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.logcdf( 9.0, 10.0, 3.0 )\ny = base.dists.cosine.logcdf( 2.0, 0.0, NaN )\ny = base.dists.cosine.logcdf( 2.0, NaN, 1.0 )\ny = base.dists.cosine.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.logcdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.logcdf( 8.0, 8.0, 0.0 )\ny = base.dists.cosine.logcdf( 10.0, 8.0, 0.0 )\n","base.dists.cosine.logcdf.factory":"var mylogcdf = base.dists.cosine.logcdf.factory( 3.0, 1.5 );\nvar y = mylogcdf( 1.9 )\n","base.dists.cosine.logpdf":"var y = base.dists.cosine.logpdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.logpdf( -1.0, 2.0, 4.0 )\ny = base.dists.cosine.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.cosine.logpdf( 0.0, 0.0, NaN )\ny = base.dists.cosine.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.cosine.logpdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.logpdf( 8.0, 8.0, 0.0 )\n","base.dists.cosine.logpdf.factory":"var mylogpdf = base.dists.cosine.logpdf.factory( 10.0, 2.0 );\nvar y = mylogpdf( 10.0 )\n","base.dists.cosine.mean":"var y = base.dists.cosine.mean( 0.0, 1.0 )\ny = base.dists.cosine.mean( 4.0, 2.0 )\ny = base.dists.cosine.mean( NaN, 1.0 )\ny = base.dists.cosine.mean( 0.0, NaN )\ny = base.dists.cosine.mean( 0.0, 0.0 )\n","base.dists.cosine.median":"var y = base.dists.cosine.median( 0.0, 1.0 )\ny = base.dists.cosine.median( 4.0, 2.0 )\ny = base.dists.cosine.median( NaN, 1.0 )\ny = base.dists.cosine.median( 0.0, NaN )\ny = base.dists.cosine.median( 0.0, 0.0 )\n","base.dists.cosine.mgf":"var y = base.dists.cosine.mgf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.mgf( 9.0, 10.0, 3.0 )\ny = base.dists.cosine.mgf( 0.5, 0.0, NaN )\ny = base.dists.cosine.mgf( 0.5, NaN, 1.0 )\ny = base.dists.cosine.mgf( NaN, 0.0, 1.0 )\n","base.dists.cosine.mgf.factory":"var mymgf = base.dists.cosine.mgf.factory( 3.0, 1.5 );\nvar y = mymgf( 1.9 )\n","base.dists.cosine.mode":"var y = base.dists.cosine.mode( 0.0, 1.0 )\ny = base.dists.cosine.mode( 4.0, 2.0 )\ny = base.dists.cosine.mode( NaN, 1.0 )\ny = base.dists.cosine.mode( 0.0, NaN )\ny = base.dists.cosine.mode( 0.0, 0.0 )\n","base.dists.cosine.pdf":"var y = base.dists.cosine.pdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.pdf( 2.4, 4.0, 2.0 )\ny = base.dists.cosine.pdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.pdf( 0.0, NaN, 1.0 )\ny = base.dists.cosine.pdf( 0.0, 0.0, NaN )\ny = base.dists.cosine.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.cosine.pdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.pdf( 8.0, 8.0, 0.0 )\n","base.dists.cosine.pdf.factory":"var myPDF = base.dists.cosine.pdf.factory( 0.0, 3.0 );\nvar y = myPDF( 2.0 )\n","base.dists.cosine.quantile":"var y = base.dists.cosine.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.cosine.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.cosine.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.cosine.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.cosine.quantile( NaN, 0.0, 1.0 )\ny = base.dists.cosine.quantile( 0.0, NaN, 1.0 )\ny = base.dists.cosine.quantile( 0.0, 0.0, NaN )\ny = base.dists.cosine.quantile( 0.5, 0.0, -1.0 )\n","base.dists.cosine.quantile.factory":"var myQuantile = base.dists.cosine.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.3 )\n","base.dists.cosine.skewness":"var y = base.dists.cosine.skewness( 0.0, 1.0 )\ny = base.dists.cosine.skewness( 4.0, 2.0 )\ny = base.dists.cosine.skewness( NaN, 1.0 )\ny = base.dists.cosine.skewness( 0.0, NaN )\ny = base.dists.cosine.skewness( 0.0, 0.0 )\n","base.dists.cosine.stdev":"var y = base.dists.cosine.stdev( 0.0, 1.0 )\ny = base.dists.cosine.stdev( 4.0, 2.0 )\ny = base.dists.cosine.stdev( NaN, 1.0 )\ny = base.dists.cosine.stdev( 0.0, NaN )\ny = base.dists.cosine.stdev( 0.0, 0.0 )\n","base.dists.cosine.variance":"var y = base.dists.cosine.variance( 0.0, 1.0 )\ny = base.dists.cosine.variance( 4.0, 2.0 )\ny = base.dists.cosine.variance( NaN, 1.0 )\ny = base.dists.cosine.variance( 0.0, NaN )\ny = base.dists.cosine.variance( 0.0, 0.0 )\n","base.dists.degenerate.cdf":"var y = base.dists.degenerate.cdf( 2.0, 3.0 )\ny = base.dists.degenerate.cdf( 4.0, 3.0 )\ny = base.dists.degenerate.cdf( 3.0, 3.0 )\ny = base.dists.degenerate.cdf( NaN, 0.0 )\ny = base.dists.degenerate.cdf( 0.0, NaN )\n","base.dists.degenerate.cdf.factory":"var myCDF = base.dists.degenerate.cdf.factory( 5.0 );\nvar y = myCDF( 3.0 )\ny = myCDF( 6.0 )\n","base.dists.degenerate.Degenerate":"var degenerate = base.dists.degenerate.Degenerate( 2.0 );\ndegenerate.mu\ndegenerate.entropy\ndegenerate.mean\ndegenerate.mode\ndegenerate.median\ndegenerate.stdev\ndegenerate.variance\ndegenerate.cdf( 0.5 )\ndegenerate.logcdf( 2.5 )\ndegenerate.logpdf( 0.5 )\ndegenerate.logpmf( 2.5 )\ndegenerate.mgf( 0.2 )\ndegenerate.pdf( 2.0 )\ndegenerate.pmf( 2.0 )\ndegenerate.quantile( 0.7 )\n","base.dists.degenerate.entropy":"var v = base.dists.degenerate.entropy( 20.0 )\nv = base.dists.degenerate.entropy( -10.0 )\n","base.dists.degenerate.logcdf":"var y = base.dists.degenerate.logcdf( 2.0, 3.0 )\ny = base.dists.degenerate.logcdf( 4.0, 3.0 )\ny = base.dists.degenerate.logcdf( 3.0, 3.0 )\ny = base.dists.degenerate.logcdf( NaN, 0.0 )\ny = base.dists.degenerate.logcdf( 0.0, NaN )\n","base.dists.degenerate.logcdf.factory":"var mylogcdf = base.dists.degenerate.logcdf.factory( 5.0 );\nvar y = mylogcdf( 3.0 )\ny = mylogcdf( 6.0 )\n","base.dists.degenerate.logpdf":"var y = base.dists.degenerate.logpdf( 2.0, 3.0 )\ny = base.dists.degenerate.logpdf( 3.0, 3.0 )\ny = base.dists.degenerate.logpdf( NaN, 0.0 )\ny = base.dists.degenerate.logpdf( 0.0, NaN )\n","base.dists.degenerate.logpdf.factory":"var mylogPDF = base.dists.degenerate.logpdf.factory( 10.0 );\nvar y = mylogPDF( 10.0 )\n","base.dists.degenerate.logpmf":"var y = base.dists.degenerate.logpmf( 2.0, 3.0 )\ny = base.dists.degenerate.logpmf( 3.0, 3.0 )\ny = base.dists.degenerate.logpmf( NaN, 0.0 )\ny = base.dists.degenerate.logpmf( 0.0, NaN )\n","base.dists.degenerate.logpmf.factory":"var mylogPMF = base.dists.degenerate.logpmf.factory( 10.0 );\nvar y = mylogPMF( 10.0 )\n","base.dists.degenerate.mean":"var v = base.dists.degenerate.mean( 20.0 )\nv = base.dists.degenerate.mean( -10.0 )\n","base.dists.degenerate.median":"var v = base.dists.degenerate.median( 20.0 )\nv = base.dists.degenerate.median( -10.0 )\n","base.dists.degenerate.mgf":"var y = base.dists.degenerate.mgf( 1.0, 1.0 )\ny = base.dists.degenerate.mgf( 2.0, 3.0 )\ny = base.dists.degenerate.mgf( NaN, 0.0 )\ny = base.dists.degenerate.mgf( 0.0, NaN )\n","base.dists.degenerate.mgf.factory":"var myMGF = base.dists.degenerate.mgf.factory( 10.0 );\nvar y = myMGF( 0.1 )\n","base.dists.degenerate.mode":"var v = base.dists.degenerate.mode( 20.0 )\nv = base.dists.degenerate.mode( -10.0 )\n","base.dists.degenerate.pdf":"var y = base.dists.degenerate.pdf( 2.0, 3.0 )\ny = base.dists.degenerate.pdf( 3.0, 3.0 )\ny = base.dists.degenerate.pdf( NaN, 0.0 )\ny = base.dists.degenerate.pdf( 0.0, NaN )\n","base.dists.degenerate.pdf.factory":"var myPDF = base.dists.degenerate.pdf.factory( 10.0 );\nvar y = myPDF( 10.0 )\n","base.dists.degenerate.pmf":"var y = base.dists.degenerate.pmf( 2.0, 3.0 )\ny = base.dists.degenerate.pmf( 3.0, 3.0 )\ny = base.dists.degenerate.pmf( NaN, 0.0 )\ny = base.dists.degenerate.pmf( 0.0, NaN )\n","base.dists.degenerate.pmf.factory":"var myPMF = base.dists.degenerate.pmf.factory( 10.0 );\nvar y = myPMF( 10.0 )\n","base.dists.degenerate.quantile":"var y = base.dists.degenerate.quantile( 0.5, 2.0 )\ny = base.dists.degenerate.quantile( 0.9, 4.0 )\ny = base.dists.degenerate.quantile( 1.1, 0.0 )\ny = base.dists.degenerate.quantile( -0.2, 0.0 )\ny = base.dists.degenerate.quantile( NaN, 0.0 )\ny = base.dists.degenerate.quantile( 0.0, NaN )\n","base.dists.degenerate.quantile.factory":"var myQuantile = base.dists.degenerate.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.degenerate.stdev":"var v = base.dists.degenerate.stdev( 20.0 )\nv = base.dists.degenerate.stdev( -10.0 )\n","base.dists.degenerate.variance":"var v = base.dists.degenerate.variance( 20.0 )\nv = base.dists.degenerate.variance( -10.0 )\n","base.dists.discreteUniform.cdf":"var y = base.dists.discreteUniform.cdf( 9.0, 0, 10 )\ny = base.dists.discreteUniform.cdf( 0.5, 0, 2 )\ny = base.dists.discreteUniform.cdf( PINF, 2, 4 )\ny = base.dists.discreteUniform.cdf( NINF, 2, 4 )\ny = base.dists.discreteUniform.cdf( NaN, 0, 1 )\ny = base.dists.discreteUniform.cdf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.cdf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.cdf( 2.0, 1, 0 )\n","base.dists.discreteUniform.cdf.factory":"var mycdf = base.dists.discreteUniform.cdf.factory( 0, 10 );\nvar y = mycdf( 0.5 )\ny = mycdf( 8.0 )\n","base.dists.discreteUniform.DiscreteUniform":"var discreteUniform = base.dists.discreteUniform.DiscreteUniform( -2, 2 );\ndiscreteUniform.a\ndiscreteUniform.b\ndiscreteUniform.entropy\ndiscreteUniform.kurtosis\ndiscreteUniform.mean\ndiscreteUniform.median\ndiscreteUniform.skewness\ndiscreteUniform.stdev\ndiscreteUniform.variance\ndiscreteUniform.cdf( 0.8 )\ndiscreteUniform.logcdf( 0.5 )\ndiscreteUniform.logpmf( 1.0 )\ndiscreteUniform.mgf( 0.8 )\ndiscreteUniform.pmf( 0.0 )\ndiscreteUniform.quantile( 0.8 )\n","base.dists.discreteUniform.entropy":"var v = base.dists.discreteUniform.entropy( 0, 1 )\nv = base.dists.discreteUniform.entropy( 4, 12 )\nv = base.dists.discreteUniform.entropy( 2, 8 )\n","base.dists.discreteUniform.kurtosis":"var v = base.dists.discreteUniform.kurtosis( 0, 1 )\nv = base.dists.discreteUniform.kurtosis( 4, 12 )\nv = base.dists.discreteUniform.kurtosis( -4, 8 )\n","base.dists.discreteUniform.logcdf":"var y = base.dists.discreteUniform.logcdf( 9.0, 0, 10 )\ny = base.dists.discreteUniform.logcdf( 0.5, 0, 2 )\ny = base.dists.discreteUniform.logcdf( PINF, 2, 4 )\ny = base.dists.discreteUniform.logcdf( NINF, 2, 4 )\ny = base.dists.discreteUniform.logcdf( NaN, 0, 1 )\ny = base.dists.discreteUniform.logcdf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.logcdf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.logcdf( 2.0, 1, 0 )\n","base.dists.discreteUniform.logcdf.factory":"var myLogCDF = base.dists.discreteUniform.logcdf.factory( 0, 10 );\nvar y = myLogCDF( 0.5 )\ny = myLogCDF( 8.0 )\n","base.dists.discreteUniform.logpmf":"var y = base.dists.discreteUniform.logpmf( 2.0, 0, 4 )\ny = base.dists.discreteUniform.logpmf( 5.0, 0, 4 )\ny = base.dists.discreteUniform.logpmf( 3.0, -4, 4 )\ny = base.dists.discreteUniform.logpmf( NaN, 0, 1 )\ny = base.dists.discreteUniform.logpmf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.logpmf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.logpmf( 2.0, 3, 1 )\ny = base.dists.discreteUniform.logpmf( 2.0, 1, 2.4 )\n","base.dists.discreteUniform.logpmf.factory":"var myLogPMF = base.dists.discreteUniform.logpmf.factory( 6, 7 );\nvar y = myLogPMF( 7.0 )\ny = myLogPMF( 5.0 )\n","base.dists.discreteUniform.mean":"var v = base.dists.discreteUniform.mean( -2, 2 )\nv = base.dists.discreteUniform.mean( 4, 12 )\nv = base.dists.discreteUniform.mean( 2, 8 )\n","base.dists.discreteUniform.median":"var v = base.dists.discreteUniform.median( -2, 2 )\nv = base.dists.discreteUniform.median( 4, 12 )\nv = base.dists.discreteUniform.median( 2, 8 )\n","base.dists.discreteUniform.mgf":"var y = base.dists.discreteUniform.mgf( 2.0, 0, 4 )\ny = base.dists.discreteUniform.mgf( -0.2, 0, 4 )\ny = base.dists.discreteUniform.mgf( 2.0, 0, 1 )\ny = base.dists.discreteUniform.mgf( 0.5, 3, 2 )\ny = base.dists.discreteUniform.mgf( NaN, 0, 1  )\ny = base.dists.discreteUniform.mgf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.mgf( 0.0, 0, NaN )\n","base.dists.discreteUniform.mgf.factory":"var mymgf = base.dists.discreteUniform.mgf.factory( 6, 7 );\nvar y = mymgf( 0.1 )\ny = mymgf( 1.1 )\n","base.dists.discreteUniform.pmf":"var y = base.dists.discreteUniform.pmf( 2.0, 0, 4 )\ny = base.dists.discreteUniform.pmf( 5.0, 0, 4 )\ny = base.dists.discreteUniform.pmf( 3.0, -4, 4 )\ny = base.dists.discreteUniform.pmf( NaN, 0, 1 )\ny = base.dists.discreteUniform.pmf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.pmf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.pmf( 2.0, 3, 1 )\ny = base.dists.discreteUniform.pmf( 2.0, 1, 2.4 )\n","base.dists.discreteUniform.pmf.factory":"var myPMF = base.dists.discreteUniform.pmf.factory( 6, 7 );\nvar y = myPMF( 7.0 )\ny = myPMF( 5.0 )\n","base.dists.discreteUniform.quantile":"var y = base.dists.discreteUniform.quantile( 0.8, 0, 1 )\ny = base.dists.discreteUniform.quantile( 0.5, 0.0, 10.0 )\ny = base.dists.discreteUniform.quantile( 1.1, 0, 4 )\ny = base.dists.discreteUniform.quantile( -0.2, 0, 4 )\ny = base.dists.discreteUniform.quantile( NaN, -2, 2 )\ny = base.dists.discreteUniform.quantile( 0.1, NaN, 2 )\ny = base.dists.discreteUniform.quantile( 0.1, -2, NaN )\ny = base.dists.discreteUniform.quantile( 0.5, 2, 1 )\n","base.dists.discreteUniform.quantile.factory":"var myQuantile = base.dists.discreteUniform.quantile.factory( 0, 4 );\nvar y = myQuantile( 0.8 )\n","base.dists.discreteUniform.skewness":"var v = base.dists.discreteUniform.skewness( -2, 2 )\nv = base.dists.discreteUniform.skewness( 4, 12 )\nv = base.dists.discreteUniform.skewness( 2, 8 )\n","base.dists.discreteUniform.stdev":"var v = base.dists.discreteUniform.stdev( 0, 1 )\nv = base.dists.discreteUniform.stdev( 4, 12 )\nv = base.dists.discreteUniform.stdev( 2, 8 )\n","base.dists.discreteUniform.variance":"var v = base.dists.discreteUniform.variance( 0, 1 )\nv = base.dists.discreteUniform.variance( 4, 12 )\nv = base.dists.discreteUniform.variance( 2, 8 )\n","base.dists.erlang.cdf":"var y = base.dists.erlang.cdf( 2.0, 1, 1.0 )\ny = base.dists.erlang.cdf( 2.0, 3, 1.0 )\ny = base.dists.erlang.cdf( 2.0, 2.5, 1.0 )\ny = base.dists.erlang.cdf( -1.0, 2, 2.0 )\ny = base.dists.erlang.cdf( PINF, 4, 2.0 )\ny = base.dists.erlang.cdf( NINF, 4, 2.0 )\ny = base.dists.erlang.cdf( NaN, 0, 1.0 )\ny = base.dists.erlang.cdf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.cdf( 0.0, 0, NaN )\ny = base.dists.erlang.cdf( 2.0, -1, 1.0 )\ny = base.dists.erlang.cdf( 2.0, 1, -1.0 )\n","base.dists.erlang.cdf.factory":"var mycdf = base.dists.erlang.cdf.factory( 2, 0.5 );\nvar y = mycdf( 6.0 )\ny = mycdf( 2.0 )\n","base.dists.erlang.entropy":"var v = base.dists.erlang.entropy( 1, 1.0 )\nv = base.dists.erlang.entropy( 4, 12.0 )\nv = base.dists.erlang.entropy( 8, 2.0 )\n","base.dists.erlang.Erlang":"var erlang = base.dists.erlang.Erlang( 6, 5.0 );\nerlang.k\nerlang.lambda\nerlang.entropy\nerlang.kurtosis\nerlang.mean\nerlang.mode\nerlang.skewness\nerlang.stdev\nerlang.variance\nerlang.cdf( 3.0 )\nerlang.logpdf( 3.0 )\nerlang.mgf( -0.5 )\nerlang.pdf( 3.0 )\nerlang.quantile( 0.8 )\n","base.dists.erlang.kurtosis":"var v = base.dists.erlang.kurtosis( 1, 1.0 )\nv = base.dists.erlang.kurtosis( 4, 12.0 )\nv = base.dists.erlang.kurtosis( 8, 2.0 )\n","base.dists.erlang.logpdf":"var y = base.dists.erlang.logpdf( 0.1, 1, 1.0 )\ny = base.dists.erlang.logpdf( 0.5, 2, 2.5 )\ny = base.dists.erlang.logpdf( -1.0, 4, 2.0 )\ny = base.dists.erlang.logpdf( NaN, 1, 1.0 )\ny = base.dists.erlang.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.logpdf( 0.0, 1, NaN )\ny = base.dists.erlang.logpdf( 2.0, -2, 0.5 )\ny = base.dists.erlang.logpdf( 2.0, 0.5, 0.5 )\ny = base.dists.erlang.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.erlang.logpdf( 0.0, 0.0, 2.0 )\ny = base.dists.erlang.logpdf( 2.0, 1, 0.0 )\ny = base.dists.erlang.logpdf( 2.0, 1, -1.0 )\n","base.dists.erlang.logpdf.factory":"var myLogPDF = base.dists.erlang.logpdf.factory( 6.0, 7.0 );\ny = myLogPDF( 7.0 )\n","base.dists.erlang.mean":"var v = base.dists.erlang.mean( 1, 1.0 )\nv = base.dists.erlang.mean( 4, 12.0 )\nv = base.dists.erlang.mean( 8, 2.0 )\n","base.dists.erlang.mgf":"var y = base.dists.erlang.mgf( 0.3, 1, 1.0 )\ny = base.dists.erlang.mgf( 2.0, 2, 3.0 )\ny = base.dists.erlang.mgf( -1.0, 2, 2.0 )\ny = base.dists.erlang.mgf( NaN, 1, 1.0 )\ny = base.dists.erlang.mgf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.mgf( 0.0, 1, NaN )\ny = base.dists.erlang.mgf( 0.2, -2, 0.5 )\ny = base.dists.erlang.mgf( 0.2, 0.5, 0.5 )\ny = base.dists.erlang.mgf( 0.2, 1, 0.0 )\ny = base.dists.erlang.mgf( 0.2, 1, -5.0 )\n","base.dists.erlang.mgf.factory":"var myMGF = base.dists.erlang.mgf.factory( 2, 0.5 );\nvar y = myMGF( 0.2 )\ny = myMGF( -0.5 )\n","base.dists.erlang.mode":"var v = base.dists.erlang.mode( 1, 1.0 )\nv = base.dists.erlang.mode( 4, 12.0 )\nv = base.dists.erlang.mode( 8, 2.0 )\n","base.dists.erlang.pdf":"var y = base.dists.erlang.pdf( 0.1, 1, 1.0 )\ny = base.dists.erlang.pdf( 0.5, 2, 2.5 )\ny = base.dists.erlang.pdf( -1.0, 4, 2.0 )\ny = base.dists.erlang.pdf( NaN, 1, 1.0 )\ny = base.dists.erlang.pdf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.pdf( 0.0, 1, NaN )\ny = base.dists.erlang.pdf( 2.0, -2, 0.5 )\ny = base.dists.erlang.pdf( 2.0, 0.5, 0.5 )\ny = base.dists.erlang.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.erlang.pdf( 0.0, 0.0, 2.0 )\ny = base.dists.erlang.pdf( 2.0, 1, 0.0 )\ny = base.dists.erlang.pdf( 2.0, 1, -1.0 )\n","base.dists.erlang.pdf.factory":"var myPDF = base.dists.erlang.pdf.factory( 6.0, 7.0 );\ny = myPDF( 7.0 )\n","base.dists.erlang.quantile":"var y = base.dists.erlang.quantile( 0.8, 2, 1.0 )\ny = base.dists.erlang.quantile( 0.5, 4, 2.0 )\ny = base.dists.erlang.quantile( 1.1, 1, 1.0 )\ny = base.dists.erlang.quantile( -0.2, 1, 1.0 )\ny = base.dists.erlang.quantile( NaN, 1, 1.0 )\ny = base.dists.erlang.quantile( 0.0, NaN, 1.0 )\ny = base.dists.erlang.quantile( 0.0, 1, NaN )\ny = base.dists.erlang.quantile( 0.5, 0.5, 1.0 )\ny = base.dists.erlang.quantile( 0.5, -1, 1.0 )\ny = base.dists.erlang.quantile( 0.5, 1, -1.0 )\n","base.dists.erlang.quantile.factory":"var myQuantile = base.dists.erlang.quantile.factory( 10, 2.0 );\nvar y = myQuantile( 0.4 )\n","base.dists.erlang.skewness":"var v = base.dists.erlang.skewness( 1, 1.0 )\nv = base.dists.erlang.skewness( 4, 12.0 )\nv = base.dists.erlang.skewness( 8, 2.0 )\n","base.dists.erlang.stdev":"var v = base.dists.erlang.stdev( 1, 1.0 )\nv = base.dists.erlang.stdev( 4, 12.0 )\nv = base.dists.erlang.stdev( 8, 2.0 )\n","base.dists.erlang.variance":"var v = base.dists.erlang.variance( 1, 1.0 )\nv = base.dists.erlang.variance( 4, 12.0 )\nv = base.dists.erlang.variance( 8, 2.0 )\n","base.dists.exponential.cdf":"var y = base.dists.exponential.cdf( 2.0, 0.1 )\ny = base.dists.exponential.cdf( 1.0, 2.0 )\ny = base.dists.exponential.cdf( -1.0, 4.0 )\ny = base.dists.exponential.cdf( NaN, 1.0 )\ny = base.dists.exponential.cdf( 0.0, NaN )\ny = base.dists.exponential.cdf( 2.0, -1.0 )\n","base.dists.exponential.cdf.factory":"var myCDF = base.dists.exponential.cdf.factory( 0.5 );\nvar y = myCDF( 3.0 )\n","base.dists.exponential.entropy":"var v = base.dists.exponential.entropy( 11.0 )\nv = base.dists.exponential.entropy( 4.5 )\n","base.dists.exponential.Exponential":"var exponential = base.dists.exponential.Exponential( 6.0 );\nexponential.lambda\nexponential.entropy\nexponential.kurtosis\nexponential.mean\nexponential.median\nexponential.mode\nexponential.skewness\nexponential.stdev\nexponential.variance\nexponential.cdf( 1.0 )\nexponential.logcdf( 1.0 )\nexponential.logpdf( 1.5 )\nexponential.mgf( -0.5 )\nexponential.pdf( 1.5 )\nexponential.quantile( 0.5 )\n","base.dists.exponential.kurtosis":"var v = base.dists.exponential.kurtosis( 11.0 )\nv = base.dists.exponential.kurtosis( 4.5 )\n","base.dists.exponential.logcdf":"var y = base.dists.exponential.logcdf( 2.0, 0.1 )\ny = base.dists.exponential.logcdf( 1.0, 2.0 )\ny = base.dists.exponential.logcdf( -1.0, 4.0 )\ny = base.dists.exponential.logcdf( NaN, 1.0 )\ny = base.dists.exponential.logcdf( 0.0, NaN )\ny = base.dists.exponential.logcdf( 2.0, -1.0 )\n","base.dists.exponential.logcdf.factory":"var mylogCDF = base.dists.exponential.logcdf.factory( 0.5 );\nvar y = mylogCDF( 3.0 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)\n","base.dists.exponential.mgf.factory":"var myMGF = base.dists.exponential.mgf.factory( 4.0 );\nvar y = myMGF( 3.0 )\ny = myMGF( 0.5 )\n","base.dists.exponential.mode":"var v = base.dists.exponential.mode( 11.0 )\nv = base.dists.exponential.mode( 4.5 )\n","base.dists.exponential.pdf":"var y = base.dists.exponential.pdf( 0.3, 4.0 )\ny = base.dists.exponential.pdf( 2.0, 0.7 )\ny = base.dists.exponential.pdf( -1.0, 0.5 )\ny = base.dists.exponential.pdf( 0, NaN )\ny = base.dists.exponential.pdf( NaN, 2.0 )\ny = base.dists.exponential.pdf( 2.0, -1.0 )\n","base.dists.exponential.pdf.factory":"var myPDF = base.dists.exponential.pdf.factory( 0.5 );\nvar y = myPDF( 3.0 )\n","base.dists.exponential.quantile":"var y = base.dists.exponential.quantile( 0.8, 1.0 )\ny = base.dists.exponential.quantile( 0.5, 4.0 )\ny = base.dists.exponential.quantile( 0.5, 0.1 )\ny = base.dists.exponential.quantile( -0.2, 0.1 )\ny = base.dists.exponential.quantile( NaN, 1.0 )\ny = base.dists.exponential.quantile( 0.0, NaN )\ny = base.dists.exponential.quantile( 0.5, -1.0 )\n","base.dists.exponential.quantile.factory":"var myQuantile = base.dists.exponential.quantile.factory( 0.4 );\nvar y = myQuantile( 0.4 )\ny = myQuantile( 1.0 )\n","base.dists.exponential.skewness":"var v = base.dists.exponential.skewness( 11.0 )\nv = base.dists.exponential.skewness( 4.5 )\n","base.dists.exponential.stdev":"var v = base.dists.exponential.stdev( 9.0 )\nv = base.dists.exponential.stdev( 1.0 )\n","base.dists.exponential.variance":"var v = base.dists.exponential.variance( 9.0 )\nv = base.dists.exponential.variance( 1.0 )\n","base.dists.f.cdf":"var y = base.dists.f.cdf( 2.0, 1.0, 1.0 )\nvar y = base.dists.f.cdf( 2.0, 8.0, 4.0 )\nvar y = base.dists.f.cdf( -1.0, 2.0, 2.0 )\nvar y = base.dists.f.cdf( PINF, 4.0, 2.0 )\nvar y = base.dists.f.cdf( NINF, 4.0, 2.0 )\nvar y = base.dists.f.cdf( NaN, 1.0, 1.0 )\nvar y = base.dists.f.cdf( 0.0, NaN, 1.0 )\nvar y = base.dists.f.cdf( 0.0, 1.0, NaN )\nvar y = base.dists.f.cdf( 2.0, 1.0, -1.0 )\nvar y = base.dists.f.cdf( 2.0, -1.0, 1.0 )\n","base.dists.f.cdf.factory":"var myCDF = base.dists.f.cdf.factory( 10.0, 2.0 );\nvar y = myCDF( 10.0 )\ny = myCDF( 8.0 )\n","base.dists.f.entropy":"var v = base.dists.f.entropy( 3.0, 7.0 )\nv = base.dists.f.entropy( 4.0, 12.0 )\nv = base.dists.f.entropy( 8.0, 2.0 )\n","base.dists.f.F":"var f = base.dists.f.F( 6.0, 9.0 );\nf.d1\nf.d2\nf.entropy\nf.kurtosis\nf.mean\nf.mode\nf.skewness\nf.stdev\nf.variance\nf.cdf( 3.0 )\nf.pdf( 2.5 )\nf.quantile( 0.8 )\n","base.dists.f.kurtosis":"var v = base.dists.f.kurtosis( 3.0, 9.0 )\nv = base.dists.f.kurtosis( 4.0, 12.0 )\nv = base.dists.f.kurtosis( 8.0, 9.0 )\n","base.dists.f.mean":"var v = base.dists.f.mean( 3.0, 5.0 )\nv = base.dists.f.mean( 4.0, 12.0 )\nv = base.dists.f.mean( 8.0, 4.0 )\n","base.dists.f.mode":"var v = base.dists.f.mode( 3.0, 5.0 )\nv = base.dists.f.mode( 4.0, 12.0 )\nv = base.dists.f.mode( 8.0, 4.0 )\n","base.dists.f.pdf":"var y = base.dists.f.pdf( 2.0, 0.5, 1.0 )\ny = base.dists.f.pdf( 0.1, 1.0, 1.0 )\ny = base.dists.f.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.f.pdf( NaN, 1.0, 1.0 )\ny = base.dists.f.pdf( 0.0, NaN, 1.0 )\ny = base.dists.f.pdf( 0.0, 1.0, NaN )\ny = base.dists.f.pdf( 2.0, 1.0, -1.0 )\ny = base.dists.f.pdf( 2.0, -1.0, 1.0 )\n","base.dists.f.pdf.factory":"var myPDF = base.dists.f.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 7.0 )\ny = myPDF( 2.0 )\n","base.dists.f.quantile":"var y = base.dists.f.quantile( 0.8, 1.0, 1.0 )\ny = base.dists.f.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.f.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.f.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.f.quantile( NaN, 1.0, 1.0 )\ny = base.dists.f.quantile( 0.5, NaN, 1.0 )\ny = base.dists.f.quantile( 0.5, 1.0, NaN )\ny = base.dists.f.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.f.quantile( 0.5, 1.0, -1.0 )\n","base.dists.f.quantile.factory":"var myQuantile = base.dists.f.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.2 )\ny = myQuantile( 0.8 )\n","base.dists.f.skewness":"var v = base.dists.f.skewness( 3.0, 7.0 )\nv = base.dists.f.skewness( 4.0, 12.0 )\nv = base.dists.f.skewness( 8.0, 7.0 )\n","base.dists.f.stdev":"var v = base.dists.f.stdev( 3.0, 5.0 )\nv = base.dists.f.stdev( 4.0, 12.0 )\nv = base.dists.f.stdev( 8.0, 5.0 )\n","base.dists.f.variance":"var v = base.dists.f.variance( 3.0, 5.0 )\nv = base.dists.f.variance( 4.0, 12.0 )\nv = base.dists.f.variance( 8.0, 5.0 )\n","base.dists.frechet.cdf":"var y = base.dists.frechet.cdf( 10.0, 2.0, 3.0, 0.0 )\ny = base.dists.frechet.cdf( -1.0, 2.0, 3.0, -3.0 )\ny = base.dists.frechet.cdf( 2.5, 2.0, 1.0, 2.0 )\ny = base.dists.frechet.cdf( NaN, 1.0, 1.0, 0.0 )\ny = base.dists.frechet.cdf( 0.0, NaN, 1.0, 0.0 )\ny = base.dists.frechet.cdf( 0.0, 1.0, NaN, 0.0 )\ny = base.dists.frechet.cdf( 0.0, 1.0, 1.0, NaN )\ny = base.dists.frechet.cdf( 0.0, -1.0, 1.0, 0.0 )\ny = base.dists.frechet.cdf( 0.0, 1.0, -1.0, 0.0 )\n","base.dists.frechet.cdf.factory":"var myCDF = base.dists.frechet.cdf.factory( 3.0, 3.0, 5.0 );\nvar y = myCDF( 10.0 )\ny = myCDF( 7.0 )\n","base.dists.frechet.entropy":"var y = base.dists.frechet.entropy( 1.0, 1.0, 1.0 )\ny = base.dists.frechet.entropy( 4.0, 2.0, 1.0 )\ny = base.dists.frechet.entropy( NaN, 1.0, 0.0 )\ny = base.dists.frechet.entropy( 1.0, NaN, 0.0 )\ny = base.dists.frechet.entropy( 1.0, 1.0, NaN )\n","base.dists.frechet.Frechet":"var frechet = base.dists.frechet.Frechet( 1.0, 1.0, 0.0 );\nfrechet.alpha\nfrechet.s\nfrechet.m\nfrechet.entropy\nfrechet.kurtosis\nfrechet.mean\nfrechet.median\nfrechet.mode\nfrechet.skewness\nfrechet.stdev\nfrechet.variance\nfrechet.cdf( 0.8 )\nfrechet.logcdf( 0.8 )\nfrechet.logpdf( 0.8 )\nfrechet.pdf( 0.8 )\nfrechet.quantile( 0.8 )\n","base.dists.frechet.kurtosis":"var y = base.dists.frechet.kurtosis( 5.0, 2.0, 1.0 )\nvar y = base.dists.frechet.kurtosis( 5.0, 10.0, -3.0 )\ny = base.dists.frechet.kurtosis( 3.5, 2.0, 1.0 )\ny = base.dists.frechet.kurtosis( NaN, 1.0, 0.0 )\ny = base.dists.frechet.kurtosis( 1.0, NaN, 0.0 )\ny = base.dists.frechet.kurtosis( 1.0, 1.0, NaN )\n","base.dists.frechet.logcdf":"var y = base.dists.frechet.logcdf( 10.0, 2.0, 3.0, 0.0 )\ny = base.dists.frechet.logcdf( -1.0, 2.0, 3.0, -3.0 )\ny = base.dists.frechet.logcdf( 2.5, 2.0, 1.0, 2.0 )\ny = base.dists.frechet.logcdf( NaN, 1.0, 1.0, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, NaN, 1.0, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, 1.0, NaN, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, 1.0, 1.0, NaN )\ny = base.dists.frechet.logcdf( 0.0, -1.0, 1.0, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, 1.0, -1.0, 0.0 )\n","base.dists.frechet.logcdf.factory":"var mylogcdf = base.dists.frechet.logcdf.factory( 3.0, 3.0, 5.0 );\nvar y = mylogcdf( 10.0 )\ny = mylogcdf( 7.0 )\n","base.dists.frechet.logpdf":"var y = base.dists.frechet.logpdf( 10.0, 1.0, 3.0, 5.0 )\ny = base.dists.frechet.logpdf( -2.0, 1.0, 3.0, -3.0 )\ny = base.dists.frechet.logpdf( 0.0, 2.0, 1.0, -1.0 )\ny = base.dists.frechet.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.frechet.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.frechet.logpdf( 0.0, 0.0, NaN )\ny = base.dists.frechet.logpdf( 0.0, 0.0, -1.0 )\n","base.dists.frechet.logpdf.factory":"var mylogPDF = base.dists.frechet.logpdf.factory( 2.0, 3.0, 1.0 );\nvar y = mylogPDF( 10.0 )\ny = mylogPDF( 2.0 )\n","base.dists.frechet.mean":"var y = base.dists.frechet.mean( 4.0, 2.0, 1.0 )\ny = base.dists.frechet.mean( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.mean( NaN, 1.0, 0.0 )\ny = base.dists.frechet.mean( 1.0, NaN, 0.0 )\ny = base.dists.frechet.mean( 1.0, 1.0, NaN )\n","base.dists.frechet.median":"var y = base.dists.frechet.median( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.median( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.median( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.median( NaN, 1.0, 0.0 )\ny = base.dists.frechet.median( 1.0, NaN, 0.0 )\ny = base.dists.frechet.median( 1.0, 1.0, NaN )\n","base.dists.frechet.mode":"var y = base.dists.frechet.mode( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.mode( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.mode( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.mode( NaN, 1.0, 0.0 )\ny = base.dists.frechet.mode( 1.0, NaN, 0.0 )\ny = base.dists.frechet.mode( 1.0, 1.0, NaN )\n","base.dists.frechet.pdf":"var y = base.dists.frechet.pdf( 10.0, 0.0, 3.0 )\ny = base.dists.frechet.pdf( -2.0, 0.0, 3.0 )\ny = base.dists.frechet.pdf( 0.0, 0.0, 1.0 )\ny = base.dists.frechet.pdf( NaN, 0.0, 1.0 )\ny = base.dists.frechet.pdf( 0.0, NaN, 1.0 )\ny = base.dists.frechet.pdf( 0.0, 0.0, NaN )\ny = base.dists.frechet.pdf( 0.0, 0.0, -1.0 )\n","base.dists.frechet.pdf.factory":"var myPDF = base.dists.frechet.pdf.factory( 2.0, 3.0 );\nvar y = myPDF( 10.0 )\ny = myPDF( 2.0 )\n","base.dists.frechet.quantile":"var y = base.dists.frechet.quantile( 0.3, 10.0, 2.0, 3.0 )\ny = base.dists.frechet.quantile( 0.2, 3.0, 3.0, 3.0 )\ny = base.dists.frechet.quantile( 0.9, 1.0, 1.0, -3.0 )\ny = base.dists.frechet.quantile( NaN, 1.0, 1.0, 0.0 )\ny = base.dists.frechet.quantile( 0.0, NaN, 1.0, 0.0)\ny = base.dists.frechet.quantile( 0.0, 1.0, NaN, 0.0 )\ny = base.dists.frechet.quantile( 0.0, 1.0, 1.0, NaN )\ny = base.dists.frechet.quantile( 0.0, -1.0, 1.0, 0.0 )\ny = base.dists.frechet.quantile( 0.0, 1.0, -1.0, 0.0 )\n","base.dists.frechet.quantile.factory":"var myQuantile = base.dists.frechet.quantile.factory( 2.0, 2.0, 3.0 );\nvar y = myQuantile( 0.5 )\ny = myQuantile( 0.2 )\n","base.dists.frechet.skewness":"var y = base.dists.frechet.skewness( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.skewness( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.skewness( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.skewness( NaN, 1.0, 0.0 )\ny = base.dists.frechet.skewness( 1.0, NaN, 0.0 )\ny = base.dists.frechet.skewness( 1.0, 1.0, NaN )\n","base.dists.frechet.stdev":"var y = base.dists.frechet.stdev( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.stdev( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.stdev( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.stdev( NaN, 1.0, 0.0 )\ny = base.dists.frechet.stdev( 1.0, NaN, 0.0 )\ny = base.dists.frechet.stdev( 1.0, 1.0, NaN )\n","base.dists.frechet.variance":"var y = base.dists.frechet.variance( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.variance( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.variance( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.variance( NaN, 1.0, 0.0 )\ny = base.dists.frechet.variance( 1.0, NaN, 0.0 )\ny = base.dists.frechet.variance( 1.0, 1.0, NaN )\n","base.dists.gamma.cdf":"var y = base.dists.gamma.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.gamma.cdf( 2.0, 3.0, 1.0 )\ny = base.dists.gamma.cdf( -1.0, 2.0, 2.0 )\ny = base.dists.gamma.cdf( PINF, 4.0, 2.0 )\ny = base.dists.gamma.cdf( NINF, 4.0, 2.0 )\ny = base.dists.gamma.cdf( NaN, 0.0, 1.0 )\ny = base.dists.gamma.cdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.cdf( 0.0, 0.0, NaN )\ny = base.dists.gamma.cdf( 2.0, -1.0, 1.0 )\ny = base.dists.gamma.cdf( 2.0, 1.0, -1.0 )\ny = base.dists.gamma.cdf( 2.0, 0.0, 2.0 )\ny = base.dists.gamma.cdf( -2.0, 0.0, 2.0 )\ny = base.dists.gamma.cdf( 0.0, 0.0, 2.0 )\n","base.dists.gamma.cdf.factory":"var myCDF = base.dists.gamma.cdf.factory( 2.0, 0.5 );\nvar y = myCDF( 6.0 )\ny = myCDF( 2.0 )\n","base.dists.gamma.entropy":"var v = base.dists.gamma.entropy( 1.0, 1.0 )\nv = base.dists.gamma.entropy( 4.0, 12.0 )\nv = base.dists.gamma.entropy( 8.0, 2.0 )\n","base.dists.gamma.Gamma":"var gamma = base.dists.gamma.Gamma( 6.0, 5.0 );\ngamma.alpha\ngamma.beta\ngamma.entropy\ngamma.kurtosis\ngamma.mean\ngamma.mode\ngamma.skewness\ngamma.stdev\ngamma.variance\ngamma.cdf( 0.8 )\ngamma.logcdf( 0.8 )\ngamma.logpdf( 1.0 )\ngamma.mgf( -0.5 )\ngamma.pdf( 1.0 )\ngamma.quantile( 0.8 )\n","base.dists.gamma.kurtosis":"var v = base.dists.gamma.kurtosis( 1.0, 1.0 )\nv = base.dists.gamma.kurtosis( 4.0, 12.0 )\nv = base.dists.gamma.kurtosis( 8.0, 2.0 )\n","base.dists.gamma.logcdf":"var y = base.dists.gamma.logcdf( 2.0, 0.5, 1.0 )\ny = base.dists.gamma.logcdf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.logcdf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.logcdf( NaN, 0.6, 1.0 )\ny = base.dists.gamma.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.logcdf( 0.0, 1.0, NaN )\ny = base.dists.gamma.logcdf( 2.0, -1.0, 1.0 )\ny = base.dists.gamma.logcdf( 2.0, 1.0, -1.0 )\n","base.dists.gamma.logcdf.factory":"var mylogCDF = base.dists.gamma.logcdf.factory( 6.0, 7.0 );\nvar y = mylogCDF( 2.0 )\n","base.dists.gamma.logpdf":"var y = base.dists.gamma.logpdf( 2.0, 0.5, 1.0 )\ny = base.dists.gamma.logpdf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.logpdf( NaN, 0.6, 1.0 )\ny = base.dists.gamma.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.logpdf( 0.0, 1.0, NaN )\ny = base.dists.gamma.logpdf( 2.0, -1.0, 1.0 )\ny = base.dists.gamma.logpdf( 2.0, 1.0, -1.0 )\ny = base.dists.gamma.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.gamma.logpdf( 0.0, 0.0, 2.0 )\n","base.dists.gamma.logpdf.factory":"var mylogPDF = base.dists.gamma.logpdf.factory( 6.0, 7.0 );\nvar y = mylogPDF( 2.0 )\n","base.dists.gamma.mean":"var v = base.dists.gamma.mean( 1.0, 1.0 )\nv = base.dists.gamma.mean( 4.0, 12.0 )\nv = base.dists.gamma.mean( 8.0, 2.0 )\n","base.dists.gamma.mgf":"var y = base.dists.gamma.mgf( 0.5, 0.5, 1.0 )\ny = base.dists.gamma.mgf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.mgf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.mgf( NaN, 1.0, 1.0 )\ny = base.dists.gamma.mgf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.mgf( 0.0, 1.0, NaN )\ny = base.dists.gamma.mgf( 2.0, 4.0, 1.0 )\ny = base.dists.gamma.mgf( 2.0, -0.5, 1.0 )\ny = base.dists.gamma.mgf( 2.0, 1.0, 0.0 )\ny = base.dists.gamma.mgf( 2.0, 1.0, -1.0 )\n","base.dists.gamma.mgf.factory":"var myMGF = base.dists.gamma.mgf.factory( 3.0, 1.5 );\nvar y = myMGF( 1.0 )\ny = myMGF( 0.5 )\n","base.dists.gamma.mode":"var v = base.dists.gamma.mode( 1.0, 1.0 )\nv = base.dists.gamma.mode( 4.0, 12.0 )\nv = base.dists.gamma.mode( 8.0, 2.0 )\n","base.dists.gamma.pdf":"var y = base.dists.gamma.pdf( 2.0, 0.5, 1.0 )\ny = base.dists.gamma.pdf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.pdf( NaN, 0.6, 1.0 )\ny = base.dists.gamma.pdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.pdf( 0.0, 1.0, NaN )\ny = base.dists.gamma.pdf( 2.0, -1.0, 1.0 )\ny = base.dists.gamma.pdf( 2.0, 1.0, -1.0 )\ny = base.dists.gamma.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.gamma.pdf( 0.0, 0.0, 2.0 )\n","base.dists.gamma.pdf.factory":"var myPDF = base.dists.gamma.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 2.0 )\n","base.dists.gamma.quantile":"var y = base.dists.gamma.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.gamma.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.gamma.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.gamma.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.gamma.quantile( NaN, 1.0, 1.0 )\ny = base.dists.gamma.quantile( 0.0, NaN, 1.0 )\ny = base.dists.gamma.quantile( 0.0, 1.0, NaN )\ny = base.dists.gamma.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.gamma.quantile( 0.5, 1.0, -1.0 )\ny = base.dists.gamma.quantile( 0.3, 0.0, 2.0 )\ny = base.dists.gamma.quantile( 0.9, 0.0, 2.0 )\n","base.dists.gamma.quantile.factory":"var myQuantile = base.dists.gamma.quantile.factory( 2.0, 2.0 );\nvar y = myQuantile( 0.8 )\ny = myQuantile( 0.4 )\n","base.dists.gamma.skewness":"var v = base.dists.gamma.skewness( 1.0, 1.0 )\nv = base.dists.gamma.skewness( 4.0, 12.0 )\nv = base.dists.gamma.skewness( 8.0, 2.0 )\n","base.dists.gamma.stdev":"var v = base.dists.gamma.stdev( 1.0, 1.0 )\nv = base.dists.gamma.stdev( 4.0, 12.0 )\nv = base.dists.gamma.stdev( 8.0, 2.0 )\n","base.dists.gamma.variance":"var v = base.dists.gamma.variance( 1.0, 1.0 )\nv = base.dists.gamma.variance( 4.0, 12.0 )\nv = base.dists.gamma.variance( 8.0, 2.0 )\n","base.dists.geometric.cdf":"var y = base.dists.geometric.cdf( 2.0, 0.5 )\ny = base.dists.geometric.cdf( 2.0, 0.1 )\ny = base.dists.geometric.cdf( -1.0, 4.0 )\ny = base.dists.geometric.cdf( NaN, 0.5 )\ny = base.dists.geometric.cdf( 0.0, NaN )\ny = base.dists.geometric.cdf( 2.0, 1.4 )\n","base.dists.geometric.cdf.factory":"var mycdf = base.dists.geometric.cdf.factory( 0.5 );\nvar y = mycdf( 3.0 )\ny = mycdf( 1.0 )\n","base.dists.geometric.entropy":"var v = base.dists.geometric.entropy( 0.1 )\nv = base.dists.geometric.entropy( 0.5 )\n","base.dists.geometric.Geometric":"var geometric = base.dists.geometric.Geometric( 0.6 );\ngeometric.p\ngeometric.entropy\ngeometric.kurtosis\ngeometric.mean\ngeometric.median\ngeometric.mode\ngeometric.skewness\ngeometric.stdev\ngeometric.variance\ngeometric.cdf( 3.0 )\ngeometric.logcdf( 3.0 )\ngeometric.logpmf( 4.0 )\ngeometric.mgf( 0.5 )\ngeometric.pmf( 2.0 )\ngeometric.quantile( 0.7 )\n","base.dists.geometric.kurtosis":"var v = base.dists.geometric.kurtosis( 0.1 )\nv = base.dists.geometric.kurtosis( 0.5 )\n","base.dists.geometric.logcdf":"var y = base.dists.geometric.logcdf( 2.0, 0.5 )\ny = base.dists.geometric.logcdf( 2.0, 0.1 )\ny = base.dists.geometric.logcdf( -1.0, 4.0 )\ny = base.dists.geometric.logcdf( NaN, 0.5 )\ny = base.dists.geometric.logcdf( 0.0, NaN )\ny = base.dists.geometric.logcdf( 2.0, 1.4 )\n","base.dists.geometric.logcdf.factory":"var mylogcdf = base.dists.geometric.logcdf.factory( 0.5 );\nvar y = mylogcdf( 3.0 )\ny = mylogcdf( 1.0 )\n","base.dists.geometric.logpmf":"var y = base.dists.geometric.logpmf( 4.0, 0.3 )\ny = base.dists.geometric.logpmf( 2.0, 0.7 )\ny = base.dists.geometric.logpmf( -1.0, 0.5 )\ny = base.dists.geometric.logpmf( 0.0, NaN )\ny = base.dists.geometric.logpmf( NaN, 0.5 )\ny = base.dists.geometric.logpmf( 2.0, 1.5 )\n","base.dists.geometric.logpmf.factory":"var mylogpmf = base.dists.geometric.logpmf.factory( 0.5 );\nvar y = mylogpmf( 3.0 )\ny = mylogpmf( 1.0 )\n","base.dists.geometric.mean":"var v = base.dists.geometric.mean( 0.1 )\nv = base.dists.geometric.mean( 0.5 )\n","base.dists.geometric.median":"var v = base.dists.geometric.median( 0.1 )\nv = base.dists.geometric.median( 0.5 )\n","base.dists.geometric.mgf":"var y = base.dists.geometric.mgf( 0.2, 0.5 )\ny = base.dists.geometric.mgf( 0.4, 0.5 )\ny = base.dists.geometric.mgf( 0.8, 0.5 )\ny = base.dists.geometric.mgf( NaN, 0.0 )\ny = base.dists.geometric.mgf( 0.0, NaN )\ny = base.dists.geometric.mgf( -2.0, -1.0 )\ny = base.dists.geometric.mgf( 0.2, 2.0 )\n","base.dists.geometric.mgf.factory":"var mymgf = base.dists.geometric.mgf.factory( 0.8 );\nvar y = mymgf( -0.2 )\n","base.dists.geometric.mode":"var v = base.dists.geometric.mode( 0.1 )\nv = base.dists.geometric.mode( 0.5 )\n","base.dists.geometric.pmf":"var y = base.dists.geometric.pmf( 4.0, 0.3 )\ny = base.dists.geometric.pmf( 2.0, 0.7 )\ny = base.dists.geometric.pmf( -1.0, 0.5 )\ny = base.dists.geometric.pmf( 0.0, NaN )\ny = base.dists.geometric.pmf( NaN, 0.5 )\ny = base.dists.geometric.pmf( 2.0, 1.5 )\n","base.dists.geometric.pmf.factory":"var mypmf = base.dists.geometric.pmf.factory( 0.5 );\nvar y = mypmf( 3.0 )\ny = mypmf( 1.0 )\n","base.dists.geometric.quantile":"var y = base.dists.geometric.quantile( 0.8, 0.4 )\ny = base.dists.geometric.quantile( 0.5, 0.4 )\ny = base.dists.geometric.quantile( 0.9, 0.1 )\ny = base.dists.geometric.quantile( -0.2, 0.1 )\ny = base.dists.geometric.quantile( NaN, 0.8 )\ny = base.dists.geometric.quantile( 0.4, NaN )\ny = base.dists.geometric.quantile( 0.5, -1.0 )\ny = base.dists.geometric.quantile( 0.5, 1.5 )\n","base.dists.geometric.quantile.factory":"var myquantile = base.dists.geometric.quantile.factory( 0.4 );\nvar y = myquantile( 0.4 )\ny = myquantile( 0.8 )\ny = myquantile( 1.0 )\n","base.dists.geometric.skewness":"var v = base.dists.geometric.skewness( 0.1 )\nv = base.dists.geometric.skewness( 0.5 )\n","base.dists.geometric.stdev":"var v = base.dists.geometric.stdev( 0.1 )\nv = base.dists.geometric.stdev( 0.5 )\n","base.dists.geometric.variance":"var v = base.dists.geometric.variance( 0.1 )\nv = base.dists.geometric.variance( 0.5 )\n","base.dists.gumbel.cdf":"var y = base.dists.gumbel.cdf( 10.0, 0.0, 3.0 )\ny = base.dists.gumbel.cdf( -2.0, 0.0, 3.0 )\ny = base.dists.gumbel.cdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.cdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.cdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.cdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.cdf( 0.0, 0.0, -1.0 )\n","base.dists.gumbel.cdf.factory":"var myCDF = base.dists.gumbel.cdf.factory( 2.0, 3.0 );\nvar y = myCDF( 10.0 )\ny = myCDF( 2.0 )\n","base.dists.gumbel.entropy":"var y = base.dists.gumbel.entropy( 0.0, 1.0 )\ny = base.dists.gumbel.entropy( 4.0, 2.0 )\ny = base.dists.gumbel.entropy( NaN, 1.0 )\ny = base.dists.gumbel.entropy( 0.0, NaN )\ny = base.dists.gumbel.entropy( 0.0, 0.0 )\n","base.dists.gumbel.Gumbel":"var gumbel = base.dists.gumbel.Gumbel( -2.0, 3.0 );\ngumbel.mu\ngumbel.beta\ngumbel.entropy\ngumbel.kurtosis\ngumbel.mean\ngumbel.median\ngumbel.mode\ngumbel.skewness\ngumbel.stdev\ngumbel.variance\ngumbel.cdf( 0.8 )\ngumbel.logcdf( 0.8 )\ngumbel.logpdf( 1.0 )\ngumbel.mgf( 0.2 )\ngumbel.pdf( 1.0 )\ngumbel.quantile( 0.8 )\n","base.dists.gumbel.kurtosis":"var y = base.dists.gumbel.kurtosis( 0.0, 1.0 )\ny = base.dists.gumbel.kurtosis( 4.0, 2.0 )\ny = base.dists.gumbel.kurtosis( NaN, 1.0 )\ny = base.dists.gumbel.kurtosis( 0.0, NaN )\ny = base.dists.gumbel.kurtosis( 0.0, 0.0 )\n","base.dists.gumbel.logcdf":"var y = base.dists.gumbel.logcdf( 10.0, 0.0, 3.0 )\ny = base.dists.gumbel.logcdf( -2.0, 0.0, 3.0 )\ny = base.dists.gumbel.logcdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.logcdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.logcdf( 0.0, 0.0, -1.0 )\n","base.dists.gumbel.logcdf.factory":"var myLCDF = base.dists.gumbel.logcdf.factory( 2.0, 3.0 );\nvar y = myLCDF( 10.0 )\ny = myLCDF( 2.0 )\n","base.dists.gumbel.logpdf":"var y = base.dists.gumbel.logpdf( 0.0, 0.0, 2.0 )\ny = base.dists.gumbel.logpdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.logpdf( 1.0, 3.0, 2.0 )\ny = base.dists.gumbel.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.logpdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.logpdf( 2.0, 0.0, -1.0 )\n","base.dists.gumbel.logpdf.factory":"var mylogpdf = base.dists.gumbel.logpdf.factory( 10.0, 2.0 );\nvar y = mylogpdf( 10.0 )\ny = mylogpdf( 12.0 )\n","base.dists.gumbel.mean":"var y = base.dists.gumbel.mean( 0.0, 1.0 )\ny = base.dists.gumbel.mean( 4.0, 2.0 )\ny = base.dists.gumbel.mean( NaN, 1.0 )\ny = base.dists.gumbel.mean( 0.0, NaN )\ny = base.dists.gumbel.mean( 0.0, 0.0 )\n","base.dists.gumbel.median":"var y = base.dists.gumbel.median( 0.0, 1.0 )\ny = base.dists.gumbel.median( 4.0, 2.0 )\ny = base.dists.gumbel.median( NaN, 1.0 )\ny = base.dists.gumbel.median( 0.0, NaN )\ny = base.dists.gumbel.median( 0.0, 0.0 )\n","base.dists.gumbel.mgf":"var y = base.dists.gumbel.mgf( -1.0, 0.0, 3.0 )\ny = base.dists.gumbel.mgf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.mgf( 0.1, 0.0, 3.0 )\ny = base.dists.gumbel.mgf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.mgf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.mgf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.mgf( 0.8, 0.0, 2.0 )\ny = base.dists.gumbel.mgf( 0.0, 0.0, -1.0 )\n","base.dists.gumbel.mgf.factory":"var myMGF = base.dists.gumbel.mgf.factory( 0.0, 3.0 );\nvar y = myMGF( -1.5 )\ny = myMGF( -1.0 )\n","base.dists.gumbel.mode":"var y = base.dists.gumbel.mode( 0.0, 1.0 )\ny = base.dists.gumbel.mode( 4.0, 2.0 )\ny = base.dists.gumbel.mode( NaN, 1.0 )\ny = base.dists.gumbel.mode( 0.0, NaN )\ny = base.dists.gumbel.mode( 0.0, 0.0 )\n","base.dists.gumbel.pdf":"var y = base.dists.gumbel.pdf( 0.0, 0.0, 2.0 )\ny = base.dists.gumbel.pdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.pdf( 1.0, 3.0, 2.0 )\ny = base.dists.gumbel.pdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.pdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.pdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.pdf( 2.0, 0.0, -1.0 )\n","base.dists.gumbel.pdf.factory":"var myPDF = base.dists.gumbel.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\ny = myPDF( 12.0 )\n","base.dists.gumbel.quantile":"var y = base.dists.gumbel.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.gumbel.quantile( 0.5, 4.0, 4.0 )\ny = base.dists.gumbel.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.quantile( 0.0, 0.0, NaN )\ny = base.dists.gumbel.quantile( 0.5, 0.0, -1.0 )\n","base.dists.gumbel.quantile.factory":"var myQuantile = base.dists.gumbel.quantile.factory( 8.0, 2.0 );\nvar y = myQuantile( 0.5 )\ny = myQuantile( 0.7 )\n","base.dists.gumbel.skewness":"var y = base.dists.gumbel.skewness( 0.0, 1.0 )\ny = base.dists.gumbel.skewness( 4.0, 2.0 )\ny = base.dists.gumbel.skewness( NaN, 1.0 )\ny = base.dists.gumbel.skewness( 0.0, NaN )\ny = base.dists.gumbel.skewness( 0.0, 0.0 )\n","base.dists.gumbel.stdev":"var y = base.dists.gumbel.stdev( 0.0, 1.0 )\ny = base.dists.gumbel.stdev( 4.0, 2.0 )\ny = base.dists.gumbel.stdev( NaN, 1.0 )\ny = base.dists.gumbel.stdev( 0.0, NaN )\ny = base.dists.gumbel.stdev( 0.0, 0.0 )\n","base.dists.gumbel.variance":"var y = base.dists.gumbel.variance( 0.0, 1.0 )\ny = base.dists.gumbel.variance( 4.0, 2.0 )\ny = base.dists.gumbel.variance( NaN, 1.0 )\ny = base.dists.gumbel.variance( 0.0, NaN )\ny = base.dists.gumbel.variance( 0.0, 0.0 )\n","base.dists.hypergeometric.cdf":"var y = base.dists.hypergeometric.cdf( 1.0, 8, 4, 2 )\ny = base.dists.hypergeometric.cdf( 1.5, 8, 4, 2 )\ny = base.dists.hypergeometric.cdf( 2.0, 8, 4, 2 )\ny = base.dists.hypergeometric.cdf( 0, 8, 4, 2)\ny = base.dists.hypergeometric.cdf( NaN, 10, 5, 2 )\ny = base.dists.hypergeometric.cdf( 0.0, NaN, 5, 2 )\ny = base.dists.hypergeometric.cdf( 0.0, 10, NaN, 2 )\ny = base.dists.hypergeometric.cdf( 0.0, 10, 5, NaN )\ny = base.dists.hypergeometric.cdf( 2.0, 10.5, 5, 2 )\ny = base.dists.hypergeometric.cdf( 2.0, 10, 1.5, 2 )\ny = base.dists.hypergeometric.cdf( 2.0, 10, 5, -2.0 )\ny = base.dists.hypergeometric.cdf( 2.0, 10, 5, 12 )\ny = base.dists.hypergeometric.cdf( 2.0, 8, 3, 9 )\n","base.dists.hypergeometric.cdf.factory":"var myCDF = base.dists.hypergeometric.cdf.factory( 30, 20, 5 );\nvar y = myCDF( 4.0 )\ny = myCDF( 1.0 )\n","base.dists.hypergeometric.Hypergeometric":"var hypergeometric = base.dists.hypergeometric.Hypergeometric( 100, 70, 20 );\nhypergeometric.N\nhypergeometric.K\nhypergeometric.n\nhypergeometric.kurtosis\nhypergeometric.mean\nhypergeometric.mode\nhypergeometric.skewness\nhypergeometric.stdev\nhypergeometric.variance\nhypergeometric.cdf( 2.9 )\nhypergeometric.logpmf( 10 )\nhypergeometric.pmf( 10 )\nhypergeometric.quantile( 0.8 )\n","base.dists.hypergeometric.kurtosis":"var v = base.dists.hypergeometric.kurtosis( 16, 11, 4 )\nv = base.dists.hypergeometric.kurtosis( 4, 2, 2 )\nv = base.dists.hypergeometric.kurtosis( 10, 5, 12 )\nv = base.dists.hypergeometric.kurtosis( 10.3, 10, 4 )\nv = base.dists.hypergeometric.kurtosis( 10, 5.5, 4 )\nv = base.dists.hypergeometric.kurtosis( 10, 5, 4.5 )\nv = base.dists.hypergeometric.kurtosis( NaN, 10, 4 )\nv = base.dists.hypergeometric.kurtosis( 20, NaN, 4 )\nv = base.dists.hypergeometric.kurtosis( 20, 10, NaN )\n","base.dists.hypergeometric.logpmf":"var y = base.dists.hypergeometric.logpmf( 1.0, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( 2.0, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( 1.5, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( NaN, 10, 5, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, NaN, 5, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, 10, NaN, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, 10, 5, NaN )\ny = base.dists.hypergeometric.logpmf( 2.0, 10.5, 5, 2 )\ny = base.dists.hypergeometric.logpmf( 2.0, 5, 1.5, 2 )\ny = base.dists.hypergeometric.logpmf( 2.0, 10, 5, -2.0 )\ny = base.dists.hypergeometric.logpmf( 2.0, 10, 5, 12 )\ny = base.dists.hypergeometric.logpmf( 2.0, 8, 3, 9 )\n","base.dists.hypergeometric.logpmf.factory":"var mylogPMF = base.dists.hypergeometric.logpmf.factory( 30, 20, 5 );\nvar y = mylogPMF( 4.0 )\ny = mylogPMF( 1.0 )\n","base.dists.hypergeometric.mean":"var v = base.dists.hypergeometric.mean( 16, 11, 4 )\nv = base.dists.hypergeometric.mean( 2, 1, 1 )\nv = base.dists.hypergeometric.mean( 10, 5, 12 )\nv = base.dists.hypergeometric.mean( 10.3, 10, 4 )\nv = base.dists.hypergeometric.mean( 10, 5.5, 4 )\nv = base.dists.hypergeometric.mean( 10, 5, 4.5 )\nv = base.dists.hypergeometric.mean( NaN, 10, 4 )\nv = base.dists.hypergeometric.mean( 20, NaN, 4 )\nv = base.dists.hypergeometric.mean( 20, 10, NaN )\n","base.dists.hypergeometric.mode":"var v = base.dists.hypergeometric.mode( 16, 11, 4 )\nv = base.dists.hypergeometric.mode( 2, 1, 1 )\nv = base.dists.hypergeometric.mode( 10, 5, 12 )\nv = base.dists.hypergeometric.mode( 10.3, 10, 4 )\nv = base.dists.hypergeometric.mode( 10, 5.5, 4 )\nv = base.dists.hypergeometric.mode( 10, 5, 4.5 )\nv = base.dists.hypergeometric.mode( NaN, 10, 4 )\nv = base.dists.hypergeometric.mode( 20, NaN, 4 )\nv = base.dists.hypergeometric.mode( 20, 10, NaN )\n","base.dists.hypergeometric.pmf":"var y = base.dists.hypergeometric.pmf( 1.0, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( 2.0, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( 1.5, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( NaN, 10, 5, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, NaN, 5, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, 10, NaN, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, 10, 5, NaN )\ny = base.dists.hypergeometric.pmf( 2.0, 10.5, 5, 2 )\ny = base.dists.hypergeometric.pmf( 2.0, 5, 1.5, 2 )\ny = base.dists.hypergeometric.pmf( 2.0, 10, 5, -2.0 )\ny = base.dists.hypergeometric.pmf( 2.0, 10, 5, 12 )\ny = base.dists.hypergeometric.pmf( 2.0, 8, 3, 9 )\n","base.dists.hypergeometric.pmf.factory":"var myPMF = base.dists.hypergeometric.pmf.factory( 30, 20, 5 );\nvar y = myPMF( 4.0 )\ny = myPMF( 1.0 )\n","base.dists.hypergeometric.quantile":"var y = base.dists.hypergeometric.quantile( 0.4, 40, 20, 10 )\ny = base.dists.hypergeometric.quantile( 0.8, 60, 40, 20 )\ny = base.dists.hypergeometric.quantile( 0.5, 100, 10, 10 )\ny = base.dists.hypergeometric.quantile( 0.0, 100, 40, 20 )\ny = base.dists.hypergeometric.quantile( 1.0, 100, 40, 20 )\ny = base.dists.hypergeometric.quantile( NaN, 40, 20, 10 )\ny = base.dists.hypergeometric.quantile( 0.2, NaN, 20, 10 )\ny = base.dists.hypergeometric.quantile( 0.2, 40, NaN, 10 )\ny = base.dists.hypergeometric.quantile( 0.2, 40, 20, NaN )\n","base.dists.hypergeometric.quantile.factory":"var myQuantile = base.dists.hypergeometric.quantile.factory( 100, 20, 10 );\nvar y = myQuantile( 0.2 )\ny = myQuantile( 0.9 )\n","base.dists.hypergeometric.skewness":"var v = base.dists.hypergeometric.skewness( 16, 11, 4 )\nv = base.dists.hypergeometric.skewness( 4, 2, 2 )\nv = base.dists.hypergeometric.skewness( 10, 5, 12 )\nv = base.dists.hypergeometric.skewness( 10.3, 10, 4 )\nv = base.dists.hypergeometric.skewness( 10, 5.5, 4 )\nv = base.dists.hypergeometric.skewness( 10, 5, 4.5 )\nv = base.dists.hypergeometric.skewness( NaN, 10, 4 )\nv = base.dists.hypergeometric.skewness( 20, NaN, 4 )\nv = base.dists.hypergeometric.skewness( 20, 10, NaN )\n","base.dists.hypergeometric.stdev":"var v = base.dists.hypergeometric.stdev( 16, 11, 4 )\nv = base.dists.hypergeometric.stdev( 2, 1, 1 )\nv = base.dists.hypergeometric.stdev( 10, 5, 12 )\nv = base.dists.hypergeometric.stdev( 10.3, 10, 4 )\nv = base.dists.hypergeometric.stdev( 10, 5.5, 4 )\nv = base.dists.hypergeometric.stdev( 10, 5, 4.5 )\nv = base.dists.hypergeometric.stdev( NaN, 10, 4 )\nv = base.dists.hypergeometric.stdev( 20, NaN, 4 )\nv = base.dists.hypergeometric.stdev( 20, 10, NaN )\n","base.dists.hypergeometric.variance":"var v = base.dists.hypergeometric.variance( 16, 11, 4 )\nv = base.dists.hypergeometric.variance( 2, 1, 1 )\nv = base.dists.hypergeometric.variance( 10, 5, 12 )\nv = base.dists.hypergeometric.variance( 10.3, 10, 4 )\nv = base.dists.hypergeometric.variance( 10, 5.5, 4 )\nv = base.dists.hypergeometric.variance( 10, 5, 4.5 )\nv = base.dists.hypergeometric.variance( NaN, 10, 4 )\nv = base.dists.hypergeometric.variance( 20, NaN, 4 )\nv = base.dists.hypergeometric.variance( 20, 10, NaN )\n","base.dists.invgamma.cdf":"var y = base.dists.invgamma.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.invgamma.cdf( 2.0, 3.0, 1.0 )\ny = base.dists.invgamma.cdf( -1.0, 2.0, 2.0 )\ny = base.dists.invgamma.cdf( PINF, 4.0, 2.0 )\ny = base.dists.invgamma.cdf( NINF, 4.0, 2.0 )\ny = base.dists.invgamma.cdf( NaN, 0.0, 1.0 )\ny = base.dists.invgamma.cdf( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.cdf( 0.0, 0.0, NaN )\ny = base.dists.invgamma.cdf( 2.0, -1.0, 1.0 )\ny = base.dists.invgamma.cdf( 2.0, 1.0, -1.0 )\n","base.dists.invgamma.cdf.factory":"var myCDF = base.dists.invgamma.cdf.factory( 2.0, 0.5 );\nvar y = myCDF( 0.5 )\ny = myCDF( 2.0 )\n","base.dists.invgamma.entropy":"var v = base.dists.invgamma.entropy( 1.0, 1.0 )\nv = base.dists.invgamma.entropy( 4.0, 12.0 )\nv = base.dists.invgamma.entropy( 8.0, 2.0 )\n","base.dists.invgamma.InvGamma":"var invgamma = base.dists.invgamma.InvGamma( 6.0, 5.0 );\ninvgamma.alpha\ninvgamma.beta\ninvgamma.entropy\ninvgamma.kurtosis\ninvgamma.mean\ninvgamma.mode\ninvgamma.skewness\ninvgamma.stdev\ninvgamma.variance\ninvgamma.cdf( 0.8 )\ninvgamma.pdf( 1.0 )\ninvgamma.logpdf( 1.0 )\ninvgamma.quantile( 0.8 )\n","base.dists.invgamma.kurtosis":"var v = base.dists.invgamma.kurtosis( 7.0, 5.0 )\nv = base.dists.invgamma.kurtosis( 6.0, 12.0 )\nv = base.dists.invgamma.kurtosis( 8.0, 2.0 )\n","base.dists.invgamma.logpdf":"var y = base.dists.invgamma.logpdf( 2.0, 0.5, 1.0 )\ny = base.dists.invgamma.logpdf( 0.2, 1.0, 1.0 )\ny = base.dists.invgamma.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.invgamma.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.invgamma.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.logpdf( 0.0, 1.0, NaN )\ny = base.dists.invgamma.logpdf( 2.0, -1.0, 1.0 )\ny = base.dists.invgamma.logpdf( 2.0, 1.0, -1.0 )\n","base.dists.invgamma.logpdf.factory":"var mylogPDF = base.dists.invgamma.logpdf.factory( 6.0, 7.0 );\nvar y = mylogPDF( 2.0 )\n","base.dists.invgamma.mean":"var v = base.dists.invgamma.mean( 4.0, 12.0 )\nv = base.dists.invgamma.mean( 8.0, 2.0 )\n","base.dists.invgamma.mode":"var v = base.dists.invgamma.mode( 1.0, 1.0 )\nv = base.dists.invgamma.mode( 4.0, 12.0 )\nv = base.dists.invgamma.mode( 8.0, 2.0 )\n","base.dists.invgamma.pdf":"var y = base.dists.invgamma.pdf( 2.0, 0.5, 1.0 )\ny = base.dists.invgamma.pdf( 0.2, 1.0, 1.0 )\ny = base.dists.invgamma.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.invgamma.pdf( NaN, 1.0, 1.0 )\ny = base.dists.invgamma.pdf( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.pdf( 0.0, 1.0, NaN )\ny = base.dists.invgamma.pdf( 2.0, -1.0, 1.0 )\ny = base.dists.invgamma.pdf( 2.0, 1.0, -1.0 )\n","base.dists.invgamma.pdf.factory":"var myPDF = base.dists.invgamma.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 2.0 )\n","base.dists.invgamma.quantile":"var y = base.dists.invgamma.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.invgamma.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.invgamma.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.invgamma.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.invgamma.quantile( NaN, 1.0, 1.0 )\ny = base.dists.invgamma.quantile( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.quantile( 0.0, 1.0, NaN )\ny = base.dists.invgamma.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.invgamma.quantile( 0.5, 1.0, -1.0 )\n","base.dists.invgamma.quantile.factory":"var myQuantile = base.dists.invgamma.quantile.factory( 2.0, 2.0 );\nvar y = myQuantile( 0.8 )\ny = myQuantile( 0.4 )\n","base.dists.invgamma.skewness":"var v = base.dists.invgamma.skewness( 4.0, 12.0 )\nv = base.dists.invgamma.skewness( 8.0, 2.0 )\n","base.dists.invgamma.stdev":"var v = base.dists.invgamma.stdev( 5.0, 7.0 )\nv = base.dists.invgamma.stdev( 4.0, 12.0 )\nv = base.dists.invgamma.stdev( 8.0, 2.0 )\n","base.dists.invgamma.variance":"var v = base.dists.invgamma.variance( 5.0, 7.0 )\nv = base.dists.invgamma.variance( 4.0, 12.0 )\nv = base.dists.invgamma.variance( 8.0, 2.0 )\n","base.dists.kumaraswamy.cdf":"var y = base.dists.kumaraswamy.cdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.cdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.cdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.cdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.cdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.cdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.cdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.cdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.cdf( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.cdf.factory":"var mycdf = base.dists.kumaraswamy.cdf.factory( 0.5, 1.0 );\nvar y = mycdf( 0.8 )\ny = mycdf( 0.3 )\n","base.dists.kumaraswamy.Kumaraswamy":"var kumaraswamy = base.dists.kumaraswamy.Kumaraswamy( 6.0, 5.0 );\nkumaraswamy.a\nkumaraswamy.b\nkumaraswamy.kurtosis\nkumaraswamy.mean\nkumaraswamy.mode\nkumaraswamy.skewness\nkumaraswamy.stdev\nkumaraswamy.variance\nkumaraswamy.cdf( 0.8 )\nkumaraswamy.pdf( 1.0 )\nkumaraswamy.quantile( 0.8 )\n","base.dists.kumaraswamy.kurtosis":"var v = base.dists.kumaraswamy.kurtosis( 1.0, 1.0 )\nv = base.dists.kumaraswamy.kurtosis( 4.0, 12.0 )\nv = base.dists.kumaraswamy.kurtosis( 16.0, 8.0 )\n","base.dists.kumaraswamy.logcdf":"var y = base.dists.kumaraswamy.logcdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logcdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.logcdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.logcdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.logcdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logcdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.logcdf( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.logcdf.factory":"var mylogcdf = base.dists.kumaraswamy.logcdf.factory( 0.5, 1.0 );\nvar y = mylogcdf( 0.8 )\ny = mylogcdf( 0.3 )\n","base.dists.kumaraswamy.logpdf":"var y = base.dists.kumaraswamy.logpdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logpdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.logpdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.logpdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.logpdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logpdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logpdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.logpdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.logpdf( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.logpdf.factory":"var mylogpdf = base.dists.kumaraswamy.logpdf.factory( 0.5, 1.0 );\nvar y = mylogpdf( 0.8 )\ny = mylogpdf( 0.3 )\n","base.dists.kumaraswamy.mean":"var v = base.dists.kumaraswamy.mean( 1.5, 1.5 )\nv = base.dists.kumaraswamy.mean( 4.0, 12.0 )\nv = base.dists.kumaraswamy.mean( 16.0, 8.0 )\n","base.dists.kumaraswamy.median":"var v = base.dists.kumaraswamy.median( 1.0, 1.0 )\nv = base.dists.kumaraswamy.median( 4.0, 12.0 )\nv = base.dists.kumaraswamy.median( 16.0, 8.0 )\n","base.dists.kumaraswamy.mode":"var v = base.dists.kumaraswamy.mode( 1.5, 1.5 )\nv = base.dists.kumaraswamy.mode( 4.0, 12.0 )\nv = base.dists.kumaraswamy.mode( 16.0, 8.0 )\n","base.dists.kumaraswamy.pdf":"var y = base.dists.kumaraswamy.pdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.pdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.pdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.pdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.pdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.pdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.pdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.pdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.pdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.pdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.pdf( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.pdf.factory":"var mypdf = base.dists.kumaraswamy.pdf.factory( 0.5, 1.0 );\nvar y = mypdf( 0.8 )\ny = mypdf( 0.3 )\n","base.dists.kumaraswamy.quantile":"var y = base.dists.kumaraswamy.quantile( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.quantile( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.quantile( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.quantile( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.quantile( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.quantile( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.quantile( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.quantile( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.quantile( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.quantile( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.quantile( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.quantile.factory":"var myQuantile = base.dists.kumaraswamy.quantile.factory( 0.5, 1.0 );\nvar y = myQuantile( 0.8 )\ny = myQuantile( 0.3 )\n","base.dists.kumaraswamy.skewness":"var v = base.dists.kumaraswamy.skewness( 1.0, 1.0 )\nv = base.dists.kumaraswamy.skewness( 4.0, 12.0 )\nv = base.dists.kumaraswamy.skewness( 16.0, 8.0 )\n","base.dists.kumaraswamy.stdev":"var v = base.dists.kumaraswamy.stdev( 1.0, 1.0 )\nv = base.dists.kumaraswamy.stdev( 4.0, 12.0 )\nv = base.dists.kumaraswamy.stdev( 16.0, 8.0 )\n","base.dists.kumaraswamy.variance":"var v = base.dists.kumaraswamy.variance( 1.0, 1.0 )\nv = base.dists.kumaraswamy.variance( 4.0, 12.0 )\nv = base.dists.kumaraswamy.variance( 16.0, 8.0 )\n","base.dists.laplace.cdf":"var y = base.dists.laplace.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.cdf( 5.0, 10.0, 3.0 )\ny = base.dists.laplace.cdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.cdf( 2, NaN, 1.0 )\ny = base.dists.laplace.cdf( 2.0, 0.0, NaN )\ny = base.dists.laplace.cdf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.cdf.factory":"var myCDF = base.dists.laplace.cdf.factory( 2.0, 3.0 );\nvar y = myCDF( 10.0 )\ny = myCDF( 2.0 )\n","base.dists.laplace.entropy":"var y = base.dists.laplace.entropy( 0.0, 1.0 )\ny = base.dists.laplace.entropy( 4.0, 2.0 )\ny = base.dists.laplace.entropy( NaN, 1.0 )\ny = base.dists.laplace.entropy( 0.0, NaN )\ny = base.dists.laplace.entropy( 0.0, 0.0 )\n","base.dists.laplace.kurtosis":"var y = base.dists.laplace.kurtosis( 0.0, 1.0 )\ny = base.dists.laplace.kurtosis( 4.0, 2.0 )\ny = base.dists.laplace.kurtosis( NaN, 1.0 )\ny = base.dists.laplace.kurtosis( 0.0, NaN )\ny = base.dists.laplace.kurtosis( 0.0, 0.0 )\n","base.dists.laplace.Laplace":"var laplace = base.dists.laplace.Laplace( -2.0, 3.0 );\nlaplace.mu\nlaplace.b\nlaplace.entropy\nlaplace.kurtosis\nlaplace.mean\nlaplace.median\nlaplace.mode\nlaplace.skewness\nlaplace.stdev\nlaplace.variance\nlaplace.cdf( 0.8 )\nlaplace.logcdf( 0.8 )\nlaplace.logpdf( 1.0 )\nlaplace.mgf( 0.2 )\nlaplace.pdf( 2.0 )\nlaplace.quantile( 0.9 )\n","base.dists.laplace.logcdf":"var y = 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base.dists.logistic.median( 0.0, 0.0 )\n","base.dists.logistic.mgf":"var y = base.dists.logistic.mgf( 0.9, 0.0, 1.0 )\ny = base.dists.logistic.mgf( 0.1, 4.0, 4.0 )\ny = base.dists.logistic.mgf( -0.2, 4.0, 4.0 )\ny = base.dists.logistic.mgf( 0.5, 0.0, -1.0 )\ny = base.dists.logistic.mgf( 0.5, 0.0, 4.0 )\ny = base.dists.logistic.mgf( NaN, 0.0, 1.0 )\ny = base.dists.logistic.mgf( 0.0, NaN, 1.0 )\ny = base.dists.logistic.mgf( 0.0, 0.0, NaN )\n","base.dists.logistic.mgf.factory":"var mymgf = base.dists.logistic.mgf.factory( 10.0, 0.5 );\nvar y = mymgf( 0.5 )\ny = mymgf( 2.0 )\n","base.dists.logistic.mode":"var y = base.dists.logistic.mode( 0.0, 1.0 )\ny = base.dists.logistic.mode( 4.0, 2.0 )\ny = base.dists.logistic.mode( NaN, 1.0 )\ny = base.dists.logistic.mode( 0.0, NaN )\ny = base.dists.logistic.mode( 0.0, 0.0 )\n","base.dists.logistic.pdf":"var y = base.dists.logistic.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.logistic.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.logistic.pdf( NaN, 0.0, 1.0 )\ny = 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base.dists.logistic.skewness( 0.0, 1.0 )\ny = base.dists.logistic.skewness( 4.0, 2.0 )\ny = base.dists.logistic.skewness( NaN, 1.0 )\ny = base.dists.logistic.skewness( 0.0, NaN )\ny = base.dists.logistic.skewness( 0.0, 0.0 )\n","base.dists.logistic.stdev":"var y = base.dists.logistic.stdev( 0.0, 1.0 )\ny = base.dists.logistic.stdev( 4.0, 2.0 )\ny = base.dists.logistic.stdev( NaN, 1.0 )\ny = base.dists.logistic.stdev( 0.0, NaN )\ny = base.dists.logistic.stdev( 0.0, 0.0 )\n","base.dists.logistic.variance":"var y = base.dists.logistic.variance( 0.0, 1.0 )\ny = base.dists.logistic.variance( 4.0, 2.0 )\ny = base.dists.logistic.variance( NaN, 1.0 )\ny = base.dists.logistic.variance( 0.0, NaN )\ny = base.dists.logistic.variance( 0.0, 0.0 )\n","base.dists.lognormal.cdf":"var y = base.dists.lognormal.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.cdf( 5.0, 10.0, 3.0 )\ny = base.dists.lognormal.cdf( 2.0, 0.0, NaN )\ny = base.dists.lognormal.cdf( 2.0, NaN, 1.0 )\ny = base.dists.lognormal.cdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.cdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.cdf( 2.0, 0.0, 0.0 )\n","base.dists.lognormal.cdf.factory":"var myCDF = base.dists.lognormal.cdf.factory( 3.0, 1.5 );\nvar y = myCDF( 1.0 )\ny = myCDF( 4.0 )\n","base.dists.lognormal.entropy":"var y = base.dists.lognormal.entropy( 0.0, 1.0 )\ny = base.dists.lognormal.entropy( 5.0, 2.0 )\ny = base.dists.lognormal.entropy( NaN, 1.0 )\ny = base.dists.lognormal.entropy( 0.0, NaN )\ny = base.dists.lognormal.entropy( 0.0, 0.0 )\n","base.dists.lognormal.kurtosis":"var y = base.dists.lognormal.kurtosis( 0.0, 1.0 )\ny = base.dists.lognormal.kurtosis( 5.0, 2.0 )\ny = base.dists.lognormal.kurtosis( NaN, 1.0 )\ny = base.dists.lognormal.kurtosis( 0.0, NaN )\ny = base.dists.lognormal.kurtosis( 0.0, 0.0 )\n","base.dists.lognormal.LogNormal":"var lognormal = base.dists.lognormal.LogNormal( -2.0, 3.0 );\nlognormal.mu\nlognormal.sigma\nlognormal.entropy\nlognormal.kurtosis\nlognormal.mean\nlognormal.median\nlognormal.mode\nlognormal.skewness\nlognormal.stdev\nlognormal.variance\nlognormal.cdf( 0.8 )\nlognormal.logcdf( 0.8 )\nlognormal.logpdf( 2.0 )\nlognormal.pdf( 2.0 )\nlognormal.quantile( 0.9 )\n","base.dists.lognormal.logcdf":"var y = base.dists.lognormal.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.logcdf( 13.0, 4.0, 2.0 )\ny = base.dists.lognormal.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.logcdf( 0.0, 0.0, NaN )\ny = base.dists.lognormal.logcdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.logcdf( 2.0, 8.0, 0.0 )\ny = base.dists.lognormal.logcdf( 8.0, 8.0, 0.0 )\n","base.dists.lognormal.logcdf.factory":"var mylogcdf = base.dists.lognormal.logcdf.factory( 10.0, 2.0 );\nvar y = mylogcdf( 10.0 )\n","base.dists.lognormal.logpdf":"var y = base.dists.lognormal.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.logpdf( 1.0, 0.0, 1.0 )\ny = base.dists.lognormal.logpdf( 1.0, 3.0, 1.0 )\ny = base.dists.lognormal.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.lognormal.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.logpdf( 0.0, 0.0, NaN )\ny = base.dists.lognormal.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.logpdf( 2.0, 0.0, 0.0 )\n","base.dists.lognormal.logpdf.factory":"var mylogPDF = base.dists.lognormal.logpdf.factory( 4.0, 2.0 );\nvar y = mylogPDF( 10.0 )\ny = mylogPDF( 2.0 )\n","base.dists.lognormal.mean":"var y = base.dists.lognormal.mean( 0.0, 1.0 )\ny = base.dists.lognormal.mean( 4.0, 2.0 )\ny = base.dists.lognormal.mean( NaN, 1.0 )\ny = base.dists.lognormal.mean( 0.0, NaN )\ny = base.dists.lognormal.mean( 0.0, 0.0 )\n","base.dists.lognormal.median":"var y = base.dists.lognormal.median( 0.0, 1.0 )\ny = base.dists.lognormal.median( 5.0, 2.0 )\ny = base.dists.lognormal.median( NaN, 1.0 )\ny = base.dists.lognormal.median( 0.0, NaN )\ny = base.dists.lognormal.median( 0.0, 0.0 )\n","base.dists.lognormal.mode":"var y = base.dists.lognormal.mode( 0.0, 1.0 )\ny = base.dists.lognormal.mode( 5.0, 2.0 )\ny = base.dists.lognormal.mode( NaN, 1.0 )\ny = base.dists.lognormal.mode( 0.0, NaN )\ny = base.dists.lognormal.mode( 0.0, 0.0 )\n","base.dists.lognormal.pdf":"var y = base.dists.lognormal.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.pdf( 1.0, 0.0, 1.0 )\ny = base.dists.lognormal.pdf( 1.0, 3.0, 1.0 )\ny = base.dists.lognormal.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.lognormal.pdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.pdf( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.pdf( 0.0, 0.0, NaN )\ny = base.dists.lognormal.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.pdf( 2.0, 0.0, 0.0 )\n","base.dists.lognormal.pdf.factory":"var myPDF = base.dists.lognormal.pdf.factory( 4.0, 2.0 );\nvar y = myPDF( 10.0 )\ny = myPDF( 2.0 )\n","base.dists.lognormal.quantile":"var y = base.dists.lognormal.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.lognormal.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.quantile( 0.0, 0.0, NaN )\ny = base.dists.lognormal.quantile( 0.5, 0.0, -1.0 )\ny = base.dists.lognormal.quantile( 0.5, 0.0, 0.0 )\n","base.dists.lognormal.quantile.factory":"var myQuantile = base.dists.lognormal.quantile.factory( 4.0, 2.0 );\nvar y = myQuantile( 0.2 )\ny = myQuantile( 0.8 )\n","base.dists.lognormal.skewness":"var y = base.dists.lognormal.skewness( 0.0, 1.0 )\ny = base.dists.lognormal.skewness( 5.0, 2.0 )\ny = base.dists.lognormal.skewness( NaN, 1.0 )\ny = base.dists.lognormal.skewness( 0.0, NaN )\ny = base.dists.lognormal.skewness( 0.0, 0.0 )\n","base.dists.lognormal.stdev":"var y = base.dists.lognormal.stdev( 0.0, 1.0 )\ny = base.dists.lognormal.stdev( 4.0, 2.0 )\ny = base.dists.lognormal.stdev( NaN, 1.0 )\ny = base.dists.lognormal.stdev( 0.0, NaN )\ny = base.dists.lognormal.stdev( 0.0, 0.0 )\n","base.dists.lognormal.variance":"var y = base.dists.lognormal.variance( 0.0, 1.0 )\ny = base.dists.lognormal.variance( 4.0, 2.0 )\ny = base.dists.lognormal.variance( NaN, 1.0 )\ny = base.dists.lognormal.variance( 0.0, NaN )\ny = base.dists.lognormal.variance( 0.0, 0.0 )\n","base.dists.negativeBinomial.cdf":"var y = base.dists.negativeBinomial.cdf( 5.0, 20.0, 0.8 )\ny = base.dists.negativeBinomial.cdf( 21.0, 20.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( 5.0, 10.0, 0.4 )\ny = base.dists.negativeBinomial.cdf( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.cdf( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.cdf( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.cdf( 2.0, 0.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( 2.0, -2.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.cdf( 0.0, 20.0, NaN )\ny = base.dists.negativeBinomial.cdf( 2.0, 20, -1.0 )\ny = base.dists.negativeBinomial.cdf( 2.0, 20, 1.5 )\n","base.dists.negativeBinomial.cdf.factory":"var myCDF = base.dists.negativeBinomial.cdf.factory( 10, 0.5 );\nvar y = myCDF( 3.0 )\ny = myCDF( 11.0 )\n","base.dists.negativeBinomial.kurtosis":"var v = base.dists.negativeBinomial.kurtosis( 100, 0.2 )\nv = base.dists.negativeBinomial.kurtosis( 20, 0.5 )\n","base.dists.negativeBinomial.logpmf":"var y = base.dists.negativeBinomial.logpmf( 5.0, 20.0, 0.8 )\ny = base.dists.negativeBinomial.logpmf( 21.0, 20.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 5.0, 10.0, 0.4 )\ny = base.dists.negativeBinomial.logpmf( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.logpmf( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.logpmf( 2.0, 0.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 2.0, -2.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 2.0, 20, -1.0 )\ny = base.dists.negativeBinomial.logpmf( 2.0, 20, 1.5 )\ny = base.dists.negativeBinomial.logpmf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 0.0, 20.0, NaN )\n","base.dists.negativeBinomial.logpmf.factory":"var mylogPMF = base.dists.negativeBinomial.logpmf.factory( 10, 0.5 );\nvar y = mylogPMF( 3.0 )\ny = mylogPMF( 5.0 )\n","base.dists.negativeBinomial.mean":"var v = base.dists.negativeBinomial.mean( 100, 0.2 )\nv = base.dists.negativeBinomial.mean( 20, 0.5 )\n","base.dists.negativeBinomial.mgf":"var y = base.dists.negativeBinomial.mgf( 0.05, 20.0, 0.8 )\ny = base.dists.negativeBinomial.mgf( 0.1, 20.0, 0.1 )\ny = base.dists.negativeBinomial.mgf( 0.5, 10.0, 0.4 )\ny = base.dists.negativeBinomial.mgf( 0.1, 0.0, 0.5 )\ny = base.dists.negativeBinomial.mgf( 0.1, -2.0, 0.5 )\ny = base.dists.negativeBinomial.mgf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.mgf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.mgf( 0.0, 20.0, NaN )\ny = base.dists.negativeBinomial.mgf( 0.2, 20, -1.0 )\ny = base.dists.negativeBinomial.mgf( 0.2, 20, 1.5 )\n","base.dists.negativeBinomial.mgf.factory":"var myMGF = base.dists.negativeBinomial.mgf.factory( 4.3, 0.4 );\nvar y = myMGF( 0.2 )\ny = myMGF( 0.4 )\n","base.dists.negativeBinomial.mode":"var v = base.dists.negativeBinomial.mode( 100, 0.2 )\nv = base.dists.negativeBinomial.mode( 20, 0.5 )\n","base.dists.negativeBinomial.NegativeBinomial":"var nbinomial = base.dists.negativeBinomial.NegativeBinomial( 8.0, 0.5 );\nnbinomial.r\nnbinomial.p\nnbinomial.kurtosis\nnbinomial.mean\nnbinomial.mode\nnbinomial.skewness\nnbinomial.stdev\nnbinomial.variance\nnbinomial.cdf( 2.9 )\nnbinomial.logpmf( 3.0 )\nnbinomial.mgf( 0.2 )\nnbinomial.pmf( 3.0 )\nnbinomial.quantile( 0.8 )\n","base.dists.negativeBinomial.pmf":"var y = base.dists.negativeBinomial.pmf( 5.0, 20.0, 0.8 )\ny = base.dists.negativeBinomial.pmf( 21.0, 20.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 5.0, 10.0, 0.4 )\ny = base.dists.negativeBinomial.pmf( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.pmf( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.pmf( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.pmf( 2.0, 0.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 2.0, -2.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 2.0, 20, -1.0 )\ny = base.dists.negativeBinomial.pmf( 2.0, 20, 1.5 )\ny = base.dists.negativeBinomial.pmf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.pmf( 0.0, 20.0, NaN )\n","base.dists.negativeBinomial.pmf.factory":"var myPMF = base.dists.negativeBinomial.pmf.factory( 10, 0.5 );\nvar y = myPMF( 3.0 )\ny = myPMF( 5.0 )\n","base.dists.negativeBinomial.quantile":"var y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.2 )\ny = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.8 )\ny = base.dists.negativeBinomial.quantile( 0.5, 10.0, 0.4 )\ny = base.dists.negativeBinomial.quantile( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.quantile( 1.1, 20.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( -0.1, 20.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.quantile( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.quantile( 0.5, 0.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.5, -2.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.3, 20.0, -1.0 )\ny = base.dists.negativeBinomial.quantile( 0.3, 20.0, 1.5 )\ny = base.dists.negativeBinomial.quantile( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.3, NaN, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.3, 20.0, NaN )\n","base.dists.negativeBinomial.quantile.factory":"var myQuantile = base.dists.negativeBinomial.quantile.factory( 10.0, 0.5 );\nvar y = myQuantile( 0.1 )\ny = myQuantile( 0.9 )\n","base.dists.negativeBinomial.skewness":"var v = base.dists.negativeBinomial.skewness( 100, 0.2 )\nv = base.dists.negativeBinomial.skewness( 20, 0.5 )\n","base.dists.negativeBinomial.stdev":"var v = base.dists.negativeBinomial.stdev( 100, 0.2 )\nv = base.dists.negativeBinomial.stdev( 20, 0.5 )\n","base.dists.negativeBinomial.variance":"var v = base.dists.negativeBinomial.variance( 100, 0.2 )\nv = base.dists.negativeBinomial.variance( 20, 0.5 )\n","base.dists.normal.cdf":"var y = base.dists.normal.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.cdf( -1.0, -1.0, 2.0 )\ny = base.dists.normal.cdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.cdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.cdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.cdf( 0.0, 0.0, NaN )\ny = base.dists.normal.cdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.cdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.cdf( 8.0, 8.0, 0.0 )\ny = base.dists.normal.cdf( 10.0, 8.0, 0.0 )\n","base.dists.normal.cdf.factory":"var myCDF = base.dists.normal.cdf.factory( 10.0, 2.0 );\nvar y = myCDF( 10.0 )\n","base.dists.normal.entropy":"var y = base.dists.normal.entropy( 0.0, 1.0 )\ny = base.dists.normal.entropy( 4.0, 3.0 )\ny = base.dists.normal.entropy( NaN, 1.0 )\ny = base.dists.normal.entropy( 0.0, NaN )\ny = base.dists.normal.entropy( 0.0, 0.0 )\n","base.dists.normal.kurtosis":"var y = base.dists.normal.kurtosis( 0.0, 1.0 )\ny = base.dists.normal.kurtosis( 4.0, 3.0 )\ny = base.dists.normal.kurtosis( NaN, 1.0 )\ny = base.dists.normal.kurtosis( 0.0, NaN )\ny = base.dists.normal.kurtosis( 0.0, 0.0 )\n","base.dists.normal.logcdf":"var y = base.dists.normal.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.logcdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.logcdf( 0.0, 0.0, NaN )\ny = base.dists.normal.logcdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.logcdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.logcdf( 8.0, 8.0, 0.0 )\n","base.dists.normal.logcdf.factory":"var mylogcdf = base.dists.normal.logcdf.factory( 10.0, 2.0 );\nvar y = mylogcdf( 10.0 )\n","base.dists.normal.logpdf":"var y = base.dists.normal.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.logpdf( 0.0, 0.0, NaN )\ny = base.dists.normal.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.logpdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.logpdf( 8.0, 8.0, 0.0 )\n","base.dists.normal.logpdf.factory":"var myLogPDF = base.dists.normal.logpdf.factory( 10.0, 2.0 );\nvar y = myLogPDF( 10.0 )\n","base.dists.normal.mean":"var y = base.dists.normal.mean( 0.0, 1.0 )\ny = base.dists.normal.mean( 4.0, 2.0 )\ny = base.dists.normal.mean( NaN, 1.0 )\ny = base.dists.normal.mean( 0.0, NaN )\ny = base.dists.normal.mean( 0.0, 0.0 )\n","base.dists.normal.median":"var y = base.dists.normal.median( 0.0, 1.0 )\ny = base.dists.normal.median( 4.0, 2.0 )\ny = base.dists.normal.median( NaN, 1.0 )\ny = base.dists.normal.median( 0.0, NaN )\ny = base.dists.normal.median( 0.0, 0.0 )\n","base.dists.normal.mgf":"var y = base.dists.normal.mgf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.mgf( 0.0, 0.0, 1.0 )\ny = base.dists.normal.mgf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.mgf( NaN, 0.0, 1.0 )\ny = base.dists.normal.mgf( 0.0, NaN, 1.0 )\ny = base.dists.normal.mgf( 0.0, 0.0, NaN )\ny = base.dists.normal.mgf( 2.0, 0.0, 0.0 )\n","base.dists.normal.mgf.factory":"var myMGF = base.dists.normal.mgf.factory( 4.0, 2.0 );\nvar y = myMGF( 1.0 )\ny = myMGF( 0.5 )\n","base.dists.normal.mode":"var y = base.dists.normal.mode( 0.0, 1.0 )\ny = base.dists.normal.mode( 4.0, 2.0 )\ny = base.dists.normal.mode( NaN, 1.0 )\ny = base.dists.normal.mode( 0.0, NaN )\ny = base.dists.normal.mode( 0.0, 0.0 )\n","base.dists.normal.Normal":"var normal = base.dists.normal.Normal( -2.0, 3.0 );\nnormal.mu\nnormal.sigma\nnormal.entropy\nnormal.kurtosis\nnormal.mean\nnormal.median\nnormal.mode\nnormal.skewness\nnormal.stdev\nnormal.variance\nnormal.cdf( 0.8 )\nnormal.logcdf( 0.8 )\nnormal.logpdf( 2.0 )\nnormal.mgf( 0.2 )\nnormal.pdf( 2.0 )\nnormal.quantile( 0.9 )\n","base.dists.normal.pdf":"var y = base.dists.normal.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.pdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.pdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.pdf( 0.0, 0.0, NaN )\ny = base.dists.normal.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.pdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.pdf( 8.0, 8.0, 0.0 )\n","base.dists.normal.pdf.factory":"var myPDF = base.dists.normal.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\n","base.dists.normal.quantile":"var y = base.dists.normal.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.normal.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.normal.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.normal.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.normal.quantile( NaN, 0.0, 1.0 )\ny = base.dists.normal.quantile( 0.0, NaN, 1.0 )\ny = base.dists.normal.quantile( 0.0, 0.0, NaN )\ny = base.dists.normal.quantile( 0.5, 0.0, -1.0 )\ny = base.dists.normal.quantile( 0.3, 8.0, 0.0 )\ny = base.dists.normal.quantile( 0.9, 8.0, 0.0 )\n","base.dists.normal.quantile.factory":"var myQuantile = base.dists.normal.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.normal.skewness":"var y = base.dists.normal.skewness( 0.0, 1.0 )\ny = base.dists.normal.skewness( 4.0, 3.0 )\ny = base.dists.normal.skewness( NaN, 1.0 )\ny = base.dists.normal.skewness( 0.0, NaN )\ny = base.dists.normal.skewness( 0.0, 0.0 )\n","base.dists.normal.stdev":"var y = base.dists.normal.stdev( 0.0, 1.0 )\ny = base.dists.normal.stdev( 4.0, 3.0 )\ny = base.dists.normal.stdev( NaN, 1.0 )\ny = base.dists.normal.stdev( 0.0, NaN )\ny = base.dists.normal.stdev( 0.0, 0.0 )\n","base.dists.normal.variance":"var y = base.dists.normal.variance( 0.0, 1.0 )\ny = base.dists.normal.variance( 4.0, 3.0 )\ny = base.dists.normal.variance( NaN, 1.0 )\ny = base.dists.normal.variance( 0.0, NaN )\ny = base.dists.normal.variance( 0.0, 0.0 )\n","base.dists.pareto1.cdf":"var y = base.dists.pareto1.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.pareto1.cdf( 5.0, 2.0, 4.0 )\ny = base.dists.pareto1.cdf( 4.0, 2.0, 2.0 )\ny = base.dists.pareto1.cdf( 1.9, 2.0, 2.0 )\ny = base.dists.pareto1.cdf( PINF, 4.0, 2.0 )\ny = base.dists.pareto1.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.pareto1.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.pareto1.cdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.cdf( 0.0, NaN, 1.0 )\ny = base.dists.pareto1.cdf( 0.0, 1.0, NaN )\n","base.dists.pareto1.cdf.factory":"var myCDF = base.dists.pareto1.cdf.factory( 10.0, 2.0 );\nvar y = myCDF( 3.0 )\ny = myCDF( 2.5 )\n","base.dists.pareto1.entropy":"var v = base.dists.pareto1.entropy( 0.8, 1.0 )\nv = base.dists.pareto1.entropy( 4.0, 12.0 )\nv = base.dists.pareto1.entropy( 8.0, 2.0 )\n","base.dists.pareto1.kurtosis":"var v = base.dists.pareto1.kurtosis( 5.0, 1.0 )\nv = base.dists.pareto1.kurtosis( 4.5, 12.0 )\nv = base.dists.pareto1.kurtosis( 8.0, 2.0 )\n","base.dists.pareto1.logcdf":"var y = base.dists.pareto1.logcdf( 2.0, 1.0, 1.0 )\ny = base.dists.pareto1.logcdf( 5.0, 2.0, 4.0 )\ny = base.dists.pareto1.logcdf( 4.0, 2.0, 2.0 )\ny = base.dists.pareto1.logcdf( 1.9, 2.0, 2.0 )\ny = base.dists.pareto1.logcdf( PINF, 4.0, 2.0 )\ny = base.dists.pareto1.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.pareto1.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.pareto1.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.pareto1.logcdf( 0.0, 1.0, NaN )\n","base.dists.pareto1.logcdf.factory":"var mylogCDF = base.dists.pareto1.logcdf.factory( 10.0, 2.0 );\nvar y = mylogCDF( 3.0 )\ny = mylogCDF( 2.5 )\n","base.dists.pareto1.logpdf":"var y = base.dists.pareto1.logpdf( 4.0, 1.0, 1.0 )\ny = base.dists.pareto1.logpdf( 20.0, 1.0, 10.0 )\ny = base.dists.pareto1.logpdf( 7.0, 2.0, 6.0 )\ny = base.dists.pareto1.logpdf( 7.0, 6.0, 3.0 )\ny = base.dists.pareto1.logpdf( 1.0, 4.0, 2.0 )\ny = base.dists.pareto1.logpdf( 1.5, 4.0, 2.0 )\ny = base.dists.pareto1.logpdf( 0.5, -1.0, 0.5 )\ny = base.dists.pareto1.logpdf( 0.5, 0.5, -1.0 )\ny = base.dists.pareto1.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.logpdf( 0.5, NaN, 1.0 )\ny = base.dists.pareto1.logpdf( 0.5, 1.0, NaN )\n","base.dists.pareto1.logpdf.factory":"var mylogPDF = base.dists.pareto1.logpdf.factory( 0.5, 0.5 );\nvar y = mylogPDF( 0.8 )\ny = mylogPDF( 2.0 )\n","base.dists.pareto1.mean":"var v = base.dists.pareto1.mean( 0.8, 1.0 )\nv = base.dists.pareto1.mean( 4.0, 12.0 )\nv = base.dists.pareto1.mean( 8.0, 2.0 )\n","base.dists.pareto1.median":"var v = base.dists.pareto1.median( 0.8, 1.0 )\nv = base.dists.pareto1.median( 4.0, 12.0 )\nv = base.dists.pareto1.median( 8.0, 2.0 )\n","base.dists.pareto1.mode":"var v = base.dists.pareto1.mode( 0.8, 1.0 )\nv = base.dists.pareto1.mode( 4.0, 12.0 )\nv = base.dists.pareto1.mode( 8.0, 2.0 )\n","base.dists.pareto1.Pareto1":"var pareto1 = base.dists.pareto1.Pareto1( 6.0, 5.0 );\npareto1.alpha\npareto1.beta\npareto1.entropy\npareto1.kurtosis\npareto1.mean\npareto1.median\npareto1.mode\npareto1.skewness\npareto1.variance\npareto1.cdf( 7.0 )\npareto1.logcdf( 7.0 )\npareto1.logpdf( 5.0 )\npareto1.pdf( 5.0 )\npareto1.quantile( 0.8 )\n","base.dists.pareto1.pdf":"var y = base.dists.pareto1.pdf( 4.0, 1.0, 1.0 )\ny = base.dists.pareto1.pdf( 20.0, 1.0, 10.0 )\ny = base.dists.pareto1.pdf( 7.0, 2.0, 6.0 )\ny = base.dists.pareto1.pdf( 7.0, 6.0, 3.0 )\ny = base.dists.pareto1.pdf( 1.0, 4.0, 2.0 )\ny = base.dists.pareto1.pdf( 1.5, 4.0, 2.0 )\ny = base.dists.pareto1.pdf( 0.5, -1.0, 0.5 )\ny = base.dists.pareto1.pdf( 0.5, 0.5, -1.0 )\ny = base.dists.pareto1.pdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.pdf( 0.5, NaN, 1.0 )\ny = base.dists.pareto1.pdf( 0.5, 1.0, NaN )\n","base.dists.pareto1.pdf.factory":"var myPDF = base.dists.pareto1.pdf.factory( 0.5, 0.5 );\nvar y = myPDF( 0.8 )\ny = myPDF( 2.0 )\n","base.dists.pareto1.quantile":"var y = base.dists.pareto1.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.pareto1.quantile( 0.8, 1.0, 10.0 )\ny = base.dists.pareto1.quantile( 0.1, 1.0, 10.0 )\ny = base.dists.pareto1.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.pareto1.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.pareto1.quantile( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.quantile( 0.5, NaN, 1.0 )\ny = base.dists.pareto1.quantile( 0.5, 1.0, NaN )\ny = base.dists.pareto1.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.pareto1.quantile( 0.5, 1.0, -1.0 )\n","base.dists.pareto1.quantile.factory":"var myQuantile = base.dists.pareto1.quantile.factory( 2.5, 0.5 );\nvar y = myQuantile( 0.5 )\ny = myQuantile( 0.8 )\n","base.dists.pareto1.skewness":"var v = base.dists.pareto1.skewness( 3.5, 1.0 )\nv = base.dists.pareto1.skewness( 4.0, 12.0 )\nv = base.dists.pareto1.skewness( 8.0, 2.0 )\n","base.dists.pareto1.stdev":"var v = base.dists.pareto1.stdev( 0.8, 1.0 )\nv = base.dists.pareto1.stdev( 4.0, 12.0 )\nv = base.dists.pareto1.stdev( 8.0, 2.0 )\n","base.dists.pareto1.variance":"var v = base.dists.pareto1.variance( 0.8, 1.0 )\nv = base.dists.pareto1.variance( 4.0, 12.0 )\nv = base.dists.pareto1.variance( 8.0, 2.0 )\n","base.dists.poisson.cdf":"var y = base.dists.poisson.cdf( 2.0, 0.5 )\ny = base.dists.poisson.cdf( 2.0, 10.0 )\ny = base.dists.poisson.cdf( -1.0, 4.0 )\ny = base.dists.poisson.cdf( NaN, 1.0 )\ny = base.dists.poisson.cdf( 0.0, NaN )\ny = base.dists.poisson.cdf( 2.0, -1.0 )\ny = base.dists.poisson.cdf( -2.0, 0.0 )\ny = base.dists.poisson.cdf( 0.0, 0.0 )\ny = base.dists.poisson.cdf( 10.0, 0.0 )\n","base.dists.poisson.cdf.factory":"var mycdf = base.dists.poisson.cdf.factory( 5.0 );\nvar y = mycdf( 3.0 )\ny = mycdf( 8.0 )\n","base.dists.poisson.entropy":"var v = base.dists.poisson.entropy( 11.0 )\nv = base.dists.poisson.entropy( 4.5 )\n","base.dists.poisson.kurtosis":"var v = base.dists.poisson.kurtosis( 11.0 )\nv = base.dists.poisson.kurtosis( 4.5 )\n","base.dists.poisson.logpmf":"var y = base.dists.poisson.logpmf( 4.0, 3.0 )\ny = base.dists.poisson.logpmf( 1.0, 3.0 )\ny = base.dists.poisson.logpmf( -1.0, 2.0 )\ny = base.dists.poisson.logpmf( 0.0, NaN )\ny = base.dists.poisson.logpmf( NaN, 0.5 )\ny = base.dists.poisson.logpmf( 2.0, -0.5 )\ny = base.dists.poisson.logpmf( 2.0, 0.0 )\ny = base.dists.poisson.logpmf( 0.0, 0.0 )\n","base.dists.poisson.logpmf.factory":"var mylogpmf = base.dists.poisson.logpmf.factory( 1.0 );\nvar y = mylogpmf( 3.0 )\ny = mylogpmf( 1.0 )\n","base.dists.poisson.mean":"var v = base.dists.poisson.mean( 11.0 )\nv = base.dists.poisson.mean( 4.5 )\n","base.dists.poisson.median":"var v = base.dists.poisson.median( 11.0 )\nv = base.dists.poisson.median( 4.5 )\n","base.dists.poisson.mgf":"var y = base.dists.poisson.mgf( 1.0, 1.5 )\ny = base.dists.poisson.mgf( 0.5, 0.5 )\ny = base.dists.poisson.mgf( NaN, 0.5 )\ny = base.dists.poisson.mgf( 0.0, NaN )\ny = base.dists.poisson.mgf( -2.0, -1.0 )\n","base.dists.poisson.mgf.factory":"var myMGF = base.dists.poisson.mgf.factory( 2.0 );\nvar y = myMGF( 0.1 )\n","base.dists.poisson.mode":"var v = base.dists.poisson.mode( 11.0 )\nv = base.dists.poisson.mode( 4.5 )\n","base.dists.poisson.pmf":"var y = base.dists.poisson.pmf( 4.0, 3.0 )\ny = base.dists.poisson.pmf( 1.0, 3.0 )\ny = base.dists.poisson.pmf( -1.0, 2.0 )\ny = base.dists.poisson.pmf( 0.0, NaN )\ny = base.dists.poisson.pmf( NaN, 0.5 )\ny = base.dists.poisson.pmf( 2.0, -0.5 )\ny = base.dists.poisson.pmf( 2.0, 0.0 )\ny = base.dists.poisson.pmf( 0.0, 0.0 )\n","base.dists.poisson.pmf.factory":"var mypmf = base.dists.poisson.pmf.factory( 1.0 );\nvar y = mypmf( 3.0 )\ny = mypmf( 1.0 )\n","base.dists.poisson.Poisson":"var poisson = base.dists.poisson.Poisson( 6.0 );\npoisson.lambda\npoisson.entropy\npoisson.kurtosis\npoisson.mean\npoisson.median\npoisson.mode\npoisson.skewness\npoisson.stdev\npoisson.variance\npoisson.cdf( 4.0 )\npoisson.logpmf( 2.0 )\npoisson.mgf( 0.5 )\npoisson.pmf( 2.0 )\npoisson.quantile( 0.5 )\n","base.dists.poisson.quantile":"var y = base.dists.poisson.quantile( 0.5, 2.0 )\ny = base.dists.poisson.quantile( 0.9, 4.0 )\ny = base.dists.poisson.quantile( 0.1, 200.0 )\ny = base.dists.poisson.quantile( 1.1, 0.0 )\ny = base.dists.poisson.quantile( -0.2, 0.0 )\ny = base.dists.poisson.quantile( NaN, 0.5 )\ny = base.dists.poisson.quantile( 0.0, NaN )\ny = base.dists.poisson.quantile( 2.0, -1.0 )\ny = base.dists.poisson.quantile( 0.1, 0.0 )\ny = base.dists.poisson.quantile( 0.9, 0.0 )\n","base.dists.poisson.quantile.factory":"var myQuantile = base.dists.poisson.quantile.factory( 0.4 );\nvar y = myQuantile( 0.4 )\ny = myQuantile( 1.0 )\n","base.dists.poisson.skewness":"var v = base.dists.poisson.skewness( 11.0 )\nv = base.dists.poisson.skewness( 4.5 )\n","base.dists.poisson.stdev":"var v = base.dists.poisson.stdev( 11.0 )\nv = base.dists.poisson.stdev( 4.5 )\n","base.dists.poisson.variance":"var v = base.dists.poisson.variance( 11.0 )\nv = base.dists.poisson.variance( 4.5 )\n","base.dists.rayleigh.cdf":"var y = base.dists.rayleigh.cdf( 2.0, 3.0 )\ny = base.dists.rayleigh.cdf( 1.0, 2.0 )\ny = base.dists.rayleigh.cdf( -1.0, 4.0 )\ny = base.dists.rayleigh.cdf( NaN, 1.0 )\ny = base.dists.rayleigh.cdf( 0.0, NaN )\ny = base.dists.rayleigh.cdf( 2.0, -1.0 )\ny = base.dists.rayleigh.cdf( -2.0, 0.0 )\ny = base.dists.rayleigh.cdf( 0.0, 0.0 )\ny = base.dists.rayleigh.cdf( 2.0, 0.0 )\n","base.dists.rayleigh.cdf.factory":"var myCDF = base.dists.rayleigh.cdf.factory( 0.5 );\nvar y = myCDF( 1.0 )\ny = myCDF( 0.5 )\n","base.dists.rayleigh.entropy":"var v = base.dists.rayleigh.entropy( 11.0 )\nv = base.dists.rayleigh.entropy( 4.5 )\n","base.dists.rayleigh.kurtosis":"var v = base.dists.rayleigh.kurtosis( 11.0 )\nv = base.dists.rayleigh.kurtosis( 4.5 )\n","base.dists.rayleigh.logcdf":"var y = base.dists.rayleigh.logcdf( 2.0, 3.0 )\ny = base.dists.rayleigh.logcdf( 1.0, 2.0 )\ny = base.dists.rayleigh.logcdf( -1.0, 4.0 )\ny = base.dists.rayleigh.logcdf( NaN, 1.0 )\ny = base.dists.rayleigh.logcdf( 0.0, NaN )\ny = base.dists.rayleigh.logcdf( 2.0, -1.0 )\n","base.dists.rayleigh.logcdf.factory":"var mylogcdf = base.dists.rayleigh.logcdf.factory( 0.5 );\nvar y = mylogcdf( 1.0 )\ny = mylogcdf( 0.5 )\n","base.dists.rayleigh.logpdf":"var y = base.dists.rayleigh.logpdf( 0.3, 1.0 )\ny = base.dists.rayleigh.logpdf( 2.0, 0.8 )\ny = base.dists.rayleigh.logpdf( -1.0, 0.5 )\ny = base.dists.rayleigh.logpdf( 0.0, NaN )\ny = base.dists.rayleigh.logpdf( NaN, 2.0 )\ny = base.dists.rayleigh.logpdf( 2.0, -1.0 )\n","base.dists.rayleigh.logpdf.factory":"var mylogpdf = base.dists.rayleigh.logpdf.factory( 4.0 );\nvar y = mylogpdf( 6.0 )\ny = mylogpdf( 4.0 )\n","base.dists.rayleigh.mean":"var v = base.dists.rayleigh.mean( 11.0 )\nv = base.dists.rayleigh.mean( 4.5 )\n","base.dists.rayleigh.median":"var v = base.dists.rayleigh.median( 11.0 )\nv = base.dists.rayleigh.median( 4.5 )\n","base.dists.rayleigh.mgf":"var y = base.dists.rayleigh.mgf( 1.0, 3.0 )\ny = base.dists.rayleigh.mgf( 1.0, 2.0 )\ny = base.dists.rayleigh.mgf( -1.0, 4.0 )\ny = base.dists.rayleigh.mgf( NaN, 1.0 )\ny = base.dists.rayleigh.mgf( 0.0, NaN )\ny = base.dists.rayleigh.mgf( 0.5, -1.0 )\n","base.dists.rayleigh.mgf.factory":"var myMGF = base.dists.rayleigh.mgf.factory( 0.5 );\nvar y = myMGF( 1.0 )\ny = myMGF( 0.5 )\n","base.dists.rayleigh.mode":"var v = base.dists.rayleigh.mode( 11.0 )\nv = base.dists.rayleigh.mode( 4.5 )\n","base.dists.rayleigh.pdf":"var y = base.dists.rayleigh.pdf( 0.3, 1.0 )\ny = base.dists.rayleigh.pdf( 2.0, 0.8 )\ny = base.dists.rayleigh.pdf( -1.0, 0.5 )\ny = base.dists.rayleigh.pdf( 0.0, NaN )\ny = base.dists.rayleigh.pdf( NaN, 2.0 )\ny = base.dists.rayleigh.pdf( 2.0, -1.0 )\ny = base.dists.rayleigh.pdf( -2.0, 0.0 )\ny = base.dists.rayleigh.pdf( 0.0, 0.0 )\ny = base.dists.rayleigh.pdf( 2.0, 0.0 )\n","base.dists.rayleigh.pdf.factory":"var myPDF = base.dists.rayleigh.pdf.factory( 4.0 );\nvar y = myPDF( 6.0 )\ny = myPDF( 4.0 )\n","base.dists.rayleigh.quantile":"var y = base.dists.rayleigh.quantile( 0.8, 1.0 )\ny = base.dists.rayleigh.quantile( 0.5, 4.0 )\ny = base.dists.rayleigh.quantile( 1.1, 1.0 )\ny = base.dists.rayleigh.quantile( -0.2, 1.0 )\ny = base.dists.rayleigh.quantile( NaN, 1.0 )\ny = base.dists.rayleigh.quantile( 0.0, NaN )\ny = base.dists.rayleigh.quantile( 0.5, -1.0 )\n","base.dists.rayleigh.quantile.factory":"var myQuantile = base.dists.rayleigh.quantile.factory( 0.4 );\nvar y = myQuantile( 0.4 )\ny = myQuantile( 1.0 )\n","base.dists.rayleigh.Rayleigh":"var rayleigh = base.dists.rayleigh.Rayleigh( 6.0 );\nrayleigh.sigma\nrayleigh.entropy\nrayleigh.kurtosis\nrayleigh.mean\nrayleigh.median\nrayleigh.mode\nrayleigh.skewness\nrayleigh.stdev\nrayleigh.variance\nrayleigh.cdf( 1.0 )\nrayleigh.logcdf( 1.0 )\nrayleigh.logpdf( 1.5 )\nrayleigh.mgf( -0.5 )\nrayleigh.pdf( 1.5 )\nrayleigh.quantile( 0.5 )\n","base.dists.rayleigh.skewness":"var v = base.dists.rayleigh.skewness( 11.0 )\nv = base.dists.rayleigh.skewness( 4.5 )\n","base.dists.rayleigh.stdev":"var v = base.dists.rayleigh.stdev( 9.0 )\nv = base.dists.rayleigh.stdev( 4.5 )\n","base.dists.rayleigh.variance":"var v = base.dists.rayleigh.variance( 9.0 )\nv = base.dists.rayleigh.variance( 4.5 )\n","base.dists.signrank.cdf":"var y = base.dists.signrank.cdf( 3, 7 )\ny = base.dists.signrank.cdf( 1.8, 3 )\ny = base.dists.signrank.cdf( -1.0, 40 )\ny = base.dists.signrank.cdf( NaN, 10 )\ny = base.dists.signrank.cdf( 0.0, NaN )\n","base.dists.signrank.cdf.factory":"var myCDF = base.dists.signrank.cdf.factory( 8 );\nvar y = myCDF( 5.7 )\ny = myCDF( 2.2 )\n","base.dists.signrank.pdf":"var y = base.dists.signrank.pdf( 3, 7 )\ny = base.dists.signrank.pdf( 1.8, 3 )\ny = base.dists.signrank.pdf( -1.0, 40 )\ny = base.dists.signrank.pdf( NaN, 10 )\ny = base.dists.signrank.pdf( 0.0, NaN )\n","base.dists.signrank.pdf.factory":"var myPDF = base.dists.signrank.pdf.factory( 8 );\nvar y = myPDF( 6.0 )\ny = myPDF( 2.0 )\n","base.dists.signrank.quantile":"var y = base.dists.signrank.quantile( 0.8, 5 )\ny = base.dists.signrank.quantile( 0.5, 4 )\ny = base.dists.signrank.quantile( 1.1, 5 )\ny = base.dists.signrank.quantile( -0.2, 5 )\ny = base.dists.signrank.quantile( NaN, 5 )\ny = base.dists.signrank.quantile( 0.0, NaN )\n","base.dists.signrank.quantile.factory":"var myQuantile = base.dists.signrank.quantile.factory( 8 );\nvar y = myQuantile( 0.4 )\ny = myQuantile( 1.0 )\n","base.dists.studentizedRange.cdf":"var y = base.dists.studentizedRange.cdf( 0.5, 3.0, 2.0 )\ny = base.dists.studentizedRange.cdf( 12.1, 17.0, 2.0 )\n","base.dists.studentizedRange.cdf.factory":"var mycdf = base.dists.studentizedRange.cdf.factory( 3.0, 2.0 );\nvar y = mycdf( 3.0 )\ny = mycdf( 1.0 )\n","base.dists.studentizedRange.quantile":"var y = quantile( 0.5, 3.0, 2.0 )\ny = quantile( 0.9, 17.0, 2.0 )\ny = quantile( 0.5, 3.0, 2.0, 2 )\ny = base.dists.studentizedRange.quantile( -0.2, 3.0, 3.0 )\ny = base.dists.studentizedRange.quantile( NaN, 2.0, 2.0 )\ny = base.dists.studentizedRange.quantile( 0.0, NaN, 2.0 )\ny = base.dists.studentizedRange.quantile( 0.5, -1.0, 2.0 )\n","base.dists.studentizedRange.quantile.factory":"var myQuantile = quantile.factory( 3.0, 3.0 );\nvar y = myQuantile( 0.5 )\n   ~1.791\ny = myQuantile( 0.8 )\n   ~3.245\n","base.dists.t.cdf":"var y = base.dists.t.cdf( 2.0, 0.1 )\ny = base.dists.t.cdf( 1.0, 2.0 )\ny = base.dists.t.cdf( -1.0, 4.0 )\ny = base.dists.t.cdf( NaN, 1.0 )\ny = base.dists.t.cdf( 0.0, NaN )\ny = base.dists.t.cdf( 2.0, -1.0 )\n","base.dists.t.cdf.factory":"var mycdf = base.dists.t.cdf.factory( 0.5 );\nvar y = mycdf( 3.0 )\ny = mycdf( 1.0 )\n","base.dists.t.entropy":"var v = base.dists.t.entropy( 11.0 )\nv = base.dists.t.entropy( 4.5 )\n","base.dists.t.kurtosis":"var v = base.dists.t.kurtosis( 11.0 )\nv = base.dists.t.kurtosis( 4.5 )\n","base.dists.t.logcdf":"var y = base.dists.t.logcdf( 2.0, 0.1 )\ny = base.dists.t.logcdf( 1.0, 2.0 )\ny = base.dists.t.logcdf( -1.0, 4.0 )\ny = base.dists.t.logcdf( NaN, 1.0 )\ny = base.dists.t.logcdf( 0.0, NaN )\ny = base.dists.t.logcdf( 2.0, -1.0 )\n","base.dists.t.logcdf.factory":"var mylogcdf = base.dists.t.logcdf.factory( 0.5 );\nvar y = mylogcdf( 3.0 )\ny = mylogcdf( 1.0 )\n","base.dists.t.logpdf":"var y = base.dists.t.logpdf( 0.3, 4.0 )\ny = base.dists.t.logpdf( 2.0, 0.7 )\ny = base.dists.t.logpdf( -1.0, 0.5 )\ny = base.dists.t.logpdf( 0.0, NaN )\ny = base.dists.t.logpdf( NaN, 2.0 )\ny = base.dists.t.logpdf( 2.0, -1.0 )\n","base.dists.t.logpdf.factory":"var mylogPDF = base.dists.t.logpdf.factory( 3.0 );\nvar y = mylogPDF( 1.0 )\n","base.dists.t.mean":"var v = base.dists.t.mean( 11.0 )\nv = base.dists.t.mean( 4.5 )\n","base.dists.t.median":"var v = base.dists.t.median( 11.0 )\nv = base.dists.t.median( 4.5 )\n","base.dists.t.mode":"var v = base.dists.t.mode( 11.0 )\nv = base.dists.t.mode( 4.5 )\n","base.dists.t.pdf":"var y = base.dists.t.pdf( 0.3, 4.0 )\ny = base.dists.t.pdf( 2.0, 0.7 )\ny = base.dists.t.pdf( -1.0, 0.5 )\ny = base.dists.t.pdf( 0.0, NaN )\ny = base.dists.t.pdf( NaN, 2.0 )\ny = base.dists.t.pdf( 2.0, -1.0 )\n","base.dists.t.pdf.factory":"var myPDF = base.dists.t.pdf.factory( 3.0 );\nvar y = myPDF( 1.0 )\n","base.dists.t.quantile":"var y = base.dists.t.quantile( 0.8, 1.0 )\ny = base.dists.t.quantile( 0.1, 1.0 )\ny = base.dists.t.quantile( 0.5, 0.1 )\ny = base.dists.t.quantile( -0.2, 0.1 )\ny = base.dists.t.quantile( NaN, 1.0 )\ny = base.dists.t.quantile( 0.0, NaN )\ny = base.dists.t.quantile( 0.5, -1.0 )\n","base.dists.t.quantile.factory":"var myQuantile = base.dists.t.quantile.factory( 4.0 );\nvar y = myQuantile( 0.2 )\ny = myQuantile( 0.9 )\n","base.dists.t.skewness":"var v = base.dists.t.skewness( 11.0 )\nv = base.dists.t.skewness( 4.5 )\n","base.dists.t.stdev":"var v = base.dists.t.stdev( 9.0 )\nv = base.dists.t.stdev( 4.5 )\n","base.dists.t.T":"var t = base.dists.t.T( 6.0 );\nt.v\nt.entropy\nt.kurtosis\nt.mean\nt.median\nt.mode\nt.skewness\nt.stdev\nt.variance\nt.cdf( 1.0 )\nt.logcdf( 1.0 )\nt.logpdf( 1.5 )\nt.pdf( 1.5 )\nt.quantile( 0.8 )\n","base.dists.t.variance":"var v = base.dists.t.variance( 9.0 )\nv = base.dists.t.variance( 4.5 )\n","base.dists.triangular.cdf":"var y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.cdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.cdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.cdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.cdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.cdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.cdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.cdf( 2.0, 1.0, 0.0, 1.5 )\n","base.dists.triangular.cdf.factory":"var mycdf = base.dists.triangular.cdf.factory( 0.0, 10.0, 2.0 );\nvar y = mycdf( 0.5 )\ny = mycdf( 8.0 )\n","base.dists.triangular.entropy":"var v = base.dists.triangular.entropy( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.entropy( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.entropy( 2.0, 8.0, 5.0 )\n","base.dists.triangular.kurtosis":"var v = base.dists.triangular.kurtosis( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.kurtosis( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.kurtosis( 2.0, 8.0, 5.0 )\n","base.dists.triangular.logcdf":"var y = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.logcdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.logcdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logcdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.logcdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.logcdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, 1.5 )\n","base.dists.triangular.logcdf.factory":"var mylogcdf = base.dists.triangular.logcdf.factory( 0.0, 10.0, 2.0 );\nvar y = mylogcdf( 0.5 )\ny = mylogcdf( 8.0 )\n","base.dists.triangular.logpdf":"var y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.logpdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.logpdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.logpdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.logpdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.logpdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, 1.5 )\n","base.dists.triangular.logpdf.factory":"var mylogpdf = base.dists.triangular.logpdf.factory( 0.0, 10.0, 5.0 );\nvar y = mylogpdf( 2.0 )\ny = mylogpdf( 12.0 )\n","base.dists.triangular.mean":"var v = base.dists.triangular.mean( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.mean( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.mean( 2.0, 8.0, 5.0 )\n","base.dists.triangular.median":"var v = base.dists.triangular.median( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.median( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.median( 2.0, 8.0, 5.0 )\n","base.dists.triangular.mgf":"var y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.mgf( -0.3, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.mgf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.mgf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.mgf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.mgf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.mgf( 0.5, 1.0, 0.0, NaN )\ny = base.dists.triangular.mgf( 0.5, 1.0, 0.0, 1.5 )\n","base.dists.triangular.mgf.factory":"var mymgf = base.dists.triangular.mgf.factory( 0.0, 2.0, 1.0 );\nvar y = mymgf( -1.0 )\ny = mymgf( 2.0 )\n","base.dists.triangular.mode":"var v = base.dists.triangular.mode( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.mode( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.mode( 2.0, 8.0, 5.0 )\n","base.dists.triangular.pdf":"var y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.pdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.pdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.pdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.pdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.pdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.pdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.pdf( 2.0, 1.0, 0.0, 1.5 )\n","base.dists.triangular.pdf.factory":"var mypdf = base.dists.triangular.pdf.factory( 0.0, 10.0, 5.0 );\nvar y = mypdf( 2.0 )\ny = mypdf( 12.0 )\n","base.dists.triangular.quantile":"var y = base.dists.triangular.quantile( 0.9, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.quantile( 0.1, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.quantile( 0.1, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.quantile( 0.8, 0.0, 20.0, 0.0 )\ny = base.dists.triangular.quantile( 1.1, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.quantile( -0.1, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.quantile( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.quantile( 0.3, NaN, 1.0, 0.5 )\ny = base.dists.triangular.quantile( 0.3, 0.0, NaN, 0.5 )\ny = base.dists.triangular.quantile( 0.3, 1.0, 0.0, NaN )\ny = base.dists.triangular.quantile( 0.3, 1.0, 0.0, 1.5 )\n","base.dists.triangular.quantile.factory":"var myquantile = base.dists.triangular.quantile.factory( 2.0, 4.0, 2.5 );\nvar y = myquantile( 0.4 )\ny = myquantile( 0.8 )\n","base.dists.triangular.skewness":"var v = base.dists.triangular.skewness( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.skewness( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.skewness( 2.0, 8.0, 5.0 )\n","base.dists.triangular.stdev":"var v = base.dists.triangular.stdev( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.stdev( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.stdev( 2.0, 8.0, 5.0 )\n","base.dists.triangular.Triangular":"var triangular = base.dists.triangular.Triangular( 0.0, 1.0, 0.5 );\ntriangular.a\ntriangular.b\ntriangular.c\ntriangular.entropy\ntriangular.kurtosis\ntriangular.mean\ntriangular.median\ntriangular.mode\ntriangular.skewness\ntriangular.stdev\ntriangular.variance\ntriangular.cdf( 0.8 )\ntriangular.logcdf( 0.8 )\ntriangular.logpdf( 0.8 )\ntriangular.mgf( 0.8 )\ntriangular.pdf( 0.8 )\ntriangular.quantile( 0.8 )\n","base.dists.triangular.variance":"var v = base.dists.triangular.variance( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.variance( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.variance( 2.0, 8.0, 5.0 )\n","base.dists.uniform.cdf":"var y = base.dists.uniform.cdf( 9.0, 0.0, 10.0 )\ny = base.dists.uniform.cdf( 0.5, 0.0, 2.0 )\ny = base.dists.uniform.cdf( PINF, 2.0, 4.0 )\ny = base.dists.uniform.cdf( NINF, 2.0, 4.0 )\ny = base.dists.uniform.cdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.cdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.cdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.cdf( 2.0, 1.0, 0.0 )\n","base.dists.uniform.cdf.factory":"var mycdf = base.dists.uniform.cdf.factory( 0.0, 10.0 );\nvar y = mycdf( 0.5 )\ny = mycdf( 8.0 )\n","base.dists.uniform.entropy":"var v = base.dists.uniform.entropy( 0.0, 1.0 )\nv = base.dists.uniform.entropy( 4.0, 12.0 )\nv = base.dists.uniform.entropy( 2.0, 8.0 )\n","base.dists.uniform.kurtosis":"var v = base.dists.uniform.kurtosis( 0.0, 1.0 )\nv = base.dists.uniform.kurtosis( 4.0, 12.0 )\nv = base.dists.uniform.kurtosis( 2.0, 8.0 )\n","base.dists.uniform.logcdf":"var y = base.dists.uniform.logcdf( 9.0, 0.0, 10.0 )\ny = base.dists.uniform.logcdf( 0.5, 0.0, 2.0 )\ny = base.dists.uniform.logcdf( PINF, 2.0, 4.0 )\ny = base.dists.uniform.logcdf( NINF, 2.0, 4.0 )\ny = base.dists.uniform.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.logcdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.logcdf( 2.0, 1.0, 0.0 )\n","base.dists.uniform.logcdf.factory":"var mylogcdf = base.dists.uniform.logcdf.factory( 0.0, 10.0 );\nvar y = mylogcdf( 0.5 )\ny = mylogcdf( 8.0 )\n","base.dists.uniform.logpdf":"var y = base.dists.uniform.logpdf( 2.0, 0.0, 4.0 )\ny = base.dists.uniform.logpdf( 5.0, 0.0, 4.0 )\ny = base.dists.uniform.logpdf( 0.25, 0.0, 1.0 )\ny = base.dists.uniform.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.logpdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.logpdf( 2.0, 3.0, 1.0 )\n","base.dists.uniform.logpdf.factory":"var mylogPDF = base.dists.uniform.logpdf.factory( 6.0, 7.0 );\nvar y = mylogPDF( 7.0 )\ny = mylogPDF( 5.0 )\n","base.dists.uniform.mean":"var v = base.dists.uniform.mean( 0.0, 1.0 )\nv = base.dists.uniform.mean( 4.0, 12.0 )\nv = base.dists.uniform.mean( 2.0, 8.0 )\n","base.dists.uniform.median":"var v = base.dists.uniform.median( 0.0, 1.0 )\nv = base.dists.uniform.median( 4.0, 12.0 )\nv = base.dists.uniform.median( 2.0, 8.0 )\n","base.dists.uniform.mgf":"var y = base.dists.uniform.mgf( 2.0, 0.0, 4.0 )\ny = base.dists.uniform.mgf( -0.2, 0.0, 4.0 )\ny = base.dists.uniform.mgf( 2.0, 0.0, 1.0 )\ny = base.dists.uniform.mgf( 0.5, 3.0, 2.0 )\ny = base.dists.uniform.mgf( 0.5, 3.0, 3.0 )\ny = base.dists.uniform.mgf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.mgf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.mgf( 0.0, 0.0, NaN )\n","base.dists.uniform.mgf.factory":"var mymgf = base.dists.uniform.mgf.factory( 6.0, 7.0 );\nvar y = mymgf( 0.1 )\ny = mymgf( 1.1 )\n","base.dists.uniform.pdf":"var y = base.dists.uniform.pdf( 2.0, 0.0, 4.0 )\ny = base.dists.uniform.pdf( 5.0, 0.0, 4.0 )\ny = base.dists.uniform.pdf( 0.25, 0.0, 1.0 )\ny = base.dists.uniform.pdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.pdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.pdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.pdf( 2.0, 3.0, 1.0 )\n","base.dists.uniform.pdf.factory":"var myPDF = base.dists.uniform.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 7.0 )\ny = myPDF( 5.0 )\n","base.dists.uniform.quantile":"var y = base.dists.uniform.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.uniform.quantile( 0.5, 0.0, 10.0 )\ny = base.dists.uniform.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.uniform.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.uniform.quantile( NaN, 0.0, 1.0 )\ny = base.dists.uniform.quantile( 0.0, NaN, 1.0 )\ny = base.dists.uniform.quantile( 0.0, 0.0, NaN )\ny = base.dists.uniform.quantile( 0.5, 2.0, 1.0 )\n","base.dists.uniform.quantile.factory":"var myQuantile = base.dists.uniform.quantile.factory( 0.0, 4.0 );\nvar y = myQuantile( 0.8 )\n","base.dists.uniform.skewness":"var v = base.dists.uniform.skewness( 0.0, 1.0 )\nv = base.dists.uniform.skewness( 4.0, 12.0 )\nv = base.dists.uniform.skewness( 2.0, 8.0 )\n","base.dists.uniform.stdev":"var v = base.dists.uniform.stdev( 0.0, 1.0 )\nv = base.dists.uniform.stdev( 4.0, 12.0 )\nv = base.dists.uniform.stdev( 2.0, 8.0 )\n","base.dists.uniform.Uniform":"var uniform = base.dists.uniform.Uniform( 0.0, 1.0 );\nuniform.a\nuniform.b\nuniform.entropy\nuniform.kurtosis\nuniform.mean\nuniform.median\nuniform.skewness\nuniform.stdev\nuniform.variance\nuniform.cdf( 0.8 )\nuniform.logcdf( 0.5 )\nuniform.logpdf( 1.0 )\nuniform.mgf( 0.8 )\nuniform.pdf( 0.8 )\nuniform.quantile( 0.8 )\n","base.dists.uniform.variance":"var v = base.dists.uniform.variance( 0.0, 1.0 )\nv = base.dists.uniform.variance( 4.0, 12.0 )\nv = base.dists.uniform.variance( 2.0, 8.0 )\n","base.dists.weibull.cdf":"var y = base.dists.weibull.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.weibull.cdf( -1.0, 2.0, 2.0 )\ny = base.dists.weibull.cdf( PINF, 4.0, 2.0 )\ny = base.dists.weibull.cdf( NINF, 4.0, 2.0 )\ny = base.dists.weibull.cdf( NaN, 0.0, 1.0 )\ny = base.dists.weibull.cdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.cdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.cdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.cdf.factory":"var myCDF = base.dists.weibull.cdf.factory( 2.0, 10.0 );\nvar y = myCDF( 12.0 )\n","base.dists.weibull.entropy":"var v = base.dists.weibull.entropy( 1.0, 1.0 )\nv = base.dists.weibull.entropy( 4.0, 12.0 )\nv = base.dists.weibull.entropy( 8.0, 2.0 )\n","base.dists.weibull.kurtosis":"var v = base.dists.weibull.kurtosis( 1.0, 1.0 )\nv = base.dists.weibull.kurtosis( 4.0, 12.0 )\nv = base.dists.weibull.kurtosis( 8.0, 2.0 )\n","base.dists.weibull.logcdf":"var y = base.dists.weibull.logcdf( 2.0, 1.0, 1.0 )\ny = base.dists.weibull.logcdf( -1.0, 2.0, 2.0 )\ny = base.dists.weibull.logcdf( PINF, 4.0, 2.0 )\ny = base.dists.weibull.logcdf( NINF, 4.0, 2.0 )\ny = base.dists.weibull.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.weibull.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.logcdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.logcdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.logcdf.factory":"var mylogcdf = base.dists.weibull.logcdf.factory( 2.0, 10.0 );\nvar y = mylogcdf( 12.0 )\n","base.dists.weibull.logpdf":"var y = base.dists.weibull.logpdf( 2.0, 1.0, 0.5 )\ny = base.dists.weibull.logpdf( 0.1, 1.0, 1.0 )\ny = base.dists.weibull.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.weibull.logpdf( NaN, 0.6, 1.0 )\ny = base.dists.weibull.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.logpdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.logpdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.logpdf.factory":"var mylofpdf = base.dists.weibull.logpdf.factory( 7.0, 6.0 );\ny = mylofpdf( 7.0 )\n","base.dists.weibull.mean":"var v = base.dists.weibull.mean( 1.0, 1.0 )\nv = base.dists.weibull.mean( 4.0, 12.0 )\nv = base.dists.weibull.mean( 8.0, 2.0 )\n","base.dists.weibull.median":"var v = base.dists.weibull.median( 1.0, 1.0 )\nv = base.dists.weibull.median( 4.0, 12.0 )\nv = base.dists.weibull.median( 8.0, 2.0 )\n","base.dists.weibull.mgf":"var y = base.dists.weibull.mgf( 1.0, 1.0, 0.5 )\ny = base.dists.weibull.mgf( -1.0, 4.0, 4.0 )\ny = base.dists.weibull.mgf( NaN, 1.0, 1.0 )\ny = base.dists.weibull.mgf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.mgf( 0.0, 1.0, NaN )\ny = base.dists.weibull.mgf( 0.2, -1.0, 0.5 )\ny = base.dists.weibull.mgf( 0.2, 0.0, 0.5 )\ny = base.dists.weibull.mgf( 0.2, 0.5, -1.0 )\ny = base.dists.weibull.mgf( 0.2, 0.5, 0.0 )\n","base.dists.weibull.mgf.factory":"var myMGF = base.dists.weibull.mgf.factory( 8.0, 10.0 );\nvar y = myMGF( 0.8 )\ny = myMGF( 0.08 )\n","base.dists.weibull.mode":"var v = base.dists.weibull.mode( 1.0, 1.0 )\nv = base.dists.weibull.mode( 4.0, 12.0 )\nv = base.dists.weibull.mode( 8.0, 2.0 )\n","base.dists.weibull.pdf":"var y = base.dists.weibull.pdf( 2.0, 1.0, 0.5 )\ny = base.dists.weibull.pdf( 0.1, 1.0, 1.0 )\ny = base.dists.weibull.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.weibull.pdf( NaN, 0.6, 1.0 )\ny = base.dists.weibull.pdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.pdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.pdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.pdf.factory":"var myPDF = base.dists.weibull.pdf.factory( 7.0, 6.0 );\nvar y = myPDF( 7.0 )\n","base.dists.weibull.quantile":"var y = base.dists.weibull.quantile( 0.8, 1.0, 1.0 )\ny = base.dists.weibull.quantile( 0.5, 2.0, 4.0 )\ny = base.dists.weibull.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.weibull.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.weibull.quantile( NaN, 0.0, 1.0 )\ny = base.dists.weibull.quantile( 0.0, NaN, 1.0 )\ny = base.dists.weibull.quantile( 0.0, 0.0, NaN )\ny = base.dists.weibull.quantile( 0.5, 1.0, -1.0 )\n","base.dists.weibull.quantile.factory":"var myQuantile = base.dists.weibull.quantile.factory( 2.0, 10.0 );\nvar y = myQuantile( 0.4 )\n","base.dists.weibull.skewness":"var v = base.dists.weibull.skewness( 1.0, 1.0 )\nv = base.dists.weibull.skewness( 4.0, 12.0 )\nv = base.dists.weibull.skewness( 8.0, 2.0 )\n","base.dists.weibull.stdev":"var v = base.dists.weibull.stdev( 1.0, 1.0 )\nv = base.dists.weibull.stdev( 4.0, 12.0 )\nv = base.dists.weibull.stdev( 8.0, 2.0 )\n","base.dists.weibull.variance":"var v = base.dists.weibull.variance( 1.0, 1.0 )\nv = base.dists.weibull.variance( 4.0, 12.0 )\nv = base.dists.weibull.variance( 8.0, 2.0 )\n","base.dists.weibull.Weibull":"var weibull = base.dists.weibull.Weibull( 6.0, 5.0 );\nweibull.k\nweibull.lambda\nweibull.entropy\nweibull.kurtosis\nweibull.mean\nweibull.median\nweibull.mode\nweibull.skewness\nweibull.stdev\nweibull.variance\nweibull.cdf( 3.0 )\nweibull.logcdf( 3.0 )\nweibull.logpdf( 1.0 )\nweibull.mgf( -0.5 )\nweibull.pdf( 3.0 )\nweibull.quantile( 0.8 )\n","base.ellipe":"var y = base.ellipe( 0.5 )\ny = base.ellipe( -1.0 )\ny = base.ellipe( 2.0 )\ny = base.ellipe( PINF )\ny = base.ellipe( NINF )\ny = base.ellipe( NaN )\n","base.ellipj":"var v = base.ellipj( 0.3, 0.5 )\nv = base.ellipj( 0.0, 0.0 )\nv = base.ellipj( Infinity, 1.0 )\nv = base.ellipj( 0.0, -2.0)\nv = base.ellipj( NaN, NaN )\n","base.ellipj.assign":"var out = new Float64Array( 4 );\nvar v = base.ellipj.assign( 0.3, 0.5, out, 1, 0 )\nvar bool = ( v === out )\n","base.ellipj.sn":"var v = base.ellipj.sn( 0.3, 0.5 )\n","base.ellipj.cn":"var v = base.ellipj.cn( 0.3, 0.5 )\n","base.ellipj.dn":"var v = base.ellipj.dn( 0.3, 0.5 )\n","base.ellipj.am":"var v = base.ellipj.am( 0.3, 0.5 )\n","base.ellipk":"var y = base.ellipk( 0.5 )\ny = base.ellipk( -1.0 )\ny = base.ellipk( 2.0 )\ny = base.ellipk( PINF )\ny = base.ellipk( NINF )\ny = base.ellipk( NaN )\n","base.endsWith":"var bool = base.endsWith( 'beep', 'ep', 4 )\nbool = base.endsWith( 'Beep', 'op', 4 )\nbool = base.endsWith( 'Beep', 'ee', 3 )\nbool = base.endsWith( 'Beep', 'ee', -1 )\nbool = base.endsWith( 'beep', '', 4 )\n","base.epsdiff":"var d = base.epsdiff( 12.15, 12.149999999999999 )\nd = base.epsdiff( 2.4341309458983933, 2.4341309458633909, 'mean-abs' )\nfunction scale( x, y ) { return ( x > y ) ? y : x; };\nd = base.epsdiff( 1.0000000000000002, 1.0000000000000100, scale )\n","base.erf":"var y = base.erf( 2.0 )\ny = base.erf( -1.0 )\ny = base.erf( -0.0 )\ny = base.erf( NaN )\n","base.erfc":"var y = base.erfc( 2.0 )\ny = base.erfc( -1.0 )\ny = base.erfc( 0.0 )\ny = base.erfc( PINF )\ny = base.erfc( NINF )\ny = base.erfc( NaN )\n","base.erfcinv":"var y = base.erfcinv( 0.5 )\ny = base.erfcinv( 0.8 )\ny = base.erfcinv( 0.0 )\ny = base.erfcinv( 2.0 )\ny = base.erfcinv( NaN )\n","base.erfcx":"var y = base.erfcx( 1.0 )\ny = base.erfcx( -1.0 )\ny = base.erfcx( 0.0 )\ny = base.erfcx( NaN )\n","base.erfinv":"var y = base.erfinv( 0.5 )\ny = base.erfinv( 0.8 )\ny = base.erfinv( 0.0 )\ny = base.erfinv( -0.0 )\ny = base.erfinv( -1.0 )\ny = base.erfinv( 1.0 )\ny = base.erfinv( NaN )\n","base.eta":"var y = base.eta( 0.0 )\ny = base.eta( -1.0 )\ny = base.eta( 1.0 )\ny = base.eta( 3.14 )\ny = base.eta( NaN )\n","base.evalpoly":"var arr = [ 3.0, 2.0, 1.0 ];\nvar v = base.evalpoly( arr, 10.0 )\n","base.evalpoly.factory":"var f = base.evalpoly.factory( [ 3.0, 2.0, 1.0 ] );\nvar v = f( 10.0 )\nv = f( 5.0 )\n","base.evalrational":"var P = [ -6.0, -5.0, 4.0, 2.0 ];\nvar Q = [ 3.0, 0.5, 0.0, 0.0 ]; // zero-padded\nvar v = base.evalrational( P, Q, 6.0 )\n","base.evalrational.factory":"var P = [ 20.0, 8.0, 3.0 ];\nvar Q = [ 10.0, 9.0, 1.0 ];\nvar f = base.evalrational.factory( P, Q );\nvar v = f( 10.0 )\nv = f( 2.0 )\n","base.exp":"var y = base.exp( 4.0 )\ny = base.exp( -9.0 )\ny = base.exp( 0.0 )\ny = base.exp( NaN )\n","base.exp2":"var y = base.exp2( 3.0 )\ny = base.exp2( -9.0 )\ny = base.exp2( 0.0 )\ny = base.exp2( NaN )\n","base.exp10":"var y = base.exp10( 3.0 )\ny = base.exp10( -9.0 )\ny = base.exp10( 0.0 )\ny = base.exp10( NaN )\n","base.expit":"var y = base.expit( 0.0 )\ny = base.expit( 1.0 )\ny = base.expit( -1.0 )\ny = base.expit( Infinity )\ny = base.expit( NaN )\n","base.expm1":"var y = base.expm1( 0.2 )\ny = base.expm1( -9.0 )\ny = base.expm1( 0.0 )\ny = base.expm1( NaN )\n","base.expm1rel":"var y = base.expm1rel( 0.0 )\ny = base.expm1rel( 1.0 )\ny = base.expm1rel( -1.0 )\ny = base.expm1rel( NaN )\n","base.exponent":"var exponent = base.exponent( 3.14e-307 )\nexponent = base.exponent( -3.14 )\nexponent = base.exponent( 0.0 )\nexponent = base.exponent( NaN )\n","base.exponentf":"var exponent = base.exponentf( base.float64ToFloat32( 3.14e34 ) )\nexponent = base.exponentf( base.float64ToFloat32( 3.14e-34 ) )\nexponent = base.exponentf( base.float64ToFloat32( -3.14 ) )\nexponent = base.exponentf( 0.0 )\nexponent = base.exponentf( NaN )\n","base.factorial":"var y = base.factorial( 3.0 )\ny = base.factorial( -1.5 )\ny = base.factorial( -0.5 )\ny = base.factorial( 0.5 )\ny = base.factorial( -10.0 )\ny = base.factorial( 171.0 )\ny = base.factorial( NaN )\n","base.factorial2":"var y = base.factorial2( 3 )\ny = base.factorial2( 5 )\ny = base.factorial2( 6 )\ny = base.factorial2( 301 )\ny = base.factorial2( NaN )\n","base.factorialln":"var y = base.factorialln( 3.0 )\ny = base.factorialln( 2.4 )\ny = base.factorialln( -1.0 )\ny = base.factorialln( -1.5 )\ny = base.factorialln( NaN )\n","base.fallingFactorial":"var v = base.fallingFactorial( 0.9, 5 )\nv = base.fallingFactorial( -9.0, 3 )\nv = base.fallingFactorial( 0.0, 2 )\nv = base.fallingFactorial( 3.0, -2 )\n","base.fibonacci":"var y = base.fibonacci( 0 )\ny = base.fibonacci( 1 )\ny = base.fibonacci( 2 )\ny = base.fibonacci( 3 )\ny = base.fibonacci( 4 )\ny = base.fibonacci( 79 )\ny = base.fibonacci( NaN )\n","base.fibonacciIndex":"var n = base.fibonacciIndex( 2 )\nn = base.fibonacciIndex( 3 )\nn = base.fibonacciIndex( 5 )\nn = base.fibonacciIndex( NaN )\nn = base.fibonacciIndex( 1 )\n","base.fibpoly":"var v = base.fibpoly( 5, 2.0 )\n","base.fibpoly.factory":"var polyval = base.fibpoly.factory( 5 );\nvar v = polyval( 1.0 )\nv = polyval( 2.0 )\n","base.firstCodePoint":"var out = base.firstCodePoint( 'beep', 1 )\nout = base.firstCodePoint( 'Boop', 1 )\nout = base.firstCodePoint( 'foo bar', 5 )\n","base.firstCodeUnit":"var out = base.firstCodeUnit( 'beep', 1 )\nout = base.firstCodeUnit( 'Boop', 1 )\nout = base.firstCodeUnit( 'foo bar', 5 )\n","base.firstGraphemeCluster":"var out = base.firstGraphemeCluster( 'beep', 1 )\nout = base.firstGraphemeCluster( 'Boop', 1 )\nout = base.firstGraphemeCluster( 'foo bar', 5 )\n","base.flipsign":"var z = base.flipsign( -3.0, 10.0 )\nz = base.flipsign( -3.0, -1.0 )\nz = base.flipsign( 1.0, -0.0 )\nz = base.flipsign( -3.0, -0.0 )\nz = base.flipsign( -0.0, 1.0 )\nz = base.flipsign( 0.0, -1.0 )\n","base.flipsignf":"var z = base.flipsignf( -3.0, 10.0 )\nz = base.flipsignf( -3.0, -1.0 )\nz = base.flipsignf( 1.0, -0.0 )\nz = base.flipsignf( -3.0, -0.0 )\nz = base.flipsignf( -0.0, 1.0 )\nz = base.flipsignf( 0.0, -1.0 )\n","base.float32ToInt32":"var y = base.float32ToInt32( base.float64ToFloat32( 4294967295.0 ) )\ny = base.float32ToInt32( base.float64ToFloat32( 3.14 ) )\ny = base.float32ToInt32( base.float64ToFloat32( -3.14 ) )\ny = base.float32ToInt32( base.float64ToFloat32( NaN ) )\ny = base.float32ToInt32( FLOAT32_PINF )\ny = base.float32ToInt32( FLOAT32_NINF )\n","base.float32ToUint32":"var y = base.float32ToUint32( base.float64ToFloat32( 4294967297.0 ) )\ny = base.float32ToUint32( base.float64ToFloat32( 3.14 ) )\ny = base.float32ToUint32( base.float64ToFloat32( -3.14 ) )\ny = base.float32ToUint32( base.float64ToFloat32( NaN ) )\ny = base.float32ToUint32( FLOAT32_PINF )\ny = base.float32ToUint32( FLOAT32_NINF )\n","base.float64ToFloat32":"var y = base.float64ToFloat32( 1.337 )\n","base.float64ToInt32":"var y = base.float64ToInt32( 4294967295.0 )\ny = base.float64ToInt32( 3.14 )\ny = base.float64ToInt32( -3.14 )\ny = base.float64ToInt32( NaN )\ny = base.float64ToInt32( PINF )\ny = base.float64ToInt32( NINF )\n","base.float64ToInt64Bytes":"var y = base.float64ToInt64Bytes( 4294967297.0 )\n","base.float64ToInt64Bytes.assign":"var out = new Uint8Array( 16 );\nvar y = base.float64ToInt64Bytes( 4294967297.0, out, 2, 1 )\n","base.float64ToUint32":"var y = base.float64ToUint32( 4294967297.0 )\ny = base.float64ToUint32( 3.14 )\ny = base.float64ToUint32( -3.14 )\ny = base.float64ToUint32( NaN )\ny = base.float64ToUint32( PINF )\ny = base.float64ToUint32( NINF )\n","base.floor":"var y = base.floor( 3.14 )\ny = base.floor( -4.2 )\ny = base.floor( -4.6 )\ny = base.floor( 9.5 )\ny = base.floor( -0.0 )\n","base.floor2":"var y = base.floor2( 3.14 )\ny = base.floor2( -4.2 )\ny = base.floor2( -4.6 )\ny = base.floor2( 9.5 )\ny = base.floor2( 13.0 )\ny = base.floor2( -13.0 )\ny = base.floor2( -0.0 )\n","base.floor10":"var y = base.floor10( 3.14 )\ny = base.floor10( -4.2 )\ny = base.floor10( -4.6 )\ny = base.floor10( 9.5 )\ny = base.floor10( 13.0 )\ny = base.floor10( -13.0 )\ny = base.floor10( -0.0 )\n","base.floorb":"var y = base.floorb( 3.14159, -4, 10 )\ny = base.floorb( 3.14159, 0, 2 )\ny = base.floorb( 5.0, 1, 2 )\n","base.floorf":"var y = base.floorf( 3.14 )\ny = base.floorf( -4.2 )\ny = base.floorf( -4.6 )\ny = base.floorf( 9.5 )\ny = base.floorf( -0.0 )\n","base.floorn":"var y = base.floorn( 3.14159, -4 )\ny = base.floorn( 3.14159, 0 )\ny = base.floorn( 12368.0, 3 )\n","base.floorsd":"var y = base.floorsd( 3.14159, 5, 10 )\ny = base.floorsd( 3.14159, 1, 10 )\ny = base.floorsd( 12368.0, 2, 10 )\ny = base.floorsd( 0.0313, 2, 2 )\n","base.forEachChar":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachChar( 'hello world!', fcn );\nn\n","base.forEachCodePoint":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachCodePoint( 'hello world!', fcn );\nn\n","base.forEachCodePointRight":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachCodePointRight( 'hello world!', fcn );\nn\n","base.forEachGraphemeCluster":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachGraphemeCluster( 'hello world!', fcn );\nn\n","base.forEachRight":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachRight( 'hello world!', fcn );\nn\n","base.formatInterpolate":"var out = base.formatInterpolate( [ 'beep ', { 'specifier': 's' } ], 'boop' )\nout = base.formatInterpolate( [ 'baz ', { 'specifier': 'd', 'precision': 2 } ], 1 )\nout = base.formatInterpolate( [ { 'specifier': 'u', 'width': 6 } ], 12 )\n","base.formatTokenize":"var out = base.formatTokenize( 'Hello %s!' )\nout = base.formatTokenize( '%s %s %d' )\nout = base.formatTokenize( 'Pi: %.2f' )\n","base.fresnel":"var y = base.fresnel( 0.0 )\ny = base.fresnel( 1.0 )\ny = base.fresnel( PINF )\ny = base.fresnel( NINF )\ny = base.fresnel( NaN )\n","base.fresnel.assign":"var out = new Float64Array( 2 );\nvar v = base.fresnel.assign( 0.0, out, 1, 0 )\nvar bool = ( v === out )\n","base.fresnelc":"var y = base.fresnelc( 0.0 )\ny = base.fresnelc( 1.0 )\ny = base.fresnelc( PINF )\ny = base.fresnelc( NINF )\ny = base.fresnelc( NaN )\n","base.fresnels":"var y = base.fresnels( 0.0 )\ny = base.fresnels( 1.0 )\ny = base.fresnels( PINF )\ny = base.fresnels( NINF )\ny = base.fresnels( NaN )\n","base.frexp":"var out = base.frexp( 4.0 )\nout = base.frexp( 0.0 )\nout = base.frexp( -0.0 )\nout = base.frexp( NaN )\nout = base.frexp( PINF )\nout = base.frexp( NINF )\n","base.frexp.assign":"var out = new Float64Array( 2 );\nvar y = base.frexp.assign( 4.0, out, 1, 0 )\nvar bool = ( y === out )\n","base.fromBinaryString":"var bstr;\nbstr = '0100000000010000000000000000000000000000000000000000000000000000';\nvar val = base.fromBinaryString( bstr )\nbstr = '0100000000001001001000011111101101010100010001000010110100011000';\nval = base.fromBinaryString( bstr )\nbstr = '1111111111100001110011001111001110000101111010111100100010100000';\nval = base.fromBinaryString( bstr )\nbstr = '1000000000000000000000000000000000000000000000000001100011010011';\nval = base.fromBinaryString( bstr )\nbstr = '0000000000000000000000000000000000000000000000000000000000000001';\nval = base.fromBinaryString( bstr )\nbstr = '0000000000000000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '1000000000000000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '0111111111111000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '0111111111110000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '1111111111110000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\n","base.fromBinaryStringf":"var bstr = '01000000100000000000000000000000';\nvar val = base.fromBinaryStringf( bstr )\nbstr = '01000000010010010000111111011011';\nval = base.fromBinaryStringf( bstr )\nbstr = '11111111011011000011101000110011';\nval = base.fromBinaryStringf( bstr )\nbstr = '10000000000000000000000000010110';\nval = base.fromBinaryStringf( bstr )\nbstr = '00000000000000000000000000000001';\nval = base.fromBinaryStringf( bstr )\nbstr = '00000000000000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '10000000000000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '01111111110000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '01111111100000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '11111111100000000000000000000000';\nval = base.fromBinaryStringf( bstr )\n","base.fromBinaryStringUint8":"var bstr = '01010101';\nvar val = base.fromBinaryStringUint8( bstr )\nbstr = '00000000';\nval = base.fromBinaryStringUint8( bstr )\nbstr = '00000010';\nval = base.fromBinaryStringUint8( bstr )\nbstr = '11111111';\nval = base.fromBinaryStringUint8( bstr )\n","base.fromBinaryStringUint16":"var bstr = '0101010101010101';\nvar val = base.fromBinaryStringUint16( bstr )\nbstr = '0000000000000000';\nval = base.fromBinaryStringUint16( bstr )\nbstr = '0000000000000010';\nval = base.fromBinaryStringUint16( bstr )\nbstr = '1111111111111111';\nval = base.fromBinaryStringUint16( bstr )\n","base.fromBinaryStringUint32":"var bstr = '01010101010101010101010101010101';\nvar val = base.fromBinaryStringUint32( bstr )\nbstr = '00000000000000000000000000000000';\nval = base.fromBinaryStringUint32( bstr )\nbstr = '00000000000000000000000000000010';\nval = base.fromBinaryStringUint32( bstr )\nbstr = '11111111111111111111111111111111';\nval = base.fromBinaryStringUint32( bstr )\n","base.fromInt64Bytes":"var bytes = new Uint8Array( [ 255, 255, 255, 255, 255, 255, 255, 255 ] );\nvar y = base.fromInt64Bytes( bytes, 1, 0 )\n","base.fromWordf":"var word = 1068180177; // => 0 01111111 01010110010001011010001\nvar f32 = base.fromWordf( word ) // when printed, promoted to float64\n","base.fromWords":"var v = base.fromWords( 1774486211, 2479577218 )\nv = base.fromWords( 3221823995, 1413754136 )\nv = base.fromWords( 0, 0 )\nv = base.fromWords( 2147483648, 0 )\nv = base.fromWords( 2146959360, 0 )\nv = base.fromWords( 2146435072, 0 )\nv = base.fromWords( 4293918720, 0 )\n","base.gamma":"var y = base.gamma( 4.0 )\ny = base.gamma( -1.5 )\ny = base.gamma( -0.5 )\ny = base.gamma( 0.5 )\ny = base.gamma( 0.0 )\ny = base.gamma( -0.0 )\ny = base.gamma( NaN )\n","base.gamma1pm1":"var y = base.gamma1pm1( 0.2 )\ny = base.gamma1pm1( -6.7 )\ny = base.gamma1pm1( 0.0 )\ny = base.gamma1pm1( NaN )\n","base.gammaDeltaRatio":"var y = base.gammaDeltaRatio( 2.0, 3.0 )\ny = base.gammaDeltaRatio( 4.0, 0.5 )\ny = base.gammaDeltaRatio( 100.0, 0.0 )\ny = base.gammaDeltaRatio( NaN, 3.0 )\ny = base.gammaDeltaRatio( 5.0, NaN )\ny = base.gammaDeltaRatio( NaN, NaN )\n","base.gammainc":"var y = base.gammainc( 6.0, 2.0 )\ny = base.gammainc( 1.0, 2.0, true, true )\ny = base.gammainc( 7.0, 5.0 )\ny = base.gammainc( 7.0, 5.0, false )\ny = base.gammainc( NaN, 2.0 )\ny = base.gammainc( 6.0, NaN )\n","base.gammaincinv":"var y = base.gammaincinv( 0.5, 2.0 )\ny = base.gammaincinv( 0.1, 10.0 )\ny = base.gammaincinv( 0.75, 3.0 )\ny = base.gammaincinv( 0.75, 3.0, true )\ny = base.gammaincinv( 0.75, NaN )\ny = base.gammaincinv( NaN, 3.0 )\n","base.gammaLanczosSum":"var y = base.gammaLanczosSum( 4.0 )\ny = base.gammaLanczosSum( -1.5 )\ny = base.gammaLanczosSum( -0.5 )\ny = base.gammaLanczosSum( 0.5 )\ny = base.gammaLanczosSum( 0.0 )\ny = base.gammaLanczosSum( NaN )\n","base.gammaLanczosSumExpGScaled":"var y = base.gammaLanczosSumExpGScaled( 4.0 )\ny = base.gammaLanczosSumExpGScaled( -1.5 )\ny = base.gammaLanczosSumExpGScaled( -0.5 )\ny = base.gammaLanczosSumExpGScaled( 0.5 )\ny = base.gammaLanczosSumExpGScaled( 0.0 )\ny = base.gammaLanczosSumExpGScaled( NaN )\n","base.gammaln":"var y = base.gammaln( 1.0 )\ny = base.gammaln( 2.0 )\ny = base.gammaln( 4.0 )\ny = base.gammaln( -0.5 )\ny = base.gammaln( 0.5 )\ny = base.gammaln( 0.0 )\ny = base.gammaln( NaN )\n","base.gammasgn":"var y = base.gammasgn( 1.0 )\ny = base.gammasgn( -2.5 )\ny = base.gammasgn( 0.0 )\ny = base.gammasgn( NaN )\n","base.gcd":"var v = base.gcd( 48, 18 )\n","base.getHighWord":"var w = base.getHighWord( 3.14e201 )\n","base.getLowWord":"var w = base.getLowWord( 3.14e201 )\n","base.hacovercos":"var y = base.hacovercos( 3.14 )\ny = base.hacovercos( -4.2 )\ny = base.hacovercos( -4.6 )\ny = base.hacovercos( 9.5 )\ny = base.hacovercos( -0.0 )\n","base.hacoversin":"var y = base.hacoversin( 3.14 )\ny = base.hacoversin( -4.2 )\ny = base.hacoversin( -4.6 )\ny = base.hacoversin( 9.5 )\ny = base.hacoversin( -0.0 )\n","base.havercos":"var y = base.havercos( 3.14 )\ny = base.havercos( -4.2 )\ny = base.havercos( -4.6 )\ny = base.havercos( 9.5 )\ny = base.havercos( -0.0 )\n","base.haversin":"var y = base.haversin( 3.14 )\ny = base.haversin( -4.2 )\ny = base.haversin( -4.6 )\ny = base.haversin( 9.5 )\ny = base.haversin( -0.0 )\n","base.headercase":"var out = base.headercase( 'Hello World!' )\nout = base.headercase( 'beep boop' )\n","base.heaviside":"var y = base.heaviside( 3.14 )\ny = base.heaviside( -3.14 )\ny = base.heaviside( 0.0 )\ny = base.heaviside( 0.0, 'half-maximum' )\ny = base.heaviside( 0.0, 'left-continuous' )\ny = base.heaviside( 0.0, 'right-continuous' )\n","base.hermitepoly":"var y = base.hermitepoly( 1, 0.5 )\ny = base.hermitepoly( -1, 0.5 )\ny = base.hermitepoly( 0, 0.5 )\ny = base.hermitepoly( 2, 0.5 )\n","base.hermitepoly.factory":"var polyval = base.hermitepoly.factory( 2 );\nvar v = polyval( 0.5 )\n","base.hypot":"var h = base.hypot( -5.0, 12.0 )\nh = base.hypot( NaN, 12.0 )\nh = base.hypot( -0.0, -0.0 )\n","base.hypotf":"var h = base.hypotf( -5.0, 12.0 )\nh = base.hypotf( NaN, 12.0 )\nh = base.hypotf( -0.0, -0.0 )\n","base.identity":"var y = base.identity( -1.0 )\ny = base.identity( 2.0 )\ny = base.identity( 0.0 )\ny = base.identity( -0.0 )\ny = base.identity( NaN )\n","base.identityf":"var y = base.identityf( -1.0 )\ny = base.identityf( 2.0 )\ny = base.identityf( 0.0 )\ny = base.identityf( -0.0 )\ny = base.identityf( NaN )\n","base.imul":"var v = base.imul( -10|0, 4|0 )\n","base.imuldw":"var v = base.imuldw( 1, 10 )\n","base.imuldw.assign":"var out = [ 0, 0 ];\nvar v = base.imuldw.assign( 1, 10, out, 1, 0 )\nvar bool = ( v === out )\n","base.int2slice":"var s = base.int2slice( -1, 5, false );\ns.start\ns.stop\ns.step\n","base.int32ToUint32":"var y = base.int32ToUint32( base.float64ToInt32( -32 ) )\ny = base.int32ToUint32( base.float64ToInt32( 3 ) )\n","base.inv":"var y = base.inv( -1.0 )\ny = base.inv( 2.0 )\ny = base.inv( 0.0 )\ny = base.inv( -0.0 )\ny = base.inv( NaN )\n","base.invcase":"var out = base.invcase( 'Hello World!' )\nout = base.invcase( 'I am A tiny LITTLE teapot' )\n","base.invf":"var y = base.invf( -1.0 )\ny = base.invf( 2.0 )\ny = base.invf( 0.0 )\ny = base.invf( -0.0 )\ny = base.invf( NaN )\n","base.isComposite":"var bool = base.isComposite( 10.0 )\nbool = base.isComposite( 11.0 )\n","base.isCoprime":"var bool = base.isCoprime( 14.0, 15.0 )\nbool = base.isCoprime( 14.0, 21.0 )\n","base.isEven":"var bool = base.isEven( 5.0 )\nbool = base.isEven( -2.0 )\nbool = base.isEven( 0.0 )\nbool = base.isEven( NaN )\n","base.isEvenInt32":"var bool = base.isEvenInt32( 5 )\nbool = base.isEvenInt32( -2 )\nbool = base.isEvenInt32( 0 )\n","base.isFinite":"var bool = base.isFinite( 5.0 )\nbool = base.isFinite( -2.0e64 )\nbool = base.isFinite( PINF )\nbool = base.isFinite( NINF )\n","base.isFinitef":"var bool = base.isFinitef( 5.0 )\nbool = base.isFinitef( -1.0e38 )\nbool = base.isFinitef( FLOAT32_PINF )\nbool = base.isFinitef( FLOAT32_NINF )\n","base.isInfinite":"var bool = base.isInfinite( PINF )\nbool = base.isInfinite( NINF )\nbool = base.isInfinite( 5.0 )\nbool = base.isInfinite( NaN )\n","base.isInfinitef":"var bool = base.isInfinitef( FLOAT32_PINF )\nbool = base.isInfinitef( FLOAT32_NINF )\nbool = base.isInfinitef( 5.0 )\nbool = base.isInfinitef( NaN )\n","base.isInteger":"var bool = base.isInteger( 1.0 )\nbool = base.isInteger( 3.14 )\n","base.isnan":"var bool = base.isnan( NaN )\nbool = base.isnan( 7.0 )\n","base.isnanf":"var bool = base.isnanf( NaN )\nbool = base.isnanf( 7.0 )\n","base.isNegativeFinite":"var bool = base.isNegativeFinite( -3.14 )\nbool = base.isNegativeFinite( -Infinity )\nbool = base.isNegativeFinite( 2.0 )\nbool = base.isNegativeFinite( NaN )\nbool = base.isNegativeFinite( -0.0 )\n","base.isNegativeInteger":"var bool = base.isNegativeInteger( -1.0 )\nbool = base.isNegativeInteger( 0.0 )\nbool = base.isNegativeInteger( 10.0 )\n","base.isNegativeZero":"var bool = base.isNegativeZero( -0.0 )\nbool = base.isNegativeZero( 0.0 )\n","base.isNegativeZerof":"var bool = base.isNegativeZerof( -0.0 )\nbool = base.isNegativeZerof( 0.0 )\n","base.isNonNegativeFinite":"var out = base.isNonNegativeFinite( 5.0 )\nout = base.isNonNegativeFinite( 3.14 )\nout = base.isNonNegativeFinite( 0.0 )\nout = base.isNonNegativeFinite( Infinity )\nout = base.isNonNegativeFinite( -3.14 )\nout = base.isNonNegativeFinite( NaN )\n","base.isNonNegativeInteger":"var bool = base.isNonNegativeInteger( 1.0 )\nbool = base.isNonNegativeInteger( 0.0 )\nbool = base.isNonNegativeInteger( -10.0 )\n","base.isNonPositiveFinite":"var bool = base.isNonPositiveFinite( -3.14 )\nvar bool = base.isNonPositiveFinite( 0.0 )\nvar bool = base.isNonPositiveFinite( -Infinity )\nvar bool = base.isNonPositiveFinite( 3.14 )\nvar bool = base.isNonPositiveFinite( NaN )\n","base.isNonPositiveInteger":"var bool = base.isNonPositiveInteger( -1.0 )\nbool = base.isNonPositiveInteger( 0.0 )\nbool = base.isNonPositiveInteger( 10.0 )\n","base.isOdd":"var bool = base.isOdd( 5.0 )\nbool = base.isOdd( -2.0 )\nbool = base.isOdd( 0.0 )\nbool = base.isOdd( NaN )\n","base.isOddInt32":"var bool = base.isOddInt32( 5 )\nbool = base.isOddInt32( -2 )\nbool = base.isOddInt32( 0 )\n","base.isPositiveFinite":"var bool = base.isPositiveFinite( 5.0 )\nbool = base.isPositiveFinite( 3.14 )\nbool = base.isPositiveFinite( 0.0 )\nbool = base.isPositiveFinite( Infinity )\nbool = base.isPositiveFinite( -3.14 )\nbool = base.isPositiveFinite( NaN )\n","base.isPositiveInteger":"var bool = base.isPositiveInteger( 1.0 )\nbool = base.isPositiveInteger( 0.0 )\nbool = base.isPositiveInteger( -10.0 )\n","base.isPositiveZero":"var bool = base.isPositiveZero( 0.0 )\nbool = base.isPositiveZero( -0.0 )\n","base.isPositiveZerof":"var bool = base.isPositiveZerof( 0.0 )\nbool = base.isPositiveZerof( -0.0 )\n","base.isPow2Uint32":"var bool = base.isPow2Uint32( 2 )\nbool = base.isPow2Uint32( 5 )\n","base.isPrime":"var bool = base.isPrime( 11.0 )\nbool = base.isPrime( 3.14 )\n","base.isProbability":"var bool = base.isProbability( 0.5 )\nbool = base.isProbability( 3.14 )\nbool = base.isProbability( NaN )\n","base.isSafeInteger":"var bool = base.isSafeInteger( 1.0 )\nbool = base.isSafeInteger( 2.0e200 )\nbool = base.isSafeInteger( 3.14 )\n","base.kebabcase":"var out = base.kebabcase( 'Hello World!' )\nout = base.kebabcase( 'I am a tiny little teapot' )\n","base.kernelBetainc":"var out = base.kernelBetainc( 0.8, 1.0, 0.3, false, false )\nout = base.kernelBetainc( 0.2, 1.0, 2.0, true, false )\n","base.kernelBetainc.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.kernelBetainc.assign( 0.2, 1.0, 2.0, true, true, out, 1, 0 )\nvar bool = ( v === out )\n","base.kernelBetaincinv":"var y = base.kernelBetaincinv( 3.0, 3.0, 0.2, 0.8 )\ny = base.kernelBetaincinv( 3.0, 3.0, 0.4, 0.6 )\ny = base.kernelBetaincinv( 1.0, 6.0, 0.4, 0.6 )\ny = base.kernelBetaincinv( 1.0, 6.0, 0.8, 0.2 )\n","base.kernelCos":"var out = base.kernelCos( 0.0, 0.0 )\nout = base.kernelCos( PI/6.0, 0.0 )\nout = base.kernelCos( 0.785, -1.144e-17 )\nout = base.kernelCos( NaN )\n","base.kernelLog1p":"var y = base.kernelLog1p( 1.0 )\ny = base.kernelLog1p( 1.4142135623730951 )\ny = base.kernelLog1p( NaN )\n","base.kernelSin":"var y = base.kernelSin( 0.0, 0.0 )\ny = base.kernelSin( PI/6.0, 0.0 )\ny = base.kernelSin( 0.619, 9.279e-18 )\ny = base.kernelSin( NaN, 0.0 )\ny = base.kernelSin( 2.0, NaN )\ny = base.kernelSin( NaN, NaN )\n","base.kernelTan":"var out = base.kernelTan( PI/4.0, 0.0, 1 )\nout = base.kernelTan( PI/4.0, 0.0, -1 )\nout = base.kernelTan( PI/6.0, 0.0, 1 )\nout = base.kernelTan( 0.664, 5.288e-17, 1 )\nout = base.kernelTan( NaN, 0.0, 1 )\nout = base.kernelTan( 3.0, NaN, 1 )\nout = base.kernelTan( 3.0, 0.0, NaN )\n","base.kroneckerDelta":"var y = base.kroneckerDelta( 3.14, 0.0 )\ny = base.kroneckerDelta( 3.14, 3.14 )\n","base.kroneckerDeltaf":"var y = base.kroneckerDeltaf( 3.14, 0.0 )\ny = base.kroneckerDeltaf( 3.14, 3.14 )\n","base.labs":"var v = base.labs( -1|0 )\nv = base.labs( 2|0 )\nv = base.labs( 0|0 )\n","base.last":"var out = base.last( 'hello', 1 )\nout = base.last( 'JavaScript', 6 )\nout = base.last( 'foo bar', 10 )\n","base.lastCodePoint":"var out = base.lastCodePoint( 'hello world', 1 )\nout = base.lastCodePoint( 'JavaScript', 6 )\nout = base.lastCodePoint( 'अनुच्छेद', 1 )\n","base.lastGraphemeCluster":"var out = base.lastGraphemeCluster( 'beep', 1 )\nout = base.lastGraphemeCluster( 'Boop', 2 )\nout = base.lastGraphemeCluster( 'JavaScript', 6 )\n","base.lcm":"var v = base.lcm( 21, 6 )\n","base.ldexp":"var x = base.ldexp( 0.5, 3 )\nx = base.ldexp( 4.0, -2 )\nx = base.ldexp( 0.0, 20 )\nx = base.ldexp( -0.0, 39 )\nx = base.ldexp( NaN, -101 )\nx = base.ldexp( PINF, 11 )\nx = base.ldexp( NINF, -118 )\n","base.leftPad":"var out = base.leftPad( 'a', 5, ' ' )\nout = base.leftPad( 'beep', 10, 'b' )\nout = base.leftPad( 'boop', 12, 'beep' )\n","base.leftTrim":"var out = base.leftTrim( ' \\r\\n\\t  Beep \\t\\t\\n  ' )\n","base.ln":"var y = base.ln( 4.0 )\ny = base.ln( 0.0 )\ny = base.ln( PINF )\ny = base.ln( NaN )\ny = base.ln( -4.0 )\n","base.log":"var y = base.log( 100.0, 10.0 )\ny = base.log( 16.0, 2.0 )\ny = base.log( 5.0, 1.0 )\ny = base.log( NaN, 2.0 )\ny = base.log( 1.0, NaN )\ny = base.log( -4.0, 2.0 )\ny = base.log( 4.0, -2.0 )\n","base.log1mexp":"var y = base.log1mexp( -10.0 )\ny = base.log1mexp( 0.0 )\ny = base.log1mexp( 5.0 )\ny = base.log1mexp( 10.0 )\ny = base.log1mexp( NaN )\n","base.log1p":"var y = base.log1p( 4.0 )\ny = base.log1p( -1.0 )\ny = base.log1p( 0.0 )\ny = base.log1p( -0.0 )\ny = base.log1p( -2.0 )\ny = base.log1p( NaN )\n","base.log1pexp":"var y = base.log1pexp( -10.0 )\ny = base.log1pexp( 0.0 )\ny = base.log1pexp( 5.0 )\ny = base.log1pexp( 34.0 )\ny = base.log1pexp( NaN )\n","base.log1pmx":"base.log1pmx( 1.1 )\nbase.log1pmx( 0.99 )\nbase.log1pmx( -0.99 )\nbase.log1pmx( -1.1 )\nbase.log1pmx( NaN )\n","base.log2":"var y = base.log2( 4.0 )\ny = base.log2( 8.0 )\ny = base.log2( 0.0 )\ny = base.log2( PINF )\ny = base.log2( NaN )\ny = base.log2( -4.0 )\n","base.log10":"var y = base.log10( 100.0 )\ny = base.log10( 8.0 )\ny = base.log10( 0.0 )\ny = base.log10( PINF )\ny = base.log10( NaN )\ny = base.log10( -4.0 )\n","base.logaddexp":"var v = base.logaddexp( 90.0, 90.0 )\nv = base.logaddexp( -20.0, 90.0 )\nv = base.logaddexp( 0.0, -100.0 )\nv = base.logaddexp( NaN, NaN )\n","base.logit":"var y = base.logit( 0.2 )\ny = base.logit( 0.9 )\ny = base.logit( -4.0 )\ny = base.logit( 1.5 )\ny = base.logit( NaN )\n","base.lowercase":"var out = base.lowercase( 'bEEp' )\n","base.lucas":"var y = base.lucas( 0 )\ny = base.lucas( 1 )\ny = base.lucas( 2 )\ny = base.lucas( 3 )\ny = base.lucas( 4 )\ny = base.lucas( 77 )\ny = base.lucas( NaN )\n","base.lucaspoly":"var v = base.lucaspoly( 5, 2.0 )\n","base.lucaspoly.factory":"var polyval = base.lucaspoly.factory( 5 );\nvar v = polyval( 1.0 )\nv = polyval( 2.0 )\n","base.max":"var v = base.max( 3.14, 4.2 )\nv = base.max( 3.14, NaN )\nv = base.max( +0.0, -0.0 )\n","base.maxabs":"var v = base.maxabs( 3.14, -4.2 )\nv = base.maxabs( 3.14, NaN )\nv = base.maxabs( +0.0, -0.0 )\n","base.maxabsn":"var v = base.maxabsn( 3.14, -4.2 )\nv = base.maxabsn( 5.9, 3.14, 4.2 )\nv = base.maxabsn( 3.14, NaN )\nv = base.maxabsn( +0.0, -0.0 )\n","base.maxn":"var v = base.maxn( 3.14, 4.2 )\nv = base.maxn( 5.9, 3.14, 4.2 )\nv = base.maxn( 3.14, NaN )\nv = base.maxn( +0.0, -0.0 )\n","base.min":"var v = base.min( 3.14, 4.2 )\nv = base.min( 3.14, NaN )\nv = base.min( +0.0, -0.0 )\n","base.minabs":"var v = base.minabs( 3.14, -4.2 )\nv = base.minabs( 3.14, NaN )\nv = base.minabs( +0.0, -0.0 )\n","base.minabsn":"var v = base.minabsn( 3.14, -4.2 )\nv = base.minabsn( 5.9, 3.14, 4.2 )\nv = base.minabsn( 3.14, NaN )\nv = base.minabsn( +0.0, -0.0 )\n","base.minmax":"var v = base.minmax( 3.14, 4.2 )\nv = base.minmax( 3.14, NaN )\nv = base.minmax( +0.0, -0.0 )\n","base.minmax.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.minmax.assign( 3.14, -1.5, out, 1, 0 )\nvar bool = ( v === out )\n","base.minmaxabs":"var v = base.minmaxabs( 3.14, 4.2 )\nv = base.minmaxabs( -5.9, 3.14)\nv = base.minmaxabs( 3.14, NaN )\nv = base.minmaxabs( +0.0, -0.0 )\n","base.minmaxabs.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.minmaxabs.assign( 3.14, -3.14, out, 1, 0 )\nvar bool = ( v === out )\n","base.minmaxabsn":"var v = base.minmaxabsn( 3.14, 4.2 )\nv = base.minmaxabsn( -5.9, 3.14, 4.2 )\nv = base.minmaxabsn( 3.14, NaN )\nv = base.minmaxabsn( +0.0, -0.0 )\nv = base.minmaxabsn( 3.14 )\n","base.minmaxabsn.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.minmaxabsn.assign( 3.14, out, 1, 0 )\nvar bool = ( v === out )\n","base.minmaxn":"var v = base.minmaxn( 3.14, 4.2 )\nv = base.minmaxn( 5.9, 3.14, 4.2 )\nv = base.minmaxn( 3.14, NaN )\nv = base.minmaxn( +0.0, -0.0 )\nv = base.minmaxn( 3.14 )\n","base.minmaxn.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.minmaxn.assign( 3.14, -1.5, out, 1, 0 )\nvar bool = ( v === out )\n","base.minn":"var v = base.minn( 3.14, 4.2 )\nv = base.minn( 5.9, 3.14, 4.2 )\nv = base.minn( 3.14, NaN )\nv = base.minn( +0.0, -0.0 )\n","base.modf":"var parts = base.modf( 3.14 )\nparts = base.modf( 3.14 )\nparts = base.modf( +0.0 )\nparts = base.modf( -0.0 )\nparts = base.modf( PINF )\nparts = base.modf( NINF )\nparts = base.modf( NaN )\n","base.modf.assign":"var out = new Float64Array( 2 );\nvar parts = base.modf.assign( 3.14, out, 1, 0 )\nvar bool = ( parts === out )\n","base.mul":"var v = base.mul( -1.0, 5.0 )\nv = base.mul( 2.0, 5.0 )\nv = base.mul( 0.0, 5.0 )\nv = base.mul( -0.0, 0.0 )\nv = base.mul( NaN, NaN )\n","base.mulf":"var v = base.mulf( -1.0, 5.0 )\nv = base.mulf( 2.0, 5.0 )\nv = base.mulf( 0.0, 5.0 )\nv = base.mulf( -0.0, 0.0 )\nv = base.mulf( NaN, NaN )\n","base.ndarray":"var b = [ 1, 2, 3, 4 ]; // underlying data buffer\nvar d = [ 2, 2 ]; // shape\nvar s = [ 2, 1 ]; // strides\nvar o = 0; // index offset\nvar arr = base.ndarray( 'generic', b, d, s, o, 'row-major' )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40 );\narr.get( 1, 1 )\narr.iset( 3, 99 );\narr.get( 1, 1 )\n","base.ndarray.prototype.byteLength":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.byteLength\n","base.ndarray.prototype.BYTES_PER_ELEMENT":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.BYTES_PER_ELEMENT\n","base.ndarray.prototype.data":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar buf = arr.data\n","base.ndarray.prototype.dtype":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar dt = arr.dtype\n","base.ndarray.prototype.flags":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar fl = arr.flags\n","base.ndarray.prototype.length":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar len = arr.length\n","base.ndarray.prototype.ndims":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar n = arr.ndims\n","base.ndarray.prototype.offset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.offset\n","base.ndarray.prototype.order: string":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar ord = arr.order\n","base.ndarray.prototype.shape":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sh = arr.shape\n","base.ndarray.prototype.strides":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar st = arr.strides\n","base.ndarray.prototype.get":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.get( 1, 1 )\n","base.ndarray.prototype.iget":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.iget( 3 )\n","base.ndarray.prototype.set":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\narr.set( 1, 1, -4.0 );\narr.get( 1, 1 )\n","base.ndarray.prototype.iset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\narr.iset( 3, -4.0 );\narr.iget( 3 )\n","base.ndarray.prototype.toString":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toString()\n","base.ndarray.prototype.toJSON":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toJSON()\n","base.ndarrayUnary":"var xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dtype = 'float64';\nvar shape = [ 2, 2 ];\nvar sx = [ 2, 1 ];\nvar sy = [ 2, 1 ];\nvar ox = 0;\nvar oy = 0;\nvar order = 'row-major';\nvar x = ndarray( dtype, xbuf, shape, sx, ox, order );\nvar y = ndarray( dtype, ybuf, shape, sy, oy, order );\nbase.ndarrayUnary( [ x, y ], base.abs );\ny.data\nx = {\n 'dtype': dtype,\n 'data': xbuf,\n 'shape': shape,\n 'strides': sx,\n 'offset': ox,\n 'order': order\n };\ny = {\n 'dtype': dtype,\n 'data': ybuf,\n 'shape': shape,\n 'strides': sy,\n 'offset': oy,\n 'order': order\n };\nbase.ndarrayUnary( [ x, y ], base.abs );\ny.data\n","base.ndzeros":"var arr = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\nvar sh = arr.shape\nvar dt = arr.dtype\n","base.ndzerosLike":"var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\nvar sh = x.shape\nvar dt = x.dtype\nvar y = base.ndzerosLike( x )\nsh = y.shape\ndt = y.dtype\n","base.negafibonacci":"var y = base.negafibonacci( 0 )\ny = base.negafibonacci( -1 )\ny = base.negafibonacci( -2 )\ny = base.negafibonacci( -3 )\ny = base.negafibonacci( -4 )\ny = base.negafibonacci( -79 )\ny = base.negafibonacci( -80 )\ny = base.negafibonacci( NaN )\n","base.negalucas":"var y = base.negalucas( 0 )\ny = base.negalucas( -1 )\ny = base.negalucas( -2 )\ny = base.negalucas( -3 )\ny = base.negalucas( -4 )\ny = base.negalucas( -77 )\ny = base.negalucas( -78 )\ny = base.negalucas( NaN )\n","base.nonfibonacci":"var v = base.nonfibonacci( 1 )\nv = base.nonfibonacci( 2 )\nv = base.nonfibonacci( 3 )\nv = base.nonfibonacci( NaN )\n","base.normalize":"var out = base.normalize( 3.14e-319 )\nvar y = out[ 0 ];\nvar exponent = out[ 1 ];\nvar bool = ( y*base.pow(2.0, exponent) === 3.14e-319 )\nout = base.normalize( 0.0 )\nout = base.normalize( PINF )\nout = base.normalize( NINF )\nout = base.normalize( NaN )\n","base.normalize.assign":"var out = new Float64Array( 2 )\nvar v = base.normalize.assign( 3.14e-319, out, 1, 0 )\nvar bool = ( v === out )\n","base.normalizef":"var out = base.normalizef( base.float64ToFloat32( 1.401e-45 ) )\nvar y = out[ 0 ];\nvar exp = out[ 1 ];\nvar bool = ( y*base.pow(2,exp) === base.float64ToFloat32(1.401e-45) )\nout = base.normalizef( FLOAT32_PINF )\nout = base.normalizef( FLOAT32_NINF )\nout = base.normalizef( NaN )\n","base.normalizef.assign":"out = new Float32Array( 2 );\nvar v = base.normalizef.assign( base.float64ToFloat32( 1.401e-45 ), out, 1, 0 )\nbool = ( v === out )\n","base.normalizeSlice":"var s1 = new Slice( 1, 10, 1 );\nvar s2 = base.normalizeSlice( s1, 5, false );\ns2.start\ns2.stop\ns2.step\ns1 = new Slice( -2, null, -1 );\ns2 = base.normalizeSlice( s1, 10, false );\ns2.start\ns2.stop\ns2.step\n","base.normhermitepoly":"var y = base.normhermitepoly( 1, 0.5 )\ny = base.normhermitepoly( -1, 0.5 )\ny = base.normhermitepoly( 0, 0.5 )\ny = base.normhermitepoly( 2, 0.5 )\n","base.normhermitepoly.factory":"var f = base.normhermitepoly.factory( 2 );\nvar v = f( 0.5 )\n","base.pascalcase":"var out = base.pascalcase( 'Hello World!' )\nout = base.pascalcase( 'beep boop' )\n","base.pdiff":"var v = base.pdiff( 5.9, 3.14 )\nv = base.pdiff( 3.14, 4.2 )\nv = base.pdiff( 3.14, NaN )\nv = base.pdiff( -0.0, +0.0 )\n","base.pdifff":"var v = base.pdifff( 5.9, 3.15 )\nv = base.pdifff( 3.14, 4.2 )\nv = base.pdifff( 3.14, NaN )\nv = base.pdifff( -0.0, +0.0 )\n","base.percentEncode":"var out = base.percentEncode( '☃' )\n","base.polygamma":"var v = base.polygamma( 3, 1.2 )\nv = base.polygamma( 5, 1.2 )\nv = base.polygamma( 3, -4.9 )\nv = base.polygamma( -1, 5.3 )\nv = base.polygamma( 2, -1.0 )\n","base.pow":"var y = base.pow( 2.0, 3.0 )\ny = base.pow( 4.0, 0.5 )\ny = base.pow( 100.0, 0.0 )\ny = base.pow( PI, 5.0 )\ny = base.pow( PI, -0.2 )\ny = base.pow( NaN, 3.0 )\ny = base.pow( 5.0, NaN )\ny = base.pow( NaN, NaN )\n","base.powm1":"var y = base.powm1( 2.0, 3.0 )\ny = base.powm1( 4.0, 0.5 )\ny = base.powm1( 0.0, 100.0 )\ny = base.powm1( 100.0, 0.0 )\ny = base.powm1( 0.0, 0.0 )\ny = base.powm1( PI, 5.0 )\ny = base.powm1( NaN, 3.0 )\ny = base.powm1( 5.0, NaN )\n","base.rad2deg":"var d = base.rad2deg( PI/2.0 )\nd = base.rad2deg( -PI/4.0 )\nd = base.rad2deg( NaN )\nd = base.rad2deg( PI/6.0 )\n","base.rad2degf":"var d = base.rad2degf( 3.141592653589793 / 2.0 )\nd = base.rad2degf( -3.141592653589793 / 4.0 )\nd = base.rad2degf( NaN )\nd = base.rad2degf( 3.141592653589793 / 6.0 )\n","base.ramp":"var y = base.ramp( 3.14 )\ny = base.ramp( -3.14 )\n","base.rampf":"var y = base.rampf( 3.14 )\ny = base.rampf( -3.14 )\n","base.random.arcsine":"var r = base.random.arcsine( 2.0, 5.0 )\n","base.random.arcsine.factory":"var rand = base.random.arcsine.factory();\nvar r = rand( 0.0, 1.0 )\nr = rand( -2.0, 2.0 )\nrand = base.random.arcsine.factory( 0.0, 1.0 );\nr = rand()\nr = rand()\n","base.random.arcsine.NAME":"var str = base.random.arcsine.NAME\n","base.random.arcsine.PRNG":"var prng = base.random.arcsine.PRNG;\n","base.random.arcsine.seed":"var seed = base.random.arcsine.seed;\n","base.random.arcsine.seedLength":"var len = base.random.arcsine.seedLength;\n","base.random.arcsine.state":"var r = base.random.arcsine( 2.0, 4.0 )\nr = base.random.arcsine( 2.0, 4.0 )\nr = base.random.arcsine( 2.0, 4.0 )\nvar state = base.random.arcsine.state\nr = base.random.arcsine( 2.0, 4.0 )\nr = base.random.arcsine( 2.0, 4.0 )\nbase.random.arcsine.state = state;\nr = base.random.arcsine( 2.0, 4.0 )\nr = base.random.arcsine( 2.0, 4.0 )\n","base.random.arcsine.stateLength":"var len = base.random.arcsine.stateLength;\n","base.random.arcsine.byteLength":"var sz = base.random.arcsine.byteLength;\n","base.random.arcsine.toJSON":"var o = base.random.arcsine.toJSON()\n","base.random.bernoulli":"var r = base.random.bernoulli( 0.8 );\n","base.random.bernoulli.factory":"var rand = base.random.bernoulli.factory();\nvar r = rand( 0.3 );\nr = rand( 0.59 );\nrand = base.random.bernoulli.factory( 0.3 );\nr = rand();\nr = rand();\n","base.random.bernoulli.NAME":"var str = base.random.bernoulli.NAME\n","base.random.bernoulli.PRNG":"var prng = base.random.bernoulli.PRNG;\n","base.random.bernoulli.seed":"var seed = base.random.bernoulli.seed;\n","base.random.bernoulli.seedLength":"var len = base.random.bernoulli.seedLength;\n","base.random.bernoulli.state":"var r = base.random.bernoulli( 0.3 )\nr = base.random.bernoulli( 0.3 )\nr = base.random.bernoulli( 0.3 )\nvar state = base.random.bernoulli.state\nr = base.random.bernoulli( 0.3 )\nr = base.random.bernoulli( 0.3 )\nbase.random.bernoulli.state = state;\nr = base.random.bernoulli( 0.3 )\nr = base.random.bernoulli( 0.3 )\n","base.random.bernoulli.stateLength":"var len = base.random.bernoulli.stateLength;\n","base.random.bernoulli.byteLength":"var sz = base.random.bernoulli.byteLength;\n","base.random.bernoulli.toJSON":"var o = base.random.bernoulli.toJSON()\n","base.random.beta":"var r = base.random.beta( 2.0, 5.0 );\n","base.random.beta.factory":"var rand = base.random.beta.factory();\nvar r = rand( 1.5, 1.5 );\nr = rand( 2.0, 3.14 );\nrand = base.random.beta.factory( 1.5, 1.5 );\nr = rand();\nr = rand();\n","base.random.beta.NAME":"var str = base.random.beta.NAME\n","base.random.beta.PRNG":"var prng = base.random.beta.PRNG;\n","base.random.beta.seed":"var seed = base.random.beta.seed;\n","base.random.beta.seedLength":"var len = base.random.beta.seedLength;\n","base.random.beta.state":"var r = base.random.beta( 2.0, 5.0 )\nr = base.random.beta( 2.0, 5.0 )\nr = base.random.beta( 2.0, 5.0 )\nvar state = base.random.beta.state\nr = base.random.beta( 2.0, 5.0 )\nr = base.random.beta( 2.0, 5.0 )\nbase.random.beta.state = state;\nr = base.random.beta( 2.0, 5.0 )\nr = base.random.beta( 2.0, 5.0 )\n","base.random.beta.stateLength":"var len = base.random.beta.stateLength;\n","base.random.beta.byteLength":"var sz = base.random.beta.byteLength;\n","base.random.beta.toJSON":"var o = base.random.beta.toJSON()\n","base.random.betaprime":"var r = base.random.betaprime( 2.0, 5.0 );\n","base.random.betaprime.factory":"var rand = base.random.betaprime.factory();\nvar r = rand( 1.5, 1.5 );\nr = rand( 2.0, 3.14 );\nrand = base.random.betaprime.factory( 1.5, 1.5 );\nr = rand();\nr = rand();\n","base.random.betaprime.NAME":"var str = base.random.betaprime.NAME\n","base.random.betaprime.PRNG":"var prng = base.random.betaprime.PRNG;\n","base.random.betaprime.seed":"var seed = base.random.betaprime.seed;\n","base.random.betaprime.seedLength":"var len = base.random.betaprime.seedLength;\n","base.random.betaprime.state":"var r = base.random.betaprime( 2.0, 5.0 )\nr = base.random.betaprime( 2.0, 5.0 )\nr = base.random.betaprime( 2.0, 5.0 )\nvar state = base.random.betaprime.state\nr = base.random.betaprime( 2.0, 5.0 )\nr = base.random.betaprime( 2.0, 5.0 )\nbase.random.betaprime.state = state;\nr = base.random.betaprime( 2.0, 5.0 )\nr = base.random.betaprime( 2.0, 5.0 )\n","base.random.betaprime.stateLength":"var len = base.random.betaprime.stateLength;\n","base.random.betaprime.byteLength":"var sz = base.random.betaprime.byteLength;\n","base.random.betaprime.toJSON":"var o = base.random.betaprime.toJSON()\n","base.random.binomial":"var r = base.random.binomial( 20, 0.8 );\n","base.random.binomial.factory":"var rand = base.random.binomial.factory();\nvar r = rand( 20, 0.3 );\nr = rand( 10, 0.77 );\nrand = base.random.binomial.factory( 10, 0.8 );\nr = rand();\nr = rand();\n","base.random.binomial.NAME":"var str = base.random.binomial.NAME\n","base.random.binomial.PRNG":"var prng = base.random.binomial.PRNG;\n","base.random.binomial.seed":"var seed = base.random.binomial.seed;\n","base.random.binomial.seedLength":"var len = base.random.binomial.seedLength;\n","base.random.binomial.state":"var r = base.random.binomial( 20, 0.8 )\nr = base.random.binomial( 20, 0.8 )\nr = base.random.binomial( 20, 0.8 )\nvar state = base.random.binomial.state\nr = base.random.binomial( 20, 0.8 )\nr = base.random.binomial( 20, 0.8 )\nbase.random.binomial.state = state;\nr = base.random.binomial( 20, 0.8 )\nr = base.random.binomial( 20, 0.8 )\n","base.random.binomial.stateLength":"var len = base.random.binomial.stateLength;\n","base.random.binomial.byteLength":"var sz = base.random.binomial.byteLength;\n","base.random.binomial.toJSON":"var o = base.random.binomial.toJSON()\n","base.random.boxMuller":"var r = base.random.boxMuller();\n","base.random.boxMuller.factory":"var rand = base.random.boxMuller.factory();\nr = rand();\nr = rand();\n","base.random.boxMuller.NAME":"var str = base.random.boxMuller.NAME\n","base.random.boxMuller.PRNG":"var prng = base.random.boxMuller.PRNG;\n","base.random.boxMuller.seed":"var seed = base.random.boxMuller.seed;\n","base.random.boxMuller.seedLength":"var len = base.random.boxMuller.seedLength;\n","base.random.boxMuller.state":"var r = base.random.boxMuller()\nr = base.random.boxMuller()\nr = base.random.boxMuller()\nvar state = base.random.boxMuller.state\nr = 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base.random.uniform.seedLength;\n","base.random.uniform.state":"var r = base.random.uniform( 2.0, 5.0 )\nr = base.random.uniform( 2.0, 5.0 )\nr = base.random.uniform( 2.0, 5.0 )\nvar state = base.random.uniform.state\nr = base.random.uniform( 2.0, 5.0 )\nr = base.random.uniform( 2.0, 5.0 )\nbase.random.uniform.state = state;\nr = base.random.uniform( 2.0, 5.0 )\nr = base.random.uniform( 2.0, 5.0 )\n","base.random.uniform.stateLength":"var len = base.random.uniform.stateLength;\n","base.random.uniform.byteLength":"var sz = base.random.uniform.byteLength;\n","base.random.uniform.toJSON":"var o = base.random.uniform.toJSON()\n","base.random.weibull":"var r = base.random.weibull( 2.0, 5.0 );\n","base.random.weibull.factory":"var rand = base.random.weibull.factory();\nvar r = rand( 0.1, 1.5 );\nr = rand( 2.0, 3.14 );\nrand = base.random.weibull.factory( 0.1, 1.5 );\nr = rand();\nr = rand();\n","base.random.weibull.NAME":"var str = base.random.weibull.NAME\n","base.random.weibull.PRNG":"var prng = base.random.weibull.PRNG;\n","base.random.weibull.seed":"var seed = base.random.weibull.seed;\n","base.random.weibull.seedLength":"var len = base.random.weibull.seedLength;\n","base.random.weibull.state":"var r = base.random.weibull( 2.0, 5.0 )\nr = base.random.weibull( 2.0, 5.0 )\nr = base.random.weibull( 2.0, 5.0 )\nvar state = base.random.weibull.state\nr = base.random.weibull( 2.0, 5.0 )\nr = base.random.weibull( 2.0, 5.0 )\nbase.random.weibull.state = state;\nr = base.random.weibull( 2.0, 5.0 )\nr = base.random.weibull( 2.0, 5.0 )\n","base.random.weibull.stateLength":"var len = base.random.weibull.stateLength;\n","base.random.weibull.byteLength":"var sz = base.random.weibull.byteLength;\n","base.random.weibull.toJSON":"var o = base.random.weibull.toJSON()\n","base.rcbrt":"var y = base.rcbrt( 8.0 )\ny = base.rcbrt( 1000.0 )\ny = base.rcbrt( 0.0 )\ny = base.rcbrt( PINF )\ny = base.rcbrt( -8.0 )\ny = base.rcbrt( NaN )\n","base.rcbrtf":"var y = base.rcbrtf( 8.0 )\ny = base.rcbrtf( 1000.0 )\ny = base.rcbrtf( 0.0 )\ny = base.rcbrtf( PINF )\ny = base.rcbrtf( -8.0 )\ny = base.rcbrtf( NaN )\n","base.reldiff":"var d = base.reldiff( 2.0, 5.0 )\nd = base.reldiff( -1.0, 3.14 )\nd = base.reldiff( -2.0, 5.0, 'max-abs' )\nd = base.reldiff( -2.0, 5.0, 'max' )\nd = base.reldiff( -2.0, 5.0, 'min-abs' )\nd = base.reldiff( -2.0, 5.0, 'min' )\nd = base.reldiff( -2.0, 5.0, 'mean-abs' )\nd = base.reldiff( -2.0, 5.0, 'mean' )\nd = base.reldiff( -2.0, 5.0, 'x' )\nd = base.reldiff( 5.0, -2.0, 'x' )\nd = base.reldiff( -2.0, 5.0, 'y' )\nd = base.reldiff( 5.0, -2.0, 'y' )\nfunction scale( x, y ) {\n var s;\n\n x = base.abs( x );\n y = base.abs( y );\n\n // Maximum absolute value:\n s = (x < y ) ? y : x;\n\n // Scale in units of epsilon:\n return s * EPS;\n };\nd = base.reldiff( 12.15, 12.149999999999999, scale )\n","base.removeFirst":"var out = base.removeFirst( 'beep', 1 )\nout = base.removeFirst( 'Boop', 1 )\nout = base.removeFirst( 'foo bar', 5 )\n","base.removeFirstCodePoint":"var out = base.removeFirstCodePoint( 'beep', 1 )\nout = base.removeFirstCodePoint( 'Boop', 1 )\nout = base.removeFirstCodePoint( 'foo bar', 5 )\n","base.removeFirstGraphemeCluster":"var out = base.removeFirstGraphemeCluster( 'beep', 1 )\nout = base.removeFirstGraphemeCluster( 'Boop', 1 )\nout = base.removeFirstGraphemeCluster( 'foo bar', 5 )\n","base.removeLast":"var out = base.removeLast( 'beep', 1 )\nout = base.removeLast( 'Boop', 1 )\nout = base.removeLast( 'foo bar', 5 )\n","base.removeLastCodePoint":"var out = base.removeLastCodePoint( 'beep', 1 )\nout = base.removeLastCodePoint( 'Boop', 1 )\nout = base.removeLastCodePoint( 'foo bar', 5 )\n","base.removeLastGraphemeCluster":"var out = base.removeLastGraphemeCluster( 'beep', 1 )\nout = base.removeLastGraphemeCluster( 'Boop', 1 )\nout = base.removeLastGraphemeCluster( 'foo bar', 5 )\n","base.rempio2":"var y = [ 0.0, 0.0 ];\nvar n = base.rempio2( 128.0, y )\nvar y1 = y[ 0 ]\nvar y2 = y[ 1 ]\n","base.repeat":"var out = base.repeat( 'a', 5 )\nout = base.repeat( '', 100 )\nout = base.repeat( 'beep', 0 )\n","base.replace":"function replacer( match, p1 ) { return '/'+p1+'/'; };\nvar str = 'Oranges and lemons';\nvar out = base.replace( str, /([^\\s]+)/gi, replacer )\nout = base.replace( 'beep', /e/, 'o' )\n","base.replaceAfter":"var out = base.replaceAfter( 'beep boop', ' ', 'foo', 0 )\nout = base.replaceAfter( 'beep boop', 'o', 'foo', 0 )\nout = base.replaceAfter( 'Hello World!', 'o', 'foo', 5 )\nout = base.replaceAfter( 'beep boop beep baz', 'beep', 'foo', 5 )\n","base.replaceAfterLast":"var str = 'beep boop';\nvar out = base.replaceAfterLast( str, ' ', 'foo', str.length )\nout = base.replaceAfterLast( str, 'o', 'foo', str.length )\nout = base.replaceAfterLast( 'Hello World!', 'o', 'foo', 5 )\n","base.replaceBefore":"var out = base.replaceBefore( 'beep boop', ' ', 'foo', 0 )\nout = base.replaceBefore( 'beep boop', 'o', 'foo', 0 )\n","base.replaceBeforeLast":"var str = 'beep boop';\nvar out = base.replaceBeforeLast( str, ' ', 'foo', str.length )\nout = base.replaceBeforeLast( str, 'o', 'foo', str.length )\nout = base.replaceBeforeLast( 'Hello World!', 'o', 'foo', 5 )\n","base.reverse":"var out = base.reverse( 'beep' )\nout = base.reverse( 'Boop' )\nout = base.reverse( 'foo bar' )\n","base.reverseCodePoints":"var out = base.reverseCodePoints( 'beep' )\nout = base.reverseCodePoints( 'Boop' )\nout = base.reverseCodePoints( 'foo bar' )\n","base.reverseGraphemeClusters":"var out = base.reverseGraphemeClusters( 'beep' )\nout = base.reverseGraphemeClusters( 'Boop' )\nout = base.reverseGraphemeClusters( 'foo bar' )\n","base.rightPad":"var out = base.rightPad( 'a', 5, ' ' )\nout = base.rightPad( 'beep', 10, 'b' )\nout = base.rightPad( 'boop', 12, 'beep' )\n","base.rightTrim":"var out = base.rightTrim( ' \\t\\t\\n  Beep \\r\\n\\t  ' )\n","base.risingFactorial":"var v = base.risingFactorial( 0.9, 5 )\nv = base.risingFactorial( -9.0, 3 )\nv = base.risingFactorial( 0.0, 2 )\nv = base.risingFactorial( 3.0, -2 )\n","base.rotl32":"var x = 2147483649;\nvar bStr = base.toBinaryStringUint32( x )\nvar y = base.rotl32( x, 10 )\nbstr = base.toBinaryStringUint32( y )\n","base.rotr32":"var x = 1;\nvar bStr = base.toBinaryStringUint32( x )\nvar y = base.rotr32( x, 10 )\nbstr = base.toBinaryStringUint32( y )\n","base.round":"var y = base.round( 3.14 )\ny = base.round( -4.2 )\ny = base.round( -4.6 )\ny = base.round( 9.5 )\ny = base.round( -0.0 )\n","base.round2":"var y = base.round2( 3.14 )\ny = base.round2( -4.2 )\ny = base.round2( -4.6 )\ny = base.round2( 9.5 )\ny = base.round2( 13.0 )\ny = base.round2( -13.0 )\ny = base.round2( -0.0 )\n","base.round10":"var y = base.round10( 3.14 )\ny = base.round10( -4.2 )\ny = base.round10( -4.6 )\ny = base.round10( 9.5 )\ny = base.round10( 13.0 )\ny = base.round10( -13.0 )\ny = base.round10( -0.0 )\n","base.roundb":"var y = base.roundb( 3.14159, -2, 10 )\ny = base.roundb( 3.14159, 0, 2 )\ny = base.roundb( 5.0, 1, 2 )\n","base.roundn":"var y = base.roundn( 3.14159, -2 )\ny = base.roundn( 3.14159, 0 )\ny = base.roundn( 12368.0, 3 )\n","base.roundsd":"var y = base.roundsd( 3.14159, 3 )\ny = base.roundsd( 3.14159, 1 )\ny = base.roundsd( 12368.0, 2 )\ny = base.roundsd( 0.0313, 2, 2 )\n","base.rsqrt":"var y = base.rsqrt( 4.0 )\ny = base.rsqrt( 100.0 )\ny = base.rsqrt( 0.0 )\ny = base.rsqrt( Infinity )\ny = base.rsqrt( -4.0 )\ny = base.rsqrt( NaN )\n","base.rsqrtf":"var y = base.rsqrtf( 4.0 )\ny = base.rsqrtf( 0.0 )\ny = base.rsqrtf( Infinity )\ny = base.rsqrtf( -4.0 )\ny = base.rsqrtf( NaN )\n","base.sargs2multislice":"var s = new base.sargs2multislice( 'null,null,null' );\ns.data\ns = new base.sargs2multislice( '10,Slice(0,10,1),null' );\ns.data\n","base.scalar2ndarray":"var x = base.scalar2ndarray( 1.0, 'float64', 'row-major' )\nvar sh = x.shape\nvar dt = x.dtype\nvar v = x.get()\n","base.secd":"var y = base.secd( 1.0 )\ny = base.secd( PI )\ny = base.secd( -PI )\ny = base.secd( NaN )\n","base.seq2multislice":"var s = new base.seq2multislice( '1:10', [ 10 ], false );\ns.data\ns = new base.seq2multislice( '4,2:5:2,:', [ 10, 10, 10 ], false );\ns.data\n","base.seq2slice":"var s = new base.seq2slice( '1:10', 10, false );\ns.start\ns.stop\ns.step\ns = new base.seq2slice( '2:5:2', 10, false );\ns.start\ns.stop\ns.step\n","base.setHighWord":"var high = 1072693248 >>> 0;\nvar y = base.setHighWord( PINF, high )\n","base.setLowWord":"var low = 5 >>> 0;\nvar x = 3.14e201;\nvar y = base.setLowWord( x, low )\nvar low = 12345678;\nvar y = base.setLowWord( PINF, low )\ny = base.setLowWord( NINF, low )\ny = base.setLowWord( NaN, low )\n","base.sici":"var y = base.sici( 3.0 )\ny = base.sici( 0.0 )\ny = base.sici( -9.0 )\ny = base.sici( NaN )\n","base.sici.assign":"var out = new Float64Array( 2 );\nvar y = base.sici.assign( 3.0, out, 1, 0 )\nvar bool = ( y === out )\n","base.signbit":"var bool = base.signbit( 4.0 )\nbool = base.signbit( -9.14e-34 )\nbool = base.signbit( 0.0 )\nbool = base.signbit( -0.0 )\n","base.signbitf":"var bool = base.signbitf( base.float64ToFloat32( 4.0 ) )\nbool = base.signbitf( base.float64ToFloat32( -9.14e-34 ) )\nbool = base.signbitf( 0.0 )\nbool = base.signbitf( -0.0 )\n","base.significandf":"var s = base.significandf( base.float64ToFloat32( 3.14e34 ) )\ns = base.significandf( base.float64ToFloat32( 3.14e-34 ) )\ns = base.significandf( base.float64ToFloat32( -3.14 ) )\ns = base.significandf( 0.0 )\ns = base.significandf( NaN )\n","base.signum":"var sign = base.signum( -5.0 )\nsign = base.signum( 5.0 )\nsign = base.signum( -0.0 )\nsign = base.signum( 0.0 )\nsign = base.signum( NaN )\n","base.signumf":"var sign = base.signumf( -5.0 )\nsign = base.signumf( 5.0 )\nsign = base.signumf( -0.0 )\nsign = base.signumf( 0.0 )\nsign = base.signumf( NaN )\n","base.sin":"var y = base.sin( 0.0 )\ny = base.sin( PI/2.0 )\ny = base.sin( -PI/6.0 )\ny = base.sin( NaN )\n","base.sinc":"var y = base.sinc( 0.5 )\ny = base.sinc( -1.2 )\ny = base.sinc( 0.0 )\ny = base.sinc( NaN )\n","base.sincos":"var y = base.sincos( 0.0 )\ny = base.sincos( PI/2.0 )\ny = base.sincos( -PI/6.0 )\ny = base.sincos( NaN )\nvar out = new Float64Array( 2 );\nvar v = base.sincos.assign( 0.0, out, 1, 0 )\nvar bool = ( v === out )\n","base.sincospi":"var y = base.sincospi( 0.0 )\ny = base.sincospi( 0.5 )\ny = base.sincospi( 0.1 )\ny = base.sincospi( NaN )\n","base.sincospi.assign":"var out = new Float64Array( 2 );\nvar v = base.sincospi.assign( 0.0, out, 1, 0 )\nvar bool = ( v === out )\n","base.sinh":"var y = base.sinh( 0.0 )\ny = base.sinh( 2.0 )\ny = base.sinh( -2.0 )\ny = base.sinh( NaN )\n","base.sinpi":"var y = base.sinpi( 0.0 )\ny = base.sinpi( 0.5 )\ny = base.sinpi( 0.9 )\ny = base.sinpi( NaN )\n","base.slice2seq":"var out = base.slice2seq( new Slice( 1, 10, 1 ) )\nout = base.slice2seq( new Slice( null, 10 ) )\n","base.sliceLength":"var s = new Slice( 1, 10, 1 );\nbase.sliceLength( s )\n","base.sliceNonReducedDimensions":"var s = new MultiSlice( 1, 3, null );\nvar out = base.sliceNonReducedDimensions( s )\n","base.sliceReducedDimensions":"var s = new MultiSlice( 1, 3, null );\nvar out = base.sliceReducedDimensions( s )\n","base.sliceShape":"var s = new Slice( 1, 10, 1 );\nvar ms = new MultiSlice( s, s );\nbase.sliceShape( ms )\n","base.snakecase":"var out = base.snakecase( 'Hello World!' )\nout = base.snakecase( 'I am a tiny little teapot' )\n","base.spence":"var y = base.spence( 3.0 )\ny = base.spence( 0.0 )\ny = base.spence( -9.0 )\ny = base.spence( NaN )\n","base.sqrt":"var y = base.sqrt( 4.0 )\ny = base.sqrt( 9.0 )\ny = base.sqrt( 0.0 )\ny = base.sqrt( -4.0 )\ny = base.sqrt( NaN )\n","base.sqrt1pm1":"var y = base.sqrt1pm1( 3.0 )\ny = base.sqrt1pm1( 0.5 )\ny = base.sqrt1pm1( 0.02 )\ny = base.sqrt1pm1( -0.5 )\ny = base.sqrt1pm1( -1.1 )\ny = base.sqrt1pm1( NaN )\n","base.sqrtf":"var y = base.sqrtf( 4.0 )\ny = base.sqrtf( 9.0 )\ny = base.sqrtf( 0.0 )\ny = base.sqrtf( -4.0 )\ny = base.sqrtf( NaN )\n","base.sqrtpi":"var y = base.sqrtpi( 4.0 )\ny = base.sqrtpi( 10.0 )\ny = base.sqrtpi( 0.0 )\ny = base.sqrtpi( -4.0 )\ny = base.sqrtpi( NaN )\n","base.startcase":"var out = base.startcase( 'beep boop' )\n","base.startsWith":"var bool = base.startsWith( 'Beep', 'Be', 0 )\nbool = base.startsWith( 'Beep', 'ep', 0 )\nbool = base.startsWith( 'Beep', 'ee', 1 )\nbool = base.startsWith( 'Beep', 'ee', -3 )\nbool = base.startsWith( 'Beep', '', 0 )\n","base.stickycase":"var out = base.stickycase( 'Hello World!' )\nout = base.stickycase( 'I am a tiny little teapot' )\n","base.strided.binary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nfunction f( x, y ) { return x + y; };\nbase.strided.binary( [ x, y, z ], shape, strides, f );\nz\n","base.strided.binary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nvar offsets = [ 0, 0, 0 ];\nfunction f( x, y ) { return x + y; };\nbase.strided.binary.ndarray( [ x, y, z ], shape, strides, offsets, f );\nz\n","base.strided.binaryDtypeSignatures":"var dt = strided.dataTypes();\nvar out = base.strided.binaryDtypeSignatures( dt, dt, dt )\n","base.strided.binarySignatureCallbacks":"var dt = strided.dataTypes();\nvar sigs = base.strided.binaryDtypeSignatures( dt, dt, dt );\nvar t = {\n 'default': base.add,\n 'complex64': base.caddf,\n 'complex128': base.cadd\n };\nvar out = base.strided.binarySignatureCallbacks( t, sigs )\n","base.strided.ccopy":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.ccopy( x.length, x, 1, y, 1 );\nvar z = y.get( 0 );\nvar re = realf( z )\nvar im = imagf( z )\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ccopy( 2, x, -2, y, 1 );\nz = y.get( 0 );\nre = realf( z )\nim = imagf( z )\nvar x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\nvar y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.ccopy( 2, x1, -2, y1, 1 );\nz = y0.get( 2 );\nre = realf( z )\nim = imagf( z )\n","base.strided.ccopy.ndarray":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.ccopy.ndarray( x.length, x, 1, 0, y, 1, 0 );\nvar z = y.get( 0 );\nvar re = realf( z )\nvar im = imagf( z )\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ccopy.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\nz = y.get( y.length-1 );\nre = realf( z )\nim = imagf( z )\n","base.strided.cmap":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex64Array( xbuf );\nvar y = new Complex64Array( x.length );\nbase.strided.cmap( x.length, x, 1, y, 1, base.cidentityf );\nvar v = y.get( 0 )\nvar re = real( v )\nvar im = imag( v )\ny = new Complex64Array( x.length );\nbase.strided.cmap( 2, x, 2, y, -1, base.cidentityf );\nv = y.get( 0 )\nre = real( v )\nim = imag( v )\nvar x0 = new Complex64Array( xbuf );\nvar y0 = new Complex64Array( x0.length );\nvar x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.cmap( 2, x1, -2, y1, 1, base.cidentityf );\nv = y1.get( 0 )\nre = real( v )\nim = imag( v )\n","base.strided.cmap.ndarray":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex64Array( xbuf );\nvar y = new Complex64Array( x.length );\nbase.strided.cmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentityf );\nvar v = y.get( 0 )\nvar re = real( v )\nvar im = imag( v )\nx = new Complex64Array( xbuf );\ny = new Complex64Array( x.length );\nbase.strided.cmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentityf );\nv = y.get( y.length-1 )\nre = real( v )\nim = imag( v )\n","base.strided.cswap":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.cswap( x.length, x, 1, y, 1 );\nvar z = y.get( 0 );\nvar re = realf( z )\nvar im = imagf( z )\nz = x.get( 0 );\nre = realf( z )\nim = imagf( z )\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.cswap( 2, x, -2, y, 1 );\nz = y.get( 0 );\nre = realf( z )\nim = imagf( z )\nz = x.get( 0 );\nre = realf( z )\nim = imagf( z )\nvar x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\nvar y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.cswap( 2, x1, -2, y1, 1 );\nz = y0.get( 2 );\nre = realf( z )\nim = imagf( z )\nz = x0.get( 1 );\nre = realf( z )\nim = imagf( z )\n","base.strided.cswap.ndarray":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.cswap.ndarray( x.length, x, 1, 0, y, 1, 0 );\nvar z = y.get( 0 );\nvar re = realf( z )\nvar im = imagf( z )\nz = x.get( 0 );\nre = realf( z )\nim = imagf( z )\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.cswap.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\nz = y.get( y.length-1 );\nre = realf( z )\nim = imagf( z )\nz = x.get( 1 );\nre = realf( z )\nim = imagf( z )\n","base.strided.cumax":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumax( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumax( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.cumax( N, x1, 2, y1, 1 )\ny0\n","base.strided.cumax.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumax.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.cumaxabs":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumaxabs( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumaxabs( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.cumaxabs( N, x1, 2, y1, 1 )\ny0\n","base.strided.cumaxabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.cumin":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumin( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumin( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.cumin( N, x1, 2, y1, 1 )\ny0\n","base.strided.cumin.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.cuminabs":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cuminabs( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cuminabs( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.cuminabs( N, x1, 2, y1, 1 )\ny0\n","base.strided.cuminabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dabs":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dabs( N, x1, -2, y1, 1 )\ny0\n","base.strided.dabs.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dabs2":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs2( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs2( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dabs2( N, x1, -2, y1, 1 )\ny0\n","base.strided.dabs2.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dapx":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dapx( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dapx( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapx( 3, 5.0, x1, 2 )\nx0\n","base.strided.dapx.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dapx.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.dapx.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsum":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsum( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsum( 3, 5.0, x1, 2 )\n","base.strided.dapxsum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsumkbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsumkbn( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsumkbn( 3, 5.0, x1, 2)\n","base.strided.dapxsumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsumkbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn2( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsumkbn2( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsumkbn2( 3, 5.0, x1, 2 )\n","base.strided.dapxsumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsumors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumors( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsumors( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsumors( 3, 5.0, x1, 2 )\n","base.strided.dapxsumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumpw( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsumpw( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsumpw( 3, 5.0, x1, 2 )\n","base.strided.dapxsumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dasum":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.dasum( x.length, x, 1 )\ns = base.strided.dasum( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\ns = base.strided.dasum( 3, x1, 2 )\n","base.strided.dasum.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.dasum.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\ns = base.strided.dasum.ndarray( 3, x, -1, x.length-1 )\n","base.strided.dasumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dasumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar stride = 2;\nbase.strided.dasumpw( 3, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.dasumpw( 3, x1, stride )\n","base.strided.dasumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dasumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dasumpw.ndarray( 3, x, 2, 1 )\n","base.strided.daxpy":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.daxpy( x.length, alpha, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nbase.strided.daxpy( 3, alpha, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.daxpy( 3, 5.0, x1, -2, y1, 1 )\ny0\n","base.strided.daxpy.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.daxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.daxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcbrt":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dcbrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dcbrt( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dcbrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.dcbrt.ndarray":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dcbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dceil":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dceil( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dceil( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dceil( N, x1, -2, y1, 1 )\ny0\n","base.strided.dceil.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcopy":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dcopy( x.length, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dcopy( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcopy( 3, x1, -2, y1, 1 )\ny0\n","base.strided.dcopy.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcumax":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumax( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumax( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcumax( 3, x1, 2, y1, 1 )\ny0\n","base.strided.dcumax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcumaxabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumaxabs( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumaxabs( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcumaxabs( 3, x1, 2, y1, 1 )\ny0\n","base.strided.dcumaxabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcumin":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumin( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumin( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcumin( 3, x1, 2, y1, 1 )\ny0\n","base.strided.dcumin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcuminabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcuminabs( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcuminabs( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcuminabs( 3, x1, 2, y1, 1 )\ny0\n","base.strided.dcuminabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusum":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusum( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusum( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusum( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumkbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumkbn( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusumkbn( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumkbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn2( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumkbn2( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusumkbn2( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumors( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumors( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusumors( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumpw( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumpw( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusumpw( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.ddeg2rad":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ddeg2rad( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ddeg2rad( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.ddeg2rad( N, x1, -2, y1, 1 )\ny0\n","base.strided.ddeg2rad.ndarray":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ddeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ddeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.ddot":"var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.ddot( x.length, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.ddot( 3, x, 2, y, -1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.ddot( 3, x1, -2, y1, 1 )\n","base.strided.ddot.ndarray":"var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.ddot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.ddot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nout = base.strided.ddot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.dfill":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dfill( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dfill( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dfill( 3, 5.0, x1, 2 )\nx0\n","base.strided.dfill.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dfill.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.dfill.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dfloor":"var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dfloor( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dfloor( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dfloor( N, x1, -2, y1, 1 )\ny0\n","base.strided.dfloor.ndarray":"var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dinv":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dinv( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dinv( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dinv( N, x1, -2, y1, 1 )\ny0\n","base.strided.dinv.ndarray":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dmap":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap( x.length, x, 1, y, 1, base.identity )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap( 2, x, 2, y, -1, base.identity )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmap( 2, x1, -2, y1, 1, base.identity )\ny0\n","base.strided.dmap.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identity )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identity )\n","base.strided.dmap2":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2( x.length, x, 1, y, 1, z, 1, base.add )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2( 2, x, 2, y, -1, z, 1, base.add )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmap2( 2, x1, -2, y1, 1, z1, 1, base.add )\nz0\n","base.strided.dmap2.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.add )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.add )\n","base.strided.dmax":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmax( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmax( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmax( 3, x1, 2 )\n","base.strided.dmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmax.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmax.ndarray( 3, x, 2, 1 )\n","base.strided.dmaxabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmaxabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmaxabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmaxabs( 3, x1, 2 )\n","base.strided.dmaxabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmaxabs.ndarray( 3, x, 2, 1 )\n","base.strided.dmaxabssorted":"var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.dmaxabssorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmaxabssorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmaxabssorted( 3, x1, 2 )\n","base.strided.dmaxabssorted.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.dmaxabssorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.dmaxabssorted.ndarray( 3, x, 2, 1 )\n","base.strided.dmaxsorted":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmaxsorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmaxsorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmaxsorted( 3, x1, 2 )\n","base.strided.dmaxsorted.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmaxsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.dmaxsorted.ndarray( 3, x, 2, 1 )\n","base.strided.dmean":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmean( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmean( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmean( N, x1, stride )\n","base.strided.dmean.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmean.ndarray( N, x, 2, 1 )\n","base.strided.dmeankbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeankbn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeankbn( N, x1, stride )\n","base.strided.dmeankbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeankbn.ndarray( N, x, 2, 1 )\n","base.strided.dmeankbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeankbn2( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeankbn2( N, x1, stride )\n","base.strided.dmeankbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeankbn2.ndarray( N, x, 2, 1 )\n","base.strided.dmeanli":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanli( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanli( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanli( N, x1, stride )\n","base.strided.dmeanli.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanli.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanli.ndarray( N, x, 2, 1 )\n","base.strided.dmeanlipw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanlipw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanlipw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanlipw( N, x1, stride )\n","base.strided.dmeanlipw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanlipw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanlipw.ndarray( N, x, 2, 1 )\n","base.strided.dmeanors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanors( N, x1, stride )\n","base.strided.dmeanors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanors.ndarray( N, x, 2, 1 )\n","base.strided.dmeanpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanpn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanpn( N, x1, stride )\n","base.strided.dmeanpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.dmeanpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanpw( N, x1, stride )\n","base.strided.dmeanpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanpw.ndarray( N, x, 2, 1 )\n","base.strided.dmeanstdev":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdev( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanstdev( N, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdev( N, 1, x1, 2, out, 1 )\n","base.strided.dmeanstdev.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdev.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdev.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanstdevpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdevpn( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanstdevpn( N, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdevpn( N, 1, x1, 2, out, 1 )\n","base.strided.dmeanstdevpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdevpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdevpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanvar":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvar( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanvar( N, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanvar( N, 1, x1, 2, out, 1 )\n","base.strided.dmeanvar.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvar.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanvar.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanvarpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvarpn( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanvarpn( N, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanvarpn( N, 1, x1, 2, out, 1 )\n","base.strided.dmeanvarpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvarpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanvarpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanwd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanwd( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanwd( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanwd( N, x1, stride )\n","base.strided.dmeanwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanwd.ndarray( N, x, 2, 1 )\n","base.strided.dmediansorted":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmediansorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmediansorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmediansorted( 3, x1, 2 )\n","base.strided.dmediansorted.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.dmediansorted.ndarray( 3, x, 2, 1 )\n","base.strided.dmidrange":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmidrange( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmidrange( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmidrange( 3, x1, 2 )\n","base.strided.dmidrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmidrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmidrange.ndarray( 3, x, 2, 1 )\n","base.strided.dmin":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmin( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmin( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmin( N, x1, stride )\n","base.strided.dmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmin.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmin.ndarray( 3, x, 2, 1 )\n","base.strided.dminabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dminabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dminabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dminabs( 3, x1, 2 )\n","base.strided.dminabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dminabs.ndarray( 3, x, 2, 1 )\n","base.strided.dminsorted":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dminsorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dminsorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dminsorted( 3, x1, 2 )\n","base.strided.dminsorted.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dminsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.dminsorted.ndarray( 3, x, 2, 1 )\n","base.strided.dmskabs":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskabs( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskabs.ndarray":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskabs2":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskabs2( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskabs2.ndarray":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskcbrt":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskcbrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskcbrt.ndarray":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskceil":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskceil( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskceil.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskdeg2rad":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskdeg2rad.ndarray":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskfloor":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskfloor( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskfloor.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskinv":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskinv( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskinv.ndarray":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskmap":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap( x.length, x, 1, m, 1, y, 1, base.identity )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap( 2, x, 2, m, 2, y, -1, base.identity )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\ny0\n","base.strided.dmskmap.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n","base.strided.dmskmap2":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.add )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.add )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.add )\nz0\n","base.strided.dmskmap2.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.add )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.add )\n","base.strided.dmskmax":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmax( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskmax( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmskmax( 3, x1, 2, mask1, 2 )\n","base.strided.dmskmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.dmskmin":"var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmin( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskmin( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmskmin( 3, x1, 2, mask1, 2 )\n","base.strided.dmskmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.dmskramp":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskramp( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskramp.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskrange":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskrange( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskrange( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmskrange( 3, x1, 2, mask1, 2 )\n","base.strided.dmskrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.dmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.dmskrsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskrsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmsksqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmsksqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmsksqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmsktrunc":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmsktrunc( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmsktrunc.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dnanasum":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasum( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanasum( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanasum( 4, x1, 2 )\n","base.strided.dnanasum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasum.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanasum.ndarray( 4, x, 2, 1 )\n","base.strided.dnanasumors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasumors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanasumors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanasumors( N, x1, stride )\n","base.strided.dnanasumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanasumors.ndarray( N, x, 2, 1 )\n","base.strided.dnanmax":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmax( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanmax( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmax( 3, x1, 2 )\n","base.strided.dnanmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanmax.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanmax.ndarray( 3, x, 2, 1 )\n","base.strided.dnanmaxabs":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmaxabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanmaxabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmaxabs( 3, x1, 2 )\n","base.strided.dnanmaxabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanmaxabs.ndarray( 3, x, 2, 1 )\n","base.strided.dnanmean":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmean( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmean( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmean( N, x1, stride )\n","base.strided.dnanmean.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmean.ndarray( N, x, 2, 1 )\n","base.strided.dnanmeanors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmeanors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmeanors( N, x1, stride )\n","base.strided.dnanmeanors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmeanors.ndarray( N, x, 2, 1 )\n","base.strided.dnanmeanpn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmeanpn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmeanpn( N, x1, stride )\n","base.strided.dnanmeanpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.dnanmeanpw":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmeanpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmeanpw( N, x1, stride )\n","base.strided.dnanmeanpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmeanpw.ndarray( N, x, 2, 1 )\n","base.strided.dnanmeanwd":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanwd( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmeanwd( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmeanwd( N, x1, stride )\n","base.strided.dnanmeanwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmeanwd.ndarray( N, x, 2, 1 )\n","base.strided.dnanmin":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmin( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanmin( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmin( 3, x1, 2 )\n","base.strided.dnanmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanmin.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanmin.ndarray( 3, x, 2, 1 )\n","base.strided.dnanminabs":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanminabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanminabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanminabs( 3, x1, 2 )\n","base.strided.dnanminabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanminabs.ndarray( 3, x, 2, 1 )\n","base.strided.dnanmskmax":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.dnanmskmax( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskmax( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dnanmskmax( N, x1, 2, mask1, 2 )\n","base.strided.dnanmskmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.dnanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.dnanmskmin":"var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.dnanmskmin( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskmin( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dnanmskmin( N, x1, 2, mask1, 2 )\n","base.strided.dnanmskmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.dnanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.dnanmskrange":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.dnanmskrange( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskrange( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dnanmskrange( N, x1, 2, mask1, 2 )\n","base.strided.dnanmskrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.dnanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.dnannsum":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsum( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsum( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsum( 4, x1, 2, out, 1 )\n","base.strided.dnannsum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsum.ndarray( x.length, x, 1, 0, out, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsum.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumkbn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn( 4, x1, 2, out, 1 )\n","base.strided.dnannsumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn.ndarray( 4, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumkbn2":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn2( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn2( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn2( 4, x1, 2, out, 1 )\n","base.strided.dnannsumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn2.ndarray( 4, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn2.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumors( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumors( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumors( 4, x1, 2, out, 1 )\n","base.strided.dnannsumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumpw":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumpw( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumpw( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumpw( 4, x1, 2, out, 1 )\n","base.strided.dnannsumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumpw.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumpw.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnanrange":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanrange( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanrange( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanrange( 3, x1, 2 )\n","base.strided.dnanrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanrange.ndarray( 3, x, 2, 1 )\n","base.strided.dnanstdev":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdev( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdev( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdev( N, 1, x1, stride )\n","base.strided.dnanstdev.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanstdevch":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevch( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdevch( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdevch( N, 1, x1, stride )\n","base.strided.dnanstdevch.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanstdevpn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevpn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdevpn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdevpn( N, 1, x1, stride )\n","base.strided.dnanstdevpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanstdevtk":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevtk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdevtk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdevtk( N, 1, x1, stride )\n","base.strided.dnanstdevtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanstdevwd":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevwd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdevwd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdevwd( N, 1, x1, stride )\n","base.strided.dnanstdevwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanstdevyc":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdevyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdevyc( N, 1, x1, stride )\n","base.strided.dnanstdevyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnansum":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansum( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansum( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansum( 4, x1, 2 )\n","base.strided.dnansum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansum.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansum.ndarray( 4, x, 2, 1 )\n","base.strided.dnansumkbn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumkbn( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansumkbn( 4, x1, 2 )\n","base.strided.dnansumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumkbn.ndarray( 4, x, 2, 1 )\n","base.strided.dnansumkbn2":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumkbn2( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansumkbn2( 4, x1, 2 )\n","base.strided.dnansumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumkbn2.ndarray( 4, x, 2, 1 )\n","base.strided.dnansumors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumors( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansumors( 4, x1, 2 )\n","base.strided.dnansumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumors.ndarray( 4, x, 2, 1 )\n","base.strided.dnansumpw":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumpw( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansumpw( 4, x1, 2 )\n","base.strided.dnansumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumpw.ndarray( 4, x, 2, 1 )\n","base.strided.dnanvariance":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariance( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvariance( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvariance( N, 1, x1, stride )\n","base.strided.dnanvariance.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanvariancech":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancech( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvariancech( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvariancech( N, 1, x1, stride )\n","base.strided.dnanvariancech.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvariancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanvariancepn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancepn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvariancepn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvariancepn( N, 1, x1, stride )\n","base.strided.dnanvariancepn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanvariancetk":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancetk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvariancetk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvariancetk( N, 1, x1, stride )\n","base.strided.dnanvariancetk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvariancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanvariancewd":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancewd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvariancewd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvariancewd( N, 1, x1, stride )\n","base.strided.dnanvariancewd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvariancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanvarianceyc":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvarianceyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvarianceyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvarianceyc( N, 1, x1, stride )\n","base.strided.dnanvarianceyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvarianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnrm2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dnrm2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dnrm2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnrm2( 3, x1, 2 )\n","base.strided.dnrm2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dnrm2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dnrm2.ndarray( 3, x, 2, 1 )\n","base.strided.dramp":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dramp( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dramp( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dramp( N, x1, -2, y1, 1 )\ny0\n","base.strided.dramp.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.drange":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.drange( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.drange( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.drange( 3, x1, 2 )\n","base.strided.drange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.drange.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.drange.ndarray( 3, x, 2, 1 )\n","base.strided.drev":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.drev( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.drev( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.drev( 3, x1, 2 )\nx0\n","base.strided.drev.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.drev.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.drev.ndarray( 3, x, 2, 1 )\n","base.strided.drsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.drsqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.drsqrt( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.drsqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.drsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.drsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.drsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dsapxsum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsum( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsapxsum( 3, 5.0, x1, 2 )\n","base.strided.dsapxsum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dsapxsumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsumpw( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsapxsumpw( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsapxsumpw( 3, 5.0, x1, 2 )\n","base.strided.dsapxsumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dscal":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dscal( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dscal( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dscal( 3, 5.0, x1, 2 )\nx0\n","base.strided.dscal.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dscal.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.dscal.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dsdot":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar dot = base.strided.dsdot( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\ndot = base.strided.dsdot( 3, x, 2, y, -1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\ndot = base.strided.dsdot( 3, x1, -2, y1, 1 )\n","base.strided.dsdot.ndarray":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar dot = base.strided.dsdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\ndot = base.strided.dsdot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\ndot = base.strided.dsdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.dsem":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsem( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsem( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsem( N, 1, x1, stride )\n","base.strided.dsem.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsem.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsem.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsemch":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemch( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsemch( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsemch( N, 1, x1, stride )\n","base.strided.dsemch.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsemch.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsempn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsempn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsempn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsempn( N, 1, x1, stride )\n","base.strided.dsempn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsempn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsempn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsemtk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemtk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsemtk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsemtk( N, 1, x1, stride )\n","base.strided.dsemtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsemtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsemwd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemwd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsemwd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsemwd( N, 1, x1, stride )\n","base.strided.dsemwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsemwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsemyc":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsemyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsemyc( N, 1, x1, stride )\n","base.strided.dsemyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsemyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsmean":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsmean( N, x1, stride )\n","base.strided.dsmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsmean.ndarray( N, x, 2, 1 )\n","base.strided.dsmeanors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsmeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsmeanors( N, x1, stride )\n","base.strided.dsmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsmeanors.ndarray( N, x, 2, 1 )\n","base.strided.dsmeanpn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsmeanpn( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsmeanpn( N, x1, stride )\n","base.strided.dsmeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.dsmeanpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsmeanpw( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsmeanpw( N, x1, stride )\n","base.strided.dsmeanpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsmeanpw.ndarray( N, x, 2, 1 )\n","base.strided.dsmeanwd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsmeanwd( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsmeanwd( N, x1, stride )\n","base.strided.dsmeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsmeanwd.ndarray( N, x, 2, 1 )\n","base.strided.dsnanmean":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsnanmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsnanmean( N, x1, stride )\n","base.strided.dsnanmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsnanmean.ndarray( N, x, 2, 1 )\n","base.strided.dsnanmeanors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsnanmeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsnanmeanors( N, x1, stride )\n","base.strided.dsnanmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsnanmeanors.ndarray( N, x, 2, 1 )\n","base.strided.dsnanmeanpn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsnanmeanpn( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsnanmeanpn( N, x1, stride )\n","base.strided.dsnanmeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsnanmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.dsnanmeanwd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsnanmeanwd( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsnanmeanwd( N, x1, stride )\n","base.strided.dsnanmeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsnanmeanwd.ndarray( N, x, 2, 1 )\n","base.strided.dsnannsumors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dsnannsumors( x.length, x, 1, out, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dsnannsumors( 4, x, 2, out, 1 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dsnannsumors( N, x1, 2, out, 1 )\n","base.strided.dsnannsumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dsnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dsnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dsnansum":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansum( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnansum( 4, x1, 2 )\n","base.strided.dsnansum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansum.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsnansum.ndarray( 3, x, 2, 1 )\n","base.strided.dsnansumors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansumors( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnansumors( 4, x1, 2 )\n","base.strided.dsnansumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansumors.ndarray( 4, x, 2, 1 )\n","base.strided.dsnansumpw":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansumpw( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnansumpw( 4, x1, 2 )\n","base.strided.dsnansumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansumpw.ndarray( 4, x, 2, 1 )\n","base.strided.dsort2hp":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2hp( x.length, 1, x, 1, y, 1 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2hp( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsort2hp( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.dsort2hp.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.dsort2ins":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2ins( x.length, 1, x, 1, y, 1 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2ins( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsort2ins( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.dsort2ins.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.dsort2sh":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2sh( x.length, 1, x, 1, y, 1 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2sh( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsort2sh( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.dsort2sh.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.dsorthp":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsorthp( x.length, 1, x, 1 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsorthp( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsorthp( N, 1, x1, 2 )\nx0\n","base.strided.dsorthp.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsorthp.ndarray( x.length, 1, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsorthp.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsortins":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortins( x.length, 1, x, 1 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsortins( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsortins( N, 1, x1, 2 )\nx0\n","base.strided.dsortins.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortins.ndarray( x.length, 1, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsortins.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsortsh":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortsh( x.length, 1, x, 1 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsortsh( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsortsh( N, 1, x1, 2 )\nx0\n","base.strided.dsortsh.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortsh.ndarray( x.length, 1, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsortsh.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dsqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dsqrt( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.dsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dssum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dssum( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dssum( 3, x1, 2 )\n","base.strided.dssum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssum.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dssum.ndarray(3, x, 2, 1 )\n","base.strided.dssumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dssumors( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dssumors( 3, x1, 2 )\n","base.strided.dssumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dssumors.ndarray( 3, x, 2, 1 )\n","base.strided.dssumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dssumpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dssumpw( 3, x1, 2 )\n","base.strided.dssumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dssumpw.ndarray( 3, x, 2, 1 )\n","base.strided.dstdev":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdev( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdev( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdev( N, 1, x1, stride )\n","base.strided.dstdev.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.dstdevch":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevch( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdevch( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdevch( N, 1, x1, stride )\n","base.strided.dstdevch.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.dstdevpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevpn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdevpn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdevpn( N, 1, x1, stride )\n","base.strided.dstdevpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dstdevtk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevtk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdevtk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdevtk( N, 1, x1, stride )\n","base.strided.dstdevtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.dstdevwd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevwd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdevwd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdevwd( N, 1, x1, stride )\n","base.strided.dstdevwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.dstdevyc":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdevyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdevyc( N, 1, x1, stride )\n","base.strided.dstdevyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsum":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsum( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsum( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsum( 3, x1, 2 )\n","base.strided.dsum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsum.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsum.ndarray( 3, x, 2, 1 )\n","base.strided.dsumkbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumkbn( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumkbn( 3, x1, 2 )\n","base.strided.dsumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsumkbn.ndarray( 3, x, 2, 1 )\n","base.strided.dsumkbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumkbn2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumkbn2( 3, x1, 2 )\n","base.strided.dsumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsumkbn2.ndarray( 3, x, 2, 1 )\n","base.strided.dsumors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumors( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumors( 3, x1, 2 )\n","base.strided.dsumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsumors.ndarray( 3, x, 2, 1 )\n","base.strided.dsumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumpw( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumpw( 3, x1, 2 )\n","base.strided.dsumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumpw.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsumpw.ndarray( 3, x, 2, 1 )\n","base.strided.dsvariance":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariance( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsvariance( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsvariance( N, 1, x1, stride )\n","base.strided.dsvariance.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsvariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsvariancepn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariancepn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsvariancepn( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsvariancepn( N, 1, x1, stride )\n","base.strided.dsvariancepn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsvariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dswap":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dswap( x.length, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dswap( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dswap( 3, x1, -2, y1, 1 )\ny0\n","base.strided.dswap.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dtrunc":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dtrunc( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dtrunc( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dtrunc( N, x1, -2, y1, 1 )\ny0\n","base.strided.dtrunc.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dtrunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dtrunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dtypeEnum2Str":"var out = base.strided.dtypeEnum2Str( base.strided.dtypeStr2Enum( 'float64' ) )\n","base.strided.dtypeResolveEnum":"var out = base.strided.dtypeResolveEnum( 'float64' )\nout = base.strided.dtypeResolveEnum( base.strided.dtypeStr2Enum( 'float64' ) )\n","base.strided.dtypeResolveStr":"var out = base.strided.dtypeResolveStr( 'float64' )\nout = base.strided.dtypeResolveStr( base.strided.dtypeStr2Enum( 'float64' ) )\n","base.strided.dtypeStr2Enum":"var out = base.strided.dtypeStr2Enum( 'float64' )\n","base.strided.dvariance":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariance( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvariance( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvariance( N, 1, x1, stride )\n","base.strided.dvariance.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.dvariancech":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancech( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvariancech( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvariancech( N, 1, x1, stride )\n","base.strided.dvariancech.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvariancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.dvariancepn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancepn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvariancepn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvariancepn( N, 1, x1, stride )\n","base.strided.dvariancepn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dvariancetk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancetk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvariancetk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvariancetk( N, 1, x1, stride )\n","base.strided.dvariancetk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvariancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.dvariancewd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancewd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvariancewd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvariancewd( N, 1, x1, stride )\n","base.strided.dvariancewd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvariancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.dvarianceyc":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarianceyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvarianceyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvarianceyc( N, 1, x1, stride )\n","base.strided.dvarianceyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.dvarm":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarm( x.length, 1.0/3.0, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarm( N, 1.0/3.0, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dvarm( N, 1.0/3.0, 1, x1, 2 )\n","base.strided.dvarm.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarm.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarm.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n","base.strided.dvarmpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmpn( x.length, 1.0/3.0, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarmpn( N, 1.0/3.0, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dvarmpn( N, 1.0/3.0, 1, x1, 2 )\n","base.strided.dvarmpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmpn.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarmpn.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n","base.strided.dvarmtk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmtk( x.length, 1.0/3.0, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarmtk( N, 1.0/3.0, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dvarmtk( N, 1.0/3.0, 1, x1, 2 )\n","base.strided.dvarmtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmtk.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarmtk.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n","base.strided.gapx":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar alpha = 5.0;\nbase.strided.gapx( x.length, alpha, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nalpha = 5.0;\nvar stride = 2;\nbase.strided.gapx( N, alpha, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nalpha = 5.0;\nstride = 2;\nbase.strided.gapx( N, alpha, x1, stride )\nx0\n","base.strided.gapx.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar alpha = 5.0;\nbase.strided.gapx.ndarray( x.length, alpha, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nalpha = 5.0;\nvar stride = 2;\nbase.strided.gapx.ndarray( N, alpha, x, stride, 1 )\n","base.strided.gapxsum":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsum( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gapxsum( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gapxsum( N, 5.0, x1, stride )\n","base.strided.gapxsum.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gapxsum.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.gapxsumkbn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gapxsumkbn( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gapxsumkbn( 3, 5.0, x1, 2 )\n","base.strided.gapxsumkbn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gapxsumkbn2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn2( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gapxsumkbn2( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gapxsumkbn2( N, 5.0, x1, stride )\n","base.strided.gapxsumkbn2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gapxsumkbn2.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.gapxsumors":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumors( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gapxsumors( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gapxsumors( N, 5.0, x1, stride )\n","base.strided.gapxsumors.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gapxsumors.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.gapxsumpw":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumpw( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gapxsumpw( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gapxsumpw( N, 5.0, x1, stride )\n","base.strided.gapxsumpw.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.gasum":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nvar s = base.strided.gasum( x.length, x, 1 )\ns = base.strided.gasum( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\ns = base.strided.gasum( 3, x1, 2 )\n","base.strided.gasum.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nvar s = base.strided.gasum.ndarray( x.length, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\ns = base.strided.gasum.ndarray( 3, x, -1, x.length-1 )\n","base.strided.gasumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.gasumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gasumpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gasumpw( N, x1, stride )\n","base.strided.gasumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.gasumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.gasumpw.ndarray( N, x, 2, 1 )\n","base.strided.gaxpy":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\nbase.strided.gaxpy( x.length, 5.0, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\nbase.strided.gaxpy( 3, 5.0, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gaxpy( 3, 5.0, x1, -2, y1, 1 )\ny0\n","base.strided.gaxpy.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\nbase.strided.gaxpy.ndarray( x.length, 5.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gaxpy.ndarray( 3, 5.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcopy":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gcopy( x.length, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gcopy( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcopy( 3, x1, -2, y1, 1 )\ny0\n","base.strided.gcopy.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusum":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusum( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusum( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.gcusum( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusum.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusum.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumkbn":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcusumkbn( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumkbn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumkbn2":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn2( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumkbn2( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.gcusumkbn2( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumkbn2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumkbn2.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumors":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumors( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumors( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.gcusumors( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumors.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumors.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumpw":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumpw( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumpw( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.gcusumpw( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumpw.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumpw.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gdot":"var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\nvar y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\nvar out = base.strided.gdot( x.length, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\nout = base.strided.gdot( 3, x, 2, y, -1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.gdot( 3, x1, -2, y1, 1 )\n","base.strided.gdot.ndarray":"var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\nvar y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\nvar out = base.strided.gdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\nout = base.strided.gdot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nout = base.strided.gdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.gfill":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfill( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gfill( N, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gfill( N, 5.0, x1, 2 )\nx0\n","base.strided.gfill.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfill.ndarray( x.length, 5.0, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gfill.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.gfillBy":"function fill() { return 5.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfillBy( x.length, x, 1, fill )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gfillBy( N, x, 2, fill )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gfillBy( N, x1, 2, fill )\nx0\n","base.strided.gfillBy.ndarray":"function fill() { return 5.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfillBy.ndarray( x.length, x, 1, 0, fill )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gfillBy.ndarray( N, x, 2, 1, fill )\n","base.strided.gnannsumkbn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nvar out = [ 0.0, 0 ];\nbase.strided.gnannsumkbn( x.length, x, 1, out, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nout = [ 0.0, 0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnannsumkbn( N, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = [ 0.0, 0 ];\nbase.strided.gnannsumkbn( N, x1, 2, out, 1 )\n","base.strided.gnannsumkbn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nvar out = [ 0.0, 0 ];\nbase.strided.gnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nout = [ 0.0, 0 ];\nbase.strided.gnannsumkbn.ndarray( N, x, 2, 1, out, 1, 0 )\n","base.strided.gnansum":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansum( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gnansum( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gnansum( N, x1, stride )\n","base.strided.gnansum.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansum.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnansum.ndarray( N, x, 2, 1 )\n","base.strided.gnansumkbn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gnansumkbn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gnansumkbn( N, x1, stride )\n","base.strided.gnansumkbn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnansumkbn.ndarray( N, x, 2, 1 )\n","base.strided.gnansumkbn2":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gnansumkbn2( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gnansumkbn2( N, x1, stride )\n","base.strided.gnansumkbn2.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnansumkbn2.ndarray( N, x, 2, 1 )\n","base.strided.gnansumors":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gnansumors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gnansumors( N, x1, stride )\n","base.strided.gnansumors.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnansumors.ndarray( N, x, 2, 1 )\n","base.strided.gnansumpw":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumpw( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gnansumpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gnansumpw( N, x1, stride )\n","base.strided.gnansumpw.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnansumpw.ndarray( N, x, 2, 1 )\n","base.strided.gnrm2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gnrm2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gnrm2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gnrm2( 3, x1, 2 )\n","base.strided.gnrm2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gnrm2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gnrm2.ndarray( 3, x, 2, 1 )\n","base.strided.grev":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.grev( x.length, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.grev( N, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.grev( N, x1, 2 )\nx0\n","base.strided.grev.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.grev.ndarray( x.length, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.grev.ndarray( N, x, 2, 1 )\n","base.strided.gscal":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar alpha = 5.0;\nbase.strided.gscal( x.length, alpha, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gscal( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gscal( 3, 5.0, x1, 2 )\nx0\n","base.strided.gscal.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gscal.ndarray( x.length, 5.0, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.gscal.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gsort2hp":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2hp( x.length, 1, x, 1, y, 1 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2hp( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsort2hp( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.gsort2hp.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.gsort2ins":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2ins( x.length, 1, x, 1, y, 1 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2ins( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsort2ins( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.gsort2ins.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2ins.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.gsort2sh":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2sh( x.length, 1, x, 1, y, 1 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2sh( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsort2sh( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.gsort2sh.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.gsorthp":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsorthp( x.length, 1, x, 1 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsorthp( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsorthp( N, 1, x1, 2 )\nx0\n","base.strided.gsorthp.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsorthp.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsorthp.ndarray( N, 1, x, 2, 1 )\n","base.strided.gsortins":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortins( x.length, 1, x, 1 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsortins( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsortins( N, 1, x1, 2 )\nx0\n","base.strided.gsortins.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortins.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsortins.ndarray( N, 1, x, 2, 1 )\n","base.strided.gsortsh":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortsh( x.length, 1, x, 1 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsortsh( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsortsh( N, 1, x1, 2 )\nx0\n","base.strided.gsortsh.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortsh.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsortsh.ndarray( N, 1, x, 2, 1 )\n","base.strided.gsum":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsum( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gsum( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gsum( N, x1, stride )\n","base.strided.gsum.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsum.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsum.ndarray( N, x, 2, 1 )\n","base.strided.gsumkbn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gsumkbn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gsumkbn( N, x1, stride )\n","base.strided.gsumkbn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsumkbn.ndarray( N, x, 2, 1 )\n","base.strided.gsumkbn2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gsumkbn2( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gsumkbn2( N, x1, stride )\n","base.strided.gsumkbn2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsumkbn2.ndarray( N, x, 2, 1 )\n","base.strided.gsumors":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gsumors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gsumors( N, x1, stride )\n","base.strided.gsumors.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsumors.ndarray( N, x, 2, 1 )\n","base.strided.gsumpw":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumpw( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gsumpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gsumpw( N, x1, stride )\n","base.strided.gsumpw.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumpw.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsumpw.ndarray( N, x, 2, 1 )\n","base.strided.gswap":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gswap( x.length, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gswap( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gswap( 3, x1, -2, y1, 1 )\ny0\n","base.strided.gswap.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.mapBy":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.mapBy( x.length, x, 1, y, 1, base.abs, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy( 2, x, 2, y, -1, base.abs, clbk )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.mapBy( 2, x1, -2, y1, 1, base.abs, clbk )\ny0\n","base.strided.mapBy.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.mapBy.ndarray( x.length, x, 1, 0, y, 1, 0, base.abs, clbk )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.abs, clbk )\n","base.strided.mapBy2":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 1.0, 1.0, 2.0, 2.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\nbase.strided.mapBy2( x.length, x, 1, y, 1, z, 1, base.add, clbk )\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy2( 2, x, 2, y, -1, z, -1, base.add, clbk )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 1.0, 1.0, 2.0, 2.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nbase.strided.mapBy2( 2, x1, -2, y1, 1, z1, 1, base.add, clbk )\nz0\n","base.strided.mapBy2.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 1.0, 1.0, 2.0, 2.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\nbase.strided.mapBy2.ndarray( 4, x, 1, 0, y, 1, 0, z, 1, 0, base.add, clbk )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 1.0, 1.0, 2.0, 2.0 ];\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy2.ndarray( 2, x, 2, 1, y, -1, 3, z, 1, 0, base.add, clbk )\n","base.strided.max":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.max( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.max( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.max( N, x1, stride )\n","base.strided.max.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.max.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.max.ndarray( N, x, 2, 1 )\n","base.strided.maxabs":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.maxabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.maxabs( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.maxabs( N, x1, stride )\n","base.strided.maxabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.maxabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.maxabs.ndarray( N, x, 2, 1 )\n","base.strided.maxBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.maxBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.maxBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.maxBy( N, x1, 2, accessor )\n","base.strided.maxBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.maxBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.maxBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.maxsorted":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.maxsorted( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.maxsorted( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.maxsorted( N, x1, stride )\n","base.strided.maxsorted.ndarray":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.maxsorted.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.maxsorted.ndarray( N, x, 2, 1 )\n","base.strided.maxViewBufferIndex":"var idx = base.strided.maxViewBufferIndex( 3, 2, 10 )\n","base.strided.mean":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.mean( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.mean( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.mean( N, x1, stride )\n","base.strided.mean.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.mean.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mean.ndarray( N, x, 2, 1 )\n","base.strided.meankbn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meankbn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meankbn( N, x1, stride )\n","base.strided.meankbn.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meankbn.ndarray( N, x, 2, 1 )\n","base.strided.meankbn2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meankbn2( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meankbn2( N, x1, stride )\n","base.strided.meankbn2.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meankbn2.ndarray( N, x, 2, 1 )\n","base.strided.meanors":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meanors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meanors( N, x1, stride )\n","base.strided.meanors.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meanors.ndarray( N, x, 2, 1 )\n","base.strided.meanpn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanpn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meanpn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meanpn( N, x1, stride )\n","base.strided.meanpn.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanpn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meanpn.ndarray( N, x, 2, 1 )\n","base.strided.meanpw":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanpw( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meanpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meanpw( N, x1, stride )\n","base.strided.meanpw.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanpw.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meanpw.ndarray( N, x, 2, 1 )\n","base.strided.meanwd":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanwd( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meanwd( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meanwd( N, x1, stride )\n","base.strided.meanwd.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanwd.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meanwd.ndarray( N, x, 2, 1 )\n","base.strided.mediansorted":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.mediansorted( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mediansorted( N, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.mediansorted( N, x1, 2 )\n","base.strided.mediansorted.ndarray":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.mediansorted.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mediansorted.ndarray( N, x, 2, 1 )\n","base.strided.metaDataProps":"var meta = { 'nargs': 7, 'nin': 1, 'nout': 1 };\nvar dt = [ 'float64', 'float64' ];\nvar obj = {};\nbase.strided.metaDataProps( meta, dt, obj, false );\nobj.nargs\nobj.nin\nobj.nout\nobj.types\n","base.strided.min":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.min( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.min( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.min( N, x1, stride )\n","base.strided.min.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.min.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.min.ndarray( N, x, 2, 1 )\n","base.strided.minabs":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.minabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.minabs( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.minabs( N, x1, stride )\n","base.strided.minabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.minabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.minabs.ndarray( N, x, 2, 1 )\n","base.strided.minBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.minBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.minBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.minBy( N, x1, 2, accessor )\n","base.strided.minBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.minBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.minBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.minsorted":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.minsorted( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.minsorted( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.minsorted( N, x1, stride )\n","base.strided.minsorted.ndarray":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.minsorted.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.minsorted.ndarray( N, x, 2, 1 )\n","base.strided.minViewBufferIndex":"var idx = base.strided.minViewBufferIndex( 3, -2, 10 )\n","base.strided.mskmax":"var x = [ 1.0, -2.0, 4.0, 2.0 ];\nvar mask = [ 0, 0, 1, 0 ];\nbase.strided.mskmax( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskmax( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.mskmax( N, x1, 2, mask1, 2 )\n","base.strided.mskmax.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0 ];\nvar mask = [ 0, 0, 0, 1 ];\nbase.strided.mskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.mskmin":"var x = [ 1.0, -2.0, -4.0, 2.0 ];\nvar mask = [ 0, 0, 1, 0 ];\nbase.strided.mskmin( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskmin( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.mskmin( N, x1, 2, mask1, 2 )\n","base.strided.mskmin.ndarray":"var x = [ 1.0, -2.0, 2.0, -4.0 ];\nvar mask = [ 0, 0, 0, 1 ];\nbase.strided.mskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.mskrange":"var x = [ 1.0, -2.0, 4.0, 2.0 ];\nvar mask = [ 0, 0, 1, 0 ];\nbase.strided.mskrange( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskrange( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.mskrange( N, x1, 2, mask1, 2 )\n","base.strided.mskrange.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0 ];\nvar mask = [ 0, 0, 0, 1 ];\nbase.strided.mskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.mskunary":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nbase.strided.mskunary( [ x, m, y ], shape, strides, base.abs );\ny\n","base.strided.mskunary.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nvar offsets = [ 0, 0, 0 ];\nbase.strided.mskunary.ndarray( [ x, m, y ], shape, strides, offsets, base.abs );\ny\n","base.strided.mskunaryDtypeSignatures":"var dt = strided.dataTypes();\nvar out = base.strided.mskunaryDtypeSignatures( dt, dt )\n","base.strided.mskunarySignatureCallbacks":"var dt = strided.dataTypes();\nvar sigs = base.strided.mskunaryDtypeSignatures( dt, dt );\nvar t = {\n 'default': base.identity,\n 'complex64': base.cidentityf,\n 'complex128': base.cidentity\n };\nvar out = base.strided.mskunarySignatureCallbacks( t, sigs )\n","base.strided.nanmax":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmax( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmax( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmax( N, x1, stride )\n","base.strided.nanmax.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmax.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmax.ndarray( N, x, 2, 1 )\n","base.strided.nanmaxabs":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmaxabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmaxabs( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmaxabs( N, x1, stride )\n","base.strided.nanmaxabs.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmaxabs.ndarray( N, x, 2, 1 )\n","base.strided.nanmaxBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanmaxBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmaxBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanmaxBy( N, x1, 2, accessor )\n","base.strided.nanmaxBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanmaxBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmaxBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.nanmean":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmean( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmean( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmean( N, x1, stride )\n","base.strided.nanmean.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmean.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmean.ndarray( N, x, 2, 1 )\n","base.strided.nanmeanors":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmeanors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmeanors( N, x1, stride )\n","base.strided.nanmeanors.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmeanors.ndarray( N, x, 2, 1 )\n","base.strided.nanmeanpn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanpn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmeanpn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmeanpn( N, x1, stride )\n","base.strided.nanmeanpn.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.nanmeanwd":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanwd( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmeanwd( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmeanwd( N, x1, stride )\n","base.strided.nanmeanwd.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmeanwd.ndarray( N, x, 2, 1 )\n","base.strided.nanmin":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmin( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmin( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmin( N, x1, stride )\n","base.strided.nanmin.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmin.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmin.ndarray( N, x, 2, 1 )\n","base.strided.nanminabs":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanminabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanminabs( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanminabs( N, x1, stride )\n","base.strided.nanminabs.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanminabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanminabs.ndarray( N, x, 2, 1 )\n","base.strided.nanminBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanminBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, NaN, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanminBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanminBy( N, x1, 2, accessor )\n","base.strided.nanminBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanminBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanminBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.nanmskmax":"var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\nvar mask = [ 0, 0, 1, 0, 0 ];\nbase.strided.nanmskmax( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskmax( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanmskmax( N, x1, 2, mask1, 2 )\n","base.strided.nanmskmax.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\nvar mask = [ 0, 0, 0, 1, 0 ];\nbase.strided.nanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.nanmskmin":"var x = [ 1.0, -2.0, -4.0, 2.0, NaN ];\nvar mask = [ 0, 0, 1, 0, 0 ];\nbase.strided.nanmskmin( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskmin( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanmskmin( N, x1, 2, mask1, 2 )\n","base.strided.nanmskmin.ndarray":"var x = [ 1.0, -2.0, 2.0, -4.0, NaN ];\nvar mask = [ 0, 0, 0, 1, 0 ];\nbase.strided.nanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.nanmskrange":"var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\nvar mask = [ 0, 0, 1, 0, 0 ];\nbase.strided.nanmskrange( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskrange( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanmskrange( N, x1, 2, mask1, 2 )\n","base.strided.nanmskrange.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\nvar mask = [ 0, 0, 0, 1, 0 ];\nbase.strided.nanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.nanrange":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanrange( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanrange( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanrange( N, x1, stride )\n","base.strided.nanrange.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanrange.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanrange.ndarray( N, x, 2, 1 )\n","base.strided.nanrangeBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanrangeBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0, 1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanrangeBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanrangeBy( N, x1, 2, accessor )\n","base.strided.nanrangeBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanrangeBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanrangeBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.nanstdev":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdev( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdev( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdev( N, 1, x1, 2 )\n","base.strided.nanstdev.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanstdevch":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevch( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevch( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdevch( N, 1, x1, 2 )\n","base.strided.nanstdevch.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanstdevpn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevpn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevpn( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdevpn( N, 1, x1, 2 )\n","base.strided.nanstdevpn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanstdevtk":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevtk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevtk( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdevtk( N, 1, x1, 2 )\n","base.strided.nanstdevtk.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanstdevwd":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevwd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevwd( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdevwd( N, 1, x1, 2 )\n","base.strided.nanstdevwd.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanstdevyc":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevyc( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevyc( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdevyc( N, 1, x1, 2 )\n","base.strided.nanstdevyc.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvariance":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariance( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvariance( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvariance( N, 1, x1, stride )\n","base.strided.nanvariance.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvariancech":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancech( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvariancech( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvariancech( N, 1, x1, stride )\n","base.strided.nanvariancech.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvariancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvariancepn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancepn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvariancepn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvariancepn( N, 1, x1, stride )\n","base.strided.nanvariancepn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvariancetk":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancetk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvariancetk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvariancetk( N, 1, x1, stride )\n","base.strided.nanvariancetk.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvariancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvariancewd":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancewd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvariancewd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvariancewd( N, 1, x1, stride )\n","base.strided.nanvariancewd.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvariancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvarianceyc":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvarianceyc( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvarianceyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvarianceyc( N, 1, x1, stride )\n","base.strided.nanvarianceyc.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvarianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.nullary":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1 ];\nvar fcn = constantFunction( 3.0 );\nbase.strided.nullary( [ x ], shape, strides, fcn );\nx\n","base.strided.nullary.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1 ];\nvar offsets = [ 0 ];\nvar fcn = constantFunction( 3.0 );\nbase.strided.nullary.ndarray( [ x ], shape, strides, offsets, fcn );\nx\n","base.strided.offsetView":"var x = new Float64Array( 10 );\nvar out = base.strided.offsetView( x, 0 )\nvar bool = ( out.buffer === x.buffer )\n","base.strided.quaternary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1 ];\nfunction f( x, y, z, w ) { return x + y + z + w; };\nbase.strided.quaternary( [ x, y, z, w, u ], shape, strides, f );\nu\n","base.strided.quaternary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1 ];\nvar offsets = [ 0, 0, 0, 0, 0 ];\nfunction f( x, y, z, w ) { return x + y + z + w; };\nbase.strided.quaternary.ndarray( [ x, y, z, w, u ], shape, strides, offsets, f );\nu\n","base.strided.quinary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1, 1 ];\nfunction f( x, y, z, w, u ) { return x + y + z + w + u; };\nbase.strided.quinary( [ x, y, z, w, u, v ], shape, strides, f );\nv\n","base.strided.quinary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1, 1 ];\nvar offsets = [ 0, 0, 0, 0, 0, 0 ];\nfunction f( x, y, z, w, u ) { return x + y + z + w + u; };\nbase.strided.quinary.ndarray( [ x, y, z, w, u, v ], shape, strides, offsets, f );\nv\n","base.strided.range":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.range( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.range( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.range( N, x1, stride )\n","base.strided.range.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.range.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.range.ndarray( N, x, 2, 1 )\n","base.strided.rangeBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.rangeBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.rangeBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.rangeBy( N, x1, 2, accessor )\n","base.strided.rangeBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.rangeBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.rangeBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.reinterpretComplex":"var x = new Complex128Array( 10 );\nvar out = base.strided.reinterpretComplex( x, 0 )\nvar bool = ( out.buffer === x.buffer )\nx = new Complex64Array( 10 );\nout = base.strided.reinterpretComplex( x, 0 )\nbool = ( out.buffer === x.buffer )\n","base.strided.reinterpretComplex64":"var x = new Complex64Array( 10 );\nvar out = base.strided.reinterpretComplex64( x, 0 )\nvar bool = ( out.buffer === x.buffer )\n","base.strided.reinterpretComplex128":"var x = new Complex128Array( 10 );\nvar out = base.strided.reinterpretComplex128( x, 0 )\nvar bool = ( out.buffer === x.buffer )\n","base.strided.sabs":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sabs( N, x1, -2, y1, 1 )\ny0\n","base.strided.sabs.ndarray":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sabs2":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs2( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs2( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sabs2( N, x1, -2, y1, 1 )\ny0\n","base.strided.sabs2.ndarray":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sapx":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sapx( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sapx( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapx( 3, 5.0, x1, 2 )\nx0\n","base.strided.sapx.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sapx.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.sapx.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsum( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsum( 3, 5.0, x1, 2 )\n","base.strided.sapxsum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsumkbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsumkbn( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsumkbn( 3, 5.0, x1, 2 )\n","base.strided.sapxsumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsumkbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn2( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsumkbn2( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsumkbn2( 3, 5.0, x1, 2 )\n","base.strided.sapxsumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumors( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sapxsumors( N, 5.0, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sapxsumors( N, 5.0, x1, stride )\n","base.strided.sapxsumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sapxsumors.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.sapxsumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumpw( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar stride = 2;\nbase.strided.sapxsumpw( 3, 5.0, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.sapxsumpw( 3, 5.0, x1, stride )\n","base.strided.sapxsumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sasum":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.sasum( x.length, x, 1 )\ns = base.strided.sasum( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\ns = base.strided.sasum( 3, x1, 2 )\n","base.strided.sasum.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.sasum.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\ns = base.strided.sasum.ndarray( 3, x, -1, x.length-1 )\n","base.strided.sasumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sasumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sasumpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sasumpw( 3, x1, 2 )\n","base.strided.sasumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sasumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sasumpw.ndarray( 3, x, 2, 1 )\n","base.strided.saxpy":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.saxpy( x.length, alpha, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nbase.strided.saxpy( 3, alpha, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.saxpy( 3, 5.0, x1, -2, y1, 1 )\ny0\n","base.strided.saxpy.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.saxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.saxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scbrt":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.scbrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.scbrt( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.scbrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.scbrt.ndarray":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.scbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.scbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sceil":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sceil( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sceil( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sceil( N, x1, -2, y1, 1 )\ny0\n","base.strided.sceil.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scopy":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.scopy( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.scopy( 3, x, -2, y, 1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scopy( 3, x1, -2, y1, 1 )\ny0\n","base.strided.scopy.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.scopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scumax":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumax( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumax( 3, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scumax( 3, x1, 2, y1, 1 )\ny0\n","base.strided.scumax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scumaxabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumaxabs( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scumaxabs( N, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scumaxabs( N, x1, 2, y1, 1 )\ny0\n","base.strided.scumaxabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scumin":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumin( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scumin( N, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scumin( N, x1, 2, y1, 1 )\ny0\n","base.strided.scumin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scuminabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scuminabs( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scuminabs( N, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scuminabs( N, x1, 2, y1, 1 )\ny0\n","base.strided.scuminabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusum( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusum( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusum( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumkbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scusumkbn( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumkbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn2( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn2( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scusumkbn2( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumors( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumors( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusumors( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumpw( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumpw( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusumpw( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sdeg2rad":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sdeg2rad( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sdeg2rad( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sdeg2rad( N, x1, -2, y1, 1 )\ny0\n","base.strided.sdeg2rad.ndarray":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sdeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sdot":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdot( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdot( 3, x, 2, y, -1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.sdot( 3, x1, -2, y1, 1 )\n","base.strided.sdot.ndarray":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nout = base.strided.sdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.sdsapxsum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsum( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sdsapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsapxsum( 3, 5.0, x1, 2 )\n","base.strided.sdsapxsum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sdsapxsumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsumpw( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sdsapxsumpw( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsapxsumpw( 3, 5.0, x1, 2 )\n","base.strided.sdsapxsumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sdsdot":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdsdot( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdsdot( 3, 0.0, x, 2, y, -1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.sdsdot( 3, 0.0, x1, -2, y1, 1 )\n","base.strided.sdsdot.ndarray":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdsdot.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdsdot.ndarray( 3, 0.0, x, 2, 0, y, 2, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nout = base.strided.sdsdot.ndarray( 3, 0.0, x, -2, x.length-1, y, 1, 3 )\n","base.strided.sdsmean":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsmean( N, x1, stride )\n","base.strided.sdsmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsmean.ndarray( N, x, 2, 1 )\n","base.strided.sdsmeanors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsmeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsmeanors( N, x1, stride )\n","base.strided.sdsmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsmeanors.ndarray( N, x, 2, 1 )\n","base.strided.sdsnanmean":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsnanmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsnanmean( N, x1, stride )\n","base.strided.sdsnanmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsnanmean.ndarray( N, x, 2, 1 )\n","base.strided.sdsnanmeanors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsnanmeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsnanmeanors( N, x1, stride )\n","base.strided.sdsnanmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsnanmeanors.ndarray( N, x, 2, 1 )\n","base.strided.sdsnansum":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar stride = 2;\nbase.strided.sdsnansum( 4, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.sdsnansum( 4, x1, stride )\n","base.strided.sdsnansum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansum.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.sdsnansum.ndarray( 4, x, 2, 1 )\n","base.strided.sdsnansumpw":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.sdsnansumpw( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsnansumpw( 4, x1, 2 )\n","base.strided.sdsnansumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.sdsnansumpw.ndarray( 4, x, 2, 1 )\n","base.strided.sdssum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar stride = 2;\nbase.strided.sdssum( 3, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.sdssum( 3, x1, stride )\n","base.strided.sdssum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssum.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdssum.ndarray( 3, x, 2, 1 )\n","base.strided.sdssumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar stride = 2;\nbase.strided.sdssumpw( 3, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.sdssumpw( 3, x1, stride )\n","base.strided.sdssumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdssumpw.ndarray( 3, x, 2, 1 )\n","base.strided.sfill":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sfill( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sfill( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sfill( 3, 5.0, x1, 2 )\nx0\n","base.strided.sfill.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sfill.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.sfill.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sfloor":"var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sfloor( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sfloor( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sfloor( N, x1, -2, y1, 1 )\ny0\n","base.strided.sfloor.ndarray":"var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sinv":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sinv( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sinv( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sinv( N, x1, -2, y1, 1 )\ny0\n","base.strided.sinv.ndarray":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.smap":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap( x.length, x, 1, y, 1, base.identityf )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap( 2, x, 2, y, -1, base.identityf )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smap( 2, x1, -2, y1, 1, base.identityf )\ny0\n","base.strided.smap.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identityf )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identityf )\n","base.strided.smap2":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2( x.length, x, 1, y, 1, z, 1, base.addf )\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2( 2, x, 2, y, -1, z, 1, base.addf )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nbase.strided.smap2( 2, x1, -2, y1, 1, z1, 1, base.addf )\nz0\n","base.strided.smap2.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.addf )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.addf )\n","base.strided.smax":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smax( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smax( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smax( 3, x1, 2 )\n","base.strided.smax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smax.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smax.ndarray( N, x, 2, 1 )\n","base.strided.smaxabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smaxabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smaxabs( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smaxabs( 3, x1, 2 )\n","base.strided.smaxabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smaxabs.ndarray( 3, x, 2, 1 )\n","base.strided.smaxabssorted":"var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.smaxabssorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smaxabssorted( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smaxabssorted( 3, x1, 2 )\n","base.strided.smaxabssorted.ndarray":"var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.smaxabssorted.ndarray( 3, x, 2, 1 )\n","base.strided.smaxsorted":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smaxsorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smaxsorted( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smaxsorted( 3, x1, 2 )\n","base.strided.smaxsorted.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.smaxsorted.ndarray( 3, x, 2, 1 )\n","base.strided.smean":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smean( N, x1, stride )\n","base.strided.smean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smean.ndarray( N, x, 2, 1 )\n","base.strided.smeankbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeankbn( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeankbn( N, x1, stride )\n","base.strided.smeankbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeankbn.ndarray( N, x, 2, 1 )\n","base.strided.smeankbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeankbn2( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeankbn2( N, x1, stride )\n","base.strided.smeankbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeankbn2.ndarray( N, x, 2, 1 )\n","base.strided.smeanli":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanli( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanli( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanli( N, x1, stride )\n","base.strided.smeanli.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanli.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanli.ndarray( N, x, 2, 1 )\n","base.strided.smeanlipw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanlipw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanlipw( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanlipw( N, x1, stride )\n","base.strided.smeanlipw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanlipw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanlipw.ndarray( N, x, 2, 1 )\n","base.strided.smeanors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanors( N, x1, stride )\n","base.strided.smeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanors.ndarray( N, x, 2, 1 )\n","base.strided.smeanpn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanpn( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanpn( N, x1, stride )\n","base.strided.smeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanpn.ndarray( N, x, 2, 1 )\n","base.strided.smeanpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanpw( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanpw( N, x1, stride )\n","base.strided.smeanpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanpw.ndarray( N, x, 2, 1 )\n","base.strided.smeanwd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanwd( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanwd( N, x1, stride )\n","base.strided.smeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanwd.ndarray( N, x, 2, 1 )\n","base.strided.smediansorted":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smediansorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smediansorted( N, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.smediansorted( N, x1, 2 )\n","base.strided.smediansorted.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smediansorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smediansorted.ndarray( N, x, 2, 1 )\n","base.strided.smidrange":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smidrange( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smidrange( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smidrange( 3, x1, 2 )\n","base.strided.smidrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smidrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smidrange.ndarray( 3, x, 2, 1 )\n","base.strided.smin":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smin( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smin( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smin( 3, x1, 2 )\n","base.strided.smin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smin.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smin.ndarray( 3, x, 2, 1 )\n","base.strided.sminabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sminabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sminabs( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sminabs( 3, x1, 2 )\n","base.strided.sminabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sminabs.ndarray( 3, x, 2, 1 )\n","base.strided.sminsorted":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.sminsorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sminsorted( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sminsorted( N, x1, stride )\n","base.strided.sminsorted.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.sminsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sminsorted.ndarray( N, x, 2, 1 )\n","base.strided.smskabs":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskabs( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskabs.ndarray":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskabs2":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskabs2( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskabs2.ndarray":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskcbrt":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskcbrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskcbrt.ndarray":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskceil":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskceil( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskceil.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskdeg2rad":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskdeg2rad.ndarray":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskfloor":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskfloor( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskfloor.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskinv":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskinv( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskinv.ndarray":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskmap":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap( x.length, x, 1, m, 1, y, 1, base.identity )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap( 2, x, 2, m, 2, y, -1, base.identity )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\ny0\n","base.strided.smskmap.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n","base.strided.smskmap2":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.addf )\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.addf )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.addf )\nz0\n","base.strided.smskmap2.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.addf )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.addf )\n","base.strided.smskmax":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmax( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskmax( 3, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.smskmax( 3, x1, 2, mask1, 2 )\n","base.strided.smskmax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.smskmin":"var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmin( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskmin( 3, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.smskmin( 3, x1, 2, mask1, 2 )\n","base.strided.smskmin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.smskramp":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskramp( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskramp.ndarray":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskrange":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskrange( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskrange( 3, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.smskrange( 3, x1, 2, mask1, 2 )\n","base.strided.smskrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.smskrsqrt":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskrsqrt.ndarray":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smsksqrt":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smsksqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smsksqrt.ndarray":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smsktrunc":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smsktrunc( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smsktrunc.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.snanmax":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmax( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanmax( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmax( 3, x1, 2 )\n","base.strided.snanmax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanmax.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanmax.ndarray( 3, x, 2, 1 )\n","base.strided.snanmaxabs":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmaxabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanmaxabs( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmaxabs( 3, x1, 2 )\n","base.strided.snanmaxabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanmaxabs.ndarray( 3, x, 2, 1 )\n","base.strided.snanmean":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanmean( N, x1, stride )\n","base.strided.snanmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmean.ndarray( N, x, 2, 1 )\n","base.strided.snanmeanors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanmeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanmeanors( N, x1, stride )\n","base.strided.snanmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmeanors.ndarray( N, x, 2, 1 )\n","base.strided.snanmeanpn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanmeanpn( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanmeanpn( N, x1, stride )\n","base.strided.snanmeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.snanmeanwd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanmeanwd( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanmeanwd( N, x1, stride )\n","base.strided.snanmeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmeanwd.ndarray( N, x, 2, 1 )\n","base.strided.snanmin":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmin( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanmin( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmin( 3, x1, 2 )\n","base.strided.snanmin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanmin.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanmin.ndarray( 3, x, 2, 1 )\n","base.strided.snanminabs":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanminabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanminabs( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanminabs( 3, x1, 2 )\n","base.strided.snanminabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanminabs.ndarray( 3, x, 2, 1 )\n","base.strided.snanmskmax":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.snanmskmax( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskmax( N, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanmskmax( N, x1, 2, mask1, 2 )\n","base.strided.snanmskmax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.snanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.snanmskmin":"var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.snanmskmin( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskmin( N, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanmskmin( N, x1, 2, mask1, 2 )\n","base.strided.snanmskmin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.snanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.snanmskrange":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.snanmskrange( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskrange( N, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanmskrange( N, x1, 2, mask1, 2 )\n","base.strided.snanmskrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.snanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.snanrange":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanrange( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanrange( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanrange( 3, x1, 2 )\n","base.strided.snanrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanrange.ndarray( 3, x, 2, 1 )\n","base.strided.snanstdev":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdev( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdev( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdev( N, 1, x1, stride )\n","base.strided.snanstdev.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevch":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevch( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevch( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevch( N, 1, x1, stride )\n","base.strided.snanstdevch.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevpn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevpn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevpn( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevpn( N, 1, x1, stride )\n","base.strided.snanstdevpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevtk":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevtk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevtk( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevtk( N, 1, x1, stride )\n","base.strided.snanstdevtk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevwd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevwd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevwd( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevwd( N, 1, x1, stride )\n","base.strided.snanstdevwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevyc":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevyc( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevyc( N, 1, x1, stride )\n","base.strided.snanstdevyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.snansum":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.snansum( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snansum( 4, x1, 2 )\n","base.strided.snansum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansum.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansum.ndarray( 4, x, 2, 1 )\n","base.strided.snansumkbn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar stride = 2;\nbase.strided.snansumkbn( 4, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.snansumkbn( 4, x1, stride )\n","base.strided.snansumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansumkbn.ndarray( 4, x, 2, 1 )\n","base.strided.snansumkbn2":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar stride = 2;\nbase.strided.snansumkbn2( 4, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.snansumkbn2( 4, x1, stride )\n","base.strided.snansumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansumkbn2.ndarray( 4, x, 2, 1 )\n","base.strided.snansumors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar stride = 2;\nbase.strided.snansumors( 4, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.snansumors( 4, x1, stride )\n","base.strided.snansumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansumors.ndarray( 4, x, 2, 1 )\n","base.strided.snansumpw":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.snansumpw( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snansumpw( 4, x1, 2 )\n","base.strided.snansumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansumpw.ndarray( 4, x, 2, 1 )\n","base.strided.snanvariance":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariance( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariance( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariance( N, 1, x1, 2 )\n","base.strided.snanvariance.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancech":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancech( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancech( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancech( N, 1, x1, 2 )\n","base.strided.snanvariancech.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancepn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancepn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancepn( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancepn( N, 1, x1, 2 )\n","base.strided.snanvariancepn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancetk":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancetk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancetk( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancetk( N, 1, x1, 2 )\n","base.strided.snanvariancetk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancewd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancewd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancewd( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancewd( N, 1, x1, 2 )\n","base.strided.snanvariancewd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvarianceyc":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvarianceyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvarianceyc( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvarianceyc( N, 1, x1, 2 )\n","base.strided.snanvarianceyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvarianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.snrm2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.snrm2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.snrm2( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snrm2( 3, x1, 2 )\n","base.strided.snrm2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.snrm2.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.snrm2.ndarray( 3, x, 2, 1 )\n","base.strided.sramp":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sramp( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sramp( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sramp( N, x1, -2, y1, 1 )\ny0\n","base.strided.sramp.ndarray":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.srange":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.srange( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.srange( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.srange( 3, x1, 2 )\n","base.strided.srange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.srange.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.srange.ndarray( 3, x, 2, 1 )\n","base.strided.srev":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.srev( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.srev( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.srev( 3, x1, 2 )\nx0\n","base.strided.srev.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.srev.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.srev.ndarray( 3, x, 2, 1 )\n","base.strided.srsqrt":"var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.srsqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.srsqrt( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.srsqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.srsqrt.ndarray":"var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.srsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.srsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sscal":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sscal( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sscal( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sscal( 3, 5.0, x1, 2 )\nx0\n","base.strided.sscal.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sscal.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.sscal.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.ssort2hp":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2hp( x.length, 1, x, 1, y, 1 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2hp( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssort2hp( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.ssort2hp.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2hp.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.ssort2ins":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2ins( x.length, 1, x, 1, y, 1 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2ins( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssort2ins( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.ssort2ins.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.ssort2sh":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2sh( x.length, 1, x, 1, y, 1 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2sh( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssort2sh( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.ssort2sh.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2sh.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.ssorthp":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssorthp( x.length, 1, x, 1 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssorthp( 2, -1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssorthp( 2, 1, x1, 2 )\nx0\n","base.strided.ssorthp.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssorthp.ndarray( x.length, 1, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssorthp.ndarray( 2, 1, x, 2, 1 )\n","base.strided.ssortins":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortins( x.length, 1, x, 1 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortins( 2, -1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssortins( 2, 1, x1, 2 )\nx0\n","base.strided.ssortins.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortins.ndarray( x.length, 1, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortins.ndarray( 2, 1, x, 2, 1 )\n","base.strided.ssortsh":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortsh( x.length, 1, x, 1 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortsh( 2, -1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssortsh( 2, 1, x1, 2 )\nx0\n","base.strided.ssortsh.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortsh.ndarray( x.length, 1, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortsh.ndarray( 2, 1, x, 2, 1 )\n","base.strided.ssqrt":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ssqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ssqrt( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.ssqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.ssqrt.ndarray":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ssqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ssqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sstdev":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdev( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdev( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdev( N, 1, x1, stride )\n","base.strided.sstdev.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.sstdevch":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevch( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdevch( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdevch( N, 1, x1, stride )\n","base.strided.sstdevch.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.sstdevpn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevpn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdevpn( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdevpn( N, 1, x1, stride )\n","base.strided.sstdevpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.sstdevtk":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevtk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdevtk( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdevtk( N, 1, x1, stride )\n","base.strided.sstdevtk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.sstdevwd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevwd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdevwd( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdevwd( N, 1, x1, stride )\n","base.strided.sstdevwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.sstdevyc":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdevyc( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdevyc( N, 1, x1, stride )\n","base.strided.sstdevyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.ssum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssum( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssum( 3, x1, 2 )\n","base.strided.ssum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssum.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssum.ndarray( 3, x, 2, 1 )\n","base.strided.ssumkbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumkbn( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumkbn( 3, x1, 2 )\n","base.strided.ssumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumkbn.ndarray( 3, x, 2, 1 )\n","base.strided.ssumkbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumkbn2( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumkbn2( 3, x1, 2 )\n","base.strided.ssumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn2.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumkbn2.ndarray( 3, x, 2, 1 )\n","base.strided.ssumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumors( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumors( 3, x1, 2 )\n","base.strided.ssumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumors.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumors.ndarray( 3, x, 2, 1 )\n","base.strided.ssumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumpw( 3, x1, 2 )\n","base.strided.ssumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumpw.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumpw.ndarray( 3, x, 2, 1 )\n","base.strided.sswap":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.sswap( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.sswap( 3, x, -2, y, 1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.sswap( 3, x1, -2, y1, 1 )\ny0\n","base.strided.sswap.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.sswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.sswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.stdev":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdev( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdev( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdev( N, 1, x1, stride )\n","base.strided.stdev.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.stdevch":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevch( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdevch( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdevch( N, 1, x1, stride )\n","base.strided.stdevch.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.stdevpn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevpn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdevpn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdevpn( N, 1, x1, stride )\n","base.strided.stdevpn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.stdevtk":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevtk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdevtk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdevtk( N, 1, x1, stride )\n","base.strided.stdevtk.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.stdevwd":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevwd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdevwd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdevwd( N, 1, x1, stride )\n","base.strided.stdevwd.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.stdevyc":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevyc( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdevyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdevyc( N, 1, x1, stride )\n","base.strided.stdevyc.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.strunc":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.strunc( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.strunc( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.strunc( N, x1, -2, y1, 1 )\ny0\n","base.strided.strunc.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.strunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.strunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.svariance":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariance( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svariance( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svariance( N, 1, x1, stride )\n","base.strided.svariance.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.svariancech":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancech( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svariancech( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svariancech( N, 1, x1, stride )\n","base.strided.svariancech.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svariancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.svariancepn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancepn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svariancepn( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svariancepn( N, 1, x1, stride )\n","base.strided.svariancepn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.svariancetk":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancetk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svariancetk( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svariancetk( N, 1, x1, stride )\n","base.strided.svariancetk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svariancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.svariancewd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancewd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svariancewd( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svariancewd( N, 1, x1, stride )\n","base.strided.svariancewd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svariancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.svarianceyc":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svarianceyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svarianceyc( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svarianceyc( N, 1, x1, stride )\n","base.strided.svarianceyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svarianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.ternary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1 ];\nfunction f( x, y, z ) { return x + y + z; };\nbase.strided.ternary( [ x, y, z, w ], shape, strides, f );\nw\n","base.strided.ternary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1 ];\nvar offsets = [ 0, 0, 0, 0 ];\nfunction f( x, y, z ) { return x + y + z; };\nbase.strided.ternary.ndarray( [ x, y, z, w ], shape, strides, offsets, f );\nw\n","base.strided.unary":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1 ];\nbase.strided.unary( [ x, y ], shape, strides, base.abs );\ny\n","base.strided.unary.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1 ];\nvar offsets = [ 0, 0 ];\nbase.strided.unary.ndarray( [ x, y ], shape, strides, offsets, base.abs );\ny\n","base.strided.unaryBy":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nvar sh = [ x.length ];\nvar st = [ 1, 1 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\ny\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nsh = [ 2 ];\nst = [ 2, -1 ];\nbase.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nsh = [ 2 ];\nst = [ -2, 1 ];\nbase.strided.unaryBy( [ x1, y1 ], sh, st, base.abs, clbk );\ny1\ny0\n","base.strided.unaryBy.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nvar sh = [ x.length ];\nvar st = [ 1, 1 ];\nvar o = [ 0, 0 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nsh = [ 2 ];\nst = [ 2, -1 ];\no = [ 1, y.length-1 ];\nbase.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\ny\n","base.strided.unaryDtypeSignatures":"var dt = strided.dataTypes();\nvar out = base.strided.unaryDtypeSignatures( dt, dt )\n","base.strided.unarySignatureCallbacks":"var dt = strided.dataTypes();\nvar sigs = base.strided.unaryDtypeSignatures( dt, dt );\nvar t = {\n 'default': base.identity,\n 'complex64': base.cidentityf,\n 'complex128': base.cidentity\n };\nvar out = base.strided.unarySignatureCallbacks( t, sigs )\n","base.strided.variance":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variance( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.variance( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.variance( N, 1, x1, stride )\n","base.strided.variance.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variance.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.variance.ndarray( N, 1, x, 2, 1 )\n","base.strided.variancech":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancech( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.variancech( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.variancech( N, 1, x1, stride )\n","base.strided.variancech.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.variancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.variancepn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancepn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.variancepn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.variancepn( N, 1, x1, stride )\n","base.strided.variancepn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.variancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.variancetk":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancetk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.variancetk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.variancetk( N, 1, x1, stride )\n","base.strided.variancetk.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.variancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.variancewd":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancewd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.variancewd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.variancewd( N, 1, x1, stride )\n","base.strided.variancewd.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.variancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.varianceyc":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.varianceyc( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.varianceyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.varianceyc( N, 1, x1, stride )\n","base.strided.varianceyc.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.varianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.varianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.zmap":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex128Array( xbuf );\nvar y = new Complex128Array( x.length );\nbase.strided.zmap( x.length, x, 1, y, 1, base.cidentity );\nvar v = y.get( 0 )\nvar re = real( v )\nvar im = imag( v )\ny = new Complex128Array( x.length );\nbase.strided.zmap( 2, x, 2, y, -1, base.cidentity );\nv = y.get( 0 )\nre = real( v )\nim = imag( v )\nvar x0 = new Complex128Array( xbuf );\nvar y0 = new Complex128Array( x0.length );\nvar x1 = new Complex128Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex128Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.zmap( 2, x1, -2, y1, 1, base.cidentity );\nv = y1.get( 0 )\nre = real( v )\nim = imag( v )\n","base.strided.zmap.ndarray":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex128Array( xbuf );\nvar y = new Complex128Array( x.length );\nbase.strided.zmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentity );\nvar v = y.get( 0 )\nvar re = real( v )\nvar im = imag( v )\nx = new Complex128Array( xbuf );\ny = new Complex128Array( x.length );\nbase.strided.zmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentity );\nv = y.get( y.length-1 )\nre = real( v )\nim = imag( v )\n","base.str2multislice":"var s = new base.str2multislice( 'MultiSlice(null,null,null)' );\ns.data\ns = new base.str2multislice( 'MultiSlice(10,Slice(0,10,1),null)' );\ns.data\n","base.str2slice":"var s = new base.str2slice( 'Slice(1,10,1)' );\ns.start\ns.stop\ns.step\ns = new base.str2slice( 'Slice(2,5,2)' );\ns.start\ns.stop\ns.step\n","base.sub":"var v = base.sub( -1.0, 5.0 )\nv = base.sub( 2.0, 5.0 )\nv = base.sub( 0.0, 5.0 )\nv = base.sub( -0.0, 0.0 )\nv = base.sub( NaN, NaN )\n","base.subf":"var v = base.subf( -1.0, 5.0 )\nv = base.subf( 2.0, 5.0 )\nv = base.subf( 0.0, 5.0 )\nv = base.subf( -0.0, 0.0 )\nv = base.subf( NaN, NaN )\n","base.sumSeries":"function* geometricSeriesGenerator( x ) {\n var exponent = 0;\n while ( true ) {\n     yield Math.pow( x, exponent );\n     exponent += 1;\n }\n };\nvar gen = geometricSeriesGenerator( 0.9 );\nvar out = base.sumSeries( gen )\nfunction geometricSeriesClosure( x ) {\n var exponent = -1;\n return function() {\n     exponent += 1;\n     return Math.pow( x, exponent );\n };\n };\ngen = geometricSeriesClosure( 0.9 );\nout = base.sumSeries( gen )\nout = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'initialValue': 1 } )\nout = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'maxTerms': 10 } )\nout = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'tolerance': 1e-3 } )\n","base.tan":"var y = base.tan( 0.0 )\ny = base.tan( -PI/4.0 )\ny = base.tan( PI/4.0 )\ny = base.tan( NaN )\n","base.tand":"var y = base.tand( 0.0 )\ny = base.tand( 90.0 )\ny = base.tand( 60.0 )\ny = base.tand( NaN )\n","base.tanh":"var y = base.tanh( 0.0 )\nvar y = base.tanh( -0.0 )\ny = base.tanh( 2.0 )\ny = base.tanh( -2.0 )\ny = base.tanh( NaN )\n","base.toBinaryString":"var str = base.toBinaryString( 4.0 )\nstr = base.toBinaryString( PI )\nstr = base.toBinaryString( -1.0e308 )\nstr = base.toBinaryString( -3.14e-320 )\nstr = base.toBinaryString( 5.0e-324 )\nstr = base.toBinaryString( 0.0 )\nstr = base.toBinaryString( -0.0 )\nstr = base.toBinaryString( NaN )\nstr = base.toBinaryString( PINF )\nstr = base.toBinaryString( NINF )\n","base.toBinaryStringf":"var str = base.toBinaryStringf( base.float64ToFloat32( 4.0 ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( PI ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( -1.0e38 ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( -3.14e-39 ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( 1.4e-45 ) )\nstr = base.toBinaryStringf( 0.0 )\nstr = base.toBinaryStringf( -0.0 )\nstr = base.toBinaryStringf( NaN )\nstr = base.toBinaryStringf( FLOAT32_PINF )\nstr = base.toBinaryStringf( FLOAT32_NINF )\n","base.toBinaryStringUint8":"var a = new Uint8Array( [ 1, 4, 9 ] );\nvar str = base.toBinaryStringUint8( a[ 0 ] )\nstr = base.toBinaryStringUint8( a[ 1 ] )\nstr = base.toBinaryStringUint8( a[ 2 ] )\n","base.toBinaryStringUint16":"var a = new Uint16Array( [ 1, 4, 9 ] );\nvar str = base.toBinaryStringUint16( a[ 0 ] )\nstr = base.toBinaryStringUint16( a[ 1 ] )\nstr = base.toBinaryStringUint16( a[ 2 ] )\n","base.toBinaryStringUint32":"var a = new Uint32Array( [ 1, 4, 9 ] );\nvar str = base.toBinaryStringUint32( a[ 0 ] )\nstr = base.toBinaryStringUint32( a[ 1 ] )\nstr = base.toBinaryStringUint32( a[ 2 ] )\n","base.toWordf":"var f32 = base.float64ToFloat32( 1.337 )\nvar w = base.toWordf( f32 )\n","base.toWords":"var w = base.toWords( 3.14e201 )\n","base.toWords.assign":"var out = new Uint32Array( 2 );\nvar w = base.toWords.assign( 3.14e201, out, 1, 0 )\nvar bool = ( w === out )\n","base.transpose":"var x = array( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\nvar sh = x.shape\nvar y = base.transpose( x )\nsh = y.shape\nvar bool = ( x.data === y.data )\nbool = ( x.get( 0, 1 ) === y.get( 1, 0 ) )\n","base.tribonacci":"var y = base.tribonacci( 0 )\ny = base.tribonacci( 1 )\ny = base.tribonacci( 2 )\ny = base.tribonacci( 3 )\ny = base.tribonacci( 4 )\ny = base.tribonacci( 64 )\ny = base.tribonacci( NaN )\n","base.trigamma":"var y = base.trigamma( -2.5 )\ny = base.trigamma( 1.0 )\ny = base.trigamma( 10.0 )\ny = base.trigamma( NaN )\ny = base.trigamma( -1.0 )\n","base.trim":"var out = base.trim( ' \\t\\t\\n  Beep \\r\\n\\t  ' )\n","base.trunc":"var y = base.trunc( 3.14 )\ny = base.trunc( -4.2 )\ny = base.trunc( -4.6 )\ny = base.trunc( 9.5 )\ny = base.trunc( -0.0 )\n","base.trunc2":"var y = base.trunc2( 3.14 )\ny = base.trunc2( -4.2 )\ny = base.trunc2( -4.6 )\ny = base.trunc2( 9.5 )\ny = base.trunc2( 13.0 )\ny = base.trunc2( -13.0 )\ny = base.trunc2( -0.0 )\n","base.trunc10":"var y = base.trunc10( 3.14 )\ny = base.trunc10( -4.2 )\ny = base.trunc10( -4.6 )\ny = base.trunc10( 9.5 )\ny = base.trunc10( 13.0 )\ny = base.trunc10( -13.0 )\ny = base.trunc10( -0.0 )\n","base.truncateMiddle":"var str = 'beep boop';\nvar out = base.truncateMiddle( str, 5, '...' )\nout = base.truncateMiddle( str, 5, '|' )\n","base.truncb":"var y = base.truncb( 3.14159, -4, 10 )\ny = base.truncb( 3.14159, 0, 2 )\ny = base.truncb( 5.0, 1, 2 )\n","base.truncf":"var y = base.truncf( 3.14 )\ny = base.truncf( -4.2 )\ny = base.truncf( -4.6 )\ny = base.truncf( 9.5 )\ny = base.truncf( -0.0 )\n","base.truncn":"var y = base.truncn( 3.14159, -4 )\ny = base.truncn( 3.14159, 0 )\ny = base.truncn( 12368.0, 3 )\n","base.truncsd":"var y = base.truncsd( 3.14159, 5, 10 )\ny = base.truncsd( 3.14159, 1, 10 )\ny = base.truncsd( 12368.0, 2, 10 )\ny = base.truncsd( 0.0313, 2, 2 )\n","base.uint32ToInt32":"var y = base.uint32ToInt32( base.float64ToUint32( 4294967295 ) )\ny = base.uint32ToInt32( base.float64ToUint32( 3 ) )\n","base.umul":"var v = base.umul( 10>>>0, 4>>>0 )\n","base.umuldw":"var v = base.umuldw( 1, 10 )\n","base.umuldw.assign":"var out = [ 0, 0 ];\nvar v = base.umuldw.assign( 1, 10, out, 1, 0 )\nvar bool = ( v === out )\n","base.uncapitalize":"var out = base.uncapitalize( 'Beep' )\nout = base.uncapitalize( 'bOOp' )\n","base.uppercase":"var out = base.uppercase( 'bEEp' )\n","base.vercos":"var y = base.vercos( 3.14 )\ny = base.vercos( -4.2 )\ny = base.vercos( -4.6 )\ny = base.vercos( 9.5 )\ny = base.vercos( -0.0 )\n","base.versin":"var y = base.versin( 3.14 )\ny = base.versin( -4.2 )\ny = base.versin( -4.6 )\ny = base.versin( 9.5 )\ny = base.versin( -0.0 )\n","base.wrap":"var y = base.wrap( 3.14, 0.0, 5.0 )\ny = base.wrap( -3.14, 0.0, 5.0 )\ny = base.wrap( 3.14, 0.0, 3.0 )\ny = base.wrap( -0.0, 0.0, 5.0 )\ny = base.wrap( 0.0, -3.14, -0.0 )\ny = base.wrap( NaN, 0.0, 5.0 )\n","base.xlog1py":"var out = base.xlog1py( 3.0, 2.0 )\nout = base.xlog1py( 1.5, 5.9 )\nout = base.xlog1py( 0.9, 1.0 )\nout = base.xlog1py( 1.0, 0.0 )\nout = base.xlog1py( 0.0, -2.0 )\nout = base.xlog1py( 1.5, NaN )\nout = base.xlog1py( 0.0, NaN )\nout = base.xlog1py( NaN, 2.3 )\n","base.xlogy":"var out = base.xlogy( 3.0, 2.0 )\nout = base.xlogy( 1.5, 5.9 )\nout = base.xlogy( 0.9, 1.0 )\nout = base.xlogy( 0.0, -2.0 )\nout = base.xlogy( 1.5, NaN )\nout = base.xlogy( 0.0, NaN )\nout = base.xlogy( NaN, 2.3 )\n","base.zeta":"var y = base.zeta( 1.1 )\ny = base.zeta( -4.0 )\ny = base.zeta( 70.0 )\ny = base.zeta( 0.5 )\ny = base.zeta( NaN )\ny = base.zeta( 1.0 )\n","BERNDT_CPS_WAGES_1985":"var data = BERNDT_CPS_WAGES_1985()\n","bifurcate":"var collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar f = [ true, true, false, true ];\nvar out = bifurcate( collection, f )\nf = [ 1, 1, 0, 1 ];\nout = bifurcate( collection, f )\nf = [ true, true, false, true ];\nvar opts = { 'returns': 'indices' };\nout = bifurcate( collection, opts, f )\nopts = { 'returns': '*' };\nout = bifurcate( collection, opts, f )\n","bifurcateBy":"function predicate( v ) { return v[ 0 ] === 'b'; };\nvar collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar out = bifurcateBy( collection, predicate )\nvar opts = { 'returns': 'indices' };\nout = bifurcateBy( collection, opts, predicate )\nopts = { 'returns': '*' };\nout = bifurcateBy( collection, opts, predicate )\n","bifurcateByAsync":"function predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nbifurcateByAsync( arr, predicate, done )\nvar opts = { 'returns': 'indices' };\nbifurcateByAsync( arr, opts, predicate, done )\nopts = { 'returns': '*' };\nbifurcateByAsync( arr, opts, predicate, done )\nfunction predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nbifurcateByAsync( arr, opts, predicate, done )\nfunction predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nbifurcateByAsync( arr, opts, predicate, done )\n","bifurcateByAsync.factory":"function predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) );\n }\n };\nvar opts = { 'series': true };\nvar f = bifurcateByAsync.factory( opts, predicate );\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","bifurcateIn":"function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\nFoo.prototype = Object.create( null );\nFoo.prototype.c = 'foo';\nFoo.prototype.d = 'bar';\nvar obj = new Foo();\nfunction predicate( v ) { return v[ 0 ] === 'b'; };\nvar out = bifurcateIn( obj, predicate )\nvar opts = { 'returns': 'keys' };\nout = bifurcateIn( obj, opts, predicate )\nopts = { 'returns': '*' };\nout = bifurcateIn( obj, opts, predicate )\n","bifurcateOwn":"function predicate( v ) { return v[ 0 ] === 'b'; };\nvar obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\nvar out = bifurcateOwn( obj, predicate )\nvar opts = { 'returns': 'keys' };\nout = bifurcateOwn( obj, opts, predicate )\nopts = { 'returns': '*' };\nout = bifurcateOwn( obj, opts, predicate )\n","BigInt":"var v = ( BigInt ) ? BigInt( '1' ) : null\n","binomialTest":"var out = binomialTest( 682, 925 )\nout = binomialTest( [ 682, 925 - 682 ] )\nout = binomialTest( 21, 40, {\n 'p': 0.4,\n 'alternative': 'greater'\n })\n","Boolean":"var b = new Boolean( null )\nb = Boolean( null )\nb = Boolean( [] )\n","Boolean.prototype.toString":"var b = new Boolean( true )\nb.toString()\n","Boolean.prototype.valueOf":"var b = new Boolean( true )\nb.valueOf()\n","BooleanArray":"var arr = new BooleanArray()\nvar arr = new BooleanArray( 10 )\nvar len = arr.length\nvar arr1 = new BooleanArray( [ true, false, false, true ] )\nvar arr2 = new BooleanArray( arr1 )\nvar len = arr2.length\nvar buf = new Uint8Array( [ 1, 0, 0, 1 ] )\nvar arr = new BooleanArray( buf )\nvar len = arr.length\nvar arr1 = new BooleanArray( [ true, false, false, true ] )\nvar len = arr1.length\nvar arr2 = new BooleanArray( [ {}, null, '', 4 ] );\nlen = arr2.length\nvar buf = new ArrayBuffer( 240 );\nvar arr1 = new BooleanArray( buf )\nvar len = arr1.length\nvar arr2 = new BooleanArray( buf, 8 )\nlen = arr2.length\nvar arr3 = new BooleanArray( buf, 8, 20 )\nlen = arr3.length\n","BooleanArray.from":"function map( v ) { return !v };\nvar src = [ true, false ];\nvar arr = BooleanArray.from( src, map )\nvar len = arr.length\nvar v = arr.get( 0 )\nv = arr.get( 1 )\n","BooleanArray.of":"var arr = BooleanArray.of( true, false, false, true )\nvar len = arr.length\n","BooleanArray.BYTES_PER_ELEMENT":"var nbytes = BooleanArray.BYTES_PER_ELEMENT\n","BooleanArray.name":"var str = BooleanArray.name\n","BooleanArray.prototype.buffer":"var arr = new BooleanArray( 2 )\nvar buf = arr.buffer\n","BooleanArray.prototype.byteLength":"var arr = new BooleanArray( 10 )\nvar nbytes = arr.byteLength\n","BooleanArray.prototype.byteOffset":"var arr = new BooleanArray( 10 )\nvar offset = arr.byteOffset\nvar buf = new ArrayBuffer( 240 );\narr = new BooleanArray( buf, 64 )\noffset = arr.byteOffset\n","BooleanArray.prototype.BYTES_PER_ELEMENT":"var arr = new BooleanArray( 10 )\narr.BYTES_PER_ELEMENT\n","BooleanArray.prototype.length":"var arr = new BooleanArray( 10 )\nvar len = arr.length\n","BooleanArray.prototype.at":"var arr = new BooleanArray( [ true, false, false, true ] )\nvar v = arr.at( 1 )\nv = arr.at( -1 )\n","BooleanArray.prototype.copyWithin":"var arr = new BooleanArray( [ true, false, false, true ] )\narr.copyWithin( 0, 2 )\nvar v = arr.get( 0 )\nv = arr.get( 1 )\n","BooleanArray.prototype.entries":"var arr = new BooleanArray( [ true, false, true ] )\nvar it = arr.entries();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","BooleanArray.prototype.every":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, true, true ] )\nvar bool = arr.every( predicate )\n","BooleanArray.prototype.fill":"var arr = new BooleanArray( 3 )\narr.fill( true );\nvar v = arr.get( 0 )\nv = arr.get( 1 )\nv = arr.get( 2 )\n","BooleanArray.prototype.filter":"function predicate( v ) { return ( v === true ); };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.filter( predicate )\nvar len = out.length\nvar v = out.get( 0 )\nv = out.get( 1 )\n","BooleanArray.prototype.find":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar v = arr.find( predicate )\n","BooleanArray.prototype.findIndex":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar idx = arr.findIndex( predicate )\n","BooleanArray.prototype.findLast":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar v = arr.findLast( predicate )\n","BooleanArray.prototype.findLastIndex":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar idx = arr.findLastIndex( predicate )\n","BooleanArray.prototype.forEach":"var str = '%';\nfunction clbk( v ) { str += v.toString() + '%'; };\nvar arr = new BooleanArray( [ true, false, false, true ] )\narr.forEach( clbk );\nstr\n","BooleanArray.prototype.get":"var arr = new BooleanArray( 10 )\narr.set( true, 0 );\nvar v = arr.get( 0 )\n","BooleanArray.prototype.includes":"var arr = new BooleanArray( [ true, false, true, true, true ] )\nvar bool = arr.includes( true )\nbool = arr.includes( false, 3 )\n","BooleanArray.prototype.indexOf":"var arr = new BooleanArray( [ true, false, true, true, true ] )\nvar idx = arr.indexOf( true )\nidx = arr.indexOf( false, 3 )\n","BooleanArray.prototype.join":"var arr = new BooleanArray( [ true, false, true ] )\nvar str = arr.join()\nstr = arr.join( '|' )\n","BooleanArray.prototype.keys":"var arr = new BooleanArray( [ true, false ] )\nvar it = arr.keys();\nvar v = it.next().value\nv = it.next().value\nv = it.next().done\n","BooleanArray.prototype.lastIndexOf":"var arr = new BooleanArray( [ true, true, true, false, true ] )\nvar idx = arr.lastIndexOf( false )\nidx = arr.lastIndexOf( false, 2 )\n","BooleanArray.prototype.map":"function invert( v ) { return !v; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.map( invert )\nvar v = out.get( 0 )\nv = out.get( 1 )\nv = out.get( 2 )\n","BooleanArray.prototype.reduce":"function reducer( acc, v ) { return ( acc && v ); };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.reduce( reducer )\n","BooleanArray.prototype.reduceRight":"function reducer( acc, v ) { return ( acc && v ); };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.reduceRight( reducer )\n","BooleanArray.prototype.reverse":"var arr = new BooleanArray( [ true, false, false ] )\narr.reverse();\nvar v = arr.get( 0 )\nv = arr.get( 1 )\nv = arr.get( 2 )\n","BooleanArray.prototype.set":"var arr = new BooleanArray( 2 )\narr.set( false );\nvar v = arr.get( 0 )\narr.set( true, 1 );\nv = arr.get( 1 )\n","BooleanArray.prototype.slice":"var arr = new BooleanArray( [ true, false, true, false, true ] )\nvar out = arr.slice( 1 )\nvar len = out.length\nvar v = out.get( 0 )\nv = out.get( 1 )\n","BooleanArray.prototype.some":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ false, true, false ] )\nvar bool = arr.some( predicate )\n","BooleanArray.prototype.sort":"function compare( a, b ) { return a === true ? -1 : 1; };\nvar arr = new BooleanArray( [ true, false, true ] )\narr.sort( compare );\nvar v = arr.get( 0 )\nv = arr.get( 1 )\nv = arr.get( 2 )\n","BooleanArray.prototype.subarray":"var arr = new BooleanArray( [ true, false, true, false, true ] )\nvar out = arr.subarray( 1, 3 )\nvar len = out.length\nvar v = out.get( 0 )\nv = out.get( 1 )\n","BooleanArray.prototype.toLocaleString":"var arr = new BooleanArray( [ true, false, true ] )\nvar str = arr.toLocaleString()\n","BooleanArray.prototype.toReversed":"var arr = new BooleanArray( [ true, false, false ] )\nvar out = arr.toReversed()\nvar v = out.get( 0 )\nv = out.get( 1 )\nv = out.get( 2 )\n","BooleanArray.prototype.toSorted":"function compare( a, b ) { return a === true ? -1 : 1; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.toSorted( compare );\nvar v = out.get( 0 )\nv = out.get( 1 )\nv = out.get( 2 )\n","BooleanArray.prototype.toString":"var arr = new BooleanArray( [ true, false, true ] )\nvar str = arr.toString()\n","BooleanArray.prototype.values":"var arr = new BooleanArray( [ true, false ] )\nvar it = arr.values();\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","BooleanArray.prototype.with":"var arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.with( 0, false )\nvar v = out.get( 0 )\n","broadcastArray":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = broadcastArray( x, [ 3, 2, 2 ] )\nsh = y.shape\nvar v = y.get( 0, 0, 0 )\nv = y.get( 0, 0, 1 )\nv = y.get( 0, 1, 0 )\nv = y.get( 0, 1, 1 )\nv = y.get( 1, 0, 0 )\nv = y.get( 1, 1, 0 )\nv = y.get( 2, 0, 0 )\nv = y.get( 2, 1, 1 )\n","broadcastArrays":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = ndzeros( [ 3, 2, 2 ] )\nvar out = broadcastArrays( [ x, y ] )\nvar bx = out[ 0 ]\nsh = bx.shape\nvar v = bx.get( 0, 0, 0 )\nv = bx.get( 0, 0, 1 )\nv = bx.get( 0, 1, 0 )\nv = bx.get( 0, 1, 1 )\nv = bx.get( 1, 0, 0 )\nv = bx.get( 1, 1, 0 )\nv = bx.get( 2, 0, 0 )\nv = bx.get( 2, 1, 1 )\n","Buffer":"var b = new Buffer( 4 )\nvar b1 = new Buffer( [ 1, 2, 3, 4 ] );\nvar b2 = new Buffer( b1 )\nvar b = new Buffer( [ 1, 2, 3, 4 ] )\nvar b = new Buffer( 'beep boop' )\n","buffer2json":"var buf = new allocUnsafe( 2 );\nbuf[ 0 ] = 1;\nbuf[ 1 ] = 2;\nvar json = buffer2json( buf )\n","BYTE_ORDER":"BYTE_ORDER\n","camelcase":"var out = camelcase( 'Hello World!' )\nout = camelcase( 'beep boop' )\n","capitalize":"var out = capitalize( 'beep' )\nout = capitalize( 'Boop' )\n","capitalizeKeys":"var obj = { 'aa': 1, 'bb': 2 };\nvar out = capitalizeKeys( obj )\n","CATALAN":"CATALAN\n","CBRT_EPS":"CBRT_EPS\n","CDC_NCHS_US_BIRTHS_1969_1988":"var data = CDC_NCHS_US_BIRTHS_1969_1988()\n","CDC_NCHS_US_BIRTHS_1994_2003":"var data = CDC_NCHS_US_BIRTHS_1994_2003()\n","CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013":"var data = CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n","chdir":"var err = chdir( '/path/to/current/working/directory' )\n","chi2gof":"var x = [ 89, 37, 30, 28, 2 ];\nvar p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\nvar out = chi2gof( x, p );\nvar o = out.toJSON()\nout.toString()\nvar opts = { 'alpha': 0.01 };\nout = chi2gof( x, p, opts );\nout.toString()\nx = [ 89, 37, 30, 28, 2 ];\np = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\nopts = { 'simulate': true, 'iterations': 1000 };\nout = chi2gof( x, p, opts );\nout.toString()\nvar lambda = 3.0;\nvar rpois = base.random.poisson.factory( lambda );\nvar len = 400;\nx = [];\nfor ( var i = 0; i < len; i++ ) { x.push( rpois() ); };\nvar freqs = new Int32Array( len );\nfor ( i = 0; i < len; i++ ) { freqs[ x[ i ] ] += 1; };\nout = chi2gof( freqs, 'poisson', lambda );\nout.toString()\n","chi2test":"var x = [ [ 20, 30 ], [ 30, 20 ] ];\nvar out = chi2test( x );\nvar o = out.toJSON()\nout.toString()\nvar opts = { 'alpha': 0.1 };\nout = chi2test( x, opts );\no = out.toJSON()\nout.toString()\nopts = { 'correct': false };\nout = chi2test( x, opts );\nout.toString()\n","circarray2iterator":"var it = circarray2iterator( [ 1, 2, 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","circularArrayStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 15 };\nvar s = circularArrayStream( [ 1, 2, 3 ], opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","circularArrayStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = circularArrayStream.factory( opts );\n","circularArrayStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 15 };\nvar s = circularArrayStream.objectMode( [ 1, 2, 3 ], opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","CircularBuffer":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.length\nb.count\nb.push( 'boop' )\n","CircularBuffer.prototype.clear":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.count\nb.clear();\nb.count\n","CircularBuffer.prototype.count":"var b = CircularBuffer( 3 );\nb.count\nb.push( 'foo' );\nb.count\nb.push( 'bar' );\nb.count\n","CircularBuffer.prototype.full":"var b = CircularBuffer( 3 );\nb.full\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.full\n","CircularBuffer.prototype.iterator":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.push( 'boop' );\nvar it = b.iterator( b.length );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","CircularBuffer.prototype.length":"var b = CircularBuffer( [ 0, 0, 0 ] );\nvar len = b.length\n","CircularBuffer.prototype.push":"var b = CircularBuffer( 3 );\nb.push( 'foo' )\nb.push( 'bar' )\nb.push( 'beep' )\nb.push( 'boop' )\n","CircularBuffer.prototype.toArray":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.push( 'boop' );\nvar vals = b.toArray()\n","CircularBuffer.prototype.toJSON":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.push( 'boop' );\nvar o = b.toJSON()\n","close":"function done( error ) {\n if ( error ) {\n     console.error( error.message );\n }\n };\nvar fd = open.sync( './beep/boop.js', 'r+' );\nif ( !isError( fd ) ) { close( fd, done ); };\n","close.sync":"var fd = open.sync( './beep/boop.js', 'r+' );\nif ( !isError( fd ) ) { close.sync( fd ); };\n","CMUDICT":"var data = CMUDICT();\nvar dict = data.dict\nvar phones = data.phones\nvar symbols = data.symbols\nvar vp = data.vp\n","codePointAt":"var out = codePointAt( 'last man standing', 4 )\nout = codePointAt( 'presidential election', 8, true )\nout = codePointAt( 'अनुच्छेद', 2 )\nout = codePointAt( '🌷', 1, true )\n","commonKeys":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\nvar keys = commonKeys( obj1, obj2 )\n","commonKeysIn":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\nvar keys = commonKeysIn( obj1, obj2 )\n","complex":"var z = complex( 5.0, 3.0, 'float64' )\nz = complex( 5.0, 3.0, 'float32' )\n","Complex64":"var z = new Complex64( 5.0, 3.0 )\nz.re\nz.im\n","Complex64.BYTES_PER_ELEMENT":"var s = Complex64.BYTES_PER_ELEMENT\n","Complex64.prototype.BYTES_PER_ELEMENT":"var z = new Complex64( 5.0, 3.0 )\nvar s = z.BYTES_PER_ELEMENT\n","Complex64.prototype.byteLength":"var z = new Complex64( 5.0, 3.0 )\nvar s = z.byteLength\n","COMPLEX64_NAN":"COMPLEX64_NAN\n","COMPLEX64_NUM_BYTES":"COMPLEX64_NUM_BYTES\n","COMPLEX64_ZERO":"COMPLEX64_ZERO\n","Complex64Array":"var arr = new Complex64Array()\nvar arr = new Complex64Array( 10 )\nvar len = arr.length\nvar arr1 = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar arr2 = new Complex64Array( arr1 )\nvar len = arr2.length\nvar buf = new Float32Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar arr = new Complex64Array( buf )\nvar len = arr.length\nvar arr1 = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar len = arr1.length\nvar buf = [ new Complex64( 1.0, -1.0 ), new Complex64( 2.0, -2.0 )];\nvar arr2 = new Complex64Array( buf )\nlen = arr2.length\nvar buf = new ArrayBuffer( 240 );\nvar arr1 = new Complex64Array( buf )\nvar len = arr1.length\nvar arr2 = new Complex64Array( buf, 8 )\nlen = arr2.length\nvar arr3 = new Complex64Array( buf, 8, 20 )\nlen = arr3.length\n","Complex64Array.from":"function clbkFcn( v ) { return v * 2.0 };\nvar arr = Complex64Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\nvar len = arr.length\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.of":"var arr = Complex64Array.of( 1.0, -1.0, 2.0, -2.0 )\nvar len = arr.length\nvar z1 = new Complex64( 1.0, -1.0 );\nvar z2 = new Complex64( 2.0, -2.0 );\narr = Complex64Array.of( z1, z2 )\nlen = arr.length\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.BYTES_PER_ELEMENT":"var nbytes = Complex64Array.BYTES_PER_ELEMENT\n","Complex64Array.name":"var str = Complex64Array.name\n","Complex64Array.prototype.buffer":"var arr = new Complex64Array( 2 )\nvar buf = arr.buffer\n","Complex64Array.prototype.byteLength":"var arr = new Complex64Array( 10 )\nvar nbytes = arr.byteLength\n","Complex64Array.prototype.byteOffset":"var arr = new Complex64Array( 5 )\nvar offset = arr.byteOffset\nvar buf = new ArrayBuffer( 240 );\narr = new Complex64Array( buf, 64 )\noffset = arr.byteOffset\n","Complex64Array.prototype.BYTES_PER_ELEMENT":"var arr = new Complex64Array( 10 )\narr.BYTES_PER_ELEMENT\n","Complex64Array.prototype.length":"var arr = new Complex64Array( 10 )\nvar len = arr.length\n","Complex64Array.prototype.at":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.at( 1 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.copyWithin":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\narr.copyWithin( 0, 2 )\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.entries":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\nvar it = arr.entries();\nvar v = it.next().value\nvar re = realf( v[ 1 ] )\nvar im = imagf( v[ 1 ] )\nv = it.next().value\nre = realf( v[ 1 ] )\nim = imagf( v[ 1 ] )\nv = it.next().value\nre = realf( v[ 1 ] )\nim = imagf( v[ 1 ] )\nvar bool = it.next().done\n","Complex64Array.prototype.every":"function predicate( v ) { return ( realf( v ) > 0.0 ); };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar bool = arr.every( predicate )\n","Complex64Array.prototype.fill":"var arr = new Complex64Array( 3 )\narr.fill( new Complex64( 1.0, 1.0 ) );\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = arr.get( 1 )\nre = realf( z )\nim = imagf( z )\nz = arr.get( 2 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.filter":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar out = arr.filter( predicate )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.find":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar z = arr.find( predicate )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.findIndex":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar idx = arr.findIndex( predicate )\n","Complex64Array.prototype.findLast":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar z = arr.findLast( predicate )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.findLastIndex":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar idx = arr.findLastIndex( predicate )\n","Complex64Array.prototype.forEach":"var str = '%';\nfunction clbk( v ) { str += v.toString() + '%'; };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\narr.forEach( clbk );\nstr\n","Complex64Array.prototype.get":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.get( 1 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.includes":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar bool = arr.includes( new Complex64( 3.0, -3.0 ) )\nbool = arr.includes( new Complex64( 3.0, -3.0 ), 3 )\n","Complex64Array.prototype.indexOf":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar idx = arr.indexOf( new Complex64( 3.0, -3.0 ) )\nidx = arr.indexOf( new Complex64( 3.0, -3.0 ), 3 )\n","Complex64Array.prototype.join":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar str = arr.join()\nstr = arr.join( '/' )\n","Complex64Array.prototype.keys":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar it = arr.keys();\nvar v = it.next().value\nv = it.next().value\nv = it.next().done\n","Complex64Array.prototype.lastIndexOf":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\nvar idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ) )\nidx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ), 2 )\n","Complex64Array.prototype.map":"function clbk( v ) { return v; };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar out = arr.map( clbk )\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = out.get( 1 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.reduce":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.reduce( base.caddf )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.reduceRight":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.reduceRight( base.caddf )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.reverse":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\narr.reverse();\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = arr.get( 1 )\nre = realf( z )\nim = imagf( z )\nz = arr.get( 2 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.set":"var arr = new Complex64Array( 2 )\narr.set( new Complex64( 1.0, -1.0 ) );\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\narr.set( new Complex64( 2.0, -2.0 ), 1 );\nz = arr.get( 1 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.slice":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\nvar out = arr.slice( 1 )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = out.get( 1 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.some":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar bool = arr.some( predicate )\n","Complex64Array.prototype.sort":"function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\nvar arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\narr.sort( compare );\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = arr.get( 1 )\nre = realf( z )\nim = imagf( z )\nz = arr.get( 2 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.subarray":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar out = arr.subarray( 1, 3 )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = out.get( 1 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.toLocaleString":"var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0 ] )\nvar str = arr.toLocaleString()\n","Complex64Array.prototype.toReversed":"var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\nvar out = arr.toReversed()\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = out.get( 1 )\nre = realf( z )\nim = imagf( z )\nz = out.get( 2 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.toSorted":"function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\nvar arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\nvar out = arr.toSorted( compare );\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = out.get( 1 )\nre = realf( z )\nim = imagf( z )\nz = out.get( 2 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.toString":"var arr = new Complex64Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\nvar str = arr.toString()\n","Complex64Array.prototype.values":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar it = arr.values();\nvar v = it.next().value\nvar re = realf( v )\nvar im = imagf( v )\nv = it.next().value\nre = realf( v )\nim = imagf( v )\nvar bool = it.next().done\n","Complex64Array.prototype.with":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\nvar z = out.get( 1 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex128.BYTES_PER_ELEMENT":"var s = Complex128.BYTES_PER_ELEMENT\n","Complex128.prototype.BYTES_PER_ELEMENT":"var z = new Complex128( 5.0, 3.0 )\nvar s = z.BYTES_PER_ELEMENT\n","Complex128.prototype.byteLength":"var z = new Complex128( 5.0, 3.0 )\nvar s = z.byteLength\n","COMPLEX128_NAN":"COMPLEX128_NAN\n","COMPLEX128_NUM_BYTES":"COMPLEX128_NUM_BYTES\n","COMPLEX128_ZERO":"COMPLEX128_ZERO\n","Complex128Array":"var arr = new Complex128Array()\nvar arr = new Complex128Array( 10 )\nvar len = arr.length\nvar arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar arr2 = new Complex128Array( arr1 )\nvar len = arr2.length\nvar buf = new Float64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar arr = new Complex128Array( buf )\nvar len = arr.length\nvar arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar len = arr1.length\nvar buf = [ new Complex128( 1.0, -1.0 ), new Complex128( 2.0, -2.0 ) ];\nvar arr2 = new Complex128Array( buf )\nlen = arr2.length\nvar buf = new ArrayBuffer( 480 );\nvar arr1 = new Complex128Array( buf )\nvar len = arr1.length\nvar arr2 = new Complex128Array( buf, 16 )\nlen = arr2.length\nvar arr3 = new Complex128Array( buf, 16, 20 )\nlen = arr3.length\n","Complex128Array.from":"function clbkFcn( v ) { return v * 2.0 };\nvar arr = Complex128Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\nvar len = arr.length\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.of":"var arr = Complex128Array.of( 1.0, -1.0, 2.0, -2.0 )\nvar len = arr.length\nvar z1 = new Complex128( 1.0, -1.0 );\nvar z2 = new Complex128( 2.0, -2.0 );\narr = Complex128Array.of( z1, z2 )\nlen = arr.length\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.BYTES_PER_ELEMENT":"var nbytes = Complex128Array.BYTES_PER_ELEMENT\n","Complex128Array.name":"var str = Complex128Array.name\n","Complex128Array.prototype.buffer":"var arr = new Complex128Array( 2 )\nvar buf = arr.buffer\n","Complex128Array.prototype.byteLength":"var arr = new Complex128Array( 10 )\nvar nbytes = arr.byteLength\n","Complex128Array.prototype.byteOffset":"var arr = new Complex128Array( 10 )\nvar offset = arr.byteOffset\nvar buf = new ArrayBuffer( 480 );\narr = new Complex128Array( buf, 128 )\noffset = arr.byteOffset\n","Complex128Array.prototype.BYTES_PER_ELEMENT":"var arr = new Complex128Array( 10 )\narr.BYTES_PER_ELEMENT\n","Complex128Array.prototype.length":"var arr = new Complex128Array( 10 )\nvar len = arr.length\n","Complex128Array.prototype.at":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.at( 1 )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.copyWithin":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\narr.copyWithin( 0, 2 )\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.entries":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\nvar it = arr.entries();\nvar v = it.next().value\nvar re = real( v[ 1 ] )\nvar im = imag( v[ 1 ] )\nv = it.next().value\nre = real( v[ 1 ] )\nim = imag( v[ 1 ] )\nv = it.next().value\nre = real( v[ 1 ] )\nim = imag( v[ 1 ] )\nvar bool = it.next().done\n","Complex128Array.prototype.every":"function predicate( v ) { return ( real( v ) > 0.0 ); };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar bool = arr.every( predicate )\n","Complex128Array.prototype.fill":"var arr = new Complex128Array( 3 )\narr.fill( new Complex128( 1.0, 1.0 ) );\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = arr.get( 1 )\nre = real( z )\nim = imag( z )\nz = arr.get( 2 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.filter":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar out = arr.filter( predicate )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.find":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar z = arr.find( predicate )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.findIndex":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar idx = arr.findIndex( predicate )\n","Complex128Array.prototype.findLast":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar z = arr.findLast( predicate )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.findLastIndex":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar idx = arr.findLastIndex( predicate )\n","Complex128Array.prototype.forEach":"var str = '%';\nfunction clbk( v ) { str += v.toString() + '%'; };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\narr.forEach( clbk );\nstr\n","Complex128Array.prototype.get":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.get( 1 )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.includes":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar bool = arr.includes( new Complex128( 3.0, -3.0 ) )\nbool = arr.includes( new Complex128( 3.0, -3.0 ), 3 )\n","Complex128Array.prototype.indexOf":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar idx = arr.indexOf( new Complex128( 3.0, -3.0 ) )\nidx = arr.indexOf( new Complex128( 3.0, -3.0 ), 3 )\n","Complex128Array.prototype.join":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar str = arr.join()\nstr = arr.join( '/' )\n","Complex128Array.prototype.keys":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar it = arr.keys();\nvar v = it.next().value\nv = it.next().value\nv = it.next().done\n","Complex128Array.prototype.lastIndexOf":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\nvar idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ) )\nidx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ), 2 )\n","Complex128Array.prototype.map":"function clbk( v ) { return v; };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar out = arr.map( clbk )\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = out.get( 1 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.reduce":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.reduce( base.cadd )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.reduceRight":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.reduceRight( base.cadd )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.reverse":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\narr.reverse();\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = arr.get( 1 )\nre = real( z )\nim = imag( z )\nz = arr.get( 2 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.set":"var arr = new Complex128Array( 2 )\narr.set( new Complex128( 1.0, -1.0 ) );\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\narr.set( new Complex128( 2.0, -2.0 ), 1 );\nz = arr.get( 1 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.slice":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\nvar out = arr.slice( 1 )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = out.get( 1 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.some":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar bool = arr.some( predicate )\n","Complex128Array.prototype.sort":"function compare( a, b ) { return ( real( a ) - real( b ) ); };\nvar arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\narr.sort( compare );\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = arr.get( 1 )\nre = real( z )\nim = imag( z )\nz = arr.get( 2 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.subarray":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar out = arr.subarray( 1, 3 )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = out.get( 1 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.toLocaleString":"var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0 ] )\nvar str = arr.toLocaleString()\n","Complex128Array.prototype.toReversed":"var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\nvar out = arr.toReversed()\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = out.get( 1 )\nre = real( z )\nim = imag( z )\nz = out.get( 2 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.toSorted":"function compare( a, b ) { return ( real( a ) - real( b ) ); };\nvar arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\nvar out = arr.toSorted( compare );\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = out.get( 1 )\nre = real( z )\nim = imag( z )\nz = out.get( 2 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.toString":"var arr = new Complex128Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\nvar str = arr.toString()\n","Complex128Array.prototype.values":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar it = arr.values();\nvar v = it.next().value\nvar re = real( v )\nvar im = imag( v )\nv = it.next().value\nre = real( v )\nim = imag( v )\nvar bool = it.next().done\n","Complex128Array.prototype.with":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\nvar z = out.get( 1 )\nvar re = real( z )\nvar im = imag( z )\n","complexarray":"var arr = complexarray()\narr = complexarray( 'complex64' )\nvar arr = complexarray( 5 )\narr = complexarray( 5, 'complex64' )\nvar arr1 = complexarray( [ 0.5, 0.5, 0.5, 0.5 ] );\nvar arr2 = complexarray( arr1, 'complex64' )\nvar arr1 = [ 0.5, 0.5, 0.5, 0.5 ];\nvar arr2 = complexarray( arr1, 'complex64' )\nvar buf = new ArrayBuffer( 64 );\nvar arr = complexarray( buf, 0, 8, 'complex64' )\n","complexarrayCtors":"var ctor = complexarrayCtors( 'complex64' )\nctor = complexarrayCtors( 'float32' )\n","complexarrayDataTypes":"var out = complexarrayDataTypes()\n","complexCtors":"var ctor = complexCtors( 'complex128' )\nctor = complexCtors( 'complex' )\n","complexDataType":"var v = new Complex128( 1.0, 2.0 );\nvar dt = complexDataType( v )\ndt = complexDataType( 'beep' )\n","complexDataTypes":"var out = complexDataTypes()\n","complexPromotionRules":"var out = complexPromotionRules( 'complex128', 'complex64' )\n","compose":"function a( x ) {\nreturn 2 * x;\n }\nfunction b( x ) {\nreturn x + 3;\n }\nfunction c( x ) {\nreturn x / 5;\n }\nvar f = compose( c, b, a );\nvar z = f( 6 )\n","composeAsync":"function a( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n    next( null, 2*x );\n}\n };\nfunction b( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n    next( null, x+3 );\n}\n };\nfunction c( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n    next( null, x/5 );\n}\n };\nvar f = composeAsync( c, b, a );\nfunction done( error, result ) {\nif ( error ) {\n    throw error;\n}\nconsole.log( result );\n };\nf( 6, done )\n","configdir":"var dir = configdir()\ndir = configdir( 'appname/config' )\n","conj":"var z = new Complex128( 5.0, 3.0 );\nz.toString()\nvar v = conj( z );\nv.toString()\n","conjf":"var z = new Complex64( 5.0, 3.0 );\nz.toString()\nvar v = conjf( z );\nv.toString()\n","constantcase":"var out = constantcase( 'Hello World!' )\nout = constantcase( 'I am a tiny little teapot' )\n","constantFunction":"var fcn = constantFunction( 3.14 );\nvar v = fcn()\nv = fcn()\nv = fcn()\n","constantStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = constantStream( 'beep', opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","constantStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = constantStream.factory( opts );\n","constantStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = constantStream.objectMode( 3.14, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","constructorName":"var v = constructorName( 'a' )\nv = constructorName( {} )\nv = constructorName( true )\n","contains":"var bool = contains( 'Hello World', 'World' )\nbool = contains( 'Hello World', 'world' )\nbool = contains( [ 1, 2, 3, 4 ], 2 )\nbool = contains( [ NaN, 2, 3, 4 ], NaN )\nbool = contains( 'Hello World', 'Hello', 6 )\nbool = contains( [ true, NaN, false ], true, 1 )\n","convertArray":"var arr = [ 1.0, 2.0, 3.0, 4.0 ];\nvar out = convertArray( arr, 'float32' )\n","convertArraySame":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = new Float32Array( 0 );\nvar out = convertArraySame( x, y )\n","convertPath":"var out = convertPath( '/c/foo/bar/beep.c', 'win32' )\nout = convertPath( '/c/foo/bar/beep.c', 'mixed' )\nout = convertPath( '/c/foo/bar/beep.c', 'posix' )\nout = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'win32' )\nout = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'mixed' )\nout = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'posix' )\n","copy":"var value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\nvar out = copy( value )\nvar bool = ( value[ 0 ].c === out[ 0 ].c )\nvalue = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\nout = copy( value, 1 );\nbool = ( value[ 0 ] === out[ 0 ] )\nbool = ( value[ 0 ].c === out[ 0 ].c )\n","copyBuffer":"var b1 = array2buffer( [ 1, 2, 3, 4 ] );\nvar b2 = copyBuffer( b1 )\n","countBy":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n     return 'b';\n }\n return 'other';\n };\nvar collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar out = countBy( collection, indicator )\n","countByAsync":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\ncountByAsync( arr, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\ncountByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\ncountByAsync( arr, opts, indicator, done )\n","countByAsync.factory":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nvar opts = { 'series': true };\nvar f = countByAsync.factory( opts, indicator );\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000, 500 ];\nf( arr, done )\n","currentYear":"var y = currentYear()\n","curry":"function add( x, y ) { return x + y; };\nvar f = curry( add );\nvar sum = f( 2 )( 3 )\nfunction add() { return arguments[ 0 ] + arguments[ 1 ]; };\nf = curry( add, 2 );\nsum = f( 2 )( 3 )\nvar obj = {\n 'name': 'Ada',\n 'greet': function greet( word1, word2 ) {\n    return word1 + ' ' + word2 + ', ' + this.name + '!'\n }\n };\nf = curry( obj.greet, obj );\nvar str = f( 'Hello' )( 'there' )\n","curryRight":"function add( x, y ) { return x + y; };\nvar f = curryRight( add );\nvar sum = f( 2 )( 3 )\nfunction add() { return arguments[ 0 ] + arguments[ 1 ]; };\nf = curryRight( add, 2 );\nsum = f( 2 )( 3 )\nvar obj = {\n 'name': 'Ada',\n 'greet': function greet( word1, word2 ) {\n     return word1 + ' ' + word2 + ', ' + this.name + '!'\n }\n };\nf = curryRight( obj.greet, obj );\nvar str = f( 'there' )( 'Hello' )\n","cwd":"var dir = cwd()\n","DALE_CHALL_NEW":"var list = DALE_CHALL_NEW()\n","datasets":"var out = datasets( 'MONTH_NAMES_EN' )\nvar opts = { 'data': 'cities' };\nout = datasets( 'MINARD_NAPOLEONS_MARCH', opts )\n","DataView":"var buf = new ArrayBuffer( 5 )\nvar dv = new DataView( buf )\n","DataView.prototype.buffer":"var buf1 = new ArrayBuffer( 5 );\nvar dv = new DataView( buf1 );\nvar buf2 = dv.buffer\nvar b = ( buf1 === buf2 )\n","DataView.prototype.byteLength":"var buf = new ArrayBuffer( 5 );\nvar dv = new DataView( buf );\ndv.byteLength\n","DataView.prototype.byteOffset":"var buf = new ArrayBuffer( 5 );\nvar dv = new DataView( buf, 2 );\ndv.byteLength\ndv.byteOffset\n","datespace":"var stop = '2014-12-02T07:00:54.973Z';\nvar start = new Date( stop ) - 60000;\nvar arr = datespace( start, stop, 6 )\nvar opts = { 'round': 'ceil' };\narr = datespace( 1417503655000, 1417503655001, 3, opts )\n","dayOfQuarter":"var day = dayOfQuarter()\nday = dayOfQuarter( new Date() )\nday = dayOfQuarter( 12, 31, 2017 )\nday = dayOfQuarter( 'dec', 31, 2017 )\nday = dayOfQuarter( 'december', 31, 2017 )\n","dayOfYear":"var day = dayOfYear()\nday = dayOfYear( new Date() )\nday = dayOfYear( 12, 31, 2016 )\nday = dayOfYear( 'dec', 31, 2016 )\nday = dayOfYear( 'december', 31, 2016 )\n","daysInMonth":"var num = daysInMonth()\nnum = daysInMonth( 2 )\nnum = daysInMonth( 2, 2016 )\nnum = daysInMonth( 2, 2017 )\nnum = daysInMonth( 'feb', 2016 )\nnum = daysInMonth( 'february', 2016 )\n","daysInYear":"var num = daysInYear()\nnum = daysInYear( 2016 )\nnum = daysInYear( 2017 )\n","ddot":"var xbuf = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar x = array( xbuf );\nvar ybuf = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar y = array( ybuf );\nvar z = ddot( x, y )\nz.get()\n","debugSinkStream":"var s = debugSinkStream( { 'name': 'foo' } );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","debugSinkStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = debugSinkStream.factory( opts );\n","debugSinkStream.objectMode":"var s = debugSinkStream.objectMode( { 'name': 'foo' } );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","debugStream":"var s = debugStream( { 'name': 'foo' } );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","debugStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = debugStream.factory( opts );\n","debugStream.objectMode":"var s = debugStream.objectMode( { 'name': 'foo' } );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","decorateAfter":"function f( v ) { return -v; };\nvar fcn = decorateAfter( base.abs, 1, f );\nvar v = fcn( -5 )\nv = fcn( 5 )\n","decorateAfter.factory":"function f( v ) { return -v; };\nvar fcn = decorateAfter.factory( base.abs, 1, f );\nvar v = fcn( -5 )\nv = fcn( 5 )\n","deepEqual":"var bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, 3 ] )\nbool = deepEqual( [ 1, 2, 3 ], [ 1, 2, '3' ] )\nbool = deepEqual( { 'a': 2 }, { 'a': [ 2 ] } )\n","deepGet":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar val = deepGet( obj, 'a.b.c' )\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar val = deepGet( obj, 'a/b/c', { 'sep': '/' } )\n","deepGet.factory":"var dget = deepGet.factory( 'a/b/c', { 'sep': '/' } );\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar val = dget( obj )\n","deepHasOwnProp":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = deepHasOwnProp( obj, 'a.b.c' )\nobj = { 'a': { 'b': { 'c': 'd' } } };\nbool = deepHasOwnProp( obj, 'a/b/c', { 'sep': '/' } )\n","deepHasOwnProp.factory":"var has = deepHasOwnProp.factory( 'a/b/c', { 'sep': '/' } );\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = has( obj )\n","deepHasProp":"function Foo() { return this; };\nFoo.prototype.b = { 'c': 'd' };\nvar obj = { 'a': new Foo() };\nvar bool = deepHasProp( obj, 'a.b.c' )\nbool = deepHasProp( obj, 'a/b/c', { 'sep': '/' } )\n","deepHasProp.factory":"function Foo() { return this; };\nFoo.prototype.b = { 'c': 'd' };\nvar has = deepHasProp.factory( 'a/b/c', { 'sep': '/' } );\nvar obj = { 'a': new Foo() };\nvar bool = has( obj )\n","deepPluck":"var arr = [\n { 'a': { 'b': { 'c': 1 } } },\n { 'a': { 'b': { 'c': 2 } } }\n ];\nvar out = deepPluck( arr, 'a.b.c' )\narr = [\n { 'a': [ 0, 1, 2 ] },\n { 'a': [ 3, 4, 5 ] }\n ];\nout = deepPluck( arr, [ 'a', 1 ] )\n","deepSet":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = deepSet( obj, 'a.b.c', 'beep' )\nobj = { 'a': { 'b': { 'c': 'd' } } };\nbool = deepSet( obj, 'a/b/c', 'beep', { 'sep': '/' } );\nobj\nbool = deepSet( obj, 'a.e.c', 'boop', { 'create': true } );\nobj\n","deepSet.factory":"var dset = deepSet.factory( 'a/b/c', {\n 'create': true,\n 'sep': '/'\n });\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = dset( obj, 'beep' )\nobj\n","defineMemoizedProperty":"var obj = {};\nfunction foo() {\n return 'bar';\n };\ndefineMemoizedProperty( obj, 'foo', {\n 'configurable': false,\n 'enumerable': true,\n 'writable': false,\n 'value': foo\n });\nobj.foo\n","defineProperties":"var obj = {};\ndefineProperties( obj, {\n 'foo': {\n     'value': 'bar',\n     'writable': false,\n     'configurable': false,\n     'enumerable': true\n },\n 'baz': {\n     'value': 13\n }\n });\nobj.foo\nobj.baz\n","defineProperty":"var obj = {};\ndefineProperty( obj, 'foo', {\n 'value': 'bar',\n 'enumerable': true,\n 'writable': false\n });\nobj.foo = 'boop';\nobj\n","dirname":"var dir = dirname( './foo/bar/index.js' )\n","dotcase":"var out = dotcase( 'Hello World!' )\nout = dotcase( 'beep boop' )\n","DoublyLinkedList":"var list = DoublyLinkedList();\nlist.push( 'foo' ).push( 'bar' );\nlist.length\nlist.pop()\nlist.length\nlist.pop()\nlist.length\n","doUntil":"function predicate( i ) { return ( i >= 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\ndoUntil( beep, predicate )\n","doUntilAsync":"function fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n     next( null, 'boop'+i );\n }\n };\nfunction predicate( i, clbk ) { clbk( null, i >= 5 ); };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\ndoUntilAsync( fcn, predicate, done )\n","doUntilEach":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\ndoUntilEach( arr, logger, predicate )\n","doUntilEachRight":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\ndoUntilEachRight( arr, logger, predicate )\n","doWhile":"function predicate( i ) { return ( i < 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\ndoWhile( beep, predicate )\n","doWhileAsync":"function fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n     next( null, 'boop'+i );\n }\n };\nfunction predicate( i, clbk ) { clbk( null, i < 5 ); };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\ndoWhileAsync( fcn, predicate, done )\n","doWhileEach":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\ndoWhileEach( arr, logger, predicate )\n","doWhileEachRight":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\ndoWhileEachRight( arr, logger, predicate )\n","dswap":"var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\ndswap( x, y );\nx.data\ny.data\n","E":"E\n","EMOJI":"var data = EMOJI()\n","EMOJI_CODE_PICTO":"var out = EMOJI_CODE_PICTO()\n","EMOJI_PICTO_CODE":"var out = EMOJI_PICTO_CODE()\n","emptyStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar s = emptyStream();\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","emptyStream.factory":"var opts = { 'objectMode': true };\nvar createStream = emptyStream.factory( opts );\n","emptyStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar s = emptyStream.objectMode();\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","endsWith":"var bool = endsWith( 'beep', 'ep' )\nbool = endsWith( 'Beep', 'op' )\nbool = endsWith( 'Beep', 'ee', 3 )\nbool = endsWith( 'Beep', 'ee', -1 )\nbool = endsWith( 'beep', '' )\n","enumerableProperties":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar props = enumerableProperties( obj )\n","enumerablePropertiesIn":"var props = enumerablePropertiesIn( [] )\n","enumerablePropertySymbols":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = enumerablePropertySymbols( obj )\n","enumerablePropertySymbolsIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = enumerablePropertySymbolsIn( obj )\n","ENV":"var user = ENV.USER\n","EPS":"EPS\n","error2json":"var err = new Error( 'beep' );\nvar json = error2json( err )\n","EULERGAMMA":"EULERGAMMA\n","every":"var arr = [ 1, 1, 1, 1, 1 ];\nvar bool = every( arr )\n","everyBy":"function positive( v ) { return ( v > 0 ); };\nvar arr = [ 1, 2, 3, 4 ];\nvar bool = everyBy( arr, positive )\n","everyByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\neveryByAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\neveryByAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\neveryByAsync( arr, opts, predicate, done )\n","everyByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, true );\n }\n };\nvar opts = { 'series': true };\nvar f = everyByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","everyByRight":"function positive( v ) { return ( v > 0 ); };\nvar arr = [ 1, 2, 3, 4 ];\nvar bool = everyByRight( arr, positive )\n","everyByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\neveryByRightAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\neveryByRightAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\neveryByRightAsync( arr, opts, predicate, done )\n","everyByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, true );\n }\n };\nvar opts = { 'series': true };\nvar f = everyByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","everyInBy":"function positive( v ) { return ( v > 0 ); };\nvar o = {a: 1, b: 2, c: 3};\nvar bool = everyInBy( o, positive )\n","everyOwnBy":"function positive( v ) { return ( v > 0 ); };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nvar bool = everyOwnBy( obj, positive )\n","evil":"var v = evil( '5*4*3*2*1' )\n","EXEC_PATH":"EXEC_PATH\n","exists":"function done( error, bool ) { console.log( bool ); };\nexists( './beep/boop', done );\n","exists.sync":"var bool = exists.sync( './beep/boop' )\n","expandAcronyms":"var str = 'LOL, this is fun. I am ROFL.';\nvar out = expandAcronyms( str )\nstr = 'brb, I need to check my mail. thx!';\nout = expandAcronyms( str )\n","expandContractions":"var str = 'I won\\'t be able to get y\\'all out of this one.';\nvar out = expandContractions( str )\nstr = 'It oughtn\\'t to be my fault, because, you know, I didn\\'t know';\nout = expandContractions( str )\n","extname":"var ext = extname( 'index.js' )\n","FancyArray":"var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\nvar d = [ 2, 2 ]; // shape\nvar s = [ 2, 1 ]; // strides\nvar o = 0; // index offset\nvar arr = FancyArray( 'generic', b, d, s, o, 'row-major' )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","FancyArray.prototype.byteLength":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.byteLength\n","FancyArray.prototype.BYTES_PER_ELEMENT":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.BYTES_PER_ELEMENT\n","FancyArray.prototype.data":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar buf = arr.data\n","FancyArray.prototype.dtype":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar dt = arr.dtype\n","FancyArray.prototype.flags":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar fl = arr.flags\n","FancyArray.prototype.length":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar len = arr.length\n","FancyArray.prototype.ndims":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar n = arr.ndims\n","FancyArray.prototype.offset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.offset\n","FancyArray.prototype.order":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar ord = arr.order\n","FancyArray.prototype.shape":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar sh = arr.shape\n","FancyArray.prototype.strides":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar st = arr.strides\n","FancyArray.prototype.get":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.get( 1, 1 )\n","FancyArray.prototype.iget":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.iget( 3 )\n","FancyArray.prototype.set":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\narr.set( 1, 1, -4.0 );\narr.get( 1, 1 )\n","FancyArray.prototype.iset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\narr.iset( 3, -4.0 );\narr.iget( 3 )\n","FancyArray.prototype.toString":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\narr.toString()\n","FancyArray.prototype.toJSON":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\narr.toJSON()\n","fastmath.abs":"var v = fastmath.abs( -1.0 )\nv = fastmath.abs( 2.0 )\nv = fastmath.abs( 0.0 )\nv = fastmath.abs( -0.0 )\nv = fastmath.abs( NaN )\n","fastmath.acosh":"var v = fastmath.acosh( 1.0 )\nv = fastmath.acosh( 2.0 )\nv = fastmath.acosh( NaN )\nv = fastmath.acosh( 1.0e308 )\n","fastmath.ampbm":"var h = fastmath.ampbm( 5.0, 12.0 )\n","fastmath.ampbm.factory":"var hypot = fastmath.ampbm.factory( 1.0, 0.5 )\n","fastmath.asinh":"var v = fastmath.asinh( 0.0 )\nv = fastmath.asinh( 2.0 )\nv = fastmath.asinh( -2.0 )\nv = fastmath.asinh( NaN )\nv = fastmath.asinh( 1.0e200 )\nv = fastmath.asinh( 1.0e-50 )\n","fastmath.atanh":"var v = fastmath.atanh( 0.0 )\nv = fastmath.atanh( 0.9 )\nv = fastmath.atanh( 1.0 )\nv = fastmath.atanh( -1.0 )\nv = fastmath.atanh( NaN )\nv = fastmath.atanh( 1.0e-17 )\n","fastmath.hypot":"var h = fastmath.hypot( -5.0, 12.0 )\nh = fastmath.hypot( 1.0e154, 1.0e154 )\nh = fastmath.hypot( 1e-200, 1.0e-200 )\n","fastmath.log2Uint32":"var v = fastmath.log2Uint32( 4 >>> 0 )\nv = fastmath.log2Uint32( 8 >>> 0 )\nv = fastmath.log2Uint32( 9 >>> 0 )\n","fastmath.max":"var v = fastmath.max( 3.14, 4.2 )\nv = fastmath.max( 3.14, NaN )\nv = fastmath.max( NaN, 3.14 )\nv = fastmath.max( -0.0, +0.0 )\nv = fastmath.max( +0.0, -0.0 )\n","fastmath.min":"var v = fastmath.min( 3.14, 4.2 )\nv = fastmath.min( 3.14, NaN )\nv = fastmath.min( NaN, 3.14 )\nv = fastmath.min( -0.0, +0.0 )\nv = fastmath.min( +0.0, -0.0 )\n","fastmath.powint":"var v = fastmath.powint( 2.0, 3 )\nv = fastmath.powint( 3.14, 0 )\nv = fastmath.powint( 2.0, -2 )\nv = fastmath.powint( 0.0, 0 )\nv = fastmath.powint( -3.14, 1 )\nv = fastmath.powint( NaN, 0 )\n","fastmath.sqrtUint32":"var v = fastmath.sqrtUint32( 9 >>> 0 )\nv = fastmath.sqrtUint32( 2 >>> 0 )\nv = fastmath.sqrtUint32( 3 >>> 0 )\nv = fastmath.sqrtUint32( 0 >>> 0 )\n","FEMALE_FIRST_NAMES_EN":"var list = FEMALE_FIRST_NAMES_EN()\n","FIFO":"var q = FIFO();\nq.push( 'foo' ).push( 'bar' );\nq.length\nq.pop()\nq.length\nq.pop()\nq.length\n","filledarray":"var arr = filledarray()\narr = filledarray( 'float32' )\nvar arr = filledarray( 1.0, 5 )\narr = filledarray( 1, 5, 'int32' )\nvar arr1 = filledarray( 2.0, [ 0.5, 0.5, 0.5 ] )\nvar arr2 = filledarray( 1.0, arr1, 'float32' )\nvar arr1 = iterConstant( 3.0, {'iter': 3} );\nvar arr2 = filledarray( 1.0, arr1, 'float32' )\nvar buf = new ArrayBuffer( 16 );\nvar arr = filledarray( 1.0, buf, 0, 4, 'float32' )\n","filledarrayBy":"var arr = filledarrayBy()\narr = filledarrayBy( 'float32' )\nfunction clbk() { return 1.0; };\nvar arr = filledarrayBy( 5, clbk )\narr = filledarrayBy( 5, 'int32', clbk )\nvar arr1 = filledarrayBy( [ 0.5, 0.5, 0.5 ], constantFunction( 2.0 ) )\nvar arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\nvar arr1 = iterConstant( 3.0, {'iter': 3} );\nvar arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\nvar buf = new ArrayBuffer( 16 );\nvar arr = filledarrayBy( buf, 0, 4, 'float32', constantFunction( 1.0 ) )\n","filterArguments":"function foo( a, b ) { return [ a, b ]; };\nfunction predicate( v ) { return ( v !== 2 ); };\nvar bar = filterArguments( foo, predicate );\nvar out = bar( 1, 2, 3 )\n","find":"var data = [ 30, 20, 50, 60, 10 ];\nfunction condition( val ) { return val > 20; };\nvar vals = find( data, condition )\ndata = [ 30, 20, 50, 60, 10 ];\nvar opts = { 'k': 2, 'returns': 'values' };\nvals = find( data, opts, condition )\ndata = [ 30, 20, 50, 60, 10 ];\nopts = { 'k': -2, 'returns': '*' };\nvals = find( data, opts, condition )\n","firstChar":"var out = firstChar( 'beep' )\nout = firstChar( 'Boop', 1 )\nout = firstChar( 'foo bar', 5 )\n","FIVETHIRTYEIGHT_FFQ":"var data = FIVETHIRTYEIGHT_FFQ()\n","flattenArray":"var arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\nvar out = flattenArray( arr )\narr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\nout = flattenArray( arr, { 'depth': 2 } )\nvar bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\narr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\nout = flattenArray( arr, { 'depth': 2, 'copy': true } )\nbool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n","flattenArray.factory":"var flatten = flattenArray.factory( [ 2, 2 ], {\n 'copy': false\n });\nvar out = flatten( [ [ 1, 2 ], [ 3, 4 ] ] )\nout = flatten( [ [ 5, 6 ], [ 7, 8 ] ] )\n","flattenObject":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar out = flattenObject( obj )\nobj = { 'a': { 'b': { 'c': 'd' } } };\nout = flattenObject( obj, { 'depth': 1 } )\nvar bool = ( obj.a.b === out[ 'a.b' ] )\nobj = { 'a': { 'b': { 'c': 'd' } } };\nout = flattenObject( obj, { 'delimiter': '-|-' } )\nobj = { 'a': { 'b': [ 1, 2, 3 ] } };\nout = flattenObject( obj, { 'flattenArrays': true } )\n","flattenObject.factory":"var flatten = flattenObject.factory({\n 'depth': 1,\n 'copy': true,\n 'delimiter': '|'\n });\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar out = flatten( obj )\n","flignerTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = flignerTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = flignerTest( arr, { 'groups': groups } )\n","FLOAT_WORD_ORDER":"FLOAT_WORD_ORDER\n","FLOAT16_CBRT_EPS":"FLOAT16_CBRT_EPS\n","FLOAT16_EPS":"FLOAT16_EPS\n","FLOAT16_EXPONENT_BIAS":"FLOAT16_EXPONENT_BIAS\n","FLOAT16_MAX":"FLOAT16_MAX\n","FLOAT16_MAX_SAFE_INTEGER":"FLOAT16_MAX_SAFE_INTEGER\n","FLOAT16_MIN_SAFE_INTEGER":"FLOAT16_MIN_SAFE_INTEGER\n","FLOAT16_NINF":"FLOAT16_NINF\n","FLOAT16_NUM_BYTES":"FLOAT16_NUM_BYTES\n","FLOAT16_PINF":"FLOAT16_PINF\n","FLOAT16_PRECISION":"FLOAT16_PRECISION\n","FLOAT16_SMALLEST_NORMAL":"FLOAT16_SMALLEST_NORMAL\n","FLOAT16_SMALLEST_SUBNORMAL":"FLOAT16_SMALLEST_SUBNORMAL\n","FLOAT16_SQRT_EPS":"FLOAT16_SQRT_EPS\n","FLOAT32_ABS_MASK":"FLOAT32_ABS_MASK\nbase.toBinaryStringUint32( FLOAT32_ABS_MASK )\n","FLOAT32_CBRT_EPS":"FLOAT32_CBRT_EPS\n","FLOAT32_E":"FLOAT32_E\n","FLOAT32_EPS":"FLOAT32_EPS\n","FLOAT32_EXPONENT_BIAS":"FLOAT32_EXPONENT_BIAS\n","FLOAT32_EXPONENT_MASK":"FLOAT32_EXPONENT_MASK\nbase.toBinaryStringUint32( FLOAT32_EXPONENT_MASK )\n","FLOAT32_FOURTH_PI":"FLOAT32_FOURTH_PI\n","FLOAT32_HALF_LN_TWO":"FLOAT32_HALF_LN_TWO\n","FLOAT32_HALF_PI":"FLOAT32_HALF_PI\n","FLOAT32_LN_HALF":"FLOAT32_LN_HALF\n","FLOAT32_LN_PI":"FLOAT32_LN_PI\n","FLOAT32_LN_TEN":"FLOAT32_LN_TEN\n","FLOAT32_LN_TWO":"FLOAT32_LN_TWO\n","FLOAT32_MAX":"FLOAT32_MAX\n","FLOAT32_MAX_BASE2_EXPONENT":"FLOAT32_MAX_BASE2_EXPONENT\n","FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL":"FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL\n","FLOAT32_MAX_BASE10_EXPONENT":"FLOAT32_MAX_BASE10_EXPONENT\n","FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL":"FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL\n","FLOAT32_MAX_SAFE_FIBONACCI":"FLOAT32_MAX_SAFE_FIBONACCI\n","FLOAT32_MAX_SAFE_INTEGER":"FLOAT32_MAX_SAFE_INTEGER\n","FLOAT32_MAX_SAFE_NTH_FACTORIAL":"FLOAT32_MAX_SAFE_NTH_FACTORIAL\n","FLOAT32_MAX_SAFE_NTH_FIBONACCI":"FLOAT32_MAX_SAFE_NTH_FIBONACCI\n","FLOAT32_MAX_SAFE_NTH_LUCAS":"FLOAT32_MAX_SAFE_NTH_LUCAS\n","FLOAT32_MIN_BASE2_EXPONENT":"FLOAT32_MIN_BASE2_EXPONENT\n","FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL":"FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT32_MIN_BASE10_EXPONENT":"FLOAT32_MIN_BASE10_EXPONENT\n","FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL":"FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT32_MIN_SAFE_INTEGER":"FLOAT32_MIN_SAFE_INTEGER\n","FLOAT32_NAN":"FLOAT32_NAN\n","FLOAT32_NINF":"FLOAT32_NINF\n","FLOAT32_NUM_BYTES":"FLOAT32_NUM_BYTES\n","FLOAT32_PHI":"FLOAT32_PHI\n","FLOAT32_PI":"FLOAT32_PI\n","FLOAT32_PINF":"FLOAT32_PINF\n","FLOAT32_PRECISION":"FLOAT32_PRECISION\n","FLOAT32_SIGN_MASK":"FLOAT32_SIGN_MASK\nbase.toBinaryStringUint32( FLOAT32_SIGN_MASK )\n","FLOAT32_SIGNIFICAND_MASK":"FLOAT32_SIGNIFICAND_MASK\nbase.toBinaryStringUint32( FLOAT32_SIGNIFICAND_MASK )\n","FLOAT32_SMALLEST_NORMAL":"FLOAT32_SMALLEST_NORMAL\n","FLOAT32_SMALLEST_SUBNORMAL":"FLOAT32_SMALLEST_SUBNORMAL\n","FLOAT32_SQRT_EPS":"FLOAT32_SQRT_EPS\n","FLOAT32_SQRT_HALF":"FLOAT32_SQRT_HALF\n","FLOAT32_SQRT_HALF_PI":"FLOAT32_SQRT_HALF_PI\n","FLOAT32_SQRT_PHI":"FLOAT32_SQRT_PHI\n","FLOAT32_SQRT_PI":"FLOAT32_SQRT_PI\n","FLOAT32_SQRT_THREE":"FLOAT32_SQRT_THREE\n","FLOAT32_SQRT_TWO":"FLOAT32_SQRT_TWO\n","FLOAT32_SQRT_TWO_PI":"FLOAT32_SQRT_TWO_PI\n","FLOAT32_TWO_PI":"FLOAT32_TWO_PI\n","Float32Array":"var arr = new Float32Array()\nvar arr = new Float32Array( 5 )\nvar arr1 = new Float64Array( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = new Float32Array( arr1 )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = new Float32Array( arr1 )\nvar buf = new ArrayBuffer( 16 );\nvar arr = new Float32Array( buf, 0, 4 )\n","Float32Array.from":"function mapFcn( v ) { return v * 2.0; };\nvar arr = Float32Array.from( [ 1.0, -1.0 ], mapFcn )\n","Float32Array.of":"var arr = Float32Array.of( 2.0, -2.0 )\n","Float32Array.BYTES_PER_ELEMENT":"Float32Array.BYTES_PER_ELEMENT\n","Float32Array.name":"Float32Array.name\n","Float32Array.prototype.buffer":"var arr = new Float32Array( 5 );\narr.buffer\n","Float32Array.prototype.byteLength":"var arr = new Float32Array( 5 );\narr.byteLength\n","Float32Array.prototype.byteOffset":"var arr = new Float32Array( 5 );\narr.byteOffset\n","Float32Array.prototype.BYTES_PER_ELEMENT":"var arr = new Float32Array( 5 );\narr.BYTES_PER_ELEMENT\n","Float32Array.prototype.length":"var arr = new Float32Array( 5 );\narr.length\n","Float32Array.prototype.copyWithin":"var arr = new Float32Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Float32Array.prototype.entries":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Float32Array.prototype.every":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\narr.every( predicate )\n","Float32Array.prototype.fill":"var arr = new Float32Array( [ 1.0, -1.0 ] );\narr.fill( 2.0 );\narr[ 0 ]\narr[ 1 ]\n","Float32Array.prototype.filter":"var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Float32Array.prototype.find":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar v = arr.find( predicate )\n","Float32Array.prototype.findIndex":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar idx = arr.findIndex( predicate )\n","Float32Array.prototype.forEach":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Float32Array.prototype.includes":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar bool = arr.includes( 2.0 )\nbool = arr.includes( -1.0 )\n","Float32Array.prototype.indexOf":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar idx = arr.indexOf( 2.0 )\nidx = arr.indexOf( -1.0 )\n","Float32Array.prototype.join":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\narr.join( '|' )\n","Float32Array.prototype.keys":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Float32Array.prototype.lastIndexOf":"var arr = new Float32Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\nvar idx = arr.lastIndexOf( 2.0 )\nidx = arr.lastIndexOf( 0.0 )\n","Float32Array.prototype.map":"var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( v ) { return v * 2.0; };\nvar arr2 = arr1.map( fcn )\n","Float32Array.prototype.reduce":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0.0 )\n","Float32Array.prototype.reduceRight":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0.0 )\n","Float32Array.prototype.reverse":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] )\narr.reverse()\n","Float32Array.prototype.set":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\narr.set( [ -2.0, 2.0 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Float32Array.prototype.slice":"var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Float32Array.prototype.some":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\narr.some( predicate )\n","Float32Array.prototype.sort":"var arr = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\narr.sort()\n","Float32Array.prototype.subarray":"var arr1 = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\nvar arr2 = arr1.subarray( 2 )\n","Float32Array.prototype.toLocaleString":"var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\narr.toLocaleString()\n","Float32Array.prototype.toString":"var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\narr.toString()\n","Float32Array.prototype.values":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","FLOAT64_EXPONENT_BIAS":"FLOAT64_EXPONENT_BIAS\n","FLOAT64_HIGH_WORD_ABS_MASK":"FLOAT64_HIGH_WORD_ABS_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_ABS_MASK )\n","FLOAT64_HIGH_WORD_EXPONENT_MASK":"FLOAT64_HIGH_WORD_EXPONENT_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_EXPONENT_MASK )\n","FLOAT64_HIGH_WORD_SIGN_MASK":"FLOAT64_HIGH_WORD_SIGN_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGN_MASK )\n","FLOAT64_HIGH_WORD_SIGNIFICAND_MASK":"FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGNIFICAND_MASK )\n","FLOAT64_MAX":"FLOAT64_MAX\n","FLOAT64_MAX_BASE2_EXPONENT":"FLOAT64_MAX_BASE2_EXPONENT\n","FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL":"FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_BASE10_EXPONENT":"FLOAT64_MAX_BASE10_EXPONENT\n","FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL":"FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_LN":"FLOAT64_MAX_LN\n","FLOAT64_MAX_SAFE_FIBONACCI":"FLOAT64_MAX_SAFE_FIBONACCI\n","FLOAT64_MAX_SAFE_INTEGER":"FLOAT64_MAX_SAFE_INTEGER\n","FLOAT64_MAX_SAFE_LUCAS":"FLOAT64_MAX_SAFE_LUCAS\n","FLOAT64_MAX_SAFE_NTH_FIBONACCI":"FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT64_MAX_SAFE_NTH_LUCAS":"FLOAT64_MAX_SAFE_NTH_LUCAS\n","FLOAT64_MIN_BASE2_EXPONENT":"FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL":"FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_BASE10_EXPONENT":"FLOAT64_MIN_BASE10_EXPONENT\n","FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL":"FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_LN":"FLOAT64_MIN_LN\n","FLOAT64_MIN_SAFE_INTEGER":"FLOAT64_MIN_SAFE_INTEGER\n","FLOAT64_NUM_BYTES":"FLOAT64_NUM_BYTES\n","FLOAT64_PRECISION":"FLOAT64_PRECISION\n","FLOAT64_SMALLEST_NORMAL":"FLOAT64_SMALLEST_NORMAL\n","FLOAT64_SMALLEST_SUBNORMAL":"FLOAT64_SMALLEST_SUBNORMAL\n","Float64Array":"var arr = new Float64Array()\nvar arr = new Float64Array( 5 )\nvar arr1 = new Float32Array( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = new Float64Array( arr1 )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = new Float64Array( arr1 )\nvar buf = new ArrayBuffer( 32 );\nvar arr = new Float64Array( buf, 0, 4 )\n","Float64Array.from":"function mapFcn( v ) { return v * 2.0; };\nvar arr = Float64Array.from( [ 1.0, -1.0 ], mapFcn )\n","Float64Array.of":"var arr = Float64Array.of( 2.0, -2.0 )\n","Float64Array.BYTES_PER_ELEMENT":"Float64Array.BYTES_PER_ELEMENT\n","Float64Array.name":"Float64Array.name\n","Float64Array.prototype.buffer":"var arr = new Float64Array( 5 );\narr.buffer\n","Float64Array.prototype.byteLength":"var arr = new Float64Array( 5 );\narr.byteLength\n","Float64Array.prototype.byteOffset":"var arr = new Float64Array( 5 );\narr.byteOffset\n","Float64Array.prototype.BYTES_PER_ELEMENT":"var arr = new Float64Array( 5 );\narr.BYTES_PER_ELEMENT\n","Float64Array.prototype.length":"var arr = new Float64Array( 5 );\narr.length\n","Float64Array.prototype.copyWithin":"var arr = new Float64Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Float64Array.prototype.entries":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Float64Array.prototype.every":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\narr.every( predicate )\n","Float64Array.prototype.fill":"var arr = new Float64Array( [ 1.0, -1.0 ] );\narr.fill( 2.0 );\narr[ 0 ]\narr[ 1 ]\n","Float64Array.prototype.filter":"var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Float64Array.prototype.find":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar v = arr.find( predicate )\n","Float64Array.prototype.findIndex":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar idx = arr.findIndex( predicate )\n","Float64Array.prototype.forEach":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Float64Array.prototype.includes":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar bool = arr.includes( 2.0 )\nbool = arr.includes( -1.0 )\n","Float64Array.prototype.indexOf":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar idx = arr.indexOf( 2.0 )\nidx = arr.indexOf( -1.0 )\n","Float64Array.prototype.join":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\narr.join( '|' )\n","Float64Array.prototype.keys":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Float64Array.prototype.lastIndexOf":"var arr = new Float64Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\nvar idx = arr.lastIndexOf( 2.0 )\nidx = arr.lastIndexOf( 0.0 )\n","Float64Array.prototype.map":"var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( v ) { return v * 2.0; };\nvar arr2 = arr1.map( fcn )\n","Float64Array.prototype.reduce":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0.0 )\n","Float64Array.prototype.reduceRight":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0.0 )\n","Float64Array.prototype.reverse":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] )\narr.reverse()\n","Float64Array.prototype.set":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\narr.set( [ -2.0, 2.0 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Float64Array.prototype.slice":"var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Float64Array.prototype.some":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\narr.some( predicate )\n","Float64Array.prototype.sort":"var arr = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\narr.sort()\n","Float64Array.prototype.subarray":"var arr1 = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\nvar arr2 = arr1.subarray( 2 )\n","Float64Array.prototype.toLocaleString":"var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\narr.toLocaleString()\n","Float64Array.prototype.toString":"var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\narr.toString()\n","Float64Array.prototype.values":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","forEach":"function logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4 ];\nforEach( arr, logger )\n","forEachAsync":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n     throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 3000, 2500, 1000 ];\nforEachAsync( arr, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n     throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nforEachAsync( arr, opts, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n     throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nforEachAsync( arr, opts, onDuration, done )\n","forEachAsync.factory":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next();\n }\n };\nvar opts = { 'series': true };\nvar f = forEachAsync.factory( opts, onDuration );\nfunction done( error ) {\n if ( error ) {\n     throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","forEachChar":"var n = 0;\nfunction fcn() { n += 1; };\nforEachChar( 'hello world!', fcn );\nn\n","forEachRight":"function logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4 ];\nforEachRight( arr, logger )\n","forEachRightAsync":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n     throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 1000, 2500, 3000 ];\nforEachRightAsync( arr, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n     throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nforEachRightAsync( arr, opts, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n     throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nforEachRightAsync( arr, opts, onDuration, done )\n","forEachRightAsync.factory":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next();\n }\n };\nvar opts = { 'series': true };\nvar f = forEachRightAsync.factory( opts, onDuration );\nfunction done( error ) {\n if ( error ) {\n     throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","forIn":"function logger( v, k ) { console.log( '%s: %d', k, v ); };\nfunction Foo() { return this; };\nFoo.prototype.beep = 'boop';\nvar obj = new Foo();\nforIn( obj, logger )\n","format":"var out = format( 'Hello, %s!', 'World' )\nout = format( '%s %s', 'Hello', 'World' )\nout = format( 'Pi: %.2f', PI )\n","forOwn":"function logger( v, k ) { console.log( '%s: %d', k, v ); };\nvar obj = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\nforOwn( obj, logger )\n","FOURTH_PI":"FOURTH_PI\n","FOURTH_ROOT_EPS":"FOURTH_ROOT_EPS\n","FRB_SF_WAGE_RIGIDITY":"var data = FRB_SF_WAGE_RIGIDITY()\n","fromCodePoint":"var out = fromCodePoint( 9731 )\nout = fromCodePoint( [ 9731 ] )\nout = fromCodePoint( 97, 98, 99 )\nout = fromCodePoint( [ 97, 98, 99 ] )\n","Function":"var f = new Function( 'x', 'y', 'return x + y' );\nf( 1, 2 )\n","Function.prototype.apply":"var f = new Function( 'x', 'y', 'return x + y' );\nf.apply( null, [ 1, 2 ] )\n","Function.prototype.call":"var f = new Function( 'x', 'y', 'return x + y' );\nf.call( null, 1, 2 )\n","Function.prototype.bind":"var f = new Function( 'x', 'y', 'return x + y' );\nvar g = f.bind( null, 1 );\ng( 2 )\n","Function.prototype.toString":"var f = new Function( 'x', 'y', 'return x + y' );\nf.toString()\n","Function.prototype.length":"var f = new Function( 'x', 'y', 'return x + y' );\nf.length\n","Function.prototype.name":"var f = new Function( 'x', 'y', 'return x + y' );\nf.name\nvar f = new Function( 'x', 'y', 'return x + y' );\nf.name = 'add';\nf.name\n","Function.prototype.prototype":"var f = new Function( 'x', 'y', 'return x + y' );\nf.prototype\n","function2string":"function2string( base.erf )\n","functionName":"var v = functionName( String )\nv = functionName( function foo(){} )\nv = functionName( function(){} )\n","functionSequence":"function a( x ) { return 2 * x; };\nfunction b( x ) { return x + 3; };\nfunction c( x ) { return x / 5; };\nvar f = functionSequence( a, b, c );\nvar z = f( 6 )\n","functionSequenceAsync":"function a( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n    next( null, 2*x );\n}\n };\nfunction b( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n    next( null, x+3 );\n}\n };\nfunction c( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n    next( null, x/5 );\n}\n };\nvar f = functionSequenceAsync( a, b, c );\nfunction done( error, result ) {\nif ( error ) {\n    throw error;\n}\nconsole.log( result );\n };\nf( 6, done )\n","GAMMA_LANCZOS_G":"GAMMA_LANCZOS_G\n","gdot":"var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\ngdot( x, y )\nx = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\ny = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\ngdot( x, y )\n","getegid":"var gid = getegid()\n","geteuid":"var uid = geteuid()\n","getgid":"var gid = getgid()\n","getGlobal":"var g = getGlobal()\n","getPrototypeOf":"var proto = getPrototypeOf( {} )\n","getuid":"var uid = getuid()\n","GLAISHER":"GLAISHER\n","graphemeClusters2iterator":"var it = graphemeClusters2iterator( '🌷🍕' );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","graphemeClusters2iteratorRight":"var it = graphemeClusters2iteratorRight( '🌷🍕' );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","group":"var collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar groups = [ 'b', 'b', 'f', 'b' ];\nvar out = group( collection, groups )\ngroups = [ 1, 1, 2, 1 ];\nout = group( collection, groups )\ngroups = [ 'b', 'b', 'f', 'b' ];\nvar opts = { 'returns': 'indices' };\nout = group( collection, opts, groups )\nopts = { 'returns': '*' };\nout = group( collection, opts, groups )\n","groupBy":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n     return 'b';\n }\n return 'other';\n };\nvar collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar out = groupBy( collection, indicator )\nvar opts = { 'returns': 'indices' };\nout = groupBy( collection, opts, indicator )\nopts = { 'returns': '*' };\nout = groupBy( collection, opts, indicator )\n","groupByAsync":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\ngroupByAsync( arr, indicator, done )\nvar opts = { 'returns': 'indices' };\ngroupByAsync( arr, opts, indicator, done )\nopts = { 'returns': '*' };\ngroupByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\ngroupByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\ngroupByAsync( arr, opts, indicator, done )\n","groupByAsync.factory":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) );\n }\n };\nvar opts = { 'series': true };\nvar f = groupByAsync.factory( opts, indicator );\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","groupIn":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n     return 'b';\n }\n return 'other';\n };\nfunction Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\nFoo.prototype = Object.create( null );\nFoo.prototype.c = 'foo';\nFoo.prototype.d = 'bar';\nvar obj = new Foo();\nvar out = groupIn( obj, indicator )\nvar opts = { 'returns': 'keys' };\nout = groupIn( obj, opts, indicator )\nopts = { 'returns': '*' };\nout = groupIn( obj, opts, indicator )\n","groupOwn":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n     return 'b';\n }\n return 'other';\n };\nvar obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\nvar out = groupOwn( obj, indicator )\nvar opts = { 'returns': 'keys' };\nout = groupOwn( obj, opts, indicator )\nopts = { 'returns': '*' };\nout = groupOwn( obj, opts, indicator )\n","gswap":"var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\ngswap( x, y );\nx.data\ny.data\nx = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\ny = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\ngswap( x, y );\nx\ny\n","HALF_LN2":"HALF_LN2\n","HALF_PI":"HALF_PI\n","HARRISON_BOSTON_HOUSE_PRICES":"var data = HARRISON_BOSTON_HOUSE_PRICES()\n","HARRISON_BOSTON_HOUSE_PRICES_CORRECTED":"var data = HARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n","hasArrayBufferSupport":"var bool = hasArrayBufferSupport()\n","hasArrowFunctionSupport":"var bool = hasArrowFunctionSupport()\n","hasAsyncAwaitSupport":"var bool = hasAsyncAwaitSupport()\n","hasAsyncIteratorSymbolSupport":"var bool = hasAsyncIteratorSymbolSupport()\n","hasAtobSupport":"var bool = hasAtobSupport()\n","hasBigInt64ArraySupport":"var bool = hasBigInt64ArraySupport()\n","hasBigIntSupport":"var bool = hasBigIntSupport()\n","hasBigUint64ArraySupport":"var bool = hasBigUint64ArraySupport()\n","hasBtoaSupport":"var bool = hasBtoaSupport()\n","hasClassSupport":"var bool = hasClassSupport()\n","hasDataViewSupport":"var bool = hasDataViewSupport()\n","hasDefinePropertiesSupport":"var bool = hasDefinePropertiesSupport()\n","hasDefinePropertySupport":"var bool = hasDefinePropertySupport()\n","hasFloat32ArraySupport":"var bool = hasFloat32ArraySupport()\n","hasFloat64ArraySupport":"var bool = hasFloat64ArraySupport()\n","hasFunctionNameSupport":"var bool = hasFunctionNameSupport()\n","hasGeneratorSupport":"var bool = hasGeneratorSupport()\n","hasGlobalThisSupport":"var bool = hasGlobalThisSupport()\n","hasInt8ArraySupport":"var bool = hasInt8ArraySupport()\n","hasInt16ArraySupport":"var bool = hasInt16ArraySupport()\n","hasInt32ArraySupport":"var bool = hasInt32ArraySupport()\n","hasIteratorSymbolSupport":"var bool = hasIteratorSymbolSupport()\n","hasMapSupport":"var bool = hasMapSupport()\n","hasNodeBufferSupport":"var bool = hasNodeBufferSupport()\n","hasOwnProp":"var beep = { 'boop': true };\nvar bool = hasOwnProp( beep, 'boop' )\nbool = hasOwnProp( beep, 'bop' )\n","hasProp":"var beep = { 'boop': true };\nvar bool = hasProp( beep, 'boop' )\nbool = hasProp( beep, 'toString' )\nbool = hasProp( beep, 'bop' )\n","hasProxySupport":"var bool = hasProxySupport()\n","hasSetSupport":"var bool = hasSetSupport()\n","hasSharedArrayBufferSupport":"var bool = hasSharedArrayBufferSupport()\n","hasSymbolSupport":"var bool = hasSymbolSupport()\n","hasToStringTagSupport":"var bool = hasToStringTagSupport()\n","hasUint8ArraySupport":"var bool = hasUint8ArraySupport()\n","hasUint8ClampedArraySupport":"var bool = hasUint8ClampedArraySupport()\n","hasUint16ArraySupport":"var bool = hasUint16ArraySupport()\n","hasUint32ArraySupport":"var bool = hasUint32ArraySupport()\n","hasUTF16SurrogatePairAt":"var out = hasUTF16SurrogatePairAt( '🌷', 0 )\nout = hasUTF16SurrogatePairAt( '🌷', 1 )\n","hasWeakMapSupport":"var bool = hasWeakMapSupport()\n","hasWeakSetSupport":"var bool = hasWeakSetSupport()\n","hasWebAssemblySupport":"var bool = hasWebAssemblySupport()\n","headercase":"var out = headercase( 'Hello World!' )\nout = headercase( 'beep boop' )\n","HERNDON_VENUS_SEMIDIAMETERS":"var d = HERNDON_VENUS_SEMIDIAMETERS()\n","homedir":"var home = homedir()\n","HOURS_IN_DAY":"var days = 3.14;\nvar hrs = days * HOURS_IN_DAY\n","HOURS_IN_WEEK":"var wks = 3.14;\nvar hrs = wks * HOURS_IN_WEEK\n","hoursInMonth":"var num = hoursInMonth()\nnum = hoursInMonth( 2 )\nnum = hoursInMonth( 2, 2016 )\nnum = hoursInMonth( 2, 2017 )\nnum = hoursInMonth( 'feb', 2016 )\nnum = hoursInMonth( 'february', 2016 )\n","hoursInYear":"var num = hoursInYear()\nnum = hoursInYear( 2016 )\nnum = hoursInYear( 2017 )\n","httpServer":"var createServer = httpServer()\nfunction onRequest( request, response ) {\nconsole.log( request.url );\nresponse.end( 'OK' );\n };\ncreateServer = httpServer( onRequest )\nvar opts = { 'port': 7331 };\ncreateServer = httpServer( opts )\n","identity":"var v = identity( 3.14 )\n","ifelse":"var z = ifelse( true, 1.0, -1.0 )\nz = ifelse( false, 1.0, -1.0 )\n","ifelseAsync":"function predicate( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n     clbk( null, true );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nifelseAsync( predicate, 'beep', 'boop', done )\n","ifthen":"function x() { return 1.0; };\nfunction y() { return -1.0; };\nvar z = ifthen( true, x, y )\nz = ifthen( false, x, y )\n","ifthenAsync":"function predicate( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n     clbk( null, false );\n }\n };\nfunction x( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n     clbk( null, 'beep' );\n }\n };\nfunction y( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n     clbk( null, 'boop' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nifthenAsync( predicate, x, y, done )\n","imag":"var z = new Complex128( 5.0, 3.0 );\nvar im = imag( z )\n","imagf":"var z = new Complex64( 5.0, 3.0 );\nvar im = imagf( z )\n","IMG_ACANTHUS_MOLLIS":"var img = IMG_ACANTHUS_MOLLIS()\n","IMG_AIRPLANE_FROM_ABOVE":"var img = IMG_AIRPLANE_FROM_ABOVE()\n","IMG_ALLIUM_OREOPHILUM":"var img = IMG_ALLIUM_OREOPHILUM()\n","IMG_BLACK_CANYON":"var img = IMG_BLACK_CANYON()\n","IMG_DUST_BOWL_HOME":"var img = IMG_DUST_BOWL_HOME()\n","IMG_FRENCH_ALPINE_LANDSCAPE":"var img = IMG_FRENCH_ALPINE_LANDSCAPE()\n","IMG_LOCOMOTION_HOUSE_CAT":"var img = IMG_LOCOMOTION_HOUSE_CAT()\n","IMG_LOCOMOTION_NUDE_MALE":"var img = IMG_LOCOMOTION_NUDE_MALE()\n","IMG_MARCH_PASTORAL":"var img = IMG_MARCH_PASTORAL()\n","IMG_NAGASAKI_BOATS":"var img = IMG_NAGASAKI_BOATS()\n","incrapcorr":"var accumulator = incrapcorr();\nvar ar = accumulator()\nar = accumulator( 2.0, 1.0 )\nar = accumulator( -5.0, 3.14 )\nar = accumulator()\n","incrBinaryClassification":"var opts = {};\nopts.intercept = true;\nopts.lambda = 1.0e-5;\nvar acc = incrBinaryClassification( 3, opts );\nvar buf = new Float64Array( [ 2.3, 1.0, 5.0 ] );\nvar x = array( buf );\nvar coefs = acc( x, 1 )\nbuf = new Float64Array( [ 2.3, 5.3, 8.6 ] );\nx = array( buf );\nvar yhat = acc.predict( x )\n","incrcount":"var accumulator = incrcount();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrcovariance":"var accumulator = incrcovariance();\nvar v = accumulator()\nv = accumulator( 2.0, 1.0 )\nv = accumulator( -5.0, 3.14 )\nv = accumulator()\n","incrcovmat":"var accumulator = incrcovmat( 2 );\nvar out = accumulator()\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v )\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v )\nout = accumulator()\n","incrcv":"var accumulator = incrcv();\nvar cv = accumulator()\ncv = accumulator( 2.0 )\ncv = accumulator( 1.0 )\ncv = accumulator()\n","increwmean":"var accumulator = increwmean( 0.5 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","increwstdev":"var accumulator = increwstdev( 0.5 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","increwvariance":"var accumulator = increwvariance( 0.5 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrgmean":"var accumulator = incrgmean();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrgrubbs":"var acc = incrgrubbs();\nvar res = acc()\nfor ( var i = 0; i < 200; i++ ) {\n res = acc( base.random.normal( 10.0, 5.0 ) );\n };\nres.print()\n","incrhmean":"var accumulator = incrhmean();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrkmeans":"var accumulator = incrkmeans( 5, 2 );\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v );\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v );\n","incrkurtosis":"var accumulator = incrkurtosis();\nvar v = accumulator( 2.0 )\nv = accumulator( 2.0 )\nv = accumulator( -4.0 )\nv = accumulator( -4.0 )\n","incrmaape":"var accumulator = incrmaape();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator()\n","incrmae":"var accumulator = incrmae();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator()\n","incrmapcorr":"var accumulator = incrmapcorr( 3 );\nvar ar = accumulator()\nar = accumulator( 2.0, 1.0 )\nar = accumulator( -5.0, 3.14 )\nar = accumulator( 3.0, -1.0 )\nar = accumulator( 5.0, -9.5 )\nar = accumulator()\n","incrmape":"var accumulator = incrmape();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator()\n","incrmax":"var accumulator = incrmax();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrmaxabs":"var accumulator = incrmaxabs();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrmcovariance":"var accumulator = incrmcovariance( 3 );\nvar v = accumulator()\nv = accumulator( 2.0, 1.0 )\nv = accumulator( -5.0, 3.14 )\nv = accumulator( 3.0, -1.0 )\nv = accumulator( 5.0, -9.5 )\nv = accumulator()\n","incrmcv":"var accumulator = incrmcv( 3 );\nvar cv = accumulator()\ncv = accumulator( 2.0 )\ncv = accumulator( 1.0 )\ncv = accumulator( 3.0 )\ncv = accumulator( 7.0 )\ncv = accumulator()\n","incrmda":"var accumulator = incrmda();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 4.0 )\nm = accumulator()\n","incrme":"var accumulator = incrme();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator()\n","incrmean":"var accumulator = incrmean();\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator()\n","incrmeanabs":"var accumulator = incrmeanabs();\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator()\n","incrmeanabs2":"var accumulator = incrmeanabs2();\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator()\n","incrmeanstdev":"var accumulator = incrmeanstdev();\nvar ms = accumulator()\nms = accumulator( 2.0 )\nms = accumulator( -5.0 )\nms = accumulator( 3.0 )\nms = accumulator( 5.0 )\nms = accumulator()\n","incrmeanvar":"var accumulator = incrmeanvar();\nvar mv = accumulator()\nmv = accumulator( 2.0 )\nmv = accumulator( -5.0 )\nmv = accumulator( 3.0 )\nmv = accumulator( 5.0 )\nmv = accumulator()\n","incrmgmean":"var accumulator = incrmgmean( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmgrubbs":"var acc = incrmgrubbs( 20 );\nvar res = acc()\nfor ( var i = 0; i < 200; i++ ) {\n res = acc( base.random.normal( 10.0, 5.0 ) );\n };\nres.print()\n","incrmhmean":"var accumulator = incrmhmean( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmidrange":"var accumulator = incrmidrange();\nvar v = accumulator()\nv = accumulator( 3.14 )\nv = accumulator( -5.0 )\nv = accumulator( 10.1 )\nv = accumulator()\n","incrmin":"var accumulator = incrmin();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrminabs":"var accumulator = incrminabs();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrminmax":"var accumulator = incrminmax();\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrminmaxabs":"var accumulator = incrminmaxabs();\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrmmaape":"var accumulator = incrmmaape( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 2.0, 5.0 )\nm = accumulator()\n","incrmmae":"var accumulator = incrmmae( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 5.0, -2.0 )\nm = accumulator()\n","incrmmape":"var accumulator = incrmmape( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 2.0, 5.0 )\nm = accumulator()\n","incrmmax":"var accumulator = incrmmax( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmmaxabs":"var accumulator = incrmmaxabs( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmmda":"var accumulator = incrmmda( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 4.0, 5.0 )\nm = accumulator()\n","incrmme":"var accumulator = incrmme( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 5.0, -2.0 )\nm = accumulator()\n","incrmmean":"var accumulator = incrmmean( 3 );\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator( 3.0 )\nmu = accumulator( 5.0 )\nmu = accumulator()\n","incrmmeanabs":"var accumulator = incrmmeanabs( 3 );\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator( 3.0 )\nmu = accumulator( 5.0 )\nmu = accumulator()\n","incrmmeanabs2":"var accumulator = incrmmeanabs2( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmmeanstdev":"var accumulator = incrmmeanstdev( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmmeanvar":"var accumulator = incrmmeanvar( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmmidrange":"var accumulator = incrmmidrange( 3 );\nvar mr = accumulator()\nmr = accumulator( 2.0 )\nmr = accumulator( -5.0 )\nmr = accumulator( 3.0 )\nmr = accumulator( 5.0 )\nmr = accumulator()\n","incrmmin":"var accumulator = incrmmin( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmminabs":"var accumulator = incrmminabs( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmminmax":"var accumulator = incrmminmax( 3 );\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrmminmaxabs":"var accumulator = incrmminmaxabs( 3 );\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrmmpe":"var accumulator = incrmmpe( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 2.0, 5.0 )\nm = accumulator()\n","incrmmse":"var accumulator = incrmmse( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 5.0, -2.0 )\nm = accumulator()\n","incrmpcorr":"var accumulator = incrmpcorr( 3 );\nvar r = accumulator()\nr = accumulator( 2.0, 1.0 )\nr = accumulator( -5.0, 3.14 )\nr = accumulator( 3.0, -1.0 )\nr = accumulator( 5.0, -9.5 )\nr = accumulator()\n","incrmpcorr2":"var accumulator = incrmpcorr2( 3 );\nvar r2 = accumulator()\nr2 = accumulator( 2.0, 1.0 )\nr2 = accumulator( -5.0, 3.14 )\nr2 = accumulator( 3.0, -1.0 )\nr2 = accumulator( 5.0, -9.5 )\nr2 = accumulator()\n","incrmpcorrdist":"var accumulator = incrmpcorrdist( 3 );\nvar d = accumulator()\nd = accumulator( 2.0, 1.0 )\nd = accumulator( -5.0, 3.14 )\nd = accumulator( 3.0, -1.0 )\nd = accumulator( 5.0, -9.5 )\nd = accumulator()\n","incrmpe":"var accumulator = incrmpe();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator()\n","incrmprod":"var accumulator = incrmprod( 3 );\nvar p = accumulator()\np = accumulator( 2.0 )\np = accumulator( -5.0 )\np = accumulator( 3.0 )\np = accumulator( 5.0 )\np = accumulator()\n","incrmrange":"var accumulator = incrmrange( 3 );\nvar r = accumulator()\nr = accumulator( 2.0 )\nr = accumulator( -5.0 )\nr = accumulator( 3.0 )\nr = accumulator( 5.0 )\nr = accumulator()\n","incrmrmse":"var accumulator = incrmrmse( 3 );\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator( 3.0, 2.0 )\nr = accumulator( 5.0, -2.0 )\nr = accumulator()\n","incrmrss":"var accumulator = incrmrss( 3 );\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator( 3.0, 2.0 )\nr = accumulator( 5.0, -2.0 )\nr = accumulator()\n","incrmse":"var accumulator = incrmse();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator()\n","incrmstdev":"var accumulator = incrmstdev( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( 5.0 )\ns = accumulator()\n","incrmsum":"var accumulator = incrmsum( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( 5.0 )\ns = accumulator()\n","incrmsumabs":"var accumulator = incrmsumabs( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrmsumabs2":"var accumulator = incrmsumabs2( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrmsummary":"var accumulator = incrmsummary( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrmsumprod":"var accumulator = incrmsumprod( 3 );\nvar s = accumulator()\ns = accumulator( 2.0, 3.0 )\ns = accumulator( -5.0, 2.0 )\ns = accumulator( 3.0, -2.0 )\ns = accumulator( 5.0, 3.0 )\ns = accumulator()\n","incrmvariance":"var accumulator = incrmvariance( 3 );\nvar s2 = accumulator()\ns2 = accumulator( 2.0 )\ns2 = accumulator( -5.0 )\ns2 = accumulator( 3.0 )\ns2 = accumulator( 5.0 )\ns2 = accumulator()\n","incrmvmr":"var accumulator = incrmvmr( 3 );\nvar F = accumulator()\nF = accumulator( 2.0 )\nF = accumulator( 1.0 )\nF = accumulator( 3.0 )\nF = accumulator( 7.0 )\nF = accumulator()\n","incrnancount":"var accumulator = incrnancount();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrnansum":"var accumulator = incrnansum();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( NaN )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrnansumabs":"var accumulator = incrnansumabs();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( NaN )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrnansumabs2":"var accumulator = incrnansumabs2();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( NaN )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrpcorr":"var accumulator = incrpcorr();\nvar r = accumulator()\nr = accumulator( 2.0, 1.0 )\nr = accumulator( -5.0, 3.14 )\nr = accumulator()\n","incrpcorr2":"var accumulator = incrpcorr2();\nvar r2 = accumulator()\nr2 = accumulator( 2.0, 1.0 )\nr2 = accumulator( -5.0, 3.14 )\nr2 = accumulator()\n","incrpcorrdist":"var accumulator = incrpcorrdist();\nvar d = accumulator()\nd = accumulator( 2.0, 1.0 )\nd = accumulator( -5.0, 3.14 )\nd = accumulator()\n","incrpcorrdistmat":"var accumulator = incrpcorrdistmat( 2 );\nvar out = accumulator()\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v )\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v )\nout = accumulator()\n","incrpcorrmat":"var accumulator = incrpcorrmat( 2 );\nvar out = accumulator()\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v )\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v )\nout = accumulator()\n","incrprod":"var accumulator = incrprod();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrrange":"var accumulator = incrrange();\nvar v = accumulator()\nv = accumulator( -2.0 )\nv = accumulator( 1.0 )\nv = accumulator( 3.0 )\nv = accumulator()\n","incrrmse":"var accumulator = incrrmse();\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator()\n","incrrss":"var accumulator = incrrss();\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator()\n","incrskewness":"var accumulator = incrskewness();\nvar v = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator( -10.0 )\nv = accumulator()\n","incrspace":"var arr = incrspace( 0, 11, 2 )\n","incrstdev":"var accumulator = incrstdev();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsum":"var accumulator = incrsum();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsumabs":"var accumulator = incrsumabs();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsumabs2":"var accumulator = incrsumabs2();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsummary":"var accumulator = incrsummary();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsumprod":"var accumulator = incrsumprod();\nvar s = accumulator()\ns = accumulator( 2.0, 3.0 )\ns = accumulator( -5.0, 2.0 )\ns = accumulator()\n","incrvariance":"var accumulator = incrvariance();\nvar s2 = accumulator()\ns2 = accumulator( 2.0 )\ns2 = accumulator( -5.0 )\ns2 = accumulator()\n","incrvmr":"var accumulator = incrvmr();\nvar D = accumulator()\nD = accumulator( 2.0 )\nD = accumulator( 1.0 )\nD = accumulator()\n","incrwmean":"var accumulator = incrwmean();\nvar mu = accumulator()\nmu = accumulator( 2.0, 1.0 )\nmu = accumulator( 2.0, 0.5 )\nmu = accumulator( 3.0, 1.5 )\nmu = accumulator()\n","ind2sub":"var d = [ 3, 3, 3 ];\nvar s = ind2sub( d, 17 )\n","ind2sub.assign":"var d = [ 3, 3, 3 ];\nvar out = [ 0, 0, 0 ];\nvar s = ind2sub.assign( d, 17, out )\nvar bool = ( s === out )\n","indexOf":"var arr = [ 4, 3, 2, 1 ];\nvar idx = indexOf( arr, 3 )\narr = [ 4, 3, 2, 1 ];\nidx = indexOf( arr, 5 )\narr = [ 1, 2, 3, 4, 5, 2, 6 ];\nidx = indexOf( arr, 2, 3 )\narr = [ 1, 2, 3, 4, 2, 5 ];\nidx = indexOf( arr, 2, 10 )\narr = [ 1, 2, 3, 4, 5, 2, 6, 2 ];\nidx = indexOf( arr, 2, -4 )\nidx = indexOf( arr, 2, -1 )\narr = [ 1, 2, 3, 4, 5, 2, 6 ];\nidx = indexOf( arr, 2, -10 )\nvar str = 'bebop';\nidx = indexOf( str, 'o' )\n","inherit":"function Foo() { return this; };\nFoo.prototype.beep = function beep() { return 'boop'; };\nfunction Bar() { Foo.call( this ); return this; };\ninherit( Bar, Foo );\nvar bar = new Bar();\nvar v = bar.beep()\n","inheritedEnumerableProperties":"var props = inheritedEnumerableProperties( {} )\n","inheritedEnumerablePropertySymbols":"var symbols = inheritedEnumerablePropertySymbols( [] )\n","inheritedKeys":"var keys = inheritedKeys( {} )\n","inheritedNonEnumerableProperties":"var props = inheritedNonEnumerableProperties( {} )\n","inheritedNonEnumerablePropertyNames":"var keys = inheritedNonEnumerablePropertyNames( {} )\n","inheritedNonEnumerablePropertySymbols":"var symbols = inheritedNonEnumerablePropertySymbols( [] )\n","inheritedProperties":"var symbols = inheritedProperties( [] )\n","inheritedPropertyDescriptor":"var desc = inheritedPropertyDescriptor( {}, 'toString' )\n","inheritedPropertyDescriptors":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar desc = inheritedPropertyDescriptors( obj )\n","inheritedPropertyNames":"var keys = inheritedPropertyNames( [] )\n","inheritedPropertySymbols":"var symbols = inheritedPropertySymbols( [] )\n","inheritedWritableProperties":"var props = inheritedWritableProperties( {} )\n","inheritedWritablePropertyNames":"var keys = inheritedWritablePropertyNames( {} )\n","inheritedWritablePropertySymbols":"var symbols = inheritedWritablePropertySymbols( [] )\n","inmap":"function foo( v, i ) { return v * i; };\nvar arr = [ 1.0, 2.0, 3.0 ];\nvar out = inmap( arr, foo )\nvar bool = ( out === arr )\n","inmapAsync":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n     throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 3000, 2500, 1000 ];\ninmapAsync( arr, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n     throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\ninmapAsync( arr, opts, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n     throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\ninmapAsync( arr, opts, fcn, done )\n","inmapAsync.factory":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, value*index );\n }\n };\nvar opts = { 'series': true };\nvar f = inmapAsync.factory( opts, fcn );\nfunction done( error, collection ) {\n if ( error ) {\n     throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","inmapRight":"function foo( v, i ) { console.log( '%s: %d', i, v ); return v * i; };\nvar arr = [ 1.0, 2.0, 3.0 ];\nvar out = inmapRight( arr, foo )\nvar bool = ( out === arr )\n","inmapRightAsync":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n     throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 1000, 2500, 3000 ];\ninmapRightAsync( arr, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n     throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\ninmapRightAsync( arr, opts, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n     throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\ninmapRightAsync( arr, opts, fcn, done )\n","inmapRightAsync.factory":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, value*index );\n }\n };\nvar opts = { 'series': true };\nvar f = inmapRightAsync.factory( opts, fcn );\nfunction done( error, collection ) {\n if ( error ) {\n     throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","inspectSinkStream":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectSinkStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectSinkStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = inspectSinkStream.factory( opts );\nfunction clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = createStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectSinkStream.objectMode":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectSinkStream.objectMode( clbk );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","inspectStream":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = inspectStream.factory( opts );\nfunction clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = createStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectStream.objectMode":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectStream.objectMode( clbk );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","instanceOf":"var bool = instanceOf( [], Array )\nbool = instanceOf( {}, Object )\nbool = instanceOf( null, Object )\n","INT8_MAX":"INT8_MAX\n","INT8_MIN":"INT8_MIN\n","INT8_NUM_BYTES":"INT8_NUM_BYTES\n","Int8Array":"var arr = new Int8Array()\nvar arr = new Int8Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Int8Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Int8Array( arr1 )\nvar buf = new ArrayBuffer( 4 );\nvar arr = new Int8Array( buf, 0, 4 )\n","Int8Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Int8Array.from( [ 1, 2 ], mapFcn )\n","Int8Array.of":"var arr = Int8Array.of( 1, 2 )\n","Int8Array.BYTES_PER_ELEMENT":"Int8Array.BYTES_PER_ELEMENT\n","Int8Array.name":"Int8Array.name\n","Int8Array.prototype.buffer":"var arr = new Int8Array( 5 );\narr.buffer\n","Int8Array.prototype.byteLength":"var arr = new Int8Array( 5 );\narr.byteLength\n","Int8Array.prototype.byteOffset":"var arr = new Int8Array( 5 );\narr.byteOffset\n","Int8Array.prototype.BYTES_PER_ELEMENT":"var arr = new Int8Array( 5 );\narr.BYTES_PER_ELEMENT\n","Int8Array.prototype.length":"var arr = new Int8Array( 5 );\narr.length\n","Int8Array.prototype.copyWithin":"var arr = new Int8Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Int8Array.prototype.entries":"var arr = new Int8Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Int8Array.prototype.every":"var arr = new Int8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Int8Array.prototype.fill":"var arr = new Int8Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Int8Array.prototype.filter":"var arr1 = new Int8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Int8Array.prototype.find":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Int8Array.prototype.findIndex":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Int8Array.prototype.forEach":"var arr = new Int8Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Int8Array.prototype.includes":"var arr = new Int8Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Int8Array.prototype.indexOf":"var arr = new Int8Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Int8Array.prototype.join":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Int8Array.prototype.keys":"var arr = new Int8Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Int8Array.prototype.lastIndexOf":"var arr = new Int8Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Int8Array.prototype.map":"var arr1 = new Int8Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Int8Array.prototype.reduce":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Int8Array.prototype.reduceRight":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Int8Array.prototype.reverse":"var arr = new Int8Array( [ 1, 2, 3 ] )\narr.reverse()\n","Int8Array.prototype.set":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Int8Array.prototype.slice":"var arr1 = new Int8Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Int8Array.prototype.some":"var arr = new Int8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Int8Array.prototype.sort":"var arr = new Int8Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Int8Array.prototype.subarray":"var arr1 = new Int8Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Int8Array.prototype.toLocaleString":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Int8Array.prototype.toString":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.toString()\n","Int8Array.prototype.values":"var arr = new Int8Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","INT16_MAX":"INT16_MAX\n","INT16_MIN":"INT16_MIN\n","INT16_NUM_BYTES":"INT16_NUM_BYTES\n","Int16Array":"var arr = new Int16Array()\nvar arr = new Int16Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Int16Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Int16Array( arr1 )\nvar buf = new ArrayBuffer( 8 );\nvar arr = new Int16Array( buf, 0, 4 )\n","Int16Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Int16Array.from( [ 1, 2 ], mapFcn )\n","Int16Array.of":"var arr = Int16Array.of( 1, 2 )\n","Int16Array.BYTES_PER_ELEMENT":"Int16Array.BYTES_PER_ELEMENT\n","Int16Array.name":"Int16Array.name\n","Int16Array.prototype.buffer":"var arr = new Int16Array( 5 );\narr.buffer\n","Int16Array.prototype.byteLength":"var arr = new Int16Array( 5 );\narr.byteLength\n","Int16Array.prototype.byteOffset":"var arr = new Int16Array( 5 );\narr.byteOffset\n","Int16Array.prototype.BYTES_PER_ELEMENT":"var arr = new Int16Array( 5 );\narr.BYTES_PER_ELEMENT\n","Int16Array.prototype.length":"var arr = new Int16Array( 5 );\narr.length\n","Int16Array.prototype.copyWithin":"var arr = new Int16Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Int16Array.prototype.entries":"var arr = new Int16Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Int16Array.prototype.every":"var arr = new Int16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Int16Array.prototype.fill":"var arr = new Int16Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Int16Array.prototype.filter":"var arr1 = new Int16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Int16Array.prototype.find":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Int16Array.prototype.findIndex":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Int16Array.prototype.forEach":"var arr = new Int16Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Int16Array.prototype.includes":"var arr = new Int16Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Int16Array.prototype.indexOf":"var arr = new Int16Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Int16Array.prototype.join":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Int16Array.prototype.keys":"var arr = new Int16Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Int16Array.prototype.lastIndexOf":"var arr = new Int16Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Int16Array.prototype.map":"var arr1 = new Int16Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Int16Array.prototype.reduce":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Int16Array.prototype.reduceRight":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Int16Array.prototype.reverse":"var arr = new Int16Array( [ 1, 2, 3 ] )\narr.reverse()\n","Int16Array.prototype.set":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Int16Array.prototype.slice":"var arr1 = new Int16Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Int16Array.prototype.some":"var arr = new Int16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Int16Array.prototype.sort":"var arr = new Int16Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Int16Array.prototype.subarray":"var arr1 = new Int16Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Int16Array.prototype.toLocaleString":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Int16Array.prototype.toString":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.toString()\n","Int16Array.prototype.values":"var arr = new Int16Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","INT32_MAX":"INT32_MAX\n","INT32_MIN":"INT32_MIN\n","INT32_NUM_BYTES":"INT32_NUM_BYTES\n","Int32Array":"var arr = new Int32Array()\nvar arr = new Int32Array( 5 )\nvar arr1 = new Int16Array( [ 5, 5, 5 ] );\nvar arr2 = new Int32Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Int32Array( arr1 )\nvar buf = new ArrayBuffer( 16 );\nvar arr = new Int32Array( buf, 0, 4 )\n","Int32Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Int32Array.from( [ 1, 2 ], mapFcn )\n","Int32Array.of":"var arr = Int32Array.of( 1, 2 )\n","Int32Array.BYTES_PER_ELEMENT":"Int32Array.BYTES_PER_ELEMENT\n","Int32Array.name":"Int32Array.name\n","Int32Array.prototype.buffer":"var arr = new Int32Array( 5 );\narr.buffer\n","Int32Array.prototype.byteLength":"var arr = new Int32Array( 5 );\narr.byteLength\n","Int32Array.prototype.byteOffset":"var arr = new Int32Array( 5 );\narr.byteOffset\n","Int32Array.prototype.BYTES_PER_ELEMENT":"var arr = new Int32Array( 5 );\narr.BYTES_PER_ELEMENT\n","Int32Array.prototype.length":"var arr = new Int32Array( 5 );\narr.length\n","Int32Array.prototype.copyWithin":"var arr = new Int32Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Int32Array.prototype.entries":"var arr = new Int32Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Int32Array.prototype.every":"var arr = new Int32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Int32Array.prototype.fill":"var arr = new Int32Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Int32Array.prototype.filter":"var arr1 = new Int32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Int32Array.prototype.find":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Int32Array.prototype.findIndex":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Int32Array.prototype.forEach":"var arr = new Int32Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Int32Array.prototype.includes":"var arr = new Int32Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Int32Array.prototype.indexOf":"var arr = new Int32Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Int32Array.prototype.join":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Int32Array.prototype.keys":"var arr = new Int32Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Int32Array.prototype.lastIndexOf":"var arr = new Int32Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Int32Array.prototype.map":"var arr1 = new Int32Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Int32Array.prototype.reduce":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Int32Array.prototype.reduceRight":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Int32Array.prototype.reverse":"var arr = new Int32Array( [ 1, 2, 3 ] )\narr.reverse()\n","Int32Array.prototype.set":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Int32Array.prototype.slice":"var arr1 = new Int32Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Int32Array.prototype.some":"var arr = new Int32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Int32Array.prototype.sort":"var arr = new Int32Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Int32Array.prototype.subarray":"var arr1 = new Int32Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Int32Array.prototype.toLocaleString":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Int32Array.prototype.toString":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.toString()\n","Int32Array.prototype.values":"var arr = new Int32Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","IS_BIG_ENDIAN":"IS_BIG_ENDIAN\n","IS_BROWSER":"IS_BROWSER\n","IS_DARWIN":"IS_DARWIN\n","IS_DOCKER":"IS_DOCKER\n","IS_ELECTRON":"IS_ELECTRON\n","IS_ELECTRON_MAIN":"IS_ELECTRON_MAIN\n","IS_ELECTRON_RENDERER":"IS_ELECTRON_RENDERER\n","IS_LITTLE_ENDIAN":"IS_LITTLE_ENDIAN\n","IS_MOBILE":"IS_MOBILE\n","IS_NODE":"IS_NODE\n","IS_TOUCH_DEVICE":"IS_TOUCH_DEVICE\n","IS_WEB_WORKER":"IS_WEB_WORKER\n","IS_WINDOWS":"IS_WINDOWS\n","isAbsoluteHttpURI":"var bool = isAbsoluteHttpURI( 'http://example.com/' )\nbool = isAbsoluteHttpURI( 'example.com' )\nbool = isAbsoluteHttpURI( 'foo@bar.com' )\n","isAbsolutePath":"var bool = isAbsolutePath( 'C:\\\\foo\\\\bar\\\\baz' )\nbool = isAbsolutePath( '/foo/bar/baz' )\n","isAbsolutePath.posix":"var bool = isAbsolutePath.posix( '/foo/bar/baz' )\nbool = isAbsolutePath.posix( 'foo/bar/baz' )\n","isAbsolutePath.win32":"var bool = isAbsolutePath.win32( 'C:\\\\foo\\\\bar\\\\baz' )\nbool = isAbsolutePath.win32( 'foo\\\\bar\\\\baz' )\n","isAbsoluteURI":"var bool = isAbsoluteURI( 'http://example.com/' )\nbool = isAbsoluteURI( 'example.com' )\nbool = isAbsoluteURI( 'foo@bar.com' )\n","isAccessorArray":"var bool = isAccessorArray( new Complex64Array( 10 ) )\nbool = isAccessorArray( [] )\nbool = isAccessorArray( { 'length': 0 } )\nbool = isAccessorArray( {} )\n","isAccessorProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isAccessorProperty( obj, 'boop' )\nbool = isAccessorProperty( obj, 'beep' )\n","isAccessorPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isAccessorPropertyIn( obj, 'boop' )\nbool = isAccessorPropertyIn( obj, 'beep' )\n","isAlphagram":"var out = isAlphagram( 'beep' )\nout = isAlphagram( 'zba' )\nout = isAlphagram( '' )\n","isAlphaNumeric":"var bool = isAlphaNumeric( 'abc0123456789' )\nbool = isAlphaNumeric( 'abcdef' )\nbool = isAlphaNumeric( '0xff' )\nbool = isAlphaNumeric( '' )\n","isAnagram":"var str1 = 'I am a weakish speller';\nvar str2 = 'William Shakespeare';\nvar bool = isAnagram( str1, str2 )\nbool = isAnagram( 'bat', 'tabba' )\n","isArguments":"function foo() { return arguments; };\nvar bool = isArguments( foo() )\nbool = isArguments( [] )\n","isArray":"var bool = isArray( [] )\nbool = isArray( {} )\n","isArrayArray":"var bool = isArrayArray( [ [], [] ] )\nbool = isArrayArray( [ {}, {} ] )\nbool = isArrayArray( [] )\n","isArrayBuffer":"var bool = isArrayBuffer( new ArrayBuffer( 10 ) )\nbool = isArrayBuffer( [] )\n","isArrayBufferView":"var bool = isArrayBufferView( new Int8Array() )\nbool = isArrayBufferView( [] )\n","isArrayLength":"var bool = isArrayLength( 5 )\nbool = isArrayLength( 2.0e200 )\nbool = isArrayLength( -3.14 )\nbool = isArrayLength( null )\n","isArrayLike":"var bool = isArrayLike( [] )\nbool = isArrayLike( { 'length': 10 } )\nbool = isArrayLike( 'beep' )\nbool = isArrayLike( null )\n","isArrayLikeObject":"var bool = isArrayLikeObject( [] )\nbool = isArrayLikeObject( { 'length': 10 } )\nbool = isArrayLikeObject( 'beep' )\n","isArrowFunction":"function beep() {};\nvar bool = isArrowFunction( beep )\nbool = isArrowFunction( {} )\n","isASCII":"var str = 'beep boop';\nvar bool = isASCII( str )\nbool = isASCII( fromCodePoint( 130 ) )\n","isBetween":"var bool = isBetween( 3.14, 3.0, 4.0 )\nbool = isBetween( 3.0, 3.0, 4.0 )\nbool = isBetween( 4.0, 3.0, 4.0 )\nbool = isBetween( 3.0, 3.14, 4.0 )\nbool = isBetween( 3.14, 3.14, 4.0, 'open', 'closed' )\nbool = isBetween( 3.14, 3.0, 3.14, 'closed', 'open' )\n","isBetweenArray":"var arr = [ 3.0, 3.14, 4.0 ];\nvar bool = isBetweenArray( arr, 3.0, 4.0 )\nbool = isBetweenArray( arr, 3.14, 4.0 )\nbool = isBetweenArray( arr, 3.0, 3.14 )\nbool = isBetweenArray( arr, 3.0, 4.0, 'open', 'closed' )\nbool = isBetweenArray( arr, 3.0, 4.0, 'closed', 'open' )\n","isBigInt":"var bool = isBigInt( BigInt( '1' ) )\nbool = isBigInt( Object( BigInt( '1' ) ) )\nbool = isBigInt( {} )\nbool = isBigInt( null )\nbool = isBigInt( true )\n","isBigInt64Array":"var bool = isBigInt64Array( new BigInt64Array( 10 ) )\nbool = isBigInt64Array( [] )\n","isBigUint64Array":"var bool = isBigUint64Array( new BigUint64Array( 10 ) )\nbool = isBigUint64Array( [] )\n","isBinaryString":"var bool = isBinaryString( '1000101' )\nbool = isBinaryString( 'beep' )\nbool = isBinaryString( '' )\n","isBlankString":"var bool = isBlankString( '   ' )\nbool = isBlankString( 'beep' )\nbool = isBlankString( null )\n","isBoolean":"var bool = isBoolean( false )\nbool = isBoolean( new Boolean( false ) )\n","isBoolean.isPrimitive":"var bool = isBoolean.isPrimitive( true )\nbool = isBoolean.isPrimitive( false )\nbool = isBoolean.isPrimitive( new Boolean( true ) )\n","isBoolean.isObject":"var bool = isBoolean.isObject( true )\nbool = isBoolean.isObject( new Boolean( false ) )\n","isBooleanArray":"var bool = isBooleanArray( [ true, false, true ] )\nbool = isBooleanArray( [ true, 'abc', false ] )\n","isBooleanArray.primitives":"var bool = isBooleanArray.primitives( [ true, false ] )\nbool = isBooleanArray.primitives( [ false, new Boolean( true ) ] )\n","isBooleanArray.objects":"var bool = isBooleanArray.objects( [ new Boolean( false ), true ] )\nbool = isBooleanArray.objects( [ new Boolean( false ), new Boolean( true ) ] )\n","isBoxedPrimitive":"var bool = isBoxedPrimitive( new Boolean( false ) )\nbool = isBoxedPrimitive( true )\n","isBuffer":"var bool = isBuffer( new Buffer( 'beep' ) )\nbool = isBuffer( new Buffer( [ 1, 2, 3, 4 ] ) )\nbool = isBuffer( {} )\nbool = isBuffer( [] )\n","isCamelcase":"var bool = isCamelcase( 'helloWorld' )\nbool = isCamelcase( 'hello world' )\n","isCapitalized":"var bool = isCapitalized( 'Hello' )\nbool = isCapitalized( 'world' )\n","isCentrosymmetricMatrix":"var buf = [ 2, 1, 1, 2 ];\nvar M = ndarray( 'generic', buf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\nvar bool = isCentrosymmetricMatrix( M )\nbool = isCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isCentrosymmetricMatrix( 3.14 )\nbool = isCentrosymmetricMatrix( {} )\n","isCircular":"var obj = { 'beep': 'boop' };\nobj.self = obj;\nvar bool = isCircular( obj )\nbool = isCircular( {} )\nbool = isCircular( null )\n","isCircularArray":"var arr = [ 1, 2, 3 ];\narr.push( arr );\nvar bool = isCircularArray( arr )\nbool = isCircularArray( [] )\nbool = isCircularArray( null )\n","isCircularPlainObject":"var obj = { 'beep': 'boop' };\nobj.self = obj;\nvar bool = isCircularPlainObject( obj )\nbool = isCircularPlainObject( {} )\nbool = isCircularPlainObject( null )\n","isClass":"var bool = isClass( class Person {} )\nbool = isClass( function Person() {} )\nbool = isClass( {} )\nbool = isClass( null )\nbool = isClass( true )\n","isCollection":"var bool = isCollection( [] )\nbool = isCollection( { 'length': 0 } )\nbool = isCollection( {} )\n","isComplex":"var bool = isComplex( new Complex64( 2.0, 2.0 ) )\nbool = isComplex( new Complex128( 3.0, 1.0 ) )\nbool = isComplex( 3.14 )\nbool = isComplex( {} )\n","isComplex64":"var bool = isComplex64( new Complex64( 2.0, 2.0 ) )\nbool = isComplex64( new Complex128( 3.0, 1.0 ) )\nbool = isComplex64( 3.14 )\nbool = isComplex64( {} )\n","isComplex64Array":"var bool = isComplex64Array( new Complex64Array( 10 ) )\nbool = isComplex64Array( [] )\n","isComplex64MatrixLike":"var M = {};\nM.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex64MatrixLike( M )\nbool = isComplex64MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isComplex64MatrixLike( 3.14 )\nbool = isComplex64MatrixLike( {} )\n","isComplex64ndarrayLike":"var M = {};\nM.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex64ndarrayLike( M )\nbool = isComplex64ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isComplex64ndarrayLike( 3.14 )\nbool = isComplex64ndarrayLike( {} )\n","isComplex64VectorLike":"var M = {};\nM.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex64VectorLike( M )\nbool = isComplex64VectorLike( [ 1, 2, 3, 4 ] )\nbool = isComplex64VectorLike( 3.14 )\nbool = isComplex64VectorLike( {} )\n","isComplex128":"var bool = isComplex128( new Complex128( 3.0, 1.0 ) )\nbool = isComplex128( new Complex64( 2.0, 2.0 ) )\nbool = isComplex128( 3.14 )\nbool = isComplex128( {} )\n","isComplex128Array":"var bool = isComplex128Array( new Complex128Array( 10 ) )\nbool = isComplex128Array( [] )\n","isComplex128MatrixLike":"var M = {};\nM.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex128';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex128MatrixLike( M )\nbool = isComplex128MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isComplex128MatrixLike( 3.14 )\nbool = isComplex128MatrixLike( {} )\n","isComplex128ndarrayLike":"var M = {};\nM.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex128';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex128ndarrayLike( M )\nbool = isComplex128ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isComplex128ndarrayLike( 3.14 )\nbool = isComplex128ndarrayLike( {} )\n","isComplex128VectorLike":"var M = {};\nM.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex128';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex128VectorLike( M )\nbool = isComplex128VectorLike( [ 1, 2, 3, 4 ] )\nbool = isComplex128VectorLike( 3.14 )\nbool = isComplex128VectorLike( {} )\n","isComplexLike":"var bool = isComplexLike( new Complex64( 2.0, 2.0 ) )\nbool = isComplexLike( new Complex128( 3.0, 1.0 ) )\nbool = isComplexLike( 3.14 )\nbool = isComplexLike( {} )\n","isComplexTypedArray":"var bool = isComplexTypedArray( new Complex64Array( 10 ) )\n","isComplexTypedArrayLike":"var bool = isComplexTypedArrayLike( new Complex128Array() )\nbool = isComplexTypedArrayLike({\n'length': 10,\n'byteOffset': 0,\n'byteLength': 10,\n'BYTES_PER_ELEMENT': 4,\n'get': function get() {},\n'set': function set() {}\n })\n","isComposite":"var bool = isComposite( 4.0 )\nbool = isComposite( new Number( 4.0 ) )\nbool = isComposite( 3.14 )\nbool = isComposite( -4.0 )\nbool = isComposite( null )\n","isComposite.isPrimitive":"var bool = isComposite.isPrimitive( 4.0 )\nbool = isComposite.isPrimitive( new Number( 4.0 ) )\n","isComposite.isObject":"var bool = isComposite.isObject( 4.0 )\nbool = isComposite.isObject( new Number( 4.0 ) )\n","isConfigurableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isConfigurableProperty( obj, 'boop' )\nbool = isConfigurableProperty( obj, 'beep' )\n","isConfigurablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isConfigurablePropertyIn( obj, 'boop' )\nbool = isConfigurablePropertyIn( obj, 'beep' )\n","isConstantcase":"var bool = isConstantcase( 'BEEP_BOOP' )\nbool = isConstantcase( 'BEEP and BOOP' )\n","isCubeNumber":"var bool = isCubeNumber( 8.0 )\nbool = isCubeNumber( new Number( 8.0 ) )\nbool = isCubeNumber( 3.14 )\nbool = isCubeNumber( -5.0 )\nbool = isCubeNumber( null )\n","isCubeNumber.isPrimitive":"var bool = isCubeNumber.isPrimitive( 8.0 )\nbool = isCubeNumber.isPrimitive( new Number( 8.0 ) )\n","isCubeNumber.isObject":"var bool = isCubeNumber.isObject( 8.0 )\nbool = isCubeNumber.isObject( new Number( 8.0 ) )\n","isCurrentYear":"var bool = isCurrentYear( new Date() )\nbool = isCurrentYear( currentYear() )\nbool = isCurrentYear( 2021 )\nbool = isCurrentYear( null )\n","isDataProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isDataProperty( obj, 'boop' )\nbool = isDataProperty( obj, 'beep' )\n","isDataPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isDataPropertyIn( obj, 'boop' )\nbool = isDataPropertyIn( obj, 'beep' )\n","isDataView":"var buf = new ArrayBuffer( 10 );\nvar bool = isDataView( new DataView( buf ) )\nbool = isDataView( [] )\n","isDateObject":"var bool = isDateObject( new Date() )\nbool = isDateObject( '2017-01-01' )\n","isDateObjectArray":"var bool = isDateObjectArray( [ new Date(), new Date() ] )\nbool = isDateObjectArray( [ {}, {} ] )\nbool = isDateObjectArray( [ new Date(), '2011-01-01' ] )\nbool = isDateObjectArray( [] )\n","isDigitString":"var bool = isDigitString( '0123456789' )\nbool = isDigitString( 'abcdef' )\nbool = isDigitString( '0xff' )\nbool = isDigitString( '' )\n","isDomainName":"var bool = isDomainName( 'example.com' )\nbool = isDomainName( 'foo@bar.com' )\n","isDurationString":"var bool = isDurationString( '1d' )\nbool = isDurationString( '1h' )\nbool = isDurationString( 'beep' )\n","isEmailAddress":"var bool = isEmailAddress( 'beep@boop.com' )\nbool = isEmailAddress( 'beep' )\nbool = isEmailAddress( null )\n","isEmptyArray":"var bool = isEmptyArray( [] )\nbool = isEmptyArray( [ 1, 2, 3 ] )\nbool = isEmptyArray( {} )\n","isEmptyArrayLikeObject":"var bool = isEmptyArrayLikeObject( [] )\nbool = isEmptyArrayLikeObject( { 'length': 0 } )\nbool = isEmptyArrayLikeObject( '' )\n","isEmptyCollection":"var bool = isEmptyCollection( [] )\nbool = isEmptyCollection( { 'length': 0 } )\nbool = isEmptyCollection( [ 1, 2, 3 ] )\nbool = isEmptyCollection( {} )\n","isEmptyObject":"var bool = isEmptyObject( {} )\nbool = isEmptyObject( { 'beep': 'boop' } )\nbool = isEmptyObject( [] )\n","isEmptyString":"var bool = isEmptyString( '' )\nbool = isEmptyString( new String( '' ) )\nbool = isEmptyString( 'beep' )\nbool = isEmptyString( [] )\n","isEmptyString.isPrimitive":"var bool = isEmptyString.isPrimitive( '' )\nbool = isEmptyString.isPrimitive( new String( '' ) )\n","isEmptyString.isObject":"var bool = isEmptyString.isObject( new String( '' ) )\nbool = isEmptyString.isObject( '' )\n","isEnumerableProperty":"var beep = { 'boop': true };\nvar bool = isEnumerableProperty( beep, 'boop' )\nbool = isEnumerableProperty( beep, 'hasOwnProperty' )\n","isEnumerablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = true;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isEnumerablePropertyIn( obj, 'boop' )\nbool = isEnumerablePropertyIn( obj, 'beep' )\n","isEqualArray":"var x = [ 1.0, 2.0, 3.0 ];\nvar y = [ 1.0, 2.0, 3.0 ];\nvar bool = isEqualArray( x, y )\nx = [ NaN, NaN, NaN ];\ny = [ NaN, NaN, NaN ];\nbool = isEqualArray( x, y )\n","isError":"var bool = isError( new Error( 'beep' ) )\nbool = isError( {} )\n","isEvalError":"var bool = isEvalError( new EvalError( 'beep' ) )\nbool = isEvalError( {} )\n","isEven":"var bool = isEven( 4.0 )\nbool = isEven( new Number( 4.0 ) )\nbool = isEven( 3.0 )\nbool = isEven( -3.14 )\nbool = isEven( null )\n","isEven.isPrimitive":"var bool = isEven.isPrimitive( -4.0 )\nbool = isEven.isPrimitive( new Number( -4.0 ) )\n","isEven.isObject":"var bool = isEven.isObject( 4.0 )\nbool = isEven.isObject( new Number( 4.0 ) )\n","isFalsy":"var bool = isFalsy( false )\nbool = isFalsy( '' )\nbool = isFalsy( 0 )\nbool = isFalsy( null )\nbool = isFalsy( void 0 )\nbool = isFalsy( NaN )\nbool = isFalsy( {} )\nbool = isFalsy( [] )\n","isFalsyArray":"var bool = isFalsyArray( [ null, '' ] )\nbool = isFalsyArray( [ {}, [] ] )\nbool = isFalsyArray( [] )\n","isFinite":"var bool = isFinite( 5.0 )\nbool = isFinite( new Number( 5.0 ) )\nbool = isFinite( 1.0/0.0 )\nbool = isFinite( null )\n","isFinite.isPrimitive":"var bool = isFinite.isPrimitive( -3.0 )\nbool = isFinite.isPrimitive( new Number( -3.0 ) )\n","isFinite.isObject":"var bool = isFinite.isObject( 3.0 )\nbool = isFinite.isObject( new Number( 3.0 ) )\n","isFiniteArray":"var bool = isFiniteArray( [ -3.0, new Number(0.0), 2.0 ] )\nbool = isFiniteArray( [ -3.0, 1.0/0.0 ] )\n","isFiniteArray.primitives":"var bool = isFiniteArray.primitives( [ -1.0, 10.0 ] )\nbool = isFiniteArray.primitives( [ -1.0, 0.0, 5.0 ] )\nbool = isFiniteArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isFiniteArray.objects":"var bool = isFiniteArray.objects( [ new Number(1.0), new Number(3.0) ] )\nbool = isFiniteArray.objects( [ -1.0, 0.0, 3.0 ] )\nbool = isFiniteArray.objects( [ 3.0, new Number(-1.0) ] )\n","isFloat32Array":"var bool = isFloat32Array( new Float32Array( 10 ) )\nbool = isFloat32Array( [] )\n","isFloat32MatrixLike":"var M = {};\nM.data = new Float32Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float32';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat32MatrixLike( M )\nbool = isFloat32MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isFloat32MatrixLike( 3.14 )\nbool = isFloat32MatrixLike( {} )\n","isFloat32ndarrayLike":"var M = {};\nM.data = new Float32Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float32';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat32ndarrayLike( M )\nbool = isFloat32ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isFloat32ndarrayLike( 3.14 )\nbool = isFloat32ndarrayLike( {} )\n","isFloat32VectorLike":"var M = {};\nM.data = new Float32Array( [ 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float32';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat32VectorLike( M )\nbool = isFloat32VectorLike( [ 1, 2, 3, 4 ] )\nbool = isFloat32VectorLike( 3.14 )\nbool = isFloat32VectorLike( {} )\n","isFloat64Array":"var bool = isFloat64Array( new Float64Array( 10 ) )\nbool = isFloat64Array( [] )\n","isFloat64MatrixLike":"var M = {};\nM.data = new Float64Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat64MatrixLike( M )\nbool = isFloat64MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isFloat64MatrixLike( 3.14 )\nbool = isFloat64MatrixLike( {} )\n","isFloat64ndarrayLike":"var M = {};\nM.data = new Float64Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat64ndarrayLike( M )\nbool = isFloat64ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isFloat64ndarrayLike( 3.14 )\nbool = isFloat64ndarrayLike( {} )\n","isFloat64VectorLike":"var M = {};\nM.data = new Float64Array( [ 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat64VectorLike( M )\nbool = isFloat64VectorLike( [ 1, 2, 3, 4 ] )\nbool = isFloat64VectorLike( 3.14 )\nbool = isFloat64VectorLike( {} )\n","isFunction":"function beep() {};\nvar bool = isFunction( beep )\nbool = isFunction( {} )\n","isFunctionArray":"function beep() {};\nfunction boop() {};\nvar bool = isFunctionArray( [ beep, boop ] )\nbool = isFunctionArray( [ {}, beep ] )\nbool = isFunctionArray( [] )\n","isGeneratorObject":"function* generateID() {\n var idx = 0;\n while ( idx < idx+1 ) {\n     yield idx;\n     idx += 1;\n }\n };\nvar bool = isGeneratorObject( generateID() )\nbool = isGeneratorObject( generateID )\nbool = isGeneratorObject( {} )\nbool = isGeneratorObject( null )\n","isGeneratorObjectLike":"var obj = {\n 'next': function noop() {},\n 'return': function noop() {},\n 'throw': function noop() {}\n };\nvar bool = isGeneratorObjectLike( obj )\nbool = isGeneratorObjectLike( {} )\nbool = isGeneratorObjectLike( null )\n","isgzipBuffer":"var buf = new Uint8Array( 20 );\nbuf[ 0 ] = 31;  // 0x1f => magic number\nbuf[ 1 ] = 139; // 0x8b\nbuf[ 2 ] = 8;   // 0x08 => compression method\nvar bool = isgzipBuffer( buf )\nbool = isgzipBuffer( [] )\n","isHexString":"var bool = isHexString( '0123456789abcdefABCDEF' )\nbool = isHexString( '0xffffff' )\nbool = isHexString( 'x' )\nbool = isHexString( '' )\n","isInfinite":"var bool = isInfinite( 1.0/0.0 )\nbool = isInfinite( new Number( -1.0/0.0 ) )\nbool = isInfinite( 5.0 )\nbool = isInfinite( '1.0/0.0' )\n","isInfinite.isPrimitive":"var bool = isInfinite.isPrimitive( -1.0/0.0 )\nbool = isInfinite.isPrimitive( new Number( -1.0/0.0 ) )\n","isInfinite.isObject":"var bool = isInfinite.isObject( 1.0/0.0 )\nbool = isInfinite.isObject( new Number( 1.0/0.0 ) )\n","isInheritedProperty":"var beep = { 'boop': true };\nvar bool = isInheritedProperty( beep, 'boop' )\nbool = isInheritedProperty( beep, 'toString' )\nbool = isInheritedProperty( beep, 'bop' )\n","isInt8Array":"var bool = isInt8Array( new Int8Array( 10 ) )\nbool = isInt8Array( [] )\n","isInt16Array":"var bool = isInt16Array( new Int16Array( 10 ) )\nbool = isInt16Array( [] )\n","isInt32Array":"var bool = isInt32Array( new Int32Array( 10 ) )\nbool = isInt32Array( [] )\n","isInteger":"var bool = isInteger( 5.0 )\nbool = isInteger( new Number( 5.0 ) )\nbool = isInteger( -3.14 )\nbool = isInteger( null )\n","isInteger.isPrimitive":"var bool = isInteger.isPrimitive( -3.0 )\nbool = isInteger.isPrimitive( new Number( -3.0 ) )\n","isInteger.isObject":"var bool = isInteger.isObject( 3.0 )\nbool = isInteger.isObject( new Number( 3.0 ) )\n","isIntegerArray":"var bool = isIntegerArray( [ -3.0, new Number(0.0), 2.0 ] )\nbool = isIntegerArray( [ -3.0, '3.0' ] )\n","isIntegerArray.primitives":"var bool = isIntegerArray.primitives( [ -1.0, 10.0 ] )\nbool = isIntegerArray.primitives( [ -1.0, 0.0, 5.0 ] )\nbool = isIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isIntegerArray.objects":"var bool = isIntegerArray.objects( [ new Number(1.0), new Number(3.0) ] )\nbool = isIntegerArray.objects( [ -1.0, 0.0, 3.0 ] )\nbool = isIntegerArray.objects( [ 3.0, new Number(-1.0) ] )\n","isIterableLike":"var bool = isIterableLike( [ 1, 2, 3 ] )\nbool = isIterableLike( {} )\nbool = isIterableLike( null )\n","isIteratorLike":"var obj = {\n 'next': function noop() {}\n };\nvar bool = isIteratorLike( obj )\nbool = isIteratorLike( {} )\nbool = isIteratorLike( null )\n","isJSON":"var bool = isJSON( '{\"a\":5}' )\nbool = isJSON( '{a\":5}' )\n","isKebabcase":"var bool = isKebabcase( 'beep-boop' )\nbool = isKebabcase( 'BEEP_BOOP' )\n","isLeapYear":"var bool = isLeapYear( new Date() )\nbool = isLeapYear( 1996 )\nbool = isLeapYear( 2001 )\n","isLocalhost":"var bool = isLocalhost( 'localhost' )\nbool = isLocalhost( '127.0.0.1' )\nbool = isLocalhost( 'stdlib.io' )\n","isLowercase":"var bool = isLowercase( 'hello' )\nbool = isLowercase( 'World' )\n","isMatrixLike":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isMatrixLike( M )\nbool = isMatrixLike( [ 1, 2, 3, 4 ] )\nbool = isMatrixLike( 3.14 )\nbool = isMatrixLike( {} )\n","isMethod":"var beep = { 'boop': function beep() { return 'beep'; } };\nvar bool = isMethod( beep, 'boop' )\nbool = isMethod( beep, 'toString' )\n","isMethodIn":"var beep = { 'boop': true };\nvar bool = isMethodIn( beep, 'toString' )\nbool = isMethodIn( beep, 'boop' )\nbool = isMethodIn( beep, 'bop' )\n","isMultiSlice":"var bool = isMultiSlice( new MultiSlice() )\nbool = isMultiSlice( 3.14 )\nbool = isMultiSlice( {} )\n","isNamedTypedTupleLike":"var Point = namedtypedtuple( [ 'x', 'y' ] );\nvar p = new Point();\nvar bool = isNamedTypedTupleLike( p )\nbool = isNamedTypedTupleLike( [ 1, 2, 3, 4 ] )\nbool = isNamedTypedTupleLike( 3.14 )\nbool = isNamedTypedTupleLike( {} )\n","isnan":"var bool = isnan( NaN )\nbool = isnan( new Number( NaN ) )\nbool = isnan( 3.14 )\nbool = isnan( null )\n","isnan.isPrimitive":"var bool = isnan.isPrimitive( NaN )\nbool = isnan.isPrimitive( 3.14 )\nbool = isnan.isPrimitive( new Number( NaN ) )\n","isnan.isObject":"var bool = isnan.isObject( NaN )\nbool = isnan.isObject( new Number( NaN ) )\n","isNaNArray":"var bool = isNaNArray( [ NaN, NaN, NaN ] )\nbool = isNaNArray( [ NaN, 2 ] )\n","isNaNArray.primitives":"var bool = isNaNArray.primitives( [ NaN, new Number( NaN ) ] )\nbool = isNaNArray.primitives( [ NaN, NaN, NaN ] )\n","isNaNArray.objects":"var bool = isNaNArray.objects( [ new Number( NaN ), new Number( NaN ) ] )\nbool = isNaNArray.objects( [ NaN, new Number( NaN ), new Number( NaN ) ] )\nbool = isNaNArray.objects( [ NaN, NaN, NaN ] )\n","isNativeFunction":"var bool = isNativeFunction( Date )\nfunction beep() {};\nbool = isNativeFunction( beep )\nbool = isNativeFunction( {} )\n","isndarrayLike":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isndarrayLike( M )\nbool = isndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isndarrayLike( 3.14 )\nbool = isndarrayLike( {} )\n","isndarrayLikeWithDataType":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isndarrayLikeWithDataType( M, 'generic' )\nbool = isndarrayLikeWithDataType( [ 1, 2, 3, 4 ], 'generic' )\nbool = isndarrayLikeWithDataType( 3.14, 'generic' )\nbool = isndarrayLikeWithDataType( {}, 'generic' )\n","isNegativeFinite":"var bool = isNegativeFinite( -5.0 )\nbool = isNegativeFinite( new Number( -5.0 ) )\nbool = isNegativeFinite( -3.14 )\nbool = isNegativeFinite( 5.0 )\nbool = isNegativeFinite( null )\nbool = isNegativeFinite( -1.0/0.0 )\nbool = isNegativeFinite( new Number( -1.0/0.0 ) )\n","isNegativeFinite.isPrimitive":"var bool = isNegativeFinite.isPrimitive( -3.0 )\nbool = isNegativeFinite.isPrimitive( new Number( -3.0 ) )\nvar bool = isNegativeFinite.isPrimitive( -1.0/0.0 )\nbool = isNegativeFinite.isPrimitive( new Number( -1.0/0.0 ) )\n","isNegativeFinite.isObject":"var bool = isNegativeFinite.isObject( -3.0 )\nbool = isNegativeFinite.isObject( new Number( -3.0 ) )\nbool = isNegativeFinite.isObject( -1.0/0.0 )\nbool = isNegativeFinite.isObject( new Number( -1.0/0.0 ) )\n","isNegativeInteger":"var bool = isNegativeInteger( -5.0 )\nbool = isNegativeInteger( new Number( -5.0 ) )\nbool = isNegativeInteger( 5.0 )\nbool = isNegativeInteger( -3.14 )\nbool = isNegativeInteger( null )\n","isNegativeInteger.isPrimitive":"var bool = isNegativeInteger.isPrimitive( -3.0 )\nbool = isNegativeInteger.isPrimitive( new Number( -3.0 ) )\n","isNegativeInteger.isObject":"var bool = isNegativeInteger.isObject( -3.0 )\nbool = isNegativeInteger.isObject( new Number( -3.0 ) )\n","isNegativeIntegerArray":"var bool = isNegativeIntegerArray( [ -3.0, new Number(-3.0) ] )\nbool = isNegativeIntegerArray( [ -3.0, '-3.0' ] )\n","isNegativeIntegerArray.primitives":"var bool = isNegativeIntegerArray.primitives( [ -1.0, -10.0 ] )\nbool = isNegativeIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNegativeIntegerArray.objects":"var bool = isNegativeIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNegativeIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNegativeNumber":"var bool = isNegativeNumber( -5.0 )\nbool = isNegativeNumber( new Number( -5.0 ) )\nbool = isNegativeNumber( -3.14 )\nbool = isNegativeNumber( 5.0 )\nbool = isNegativeNumber( null )\n","isNegativeNumber.isPrimitive":"var bool = isNegativeNumber.isPrimitive( -3.0 )\nbool = isNegativeNumber.isPrimitive( new Number( -3.0 ) )\n","isNegativeNumber.isObject":"var bool = isNegativeNumber.isObject( -3.0 )\nbool = isNegativeNumber.isObject( new Number( -3.0 ) )\n","isNegativeNumberArray":"var bool = isNegativeNumberArray( [ -3.0, new Number(-3.0) ] )\nbool = isNegativeNumberArray( [ -3.0, '-3.0' ] )\n","isNegativeNumberArray.primitives":"var bool = isNegativeNumberArray.primitives( [ -1.0, -10.0 ] )\nbool = isNegativeNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNegativeNumberArray.objects":"var bool = isNegativeNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNegativeNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNegativeZero":"var bool = isNegativeZero( -0.0 )\nbool = isNegativeZero( new Number( -0.0 ) )\nbool = isNegativeZero( -3.14 )\nbool = isNegativeZero( 0.0 )\nbool = isNegativeZero( null )\n","isNegativeZero.isPrimitive":"var bool = isNegativeZero.isPrimitive( -0.0 )\nbool = isNegativeZero.isPrimitive( new Number( -0.0 ) )\n","isNegativeZero.isObject":"var bool = isNegativeZero.isObject( -0.0 )\nbool = isNegativeZero.isObject( new Number( -0.0 ) )\n","isNodeBuiltin":"var bool = isNodeBuiltin( 'cluster' )\nbool = isNodeBuiltin( 'crypto' )\nbool = isNodeBuiltin( 'fs-extra' )\nbool = isNodeBuiltin( '' )\n","isNodeDuplexStreamLike":"var Stream = require( 'stream' ).Duplex;\ns = new Stream();\nvar bool = isNodeDuplexStreamLike( s )\nbool = isNodeDuplexStreamLike( {} )\n","isNodeReadableStreamLike":"var Stream = require( 'stream' ).Readable;\ns = new Stream();\nvar bool = isNodeReadableStreamLike( s )\nbool = isNodeReadableStreamLike( {} )\n","isNodeREPL":"var bool = isNodeREPL()\n","isNodeStreamLike":"var Stream = require( 'stream' ).Stream;\ns = new Stream();\nvar bool = isNodeStreamLike( s )\nbool = isNodeStreamLike( {} )\n","isNodeTransformStreamLike":"var Stream = require( 'stream' ).Transform;\ns = new Stream();\nvar bool = isNodeTransformStreamLike( s )\nbool = isNodeTransformStreamLike( {} )\n","isNodeWritableStreamLike":"var Stream = require( 'stream' ).Writable;\ns = new Stream();\nvar bool = isNodeWritableStreamLike( s )\nbool = isNodeWritableStreamLike( {} )\n","isNonConfigurableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonConfigurableProperty( obj, 'boop' )\nbool = isNonConfigurableProperty( obj, 'beep' )\n","isNonConfigurablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonConfigurablePropertyIn( obj, 'boop' )\nbool = isNonConfigurablePropertyIn( obj, 'beep' )\n","isNonEnumerableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonEnumerableProperty( obj, 'boop' )\nbool = isNonEnumerableProperty( obj, 'beep' )\n","isNonEnumerablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = true;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonEnumerablePropertyIn( obj, 'boop' )\nbool = isNonEnumerablePropertyIn( obj, 'beep' )\n","isNonNegativeFinite":"var bool = isNonNegativeFinite( 5.0 )\nbool = isNonNegativeFinite( new Number( 5.0 ) )\nbool = isNonNegativeFinite( 3.14 )\nbool = isNonNegativeFinite( -5.0 )\nbool = isNonNegativeFinite( null )\nbool = isNonNegativeFinite( PINF )\n","isNonNegativeFinite.isPrimitive":"var bool = isNonNegativeFinite.isPrimitive( 3.0 )\nbool = isNonNegativeFinite.isPrimitive( new Number( 3.0 ) )\n","isNonNegativeFinite.isObject":"var bool = isNonNegativeFinite.isObject( 3.0 )\nbool = isNonNegativeFinite.isObject( new Number( 3.0 ) )\n","isNonNegativeInteger":"var bool = isNonNegativeInteger( 5.0 )\nbool = isNonNegativeInteger( new Number( 5.0 ) )\nbool = isNonNegativeInteger( 3.14 )\nbool = isNonNegativeInteger( -5.0 )\nbool = isNonNegativeInteger( null )\n","isNonNegativeInteger.isPrimitive":"var bool = isNonNegativeInteger.isPrimitive( 3.0 )\nbool = isNonNegativeInteger.isPrimitive( new Number( 3.0 ) )\n","isNonNegativeInteger.isObject":"var bool = isNonNegativeInteger.isObject( 3.0 )\nbool = isNonNegativeInteger.isObject( new Number( 3.0 ) )\n","isNonNegativeIntegerArray":"var bool = isNonNegativeIntegerArray( [ 3.0, new Number(3.0) ] )\nbool = isNonNegativeIntegerArray( [ 3.0, '3.0' ] )\n","isNonNegativeIntegerArray.primitives":"var bool = isNonNegativeIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n","isNonNegativeIntegerArray.objects":"var bool = isNonNegativeIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isNonNegativeIntegerArray.objects( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n","isNonNegativeNumber":"var bool = isNonNegativeNumber( 5.0 )\nbool = isNonNegativeNumber( new Number( 5.0 ) )\nbool = isNonNegativeNumber( 3.14 )\nbool = isNonNegativeNumber( -5.0 )\nbool = isNonNegativeNumber( null )\n","isNonNegativeNumber.isPrimitive":"var bool = isNonNegativeNumber.isPrimitive( 3.0 )\nbool = isNonNegativeNumber.isPrimitive( new Number( 3.0 ) )\n","isNonNegativeNumber.isObject":"var bool = isNonNegativeNumber.isObject( 3.0 )\nbool = isNonNegativeNumber.isObject( new Number( 3.0 ) )\n","isNonNegativeNumberArray":"var bool = isNonNegativeNumberArray( [ 3.0, new Number(3.0) ] )\nbool = isNonNegativeNumberArray( [ 3.0, '3.0' ] )\n","isNonNegativeNumberArray.primitives":"var bool = isNonNegativeNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n","isNonNegativeNumberArray.objects":"var bool = isNonNegativeNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isNonNegativeNumberArray.objects( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeNumberArray.objects( [ 3.0, new Number(1.0) ] )\n","isNonPositiveFinite":"var bool = isNonPositiveFinite( -5.0 )\nbool = isNonPositiveFinite( new Number( -5.0 ) )\nbool = isNonPositiveFinite( -3.14 )\nbool = isNonPositiveFinite( 5.0 )\nbool = isNonPositiveFinite( null )\n","isNonPositiveFinite.isPrimitive":"var bool = isNonPositiveFinite.isPrimitive( -3.0 )\nbool = isNonPositiveFinite.isPrimitive( new Number( -3.0 ) )\n","isNonPositiveFinite.isObject":"var bool = isNonPositiveFinite.isObject( -3.0 )\nbool = isNonPositiveFinite.isObject( new Number( -3.0 ) )\n","isNonPositiveInteger":"var bool = isNonPositiveInteger( -5.0 )\nbool = isNonPositiveInteger( new Number( -5.0 ) )\nbool = isNonPositiveInteger( 5.0 )\nbool = isNonPositiveInteger( -3.14 )\nbool = isNonPositiveInteger( null )\n","isNonPositiveInteger.isPrimitive":"var bool = isNonPositiveInteger.isPrimitive( -3.0 )\nbool = isNonPositiveInteger.isPrimitive( new Number( -3.0 ) )\n","isNonPositiveInteger.isObject":"var bool = isNonPositiveInteger.isObject( -3.0 )\nbool = isNonPositiveInteger.isObject( new Number( -3.0 ) )\n","isNonPositiveIntegerArray":"var bool = isNonPositiveIntegerArray( [ -3.0, new Number(-3.0) ] )\nbool = isNonPositiveIntegerArray( [ -3.0, '-3.0' ] )\n","isNonPositiveIntegerArray.primitives":"var bool = isNonPositiveIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNonPositiveIntegerArray.objects":"var bool = isNonPositiveIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNonPositiveIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNonPositiveNumber":"var bool = isNonPositiveNumber( -5.0 )\nbool = isNonPositiveNumber( new Number( -5.0 ) )\nbool = isNonPositiveNumber( -3.14 )\nbool = isNonPositiveNumber( 5.0 )\nbool = isNonPositiveNumber( null )\n","isNonPositiveNumber.isPrimitive":"var bool = isNonPositiveNumber.isPrimitive( -3.0 )\nbool = isNonPositiveNumber.isPrimitive( new Number( -3.0 ) )\n","isNonPositiveNumber.isObject":"var bool = isNonPositiveNumber.isObject( -3.0 )\nbool = isNonPositiveNumber.isObject( new Number( -3.0 ) )\n","isNonPositiveNumberArray":"var bool = isNonPositiveNumberArray( [ -3.0, new Number(-3.0) ] )\nbool = isNonPositiveNumberArray( [ -3.0, '-3.0' ] )\n","isNonPositiveNumberArray.primitives":"var bool = isNonPositiveNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNonPositiveNumberArray.objects":"var bool = isNonPositiveNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNonPositiveNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNonSymmetricMatrix":"var buf = [ 1, 2, 3, 4 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isNonSymmetricMatrix( M )\nbool = isNonSymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isNonSymmetricMatrix( 3.14 )\nbool = isNonSymmetricMatrix( {} )\n","isNull":"var bool = isNull( null )\nbool = isNull( true )\n","isNullArray":"var bool = isNullArray( [ null, null, null ] )\nbool = isNullArray( [ NaN, 2, null ] )\n","isNumber":"var bool = isNumber( 3.14 )\nbool = isNumber( new Number( 3.14 ) )\nbool = isNumber( NaN )\nbool = isNumber( null )\n","isNumber.isPrimitive":"var bool = isNumber.isPrimitive( 3.14 )\nbool = isNumber.isPrimitive( NaN )\nbool = isNumber.isPrimitive( new Number( 3.14 ) )\n","isNumber.isObject":"var bool = isNumber.isObject( 3.14 )\nbool = isNumber.isObject( new Number( 3.14 ) )\n","isNumberArray":"var bool = isNumberArray( [ 1, 2, 3 ] )\nbool = isNumberArray( [ '1', 2, 3 ] )\n","isNumberArray.primitives":"var arr = [ 1, 2, 3 ];\nvar bool = isNumberArray.primitives( arr )\narr = [ 1, new Number( 2 ) ];\nbool = isNumberArray.primitives( arr )\n","isNumberArray.objects":"var arr = [ new Number( 1 ), new Number( 2 ) ];\nvar bool = isNumberArray.objects( arr )\narr = [ new Number( 1 ), 2 ];\nbool = isNumberArray.objects( arr )\n","isNumericArray":"var bool = isNumericArray( new Int8Array( 10 ) )\nbool = isNumericArray( [ 1, 2, 3 ] )\nbool = isNumericArray( [ '1', '2', '3' ] )\n","isObject":"var bool = isObject( {} )\nbool = isObject( true )\n","isObjectArray":"var bool = isObjectArray( [ {}, new Number(3.0) ] )\nbool = isObjectArray( [ {}, { 'beep': 'boop' } ] )\nbool = isObjectArray( [ {}, '3.0' ] )\n","isObjectLike":"var bool = isObjectLike( {} )\nbool = isObjectLike( [] )\nbool = isObjectLike( null )\n","isOdd":"var bool = isOdd( 5.0 )\nbool = isOdd( new Number( 5.0 ) )\nbool = isOdd( 4.0 )\nbool = isOdd( new Number( 4.0 ) )\nbool = isOdd( -3.14 )\nbool = isOdd( null )\n","isOdd.isPrimitive":"var bool = isOdd.isPrimitive( -5.0 )\nbool = isOdd.isPrimitive( new Number( -5.0 ) )\n","isOdd.isObject":"var bool = isOdd.isObject( 5.0 )\nbool = isOdd.isObject( new Number( 5.0 ) )\n","isoWeeksInYear":"var num = isoWeeksInYear()\nnum = isoWeeksInYear( 2015 )\nnum = isoWeeksInYear( 2017 )\n","isPascalcase":"var bool = isPascalcase( 'HelloWorld' )\nbool = isPascalcase( 'hello-world' )\n","isPersymmetricMatrix":"var buf = [ 1, 2, 3, 1 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isPersymmetricMatrix( M )\nbool = isPersymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isPersymmetricMatrix( 3.14 )\nbool = isPersymmetricMatrix( {} )\n","isPlainObject":"var bool = isPlainObject( {} )\nbool = isPlainObject( null )\n","isPlainObjectArray":"var bool = isPlainObjectArray( [ {}, { 'beep': 'boop' } ] )\nbool = isPlainObjectArray( [ {}, new Number(3.0) ] )\nbool = isPlainObjectArray( [ {}, '3.0' ] )\n","isPositiveFinite":"var bool = isPositiveFinite( 5.0 )\nbool = isPositiveFinite( new Number( 5.0 ) )\nbool = isPositiveFinite( 3.14 )\nbool = isPositiveFinite( -5.0 )\nvar bool = isPositiveFinite( 1.0/0.0 )\nbool = isPositiveFinite( new Number( 1.0/0.0 ) )\nbool = isPositiveFinite( null )\n","isPositiveFinite.isPrimitive":"var bool = isPositiveFinite.isPrimitive( 3.0 )\nvar bool = isPositiveFinite.isPrimitive( 1.0/0.0 )\nbool = isPositiveFinite.isPrimitive( new Number( 3.0 ) )\n","isPositiveFinite.isObject":"var bool = isPositiveFinite.isObject( 3.0 )\nbool = isPositiveFinite.isObject( new Number( 3.0 ) )\nbool = isPositiveFinite.isObject( new Number( 1.0/0.0 ) )\n","isPositiveInteger":"var bool = isPositiveInteger( 5.0 )\nbool = isPositiveInteger( new Number( 5.0 ) )\nbool = isPositiveInteger( 3.14 )\nbool = isPositiveInteger( -5.0 )\nbool = isPositiveInteger( null )\n","isPositiveInteger.isPrimitive":"var bool = isPositiveInteger.isPrimitive( 3.0 )\nbool = isPositiveInteger.isPrimitive( new Number( 3.0 ) )\n","isPositiveInteger.isObject":"var bool = isPositiveInteger.isObject( 3.0 )\nbool = isPositiveInteger.isObject( new Number( 3.0 ) )\n","isPositiveIntegerArray":"var bool = isPositiveIntegerArray( [ 3.0, new Number(3.0) ] )\nbool = isPositiveIntegerArray( [ 3.0, '3.0' ] )\n","isPositiveIntegerArray.primitives":"var bool = isPositiveIntegerArray.primitives( [ 1.0, 10.0 ] )\nbool = isPositiveIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isPositiveIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n","isPositiveIntegerArray.objects":"var bool = isPositiveIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isPositiveIntegerArray.objects( [ 1.0, 2.0, 10.0 ] )\nbool = isPositiveIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n","isPositiveNumber":"var bool = isPositiveNumber( 5.0 )\nbool = isPositiveNumber( new Number( 5.0 ) )\nbool = isPositiveNumber( 3.14 )\nbool = isPositiveNumber( -5.0 )\nbool = isPositiveNumber( null )\n","isPositiveNumber.isPrimitive":"var bool = isPositiveNumber.isPrimitive( 3.0 )\nbool = isPositiveNumber.isPrimitive( new Number( 3.0 ) )\n","isPositiveNumber.isObject":"var bool = isPositiveNumber.isObject( 3.0 )\nbool = isPositiveNumber.isObject( new Number( 3.0 ) )\n","isPositiveNumberArray":"var bool = isPositiveNumberArray( [ 3.0, new Number(3.0) ] )\nbool = isPositiveNumberArray( [ 3.0, '3.0' ] )\n","isPositiveNumberArray.primitives":"var bool = isPositiveNumberArray.primitives( [ 1.0, 10.0 ] )\nbool = isPositiveNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isPositiveNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n","isPositiveNumberArray.objects":"var bool = isPositiveNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isPositiveNumberArray.objects( [ 1.0, 2.0, 10.0 ] )\nbool = isPositiveNumberArray.objects( [ 3.0, new Number(1.0) ] )\n","isPositiveZero":"var bool = isPositiveZero( 0.0 )\nbool = isPositiveZero( new Number( 0.0 ) )\nbool = isPositiveZero( -3.14 )\nbool = isPositiveZero( -0.0 )\nbool = isPositiveZero( null )\n","isPositiveZero.isPrimitive":"var bool = isPositiveZero.isPrimitive( 0.0 )\nbool = isPositiveZero.isPrimitive( new Number( 0.0 ) )\n","isPositiveZero.isObject":"var bool = isPositiveZero.isObject( 0.0 )\nbool = isPositiveZero.isObject( new Number( 0.0 ) )\n","isPrime":"var bool = isPrime( 5.0 )\nbool = isPrime( new Number( 5.0 ) )\nbool = isPrime( 3.14 )\nbool = isPrime( -5.0 )\nbool = isPrime( null )\n","isPrime.isPrimitive":"var bool = isPrime.isPrimitive( 5.0 )\nbool = isPrime.isPrimitive( new Number( 5.0 ) )\n","isPrime.isObject":"var bool = isPrime.isObject( 5.0 )\nbool = isPrime.isObject( new Number( 5.0 ) )\n","isPrimitive":"var bool = isPrimitive( true )\nbool = isPrimitive( {} )\n","isPrimitiveArray":"var bool = isPrimitiveArray( [ '3', 2, null ] )\nbool = isPrimitiveArray( [ {}, 2, 1 ] )\nbool = isPrimitiveArray( [ new String('abc'), '3.0' ] )\n","isPRNGLike":"var bool = isPRNGLike( base.random.randu )\nbool = isPRNGLike( [ 1, 2, 3, 4 ] )\nbool = isPRNGLike( 3.14 )\nbool = isPRNGLike( {} )\n","isProbability":"var bool = isProbability( 0.5 )\nbool = isProbability( new Number( 0.5 ) )\nbool = isProbability( 3.14 )\nbool = isProbability( -5.0 )\nbool = isProbability( null )\n","isProbability.isPrimitive":"var bool = isProbability.isPrimitive( 0.3 )\nbool = isProbability.isPrimitive( new Number( 0.3 ) )\n","isProbability.isObject":"var bool = isProbability.isObject( 0.77 )\nbool = isProbability.isObject( new Number( 0.77 ) )\n","isProbabilityArray":"var bool = isProbabilityArray( [ 0.5, new Number(0.8) ] )\nbool = isProbabilityArray( [ 0.8, 1.2 ] )\nbool = isProbabilityArray( [ 0.8, '0.2' ] )\n","isProbabilityArray.primitives":"var bool = isProbabilityArray.primitives( [ 1.0, 0.0, 0.5 ] )\nbool = isProbabilityArray.primitives( [ 0.3, new Number(0.4) ] )\n","isProbabilityArray.objects":"var bool = isProbabilityArray.objects( [ new Number(0.7), new Number(1.0) ] )\nbool = isProbabilityArray.objects( [ 1.0, 0.0, new Number(0.7) ] )\n","isPropertyKey":"var out = isPropertyKey( 'foo' )\nout = isPropertyKey( 1 )\nout = isPropertyKey( true )\n","isPrototypeOf":"function Foo() { return this; };\nfunction Bar() { return this; };\ninherit( Bar, Foo );\nvar bar = new Bar();\nvar bool = isPrototypeOf( bar, Foo.prototype )\n","isRaggedNestedArray":"var bool = isRaggedNestedArray( [ [ 1, 2, 3 ], [ 4, 5 ] ] )\nbool = isRaggedNestedArray( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\nbool = isRaggedNestedArray( 'beep' )\n","isRangeError":"var bool = isRangeError( new RangeError( 'beep' ) )\nbool = isRangeError( {} )\n","isReadableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadableProperty( obj, 'boop' )\nbool = isReadableProperty( obj, 'beep' )\n","isReadablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadablePropertyIn( obj, 'boop' )\nbool = isReadablePropertyIn( obj, 'beep' )\n","isReadOnlyProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadOnlyProperty( obj, 'boop' )\nbool = isReadOnlyProperty( obj, 'beep' )\n","isReadOnlyPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadOnlyPropertyIn( obj, 'boop' )\nbool = isReadOnlyPropertyIn( obj, 'beep' )\n","isReadWriteProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadWriteProperty( obj, 'boop' )\nbool = isReadWriteProperty( obj, 'beep' )\n","isReadWritePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadWritePropertyIn( obj, 'boop' )\nbool = isReadWritePropertyIn( obj, 'beep' )\n","isReferenceError":"var bool = isReferenceError( new ReferenceError( 'beep' ) )\nbool = isReferenceError( {} )\n","isRegExp":"var bool = isRegExp( /\\.+/ )\nbool = isRegExp( {} )\n","isRegExpString":"var bool = isRegExpString( '/beep/' )\nbool = isRegExpString( 'beep' )\nbool = isRegExpString( '' )\nbool = isRegExpString( null )\n","isRelativePath":"var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\nbool = isRelativePath( './foo/bar/baz' )\n","isRelativePath.posix":"var bool = isRelativePath.posix( './foo/bar/baz' )\nbool = isRelativePath.posix( '/foo/../bar/baz' )\n","isRelativePath.win32":"var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\nbool = isRelativePath( 'C:\\\\foo\\\\..\\\\bar\\\\baz' )\n","isRelativeURI":"var bool = isRelativeURI( '/images/example.png' )\nbool = isRelativeURI( 'http://www.example.com' )\nbool = isRelativeURI( null )\n","isSafeInteger":"var bool = isSafeInteger( 5.0 )\nbool = isSafeInteger( new Number( 5.0 ) )\nbool = isSafeInteger( 2.0e200 )\nbool = isSafeInteger( -3.14 )\nbool = isSafeInteger( null )\n","isSafeInteger.isPrimitive":"var bool = isSafeInteger.isPrimitive( -3.0 )\nbool = isSafeInteger.isPrimitive( new Number( -3.0 ) )\n","isSafeInteger.isObject":"var bool = isSafeInteger.isObject( 3.0 )\nbool = isSafeInteger.isObject( new Number( 3.0 ) )\n","isSafeIntegerArray":"var arr = [ -3.0, new Number(0.0), 2.0 ];\nvar bool = isSafeIntegerArray( arr )\narr = [ -3.0, '3.0' ];\nbool = isSafeIntegerArray( arr )\n","isSafeIntegerArray.primitives":"var arr = [ -1.0, 10.0 ];\nvar bool = isSafeIntegerArray.primitives( arr )\narr = [ -1.0, 0.0, 5.0 ];\nbool = isSafeIntegerArray.primitives( arr )\narr = [ -3.0, new Number(-1.0) ];\nbool = isSafeIntegerArray.primitives( arr )\n","isSafeIntegerArray.objects":"var arr = [ new Number(1.0), new Number(3.0) ];\nvar bool = isSafeIntegerArray.objects( arr )\narr = [ -1.0, 0.0, 3.0 ];\nbool = isSafeIntegerArray.objects( arr )\narr = [ 3.0, new Number(-1.0) ];\nbool = isSafeIntegerArray.objects( arr )\n","isSameArray":"var x = [ 1.0, 2.0, 3.0 ];\nvar y = [ 1.0, 2.0, 3.0 ];\nvar bool = isSameArray( x, y )\nx = [ NaN, NaN, NaN ];\ny = [ NaN, NaN, NaN ];\nbool = isSameArray( x, y )\n","isSameArrayLike":"var x = [ 1.0, 2.0, 3.0 ];\nvar y = [ 1.0, 2.0, 3.0 ];\nvar bool = isSameArrayLike( x, y )\nx = [ NaN, NaN, NaN ];\ny = [ NaN, NaN, NaN ];\nbool = isSameArrayLike( x, y )\n","isSameComplex64":"var x = new Complex64( 1.0, 2.0 );\nvar y = new Complex64( 1.0, 2.0 );\nvar bool = isSameComplex64( x, y )\nx = new Complex64( NaN, NaN );\ny = new Complex64( NaN, NaN );\nbool = isSameComplex64( x, y )\n","isSameComplex64Array":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar bool = isSameComplex64Array( x, y )\nx = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\ny = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\nbool = isSameComplex64Array( x, y )\n","isSameComplex128":"var x = new Complex128( 1.0, 2.0 );\nvar y = new Complex128( 1.0, 2.0 );\nvar bool = isSameComplex128( x, y )\nx = new Complex128( NaN, NaN );\ny = new Complex128( NaN, NaN );\nbool = isSameComplex128( x, y )\n","isSameComplex128Array":"var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar bool = isSameComplex128Array( x, y )\nx = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\ny = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\nbool = isSameComplex128Array( x, y )\n","isSameDateObject":"var d1 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\nvar d2 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\nvar bool = isSameDateObject( d1, d2 )\nvar d1 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\nvar d2 = new Date( 2024, 11, 31, 23, 59, 59, 78 );\nvar bool = isSameDateObject( d1, d2 )\n","isSameFloat32Array":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nvar bool = isSameFloat32Array( x, y )\nx = new Float32Array( [ NaN, NaN, NaN ] );\ny = new Float32Array( [ NaN, NaN, NaN ] );\nbool = isSameFloat32Array( x, y )\n","isSameFloat64Array":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nvar bool = isSameFloat64Array( x, y )\nx = new Float64Array( [ NaN, NaN, NaN ] );\ny = new Float64Array( [ NaN, NaN, NaN ] );\nbool = isSameFloat64Array( x, y )\n","isSameNativeClass":"var bool = isSameNativeClass( 3.14, new Number( 3.14 ) )\nbool = isSameNativeClass( 'beep', 'boop' )\nbool = isSameNativeClass( {}, [] )\n","isSameType":"var bool = isSameType( true, true )\nbool = isSameType( {}, [] )\nbool = isSameType( 3.12, -3.12 )\nbool = isSameType( 0.0, '0.0' )\n","isSameValue":"var bool = isSameValue( true, true )\nbool = isSameValue( {}, {} )\nbool = isSameValue( -0.0, -0.0 )\nbool = isSameValue( -0.0, 0.0 )\nbool = isSameValue( NaN, NaN )\n","isSameValueZero":"var bool = isSameValueZero( true, true )\nbool = isSameValueZero( {}, {} )\nbool = isSameValueZero( -0.0, -0.0 )\nbool = isSameValueZero( -0.0, 0.0 )\nbool = isSameValueZero( NaN, NaN )\n","isSemVer":"var bool = isSemVer( '1.0.0' )\nbool = isSemVer( '1.0.0-alpha.1' )\nbool = isSemVer( '0.1' )\nbool = isSemVer( null )\n","isSharedArrayBuffer":"var bool = isSharedArrayBuffer( new SharedArrayBuffer( 10 ) )\nbool = isSharedArrayBuffer( [] )\n","isSkewCentrosymmetricMatrix":"var buf = [ 2, 1, -1, -2 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSkewCentrosymmetricMatrix( M )\nbool = isSkewCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSkewCentrosymmetricMatrix( 3.14 )\nbool = isSkewCentrosymmetricMatrix( {} )\n","isSkewPersymmetricMatrix":"var buf = [ 1, 0, 0, -1 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSkewPersymmetricMatrix( M )\nbool = isSkewPersymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSkewPersymmetricMatrix( 3.14 )\nbool = isSkewPersymmetricMatrix( {} )\n","isSkewSymmetricMatrix":"var buf = [ 0, -1, 1, 0 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSkewSymmetricMatrix( M )\nbool = isSkewSymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSkewSymmetricMatrix( 3.14 )\nbool = isSkewSymmetricMatrix( {} )\n","isSlice":"var bool = isSlice( new Slice( 10 ) )\nbool = isSlice( 3.14 )\nbool = isSlice( {} )\n","isSnakecase":"var bool = isSnakecase( 'hello_world' )\nbool = isSnakecase( 'Hello World' )\n","isSquareMatrix":"var buf = [ 0, 0, 0, 0 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSquareMatrix( M )\nbool = isSquareMatrix( [ 1, 2, 3, 4 ] )\nbool = isSquareMatrix( 3.14 )\nbool = isSquareMatrix( {} )\n","isSquareNumber":"var bool = isSquareNumber( 4.0 )\nbool = isSquareNumber( new Number( 4.0 ) )\nbool = isSquareNumber( 3.14 )\nbool = isSquareNumber( -5.0 )\nbool = isSquareNumber( null )\n","isSquareNumber.isPrimitive":"var bool = isSquareNumber.isPrimitive( 4.0 )\nbool = isSquareNumber.isPrimitive( new Number( 4.0 ) )\n","isSquareNumber.isObject":"var bool = isSquareNumber.isObject( 4.0 )\nbool = isSquareNumber.isObject( new Number( 4.0 ) )\n","isSquareTriangularNumber":"var bool = isSquareTriangularNumber( 36.0 )\nbool = isSquareTriangularNumber( new Number( 36.0 ) )\nbool = isSquareTriangularNumber( 3.14 )\nbool = isSquareTriangularNumber( -5.0 )\nbool = isSquareTriangularNumber( null )\n","isSquareTriangularNumber.isPrimitive":"var bool = isSquareTriangularNumber.isPrimitive( 36.0 )\nbool = isSquareTriangularNumber.isPrimitive( new Number( 36.0 ) )\n","isSquareTriangularNumber.isObject":"var bool = isSquareTriangularNumber.isObject( 36.0 )\nbool = isSquareTriangularNumber.isObject( new Number( 36.0 ) )\n","isStartcase":"var bool = isStartcase( 'Beep Boop' )\nbool = isStartcase( 'Beep and Boop' )\n","isStrictEqual":"var bool = isStrictEqual( true, true )\nbool = isStrictEqual( {}, {} )\nbool = isStrictEqual( -0.0, -0.0 )\nbool = isStrictEqual( -0.0, 0.0 )\nbool = isStrictEqual( NaN, NaN )\n","isString":"var bool = isString( 'beep' )\nbool = isString( new String( 'beep' ) )\nbool = isString( 5 )\n","isString.isPrimitive":"var bool = isString.isPrimitive( 'beep' )\nbool = isString.isPrimitive( new String( 'beep' ) )\n","isString.isObject":"var bool = isString.isObject( new String( 'beep' ) )\nbool = isString.isObject( 'beep' )\n","isStringArray":"var bool = isStringArray( [ 'abc', 'def' ] )\nbool = isStringArray( [ 'abc', 123 ] )\n","isStringArray.primitives":"var arr = [ 'abc', 'def' ];\nvar bool = isStringArray.primitives( arr )\narr = [ 'abc', new String( 'def' ) ];\nbool = isStringArray.primitives( arr )\n","isStringArray.objects":"var arr = [ new String( 'ab' ), new String( 'cd' ) ];\nvar bool = isStringArray.objects( arr )\narr = [ new String( 'abc' ), 'def' ];\nbool = isStringArray.objects( arr )\n","isSymbol":"var bool = isSymbol( Symbol( 'beep' ) )\nbool = isSymbol( Object( Symbol( 'beep' ) ) )\nbool = isSymbol( {} )\nbool = isSymbol( null )\nbool = isSymbol( true )\n","isSymbolArray":"var bool = isSymbolArray( [ Symbol( 'beep' ), Symbol( 'boop' ) ] )\nbool = isSymbolArray( Symbol( 'beep' ) )\nbool = isSymbolArray( [] )\nbool = isSymbolArray( {} )\nbool = isSymbolArray( null )\nbool = isSymbolArray( true )\n","isSymbolArray.primitives":"var bool = isSymbolArray.primitives( [ Symbol( 'beep' ) ] )\nbool = isSymbolArray.primitives( [ Object( Symbol( 'beep' ) ) ] )\nbool = isSymbolArray.primitives( [] )\nbool = isSymbolArray.primitives( {} )\nbool = isSymbolArray.primitives( null )\nbool = isSymbolArray.primitives( true )\n","isSymbolArray.objects":"var bool = isSymbolArray.objects( [ Object( Symbol( 'beep' ) ) ] )\nbool = isSymbolArray.objects( [ Symbol( 'beep' ) ] )\nbool = isSymbolArray.objects( [] )\nbool = isSymbolArray.objects( {} )\nbool = isSymbolArray.objects( null )\nbool = isSymbolArray.objects( true )\n","isSymmetricMatrix":"var buf = [ 0, 1, 1, 2 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSymmetricMatrix( M )\nbool = isSymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSymmetricMatrix( 3.14 )\nbool = isSymmetricMatrix( {} )\n","isSyntaxError":"var bool = isSyntaxError( new SyntaxError( 'beep' ) )\nbool = isSyntaxError( {} )\n","isTriangularNumber":"var bool = isTriangularNumber( 36.0 )\nbool = isTriangularNumber( new Number( 36.0 ) )\nbool = isTriangularNumber( 3.14 )\nbool = isTriangularNumber( -5.0 )\nbool = isTriangularNumber( null )\n","isTriangularNumber.isPrimitive":"var bool = isTriangularNumber.isPrimitive( 36.0 )\nbool = isTriangularNumber.isPrimitive( new Number( 36.0 ) )\n","isTriangularNumber.isObject":"var bool = isTriangularNumber.isObject( 36.0 )\nbool = isTriangularNumber.isObject( new Number( 36.0 ) )\n","isTruthy":"var bool = isTruthy( true )\nbool = isTruthy( {} )\nbool = isTruthy( [] )\nbool = isTruthy( false )\nbool = isTruthy( '' )\nbool = isTruthy( 0 )\nbool = isTruthy( null )\nbool = isTruthy( void 0 )\nbool = isTruthy( NaN )\n","isTruthyArray":"var bool = isTruthyArray( [ {}, [] ] )\nbool = isTruthyArray( [ null, '' ] )\nbool = isTruthyArray( [] )\n","isTypedArray":"var bool = isTypedArray( new Int8Array( 10 ) )\n","isTypedArrayLength":"var bool = isTypedArrayLength( 5 )\nbool = isTypedArrayLength( 2.0e200 )\nbool = isTypedArrayLength( -3.14 )\nbool = isTypedArrayLength( null )\n","isTypedArrayLike":"var bool = isTypedArrayLike( new Int16Array() )\nbool = isTypedArrayLike({\n'length': 10,\n'byteOffset': 0,\n'byteLength': 10,\n'BYTES_PER_ELEMENT': 4\n })\n","isTypeError":"var bool = isTypeError( new TypeError( 'beep' ) )\nbool = isTypeError( {} )\n","isUint8Array":"var bool = isUint8Array( new Uint8Array( 10 ) )\nbool = isUint8Array( [] )\n","isUint8ClampedArray":"var bool = isUint8ClampedArray( new Uint8ClampedArray( 10 ) )\nbool = isUint8ClampedArray( [] )\n","isUint16Array":"var bool = isUint16Array( new Uint16Array( 10 ) )\nbool = isUint16Array( [] )\n","isUint32Array":"var bool = isUint32Array( new Uint32Array( 10 ) )\nbool = isUint32Array( [] )\n","isUNCPath":"var bool = isUNCPath( '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz' )\nbool = isUNCPath( '/foo/bar/baz' )\n","isUndefined":"var bool = isUndefined( void 0 )\nbool = isUndefined( null )\n","isUndefinedOrNull":"var bool = isUndefinedOrNull( void 0 )\nbool = isUndefinedOrNull( null )\nbool = isUndefinedOrNull( false )\n","isUnityProbabilityArray":"var bool = isUnityProbabilityArray( [ 0.25, 0.5, 0.25 ] )\nbool = isUnityProbabilityArray( new Uint8Array( [ 0, 1 ] ) )\nbool = isUnityProbabilityArray( [ 0.4, 0.4, 0.4 ] )\nbool = isUnityProbabilityArray( [ 3.14, 0.0 ] )\n","isUppercase":"var bool = isUppercase( 'HELLO' )\nbool = isUppercase( 'World' )\n","isURI":"var bool = isURI( 'http://google.com' )\nbool = isURI( 'http://localhost/' )\nbool = isURI( 'http://example.w3.org/path%20with%20spaces.html' )\nbool = isURI( 'ftp://ftp.is.co.za/rfc/rfc1808.txt' )\nbool = isURI( '' )\nbool = isURI( 'foo@bar' )\nbool = isURI( '://foo/' )\nbool = isURI( 'http://<foo>' )\nbool = isURI( 'http:////foo.html' )\nbool = isURI( 'http://example.w3.org/%a' )\n","isURIError":"var bool = isURIError( new URIError( 'beep' ) )\nbool = isURIError( {} )\n","isVectorLike":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isVectorLike( M )\nbool = isVectorLike( [ 1, 2, 3, 4 ] )\nbool = isVectorLike( 3.14 )\nbool = isVectorLike( {} )\n","isWebAssemblyMemory":"var bool = isWebAssemblyMemory( {} )\n","isWellFormedString":"var bool = isWellFormedString( '' )\nbool = isWellFormedString( new String( '' ) )\nbool = isWellFormedString( '\\uDBFF' )\nbool = isWellFormedString( '\\uDBFFFF\\uDBFF' )\nbool = isWellFormedString( [] )\nbool = isWellFormedString( '-5' )\nbool = isWellFormedString( null )\n","isWellFormedString.isPrimitive":"var bool = isWellFormedString.isPrimitive( '' )\nbool = isWellFormedString.isPrimitive( new String( '' ) )\n","isWellFormedString.isObject":"var bool = isWellFormedString.isObject( '' )\nbool = isWellFormedString.isObject( new String( '' ) )\n","isWhitespace":"var bool = isWhitespace( '       ' )\nbool = isWhitespace( 'abcdef' )\nbool = isWhitespace( '' )\n","isWritableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = false;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isWritableProperty( obj, 'boop' )\nbool = isWritableProperty( obj, 'beep' )\n","isWritablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = false;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isWritablePropertyIn( obj, 'boop' )\nbool = isWritablePropertyIn( obj, 'beep' )\n","isWriteOnlyProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isWriteOnlyProperty( obj, 'boop' )\nbool = isWriteOnlyProperty( obj, 'beep' )\n","isWriteOnlyPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isWriteOnlyPropertyIn( obj, 'boop' )\nbool = isWriteOnlyPropertyIn( obj, 'beep' )\n","iterAbs":"var it = iterAbs( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterAbs2":"var it = iterAbs2( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterAcos":"var it = iterAcos( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcosh":"var it = iterAcosh( random.iterators.uniform( 1.0, 10.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcot":"var it = iterAcot( random.iterators.uniform( -5.0, 5.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcoth":"var it = iterAcoth( random.iterators.uniform( 1.0, 10.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcovercos":"var it = iterAcovercos( random.iterators.uniform( -2.0, 0.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcoversin":"var it = iterAcoversin( random.iterators.uniform( 0.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAdd":"var it1 = array2iterator( [ 1.0, 2.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nvar it = iterAdd( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterAdvance":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar it = iterAdvance( arr, 4 );\nvar v = it.next().value\nvar bool = it.next().done\n","iterAhavercos":"var it = iterAhavercos( random.iterators.uniform( 0.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAhaversin":"var it = iterAhaversin( random.iterators.uniform( 0.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAny":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar bool = iterAny( arr )\n","iterAnyBy":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nfunction fcn( v ) { return ( v === 1 ); };\nvar bool = iterAnyBy( arr, fcn )\n","iterAsin":"var it = iterAsin( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAsinh":"var it = iterAsinh( random.iterators.uniform( -2.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAtan":"var it = iterAtan( random.iterators.uniform( -2.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAtan2":"var x = random.iterators.uniform( -2.0, 2.0 );\nvar y = random.iterators.uniform( -2.0, 2.0 );\nvar it = iterAtan2( y, x );\nvar r = it.next().value\nr = it.next().value\n","iterAtanh":"var it = iterAtanh( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterator2array":"var opts = { 'iter': 10 };\nvar arr = iterator2array( random.iterators.randu( opts ) )\n","iterator2arrayview":"var it = random.iterators.randu({ 'iter': 10 });\nvar out = new Float64Array( 20 );\nvar arr = iterator2arrayview( it, out, 5, 15 )\n","iterator2arrayviewRight":"var it = random.iterators.randu({ 'iter': 10 });\nvar out = new Float64Array( 20 );\nvar arr = iterator2arrayviewRight( it, out, 5, 15 )\n","iteratorStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar it = random.iterators.randu( opts );\nvar s = iteratorStream( it );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","iteratorStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = iteratorStream.factory( opts );\n","iteratorStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar it = random.iterators.randu( opts );\nvar s = iteratorStream.objectMode( it );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","IteratorSymbol":"var s = IteratorSymbol\n","iterAvercos":"var it = iterAvercos( random.iterators.uniform( -2.0, 0.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAversin":"var it = iterAversin( random.iterators.uniform( 0.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterawgn":"var src = iterSineWave();\nvar it = iterawgn( src, 0.5 );\nvar v = it.next().value\nv = it.next().value\n","iterawln":"var src = iterSineWave();\nvar it = iterawln( src, 0.5 );\nvar v = it.next().value\nv = it.next().value\n","iterawun":"var src = iterSineWave();\nvar it = iterawun( src, 0.5 );\nvar v = it.next().value\nv = it.next().value\n","iterBartlettHannPulse":"var it = iterBartlettHannPulse();\nvar v = it.next().value\nv = it.next().value\n","iterBartlettPulse":"var it = iterBartlettPulse();\nvar v = it.next().value\nv = it.next().value\n","iterBesselj0":"var it = iterBesselj0( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBesselj1":"var it = iterBesselj1( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBessely0":"var it = iterBessely0( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBessely1":"var it = iterBessely1( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBeta":"var x = random.iterators.uniform( 0.0, 2.0 );\nvar y = random.iterators.uniform( 0.0, 2.0 );\nvar it = iterBeta( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterBetaln":"var x = random.iterators.uniform( 0.0, 2.0 );\nvar y = random.iterators.uniform( 0.0, 2.0 );\nvar it = iterBetaln( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterBinet":"var it = iterBinet( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCbrt":"var it = iterCbrt( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCeil":"var it = iterCeil( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCeil2":"var it = iterCeil2( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCeil10":"var it = iterCeil10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterCompositesSeq":"var it = iterCompositesSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterConcat":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = array2iterator( [ 3, 4 ] );\nvar it = iterConcat( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterConstant":"var it = iterConstant( 3.14 );\nvar v = it.next().value\nv = it.next().value\n","iterContinuedFraction":"var terms = array2iterator( [ 3, 4, 12, 4 ] );\nvar v = iterContinuedFraction( terms )\n","iterContinuedFractionSeq":"var it = iterContinuedFractionSeq( 3.245 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\nit = iterContinuedFractionSeq( 3.245, { 'returns': 'convergents' } );\nv = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nbool = it.next().done\n","iterCos":"var it = iterCos( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCosh":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterCosh( r );\nvar v = it.next().value\nv = it.next().value\n","iterCosineWave":"var it = iterCosineWave();\nvar v = it.next().value\nv = it.next().value\n","iterCosm1":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterCosm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterCospi":"var it = iterCospi( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCounter":"var it = iterCounter( random.iterators.randu() );\nvar v = it.next().value\nv = it.next().value\n","iterCovercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterCovercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterCoversin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterCoversin( r );\nvar v = it.next().value\nv = it.next().value\n","iterCubesSeq":"var it = iterCubesSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","itercugmean":"var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\nvar it = itercugmean( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itercuhmean":"var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\nvar it = itercuhmean( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itercumax":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumax( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumaxabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumaxabs( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumean":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumean( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumeanabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumeanabs( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumeanabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumeanabs2( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumidrange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumidrange( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itercumin":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumin( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercuminabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercuminabs( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercuprod":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercuprod( arr );\nvar p = it.next().value\np = it.next().value\np = it.next().value\np = it.next().value\n","itercurange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercurange( arr );\nvar r = it.next().value\nr = it.next().value\nr = it.next().value\nr = it.next().value\n","itercusum":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercusum( arr );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itercusumabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercusumabs( arr );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itercusumabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercusumabs2( arr );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","iterDatespace":"var t1 = new Date();\nvar it = iterDatespace( t1, new Date( t1.getTime()+86400000 ) );\nvar v = it.next().value\nv = it.next().value\n","iterDedupe":"var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\nvar it = iterDedupe( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterDedupeBy":"var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\nfunction fcn( v ) { return v; };\nvar it = iterDedupeBy( arr, fcn );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterDeg2rad":"var r = random.iterators.uniform( -360.0, 360.0 );\nvar it = iterDeg2rad( r );\nvar v = it.next().value\nv = it.next().value\n","iterDigamma":"var r = random.iterators.uniform( 0.01, 5.0 );\nvar it = iterDigamma( r );\nvar v = it.next().value\nv = it.next().value\n","iterDiracComb":"var it = iterDiracComb();\nvar v = it.next().value\nv = it.next().value\n","iterDiracDelta":"var it = iterDiracDelta( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterDivide":"var it1 = array2iterator( [ 3.0, 2.0 ] );\nvar it2 = array2iterator( [ 1.0, 4.0 ] );\nvar it = iterDivide( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterDoWhileEach":"function predicate( v ) { return v === v };\nfunction f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterDoWhileEach( random.iterators.randu(), predicate, f );\nvar r = it.next().value\nr = it.next().value\n","iterEllipe":"var r = random.iterators.uniform( -1.0, 1.0 );\nvar it = iterEllipe( r );\nvar v = it.next().value\nv = it.next().value\n","iterEllipk":"var r = random.iterators.uniform( -1.0, 1.0 );\nvar it = iterEllipk( r );\nvar v = it.next().value\nv = it.next().value\n","iterEmpty":"var it = iterEmpty();\nvar bool = it.next().done\n","iterErf":"var it = iterErf( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterErfc":"var it = iterErfc( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterErfcinv":"var it = iterErfcinv( random.iterators.uniform( 0.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterErfinv":"var it = iterErfinv( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterEta":"var it = iterEta( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterEvenIntegersSeq":"var it = iterEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterEvery":"var arr = array2iterator( [ 1, 1, 1, 1, 0 ] );\nvar bool = iterEvery( arr )\n","iterEveryBy":"var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\nfunction fcn( v ) { return ( v > 0 ); };\nvar bool = iterEveryBy( arr, fcn )\n","iterExp":"var it = iterExp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterExp2":"var r = random.iterators.uniform( -50.0, 50.0 );\nvar it = iterExp2( r );\nvar v = it.next().value\nv = it.next().value\n","iterExp10":"var r = random.iterators.uniform( -50.0, 50.0 );\nvar it = iterExp10( r );\nvar v = it.next().value\nv = it.next().value\n","iterExpit":"var r = random.iterators.uniform( 0.0, 1.0 );\nvar it = iterExpit( r );\nvar v = it.next().value\nv = it.next().value\n","iterExpm1":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterExpm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterExpm1rel":"var r = random.iterators.uniform( -50.0, 50.0 );\nvar it = iterExpm1rel( r );\nvar v = it.next().value\nv = it.next().value\n","iterFactorial":"var it = iterFactorial( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterFactorialln":"var it = iterFactorialln( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterFactorialsSeq":"var it = iterFactorialsSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterFibonacciSeq":"var it = iterFibonacciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterFifthPowersSeq":"var it = iterFifthPowersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterFill":"var it = iterFill( random.iterators.randu(), 3.14, 0, 2 );\nvar r = it.next().value\nr = it.next().value\nr = it.next().value\n","iterFilter":"function f( v ) { return ( v > 2 ); };\nvar it1 = array2iterator( [ 1, 3, 2, 4 ] );\nvar it2 = iterFilter( it1, f );\nvar v = it2.next().value\nv = it2.next().value\n","iterFilterMap":"function f( v ) { if ( v > 2 ) { return v * 10 }; };\nvar it1 = array2iterator( [ 1, 3, 2, 4 ] );\nvar it2 = iterFilterMap( it1, f );\nvar v = it2.next().value\nv = it2.next().value\n","iterFirst":"var arr = array2iterator( [ 1, 0, 0, 0, 0 ] );\nvar v = iterFirst( arr )\n","iterFlatTopPulse":"var it = iterFlatTopPulse();\nvar v = it.next().value\nv = it.next().value\n","iterFloor":"var it = iterFloor( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterFloor2":"var it = iterFloor2( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterFloor10":"var it = iterFloor10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterFlow":"var o = {};\no.head = iterHead;\no.some = iterSome;\nvar fiter = iterFlow( o )\n","iterForEach":"function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterForEach( random.iterators.randu(), f );\nvar r = it.next().value\nr = it.next().value\n","iterFourthPowersSeq":"var it = iterFourthPowersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterFresnelc":"var r = random.iterators.uniform( 0.0, 10.0 );\nvar it = iterFresnelc( r );\nvar v = it.next().value\nv = it.next().value\n","iterFresnels":"var r = random.iterators.uniform( 0.0, 10.0 );\nvar it = iterFresnels( r );\nvar v = it.next().value\nv = it.next().value\n","iterGamma":"var it = iterGamma( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterGamma1pm1":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterGamma1pm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterGammaln":"var it = iterGammaln( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterHacovercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHacovercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterHacoversin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHacoversin( r );\nvar v = it.next().value\nv = it.next().value\n","iterHannPulse":"var it = iterHannPulse();\nvar v = it.next().value\nv = it.next().value\n","iterHavercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHavercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterHaversin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHaversin( r );\nvar v = it.next().value\nv = it.next().value\n","iterHead":"var it = iterHead( random.iterators.randu(), 5 );\nvar r = it.next().value\nr = it.next().value\n","iterIncrspace":"var it = iterIncrspace( 0, 101, 2 );\nvar v = it.next().value\nv = it.next().value\n","iterIntegersSeq":"var it = iterIntegersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterIntersection":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\nvar it = iterIntersection( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterIntersectionByHash":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\nfunction f( v ) { return v.toString(); };\nvar it = iterIntersectionByHash( it1, it2, f );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterInv":"var it = iterInv( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLanczosPulse":"var it = iterLanczosPulse();\nvar v = it.next().value\nv = it.next().value\n","iterLast":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar v = iterLast( arr )\n","iterLength":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar len = iterLength( arr )\n","iterLinspace":"var it = iterLinspace( 0, 99, 100 );\nvar v = it.next().value\nv = it.next().value\n","iterLn":"var it = iterLn( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog":"var x = random.iterators.uniform( 0.0, 100.0 );\nvar y = random.iterators.uniform( 0.0, 10.0 );\nvar it = iterLog( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterLog1mexp":"var it = iterLog1mexp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog1p":"var it = iterLog1p( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog1pexp":"var it = iterLog1pexp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog2":"var it = iterLog2( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog10":"var it = iterLog10( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLogit":"var r = random.iterators.uniform( 0.0, 1.0 );\nvar it = iterLogit( r );\nvar v = it.next().value\nv = it.next().value\n","iterLogspace":"var it = iterLogspace( 0, 3, 4 );\nvar v = it.next().value\nv = it.next().value\n","iterLucasSeq":"var it = iterLucasSeq();\nvar v = it.next().value\nv = it.next().value\n","iterMap":"function f( v ) { return v * 10.0; };\nvar it = iterMap( random.iterators.randu(), f );\nvar r = it.next().value\nr = it.next().value\n","iterMapN":"var it1 = array2iterator( [ 1.0, 2.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nfunction fcn( x, y ) { return x + y; };\nvar it = iterMapN( it1, it2, fcn );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","itermax":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar m = itermax( arr )\n","itermaxabs":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar m = itermaxabs( arr )\n","itermean":"var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = itermean( arr )\n","itermeanabs":"var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\nvar m = itermeanabs( arr )\n","itermeanabs2":"var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\nvar m = itermeanabs2( arr )\n","itermidrange":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar v = itermidrange( arr )\n","itermin":"var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\nvar m = itermin( arr )\n","iterminabs":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar m = iterminabs( arr )\n","itermmax":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmax( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmaxabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmaxabs( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmean":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmean( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmeanabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmeanabs( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmeanabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmeanabs2( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmidrange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmidrange( arr, 3 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itermmin":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmin( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermminabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermminabs( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","iterMod":"var it1 = array2iterator( [ 3.0, 2.0 ] );\nvar it2 = array2iterator( [ 1.0, 4.0 ] );\nvar it = iterMod( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","itermprod":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermprod( arr, 3 );\nvar p = it.next().value\np = it.next().value\np = it.next().value\np = it.next().value\n","itermrange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermrange( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermsum":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermsum( arr, 3 );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itermsumabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermsumabs( arr, 3 );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itermsumabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermsumabs2( arr, 3 );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","iterMultiply":"var it1 = array2iterator( [ 1.0, 2.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nvar it = iterMultiply( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterNegaFibonacciSeq":"var it = iterNegaFibonacciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegaLucasSeq":"var it = iterNegaLucasSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegativeEvenIntegersSeq":"var it = iterNegativeEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegativeIntegersSeq":"var it = iterNegativeIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegativeOddIntegersSeq":"var it = iterNegativeOddIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNone":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar bool = iterNone( arr )\n","iterNoneBy":"var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\nfunction fcn( v ) { return ( v <= 0 ); };\nvar bool = iterNoneBy( arr, fcn )\n","iterNonFibonacciSeq":"var it = iterNonFibonacciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonNegativeEvenIntegersSeq":"var it = iterNonNegativeEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonNegativeIntegersSeq":"var it = iterNonNegativeIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonPositiveEvenIntegersSeq":"var it = iterNonPositiveEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonPositiveIntegersSeq":"var it = iterNonPositiveIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonSquaresSeq":"var it = iterNonSquaresSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterNth":"var arr = array2iterator( [ 0, 0, 1, 0, 0 ] );\nvar v = iterNth( arr, 3 )\n","iterOddIntegersSeq":"var it = iterOddIntegersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterPeriodicSinc":"var it = iterPeriodicSinc( 7 );\nvar v = it.next().value\nv = it.next().value\n","iterPipeline":"var it1 = iterThunk( iterHead, 100 );\nfunction f( r ) { return ( r > 0.95 ); };\nvar it2 = iterThunk( iterSomeBy, 5, f );\nvar p = iterPipeline( it1, it2 );\nvar bool = p( random.iterators.randu() )\n","iterPop":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterPop( it1 );\nvar v = it2.next().value\nvar bool = it2.next().done\n","iterPositiveEvenIntegersSeq":"var it = iterPositiveEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterPositiveIntegersSeq":"var it = iterPositiveIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterPositiveOddIntegersSeq":"var it = iterPositiveOddIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterPow":"var x = random.iterators.uniform( 0.0, 2.0 );\nvar y = random.iterators.uniform( -2.0, 2.0 );\nvar it = iterPow( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterPrimesSeq":"var it = iterPrimesSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterprod":"var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar s = iterprod( arr )\n","iterPulse":"var it = iterPulse();\nvar v = it.next().value\nv = it.next().value\n","iterPush":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterPush( it1, 3, 4 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterRad2deg":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterRad2deg( r );\nvar v = it.next().value\nv = it.next().value\n","iterRamp":"var it = iterRamp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterrange":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar v = iterrange( arr )\n","iterReject":"function f( v ) { return ( v > 2 ); };\nvar it1 = array2iterator( [ 1, 3, 2, 4 ] );\nvar it2 = iterReject( it1, f );\nvar v = it2.next().value\nv = it2.next().value\n","iterReplicate":"var it1 = array2iterator( [ 1, 2, 3, 4 ] );\nvar it2 = iterReplicate( it1, 2 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\n","iterReplicateBy":"var it1 = array2iterator( [ 1, 2, 3, 4 ] );\nfunction f( v, i ) { return i + 1; };\nvar it2 = iterReplicateBy( it1, f );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\n","iterRound":"var it = iterRound( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterRound2":"var it = iterRound2( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterRound10":"var it = iterRound10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterRsqrt":"var it = iterRsqrt( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSawtoothWave":"var it = iterSawtoothWave();\nvar v = it.next().value\nv = it.next().value\n","iterShift":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterShift( it1 );\nvar v = it2.next().value\nvar bool = it2.next().done\n","iterSignum":"var it = iterSignum( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSin":"var it = iterSin( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSinc":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterSinc( r );\nvar v = it.next().value\nv = it.next().value\n","iterSineWave":"var it = iterSineWave();\nvar v = it.next().value\nv = it.next().value\n","iterSinh":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterSinh( r );\nvar v = it.next().value\nv = it.next().value\n","iterSinpi":"var it = iterSinpi( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSlice":"var it = iterSlice( random.iterators.randu(), 5, 10 );\nvar r = it.next().value\nr = it.next().value\n","iterSome":"var arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\nvar bool = iterSome( arr, 3 )\n","iterSomeBy":"var arr = array2iterator( [ 1, 1, 0, 0, 1 ] );\nfunction fcn( v ) { return ( v > 0 ); };\nvar bool = iterSomeBy( arr, 3, fcn )\n","iterSpence":"var r = random.iterators.uniform( 0.0, 100.0 );\nvar it = iterSpence( r );\nvar v = it.next().value\nv = it.next().value\n","iterSqrt":"var it = iterSqrt( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSqrt1pm1":"var r = random.iterators.uniform( 0.0, 100.0 );\nvar it = iterSqrt1pm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterSquaredTriangularSeq":"var it = iterSquaredTriangularSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterSquaresSeq":"var it = iterSquaresSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterSquareWave":"var it = iterSquareWave();\nvar v = it.next().value\nv = it.next().value\n","iterstdev":"var arr = array2iterator( [ 2.0, -5.0 ] );\nvar m = iterstdev( arr )\n","iterStep":"var it = iterStep( 0, 2, 10 );\nvar v = it.next().value\nv = it.next().value\n","iterStrided":"var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\nvar it = iterStrided( arr, 2, 1 );\nvar r = it.next().value\nr = it.next().value\n","iterStridedBy":"var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\nfunction stride( v, i ) { return (i % 10)+1; };\nvar it = iterStridedBy( arr, stride );\nvar r = it.next().value\nr = it.next().value\nr = it.next().value\n","iterSubtract":"var it1 = array2iterator( [ 1.0, 5.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nvar it = iterSubtract( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","itersum":"var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar s = itersum( arr )\n","itersumabs":"var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\nvar s = itersumabs( arr )\n","itersumabs2":"var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\nvar s = itersumabs2( arr )\n","iterTan":"var r = random.iterators.uniform( -1.57, 1.57 );\nvar it = iterTan( r );\nvar v = it.next().value\nv = it.next().value\n","iterTanh":"var r = random.iterators.uniform( -4.0, 4.0 );\nvar it = iterTanh( r );\nvar v = it.next().value\nv = it.next().value\n","iterThunk":"var fcn = iterThunk( iterSome, 3 );\nvar arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\nvar bool = fcn( arr )\n","iterTriangleWave":"var it = iterTriangleWave();\nvar v = it.next().value\nv = it.next().value\n","iterTriangularSeq":"var it = iterTriangularSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterTribonnaciSeq":"var it = iterTribonnaciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterTrigamma":"var r = random.iterators.uniform( 0.01, 50.0 );\nvar it = iterTrigamma( r );\nvar v = it.next().value\nv = it.next().value\n","iterTrunc":"var it = iterTrunc( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterTrunc2":"var it = iterTrunc2( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterTrunc10":"var it = iterTrunc10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterUnion":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\nvar it = iterUnion( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterUnique":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = iterUnique( it1 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUniqueBy":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nfunction f( a, b ) { return ( a !== b ); };\nvar it2 = iterUniqueBy( it1, f );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUniqueByHash":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nfunction f( v ) { return v.toString(); };\nvar it2 = iterUniqueByHash( it1, f );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUnitspace":"var it = iterUnitspace( 0, 99 );\nvar v = it.next().value\nv = it.next().value\n","iterUnshift":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterUnshift( it1, 3, 4 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUntilEach":"function predicate( v ) { return v !== v };\nfunction f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterUntilEach( random.iterators.randu(), predicate, f );\nvar r = it.next().value\nr = it.next().value\n","itervariance":"var arr = array2iterator( [ 2.0, -5.0 ] );\nvar s2 = itervariance( arr )\n","iterVercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterVercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterVersin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterVersin( r );\nvar v = it.next().value\nv = it.next().value\n","iterWhileEach":"function predicate( v ) { return v === v };\nfunction f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterWhileEach( random.iterators.randu(), predicate, f );\nvar r = it.next().value\nr = it.next().value\n","iterZeta":"var r = random.iterators.uniform( 1.1, 50.0 );\nvar it = iterZeta( r );\nvar v = it.next().value\nv = it.next().value\n","joinStream":"var s = joinStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","joinStream.factory":"var opts = { 'highWaterMark': 64 };\nvar createStream = joinStream.factory( opts );\nvar s = createStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","joinStream.objectMode":"var s = joinStream.objectMode();\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","kde2d":"var x = [ 1, 3, 5, 6, 21, 23, 16, 17, 20, 10 ];\nvar y = [ 0.40, 0.20, 0.20, 0.15, 0.05, 0.55, 0.6, 0.33, 0.8, 0.41 ];\nvar out = kde2d( x, y )\n","kebabcase":"var out = kebabcase( 'Hello World!' )\nout = kebabcase( 'I am a tiny little teapot' )\n","keyBy":"function toKey( v ) { return v.a; };\nvar arr = [ { 'a': 1 }, { 'a': 2 } ];\nkeyBy( arr, toKey )\n","keyByRight":"function toKey( v ) { return v.a; };\nvar arr = [ { 'a': 1 }, { 'a': 2 } ];\nkeyByRight( arr, toKey )\n","keysIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = keysIn( obj )\n","kruskalTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = kruskalTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = kruskalTest( arr, { 'groups': groups } )\n","kstest":"var rnorm = base.random.normal.factory({ 'seed': 4839 } );\nvar x = new Array( 100 );\nfor ( var i = 0; i < 100; i++ ) { x[ i ] = rnorm( 3.0, 1.0 ); }\nvar out = kstest( x, 'normal', 0.0, 1.0 )\nout = kstest( x, 'normal', 3.0, 1.0 )\nrunif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } )\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\nout = kstest( x, 'uniform', 0.0, 1.0 )\nout.print()\nout = kstest( x, 'uniform', 0.0, 1.0, { 'alpha': 0.1 } )\nrunif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } );\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\nout = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'less' } )\nout = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'greater' } )\nx = [ 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 ];\nout = kstest( x, 'uniform', 0.0, 1.0, { 'sorted': true } )\n","last":"var out = last( 'beep' )\nout = last( 'Boop', 2 )\nout = last( 'foo bar', 3 )\n","leveneTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = leveneTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = leveneTest( arr, { 'groups': groups } )\n","LinkedList":"var list = LinkedList();\nlist.push( 'foo' ).push( 'bar' );\nlist.length\nlist.pop()\nlist.length\nlist.pop()\nlist.length\n","linspace":"var arr = linspace( 0.0, 100.0, 6 )\narr = linspace( 0.0, 100.0, 5, { 'endpoint': false } )\narr = linspace( 0.0, 100.0, 6, { 'dtype': 'generic' } )\n","linspace.assign":"var arr = [ 0, 0, 0, 0, 0, 0 ];\nvar out = linspace.assign( 0, 100, arr )\nvar bool = ( arr === out )\narr = [ 0, 0, 0, 0, 0 ];\nout = linspace.assign( 0, 100, arr, { 'endpoint': false } )\n","LIU_NEGATIVE_OPINION_WORDS_EN":"var list = LIU_NEGATIVE_OPINION_WORDS_EN()\n","LIU_POSITIVE_OPINION_WORDS_EN":"var list = LIU_POSITIVE_OPINION_WORDS_EN()\n","LN_HALF":"LN_HALF\n","LN_PI":"LN_PI\n","LN_SQRT_TWO_PI":"LN_SQRT_TWO_PI\n","LN_TWO_PI":"LN_TWO_PI\n","LN2":"LN2\n","LN10":"LN10\n","LOG2E":"LOG2E\n","LOG10E":"LOG10E\n","logspace":"var arr = logspace( 0, 2, 6 )\n","lowercase":"var out = lowercase( 'bEEp' )\n","lowercaseKeys":"var obj = { 'A': 1, 'B': 2 };\nvar out = lowercaseKeys( obj )\n","lowess":"var x = new Float64Array( 100 );\nvar y = new Float64Array( x.length );\nfor ( var i = 0; i < x.length; i++ ) {\n x[ i ] = i;\n y[ i ] = ( 0.5*i ) + ( 10.0*base.random.randn() );\n }\nvar out = lowess( x, y );\nvar yhat = out.y;\nvar h = Plot( [ x, x ], [ y, yhat ] );\nh.lineStyle = [ 'none', '-' ];\nh.symbols = [ 'closed-circle', 'none' ];\nh.view( 'window' );\n","lpad":"var out = lpad( 'a', 5 )\nout = lpad( 'beep', 10, 'b' )\nout = lpad( 'boop', 12, 'beep' )\n","ltrim":"var out = ltrim( ' \\r\\n\\t  Beep \\t\\t\\n  ' )\n","ltrimN":"var out = ltrimN( '  abc  ', 2 )\nvar out = ltrimN( '!!!abc!!!', 2, '!' )\n","MALE_FIRST_NAMES_EN":"var list = MALE_FIRST_NAMES_EN()\n","map":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = map( arr, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = map( arr, f );\nvar v = out.get( 1, 1 )\n","map.assign":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmap.assign( arr, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\narr = array( arr, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmap.assign( arr, out, f );\nvar v = out.get( 1, 1 )\n","map2":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = map2( x, y, f )\nx = array( x, { 'shape': [ 2, 3 ] } );\ny = array( y, { 'shape': [ 2, 3 ] } );\nout = map2( x, y, f );\nvar v = out.get( 1, 1 )\n","map2.assign":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmap2.assign( x, y, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\nx = array( x, opts );\ny = array( y, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmap2.assign( x, y, out, f );\nvar v = out.get( 1, 1 )\n","map2d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ -1, -2, -3 ], [ -4, -5, -6 ] ];\nvar out = map2d( arr, f );\nout[ 0 ]\nout[ 1 ]\n","map2Right":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = map2Right( x, y, f )\nx = array( x, { 'shape': [ 2, 3 ] } );\ny = array( y, { 'shape': [ 2, 3 ] } );\nout = map2Right( x, y, f );\nvar v = out.get( 1, 1 )\n","map2Right.assign":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmap2Right.assign( x, y, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\nx = array( x, opts );\ny = array( y, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmap2Right.assign( x, y, out, f );\nvar v = out.get( 1, 1 )\n","map3d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ [ -1, -2, -3 ] ], [ [ -4, -5, -6 ] ] ];\nvar out = map3d( arr, f );\nout[ 0 ][ 0 ]\nout[ 1 ][ 0 ]\n","map4d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ [ [ -1, -2, -3 ] ] ], [ [ [ -4, -5, -6 ] ] ] ];\nvar out = map4d( arr, f );\nout[ 0 ][ 0 ][ 0 ]\nout[ 1 ][ 0 ][ 0 ]\n","map5d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ [ [ [ -1, -2, -3 ] ] ] ], [ [ [ [ -4, -5, -6 ] ] ] ] ];\nvar out = map5d( arr, f );\nout[ 0 ][ 0 ][ 0 ][ 0 ]\nout[ 1 ][ 0 ][ 0 ][ 0 ]\n","mapArguments":"function foo( a, b, c ) { return [ a, b, c ]; };\nfunction clbk( v ) { return v * 2; };\nvar bar = mapArguments( foo, clbk );\nvar out = bar( 1, 2, 3 )\n","mapFun":"function fcn( i ) { return i; };\nvar arr = mapFun( fcn, 5 )\n","mapFunAsync":"function fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n     next( null, i );\n }\n };\nfunction done( error, arr ) {\n if ( error ) {\n     throw error;\n }\n console.log( arr );\n };\nmapFunAsync( fcn, 10, done )\nfunction fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n     next( null, i );\n }\n };\nfunction done( error, arr ) {\n if ( error ) {\n     throw error;\n }\n console.log( arr );\n };\nvar opts = { 'limit': 2 };\nmapFunAsync( fcn, 10, opts, done )\nfunction fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n     next( null, i );\n }\n };\nfunction done( error, arr ) {\n if ( error ) {\n     throw error;\n }\n console.log( arr );\n };\nvar opts = { 'series': true };\nmapFunAsync( fcn, 10, opts, done )\n","mapFunAsync.factory":"function fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n     next( null, i );\n }\n };\nvar opts = { 'series': true };\nvar f = mapFunAsync.factory( opts, fcn );\nfunction done( error, arr ) {\n if ( error ) {\n     throw error;\n }\n console.log( arr );\n };\nf( 10, done )\n","mapKeys":"function transform( key, value ) { return key + value; };\nvar obj = { 'a': 1, 'b': 2 };\nvar out = mapKeys( obj, transform )\n","mapKeysAsync":"function transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n     throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2 };\nmapKeysAsync( obj, transform, done )\nfunction transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n     throw error;\n }\n console.log( out );\n };\nvar opts = { 'limit': 2 };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapKeysAsync( obj, opts, transform, done )\nfunction transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n     throw error;\n }\n console.log( out );\n };\nvar opts = { 'series': true };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapKeysAsync( obj, opts, transform, done )\n","mapKeysAsync.factory":"function transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     next( null, key+':'+value );\n }\n };\nvar opts = { 'series': true };\nvar f = mapKeysAsync.factory( opts, transform );\nfunction done( error, out ) {\n if ( error ) {\n     throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nf( obj, done )\nobj = { 'beep': 'boop' };\nf( obj, done )\n","mapReduce":"var f1 = naryFunction( base.abs, 1 );\nvar f2 = naryFunction( base.add, 2 );\nvar arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\nvar out = mapReduce( arr, 0.0, f1, f2 )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = mapReduce( arr, 0.0, f1, f2 )\n","mapReduceRight":"var f1 = naryFunction( base.abs, 1 );\nvar f2 = naryFunction( base.add, 2 );\nvar arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\nvar out = mapReduceRight( arr, 0.0, f1, f2 )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = mapReduceRight( arr, 0.0, f1, f2 )\n","mapRight":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = mapRight( arr, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = mapRight( arr, f );\nvar v = out.get( 1, 1 )\n","mapRight.assign":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmapRight.assign( arr, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\narr = array( arr, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmapRight.assign( arr, out, f );\nvar v = out.get( 1, 1 )\n","mapValues":"function transform( value, key ) { return key + value; };\nvar obj = { 'a': 1, 'b': 2 };\nvar out = mapValues( obj, transform )\n","mapValuesAsync":"function transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n     throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2 };\nmapValuesAsync( obj, transform, done )\nfunction transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n     throw error;\n }\n console.log( out );\n };\nvar opts = { 'limit': 2 };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapValuesAsync( obj, opts, transform, done )\nfunction transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n     throw error;\n }\n console.log( out );\n };\nvar opts = { 'series': true };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapValuesAsync( obj, opts, transform, done )\n","mapValuesAsync.factory":"function transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     next( null, key+':'+value );\n }\n };\nvar opts = { 'series': true };\nvar f = mapValuesAsync.factory( opts, transform );\nfunction done( error, out ) {\n if ( error ) {\n     throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nf( obj, done )\nobj = { 'beep': 'boop' };\nf( obj, done )\n","maskArguments":"function foo( a, b ) { return [ a, b ]; };\nvar bar = maskArguments( foo, [ 1, 0, 1 ] );\nvar out = bar( 1, 2, 3 )\n","MAX_ARRAY_LENGTH":"MAX_ARRAY_LENGTH\n","MAX_TYPED_ARRAY_LENGTH":"MAX_TYPED_ARRAY_LENGTH\n","maybeBroadcastArray":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = maybeBroadcastArray( x, [ 3, 2, 2 ] )\nsh = y.shape\nvar v = y.get( 0, 0, 0 )\nv = y.get( 0, 0, 1 )\nv = y.get( 0, 1, 0 )\nv = y.get( 0, 1, 1 )\nv = y.get( 1, 0, 0 )\nv = y.get( 1, 1, 0 )\nv = y.get( 2, 0, 0 )\nv = y.get( 2, 1, 1 )\n","maybeBroadcastArrays":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = ndzeros( [ 3, 2, 2 ] )\nvar out = maybeBroadcastArrays( [ x, y ] )\nvar bx = out[ 0 ]\nsh = bx.shape\nvar v = bx.get( 0, 0, 0 )\nv = bx.get( 0, 0, 1 )\nv = bx.get( 0, 1, 0 )\nv = bx.get( 0, 1, 1 )\nv = bx.get( 1, 0, 0 )\nv = bx.get( 1, 1, 0 )\nv = bx.get( 2, 0, 0 )\nv = bx.get( 2, 1, 1 )\n","memoize":"function factorial( n ) {\n var prod;\n var i;\n prod = 1;\n for ( i = n; i > 1; i-- ) {\n     prod *= i;\n }\n return prod;\n };\nvar memoized = memoize( factorial );\nvar v = memoized( 5 )\nv = memoized( 5 )\n","merge":"var target = { 'a': 'beep' };\nvar source = { 'a': 'boop', 'b': 'bap' };\nvar out = merge( target, source )\nvar bool = ( out === target )\n","merge.factory":"var opts = {\n 'level': 100,\n 'copy': true,\n 'override': true,\n 'extend': true\n };\nvar merge = merge.factory( opts )\nmerge = merge.factory( { 'level': 2 } );\nvar target = {\n '1': { 'a': 'beep', '2': { '3': null, 'b': [ 5, 6, 7 ] } }\n };\nvar source = {\n '1': { 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } }\n };\nvar out = merge( target, source )\nmerge = merge.factory( { 'copy': false } );\ntarget = {};\nsource = { 'a': [ 1, 2, 3 ] };\nout = merge( target, source );\nvar bool = ( out.a === source.a )\nmerge = merge.factory( { 'override': false } );\ntarget = { 'a': 'beep', 'b': 'boop' };\nsource = { 'a': null, 'c': 'bop' };\nout = merge( target, source )\nfunction strategy( a, b, key ) {\n // a => target value\n // b => source value\n // key => object key\n if ( key === 'a' ) {\n     return b;\n }\n if ( key === 'b' ) {\n     return a;\n }\n return 'bebop';\n };\nmerge = merge.factory( { 'override': strategy } );\ntarget = { 'a': 'beep', 'b': 'boop', 'c': 1234 };\nsource = { 'a': null, 'b': {}, 'c': 'bop' };\nout = merge( target, source )\nmerge = merge.factory( { 'extend': false } );\ntarget = { 'a': 'beep', 'b': 'boop' };\nsource = { 'b': 'hello', 'c': 'world' };\nout = merge( target, source )\n","MILLISECONDS_IN_DAY":"var days = 3.14;\nvar ms = days * MILLISECONDS_IN_DAY\n","MILLISECONDS_IN_HOUR":"var hrs = 3.14;\nvar ms = hrs * MILLISECONDS_IN_HOUR\n","MILLISECONDS_IN_MINUTE":"var mins = 3.14;\nvar ms = mins * MILLISECONDS_IN_MINUTE\n","MILLISECONDS_IN_SECOND":"var secs = 3.14;\nvar ms = secs * MILLISECONDS_IN_SECOND\n","MILLISECONDS_IN_WEEK":"var weeks = 3.14;\nvar ms = weeks * MILLISECONDS_IN_WEEK\n","MINARD_NAPOLEONS_MARCH":"var data = MINARD_NAPOLEONS_MARCH();\nvar army = data.army\nvar cities = data.cities\nvar labels = data.labels\nvar river = data.river\nvar t = data.temperature\n","MINUTES_IN_DAY":"var days = 3.14;\nvar mins = days * MINUTES_IN_DAY\n","MINUTES_IN_HOUR":"var hrs = 3.14;\nvar mins = hrs * MINUTES_IN_HOUR\n","MINUTES_IN_WEEK":"var wks = 3.14;\nvar mins = wks * MINUTES_IN_WEEK\n","minutesInMonth":"var num = minutesInMonth()\nnum = minutesInMonth( 2 )\nnum = minutesInMonth( 2, 2016 )\nnum = minutesInMonth( 2, 2017 )\nnum = minutesInMonth( 'feb', 2016 )\nnum = minutesInMonth( 'february', 2016 )\n","minutesInYear":"var num = minutesInYear()\nnum = minutesInYear( 2016 )\nnum = minutesInYear( 2017 )\n","MOBY_DICK":"var data = MOBY_DICK()\n","MONTH_NAMES_EN":"var list = MONTH_NAMES_EN()\n","MONTHS_IN_YEAR":"var yrs = 3.14;\nvar mons = yrs * MONTHS_IN_YEAR\n","moveProperty":"var obj1 = { 'a': 'b' };\nvar obj2 = {};\nvar bool = moveProperty( obj1, 'a', obj2 )\nbool = moveProperty( obj1, 'c', obj2 )\n","MultiSlice":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\n","MultiSlice.prototype.ndims":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\nms.ndims\n","MultiSlice.prototype.data":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\nms.data\n","MultiSlice.prototype.toString":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\nms.toString()\n","MultiSlice.prototype.toJSON":"var s = new Slice( 2, 10, 1 );\nvar ms = new MultiSlice( 2, s );\nms.toJSON()\n","namedtypedtuple":"var opts = {};\nopts.name = 'Point';\nvar factory = namedtypedtuple( [ 'x', 'y' ], opts );\nvar tuple = factory();\n","NAN":"NAN\n","naryFunction":"function foo( a, b, c ) { return [ a, b, c ]; };\nvar bar = naryFunction( foo, 2 );\nvar out = bar( 1, 2, 3 )\n","nativeClass":"var str = nativeClass( 'a' )\nstr = nativeClass( 5 )\nfunction Beep(){};\nstr = nativeClass( new Beep() )\n","ndarray":"var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\nvar d = [ 2, 2 ]; // shape\nvar s = [ 2, 1 ]; // strides\nvar o = 0; // index offset\nvar arr = ndarray( 'generic', b, d, s, o, 'row-major' )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","ndarray.prototype.byteLength":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.byteLength\n","ndarray.prototype.BYTES_PER_ELEMENT":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.BYTES_PER_ELEMENT\n","ndarray.prototype.data":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar buf = arr.data\n","ndarray.prototype.dtype":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar dt = arr.dtype\n","ndarray.prototype.flags":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar fl = arr.flags\n","ndarray.prototype.length":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar len = arr.length\n","ndarray.prototype.ndims":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar n = arr.ndims\n","ndarray.prototype.offset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.offset\n","ndarray.prototype.order":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar ord = arr.order\n","ndarray.prototype.shape":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sh = arr.shape\n","ndarray.prototype.strides":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar st = arr.strides\n","ndarray.prototype.get":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.get( 1, 1 )\n","ndarray.prototype.iget":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.iget( 3 )\n","ndarray.prototype.set":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\narr.set( 1, 1, -4.0 );\narr.get( 1, 1 )\n","ndarray.prototype.iset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\narr.iset( 3, -4.0 );\narr.iget( 3 )\n","ndarray.prototype.toString":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toString()\n","ndarray.prototype.toJSON":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toJSON()\n","ndarray2array":"var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar out = ndarray2array( arr )\n","ndarray2fancy":"var b = [ 1.0, 2.0, 3.0, 4.0 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar x = ndarray( 'generic', b, d, s, o, 'row-major' );\nvar arr = ndarray2fancy( x );\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","ndarray2fancy.factory":"var b = [ 1.0, 2.0, 3.0, 4.0 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar x = ndarray( 'generic', b, d, s, o, 'row-major' );\nvar f = ndarray2fancy.factory();\nvar y = f( x );\n","ndarray2fancy.idx":"var opts = { 'dtype': 'int32' };\nvar buf = new Int32Array( [ 1, 2, 3, 4 ] );\nvar arr = array( buf, opts );\nvar idx = ndarray2fancy.idx( arr );\n","ndarray2json":"var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar out = ndarray2json( arr )\n","ndarrayCastingModes":"var out = ndarrayCastingModes()\n","ndarrayDataBuffer":"var opts = { 'dtype': 'float64' };\nvar out = ndarrayDataBuffer( ndzeros( [ 3, 3, 3 ], opts ) )\n","ndarrayDataType":"var opts = { 'dtype': 'float64' };\nvar dt = ndarrayDataType( ndzeros( [ 3, 3, 3 ], opts ) )\n","ndarrayDataTypes":"var out = ndarrayDataTypes()\nout = ndarrayDataTypes( 'floating_point' )\nout = ndarrayDataTypes( 'floating_point_and_generic' )\n","ndarrayDispatch":"var t = [ 'float64', 'float64', 'float32', 'float32' ];\nvar d = [ base.abs, base.absf ];\nvar f = ndarrayDispatch( base.ndarrayUnary, t, d, 2, 1, 1 );\nvar xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar x = ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );\nvar ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar y = ndarray( 'float64', ybuf, [ 4 ], [ 1 ], 0, 'row-major' );\nf( x, y );\nybuf\n","ndarrayFlag":"var out = ndarrayFlag( ndzeros( [ 3, 3, 3 ] ), 'READONLY' )\n","ndarrayFlags":"var out = ndarrayFlags( ndzeros( [ 3, 3, 3 ] ) )\n","ndarrayIndexModes":"var out = ndarrayIndexModes()\n","ndarraylike2ndarray":"var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar out = ndarraylike2ndarray( arr )\n","ndarrayMinDataType":"var dt = ndarrayMinDataType( 3.141592653589793 )\ndt = ndarrayMinDataType( 3 )\ndt = ndarrayMinDataType( -3 )\ndt = ndarrayMinDataType( '-3' )\n","ndarrayMostlySafeCasts":"var out = ndarrayMostlySafeCasts( 'float32' )\n","ndarrayNextDataType":"var out = ndarrayNextDataType( 'float32' )\n","ndarrayOffset":"var n = ndarrayOffset( ndzeros( [ 3, 3, 3 ] ) )\n","ndarrayOrder":"var opts = { 'order': 'row-major' };\nvar dt = ndarrayOrder( ndzeros( [ 3, 3, 3 ], opts ) )\n","ndarrayOrders":"var out = ndarrayOrders()\n","ndarrayPromotionRules":"var out = ndarrayPromotionRules( 'float32', 'int32' )\n","ndarraySafeCasts":"var out = ndarraySafeCasts( 'float32' )\n","ndarraySameKindCasts":"var out = ndarraySameKindCasts( 'float32' )\n","ndarrayShape":"var out = ndarrayShape( ndzeros( [ 3, 3, 3 ] ) )\n","ndarrayStride":"var out = ndarrayStride( ndzeros( [ 3, 3, 3 ] ), 0 )\n","ndarrayStrides":"var out = ndarrayStrides( ndzeros( [ 3, 3, 3 ] ) )\n","ndat":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nndat( x, 0, 1 )\nndat( x, 1, 0 )\n","ndempty":"var arr = ndempty( [ 2, 2 ] )\nvar sh = arr.shape\nvar dt = arr.dtype\n","ndemptyLike":"var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\nvar sh = x.shape\nvar dt = x.dtype\nvar y = ndemptyLike( x )\nsh = y.shape\ndt = y.dtype\n","ndfilter":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { return v > 2.0; };\nvar y = ndfilter( x, f );\nndarray2array( y )\n","ndfilterMap":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { if ( v > 2.0 ) { return v * 10.0; } };\nvar y = ndfilterMap( x, f );\nndarray2array( y )\n","ndforEach":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { if ( v !== v ) { throw new Error( '...' ); } };\nndforEach( x, f );\n","ndims":"var n = ndims( ndzeros( [ 3, 3, 3 ] ) )\n","ndindex":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\n","ndindex.free":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nndindex.free( idx.id )\n","ndindex.get":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nndindex.get( idx.id )\n","ndindex.cartesianIndex":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = ndindex.cartesianIndex( x );\n","ndindex.linearIndex":"var x = ndempty( [ 5 ], { 'dtype': 'int32' } );\nvar idx = ndindex.linearIndex( x );\n","ndindex.prototype.data":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.data\n","ndindex.prototype.dtype":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.dtype\n","ndindex.prototype.id":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.id\n","ndindex.prototype.isCached":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.isCached\n","ndindex.prototype.kind":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x, { 'kind': 'cartesian' } );\nidx.kind\n","ndindex.prototype.type":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.type\n","ndindex.prototype.toString":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.toString()\n","ndindex.prototype.toJSON":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.toJSON()\n","nditerColumnEntries":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerColumnEntries( x );\nvar v = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\nv = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\n","nditerColumns":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerColumns( x );\nvar v = it.next().value;\nndarray2array( v )\nv = it.next().value;\nndarray2array( v )\n","nditerEntries":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerEntries( x );\nvar v = it.next().value\nv = it.next().value\n","nditerIndices":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerIndices( x.shape );\nvar v = it.next().value\nv = it.next().value\n","nditerInterleaveSubarrays":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerInterleaveSubarrays( [ x, x ], 2 );\nvar v = it.next().value;\nndarray2array( v )\n","nditerMatrices":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerMatrices( x );\nvar v = it.next().value;\nndarray2array( v )\n","nditerMatrixEntries":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerMatrixEntries( x );\nvar v = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\n","nditerRowEntries":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerRowEntries( x );\nvar v = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\nv = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\n","nditerRows":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerRows( x );\nvar v = it.next().value;\nndarray2array( v )\nv = it.next().value;\nndarray2array( v )\n","nditerSelectDimension":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerSelectDimension( x, 0 );\nvar v = it.next().value;\nndarray2array( v )\n","nditerStacks":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerStacks( x, [ 1, 2 ] );\nvar v = it.next().value;\nndarray2array( v )\n","nditerSubarrays":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerSubarrays( x, 2 );\nvar v = it.next().value;\nndarray2array( v )\n","nditerValues":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerValues( x );\nvar v = it.next().value\nv = it.next().value\n","ndmap":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { return v*10.0; };\nvar y = ndmap( x, f );\nndarray2array( y )\n","ndreject":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { return v <= 2.0; };\nvar y = ndreject( x, f );\nndarray2array( y )\n","ndslice":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar s = new MultiSlice( null, 1 )\nvar y = ndslice( x, s )\ny.shape\nndarray2array( y )\n","ndsliceAssign":"var y = ndzeros( [ 2, 2 ] )\nvar x = scalar2ndarray( 3.0 )\nvar s = new MultiSlice( null, 1 )\nvar out = ndsliceAssign( x, y, s )\nvar bool = ( out === y )\nndarray2array( y )\n","ndsliceDimension":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceDimension( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndsliceDimensionFrom":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceDimensionFrom( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndsliceDimensionTo":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceDimensionTo( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndsliceFrom":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceFrom( x, 0, 1 )\ny.shape\nndarray2array( y )\n","ndsliceTo":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceTo( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndzeros":"var arr = ndzeros( [ 2, 2 ] )\nvar sh = arr.shape\nvar dt = arr.dtype\n","ndzerosLike":"var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\nvar sh = x.shape\nvar dt = x.dtype\nvar y = ndzerosLike( x )\nsh = y.shape\ndt = y.dtype\n","nextGraphemeClusterBreak":"var out = nextGraphemeClusterBreak( 'last man standing', 4 )\nout = nextGraphemeClusterBreak( 'presidential election', 8 )\nout = nextGraphemeClusterBreak( 'अनुच्छेद', 1 )\nout = nextGraphemeClusterBreak( '🌷' )\n","nextTick":"function f() { console.log( 'beep' ); };\nnextTick( f )\n","NIGHTINGALES_ROSE":"var data = NIGHTINGALES_ROSE()\n","NINF":"NINF\n","NODE_VERSION":"NODE_VERSION\n","none":"var arr = [ 0, 0, 0, 0, 0 ];\nvar bool = none( arr )\n","noneBy":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ 1, 2, 3, 4 ];\nvar bool = noneBy( arr, negative )\n","noneByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nnoneByAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nnoneByAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nnoneByAsync( arr, opts, predicate, done )\n","noneByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = noneByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","noneByRight":"function positive( v ) { return ( v > 0 ); };\nvar arr = [ -1, -2, -3, -4 ];\nvar bool = noneByRight( arr, positive )\n","noneByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nnoneByRightAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nnoneByRightAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nnoneByRightAsync( arr, opts, predicate, done )\n","noneByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = noneByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","noneInBy":"function negative( v ) { return ( v < 0 ); };\nvar obj = { 'a': 1, 'b': 2, 'c': 4 };\nvar bool = noneInBy( obj, negative )\n","nonEnumerableProperties":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = false;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar props = nonEnumerableProperties( obj )\n","nonEnumerablePropertiesIn":"var props = nonEnumerablePropertiesIn( [] )\n","nonEnumerablePropertyNames":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = nonEnumerablePropertyNames( obj )\n","nonEnumerablePropertyNamesIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = nonEnumerablePropertyNamesIn( obj )\n","nonEnumerablePropertySymbols":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = nonEnumerablePropertySymbols( obj )\n","nonEnumerablePropertySymbolsIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? 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Object.assign( {}, { 'a': 1 }, { 'b': 2 } )\n","Object.create":"var o = Object.create( {}, { 'a': { 'value': 1 } } )\n","Object.defineProperties":"var o = Object.defineProperties( {}, { 'a': { 'value': 1 } } )\n","Object.defineProperty":"var o = Object.defineProperty( {}, 'a', {\n","Object.entries":"var o = Object.entries( { 'a': 1, 'b': 2 } )\n","Object.freeze":"var o = Object.freeze( { 'a': 1 } )\n","Object.getOwnPropertyDescriptor":"var o = Object.getOwnPropertyDescriptor( { 'a': 1 }, 'a' )\n","Object.getOwnPropertyDescriptors":"var o = Object.getOwnPropertyDescriptors( { 'a': 1, 'b': 2 } )\n","Object.getOwnPropertyNames":"var o = Object.getOwnPropertyNames( { 'a': 1, 'b': 2 } )\n","Object.getOwnPropertySymbols":"var o = Object.getOwnPropertySymbols( { 'a': 1, 'b': 2 } )\n","Object.getPrototypeOf":"var o = Object.getPrototypeOf( { 'a': 1, 'b': 2 } )\n","Object.hasOwn":"var o = Object.hasOwn( { 'a': 1, 'b': 2 }, 'a' )\n","Object.is":"var o = Object.is( 1, 1 )\nvar o = Object.is( 1, '1' )\n","Object.isExtensible":"var o = Object.isExtensible( { 'a': 1 } )\n","Object.isFrozen":"var o = Object.isFrozen( { 'a': 1 } )\nvar o = Object.isFrozen( Object.freeze( { 'a': 1 } ) )\n","Object.isSealed":"var o = Object.isSealed( { 'a': 1 } )\nvar o = Object.isSealed( Object.seal( { 'a': 1 } ) )\n","Object.keys":"var o = Object.keys( { 'a': 1, 'b': 2 } )\n","Object.preventExtensions":"var o = Object.preventExtensions( { 'a': 1 } )\no.b = 2;\no\n","Object.seal":"var o = Object.seal( { 'a': 1 } )\no.b = 2;\no\ndelete o.a;\no\n","Object.setPrototypeOf":"var o = Object.setPrototypeOf( { 'a': 1 }, { 'b': 2 } )\no.b\n","Object.values":"var o = Object.values( { 'a': 1, 'b': 2 } )\n","Object.prototype.toLocaleString":"var o = Object.prototype.toLocaleString.call( { 'a': 1, 'b': 2 } )\n","Object.prototype.toString":"var o = Object.prototype.toString.call( { 'a': 1, 'b': 2 } )\n","Object.prototype.valueOf":"var o = Object.prototype.valueOf.call( { 'a': 1, 'b': 2 } )\n","Object.prototype.hasOwnProperty":"var o = Object.prototype.hasOwnProperty.call( { 'a': 1, 'b': 2 }, 'a' )\n","Object.prototype.isPrototypeOf":"var p = { 'a': 1 };\nvar o = { '__proto__': p };\nvar b = o.isPrototypeOf( p );\n","Object.prototype.propertyIsEnumerable":"var o = { 'a': 1, 'b': 2 };\nvar bool = Object.prototype.propertyIsEnumerable.call( o, 'a' )\n","Object.prototype.constructor":"var o = new Object( null );\nvar ctr = o.constructor;\n","objectEntries":"var obj = { 'beep': 'boop', 'foo': 'bar' };\nvar entries = objectEntries( obj )\n","objectEntriesIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar entries = objectEntriesIn( obj )\n","objectFromEntries":"var entries = [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ];\nvar obj = objectFromEntries( entries )\n","objectInverse":"var obj = { 'a': 'beep', 'b': 'boop' };\nvar out = objectInverse( obj )\nobj = { 'a': 'beep', 'b': 'beep' };\nout = objectInverse( obj )\nobj = {};\nobj.a = 'beep';\nobj.b = 'boop';\nobj.c = 'beep';\nout = objectInverse( obj, { 'duplicates': false } )\n","objectInverseBy":"function transform( key, value ) { return key + value; };\nvar obj = { 'a': 'beep', 'b': 'boop' };\nvar out = objectInverseBy( obj, transform )\nfunction transform( key, value ) { return value; };\nobj = { 'a': 'beep', 'b': 'beep' };\nout = objectInverseBy( obj, transform )\nobj = {};\nobj.a = 'beep';\nobj.b = 'boop';\nobj.c = 'beep';\nout = objectInverseBy( obj, { 'duplicates': false }, transform )\n","objectKeys":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = objectKeys( obj )\n","objectValues":"var obj = { 'beep': 'boop', 'foo': 'bar' };\nvar vals = objectValues( obj )\n","objectValuesIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar values = objectValuesIn( obj )\n","omit":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = omit( obj1, 'b' )\n","omitBy":"function predicate( key, value ) { return ( value > 1 ); };\nvar obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = omitBy( obj1, predicate )\n","open":"function onOpen( error, fd ) {\n if ( error ) {\n     console.error( error.message );\n } else {\n     close.sync( fd );\n }\n };\nopen( './beep/boop.txt', onOpen );\n","open.sync":"var fd = open.sync( './beep/boop.txt' );\nif ( !isError( fd ) ) { close.sync( fd ); };\n","openURL":"var out = openURL( 'https://google.com' );\n","ordinalize":"var out = ordinalize( '1' )\nout = ordinalize( 2, { 'suffixOnly': true } )\nout = ordinalize( '3', { 'lang': 'es' } )\n","PACE_BOSTON_HOUSE_PRICES":"var data = PACE_BOSTON_HOUSE_PRICES()\n","pad":"var out = pad( 'a', 5 )\nout = pad( 'a', 10, { 'lpad': 'b' } )\nout = pad( 'a', 12, { 'rpad': 'b' } )\nvar opts = { 'lpad': 'a', 'rpad': 'c' };\nout = pad( 'b', 11, opts )\nopts.centerRight = false;\nout = pad( 'b', 10, opts )\nopts.centerRight = true;\nout = pad( 'b', 10, opts )\nopts = { 'lpad': 'boop', 'rpad': 'woot' };\nout = pad( 'beep', 10, opts )\nout = pad( 'beep', 2 )\nopts = { 'lpad': 'b' };\nout = pad( 'beep', 2, opts )\nopts = { 'lpad': '@', 'rpad': '!' };\nout = pad( 'beep', 2, opts )\nout = pad( 'abcdef', 3, opts )\nopts.centerRight = true;\nout = pad( 'abcdef', 3, opts )\n","padjust":"var pvalues = [ 0.008, 0.03, 0.123, 0.6, 0.2 ];\nvar out = padjust( pvalues, 'bh' )\nout = padjust( pvalues, 'bonferroni' )\nout = padjust( pvalues, 'by' )\nout = padjust( pvalues, 'holm' )\nout = padjust( pvalues, 'hommel' )\n","papply":"function add( x, y ) { return x + y; };\nvar add2 = papply( add, 2 );\nvar sum = add2( 3 )\n","papplyRight":"function say( text, name ) { return text + ', ' + name + '.'; };\nvar toGrace = papplyRight( say, 'Grace Hopper' );\nvar str = toGrace( 'Hello' )\nstr = toGrace( 'Thank you' )\n","parallel":"function done( error ) { if ( error ) { throw error; } };\nvar files = [ './a.js', './b.js' ];\nparallel( files, done );\nvar opts = { 'workers': 8 };\nparallel( files, opts, done );\n","parseJSON":"var obj = parseJSON( '{\"beep\":\"boop\"}' )\nfunction reviver( key, value ) {\n if ( key === '' ) { return value; }\n if ( key === 'beep' ) { return value; }\n };\nvar str = '{\"beep\":\"boop\",\"a\":\"b\"}';\nvar out = parseJSON( str, reviver )\n","pascalcase":"var out = pascalcase( 'Hello World!' )\nout = pascalcase( 'beep boop' )\n","PATH_DELIMITER":"PATH_DELIMITER\nvar path = '/usr/bin:/bin:/usr/sbin';\nvar parts = path.split( PATH_DELIMITER )\npath = 'C:\\\\Windows\\\\system32;C:\\\\Windows';\nparts = path.split( PATH_DELIMITER )\n","PATH_DELIMITER_POSIX":"PATH_DELIMITER_POSIX\nvar PATH = '/usr/bin:/bin:/usr/sbin:/sbin:/usr/local/bin';\nvar paths = PATH.split( PATH_DELIMITER_POSIX )\n","PATH_DELIMITER_WIN32":"PATH_DELIMITER_WIN32\nvar PATH = 'C:\\\\Windows\\\\system32;C:\\\\Windows;C:\\\\Program Files\\\\node\\\\';\nvar paths = PATH.split( PATH_DELIMITER_WIN32 )\n","PATH_SEP":"PATH_SEP\nvar parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP )\nparts = 'foo/bar/baz'.split( PATH_SEP )\n","PATH_SEP_POSIX":"PATH_SEP_POSIX\nvar parts = 'foo/bar/baz'.split( PATH_SEP_POSIX )\n","PATH_SEP_WIN32":"PATH_SEP_WIN32\nvar parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP_WIN32 )\n","pcorrtest":"var rho = 0.5;\nvar x = new Array( 300 );\nvar y = new Array( 300 );\nfor ( var i = 0; i < 300; i++ ) {\nx[ i ] = base.random.normal( 0.0, 1.0 );\ny[ i ] = ( rho * x[ i ] ) + base.random.normal( 0.0,\nbase.sqrt( 1.0 - (rho*rho) ) );\n }\nvar out = pcorrtest( x, y )\nvar table = out.print()\n","percentEncode":"var out = percentEncode( '☃' )\n","PHI":"PHI\n","PI":"PI\n","PI_SQUARED":"PI_SQUARED\n","pick":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = pick( obj1, 'b' )\n","pickArguments":"function foo( a, b ) { return [ a, b ]; };\nvar bar = pickArguments( foo, [ 0, 2 ] );\nvar out = bar( 1, 2, 3 )\n","pickBy":"function predicate( key, value ) {\n return ( value > 1 );\n };\nvar obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = pickBy( obj1, predicate )\n","PINF":"PINF\n","pkg2alias":"var v = pkg2alias( '@stdlib/math/base/special/sin' )\nv = pkg2alias( '@stdlib/math-base-special-sin' )\n","pkg2related":"var v = pkg2related( '@stdlib/math/base/special/sin' )\nv = pkg2related( '@stdlib/math-base-special-sin' )\n","pkg2standalone":"var v = pkg2standalone( '@stdlib/math/base/special/sin' )\n","PLATFORM":"PLATFORM\n","plot":"var plot = plot()\nvar x = [[0.10, 0.20, 0.30]];\nvar y = [[0.52, 0.79, 0.64]];\nplot = plot( x, y )\n","Plot":"var plot = Plot()\nvar x = [[0.10, 0.20, 0.30]];\nvar y = [[0.52, 0.79, 0.64]];\nplot = Plot( x, y )\n","pluck":"var arr = [\n { 'a': 1, 'b': 2 },\n { 'a': 0.5, 'b': 3 }\n ];\nvar out = pluck( arr, 'a' )\narr = [\n { 'a': 1, 'b': 2 },\n { 'a': 0.5, 'b': 3 }\n ];\nout = pluck( arr, 'a', { 'copy': false } )\nvar bool = ( arr[ 0 ] === out[ 0 ] )\n","pop":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar out = pop( arr )\narr = new Float64Array( [ 1.0, 2.0 ] );\nout = pop( arr )\narr = { 'length': 2, '0': 1.0, '1': 2.0 };\nout = pop( arr )\n","porterStemmer":"var out = porterStemmer( 'walking' )\nout = porterStemmer( 'walked' )\nout = porterStemmer( 'walks' )\nout = porterStemmer( '' )\n","prepend":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = prepend( arr, [ 6.0, 7.0 ] )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = prepend( arr, [ 3.0, 4.0 ] )\narr = { 'length': 1, '0': 1.0 };\narr = prepend( arr, [ 2.0, 3.0 ] )\n","prevGraphemeClusterBreak":"var out = prevGraphemeClusterBreak( 'last man standing', 4 )\nout = prevGraphemeClusterBreak( 'presidential election', 8 )\nout = prevGraphemeClusterBreak( 'अनुच्छेद', 2 )\nout = prevGraphemeClusterBreak( '🌷', 1 )\n","PRIMES_100K":"var list = PRIMES_100K()\n","properties":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar props = properties( obj )\n","propertiesIn":"var props = propertiesIn( [] )\n","propertyDescriptor":"var obj = { 'a': 'b' };\nvar desc = propertyDescriptor( obj, 'a' )\n","propertyDescriptorIn":"var obj = { 'a': 'b' };\nvar desc = propertyDescriptorIn( obj, 'a' )\n","propertyDescriptors":"var obj = { 'a': 'b' };\nvar desc = propertyDescriptors( obj )\n","propertyDescriptorsIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar desc = propertyDescriptorsIn( obj )\n","propertyNames":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = propertyNames( obj )\n","propertyNamesIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = propertyNamesIn( obj )\n","propertySymbols":"var s = propertySymbols( {} )\n","propertySymbolsIn":"var s = propertySymbolsIn( [] )\n","Proxy":"function get( obj, prop ) { return obj[ prop ] * 2.0 };\nvar h = { 'get': get };\nvar p = new Proxy( {}, h );\np.a = 3.14;\np.a\n","Proxy.revocable":"function get( obj, prop ) { return obj[ prop ] * 2.0 };\nvar h = { 'get': get };\nvar p = Proxy.revocable( {}, h );\np.proxy.a = 3.14;\np.proxy.a\np.revoke();\n","push":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = push( arr, 6.0, 7.0 )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = push( arr, 3.0, 4.0 )\narr = { 'length': 0 };\narr = push( arr, 1.0, 2.0 )\n","quarterOfYear":"var q = quarterOfYear( new Date() )\nq = quarterOfYear( 4 )\nq = quarterOfYear( 'June' )\nq = quarterOfYear( 'April' )\nq = quarterOfYear( 'apr' )\n","random.array.arcsine":"var out = random.array.arcsine( 3, 2.0, 5.0 )\n","random.array.arcsine.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.arcsine.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.arcsine.factory":"var fcn = random.array.arcsine.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.arcsine.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.arcsine.PRNG":"var prng = random.array.arcsine.PRNG;\n","random.array.arcsine.seed":"var seed = random.array.arcsine.seed;\n","random.array.arcsine.seedLength":"var len = random.array.arcsine.seedLength;\n","random.array.arcsine.state":"var out = random.array.arcsine( 3, 2.0, 5.0 )\nvar state = random.array.arcsine.state\nout = random.array.arcsine( 3, 2.0, 5.0 )\nout = random.array.arcsine( 3, 2.0, 5.0 )\nrandom.array.arcsine.state = state;\nout = random.array.arcsine( 3, 2.0, 5.0 )\n","random.array.arcsine.stateLength":"var len = random.array.arcsine.stateLength;\n","random.array.arcsine.byteLength":"var sz = random.array.arcsine.byteLength;\n","random.array.bernoulli":"var out = random.array.bernoulli( 3, 0.5 )\n","random.array.bernoulli.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.bernoulli.assign( 0.5, x )\nvar bool = ( out === x )\n","random.array.bernoulli.factory":"var fcn = random.array.bernoulli.factory();\nvar out = fcn( 3, 0.5 )\nfcn = random.array.bernoulli.factory( 0.5 );\nout = fcn( 3 )\n","random.array.bernoulli.PRNG":"var prng = random.array.bernoulli.PRNG;\n","random.array.bernoulli.seed":"var seed = random.array.bernoulli.seed;\n","random.array.bernoulli.seedLength":"var len = random.array.bernoulli.seedLength;\n","random.array.bernoulli.state":"var out = random.array.bernoulli( 3, 0.5 )\nvar state = random.array.bernoulli.state\nout = random.array.bernoulli( 3, 0.5 )\nout = random.array.bernoulli( 3, 0.5 )\nrandom.array.bernoulli.state = state;\nout = random.array.bernoulli( 3, 0.5 )\n","random.array.bernoulli.stateLength":"var len = random.array.bernoulli.stateLength;\n","random.array.bernoulli.byteLength":"var sz = random.array.bernoulli.byteLength;\n","random.array.beta":"var out = random.array.beta( 3, 2.0, 5.0 )\n","random.array.beta.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.beta.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.beta.factory":"var fcn = random.array.beta.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.beta.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.beta.PRNG":"var prng = random.array.beta.PRNG;\n","random.array.beta.seed":"var seed = random.array.beta.seed;\n","random.array.beta.seedLength":"var len = random.array.beta.seedLength;\n","random.array.beta.state":"var out = random.array.beta( 3, 2.0, 5.0 )\nvar state = random.array.beta.state\nout = random.array.beta( 3, 2.0, 5.0 )\nout = random.array.beta( 3, 2.0, 5.0 )\nrandom.array.beta.state = state;\nout = random.array.beta( 3, 2.0, 5.0 )\n","random.array.beta.stateLength":"var len = random.array.beta.stateLength;\n","random.array.beta.byteLength":"var sz = random.array.beta.byteLength;\n","random.array.betaprime":"var out = random.array.betaprime( 3, 2.0, 5.0 )\n","random.array.betaprime.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.betaprime.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.betaprime.factory":"var fcn = random.array.betaprime.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.betaprime.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.betaprime.PRNG":"var prng = random.array.betaprime.PRNG;\n","random.array.betaprime.seed":"var seed = random.array.betaprime.seed;\n","random.array.betaprime.seedLength":"var len = random.array.betaprime.seedLength;\n","random.array.betaprime.state":"var out = random.array.betaprime( 3, 2.0, 5.0 )\nvar state = random.array.betaprime.state\nout = random.array.betaprime( 3, 2.0, 5.0 )\nout = random.array.betaprime( 3, 2.0, 5.0 )\nrandom.array.betaprime.state = state;\nout = random.array.betaprime( 3, 2.0, 5.0 )\n","random.array.betaprime.stateLength":"var len = random.array.betaprime.stateLength;\n","random.array.betaprime.byteLength":"var sz = random.array.betaprime.byteLength;\n","random.array.binomial":"var out = random.array.binomial( 3, 17, 0.5 )\n","random.array.binomial.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.binomial.assign( 17, 0.5, x )\nvar bool = ( out === x )\n","random.array.binomial.factory":"var fcn = random.array.binomial.factory();\nvar out = fcn( 3, 17, 0.5 )\nfcn = random.array.binomial.factory( 17, 0.5 );\nout = fcn( 3 )\n","random.array.binomial.PRNG":"var prng = random.array.binomial.PRNG;\n","random.array.binomial.seed":"var seed = random.array.binomial.seed;\n","random.array.binomial.seedLength":"var len = random.array.binomial.seedLength;\n","random.array.binomial.state":"var out = random.array.binomial( 3, 17, 0.5 )\nvar state = random.array.binomial.state\nout = random.array.binomial( 3, 17, 0.5 )\nout = random.array.binomial( 3, 17, 0.5 )\nrandom.array.binomial.state = state;\nout = random.array.binomial( 3, 17, 0.5 )\n","random.array.binomial.stateLength":"var len = random.array.binomial.stateLength;\n","random.array.binomial.byteLength":"var sz = random.array.binomial.byteLength;\n","random.array.cauchy":"var out = random.array.cauchy( 3, 2.0, 5.0 )\n","random.array.cauchy.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.cauchy.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.cauchy.factory":"var fcn = random.array.cauchy.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.cauchy.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.cauchy.PRNG":"var prng = random.array.cauchy.PRNG;\n","random.array.cauchy.seed":"var seed = random.array.cauchy.seed;\n","random.array.cauchy.seedLength":"var len = random.array.cauchy.seedLength;\n","random.array.cauchy.state":"var out = random.array.cauchy( 3, 2.0, 5.0 )\nvar state = random.array.cauchy.state\nout = random.array.cauchy( 3, 2.0, 5.0 )\nout = random.array.cauchy( 3, 2.0, 5.0 )\nrandom.array.cauchy.state = state;\nout = random.array.cauchy( 3, 2.0, 5.0 )\n","random.array.cauchy.stateLength":"var len = random.array.cauchy.stateLength;\n","random.array.cauchy.byteLength":"var sz = random.array.cauchy.byteLength;\n","random.array.chi":"var out = random.array.chi( 3, 2.0 )\n","random.array.chi.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.chi.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.chi.factory":"var fcn = random.array.chi.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.chi.factory( 2.0 );\nout = fcn( 3 )\n","random.array.chi.PRNG":"var prng = random.array.chi.PRNG;\n","random.array.chi.seed":"var seed = random.array.chi.seed;\n","random.array.chi.seedLength":"var len = random.array.chi.seedLength;\n","random.array.chi.state":"var out = random.array.chi( 3, 2.0 )\nvar state = random.array.chi.state\nout = random.array.chi( 3, 2.0 )\nout = random.array.chi( 3, 2.0 )\nrandom.array.chi.state = state;\nout = random.array.chi( 3, 2.0 )\n","random.array.chi.stateLength":"var len = random.array.chi.stateLength;\n","random.array.chi.byteLength":"var sz = random.array.chi.byteLength;\n","random.array.chisquare":"var out = random.array.chisquare( 3, 2.0 )\n","random.array.chisquare.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.chisquare.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.chisquare.factory":"var fcn = random.array.chisquare.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.chisquare.factory( 2.0 );\nout = fcn( 3 )\n","random.array.chisquare.PRNG":"var prng = random.array.chisquare.PRNG;\n","random.array.chisquare.seed":"var seed = random.array.chisquare.seed;\n","random.array.chisquare.seedLength":"var len = random.array.chisquare.seedLength;\n","random.array.chisquare.state":"var out = random.array.chisquare( 3, 2.0 )\nvar state = random.array.chisquare.state\nout = random.array.chisquare( 3, 2.0 )\nout = random.array.chisquare( 3, 2.0 )\nrandom.array.chisquare.state = state;\nout = random.array.chisquare( 3, 2.0 )\n","random.array.chisquare.stateLength":"var len = random.array.chisquare.stateLength;\n","random.array.chisquare.byteLength":"var sz = random.array.chisquare.byteLength;\n","random.array.cosine":"var out = random.array.cosine( 3, 2.0, 5.0 )\n","random.array.cosine.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.cosine.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.cosine.factory":"var fcn = random.array.cosine.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.cosine.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.cosine.PRNG":"var prng = random.array.cosine.PRNG;\n","random.array.cosine.seed":"var seed = random.array.cosine.seed;\n","random.array.cosine.seedLength":"var len = random.array.cosine.seedLength;\n","random.array.cosine.state":"var out = random.array.cosine( 3, 2.0, 5.0 )\nvar state = random.array.cosine.state\nout = random.array.cosine( 3, 2.0, 5.0 )\nout = random.array.cosine( 3, 2.0, 5.0 )\nrandom.array.cosine.state = state;\nout = random.array.cosine( 3, 2.0, 5.0 )\n","random.array.cosine.stateLength":"var len = random.array.cosine.stateLength;\n","random.array.cosine.byteLength":"var sz = random.array.cosine.byteLength;\n","random.array.discreteUniform":"var out = random.array.discreteUniform( 3, -10, 10 )\n","random.array.discreteUniform.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.discreteUniform.assign( -10, 10, x )\nvar bool = ( out === x )\n","random.array.discreteUniform.factory":"var fcn = random.array.discreteUniform.factory();\nvar out = fcn( 3, -10, 10 )\nfcn = random.array.discreteUniform.factory( -10, 10 );\nout = fcn( 3 )\n","random.array.discreteUniform.PRNG":"var prng = random.array.discreteUniform.PRNG;\n","random.array.discreteUniform.seed":"var seed = random.array.discreteUniform.seed;\n","random.array.discreteUniform.seedLength":"var len = random.array.discreteUniform.seedLength;\n","random.array.discreteUniform.state":"var out = random.array.discreteUniform( 3, -10, 10 )\nvar state = random.array.discreteUniform.state\nout = random.array.discreteUniform( 3, -10, 10 )\nout = random.array.discreteUniform( 3, -10, 10 )\nrandom.array.discreteUniform.state = state;\nout = random.array.discreteUniform( 3, -10, 10 )\n","random.array.discreteUniform.stateLength":"var len = random.array.discreteUniform.stateLength;\n","random.array.discreteUniform.byteLength":"var sz = random.array.discreteUniform.byteLength;\n","random.array.erlang":"var out = random.array.erlang( 3, 2, 5.0 )\n","random.array.erlang.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.erlang.assign( 2, 5.0, x )\nvar bool = ( out === x )\n","random.array.erlang.factory":"var fcn = random.array.erlang.factory();\nvar out = fcn( 3, 2, 5.0 )\nfcn = random.array.erlang.factory( 2, 5.0 );\nout = fcn( 3 )\n","random.array.erlang.PRNG":"var prng = random.array.erlang.PRNG;\n","random.array.erlang.seed":"var seed = random.array.erlang.seed;\n","random.array.erlang.seedLength":"var len = random.array.erlang.seedLength;\n","random.array.erlang.state":"var out = random.array.erlang( 3, 2, 5.0 )\nvar state = random.array.erlang.state\nout = random.array.erlang( 3, 2, 5.0 )\nout = random.array.erlang( 3, 2, 5.0 )\nrandom.array.erlang.state = state;\nout = random.array.erlang( 3, 2, 5.0 )\n","random.array.erlang.stateLength":"var len = random.array.erlang.stateLength;\n","random.array.erlang.byteLength":"var sz = random.array.erlang.byteLength;\n","random.array.exponential":"var out = random.array.exponential( 3, 2.0 )\n","random.array.exponential.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.exponential.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.exponential.factory":"var fcn = random.array.exponential.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.exponential.factory( 2.0 );\nout = fcn( 3 )\n","random.array.exponential.PRNG":"var prng = random.array.exponential.PRNG;\n","random.array.exponential.seed":"var seed = random.array.exponential.seed;\n","random.array.exponential.seedLength":"var len = random.array.exponential.seedLength;\n","random.array.exponential.state":"var out = random.array.exponential( 3, 2.0 )\nvar state = random.array.exponential.state\nout = random.array.exponential( 3, 2.0 )\nout = random.array.exponential( 3, 2.0 )\nrandom.array.exponential.state = state;\nout = random.array.exponential( 3, 2.0 )\n","random.array.exponential.stateLength":"var len = random.array.exponential.stateLength;\n","random.array.exponential.byteLength":"var sz = random.array.exponential.byteLength;\n","random.array.f":"var out = random.array.f( 3, 2.0, 5.0 )\n","random.array.f.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.f.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.f.factory":"var fcn = random.array.f.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.f.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.f.PRNG":"var prng = random.array.f.PRNG;\n","random.array.f.seed":"var seed = random.array.f.seed;\n","random.array.f.seedLength":"var len = random.array.f.seedLength;\n","random.array.f.state":"var out = random.array.f( 3, 2.0, 5.0 )\nvar state = random.array.f.state\nout = random.array.f( 3, 2.0, 5.0 )\nout = random.array.f( 3, 2.0, 5.0 )\nrandom.array.f.state = state;\nout = random.array.f( 3, 2.0, 5.0 )\n","random.array.f.stateLength":"var len = random.array.f.stateLength;\n","random.array.f.byteLength":"var sz = random.array.f.byteLength;\n","random.array.frechet":"var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n","random.array.frechet.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.frechet.assign( 2.0, 5.0, 3.0, x )\nvar bool = ( out === x )\n","random.array.frechet.factory":"var fcn = random.array.frechet.factory();\nvar out = fcn( 3, 2.0, 5.0, 3.0 )\nfcn = random.array.frechet.factory( 2.0, 5.0, 3.0 );\nout = fcn( 3 )\n","random.array.frechet.PRNG":"var prng = random.array.frechet.PRNG;\n","random.array.frechet.seed":"var seed = random.array.frechet.seed;\n","random.array.frechet.seedLength":"var len = random.array.frechet.seedLength;\n","random.array.frechet.state":"var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\nvar state = random.array.frechet.state\nout = random.array.frechet( 3, 2.0, 5.0, 3.0 )\nout = random.array.frechet( 3, 2.0, 5.0, 3.0 )\nrandom.array.frechet.state = state;\nout = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n","random.array.frechet.stateLength":"var len = random.array.frechet.stateLength;\n","random.array.frechet.byteLength":"var sz = random.array.frechet.byteLength;\n","random.array.gamma":"var out = random.array.gamma( 3, 2.0, 5.0 )\n","random.array.gamma.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.gamma.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.gamma.factory":"var fcn = random.array.gamma.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.gamma.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.gamma.PRNG":"var prng = random.array.gamma.PRNG;\n","random.array.gamma.seed":"var seed = random.array.gamma.seed;\n","random.array.gamma.seedLength":"var len = random.array.gamma.seedLength;\n","random.array.gamma.state":"var out = random.array.gamma( 3, 2.0, 5.0 )\nvar state = random.array.gamma.state\nout = random.array.gamma( 3, 2.0, 5.0 )\nout = random.array.gamma( 3, 2.0, 5.0 )\nrandom.array.gamma.state = state;\nout = random.array.gamma( 3, 2.0, 5.0 )\n","random.array.gamma.stateLength":"var len = random.array.gamma.stateLength;\n","random.array.gamma.byteLength":"var sz = random.array.gamma.byteLength;\n","random.array.geometric":"var out = random.array.geometric( 3, 0.01 )\n","random.array.geometric.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.geometric.assign( 0.01, x )\nvar bool = ( out === x )\n","random.array.geometric.factory":"var fcn = random.array.geometric.factory();\nvar out = fcn( 3, 0.01 )\nfcn = random.array.geometric.factory( 0.01 );\nout = fcn( 3 )\n","random.array.geometric.PRNG":"var prng = random.array.geometric.PRNG;\n","random.array.geometric.seed":"var seed = random.array.geometric.seed;\n","random.array.geometric.seedLength":"var len = random.array.geometric.seedLength;\n","random.array.geometric.state":"var out = random.array.geometric( 3, 0.01 )\nvar state = random.array.geometric.state\nout = random.array.geometric( 3, 0.01 )\nout = random.array.geometric( 3, 0.01 )\nrandom.array.geometric.state = state;\nout = random.array.geometric( 3, 0.01 )\n","random.array.geometric.stateLength":"var len = random.array.geometric.stateLength;\n","random.array.geometric.byteLength":"var sz = random.array.geometric.byteLength;\n","random.array.gumbel":"var out = random.array.gumbel( 3, 2.0, 5.0 )\n","random.array.gumbel.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.gumbel.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.gumbel.factory":"var fcn = random.array.gumbel.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.gumbel.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.gumbel.PRNG":"var prng = random.array.gumbel.PRNG;\n","random.array.gumbel.seed":"var seed = random.array.gumbel.seed;\n","random.array.gumbel.seedLength":"var len = random.array.gumbel.seedLength;\n","random.array.gumbel.state":"var out = random.array.gumbel( 3, 2.0, 5.0 )\nvar state = random.array.gumbel.state\nout = random.array.gumbel( 3, 2.0, 5.0 )\nout = random.array.gumbel( 3, 2.0, 5.0 )\nrandom.array.gumbel.state = state;\nout = random.array.gumbel( 3, 2.0, 5.0 )\n","random.array.gumbel.stateLength":"var len = random.array.gumbel.stateLength;\n","random.array.gumbel.byteLength":"var sz = random.array.gumbel.byteLength;\n","random.array.hypergeometric":"var out = random.array.hypergeometric( 3, 20, 10, 7 )\n","random.array.hypergeometric.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.hypergeometric.assign( 20, 10, 7, x )\nvar bool = ( out === x )\n","random.array.hypergeometric.factory":"var fcn = random.array.hypergeometric.factory();\nvar out = fcn( 3, 20, 10, 7 )\nfcn = random.array.hypergeometric.factory( 20, 10, 7 );\nout = fcn( 3 )\n","random.array.hypergeometric.PRNG":"var prng = random.array.hypergeometric.PRNG;\n","random.array.hypergeometric.seed":"var seed = random.array.hypergeometric.seed;\n","random.array.hypergeometric.seedLength":"var len = random.array.hypergeometric.seedLength;\n","random.array.hypergeometric.state":"var out = random.array.hypergeometric( 3, 20, 10, 7 )\nvar state = random.array.hypergeometric.state\nout = random.array.hypergeometric( 3, 20, 10, 7 )\nout = random.array.hypergeometric( 3, 20, 10, 7 )\nrandom.array.hypergeometric.state = state;\nout = random.array.hypergeometric( 3, 20, 10, 7 )\n","random.array.hypergeometric.stateLength":"var len = random.array.hypergeometric.stateLength;\n","random.array.hypergeometric.byteLength":"var sz = random.array.hypergeometric.byteLength;\n","random.array.invgamma":"var out = random.array.invgamma( 3, 2.0, 5.0 )\n","random.array.invgamma.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.invgamma.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.invgamma.factory":"var fcn = random.array.invgamma.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.invgamma.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.invgamma.PRNG":"var prng = random.array.invgamma.PRNG;\n","random.array.invgamma.seed":"var seed = random.array.invgamma.seed;\n","random.array.invgamma.seedLength":"var len = random.array.invgamma.seedLength;\n","random.array.invgamma.state":"var out = random.array.invgamma( 3, 2.0, 5.0 )\nvar state = random.array.invgamma.state\nout = random.array.invgamma( 3, 2.0, 5.0 )\nout = random.array.invgamma( 3, 2.0, 5.0 )\nrandom.array.invgamma.state = state;\nout = random.array.invgamma( 3, 2.0, 5.0 )\n","random.array.invgamma.stateLength":"var len = random.array.invgamma.stateLength;\n","random.array.invgamma.byteLength":"var sz = random.array.invgamma.byteLength;\n","random.array.kumaraswamy":"var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n","random.array.kumaraswamy.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.kumaraswamy.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.kumaraswamy.factory":"var fcn = random.array.kumaraswamy.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.kumaraswamy.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.kumaraswamy.PRNG":"var prng = random.array.kumaraswamy.PRNG;\n","random.array.kumaraswamy.seed":"var seed = random.array.kumaraswamy.seed;\n","random.array.kumaraswamy.seedLength":"var len = random.array.kumaraswamy.seedLength;\n","random.array.kumaraswamy.state":"var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\nvar state = random.array.kumaraswamy.state\nout = random.array.kumaraswamy( 3, 2.0, 5.0 )\nout = random.array.kumaraswamy( 3, 2.0, 5.0 )\nrandom.array.kumaraswamy.state = state;\nout = random.array.kumaraswamy( 3, 2.0, 5.0 )\n","random.array.kumaraswamy.stateLength":"var len = random.array.kumaraswamy.stateLength;\n","random.array.kumaraswamy.byteLength":"var sz = random.array.kumaraswamy.byteLength;\n","random.array.laplace":"var out = random.array.laplace( 3, 2.0, 5.0 )\n","random.array.laplace.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.laplace.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.laplace.factory":"var fcn = random.array.laplace.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.laplace.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.laplace.PRNG":"var prng = random.array.laplace.PRNG;\n","random.array.laplace.seed":"var seed = random.array.laplace.seed;\n","random.array.laplace.seedLength":"var len = random.array.laplace.seedLength;\n","random.array.laplace.state":"var out = random.array.laplace( 3, 2.0, 5.0 )\nvar state = random.array.laplace.state\nout = random.array.laplace( 3, 2.0, 5.0 )\nout = random.array.laplace( 3, 2.0, 5.0 )\nrandom.array.laplace.state = state;\nout = random.array.laplace( 3, 2.0, 5.0 )\n","random.array.laplace.stateLength":"var len = random.array.laplace.stateLength;\n","random.array.laplace.byteLength":"var sz = random.array.laplace.byteLength;\n","random.array.levy":"var out = random.array.levy( 3, 2.0, 5.0 )\n","random.array.levy.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.levy.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.levy.factory":"var fcn = random.array.levy.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.levy.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.levy.PRNG":"var prng = random.array.levy.PRNG;\n","random.array.levy.seed":"var seed = random.array.levy.seed;\n","random.array.levy.seedLength":"var len = random.array.levy.seedLength;\n","random.array.levy.state":"var out = random.array.levy( 3, 2.0, 5.0 )\nvar state = random.array.levy.state\nout = random.array.levy( 3, 2.0, 5.0 )\nout = random.array.levy( 3, 2.0, 5.0 )\nrandom.array.levy.state = state;\nout = random.array.levy( 3, 2.0, 5.0 )\n","random.array.levy.stateLength":"var len = random.array.levy.stateLength;\n","random.array.levy.byteLength":"var sz = random.array.levy.byteLength;\n","random.array.logistic":"var out = random.array.logistic( 3, 2.0, 5.0 )\n","random.array.logistic.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.logistic.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.logistic.factory":"var fcn = random.array.logistic.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.logistic.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.logistic.PRNG":"var prng = random.array.logistic.PRNG;\n","random.array.logistic.seed":"var seed = random.array.logistic.seed;\n","random.array.logistic.seedLength":"var len = random.array.logistic.seedLength;\n","random.array.logistic.state":"var out = random.array.logistic( 3, 2.0, 5.0 )\nvar state = random.array.logistic.state\nout = random.array.logistic( 3, 2.0, 5.0 )\nout = random.array.logistic( 3, 2.0, 5.0 )\nrandom.array.logistic.state = state;\nout = random.array.logistic( 3, 2.0, 5.0 )\n","random.array.logistic.stateLength":"var len = random.array.logistic.stateLength;\n","random.array.logistic.byteLength":"var sz = random.array.logistic.byteLength;\n","random.array.lognormal":"var out = random.array.lognormal( 3, 2.0, 5.0 )\n","random.array.lognormal.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.lognormal.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.lognormal.factory":"var fcn = random.array.lognormal.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.lognormal.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.lognormal.PRNG":"var prng = random.array.lognormal.PRNG;\n","random.array.lognormal.seed":"var seed = random.array.lognormal.seed;\n","random.array.lognormal.seedLength":"var len = random.array.lognormal.seedLength;\n","random.array.lognormal.state":"var out = random.array.lognormal( 3, 2.0, 5.0 )\nvar state = random.array.lognormal.state\nout = random.array.lognormal( 3, 2.0, 5.0 )\nout = random.array.lognormal( 3, 2.0, 5.0 )\nrandom.array.lognormal.state = state;\nout = random.array.lognormal( 3, 2.0, 5.0 )\n","random.array.lognormal.stateLength":"var len = random.array.lognormal.stateLength;\n","random.array.lognormal.byteLength":"var sz = random.array.lognormal.byteLength;\n","random.array.minstd":"var out = random.array.minstd( 3 )\n","random.array.minstd.normalized":"var out = random.array.minstd.normalized( 3 )\n","random.array.minstd.factory":"var fcn = random.array.minstd.factory();\nvar out = fcn( 3 )\n","random.array.minstd.PRNG":"var prng = random.array.minstd.PRNG;\n","random.array.minstd.seed":"var seed = random.array.minstd.seed;\n","random.array.minstd.seedLength":"var len = random.array.minstd.seedLength;\n","random.array.minstd.state":"var out = random.array.minstd( 3 )\nvar state = random.array.minstd.state;\nout = random.array.minstd( 3 )\nout = random.array.minstd( 3 )\nrandom.array.minstd.state = state;\nout = random.array.minstd( 3 )\n","random.array.minstd.stateLength":"var len = random.array.minstd.stateLength;\n","random.array.minstd.byteLength":"var sz = random.array.minstd.byteLength;\n","random.array.minstdShuffle":"var out = random.array.minstdShuffle( 3 )\n","random.array.minstdShuffle.normalized":"var out = random.array.minstdShuffle.normalized( 3 )\n","random.array.minstdShuffle.factory":"var fcn = random.array.minstdShuffle.factory();\nvar out = fcn( 3 )\n","random.array.minstdShuffle.PRNG":"var prng = random.array.minstdShuffle.PRNG;\n","random.array.minstdShuffle.seed":"var seed = random.array.minstdShuffle.seed;\n","random.array.minstdShuffle.seedLength":"var len = random.array.minstdShuffle.seedLength;\n","random.array.minstdShuffle.state":"var out = random.array.minstdShuffle( 3 )\nvar state = random.array.minstdShuffle.state;\nout = random.array.minstdShuffle( 3 )\nout = random.array.minstdShuffle( 3 )\nrandom.array.minstdShuffle.state = state;\nout = random.array.minstdShuffle( 3 )\n","random.array.minstdShuffle.stateLength":"var len = random.array.minstdShuffle.stateLength;\n","random.array.minstdShuffle.byteLength":"var sz = random.array.minstdShuffle.byteLength;\n","random.array.mt19937":"var out = random.array.mt19937( 3 )\n","random.array.mt19937.normalized":"var out = random.array.mt19937.normalized( 3 )\n","random.array.mt19937.factory":"var fcn = random.array.mt19937.factory();\nvar out = fcn( 3 )\n","random.array.mt19937.PRNG":"var prng = random.array.mt19937.PRNG;\n","random.array.mt19937.seed":"var seed = random.array.mt19937.seed;\n","random.array.mt19937.seedLength":"var len = random.array.mt19937.seedLength;\n","random.array.mt19937.state":"var out = random.array.mt19937( 3 )\nvar state = random.array.mt19937.state;\nout = random.array.mt19937( 3 )\nout = random.array.mt19937( 3 )\nrandom.array.mt19937.state = state;\nout = random.array.mt19937( 3 )\n","random.array.mt19937.stateLength":"var len = random.array.mt19937.stateLength;\n","random.array.mt19937.byteLength":"var sz = random.array.mt19937.byteLength;\n","random.array.negativeBinomial":"var out = random.array.negativeBinomial( 3, 10, 0.5 )\n","random.array.negativeBinomial.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.negativeBinomial.assign( 10, 0.5, x )\nvar bool = ( out === x )\n","random.array.negativeBinomial.factory":"var fcn = random.array.negativeBinomial.factory();\nvar out = fcn( 3, 10, 0.5 )\nfcn = random.array.negativeBinomial.factory( 10, 0.5 );\nout = fcn( 3 )\n","random.array.negativeBinomial.PRNG":"var prng = random.array.negativeBinomial.PRNG;\n","random.array.negativeBinomial.seed":"var seed = random.array.negativeBinomial.seed;\n","random.array.negativeBinomial.seedLength":"var len = random.array.negativeBinomial.seedLength;\n","random.array.negativeBinomial.state":"var out = random.array.negativeBinomial( 3, 10, 0.5 )\nvar state = random.array.negativeBinomial.state\nout = random.array.negativeBinomial( 3, 10, 0.5 )\nout = random.array.negativeBinomial( 3, 10, 0.5 )\nrandom.array.negativeBinomial.state = state;\nout = random.array.negativeBinomial( 3, 10, 0.5 )\n","random.array.negativeBinomial.stateLength":"var len = random.array.negativeBinomial.stateLength;\n","random.array.negativeBinomial.byteLength":"var sz = random.array.negativeBinomial.byteLength;\n","random.array.normal":"var out = random.array.normal( 3, 2.0, 5.0 )\n","random.array.normal.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.normal.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.normal.factory":"var fcn = random.array.normal.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.normal.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.normal.PRNG":"var prng = random.array.normal.PRNG;\n","random.array.normal.seed":"var seed = random.array.normal.seed;\n","random.array.normal.seedLength":"var len = random.array.normal.seedLength;\n","random.array.normal.state":"var out = random.array.normal( 3, 2.0, 5.0 )\nvar state = random.array.normal.state\nout = random.array.normal( 3, 2.0, 5.0 )\nout = random.array.normal( 3, 2.0, 5.0 )\nrandom.array.normal.state = state;\nout = random.array.normal( 3, 2.0, 5.0 )\n","random.array.normal.stateLength":"var len = random.array.normal.stateLength;\n","random.array.normal.byteLength":"var sz = random.array.normal.byteLength;\n","random.array.pareto1":"var out = random.array.pareto1( 3, 2.0, 5.0 )\n","random.array.pareto1.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.pareto1.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.pareto1.factory":"var fcn = random.array.pareto1.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.pareto1.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.pareto1.PRNG":"var prng = random.array.pareto1.PRNG;\n","random.array.pareto1.seed":"var seed = random.array.pareto1.seed;\n","random.array.pareto1.seedLength":"var len = random.array.pareto1.seedLength;\n","random.array.pareto1.state":"var out = random.array.pareto1( 3, 2.0, 5.0 )\nvar state = random.array.pareto1.state\nout = random.array.pareto1( 3, 2.0, 5.0 )\nout = random.array.pareto1( 3, 2.0, 5.0 )\nrandom.array.pareto1.state = state;\nout = random.array.pareto1( 3, 2.0, 5.0 )\n","random.array.pareto1.stateLength":"var len = random.array.pareto1.stateLength;\n","random.array.pareto1.byteLength":"var sz = random.array.pareto1.byteLength;\n","random.array.poisson":"var out = random.array.poisson( 3, 2.0 )\n","random.array.poisson.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.poisson.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.poisson.factory":"var fcn = random.array.poisson.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.poisson.factory( 2.0 );\nout = fcn( 3 )\n","random.array.poisson.PRNG":"var prng = random.array.poisson.PRNG;\n","random.array.poisson.seed":"var seed = random.array.poisson.seed;\n","random.array.poisson.seedLength":"var len = random.array.poisson.seedLength;\n","random.array.poisson.state":"var out = random.array.poisson( 3, 2.0 )\nvar state = random.array.poisson.state\nout = random.array.poisson( 3, 2.0 )\nout = random.array.poisson( 3, 2.0 )\nrandom.array.poisson.state = state;\nout = random.array.poisson( 3, 2.0 )\n","random.array.poisson.stateLength":"var len = random.array.poisson.stateLength;\n","random.array.poisson.byteLength":"var sz = random.array.poisson.byteLength;\n","random.array.randu":"var out = random.array.randu( 3 )\n","random.array.randu.factory":"var fcn = random.array.randu.factory();\nvar out = fcn( 3 )\n","random.array.randu.PRNG":"var prng = random.array.randu.PRNG;\n","random.array.randu.seed":"var seed = random.array.randu.seed;\n","random.array.randu.seedLength":"var len = random.array.randu.seedLength;\n","random.array.randu.state":"var out = random.array.randu( 3 )\nvar state = random.array.randu.state;\nout = random.array.randu( 3 )\nout = random.array.randu( 3 )\nrandom.array.randu.state = state;\nout = random.array.randu( 3 )\n","random.array.randu.stateLength":"var len = random.array.randu.stateLength;\n","random.array.randu.byteLength":"var sz = random.array.randu.byteLength;\n","random.array.rayleigh":"var out = random.array.rayleigh( 3, 2.0 )\n","random.array.rayleigh.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.rayleigh.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.rayleigh.factory":"var fcn = random.array.rayleigh.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.rayleigh.factory( 2.0 );\nout = fcn( 3 )\n","random.array.rayleigh.PRNG":"var prng = random.array.rayleigh.PRNG;\n","random.array.rayleigh.seed":"var seed = random.array.rayleigh.seed;\n","random.array.rayleigh.seedLength":"var len = random.array.rayleigh.seedLength;\n","random.array.rayleigh.state":"var out = random.array.rayleigh( 3, 2.0 )\nvar state = random.array.rayleigh.state\nout = random.array.rayleigh( 3, 2.0 )\nout = random.array.rayleigh( 3, 2.0 )\nrandom.array.rayleigh.state = state;\nout = random.array.rayleigh( 3, 2.0 )\n","random.array.rayleigh.stateLength":"var len = random.array.rayleigh.stateLength;\n","random.array.rayleigh.byteLength":"var sz = random.array.rayleigh.byteLength;\n","random.array.t":"var out = random.array.t( 3, 2.0 )\n","random.array.t.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.t.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.t.factory":"var fcn = random.array.t.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.t.factory( 2.0 );\nout = fcn( 3 )\n","random.array.t.PRNG":"var prng = random.array.t.PRNG;\n","random.array.t.seed":"var seed = random.array.t.seed;\n","random.array.t.seedLength":"var len = random.array.t.seedLength;\n","random.array.t.state":"var out = random.array.t( 3, 2.0 )\nvar state = random.array.t.state\nout = random.array.t( 3, 2.0 )\nout = random.array.t( 3, 2.0 )\nrandom.array.t.state = state;\nout = random.array.t( 3, 2.0 )\n","random.array.t.stateLength":"var len = random.array.t.stateLength;\n","random.array.t.byteLength":"var sz = random.array.t.byteLength;\n","random.array.triangular":"var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n","random.array.triangular.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.triangular.assign( 2.0, 5.0, 3.0, x )\nvar bool = ( out === x )\n","random.array.triangular.factory":"var fcn = random.array.triangular.factory();\nvar out = fcn( 3, 2.0, 5.0, 3.0 )\nfcn = random.array.triangular.factory( 2.0, 5.0, 3.0 );\nout = fcn( 3 )\n","random.array.triangular.PRNG":"var prng = random.array.triangular.PRNG;\n","random.array.triangular.seed":"var seed = random.array.triangular.seed;\n","random.array.triangular.seedLength":"var len = random.array.triangular.seedLength;\n","random.array.triangular.state":"var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\nvar state = random.array.triangular.state\nout = random.array.triangular( 3, 2.0, 5.0, 3.0 )\nout = random.array.triangular( 3, 2.0, 5.0, 3.0 )\nrandom.array.triangular.state = state;\nout = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n","random.array.triangular.stateLength":"var len = random.array.triangular.stateLength;\n","random.array.triangular.byteLength":"var sz = random.array.triangular.byteLength;\n","random.array.uniform":"var out = random.array.uniform( 3, 2.0, 5.0 )\n","random.array.uniform.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.uniform.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.uniform.factory":"var fcn = random.array.uniform.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.uniform.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.uniform.PRNG":"var prng = random.array.uniform.PRNG;\n","random.array.uniform.seed":"var seed = random.array.uniform.seed;\n","random.array.uniform.seedLength":"var len = random.array.uniform.seedLength;\n","random.array.uniform.state":"var out = random.array.uniform( 3, 2.0, 5.0 )\nvar state = random.array.uniform.state\nout = random.array.uniform( 3, 2.0, 5.0 )\nout = random.array.uniform( 3, 2.0, 5.0 )\nrandom.array.uniform.state = state;\nout = random.array.uniform( 3, 2.0, 5.0 )\n","random.array.uniform.stateLength":"var len = random.array.uniform.stateLength;\n","random.array.uniform.byteLength":"var sz = random.array.uniform.byteLength;\n","random.array.weibull":"var out = random.array.weibull( 3, 2.0, 5.0 )\n","random.array.weibull.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.weibull.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.weibull.factory":"var fcn = random.array.weibull.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.weibull.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.weibull.PRNG":"var prng = random.array.weibull.PRNG;\n","random.array.weibull.seed":"var seed = random.array.weibull.seed;\n","random.array.weibull.seedLength":"var len = random.array.weibull.seedLength;\n","random.array.weibull.state":"var out = random.array.weibull( 3, 2.0, 5.0 )\nvar state = random.array.weibull.state\nout = random.array.weibull( 3, 2.0, 5.0 )\nout = random.array.weibull( 3, 2.0, 5.0 )\nrandom.array.weibull.state = state;\nout = random.array.weibull( 3, 2.0, 5.0 )\n","random.array.weibull.stateLength":"var len = random.array.weibull.stateLength;\n","random.array.weibull.byteLength":"var sz = random.array.weibull.byteLength;\n","random.iterators.arcsine":"var it = random.iterators.arcsine( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.bernoulli":"var it = random.iterators.bernoulli( 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.beta":"var it = random.iterators.beta( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.betaprime":"var it = random.iterators.betaprime( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.binomial":"var it = random.iterators.binomial( 10, 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.boxMuller":"var it = random.iterators.boxMuller();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.cauchy":"var it = random.iterators.cauchy( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.chi":"var it = random.iterators.chi( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.chisquare":"var it = random.iterators.chisquare( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.cosine":"var it = random.iterators.cosine( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.discreteUniform":"var it = random.iterators.discreteUniform( 0, 3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.erlang":"var it = random.iterators.erlang( 1, 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.exponential":"var it = random.iterators.exponential( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.f":"var it = random.iterators.f( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.frechet":"var it = random.iterators.frechet( 1.0, 1.0, 0.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.gamma":"var it = random.iterators.gamma( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.geometric":"var it = random.iterators.geometric( 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.gumbel":"var it = random.iterators.gumbel( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.hypergeometric":"var it = random.iterators.hypergeometric( 20, 10, 7 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.improvedZiggurat":"var it = random.iterators.improvedZiggurat();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.invgamma":"var it = random.iterators.invgamma( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.kumaraswamy":"var it = random.iterators.kumaraswamy( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.laplace":"var it = random.iterators.laplace( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.levy":"var it = random.iterators.levy( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.logistic":"var it = random.iterators.logistic( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.lognormal":"var it = random.iterators.lognormal( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.minstd":"var it = random.iterators.minstd();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.minstdShuffle":"var it = random.iterators.minstdShuffle();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.mt19937":"var it = random.iterators.mt19937();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.negativeBinomial":"var it = random.iterators.negativeBinomial( 10, 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.normal":"var it = random.iterators.normal( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.pareto1":"var it = random.iterators.pareto1( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.poisson":"var it = random.iterators.poisson( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.randi":"var it = random.iterators.randi();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.randn":"var it = random.iterators.randn();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.randu":"var it = random.iterators.randu();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.rayleigh":"var it = random.iterators.rayleigh( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.t":"var it = random.iterators.t( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.triangular":"var it = random.iterators.triangular( 0.0, 1.0, 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.uniform":"var it = random.iterators.uniform( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.weibull":"var it = random.iterators.weibull( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.streams.arcsine":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.arcsine( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.arcsine.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.arcsine.factory( opts );\n","random.streams.arcsine.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.arcsine.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.bernoulli":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.bernoulli( 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.bernoulli.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.bernoulli.factory( opts );\n","random.streams.bernoulli.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.bernoulli.objectMode( 0.3, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.beta":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.beta( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.beta.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.beta.factory( opts );\n","random.streams.beta.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.beta.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.betaprime":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.betaprime( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.betaprime.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.betaprime.factory( opts );\n","random.streams.betaprime.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.betaprime.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.binomial":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.binomial( 20, 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.binomial.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.binomial.factory( opts );\n","random.streams.binomial.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.binomial.objectMode( 20, 0.5, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.boxMuller":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.boxMuller( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.boxMuller.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.boxMuller.factory( opts );\n","random.streams.boxMuller.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.boxMuller.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.cauchy":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cauchy( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.cauchy.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.cauchy.factory( opts );\n","random.streams.cauchy.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cauchy.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.chi":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chi( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.chi.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.chi.factory( opts );\n","random.streams.chi.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chi.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.chisquare":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chisquare( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.chisquare.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.chisquare.factory( opts );\n","random.streams.chisquare.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chisquare.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.cosine":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cosine( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.cosine.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.cosine.factory( opts );\n","random.streams.cosine.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cosine.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.discreteUniform":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.discreteUniform( 2, 5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.discreteUniform.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.discreteUniform.factory( opts );\n","random.streams.discreteUniform.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.discreteUniform.objectMode( 2, 5, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.erlang":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.erlang( 2, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.erlang.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.erlang.factory( opts );\n","random.streams.erlang.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.erlang.objectMode( 2, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.exponential":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.exponential( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.exponential.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.exponential.factory( opts );\n","random.streams.exponential.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.exponential.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.f":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.f( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.f.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.f.factory( opts );\n","random.streams.f.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.f.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.frechet":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.frechet( 2.0, 5.0, 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.frechet.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.frechet.factory( opts );\n","random.streams.frechet.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.frechet.objectMode( 2.0, 5.0, 3.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.gamma":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gamma( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.gamma.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.gamma.factory( opts );\n","random.streams.gamma.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gamma.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.geometric":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.geometric( 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.geometric.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.geometric.factory( opts );\n","random.streams.geometric.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.geometric.objectMode( 0.3, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.gumbel":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gumbel( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.gumbel.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.gumbel.factory( opts );\n","random.streams.gumbel.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gumbel.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.hypergeometric":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.hypergeometric( 5, 3, 2, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.hypergeometric.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.hypergeometric.factory( opts );\n","random.streams.hypergeometric.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.hypergeometric.objectMode( 5, 3, 2, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.improvedZiggurat":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.improvedZiggurat( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.improvedZiggurat.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.improvedZiggurat.factory( opts );\n","random.streams.improvedZiggurat.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.improvedZiggurat.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.invgamma":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.invgamma( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.invgamma.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.invgamma.factory( opts );\n","random.streams.invgamma.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.invgamma.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.kumaraswamy":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.kumaraswamy( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.kumaraswamy.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.kumaraswamy.factory( opts );\n","random.streams.kumaraswamy.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.kumaraswamy.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.laplace":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.laplace( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.laplace.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.laplace.factory( opts );\n","random.streams.laplace.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.laplace.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.levy":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.levy( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.levy.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.levy.factory( opts );\n","random.streams.levy.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.levy.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.logistic":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.logistic( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.logistic.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.logistic.factory( opts );\n","random.streams.logistic.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.logistic.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.lognormal":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.lognormal( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.lognormal.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.lognormal.factory( opts );\n","random.streams.lognormal.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.lognormal.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.minstd":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstd( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.minstd.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.minstd.factory( opts );\n","random.streams.minstd.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstd.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.minstdShuffle":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstdShuffle( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.minstdShuffle.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.minstdShuffle.factory( opts );\n","random.streams.minstdShuffle.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstdShuffle.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.mt19937":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.mt19937( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.mt19937.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.mt19937.factory( opts );\n","random.streams.mt19937.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.mt19937.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.negativeBinomial":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.negativeBinomial( 20.0, 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.negativeBinomial.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.negativeBinomial.factory( opts );\n","random.streams.negativeBinomial.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.negativeBinomial.objectMode( 20.0, 0.5, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.normal":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.normal( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.normal.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.normal.factory( opts );\n","random.streams.normal.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.normal.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.pareto1":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.pareto1( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.pareto1.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.pareto1.factory( opts );\n","random.streams.pareto1.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.pareto1.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.poisson":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.poisson( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.poisson.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.poisson.factory( opts );\n","random.streams.poisson.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.poisson.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.randi":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randi( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.randi.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.randi.factory( opts );\n","random.streams.randi.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randi.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.randn":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randn( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.randn.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.randn.factory( opts );\n","random.streams.randn.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randn.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.randu":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randu( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.randu.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.randu.factory( opts );\n","random.streams.randu.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randu.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.rayleigh":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.rayleigh( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.rayleigh.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.rayleigh.factory( opts );\n","random.streams.rayleigh.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.rayleigh.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.t":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.t( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.t.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.t.factory( opts );\n","random.streams.t.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.t.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.triangular":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.triangular( 2.0, 5.0, 4.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.triangular.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.triangular.factory( opts );\n","random.streams.triangular.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.triangular.objectMode( 2.0, 5.0, 4.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.uniform":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.uniform( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.uniform.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.uniform.factory( opts );\n","random.streams.uniform.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.uniform.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.weibull":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.weibull( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.weibull.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.weibull.factory( opts );\n","random.streams.weibull.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.weibull.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.strided.arcsine":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.arcsine( out.length, a, 1, b, 1, out, 1 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.arcsine( 3, a, -2, b, 1, out, 1 )\n","random.strided.arcsine.ndarray":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.arcsine.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.arcsine.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.bernoulli":"var out = azeros( 5, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n","random.strided.bernoulli.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.bernoulli.ndarray( out.length, [ 0.5 ], 0, 0, out, 1, 0 )\n","random.strided.bernoulli.factory":"var fcn = random.strided.bernoulli.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 0.5 ], 0, out, 1 )\n","random.strided.bernoulli.PRNG":"var prng = random.strided.bernoulli.PRNG;\n","random.strided.bernoulli.seed":"var seed = random.strided.bernoulli.seed;\n","random.strided.bernoulli.seedLength":"var len = random.strided.bernoulli.seedLength;\n","random.strided.bernoulli.state":"var out = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\nvar state = random.strided.bernoulli.state\nout = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\nrandom.strided.bernoulli.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n","random.strided.bernoulli.stateLength":"var len = random.strided.bernoulli.stateLength;\n","random.strided.bernoulli.byteLength":"var sz = random.strided.bernoulli.byteLength;\n","random.strided.beta":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.beta( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.beta( 3, a, -2, b, 1, out, 1 )\n","random.strided.beta.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.beta.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.beta.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.betaprime":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.betaprime( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.betaprime( 3, a, -2, b, 1, out, 1 )\n","random.strided.betaprime.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.betaprime.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.betaprime.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.chi":"var out = azeros( 5, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chi.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.chi.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.chi.factory":"var fcn = random.strided.chi.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chi.PRNG":"var prng = random.strided.chi.PRNG;\n","random.strided.chi.seed":"var seed = random.strided.chi.seed;\n","random.strided.chi.seedLength":"var len = random.strided.chi.seedLength;\n","random.strided.chi.state":"var out = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.chi.state\nout = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.chi.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chi.stateLength":"var len = random.strided.chi.stateLength;\n","random.strided.chi.byteLength":"var sz = random.strided.chi.byteLength;\n","random.strided.chisquare":"var out = azeros( 5, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chisquare.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.chisquare.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.chisquare.factory":"var fcn = random.strided.chisquare.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chisquare.PRNG":"var prng = random.strided.chisquare.PRNG;\n","random.strided.chisquare.seed":"var seed = random.strided.chisquare.seed;\n","random.strided.chisquare.seedLength":"var len = random.strided.chisquare.seedLength;\n","random.strided.chisquare.state":"var out = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.chisquare.state\nout = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.chisquare.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chisquare.stateLength":"var len = random.strided.chisquare.stateLength;\n","random.strided.chisquare.byteLength":"var sz = random.strided.chisquare.byteLength;\n","random.strided.cosine":"var mu = linspace( 0.0, 1.0, 5 );\nvar s = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.cosine( out.length, mu, 1, s, 1, out, 1 )\nmu = linspace( 0.0, 1.0, 6 );\ns = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.cosine( 3, mu, -2, s, 1, out, 1 )\n","random.strided.cosine.ndarray":"var mu = linspace( 0.0, 1.0, 5 );\nvar s = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.cosine.ndarray( out.length, mu, 1, 0, s, 1, 0, out, 1, 0 )\nmu = linspace( 0.0, 1.0, 6 );\ns = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.cosine.ndarray( 3, mu, 2, 1, s, -1, s.length-1, out, 1, 0 )\n","random.strided.discreteUniform":"var a = [ -10, -5, 0, 5, 10 ];\nvar b = [ 20, 20, 20, 20, 20 ];\nvar out = azeros( 5, 'generic' );\nrandom.strided.discreteUniform( out.length, a, 1, b, 1, out, 1 )\na = [ -10, -5, 0, 5, 10, 15 ];\nb = [ 20, 20, 20, 20, 20, 20 ];\nout = azeros( 6, 'generic' );\nrandom.strided.discreteUniform( 3, a, -2, b, 1, out, 1 )\n","random.strided.discreteUniform.ndarray":"var a = [ -10, -5, 0, 5, 10 ];\nvar b = [ 20, 20, 20, 20, 20 ];\nvar out = azeros( 5, 'generic' );\nrandom.strided.discreteUniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = [ -10, -5, 0, 5, 10, 15 ];\nb = [ 20, 20, 20, 20, 20, 20 ];\nout = azeros( 6, 'generic' );\nrandom.strided.discreteUniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.exponential":"var out = azeros( 5, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.exponential.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.exponential.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.exponential.factory":"var fcn = random.strided.exponential.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.exponential.PRNG":"var prng = random.strided.exponential.PRNG;\n","random.strided.exponential.seed":"var seed = random.strided.exponential.seed;\n","random.strided.exponential.seedLength":"var len = random.strided.exponential.seedLength;\n","random.strided.exponential.state":"var out = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.exponential.state\nout = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.exponential.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.exponential.stateLength":"var len = random.strided.exponential.stateLength;\n","random.strided.exponential.byteLength":"var sz = random.strided.exponential.byteLength;\n","random.strided.gamma":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.gamma( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.gamma( 3, a, -2, b, 1, out, 1 )\n","random.strided.gamma.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.gamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.gamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.geometric":"var out = azeros( 5, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n","random.strided.geometric.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.geometric.ndarray( out.length, [ 0.01 ], 0, 0, out, 1, 0 )\n","random.strided.geometric.factory":"var fcn = random.strided.geometric.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 0.01 ], 0, out, 1 )\n","random.strided.geometric.PRNG":"var prng = random.strided.geometric.PRNG;\n","random.strided.geometric.seed":"var seed = random.strided.geometric.seed;\n","random.strided.geometric.seedLength":"var len = random.strided.geometric.seedLength;\n","random.strided.geometric.state":"var out = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\nvar state = random.strided.geometric.state\nout = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\nrandom.strided.geometric.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n","random.strided.geometric.stateLength":"var len = random.strided.geometric.stateLength;\n","random.strided.geometric.byteLength":"var sz = random.strided.geometric.byteLength;\n","random.strided.invgamma":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.invgamma( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.invgamma( 3, a, -2, b, 1, out, 1 )\n","random.strided.invgamma.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.invgamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.invgamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.lognormal":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.lognormal( out.length, mu, 1, sigma, 1, out, 1 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.lognormal( 3, mu, -2, sigma, 1, out, 1 )\n","random.strided.lognormal.ndarray":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.lognormal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.lognormal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n","random.strided.minstd":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd( out.length, out, 1 )\n","random.strided.minstd.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd.ndarray( out.length, out, 1, 0 )\n","random.strided.minstd.normalized":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd.normalized( out.length, out, 1 )\n","random.strided.minstd.normalized.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd.normalized.ndarray( out.length, out, 1, 0 )\n","random.strided.minstdShuffle":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle( out.length, out, 1 )\n","random.strided.minstdShuffle.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle.ndarray( out.length, out, 1, 0 )\n","random.strided.minstdShuffle.normalized":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle.normalized( out.length, out, 1 )\n","random.strided.minstdShuffle.normalized.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle.normalized.ndarray( out.length, out, 1, 0 )\n","random.strided.mt19937":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937( out.length, out, 1 )\n","random.strided.mt19937.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937.ndarray( out.length, out, 1, 0 )\n","random.strided.mt19937.normalized":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937.normalized( out.length, out, 1 )\n","random.strided.mt19937.normalized.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937.normalized.ndarray( out.length, out, 1, 0 )\n","random.strided.normal":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.normal( out.length, mu, 1, sigma, 1, out, 1 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.normal( 3, mu, -2, sigma, 1, out, 1 )\n","random.strided.normal.ndarray":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.normal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.normal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n","random.strided.poisson":"var out = azeros( 5, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.poisson.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.poisson.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.poisson.factory":"var fcn = random.strided.poisson.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.poisson.PRNG":"var prng = random.strided.poisson.PRNG;\n","random.strided.poisson.seed":"var seed = random.strided.poisson.seed;\n","random.strided.poisson.seedLength":"var len = random.strided.poisson.seedLength;\n","random.strided.poisson.state":"var out = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.poisson.state\nout = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.poisson.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.poisson.stateLength":"var len = random.strided.poisson.stateLength;\n","random.strided.poisson.byteLength":"var sz = random.strided.poisson.byteLength;\n","random.strided.randu":"var out = azeros( 5, 'generic' );\nrandom.strided.randu( out.length, out, 1 )\n","random.strided.randu.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.randu.ndarray( out.length, out, 1, 0 )\n","random.strided.rayleigh":"var out = azeros( 5, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.rayleigh.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.rayleigh.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.rayleigh.factory":"var fcn = random.strided.rayleigh.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.rayleigh.PRNG":"var prng = random.strided.rayleigh.PRNG;\n","random.strided.rayleigh.seed":"var seed = random.strided.rayleigh.seed;\n","random.strided.rayleigh.seedLength":"var len = random.strided.rayleigh.seedLength;\n","random.strided.rayleigh.state":"var out = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.rayleigh.state\nout = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.rayleigh.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.rayleigh.stateLength":"var len = random.strided.rayleigh.stateLength;\n","random.strided.rayleigh.byteLength":"var sz = random.strided.rayleigh.byteLength;\n","random.strided.t":"var out = azeros( 5, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.t.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.t.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.t.factory":"var fcn = random.strided.t.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.t.PRNG":"var prng = random.strided.t.PRNG;\n","random.strided.t.seed":"var seed = random.strided.t.seed;\n","random.strided.t.seedLength":"var len = random.strided.t.seedLength;\n","random.strided.t.state":"var out = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.t.state\nout = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.t.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.t.stateLength":"var len = random.strided.t.stateLength;\n","random.strided.t.byteLength":"var sz = random.strided.t.byteLength;\n","random.strided.uniform":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.uniform( out.length, a, 1, b, 1, out, 1 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.uniform( 3, a, -2, b, 1, out, 1 )\n","random.strided.uniform.ndarray":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.uniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.uniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.weibull":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.weibull( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.weibull( 3, a, -2, b, 1, out, 1 )\n","random.strided.weibull.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.weibull.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.weibull.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","ranks":"var arr = [ 1.1, 2.0, 3.5, 0.0, 2.4 ] ;\nvar out = ranks( arr )\narr =  [ 2, 2, 1, 4, 3 ];\nout = ranks( arr )\narr = [ null, 2, 2, 1, 4, 3, NaN, NaN ];\nout = ranks( arr )\n","readDir":"function onRead( error, data ) {\n if ( error ) {\n     console.error( error.message );\n } else {\n     console.log( data );\n }\n };\nreadDir( './beep/boop', onRead );\n","readDir.sync":"var out = readDir.sync( './beep/boop' );\n","readFile":"function onRead( error, data ) {\n if ( error ) {\n     console.error( error.message );\n } else {\n     console.log( data );\n }\n };\nreadFile( './beep/boop.js', onRead );\n","readFile.sync":"var out = readFile.sync( './beep/boop.js' );\n","readFileList":"function onRead( error, data ) {\n if ( error ) {\n     console.error( error.message );\n } else {\n     console.log( data );\n }\n };\nvar filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\nreadFileList( filepaths, onRead );\n","readFileList.sync":"var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\nvar out = readFileList.sync( filepaths );\n","readJSON":"function onRead( error, data ) {\n if ( error ) {\n     console.error( error.message );\n } else {\n     console.log( data );\n }\n };\nreadJSON( './beep/boop.json', onRead );\n","readJSON.sync":"var out = readJSON.sync( './beep/boop.json' );\n","readWASM":"function onRead( error, data ) {\n if ( error ) {\n     console.error( error.message );\n } else {\n     console.log( data );\n }\n };\nreadWASM( './beep/boop.wasm', onRead );\n","readWASM.sync":"var out = readWASM.sync( './beep/boop.wasm' );\n","real":"var z = new Complex128( 5.0, 3.0 );\nvar re = real( z )\n","realarray":"var arr = realarray()\narr = realarray( 'float32' )\nvar arr = realarray( 5 )\narr = realarray( 5, 'int32' )\nvar arr1 = realarray( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = realarray( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = realarray( arr1, 'float32' )\nvar buf = new ArrayBuffer( 16 );\nvar arr = realarray( buf, 0, 4, 'float32' )\n","realarrayCtors":"var ctor = realarrayCtors( 'float64' )\nctor = realarrayCtors( 'float' )\n","realarrayDataTypes":"var out = realarrayDataTypes()\n","realf":"var z = new Complex64( 5.0, 3.0 );\nvar re = realf( z )\n","realmax":"var m = realmax( 'float16' )\nm = realmax( 'float32' )\n","realmin":"var m = realmin( 'float16' )\nm = realmin( 'float32' )\n","reBasename":"var RE = reBasename()\nvar RE_POSIX = reBasename( 'posix' );\nvar RE_WIN32 = reBasename( 'win32' );\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reBasename.REGEXP":"var RE = reBasename.REGEXP\n","reBasename.REGEXP_POSIX":"var base = reBasename.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n","reBasename.REGEXP_WIN32":"var base = reBasename.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reBasenamePosix":"var RE_BASENAME_POSIX = reBasenamePosix();\nvar base = RE_BASENAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( 'index.js' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( '.' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( './' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( '' )[ 1 ]\n","reBasenamePosix.REGEXP":"var base = reBasenamePosix.REGEXP.exec( 'foo/bar/index.js' )[ 1 ]\n","reBasenameWindows":"var RE_BASENAME_WINDOWS = reBasenameWindows();\nvar base = RE_BASENAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\index.js' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'foo\\\\file.pdf' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'foo\\\\bar\\\\file' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'index.js' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( '.' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( '' )[ 1 ]\n","reBasenameWindows.REGEXP":"var match = reBasenameWindows.REGEXP.exec( 'foo\\\\file.pdf' )[ 1 ]\n","reColorHexadecimal":"var RE = reColorHexadecimal();\nvar bool = RE.test( 'ffffff' )\nbool = RE.test( '000' )\nbool = RE.test( 'beep' )\n","reColorHexadecimal.REGEXP":"var bool = reColorHexadecimal.REGEXP.test( 'ffffff' )\nbool = reColorHexadecimal.REGEXP.test( '000' )\nbool = reColorHexadecimal.REGEXP.test( 'beep' )\n","reColorHexadecimal.REGEXP_SHORTHAND":"var bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'ffffff' )\nbool = reColorHexadecimal.REGEXP_SHORTHAND.test( '000' )\nbool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'beep' )\n","reColorHexadecimal.REGEXP_EITHER":"var bool = reColorHexadecimal.REGEXP_EITHER.test( 'ffffff' )\nbool = reColorHexadecimal.REGEXP_EITHER.test( '000' )\nbool = reColorHexadecimal.REGEXP_EITHER.test( 'beep' )\n","reDecimalNumber":"var RE = reDecimalNumber();\nvar bool = RE.test( '1.234' )\nbool = RE.test( '-1.234' )\nbool = RE.test( '0.0' )\nbool = RE.test( '.0' )\nbool = RE.test( '0' )\nbool = RE.test( 'beep' )\nvar re = reDecimalNumber({ 'flags': 'g' });\nvar str = '1.234 5.6, 7.8';\nvar out = str.match( re )\n","reDecimalNumber.REGEXP":"var RE = reDecimalNumber.REGEXP;\nvar bool = RE.test( '1.234' )\nbool = RE.test( '-1.234' )\n","reDecimalNumber.REGEXP_CAPTURE":"var RE = reDecimalNumber.REGEXP_CAPTURE;\nvar str = '1.02';\nvar out = replace( str, RE, '$1 x $1' )\n","reDirname":"var RE = reDirname()\nvar RE_POSIX = reDirname( 'posix' );\nvar dir = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\nvar RE_WIN32 = reDirname( 'win32' );\ndir = RE_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reDirname.REGEXP":"var RE = reDirname.REGEXP\n","reDirname.REGEXP_POSIX":"var dir = reDirname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n","reDirname.REGEXP_WIN32":"var dir = reDirname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reDirnamePosix":"var RE = reDirnamePosix();\nvar dir = RE.exec( '/foo/bar/index.js' )[ 1 ]\ndir = RE.exec( './foo/bar/.gitignore' )[ 1 ]\ndir = RE.exec( 'foo/file.pdf' )[ 1 ]\ndir = RE.exec( '/foo/bar/file' )[ 1 ]\ndir = RE.exec( 'index.js' )[ 1 ]\ndir = RE.exec( '.' )[ 1 ]\ndir = RE.exec( './' )[ 1 ]\ndir = RE.exec( '' )[ 1 ]\n","reDirnamePosix.REGEXP":"var ext = reDirnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n","reDirnameWindows":"var RE = reDirnameWindows();\nvar dir = RE.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\ndir = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\ndir = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\ndir = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\ndir = RE.exec( 'index.js' )[ 1 ]\ndir = RE.exec( '' )[ 1 ]\n","reDirnameWindows.REGEXP":"var dir = reDirnameWindows.REGEXP.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n","reduce":"var f = naryFunction( base.add, 2 );\nvar arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\nvar out = reduce( arr, 0.0, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = reduce( arr, 0.0, f )\n","reduce2d":"var f = naryFunction( base.add, 2 );\nvar arr = [ [ 1, 2, 3 ], [ 4, 5, 6 ] ];\nvar out = reduce2d( arr, [ 0, 0 ], f )\n","reduceAsync":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     acc.sum += value;\n     next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n     throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nreduceAsync( arr, acc, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     acc.sum += value;\n     next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n     throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nreduceAsync( arr, acc, opts, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     acc.sum += value;\n     next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n     throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'series': false };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nreduceAsync( arr, acc, opts, fcn, done )\n","reduceAsync.factory":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     acc.sum += value;\n     next( null, acc );\n }\n };\nvar opts = { 'series': false };\nvar f = reduceAsync.factory( opts, fcn );\nfunction done( error, acc ) {\n if ( error ) {\n     throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nf( arr, acc, done )\nacc = { 'sum': 0 };\narr = [ 2000, 1500, 1000 ];\nf( arr, acc, done )\n","reduceRight":"var f = naryFunction( base.add, 2 );\nvar arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\nvar out = reduceRight( arr, 0.0, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = reduceRight( arr, 0.0, f )\n","reduceRightAsync":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     acc.sum += value;\n     next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n     throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nreduceRightAsync( arr, acc, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     acc.sum += value;\n     next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n     throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nreduceRightAsync( arr, acc, opts, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     acc.sum += value;\n     next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n     throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'series': false };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nreduceRightAsync( arr, acc, opts, fcn, done )\n","reduceRightAsync.factory":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     acc.sum += value;\n     next( null, acc );\n }\n };\nvar opts = { 'series': false };\nvar f = reduceRightAsync.factory( opts, fcn );\nfunction done( error, acc ) {\n if ( error ) {\n     throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nf( arr, acc, done )\nacc = { 'sum': 0 };\narr = [ 1000, 1500, 2000 ];\nf( arr, acc, done )\n","reDurationString":"var RE = reDurationString();\nvar parts = RE.exec( '3d2ms' )\nparts = RE.exec( '4h3m20s' )\n","reDurationString.REGEXP":"var bool = reDurationString.REGEXP.test( '3d2ms' )\nbool = reDurationString.REGEXP.test( 'foo' )\n","reEOL":"var RE_EOL = reEOL();\nvar bool = RE_EOL.test( '\\n' )\nbool = RE_EOL.test( '\\r\\n' )\nbool = RE_EOL.test( '\\\\r\\\\n' )\n","reEOL.REGEXP":"var bool = reEOL.REGEXP.test( 'abc' )\n","reEOL.REGEXP_CAPTURE":"var parts = reEOL.REGEXP_CAPTURE.exec( '\\n' )\n","reExtendedLengthPath":"var RE = reExtendedLengthPath();\nvar path = '\\\\\\\\?\\\\C:\\\\foo\\\\bar';\nvar bool = RE.test( path )\npath = '\\\\\\\\?\\\\UNC\\\\server\\\\share';\nbool = RE.test( path )\npath = 'C:\\\\foo\\\\bar';\nbool = RE.test( path )\npath = '/c/foo/bar';\nbool = RE.test( path )\npath = '/foo/bar';\nbool = RE.test( path )\n","reExtendedLengthPath.REGEXP":"var bool = reExtendedLengthPath.REGEXP.test( 'C:\\\\foo\\\\bar' )\n","reExtname":"var RE = reExtname()\nvar RE_POSIX = reExtname( 'posix' );\nvar ext = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\nvar RE_WIN32 = reExtname( 'win32' );\next = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reExtname.REGEXP":"var RE = reExtname.REGEXP\n","reExtname.REGEXP_POSIX":"var ext = reExtname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n","reExtname.REGEXP_WIN32":"var ext = reExtname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reExtnamePosix":"var RE = reExtnamePosix();\nvar ext = RE.exec( '/foo/bar/index.js' )[ 1 ]\next = RE.exec( './foo/bar/.gitignore' )[ 1 ]\next = RE.exec( 'foo/file.pdf' )[ 1 ]\next = RE.exec( '/foo/bar/file' )[ 1 ]\next = RE.exec( 'index.js' )[ 1 ]\next = RE.exec( '.' )[ 1 ]\next = RE.exec( './' )[ 1 ]\next = RE.exec( '' )[ 1 ]\n","reExtnamePosix.REGEXP":"var ext = reExtnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n","reExtnameWindows":"var RE = reExtnameWindows();\nvar ext = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\next = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\next = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\next = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\next = RE.exec( 'beep\\\\boop.' )[ 1 ]\next = RE.exec( 'index.js' )[ 1 ]\next = RE.exec( '' )[ 1 ]\n","reExtnameWindows.REGEXP":"var ext = reExtnameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reFilename":"var RE = reFilename()\nvar RE_POSIX = reFilename( 'posix' );\nvar parts = RE_POSIX.exec( '/foo/bar/index.js' ).slice()\nvar RE_WIN32 = reFilename( 'win32' );\nparts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reFilename.REGEXP":"var RE = reFilename.REGEXP\n","reFilename.REGEXP_POSIX":"var f = '/foo/bar/index.js';\nvar parts = reFilename.REGEXP_POSIX.exec( f ).slice()\n","reFilename.REGEXP_WIN32":"var f = 'C:\\\\foo\\\\bar\\\\index.js';\nvar parts = reFilename.REGEXP_WIN32.exec( f ).slice()\n","reFilenamePosix":"var RE = reFilenamePosix();\nvar parts = RE.exec( '/foo/bar/index.js' ).slice()\nparts = RE.exec( './foo/bar/.gitignore' ).slice()\nparts = RE.exec( 'foo/file.pdf' ).slice()\nparts = RE.exec( '/foo/bar/file' ).slice()\nparts = RE.exec( 'index.js' ).slice()\nparts = RE.exec( '.' ).slice()\nparts = RE.exec( './' ).slice()\nparts = RE.exec( '' ).slice()\n","reFilenamePosix.REGEXP":"var parts = reFilenamePosix.REGEXP.exec( '/foo/bar/index.js' ).slice()\n","reFilenameWindows":"var RE = reFilenameWindows();\nvar parts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\nparts = RE.exec( '\\\\foo\\\\bar\\\\.gitignore' ).slice()\nparts = RE.exec( 'foo\\\\file.pdf' ).slice()\nparts = RE.exec( '\\\\foo\\\\bar\\\\file' ).slice()\nparts = RE.exec( 'index.js' ).slice()\nparts = RE.exec( '.' ).slice()\nparts = RE.exec( './' ).slice()\nparts = RE.exec( '' ).slice()\n","reFilenameWindows.REGEXP":"var parts = reFilenameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n","reFromString":"var re = reFromString( '/beep/' )\nre = reFromString( '/beep' )\n","reFunctionName":"var RE_FUNCTION_NAME = reFunctionName();\nfunction beep() { return 'boop'; };\nvar name = RE_FUNCTION_NAME.exec( beep.toString() )[ 1 ]\nname = RE_FUNCTION_NAME.exec( function () {} )[ 1 ]\n","reFunctionName.REGEXP":"var str = reFunctionName.REGEXP.exec( Math.sqrt.toString() )[ 1 ]\n","regexp2json":"var json = regexp2json( /ab+c/ )\n","reim":"var z = new Complex128( 5.0, 3.0 );\nvar out = reim( z )\n","reimf":"var z = new Complex64( 5.0, 3.0 );\nvar out = reimf( z )\n","rejectArguments":"function foo( a, b ) { return [ a, b ]; };\nfunction predicate( v ) { return ( v === 2 ); };\nvar bar = rejectArguments( foo, predicate );\nvar out = bar( 1, 2, 3 )\n","removeFirst":"var out = removeFirst( 'beep' )\nout = removeFirst( 'Boop' )\nout = removeFirst( 'foo bar', 4 )\n","removeLast":"var out = removeLast( 'beep' )\nout = removeLast( 'Boop' )\nout = removeLast( 'foo bar', 4 )\n","removePunctuation":"var str = 'Sun Tzu said: \"A leader leads by example not by force.\"';\nvar out = removePunctuation( str )\nstr = 'This function removes these characters: `{}[]:,!/<>().;~|?\\'\"';\nout = removePunctuation( str )\n","removeUTF8BOM":"var out = removeUTF8BOM( '\\ufeffbeep' )\n","removeWords":"var out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ] )\nout = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ], true )\n","rename":"function done( error ) {\n if ( error ) {\n     console.error( error.message );\n }\n };\nrename( './beep/boop.txt', './beep/foo.txt', done );\n","rename.sync":"var err = rename.sync( './beep/boop.txt', './beep/foo.txt' );\n","reNativeFunction":"var RE = reNativeFunction();\nvar bool = RE.test( Date.toString() )\nbool = RE.test( (function noop() {}).toString() )\n","reNativeFunction.REGEXP":"var bool = reNativeFunction.REGEXP.test( Date.toString() )\nbool = reNativeFunction.REGEXP.test( (function noop() {}).toString() )\n","reorderArguments":"function foo( a, b, c ) { return [ a, b, c ]; };\nvar bar = reorderArguments( foo, [ 2, 0, 1 ] );\nvar out = bar( 1, 2, 3 )\n","repeat":"var out = repeat( 'a', 5 )\nout = repeat( '', 100 )\nout = repeat( 'beep', 0 )\n","replace":"var out = replace( 'beep', 'e', 'o' )\nfunction replacer( match, p1 ) { return '/'+p1+'/'; };\nvar str = 'Oranges and lemons';\nout = replace( str, /([^\\s]+)/gi, replacer )\nout = replace( 'beep', /e/, 'o' )\n","replaceBefore":"var str = 'beep boop';\nvar out = replaceBefore( str, ' ', 'foo' )\nout = replaceBefore( str, 'o', 'foo' )\n","reRegExp":"var RE = reRegExp();\nvar bool = RE.test( '/^beep$/' )\nbool = RE.test( '/boop' )\nbool = RE.test( '/^\\/([^\\/]+)\\/(.*)$/' )\nbool = RE.test( '/^\\\\/([^\\\\/]+)\\\\/(.*)$/' )\n","reRegExp.REGEXP":"var bool = reRegExp.REGEXP.test( '/^beep$/' )\nbool = reRegExp.REGEXP.test( '/boop' )\n","rescape":"var str = rescape( '[A-Z]*' )\n","reSemVer":"var RE_SEMVER = reSemVer()\nvar bool = RE_SEMVER.test( '1.0.0' )\nbool = RE_SEMVER.test( '1.0.0-alpha.1' )\nbool = RE_SEMVER.test( 'abc' )\nbool = RE_SEMVER.test( '1.0.0-alpha.1+build.1' )\n","reSemVer.REGEXP":"var bool = reSemVer.REGEXP.test( '1.0.0' )\nbool = reSemVer.REGEXP.test( '-1.0.0-alpha.1' )\n","resolveParentPath":"function onPath( error, path ) {\n if ( error ) {\n     console.error( error.message );\n } else {\n     console.log( path );\n }\n };\nresolveParentPath( 'package.json', onPath );\n","resolveParentPath.sync":"var out = resolveParentPath.sync( 'package.json' );\n","resolveParentPathBy":"function predicate( path, next ) {\n setTimeout( onTimeout, path );\n function onTimeout() {\n     console.log( path );\n     next( null, false );\n }\n };\nfunction onPath( error, path ) {\n if ( error ) {\n     console.error( error.message );\n } else {\n     console.log( path );\n }\n };\nresolveParentPathBy( 'package.json', predicate, onPath );\n","resolveParentPathBy.sync":"function predicate() { return false; };\nvar out = resolveParentPathBy.sync( 'package.json', predicate );\n","reUncPath":"var RE = reUncPath();\nvar path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\nvar bool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\\\\\share';\nbool = RE.test( path )\npath = '\\\\\\\\\\\\\\\\server\\\\share';\nbool = RE.test( path )\npath = 'beep boop \\\\\\\\server\\\\share';\nbool = RE.test( path )\npath = '\\\\\\\\server';\nbool = RE.test( path )\npath = '\\\\';\nbool = RE.test( path )\npath = '';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b:c';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\';\nbool = RE.test( path )\npath = '//server/share';\nbool = RE.test( path )\npath = '/foo/bar';\nbool = RE.test( path )\npath = 'foo/bar';\nbool = RE.test( path )\npath = './foo/bar';\nbool = RE.test( path )\npath = '/foo/../bar';\nbool = RE.test( path )\n","reUncPath.REGEXP":"var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\nvar bool = reUncPath.REGEXP.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\nbool = reUncPath.REGEXP.test( path )\n","reUtf16SurrogatePair":"var RE = reUtf16SurrogatePair();\nvar bool = RE.test( 'abc\\uD800\\uDC00def' )\nbool = RE.test( 'abcdef' )\n","reUtf16SurrogatePair.REGEXP":"var RE = reUtf16SurrogatePair.REGEXP;\nvar bool = RE.test( 'abc\\uD800\\uDC00def' )\nbool = RE.test( 'abcdef' )\n","reUtf16UnpairedSurrogate":"var RE = reUtf16UnpairedSurrogate();\nvar bool = RE.test( 'abc' )\nbool = RE.test( '\\uD800' )\n","reUtf16UnpairedSurrogate.REGEXP":"var RE = reUtf16UnpairedSurrogate.REGEXP;\nvar bool = RE.test( 'abc' )\nbool = RE.test( '\\uD800' )\n","reverseArguments":"function foo( a, b, c ) { return [ a, b, c ]; };\nvar bar = reverseArguments( foo );\nvar out = bar( 1, 2, 3 )\n","reverseString":"var out = reverseString( 'foo' )\nout = reverseString( 'abcdef' )\n","reviveBasePRNG":"var str = JSON.stringify( base.random.mt19937 );\nvar r = parseJSON( str, reviveBasePRNG )\n","reviveBuffer":"var str = '{\"type\":\"Buffer\",\"data\":[5,3]}';\nvar buf = parseJSON( str, reviveBuffer )\n","reviveComplex":"var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\nvar z = parseJSON( str, reviveComplex )\n","reviveComplex64":"var str = '{\"type\":\"Complex64\",\"re\":5,\"im\":3}';\nvar z = parseJSON( str, reviveComplex64 )\n","reviveComplex128":"var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\nvar z = parseJSON( str, reviveComplex128 )\n","reviveError":"var str = '{\"type\":\"TypeError\",\"message\":\"beep\"}';\nvar err = JSON.parse( str, reviveError )\n","reviveRegExp":"var str = '{\"type\":\"RegExp\",\"pattern\":\"ab+c\",\"flags\":\"\"}';\nvar v = parseJSON( str, reviveRegExp )\n","reviveTypedArray":"var str = '{\"type\":\"Float64Array\",\"data\":[5,3]}';\nvar arr = parseJSON( str, reviveTypedArray )\n","reWhitespace":"var RE = reWhitespace();\nvar bool = RE.test( '\\n' )\nbool = RE.test( ' ' )\nbool = RE.test( 'a' )\n","reWhitespace.REGEXP":"var RE = reWhitespace.REGEXP;\nvar bool = RE.test( '\\n' )\nbool = RE.test( ' ' )\nbool = RE.test( 'a' )\n","reWhitespace.REGEXP_CAPTURE":"var RE = reWhitespace.REGEXP_CAPTURE;\nvar str = 'Duplicate capture';\nvar out = replace( str, RE, '$1$1' )\n","rpad":"var out = rpad( 'a', 5 )\nout = rpad( 'beep', 10, 'p' )\nout = rpad( 'beep', 12, 'boop' )\n","rtrim":"var out = rtrim( ' \\t\\t\\n  Beep \\r\\n\\t  ' )\n","rtrimN":"var out = rtrimN( '  abc  ', 2 )\nvar out = rtrimN( '!!!abc!!!', 2, '!' )\n","safeintmax":"var m = safeintmax( 'float16' )\nm = safeintmax( 'float32' )\n","safeintmin":"var m = safeintmin( 'float16' )\nm = safeintmin( 'float32' )\n","sample":"var out = sample( 'abc' )\nout = sample( [ 3, 6, 9 ] )\nvar bool = ( out.length === 3 )\nout = sample( [ 3, null, NaN, 'abc', function(){} ] )\nout = sample( [ 3, 6, 9 ], { 'size': 10 } )\nout = sample( [ 0, 1 ], { 'size': 20 } )\nout = sample( [ 1, 2, 3, 4, 5, 6 ], { 'replace': false, 'size': 3 } )\nout = sample( [ 0, 1 ], { 'replace': false } )\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar probs = [ 0.1, 0.1, 0.1, 0.1, 0.1, 0.5 ];\nout = sample( x, { 'probs': probs } )\nout = sample( x, { 'probs': probs, 'size': 3, 'replace': false } )\n","sample.factory":"var mysample = sample.factory({ 'seed': 232 } );\nvar out = mysample( 'abcdefg' )\nvar pool = [ 1, 2, 3, 4, 5, 6 ];\nmysample = sample.factory( pool, { 'seed': 232, 'size': 2 } );\nout = mysample()\nout = mysample()\nvar opts = { 'seed': 474, 'size': 3, 'mutate': true, 'replace': false };\npool = [ 1, 2, 3, 4, 5, 6 ];\nmysample = sample.factory( pool, opts );\nout = mysample()\nout = mysample()\nout = mysample()\nmysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\nout = mysample()\nout = mysample({ 'size': 10 })\nmysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\nout = mysample()\nout = mysample({ 'replace': false })\nout = mysample()\n","SAVOY_STOPWORDS_FIN":"var list = SAVOY_STOPWORDS_FIN()\n","SAVOY_STOPWORDS_FR":"var list = SAVOY_STOPWORDS_FR()\n","SAVOY_STOPWORDS_GER":"var list = SAVOY_STOPWORDS_GER()\n","SAVOY_STOPWORDS_IT":"var list = SAVOY_STOPWORDS_IT()\n","SAVOY_STOPWORDS_POR":"var list = SAVOY_STOPWORDS_POR()\n","SAVOY_STOPWORDS_SP":"var list = SAVOY_STOPWORDS_SP()\n","SAVOY_STOPWORDS_SWE":"var list = SAVOY_STOPWORDS_SWE()\n","scalar2array":"var x = scalar2array( 1.0 )\n","scalar2ndarray":"var x = scalar2ndarray( 1.0 )\nvar sh = x.shape\nvar dt = x.dtype\nvar v = x.get()\n","sdot":"var xbuf = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar x = array( xbuf );\nvar ybuf = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar y = array( ybuf );\nvar z = sdot( x, y )\nz.get()\n","SECONDS_IN_DAY":"var days = 3.14;\nvar secs = days * SECONDS_IN_DAY\n","SECONDS_IN_HOUR":"var hrs = 3.14;\nvar secs = hrs * SECONDS_IN_HOUR\n","SECONDS_IN_MINUTE":"var mins = 3.14;\nvar secs = mins * SECONDS_IN_MINUTE\n","SECONDS_IN_WEEK":"var wks = 3.14;\nvar secs = wks * SECONDS_IN_WEEK\n","secondsInMonth":"var num = secondsInMonth()\nnum = secondsInMonth( 2 )\nnum = secondsInMonth( 2, 2016 )\nnum = secondsInMonth( 2, 2017 )\nnum = secondsInMonth( 'feb', 2016 )\nnum = secondsInMonth( 'february', 2016 )\n","secondsInYear":"var num = secondsInYear()\nnum = secondsInYear( 2016 )\nnum = secondsInYear( 2017 )\n","sentencize":"var out = sentencize( 'Hello Mrs. Maple, could you call me back?' )\nout = sentencize( 'Hello World! How are you?' )\n","seq2slice":"var s = new seq2slice( '1:10', 10, false );\ns.start\ns.stop\ns.step\ns = new seq2slice( '2:5:2', 10, false );\ns.start\ns.stop\ns.step\n","setConfigurableReadOnly":"var obj = {};\nsetConfigurableReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n","setConfigurableReadOnlyAccessor":"var obj = {};\nfunction getter() { return 'bar'; };\nsetConfigurableReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n","setConfigurableReadWriteAccessor":"var obj = {};\nvar name = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetConfigurableReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n","setConfigurableWriteOnlyAccessor":"var obj = {};\nvar val = '';\nfunction setter( v ) { val = v; };\nsetConfigurableWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n","setMemoizedConfigurableReadOnly":"var obj = {};\nfunction foo() { return 'bar'; };\nsetMemoizedConfigurableReadOnly( obj, 'foo', foo );\nobj.foo\n","setMemoizedReadOnly":"var obj = {};\nfunction foo() { return 'bar'; };\nsetMemoizedReadOnly( obj, 'foo', foo );\nobj.foo\n","setNonEnumerableProperty":"var obj = {};\nsetNonEnumerableProperty( obj, 'foo', 'bar' );\nobj.foo\nobjectKeys( obj )\n","setNonEnumerableReadOnly":"var obj = {};\nsetNonEnumerableReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n","setNonEnumerableReadOnlyAccessor":"var obj = {};\nfunction getter() { return 'bar'; };\nsetNonEnumerableReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n","setNonEnumerableReadWriteAccessor":"var obj = {};\nvar name = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetNonEnumerableReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n","setNonEnumerableWriteOnlyAccessor":"var obj = {};\nvar val = '';\nfunction setter( v ) { val = v; };\nsetNonEnumerableWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n","setReadOnly":"var obj = {};\nsetReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n","setReadOnlyAccessor":"var obj = {};\nfunction getter() { return 'bar'; };\nsetReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n","setReadWriteAccessor":"var obj = {};\nvar name = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n","setWriteOnlyAccessor":"var obj = {};\nvar val = '';\nfunction setter( v ) { val = v; };\nsetWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n","SharedArrayBuffer":"var buf = new SharedArrayBuffer( 5 )\n","SharedArrayBuffer.length":"SharedArrayBuffer.length\n","SharedArrayBuffer.prototype.byteLength":"var buf = new SharedArrayBuffer( 5 );\nbuf.byteLength\n","SharedArrayBuffer.prototype.slice":"var b1 = new SharedArrayBuffer( 10 );\nvar b2 = b1.slice( 2, 6 );\nvar bool = ( b1 === b2 )\nb2.byteLength\n","shift":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar out = shift( arr )\narr = new Float64Array( [ 1.0, 2.0 ] );\nout = shift( arr )\narr = { 'length': 2, '0': 1.0, '1': 2.0 };\nout = shift( arr )\n","shuffle":"var data = [ 1, 2, 3 ];\nvar out = shuffle( data )\nout = shuffle( data, { 'copy': 'none' } );\nvar bool = ( data === out )\n","shuffle.factory":"var myshuffle = shuffle.factory();\nmyshuffle = shuffle.factory({ 'seed': 239 });\nvar arr = [ 0, 1, 2, 3, 4 ];\nvar out = myshuffle( arr )\nmyshuffle = shuffle.factory({ 'copy': 'none', 'seed': 867 });\narr = [ 1, 2, 3, 4, 5, 6 ];\nout = myshuffle( arr );\nvar bool = ( arr === out )\narr = [ 1, 2, 3, 4 ];\nout = myshuffle( arr, { 'copy': 'shallow' } );\nbool = ( arr === out )\n","sizeOf":"var s = sizeOf( 'int8' )\ns = sizeOf( 'uint32' )\n","Slice":"var s = new Slice();\ns = new Slice( 10 );\nvar s = new Slice( 2, 10 );\ns = new Slice( 2, 10, 1 );\n","Slice.prototype.start":"var s = new Slice( 10 );\ns.start\ns = new Slice( 2, 10 );\ns.start\n","Slice.prototype.stop":"var s = new Slice( 10 );\ns.stop\ns = new Slice( 2, 10 );\ns.stop\n","Slice.prototype.step":"var s = new Slice( 10 );\ns.step\ns = new Slice( 2, 10 );\ns.step\ns = new Slice( 2, 10, 1 );\ns.step\n","Slice.prototype.toString":"var s = new Slice( 10 );\ns.toString()\ns = new Slice( 2, 10, 1 );\ns.toString()\n","Slice.prototype.toJSON":"var s = new Slice( 10 );\ns.toJSON()\ns = new Slice( 2, 10, 1 );\ns.toJSON()\n","snakecase":"var out = snakecase( 'Hello World!' )\nout = snakecase( 'I am a tiny little teapot' )\n","some":"var arr = [ 0, 0, 1, 2, 3 ];\nvar bool = some( arr, 3 )\n","someBy":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ 1, 2, -3, 4, -1 ];\nvar bool = someBy( arr, 2, negative )\n","someByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nsomeByAsync( arr, 2, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nsomeByAsync( arr, 2, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nsomeByAsync( arr, 2, opts, predicate, done )\n","someByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = someByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, 2, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, 2, done )\n","someByRight":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ -1, 1, -2, 3, 4 ];\nvar bool = someByRight( arr, 2, negative )\n","someByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nsomeByRightAsync( arr, 2, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nsomeByRightAsync( arr, 2, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nsomeByRightAsync( arr, 2, opts, predicate, done )\n","someByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = someByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, 2, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, 2, done )\n","someInBy":"function negative( v ) { return ( v < 0 ); };\nvar obj = { 'a': 1, 'b': 2, 'c': -3, 'd': 4, 'e': -1 };\nvar bool = someInBy( obj, 2, negative )\n","someOwnBy":"function negative( v ) { return ( v < 0 ); };\nvar obj = { a: 1, b: 2, c: -3, d: 4, e: -1 };\nvar bool = someOwnBy( obj, 2, negative )\n","SOTU":"var out = SOTU()\nvar opts = { 'name': 'Barack Obama' };\nout = SOTU( opts )\nopts = { 'party': [ 'Democratic', 'Federalist' ] };\nout = SOTU( opts )\nopts = { 'year': [ 2008, 2009, 2011 ] };\nout = SOTU( opts )\nopts = { 'range': [ 2008, 2016 ] }\nout = SOTU( opts )\n","SPACHE_REVISED":"var list = SPACHE_REVISED()\n","SPAM_ASSASSIN":"var data = SPAM_ASSASSIN()\n","SparklineBase":"var sparkline = new SparklineBase()\nvar data = [ 1, 2, 3 ];\nsparkline = new SparklineBase( data )\n","sparsearray2iterator":"var it = sparsearray2iterator( [ 1, , 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","sparsearray2iteratorRight":"var it = sparsearray2iteratorRight( [ 1, 2, , 4 ] );\nvar v = it.next().value\nv = it.next().value\n","splitStream":"var s = splitStream();\ns.write( 'a\\nb\\nc' );\ns.end();\n","splitStream.factory":"var opts = { 'highWaterMark': 64 };\nvar createStream = splitStream.factory( opts );\nvar s = createStream();\ns.write( 'a\\nb\\nc' );\ns.end();\n","splitStream.objectMode":"var s = splitStream.objectMode();\ns.write( 'a\\nb\\c' );\ns.end();\n","SQRT_EPS":"SQRT_EPS\n","SQRT_HALF":"SQRT_HALF\n","SQRT_HALF_PI":"SQRT_HALF_PI\n","SQRT_PHI":"SQRT_PHI\n","SQRT_PI":"SQRT_PI\n","SQRT_THREE":"SQRT_THREE\n","SQRT_TWO":"SQRT_TWO\n","SQRT_TWO_PI":"SQRT_TWO_PI\n","SSA_US_BIRTHS_2000_2014":"var data = SSA_US_BIRTHS_2000_2014()\n","sswap":"var x = array( new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\nsswap( x, y );\nx.data\ny.data\n","Stack":"var s = Stack();\ns.push( 'foo' ).push( 'bar' );\ns.length\ns.pop()\ns.length\ns.pop()\ns.length\n","standalone2pkg":"var v = standalone2pkg( '@stdlib/math-base-special-sin' )\n","STANDARD_CARD_DECK":"var list = STANDARD_CARD_DECK()\n","startcase":"var out = startcase( 'beep boop' )\n","startsWith":"var bool = startsWith( 'Beep', 'Be' )\nbool = startsWith( 'Beep', 'ep' )\nbool = startsWith( 'Beep', 'ee', 1 )\nbool = startsWith( 'Beep', 'ee', -3 )\nbool = startsWith( 'Beep', '' )\n","STOPWORDS_EN":"var list = STOPWORDS_EN()\n","strided.abs":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs( 2, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.abs( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.abs.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.abs2":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.abs2( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.abs2.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.abs2By":"var x = [ -1.0, -2.0, -3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.abs2By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.abs2By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.abs2By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.abs2By.ndarray":"var x = [ -1.0, -2.0, -3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.abs2By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ -1.0, -2.0, -3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.abs2By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.absBy":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nstrided.absBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.absBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.absBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.absBy.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nstrided.absBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.absBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acosBy":"var x = [ 1.0, 0.707, 0.866, -0.707 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, 0.707, 0.866, -0.707 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acosBy.ndarray":"var x = [ 1.0, 0.707, 0.866, -0.707 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 1.0, 0.707, 0.866, -0.707 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acoshBy":"var x = [ 1.0, 1.5, 2.0, 2.5 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acoshBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acoshBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, 1.5, 2.0, 2.5 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acoshBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acoshBy.ndarray":"var x = [ 1.0, 1.5, 2.0, 2.5 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acoshBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 1.0, 1.5, 2.0, 2.5 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acoshBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acotBy":"var x = [ -2.5, -1.5, -0.5, 0.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acotBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acotBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ -2.5, -1.5, -0.5, 0.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acotBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acotBy.ndarray":"var x = [ -2.5, -1.5, -0.5, 0.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acotBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ -2.5, -1.5, -0.5, 0.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acotBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acothBy":"var x = [ -5.0, -4.0, -3.0, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acothBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acothBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ -5.0, -4.0, -3.0, -1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acothBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acothBy.ndarray":"var x = [ -5.0, -4.0, -3.0, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acothBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ -5.0, -4.0, -3.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acothBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acovercosBy":"var x = [ 0.0, -1.57, -0.5, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acovercosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acovercosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -1.57, -0.5, -1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acovercosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acovercosBy.ndarray":"var x = [ 0.0, -1.57, -0.5, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acovercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -1.57, -0.5, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acovercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acoversinBy":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acoversinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acoversinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acoversinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acoversinBy.ndarray":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acoversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.57, 0.5, 1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acoversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.add":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.add( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.add( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.add( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\nz0\n","strided.add.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.add.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.add.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n","strided.addBy":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = [ 11.0, 12.0, 13.0, 14.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.addBy( x.length, x, 1, y, 1, z, 1, clbk )\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.addBy( 2, x, 2, y, -1, z, 1, clbk )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.addBy( 2, x1, -2, y1, 1, z1, 1, clbk )\nz0\n","strided.addBy.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = [ 11.0, 12.0, 13.0, 14.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.addBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\nx = [ 1.0, 2.0, 3.0, 4.0 ];\ny = [ 11.0, 12.0, 13.0, 14.0 ];\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nvar oy = y.length - 1;\nvar oz = z.length - 1;\nstrided.addBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n","strided.ahavercosBy":"var x = [ 0.0, 0.5, 1.0, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.ahavercosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.ahavercosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 0.5, 1.0, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.ahavercosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.ahavercosBy.ndarray":"var x = [ 0.0, 0.5, 1.0, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.ahavercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 0.5, 1.0, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.ahavercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.ahaversinBy":"var x = [ 0.0, 0.5, 1.0, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.ahaversinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.ahaversinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 0.5, 1.0, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.ahaversinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.ahaversinBy.ndarray":"var x = [ 0.0, 0.5, 1.0, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.ahaversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 0.5, 1.0, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.ahaversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.asinBy":"var x = [ 0.0, -0.5, 1.0, -0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.asinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.asinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -0.5, 1.0, -0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.asinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.asinBy.ndarray":"var x = [ 0.0, -0.5, 1.0, -0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.asinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -0.5, 1.0, -0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.asinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.asinhBy":"var x = [ 0.0, -0.0, 2.0, -2.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.asinhBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.asinhBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -0.0, 2.0, -2.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.asinhBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.asinhBy.ndarray":"var x = [ 0.0, -0.0, 2.0, -2.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.asinhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -0.0, 2.0, -2.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.asinhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.atanBy":"var x = [ 0.0, -0.5, 1.0, -1.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.atanBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.atanBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -0.5, 1.0, -1.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.atanBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.atanBy.ndarray":"var x = [ 0.0, -0.5, 1.0, -1.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.atanBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -0.5, 1.0, -1.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.atanBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.atanhBy":"var x = [ 0.0, -0.5, 1.0, -0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.atanhBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.atanhBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -0.5, 1.0, -0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.atanhBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.atanhBy.ndarray":"var x = [ 0.0, -0.5, 1.0, -0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.atanhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -0.5, 1.0, -0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.atanhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.avercosBy":"var x = [ 0.0, -1.57, -0.5, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.avercosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.avercosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -1.57, -0.5, -1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.avercosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.avercosBy.ndarray":"var x = [ 0.0, -1.57, -0.5, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.avercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -1.57, -0.5, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.avercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.aversinBy":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.aversinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.aversinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.aversinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.aversinBy.ndarray":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.aversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.57, 0.5, 1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.aversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.besselj0By":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.besselj0By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.besselj0By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.besselj0By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.besselj0By.ndarray":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.besselj0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 0.1, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.besselj0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.besselj1By":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.besselj1By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.besselj1By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.besselj1By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.besselj1By.ndarray":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.besselj1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 0.1, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.besselj1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.bessely0By":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.bessely0By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.bessely0By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.bessely0By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.bessely0By.ndarray":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.bessely0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 0.1, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.bessely0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.bessely1By":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.bessely1By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.bessely1By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.bessely1By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.bessely1By.ndarray":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.bessely1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 0.1, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.bessely1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.binetBy":"var x = [ 0.0, 1.0, 2.0, 3.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.binetBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.binetBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.binetBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.binetBy.ndarray":"var x = [ 0.0, 1.0, 2.0, 3.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.binetBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 2.0, 3.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.binetBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.cbrt":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.cbrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.cbrt.ndarray":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.cbrtBy":"var x = [ 1.0, 9.0, -27.0, 81.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.cbrtBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.cbrtBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.cbrtBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.cbrtBy.ndarray":"var x = [ 1.0, 9.0, -27.0, 81.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.cbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 1.0, 9.0, -27.0, 81.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.cbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.ceil":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.ceil( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.ceil.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.cosBy":"var x = [ 0.0, 3.14, -3.14, 10.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.cosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.cosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 3.14, -3.14, 10.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.cosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.cosBy.ndarray":"var x = [ 0.0, 3.14, -3.14, 10.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.cosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 3.14, -3.14, 10.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.cosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.deg2rad":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.deg2rad( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.deg2rad.ndarray":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.dataTypes":"var out = strided.dataTypes()\n","strided.dcbrtBy":"var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nfunction clbk( v ) { return v; };\nstrided.dcbrtBy( x.length, x, 1, y, 1, clbk )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.dcbrtBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.dcbrtBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.dcbrtBy.ndarray":"var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nfunction clbk( v ) { return v; };\nstrided.dcbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.dcbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.dispatch":"var t = [ 'float64', 'float64', 'float32', 'float32' ];\nvar d = [ base.abs, base.absf ];\nvar f = strided.dispatch( base.strided.unary, t, d, 7, 1, 1 );\nvar x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( x.length, 'float64', x, 1, 'float64', y, 1 );\ny\nf = strided.dispatch( base.strided.unary.ndarray, t, d, 9, 1, 1 );\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( 2, 'float64', x, 1, 2, 'float64', y, 1, 2 );\ny\n","strided.dispatchBy":"var t = [ 'float64', 'float64', 'float32', 'float32' ];\nvar d = [ base.abs, base.absf ];\nvar f = strided.dispatchBy( base.strided.unaryBy, t, d, 8, 1, 1 );\nvar x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( x.length, 'float64', x, 1, 'float64', y, 1, base.identity );\ny\nf = strided.dispatchBy( base.strided.unary.ndarray, t, d, 10, 1, 1 );\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( 2, 'float64', x, 1, 2, 'float64', y, 1, 2, base.identity );\ny\n","strided.floor":"var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.floor( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.floor.ndarray":"var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.inv":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.inv( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.inv.ndarray":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.mul":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.mul( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.mul( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.mul( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\nz0\n","strided.mul.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.mul.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.mul.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n","strided.mulBy":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = [ 11.0, 12.0, 13.0, 14.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.mulBy( x.length, x, 1, y, 1, z, 1, clbk )\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.mulBy( 2, x, 2, y, -1, z, 1, clbk )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.mulBy( 2, x1, -2, y1, 1, z1, 1, clbk )\nz0\n","strided.mulBy.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = [ 11.0, 12.0, 13.0, 14.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.mulBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\nx = [ 1.0, 2.0, 3.0, 4.0 ];\ny = [ 11.0, 12.0, 13.0, 14.0 ];\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nvar oy = y.length - 1;\nvar oz = z.length - 1;\nstrided.mulBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n","strided.ramp":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.ramp( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.ramp.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.rsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.rsqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.rsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.sinBy":"var x = [ 0.0, 3.14, -3.14, 10.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.sinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.sinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 3.14, -3.14, 10.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.sinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.sinBy.ndarray":"var x = [ 0.0, 3.14, -3.14, 10.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.sinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 3.14, -3.14, 10.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.sinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.sqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.sqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.sqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.sqrtBy":"var x = [ 0.0, 1.0, 122.0, 50.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.sqrtBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.sqrtBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 122.0, 50.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.sqrtBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.sqrtBy.ndarray":"var x = [ 0.0, 1.0, 122.0, 50.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.sqrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 122.0, 50.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.sqrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.sub":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.sub( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sub( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.sub( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\nz0\n","strided.sub.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.sub.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sub.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n","strided.subBy":"var x = [ 11.0, 12.0, 13.0, 14.0 ];\nvar y = [ 8.0, 7.0, 6.0, 5.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.subBy( x.length, x, 1, y, 1, z, 1, clbk )\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.subBy( 2, x, 2, y, -1, z, 1, clbk )\nvar x0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\nvar y0 = new Float64Array( [ 8.0, 7.0, 6.0, 5.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.subBy( 2, x1, -2, y1, 1, z1, 1, clbk )\nz0\n","strided.subBy.ndarray":"var x = [ 11.0, 12.0, 13.0, 14.0 ];\nvar y = [ 8.0, 7.0, 6.0, 5.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.subBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\nx = [ 11.0, 12.0, 13.0, 14.0 ];\ny = [ 8.0, 7.0, 6.0, 5.0 ];\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nvar oy = y.length - 1;\nvar oz = z.length - 1;\nstrided.subBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n","strided.trunc":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.trunc( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.trunc.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","stridedarray2iterator":"var it = stridedarray2iterator( 2, [ 1, 2, 3, 4 ], -2, 3 );\nvar v = it.next().value\nv = it.next().value\n","stridedArrayStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar s = stridedArrayStream( 3, [ 1, 2, 3 ], 1, 0 );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","stridedArrayStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = stridedArrayStream.factory( opts );\n","stridedArrayStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar s = stridedArrayStream.objectMode( 3, [ 1, 2, 3 ], 1, 0 );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","string2buffer":"var b = string2buffer( 'beep boop' )\nb = string2buffer( '7468697320697320612074c3a97374', 'hex' );\nb.toString()\n","sub2ind":"var d = [ 3, 3, 3 ];\nvar idx = sub2ind( d, 1, 2, 2 )\n","substringAfter":"var out = substringAfter( 'Hello World!', 'World' )\nout = substringAfter( 'Hello World!', 'Hello ' )\nout = substringAfter( 'Hello World!', 'l', 5 )\n","substringAfterLast":"var out = substringAfterLast( 'beep boop beep baz', 'beep' )\nout = substringAfterLast( 'Hello World!', 'Hello ' )\nout = substringAfterLast( 'Hello World!', 'o', 5 )\n","substringBefore":"var str = 'beep boop';\nvar out = substringBefore( str, ' ' )\nout = substringBefore( str, 'o' )\n","substringBeforeLast":"var str = 'Beep Boop Beep';\nvar out = substringBeforeLast( str, 'Beep' )\nout = substringBeforeLast( str, 'Boop' )\n","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"var data = SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"var data = SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n","Symbol":"var s = ( Symbol ) ? Symbol( 'beep' ) : null\n","tabulate":"var collection = [ 'beep', 'boop', 'foo', 'beep' ];\nvar out = tabulate( collection )\n","tabulateBy":"function indicator( value ) { return value[ 0 ]; };\nvar collection = [ 'beep', 'boop', 'foo', 'beep' ];\nvar out = tabulateBy( collection, indicator )\n","tabulateByAsync":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000, 750 ];\ntabulateByAsync( arr, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000, 750 ];\ntabulateByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000, 750 ];\ntabulateByAsync( arr, opts, indicator, done )\n","tabulateByAsync.factory":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nvar opts = { 'series': true };\nvar f = tabulateByAsync.factory( opts, indicator );\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000, 750 ];\nf( arr, done )\narr = [ 2000, 1500, 1000, 750 ];\nf( arr, done )\n","thunk":"var fcn = thunk( base.add, 2, 3 );\nvar v = fcn()\nv = fcn()\n","tic":"var t = tic()\n","timeit":"var code = 'var x = Math.pow( Math.random(), 3 );';\ncode += 'if ( x !== x ) {';\ncode += 'throw new Error( \\'Something went wrong.\\' );';\ncode += '}';\nfunction done( error, results ) {\n if ( error ) {\n     throw error;\n }\n console.dir( results );\n };\ntimeit( code, done )\n","tmpdir":"var dir = tmpdir()\n","toc":"var start = tic();\nvar delta = toc( start )\n","tokenize":"var out = tokenize( 'Hello Mrs. Maple, could you call me back?' )\nout = tokenize( 'Hello World!', true )\n","transformStream":"var s = transformStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","transformStream.factory":"var opts = { 'highWaterMark': 64 };\nvar createStream = transformStream.factory( opts );\nfunction fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\nvar s = createStream( fcn );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","transformStream.objectMode":"var s = transformStream.objectMode();\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","transformStream.ctor":"function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\nvar opts = { 'highWaterMark': 64, 'transform': fcn };\nvar customStream = transformStream.ctor( opts );\nvar s = customStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","trim":"var out = trim( ' \\t\\t\\n  Beep \\r\\n\\t  ' )\n","truncate":"var str = 'beep boop';\nvar out = truncate( str, 5 )\nout = truncate( str, 5, '|' )\n","truncateMiddle":"var str = 'beep boop';\nvar out = truncateMiddle( str, 5 )\nout = truncateMiddle( str, 5, '|' )\n","trycatch":"function x() {\n if ( base.random.randu() < 0.5 ) {\n     throw new Error( 'beep' );\n }\n return 1.0;\n };\nvar z = trycatch( x, -1.0 )\n","trycatchAsync":"function x( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n     clbk( new Error( 'beep' ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     // process error...\n }\n console.log( result );\n };\ntrycatchAsync( x, 'boop', done )\n","tryFunction":"function fcn() { throw new Error( 'beep boop' ); };\nvar f = tryFunction( fcn );\nvar out = f();\nout.message\n","tryRequire":"var out = tryRequire( '_unknown_module_id_' )\n","trythen":"function x() {\n if ( base.random.randu() < 0.5 ) {\n     throw new Error( 'beep' );\n }\n return 1.0;\n };\nfunction y() {\n return -1.0;\n };\nvar z = trythen( x, y )\n","trythenAsync":"function x( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n     clbk( new Error( 'beep' ) );\n }\n };\nfunction y( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n     clbk( null, 'boop' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\ntrythenAsync( x, y, done )\n","ttest":"var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 5776 } );\nvar x = new Array( 100 );\nfor ( var i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm();\n }\nvar out = ttest( x )\nrnorm = base.random.normal.factory( 1.0, 2.0, { 'seed': 786 } );\nx = new Array( 100 );\nvar y = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm();\n y[ i ] = rnorm();\n }\nout = ttest( x, y )\nvar table = out.print()\nvar arr = [ 2, 4, 3, 1, 0 ];\nout = ttest( arr, { 'alpha': 0.01 } );\ntable = out.print()\narr = [ 4, 4, 6, 6, 5 ];\nout = ttest( arr, { 'mu': 5 } )\narr = [ 4, 4, 6, 6, 5 ];\nout = ttest( arr, { 'alternative': 'less' } );\ntable = out.print()\nout = ttest( arr, { 'alternative': 'greater' } );\ntable = out.print()\n","ttest2":"var x = [ 0.7, -1.6, -0.2, -1.2, -0.1, 3.4, 3.7, 0.8, 0.0, 2.0 ];\nvar y = [ 1.9, 0.8, 1.1, 0.1, -0.1, 4.4, 5.5, 1.6, 4.6, 3.4 ];\nvar out = ttest2( x, y )\nvar table = out.print()\nout = ttest2( x, y, { 'alpha': 0.1 } );\ntable = out.print()\nout = ttest2( x, y, { 'alternative': 'less' } );\ntable = out.print()\nout = ttest2( x, y, { 'alternative': 'greater' } );\ntable = out.print()\nx = [ 2, 3, 1, 4 ];\ny = [ 1, 2, 3, 1, 2, 5, 3, 4 ];\nout = ttest2( x, y, { 'variance': 'equal' } );\ntable = out.print()\nvar rnorm = base.random.normal.factory({ 'seed': 372 } );\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm( 2.0, 3.0 );\n }\ny = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n y[ i ] = rnorm( 1.0, 3.0 );\n }\nout = ttest2( x, y, { 'difference': 1.0, 'variance': 'equal' } )\n","TWO_PI":"TWO_PI\n","typedarray":"var arr = typedarray()\narr = typedarray( 'float32' )\nvar arr = typedarray( 5 )\narr = typedarray( 5, 'int32' )\nvar arr1 = typedarray( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = typedarray( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = typedarray( arr1, 'float32' )\nvar buf = new ArrayBuffer( 16 );\nvar arr = typedarray( buf, 0, 4, 'float32' )\n","typedarray2json":"var arr = new Float64Array( 2 );\narr[ 0 ] = 5.0;\narr[ 1 ] = 3.0;\nvar json = typedarray2json( arr )\n","typedarrayCtors":"var ctor = typedarrayCtors( 'float64' )\nctor = typedarrayCtors( 'float' )\n","typedarrayDataTypes":"var out = typedarrayDataTypes()\n","typedarraypool":"var arr = typedarraypool()\narr = typedarraypool( 'float32' )\nvar arr = typedarraypool( 5 )\narr = typedarraypool( 5, 'int32' )\nvar arr1 = typedarraypool( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = typedarraypool( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = typedarraypool( arr1, 'float32' )\n","typedarraypool.malloc":"var arr = typedarraypool.malloc()\narr = typedarraypool.malloc( 'float32' )\nvar arr = typedarraypool.malloc( 5 )\narr = typedarraypool.malloc( 5, 'int32' )\nvar arr1 = typedarraypool.malloc( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = typedarraypool.malloc( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = typedarraypool.malloc( arr1, 'float32' )\n","typedarraypool.calloc":"var arr = typedarraypool.calloc()\narr = typedarraypool.calloc( 'float32' )\nvar arr = typedarraypool.calloc( 5 )\narr = typedarraypool.calloc( 5, 'int32' )\n","typedarraypool.free":"var arr = typedarraypool( 5 )\ntypedarraypool.free( arr );\n","typedarraypool.clear":"var arr = typedarraypool( 5 )\ntypedarraypool.free( arr );\ntypedarraypool.clear();\n","typedarraypool.highWaterMark":"typedarraypool.highWaterMark\n","typedarraypool.nbytes":"var arr = typedarraypool( 5 )\ntypedarraypool.nbytes\n","typedarraypool.factory":"var pool = typedarraypool.factory();\nvar arr1 = pool( 3, 'float64' )\n","typemax":"var m = typemax( 'int8' )\nm = typemax( 'uint32' )\n","typemin":"var m = typemin( 'int8' )\nm = typemin( 'uint32' )\n","typeOf":"var t = typeOf( 'a' )\nt = typeOf( 5 )\nt = typeOf( NaN )\nt = typeOf( true )\nt = typeOf( false )\nt = typeOf( null )\nt = typeOf( undefined )\nt = typeOf( [] )\nt = typeOf( {} )\nt = typeOf( function noop() {} )\nt = typeOf( Symbol( 'beep' ) )\nt = typeOf( /.+/ )\nt = typeOf( new String( 'beep' ) )\nt = typeOf( new Number( 5 ) )\nt = typeOf( new Boolean( false ) )\nt = typeOf( new Array() )\nt = typeOf( new Object() )\nt = typeOf( new Int8Array( 10 ) )\nt = typeOf( new Uint8Array( 10 ) )\nt = typeOf( new Uint8ClampedArray( 10 ) )\nt = typeOf( new Int16Array( 10 ) )\nt = typeOf( new Uint16Array( 10 ) )\nt = typeOf( new Int32Array( 10 ) )\nt = typeOf( new Uint32Array( 10 ) )\nt = typeOf( new Float32Array( 10 ) )\nt = typeOf( new Float64Array( 10 ) )\nt = typeOf( new ArrayBuffer( 10 ) )\nt = typeOf( new Date() )\nt = typeOf( new RegExp( '.+' ) )\nt = typeOf( new Map() )\nt = typeOf( new Set() )\nt = typeOf( new WeakMap() )\nt = typeOf( new WeakSet() )\nt = typeOf( new Error( 'beep' ) )\nt = typeOf( new TypeError( 'beep' ) )\nt = typeOf( new SyntaxError( 'beep' ) )\nt = typeOf( new ReferenceError( 'beep' ) )\nt = typeOf( new URIError( 'beep' ) )\nt = typeOf( new RangeError( 'beep' ) )\nt = typeOf( new EvalError( 'beep' ) )\nt = typeOf( Math )\nt = typeOf( JSON )\nfunction beep() { return arguments; };\nt = typeOf( beep() )\nt = typeOf( new Buffer( 10 ) )\nfunction Person() { return this };\nt = typeOf( new Person() )\nvar Foo = function () { return this; };\nt = typeOf( new Foo() )\n","UINT8_MAX":"UINT8_MAX\n","UINT8_NUM_BYTES":"UINT8_NUM_BYTES\n","Uint8Array":"var arr = new Uint8Array()\nvar arr = new Uint8Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint8Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint8Array( arr1 )\nvar buf = new ArrayBuffer( 4 );\nvar arr = new Uint8Array( buf, 0, 4 )\n","Uint8Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint8Array.from( [ 1, 2 ], mapFcn )\n","Uint8Array.of":"var arr = Uint8Array.of( 1, 2 )\n","Uint8Array.BYTES_PER_ELEMENT":"Uint8Array.BYTES_PER_ELEMENT\n","Uint8Array.name":"Uint8Array.name\n","Uint8Array.prototype.buffer":"var arr = new Uint8Array( 5 );\narr.buffer\n","Uint8Array.prototype.byteLength":"var arr = new Uint8Array( 5 );\narr.byteLength\n","Uint8Array.prototype.byteOffset":"var arr = new Uint8Array( 5 );\narr.byteOffset\n","Uint8Array.prototype.BYTES_PER_ELEMENT":"var arr = new Uint8Array( 5 );\narr.BYTES_PER_ELEMENT\n","Uint8Array.prototype.length":"var arr = new Uint8Array( 5 );\narr.length\n","Uint8Array.prototype.copyWithin":"var arr = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint8Array.prototype.entries":"var arr = new Uint8Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint8Array.prototype.every":"var arr = new Uint8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint8Array.prototype.fill":"var arr = new Uint8Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint8Array.prototype.filter":"var arr1 = new Uint8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint8Array.prototype.find":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint8Array.prototype.findIndex":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint8Array.prototype.forEach":"var arr = new Uint8Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint8Array.prototype.includes":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint8Array.prototype.indexOf":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint8Array.prototype.join":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint8Array.prototype.keys":"var arr = new Uint8Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint8Array.prototype.lastIndexOf":"var arr = new Uint8Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint8Array.prototype.map":"var arr1 = new Uint8Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Uint8Array.prototype.reduce":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint8Array.prototype.reduceRight":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint8Array.prototype.reverse":"var arr = new Uint8Array( [ 1, 2, 3 ] )\narr.reverse()\n","Uint8Array.prototype.set":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint8Array.prototype.slice":"var arr1 = new Uint8Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint8Array.prototype.some":"var arr = new Uint8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint8Array.prototype.sort":"var arr = new Uint8Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint8Array.prototype.subarray":"var arr1 = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint8Array.prototype.toLocaleString":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint8Array.prototype.toString":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.toString()\n","Uint8Array.prototype.values":"var arr = new Uint8Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","Uint8ClampedArray":"var arr = new Uint8ClampedArray()\nvar arr = new Uint8ClampedArray( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint8ClampedArray( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint8ClampedArray( arr1 )\nvar buf = new ArrayBuffer( 4 );\nvar arr = new Uint8ClampedArray( buf, 0, 4 )\n","Uint8ClampedArray.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint8ClampedArray.from( [ 1, 2 ], mapFcn )\n","Uint8ClampedArray.of":"var arr = Uint8ClampedArray.of( 1, 2 )\n","Uint8ClampedArray.BYTES_PER_ELEMENT":"Uint8ClampedArray.BYTES_PER_ELEMENT\n","Uint8ClampedArray.name":"Uint8ClampedArray.name\n","Uint8ClampedArray.prototype.buffer":"var arr = new Uint8ClampedArray( 5 );\narr.buffer\n","Uint8ClampedArray.prototype.byteLength":"var arr = new Uint8ClampedArray( 5 );\narr.byteLength\n","Uint8ClampedArray.prototype.byteOffset":"var arr = new Uint8ClampedArray( 5 );\narr.byteOffset\n","Uint8ClampedArray.prototype.BYTES_PER_ELEMENT":"var arr = new Uint8ClampedArray( 5 );\narr.BYTES_PER_ELEMENT\n","Uint8ClampedArray.prototype.length":"var arr = new Uint8ClampedArray( 5 );\narr.length\n","Uint8ClampedArray.prototype.copyWithin":"var arr = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint8ClampedArray.prototype.entries":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint8ClampedArray.prototype.every":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint8ClampedArray.prototype.fill":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint8ClampedArray.prototype.filter":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint8ClampedArray.prototype.find":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint8ClampedArray.prototype.findIndex":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint8ClampedArray.prototype.forEach":"var arr = new Uint8ClampedArray( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint8ClampedArray.prototype.includes":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint8ClampedArray.prototype.indexOf":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint8ClampedArray.prototype.join":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint8ClampedArray.prototype.keys":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint8ClampedArray.prototype.lastIndexOf":"var arr = new Uint8ClampedArray( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint8ClampedArray.prototype.map":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Uint8ClampedArray.prototype.reduce":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint8ClampedArray.prototype.reduceRight":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint8ClampedArray.prototype.reverse":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] )\narr.reverse()\n","Uint8ClampedArray.prototype.set":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint8ClampedArray.prototype.slice":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint8ClampedArray.prototype.some":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint8ClampedArray.prototype.sort":"var arr = new Uint8ClampedArray( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint8ClampedArray.prototype.subarray":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint8ClampedArray.prototype.toLocaleString":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint8ClampedArray.prototype.toString":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.toString()\n","Uint8ClampedArray.prototype.values":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","UINT16_MAX":"UINT16_MAX\n","UINT16_NUM_BYTES":"UINT16_NUM_BYTES\n","Uint16Array":"var arr = new Uint16Array()\nvar arr = new Uint16Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint16Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint16Array( arr1 )\nvar buf = new ArrayBuffer( 8 );\nvar arr = new Uint16Array( buf, 0, 4 )\n","Uint16Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint16Array.from( [ 1, 2 ], mapFcn )\n","Uint16Array.of":"var arr = Uint16Array.of( 1, 2 )\n","Uint16Array.BYTES_PER_ELEMENT":"Uint16Array.BYTES_PER_ELEMENT\n","Uint16Array.name":"Uint16Array.name\n","Uint16Array.prototype.buffer":"var arr = new Uint16Array( 5 );\narr.buffer\n","Uint16Array.prototype.byteLength":"var arr = new Uint16Array( 5 );\narr.byteLength\n","Uint16Array.prototype.byteOffset":"var arr = new Uint16Array( 5 );\narr.byteOffset\n","Uint16Array.prototype.BYTES_PER_ELEMENT":"var arr = new Uint16Array( 5 );\narr.BYTES_PER_ELEMENT\n","Uint16Array.prototype.length":"var arr = new Uint16Array( 5 );\narr.length\n","Uint16Array.prototype.copyWithin":"var arr = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint16Array.prototype.entries":"var arr = new Uint16Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint16Array.prototype.every":"var arr = new Uint16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint16Array.prototype.fill":"var arr = new Uint16Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint16Array.prototype.filter":"var arr1 = new Uint16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint16Array.prototype.find":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint16Array.prototype.findIndex":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint16Array.prototype.forEach":"var arr = new Uint16Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint16Array.prototype.includes":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint16Array.prototype.indexOf":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint16Array.prototype.join":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint16Array.prototype.keys":"var arr = new Uint16Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint16Array.prototype.lastIndexOf":"var arr = new Uint16Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint16Array.prototype.map":"var arr1 = new Uint16Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Uint16Array.prototype.reduce":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint16Array.prototype.reduceRight":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint16Array.prototype.reverse":"var arr = new Uint16Array( [ 1, 2, 3 ] )\narr.reverse()\n","Uint16Array.prototype.set":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint16Array.prototype.slice":"var arr1 = new Uint16Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint16Array.prototype.some":"var arr = new Uint16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint16Array.prototype.sort":"var arr = new Uint16Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint16Array.prototype.subarray":"var arr1 = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint16Array.prototype.toLocaleString":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint16Array.prototype.toString":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.toString()\n","Uint16Array.prototype.values":"var arr = new Uint16Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","UINT32_MAX":"UINT32_MAX\n","UINT32_NUM_BYTES":"UINT32_NUM_BYTES\n","Uint32Array":"var arr = new Uint32Array()\nvar arr = new Uint32Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint32Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint32Array( arr1 )\nvar buf = new ArrayBuffer( 16 );\nvar arr = new Uint32Array( buf, 0, 4 )\n","Uint32Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint32Array.from( [ 1, 2 ], mapFcn )\n","Uint32Array.of":"var arr = Uint32Array.of( 1, 2 )\n","Uint32Array.BYTES_PER_ELEMENT":"Uint32Array.BYTES_PER_ELEMENT\n","Uint32Array.name":"Uint32Array.name\n","Uint32Array.prototype.buffer":"var arr = new Uint32Array( 5 );\narr.buffer\n","Uint32Array.prototype.byteLength":"var arr = new Uint32Array( 5 );\narr.byteLength\n","Uint32Array.prototype.byteOffset":"var arr = new Uint32Array( 5 );\narr.byteOffset\n","Uint32Array.prototype.BYTES_PER_ELEMENT":"var arr = new Uint32Array( 5 );\narr.BYTES_PER_ELEMENT\n","Uint32Array.prototype.length":"var arr = new Uint32Array( 5 );\narr.length\n","Uint32Array.prototype.copyWithin":"var arr = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint32Array.prototype.entries":"var arr = new Uint32Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint32Array.prototype.every":"var arr = new Uint32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint32Array.prototype.fill":"var arr = new Uint32Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint32Array.prototype.filter":"var arr1 = new Uint32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint32Array.prototype.find":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint32Array.prototype.findIndex":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint32Array.prototype.forEach":"var arr = new Uint32Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint32Array.prototype.includes":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint32Array.prototype.indexOf":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint32Array.prototype.join":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint32Array.prototype.keys":"var arr = new Uint32Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint32Array.prototype.lastIndexOf":"var arr = new Uint32Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint32Array.prototype.map":"var arr1 = new Uint32Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Uint32Array.prototype.reduce":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint32Array.prototype.reduceRight":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint32Array.prototype.reverse":"var arr = new Uint32Array( [ 1, 2, 3 ] )\narr.reverse()\n","Uint32Array.prototype.set":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint32Array.prototype.slice":"var arr1 = new Uint32Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint32Array.prototype.some":"var arr = new Uint32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint32Array.prototype.sort":"var arr = new Uint32Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint32Array.prototype.subarray":"var arr1 = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint32Array.prototype.toLocaleString":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint32Array.prototype.toString":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.toString()\n","Uint32Array.prototype.values":"var arr = new Uint32Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","umask":"var mask = umask()\nmask = umask( { 'symbolic': true } )\n","uncapitalize":"var out = uncapitalize( 'Beep' )\nout = uncapitalize( 'bOOp' )\n","uncapitalizeKeys":"var obj = { 'AA': 1, 'BB': 2 };\nvar out = uncapitalizeKeys( obj )\n","uncurry":"function addX( x ) {\n return function addY( y ) {\n     return x + y;\n };\n };\nvar fcn = uncurry( addX );\nvar sum = fcn( 2, 3 )\nfunction add( x ) {\n return function add( y ) {\n     return x + y;\n };\n };\nfcn = uncurry( add, 2 );\nsum = fcn( 9 )\nfunction addX( x ) {\n this.x = x;\n return addY;\n };\nfunction addY( y ) {\n return this.x + y;\n };\nfcn = uncurry( addX, {} );\nsum = fcn( 2, 3 )\n","uncurryRight":"function addX( x ) {\n return function addY( y ) {\n     return x + y;\n };\n };\nvar fcn = uncurryRight( addX );\nvar sum = fcn( 3, 2 )\nfunction add( y ) {\n return function add( x ) {\n     return x + y;\n };\n };\nfcn = uncurryRight( add, 2 );\nsum = fcn( 9 )\nfunction addY( y ) {\n this.y = y;\n return addX;\n };\nfunction addX( x ) {\n return x + this.y;\n };\nfcn = uncurryRight( addY, {} );\nsum = fcn( 3, 2 )\n","UNICODE_MAX":"UNICODE_MAX\n","UNICODE_MAX_BMP":"UNICODE_MAX_BMP\n","UnicodeColumnChartSparkline":"var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\nvar chart = new UnicodeColumnChartSparkline( data );\nchart.render()\n","UnicodeLineChartSparkline":"var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\nvar chart = new UnicodeLineChartSparkline( data );\nchart.render()\n","UnicodeSparkline":"var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\nvar chart = new UnicodeSparkline( data );\nchart.render()\nchart.type = 'line';\nchart.render()\n","UnicodeTristateChartSparkline":"var data = [ -1, 1, 0, 0, 1, -1, -1, 1 ];\nvar chart = new UnicodeTristateChartSparkline( data );\nchart.render()\n","UnicodeUpDownChartSparkline":"var data = [ -1, 1, 1, 1, 1, -1, -1, 1 ];\nvar chart = new UnicodeUpDownChartSparkline( data );\nchart.render()\n","UnicodeWinLossChartSparkline":"var data = [ -2, 1, 2, 2, 1, -1, -1, 1 ];\nvar chart = new UnicodeWinLossChartSparkline( data );\nchart.render()\n","unlink":"function done( error ) {\n if ( error ) {\n     console.error( error.message );\n }\n };\nunlink( './beep/boop.txt', done );\n","unlink.sync":"var out = unlink.sync( './beep/boop.txt' );\n","unshift":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = unshift( arr, 6.0, 7.0 )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = unshift( arr, 3.0, 4.0 )\narr = { 'length': 1, '0': 1.0 };\narr = unshift( arr, 2.0, 3.0 )\n","until":"function predicate( i ) { return ( i >= 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\nuntil( predicate, beep )\n","untilAsync":"function predicate( i, clbk ) { clbk( null, i >= 5 ); };\nfunction fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n     next( null, 'boop'+i );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nuntilAsync( predicate, fcn, done )\n","untilEach":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\nuntilEach( arr, predicate, logger )\n","untilEachRight":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\nuntilEachRight( arr, predicate, logger )\n","unzip":"var arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\nvar out = unzip( arr )\narr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\nout = unzip( arr, [ 0, 2 ] )\n","uppercase":"var out = uppercase( 'bEEp' )\n","uppercaseKeys":"var obj = { 'a': 1, 'b': 2 };\nvar out = uppercaseKeys( obj )\n","US_STATES_ABBR":"var list = US_STATES_ABBR()\n","US_STATES_CAPITALS":"var list = US_STATES_CAPITALS()\n","US_STATES_CAPITALS_NAMES":"var out = US_STATES_CAPITALS_NAMES()\n","US_STATES_NAMES":"var list = US_STATES_NAMES()\n","US_STATES_NAMES_CAPITALS":"var out = US_STATES_NAMES_CAPITALS()\n","utf16ToUTF8Array":"var str = '☃';\nvar out = utf16ToUTF8Array( str )\n","vartest":"var x = [ 610, 610, 550, 590, 565, 570 ];\nvar y = [ 560, 550, 580, 550, 560, 590, 550, 590 ];\nvar out = vartest( x, y )\nvar table = out.print()\n","waterfall":"function foo( next ) { next( null, 'beep' ); };\nfunction bar( str, next ) { console.log( str ); next(); };\nfunction done( error ) { if ( error ) { throw error; } };\nvar fcns = [ foo, bar ];\nwaterfall( fcns, done );\n","waterfall.factory":"function foo( next ) { next( null, 'beep' ); };\nfunction bar( str, next ) { console.log( str ); next(); };\nfunction done( error ) { if ( error ) { throw error; } };\nvar fcns = [ foo, bar ];\nvar waterfall = waterfall.factory( fcns, done );\nwaterfall();\nwaterfall();\nwaterfall();\n","WebAssemblyMemory":"var mem = new WebAssemblyMemory( { 'initial': 0 } )\n","WebAssemblyMemory.prototype.buffer":"var mem = new WebAssemblyMemory( { 'initial': 0 } );\nmem.buffer\n","WebAssemblyMemory.prototype.grow":"var mem = new WebAssemblyMemory( { 'initial': 0 } );\nmem.grow( 1 )\n","whileAsync":"function predicate( i, clbk ) { clbk( null, i < 5 ); };\nfunction fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n     next( null, 'boop'+i );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nwhileAsync( predicate, fcn, done )\n","whileEach":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\nwhileEach( arr, predicate, logger )\n","whileEachRight":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\nwhileEachRight( arr, predicate, logger )\n","whilst":"function predicate( i ) { return ( i < 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\nwhilst( predicate, beep )\n","wilcoxon":"var arr = [ 6, 8, 14, 16, 23, 24, 28, 29, 41, -48, 49, 56, 60, -67, 75 ];\nvar out = wilcoxon( x )\nrunif = base.random.discreteUniform.factory( 1, 5, { 'seed': 786 });\nvar x = new Array( 100 );\nvar y = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = runif();\n y[ i ] = runif();\n }\nout = wilcoxon( x, y )\nvar table = out.print()\nout = wilcoxon( arr, { 'alpha': 0.01 });\ntable = out.print()\nout = wilcoxon( arr, { 'mu': 10 })\nout = wilcoxon( arr, { 'alternative': 'less' });\ntable = out.print()\nout = wilcoxon( arr, { 'alternative': 'greater' });\ntable = out.print()\n","writableProperties":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar props = writableProperties( obj )\n","writablePropertiesIn":"var props = writablePropertiesIn( [] )\n","writablePropertyNames":"var obj = { 'a': 'b' };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = writablePropertyNames( obj )\n","writablePropertyNamesIn":"var obj = { 'a': 'b' };\nvar desc = {};\ndesc.configurable = true;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = writablePropertyNamesIn( obj )\n","writablePropertySymbols":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = writablePropertySymbols( obj )\n","writablePropertySymbolsIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = writablePropertySymbolsIn( obj )\n","writeFile":"function onWrite( error ) {\n if ( error ) {\n     console.error( error.message );\n }\n };\nwriteFile( './beep/boop.txt', 'beep boop', onWrite );\n","writeFile.sync":"var err = writeFile.sync( './beep/boop.txt', 'beep boop' );\n","zip":"var out = zip( [ 1, 2 ], [ 'a', 'b' ] )\nvar opts = { 'trunc': false };\nout = zip( [ 1, 2, 3 ], [ 'a', 'b' ], opts )\n","ztest":"var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 212 } );\nvar x = new Array( 100 );\nfor ( var i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm();\n }\nvar out = ztest( x, 2.0 )\narr = [ 2, 4, 3, 1, 0 ];\nout = ztest( arr, 2.0, { 'alpha': 0.01 } );\ntable = out.print()\nvar arr = [ 4, 4, 6, 6, 5 ];\nout = ztest( arr, 1.0, { 'mu': 5 } )\narr = [ 4, 4, 6, 6, 5 ];\nout = ztest( arr, 1.0, { 'alternative': 'less' } )\nout = ztest( arr, 1.0, { 'alternative': 'greater' } )\n","ztest2":"var x = [ -0.21, 0.14, 1.65, 2.11, -1.86, -0.29, 1.48, 0.81, 0.86, 1.04 ];\nvar y = [ -1.53, -2.93, 2.34, -1.15, 2.7, -0.12, 4.22, 1.66, 3.43, 4.66 ];\nvar out = ztest2( x, y, 2.0, 2.0 )\nvar table = out.print()\nout = ztest2( x, y, 2.0, 2.0, { 'alpha': 0.4 } );\ntable = out.print()\nout = ztest2( x, y, 2.0, 2.0, { 'alternative': 'less' } );\ntable = out.print()\nout = ztest2( x, y, 2.0, 2.0, { 'alternative': 'greater' } );\ntable = out.print()\nvar rnorm = base.random.normal.factory({ 'seed': 372 } );\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm( 2.0, 1.0 );\n }\ny = new Array( 100 );\n for ( i = 0; i < x.length; i++ ) {\n y[ i ] = rnorm( 0.0, 2.0 );\n }\nout = ztest2( x, y, 1.0, 2.0, { 'difference': 2.0 } )\n"}
+{"abs":"var y = abs( -1.0 )\nvar x = new Float64Array( [ -1.0, -2.0 ] );\ny = abs( x )\nx = [ -1.0, -2.0 ];\ny = abs( x )\nx = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] );\ny = abs( x )\ny.get( 0, 1 )\n","abs.assign":"var x = new Float64Array( [ -1.0, -2.0 ] );\nvar y = new Float64Array( x.length );\nvar out = abs.assign( x, y )\nvar bool = ( out === y )\nx = [ -1.0, -2.0 ];\ny = [ 0.0, 0.0 ];\nout = abs.assign( x, y )\nbool = ( out === y )\nx = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] );\ny = array( [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ] );\nout = abs.assign( x, y )\nout.get( 0, 1 )\nbool = ( out === y )\n","acartesianPower":"var x = [ 1, 2 ];\nvar out = acartesianPower( x, 2 )\n","acartesianProduct":"var x1 = [ 1, 2 ];\nvar x2 = [ 3, 4 ];\nvar out = acartesianProduct( x1, x2 )\n","acartesianSquare":"var out = acartesianSquare( [ 1, 2 ] )\n","acronym":"var out = acronym( 'the quick brown fox' )\nout = acronym( 'Hard-boiled eggs' )\n","aempty":"var arr = aempty( 2 )\narr = aempty( 2, 'float32' )\n","aemptyLike":"var x = new Float64Array( 2 );\nvar arr = aemptyLike( x )\narr = aemptyLike( x, 'float32' )\n","AFINN_96":"var list = AFINN_96()\n","AFINN_111":"var list = AFINN_111()\n","afull":"var arr = afull( 2, 1.0 )\narr = afull( 2, 1.0, 'float32' )\n","afullLike":"var x = new Float64Array( 2 );\nvar y = afullLike( x, 1.0 )\ny = afullLike( x, 1.0, 'float32' )\n","alias2pkg":"var v = alias2pkg( 'base.sin' )\n","alias2related":"var v = alias2related( 'base.sin' )\n","alias2standalone":"var v = alias2standalone( 'base.sin' )\n","aliases":"var o = aliases()\no = aliases( '@stdlib/math/base/special' )\n","allocUnsafe":"var buf = allocUnsafe( 100 )\n","amskfilter":"var x = [ 1, 2, 3, 4 ];\nvar y = amskfilter( x, [ 0, 1, 0, 1 ] )\n","amskput":"var x = [ 1, 2, 3, 4 ];\nvar out = amskput( x, [ 1, 0, 1, 0 ], [ 20, 40 ] )\nvar bool = ( out === x )\n","amskreject":"var x = [ 1, 2, 3, 4 ];\nvar y = amskreject( x, [ 0, 1, 0, 1 ] )\n","anans":"var arr = anans( 2 )\narr = anans( 2, 'float32' )\n","anansLike":"var x = new Float64Array( 2 );\nvar y = anansLike( x )\ny = anansLike( x, 'float32' )\n","anova1":"var x = [1, 3, 5, 2, 4, 6, 8, 7, 10, 11, 12, 15];\nvar f = [\n 'control', 'treatA', 'treatB', 'treatC', 'control',\n 'treatA', 'treatB', 'treatC', 'control', 'treatA', 'treatB', 'treatC'\n ];\nvar out = anova1( x, f )\n","ANSCOMBES_QUARTET":"var d = ANSCOMBES_QUARTET()\n","any":"var arr = [ 0, 0, 0, 0, 1 ];\nvar bool = any( arr )\n","anyBy":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ 1, 2, 3, 4, -1 ];\nvar bool = anyBy( arr, negative )\n","anyByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nanyByAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nanyByAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nanyByAsync( arr, opts, predicate, done )\n","anyByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = anyByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","anyByRight":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ -1, 1, 2, 3, 4 ];\nvar bool = anyByRight( arr, negative )\n","anyByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nanyByRightAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nanyByRightAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nanyByRightAsync( arr, opts, predicate, done )\n","anyByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = anyByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","anyInBy":"function isNegative(value) { return value < 0 }\nvar obj = { a: 1, b: -2, c: 3, d: 4 }\nvar result = anyInBy(obj, isNegative)\n","anyOwnBy":"function positive( v ) { return ( v > 0 ); };\nvar obj = { 'a': -1, 'b': 2, 'c': -3 };\nvar bool = anyOwnBy( obj, positive )\n","aones":"var arr = aones( 2 )\narr = aones( 2, 'float32' )\n","aonesLike":"var x = new Float64Array( 2 );\nvar y = aonesLike( x )\ny = aonesLike( x, 'float32' )\n","aoneTo":"var arr = aoneTo( 2 )\narr = aoneTo( 2, 'float32' )\n","aoneToLike":"var arr = aoneToLike( [ 0, 0 ] )\narr = aoneToLike( [ 0, 0 ], 'float32' )\n","APERY":"APERY\n","aplace":"var x = [ 1, 2, 3, 4 ];\nvar out = aplace( x, [ 0, 1, 0, 1 ], [ 20, 40 ] )\nvar bool = ( out === x )\n","append":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = append( arr, [ 6.0, 7.0 ] )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = append( arr, [ 3.0, 4.0 ] )\narr = { 'length': 0 };\narr = append( arr, [ 1.0, 2.0 ] )\n","aput":"var x = [ 1, 2, 3, 4 ];\nvar out = aput( x, [ 1, 3 ], [ 20, 40 ] )\nvar bool = ( out === x )\n","ARCH":"ARCH\n","argumentFunction":"var argn = argumentFunction( 1 );\nvar v = argn( 3.14, -3.14, 0.0 )\nv = argn( -1.0, -0.0, 1.0 )\nv = argn( 'beep', 'boop', 'bop' )\nv = argn( 'beep' )\n","ARGV":"var execPath = ARGV[ 0 ]\n","array":"var arr = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","array2buffer":"var buf = array2buffer( [ 1, 2, 3, 4 ] )\n","array2fancy":"var y = array2fancy( [ 1, 2, 3, 4 ] );\ny[ '1::2' ]\ny[ '::-1' ]\n","array2fancy.factory":"var f = array2fancy.factory();\nvar y = f( [ 1, 2, 3, 4 ] );\ny[ '1::2' ]\ny[ '::-1' ]\n","array2fancy.idx":"var idx = array2fancy.idx( [ 1, 2, 3, 4 ] );\n","array2iterator":"var it = array2iterator( [ 1, 2, 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","array2iteratorRight":"var it = array2iteratorRight( [ 1, 2, 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","ArrayBuffer":"var buf = new ArrayBuffer( 5 )\n","ArrayBuffer.length":"ArrayBuffer.length\n","ArrayBuffer.isView":"var arr = new Float64Array( 10 );\nArrayBuffer.isView( arr )\n","ArrayBuffer.prototype.byteLength":"var buf = new ArrayBuffer( 5 );\nbuf.byteLength\n","ArrayBuffer.prototype.slice":"var b1 = new ArrayBuffer( 10 );\nvar b2 = b1.slice( 2, 6 );\nvar bool = ( b1 === b2 )\nb2.byteLength\n","arraybuffer2buffer":"var ab = new ArrayBuffer( 10 )\nvar buf = arraybuffer2buffer( ab )\nvar len = buf.length\nbuf = arraybuffer2buffer( ab, 2, 6 )\nlen = buf.length\n","arrayCtors":"var ctor = arrayCtors( 'float64' )\nctor = arrayCtors( 'float' )\n","arrayDataType":"var arr = new Float64Array( 10 );\nvar dt = arrayDataType( arr )\ndt = arrayDataType( 'beep' )\n","arrayDataTypes":"var out = arrayDataTypes()\nout = arrayDataTypes( 'floating_point' )\nout = arrayDataTypes( 'floating_point_and_generic' )\n","ArrayIndex":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n","ArrayIndex.free":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nArrayIndex.free( idx.id )\n","ArrayIndex.get":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nArrayIndex.get( idx.id )\n","ArrayIndex.prototype.data":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.data\n","ArrayIndex.prototype.dtype":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.dtype\n","ArrayIndex.prototype.id":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.id\n","ArrayIndex.prototype.isCached":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.isCached\n","ArrayIndex.prototype.type":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.type\n","ArrayIndex.prototype.toString":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.toString()\n","ArrayIndex.prototype.toJSON":"var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\nidx.toJSON()\n","arrayMinDataType":"var dt = arrayMinDataType( 3.141592653589793 )\ndt = arrayMinDataType( 3 )\ndt = arrayMinDataType( -3 )\ndt = arrayMinDataType( '-3' )\n","arrayMostlySafeCasts":"var out = arrayMostlySafeCasts( 'float32' )\n","arrayNextDataType":"var out = arrayNextDataType( 'float32' )\n","arrayPromotionRules":"var out = arrayPromotionRules( 'float32', 'int32' )\n","arraySafeCasts":"var out = arraySafeCasts( 'float32' )\n","arraySameKindCasts":"var out = arraySameKindCasts( 'float32' )\n","arrayShape":"var out = arrayShape( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n","arrayStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar s = arrayStream( [ 1, 2, 3 ] );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","arrayStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = arrayStream.factory( opts );\n","arrayStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar s = arrayStream.objectMode( [ 1, 2, 3 ] );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","arrayview2iterator":"var it = arrayview2iterator( [ 1, 2, 3, 4 ], 1, 3 );\nvar v = it.next().value\nv = it.next().value\n","arrayview2iteratorRight":"var it = arrayview2iteratorRight( [ 1, 2, 3, 4 ], 1, 3 );\nvar v = it.next().value\nv = it.next().value\n","aslice":"var out = aslice( [ 1, 2, 3, 4 ] )\nout = aslice( [ 1, 2, 3, 4 ], 1 )\nout = aslice( [ 1, 2, 3, 4 ], 1, 3 )\n","AsyncIteratorSymbol":"var s = AsyncIteratorSymbol\n","atake":"var x = [ 1, 2, 3, 4 ];\nvar y = atake( x, [ 1, 3 ] )\n","azeros":"var arr = azeros( 2 )\narr = azeros( 2, 'float32' )\n","azerosLike":"var x = new Float64Array( 2 );\nvar y = azerosLike( x )\ny = azerosLike( x, 'float32' )\n","azeroTo":"var arr = azeroTo( 2 )\narr = azeroTo( 2, 'float32' )\n","azeroToLike":"var arr = azeroToLike( [ 0, 0 ] )\narr = azeroToLike( [ 0, 0 ], 'float32' )\n","bartlettTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = bartlettTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = bartlettTest( arr, { 'groups': groups } )\n","base.abs":"var y = base.abs( -1.0 )\ny = base.abs( 2.0 )\ny = base.abs( 0.0 )\ny = base.abs( -0.0 )\ny = base.abs( NaN )\n","base.abs2":"var y = base.abs2( -1.0 )\ny = base.abs2( 2.0 )\ny = base.abs2( 0.0 )\ny = base.abs2( -0.0 )\ny = base.abs2( NaN )\n","base.abs2f":"var y = base.abs2f( -1.0 )\ny = base.abs2f( 2.0 )\ny = base.abs2f( 0.0 )\ny = base.abs2f( -0.0 )\ny = base.abs2f( NaN )\n","base.absdiff":"var d = base.absdiff( 2.0, 5.0 )\nd = base.absdiff( -1.0, 3.14 )\nd = base.absdiff( 10.1, -2.05 )\nd = base.absdiff( -0.0, 0.0 )\nd = base.absdiff( NaN, 5.0 )\nd = base.absdiff( PINF, NINF )\nd = base.absdiff( PINF, PINF )\n","base.absf":"var y = base.absf( -1.0 )\ny = base.absf( 2.0 )\ny = base.absf( 0.0 )\ny = base.absf( -0.0 )\ny = base.absf( NaN )\n","base.acartesianPower":"var x = [ 1, 2 ];\nvar out = base.acartesianPower( x, 2 )\n","base.acartesianProduct":"var x1 = [ 1, 2 ];\nvar x2 = [ 3, 4 ];\nvar out = base.acartesianProduct( x1, x2 )\n","base.acartesianSquare":"var x = [ 1, 2 ];\nvar out = base.acartesianSquare( x )\n","base.acos":"var y = base.acos( 1.0 )\ny = base.acos( 0.707 )\ny = base.acos( NaN )\n","base.acosd":"var y = base.acosd( 0.0 )\ny = base.acosd( PI/6.0 )\ny = base.acosd( NaN )\n","base.acosf":"var y = base.acosf( 1.0 )\ny = base.acosf( 0.707 )\ny = base.acosf( NaN )\n","base.acosh":"var y = base.acosh( 1.0 )\ny = base.acosh( 2.0 )\ny = base.acosh( NaN )\n","base.acot":"var y = base.acot( 2.0 )\ny = base.acot( 0.0 )\ny = base.acot( 0.5 )\ny = base.acot( 1.0 )\ny = base.acot( NaN )\n","base.acotd":"var y = base.acotd( 0.0 )\ny = base.acotd( PI/6.0 )\ny = base.acotd( NaN )\n","base.acotf":"var y = base.acotf( 2.0 )\ny = base.acotf( 0.0 )\ny = base.acotf( 0.5 )\ny = base.acotf( 1.0 )\ny = base.acotf( NaN )\n","base.acoth":"var y = base.acoth( 2.0 )\ny = base.acoth( 0.0 )\ny = base.acoth( 0.5 )\ny = base.acoth( 1.0 )\ny = base.acoth( NaN )\n","base.acovercos":"var y = base.acovercos( -1.5 )\ny = base.acovercos( -0.0 )\n","base.acoversin":"var y = base.acoversin( 1.5 )\ny = base.acoversin( 0.0 )\n","base.acsc":"var y = base.acsc( 1.0 )\ny = base.acsc( PI )\ny = base.acsc( -PI )\ny = base.acsc( NaN )\n","base.acscd":"var y = base.acscd( 0.0 )\ny = base.acscd( PI/6.0 )\ny = base.acscd( 1 )\ny = base.acscd( NaN )\n","base.acscdf":"var y = base.acscdf( 0.0 )\ny = base.acscdf( 3.1415927410125732 / 6.0 )\ny = base.acscdf( 1.0 )\ny = base.acscdf( NaN )\n","base.acscf":"var y = base.acscf( 1.0 )\ny = base.acscf( 3.141592653589793 )\ny = base.acscf( -3.141592653589793 )\ny = base.acscf( NaN )\n","base.acsch":"var y = base.acsch( 0.0 )\ny = base.acsch( -1.0 )\ny = base.acsch( NaN )\n","base.add":"var v = base.add( -1.0, 5.0 )\nv = base.add( 2.0, 5.0 )\nv = base.add( 0.0, 5.0 )\nv = base.add( -0.0, 0.0 )\nv = base.add( NaN, NaN )\n","base.add3":"var v = base.add3( -1.0, 5.0, 2.0 )\nv = base.add3( 2.0, 5.0, 2.0 )\nv = base.add3( 0.0, 5.0, 2.0 )\nv = base.add3( -0.0, 0.0, -0.0 )\nv = base.add3( NaN, NaN, NaN )\n","base.add4":"var v = base.add4( -1.0, 5.0, 2.0, -3.0 )\nv = base.add4( 2.0, 5.0, 2.0, -3.0 )\nv = base.add4( 0.0, 5.0, 2.0, -3.0 )\nv = base.add4( -0.0, 0.0, -0.0, -0.0 )\nv = base.add4( NaN, NaN, NaN, NaN )\n","base.add5":"var v = base.add5( -1.0, 5.0, 2.0, -3.0, 4.0 )\nv = base.add5( 2.0, 5.0, 2.0, -3.0, 4.0 )\nv = base.add5( 0.0, 5.0, 2.0, -3.0, 4.0 )\nv = base.add5( -0.0, 0.0, -0.0, -0.0, -0.0 )\nv = base.add5( NaN, NaN, NaN, NaN, NaN )\n","base.addf":"var v = base.addf( -1.0, 5.0 )\nv = base.addf( 2.0, 5.0 )\nv = base.addf( 0.0, 5.0 )\nv = base.addf( -0.0, 0.0 )\nv = base.addf( NaN, NaN )\n","base.afilled":"var out = base.afilled( 0.0, 3 )\n","base.afilled2d":"var out = base.afilled2d( 0.0, [ 1, 3 ] )\n","base.afilled2dBy":"function clbk() { return 1.0; };\nvar out = base.afilled2dBy( [ 1, 3 ], clbk )\n","base.afilled3d":"var out = base.afilled3d( 0.0, [ 1, 1, 3 ] )\n","base.afilled3dBy":"function clbk() { return 1.0; };\nvar out = base.afilled3dBy( [ 1, 1, 3 ], clbk )\n","base.afilled4d":"var out = base.afilled4d( 0.0, [ 1, 1, 1, 3 ] )\n","base.afilled4dBy":"function clbk() { return 1.0; };\nvar out = base.afilled4dBy( [ 1, 1, 1, 3 ], clbk )\n","base.afilled5d":"var out = base.afilled5d( 0.0, [ 1, 1, 1, 1, 3 ] )\n","base.afilled5dBy":"function clbk() { return 1.0; };\nvar out = base.afilled5dBy( [ 1, 1, 1, 1, 3 ], clbk )\n","base.afilledBy":"function clbk() { return 1.0; };\nvar out = base.afilledBy( 3, clbk )\n","base.afillednd":"var out = base.afillednd( 0.0, [ 1, 3 ] )\n","base.afilledndBy":"function clbk() { return 1.0; };\nvar out = base.afilledndBy( [ 1, 3 ], clbk )\n","base.afilter":"function f( v ) { return ( v > 0 ); };\nvar x = [ 1, -2, -3, 4 ];\nvar out = base.afilter( x, f )\n","base.afirst":"var out = base.afirst( [ 1, 2, 3 ] )\n","base.aflatten":"var x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = base.aflatten( x, [ 2, 2 ], false )\nout = base.aflatten( x, [ 2, 2 ], true )\n","base.aflatten.assign":"var x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten.assign( x, [ 2, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten.assign( x, [ 2, 2 ], true, out, 1, 0 );\nout\n","base.aflatten2d":"var x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = base.aflatten2d( x, [ 2, 2 ], false )\nout = base.aflatten2d( x, [ 2, 2 ], true )\n","base.aflatten2d.assign":"var x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten2d.assign( x, [ 2, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten2d.assign( x, [ 2, 2 ], true, out, 1, 0 );\nout\n","base.aflatten2dBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = base.aflatten2dBy( x, [ 2, 2 ], false, fcn )\nout = base.aflatten2dBy( x, [ 2, 2 ], true, fcn )\n","base.aflatten2dBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten2dBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten2dBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\nout\n","base.aflatten3d":"var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\nvar out = base.aflatten3d( x, [ 2, 1, 2 ], false )\nout = base.aflatten3d( x, [ 2, 1, 2 ], true )\n","base.aflatten3d.assign":"var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten3d.assign( x, [ 2, 1, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten3d.assign( x, [ 2, 1, 2 ], true, out, 1, 0 );\nout\n","base.aflatten3dBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\nvar out = base.aflatten3dBy( x, [ 2, 1, 2 ], false, fcn )\nout = base.aflatten3dBy( x, [ 2, 1, 2 ], true, fcn )\n","base.aflatten3dBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten3dBy.assign( x, [ 2, 1, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten3dBy.assign( x, [ 2, 1, 2 ], true, out, 1, 0, fcn );\nout\n","base.aflatten4d":"var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\nvar out = base.aflatten4d( x, [ 2, 1, 1, 2 ], false )\nout = base.aflatten4d( x, [ 2, 1, 1, 2 ], true )\n","base.aflatten4d.assign":"var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten4d.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0 );\nout\n","base.aflatten4dBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\nvar out = base.aflatten4dBy( x, [ 2, 1, 1, 2 ], false, fcn )\nout = base.aflatten4dBy( x, [ 2, 1, 1, 2 ], true, fcn )\n","base.aflatten4dBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0, fcn );\nout\n","base.aflatten5d":"var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\nvar out = base.aflatten5d( x, [ 2, 1, 1, 1, 2 ], false )\nout = base.aflatten5d( x, [ 2, 1, 1, 1, 2 ], true )\n","base.aflatten5d.assign":"var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0 )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0 );\nout\n","base.aflatten5dBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\nvar out = base.aflatten5dBy( x, [ 2, 1, 1, 1, 2 ], false, fcn )\nout = base.aflatten5dBy( x, [ 2, 1, 1, 1, 2 ], true, fcn )\n","base.aflatten5dBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0, fcn );\nout\n","base.aflattenBy":"function fcn( v ) { return v * 2; };\nvar x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = base.aflattenBy( x, [ 2, 2 ], false, fcn )\nout = base.aflattenBy( x, [ 2, 2 ], true, fcn )\n","base.aflattenBy.assign":"function fcn( v ) { return v * 2; };\nvar x = [ [ 1, 2 ], [ 3, 4 ] ];\nvar out = [ 0, 0, 0, 0 ];\nvar v = base.aflattenBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\nvar bool = ( v === out )\nout = [ 0, 0, 0, 0 ];\nbase.aflattenBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\nout\n","base.afliplr2d":"var out = base.afliplr2d( [ [ 1, 2 ], [ 3, 4 ] ] )\n","base.afliplr3d":"var out = base.afliplr3d( [ [ [ 1, 2 ], [ 3, 4 ] ] ] )\n","base.afliplr4d":"var out = base.afliplr4d( [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] )\n","base.afliplr5d":"var out = base.afliplr5d( [ [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] ] )\n","base.aflipud2d":"var out = base.aflipud2d( [ [ 1, 2 ], [ 3, 4 ] ] )\n","base.aflipud3d":"var out = base.aflipud3d( [ [ [ 1, 2 ], [ 3, 4 ] ] ] )\n","base.aflipud4d":"var out = base.aflipud4d( [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] )\n","base.aflipud5d":"var out = base.aflipud5d( [ [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] ] )\n","base.ahavercos":"var y = base.ahavercos( 0.5 )\ny = base.ahavercos( 0.0 )\n","base.ahaversin":"var y = base.ahaversin( 0.5 )\ny = base.ahaversin( 0.0 )\n","base.altcase":"var out = base.altcase( 'Hello World!' )\nout = base.altcase( 'I am a tiny little teapot' )\n","base.aones":"var out = base.aones( 3 )\n","base.aones2d":"var out = base.aones2d( [ 1, 3 ] )\n","base.aones3d":"var out = base.aones3d( [ 1, 1, 3 ] )\n","base.aones4d":"var out = base.aones4d( [ 1, 1, 1, 3 ] )\n","base.aones5d":"var out = base.aones5d( [ 1, 1, 1, 1, 3 ] )\n","base.aonesnd":"var out = base.aonesnd( [ 1, 3 ] )\n","base.aoneTo":"var arr = base.aoneTo( 6 )\n","base.aoneTo.assign":"var out = [ 0, 0, 0, 0, 0, 0 ];\nbase.aoneTo.assign( out, -1, out.length-1 );\nout\n","base.args2multislice":"var args = [ null, null, null ];\nvar s = new base.args2multislice( args );\ns.data\nargs = [ 10, new Slice( 0, 10, 1 ), null ];\ns = new base.args2multislice( args );\ns.data\n","base.asec":"var y = base.asec( 1.0 )\ny = base.asec( 2.0 )\ny = base.asec( NaN )\n","base.asecd":"var y = base.asecd( 0.0 )\ny = base.asecd( 2 )\ny = base.asecd( NaN )\n","base.asecdf":"var y = base.asecdf( 2.0 )\ny = base.asecdf( 0.0 )\ny = base.asecdf( NaN )\n","base.asecf":"var y = base.asecf( 1.0 )\ny = base.asecf( 2.0 )\ny = base.asecf( NaN )\n","base.asech":"var y = base.asech( 1.0 )\ny = base.asech( 0.5 )\ny = base.asech( NaN )\n","base.asin":"var y = base.asin( 0.0 )\ny = base.asin( -PI/6.0 )\ny = base.asin( NaN )\n","base.asind":"var y = base.asind( 0.0 )\ny = base.asind( PI / 6.0 )\ny = base.asind( NaN )\n","base.asindf":"var y = base.asindf( 0.0 )\ny = base.asindf( 3.1415927410125732 / 6.0 )\ny = base.asindf( NaN )\n","base.asinf":"var y = base.asinf( 0.0 )\ny = base.asinf( -3.14/6.0 )\ny = base.asinf( NaN )\n","base.asinh":"var y = base.asinh( 0.0 )\ny = base.asinh( 2.0 )\ny = base.asinh( -2.0 )\ny = base.asinh( NaN )\ny = base.asinh( NINF )\ny = base.asinh( PINF )\n","base.atan":"var y = base.atan( 0.0 )\ny = base.atan( -PI/2.0 )\ny = base.atan( PI/2.0 )\ny = base.atan( NaN )\n","base.atan2":"var v = base.atan2( 2.0, 2.0 )\nv = base.atan2( 6.0, 2.0 )\nv = base.atan2( -1.0, -1.0 )\nv = base.atan2( 3.0, 0.0 )\nv = base.atan2( -2.0, 0.0 )\nv = base.atan2( 0.0, 0.0 )\nv = base.atan2( 3.0, NaN )\nv = base.atan2( NaN, 2.0 )\n","base.atand":"var y = base.atand( 0.0 )\ny = base.atand( PI/6.0 )\ny = base.atand( NaN )\n","base.atanf":"var y = base.atanf( 0.0 )\ny = base.atanf( -3.14/4.0 )\ny = base.atanf( 3.14/4.0 )\ny = base.atanf( NaN )\n","base.atanh":"var y = base.atanh( 0.0 )\ny = base.atanh( 0.9 )\ny = base.atanh( 1.0 )\ny = base.atanh( -1.0 )\ny = base.atanh( NaN 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1.0 )\ny = base.besselj0( PINF )\ny = base.besselj0( NINF )\ny = base.besselj0( NaN )\n","base.besselj1":"var y = base.besselj1( 0.0 )\ny = base.besselj1( 1.0 )\ny = base.besselj1( PINF )\ny = base.besselj1( NINF )\ny = base.besselj1( NaN )\n","base.bessely0":"var y = base.bessely0( 0.0 )\ny = base.bessely0( 1.0 )\ny = base.bessely0( -1.0 )\ny = base.bessely0( PINF )\ny = base.bessely0( NINF )\ny = base.bessely0( NaN )\n","base.bessely1":"var y = base.bessely1( 0.0 )\ny = base.bessely1( 1.0 )\ny = base.bessely1( -1.0 )\ny = base.bessely1( PINF )\ny = base.bessely1( NINF )\ny = base.bessely1( NaN )\n","base.beta":"var v = base.beta( 0.0, 0.5 )\nv = base.beta( 1.0, 1.0 )\nv = base.beta( -1.0, 2.0 )\nv = base.beta( 5.0, 0.2 )\nv = base.beta( 4.0, 1.0 )\nv = base.beta( NaN, 2.0 )\n","base.betainc":"var y = base.betainc( 0.5, 2.0, 2.0 )\ny = base.betainc( 0.5, 2.0, 2.0, false )\ny = base.betainc( 0.2, 1.0, 2.0 )\ny = base.betainc( 0.2, 1.0, 2.0, true, true )\ny = base.betainc( NaN, 1.0, 1.0 )\ny = base.betainc( 0.8, NaN, 1.0 )\ny = base.betainc( 0.8, 1.0, NaN )\ny = base.betainc( 1.5, 1.0, 1.0 )\ny = base.betainc( -0.5, 1.0, 1.0 )\ny = base.betainc( 0.5, -2.0, 2.0 )\ny = base.betainc( 0.5, 2.0, -2.0 )\n","base.betaincinv":"var y = base.betaincinv( 0.2, 3.0, 3.0 )\ny = base.betaincinv( 0.4, 3.0, 3.0 )\ny = base.betaincinv( 0.4, 3.0, 3.0, true )\ny = base.betaincinv( 0.4, 1.0, 6.0 )\ny = base.betaincinv( 0.8, 1.0, 6.0 )\ny = base.betaincinv( NaN, 1.0, 1.0 )\ny = base.betaincinv( 0.5, NaN, 1.0 )\ny = base.betaincinv( 0.5, 1.0, NaN )\ny = base.betaincinv( 1.2, 1.0, 1.0 )\ny = base.betaincinv( -0.5, 1.0, 1.0 )\ny = base.betaincinv( 0.5, -2.0, 2.0 )\ny = base.betaincinv( 0.5, 0.0, 2.0 )\ny = base.betaincinv( 0.5, 2.0, -2.0 )\ny = base.betaincinv( 0.5, 2.0, 0.0 )\n","base.betaln":"var v = base.betaln( 0.0, 0.0 )\nv = base.betaln( 1.0, 1.0 )\nv = base.betaln( -1.0, 2.0 )\nv = base.betaln( 5.0, 0.2 )\nv = base.betaln( 4.0, 1.0 )\nv = base.betaln( NaN, 2.0 )\n","base.binet":"var y = base.binet( 0.0 )\ny = base.binet( 1.0 )\ny = base.binet( 2.0 )\ny = base.binet( 3.0 )\ny = base.binet( 4.0 )\ny = base.binet( 5.0 )\ny = base.binet( NaN )\n","base.binomcoef":"var v = base.binomcoef( 8, 2 )\nv = base.binomcoef( 0, 0 )\nv = base.binomcoef( -4, 2 )\nv = base.binomcoef( 5, 3 )\nv = base.binomcoef( NaN, 3 )\nv = base.binomcoef( 5, NaN )\nv = base.binomcoef( NaN, NaN )\n","base.binomcoefln":"var v = base.binomcoefln( 8, 2 )\nv = base.binomcoefln( 0, 0 )\nv = base.binomcoefln( -4, 2 )\nv = base.binomcoefln( 88, 3 )\nv = base.binomcoefln( NaN, 3 )\nv = base.binomcoefln( 5, NaN )\nv = base.binomcoefln( NaN, NaN )\n","base.boxcox":"var v = base.boxcox( 1.0, 2.5 )\nv = base.boxcox( 4.0, 2.5 )\nv = base.boxcox( 10.0, 2.5 )\nv = base.boxcox( 2.0, 0.0 )\nv = base.boxcox( -1.0, 2.5 )\nv = base.boxcox( 0.0, -1.0 )\n","base.boxcox1p":"var v =  base.boxcox1p( 1.0, 2.5 )\nv = base.boxcox1p( 4.0, 2.5 )\nv = base.boxcox1p( 10.0, 2.5 )\nv = base.boxcox1p( 2.0, 0.0 )\nv = base.boxcox1p( -1.0, 2.5 )\nv = base.boxcox1p( 0.0, -1.0 )\nv = base.boxcox1p( -1.0, -1.0 )\n","base.boxcox1pinv":"var v = base.boxcox1pinv( 1.0, 2.5 )\nv = base.boxcox1pinv( 4.0, 2.5 )\nv = base.boxcox1pinv( 10.0, 2.5 )\nv = base.boxcox1pinv( 2.0, 0.0 )\nv = base.boxcox1pinv( -1.0, 2.5 )\nv = base.boxcox1pinv( 0.0, -1.0 )\nv = base.boxcox1pinv( 1.0, NaN )\nv = base.boxcox1pinv( NaN, 3.1 )\n","base.boxcoxinv":"var v = base.boxcoxinv( 1.0, 2.5 )\nv = base.boxcoxinv( 4.0, 2.5 )\nv = base.boxcoxinv( 10.0, 2.5 )\nv = base.boxcoxinv( 2.0, 0.0 )\nv = base.boxcoxinv( -1.0, 2.5 )\nv = base.boxcoxinv( 0.0, -1.0 )\nv = base.boxcoxinv( 1.0, NaN )\nv = base.boxcoxinv( NaN, 3.1 )\n","base.cabs":"var y = base.cabs( new Complex128( 5.0, 3.0 ) )\n","base.cabs2":"var y = base.cabs2( new Complex128( 5.0, 3.0 ) )\n","base.cabs2f":"var y = base.cabs2f( new Complex64( 5.0, 3.0 ) )\n","base.cabsf":"var y = base.cabsf( new Complex64( 5.0, 3.0 ) )\n","base.cadd":"var z = new Complex128( 5.0, 3.0 )\nvar out = base.cadd( z, z )\nvar re = real( out )\nvar im = imag( out )\n","base.caddf":"var z = new Complex64( 5.0, 3.0 )\nvar out = base.caddf( z, z )\nvar re = realf( out )\nvar im = imagf( out )\n","base.camelcase":"var out = base.camelcase( 'Hello World!' )\nout = base.camelcase( 'beep boop' )\n","base.capitalize":"var out = base.capitalize( 'beep' )\nout = base.capitalize( 'Boop' )\n","base.cbrt":"var y = base.cbrt( 64.0 )\ny = base.cbrt( 27.0 )\ny = base.cbrt( 0.0 )\ny = base.cbrt( -0.0 )\ny = base.cbrt( -9.0 )\ny = base.cbrt( NaN )\n","base.cbrtf":"var y = base.cbrtf( 64.0 )\ny = base.cbrtf( 27.0 )\ny = base.cbrtf( 0.0 )\ny = base.cbrtf( -0.0 )\ny = base.cbrtf( -9.0 )\ny = base.cbrtf( NaN )\n","base.cceil":"var v = base.cceil( new Complex128( -1.5, 2.5 ) )\nvar re = real( v )\nvar im = imag( v )\n","base.cceilf":"var v = base.cceilf( new Complex64( -1.5, 2.5 ) )\nvar re = realf( v )\nvar im = imagf( v )\n","base.cceiln":"var out = base.cceiln( new Complex128( 5.555, -3.333 ), -2 )\nvar re = real( out )\nvar im = imag( out )\n","base.ccis":"var y = base.ccis( new Complex128( 0.0, 0.0 ) )\nvar re = real( y )\nvar im = imag( y )\ny = base.ccis( new Complex128( 1.0, 0.0 ) )\nre = real( y )\nim = imag( y )\n","base.cdiv":"var z1 = new Complex128( -13.0, -1.0 )\nvar z2 = new Complex128( -2.0, 1.0 )\nvar y = base.cdiv( z1, z2 )\nvar re = real( y )\nvar im = imag( y )\n","base.ceil":"var y = base.ceil( 3.14 )\ny = base.ceil( -4.2 )\ny = base.ceil( -4.6 )\ny = base.ceil( 9.5 )\ny = base.ceil( -0.0 )\n","base.ceil2":"var y = base.ceil2( 3.14 )\ny = base.ceil2( -4.2 )\ny = base.ceil2( -4.6 )\ny = base.ceil2( 9.5 )\ny = base.ceil2( 13.0 )\ny = base.ceil2( -13.0 )\ny = base.ceil2( -0.0 )\n","base.ceil10":"var y = base.ceil10( 3.14 )\ny = base.ceil10( -4.2 )\ny = base.ceil10( -4.6 )\ny = base.ceil10( 9.5 )\ny = base.ceil10( 13.0 )\ny = base.ceil10( -13.0 )\ny = base.ceil10( -0.0 )\n","base.ceilb":"var y = base.ceilb( 3.14159, -4, 10 )\ny = base.ceilb( 3.14159, 0, 2 )\ny = base.ceilb( 5.0, 1, 2 )\n","base.ceilf":"var y = base.ceilf( 3.14 )\ny = base.ceilf( -4.2 )\ny = base.ceilf( -4.6 )\ny = base.ceilf( 9.5 )\ny = base.ceilf( -0.0 )\n","base.ceiln":"var y = base.ceiln( 3.14159, -2 )\ny = base.ceiln( 3.14159, 0 )\ny = base.ceiln( 12368.0, 3 )\n","base.ceilsd":"var y = base.ceilsd( 3.14159, 5, 10 )\ny = base.ceilsd( 3.14159, 1, 10 )\ny = base.ceilsd( 12368.0, 2, 10 )\ny = base.ceilsd( 0.0313, 2, 2 )\n","base.cexp":"var y = base.cexp( new Complex128( 0.0, 0.0 ) )\nvar re = real( y )\nvar im = imag( y )\ny = base.cexp( new Complex128( 0.0, 1.0 ) )\nre = real( y )\nim = imag( y )\n","base.cflipsign":"var v = base.cflipsign( new Complex128( -4.2, 5.5 ), -9.0 )\nvar re = real( v )\nvar im = imag( v )\n","base.cflipsignf":"var v = base.cflipsignf( new Complex64( -4.0, 5.0 ), -9.0 )\nvar re = realf( v )\nvar im = imagf( v )\n","base.cfloor":"var v = base.cfloor( new Complex128( 5.5, 3.3 ) )\nvar re = real( v )\nvar im = imag( v )\n","base.cfloorn":"var v = base.cfloorn( new Complex128( 5.555, -3.333 ), -2 )\nvar re = real( v )\nvar im = imag( v )\n","base.cidentity":"var v = base.cidentity( new Complex128( -1.0, 2.0 ) )\nvar re = real( v )\nvar img = imag( v )\n","base.cidentityf":"var v = base.cidentityf( new Complex64( -1.0, 2.0 ) )\nvar re = realf( v )\nvar img = imagf( v )\n","base.cinv":"var v = base.cinv( new Complex128( 2.0, 4.0 ) )\nvar re = real( v )\nvar im = imag( v )\n","base.clamp":"var y = base.clamp( 3.14, 0.0, 5.0 )\ny = base.clamp( -3.14, 0.0, 5.0 )\ny = base.clamp( 3.14, 0.0, 3.0 )\ny = base.clamp( -0.0, 0.0, 5.0 )\ny = base.clamp( 0.0, -3.14, -0.0 )\ny = base.clamp( NaN, 0.0, 5.0 )\n","base.clampf":"var y = base.clampf( 3.14, 0.0, 5.0 )\ny = base.clampf( -3.14, 0.0, 5.0 )\ny = base.clampf( 3.14, 0.0, 3.0 )\ny = base.clampf( -0.0, 0.0, 5.0 )\ny = base.clampf( 0.0, -3.14, -0.0 )\ny = base.clampf( NaN, 0.0, 5.0 )\n","base.cmul":"var z1 = new Complex128( 5.0, 3.0 )\nvar z2 = new Complex128( -2.0, 1.0 )\nvar out = base.cmul( z1, z2 )\nvar re = real( out )\nvar im = imag( out )\n","base.cmulf":"var z1 = new Complex64( 5.0, 3.0 )\nvar z2 = new Complex64( -2.0, 1.0 )\nvar out = base.cmulf( z1, z2 )\nvar re = realf( out )\nvar im = imagf( out )\n","base.cneg":"var z = new Complex128( -4.2, 5.5 )\nvar v = base.cneg( z )\nvar re = real( v )\nvar im = imag( v )\n","base.cnegf":"var z = new Complex64( -4.0, 5.0 )\nvar v = base.cnegf( z )\nvar re = realf( v )\nvar im = imagf( v )\n","base.codePointAt":"var out = base.codePointAt( 'last man standing', 4, false )\nout = base.codePointAt( 'presidential election', 8, true )\nout = base.codePointAt( 'अनुच्छेद', 2, false )\nout = base.codePointAt( '🌷', 1, true )\n","base.constantcase":"var out = base.constantcase( 'Hello World!' )\nout = base.constantcase( 'I am a tiny little teapot' )\n","base.continuedFraction":"function closure() {\nvar i = 0;\nreturn function() {\n    i += 1;\n    return [ i, i ];\n};\n };\nvar gen = closure();\nvar out = base.continuedFraction( gen )\nfunction* generator() {\n var i = 0;\n while ( true ) {\n     i += 1;\n     yield [ i, i ];\n }\n };\ngen = generator();\nout = base.continuedFraction( gen )\nout = base.continuedFraction( generator(), { 'keep': true } )\nout = base.continuedFraction( generator(), { 'maxIter': 10 } )\nout = base.continuedFraction( generator(), { 'tolerance': 1e-1 } )\n","base.copysign":"var z = base.copysign( -3.14, 10.0 )\nz = base.copysign( 3.14, -1.0 )\nz = base.copysign( 1.0, -0.0 )\nz = base.copysign( -3.14, -0.0 )\nz = base.copysign( -0.0, 1.0 )\n","base.copysignf":"var z = base.copysignf( -3.0, 10.0 )\nz = base.copysignf( 3.0, -1.0 )\nz = base.copysignf( 1.0, -0.0 )\nz = base.copysignf( -3.0, -0.0 )\nz = base.copysignf( -0.0, 1.0 )\n","base.cos":"var y = base.cos( 0.0 )\ny = base.cos( PI/4.0 )\ny = base.cos( -PI/6.0 )\ny = base.cos( NaN )\n","base.cosd":"var y = base.cosd( 0.0 )\ny = base.cosd( 90.0 )\ny = base.cosd( 60.0 )\ny = base.cosd( NaN )\n","base.cosh":"var y = base.cosh( 0.0 )\ny = base.cosh( 2.0 )\ny = base.cosh( -2.0 )\ny = base.cosh( NaN )\n","base.cosm1":"var y = base.cosm1( 0.0 )\ny = base.cosm1( PI/4.0 )\ny = base.cosm1( -PI/6.0 )\ny = base.cosm1( NaN )\n","base.cospi":"var y = base.cospi( 0.0 )\ny = base.cospi( 0.5 )\ny = base.cospi( 0.1 )\ny = base.cospi( NaN )\n","base.cot":"var y = base.cot( 0.0 )\ny = base.cot( -PI/4.0 )\ny = base.cot( PI/4.0 )\ny = base.cot( NaN )\n","base.cotd":"var y = base.cotd( 0.0 )\ny = base.cotd( 90.0 )\ny = base.cotd( 60.0 )\ny = base.cotd( NaN )\n","base.coth":"var y = base.coth( 0.0 )\ny = base.coth( -0.0 )\ny = base.coth( 2.0 )\ny = base.coth( -2.0 )\ny = base.coth( +Infinity )\ny = base.coth( -Infinity )\ny = base.coth( NaN )\n","base.covercos":"var y = base.covercos( 3.14 )\ny = base.covercos( -4.2 )\ny = base.covercos( -4.6 )\ny = base.covercos( 9.5 )\ny = base.covercos( -0.0 )\n","base.coversin":"var y = base.coversin( 3.14 )\ny = base.coversin( -4.2 )\ny = base.coversin( -4.6 )\ny = base.coversin( 9.5 )\ny = base.coversin( -0.0 )\n","base.cphase":"var phi = base.cphase( new Complex128( 5.0, 3.0 ) )\n","base.cpolar":"var out = base.cpolar( new Complex128( 5.0, 3.0 ) )\n","base.cpolar.assign":"var out = new Float64Array( 2 );\nvar v = base.cpolar.assign( new Complex128( 5.0, 3.0 ), out, 1, 0 )\nvar bool = ( v === out )\n","base.cround":"var v = base.cround( new Complex128( 5.5, 3.3 ) )\nvar re = real( v )\nvar im = imag( v )\n","base.croundn":"var v = base.croundn( new Complex128( 5.555, -3.336 ), -2 )\nvar re = real( v )\nvar im = imag( v )\n","base.csc":"var y = base.csc( 0.0 )\ny = base.csc( PI/2.0 )\ny = base.csc( -PI/6.0 )\ny = base.csc( NaN )\n","base.cscd":"var y = base.cscd( 1.0 )\ny = base.cscd( PI )\ny = base.cscd( -PI )\ny = base.cscd( NaN )\n","base.csch":"var y = base.csch( +0.0 )\nvar y = base.csch( -0.0 )\nvar y = base.csch( +Infinity )\nvar y = base.csch( -Infinity )\ny = base.csch( 2.0 )\ny = base.csch( -2.0 )\ny = base.csch( NaN )\n","base.csignum":"var v = base.csignum( new Complex128( -4.2, 5.5 ) )\nvar re = real( v )\nvar im = imag( v )\n","base.csub":"var z1 = new Complex128( 5.0, 3.0 )\nvar z2 = new Complex128( -2.0, 1.0 )\nvar out = base.csub( z1, z2 )\nvar re = real( out )\nvar im = imag( out )\n","base.csubf":"var z1 = new Complex64( 5.0, 3.0 )\nvar z2 = new Complex64( -2.0, 1.0 )\nvar out = base.csubf( z1, z2 )\nvar re = realf( out )\nvar im = imagf( out )\n","base.deg2rad":"var r = base.deg2rad( 90.0 )\nr = base.deg2rad( -45.0 )\nr = base.deg2rad( NaN )\n","base.deg2radf":"var r = base.deg2radf( 90.0 )\nr = base.deg2radf( -45.0 )\nr = base.deg2radf( NaN )\n","base.digamma":"var y = base.digamma( -2.5 )\ny = base.digamma( 1.0 )\ny = base.digamma( 10.0 )\ny = base.digamma( NaN )\ny = base.digamma( -1.0 )\n","base.diracDelta":"var y = base.diracDelta( 3.14 )\ny = base.diracDelta( 0.0 )\n","base.div":"var v = base.div( -1.0, 5.0 )\nv = base.div( 2.0, 5.0 )\nv = base.div( 0.0, 5.0 )\nv = base.div( -0.0, 5.0 )\nv = base.div( NaN, NaN )\n","base.divf":"var v = base.divf( 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)\n","base.dists.arcsine.cdf.factory":"var mycdf = base.dists.arcsine.cdf.factory( 0.0, 10.0 );\nvar y = mycdf( 0.5 )\ny = mycdf( 8.0 )\n","base.dists.arcsine.entropy":"var v = base.dists.arcsine.entropy( 0.0, 1.0 )\nv = base.dists.arcsine.entropy( 4.0, 12.0 )\nv = base.dists.arcsine.entropy( 2.0, 8.0 )\n","base.dists.arcsine.kurtosis":"var v = base.dists.arcsine.kurtosis( 0.0, 1.0 )\nv = base.dists.arcsine.kurtosis( 4.0, 12.0 )\nv = base.dists.arcsine.kurtosis( 2.0, 8.0 )\n","base.dists.arcsine.logcdf":"var y = base.dists.arcsine.logcdf( 9.0, 0.0, 10.0 )\ny = base.dists.arcsine.logcdf( 0.5, 0.0, 2.0 )\ny = base.dists.arcsine.logcdf( PINF, 2.0, 4.0 )\ny = base.dists.arcsine.logcdf( NINF, 2.0, 4.0 )\ny = base.dists.arcsine.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.logcdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.logcdf( 2.0, 1.0, 0.0 )\n","base.dists.arcsine.logcdf.factory":"var mylogcdf = base.dists.arcsine.logcdf.factory( 0.0, 10.0 );\nvar y = mylogcdf( 0.5 )\ny = mylogcdf( 8.0 )\n","base.dists.arcsine.logpdf":"var y = base.dists.arcsine.logpdf( 2.0, 0.0, 4.0 )\ny = base.dists.arcsine.logpdf( 5.0, 0.0, 4.0 )\ny = base.dists.arcsine.logpdf( 0.25, 0.0, 1.0 )\ny = base.dists.arcsine.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.logpdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.logpdf( 2.0, 3.0, 1.0 )\n","base.dists.arcsine.logpdf.factory":"var mylogPDF = base.dists.arcsine.logpdf.factory( 6.0, 7.0 );\nvar y = mylogPDF( 7.0 )\ny = mylogPDF( 5.0 )\n","base.dists.arcsine.mean":"var v = base.dists.arcsine.mean( 0.0, 1.0 )\nv = base.dists.arcsine.mean( 4.0, 12.0 )\nv = base.dists.arcsine.mean( 2.0, 8.0 )\n","base.dists.arcsine.median":"var v = base.dists.arcsine.median( 0.0, 1.0 )\nv = base.dists.arcsine.median( 4.0, 12.0 )\nv = base.dists.arcsine.median( 2.0, 8.0 )\n","base.dists.arcsine.mode":"var v = base.dists.arcsine.mode( 0.0, 1.0 )\nv = base.dists.arcsine.mode( 4.0, 12.0 )\nv = base.dists.arcsine.mode( 2.0, 8.0 )\n","base.dists.arcsine.pdf":"var y = base.dists.arcsine.pdf( 2.0, 0.0, 4.0 )\ny = base.dists.arcsine.pdf( 5.0, 0.0, 4.0 )\ny = base.dists.arcsine.pdf( 0.25, 0.0, 1.0 )\ny = base.dists.arcsine.pdf( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.pdf( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.pdf( 0.0, 0.0, NaN )\ny = base.dists.arcsine.pdf( 2.0, 3.0, 1.0 )\n","base.dists.arcsine.pdf.factory":"var myPDF = base.dists.arcsine.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 7.0 )\ny = myPDF( 5.0 )\n","base.dists.arcsine.quantile":"var y = base.dists.arcsine.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( 0.5, 0.0, 10.0 )\ny = base.dists.arcsine.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( NaN, 0.0, 1.0 )\ny = base.dists.arcsine.quantile( 0.0, NaN, 1.0 )\ny = base.dists.arcsine.quantile( 0.0, 0.0, NaN )\ny = base.dists.arcsine.quantile( 0.5, 2.0, 1.0 )\n","base.dists.arcsine.quantile.factory":"var myQuantile = base.dists.arcsine.quantile.factory( 0.0, 4.0 );\nvar y = myQuantile( 0.8 )\n","base.dists.arcsine.skewness":"var v = base.dists.arcsine.skewness( 0.0, 1.0 )\nv = base.dists.arcsine.skewness( 4.0, 12.0 )\nv = base.dists.arcsine.skewness( 2.0, 8.0 )\n","base.dists.arcsine.stdev":"var v = base.dists.arcsine.stdev( 0.0, 1.0 )\nv = base.dists.arcsine.stdev( 4.0, 12.0 )\nv = base.dists.arcsine.stdev( 2.0, 8.0 )\n","base.dists.arcsine.variance":"var v = base.dists.arcsine.variance( 0.0, 1.0 )\nv = base.dists.arcsine.variance( 4.0, 12.0 )\nv = base.dists.arcsine.variance( 2.0, 8.0 )\n","base.dists.bernoulli.Bernoulli":"var bernoulli = base.dists.bernoulli.Bernoulli( 0.6 );\nbernoulli.p\nbernoulli.entropy\nbernoulli.kurtosis\nbernoulli.mean\nbernoulli.median\nbernoulli.skewness\nbernoulli.stdev\nbernoulli.variance\nbernoulli.cdf( 0.5 )\nbernoulli.mgf( 3.0 )\nbernoulli.pmf( 0.0 )\nbernoulli.quantile( 0.7 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0.2, 0.5 )\ny = base.dists.bernoulli.mgf( 0.4, 0.5 )\ny = base.dists.bernoulli.mgf( NaN, 0.0 )\ny = base.dists.bernoulli.mgf( 0.0, NaN )\ny = base.dists.bernoulli.mgf( -2.0, -1.0 )\ny = base.dists.bernoulli.mgf( 0.2, 2.0 )\n","base.dists.bernoulli.mgf.factory":"var mymgf = base.dists.bernoulli.mgf.factory( 0.8 );\nvar y = mymgf( -0.2 )\n","base.dists.bernoulli.mode":"var v = base.dists.bernoulli.mode( 0.1 )\nv = base.dists.bernoulli.mode( 0.8 )\n","base.dists.bernoulli.pmf":"var y = base.dists.bernoulli.pmf( 1.0, 0.3 )\ny = base.dists.bernoulli.pmf( 0.0, 0.7 )\ny = base.dists.bernoulli.pmf( -1.0, 0.5 )\ny = base.dists.bernoulli.pmf( 0.0, NaN )\ny = base.dists.bernoulli.pmf( NaN, 0.5 )\ny = base.dists.bernoulli.pmf( 0.0, 1.5 )\n","base.dists.bernoulli.pmf.factory":"var mypmf = base.dists.bernoulli.pmf.factory( 0.5 );\nvar y = mypmf( 1.0 )\ny = mypmf( 0.0 )\n","base.dists.bernoulli.quantile":"var y = base.dists.bernoulli.quantile( 0.8, 0.4 )\ny = base.dists.bernoulli.quantile( 0.5, 0.4 )\ny = base.dists.bernoulli.quantile( 0.9, 0.1 )\ny = base.dists.bernoulli.quantile( -0.2, 0.1 )\ny = base.dists.bernoulli.quantile( NaN, 0.8 )\ny = base.dists.bernoulli.quantile( 0.4, NaN )\ny = base.dists.bernoulli.quantile( 0.5, -1.0 )\ny = base.dists.bernoulli.quantile( 0.5, 1.5 )\n","base.dists.bernoulli.quantile.factory":"var myquantile = base.dists.bernoulli.quantile.factory( 0.4 );\nvar y = myquantile( 0.4 )\ny = myquantile( 0.8 )\ny = myquantile( 1.0 )\n","base.dists.bernoulli.skewness":"var v = base.dists.bernoulli.skewness( 0.1 )\nv = base.dists.bernoulli.skewness( 0.5 )\n","base.dists.bernoulli.stdev":"var v = base.dists.bernoulli.stdev( 0.1 )\nv = base.dists.bernoulli.stdev( 0.5 )\n","base.dists.bernoulli.variance":"var v = base.dists.bernoulli.variance( 0.1 )\nv = base.dists.bernoulli.variance( 0.5 )\n","base.dists.beta.Beta":"var beta = base.dists.beta.Beta( 1.0, 1.0 );\nbeta.alpha\nbeta.beta\nbeta.entropy\nbeta.kurtosis\nbeta.mean\nbeta.median\nbeta.mode\nbeta.skewness\nbeta.stdev\nbeta.variance\nbeta.cdf( 0.8 )\nbeta.logcdf( 0.8 )\nbeta.logpdf( 1.0 )\nbeta.mgf( 3.14 )\nbeta.pdf( 1.0 )\nbeta.quantile( 0.8 )\n","base.dists.beta.cdf":"var y = base.dists.beta.cdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.cdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.cdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.cdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.cdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.cdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.beta.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.beta.cdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.cdf( 0.0, NaN, 1.0 )\ny = base.dists.beta.cdf( 0.0, 1.0, NaN )\n","base.dists.beta.cdf.factory":"var mycdf = base.dists.beta.cdf.factory( 0.5, 0.5 );\nvar y = mycdf( 0.8 )\ny = mycdf( 0.3 )\n","base.dists.beta.entropy":"var v = base.dists.beta.entropy( 1.0, 1.0 )\nv = base.dists.beta.entropy( 4.0, 12.0 )\nv = base.dists.beta.entropy( 8.0, 2.0 )\nv = base.dists.beta.entropy( 1.0, -0.1 )\nv = base.dists.beta.entropy( -0.1, 1.0 )\nv = base.dists.beta.entropy( 2.0, NaN )\nv = base.dists.beta.entropy( NaN, 2.0 )\n","base.dists.beta.kurtosis":"var v = base.dists.beta.kurtosis( 1.0, 1.0 )\nv = base.dists.beta.kurtosis( 4.0, 12.0 )\nv = base.dists.beta.kurtosis( 8.0, 2.0 )\nv = base.dists.beta.kurtosis( 1.0, -0.1 )\nv = base.dists.beta.kurtosis( -0.1, 1.0 )\nv = base.dists.beta.kurtosis( 2.0, NaN )\nv = base.dists.beta.kurtosis( NaN, 2.0 )\n","base.dists.beta.logcdf":"var y = base.dists.beta.logcdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.logcdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.logcdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.logcdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.logcdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.logcdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.beta.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.beta.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.beta.logcdf( 0.0, 1.0, NaN )\n","base.dists.beta.logcdf.factory":"var mylogcdf = base.dists.beta.logcdf.factory( 0.5, 0.5 );\nvar y = mylogcdf( 0.8 )\ny = mylogcdf( 0.3 )\n","base.dists.beta.logpdf":"var y = base.dists.beta.logpdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.logpdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.logpdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.logpdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.logpdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.logpdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.logpdf( 0.5, -1.0, 0.5 )\ny = base.dists.beta.logpdf( 0.5, 0.5, -1.0 )\ny = base.dists.beta.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.logpdf( 0.5, NaN, 1.0 )\ny = base.dists.beta.logpdf( 0.5, 1.0, NaN )\n","base.dists.beta.logpdf.factory":"var mylogpdf = base.dists.beta.logpdf.factory( 0.5, 0.5 );\nvar y = mylogpdf( 0.8 )\ny = mylogpdf( 0.3 )\n","base.dists.beta.mean":"var v = base.dists.beta.mean( 1.0, 1.0 )\nv = base.dists.beta.mean( 4.0, 12.0 )\nv = base.dists.beta.mean( 8.0, 2.0 )\n","base.dists.beta.median":"var v = base.dists.beta.median( 1.0, 1.0 )\nv = base.dists.beta.median( 4.0, 12.0 )\nv = base.dists.beta.median( 8.0, 2.0 )\nv = base.dists.beta.median( 1.0, -0.1 )\nv = base.dists.beta.median( -0.1, 1.0 )\nv = base.dists.beta.median( 2.0, NaN )\nv = base.dists.beta.median( NaN, 2.0 )\n","base.dists.beta.mgf":"var y = base.dists.beta.mgf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.mgf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.mgf( 3.0, 2.0, 2.0 )\ny = base.dists.beta.mgf( -0.8, 4.0, 4.0 )\ny = base.dists.beta.mgf( NaN, 1.0, 1.0 )\ny = base.dists.beta.mgf( 0.0, NaN, 1.0 )\ny = base.dists.beta.mgf( 0.0, 1.0, NaN )\ny = base.dists.beta.mgf( 2.0, -1.0, 0.5 )\ny = base.dists.beta.mgf( 2.0, 0.0, 0.5 )\ny = base.dists.beta.mgf( 2.0, 0.5, -1.0 )\ny = base.dists.beta.mgf( 2.0, 0.5, 0.0 )\n","base.dists.beta.mgf.factory":"var myMGF = base.dists.beta.mgf.factory( 0.5, 0.5 );\nvar y = myMGF( 0.8 )\ny = myMGF( 0.3 )\n","base.dists.beta.mode":"var v = base.dists.beta.mode( 4.0, 12.0 )\nv = base.dists.beta.mode( 8.0, 2.0 )\nv = base.dists.beta.mode( 1.0, 1.0 )\n","base.dists.beta.pdf":"var y = base.dists.beta.pdf( 0.5, 1.0, 1.0 )\ny = base.dists.beta.pdf( 0.5, 2.0, 4.0 )\ny = base.dists.beta.pdf( 0.2, 2.0, 2.0 )\ny = base.dists.beta.pdf( 0.8, 4.0, 4.0 )\ny = base.dists.beta.pdf( -0.5, 4.0, 2.0 )\ny = base.dists.beta.pdf( 1.5, 4.0, 2.0 )\ny = base.dists.beta.pdf( 0.5, -1.0, 0.5 )\ny = base.dists.beta.pdf( 0.5, 0.5, -1.0 )\ny = base.dists.beta.pdf( NaN, 1.0, 1.0 )\ny = base.dists.beta.pdf( 0.5, NaN, 1.0 )\ny = base.dists.beta.pdf( 0.5, 1.0, NaN )\n","base.dists.beta.pdf.factory":"var mypdf = base.dists.beta.pdf.factory( 0.5, 0.5 );\nvar y = mypdf( 0.8 )\ny = mypdf( 0.3 )\n","base.dists.beta.quantile":"var y = base.dists.beta.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.beta.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.beta.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.beta.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.beta.quantile( NaN, 1.0, 1.0 )\ny = base.dists.beta.quantile( 0.5, NaN, 1.0 )\ny = base.dists.beta.quantile( 0.5, 1.0, NaN )\ny = base.dists.beta.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.beta.quantile( 0.5, 1.0, -1.0 )\n","base.dists.beta.quantile.factory":"var myquantile = base.dists.beta.quantile.factory( 2.0, 2.0 );\ny = myquantile( 0.8 )\ny = myquantile( 0.4 )\n","base.dists.beta.skewness":"var v = base.dists.beta.skewness( 1.0, 1.0 )\nv = base.dists.beta.skewness( 4.0, 12.0 )\nv = base.dists.beta.skewness( 8.0, 2.0 )\nv = base.dists.beta.skewness( 1.0, -0.1 )\nv = base.dists.beta.skewness( -0.1, 1.0 )\nv = base.dists.beta.skewness( 2.0, NaN )\nv = base.dists.beta.skewness( NaN, 2.0 )\n","base.dists.beta.stdev":"var v = base.dists.beta.stdev( 1.0, 1.0 )\nv = base.dists.beta.stdev( 4.0, 12.0 )\nv = base.dists.beta.stdev( 8.0, 2.0 )\nv = base.dists.beta.stdev( 1.0, -0.1 )\nv = base.dists.beta.stdev( -0.1, 1.0 )\nv = base.dists.beta.stdev( 2.0, NaN )\nv = base.dists.beta.stdev( NaN, 2.0 )\n","base.dists.beta.variance":"var v = base.dists.beta.variance( 1.0, 1.0 )\nv = base.dists.beta.variance( 4.0, 12.0 )\nv = base.dists.beta.variance( 8.0, 2.0 )\nv = base.dists.beta.variance( 1.0, -0.1 )\nv = base.dists.beta.variance( -0.1, 1.0 )\nv = base.dists.beta.variance( 2.0, NaN )\nv = base.dists.beta.variance( NaN, 2.0 )\n","base.dists.betaprime.BetaPrime":"var betaprime = base.dists.betaprime.BetaPrime( 6.0, 5.0 );\nbetaprime.alpha\nbetaprime.beta\nbetaprime.kurtosis\nbetaprime.mean\nbetaprime.mode\nbetaprime.skewness\nbetaprime.stdev\nbetaprime.variance\nbetaprime.cdf( 0.8 )\nbetaprime.logcdf( 0.8 )\nbetaprime.logpdf( 1.0 )\nbetaprime.pdf( 1.0 )\nbetaprime.quantile( 0.8 )\n","base.dists.betaprime.cdf":"var y = base.dists.betaprime.cdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.cdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.cdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.cdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.cdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.betaprime.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.betaprime.cdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.cdf( 0.0, NaN, 1.0 )\ny = base.dists.betaprime.cdf( 0.0, 1.0, NaN )\n","base.dists.betaprime.cdf.factory":"var mycdf = base.dists.betaprime.cdf.factory( 0.5, 0.5 );\nvar y = mycdf( 0.8 )\ny = mycdf( 0.3 )\n","base.dists.betaprime.kurtosis":"var v = base.dists.betaprime.kurtosis( 2.0, 6.0 )\nv = base.dists.betaprime.kurtosis( 4.0, 12.0 )\nv = base.dists.betaprime.kurtosis( 8.0, 6.0 )\nv = base.dists.betaprime.kurtosis( 1.0, 2.8 )\nv = base.dists.betaprime.kurtosis( 1.0, -0.1 )\nv = base.dists.betaprime.kurtosis( -0.1, 5.0 )\nv = base.dists.betaprime.kurtosis( 2.0, NaN )\nv = base.dists.betaprime.kurtosis( NaN, 6.0 )\n","base.dists.betaprime.logcdf":"var y = base.dists.betaprime.logcdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.logcdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.logcdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.logcdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.logcdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.betaprime.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.betaprime.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.betaprime.logcdf( 0.0, 1.0, NaN )\n","base.dists.betaprime.logcdf.factory":"var mylogcdf = base.dists.betaprime.logcdf.factory( 0.5, 0.5 );\nvar y = mylogcdf( 0.8 )\ny = mylogcdf( 0.3 )\n","base.dists.betaprime.logpdf":"var y = base.dists.betaprime.logpdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.logpdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.logpdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.logpdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.logpdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.logpdf( 0.5, -1.0, 0.5 )\ny = base.dists.betaprime.logpdf( 0.5, 0.5, -1.0 )\ny = base.dists.betaprime.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.logpdf( 0.5, NaN, 1.0 )\ny = base.dists.betaprime.logpdf( 0.5, 1.0, NaN )\n","base.dists.betaprime.logpdf.factory":"var mylogpdf = base.dists.betaprime.logpdf.factory( 0.5, 0.5 );\nvar y = mylogpdf( 0.8 )\ny = mylogpdf( 0.3 )\n","base.dists.betaprime.mean":"var v = base.dists.betaprime.mean( 1.0, 2.0 )\nv = base.dists.betaprime.mean( 4.0, 12.0 )\nv = base.dists.betaprime.mean( 8.0, 2.0 )\n","base.dists.betaprime.mode":"var v = base.dists.betaprime.mode( 1.0, 2.0 )\nv = base.dists.betaprime.mode( 4.0, 12.0 )\nv = base.dists.betaprime.mode( 8.0, 2.0 )\n","base.dists.betaprime.pdf":"var y = base.dists.betaprime.pdf( 0.5, 1.0, 1.0 )\ny = base.dists.betaprime.pdf( 0.5, 2.0, 4.0 )\ny = base.dists.betaprime.pdf( 0.2, 2.0, 2.0 )\ny = base.dists.betaprime.pdf( 0.8, 4.0, 4.0 )\ny = base.dists.betaprime.pdf( -0.5, 4.0, 2.0 )\ny = base.dists.betaprime.pdf( 0.5, -1.0, 0.5 )\ny = base.dists.betaprime.pdf( 0.5, 0.5, -1.0 )\ny = base.dists.betaprime.pdf( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.pdf( 0.5, NaN, 1.0 )\ny = base.dists.betaprime.pdf( 0.5, 1.0, NaN )\n","base.dists.betaprime.pdf.factory":"var mypdf = base.dists.betaprime.pdf.factory( 0.5, 0.5 );\nvar y = mypdf( 0.8 )\ny = mypdf( 0.3 )\n","base.dists.betaprime.quantile":"var y = base.dists.betaprime.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.betaprime.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.betaprime.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.betaprime.quantile( NaN, 1.0, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, NaN, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, 1.0, NaN )\ny = base.dists.betaprime.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.betaprime.quantile( 0.5, 1.0, -1.0 )\n","base.dists.betaprime.quantile.factory":"var myQuantile = base.dists.betaprime.quantile.factory( 2.0, 2.0 );\ny = myQuantile( 0.8 )\ny = myQuantile( 0.4 )\n","base.dists.betaprime.skewness":"var v = base.dists.betaprime.skewness( 2.0, 4.0 )\nv = base.dists.betaprime.skewness( 4.0, 12.0 )\nv = base.dists.betaprime.skewness( 8.0, 4.0 )\nv = base.dists.betaprime.skewness( 1.0, 2.8 )\nv = base.dists.betaprime.skewness( 1.0, -0.1 )\nv = base.dists.betaprime.skewness( -0.1, 4.0 )\nv = base.dists.betaprime.skewness( 2.0, NaN )\nv = base.dists.betaprime.skewness( NaN, 4.0 )\n","base.dists.betaprime.stdev":"var v = base.dists.betaprime.stdev( 1.0, 2.5 )\nv = base.dists.betaprime.stdev( 4.0, 12.0 )\nv = base.dists.betaprime.stdev( 8.0, 2.5 )\nv = base.dists.betaprime.stdev( 8.0, 1.0 )\nv = base.dists.betaprime.stdev( 1.0, -0.1 )\nv = base.dists.betaprime.stdev( -0.1, 3.0 )\nv = base.dists.betaprime.stdev( 2.0, NaN )\nv = base.dists.betaprime.stdev( NaN, 3.0 )\n","base.dists.betaprime.variance":"var v = base.dists.betaprime.variance( 1.0, 2.5 )\nv = base.dists.betaprime.variance( 4.0, 12.0 )\nv = base.dists.betaprime.variance( 8.0, 2.5 )\nv = base.dists.betaprime.variance( 8.0, 1.0 )\nv = base.dists.betaprime.variance( 1.0, -0.1 )\nv = base.dists.betaprime.variance( -0.1, 3.0 )\nv = base.dists.betaprime.variance( 2.0, NaN )\nv = base.dists.betaprime.variance( NaN, 3.0 )\n","base.dists.binomial.Binomial":"var binomial = base.dists.binomial.Binomial( 8, 0.5 );\nbinomial.n\nbinomial.p\nbinomial.kurtosis\nbinomial.mean\nbinomial.median\nbinomial.mode\nbinomial.skewness\nbinomial.stdev\nbinomial.variance\nbinomial.cdf( 2.9 )\nbinomial.logpmf( 3.0 )\nbinomial.mgf( 0.2 )\nbinomial.pmf( 3.0 )\nbinomial.quantile( 0.8 )\n","base.dists.binomial.cdf":"var y = base.dists.binomial.cdf( 3.0, 20, 0.2 )\ny = base.dists.binomial.cdf( 21.0, 20, 0.2 )\ny = base.dists.binomial.cdf( 5.0, 10, 0.4 )\ny = base.dists.binomial.cdf( 0.0, 10, 0.4 )\ny = base.dists.binomial.cdf( NaN, 20, 0.5 )\ny = base.dists.binomial.cdf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.cdf( 0.0, 20, NaN )\ny = base.dists.binomial.cdf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.cdf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.cdf( 2.0, 20, -1.0 )\ny = base.dists.binomial.cdf( 2.0, 20, 1.5 )\n","base.dists.binomial.cdf.factory":"var mycdf = base.dists.binomial.cdf.factory( 10, 0.5 );\nvar y = mycdf( 3.0 )\ny = mycdf( 1.0 )\n","base.dists.binomial.entropy":"var v = base.dists.binomial.entropy( 100, 0.1 )\nv = base.dists.binomial.entropy( 20, 0.5 )\nv = base.dists.binomial.entropy( 10.3, 0.5 )\nv = base.dists.binomial.entropy( 20, 1.1 )\nv = base.dists.binomial.entropy( 20, NaN )\n","base.dists.binomial.kurtosis":"var v = base.dists.binomial.kurtosis( 100, 0.1 )\nv = base.dists.binomial.kurtosis( 20, 0.5 )\nv = base.dists.binomial.kurtosis( 10.3, 0.5 )\nv = base.dists.binomial.kurtosis( 20, 1.1 )\nv = base.dists.binomial.kurtosis( 20, NaN )\n","base.dists.binomial.logpmf":"var y = base.dists.binomial.logpmf( 3.0, 20, 0.2 )\ny = base.dists.binomial.logpmf( 21.0, 20, 0.2 )\ny = base.dists.binomial.logpmf( 5.0, 10, 0.4 )\ny = base.dists.binomial.logpmf( 0.0, 10, 0.4 )\ny = base.dists.binomial.logpmf( NaN, 20, 0.5 )\ny = base.dists.binomial.logpmf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.logpmf( 0.0, 20, NaN )\ny = base.dists.binomial.logpmf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.logpmf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.logpmf( 2.0, 20, -1.0 )\ny = base.dists.binomial.logpmf( 2.0, 20, 1.5 )\n","base.dists.binomial.logpmf.factory":"var mylogpmf = base.dists.binomial.logpmf.factory( 10, 0.5 );\nvar y = mylogpmf( 3.0 )\ny = mylogpmf( 5.0 )\n","base.dists.binomial.mean":"var v = base.dists.binomial.mean( 100, 0.1 )\nv = base.dists.binomial.mean( 20, 0.5 )\nv = base.dists.binomial.mean( 10.3, 0.5 )\nv = base.dists.binomial.mean( 20, 1.1 )\nv = base.dists.binomial.mean( 20, NaN )\n","base.dists.binomial.median":"var v = base.dists.binomial.median( 100, 0.1 )\nv = base.dists.binomial.median( 20, 0.5 )\nv = base.dists.binomial.median( 10.3, 0.5 )\nv = base.dists.binomial.median( 20, 1.1 )\nv = base.dists.binomial.median( 20, NaN )\n","base.dists.binomial.mgf":"var y = base.dists.binomial.mgf( 0.5, 20, 0.2 )\ny = base.dists.binomial.mgf( 5.0, 20, 0.2 )\ny = base.dists.binomial.mgf( 0.9, 10, 0.4 )\ny = base.dists.binomial.mgf( 0.0, 10, 0.4 )\ny = base.dists.binomial.mgf( NaN, 20, 0.5 )\ny = base.dists.binomial.mgf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.mgf( 0.0, 20, NaN )\ny = base.dists.binomial.mgf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.mgf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.mgf( 2.0, 20, -1.0 )\ny = base.dists.binomial.mgf( 2.0, 20, 1.5 )\n","base.dists.binomial.mgf.factory":"var myMGF = base.dists.binomial.mgf.factory( 10, 0.5 );\nvar y = myMGF( 0.3 )\n","base.dists.binomial.mode":"var v = base.dists.binomial.mode( 100, 0.1 )\nv = base.dists.binomial.mode( 20, 0.5 )\nv = base.dists.binomial.mode( 10.3, 0.5 )\nv = base.dists.binomial.mode( 20, 1.1 )\nv = base.dists.binomial.mode( 20, NaN )\n","base.dists.binomial.pmf":"var y = base.dists.binomial.pmf( 3.0, 20, 0.2 )\ny = base.dists.binomial.pmf( 21.0, 20, 0.2 )\ny = base.dists.binomial.pmf( 5.0, 10, 0.4 )\ny = base.dists.binomial.pmf( 0.0, 10, 0.4 )\ny = base.dists.binomial.pmf( NaN, 20, 0.5 )\ny = base.dists.binomial.pmf( 0.0, NaN, 0.5 )\ny = base.dists.binomial.pmf( 0.0, 20, NaN )\ny = base.dists.binomial.pmf( 2.0, 1.5, 0.5 )\ny = base.dists.binomial.pmf( 2.0, -2.0, 0.5 )\ny = base.dists.binomial.pmf( 2.0, 20, -1.0 )\ny = base.dists.binomial.pmf( 2.0, 20, 1.5 )\n","base.dists.binomial.pmf.factory":"var mypmf = base.dists.binomial.pmf.factory( 10, 0.5 );\nvar y = mypmf( 3.0 )\ny = mypmf( 5.0 )\n","base.dists.binomial.quantile":"var y = base.dists.binomial.quantile( 0.4, 20, 0.2 )\ny = base.dists.binomial.quantile( 0.8, 20, 0.2 )\ny = base.dists.binomial.quantile( 0.5, 10, 0.4 )\ny = base.dists.binomial.quantile( 0.0, 10, 0.4 )\ny = base.dists.binomial.quantile( 1.0, 10, 0.4 )\ny = base.dists.binomial.quantile( NaN, 20, 0.5 )\ny = base.dists.binomial.quantile( 0.2, NaN, 0.5 )\ny = base.dists.binomial.quantile( 0.2, 20, NaN )\ny = base.dists.binomial.quantile( 0.5, 1.5, 0.5 )\ny = base.dists.binomial.quantile( 0.5, -2.0, 0.5 )\ny = base.dists.binomial.quantile( 0.5, 20, -1.0 )\ny = base.dists.binomial.quantile( 0.5, 20, 1.5 )\n","base.dists.binomial.quantile.factory":"var myquantile = base.dists.binomial.quantile.factory( 10, 0.5 );\nvar y = myquantile( 0.1 )\ny = myquantile( 0.9 )\n","base.dists.binomial.skewness":"var v = base.dists.binomial.skewness( 100, 0.1 )\nv = base.dists.binomial.skewness( 20, 0.5 )\nv = base.dists.binomial.skewness( 10.3, 0.5 )\nv = base.dists.binomial.skewness( 20, 1.1 )\nv = base.dists.binomial.skewness( 20, NaN )\n","base.dists.binomial.stdev":"var v = base.dists.binomial.stdev( 100, 0.1 )\nv = base.dists.binomial.stdev( 20, 0.5 )\nv = base.dists.binomial.stdev( 10.3, 0.5 )\nv = base.dists.binomial.stdev( 20, 1.1 )\nv = base.dists.binomial.stdev( 20, NaN )\n","base.dists.binomial.variance":"var v = base.dists.binomial.variance( 100, 0.1 )\nv = base.dists.binomial.variance( 20, 0.5 )\nv = base.dists.binomial.variance( 10.3, 0.5 )\nv = base.dists.binomial.variance( 20, 1.1 )\nv = base.dists.binomial.variance( 20, NaN )\n","base.dists.cauchy.Cauchy":"var cauchy = base.dists.cauchy.Cauchy( 0.0, 1.0 );\ncauchy.x0\ncauchy.gamma\ncauchy.entropy\ncauchy.median\ncauchy.mode\ncauchy.cdf( 0.8 )\ncauchy.logcdf( 1.0 )\ncauchy.logpdf( 1.0 )\ncauchy.pdf( 1.0 )\ncauchy.quantile( 0.8 )\n","base.dists.cauchy.cdf":"var y = base.dists.cauchy.cdf( 4.0, 0.0, 2.0 )\ny = base.dists.cauchy.cdf( 1.0, 0.0, 2.0 )\ny = base.dists.cauchy.cdf( 1.0, 3.0, 2.0 )\ny = base.dists.cauchy.cdf( NaN, 0.0, 2.0 )\ny = base.dists.cauchy.cdf( 1.0, 2.0, NaN )\ny = base.dists.cauchy.cdf( 1.0, NaN, 3.0 )\n","base.dists.cauchy.cdf.factory":"var myCDF = base.dists.cauchy.cdf.factory( 1.5, 3.0 );\nvar y = myCDF( 1.0 )\n","base.dists.cauchy.entropy":"var v = base.dists.cauchy.entropy( 10.0, 7.0 )\nv = base.dists.cauchy.entropy( 22.0, 0.5 )\nv = base.dists.cauchy.entropy( 10.3, -0.5 )\n","base.dists.cauchy.logcdf":"var y = base.dists.cauchy.logcdf( 4.0, 0.0, 2.0 )\ny = base.dists.cauchy.logcdf( 1.0, 0.0, 2.0 )\ny = base.dists.cauchy.logcdf( 1.0, 3.0, 2.0 )\ny = base.dists.cauchy.logcdf( NaN, 0.0, 2.0 )\ny = base.dists.cauchy.logcdf( 1.0, 2.0, NaN )\ny = base.dists.cauchy.logcdf( 1.0, NaN, 3.0 )\n","base.dists.cauchy.logcdf.factory":"var mylogCDF = base.dists.cauchy.logcdf.factory( 1.5, 3.0 );\nvar y = mylogCDF( 1.0 )\n","base.dists.cauchy.logpdf":"var y = base.dists.cauchy.logpdf( 2.0, 1.0, 1.0 )\ny = base.dists.cauchy.logpdf( 4.0, 3.0, 0.1 )\ny = base.dists.cauchy.logpdf( 4.0, 3.0, 3.0 )\ny = base.dists.cauchy.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.cauchy.logpdf( 2.0, NaN, 1.0 )\ny = base.dists.cauchy.logpdf( 2.0, 1.0, NaN )\ny = base.dists.cauchy.logpdf( 2.0, 1.0, -2.0 )\n","base.dists.cauchy.logpdf.factory":"var mylogPDF = base.dists.cauchy.logpdf.factory( 10.0, 2.0 );\nvar y = mylogPDF( 10.0 )\n","base.dists.cauchy.median":"var v = base.dists.cauchy.median( 10.0, 5.0 )\nv = base.dists.cauchy.median( 7.0, 0.5 )\nv = base.dists.cauchy.median( 10.3, -0.5 )\n","base.dists.cauchy.mode":"var v = base.dists.cauchy.mode( 10.0, 5.0 )\nv = base.dists.cauchy.mode( 7.0, 0.5 )\nv = base.dists.cauchy.mode( 10.3, -0.5 )\n","base.dists.cauchy.pdf":"var y = base.dists.cauchy.pdf( 2.0, 1.0, 1.0 )\ny = base.dists.cauchy.pdf( 4.0, 3.0, 0.1 )\ny = base.dists.cauchy.pdf( 4.0, 3.0, 3.0 )\ny = base.dists.cauchy.pdf( NaN, 1.0, 1.0 )\ny = base.dists.cauchy.pdf( 2.0, NaN, 1.0 )\ny = base.dists.cauchy.pdf( 2.0, 1.0, NaN )\ny = base.dists.cauchy.pdf( 2.0, 1.0, -2.0 )\n","base.dists.cauchy.pdf.factory":"var myPDF = base.dists.cauchy.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\n","base.dists.cauchy.quantile":"var y = base.dists.cauchy.quantile( 0.3, 2.0, 2.0 )\ny = base.dists.cauchy.quantile( 0.8, 10, 2.0 )\ny = base.dists.cauchy.quantile( 0.1, 10.0, 2.0 )\ny = base.dists.cauchy.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.cauchy.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.cauchy.quantile( NaN, 0.0, 1.0 )\ny = base.dists.cauchy.quantile( 0.0, NaN, 1.0 )\ny = base.dists.cauchy.quantile( 0.0, 0.0, NaN )\ny = base.dists.cauchy.quantile( 0.5, 0.0, -1.0 )\n","base.dists.cauchy.quantile.factory":"var myQuantile = base.dists.cauchy.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.chi.cdf":"var y = base.dists.chi.cdf( 2.0, 3.0 )\ny = base.dists.chi.cdf( 1.0, 0.5 )\ny = base.dists.chi.cdf( -1.0, 4.0 )\ny = base.dists.chi.cdf( NaN, 1.0 )\ny = base.dists.chi.cdf( 0.0, NaN )\ny = base.dists.chi.cdf( 2.0, -1.0 )\ny = base.dists.chi.cdf( 2.0, 0.0 )\ny = base.dists.chi.cdf( -2.0, 0.0 )\ny = base.dists.chi.cdf( 0.0, 0.0 )\n","base.dists.chi.cdf.factory":"var mycdf = base.dists.chi.cdf.factory( 1.0 );\nvar y = mycdf( 2.0 )\ny = mycdf( 1.2 )\n","base.dists.chi.Chi":"var chi = base.dists.chi.Chi( 6.0 );\nchi.k\nchi.entropy\nchi.kurtosis\nchi.mean\nchi.mode\nchi.skewness\nchi.stdev\nchi.variance\nchi.cdf( 1.0 )\nchi.logpdf( 1.5 )\nchi.pdf( 1.5 )\nchi.quantile( 0.5 )\n","base.dists.chi.entropy":"var v = base.dists.chi.entropy( 11.0 )\nv = base.dists.chi.entropy( 1.5 )\n","base.dists.chi.kurtosis":"var v = base.dists.chi.kurtosis( 9.0 )\nv = base.dists.chi.kurtosis( 1.5 )\n","base.dists.chi.logpdf":"var y = base.dists.chi.logpdf( 0.3, 4.0 )\ny = base.dists.chi.logpdf( 0.7, 0.7 )\ny = base.dists.chi.logpdf( -1.0, 0.5 )\ny = base.dists.chi.logpdf( 0.0, NaN )\ny = base.dists.chi.logpdf( NaN, 2.0 )\ny = base.dists.chi.logpdf( 2.0, -1.0 )\ny = base.dists.chi.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.chi.logpdf( 0.0, 0.0, 2.0 )\n","base.dists.chi.logpdf.factory":"var mylogPDF = base.dists.chi.logpdf.factory( 6.0 );\nvar y = mylogPDF( 3.0 )\n","base.dists.chi.mean":"var v = base.dists.chi.mean( 11.0 )\nv = base.dists.chi.mean( 4.5 )\n","base.dists.chi.mode":"var v = base.dists.chi.mode( 11.0 )\nv = base.dists.chi.mode( 1.5 )\n","base.dists.chi.pdf":"var y = base.dists.chi.pdf( 0.3, 4.0 )\ny = base.dists.chi.pdf( 0.7, 0.7 )\ny = base.dists.chi.pdf( -1.0, 0.5 )\ny = base.dists.chi.pdf( 0.0, NaN )\ny = base.dists.chi.pdf( NaN, 2.0 )\ny = base.dists.chi.pdf( 2.0, -1.0 )\ny = base.dists.chi.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.chi.pdf( 0.0, 0.0, 2.0 )\n","base.dists.chi.pdf.factory":"var myPDF = base.dists.chi.pdf.factory( 6.0 );\nvar y = myPDF( 3.0 )\n","base.dists.chi.quantile":"var y = base.dists.chi.quantile( 0.8, 1.0 )\ny = base.dists.chi.quantile( 0.5, 4.0 )\ny = base.dists.chi.quantile( 0.8, 0.1 )\ny = base.dists.chi.quantile( -0.2, 0.5 )\ny = base.dists.chi.quantile( 1.1, 0.5 )\ny = base.dists.chi.quantile( NaN, 1.0 )\ny = base.dists.chi.quantile( 0.0, NaN )\ny = base.dists.chi.quantile( 0.5, -1.0 )\ny = base.dists.chi.quantile( 0.3, 0.0 )\ny = base.dists.chi.quantile( 0.9, 0.0 )\n","base.dists.chi.quantile.factory":"var myquantile = base.dists.chi.quantile.factory( 2.0 );\nvar y = myquantile( 0.3 )\ny = myquantile( 0.7 )\n","base.dists.chi.skewness":"var v = base.dists.chi.skewness( 11.0 )\nv = base.dists.chi.skewness( 1.5 )\n","base.dists.chi.stdev":"var v = base.dists.chi.stdev( 11.0 )\nv = base.dists.chi.stdev( 1.5 )\n","base.dists.chi.variance":"var v = base.dists.chi.variance( 11.0 )\nv = base.dists.chi.variance( 1.5 )\n","base.dists.chisquare.cdf":"var y = base.dists.chisquare.cdf( 2.0, 3.0 )\ny = base.dists.chisquare.cdf( 1.0, 0.5 )\ny = base.dists.chisquare.cdf( -1.0, 4.0 )\ny = base.dists.chisquare.cdf( NaN, 1.0 )\ny = base.dists.chisquare.cdf( 0.0, NaN )\ny = base.dists.chisquare.cdf( 2.0, -1.0 )\ny = base.dists.chisquare.cdf( 2.0, 0.0 )\ny = base.dists.chisquare.cdf( -2.0, 0.0 )\ny = base.dists.chisquare.cdf( 0.0, 0.0 )\n","base.dists.chisquare.cdf.factory":"var mycdf = base.dists.chisquare.cdf.factory( 1.0 );\nvar y = mycdf( 2.0 )\ny = mycdf( 1.2 )\n","base.dists.chisquare.ChiSquare":"var chisquare = base.dists.chisquare.ChiSquare( 6.0 );\nchisquare.k\nchisquare.entropy\nchisquare.kurtosis\nchisquare.mean\nchisquare.median\nchisquare.mode\nchisquare.skewness\nchisquare.stdev\nchisquare.variance\nchisquare.cdf( 3.0 )\nchisquare.mgf( 0.2 )\nchisquare.pdf( 1.5 )\nchisquare.quantile( 0.5 )\n","base.dists.chisquare.entropy":"var v = base.dists.chisquare.entropy( 11.0 )\nv = base.dists.chisquare.entropy( 1.5 )\n","base.dists.chisquare.kurtosis":"var v = base.dists.chisquare.kurtosis( 9.0 )\nv = base.dists.chisquare.kurtosis( 1.5 )\n","base.dists.chisquare.logpdf":"var y = base.dists.chisquare.logpdf( 0.3, 4.0 )\ny = base.dists.chisquare.logpdf( 0.7, 0.7 )\ny = base.dists.chisquare.logpdf( -1.0, 0.5 )\ny = base.dists.chisquare.logpdf( 0.0, NaN )\ny = base.dists.chisquare.logpdf( NaN, 2.0 )\ny = base.dists.chisquare.logpdf( 2.0, -1.0 )\ny = base.dists.chisquare.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.chisquare.logpdf( 0.0, 0.0, 2.0 )\n","base.dists.chisquare.logpdf.factory":"var myLogPDF = base.dists.chisquare.logpdf.factory( 6.0 );\nvar y = myLogPDF( 3.0 )\n","base.dists.chisquare.mean":"var v = base.dists.chisquare.mean( 11.0 )\nv = base.dists.chisquare.mean( 4.5 )\n","base.dists.chisquare.median":"var k = base.dists.chisquare.median( 9.0 )\nk = base.dists.chisquare.median( 2.0 )\n","base.dists.chisquare.mgf":"var y = base.dists.chisquare.mgf( 0.4, 2 )\ny = base.dists.chisquare.mgf( -1.0, 5.0 )\ny = base.dists.chisquare.mgf( 0.0, 10.0 )\n","base.dists.chisquare.mgf.factory":"var mymgf = base.dists.chisquare.mgf.factory( 1.0 );\nvar y = mymgf( 0.2 )\ny = mymgf( 0.4 )\n","base.dists.chisquare.mode":"var v = base.dists.chisquare.mode( 11.0 )\nv = base.dists.chisquare.mode( 1.5 )\n","base.dists.chisquare.pdf":"var y = base.dists.chisquare.pdf( 0.3, 4.0 )\ny = base.dists.chisquare.pdf( 0.7, 0.7 )\ny = base.dists.chisquare.pdf( -1.0, 0.5 )\ny = base.dists.chisquare.pdf( 0.0, NaN )\ny = base.dists.chisquare.pdf( NaN, 2.0 )\ny = base.dists.chisquare.pdf( 2.0, -1.0 )\ny = base.dists.chisquare.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.chisquare.pdf( 0.0, 0.0, 2.0 )\n","base.dists.chisquare.pdf.factory":"var myPDF = base.dists.chisquare.pdf.factory( 6.0 );\nvar y = myPDF( 3.0 )\n","base.dists.chisquare.quantile":"var y = base.dists.chisquare.quantile( 0.8, 1.0 )\ny = base.dists.chisquare.quantile( 0.5, 4.0 )\ny = base.dists.chisquare.quantile( 0.8, 0.1 )\ny = base.dists.chisquare.quantile( -0.2, 0.5 )\ny = base.dists.chisquare.quantile( 1.1, 0.5 )\ny = base.dists.chisquare.quantile( NaN, 1.0 )\ny = base.dists.chisquare.quantile( 0.0, NaN )\ny = base.dists.chisquare.quantile( 0.5, -1.0 )\ny = base.dists.chisquare.quantile( 0.3, 0.0 )\ny = base.dists.chisquare.quantile( 0.9, 0.0 )\n","base.dists.chisquare.quantile.factory":"var myquantile = base.dists.chisquare.quantile.factory( 2.0 );\nvar y = myquantile( 0.3 )\ny = myquantile( 0.7 )\n","base.dists.chisquare.skewness":"var v = base.dists.chisquare.skewness( 11.0 )\nv = base.dists.chisquare.skewness( 1.5 )\n","base.dists.chisquare.stdev":"var v = base.dists.chisquare.stdev( 11.0 )\nv = base.dists.chisquare.stdev( 1.5 )\n","base.dists.chisquare.variance":"var v = base.dists.chisquare.variance( 11.0 )\nv = base.dists.chisquare.variance( 1.5 )\n","base.dists.cosine.cdf":"var y = base.dists.cosine.cdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.cdf( 9.0, 10.0, 3.0 )\ny = base.dists.cosine.cdf( 2.0, 0.0, NaN )\ny = base.dists.cosine.cdf( 2.0, NaN, 1.0 )\ny = base.dists.cosine.cdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.cdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.cdf( 8.0, 8.0, 0.0 )\ny = base.dists.cosine.cdf( 10.0, 8.0, 0.0 )\n","base.dists.cosine.cdf.factory":"var mycdf = base.dists.cosine.cdf.factory( 3.0, 1.5 );\nvar y = mycdf( 1.9 )\n","base.dists.cosine.Cosine":"var cosine = base.dists.cosine.Cosine( -2.0, 3.0 );\ncosine.mu\ncosine.s\ncosine.kurtosis\ncosine.mean\ncosine.median\ncosine.mode\ncosine.skewness\ncosine.stdev\ncosine.variance\ncosine.cdf( 0.5 )\ncosine.logcdf( 0.5 )\ncosine.logpdf( -1.0 )\ncosine.mgf( 0.2 )\ncosine.pdf( -2.0 )\ncosine.quantile( 0.9 )\n","base.dists.cosine.kurtosis":"var y = base.dists.cosine.kurtosis( 0.0, 1.0 )\ny = base.dists.cosine.kurtosis( 4.0, 2.0 )\ny = base.dists.cosine.kurtosis( NaN, 1.0 )\ny = base.dists.cosine.kurtosis( 0.0, NaN )\ny = base.dists.cosine.kurtosis( 0.0, 0.0 )\n","base.dists.cosine.logcdf":"var y = base.dists.cosine.logcdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.logcdf( 9.0, 10.0, 3.0 )\ny = base.dists.cosine.logcdf( 2.0, 0.0, NaN )\ny = base.dists.cosine.logcdf( 2.0, NaN, 1.0 )\ny = base.dists.cosine.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.logcdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.logcdf( 8.0, 8.0, 0.0 )\ny = base.dists.cosine.logcdf( 10.0, 8.0, 0.0 )\n","base.dists.cosine.logcdf.factory":"var mylogcdf = base.dists.cosine.logcdf.factory( 3.0, 1.5 );\nvar y = mylogcdf( 1.9 )\n","base.dists.cosine.logpdf":"var y = base.dists.cosine.logpdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.logpdf( -1.0, 2.0, 4.0 )\ny = base.dists.cosine.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.cosine.logpdf( 0.0, 0.0, NaN )\ny = base.dists.cosine.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.cosine.logpdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.logpdf( 8.0, 8.0, 0.0 )\n","base.dists.cosine.logpdf.factory":"var mylogpdf = base.dists.cosine.logpdf.factory( 10.0, 2.0 );\nvar y = mylogpdf( 10.0 )\n","base.dists.cosine.mean":"var y = base.dists.cosine.mean( 0.0, 1.0 )\ny = base.dists.cosine.mean( 4.0, 2.0 )\ny = base.dists.cosine.mean( NaN, 1.0 )\ny = base.dists.cosine.mean( 0.0, NaN )\ny = base.dists.cosine.mean( 0.0, 0.0 )\n","base.dists.cosine.median":"var y = base.dists.cosine.median( 0.0, 1.0 )\ny = base.dists.cosine.median( 4.0, 2.0 )\ny = base.dists.cosine.median( NaN, 1.0 )\ny = base.dists.cosine.median( 0.0, NaN )\ny = base.dists.cosine.median( 0.0, 0.0 )\n","base.dists.cosine.mgf":"var y = base.dists.cosine.mgf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.mgf( 9.0, 10.0, 3.0 )\ny = base.dists.cosine.mgf( 0.5, 0.0, NaN )\ny = base.dists.cosine.mgf( 0.5, NaN, 1.0 )\ny = base.dists.cosine.mgf( NaN, 0.0, 1.0 )\n","base.dists.cosine.mgf.factory":"var mymgf = base.dists.cosine.mgf.factory( 3.0, 1.5 );\nvar y = mymgf( 1.9 )\n","base.dists.cosine.mode":"var y = base.dists.cosine.mode( 0.0, 1.0 )\ny = base.dists.cosine.mode( 4.0, 2.0 )\ny = base.dists.cosine.mode( NaN, 1.0 )\ny = base.dists.cosine.mode( 0.0, NaN )\ny = base.dists.cosine.mode( 0.0, 0.0 )\n","base.dists.cosine.pdf":"var y = base.dists.cosine.pdf( 2.0, 0.0, 3.0 )\ny = base.dists.cosine.pdf( 2.4, 4.0, 2.0 )\ny = base.dists.cosine.pdf( NaN, 0.0, 1.0 )\ny = base.dists.cosine.pdf( 0.0, NaN, 1.0 )\ny = base.dists.cosine.pdf( 0.0, 0.0, NaN )\ny = base.dists.cosine.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.cosine.pdf( 2.0, 8.0, 0.0 )\ny = base.dists.cosine.pdf( 8.0, 8.0, 0.0 )\n","base.dists.cosine.pdf.factory":"var myPDF = base.dists.cosine.pdf.factory( 0.0, 3.0 );\nvar y = myPDF( 2.0 )\n","base.dists.cosine.quantile":"var y = base.dists.cosine.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.cosine.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.cosine.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.cosine.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.cosine.quantile( NaN, 0.0, 1.0 )\ny = base.dists.cosine.quantile( 0.0, NaN, 1.0 )\ny = base.dists.cosine.quantile( 0.0, 0.0, NaN )\ny = base.dists.cosine.quantile( 0.5, 0.0, -1.0 )\n","base.dists.cosine.quantile.factory":"var myQuantile = base.dists.cosine.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.3 )\n","base.dists.cosine.skewness":"var y = base.dists.cosine.skewness( 0.0, 1.0 )\ny = base.dists.cosine.skewness( 4.0, 2.0 )\ny = base.dists.cosine.skewness( NaN, 1.0 )\ny = base.dists.cosine.skewness( 0.0, NaN )\ny = base.dists.cosine.skewness( 0.0, 0.0 )\n","base.dists.cosine.stdev":"var y = base.dists.cosine.stdev( 0.0, 1.0 )\ny = base.dists.cosine.stdev( 4.0, 2.0 )\ny = base.dists.cosine.stdev( NaN, 1.0 )\ny = base.dists.cosine.stdev( 0.0, NaN )\ny = base.dists.cosine.stdev( 0.0, 0.0 )\n","base.dists.cosine.variance":"var y = base.dists.cosine.variance( 0.0, 1.0 )\ny = base.dists.cosine.variance( 4.0, 2.0 )\ny = base.dists.cosine.variance( NaN, 1.0 )\ny = base.dists.cosine.variance( 0.0, NaN )\ny = base.dists.cosine.variance( 0.0, 0.0 )\n","base.dists.degenerate.cdf":"var y = base.dists.degenerate.cdf( 2.0, 3.0 )\ny = base.dists.degenerate.cdf( 4.0, 3.0 )\ny = base.dists.degenerate.cdf( 3.0, 3.0 )\ny = base.dists.degenerate.cdf( NaN, 0.0 )\ny = base.dists.degenerate.cdf( 0.0, NaN )\n","base.dists.degenerate.cdf.factory":"var myCDF = base.dists.degenerate.cdf.factory( 5.0 );\nvar y = myCDF( 3.0 )\ny = myCDF( 6.0 )\n","base.dists.degenerate.Degenerate":"var degenerate = base.dists.degenerate.Degenerate( 2.0 );\ndegenerate.mu\ndegenerate.entropy\ndegenerate.mean\ndegenerate.mode\ndegenerate.median\ndegenerate.stdev\ndegenerate.variance\ndegenerate.cdf( 0.5 )\ndegenerate.logcdf( 2.5 )\ndegenerate.logpdf( 0.5 )\ndegenerate.logpmf( 2.5 )\ndegenerate.mgf( 0.2 )\ndegenerate.pdf( 2.0 )\ndegenerate.pmf( 2.0 )\ndegenerate.quantile( 0.7 )\n","base.dists.degenerate.entropy":"var v = base.dists.degenerate.entropy( 20.0 )\nv = base.dists.degenerate.entropy( -10.0 )\n","base.dists.degenerate.logcdf":"var y = base.dists.degenerate.logcdf( 2.0, 3.0 )\ny = base.dists.degenerate.logcdf( 4.0, 3.0 )\ny = base.dists.degenerate.logcdf( 3.0, 3.0 )\ny = base.dists.degenerate.logcdf( NaN, 0.0 )\ny = base.dists.degenerate.logcdf( 0.0, NaN )\n","base.dists.degenerate.logcdf.factory":"var mylogcdf = base.dists.degenerate.logcdf.factory( 5.0 );\nvar y = mylogcdf( 3.0 )\ny = mylogcdf( 6.0 )\n","base.dists.degenerate.logpdf":"var y = base.dists.degenerate.logpdf( 2.0, 3.0 )\ny = base.dists.degenerate.logpdf( 3.0, 3.0 )\ny = base.dists.degenerate.logpdf( NaN, 0.0 )\ny = base.dists.degenerate.logpdf( 0.0, NaN )\n","base.dists.degenerate.logpdf.factory":"var mylogPDF = base.dists.degenerate.logpdf.factory( 10.0 );\nvar y = mylogPDF( 10.0 )\n","base.dists.degenerate.logpmf":"var y = base.dists.degenerate.logpmf( 2.0, 3.0 )\ny = base.dists.degenerate.logpmf( 3.0, 3.0 )\ny = base.dists.degenerate.logpmf( NaN, 0.0 )\ny = base.dists.degenerate.logpmf( 0.0, NaN )\n","base.dists.degenerate.logpmf.factory":"var mylogPMF = base.dists.degenerate.logpmf.factory( 10.0 );\nvar y = mylogPMF( 10.0 )\n","base.dists.degenerate.mean":"var v = base.dists.degenerate.mean( 20.0 )\nv = base.dists.degenerate.mean( -10.0 )\n","base.dists.degenerate.median":"var v = base.dists.degenerate.median( 20.0 )\nv = base.dists.degenerate.median( -10.0 )\n","base.dists.degenerate.mgf":"var y = base.dists.degenerate.mgf( 1.0, 1.0 )\ny = base.dists.degenerate.mgf( 2.0, 3.0 )\ny = base.dists.degenerate.mgf( NaN, 0.0 )\ny = base.dists.degenerate.mgf( 0.0, NaN )\n","base.dists.degenerate.mgf.factory":"var myMGF = base.dists.degenerate.mgf.factory( 10.0 );\nvar y = myMGF( 0.1 )\n","base.dists.degenerate.mode":"var v = base.dists.degenerate.mode( 20.0 )\nv = base.dists.degenerate.mode( -10.0 )\n","base.dists.degenerate.pdf":"var y = base.dists.degenerate.pdf( 2.0, 3.0 )\ny = base.dists.degenerate.pdf( 3.0, 3.0 )\ny = base.dists.degenerate.pdf( NaN, 0.0 )\ny = base.dists.degenerate.pdf( 0.0, NaN )\n","base.dists.degenerate.pdf.factory":"var myPDF = base.dists.degenerate.pdf.factory( 10.0 );\nvar y = myPDF( 10.0 )\n","base.dists.degenerate.pmf":"var y = base.dists.degenerate.pmf( 2.0, 3.0 )\ny = base.dists.degenerate.pmf( 3.0, 3.0 )\ny = base.dists.degenerate.pmf( NaN, 0.0 )\ny = base.dists.degenerate.pmf( 0.0, NaN )\n","base.dists.degenerate.pmf.factory":"var myPMF = base.dists.degenerate.pmf.factory( 10.0 );\nvar y = myPMF( 10.0 )\n","base.dists.degenerate.quantile":"var y = base.dists.degenerate.quantile( 0.5, 2.0 )\ny = base.dists.degenerate.quantile( 0.9, 4.0 )\ny = base.dists.degenerate.quantile( 1.1, 0.0 )\ny = base.dists.degenerate.quantile( -0.2, 0.0 )\ny = base.dists.degenerate.quantile( NaN, 0.0 )\ny = base.dists.degenerate.quantile( 0.0, NaN )\n","base.dists.degenerate.quantile.factory":"var myQuantile = base.dists.degenerate.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 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);\nvar y = myLogPMF( 7.0 )\ny = myLogPMF( 5.0 )\n","base.dists.discreteUniform.mean":"var v = base.dists.discreteUniform.mean( -2, 2 )\nv = base.dists.discreteUniform.mean( 4, 12 )\nv = base.dists.discreteUniform.mean( 2, 8 )\n","base.dists.discreteUniform.median":"var v = base.dists.discreteUniform.median( -2, 2 )\nv = base.dists.discreteUniform.median( 4, 12 )\nv = base.dists.discreteUniform.median( 2, 8 )\n","base.dists.discreteUniform.mgf":"var y = base.dists.discreteUniform.mgf( 2.0, 0, 4 )\ny = base.dists.discreteUniform.mgf( -0.2, 0, 4 )\ny = base.dists.discreteUniform.mgf( 2.0, 0, 1 )\ny = base.dists.discreteUniform.mgf( 0.5, 3, 2 )\ny = base.dists.discreteUniform.mgf( NaN, 0, 1  )\ny = base.dists.discreteUniform.mgf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.mgf( 0.0, 0, NaN )\n","base.dists.discreteUniform.mgf.factory":"var mymgf = base.dists.discreteUniform.mgf.factory( 6, 7 );\nvar y = mymgf( 0.1 )\ny = mymgf( 1.1 )\n","base.dists.discreteUniform.pmf":"var y = base.dists.discreteUniform.pmf( 2.0, 0, 4 )\ny = base.dists.discreteUniform.pmf( 5.0, 0, 4 )\ny = base.dists.discreteUniform.pmf( 3.0, -4, 4 )\ny = base.dists.discreteUniform.pmf( NaN, 0, 1 )\ny = base.dists.discreteUniform.pmf( 0.0, NaN, 1 )\ny = base.dists.discreteUniform.pmf( 0.0, 0, NaN )\ny = base.dists.discreteUniform.pmf( 2.0, 3, 1 )\ny = base.dists.discreteUniform.pmf( 2.0, 1, 2.4 )\n","base.dists.discreteUniform.pmf.factory":"var myPMF = base.dists.discreteUniform.pmf.factory( 6, 7 );\nvar y = myPMF( 7.0 )\ny = myPMF( 5.0 )\n","base.dists.discreteUniform.quantile":"var y = base.dists.discreteUniform.quantile( 0.8, 0, 1 )\ny = base.dists.discreteUniform.quantile( 0.5, 0.0, 10.0 )\ny = base.dists.discreteUniform.quantile( 1.1, 0, 4 )\ny = base.dists.discreteUniform.quantile( -0.2, 0, 4 )\ny = base.dists.discreteUniform.quantile( NaN, -2, 2 )\ny = base.dists.discreteUniform.quantile( 0.1, NaN, 2 )\ny = base.dists.discreteUniform.quantile( 0.1, -2, NaN )\ny = base.dists.discreteUniform.quantile( 0.5, 2, 1 )\n","base.dists.discreteUniform.quantile.factory":"var myQuantile = base.dists.discreteUniform.quantile.factory( 0, 4 );\nvar y = myQuantile( 0.8 )\n","base.dists.discreteUniform.skewness":"var v = base.dists.discreteUniform.skewness( -2, 2 )\nv = base.dists.discreteUniform.skewness( 4, 12 )\nv = base.dists.discreteUniform.skewness( 2, 8 )\n","base.dists.discreteUniform.stdev":"var v = base.dists.discreteUniform.stdev( 0, 1 )\nv = base.dists.discreteUniform.stdev( 4, 12 )\nv = base.dists.discreteUniform.stdev( 2, 8 )\n","base.dists.discreteUniform.variance":"var v = base.dists.discreteUniform.variance( 0, 1 )\nv = base.dists.discreteUniform.variance( 4, 12 )\nv = base.dists.discreteUniform.variance( 2, 8 )\n","base.dists.erlang.cdf":"var y = base.dists.erlang.cdf( 2.0, 1, 1.0 )\ny = base.dists.erlang.cdf( 2.0, 3, 1.0 )\ny = base.dists.erlang.cdf( 2.0, 2.5, 1.0 )\ny = base.dists.erlang.cdf( -1.0, 2, 2.0 )\ny = base.dists.erlang.cdf( PINF, 4, 2.0 )\ny = base.dists.erlang.cdf( NINF, 4, 2.0 )\ny = base.dists.erlang.cdf( NaN, 0, 1.0 )\ny = base.dists.erlang.cdf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.cdf( 0.0, 0, NaN )\ny = base.dists.erlang.cdf( 2.0, -1, 1.0 )\ny = base.dists.erlang.cdf( 2.0, 1, -1.0 )\n","base.dists.erlang.cdf.factory":"var mycdf = base.dists.erlang.cdf.factory( 2, 0.5 );\nvar y = mycdf( 6.0 )\ny = mycdf( 2.0 )\n","base.dists.erlang.entropy":"var v = base.dists.erlang.entropy( 1, 1.0 )\nv = base.dists.erlang.entropy( 4, 12.0 )\nv = base.dists.erlang.entropy( 8, 2.0 )\n","base.dists.erlang.Erlang":"var erlang = base.dists.erlang.Erlang( 6, 5.0 );\nerlang.k\nerlang.lambda\nerlang.entropy\nerlang.kurtosis\nerlang.mean\nerlang.mode\nerlang.skewness\nerlang.stdev\nerlang.variance\nerlang.cdf( 3.0 )\nerlang.logpdf( 3.0 )\nerlang.mgf( -0.5 )\nerlang.pdf( 3.0 )\nerlang.quantile( 0.8 )\n","base.dists.erlang.kurtosis":"var v = base.dists.erlang.kurtosis( 1, 1.0 )\nv = base.dists.erlang.kurtosis( 4, 12.0 )\nv = base.dists.erlang.kurtosis( 8, 2.0 )\n","base.dists.erlang.logpdf":"var y = base.dists.erlang.logpdf( 0.1, 1, 1.0 )\ny = base.dists.erlang.logpdf( 0.5, 2, 2.5 )\ny = base.dists.erlang.logpdf( -1.0, 4, 2.0 )\ny = base.dists.erlang.logpdf( NaN, 1, 1.0 )\ny = base.dists.erlang.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.logpdf( 0.0, 1, NaN )\ny = base.dists.erlang.logpdf( 2.0, -2, 0.5 )\ny = base.dists.erlang.logpdf( 2.0, 0.5, 0.5 )\ny = base.dists.erlang.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.erlang.logpdf( 0.0, 0.0, 2.0 )\ny = base.dists.erlang.logpdf( 2.0, 1, 0.0 )\ny = base.dists.erlang.logpdf( 2.0, 1, -1.0 )\n","base.dists.erlang.logpdf.factory":"var myLogPDF = base.dists.erlang.logpdf.factory( 6.0, 7.0 );\ny = myLogPDF( 7.0 )\n","base.dists.erlang.mean":"var v = base.dists.erlang.mean( 1, 1.0 )\nv = base.dists.erlang.mean( 4, 12.0 )\nv = base.dists.erlang.mean( 8, 2.0 )\n","base.dists.erlang.mgf":"var y = base.dists.erlang.mgf( 0.3, 1, 1.0 )\ny = base.dists.erlang.mgf( 2.0, 2, 3.0 )\ny = base.dists.erlang.mgf( -1.0, 2, 2.0 )\ny = base.dists.erlang.mgf( NaN, 1, 1.0 )\ny = base.dists.erlang.mgf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.mgf( 0.0, 1, NaN )\ny = base.dists.erlang.mgf( 0.2, -2, 0.5 )\ny = base.dists.erlang.mgf( 0.2, 0.5, 0.5 )\ny = base.dists.erlang.mgf( 0.2, 1, 0.0 )\ny = base.dists.erlang.mgf( 0.2, 1, -5.0 )\n","base.dists.erlang.mgf.factory":"var myMGF = base.dists.erlang.mgf.factory( 2, 0.5 );\nvar y = myMGF( 0.2 )\ny = myMGF( -0.5 )\n","base.dists.erlang.mode":"var v = base.dists.erlang.mode( 1, 1.0 )\nv = base.dists.erlang.mode( 4, 12.0 )\nv = base.dists.erlang.mode( 8, 2.0 )\n","base.dists.erlang.pdf":"var y = base.dists.erlang.pdf( 0.1, 1, 1.0 )\ny = base.dists.erlang.pdf( 0.5, 2, 2.5 )\ny = base.dists.erlang.pdf( -1.0, 4, 2.0 )\ny = base.dists.erlang.pdf( NaN, 1, 1.0 )\ny = base.dists.erlang.pdf( 0.0, NaN, 1.0 )\ny = base.dists.erlang.pdf( 0.0, 1, NaN )\ny = base.dists.erlang.pdf( 2.0, -2, 0.5 )\ny = base.dists.erlang.pdf( 2.0, 0.5, 0.5 )\ny = base.dists.erlang.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.erlang.pdf( 0.0, 0.0, 2.0 )\ny = base.dists.erlang.pdf( 2.0, 1, 0.0 )\ny = base.dists.erlang.pdf( 2.0, 1, -1.0 )\n","base.dists.erlang.pdf.factory":"var myPDF = base.dists.erlang.pdf.factory( 6.0, 7.0 );\ny = myPDF( 7.0 )\n","base.dists.erlang.quantile":"var y = base.dists.erlang.quantile( 0.8, 2, 1.0 )\ny = base.dists.erlang.quantile( 0.5, 4, 2.0 )\ny = base.dists.erlang.quantile( 1.1, 1, 1.0 )\ny = base.dists.erlang.quantile( -0.2, 1, 1.0 )\ny = base.dists.erlang.quantile( NaN, 1, 1.0 )\ny = base.dists.erlang.quantile( 0.0, NaN, 1.0 )\ny = base.dists.erlang.quantile( 0.0, 1, NaN )\ny = base.dists.erlang.quantile( 0.5, 0.5, 1.0 )\ny = base.dists.erlang.quantile( 0.5, -1, 1.0 )\ny = base.dists.erlang.quantile( 0.5, 1, -1.0 )\n","base.dists.erlang.quantile.factory":"var myQuantile = base.dists.erlang.quantile.factory( 10, 2.0 );\nvar y = myQuantile( 0.4 )\n","base.dists.erlang.skewness":"var v = base.dists.erlang.skewness( 1, 1.0 )\nv = base.dists.erlang.skewness( 4, 12.0 )\nv = base.dists.erlang.skewness( 8, 2.0 )\n","base.dists.erlang.stdev":"var v = base.dists.erlang.stdev( 1, 1.0 )\nv = base.dists.erlang.stdev( 4, 12.0 )\nv = base.dists.erlang.stdev( 8, 2.0 )\n","base.dists.erlang.variance":"var v = base.dists.erlang.variance( 1, 1.0 )\nv = base.dists.erlang.variance( 4, 12.0 )\nv = base.dists.erlang.variance( 8, 2.0 )\n","base.dists.exponential.cdf":"var y = base.dists.exponential.cdf( 2.0, 0.1 )\ny = base.dists.exponential.cdf( 1.0, 2.0 )\ny = base.dists.exponential.cdf( -1.0, 4.0 )\ny = base.dists.exponential.cdf( NaN, 1.0 )\ny = base.dists.exponential.cdf( 0.0, NaN )\ny = base.dists.exponential.cdf( 2.0, -1.0 )\n","base.dists.exponential.cdf.factory":"var myCDF = base.dists.exponential.cdf.factory( 0.5 );\nvar y = myCDF( 3.0 )\n","base.dists.exponential.entropy":"var v = base.dists.exponential.entropy( 11.0 )\nv = base.dists.exponential.entropy( 4.5 )\n","base.dists.exponential.Exponential":"var exponential = base.dists.exponential.Exponential( 6.0 );\nexponential.lambda\nexponential.entropy\nexponential.kurtosis\nexponential.mean\nexponential.median\nexponential.mode\nexponential.skewness\nexponential.stdev\nexponential.variance\nexponential.cdf( 1.0 )\nexponential.logcdf( 1.0 )\nexponential.logpdf( 1.5 )\nexponential.mgf( -0.5 )\nexponential.pdf( 1.5 )\nexponential.quantile( 0.5 )\n","base.dists.exponential.kurtosis":"var v = base.dists.exponential.kurtosis( 11.0 )\nv = base.dists.exponential.kurtosis( 4.5 )\n","base.dists.exponential.logcdf":"var y = base.dists.exponential.logcdf( 2.0, 0.1 )\ny = base.dists.exponential.logcdf( 1.0, 2.0 )\ny = base.dists.exponential.logcdf( -1.0, 4.0 )\ny = base.dists.exponential.logcdf( NaN, 1.0 )\ny = base.dists.exponential.logcdf( 0.0, NaN )\ny = base.dists.exponential.logcdf( 2.0, -1.0 )\n","base.dists.exponential.logcdf.factory":"var mylogCDF = base.dists.exponential.logcdf.factory( 0.5 );\nvar y = mylogCDF( 3.0 )\n","base.dists.exponential.logpdf":"var y = base.dists.exponential.logpdf( 0.3, 4.0 )\ny = base.dists.exponential.logpdf( 2.0, 0.7 )\ny = base.dists.exponential.logpdf( -1.0, 0.5 )\ny = base.dists.exponential.logpdf( 0, NaN )\ny = base.dists.exponential.logpdf( NaN, 2.0 )\ny = base.dists.exponential.logpdf( 2.0, -1.0 )\n","base.dists.exponential.logpdf.factory":"var mylogpdf = base.dists.exponential.logpdf.factory( 0.5 );\nvar y = mylogpdf( 3.0 )\n","base.dists.exponential.mean":"var v = base.dists.exponential.mean( 11.0 )\nv = base.dists.exponential.mean( 4.5 )\n","base.dists.exponential.median":"var v = base.dists.exponential.median( 11.0 )\nv = base.dists.exponential.median( 4.5 )\n","base.dists.exponential.mgf":"var v = base.dists.exponential.mgf( 2.0, 3.0 )\nv = base.dists.exponential.mgf( 0.4, 1.2 )\nv = base.dists.exponential.mgf( 0.8, 1.6 )\nv = base.dists.exponential.mgf( 4.0, 3.0 )\nv = base.dists.exponential.mgf( NaN, 3.0 )\nv = base.dists.exponential.mgf( 2.0, NaN )\n","base.dists.exponential.mgf.factory":"var myMGF = base.dists.exponential.mgf.factory( 4.0 );\nvar y = myMGF( 3.0 )\ny = myMGF( 0.5 )\n","base.dists.exponential.mode":"var v = base.dists.exponential.mode( 11.0 )\nv = base.dists.exponential.mode( 4.5 )\n","base.dists.exponential.pdf":"var y = base.dists.exponential.pdf( 0.3, 4.0 )\ny = base.dists.exponential.pdf( 2.0, 0.7 )\ny = base.dists.exponential.pdf( -1.0, 0.5 )\ny = base.dists.exponential.pdf( 0, NaN )\ny = base.dists.exponential.pdf( NaN, 2.0 )\ny = base.dists.exponential.pdf( 2.0, -1.0 )\n","base.dists.exponential.pdf.factory":"var myPDF = base.dists.exponential.pdf.factory( 0.5 );\nvar y = myPDF( 3.0 )\n","base.dists.exponential.quantile":"var y = base.dists.exponential.quantile( 0.8, 1.0 )\ny = base.dists.exponential.quantile( 0.5, 4.0 )\ny = base.dists.exponential.quantile( 0.5, 0.1 )\ny = base.dists.exponential.quantile( -0.2, 0.1 )\ny = base.dists.exponential.quantile( NaN, 1.0 )\ny = base.dists.exponential.quantile( 0.0, NaN )\ny = base.dists.exponential.quantile( 0.5, -1.0 )\n","base.dists.exponential.quantile.factory":"var myQuantile = base.dists.exponential.quantile.factory( 0.4 );\nvar y = myQuantile( 0.4 )\ny = myQuantile( 1.0 )\n","base.dists.exponential.skewness":"var v = base.dists.exponential.skewness( 11.0 )\nv = base.dists.exponential.skewness( 4.5 )\n","base.dists.exponential.stdev":"var v = base.dists.exponential.stdev( 9.0 )\nv = base.dists.exponential.stdev( 1.0 )\n","base.dists.exponential.variance":"var v = base.dists.exponential.variance( 9.0 )\nv = base.dists.exponential.variance( 1.0 )\n","base.dists.f.cdf":"var y = base.dists.f.cdf( 2.0, 1.0, 1.0 )\nvar y = base.dists.f.cdf( 2.0, 8.0, 4.0 )\nvar y = base.dists.f.cdf( -1.0, 2.0, 2.0 )\nvar y = base.dists.f.cdf( PINF, 4.0, 2.0 )\nvar y = base.dists.f.cdf( NINF, 4.0, 2.0 )\nvar y = base.dists.f.cdf( NaN, 1.0, 1.0 )\nvar y = base.dists.f.cdf( 0.0, NaN, 1.0 )\nvar y = base.dists.f.cdf( 0.0, 1.0, NaN )\nvar y = base.dists.f.cdf( 2.0, 1.0, -1.0 )\nvar y = base.dists.f.cdf( 2.0, -1.0, 1.0 )\n","base.dists.f.cdf.factory":"var myCDF = base.dists.f.cdf.factory( 10.0, 2.0 );\nvar y = myCDF( 10.0 )\ny = myCDF( 8.0 )\n","base.dists.f.entropy":"var v = base.dists.f.entropy( 3.0, 7.0 )\nv = base.dists.f.entropy( 4.0, 12.0 )\nv = base.dists.f.entropy( 8.0, 2.0 )\n","base.dists.f.F":"var f = base.dists.f.F( 6.0, 9.0 );\nf.d1\nf.d2\nf.entropy\nf.kurtosis\nf.mean\nf.mode\nf.skewness\nf.stdev\nf.variance\nf.cdf( 3.0 )\nf.pdf( 2.5 )\nf.quantile( 0.8 )\n","base.dists.f.kurtosis":"var v = base.dists.f.kurtosis( 3.0, 9.0 )\nv = base.dists.f.kurtosis( 4.0, 12.0 )\nv = base.dists.f.kurtosis( 8.0, 9.0 )\n","base.dists.f.mean":"var v = base.dists.f.mean( 3.0, 5.0 )\nv = base.dists.f.mean( 4.0, 12.0 )\nv = base.dists.f.mean( 8.0, 4.0 )\n","base.dists.f.mode":"var v = base.dists.f.mode( 3.0, 5.0 )\nv = base.dists.f.mode( 4.0, 12.0 )\nv = base.dists.f.mode( 8.0, 4.0 )\n","base.dists.f.pdf":"var y = base.dists.f.pdf( 2.0, 0.5, 1.0 )\ny = base.dists.f.pdf( 0.1, 1.0, 1.0 )\ny = base.dists.f.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.f.pdf( NaN, 1.0, 1.0 )\ny = base.dists.f.pdf( 0.0, NaN, 1.0 )\ny = base.dists.f.pdf( 0.0, 1.0, NaN )\ny = base.dists.f.pdf( 2.0, 1.0, -1.0 )\ny = base.dists.f.pdf( 2.0, -1.0, 1.0 )\n","base.dists.f.pdf.factory":"var myPDF = base.dists.f.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 7.0 )\ny = myPDF( 2.0 )\n","base.dists.f.quantile":"var y = base.dists.f.quantile( 0.8, 1.0, 1.0 )\ny = base.dists.f.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.f.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.f.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.f.quantile( NaN, 1.0, 1.0 )\ny = base.dists.f.quantile( 0.5, NaN, 1.0 )\ny = base.dists.f.quantile( 0.5, 1.0, NaN )\ny = base.dists.f.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.f.quantile( 0.5, 1.0, -1.0 )\n","base.dists.f.quantile.factory":"var myQuantile = base.dists.f.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.2 )\ny = myQuantile( 0.8 )\n","base.dists.f.skewness":"var v = base.dists.f.skewness( 3.0, 7.0 )\nv = base.dists.f.skewness( 4.0, 12.0 )\nv = base.dists.f.skewness( 8.0, 7.0 )\n","base.dists.f.stdev":"var v = base.dists.f.stdev( 3.0, 5.0 )\nv = base.dists.f.stdev( 4.0, 12.0 )\nv = base.dists.f.stdev( 8.0, 5.0 )\n","base.dists.f.variance":"var v = base.dists.f.variance( 3.0, 5.0 )\nv = base.dists.f.variance( 4.0, 12.0 )\nv = base.dists.f.variance( 8.0, 5.0 )\n","base.dists.frechet.cdf":"var y = base.dists.frechet.cdf( 10.0, 2.0, 3.0, 0.0 )\ny = base.dists.frechet.cdf( -1.0, 2.0, 3.0, -3.0 )\ny = base.dists.frechet.cdf( 2.5, 2.0, 1.0, 2.0 )\ny = base.dists.frechet.cdf( NaN, 1.0, 1.0, 0.0 )\ny = base.dists.frechet.cdf( 0.0, NaN, 1.0, 0.0 )\ny = base.dists.frechet.cdf( 0.0, 1.0, NaN, 0.0 )\ny = base.dists.frechet.cdf( 0.0, 1.0, 1.0, NaN )\ny = base.dists.frechet.cdf( 0.0, -1.0, 1.0, 0.0 )\ny = base.dists.frechet.cdf( 0.0, 1.0, -1.0, 0.0 )\n","base.dists.frechet.cdf.factory":"var myCDF = base.dists.frechet.cdf.factory( 3.0, 3.0, 5.0 );\nvar y = myCDF( 10.0 )\ny = myCDF( 7.0 )\n","base.dists.frechet.entropy":"var y = base.dists.frechet.entropy( 1.0, 1.0, 1.0 )\ny = base.dists.frechet.entropy( 4.0, 2.0, 1.0 )\ny = base.dists.frechet.entropy( NaN, 1.0, 0.0 )\ny = base.dists.frechet.entropy( 1.0, NaN, 0.0 )\ny = base.dists.frechet.entropy( 1.0, 1.0, NaN )\n","base.dists.frechet.Frechet":"var frechet = base.dists.frechet.Frechet( 1.0, 1.0, 0.0 );\nfrechet.alpha\nfrechet.s\nfrechet.m\nfrechet.entropy\nfrechet.kurtosis\nfrechet.mean\nfrechet.median\nfrechet.mode\nfrechet.skewness\nfrechet.stdev\nfrechet.variance\nfrechet.cdf( 0.8 )\nfrechet.logcdf( 0.8 )\nfrechet.logpdf( 0.8 )\nfrechet.pdf( 0.8 )\nfrechet.quantile( 0.8 )\n","base.dists.frechet.kurtosis":"var y = base.dists.frechet.kurtosis( 5.0, 2.0, 1.0 )\nvar y = base.dists.frechet.kurtosis( 5.0, 10.0, -3.0 )\ny = base.dists.frechet.kurtosis( 3.5, 2.0, 1.0 )\ny = base.dists.frechet.kurtosis( NaN, 1.0, 0.0 )\ny = base.dists.frechet.kurtosis( 1.0, NaN, 0.0 )\ny = base.dists.frechet.kurtosis( 1.0, 1.0, NaN )\n","base.dists.frechet.logcdf":"var y = base.dists.frechet.logcdf( 10.0, 2.0, 3.0, 0.0 )\ny = base.dists.frechet.logcdf( -1.0, 2.0, 3.0, -3.0 )\ny = base.dists.frechet.logcdf( 2.5, 2.0, 1.0, 2.0 )\ny = base.dists.frechet.logcdf( NaN, 1.0, 1.0, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, NaN, 1.0, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, 1.0, NaN, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, 1.0, 1.0, NaN )\ny = base.dists.frechet.logcdf( 0.0, -1.0, 1.0, 0.0 )\ny = base.dists.frechet.logcdf( 0.0, 1.0, -1.0, 0.0 )\n","base.dists.frechet.logcdf.factory":"var mylogcdf = base.dists.frechet.logcdf.factory( 3.0, 3.0, 5.0 );\nvar y = mylogcdf( 10.0 )\ny = mylogcdf( 7.0 )\n","base.dists.frechet.logpdf":"var y = base.dists.frechet.logpdf( 10.0, 1.0, 3.0, 5.0 )\ny = base.dists.frechet.logpdf( -2.0, 1.0, 3.0, -3.0 )\ny = base.dists.frechet.logpdf( 0.0, 2.0, 1.0, -1.0 )\ny = base.dists.frechet.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.frechet.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.frechet.logpdf( 0.0, 0.0, NaN )\ny = base.dists.frechet.logpdf( 0.0, 0.0, -1.0 )\n","base.dists.frechet.logpdf.factory":"var mylogPDF = base.dists.frechet.logpdf.factory( 2.0, 3.0, 1.0 );\nvar y = mylogPDF( 10.0 )\ny = mylogPDF( 2.0 )\n","base.dists.frechet.mean":"var y = base.dists.frechet.mean( 4.0, 2.0, 1.0 )\ny = base.dists.frechet.mean( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.mean( NaN, 1.0, 0.0 )\ny = base.dists.frechet.mean( 1.0, NaN, 0.0 )\ny = base.dists.frechet.mean( 1.0, 1.0, NaN )\n","base.dists.frechet.median":"var y = base.dists.frechet.median( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.median( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.median( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.median( NaN, 1.0, 0.0 )\ny = base.dists.frechet.median( 1.0, NaN, 0.0 )\ny = base.dists.frechet.median( 1.0, 1.0, NaN )\n","base.dists.frechet.mode":"var y = base.dists.frechet.mode( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.mode( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.mode( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.mode( NaN, 1.0, 0.0 )\ny = base.dists.frechet.mode( 1.0, NaN, 0.0 )\ny = base.dists.frechet.mode( 1.0, 1.0, NaN )\n","base.dists.frechet.pdf":"var y = base.dists.frechet.pdf( 10.0, 0.0, 3.0 )\ny = base.dists.frechet.pdf( -2.0, 0.0, 3.0 )\ny = base.dists.frechet.pdf( 0.0, 0.0, 1.0 )\ny = base.dists.frechet.pdf( NaN, 0.0, 1.0 )\ny = base.dists.frechet.pdf( 0.0, NaN, 1.0 )\ny = base.dists.frechet.pdf( 0.0, 0.0, NaN )\ny = base.dists.frechet.pdf( 0.0, 0.0, -1.0 )\n","base.dists.frechet.pdf.factory":"var myPDF = base.dists.frechet.pdf.factory( 2.0, 3.0 );\nvar y = myPDF( 10.0 )\ny = myPDF( 2.0 )\n","base.dists.frechet.quantile":"var y = base.dists.frechet.quantile( 0.3, 10.0, 2.0, 3.0 )\ny = base.dists.frechet.quantile( 0.2, 3.0, 3.0, 3.0 )\ny = base.dists.frechet.quantile( 0.9, 1.0, 1.0, -3.0 )\ny = base.dists.frechet.quantile( NaN, 1.0, 1.0, 0.0 )\ny = base.dists.frechet.quantile( 0.0, NaN, 1.0, 0.0)\ny = base.dists.frechet.quantile( 0.0, 1.0, NaN, 0.0 )\ny = base.dists.frechet.quantile( 0.0, 1.0, 1.0, NaN )\ny = base.dists.frechet.quantile( 0.0, -1.0, 1.0, 0.0 )\ny = base.dists.frechet.quantile( 0.0, 1.0, -1.0, 0.0 )\n","base.dists.frechet.quantile.factory":"var myQuantile = base.dists.frechet.quantile.factory( 2.0, 2.0, 3.0 );\nvar y = myQuantile( 0.5 )\ny = myQuantile( 0.2 )\n","base.dists.frechet.skewness":"var y = base.dists.frechet.skewness( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.skewness( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.skewness( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.skewness( NaN, 1.0, 0.0 )\ny = base.dists.frechet.skewness( 1.0, NaN, 0.0 )\ny = base.dists.frechet.skewness( 1.0, 1.0, NaN )\n","base.dists.frechet.stdev":"var y = base.dists.frechet.stdev( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.stdev( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.stdev( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.stdev( NaN, 1.0, 0.0 )\ny = base.dists.frechet.stdev( 1.0, NaN, 0.0 )\ny = base.dists.frechet.stdev( 1.0, 1.0, NaN )\n","base.dists.frechet.variance":"var y = base.dists.frechet.variance( 4.0, 2.0, 1.0 )\nvar y = base.dists.frechet.variance( 4.0, 2.0, -3.0 )\ny = base.dists.frechet.variance( 0.5, 2.0, 1.0 )\ny = base.dists.frechet.variance( NaN, 1.0, 0.0 )\ny = base.dists.frechet.variance( 1.0, NaN, 0.0 )\ny = base.dists.frechet.variance( 1.0, 1.0, NaN )\n","base.dists.gamma.cdf":"var y = base.dists.gamma.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.gamma.cdf( 2.0, 3.0, 1.0 )\ny = base.dists.gamma.cdf( -1.0, 2.0, 2.0 )\ny = base.dists.gamma.cdf( PINF, 4.0, 2.0 )\ny = base.dists.gamma.cdf( NINF, 4.0, 2.0 )\ny = base.dists.gamma.cdf( NaN, 0.0, 1.0 )\ny = base.dists.gamma.cdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.cdf( 0.0, 0.0, NaN )\ny = base.dists.gamma.cdf( 2.0, -1.0, 1.0 )\ny = base.dists.gamma.cdf( 2.0, 1.0, -1.0 )\ny = base.dists.gamma.cdf( 2.0, 0.0, 2.0 )\ny = base.dists.gamma.cdf( -2.0, 0.0, 2.0 )\ny = base.dists.gamma.cdf( 0.0, 0.0, 2.0 )\n","base.dists.gamma.cdf.factory":"var myCDF = base.dists.gamma.cdf.factory( 2.0, 0.5 );\nvar y = myCDF( 6.0 )\ny = myCDF( 2.0 )\n","base.dists.gamma.entropy":"var v = base.dists.gamma.entropy( 1.0, 1.0 )\nv = base.dists.gamma.entropy( 4.0, 12.0 )\nv = base.dists.gamma.entropy( 8.0, 2.0 )\n","base.dists.gamma.Gamma":"var gamma = base.dists.gamma.Gamma( 6.0, 5.0 );\ngamma.alpha\ngamma.beta\ngamma.entropy\ngamma.kurtosis\ngamma.mean\ngamma.mode\ngamma.skewness\ngamma.stdev\ngamma.variance\ngamma.cdf( 0.8 )\ngamma.logcdf( 0.8 )\ngamma.logpdf( 1.0 )\ngamma.mgf( -0.5 )\ngamma.pdf( 1.0 )\ngamma.quantile( 0.8 )\n","base.dists.gamma.kurtosis":"var v = base.dists.gamma.kurtosis( 1.0, 1.0 )\nv = base.dists.gamma.kurtosis( 4.0, 12.0 )\nv = base.dists.gamma.kurtosis( 8.0, 2.0 )\n","base.dists.gamma.logcdf":"var y = base.dists.gamma.logcdf( 2.0, 0.5, 1.0 )\ny = base.dists.gamma.logcdf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.logcdf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.logcdf( NaN, 0.6, 1.0 )\ny = base.dists.gamma.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.logcdf( 0.0, 1.0, NaN )\ny = base.dists.gamma.logcdf( 2.0, -1.0, 1.0 )\ny = base.dists.gamma.logcdf( 2.0, 1.0, -1.0 )\n","base.dists.gamma.logcdf.factory":"var mylogCDF = base.dists.gamma.logcdf.factory( 6.0, 7.0 );\nvar y = mylogCDF( 2.0 )\n","base.dists.gamma.logpdf":"var y = base.dists.gamma.logpdf( 2.0, 0.5, 1.0 )\ny = base.dists.gamma.logpdf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.logpdf( NaN, 0.6, 1.0 )\ny = base.dists.gamma.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.logpdf( 0.0, 1.0, NaN )\ny = base.dists.gamma.logpdf( 2.0, -1.0, 1.0 )\ny = base.dists.gamma.logpdf( 2.0, 1.0, -1.0 )\ny = base.dists.gamma.logpdf( 2.0, 0.0, 2.0 )\ny = base.dists.gamma.logpdf( 0.0, 0.0, 2.0 )\n","base.dists.gamma.logpdf.factory":"var mylogPDF = base.dists.gamma.logpdf.factory( 6.0, 7.0 );\nvar y = mylogPDF( 2.0 )\n","base.dists.gamma.mean":"var v = base.dists.gamma.mean( 1.0, 1.0 )\nv = base.dists.gamma.mean( 4.0, 12.0 )\nv = base.dists.gamma.mean( 8.0, 2.0 )\n","base.dists.gamma.mgf":"var y = base.dists.gamma.mgf( 0.5, 0.5, 1.0 )\ny = base.dists.gamma.mgf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.mgf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.mgf( NaN, 1.0, 1.0 )\ny = base.dists.gamma.mgf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.mgf( 0.0, 1.0, NaN )\ny = base.dists.gamma.mgf( 2.0, 4.0, 1.0 )\ny = base.dists.gamma.mgf( 2.0, -0.5, 1.0 )\ny = base.dists.gamma.mgf( 2.0, 1.0, 0.0 )\ny = base.dists.gamma.mgf( 2.0, 1.0, -1.0 )\n","base.dists.gamma.mgf.factory":"var myMGF = base.dists.gamma.mgf.factory( 3.0, 1.5 );\nvar y = myMGF( 1.0 )\ny = myMGF( 0.5 )\n","base.dists.gamma.mode":"var v = base.dists.gamma.mode( 1.0, 1.0 )\nv = base.dists.gamma.mode( 4.0, 12.0 )\nv = base.dists.gamma.mode( 8.0, 2.0 )\n","base.dists.gamma.pdf":"var y = base.dists.gamma.pdf( 2.0, 0.5, 1.0 )\ny = base.dists.gamma.pdf( 0.1, 1.0, 1.0 )\ny = base.dists.gamma.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.gamma.pdf( NaN, 0.6, 1.0 )\ny = base.dists.gamma.pdf( 0.0, NaN, 1.0 )\ny = base.dists.gamma.pdf( 0.0, 1.0, NaN )\ny = base.dists.gamma.pdf( 2.0, -1.0, 1.0 )\ny = base.dists.gamma.pdf( 2.0, 1.0, -1.0 )\ny = base.dists.gamma.pdf( 2.0, 0.0, 2.0 )\ny = base.dists.gamma.pdf( 0.0, 0.0, 2.0 )\n","base.dists.gamma.pdf.factory":"var myPDF = base.dists.gamma.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 2.0 )\n","base.dists.gamma.quantile":"var y = base.dists.gamma.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.gamma.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.gamma.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.gamma.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.gamma.quantile( NaN, 1.0, 1.0 )\ny = base.dists.gamma.quantile( 0.0, NaN, 1.0 )\ny = base.dists.gamma.quantile( 0.0, 1.0, NaN )\ny = base.dists.gamma.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.gamma.quantile( 0.5, 1.0, -1.0 )\ny = base.dists.gamma.quantile( 0.3, 0.0, 2.0 )\ny = base.dists.gamma.quantile( 0.9, 0.0, 2.0 )\n","base.dists.gamma.quantile.factory":"var myQuantile = base.dists.gamma.quantile.factory( 2.0, 2.0 );\nvar y = myQuantile( 0.8 )\ny = myQuantile( 0.4 )\n","base.dists.gamma.skewness":"var v = base.dists.gamma.skewness( 1.0, 1.0 )\nv = base.dists.gamma.skewness( 4.0, 12.0 )\nv = base.dists.gamma.skewness( 8.0, 2.0 )\n","base.dists.gamma.stdev":"var v = base.dists.gamma.stdev( 1.0, 1.0 )\nv = base.dists.gamma.stdev( 4.0, 12.0 )\nv = base.dists.gamma.stdev( 8.0, 2.0 )\n","base.dists.gamma.variance":"var v = base.dists.gamma.variance( 1.0, 1.0 )\nv = base.dists.gamma.variance( 4.0, 12.0 )\nv = base.dists.gamma.variance( 8.0, 2.0 )\n","base.dists.geometric.cdf":"var y = base.dists.geometric.cdf( 2.0, 0.5 )\ny = base.dists.geometric.cdf( 2.0, 0.1 )\ny = base.dists.geometric.cdf( -1.0, 4.0 )\ny = base.dists.geometric.cdf( NaN, 0.5 )\ny = base.dists.geometric.cdf( 0.0, NaN )\ny = base.dists.geometric.cdf( 2.0, 1.4 )\n","base.dists.geometric.cdf.factory":"var mycdf = base.dists.geometric.cdf.factory( 0.5 );\nvar y = mycdf( 3.0 )\ny = mycdf( 1.0 )\n","base.dists.geometric.entropy":"var v = base.dists.geometric.entropy( 0.1 )\nv = base.dists.geometric.entropy( 0.5 )\n","base.dists.geometric.Geometric":"var geometric = base.dists.geometric.Geometric( 0.6 );\ngeometric.p\ngeometric.entropy\ngeometric.kurtosis\ngeometric.mean\ngeometric.median\ngeometric.mode\ngeometric.skewness\ngeometric.stdev\ngeometric.variance\ngeometric.cdf( 3.0 )\ngeometric.logcdf( 3.0 )\ngeometric.logpmf( 4.0 )\ngeometric.mgf( 0.5 )\ngeometric.pmf( 2.0 )\ngeometric.quantile( 0.7 )\n","base.dists.geometric.kurtosis":"var v = base.dists.geometric.kurtosis( 0.1 )\nv = base.dists.geometric.kurtosis( 0.5 )\n","base.dists.geometric.logcdf":"var y = base.dists.geometric.logcdf( 2.0, 0.5 )\ny = base.dists.geometric.logcdf( 2.0, 0.1 )\ny = base.dists.geometric.logcdf( -1.0, 4.0 )\ny = base.dists.geometric.logcdf( NaN, 0.5 )\ny = base.dists.geometric.logcdf( 0.0, NaN )\ny = base.dists.geometric.logcdf( 2.0, 1.4 )\n","base.dists.geometric.logcdf.factory":"var mylogcdf = base.dists.geometric.logcdf.factory( 0.5 );\nvar y = mylogcdf( 3.0 )\ny = mylogcdf( 1.0 )\n","base.dists.geometric.logpmf":"var y = base.dists.geometric.logpmf( 4.0, 0.3 )\ny = base.dists.geometric.logpmf( 2.0, 0.7 )\ny = base.dists.geometric.logpmf( -1.0, 0.5 )\ny = base.dists.geometric.logpmf( 0.0, NaN )\ny = base.dists.geometric.logpmf( NaN, 0.5 )\ny = base.dists.geometric.logpmf( 2.0, 1.5 )\n","base.dists.geometric.logpmf.factory":"var mylogpmf = base.dists.geometric.logpmf.factory( 0.5 );\nvar y = mylogpmf( 3.0 )\ny = mylogpmf( 1.0 )\n","base.dists.geometric.mean":"var v = base.dists.geometric.mean( 0.1 )\nv = base.dists.geometric.mean( 0.5 )\n","base.dists.geometric.median":"var v = base.dists.geometric.median( 0.1 )\nv = base.dists.geometric.median( 0.5 )\n","base.dists.geometric.mgf":"var y = base.dists.geometric.mgf( 0.2, 0.5 )\ny = base.dists.geometric.mgf( 0.4, 0.5 )\ny = base.dists.geometric.mgf( 0.8, 0.5 )\ny = base.dists.geometric.mgf( NaN, 0.0 )\ny = base.dists.geometric.mgf( 0.0, NaN )\ny = base.dists.geometric.mgf( -2.0, -1.0 )\ny = base.dists.geometric.mgf( 0.2, 2.0 )\n","base.dists.geometric.mgf.factory":"var mymgf = base.dists.geometric.mgf.factory( 0.8 );\nvar y = mymgf( -0.2 )\n","base.dists.geometric.mode":"var v = base.dists.geometric.mode( 0.1 )\nv = base.dists.geometric.mode( 0.5 )\n","base.dists.geometric.pmf":"var y = base.dists.geometric.pmf( 4.0, 0.3 )\ny = base.dists.geometric.pmf( 2.0, 0.7 )\ny = base.dists.geometric.pmf( -1.0, 0.5 )\ny = base.dists.geometric.pmf( 0.0, NaN )\ny = base.dists.geometric.pmf( NaN, 0.5 )\ny = base.dists.geometric.pmf( 2.0, 1.5 )\n","base.dists.geometric.pmf.factory":"var mypmf = base.dists.geometric.pmf.factory( 0.5 );\nvar y = mypmf( 3.0 )\ny = mypmf( 1.0 )\n","base.dists.geometric.quantile":"var y = base.dists.geometric.quantile( 0.8, 0.4 )\ny = base.dists.geometric.quantile( 0.5, 0.4 )\ny = base.dists.geometric.quantile( 0.9, 0.1 )\ny = base.dists.geometric.quantile( -0.2, 0.1 )\ny = base.dists.geometric.quantile( NaN, 0.8 )\ny = base.dists.geometric.quantile( 0.4, NaN )\ny = base.dists.geometric.quantile( 0.5, -1.0 )\ny = base.dists.geometric.quantile( 0.5, 1.5 )\n","base.dists.geometric.quantile.factory":"var myquantile = base.dists.geometric.quantile.factory( 0.4 );\nvar y = myquantile( 0.4 )\ny = myquantile( 0.8 )\ny = myquantile( 1.0 )\n","base.dists.geometric.skewness":"var v = base.dists.geometric.skewness( 0.1 )\nv = base.dists.geometric.skewness( 0.5 )\n","base.dists.geometric.stdev":"var v = base.dists.geometric.stdev( 0.1 )\nv = base.dists.geometric.stdev( 0.5 )\n","base.dists.geometric.variance":"var v = base.dists.geometric.variance( 0.1 )\nv = base.dists.geometric.variance( 0.5 )\n","base.dists.gumbel.cdf":"var y = base.dists.gumbel.cdf( 10.0, 0.0, 3.0 )\ny = base.dists.gumbel.cdf( -2.0, 0.0, 3.0 )\ny = base.dists.gumbel.cdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.cdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.cdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.cdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.cdf( 0.0, 0.0, -1.0 )\n","base.dists.gumbel.cdf.factory":"var myCDF = base.dists.gumbel.cdf.factory( 2.0, 3.0 );\nvar y = myCDF( 10.0 )\ny = myCDF( 2.0 )\n","base.dists.gumbel.entropy":"var y = base.dists.gumbel.entropy( 0.0, 1.0 )\ny = base.dists.gumbel.entropy( 4.0, 2.0 )\ny = base.dists.gumbel.entropy( NaN, 1.0 )\ny = base.dists.gumbel.entropy( 0.0, NaN )\ny = base.dists.gumbel.entropy( 0.0, 0.0 )\n","base.dists.gumbel.Gumbel":"var gumbel = base.dists.gumbel.Gumbel( -2.0, 3.0 );\ngumbel.mu\ngumbel.beta\ngumbel.entropy\ngumbel.kurtosis\ngumbel.mean\ngumbel.median\ngumbel.mode\ngumbel.skewness\ngumbel.stdev\ngumbel.variance\ngumbel.cdf( 0.8 )\ngumbel.logcdf( 0.8 )\ngumbel.logpdf( 1.0 )\ngumbel.mgf( 0.2 )\ngumbel.pdf( 1.0 )\ngumbel.quantile( 0.8 )\n","base.dists.gumbel.kurtosis":"var y = base.dists.gumbel.kurtosis( 0.0, 1.0 )\ny = base.dists.gumbel.kurtosis( 4.0, 2.0 )\ny = base.dists.gumbel.kurtosis( NaN, 1.0 )\ny = base.dists.gumbel.kurtosis( 0.0, NaN )\ny = base.dists.gumbel.kurtosis( 0.0, 0.0 )\n","base.dists.gumbel.logcdf":"var y = base.dists.gumbel.logcdf( 10.0, 0.0, 3.0 )\ny = base.dists.gumbel.logcdf( -2.0, 0.0, 3.0 )\ny = base.dists.gumbel.logcdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.logcdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.logcdf( 0.0, 0.0, -1.0 )\n","base.dists.gumbel.logcdf.factory":"var myLCDF = base.dists.gumbel.logcdf.factory( 2.0, 3.0 );\nvar y = myLCDF( 10.0 )\ny = myLCDF( 2.0 )\n","base.dists.gumbel.logpdf":"var y = base.dists.gumbel.logpdf( 0.0, 0.0, 2.0 )\ny = base.dists.gumbel.logpdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.logpdf( 1.0, 3.0, 2.0 )\ny = base.dists.gumbel.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.logpdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.logpdf( 2.0, 0.0, -1.0 )\n","base.dists.gumbel.logpdf.factory":"var mylogpdf = base.dists.gumbel.logpdf.factory( 10.0, 2.0 );\nvar y = mylogpdf( 10.0 )\ny = mylogpdf( 12.0 )\n","base.dists.gumbel.mean":"var y = base.dists.gumbel.mean( 0.0, 1.0 )\ny = base.dists.gumbel.mean( 4.0, 2.0 )\ny = base.dists.gumbel.mean( NaN, 1.0 )\ny = base.dists.gumbel.mean( 0.0, NaN )\ny = base.dists.gumbel.mean( 0.0, 0.0 )\n","base.dists.gumbel.median":"var y = base.dists.gumbel.median( 0.0, 1.0 )\ny = base.dists.gumbel.median( 4.0, 2.0 )\ny = base.dists.gumbel.median( NaN, 1.0 )\ny = base.dists.gumbel.median( 0.0, NaN )\ny = base.dists.gumbel.median( 0.0, 0.0 )\n","base.dists.gumbel.mgf":"var y = base.dists.gumbel.mgf( -1.0, 0.0, 3.0 )\ny = base.dists.gumbel.mgf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.mgf( 0.1, 0.0, 3.0 )\ny = base.dists.gumbel.mgf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.mgf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.mgf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.mgf( 0.8, 0.0, 2.0 )\ny = base.dists.gumbel.mgf( 0.0, 0.0, -1.0 )\n","base.dists.gumbel.mgf.factory":"var myMGF = base.dists.gumbel.mgf.factory( 0.0, 3.0 );\nvar y = myMGF( -1.5 )\ny = myMGF( -1.0 )\n","base.dists.gumbel.mode":"var y = base.dists.gumbel.mode( 0.0, 1.0 )\ny = base.dists.gumbel.mode( 4.0, 2.0 )\ny = base.dists.gumbel.mode( NaN, 1.0 )\ny = base.dists.gumbel.mode( 0.0, NaN )\ny = base.dists.gumbel.mode( 0.0, 0.0 )\n","base.dists.gumbel.pdf":"var y = base.dists.gumbel.pdf( 0.0, 0.0, 2.0 )\ny = base.dists.gumbel.pdf( 0.0, 0.0, 1.0 )\ny = base.dists.gumbel.pdf( 1.0, 3.0, 2.0 )\ny = base.dists.gumbel.pdf( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.pdf( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.pdf( 0.0, 0.0, NaN )\ny = base.dists.gumbel.pdf( 2.0, 0.0, -1.0 )\n","base.dists.gumbel.pdf.factory":"var myPDF = base.dists.gumbel.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\ny = myPDF( 12.0 )\n","base.dists.gumbel.quantile":"var y = base.dists.gumbel.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.gumbel.quantile( 0.5, 4.0, 4.0 )\ny = base.dists.gumbel.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( NaN, 0.0, 1.0 )\ny = base.dists.gumbel.quantile( 0.0, NaN, 1.0 )\ny = base.dists.gumbel.quantile( 0.0, 0.0, NaN )\ny = base.dists.gumbel.quantile( 0.5, 0.0, -1.0 )\n","base.dists.gumbel.quantile.factory":"var myQuantile = base.dists.gumbel.quantile.factory( 8.0, 2.0 );\nvar y = myQuantile( 0.5 )\ny = myQuantile( 0.7 )\n","base.dists.gumbel.skewness":"var y = base.dists.gumbel.skewness( 0.0, 1.0 )\ny = base.dists.gumbel.skewness( 4.0, 2.0 )\ny = base.dists.gumbel.skewness( NaN, 1.0 )\ny = base.dists.gumbel.skewness( 0.0, NaN )\ny = base.dists.gumbel.skewness( 0.0, 0.0 )\n","base.dists.gumbel.stdev":"var y = base.dists.gumbel.stdev( 0.0, 1.0 )\ny = base.dists.gumbel.stdev( 4.0, 2.0 )\ny = base.dists.gumbel.stdev( NaN, 1.0 )\ny = base.dists.gumbel.stdev( 0.0, NaN )\ny = base.dists.gumbel.stdev( 0.0, 0.0 )\n","base.dists.gumbel.variance":"var y = base.dists.gumbel.variance( 0.0, 1.0 )\ny = base.dists.gumbel.variance( 4.0, 2.0 )\ny = base.dists.gumbel.variance( NaN, 1.0 )\ny = base.dists.gumbel.variance( 0.0, NaN )\ny = base.dists.gumbel.variance( 0.0, 0.0 )\n","base.dists.hypergeometric.cdf":"var y = base.dists.hypergeometric.cdf( 1.0, 8, 4, 2 )\ny = base.dists.hypergeometric.cdf( 1.5, 8, 4, 2 )\ny = base.dists.hypergeometric.cdf( 2.0, 8, 4, 2 )\ny = base.dists.hypergeometric.cdf( 0, 8, 4, 2)\ny = base.dists.hypergeometric.cdf( NaN, 10, 5, 2 )\ny = base.dists.hypergeometric.cdf( 0.0, NaN, 5, 2 )\ny = base.dists.hypergeometric.cdf( 0.0, 10, NaN, 2 )\ny = base.dists.hypergeometric.cdf( 0.0, 10, 5, NaN )\ny = base.dists.hypergeometric.cdf( 2.0, 10.5, 5, 2 )\ny = base.dists.hypergeometric.cdf( 2.0, 10, 1.5, 2 )\ny = base.dists.hypergeometric.cdf( 2.0, 10, 5, -2.0 )\ny = base.dists.hypergeometric.cdf( 2.0, 10, 5, 12 )\ny = base.dists.hypergeometric.cdf( 2.0, 8, 3, 9 )\n","base.dists.hypergeometric.cdf.factory":"var myCDF = base.dists.hypergeometric.cdf.factory( 30, 20, 5 );\nvar y = myCDF( 4.0 )\ny = myCDF( 1.0 )\n","base.dists.hypergeometric.Hypergeometric":"var hypergeometric = base.dists.hypergeometric.Hypergeometric( 100, 70, 20 );\nhypergeometric.N\nhypergeometric.K\nhypergeometric.n\nhypergeometric.kurtosis\nhypergeometric.mean\nhypergeometric.mode\nhypergeometric.skewness\nhypergeometric.stdev\nhypergeometric.variance\nhypergeometric.cdf( 2.9 )\nhypergeometric.logpmf( 10 )\nhypergeometric.pmf( 10 )\nhypergeometric.quantile( 0.8 )\n","base.dists.hypergeometric.kurtosis":"var v = base.dists.hypergeometric.kurtosis( 16, 11, 4 )\nv = base.dists.hypergeometric.kurtosis( 4, 2, 2 )\nv = base.dists.hypergeometric.kurtosis( 10, 5, 12 )\nv = base.dists.hypergeometric.kurtosis( 10.3, 10, 4 )\nv = base.dists.hypergeometric.kurtosis( 10, 5.5, 4 )\nv = base.dists.hypergeometric.kurtosis( 10, 5, 4.5 )\nv = base.dists.hypergeometric.kurtosis( NaN, 10, 4 )\nv = base.dists.hypergeometric.kurtosis( 20, NaN, 4 )\nv = base.dists.hypergeometric.kurtosis( 20, 10, NaN )\n","base.dists.hypergeometric.logpmf":"var y = base.dists.hypergeometric.logpmf( 1.0, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( 2.0, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( 1.5, 8, 4, 2 )\ny = base.dists.hypergeometric.logpmf( NaN, 10, 5, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, NaN, 5, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, 10, NaN, 2 )\ny = base.dists.hypergeometric.logpmf( 0.0, 10, 5, NaN )\ny = base.dists.hypergeometric.logpmf( 2.0, 10.5, 5, 2 )\ny = base.dists.hypergeometric.logpmf( 2.0, 5, 1.5, 2 )\ny = base.dists.hypergeometric.logpmf( 2.0, 10, 5, -2.0 )\ny = base.dists.hypergeometric.logpmf( 2.0, 10, 5, 12 )\ny = base.dists.hypergeometric.logpmf( 2.0, 8, 3, 9 )\n","base.dists.hypergeometric.logpmf.factory":"var mylogPMF = base.dists.hypergeometric.logpmf.factory( 30, 20, 5 );\nvar y = mylogPMF( 4.0 )\ny = mylogPMF( 1.0 )\n","base.dists.hypergeometric.mean":"var v = base.dists.hypergeometric.mean( 16, 11, 4 )\nv = base.dists.hypergeometric.mean( 2, 1, 1 )\nv = base.dists.hypergeometric.mean( 10, 5, 12 )\nv = base.dists.hypergeometric.mean( 10.3, 10, 4 )\nv = base.dists.hypergeometric.mean( 10, 5.5, 4 )\nv = base.dists.hypergeometric.mean( 10, 5, 4.5 )\nv = base.dists.hypergeometric.mean( NaN, 10, 4 )\nv = base.dists.hypergeometric.mean( 20, NaN, 4 )\nv = base.dists.hypergeometric.mean( 20, 10, NaN )\n","base.dists.hypergeometric.mode":"var v = base.dists.hypergeometric.mode( 16, 11, 4 )\nv = base.dists.hypergeometric.mode( 2, 1, 1 )\nv = base.dists.hypergeometric.mode( 10, 5, 12 )\nv = base.dists.hypergeometric.mode( 10.3, 10, 4 )\nv = base.dists.hypergeometric.mode( 10, 5.5, 4 )\nv = base.dists.hypergeometric.mode( 10, 5, 4.5 )\nv = base.dists.hypergeometric.mode( NaN, 10, 4 )\nv = base.dists.hypergeometric.mode( 20, NaN, 4 )\nv = base.dists.hypergeometric.mode( 20, 10, NaN )\n","base.dists.hypergeometric.pmf":"var y = base.dists.hypergeometric.pmf( 1.0, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( 2.0, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( 1.5, 8, 4, 2 )\ny = base.dists.hypergeometric.pmf( NaN, 10, 5, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, NaN, 5, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, 10, NaN, 2 )\ny = base.dists.hypergeometric.pmf( 0.0, 10, 5, NaN )\ny = base.dists.hypergeometric.pmf( 2.0, 10.5, 5, 2 )\ny = base.dists.hypergeometric.pmf( 2.0, 5, 1.5, 2 )\ny = base.dists.hypergeometric.pmf( 2.0, 10, 5, -2.0 )\ny = base.dists.hypergeometric.pmf( 2.0, 10, 5, 12 )\ny = base.dists.hypergeometric.pmf( 2.0, 8, 3, 9 )\n","base.dists.hypergeometric.pmf.factory":"var myPMF = base.dists.hypergeometric.pmf.factory( 30, 20, 5 );\nvar y = myPMF( 4.0 )\ny = myPMF( 1.0 )\n","base.dists.hypergeometric.quantile":"var y = base.dists.hypergeometric.quantile( 0.4, 40, 20, 10 )\ny = base.dists.hypergeometric.quantile( 0.8, 60, 40, 20 )\ny = base.dists.hypergeometric.quantile( 0.5, 100, 10, 10 )\ny = base.dists.hypergeometric.quantile( 0.0, 100, 40, 20 )\ny = base.dists.hypergeometric.quantile( 1.0, 100, 40, 20 )\ny = base.dists.hypergeometric.quantile( NaN, 40, 20, 10 )\ny = base.dists.hypergeometric.quantile( 0.2, NaN, 20, 10 )\ny = base.dists.hypergeometric.quantile( 0.2, 40, NaN, 10 )\ny = base.dists.hypergeometric.quantile( 0.2, 40, 20, NaN )\n","base.dists.hypergeometric.quantile.factory":"var myQuantile = base.dists.hypergeometric.quantile.factory( 100, 20, 10 );\nvar y = myQuantile( 0.2 )\ny = myQuantile( 0.9 )\n","base.dists.hypergeometric.skewness":"var v = base.dists.hypergeometric.skewness( 16, 11, 4 )\nv = base.dists.hypergeometric.skewness( 4, 2, 2 )\nv = base.dists.hypergeometric.skewness( 10, 5, 12 )\nv = base.dists.hypergeometric.skewness( 10.3, 10, 4 )\nv = base.dists.hypergeometric.skewness( 10, 5.5, 4 )\nv = base.dists.hypergeometric.skewness( 10, 5, 4.5 )\nv = base.dists.hypergeometric.skewness( NaN, 10, 4 )\nv = base.dists.hypergeometric.skewness( 20, NaN, 4 )\nv = base.dists.hypergeometric.skewness( 20, 10, NaN )\n","base.dists.hypergeometric.stdev":"var v = base.dists.hypergeometric.stdev( 16, 11, 4 )\nv = base.dists.hypergeometric.stdev( 2, 1, 1 )\nv = base.dists.hypergeometric.stdev( 10, 5, 12 )\nv = base.dists.hypergeometric.stdev( 10.3, 10, 4 )\nv = base.dists.hypergeometric.stdev( 10, 5.5, 4 )\nv = base.dists.hypergeometric.stdev( 10, 5, 4.5 )\nv = base.dists.hypergeometric.stdev( NaN, 10, 4 )\nv = base.dists.hypergeometric.stdev( 20, NaN, 4 )\nv = base.dists.hypergeometric.stdev( 20, 10, NaN )\n","base.dists.hypergeometric.variance":"var v = base.dists.hypergeometric.variance( 16, 11, 4 )\nv = base.dists.hypergeometric.variance( 2, 1, 1 )\nv = base.dists.hypergeometric.variance( 10, 5, 12 )\nv = base.dists.hypergeometric.variance( 10.3, 10, 4 )\nv = base.dists.hypergeometric.variance( 10, 5.5, 4 )\nv = base.dists.hypergeometric.variance( 10, 5, 4.5 )\nv = base.dists.hypergeometric.variance( NaN, 10, 4 )\nv = base.dists.hypergeometric.variance( 20, NaN, 4 )\nv = base.dists.hypergeometric.variance( 20, 10, NaN )\n","base.dists.invgamma.cdf":"var y = base.dists.invgamma.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.invgamma.cdf( 2.0, 3.0, 1.0 )\ny = base.dists.invgamma.cdf( -1.0, 2.0, 2.0 )\ny = base.dists.invgamma.cdf( PINF, 4.0, 2.0 )\ny = base.dists.invgamma.cdf( NINF, 4.0, 2.0 )\ny = base.dists.invgamma.cdf( NaN, 0.0, 1.0 )\ny = base.dists.invgamma.cdf( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.cdf( 0.0, 0.0, NaN )\ny = base.dists.invgamma.cdf( 2.0, -1.0, 1.0 )\ny = base.dists.invgamma.cdf( 2.0, 1.0, -1.0 )\n","base.dists.invgamma.cdf.factory":"var myCDF = base.dists.invgamma.cdf.factory( 2.0, 0.5 );\nvar y = myCDF( 0.5 )\ny = myCDF( 2.0 )\n","base.dists.invgamma.entropy":"var v = base.dists.invgamma.entropy( 1.0, 1.0 )\nv = base.dists.invgamma.entropy( 4.0, 12.0 )\nv = base.dists.invgamma.entropy( 8.0, 2.0 )\n","base.dists.invgamma.InvGamma":"var invgamma = base.dists.invgamma.InvGamma( 6.0, 5.0 );\ninvgamma.alpha\ninvgamma.beta\ninvgamma.entropy\ninvgamma.kurtosis\ninvgamma.mean\ninvgamma.mode\ninvgamma.skewness\ninvgamma.stdev\ninvgamma.variance\ninvgamma.cdf( 0.8 )\ninvgamma.pdf( 1.0 )\ninvgamma.logpdf( 1.0 )\ninvgamma.quantile( 0.8 )\n","base.dists.invgamma.kurtosis":"var v = base.dists.invgamma.kurtosis( 7.0, 5.0 )\nv = base.dists.invgamma.kurtosis( 6.0, 12.0 )\nv = base.dists.invgamma.kurtosis( 8.0, 2.0 )\n","base.dists.invgamma.logpdf":"var y = base.dists.invgamma.logpdf( 2.0, 0.5, 1.0 )\ny = base.dists.invgamma.logpdf( 0.2, 1.0, 1.0 )\ny = base.dists.invgamma.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.invgamma.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.invgamma.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.logpdf( 0.0, 1.0, NaN )\ny = base.dists.invgamma.logpdf( 2.0, -1.0, 1.0 )\ny = base.dists.invgamma.logpdf( 2.0, 1.0, -1.0 )\n","base.dists.invgamma.logpdf.factory":"var mylogPDF = base.dists.invgamma.logpdf.factory( 6.0, 7.0 );\nvar y = mylogPDF( 2.0 )\n","base.dists.invgamma.mean":"var v = base.dists.invgamma.mean( 4.0, 12.0 )\nv = base.dists.invgamma.mean( 8.0, 2.0 )\n","base.dists.invgamma.mode":"var v = base.dists.invgamma.mode( 1.0, 1.0 )\nv = base.dists.invgamma.mode( 4.0, 12.0 )\nv = base.dists.invgamma.mode( 8.0, 2.0 )\n","base.dists.invgamma.pdf":"var y = base.dists.invgamma.pdf( 2.0, 0.5, 1.0 )\ny = base.dists.invgamma.pdf( 0.2, 1.0, 1.0 )\ny = base.dists.invgamma.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.invgamma.pdf( NaN, 1.0, 1.0 )\ny = base.dists.invgamma.pdf( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.pdf( 0.0, 1.0, NaN )\ny = base.dists.invgamma.pdf( 2.0, -1.0, 1.0 )\ny = base.dists.invgamma.pdf( 2.0, 1.0, -1.0 )\n","base.dists.invgamma.pdf.factory":"var myPDF = base.dists.invgamma.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 2.0 )\n","base.dists.invgamma.quantile":"var y = base.dists.invgamma.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.invgamma.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.invgamma.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.invgamma.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.invgamma.quantile( NaN, 1.0, 1.0 )\ny = base.dists.invgamma.quantile( 0.0, NaN, 1.0 )\ny = base.dists.invgamma.quantile( 0.0, 1.0, NaN )\ny = base.dists.invgamma.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.invgamma.quantile( 0.5, 1.0, -1.0 )\n","base.dists.invgamma.quantile.factory":"var myQuantile = base.dists.invgamma.quantile.factory( 2.0, 2.0 );\nvar y = myQuantile( 0.8 )\ny = myQuantile( 0.4 )\n","base.dists.invgamma.skewness":"var v = base.dists.invgamma.skewness( 4.0, 12.0 )\nv = base.dists.invgamma.skewness( 8.0, 2.0 )\n","base.dists.invgamma.stdev":"var v = base.dists.invgamma.stdev( 5.0, 7.0 )\nv = base.dists.invgamma.stdev( 4.0, 12.0 )\nv = base.dists.invgamma.stdev( 8.0, 2.0 )\n","base.dists.invgamma.variance":"var v = base.dists.invgamma.variance( 5.0, 7.0 )\nv = base.dists.invgamma.variance( 4.0, 12.0 )\nv = base.dists.invgamma.variance( 8.0, 2.0 )\n","base.dists.kumaraswamy.cdf":"var y = base.dists.kumaraswamy.cdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.cdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.cdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.cdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.cdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.cdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.cdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.cdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.cdf( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.cdf.factory":"var mycdf = base.dists.kumaraswamy.cdf.factory( 0.5, 1.0 );\nvar y = mycdf( 0.8 )\ny = mycdf( 0.3 )\n","base.dists.kumaraswamy.Kumaraswamy":"var kumaraswamy = base.dists.kumaraswamy.Kumaraswamy( 6.0, 5.0 );\nkumaraswamy.a\nkumaraswamy.b\nkumaraswamy.kurtosis\nkumaraswamy.mean\nkumaraswamy.mode\nkumaraswamy.skewness\nkumaraswamy.stdev\nkumaraswamy.variance\nkumaraswamy.cdf( 0.8 )\nkumaraswamy.pdf( 1.0 )\nkumaraswamy.quantile( 0.8 )\n","base.dists.kumaraswamy.kurtosis":"var v = base.dists.kumaraswamy.kurtosis( 1.0, 1.0 )\nv = base.dists.kumaraswamy.kurtosis( 4.0, 12.0 )\nv = base.dists.kumaraswamy.kurtosis( 16.0, 8.0 )\n","base.dists.kumaraswamy.logcdf":"var y = base.dists.kumaraswamy.logcdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logcdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.logcdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.logcdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.logcdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logcdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.logcdf( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.logcdf.factory":"var mylogcdf = base.dists.kumaraswamy.logcdf.factory( 0.5, 1.0 );\nvar y = mylogcdf( 0.8 )\ny = mylogcdf( 0.3 )\n","base.dists.kumaraswamy.logpdf":"var y = base.dists.kumaraswamy.logpdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logpdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.logpdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.logpdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.logpdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logpdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.logpdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.logpdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.logpdf( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.logpdf.factory":"var mylogpdf = base.dists.kumaraswamy.logpdf.factory( 0.5, 1.0 );\nvar y = mylogpdf( 0.8 )\ny = mylogpdf( 0.3 )\n","base.dists.kumaraswamy.mean":"var v = base.dists.kumaraswamy.mean( 1.5, 1.5 )\nv = base.dists.kumaraswamy.mean( 4.0, 12.0 )\nv = base.dists.kumaraswamy.mean( 16.0, 8.0 )\n","base.dists.kumaraswamy.median":"var v = base.dists.kumaraswamy.median( 1.0, 1.0 )\nv = base.dists.kumaraswamy.median( 4.0, 12.0 )\nv = base.dists.kumaraswamy.median( 16.0, 8.0 )\n","base.dists.kumaraswamy.mode":"var v = base.dists.kumaraswamy.mode( 1.5, 1.5 )\nv = base.dists.kumaraswamy.mode( 4.0, 12.0 )\nv = base.dists.kumaraswamy.mode( 16.0, 8.0 )\n","base.dists.kumaraswamy.pdf":"var y = base.dists.kumaraswamy.pdf( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.pdf( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.pdf( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.pdf( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.pdf( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.pdf( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.pdf( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.pdf( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.pdf( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.pdf( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.pdf( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.pdf.factory":"var mypdf = base.dists.kumaraswamy.pdf.factory( 0.5, 1.0 );\nvar y = mypdf( 0.8 )\ny = mypdf( 0.3 )\n","base.dists.kumaraswamy.quantile":"var y = base.dists.kumaraswamy.quantile( 0.5, 1.0, 1.0 )\ny = base.dists.kumaraswamy.quantile( 0.5, 2.0, 4.0 )\ny = base.dists.kumaraswamy.quantile( 0.2, 2.0, 2.0 )\ny = base.dists.kumaraswamy.quantile( 0.8, 4.0, 4.0 )\ny = base.dists.kumaraswamy.quantile( -0.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.quantile( 1.5, 4.0, 2.0 )\ny = base.dists.kumaraswamy.quantile( 2.0, -1.0, 0.5 )\ny = base.dists.kumaraswamy.quantile( 2.0, 0.5, -1.0 )\ny = base.dists.kumaraswamy.quantile( NaN, 1.0, 1.0 )\ny = base.dists.kumaraswamy.quantile( 0.0, NaN, 1.0 )\ny = base.dists.kumaraswamy.quantile( 0.0, 1.0, NaN )\n","base.dists.kumaraswamy.quantile.factory":"var myQuantile = base.dists.kumaraswamy.quantile.factory( 0.5, 1.0 );\nvar y = myQuantile( 0.8 )\ny = myQuantile( 0.3 )\n","base.dists.kumaraswamy.skewness":"var v = base.dists.kumaraswamy.skewness( 1.0, 1.0 )\nv = base.dists.kumaraswamy.skewness( 4.0, 12.0 )\nv = base.dists.kumaraswamy.skewness( 16.0, 8.0 )\n","base.dists.kumaraswamy.stdev":"var v = base.dists.kumaraswamy.stdev( 1.0, 1.0 )\nv = base.dists.kumaraswamy.stdev( 4.0, 12.0 )\nv = base.dists.kumaraswamy.stdev( 16.0, 8.0 )\n","base.dists.kumaraswamy.variance":"var v = base.dists.kumaraswamy.variance( 1.0, 1.0 )\nv = base.dists.kumaraswamy.variance( 4.0, 12.0 )\nv = base.dists.kumaraswamy.variance( 16.0, 8.0 )\n","base.dists.laplace.cdf":"var y = base.dists.laplace.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.cdf( 5.0, 10.0, 3.0 )\ny = base.dists.laplace.cdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.cdf( 2, NaN, 1.0 )\ny = base.dists.laplace.cdf( 2.0, 0.0, NaN )\ny = base.dists.laplace.cdf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.cdf.factory":"var myCDF = base.dists.laplace.cdf.factory( 2.0, 3.0 );\nvar y = myCDF( 10.0 )\ny = myCDF( 2.0 )\n","base.dists.laplace.entropy":"var y = base.dists.laplace.entropy( 0.0, 1.0 )\ny = base.dists.laplace.entropy( 4.0, 2.0 )\ny = base.dists.laplace.entropy( NaN, 1.0 )\ny = base.dists.laplace.entropy( 0.0, NaN )\ny = base.dists.laplace.entropy( 0.0, 0.0 )\n","base.dists.laplace.kurtosis":"var y = base.dists.laplace.kurtosis( 0.0, 1.0 )\ny = base.dists.laplace.kurtosis( 4.0, 2.0 )\ny = base.dists.laplace.kurtosis( NaN, 1.0 )\ny = base.dists.laplace.kurtosis( 0.0, NaN )\ny = base.dists.laplace.kurtosis( 0.0, 0.0 )\n","base.dists.laplace.Laplace":"var laplace = base.dists.laplace.Laplace( -2.0, 3.0 );\nlaplace.mu\nlaplace.b\nlaplace.entropy\nlaplace.kurtosis\nlaplace.mean\nlaplace.median\nlaplace.mode\nlaplace.skewness\nlaplace.stdev\nlaplace.variance\nlaplace.cdf( 0.8 )\nlaplace.logcdf( 0.8 )\nlaplace.logpdf( 1.0 )\nlaplace.mgf( 0.2 )\nlaplace.pdf( 2.0 )\nlaplace.quantile( 0.9 )\n","base.dists.laplace.logcdf":"var y = base.dists.laplace.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.logcdf( 5.0, 10.0, 3.0 )\ny = base.dists.laplace.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.logcdf( 2, NaN, 1.0 )\ny = base.dists.laplace.logcdf( 2.0, 0.0, NaN )\ny = base.dists.laplace.logcdf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.logcdf.factory":"var mylogcdf = base.dists.laplace.logcdf.factory( 2.0, 3.0 );\nvar y = mylogcdf( 10.0 )\ny = mylogcdf( 2.0 )\n","base.dists.laplace.logpdf":"var y = base.dists.laplace.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.logpdf( -1.0, 2.0, 3.0 )\ny = base.dists.laplace.logpdf( 2.5, 2.0, 3.0 )\ny = base.dists.laplace.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.laplace.logpdf( 0.0, 0.0, NaN )\ny = base.dists.laplace.logpdf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.logpdf.factory":"var mylogPDF = base.dists.laplace.logpdf.factory( 10.0, 2.0 );\nvar y = mylogPDF( 10.0 )\n","base.dists.laplace.mean":"var y = base.dists.laplace.mean( 0.0, 1.0 )\ny = base.dists.laplace.mean( 4.0, 2.0 )\ny = base.dists.laplace.mean( NaN, 1.0 )\ny = base.dists.laplace.mean( 0.0, NaN )\ny = base.dists.laplace.mean( 0.0, 0.0 )\n","base.dists.laplace.median":"var y = base.dists.laplace.median( 0.0, 1.0 )\ny = base.dists.laplace.median( 4.0, 2.0 )\ny = base.dists.laplace.median( NaN, 1.0 )\ny = base.dists.laplace.median( 0.0, NaN )\ny = base.dists.laplace.median( 0.0, 0.0 )\n","base.dists.laplace.mgf":"var y = base.dists.laplace.mgf( 0.5, 0.0, 1.0 )\ny = base.dists.laplace.mgf( 0.0, 0.0, 1.0 )\ny = base.dists.laplace.mgf( -1.0, 4.0, 0.2 )\ny = base.dists.laplace.mgf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.mgf( 0.0, NaN, 1.0 )\ny = base.dists.laplace.mgf( 0.0, 0.0, NaN )\ny = base.dists.laplace.mgf( 1.0, 0.0, 2.0 )\ny = base.dists.laplace.mgf( -0.5, 0.0, 4.0 )\ny = base.dists.laplace.mgf( 2.0, 0.0, 0.0 )\ny = base.dists.laplace.mgf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.mgf.factory":"var mymgf = base.dists.laplace.mgf.factory( 4.0, 2.0 );\nvar y = mymgf( 0.2 )\ny = mymgf( 0.4 )\n","base.dists.laplace.mode":"var y = base.dists.laplace.mode( 0.0, 1.0 )\ny = base.dists.laplace.mode( 4.0, 2.0 )\ny = base.dists.laplace.mode( NaN, 1.0 )\ny = base.dists.laplace.mode( 0.0, NaN )\ny = base.dists.laplace.mode( 0.0, 0.0 )\n","base.dists.laplace.pdf":"var y = base.dists.laplace.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.laplace.pdf( -1.0, 2.0, 3.0 )\ny = base.dists.laplace.pdf( 2.5, 2.0, 3.0 )\ny = base.dists.laplace.pdf( NaN, 0.0, 1.0 )\ny = base.dists.laplace.pdf( 0.0, NaN, 1.0 )\ny = base.dists.laplace.pdf( 0.0, 0.0, NaN )\ny = base.dists.laplace.pdf( 2.0, 0.0, -1.0 )\n","base.dists.laplace.pdf.factory":"var myPDF = base.dists.laplace.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\n","base.dists.laplace.quantile":"var y = base.dists.laplace.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.laplace.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.laplace.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.laplace.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.laplace.quantile( NaN, 0.0, 1.0 )\ny = base.dists.laplace.quantile( 0.0, NaN, 1.0 )\ny = base.dists.laplace.quantile( 0.0, 0.0, NaN )\ny = base.dists.laplace.quantile( 0.5, 0.0, -1.0 )\n","base.dists.laplace.quantile.factory":"var myQuantile = base.dists.laplace.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\ny = myQuantile( 0.8 )\n","base.dists.laplace.skewness":"var y = base.dists.laplace.skewness( 0.0, 1.0 )\ny = base.dists.laplace.skewness( 4.0, 2.0 )\ny = base.dists.laplace.skewness( NaN, 1.0 )\ny = base.dists.laplace.skewness( 0.0, NaN )\ny = base.dists.laplace.skewness( 0.0, 0.0 )\n","base.dists.laplace.stdev":"var y = base.dists.laplace.stdev( 0.0, 1.0 )\ny = base.dists.laplace.stdev( 4.0, 2.0 )\ny = base.dists.laplace.stdev( NaN, 1.0 )\ny = base.dists.laplace.stdev( 0.0, NaN )\ny = base.dists.laplace.stdev( 0.0, 0.0 )\n","base.dists.laplace.variance":"var y = base.dists.laplace.variance( 0.0, 1.0 )\ny = base.dists.laplace.variance( 4.0, 2.0 )\ny = base.dists.laplace.variance( NaN, 1.0 )\ny = base.dists.laplace.variance( 0.0, NaN )\ny = base.dists.laplace.variance( 0.0, 0.0 )\n","base.dists.levy.cdf":"var y = base.dists.levy.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.levy.cdf( 12.0, 10.0, 3.0 )\ny = base.dists.levy.cdf( 9.0, 10.0, 3.0 )\ny = base.dists.levy.cdf( NaN, 0.0, 1.0 )\ny = base.dists.levy.cdf( 2, NaN, 1.0 )\ny = base.dists.levy.cdf( 2.0, 0.0, NaN )\ny = base.dists.levy.cdf( 2.0, 0.0, -1.0 )\n","base.dists.levy.cdf.factory":"var myCDF = base.dists.levy.cdf.factory( 2.0, 3.0 );\nvar y = myCDF( 10.0 )\ny = myCDF( 2.0 )\n","base.dists.levy.entropy":"var y = base.dists.levy.entropy( 0.0, 1.0 )\ny = base.dists.levy.entropy( 4.0, 2.0 )\ny = base.dists.levy.entropy( NaN, 1.0 )\ny = base.dists.levy.entropy( 0.0, NaN )\ny = base.dists.levy.entropy( 0.0, 0.0 )\n","base.dists.levy.Levy":"var levy = base.dists.levy.Levy( -2.0, 3.0 );\nlevy.mu\nlevy.c\nlevy.entropy\nlevy.mean\nlevy.median\nlevy.mode\nlevy.stdev\nlevy.variance\nlevy.cdf( 0.8 )\nlevy.logcdf( 0.8 )\nlevy.logpdf( 1.0 )\nlevy.pdf( 1.0 )\nlevy.quantile( 0.8 )\n","base.dists.levy.logcdf":"var y = base.dists.levy.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.levy.logcdf( 12.0, 10.0, 3.0 )\ny = base.dists.levy.logcdf( 9.0, 10.0, 3.0 )\ny = base.dists.levy.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.levy.logcdf( 2, NaN, 1.0 )\ny = base.dists.levy.logcdf( 2.0, 0.0, NaN )\ny = base.dists.levy.logcdf( 2.0, 0.0, -1.0 )\n","base.dists.levy.logcdf.factory":"var mylogcdf = base.dists.levy.logcdf.factory( 2.0, 3.0 );\nvar y = mylogcdf( 10.0 )\ny = mylogcdf( 2.0 )\n","base.dists.levy.logpdf":"var y = base.dists.levy.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.levy.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.levy.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.levy.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.levy.logpdf( 0.0, 0.0, NaN )\ny = base.dists.levy.logpdf( 2.0, 0.0, -1.0 )\n","base.dists.levy.logpdf.factory":"var mylogPDF = base.dists.levy.logpdf.factory( 10.0, 2.0 );\nvar y = mylogPDF( 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myPDF = base.dists.levy.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 11.0 )\n","base.dists.levy.quantile":"var y = base.dists.levy.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.levy.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.levy.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.levy.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.levy.quantile( NaN, 0.0, 1.0 )\ny = base.dists.levy.quantile( 0.0, NaN, 1.0 )\ny = base.dists.levy.quantile( 0.0, 0.0, NaN )\ny = base.dists.levy.quantile( 0.5, 0.0, -1.0 )\n","base.dists.levy.quantile.factory":"var myQuantile = base.dists.levy.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.levy.stdev":"var y = base.dists.levy.stdev( 0.0, 1.0 )\ny = base.dists.levy.stdev( 4.0, 3.0 )\ny = base.dists.levy.stdev( NaN, 1.0 )\ny = base.dists.levy.stdev( 0.0, NaN )\ny = base.dists.levy.stdev( 0.0, 0.0 )\n","base.dists.levy.variance":"var y = base.dists.levy.variance( 0.0, 1.0 )\ny = base.dists.levy.variance( 4.0, 3.0 )\ny = base.dists.levy.variance( NaN, 1.0 )\ny = base.dists.levy.variance( 0.0, NaN )\ny = base.dists.levy.variance( 0.0, 0.0 )\n","base.dists.logistic.cdf":"var y = base.dists.logistic.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.logistic.cdf( 5.0, 10.0, 3.0 )\ny = base.dists.logistic.cdf( 2.0, 0.0, NaN )\ny = base.dists.logistic.cdf( 2.0, NaN, 1.0 )\ny = base.dists.logistic.cdf( NaN, 0.0, 1.0 )\ny = base.dists.logistic.cdf( 2.0, 8.0, 0.0 )\ny = base.dists.logistic.cdf( 8.0, 8.0, 0.0 )\ny = base.dists.logistic.cdf( 10.0, 8.0, 0.0 )\n","base.dists.logistic.cdf.factory":"var mycdf = base.dists.logistic.cdf.factory( 3.0, 1.5 );\nvar y = mycdf( 1.0 )\n","base.dists.logistic.entropy":"var y = base.dists.logistic.entropy( 0.0, 1.0 )\ny = base.dists.logistic.entropy( 4.0, 2.0 )\ny = base.dists.logistic.entropy( NaN, 1.0 )\ny = base.dists.logistic.entropy( 0.0, NaN )\ny = base.dists.logistic.entropy( 0.0, 0.0 )\n","base.dists.logistic.kurtosis":"var y = base.dists.logistic.kurtosis( 0.0, 1.0 )\ny = base.dists.logistic.kurtosis( 4.0, 2.0 )\ny = base.dists.logistic.kurtosis( NaN, 1.0 )\ny = base.dists.logistic.kurtosis( 0.0, NaN )\ny = base.dists.logistic.kurtosis( 0.0, 0.0 )\n","base.dists.logistic.logcdf":"var y = base.dists.logistic.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.logistic.logcdf( 5.0, 10.0, 3.0 )\ny = base.dists.logistic.logcdf( 2.0, 0.0, NaN )\ny = base.dists.logistic.logcdf( 2, NaN, 1.0 )\ny = base.dists.logistic.logcdf( NaN, 0.0, 1.0 )\n","base.dists.logistic.logcdf.factory":"var mylogcdf = base.dists.logistic.logcdf.factory( 3.0, 1.5 );\nvar y = mylogcdf( 1.0 )\n","base.dists.logistic.Logistic":"var logistic = base.dists.logistic.Logistic( -2.0, 3.0 );\nlogistic.mu\nlogistic.s\nlogistic.entropy\nlogistic.kurtosis\nlogistic.mean\nlogistic.median\nlogistic.mode\nlogistic.skewness\nlogistic.stdev\nlogistic.variance\nlogistic.cdf( 0.8 )\nlogistic.logcdf( 0.8 )\nlogistic.logpdf( 2.0 )\nlogistic.mgf( 0.2 )\nlogistic.pdf( 2.0 )\nlogistic.quantile( 0.9 )\n","base.dists.logistic.logpdf":"var y = base.dists.logistic.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.logistic.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.logistic.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.logistic.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.logistic.logpdf( 0.0, 0.0, NaN )\ny = base.dists.logistic.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.logistic.logpdf( 2.0, 8.0, 0.0 )\ny = base.dists.logistic.logpdf( 8.0, 8.0, 0.0 )\n","base.dists.logistic.logpdf.factory":"var mylogpdf = base.dists.logistic.logpdf.factory( 10.0, 2.0 );\nvar y = mylogpdf( 10.0 )\n","base.dists.logistic.mean":"var y = base.dists.logistic.mean( 0.0, 1.0 )\ny = base.dists.logistic.mean( 4.0, 2.0 )\ny = base.dists.logistic.mean( NaN, 1.0 )\ny = base.dists.logistic.mean( 0.0, NaN )\ny = base.dists.logistic.mean( 0.0, 0.0 )\n","base.dists.logistic.median":"var y = base.dists.logistic.median( 0.0, 1.0 )\ny = base.dists.logistic.median( 4.0, 2.0 )\ny = base.dists.logistic.median( NaN, 1.0 )\ny = base.dists.logistic.median( 0.0, NaN )\ny = base.dists.logistic.median( 0.0, 0.0 )\n","base.dists.logistic.mgf":"var y = base.dists.logistic.mgf( 0.9, 0.0, 1.0 )\ny = base.dists.logistic.mgf( 0.1, 4.0, 4.0 )\ny = base.dists.logistic.mgf( -0.2, 4.0, 4.0 )\ny = base.dists.logistic.mgf( 0.5, 0.0, -1.0 )\ny = base.dists.logistic.mgf( 0.5, 0.0, 4.0 )\ny = base.dists.logistic.mgf( NaN, 0.0, 1.0 )\ny = base.dists.logistic.mgf( 0.0, NaN, 1.0 )\ny = base.dists.logistic.mgf( 0.0, 0.0, NaN )\n","base.dists.logistic.mgf.factory":"var mymgf = base.dists.logistic.mgf.factory( 10.0, 0.5 );\nvar y = mymgf( 0.5 )\ny = mymgf( 2.0 )\n","base.dists.logistic.mode":"var y = base.dists.logistic.mode( 0.0, 1.0 )\ny = base.dists.logistic.mode( 4.0, 2.0 )\ny = base.dists.logistic.mode( NaN, 1.0 )\ny = base.dists.logistic.mode( 0.0, NaN )\ny = base.dists.logistic.mode( 0.0, 0.0 )\n","base.dists.logistic.pdf":"var y = base.dists.logistic.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.logistic.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.logistic.pdf( NaN, 0.0, 1.0 )\ny = base.dists.logistic.pdf( 0.0, NaN, 1.0 )\ny = base.dists.logistic.pdf( 0.0, 0.0, NaN )\ny = base.dists.logistic.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.logistic.pdf( 2.0, 8.0, 0.0 )\ny = base.dists.logistic.pdf( 8.0, 8.0, 0.0 )\n","base.dists.logistic.pdf.factory":"var myPDF = base.dists.logistic.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\n","base.dists.logistic.quantile":"var y = base.dists.logistic.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.logistic.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.logistic.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.logistic.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.logistic.quantile( NaN, 0.0, 1.0 )\ny = base.dists.logistic.quantile( 0.0, NaN, 1.0 )\ny = base.dists.logistic.quantile( 0.0, 0.0, NaN )\ny = base.dists.logistic.quantile( 0.5, 0.0, -1.0 )\n","base.dists.logistic.quantile.factory":"var myQuantile = base.dists.logistic.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.logistic.skewness":"var y = base.dists.logistic.skewness( 0.0, 1.0 )\ny = base.dists.logistic.skewness( 4.0, 2.0 )\ny = base.dists.logistic.skewness( NaN, 1.0 )\ny = base.dists.logistic.skewness( 0.0, NaN )\ny = base.dists.logistic.skewness( 0.0, 0.0 )\n","base.dists.logistic.stdev":"var y = base.dists.logistic.stdev( 0.0, 1.0 )\ny = base.dists.logistic.stdev( 4.0, 2.0 )\ny = base.dists.logistic.stdev( NaN, 1.0 )\ny = base.dists.logistic.stdev( 0.0, NaN )\ny = base.dists.logistic.stdev( 0.0, 0.0 )\n","base.dists.logistic.variance":"var y = base.dists.logistic.variance( 0.0, 1.0 )\ny = base.dists.logistic.variance( 4.0, 2.0 )\ny = base.dists.logistic.variance( NaN, 1.0 )\ny = base.dists.logistic.variance( 0.0, NaN )\ny = base.dists.logistic.variance( 0.0, 0.0 )\n","base.dists.lognormal.cdf":"var y = base.dists.lognormal.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.cdf( 5.0, 10.0, 3.0 )\ny = base.dists.lognormal.cdf( 2.0, 0.0, NaN )\ny = base.dists.lognormal.cdf( 2.0, NaN, 1.0 )\ny = base.dists.lognormal.cdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.cdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.cdf( 2.0, 0.0, 0.0 )\n","base.dists.lognormal.cdf.factory":"var myCDF = base.dists.lognormal.cdf.factory( 3.0, 1.5 );\nvar y = myCDF( 1.0 )\ny = myCDF( 4.0 )\n","base.dists.lognormal.entropy":"var y = base.dists.lognormal.entropy( 0.0, 1.0 )\ny = base.dists.lognormal.entropy( 5.0, 2.0 )\ny = base.dists.lognormal.entropy( NaN, 1.0 )\ny = base.dists.lognormal.entropy( 0.0, NaN )\ny = base.dists.lognormal.entropy( 0.0, 0.0 )\n","base.dists.lognormal.kurtosis":"var y = base.dists.lognormal.kurtosis( 0.0, 1.0 )\ny = base.dists.lognormal.kurtosis( 5.0, 2.0 )\ny = base.dists.lognormal.kurtosis( NaN, 1.0 )\ny = base.dists.lognormal.kurtosis( 0.0, NaN )\ny = base.dists.lognormal.kurtosis( 0.0, 0.0 )\n","base.dists.lognormal.LogNormal":"var lognormal = base.dists.lognormal.LogNormal( -2.0, 3.0 );\nlognormal.mu\nlognormal.sigma\nlognormal.entropy\nlognormal.kurtosis\nlognormal.mean\nlognormal.median\nlognormal.mode\nlognormal.skewness\nlognormal.stdev\nlognormal.variance\nlognormal.cdf( 0.8 )\nlognormal.logcdf( 0.8 )\nlognormal.logpdf( 2.0 )\nlognormal.pdf( 2.0 )\nlognormal.quantile( 0.9 )\n","base.dists.lognormal.logcdf":"var y = base.dists.lognormal.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.logcdf( 13.0, 4.0, 2.0 )\ny = base.dists.lognormal.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.logcdf( 0.0, 0.0, NaN )\ny = base.dists.lognormal.logcdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.logcdf( 2.0, 8.0, 0.0 )\ny = base.dists.lognormal.logcdf( 8.0, 8.0, 0.0 )\n","base.dists.lognormal.logcdf.factory":"var mylogcdf = base.dists.lognormal.logcdf.factory( 10.0, 2.0 );\nvar y = mylogcdf( 10.0 )\n","base.dists.lognormal.logpdf":"var y = base.dists.lognormal.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.logpdf( 1.0, 0.0, 1.0 )\ny = base.dists.lognormal.logpdf( 1.0, 3.0, 1.0 )\ny = base.dists.lognormal.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.lognormal.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.logpdf( 0.0, 0.0, NaN )\ny = base.dists.lognormal.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.logpdf( 2.0, 0.0, 0.0 )\n","base.dists.lognormal.logpdf.factory":"var mylogPDF = base.dists.lognormal.logpdf.factory( 4.0, 2.0 );\nvar y = mylogPDF( 10.0 )\ny = mylogPDF( 2.0 )\n","base.dists.lognormal.mean":"var y = base.dists.lognormal.mean( 0.0, 1.0 )\ny = base.dists.lognormal.mean( 4.0, 2.0 )\ny = base.dists.lognormal.mean( NaN, 1.0 )\ny = base.dists.lognormal.mean( 0.0, NaN )\ny = base.dists.lognormal.mean( 0.0, 0.0 )\n","base.dists.lognormal.median":"var y = base.dists.lognormal.median( 0.0, 1.0 )\ny = base.dists.lognormal.median( 5.0, 2.0 )\ny = base.dists.lognormal.median( NaN, 1.0 )\ny = base.dists.lognormal.median( 0.0, NaN )\ny = base.dists.lognormal.median( 0.0, 0.0 )\n","base.dists.lognormal.mode":"var y = base.dists.lognormal.mode( 0.0, 1.0 )\ny = base.dists.lognormal.mode( 5.0, 2.0 )\ny = base.dists.lognormal.mode( NaN, 1.0 )\ny = base.dists.lognormal.mode( 0.0, NaN )\ny = base.dists.lognormal.mode( 0.0, 0.0 )\n","base.dists.lognormal.pdf":"var y = base.dists.lognormal.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.lognormal.pdf( 1.0, 0.0, 1.0 )\ny = base.dists.lognormal.pdf( 1.0, 3.0, 1.0 )\ny = base.dists.lognormal.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.lognormal.pdf( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.pdf( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.pdf( 0.0, 0.0, NaN )\ny = base.dists.lognormal.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.lognormal.pdf( 2.0, 0.0, 0.0 )\n","base.dists.lognormal.pdf.factory":"var myPDF = base.dists.lognormal.pdf.factory( 4.0, 2.0 );\nvar y = myPDF( 10.0 )\ny = myPDF( 2.0 )\n","base.dists.lognormal.quantile":"var y = base.dists.lognormal.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.lognormal.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( NaN, 0.0, 1.0 )\ny = base.dists.lognormal.quantile( 0.0, NaN, 1.0 )\ny = base.dists.lognormal.quantile( 0.0, 0.0, NaN )\ny = base.dists.lognormal.quantile( 0.5, 0.0, -1.0 )\ny = base.dists.lognormal.quantile( 0.5, 0.0, 0.0 )\n","base.dists.lognormal.quantile.factory":"var myQuantile = base.dists.lognormal.quantile.factory( 4.0, 2.0 );\nvar y = myQuantile( 0.2 )\ny = myQuantile( 0.8 )\n","base.dists.lognormal.skewness":"var y = base.dists.lognormal.skewness( 0.0, 1.0 )\ny = base.dists.lognormal.skewness( 5.0, 2.0 )\ny = base.dists.lognormal.skewness( NaN, 1.0 )\ny = base.dists.lognormal.skewness( 0.0, NaN )\ny = base.dists.lognormal.skewness( 0.0, 0.0 )\n","base.dists.lognormal.stdev":"var y = base.dists.lognormal.stdev( 0.0, 1.0 )\ny = base.dists.lognormal.stdev( 4.0, 2.0 )\ny = base.dists.lognormal.stdev( NaN, 1.0 )\ny = base.dists.lognormal.stdev( 0.0, NaN )\ny = base.dists.lognormal.stdev( 0.0, 0.0 )\n","base.dists.lognormal.variance":"var y = base.dists.lognormal.variance( 0.0, 1.0 )\ny = base.dists.lognormal.variance( 4.0, 2.0 )\ny = base.dists.lognormal.variance( NaN, 1.0 )\ny = base.dists.lognormal.variance( 0.0, NaN )\ny = base.dists.lognormal.variance( 0.0, 0.0 )\n","base.dists.negativeBinomial.cdf":"var y = base.dists.negativeBinomial.cdf( 5.0, 20.0, 0.8 )\ny = base.dists.negativeBinomial.cdf( 21.0, 20.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( 5.0, 10.0, 0.4 )\ny = base.dists.negativeBinomial.cdf( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.cdf( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.cdf( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.cdf( 2.0, 0.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( 2.0, -2.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.cdf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.cdf( 0.0, 20.0, NaN )\ny = base.dists.negativeBinomial.cdf( 2.0, 20, -1.0 )\ny = base.dists.negativeBinomial.cdf( 2.0, 20, 1.5 )\n","base.dists.negativeBinomial.cdf.factory":"var myCDF = base.dists.negativeBinomial.cdf.factory( 10, 0.5 );\nvar y = myCDF( 3.0 )\ny = myCDF( 11.0 )\n","base.dists.negativeBinomial.kurtosis":"var v = base.dists.negativeBinomial.kurtosis( 100, 0.2 )\nv = base.dists.negativeBinomial.kurtosis( 20, 0.5 )\n","base.dists.negativeBinomial.logpmf":"var y = base.dists.negativeBinomial.logpmf( 5.0, 20.0, 0.8 )\ny = base.dists.negativeBinomial.logpmf( 21.0, 20.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 5.0, 10.0, 0.4 )\ny = base.dists.negativeBinomial.logpmf( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.logpmf( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.logpmf( 2.0, 0.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 2.0, -2.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 2.0, 20, -1.0 )\ny = base.dists.negativeBinomial.logpmf( 2.0, 20, 1.5 )\ny = base.dists.negativeBinomial.logpmf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.logpmf( 0.0, 20.0, NaN )\n","base.dists.negativeBinomial.logpmf.factory":"var mylogPMF = base.dists.negativeBinomial.logpmf.factory( 10, 0.5 );\nvar y = mylogPMF( 3.0 )\ny = mylogPMF( 5.0 )\n","base.dists.negativeBinomial.mean":"var v = base.dists.negativeBinomial.mean( 100, 0.2 )\nv = base.dists.negativeBinomial.mean( 20, 0.5 )\n","base.dists.negativeBinomial.mgf":"var y = base.dists.negativeBinomial.mgf( 0.05, 20.0, 0.8 )\ny = base.dists.negativeBinomial.mgf( 0.1, 20.0, 0.1 )\ny = base.dists.negativeBinomial.mgf( 0.5, 10.0, 0.4 )\ny = base.dists.negativeBinomial.mgf( 0.1, 0.0, 0.5 )\ny = base.dists.negativeBinomial.mgf( 0.1, -2.0, 0.5 )\ny = base.dists.negativeBinomial.mgf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.mgf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.mgf( 0.0, 20.0, NaN )\ny = base.dists.negativeBinomial.mgf( 0.2, 20, -1.0 )\ny = base.dists.negativeBinomial.mgf( 0.2, 20, 1.5 )\n","base.dists.negativeBinomial.mgf.factory":"var myMGF = base.dists.negativeBinomial.mgf.factory( 4.3, 0.4 );\nvar y = myMGF( 0.2 )\ny = myMGF( 0.4 )\n","base.dists.negativeBinomial.mode":"var v = base.dists.negativeBinomial.mode( 100, 0.2 )\nv = base.dists.negativeBinomial.mode( 20, 0.5 )\n","base.dists.negativeBinomial.NegativeBinomial":"var nbinomial = base.dists.negativeBinomial.NegativeBinomial( 8.0, 0.5 );\nnbinomial.r\nnbinomial.p\nnbinomial.kurtosis\nnbinomial.mean\nnbinomial.mode\nnbinomial.skewness\nnbinomial.stdev\nnbinomial.variance\nnbinomial.cdf( 2.9 )\nnbinomial.logpmf( 3.0 )\nnbinomial.mgf( 0.2 )\nnbinomial.pmf( 3.0 )\nnbinomial.quantile( 0.8 )\n","base.dists.negativeBinomial.pmf":"var y = base.dists.negativeBinomial.pmf( 5.0, 20.0, 0.8 )\ny = base.dists.negativeBinomial.pmf( 21.0, 20.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 5.0, 10.0, 0.4 )\ny = base.dists.negativeBinomial.pmf( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.pmf( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.pmf( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.pmf( 2.0, 0.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 2.0, -2.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 2.0, 20, -1.0 )\ny = base.dists.negativeBinomial.pmf( 2.0, 20, 1.5 )\ny = base.dists.negativeBinomial.pmf( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.pmf( 0.0, NaN, 0.5 )\ny = base.dists.negativeBinomial.pmf( 0.0, 20.0, NaN )\n","base.dists.negativeBinomial.pmf.factory":"var myPMF = base.dists.negativeBinomial.pmf.factory( 10, 0.5 );\nvar y = myPMF( 3.0 )\ny = myPMF( 5.0 )\n","base.dists.negativeBinomial.quantile":"var y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.2 )\ny = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.8 )\ny = base.dists.negativeBinomial.quantile( 0.5, 10.0, 0.4 )\ny = base.dists.negativeBinomial.quantile( 0.0, 10.0, 0.9 )\ny = base.dists.negativeBinomial.quantile( 1.1, 20.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( -0.1, 20.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 21.0, 15.5, 0.5 )\ny = base.dists.negativeBinomial.quantile( 5.0, 7.4, 0.4 )\ny = base.dists.negativeBinomial.quantile( 0.5, 0.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.5, -2.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.3, 20.0, -1.0 )\ny = base.dists.negativeBinomial.quantile( 0.3, 20.0, 1.5 )\ny = base.dists.negativeBinomial.quantile( NaN, 20.0, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.3, NaN, 0.5 )\ny = base.dists.negativeBinomial.quantile( 0.3, 20.0, NaN )\n","base.dists.negativeBinomial.quantile.factory":"var myQuantile = base.dists.negativeBinomial.quantile.factory( 10.0, 0.5 );\nvar y = myQuantile( 0.1 )\ny = myQuantile( 0.9 )\n","base.dists.negativeBinomial.skewness":"var v = base.dists.negativeBinomial.skewness( 100, 0.2 )\nv = base.dists.negativeBinomial.skewness( 20, 0.5 )\n","base.dists.negativeBinomial.stdev":"var v = base.dists.negativeBinomial.stdev( 100, 0.2 )\nv = base.dists.negativeBinomial.stdev( 20, 0.5 )\n","base.dists.negativeBinomial.variance":"var v = base.dists.negativeBinomial.variance( 100, 0.2 )\nv = base.dists.negativeBinomial.variance( 20, 0.5 )\n","base.dists.normal.cdf":"var y = base.dists.normal.cdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.cdf( -1.0, -1.0, 2.0 )\ny = base.dists.normal.cdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.cdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.cdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.cdf( 0.0, 0.0, NaN )\ny = base.dists.normal.cdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.cdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.cdf( 8.0, 8.0, 0.0 )\ny = base.dists.normal.cdf( 10.0, 8.0, 0.0 )\n","base.dists.normal.cdf.factory":"var myCDF = base.dists.normal.cdf.factory( 10.0, 2.0 );\nvar y = myCDF( 10.0 )\n","base.dists.normal.entropy":"var y = base.dists.normal.entropy( 0.0, 1.0 )\ny = base.dists.normal.entropy( 4.0, 3.0 )\ny = base.dists.normal.entropy( NaN, 1.0 )\ny = base.dists.normal.entropy( 0.0, NaN )\ny = base.dists.normal.entropy( 0.0, 0.0 )\n","base.dists.normal.kurtosis":"var y = base.dists.normal.kurtosis( 0.0, 1.0 )\ny = base.dists.normal.kurtosis( 4.0, 3.0 )\ny = base.dists.normal.kurtosis( NaN, 1.0 )\ny = base.dists.normal.kurtosis( 0.0, NaN )\ny = base.dists.normal.kurtosis( 0.0, 0.0 )\n","base.dists.normal.logcdf":"var y = base.dists.normal.logcdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.logcdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.logcdf( 0.0, 0.0, NaN )\ny = base.dists.normal.logcdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.logcdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.logcdf( 8.0, 8.0, 0.0 )\n","base.dists.normal.logcdf.factory":"var mylogcdf = base.dists.normal.logcdf.factory( 10.0, 2.0 );\nvar y = mylogcdf( 10.0 )\n","base.dists.normal.logpdf":"var y = base.dists.normal.logpdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.logpdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.logpdf( 0.0, 0.0, NaN )\ny = base.dists.normal.logpdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.logpdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.logpdf( 8.0, 8.0, 0.0 )\n","base.dists.normal.logpdf.factory":"var myLogPDF = base.dists.normal.logpdf.factory( 10.0, 2.0 );\nvar y = myLogPDF( 10.0 )\n","base.dists.normal.mean":"var y = base.dists.normal.mean( 0.0, 1.0 )\ny = base.dists.normal.mean( 4.0, 2.0 )\ny = base.dists.normal.mean( NaN, 1.0 )\ny = base.dists.normal.mean( 0.0, NaN )\ny = base.dists.normal.mean( 0.0, 0.0 )\n","base.dists.normal.median":"var y = base.dists.normal.median( 0.0, 1.0 )\ny = base.dists.normal.median( 4.0, 2.0 )\ny = base.dists.normal.median( NaN, 1.0 )\ny = base.dists.normal.median( 0.0, NaN )\ny = base.dists.normal.median( 0.0, 0.0 )\n","base.dists.normal.mgf":"var y = base.dists.normal.mgf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.mgf( 0.0, 0.0, 1.0 )\ny = base.dists.normal.mgf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.mgf( NaN, 0.0, 1.0 )\ny = base.dists.normal.mgf( 0.0, NaN, 1.0 )\ny = base.dists.normal.mgf( 0.0, 0.0, NaN )\ny = base.dists.normal.mgf( 2.0, 0.0, 0.0 )\n","base.dists.normal.mgf.factory":"var myMGF = base.dists.normal.mgf.factory( 4.0, 2.0 );\nvar y = myMGF( 1.0 )\ny = myMGF( 0.5 )\n","base.dists.normal.mode":"var y = base.dists.normal.mode( 0.0, 1.0 )\ny = base.dists.normal.mode( 4.0, 2.0 )\ny = base.dists.normal.mode( NaN, 1.0 )\ny = base.dists.normal.mode( 0.0, NaN )\ny = base.dists.normal.mode( 0.0, 0.0 )\n","base.dists.normal.Normal":"var normal = base.dists.normal.Normal( -2.0, 3.0 );\nnormal.mu\nnormal.sigma\nnormal.entropy\nnormal.kurtosis\nnormal.mean\nnormal.median\nnormal.mode\nnormal.skewness\nnormal.stdev\nnormal.variance\nnormal.cdf( 0.8 )\nnormal.logcdf( 0.8 )\nnormal.logpdf( 2.0 )\nnormal.mgf( 0.2 )\nnormal.pdf( 2.0 )\nnormal.quantile( 0.9 )\n","base.dists.normal.pdf":"var y = base.dists.normal.pdf( 2.0, 0.0, 1.0 )\ny = base.dists.normal.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.normal.pdf( NaN, 0.0, 1.0 )\ny = base.dists.normal.pdf( 0.0, NaN, 1.0 )\ny = base.dists.normal.pdf( 0.0, 0.0, NaN )\ny = base.dists.normal.pdf( 2.0, 0.0, -1.0 )\ny = base.dists.normal.pdf( 2.0, 8.0, 0.0 )\ny = base.dists.normal.pdf( 8.0, 8.0, 0.0 )\n","base.dists.normal.pdf.factory":"var myPDF = base.dists.normal.pdf.factory( 10.0, 2.0 );\nvar y = myPDF( 10.0 )\n","base.dists.normal.quantile":"var y = base.dists.normal.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.normal.quantile( 0.5, 4.0, 2.0 )\ny = base.dists.normal.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.normal.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.normal.quantile( NaN, 0.0, 1.0 )\ny = base.dists.normal.quantile( 0.0, NaN, 1.0 )\ny = base.dists.normal.quantile( 0.0, 0.0, NaN )\ny = base.dists.normal.quantile( 0.5, 0.0, -1.0 )\ny = base.dists.normal.quantile( 0.3, 8.0, 0.0 )\ny = base.dists.normal.quantile( 0.9, 8.0, 0.0 )\n","base.dists.normal.quantile.factory":"var myQuantile = base.dists.normal.quantile.factory( 10.0, 2.0 );\nvar y = myQuantile( 0.5 )\n","base.dists.normal.skewness":"var y = base.dists.normal.skewness( 0.0, 1.0 )\ny = base.dists.normal.skewness( 4.0, 3.0 )\ny = base.dists.normal.skewness( NaN, 1.0 )\ny = base.dists.normal.skewness( 0.0, NaN )\ny = base.dists.normal.skewness( 0.0, 0.0 )\n","base.dists.normal.stdev":"var y = base.dists.normal.stdev( 0.0, 1.0 )\ny = base.dists.normal.stdev( 4.0, 3.0 )\ny = base.dists.normal.stdev( NaN, 1.0 )\ny = base.dists.normal.stdev( 0.0, NaN )\ny = base.dists.normal.stdev( 0.0, 0.0 )\n","base.dists.normal.variance":"var y = base.dists.normal.variance( 0.0, 1.0 )\ny = base.dists.normal.variance( 4.0, 3.0 )\ny = base.dists.normal.variance( NaN, 1.0 )\ny = base.dists.normal.variance( 0.0, NaN )\ny = base.dists.normal.variance( 0.0, 0.0 )\n","base.dists.pareto1.cdf":"var y = base.dists.pareto1.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.pareto1.cdf( 5.0, 2.0, 4.0 )\ny = base.dists.pareto1.cdf( 4.0, 2.0, 2.0 )\ny = base.dists.pareto1.cdf( 1.9, 2.0, 2.0 )\ny = base.dists.pareto1.cdf( PINF, 4.0, 2.0 )\ny = base.dists.pareto1.cdf( 2.0, -1.0, 0.5 )\ny = base.dists.pareto1.cdf( 2.0, 0.5, -1.0 )\ny = base.dists.pareto1.cdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.cdf( 0.0, NaN, 1.0 )\ny = base.dists.pareto1.cdf( 0.0, 1.0, NaN )\n","base.dists.pareto1.cdf.factory":"var myCDF = base.dists.pareto1.cdf.factory( 10.0, 2.0 );\nvar y = myCDF( 3.0 )\ny = myCDF( 2.5 )\n","base.dists.pareto1.entropy":"var v = base.dists.pareto1.entropy( 0.8, 1.0 )\nv = base.dists.pareto1.entropy( 4.0, 12.0 )\nv = base.dists.pareto1.entropy( 8.0, 2.0 )\n","base.dists.pareto1.kurtosis":"var v = base.dists.pareto1.kurtosis( 5.0, 1.0 )\nv = base.dists.pareto1.kurtosis( 4.5, 12.0 )\nv = base.dists.pareto1.kurtosis( 8.0, 2.0 )\n","base.dists.pareto1.logcdf":"var y = base.dists.pareto1.logcdf( 2.0, 1.0, 1.0 )\ny = base.dists.pareto1.logcdf( 5.0, 2.0, 4.0 )\ny = base.dists.pareto1.logcdf( 4.0, 2.0, 2.0 )\ny = base.dists.pareto1.logcdf( 1.9, 2.0, 2.0 )\ny = base.dists.pareto1.logcdf( PINF, 4.0, 2.0 )\ny = base.dists.pareto1.logcdf( 2.0, -1.0, 0.5 )\ny = base.dists.pareto1.logcdf( 2.0, 0.5, -1.0 )\ny = base.dists.pareto1.logcdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.pareto1.logcdf( 0.0, 1.0, NaN )\n","base.dists.pareto1.logcdf.factory":"var mylogCDF = base.dists.pareto1.logcdf.factory( 10.0, 2.0 );\nvar y = mylogCDF( 3.0 )\ny = mylogCDF( 2.5 )\n","base.dists.pareto1.logpdf":"var y = base.dists.pareto1.logpdf( 4.0, 1.0, 1.0 )\ny = base.dists.pareto1.logpdf( 20.0, 1.0, 10.0 )\ny = base.dists.pareto1.logpdf( 7.0, 2.0, 6.0 )\ny = base.dists.pareto1.logpdf( 7.0, 6.0, 3.0 )\ny = base.dists.pareto1.logpdf( 1.0, 4.0, 2.0 )\ny = base.dists.pareto1.logpdf( 1.5, 4.0, 2.0 )\ny = base.dists.pareto1.logpdf( 0.5, -1.0, 0.5 )\ny = base.dists.pareto1.logpdf( 0.5, 0.5, -1.0 )\ny = base.dists.pareto1.logpdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.logpdf( 0.5, NaN, 1.0 )\ny = base.dists.pareto1.logpdf( 0.5, 1.0, NaN )\n","base.dists.pareto1.logpdf.factory":"var mylogPDF = base.dists.pareto1.logpdf.factory( 0.5, 0.5 );\nvar y = mylogPDF( 0.8 )\ny = mylogPDF( 2.0 )\n","base.dists.pareto1.mean":"var v = base.dists.pareto1.mean( 0.8, 1.0 )\nv = base.dists.pareto1.mean( 4.0, 12.0 )\nv = base.dists.pareto1.mean( 8.0, 2.0 )\n","base.dists.pareto1.median":"var v = base.dists.pareto1.median( 0.8, 1.0 )\nv = base.dists.pareto1.median( 4.0, 12.0 )\nv = base.dists.pareto1.median( 8.0, 2.0 )\n","base.dists.pareto1.mode":"var v = base.dists.pareto1.mode( 0.8, 1.0 )\nv = base.dists.pareto1.mode( 4.0, 12.0 )\nv = base.dists.pareto1.mode( 8.0, 2.0 )\n","base.dists.pareto1.Pareto1":"var pareto1 = base.dists.pareto1.Pareto1( 6.0, 5.0 );\npareto1.alpha\npareto1.beta\npareto1.entropy\npareto1.kurtosis\npareto1.mean\npareto1.median\npareto1.mode\npareto1.skewness\npareto1.variance\npareto1.cdf( 7.0 )\npareto1.logcdf( 7.0 )\npareto1.logpdf( 5.0 )\npareto1.pdf( 5.0 )\npareto1.quantile( 0.8 )\n","base.dists.pareto1.pdf":"var y = base.dists.pareto1.pdf( 4.0, 1.0, 1.0 )\ny = base.dists.pareto1.pdf( 20.0, 1.0, 10.0 )\ny = base.dists.pareto1.pdf( 7.0, 2.0, 6.0 )\ny = base.dists.pareto1.pdf( 7.0, 6.0, 3.0 )\ny = base.dists.pareto1.pdf( 1.0, 4.0, 2.0 )\ny = base.dists.pareto1.pdf( 1.5, 4.0, 2.0 )\ny = base.dists.pareto1.pdf( 0.5, -1.0, 0.5 )\ny = base.dists.pareto1.pdf( 0.5, 0.5, -1.0 )\ny = base.dists.pareto1.pdf( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.pdf( 0.5, NaN, 1.0 )\ny = base.dists.pareto1.pdf( 0.5, 1.0, NaN )\n","base.dists.pareto1.pdf.factory":"var myPDF = base.dists.pareto1.pdf.factory( 0.5, 0.5 );\nvar y = myPDF( 0.8 )\ny = myPDF( 2.0 )\n","base.dists.pareto1.quantile":"var y = base.dists.pareto1.quantile( 0.8, 2.0, 1.0 )\ny = base.dists.pareto1.quantile( 0.8, 1.0, 10.0 )\ny = base.dists.pareto1.quantile( 0.1, 1.0, 10.0 )\ny = base.dists.pareto1.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.pareto1.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.pareto1.quantile( NaN, 1.0, 1.0 )\ny = base.dists.pareto1.quantile( 0.5, NaN, 1.0 )\ny = base.dists.pareto1.quantile( 0.5, 1.0, NaN )\ny = base.dists.pareto1.quantile( 0.5, -1.0, 1.0 )\ny = base.dists.pareto1.quantile( 0.5, 1.0, -1.0 )\n","base.dists.pareto1.quantile.factory":"var myQuantile = base.dists.pareto1.quantile.factory( 2.5, 0.5 );\nvar y = myQuantile( 0.5 )\ny = myQuantile( 0.8 )\n","base.dists.pareto1.skewness":"var v = base.dists.pareto1.skewness( 3.5, 1.0 )\nv = base.dists.pareto1.skewness( 4.0, 12.0 )\nv = base.dists.pareto1.skewness( 8.0, 2.0 )\n","base.dists.pareto1.stdev":"var v = base.dists.pareto1.stdev( 0.8, 1.0 )\nv = base.dists.pareto1.stdev( 4.0, 12.0 )\nv = base.dists.pareto1.stdev( 8.0, 2.0 )\n","base.dists.pareto1.variance":"var v = base.dists.pareto1.variance( 0.8, 1.0 )\nv = base.dists.pareto1.variance( 4.0, 12.0 )\nv = base.dists.pareto1.variance( 8.0, 2.0 )\n","base.dists.poisson.cdf":"var y = base.dists.poisson.cdf( 2.0, 0.5 )\ny = base.dists.poisson.cdf( 2.0, 10.0 )\ny = base.dists.poisson.cdf( -1.0, 4.0 )\ny = base.dists.poisson.cdf( NaN, 1.0 )\ny = base.dists.poisson.cdf( 0.0, NaN )\ny = base.dists.poisson.cdf( 2.0, -1.0 )\ny = base.dists.poisson.cdf( -2.0, 0.0 )\ny = base.dists.poisson.cdf( 0.0, 0.0 )\ny = base.dists.poisson.cdf( 10.0, 0.0 )\n","base.dists.poisson.cdf.factory":"var mycdf = base.dists.poisson.cdf.factory( 5.0 );\nvar y = mycdf( 3.0 )\ny = mycdf( 8.0 )\n","base.dists.poisson.entropy":"var v = base.dists.poisson.entropy( 11.0 )\nv = base.dists.poisson.entropy( 4.5 )\n","base.dists.poisson.kurtosis":"var v = base.dists.poisson.kurtosis( 11.0 )\nv = base.dists.poisson.kurtosis( 4.5 )\n","base.dists.poisson.logpmf":"var y = base.dists.poisson.logpmf( 4.0, 3.0 )\ny = base.dists.poisson.logpmf( 1.0, 3.0 )\ny = base.dists.poisson.logpmf( -1.0, 2.0 )\ny = base.dists.poisson.logpmf( 0.0, NaN )\ny = base.dists.poisson.logpmf( NaN, 0.5 )\ny = base.dists.poisson.logpmf( 2.0, -0.5 )\ny = base.dists.poisson.logpmf( 2.0, 0.0 )\ny = base.dists.poisson.logpmf( 0.0, 0.0 )\n","base.dists.poisson.logpmf.factory":"var mylogpmf = base.dists.poisson.logpmf.factory( 1.0 );\nvar y = mylogpmf( 3.0 )\ny = mylogpmf( 1.0 )\n","base.dists.poisson.mean":"var v = base.dists.poisson.mean( 11.0 )\nv = base.dists.poisson.mean( 4.5 )\n","base.dists.poisson.median":"var v = base.dists.poisson.median( 11.0 )\nv = base.dists.poisson.median( 4.5 )\n","base.dists.poisson.mgf":"var y = base.dists.poisson.mgf( 1.0, 1.5 )\ny = base.dists.poisson.mgf( 0.5, 0.5 )\ny = base.dists.poisson.mgf( NaN, 0.5 )\ny = base.dists.poisson.mgf( 0.0, NaN )\ny = base.dists.poisson.mgf( -2.0, -1.0 )\n","base.dists.poisson.mgf.factory":"var myMGF = base.dists.poisson.mgf.factory( 2.0 );\nvar y = myMGF( 0.1 )\n","base.dists.poisson.mode":"var v = base.dists.poisson.mode( 11.0 )\nv = base.dists.poisson.mode( 4.5 )\n","base.dists.poisson.pmf":"var y = base.dists.poisson.pmf( 4.0, 3.0 )\ny = base.dists.poisson.pmf( 1.0, 3.0 )\ny = base.dists.poisson.pmf( -1.0, 2.0 )\ny = base.dists.poisson.pmf( 0.0, NaN )\ny = base.dists.poisson.pmf( NaN, 0.5 )\ny = base.dists.poisson.pmf( 2.0, -0.5 )\ny = base.dists.poisson.pmf( 2.0, 0.0 )\ny = base.dists.poisson.pmf( 0.0, 0.0 )\n","base.dists.poisson.pmf.factory":"var mypmf = base.dists.poisson.pmf.factory( 1.0 );\nvar y = mypmf( 3.0 )\ny = mypmf( 1.0 )\n","base.dists.poisson.Poisson":"var poisson = base.dists.poisson.Poisson( 6.0 );\npoisson.lambda\npoisson.entropy\npoisson.kurtosis\npoisson.mean\npoisson.median\npoisson.mode\npoisson.skewness\npoisson.stdev\npoisson.variance\npoisson.cdf( 4.0 )\npoisson.logpmf( 2.0 )\npoisson.mgf( 0.5 )\npoisson.pmf( 2.0 )\npoisson.quantile( 0.5 )\n","base.dists.poisson.quantile":"var y = base.dists.poisson.quantile( 0.5, 2.0 )\ny = base.dists.poisson.quantile( 0.9, 4.0 )\ny = base.dists.poisson.quantile( 0.1, 200.0 )\ny = base.dists.poisson.quantile( 1.1, 0.0 )\ny = base.dists.poisson.quantile( -0.2, 0.0 )\ny = base.dists.poisson.quantile( NaN, 0.5 )\ny = base.dists.poisson.quantile( 0.0, NaN )\ny = base.dists.poisson.quantile( 2.0, -1.0 )\ny = base.dists.poisson.quantile( 0.1, 0.0 )\ny = base.dists.poisson.quantile( 0.9, 0.0 )\n","base.dists.poisson.quantile.factory":"var myQuantile = base.dists.poisson.quantile.factory( 0.4 );\nvar y = myQuantile( 0.4 )\ny = myQuantile( 1.0 )\n","base.dists.poisson.skewness":"var v = base.dists.poisson.skewness( 11.0 )\nv = base.dists.poisson.skewness( 4.5 )\n","base.dists.poisson.stdev":"var v = base.dists.poisson.stdev( 11.0 )\nv = base.dists.poisson.stdev( 4.5 )\n","base.dists.poisson.variance":"var v = base.dists.poisson.variance( 11.0 )\nv = base.dists.poisson.variance( 4.5 )\n","base.dists.rayleigh.cdf":"var y = base.dists.rayleigh.cdf( 2.0, 3.0 )\ny = base.dists.rayleigh.cdf( 1.0, 2.0 )\ny = base.dists.rayleigh.cdf( -1.0, 4.0 )\ny = base.dists.rayleigh.cdf( NaN, 1.0 )\ny = base.dists.rayleigh.cdf( 0.0, NaN )\ny = base.dists.rayleigh.cdf( 2.0, -1.0 )\ny = base.dists.rayleigh.cdf( -2.0, 0.0 )\ny = base.dists.rayleigh.cdf( 0.0, 0.0 )\ny = base.dists.rayleigh.cdf( 2.0, 0.0 )\n","base.dists.rayleigh.cdf.factory":"var myCDF = base.dists.rayleigh.cdf.factory( 0.5 );\nvar y = myCDF( 1.0 )\ny = myCDF( 0.5 )\n","base.dists.rayleigh.entropy":"var v = base.dists.rayleigh.entropy( 11.0 )\nv = base.dists.rayleigh.entropy( 4.5 )\n","base.dists.rayleigh.kurtosis":"var v = base.dists.rayleigh.kurtosis( 11.0 )\nv = base.dists.rayleigh.kurtosis( 4.5 )\n","base.dists.rayleigh.logcdf":"var y = base.dists.rayleigh.logcdf( 2.0, 3.0 )\ny = base.dists.rayleigh.logcdf( 1.0, 2.0 )\ny = base.dists.rayleigh.logcdf( -1.0, 4.0 )\ny = base.dists.rayleigh.logcdf( NaN, 1.0 )\ny = base.dists.rayleigh.logcdf( 0.0, NaN )\ny = base.dists.rayleigh.logcdf( 2.0, -1.0 )\n","base.dists.rayleigh.logcdf.factory":"var mylogcdf = base.dists.rayleigh.logcdf.factory( 0.5 );\nvar y = mylogcdf( 1.0 )\ny = mylogcdf( 0.5 )\n","base.dists.rayleigh.logpdf":"var y = base.dists.rayleigh.logpdf( 0.3, 1.0 )\ny = base.dists.rayleigh.logpdf( 2.0, 0.8 )\ny = base.dists.rayleigh.logpdf( -1.0, 0.5 )\ny = base.dists.rayleigh.logpdf( 0.0, NaN )\ny = base.dists.rayleigh.logpdf( NaN, 2.0 )\ny = base.dists.rayleigh.logpdf( 2.0, -1.0 )\n","base.dists.rayleigh.logpdf.factory":"var mylogpdf = base.dists.rayleigh.logpdf.factory( 4.0 );\nvar y = mylogpdf( 6.0 )\ny = mylogpdf( 4.0 )\n","base.dists.rayleigh.mean":"var v = base.dists.rayleigh.mean( 11.0 )\nv = base.dists.rayleigh.mean( 4.5 )\n","base.dists.rayleigh.median":"var v = base.dists.rayleigh.median( 11.0 )\nv = base.dists.rayleigh.median( 4.5 )\n","base.dists.rayleigh.mgf":"var y = base.dists.rayleigh.mgf( 1.0, 3.0 )\ny = base.dists.rayleigh.mgf( 1.0, 2.0 )\ny = base.dists.rayleigh.mgf( -1.0, 4.0 )\ny = base.dists.rayleigh.mgf( NaN, 1.0 )\ny = base.dists.rayleigh.mgf( 0.0, NaN )\ny = base.dists.rayleigh.mgf( 0.5, -1.0 )\n","base.dists.rayleigh.mgf.factory":"var myMGF = base.dists.rayleigh.mgf.factory( 0.5 );\nvar y = myMGF( 1.0 )\ny = myMGF( 0.5 )\n","base.dists.rayleigh.mode":"var v = base.dists.rayleigh.mode( 11.0 )\nv = base.dists.rayleigh.mode( 4.5 )\n","base.dists.rayleigh.pdf":"var y = base.dists.rayleigh.pdf( 0.3, 1.0 )\ny = base.dists.rayleigh.pdf( 2.0, 0.8 )\ny = base.dists.rayleigh.pdf( -1.0, 0.5 )\ny = base.dists.rayleigh.pdf( 0.0, NaN )\ny = base.dists.rayleigh.pdf( NaN, 2.0 )\ny = base.dists.rayleigh.pdf( 2.0, -1.0 )\ny = base.dists.rayleigh.pdf( -2.0, 0.0 )\ny = base.dists.rayleigh.pdf( 0.0, 0.0 )\ny = base.dists.rayleigh.pdf( 2.0, 0.0 )\n","base.dists.rayleigh.pdf.factory":"var myPDF = base.dists.rayleigh.pdf.factory( 4.0 );\nvar y = myPDF( 6.0 )\ny = myPDF( 4.0 )\n","base.dists.rayleigh.quantile":"var y = base.dists.rayleigh.quantile( 0.8, 1.0 )\ny = base.dists.rayleigh.quantile( 0.5, 4.0 )\ny = base.dists.rayleigh.quantile( 1.1, 1.0 )\ny = base.dists.rayleigh.quantile( -0.2, 1.0 )\ny = base.dists.rayleigh.quantile( NaN, 1.0 )\ny = base.dists.rayleigh.quantile( 0.0, NaN )\ny = base.dists.rayleigh.quantile( 0.5, -1.0 )\n","base.dists.rayleigh.quantile.factory":"var myQuantile = base.dists.rayleigh.quantile.factory( 0.4 );\nvar y = myQuantile( 0.4 )\ny = myQuantile( 1.0 )\n","base.dists.rayleigh.Rayleigh":"var rayleigh = base.dists.rayleigh.Rayleigh( 6.0 );\nrayleigh.sigma\nrayleigh.entropy\nrayleigh.kurtosis\nrayleigh.mean\nrayleigh.median\nrayleigh.mode\nrayleigh.skewness\nrayleigh.stdev\nrayleigh.variance\nrayleigh.cdf( 1.0 )\nrayleigh.logcdf( 1.0 )\nrayleigh.logpdf( 1.5 )\nrayleigh.mgf( -0.5 )\nrayleigh.pdf( 1.5 )\nrayleigh.quantile( 0.5 )\n","base.dists.rayleigh.skewness":"var v = base.dists.rayleigh.skewness( 11.0 )\nv = base.dists.rayleigh.skewness( 4.5 )\n","base.dists.rayleigh.stdev":"var v = base.dists.rayleigh.stdev( 9.0 )\nv = base.dists.rayleigh.stdev( 4.5 )\n","base.dists.rayleigh.variance":"var v = base.dists.rayleigh.variance( 9.0 )\nv = base.dists.rayleigh.variance( 4.5 )\n","base.dists.signrank.cdf":"var y = base.dists.signrank.cdf( 3, 7 )\ny = base.dists.signrank.cdf( 1.8, 3 )\ny = base.dists.signrank.cdf( -1.0, 40 )\ny = base.dists.signrank.cdf( NaN, 10 )\ny = base.dists.signrank.cdf( 0.0, NaN )\n","base.dists.signrank.cdf.factory":"var myCDF = base.dists.signrank.cdf.factory( 8 );\nvar y = myCDF( 5.7 )\ny = myCDF( 2.2 )\n","base.dists.signrank.pdf":"var y = base.dists.signrank.pdf( 3, 7 )\ny = base.dists.signrank.pdf( 1.8, 3 )\ny = base.dists.signrank.pdf( -1.0, 40 )\ny = base.dists.signrank.pdf( NaN, 10 )\ny = base.dists.signrank.pdf( 0.0, NaN )\n","base.dists.signrank.pdf.factory":"var myPDF = base.dists.signrank.pdf.factory( 8 );\nvar y = myPDF( 6.0 )\ny = myPDF( 2.0 )\n","base.dists.signrank.quantile":"var y = base.dists.signrank.quantile( 0.8, 5 )\ny = base.dists.signrank.quantile( 0.5, 4 )\ny = base.dists.signrank.quantile( 1.1, 5 )\ny = base.dists.signrank.quantile( -0.2, 5 )\ny = base.dists.signrank.quantile( NaN, 5 )\ny = base.dists.signrank.quantile( 0.0, NaN )\n","base.dists.signrank.quantile.factory":"var myQuantile = base.dists.signrank.quantile.factory( 8 );\nvar y = myQuantile( 0.4 )\ny = myQuantile( 1.0 )\n","base.dists.studentizedRange.cdf":"var y = base.dists.studentizedRange.cdf( 0.5, 3.0, 2.0 )\ny = base.dists.studentizedRange.cdf( 12.1, 17.0, 2.0 )\n","base.dists.studentizedRange.cdf.factory":"var mycdf = base.dists.studentizedRange.cdf.factory( 3.0, 2.0 );\nvar y = mycdf( 3.0 )\ny = mycdf( 1.0 )\n","base.dists.studentizedRange.quantile":"var y = quantile( 0.5, 3.0, 2.0 )\ny = quantile( 0.9, 17.0, 2.0 )\ny = quantile( 0.5, 3.0, 2.0, 2 )\ny = base.dists.studentizedRange.quantile( -0.2, 3.0, 3.0 )\ny = base.dists.studentizedRange.quantile( NaN, 2.0, 2.0 )\ny = base.dists.studentizedRange.quantile( 0.0, NaN, 2.0 )\ny = base.dists.studentizedRange.quantile( 0.5, -1.0, 2.0 )\n","base.dists.studentizedRange.quantile.factory":"var myQuantile = quantile.factory( 3.0, 3.0 );\nvar y = myQuantile( 0.5 )\n   ~1.791\ny = myQuantile( 0.8 )\n   ~3.245\n","base.dists.t.cdf":"var y = base.dists.t.cdf( 2.0, 0.1 )\ny = base.dists.t.cdf( 1.0, 2.0 )\ny = base.dists.t.cdf( -1.0, 4.0 )\ny = base.dists.t.cdf( NaN, 1.0 )\ny = base.dists.t.cdf( 0.0, NaN )\ny = base.dists.t.cdf( 2.0, -1.0 )\n","base.dists.t.cdf.factory":"var mycdf = base.dists.t.cdf.factory( 0.5 );\nvar y = mycdf( 3.0 )\ny = mycdf( 1.0 )\n","base.dists.t.entropy":"var v = base.dists.t.entropy( 11.0 )\nv = base.dists.t.entropy( 4.5 )\n","base.dists.t.kurtosis":"var v = base.dists.t.kurtosis( 11.0 )\nv = base.dists.t.kurtosis( 4.5 )\n","base.dists.t.logcdf":"var y = base.dists.t.logcdf( 2.0, 0.1 )\ny = base.dists.t.logcdf( 1.0, 2.0 )\ny = base.dists.t.logcdf( -1.0, 4.0 )\ny = base.dists.t.logcdf( NaN, 1.0 )\ny = base.dists.t.logcdf( 0.0, NaN )\ny = base.dists.t.logcdf( 2.0, -1.0 )\n","base.dists.t.logcdf.factory":"var mylogcdf = base.dists.t.logcdf.factory( 0.5 );\nvar y = mylogcdf( 3.0 )\ny = mylogcdf( 1.0 )\n","base.dists.t.logpdf":"var y = base.dists.t.logpdf( 0.3, 4.0 )\ny = base.dists.t.logpdf( 2.0, 0.7 )\ny = base.dists.t.logpdf( -1.0, 0.5 )\ny = base.dists.t.logpdf( 0.0, NaN )\ny = base.dists.t.logpdf( NaN, 2.0 )\ny = base.dists.t.logpdf( 2.0, -1.0 )\n","base.dists.t.logpdf.factory":"var mylogPDF = base.dists.t.logpdf.factory( 3.0 );\nvar y = mylogPDF( 1.0 )\n","base.dists.t.mean":"var v = base.dists.t.mean( 11.0 )\nv = base.dists.t.mean( 4.5 )\n","base.dists.t.median":"var v = base.dists.t.median( 11.0 )\nv = base.dists.t.median( 4.5 )\n","base.dists.t.mode":"var v = base.dists.t.mode( 11.0 )\nv = base.dists.t.mode( 4.5 )\n","base.dists.t.pdf":"var y = base.dists.t.pdf( 0.3, 4.0 )\ny = base.dists.t.pdf( 2.0, 0.7 )\ny = base.dists.t.pdf( -1.0, 0.5 )\ny = base.dists.t.pdf( 0.0, NaN )\ny = base.dists.t.pdf( NaN, 2.0 )\ny = base.dists.t.pdf( 2.0, -1.0 )\n","base.dists.t.pdf.factory":"var myPDF = base.dists.t.pdf.factory( 3.0 );\nvar y = myPDF( 1.0 )\n","base.dists.t.quantile":"var y = base.dists.t.quantile( 0.8, 1.0 )\ny = base.dists.t.quantile( 0.1, 1.0 )\ny = base.dists.t.quantile( 0.5, 0.1 )\ny = base.dists.t.quantile( -0.2, 0.1 )\ny = base.dists.t.quantile( NaN, 1.0 )\ny = base.dists.t.quantile( 0.0, NaN )\ny = base.dists.t.quantile( 0.5, -1.0 )\n","base.dists.t.quantile.factory":"var myQuantile = base.dists.t.quantile.factory( 4.0 );\nvar y = myQuantile( 0.2 )\ny = myQuantile( 0.9 )\n","base.dists.t.skewness":"var v = base.dists.t.skewness( 11.0 )\nv = base.dists.t.skewness( 4.5 )\n","base.dists.t.stdev":"var v = base.dists.t.stdev( 9.0 )\nv = base.dists.t.stdev( 4.5 )\n","base.dists.t.T":"var t = base.dists.t.T( 6.0 );\nt.v\nt.entropy\nt.kurtosis\nt.mean\nt.median\nt.mode\nt.skewness\nt.stdev\nt.variance\nt.cdf( 1.0 )\nt.logcdf( 1.0 )\nt.logpdf( 1.5 )\nt.pdf( 1.5 )\nt.quantile( 0.8 )\n","base.dists.t.variance":"var v = base.dists.t.variance( 9.0 )\nv = base.dists.t.variance( 4.5 )\n","base.dists.triangular.cdf":"var y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.cdf( -10.0, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.cdf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.cdf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.cdf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.cdf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.cdf( 2.0, 1.0, 0.0, NaN )\ny = base.dists.triangular.cdf( 2.0, 1.0, 0.0, 1.5 )\n","base.dists.triangular.cdf.factory":"var mycdf = base.dists.triangular.cdf.factory( 0.0, 10.0, 2.0 );\nvar y = mycdf( 0.5 )\ny = mycdf( 8.0 )\n","base.dists.triangular.entropy":"var v = base.dists.triangular.entropy( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.entropy( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.entropy( 2.0, 8.0, 5.0 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5.0 )\n","base.dists.triangular.mgf":"var y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.5 )\ny = base.dists.triangular.mgf( -0.3, -20.0, 0.0, -2.0 )\ny = base.dists.triangular.mgf( -2.0, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.mgf( NaN, 0.0, 1.0, 0.5 )\ny = base.dists.triangular.mgf( 0.0, NaN, 1.0, 0.5 )\ny = base.dists.triangular.mgf( 0.0, 0.0, NaN, 0.5 )\ny = base.dists.triangular.mgf( 0.5, 1.0, 0.0, NaN )\ny = base.dists.triangular.mgf( 0.5, 1.0, 0.0, 1.5 )\n","base.dists.triangular.mgf.factory":"var mymgf = base.dists.triangular.mgf.factory( 0.0, 2.0, 1.0 );\nvar y = mymgf( -1.0 )\ny = mymgf( 2.0 )\n","base.dists.triangular.mode":"var v = base.dists.triangular.mode( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.mode( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.mode( 2.0, 8.0, 5.0 )\n","base.dists.triangular.pdf":"var y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.0 )\ny = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.5 )\ny 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base.dists.triangular.quantile( 0.3, NaN, 1.0, 0.5 )\ny = base.dists.triangular.quantile( 0.3, 0.0, NaN, 0.5 )\ny = base.dists.triangular.quantile( 0.3, 1.0, 0.0, NaN )\ny = base.dists.triangular.quantile( 0.3, 1.0, 0.0, 1.5 )\n","base.dists.triangular.quantile.factory":"var myquantile = base.dists.triangular.quantile.factory( 2.0, 4.0, 2.5 );\nvar y = myquantile( 0.4 )\ny = myquantile( 0.8 )\n","base.dists.triangular.skewness":"var v = base.dists.triangular.skewness( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.skewness( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.skewness( 2.0, 8.0, 5.0 )\n","base.dists.triangular.stdev":"var v = base.dists.triangular.stdev( 0.0, 1.0, 0.8 )\nv = base.dists.triangular.stdev( 4.0, 12.0, 5.0 )\nv = base.dists.triangular.stdev( 2.0, 8.0, 5.0 )\n","base.dists.triangular.Triangular":"var triangular = base.dists.triangular.Triangular( 0.0, 1.0, 0.5 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base.dists.uniform.cdf.factory( 0.0, 10.0 );\nvar y = mycdf( 0.5 )\ny = mycdf( 8.0 )\n","base.dists.uniform.entropy":"var v = base.dists.uniform.entropy( 0.0, 1.0 )\nv = base.dists.uniform.entropy( 4.0, 12.0 )\nv = base.dists.uniform.entropy( 2.0, 8.0 )\n","base.dists.uniform.kurtosis":"var v = base.dists.uniform.kurtosis( 0.0, 1.0 )\nv = base.dists.uniform.kurtosis( 4.0, 12.0 )\nv = base.dists.uniform.kurtosis( 2.0, 8.0 )\n","base.dists.uniform.logcdf":"var y = base.dists.uniform.logcdf( 9.0, 0.0, 10.0 )\ny = base.dists.uniform.logcdf( 0.5, 0.0, 2.0 )\ny = base.dists.uniform.logcdf( PINF, 2.0, 4.0 )\ny = base.dists.uniform.logcdf( NINF, 2.0, 4.0 )\ny = base.dists.uniform.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.logcdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.logcdf( 2.0, 1.0, 0.0 )\n","base.dists.uniform.logcdf.factory":"var mylogcdf = base.dists.uniform.logcdf.factory( 0.0, 10.0 );\nvar y = mylogcdf( 0.5 )\ny = mylogcdf( 8.0 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0.0, 1.0 )\ny = base.dists.uniform.mgf( 0.5, 3.0, 2.0 )\ny = base.dists.uniform.mgf( 0.5, 3.0, 3.0 )\ny = base.dists.uniform.mgf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.mgf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.mgf( 0.0, 0.0, NaN )\n","base.dists.uniform.mgf.factory":"var mymgf = base.dists.uniform.mgf.factory( 6.0, 7.0 );\nvar y = mymgf( 0.1 )\ny = mymgf( 1.1 )\n","base.dists.uniform.pdf":"var y = base.dists.uniform.pdf( 2.0, 0.0, 4.0 )\ny = base.dists.uniform.pdf( 5.0, 0.0, 4.0 )\ny = base.dists.uniform.pdf( 0.25, 0.0, 1.0 )\ny = base.dists.uniform.pdf( NaN, 0.0, 1.0 )\ny = base.dists.uniform.pdf( 0.0, NaN, 1.0 )\ny = base.dists.uniform.pdf( 0.0, 0.0, NaN )\ny = base.dists.uniform.pdf( 2.0, 3.0, 1.0 )\n","base.dists.uniform.pdf.factory":"var myPDF = base.dists.uniform.pdf.factory( 6.0, 7.0 );\nvar y = myPDF( 7.0 )\ny = myPDF( 5.0 )\n","base.dists.uniform.quantile":"var y = base.dists.uniform.quantile( 0.8, 0.0, 1.0 )\ny = base.dists.uniform.quantile( 0.5, 0.0, 10.0 )\ny = base.dists.uniform.quantile( 1.1, 0.0, 1.0 )\ny = base.dists.uniform.quantile( -0.2, 0.0, 1.0 )\ny = base.dists.uniform.quantile( NaN, 0.0, 1.0 )\ny = base.dists.uniform.quantile( 0.0, NaN, 1.0 )\ny = base.dists.uniform.quantile( 0.0, 0.0, NaN )\ny = base.dists.uniform.quantile( 0.5, 2.0, 1.0 )\n","base.dists.uniform.quantile.factory":"var myQuantile = base.dists.uniform.quantile.factory( 0.0, 4.0 );\nvar y = myQuantile( 0.8 )\n","base.dists.uniform.skewness":"var v = base.dists.uniform.skewness( 0.0, 1.0 )\nv = base.dists.uniform.skewness( 4.0, 12.0 )\nv = base.dists.uniform.skewness( 2.0, 8.0 )\n","base.dists.uniform.stdev":"var v = base.dists.uniform.stdev( 0.0, 1.0 )\nv = base.dists.uniform.stdev( 4.0, 12.0 )\nv = base.dists.uniform.stdev( 2.0, 8.0 )\n","base.dists.uniform.Uniform":"var uniform = base.dists.uniform.Uniform( 0.0, 1.0 );\nuniform.a\nuniform.b\nuniform.entropy\nuniform.kurtosis\nuniform.mean\nuniform.median\nuniform.skewness\nuniform.stdev\nuniform.variance\nuniform.cdf( 0.8 )\nuniform.logcdf( 0.5 )\nuniform.logpdf( 1.0 )\nuniform.mgf( 0.8 )\nuniform.pdf( 0.8 )\nuniform.quantile( 0.8 )\n","base.dists.uniform.variance":"var v = base.dists.uniform.variance( 0.0, 1.0 )\nv = base.dists.uniform.variance( 4.0, 12.0 )\nv = base.dists.uniform.variance( 2.0, 8.0 )\n","base.dists.weibull.cdf":"var y = base.dists.weibull.cdf( 2.0, 1.0, 1.0 )\ny = base.dists.weibull.cdf( -1.0, 2.0, 2.0 )\ny = base.dists.weibull.cdf( PINF, 4.0, 2.0 )\ny = base.dists.weibull.cdf( NINF, 4.0, 2.0 )\ny = base.dists.weibull.cdf( NaN, 0.0, 1.0 )\ny = base.dists.weibull.cdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.cdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.cdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.cdf.factory":"var myCDF = base.dists.weibull.cdf.factory( 2.0, 10.0 );\nvar y = myCDF( 12.0 )\n","base.dists.weibull.entropy":"var v = base.dists.weibull.entropy( 1.0, 1.0 )\nv = base.dists.weibull.entropy( 4.0, 12.0 )\nv = base.dists.weibull.entropy( 8.0, 2.0 )\n","base.dists.weibull.kurtosis":"var v = base.dists.weibull.kurtosis( 1.0, 1.0 )\nv = base.dists.weibull.kurtosis( 4.0, 12.0 )\nv = base.dists.weibull.kurtosis( 8.0, 2.0 )\n","base.dists.weibull.logcdf":"var y = base.dists.weibull.logcdf( 2.0, 1.0, 1.0 )\ny = base.dists.weibull.logcdf( -1.0, 2.0, 2.0 )\ny = base.dists.weibull.logcdf( PINF, 4.0, 2.0 )\ny = base.dists.weibull.logcdf( NINF, 4.0, 2.0 )\ny = base.dists.weibull.logcdf( NaN, 0.0, 1.0 )\ny = base.dists.weibull.logcdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.logcdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.logcdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.logcdf.factory":"var mylogcdf = base.dists.weibull.logcdf.factory( 2.0, 10.0 );\nvar y = mylogcdf( 12.0 )\n","base.dists.weibull.logpdf":"var y = base.dists.weibull.logpdf( 2.0, 1.0, 0.5 )\ny = base.dists.weibull.logpdf( 0.1, 1.0, 1.0 )\ny = base.dists.weibull.logpdf( -1.0, 4.0, 2.0 )\ny = base.dists.weibull.logpdf( NaN, 0.6, 1.0 )\ny = base.dists.weibull.logpdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.logpdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.logpdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.logpdf.factory":"var mylofpdf = base.dists.weibull.logpdf.factory( 7.0, 6.0 );\ny = mylofpdf( 7.0 )\n","base.dists.weibull.mean":"var v = base.dists.weibull.mean( 1.0, 1.0 )\nv = base.dists.weibull.mean( 4.0, 12.0 )\nv = base.dists.weibull.mean( 8.0, 2.0 )\n","base.dists.weibull.median":"var v = base.dists.weibull.median( 1.0, 1.0 )\nv = base.dists.weibull.median( 4.0, 12.0 )\nv = base.dists.weibull.median( 8.0, 2.0 )\n","base.dists.weibull.mgf":"var y = base.dists.weibull.mgf( 1.0, 1.0, 0.5 )\ny = base.dists.weibull.mgf( -1.0, 4.0, 4.0 )\ny = base.dists.weibull.mgf( NaN, 1.0, 1.0 )\ny = base.dists.weibull.mgf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.mgf( 0.0, 1.0, NaN )\ny = base.dists.weibull.mgf( 0.2, -1.0, 0.5 )\ny = base.dists.weibull.mgf( 0.2, 0.0, 0.5 )\ny = base.dists.weibull.mgf( 0.2, 0.5, -1.0 )\ny = base.dists.weibull.mgf( 0.2, 0.5, 0.0 )\n","base.dists.weibull.mgf.factory":"var myMGF = base.dists.weibull.mgf.factory( 8.0, 10.0 );\nvar y = myMGF( 0.8 )\ny = myMGF( 0.08 )\n","base.dists.weibull.mode":"var v = base.dists.weibull.mode( 1.0, 1.0 )\nv = base.dists.weibull.mode( 4.0, 12.0 )\nv = base.dists.weibull.mode( 8.0, 2.0 )\n","base.dists.weibull.pdf":"var y = base.dists.weibull.pdf( 2.0, 1.0, 0.5 )\ny = base.dists.weibull.pdf( 0.1, 1.0, 1.0 )\ny = base.dists.weibull.pdf( -1.0, 4.0, 2.0 )\ny = base.dists.weibull.pdf( NaN, 0.6, 1.0 )\ny = base.dists.weibull.pdf( 0.0, NaN, 1.0 )\ny = base.dists.weibull.pdf( 0.0, 0.0, NaN )\ny = base.dists.weibull.pdf( 2.0, 0.0, -1.0 )\n","base.dists.weibull.pdf.factory":"var myPDF = base.dists.weibull.pdf.factory( 7.0, 6.0 );\nvar y = myPDF( 7.0 )\n","base.dists.weibull.quantile":"var y = base.dists.weibull.quantile( 0.8, 1.0, 1.0 )\ny = base.dists.weibull.quantile( 0.5, 2.0, 4.0 )\ny = base.dists.weibull.quantile( 1.1, 1.0, 1.0 )\ny = base.dists.weibull.quantile( -0.2, 1.0, 1.0 )\ny = base.dists.weibull.quantile( NaN, 0.0, 1.0 )\ny = base.dists.weibull.quantile( 0.0, NaN, 1.0 )\ny = base.dists.weibull.quantile( 0.0, 0.0, NaN )\ny = base.dists.weibull.quantile( 0.5, 1.0, -1.0 )\n","base.dists.weibull.quantile.factory":"var myQuantile = base.dists.weibull.quantile.factory( 2.0, 10.0 );\nvar y = myQuantile( 0.4 )\n","base.dists.weibull.skewness":"var v = base.dists.weibull.skewness( 1.0, 1.0 )\nv = base.dists.weibull.skewness( 4.0, 12.0 )\nv = base.dists.weibull.skewness( 8.0, 2.0 )\n","base.dists.weibull.stdev":"var v = base.dists.weibull.stdev( 1.0, 1.0 )\nv = base.dists.weibull.stdev( 4.0, 12.0 )\nv = base.dists.weibull.stdev( 8.0, 2.0 )\n","base.dists.weibull.variance":"var v = base.dists.weibull.variance( 1.0, 1.0 )\nv = base.dists.weibull.variance( 4.0, 12.0 )\nv = base.dists.weibull.variance( 8.0, 2.0 )\n","base.dists.weibull.Weibull":"var weibull = base.dists.weibull.Weibull( 6.0, 5.0 );\nweibull.k\nweibull.lambda\nweibull.entropy\nweibull.kurtosis\nweibull.mean\nweibull.median\nweibull.mode\nweibull.skewness\nweibull.stdev\nweibull.variance\nweibull.cdf( 3.0 )\nweibull.logcdf( 3.0 )\nweibull.logpdf( 1.0 )\nweibull.mgf( -0.5 )\nweibull.pdf( 3.0 )\nweibull.quantile( 0.8 )\n","base.ellipe":"var y = base.ellipe( 0.5 )\ny = base.ellipe( -1.0 )\ny = base.ellipe( 2.0 )\ny = base.ellipe( PINF )\ny = base.ellipe( NINF )\ny = base.ellipe( NaN )\n","base.ellipj":"var v = base.ellipj( 0.3, 0.5 )\nv = base.ellipj( 0.0, 0.0 )\nv = base.ellipj( Infinity, 1.0 )\nv = base.ellipj( 0.0, -2.0)\nv = base.ellipj( NaN, NaN )\n","base.ellipj.assign":"var out = new Float64Array( 4 );\nvar v = base.ellipj.assign( 0.3, 0.5, out, 1, 0 )\nvar bool = ( v === out )\n","base.ellipj.sn":"var v = base.ellipj.sn( 0.3, 0.5 )\n","base.ellipj.cn":"var v = base.ellipj.cn( 0.3, 0.5 )\n","base.ellipj.dn":"var v = base.ellipj.dn( 0.3, 0.5 )\n","base.ellipj.am":"var v = base.ellipj.am( 0.3, 0.5 )\n","base.ellipk":"var y = base.ellipk( 0.5 )\ny = base.ellipk( -1.0 )\ny = base.ellipk( 2.0 )\ny = base.ellipk( PINF )\ny = base.ellipk( NINF )\ny = base.ellipk( NaN )\n","base.endsWith":"var bool = base.endsWith( 'beep', 'ep', 4 )\nbool = base.endsWith( 'Beep', 'op', 4 )\nbool = base.endsWith( 'Beep', 'ee', 3 )\nbool = base.endsWith( 'Beep', 'ee', -1 )\nbool = base.endsWith( 'beep', '', 4 )\n","base.epsdiff":"var d = base.epsdiff( 12.15, 12.149999999999999 )\nd = base.epsdiff( 2.4341309458983933, 2.4341309458633909, 'mean-abs' )\nfunction scale( x, y ) { return ( x > y ) ? y : x; };\nd = base.epsdiff( 1.0000000000000002, 1.0000000000000100, scale )\n","base.erf":"var y = base.erf( 2.0 )\ny = base.erf( -1.0 )\ny = base.erf( -0.0 )\ny = base.erf( NaN )\n","base.erfc":"var y = base.erfc( 2.0 )\ny = base.erfc( -1.0 )\ny = base.erfc( 0.0 )\ny = base.erfc( PINF )\ny = base.erfc( NINF )\ny = base.erfc( NaN )\n","base.erfcinv":"var y = base.erfcinv( 0.5 )\ny = base.erfcinv( 0.8 )\ny = base.erfcinv( 0.0 )\ny = base.erfcinv( 2.0 )\ny = base.erfcinv( NaN )\n","base.erfcx":"var y = base.erfcx( 1.0 )\ny = base.erfcx( -1.0 )\ny = base.erfcx( 0.0 )\ny = base.erfcx( NaN )\n","base.erfinv":"var y = base.erfinv( 0.5 )\ny = base.erfinv( 0.8 )\ny = base.erfinv( 0.0 )\ny = base.erfinv( -0.0 )\ny = base.erfinv( -1.0 )\ny = base.erfinv( 1.0 )\ny = base.erfinv( NaN )\n","base.eta":"var y = base.eta( 0.0 )\ny = base.eta( -1.0 )\ny = base.eta( 1.0 )\ny = base.eta( 3.14 )\ny = base.eta( NaN )\n","base.evalpoly":"var arr = [ 3.0, 2.0, 1.0 ];\nvar v = base.evalpoly( arr, 10.0 )\n","base.evalpoly.factory":"var f = base.evalpoly.factory( [ 3.0, 2.0, 1.0 ] );\nvar v = f( 10.0 )\nv = f( 5.0 )\n","base.evalrational":"var P = [ -6.0, -5.0, 4.0, 2.0 ];\nvar Q = [ 3.0, 0.5, 0.0, 0.0 ]; // zero-padded\nvar v = base.evalrational( P, Q, 6.0 )\n","base.evalrational.factory":"var P = [ 20.0, 8.0, 3.0 ];\nvar Q = [ 10.0, 9.0, 1.0 ];\nvar f = base.evalrational.factory( P, Q );\nvar v = f( 10.0 )\nv = f( 2.0 )\n","base.exp":"var y = base.exp( 4.0 )\ny = base.exp( -9.0 )\ny = base.exp( 0.0 )\ny = base.exp( NaN )\n","base.exp2":"var y = base.exp2( 3.0 )\ny = base.exp2( -9.0 )\ny = base.exp2( 0.0 )\ny = base.exp2( NaN )\n","base.exp10":"var y = base.exp10( 3.0 )\ny = base.exp10( -9.0 )\ny = base.exp10( 0.0 )\ny = base.exp10( NaN )\n","base.expit":"var y = base.expit( 0.0 )\ny = base.expit( 1.0 )\ny = base.expit( -1.0 )\ny = base.expit( Infinity )\ny = base.expit( NaN )\n","base.expm1":"var y = base.expm1( 0.2 )\ny = base.expm1( -9.0 )\ny = base.expm1( 0.0 )\ny = base.expm1( NaN )\n","base.expm1rel":"var y = base.expm1rel( 0.0 )\ny = base.expm1rel( 1.0 )\ny = base.expm1rel( -1.0 )\ny = base.expm1rel( NaN )\n","base.exponent":"var exponent = base.exponent( 3.14e-307 )\nexponent = base.exponent( -3.14 )\nexponent = base.exponent( 0.0 )\nexponent = base.exponent( NaN )\n","base.exponentf":"var exponent = base.exponentf( base.float64ToFloat32( 3.14e34 ) )\nexponent = base.exponentf( base.float64ToFloat32( 3.14e-34 ) )\nexponent = base.exponentf( base.float64ToFloat32( -3.14 ) )\nexponent = base.exponentf( 0.0 )\nexponent = base.exponentf( NaN )\n","base.factorial":"var y = base.factorial( 3.0 )\ny = base.factorial( -1.5 )\ny = base.factorial( -0.5 )\ny = base.factorial( 0.5 )\ny = base.factorial( -10.0 )\ny = base.factorial( 171.0 )\ny = base.factorial( NaN )\n","base.factorial2":"var y = base.factorial2( 3 )\ny = base.factorial2( 5 )\ny = base.factorial2( 6 )\ny = base.factorial2( 301 )\ny = base.factorial2( NaN )\n","base.factorialln":"var y = base.factorialln( 3.0 )\ny = base.factorialln( 2.4 )\ny = base.factorialln( -1.0 )\ny = base.factorialln( -1.5 )\ny = base.factorialln( NaN )\n","base.fallingFactorial":"var v = base.fallingFactorial( 0.9, 5 )\nv = base.fallingFactorial( -9.0, 3 )\nv = base.fallingFactorial( 0.0, 2 )\nv = base.fallingFactorial( 3.0, -2 )\n","base.fibonacci":"var y = base.fibonacci( 0 )\ny = base.fibonacci( 1 )\ny = base.fibonacci( 2 )\ny = base.fibonacci( 3 )\ny = base.fibonacci( 4 )\ny = base.fibonacci( 79 )\ny = base.fibonacci( NaN )\n","base.fibonacciIndex":"var n = base.fibonacciIndex( 2 )\nn = base.fibonacciIndex( 3 )\nn = base.fibonacciIndex( 5 )\nn = base.fibonacciIndex( NaN )\nn = base.fibonacciIndex( 1 )\n","base.fibpoly":"var v = base.fibpoly( 5, 2.0 )\n","base.fibpoly.factory":"var polyval = base.fibpoly.factory( 5 );\nvar v = polyval( 1.0 )\nv = polyval( 2.0 )\n","base.firstCodePoint":"var out = base.firstCodePoint( 'beep', 1 )\nout = base.firstCodePoint( 'Boop', 1 )\nout = base.firstCodePoint( 'foo bar', 5 )\n","base.firstCodeUnit":"var out = base.firstCodeUnit( 'beep', 1 )\nout = base.firstCodeUnit( 'Boop', 1 )\nout = base.firstCodeUnit( 'foo bar', 5 )\n","base.firstGraphemeCluster":"var out = base.firstGraphemeCluster( 'beep', 1 )\nout = base.firstGraphemeCluster( 'Boop', 1 )\nout = base.firstGraphemeCluster( 'foo bar', 5 )\n","base.flipsign":"var z = base.flipsign( -3.0, 10.0 )\nz = base.flipsign( -3.0, -1.0 )\nz = base.flipsign( 1.0, -0.0 )\nz = base.flipsign( -3.0, -0.0 )\nz = base.flipsign( -0.0, 1.0 )\nz = base.flipsign( 0.0, -1.0 )\n","base.flipsignf":"var z = base.flipsignf( -3.0, 10.0 )\nz = base.flipsignf( -3.0, -1.0 )\nz = base.flipsignf( 1.0, -0.0 )\nz = base.flipsignf( -3.0, -0.0 )\nz = base.flipsignf( -0.0, 1.0 )\nz = base.flipsignf( 0.0, -1.0 )\n","base.float32ToInt32":"var y = base.float32ToInt32( base.float64ToFloat32( 4294967295.0 ) )\ny = base.float32ToInt32( base.float64ToFloat32( 3.14 ) )\ny = base.float32ToInt32( base.float64ToFloat32( -3.14 ) )\ny = base.float32ToInt32( base.float64ToFloat32( NaN ) )\ny = base.float32ToInt32( FLOAT32_PINF )\ny = base.float32ToInt32( FLOAT32_NINF )\n","base.float32ToUint32":"var y = base.float32ToUint32( base.float64ToFloat32( 4294967297.0 ) )\ny = base.float32ToUint32( base.float64ToFloat32( 3.14 ) )\ny = base.float32ToUint32( base.float64ToFloat32( -3.14 ) )\ny = base.float32ToUint32( base.float64ToFloat32( NaN ) )\ny = base.float32ToUint32( FLOAT32_PINF )\ny = base.float32ToUint32( FLOAT32_NINF )\n","base.float64ToFloat32":"var y = base.float64ToFloat32( 1.337 )\n","base.float64ToInt32":"var y = base.float64ToInt32( 4294967295.0 )\ny = base.float64ToInt32( 3.14 )\ny = base.float64ToInt32( -3.14 )\ny = base.float64ToInt32( NaN )\ny = base.float64ToInt32( PINF )\ny = base.float64ToInt32( NINF )\n","base.float64ToInt64Bytes":"var y = base.float64ToInt64Bytes( 4294967297.0 )\n","base.float64ToInt64Bytes.assign":"var out = new Uint8Array( 16 );\nvar y = base.float64ToInt64Bytes( 4294967297.0, out, 2, 1 )\n","base.float64ToUint32":"var y = base.float64ToUint32( 4294967297.0 )\ny = base.float64ToUint32( 3.14 )\ny = base.float64ToUint32( -3.14 )\ny = base.float64ToUint32( NaN )\ny = base.float64ToUint32( PINF )\ny = base.float64ToUint32( NINF )\n","base.floor":"var y = base.floor( 3.14 )\ny = base.floor( -4.2 )\ny = base.floor( -4.6 )\ny = base.floor( 9.5 )\ny = base.floor( -0.0 )\n","base.floor2":"var y = base.floor2( 3.14 )\ny = base.floor2( -4.2 )\ny = base.floor2( -4.6 )\ny = base.floor2( 9.5 )\ny = base.floor2( 13.0 )\ny = base.floor2( -13.0 )\ny = base.floor2( -0.0 )\n","base.floor10":"var y = base.floor10( 3.14 )\ny = base.floor10( -4.2 )\ny = base.floor10( -4.6 )\ny = base.floor10( 9.5 )\ny = base.floor10( 13.0 )\ny = base.floor10( -13.0 )\ny = base.floor10( -0.0 )\n","base.floorb":"var y = base.floorb( 3.14159, -4, 10 )\ny = base.floorb( 3.14159, 0, 2 )\ny = base.floorb( 5.0, 1, 2 )\n","base.floorf":"var y = base.floorf( 3.14 )\ny = base.floorf( -4.2 )\ny = base.floorf( -4.6 )\ny = base.floorf( 9.5 )\ny = base.floorf( -0.0 )\n","base.floorn":"var y = base.floorn( 3.14159, -4 )\ny = base.floorn( 3.14159, 0 )\ny = base.floorn( 12368.0, 3 )\n","base.floorsd":"var y = base.floorsd( 3.14159, 5, 10 )\ny = base.floorsd( 3.14159, 1, 10 )\ny = base.floorsd( 12368.0, 2, 10 )\ny = base.floorsd( 0.0313, 2, 2 )\n","base.forEachChar":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachChar( 'hello world!', fcn );\nn\n","base.forEachCodePoint":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachCodePoint( 'hello world!', fcn );\nn\n","base.forEachCodePointRight":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachCodePointRight( 'hello world!', fcn );\nn\n","base.forEachGraphemeCluster":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachGraphemeCluster( 'hello world!', fcn );\nn\n","base.forEachRight":"var n = 0;\nfunction fcn() { n += 1; };\nbase.forEachRight( 'hello world!', fcn );\nn\n","base.formatInterpolate":"var out = base.formatInterpolate( [ 'beep ', { 'specifier': 's' } ], 'boop' )\nout = base.formatInterpolate( [ 'baz ', { 'specifier': 'd', 'precision': 2 } ], 1 )\nout = base.formatInterpolate( [ { 'specifier': 'u', 'width': 6 } ], 12 )\n","base.formatTokenize":"var out = base.formatTokenize( 'Hello %s!' )\nout = base.formatTokenize( '%s %s %d' )\nout = base.formatTokenize( 'Pi: %.2f' )\n","base.fresnel":"var y = base.fresnel( 0.0 )\ny = base.fresnel( 1.0 )\ny = base.fresnel( PINF )\ny = base.fresnel( NINF )\ny = base.fresnel( NaN )\n","base.fresnel.assign":"var out = new Float64Array( 2 );\nvar v = base.fresnel.assign( 0.0, out, 1, 0 )\nvar bool = ( v === out )\n","base.fresnelc":"var y = base.fresnelc( 0.0 )\ny = base.fresnelc( 1.0 )\ny = base.fresnelc( PINF )\ny = base.fresnelc( NINF )\ny = base.fresnelc( NaN )\n","base.fresnels":"var y = base.fresnels( 0.0 )\ny = base.fresnels( 1.0 )\ny = base.fresnels( PINF )\ny = base.fresnels( NINF )\ny = base.fresnels( NaN )\n","base.frexp":"var out = base.frexp( 4.0 )\nout = base.frexp( 0.0 )\nout = base.frexp( -0.0 )\nout = base.frexp( NaN )\nout = base.frexp( PINF )\nout = base.frexp( NINF )\n","base.frexp.assign":"var out = new Float64Array( 2 );\nvar y = base.frexp.assign( 4.0, out, 1, 0 )\nvar bool = ( y === out )\n","base.fromBinaryString":"var bstr;\nbstr = '0100000000010000000000000000000000000000000000000000000000000000';\nvar val = base.fromBinaryString( bstr )\nbstr = '0100000000001001001000011111101101010100010001000010110100011000';\nval = base.fromBinaryString( bstr )\nbstr = '1111111111100001110011001111001110000101111010111100100010100000';\nval = base.fromBinaryString( bstr )\nbstr = '1000000000000000000000000000000000000000000000000001100011010011';\nval = base.fromBinaryString( bstr )\nbstr = '0000000000000000000000000000000000000000000000000000000000000001';\nval = base.fromBinaryString( bstr )\nbstr = '0000000000000000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '1000000000000000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '0111111111111000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '0111111111110000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\nbstr = '1111111111110000000000000000000000000000000000000000000000000000';\nval = base.fromBinaryString( bstr )\n","base.fromBinaryStringf":"var bstr = '01000000100000000000000000000000';\nvar val = base.fromBinaryStringf( bstr )\nbstr = '01000000010010010000111111011011';\nval = base.fromBinaryStringf( bstr )\nbstr = '11111111011011000011101000110011';\nval = base.fromBinaryStringf( bstr )\nbstr = '10000000000000000000000000010110';\nval = base.fromBinaryStringf( bstr )\nbstr = '00000000000000000000000000000001';\nval = base.fromBinaryStringf( bstr )\nbstr = '00000000000000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '10000000000000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '01111111110000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '01111111100000000000000000000000';\nval = base.fromBinaryStringf( bstr )\nbstr = '11111111100000000000000000000000';\nval = base.fromBinaryStringf( bstr )\n","base.fromBinaryStringUint8":"var bstr = '01010101';\nvar val = base.fromBinaryStringUint8( bstr )\nbstr = '00000000';\nval = base.fromBinaryStringUint8( bstr )\nbstr = '00000010';\nval = base.fromBinaryStringUint8( bstr )\nbstr = '11111111';\nval = base.fromBinaryStringUint8( bstr )\n","base.fromBinaryStringUint16":"var bstr = '0101010101010101';\nvar val = base.fromBinaryStringUint16( bstr )\nbstr = '0000000000000000';\nval = base.fromBinaryStringUint16( bstr )\nbstr = '0000000000000010';\nval = base.fromBinaryStringUint16( bstr )\nbstr = '1111111111111111';\nval = base.fromBinaryStringUint16( bstr )\n","base.fromBinaryStringUint32":"var bstr = '01010101010101010101010101010101';\nvar val = base.fromBinaryStringUint32( bstr )\nbstr = '00000000000000000000000000000000';\nval = base.fromBinaryStringUint32( bstr )\nbstr = '00000000000000000000000000000010';\nval = base.fromBinaryStringUint32( bstr )\nbstr = '11111111111111111111111111111111';\nval = base.fromBinaryStringUint32( bstr )\n","base.fromInt64Bytes":"var bytes = new Uint8Array( [ 255, 255, 255, 255, 255, 255, 255, 255 ] );\nvar y = base.fromInt64Bytes( bytes, 1, 0 )\n","base.fromWordf":"var word = 1068180177; // => 0 01111111 01010110010001011010001\nvar f32 = base.fromWordf( word ) // when printed, promoted to float64\n","base.fromWords":"var v = base.fromWords( 1774486211, 2479577218 )\nv = base.fromWords( 3221823995, 1413754136 )\nv = base.fromWords( 0, 0 )\nv = base.fromWords( 2147483648, 0 )\nv = base.fromWords( 2146959360, 0 )\nv = base.fromWords( 2146435072, 0 )\nv = base.fromWords( 4293918720, 0 )\n","base.gamma":"var y = base.gamma( 4.0 )\ny = base.gamma( -1.5 )\ny = base.gamma( -0.5 )\ny = base.gamma( 0.5 )\ny = base.gamma( 0.0 )\ny = base.gamma( -0.0 )\ny = base.gamma( NaN )\n","base.gamma1pm1":"var y = base.gamma1pm1( 0.2 )\ny = base.gamma1pm1( -6.7 )\ny = base.gamma1pm1( 0.0 )\ny = base.gamma1pm1( NaN )\n","base.gammaDeltaRatio":"var y = base.gammaDeltaRatio( 2.0, 3.0 )\ny = base.gammaDeltaRatio( 4.0, 0.5 )\ny = base.gammaDeltaRatio( 100.0, 0.0 )\ny = base.gammaDeltaRatio( NaN, 3.0 )\ny = base.gammaDeltaRatio( 5.0, NaN )\ny = base.gammaDeltaRatio( NaN, NaN )\n","base.gammainc":"var y = base.gammainc( 6.0, 2.0 )\ny = base.gammainc( 1.0, 2.0, true, true )\ny = base.gammainc( 7.0, 5.0 )\ny = base.gammainc( 7.0, 5.0, false )\ny = base.gammainc( NaN, 2.0 )\ny = base.gammainc( 6.0, NaN )\n","base.gammaincinv":"var y = base.gammaincinv( 0.5, 2.0 )\ny = base.gammaincinv( 0.1, 10.0 )\ny = base.gammaincinv( 0.75, 3.0 )\ny = base.gammaincinv( 0.75, 3.0, true )\ny = base.gammaincinv( 0.75, NaN )\ny = base.gammaincinv( NaN, 3.0 )\n","base.gammaLanczosSum":"var y = base.gammaLanczosSum( 4.0 )\ny = base.gammaLanczosSum( -1.5 )\ny = base.gammaLanczosSum( -0.5 )\ny = base.gammaLanczosSum( 0.5 )\ny = base.gammaLanczosSum( 0.0 )\ny = base.gammaLanczosSum( NaN )\n","base.gammaLanczosSumExpGScaled":"var y = base.gammaLanczosSumExpGScaled( 4.0 )\ny = base.gammaLanczosSumExpGScaled( -1.5 )\ny = base.gammaLanczosSumExpGScaled( -0.5 )\ny = base.gammaLanczosSumExpGScaled( 0.5 )\ny = base.gammaLanczosSumExpGScaled( 0.0 )\ny = base.gammaLanczosSumExpGScaled( NaN )\n","base.gammaln":"var y = base.gammaln( 1.0 )\ny = base.gammaln( 2.0 )\ny = base.gammaln( 4.0 )\ny = base.gammaln( -0.5 )\ny = base.gammaln( 0.5 )\ny = base.gammaln( 0.0 )\ny = base.gammaln( NaN )\n","base.gammasgn":"var y = base.gammasgn( 1.0 )\ny = base.gammasgn( -2.5 )\ny = base.gammasgn( 0.0 )\ny = base.gammasgn( NaN )\n","base.gcd":"var v = base.gcd( 48, 18 )\n","base.getHighWord":"var w = base.getHighWord( 3.14e201 )\n","base.getLowWord":"var w = base.getLowWord( 3.14e201 )\n","base.hacovercos":"var y = base.hacovercos( 3.14 )\ny = base.hacovercos( -4.2 )\ny = base.hacovercos( -4.6 )\ny = base.hacovercos( 9.5 )\ny = base.hacovercos( -0.0 )\n","base.hacoversin":"var y = base.hacoversin( 3.14 )\ny = base.hacoversin( -4.2 )\ny = base.hacoversin( -4.6 )\ny = base.hacoversin( 9.5 )\ny = base.hacoversin( -0.0 )\n","base.havercos":"var y = base.havercos( 3.14 )\ny = base.havercos( -4.2 )\ny = base.havercos( -4.6 )\ny = base.havercos( 9.5 )\ny = base.havercos( -0.0 )\n","base.haversin":"var y = base.haversin( 3.14 )\ny = base.haversin( -4.2 )\ny = base.haversin( -4.6 )\ny = base.haversin( 9.5 )\ny = base.haversin( -0.0 )\n","base.headercase":"var out = base.headercase( 'Hello World!' )\nout = base.headercase( 'beep boop' )\n","base.heaviside":"var y = base.heaviside( 3.14 )\ny = base.heaviside( -3.14 )\ny = base.heaviside( 0.0 )\ny = base.heaviside( 0.0, 'half-maximum' )\ny = base.heaviside( 0.0, 'left-continuous' )\ny = base.heaviside( 0.0, 'right-continuous' )\n","base.hermitepoly":"var y = base.hermitepoly( 1, 0.5 )\ny = base.hermitepoly( -1, 0.5 )\ny = base.hermitepoly( 0, 0.5 )\ny = base.hermitepoly( 2, 0.5 )\n","base.hermitepoly.factory":"var polyval = base.hermitepoly.factory( 2 );\nvar v = polyval( 0.5 )\n","base.hypot":"var h = base.hypot( -5.0, 12.0 )\nh = base.hypot( NaN, 12.0 )\nh = base.hypot( -0.0, -0.0 )\n","base.hypotf":"var h = base.hypotf( -5.0, 12.0 )\nh = base.hypotf( NaN, 12.0 )\nh = base.hypotf( -0.0, -0.0 )\n","base.identity":"var y = base.identity( -1.0 )\ny = base.identity( 2.0 )\ny = base.identity( 0.0 )\ny = base.identity( -0.0 )\ny = base.identity( NaN )\n","base.identityf":"var y = base.identityf( -1.0 )\ny = base.identityf( 2.0 )\ny = base.identityf( 0.0 )\ny = base.identityf( -0.0 )\ny = base.identityf( NaN )\n","base.imul":"var v = base.imul( -10|0, 4|0 )\n","base.imuldw":"var v = base.imuldw( 1, 10 )\n","base.imuldw.assign":"var out = [ 0, 0 ];\nvar v = base.imuldw.assign( 1, 10, out, 1, 0 )\nvar bool = ( v === out )\n","base.int2slice":"var s = base.int2slice( -1, 5, false );\ns.start\ns.stop\ns.step\n","base.int32ToUint32":"var y = base.int32ToUint32( base.float64ToInt32( -32 ) )\ny = base.int32ToUint32( base.float64ToInt32( 3 ) )\n","base.inv":"var y = base.inv( -1.0 )\ny = base.inv( 2.0 )\ny = base.inv( 0.0 )\ny = base.inv( -0.0 )\ny = base.inv( NaN )\n","base.invcase":"var out = base.invcase( 'Hello World!' )\nout = base.invcase( 'I am A tiny LITTLE teapot' )\n","base.invf":"var y = base.invf( -1.0 )\ny = base.invf( 2.0 )\ny = base.invf( 0.0 )\ny = base.invf( -0.0 )\ny = base.invf( NaN )\n","base.isComposite":"var bool = base.isComposite( 10.0 )\nbool = base.isComposite( 11.0 )\n","base.isCoprime":"var bool = base.isCoprime( 14.0, 15.0 )\nbool = base.isCoprime( 14.0, 21.0 )\n","base.isEven":"var bool = base.isEven( 5.0 )\nbool = base.isEven( -2.0 )\nbool = base.isEven( 0.0 )\nbool = base.isEven( NaN )\n","base.isEvenInt32":"var bool = base.isEvenInt32( 5 )\nbool = base.isEvenInt32( -2 )\nbool = base.isEvenInt32( 0 )\n","base.isFinite":"var bool = base.isFinite( 5.0 )\nbool = base.isFinite( -2.0e64 )\nbool = base.isFinite( PINF )\nbool = base.isFinite( NINF )\n","base.isFinitef":"var bool = base.isFinitef( 5.0 )\nbool = base.isFinitef( -1.0e38 )\nbool = base.isFinitef( FLOAT32_PINF )\nbool = base.isFinitef( FLOAT32_NINF )\n","base.isInfinite":"var bool = base.isInfinite( PINF )\nbool = base.isInfinite( NINF )\nbool = base.isInfinite( 5.0 )\nbool = base.isInfinite( NaN )\n","base.isInfinitef":"var bool = base.isInfinitef( FLOAT32_PINF )\nbool = base.isInfinitef( FLOAT32_NINF )\nbool = base.isInfinitef( 5.0 )\nbool = base.isInfinitef( NaN )\n","base.isInteger":"var bool = base.isInteger( 1.0 )\nbool = base.isInteger( 3.14 )\n","base.isnan":"var bool = base.isnan( NaN )\nbool = base.isnan( 7.0 )\n","base.isnanf":"var bool = base.isnanf( NaN )\nbool = base.isnanf( 7.0 )\n","base.isNegativeFinite":"var bool = base.isNegativeFinite( -3.14 )\nbool = base.isNegativeFinite( -Infinity )\nbool = base.isNegativeFinite( 2.0 )\nbool = base.isNegativeFinite( NaN )\nbool = base.isNegativeFinite( -0.0 )\n","base.isNegativeInteger":"var bool = base.isNegativeInteger( -1.0 )\nbool = base.isNegativeInteger( 0.0 )\nbool = base.isNegativeInteger( 10.0 )\n","base.isNegativeZero":"var bool = base.isNegativeZero( -0.0 )\nbool = base.isNegativeZero( 0.0 )\n","base.isNegativeZerof":"var bool = base.isNegativeZerof( -0.0 )\nbool = base.isNegativeZerof( 0.0 )\n","base.isNonNegativeFinite":"var out = base.isNonNegativeFinite( 5.0 )\nout = base.isNonNegativeFinite( 3.14 )\nout = base.isNonNegativeFinite( 0.0 )\nout = base.isNonNegativeFinite( Infinity )\nout = base.isNonNegativeFinite( -3.14 )\nout = base.isNonNegativeFinite( NaN )\n","base.isNonNegativeInteger":"var bool = base.isNonNegativeInteger( 1.0 )\nbool = base.isNonNegativeInteger( 0.0 )\nbool = base.isNonNegativeInteger( -10.0 )\n","base.isNonPositiveFinite":"var bool = base.isNonPositiveFinite( -3.14 )\nvar bool = base.isNonPositiveFinite( 0.0 )\nvar bool = base.isNonPositiveFinite( -Infinity )\nvar bool = base.isNonPositiveFinite( 3.14 )\nvar bool = base.isNonPositiveFinite( NaN )\n","base.isNonPositiveInteger":"var bool = base.isNonPositiveInteger( -1.0 )\nbool = base.isNonPositiveInteger( 0.0 )\nbool = base.isNonPositiveInteger( 10.0 )\n","base.isOdd":"var bool = base.isOdd( 5.0 )\nbool = base.isOdd( -2.0 )\nbool = base.isOdd( 0.0 )\nbool = base.isOdd( NaN )\n","base.isOddInt32":"var bool = base.isOddInt32( 5 )\nbool = base.isOddInt32( -2 )\nbool = base.isOddInt32( 0 )\n","base.isPositiveFinite":"var bool = base.isPositiveFinite( 5.0 )\nbool = base.isPositiveFinite( 3.14 )\nbool = base.isPositiveFinite( 0.0 )\nbool = base.isPositiveFinite( Infinity )\nbool = base.isPositiveFinite( -3.14 )\nbool = base.isPositiveFinite( NaN )\n","base.isPositiveInteger":"var bool = base.isPositiveInteger( 1.0 )\nbool = base.isPositiveInteger( 0.0 )\nbool = base.isPositiveInteger( -10.0 )\n","base.isPositiveZero":"var bool = base.isPositiveZero( 0.0 )\nbool = base.isPositiveZero( -0.0 )\n","base.isPositiveZerof":"var bool = base.isPositiveZerof( 0.0 )\nbool = base.isPositiveZerof( -0.0 )\n","base.isPow2Uint32":"var bool = base.isPow2Uint32( 2 )\nbool = base.isPow2Uint32( 5 )\n","base.isPrime":"var bool = base.isPrime( 11.0 )\nbool = base.isPrime( 3.14 )\n","base.isProbability":"var bool = base.isProbability( 0.5 )\nbool = base.isProbability( 3.14 )\nbool = base.isProbability( NaN )\n","base.isSafeInteger":"var bool = base.isSafeInteger( 1.0 )\nbool = base.isSafeInteger( 2.0e200 )\nbool = base.isSafeInteger( 3.14 )\n","base.kebabcase":"var out = base.kebabcase( 'Hello World!' )\nout = base.kebabcase( 'I am a tiny little teapot' )\n","base.kernelBetainc":"var out = base.kernelBetainc( 0.8, 1.0, 0.3, false, false )\nout = base.kernelBetainc( 0.2, 1.0, 2.0, true, false )\n","base.kernelBetainc.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.kernelBetainc.assign( 0.2, 1.0, 2.0, true, true, out, 1, 0 )\nvar bool = ( v === out )\n","base.kernelBetaincinv":"var y = base.kernelBetaincinv( 3.0, 3.0, 0.2, 0.8 )\ny = base.kernelBetaincinv( 3.0, 3.0, 0.4, 0.6 )\ny = base.kernelBetaincinv( 1.0, 6.0, 0.4, 0.6 )\ny = base.kernelBetaincinv( 1.0, 6.0, 0.8, 0.2 )\n","base.kernelCos":"var out = base.kernelCos( 0.0, 0.0 )\nout = base.kernelCos( PI/6.0, 0.0 )\nout = base.kernelCos( 0.785, -1.144e-17 )\nout = base.kernelCos( NaN )\n","base.kernelLog1p":"var y = base.kernelLog1p( 1.0 )\ny = base.kernelLog1p( 1.4142135623730951 )\ny = base.kernelLog1p( NaN )\n","base.kernelSin":"var y = base.kernelSin( 0.0, 0.0 )\ny = base.kernelSin( PI/6.0, 0.0 )\ny = base.kernelSin( 0.619, 9.279e-18 )\ny = base.kernelSin( NaN, 0.0 )\ny = base.kernelSin( 2.0, NaN )\ny = base.kernelSin( NaN, NaN )\n","base.kernelTan":"var out = base.kernelTan( PI/4.0, 0.0, 1 )\nout = base.kernelTan( PI/4.0, 0.0, -1 )\nout = base.kernelTan( PI/6.0, 0.0, 1 )\nout = base.kernelTan( 0.664, 5.288e-17, 1 )\nout = base.kernelTan( NaN, 0.0, 1 )\nout = base.kernelTan( 3.0, NaN, 1 )\nout = base.kernelTan( 3.0, 0.0, NaN )\n","base.kroneckerDelta":"var y = base.kroneckerDelta( 3.14, 0.0 )\ny = base.kroneckerDelta( 3.14, 3.14 )\n","base.kroneckerDeltaf":"var y = base.kroneckerDeltaf( 3.14, 0.0 )\ny = base.kroneckerDeltaf( 3.14, 3.14 )\n","base.labs":"var v = base.labs( -1|0 )\nv = base.labs( 2|0 )\nv = base.labs( 0|0 )\n","base.last":"var out = base.last( 'hello', 1 )\nout = base.last( 'JavaScript', 6 )\nout = base.last( 'foo bar', 10 )\n","base.lastCodePoint":"var out = base.lastCodePoint( 'hello world', 1 )\nout = base.lastCodePoint( 'JavaScript', 6 )\nout = base.lastCodePoint( 'अनुच्छेद', 1 )\n","base.lastGraphemeCluster":"var out = base.lastGraphemeCluster( 'beep', 1 )\nout = base.lastGraphemeCluster( 'Boop', 2 )\nout = base.lastGraphemeCluster( 'JavaScript', 6 )\n","base.lcm":"var v = base.lcm( 21, 6 )\n","base.ldexp":"var x = base.ldexp( 0.5, 3 )\nx = base.ldexp( 4.0, -2 )\nx = base.ldexp( 0.0, 20 )\nx = base.ldexp( -0.0, 39 )\nx = base.ldexp( NaN, -101 )\nx = base.ldexp( PINF, 11 )\nx = base.ldexp( NINF, -118 )\n","base.leftPad":"var out = base.leftPad( 'a', 5, ' ' )\nout = base.leftPad( 'beep', 10, 'b' )\nout = base.leftPad( 'boop', 12, 'beep' )\n","base.leftTrim":"var out = base.leftTrim( ' \\r\\n\\t  Beep \\t\\t\\n  ' )\n","base.ln":"var y = base.ln( 4.0 )\ny = base.ln( 0.0 )\ny = base.ln( PINF )\ny = base.ln( NaN )\ny = base.ln( -4.0 )\n","base.log":"var y = base.log( 100.0, 10.0 )\ny = base.log( 16.0, 2.0 )\ny = base.log( 5.0, 1.0 )\ny = base.log( NaN, 2.0 )\ny = base.log( 1.0, NaN )\ny = base.log( -4.0, 2.0 )\ny = base.log( 4.0, -2.0 )\n","base.log1mexp":"var y = base.log1mexp( -10.0 )\ny = base.log1mexp( 0.0 )\ny = base.log1mexp( 5.0 )\ny = base.log1mexp( 10.0 )\ny = base.log1mexp( NaN )\n","base.log1p":"var y = base.log1p( 4.0 )\ny = base.log1p( -1.0 )\ny = base.log1p( 0.0 )\ny = base.log1p( -0.0 )\ny = base.log1p( -2.0 )\ny = base.log1p( NaN )\n","base.log1pexp":"var y = base.log1pexp( -10.0 )\ny = base.log1pexp( 0.0 )\ny = base.log1pexp( 5.0 )\ny = base.log1pexp( 34.0 )\ny = base.log1pexp( NaN )\n","base.log1pmx":"base.log1pmx( 1.1 )\nbase.log1pmx( 0.99 )\nbase.log1pmx( -0.99 )\nbase.log1pmx( -1.1 )\nbase.log1pmx( NaN )\n","base.log2":"var y = base.log2( 4.0 )\ny = base.log2( 8.0 )\ny = base.log2( 0.0 )\ny = base.log2( PINF )\ny = base.log2( NaN )\ny = base.log2( -4.0 )\n","base.log10":"var y = base.log10( 100.0 )\ny = base.log10( 8.0 )\ny = base.log10( 0.0 )\ny = base.log10( PINF )\ny = base.log10( NaN )\ny = base.log10( -4.0 )\n","base.logaddexp":"var v = base.logaddexp( 90.0, 90.0 )\nv = base.logaddexp( -20.0, 90.0 )\nv = base.logaddexp( 0.0, -100.0 )\nv = base.logaddexp( NaN, NaN )\n","base.logit":"var y = base.logit( 0.2 )\ny = base.logit( 0.9 )\ny = base.logit( -4.0 )\ny = base.logit( 1.5 )\ny = base.logit( NaN )\n","base.lowercase":"var out = base.lowercase( 'bEEp' )\n","base.lucas":"var y = base.lucas( 0 )\ny = base.lucas( 1 )\ny = base.lucas( 2 )\ny = base.lucas( 3 )\ny = base.lucas( 4 )\ny = base.lucas( 77 )\ny = base.lucas( NaN )\n","base.lucaspoly":"var v = base.lucaspoly( 5, 2.0 )\n","base.lucaspoly.factory":"var polyval = base.lucaspoly.factory( 5 );\nvar v = polyval( 1.0 )\nv = polyval( 2.0 )\n","base.max":"var v = base.max( 3.14, 4.2 )\nv = base.max( 3.14, NaN )\nv = base.max( +0.0, -0.0 )\n","base.maxabs":"var v = base.maxabs( 3.14, -4.2 )\nv = base.maxabs( 3.14, NaN )\nv = base.maxabs( +0.0, -0.0 )\n","base.maxabsn":"var v = base.maxabsn( 3.14, -4.2 )\nv = base.maxabsn( 5.9, 3.14, 4.2 )\nv = base.maxabsn( 3.14, NaN )\nv = base.maxabsn( +0.0, -0.0 )\n","base.maxn":"var v = base.maxn( 3.14, 4.2 )\nv = base.maxn( 5.9, 3.14, 4.2 )\nv = base.maxn( 3.14, NaN )\nv = base.maxn( +0.0, -0.0 )\n","base.min":"var v = base.min( 3.14, 4.2 )\nv = base.min( 3.14, NaN )\nv = base.min( +0.0, -0.0 )\n","base.minabs":"var v = base.minabs( 3.14, -4.2 )\nv = base.minabs( 3.14, NaN )\nv = base.minabs( +0.0, -0.0 )\n","base.minabsn":"var v = base.minabsn( 3.14, -4.2 )\nv = base.minabsn( 5.9, 3.14, 4.2 )\nv = base.minabsn( 3.14, NaN )\nv = base.minabsn( +0.0, -0.0 )\n","base.minmax":"var v = base.minmax( 3.14, 4.2 )\nv = base.minmax( 3.14, NaN )\nv = base.minmax( +0.0, -0.0 )\n","base.minmax.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.minmax.assign( 3.14, -1.5, out, 1, 0 )\nvar bool = ( v === out )\n","base.minmaxabs":"var v = base.minmaxabs( 3.14, 4.2 )\nv = base.minmaxabs( -5.9, 3.14)\nv = base.minmaxabs( 3.14, NaN )\nv = base.minmaxabs( +0.0, -0.0 )\n","base.minmaxabs.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.minmaxabs.assign( 3.14, -3.14, out, 1, 0 )\nvar bool = ( v === out )\n","base.minmaxabsn":"var v = base.minmaxabsn( 3.14, 4.2 )\nv = base.minmaxabsn( -5.9, 3.14, 4.2 )\nv = base.minmaxabsn( 3.14, NaN )\nv = base.minmaxabsn( +0.0, -0.0 )\nv = base.minmaxabsn( 3.14 )\n","base.minmaxabsn.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.minmaxabsn.assign( 3.14, out, 1, 0 )\nvar bool = ( v === out )\n","base.minmaxn":"var v = base.minmaxn( 3.14, 4.2 )\nv = base.minmaxn( 5.9, 3.14, 4.2 )\nv = base.minmaxn( 3.14, NaN )\nv = base.minmaxn( +0.0, -0.0 )\nv = base.minmaxn( 3.14 )\n","base.minmaxn.assign":"var out = [ 0.0, 0.0 ];\nvar v = base.minmaxn.assign( 3.14, -1.5, out, 1, 0 )\nvar bool = ( v === out )\n","base.minn":"var v = base.minn( 3.14, 4.2 )\nv = base.minn( 5.9, 3.14, 4.2 )\nv = base.minn( 3.14, NaN )\nv = base.minn( +0.0, -0.0 )\n","base.modf":"var parts = base.modf( 3.14 )\nparts = base.modf( 3.14 )\nparts = base.modf( +0.0 )\nparts = base.modf( -0.0 )\nparts = base.modf( PINF )\nparts = base.modf( NINF )\nparts = base.modf( NaN )\n","base.modf.assign":"var out = new Float64Array( 2 );\nvar parts = base.modf.assign( 3.14, out, 1, 0 )\nvar bool = ( parts === out )\n","base.mul":"var v = base.mul( -1.0, 5.0 )\nv = base.mul( 2.0, 5.0 )\nv = base.mul( 0.0, 5.0 )\nv = base.mul( -0.0, 0.0 )\nv = base.mul( NaN, NaN )\n","base.mulf":"var v = base.mulf( -1.0, 5.0 )\nv = base.mulf( 2.0, 5.0 )\nv = base.mulf( 0.0, 5.0 )\nv = base.mulf( -0.0, 0.0 )\nv = base.mulf( NaN, NaN )\n","base.ndarray":"var b = [ 1, 2, 3, 4 ]; // underlying data buffer\nvar d = [ 2, 2 ]; // shape\nvar s = [ 2, 1 ]; // strides\nvar o = 0; // index offset\nvar arr = base.ndarray( 'generic', b, d, s, o, 'row-major' )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40 );\narr.get( 1, 1 )\narr.iset( 3, 99 );\narr.get( 1, 1 )\n","base.ndarray.prototype.byteLength":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.byteLength\n","base.ndarray.prototype.BYTES_PER_ELEMENT":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.BYTES_PER_ELEMENT\n","base.ndarray.prototype.data":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar buf = arr.data\n","base.ndarray.prototype.dtype":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar dt = arr.dtype\n","base.ndarray.prototype.flags":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar fl = arr.flags\n","base.ndarray.prototype.length":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar len = arr.length\n","base.ndarray.prototype.ndims":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar n = arr.ndims\n","base.ndarray.prototype.offset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.offset\n","base.ndarray.prototype.order: string":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar ord = arr.order\n","base.ndarray.prototype.shape":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sh = arr.shape\n","base.ndarray.prototype.strides":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar st = arr.strides\n","base.ndarray.prototype.get":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.get( 1, 1 )\n","base.ndarray.prototype.iget":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.iget( 3 )\n","base.ndarray.prototype.set":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\narr.set( 1, 1, -4.0 );\narr.get( 1, 1 )\n","base.ndarray.prototype.iset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\narr.iset( 3, -4.0 );\narr.iget( 3 )\n","base.ndarray.prototype.toString":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toString()\n","base.ndarray.prototype.toJSON":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toJSON()\n","base.ndarrayUnary":"var xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dtype = 'float64';\nvar shape = [ 2, 2 ];\nvar sx = [ 2, 1 ];\nvar sy = [ 2, 1 ];\nvar ox = 0;\nvar oy = 0;\nvar order = 'row-major';\nvar x = ndarray( dtype, xbuf, shape, sx, ox, order );\nvar y = ndarray( dtype, ybuf, shape, sy, oy, order );\nbase.ndarrayUnary( [ x, y ], base.abs );\ny.data\nx = {\n 'dtype': dtype,\n 'data': xbuf,\n 'shape': shape,\n 'strides': sx,\n 'offset': ox,\n 'order': order\n };\ny = {\n 'dtype': dtype,\n 'data': ybuf,\n 'shape': shape,\n 'strides': sy,\n 'offset': oy,\n 'order': order\n };\nbase.ndarrayUnary( [ x, y ], base.abs );\ny.data\n","base.ndzeros":"var arr = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\nvar sh = arr.shape\nvar dt = arr.dtype\n","base.ndzerosLike":"var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\nvar sh = x.shape\nvar dt = x.dtype\nvar y = base.ndzerosLike( x )\nsh = y.shape\ndt = y.dtype\n","base.negafibonacci":"var y = base.negafibonacci( 0 )\ny = base.negafibonacci( -1 )\ny = base.negafibonacci( -2 )\ny = base.negafibonacci( -3 )\ny = base.negafibonacci( -4 )\ny = base.negafibonacci( -79 )\ny = base.negafibonacci( -80 )\ny = base.negafibonacci( NaN )\n","base.negalucas":"var y = base.negalucas( 0 )\ny = base.negalucas( -1 )\ny = base.negalucas( -2 )\ny = base.negalucas( -3 )\ny = base.negalucas( -4 )\ny = base.negalucas( -77 )\ny = base.negalucas( -78 )\ny = base.negalucas( NaN )\n","base.nonfibonacci":"var v = base.nonfibonacci( 1 )\nv = base.nonfibonacci( 2 )\nv = base.nonfibonacci( 3 )\nv = base.nonfibonacci( NaN )\n","base.normalize":"var out = base.normalize( 3.14e-319 )\nvar y = out[ 0 ];\nvar exponent = out[ 1 ];\nvar bool = ( y*base.pow(2.0, exponent) === 3.14e-319 )\nout = base.normalize( 0.0 )\nout = base.normalize( PINF )\nout = base.normalize( NINF )\nout = base.normalize( NaN )\n","base.normalize.assign":"var out = new Float64Array( 2 )\nvar v = base.normalize.assign( 3.14e-319, out, 1, 0 )\nvar bool = ( v === out )\n","base.normalizef":"var out = base.normalizef( base.float64ToFloat32( 1.401e-45 ) )\nvar y = out[ 0 ];\nvar exp = out[ 1 ];\nvar bool = ( y*base.pow(2,exp) === base.float64ToFloat32(1.401e-45) )\nout = base.normalizef( FLOAT32_PINF )\nout = base.normalizef( FLOAT32_NINF )\nout = base.normalizef( NaN )\n","base.normalizef.assign":"out = new Float32Array( 2 );\nvar v = base.normalizef.assign( base.float64ToFloat32( 1.401e-45 ), out, 1, 0 )\nbool = ( v === out )\n","base.normalizeSlice":"var s1 = new Slice( 1, 10, 1 );\nvar s2 = base.normalizeSlice( s1, 5, false );\ns2.start\ns2.stop\ns2.step\ns1 = new Slice( -2, null, -1 );\ns2 = base.normalizeSlice( s1, 10, false );\ns2.start\ns2.stop\ns2.step\n","base.normhermitepoly":"var y = base.normhermitepoly( 1, 0.5 )\ny = base.normhermitepoly( -1, 0.5 )\ny = base.normhermitepoly( 0, 0.5 )\ny = base.normhermitepoly( 2, 0.5 )\n","base.normhermitepoly.factory":"var f = base.normhermitepoly.factory( 2 );\nvar v = f( 0.5 )\n","base.pascalcase":"var out = base.pascalcase( 'Hello World!' )\nout = base.pascalcase( 'beep boop' )\n","base.pdiff":"var v = base.pdiff( 5.9, 3.14 )\nv = base.pdiff( 3.14, 4.2 )\nv = base.pdiff( 3.14, NaN )\nv = base.pdiff( -0.0, +0.0 )\n","base.pdifff":"var v = base.pdifff( 5.9, 3.15 )\nv = base.pdifff( 3.14, 4.2 )\nv = base.pdifff( 3.14, NaN )\nv = base.pdifff( -0.0, +0.0 )\n","base.percentEncode":"var out = base.percentEncode( '☃' )\n","base.polygamma":"var v = base.polygamma( 3, 1.2 )\nv = base.polygamma( 5, 1.2 )\nv = base.polygamma( 3, -4.9 )\nv = base.polygamma( -1, 5.3 )\nv = base.polygamma( 2, -1.0 )\n","base.pow":"var y = base.pow( 2.0, 3.0 )\ny = base.pow( 4.0, 0.5 )\ny = base.pow( 100.0, 0.0 )\ny = base.pow( PI, 5.0 )\ny = base.pow( PI, -0.2 )\ny = base.pow( NaN, 3.0 )\ny = base.pow( 5.0, NaN )\ny = base.pow( NaN, NaN )\n","base.powm1":"var y = base.powm1( 2.0, 3.0 )\ny = base.powm1( 4.0, 0.5 )\ny = base.powm1( 0.0, 100.0 )\ny = base.powm1( 100.0, 0.0 )\ny = base.powm1( 0.0, 0.0 )\ny = base.powm1( PI, 5.0 )\ny = base.powm1( NaN, 3.0 )\ny = base.powm1( 5.0, NaN )\n","base.rad2deg":"var d = base.rad2deg( PI/2.0 )\nd = base.rad2deg( -PI/4.0 )\nd = base.rad2deg( NaN )\nd = base.rad2deg( PI/6.0 )\n","base.rad2degf":"var d = base.rad2degf( 3.141592653589793 / 2.0 )\nd = base.rad2degf( -3.141592653589793 / 4.0 )\nd = base.rad2degf( NaN )\nd = base.rad2degf( 3.141592653589793 / 6.0 )\n","base.ramp":"var y = base.ramp( 3.14 )\ny = base.ramp( -3.14 )\n","base.rampf":"var y = base.rampf( 3.14 )\ny = base.rampf( -3.14 )\n","base.random.arcsine":"var r = base.random.arcsine( 2.0, 5.0 )\n","base.random.arcsine.factory":"var rand = base.random.arcsine.factory();\nvar r = rand( 0.0, 1.0 )\nr = rand( -2.0, 2.0 )\nrand = base.random.arcsine.factory( 0.0, 1.0 );\nr = rand()\nr = rand()\n","base.random.arcsine.NAME":"var str = base.random.arcsine.NAME\n","base.random.arcsine.PRNG":"var prng = base.random.arcsine.PRNG;\n","base.random.arcsine.seed":"var seed = base.random.arcsine.seed;\n","base.random.arcsine.seedLength":"var len = base.random.arcsine.seedLength;\n","base.random.arcsine.state":"var r = base.random.arcsine( 2.0, 4.0 )\nr = base.random.arcsine( 2.0, 4.0 )\nr = base.random.arcsine( 2.0, 4.0 )\nvar state = base.random.arcsine.state\nr = base.random.arcsine( 2.0, 4.0 )\nr = base.random.arcsine( 2.0, 4.0 )\nbase.random.arcsine.state = state;\nr = base.random.arcsine( 2.0, 4.0 )\nr = base.random.arcsine( 2.0, 4.0 )\n","base.random.arcsine.stateLength":"var len = base.random.arcsine.stateLength;\n","base.random.arcsine.byteLength":"var sz = base.random.arcsine.byteLength;\n","base.random.arcsine.toJSON":"var o = base.random.arcsine.toJSON()\n","base.random.bernoulli":"var r = base.random.bernoulli( 0.8 );\n","base.random.bernoulli.factory":"var rand = base.random.bernoulli.factory();\nvar r = rand( 0.3 );\nr = rand( 0.59 );\nrand = base.random.bernoulli.factory( 0.3 );\nr = rand();\nr = rand();\n","base.random.bernoulli.NAME":"var str = base.random.bernoulli.NAME\n","base.random.bernoulli.PRNG":"var prng = base.random.bernoulli.PRNG;\n","base.random.bernoulli.seed":"var seed = base.random.bernoulli.seed;\n","base.random.bernoulli.seedLength":"var len = base.random.bernoulli.seedLength;\n","base.random.bernoulli.state":"var r = base.random.bernoulli( 0.3 )\nr = base.random.bernoulli( 0.3 )\nr = base.random.bernoulli( 0.3 )\nvar state = base.random.bernoulli.state\nr = base.random.bernoulli( 0.3 )\nr = base.random.bernoulli( 0.3 )\nbase.random.bernoulli.state = state;\nr = base.random.bernoulli( 0.3 )\nr = base.random.bernoulli( 0.3 )\n","base.random.bernoulli.stateLength":"var len = base.random.bernoulli.stateLength;\n","base.random.bernoulli.byteLength":"var sz = base.random.bernoulli.byteLength;\n","base.random.bernoulli.toJSON":"var o = base.random.bernoulli.toJSON()\n","base.random.beta":"var r = base.random.beta( 2.0, 5.0 );\n","base.random.beta.factory":"var rand = base.random.beta.factory();\nvar r = rand( 1.5, 1.5 );\nr = rand( 2.0, 3.14 );\nrand = base.random.beta.factory( 1.5, 1.5 );\nr = rand();\nr = rand();\n","base.random.beta.NAME":"var str = base.random.beta.NAME\n","base.random.beta.PRNG":"var prng = base.random.beta.PRNG;\n","base.random.beta.seed":"var seed = base.random.beta.seed;\n","base.random.beta.seedLength":"var len = base.random.beta.seedLength;\n","base.random.beta.state":"var r = base.random.beta( 2.0, 5.0 )\nr = base.random.beta( 2.0, 5.0 )\nr = base.random.beta( 2.0, 5.0 )\nvar state = base.random.beta.state\nr = base.random.beta( 2.0, 5.0 )\nr = base.random.beta( 2.0, 5.0 )\nbase.random.beta.state = state;\nr = base.random.beta( 2.0, 5.0 )\nr = base.random.beta( 2.0, 5.0 )\n","base.random.beta.stateLength":"var len = base.random.beta.stateLength;\n","base.random.beta.byteLength":"var sz = base.random.beta.byteLength;\n","base.random.beta.toJSON":"var o = base.random.beta.toJSON()\n","base.random.betaprime":"var r = base.random.betaprime( 2.0, 5.0 );\n","base.random.betaprime.factory":"var rand = base.random.betaprime.factory();\nvar r = rand( 1.5, 1.5 );\nr = rand( 2.0, 3.14 );\nrand = base.random.betaprime.factory( 1.5, 1.5 );\nr = rand();\nr = rand();\n","base.random.betaprime.NAME":"var str = base.random.betaprime.NAME\n","base.random.betaprime.PRNG":"var prng = base.random.betaprime.PRNG;\n","base.random.betaprime.seed":"var seed = base.random.betaprime.seed;\n","base.random.betaprime.seedLength":"var len = base.random.betaprime.seedLength;\n","base.random.betaprime.state":"var r = base.random.betaprime( 2.0, 5.0 )\nr = base.random.betaprime( 2.0, 5.0 )\nr = base.random.betaprime( 2.0, 5.0 )\nvar state = base.random.betaprime.state\nr = base.random.betaprime( 2.0, 5.0 )\nr = base.random.betaprime( 2.0, 5.0 )\nbase.random.betaprime.state = state;\nr = base.random.betaprime( 2.0, 5.0 )\nr = base.random.betaprime( 2.0, 5.0 )\n","base.random.betaprime.stateLength":"var len = base.random.betaprime.stateLength;\n","base.random.betaprime.byteLength":"var sz = base.random.betaprime.byteLength;\n","base.random.betaprime.toJSON":"var o = base.random.betaprime.toJSON()\n","base.random.binomial":"var r = base.random.binomial( 20, 0.8 );\n","base.random.binomial.factory":"var rand = base.random.binomial.factory();\nvar r = rand( 20, 0.3 );\nr = rand( 10, 0.77 );\nrand = base.random.binomial.factory( 10, 0.8 );\nr = rand();\nr = rand();\n","base.random.binomial.NAME":"var str = base.random.binomial.NAME\n","base.random.binomial.PRNG":"var prng = base.random.binomial.PRNG;\n","base.random.binomial.seed":"var seed = base.random.binomial.seed;\n","base.random.binomial.seedLength":"var len = base.random.binomial.seedLength;\n","base.random.binomial.state":"var r = base.random.binomial( 20, 0.8 )\nr = base.random.binomial( 20, 0.8 )\nr = base.random.binomial( 20, 0.8 )\nvar state = base.random.binomial.state\nr = base.random.binomial( 20, 0.8 )\nr = base.random.binomial( 20, 0.8 )\nbase.random.binomial.state = state;\nr = base.random.binomial( 20, 0.8 )\nr = base.random.binomial( 20, 0.8 )\n","base.random.binomial.stateLength":"var len = base.random.binomial.stateLength;\n","base.random.binomial.byteLength":"var sz = base.random.binomial.byteLength;\n","base.random.binomial.toJSON":"var o = base.random.binomial.toJSON()\n","base.random.boxMuller":"var r = base.random.boxMuller();\n","base.random.boxMuller.factory":"var rand = base.random.boxMuller.factory();\nr = rand();\nr = rand();\n","base.random.boxMuller.NAME":"var str = base.random.boxMuller.NAME\n","base.random.boxMuller.PRNG":"var prng = base.random.boxMuller.PRNG;\n","base.random.boxMuller.seed":"var seed = base.random.boxMuller.seed;\n","base.random.boxMuller.seedLength":"var len = base.random.boxMuller.seedLength;\n","base.random.boxMuller.state":"var r = base.random.boxMuller()\nr = base.random.boxMuller()\nr = base.random.boxMuller()\nvar state = base.random.boxMuller.state\nr = base.random.boxMuller()\nr = base.random.boxMuller()\nbase.random.boxMuller.state = state;\nr = base.random.boxMuller()\nr = base.random.boxMuller()\n","base.random.boxMuller.stateLength":"var len = base.random.boxMuller.stateLength;\n","base.random.boxMuller.byteLength":"var sz = base.random.boxMuller.byteLength;\n","base.random.boxMuller.toJSON":"var o = base.random.boxMuller.toJSON()\n","base.random.cauchy":"var r = base.random.cauchy( 2.0, 5.0 );\n","base.random.cauchy.factory":"var rand = base.random.cauchy.factory();\nvar r = rand( 0.0, 1.5 );\nr = rand( -2.0, 2.0 );\nrand = base.random.cauchy.factory( 0.0, 1.5 );\nr = rand();\nr = rand();\n","base.random.cauchy.NAME":"var str = base.random.cauchy.NAME\n","base.random.cauchy.PRNG":"var prng = base.random.cauchy.PRNG;\n","base.random.cauchy.seed":"var seed = base.random.cauchy.seed;\n","base.random.cauchy.seedLength":"var len = base.random.cauchy.seedLength;\n","base.random.cauchy.state":"var r = base.random.cauchy( 2.0, 5.0 )\nr = base.random.cauchy( 2.0, 5.0 )\nr = base.random.cauchy( 2.0, 5.0 )\nvar state = base.random.cauchy.state\nr = base.random.cauchy( 2.0, 5.0 )\nr = base.random.cauchy( 2.0, 5.0 )\nbase.random.cauchy.state = state;\nr = base.random.cauchy( 2.0, 5.0 )\nr = base.random.cauchy( 2.0, 5.0 )\n","base.random.cauchy.stateLength":"var len = base.random.cauchy.stateLength;\n","base.random.cauchy.byteLength":"var sz = base.random.cauchy.byteLength;\n","base.random.cauchy.toJSON":"var o = base.random.cauchy.toJSON()\n","base.random.chi":"var r = base.random.chi( 2 );\n","base.random.chi.factory":"var rand = base.random.chi.factory();\nvar r = rand( 5 );\nr = rand( 3.14 );\nrand = base.random.chi.factory( 3 );\nr = rand();\nr = rand();\n","base.random.chi.NAME":"var str = base.random.chi.NAME\n","base.random.chi.PRNG":"var prng = base.random.chi.PRNG;\n","base.random.chi.seed":"var seed = base.random.chi.seed;\n","base.random.chi.seedLength":"var len = base.random.chi.seedLength;\n","base.random.chi.state":"var r = base.random.chi( 2 )\nr = base.random.chi( 2 )\nr = base.random.chi( 2 )\nvar state = base.random.chi.state\nr = base.random.chi( 2 )\nr = base.random.chi( 2 )\nbase.random.chi.state = state;\nr = base.random.chi( 2 )\nr = base.random.chi( 2 )\n","base.random.chi.stateLength":"var len = base.random.chi.stateLength;\n","base.random.chi.byteLength":"var sz = base.random.chi.byteLength;\n","base.random.chi.toJSON":"var o = base.random.chi.toJSON()\n","base.random.chisquare":"var r = base.random.chisquare( 2 );\n","base.random.chisquare.factory":"var rand = base.random.chisquare.factory();\nvar r = rand( 5 );\nr = rand( 3.14 );\nrand = base.random.chisquare.factory( 3 );\nr = rand();\nr = rand();\n","base.random.chisquare.NAME":"var str = base.random.chisquare.NAME\n","base.random.chisquare.PRNG":"var prng = base.random.chisquare.PRNG;\n","base.random.chisquare.seed":"var seed = 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rand = base.random.randn.factory({ 'name': 'box-muller' });\nr = rand();\nr = rand();\n","base.random.randn.NAME":"var str = base.random.randn.NAME\n","base.random.randn.PRNG":"var prng = base.random.randn.PRNG;\n","base.random.randn.seed":"var seed = base.random.randn.seed;\n","base.random.randn.seedLength":"var len = base.random.randn.seedLength;\n","base.random.randn.state":"var r = base.random.randn()\nr = base.random.randn()\nr = base.random.randn()\nvar state = base.random.randn.state;\nr = base.random.randn()\nr = base.random.randn()\nbase.random.randn.state = state;\nr = base.random.randn()\nr = base.random.randn()\n","base.random.randn.stateLength":"var len = base.random.randn.stateLength;\n","base.random.randn.byteLength":"var sz = base.random.randn.byteLength;\n","base.random.randn.toJSON":"var o = base.random.randn.toJSON()\n","base.random.randu":"var r = base.random.randu();\n","base.random.randu.factory":"var rand = base.random.randu.factory();\nvar r = rand();\nr = 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base.random.triangular( 0.0, 1.0, 0.5 )\nr = base.random.triangular( 0.0, 1.0, 0.5 )\nbase.random.triangular.state = state;\nr = base.random.triangular( 0.0, 1.0, 0.5 )\nr = base.random.triangular( 0.0, 1.0, 0.5 )\n","base.random.triangular.stateLength":"var len = base.random.triangular.stateLength;\n","base.random.triangular.byteLength":"var sz = base.random.triangular.byteLength;\n","base.random.triangular.toJSON":"var o = base.random.triangular.toJSON()\n","base.random.uniform":"var r = base.random.uniform( 2.0, 5.0 );\n","base.random.uniform.factory":"var rand = base.random.uniform.factory();\nvar r = rand( 0.0, 1.0 );\nr = rand( -2.0, 2.0 );\nrand = base.random.uniform.factory( 0.0, 1.0 );\nr = rand();\nr = rand();\n","base.random.uniform.NAME":"var str = base.random.uniform.NAME\n","base.random.uniform.PRNG":"var prng = base.random.uniform.PRNG;\n","base.random.uniform.seed":"var seed = base.random.uniform.seed;\n","base.random.uniform.seedLength":"var len = base.random.uniform.seedLength;\n","base.random.uniform.state":"var r = base.random.uniform( 2.0, 5.0 )\nr = base.random.uniform( 2.0, 5.0 )\nr = base.random.uniform( 2.0, 5.0 )\nvar state = base.random.uniform.state\nr = base.random.uniform( 2.0, 5.0 )\nr = base.random.uniform( 2.0, 5.0 )\nbase.random.uniform.state = state;\nr = base.random.uniform( 2.0, 5.0 )\nr = base.random.uniform( 2.0, 5.0 )\n","base.random.uniform.stateLength":"var len = base.random.uniform.stateLength;\n","base.random.uniform.byteLength":"var sz = base.random.uniform.byteLength;\n","base.random.uniform.toJSON":"var o = base.random.uniform.toJSON()\n","base.random.weibull":"var r = base.random.weibull( 2.0, 5.0 );\n","base.random.weibull.factory":"var rand = base.random.weibull.factory();\nvar r = rand( 0.1, 1.5 );\nr = rand( 2.0, 3.14 );\nrand = base.random.weibull.factory( 0.1, 1.5 );\nr = rand();\nr = rand();\n","base.random.weibull.NAME":"var str = base.random.weibull.NAME\n","base.random.weibull.PRNG":"var 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base.rcbrtf( 1000.0 )\ny = base.rcbrtf( 0.0 )\ny = base.rcbrtf( PINF )\ny = base.rcbrtf( -8.0 )\ny = base.rcbrtf( NaN )\n","base.reldiff":"var d = base.reldiff( 2.0, 5.0 )\nd = base.reldiff( -1.0, 3.14 )\nd = base.reldiff( -2.0, 5.0, 'max-abs' )\nd = base.reldiff( -2.0, 5.0, 'max' )\nd = base.reldiff( -2.0, 5.0, 'min-abs' )\nd = base.reldiff( -2.0, 5.0, 'min' )\nd = base.reldiff( -2.0, 5.0, 'mean-abs' )\nd = base.reldiff( -2.0, 5.0, 'mean' )\nd = base.reldiff( -2.0, 5.0, 'x' )\nd = base.reldiff( 5.0, -2.0, 'x' )\nd = base.reldiff( -2.0, 5.0, 'y' )\nd = base.reldiff( 5.0, -2.0, 'y' )\nfunction scale( x, y ) {\n var s;\n\n x = base.abs( x );\n y = base.abs( y );\n\n // Maximum absolute value:\n s = (x < y ) ? y : x;\n\n // Scale in units of epsilon:\n return s * EPS;\n };\nd = base.reldiff( 12.15, 12.149999999999999, scale )\n","base.removeFirst":"var out = base.removeFirst( 'beep', 1 )\nout = base.removeFirst( 'Boop', 1 )\nout = base.removeFirst( 'foo bar', 5 )\n","base.removeFirstCodePoint":"var out = base.removeFirstCodePoint( 'beep', 1 )\nout = base.removeFirstCodePoint( 'Boop', 1 )\nout = base.removeFirstCodePoint( 'foo bar', 5 )\n","base.removeFirstGraphemeCluster":"var out = base.removeFirstGraphemeCluster( 'beep', 1 )\nout = base.removeFirstGraphemeCluster( 'Boop', 1 )\nout = base.removeFirstGraphemeCluster( 'foo bar', 5 )\n","base.removeLast":"var out = base.removeLast( 'beep', 1 )\nout = base.removeLast( 'Boop', 1 )\nout = base.removeLast( 'foo bar', 5 )\n","base.removeLastCodePoint":"var out = base.removeLastCodePoint( 'beep', 1 )\nout = base.removeLastCodePoint( 'Boop', 1 )\nout = base.removeLastCodePoint( 'foo bar', 5 )\n","base.removeLastGraphemeCluster":"var out = base.removeLastGraphemeCluster( 'beep', 1 )\nout = base.removeLastGraphemeCluster( 'Boop', 1 )\nout = base.removeLastGraphemeCluster( 'foo bar', 5 )\n","base.rempio2":"var y = [ 0.0, 0.0 ];\nvar n = base.rempio2( 128.0, y )\nvar y1 = y[ 0 ]\nvar y2 = y[ 1 ]\n","base.repeat":"var out = base.repeat( 'a', 5 )\nout = base.repeat( '', 100 )\nout = base.repeat( 'beep', 0 )\n","base.replace":"function replacer( match, p1 ) { return '/'+p1+'/'; };\nvar str = 'Oranges and lemons';\nvar out = base.replace( str, /([^\\s]+)/gi, replacer )\nout = base.replace( 'beep', /e/, 'o' )\n","base.replaceAfter":"var out = base.replaceAfter( 'beep boop', ' ', 'foo', 0 )\nout = base.replaceAfter( 'beep boop', 'o', 'foo', 0 )\nout = base.replaceAfter( 'Hello World!', 'o', 'foo', 5 )\nout = base.replaceAfter( 'beep boop beep baz', 'beep', 'foo', 5 )\n","base.replaceAfterLast":"var str = 'beep boop';\nvar out = base.replaceAfterLast( str, ' ', 'foo', str.length )\nout = base.replaceAfterLast( str, 'o', 'foo', str.length )\nout = base.replaceAfterLast( 'Hello World!', 'o', 'foo', 5 )\n","base.replaceBefore":"var out = base.replaceBefore( 'beep boop', ' ', 'foo', 0 )\nout = base.replaceBefore( 'beep boop', 'o', 'foo', 0 )\n","base.replaceBeforeLast":"var str = 'beep boop';\nvar out = base.replaceBeforeLast( str, ' ', 'foo', str.length )\nout = base.replaceBeforeLast( str, 'o', 'foo', str.length )\nout = base.replaceBeforeLast( 'Hello World!', 'o', 'foo', 5 )\n","base.reverse":"var out = base.reverse( 'beep' )\nout = base.reverse( 'Boop' )\nout = base.reverse( 'foo bar' )\n","base.reverseCodePoints":"var out = base.reverseCodePoints( 'beep' )\nout = base.reverseCodePoints( 'Boop' )\nout = base.reverseCodePoints( 'foo bar' )\n","base.reverseGraphemeClusters":"var out = base.reverseGraphemeClusters( 'beep' )\nout = base.reverseGraphemeClusters( 'Boop' )\nout = base.reverseGraphemeClusters( 'foo bar' )\n","base.rightPad":"var out = base.rightPad( 'a', 5, ' ' )\nout = base.rightPad( 'beep', 10, 'b' )\nout = base.rightPad( 'boop', 12, 'beep' )\n","base.rightTrim":"var out = base.rightTrim( ' \\t\\t\\n  Beep \\r\\n\\t  ' )\n","base.risingFactorial":"var v = base.risingFactorial( 0.9, 5 )\nv = base.risingFactorial( -9.0, 3 )\nv = base.risingFactorial( 0.0, 2 )\nv = base.risingFactorial( 3.0, -2 )\n","base.rotl32":"var x = 2147483649;\nvar bStr = base.toBinaryStringUint32( x )\nvar y = base.rotl32( x, 10 )\nbstr = base.toBinaryStringUint32( y )\n","base.rotr32":"var x = 1;\nvar bStr = base.toBinaryStringUint32( x )\nvar y = base.rotr32( x, 10 )\nbstr = base.toBinaryStringUint32( y )\n","base.round":"var y = base.round( 3.14 )\ny = base.round( -4.2 )\ny = base.round( -4.6 )\ny = base.round( 9.5 )\ny = base.round( -0.0 )\n","base.round2":"var y = base.round2( 3.14 )\ny = base.round2( -4.2 )\ny = base.round2( -4.6 )\ny = base.round2( 9.5 )\ny = base.round2( 13.0 )\ny = base.round2( -13.0 )\ny = base.round2( -0.0 )\n","base.round10":"var y = base.round10( 3.14 )\ny = base.round10( -4.2 )\ny = base.round10( -4.6 )\ny = base.round10( 9.5 )\ny = base.round10( 13.0 )\ny = base.round10( -13.0 )\ny = base.round10( -0.0 )\n","base.roundb":"var y = base.roundb( 3.14159, -2, 10 )\ny = base.roundb( 3.14159, 0, 2 )\ny = base.roundb( 5.0, 1, 2 )\n","base.roundn":"var y = base.roundn( 3.14159, -2 )\ny = base.roundn( 3.14159, 0 )\ny = base.roundn( 12368.0, 3 )\n","base.roundsd":"var y = base.roundsd( 3.14159, 3 )\ny = base.roundsd( 3.14159, 1 )\ny = base.roundsd( 12368.0, 2 )\ny = base.roundsd( 0.0313, 2, 2 )\n","base.rsqrt":"var y = base.rsqrt( 4.0 )\ny = base.rsqrt( 100.0 )\ny = base.rsqrt( 0.0 )\ny = base.rsqrt( Infinity )\ny = base.rsqrt( -4.0 )\ny = base.rsqrt( NaN )\n","base.rsqrtf":"var y = base.rsqrtf( 4.0 )\ny = base.rsqrtf( 0.0 )\ny = base.rsqrtf( Infinity )\ny = base.rsqrtf( -4.0 )\ny = base.rsqrtf( NaN )\n","base.sargs2multislice":"var s = new base.sargs2multislice( 'null,null,null' );\ns.data\ns = new base.sargs2multislice( '10,Slice(0,10,1),null' );\ns.data\n","base.scalar2ndarray":"var x = base.scalar2ndarray( 1.0, 'float64', 'row-major' )\nvar sh = x.shape\nvar dt = x.dtype\nvar v = x.get()\n","base.secd":"var y = base.secd( 1.0 )\ny = base.secd( PI )\ny = base.secd( -PI )\ny = base.secd( NaN )\n","base.seq2multislice":"var s = new base.seq2multislice( '1:10', [ 10 ], false );\ns.data\ns = new base.seq2multislice( '4,2:5:2,:', [ 10, 10, 10 ], false );\ns.data\n","base.seq2slice":"var s = new base.seq2slice( '1:10', 10, false );\ns.start\ns.stop\ns.step\ns = new base.seq2slice( '2:5:2', 10, false );\ns.start\ns.stop\ns.step\n","base.setHighWord":"var high = 1072693248 >>> 0;\nvar y = base.setHighWord( PINF, high )\n","base.setLowWord":"var low = 5 >>> 0;\nvar x = 3.14e201;\nvar y = base.setLowWord( x, low )\nvar low = 12345678;\nvar y = base.setLowWord( PINF, low )\ny = base.setLowWord( NINF, low )\ny = base.setLowWord( NaN, low )\n","base.sici":"var y = base.sici( 3.0 )\ny = base.sici( 0.0 )\ny = base.sici( -9.0 )\ny = base.sici( NaN )\n","base.sici.assign":"var out = new Float64Array( 2 );\nvar y = base.sici.assign( 3.0, out, 1, 0 )\nvar bool = ( y === out )\n","base.signbit":"var bool = base.signbit( 4.0 )\nbool = base.signbit( -9.14e-34 )\nbool = base.signbit( 0.0 )\nbool = base.signbit( -0.0 )\n","base.signbitf":"var bool = base.signbitf( base.float64ToFloat32( 4.0 ) )\nbool = base.signbitf( base.float64ToFloat32( -9.14e-34 ) )\nbool = base.signbitf( 0.0 )\nbool = base.signbitf( -0.0 )\n","base.significandf":"var s = base.significandf( base.float64ToFloat32( 3.14e34 ) )\ns = base.significandf( base.float64ToFloat32( 3.14e-34 ) )\ns = base.significandf( base.float64ToFloat32( -3.14 ) )\ns = base.significandf( 0.0 )\ns = base.significandf( NaN )\n","base.signum":"var sign = base.signum( -5.0 )\nsign = base.signum( 5.0 )\nsign = base.signum( -0.0 )\nsign = base.signum( 0.0 )\nsign = base.signum( NaN )\n","base.signumf":"var sign = base.signumf( -5.0 )\nsign = base.signumf( 5.0 )\nsign = base.signumf( -0.0 )\nsign = base.signumf( 0.0 )\nsign = base.signumf( NaN )\n","base.sin":"var y = base.sin( 0.0 )\ny = base.sin( PI/2.0 )\ny = base.sin( -PI/6.0 )\ny = base.sin( NaN )\n","base.sinc":"var y = base.sinc( 0.5 )\ny = base.sinc( -1.2 )\ny = base.sinc( 0.0 )\ny = base.sinc( NaN )\n","base.sincos":"var y = base.sincos( 0.0 )\ny = base.sincos( PI/2.0 )\ny = base.sincos( -PI/6.0 )\ny = base.sincos( NaN )\nvar out = new Float64Array( 2 );\nvar v = base.sincos.assign( 0.0, out, 1, 0 )\nvar bool = ( v === out )\n","base.sincospi":"var y = base.sincospi( 0.0 )\ny = base.sincospi( 0.5 )\ny = base.sincospi( 0.1 )\ny = base.sincospi( NaN )\n","base.sincospi.assign":"var out = new Float64Array( 2 );\nvar v = base.sincospi.assign( 0.0, out, 1, 0 )\nvar bool = ( v === out )\n","base.sinh":"var y = base.sinh( 0.0 )\ny = base.sinh( 2.0 )\ny = base.sinh( -2.0 )\ny = base.sinh( NaN )\n","base.sinpi":"var y = base.sinpi( 0.0 )\ny = base.sinpi( 0.5 )\ny = base.sinpi( 0.9 )\ny = base.sinpi( NaN )\n","base.slice2seq":"var out = base.slice2seq( new Slice( 1, 10, 1 ) )\nout = base.slice2seq( new Slice( null, 10 ) )\n","base.sliceLength":"var s = new Slice( 1, 10, 1 );\nbase.sliceLength( s )\n","base.sliceNonReducedDimensions":"var s = new MultiSlice( 1, 3, null );\nvar out = base.sliceNonReducedDimensions( s )\n","base.sliceReducedDimensions":"var s = new MultiSlice( 1, 3, null );\nvar out = base.sliceReducedDimensions( s )\n","base.sliceShape":"var s = new Slice( 1, 10, 1 );\nvar ms = new MultiSlice( s, s );\nbase.sliceShape( ms )\n","base.snakecase":"var out = base.snakecase( 'Hello World!' )\nout = base.snakecase( 'I am a tiny little teapot' )\n","base.spence":"var y = base.spence( 3.0 )\ny = base.spence( 0.0 )\ny = base.spence( -9.0 )\ny = base.spence( NaN )\n","base.sqrt":"var y = base.sqrt( 4.0 )\ny = base.sqrt( 9.0 )\ny = base.sqrt( 0.0 )\ny = base.sqrt( -4.0 )\ny = base.sqrt( NaN )\n","base.sqrt1pm1":"var y = base.sqrt1pm1( 3.0 )\ny = base.sqrt1pm1( 0.5 )\ny = base.sqrt1pm1( 0.02 )\ny = base.sqrt1pm1( -0.5 )\ny = base.sqrt1pm1( -1.1 )\ny = base.sqrt1pm1( NaN )\n","base.sqrtf":"var y = base.sqrtf( 4.0 )\ny = base.sqrtf( 9.0 )\ny = base.sqrtf( 0.0 )\ny = base.sqrtf( -4.0 )\ny = base.sqrtf( NaN )\n","base.sqrtpi":"var y = base.sqrtpi( 4.0 )\ny = base.sqrtpi( 10.0 )\ny = base.sqrtpi( 0.0 )\ny = base.sqrtpi( -4.0 )\ny = base.sqrtpi( NaN )\n","base.startcase":"var out = base.startcase( 'beep boop' )\n","base.startsWith":"var bool = base.startsWith( 'Beep', 'Be', 0 )\nbool = base.startsWith( 'Beep', 'ep', 0 )\nbool = base.startsWith( 'Beep', 'ee', 1 )\nbool = base.startsWith( 'Beep', 'ee', -3 )\nbool = base.startsWith( 'Beep', '', 0 )\n","base.stickycase":"var out = base.stickycase( 'Hello World!' )\nout = base.stickycase( 'I am a tiny little teapot' )\n","base.strided.binary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nfunction f( x, y ) { return x + y; };\nbase.strided.binary( [ x, y, z ], shape, strides, f );\nz\n","base.strided.binary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nvar offsets = [ 0, 0, 0 ];\nfunction f( x, y ) { return x + y; };\nbase.strided.binary.ndarray( [ x, y, z ], shape, strides, offsets, f );\nz\n","base.strided.binaryDtypeSignatures":"var dt = strided.dataTypes();\nvar out = base.strided.binaryDtypeSignatures( dt, dt, dt )\n","base.strided.binarySignatureCallbacks":"var dt = strided.dataTypes();\nvar sigs = base.strided.binaryDtypeSignatures( dt, dt, dt );\nvar t = {\n 'default': base.add,\n 'complex64': base.caddf,\n 'complex128': base.cadd\n };\nvar out = base.strided.binarySignatureCallbacks( t, sigs )\n","base.strided.ccopy":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.ccopy( x.length, x, 1, y, 1 );\nvar z = y.get( 0 );\nvar re = realf( z )\nvar im = imagf( z )\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ccopy( 2, x, -2, y, 1 );\nz = y.get( 0 );\nre = realf( z )\nim = imagf( z )\nvar x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\nvar y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.ccopy( 2, x1, -2, y1, 1 );\nz = y0.get( 2 );\nre = realf( z )\nim = imagf( z )\n","base.strided.ccopy.ndarray":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.ccopy.ndarray( x.length, x, 1, 0, y, 1, 0 );\nvar z = y.get( 0 );\nvar re = realf( z )\nvar im = imagf( z )\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ccopy.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\nz = y.get( y.length-1 );\nre = realf( z )\nim = imagf( z )\n","base.strided.cmap":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex64Array( xbuf );\nvar y = new Complex64Array( x.length );\nbase.strided.cmap( x.length, x, 1, y, 1, base.cidentityf );\nvar v = y.get( 0 )\nvar re = real( v )\nvar im = imag( v )\ny = new Complex64Array( x.length );\nbase.strided.cmap( 2, x, 2, y, -1, base.cidentityf );\nv = y.get( 0 )\nre = real( v )\nim = imag( v )\nvar x0 = new Complex64Array( xbuf );\nvar y0 = new Complex64Array( x0.length );\nvar x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.cmap( 2, x1, -2, y1, 1, base.cidentityf );\nv = y1.get( 0 )\nre = real( v )\nim = imag( v )\n","base.strided.cmap.ndarray":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex64Array( xbuf );\nvar y = new Complex64Array( x.length );\nbase.strided.cmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentityf );\nvar v = y.get( 0 )\nvar re = real( v )\nvar im = imag( v )\nx = new Complex64Array( xbuf );\ny = new Complex64Array( x.length );\nbase.strided.cmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentityf );\nv = y.get( y.length-1 )\nre = real( v )\nim = imag( v )\n","base.strided.cswap":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.cswap( x.length, x, 1, y, 1 );\nvar z = y.get( 0 );\nvar re = realf( z )\nvar im = imagf( z )\nz = x.get( 0 );\nre = realf( z )\nim = imagf( z )\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.cswap( 2, x, -2, y, 1 );\nz = y.get( 0 );\nre = realf( z )\nim = imagf( z )\nz = x.get( 0 );\nre = realf( z )\nim = imagf( z )\nvar x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\nvar y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.cswap( 2, x1, -2, y1, 1 );\nz = y0.get( 2 );\nre = realf( z )\nim = imagf( z )\nz = x0.get( 1 );\nre = realf( z )\nim = imagf( z )\n","base.strided.cswap.ndarray":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\nbase.strided.cswap.ndarray( x.length, x, 1, 0, y, 1, 0 );\nvar z = y.get( 0 );\nvar re = realf( z )\nvar im = imagf( z )\nz = x.get( 0 );\nre = realf( z )\nim = imagf( z )\nx = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\ny = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.cswap.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\nz = y.get( y.length-1 );\nre = realf( z )\nim = imagf( z )\nz = x.get( 1 );\nre = realf( z )\nim = imagf( z )\n","base.strided.cumax":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumax( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumax( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.cumax( N, x1, 2, y1, 1 )\ny0\n","base.strided.cumax.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumax.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.cumaxabs":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumaxabs( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumaxabs( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.cumaxabs( N, x1, 2, y1, 1 )\ny0\n","base.strided.cumaxabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.cumin":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumin( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumin( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.cumin( N, x1, 2, y1, 1 )\ny0\n","base.strided.cumin.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.cuminabs":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cuminabs( x.length, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cuminabs( N, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.cuminabs( N, x1, 2, y1, 1 )\ny0\n","base.strided.cuminabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.cuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.cuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dabs":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dabs( N, x1, -2, y1, 1 )\ny0\n","base.strided.dabs.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dabs2":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs2( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs2( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dabs2( N, x1, -2, y1, 1 )\ny0\n","base.strided.dabs2.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dapx":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dapx( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dapx( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapx( 3, 5.0, x1, 2 )\nx0\n","base.strided.dapx.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dapx.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.dapx.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsum":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsum( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsum( 3, 5.0, x1, 2 )\n","base.strided.dapxsum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsumkbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsumkbn( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsumkbn( 3, 5.0, x1, 2)\n","base.strided.dapxsumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsumkbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn2( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsumkbn2( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsumkbn2( 3, 5.0, x1, 2 )\n","base.strided.dapxsumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsumors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumors( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsumors( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsumors( 3, 5.0, x1, 2 )\n","base.strided.dapxsumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dapxsumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumpw( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dapxsumpw( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dapxsumpw( 3, 5.0, x1, 2 )\n","base.strided.dapxsumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dasum":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.dasum( x.length, x, 1 )\ns = base.strided.dasum( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\ns = base.strided.dasum( 3, x1, 2 )\n","base.strided.dasum.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.dasum.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\ns = base.strided.dasum.ndarray( 3, x, -1, x.length-1 )\n","base.strided.dasumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dasumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar stride = 2;\nbase.strided.dasumpw( 3, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.dasumpw( 3, x1, stride )\n","base.strided.dasumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dasumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dasumpw.ndarray( 3, x, 2, 1 )\n","base.strided.daxpy":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.daxpy( x.length, alpha, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nbase.strided.daxpy( 3, alpha, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.daxpy( 3, 5.0, x1, -2, y1, 1 )\ny0\n","base.strided.daxpy.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.daxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.daxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcbrt":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dcbrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dcbrt( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dcbrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.dcbrt.ndarray":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dcbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dcbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dceil":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dceil( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dceil( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dceil( N, x1, -2, y1, 1 )\ny0\n","base.strided.dceil.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcopy":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dcopy( x.length, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dcopy( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcopy( 3, x1, -2, y1, 1 )\ny0\n","base.strided.dcopy.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcumax":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumax( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumax( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcumax( 3, x1, 2, y1, 1 )\ny0\n","base.strided.dcumax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcumaxabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumaxabs( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumaxabs( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcumaxabs( 3, x1, 2, y1, 1 )\ny0\n","base.strided.dcumaxabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcumin":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumin( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumin( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcumin( 3, x1, 2, y1, 1 )\ny0\n","base.strided.dcumin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcuminabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcuminabs( x.length, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcuminabs( 3, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcuminabs( 3, x1, 2, y1, 1 )\ny0\n","base.strided.dcuminabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusum":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusum( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusum( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusum( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumkbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumkbn( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusumkbn( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumkbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn2( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumkbn2( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusumkbn2( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumors( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumors( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusumors( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dcusumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumpw( x.length, 0.0, x, 1, y, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumpw( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dcusumpw( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.dcusumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float64Array( x.length );\nbase.strided.dcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float64Array( x.length );\nbase.strided.dcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.ddeg2rad":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ddeg2rad( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ddeg2rad( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.ddeg2rad( N, x1, -2, y1, 1 )\ny0\n","base.strided.ddeg2rad.ndarray":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ddeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ddeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.ddot":"var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.ddot( x.length, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.ddot( 3, x, 2, y, -1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.ddot( 3, x1, -2, y1, 1 )\n","base.strided.ddot.ndarray":"var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.ddot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.ddot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nout = base.strided.ddot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.dfill":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dfill( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dfill( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dfill( 3, 5.0, x1, 2 )\nx0\n","base.strided.dfill.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dfill.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.dfill.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dfloor":"var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dfloor( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dfloor( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dfloor( N, x1, -2, y1, 1 )\ny0\n","base.strided.dfloor.ndarray":"var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dinv":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dinv( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dinv( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dinv( N, x1, -2, y1, 1 )\ny0\n","base.strided.dinv.ndarray":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dmap":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap( x.length, x, 1, y, 1, base.identity )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap( 2, x, 2, y, -1, base.identity )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmap( 2, x1, -2, y1, 1, base.identity )\ny0\n","base.strided.dmap.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identity )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identity )\n","base.strided.dmap2":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2( x.length, x, 1, y, 1, z, 1, base.add )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2( 2, x, 2, y, -1, z, 1, base.add )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmap2( 2, x1, -2, y1, 1, z1, 1, base.add )\nz0\n","base.strided.dmap2.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.add )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.add )\n","base.strided.dmax":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmax( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmax( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmax( 3, x1, 2 )\n","base.strided.dmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmax.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmax.ndarray( 3, x, 2, 1 )\n","base.strided.dmaxabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmaxabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmaxabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmaxabs( 3, x1, 2 )\n","base.strided.dmaxabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmaxabs.ndarray( 3, x, 2, 1 )\n","base.strided.dmaxabssorted":"var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.dmaxabssorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmaxabssorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmaxabssorted( 3, x1, 2 )\n","base.strided.dmaxabssorted.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.dmaxabssorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.dmaxabssorted.ndarray( 3, x, 2, 1 )\n","base.strided.dmaxsorted":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmaxsorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmaxsorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmaxsorted( 3, x1, 2 )\n","base.strided.dmaxsorted.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmaxsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.dmaxsorted.ndarray( 3, x, 2, 1 )\n","base.strided.dmean":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmean( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmean( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmean( N, x1, stride )\n","base.strided.dmean.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmean.ndarray( N, x, 2, 1 )\n","base.strided.dmeankbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeankbn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeankbn( N, x1, stride )\n","base.strided.dmeankbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeankbn.ndarray( N, x, 2, 1 )\n","base.strided.dmeankbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeankbn2( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeankbn2( N, x1, stride )\n","base.strided.dmeankbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeankbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeankbn2.ndarray( N, x, 2, 1 )\n","base.strided.dmeanli":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanli( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanli( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanli( N, x1, stride )\n","base.strided.dmeanli.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanli.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanli.ndarray( N, x, 2, 1 )\n","base.strided.dmeanlipw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanlipw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanlipw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanlipw( N, x1, stride )\n","base.strided.dmeanlipw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanlipw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanlipw.ndarray( N, x, 2, 1 )\n","base.strided.dmeanors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanors( N, x1, stride )\n","base.strided.dmeanors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanors.ndarray( N, x, 2, 1 )\n","base.strided.dmeanpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanpn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanpn( N, x1, stride )\n","base.strided.dmeanpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.dmeanpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanpw( N, x1, stride )\n","base.strided.dmeanpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanpw.ndarray( N, x, 2, 1 )\n","base.strided.dmeanstdev":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdev( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanstdev( N, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdev( N, 1, x1, 2, out, 1 )\n","base.strided.dmeanstdev.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdev.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdev.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanstdevpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdevpn( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanstdevpn( N, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdevpn( N, 1, x1, 2, out, 1 )\n","base.strided.dmeanstdevpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanstdevpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanstdevpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanvar":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvar( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanvar( N, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanvar( N, 1, x1, 2, out, 1 )\n","base.strided.dmeanvar.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvar.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanvar.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanvarpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvarpn( x.length, 1, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nout = new Float64Array( 2 );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanvarpn( N, 1, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanvarpn( N, 1, x1, 2, out, 1 )\n","base.strided.dmeanvarpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dmeanvarpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dmeanvarpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n","base.strided.dmeanwd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanwd( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dmeanwd( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmeanwd( N, x1, stride )\n","base.strided.dmeanwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dmeanwd.ndarray( N, x, 2, 1 )\n","base.strided.dmediansorted":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmediansorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmediansorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmediansorted( 3, x1, 2 )\n","base.strided.dmediansorted.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.dmediansorted.ndarray( 3, x, 2, 1 )\n","base.strided.dmidrange":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmidrange( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmidrange( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmidrange( 3, x1, 2 )\n","base.strided.dmidrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmidrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmidrange.ndarray( 3, x, 2, 1 )\n","base.strided.dmin":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmin( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dmin( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dmin( N, x1, stride )\n","base.strided.dmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dmin.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dmin.ndarray( 3, x, 2, 1 )\n","base.strided.dminabs":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dminabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dminabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dminabs( 3, x1, 2 )\n","base.strided.dminabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dminabs.ndarray( 3, x, 2, 1 )\n","base.strided.dminsorted":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dminsorted( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dminsorted( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dminsorted( 3, x1, 2 )\n","base.strided.dminsorted.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.dminsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.dminsorted.ndarray( 3, x, 2, 1 )\n","base.strided.dmskabs":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskabs( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskabs.ndarray":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskabs2":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskabs2( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskabs2.ndarray":"var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskcbrt":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskcbrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskcbrt.ndarray":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskceil":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskceil( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskceil.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskdeg2rad":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskdeg2rad.ndarray":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskfloor":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskfloor( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskfloor.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskinv":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskinv( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskinv.ndarray":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskmap":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap( x.length, x, 1, m, 1, y, 1, base.identity )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap( 2, x, 2, m, 2, y, -1, base.identity )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\ny0\n","base.strided.dmskmap.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n","base.strided.dmskmap2":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.add )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.add )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.add )\nz0\n","base.strided.dmskmap2.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.add )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.add )\n","base.strided.dmskmax":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmax( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskmax( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmskmax( 3, x1, 2, mask1, 2 )\n","base.strided.dmskmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.dmskmin":"var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskmin( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskmin( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmskmin( 3, x1, 2, mask1, 2 )\n","base.strided.dmskmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.dmskramp":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskramp( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskramp.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmskrange":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.dmskrange( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskrange( 3, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.dmskrange( 3, x1, 2, mask1, 2 )\n","base.strided.dmskrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.dmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.dmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.dmskrsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmskrsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmsksqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmsksqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmsksqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dmsktrunc":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc( x.length, x, 1, m, 1, y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.dmsktrunc( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.dmsktrunc.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dmsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.dnanasum":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasum( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnanasum( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanasum( 4, x1, 2 )\n","base.strided.dnanasum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasum.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnanasum.ndarray( 4, x, 2, 1 )\n","base.strided.dnanasumors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasumors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanasumors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanasumors( N, x1, stride )\n","base.strided.dnanasumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanasumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanasumors.ndarray( N, x, 2, 1 )\n","base.strided.dnanmax":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmax( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanmax( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmax( 3, x1, 2 )\n","base.strided.dnanmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanmax.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanmax.ndarray( 3, x, 2, 1 )\n","base.strided.dnanmaxabs":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmaxabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanmaxabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmaxabs( 3, x1, 2 )\n","base.strided.dnanmaxabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanmaxabs.ndarray( 3, x, 2, 1 )\n","base.strided.dnanmean":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmean( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmean( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmean( N, x1, stride )\n","base.strided.dnanmean.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmean.ndarray( N, x, 2, 1 )\n","base.strided.dnanmeanors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmeanors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmeanors( N, x1, stride )\n","base.strided.dnanmeanors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmeanors.ndarray( N, x, 2, 1 )\n","base.strided.dnanmeanpn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmeanpn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmeanpn( N, x1, stride )\n","base.strided.dnanmeanpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.dnanmeanpw":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanmeanpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanmeanpw( N, x1, stride )\n","base.strided.dnanmeanpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmeanpw.ndarray( N, x, 2, 1 )\n","base.strided.dnanmeanwd":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanwd( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanmeanwd( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmeanwd( 3, x1, 2 )\n","base.strided.dnanmeanwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanmeanwd.ndarray( 3, x, 2, 1 )\n","base.strided.dnanmin":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanmin( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanmin( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanmin( 3, x1, 2 )\n","base.strided.dnanmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanmin.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanmin.ndarray( 3, x, 2, 1 )\n","base.strided.dnanminabs":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanminabs( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanminabs( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanminabs( 3, x1, 2 )\n","base.strided.dnanminabs.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanminabs.ndarray( 3, x, 2, 1 )\n","base.strided.dnanmskmax":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.dnanmskmax( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskmax( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dnanmskmax( N, x1, 2, mask1, 2 )\n","base.strided.dnanmskmax.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.dnanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.dnanmskmin":"var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.dnanmskmin( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskmin( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dnanmskmin( N, x1, 2, mask1, 2 )\n","base.strided.dnanmskmin.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.dnanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.dnanmskrange":"var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.dnanmskrange( x.length, x, 1, mask, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskrange( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dnanmskrange( N, x1, 2, mask1, 2 )\n","base.strided.dnanmskrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.dnanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.dnannsum":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsum( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsum( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsum( 4, x1, 2, out, 1 )\n","base.strided.dnannsum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsum.ndarray( x.length, x, 1, 0, out, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsum.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumkbn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn( 4, x1, 2, out, 1 )\n","base.strided.dnannsumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn.ndarray( 4, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumkbn2":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn2( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn2( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn2( 4, x1, 2, out, 1 )\n","base.strided.dnannsumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumkbn2.ndarray( 4, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumkbn2.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumors( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumors( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumors( 4, x1, 2, out, 1 )\n","base.strided.dnannsumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnannsumpw":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumpw( x.length, x, 1, out, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumpw( 4, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nout = new Float64Array( 2 );\nbase.strided.dnannsumpw( 4, x1, 2, out, 1 )\n","base.strided.dnannsumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dnannsumpw.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dnannsumpw.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dnanrange":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanrange( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.dnanrange( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnanrange( 3, x1, 2 )\n","base.strided.dnanrange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.dnanrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.dnanrange.ndarray( 3, x, 2, 1 )\n","base.strided.dnanstdev":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdev( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdev( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdev( N, 1, x1, stride )\n","base.strided.dnanstdev.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanstdevch":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevch( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdevch( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdevch( N, 1, x1, stride )\n","base.strided.dnanstdevch.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanstdevpn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevpn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdevpn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdevpn( N, 1, x1, stride )\n","base.strided.dnanstdevpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanstdevtk":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevtk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdevtk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdevtk( N, 1, x1, stride )\n","base.strided.dnanstdevtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanstdevwd":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevwd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdevwd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdevwd( N, 1, x1, stride )\n","base.strided.dnanstdevwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanstdevyc":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanstdevyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanstdevyc( N, 1, x1, stride )\n","base.strided.dnanstdevyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanstdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnansum":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansum( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansum( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansum( 4, x1, 2 )\n","base.strided.dnansum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansum.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansum.ndarray( 4, x, 2, 1 )\n","base.strided.dnansumkbn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumkbn( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansumkbn( 4, x1, 2 )\n","base.strided.dnansumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumkbn.ndarray( 4, x, 2, 1 )\n","base.strided.dnansumkbn2":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumkbn2( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansumkbn2( 4, x1, 2 )\n","base.strided.dnansumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumkbn2.ndarray( 4, x, 2, 1 )\n","base.strided.dnansumors":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumors( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansumors( 4, x1, 2 )\n","base.strided.dnansumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumors.ndarray( 4, x, 2, 1 )\n","base.strided.dnansumpw":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumpw( 4, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnansumpw( 4, x1, 2 )\n","base.strided.dnansumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dnansumpw.ndarray( 4, x, 2, 1 )\n","base.strided.dnanvariance":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariance( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvariance( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvariance( N, 1, x1, stride )\n","base.strided.dnanvariance.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanvariancech":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancech( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvariancech( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvariancech( N, 1, x1, stride )\n","base.strided.dnanvariancech.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvariancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanvariancepn":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancepn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvariancepn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvariancepn( N, 1, x1, stride )\n","base.strided.dnanvariancepn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanvariancetk":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancetk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvariancetk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvariancetk( N, 1, x1, stride )\n","base.strided.dnanvariancetk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvariancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanvariancewd":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancewd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvariancewd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvariancewd( N, 1, x1, stride )\n","base.strided.dnanvariancewd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvariancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnanvarianceyc":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvarianceyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dnanvarianceyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dnanvarianceyc( N, 1, x1, stride )\n","base.strided.dnanvarianceyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dnanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dnanvarianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.dnrm2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dnrm2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dnrm2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dnrm2( 3, x1, 2 )\n","base.strided.dnrm2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dnrm2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dnrm2.ndarray( 3, x, 2, 1 )\n","base.strided.dramp":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dramp( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dramp( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dramp( N, x1, -2, y1, 1 )\ny0\n","base.strided.dramp.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.drange":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.drange( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.drange( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.drange( 3, x1, 2 )\n","base.strided.drange.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.drange.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.drange.ndarray( 3, x, 2, 1 )\n","base.strided.drev":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.drev( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.drev( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.drev( 3, x1, 2 )\nx0\n","base.strided.drev.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.drev.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.drev.ndarray( 3, x, 2, 1 )\n","base.strided.drsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.drsqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.drsqrt( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.drsqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.drsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.drsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.drsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dsapxsum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsum( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsapxsum( 3, 5.0, x1, 2 )\n","base.strided.dsapxsum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dsapxsumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsumpw( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsapxsumpw( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsapxsumpw( 3, 5.0, x1, 2 )\n","base.strided.dsapxsumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dscal":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dscal( x.length, 5.0, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dscal( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dscal( 3, 5.0, x1, 2 )\nx0\n","base.strided.dscal.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.dscal.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.dscal.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.dsdot":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar dot = base.strided.dsdot( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\ndot = base.strided.dsdot( 3, x, 2, y, -1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\ndot = base.strided.dsdot( 3, x1, -2, y1, 1 )\n","base.strided.dsdot.ndarray":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar dot = base.strided.dsdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\ndot = base.strided.dsdot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\ndot = base.strided.dsdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.dsem":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsem( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsem( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsem( N, 1, x1, stride )\n","base.strided.dsem.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsem.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsem.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsemch":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemch( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsemch( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsemch( N, 1, x1, stride )\n","base.strided.dsemch.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsemch.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsempn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsempn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsempn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsempn( N, 1, x1, stride )\n","base.strided.dsempn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsempn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsempn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsemtk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemtk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsemtk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsemtk( N, 1, x1, stride )\n","base.strided.dsemtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsemtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsemwd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemwd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsemwd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsemwd( N, 1, x1, stride )\n","base.strided.dsemwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsemwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsemyc":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsemyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsemyc( N, 1, x1, stride )\n","base.strided.dsemyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsemyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsemyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsmean":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsmean( N, x1, stride )\n","base.strided.dsmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsmean.ndarray( N, x, 2, 1 )\n","base.strided.dsmeanors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsmeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsmeanors( N, x1, stride )\n","base.strided.dsmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsmeanors.ndarray( N, x, 2, 1 )\n","base.strided.dsmeanpn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsmeanpn( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsmeanpn( N, x1, stride )\n","base.strided.dsmeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.dsmeanpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsmeanpw( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsmeanpw( N, x1, stride )\n","base.strided.dsmeanpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsmeanpw.ndarray( N, x, 2, 1 )\n","base.strided.dsmeanwd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsmeanwd( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsmeanwd( N, x1, stride )\n","base.strided.dsmeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsmeanwd.ndarray( N, x, 2, 1 )\n","base.strided.dsnanmean":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsnanmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsnanmean( N, x1, stride )\n","base.strided.dsnanmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsnanmean.ndarray( N, x, 2, 1 )\n","base.strided.dsnanmeanors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsnanmeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsnanmeanors( N, x1, stride )\n","base.strided.dsnanmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsnanmeanors.ndarray( N, x, 2, 1 )\n","base.strided.dsnanmeanpn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsnanmeanpn( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsnanmeanpn( N, x1, stride )\n","base.strided.dsnanmeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsnanmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.dsnanmeanwd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsnanmeanwd( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsnanmeanwd( N, x1, stride )\n","base.strided.dsnanmeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsnanmeanwd.ndarray( N, x, 2, 1 )\n","base.strided.dsnannsumors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dsnannsumors( x.length, x, 1, out, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dsnannsumors( 4, x, 2, out, 1 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = new Float64Array( 2 );\nbase.strided.dsnannsumors( N, x1, 2, out, 1 )\n","base.strided.dsnannsumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nvar out = new Float64Array( 2 );\nbase.strided.dsnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nout = new Float64Array( 2 );\nbase.strided.dsnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n","base.strided.dsnansum":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansum( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnansum( 4, x1, 2 )\n","base.strided.dsnansum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansum.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsnansum.ndarray( 3, x, 2, 1 )\n","base.strided.dsnansumors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansumors( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnansumors( 4, x1, 2 )\n","base.strided.dsnansumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansumors.ndarray( 4, x, 2, 1 )\n","base.strided.dsnansumpw":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansumpw( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsnansumpw( 4, x1, 2 )\n","base.strided.dsnansumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.dsnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.dsnansumpw.ndarray( 4, x, 2, 1 )\n","base.strided.dsort2hp":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2hp( x.length, 1, x, 1, y, 1 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2hp( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsort2hp( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.dsort2hp.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.dsort2ins":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2ins( x.length, 1, x, 1, y, 1 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2ins( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsort2ins( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.dsort2ins.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.dsort2sh":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2sh( x.length, 1, x, 1, y, 1 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2sh( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsort2sh( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.dsort2sh.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.dsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.dsorthp":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsorthp( x.length, 1, x, 1 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsorthp( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsorthp( N, 1, x1, 2 )\nx0\n","base.strided.dsorthp.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsorthp.ndarray( x.length, 1, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsorthp.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsortins":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortins( x.length, 1, x, 1 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsortins( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsortins( N, 1, x1, 2 )\nx0\n","base.strided.dsortins.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortins.ndarray( x.length, 1, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsortins.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsortsh":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortsh( x.length, 1, x, 1 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsortsh( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsortsh( N, 1, x1, 2 )\nx0\n","base.strided.dsortsh.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.dsortsh.ndarray( x.length, 1, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsortsh.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dsqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dsqrt( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dsqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.dsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dssum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dssum( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dssum( 3, x1, 2 )\n","base.strided.dssum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssum.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dssum.ndarray(3, x, 2, 1 )\n","base.strided.dssumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dssumors( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dssumors( 3, x1, 2 )\n","base.strided.dssumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dssumors.ndarray( 3, x, 2, 1 )\n","base.strided.dssumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dssumpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dssumpw( 3, x1, 2 )\n","base.strided.dssumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dssumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dssumpw.ndarray( 3, x, 2, 1 )\n","base.strided.dstdev":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdev( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdev( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdev( N, 1, x1, stride )\n","base.strided.dstdev.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.dstdevch":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevch( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdevch( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdevch( N, 1, x1, stride )\n","base.strided.dstdevch.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.dstdevpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevpn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdevpn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdevpn( N, 1, x1, stride )\n","base.strided.dstdevpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dstdevtk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevtk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdevtk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdevtk( N, 1, x1, stride )\n","base.strided.dstdevtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.dstdevwd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevwd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdevwd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdevwd( N, 1, x1, stride )\n","base.strided.dstdevwd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.dstdevyc":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dstdevyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dstdevyc( N, 1, x1, stride )\n","base.strided.dstdevyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dstdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsum":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsum( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsum( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsum( 3, x1, 2 )\n","base.strided.dsum.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsum.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsum.ndarray( 3, x, 2, 1 )\n","base.strided.dsumkbn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumkbn( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumkbn( 3, x1, 2 )\n","base.strided.dsumkbn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsumkbn.ndarray( 3, x, 2, 1 )\n","base.strided.dsumkbn2":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn2( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumkbn2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumkbn2( 3, x1, 2 )\n","base.strided.dsumkbn2.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsumkbn2.ndarray( 3, x, 2, 1 )\n","base.strided.dsumors":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumors( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumors( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumors( 3, x1, 2 )\n","base.strided.dsumors.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsumors.ndarray( 3, x, 2, 1 )\n","base.strided.dsumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.dsumpw( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.dsumpw( 3, x1, 2 )\n","base.strided.dsumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsumpw.ndarray( x.length, x, 1, 0 )\nx = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.dsumpw.ndarray( 3, x, 2, 1 )\n","base.strided.dsvariance":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariance( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsvariance( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsvariance( N, 1, x1, stride )\n","base.strided.dsvariance.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsvariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.dsvariancepn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariancepn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dsvariancepn( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dsvariancepn( N, 1, x1, stride )\n","base.strided.dsvariancepn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dsvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dsvariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dswap":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dswap( x.length, x, 1, y, 1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dswap( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.dswap( 3, x1, -2, y1, 1 )\ny0\n","base.strided.dswap.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.dswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.dswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dtrunc":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dtrunc( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dtrunc( N, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.dtrunc( N, x1, -2, y1, 1 )\ny0\n","base.strided.dtrunc.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.dtrunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dtrunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.dtypeEnum2Str":"var out = base.strided.dtypeEnum2Str( base.strided.dtypeStr2Enum( 'float64' ) )\n","base.strided.dtypeResolveEnum":"var out = base.strided.dtypeResolveEnum( 'float64' )\nout = base.strided.dtypeResolveEnum( base.strided.dtypeStr2Enum( 'float64' ) )\n","base.strided.dtypeResolveStr":"var out = base.strided.dtypeResolveStr( 'float64' )\nout = base.strided.dtypeResolveStr( base.strided.dtypeStr2Enum( 'float64' ) )\n","base.strided.dtypeStr2Enum":"var out = base.strided.dtypeStr2Enum( 'float64' )\n","base.strided.dvariance":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariance( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvariance( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvariance( N, 1, x1, stride )\n","base.strided.dvariance.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.dvariancech":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancech( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvariancech( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvariancech( N, 1, x1, stride )\n","base.strided.dvariancech.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvariancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.dvariancepn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancepn( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvariancepn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvariancepn( N, 1, x1, stride )\n","base.strided.dvariancepn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.dvariancetk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancetk( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvariancetk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvariancetk( N, 1, x1, stride )\n","base.strided.dvariancetk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvariancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.dvariancewd":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancewd( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvariancewd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvariancewd( N, 1, x1, stride )\n","base.strided.dvariancewd.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvariancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.dvarianceyc":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarianceyc( x.length, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.dvarianceyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.dvarianceyc( N, 1, x1, stride )\n","base.strided.dvarianceyc.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.dvarm":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarm( x.length, 1.0/3.0, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarm( N, 1.0/3.0, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dvarm( N, 1.0/3.0, 1, x1, 2 )\n","base.strided.dvarm.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarm.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarm.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n","base.strided.dvarmpn":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmpn( x.length, 1.0/3.0, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarmpn( N, 1.0/3.0, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dvarmpn( N, 1.0/3.0, 1, x1, 2 )\n","base.strided.dvarmpn.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmpn.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarmpn.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n","base.strided.dvarmtk":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmtk( x.length, 1.0/3.0, 1, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarmtk( N, 1.0/3.0, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.dvarmtk( N, 1.0/3.0, 1, x1, 2 )\n","base.strided.dvarmtk.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.dvarmtk.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.dvarmtk.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n","base.strided.gapx":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar alpha = 5.0;\nbase.strided.gapx( x.length, alpha, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nalpha = 5.0;\nvar stride = 2;\nbase.strided.gapx( N, alpha, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nalpha = 5.0;\nstride = 2;\nbase.strided.gapx( N, alpha, x1, stride )\nx0\n","base.strided.gapx.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar alpha = 5.0;\nbase.strided.gapx.ndarray( x.length, alpha, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nalpha = 5.0;\nvar stride = 2;\nbase.strided.gapx.ndarray( N, alpha, x, stride, 1 )\n","base.strided.gapxsum":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsum( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gapxsum( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gapxsum( N, 5.0, x1, stride )\n","base.strided.gapxsum.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gapxsum.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.gapxsumkbn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gapxsumkbn( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gapxsumkbn( 3, 5.0, x1, 2 )\n","base.strided.gapxsumkbn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gapxsumkbn2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn2( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gapxsumkbn2( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gapxsumkbn2( N, 5.0, x1, stride )\n","base.strided.gapxsumkbn2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gapxsumkbn2.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.gapxsumors":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumors( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gapxsumors( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gapxsumors( N, 5.0, x1, stride )\n","base.strided.gapxsumors.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gapxsumors.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.gapxsumpw":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumpw( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gapxsumpw( N, 5.0, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gapxsumpw( N, 5.0, x1, stride )\n","base.strided.gapxsumpw.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.gasum":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nvar s = base.strided.gasum( x.length, x, 1 )\ns = base.strided.gasum( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\ns = base.strided.gasum( 3, x1, 2 )\n","base.strided.gasum.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\nvar s = base.strided.gasum.ndarray( x.length, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\ns = base.strided.gasum.ndarray( 3, x, -1, x.length-1 )\n","base.strided.gasumpw":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.gasumpw( x.length, x, 1 )\nx = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gasumpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gasumpw( N, x1, stride )\n","base.strided.gasumpw.ndarray":"var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.gasumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.gasumpw.ndarray( N, x, 2, 1 )\n","base.strided.gaxpy":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\nbase.strided.gaxpy( x.length, 5.0, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\nbase.strided.gaxpy( 3, 5.0, x, 2, y, -1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gaxpy( 3, 5.0, x1, -2, y1, 1 )\ny0\n","base.strided.gaxpy.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\nbase.strided.gaxpy.ndarray( x.length, 5.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gaxpy.ndarray( 3, 5.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcopy":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gcopy( x.length, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gcopy( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcopy( 3, x1, -2, y1, 1 )\ny0\n","base.strided.gcopy.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusum":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusum( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusum( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.gcusum( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusum.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusum.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumkbn":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gcusumkbn( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumkbn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumkbn2":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn2( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumkbn2( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.gcusumkbn2( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumkbn2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumkbn2.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumors":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumors( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumors( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.gcusumors( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumors.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumors.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gcusumpw":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumpw( x.length, 0.0, x, 1, y, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumpw( N, 0.0, x, 2, y, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float64Array( x0.length );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.gcusumpw( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.gcusumpw.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nvar y = [ 0.0, 0.0, 0.0 ];\nbase.strided.gcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gcusumpw.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.gdot":"var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\nvar y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\nvar out = base.strided.gdot( x.length, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\nout = base.strided.gdot( 3, x, 2, y, -1 )\nx = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.gdot( 3, x1, -2, y1, 1 )\n","base.strided.gdot.ndarray":"var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\nvar y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\nvar out = base.strided.gdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\nout = base.strided.gdot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nout = base.strided.gdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.gfill":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfill( x.length, 5.0, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gfill( N, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gfill( N, 5.0, x1, 2 )\nx0\n","base.strided.gfill.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfill.ndarray( x.length, 5.0, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gfill.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.gfillBy":"function fill() { return 5.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfillBy( x.length, x, 1, fill )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gfillBy( N, x, 2, fill )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gfillBy( N, x1, 2, fill )\nx0\n","base.strided.gfillBy.ndarray":"function fill() { return 5.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gfillBy.ndarray( x.length, x, 1, 0, fill )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gfillBy.ndarray( N, x, 2, 1, fill )\n","base.strided.gnannsumkbn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nvar out = [ 0.0, 0 ];\nbase.strided.gnannsumkbn( x.length, x, 1, out, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nout = [ 0.0, 0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnannsumkbn( N, x, 2, out, 1 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nout = [ 0.0, 0 ];\nbase.strided.gnannsumkbn( N, x1, 2, out, 1 )\n","base.strided.gnannsumkbn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nvar out = [ 0.0, 0 ];\nbase.strided.gnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nout = [ 0.0, 0 ];\nbase.strided.gnannsumkbn.ndarray( N, x, 2, 1, out, 1, 0 )\n","base.strided.gnansum":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansum( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gnansum( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gnansum( N, x1, stride )\n","base.strided.gnansum.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansum.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnansum.ndarray( N, x, 2, 1 )\n","base.strided.gnansumkbn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gnansumkbn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gnansumkbn( N, x1, stride )\n","base.strided.gnansumkbn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnansumkbn.ndarray( N, x, 2, 1 )\n","base.strided.gnansumkbn2":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gnansumkbn2( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gnansumkbn2( N, x1, stride )\n","base.strided.gnansumkbn2.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnansumkbn2.ndarray( N, x, 2, 1 )\n","base.strided.gnansumors":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gnansumors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gnansumors( N, x1, stride )\n","base.strided.gnansumors.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnansumors.ndarray( N, x, 2, 1 )\n","base.strided.gnansumpw":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumpw( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gnansumpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gnansumpw( N, x1, stride )\n","base.strided.gnansumpw.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.gnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gnansumpw.ndarray( N, x, 2, 1 )\n","base.strided.gnrm2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gnrm2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nbase.strided.gnrm2( 3, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gnrm2( 3, x1, 2 )\n","base.strided.gnrm2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gnrm2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nbase.strided.gnrm2.ndarray( 3, x, 2, 1 )\n","base.strided.grev":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.grev( x.length, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.grev( N, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.grev( N, x1, 2 )\nx0\n","base.strided.grev.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.grev.ndarray( x.length, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.grev.ndarray( N, x, 2, 1 )\n","base.strided.gscal":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar alpha = 5.0;\nbase.strided.gscal( x.length, alpha, x, 1 )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gscal( 3, 5.0, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.gscal( 3, 5.0, x1, 2 )\nx0\n","base.strided.gscal.ndarray":"var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.gscal.ndarray( x.length, 5.0, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nbase.strided.gscal.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.gsort2hp":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2hp( x.length, 1, x, 1, y, 1 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2hp( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsort2hp( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.gsort2hp.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.gsort2ins":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2ins( x.length, 1, x, 1, y, 1 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2ins( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsort2ins( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.gsort2ins.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2ins.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.gsort2sh":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2sh( x.length, 1, x, 1, y, 1 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2sh( N, -1, x, 2, y, 2 )\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsort2sh( N, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.gsort2sh.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 1.0, 2.0, 3.0 ];\nbase.strided.gsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 1.0, 2.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.gsorthp":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsorthp( x.length, 1, x, 1 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsorthp( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsorthp( N, 1, x1, 2 )\nx0\n","base.strided.gsorthp.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsorthp.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsorthp.ndarray( N, 1, x, 2, 1 )\n","base.strided.gsortins":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortins( x.length, 1, x, 1 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsortins( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsortins( N, 1, x1, 2 )\nx0\n","base.strided.gsortins.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortins.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsortins.ndarray( N, 1, x, 2, 1 )\n","base.strided.gsortsh":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortsh( x.length, 1, x, 1 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsortsh( N, -1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.gsortsh( N, 1, x1, 2 )\nx0\n","base.strided.gsortsh.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nbase.strided.gsortsh.ndarray( x.length, 1, x, 1, 0 )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsortsh.ndarray( N, 1, x, 2, 1 )\n","base.strided.gsum":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsum( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gsum( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gsum( N, x1, stride )\n","base.strided.gsum.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsum.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsum.ndarray( N, x, 2, 1 )\n","base.strided.gsumkbn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gsumkbn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gsumkbn( N, x1, stride )\n","base.strided.gsumkbn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsumkbn.ndarray( N, x, 2, 1 )\n","base.strided.gsumkbn2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gsumkbn2( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gsumkbn2( N, x1, stride )\n","base.strided.gsumkbn2.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsumkbn2.ndarray( N, x, 2, 1 )\n","base.strided.gsumors":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gsumors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gsumors( N, x1, stride )\n","base.strided.gsumors.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsumors.ndarray( N, x, 2, 1 )\n","base.strided.gsumpw":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumpw( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.gsumpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.gsumpw( N, x1, stride )\n","base.strided.gsumpw.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.gsumpw.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.gsumpw.ndarray( N, x, 2, 1 )\n","base.strided.gswap":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gswap( x.length, x, 1, y, 1 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gswap( 3, x, -2, y, 1 )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.gswap( 3, x1, -2, y1, 1 )\ny0\n","base.strided.gswap.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\nbase.strided.gswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\ny = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\nbase.strided.gswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.mapBy":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.mapBy( x.length, x, 1, y, 1, base.abs, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy( 2, x, 2, y, -1, base.abs, clbk )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.mapBy( 2, x1, -2, y1, 1, base.abs, clbk )\ny0\n","base.strided.mapBy.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.mapBy.ndarray( x.length, x, 1, 0, y, 1, 0, base.abs, clbk )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.abs, clbk )\n","base.strided.mapBy2":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 1.0, 1.0, 2.0, 2.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\nbase.strided.mapBy2( x.length, x, 1, y, 1, z, 1, base.add, clbk )\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy2( 2, x, 2, y, -1, z, -1, base.add, clbk )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 1.0, 1.0, 2.0, 2.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nbase.strided.mapBy2( 2, x1, -2, y1, 1, z1, 1, base.add, clbk )\nz0\n","base.strided.mapBy2.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 1.0, 1.0, 2.0, 2.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\nbase.strided.mapBy2.ndarray( 4, x, 1, 0, y, 1, 0, z, 1, 0, base.add, clbk )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 1.0, 1.0, 2.0, 2.0 ];\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nbase.strided.mapBy2.ndarray( 2, x, 2, 1, y, -1, 3, z, 1, 0, base.add, clbk )\n","base.strided.max":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.max( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.max( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.max( N, x1, stride )\n","base.strided.max.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.max.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.max.ndarray( N, x, 2, 1 )\n","base.strided.maxabs":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.maxabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.maxabs( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.maxabs( N, x1, stride )\n","base.strided.maxabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.maxabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.maxabs.ndarray( N, x, 2, 1 )\n","base.strided.maxBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.maxBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.maxBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.maxBy( N, x1, 2, accessor )\n","base.strided.maxBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.maxBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.maxBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.maxsorted":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.maxsorted( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.maxsorted( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.maxsorted( N, x1, stride )\n","base.strided.maxsorted.ndarray":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.maxsorted.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.maxsorted.ndarray( N, x, 2, 1 )\n","base.strided.maxViewBufferIndex":"var idx = base.strided.maxViewBufferIndex( 3, 2, 10 )\n","base.strided.mean":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.mean( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.mean( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.mean( N, x1, stride )\n","base.strided.mean.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.mean.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mean.ndarray( N, x, 2, 1 )\n","base.strided.meankbn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meankbn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meankbn( N, x1, stride )\n","base.strided.meankbn.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meankbn.ndarray( N, x, 2, 1 )\n","base.strided.meankbn2":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn2( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meankbn2( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meankbn2( N, x1, stride )\n","base.strided.meankbn2.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meankbn2.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meankbn2.ndarray( N, x, 2, 1 )\n","base.strided.meanors":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meanors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meanors( N, x1, stride )\n","base.strided.meanors.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meanors.ndarray( N, x, 2, 1 )\n","base.strided.meanpn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanpn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meanpn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meanpn( N, x1, stride )\n","base.strided.meanpn.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanpn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meanpn.ndarray( N, x, 2, 1 )\n","base.strided.meanpw":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanpw( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meanpw( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meanpw( N, x1, stride )\n","base.strided.meanpw.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanpw.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meanpw.ndarray( N, x, 2, 1 )\n","base.strided.meanwd":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.meanwd( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.meanwd( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.meanwd( N, x1, stride )\n","base.strided.meanwd.ndarray":"var x =[ 1.0, -2.0, 2.0 ];\nbase.strided.meanwd.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.meanwd.ndarray( N, x, 2, 1 )\n","base.strided.mediansorted":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.mediansorted( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mediansorted( N, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.mediansorted( N, x1, 2 )\n","base.strided.mediansorted.ndarray":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.mediansorted.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mediansorted.ndarray( N, x, 2, 1 )\n","base.strided.metaDataProps":"var meta = { 'nargs': 7, 'nin': 1, 'nout': 1 };\nvar dt = [ 'float64', 'float64' ];\nvar obj = {};\nbase.strided.metaDataProps( meta, dt, obj, false );\nobj.nargs\nobj.nin\nobj.nout\nobj.types\n","base.strided.min":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.min( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.min( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.min( N, x1, stride )\n","base.strided.min.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.min.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.min.ndarray( N, x, 2, 1 )\n","base.strided.minabs":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.minabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.minabs( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.minabs( N, x1, stride )\n","base.strided.minabs.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.minabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.minabs.ndarray( N, x, 2, 1 )\n","base.strided.minBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.minBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.minBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.minBy( N, x1, 2, accessor )\n","base.strided.minBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.minBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.minBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.minsorted":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.minsorted( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.minsorted( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.minsorted( N, x1, stride )\n","base.strided.minsorted.ndarray":"var x = [ 1.0, 2.0, 3.0 ];\nbase.strided.minsorted.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.minsorted.ndarray( N, x, 2, 1 )\n","base.strided.minViewBufferIndex":"var idx = base.strided.minViewBufferIndex( 3, -2, 10 )\n","base.strided.mskmax":"var x = [ 1.0, -2.0, 4.0, 2.0 ];\nvar mask = [ 0, 0, 1, 0 ];\nbase.strided.mskmax( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskmax( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.mskmax( N, x1, 2, mask1, 2 )\n","base.strided.mskmax.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0 ];\nvar mask = [ 0, 0, 0, 1 ];\nbase.strided.mskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.mskmin":"var x = [ 1.0, -2.0, -4.0, 2.0 ];\nvar mask = [ 0, 0, 1, 0 ];\nbase.strided.mskmin( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskmin( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.mskmin( N, x1, 2, mask1, 2 )\n","base.strided.mskmin.ndarray":"var x = [ 1.0, -2.0, 2.0, -4.0 ];\nvar mask = [ 0, 0, 0, 1 ];\nbase.strided.mskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.mskrange":"var x = [ 1.0, -2.0, 4.0, 2.0 ];\nvar mask = [ 0, 0, 1, 0 ];\nbase.strided.mskrange( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskrange( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.mskrange( N, x1, 2, mask1, 2 )\n","base.strided.mskrange.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0 ];\nvar mask = [ 0, 0, 0, 1 ];\nbase.strided.mskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.mskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.mskunary":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nbase.strided.mskunary( [ x, m, y ], shape, strides, base.abs );\ny\n","base.strided.mskunary.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1 ];\nvar offsets = [ 0, 0, 0 ];\nbase.strided.mskunary.ndarray( [ x, m, y ], shape, strides, offsets, base.abs );\ny\n","base.strided.mskunaryDtypeSignatures":"var dt = strided.dataTypes();\nvar out = base.strided.mskunaryDtypeSignatures( dt, dt )\n","base.strided.mskunarySignatureCallbacks":"var dt = strided.dataTypes();\nvar sigs = base.strided.mskunaryDtypeSignatures( dt, dt );\nvar t = {\n 'default': base.identity,\n 'complex64': base.cidentityf,\n 'complex128': base.cidentity\n };\nvar out = base.strided.mskunarySignatureCallbacks( t, sigs )\n","base.strided.nanmax":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmax( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmax( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmax( N, x1, stride )\n","base.strided.nanmax.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmax.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmax.ndarray( N, x, 2, 1 )\n","base.strided.nanmaxabs":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmaxabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmaxabs( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmaxabs( N, x1, stride )\n","base.strided.nanmaxabs.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmaxabs.ndarray( N, x, 2, 1 )\n","base.strided.nanmaxBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanmaxBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmaxBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanmaxBy( N, x1, 2, accessor )\n","base.strided.nanmaxBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanmaxBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmaxBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.nanmean":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmean( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmean( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmean( N, x1, stride )\n","base.strided.nanmean.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmean.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmean.ndarray( N, x, 2, 1 )\n","base.strided.nanmeanors":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanors( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmeanors( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmeanors( N, x1, stride )\n","base.strided.nanmeanors.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmeanors.ndarray( N, x, 2, 1 )\n","base.strided.nanmeanpn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanpn( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmeanpn( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmeanpn( N, x1, stride )\n","base.strided.nanmeanpn.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.nanmeanwd":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanwd( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmeanwd( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmeanwd( N, x1, stride )\n","base.strided.nanmeanwd.ndarray":"var x =[ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmeanwd.ndarray( N, x, 2, 1 )\n","base.strided.nanmin":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmin( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanmin( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanmin( N, x1, stride )\n","base.strided.nanmin.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanmin.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmin.ndarray( N, x, 2, 1 )\n","base.strided.nanminabs":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanminabs( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanminabs( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanminabs( N, x1, stride )\n","base.strided.nanminabs.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanminabs.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanminabs.ndarray( N, x, 2, 1 )\n","base.strided.nanminBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanminBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, NaN, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanminBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanminBy( N, x1, 2, accessor )\n","base.strided.nanminBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanminBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanminBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.nanmskmax":"var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\nvar mask = [ 0, 0, 1, 0, 0 ];\nbase.strided.nanmskmax( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskmax( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanmskmax( N, x1, 2, mask1, 2 )\n","base.strided.nanmskmax.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\nvar mask = [ 0, 0, 0, 1, 0 ];\nbase.strided.nanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.nanmskmin":"var x = [ 1.0, -2.0, -4.0, 2.0, NaN ];\nvar mask = [ 0, 0, 1, 0, 0 ];\nbase.strided.nanmskmin( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskmin( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanmskmin( N, x1, 2, mask1, 2 )\n","base.strided.nanmskmin.ndarray":"var x = [ 1.0, -2.0, 2.0, -4.0, NaN ];\nvar mask = [ 0, 0, 0, 1, 0 ];\nbase.strided.nanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.nanmskrange":"var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\nvar mask = [ 0, 0, 1, 0, 0 ];\nbase.strided.nanmskrange( x.length, x, 1, mask, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskrange( N, x, 2, mask, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanmskrange( N, x1, 2, mask1, 2 )\n","base.strided.nanmskrange.ndarray":"var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\nvar mask = [ 0, 0, 0, 1, 0 ];\nbase.strided.nanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\nmask = [ 0, 0, 0, 0, 0, 0, 1 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.nanrange":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanrange( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanrange( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanrange( N, x1, stride )\n","base.strided.nanrange.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanrange.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanrange.ndarray( N, x, 2, 1 )\n","base.strided.nanrangeBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanrangeBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0, 1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanrangeBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanrangeBy( N, x1, 2, accessor )\n","base.strided.nanrangeBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\nbase.strided.nanrangeBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanrangeBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.nanstdev":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdev( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdev( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdev( N, 1, x1, 2 )\n","base.strided.nanstdev.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanstdevch":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevch( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevch( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdevch( N, 1, x1, 2 )\n","base.strided.nanstdevch.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanstdevpn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevpn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevpn( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdevpn( N, 1, x1, 2 )\n","base.strided.nanstdevpn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanstdevtk":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevtk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevtk( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdevtk( N, 1, x1, 2 )\n","base.strided.nanstdevtk.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanstdevwd":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevwd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevwd( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdevwd( N, 1, x1, 2 )\n","base.strided.nanstdevwd.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanstdevyc":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevyc( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevyc( N, 1, x, 2 )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.nanstdevyc( N, 1, x1, 2 )\n","base.strided.nanstdevyc.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanstdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvariance":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariance( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvariance( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvariance( N, 1, x1, stride )\n","base.strided.nanvariance.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvariancech":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancech( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvariancech( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvariancech( N, 1, x1, stride )\n","base.strided.nanvariancech.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvariancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvariancepn":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancepn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvariancepn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvariancepn( N, 1, x1, stride )\n","base.strided.nanvariancepn.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvariancetk":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancetk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvariancetk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvariancetk( N, 1, x1, stride )\n","base.strided.nanvariancetk.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvariancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvariancewd":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancewd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvariancewd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvariancewd( N, 1, x1, stride )\n","base.strided.nanvariancewd.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvariancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.nanvarianceyc":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvarianceyc( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.nanvarianceyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.nanvarianceyc( N, 1, x1, stride )\n","base.strided.nanvarianceyc.ndarray":"var x = [ 1.0, -2.0, NaN, 2.0 ];\nbase.strided.nanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.nanvarianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.nullary":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1 ];\nvar fcn = constantFunction( 3.0 );\nbase.strided.nullary( [ x ], shape, strides, fcn );\nx\n","base.strided.nullary.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1 ];\nvar offsets = [ 0 ];\nvar fcn = constantFunction( 3.0 );\nbase.strided.nullary.ndarray( [ x ], shape, strides, offsets, fcn );\nx\n","base.strided.offsetView":"var x = new Float64Array( 10 );\nvar out = base.strided.offsetView( x, 0 )\nvar bool = ( out.buffer === x.buffer )\n","base.strided.quaternary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1 ];\nfunction f( x, y, z, w ) { return x + y + z + w; };\nbase.strided.quaternary( [ x, y, z, w, u ], shape, strides, f );\nu\n","base.strided.quaternary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1 ];\nvar offsets = [ 0, 0, 0, 0, 0 ];\nfunction f( x, y, z, w ) { return x + y + z + w; };\nbase.strided.quaternary.ndarray( [ x, y, z, w, u ], shape, strides, offsets, f );\nu\n","base.strided.quinary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1, 1 ];\nfunction f( x, y, z, w, u ) { return x + y + z + w + u; };\nbase.strided.quinary( [ x, y, z, w, u, v ], shape, strides, f );\nv\n","base.strided.quinary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1, 1, 1 ];\nvar offsets = [ 0, 0, 0, 0, 0, 0 ];\nfunction f( x, y, z, w, u ) { return x + y + z + w + u; };\nbase.strided.quinary.ndarray( [ x, y, z, w, u, v ], shape, strides, offsets, f );\nv\n","base.strided.range":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.range( x.length, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.range( N, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.range( N, x1, stride )\n","base.strided.range.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.range.ndarray( x.length, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.range.ndarray( N, x, 2, 1 )\n","base.strided.rangeBy":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.rangeBy( x.length, x, 1, accessor )\nx = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.rangeBy( N, x, 2, accessor )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.rangeBy( N, x1, 2, accessor )\n","base.strided.rangeBy.ndarray":"function accessor( v ) { return v * 2.0; };\nvar x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\nbase.strided.rangeBy.ndarray( x.length, x, 1, 0, accessor )\nx = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.rangeBy.ndarray( N, x, 2, 1, accessor )\n","base.strided.reinterpretComplex":"var x = new Complex128Array( 10 );\nvar out = base.strided.reinterpretComplex( x, 0 )\nvar bool = ( out.buffer === x.buffer )\nx = new Complex64Array( 10 );\nout = base.strided.reinterpretComplex( x, 0 )\nbool = ( out.buffer === x.buffer )\n","base.strided.reinterpretComplex64":"var x = new Complex64Array( 10 );\nvar out = base.strided.reinterpretComplex64( x, 0 )\nvar bool = ( out.buffer === x.buffer )\n","base.strided.reinterpretComplex128":"var x = new Complex128Array( 10 );\nvar out = base.strided.reinterpretComplex128( x, 0 )\nvar bool = ( out.buffer === x.buffer )\n","base.strided.sabs":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sabs( N, x1, -2, y1, 1 )\ny0\n","base.strided.sabs.ndarray":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sabs2":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs2( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs2( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sabs2( N, x1, -2, y1, 1 )\ny0\n","base.strided.sabs2.ndarray":"var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sapx":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sapx( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sapx( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapx( 3, 5.0, x1, 2 )\nx0\n","base.strided.sapx.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sapx.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.sapx.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsum( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsum( 3, 5.0, x1, 2 )\n","base.strided.sapxsum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsumkbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsumkbn( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsumkbn( 3, 5.0, x1, 2 )\n","base.strided.sapxsumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsumkbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn2( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sapxsumkbn2( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sapxsumkbn2( 3, 5.0, x1, 2 )\n","base.strided.sapxsumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sapxsumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumors( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sapxsumors( N, 5.0, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sapxsumors( N, 5.0, x1, stride )\n","base.strided.sapxsumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sapxsumors.ndarray( N, 5.0, x, 2, 1 )\n","base.strided.sapxsumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumpw( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar stride = 2;\nbase.strided.sapxsumpw( 3, 5.0, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.sapxsumpw( 3, 5.0, x1, stride )\n","base.strided.sapxsumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sasum":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.sasum( x.length, x, 1 )\ns = base.strided.sasum( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\ns = base.strided.sasum( 3, x1, 2 )\n","base.strided.sasum.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\nvar s = base.strided.sasum.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\ns = base.strided.sasum.ndarray( 3, x, -1, x.length-1 )\n","base.strided.sasumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sasumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sasumpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sasumpw( 3, x1, 2 )\n","base.strided.sasumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sasumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sasumpw.ndarray( 3, x, 2, 1 )\n","base.strided.saxpy":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.saxpy( x.length, alpha, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nbase.strided.saxpy( 3, alpha, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.saxpy( 3, 5.0, x1, -2, y1, 1 )\ny0\n","base.strided.saxpy.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nvar alpha = 5.0;\nbase.strided.saxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.saxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scbrt":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.scbrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.scbrt( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.scbrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.scbrt.ndarray":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.scbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.scbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sceil":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sceil( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sceil( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sceil( N, x1, -2, y1, 1 )\ny0\n","base.strided.sceil.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scopy":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.scopy( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.scopy( 3, x, -2, y, 1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scopy( 3, x1, -2, y1, 1 )\ny0\n","base.strided.scopy.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.scopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scumax":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumax( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumax( 3, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scumax( 3, x1, 2, y1, 1 )\ny0\n","base.strided.scumax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scumaxabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumaxabs( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scumaxabs( N, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scumaxabs( N, x1, 2, y1, 1 )\ny0\n","base.strided.scumaxabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scumin":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumin( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scumin( N, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scumin( N, x1, 2, y1, 1 )\ny0\n","base.strided.scumin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scuminabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scuminabs( x.length, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scuminabs( N, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scuminabs( N, x1, 2, y1, 1 )\ny0\n","base.strided.scuminabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nvar N = base.floor( x.length / 2 );\nbase.strided.scuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusum( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusum( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusum( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumkbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scusumkbn( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumkbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn2( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn2( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nN = base.floor( x0.length / 2 );\nbase.strided.scusumkbn2( N, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumors( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumors( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusumors( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.scusumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumpw( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumpw( 3, 0.0, x, 2, y, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar y0 = new Float32Array( x0.length );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.scusumpw( 3, 0.0, x1, 2, y1, 1 )\ny0\n","base.strided.scusumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nvar y = new Float32Array( x.length );\nbase.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\ny = new Float32Array( x.length );\nbase.strided.scusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sdeg2rad":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sdeg2rad( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sdeg2rad( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sdeg2rad( N, x1, -2, y1, 1 )\ny0\n","base.strided.sdeg2rad.ndarray":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sdeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sdot":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdot( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdot( 3, x, 2, y, -1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.sdot( 3, x1, -2, y1, 1 )\n","base.strided.sdot.ndarray":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdot.ndarray( 3, x, 2, 0, y, 2, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nout = base.strided.sdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n","base.strided.sdsapxsum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsum( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sdsapxsum( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsapxsum( 3, 5.0, x1, 2 )\n","base.strided.sdsapxsum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sdsapxsumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsumpw( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sdsapxsumpw( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsapxsumpw( 3, 5.0, x1, 2 )\n","base.strided.sdsapxsumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sdsdot":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdsdot( x.length, 0.0, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdsdot( 3, 0.0, x, 2, y, -1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\nout = base.strided.sdsdot( 3, 0.0, x1, -2, y1, 1 )\n","base.strided.sdsdot.ndarray":"var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar out = base.strided.sdsdot.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\nout = base.strided.sdsdot.ndarray( 3, 0.0, x, 2, 0, y, 2, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nout = base.strided.sdsdot.ndarray( 3, 0.0, x, -2, x.length-1, y, 1, 3 )\n","base.strided.sdsmean":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsmean( N, x1, stride )\n","base.strided.sdsmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsmean.ndarray( N, x, 2, 1 )\n","base.strided.sdsmeanors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsmeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsmeanors( N, x1, stride )\n","base.strided.sdsmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdsmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsmeanors.ndarray( N, x, 2, 1 )\n","base.strided.sdsnanmean":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsnanmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsnanmean( N, x1, stride )\n","base.strided.sdsnanmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsnanmean.ndarray( N, x, 2, 1 )\n","base.strided.sdsnanmeanors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sdsnanmeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sdsnanmeanors( N, x1, stride )\n","base.strided.sdsnanmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sdsnanmeanors.ndarray( N, x, 2, 1 )\n","base.strided.sdsnansum":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar stride = 2;\nbase.strided.sdsnansum( 4, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.sdsnansum( 4, x1, stride )\n","base.strided.sdsnansum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansum.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.sdsnansum.ndarray( 4, x, 2, 1 )\n","base.strided.sdsnansumpw":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.sdsnansumpw( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sdsnansumpw( 4, x1, 2 )\n","base.strided.sdsnansumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.sdsnansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.sdsnansumpw.ndarray( 4, x, 2, 1 )\n","base.strided.sdssum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar stride = 2;\nbase.strided.sdssum( 3, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.sdssum( 3, x1, stride )\n","base.strided.sdssum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssum.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdssum.ndarray( 3, x, 2, 1 )\n","base.strided.sdssumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar stride = 2;\nbase.strided.sdssumpw( 3, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.sdssumpw( 3, x1, stride )\n","base.strided.sdssumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sdssumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sdssumpw.ndarray( 3, x, 2, 1 )\n","base.strided.sfill":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sfill( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sfill( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sfill( 3, 5.0, x1, 2 )\nx0\n","base.strided.sfill.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sfill.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.sfill.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.sfloor":"var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sfloor( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sfloor( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sfloor( N, x1, -2, y1, 1 )\ny0\n","base.strided.sfloor.ndarray":"var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sinv":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sinv( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sinv( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sinv( N, x1, -2, y1, 1 )\ny0\n","base.strided.sinv.ndarray":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.smap":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap( x.length, x, 1, y, 1, base.identityf )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap( 2, x, 2, y, -1, base.identityf )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smap( 2, x1, -2, y1, 1, base.identityf )\ny0\n","base.strided.smap.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identityf )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identityf )\n","base.strided.smap2":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2( x.length, x, 1, y, 1, z, 1, base.addf )\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2( 2, x, 2, y, -1, z, 1, base.addf )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nbase.strided.smap2( 2, x1, -2, y1, 1, z1, 1, base.addf )\nz0\n","base.strided.smap2.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.addf )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.addf )\n","base.strided.smax":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smax( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smax( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smax( 3, x1, 2 )\n","base.strided.smax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smax.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smax.ndarray( N, x, 2, 1 )\n","base.strided.smaxabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smaxabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smaxabs( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smaxabs( 3, x1, 2 )\n","base.strided.smaxabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smaxabs.ndarray( 3, x, 2, 1 )\n","base.strided.smaxabssorted":"var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.smaxabssorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smaxabssorted( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smaxabssorted( 3, x1, 2 )\n","base.strided.smaxabssorted.ndarray":"var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\nbase.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.smaxabssorted.ndarray( 3, x, 2, 1 )\n","base.strided.smaxsorted":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smaxsorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smaxsorted( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smaxsorted( 3, x1, 2 )\n","base.strided.smaxsorted.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.smaxsorted.ndarray( 3, x, 2, 1 )\n","base.strided.smean":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smean( N, x1, stride )\n","base.strided.smean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smean.ndarray( N, x, 2, 1 )\n","base.strided.smeankbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeankbn( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeankbn( N, x1, stride )\n","base.strided.smeankbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeankbn.ndarray( N, x, 2, 1 )\n","base.strided.smeankbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeankbn2( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeankbn2( N, x1, stride )\n","base.strided.smeankbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeankbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeankbn2.ndarray( N, x, 2, 1 )\n","base.strided.smeanli":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanli( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanli( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanli( N, x1, stride )\n","base.strided.smeanli.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanli.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanli.ndarray( N, x, 2, 1 )\n","base.strided.smeanlipw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanlipw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanlipw( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanlipw( N, x1, stride )\n","base.strided.smeanlipw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanlipw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanlipw.ndarray( N, x, 2, 1 )\n","base.strided.smeanors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanors( N, x1, stride )\n","base.strided.smeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanors.ndarray( N, x, 2, 1 )\n","base.strided.smeanpn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanpn( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanpn( N, x1, stride )\n","base.strided.smeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanpn.ndarray( N, x, 2, 1 )\n","base.strided.smeanpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanpw( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanpw( N, x1, stride )\n","base.strided.smeanpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanpw.ndarray( N, x, 2, 1 )\n","base.strided.smeanwd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.smeanwd( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.smeanwd( N, x1, stride )\n","base.strided.smeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.smeanwd.ndarray( N, x, 2, 1 )\n","base.strided.smediansorted":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smediansorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smediansorted( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smediansorted( 3, x1, 2 )\n","base.strided.smediansorted.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.smediansorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.smediansorted.ndarray( 3, x, 2, 1 )\n","base.strided.smidrange":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smidrange( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smidrange( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smidrange( 3, x1, 2 )\n","base.strided.smidrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smidrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smidrange.ndarray( 3, x, 2, 1 )\n","base.strided.smin":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smin( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.smin( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.smin( 3, x1, 2 )\n","base.strided.smin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.smin.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.smin.ndarray( 3, x, 2, 1 )\n","base.strided.sminabs":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sminabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sminabs( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sminabs( 3, x1, 2 )\n","base.strided.sminabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.sminabs.ndarray( 3, x, 2, 1 )\n","base.strided.sminsorted":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.sminsorted( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.sminsorted( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sminsorted( 3, x1, 2 )\n","base.strided.sminsorted.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nbase.strided.sminsorted.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\nbase.strided.sminsorted.ndarray( 3, x, 2, 1 )\n","base.strided.smskabs":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskabs( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskabs.ndarray":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskabs2":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskabs2( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskabs2.ndarray":"var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskcbrt":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskcbrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskcbrt.ndarray":"var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskceil":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskceil( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskceil.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskdeg2rad":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskdeg2rad.ndarray":"var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskfloor":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskfloor( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskfloor.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskinv":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskinv( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskinv.ndarray":"var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskmap":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap( x.length, x, 1, m, 1, y, 1, base.identity )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap( 2, x, 2, m, 2, y, -1, base.identity )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\ny0\n","base.strided.smskmap.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n","base.strided.smskmap2":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.addf )\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.addf )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.addf )\nz0\n","base.strided.smskmap2.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.addf )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\ny = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.addf )\n","base.strided.smskmax":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmax( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskmax( 3, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.smskmax( 3, x1, 2, mask1, 2 )\n","base.strided.smskmax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.smskmin":"var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskmin( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskmin( 3, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.smskmin( 3, x1, 2, mask1, 2 )\n","base.strided.smskmin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.smskramp":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskramp( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskramp.ndarray":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smskrange":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0 ] );\nbase.strided.smskrange( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskrange( 3, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nbase.strided.smskrange( 3, x1, 2, mask1, 2 )\n","base.strided.smskrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1 ] );\nbase.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nbase.strided.smskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n","base.strided.smskrsqrt":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smskrsqrt.ndarray":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smsksqrt":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smsksqrt( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smsksqrt.ndarray":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.smsktrunc":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc( x.length, x, 1, m, 1, y, 1 )\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc( 2, x, 2, m, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.smsktrunc( 2, x1, -2, m1, -2, y1, 1 )\ny0\n","base.strided.smsktrunc.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar m = new Uint8Array( [ 0, 0, 1, 0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nm = new Uint8Array( [ 0, 0, 1, 0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.smsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n","base.strided.snanmax":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmax( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanmax( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmax( 3, x1, 2 )\n","base.strided.snanmax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanmax.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanmax.ndarray( 3, x, 2, 1 )\n","base.strided.snanmaxabs":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmaxabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanmaxabs( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmaxabs( 3, x1, 2 )\n","base.strided.snanmaxabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanmaxabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanmaxabs.ndarray( 3, x, 2, 1 )\n","base.strided.snanmean":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmean( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanmean( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanmean( N, x1, stride )\n","base.strided.snanmean.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmean.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmean.ndarray( N, x, 2, 1 )\n","base.strided.snanmeanors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanmeanors( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanmeanors( N, x1, stride )\n","base.strided.snanmeanors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmeanors.ndarray( N, x, 2, 1 )\n","base.strided.snanmeanpn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanpn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanmeanpn( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanmeanpn( N, x1, stride )\n","base.strided.snanmeanpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanpn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmeanpn.ndarray( N, x, 2, 1 )\n","base.strided.snanmeanwd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanwd( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanmeanwd( N, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanmeanwd( N, x1, stride )\n","base.strided.snanmeanwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmeanwd.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmeanwd.ndarray( N, x, 2, 1 )\n","base.strided.snanmin":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanmin( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanmin( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanmin( 3, x1, 2 )\n","base.strided.snanmin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanmin.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanmin.ndarray( 3, x, 2, 1 )\n","base.strided.snanminabs":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanminabs( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanminabs( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanminabs( 3, x1, 2 )\n","base.strided.snanminabs.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanminabs.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanminabs.ndarray( 3, x, 2, 1 )\n","base.strided.snanmskmax":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.snanmskmax( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskmax( N, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanmskmax( N, x1, 2, mask1, 2 )\n","base.strided.snanmskmax.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.snanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.snanmskmin":"var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.snanmskmin( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskmin( N, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanmskmin( N, x1, 2, mask1, 2 )\n","base.strided.snanmskmin.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.snanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.snanmskrange":"var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\nbase.strided.snanmskrange( x.length, x, 1, mask, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskrange( N, x, 2, mask, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanmskrange( N, x1, 2, mask1, 2 )\n","base.strided.snanmskrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\nvar mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\nbase.strided.snanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\nmask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n","base.strided.snanrange":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanrange( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\nbase.strided.snanrange( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snanrange( 3, x1, 2 )\n","base.strided.snanrange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\nbase.strided.snanrange.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\nbase.strided.snanrange.ndarray( 3, x, 2, 1 )\n","base.strided.snanstdev":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdev( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdev( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdev( N, 1, x1, stride )\n","base.strided.snanstdev.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevch":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevch( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevch( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevch( N, 1, x1, stride )\n","base.strided.snanstdevch.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevpn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevpn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevpn( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevpn( N, 1, x1, stride )\n","base.strided.snanstdevpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevtk":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevtk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevtk( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevtk( N, 1, x1, stride )\n","base.strided.snanstdevtk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevwd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevwd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevwd( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevwd( N, 1, x1, stride )\n","base.strided.snanstdevwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanstdevyc":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.snanstdevyc( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.snanstdevyc( N, 1, x1, stride )\n","base.strided.snanstdevyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanstdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.snansum":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.snansum( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snansum( 4, x1, 2 )\n","base.strided.snansum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansum.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansum.ndarray( 4, x, 2, 1 )\n","base.strided.snansumkbn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar stride = 2;\nbase.strided.snansumkbn( 4, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.snansumkbn( 4, x1, stride )\n","base.strided.snansumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansumkbn.ndarray( 4, x, 2, 1 )\n","base.strided.snansumkbn2":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar stride = 2;\nbase.strided.snansumkbn2( 4, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.snansumkbn2( 4, x1, stride )\n","base.strided.snansumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumkbn2.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansumkbn2.ndarray( 4, x, 2, 1 )\n","base.strided.snansumors":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nvar stride = 2;\nbase.strided.snansumors( 4, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nstride = 2;\nbase.strided.snansumors( 4, x1, stride )\n","base.strided.snansumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumors.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansumors.ndarray( 4, x, 2, 1 )\n","base.strided.snansumpw":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\nbase.strided.snansumpw( 4, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snansumpw( 4, x1, 2 )\n","base.strided.snansumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snansumpw.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\nbase.strided.snansumpw.ndarray( 4, x, 2, 1 )\n","base.strided.snanvariance":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariance( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariance( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariance( N, 1, x1, 2 )\n","base.strided.snanvariance.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancech":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancech( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancech( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancech( N, 1, x1, 2 )\n","base.strided.snanvariancech.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancepn":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancepn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancepn( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancepn( N, 1, x1, 2 )\n","base.strided.snanvariancepn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancetk":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancetk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancetk( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancetk( N, 1, x1, 2 )\n","base.strided.snanvariancetk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvariancewd":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancewd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancewd( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvariancewd( N, 1, x1, 2 )\n","base.strided.snanvariancewd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvariancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.snanvarianceyc":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvarianceyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvarianceyc( N, 1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nbase.strided.snanvarianceyc( N, 1, x1, 2 )\n","base.strided.snanvarianceyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\nbase.strided.snanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.snanvarianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.snrm2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.snrm2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.snrm2( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.snrm2( 3, x1, 2 )\n","base.strided.snrm2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.snrm2.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.snrm2.ndarray( 3, x, 2, 1 )\n","base.strided.sramp":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sramp( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sramp( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.sramp( N, x1, -2, y1, 1 )\ny0\n","base.strided.sramp.ndarray":"var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.sramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.srange":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.srange( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.srange( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.srange( 3, x1, 2 )\n","base.strided.srange.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.srange.ndarray( x.length, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.srange.ndarray( 3, x, 2, 1 )\n","base.strided.srev":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.srev( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.srev( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.srev( 3, x1, 2 )\nx0\n","base.strided.srev.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.srev.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.srev.ndarray( 3, x, 2, 1 )\n","base.strided.srsqrt":"var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.srsqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.srsqrt( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.srsqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.srsqrt.ndarray":"var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.srsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.srsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sscal":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sscal( x.length, 5.0, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sscal( 3, 5.0, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.sscal( 3, 5.0, x1, 2 )\nx0\n","base.strided.sscal.ndarray":"var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\nbase.strided.sscal.ndarray( x.length, 5.0, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\nbase.strided.sscal.ndarray( 3, 5.0, x, 2, 1 )\n","base.strided.ssort2hp":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2hp( x.length, 1, x, 1, y, 1 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2hp( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssort2hp( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.ssort2hp.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2hp.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.ssort2ins":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2ins( x.length, 1, x, 1, y, 1 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2ins( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssort2ins( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.ssort2ins.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.ssort2sh":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2sh( x.length, 1, x, 1, y, 1 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2sh( 2, -1, x, 2, y, 2 )\ny\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssort2sh( 2, 1, x1, 2, y1, 2 )\nx0\ny0\n","base.strided.ssort2sh.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\ny\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\ny = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nbase.strided.ssort2sh.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\ny\n","base.strided.ssorthp":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssorthp( x.length, 1, x, 1 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssorthp( 2, -1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssorthp( 2, 1, x1, 2 )\nx0\n","base.strided.ssorthp.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssorthp.ndarray( x.length, 1, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssorthp.ndarray( 2, 1, x, 2, 1 )\n","base.strided.ssortins":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortins( x.length, 1, x, 1 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortins( 2, -1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssortins( 2, 1, x1, 2 )\nx0\n","base.strided.ssortins.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortins.ndarray( x.length, 1, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortins.ndarray( 2, 1, x, 2, 1 )\n","base.strided.ssortsh":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortsh( x.length, 1, x, 1 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortsh( 2, -1, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssortsh( 2, 1, x1, 2 )\nx0\n","base.strided.ssortsh.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortsh.ndarray( x.length, 1, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nbase.strided.ssortsh.ndarray( 2, 1, x, 2, 1 )\n","base.strided.ssqrt":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ssqrt( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ssqrt( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.ssqrt( N, x1, -2, y1, 1 )\ny0\n","base.strided.ssqrt.ndarray":"var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.ssqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.ssqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.sstdev":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdev( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdev( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdev( N, 1, x1, stride )\n","base.strided.sstdev.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.sstdevch":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevch( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdevch( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdevch( N, 1, x1, stride )\n","base.strided.sstdevch.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.sstdevpn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevpn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdevpn( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdevpn( N, 1, x1, stride )\n","base.strided.sstdevpn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.sstdevtk":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevtk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdevtk( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdevtk( N, 1, x1, stride )\n","base.strided.sstdevtk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.sstdevwd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevwd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdevwd( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdevwd( N, 1, x1, stride )\n","base.strided.sstdevwd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.sstdevyc":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.sstdevyc( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.sstdevyc( N, 1, x1, stride )\n","base.strided.sstdevyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.sstdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.sstdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.ssum":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssum( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssum( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssum( 3, x1, 2 )\n","base.strided.ssum.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssum.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssum.ndarray( 3, x, 2, 1 )\n","base.strided.ssumkbn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumkbn( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumkbn( 3, x1, 2 )\n","base.strided.ssumkbn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumkbn.ndarray( 3, x, 2, 1 )\n","base.strided.ssumkbn2":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn2( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumkbn2( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumkbn2( 3, x1, 2 )\n","base.strided.ssumkbn2.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumkbn2.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumkbn2.ndarray( 3, x, 2, 1 )\n","base.strided.ssumors":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumors( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumors( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumors( 3, x1, 2 )\n","base.strided.ssumors.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumors.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumors.ndarray( 3, x, 2, 1 )\n","base.strided.ssumpw":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumpw( x.length, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nbase.strided.ssumpw( 3, x, 2 )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nbase.strided.ssumpw( 3, x1, 2 )\n","base.strided.ssumpw.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.ssumpw.ndarray( x.length, x, 1, 0 )\nx = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nbase.strided.ssumpw.ndarray( 3, x, 2, 1 )\n","base.strided.sswap":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.sswap( x.length, x, 1, y, 1 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.sswap( 3, x, -2, y, 1 )\nvar x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\nvar y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\nbase.strided.sswap( 3, x1, -2, y1, 1 )\ny0\n","base.strided.sswap.ndarray":"var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\nvar y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\nbase.strided.sswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\ny = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\nbase.strided.sswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n","base.strided.stdev":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdev( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdev( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdev( N, 1, x1, stride )\n","base.strided.stdev.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdev.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdev.ndarray( N, 1, x, 2, 1 )\n","base.strided.stdevch":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevch( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdevch( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdevch( N, 1, x1, stride )\n","base.strided.stdevch.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevch.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdevch.ndarray( N, 1, x, 2, 1 )\n","base.strided.stdevpn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevpn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdevpn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdevpn( N, 1, x1, stride )\n","base.strided.stdevpn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevpn.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdevpn.ndarray( N, 1, x, 2, 1 )\n","base.strided.stdevtk":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevtk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdevtk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdevtk( N, 1, x1, stride )\n","base.strided.stdevtk.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevtk.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdevtk.ndarray( N, 1, x, 2, 1 )\n","base.strided.stdevwd":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevwd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdevwd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdevwd( N, 1, x1, stride )\n","base.strided.stdevwd.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevwd.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdevwd.ndarray( N, 1, x, 2, 1 )\n","base.strided.stdevyc":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevyc( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.stdevyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.stdevyc( N, 1, x1, stride )\n","base.strided.stdevyc.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.stdevyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.stdevyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.strunc":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.strunc( x.length, x, 1, y, 1 )\nvar N = base.floor( x.length / 2 );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.strunc( N, x, 2, y, -1 )\nvar x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nN = base.floor( x0.length / 2 );\nbase.strided.strunc( N, x1, -2, y1, 1 )\ny0\n","base.strided.strunc.ndarray":"var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nbase.strided.strunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\nx = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.strunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n","base.strided.svariance":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariance( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svariance( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svariance( N, 1, x1, stride )\n","base.strided.svariance.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariance.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svariance.ndarray( N, 1, x, 2, 1 )\n","base.strided.svariancech":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancech( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svariancech( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svariancech( N, 1, x1, stride )\n","base.strided.svariancech.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svariancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.svariancepn":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancepn( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svariancepn( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svariancepn( N, 1, x1, stride )\n","base.strided.svariancepn.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svariancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.svariancetk":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancetk( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svariancetk( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svariancetk( N, 1, x1, stride )\n","base.strided.svariancetk.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svariancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.svariancewd":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancewd( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svariancewd( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svariancewd( N, 1, x1, stride )\n","base.strided.svariancewd.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svariancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svariancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.svarianceyc":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svarianceyc( x.length, 1, x, 1 )\nx = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.svarianceyc( N, 1, x, stride )\nvar x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.svarianceyc( N, 1, x1, stride )\n","base.strided.svarianceyc.ndarray":"var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\nbase.strided.svarianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar N = base.floor( x.length / 2 );\nbase.strided.svarianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.ternary":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1 ];\nfunction f( x, y, z ) { return x + y + z; };\nbase.strided.ternary( [ x, y, z, w ], shape, strides, f );\nw\n","base.strided.ternary.ndarray":"var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1, 1, 1 ];\nvar offsets = [ 0, 0, 0, 0 ];\nfunction f( x, y, z ) { return x + y + z; };\nbase.strided.ternary.ndarray( [ x, y, z, w ], shape, strides, offsets, f );\nw\n","base.strided.unary":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1 ];\nbase.strided.unary( [ x, y ], shape, strides, base.abs );\ny\n","base.strided.unary.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar shape = [ x.length ];\nvar strides = [ 1, 1 ];\nvar offsets = [ 0, 0 ];\nbase.strided.unary.ndarray( [ x, y ], shape, strides, offsets, base.abs );\ny\n","base.strided.unaryBy":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nvar sh = [ x.length ];\nvar st = [ 1, 1 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\ny\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nsh = [ 2 ];\nst = [ 2, -1 ];\nbase.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\ny\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nsh = [ 2 ];\nst = [ -2, 1 ];\nbase.strided.unaryBy( [ x1, y1 ], sh, st, base.abs, clbk );\ny1\ny0\n","base.strided.unaryBy.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nvar sh = [ x.length ];\nvar st = [ 1, 1 ];\nvar o = [ 0, 0 ];\nfunction clbk( v ) { return v * 2.0; };\nbase.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\ny\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nsh = [ 2 ];\nst = [ 2, -1 ];\no = [ 1, y.length-1 ];\nbase.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\ny\n","base.strided.unaryDtypeSignatures":"var dt = strided.dataTypes();\nvar out = base.strided.unaryDtypeSignatures( dt, dt )\n","base.strided.unarySignatureCallbacks":"var dt = strided.dataTypes();\nvar sigs = base.strided.unaryDtypeSignatures( dt, dt );\nvar t = {\n 'default': base.identity,\n 'complex64': base.cidentityf,\n 'complex128': base.cidentity\n };\nvar out = base.strided.unarySignatureCallbacks( t, sigs )\n","base.strided.variance":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variance( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.variance( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.variance( N, 1, x1, stride )\n","base.strided.variance.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variance.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.variance.ndarray( N, 1, x, 2, 1 )\n","base.strided.variancech":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancech( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.variancech( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.variancech( N, 1, x1, stride )\n","base.strided.variancech.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancech.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.variancech.ndarray( N, 1, x, 2, 1 )\n","base.strided.variancepn":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancepn( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.variancepn( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.variancepn( N, 1, x1, stride )\n","base.strided.variancepn.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancepn.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.variancepn.ndarray( N, 1, x, 2, 1 )\n","base.strided.variancetk":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancetk( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.variancetk( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.variancetk( N, 1, x1, stride )\n","base.strided.variancetk.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancetk.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.variancetk.ndarray( N, 1, x, 2, 1 )\n","base.strided.variancewd":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancewd( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.variancewd( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.variancewd( N, 1, x1, stride )\n","base.strided.variancewd.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.variancewd.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.variancewd.ndarray( N, 1, x, 2, 1 )\n","base.strided.varianceyc":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.varianceyc( x.length, 1, x, 1 )\nx = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nvar stride = 2;\nbase.strided.varianceyc( N, 1, x, stride )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nN = base.floor( x0.length / 2 );\nstride = 2;\nbase.strided.varianceyc( N, 1, x1, stride )\n","base.strided.varianceyc.ndarray":"var x = [ 1.0, -2.0, 2.0 ];\nbase.strided.varianceyc.ndarray( x.length, 1, x, 1, 0 )\nvar x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\nvar N = base.floor( x.length / 2 );\nbase.strided.varianceyc.ndarray( N, 1, x, 2, 1 )\n","base.strided.zmap":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex128Array( xbuf );\nvar y = new Complex128Array( x.length );\nbase.strided.zmap( x.length, x, 1, y, 1, base.cidentity );\nvar v = y.get( 0 )\nvar re = real( v )\nvar im = imag( v )\ny = new Complex128Array( x.length );\nbase.strided.zmap( 2, x, 2, y, -1, base.cidentity );\nv = y.get( 0 )\nre = real( v )\nim = imag( v )\nvar x0 = new Complex128Array( xbuf );\nvar y0 = new Complex128Array( x0.length );\nvar x1 = new Complex128Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Complex128Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nbase.strided.zmap( 2, x1, -2, y1, 1, base.cidentity );\nv = y1.get( 0 )\nre = real( v )\nim = imag( v )\n","base.strided.zmap.ndarray":"var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\nvar x = new Complex128Array( xbuf );\nvar y = new Complex128Array( x.length );\nbase.strided.zmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentity );\nvar v = y.get( 0 )\nvar re = real( v )\nvar im = imag( v )\nx = new Complex128Array( xbuf );\ny = new Complex128Array( x.length );\nbase.strided.zmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentity );\nv = y.get( y.length-1 )\nre = real( v )\nim = imag( v )\n","base.str2multislice":"var s = new base.str2multislice( 'MultiSlice(null,null,null)' );\ns.data\ns = new base.str2multislice( 'MultiSlice(10,Slice(0,10,1),null)' );\ns.data\n","base.str2slice":"var s = new base.str2slice( 'Slice(1,10,1)' );\ns.start\ns.stop\ns.step\ns = new base.str2slice( 'Slice(2,5,2)' );\ns.start\ns.stop\ns.step\n","base.sub":"var v = base.sub( -1.0, 5.0 )\nv = base.sub( 2.0, 5.0 )\nv = base.sub( 0.0, 5.0 )\nv = base.sub( -0.0, 0.0 )\nv = base.sub( NaN, NaN )\n","base.subf":"var v = base.subf( -1.0, 5.0 )\nv = base.subf( 2.0, 5.0 )\nv = base.subf( 0.0, 5.0 )\nv = base.subf( -0.0, 0.0 )\nv = base.subf( NaN, NaN )\n","base.sumSeries":"function* geometricSeriesGenerator( x ) {\n var exponent = 0;\n while ( true ) {\n     yield Math.pow( x, exponent );\n     exponent += 1;\n }\n };\nvar gen = geometricSeriesGenerator( 0.9 );\nvar out = base.sumSeries( gen )\nfunction geometricSeriesClosure( x ) {\n var exponent = -1;\n return function() {\n     exponent += 1;\n     return Math.pow( x, exponent );\n };\n };\ngen = geometricSeriesClosure( 0.9 );\nout = base.sumSeries( gen )\nout = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'initialValue': 1 } )\nout = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'maxTerms': 10 } )\nout = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'tolerance': 1e-3 } )\n","base.tan":"var y = base.tan( 0.0 )\ny = base.tan( -PI/4.0 )\ny = base.tan( PI/4.0 )\ny = base.tan( NaN )\n","base.tand":"var y = base.tand( 0.0 )\ny = base.tand( 90.0 )\ny = base.tand( 60.0 )\ny = base.tand( NaN )\n","base.tanh":"var y = base.tanh( 0.0 )\nvar y = base.tanh( -0.0 )\ny = base.tanh( 2.0 )\ny = base.tanh( -2.0 )\ny = base.tanh( NaN )\n","base.toBinaryString":"var str = base.toBinaryString( 4.0 )\nstr = base.toBinaryString( PI )\nstr = base.toBinaryString( -1.0e308 )\nstr = base.toBinaryString( -3.14e-320 )\nstr = base.toBinaryString( 5.0e-324 )\nstr = base.toBinaryString( 0.0 )\nstr = base.toBinaryString( -0.0 )\nstr = base.toBinaryString( NaN )\nstr = base.toBinaryString( PINF )\nstr = base.toBinaryString( NINF )\n","base.toBinaryStringf":"var str = base.toBinaryStringf( base.float64ToFloat32( 4.0 ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( PI ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( -1.0e38 ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( -3.14e-39 ) )\nstr = base.toBinaryStringf( base.float64ToFloat32( 1.4e-45 ) )\nstr = base.toBinaryStringf( 0.0 )\nstr = base.toBinaryStringf( -0.0 )\nstr = base.toBinaryStringf( NaN )\nstr = base.toBinaryStringf( FLOAT32_PINF )\nstr = base.toBinaryStringf( FLOAT32_NINF )\n","base.toBinaryStringUint8":"var a = new Uint8Array( [ 1, 4, 9 ] );\nvar str = base.toBinaryStringUint8( a[ 0 ] )\nstr = base.toBinaryStringUint8( a[ 1 ] )\nstr = base.toBinaryStringUint8( a[ 2 ] )\n","base.toBinaryStringUint16":"var a = new Uint16Array( [ 1, 4, 9 ] );\nvar str = base.toBinaryStringUint16( a[ 0 ] )\nstr = base.toBinaryStringUint16( a[ 1 ] )\nstr = base.toBinaryStringUint16( a[ 2 ] )\n","base.toBinaryStringUint32":"var a = new Uint32Array( [ 1, 4, 9 ] );\nvar str = base.toBinaryStringUint32( a[ 0 ] )\nstr = base.toBinaryStringUint32( a[ 1 ] )\nstr = base.toBinaryStringUint32( a[ 2 ] )\n","base.toWordf":"var f32 = base.float64ToFloat32( 1.337 )\nvar w = base.toWordf( f32 )\n","base.toWords":"var w = base.toWords( 3.14e201 )\n","base.toWords.assign":"var out = new Uint32Array( 2 );\nvar w = base.toWords.assign( 3.14e201, out, 1, 0 )\nvar bool = ( w === out )\n","base.transpose":"var x = array( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\nvar sh = x.shape\nvar y = base.transpose( x )\nsh = y.shape\nvar bool = ( x.data === y.data )\nbool = ( x.get( 0, 1 ) === y.get( 1, 0 ) )\n","base.tribonacci":"var y = base.tribonacci( 0 )\ny = base.tribonacci( 1 )\ny = base.tribonacci( 2 )\ny = base.tribonacci( 3 )\ny = base.tribonacci( 4 )\ny = base.tribonacci( 64 )\ny = base.tribonacci( NaN )\n","base.trigamma":"var y = base.trigamma( -2.5 )\ny = base.trigamma( 1.0 )\ny = base.trigamma( 10.0 )\ny = base.trigamma( NaN )\ny = base.trigamma( -1.0 )\n","base.trim":"var out = base.trim( ' \\t\\t\\n  Beep \\r\\n\\t  ' )\n","base.trunc":"var y = base.trunc( 3.14 )\ny = base.trunc( -4.2 )\ny = base.trunc( -4.6 )\ny = base.trunc( 9.5 )\ny = base.trunc( -0.0 )\n","base.trunc2":"var y = base.trunc2( 3.14 )\ny = base.trunc2( -4.2 )\ny = base.trunc2( -4.6 )\ny = base.trunc2( 9.5 )\ny = base.trunc2( 13.0 )\ny = base.trunc2( -13.0 )\ny = base.trunc2( -0.0 )\n","base.trunc10":"var y = base.trunc10( 3.14 )\ny = base.trunc10( -4.2 )\ny = base.trunc10( -4.6 )\ny = base.trunc10( 9.5 )\ny = base.trunc10( 13.0 )\ny = base.trunc10( -13.0 )\ny = base.trunc10( -0.0 )\n","base.truncateMiddle":"var str = 'beep boop';\nvar out = base.truncateMiddle( str, 5, '...' )\nout = base.truncateMiddle( str, 5, '|' )\n","base.truncb":"var y = base.truncb( 3.14159, -4, 10 )\ny = base.truncb( 3.14159, 0, 2 )\ny = base.truncb( 5.0, 1, 2 )\n","base.truncf":"var y = base.truncf( 3.14 )\ny = base.truncf( -4.2 )\ny = base.truncf( -4.6 )\ny = base.truncf( 9.5 )\ny = base.truncf( -0.0 )\n","base.truncn":"var y = base.truncn( 3.14159, -4 )\ny = base.truncn( 3.14159, 0 )\ny = base.truncn( 12368.0, 3 )\n","base.truncsd":"var y = base.truncsd( 3.14159, 5, 10 )\ny = base.truncsd( 3.14159, 1, 10 )\ny = base.truncsd( 12368.0, 2, 10 )\ny = base.truncsd( 0.0313, 2, 2 )\n","base.uint32ToInt32":"var y = base.uint32ToInt32( base.float64ToUint32( 4294967295 ) )\ny = base.uint32ToInt32( base.float64ToUint32( 3 ) )\n","base.umul":"var v = base.umul( 10>>>0, 4>>>0 )\n","base.umuldw":"var v = base.umuldw( 1, 10 )\n","base.umuldw.assign":"var out = [ 0, 0 ];\nvar v = base.umuldw.assign( 1, 10, out, 1, 0 )\nvar bool = ( v === out )\n","base.uncapitalize":"var out = base.uncapitalize( 'Beep' )\nout = base.uncapitalize( 'bOOp' )\n","base.uppercase":"var out = base.uppercase( 'bEEp' )\n","base.vercos":"var y = base.vercos( 3.14 )\ny = base.vercos( -4.2 )\ny = base.vercos( -4.6 )\ny = base.vercos( 9.5 )\ny = base.vercos( -0.0 )\n","base.versin":"var y = base.versin( 3.14 )\ny = base.versin( -4.2 )\ny = base.versin( -4.6 )\ny = base.versin( 9.5 )\ny = base.versin( -0.0 )\n","base.wrap":"var y = base.wrap( 3.14, 0.0, 5.0 )\ny = base.wrap( -3.14, 0.0, 5.0 )\ny = base.wrap( 3.14, 0.0, 3.0 )\ny = base.wrap( -0.0, 0.0, 5.0 )\ny = base.wrap( 0.0, -3.14, -0.0 )\ny = base.wrap( NaN, 0.0, 5.0 )\n","base.xlog1py":"var out = base.xlog1py( 3.0, 2.0 )\nout = base.xlog1py( 1.5, 5.9 )\nout = base.xlog1py( 0.9, 1.0 )\nout = base.xlog1py( 1.0, 0.0 )\nout = base.xlog1py( 0.0, -2.0 )\nout = base.xlog1py( 1.5, NaN )\nout = base.xlog1py( 0.0, NaN )\nout = base.xlog1py( NaN, 2.3 )\n","base.xlogy":"var out = base.xlogy( 3.0, 2.0 )\nout = base.xlogy( 1.5, 5.9 )\nout = base.xlogy( 0.9, 1.0 )\nout = base.xlogy( 0.0, -2.0 )\nout = base.xlogy( 1.5, NaN )\nout = base.xlogy( 0.0, NaN )\nout = base.xlogy( NaN, 2.3 )\n","base.zeta":"var y = base.zeta( 1.1 )\ny = base.zeta( -4.0 )\ny = base.zeta( 70.0 )\ny = base.zeta( 0.5 )\ny = base.zeta( NaN )\ny = base.zeta( 1.0 )\n","BERNDT_CPS_WAGES_1985":"var data = BERNDT_CPS_WAGES_1985()\n","bifurcate":"var collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar f = [ true, true, false, true ];\nvar out = bifurcate( collection, f )\nf = [ 1, 1, 0, 1 ];\nout = bifurcate( collection, f )\nf = [ true, true, false, true ];\nvar opts = { 'returns': 'indices' };\nout = bifurcate( collection, opts, f )\nopts = { 'returns': '*' };\nout = bifurcate( collection, opts, f )\n","bifurcateBy":"function predicate( v ) { return v[ 0 ] === 'b'; };\nvar collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar out = bifurcateBy( collection, predicate )\nvar opts = { 'returns': 'indices' };\nout = bifurcateBy( collection, opts, predicate )\nopts = { 'returns': '*' };\nout = bifurcateBy( collection, opts, predicate )\n","bifurcateByAsync":"function predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nbifurcateByAsync( arr, predicate, done )\nvar opts = { 'returns': 'indices' };\nbifurcateByAsync( arr, opts, predicate, done )\nopts = { 'returns': '*' };\nbifurcateByAsync( arr, opts, predicate, done )\nfunction predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nbifurcateByAsync( arr, opts, predicate, done )\nfunction predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nbifurcateByAsync( arr, opts, predicate, done )\n","bifurcateByAsync.factory":"function predicate( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) );\n }\n };\nvar opts = { 'series': true };\nvar f = bifurcateByAsync.factory( opts, predicate );\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","bifurcateIn":"function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\nFoo.prototype = Object.create( null );\nFoo.prototype.c = 'foo';\nFoo.prototype.d = 'bar';\nvar obj = new Foo();\nfunction predicate( v ) { return v[ 0 ] === 'b'; };\nvar out = bifurcateIn( obj, predicate )\nvar opts = { 'returns': 'keys' };\nout = bifurcateIn( obj, opts, predicate )\nopts = { 'returns': '*' };\nout = bifurcateIn( obj, opts, predicate )\n","bifurcateOwn":"function predicate( v ) { return v[ 0 ] === 'b'; };\nvar obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\nvar out = bifurcateOwn( obj, predicate )\nvar opts = { 'returns': 'keys' };\nout = bifurcateOwn( obj, opts, predicate )\nopts = { 'returns': '*' };\nout = bifurcateOwn( obj, opts, predicate )\n","BigInt":"var v = ( BigInt ) ? BigInt( '1' ) : null\n","binomialTest":"var out = binomialTest( 682, 925 )\nout = binomialTest( [ 682, 925 - 682 ] )\nout = binomialTest( 21, 40, {\n 'p': 0.4,\n 'alternative': 'greater'\n })\n","Boolean":"var b = new Boolean( null )\nb = Boolean( null )\nb = Boolean( [] )\n","Boolean.prototype.toString":"var b = new Boolean( true )\nb.toString()\n","Boolean.prototype.valueOf":"var b = new Boolean( true )\nb.valueOf()\n","BooleanArray":"var arr = new BooleanArray()\nvar arr = new BooleanArray( 10 )\nvar len = arr.length\nvar arr1 = new BooleanArray( [ true, false, false, true ] )\nvar arr2 = new BooleanArray( arr1 )\nvar len = arr2.length\nvar buf = new Uint8Array( [ 1, 0, 0, 1 ] )\nvar arr = new BooleanArray( buf )\nvar len = arr.length\nvar arr1 = new BooleanArray( [ true, false, false, true ] )\nvar len = arr1.length\nvar arr2 = new BooleanArray( [ {}, null, '', 4 ] );\nlen = arr2.length\nvar buf = new ArrayBuffer( 240 );\nvar arr1 = new BooleanArray( buf )\nvar len = arr1.length\nvar arr2 = new BooleanArray( buf, 8 )\nlen = arr2.length\nvar arr3 = new BooleanArray( buf, 8, 20 )\nlen = arr3.length\n","BooleanArray.from":"function map( v ) { return !v };\nvar src = [ true, false ];\nvar arr = BooleanArray.from( src, map )\nvar len = arr.length\nvar v = arr.get( 0 )\nv = arr.get( 1 )\n","BooleanArray.of":"var arr = BooleanArray.of( true, false, false, true )\nvar len = arr.length\n","BooleanArray.BYTES_PER_ELEMENT":"var nbytes = BooleanArray.BYTES_PER_ELEMENT\n","BooleanArray.name":"var str = BooleanArray.name\n","BooleanArray.prototype.buffer":"var arr = new BooleanArray( 2 )\nvar buf = arr.buffer\n","BooleanArray.prototype.byteLength":"var arr = new BooleanArray( 10 )\nvar nbytes = arr.byteLength\n","BooleanArray.prototype.byteOffset":"var arr = new BooleanArray( 10 )\nvar offset = arr.byteOffset\nvar buf = new ArrayBuffer( 240 );\narr = new BooleanArray( buf, 64 )\noffset = arr.byteOffset\n","BooleanArray.prototype.BYTES_PER_ELEMENT":"var arr = new BooleanArray( 10 )\narr.BYTES_PER_ELEMENT\n","BooleanArray.prototype.length":"var arr = new BooleanArray( 10 )\nvar len = arr.length\n","BooleanArray.prototype.at":"var arr = new BooleanArray( [ true, false, false, true ] )\nvar v = arr.at( 1 )\nv = arr.at( -1 )\n","BooleanArray.prototype.copyWithin":"var arr = new BooleanArray( [ true, false, false, true ] )\narr.copyWithin( 0, 2 )\nvar v = arr.get( 0 )\nv = arr.get( 1 )\n","BooleanArray.prototype.entries":"var arr = new BooleanArray( [ true, false, true ] )\nvar it = arr.entries();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","BooleanArray.prototype.every":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, true, true ] )\nvar bool = arr.every( predicate )\n","BooleanArray.prototype.fill":"var arr = new BooleanArray( 3 )\narr.fill( true );\nvar v = arr.get( 0 )\nv = arr.get( 1 )\nv = arr.get( 2 )\n","BooleanArray.prototype.filter":"function predicate( v ) { return ( v === true ); };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.filter( predicate )\nvar len = out.length\nvar v = out.get( 0 )\nv = out.get( 1 )\n","BooleanArray.prototype.find":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar v = arr.find( predicate )\n","BooleanArray.prototype.findIndex":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar idx = arr.findIndex( predicate )\n","BooleanArray.prototype.findLast":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar v = arr.findLast( predicate )\n","BooleanArray.prototype.findLastIndex":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar idx = arr.findLastIndex( predicate )\n","BooleanArray.prototype.forEach":"var str = '%';\nfunction clbk( v ) { str += v.toString() + '%'; };\nvar arr = new BooleanArray( [ true, false, false, true ] )\narr.forEach( clbk );\nstr\n","BooleanArray.prototype.get":"var arr = new BooleanArray( 10 )\narr.set( true, 0 );\nvar v = arr.get( 0 )\n","BooleanArray.prototype.includes":"var arr = new BooleanArray( [ true, false, true, true, true ] )\nvar bool = arr.includes( true )\nbool = arr.includes( false, 3 )\n","BooleanArray.prototype.indexOf":"var arr = new BooleanArray( [ true, false, true, true, true ] )\nvar idx = arr.indexOf( true )\nidx = arr.indexOf( false, 3 )\n","BooleanArray.prototype.join":"var arr = new BooleanArray( [ true, false, true ] )\nvar str = arr.join()\nstr = arr.join( '|' )\n","BooleanArray.prototype.keys":"var arr = new BooleanArray( [ true, false ] )\nvar it = arr.keys();\nvar v = it.next().value\nv = it.next().value\nv = it.next().done\n","BooleanArray.prototype.lastIndexOf":"var arr = new BooleanArray( [ true, true, true, false, true ] )\nvar idx = arr.lastIndexOf( false )\nidx = arr.lastIndexOf( false, 2 )\n","BooleanArray.prototype.map":"function invert( v ) { return !v; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.map( invert )\nvar v = out.get( 0 )\nv = out.get( 1 )\nv = out.get( 2 )\n","BooleanArray.prototype.reduce":"function reducer( acc, v ) { return ( acc && v ); };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.reduce( reducer )\n","BooleanArray.prototype.reduceRight":"function reducer( acc, v ) { return ( acc && v ); };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.reduceRight( reducer )\n","BooleanArray.prototype.reverse":"var arr = new BooleanArray( [ true, false, false ] )\narr.reverse();\nvar v = arr.get( 0 )\nv = arr.get( 1 )\nv = arr.get( 2 )\n","BooleanArray.prototype.set":"var arr = new BooleanArray( 2 )\narr.set( false );\nvar v = arr.get( 0 )\narr.set( true, 1 );\nv = arr.get( 1 )\n","BooleanArray.prototype.slice":"var arr = new BooleanArray( [ true, false, true, false, true ] )\nvar out = arr.slice( 1 )\nvar len = out.length\nvar v = out.get( 0 )\nv = out.get( 1 )\n","BooleanArray.prototype.some":"function predicate( v ) { return v === true; };\nvar arr = new BooleanArray( [ false, true, false ] )\nvar bool = arr.some( predicate )\n","BooleanArray.prototype.sort":"function compare( a, b ) { return a === true ? -1 : 1; };\nvar arr = new BooleanArray( [ true, false, true ] )\narr.sort( compare );\nvar v = arr.get( 0 )\nv = arr.get( 1 )\nv = arr.get( 2 )\n","BooleanArray.prototype.subarray":"var arr = new BooleanArray( [ true, false, true, false, true ] )\nvar out = arr.subarray( 1, 3 )\nvar len = out.length\nvar v = out.get( 0 )\nv = out.get( 1 )\n","BooleanArray.prototype.toLocaleString":"var arr = new BooleanArray( [ true, false, true ] )\nvar str = arr.toLocaleString()\n","BooleanArray.prototype.toReversed":"var arr = new BooleanArray( [ true, false, false ] )\nvar out = arr.toReversed()\nvar v = out.get( 0 )\nv = out.get( 1 )\nv = out.get( 2 )\n","BooleanArray.prototype.toSorted":"function compare( a, b ) { return a === true ? -1 : 1; };\nvar arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.toSorted( compare );\nvar v = out.get( 0 )\nv = out.get( 1 )\nv = out.get( 2 )\n","BooleanArray.prototype.toString":"var arr = new BooleanArray( [ true, false, true ] )\nvar str = arr.toString()\n","BooleanArray.prototype.values":"var arr = new BooleanArray( [ true, false ] )\nvar it = arr.values();\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","BooleanArray.prototype.with":"var arr = new BooleanArray( [ true, false, true ] )\nvar out = arr.with( 0, false )\nvar v = out.get( 0 )\n","broadcastArray":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = broadcastArray( x, [ 3, 2, 2 ] )\nsh = y.shape\nvar v = y.get( 0, 0, 0 )\nv = y.get( 0, 0, 1 )\nv = y.get( 0, 1, 0 )\nv = y.get( 0, 1, 1 )\nv = y.get( 1, 0, 0 )\nv = y.get( 1, 1, 0 )\nv = y.get( 2, 0, 0 )\nv = y.get( 2, 1, 1 )\n","broadcastArrays":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = ndzeros( [ 3, 2, 2 ] )\nvar out = broadcastArrays( [ x, y ] )\nvar bx = out[ 0 ]\nsh = bx.shape\nvar v = bx.get( 0, 0, 0 )\nv = bx.get( 0, 0, 1 )\nv = bx.get( 0, 1, 0 )\nv = bx.get( 0, 1, 1 )\nv = bx.get( 1, 0, 0 )\nv = bx.get( 1, 1, 0 )\nv = bx.get( 2, 0, 0 )\nv = bx.get( 2, 1, 1 )\n","Buffer":"var b = new Buffer( 4 )\nvar b1 = new Buffer( [ 1, 2, 3, 4 ] );\nvar b2 = new Buffer( b1 )\nvar b = new Buffer( [ 1, 2, 3, 4 ] )\nvar b = new Buffer( 'beep boop' )\n","buffer2json":"var buf = new allocUnsafe( 2 );\nbuf[ 0 ] = 1;\nbuf[ 1 ] = 2;\nvar json = buffer2json( buf )\n","BYTE_ORDER":"BYTE_ORDER\n","camelcase":"var out = camelcase( 'Hello World!' )\nout = camelcase( 'beep boop' )\n","capitalize":"var out = capitalize( 'beep' )\nout = capitalize( 'Boop' )\n","capitalizeKeys":"var obj = { 'aa': 1, 'bb': 2 };\nvar out = capitalizeKeys( obj )\n","CATALAN":"CATALAN\n","CBRT_EPS":"CBRT_EPS\n","CDC_NCHS_US_BIRTHS_1969_1988":"var data = CDC_NCHS_US_BIRTHS_1969_1988()\n","CDC_NCHS_US_BIRTHS_1994_2003":"var data = CDC_NCHS_US_BIRTHS_1994_2003()\n","CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013":"var data = CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n","chdir":"var err = chdir( '/path/to/current/working/directory' )\n","chi2gof":"var x = [ 89, 37, 30, 28, 2 ];\nvar p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\nvar out = chi2gof( x, p );\nvar o = out.toJSON()\nout.toString()\nvar opts = { 'alpha': 0.01 };\nout = chi2gof( x, p, opts );\nout.toString()\nx = [ 89, 37, 30, 28, 2 ];\np = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\nopts = { 'simulate': true, 'iterations': 1000 };\nout = chi2gof( x, p, opts );\nout.toString()\nvar lambda = 3.0;\nvar rpois = base.random.poisson.factory( lambda );\nvar len = 400;\nx = [];\nfor ( var i = 0; i < len; i++ ) { x.push( rpois() ); };\nvar freqs = new Int32Array( len );\nfor ( i = 0; i < len; i++ ) { freqs[ x[ i ] ] += 1; };\nout = chi2gof( freqs, 'poisson', lambda );\nout.toString()\n","chi2test":"var x = [ [ 20, 30 ], [ 30, 20 ] ];\nvar out = chi2test( x );\nvar o = out.toJSON()\nout.toString()\nvar opts = { 'alpha': 0.1 };\nout = chi2test( x, opts );\no = out.toJSON()\nout.toString()\nopts = { 'correct': false };\nout = chi2test( x, opts );\nout.toString()\n","circarray2iterator":"var it = circarray2iterator( [ 1, 2, 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","circularArrayStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 15 };\nvar s = circularArrayStream( [ 1, 2, 3 ], opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","circularArrayStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = circularArrayStream.factory( opts );\n","circularArrayStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 15 };\nvar s = circularArrayStream.objectMode( [ 1, 2, 3 ], opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","CircularBuffer":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.length\nb.count\nb.push( 'boop' )\n","CircularBuffer.prototype.clear":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.count\nb.clear();\nb.count\n","CircularBuffer.prototype.count":"var b = CircularBuffer( 3 );\nb.count\nb.push( 'foo' );\nb.count\nb.push( 'bar' );\nb.count\n","CircularBuffer.prototype.full":"var b = CircularBuffer( 3 );\nb.full\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.full\n","CircularBuffer.prototype.iterator":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.push( 'boop' );\nvar it = b.iterator( b.length );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","CircularBuffer.prototype.length":"var b = CircularBuffer( [ 0, 0, 0 ] );\nvar len = b.length\n","CircularBuffer.prototype.push":"var b = CircularBuffer( 3 );\nb.push( 'foo' )\nb.push( 'bar' )\nb.push( 'beep' )\nb.push( 'boop' )\n","CircularBuffer.prototype.toArray":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.push( 'boop' );\nvar vals = b.toArray()\n","CircularBuffer.prototype.toJSON":"var b = CircularBuffer( 3 );\nb.push( 'foo' );\nb.push( 'bar' );\nb.push( 'beep' );\nb.push( 'boop' );\nvar o = b.toJSON()\n","close":"function done( error ) {\n if ( error ) {\n     console.error( error.message );\n }\n };\nvar fd = open.sync( './beep/boop.js', 'r+' );\nif ( !isError( fd ) ) { close( fd, done ); };\n","close.sync":"var fd = open.sync( './beep/boop.js', 'r+' );\nif ( !isError( fd ) ) { close.sync( fd ); };\n","CMUDICT":"var data = CMUDICT();\nvar dict = data.dict\nvar phones = data.phones\nvar symbols = data.symbols\nvar vp = data.vp\n","codePointAt":"var out = codePointAt( 'last man standing', 4 )\nout = codePointAt( 'presidential election', 8, true )\nout = codePointAt( 'अनुच्छेद', 2 )\nout = codePointAt( '🌷', 1, true )\n","commonKeys":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\nvar keys = commonKeys( obj1, obj2 )\n","commonKeysIn":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\nvar keys = commonKeysIn( obj1, obj2 )\n","complex":"var z = complex( 5.0, 3.0, 'float64' )\nz = complex( 5.0, 3.0, 'float32' )\n","Complex64":"var z = new Complex64( 5.0, 3.0 )\nz.re\nz.im\n","Complex64.BYTES_PER_ELEMENT":"var s = Complex64.BYTES_PER_ELEMENT\n","Complex64.prototype.BYTES_PER_ELEMENT":"var z = new Complex64( 5.0, 3.0 )\nvar s = z.BYTES_PER_ELEMENT\n","Complex64.prototype.byteLength":"var z = new Complex64( 5.0, 3.0 )\nvar s = z.byteLength\n","COMPLEX64_NAN":"COMPLEX64_NAN\n","COMPLEX64_NUM_BYTES":"COMPLEX64_NUM_BYTES\n","COMPLEX64_ZERO":"COMPLEX64_ZERO\n","Complex64Array":"var arr = new Complex64Array()\nvar arr = new Complex64Array( 10 )\nvar len = arr.length\nvar arr1 = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar arr2 = new Complex64Array( arr1 )\nvar len = arr2.length\nvar buf = new Float32Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar arr = new Complex64Array( buf )\nvar len = arr.length\nvar arr1 = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar len = arr1.length\nvar buf = [ new Complex64( 1.0, -1.0 ), new Complex64( 2.0, -2.0 )];\nvar arr2 = new Complex64Array( buf )\nlen = arr2.length\nvar buf = new ArrayBuffer( 240 );\nvar arr1 = new Complex64Array( buf )\nvar len = arr1.length\nvar arr2 = new Complex64Array( buf, 8 )\nlen = arr2.length\nvar arr3 = new Complex64Array( buf, 8, 20 )\nlen = arr3.length\n","Complex64Array.from":"function clbkFcn( v ) { return v * 2.0 };\nvar arr = Complex64Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\nvar len = arr.length\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.of":"var arr = Complex64Array.of( 1.0, -1.0, 2.0, -2.0 )\nvar len = arr.length\nvar z1 = new Complex64( 1.0, -1.0 );\nvar z2 = new Complex64( 2.0, -2.0 );\narr = Complex64Array.of( z1, z2 )\nlen = arr.length\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.BYTES_PER_ELEMENT":"var nbytes = Complex64Array.BYTES_PER_ELEMENT\n","Complex64Array.name":"var str = Complex64Array.name\n","Complex64Array.prototype.buffer":"var arr = new Complex64Array( 2 )\nvar buf = arr.buffer\n","Complex64Array.prototype.byteLength":"var arr = new Complex64Array( 10 )\nvar nbytes = arr.byteLength\n","Complex64Array.prototype.byteOffset":"var arr = new Complex64Array( 5 )\nvar offset = arr.byteOffset\nvar buf = new ArrayBuffer( 240 );\narr = new Complex64Array( buf, 64 )\noffset = arr.byteOffset\n","Complex64Array.prototype.BYTES_PER_ELEMENT":"var arr = new Complex64Array( 10 )\narr.BYTES_PER_ELEMENT\n","Complex64Array.prototype.length":"var arr = new Complex64Array( 10 )\nvar len = arr.length\n","Complex64Array.prototype.at":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.at( 1 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.copyWithin":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\narr.copyWithin( 0, 2 )\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.entries":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\nvar it = arr.entries();\nvar v = it.next().value\nvar re = realf( v[ 1 ] )\nvar im = imagf( v[ 1 ] )\nv = it.next().value\nre = realf( v[ 1 ] )\nim = imagf( v[ 1 ] )\nv = it.next().value\nre = realf( v[ 1 ] )\nim = imagf( v[ 1 ] )\nvar bool = it.next().done\n","Complex64Array.prototype.every":"function predicate( v ) { return ( realf( v ) > 0.0 ); };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar bool = arr.every( predicate )\n","Complex64Array.prototype.fill":"var arr = new Complex64Array( 3 )\narr.fill( new Complex64( 1.0, 1.0 ) );\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = arr.get( 1 )\nre = realf( z )\nim = imagf( z )\nz = arr.get( 2 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.filter":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar out = arr.filter( predicate )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.find":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar z = arr.find( predicate )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.findIndex":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar idx = arr.findIndex( predicate )\n","Complex64Array.prototype.findLast":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar z = arr.findLast( predicate )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.findLastIndex":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar idx = arr.findLastIndex( predicate )\n","Complex64Array.prototype.forEach":"var str = '%';\nfunction clbk( v ) { str += v.toString() + '%'; };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\narr.forEach( clbk );\nstr\n","Complex64Array.prototype.get":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.get( 1 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.includes":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar bool = arr.includes( new Complex64( 3.0, -3.0 ) )\nbool = arr.includes( new Complex64( 3.0, -3.0 ), 3 )\n","Complex64Array.prototype.indexOf":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar idx = arr.indexOf( new Complex64( 3.0, -3.0 ) )\nidx = arr.indexOf( new Complex64( 3.0, -3.0 ), 3 )\n","Complex64Array.prototype.join":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar str = arr.join()\nstr = arr.join( '/' )\n","Complex64Array.prototype.keys":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar it = arr.keys();\nvar v = it.next().value\nv = it.next().value\nv = it.next().done\n","Complex64Array.prototype.lastIndexOf":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\nvar idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ) )\nidx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ), 2 )\n","Complex64Array.prototype.map":"function clbk( v ) { return v; };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar out = arr.map( clbk )\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = out.get( 1 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.reduce":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.reduce( base.caddf )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.reduceRight":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.reduceRight( base.caddf )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex64Array.prototype.reverse":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\narr.reverse();\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = arr.get( 1 )\nre = realf( z )\nim = imagf( z )\nz = arr.get( 2 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.set":"var arr = new Complex64Array( 2 )\narr.set( new Complex64( 1.0, -1.0 ) );\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\narr.set( new Complex64( 2.0, -2.0 ), 1 );\nz = arr.get( 1 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.slice":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\nvar out = arr.slice( 1 )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = out.get( 1 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.some":"function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\nvar arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar bool = arr.some( predicate )\n","Complex64Array.prototype.sort":"function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\nvar arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\narr.sort( compare );\nvar z = arr.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = arr.get( 1 )\nre = realf( z )\nim = imagf( z )\nz = arr.get( 2 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.subarray":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar out = arr.subarray( 1, 3 )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = out.get( 1 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.toLocaleString":"var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0 ] )\nvar str = arr.toLocaleString()\n","Complex64Array.prototype.toReversed":"var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\nvar out = arr.toReversed()\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = out.get( 1 )\nre = realf( z )\nim = imagf( z )\nz = out.get( 2 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.toSorted":"function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\nvar arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\nvar out = arr.toSorted( compare );\nvar z = out.get( 0 )\nvar re = realf( z )\nvar im = imagf( z )\nz = out.get( 1 )\nre = realf( z )\nim = imagf( z )\nz = out.get( 2 )\nre = realf( z )\nim = imagf( z )\n","Complex64Array.prototype.toString":"var arr = new Complex64Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\nvar str = arr.toString()\n","Complex64Array.prototype.values":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar it = arr.values();\nvar v = it.next().value\nvar re = realf( v )\nvar im = imagf( v )\nv = it.next().value\nre = realf( v )\nim = imagf( v )\nvar bool = it.next().done\n","Complex64Array.prototype.with":"var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\nvar z = out.get( 1 )\nvar re = realf( z )\nvar im = imagf( z )\n","Complex128.BYTES_PER_ELEMENT":"var s = Complex128.BYTES_PER_ELEMENT\n","Complex128.prototype.BYTES_PER_ELEMENT":"var z = new Complex128( 5.0, 3.0 )\nvar s = z.BYTES_PER_ELEMENT\n","Complex128.prototype.byteLength":"var z = new Complex128( 5.0, 3.0 )\nvar s = z.byteLength\n","COMPLEX128_NAN":"COMPLEX128_NAN\n","COMPLEX128_NUM_BYTES":"COMPLEX128_NUM_BYTES\n","COMPLEX128_ZERO":"COMPLEX128_ZERO\n","Complex128Array":"var arr = new Complex128Array()\nvar arr = new Complex128Array( 10 )\nvar len = arr.length\nvar arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar arr2 = new Complex128Array( arr1 )\nvar len = arr2.length\nvar buf = new Float64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar arr = new Complex128Array( buf )\nvar len = arr.length\nvar arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar len = arr1.length\nvar buf = [ new Complex128( 1.0, -1.0 ), new Complex128( 2.0, -2.0 ) ];\nvar arr2 = new Complex128Array( buf )\nlen = arr2.length\nvar buf = new ArrayBuffer( 480 );\nvar arr1 = new Complex128Array( buf )\nvar len = arr1.length\nvar arr2 = new Complex128Array( buf, 16 )\nlen = arr2.length\nvar arr3 = new Complex128Array( buf, 16, 20 )\nlen = arr3.length\n","Complex128Array.from":"function clbkFcn( v ) { return v * 2.0 };\nvar arr = Complex128Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\nvar len = arr.length\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.of":"var arr = Complex128Array.of( 1.0, -1.0, 2.0, -2.0 )\nvar len = arr.length\nvar z1 = new Complex128( 1.0, -1.0 );\nvar z2 = new Complex128( 2.0, -2.0 );\narr = Complex128Array.of( z1, z2 )\nlen = arr.length\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.BYTES_PER_ELEMENT":"var nbytes = Complex128Array.BYTES_PER_ELEMENT\n","Complex128Array.name":"var str = Complex128Array.name\n","Complex128Array.prototype.buffer":"var arr = new Complex128Array( 2 )\nvar buf = arr.buffer\n","Complex128Array.prototype.byteLength":"var arr = new Complex128Array( 10 )\nvar nbytes = arr.byteLength\n","Complex128Array.prototype.byteOffset":"var arr = new Complex128Array( 10 )\nvar offset = arr.byteOffset\nvar buf = new ArrayBuffer( 480 );\narr = new Complex128Array( buf, 128 )\noffset = arr.byteOffset\n","Complex128Array.prototype.BYTES_PER_ELEMENT":"var arr = new Complex128Array( 10 )\narr.BYTES_PER_ELEMENT\n","Complex128Array.prototype.length":"var arr = new Complex128Array( 10 )\nvar len = arr.length\n","Complex128Array.prototype.at":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.at( 1 )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.copyWithin":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\narr.copyWithin( 0, 2 )\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.entries":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\nvar it = arr.entries();\nvar v = it.next().value\nvar re = real( v[ 1 ] )\nvar im = imag( v[ 1 ] )\nv = it.next().value\nre = real( v[ 1 ] )\nim = imag( v[ 1 ] )\nv = it.next().value\nre = real( v[ 1 ] )\nim = imag( v[ 1 ] )\nvar bool = it.next().done\n","Complex128Array.prototype.every":"function predicate( v ) { return ( real( v ) > 0.0 ); };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar bool = arr.every( predicate )\n","Complex128Array.prototype.fill":"var arr = new Complex128Array( 3 )\narr.fill( new Complex128( 1.0, 1.0 ) );\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = arr.get( 1 )\nre = real( z )\nim = imag( z )\nz = arr.get( 2 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.filter":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar out = arr.filter( predicate )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.find":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar z = arr.find( predicate )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.findIndex":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar idx = arr.findIndex( predicate )\n","Complex128Array.prototype.findLast":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar z = arr.findLast( predicate )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.findLastIndex":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar idx = arr.findLastIndex( predicate )\n","Complex128Array.prototype.forEach":"var str = '%';\nfunction clbk( v ) { str += v.toString() + '%'; };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\narr.forEach( clbk );\nstr\n","Complex128Array.prototype.get":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.get( 1 )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.includes":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar bool = arr.includes( new Complex128( 3.0, -3.0 ) )\nbool = arr.includes( new Complex128( 3.0, -3.0 ), 3 )\n","Complex128Array.prototype.indexOf":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar idx = arr.indexOf( new Complex128( 3.0, -3.0 ) )\nidx = arr.indexOf( new Complex128( 3.0, -3.0 ), 3 )\n","Complex128Array.prototype.join":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar str = arr.join()\nstr = arr.join( '/' )\n","Complex128Array.prototype.keys":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar it = arr.keys();\nvar v = it.next().value\nv = it.next().value\nv = it.next().done\n","Complex128Array.prototype.lastIndexOf":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\nvar idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ) )\nidx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ), 2 )\n","Complex128Array.prototype.map":"function clbk( v ) { return v; };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar out = arr.map( clbk )\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = out.get( 1 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.reduce":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.reduce( base.cadd )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.reduceRight":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar z = arr.reduceRight( base.cadd )\nvar re = real( z )\nvar im = imag( z )\n","Complex128Array.prototype.reverse":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\narr.reverse();\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = arr.get( 1 )\nre = real( z )\nim = imag( z )\nz = arr.get( 2 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.set":"var arr = new Complex128Array( 2 )\narr.set( new Complex128( 1.0, -1.0 ) );\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\narr.set( new Complex128( 2.0, -2.0 ), 1 );\nz = arr.get( 1 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.slice":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\nvar out = arr.slice( 1 )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = out.get( 1 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.some":"function predicate( v ) { return ( real( v ) === imag( v ) ); };\nvar arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\nvar bool = arr.some( predicate )\n","Complex128Array.prototype.sort":"function compare( a, b ) { return ( real( a ) - real( b ) ); };\nvar arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\narr.sort( compare );\nvar z = arr.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = arr.get( 1 )\nre = real( z )\nim = imag( z )\nz = arr.get( 2 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.subarray":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\nvar out = arr.subarray( 1, 3 )\nvar len = out.length\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = out.get( 1 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.toLocaleString":"var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0 ] )\nvar str = arr.toLocaleString()\n","Complex128Array.prototype.toReversed":"var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\nvar out = arr.toReversed()\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = out.get( 1 )\nre = real( z )\nim = imag( z )\nz = out.get( 2 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.toSorted":"function compare( a, b ) { return ( real( a ) - real( b ) ); };\nvar arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\nvar out = arr.toSorted( compare );\nvar z = out.get( 0 )\nvar re = real( z )\nvar im = imag( z )\nz = out.get( 1 )\nre = real( z )\nim = imag( z )\nz = out.get( 2 )\nre = real( z )\nim = imag( z )\n","Complex128Array.prototype.toString":"var arr = new Complex128Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\nvar str = arr.toString()\n","Complex128Array.prototype.values":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar it = arr.values();\nvar v = it.next().value\nvar re = real( v )\nvar im = imag( v )\nv = it.next().value\nre = real( v )\nim = imag( v )\nvar bool = it.next().done\n","Complex128Array.prototype.with":"var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\nvar out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\nvar z = out.get( 1 )\nvar re = real( z )\nvar im = imag( z )\n","complexarray":"var arr = complexarray()\narr = complexarray( 'complex64' )\nvar arr = complexarray( 5 )\narr = complexarray( 5, 'complex64' )\nvar arr1 = complexarray( [ 0.5, 0.5, 0.5, 0.5 ] );\nvar arr2 = complexarray( arr1, 'complex64' )\nvar arr1 = [ 0.5, 0.5, 0.5, 0.5 ];\nvar arr2 = complexarray( arr1, 'complex64' )\nvar buf = new ArrayBuffer( 64 );\nvar arr = complexarray( buf, 0, 8, 'complex64' )\n","complexarrayCtors":"var ctor = complexarrayCtors( 'complex64' )\nctor = complexarrayCtors( 'float32' )\n","complexarrayDataTypes":"var out = complexarrayDataTypes()\n","complexCtors":"var ctor = complexCtors( 'complex128' )\nctor = complexCtors( 'complex' )\n","complexDataType":"var v = new Complex128( 1.0, 2.0 );\nvar dt = complexDataType( v )\ndt = complexDataType( 'beep' )\n","complexDataTypes":"var out = complexDataTypes()\n","complexPromotionRules":"var out = complexPromotionRules( 'complex128', 'complex64' )\n","compose":"function a( x ) {\nreturn 2 * x;\n }\nfunction b( x ) {\nreturn x + 3;\n }\nfunction c( x ) {\nreturn x / 5;\n }\nvar f = compose( c, b, a );\nvar z = f( 6 )\n","composeAsync":"function a( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n    next( null, 2*x );\n}\n };\nfunction b( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n    next( null, x+3 );\n}\n };\nfunction c( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n    next( null, x/5 );\n}\n };\nvar f = composeAsync( c, b, a );\nfunction done( error, result ) {\nif ( error ) {\n    throw error;\n}\nconsole.log( result );\n };\nf( 6, done )\n","configdir":"var dir = configdir()\ndir = configdir( 'appname/config' )\n","conj":"var z = new Complex128( 5.0, 3.0 );\nz.toString()\nvar v = conj( z );\nv.toString()\n","conjf":"var z = new Complex64( 5.0, 3.0 );\nz.toString()\nvar v = conjf( z );\nv.toString()\n","constantcase":"var out = constantcase( 'Hello World!' )\nout = constantcase( 'I am a tiny little teapot' )\n","constantFunction":"var fcn = constantFunction( 3.14 );\nvar v = fcn()\nv = fcn()\nv = fcn()\n","constantStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = constantStream( 'beep', opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","constantStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = constantStream.factory( opts );\n","constantStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = constantStream.objectMode( 3.14, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","constructorName":"var v = constructorName( 'a' )\nv = constructorName( {} )\nv = constructorName( true )\n","contains":"var bool = contains( 'Hello World', 'World' )\nbool = contains( 'Hello World', 'world' )\nbool = contains( [ 1, 2, 3, 4 ], 2 )\nbool = contains( [ NaN, 2, 3, 4 ], NaN )\nbool = contains( 'Hello World', 'Hello', 6 )\nbool = contains( [ true, NaN, false ], true, 1 )\n","convertArray":"var arr = [ 1.0, 2.0, 3.0, 4.0 ];\nvar out = convertArray( arr, 'float32' )\n","convertArraySame":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = new Float32Array( 0 );\nvar out = convertArraySame( x, y )\n","convertPath":"var out = convertPath( '/c/foo/bar/beep.c', 'win32' )\nout = convertPath( '/c/foo/bar/beep.c', 'mixed' )\nout = convertPath( '/c/foo/bar/beep.c', 'posix' )\nout = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'win32' )\nout = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'mixed' )\nout = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'posix' )\n","copy":"var value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\nvar out = copy( value )\nvar bool = ( value[ 0 ].c === out[ 0 ].c )\nvalue = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\nout = copy( value, 1 );\nbool = ( value[ 0 ] === out[ 0 ] )\nbool = ( value[ 0 ].c === out[ 0 ].c )\n","copyBuffer":"var b1 = array2buffer( [ 1, 2, 3, 4 ] );\nvar b2 = copyBuffer( b1 )\n","countBy":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n     return 'b';\n }\n return 'other';\n };\nvar collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar out = countBy( collection, indicator )\n","countByAsync":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\ncountByAsync( arr, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\ncountByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\ncountByAsync( arr, opts, indicator, done )\n","countByAsync.factory":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nvar opts = { 'series': true };\nvar f = countByAsync.factory( opts, indicator );\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000, 500 ];\nf( arr, done )\n","currentYear":"var y = currentYear()\n","curry":"function add( x, y ) { return x + y; };\nvar f = curry( add );\nvar sum = f( 2 )( 3 )\nfunction add() { return arguments[ 0 ] + arguments[ 1 ]; };\nf = curry( add, 2 );\nsum = f( 2 )( 3 )\nvar obj = {\n 'name': 'Ada',\n 'greet': function greet( word1, word2 ) {\n    return word1 + ' ' + word2 + ', ' + this.name + '!'\n }\n };\nf = curry( obj.greet, obj );\nvar str = f( 'Hello' )( 'there' )\n","curryRight":"function add( x, y ) { return x + y; };\nvar f = curryRight( add );\nvar sum = f( 2 )( 3 )\nfunction add() { return arguments[ 0 ] + arguments[ 1 ]; };\nf = curryRight( add, 2 );\nsum = f( 2 )( 3 )\nvar obj = {\n 'name': 'Ada',\n 'greet': function greet( word1, word2 ) {\n     return word1 + ' ' + word2 + ', ' + this.name + '!'\n }\n };\nf = curryRight( obj.greet, obj );\nvar str = f( 'there' )( 'Hello' )\n","cwd":"var dir = cwd()\n","DALE_CHALL_NEW":"var list = DALE_CHALL_NEW()\n","datasets":"var out = datasets( 'MONTH_NAMES_EN' )\nvar opts = { 'data': 'cities' };\nout = datasets( 'MINARD_NAPOLEONS_MARCH', opts )\n","DataView":"var buf = new ArrayBuffer( 5 )\nvar dv = new DataView( buf )\n","DataView.prototype.buffer":"var buf1 = new ArrayBuffer( 5 );\nvar dv = new DataView( buf1 );\nvar buf2 = dv.buffer\nvar b = ( buf1 === buf2 )\n","DataView.prototype.byteLength":"var buf = new ArrayBuffer( 5 );\nvar dv = new DataView( buf );\ndv.byteLength\n","DataView.prototype.byteOffset":"var buf = new ArrayBuffer( 5 );\nvar dv = new DataView( buf, 2 );\ndv.byteLength\ndv.byteOffset\n","datespace":"var stop = '2014-12-02T07:00:54.973Z';\nvar start = new Date( stop ) - 60000;\nvar arr = datespace( start, stop, 6 )\nvar opts = { 'round': 'ceil' };\narr = datespace( 1417503655000, 1417503655001, 3, opts )\n","dayOfQuarter":"var day = dayOfQuarter()\nday = dayOfQuarter( new Date() )\nday = dayOfQuarter( 12, 31, 2017 )\nday = dayOfQuarter( 'dec', 31, 2017 )\nday = dayOfQuarter( 'december', 31, 2017 )\n","dayOfYear":"var day = dayOfYear()\nday = dayOfYear( new Date() )\nday = dayOfYear( 12, 31, 2016 )\nday = dayOfYear( 'dec', 31, 2016 )\nday = dayOfYear( 'december', 31, 2016 )\n","daysInMonth":"var num = daysInMonth()\nnum = daysInMonth( 2 )\nnum = daysInMonth( 2, 2016 )\nnum = daysInMonth( 2, 2017 )\nnum = daysInMonth( 'feb', 2016 )\nnum = daysInMonth( 'february', 2016 )\n","daysInYear":"var num = daysInYear()\nnum = daysInYear( 2016 )\nnum = daysInYear( 2017 )\n","ddot":"var xbuf = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar x = array( xbuf );\nvar ybuf = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar y = array( ybuf );\nvar z = ddot( x, y )\nz.get()\n","debugSinkStream":"var s = debugSinkStream( { 'name': 'foo' } );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","debugSinkStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = debugSinkStream.factory( opts );\n","debugSinkStream.objectMode":"var s = debugSinkStream.objectMode( { 'name': 'foo' } );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","debugStream":"var s = debugStream( { 'name': 'foo' } );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","debugStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = debugStream.factory( opts );\n","debugStream.objectMode":"var s = debugStream.objectMode( { 'name': 'foo' } );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","decorateAfter":"function f( v ) { return -v; };\nvar fcn = decorateAfter( base.abs, 1, f );\nvar v = fcn( -5 )\nv = fcn( 5 )\n","decorateAfter.factory":"function f( v ) { return -v; };\nvar fcn = decorateAfter.factory( base.abs, 1, f );\nvar v = fcn( -5 )\nv = fcn( 5 )\n","deepEqual":"var bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, 3 ] )\nbool = deepEqual( [ 1, 2, 3 ], [ 1, 2, '3' ] )\nbool = deepEqual( { 'a': 2 }, { 'a': [ 2 ] } )\n","deepGet":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar val = deepGet( obj, 'a.b.c' )\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar val = deepGet( obj, 'a/b/c', { 'sep': '/' } )\n","deepGet.factory":"var dget = deepGet.factory( 'a/b/c', { 'sep': '/' } );\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar val = dget( obj )\n","deepHasOwnProp":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = deepHasOwnProp( obj, 'a.b.c' )\nobj = { 'a': { 'b': { 'c': 'd' } } };\nbool = deepHasOwnProp( obj, 'a/b/c', { 'sep': '/' } )\n","deepHasOwnProp.factory":"var has = deepHasOwnProp.factory( 'a/b/c', { 'sep': '/' } );\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = has( obj )\n","deepHasProp":"function Foo() { return this; };\nFoo.prototype.b = { 'c': 'd' };\nvar obj = { 'a': new Foo() };\nvar bool = deepHasProp( obj, 'a.b.c' )\nbool = deepHasProp( obj, 'a/b/c', { 'sep': '/' } )\n","deepHasProp.factory":"function Foo() { return this; };\nFoo.prototype.b = { 'c': 'd' };\nvar has = deepHasProp.factory( 'a/b/c', { 'sep': '/' } );\nvar obj = { 'a': new Foo() };\nvar bool = has( obj )\n","deepPluck":"var arr = [\n { 'a': { 'b': { 'c': 1 } } },\n { 'a': { 'b': { 'c': 2 } } }\n ];\nvar out = deepPluck( arr, 'a.b.c' )\narr = [\n { 'a': [ 0, 1, 2 ] },\n { 'a': [ 3, 4, 5 ] }\n ];\nout = deepPluck( arr, [ 'a', 1 ] )\n","deepSet":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = deepSet( obj, 'a.b.c', 'beep' )\nobj = { 'a': { 'b': { 'c': 'd' } } };\nbool = deepSet( obj, 'a/b/c', 'beep', { 'sep': '/' } );\nobj\nbool = deepSet( obj, 'a.e.c', 'boop', { 'create': true } );\nobj\n","deepSet.factory":"var dset = deepSet.factory( 'a/b/c', {\n 'create': true,\n 'sep': '/'\n });\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar bool = dset( obj, 'beep' )\nobj\n","defineMemoizedProperty":"var obj = {};\nfunction foo() {\n return 'bar';\n };\ndefineMemoizedProperty( obj, 'foo', {\n 'configurable': false,\n 'enumerable': true,\n 'writable': false,\n 'value': foo\n });\nobj.foo\n","defineProperties":"var obj = {};\ndefineProperties( obj, {\n 'foo': {\n     'value': 'bar',\n     'writable': false,\n     'configurable': false,\n     'enumerable': true\n },\n 'baz': {\n     'value': 13\n }\n });\nobj.foo\nobj.baz\n","defineProperty":"var obj = {};\ndefineProperty( obj, 'foo', {\n 'value': 'bar',\n 'enumerable': true,\n 'writable': false\n });\nobj.foo = 'boop';\nobj\n","dirname":"var dir = dirname( './foo/bar/index.js' )\n","dotcase":"var out = dotcase( 'Hello World!' )\nout = dotcase( 'beep boop' )\n","DoublyLinkedList":"var list = DoublyLinkedList();\nlist.push( 'foo' ).push( 'bar' );\nlist.length\nlist.pop()\nlist.length\nlist.pop()\nlist.length\n","doUntil":"function predicate( i ) { return ( i >= 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\ndoUntil( beep, predicate )\n","doUntilAsync":"function fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n     next( null, 'boop'+i );\n }\n };\nfunction predicate( i, clbk ) { clbk( null, i >= 5 ); };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\ndoUntilAsync( fcn, predicate, done )\n","doUntilEach":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\ndoUntilEach( arr, logger, predicate )\n","doUntilEachRight":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\ndoUntilEachRight( arr, logger, predicate )\n","doWhile":"function predicate( i ) { return ( i < 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\ndoWhile( beep, predicate )\n","doWhileAsync":"function fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n     next( null, 'boop'+i );\n }\n };\nfunction predicate( i, clbk ) { clbk( null, i < 5 ); };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\ndoWhileAsync( fcn, predicate, done )\n","doWhileEach":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\ndoWhileEach( arr, logger, predicate )\n","doWhileEachRight":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\ndoWhileEachRight( arr, logger, predicate )\n","dswap":"var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\ndswap( x, y );\nx.data\ny.data\n","E":"E\n","EMOJI":"var data = EMOJI()\n","EMOJI_CODE_PICTO":"var out = EMOJI_CODE_PICTO()\n","EMOJI_PICTO_CODE":"var out = EMOJI_PICTO_CODE()\n","emptyStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar s = emptyStream();\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","emptyStream.factory":"var opts = { 'objectMode': true };\nvar createStream = emptyStream.factory( opts );\n","emptyStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar s = emptyStream.objectMode();\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","endsWith":"var bool = endsWith( 'beep', 'ep' )\nbool = endsWith( 'Beep', 'op' )\nbool = endsWith( 'Beep', 'ee', 3 )\nbool = endsWith( 'Beep', 'ee', -1 )\nbool = endsWith( 'beep', '' )\n","enumerableProperties":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar props = enumerableProperties( obj )\n","enumerablePropertiesIn":"var props = enumerablePropertiesIn( [] )\n","enumerablePropertySymbols":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = enumerablePropertySymbols( obj )\n","enumerablePropertySymbolsIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = enumerablePropertySymbolsIn( obj )\n","ENV":"var user = ENV.USER\n","EPS":"EPS\n","error2json":"var err = new Error( 'beep' );\nvar json = error2json( err )\n","EULERGAMMA":"EULERGAMMA\n","every":"var arr = [ 1, 1, 1, 1, 1 ];\nvar bool = every( arr )\n","everyBy":"function positive( v ) { return ( v > 0 ); };\nvar arr = [ 1, 2, 3, 4 ];\nvar bool = everyBy( arr, positive )\n","everyByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\neveryByAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\neveryByAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\neveryByAsync( arr, opts, predicate, done )\n","everyByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, true );\n }\n };\nvar opts = { 'series': true };\nvar f = everyByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","everyByRight":"function positive( v ) { return ( v > 0 ); };\nvar arr = [ 1, 2, 3, 4 ];\nvar bool = everyByRight( arr, positive )\n","everyByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\neveryByRightAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\neveryByRightAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, true );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\neveryByRightAsync( arr, opts, predicate, done )\n","everyByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, true );\n }\n };\nvar opts = { 'series': true };\nvar f = everyByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","everyInBy":"function positive( v ) { return ( v > 0 ); };\nvar o = {a: 1, b: 2, c: 3};\nvar bool = everyInBy( o, positive )\n","everyOwnBy":"function positive( v ) { return ( v > 0 ); };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nvar bool = everyOwnBy( obj, positive )\n","evil":"var v = evil( '5*4*3*2*1' )\n","EXEC_PATH":"EXEC_PATH\n","exists":"function done( error, bool ) { console.log( bool ); };\nexists( './beep/boop', done );\n","exists.sync":"var bool = exists.sync( './beep/boop' )\n","expandAcronyms":"var str = 'LOL, this is fun. I am ROFL.';\nvar out = expandAcronyms( str )\nstr = 'brb, I need to check my mail. thx!';\nout = expandAcronyms( str )\n","expandContractions":"var str = 'I won\\'t be able to get y\\'all out of this one.';\nvar out = expandContractions( str )\nstr = 'It oughtn\\'t to be my fault, because, you know, I didn\\'t know';\nout = expandContractions( str )\n","extname":"var ext = extname( 'index.js' )\n","FancyArray":"var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\nvar d = [ 2, 2 ]; // shape\nvar s = [ 2, 1 ]; // strides\nvar o = 0; // index offset\nvar arr = FancyArray( 'generic', b, d, s, o, 'row-major' )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","FancyArray.prototype.byteLength":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.byteLength\n","FancyArray.prototype.BYTES_PER_ELEMENT":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.BYTES_PER_ELEMENT\n","FancyArray.prototype.data":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar buf = arr.data\n","FancyArray.prototype.dtype":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar dt = arr.dtype\n","FancyArray.prototype.flags":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar fl = arr.flags\n","FancyArray.prototype.length":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar len = arr.length\n","FancyArray.prototype.ndims":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar n = arr.ndims\n","FancyArray.prototype.offset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.offset\n","FancyArray.prototype.order":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar ord = arr.order\n","FancyArray.prototype.shape":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar sh = arr.shape\n","FancyArray.prototype.strides":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar st = arr.strides\n","FancyArray.prototype.get":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.get( 1, 1 )\n","FancyArray.prototype.iget":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.iget( 3 )\n","FancyArray.prototype.set":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\narr.set( 1, 1, -4.0 );\narr.get( 1, 1 )\n","FancyArray.prototype.iset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\narr.iset( 3, -4.0 );\narr.iget( 3 )\n","FancyArray.prototype.toString":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\narr.toString()\n","FancyArray.prototype.toJSON":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\narr.toJSON()\n","fastmath.abs":"var v = fastmath.abs( -1.0 )\nv = fastmath.abs( 2.0 )\nv = fastmath.abs( 0.0 )\nv = fastmath.abs( -0.0 )\nv = fastmath.abs( NaN )\n","fastmath.acosh":"var v = fastmath.acosh( 1.0 )\nv = fastmath.acosh( 2.0 )\nv = fastmath.acosh( NaN )\nv = fastmath.acosh( 1.0e308 )\n","fastmath.ampbm":"var h = fastmath.ampbm( 5.0, 12.0 )\n","fastmath.ampbm.factory":"var hypot = fastmath.ampbm.factory( 1.0, 0.5 )\n","fastmath.asinh":"var v = fastmath.asinh( 0.0 )\nv = fastmath.asinh( 2.0 )\nv = fastmath.asinh( -2.0 )\nv = fastmath.asinh( NaN )\nv = fastmath.asinh( 1.0e200 )\nv = fastmath.asinh( 1.0e-50 )\n","fastmath.atanh":"var v = fastmath.atanh( 0.0 )\nv = fastmath.atanh( 0.9 )\nv = fastmath.atanh( 1.0 )\nv = fastmath.atanh( -1.0 )\nv = fastmath.atanh( NaN )\nv = fastmath.atanh( 1.0e-17 )\n","fastmath.hypot":"var h = fastmath.hypot( -5.0, 12.0 )\nh = fastmath.hypot( 1.0e154, 1.0e154 )\nh = fastmath.hypot( 1e-200, 1.0e-200 )\n","fastmath.log2Uint32":"var v = fastmath.log2Uint32( 4 >>> 0 )\nv = fastmath.log2Uint32( 8 >>> 0 )\nv = fastmath.log2Uint32( 9 >>> 0 )\n","fastmath.max":"var v = fastmath.max( 3.14, 4.2 )\nv = fastmath.max( 3.14, NaN )\nv = fastmath.max( NaN, 3.14 )\nv = fastmath.max( -0.0, +0.0 )\nv = fastmath.max( +0.0, -0.0 )\n","fastmath.min":"var v = fastmath.min( 3.14, 4.2 )\nv = fastmath.min( 3.14, NaN )\nv = fastmath.min( NaN, 3.14 )\nv = fastmath.min( -0.0, +0.0 )\nv = fastmath.min( +0.0, -0.0 )\n","fastmath.powint":"var v = fastmath.powint( 2.0, 3 )\nv = fastmath.powint( 3.14, 0 )\nv = fastmath.powint( 2.0, -2 )\nv = fastmath.powint( 0.0, 0 )\nv = fastmath.powint( -3.14, 1 )\nv = fastmath.powint( NaN, 0 )\n","fastmath.sqrtUint32":"var v = fastmath.sqrtUint32( 9 >>> 0 )\nv = fastmath.sqrtUint32( 2 >>> 0 )\nv = fastmath.sqrtUint32( 3 >>> 0 )\nv = fastmath.sqrtUint32( 0 >>> 0 )\n","FEMALE_FIRST_NAMES_EN":"var list = FEMALE_FIRST_NAMES_EN()\n","FIFO":"var q = FIFO();\nq.push( 'foo' ).push( 'bar' );\nq.length\nq.pop()\nq.length\nq.pop()\nq.length\n","filledarray":"var arr = filledarray()\narr = filledarray( 'float32' )\nvar arr = filledarray( 1.0, 5 )\narr = filledarray( 1, 5, 'int32' )\nvar arr1 = filledarray( 2.0, [ 0.5, 0.5, 0.5 ] )\nvar arr2 = filledarray( 1.0, arr1, 'float32' )\nvar arr1 = iterConstant( 3.0, {'iter': 3} );\nvar arr2 = filledarray( 1.0, arr1, 'float32' )\nvar buf = new ArrayBuffer( 16 );\nvar arr = filledarray( 1.0, buf, 0, 4, 'float32' )\n","filledarrayBy":"var arr = filledarrayBy()\narr = filledarrayBy( 'float32' )\nfunction clbk() { return 1.0; };\nvar arr = filledarrayBy( 5, clbk )\narr = filledarrayBy( 5, 'int32', clbk )\nvar arr1 = filledarrayBy( [ 0.5, 0.5, 0.5 ], constantFunction( 2.0 ) )\nvar arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\nvar arr1 = iterConstant( 3.0, {'iter': 3} );\nvar arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\nvar buf = new ArrayBuffer( 16 );\nvar arr = filledarrayBy( buf, 0, 4, 'float32', constantFunction( 1.0 ) )\n","filterArguments":"function foo( a, b ) { return [ a, b ]; };\nfunction predicate( v ) { return ( v !== 2 ); };\nvar bar = filterArguments( foo, predicate );\nvar out = bar( 1, 2, 3 )\n","find":"var data = [ 30, 20, 50, 60, 10 ];\nfunction condition( val ) { return val > 20; };\nvar vals = find( data, condition )\ndata = [ 30, 20, 50, 60, 10 ];\nvar opts = { 'k': 2, 'returns': 'values' };\nvals = find( data, opts, condition )\ndata = [ 30, 20, 50, 60, 10 ];\nopts = { 'k': -2, 'returns': '*' };\nvals = find( data, opts, condition )\n","firstChar":"var out = firstChar( 'beep' )\nout = firstChar( 'Boop', 1 )\nout = firstChar( 'foo bar', 5 )\n","FIVETHIRTYEIGHT_FFQ":"var data = FIVETHIRTYEIGHT_FFQ()\n","flattenArray":"var arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\nvar out = flattenArray( arr )\narr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\nout = flattenArray( arr, { 'depth': 2 } )\nvar bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\narr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\nout = flattenArray( arr, { 'depth': 2, 'copy': true } )\nbool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n","flattenArray.factory":"var flatten = flattenArray.factory( [ 2, 2 ], {\n 'copy': false\n });\nvar out = flatten( [ [ 1, 2 ], [ 3, 4 ] ] )\nout = flatten( [ [ 5, 6 ], [ 7, 8 ] ] )\n","flattenObject":"var obj = { 'a': { 'b': { 'c': 'd' } } };\nvar out = flattenObject( obj )\nobj = { 'a': { 'b': { 'c': 'd' } } };\nout = flattenObject( obj, { 'depth': 1 } )\nvar bool = ( obj.a.b === out[ 'a.b' ] )\nobj = { 'a': { 'b': { 'c': 'd' } } };\nout = flattenObject( obj, { 'delimiter': '-|-' } )\nobj = { 'a': { 'b': [ 1, 2, 3 ] } };\nout = flattenObject( obj, { 'flattenArrays': true } )\n","flattenObject.factory":"var flatten = flattenObject.factory({\n 'depth': 1,\n 'copy': true,\n 'delimiter': '|'\n });\nvar obj = { 'a': { 'b': { 'c': 'd' } } };\nvar out = flatten( obj )\n","flignerTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = flignerTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = flignerTest( arr, { 'groups': groups } )\n","FLOAT_WORD_ORDER":"FLOAT_WORD_ORDER\n","FLOAT16_CBRT_EPS":"FLOAT16_CBRT_EPS\n","FLOAT16_EPS":"FLOAT16_EPS\n","FLOAT16_EXPONENT_BIAS":"FLOAT16_EXPONENT_BIAS\n","FLOAT16_MAX":"FLOAT16_MAX\n","FLOAT16_MAX_SAFE_INTEGER":"FLOAT16_MAX_SAFE_INTEGER\n","FLOAT16_MIN_SAFE_INTEGER":"FLOAT16_MIN_SAFE_INTEGER\n","FLOAT16_NINF":"FLOAT16_NINF\n","FLOAT16_NUM_BYTES":"FLOAT16_NUM_BYTES\n","FLOAT16_PINF":"FLOAT16_PINF\n","FLOAT16_PRECISION":"FLOAT16_PRECISION\n","FLOAT16_SMALLEST_NORMAL":"FLOAT16_SMALLEST_NORMAL\n","FLOAT16_SMALLEST_SUBNORMAL":"FLOAT16_SMALLEST_SUBNORMAL\n","FLOAT16_SQRT_EPS":"FLOAT16_SQRT_EPS\n","FLOAT32_ABS_MASK":"FLOAT32_ABS_MASK\nbase.toBinaryStringUint32( FLOAT32_ABS_MASK )\n","FLOAT32_CBRT_EPS":"FLOAT32_CBRT_EPS\n","FLOAT32_E":"FLOAT32_E\n","FLOAT32_EPS":"FLOAT32_EPS\n","FLOAT32_EXPONENT_BIAS":"FLOAT32_EXPONENT_BIAS\n","FLOAT32_EXPONENT_MASK":"FLOAT32_EXPONENT_MASK\nbase.toBinaryStringUint32( FLOAT32_EXPONENT_MASK )\n","FLOAT32_FOURTH_PI":"FLOAT32_FOURTH_PI\n","FLOAT32_HALF_LN_TWO":"FLOAT32_HALF_LN_TWO\n","FLOAT32_HALF_PI":"FLOAT32_HALF_PI\n","FLOAT32_LN_HALF":"FLOAT32_LN_HALF\n","FLOAT32_LN_PI":"FLOAT32_LN_PI\n","FLOAT32_LN_TEN":"FLOAT32_LN_TEN\n","FLOAT32_LN_TWO":"FLOAT32_LN_TWO\n","FLOAT32_MAX":"FLOAT32_MAX\n","FLOAT32_MAX_BASE2_EXPONENT":"FLOAT32_MAX_BASE2_EXPONENT\n","FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL":"FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL\n","FLOAT32_MAX_BASE10_EXPONENT":"FLOAT32_MAX_BASE10_EXPONENT\n","FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL":"FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL\n","FLOAT32_MAX_SAFE_FIBONACCI":"FLOAT32_MAX_SAFE_FIBONACCI\n","FLOAT32_MAX_SAFE_INTEGER":"FLOAT32_MAX_SAFE_INTEGER\n","FLOAT32_MAX_SAFE_NTH_FACTORIAL":"FLOAT32_MAX_SAFE_NTH_FACTORIAL\n","FLOAT32_MAX_SAFE_NTH_FIBONACCI":"FLOAT32_MAX_SAFE_NTH_FIBONACCI\n","FLOAT32_MAX_SAFE_NTH_LUCAS":"FLOAT32_MAX_SAFE_NTH_LUCAS\n","FLOAT32_MIN_BASE2_EXPONENT":"FLOAT32_MIN_BASE2_EXPONENT\n","FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL":"FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT32_MIN_BASE10_EXPONENT":"FLOAT32_MIN_BASE10_EXPONENT\n","FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL":"FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT32_MIN_SAFE_INTEGER":"FLOAT32_MIN_SAFE_INTEGER\n","FLOAT32_NAN":"FLOAT32_NAN\n","FLOAT32_NINF":"FLOAT32_NINF\n","FLOAT32_NUM_BYTES":"FLOAT32_NUM_BYTES\n","FLOAT32_PHI":"FLOAT32_PHI\n","FLOAT32_PI":"FLOAT32_PI\n","FLOAT32_PINF":"FLOAT32_PINF\n","FLOAT32_PRECISION":"FLOAT32_PRECISION\n","FLOAT32_SIGN_MASK":"FLOAT32_SIGN_MASK\nbase.toBinaryStringUint32( FLOAT32_SIGN_MASK )\n","FLOAT32_SIGNIFICAND_MASK":"FLOAT32_SIGNIFICAND_MASK\nbase.toBinaryStringUint32( FLOAT32_SIGNIFICAND_MASK )\n","FLOAT32_SMALLEST_NORMAL":"FLOAT32_SMALLEST_NORMAL\n","FLOAT32_SMALLEST_SUBNORMAL":"FLOAT32_SMALLEST_SUBNORMAL\n","FLOAT32_SQRT_EPS":"FLOAT32_SQRT_EPS\n","FLOAT32_SQRT_HALF":"FLOAT32_SQRT_HALF\n","FLOAT32_SQRT_HALF_PI":"FLOAT32_SQRT_HALF_PI\n","FLOAT32_SQRT_PHI":"FLOAT32_SQRT_PHI\n","FLOAT32_SQRT_PI":"FLOAT32_SQRT_PI\n","FLOAT32_SQRT_THREE":"FLOAT32_SQRT_THREE\n","FLOAT32_SQRT_TWO":"FLOAT32_SQRT_TWO\n","FLOAT32_SQRT_TWO_PI":"FLOAT32_SQRT_TWO_PI\n","FLOAT32_TWO_PI":"FLOAT32_TWO_PI\n","Float32Array":"var arr = new Float32Array()\nvar arr = new Float32Array( 5 )\nvar arr1 = new Float64Array( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = new Float32Array( arr1 )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = new Float32Array( arr1 )\nvar buf = new ArrayBuffer( 16 );\nvar arr = new Float32Array( buf, 0, 4 )\n","Float32Array.from":"function mapFcn( v ) { return v * 2.0; };\nvar arr = Float32Array.from( [ 1.0, -1.0 ], mapFcn )\n","Float32Array.of":"var arr = Float32Array.of( 2.0, -2.0 )\n","Float32Array.BYTES_PER_ELEMENT":"Float32Array.BYTES_PER_ELEMENT\n","Float32Array.name":"Float32Array.name\n","Float32Array.prototype.buffer":"var arr = new Float32Array( 5 );\narr.buffer\n","Float32Array.prototype.byteLength":"var arr = new Float32Array( 5 );\narr.byteLength\n","Float32Array.prototype.byteOffset":"var arr = new Float32Array( 5 );\narr.byteOffset\n","Float32Array.prototype.BYTES_PER_ELEMENT":"var arr = new Float32Array( 5 );\narr.BYTES_PER_ELEMENT\n","Float32Array.prototype.length":"var arr = new Float32Array( 5 );\narr.length\n","Float32Array.prototype.copyWithin":"var arr = new Float32Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Float32Array.prototype.entries":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Float32Array.prototype.every":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\narr.every( predicate )\n","Float32Array.prototype.fill":"var arr = new Float32Array( [ 1.0, -1.0 ] );\narr.fill( 2.0 );\narr[ 0 ]\narr[ 1 ]\n","Float32Array.prototype.filter":"var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Float32Array.prototype.find":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar v = arr.find( predicate )\n","Float32Array.prototype.findIndex":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar idx = arr.findIndex( predicate )\n","Float32Array.prototype.forEach":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Float32Array.prototype.includes":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar bool = arr.includes( 2.0 )\nbool = arr.includes( -1.0 )\n","Float32Array.prototype.indexOf":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar idx = arr.indexOf( 2.0 )\nidx = arr.indexOf( -1.0 )\n","Float32Array.prototype.join":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\narr.join( '|' )\n","Float32Array.prototype.keys":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Float32Array.prototype.lastIndexOf":"var arr = new Float32Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\nvar idx = arr.lastIndexOf( 2.0 )\nidx = arr.lastIndexOf( 0.0 )\n","Float32Array.prototype.map":"var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( v ) { return v * 2.0; };\nvar arr2 = arr1.map( fcn )\n","Float32Array.prototype.reduce":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0.0 )\n","Float32Array.prototype.reduceRight":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0.0 )\n","Float32Array.prototype.reverse":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] )\narr.reverse()\n","Float32Array.prototype.set":"var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\narr.set( [ -2.0, 2.0 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Float32Array.prototype.slice":"var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Float32Array.prototype.some":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\narr.some( predicate )\n","Float32Array.prototype.sort":"var arr = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\narr.sort()\n","Float32Array.prototype.subarray":"var arr1 = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\nvar arr2 = arr1.subarray( 2 )\n","Float32Array.prototype.toLocaleString":"var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\narr.toLocaleString()\n","Float32Array.prototype.toString":"var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\narr.toString()\n","Float32Array.prototype.values":"var arr = new Float32Array( [ 1.0, -1.0 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","FLOAT64_EXPONENT_BIAS":"FLOAT64_EXPONENT_BIAS\n","FLOAT64_HIGH_WORD_ABS_MASK":"FLOAT64_HIGH_WORD_ABS_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_ABS_MASK )\n","FLOAT64_HIGH_WORD_EXPONENT_MASK":"FLOAT64_HIGH_WORD_EXPONENT_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_EXPONENT_MASK )\n","FLOAT64_HIGH_WORD_SIGN_MASK":"FLOAT64_HIGH_WORD_SIGN_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGN_MASK )\n","FLOAT64_HIGH_WORD_SIGNIFICAND_MASK":"FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\nbase.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGNIFICAND_MASK )\n","FLOAT64_MAX":"FLOAT64_MAX\n","FLOAT64_MAX_BASE2_EXPONENT":"FLOAT64_MAX_BASE2_EXPONENT\n","FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL":"FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_BASE10_EXPONENT":"FLOAT64_MAX_BASE10_EXPONENT\n","FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL":"FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_LN":"FLOAT64_MAX_LN\n","FLOAT64_MAX_SAFE_FIBONACCI":"FLOAT64_MAX_SAFE_FIBONACCI\n","FLOAT64_MAX_SAFE_INTEGER":"FLOAT64_MAX_SAFE_INTEGER\n","FLOAT64_MAX_SAFE_LUCAS":"FLOAT64_MAX_SAFE_LUCAS\n","FLOAT64_MAX_SAFE_NTH_FIBONACCI":"FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT64_MAX_SAFE_NTH_LUCAS":"FLOAT64_MAX_SAFE_NTH_LUCAS\n","FLOAT64_MIN_BASE2_EXPONENT":"FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL":"FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_BASE10_EXPONENT":"FLOAT64_MIN_BASE10_EXPONENT\n","FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL":"FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_LN":"FLOAT64_MIN_LN\n","FLOAT64_MIN_SAFE_INTEGER":"FLOAT64_MIN_SAFE_INTEGER\n","FLOAT64_NUM_BYTES":"FLOAT64_NUM_BYTES\n","FLOAT64_PRECISION":"FLOAT64_PRECISION\n","FLOAT64_SMALLEST_NORMAL":"FLOAT64_SMALLEST_NORMAL\n","FLOAT64_SMALLEST_SUBNORMAL":"FLOAT64_SMALLEST_SUBNORMAL\n","Float64Array":"var arr = new Float64Array()\nvar arr = new Float64Array( 5 )\nvar arr1 = new Float32Array( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = new Float64Array( arr1 )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = new Float64Array( arr1 )\nvar buf = new ArrayBuffer( 32 );\nvar arr = new Float64Array( buf, 0, 4 )\n","Float64Array.from":"function mapFcn( v ) { return v * 2.0; };\nvar arr = Float64Array.from( [ 1.0, -1.0 ], mapFcn )\n","Float64Array.of":"var arr = Float64Array.of( 2.0, -2.0 )\n","Float64Array.BYTES_PER_ELEMENT":"Float64Array.BYTES_PER_ELEMENT\n","Float64Array.name":"Float64Array.name\n","Float64Array.prototype.buffer":"var arr = new Float64Array( 5 );\narr.buffer\n","Float64Array.prototype.byteLength":"var arr = new Float64Array( 5 );\narr.byteLength\n","Float64Array.prototype.byteOffset":"var arr = new Float64Array( 5 );\narr.byteOffset\n","Float64Array.prototype.BYTES_PER_ELEMENT":"var arr = new Float64Array( 5 );\narr.BYTES_PER_ELEMENT\n","Float64Array.prototype.length":"var arr = new Float64Array( 5 );\narr.length\n","Float64Array.prototype.copyWithin":"var arr = new Float64Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Float64Array.prototype.entries":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Float64Array.prototype.every":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\narr.every( predicate )\n","Float64Array.prototype.fill":"var arr = new Float64Array( [ 1.0, -1.0 ] );\narr.fill( 2.0 );\narr[ 0 ]\narr[ 1 ]\n","Float64Array.prototype.filter":"var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v >= 0.0 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Float64Array.prototype.find":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar v = arr.find( predicate )\n","Float64Array.prototype.findIndex":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\nvar idx = arr.findIndex( predicate )\n","Float64Array.prototype.forEach":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Float64Array.prototype.includes":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar bool = arr.includes( 2.0 )\nbool = arr.includes( -1.0 )\n","Float64Array.prototype.indexOf":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar idx = arr.indexOf( 2.0 )\nidx = arr.indexOf( -1.0 )\n","Float64Array.prototype.join":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\narr.join( '|' )\n","Float64Array.prototype.keys":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Float64Array.prototype.lastIndexOf":"var arr = new Float64Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\nvar idx = arr.lastIndexOf( 2.0 )\nidx = arr.lastIndexOf( 0.0 )\n","Float64Array.prototype.map":"var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( v ) { return v * 2.0; };\nvar arr2 = arr1.map( fcn )\n","Float64Array.prototype.reduce":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0.0 )\n","Float64Array.prototype.reduceRight":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0.0 )\n","Float64Array.prototype.reverse":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] )\narr.reverse()\n","Float64Array.prototype.set":"var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\narr.set( [ -2.0, 2.0 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Float64Array.prototype.slice":"var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Float64Array.prototype.some":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nfunction predicate( v ) { return ( v < 0.0 ); };\narr.some( predicate )\n","Float64Array.prototype.sort":"var arr = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\narr.sort()\n","Float64Array.prototype.subarray":"var arr1 = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\nvar arr2 = arr1.subarray( 2 )\n","Float64Array.prototype.toLocaleString":"var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\narr.toLocaleString()\n","Float64Array.prototype.toString":"var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\narr.toString()\n","Float64Array.prototype.values":"var arr = new Float64Array( [ 1.0, -1.0 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","forEach":"function logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4 ];\nforEach( arr, logger )\n","forEachAsync":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n     throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 3000, 2500, 1000 ];\nforEachAsync( arr, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n     throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nforEachAsync( arr, opts, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n     throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nforEachAsync( arr, opts, onDuration, done )\n","forEachAsync.factory":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next();\n }\n };\nvar opts = { 'series': true };\nvar f = forEachAsync.factory( opts, onDuration );\nfunction done( error ) {\n if ( error ) {\n     throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","forEachChar":"var n = 0;\nfunction fcn() { n += 1; };\nforEachChar( 'hello world!', fcn );\nn\n","forEachRight":"function logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4 ];\nforEachRight( arr, logger )\n","forEachRightAsync":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n     throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 1000, 2500, 3000 ];\nforEachRightAsync( arr, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n     throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nforEachRightAsync( arr, opts, onDuration, done )\nfunction onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next();\n }\n };\nfunction done( error ) {\n if ( error ) {\n     throw error;\n }\n console.log( 'Done.' );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nforEachRightAsync( arr, opts, onDuration, done )\n","forEachRightAsync.factory":"function onDuration( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next();\n }\n };\nvar opts = { 'series': true };\nvar f = forEachRightAsync.factory( opts, onDuration );\nfunction done( error ) {\n if ( error ) {\n     throw error;\n }\n console.log( 'Done.' );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","forIn":"function logger( v, k ) { console.log( '%s: %d', k, v ); };\nfunction Foo() { return this; };\nFoo.prototype.beep = 'boop';\nvar obj = new Foo();\nforIn( obj, logger )\n","format":"var out = format( 'Hello, %s!', 'World' )\nout = format( '%s %s', 'Hello', 'World' )\nout = format( 'Pi: %.2f', PI )\n","forOwn":"function logger( v, k ) { console.log( '%s: %d', k, v ); };\nvar obj = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\nforOwn( obj, logger )\n","FOURTH_PI":"FOURTH_PI\n","FOURTH_ROOT_EPS":"FOURTH_ROOT_EPS\n","FRB_SF_WAGE_RIGIDITY":"var data = FRB_SF_WAGE_RIGIDITY()\n","fromCodePoint":"var out = fromCodePoint( 9731 )\nout = fromCodePoint( [ 9731 ] )\nout = fromCodePoint( 97, 98, 99 )\nout = fromCodePoint( [ 97, 98, 99 ] )\n","Function":"var f = new Function( 'x', 'y', 'return x + y' );\nf( 1, 2 )\n","Function.prototype.apply":"var f = new Function( 'x', 'y', 'return x + y' );\nf.apply( null, [ 1, 2 ] )\n","Function.prototype.call":"var f = new Function( 'x', 'y', 'return x + y' );\nf.call( null, 1, 2 )\n","Function.prototype.bind":"var f = new Function( 'x', 'y', 'return x + y' );\nvar g = f.bind( null, 1 );\ng( 2 )\n","Function.prototype.toString":"var f = new Function( 'x', 'y', 'return x + y' );\nf.toString()\n","Function.prototype.length":"var f = new Function( 'x', 'y', 'return x + y' );\nf.length\n","Function.prototype.name":"var f = new Function( 'x', 'y', 'return x + y' );\nf.name\nvar f = new Function( 'x', 'y', 'return x + y' );\nf.name = 'add';\nf.name\n","Function.prototype.prototype":"var f = new Function( 'x', 'y', 'return x + y' );\nf.prototype\n","function2string":"function2string( base.erf )\n","functionName":"var v = functionName( String )\nv = functionName( function foo(){} )\nv = functionName( function(){} )\n","functionSequence":"function a( x ) { return 2 * x; };\nfunction b( x ) { return x + 3; };\nfunction c( x ) { return x / 5; };\nvar f = functionSequence( a, b, c );\nvar z = f( 6 )\n","functionSequenceAsync":"function a( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n    next( null, 2*x );\n}\n };\nfunction b( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n    next( null, x+3 );\n}\n };\nfunction c( x, next ) {\nsetTimeout( onTimeout, 0 );\nfunction onTimeout() {\n    next( null, x/5 );\n}\n };\nvar f = functionSequenceAsync( a, b, c );\nfunction done( error, result ) {\nif ( error ) {\n    throw error;\n}\nconsole.log( result );\n };\nf( 6, done )\n","GAMMA_LANCZOS_G":"GAMMA_LANCZOS_G\n","gdot":"var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\ngdot( x, y )\nx = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\ny = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\ngdot( x, y )\n","getegid":"var gid = getegid()\n","geteuid":"var uid = geteuid()\n","getgid":"var gid = getgid()\n","getGlobal":"var g = getGlobal()\n","getPrototypeOf":"var proto = getPrototypeOf( {} )\n","getuid":"var uid = getuid()\n","GLAISHER":"GLAISHER\n","graphemeClusters2iterator":"var it = graphemeClusters2iterator( '🌷🍕' );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","graphemeClusters2iteratorRight":"var it = graphemeClusters2iteratorRight( '🌷🍕' );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","group":"var collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar groups = [ 'b', 'b', 'f', 'b' ];\nvar out = group( collection, groups )\ngroups = [ 1, 1, 2, 1 ];\nout = group( collection, groups )\ngroups = [ 'b', 'b', 'f', 'b' ];\nvar opts = { 'returns': 'indices' };\nout = group( collection, opts, groups )\nopts = { 'returns': '*' };\nout = group( collection, opts, groups )\n","groupBy":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n     return 'b';\n }\n return 'other';\n };\nvar collection = [ 'beep', 'boop', 'foo', 'bar' ];\nvar out = groupBy( collection, indicator )\nvar opts = { 'returns': 'indices' };\nout = groupBy( collection, opts, indicator )\nopts = { 'returns': '*' };\nout = groupBy( collection, opts, indicator )\n","groupByAsync":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\ngroupByAsync( arr, indicator, done )\nvar opts = { 'returns': 'indices' };\ngroupByAsync( arr, opts, indicator, done )\nopts = { 'returns': '*' };\ngroupByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\ngroupByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\ngroupByAsync( arr, opts, indicator, done )\n","groupByAsync.factory":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) );\n }\n };\nvar opts = { 'series': true };\nvar f = groupByAsync.factory( opts, indicator );\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","groupIn":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n     return 'b';\n }\n return 'other';\n };\nfunction Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\nFoo.prototype = Object.create( null );\nFoo.prototype.c = 'foo';\nFoo.prototype.d = 'bar';\nvar obj = new Foo();\nvar out = groupIn( obj, indicator )\nvar opts = { 'returns': 'keys' };\nout = groupIn( obj, opts, indicator )\nopts = { 'returns': '*' };\nout = groupIn( obj, opts, indicator )\n","groupOwn":"function indicator( v ) {\n if ( v[ 0 ] === 'b' ) {\n     return 'b';\n }\n return 'other';\n };\nvar obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\nvar out = groupOwn( obj, indicator )\nvar opts = { 'returns': 'keys' };\nout = groupOwn( obj, opts, indicator )\nopts = { 'returns': '*' };\nout = groupOwn( obj, opts, indicator )\n","gswap":"var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\ngswap( x, y );\nx.data\ny.data\nx = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\ny = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\ngswap( x, y );\nx\ny\n","HALF_LN2":"HALF_LN2\n","HALF_PI":"HALF_PI\n","HARRISON_BOSTON_HOUSE_PRICES":"var data = HARRISON_BOSTON_HOUSE_PRICES()\n","HARRISON_BOSTON_HOUSE_PRICES_CORRECTED":"var data = HARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n","hasArrayBufferSupport":"var bool = hasArrayBufferSupport()\n","hasArrowFunctionSupport":"var bool = hasArrowFunctionSupport()\n","hasAsyncAwaitSupport":"var bool = hasAsyncAwaitSupport()\n","hasAsyncIteratorSymbolSupport":"var bool = hasAsyncIteratorSymbolSupport()\n","hasAtobSupport":"var bool = hasAtobSupport()\n","hasBigInt64ArraySupport":"var bool = hasBigInt64ArraySupport()\n","hasBigIntSupport":"var bool = hasBigIntSupport()\n","hasBigUint64ArraySupport":"var bool = hasBigUint64ArraySupport()\n","hasBtoaSupport":"var bool = hasBtoaSupport()\n","hasClassSupport":"var bool = hasClassSupport()\n","hasDataViewSupport":"var bool = hasDataViewSupport()\n","hasDefinePropertiesSupport":"var bool = hasDefinePropertiesSupport()\n","hasDefinePropertySupport":"var bool = hasDefinePropertySupport()\n","hasFloat32ArraySupport":"var bool = hasFloat32ArraySupport()\n","hasFloat64ArraySupport":"var bool = hasFloat64ArraySupport()\n","hasFunctionNameSupport":"var bool = hasFunctionNameSupport()\n","hasGeneratorSupport":"var bool = hasGeneratorSupport()\n","hasGlobalThisSupport":"var bool = hasGlobalThisSupport()\n","hasInt8ArraySupport":"var bool = hasInt8ArraySupport()\n","hasInt16ArraySupport":"var bool = hasInt16ArraySupport()\n","hasInt32ArraySupport":"var bool = hasInt32ArraySupport()\n","hasIteratorSymbolSupport":"var bool = hasIteratorSymbolSupport()\n","hasMapSupport":"var bool = hasMapSupport()\n","hasNodeBufferSupport":"var bool = hasNodeBufferSupport()\n","hasOwnProp":"var beep = { 'boop': true };\nvar bool = hasOwnProp( beep, 'boop' )\nbool = hasOwnProp( beep, 'bop' )\n","hasProp":"var beep = { 'boop': true };\nvar bool = hasProp( beep, 'boop' )\nbool = hasProp( beep, 'toString' )\nbool = hasProp( beep, 'bop' )\n","hasProxySupport":"var bool = hasProxySupport()\n","hasSetSupport":"var bool = hasSetSupport()\n","hasSharedArrayBufferSupport":"var bool = hasSharedArrayBufferSupport()\n","hasSymbolSupport":"var bool = hasSymbolSupport()\n","hasToStringTagSupport":"var bool = hasToStringTagSupport()\n","hasUint8ArraySupport":"var bool = hasUint8ArraySupport()\n","hasUint8ClampedArraySupport":"var bool = hasUint8ClampedArraySupport()\n","hasUint16ArraySupport":"var bool = hasUint16ArraySupport()\n","hasUint32ArraySupport":"var bool = hasUint32ArraySupport()\n","hasUTF16SurrogatePairAt":"var out = hasUTF16SurrogatePairAt( '🌷', 0 )\nout = hasUTF16SurrogatePairAt( '🌷', 1 )\n","hasWeakMapSupport":"var bool = hasWeakMapSupport()\n","hasWeakSetSupport":"var bool = hasWeakSetSupport()\n","hasWebAssemblySupport":"var bool = hasWebAssemblySupport()\n","headercase":"var out = headercase( 'Hello World!' )\nout = headercase( 'beep boop' )\n","HERNDON_VENUS_SEMIDIAMETERS":"var d = HERNDON_VENUS_SEMIDIAMETERS()\n","homedir":"var home = homedir()\n","HOURS_IN_DAY":"var days = 3.14;\nvar hrs = days * HOURS_IN_DAY\n","HOURS_IN_WEEK":"var wks = 3.14;\nvar hrs = wks * HOURS_IN_WEEK\n","hoursInMonth":"var num = hoursInMonth()\nnum = hoursInMonth( 2 )\nnum = hoursInMonth( 2, 2016 )\nnum = hoursInMonth( 2, 2017 )\nnum = hoursInMonth( 'feb', 2016 )\nnum = hoursInMonth( 'february', 2016 )\n","hoursInYear":"var num = hoursInYear()\nnum = hoursInYear( 2016 )\nnum = hoursInYear( 2017 )\n","httpServer":"var createServer = httpServer()\nfunction onRequest( request, response ) {\nconsole.log( request.url );\nresponse.end( 'OK' );\n };\ncreateServer = httpServer( onRequest )\nvar opts = { 'port': 7331 };\ncreateServer = httpServer( opts )\n","identity":"var v = identity( 3.14 )\n","ifelse":"var z = ifelse( true, 1.0, -1.0 )\nz = ifelse( false, 1.0, -1.0 )\n","ifelseAsync":"function predicate( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n     clbk( null, true );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nifelseAsync( predicate, 'beep', 'boop', done )\n","ifthen":"function x() { return 1.0; };\nfunction y() { return -1.0; };\nvar z = ifthen( true, x, y )\nz = ifthen( false, x, y )\n","ifthenAsync":"function predicate( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n     clbk( null, false );\n }\n };\nfunction x( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n     clbk( null, 'beep' );\n }\n };\nfunction y( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n     clbk( null, 'boop' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nifthenAsync( predicate, x, y, done )\n","imag":"var z = new Complex128( 5.0, 3.0 );\nvar im = imag( z )\n","imagf":"var z = new Complex64( 5.0, 3.0 );\nvar im = imagf( z )\n","IMG_ACANTHUS_MOLLIS":"var img = IMG_ACANTHUS_MOLLIS()\n","IMG_AIRPLANE_FROM_ABOVE":"var img = IMG_AIRPLANE_FROM_ABOVE()\n","IMG_ALLIUM_OREOPHILUM":"var img = IMG_ALLIUM_OREOPHILUM()\n","IMG_BLACK_CANYON":"var img = IMG_BLACK_CANYON()\n","IMG_DUST_BOWL_HOME":"var img = IMG_DUST_BOWL_HOME()\n","IMG_FRENCH_ALPINE_LANDSCAPE":"var img = IMG_FRENCH_ALPINE_LANDSCAPE()\n","IMG_LOCOMOTION_HOUSE_CAT":"var img = IMG_LOCOMOTION_HOUSE_CAT()\n","IMG_LOCOMOTION_NUDE_MALE":"var img = IMG_LOCOMOTION_NUDE_MALE()\n","IMG_MARCH_PASTORAL":"var img = IMG_MARCH_PASTORAL()\n","IMG_NAGASAKI_BOATS":"var img = IMG_NAGASAKI_BOATS()\n","incrapcorr":"var accumulator = incrapcorr();\nvar ar = accumulator()\nar = accumulator( 2.0, 1.0 )\nar = accumulator( -5.0, 3.14 )\nar = accumulator()\n","incrBinaryClassification":"var opts = {};\nopts.intercept = true;\nopts.lambda = 1.0e-5;\nvar acc = incrBinaryClassification( 3, opts );\nvar buf = new Float64Array( [ 2.3, 1.0, 5.0 ] );\nvar x = array( buf );\nvar coefs = acc( x, 1 )\nbuf = new Float64Array( [ 2.3, 5.3, 8.6 ] );\nx = array( buf );\nvar yhat = acc.predict( x )\n","incrcount":"var accumulator = incrcount();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrcovariance":"var accumulator = incrcovariance();\nvar v = accumulator()\nv = accumulator( 2.0, 1.0 )\nv = accumulator( -5.0, 3.14 )\nv = accumulator()\n","incrcovmat":"var accumulator = incrcovmat( 2 );\nvar out = accumulator()\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v )\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v )\nout = accumulator()\n","incrcv":"var accumulator = incrcv();\nvar cv = accumulator()\ncv = accumulator( 2.0 )\ncv = accumulator( 1.0 )\ncv = accumulator()\n","increwmean":"var accumulator = increwmean( 0.5 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","increwstdev":"var accumulator = increwstdev( 0.5 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","increwvariance":"var accumulator = increwvariance( 0.5 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrgmean":"var accumulator = incrgmean();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrgrubbs":"var acc = incrgrubbs();\nvar res = acc()\nfor ( var i = 0; i < 200; i++ ) {\n res = acc( base.random.normal( 10.0, 5.0 ) );\n };\nres.print()\n","incrhmean":"var accumulator = incrhmean();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrkmeans":"var accumulator = incrkmeans( 5, 2 );\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v );\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v );\n","incrkurtosis":"var accumulator = incrkurtosis();\nvar v = accumulator( 2.0 )\nv = accumulator( 2.0 )\nv = accumulator( -4.0 )\nv = accumulator( -4.0 )\n","incrmaape":"var accumulator = incrmaape();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator()\n","incrmae":"var accumulator = incrmae();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator()\n","incrmapcorr":"var accumulator = incrmapcorr( 3 );\nvar ar = accumulator()\nar = accumulator( 2.0, 1.0 )\nar = accumulator( -5.0, 3.14 )\nar = accumulator( 3.0, -1.0 )\nar = accumulator( 5.0, -9.5 )\nar = accumulator()\n","incrmape":"var accumulator = incrmape();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator()\n","incrmax":"var accumulator = incrmax();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrmaxabs":"var accumulator = incrmaxabs();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrmcovariance":"var accumulator = incrmcovariance( 3 );\nvar v = accumulator()\nv = accumulator( 2.0, 1.0 )\nv = accumulator( -5.0, 3.14 )\nv = accumulator( 3.0, -1.0 )\nv = accumulator( 5.0, -9.5 )\nv = accumulator()\n","incrmcv":"var accumulator = incrmcv( 3 );\nvar cv = accumulator()\ncv = accumulator( 2.0 )\ncv = accumulator( 1.0 )\ncv = accumulator( 3.0 )\ncv = accumulator( 7.0 )\ncv = accumulator()\n","incrmda":"var accumulator = incrmda();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 4.0 )\nm = accumulator()\n","incrme":"var accumulator = incrme();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator()\n","incrmean":"var accumulator = incrmean();\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator()\n","incrmeanabs":"var accumulator = incrmeanabs();\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator()\n","incrmeanabs2":"var accumulator = incrmeanabs2();\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator()\n","incrmeanstdev":"var accumulator = incrmeanstdev();\nvar ms = accumulator()\nms = accumulator( 2.0 )\nms = accumulator( -5.0 )\nms = accumulator( 3.0 )\nms = accumulator( 5.0 )\nms = accumulator()\n","incrmeanvar":"var accumulator = incrmeanvar();\nvar mv = accumulator()\nmv = accumulator( 2.0 )\nmv = accumulator( -5.0 )\nmv = accumulator( 3.0 )\nmv = accumulator( 5.0 )\nmv = accumulator()\n","incrmgmean":"var accumulator = incrmgmean( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmgrubbs":"var acc = incrmgrubbs( 20 );\nvar res = acc()\nfor ( var i = 0; i < 200; i++ ) {\n res = acc( base.random.normal( 10.0, 5.0 ) );\n };\nres.print()\n","incrmhmean":"var accumulator = incrmhmean( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( 5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmidrange":"var accumulator = incrmidrange();\nvar v = accumulator()\nv = accumulator( 3.14 )\nv = accumulator( -5.0 )\nv = accumulator( 10.1 )\nv = accumulator()\n","incrmin":"var accumulator = incrmin();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrminabs":"var accumulator = incrminabs();\nvar m = accumulator()\nm = accumulator( 3.14 )\nm = accumulator( -5.0 )\nm = accumulator( 10.1 )\nm = accumulator()\n","incrminmax":"var accumulator = incrminmax();\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrminmaxabs":"var accumulator = incrminmaxabs();\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrmmaape":"var accumulator = incrmmaape( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 2.0, 5.0 )\nm = accumulator()\n","incrmmae":"var accumulator = incrmmae( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 5.0, -2.0 )\nm = accumulator()\n","incrmmape":"var accumulator = incrmmape( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 2.0, 5.0 )\nm = accumulator()\n","incrmmax":"var accumulator = incrmmax( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmmaxabs":"var accumulator = incrmmaxabs( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmmda":"var accumulator = incrmmda( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 4.0, 5.0 )\nm = accumulator()\n","incrmme":"var accumulator = incrmme( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 5.0, -2.0 )\nm = accumulator()\n","incrmmean":"var accumulator = incrmmean( 3 );\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator( 3.0 )\nmu = accumulator( 5.0 )\nmu = accumulator()\n","incrmmeanabs":"var accumulator = incrmmeanabs( 3 );\nvar mu = accumulator()\nmu = accumulator( 2.0 )\nmu = accumulator( -5.0 )\nmu = accumulator( 3.0 )\nmu = accumulator( 5.0 )\nmu = accumulator()\n","incrmmeanabs2":"var accumulator = incrmmeanabs2( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmmeanstdev":"var accumulator = incrmmeanstdev( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmmeanvar":"var accumulator = incrmmeanvar( 3 );\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator( 3.0 )\nv = accumulator( 5.0 )\nv = accumulator()\n","incrmmidrange":"var accumulator = incrmmidrange( 3 );\nvar mr = accumulator()\nmr = accumulator( 2.0 )\nmr = accumulator( -5.0 )\nmr = accumulator( 3.0 )\nmr = accumulator( 5.0 )\nmr = accumulator()\n","incrmmin":"var accumulator = incrmmin( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmminabs":"var accumulator = incrmminabs( 3 );\nvar m = accumulator()\nm = accumulator( 2.0 )\nm = accumulator( -5.0 )\nm = accumulator( 3.0 )\nm = accumulator( 5.0 )\nm = accumulator()\n","incrmminmax":"var accumulator = incrmminmax( 3 );\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrmminmaxabs":"var accumulator = incrmminmaxabs( 3 );\nvar mm = accumulator()\nmm = accumulator( 2.0 )\nmm = accumulator( -5.0 )\nmm = accumulator( 3.0 )\nmm = accumulator( 5.0 )\nmm = accumulator()\n","incrmmpe":"var accumulator = incrmmpe( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 2.0, 5.0 )\nm = accumulator()\n","incrmmse":"var accumulator = incrmmse( 3 );\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator( 3.0, 2.0 )\nm = accumulator( 5.0, -2.0 )\nm = accumulator()\n","incrmpcorr":"var accumulator = incrmpcorr( 3 );\nvar r = accumulator()\nr = accumulator( 2.0, 1.0 )\nr = accumulator( -5.0, 3.14 )\nr = accumulator( 3.0, -1.0 )\nr = accumulator( 5.0, -9.5 )\nr = accumulator()\n","incrmpcorr2":"var accumulator = incrmpcorr2( 3 );\nvar r2 = accumulator()\nr2 = accumulator( 2.0, 1.0 )\nr2 = accumulator( -5.0, 3.14 )\nr2 = accumulator( 3.0, -1.0 )\nr2 = accumulator( 5.0, -9.5 )\nr2 = accumulator()\n","incrmpcorrdist":"var accumulator = incrmpcorrdist( 3 );\nvar d = accumulator()\nd = accumulator( 2.0, 1.0 )\nd = accumulator( -5.0, 3.14 )\nd = accumulator( 3.0, -1.0 )\nd = accumulator( 5.0, -9.5 )\nd = accumulator()\n","incrmpe":"var accumulator = incrmpe();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( 5.0, 2.0 )\nm = accumulator()\n","incrmprod":"var accumulator = incrmprod( 3 );\nvar p = accumulator()\np = accumulator( 2.0 )\np = accumulator( -5.0 )\np = accumulator( 3.0 )\np = accumulator( 5.0 )\np = accumulator()\n","incrmrange":"var accumulator = incrmrange( 3 );\nvar r = accumulator()\nr = accumulator( 2.0 )\nr = accumulator( -5.0 )\nr = accumulator( 3.0 )\nr = accumulator( 5.0 )\nr = accumulator()\n","incrmrmse":"var accumulator = incrmrmse( 3 );\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator( 3.0, 2.0 )\nr = accumulator( 5.0, -2.0 )\nr = accumulator()\n","incrmrss":"var accumulator = incrmrss( 3 );\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator( 3.0, 2.0 )\nr = accumulator( 5.0, -2.0 )\nr = accumulator()\n","incrmse":"var accumulator = incrmse();\nvar m = accumulator()\nm = accumulator( 2.0, 3.0 )\nm = accumulator( -5.0, 2.0 )\nm = accumulator()\n","incrmstdev":"var accumulator = incrmstdev( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( 5.0 )\ns = accumulator()\n","incrmsum":"var accumulator = incrmsum( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( 5.0 )\ns = accumulator()\n","incrmsumabs":"var accumulator = incrmsumabs( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrmsumabs2":"var accumulator = incrmsumabs2( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator( 3.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrmsummary":"var accumulator = incrmsummary( 3 );\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrmsumprod":"var accumulator = incrmsumprod( 3 );\nvar s = accumulator()\ns = accumulator( 2.0, 3.0 )\ns = accumulator( -5.0, 2.0 )\ns = accumulator( 3.0, -2.0 )\ns = accumulator( 5.0, 3.0 )\ns = accumulator()\n","incrmvariance":"var accumulator = incrmvariance( 3 );\nvar s2 = accumulator()\ns2 = accumulator( 2.0 )\ns2 = accumulator( -5.0 )\ns2 = accumulator( 3.0 )\ns2 = accumulator( 5.0 )\ns2 = accumulator()\n","incrmvmr":"var accumulator = incrmvmr( 3 );\nvar F = accumulator()\nF = accumulator( 2.0 )\nF = accumulator( 1.0 )\nF = accumulator( 3.0 )\nF = accumulator( 7.0 )\nF = accumulator()\n","incrnancount":"var accumulator = incrnancount();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrnansum":"var accumulator = incrnansum();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( NaN )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrnansumabs":"var accumulator = incrnansumabs();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( NaN )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrnansumabs2":"var accumulator = incrnansumabs2();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( NaN )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrpcorr":"var accumulator = incrpcorr();\nvar r = accumulator()\nr = accumulator( 2.0, 1.0 )\nr = accumulator( -5.0, 3.14 )\nr = accumulator()\n","incrpcorr2":"var accumulator = incrpcorr2();\nvar r2 = accumulator()\nr2 = accumulator( 2.0, 1.0 )\nr2 = accumulator( -5.0, 3.14 )\nr2 = accumulator()\n","incrpcorrdist":"var accumulator = incrpcorrdist();\nvar d = accumulator()\nd = accumulator( 2.0, 1.0 )\nd = accumulator( -5.0, 3.14 )\nd = accumulator()\n","incrpcorrdistmat":"var accumulator = incrpcorrdistmat( 2 );\nvar out = accumulator()\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v )\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v )\nout = accumulator()\n","incrpcorrmat":"var accumulator = incrpcorrmat( 2 );\nvar out = accumulator()\nvar buf = new Float64Array( 2 );\nvar shape = [ 2 ];\nvar strides = [ 1 ];\nvar v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\nv.set( 0, 2.0 );\nv.set( 1, 1.0 );\nout = accumulator( v )\nv.set( 0, -5.0 );\nv.set( 1, 3.14 );\nout = accumulator( v )\nout = accumulator()\n","incrprod":"var accumulator = incrprod();\nvar v = accumulator()\nv = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator()\n","incrrange":"var accumulator = incrrange();\nvar v = accumulator()\nv = accumulator( -2.0 )\nv = accumulator( 1.0 )\nv = accumulator( 3.0 )\nv = accumulator()\n","incrrmse":"var accumulator = incrrmse();\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator()\n","incrrss":"var accumulator = incrrss();\nvar r = accumulator()\nr = accumulator( 2.0, 3.0 )\nr = accumulator( -5.0, 2.0 )\nr = accumulator()\n","incrskewness":"var accumulator = incrskewness();\nvar v = accumulator( 2.0 )\nv = accumulator( -5.0 )\nv = accumulator( -10.0 )\nv = accumulator()\n","incrspace":"var arr = incrspace( 0, 11, 2 )\n","incrstdev":"var accumulator = incrstdev();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsum":"var accumulator = incrsum();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsumabs":"var accumulator = incrsumabs();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsumabs2":"var accumulator = incrsumabs2();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsummary":"var accumulator = incrsummary();\nvar s = accumulator()\ns = accumulator( 2.0 )\ns = accumulator( -5.0 )\ns = accumulator()\n","incrsumprod":"var accumulator = incrsumprod();\nvar s = accumulator()\ns = accumulator( 2.0, 3.0 )\ns = accumulator( -5.0, 2.0 )\ns = accumulator()\n","incrvariance":"var accumulator = incrvariance();\nvar s2 = accumulator()\ns2 = accumulator( 2.0 )\ns2 = accumulator( -5.0 )\ns2 = accumulator()\n","incrvmr":"var accumulator = incrvmr();\nvar D = accumulator()\nD = accumulator( 2.0 )\nD = accumulator( 1.0 )\nD = accumulator()\n","incrwmean":"var accumulator = incrwmean();\nvar mu = accumulator()\nmu = accumulator( 2.0, 1.0 )\nmu = accumulator( 2.0, 0.5 )\nmu = accumulator( 3.0, 1.5 )\nmu = accumulator()\n","ind2sub":"var d = [ 3, 3, 3 ];\nvar s = ind2sub( d, 17 )\n","ind2sub.assign":"var d = [ 3, 3, 3 ];\nvar out = [ 0, 0, 0 ];\nvar s = ind2sub.assign( d, 17, out )\nvar bool = ( s === out )\n","indexOf":"var arr = [ 4, 3, 2, 1 ];\nvar idx = indexOf( arr, 3 )\narr = [ 4, 3, 2, 1 ];\nidx = indexOf( arr, 5 )\narr = [ 1, 2, 3, 4, 5, 2, 6 ];\nidx = indexOf( arr, 2, 3 )\narr = [ 1, 2, 3, 4, 2, 5 ];\nidx = indexOf( arr, 2, 10 )\narr = [ 1, 2, 3, 4, 5, 2, 6, 2 ];\nidx = indexOf( arr, 2, -4 )\nidx = indexOf( arr, 2, -1 )\narr = [ 1, 2, 3, 4, 5, 2, 6 ];\nidx = indexOf( arr, 2, -10 )\nvar str = 'bebop';\nidx = indexOf( str, 'o' )\n","inherit":"function Foo() { return this; };\nFoo.prototype.beep = function beep() { return 'boop'; };\nfunction Bar() { Foo.call( this ); return this; };\ninherit( Bar, Foo );\nvar bar = new Bar();\nvar v = bar.beep()\n","inheritedEnumerableProperties":"var props = inheritedEnumerableProperties( {} )\n","inheritedEnumerablePropertySymbols":"var symbols = inheritedEnumerablePropertySymbols( [] )\n","inheritedKeys":"var keys = inheritedKeys( {} )\n","inheritedNonEnumerableProperties":"var props = inheritedNonEnumerableProperties( {} )\n","inheritedNonEnumerablePropertyNames":"var keys = inheritedNonEnumerablePropertyNames( {} )\n","inheritedNonEnumerablePropertySymbols":"var symbols = inheritedNonEnumerablePropertySymbols( [] )\n","inheritedProperties":"var symbols = inheritedProperties( [] )\n","inheritedPropertyDescriptor":"var desc = inheritedPropertyDescriptor( {}, 'toString' )\n","inheritedPropertyDescriptors":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar desc = inheritedPropertyDescriptors( obj )\n","inheritedPropertyNames":"var keys = inheritedPropertyNames( [] )\n","inheritedPropertySymbols":"var symbols = inheritedPropertySymbols( [] )\n","inheritedWritableProperties":"var props = inheritedWritableProperties( {} )\n","inheritedWritablePropertyNames":"var keys = inheritedWritablePropertyNames( {} )\n","inheritedWritablePropertySymbols":"var symbols = inheritedWritablePropertySymbols( [] )\n","inmap":"function foo( v, i ) { return v * i; };\nvar arr = [ 1.0, 2.0, 3.0 ];\nvar out = inmap( arr, foo )\nvar bool = ( out === arr )\n","inmapAsync":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n     throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 3000, 2500, 1000 ];\ninmapAsync( arr, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n     throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\ninmapAsync( arr, opts, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n     throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\ninmapAsync( arr, opts, fcn, done )\n","inmapAsync.factory":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, value*index );\n }\n };\nvar opts = { 'series': true };\nvar f = inmapAsync.factory( opts, fcn );\nfunction done( error, collection ) {\n if ( error ) {\n     throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","inmapRight":"function foo( v, i ) { console.log( '%s: %d', i, v ); return v * i; };\nvar arr = [ 1.0, 2.0, 3.0 ];\nvar out = inmapRight( arr, foo )\nvar bool = ( out === arr )\n","inmapRightAsync":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n     throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 1000, 2500, 3000 ];\ninmapRightAsync( arr, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n     throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\ninmapRightAsync( arr, opts, fcn, done )\nfunction fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, value*index );\n }\n };\nfunction done( error, collection ) {\n if ( error ) {\n     throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\ninmapRightAsync( arr, opts, fcn, done )\n","inmapRightAsync.factory":"function fcn( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, value*index );\n }\n };\nvar opts = { 'series': true };\nvar f = inmapRightAsync.factory( opts, fcn );\nfunction done( error, collection ) {\n if ( error ) {\n     throw error;\n }\n console.log( collection === arr );\n console.log( collection );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","inspectSinkStream":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectSinkStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectSinkStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = inspectSinkStream.factory( opts );\nfunction clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = createStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectSinkStream.objectMode":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectSinkStream.objectMode( clbk );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","inspectStream":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = inspectStream.factory( opts );\nfunction clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = createStream( clbk );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","inspectStream.objectMode":"function clbk( chunk, idx ) { console.log( chunk.toString() ); };\nvar s = inspectStream.objectMode( clbk );\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","instanceOf":"var bool = instanceOf( [], Array )\nbool = instanceOf( {}, Object )\nbool = instanceOf( null, Object )\n","INT8_MAX":"INT8_MAX\n","INT8_MIN":"INT8_MIN\n","INT8_NUM_BYTES":"INT8_NUM_BYTES\n","Int8Array":"var arr = new Int8Array()\nvar arr = new Int8Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Int8Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Int8Array( arr1 )\nvar buf = new ArrayBuffer( 4 );\nvar arr = new Int8Array( buf, 0, 4 )\n","Int8Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Int8Array.from( [ 1, 2 ], mapFcn )\n","Int8Array.of":"var arr = Int8Array.of( 1, 2 )\n","Int8Array.BYTES_PER_ELEMENT":"Int8Array.BYTES_PER_ELEMENT\n","Int8Array.name":"Int8Array.name\n","Int8Array.prototype.buffer":"var arr = new Int8Array( 5 );\narr.buffer\n","Int8Array.prototype.byteLength":"var arr = new Int8Array( 5 );\narr.byteLength\n","Int8Array.prototype.byteOffset":"var arr = new Int8Array( 5 );\narr.byteOffset\n","Int8Array.prototype.BYTES_PER_ELEMENT":"var arr = new Int8Array( 5 );\narr.BYTES_PER_ELEMENT\n","Int8Array.prototype.length":"var arr = new Int8Array( 5 );\narr.length\n","Int8Array.prototype.copyWithin":"var arr = new Int8Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Int8Array.prototype.entries":"var arr = new Int8Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Int8Array.prototype.every":"var arr = new Int8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Int8Array.prototype.fill":"var arr = new Int8Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Int8Array.prototype.filter":"var arr1 = new Int8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Int8Array.prototype.find":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Int8Array.prototype.findIndex":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Int8Array.prototype.forEach":"var arr = new Int8Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Int8Array.prototype.includes":"var arr = new Int8Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Int8Array.prototype.indexOf":"var arr = new Int8Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Int8Array.prototype.join":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Int8Array.prototype.keys":"var arr = new Int8Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Int8Array.prototype.lastIndexOf":"var arr = new Int8Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Int8Array.prototype.map":"var arr1 = new Int8Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Int8Array.prototype.reduce":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Int8Array.prototype.reduceRight":"var arr = new Int8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Int8Array.prototype.reverse":"var arr = new Int8Array( [ 1, 2, 3 ] )\narr.reverse()\n","Int8Array.prototype.set":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Int8Array.prototype.slice":"var arr1 = new Int8Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Int8Array.prototype.some":"var arr = new Int8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Int8Array.prototype.sort":"var arr = new Int8Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Int8Array.prototype.subarray":"var arr1 = new Int8Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Int8Array.prototype.toLocaleString":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Int8Array.prototype.toString":"var arr = new Int8Array( [ 1, 2, 3 ] );\narr.toString()\n","Int8Array.prototype.values":"var arr = new Int8Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","INT16_MAX":"INT16_MAX\n","INT16_MIN":"INT16_MIN\n","INT16_NUM_BYTES":"INT16_NUM_BYTES\n","Int16Array":"var arr = new Int16Array()\nvar arr = new Int16Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Int16Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Int16Array( arr1 )\nvar buf = new ArrayBuffer( 8 );\nvar arr = new Int16Array( buf, 0, 4 )\n","Int16Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Int16Array.from( [ 1, 2 ], mapFcn )\n","Int16Array.of":"var arr = Int16Array.of( 1, 2 )\n","Int16Array.BYTES_PER_ELEMENT":"Int16Array.BYTES_PER_ELEMENT\n","Int16Array.name":"Int16Array.name\n","Int16Array.prototype.buffer":"var arr = new Int16Array( 5 );\narr.buffer\n","Int16Array.prototype.byteLength":"var arr = new Int16Array( 5 );\narr.byteLength\n","Int16Array.prototype.byteOffset":"var arr = new Int16Array( 5 );\narr.byteOffset\n","Int16Array.prototype.BYTES_PER_ELEMENT":"var arr = new Int16Array( 5 );\narr.BYTES_PER_ELEMENT\n","Int16Array.prototype.length":"var arr = new Int16Array( 5 );\narr.length\n","Int16Array.prototype.copyWithin":"var arr = new Int16Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Int16Array.prototype.entries":"var arr = new Int16Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Int16Array.prototype.every":"var arr = new Int16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Int16Array.prototype.fill":"var arr = new Int16Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Int16Array.prototype.filter":"var arr1 = new Int16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Int16Array.prototype.find":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Int16Array.prototype.findIndex":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Int16Array.prototype.forEach":"var arr = new Int16Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Int16Array.prototype.includes":"var arr = new Int16Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Int16Array.prototype.indexOf":"var arr = new Int16Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Int16Array.prototype.join":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Int16Array.prototype.keys":"var arr = new Int16Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Int16Array.prototype.lastIndexOf":"var arr = new Int16Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Int16Array.prototype.map":"var arr1 = new Int16Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Int16Array.prototype.reduce":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Int16Array.prototype.reduceRight":"var arr = new Int16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Int16Array.prototype.reverse":"var arr = new Int16Array( [ 1, 2, 3 ] )\narr.reverse()\n","Int16Array.prototype.set":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Int16Array.prototype.slice":"var arr1 = new Int16Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Int16Array.prototype.some":"var arr = new Int16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Int16Array.prototype.sort":"var arr = new Int16Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Int16Array.prototype.subarray":"var arr1 = new Int16Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Int16Array.prototype.toLocaleString":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Int16Array.prototype.toString":"var arr = new Int16Array( [ 1, 2, 3 ] );\narr.toString()\n","Int16Array.prototype.values":"var arr = new Int16Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","INT32_MAX":"INT32_MAX\n","INT32_MIN":"INT32_MIN\n","INT32_NUM_BYTES":"INT32_NUM_BYTES\n","Int32Array":"var arr = new Int32Array()\nvar arr = new Int32Array( 5 )\nvar arr1 = new Int16Array( [ 5, 5, 5 ] );\nvar arr2 = new Int32Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Int32Array( arr1 )\nvar buf = new ArrayBuffer( 16 );\nvar arr = new Int32Array( buf, 0, 4 )\n","Int32Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Int32Array.from( [ 1, 2 ], mapFcn )\n","Int32Array.of":"var arr = Int32Array.of( 1, 2 )\n","Int32Array.BYTES_PER_ELEMENT":"Int32Array.BYTES_PER_ELEMENT\n","Int32Array.name":"Int32Array.name\n","Int32Array.prototype.buffer":"var arr = new Int32Array( 5 );\narr.buffer\n","Int32Array.prototype.byteLength":"var arr = new Int32Array( 5 );\narr.byteLength\n","Int32Array.prototype.byteOffset":"var arr = new Int32Array( 5 );\narr.byteOffset\n","Int32Array.prototype.BYTES_PER_ELEMENT":"var arr = new Int32Array( 5 );\narr.BYTES_PER_ELEMENT\n","Int32Array.prototype.length":"var arr = new Int32Array( 5 );\narr.length\n","Int32Array.prototype.copyWithin":"var arr = new Int32Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Int32Array.prototype.entries":"var arr = new Int32Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Int32Array.prototype.every":"var arr = new Int32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Int32Array.prototype.fill":"var arr = new Int32Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Int32Array.prototype.filter":"var arr1 = new Int32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Int32Array.prototype.find":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Int32Array.prototype.findIndex":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Int32Array.prototype.forEach":"var arr = new Int32Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Int32Array.prototype.includes":"var arr = new Int32Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Int32Array.prototype.indexOf":"var arr = new Int32Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Int32Array.prototype.join":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Int32Array.prototype.keys":"var arr = new Int32Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Int32Array.prototype.lastIndexOf":"var arr = new Int32Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Int32Array.prototype.map":"var arr1 = new Int32Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Int32Array.prototype.reduce":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Int32Array.prototype.reduceRight":"var arr = new Int32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Int32Array.prototype.reverse":"var arr = new Int32Array( [ 1, 2, 3 ] )\narr.reverse()\n","Int32Array.prototype.set":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Int32Array.prototype.slice":"var arr1 = new Int32Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Int32Array.prototype.some":"var arr = new Int32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Int32Array.prototype.sort":"var arr = new Int32Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Int32Array.prototype.subarray":"var arr1 = new Int32Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Int32Array.prototype.toLocaleString":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Int32Array.prototype.toString":"var arr = new Int32Array( [ 1, 2, 3 ] );\narr.toString()\n","Int32Array.prototype.values":"var arr = new Int32Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","IS_BIG_ENDIAN":"IS_BIG_ENDIAN\n","IS_BROWSER":"IS_BROWSER\n","IS_DARWIN":"IS_DARWIN\n","IS_DOCKER":"IS_DOCKER\n","IS_ELECTRON":"IS_ELECTRON\n","IS_ELECTRON_MAIN":"IS_ELECTRON_MAIN\n","IS_ELECTRON_RENDERER":"IS_ELECTRON_RENDERER\n","IS_LITTLE_ENDIAN":"IS_LITTLE_ENDIAN\n","IS_MOBILE":"IS_MOBILE\n","IS_NODE":"IS_NODE\n","IS_TOUCH_DEVICE":"IS_TOUCH_DEVICE\n","IS_WEB_WORKER":"IS_WEB_WORKER\n","IS_WINDOWS":"IS_WINDOWS\n","isAbsoluteHttpURI":"var bool = isAbsoluteHttpURI( 'http://example.com/' )\nbool = isAbsoluteHttpURI( 'example.com' )\nbool = isAbsoluteHttpURI( 'foo@bar.com' )\n","isAbsolutePath":"var bool = isAbsolutePath( 'C:\\\\foo\\\\bar\\\\baz' )\nbool = isAbsolutePath( '/foo/bar/baz' )\n","isAbsolutePath.posix":"var bool = isAbsolutePath.posix( '/foo/bar/baz' )\nbool = isAbsolutePath.posix( 'foo/bar/baz' )\n","isAbsolutePath.win32":"var bool = isAbsolutePath.win32( 'C:\\\\foo\\\\bar\\\\baz' )\nbool = isAbsolutePath.win32( 'foo\\\\bar\\\\baz' )\n","isAbsoluteURI":"var bool = isAbsoluteURI( 'http://example.com/' )\nbool = isAbsoluteURI( 'example.com' )\nbool = isAbsoluteURI( 'foo@bar.com' )\n","isAccessorArray":"var bool = isAccessorArray( new Complex64Array( 10 ) )\nbool = isAccessorArray( [] )\nbool = isAccessorArray( { 'length': 0 } )\nbool = isAccessorArray( {} )\n","isAccessorProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isAccessorProperty( obj, 'boop' )\nbool = isAccessorProperty( obj, 'beep' )\n","isAccessorPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isAccessorPropertyIn( obj, 'boop' )\nbool = isAccessorPropertyIn( obj, 'beep' )\n","isAlphagram":"var out = isAlphagram( 'beep' )\nout = isAlphagram( 'zba' )\nout = isAlphagram( '' )\n","isAlphaNumeric":"var bool = isAlphaNumeric( 'abc0123456789' )\nbool = isAlphaNumeric( 'abcdef' )\nbool = isAlphaNumeric( '0xff' )\nbool = isAlphaNumeric( '' )\n","isAnagram":"var str1 = 'I am a weakish speller';\nvar str2 = 'William Shakespeare';\nvar bool = isAnagram( str1, str2 )\nbool = isAnagram( 'bat', 'tabba' )\n","isArguments":"function foo() { return arguments; };\nvar bool = isArguments( foo() )\nbool = isArguments( [] )\n","isArray":"var bool = isArray( [] )\nbool = isArray( {} )\n","isArrayArray":"var bool = isArrayArray( [ [], [] ] )\nbool = isArrayArray( [ {}, {} ] )\nbool = isArrayArray( [] )\n","isArrayBuffer":"var bool = isArrayBuffer( new ArrayBuffer( 10 ) )\nbool = isArrayBuffer( [] )\n","isArrayBufferView":"var bool = isArrayBufferView( new Int8Array() )\nbool = isArrayBufferView( [] )\n","isArrayLength":"var bool = isArrayLength( 5 )\nbool = isArrayLength( 2.0e200 )\nbool = isArrayLength( -3.14 )\nbool = isArrayLength( null )\n","isArrayLike":"var bool = isArrayLike( [] )\nbool = isArrayLike( { 'length': 10 } )\nbool = isArrayLike( 'beep' )\nbool = isArrayLike( null )\n","isArrayLikeObject":"var bool = isArrayLikeObject( [] )\nbool = isArrayLikeObject( { 'length': 10 } )\nbool = isArrayLikeObject( 'beep' )\n","isArrowFunction":"function beep() {};\nvar bool = isArrowFunction( beep )\nbool = isArrowFunction( {} )\n","isASCII":"var str = 'beep boop';\nvar bool = isASCII( str )\nbool = isASCII( fromCodePoint( 130 ) )\n","isBetween":"var bool = isBetween( 3.14, 3.0, 4.0 )\nbool = isBetween( 3.0, 3.0, 4.0 )\nbool = isBetween( 4.0, 3.0, 4.0 )\nbool = isBetween( 3.0, 3.14, 4.0 )\nbool = isBetween( 3.14, 3.14, 4.0, 'open', 'closed' )\nbool = isBetween( 3.14, 3.0, 3.14, 'closed', 'open' )\n","isBetweenArray":"var arr = [ 3.0, 3.14, 4.0 ];\nvar bool = isBetweenArray( arr, 3.0, 4.0 )\nbool = isBetweenArray( arr, 3.14, 4.0 )\nbool = isBetweenArray( arr, 3.0, 3.14 )\nbool = isBetweenArray( arr, 3.0, 4.0, 'open', 'closed' )\nbool = isBetweenArray( arr, 3.0, 4.0, 'closed', 'open' )\n","isBigInt":"var bool = isBigInt( BigInt( '1' ) )\nbool = isBigInt( Object( BigInt( '1' ) ) )\nbool = isBigInt( {} )\nbool = isBigInt( null )\nbool = isBigInt( true )\n","isBigInt64Array":"var bool = isBigInt64Array( new BigInt64Array( 10 ) )\nbool = isBigInt64Array( [] )\n","isBigUint64Array":"var bool = isBigUint64Array( new BigUint64Array( 10 ) )\nbool = isBigUint64Array( [] )\n","isBinaryString":"var bool = isBinaryString( '1000101' )\nbool = isBinaryString( 'beep' )\nbool = isBinaryString( '' )\n","isBlankString":"var bool = isBlankString( '   ' )\nbool = isBlankString( 'beep' )\nbool = isBlankString( null )\n","isBoolean":"var bool = isBoolean( false )\nbool = isBoolean( new Boolean( false ) )\n","isBoolean.isPrimitive":"var bool = isBoolean.isPrimitive( true )\nbool = isBoolean.isPrimitive( false )\nbool = isBoolean.isPrimitive( new Boolean( true ) )\n","isBoolean.isObject":"var bool = isBoolean.isObject( true )\nbool = isBoolean.isObject( new Boolean( false ) )\n","isBooleanArray":"var bool = isBooleanArray( [ true, false, true ] )\nbool = isBooleanArray( [ true, 'abc', false ] )\n","isBooleanArray.primitives":"var bool = isBooleanArray.primitives( [ true, false ] )\nbool = isBooleanArray.primitives( [ false, new Boolean( true ) ] )\n","isBooleanArray.objects":"var bool = isBooleanArray.objects( [ new Boolean( false ), true ] )\nbool = isBooleanArray.objects( [ new Boolean( false ), new Boolean( true ) ] )\n","isBoxedPrimitive":"var bool = isBoxedPrimitive( new Boolean( false ) )\nbool = isBoxedPrimitive( true )\n","isBuffer":"var bool = isBuffer( new Buffer( 'beep' ) )\nbool = isBuffer( new Buffer( [ 1, 2, 3, 4 ] ) )\nbool = isBuffer( {} )\nbool = isBuffer( [] )\n","isCamelcase":"var bool = isCamelcase( 'helloWorld' )\nbool = isCamelcase( 'hello world' )\n","isCapitalized":"var bool = isCapitalized( 'Hello' )\nbool = isCapitalized( 'world' )\n","isCentrosymmetricMatrix":"var buf = [ 2, 1, 1, 2 ];\nvar M = ndarray( 'generic', buf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\nvar bool = isCentrosymmetricMatrix( M )\nbool = isCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isCentrosymmetricMatrix( 3.14 )\nbool = isCentrosymmetricMatrix( {} )\n","isCircular":"var obj = { 'beep': 'boop' };\nobj.self = obj;\nvar bool = isCircular( obj )\nbool = isCircular( {} )\nbool = isCircular( null )\n","isCircularArray":"var arr = [ 1, 2, 3 ];\narr.push( arr );\nvar bool = isCircularArray( arr )\nbool = isCircularArray( [] )\nbool = isCircularArray( null )\n","isCircularPlainObject":"var obj = { 'beep': 'boop' };\nobj.self = obj;\nvar bool = isCircularPlainObject( obj )\nbool = isCircularPlainObject( {} )\nbool = isCircularPlainObject( null )\n","isClass":"var bool = isClass( class Person {} )\nbool = isClass( function Person() {} )\nbool = isClass( {} )\nbool = isClass( null )\nbool = isClass( true )\n","isCollection":"var bool = isCollection( [] )\nbool = isCollection( { 'length': 0 } )\nbool = isCollection( {} )\n","isComplex":"var bool = isComplex( new Complex64( 2.0, 2.0 ) )\nbool = isComplex( new Complex128( 3.0, 1.0 ) )\nbool = isComplex( 3.14 )\nbool = isComplex( {} )\n","isComplex64":"var bool = isComplex64( new Complex64( 2.0, 2.0 ) )\nbool = isComplex64( new Complex128( 3.0, 1.0 ) )\nbool = isComplex64( 3.14 )\nbool = isComplex64( {} )\n","isComplex64Array":"var bool = isComplex64Array( new Complex64Array( 10 ) )\nbool = isComplex64Array( [] )\n","isComplex64MatrixLike":"var M = {};\nM.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex64MatrixLike( M )\nbool = isComplex64MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isComplex64MatrixLike( 3.14 )\nbool = isComplex64MatrixLike( {} )\n","isComplex64ndarrayLike":"var M = {};\nM.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex64ndarrayLike( M )\nbool = isComplex64ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isComplex64ndarrayLike( 3.14 )\nbool = isComplex64ndarrayLike( {} )\n","isComplex64VectorLike":"var M = {};\nM.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex64VectorLike( M )\nbool = isComplex64VectorLike( [ 1, 2, 3, 4 ] )\nbool = isComplex64VectorLike( 3.14 )\nbool = isComplex64VectorLike( {} )\n","isComplex128":"var bool = isComplex128( new Complex128( 3.0, 1.0 ) )\nbool = isComplex128( new Complex64( 2.0, 2.0 ) )\nbool = isComplex128( 3.14 )\nbool = isComplex128( {} )\n","isComplex128Array":"var bool = isComplex128Array( new Complex128Array( 10 ) )\nbool = isComplex128Array( [] )\n","isComplex128MatrixLike":"var M = {};\nM.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex128';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex128MatrixLike( M )\nbool = isComplex128MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isComplex128MatrixLike( 3.14 )\nbool = isComplex128MatrixLike( {} )\n","isComplex128ndarrayLike":"var M = {};\nM.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex128';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex128ndarrayLike( M )\nbool = isComplex128ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isComplex128ndarrayLike( 3.14 )\nbool = isComplex128ndarrayLike( {} )\n","isComplex128VectorLike":"var M = {};\nM.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'complex128';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isComplex128VectorLike( M )\nbool = isComplex128VectorLike( [ 1, 2, 3, 4 ] )\nbool = isComplex128VectorLike( 3.14 )\nbool = isComplex128VectorLike( {} )\n","isComplexLike":"var bool = isComplexLike( new Complex64( 2.0, 2.0 ) )\nbool = isComplexLike( new Complex128( 3.0, 1.0 ) )\nbool = isComplexLike( 3.14 )\nbool = isComplexLike( {} )\n","isComplexTypedArray":"var bool = isComplexTypedArray( new Complex64Array( 10 ) )\n","isComplexTypedArrayLike":"var bool = isComplexTypedArrayLike( new Complex128Array() )\nbool = isComplexTypedArrayLike({\n'length': 10,\n'byteOffset': 0,\n'byteLength': 10,\n'BYTES_PER_ELEMENT': 4,\n'get': function get() {},\n'set': function set() {}\n })\n","isComposite":"var bool = isComposite( 4.0 )\nbool = isComposite( new Number( 4.0 ) )\nbool = isComposite( 3.14 )\nbool = isComposite( -4.0 )\nbool = isComposite( null )\n","isComposite.isPrimitive":"var bool = isComposite.isPrimitive( 4.0 )\nbool = isComposite.isPrimitive( new Number( 4.0 ) )\n","isComposite.isObject":"var bool = isComposite.isObject( 4.0 )\nbool = isComposite.isObject( new Number( 4.0 ) )\n","isConfigurableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isConfigurableProperty( obj, 'boop' )\nbool = isConfigurableProperty( obj, 'beep' )\n","isConfigurablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isConfigurablePropertyIn( obj, 'boop' )\nbool = isConfigurablePropertyIn( obj, 'beep' )\n","isConstantcase":"var bool = isConstantcase( 'BEEP_BOOP' )\nbool = isConstantcase( 'BEEP and BOOP' )\n","isCubeNumber":"var bool = isCubeNumber( 8.0 )\nbool = isCubeNumber( new Number( 8.0 ) )\nbool = isCubeNumber( 3.14 )\nbool = isCubeNumber( -5.0 )\nbool = isCubeNumber( null )\n","isCubeNumber.isPrimitive":"var bool = isCubeNumber.isPrimitive( 8.0 )\nbool = isCubeNumber.isPrimitive( new Number( 8.0 ) )\n","isCubeNumber.isObject":"var bool = isCubeNumber.isObject( 8.0 )\nbool = isCubeNumber.isObject( new Number( 8.0 ) )\n","isCurrentYear":"var bool = isCurrentYear( new Date() )\nbool = isCurrentYear( currentYear() )\nbool = isCurrentYear( 2021 )\nbool = isCurrentYear( null )\n","isDataProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isDataProperty( obj, 'boop' )\nbool = isDataProperty( obj, 'beep' )\n","isDataPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.get = function getter() { return 'beep'; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isDataPropertyIn( obj, 'boop' )\nbool = isDataPropertyIn( obj, 'beep' )\n","isDataView":"var buf = new ArrayBuffer( 10 );\nvar bool = isDataView( new DataView( buf ) )\nbool = isDataView( [] )\n","isDateObject":"var bool = isDateObject( new Date() )\nbool = isDateObject( '2017-01-01' )\n","isDateObjectArray":"var bool = isDateObjectArray( [ new Date(), new Date() ] )\nbool = isDateObjectArray( [ {}, {} ] )\nbool = isDateObjectArray( [ new Date(), '2011-01-01' ] )\nbool = isDateObjectArray( [] )\n","isDigitString":"var bool = isDigitString( '0123456789' )\nbool = isDigitString( 'abcdef' )\nbool = isDigitString( '0xff' )\nbool = isDigitString( '' )\n","isDomainName":"var bool = isDomainName( 'example.com' )\nbool = isDomainName( 'foo@bar.com' )\n","isDurationString":"var bool = isDurationString( '1d' )\nbool = isDurationString( '1h' )\nbool = isDurationString( 'beep' )\n","isEmailAddress":"var bool = isEmailAddress( 'beep@boop.com' )\nbool = isEmailAddress( 'beep' )\nbool = isEmailAddress( null )\n","isEmptyArray":"var bool = isEmptyArray( [] )\nbool = isEmptyArray( [ 1, 2, 3 ] )\nbool = isEmptyArray( {} )\n","isEmptyArrayLikeObject":"var bool = isEmptyArrayLikeObject( [] )\nbool = isEmptyArrayLikeObject( { 'length': 0 } )\nbool = isEmptyArrayLikeObject( '' )\n","isEmptyCollection":"var bool = isEmptyCollection( [] )\nbool = isEmptyCollection( { 'length': 0 } )\nbool = isEmptyCollection( [ 1, 2, 3 ] )\nbool = isEmptyCollection( {} )\n","isEmptyObject":"var bool = isEmptyObject( {} )\nbool = isEmptyObject( { 'beep': 'boop' } )\nbool = isEmptyObject( [] )\n","isEmptyString":"var bool = isEmptyString( '' )\nbool = isEmptyString( new String( '' ) )\nbool = isEmptyString( 'beep' )\nbool = isEmptyString( [] )\n","isEmptyString.isPrimitive":"var bool = isEmptyString.isPrimitive( '' )\nbool = isEmptyString.isPrimitive( new String( '' ) )\n","isEmptyString.isObject":"var bool = isEmptyString.isObject( new String( '' ) )\nbool = isEmptyString.isObject( '' )\n","isEnumerableProperty":"var beep = { 'boop': true };\nvar bool = isEnumerableProperty( beep, 'boop' )\nbool = isEnumerableProperty( beep, 'hasOwnProperty' )\n","isEnumerablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = true;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isEnumerablePropertyIn( obj, 'boop' )\nbool = isEnumerablePropertyIn( obj, 'beep' )\n","isEqualArray":"var x = [ 1.0, 2.0, 3.0 ];\nvar y = [ 1.0, 2.0, 3.0 ];\nvar bool = isEqualArray( x, y )\nx = [ NaN, NaN, NaN ];\ny = [ NaN, NaN, NaN ];\nbool = isEqualArray( x, y )\n","isError":"var bool = isError( new Error( 'beep' ) )\nbool = isError( {} )\n","isEvalError":"var bool = isEvalError( new EvalError( 'beep' ) )\nbool = isEvalError( {} )\n","isEven":"var bool = isEven( 4.0 )\nbool = isEven( new Number( 4.0 ) )\nbool = isEven( 3.0 )\nbool = isEven( -3.14 )\nbool = isEven( null )\n","isEven.isPrimitive":"var bool = isEven.isPrimitive( -4.0 )\nbool = isEven.isPrimitive( new Number( -4.0 ) )\n","isEven.isObject":"var bool = isEven.isObject( 4.0 )\nbool = isEven.isObject( new Number( 4.0 ) )\n","isFalsy":"var bool = isFalsy( false )\nbool = isFalsy( '' )\nbool = isFalsy( 0 )\nbool = isFalsy( null )\nbool = isFalsy( void 0 )\nbool = isFalsy( NaN )\nbool = isFalsy( {} )\nbool = isFalsy( [] )\n","isFalsyArray":"var bool = isFalsyArray( [ null, '' ] )\nbool = isFalsyArray( [ {}, [] ] )\nbool = isFalsyArray( [] )\n","isFinite":"var bool = isFinite( 5.0 )\nbool = isFinite( new Number( 5.0 ) )\nbool = isFinite( 1.0/0.0 )\nbool = isFinite( null )\n","isFinite.isPrimitive":"var bool = isFinite.isPrimitive( -3.0 )\nbool = isFinite.isPrimitive( new Number( -3.0 ) )\n","isFinite.isObject":"var bool = isFinite.isObject( 3.0 )\nbool = isFinite.isObject( new Number( 3.0 ) )\n","isFiniteArray":"var bool = isFiniteArray( [ -3.0, new Number(0.0), 2.0 ] )\nbool = isFiniteArray( [ -3.0, 1.0/0.0 ] )\n","isFiniteArray.primitives":"var bool = isFiniteArray.primitives( [ -1.0, 10.0 ] )\nbool = isFiniteArray.primitives( [ -1.0, 0.0, 5.0 ] )\nbool = isFiniteArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isFiniteArray.objects":"var bool = isFiniteArray.objects( [ new Number(1.0), new Number(3.0) ] )\nbool = isFiniteArray.objects( [ -1.0, 0.0, 3.0 ] )\nbool = isFiniteArray.objects( [ 3.0, new Number(-1.0) ] )\n","isFloat32Array":"var bool = isFloat32Array( new Float32Array( 10 ) )\nbool = isFloat32Array( [] )\n","isFloat32MatrixLike":"var M = {};\nM.data = new Float32Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float32';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat32MatrixLike( M )\nbool = isFloat32MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isFloat32MatrixLike( 3.14 )\nbool = isFloat32MatrixLike( {} )\n","isFloat32ndarrayLike":"var M = {};\nM.data = new Float32Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float32';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat32ndarrayLike( M )\nbool = isFloat32ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isFloat32ndarrayLike( 3.14 )\nbool = isFloat32ndarrayLike( {} )\n","isFloat32VectorLike":"var M = {};\nM.data = new Float32Array( [ 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float32';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat32VectorLike( M )\nbool = isFloat32VectorLike( [ 1, 2, 3, 4 ] )\nbool = isFloat32VectorLike( 3.14 )\nbool = isFloat32VectorLike( {} )\n","isFloat64Array":"var bool = isFloat64Array( new Float64Array( 10 ) )\nbool = isFloat64Array( [] )\n","isFloat64MatrixLike":"var M = {};\nM.data = new Float64Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat64MatrixLike( M )\nbool = isFloat64MatrixLike( [ 1, 2, 3, 4 ] )\nbool = isFloat64MatrixLike( 3.14 )\nbool = isFloat64MatrixLike( {} )\n","isFloat64ndarrayLike":"var M = {};\nM.data = new Float64Array( [ 0, 0, 0, 0 ] );\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat64ndarrayLike( M )\nbool = isFloat64ndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isFloat64ndarrayLike( 3.14 )\nbool = isFloat64ndarrayLike( {} )\n","isFloat64VectorLike":"var M = {};\nM.data = new Float64Array( [ 0, 0, 0, 0 ] );\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'float64';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isFloat64VectorLike( M )\nbool = isFloat64VectorLike( [ 1, 2, 3, 4 ] )\nbool = isFloat64VectorLike( 3.14 )\nbool = isFloat64VectorLike( {} )\n","isFunction":"function beep() {};\nvar bool = isFunction( beep )\nbool = isFunction( {} )\n","isFunctionArray":"function beep() {};\nfunction boop() {};\nvar bool = isFunctionArray( [ beep, boop ] )\nbool = isFunctionArray( [ {}, beep ] )\nbool = isFunctionArray( [] )\n","isGeneratorObject":"function* generateID() {\n var idx = 0;\n while ( idx < idx+1 ) {\n     yield idx;\n     idx += 1;\n }\n };\nvar bool = isGeneratorObject( generateID() )\nbool = isGeneratorObject( generateID )\nbool = isGeneratorObject( {} )\nbool = isGeneratorObject( null )\n","isGeneratorObjectLike":"var obj = {\n 'next': function noop() {},\n 'return': function noop() {},\n 'throw': function noop() {}\n };\nvar bool = isGeneratorObjectLike( obj )\nbool = isGeneratorObjectLike( {} )\nbool = isGeneratorObjectLike( null )\n","isgzipBuffer":"var buf = new Uint8Array( 20 );\nbuf[ 0 ] = 31;  // 0x1f => magic number\nbuf[ 1 ] = 139; // 0x8b\nbuf[ 2 ] = 8;   // 0x08 => compression method\nvar bool = isgzipBuffer( buf )\nbool = isgzipBuffer( [] )\n","isHexString":"var bool = isHexString( '0123456789abcdefABCDEF' )\nbool = isHexString( '0xffffff' )\nbool = isHexString( 'x' )\nbool = isHexString( '' )\n","isInfinite":"var bool = isInfinite( 1.0/0.0 )\nbool = isInfinite( new Number( -1.0/0.0 ) )\nbool = isInfinite( 5.0 )\nbool = isInfinite( '1.0/0.0' )\n","isInfinite.isPrimitive":"var bool = isInfinite.isPrimitive( -1.0/0.0 )\nbool = isInfinite.isPrimitive( new Number( -1.0/0.0 ) )\n","isInfinite.isObject":"var bool = isInfinite.isObject( 1.0/0.0 )\nbool = isInfinite.isObject( new Number( 1.0/0.0 ) )\n","isInheritedProperty":"var beep = { 'boop': true };\nvar bool = isInheritedProperty( beep, 'boop' )\nbool = isInheritedProperty( beep, 'toString' )\nbool = isInheritedProperty( beep, 'bop' )\n","isInt8Array":"var bool = isInt8Array( new Int8Array( 10 ) )\nbool = isInt8Array( [] )\n","isInt16Array":"var bool = isInt16Array( new Int16Array( 10 ) )\nbool = isInt16Array( [] )\n","isInt32Array":"var bool = isInt32Array( new Int32Array( 10 ) )\nbool = isInt32Array( [] )\n","isInteger":"var bool = isInteger( 5.0 )\nbool = isInteger( new Number( 5.0 ) )\nbool = isInteger( -3.14 )\nbool = isInteger( null )\n","isInteger.isPrimitive":"var bool = isInteger.isPrimitive( -3.0 )\nbool = isInteger.isPrimitive( new Number( -3.0 ) )\n","isInteger.isObject":"var bool = isInteger.isObject( 3.0 )\nbool = isInteger.isObject( new Number( 3.0 ) )\n","isIntegerArray":"var bool = isIntegerArray( [ -3.0, new Number(0.0), 2.0 ] )\nbool = isIntegerArray( [ -3.0, '3.0' ] )\n","isIntegerArray.primitives":"var bool = isIntegerArray.primitives( [ -1.0, 10.0 ] )\nbool = isIntegerArray.primitives( [ -1.0, 0.0, 5.0 ] )\nbool = isIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isIntegerArray.objects":"var bool = isIntegerArray.objects( [ new Number(1.0), new Number(3.0) ] )\nbool = isIntegerArray.objects( [ -1.0, 0.0, 3.0 ] )\nbool = isIntegerArray.objects( [ 3.0, new Number(-1.0) ] )\n","isIterableLike":"var bool = isIterableLike( [ 1, 2, 3 ] )\nbool = isIterableLike( {} )\nbool = isIterableLike( null )\n","isIteratorLike":"var obj = {\n 'next': function noop() {}\n };\nvar bool = isIteratorLike( obj )\nbool = isIteratorLike( {} )\nbool = isIteratorLike( null )\n","isJSON":"var bool = isJSON( '{\"a\":5}' )\nbool = isJSON( '{a\":5}' )\n","isKebabcase":"var bool = isKebabcase( 'beep-boop' )\nbool = isKebabcase( 'BEEP_BOOP' )\n","isLeapYear":"var bool = isLeapYear( new Date() )\nbool = isLeapYear( 1996 )\nbool = isLeapYear( 2001 )\n","isLocalhost":"var bool = isLocalhost( 'localhost' )\nbool = isLocalhost( '127.0.0.1' )\nbool = isLocalhost( 'stdlib.io' )\n","isLowercase":"var bool = isLowercase( 'hello' )\nbool = isLowercase( 'World' )\n","isMatrixLike":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isMatrixLike( M )\nbool = isMatrixLike( [ 1, 2, 3, 4 ] )\nbool = isMatrixLike( 3.14 )\nbool = isMatrixLike( {} )\n","isMethod":"var beep = { 'boop': function beep() { return 'beep'; } };\nvar bool = isMethod( beep, 'boop' )\nbool = isMethod( beep, 'toString' )\n","isMethodIn":"var beep = { 'boop': true };\nvar bool = isMethodIn( beep, 'toString' )\nbool = isMethodIn( beep, 'boop' )\nbool = isMethodIn( beep, 'bop' )\n","isMultiSlice":"var bool = isMultiSlice( new MultiSlice() )\nbool = isMultiSlice( 3.14 )\nbool = isMultiSlice( {} )\n","isNamedTypedTupleLike":"var Point = namedtypedtuple( [ 'x', 'y' ] );\nvar p = new Point();\nvar bool = isNamedTypedTupleLike( p )\nbool = isNamedTypedTupleLike( [ 1, 2, 3, 4 ] )\nbool = isNamedTypedTupleLike( 3.14 )\nbool = isNamedTypedTupleLike( {} )\n","isnan":"var bool = isnan( NaN )\nbool = isnan( new Number( NaN ) )\nbool = isnan( 3.14 )\nbool = isnan( null )\n","isnan.isPrimitive":"var bool = isnan.isPrimitive( NaN )\nbool = isnan.isPrimitive( 3.14 )\nbool = isnan.isPrimitive( new Number( NaN ) )\n","isnan.isObject":"var bool = isnan.isObject( NaN )\nbool = isnan.isObject( new Number( NaN ) )\n","isNaNArray":"var bool = isNaNArray( [ NaN, NaN, NaN ] )\nbool = isNaNArray( [ NaN, 2 ] )\n","isNaNArray.primitives":"var bool = isNaNArray.primitives( [ NaN, new Number( NaN ) ] )\nbool = isNaNArray.primitives( [ NaN, NaN, NaN ] )\n","isNaNArray.objects":"var bool = isNaNArray.objects( [ new Number( NaN ), new Number( NaN ) ] )\nbool = isNaNArray.objects( [ NaN, new Number( NaN ), new Number( NaN ) ] )\nbool = isNaNArray.objects( [ NaN, NaN, NaN ] )\n","isNativeFunction":"var bool = isNativeFunction( Date )\nfunction beep() {};\nbool = isNativeFunction( beep )\nbool = isNativeFunction( {} )\n","isndarrayLike":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isndarrayLike( M )\nbool = isndarrayLike( [ 1, 2, 3, 4 ] )\nbool = isndarrayLike( 3.14 )\nbool = isndarrayLike( {} )\n","isndarrayLikeWithDataType":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 2;\nM.shape = [ 2, 2 ];\nM.strides = [ 2, 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isndarrayLikeWithDataType( M, 'generic' )\nbool = isndarrayLikeWithDataType( [ 1, 2, 3, 4 ], 'generic' )\nbool = isndarrayLikeWithDataType( 3.14, 'generic' )\nbool = isndarrayLikeWithDataType( {}, 'generic' )\n","isNegativeFinite":"var bool = isNegativeFinite( -5.0 )\nbool = isNegativeFinite( new Number( -5.0 ) )\nbool = isNegativeFinite( -3.14 )\nbool = isNegativeFinite( 5.0 )\nbool = isNegativeFinite( null )\nbool = isNegativeFinite( -1.0/0.0 )\nbool = isNegativeFinite( new Number( -1.0/0.0 ) )\n","isNegativeFinite.isPrimitive":"var bool = isNegativeFinite.isPrimitive( -3.0 )\nbool = isNegativeFinite.isPrimitive( new Number( -3.0 ) )\nvar bool = isNegativeFinite.isPrimitive( -1.0/0.0 )\nbool = isNegativeFinite.isPrimitive( new Number( -1.0/0.0 ) )\n","isNegativeFinite.isObject":"var bool = isNegativeFinite.isObject( -3.0 )\nbool = isNegativeFinite.isObject( new Number( -3.0 ) )\nbool = isNegativeFinite.isObject( -1.0/0.0 )\nbool = isNegativeFinite.isObject( new Number( -1.0/0.0 ) )\n","isNegativeInteger":"var bool = isNegativeInteger( -5.0 )\nbool = isNegativeInteger( new Number( -5.0 ) )\nbool = isNegativeInteger( 5.0 )\nbool = isNegativeInteger( -3.14 )\nbool = isNegativeInteger( null )\n","isNegativeInteger.isPrimitive":"var bool = isNegativeInteger.isPrimitive( -3.0 )\nbool = isNegativeInteger.isPrimitive( new Number( -3.0 ) )\n","isNegativeInteger.isObject":"var bool = isNegativeInteger.isObject( -3.0 )\nbool = isNegativeInteger.isObject( new Number( -3.0 ) )\n","isNegativeIntegerArray":"var bool = isNegativeIntegerArray( [ -3.0, new Number(-3.0) ] )\nbool = isNegativeIntegerArray( [ -3.0, '-3.0' ] )\n","isNegativeIntegerArray.primitives":"var bool = isNegativeIntegerArray.primitives( [ -1.0, -10.0 ] )\nbool = isNegativeIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNegativeIntegerArray.objects":"var bool = isNegativeIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNegativeIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNegativeNumber":"var bool = isNegativeNumber( -5.0 )\nbool = isNegativeNumber( new Number( -5.0 ) )\nbool = isNegativeNumber( -3.14 )\nbool = isNegativeNumber( 5.0 )\nbool = isNegativeNumber( null )\n","isNegativeNumber.isPrimitive":"var bool = isNegativeNumber.isPrimitive( -3.0 )\nbool = isNegativeNumber.isPrimitive( new Number( -3.0 ) )\n","isNegativeNumber.isObject":"var bool = isNegativeNumber.isObject( -3.0 )\nbool = isNegativeNumber.isObject( new Number( -3.0 ) )\n","isNegativeNumberArray":"var bool = isNegativeNumberArray( [ -3.0, new Number(-3.0) ] )\nbool = isNegativeNumberArray( [ -3.0, '-3.0' ] )\n","isNegativeNumberArray.primitives":"var bool = isNegativeNumberArray.primitives( [ -1.0, -10.0 ] )\nbool = isNegativeNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNegativeNumberArray.objects":"var bool = isNegativeNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNegativeNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNegativeNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNegativeZero":"var bool = isNegativeZero( -0.0 )\nbool = isNegativeZero( new Number( -0.0 ) )\nbool = isNegativeZero( -3.14 )\nbool = isNegativeZero( 0.0 )\nbool = isNegativeZero( null )\n","isNegativeZero.isPrimitive":"var bool = isNegativeZero.isPrimitive( -0.0 )\nbool = isNegativeZero.isPrimitive( new Number( -0.0 ) )\n","isNegativeZero.isObject":"var bool = isNegativeZero.isObject( -0.0 )\nbool = isNegativeZero.isObject( new Number( -0.0 ) )\n","isNodeBuiltin":"var bool = isNodeBuiltin( 'cluster' )\nbool = isNodeBuiltin( 'crypto' )\nbool = isNodeBuiltin( 'fs-extra' )\nbool = isNodeBuiltin( '' )\n","isNodeDuplexStreamLike":"var Stream = require( 'stream' ).Duplex;\ns = new Stream();\nvar bool = isNodeDuplexStreamLike( s )\nbool = isNodeDuplexStreamLike( {} )\n","isNodeReadableStreamLike":"var Stream = require( 'stream' ).Readable;\ns = new Stream();\nvar bool = isNodeReadableStreamLike( s )\nbool = isNodeReadableStreamLike( {} )\n","isNodeREPL":"var bool = isNodeREPL()\n","isNodeStreamLike":"var Stream = require( 'stream' ).Stream;\ns = new Stream();\nvar bool = isNodeStreamLike( s )\nbool = isNodeStreamLike( {} )\n","isNodeTransformStreamLike":"var Stream = require( 'stream' ).Transform;\ns = new Stream();\nvar bool = isNodeTransformStreamLike( s )\nbool = isNodeTransformStreamLike( {} )\n","isNodeWritableStreamLike":"var Stream = require( 'stream' ).Writable;\ns = new Stream();\nvar bool = isNodeWritableStreamLike( s )\nbool = isNodeWritableStreamLike( {} )\n","isNonConfigurableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonConfigurableProperty( obj, 'boop' )\nbool = isNonConfigurableProperty( obj, 'beep' )\n","isNonConfigurablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonConfigurablePropertyIn( obj, 'boop' )\nbool = isNonConfigurablePropertyIn( obj, 'beep' )\n","isNonEnumerableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonEnumerableProperty( obj, 'boop' )\nbool = isNonEnumerableProperty( obj, 'beep' )\n","isNonEnumerablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = true;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isNonEnumerablePropertyIn( obj, 'boop' )\nbool = isNonEnumerablePropertyIn( obj, 'beep' )\n","isNonNegativeFinite":"var bool = isNonNegativeFinite( 5.0 )\nbool = isNonNegativeFinite( new Number( 5.0 ) )\nbool = isNonNegativeFinite( 3.14 )\nbool = isNonNegativeFinite( -5.0 )\nbool = isNonNegativeFinite( null )\nbool = isNonNegativeFinite( PINF )\n","isNonNegativeFinite.isPrimitive":"var bool = isNonNegativeFinite.isPrimitive( 3.0 )\nbool = isNonNegativeFinite.isPrimitive( new Number( 3.0 ) )\n","isNonNegativeFinite.isObject":"var bool = isNonNegativeFinite.isObject( 3.0 )\nbool = isNonNegativeFinite.isObject( new Number( 3.0 ) )\n","isNonNegativeInteger":"var bool = isNonNegativeInteger( 5.0 )\nbool = isNonNegativeInteger( new Number( 5.0 ) )\nbool = isNonNegativeInteger( 3.14 )\nbool = isNonNegativeInteger( -5.0 )\nbool = isNonNegativeInteger( null )\n","isNonNegativeInteger.isPrimitive":"var bool = isNonNegativeInteger.isPrimitive( 3.0 )\nbool = isNonNegativeInteger.isPrimitive( new Number( 3.0 ) )\n","isNonNegativeInteger.isObject":"var bool = isNonNegativeInteger.isObject( 3.0 )\nbool = isNonNegativeInteger.isObject( new Number( 3.0 ) )\n","isNonNegativeIntegerArray":"var bool = isNonNegativeIntegerArray( [ 3.0, new Number(3.0) ] )\nbool = isNonNegativeIntegerArray( [ 3.0, '3.0' ] )\n","isNonNegativeIntegerArray.primitives":"var bool = isNonNegativeIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n","isNonNegativeIntegerArray.objects":"var bool = isNonNegativeIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isNonNegativeIntegerArray.objects( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n","isNonNegativeNumber":"var bool = isNonNegativeNumber( 5.0 )\nbool = isNonNegativeNumber( new Number( 5.0 ) )\nbool = isNonNegativeNumber( 3.14 )\nbool = isNonNegativeNumber( -5.0 )\nbool = isNonNegativeNumber( null )\n","isNonNegativeNumber.isPrimitive":"var bool = isNonNegativeNumber.isPrimitive( 3.0 )\nbool = isNonNegativeNumber.isPrimitive( new Number( 3.0 ) )\n","isNonNegativeNumber.isObject":"var bool = isNonNegativeNumber.isObject( 3.0 )\nbool = isNonNegativeNumber.isObject( new Number( 3.0 ) )\n","isNonNegativeNumberArray":"var bool = isNonNegativeNumberArray( [ 3.0, new Number(3.0) ] )\nbool = isNonNegativeNumberArray( [ 3.0, '3.0' ] )\n","isNonNegativeNumberArray.primitives":"var bool = isNonNegativeNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n","isNonNegativeNumberArray.objects":"var bool = isNonNegativeNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isNonNegativeNumberArray.objects( [ 1.0, 0.0, 10.0 ] )\nbool = isNonNegativeNumberArray.objects( [ 3.0, new Number(1.0) ] )\n","isNonPositiveFinite":"var bool = isNonPositiveFinite( -5.0 )\nbool = isNonPositiveFinite( new Number( -5.0 ) )\nbool = isNonPositiveFinite( -3.14 )\nbool = isNonPositiveFinite( 5.0 )\nbool = isNonPositiveFinite( null )\n","isNonPositiveFinite.isPrimitive":"var bool = isNonPositiveFinite.isPrimitive( -3.0 )\nbool = isNonPositiveFinite.isPrimitive( new Number( -3.0 ) )\n","isNonPositiveFinite.isObject":"var bool = isNonPositiveFinite.isObject( -3.0 )\nbool = isNonPositiveFinite.isObject( new Number( -3.0 ) )\n","isNonPositiveInteger":"var bool = isNonPositiveInteger( -5.0 )\nbool = isNonPositiveInteger( new Number( -5.0 ) )\nbool = isNonPositiveInteger( 5.0 )\nbool = isNonPositiveInteger( -3.14 )\nbool = isNonPositiveInteger( null )\n","isNonPositiveInteger.isPrimitive":"var bool = isNonPositiveInteger.isPrimitive( -3.0 )\nbool = isNonPositiveInteger.isPrimitive( new Number( -3.0 ) )\n","isNonPositiveInteger.isObject":"var bool = isNonPositiveInteger.isObject( -3.0 )\nbool = isNonPositiveInteger.isObject( new Number( -3.0 ) )\n","isNonPositiveIntegerArray":"var bool = isNonPositiveIntegerArray( [ -3.0, new Number(-3.0) ] )\nbool = isNonPositiveIntegerArray( [ -3.0, '-3.0' ] )\n","isNonPositiveIntegerArray.primitives":"var bool = isNonPositiveIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNonPositiveIntegerArray.objects":"var bool = isNonPositiveIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNonPositiveIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNonPositiveNumber":"var bool = isNonPositiveNumber( -5.0 )\nbool = isNonPositiveNumber( new Number( -5.0 ) )\nbool = isNonPositiveNumber( -3.14 )\nbool = isNonPositiveNumber( 5.0 )\nbool = isNonPositiveNumber( null )\n","isNonPositiveNumber.isPrimitive":"var bool = isNonPositiveNumber.isPrimitive( -3.0 )\nbool = isNonPositiveNumber.isPrimitive( new Number( -3.0 ) )\n","isNonPositiveNumber.isObject":"var bool = isNonPositiveNumber.isObject( -3.0 )\nbool = isNonPositiveNumber.isObject( new Number( -3.0 ) )\n","isNonPositiveNumberArray":"var bool = isNonPositiveNumberArray( [ -3.0, new Number(-3.0) ] )\nbool = isNonPositiveNumberArray( [ -3.0, '-3.0' ] )\n","isNonPositiveNumberArray.primitives":"var bool = isNonPositiveNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n","isNonPositiveNumberArray.objects":"var bool = isNonPositiveNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\nbool = isNonPositiveNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\nbool = isNonPositiveNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n","isNonSymmetricMatrix":"var buf = [ 1, 2, 3, 4 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isNonSymmetricMatrix( M )\nbool = isNonSymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isNonSymmetricMatrix( 3.14 )\nbool = isNonSymmetricMatrix( {} )\n","isNull":"var bool = isNull( null )\nbool = isNull( true )\n","isNullArray":"var bool = isNullArray( [ null, null, null ] )\nbool = isNullArray( [ NaN, 2, null ] )\n","isNumber":"var bool = isNumber( 3.14 )\nbool = isNumber( new Number( 3.14 ) )\nbool = isNumber( NaN )\nbool = isNumber( null )\n","isNumber.isPrimitive":"var bool = isNumber.isPrimitive( 3.14 )\nbool = isNumber.isPrimitive( NaN )\nbool = isNumber.isPrimitive( new Number( 3.14 ) )\n","isNumber.isObject":"var bool = isNumber.isObject( 3.14 )\nbool = isNumber.isObject( new Number( 3.14 ) )\n","isNumberArray":"var bool = isNumberArray( [ 1, 2, 3 ] )\nbool = isNumberArray( [ '1', 2, 3 ] )\n","isNumberArray.primitives":"var arr = [ 1, 2, 3 ];\nvar bool = isNumberArray.primitives( arr )\narr = [ 1, new Number( 2 ) ];\nbool = isNumberArray.primitives( arr )\n","isNumberArray.objects":"var arr = [ new Number( 1 ), new Number( 2 ) ];\nvar bool = isNumberArray.objects( arr )\narr = [ new Number( 1 ), 2 ];\nbool = isNumberArray.objects( arr )\n","isNumericArray":"var bool = isNumericArray( new Int8Array( 10 ) )\nbool = isNumericArray( [ 1, 2, 3 ] )\nbool = isNumericArray( [ '1', '2', '3' ] )\n","isObject":"var bool = isObject( {} )\nbool = isObject( true )\n","isObjectArray":"var bool = isObjectArray( [ {}, new Number(3.0) ] )\nbool = isObjectArray( [ {}, { 'beep': 'boop' } ] )\nbool = isObjectArray( [ {}, '3.0' ] )\n","isObjectLike":"var bool = isObjectLike( {} )\nbool = isObjectLike( [] )\nbool = isObjectLike( null )\n","isOdd":"var bool = isOdd( 5.0 )\nbool = isOdd( new Number( 5.0 ) )\nbool = isOdd( 4.0 )\nbool = isOdd( new Number( 4.0 ) )\nbool = isOdd( -3.14 )\nbool = isOdd( null )\n","isOdd.isPrimitive":"var bool = isOdd.isPrimitive( -5.0 )\nbool = isOdd.isPrimitive( new Number( -5.0 ) )\n","isOdd.isObject":"var bool = isOdd.isObject( 5.0 )\nbool = isOdd.isObject( new Number( 5.0 ) )\n","isoWeeksInYear":"var num = isoWeeksInYear()\nnum = isoWeeksInYear( 2015 )\nnum = isoWeeksInYear( 2017 )\n","isPascalcase":"var bool = isPascalcase( 'HelloWorld' )\nbool = isPascalcase( 'hello-world' )\n","isPersymmetricMatrix":"var buf = [ 1, 2, 3, 1 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isPersymmetricMatrix( M )\nbool = isPersymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isPersymmetricMatrix( 3.14 )\nbool = isPersymmetricMatrix( {} )\n","isPlainObject":"var bool = isPlainObject( {} )\nbool = isPlainObject( null )\n","isPlainObjectArray":"var bool = isPlainObjectArray( [ {}, { 'beep': 'boop' } ] )\nbool = isPlainObjectArray( [ {}, new Number(3.0) ] )\nbool = isPlainObjectArray( [ {}, '3.0' ] )\n","isPositiveFinite":"var bool = isPositiveFinite( 5.0 )\nbool = isPositiveFinite( new Number( 5.0 ) )\nbool = isPositiveFinite( 3.14 )\nbool = isPositiveFinite( -5.0 )\nvar bool = isPositiveFinite( 1.0/0.0 )\nbool = isPositiveFinite( new Number( 1.0/0.0 ) )\nbool = isPositiveFinite( null )\n","isPositiveFinite.isPrimitive":"var bool = isPositiveFinite.isPrimitive( 3.0 )\nvar bool = isPositiveFinite.isPrimitive( 1.0/0.0 )\nbool = isPositiveFinite.isPrimitive( new Number( 3.0 ) )\n","isPositiveFinite.isObject":"var bool = isPositiveFinite.isObject( 3.0 )\nbool = isPositiveFinite.isObject( new Number( 3.0 ) )\nbool = isPositiveFinite.isObject( new Number( 1.0/0.0 ) )\n","isPositiveInteger":"var bool = isPositiveInteger( 5.0 )\nbool = isPositiveInteger( new Number( 5.0 ) )\nbool = isPositiveInteger( 3.14 )\nbool = isPositiveInteger( -5.0 )\nbool = isPositiveInteger( null )\n","isPositiveInteger.isPrimitive":"var bool = isPositiveInteger.isPrimitive( 3.0 )\nbool = isPositiveInteger.isPrimitive( new Number( 3.0 ) )\n","isPositiveInteger.isObject":"var bool = isPositiveInteger.isObject( 3.0 )\nbool = isPositiveInteger.isObject( new Number( 3.0 ) )\n","isPositiveIntegerArray":"var bool = isPositiveIntegerArray( [ 3.0, new Number(3.0) ] )\nbool = isPositiveIntegerArray( [ 3.0, '3.0' ] )\n","isPositiveIntegerArray.primitives":"var bool = isPositiveIntegerArray.primitives( [ 1.0, 10.0 ] )\nbool = isPositiveIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isPositiveIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n","isPositiveIntegerArray.objects":"var bool = isPositiveIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isPositiveIntegerArray.objects( [ 1.0, 2.0, 10.0 ] )\nbool = isPositiveIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n","isPositiveNumber":"var bool = isPositiveNumber( 5.0 )\nbool = isPositiveNumber( new Number( 5.0 ) )\nbool = isPositiveNumber( 3.14 )\nbool = isPositiveNumber( -5.0 )\nbool = isPositiveNumber( null )\n","isPositiveNumber.isPrimitive":"var bool = isPositiveNumber.isPrimitive( 3.0 )\nbool = isPositiveNumber.isPrimitive( new Number( 3.0 ) )\n","isPositiveNumber.isObject":"var bool = isPositiveNumber.isObject( 3.0 )\nbool = isPositiveNumber.isObject( new Number( 3.0 ) )\n","isPositiveNumberArray":"var bool = isPositiveNumberArray( [ 3.0, new Number(3.0) ] )\nbool = isPositiveNumberArray( [ 3.0, '3.0' ] )\n","isPositiveNumberArray.primitives":"var bool = isPositiveNumberArray.primitives( [ 1.0, 10.0 ] )\nbool = isPositiveNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\nbool = isPositiveNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n","isPositiveNumberArray.objects":"var bool = isPositiveNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\nbool = isPositiveNumberArray.objects( [ 1.0, 2.0, 10.0 ] )\nbool = isPositiveNumberArray.objects( [ 3.0, new Number(1.0) ] )\n","isPositiveZero":"var bool = isPositiveZero( 0.0 )\nbool = isPositiveZero( new Number( 0.0 ) )\nbool = isPositiveZero( -3.14 )\nbool = isPositiveZero( -0.0 )\nbool = isPositiveZero( null )\n","isPositiveZero.isPrimitive":"var bool = isPositiveZero.isPrimitive( 0.0 )\nbool = isPositiveZero.isPrimitive( new Number( 0.0 ) )\n","isPositiveZero.isObject":"var bool = isPositiveZero.isObject( 0.0 )\nbool = isPositiveZero.isObject( new Number( 0.0 ) )\n","isPrime":"var bool = isPrime( 5.0 )\nbool = isPrime( new Number( 5.0 ) )\nbool = isPrime( 3.14 )\nbool = isPrime( -5.0 )\nbool = isPrime( null )\n","isPrime.isPrimitive":"var bool = isPrime.isPrimitive( 5.0 )\nbool = isPrime.isPrimitive( new Number( 5.0 ) )\n","isPrime.isObject":"var bool = isPrime.isObject( 5.0 )\nbool = isPrime.isObject( new Number( 5.0 ) )\n","isPrimitive":"var bool = isPrimitive( true )\nbool = isPrimitive( {} )\n","isPrimitiveArray":"var bool = isPrimitiveArray( [ '3', 2, null ] )\nbool = isPrimitiveArray( [ {}, 2, 1 ] )\nbool = isPrimitiveArray( [ new String('abc'), '3.0' ] )\n","isPRNGLike":"var bool = isPRNGLike( base.random.randu )\nbool = isPRNGLike( [ 1, 2, 3, 4 ] )\nbool = isPRNGLike( 3.14 )\nbool = isPRNGLike( {} )\n","isProbability":"var bool = isProbability( 0.5 )\nbool = isProbability( new Number( 0.5 ) )\nbool = isProbability( 3.14 )\nbool = isProbability( -5.0 )\nbool = isProbability( null )\n","isProbability.isPrimitive":"var bool = isProbability.isPrimitive( 0.3 )\nbool = isProbability.isPrimitive( new Number( 0.3 ) )\n","isProbability.isObject":"var bool = isProbability.isObject( 0.77 )\nbool = isProbability.isObject( new Number( 0.77 ) )\n","isProbabilityArray":"var bool = isProbabilityArray( [ 0.5, new Number(0.8) ] )\nbool = isProbabilityArray( [ 0.8, 1.2 ] )\nbool = isProbabilityArray( [ 0.8, '0.2' ] )\n","isProbabilityArray.primitives":"var bool = isProbabilityArray.primitives( [ 1.0, 0.0, 0.5 ] )\nbool = isProbabilityArray.primitives( [ 0.3, new Number(0.4) ] )\n","isProbabilityArray.objects":"var bool = isProbabilityArray.objects( [ new Number(0.7), new Number(1.0) ] )\nbool = isProbabilityArray.objects( [ 1.0, 0.0, new Number(0.7) ] )\n","isPropertyKey":"var out = isPropertyKey( 'foo' )\nout = isPropertyKey( 1 )\nout = isPropertyKey( true )\n","isPrototypeOf":"function Foo() { return this; };\nfunction Bar() { return this; };\ninherit( Bar, Foo );\nvar bar = new Bar();\nvar bool = isPrototypeOf( bar, Foo.prototype )\n","isRaggedNestedArray":"var bool = isRaggedNestedArray( [ [ 1, 2, 3 ], [ 4, 5 ] ] )\nbool = isRaggedNestedArray( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\nbool = isRaggedNestedArray( 'beep' )\n","isRangeError":"var bool = isRangeError( new RangeError( 'beep' ) )\nbool = isRangeError( {} )\n","isReadableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadableProperty( obj, 'boop' )\nbool = isReadableProperty( obj, 'beep' )\n","isReadablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadablePropertyIn( obj, 'boop' )\nbool = isReadablePropertyIn( obj, 'beep' )\n","isReadOnlyProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadOnlyProperty( obj, 'boop' )\nbool = isReadOnlyProperty( obj, 'beep' )\n","isReadOnlyPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = true;\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadOnlyPropertyIn( obj, 'boop' )\nbool = isReadOnlyPropertyIn( obj, 'beep' )\n","isReadWriteProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadWriteProperty( obj, 'boop' )\nbool = isReadWriteProperty( obj, 'beep' )\n","isReadWritePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isReadWritePropertyIn( obj, 'boop' )\nbool = isReadWritePropertyIn( obj, 'beep' )\n","isReferenceError":"var bool = isReferenceError( new ReferenceError( 'beep' ) )\nbool = isReferenceError( {} )\n","isRegExp":"var bool = isRegExp( /\\.+/ )\nbool = isRegExp( {} )\n","isRegExpString":"var bool = isRegExpString( '/beep/' )\nbool = isRegExpString( 'beep' )\nbool = isRegExpString( '' )\nbool = isRegExpString( null )\n","isRelativePath":"var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\nbool = isRelativePath( './foo/bar/baz' )\n","isRelativePath.posix":"var bool = isRelativePath.posix( './foo/bar/baz' )\nbool = isRelativePath.posix( '/foo/../bar/baz' )\n","isRelativePath.win32":"var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\nbool = isRelativePath( 'C:\\\\foo\\\\..\\\\bar\\\\baz' )\n","isRelativeURI":"var bool = isRelativeURI( '/images/example.png' )\nbool = isRelativeURI( 'http://www.example.com' )\nbool = isRelativeURI( null )\n","isSafeInteger":"var bool = isSafeInteger( 5.0 )\nbool = isSafeInteger( new Number( 5.0 ) )\nbool = isSafeInteger( 2.0e200 )\nbool = isSafeInteger( -3.14 )\nbool = isSafeInteger( null )\n","isSafeInteger.isPrimitive":"var bool = isSafeInteger.isPrimitive( -3.0 )\nbool = isSafeInteger.isPrimitive( new Number( -3.0 ) )\n","isSafeInteger.isObject":"var bool = isSafeInteger.isObject( 3.0 )\nbool = isSafeInteger.isObject( new Number( 3.0 ) )\n","isSafeIntegerArray":"var arr = [ -3.0, new Number(0.0), 2.0 ];\nvar bool = isSafeIntegerArray( arr )\narr = [ -3.0, '3.0' ];\nbool = isSafeIntegerArray( arr )\n","isSafeIntegerArray.primitives":"var arr = [ -1.0, 10.0 ];\nvar bool = isSafeIntegerArray.primitives( arr )\narr = [ -1.0, 0.0, 5.0 ];\nbool = isSafeIntegerArray.primitives( arr )\narr = [ -3.0, new Number(-1.0) ];\nbool = isSafeIntegerArray.primitives( arr )\n","isSafeIntegerArray.objects":"var arr = [ new Number(1.0), new Number(3.0) ];\nvar bool = isSafeIntegerArray.objects( arr )\narr = [ -1.0, 0.0, 3.0 ];\nbool = isSafeIntegerArray.objects( arr )\narr = [ 3.0, new Number(-1.0) ];\nbool = isSafeIntegerArray.objects( arr )\n","isSameArray":"var x = [ 1.0, 2.0, 3.0 ];\nvar y = [ 1.0, 2.0, 3.0 ];\nvar bool = isSameArray( x, y )\nx = [ NaN, NaN, NaN ];\ny = [ NaN, NaN, NaN ];\nbool = isSameArray( x, y )\n","isSameArrayLike":"var x = [ 1.0, 2.0, 3.0 ];\nvar y = [ 1.0, 2.0, 3.0 ];\nvar bool = isSameArrayLike( x, y )\nx = [ NaN, NaN, NaN ];\ny = [ NaN, NaN, NaN ];\nbool = isSameArrayLike( x, y )\n","isSameComplex64":"var x = new Complex64( 1.0, 2.0 );\nvar y = new Complex64( 1.0, 2.0 );\nvar bool = isSameComplex64( x, y )\nx = new Complex64( NaN, NaN );\ny = new Complex64( NaN, NaN );\nbool = isSameComplex64( x, y )\n","isSameComplex64Array":"var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar bool = isSameComplex64Array( x, y )\nx = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\ny = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\nbool = isSameComplex64Array( x, y )\n","isSameComplex128":"var x = new Complex128( 1.0, 2.0 );\nvar y = new Complex128( 1.0, 2.0 );\nvar bool = isSameComplex128( x, y )\nx = new Complex128( NaN, NaN );\ny = new Complex128( NaN, NaN );\nbool = isSameComplex128( x, y )\n","isSameComplex128Array":"var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar bool = isSameComplex128Array( x, y )\nx = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\ny = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\nbool = isSameComplex128Array( x, y )\n","isSameDateObject":"var d1 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\nvar d2 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\nvar bool = isSameDateObject( d1, d2 )\nvar d1 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\nvar d2 = new Date( 2024, 11, 31, 23, 59, 59, 78 );\nvar bool = isSameDateObject( d1, d2 )\n","isSameFloat32Array":"var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nvar y = new Float32Array( [ 1.0, 2.0, 3.0 ] );\nvar bool = isSameFloat32Array( x, y )\nx = new Float32Array( [ NaN, NaN, NaN ] );\ny = new Float32Array( [ NaN, NaN, NaN ] );\nbool = isSameFloat32Array( x, y )\n","isSameFloat64Array":"var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0 ] );\nvar bool = isSameFloat64Array( x, y )\nx = new Float64Array( [ NaN, NaN, NaN ] );\ny = new Float64Array( [ NaN, NaN, NaN ] );\nbool = isSameFloat64Array( x, y )\n","isSameNativeClass":"var bool = isSameNativeClass( 3.14, new Number( 3.14 ) )\nbool = isSameNativeClass( 'beep', 'boop' )\nbool = isSameNativeClass( {}, [] )\n","isSameType":"var bool = isSameType( true, true )\nbool = isSameType( {}, [] )\nbool = isSameType( 3.12, -3.12 )\nbool = isSameType( 0.0, '0.0' )\n","isSameValue":"var bool = isSameValue( true, true )\nbool = isSameValue( {}, {} )\nbool = isSameValue( -0.0, -0.0 )\nbool = isSameValue( -0.0, 0.0 )\nbool = isSameValue( NaN, NaN )\n","isSameValueZero":"var bool = isSameValueZero( true, true )\nbool = isSameValueZero( {}, {} )\nbool = isSameValueZero( -0.0, -0.0 )\nbool = isSameValueZero( -0.0, 0.0 )\nbool = isSameValueZero( NaN, NaN )\n","isSemVer":"var bool = isSemVer( '1.0.0' )\nbool = isSemVer( '1.0.0-alpha.1' )\nbool = isSemVer( '0.1' )\nbool = isSemVer( null )\n","isSharedArrayBuffer":"var bool = isSharedArrayBuffer( new SharedArrayBuffer( 10 ) )\nbool = isSharedArrayBuffer( [] )\n","isSkewCentrosymmetricMatrix":"var buf = [ 2, 1, -1, -2 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSkewCentrosymmetricMatrix( M )\nbool = isSkewCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSkewCentrosymmetricMatrix( 3.14 )\nbool = isSkewCentrosymmetricMatrix( {} )\n","isSkewPersymmetricMatrix":"var buf = [ 1, 0, 0, -1 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSkewPersymmetricMatrix( M )\nbool = isSkewPersymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSkewPersymmetricMatrix( 3.14 )\nbool = isSkewPersymmetricMatrix( {} )\n","isSkewSymmetricMatrix":"var buf = [ 0, -1, 1, 0 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSkewSymmetricMatrix( M )\nbool = isSkewSymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSkewSymmetricMatrix( 3.14 )\nbool = isSkewSymmetricMatrix( {} )\n","isSlice":"var bool = isSlice( new Slice( 10 ) )\nbool = isSlice( 3.14 )\nbool = isSlice( {} )\n","isSnakecase":"var bool = isSnakecase( 'hello_world' )\nbool = isSnakecase( 'Hello World' )\n","isSquareMatrix":"var buf = [ 0, 0, 0, 0 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSquareMatrix( M )\nbool = isSquareMatrix( [ 1, 2, 3, 4 ] )\nbool = isSquareMatrix( 3.14 )\nbool = isSquareMatrix( {} )\n","isSquareNumber":"var bool = isSquareNumber( 4.0 )\nbool = isSquareNumber( new Number( 4.0 ) )\nbool = isSquareNumber( 3.14 )\nbool = isSquareNumber( -5.0 )\nbool = isSquareNumber( null )\n","isSquareNumber.isPrimitive":"var bool = isSquareNumber.isPrimitive( 4.0 )\nbool = isSquareNumber.isPrimitive( new Number( 4.0 ) )\n","isSquareNumber.isObject":"var bool = isSquareNumber.isObject( 4.0 )\nbool = isSquareNumber.isObject( new Number( 4.0 ) )\n","isSquareTriangularNumber":"var bool = isSquareTriangularNumber( 36.0 )\nbool = isSquareTriangularNumber( new Number( 36.0 ) )\nbool = isSquareTriangularNumber( 3.14 )\nbool = isSquareTriangularNumber( -5.0 )\nbool = isSquareTriangularNumber( null )\n","isSquareTriangularNumber.isPrimitive":"var bool = isSquareTriangularNumber.isPrimitive( 36.0 )\nbool = isSquareTriangularNumber.isPrimitive( new Number( 36.0 ) )\n","isSquareTriangularNumber.isObject":"var bool = isSquareTriangularNumber.isObject( 36.0 )\nbool = isSquareTriangularNumber.isObject( new Number( 36.0 ) )\n","isStartcase":"var bool = isStartcase( 'Beep Boop' )\nbool = isStartcase( 'Beep and Boop' )\n","isStrictEqual":"var bool = isStrictEqual( true, true )\nbool = isStrictEqual( {}, {} )\nbool = isStrictEqual( -0.0, -0.0 )\nbool = isStrictEqual( -0.0, 0.0 )\nbool = isStrictEqual( NaN, NaN )\n","isString":"var bool = isString( 'beep' )\nbool = isString( new String( 'beep' ) )\nbool = isString( 5 )\n","isString.isPrimitive":"var bool = isString.isPrimitive( 'beep' )\nbool = isString.isPrimitive( new String( 'beep' ) )\n","isString.isObject":"var bool = isString.isObject( new String( 'beep' ) )\nbool = isString.isObject( 'beep' )\n","isStringArray":"var bool = isStringArray( [ 'abc', 'def' ] )\nbool = isStringArray( [ 'abc', 123 ] )\n","isStringArray.primitives":"var arr = [ 'abc', 'def' ];\nvar bool = isStringArray.primitives( arr )\narr = [ 'abc', new String( 'def' ) ];\nbool = isStringArray.primitives( arr )\n","isStringArray.objects":"var arr = [ new String( 'ab' ), new String( 'cd' ) ];\nvar bool = isStringArray.objects( arr )\narr = [ new String( 'abc' ), 'def' ];\nbool = isStringArray.objects( arr )\n","isSymbol":"var bool = isSymbol( Symbol( 'beep' ) )\nbool = isSymbol( Object( Symbol( 'beep' ) ) )\nbool = isSymbol( {} )\nbool = isSymbol( null )\nbool = isSymbol( true )\n","isSymbolArray":"var bool = isSymbolArray( [ Symbol( 'beep' ), Symbol( 'boop' ) ] )\nbool = isSymbolArray( Symbol( 'beep' ) )\nbool = isSymbolArray( [] )\nbool = isSymbolArray( {} )\nbool = isSymbolArray( null )\nbool = isSymbolArray( true )\n","isSymbolArray.primitives":"var bool = isSymbolArray.primitives( [ Symbol( 'beep' ) ] )\nbool = isSymbolArray.primitives( [ Object( Symbol( 'beep' ) ) ] )\nbool = isSymbolArray.primitives( [] )\nbool = isSymbolArray.primitives( {} )\nbool = isSymbolArray.primitives( null )\nbool = isSymbolArray.primitives( true )\n","isSymbolArray.objects":"var bool = isSymbolArray.objects( [ Object( Symbol( 'beep' ) ) ] )\nbool = isSymbolArray.objects( [ Symbol( 'beep' ) ] )\nbool = isSymbolArray.objects( [] )\nbool = isSymbolArray.objects( {} )\nbool = isSymbolArray.objects( null )\nbool = isSymbolArray.objects( true )\n","isSymmetricMatrix":"var buf = [ 0, 1, 1, 2 ];\nvar sh = [ 2, 2 ];\nvar st = [ 2, 1 ];\nvar M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\nvar bool = isSymmetricMatrix( M )\nbool = isSymmetricMatrix( [ 1, 2, 3, 4 ] )\nbool = isSymmetricMatrix( 3.14 )\nbool = isSymmetricMatrix( {} )\n","isSyntaxError":"var bool = isSyntaxError( new SyntaxError( 'beep' ) )\nbool = isSyntaxError( {} )\n","isTriangularNumber":"var bool = isTriangularNumber( 36.0 )\nbool = isTriangularNumber( new Number( 36.0 ) )\nbool = isTriangularNumber( 3.14 )\nbool = isTriangularNumber( -5.0 )\nbool = isTriangularNumber( null )\n","isTriangularNumber.isPrimitive":"var bool = isTriangularNumber.isPrimitive( 36.0 )\nbool = isTriangularNumber.isPrimitive( new Number( 36.0 ) )\n","isTriangularNumber.isObject":"var bool = isTriangularNumber.isObject( 36.0 )\nbool = isTriangularNumber.isObject( new Number( 36.0 ) )\n","isTruthy":"var bool = isTruthy( true )\nbool = isTruthy( {} )\nbool = isTruthy( [] )\nbool = isTruthy( false )\nbool = isTruthy( '' )\nbool = isTruthy( 0 )\nbool = isTruthy( null )\nbool = isTruthy( void 0 )\nbool = isTruthy( NaN )\n","isTruthyArray":"var bool = isTruthyArray( [ {}, [] ] )\nbool = isTruthyArray( [ null, '' ] )\nbool = isTruthyArray( [] )\n","isTypedArray":"var bool = isTypedArray( new Int8Array( 10 ) )\n","isTypedArrayLength":"var bool = isTypedArrayLength( 5 )\nbool = isTypedArrayLength( 2.0e200 )\nbool = isTypedArrayLength( -3.14 )\nbool = isTypedArrayLength( null )\n","isTypedArrayLike":"var bool = isTypedArrayLike( new Int16Array() )\nbool = isTypedArrayLike({\n'length': 10,\n'byteOffset': 0,\n'byteLength': 10,\n'BYTES_PER_ELEMENT': 4\n })\n","isTypeError":"var bool = isTypeError( new TypeError( 'beep' ) )\nbool = isTypeError( {} )\n","isUint8Array":"var bool = isUint8Array( new Uint8Array( 10 ) )\nbool = isUint8Array( [] )\n","isUint8ClampedArray":"var bool = isUint8ClampedArray( new Uint8ClampedArray( 10 ) )\nbool = isUint8ClampedArray( [] )\n","isUint16Array":"var bool = isUint16Array( new Uint16Array( 10 ) )\nbool = isUint16Array( [] )\n","isUint32Array":"var bool = isUint32Array( new Uint32Array( 10 ) )\nbool = isUint32Array( [] )\n","isUNCPath":"var bool = isUNCPath( '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz' )\nbool = isUNCPath( '/foo/bar/baz' )\n","isUndefined":"var bool = isUndefined( void 0 )\nbool = isUndefined( null )\n","isUndefinedOrNull":"var bool = isUndefinedOrNull( void 0 )\nbool = isUndefinedOrNull( null )\nbool = isUndefinedOrNull( false )\n","isUnityProbabilityArray":"var bool = isUnityProbabilityArray( [ 0.25, 0.5, 0.25 ] )\nbool = isUnityProbabilityArray( new Uint8Array( [ 0, 1 ] ) )\nbool = isUnityProbabilityArray( [ 0.4, 0.4, 0.4 ] )\nbool = isUnityProbabilityArray( [ 3.14, 0.0 ] )\n","isUppercase":"var bool = isUppercase( 'HELLO' )\nbool = isUppercase( 'World' )\n","isURI":"var bool = isURI( 'http://google.com' )\nbool = isURI( 'http://localhost/' )\nbool = isURI( 'http://example.w3.org/path%20with%20spaces.html' )\nbool = isURI( 'ftp://ftp.is.co.za/rfc/rfc1808.txt' )\nbool = isURI( '' )\nbool = isURI( 'foo@bar' )\nbool = isURI( '://foo/' )\nbool = isURI( 'http://<foo>' )\nbool = isURI( 'http:////foo.html' )\nbool = isURI( 'http://example.w3.org/%a' )\n","isURIError":"var bool = isURIError( new URIError( 'beep' ) )\nbool = isURIError( {} )\n","isVectorLike":"var M = {};\nM.data = [ 0, 0, 0, 0 ];\nM.ndims = 1;\nM.shape = [ 4 ];\nM.strides = [ 1 ];\nM.offset = 0;\nM.order = 'row-major';\nM.dtype = 'generic';\nM.length = 4;\nM.flags = {};\nM.get = function get( i, j ) {};\nM.set = function set( i, j ) {};\nvar bool = isVectorLike( M )\nbool = isVectorLike( [ 1, 2, 3, 4 ] )\nbool = isVectorLike( 3.14 )\nbool = isVectorLike( {} )\n","isWebAssemblyMemory":"var bool = isWebAssemblyMemory( {} )\n","isWellFormedString":"var bool = isWellFormedString( '' )\nbool = isWellFormedString( new String( '' ) )\nbool = isWellFormedString( '\\uDBFF' )\nbool = isWellFormedString( '\\uDBFFFF\\uDBFF' )\nbool = isWellFormedString( [] )\nbool = isWellFormedString( '-5' )\nbool = isWellFormedString( null )\n","isWellFormedString.isPrimitive":"var bool = isWellFormedString.isPrimitive( '' )\nbool = isWellFormedString.isPrimitive( new String( '' ) )\n","isWellFormedString.isObject":"var bool = isWellFormedString.isObject( '' )\nbool = isWellFormedString.isObject( new String( '' ) )\n","isWhitespace":"var bool = isWhitespace( '       ' )\nbool = isWhitespace( 'abcdef' )\nbool = isWhitespace( '' )\n","isWritableProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = false;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isWritableProperty( obj, 'boop' )\nbool = isWritableProperty( obj, 'beep' )\n","isWritablePropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = false;\ndesc.value = 'beep';\ndefineProperty( obj, 'beep', desc );\nvar bool = isWritablePropertyIn( obj, 'boop' )\nbool = isWritablePropertyIn( obj, 'beep' )\n","isWriteOnlyProperty":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isWriteOnlyProperty( obj, 'boop' )\nbool = isWriteOnlyProperty( obj, 'beep' )\n","isWriteOnlyPropertyIn":"var obj = { 'boop': true };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.set = function setter( v ) { obj.boop = v; };\ndefineProperty( obj, 'beep', desc );\nvar bool = isWriteOnlyPropertyIn( obj, 'boop' )\nbool = isWriteOnlyPropertyIn( obj, 'beep' )\n","iterAbs":"var it = iterAbs( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterAbs2":"var it = iterAbs2( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterAcos":"var it = iterAcos( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcosh":"var it = iterAcosh( random.iterators.uniform( 1.0, 10.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcot":"var it = iterAcot( random.iterators.uniform( -5.0, 5.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcoth":"var it = iterAcoth( random.iterators.uniform( 1.0, 10.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcovercos":"var it = iterAcovercos( random.iterators.uniform( -2.0, 0.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAcoversin":"var it = iterAcoversin( random.iterators.uniform( 0.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAdd":"var it1 = array2iterator( [ 1.0, 2.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nvar it = iterAdd( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterAdvance":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar it = iterAdvance( arr, 4 );\nvar v = it.next().value\nvar bool = it.next().done\n","iterAhavercos":"var it = iterAhavercos( random.iterators.uniform( 0.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAhaversin":"var it = iterAhaversin( random.iterators.uniform( 0.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAny":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar bool = iterAny( arr )\n","iterAnyBy":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nfunction fcn( v ) { return ( v === 1 ); };\nvar bool = iterAnyBy( arr, fcn )\n","iterAsin":"var it = iterAsin( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAsinh":"var it = iterAsinh( random.iterators.uniform( -2.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAtan":"var it = iterAtan( random.iterators.uniform( -2.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAtan2":"var x = random.iterators.uniform( -2.0, 2.0 );\nvar y = random.iterators.uniform( -2.0, 2.0 );\nvar it = iterAtan2( y, x );\nvar r = it.next().value\nr = it.next().value\n","iterAtanh":"var it = iterAtanh( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterator2array":"var opts = { 'iter': 10 };\nvar arr = iterator2array( random.iterators.randu( opts ) )\n","iterator2arrayview":"var it = random.iterators.randu({ 'iter': 10 });\nvar out = new Float64Array( 20 );\nvar arr = iterator2arrayview( it, out, 5, 15 )\n","iterator2arrayviewRight":"var it = random.iterators.randu({ 'iter': 10 });\nvar out = new Float64Array( 20 );\nvar arr = iterator2arrayviewRight( it, out, 5, 15 )\n","iteratorStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar it = random.iterators.randu( opts );\nvar s = iteratorStream( it );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","iteratorStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = iteratorStream.factory( opts );\n","iteratorStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar it = random.iterators.randu( opts );\nvar s = iteratorStream.objectMode( it );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","IteratorSymbol":"var s = IteratorSymbol\n","iterAvercos":"var it = iterAvercos( random.iterators.uniform( -2.0, 0.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterAversin":"var it = iterAversin( random.iterators.uniform( 0.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterawgn":"var src = iterSineWave();\nvar it = iterawgn( src, 0.5 );\nvar v = it.next().value\nv = it.next().value\n","iterawln":"var src = iterSineWave();\nvar it = iterawln( src, 0.5 );\nvar v = it.next().value\nv = it.next().value\n","iterawun":"var src = iterSineWave();\nvar it = iterawun( src, 0.5 );\nvar v = it.next().value\nv = it.next().value\n","iterBartlettHannPulse":"var it = iterBartlettHannPulse();\nvar v = it.next().value\nv = it.next().value\n","iterBartlettPulse":"var it = iterBartlettPulse();\nvar v = it.next().value\nv = it.next().value\n","iterBesselj0":"var it = iterBesselj0( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBesselj1":"var it = iterBesselj1( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBessely0":"var it = iterBessely0( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBessely1":"var it = iterBessely1( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterBeta":"var x = random.iterators.uniform( 0.0, 2.0 );\nvar y = random.iterators.uniform( 0.0, 2.0 );\nvar it = iterBeta( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterBetaln":"var x = random.iterators.uniform( 0.0, 2.0 );\nvar y = random.iterators.uniform( 0.0, 2.0 );\nvar it = iterBetaln( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterBinet":"var it = iterBinet( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCbrt":"var it = iterCbrt( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCeil":"var it = iterCeil( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCeil2":"var it = iterCeil2( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCeil10":"var it = iterCeil10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterCompositesSeq":"var it = iterCompositesSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterConcat":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = array2iterator( [ 3, 4 ] );\nvar it = iterConcat( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterConstant":"var it = iterConstant( 3.14 );\nvar v = it.next().value\nv = it.next().value\n","iterContinuedFraction":"var terms = array2iterator( [ 3, 4, 12, 4 ] );\nvar v = iterContinuedFraction( terms )\n","iterContinuedFractionSeq":"var it = iterContinuedFractionSeq( 3.245 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\nit = iterContinuedFractionSeq( 3.245, { 'returns': 'convergents' } );\nv = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nbool = it.next().done\n","iterCos":"var it = iterCos( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCosh":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterCosh( r );\nvar v = it.next().value\nv = it.next().value\n","iterCosineWave":"var it = iterCosineWave();\nvar v = it.next().value\nv = it.next().value\n","iterCosm1":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterCosm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterCospi":"var it = iterCospi( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterCounter":"var it = iterCounter( random.iterators.randu() );\nvar v = it.next().value\nv = it.next().value\n","iterCovercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterCovercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterCoversin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterCoversin( r );\nvar v = it.next().value\nv = it.next().value\n","iterCubesSeq":"var it = iterCubesSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","itercugmean":"var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\nvar it = itercugmean( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itercuhmean":"var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\nvar it = itercuhmean( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itercumax":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumax( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumaxabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumaxabs( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumean":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumean( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumeanabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumeanabs( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumeanabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumeanabs2( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercumidrange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumidrange( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itercumin":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercumin( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercuminabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercuminabs( arr );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itercuprod":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercuprod( arr );\nvar p = it.next().value\np = it.next().value\np = it.next().value\np = it.next().value\n","itercurange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercurange( arr );\nvar r = it.next().value\nr = it.next().value\nr = it.next().value\nr = it.next().value\n","itercusum":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercusum( arr );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itercusumabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercusumabs( arr );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itercusumabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itercusumabs2( arr );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","iterDatespace":"var t1 = new Date();\nvar it = iterDatespace( t1, new Date( t1.getTime()+86400000 ) );\nvar v = it.next().value\nv = it.next().value\n","iterDedupe":"var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\nvar it = iterDedupe( arr );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterDedupeBy":"var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\nfunction fcn( v ) { return v; };\nvar it = iterDedupeBy( arr, fcn );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterDeg2rad":"var r = random.iterators.uniform( -360.0, 360.0 );\nvar it = iterDeg2rad( r );\nvar v = it.next().value\nv = it.next().value\n","iterDigamma":"var r = random.iterators.uniform( 0.01, 5.0 );\nvar it = iterDigamma( r );\nvar v = it.next().value\nv = it.next().value\n","iterDiracComb":"var it = iterDiracComb();\nvar v = it.next().value\nv = it.next().value\n","iterDiracDelta":"var it = iterDiracDelta( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterDivide":"var it1 = array2iterator( [ 3.0, 2.0 ] );\nvar it2 = array2iterator( [ 1.0, 4.0 ] );\nvar it = iterDivide( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterDoWhileEach":"function predicate( v ) { return v === v };\nfunction f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterDoWhileEach( random.iterators.randu(), predicate, f );\nvar r = it.next().value\nr = it.next().value\n","iterEllipe":"var r = random.iterators.uniform( -1.0, 1.0 );\nvar it = iterEllipe( r );\nvar v = it.next().value\nv = it.next().value\n","iterEllipk":"var r = random.iterators.uniform( -1.0, 1.0 );\nvar it = iterEllipk( r );\nvar v = it.next().value\nv = it.next().value\n","iterEmpty":"var it = iterEmpty();\nvar bool = it.next().done\n","iterErf":"var it = iterErf( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterErfc":"var it = iterErfc( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterErfcinv":"var it = iterErfcinv( random.iterators.uniform( 0.0, 2.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterErfinv":"var it = iterErfinv( random.iterators.uniform( -1.0, 1.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterEta":"var it = iterEta( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterEvenIntegersSeq":"var it = iterEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterEvery":"var arr = array2iterator( [ 1, 1, 1, 1, 0 ] );\nvar bool = iterEvery( arr )\n","iterEveryBy":"var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\nfunction fcn( v ) { return ( v > 0 ); };\nvar bool = iterEveryBy( arr, fcn )\n","iterExp":"var it = iterExp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterExp2":"var r = random.iterators.uniform( -50.0, 50.0 );\nvar it = iterExp2( r );\nvar v = it.next().value\nv = it.next().value\n","iterExp10":"var r = random.iterators.uniform( -50.0, 50.0 );\nvar it = iterExp10( r );\nvar v = it.next().value\nv = it.next().value\n","iterExpit":"var r = random.iterators.uniform( 0.0, 1.0 );\nvar it = iterExpit( r );\nvar v = it.next().value\nv = it.next().value\n","iterExpm1":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterExpm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterExpm1rel":"var r = random.iterators.uniform( -50.0, 50.0 );\nvar it = iterExpm1rel( r );\nvar v = it.next().value\nv = it.next().value\n","iterFactorial":"var it = iterFactorial( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterFactorialln":"var it = iterFactorialln( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterFactorialsSeq":"var it = iterFactorialsSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterFibonacciSeq":"var it = iterFibonacciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterFifthPowersSeq":"var it = iterFifthPowersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterFill":"var it = iterFill( random.iterators.randu(), 3.14, 0, 2 );\nvar r = it.next().value\nr = it.next().value\nr = it.next().value\n","iterFilter":"function f( v ) { return ( v > 2 ); };\nvar it1 = array2iterator( [ 1, 3, 2, 4 ] );\nvar it2 = iterFilter( it1, f );\nvar v = it2.next().value\nv = it2.next().value\n","iterFilterMap":"function f( v ) { if ( v > 2 ) { return v * 10 }; };\nvar it1 = array2iterator( [ 1, 3, 2, 4 ] );\nvar it2 = iterFilterMap( it1, f );\nvar v = it2.next().value\nv = it2.next().value\n","iterFirst":"var arr = array2iterator( [ 1, 0, 0, 0, 0 ] );\nvar v = iterFirst( arr )\n","iterFlatTopPulse":"var it = iterFlatTopPulse();\nvar v = it.next().value\nv = it.next().value\n","iterFloor":"var it = iterFloor( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterFloor2":"var it = iterFloor2( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterFloor10":"var it = iterFloor10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterFlow":"var o = {};\no.head = iterHead;\no.some = iterSome;\nvar fiter = iterFlow( o )\n","iterForEach":"function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterForEach( random.iterators.randu(), f );\nvar r = it.next().value\nr = it.next().value\n","iterFourthPowersSeq":"var it = iterFourthPowersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterFresnelc":"var r = random.iterators.uniform( 0.0, 10.0 );\nvar it = iterFresnelc( r );\nvar v = it.next().value\nv = it.next().value\n","iterFresnels":"var r = random.iterators.uniform( 0.0, 10.0 );\nvar it = iterFresnels( r );\nvar v = it.next().value\nv = it.next().value\n","iterGamma":"var it = iterGamma( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterGamma1pm1":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterGamma1pm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterGammaln":"var it = iterGammaln( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterHacovercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHacovercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterHacoversin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHacoversin( r );\nvar v = it.next().value\nv = it.next().value\n","iterHannPulse":"var it = iterHannPulse();\nvar v = it.next().value\nv = it.next().value\n","iterHavercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHavercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterHaversin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterHaversin( r );\nvar v = it.next().value\nv = it.next().value\n","iterHead":"var it = iterHead( random.iterators.randu(), 5 );\nvar r = it.next().value\nr = it.next().value\n","iterIncrspace":"var it = iterIncrspace( 0, 101, 2 );\nvar v = it.next().value\nv = it.next().value\n","iterIntegersSeq":"var it = iterIntegersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterIntersection":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\nvar it = iterIntersection( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterIntersectionByHash":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\nfunction f( v ) { return v.toString(); };\nvar it = iterIntersectionByHash( it1, it2, f );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterInv":"var it = iterInv( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLanczosPulse":"var it = iterLanczosPulse();\nvar v = it.next().value\nv = it.next().value\n","iterLast":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar v = iterLast( arr )\n","iterLength":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar len = iterLength( arr )\n","iterLinspace":"var it = iterLinspace( 0, 99, 100 );\nvar v = it.next().value\nv = it.next().value\n","iterLn":"var it = iterLn( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog":"var x = random.iterators.uniform( 0.0, 100.0 );\nvar y = random.iterators.uniform( 0.0, 10.0 );\nvar it = iterLog( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterLog1mexp":"var it = iterLog1mexp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog1p":"var it = iterLog1p( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog1pexp":"var it = iterLog1pexp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog2":"var it = iterLog2( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLog10":"var it = iterLog10( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterLogit":"var r = random.iterators.uniform( 0.0, 1.0 );\nvar it = iterLogit( r );\nvar v = it.next().value\nv = it.next().value\n","iterLogspace":"var it = iterLogspace( 0, 3, 4 );\nvar v = it.next().value\nv = it.next().value\n","iterLucasSeq":"var it = iterLucasSeq();\nvar v = it.next().value\nv = it.next().value\n","iterMap":"function f( v ) { return v * 10.0; };\nvar it = iterMap( random.iterators.randu(), f );\nvar r = it.next().value\nr = it.next().value\n","iterMapN":"var it1 = array2iterator( [ 1.0, 2.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nfunction fcn( x, y ) { return x + y; };\nvar it = iterMapN( it1, it2, fcn );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","itermax":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar m = itermax( arr )\n","itermaxabs":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar m = itermaxabs( arr )\n","itermean":"var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar m = itermean( arr )\n","itermeanabs":"var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\nvar m = itermeanabs( arr )\n","itermeanabs2":"var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\nvar m = itermeanabs2( arr )\n","itermidrange":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar v = itermidrange( arr )\n","itermin":"var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\nvar m = itermin( arr )\n","iterminabs":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar m = iterminabs( arr )\n","itermmax":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmax( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmaxabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmaxabs( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmean":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmean( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmeanabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmeanabs( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmeanabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmeanabs2( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermmidrange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmidrange( arr, 3 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\n","itermmin":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermmin( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermminabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermminabs( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","iterMod":"var it1 = array2iterator( [ 3.0, 2.0 ] );\nvar it2 = array2iterator( [ 1.0, 4.0 ] );\nvar it = iterMod( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","itermprod":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermprod( arr, 3 );\nvar p = it.next().value\np = it.next().value\np = it.next().value\np = it.next().value\n","itermrange":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermrange( arr, 3 );\nvar m = it.next().value\nm = it.next().value\nm = it.next().value\nm = it.next().value\n","itermsum":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermsum( arr, 3 );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itermsumabs":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermsumabs( arr, 3 );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","itermsumabs2":"var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\nvar it = itermsumabs2( arr, 3 );\nvar s = it.next().value\ns = it.next().value\ns = it.next().value\ns = it.next().value\n","iterMultiply":"var it1 = array2iterator( [ 1.0, 2.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nvar it = iterMultiply( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterNegaFibonacciSeq":"var it = iterNegaFibonacciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegaLucasSeq":"var it = iterNegaLucasSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegativeEvenIntegersSeq":"var it = iterNegativeEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegativeIntegersSeq":"var it = iterNegativeIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNegativeOddIntegersSeq":"var it = iterNegativeOddIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNone":"var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\nvar bool = iterNone( arr )\n","iterNoneBy":"var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\nfunction fcn( v ) { return ( v <= 0 ); };\nvar bool = iterNoneBy( arr, fcn )\n","iterNonFibonacciSeq":"var it = iterNonFibonacciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonNegativeEvenIntegersSeq":"var it = iterNonNegativeEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonNegativeIntegersSeq":"var it = iterNonNegativeIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonPositiveEvenIntegersSeq":"var it = iterNonPositiveEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonPositiveIntegersSeq":"var it = iterNonPositiveIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterNonSquaresSeq":"var it = iterNonSquaresSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterNth":"var arr = array2iterator( [ 0, 0, 1, 0, 0 ] );\nvar v = iterNth( arr, 3 )\n","iterOddIntegersSeq":"var it = iterOddIntegersSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterPeriodicSinc":"var it = iterPeriodicSinc( 7 );\nvar v = it.next().value\nv = it.next().value\n","iterPipeline":"var it1 = iterThunk( iterHead, 100 );\nfunction f( r ) { return ( r > 0.95 ); };\nvar it2 = iterThunk( iterSomeBy, 5, f );\nvar p = iterPipeline( it1, it2 );\nvar bool = p( random.iterators.randu() )\n","iterPop":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterPop( it1 );\nvar v = it2.next().value\nvar bool = it2.next().done\n","iterPositiveEvenIntegersSeq":"var it = iterPositiveEvenIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterPositiveIntegersSeq":"var it = iterPositiveIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterPositiveOddIntegersSeq":"var it = iterPositiveOddIntegersSeq();\nvar v = it.next().value\nv = it.next().value\n","iterPow":"var x = random.iterators.uniform( 0.0, 2.0 );\nvar y = random.iterators.uniform( -2.0, 2.0 );\nvar it = iterPow( x, y );\nvar r = it.next().value\nr = it.next().value\n","iterPrimesSeq":"var it = iterPrimesSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterprod":"var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar s = iterprod( arr )\n","iterPulse":"var it = iterPulse();\nvar v = it.next().value\nv = it.next().value\n","iterPush":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterPush( it1, 3, 4 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterRad2deg":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterRad2deg( r );\nvar v = it.next().value\nv = it.next().value\n","iterRamp":"var it = iterRamp( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterrange":"var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar v = iterrange( arr )\n","iterReject":"function f( v ) { return ( v > 2 ); };\nvar it1 = array2iterator( [ 1, 3, 2, 4 ] );\nvar it2 = iterReject( it1, f );\nvar v = it2.next().value\nv = it2.next().value\n","iterReplicate":"var it1 = array2iterator( [ 1, 2, 3, 4 ] );\nvar it2 = iterReplicate( it1, 2 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\n","iterReplicateBy":"var it1 = array2iterator( [ 1, 2, 3, 4 ] );\nfunction f( v, i ) { return i + 1; };\nvar it2 = iterReplicateBy( it1, f );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\n","iterRound":"var it = iterRound( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterRound2":"var it = iterRound2( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterRound10":"var it = iterRound10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterRsqrt":"var it = iterRsqrt( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSawtoothWave":"var it = iterSawtoothWave();\nvar v = it.next().value\nv = it.next().value\n","iterShift":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterShift( it1 );\nvar v = it2.next().value\nvar bool = it2.next().done\n","iterSignum":"var it = iterSignum( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSin":"var it = iterSin( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSinc":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterSinc( r );\nvar v = it.next().value\nv = it.next().value\n","iterSineWave":"var it = iterSineWave();\nvar v = it.next().value\nv = it.next().value\n","iterSinh":"var r = random.iterators.uniform( -5.0, 5.0 );\nvar it = iterSinh( r );\nvar v = it.next().value\nv = it.next().value\n","iterSinpi":"var it = iterSinpi( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSlice":"var it = iterSlice( random.iterators.randu(), 5, 10 );\nvar r = it.next().value\nr = it.next().value\n","iterSome":"var arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\nvar bool = iterSome( arr, 3 )\n","iterSomeBy":"var arr = array2iterator( [ 1, 1, 0, 0, 1 ] );\nfunction fcn( v ) { return ( v > 0 ); };\nvar bool = iterSomeBy( arr, 3, fcn )\n","iterSpence":"var r = random.iterators.uniform( 0.0, 100.0 );\nvar it = iterSpence( r );\nvar v = it.next().value\nv = it.next().value\n","iterSqrt":"var it = iterSqrt( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterSqrt1pm1":"var r = random.iterators.uniform( 0.0, 100.0 );\nvar it = iterSqrt1pm1( r );\nvar v = it.next().value\nv = it.next().value\n","iterSquaredTriangularSeq":"var it = iterSquaredTriangularSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterSquaresSeq":"var it = iterSquaresSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterSquareWave":"var it = iterSquareWave();\nvar v = it.next().value\nv = it.next().value\n","iterstdev":"var arr = array2iterator( [ 2.0, -5.0 ] );\nvar m = iterstdev( arr )\n","iterStep":"var it = iterStep( 0, 2, 10 );\nvar v = it.next().value\nv = it.next().value\n","iterStrided":"var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\nvar it = iterStrided( arr, 2, 1 );\nvar r = it.next().value\nr = it.next().value\n","iterStridedBy":"var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\nfunction stride( v, i ) { return (i % 10)+1; };\nvar it = iterStridedBy( arr, stride );\nvar r = it.next().value\nr = it.next().value\nr = it.next().value\n","iterSubtract":"var it1 = array2iterator( [ 1.0, 5.0 ] );\nvar it2 = array2iterator( [ 3.0, 4.0 ] );\nvar it = iterSubtract( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","itersum":"var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar s = itersum( arr )\n","itersumabs":"var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\nvar s = itersumabs( arr )\n","itersumabs2":"var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\nvar s = itersumabs2( arr )\n","iterTan":"var r = random.iterators.uniform( -1.57, 1.57 );\nvar it = iterTan( r );\nvar v = it.next().value\nv = it.next().value\n","iterTanh":"var r = random.iterators.uniform( -4.0, 4.0 );\nvar it = iterTanh( r );\nvar v = it.next().value\nv = it.next().value\n","iterThunk":"var fcn = iterThunk( iterSome, 3 );\nvar arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\nvar bool = fcn( arr )\n","iterTriangleWave":"var it = iterTriangleWave();\nvar v = it.next().value\nv = it.next().value\n","iterTriangularSeq":"var it = iterTriangularSeq();\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\n","iterTribonnaciSeq":"var it = iterTribonnaciSeq();\nvar v = it.next().value\nv = it.next().value\n","iterTrigamma":"var r = random.iterators.uniform( 0.01, 50.0 );\nvar it = iterTrigamma( r );\nvar v = it.next().value\nv = it.next().value\n","iterTrunc":"var it = iterTrunc( random.iterators.randu() );\nvar r = it.next().value\nr = it.next().value\n","iterTrunc2":"var it = iterTrunc2( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterTrunc10":"var it = iterTrunc10( random.iterators.uniform( -100.0, 100.0 ) );\nvar r = it.next().value\nr = it.next().value\n","iterUnion":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\nvar it = iterUnion( it1, it2 );\nvar v = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nv = it.next().value\nvar bool = it.next().done\n","iterUnique":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nvar it2 = iterUnique( it1 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUniqueBy":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nfunction f( a, b ) { return ( a !== b ); };\nvar it2 = iterUniqueBy( it1, f );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUniqueByHash":"var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\nfunction f( v ) { return v.toString(); };\nvar it2 = iterUniqueByHash( it1, f );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUnitspace":"var it = iterUnitspace( 0, 99 );\nvar v = it.next().value\nv = it.next().value\n","iterUnshift":"var it1 = array2iterator( [ 1, 2 ] );\nvar it2 = iterUnshift( it1, 3, 4 );\nvar v = it2.next().value\nv = it2.next().value\nv = it2.next().value\nv = it2.next().value\nvar bool = it2.next().done\n","iterUntilEach":"function predicate( v ) { return v !== v };\nfunction f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterUntilEach( random.iterators.randu(), predicate, f );\nvar r = it.next().value\nr = it.next().value\n","itervariance":"var arr = array2iterator( [ 2.0, -5.0 ] );\nvar s2 = itervariance( arr )\n","iterVercos":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterVercos( r );\nvar v = it.next().value\nv = it.next().value\n","iterVersin":"var r = random.iterators.uniform( 0.0, 6.28 );\nvar it = iterVersin( r );\nvar v = it.next().value\nv = it.next().value\n","iterWhileEach":"function predicate( v ) { return v === v };\nfunction f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\nvar it = iterWhileEach( random.iterators.randu(), predicate, f );\nvar r = it.next().value\nr = it.next().value\n","iterZeta":"var r = random.iterators.uniform( 1.1, 50.0 );\nvar it = iterZeta( r );\nvar v = it.next().value\nv = it.next().value\n","joinStream":"var s = joinStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","joinStream.factory":"var opts = { 'highWaterMark': 64 };\nvar createStream = joinStream.factory( opts );\nvar s = createStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","joinStream.objectMode":"var s = joinStream.objectMode();\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","kde2d":"var x = [ 1, 3, 5, 6, 21, 23, 16, 17, 20, 10 ];\nvar y = [ 0.40, 0.20, 0.20, 0.15, 0.05, 0.55, 0.6, 0.33, 0.8, 0.41 ];\nvar out = kde2d( x, y )\n","kebabcase":"var out = kebabcase( 'Hello World!' )\nout = kebabcase( 'I am a tiny little teapot' )\n","keyBy":"function toKey( v ) { return v.a; };\nvar arr = [ { 'a': 1 }, { 'a': 2 } ];\nkeyBy( arr, toKey )\n","keyByRight":"function toKey( v ) { return v.a; };\nvar arr = [ { 'a': 1 }, { 'a': 2 } ];\nkeyByRight( arr, toKey )\n","keysIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = keysIn( obj )\n","kruskalTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = kruskalTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = kruskalTest( arr, { 'groups': groups } )\n","kstest":"var rnorm = base.random.normal.factory({ 'seed': 4839 } );\nvar x = new Array( 100 );\nfor ( var i = 0; i < 100; i++ ) { x[ i ] = rnorm( 3.0, 1.0 ); }\nvar out = kstest( x, 'normal', 0.0, 1.0 )\nout = kstest( x, 'normal', 3.0, 1.0 )\nrunif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } )\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\nout = kstest( x, 'uniform', 0.0, 1.0 )\nout.print()\nout = kstest( x, 'uniform', 0.0, 1.0, { 'alpha': 0.1 } )\nrunif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } );\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\nout = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'less' } )\nout = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'greater' } )\nx = [ 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 ];\nout = kstest( x, 'uniform', 0.0, 1.0, { 'sorted': true } )\n","last":"var out = last( 'beep' )\nout = last( 'Boop', 2 )\nout = last( 'foo bar', 3 )\n","leveneTest":"var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\nvar y = [ 3.8, 2.7, 4.0, 2.4 ];\nvar z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\nvar out = leveneTest( x, y, z )\nvar arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n 3.8, 2.7, 4.0, 2.4,\n 2.8, 3.4, 3.7, 2.2, 2.0\n ];\nvar groups = [\n 'a', 'a', 'a', 'a', 'a',\n 'b', 'b', 'b', 'b',\n 'c', 'c', 'c', 'c', 'c'\n ];\nout = leveneTest( arr, { 'groups': groups } )\n","LinkedList":"var list = LinkedList();\nlist.push( 'foo' ).push( 'bar' );\nlist.length\nlist.pop()\nlist.length\nlist.pop()\nlist.length\n","linspace":"var arr = linspace( 0.0, 100.0, 6 )\narr = linspace( 0.0, 100.0, 5, { 'endpoint': false } )\narr = linspace( 0.0, 100.0, 6, { 'dtype': 'generic' } )\n","linspace.assign":"var arr = [ 0, 0, 0, 0, 0, 0 ];\nvar out = linspace.assign( 0, 100, arr )\nvar bool = ( arr === out )\narr = [ 0, 0, 0, 0, 0 ];\nout = linspace.assign( 0, 100, arr, { 'endpoint': false } )\n","LIU_NEGATIVE_OPINION_WORDS_EN":"var list = LIU_NEGATIVE_OPINION_WORDS_EN()\n","LIU_POSITIVE_OPINION_WORDS_EN":"var list = LIU_POSITIVE_OPINION_WORDS_EN()\n","LN_HALF":"LN_HALF\n","LN_PI":"LN_PI\n","LN_SQRT_TWO_PI":"LN_SQRT_TWO_PI\n","LN_TWO_PI":"LN_TWO_PI\n","LN2":"LN2\n","LN10":"LN10\n","LOG2E":"LOG2E\n","LOG10E":"LOG10E\n","logspace":"var arr = logspace( 0, 2, 6 )\n","lowercase":"var out = lowercase( 'bEEp' )\n","lowercaseKeys":"var obj = { 'A': 1, 'B': 2 };\nvar out = lowercaseKeys( obj )\n","lowess":"var x = new Float64Array( 100 );\nvar y = new Float64Array( x.length );\nfor ( var i = 0; i < x.length; i++ ) {\n x[ i ] = i;\n y[ i ] = ( 0.5*i ) + ( 10.0*base.random.randn() );\n }\nvar out = lowess( x, y );\nvar yhat = out.y;\nvar h = Plot( [ x, x ], [ y, yhat ] );\nh.lineStyle = [ 'none', '-' ];\nh.symbols = [ 'closed-circle', 'none' ];\nh.view( 'window' );\n","lpad":"var out = lpad( 'a', 5 )\nout = lpad( 'beep', 10, 'b' )\nout = lpad( 'boop', 12, 'beep' )\n","ltrim":"var out = ltrim( ' \\r\\n\\t  Beep \\t\\t\\n  ' )\n","ltrimN":"var out = ltrimN( '  abc  ', 2 )\nvar out = ltrimN( '!!!abc!!!', 2, '!' )\n","MALE_FIRST_NAMES_EN":"var list = MALE_FIRST_NAMES_EN()\n","map":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = map( arr, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = map( arr, f );\nvar v = out.get( 1, 1 )\n","map.assign":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmap.assign( arr, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\narr = array( arr, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmap.assign( arr, out, f );\nvar v = out.get( 1, 1 )\n","map2":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = map2( x, y, f )\nx = array( x, { 'shape': [ 2, 3 ] } );\ny = array( y, { 'shape': [ 2, 3 ] } );\nout = map2( x, y, f );\nvar v = out.get( 1, 1 )\n","map2.assign":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmap2.assign( x, y, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\nx = array( x, opts );\ny = array( y, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmap2.assign( x, y, out, f );\nvar v = out.get( 1, 1 )\n","map2d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ -1, -2, -3 ], [ -4, -5, -6 ] ];\nvar out = map2d( arr, f );\nout[ 0 ]\nout[ 1 ]\n","map2Right":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = map2Right( x, y, f )\nx = array( x, { 'shape': [ 2, 3 ] } );\ny = array( y, { 'shape': [ 2, 3 ] } );\nout = map2Right( x, y, f );\nvar v = out.get( 1, 1 )\n","map2Right.assign":"var f = naryFunction( base.add, 2 );\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar y = [ 1, 1, 1, 1, 1, 1 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmap2Right.assign( x, y, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\nx = array( x, opts );\ny = array( y, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmap2Right.assign( x, y, out, f );\nvar v = out.get( 1, 1 )\n","map3d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ [ -1, -2, -3 ] ], [ [ -4, -5, -6 ] ] ];\nvar out = map3d( arr, f );\nout[ 0 ][ 0 ]\nout[ 1 ][ 0 ]\n","map4d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ [ [ -1, -2, -3 ] ] ], [ [ [ -4, -5, -6 ] ] ] ];\nvar out = map4d( arr, f );\nout[ 0 ][ 0 ][ 0 ]\nout[ 1 ][ 0 ][ 0 ]\n","map5d":"var f = naryFunction( base.abs, 1 );\nvar arr = [ [ [ [ [ -1, -2, -3 ] ] ] ], [ [ [ [ -4, -5, -6 ] ] ] ] ];\nvar out = map5d( arr, f );\nout[ 0 ][ 0 ][ 0 ][ 0 ]\nout[ 1 ][ 0 ][ 0 ][ 0 ]\n","mapArguments":"function foo( a, b, c ) { return [ a, b, c ]; };\nfunction clbk( v ) { return v * 2; };\nvar bar = mapArguments( foo, clbk );\nvar out = bar( 1, 2, 3 )\n","mapFun":"function fcn( i ) { return i; };\nvar arr = mapFun( fcn, 5 )\n","mapFunAsync":"function fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n     next( null, i );\n }\n };\nfunction done( error, arr ) {\n if ( error ) {\n     throw error;\n }\n console.log( arr );\n };\nmapFunAsync( fcn, 10, done )\nfunction fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n     next( null, i );\n }\n };\nfunction done( error, arr ) {\n if ( error ) {\n     throw error;\n }\n console.log( arr );\n };\nvar opts = { 'limit': 2 };\nmapFunAsync( fcn, 10, opts, done )\nfunction fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n     next( null, i );\n }\n };\nfunction done( error, arr ) {\n if ( error ) {\n     throw error;\n }\n console.log( arr );\n };\nvar opts = { 'series': true };\nmapFunAsync( fcn, 10, opts, done )\n","mapFunAsync.factory":"function fcn( i, next ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n     next( null, i );\n }\n };\nvar opts = { 'series': true };\nvar f = mapFunAsync.factory( opts, fcn );\nfunction done( error, arr ) {\n if ( error ) {\n     throw error;\n }\n console.log( arr );\n };\nf( 10, done )\n","mapKeys":"function transform( key, value ) { return key + value; };\nvar obj = { 'a': 1, 'b': 2 };\nvar out = mapKeys( obj, transform )\n","mapKeysAsync":"function transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n     throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2 };\nmapKeysAsync( obj, transform, done )\nfunction transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n     throw error;\n }\n console.log( out );\n };\nvar opts = { 'limit': 2 };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapKeysAsync( obj, opts, transform, done )\nfunction transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n     throw error;\n }\n console.log( out );\n };\nvar opts = { 'series': true };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapKeysAsync( obj, opts, transform, done )\n","mapKeysAsync.factory":"function transform( key, value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     next( null, key+':'+value );\n }\n };\nvar opts = { 'series': true };\nvar f = mapKeysAsync.factory( opts, transform );\nfunction done( error, out ) {\n if ( error ) {\n     throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nf( obj, done )\nobj = { 'beep': 'boop' };\nf( obj, done )\n","mapReduce":"var f1 = naryFunction( base.abs, 1 );\nvar f2 = naryFunction( base.add, 2 );\nvar arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\nvar out = mapReduce( arr, 0.0, f1, f2 )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = mapReduce( arr, 0.0, f1, f2 )\n","mapReduceRight":"var f1 = naryFunction( base.abs, 1 );\nvar f2 = naryFunction( base.add, 2 );\nvar arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\nvar out = mapReduceRight( arr, 0.0, f1, f2 )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = mapReduceRight( arr, 0.0, f1, f2 )\n","mapRight":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = mapRight( arr, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = mapRight( arr, f );\nvar v = out.get( 1, 1 )\n","mapRight.assign":"var f = naryFunction( base.abs, 1 );\nvar arr = [ -1, -2, -3, -4, -5, -6 ];\nvar out = [ 0, 0, 0, 0, 0, 0 ];\nmapRight.assign( arr, out, f );\nout\nvar opts = { 'shape': [ 2, 3 ] };\narr = array( arr, opts );\nout = array( [ 0, 0, 0, 0, 0, 0 ], opts );\nmapRight.assign( arr, out, f );\nvar v = out.get( 1, 1 )\n","mapValues":"function transform( value, key ) { return key + value; };\nvar obj = { 'a': 1, 'b': 2 };\nvar out = mapValues( obj, transform )\n","mapValuesAsync":"function transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n     throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2 };\nmapValuesAsync( obj, transform, done )\nfunction transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n     throw error;\n }\n console.log( out );\n };\nvar opts = { 'limit': 2 };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapValuesAsync( obj, opts, transform, done )\nfunction transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     next( null, key+':'+value );\n }\n };\nfunction done( error, out ) {\n if ( error ) {\n     throw error;\n }\n console.log( out );\n };\nvar opts = { 'series': true };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nmapValuesAsync( obj, opts, transform, done )\n","mapValuesAsync.factory":"function transform( value, key, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     next( null, key+':'+value );\n }\n };\nvar opts = { 'series': true };\nvar f = mapValuesAsync.factory( opts, transform );\nfunction done( error, out ) {\n if ( error ) {\n     throw error;\n }\n console.log( out );\n };\nvar obj = { 'a': 1, 'b': 2, 'c': 3 };\nf( obj, done )\nobj = { 'beep': 'boop' };\nf( obj, done )\n","maskArguments":"function foo( a, b ) { return [ a, b ]; };\nvar bar = maskArguments( foo, [ 1, 0, 1 ] );\nvar out = bar( 1, 2, 3 )\n","MAX_ARRAY_LENGTH":"MAX_ARRAY_LENGTH\n","MAX_TYPED_ARRAY_LENGTH":"MAX_TYPED_ARRAY_LENGTH\n","maybeBroadcastArray":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = maybeBroadcastArray( x, [ 3, 2, 2 ] )\nsh = y.shape\nvar v = y.get( 0, 0, 0 )\nv = y.get( 0, 0, 1 )\nv = y.get( 0, 1, 0 )\nv = y.get( 0, 1, 1 )\nv = y.get( 1, 0, 0 )\nv = y.get( 1, 1, 0 )\nv = y.get( 2, 0, 0 )\nv = y.get( 2, 1, 1 )\n","maybeBroadcastArrays":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nvar sh = x.shape\nvar y = ndzeros( [ 3, 2, 2 ] )\nvar out = maybeBroadcastArrays( [ x, y ] )\nvar bx = out[ 0 ]\nsh = bx.shape\nvar v = bx.get( 0, 0, 0 )\nv = bx.get( 0, 0, 1 )\nv = bx.get( 0, 1, 0 )\nv = bx.get( 0, 1, 1 )\nv = bx.get( 1, 0, 0 )\nv = bx.get( 1, 1, 0 )\nv = bx.get( 2, 0, 0 )\nv = bx.get( 2, 1, 1 )\n","memoize":"function factorial( n ) {\n var prod;\n var i;\n prod = 1;\n for ( i = n; i > 1; i-- ) {\n     prod *= i;\n }\n return prod;\n };\nvar memoized = memoize( factorial );\nvar v = memoized( 5 )\nv = memoized( 5 )\n","merge":"var target = { 'a': 'beep' };\nvar source = { 'a': 'boop', 'b': 'bap' };\nvar out = merge( target, source )\nvar bool = ( out === target )\n","merge.factory":"var opts = {\n 'level': 100,\n 'copy': true,\n 'override': true,\n 'extend': true\n };\nvar merge = merge.factory( opts )\nmerge = merge.factory( { 'level': 2 } );\nvar target = {\n '1': { 'a': 'beep', '2': { '3': null, 'b': [ 5, 6, 7 ] } }\n };\nvar source = {\n '1': { 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } }\n };\nvar out = merge( target, source )\nmerge = merge.factory( { 'copy': false } );\ntarget = {};\nsource = { 'a': [ 1, 2, 3 ] };\nout = merge( target, source );\nvar bool = ( out.a === source.a )\nmerge = merge.factory( { 'override': false } );\ntarget = { 'a': 'beep', 'b': 'boop' };\nsource = { 'a': null, 'c': 'bop' };\nout = merge( target, source )\nfunction strategy( a, b, key ) {\n // a => target value\n // b => source value\n // key => object key\n if ( key === 'a' ) {\n     return b;\n }\n if ( key === 'b' ) {\n     return a;\n }\n return 'bebop';\n };\nmerge = merge.factory( { 'override': strategy } );\ntarget = { 'a': 'beep', 'b': 'boop', 'c': 1234 };\nsource = { 'a': null, 'b': {}, 'c': 'bop' };\nout = merge( target, source )\nmerge = merge.factory( { 'extend': false } );\ntarget = { 'a': 'beep', 'b': 'boop' };\nsource = { 'b': 'hello', 'c': 'world' };\nout = merge( target, source )\n","MILLISECONDS_IN_DAY":"var days = 3.14;\nvar ms = days * MILLISECONDS_IN_DAY\n","MILLISECONDS_IN_HOUR":"var hrs = 3.14;\nvar ms = hrs * MILLISECONDS_IN_HOUR\n","MILLISECONDS_IN_MINUTE":"var mins = 3.14;\nvar ms = mins * MILLISECONDS_IN_MINUTE\n","MILLISECONDS_IN_SECOND":"var secs = 3.14;\nvar ms = secs * MILLISECONDS_IN_SECOND\n","MILLISECONDS_IN_WEEK":"var weeks = 3.14;\nvar ms = weeks * MILLISECONDS_IN_WEEK\n","MINARD_NAPOLEONS_MARCH":"var data = MINARD_NAPOLEONS_MARCH();\nvar army = data.army\nvar cities = data.cities\nvar labels = data.labels\nvar river = data.river\nvar t = data.temperature\n","MINUTES_IN_DAY":"var days = 3.14;\nvar mins = days * MINUTES_IN_DAY\n","MINUTES_IN_HOUR":"var hrs = 3.14;\nvar mins = hrs * MINUTES_IN_HOUR\n","MINUTES_IN_WEEK":"var wks = 3.14;\nvar mins = wks * MINUTES_IN_WEEK\n","minutesInMonth":"var num = minutesInMonth()\nnum = minutesInMonth( 2 )\nnum = minutesInMonth( 2, 2016 )\nnum = minutesInMonth( 2, 2017 )\nnum = minutesInMonth( 'feb', 2016 )\nnum = minutesInMonth( 'february', 2016 )\n","minutesInYear":"var num = minutesInYear()\nnum = minutesInYear( 2016 )\nnum = minutesInYear( 2017 )\n","MOBY_DICK":"var data = MOBY_DICK()\n","MONTH_NAMES_EN":"var list = MONTH_NAMES_EN()\n","MONTHS_IN_YEAR":"var yrs = 3.14;\nvar mons = yrs * MONTHS_IN_YEAR\n","moveProperty":"var obj1 = { 'a': 'b' };\nvar obj2 = {};\nvar bool = moveProperty( obj1, 'a', obj2 )\nbool = moveProperty( obj1, 'c', obj2 )\n","MultiSlice":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\n","MultiSlice.prototype.ndims":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\nms.ndims\n","MultiSlice.prototype.data":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\nms.data\n","MultiSlice.prototype.toString":"var s = new Slice( 2, 10 );\nvar ms = new MultiSlice( 2, s, 1 );\nms.toString()\n","MultiSlice.prototype.toJSON":"var s = new Slice( 2, 10, 1 );\nvar ms = new MultiSlice( 2, s );\nms.toJSON()\n","namedtypedtuple":"var opts = {};\nopts.name = 'Point';\nvar factory = namedtypedtuple( [ 'x', 'y' ], opts );\nvar tuple = factory();\n","NAN":"NAN\n","naryFunction":"function foo( a, b, c ) { return [ a, b, c ]; };\nvar bar = naryFunction( foo, 2 );\nvar out = bar( 1, 2, 3 )\n","nativeClass":"var str = nativeClass( 'a' )\nstr = nativeClass( 5 )\nfunction Beep(){};\nstr = nativeClass( new Beep() )\n","ndarray":"var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\nvar d = [ 2, 2 ]; // shape\nvar s = [ 2, 1 ]; // strides\nvar o = 0; // index offset\nvar arr = ndarray( 'generic', b, d, s, o, 'row-major' )\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","ndarray.prototype.byteLength":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.byteLength\n","ndarray.prototype.BYTES_PER_ELEMENT":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sz = arr.BYTES_PER_ELEMENT\n","ndarray.prototype.data":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar buf = arr.data\n","ndarray.prototype.dtype":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar dt = arr.dtype\n","ndarray.prototype.flags":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar fl = arr.flags\n","ndarray.prototype.length":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar len = arr.length\n","ndarray.prototype.ndims":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar n = arr.ndims\n","ndarray.prototype.offset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.offset\n","ndarray.prototype.order":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar ord = arr.order\n","ndarray.prototype.shape":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar sh = arr.shape\n","ndarray.prototype.strides":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar st = arr.strides\n","ndarray.prototype.get":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.get( 1, 1 )\n","ndarray.prototype.iget":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\nvar v = arr.iget( 3 )\n","ndarray.prototype.set":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\narr.set( 1, 1, -4.0 );\narr.get( 1, 1 )\n","ndarray.prototype.iset":"var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'float64', b, d, s, o, 'row-major' );\narr.iset( 3, -4.0 );\narr.iget( 3 )\n","ndarray.prototype.toString":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toString()\n","ndarray.prototype.toJSON":"var b = [ 1, 2, 3, 4 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar arr = ndarray( 'generic', b, d, s, o, 'row-major' );\narr.toJSON()\n","ndarray2array":"var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar out = ndarray2array( arr )\n","ndarray2fancy":"var b = [ 1.0, 2.0, 3.0, 4.0 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar x = ndarray( 'generic', b, d, s, o, 'row-major' );\nvar arr = ndarray2fancy( x );\nvar v = arr.get( 1, 1 )\nv = arr.iget( 3 )\narr.set( 1, 1, 40.0 );\narr.get( 1, 1 )\narr.iset( 3, 99.0 );\narr.get( 1, 1 )\n","ndarray2fancy.factory":"var b = [ 1.0, 2.0, 3.0, 4.0 ];\nvar d = [ 2, 2 ];\nvar s = [ 2, 1 ];\nvar o = 0;\nvar x = ndarray( 'generic', b, d, s, o, 'row-major' );\nvar f = ndarray2fancy.factory();\nvar y = f( x );\n","ndarray2fancy.idx":"var opts = { 'dtype': 'int32' };\nvar buf = new Int32Array( [ 1, 2, 3, 4 ] );\nvar arr = array( buf, opts );\nvar idx = ndarray2fancy.idx( arr );\n","ndarray2json":"var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar out = ndarray2json( arr )\n","ndarrayCastingModes":"var out = ndarrayCastingModes()\n","ndarrayDataBuffer":"var opts = { 'dtype': 'float64' };\nvar out = ndarrayDataBuffer( ndzeros( [ 3, 3, 3 ], opts ) )\n","ndarrayDataType":"var opts = { 'dtype': 'float64' };\nvar dt = ndarrayDataType( ndzeros( [ 3, 3, 3 ], opts ) )\n","ndarrayDataTypes":"var out = ndarrayDataTypes()\nout = ndarrayDataTypes( 'floating_point' )\nout = ndarrayDataTypes( 'floating_point_and_generic' )\n","ndarrayDispatch":"var t = [ 'float64', 'float64', 'float32', 'float32' ];\nvar d = [ base.abs, base.absf ];\nvar f = ndarrayDispatch( base.ndarrayUnary, t, d, 2, 1, 1 );\nvar xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar x = ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );\nvar ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar y = ndarray( 'float64', ybuf, [ 4 ], [ 1 ], 0, 'row-major' );\nf( x, y );\nybuf\n","ndarrayFlag":"var out = ndarrayFlag( ndzeros( [ 3, 3, 3 ] ), 'READONLY' )\n","ndarrayFlags":"var out = ndarrayFlags( ndzeros( [ 3, 3, 3 ] ) )\n","ndarrayIndexModes":"var out = ndarrayIndexModes()\n","ndarraylike2ndarray":"var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar out = ndarraylike2ndarray( arr )\n","ndarrayMinDataType":"var dt = ndarrayMinDataType( 3.141592653589793 )\ndt = ndarrayMinDataType( 3 )\ndt = ndarrayMinDataType( -3 )\ndt = ndarrayMinDataType( '-3' )\n","ndarrayMostlySafeCasts":"var out = ndarrayMostlySafeCasts( 'float32' )\n","ndarrayNextDataType":"var out = ndarrayNextDataType( 'float32' )\n","ndarrayOffset":"var n = ndarrayOffset( ndzeros( [ 3, 3, 3 ] ) )\n","ndarrayOrder":"var opts = { 'order': 'row-major' };\nvar dt = ndarrayOrder( ndzeros( [ 3, 3, 3 ], opts ) )\n","ndarrayOrders":"var out = ndarrayOrders()\n","ndarrayPromotionRules":"var out = ndarrayPromotionRules( 'float32', 'int32' )\n","ndarraySafeCasts":"var out = ndarraySafeCasts( 'float32' )\n","ndarraySameKindCasts":"var out = ndarraySameKindCasts( 'float32' )\n","ndarrayShape":"var out = ndarrayShape( ndzeros( [ 3, 3, 3 ] ) )\n","ndarrayStride":"var out = ndarrayStride( ndzeros( [ 3, 3, 3 ] ), 0 )\n","ndarrayStrides":"var out = ndarrayStrides( ndzeros( [ 3, 3, 3 ] ) )\n","ndat":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nndat( x, 0, 1 )\nndat( x, 1, 0 )\n","ndempty":"var arr = ndempty( [ 2, 2 ] )\nvar sh = arr.shape\nvar dt = arr.dtype\n","ndemptyLike":"var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\nvar sh = x.shape\nvar dt = x.dtype\nvar y = ndemptyLike( x )\nsh = y.shape\ndt = y.dtype\n","ndfilter":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { return v > 2.0; };\nvar y = ndfilter( x, f );\nndarray2array( y )\n","ndfilterMap":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { if ( v > 2.0 ) { return v * 10.0; } };\nvar y = ndfilterMap( x, f );\nndarray2array( y )\n","ndforEach":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { if ( v !== v ) { throw new Error( '...' ); } };\nndforEach( x, f );\n","ndims":"var n = ndims( ndzeros( [ 3, 3, 3 ] ) )\n","ndindex":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\n","ndindex.free":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nndindex.free( idx.id )\n","ndindex.get":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nndindex.get( idx.id )\n","ndindex.cartesianIndex":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = ndindex.cartesianIndex( x );\n","ndindex.linearIndex":"var x = ndempty( [ 5 ], { 'dtype': 'int32' } );\nvar idx = ndindex.linearIndex( x );\n","ndindex.prototype.data":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.data\n","ndindex.prototype.dtype":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.dtype\n","ndindex.prototype.id":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.id\n","ndindex.prototype.isCached":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.isCached\n","ndindex.prototype.kind":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x, { 'kind': 'cartesian' } );\nidx.kind\n","ndindex.prototype.type":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.type\n","ndindex.prototype.toString":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.toString()\n","ndindex.prototype.toJSON":"var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\nvar idx = new ndindex( x );\nidx.toJSON()\n","nditerColumnEntries":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerColumnEntries( x );\nvar v = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\nv = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\n","nditerColumns":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerColumns( x );\nvar v = it.next().value;\nndarray2array( v )\nv = it.next().value;\nndarray2array( v )\n","nditerEntries":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerEntries( x );\nvar v = it.next().value\nv = it.next().value\n","nditerIndices":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerIndices( x.shape );\nvar v = it.next().value\nv = it.next().value\n","nditerInterleaveSubarrays":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerInterleaveSubarrays( [ x, x ], 2 );\nvar v = it.next().value;\nndarray2array( v )\n","nditerMatrices":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerMatrices( x );\nvar v = it.next().value;\nndarray2array( v )\n","nditerMatrixEntries":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerMatrixEntries( x );\nvar v = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\n","nditerRowEntries":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerRowEntries( x );\nvar v = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\nv = it.next().value;\nv[ 0 ]\nndarray2array( v[ 1 ] )\n","nditerRows":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerRows( x );\nvar v = it.next().value;\nndarray2array( v )\nv = it.next().value;\nndarray2array( v )\n","nditerSelectDimension":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerSelectDimension( x, 0 );\nvar v = it.next().value;\nndarray2array( v )\n","nditerStacks":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerStacks( x, [ 1, 2 ] );\nvar v = it.next().value;\nndarray2array( v )\n","nditerSubarrays":"var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\nvar it = nditerSubarrays( x, 2 );\nvar v = it.next().value;\nndarray2array( v )\n","nditerValues":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\nvar it = nditerValues( x );\nvar v = it.next().value\nv = it.next().value\n","ndmap":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { return v*10.0; };\nvar y = ndmap( x, f );\nndarray2array( y )\n","ndreject":"var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\nfunction f( v ) { return v <= 2.0; };\nvar y = ndreject( x, f );\nndarray2array( y )\n","ndslice":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar s = new MultiSlice( null, 1 )\nvar y = ndslice( x, s )\ny.shape\nndarray2array( y )\n","ndsliceAssign":"var y = ndzeros( [ 2, 2 ] )\nvar x = scalar2ndarray( 3.0 )\nvar s = new MultiSlice( null, 1 )\nvar out = ndsliceAssign( x, y, s )\nvar bool = ( out === y )\nndarray2array( y )\n","ndsliceDimension":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceDimension( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndsliceDimensionFrom":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceDimensionFrom( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndsliceDimensionTo":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceDimensionTo( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndsliceFrom":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceFrom( x, 0, 1 )\ny.shape\nndarray2array( y )\n","ndsliceTo":"var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\nx.shape\nvar y = ndsliceTo( x, 1, 1 )\ny.shape\nndarray2array( y )\n","ndzeros":"var arr = ndzeros( [ 2, 2 ] )\nvar sh = arr.shape\nvar dt = arr.dtype\n","ndzerosLike":"var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\nvar sh = x.shape\nvar dt = x.dtype\nvar y = ndzerosLike( x )\nsh = y.shape\ndt = y.dtype\n","nextGraphemeClusterBreak":"var out = nextGraphemeClusterBreak( 'last man standing', 4 )\nout = nextGraphemeClusterBreak( 'presidential election', 8 )\nout = nextGraphemeClusterBreak( 'अनुच्छेद', 1 )\nout = nextGraphemeClusterBreak( '🌷' )\n","nextTick":"function f() { console.log( 'beep' ); };\nnextTick( f )\n","NIGHTINGALES_ROSE":"var data = NIGHTINGALES_ROSE()\n","NINF":"NINF\n","NODE_VERSION":"NODE_VERSION\n","none":"var arr = [ 0, 0, 0, 0, 0 ];\nvar bool = none( arr )\n","noneBy":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ 1, 2, 3, 4 ];\nvar bool = noneBy( arr, negative )\n","noneByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nnoneByAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nnoneByAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nnoneByAsync( arr, opts, predicate, done )\n","noneByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = noneByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, done )\n","noneByRight":"function positive( v ) { return ( v > 0 ); };\nvar arr = [ -1, -2, -3, -4 ];\nvar bool = noneByRight( arr, positive )\n","noneByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nnoneByRightAsync( arr, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nnoneByRightAsync( arr, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nnoneByRightAsync( arr, opts, predicate, done )\n","noneByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = noneByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, done )\n","noneInBy":"function negative( v ) { return ( v < 0 ); };\nvar obj = { 'a': 1, 'b': 2, 'c': 4 };\nvar bool = noneInBy( obj, negative )\n","nonEnumerableProperties":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = false;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar props = nonEnumerableProperties( obj )\n","nonEnumerablePropertiesIn":"var props = nonEnumerablePropertiesIn( [] )\n","nonEnumerablePropertyNames":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = nonEnumerablePropertyNames( obj )\n","nonEnumerablePropertyNamesIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = nonEnumerablePropertyNamesIn( obj )\n","nonEnumerablePropertySymbols":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = nonEnumerablePropertySymbols( obj )\n","nonEnumerablePropertySymbolsIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? 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Object.assign( {}, { 'a': 1 }, { 'b': 2 } )\n","Object.create":"var o = Object.create( {}, { 'a': { 'value': 1 } } )\n","Object.defineProperties":"var o = Object.defineProperties( {}, { 'a': { 'value': 1 } } )\n","Object.defineProperty":"var o = Object.defineProperty( {}, 'a', {\n","Object.entries":"var o = Object.entries( { 'a': 1, 'b': 2 } )\n","Object.freeze":"var o = Object.freeze( { 'a': 1 } )\n","Object.getOwnPropertyDescriptor":"var o = Object.getOwnPropertyDescriptor( { 'a': 1 }, 'a' )\n","Object.getOwnPropertyDescriptors":"var o = Object.getOwnPropertyDescriptors( { 'a': 1, 'b': 2 } )\n","Object.getOwnPropertyNames":"var o = Object.getOwnPropertyNames( { 'a': 1, 'b': 2 } )\n","Object.getOwnPropertySymbols":"var o = Object.getOwnPropertySymbols( { 'a': 1, 'b': 2 } )\n","Object.getPrototypeOf":"var o = Object.getPrototypeOf( { 'a': 1, 'b': 2 } )\n","Object.hasOwn":"var o = Object.hasOwn( { 'a': 1, 'b': 2 }, 'a' )\n","Object.is":"var o = Object.is( 1, 1 )\nvar o = Object.is( 1, '1' )\n","Object.isExtensible":"var o = Object.isExtensible( { 'a': 1 } )\n","Object.isFrozen":"var o = Object.isFrozen( { 'a': 1 } )\nvar o = Object.isFrozen( Object.freeze( { 'a': 1 } ) )\n","Object.isSealed":"var o = Object.isSealed( { 'a': 1 } )\nvar o = Object.isSealed( Object.seal( { 'a': 1 } ) )\n","Object.keys":"var o = Object.keys( { 'a': 1, 'b': 2 } )\n","Object.preventExtensions":"var o = Object.preventExtensions( { 'a': 1 } )\no.b = 2;\no\n","Object.seal":"var o = Object.seal( { 'a': 1 } )\no.b = 2;\no\ndelete o.a;\no\n","Object.setPrototypeOf":"var o = Object.setPrototypeOf( { 'a': 1 }, { 'b': 2 } )\no.b\n","Object.values":"var o = Object.values( { 'a': 1, 'b': 2 } )\n","Object.prototype.toLocaleString":"var o = Object.prototype.toLocaleString.call( { 'a': 1, 'b': 2 } )\n","Object.prototype.toString":"var o = Object.prototype.toString.call( { 'a': 1, 'b': 2 } )\n","Object.prototype.valueOf":"var o = Object.prototype.valueOf.call( { 'a': 1, 'b': 2 } )\n","Object.prototype.hasOwnProperty":"var o = Object.prototype.hasOwnProperty.call( { 'a': 1, 'b': 2 }, 'a' )\n","Object.prototype.isPrototypeOf":"var p = { 'a': 1 };\nvar o = { '__proto__': p };\nvar b = o.isPrototypeOf( p );\n","Object.prototype.propertyIsEnumerable":"var o = { 'a': 1, 'b': 2 };\nvar bool = Object.prototype.propertyIsEnumerable.call( o, 'a' )\n","Object.prototype.constructor":"var o = new Object( null );\nvar ctr = o.constructor;\n","objectEntries":"var obj = { 'beep': 'boop', 'foo': 'bar' };\nvar entries = objectEntries( obj )\n","objectEntriesIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar entries = objectEntriesIn( obj )\n","objectFromEntries":"var entries = [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ];\nvar obj = objectFromEntries( entries )\n","objectInverse":"var obj = { 'a': 'beep', 'b': 'boop' };\nvar out = objectInverse( obj )\nobj = { 'a': 'beep', 'b': 'beep' };\nout = objectInverse( obj )\nobj = {};\nobj.a = 'beep';\nobj.b = 'boop';\nobj.c = 'beep';\nout = objectInverse( obj, { 'duplicates': false } )\n","objectInverseBy":"function transform( key, value ) { return key + value; };\nvar obj = { 'a': 'beep', 'b': 'boop' };\nvar out = objectInverseBy( obj, transform )\nfunction transform( key, value ) { return value; };\nobj = { 'a': 'beep', 'b': 'beep' };\nout = objectInverseBy( obj, transform )\nobj = {};\nobj.a = 'beep';\nobj.b = 'boop';\nobj.c = 'beep';\nout = objectInverseBy( obj, { 'duplicates': false }, transform )\n","objectKeys":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = objectKeys( obj )\n","objectValues":"var obj = { 'beep': 'boop', 'foo': 'bar' };\nvar vals = objectValues( obj )\n","objectValuesIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar values = objectValuesIn( obj )\n","omit":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = omit( obj1, 'b' )\n","omitBy":"function predicate( key, value ) { return ( value > 1 ); };\nvar obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = omitBy( obj1, predicate )\n","open":"function onOpen( error, fd ) {\n if ( error ) {\n     console.error( error.message );\n } else {\n     close.sync( fd );\n }\n };\nopen( './beep/boop.txt', onOpen );\n","open.sync":"var fd = open.sync( './beep/boop.txt' );\nif ( !isError( fd ) ) { close.sync( fd ); };\n","openURL":"var out = openURL( 'https://google.com' );\n","ordinalize":"var out = ordinalize( '1' )\nout = ordinalize( 2, { 'suffixOnly': true } )\nout = ordinalize( '3', { 'lang': 'es' } )\n","PACE_BOSTON_HOUSE_PRICES":"var data = PACE_BOSTON_HOUSE_PRICES()\n","pad":"var out = pad( 'a', 5 )\nout = pad( 'a', 10, { 'lpad': 'b' } )\nout = pad( 'a', 12, { 'rpad': 'b' } )\nvar opts = { 'lpad': 'a', 'rpad': 'c' };\nout = pad( 'b', 11, opts )\nopts.centerRight = false;\nout = pad( 'b', 10, opts )\nopts.centerRight = true;\nout = pad( 'b', 10, opts )\nopts = { 'lpad': 'boop', 'rpad': 'woot' };\nout = pad( 'beep', 10, opts )\nout = pad( 'beep', 2 )\nopts = { 'lpad': 'b' };\nout = pad( 'beep', 2, opts )\nopts = { 'lpad': '@', 'rpad': '!' };\nout = pad( 'beep', 2, opts )\nout = pad( 'abcdef', 3, opts )\nopts.centerRight = true;\nout = pad( 'abcdef', 3, opts )\n","padjust":"var pvalues = [ 0.008, 0.03, 0.123, 0.6, 0.2 ];\nvar out = padjust( pvalues, 'bh' )\nout = padjust( pvalues, 'bonferroni' )\nout = padjust( pvalues, 'by' )\nout = padjust( pvalues, 'holm' )\nout = padjust( pvalues, 'hommel' )\n","papply":"function add( x, y ) { return x + y; };\nvar add2 = papply( add, 2 );\nvar sum = add2( 3 )\n","papplyRight":"function say( text, name ) { return text + ', ' + name + '.'; };\nvar toGrace = papplyRight( say, 'Grace Hopper' );\nvar str = toGrace( 'Hello' )\nstr = toGrace( 'Thank you' )\n","parallel":"function done( error ) { if ( error ) { throw error; } };\nvar files = [ './a.js', './b.js' ];\nparallel( files, done );\nvar opts = { 'workers': 8 };\nparallel( files, opts, done );\n","parseJSON":"var obj = parseJSON( '{\"beep\":\"boop\"}' )\nfunction reviver( key, value ) {\n if ( key === '' ) { return value; }\n if ( key === 'beep' ) { return value; }\n };\nvar str = '{\"beep\":\"boop\",\"a\":\"b\"}';\nvar out = parseJSON( str, reviver )\n","pascalcase":"var out = pascalcase( 'Hello World!' )\nout = pascalcase( 'beep boop' )\n","PATH_DELIMITER":"PATH_DELIMITER\nvar path = '/usr/bin:/bin:/usr/sbin';\nvar parts = path.split( PATH_DELIMITER )\npath = 'C:\\\\Windows\\\\system32;C:\\\\Windows';\nparts = path.split( PATH_DELIMITER )\n","PATH_DELIMITER_POSIX":"PATH_DELIMITER_POSIX\nvar PATH = '/usr/bin:/bin:/usr/sbin:/sbin:/usr/local/bin';\nvar paths = PATH.split( PATH_DELIMITER_POSIX )\n","PATH_DELIMITER_WIN32":"PATH_DELIMITER_WIN32\nvar PATH = 'C:\\\\Windows\\\\system32;C:\\\\Windows;C:\\\\Program Files\\\\node\\\\';\nvar paths = PATH.split( PATH_DELIMITER_WIN32 )\n","PATH_SEP":"PATH_SEP\nvar parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP )\nparts = 'foo/bar/baz'.split( PATH_SEP )\n","PATH_SEP_POSIX":"PATH_SEP_POSIX\nvar parts = 'foo/bar/baz'.split( PATH_SEP_POSIX )\n","PATH_SEP_WIN32":"PATH_SEP_WIN32\nvar parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP_WIN32 )\n","pcorrtest":"var rho = 0.5;\nvar x = new Array( 300 );\nvar y = new Array( 300 );\nfor ( var i = 0; i < 300; i++ ) {\nx[ i ] = base.random.normal( 0.0, 1.0 );\ny[ i ] = ( rho * x[ i ] ) + base.random.normal( 0.0,\nbase.sqrt( 1.0 - (rho*rho) ) );\n }\nvar out = pcorrtest( x, y )\nvar table = out.print()\n","percentEncode":"var out = percentEncode( '☃' )\n","PHI":"PHI\n","PI":"PI\n","PI_SQUARED":"PI_SQUARED\n","pick":"var obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = pick( obj1, 'b' )\n","pickArguments":"function foo( a, b ) { return [ a, b ]; };\nvar bar = pickArguments( foo, [ 0, 2 ] );\nvar out = bar( 1, 2, 3 )\n","pickBy":"function predicate( key, value ) {\n return ( value > 1 );\n };\nvar obj1 = { 'a': 1, 'b': 2 };\nvar obj2 = pickBy( obj1, predicate )\n","PINF":"PINF\n","pkg2alias":"var v = pkg2alias( '@stdlib/math/base/special/sin' )\nv = pkg2alias( '@stdlib/math-base-special-sin' )\n","pkg2related":"var v = pkg2related( '@stdlib/math/base/special/sin' )\nv = pkg2related( '@stdlib/math-base-special-sin' )\n","pkg2standalone":"var v = pkg2standalone( '@stdlib/math/base/special/sin' )\n","PLATFORM":"PLATFORM\n","plot":"var plot = plot()\nvar x = [[0.10, 0.20, 0.30]];\nvar y = [[0.52, 0.79, 0.64]];\nplot = plot( x, y )\n","Plot":"var plot = Plot()\nvar x = [[0.10, 0.20, 0.30]];\nvar y = [[0.52, 0.79, 0.64]];\nplot = Plot( x, y )\n","pluck":"var arr = [\n { 'a': 1, 'b': 2 },\n { 'a': 0.5, 'b': 3 }\n ];\nvar out = pluck( arr, 'a' )\narr = [\n { 'a': 1, 'b': 2 },\n { 'a': 0.5, 'b': 3 }\n ];\nout = pluck( arr, 'a', { 'copy': false } )\nvar bool = ( arr[ 0 ] === out[ 0 ] )\n","pop":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar out = pop( arr )\narr = new Float64Array( [ 1.0, 2.0 ] );\nout = pop( arr )\narr = { 'length': 2, '0': 1.0, '1': 2.0 };\nout = pop( arr )\n","porterStemmer":"var out = porterStemmer( 'walking' )\nout = porterStemmer( 'walked' )\nout = porterStemmer( 'walks' )\nout = porterStemmer( '' )\n","prepend":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = prepend( arr, [ 6.0, 7.0 ] )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = prepend( arr, [ 3.0, 4.0 ] )\narr = { 'length': 1, '0': 1.0 };\narr = prepend( arr, [ 2.0, 3.0 ] )\n","prevGraphemeClusterBreak":"var out = prevGraphemeClusterBreak( 'last man standing', 4 )\nout = prevGraphemeClusterBreak( 'presidential election', 8 )\nout = prevGraphemeClusterBreak( 'अनुच्छेद', 2 )\nout = prevGraphemeClusterBreak( '🌷', 1 )\n","PRIMES_100K":"var list = PRIMES_100K()\n","properties":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar props = properties( obj )\n","propertiesIn":"var props = propertiesIn( [] )\n","propertyDescriptor":"var obj = { 'a': 'b' };\nvar desc = propertyDescriptor( obj, 'a' )\n","propertyDescriptorIn":"var obj = { 'a': 'b' };\nvar desc = propertyDescriptorIn( obj, 'a' )\n","propertyDescriptors":"var obj = { 'a': 'b' };\nvar desc = propertyDescriptors( obj )\n","propertyDescriptorsIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar desc = propertyDescriptorsIn( obj )\n","propertyNames":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = propertyNames( obj )\n","propertyNamesIn":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar keys = propertyNamesIn( obj )\n","propertySymbols":"var s = propertySymbols( {} )\n","propertySymbolsIn":"var s = propertySymbolsIn( [] )\n","Proxy":"function get( obj, prop ) { return obj[ prop ] * 2.0 };\nvar h = { 'get': get };\nvar p = new Proxy( {}, h );\np.a = 3.14;\np.a\n","Proxy.revocable":"function get( obj, prop ) { return obj[ prop ] * 2.0 };\nvar h = { 'get': get };\nvar p = Proxy.revocable( {}, h );\np.proxy.a = 3.14;\np.proxy.a\np.revoke();\n","push":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = push( arr, 6.0, 7.0 )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = push( arr, 3.0, 4.0 )\narr = { 'length': 0 };\narr = push( arr, 1.0, 2.0 )\n","quarterOfYear":"var q = quarterOfYear( new Date() )\nq = quarterOfYear( 4 )\nq = quarterOfYear( 'June' )\nq = quarterOfYear( 'April' )\nq = quarterOfYear( 'apr' )\n","random.array.arcsine":"var out = random.array.arcsine( 3, 2.0, 5.0 )\n","random.array.arcsine.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.arcsine.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.arcsine.factory":"var fcn = random.array.arcsine.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.arcsine.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.arcsine.PRNG":"var prng = random.array.arcsine.PRNG;\n","random.array.arcsine.seed":"var seed = random.array.arcsine.seed;\n","random.array.arcsine.seedLength":"var len = random.array.arcsine.seedLength;\n","random.array.arcsine.state":"var out = random.array.arcsine( 3, 2.0, 5.0 )\nvar state = random.array.arcsine.state\nout = random.array.arcsine( 3, 2.0, 5.0 )\nout = random.array.arcsine( 3, 2.0, 5.0 )\nrandom.array.arcsine.state = state;\nout = random.array.arcsine( 3, 2.0, 5.0 )\n","random.array.arcsine.stateLength":"var len = random.array.arcsine.stateLength;\n","random.array.arcsine.byteLength":"var sz = random.array.arcsine.byteLength;\n","random.array.bernoulli":"var out = random.array.bernoulli( 3, 0.5 )\n","random.array.bernoulli.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.bernoulli.assign( 0.5, x )\nvar bool = ( out === x )\n","random.array.bernoulli.factory":"var fcn = random.array.bernoulli.factory();\nvar out = fcn( 3, 0.5 )\nfcn = random.array.bernoulli.factory( 0.5 );\nout = fcn( 3 )\n","random.array.bernoulli.PRNG":"var prng = random.array.bernoulli.PRNG;\n","random.array.bernoulli.seed":"var seed = random.array.bernoulli.seed;\n","random.array.bernoulli.seedLength":"var len = random.array.bernoulli.seedLength;\n","random.array.bernoulli.state":"var out = random.array.bernoulli( 3, 0.5 )\nvar state = random.array.bernoulli.state\nout = random.array.bernoulli( 3, 0.5 )\nout = random.array.bernoulli( 3, 0.5 )\nrandom.array.bernoulli.state = state;\nout = random.array.bernoulli( 3, 0.5 )\n","random.array.bernoulli.stateLength":"var len = random.array.bernoulli.stateLength;\n","random.array.bernoulli.byteLength":"var sz = random.array.bernoulli.byteLength;\n","random.array.beta":"var out = random.array.beta( 3, 2.0, 5.0 )\n","random.array.beta.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.beta.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.beta.factory":"var fcn = random.array.beta.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.beta.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.beta.PRNG":"var prng = random.array.beta.PRNG;\n","random.array.beta.seed":"var seed = random.array.beta.seed;\n","random.array.beta.seedLength":"var len = random.array.beta.seedLength;\n","random.array.beta.state":"var out = random.array.beta( 3, 2.0, 5.0 )\nvar state = random.array.beta.state\nout = random.array.beta( 3, 2.0, 5.0 )\nout = random.array.beta( 3, 2.0, 5.0 )\nrandom.array.beta.state = state;\nout = random.array.beta( 3, 2.0, 5.0 )\n","random.array.beta.stateLength":"var len = random.array.beta.stateLength;\n","random.array.beta.byteLength":"var sz = random.array.beta.byteLength;\n","random.array.betaprime":"var out = random.array.betaprime( 3, 2.0, 5.0 )\n","random.array.betaprime.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.betaprime.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.betaprime.factory":"var fcn = random.array.betaprime.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.betaprime.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.betaprime.PRNG":"var prng = random.array.betaprime.PRNG;\n","random.array.betaprime.seed":"var seed = random.array.betaprime.seed;\n","random.array.betaprime.seedLength":"var len = random.array.betaprime.seedLength;\n","random.array.betaprime.state":"var out = random.array.betaprime( 3, 2.0, 5.0 )\nvar state = random.array.betaprime.state\nout = random.array.betaprime( 3, 2.0, 5.0 )\nout = random.array.betaprime( 3, 2.0, 5.0 )\nrandom.array.betaprime.state = state;\nout = random.array.betaprime( 3, 2.0, 5.0 )\n","random.array.betaprime.stateLength":"var len = random.array.betaprime.stateLength;\n","random.array.betaprime.byteLength":"var sz = random.array.betaprime.byteLength;\n","random.array.binomial":"var out = random.array.binomial( 3, 17, 0.5 )\n","random.array.binomial.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.binomial.assign( 17, 0.5, x )\nvar bool = ( out === x )\n","random.array.binomial.factory":"var fcn = random.array.binomial.factory();\nvar out = fcn( 3, 17, 0.5 )\nfcn = random.array.binomial.factory( 17, 0.5 );\nout = fcn( 3 )\n","random.array.binomial.PRNG":"var prng = random.array.binomial.PRNG;\n","random.array.binomial.seed":"var seed = random.array.binomial.seed;\n","random.array.binomial.seedLength":"var len = random.array.binomial.seedLength;\n","random.array.binomial.state":"var out = random.array.binomial( 3, 17, 0.5 )\nvar state = random.array.binomial.state\nout = random.array.binomial( 3, 17, 0.5 )\nout = random.array.binomial( 3, 17, 0.5 )\nrandom.array.binomial.state = state;\nout = random.array.binomial( 3, 17, 0.5 )\n","random.array.binomial.stateLength":"var len = random.array.binomial.stateLength;\n","random.array.binomial.byteLength":"var sz = random.array.binomial.byteLength;\n","random.array.cauchy":"var out = random.array.cauchy( 3, 2.0, 5.0 )\n","random.array.cauchy.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.cauchy.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.cauchy.factory":"var fcn = random.array.cauchy.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.cauchy.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.cauchy.PRNG":"var prng = random.array.cauchy.PRNG;\n","random.array.cauchy.seed":"var seed = random.array.cauchy.seed;\n","random.array.cauchy.seedLength":"var len = random.array.cauchy.seedLength;\n","random.array.cauchy.state":"var out = random.array.cauchy( 3, 2.0, 5.0 )\nvar state = random.array.cauchy.state\nout = random.array.cauchy( 3, 2.0, 5.0 )\nout = random.array.cauchy( 3, 2.0, 5.0 )\nrandom.array.cauchy.state = state;\nout = random.array.cauchy( 3, 2.0, 5.0 )\n","random.array.cauchy.stateLength":"var len = random.array.cauchy.stateLength;\n","random.array.cauchy.byteLength":"var sz = random.array.cauchy.byteLength;\n","random.array.chi":"var out = random.array.chi( 3, 2.0 )\n","random.array.chi.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.chi.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.chi.factory":"var fcn = random.array.chi.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.chi.factory( 2.0 );\nout = fcn( 3 )\n","random.array.chi.PRNG":"var prng = random.array.chi.PRNG;\n","random.array.chi.seed":"var seed = random.array.chi.seed;\n","random.array.chi.seedLength":"var len = random.array.chi.seedLength;\n","random.array.chi.state":"var out = random.array.chi( 3, 2.0 )\nvar state = random.array.chi.state\nout = random.array.chi( 3, 2.0 )\nout = random.array.chi( 3, 2.0 )\nrandom.array.chi.state = state;\nout = random.array.chi( 3, 2.0 )\n","random.array.chi.stateLength":"var len = random.array.chi.stateLength;\n","random.array.chi.byteLength":"var sz = random.array.chi.byteLength;\n","random.array.chisquare":"var out = random.array.chisquare( 3, 2.0 )\n","random.array.chisquare.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.chisquare.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.chisquare.factory":"var fcn = random.array.chisquare.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.chisquare.factory( 2.0 );\nout = fcn( 3 )\n","random.array.chisquare.PRNG":"var prng = random.array.chisquare.PRNG;\n","random.array.chisquare.seed":"var seed = random.array.chisquare.seed;\n","random.array.chisquare.seedLength":"var len = random.array.chisquare.seedLength;\n","random.array.chisquare.state":"var out = random.array.chisquare( 3, 2.0 )\nvar state = random.array.chisquare.state\nout = random.array.chisquare( 3, 2.0 )\nout = random.array.chisquare( 3, 2.0 )\nrandom.array.chisquare.state = state;\nout = random.array.chisquare( 3, 2.0 )\n","random.array.chisquare.stateLength":"var len = random.array.chisquare.stateLength;\n","random.array.chisquare.byteLength":"var sz = random.array.chisquare.byteLength;\n","random.array.cosine":"var out = random.array.cosine( 3, 2.0, 5.0 )\n","random.array.cosine.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.cosine.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.cosine.factory":"var fcn = random.array.cosine.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.cosine.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.cosine.PRNG":"var prng = random.array.cosine.PRNG;\n","random.array.cosine.seed":"var seed = random.array.cosine.seed;\n","random.array.cosine.seedLength":"var len = random.array.cosine.seedLength;\n","random.array.cosine.state":"var out = random.array.cosine( 3, 2.0, 5.0 )\nvar state = random.array.cosine.state\nout = random.array.cosine( 3, 2.0, 5.0 )\nout = random.array.cosine( 3, 2.0, 5.0 )\nrandom.array.cosine.state = state;\nout = random.array.cosine( 3, 2.0, 5.0 )\n","random.array.cosine.stateLength":"var len = random.array.cosine.stateLength;\n","random.array.cosine.byteLength":"var sz = random.array.cosine.byteLength;\n","random.array.discreteUniform":"var out = random.array.discreteUniform( 3, -10, 10 )\n","random.array.discreteUniform.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.discreteUniform.assign( -10, 10, x )\nvar bool = ( out === x )\n","random.array.discreteUniform.factory":"var fcn = random.array.discreteUniform.factory();\nvar out = fcn( 3, -10, 10 )\nfcn = random.array.discreteUniform.factory( -10, 10 );\nout = fcn( 3 )\n","random.array.discreteUniform.PRNG":"var prng = random.array.discreteUniform.PRNG;\n","random.array.discreteUniform.seed":"var seed = random.array.discreteUniform.seed;\n","random.array.discreteUniform.seedLength":"var len = random.array.discreteUniform.seedLength;\n","random.array.discreteUniform.state":"var out = random.array.discreteUniform( 3, -10, 10 )\nvar state = random.array.discreteUniform.state\nout = random.array.discreteUniform( 3, -10, 10 )\nout = random.array.discreteUniform( 3, -10, 10 )\nrandom.array.discreteUniform.state = state;\nout = random.array.discreteUniform( 3, -10, 10 )\n","random.array.discreteUniform.stateLength":"var len = random.array.discreteUniform.stateLength;\n","random.array.discreteUniform.byteLength":"var sz = random.array.discreteUniform.byteLength;\n","random.array.erlang":"var out = random.array.erlang( 3, 2, 5.0 )\n","random.array.erlang.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.erlang.assign( 2, 5.0, x )\nvar bool = ( out === x )\n","random.array.erlang.factory":"var fcn = random.array.erlang.factory();\nvar out = fcn( 3, 2, 5.0 )\nfcn = random.array.erlang.factory( 2, 5.0 );\nout = fcn( 3 )\n","random.array.erlang.PRNG":"var prng = random.array.erlang.PRNG;\n","random.array.erlang.seed":"var seed = random.array.erlang.seed;\n","random.array.erlang.seedLength":"var len = random.array.erlang.seedLength;\n","random.array.erlang.state":"var out = random.array.erlang( 3, 2, 5.0 )\nvar state = random.array.erlang.state\nout = random.array.erlang( 3, 2, 5.0 )\nout = random.array.erlang( 3, 2, 5.0 )\nrandom.array.erlang.state = state;\nout = random.array.erlang( 3, 2, 5.0 )\n","random.array.erlang.stateLength":"var len = random.array.erlang.stateLength;\n","random.array.erlang.byteLength":"var sz = random.array.erlang.byteLength;\n","random.array.exponential":"var out = random.array.exponential( 3, 2.0 )\n","random.array.exponential.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.exponential.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.exponential.factory":"var fcn = random.array.exponential.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.exponential.factory( 2.0 );\nout = fcn( 3 )\n","random.array.exponential.PRNG":"var prng = random.array.exponential.PRNG;\n","random.array.exponential.seed":"var seed = random.array.exponential.seed;\n","random.array.exponential.seedLength":"var len = random.array.exponential.seedLength;\n","random.array.exponential.state":"var out = random.array.exponential( 3, 2.0 )\nvar state = random.array.exponential.state\nout = random.array.exponential( 3, 2.0 )\nout = random.array.exponential( 3, 2.0 )\nrandom.array.exponential.state = state;\nout = random.array.exponential( 3, 2.0 )\n","random.array.exponential.stateLength":"var len = random.array.exponential.stateLength;\n","random.array.exponential.byteLength":"var sz = random.array.exponential.byteLength;\n","random.array.f":"var out = random.array.f( 3, 2.0, 5.0 )\n","random.array.f.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.f.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.f.factory":"var fcn = random.array.f.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.f.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.f.PRNG":"var prng = random.array.f.PRNG;\n","random.array.f.seed":"var seed = random.array.f.seed;\n","random.array.f.seedLength":"var len = random.array.f.seedLength;\n","random.array.f.state":"var out = random.array.f( 3, 2.0, 5.0 )\nvar state = random.array.f.state\nout = random.array.f( 3, 2.0, 5.0 )\nout = random.array.f( 3, 2.0, 5.0 )\nrandom.array.f.state = state;\nout = random.array.f( 3, 2.0, 5.0 )\n","random.array.f.stateLength":"var len = random.array.f.stateLength;\n","random.array.f.byteLength":"var sz = random.array.f.byteLength;\n","random.array.frechet":"var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n","random.array.frechet.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.frechet.assign( 2.0, 5.0, 3.0, x )\nvar bool = ( out === x )\n","random.array.frechet.factory":"var fcn = random.array.frechet.factory();\nvar out = fcn( 3, 2.0, 5.0, 3.0 )\nfcn = random.array.frechet.factory( 2.0, 5.0, 3.0 );\nout = fcn( 3 )\n","random.array.frechet.PRNG":"var prng = random.array.frechet.PRNG;\n","random.array.frechet.seed":"var seed = random.array.frechet.seed;\n","random.array.frechet.seedLength":"var len = random.array.frechet.seedLength;\n","random.array.frechet.state":"var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\nvar state = random.array.frechet.state\nout = random.array.frechet( 3, 2.0, 5.0, 3.0 )\nout = random.array.frechet( 3, 2.0, 5.0, 3.0 )\nrandom.array.frechet.state = state;\nout = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n","random.array.frechet.stateLength":"var len = random.array.frechet.stateLength;\n","random.array.frechet.byteLength":"var sz = random.array.frechet.byteLength;\n","random.array.gamma":"var out = random.array.gamma( 3, 2.0, 5.0 )\n","random.array.gamma.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.gamma.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.gamma.factory":"var fcn = random.array.gamma.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.gamma.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.gamma.PRNG":"var prng = random.array.gamma.PRNG;\n","random.array.gamma.seed":"var seed = random.array.gamma.seed;\n","random.array.gamma.seedLength":"var len = random.array.gamma.seedLength;\n","random.array.gamma.state":"var out = random.array.gamma( 3, 2.0, 5.0 )\nvar state = random.array.gamma.state\nout = random.array.gamma( 3, 2.0, 5.0 )\nout = random.array.gamma( 3, 2.0, 5.0 )\nrandom.array.gamma.state = state;\nout = random.array.gamma( 3, 2.0, 5.0 )\n","random.array.gamma.stateLength":"var len = random.array.gamma.stateLength;\n","random.array.gamma.byteLength":"var sz = random.array.gamma.byteLength;\n","random.array.geometric":"var out = random.array.geometric( 3, 0.01 )\n","random.array.geometric.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.geometric.assign( 0.01, x )\nvar bool = ( out === x )\n","random.array.geometric.factory":"var fcn = random.array.geometric.factory();\nvar out = fcn( 3, 0.01 )\nfcn = random.array.geometric.factory( 0.01 );\nout = fcn( 3 )\n","random.array.geometric.PRNG":"var prng = random.array.geometric.PRNG;\n","random.array.geometric.seed":"var seed = random.array.geometric.seed;\n","random.array.geometric.seedLength":"var len = random.array.geometric.seedLength;\n","random.array.geometric.state":"var out = random.array.geometric( 3, 0.01 )\nvar state = random.array.geometric.state\nout = random.array.geometric( 3, 0.01 )\nout = random.array.geometric( 3, 0.01 )\nrandom.array.geometric.state = state;\nout = random.array.geometric( 3, 0.01 )\n","random.array.geometric.stateLength":"var len = random.array.geometric.stateLength;\n","random.array.geometric.byteLength":"var sz = random.array.geometric.byteLength;\n","random.array.gumbel":"var out = random.array.gumbel( 3, 2.0, 5.0 )\n","random.array.gumbel.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.gumbel.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.gumbel.factory":"var fcn = random.array.gumbel.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.gumbel.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.gumbel.PRNG":"var prng = random.array.gumbel.PRNG;\n","random.array.gumbel.seed":"var seed = random.array.gumbel.seed;\n","random.array.gumbel.seedLength":"var len = random.array.gumbel.seedLength;\n","random.array.gumbel.state":"var out = random.array.gumbel( 3, 2.0, 5.0 )\nvar state = random.array.gumbel.state\nout = random.array.gumbel( 3, 2.0, 5.0 )\nout = random.array.gumbel( 3, 2.0, 5.0 )\nrandom.array.gumbel.state = state;\nout = random.array.gumbel( 3, 2.0, 5.0 )\n","random.array.gumbel.stateLength":"var len = random.array.gumbel.stateLength;\n","random.array.gumbel.byteLength":"var sz = random.array.gumbel.byteLength;\n","random.array.hypergeometric":"var out = random.array.hypergeometric( 3, 20, 10, 7 )\n","random.array.hypergeometric.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.hypergeometric.assign( 20, 10, 7, x )\nvar bool = ( out === x )\n","random.array.hypergeometric.factory":"var fcn = random.array.hypergeometric.factory();\nvar out = fcn( 3, 20, 10, 7 )\nfcn = random.array.hypergeometric.factory( 20, 10, 7 );\nout = fcn( 3 )\n","random.array.hypergeometric.PRNG":"var prng = random.array.hypergeometric.PRNG;\n","random.array.hypergeometric.seed":"var seed = random.array.hypergeometric.seed;\n","random.array.hypergeometric.seedLength":"var len = random.array.hypergeometric.seedLength;\n","random.array.hypergeometric.state":"var out = random.array.hypergeometric( 3, 20, 10, 7 )\nvar state = random.array.hypergeometric.state\nout = random.array.hypergeometric( 3, 20, 10, 7 )\nout = random.array.hypergeometric( 3, 20, 10, 7 )\nrandom.array.hypergeometric.state = state;\nout = random.array.hypergeometric( 3, 20, 10, 7 )\n","random.array.hypergeometric.stateLength":"var len = random.array.hypergeometric.stateLength;\n","random.array.hypergeometric.byteLength":"var sz = random.array.hypergeometric.byteLength;\n","random.array.invgamma":"var out = random.array.invgamma( 3, 2.0, 5.0 )\n","random.array.invgamma.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.invgamma.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.invgamma.factory":"var fcn = random.array.invgamma.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.invgamma.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.invgamma.PRNG":"var prng = random.array.invgamma.PRNG;\n","random.array.invgamma.seed":"var seed = random.array.invgamma.seed;\n","random.array.invgamma.seedLength":"var len = random.array.invgamma.seedLength;\n","random.array.invgamma.state":"var out = random.array.invgamma( 3, 2.0, 5.0 )\nvar state = random.array.invgamma.state\nout = random.array.invgamma( 3, 2.0, 5.0 )\nout = random.array.invgamma( 3, 2.0, 5.0 )\nrandom.array.invgamma.state = state;\nout = random.array.invgamma( 3, 2.0, 5.0 )\n","random.array.invgamma.stateLength":"var len = random.array.invgamma.stateLength;\n","random.array.invgamma.byteLength":"var sz = random.array.invgamma.byteLength;\n","random.array.kumaraswamy":"var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n","random.array.kumaraswamy.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.kumaraswamy.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.kumaraswamy.factory":"var fcn = random.array.kumaraswamy.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.kumaraswamy.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.kumaraswamy.PRNG":"var prng = random.array.kumaraswamy.PRNG;\n","random.array.kumaraswamy.seed":"var seed = random.array.kumaraswamy.seed;\n","random.array.kumaraswamy.seedLength":"var len = random.array.kumaraswamy.seedLength;\n","random.array.kumaraswamy.state":"var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\nvar state = random.array.kumaraswamy.state\nout = random.array.kumaraswamy( 3, 2.0, 5.0 )\nout = random.array.kumaraswamy( 3, 2.0, 5.0 )\nrandom.array.kumaraswamy.state = state;\nout = random.array.kumaraswamy( 3, 2.0, 5.0 )\n","random.array.kumaraswamy.stateLength":"var len = random.array.kumaraswamy.stateLength;\n","random.array.kumaraswamy.byteLength":"var sz = random.array.kumaraswamy.byteLength;\n","random.array.laplace":"var out = random.array.laplace( 3, 2.0, 5.0 )\n","random.array.laplace.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.laplace.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.laplace.factory":"var fcn = random.array.laplace.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.laplace.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.laplace.PRNG":"var prng = random.array.laplace.PRNG;\n","random.array.laplace.seed":"var seed = random.array.laplace.seed;\n","random.array.laplace.seedLength":"var len = random.array.laplace.seedLength;\n","random.array.laplace.state":"var out = random.array.laplace( 3, 2.0, 5.0 )\nvar state = random.array.laplace.state\nout = random.array.laplace( 3, 2.0, 5.0 )\nout = random.array.laplace( 3, 2.0, 5.0 )\nrandom.array.laplace.state = state;\nout = random.array.laplace( 3, 2.0, 5.0 )\n","random.array.laplace.stateLength":"var len = random.array.laplace.stateLength;\n","random.array.laplace.byteLength":"var sz = random.array.laplace.byteLength;\n","random.array.levy":"var out = random.array.levy( 3, 2.0, 5.0 )\n","random.array.levy.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.levy.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.levy.factory":"var fcn = random.array.levy.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.levy.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.levy.PRNG":"var prng = random.array.levy.PRNG;\n","random.array.levy.seed":"var seed = random.array.levy.seed;\n","random.array.levy.seedLength":"var len = random.array.levy.seedLength;\n","random.array.levy.state":"var out = random.array.levy( 3, 2.0, 5.0 )\nvar state = random.array.levy.state\nout = random.array.levy( 3, 2.0, 5.0 )\nout = random.array.levy( 3, 2.0, 5.0 )\nrandom.array.levy.state = state;\nout = random.array.levy( 3, 2.0, 5.0 )\n","random.array.levy.stateLength":"var len = random.array.levy.stateLength;\n","random.array.levy.byteLength":"var sz = random.array.levy.byteLength;\n","random.array.logistic":"var out = random.array.logistic( 3, 2.0, 5.0 )\n","random.array.logistic.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.logistic.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.logistic.factory":"var fcn = random.array.logistic.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.logistic.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.logistic.PRNG":"var prng = random.array.logistic.PRNG;\n","random.array.logistic.seed":"var seed = random.array.logistic.seed;\n","random.array.logistic.seedLength":"var len = random.array.logistic.seedLength;\n","random.array.logistic.state":"var out = random.array.logistic( 3, 2.0, 5.0 )\nvar state = random.array.logistic.state\nout = random.array.logistic( 3, 2.0, 5.0 )\nout = random.array.logistic( 3, 2.0, 5.0 )\nrandom.array.logistic.state = state;\nout = random.array.logistic( 3, 2.0, 5.0 )\n","random.array.logistic.stateLength":"var len = random.array.logistic.stateLength;\n","random.array.logistic.byteLength":"var sz = random.array.logistic.byteLength;\n","random.array.lognormal":"var out = random.array.lognormal( 3, 2.0, 5.0 )\n","random.array.lognormal.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.lognormal.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.lognormal.factory":"var fcn = random.array.lognormal.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.lognormal.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.lognormal.PRNG":"var prng = random.array.lognormal.PRNG;\n","random.array.lognormal.seed":"var seed = random.array.lognormal.seed;\n","random.array.lognormal.seedLength":"var len = random.array.lognormal.seedLength;\n","random.array.lognormal.state":"var out = random.array.lognormal( 3, 2.0, 5.0 )\nvar state = random.array.lognormal.state\nout = random.array.lognormal( 3, 2.0, 5.0 )\nout = random.array.lognormal( 3, 2.0, 5.0 )\nrandom.array.lognormal.state = state;\nout = random.array.lognormal( 3, 2.0, 5.0 )\n","random.array.lognormal.stateLength":"var len = random.array.lognormal.stateLength;\n","random.array.lognormal.byteLength":"var sz = random.array.lognormal.byteLength;\n","random.array.minstd":"var out = random.array.minstd( 3 )\n","random.array.minstd.normalized":"var out = random.array.minstd.normalized( 3 )\n","random.array.minstd.factory":"var fcn = random.array.minstd.factory();\nvar out = fcn( 3 )\n","random.array.minstd.PRNG":"var prng = random.array.minstd.PRNG;\n","random.array.minstd.seed":"var seed = random.array.minstd.seed;\n","random.array.minstd.seedLength":"var len = random.array.minstd.seedLength;\n","random.array.minstd.state":"var out = random.array.minstd( 3 )\nvar state = random.array.minstd.state;\nout = random.array.minstd( 3 )\nout = random.array.minstd( 3 )\nrandom.array.minstd.state = state;\nout = random.array.minstd( 3 )\n","random.array.minstd.stateLength":"var len = random.array.minstd.stateLength;\n","random.array.minstd.byteLength":"var sz = random.array.minstd.byteLength;\n","random.array.minstdShuffle":"var out = random.array.minstdShuffle( 3 )\n","random.array.minstdShuffle.normalized":"var out = random.array.minstdShuffle.normalized( 3 )\n","random.array.minstdShuffle.factory":"var fcn = random.array.minstdShuffle.factory();\nvar out = fcn( 3 )\n","random.array.minstdShuffle.PRNG":"var prng = random.array.minstdShuffle.PRNG;\n","random.array.minstdShuffle.seed":"var seed = random.array.minstdShuffle.seed;\n","random.array.minstdShuffle.seedLength":"var len = random.array.minstdShuffle.seedLength;\n","random.array.minstdShuffle.state":"var out = random.array.minstdShuffle( 3 )\nvar state = random.array.minstdShuffle.state;\nout = random.array.minstdShuffle( 3 )\nout = random.array.minstdShuffle( 3 )\nrandom.array.minstdShuffle.state = state;\nout = random.array.minstdShuffle( 3 )\n","random.array.minstdShuffle.stateLength":"var len = random.array.minstdShuffle.stateLength;\n","random.array.minstdShuffle.byteLength":"var sz = random.array.minstdShuffle.byteLength;\n","random.array.mt19937":"var out = random.array.mt19937( 3 )\n","random.array.mt19937.normalized":"var out = random.array.mt19937.normalized( 3 )\n","random.array.mt19937.factory":"var fcn = random.array.mt19937.factory();\nvar out = fcn( 3 )\n","random.array.mt19937.PRNG":"var prng = random.array.mt19937.PRNG;\n","random.array.mt19937.seed":"var seed = random.array.mt19937.seed;\n","random.array.mt19937.seedLength":"var len = random.array.mt19937.seedLength;\n","random.array.mt19937.state":"var out = random.array.mt19937( 3 )\nvar state = random.array.mt19937.state;\nout = random.array.mt19937( 3 )\nout = random.array.mt19937( 3 )\nrandom.array.mt19937.state = state;\nout = random.array.mt19937( 3 )\n","random.array.mt19937.stateLength":"var len = random.array.mt19937.stateLength;\n","random.array.mt19937.byteLength":"var sz = random.array.mt19937.byteLength;\n","random.array.negativeBinomial":"var out = random.array.negativeBinomial( 3, 10, 0.5 )\n","random.array.negativeBinomial.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.negativeBinomial.assign( 10, 0.5, x )\nvar bool = ( out === x )\n","random.array.negativeBinomial.factory":"var fcn = random.array.negativeBinomial.factory();\nvar out = fcn( 3, 10, 0.5 )\nfcn = random.array.negativeBinomial.factory( 10, 0.5 );\nout = fcn( 3 )\n","random.array.negativeBinomial.PRNG":"var prng = random.array.negativeBinomial.PRNG;\n","random.array.negativeBinomial.seed":"var seed = random.array.negativeBinomial.seed;\n","random.array.negativeBinomial.seedLength":"var len = random.array.negativeBinomial.seedLength;\n","random.array.negativeBinomial.state":"var out = random.array.negativeBinomial( 3, 10, 0.5 )\nvar state = random.array.negativeBinomial.state\nout = random.array.negativeBinomial( 3, 10, 0.5 )\nout = random.array.negativeBinomial( 3, 10, 0.5 )\nrandom.array.negativeBinomial.state = state;\nout = random.array.negativeBinomial( 3, 10, 0.5 )\n","random.array.negativeBinomial.stateLength":"var len = random.array.negativeBinomial.stateLength;\n","random.array.negativeBinomial.byteLength":"var sz = random.array.negativeBinomial.byteLength;\n","random.array.normal":"var out = random.array.normal( 3, 2.0, 5.0 )\n","random.array.normal.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.normal.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.normal.factory":"var fcn = random.array.normal.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.normal.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.normal.PRNG":"var prng = random.array.normal.PRNG;\n","random.array.normal.seed":"var seed = random.array.normal.seed;\n","random.array.normal.seedLength":"var len = random.array.normal.seedLength;\n","random.array.normal.state":"var out = random.array.normal( 3, 2.0, 5.0 )\nvar state = random.array.normal.state\nout = random.array.normal( 3, 2.0, 5.0 )\nout = random.array.normal( 3, 2.0, 5.0 )\nrandom.array.normal.state = state;\nout = random.array.normal( 3, 2.0, 5.0 )\n","random.array.normal.stateLength":"var len = random.array.normal.stateLength;\n","random.array.normal.byteLength":"var sz = random.array.normal.byteLength;\n","random.array.pareto1":"var out = random.array.pareto1( 3, 2.0, 5.0 )\n","random.array.pareto1.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.pareto1.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.pareto1.factory":"var fcn = random.array.pareto1.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.pareto1.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.pareto1.PRNG":"var prng = random.array.pareto1.PRNG;\n","random.array.pareto1.seed":"var seed = random.array.pareto1.seed;\n","random.array.pareto1.seedLength":"var len = random.array.pareto1.seedLength;\n","random.array.pareto1.state":"var out = random.array.pareto1( 3, 2.0, 5.0 )\nvar state = random.array.pareto1.state\nout = random.array.pareto1( 3, 2.0, 5.0 )\nout = random.array.pareto1( 3, 2.0, 5.0 )\nrandom.array.pareto1.state = state;\nout = random.array.pareto1( 3, 2.0, 5.0 )\n","random.array.pareto1.stateLength":"var len = random.array.pareto1.stateLength;\n","random.array.pareto1.byteLength":"var sz = random.array.pareto1.byteLength;\n","random.array.poisson":"var out = random.array.poisson( 3, 2.0 )\n","random.array.poisson.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.poisson.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.poisson.factory":"var fcn = random.array.poisson.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.poisson.factory( 2.0 );\nout = fcn( 3 )\n","random.array.poisson.PRNG":"var prng = random.array.poisson.PRNG;\n","random.array.poisson.seed":"var seed = random.array.poisson.seed;\n","random.array.poisson.seedLength":"var len = random.array.poisson.seedLength;\n","random.array.poisson.state":"var out = random.array.poisson( 3, 2.0 )\nvar state = random.array.poisson.state\nout = random.array.poisson( 3, 2.0 )\nout = random.array.poisson( 3, 2.0 )\nrandom.array.poisson.state = state;\nout = random.array.poisson( 3, 2.0 )\n","random.array.poisson.stateLength":"var len = random.array.poisson.stateLength;\n","random.array.poisson.byteLength":"var sz = random.array.poisson.byteLength;\n","random.array.randu":"var out = random.array.randu( 3 )\n","random.array.randu.factory":"var fcn = random.array.randu.factory();\nvar out = fcn( 3 )\n","random.array.randu.PRNG":"var prng = random.array.randu.PRNG;\n","random.array.randu.seed":"var seed = random.array.randu.seed;\n","random.array.randu.seedLength":"var len = random.array.randu.seedLength;\n","random.array.randu.state":"var out = random.array.randu( 3 )\nvar state = random.array.randu.state;\nout = random.array.randu( 3 )\nout = random.array.randu( 3 )\nrandom.array.randu.state = state;\nout = random.array.randu( 3 )\n","random.array.randu.stateLength":"var len = random.array.randu.stateLength;\n","random.array.randu.byteLength":"var sz = random.array.randu.byteLength;\n","random.array.rayleigh":"var out = random.array.rayleigh( 3, 2.0 )\n","random.array.rayleigh.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.rayleigh.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.rayleigh.factory":"var fcn = random.array.rayleigh.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.rayleigh.factory( 2.0 );\nout = fcn( 3 )\n","random.array.rayleigh.PRNG":"var prng = random.array.rayleigh.PRNG;\n","random.array.rayleigh.seed":"var seed = random.array.rayleigh.seed;\n","random.array.rayleigh.seedLength":"var len = random.array.rayleigh.seedLength;\n","random.array.rayleigh.state":"var out = random.array.rayleigh( 3, 2.0 )\nvar state = random.array.rayleigh.state\nout = random.array.rayleigh( 3, 2.0 )\nout = random.array.rayleigh( 3, 2.0 )\nrandom.array.rayleigh.state = state;\nout = random.array.rayleigh( 3, 2.0 )\n","random.array.rayleigh.stateLength":"var len = random.array.rayleigh.stateLength;\n","random.array.rayleigh.byteLength":"var sz = random.array.rayleigh.byteLength;\n","random.array.t":"var out = random.array.t( 3, 2.0 )\n","random.array.t.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.t.assign( 2.0, x )\nvar bool = ( out === x )\n","random.array.t.factory":"var fcn = random.array.t.factory();\nvar out = fcn( 3, 2.0 )\nfcn = random.array.t.factory( 2.0 );\nout = fcn( 3 )\n","random.array.t.PRNG":"var prng = random.array.t.PRNG;\n","random.array.t.seed":"var seed = random.array.t.seed;\n","random.array.t.seedLength":"var len = random.array.t.seedLength;\n","random.array.t.state":"var out = random.array.t( 3, 2.0 )\nvar state = random.array.t.state\nout = random.array.t( 3, 2.0 )\nout = random.array.t( 3, 2.0 )\nrandom.array.t.state = state;\nout = random.array.t( 3, 2.0 )\n","random.array.t.stateLength":"var len = random.array.t.stateLength;\n","random.array.t.byteLength":"var sz = random.array.t.byteLength;\n","random.array.triangular":"var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n","random.array.triangular.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.triangular.assign( 2.0, 5.0, 3.0, x )\nvar bool = ( out === x )\n","random.array.triangular.factory":"var fcn = random.array.triangular.factory();\nvar out = fcn( 3, 2.0, 5.0, 3.0 )\nfcn = random.array.triangular.factory( 2.0, 5.0, 3.0 );\nout = fcn( 3 )\n","random.array.triangular.PRNG":"var prng = random.array.triangular.PRNG;\n","random.array.triangular.seed":"var seed = random.array.triangular.seed;\n","random.array.triangular.seedLength":"var len = random.array.triangular.seedLength;\n","random.array.triangular.state":"var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\nvar state = random.array.triangular.state\nout = random.array.triangular( 3, 2.0, 5.0, 3.0 )\nout = random.array.triangular( 3, 2.0, 5.0, 3.0 )\nrandom.array.triangular.state = state;\nout = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n","random.array.triangular.stateLength":"var len = random.array.triangular.stateLength;\n","random.array.triangular.byteLength":"var sz = random.array.triangular.byteLength;\n","random.array.uniform":"var out = random.array.uniform( 3, 2.0, 5.0 )\n","random.array.uniform.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.uniform.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.uniform.factory":"var fcn = random.array.uniform.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.uniform.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.uniform.PRNG":"var prng = random.array.uniform.PRNG;\n","random.array.uniform.seed":"var seed = random.array.uniform.seed;\n","random.array.uniform.seedLength":"var len = random.array.uniform.seedLength;\n","random.array.uniform.state":"var out = random.array.uniform( 3, 2.0, 5.0 )\nvar state = random.array.uniform.state\nout = random.array.uniform( 3, 2.0, 5.0 )\nout = random.array.uniform( 3, 2.0, 5.0 )\nrandom.array.uniform.state = state;\nout = random.array.uniform( 3, 2.0, 5.0 )\n","random.array.uniform.stateLength":"var len = random.array.uniform.stateLength;\n","random.array.uniform.byteLength":"var sz = random.array.uniform.byteLength;\n","random.array.weibull":"var out = random.array.weibull( 3, 2.0, 5.0 )\n","random.array.weibull.assign":"var x = azeros( 3, 'float64' );\nvar out = random.array.weibull.assign( 2.0, 5.0, x )\nvar bool = ( out === x )\n","random.array.weibull.factory":"var fcn = random.array.weibull.factory();\nvar out = fcn( 3, 2.0, 5.0 )\nfcn = random.array.weibull.factory( 2.0, 5.0 );\nout = fcn( 3 )\n","random.array.weibull.PRNG":"var prng = random.array.weibull.PRNG;\n","random.array.weibull.seed":"var seed = random.array.weibull.seed;\n","random.array.weibull.seedLength":"var len = random.array.weibull.seedLength;\n","random.array.weibull.state":"var out = random.array.weibull( 3, 2.0, 5.0 )\nvar state = random.array.weibull.state\nout = random.array.weibull( 3, 2.0, 5.0 )\nout = random.array.weibull( 3, 2.0, 5.0 )\nrandom.array.weibull.state = state;\nout = random.array.weibull( 3, 2.0, 5.0 )\n","random.array.weibull.stateLength":"var len = random.array.weibull.stateLength;\n","random.array.weibull.byteLength":"var sz = random.array.weibull.byteLength;\n","random.iterators.arcsine":"var it = random.iterators.arcsine( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.bernoulli":"var it = random.iterators.bernoulli( 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.beta":"var it = random.iterators.beta( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.betaprime":"var it = random.iterators.betaprime( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.binomial":"var it = random.iterators.binomial( 10, 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.boxMuller":"var it = random.iterators.boxMuller();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.cauchy":"var it = random.iterators.cauchy( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.chi":"var it = random.iterators.chi( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.chisquare":"var it = random.iterators.chisquare( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.cosine":"var it = random.iterators.cosine( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.discreteUniform":"var it = random.iterators.discreteUniform( 0, 3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.erlang":"var it = random.iterators.erlang( 1, 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.exponential":"var it = random.iterators.exponential( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.f":"var it = random.iterators.f( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.frechet":"var it = random.iterators.frechet( 1.0, 1.0, 0.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.gamma":"var it = random.iterators.gamma( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.geometric":"var it = random.iterators.geometric( 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.gumbel":"var it = random.iterators.gumbel( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.hypergeometric":"var it = random.iterators.hypergeometric( 20, 10, 7 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.improvedZiggurat":"var it = random.iterators.improvedZiggurat();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.invgamma":"var it = random.iterators.invgamma( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.kumaraswamy":"var it = random.iterators.kumaraswamy( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.laplace":"var it = random.iterators.laplace( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.levy":"var it = random.iterators.levy( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.logistic":"var it = random.iterators.logistic( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.lognormal":"var it = random.iterators.lognormal( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.minstd":"var it = random.iterators.minstd();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.minstdShuffle":"var it = random.iterators.minstdShuffle();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.mt19937":"var it = random.iterators.mt19937();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.negativeBinomial":"var it = random.iterators.negativeBinomial( 10, 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.normal":"var it = random.iterators.normal( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.pareto1":"var it = random.iterators.pareto1( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.poisson":"var it = random.iterators.poisson( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.randi":"var it = random.iterators.randi();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.randn":"var it = random.iterators.randn();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.randu":"var it = random.iterators.randu();\nvar r = it.next().value\nr = it.next().value\n","random.iterators.rayleigh":"var it = random.iterators.rayleigh( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.t":"var it = random.iterators.t( 1.5 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.triangular":"var it = random.iterators.triangular( 0.0, 1.0, 0.3 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.uniform":"var it = random.iterators.uniform( 0.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.iterators.weibull":"var it = random.iterators.weibull( 1.0, 1.0 );\nvar r = it.next().value\nr = it.next().value\n","random.streams.arcsine":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.arcsine( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.arcsine.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.arcsine.factory( opts );\n","random.streams.arcsine.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.arcsine.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.bernoulli":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.bernoulli( 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.bernoulli.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.bernoulli.factory( opts );\n","random.streams.bernoulli.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.bernoulli.objectMode( 0.3, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.beta":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.beta( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.beta.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.beta.factory( opts );\n","random.streams.beta.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.beta.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.betaprime":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.betaprime( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.betaprime.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.betaprime.factory( opts );\n","random.streams.betaprime.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.betaprime.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.binomial":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.binomial( 20, 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.binomial.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.binomial.factory( opts );\n","random.streams.binomial.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.binomial.objectMode( 20, 0.5, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.boxMuller":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.boxMuller( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.boxMuller.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.boxMuller.factory( opts );\n","random.streams.boxMuller.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.boxMuller.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.cauchy":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cauchy( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.cauchy.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.cauchy.factory( opts );\n","random.streams.cauchy.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cauchy.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.chi":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chi( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.chi.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.chi.factory( opts );\n","random.streams.chi.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chi.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.chisquare":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chisquare( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.chisquare.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.chisquare.factory( opts );\n","random.streams.chisquare.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.chisquare.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.cosine":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cosine( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.cosine.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.cosine.factory( opts );\n","random.streams.cosine.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.cosine.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.discreteUniform":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.discreteUniform( 2, 5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.discreteUniform.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.discreteUniform.factory( opts );\n","random.streams.discreteUniform.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.discreteUniform.objectMode( 2, 5, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.erlang":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.erlang( 2, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.erlang.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.erlang.factory( opts );\n","random.streams.erlang.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.erlang.objectMode( 2, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.exponential":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.exponential( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.exponential.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.exponential.factory( opts );\n","random.streams.exponential.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.exponential.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.f":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.f( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.f.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.f.factory( opts );\n","random.streams.f.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.f.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.frechet":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.frechet( 2.0, 5.0, 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.frechet.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.frechet.factory( opts );\n","random.streams.frechet.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.frechet.objectMode( 2.0, 5.0, 3.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.gamma":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gamma( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.gamma.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.gamma.factory( opts );\n","random.streams.gamma.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gamma.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.geometric":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.geometric( 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.geometric.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.geometric.factory( opts );\n","random.streams.geometric.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.geometric.objectMode( 0.3, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.gumbel":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gumbel( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.gumbel.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.gumbel.factory( opts );\n","random.streams.gumbel.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.gumbel.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.hypergeometric":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.hypergeometric( 5, 3, 2, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.hypergeometric.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.hypergeometric.factory( opts );\n","random.streams.hypergeometric.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.hypergeometric.objectMode( 5, 3, 2, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.improvedZiggurat":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.improvedZiggurat( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.improvedZiggurat.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.improvedZiggurat.factory( opts );\n","random.streams.improvedZiggurat.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.improvedZiggurat.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.invgamma":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.invgamma( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.invgamma.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.invgamma.factory( opts );\n","random.streams.invgamma.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.invgamma.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.kumaraswamy":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.kumaraswamy( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.kumaraswamy.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.kumaraswamy.factory( opts );\n","random.streams.kumaraswamy.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.kumaraswamy.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.laplace":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.laplace( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.laplace.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.laplace.factory( opts );\n","random.streams.laplace.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.laplace.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.levy":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.levy( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.levy.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.levy.factory( opts );\n","random.streams.levy.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.levy.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.logistic":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.logistic( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.logistic.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.logistic.factory( opts );\n","random.streams.logistic.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.logistic.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.lognormal":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.lognormal( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.lognormal.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.lognormal.factory( opts );\n","random.streams.lognormal.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.lognormal.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.minstd":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstd( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.minstd.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.minstd.factory( opts );\n","random.streams.minstd.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstd.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.minstdShuffle":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstdShuffle( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.minstdShuffle.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.minstdShuffle.factory( opts );\n","random.streams.minstdShuffle.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.minstdShuffle.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.mt19937":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.mt19937( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.mt19937.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.mt19937.factory( opts );\n","random.streams.mt19937.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.mt19937.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.negativeBinomial":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.negativeBinomial( 20.0, 0.5, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.negativeBinomial.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.negativeBinomial.factory( opts );\n","random.streams.negativeBinomial.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.negativeBinomial.objectMode( 20.0, 0.5, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.normal":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.normal( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.normal.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.normal.factory( opts );\n","random.streams.normal.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.normal.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.pareto1":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.pareto1( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.pareto1.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.pareto1.factory( opts );\n","random.streams.pareto1.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.pareto1.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.poisson":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.poisson( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.poisson.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.poisson.factory( opts );\n","random.streams.poisson.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.poisson.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.randi":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randi( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.randi.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.randi.factory( opts );\n","random.streams.randi.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randi.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.randn":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randn( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.randn.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.randn.factory( opts );\n","random.streams.randn.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randn.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.randu":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randu( opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.randu.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.randu.factory( opts );\n","random.streams.randu.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.randu.objectMode( opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.rayleigh":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.rayleigh( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.rayleigh.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.rayleigh.factory( opts );\n","random.streams.rayleigh.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.rayleigh.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.t":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.t( 3.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.t.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.t.factory( opts );\n","random.streams.t.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.t.objectMode( 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.triangular":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.triangular( 2.0, 5.0, 4.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.triangular.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.triangular.factory( opts );\n","random.streams.triangular.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.triangular.objectMode( 2.0, 5.0, 4.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.uniform":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.uniform( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.uniform.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.uniform.factory( opts );\n","random.streams.uniform.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.uniform.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.streams.weibull":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.weibull( 2.0, 5.0, opts );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","random.streams.weibull.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = random.streams.weibull.factory( opts );\n","random.streams.weibull.objectMode":"function fcn( v ) { console.log( v ); };\nvar opts = { 'iter': 10 };\nvar s = random.streams.weibull.objectMode( 2.0, 5.0, opts );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","random.strided.arcsine":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.arcsine( out.length, a, 1, b, 1, out, 1 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.arcsine( 3, a, -2, b, 1, out, 1 )\n","random.strided.arcsine.ndarray":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.arcsine.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.arcsine.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.bernoulli":"var out = azeros( 5, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n","random.strided.bernoulli.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.bernoulli.ndarray( out.length, [ 0.5 ], 0, 0, out, 1, 0 )\n","random.strided.bernoulli.factory":"var fcn = random.strided.bernoulli.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 0.5 ], 0, out, 1 )\n","random.strided.bernoulli.PRNG":"var prng = random.strided.bernoulli.PRNG;\n","random.strided.bernoulli.seed":"var seed = random.strided.bernoulli.seed;\n","random.strided.bernoulli.seedLength":"var len = random.strided.bernoulli.seedLength;\n","random.strided.bernoulli.state":"var out = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\nvar state = random.strided.bernoulli.state\nout = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\nrandom.strided.bernoulli.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n","random.strided.bernoulli.stateLength":"var len = random.strided.bernoulli.stateLength;\n","random.strided.bernoulli.byteLength":"var sz = random.strided.bernoulli.byteLength;\n","random.strided.beta":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.beta( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.beta( 3, a, -2, b, 1, out, 1 )\n","random.strided.beta.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.beta.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.beta.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.betaprime":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.betaprime( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.betaprime( 3, a, -2, b, 1, out, 1 )\n","random.strided.betaprime.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.betaprime.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.betaprime.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.chi":"var out = azeros( 5, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chi.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.chi.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.chi.factory":"var fcn = random.strided.chi.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chi.PRNG":"var prng = random.strided.chi.PRNG;\n","random.strided.chi.seed":"var seed = random.strided.chi.seed;\n","random.strided.chi.seedLength":"var len = random.strided.chi.seedLength;\n","random.strided.chi.state":"var out = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.chi.state\nout = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.chi.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chi.stateLength":"var len = random.strided.chi.stateLength;\n","random.strided.chi.byteLength":"var sz = random.strided.chi.byteLength;\n","random.strided.chisquare":"var out = azeros( 5, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chisquare.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.chisquare.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.chisquare.factory":"var fcn = random.strided.chisquare.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chisquare.PRNG":"var prng = random.strided.chisquare.PRNG;\n","random.strided.chisquare.seed":"var seed = random.strided.chisquare.seed;\n","random.strided.chisquare.seedLength":"var len = random.strided.chisquare.seedLength;\n","random.strided.chisquare.state":"var out = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.chisquare.state\nout = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.chisquare.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.chisquare.stateLength":"var len = random.strided.chisquare.stateLength;\n","random.strided.chisquare.byteLength":"var sz = random.strided.chisquare.byteLength;\n","random.strided.cosine":"var mu = linspace( 0.0, 1.0, 5 );\nvar s = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.cosine( out.length, mu, 1, s, 1, out, 1 )\nmu = linspace( 0.0, 1.0, 6 );\ns = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.cosine( 3, mu, -2, s, 1, out, 1 )\n","random.strided.cosine.ndarray":"var mu = linspace( 0.0, 1.0, 5 );\nvar s = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.cosine.ndarray( out.length, mu, 1, 0, s, 1, 0, out, 1, 0 )\nmu = linspace( 0.0, 1.0, 6 );\ns = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.cosine.ndarray( 3, mu, 2, 1, s, -1, s.length-1, out, 1, 0 )\n","random.strided.discreteUniform":"var a = [ -10, -5, 0, 5, 10 ];\nvar b = [ 20, 20, 20, 20, 20 ];\nvar out = azeros( 5, 'generic' );\nrandom.strided.discreteUniform( out.length, a, 1, b, 1, out, 1 )\na = [ -10, -5, 0, 5, 10, 15 ];\nb = [ 20, 20, 20, 20, 20, 20 ];\nout = azeros( 6, 'generic' );\nrandom.strided.discreteUniform( 3, a, -2, b, 1, out, 1 )\n","random.strided.discreteUniform.ndarray":"var a = [ -10, -5, 0, 5, 10 ];\nvar b = [ 20, 20, 20, 20, 20 ];\nvar out = azeros( 5, 'generic' );\nrandom.strided.discreteUniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = [ -10, -5, 0, 5, 10, 15 ];\nb = [ 20, 20, 20, 20, 20, 20 ];\nout = azeros( 6, 'generic' );\nrandom.strided.discreteUniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.exponential":"var out = azeros( 5, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.exponential.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.exponential.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.exponential.factory":"var fcn = random.strided.exponential.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.exponential.PRNG":"var prng = random.strided.exponential.PRNG;\n","random.strided.exponential.seed":"var seed = random.strided.exponential.seed;\n","random.strided.exponential.seedLength":"var len = random.strided.exponential.seedLength;\n","random.strided.exponential.state":"var out = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.exponential.state\nout = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.exponential.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.exponential.stateLength":"var len = random.strided.exponential.stateLength;\n","random.strided.exponential.byteLength":"var sz = random.strided.exponential.byteLength;\n","random.strided.gamma":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.gamma( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.gamma( 3, a, -2, b, 1, out, 1 )\n","random.strided.gamma.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.gamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.gamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.geometric":"var out = azeros( 5, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n","random.strided.geometric.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.geometric.ndarray( out.length, [ 0.01 ], 0, 0, out, 1, 0 )\n","random.strided.geometric.factory":"var fcn = random.strided.geometric.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 0.01 ], 0, out, 1 )\n","random.strided.geometric.PRNG":"var prng = random.strided.geometric.PRNG;\n","random.strided.geometric.seed":"var seed = random.strided.geometric.seed;\n","random.strided.geometric.seedLength":"var len = random.strided.geometric.seedLength;\n","random.strided.geometric.state":"var out = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\nvar state = random.strided.geometric.state\nout = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\nrandom.strided.geometric.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n","random.strided.geometric.stateLength":"var len = random.strided.geometric.stateLength;\n","random.strided.geometric.byteLength":"var sz = random.strided.geometric.byteLength;\n","random.strided.invgamma":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.invgamma( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.invgamma( 3, a, -2, b, 1, out, 1 )\n","random.strided.invgamma.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.invgamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.invgamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.lognormal":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.lognormal( out.length, mu, 1, sigma, 1, out, 1 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.lognormal( 3, mu, -2, sigma, 1, out, 1 )\n","random.strided.lognormal.ndarray":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.lognormal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.lognormal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n","random.strided.minstd":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd( out.length, out, 1 )\n","random.strided.minstd.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd.ndarray( out.length, out, 1, 0 )\n","random.strided.minstd.normalized":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd.normalized( out.length, out, 1 )\n","random.strided.minstd.normalized.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstd.normalized.ndarray( out.length, out, 1, 0 )\n","random.strided.minstdShuffle":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle( out.length, out, 1 )\n","random.strided.minstdShuffle.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle.ndarray( out.length, out, 1, 0 )\n","random.strided.minstdShuffle.normalized":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle.normalized( out.length, out, 1 )\n","random.strided.minstdShuffle.normalized.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.minstdShuffle.normalized.ndarray( out.length, out, 1, 0 )\n","random.strided.mt19937":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937( out.length, out, 1 )\n","random.strided.mt19937.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937.ndarray( out.length, out, 1, 0 )\n","random.strided.mt19937.normalized":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937.normalized( out.length, out, 1 )\n","random.strided.mt19937.normalized.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.mt19937.normalized.ndarray( out.length, out, 1, 0 )\n","random.strided.normal":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.normal( out.length, mu, 1, sigma, 1, out, 1 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.normal( 3, mu, -2, sigma, 1, out, 1 )\n","random.strided.normal.ndarray":"var mu = linspace( 0.0, 1.0, 5 );\nvar sigma = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.normal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\nmu = linspace( 0.0, 1.0, 6 );\nsigma = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.normal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n","random.strided.poisson":"var out = azeros( 5, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.poisson.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.poisson.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.poisson.factory":"var fcn = random.strided.poisson.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.poisson.PRNG":"var prng = random.strided.poisson.PRNG;\n","random.strided.poisson.seed":"var seed = random.strided.poisson.seed;\n","random.strided.poisson.seedLength":"var len = random.strided.poisson.seedLength;\n","random.strided.poisson.state":"var out = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.poisson.state\nout = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.poisson.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.poisson.stateLength":"var len = random.strided.poisson.stateLength;\n","random.strided.poisson.byteLength":"var sz = random.strided.poisson.byteLength;\n","random.strided.randu":"var out = azeros( 5, 'generic' );\nrandom.strided.randu( out.length, out, 1 )\n","random.strided.randu.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.randu.ndarray( out.length, out, 1, 0 )\n","random.strided.rayleigh":"var out = azeros( 5, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.rayleigh.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.rayleigh.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.rayleigh.factory":"var fcn = random.strided.rayleigh.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.rayleigh.PRNG":"var prng = random.strided.rayleigh.PRNG;\n","random.strided.rayleigh.seed":"var seed = random.strided.rayleigh.seed;\n","random.strided.rayleigh.seedLength":"var len = random.strided.rayleigh.seedLength;\n","random.strided.rayleigh.state":"var out = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.rayleigh.state\nout = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.rayleigh.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.rayleigh.stateLength":"var len = random.strided.rayleigh.stateLength;\n","random.strided.rayleigh.byteLength":"var sz = random.strided.rayleigh.byteLength;\n","random.strided.t":"var out = azeros( 5, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.t.ndarray":"var out = azeros( 5, 'generic' );\nrandom.strided.t.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n","random.strided.t.factory":"var fcn = random.strided.t.factory();\nvar out = azeros( 5, 'generic' );\nfcn( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.t.PRNG":"var prng = random.strided.t.PRNG;\n","random.strided.t.seed":"var seed = random.strided.t.seed;\n","random.strided.t.seedLength":"var len = random.strided.t.seedLength;\n","random.strided.t.state":"var out = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\nvar state = random.strided.t.state\nout = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\nout = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\nrandom.strided.t.state = state;\nout = azeros( 3, 'generic' );\nrandom.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n","random.strided.t.stateLength":"var len = random.strided.t.stateLength;\n","random.strided.t.byteLength":"var sz = random.strided.t.byteLength;\n","random.strided.uniform":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.uniform( out.length, a, 1, b, 1, out, 1 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.uniform( 3, a, -2, b, 1, out, 1 )\n","random.strided.uniform.ndarray":"var a = linspace( 0.0, 1.0, 5 );\nvar b = linspace( 2.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.uniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 0.0, 1.0, 6 );\nb = linspace( 2.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.uniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","random.strided.weibull":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.weibull( out.length, a, 1, b, 1, out, 1 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.weibull( 3, a, -2, b, 1, out, 1 )\n","random.strided.weibull.ndarray":"var a = linspace( 1.0, 5.0, 5 );\nvar b = linspace( 1.0, 5.0, 5 );\nvar out = azeros( 5, 'generic' );\nrandom.strided.weibull.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\na = linspace( 1.0, 5.0, 6 );\nb = linspace( 1.0, 5.0, 6 );\nout = azeros( 6, 'generic' );\nrandom.strided.weibull.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n","ranks":"var arr = [ 1.1, 2.0, 3.5, 0.0, 2.4 ] ;\nvar out = ranks( arr )\narr =  [ 2, 2, 1, 4, 3 ];\nout = ranks( arr )\narr = [ null, 2, 2, 1, 4, 3, NaN, NaN ];\nout = ranks( arr )\n","readDir":"function onRead( error, data ) {\n if ( error ) {\n     console.error( error.message );\n } else {\n     console.log( data );\n }\n };\nreadDir( './beep/boop', onRead );\n","readDir.sync":"var out = readDir.sync( './beep/boop' );\n","readFile":"function onRead( error, data ) {\n if ( error ) {\n     console.error( error.message );\n } else {\n     console.log( data );\n }\n };\nreadFile( './beep/boop.js', onRead );\n","readFile.sync":"var out = readFile.sync( './beep/boop.js' );\n","readFileList":"function onRead( error, data ) {\n if ( error ) {\n     console.error( error.message );\n } else {\n     console.log( data );\n }\n };\nvar filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\nreadFileList( filepaths, onRead );\n","readFileList.sync":"var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\nvar out = readFileList.sync( filepaths );\n","readJSON":"function onRead( error, data ) {\n if ( error ) {\n     console.error( error.message );\n } else {\n     console.log( data );\n }\n };\nreadJSON( './beep/boop.json', onRead );\n","readJSON.sync":"var out = readJSON.sync( './beep/boop.json' );\n","readWASM":"function onRead( error, data ) {\n if ( error ) {\n     console.error( error.message );\n } else {\n     console.log( data );\n }\n };\nreadWASM( './beep/boop.wasm', onRead );\n","readWASM.sync":"var out = readWASM.sync( './beep/boop.wasm' );\n","real":"var z = new Complex128( 5.0, 3.0 );\nvar re = real( z )\n","realarray":"var arr = realarray()\narr = realarray( 'float32' )\nvar arr = realarray( 5 )\narr = realarray( 5, 'int32' )\nvar arr1 = realarray( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = realarray( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = realarray( arr1, 'float32' )\nvar buf = new ArrayBuffer( 16 );\nvar arr = realarray( buf, 0, 4, 'float32' )\n","realarrayCtors":"var ctor = realarrayCtors( 'float64' )\nctor = realarrayCtors( 'float' )\n","realarrayDataTypes":"var out = realarrayDataTypes()\n","realf":"var z = new Complex64( 5.0, 3.0 );\nvar re = realf( z )\n","realmax":"var m = realmax( 'float16' )\nm = realmax( 'float32' )\n","realmin":"var m = realmin( 'float16' )\nm = realmin( 'float32' )\n","reBasename":"var RE = reBasename()\nvar RE_POSIX = reBasename( 'posix' );\nvar RE_WIN32 = reBasename( 'win32' );\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reBasename.REGEXP":"var RE = reBasename.REGEXP\n","reBasename.REGEXP_POSIX":"var base = reBasename.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n","reBasename.REGEXP_WIN32":"var base = reBasename.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reBasenamePosix":"var RE_BASENAME_POSIX = reBasenamePosix();\nvar base = RE_BASENAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( 'index.js' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( '.' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( './' )[ 1 ]\nbase = RE_BASENAME_POSIX.exec( '' )[ 1 ]\n","reBasenamePosix.REGEXP":"var base = reBasenamePosix.REGEXP.exec( 'foo/bar/index.js' )[ 1 ]\n","reBasenameWindows":"var RE_BASENAME_WINDOWS = reBasenameWindows();\nvar base = RE_BASENAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\index.js' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'foo\\\\file.pdf' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'foo\\\\bar\\\\file' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( 'index.js' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( '.' )[ 1 ]\nbase = RE_BASENAME_WINDOWS.exec( '' )[ 1 ]\n","reBasenameWindows.REGEXP":"var match = reBasenameWindows.REGEXP.exec( 'foo\\\\file.pdf' )[ 1 ]\n","reColorHexadecimal":"var RE = reColorHexadecimal();\nvar bool = RE.test( 'ffffff' )\nbool = RE.test( '000' )\nbool = RE.test( 'beep' )\n","reColorHexadecimal.REGEXP":"var bool = reColorHexadecimal.REGEXP.test( 'ffffff' )\nbool = reColorHexadecimal.REGEXP.test( '000' )\nbool = reColorHexadecimal.REGEXP.test( 'beep' )\n","reColorHexadecimal.REGEXP_SHORTHAND":"var bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'ffffff' )\nbool = reColorHexadecimal.REGEXP_SHORTHAND.test( '000' )\nbool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'beep' )\n","reColorHexadecimal.REGEXP_EITHER":"var bool = reColorHexadecimal.REGEXP_EITHER.test( 'ffffff' )\nbool = reColorHexadecimal.REGEXP_EITHER.test( '000' )\nbool = reColorHexadecimal.REGEXP_EITHER.test( 'beep' )\n","reDecimalNumber":"var RE = reDecimalNumber();\nvar bool = RE.test( '1.234' )\nbool = RE.test( '-1.234' )\nbool = RE.test( '0.0' )\nbool = RE.test( '.0' )\nbool = RE.test( '0' )\nbool = RE.test( 'beep' )\nvar re = reDecimalNumber({ 'flags': 'g' });\nvar str = '1.234 5.6, 7.8';\nvar out = str.match( re )\n","reDecimalNumber.REGEXP":"var RE = reDecimalNumber.REGEXP;\nvar bool = RE.test( '1.234' )\nbool = RE.test( '-1.234' )\n","reDecimalNumber.REGEXP_CAPTURE":"var RE = reDecimalNumber.REGEXP_CAPTURE;\nvar str = '1.02';\nvar out = replace( str, RE, '$1 x $1' )\n","reDirname":"var RE = reDirname()\nvar RE_POSIX = reDirname( 'posix' );\nvar dir = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\nvar RE_WIN32 = reDirname( 'win32' );\ndir = RE_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reDirname.REGEXP":"var RE = reDirname.REGEXP\n","reDirname.REGEXP_POSIX":"var dir = reDirname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n","reDirname.REGEXP_WIN32":"var dir = reDirname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reDirnamePosix":"var RE = reDirnamePosix();\nvar dir = RE.exec( '/foo/bar/index.js' )[ 1 ]\ndir = RE.exec( './foo/bar/.gitignore' )[ 1 ]\ndir = RE.exec( 'foo/file.pdf' )[ 1 ]\ndir = RE.exec( '/foo/bar/file' )[ 1 ]\ndir = RE.exec( 'index.js' )[ 1 ]\ndir = RE.exec( '.' )[ 1 ]\ndir = RE.exec( './' )[ 1 ]\ndir = RE.exec( '' )[ 1 ]\n","reDirnamePosix.REGEXP":"var ext = reDirnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n","reDirnameWindows":"var RE = reDirnameWindows();\nvar dir = RE.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\ndir = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\ndir = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\ndir = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\ndir = RE.exec( 'index.js' )[ 1 ]\ndir = RE.exec( '' )[ 1 ]\n","reDirnameWindows.REGEXP":"var dir = reDirnameWindows.REGEXP.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n","reduce":"var f = naryFunction( base.add, 2 );\nvar arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\nvar out = reduce( arr, 0.0, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = reduce( arr, 0.0, f )\n","reduce2d":"var f = naryFunction( base.add, 2 );\nvar arr = [ [ 1, 2, 3 ], [ 4, 5, 6 ] ];\nvar out = reduce2d( arr, [ 0, 0 ], f )\n","reduceAsync":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     acc.sum += value;\n     next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n     throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nreduceAsync( arr, acc, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     acc.sum += value;\n     next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n     throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nreduceAsync( arr, acc, opts, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     acc.sum += value;\n     next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n     throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'series': false };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nreduceAsync( arr, acc, opts, fcn, done )\n","reduceAsync.factory":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     acc.sum += value;\n     next( null, acc );\n }\n };\nvar opts = { 'series': false };\nvar f = reduceAsync.factory( opts, fcn );\nfunction done( error, acc ) {\n if ( error ) {\n     throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 3000, 2500, 1000 ];\nvar acc = { 'sum': 0 };\nf( arr, acc, done )\nacc = { 'sum': 0 };\narr = [ 2000, 1500, 1000 ];\nf( arr, acc, done )\n","reduceRight":"var f = naryFunction( base.add, 2 );\nvar arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\nvar out = reduceRight( arr, 0.0, f )\narr = array( arr, { 'shape': [ 2, 3 ] } );\nout = reduceRight( arr, 0.0, f )\n","reduceRightAsync":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     acc.sum += value;\n     next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n     throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nreduceRightAsync( arr, acc, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     acc.sum += value;\n     next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n     throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nreduceRightAsync( arr, acc, opts, fcn, done )\nfunction fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     acc.sum += value;\n     next( null, acc );\n }\n };\nfunction done( error, acc ) {\n if ( error ) {\n     throw error;\n }\n console.log( acc.sum );\n };\nvar opts = { 'series': false };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nreduceRightAsync( arr, acc, opts, fcn, done )\n","reduceRightAsync.factory":"function fcn( acc, value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     acc.sum += value;\n     next( null, acc );\n }\n };\nvar opts = { 'series': false };\nvar f = reduceRightAsync.factory( opts, fcn );\nfunction done( error, acc ) {\n if ( error ) {\n     throw error;\n }\n console.log( acc.sum );\n };\nvar arr = [ 1000, 2500, 3000 ];\nvar acc = { 'sum': 0 };\nf( arr, acc, done )\nacc = { 'sum': 0 };\narr = [ 1000, 1500, 2000 ];\nf( arr, acc, done )\n","reDurationString":"var RE = reDurationString();\nvar parts = RE.exec( '3d2ms' )\nparts = RE.exec( '4h3m20s' )\n","reDurationString.REGEXP":"var bool = reDurationString.REGEXP.test( '3d2ms' )\nbool = reDurationString.REGEXP.test( 'foo' )\n","reEOL":"var RE_EOL = reEOL();\nvar bool = RE_EOL.test( '\\n' )\nbool = RE_EOL.test( '\\r\\n' )\nbool = RE_EOL.test( '\\\\r\\\\n' )\n","reEOL.REGEXP":"var bool = reEOL.REGEXP.test( 'abc' )\n","reEOL.REGEXP_CAPTURE":"var parts = reEOL.REGEXP_CAPTURE.exec( '\\n' )\n","reExtendedLengthPath":"var RE = reExtendedLengthPath();\nvar path = '\\\\\\\\?\\\\C:\\\\foo\\\\bar';\nvar bool = RE.test( path )\npath = '\\\\\\\\?\\\\UNC\\\\server\\\\share';\nbool = RE.test( path )\npath = 'C:\\\\foo\\\\bar';\nbool = RE.test( path )\npath = '/c/foo/bar';\nbool = RE.test( path )\npath = '/foo/bar';\nbool = RE.test( path )\n","reExtendedLengthPath.REGEXP":"var bool = reExtendedLengthPath.REGEXP.test( 'C:\\\\foo\\\\bar' )\n","reExtname":"var RE = reExtname()\nvar RE_POSIX = reExtname( 'posix' );\nvar ext = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\nvar RE_WIN32 = reExtname( 'win32' );\next = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reExtname.REGEXP":"var RE = reExtname.REGEXP\n","reExtname.REGEXP_POSIX":"var ext = reExtname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n","reExtname.REGEXP_WIN32":"var ext = reExtname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reExtnamePosix":"var RE = reExtnamePosix();\nvar ext = RE.exec( '/foo/bar/index.js' )[ 1 ]\next = RE.exec( './foo/bar/.gitignore' )[ 1 ]\next = RE.exec( 'foo/file.pdf' )[ 1 ]\next = RE.exec( '/foo/bar/file' )[ 1 ]\next = RE.exec( 'index.js' )[ 1 ]\next = RE.exec( '.' )[ 1 ]\next = RE.exec( './' )[ 1 ]\next = RE.exec( '' )[ 1 ]\n","reExtnamePosix.REGEXP":"var ext = reExtnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n","reExtnameWindows":"var RE = reExtnameWindows();\nvar ext = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\next = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\next = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\next = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\next = RE.exec( 'beep\\\\boop.' )[ 1 ]\next = RE.exec( 'index.js' )[ 1 ]\next = RE.exec( '' )[ 1 ]\n","reExtnameWindows.REGEXP":"var ext = reExtnameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n","reFilename":"var RE = reFilename()\nvar RE_POSIX = reFilename( 'posix' );\nvar parts = RE_POSIX.exec( '/foo/bar/index.js' ).slice()\nvar RE_WIN32 = reFilename( 'win32' );\nparts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\nvar str = RE.toString();\nvar bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n","reFilename.REGEXP":"var RE = reFilename.REGEXP\n","reFilename.REGEXP_POSIX":"var f = '/foo/bar/index.js';\nvar parts = reFilename.REGEXP_POSIX.exec( f ).slice()\n","reFilename.REGEXP_WIN32":"var f = 'C:\\\\foo\\\\bar\\\\index.js';\nvar parts = reFilename.REGEXP_WIN32.exec( f ).slice()\n","reFilenamePosix":"var RE = reFilenamePosix();\nvar parts = RE.exec( '/foo/bar/index.js' ).slice()\nparts = RE.exec( './foo/bar/.gitignore' ).slice()\nparts = RE.exec( 'foo/file.pdf' ).slice()\nparts = RE.exec( '/foo/bar/file' ).slice()\nparts = RE.exec( 'index.js' ).slice()\nparts = RE.exec( '.' ).slice()\nparts = RE.exec( './' ).slice()\nparts = RE.exec( '' ).slice()\n","reFilenamePosix.REGEXP":"var parts = reFilenamePosix.REGEXP.exec( '/foo/bar/index.js' ).slice()\n","reFilenameWindows":"var RE = reFilenameWindows();\nvar parts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\nparts = RE.exec( '\\\\foo\\\\bar\\\\.gitignore' ).slice()\nparts = RE.exec( 'foo\\\\file.pdf' ).slice()\nparts = RE.exec( '\\\\foo\\\\bar\\\\file' ).slice()\nparts = RE.exec( 'index.js' ).slice()\nparts = RE.exec( '.' ).slice()\nparts = RE.exec( './' ).slice()\nparts = RE.exec( '' ).slice()\n","reFilenameWindows.REGEXP":"var parts = reFilenameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n","reFromString":"var re = reFromString( '/beep/' )\nre = reFromString( '/beep' )\n","reFunctionName":"var RE_FUNCTION_NAME = reFunctionName();\nfunction beep() { return 'boop'; };\nvar name = RE_FUNCTION_NAME.exec( beep.toString() )[ 1 ]\nname = RE_FUNCTION_NAME.exec( function () {} )[ 1 ]\n","reFunctionName.REGEXP":"var str = reFunctionName.REGEXP.exec( Math.sqrt.toString() )[ 1 ]\n","regexp2json":"var json = regexp2json( /ab+c/ )\n","reim":"var z = new Complex128( 5.0, 3.0 );\nvar out = reim( z )\n","reimf":"var z = new Complex64( 5.0, 3.0 );\nvar out = reimf( z )\n","rejectArguments":"function foo( a, b ) { return [ a, b ]; };\nfunction predicate( v ) { return ( v === 2 ); };\nvar bar = rejectArguments( foo, predicate );\nvar out = bar( 1, 2, 3 )\n","removeFirst":"var out = removeFirst( 'beep' )\nout = removeFirst( 'Boop' )\nout = removeFirst( 'foo bar', 4 )\n","removeLast":"var out = removeLast( 'beep' )\nout = removeLast( 'Boop' )\nout = removeLast( 'foo bar', 4 )\n","removePunctuation":"var str = 'Sun Tzu said: \"A leader leads by example not by force.\"';\nvar out = removePunctuation( str )\nstr = 'This function removes these characters: `{}[]:,!/<>().;~|?\\'\"';\nout = removePunctuation( str )\n","removeUTF8BOM":"var out = removeUTF8BOM( '\\ufeffbeep' )\n","removeWords":"var out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ] )\nout = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ], true )\n","rename":"function done( error ) {\n if ( error ) {\n     console.error( error.message );\n }\n };\nrename( './beep/boop.txt', './beep/foo.txt', done );\n","rename.sync":"var err = rename.sync( './beep/boop.txt', './beep/foo.txt' );\n","reNativeFunction":"var RE = reNativeFunction();\nvar bool = RE.test( Date.toString() )\nbool = RE.test( (function noop() {}).toString() )\n","reNativeFunction.REGEXP":"var bool = reNativeFunction.REGEXP.test( Date.toString() )\nbool = reNativeFunction.REGEXP.test( (function noop() {}).toString() )\n","reorderArguments":"function foo( a, b, c ) { return [ a, b, c ]; };\nvar bar = reorderArguments( foo, [ 2, 0, 1 ] );\nvar out = bar( 1, 2, 3 )\n","repeat":"var out = repeat( 'a', 5 )\nout = repeat( '', 100 )\nout = repeat( 'beep', 0 )\n","replace":"var out = replace( 'beep', 'e', 'o' )\nfunction replacer( match, p1 ) { return '/'+p1+'/'; };\nvar str = 'Oranges and lemons';\nout = replace( str, /([^\\s]+)/gi, replacer )\nout = replace( 'beep', /e/, 'o' )\n","replaceBefore":"var str = 'beep boop';\nvar out = replaceBefore( str, ' ', 'foo' )\nout = replaceBefore( str, 'o', 'foo' )\n","reRegExp":"var RE = reRegExp();\nvar bool = RE.test( '/^beep$/' )\nbool = RE.test( '/boop' )\nbool = RE.test( '/^\\/([^\\/]+)\\/(.*)$/' )\nbool = RE.test( '/^\\\\/([^\\\\/]+)\\\\/(.*)$/' )\n","reRegExp.REGEXP":"var bool = reRegExp.REGEXP.test( '/^beep$/' )\nbool = reRegExp.REGEXP.test( '/boop' )\n","rescape":"var str = rescape( '[A-Z]*' )\n","reSemVer":"var RE_SEMVER = reSemVer()\nvar bool = RE_SEMVER.test( '1.0.0' )\nbool = RE_SEMVER.test( '1.0.0-alpha.1' )\nbool = RE_SEMVER.test( 'abc' )\nbool = RE_SEMVER.test( '1.0.0-alpha.1+build.1' )\n","reSemVer.REGEXP":"var bool = reSemVer.REGEXP.test( '1.0.0' )\nbool = reSemVer.REGEXP.test( '-1.0.0-alpha.1' )\n","resolveParentPath":"function onPath( error, path ) {\n if ( error ) {\n     console.error( error.message );\n } else {\n     console.log( path );\n }\n };\nresolveParentPath( 'package.json', onPath );\n","resolveParentPath.sync":"var out = resolveParentPath.sync( 'package.json' );\n","resolveParentPathBy":"function predicate( path, next ) {\n setTimeout( onTimeout, path );\n function onTimeout() {\n     console.log( path );\n     next( null, false );\n }\n };\nfunction onPath( error, path ) {\n if ( error ) {\n     console.error( error.message );\n } else {\n     console.log( path );\n }\n };\nresolveParentPathBy( 'package.json', predicate, onPath );\n","resolveParentPathBy.sync":"function predicate() { return false; };\nvar out = resolveParentPathBy.sync( 'package.json', predicate );\n","reUncPath":"var RE = reUncPath();\nvar path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\nvar bool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\\\\\share';\nbool = RE.test( path )\npath = '\\\\\\\\\\\\\\\\server\\\\share';\nbool = RE.test( path )\npath = 'beep boop \\\\\\\\server\\\\share';\nbool = RE.test( path )\npath = '\\\\\\\\server';\nbool = RE.test( path )\npath = '\\\\';\nbool = RE.test( path )\npath = '';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b:c';\nbool = RE.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\';\nbool = RE.test( path )\npath = '//server/share';\nbool = RE.test( path )\npath = '/foo/bar';\nbool = RE.test( path )\npath = 'foo/bar';\nbool = RE.test( path )\npath = './foo/bar';\nbool = RE.test( path )\npath = '/foo/../bar';\nbool = RE.test( path )\n","reUncPath.REGEXP":"var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\nvar bool = reUncPath.REGEXP.test( path )\npath = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\nbool = reUncPath.REGEXP.test( path )\n","reUtf16SurrogatePair":"var RE = reUtf16SurrogatePair();\nvar bool = RE.test( 'abc\\uD800\\uDC00def' )\nbool = RE.test( 'abcdef' )\n","reUtf16SurrogatePair.REGEXP":"var RE = reUtf16SurrogatePair.REGEXP;\nvar bool = RE.test( 'abc\\uD800\\uDC00def' )\nbool = RE.test( 'abcdef' )\n","reUtf16UnpairedSurrogate":"var RE = reUtf16UnpairedSurrogate();\nvar bool = RE.test( 'abc' )\nbool = RE.test( '\\uD800' )\n","reUtf16UnpairedSurrogate.REGEXP":"var RE = reUtf16UnpairedSurrogate.REGEXP;\nvar bool = RE.test( 'abc' )\nbool = RE.test( '\\uD800' )\n","reverseArguments":"function foo( a, b, c ) { return [ a, b, c ]; };\nvar bar = reverseArguments( foo );\nvar out = bar( 1, 2, 3 )\n","reverseString":"var out = reverseString( 'foo' )\nout = reverseString( 'abcdef' )\n","reviveBasePRNG":"var str = JSON.stringify( base.random.mt19937 );\nvar r = parseJSON( str, reviveBasePRNG )\n","reviveBuffer":"var str = '{\"type\":\"Buffer\",\"data\":[5,3]}';\nvar buf = parseJSON( str, reviveBuffer )\n","reviveComplex":"var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\nvar z = parseJSON( str, reviveComplex )\n","reviveComplex64":"var str = '{\"type\":\"Complex64\",\"re\":5,\"im\":3}';\nvar z = parseJSON( str, reviveComplex64 )\n","reviveComplex128":"var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\nvar z = parseJSON( str, reviveComplex128 )\n","reviveError":"var str = '{\"type\":\"TypeError\",\"message\":\"beep\"}';\nvar err = JSON.parse( str, reviveError )\n","reviveRegExp":"var str = '{\"type\":\"RegExp\",\"pattern\":\"ab+c\",\"flags\":\"\"}';\nvar v = parseJSON( str, reviveRegExp )\n","reviveTypedArray":"var str = '{\"type\":\"Float64Array\",\"data\":[5,3]}';\nvar arr = parseJSON( str, reviveTypedArray )\n","reWhitespace":"var RE = reWhitespace();\nvar bool = RE.test( '\\n' )\nbool = RE.test( ' ' )\nbool = RE.test( 'a' )\n","reWhitespace.REGEXP":"var RE = reWhitespace.REGEXP;\nvar bool = RE.test( '\\n' )\nbool = RE.test( ' ' )\nbool = RE.test( 'a' )\n","reWhitespace.REGEXP_CAPTURE":"var RE = reWhitespace.REGEXP_CAPTURE;\nvar str = 'Duplicate capture';\nvar out = replace( str, RE, '$1$1' )\n","rpad":"var out = rpad( 'a', 5 )\nout = rpad( 'beep', 10, 'p' )\nout = rpad( 'beep', 12, 'boop' )\n","rtrim":"var out = rtrim( ' \\t\\t\\n  Beep \\r\\n\\t  ' )\n","rtrimN":"var out = rtrimN( '  abc  ', 2 )\nvar out = rtrimN( '!!!abc!!!', 2, '!' )\n","safeintmax":"var m = safeintmax( 'float16' )\nm = safeintmax( 'float32' )\n","safeintmin":"var m = safeintmin( 'float16' )\nm = safeintmin( 'float32' )\n","sample":"var out = sample( 'abc' )\nout = sample( [ 3, 6, 9 ] )\nvar bool = ( out.length === 3 )\nout = sample( [ 3, null, NaN, 'abc', function(){} ] )\nout = sample( [ 3, 6, 9 ], { 'size': 10 } )\nout = sample( [ 0, 1 ], { 'size': 20 } )\nout = sample( [ 1, 2, 3, 4, 5, 6 ], { 'replace': false, 'size': 3 } )\nout = sample( [ 0, 1 ], { 'replace': false } )\nvar x = [ 1, 2, 3, 4, 5, 6 ];\nvar probs = [ 0.1, 0.1, 0.1, 0.1, 0.1, 0.5 ];\nout = sample( x, { 'probs': probs } )\nout = sample( x, { 'probs': probs, 'size': 3, 'replace': false } )\n","sample.factory":"var mysample = sample.factory({ 'seed': 232 } );\nvar out = mysample( 'abcdefg' )\nvar pool = [ 1, 2, 3, 4, 5, 6 ];\nmysample = sample.factory( pool, { 'seed': 232, 'size': 2 } );\nout = mysample()\nout = mysample()\nvar opts = { 'seed': 474, 'size': 3, 'mutate': true, 'replace': false };\npool = [ 1, 2, 3, 4, 5, 6 ];\nmysample = sample.factory( pool, opts );\nout = mysample()\nout = mysample()\nout = mysample()\nmysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\nout = mysample()\nout = mysample({ 'size': 10 })\nmysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\nout = mysample()\nout = mysample({ 'replace': false })\nout = mysample()\n","SAVOY_STOPWORDS_FIN":"var list = SAVOY_STOPWORDS_FIN()\n","SAVOY_STOPWORDS_FR":"var list = SAVOY_STOPWORDS_FR()\n","SAVOY_STOPWORDS_GER":"var list = SAVOY_STOPWORDS_GER()\n","SAVOY_STOPWORDS_IT":"var list = SAVOY_STOPWORDS_IT()\n","SAVOY_STOPWORDS_POR":"var list = SAVOY_STOPWORDS_POR()\n","SAVOY_STOPWORDS_SP":"var list = SAVOY_STOPWORDS_SP()\n","SAVOY_STOPWORDS_SWE":"var list = SAVOY_STOPWORDS_SWE()\n","scalar2array":"var x = scalar2array( 1.0 )\n","scalar2ndarray":"var x = scalar2ndarray( 1.0 )\nvar sh = x.shape\nvar dt = x.dtype\nvar v = x.get()\n","sdot":"var xbuf = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\nvar x = array( xbuf );\nvar ybuf = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\nvar y = array( ybuf );\nvar z = sdot( x, y )\nz.get()\n","SECONDS_IN_DAY":"var days = 3.14;\nvar secs = days * SECONDS_IN_DAY\n","SECONDS_IN_HOUR":"var hrs = 3.14;\nvar secs = hrs * SECONDS_IN_HOUR\n","SECONDS_IN_MINUTE":"var mins = 3.14;\nvar secs = mins * SECONDS_IN_MINUTE\n","SECONDS_IN_WEEK":"var wks = 3.14;\nvar secs = wks * SECONDS_IN_WEEK\n","secondsInMonth":"var num = secondsInMonth()\nnum = secondsInMonth( 2 )\nnum = secondsInMonth( 2, 2016 )\nnum = secondsInMonth( 2, 2017 )\nnum = secondsInMonth( 'feb', 2016 )\nnum = secondsInMonth( 'february', 2016 )\n","secondsInYear":"var num = secondsInYear()\nnum = secondsInYear( 2016 )\nnum = secondsInYear( 2017 )\n","sentencize":"var out = sentencize( 'Hello Mrs. Maple, could you call me back?' )\nout = sentencize( 'Hello World! How are you?' )\n","seq2slice":"var s = new seq2slice( '1:10', 10, false );\ns.start\ns.stop\ns.step\ns = new seq2slice( '2:5:2', 10, false );\ns.start\ns.stop\ns.step\n","setConfigurableReadOnly":"var obj = {};\nsetConfigurableReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n","setConfigurableReadOnlyAccessor":"var obj = {};\nfunction getter() { return 'bar'; };\nsetConfigurableReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n","setConfigurableReadWriteAccessor":"var obj = {};\nvar name = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetConfigurableReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n","setConfigurableWriteOnlyAccessor":"var obj = {};\nvar val = '';\nfunction setter( v ) { val = v; };\nsetConfigurableWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n","setMemoizedConfigurableReadOnly":"var obj = {};\nfunction foo() { return 'bar'; };\nsetMemoizedConfigurableReadOnly( obj, 'foo', foo );\nobj.foo\n","setMemoizedReadOnly":"var obj = {};\nfunction foo() { return 'bar'; };\nsetMemoizedReadOnly( obj, 'foo', foo );\nobj.foo\n","setNonEnumerableProperty":"var obj = {};\nsetNonEnumerableProperty( obj, 'foo', 'bar' );\nobj.foo\nobjectKeys( obj )\n","setNonEnumerableReadOnly":"var obj = {};\nsetNonEnumerableReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n","setNonEnumerableReadOnlyAccessor":"var obj = {};\nfunction getter() { return 'bar'; };\nsetNonEnumerableReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n","setNonEnumerableReadWriteAccessor":"var obj = {};\nvar name = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetNonEnumerableReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n","setNonEnumerableWriteOnlyAccessor":"var obj = {};\nvar val = '';\nfunction setter( v ) { val = v; };\nsetNonEnumerableWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n","setReadOnly":"var obj = {};\nsetReadOnly( obj, 'foo', 'bar' );\nobj.foo = 'boop';\nobj\n","setReadOnlyAccessor":"var obj = {};\nfunction getter() { return 'bar'; };\nsetReadOnlyAccessor( obj, 'foo', getter );\nobj.foo\n","setReadWriteAccessor":"var obj = {};\nvar name = 'bar';\nfunction getter() { return name + ' foo'; };\nfunction setter( v ) { name = v; };\nsetReadWriteAccessor( obj, 'foo', getter, setter );\nobj.foo\nobj.foo = 'beep';\nobj.foo\n","setWriteOnlyAccessor":"var obj = {};\nvar val = '';\nfunction setter( v ) { val = v; };\nsetWriteOnlyAccessor( obj, 'foo', setter );\nobj.foo = 'bar';\nval\n","SharedArrayBuffer":"var buf = new SharedArrayBuffer( 5 )\n","SharedArrayBuffer.length":"SharedArrayBuffer.length\n","SharedArrayBuffer.prototype.byteLength":"var buf = new SharedArrayBuffer( 5 );\nbuf.byteLength\n","SharedArrayBuffer.prototype.slice":"var b1 = new SharedArrayBuffer( 10 );\nvar b2 = b1.slice( 2, 6 );\nvar bool = ( b1 === b2 )\nb2.byteLength\n","shift":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\nvar out = shift( arr )\narr = new Float64Array( [ 1.0, 2.0 ] );\nout = shift( arr )\narr = { 'length': 2, '0': 1.0, '1': 2.0 };\nout = shift( arr )\n","shuffle":"var data = [ 1, 2, 3 ];\nvar out = shuffle( data )\nout = shuffle( data, { 'copy': 'none' } );\nvar bool = ( data === out )\n","shuffle.factory":"var myshuffle = shuffle.factory();\nmyshuffle = shuffle.factory({ 'seed': 239 });\nvar arr = [ 0, 1, 2, 3, 4 ];\nvar out = myshuffle( arr )\nmyshuffle = shuffle.factory({ 'copy': 'none', 'seed': 867 });\narr = [ 1, 2, 3, 4, 5, 6 ];\nout = myshuffle( arr );\nvar bool = ( arr === out )\narr = [ 1, 2, 3, 4 ];\nout = myshuffle( arr, { 'copy': 'shallow' } );\nbool = ( arr === out )\n","sizeOf":"var s = sizeOf( 'int8' )\ns = sizeOf( 'uint32' )\n","Slice":"var s = new Slice();\ns = new Slice( 10 );\nvar s = new Slice( 2, 10 );\ns = new Slice( 2, 10, 1 );\n","Slice.prototype.start":"var s = new Slice( 10 );\ns.start\ns = new Slice( 2, 10 );\ns.start\n","Slice.prototype.stop":"var s = new Slice( 10 );\ns.stop\ns = new Slice( 2, 10 );\ns.stop\n","Slice.prototype.step":"var s = new Slice( 10 );\ns.step\ns = new Slice( 2, 10 );\ns.step\ns = new Slice( 2, 10, 1 );\ns.step\n","Slice.prototype.toString":"var s = new Slice( 10 );\ns.toString()\ns = new Slice( 2, 10, 1 );\ns.toString()\n","Slice.prototype.toJSON":"var s = new Slice( 10 );\ns.toJSON()\ns = new Slice( 2, 10, 1 );\ns.toJSON()\n","snakecase":"var out = snakecase( 'Hello World!' )\nout = snakecase( 'I am a tiny little teapot' )\n","some":"var arr = [ 0, 0, 1, 2, 3 ];\nvar bool = some( arr, 3 )\n","someBy":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ 1, 2, -3, 4, -1 ];\nvar bool = someBy( arr, 2, negative )\n","someByAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nsomeByAsync( arr, 2, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000 ];\nsomeByAsync( arr, 2, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000 ];\nsomeByAsync( arr, 2, opts, predicate, done )\n","someByAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = someByAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 3000, 2500, 1000 ];\nf( arr, 2, done )\narr = [ 2000, 1500, 1000 ];\nf( arr, 2, done )\n","someByRight":"function negative( v ) { return ( v < 0 ); };\nvar arr = [ -1, 1, -2, 3, 4 ];\nvar bool = someByRight( arr, 2, negative )\n","someByRightAsync":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nsomeByRightAsync( arr, 2, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 1000, 2500, 3000 ];\nsomeByRightAsync( arr, 2, opts, predicate, done )\nfunction predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar opts = { 'series': true };\nvar arr = [ 1000, 2500, 3000 ];\nsomeByRightAsync( arr, 2, opts, predicate, done )\n","someByRightAsync.factory":"function predicate( value, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, false );\n }\n };\nvar opts = { 'series': true };\nvar f = someByRightAsync.factory( opts, predicate );\nfunction done( error, bool ) {\n if ( error ) {\n     throw error;\n }\n console.log( bool );\n };\nvar arr = [ 1000, 2500, 3000 ];\nf( arr, 2, done )\narr = [ 1000, 1500, 2000 ];\nf( arr, 2, done )\n","someInBy":"function negative( v ) { return ( v < 0 ); };\nvar obj = { 'a': 1, 'b': 2, 'c': -3, 'd': 4, 'e': -1 };\nvar bool = someInBy( obj, 2, negative )\n","someOwnBy":"function negative( v ) { return ( v < 0 ); };\nvar obj = { a: 1, b: 2, c: -3, d: 4, e: -1 };\nvar bool = someOwnBy( obj, 2, negative )\n","SOTU":"var out = SOTU()\nvar opts = { 'name': 'Barack Obama' };\nout = SOTU( opts )\nopts = { 'party': [ 'Democratic', 'Federalist' ] };\nout = SOTU( opts )\nopts = { 'year': [ 2008, 2009, 2011 ] };\nout = SOTU( opts )\nopts = { 'range': [ 2008, 2016 ] }\nout = SOTU( opts )\n","SPACHE_REVISED":"var list = SPACHE_REVISED()\n","SPAM_ASSASSIN":"var data = SPAM_ASSASSIN()\n","SparklineBase":"var sparkline = new SparklineBase()\nvar data = [ 1, 2, 3 ];\nsparkline = new SparklineBase( data )\n","sparsearray2iterator":"var it = sparsearray2iterator( [ 1, , 3, 4 ] );\nvar v = it.next().value\nv = it.next().value\n","sparsearray2iteratorRight":"var it = sparsearray2iteratorRight( [ 1, 2, , 4 ] );\nvar v = it.next().value\nv = it.next().value\n","splitStream":"var s = splitStream();\ns.write( 'a\\nb\\nc' );\ns.end();\n","splitStream.factory":"var opts = { 'highWaterMark': 64 };\nvar createStream = splitStream.factory( opts );\nvar s = createStream();\ns.write( 'a\\nb\\nc' );\ns.end();\n","splitStream.objectMode":"var s = splitStream.objectMode();\ns.write( 'a\\nb\\c' );\ns.end();\n","SQRT_EPS":"SQRT_EPS\n","SQRT_HALF":"SQRT_HALF\n","SQRT_HALF_PI":"SQRT_HALF_PI\n","SQRT_PHI":"SQRT_PHI\n","SQRT_PI":"SQRT_PI\n","SQRT_THREE":"SQRT_THREE\n","SQRT_TWO":"SQRT_TWO\n","SQRT_TWO_PI":"SQRT_TWO_PI\n","SSA_US_BIRTHS_2000_2014":"var data = SSA_US_BIRTHS_2000_2014()\n","sswap":"var x = array( new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\nvar y = array( new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\nsswap( x, y );\nx.data\ny.data\n","Stack":"var s = Stack();\ns.push( 'foo' ).push( 'bar' );\ns.length\ns.pop()\ns.length\ns.pop()\ns.length\n","standalone2pkg":"var v = standalone2pkg( '@stdlib/math-base-special-sin' )\n","STANDARD_CARD_DECK":"var list = STANDARD_CARD_DECK()\n","startcase":"var out = startcase( 'beep boop' )\n","startsWith":"var bool = startsWith( 'Beep', 'Be' )\nbool = startsWith( 'Beep', 'ep' )\nbool = startsWith( 'Beep', 'ee', 1 )\nbool = startsWith( 'Beep', 'ee', -3 )\nbool = startsWith( 'Beep', '' )\n","STOPWORDS_EN":"var list = STOPWORDS_EN()\n","strided.abs":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs( 2, x, 2, y, -1 )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.abs( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.abs.ndarray":"var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.abs2":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.abs2( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.abs2.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.abs2.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.abs2By":"var x = [ -1.0, -2.0, -3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.abs2By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.abs2By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.abs2By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.abs2By.ndarray":"var x = [ -1.0, -2.0, -3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.abs2By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ -1.0, -2.0, -3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.abs2By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.absBy":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nstrided.absBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.absBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.absBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.absBy.ndarray":"var x = [ 1.0, -2.0, 3.0, -4.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v * 2.0; };\nstrided.absBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 1.0, -2.0, 3.0, -4.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.absBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acosBy":"var x = [ 1.0, 0.707, 0.866, -0.707 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, 0.707, 0.866, -0.707 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acosBy.ndarray":"var x = [ 1.0, 0.707, 0.866, -0.707 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 1.0, 0.707, 0.866, -0.707 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acoshBy":"var x = [ 1.0, 1.5, 2.0, 2.5 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acoshBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acoshBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, 1.5, 2.0, 2.5 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acoshBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acoshBy.ndarray":"var x = [ 1.0, 1.5, 2.0, 2.5 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acoshBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 1.0, 1.5, 2.0, 2.5 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acoshBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acotBy":"var x = [ -2.5, -1.5, -0.5, 0.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acotBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acotBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ -2.5, -1.5, -0.5, 0.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acotBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acotBy.ndarray":"var x = [ -2.5, -1.5, -0.5, 0.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acotBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ -2.5, -1.5, -0.5, 0.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acotBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acothBy":"var x = [ -5.0, -4.0, -3.0, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acothBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acothBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ -5.0, -4.0, -3.0, -1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acothBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acothBy.ndarray":"var x = [ -5.0, -4.0, -3.0, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acothBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ -5.0, -4.0, -3.0, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acothBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acovercosBy":"var x = [ 0.0, -1.57, -0.5, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acovercosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acovercosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -1.57, -0.5, -1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acovercosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acovercosBy.ndarray":"var x = [ 0.0, -1.57, -0.5, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acovercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -1.57, -0.5, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acovercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.acoversinBy":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acoversinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acoversinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.acoversinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.acoversinBy.ndarray":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.acoversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.57, 0.5, 1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.acoversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.add":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.add( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.add( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.add( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\nz0\n","strided.add.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.add.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.add.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n","strided.addBy":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = [ 11.0, 12.0, 13.0, 14.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.addBy( x.length, x, 1, y, 1, z, 1, clbk )\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.addBy( 2, x, 2, y, -1, z, 1, clbk )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.addBy( 2, x1, -2, y1, 1, z1, 1, clbk )\nz0\n","strided.addBy.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = [ 11.0, 12.0, 13.0, 14.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.addBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\nx = [ 1.0, 2.0, 3.0, 4.0 ];\ny = [ 11.0, 12.0, 13.0, 14.0 ];\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nvar oy = y.length - 1;\nvar oz = z.length - 1;\nstrided.addBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n","strided.ahavercosBy":"var x = [ 0.0, 0.5, 1.0, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.ahavercosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.ahavercosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 0.5, 1.0, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.ahavercosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.ahavercosBy.ndarray":"var x = [ 0.0, 0.5, 1.0, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.ahavercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 0.5, 1.0, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.ahavercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.ahaversinBy":"var x = [ 0.0, 0.5, 1.0, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.ahaversinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.ahaversinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 0.5, 1.0, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.ahaversinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.ahaversinBy.ndarray":"var x = [ 0.0, 0.5, 1.0, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.ahaversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 0.5, 1.0, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.ahaversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.asinBy":"var x = [ 0.0, -0.5, 1.0, -0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.asinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.asinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -0.5, 1.0, -0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.asinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.asinBy.ndarray":"var x = [ 0.0, -0.5, 1.0, -0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.asinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -0.5, 1.0, -0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.asinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.asinhBy":"var x = [ 0.0, -0.0, 2.0, -2.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.asinhBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.asinhBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -0.0, 2.0, -2.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.asinhBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.asinhBy.ndarray":"var x = [ 0.0, -0.0, 2.0, -2.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.asinhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -0.0, 2.0, -2.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.asinhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.atanBy":"var x = [ 0.0, -0.5, 1.0, -1.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.atanBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.atanBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -0.5, 1.0, -1.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.atanBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.atanBy.ndarray":"var x = [ 0.0, -0.5, 1.0, -1.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.atanBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -0.5, 1.0, -1.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.atanBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.atanhBy":"var x = [ 0.0, -0.5, 1.0, -0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.atanhBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.atanhBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -0.5, 1.0, -0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.atanhBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.atanhBy.ndarray":"var x = [ 0.0, -0.5, 1.0, -0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.atanhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -0.5, 1.0, -0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.atanhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.avercosBy":"var x = [ 0.0, -1.57, -0.5, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.avercosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.avercosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, -1.57, -0.5, -1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.avercosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.avercosBy.ndarray":"var x = [ 0.0, -1.57, -0.5, -1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.avercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, -1.57, -0.5, -1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.avercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.aversinBy":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.aversinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.aversinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.aversinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.aversinBy.ndarray":"var x = [ 0.0, 1.57, 0.5, 1.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.aversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.57, 0.5, 1.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.aversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.besselj0By":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.besselj0By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.besselj0By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.besselj0By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.besselj0By.ndarray":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.besselj0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 0.1, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.besselj0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.besselj1By":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.besselj1By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.besselj1By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.besselj1By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.besselj1By.ndarray":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.besselj1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 0.1, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.besselj1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.bessely0By":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.bessely0By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.bessely0By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.bessely0By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.bessely0By.ndarray":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.bessely0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 0.1, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.bessely0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.bessely1By":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.bessely1By( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.bessely1By( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.bessely1By( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.bessely1By.ndarray":"var x = [ 0.0, 1.0, 0.1, 0.25 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.bessely1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 0.1, 0.25 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.bessely1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.binetBy":"var x = [ 0.0, 1.0, 2.0, 3.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.binetBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.binetBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.binetBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.binetBy.ndarray":"var x = [ 0.0, 1.0, 2.0, 3.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.binetBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 2.0, 3.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.binetBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.cbrt":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.cbrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.cbrt.ndarray":"var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.cbrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.cbrtBy":"var x = [ 1.0, 9.0, -27.0, 81.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.cbrtBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.cbrtBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.cbrtBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.cbrtBy.ndarray":"var x = [ 1.0, 9.0, -27.0, 81.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.cbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 1.0, 9.0, -27.0, 81.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.cbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.ceil":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.ceil( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.ceil.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ceil.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.cosBy":"var x = [ 0.0, 3.14, -3.14, 10.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.cosBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.cosBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 3.14, -3.14, 10.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.cosBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.cosBy.ndarray":"var x = [ 0.0, 3.14, -3.14, 10.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.cosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 3.14, -3.14, 10.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.cosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.deg2rad":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.deg2rad( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.deg2rad.ndarray":"var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.deg2rad.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.dataTypes":"var out = strided.dataTypes()\n","strided.dcbrtBy":"var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nfunction clbk( v ) { return v; };\nstrided.dcbrtBy( x.length, x, 1, y, 1, clbk )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.dcbrtBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.dcbrtBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.dcbrtBy.ndarray":"var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nfunction clbk( v ) { return v; };\nstrided.dcbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.dcbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.dispatch":"var t = [ 'float64', 'float64', 'float32', 'float32' ];\nvar d = [ base.abs, base.absf ];\nvar f = strided.dispatch( base.strided.unary, t, d, 7, 1, 1 );\nvar x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( x.length, 'float64', x, 1, 'float64', y, 1 );\ny\nf = strided.dispatch( base.strided.unary.ndarray, t, d, 9, 1, 1 );\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( 2, 'float64', x, 1, 2, 'float64', y, 1, 2 );\ny\n","strided.dispatchBy":"var t = [ 'float64', 'float64', 'float32', 'float32' ];\nvar d = [ base.abs, base.absf ];\nvar f = strided.dispatchBy( base.strided.unaryBy, t, d, 8, 1, 1 );\nvar x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( x.length, 'float64', x, 1, 'float64', y, 1, base.identity );\ny\nf = strided.dispatchBy( base.strided.unary.ndarray, t, d, 10, 1, 1 );\nx = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nf( 2, 'float64', x, 1, 2, 'float64', y, 1, 2, base.identity );\ny\n","strided.floor":"var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.floor( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.floor.ndarray":"var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.floor.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.inv":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.inv( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.inv.ndarray":"var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.inv.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.mul":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.mul( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.mul( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.mul( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\nz0\n","strided.mul.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.mul.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.mul.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n","strided.mulBy":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = [ 11.0, 12.0, 13.0, 14.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.mulBy( x.length, x, 1, y, 1, z, 1, clbk )\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.mulBy( 2, x, 2, y, -1, z, 1, clbk )\nvar x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar y0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.mulBy( 2, x1, -2, y1, 1, z1, 1, clbk )\nz0\n","strided.mulBy.ndarray":"var x = [ 1.0, 2.0, 3.0, 4.0 ];\nvar y = [ 11.0, 12.0, 13.0, 14.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.mulBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\nx = [ 1.0, 2.0, 3.0, 4.0 ];\ny = [ 11.0, 12.0, 13.0, 14.0 ];\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nvar oy = y.length - 1;\nvar oz = z.length - 1;\nstrided.mulBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n","strided.ramp":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.ramp( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.ramp.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.ramp.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.rsqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.rsqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.rsqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.rsqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.sinBy":"var x = [ 0.0, 3.14, -3.14, 10.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.sinBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.sinBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 3.14, -3.14, 10.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.sinBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.sinBy.ndarray":"var x = [ 0.0, 3.14, -3.14, 10.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.sinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 3.14, -3.14, 10.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.sinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.sqrt":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.sqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.sqrt.ndarray":"var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","strided.sqrtBy":"var x = [ 0.0, 1.0, 122.0, 50.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.sqrtBy( x.length, x, 1, y, 1, clbk )\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.sqrtBy( 2, x, 2, y, -1, clbk )\nvar x0 = new Float64Array( [ 0.0, 1.0, 122.0, 50.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.sqrtBy( 2, x1, -2, y1, 1, clbk )\ny0\n","strided.sqrtBy.ndarray":"var x = [ 0.0, 1.0, 122.0, 50.0 ];\nvar y = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( v ) { return v; };\nstrided.sqrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\nx = [ 0.0, 1.0, 122.0, 50.0 ];\ny = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.sqrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n","strided.sub":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.sub( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sub( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\nvar x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.sub( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\nz0\n","strided.sub.ndarray":"var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\nvar y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nvar z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar dt = 'float64';\nstrided.sub.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\nx = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\ny = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\nz = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.sub.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n","strided.subBy":"var x = [ 11.0, 12.0, 13.0, 14.0 ];\nvar y = [ 8.0, 7.0, 6.0, 5.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.subBy( x.length, x, 1, y, 1, z, 1, clbk )\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nstrided.subBy( 2, x, 2, y, -1, z, 1, clbk )\nvar x0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\nvar y0 = new Float64Array( [ 8.0, 7.0, 6.0, 5.0 ] );\nvar z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nvar z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\nstrided.subBy( 2, x1, -2, y1, 1, z1, 1, clbk )\nz0\n","strided.subBy.ndarray":"var x = [ 11.0, 12.0, 13.0, 14.0 ];\nvar y = [ 8.0, 7.0, 6.0, 5.0 ];\nvar z = [ 0.0, 0.0, 0.0, 0.0 ];\nfunction clbk( values ) { return values; };\nstrided.subBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\nx = [ 11.0, 12.0, 13.0, 14.0 ];\ny = [ 8.0, 7.0, 6.0, 5.0 ];\nz = [ 0.0, 0.0, 0.0, 0.0 ];\nvar oy = y.length - 1;\nvar oz = z.length - 1;\nstrided.subBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n","strided.trunc":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc( x.length, 'float64', x, 1, 'float64', y, 1 )\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc( 2, 'float64', x, 2, 'float64', y, -1 )\nvar x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nvar x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\nvar y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\nstrided.trunc( 2, 'float64', x1, -2, 'float64', y1, 1 )\ny0\n","strided.trunc.ndarray":"var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\nvar y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\nx = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\ny = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\nstrided.trunc.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n","stridedarray2iterator":"var it = stridedarray2iterator( 2, [ 1, 2, 3, 4 ], -2, 3 );\nvar v = it.next().value\nv = it.next().value\n","stridedArrayStream":"function fcn( chunk ) { console.log( chunk.toString() ); };\nvar s = stridedArrayStream( 3, [ 1, 2, 3 ], 1, 0 );\nvar o = inspectSinkStream( fcn );\ns.pipe( o );\n","stridedArrayStream.factory":"var opts = { 'objectMode': true, 'highWaterMark': 64 };\nvar createStream = stridedArrayStream.factory( opts );\n","stridedArrayStream.objectMode":"function fcn( v ) { console.log( v ); };\nvar s = stridedArrayStream.objectMode( 3, [ 1, 2, 3 ], 1, 0 );\nvar o = inspectSinkStream.objectMode( fcn );\ns.pipe( o );\n","string2buffer":"var b = string2buffer( 'beep boop' )\nb = string2buffer( '7468697320697320612074c3a97374', 'hex' );\nb.toString()\n","sub2ind":"var d = [ 3, 3, 3 ];\nvar idx = sub2ind( d, 1, 2, 2 )\n","substringAfter":"var out = substringAfter( 'Hello World!', 'World' )\nout = substringAfter( 'Hello World!', 'Hello ' )\nout = substringAfter( 'Hello World!', 'l', 5 )\n","substringAfterLast":"var out = substringAfterLast( 'beep boop beep baz', 'beep' )\nout = substringAfterLast( 'Hello World!', 'Hello ' )\nout = substringAfterLast( 'Hello World!', 'o', 5 )\n","substringBefore":"var str = 'beep boop';\nvar out = substringBefore( str, ' ' )\nout = substringBefore( str, 'o' )\n","substringBeforeLast":"var str = 'Beep Boop Beep';\nvar out = substringBeforeLast( str, 'Beep' )\nout = substringBeforeLast( str, 'Boop' )\n","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"var data = SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"var data = SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n","Symbol":"var s = ( Symbol ) ? Symbol( 'beep' ) : null\n","tabulate":"var collection = [ 'beep', 'boop', 'foo', 'beep' ];\nvar out = tabulate( collection )\n","tabulateBy":"function indicator( value ) { return value[ 0 ]; };\nvar collection = [ 'beep', 'boop', 'foo', 'beep' ];\nvar out = tabulateBy( collection, indicator )\n","tabulateByAsync":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000, 750 ];\ntabulateByAsync( arr, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar opts = { 'limit': 2 };\nvar arr = [ 3000, 2500, 1000, 750 ];\ntabulateByAsync( arr, opts, indicator, done )\nfunction indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar opts = { 'series': true };\nvar arr = [ 3000, 2500, 1000, 750 ];\ntabulateByAsync( arr, opts, indicator, done )\n","tabulateByAsync.factory":"function indicator( value, index, next ) {\n setTimeout( onTimeout, value );\n function onTimeout() {\n     console.log( value );\n     next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n }\n };\nvar opts = { 'series': true };\nvar f = tabulateByAsync.factory( opts, indicator );\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nvar arr = [ 3000, 2500, 1000, 750 ];\nf( arr, done )\narr = [ 2000, 1500, 1000, 750 ];\nf( arr, done )\n","thunk":"var fcn = thunk( base.add, 2, 3 );\nvar v = fcn()\nv = fcn()\n","tic":"var t = tic()\n","timeit":"var code = 'var x = Math.pow( Math.random(), 3 );';\ncode += 'if ( x !== x ) {';\ncode += 'throw new Error( \\'Something went wrong.\\' );';\ncode += '}';\nfunction done( error, results ) {\n if ( error ) {\n     throw error;\n }\n console.dir( results );\n };\ntimeit( code, done )\n","tmpdir":"var dir = tmpdir()\n","toc":"var start = tic();\nvar delta = toc( start )\n","tokenize":"var out = tokenize( 'Hello Mrs. Maple, could you call me back?' )\nout = tokenize( 'Hello World!', true )\n","transformStream":"var s = transformStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","transformStream.factory":"var opts = { 'highWaterMark': 64 };\nvar createStream = transformStream.factory( opts );\nfunction fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\nvar s = createStream( fcn );\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","transformStream.objectMode":"var s = transformStream.objectMode();\ns.write( { 'value': 'a' } );\ns.write( { 'value': 'b' } );\ns.write( { 'value': 'c' } );\ns.end();\n","transformStream.ctor":"function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\nvar opts = { 'highWaterMark': 64, 'transform': fcn };\nvar customStream = transformStream.ctor( opts );\nvar s = customStream();\ns.write( 'a' );\ns.write( 'b' );\ns.write( 'c' );\ns.end();\n","trim":"var out = trim( ' \\t\\t\\n  Beep \\r\\n\\t  ' )\n","truncate":"var str = 'beep boop';\nvar out = truncate( str, 5 )\nout = truncate( str, 5, '|' )\n","truncateMiddle":"var str = 'beep boop';\nvar out = truncateMiddle( str, 5 )\nout = truncateMiddle( str, 5, '|' )\n","trycatch":"function x() {\n if ( base.random.randu() < 0.5 ) {\n     throw new Error( 'beep' );\n }\n return 1.0;\n };\nvar z = trycatch( x, -1.0 )\n","trycatchAsync":"function x( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n     clbk( new Error( 'beep' ) );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     // process error...\n }\n console.log( result );\n };\ntrycatchAsync( x, 'boop', done )\n","tryFunction":"function fcn() { throw new Error( 'beep boop' ); };\nvar f = tryFunction( fcn );\nvar out = f();\nout.message\n","tryRequire":"var out = tryRequire( '_unknown_module_id_' )\n","trythen":"function x() {\n if ( base.random.randu() < 0.5 ) {\n     throw new Error( 'beep' );\n }\n return 1.0;\n };\nfunction y() {\n return -1.0;\n };\nvar z = trythen( x, y )\n","trythenAsync":"function x( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n     clbk( new Error( 'beep' ) );\n }\n };\nfunction y( clbk ) {\n setTimeout( onTimeout, 0 );\n function onTimeout() {\n     clbk( null, 'boop' );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\ntrythenAsync( x, y, done )\n","ttest":"var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 5776 } );\nvar x = new Array( 100 );\nfor ( var i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm();\n }\nvar out = ttest( x )\nrnorm = base.random.normal.factory( 1.0, 2.0, { 'seed': 786 } );\nx = new Array( 100 );\nvar y = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm();\n y[ i ] = rnorm();\n }\nout = ttest( x, y )\nvar table = out.print()\nvar arr = [ 2, 4, 3, 1, 0 ];\nout = ttest( arr, { 'alpha': 0.01 } );\ntable = out.print()\narr = [ 4, 4, 6, 6, 5 ];\nout = ttest( arr, { 'mu': 5 } )\narr = [ 4, 4, 6, 6, 5 ];\nout = ttest( arr, { 'alternative': 'less' } );\ntable = out.print()\nout = ttest( arr, { 'alternative': 'greater' } );\ntable = out.print()\n","ttest2":"var x = [ 0.7, -1.6, -0.2, -1.2, -0.1, 3.4, 3.7, 0.8, 0.0, 2.0 ];\nvar y = [ 1.9, 0.8, 1.1, 0.1, -0.1, 4.4, 5.5, 1.6, 4.6, 3.4 ];\nvar out = ttest2( x, y )\nvar table = out.print()\nout = ttest2( x, y, { 'alpha': 0.1 } );\ntable = out.print()\nout = ttest2( x, y, { 'alternative': 'less' } );\ntable = out.print()\nout = ttest2( x, y, { 'alternative': 'greater' } );\ntable = out.print()\nx = [ 2, 3, 1, 4 ];\ny = [ 1, 2, 3, 1, 2, 5, 3, 4 ];\nout = ttest2( x, y, { 'variance': 'equal' } );\ntable = out.print()\nvar rnorm = base.random.normal.factory({ 'seed': 372 } );\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm( 2.0, 3.0 );\n }\ny = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n y[ i ] = rnorm( 1.0, 3.0 );\n }\nout = ttest2( x, y, { 'difference': 1.0, 'variance': 'equal' } )\n","TWO_PI":"TWO_PI\n","typedarray":"var arr = typedarray()\narr = typedarray( 'float32' )\nvar arr = typedarray( 5 )\narr = typedarray( 5, 'int32' )\nvar arr1 = typedarray( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = typedarray( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = typedarray( arr1, 'float32' )\nvar buf = new ArrayBuffer( 16 );\nvar arr = typedarray( buf, 0, 4, 'float32' )\n","typedarray2json":"var arr = new Float64Array( 2 );\narr[ 0 ] = 5.0;\narr[ 1 ] = 3.0;\nvar json = typedarray2json( arr )\n","typedarrayCtors":"var ctor = typedarrayCtors( 'float64' )\nctor = typedarrayCtors( 'float' )\n","typedarrayDataTypes":"var out = typedarrayDataTypes()\n","typedarraypool":"var arr = typedarraypool()\narr = typedarraypool( 'float32' )\nvar arr = typedarraypool( 5 )\narr = typedarraypool( 5, 'int32' )\nvar arr1 = typedarraypool( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = typedarraypool( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = typedarraypool( arr1, 'float32' )\n","typedarraypool.malloc":"var arr = typedarraypool.malloc()\narr = typedarraypool.malloc( 'float32' )\nvar arr = typedarraypool.malloc( 5 )\narr = typedarraypool.malloc( 5, 'int32' )\nvar arr1 = typedarraypool.malloc( [ 0.5, 0.5, 0.5 ] );\nvar arr2 = typedarraypool.malloc( arr1, 'float32' )\nvar arr1 = [ 0.5, 0.5, 0.5 ];\nvar arr2 = typedarraypool.malloc( arr1, 'float32' )\n","typedarraypool.calloc":"var arr = typedarraypool.calloc()\narr = typedarraypool.calloc( 'float32' )\nvar arr = typedarraypool.calloc( 5 )\narr = typedarraypool.calloc( 5, 'int32' )\n","typedarraypool.free":"var arr = typedarraypool( 5 )\ntypedarraypool.free( arr );\n","typedarraypool.clear":"var arr = typedarraypool( 5 )\ntypedarraypool.free( arr );\ntypedarraypool.clear();\n","typedarraypool.highWaterMark":"typedarraypool.highWaterMark\n","typedarraypool.nbytes":"var arr = typedarraypool( 5 )\ntypedarraypool.nbytes\n","typedarraypool.factory":"var pool = typedarraypool.factory();\nvar arr1 = pool( 3, 'float64' )\n","typemax":"var m = typemax( 'int8' )\nm = typemax( 'uint32' )\n","typemin":"var m = typemin( 'int8' )\nm = typemin( 'uint32' )\n","typeOf":"var t = typeOf( 'a' )\nt = typeOf( 5 )\nt = typeOf( NaN )\nt = typeOf( true )\nt = typeOf( false )\nt = typeOf( null )\nt = typeOf( undefined )\nt = typeOf( [] )\nt = typeOf( {} )\nt = typeOf( function noop() {} )\nt = typeOf( Symbol( 'beep' ) )\nt = typeOf( /.+/ )\nt = typeOf( new String( 'beep' ) )\nt = typeOf( new Number( 5 ) )\nt = typeOf( new Boolean( false ) )\nt = typeOf( new Array() )\nt = typeOf( new Object() )\nt = typeOf( new Int8Array( 10 ) )\nt = typeOf( new Uint8Array( 10 ) )\nt = typeOf( new Uint8ClampedArray( 10 ) )\nt = typeOf( new Int16Array( 10 ) )\nt = typeOf( new Uint16Array( 10 ) )\nt = typeOf( new Int32Array( 10 ) )\nt = typeOf( new Uint32Array( 10 ) )\nt = typeOf( new Float32Array( 10 ) )\nt = typeOf( new Float64Array( 10 ) )\nt = typeOf( new ArrayBuffer( 10 ) )\nt = typeOf( new Date() )\nt = typeOf( new RegExp( '.+' ) )\nt = typeOf( new Map() )\nt = typeOf( new Set() )\nt = typeOf( new WeakMap() )\nt = typeOf( new WeakSet() )\nt = typeOf( new Error( 'beep' ) )\nt = typeOf( new TypeError( 'beep' ) )\nt = typeOf( new SyntaxError( 'beep' ) )\nt = typeOf( new ReferenceError( 'beep' ) )\nt = typeOf( new URIError( 'beep' ) )\nt = typeOf( new RangeError( 'beep' ) )\nt = typeOf( new EvalError( 'beep' ) )\nt = typeOf( Math )\nt = typeOf( JSON )\nfunction beep() { return arguments; };\nt = typeOf( beep() )\nt = typeOf( new Buffer( 10 ) )\nfunction Person() { return this };\nt = typeOf( new Person() )\nvar Foo = function () { return this; };\nt = typeOf( new Foo() )\n","UINT8_MAX":"UINT8_MAX\n","UINT8_NUM_BYTES":"UINT8_NUM_BYTES\n","Uint8Array":"var arr = new Uint8Array()\nvar arr = new Uint8Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint8Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint8Array( arr1 )\nvar buf = new ArrayBuffer( 4 );\nvar arr = new Uint8Array( buf, 0, 4 )\n","Uint8Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint8Array.from( [ 1, 2 ], mapFcn )\n","Uint8Array.of":"var arr = Uint8Array.of( 1, 2 )\n","Uint8Array.BYTES_PER_ELEMENT":"Uint8Array.BYTES_PER_ELEMENT\n","Uint8Array.name":"Uint8Array.name\n","Uint8Array.prototype.buffer":"var arr = new Uint8Array( 5 );\narr.buffer\n","Uint8Array.prototype.byteLength":"var arr = new Uint8Array( 5 );\narr.byteLength\n","Uint8Array.prototype.byteOffset":"var arr = new Uint8Array( 5 );\narr.byteOffset\n","Uint8Array.prototype.BYTES_PER_ELEMENT":"var arr = new Uint8Array( 5 );\narr.BYTES_PER_ELEMENT\n","Uint8Array.prototype.length":"var arr = new Uint8Array( 5 );\narr.length\n","Uint8Array.prototype.copyWithin":"var arr = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint8Array.prototype.entries":"var arr = new Uint8Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint8Array.prototype.every":"var arr = new Uint8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint8Array.prototype.fill":"var arr = new Uint8Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint8Array.prototype.filter":"var arr1 = new Uint8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint8Array.prototype.find":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint8Array.prototype.findIndex":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint8Array.prototype.forEach":"var arr = new Uint8Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint8Array.prototype.includes":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint8Array.prototype.indexOf":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint8Array.prototype.join":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint8Array.prototype.keys":"var arr = new Uint8Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint8Array.prototype.lastIndexOf":"var arr = new Uint8Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint8Array.prototype.map":"var arr1 = new Uint8Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Uint8Array.prototype.reduce":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint8Array.prototype.reduceRight":"var arr = new Uint8Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint8Array.prototype.reverse":"var arr = new Uint8Array( [ 1, 2, 3 ] )\narr.reverse()\n","Uint8Array.prototype.set":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint8Array.prototype.slice":"var arr1 = new Uint8Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint8Array.prototype.some":"var arr = new Uint8Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint8Array.prototype.sort":"var arr = new Uint8Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint8Array.prototype.subarray":"var arr1 = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint8Array.prototype.toLocaleString":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint8Array.prototype.toString":"var arr = new Uint8Array( [ 1, 2, 3 ] );\narr.toString()\n","Uint8Array.prototype.values":"var arr = new Uint8Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","Uint8ClampedArray":"var arr = new Uint8ClampedArray()\nvar arr = new Uint8ClampedArray( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint8ClampedArray( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint8ClampedArray( arr1 )\nvar buf = new ArrayBuffer( 4 );\nvar arr = new Uint8ClampedArray( buf, 0, 4 )\n","Uint8ClampedArray.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint8ClampedArray.from( [ 1, 2 ], mapFcn )\n","Uint8ClampedArray.of":"var arr = Uint8ClampedArray.of( 1, 2 )\n","Uint8ClampedArray.BYTES_PER_ELEMENT":"Uint8ClampedArray.BYTES_PER_ELEMENT\n","Uint8ClampedArray.name":"Uint8ClampedArray.name\n","Uint8ClampedArray.prototype.buffer":"var arr = new Uint8ClampedArray( 5 );\narr.buffer\n","Uint8ClampedArray.prototype.byteLength":"var arr = new Uint8ClampedArray( 5 );\narr.byteLength\n","Uint8ClampedArray.prototype.byteOffset":"var arr = new Uint8ClampedArray( 5 );\narr.byteOffset\n","Uint8ClampedArray.prototype.BYTES_PER_ELEMENT":"var arr = new Uint8ClampedArray( 5 );\narr.BYTES_PER_ELEMENT\n","Uint8ClampedArray.prototype.length":"var arr = new Uint8ClampedArray( 5 );\narr.length\n","Uint8ClampedArray.prototype.copyWithin":"var arr = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint8ClampedArray.prototype.entries":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint8ClampedArray.prototype.every":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint8ClampedArray.prototype.fill":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint8ClampedArray.prototype.filter":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint8ClampedArray.prototype.find":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint8ClampedArray.prototype.findIndex":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint8ClampedArray.prototype.forEach":"var arr = new Uint8ClampedArray( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint8ClampedArray.prototype.includes":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint8ClampedArray.prototype.indexOf":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint8ClampedArray.prototype.join":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint8ClampedArray.prototype.keys":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint8ClampedArray.prototype.lastIndexOf":"var arr = new Uint8ClampedArray( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint8ClampedArray.prototype.map":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Uint8ClampedArray.prototype.reduce":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint8ClampedArray.prototype.reduceRight":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint8ClampedArray.prototype.reverse":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] )\narr.reverse()\n","Uint8ClampedArray.prototype.set":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint8ClampedArray.prototype.slice":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint8ClampedArray.prototype.some":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint8ClampedArray.prototype.sort":"var arr = new Uint8ClampedArray( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint8ClampedArray.prototype.subarray":"var arr1 = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint8ClampedArray.prototype.toLocaleString":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint8ClampedArray.prototype.toString":"var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\narr.toString()\n","Uint8ClampedArray.prototype.values":"var arr = new Uint8ClampedArray( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","UINT16_MAX":"UINT16_MAX\n","UINT16_NUM_BYTES":"UINT16_NUM_BYTES\n","Uint16Array":"var arr = new Uint16Array()\nvar arr = new Uint16Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint16Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint16Array( arr1 )\nvar buf = new ArrayBuffer( 8 );\nvar arr = new Uint16Array( buf, 0, 4 )\n","Uint16Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint16Array.from( [ 1, 2 ], mapFcn )\n","Uint16Array.of":"var arr = Uint16Array.of( 1, 2 )\n","Uint16Array.BYTES_PER_ELEMENT":"Uint16Array.BYTES_PER_ELEMENT\n","Uint16Array.name":"Uint16Array.name\n","Uint16Array.prototype.buffer":"var arr = new Uint16Array( 5 );\narr.buffer\n","Uint16Array.prototype.byteLength":"var arr = new Uint16Array( 5 );\narr.byteLength\n","Uint16Array.prototype.byteOffset":"var arr = new Uint16Array( 5 );\narr.byteOffset\n","Uint16Array.prototype.BYTES_PER_ELEMENT":"var arr = new Uint16Array( 5 );\narr.BYTES_PER_ELEMENT\n","Uint16Array.prototype.length":"var arr = new Uint16Array( 5 );\narr.length\n","Uint16Array.prototype.copyWithin":"var arr = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint16Array.prototype.entries":"var arr = new Uint16Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint16Array.prototype.every":"var arr = new Uint16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint16Array.prototype.fill":"var arr = new Uint16Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint16Array.prototype.filter":"var arr1 = new Uint16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint16Array.prototype.find":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint16Array.prototype.findIndex":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint16Array.prototype.forEach":"var arr = new Uint16Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint16Array.prototype.includes":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint16Array.prototype.indexOf":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint16Array.prototype.join":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint16Array.prototype.keys":"var arr = new Uint16Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint16Array.prototype.lastIndexOf":"var arr = new Uint16Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint16Array.prototype.map":"var arr1 = new Uint16Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Uint16Array.prototype.reduce":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint16Array.prototype.reduceRight":"var arr = new Uint16Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint16Array.prototype.reverse":"var arr = new Uint16Array( [ 1, 2, 3 ] )\narr.reverse()\n","Uint16Array.prototype.set":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint16Array.prototype.slice":"var arr1 = new Uint16Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint16Array.prototype.some":"var arr = new Uint16Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint16Array.prototype.sort":"var arr = new Uint16Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint16Array.prototype.subarray":"var arr1 = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint16Array.prototype.toLocaleString":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint16Array.prototype.toString":"var arr = new Uint16Array( [ 1, 2, 3 ] );\narr.toString()\n","Uint16Array.prototype.values":"var arr = new Uint16Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","UINT32_MAX":"UINT32_MAX\n","UINT32_NUM_BYTES":"UINT32_NUM_BYTES\n","Uint32Array":"var arr = new Uint32Array()\nvar arr = new Uint32Array( 5 )\nvar arr1 = new Int32Array( [ 5, 5, 5 ] );\nvar arr2 = new Uint32Array( arr1 )\nvar arr1 = [ 5.0, 5.0, 5.0 ];\nvar arr2 = new Uint32Array( arr1 )\nvar buf = new ArrayBuffer( 16 );\nvar arr = new Uint32Array( buf, 0, 4 )\n","Uint32Array.from":"function mapFcn( v ) { return v * 2; };\nvar arr = Uint32Array.from( [ 1, 2 ], mapFcn )\n","Uint32Array.of":"var arr = Uint32Array.of( 1, 2 )\n","Uint32Array.BYTES_PER_ELEMENT":"Uint32Array.BYTES_PER_ELEMENT\n","Uint32Array.name":"Uint32Array.name\n","Uint32Array.prototype.buffer":"var arr = new Uint32Array( 5 );\narr.buffer\n","Uint32Array.prototype.byteLength":"var arr = new Uint32Array( 5 );\narr.byteLength\n","Uint32Array.prototype.byteOffset":"var arr = new Uint32Array( 5 );\narr.byteOffset\n","Uint32Array.prototype.BYTES_PER_ELEMENT":"var arr = new Uint32Array( 5 );\narr.BYTES_PER_ELEMENT\n","Uint32Array.prototype.length":"var arr = new Uint32Array( 5 );\narr.length\n","Uint32Array.prototype.copyWithin":"var arr = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\narr.copyWithin( 3, 0, 2 );\narr[ 3 ]\narr[ 4 ]\n","Uint32Array.prototype.entries":"var arr = new Uint32Array( [ 1, 2 ] );\nit = arr.entries();\nit.next().value\nit.next().value\nit.next().done\n","Uint32Array.prototype.every":"var arr = new Uint32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v <= 1 ); };\narr.every( predicate )\n","Uint32Array.prototype.fill":"var arr = new Uint32Array( [ 1, 2 ] );\narr.fill( 3 );\narr[ 0 ]\narr[ 1 ]\n","Uint32Array.prototype.filter":"var arr1 = new Uint32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 1 ); };\nvar arr2 = arr1.filter( predicate );\narr2.length\n","Uint32Array.prototype.find":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar v = arr.find( predicate )\n","Uint32Array.prototype.findIndex":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction predicate( v ) { return ( v > 2 ); };\nvar idx = arr.findIndex( predicate )\n","Uint32Array.prototype.forEach":"var arr = new Uint32Array( [ 3, 2, 1 ] );\nvar str = ' ';\nfunction fcn( v, i ) { str += i + ':' + v + ' '; };\narr.forEach( fcn );\nstr\n","Uint32Array.prototype.includes":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nvar bool = arr.includes( 4 )\nbool = arr.includes( 3 )\n","Uint32Array.prototype.indexOf":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nvar idx = arr.indexOf( 4 )\nidx = arr.indexOf( 3 )\n","Uint32Array.prototype.join":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.join( '|' )\n","Uint32Array.prototype.keys":"var arr = new Uint32Array( [ 1, 2 ] );\nit = arr.keys();\nit.next().value\nit.next().value\nit.next().done\n","Uint32Array.prototype.lastIndexOf":"var arr = new Uint32Array( [ 1, 0, 2, 0, 1 ] );\nvar idx = arr.lastIndexOf( 3 )\nidx = arr.lastIndexOf( 0 )\n","Uint32Array.prototype.map":"var arr1 = new Uint32Array( [ 1, 2, 3 ] );\nfunction fcn( v ) { return v * 2; };\nvar arr2 = arr1.map( fcn )\n","Uint32Array.prototype.reduce":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduce( fcn, 0 )\n","Uint32Array.prototype.reduceRight":"var arr = new Uint32Array( [ 1, 2, 3 ] );\nfunction fcn( acc, v ) { return acc + (v*v); };\nvar v = arr.reduceRight( fcn, 0 )\n","Uint32Array.prototype.reverse":"var arr = new Uint32Array( [ 1, 2, 3 ] )\narr.reverse()\n","Uint32Array.prototype.set":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.set( [ 4, 4 ], 1 );\narr[ 1 ]\narr[ 2 ]\n","Uint32Array.prototype.slice":"var arr1 = new Uint32Array( [ 1, 2, 3 ] );\nvar arr2 = arr1.slice( 1 );\narr2.length\narr2[ 0 ]\narr2[ 1 ]\n","Uint32Array.prototype.some":"var arr = new Uint32Array( [ 1, 2 ] );\nfunction predicate( v ) { return ( v > 1 ); };\narr.some( predicate )\n","Uint32Array.prototype.sort":"var arr = new Uint32Array( [ 1, 2, 0, 2, 1 ] );\narr.sort()\n","Uint32Array.prototype.subarray":"var arr1 = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\nvar arr2 = arr1.subarray( 2 )\n","Uint32Array.prototype.toLocaleString":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.toLocaleString()\n","Uint32Array.prototype.toString":"var arr = new Uint32Array( [ 1, 2, 3 ] );\narr.toString()\n","Uint32Array.prototype.values":"var arr = new Uint32Array( [ 1, 2 ] );\nit = arr.values();\nit.next().value\nit.next().value\nit.next().done\n","umask":"var mask = umask()\nmask = umask( { 'symbolic': true } )\n","uncapitalize":"var out = uncapitalize( 'Beep' )\nout = uncapitalize( 'bOOp' )\n","uncapitalizeKeys":"var obj = { 'AA': 1, 'BB': 2 };\nvar out = uncapitalizeKeys( obj )\n","uncurry":"function addX( x ) {\n return function addY( y ) {\n     return x + y;\n };\n };\nvar fcn = uncurry( addX );\nvar sum = fcn( 2, 3 )\nfunction add( x ) {\n return function add( y ) {\n     return x + y;\n };\n };\nfcn = uncurry( add, 2 );\nsum = fcn( 9 )\nfunction addX( x ) {\n this.x = x;\n return addY;\n };\nfunction addY( y ) {\n return this.x + y;\n };\nfcn = uncurry( addX, {} );\nsum = fcn( 2, 3 )\n","uncurryRight":"function addX( x ) {\n return function addY( y ) {\n     return x + y;\n };\n };\nvar fcn = uncurryRight( addX );\nvar sum = fcn( 3, 2 )\nfunction add( y ) {\n return function add( x ) {\n     return x + y;\n };\n };\nfcn = uncurryRight( add, 2 );\nsum = fcn( 9 )\nfunction addY( y ) {\n this.y = y;\n return addX;\n };\nfunction addX( x ) {\n return x + this.y;\n };\nfcn = uncurryRight( addY, {} );\nsum = fcn( 3, 2 )\n","UNICODE_MAX":"UNICODE_MAX\n","UNICODE_MAX_BMP":"UNICODE_MAX_BMP\n","UnicodeColumnChartSparkline":"var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\nvar chart = new UnicodeColumnChartSparkline( data );\nchart.render()\n","UnicodeLineChartSparkline":"var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\nvar chart = new UnicodeLineChartSparkline( data );\nchart.render()\n","UnicodeSparkline":"var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\nvar chart = new UnicodeSparkline( data );\nchart.render()\nchart.type = 'line';\nchart.render()\n","UnicodeTristateChartSparkline":"var data = [ -1, 1, 0, 0, 1, -1, -1, 1 ];\nvar chart = new UnicodeTristateChartSparkline( data );\nchart.render()\n","UnicodeUpDownChartSparkline":"var data = [ -1, 1, 1, 1, 1, -1, -1, 1 ];\nvar chart = new UnicodeUpDownChartSparkline( data );\nchart.render()\n","UnicodeWinLossChartSparkline":"var data = [ -2, 1, 2, 2, 1, -1, -1, 1 ];\nvar chart = new UnicodeWinLossChartSparkline( data );\nchart.render()\n","unlink":"function done( error ) {\n if ( error ) {\n     console.error( error.message );\n }\n };\nunlink( './beep/boop.txt', done );\n","unlink.sync":"var out = unlink.sync( './beep/boop.txt' );\n","unshift":"var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\narr = unshift( arr, 6.0, 7.0 )\narr = new Float64Array( [ 1.0, 2.0 ] );\narr = unshift( arr, 3.0, 4.0 )\narr = { 'length': 1, '0': 1.0 };\narr = unshift( arr, 2.0, 3.0 )\n","until":"function predicate( i ) { return ( i >= 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\nuntil( predicate, beep )\n","untilAsync":"function predicate( i, clbk ) { clbk( null, i >= 5 ); };\nfunction fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n     next( null, 'boop'+i );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nuntilAsync( predicate, fcn, done )\n","untilEach":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\nuntilEach( arr, predicate, logger )\n","untilEachRight":"function predicate( v ) { return v !== v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\nuntilEachRight( arr, predicate, logger )\n","unzip":"var arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\nvar out = unzip( arr )\narr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\nout = unzip( arr, [ 0, 2 ] )\n","uppercase":"var out = uppercase( 'bEEp' )\n","uppercaseKeys":"var obj = { 'a': 1, 'b': 2 };\nvar out = uppercaseKeys( obj )\n","US_STATES_ABBR":"var list = US_STATES_ABBR()\n","US_STATES_CAPITALS":"var list = US_STATES_CAPITALS()\n","US_STATES_CAPITALS_NAMES":"var out = US_STATES_CAPITALS_NAMES()\n","US_STATES_NAMES":"var list = US_STATES_NAMES()\n","US_STATES_NAMES_CAPITALS":"var out = US_STATES_NAMES_CAPITALS()\n","utf16ToUTF8Array":"var str = '☃';\nvar out = utf16ToUTF8Array( str )\n","vartest":"var x = [ 610, 610, 550, 590, 565, 570 ];\nvar y = [ 560, 550, 580, 550, 560, 590, 550, 590 ];\nvar out = vartest( x, y )\nvar table = out.print()\n","waterfall":"function foo( next ) { next( null, 'beep' ); };\nfunction bar( str, next ) { console.log( str ); next(); };\nfunction done( error ) { if ( error ) { throw error; } };\nvar fcns = [ foo, bar ];\nwaterfall( fcns, done );\n","waterfall.factory":"function foo( next ) { next( null, 'beep' ); };\nfunction bar( str, next ) { console.log( str ); next(); };\nfunction done( error ) { if ( error ) { throw error; } };\nvar fcns = [ foo, bar ];\nvar waterfall = waterfall.factory( fcns, done );\nwaterfall();\nwaterfall();\nwaterfall();\n","WebAssemblyMemory":"var mem = new WebAssemblyMemory( { 'initial': 0 } )\n","WebAssemblyMemory.prototype.buffer":"var mem = new WebAssemblyMemory( { 'initial': 0 } );\nmem.buffer\n","WebAssemblyMemory.prototype.grow":"var mem = new WebAssemblyMemory( { 'initial': 0 } );\nmem.grow( 1 )\n","whileAsync":"function predicate( i, clbk ) { clbk( null, i < 5 ); };\nfunction fcn( i, next ) {\n setTimeout( onTimeout, i );\n function onTimeout() {\n     next( null, 'boop'+i );\n }\n };\nfunction done( error, result ) {\n if ( error ) {\n     throw error;\n }\n console.log( result );\n };\nwhileAsync( predicate, fcn, done )\n","whileEach":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, 2, 3, 4, NaN, 5 ];\nwhileEach( arr, predicate, logger )\n","whileEachRight":"function predicate( v ) { return v === v; };\nfunction logger( v, i ) { console.log( '%s: %d', i, v ); };\nvar arr = [ 1, NaN, 2, 3, 4, 5 ];\nwhileEachRight( arr, predicate, logger )\n","whilst":"function predicate( i ) { return ( i < 5 ); };\nfunction beep( i ) { console.log( 'boop: %d', i ); };\nwhilst( predicate, beep )\n","wilcoxon":"var arr = [ 6, 8, 14, 16, 23, 24, 28, 29, 41, -48, 49, 56, 60, -67, 75 ];\nvar out = wilcoxon( x )\nrunif = base.random.discreteUniform.factory( 1, 5, { 'seed': 786 });\nvar x = new Array( 100 );\nvar y = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = runif();\n y[ i ] = runif();\n }\nout = wilcoxon( x, y )\nvar table = out.print()\nout = wilcoxon( arr, { 'alpha': 0.01 });\ntable = out.print()\nout = wilcoxon( arr, { 'mu': 10 })\nout = wilcoxon( arr, { 'alternative': 'less' });\ntable = out.print()\nout = wilcoxon( arr, { 'alternative': 'greater' });\ntable = out.print()\n","writableProperties":"function Foo() { this.beep = 'boop'; return this; };\nFoo.prototype.foo = 'bar';\nvar obj = new Foo();\nvar props = writableProperties( obj )\n","writablePropertiesIn":"var props = writablePropertiesIn( [] )\n","writablePropertyNames":"var obj = { 'a': 'b' };\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = writablePropertyNames( obj )\n","writablePropertyNamesIn":"var obj = { 'a': 'b' };\nvar desc = {};\ndesc.configurable = true;\ndesc.enumerable = true;\ndesc.writable = false;\ndesc.value = 'boop';\ndefineProperty( obj, 'beep', desc );\nvar keys = writablePropertyNamesIn( obj )\n","writablePropertySymbols":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = writablePropertySymbols( obj )\n","writablePropertySymbolsIn":"var obj = {};\nvar desc = {};\ndesc.configurable = false;\ndesc.enumerable = false;\ndesc.writable = true;\ndesc.value = 'boop';\nvar sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\ndefineProperty( obj, sym, desc );\nvar symbols = writablePropertySymbolsIn( obj )\n","writeFile":"function onWrite( error ) {\n if ( error ) {\n     console.error( error.message );\n }\n };\nwriteFile( './beep/boop.txt', 'beep boop', onWrite );\n","writeFile.sync":"var err = writeFile.sync( './beep/boop.txt', 'beep boop' );\n","zip":"var out = zip( [ 1, 2 ], [ 'a', 'b' ] )\nvar opts = { 'trunc': false };\nout = zip( [ 1, 2, 3 ], [ 'a', 'b' ], opts )\n","ztest":"var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 212 } );\nvar x = new Array( 100 );\nfor ( var i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm();\n }\nvar out = ztest( x, 2.0 )\narr = [ 2, 4, 3, 1, 0 ];\nout = ztest( arr, 2.0, { 'alpha': 0.01 } );\ntable = out.print()\nvar arr = [ 4, 4, 6, 6, 5 ];\nout = ztest( arr, 1.0, { 'mu': 5 } )\narr = [ 4, 4, 6, 6, 5 ];\nout = ztest( arr, 1.0, { 'alternative': 'less' } )\nout = ztest( arr, 1.0, { 'alternative': 'greater' } )\n","ztest2":"var x = [ -0.21, 0.14, 1.65, 2.11, -1.86, -0.29, 1.48, 0.81, 0.86, 1.04 ];\nvar y = [ -1.53, -2.93, 2.34, -1.15, 2.7, -0.12, 4.22, 1.66, 3.43, 4.66 ];\nvar out = ztest2( x, y, 2.0, 2.0 )\nvar table = out.print()\nout = ztest2( x, y, 2.0, 2.0, { 'alpha': 0.4 } );\ntable = out.print()\nout = ztest2( x, y, 2.0, 2.0, { 'alternative': 'less' } );\ntable = out.print()\nout = ztest2( x, y, 2.0, 2.0, { 'alternative': 'greater' } );\ntable = out.print()\nvar rnorm = base.random.normal.factory({ 'seed': 372 } );\nx = new Array( 100 );\nfor ( i = 0; i < x.length; i++ ) {\n x[ i ] = rnorm( 2.0, 1.0 );\n }\ny = new Array( 100 );\n for ( i = 0; i < x.length; i++ ) {\n y[ i ] = rnorm( 0.0, 2.0 );\n }\nout = ztest2( x, y, 1.0, 2.0, { 'difference': 2.0 } )\n"}
diff --git a/lib/node_modules/@stdlib/repl/data/contributor.json b/lib/node_modules/@stdlib/repl/data/contributor.json
index 59638900290e..dace9792483a 100644
--- a/lib/node_modules/@stdlib/repl/data/contributor.json
+++ b/lib/node_modules/@stdlib/repl/data/contributor.json
@@ -1 +1 @@
-["Aadish Jain","Aayush Khanna","Abhijit Raut","Adarsh Palaskar","Aditya Sapra","Ahmed Atwa","Ahmed Kashkoush","Ahmed Khaled","Aleksandr","Ali Salesi","Aman Bhansali","Amit Jimiwal","Anudeep Sanapala","Athan Reines","Ayaka","Brendan Graetz","Bruno Fenzl","Bryan Elee","Chinmay Joshi","Christopher Dambamuromo","Dan Rose","Daniel Killenberger","Daniel Yu","Debashis Maharana","Desh Deepak Kant","Divyansh Seth","Dominic Lim","Dominik Moritz","Dorrin Sotoudeh","EuniceSim142","Frank Kovacs","Golden Kumar","Gunj Joshi","Gururaj Gurram","HarshaNP","Harshita Kalani","Hridyanshu","Jaimin Godhani","James Gelok","Jaysukh Makvana","Jenish Thapa","Jithin KS","Joel Mathew Koshy","Joey Reed","Jordan Gallivan","Joris Labie","Justin Dennison","Karthik Prakash","Kohantika Nath","Krishnendu Das","Kshitij-Dale","Lovelin Dhoni J B","Manik Sharma","Manvith M","Marcus Fantham","Matt Cochrane","Mihir Pandit","Milan Raj","Mohammad Kaif","Momtchil Momtchev","Muhammad Haris","Naresh Jagadeesan","Naveen Kumar","Neeraj Pathak","Nishant Shinde","Nithin Katta","Nourhan Hasan","Ognjen Jevremović","Oneday12323","Ori Miles","Philipp Burckhardt","Prajwal Kulkarni","Pranav Goswami","Pranjal Jha","Prashant Kumar Yadav","Pratik Singh","Pratyush Kumar Chouhan","Priyansh Prajapati","Priyanshu Agarwal","Pushpendra Chandravanshi","Raunak Kumar Gupta","Rejoan Sardar","Ricky Reusser","Ridam Garg","Rishav","Robert Gislason","Roman Stetsyk","Rutam Kathale","Ruthwik Chikoti","Ryan Seal","Rylan Yang","Sai Srikar Dumpeti","Sarthak Paandey","Saurabh Singh","Seyyed Parsa Neshaei","Shashank Shekhar Singh","Shivam Ahir","Shraddheya Shendre","Shubh Mehta","Shubham Mishra","Sivam Das","Snehil Shah","Soumajit Chatterjee","Spandan Barve","Stephannie Jiménez Gacha","Suraj Kumar","Tirtadwipa Manunggal","Tudor Pagu","Tufailahmed Bargir","Utkarsh","Utkarsh Raj","UtkershBasnet","Vaibhav Patel","Varad Gupta","Vinit Pandit","Vivek maurya","Xiaochuan Ye","Yaswanth Kosuru","Yernar Yergaziyev","olenkabilonizhka","rainn","rei2hu"]
+["Aadish Jain","Aayush Khanna","Abhijit Raut","Adarsh Palaskar","Aditya Sapra","Ahmed Atwa","Ahmed Kashkoush","Ahmed Khaled","Aleksandr","Ali Salesi","Aman Bhansali","Amit Jimiwal","Anudeep Sanapala","Athan Reines","Ayaka","Brendan Graetz","Bruno Fenzl","Bryan Elee","Chinmay Joshi","Christopher Dambamuromo","Dan Rose","Daniel Killenberger","Daniel Yu","Debashis Maharana","Desh Deepak Kant","Dhruv/","Divyansh Seth","Dominic Lim","Dominik Moritz","Dorrin Sotoudeh","EuniceSim142","Frank Kovacs","Golden Kumar","Gunj Joshi","Gururaj Gurram","HarshaNP","Harshita Kalani","Hridyanshu","Jaimin Godhani","James Gelok","Jaysukh Makvana","Jenish Thapa","Jithin KS","Joel Mathew Koshy","Joey Reed","Jordan Gallivan","Joris Labie","Justin Dennison","Karthik Prakash","Kohantika Nath","Krishnendu Das","Kshitij-Dale","Lovelin Dhoni J B","Manik Sharma","Manvith M","Marcus Fantham","Matt Cochrane","Mihir Pandit","Milan Raj","Mohammad Kaif","Momtchil Momtchev","Muhammad Haris","Naresh Jagadeesan","Naveen Kumar","Neeraj Pathak","Nishant Shinde","Nithin Katta","Nourhan Hasan","Ognjen Jevremović","Oneday12323","Ori Miles","Philipp Burckhardt","Prajwal Kulkarni","Pranav Goswami","Pranjal Jha","Prashant Kumar Yadav","Pratik Singh","Pratyush Kumar Chouhan","Priyansh Prajapati","Priyanshu Agarwal","Pushpendra Chandravanshi","Raunak Kumar Gupta","Rejoan Sardar","Ricky Reusser","Ridam Garg","Rishav","Robert Gislason","Roman Stetsyk","Rutam Kathale","Ruthwik Chikoti","Ryan Seal","Rylan Yang","Sai Srikar Dumpeti","Sarthak Paandey","Saurabh Singh","Seyyed Parsa Neshaei","Shashank Shekhar Singh","Shivam Ahir","Shraddheya Shendre","Shubh Mehta","Shubham Mishra","Sivam Das","Snehil Shah","Soumajit Chatterjee","Spandan Barve","Stephannie Jiménez Gacha","Suraj Kumar","Tirtadwipa Manunggal","Tudor Pagu","Tufailahmed Bargir","Utkarsh","Utkarsh Raj","UtkershBasnet","Vaibhav Patel","Varad Gupta","Vinit Pandit","Vivek maurya","Xiaochuan Ye","Yaswanth Kosuru","Yernar Yergaziyev","olenkabilonizhka","rainn","rei2hu"]
diff --git a/lib/node_modules/@stdlib/repl/help/data/data.csv b/lib/node_modules/@stdlib/repl/help/data/data.csv
index de78fff5fc4f..cd2298d8ce40 100644
--- a/lib/node_modules/@stdlib/repl/help/data/data.csv
+++ b/lib/node_modules/@stdlib/repl/help/data/data.csv
@@ -1822,8 +1822,8 @@ base.strided.dnanmeanpn,"\nbase.strided.dnanmeanpn( N, x, stride )\n    Computes
 base.strided.dnanmeanpn.ndarray,"\nbase.strided.dnanmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction algorithm\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.dnanmean, base.strided.nanmeanpn, base.strided.snanmeanpn"
 base.strided.dnanmeanpw,"\nbase.strided.dnanmeanpw( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanpw( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanmeanpw( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanmeanpw( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dnanmeanpw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using pairwise summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanpw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmeanpw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpw, base.strided.dnanmean\n"
 base.strided.dnanmeanpw.ndarray,"\nbase.strided.dnanmeanpw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using pairwise summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanpw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmeanpw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpw, base.strided.dnanmean"
-base.strided.dnanmeanwd,"\nbase.strided.dnanmeanwd( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, using Welford's algorithm and ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanwd( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanmeanwd( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanmeanwd( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dnanmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanwd, base.strided.dnanmean, base.strided.nanmeanwd, base.strided.snanmeanwd\n"
-base.strided.dnanmeanwd.ndarray,"\nbase.strided.dnanmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanwd, base.strided.dnanmean, base.strided.nanmeanwd, base.strided.snanmeanwd"
+base.strided.dnanmeanwd,"\nbase.strided.dnanmeanwd( N, x, strideX )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, using Welford's algorithm and ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanwd( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > base.strided.dnanmeanwd( 3, x, 2 )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnanmeanwd( 3, x1, 2 )\n    ~-0.3333\n\n\nbase.strided.dnanmeanwd.ndarray( N, x, strideX, offsetX )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanmeanwd.ndarray( 3, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanwd, base.strided.dnanmean, base.strided.nanmeanwd, base.strided.snanmeanwd\n"
+base.strided.dnanmeanwd.ndarray,"\nbase.strided.dnanmeanwd.ndarray( N, x, strideX, offsetX )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanmeanwd.ndarray( 3, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanwd, base.strided.dnanmean, base.strided.nanmeanwd, base.strided.snanmeanwd"
 base.strided.dnanmin,"\nbase.strided.dnanmin( N, x, strideX )\n    Computes the minimum value of a double-precision floating-point strided\n    array, ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmin( x.length, x, 1 )\n    -2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > base.strided.dnanmin( 3, x, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnanmin( 3, x1, 2 )\n    -2.0\n\n\nbase.strided.dnanmin.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a double-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.dnanmin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanmin.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dnanmax, base.strided.nanmin, base.strided.snanmin\n"
 base.strided.dnanmin.ndarray,"\nbase.strided.dnanmin.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a double-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.dnanmin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanmin.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dnanmax, base.strided.nanmin, base.strided.snanmin"
 base.strided.dnanminabs,"\nbase.strided.dnanminabs( N, x, strideX )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array, ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanminabs( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > base.strided.dnanminabs( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnanminabs( 3, x1, 2 )\n    1.0\n\n\nbase.strided.dnanminabs.ndarray( N, x, strideX, offsetX )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.dnanminabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanminabs.ndarray( 3, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dminabs, base.strided.dnanmaxabs, base.strided.dnanmin, base.strided.nanminabs, base.strided.snanminabs\n"
@@ -2311,16 +2311,16 @@ base.strided.smeanpw,"\nbase.strided.smeanpw( N, x, stride )\n    Computes the a
 base.strided.smeanpw.ndarray,"\nbase.strided.smeanpw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanpw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanpw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpw, base.strided.meanpw, base.strided.smean"
 base.strided.smeanwd,"\nbase.strided.smeanwd( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanwd( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.smeanwd( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.smeanwd( N, x1, stride )\n    ~-0.3333\n\nbase.strided.smeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanwd, base.strided.meanwd, base.strided.smean, base.strided.snanmeanwd\n"
 base.strided.smeanwd.ndarray,"\nbase.strided.smeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanwd, base.strided.meanwd, base.strided.smean, base.strided.snanmeanwd"
-base.strided.smediansorted,"\nbase.strided.smediansorted( N, x, stride )\n    Computes the median value of a sorted single-precision floating-point\n    strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.smediansorted( x.length, x, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smediansorted( N, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.smediansorted( N, x1, 2 )\n    2.0\n\nbase.strided.smediansorted.ndarray( N, x, stride, offset )\n    Computes the median value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.smediansorted.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smediansorted.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmediansorted, base.strided.mediansorted, base.strided.smean\n"
-base.strided.smediansorted.ndarray,"\nbase.strided.smediansorted.ndarray( N, x, stride, offset )\n    Computes the median value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.smediansorted.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smediansorted.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmediansorted, base.strided.mediansorted, base.strided.smean"
+base.strided.smediansorted,"\nbase.strided.smediansorted( N, x, strideX )\n    Computes the median value of a sorted single-precision floating-point\n    strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    strideX: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.smediansorted( x.length, x, 1 )\n    2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.smediansorted( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.smediansorted( 3, x1, 2 )\n    2.0\n\n\nbase.strided.smediansorted.ndarray( N, x, strideX, offsetX )\n    Computes the median value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    strideX: integer\n        Index increment.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.smediansorted.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.smediansorted.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmediansorted, base.strided.mediansorted, base.strided.smean\n"
+base.strided.smediansorted.ndarray,"\nbase.strided.smediansorted.ndarray( N, x, strideX, offsetX )\n    Computes the median value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    strideX: integer\n        Index increment.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.smediansorted.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.smediansorted.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmediansorted, base.strided.mediansorted, base.strided.smean"
 base.strided.smidrange,"\nbase.strided.smidrange( N, x, strideX )\n    Computes the mid-range of a single-precision floating-point strided array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Mid-range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smidrange( x.length, x, 1 )\n    0.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.smidrange( 3, x, 2 )\n    0.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.smidrange( 3, x1, 2 )\n    0.0\n\n\nbase.strided.smidrange.ndarray( N, x, strideX, offsetX )\n    Computes the mid-range of a single-precision floating-point strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Mid-range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smidrange.ndarray( x.length, x, 1, 0 )\n    0.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.smidrange.ndarray( 3, x, 2, 1 )\n    0.0\n\n    See Also\n    --------\n    base.strided.dmidrange, base.strided.smax, base.strided.smean, base.strided.smin, base.strided.srange\n"
 base.strided.smidrange.ndarray,"\nbase.strided.smidrange.ndarray( N, x, strideX, offsetX )\n    Computes the mid-range of a single-precision floating-point strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Mid-range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smidrange.ndarray( x.length, x, 1, 0 )\n    0.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.smidrange.ndarray( 3, x, 2, 1 )\n    0.0\n\n    See Also\n    --------\n    base.strided.dmidrange, base.strided.smax, base.strided.smean, base.strided.smin, base.strided.srange"
 base.strided.smin,"\nbase.strided.smin( N, x, strideX )\n    Computes the minimum value of a single-precision floating-point strided\n    array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smin( x.length, x, 1 )\n    -2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.smin( 3, x, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.smin( 3, x1, 2 )\n    -2.0\n\n\nbase.strided.smin.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a single-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.smin.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.min, base.strided.smax, base.strided.snanmin\n"
 base.strided.smin.ndarray,"\nbase.strided.smin.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a single-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.smin.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.min, base.strided.smax, base.strided.snanmin"
 base.strided.sminabs,"\nbase.strided.sminabs( N, x, strideX )\n    Computes the minimum absolute value of a single-precision floating-point\n    strided array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sminabs( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.sminabs( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sminabs( 3, x1, 2 )\n    1.0\n\n\nbase.strided.sminabs.ndarray( N, x, strideX, offsetX )\n    Computes the minimum absolute value of a single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sminabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sminabs.ndarray( 3, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dminabs, base.strided.minabs, base.strided.smaxabs, base.strided.smin, base.strided.snanminabs\n"
 base.strided.sminabs.ndarray,"\nbase.strided.sminabs.ndarray( N, x, strideX, offsetX )\n    Computes the minimum absolute value of a single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sminabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sminabs.ndarray( 3, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dminabs, base.strided.minabs, base.strided.smaxabs, base.strided.smin, base.strided.snanminabs"
-base.strided.sminsorted,"\nbase.strided.sminsorted( N, x, stride )\n    Computes the minimum value of a sorted single-precision floating-point\n    strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.sminsorted( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sminsorted( N, x, stride )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sminsorted( N, x1, stride )\n    -2.0\n\nbase.strided.sminsorted.ndarray( N, x, stride, offset )\n    Computes the minimum value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.sminsorted.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sminsorted.ndarray( N, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dminsorted, base.strided.minsorted, base.strided.smaxsorted, base.strided.smin\n"
-base.strided.sminsorted.ndarray,"\nbase.strided.sminsorted.ndarray( N, x, stride, offset )\n    Computes the minimum value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.sminsorted.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sminsorted.ndarray( N, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dminsorted, base.strided.minsorted, base.strided.smaxsorted, base.strided.smin"
+base.strided.sminsorted,"\nbase.strided.sminsorted( N, x, strideX )\n    Computes the minimum value of a sorted single-precision floating-point\n    strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.sminsorted( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.sminsorted( 3, x, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sminsorted( 3, x1, 2 )\n    -2.0\n\n\nbase.strided.sminsorted.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.sminsorted.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.sminsorted.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dminsorted, base.strided.minsorted, base.strided.smaxsorted, base.strided.smin\n"
+base.strided.sminsorted.ndarray,"\nbase.strided.sminsorted.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.sminsorted.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.sminsorted.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dminsorted, base.strided.minsorted, base.strided.smaxsorted, base.strided.smin"
 base.strided.smskabs,"\nbase.strided.smskabs( N, x, sx, m, sm, y, sy )\n    Computes the absolute value for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ 2.0, 1.0, 0.0, 5.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskabs( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ 5.0, 1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 5.0, 1.0 ]\n\n\nbase.strided.smskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the absolute value for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 2.0, 1.0, 0.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 5.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dmskabs, base.strided.sabs, base.strided.smskabs2\n"
 base.strided.smskabs.ndarray,"\nbase.strided.smskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the absolute value for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 2.0, 1.0, 0.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 5.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dmskabs, base.strided.sabs, base.strided.smskabs2"
 base.strided.smskabs2,"\nbase.strided.smskabs2( N, x, sx, m, sm, y, sy )\n    Computes the squared absolute value for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point\n    strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs2( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ 4.0, 1.0, 0.0, 25.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs2( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, 4.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskabs2( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ 25.0, 1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 25.0, 1.0 ]\n\n\nbase.strided.smskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the squared absolute value for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point\n    strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 4.0, 1.0, 0.0, 25.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 25.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dmskabs2, base.strided.sabs2, base.strided.smskabs\n"
diff --git a/lib/node_modules/@stdlib/repl/help/data/data.json b/lib/node_modules/@stdlib/repl/help/data/data.json
index 03a7de903de9..2698f2c6682a 100644
--- a/lib/node_modules/@stdlib/repl/help/data/data.json
+++ b/lib/node_modules/@stdlib/repl/help/data/data.json
@@ -1 +1 @@
-{"abs":"\nabs( x[, options] )\n    Computes the absolute value.\n\n    If provided a number, the function returns a number.\n\n    If provided an ndarray or array-like object, the function performs element-\n    wise computation.\n\n    If provided an array-like object, the function returns an array-like object\n    having the same length and data type as `x`.\n\n    If provided an ndarray, the function returns an ndarray having the same\n    shape and data type as `x`.\n\n    Parameters\n    ----------\n    x: ndarray|ArrayLikeObject|number\n        Input value.\n\n    options: Object (optional)\n        Options.\n\n    options.order: string (optional)\n        Output array order (either row-major (C-style) or column-major (Fortran-\n        style)). Only applicable when the input array is an ndarray. By default,\n        the output array order is inferred from the input array.\n\n    options.dtype: string (optional)\n        Output array data type. Only applicable when the input array is either\n        an ndarray or array-like object. By default, the output array data type\n        is inferred from the input array.\n\n    Returns\n    -------\n    y: ndarray|ArrayLikeObject|number\n        Results.\n\n    Examples\n    --------\n    // Provide a number:\n    > var y = abs( -1.0 )\n    1.0\n\n    // Provide an array-like object:\n    > var x = new Float64Array( [ -1.0, -2.0 ] );\n    > y = abs( x )\n    <Float64Array>[ 1.0, 2.0 ]\n\n    > x = [ -1.0, -2.0 ];\n    > y = abs( x )\n    [ 1.0, 2.0 ]\n\n    // Provide an ndarray:\n    > x = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] );\n    > y = abs( x )\n    <ndarray>\n    > y.get( 0, 1 )\n    2.0\n\n\nabs.assign( x, y )\n    Computes the absolute value and assigns results to a provided output array.\n\n    Parameters\n    ----------\n    x: ndarray|ArrayLikeObject\n        Input array.\n\n    y: ndarray|ArrayLikeObject\n        Output array. Must be the same data \"kind\" (i.e., ndarray or array-like\n        object) as the input array.\n\n    Returns\n    -------\n    y: ndarray|ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Provide an array-like object:\n    > var x = new Float64Array( [ -1.0, -2.0 ] );\n    > var y = new Float64Array( x.length );\n    > var out = abs.assign( x, y )\n    <Float64Array>[ 1.0, 2.0 ]\n    > var bool = ( out === y )\n    true\n\n    > x = [ -1.0, -2.0 ];\n    > y = [ 0.0, 0.0 ];\n    > out = abs.assign( x, y )\n    [ 1.0, 2.0 ]\n    > bool = ( out === y )\n    true\n\n    // Provide an ndarray:\n    > x = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] );\n    > y = array( [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ] );\n    > out = abs.assign( x, y )\n    <ndarray>\n    > out.get( 0, 1 )\n    2.0\n    > bool = ( out === y )\n    true\n\n","abs.assign":"\nabs.assign( x, y )\n    Computes the absolute value and assigns results to a provided output array.\n\n    Parameters\n    ----------\n    x: ndarray|ArrayLikeObject\n        Input array.\n\n    y: ndarray|ArrayLikeObject\n        Output array. Must be the same data \"kind\" (i.e., ndarray or array-like\n        object) as the input array.\n\n    Returns\n    -------\n    y: ndarray|ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Provide an array-like object:\n    > var x = new Float64Array( [ -1.0, -2.0 ] );\n    > var y = new Float64Array( x.length );\n    > var out = abs.assign( x, y )\n    <Float64Array>[ 1.0, 2.0 ]\n    > var bool = ( out === y )\n    true\n\n    > x = [ -1.0, -2.0 ];\n    > y = [ 0.0, 0.0 ];\n    > out = abs.assign( x, y )\n    [ 1.0, 2.0 ]\n    > bool = ( out === y )\n    true\n\n    // Provide an ndarray:\n    > x = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] );\n    > y = array( [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ] );\n    > out = abs.assign( x, y )\n    <ndarray>\n    > out.get( 0, 1 )\n    2.0\n    > bool = ( out === y )\n    true","acartesianPower":"\nacartesianPower( x, n )\n    Returns the Cartesian power.\n\n    If provided an empty array, the function returns an empty array.\n\n    If `n` is less than or equal to zero, the function returns an empty array.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    n: integer\n        Power.\n\n    Returns\n    -------\n    out: Array<Array>\n        Cartesian product.\n\n    Examples\n    --------\n    > var x = [ 1, 2 ];\n    > var out = acartesianPower( x, 2 )\n    [ [ 1, 1 ], [ 1, 2 ], [ 2, 1 ], [ 2, 2 ] ]\n\n    See Also\n    --------\n    acartesianProduct, acartesianSquare\n","acartesianProduct":"\nacartesianProduct( x1, x2 )\n    Returns the Cartesian product.\n\n    If provided one or more empty arrays, the function returns an empty array.\n\n    Parameters\n    ----------\n    x1: ArrayLikeObject\n        First input array.\n\n    x2: ArrayLikeObject\n        Second input array.\n\n    Returns\n    -------\n    out: Array<Array>\n        Cartesian product.\n\n    Examples\n    --------\n    > var x1 = [ 1, 2 ];\n    > var x2 = [ 3, 4 ];\n    > var out = acartesianProduct( x1, x2 )\n    [ [ 1, 3 ], [ 1, 4 ], [ 2, 3 ], [ 2, 4 ] ]\n\n    See Also\n    --------\n    acartesianPower, acartesianSquare\n","acartesianSquare":"\nacartesianSquare( x )\n    Returns the Cartesian square.\n\n    If provided an empty array, the function returns an empty array.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    Returns\n    -------\n    out: Array<Array>\n        Cartesian product.\n\n    Examples\n    --------\n    > var out = acartesianSquare( [ 1, 2 ] )\n    [ [ 1, 1 ], [ 1, 2 ], [ 2, 1 ], [ 2, 2 ] ]\n\n    See Also\n    --------\n    acartesianPower, acartesianProduct\n","acronym":"\nacronym( str[, options] )\n    Generates an acronym for a given string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    options: Object (optional)\n        Options.\n\n    options.stopwords: Array<string> (optional)\n        Array of custom stop words.\n\n    Returns\n    -------\n    out: string\n        Acronym for the given string.\n\n    Examples\n    --------\n    > var out = acronym( 'the quick brown fox' )\n    'QBF'\n    > out = acronym( 'Hard-boiled eggs' )\n    'HBE'\n","aempty":"\naempty( length[, dtype] )\n    Creates an uninitialized array having a specified length.\n\n    In browser environments, the function always returns zero-filled arrays.\n\n    If `dtype` is 'generic', the function always returns a zero-filled array.\n\n    In Node.js versions >=3.0.0, the underlying memory of returned typed arrays\n    is *not* initialized. Memory contents are unknown and may contain\n    *sensitive* data.\n\n    Parameters\n    ----------\n    length: integer\n        Array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = aempty( 2 )\n    <Float64Array>\n    > arr = aempty( 2, 'float32' )\n    <Float32Array>\n\n    See Also\n    --------\n    aemptyLike, afull, aones, azeros, ndempty\n","aemptyLike":"\naemptyLike( x[, dtype] )\n    Creates an uninitialized array having the same length and data type as a\n    provided input array.\n\n    In browser environments, the function always returns zero-filled arrays.\n\n    If `dtype` is 'generic', the function always returns a zero-filled array.\n\n    In Node.js versions >=3.0.0, the underlying memory of returned typed arrays\n    is *not* initialized. Memory contents are unknown and may contain\n    *sensitive* data.\n\n    Parameters\n    ----------\n    x: TypedArray|Array\n        Input array.\n\n    dtype: string (optional)\n        Data type. If not provided, the output array data type is inferred from\n        the input array.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var x = new Float64Array( 2 );\n    > var arr = aemptyLike( x )\n    <Float64Array>\n    > arr = aemptyLike( x, 'float32' )\n    <Float32Array>\n\n    See Also\n    --------\n    aempty, afullLike, aonesLike, azerosLike, ndemptyLike\n","AFINN_96":"\nAFINN_96()\n    Returns a list of English words rated for valence.\n\n    The returned list contains 1468 English words (and phrases) rated for\n    valence. Negative words have a negative valence [-5,0). Positive words have\n    a positive valence (0,5]. Neutral words have a valence of 0.\n\n    A few notes:\n\n    - The list is an earlier version of AFINN-111.\n    - The list includes misspelled words. Their presence is intentional, as such\n      misspellings frequently occur in social media content.\n    - All words are lowercase.\n    - Some \"words\" are phrases; e.g., \"cashing in\", \"cool stuff\".\n    - Words may contain apostrophes; e.g., \"can't stand\".\n    - Words may contain dashes; e.g., \"cover-up\", \"made-up\".\n\n    Returns\n    -------\n    out: Array<Array>\n        List of English words and their valence.\n\n    Examples\n    --------\n    > var list = AFINN_96()\n    [ [ 'abandon', -2 ], [ 'abandons', -2 ], [ 'abandoned', -2 ], ... ]\n\n    References\n    ----------\n    - Nielsen, Finn Årup. 2011. \"A new ANEW: Evaluation of a word list for\n    sentiment analysis in microblogs.\" In *Proceedings of the ESWC2011 Workshop\n    on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n    718:93–98. CEUR Workshop Proceedings. <http://ceur-ws.org/Vol-718/paper_16.\n    pdf>.\n\n    * If you use the list for publication or third party consumption, please\n    cite the listed reference.\n\n    See Also\n    --------\n    AFINN_111\n","AFINN_111":"\nAFINN_111()\n    Returns a list of English words rated for valence.\n\n    The returned list contains 2477 English words (and phrases) rated for\n    valence. Negative words have a negative valence [-5,0). Positive words have\n    a positive valence (0,5]. Neutral words have a valence of 0.\n\n    A few notes:\n\n    - The list includes misspelled words. Their presence is intentional, as such\n      misspellings frequently occur in social media content.\n    - All words are lowercase.\n    - Words may contain numbers; e.g., \"n00b\".\n    - Some \"words\" are phrases; e.g., \"cool stuff\", \"not good\".\n    - Words may contain apostrophes; e.g., \"can't stand\".\n    - Words may contain diaeresis; e.g., \"naïve\".\n    - Words may contain dashes; e.g., \"self-deluded\", \"self-confident\".\n\n    Returns\n    -------\n    out: Array<Array>\n        List of English words and their valence.\n\n    Examples\n    --------\n    > var list = AFINN_111()\n    [ [ 'abandon', -2 ], [ 'abandoned', -2 ], [ 'abandons', -2 ], ... ]\n\n    References\n    ----------\n    - Nielsen, Finn Årup. 2011. \"A new ANEW: Evaluation of a word list for\n    sentiment analysis in microblogs.\" In *Proceedings of the ESWC2011 Workshop\n    on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n    718:93–98. CEUR Workshop Proceedings. <http://ceur-ws.org/Vol-718/paper_16.\n    pdf>.\n\n    * If you use the list for publication or third party consumption, please\n    cite the listed reference.\n\n    See Also\n    --------\n    AFINN_96\n","afull":"\nafull( length, value[, dtype] )\n    Returns a filled array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Array length.\n\n    value: any\n        Fill value.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = afull( 2, 1.0 )\n    <Float64Array>[ 1.0, 1.0 ]\n    > arr = afull( 2, 1.0, 'float32' )\n    <Float32Array>[ 1.0, 1.0 ]\n\n    See Also\n    --------\n    afullLike, aones, azeros\n","afullLike":"\nafullLike( x[, dtype] )\n    Returns a filled array having the same length and data type as a provided\n    input array.\n\n    Parameters\n    ----------\n    x: TypedArray|Array\n        Input array.\n\n    dtype: string (optional)\n        Data type. If not provided, the output array data type is inferred from\n        the input array.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var x = new Float64Array( 2 );\n    > var y = afullLike( x, 1.0 )\n    <Float64Array>[ 1.0, 1.0 ]\n    > y = afullLike( x, 1.0, 'float32' )\n    <Float32Array>[ 1.0, 1.0 ]\n\n    See Also\n    --------\n    afull, aonesLike, azerosLike\n","alias2pkg":"\nalias2pkg( alias )\n    Returns the package name associated with a provided alias.\n\n    Parameters\n    ----------\n    alias: string\n        Alias.\n\n    Returns\n    -------\n    out: string|null\n        Package name.\n\n    Examples\n    --------\n    > var v = alias2pkg( 'base.sin' )\n    '@stdlib/math/base/special/sin'\n\n    See Also\n    --------\n    alias2related, aliases, pkg2alias\n","alias2related":"\nalias2related( alias )\n    Returns aliases related to a specified alias.\n\n    Parameters\n    ----------\n    alias: string\n        Alias.\n\n    Returns\n    -------\n    out: Array|null\n        Related aliases.\n\n    Examples\n    --------\n    > var v = alias2related( 'base.sin' )\n    [...]\n\n    See Also\n    --------\n    alias2pkg, aliases, pkg2related\n","alias2standalone":"\nalias2standalone( alias )\n    Returns the standalone package name associated with a provided alias.\n\n    Parameters\n    ----------\n    alias: string\n        Alias.\n\n    Returns\n    -------\n    out: string|null\n        Standalone package name.\n\n    Examples\n    --------\n    > var v = alias2standalone( 'base.sin' )\n    '@stdlib/math-base-special-sin'\n\n    See Also\n    --------\n    alias2pkg, alias2related, aliases, pkg2alias, pkg2standalone\n","aliases":"\naliases( [namespace] )\n    Returns a list of standard library aliases.\n\n    Parameters\n    ----------\n    namespace: string (optional)\n        Namespace filter.\n\n    Returns\n    -------\n    out: Array\n        List of aliases.\n\n    Examples\n    --------\n    > var o = aliases()\n    [...]\n    > o = aliases( '@stdlib/math/base/special' )\n    [...]\n\n    See Also\n    --------\n    alias2pkg, alias2related, pkg2alias\n","allocUnsafe":"\nallocUnsafe( size )\n    Allocates a buffer having a specified number of bytes.\n\n    The underlying memory of returned buffers is not initialized. Memory\n    contents are unknown and may contain sensitive data.\n\n    When the size is less than half a buffer pool size, memory is allocated from\n    the buffer pool for faster allocation of Buffer instances.\n\n    Parameters\n    ----------\n    size: integer\n        Number of bytes to allocate.\n\n    Returns\n    -------\n    out: Buffer\n        Buffer instance.\n\n    Examples\n    --------\n    > var buf = allocUnsafe( 100 )\n    <Buffer>\n\n    See Also\n    --------\n    Buffer, array2buffer, arraybuffer2buffer, copyBuffer, string2buffer\n","amskfilter":"\namskfilter( x, mask )\n    Returns a new array by applying a mask to a provided input array.\n\n    If a mask array element is truthy, the corresponding element in `x` is\n    included in the output array; otherwise, the corresponding element in `x` is\n    \"masked\" and thus excluded from the output array.\n\n    Parameters\n    ----------\n    x: Array|TypedArray|Object\n        Input array.\n\n    mask: Array|TypedArray|Object\n        Mask array.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Output array.\n\n    Examples\n    --------\n    > var x = [ 1, 2, 3, 4 ];\n    > var y = amskfilter( x, [ 0, 1, 0, 1 ] )\n    [ 2, 4 ]\n\n    See Also\n    --------\n    amskreject\n","amskput":"\namskput( x, mask, values[, options] )\n    Replaces elements of an array with provided values according to a provided\n    mask array.\n\n    In broadcasting modes, the function supports broadcasting a values array\n    containing a single element against the number of falsy values in the mask\n    array.\n\n    In repeat mode, the function supports recycling elements in a values array\n    to satisfy the number of falsy values in the mask array.\n\n    The function mutates the input array.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    mask: ArrayLikeObject\n        Mask array. If a mask array element is falsy, the corresponding element\n        in `x` is *replaced*; otherwise, the corresponding element in `x` is\n        \"masked\" and thus left unchanged.\n\n    values: ArrayLikeObject\n        Values to set.\n\n    options: Object (optional)\n        Function options.\n\n    options.mode: string (optional)\n        String specifying behavior when the number of values to set does not\n        equal the number of falsy mask values. The function supports the\n        following modes:\n\n        - 'strict': specifies that the function must raise an exception when the\n        number of values does not *exactly* equal the number of falsy mask\n        values.\n        - 'non_strict': specifies that the function must raise an exception when\n        the function is provided insufficient values to satisfy the mask array.\n        - 'strict_broadcast': specifies that the function must broadcast a\n        single-element values array and otherwise raise an exception when the\n        number of values does not **exactly** equal the number of falsy mask\n        values.\n        - 'broadcast': specifies that the function must broadcast a single-\n        element values array and otherwise raise an exception when the function\n        is provided insufficient values to satisfy the mask array.\n        - 'repeat': specifies that the function must reuse provided values when\n        replacing elements in `x` in order to satisfy the mask array.\n\n        Default: 'repeat'.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Input array.\n\n    Examples\n    --------\n    > var x = [ 1, 2, 3, 4 ];\n    > var out = amskput( x, [ 1, 0, 1, 0 ], [ 20, 40 ] )\n    [ 1, 20, 3, 40 ]\n    > var bool = ( out === x )\n    true\n\n    See Also\n    --------\n    aplace, aput, atake\n","amskreject":"\namskreject( x, mask )\n    Returns a new array by applying a mask to a provided input array.\n\n    If a mask array element is falsy, the corresponding element in `x` is\n    included in the output array; otherwise, the corresponding element in `x` is\n    \"masked\" and thus excluded from the output array.\n\n    Parameters\n    ----------\n    x: Array|TypedArray|Object\n        Input array.\n\n    mask: Array|TypedArray|Object\n        Mask array.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Output array.\n\n    Examples\n    --------\n    > var x = [ 1, 2, 3, 4 ];\n    > var y = amskreject( x, [ 0, 1, 0, 1 ] )\n    [ 1, 3 ]\n\n    See Also\n    --------\n    amskfilter\n","anans":"\nanans( length[, dtype] )\n    Returns an array filled with NaNs and having a specified length.\n\n    The function supports the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754)\n    - float32: single-precision floating-point numbers (IEEE 754)\n    - complex128: double-precision complex floating-point numbers\n    - complex64: single-precision complex floating-point numbers\n    - generic: generic JavaScript values\n\n    The default array data type is `float64`.\n\n    Parameters\n    ----------\n    length: integer\n        Array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = anans( 2 )\n    <Float64Array>[ NaN, NaN ]\n    > arr = anans( 2, 'float32' )\n    <Float32Array>[ NaN, NaN ]\n\n    See Also\n    --------\n    afull, anansLike, aones, azeros\n","anansLike":"\nanansLike( x[, dtype] )\n    Returns an array filled with NaNs and having the same length and data type\n    as a provided input array.\n\n    The function supports the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754).\n    - float32: single-precision floating-point numbers (IEEE 754).\n    - complex128: double-precision complex floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - generic: generic JavaScript values.\n\n    Parameters\n    ----------\n    x: TypedArray|Array\n        Input array.\n\n    dtype: string (optional)\n        Data type. If not provided, the output array data type is inferred from\n        the input array.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var x = new Float64Array( 2 );\n    > var y = anansLike( x )\n    <Float64Array>[ NaN, NaN ]\n    > y = anansLike( x, 'float32' )\n    <Float32Array>[ NaN, NaN ]\n\n    See Also\n    --------\n    afullLike, anans, aonesLike, azerosLike\n","anova1":"\nanova1( x, factor[, options] )\n    Performs a one-way analysis of variance.\n\n    Parameters\n    ----------\n    x: Array<number>\n        Measured values.\n\n    factor: Array\n        Array of treatments.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.method: string\n        Name of test.\n\n    out.means: Object\n        Group means alongside sample sizes and standard errors.\n\n    out.treatment: Object\n        Treatment results.\n\n    out.treatment.df: number\n        Treatment degrees of freedom.\n\n    out.treatment.ss: number\n        Treatment sum of squares.\n\n    out.treatment.ms: number\n        Treatment mean sum of squares.\n\n    out.error: Object\n        Error results.\n\n    out.error.df: number\n        Error degrees of freedom.\n\n    out.error.ss: number\n        Error sum of squares.\n\n    out.error.ms: number\n        Error mean sum of squares.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    > var x = [1, 3, 5, 2, 4, 6, 8, 7, 10, 11, 12, 15];\n    > var f = [\n    ... 'control', 'treatA', 'treatB', 'treatC', 'control',\n    ... 'treatA', 'treatB', 'treatC', 'control', 'treatA', 'treatB', 'treatC'\n    ... ];\n    > var out = anova1( x, f )\n    {...}\n\n","ANSCOMBES_QUARTET":"\nANSCOMBES_QUARTET()\n    Returns Anscombe's quartet.\n\n    Anscombe's quartet is a set of 4 datasets which all have nearly identical\n    simple statistical properties but vary considerably when graphed. Anscombe\n    created the datasets to demonstrate why graphical data exploration should\n    precede statistical data analysis and to show the effect of outliers on\n    statistical properties.\n\n    Returns\n    -------\n    out: Array<Array>\n        Anscombe's quartet.\n\n    Examples\n    --------\n    > var d = ANSCOMBES_QUARTET()\n    [[[10,8.04],...],[[10,9.14],...],[[10,7.46],...],[[8,6.58],...]]\n\n    References\n    ----------\n    - Anscombe, Francis J. 1973. \"Graphs in Statistical Analysis.\" *The American\n    Statistician* 27 (1). [American Statistical Association, Taylor & Francis,\n    Ltd.]: 17–21. <http://www.jstor.org/stable/2682899>.\n\n","any":"\nany( collection )\n    Tests whether at least one element in a collection is truthy.\n\n    The function immediately returns upon encountering a truthy value.\n\n    If provided an empty collection, the function returns `false`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if an element is truthy; otherwise, the\n        function returns `false`.\n\n    Examples\n    --------\n    > var arr = [ 0, 0, 0, 0, 1 ];\n    > var bool = any( arr )\n    true\n\n    See Also\n    --------\n    anyBy, every, forEach, none, some\n","anyBy":"\nanyBy( collection, predicate[, thisArg ] )\n    Tests whether at least one element in a collection passes a test implemented\n    by a predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    The function immediately returns upon encountering a truthy return value.\n\n    If provided an empty collection, the function returns `false`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns `true` for\n        any element; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function negative( v ) { return ( v < 0 ); };\n    > var arr = [ 1, 2, 3, 4, -1 ];\n    > var bool = anyBy( arr, negative )\n    true\n\n    See Also\n    --------\n    anyByAsync, anyByRight, everyBy, forEach, noneBy, someBy\n","anyByAsync":"\nanyByAsync( collection, [options,] predicate, done )\n    Tests whether at least one element in a collection passes a test implemented\n    by a predicate function.\n\n    When invoked, the predicate function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If the\n    predicate function accepts two arguments, the predicate function is\n    provided:\n\n    - value\n    - next\n\n    If the predicate function accepts three arguments, the predicate function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other predicate function signature, the predicate function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - result: test result.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    The function immediately returns upon encountering a non-falsy `result`\n    value and calls the `done` callback with `null` as the first argument and\n    `true` as the second argument.\n\n    If all elements fail, the function calls the `done` callback with `null`\n    as the first argument and `false` as the second argument.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > anyByAsync( arr, predicate, done )\n    1000\n    2500\n    3000\n    false\n\n    // Limit number of concurrent invocations:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 3000, 2500, 1000 ];\n    > anyByAsync( arr, opts, predicate, done )\n    2500\n    3000\n    1000\n    false\n\n    // Process sequentially:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 3000, 2500, 1000 ];\n    > anyByAsync( arr, opts, predicate, done )\n    3000\n    2500\n    1000\n    false\n\n\nanyByAsync.factory( [options,] predicate )\n    Returns a function which tests whether at least one element in a collection\n    passes a test implemented by a predicate function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = anyByAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    false\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    false\n\n    See Also\n    --------\n    anyBy, anyByRightAsync, everyByAsync, forEachAsync, noneByAsync, someByAsync\n","anyByAsync.factory":"\nanyByAsync.factory( [options,] predicate )\n    Returns a function which tests whether at least one element in a collection\n    passes a test implemented by a predicate function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = anyByAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    false\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    false\n\n    See Also\n    --------\n    anyBy, anyByRightAsync, everyByAsync, forEachAsync, noneByAsync, someByAsync","anyByRight":"\nanyByRight( collection, predicate[, thisArg ] )\n    Tests whether at least one element in a collection passes a test implemented\n    by a predicate function, iterating from right to left.\n\n    The predicate function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    The function immediately returns upon encountering a truthy return value.\n\n    If provided an empty collection, the function returns `false`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns `true` for\n        any element; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function negative( v ) { return ( v < 0 ); };\n    > var arr = [ -1, 1, 2, 3, 4 ];\n    > var bool = anyByRight( arr, negative )\n    true\n\n    See Also\n    --------\n    anyBy, anyByRightAsync, everyByRight, forEachRight, noneByRight, someByRight\n","anyByRightAsync":"\nanyByRightAsync( collection, [options,] predicate, done )\n    Tests whether at least one element in a collection passes a test implemented\n    by a predicate function, iterating from right to left.\n\n    When invoked, the predicate function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If the\n    predicate function accepts two arguments, the predicate function is\n    provided:\n\n    - value\n    - next\n\n    If the predicate function accepts three arguments, the predicate function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other predicate function signature, the predicate function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - result: test result.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    The function immediately returns upon encountering a non-falsy `result`\n    value and calls the `done` callback with `null` as the first argument and\n    `true` as the second argument.\n\n    If all elements fail, the function calls the `done` callback with `null`\n    as the first argument and `false` as the second argument.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > anyByRightAsync( arr, predicate, done )\n    1000\n    2500\n    3000\n    false\n\n    // Limit number of concurrent invocations:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 1000, 2500, 3000 ];\n    > anyByRightAsync( arr, opts, predicate, done )\n    2500\n    3000\n    1000\n    false\n\n    // Process sequentially:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 1000, 2500, 3000 ];\n    > anyByRightAsync( arr, opts, predicate, done )\n    3000\n    2500\n    1000\n    false\n\n\nanyByRightAsync.factory( [options,] predicate )\n    Returns a function which tests whether at least one element in a collection\n    passes a test implemented by a predicate function, iterating from right to\n    left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = anyByRightAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    false\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    false\n\n    See Also\n    --------\n    anyByAsync, anyByRight, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByRightAsync\n","anyByRightAsync.factory":"\nanyByRightAsync.factory( [options,] predicate )\n    Returns a function which tests whether at least one element in a collection\n    passes a test implemented by a predicate function, iterating from right to\n    left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = anyByRightAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    false\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    false\n\n    See Also\n    --------\n    anyByAsync, anyByRight, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByRightAsync","anyInBy":"\nanyInBy( object, predicate[, thisArg ] )\n    Tests whether at least one value in an object passes a test implemented by\n    a predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: the value of the current property being processed in the object\n    - key: the key of the current property being processed in the object\n    - object: the input object\n\n    The function immediately returns upon encountering a truthy return value.\n\n    If provided an empty object, the function returns `false`.\n\n    Parameters\n    ----------\n    object: Object\n        Input object over which to iterate. It must be non-null.\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns `true` for\n        any value; otherwise, it returns `false`.\n\n    Examples\n    --------\n    > function isNegative(value) { return value < 0 }\n    > var obj = { a: 1, b: -2, c: 3, d: 4 }\n    > var result = anyInBy(obj, isNegative)\n    true\n\n    See Also\n    --------\n    anyBy, anyOwnBy, everyInBy, someInBy","anyOwnBy":"\nanyOwnBy( object, predicate[, thisArg ] )\n    Tests whether at least one own property of an object passes a\n    test implemented by a predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: property value.\n    - index: property key.\n    - object: the input object.\n\n    The function immediately returns upon encountering a truthy return\n    value.\n\n    If provided an empty object, the function returns `false`.\n\n    Parameters\n    ----------\n    object: Object\n        Input object.\n\n    predicate: Function\n        Test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns a truthy\n        value for one own property; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function positive( v ) { return ( v > 0 ); };\n    > var obj = { 'a': -1, 'b': 2, 'c': -3 };\n    > var bool = anyOwnBy( obj, positive )\n    true\n\n    See Also\n    --------\n    anyBy, anyInBy, everyOwnBy, someOwnBy\n","aones":"\naones( length[, dtype] )\n    Returns an array filled with ones and having a specified length.\n\n    The function supports the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754).\n    - float32: single-precision floating-point numbers (IEEE 754).\n    - complex128: double-precision complex floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n    - generic: generic JavaScript values.\n\n    The default array data type is `float64`.\n\n    Parameters\n    ----------\n    length: integer\n        Array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = aones( 2 )\n    <Float64Array>[ 1.0, 1.0 ]\n    > arr = aones( 2, 'float32' )\n    <Float32Array>[ 1.0, 1.0 ]\n\n    See Also\n    --------\n    afull, anans, aonesLike, azeros\n","aonesLike":"\naonesLike( x[, dtype] )\n    Returns an array filled with ones and having the same length and data type\n    as a provided input array.\n\n    The function supports the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754).\n    - float32: single-precision floating-point numbers (IEEE 754).\n    - complex128: double-precision complex floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n    - generic: generic JavaScript values.\n\n    Parameters\n    ----------\n    x: TypedArray|Array\n        Input array.\n\n    dtype: string (optional)\n        Data type. If not provided, the output array data type is inferred from\n        the input array.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var x = new Float64Array( 2 );\n    > var y = aonesLike( x )\n    <Float64Array>[ 1.0, 1.0 ]\n    > y = aonesLike( x, 'float32' )\n    <Float32Array>[ 1.0, 1.0 ]\n\n    See Also\n    --------\n    afullLike, anansLike, aones, azerosLike\n","aoneTo":"\naoneTo( n[, dtype] )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from one.\n\n    The function supports the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754).\n    - float32: single-precision floating-point numbers (IEEE 754).\n    - complex128: double-precision complex floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n    - generic: generic JavaScript values.\n\n    The default array data type is `float64`.\n\n    If `n` is equal to zero, the function returns an empty array.\n\n    Parameters\n    ----------\n    n: integer\n        Number of elements.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = aoneTo( 2 )\n    <Float64Array>[ 1.0, 2.0 ]\n    > arr = aoneTo( 2, 'float32' )\n    <Float32Array>[ 1.0, 2.0 ]\n\n    See Also\n    --------\n    afull, aones, aoneToLike, azeroTo\n","aoneToLike":"\naoneToLike( x[, dtype] )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from one and having the same length and data type as a provided\n    input array.\n\n    The function supports the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754).\n    - float32: single-precision floating-point numbers (IEEE 754).\n    - complex128: double-precision complex floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n    - generic: generic JavaScript values.\n\n    Parameters\n    ----------\n    x: TypedArray|Array\n        Input array.\n\n    dtype: string (optional)\n        Data type. If not provided, the output array data type is inferred from\n        the input array.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = aoneToLike( [ 0, 0 ] )\n    [ 1, 2 ]\n    > arr = aoneToLike( [ 0, 0 ], 'float32' )\n    <Float32Array>[ 1.0, 2.0 ]\n\n    See Also\n    --------\n    afullLike, aonesLike, aoneTo, azeroToLike\n","APERY":"\nAPERY\n    Apéry's constant.\n\n    Examples\n    --------\n    > APERY\n    1.2020569031595942\n\n","aplace":"\naplace( x, mask, values[, options] )\n    Replaces elements of an array with provided values according to a provided\n    mask array.\n\n    In broadcasting modes, the function supports broadcasting a values array\n    containing a single element against the number of truthy values in the mask\n    array.\n\n    In repeat mode, the function supports recycling elements in a values array\n    to satisfy the number of truthy values in the mask array.\n\n    The function mutates the input array.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    mask: ArrayLikeObject\n        Mask array. If a mask array element is truthy, the corresponding element\n        in `x` is *replaced*; otherwise, the corresponding element in `x` is\n        \"masked\" and thus left unchanged.\n\n    values: ArrayLikeObject\n        Values to set.\n\n    options: Object (optional)\n        Function options.\n\n    options.mode: string (optional)\n        String specifying behavior when the number of values to set does not\n        equal the number of truthy mask values. The function supports the\n        following modes:\n\n        - 'strict': specifies that the function must raise an exception when the\n        number of values does not *exactly* equal the number of truthy mask\n        values.\n        - 'non_strict': specifies that the function must raise an exception when\n        the function is provided insufficient values to satisfy the mask array.\n        - 'strict_broadcast': specifies that the function must broadcast a\n        single-element values array and otherwise raise an exception when the\n        number of values does not **exactly** equal the number of truthy mask\n        values.\n        - 'broadcast': specifies that the function must broadcast a single-\n        element values array and otherwise raise an exception when the function\n        is provided insufficient values to satisfy the mask array.\n        - 'repeat': specifies that the function must reuse provided values when\n        replacing elements in `x` in order to satisfy the mask array.\n\n        Default: 'repeat'.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Input array.\n\n    Examples\n    --------\n    > var x = [ 1, 2, 3, 4 ];\n    > var out = aplace( x, [ 0, 1, 0, 1 ], [ 20, 40 ] )\n    [ 1, 20, 3, 40 ]\n    > var bool = ( out === x )\n    true\n\n    See Also\n    --------\n    amskput, aput, atake\n","append":"\nappend( collection1, collection2 )\n    Adds the elements of one collection to the end of another collection.\n\n    If the input collection is a typed array, the output value does not equal\n    the input reference and the underlying `ArrayBuffer` may *not* be the same\n    as the `ArrayBuffer` belonging to the input view.\n\n    For purposes of generality, always treat the output collection as distinct\n    from the input collection.\n\n    Parameters\n    ----------\n    collection1: Array|TypedArray|Object\n        A collection. If the collection is an `Object`, the collection should be\n        array-like.\n\n    collection2: Array|TypedArray|Object\n        A collection containing the elements to add. If the collection is an\n        `Object`, the collection should be array-like.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Updated collection.\n\n    Examples\n    --------\n    // Arrays:\n    > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > arr = append( arr, [ 6.0, 7.0 ] )\n    [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]\n\n    // Typed arrays:\n    > arr = new Float64Array( [ 1.0, 2.0 ] );\n    > arr = append( arr, [ 3.0, 4.0 ] )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Array-like object:\n    > arr = { 'length': 0 };\n    > arr = append( arr, [ 1.0, 2.0 ] )\n    { 'length': 2, '0': 1.0, '1': 2.0 }\n\n    See Also\n    --------\n    prepend, push\n","aput":"\naput( x, indices, values[, options] )\n    Replaces specified elements of an array with provided values.\n\n    The function supports broadcasting a `values` array containing a single\n    element against an `indices` array containing one or more elements.\n\n    The function mutates the input array.\n\n    Because each index is only validated at the time of replacing a particular\n    element, mutation may occur even when one or more indices are out-of-bounds,\n    including when the index mode indicates to raise an exception.\n\n    If `indices` is an empty array, the function returns the input array\n    unchanged.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    indices: ArrayLikeObject<integer>\n        List of element indices.\n\n    values: ArrayLikeObject\n        Values to set. When `indices` contains one or more elements, `values`\n        must be broadcast compatible with `indices` (i.e., must have either one\n        element or the same number of elements as `indices`).\n\n    options: Object (optional)\n        Function options.\n\n    options.mode: string (optional)\n        Specifies how to handle an index outside the interval [0, max], where\n        `max` is the maximum possible array index. If equal to 'throw', the\n        function throws an error. If equal to 'normalize', the function throws\n        an error if provided an out-of-bounds normalized index. If equal to\n        'wrap', the function wraps around an index using modulo arithmetic. If\n        equal to 'clamp', the function sets an index to either 0 (minimum index)\n        or the maximum index. Default: 'normalize'.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Input array.\n\n    Examples\n    --------\n    > var x = [ 1, 2, 3, 4 ];\n    > var out = aput( x, [ 1, 3 ], [ 20, 40 ] )\n    [ 1, 20, 3, 40 ]\n    > var bool = ( out === x )\n    true\n\n    See Also\n    --------\n    amskput, aplace, atake\n","ARCH":"\nARCH\n    Operating system CPU architecture for which the JavaScript runtime binary\n    was compiled.\n\n    Current possible values:\n\n    - arm\n    - arm64\n    - ia32\n    - mips\n    - mipsel\n    - ppc\n    - ppc64\n    - s390\n    - s390x\n    - x32\n    - x64\n\n    Examples\n    --------\n    > ARCH\n    <string>\n\n    See Also\n    --------\n    PLATFORM\n","argumentFunction":"\nargumentFunction( idx )\n    Returns a function which always returns a specified argument.\n\n    The input argument corresponds to the zero-based index of the argument to\n    return.\n\n    Parameters\n    ----------\n    idx: integer\n        Argument index to return (zero-based).\n\n    Returns\n    -------\n    out: Function\n        Argument function.\n\n    Examples\n    --------\n    > var argn = argumentFunction( 1 );\n    > var v = argn( 3.14, -3.14, 0.0 )\n    -3.14\n    > v = argn( -1.0, -0.0, 1.0 )\n    -0.0\n    > v = argn( 'beep', 'boop', 'bop' )\n    'boop'\n    > v = argn( 'beep' )\n    undefined\n\n    See Also\n    --------\n    constantFunction, identity\n","ARGV":"\nARGV\n    An array containing command-line arguments passed when launching the calling\n    process.\n\n    The first element is the absolute pathname of the executable that started\n    the calling process.\n\n    The second element is the path of the executed file.\n\n    Any additional elements are additional command-line arguments.\n\n    In browser environments, the array is empty.\n\n    Examples\n    --------\n    > var execPath = ARGV[ 0 ]\n    e.g., /usr/local/bin/node\n\n    See Also\n    --------\n    ENV\n","array":"\narray( [buffer,] [options] )\n    Returns a multidimensional array.\n\n    Parameters\n    ----------\n    buffer: Array|TypedArray|Buffer|ndarray (optional)\n        Data source.\n\n    options: Object (optional)\n        Options.\n\n    options.buffer: Array|TypedArray|Buffer|ndarray (optional)\n        Data source. If provided along with a `buffer` argument, the argument\n        takes precedence.\n\n    options.dtype: string (optional)\n        Underlying storage data type. If not specified and a data source is\n        provided, the data type is inferred from the provided data source. If an\n        input data source is not of the same type, this option specifies the\n        data type to which to cast the input data. For non-ndarray generic array\n        data sources, the function casts generic array data elements to the\n        default data type. In order to prevent this cast, the `dtype` option\n        must be explicitly set to `'generic'`. Any time a cast is required, the\n        `copy` option is set to `true`, as memory must be copied from the data\n        source to an output data buffer. Default: 'float64'.\n\n    options.order: string (optional)\n        Specifies the memory layout of the data source as either row-major (C-\n        style) or column-major (Fortran-style). The option may be one of the\n        following values:\n\n        - 'row-major': the order of the returned array is row-major.\n        - 'column-major': the order of the returned array is column-major.\n        - 'any': if a data source is column-major and not row-major, the order\n          of the returned array is column-major; otherwise, the order of the\n          returned array is row-major.\n        - 'same': the order of the returned array matches the order of an input\n          data source.\n\n        Note that specifying an order which differs from the order of a\n        provided data source does *not* entail a conversion from one memory\n        layout to another. In short, this option is descriptive, not\n        prescriptive. Default: 'row-major'.\n\n    options.shape: Array<integer> (optional)\n        Array shape (dimensions). If a shape is not specified, the function\n        attempts to infer a shape based on a provided data source. For example,\n        if provided a nested array, the function resolves nested array\n        dimensions. If provided a multidimensional array data source, the\n        function uses the array's associated shape. For most use cases, such\n        inference suffices. For the remaining use cases, specifying a shape is\n        necessary. For example, provide a shape to create a multidimensional\n        array view over a linear data buffer, ignoring any existing shape meta\n        data associated with a provided data source.\n\n    options.flatten: boolean (optional)\n        Boolean indicating whether to automatically flatten generic array data\n        sources. If an array shape is not specified, the shape is inferred from\n        the dimensions of nested arrays prior to flattening. If a use case\n        requires partial flattening, partially flatten prior to invoking this\n        function and set the option value to `false` to prevent further\n        flattening during invocation. Default: true.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to (shallow) copy source data to a new data\n        buffer. The function does *not* perform a deep copy. To prevent\n        undesired shared changes in state for generic arrays containing objects,\n        perform a deep copy prior to invoking this function. Default: false.\n\n    options.ndmin: integer (optional)\n        Specifies the minimum number of dimensions. If an array shape has fewer\n        dimensions than required by `ndmin`, the function prepends singleton\n        dimensions to the array shape in order to satisfy the dimensions\n        requirement. Default: 0.\n\n    options.casting: string (optional)\n        Specifies the casting rule used to determine acceptable casts. The\n        option may be one of the following values:\n\n        - 'none': only allow casting between identical types.\n        - 'equiv': allow casting between identical and byte swapped types.\n        - 'safe': only allow \"safe\" casts.\n        - 'mostly-safe': allow \"safe casts\" and, for floating-point data types,\n          downcasts.\n        - 'same-kind': allow \"safe\" casts and casts within the same kind (e.g.,\n          between signed integers or between floats).\n        - 'unsafe': allow casting between all types (including between integers\n          and floats).\n\n        Default: 'safe'.\n\n    options.codegen: boolean (optional)\n        Boolean indicating whether to use code generation. Code generation can\n        boost performance, but may be problematic in browser contexts enforcing\n        a strict content security policy (CSP). Default: true.\n\n    options.mode: string (optional)\n        Specifies how to handle indices which exceed array dimensions. The\n        option may be one of the following values:\n\n        - 'throw': an ndarray instance throws an error when an index exceeds\n          array dimensions.\n        - 'normalize': an ndarray instance normalizes negative indices and\n          throws an error when an index exceeds array dimensions.\n        - 'wrap': an ndarray instance wraps around indices exceeding array\n          dimensions using modulo arithmetic.\n        - 'clamp', an ndarray instance sets an index exceeding array dimensions\n          to either `0` (minimum index) or the maximum index.\n\n        Default: 'throw'.\n\n    options.submode: Array<string> (optional)\n        Specifies how to handle subscripts which exceed array dimensions. If a\n        mode for a corresponding dimension is equal to\n\n        - 'throw': an ndarray instance throws an error when a subscript exceeds\n          array dimensions.\n        - 'normalize': an ndarray instance normalizes negative subscripts and\n          throws an error when a subscript exceeds array dimensions.\n        - 'wrap': an ndarray instance wraps around subscripts exceeding array\n          dimensions using modulo arithmetic.\n        - 'clamp': an ndarray instance sets a subscript exceeding array\n          dimensions to either `0` (minimum index) or the maximum index.\n\n        If the number of modes is fewer than the number of dimensions, the\n        function recycles modes using modulo arithmetic.\n\n        Default: [ options.mode ].\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether an array should be read-only. Default: false.\n\n    Returns\n    -------\n    out: ndarray\n        Multidimensional array.\n\n    Examples\n    --------\n    // Create a 2x2 matrix:\n    > var arr = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] )\n    <ndarray>\n\n    // Get an element using subscripts:\n    > var v = arr.get( 1, 1 )\n    4.0\n\n    // Get an element using a linear index:\n    > v = arr.iget( 3 )\n    4.0\n\n    // Set an element using subscripts:\n    > arr.set( 1, 1, 40.0 );\n    > arr.get( 1, 1 )\n    40.0\n\n    // Set an element using a linear index:\n    > arr.iset( 3, 99.0 );\n    > arr.get( 1, 1 )\n    99.0\n\n    See Also\n    --------\n    ndarray\n","array2buffer":"\narray2buffer( arr )\n    Allocates a buffer using an octet array.\n\n    Parameters\n    ----------\n    arr: Array<integer>\n        Array (or array-like object) of octets from which to copy.\n\n    Returns\n    -------\n    out: Buffer\n        Buffer instance.\n\n    Examples\n    --------\n    > var buf = array2buffer( [ 1, 2, 3, 4 ] )\n    <Buffer>[ 1, 2, 3, 4 ]\n\n    See Also\n    --------\n    Buffer, arraybuffer2buffer, copyBuffer, string2buffer\n","array2fancy":"\narray2fancy( x[, options] )\n    Converts an array to an object supporting fancy indexing.\n\n    An array supporting fancy indexing is an array which supports slicing via\n    indexing expressions for both retrieval and assignment.\n\n    A fancy array shares the *same* data as the provided input array. Hence, any\n    mutations to the returned array will affect the underlying input array and\n    vice versa.\n\n    For operations returning a new array (e.g., when slicing or invoking an\n    instance method), a fancy array returns a new fancy array having the same\n    configuration as specified by provided options.\n\n    A fancy array supports indexing using positive and negative integers (both\n    numeric literals and strings), Slice instances, subsequence expressions,\n    mask arrays, boolean arrays, and integer arrays.\n\n    A fancy array supports all properties and methods of the input array, and,\n    thus, a fancy array can be consumed by any API which supports array-like\n    objects.\n\n    Indexing expressions provide a convenient and powerful means for creating\n    and operating on array views; however, their use does entail a performance\n    cost. Indexing expressions are best suited for interactive use (e.g., in the\n    REPL) and scripting. For performance critical applications, prefer\n    equivalent functional APIs supporting array-like objects.\n\n    Fancy arrays support broadcasting in which assigned scalars and single-\n    element arrays are repeated (without additional memory allocation) to match\n    the length of a target array instance.\n\n    Fancy array broadcasting follows the same rules as for ndarrays.\n\n    Consequently, when assigning arrays to slices, the array on the right-hand-\n    side must be broadcast-compatible with number of elements in the slice.\n\n    Fancy arrays support (mostly) safe casts (i.e., any cast which can be\n    performed without overflow or loss of precision, with the exception of\n    floating-point arrays which are also allowed to downcast from higher\n    precision to lower precision).\n\n    When attempting to perform an unsafe cast, fancy arrays will raise an\n    exception.\n\n    When assigning a real-valued scalar to a complex number array (e.g.,\n    Complex128Array or Complex64Array), a fancy array will cast the real-valued\n    scalar to a complex number argument having an imaginary component equal to\n    zero.\n\n    In older JavaScript environments which do not support Proxy objects, the use\n    of indexing expressions is not supported.\n\n    Parameters\n    ----------\n    x: Array|TypedArray|Object\n        Input array.\n\n    options: Object (optional)\n        Function options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking. Default:\n        false.\n\n    options.cache: Object (optional)\n        Cache for resolving array index objects. Must have a 'get' method which\n        accepts a single argument: a string identifier associated with an array\n        index. If an array index associated with a provided identifier exists,\n        the 'get' method should return an object having the following\n        properties:\n\n        - data: the underlying index array.\n        - type: the index type. Must be either 'mask', 'bool', or 'int'.\n        - dtype: the data type of the underlying array.\n\n        If an array index is not associated with a provided identifier, the\n        'get' method should return `null`.\n\n        Default: `ArrayIndex`.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Output array supporting fancy indexing.\n\n    Examples\n    --------\n    > var y = array2fancy( [ 1, 2, 3, 4 ] );\n    > y[ '1::2' ]\n    [ 2, 4 ]\n    > y[ '::-1' ]\n    [ 4, 3, 2, 1 ]\n\n\narray2fancy.factory( [options] )\n    Returns a function for converting an array to an object supporting fancy\n    indexing.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking by default.\n        Default: false.\n\n    options.cache: Object (optional)\n        Cache for resolving array index objects. Must have a 'get' method which\n        accepts a single argument: a string identifier associated with an array\n        index. If an array index associated with a provided identifier exists,\n        the 'get' method should return an object having the following\n        properties:\n\n        - data: the underlying index array.\n        - type: the index type. Must be either 'mask', 'bool', or 'int'.\n        - dtype: the data type of the underlying array.\n\n        If an array index is not associated with a provided identifier, the\n        'get' method should return `null`.\n\n        Default: `ArrayIndex`.\n\n    Returns\n    -------\n    fcn: Function\n        Function for converting an array to an object supporting fancy indexing.\n\n    Examples\n    --------\n    > var f = array2fancy.factory();\n    > var y = f( [ 1, 2, 3, 4 ] );\n    > y[ '1::2' ]\n    [ 2, 4 ]\n    > y[ '::-1' ]\n    [ 4, 3, 2, 1 ]\n\n\narray2fancy.idx( x[, options] )\n    Wraps a provided array as an array index object.\n\n    For documentation and usage, see `ArrayIndex`.\n\n    Parameters\n    ----------\n    x: Array|TypedArray|Object\n        Input array.\n\n    options: Object (optional)\n        Function options.\n\n    options.persist: boolean (optional)\n        Boolean indicating whether to continue persisting an index object after\n        first usage. Default: false.\n\n    Returns\n    -------\n    out: ArrayIndex\n        ArrayIndex instance.\n\n    Examples\n    --------\n    > var idx = array2fancy.idx( [ 1, 2, 3, 4 ] );\n\n    See Also\n    --------\n    aslice, FancyArray\n","array2fancy.factory":"\narray2fancy.factory( [options] )\n    Returns a function for converting an array to an object supporting fancy\n    indexing.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking by default.\n        Default: false.\n\n    options.cache: Object (optional)\n        Cache for resolving array index objects. Must have a 'get' method which\n        accepts a single argument: a string identifier associated with an array\n        index. If an array index associated with a provided identifier exists,\n        the 'get' method should return an object having the following\n        properties:\n\n        - data: the underlying index array.\n        - type: the index type. Must be either 'mask', 'bool', or 'int'.\n        - dtype: the data type of the underlying array.\n\n        If an array index is not associated with a provided identifier, the\n        'get' method should return `null`.\n\n        Default: `ArrayIndex`.\n\n    Returns\n    -------\n    fcn: Function\n        Function for converting an array to an object supporting fancy indexing.\n\n    Examples\n    --------\n    > var f = array2fancy.factory();\n    > var y = f( [ 1, 2, 3, 4 ] );\n    > y[ '1::2' ]\n    [ 2, 4 ]\n    > y[ '::-1' ]\n    [ 4, 3, 2, 1 ]","array2fancy.idx":"\narray2fancy.idx( x[, options] )\n    Wraps a provided array as an array index object.\n\n    For documentation and usage, see `ArrayIndex`.\n\n    Parameters\n    ----------\n    x: Array|TypedArray|Object\n        Input array.\n\n    options: Object (optional)\n        Function options.\n\n    options.persist: boolean (optional)\n        Boolean indicating whether to continue persisting an index object after\n        first usage. Default: false.\n\n    Returns\n    -------\n    out: ArrayIndex\n        ArrayIndex instance.\n\n    Examples\n    --------\n    > var idx = array2fancy.idx( [ 1, 2, 3, 4 ] );\n\n    See Also\n    --------\n    aslice, FancyArray","array2iterator":"\narray2iterator( src[, mapFcn[, thisArg]] )\n    Returns an iterator which iterates over the elements of an array-like\n    object.\n\n    When invoked, an input function is provided three arguments:\n\n    - value: iterated value.\n    - index: iterated value index.\n    - src: source array-like object.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an array's `@@iterator` method, regardless of whether this method is\n    defined. To convert an array to an implementation defined iterator, invoke\n    this method directly.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Array-like object from which to create the iterator.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = array2iterator( [ 1, 2, 3, 4 ] );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    iterator2array, circarray2iterator, array2iteratorRight, stridedarray2iterator\n","array2iteratorRight":"\narray2iteratorRight( src[, mapFcn[, thisArg]] )\n    Returns an iterator which iterates from right to left over the elements of\n    an array-like object.\n\n    When invoked, an input function is provided three arguments:\n\n    - value: iterated value.\n    - index: iterated value index.\n    - src: source array-like object.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an array's `@@iterator` method, regardless of whether this method is\n    defined. To convert an array to an implementation defined iterator, invoke\n    this method directly.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Array-like object from which to create the iterator.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = array2iteratorRight( [ 1, 2, 3, 4 ] );\n    > var v = it.next().value\n    4\n    > v = it.next().value\n    3\n\n    See Also\n    --------\n    iterator2array, array2iterator\n","ArrayBuffer":"\nArrayBuffer( size )\n    Returns an array buffer having a specified number of bytes.\n\n    Buffer contents are initialized to 0.\n\n    Parameters\n    ----------\n    size: integer\n        Number of bytes.\n\n    Returns\n    -------\n    out: ArrayBuffer\n        An array buffer.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 5 )\n    <ArrayBuffer>\n\n\nArrayBuffer.length\n    Number of input arguments the constructor accepts.\n\n    Examples\n    --------\n    > ArrayBuffer.length\n    1\n\n\nArrayBuffer.isView( arr )\n    Returns a boolean indicating if provided an array buffer view.\n\n    Parameters\n    ----------\n    arr: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an input argument is a buffer view.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 10 );\n    > ArrayBuffer.isView( arr )\n    true\n\n\nArrayBuffer.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the array buffer.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 5 );\n    > buf.byteLength\n    5\n\n\nArrayBuffer.prototype.slice( [start[, end]] )\n    Copies the bytes of an array buffer to a new array buffer.\n\n    Parameters\n    ----------\n    start: integer (optional)\n        Index at which to start copying buffer contents (inclusive). If\n        negative, the index is relative to the end of the buffer.\n\n    end: integer (optional)\n        Index at which to stop copying buffer contents (exclusive). If negative,\n        the index is relative to the end of the buffer.\n\n    Returns\n    -------\n    out: ArrayBuffer\n        A new array buffer whose contents have been copied from the calling\n        array buffer.\n\n    Examples\n    --------\n    > var b1 = new ArrayBuffer( 10 );\n    > var b2 = b1.slice( 2, 6 );\n    > var bool = ( b1 === b2 )\n    false\n    > b2.byteLength\n    4\n\n    See Also\n    --------\n    Buffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, SharedArrayBuffer, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","ArrayBuffer.length":"\nArrayBuffer.length\n    Number of input arguments the constructor accepts.\n\n    Examples\n    --------\n    > ArrayBuffer.length\n    1","ArrayBuffer.isView":"\nArrayBuffer.isView( arr )\n    Returns a boolean indicating if provided an array buffer view.\n\n    Parameters\n    ----------\n    arr: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an input argument is a buffer view.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 10 );\n    > ArrayBuffer.isView( arr )\n    true","ArrayBuffer.prototype.byteLength":"\nArrayBuffer.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the array buffer.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 5 );\n    > buf.byteLength\n    5","ArrayBuffer.prototype.slice":"\nArrayBuffer.prototype.slice( [start[, end]] )\n    Copies the bytes of an array buffer to a new array buffer.\n\n    Parameters\n    ----------\n    start: integer (optional)\n        Index at which to start copying buffer contents (inclusive). If\n        negative, the index is relative to the end of the buffer.\n\n    end: integer (optional)\n        Index at which to stop copying buffer contents (exclusive). If negative,\n        the index is relative to the end of the buffer.\n\n    Returns\n    -------\n    out: ArrayBuffer\n        A new array buffer whose contents have been copied from the calling\n        array buffer.\n\n    Examples\n    --------\n    > var b1 = new ArrayBuffer( 10 );\n    > var b2 = b1.slice( 2, 6 );\n    > var bool = ( b1 === b2 )\n    false\n    > b2.byteLength\n    4\n\n    See Also\n    --------\n    Buffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, SharedArrayBuffer, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","arraybuffer2buffer":"\narraybuffer2buffer( buf[, byteOffset[, length]] )\n    Allocates a buffer from an ArrayBuffer.\n\n    The behavior of this function varies across Node.js versions due to changes\n    in the underlying Node.js APIs:\n\n    - <3.0.0: the function copies ArrayBuffer bytes to a new Buffer instance.\n    - >=3.0.0 and <5.10.0: if provided a byte offset, the function copies\n      ArrayBuffer bytes to a new Buffer instance; otherwise, the function\n      returns a view of an ArrayBuffer without copying the underlying memory.\n    - <6.0.0: if provided an empty ArrayBuffer, the function returns an empty\n      Buffer which is not an ArrayBuffer view.\n    - >=6.0.0: the function returns a view of an ArrayBuffer without copying\n      the underlying memory.\n\n    Parameters\n    ----------\n    buf: ArrayBuffer\n        Input array buffer.\n\n    byteOffset: integer (optional)\n        Index offset specifying the location of the first byte.\n\n    length: integer (optional)\n        Number of bytes to expose from the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Buffer\n        Buffer instance.\n\n    Examples\n    --------\n    > var ab = new ArrayBuffer( 10 )\n    <ArrayBuffer>\n    > var buf = arraybuffer2buffer( ab )\n    <Buffer>\n    > var len = buf.length\n    10\n    > buf = arraybuffer2buffer( ab, 2, 6 )\n    <Buffer>\n    > len = buf.length\n    6\n\n    See Also\n    --------\n    Buffer, array2buffer, copyBuffer, string2buffer\n","arrayCtors":"\narrayCtors( dtype )\n    Returns an array constructor.\n\n    The function returns constructors for the following data types:\n\n    - float32: single-precision floating-point numbers.\n    - float64: double-precision floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - complex128: double-precision complex floating-point numbers.\n    - bool: boolean values.\n    - generic: values of any type.\n    - int16: signed 16-bit integers.\n    - int32: signed 32-bit integers.\n    - int8: signed 8-bit integers.\n    - uint16: unsigned 16-bit integers.\n    - uint32: unsigned 32-bit integers.\n    - uint8: unsigned 8-bit integers.\n    - uint8c: unsigned clamped 8-bit integers.\n\n    Parameters\n    ----------\n    dtype: string\n        Data type.\n\n    Returns\n    -------\n    out: Function|null\n        Constructor.\n\n    Examples\n    --------\n    > var ctor = arrayCtors( 'float64' )\n    <Function>\n    > ctor = arrayCtors( 'float' )\n    null\n\n    See Also\n    --------\n    typedarrayCtors\n","arrayDataType":"\narrayDataType( array )\n    Returns the data type of an array.\n\n    If provided an argument having an unknown or unsupported type, the function\n    returns `null`.\n\n    Parameters\n    ----------\n    array: any\n        Input value.\n\n    Returns\n    -------\n    out: string|null\n        Data type.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 10 );\n    > var dt = arrayDataType( arr )\n    'float64'\n    > dt = arrayDataType( 'beep' )\n    null\n\n    See Also\n    --------\n    arrayDataTypes\n","arrayDataTypes":"\narrayDataTypes( [kind] )\n    Returns a list of array data types.\n\n    When not provided a data type \"kind\", the function returns an array\n    containing the following data types:\n\n    - float32: single-precision floating-point numbers.\n    - float64: double-precision floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - complex128: double-precision complex floating-point numbers.\n    - bool: boolean values.\n    - generic: values of any type.\n    - int16: signed 16-bit integers.\n    - int32: signed 32-bit integers.\n    - int8: signed 8-bit integers.\n    - uint16: unsigned 16-bit integers.\n    - uint32: unsigned 32-bit integers.\n    - uint8: unsigned 8-bit integers.\n    - uint8c: unsigned clamped 8-bit integers.\n\n    The function supports the following data type \"kinds\":\n\n    - floating_point: floating-point data types.\n    - real_floating_point: real-valued floating-point data types.\n    - complex_floating_point: complex-valued floating-point data types.\n    - boolean: boolean data types.\n    - integer: integer data types.\n    - signed_integer: signed integer data types.\n    - unsigned_integer: unsigned integer data types.\n    - real: real-valued data types.\n    - numeric: numeric data types.\n    - typed: \"typed\" data types.\n    - all: all data types.\n\n    Additionally, the function supports extending the \"kinds\" listed above by\n    appending a '_and_generic' suffix to the kind name (e.g., real_and_generic).\n\n    Parameters\n    ----------\n    kind: string (optional)\n        Data type kind.\n\n    Returns\n    -------\n    out: Array<string>\n        List of array data types.\n\n    Examples\n    --------\n    > var out = arrayDataTypes()\n    [...]\n    > out = arrayDataTypes( 'floating_point' )\n    [...]\n    > out = arrayDataTypes( 'floating_point_and_generic' )\n    [...]\n\n    See Also\n    --------\n    typedarrayDataTypes, ndarrayDataTypes\n","ArrayIndex":"\nArrayIndex( x[, options] )\n    Wraps a provided array as an array index object.\n\n    Array index instances have no explicit functionality; however, they are used\n    by \"fancy\" arrays for element retrieval and assignment.\n\n    By default, an instance is invalidated and removed from an internal cache\n    immediately after a consumer resolves the underlying data associated with an\n    instance using the `get` static method. Immediate invalidation and cache\n    removal ensures that references to the underlying array are not the source\n    of memory leaks.\n\n    Because instances leverage an internal cache implementing the Singleton\n    pattern, one must be sure to use the same constructor as consumers. If one\n    uses a different constructor, the consumer will *not* be able to resolve the\n    original wrapped array, as the consumer will attempt to resolve an instance\n    in the wrong internal cache.\n\n    Because non-persisted instances are freed after first use, in order to avoid\n    holding onto memory and to allow garbage collection, one should avoid\n    scenarios in which an instance is never used.\n\n    Parameters\n    ----------\n    x: Array|TypedArray|Object\n        Input array.\n\n    options: Object (optional)\n        Function options.\n\n    options.persist: boolean (optional)\n        Boolean indicating whether to continue persisting an index object after\n        first usage. Default: false.\n\n    Returns\n    -------\n    out: ArrayIndex\n        ArrayIndex instance.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n\n\nArrayIndex.free( id )\n    Frees the instance associated with a provided identifier.\n\n    Parameters\n    ----------\n    id: string\n        Instance identifier.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an instance was successfully freed.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > ArrayIndex.free( idx.id )\n    <boolean>\n\n\nArrayIndex.get( id )\n    Returns the array associated with the instance having a provided identifier.\n\n    Parameters\n    ----------\n    id: string\n        Instance identifier.\n\n    Returns\n    -------\n    out: Object\n        Object containing array data.\n\n    out.data: Array|TypedArray|Object\n        The underlying array associated with the provided identifier.\n\n    out.type: string\n        The type of array index.\n\n    out.dtype: string\n        The data type of the underlying array.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > ArrayIndex.get( idx.id )\n    {...}\n\n\nArrayIndex.prototype.data\n    Read-only property returning the underlying index array.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Array data.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.data\n    [ 1, 2, 3, 4 ]\n\n\nArrayIndex.prototype.dtype\n    Read-only property returning the underlying data type of the index array.\n\n    Returns\n    -------\n    out: string\n        Array data type.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.dtype\n    'generic'\n\n\nArrayIndex.prototype.id\n    Read-only property returning the unique identifier associated with an\n    instance.\n\n    Returns\n    -------\n    out: string\n        String identifier.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.id\n    <string>\n\n\nArrayIndex.prototype.isCached\n    Read-only property returning a boolean indicating whether an array index is\n    actively cached.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an array index is actively cached.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.isCached\n    true\n\n\nArrayIndex.prototype.type\n    Read-only property returning the array index type.\n\n    Returns\n    -------\n    out: string\n        Array index type.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.type\n    <string>\n\n\nArrayIndex.prototype.toString()\n    Serializes an instance as a string.\n\n    Returns\n    -------\n    str: string\n        Serialized string.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.toString()\n    <string>\n\n\nArrayIndex.prototype.toJSON()\n    Serializes an instance as a JSON object.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.toJSON()\n    { 'type': 'ArrayIndex', 'data': [ 1, 2, 3, 4 ] }\n\n    See Also\n    --------\n    array2fancy\n","ArrayIndex.free":"\nArrayIndex.free( id )\n    Frees the instance associated with a provided identifier.\n\n    Parameters\n    ----------\n    id: string\n        Instance identifier.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an instance was successfully freed.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > ArrayIndex.free( idx.id )\n    <boolean>","ArrayIndex.get":"\nArrayIndex.get( id )\n    Returns the array associated with the instance having a provided identifier.\n\n    Parameters\n    ----------\n    id: string\n        Instance identifier.\n\n    Returns\n    -------\n    out: Object\n        Object containing array data.\n\n    out.data: Array|TypedArray|Object\n        The underlying array associated with the provided identifier.\n\n    out.type: string\n        The type of array index.\n\n    out.dtype: string\n        The data type of the underlying array.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > ArrayIndex.get( idx.id )\n    {...}","ArrayIndex.prototype.data":"\nArrayIndex.prototype.data\n    Read-only property returning the underlying index array.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Array data.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.data\n    [ 1, 2, 3, 4 ]","ArrayIndex.prototype.dtype":"\nArrayIndex.prototype.dtype\n    Read-only property returning the underlying data type of the index array.\n\n    Returns\n    -------\n    out: string\n        Array data type.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.dtype\n    'generic'","ArrayIndex.prototype.id":"\nArrayIndex.prototype.id\n    Read-only property returning the unique identifier associated with an\n    instance.\n\n    Returns\n    -------\n    out: string\n        String identifier.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.id\n    <string>","ArrayIndex.prototype.isCached":"\nArrayIndex.prototype.isCached\n    Read-only property returning a boolean indicating whether an array index is\n    actively cached.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an array index is actively cached.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.isCached\n    true","ArrayIndex.prototype.type":"\nArrayIndex.prototype.type\n    Read-only property returning the array index type.\n\n    Returns\n    -------\n    out: string\n        Array index type.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.type\n    <string>","ArrayIndex.prototype.toString":"\nArrayIndex.prototype.toString()\n    Serializes an instance as a string.\n\n    Returns\n    -------\n    str: string\n        Serialized string.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.toString()\n    <string>","ArrayIndex.prototype.toJSON":"\nArrayIndex.prototype.toJSON()\n    Serializes an instance as a JSON object.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.toJSON()\n    { 'type': 'ArrayIndex', 'data': [ 1, 2, 3, 4 ] }\n\n    See Also\n    --------\n    array2fancy","arrayMinDataType":"\narrayMinDataType( value )\n    Returns the minimum array data type of the closest \"kind\" necessary for\n    storing a provided scalar value.\n\n    The function does *not* provide precision guarantees for non-integer-valued\n    numbers. In other words, the function returns the smallest possible\n    floating-point (i.e., inexact) data type for storing numbers having\n    decimals.\n\n    Parameters\n    ----------\n    value: any\n        Scalar value.\n\n    Returns\n    -------\n    dt: string\n        Array data type.\n\n    Examples\n    --------\n    > var dt = arrayMinDataType( 3.141592653589793 )\n    'float32'\n    > dt = arrayMinDataType( 3 )\n    'uint8'\n    > dt = arrayMinDataType( -3 )\n    'int8'\n    > dt = arrayMinDataType( '-3' )\n    'generic'\n\n    See Also\n    --------\n    arrayDataTypes, arrayPromotionRules, arraySafeCasts\n","arrayMostlySafeCasts":"\narrayMostlySafeCasts( [dtype] )\n    Returns a list of array data types to which a provided array data type can\n    be safely cast and, for floating-point data types, can be downcast.\n\n    If not provided an array data type, the function returns a casting table.\n\n    If provided an unrecognized array data type, the function returns `null`.\n\n    Parameters\n    ----------\n    dtype: any (optional)\n        Array data type value.\n\n    Returns\n    -------\n    out: Object|Array<string>|null\n        Array data types to which a data type can be cast.\n\n    Examples\n    --------\n    > var out = arrayMostlySafeCasts( 'float32' )\n    <Array>\n\n    See Also\n    --------\n    convertArray, convertArraySame, arrayDataTypes, arraySafeCasts, arraySameKindCasts, ndarrayMostlySafeCasts\n","arrayNextDataType":"\narrayNextDataType( [dtype] )\n    Returns the next larger array data type of the same kind.\n\n    If not provided a data type, the function returns a table.\n\n    If a data type does not have a next larger data type or the next larger type\n    is not supported, the function returns `-1`.\n\n    If provided an unrecognized data type, the function returns `null`.\n\n    Parameters\n    ----------\n    dtype: string (optional)\n        Array data type.\n\n    Returns\n    -------\n    out: Object|string|integer|null\n        Next larger type(s).\n\n    Examples\n    --------\n    > var out = arrayNextDataType( 'float32' )\n    'float64'\n\n    See Also\n    --------\n    arrayDataType, arrayDataTypes\n","arrayPromotionRules":"\narrayPromotionRules( [dtype1, dtype2] )\n    Returns the array data type with the smallest size and closest \"kind\" to\n    which array data types can be safely cast.\n\n    If not provided data types, the function returns a type promotion table.\n\n    If a data type to which data types can be safely cast does *not* exist (or\n    is not supported), the function returns `-1`.\n\n    If provided an unrecognized data type, the function returns `null`.\n\n    Parameters\n    ----------\n    dtype1: any (optional)\n        Array data type.\n\n    dtype2: any (optional)\n        Array data type.\n\n    Returns\n    -------\n    out: Object|string|integer|null\n        Promotion rule(s).\n\n    Examples\n    --------\n    > var out = arrayPromotionRules( 'float32', 'int32' )\n    'float64'\n\n    See Also\n    --------\n    arrayDataTypes, arraySafeCasts, ndarrayPromotionRules\n","arraySafeCasts":"\narraySafeCasts( [dtype] )\n    Returns a list of array data types to which a provided array data type can\n    be safely cast.\n\n    If not provided an array data type, the function returns a casting table.\n\n    If provided an unrecognized array data type, the function returns `null`.\n\n    Parameters\n    ----------\n    dtype: any (optional)\n        Array data type.\n\n    Returns\n    -------\n    out: Object|Array<string>|null\n        Array data types to which a data type can be safely cast.\n\n    Examples\n    --------\n    > var out = arraySafeCasts( 'float32' )\n    <Array>\n\n    See Also\n    --------\n    convertArray, convertArraySame, arrayDataTypes, arrayMostlySafeCasts, arraySameKindCasts, ndarraySafeCasts\n","arraySameKindCasts":"\narraySameKindCasts( [dtype] )\n    Returns a list of array data types to which a provided array data type can\n    be safely cast or cast within the same \"kind\".\n\n    If not provided an array data type, the function returns a casting table.\n\n    If provided an unrecognized array data type, the function returns `null`.\n\n    Parameters\n    ----------\n    dtype: any (optional)\n        Array data type.\n\n    Returns\n    -------\n    out: Object|Array<string>|null\n        Array data types to which a data type can be safely cast or cast within\n        the same \"kind\".\n\n    Examples\n    --------\n    > var out = arraySameKindCasts( 'float32' )\n    <Array>\n\n    See Also\n    --------\n    convertArray, convertArraySame, arrayDataTypes, arraySafeCasts, ndarraySameKindCasts\n","arrayShape":"\narrayShape( arr )\n    Determines array dimensions.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject\n        Input array.\n\n    Returns\n    -------\n    out: Array\n        Array shape.\n\n    Examples\n    --------\n    > var out = arrayShape( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n    [ 2, 3 ]\n\n    See Also\n    --------\n    ndarray\n","arrayStream":"\narrayStream( src[, options] )\n    Creates a readable stream from an array-like object.\n\n    In object mode, `null` is a reserved value. If an array contains `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or filter `null` values\n    prior to invocation.\n\n    In binary mode, if an array contains `undefined` values, the stream will\n    emit an error. Consider providing a custom serialization function or\n    filtering `undefined` values prior to invocation.\n\n    If a serialization function fails to return a string or Buffer, the stream\n    emits an error.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Source value.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing the stream.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize streamed\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    options.dir: integer (optional)\n        Iteration direction. If set to `-1`, a stream iterates over elements\n        from right-to-left. Default: 1.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var s = arrayStream( [ 1, 2, 3 ] );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\narrayStream.factory( [options] )\n    Returns a function for creating readable streams from array-like objects.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing streaming.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize streamed\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    options.dir: integer (optional)\n        Iteration direction. If set to `-1`, a stream iterates over elements\n        from right-to-left. Default: 1.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = arrayStream.factory( opts );\n\n\narrayStream.objectMode( src[, options] )\n    Returns an \"objectMode\" readable stream from an array-like object.\n\n    In object mode, `null` is a reserved value. If an array contains `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or filter `null` values\n    prior to invocation.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Source value.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before pausing streaming.\n\n    options.dir: integer (optional)\n        Iteration direction. If set to `-1`, a stream iterates over elements\n        from right-to-left. Default: 1.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var s = arrayStream.objectMode( [ 1, 2, 3 ] );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    circularArrayStream, iteratorStream, stridedArrayStream\n","arrayStream.factory":"\narrayStream.factory( [options] )\n    Returns a function for creating readable streams from array-like objects.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing streaming.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize streamed\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    options.dir: integer (optional)\n        Iteration direction. If set to `-1`, a stream iterates over elements\n        from right-to-left. Default: 1.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = arrayStream.factory( opts );","arrayStream.objectMode":"\narrayStream.objectMode( src[, options] )\n    Returns an \"objectMode\" readable stream from an array-like object.\n\n    In object mode, `null` is a reserved value. If an array contains `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or filter `null` values\n    prior to invocation.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Source value.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before pausing streaming.\n\n    options.dir: integer (optional)\n        Iteration direction. If set to `-1`, a stream iterates over elements\n        from right-to-left. Default: 1.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var s = arrayStream.objectMode( [ 1, 2, 3 ] );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    circularArrayStream, iteratorStream, stridedArrayStream","arrayview2iterator":"\narrayview2iterator( src[, begin[, end]][, mapFcn[, thisArg]] )\n    Returns an iterator which iterates over the elements of an array-like object\n    view.\n\n    When invoked, an input function is provided four arguments:\n\n    - value: iterated value.\n    - index: iterated value index.\n    - n: iteration count (zero-based).\n    - src: source array-like object.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an array's `@@iterator` method, regardless of whether this method is\n    defined. To convert an array to an implementation defined iterator, invoke\n    this method directly.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Array-like object from which to create the iterator.\n\n    begin: integer (optional)\n        Starting index (inclusive). When negative, determined relative to the\n        last element. Default: 0.\n\n    end: integer (optional)\n        Ending index (non-inclusive). When negative, determined relative to the\n        last element. Default: src.length.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = arrayview2iterator( [ 1, 2, 3, 4 ], 1, 3 );\n    > var v = it.next().value\n    2\n    > v = it.next().value\n    3\n\n    See Also\n    --------\n    iterator2array, array2iterator, stridedarray2iterator, arrayview2iteratorRight\n","arrayview2iteratorRight":"\narrayview2iteratorRight( src[, begin[, end]][, mapFcn[, thisArg]] )\n    Returns an iterator which iterates from right to left over the elements of\n    an array-like object view.\n\n    When invoked, an input function is provided four arguments:\n\n    - value: iterated value.\n    - index: iterated value index.\n    - n: iteration count (zero-based).\n    - src: source array-like object.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an array's `@@iterator` method, regardless of whether this method is\n    defined. To convert an array to an implementation defined iterator, invoke\n    this method directly.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Array-like object from which to create the iterator.\n\n    begin: integer (optional)\n        Starting index (inclusive). When negative, determined relative to the\n        last element. Default: 0.\n\n    end: integer (optional)\n        Ending index (non-inclusive). When negative, determined relative to the\n        last element. Default: src.length.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = arrayview2iteratorRight( [ 1, 2, 3, 4 ], 1, 3 );\n    > var v = it.next().value\n    3\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    iterator2array, array2iteratorRight, stridedarray2iterator, arrayview2iterator\n","aslice":"\naslice( x[, start[, end]] )\n    Returns a shallow copy of a portion of an array.\n\n    If provided an array-like object having a `slice` method, the function\n    defers execution to that method and assumes that the method has the\n    following signature:\n\n      x.slice( start, end )\n\n    If provided an array-like object without a `slice` method, the function\n    copies input array elements to a new generic array.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    start: integer (optional)\n        Starting index (inclusive). Default: 0.\n\n    end: integer (optional)\n        Ending index (exclusive). Default: x.length.\n\n    Returns\n    -------\n    out: Array|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var out = aslice( [ 1, 2, 3, 4 ] )\n    [ 1, 2, 3, 4 ]\n    > out = aslice( [ 1, 2, 3, 4 ], 1 )\n    [ 2, 3, 4 ]\n    > out = aslice( [ 1, 2, 3, 4 ], 1, 3 )\n    [ 2, 3 ]\n\n    See Also\n    --------\n    atake\n","AsyncIteratorSymbol":"\nAsyncIteratorSymbol\n    Async iterator symbol.\n\n    This symbol specifies the default async iterator for an object.\n\n    The symbol is only supported in ES2018+ environments. For non-supporting\n    environments, the value is `null`.\n\n    Examples\n    --------\n    > var s = AsyncIteratorSymbol\n\n    See Also\n    --------\n    Symbol, IteratorSymbol\n","atake":"\natake( x, indices[, options] )\n    Takes elements from an array.\n\n    If `indices` is an empty array, the function returns an empty array.\n\n    Parameters\n    ----------\n    x: Array|TypedArray|Object\n        Input array.\n\n    indices: ArrayLikeObject<integer>\n        List of element indices.\n\n    options: Object (optional)\n        Function options.\n\n    options.mode: string (optional)\n        Specifies how to handle an index outside the interval [0, max], where\n        `max` is the maximum possible array index. If equal to 'throw', the\n        function throws an error. If equal to 'normalize', the function throws\n        an error if provided an out-of-bounds normalized index. If equal to\n        'wrap', the function wraps around an index using modulo arithmetic. If\n        equal to 'clamp', the function sets an index to either 0 (minimum index)\n        or the maximum index. Default: 'normalize'.\n\n    Returns\n    -------\n    out: Array|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = [ 1, 2, 3, 4 ];\n    > var y = atake( x, [ 1, 3 ] )\n    [ 2, 4 ]\n\n    See Also\n    --------\n    aput, aslice\n","azeros":"\nazeros( length[, dtype] )\n    Returns a zero-filled array having a specified length.\n\n    The function supports the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754).\n    - float32: single-precision floating-point numbers (IEEE 754).\n    - complex128: double-precision complex floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n    - generic: generic JavaScript values.\n\n    The default array data type is `float64`.\n\n    Parameters\n    ----------\n    length: integer\n        Array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = azeros( 2 )\n    <Float64Array>[ 0.0, 0.0 ]\n    > arr = azeros( 2, 'float32' )\n    <Float32Array>[ 0.0, 0.0 ]\n\n    See Also\n    --------\n    aempty, afull, anans, aones, azerosLike, ndzeros\n","azerosLike":"\nazerosLike( x[, dtype] )\n    Returns a zero-filled array having the same length and data type as a\n    provided input array.\n\n    The function supports the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754).\n    - float32: single-precision floating-point numbers (IEEE 754).\n    - complex128: double-precision complex floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n    - generic: generic JavaScript values.\n\n    Parameters\n    ----------\n    x: TypedArray|Array\n        Input array.\n\n    dtype: string (optional)\n        Data type. If not provided, the output array data type is inferred from\n        the input array.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var x = new Float64Array( 2 );\n    > var y = azerosLike( x )\n    <Float64Array>[ 0.0, 0.0 ]\n    > y = azerosLike( x, 'float32' )\n    <Float32Array>[ 0.0, 0.0 ]\n\n    See Also\n    --------\n    aemptyLike, afullLike, anansLike, aonesLike, azeros, ndzerosLike\n","azeroTo":"\nazeroTo( n[, dtype] )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from zero.\n\n    The function supports the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754).\n    - float32: single-precision floating-point numbers (IEEE 754).\n    - complex128: double-precision complex floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n    - generic: generic JavaScript values.\n\n    The default array data type is `float64`.\n\n    If `n` is equal to zero, the function returns an empty array.\n\n    Parameters\n    ----------\n    n: integer\n        Number of elements.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = azeroTo( 2 )\n    <Float64Array>[ 0.0, 1.0 ]\n    > arr = azeroTo( 2, 'float32' )\n    <Float32Array>[ 0.0, 1.0 ]\n\n    See Also\n    --------\n    aempty, afull, aoneTo, azeroToLike, azeros\n","azeroToLike":"\nazeroToLike( x[, dtype] )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from zero and having the same length and data type as a provided\n    input array.\n\n    The function supports the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754).\n    - float32: single-precision floating-point numbers (IEEE 754).\n    - complex128: double-precision complex floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n    - generic: generic JavaScript values.\n\n    Parameters\n    ----------\n    x: TypedArray|Array\n        Input array.\n\n    dtype: string (optional)\n        Data type. If not provided, the output array data type is inferred from\n        the input array.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = azeroToLike( [ 0, 0 ] )\n    [ 0, 1 ]\n    > arr = azeroToLike( [ 0, 0 ], 'float32' )\n    <Float32Array>[ 0.0, 1.0 ]\n\n    See Also\n    --------\n    aemptyLike, afullLike, anansLike, aoneToLike, aonesLike, azeroTo, azerosLike\n","bartlettTest":"\nbartlettTest( ...x[, options] )\n    Computes Bartlett’s test for equal variances.\n\n    Parameters\n    ----------\n    x: ...Array\n        Measured values.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.groups: Array (optional)\n        Array of group indicators.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.method: string\n        Name of test.\n\n    out.df: Object\n        Degrees of freedom.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    // Data from Hollander & Wolfe (1973), p. 116:\n    > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n    > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n    > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n    > var out = bartlettTest( x, y, z )\n\n    > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n    ...     3.8, 2.7, 4.0, 2.4,\n    ...     2.8, 3.4, 3.7, 2.2, 2.0\n    ... ];\n    > var groups = [\n    ...     'a', 'a', 'a', 'a', 'a',\n    ...     'b', 'b', 'b', 'b',\n    ...     'c', 'c', 'c', 'c', 'c'\n    ... ];\n    > out = bartlettTest( arr, { 'groups': groups } )\n\n    See Also\n    --------\n    vartest, leveneTest\n","base.abs":"\nbase.abs( x )\n    Computes the absolute value of a double-precision floating-point number `x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Absolute value.\n\n    Examples\n    --------\n    > var y = base.abs( -1.0 )\n    1.0\n    > y = base.abs( 2.0 )\n    2.0\n    > y = base.abs( 0.0 )\n    0.0\n    > y = base.abs( -0.0 )\n    0.0\n    > y = base.abs( NaN )\n    NaN\n\n    See Also\n    --------\n    base.abs2, base.absf, base.labs\n","base.abs2":"\nbase.abs2( x )\n    Computes the squared absolute value of a double-precision floating-point\n    `x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Squared absolute value.\n\n    Examples\n    --------\n    > var y = base.abs2( -1.0 )\n    1.0\n    > y = base.abs2( 2.0 )\n    4.0\n    > y = base.abs2( 0.0 )\n    0.0\n    > y = base.abs2( -0.0 )\n    0.0\n    > y = base.abs2( NaN )\n    NaN\n\n    See Also\n    --------\n    base.abs, base.abs2f\n","base.abs2f":"\nbase.abs2f( x )\n    Computes the squared absolute value of a single-precision floating-point\n    `x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Squared absolute value.\n\n    Examples\n    --------\n    > var y = base.abs2f( -1.0 )\n    1.0\n    > y = base.abs2f( 2.0 )\n    4.0\n    > y = base.abs2f( 0.0 )\n    0.0\n    > y = base.abs2f( -0.0 )\n    0.0\n    > y = base.abs2f( NaN )\n    NaN\n\n    See Also\n    --------\n    base.abs2, base.absf\n","base.absdiff":"\nbase.absdiff( x, y )\n    Computes the absolute difference.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Absolute difference.\n\n    Examples\n    --------\n    > var d = base.absdiff( 2.0, 5.0 )\n    3.0\n    > d = base.absdiff( -1.0, 3.14 )\n    ~4.14\n    > d = base.absdiff( 10.1, -2.05 )\n    ~12.15\n    > d = base.absdiff( -0.0, 0.0 )\n    +0.0\n    > d = base.absdiff( NaN, 5.0 )\n    NaN\n    > d = base.absdiff( PINF, NINF )\n    Infinity\n    > d = base.absdiff( PINF, PINF )\n    NaN\n\n    See Also\n    --------\n    base.reldiff, base.epsdiff\n","base.absf":"\nbase.absf( x )\n    Computes the absolute value of a single-precision floating-point number `x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Absolute value.\n\n    Examples\n    --------\n    > var y = base.absf( -1.0 )\n    1.0\n    > y = base.absf( 2.0 )\n    2.0\n    > y = base.absf( 0.0 )\n    0.0\n    > y = base.absf( -0.0 )\n    0.0\n    > y = base.absf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.abs, base.abs2f, base.labs\n","base.acartesianPower":"\nbase.acartesianPower( x, n )\n    Returns the Cartesian power.\n\n    If provided an empty array, the function returns an empty array.\n\n    If `n` is less than or equal to zero, the function returns an empty array.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    n: integer\n        Power.\n\n    Returns\n    -------\n    out: Array<Array>\n        Cartesian product.\n\n    Examples\n    --------\n    > var x = [ 1, 2 ];\n    > var out = base.acartesianPower( x, 2 )\n    [ [ 1, 1 ], [ 1, 2 ], [ 2, 1 ], [ 2, 2 ] ]\n\n    See Also\n    --------\n    acartesianPower, base.acartesianProduct, base.acartesianSquare\n","base.acartesianProduct":"\nbase.acartesianProduct( x1, x2 )\n    Returns the Cartesian product.\n\n    If provided one or more empty arrays, the function returns an empty array.\n\n    Parameters\n    ----------\n    x1: ArrayLikeObject\n        First input array.\n\n    x2: ArrayLikeObject\n        Second input array.\n\n    Returns\n    -------\n    out: Array<Array>\n        Cartesian product.\n\n    Examples\n    --------\n    > var x1 = [ 1, 2 ];\n    > var x2 = [ 3, 4 ];\n    > var out = base.acartesianProduct( x1, x2 )\n    [ [ 1, 3 ], [ 1, 4 ], [ 2, 3 ], [ 2, 4 ] ]\n\n    See Also\n    --------\n    acartesianProduct, base.acartesianPower, base.acartesianSquare\n","base.acartesianSquare":"\nbase.acartesianSquare( x )\n    Returns the Cartesian square.\n\n    If provided an empty array, the function returns an empty array.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    Returns\n    -------\n    out: Array<Array>\n        Cartesian product.\n\n    Examples\n    --------\n    > var x = [ 1, 2 ];\n    > var out = base.acartesianSquare( x )\n    [ [ 1, 1 ], [ 1, 2 ], [ 2, 1 ], [ 2, 2 ] ]\n\n    See Also\n    --------\n    acartesianSquare, base.acartesianPower, base.acartesianProduct\n","base.acos":"\nbase.acos( x )\n    Compute the arccosine of a double-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arccosine (in radians).\n\n    Examples\n    --------\n    > var y = base.acos( 1.0 )\n    0.0\n    > y = base.acos( 0.707 )\n    ~0.7855\n    > y = base.acos( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acosh, base.asin, base.atan\n","base.acosd":"\nbase.acosd( x )\n    Computes the arccosine (in degrees) of a double-precision floating-point \n    number.\n\n    If `|x| > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arccosine (in degrees).\n\n    Examples\n    --------\n    > var y = base.acosd( 0.0 )\n    90.0\n    > y = base.acosd( PI/6.0 )\n    ~58.43\n    > y = base.acosd( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acos, base.acosh, base.asind, base.atand\n","base.acosf":"\nbase.acosf( x )\n    Computes the arccosine of a single-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arccosine (in radians).\n\n    Examples\n    --------\n    > var y = base.acosf( 1.0 )\n    0.0\n    > y = base.acosf( 0.707 )\n    ~0.7855\n    > y = base.acosf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acos, base.acosh, base.asinf, base.atanf\n","base.acosh":"\nbase.acosh( x )\n    Computes the hyperbolic arccosine of a double-precision floating-point\n    number.\n\n    If `x < 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Hyperbolic arccosine.\n\n    Examples\n    --------\n    > var y = base.acosh( 1.0 )\n    0.0\n    > y = base.acosh( 2.0 )\n    ~1.317\n    > y = base.acosh( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acos, base.asinh, base.atanh\n","base.acot":"\nbase.acot( x )\n    Computes the inverse cotangent of a double-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Inverse cotangent (in radians).\n\n    Examples\n    --------\n    > var y = base.acot( 2.0 )\n    ~0.4636\n    > y = base.acot( 0.0 )\n    ~1.5708\n    > y = base.acot( 0.5 )\n    ~1.1071\n    > y = base.acot( 1.0 )\n    ~0.7854\n    > y = base.acot( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acoth, base.atan, base.cot\n","base.acotd":"\nbase.acotd( x )\n    Computes the arccotangent (in degrees) of a double-precision floating-point\n    number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arccotangent (in degrees).\n\n    Examples\n    --------\n    > var y = base.acotd( 0.0 )\n    90.0\n    > y = base.acotd( PI/6.0 )\n    ~62.36\n    > y = base.acotd( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acot, base.acoth, base.atand, base.cotd\n","base.acotf":"\nbase.acotf( x )\n    Computes the inverse cotangent of a single-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Inverse cotangent (in radians).\n\n    Examples\n    --------\n    > var y = base.acotf( 2.0 )\n    ~0.4636\n    > y = base.acotf( 0.0 )\n    ~1.5708\n    > y = base.acotf( 0.5 )\n    ~1.1071\n    > y = base.acotf( 1.0 )\n    ~0.7854\n    > y = base.acotf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acot, base.acoth, base.atanf\n","base.acoth":"\nbase.acoth( x )\n    Computes the inverse hyperbolic cotangent of a double-precision floating-\n    point number.\n\n    The domain of the inverse hyperbolic cotangent is the union of the intervals\n    (-inf,-1] and [1,inf).\n\n    If provided a value on the open interval (-1,1), the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Inverse hyperbolic cotangent.\n\n    Examples\n    --------\n    > var y = base.acoth( 2.0 )\n    ~0.5493\n    > y = base.acoth( 0.0 )\n    NaN\n    > y = base.acoth( 0.5 )\n    NaN\n    > y = base.acoth( 1.0 )\n    Infinity\n    > y = base.acoth( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acosh, base.acot, base.asinh, base.atanh\n","base.acovercos":"\nbase.acovercos( x )\n    Computes the inverse coversed cosine.\n\n    The inverse coversed cosine is defined as `asin(1+x)`.\n\n    If `x < -2`, `x > 0`, or `x` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Inverse coversed cosine.\n\n    Examples\n    --------\n    > var y = base.acovercos( -1.5 )\n    ~-0.5236\n    > y = base.acovercos( -0.0 )\n    ~1.5708\n\n    See Also\n    --------\n    base.acoversin, base.avercos, base.covercos, base.vercos\n","base.acoversin":"\nbase.acoversin( x )\n    Computes the inverse coversed sine.\n\n    The inverse coversed sine is defined as `asin(1-x)`.\n\n    If `x < 0`, `x > 2`, or `x` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Inverse coversed sine.\n\n    Examples\n    --------\n    > var y = base.acoversin( 1.5 )\n    ~-0.5236\n    > y = base.acoversin( 0.0 )\n    ~1.5708\n\n    See Also\n    --------\n    base.acovercos, base.aversin, base.coversin, base.versin\n","base.acsc":"\nbase.acsc( x )\n    Computes the arccosecant of a number.\n\n    If `|x| < 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arccosecant (in radians).\n\n    Examples\n    --------\n    > var y = base.acsc( 1.0 )\n    ~1.57\n    > y = base.acsc( PI )\n    ~0.32\n    > y = base.acsc( -PI )\n    ~-0.32\n    > y = base.acsc( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acot, base.acsch, base.asec, base.asin, base.csc\n","base.acscd":"\nbase.acscd( x )\n    Computes the arccosecant of (in degrees) a double-precision floating-point\n    number.\n\n    If `x` does not satisy `x >= 1` or `x <= -1`, the function returns NaN.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arccosecant (in degrees).\n\n    Examples\n    --------\n    > var y = base.acscd( 0.0 )\n    NaN\n    > y = base.acscd( PI/6.0 )\n    NaN\n    > y = base.acscd( 1 )\n    90.0\n    > y = base.acscd( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acsc, base.acsch, base.asecd, base.asind, base.cscd\n","base.acscdf":"\nbase.acscdf( x )\n    Computes the arccosecant (in degrees) of a single-precision floating-point\n    number.\n\n    If `x` does not satisy `x >= 1` or `x <= -1`, the function returns NaN.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arccosecant (in degrees).\n\n    Examples\n    --------\n    > var y = base.acscdf( 0.0 )\n    NaN\n    > y = base.acscdf( 3.1415927410125732 / 6.0 )\n    NaN\n    > y = base.acscdf( 1.0 )\n    90.0\n    > y = base.acscdf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acsc, base.acsch, base.asecdf, base.asindf\n","base.acscf":"\nbase.acscf( x )\n    Computes the arccosecant of a single-precision floating-point number.\n\n    If `|x| < 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arccosecant (in radians).\n\n    Examples\n    --------\n    > var y = base.acscf( 1.0 )\n    ~1.57\n    > y = base.acscf( 3.141592653589793 )\n    ~0.32\n    > y = base.acscf( -3.141592653589793 )\n    ~-0.32\n    > y = base.acscf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acsc, base.acsch, base.asecf, base.asinf\n","base.acsch":"\nbase.acsch( x )\n    Computes the hyperbolic arccosecant of a number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Hyperbolic arccosecant.\n\n    Examples\n    --------\n    > var y = base.acsch( 0.0 )\n    Infinity\n    > y = base.acsch( -1.0 )\n    ~-0.881\n    > y = base.acsch( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acoth, base.acsc, base.asech, base.asinh, base.csc, base.csch\n","base.add":"\nbase.add( x, y )\n    Computes the sum of two double-precision floating-point numbers `x` and `y`.\n\n    Parameters\n    ----------\n    x: number\n        First input value.\n\n    y: number\n        Second input value.\n\n    Returns\n    -------\n    z: number\n        Sum.\n\n    Examples\n    --------\n    > var v = base.add( -1.0, 5.0 )\n    4.0\n    > v = base.add( 2.0, 5.0 )\n    7.0\n    > v = base.add( 0.0, 5.0 )\n    5.0\n    > v = base.add( -0.0, 0.0 )\n    0.0\n    > v = base.add( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.div, base.mul, base.sub\n","base.add3":"\nbase.add3( x, y, z )\n    Computes the sum of three double-precision floating-point numbers.\n\n    Parameters\n    ----------\n    x: number\n        First input value.\n\n    y: number\n        Second input value.\n\n    z: number\n        Third input value.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    > var v = base.add3( -1.0, 5.0, 2.0 )\n    6.0\n    > v = base.add3( 2.0, 5.0, 2.0 )\n    9.0\n    > v = base.add3( 0.0, 5.0, 2.0 )\n    7.0\n    > v = base.add3( -0.0, 0.0, -0.0 )\n    0.0\n    > v = base.add3( NaN, NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.add\n","base.add4":"\nbase.add4( x, y, z, w )\n    Computes the sum of four double-precision floating-point numbers.\n\n    Parameters\n    ----------\n    x: number\n        First input value.\n\n    y: number\n        Second input value.\n\n    z: number\n        Third input value.\n\n    w: number\n        Fourth input value.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    > var v = base.add4( -1.0, 5.0, 2.0, -3.0 )\n    3.0\n    > v = base.add4( 2.0, 5.0, 2.0, -3.0 )\n    6.0\n    > v = base.add4( 0.0, 5.0, 2.0, -3.0 )\n    4.0\n    > v = base.add4( -0.0, 0.0, -0.0, -0.0 )\n    0.0\n    > v = base.add4( NaN, NaN, NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.add\n","base.add5":"\nbase.add5( x, y, z, w, u )\n    Computes the sum of five double-precision floating-point numbers.\n\n    Parameters\n    ----------\n    x: number\n        First input value.\n\n    y: number\n        Second input value.\n\n    z: number\n        Third input value.\n\n    w: number\n        Fourth input value.\n\n    u: number\n        Fifth input value.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    > var v = base.add5( -1.0, 5.0, 2.0, -3.0, 4.0 )\n    7.0\n    > v = base.add5( 2.0, 5.0, 2.0, -3.0, 4.0 )\n    10.0\n    > v = base.add5( 0.0, 5.0, 2.0, -3.0, 4.0 )\n    8.0\n    > v = base.add5( -0.0, 0.0, -0.0, -0.0, -0.0 )\n    0.0\n    > v = base.add5( NaN, NaN, NaN, NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.add\n","base.addf":"\nbase.addf( x, y )\n    Computes the sum of two single-precision floating-point numbers `x` and `y`.\n\n    Parameters\n    ----------\n    x: number\n        First input value.\n\n    y: number\n        Second input value.\n\n    Returns\n    -------\n    z: number\n        Sum.\n\n    Examples\n    --------\n    > var v = base.addf( -1.0, 5.0 )\n    4.0\n    > v = base.addf( 2.0, 5.0 )\n    7.0\n    > v = base.addf( 0.0, 5.0 )\n    5.0\n    > v = base.addf( -0.0, 0.0 )\n    0.0\n    > v = base.addf( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.add, base.divf, base.mulf, base.subf\n","base.afilled":"\nbase.afilled( value, len )\n    Returns a filled \"generic\" array.\n\n    Parameters\n    ----------\n    value: any\n        Fill value.\n\n    len: integer\n        Array length.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.afilled( 0.0, 3 )\n    [ 0.0, 0.0, 0.0 ]\n\n","base.afilled2d":"\nbase.afilled2d( value, shape )\n    Returns a filled two-dimensional nested array.\n\n    Parameters\n    ----------\n    value: any\n        Fill value.\n\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.afilled2d( 0.0, [ 1, 3 ] )\n    [ [ 0.0, 0.0, 0.0 ] ]\n\n","base.afilled2dBy":"\nbase.afilled2dBy( shape, clbk[, thisArg] )\n    Returns a filled two-dimensional nested array according to a provided\n    callback function.\n\n    The callback function is provided one argument:\n\n    - indices: current array element indices.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function clbk() { return 1.0; };\n    > var out = base.afilled2dBy( [ 1, 3 ], clbk )\n    [ [ 1.0, 1.0, 1.0 ] ]\n\n    See Also\n    --------\n    base.afilled2d\n","base.afilled3d":"\nbase.afilled3d( value, shape )\n    Returns a filled three-dimensional nested array.\n\n    Parameters\n    ----------\n    value: any\n        Fill value.\n\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.afilled3d( 0.0, [ 1, 1, 3 ] )\n    [ [ [ 0.0, 0.0, 0.0 ] ] ]\n\n","base.afilled3dBy":"\nbase.afilled3dBy( shape, clbk[, thisArg] )\n    Returns a filled three-dimensional nested array according to a provided\n    callback function.\n\n    The callback function is provided one argument:\n\n    - indices: current array element indices.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function clbk() { return 1.0; };\n    > var out = base.afilled3dBy( [ 1, 1, 3 ], clbk )\n    [ [ [ 1.0, 1.0, 1.0 ] ] ]\n\n    See Also\n    --------\n    base.afilled3d\n","base.afilled4d":"\nbase.afilled4d( value, shape )\n    Returns a filled four-dimensional nested array.\n\n    Parameters\n    ----------\n    value: any\n        Fill value.\n\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.afilled4d( 0.0, [ 1, 1, 1, 3 ] )\n    [ [ [ [ 0.0, 0.0, 0.0 ] ] ] ]\n\n","base.afilled4dBy":"\nbase.afilled4dBy( shape, clbk[, thisArg] )\n    Returns a filled four-dimensional nested array according to a provided\n    callback function.\n\n    The callback function is provided one argument:\n\n    - indices: current array element indices.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function clbk() { return 1.0; };\n    > var out = base.afilled4dBy( [ 1, 1, 1, 3 ], clbk )\n    [ [ [ [ 1.0, 1.0, 1.0 ] ] ] ]\n\n    See Also\n    --------\n    base.afilled4d\n","base.afilled5d":"\nbase.afilled5d( value, shape )\n    Returns a filled five-dimensional nested array.\n\n    Parameters\n    ----------\n    value: any\n        Fill value.\n\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.afilled5d( 0.0, [ 1, 1, 1, 1, 3 ] )\n    [ [ [ [ [ 0.0, 0.0, 0.0 ] ] ] ] ]\n\n","base.afilled5dBy":"\nbase.afilled5dBy( shape, clbk[, thisArg] )\n    Returns a filled five-dimensional nested array according to a provided\n    callback function.\n\n    The callback function is provided one argument:\n\n    - indices: current array element indices.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function clbk() { return 1.0; };\n    > var out = base.afilled5dBy( [ 1, 1, 1, 1, 3 ], clbk )\n    [ [ [ [ [ 1.0, 1.0, 1.0 ] ] ] ] ]\n\n    See Also\n    --------\n    base.afilled5d\n","base.afilledBy":"\nbase.afilledBy( len, clbk[, thisArg] )\n    Returns a filled \"generic\" array according to a provided callback function.\n\n    Parameters\n    ----------\n    len: integer\n        Array length.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function clbk() { return 1.0; };\n    > var out = base.afilledBy( 3, clbk )\n    [ 1.0, 1.0, 1.0 ]\n\n    See Also\n    --------\n    base.afilled\n","base.afillednd":"\nbase.afillednd( value, shape )\n    Returns a filled n-dimensional nested array.\n\n    Parameters\n    ----------\n    value: any\n        Fill value.\n\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.afillednd( 0.0, [ 1, 3 ] )\n    [ [ 0.0, 0.0, 0.0 ] ]\n\n","base.afilledndBy":"\nbase.afilledndBy( shape, clbk[, thisArg] )\n    Returns a filled n-dimensional nested array according to a callback\n    function.\n\n    The callback function is provided one argument:\n\n    - indices: current array element indices.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function clbk() { return 1.0; };\n    > var out = base.afilledndBy( [ 1, 3 ], clbk )\n    [ [ 1.0, 1.0, 1.0 ] ]\n\n    See Also\n    --------\n    base.afillednd\n","base.afilter":"\nbase.afilter( x, predicate[, thisArg] )\n    Returns a shallow copy of an array containing only those elements which pass\n    a test implemented by a predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the input array.\n\n    If provided an array-like object having a `filter` method , the function\n    defers execution to that method and assumes that the method has the\n    following signature:\n\n      x.filter( predicate, thisArg )\n\n    If provided an array-like object without a `filter` method, the function\n    performs a linear scan and always returns a generic array.\n\n    Parameters\n    ----------\n    x: Array|TypedArray|Object\n        Input array.\n\n    predicate: Function\n        Predicate function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Output array.\n\n    Examples\n    --------\n    > function f( v ) { return ( v > 0 ); };\n    > var x = [ 1, -2, -3, 4 ];\n    > var out = base.afilter( x, f )\n    [ 1, 4 ]\n\n","base.afirst":"\nbase.afirst( arr )\n    Returns the first element of an array-like object.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject\n        Input array.\n\n    Returns\n    -------\n    out: any\n        First element.\n\n    Examples\n    --------\n    > var out = base.afirst( [ 1, 2, 3 ] )\n    1\n\n","base.aflatten":"\nbase.aflatten( x, shape, colexicographic )\n    Flattens an n-dimensional nested array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    Returns\n    -------\n    out: Array\n        Flattened array.\n\n    Examples\n    --------\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = base.aflatten( x, [ 2, 2 ], false )\n    [ 1, 2, 3, 4 ]\n    > out = base.aflatten( x, [ 2, 2 ], true )\n    [ 1, 3, 2, 4 ]\n\n\nbase.aflatten.assign( x, shape, colexicographic, out, stride, offset )\n    Flattens an n-dimensional nested array and assigns elements to a provided\n    output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten.assign( x, [ 2, 2 ], false, out, 1, 0 )\n    [ 1, 2, 3, 4 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten.assign( x, [ 2, 2 ], true, out, 1, 0 );\n    > out\n    [ 1, 3, 2, 4 ]\n\n    See Also\n    --------\n    base.aflattenBy\n","base.aflatten.assign":"\nbase.aflatten.assign( x, shape, colexicographic, out, stride, offset )\n    Flattens an n-dimensional nested array and assigns elements to a provided\n    output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten.assign( x, [ 2, 2 ], false, out, 1, 0 )\n    [ 1, 2, 3, 4 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten.assign( x, [ 2, 2 ], true, out, 1, 0 );\n    > out\n    [ 1, 3, 2, 4 ]\n\n    See Also\n    --------\n    base.aflattenBy","base.aflatten2d":"\nbase.aflatten2d( x, shape, colexicographic )\n    Flattens a two-dimensional nested array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    Returns\n    -------\n    out: Array\n        Flattened array.\n\n    Examples\n    --------\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = base.aflatten2d( x, [ 2, 2 ], false )\n    [ 1, 2, 3, 4 ]\n    > out = base.aflatten2d( x, [ 2, 2 ], true )\n    [ 1, 3, 2, 4 ]\n\n\nbase.aflatten2d.assign( x, shape, colexicographic, out, stride, offset )\n    Flattens a two-dimensional nested array and assigns elements to a provided\n    output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten2d.assign( x, [ 2, 2 ], false, out, 1, 0 )\n    [ 1, 2, 3, 4 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten2d.assign( x, [ 2, 2 ], true, out, 1, 0 );\n    > out\n    [ 1, 3, 2, 4 ]\n\n    See Also\n    --------\n    base.aflatten2dBy\n","base.aflatten2d.assign":"\nbase.aflatten2d.assign( x, shape, colexicographic, out, stride, offset )\n    Flattens a two-dimensional nested array and assigns elements to a provided\n    output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten2d.assign( x, [ 2, 2 ], false, out, 1, 0 )\n    [ 1, 2, 3, 4 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten2d.assign( x, [ 2, 2 ], true, out, 1, 0 );\n    > out\n    [ 1, 3, 2, 4 ]\n\n    See Also\n    --------\n    base.aflatten2dBy","base.aflatten2dBy":"\nbase.aflatten2dBy( x, shape, colex, clbk[, thisArg] )\n    Flattens a two-dimensional nested array according to a callback function.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Flattened array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = base.aflatten2dBy( x, [ 2, 2 ], false, fcn )\n    [ 2, 4, 6, 8 ]\n    > out = base.aflatten2dBy( x, [ 2, 2 ], true, fcn )\n    [ 2, 6, 4, 8 ]\n\n\nbase.aflatten2dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n    Flattens a two-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten2dBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\n    [ 2, 4, 6, 8 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten2dBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\n    > out\n    [ 2, 6, 4, 8 ]\n\n    See Also\n    --------\n    base.aflatten2d\n","base.aflatten2dBy.assign":"\nbase.aflatten2dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n    Flattens a two-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten2dBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\n    [ 2, 4, 6, 8 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten2dBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\n    > out\n    [ 2, 6, 4, 8 ]\n\n    See Also\n    --------\n    base.aflatten2d","base.aflatten3d":"\nbase.aflatten3d( x, shape, colexicographic )\n    Flattens a three-dimensional nested array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    Returns\n    -------\n    out: Array\n        Flattened array.\n\n    Examples\n    --------\n    > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n    > var out = base.aflatten3d( x, [ 2, 1, 2 ], false )\n    [ 1, 2, 3, 4 ]\n    > out = base.aflatten3d( x, [ 2, 1, 2 ], true )\n    [ 1, 3, 2, 4 ]\n\n\nbase.aflatten3d.assign( x, shape, colexicographic, out, stride, offset )\n    Flattens a three-dimensional nested array and assigns elements to a provided\n    output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten3d.assign( x, [ 2, 1, 2 ], false, out, 1, 0 )\n    [ 1, 2, 3, 4 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten3d.assign( x, [ 2, 1, 2 ], true, out, 1, 0 );\n    > out\n    [ 1, 3, 2, 4 ]\n\n    See Also\n    --------\n    base.aflatten3dBy\n","base.aflatten3d.assign":"\nbase.aflatten3d.assign( x, shape, colexicographic, out, stride, offset )\n    Flattens a three-dimensional nested array and assigns elements to a provided\n    output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten3d.assign( x, [ 2, 1, 2 ], false, out, 1, 0 )\n    [ 1, 2, 3, 4 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten3d.assign( x, [ 2, 1, 2 ], true, out, 1, 0 );\n    > out\n    [ 1, 3, 2, 4 ]\n\n    See Also\n    --------\n    base.aflatten3dBy","base.aflatten3dBy":"\nbase.aflatten3dBy( x, shape, colex, clbk[, thisArg] )\n    Flattens a three-dimensional nested array according to a callback function.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Flattened array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n    > var out = base.aflatten3dBy( x, [ 2, 1, 2 ], false, fcn )\n    [ 2, 4, 6, 8 ]\n    > out = base.aflatten3dBy( x, [ 2, 1, 2 ], true, fcn )\n    [ 2, 6, 4, 8 ]\n\n\nbase.aflatten3dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n    Flattens a three-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten3dBy.assign( x, [ 2, 1, 2 ], false, out, 1, 0, fcn )\n    [ 2, 4, 6, 8 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten3dBy.assign( x, [ 2, 1, 2 ], true, out, 1, 0, fcn );\n    > out\n    [ 2, 6, 4, 8 ]\n\n    See Also\n    --------\n    base.aflatten3d\n","base.aflatten3dBy.assign":"\nbase.aflatten3dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n    Flattens a three-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten3dBy.assign( x, [ 2, 1, 2 ], false, out, 1, 0, fcn )\n    [ 2, 4, 6, 8 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten3dBy.assign( x, [ 2, 1, 2 ], true, out, 1, 0, fcn );\n    > out\n    [ 2, 6, 4, 8 ]\n\n    See Also\n    --------\n    base.aflatten3d","base.aflatten4d":"\nbase.aflatten4d( x, shape, colexicographic )\n    Flattens a four-dimensional nested array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    Returns\n    -------\n    out: Array\n        Flattened array.\n\n    Examples\n    --------\n    > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n    > var out = base.aflatten4d( x, [ 2, 1, 1, 2 ], false )\n    [ 1, 2, 3, 4 ]\n    > out = base.aflatten4d( x, [ 2, 1, 1, 2 ], true )\n    [ 1, 3, 2, 4 ]\n\n\nbase.aflatten4d.assign( x, shape, colexicographic, out, stride, offset )\n    Flattens a four-dimensional nested array and assigns elements to a provided\n    output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0 )\n    [ 1, 2, 3, 4 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0 );\n    > out\n    [ 1, 3, 2, 4 ]\n\n    See Also\n    --------\n    base.aflatten4dBy\n","base.aflatten4d.assign":"\nbase.aflatten4d.assign( x, shape, colexicographic, out, stride, offset )\n    Flattens a four-dimensional nested array and assigns elements to a provided\n    output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0 )\n    [ 1, 2, 3, 4 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0 );\n    > out\n    [ 1, 3, 2, 4 ]\n\n    See Also\n    --------\n    base.aflatten4dBy","base.aflatten4dBy":"\nbase.aflatten4dBy( x, shape, colex, clbk[, thisArg] )\n    Flattens a four-dimensional nested array according to a callback function.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Flattened array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n    > var out = base.aflatten4dBy( x, [ 2, 1, 1, 2 ], false, fcn )\n    [ 2, 4, 6, 8 ]\n    > out = base.aflatten4dBy( x, [ 2, 1, 1, 2 ], true, fcn )\n    [ 2, 6, 4, 8 ]\n\n\nbase.aflatten4dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n    Flattens a four-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0, fcn )\n    [ 2, 4, 6, 8 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0, fcn );\n    > out\n    [ 2, 6, 4, 8 ]\n\n    See Also\n    --------\n    base.aflatten4d\n","base.aflatten4dBy.assign":"\nbase.aflatten4dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n    Flattens a four-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0, fcn )\n    [ 2, 4, 6, 8 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0, fcn );\n    > out\n    [ 2, 6, 4, 8 ]\n\n    See Also\n    --------\n    base.aflatten4d","base.aflatten5d":"\nbase.aflatten5d( x, shape, colexicographic )\n    Flattens a five-dimensional nested array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    Returns\n    -------\n    out: Array\n        Flattened array.\n\n    Examples\n    --------\n    > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n    > var out = base.aflatten5d( x, [ 2, 1, 1, 1, 2 ], false )\n    [ 1, 2, 3, 4 ]\n    > out = base.aflatten5d( x, [ 2, 1, 1, 1, 2 ], true )\n    [ 1, 3, 2, 4 ]\n\n\nbase.aflatten5d.assign( x, shape, colexicographic, out, stride, offset )\n    Flattens a five-dimensional nested array and assigns elements to a provided\n    output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0 )\n    [ 1, 2, 3, 4 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0 );\n    > out\n    [ 1, 3, 2, 4 ]\n\n    See Also\n    --------\n    base.aflatten5dBy\n","base.aflatten5d.assign":"\nbase.aflatten5d.assign( x, shape, colexicographic, out, stride, offset )\n    Flattens a five-dimensional nested array and assigns elements to a provided\n    output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0 )\n    [ 1, 2, 3, 4 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0 );\n    > out\n    [ 1, 3, 2, 4 ]\n\n    See Also\n    --------\n    base.aflatten5dBy","base.aflatten5dBy":"\nbase.aflatten5dBy( x, shape, colex, clbk[, thisArg] )\n    Flattens a five-dimensional nested array according to a callback function.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Flattened array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n    > var out = base.aflatten5dBy( x, [ 2, 1, 1, 1, 2 ], false, fcn )\n    [ 2, 4, 6, 8 ]\n    > out = base.aflatten5dBy( x, [ 2, 1, 1, 1, 2 ], true, fcn )\n    [ 2, 6, 4, 8 ]\n\n\nbase.aflatten5dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n    Flattens a five-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0, fcn )\n    [ 2, 4, 6, 8 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0, fcn );\n    > out\n    [ 2, 6, 4, 8 ]\n\n    See Also\n    --------\n    base.aflatten5d\n","base.aflatten5dBy.assign":"\nbase.aflatten5dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n    Flattens a five-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0, fcn )\n    [ 2, 4, 6, 8 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0, fcn );\n    > out\n    [ 2, 6, 4, 8 ]\n\n    See Also\n    --------\n    base.aflatten5d","base.aflattenBy":"\nbase.aflattenBy( x, shape, colex, clbk[, thisArg] )\n    Flattens an n-dimensional nested array according to a callback function.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Flattened array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = base.aflattenBy( x, [ 2, 2 ], false, fcn )\n    [ 2, 4, 6, 8 ]\n    > out = base.aflattenBy( x, [ 2, 2 ], true, fcn )\n    [ 2, 6, 4, 8 ]\n\n\nbase.aflattenBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n    Flattens an n-dimensional nested array according to a callback function and\n    assigns elements to a provided output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflattenBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\n    [ 2, 4, 6, 8 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflattenBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\n    > out\n    [ 2, 6, 4, 8 ]\n\n    See Also\n    --------\n    base.aflatten\n","base.aflattenBy.assign":"\nbase.aflattenBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n    Flattens an n-dimensional nested array according to a callback function and\n    assigns elements to a provided output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflattenBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\n    [ 2, 4, 6, 8 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflattenBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\n    > out\n    [ 2, 6, 4, 8 ]\n\n    See Also\n    --------\n    base.aflatten","base.afliplr2d":"\nbase.afliplr2d( x )\n    Reverses the order of elements along the last dimension of a two-dimensional\n    nested input array.\n\n    The function does *not* perform a deep copy of nested array elements.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input nested array.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.afliplr2d( [ [ 1, 2 ], [ 3, 4 ] ] )\n    [ [ 2, 1 ], [ 4, 3 ] ]\n\n    See Also\n    --------\n    base.afliplr3d, base.afliplr4d, base.afliplr5d\n","base.afliplr3d":"\nbase.afliplr3d( x )\n    Reverses the order of elements along the last dimension of a three-\n    dimensional nested input array.\n\n    The function does *not* perform a deep copy of nested array elements.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input nested array.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.afliplr3d( [ [ [ 1, 2 ], [ 3, 4 ] ] ] )\n    [ [ [ 2, 1 ], [ 4, 3 ] ] ]\n\n    See Also\n    --------\n    base.afliplr2d, base.afliplr4d, base.afliplr5d\n","base.afliplr4d":"\nbase.afliplr4d( x )\n    Reverses the order of elements along the last dimension of a four-\n    dimensional nested input array.\n\n    The function does *not* perform a deep copy of nested array elements.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input nested array.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.afliplr4d( [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] )\n    [ [ [ [ 2, 1 ], [ 4, 3 ] ] ] ]\n\n    See Also\n    --------\n    base.afliplr2d, base.afliplr3d, base.afliplr5d\n","base.afliplr5d":"\nbase.afliplr5d( x )\n    Reverses the order of elements along the last dimension of a five-\n    dimensional nested input array.\n\n    The function does *not* perform a deep copy of nested array elements.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input nested array.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.afliplr5d( [ [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] ] )\n    [ [ [ [ [ 2, 1 ], [ 4, 3 ] ] ] ] ]\n\n    See Also\n    --------\n    base.afliplr2d, base.afliplr3d, base.afliplr4d\n","base.aflipud2d":"\nbase.aflipud2d( x )\n    Reverses the order of elements along the first dimension of a two-\n    dimensional nested input array.\n\n    The function does *not* perform a deep copy of nested array elements.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input nested array.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.aflipud2d( [ [ 1, 2 ], [ 3, 4 ] ] )\n    [ [ 3, 4 ], [ 1, 2 ] ]\n\n    See Also\n    --------\n    base.aflipud3d, base.aflipud4d, base.aflipud5d\n","base.aflipud3d":"\nbase.aflipud3d( x )\n    Reverses the order of elements along the second-to-last dimension of a\n    three-dimensional nested input array.\n\n    The function does *not* perform a deep copy of nested array elements.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input nested array.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.aflipud3d( [ [ [ 1, 2 ], [ 3, 4 ] ] ] )\n    [ [ [ 3, 4 ], [ 1, 2 ] ] ]\n\n    See Also\n    --------\n    base.aflipud2d, base.aflipud4d, base.aflipud5d\n","base.aflipud4d":"\nbase.aflipud4d( x )\n    Reverses the order of elements along the second-to-last dimension of a four-\n    dimensional nested input array.\n\n    The function does *not* perform a deep copy of nested array elements.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input nested array.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.aflipud4d( [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] )\n    [ [ [ [ 3, 4 ], [ 1, 2 ] ] ] ]\n\n    See Also\n    --------\n    base.aflipud2d, base.aflipud3d, base.aflipud5d\n","base.aflipud5d":"\nbase.aflipud5d( x )\n    Reverses the order of elements along the second-to-last dimension of a five-\n    dimensional nested input array.\n\n    The function does *not* perform a deep copy of nested array elements.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input nested array.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.aflipud5d( [ [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] ] )\n    [ [ [ [ [ 3, 4 ], [ 1, 2 ] ] ] ] ]\n\n    See Also\n    --------\n    base.aflipud2d, base.aflipud3d, base.aflipud4d\n","base.ahavercos":"\nbase.ahavercos( x )\n    Computes the inverse half-value versed cosine.\n\n    The inverse half-value versed cosine is defined as `2*acos(sqrt(x))`.\n\n    If `x < 0`, `x > 1`, or `x` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Inverse half-value versed cosine.\n\n    Examples\n    --------\n    > var y = base.ahavercos( 0.5 )\n    ~1.5708\n    > y = base.ahavercos( 0.0 )\n    ~3.1416\n\n    See Also\n    --------\n    base.ahaversin, base.havercos, base.vercos\n","base.ahaversin":"\nbase.ahaversin( x )\n    Computes the inverse half-value versed sine.\n\n    The inverse half-value versed sine is defined as `2*asin(sqrt(x))`.\n\n    If `x < 0`, `x > 1`, or `x` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Inverse half-value versed sine.\n\n    Examples\n    --------\n    > var y = base.ahaversin( 0.5 )\n    ~1.5708\n    > y = base.ahaversin( 0.0 )\n    0.0\n\n    See Also\n    --------\n    base.ahavercos, base.haversin, base.versin\n","base.altcase":"\nbase.altcase( str )\n    Converts a string to alternate case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Alternate-cased string.\n\n    Examples\n    --------\n    > var out = base.altcase( 'Hello World!' )\n    'hElLo wOrLd!'\n    > out = base.altcase( 'I am a tiny little teapot' )\n    'i aM A TiNy lItTlE TeApOt'\n\n    See Also\n    --------\n    base.lowercase, base.uppercase","base.aones":"\nbase.aones( len )\n    Returns a \"generic\" array filled with ones.\n\n    Parameters\n    ----------\n    len: integer\n        Array length.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.aones( 3 )\n    [ 1.0, 1.0, 1.0 ]\n\n    See Also\n    --------\n    base.azeros, base.aones2d, base.aones3d, base.aones4d, base.aones5d, base.aonesnd\n","base.aones2d":"\nbase.aones2d( shape )\n    Returns a two-dimensional nested array filled with ones.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.aones2d( [ 1, 3 ] )\n    [ [ 1.0, 1.0, 1.0 ] ]\n\n    See Also\n    --------\n    base.azeros2d, base.aones, base.aones3d, base.aones4d, base.aones5d, base.aonesnd\n","base.aones3d":"\nbase.aones3d( shape )\n    Returns a three-dimensional nested array filled with ones.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.aones3d( [ 1, 1, 3 ] )\n    [ [ [ 1.0, 1.0, 1.0 ] ] ]\n\n    See Also\n    --------\n    base.azeros3d, base.aones, base.aones2d, base.aones4d, base.aones5d, base.aonesnd\n","base.aones4d":"\nbase.aones4d( shape )\n    Returns a four-dimensional nested array filled with ones.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.aones4d( [ 1, 1, 1, 3 ] )\n    [ [ [ [ 1.0, 1.0, 1.0 ] ] ] ]\n\n    See Also\n    --------\n    base.azeros4d, base.aones, base.aones2d, base.aones3d, base.aones5d, base.aonesnd\n","base.aones5d":"\nbase.aones5d( shape )\n    Returns a five-dimensional nested array filled with ones.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.aones5d( [ 1, 1, 1, 1, 3 ] )\n    [ [ [ [ [ 1.0, 1.0, 1.0 ] ] ] ] ]\n\n    See Also\n    --------\n    base.azeros5d, base.aones, base.aones2d, base.aones3d, base.aones4d, base.aonesnd\n","base.aonesnd":"\nbase.aonesnd( shape )\n    Returns an n-dimensional nested array filled with ones.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.aonesnd( [ 1, 3 ] )\n    [ [ 1.0, 1.0, 1.0 ] ]\n\n    See Also\n    --------\n    base.azerosnd, base.aones, base.aones2d, base.aones3d, base.aones4d, base.aones5d\n","base.aoneTo":"\nbase.aoneTo( n )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from one.\n\n    If `n` is a non-integer value greater than zero, the function returns an\n    array having `ceil(n)` elements.\n\n    If `n` is less than or equal to zero, the function returns an empty array.\n\n    Parameters\n    ----------\n    n: number\n        Number of elements.\n\n    Returns\n    -------\n    out: Array\n        Linearly spaced numeric array.\n\n    Examples\n    --------\n    > var arr = base.aoneTo( 6 )\n    [ 1, 2, 3, 4, 5, 6 ]\n\n\nbase.aoneTo.assign( out, stride, offset )\n    Fills an array with linearly spaced numeric elements which increment by 1\n    starting from one.\n\n    Parameters\n    ----------\n    out: ArrayLikeObject\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > base.aoneTo.assign( out, -1, out.length-1 );\n    > out\n    [ 6, 5, 4, 3, 2, 1 ]\n\n    See Also\n    --------\n    base.azeroTo, base.aones\n","base.aoneTo.assign":"\nbase.aoneTo.assign( out, stride, offset )\n    Fills an array with linearly spaced numeric elements which increment by 1\n    starting from one.\n\n    Parameters\n    ----------\n    out: ArrayLikeObject\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > base.aoneTo.assign( out, -1, out.length-1 );\n    > out\n    [ 6, 5, 4, 3, 2, 1 ]\n\n    See Also\n    --------\n    base.azeroTo, base.aones","base.args2multislice":"\nbase.args2multislice( args )\n    Creates a MultiSlice object from a list of MultiSlice constructor arguments.\n\n    Parameters\n    ----------\n    args: Array<Slice|integer|null|undefined>\n        Constructor arguments.\n\n    Returns\n    -------\n    s: MultiSlice\n        MultiSlice instance.\n\n    Examples\n    --------\n    > var args = [ null, null, null ];\n    > var s = new base.args2multislice( args );\n    > s.data\n    [ null, null, null ]\n    > args = [ 10, new Slice( 0, 10, 1 ), null ];\n    > s = new base.args2multislice( args );\n    > s.data\n    [ 10, <Slice>, null ]\n\n","base.asec":"\nbase.asec( x )\n    Computes the inverse (arc) secant of a number.\n\n    If `x > -1` and `x < 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Inverse (arc) secant.\n\n    Examples\n    --------\n    > var y = base.asec( 1.0 )\n    0.0\n    > y = base.asec( 2.0 )\n    ~1.0472\n    > y = base.asec( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acot, base.acsc, base.asech, base.acos\n","base.asecd":"\nbase.asecd( x )\n    Computes the arcsecant (in degrees) of a double-precision floating-point\n    number.\n\n    If `x` does not satisy `x >= 1` or `x <= -1`, the function returns NaN.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arcsecant (in degrees).\n\n    Examples\n    --------\n    > var y = base.asecd( 0.0 )\n    NaN\n    > y = base.asecd( 2 )\n    ~60.0\n    > y = base.asecd( NaN )\n    NaN\n\n    See Also\n    --------\n    base.asec, base.asech, base.acosd, base.secd\n","base.asecdf":"\nbase.asecdf( x )\n    Computes the arcsecant (in degrees) of a single-precision floating-point\n    number.\n\n    If `x` does not satisy `x >= 1` or `x <= -1`, the function returns NaN.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arcsecant (in degrees).\n\n    Examples\n    --------\n    > var y = base.asecdf( 2.0 )\n    ~60.0\n    > y = base.asecdf( 0.0 )\n    NaN\n    > y = base.asecdf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.asec, base.asech\n","base.asecf":"\nbase.asecf( x )\n    Computes the inverse (arc) secant of a single-precision\n    floating-point number.\n\n    If `x > -1` and `x < 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Inverse (arc) secant.\n\n    Examples\n    --------\n    > var y = base.asecf( 1.0 )\n    0.0\n    > y = base.asecf( 2.0 )\n    ~1.0472\n    > y = base.asecf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.asec, base.asech, base.acosf\n","base.asech":"\nbase.asech( x )\n    Computes the hyperbolic arcsecant of a number.\n\n    If `x < 0` or `x > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Hyperbolic arcsecant.\n\n    Examples\n    --------\n    > var y = base.asech( 1.0 )\n    0.0\n    > y = base.asech( 0.5 )\n    ~1.317\n    > y = base.asech( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acosh, base.asec, base.asech, base.acoth\n","base.asin":"\nbase.asin( x )\n    Computes the arcsine of a double-precision floating-point number.\n\n    If `|x| > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arcsine (in radians).\n\n    Examples\n    --------\n    > var y = base.asin( 0.0 )\n    0.0\n    > y = base.asin( -PI/6.0 )\n    ~-0.551\n    > y = base.asin( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acos, base.asinh, base.atan\n","base.asind":"\nbase.asind( x )\n    Computes the arcsine (in degrees) of a double-precision floating-point\n    number.\n\n    If `|x| > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arcsine (in degrees).\n\n    Examples\n    --------\n    > var y = base.asind( 0.0 )\n    0.0\n    > y = base.asind( PI / 6.0 )\n    ~31.57\n    > y = base.asind( NaN )\n    NaN\n\n    See Also\n    --------\n    base.asin, base.asinh, base.atand\n","base.asindf":"\nbase.asindf( x )\n    Computes the arcsine (in degrees) of a single-precision floating-point\n    number.\n\n    If `|x| > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arcsine (in degrees).\n\n    Examples\n    --------\n    > var y = base.asindf( 0.0 )\n    0.0\n    > y = base.asindf( 3.1415927410125732 / 6.0 )\n    ~31.57\n    > y = base.asindf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.asinf, base.asind\n","base.asinf":"\nbase.asinf( x )\n    Computes the arcsine of a single-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arcsine (in radians).\n\n    Examples\n    --------\n    > var y = base.asinf( 0.0 )\n    0.0\n    > y = base.asinf( -3.14/6.0 )\n    ~-0.551\n    > y = base.asinf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.asin, base.asindf\n","base.asinh":"\nbase.asinh( x )\n    Computes the hyperbolic arcsine of a double-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Hyperbolic arcsine.\n\n    Examples\n    --------\n    > var y = base.asinh( 0.0 )\n    0.0\n    > y = base.asinh( 2.0 )\n    ~1.444\n    > y = base.asinh( -2.0 )\n    ~-1.444\n    > y = base.asinh( NaN )\n    NaN\n    > y = base.asinh( NINF )\n    -Infinity\n    > y = base.asinh( PINF )\n    Infinity\n\n    See Also\n    --------\n    base.acosh, base.asin, base.atanh\n","base.atan":"\nbase.atan( x )\n    Computes the arctangent of a double-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arctangent (in radians).\n\n    Examples\n    --------\n    > var y = base.atan( 0.0 )\n    ~0.0\n    > y = base.atan( -PI/2.0 )\n    ~-1.004\n    > y = base.atan( PI/2.0 )\n    ~1.004\n    > y = base.atan( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acos, base.asin, base.atanh\n","base.atan2":"\nbase.atan2( y, x )\n    Computes the angle in the plane (in radians) between the positive x-axis and\n    the ray from (0,0) to the point (x,y).\n\n    Parameters\n    ----------\n    y: number\n        Coordinate along y-axis.\n\n    x: number\n        Coordinate along x-axis.\n\n    Returns\n    -------\n    out: number\n        Angle (in radians).\n\n    Examples\n    --------\n    > var v = base.atan2( 2.0, 2.0 )\n    ~0.785\n    > v = base.atan2( 6.0, 2.0 )\n    ~1.249\n    > v = base.atan2( -1.0, -1.0 )\n    ~-2.356\n    > v = base.atan2( 3.0, 0.0 )\n    ~1.571\n    > v = base.atan2( -2.0, 0.0 )\n    ~-1.571\n    > v = base.atan2( 0.0, 0.0 )\n    0.0\n    > v = base.atan2( 3.0, NaN )\n    NaN\n    > v = base.atan2( NaN, 2.0 )\n    NaN\n\n    See Also\n    --------\n    base.atan\n","base.atand":"\nbase.atand( x )\n    Computes the arctangent (in degrees) of a double-precision floating-point\n    number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arctangent (in degrees).\n\n    Examples\n    --------\n    > var y = base.atand( 0.0 )\n    0.0\n    > y = base.atand( PI/6.0 )\n    ~27.64\n    > y = base.atand( NaN )\n    NaN\n\n    See Also\n    --------\n    base.atan, base.atanh, base.acosd\n","base.atanf":"\nbase.atanf( x )\n    Computes the arctangent of a single-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arctangent (in radians).\n\n    Examples\n    --------\n    > var y = base.atanf( 0.0 )\n    0.0\n    > y = base.atanf( -3.14/4.0 )\n    ~-0.666\n    > y = base.atanf( 3.14/4.0 )\n    ~0.666\n    > y = base.atanf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.atan, base.atanh, base.acosf\n","base.atanh":"\nbase.atanh( x )\n    Computes the hyperbolic arctangent of a double-precision floating-point\n    number.\n\n    If `|x| > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Hyperbolic arctangent.\n\n    Examples\n    --------\n    > var y = base.atanh( 0.0 )\n    0.0\n    > y = base.atanh( 0.9 )\n    ~1.472\n    > y = base.atanh( 1.0 )\n    Infinity\n    > y = base.atanh( -1.0 )\n    -Infinity\n    > y = base.atanh( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acosh, base.asinh, base.atan\n","base.avercos":"\nbase.avercos( x )\n    Computes the inverse versed cosine.\n\n    The inverse versed cosine is defined as `acos(1+x)`.\n\n    If `x < -2`, `x > 0`, or `x` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Inverse versed cosine.\n\n    Examples\n    --------\n    > var y = base.avercos( -1.5 )\n    ~2.0944\n    > y = base.avercos( -0.0 )\n    0.0\n\n    See Also\n    --------\n    base.aversin, base.versin\n","base.aversin":"\nbase.aversin( x )\n    Computes the inverse versed sine.\n\n    The inverse versed sine is defined as `acos(1-x)`.\n\n    If `x < 0`, `x > 2`, or `x` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Inverse versed sine.\n\n    Examples\n    --------\n    > var y = base.aversin( 1.5 )\n    ~2.0944\n    > y = base.aversin( 0.0 )\n    0.0\n\n    See Also\n    --------\n    base.avercos, base.vercos\n","base.azeros":"\nbase.azeros( len )\n    Returns a zero-filled \"generic\" array.\n\n    Parameters\n    ----------\n    len: integer\n        Array length.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.azeros( 3 )\n    [ 0.0, 0.0, 0.0 ]\n\n    See Also\n    --------\n    base.aones, base.azeros2d, base.azeros3d, base.azeros4d, base.azeros5d, base.azerosnd\n","base.azeros2d":"\nbase.azeros2d( shape )\n    Returns a zero-filled two-dimensional nested array.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.azeros2d( [ 1, 3 ] )\n    [ [ 0.0, 0.0, 0.0 ] ]\n\n    See Also\n    --------\n    base.azeros, base.aones2d, base.azeros3d, base.azeros4d, base.azeros5d, base.azerosnd\n","base.azeros3d":"\nbase.azeros3d( shape )\n    Returns a zero-filled three-dimensional nested array.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.azeros3d( [ 1, 1, 3 ] )\n    [ [ [ 0.0, 0.0, 0.0 ] ] ]\n\n    See Also\n    --------\n    base.azeros, base.aones3d, base.azeros2d, base.azeros4d, base.azeros5d, base.azerosnd\n","base.azeros4d":"\nbase.azeros4d( shape )\n    Returns a zero-filled four-dimensional nested array.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.azeros4d( [ 1, 1, 1, 3 ] )\n    [ [ [ [ 0.0, 0.0, 0.0 ] ] ] ]\n\n    See Also\n    --------\n    base.azeros, base.aones4d, base.azeros2d, base.azeros3d, base.azeros5d, base.azerosnd\n","base.azeros5d":"\nbase.azeros5d( shape )\n    Returns a zero-filled five-dimensional nested array.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.azeros5d( [ 1, 1, 1, 1, 3 ] )\n    [ [ [ [ [ 0.0, 0.0, 0.0 ] ] ] ] ]\n\n    See Also\n    --------\n    base.azeros, base.aones5d, base.azeros2d, base.azeros3d, base.azeros4d, base.azerosnd\n","base.azerosnd":"\nbase.azerosnd( shape )\n    Returns a zero-filled n-dimensional nested array.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.azerosnd( [ 1, 3 ] )\n    [ [ 0.0, 0.0, 0.0 ] ]\n\n    See Also\n    --------\n    base.azeros, base.aonesnd, base.azeros2d, base.azeros3d, base.azeros4d, base.azeros5d\n","base.azeroTo":"\nbase.azeroTo( n )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from zero.\n\n    If `n` is a non-integer value greater than zero, the function returns an\n    array having `ceil(n)` elements.\n\n    If `n` is less than or equal to zero, the function returns an empty array.\n\n    Parameters\n    ----------\n    n: number\n        Number of elements.\n\n    Returns\n    -------\n    out: Array\n        Linearly spaced numeric array.\n\n    Examples\n    --------\n    > var arr = base.azeroTo( 6 )\n    [ 0, 1, 2, 3, 4, 5 ]\n\n\nbase.azeroTo.assign( out, stride, offset )\n    Fills an array with linearly spaced numeric elements which increment by 1\n    starting from zero.\n\n    Parameters\n    ----------\n    out: ArrayLikeObject\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > base.azeroTo.assign( out, -1, out.length-1 );\n    > out\n    [ 5, 4, 3, 2, 1, 0 ]\n\n    See Also\n    --------\n    base.aoneTo\n","base.azeroTo.assign":"\nbase.azeroTo.assign( out, stride, offset )\n    Fills an array with linearly spaced numeric elements which increment by 1\n    starting from zero.\n\n    Parameters\n    ----------\n    out: ArrayLikeObject\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > base.azeroTo.assign( out, -1, out.length-1 );\n    > out\n    [ 5, 4, 3, 2, 1, 0 ]\n\n    See Also\n    --------\n    base.aoneTo","base.bernoulli":"\nbase.bernoulli( n )\n    Computes the nth Bernoulli number.\n\n    If not provided a nonnegative integer value, the function returns `NaN`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Bernoulli number.\n\n    Examples\n    --------\n    > var y = base.bernoulli( 0 )\n    1.0\n    > y = base.bernoulli( 1 )\n    0.5\n    > y = base.bernoulli( 2 )\n    ~0.167\n    > y = base.bernoulli( 3 )\n    0.0\n    > y = base.bernoulli( 4 )\n    ~-0.033\n    > y = base.bernoulli( 5 )\n    0.0\n    > y = base.bernoulli( 20 )\n    ~-529.124\n    > y = base.bernoulli( 260 )\n    -Infinity\n    > y = base.bernoulli( 262 )\n    Infinity\n    > y = base.bernoulli( NaN )\n    NaN\n\n","base.besselj0":"\nbase.besselj0( x )\n    Computes the Bessel function of the first kind of order zero.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.besselj0( 0.0 )\n    1.0\n    > y = base.besselj0( 1.0 )\n    ~0.765\n    > y = base.besselj0( PINF )\n    0.0\n    > y = base.besselj0( NINF )\n    0.0\n    > y = base.besselj0( NaN )\n    NaN\n\n    See Also\n    --------\n    base.besselj1, base.bessely0, base.bessely1\n","base.besselj1":"\nbase.besselj1( x )\n    Computes the Bessel function of the first kind of order one.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.besselj1( 0.0 )\n    0.0\n    > y = base.besselj1( 1.0 )\n    ~0.440\n    > y = base.besselj1( PINF )\n    0.0\n    > y = base.besselj1( NINF )\n    0.0\n    > y = base.besselj1( NaN )\n    NaN\n\n    See Also\n    --------\n    base.besselj0, base.bessely0, base.bessely1\n","base.bessely0":"\nbase.bessely0( x )\n    Computes the Bessel function of the second kind of order zero.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.bessely0( 0.0 )\n    -Infinity\n    > y = base.bessely0( 1.0 )\n    ~0.088\n    > y = base.bessely0( -1.0 )\n    NaN\n    > y = base.bessely0( PINF )\n    0.0\n    > y = base.bessely0( NINF )\n    NaN\n    > y = base.bessely0( NaN )\n    NaN\n\n    See Also\n    --------\n    base.besselj0, base.besselj1, base.bessely1\n","base.bessely1":"\nbase.bessely1( x )\n    Computes the Bessel function of the second kind of order one.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.bessely1( 0.0 )\n    -Infinity\n    > y = base.bessely1( 1.0 )\n    ~-0.781\n    > y = base.bessely1( -1.0 )\n    NaN\n    > y = base.bessely1( PINF )\n    0.0\n    > y = base.bessely1( NINF )\n    NaN\n    > y = base.bessely1( NaN )\n    NaN\n\n    See Also\n    --------\n    base.besselj0, base.besselj1, base.bessely0\n","base.beta":"\nbase.beta( x, y )\n    Evaluates the beta function.\n\n    Parameters\n    ----------\n    x: number\n        First function parameter (nonnegative).\n\n    y: number\n        Second function parameter (nonnegative).\n\n    Returns\n    -------\n    out: number\n        Evaluated beta function.\n\n    Examples\n    --------\n    > var v = base.beta( 0.0, 0.5 )\n    Infinity\n    > v = base.beta( 1.0, 1.0 )\n    1.0\n    > v = base.beta( -1.0, 2.0 )\n    NaN\n    > v = base.beta( 5.0, 0.2 )\n    ~3.382\n    > v = base.beta( 4.0, 1.0 )\n    0.25\n    > v = base.beta( NaN, 2.0 )\n    NaN\n\n    See Also\n    --------\n    base.betainc, base.betaincinv, base.betaln\n","base.betainc":"\nbase.betainc( x, a, b[, regularized[, upper]] )\n    Computes the regularized incomplete beta function.\n\n    The `regularized` and `upper` parameters specify whether to evaluate the\n    non-regularized and/or upper incomplete beta functions, respectively.\n\n    If provided `x < 0` or `x > 1`, the function returns `NaN`.\n\n    If provided `a < 0` or `b < 0`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        First function parameter.\n\n    a: number\n        Second function parameter.\n\n    b: number\n        Third function parameter.\n\n    regularized: boolean (optional)\n        Boolean indicating whether the function should evaluate the regularized\n        or non-regularized incomplete beta function. Default: `true`.\n\n    upper: boolean (optional)\n        Boolean indicating whether the function should return the upper tail of\n        the incomplete beta function. Default: `false`.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.betainc( 0.5, 2.0, 2.0 )\n    0.5\n    > y = base.betainc( 0.5, 2.0, 2.0, false )\n    ~0.083\n    > y = base.betainc( 0.2, 1.0, 2.0 )\n    0.36\n    > y = base.betainc( 0.2, 1.0, 2.0, true, true )\n    0.64\n    > y = base.betainc( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.betainc( 0.8, NaN, 1.0 )\n    NaN\n    > y = base.betainc( 0.8, 1.0, NaN )\n    NaN\n    > y = base.betainc( 1.5, 1.0, 1.0 )\n    NaN\n    > y = base.betainc( -0.5, 1.0, 1.0 )\n    NaN\n    > y = base.betainc( 0.5, -2.0, 2.0 )\n    NaN\n    > y = base.betainc( 0.5, 2.0, -2.0 )\n    NaN\n\n    See Also\n    --------\n    base.beta, base.betaincinv, base.betaln\n","base.betaincinv":"\nbase.betaincinv( p, a, b[, upper] )\n    Computes the inverse of the lower incomplete beta function.\n\n    In contrast to a more commonly used definition, the first argument is the\n    probability `p` and the second and third arguments are `a` and `b`,\n    respectively.\n\n    By default, the function inverts the lower regularized incomplete beta\n    function. To invert the upper function, set the `upper` argument to `true`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Probability.\n\n    a: number\n        Second function parameter.\n\n    b: number\n        Third function parameter.\n\n    upper: boolean (optional)\n        Boolean indicating if the function should invert the upper tail of the\n        incomplete beta function. Default: `false`.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.betaincinv( 0.2, 3.0, 3.0 )\n    ~0.327\n    > y = base.betaincinv( 0.4, 3.0, 3.0 )\n    ~0.446\n    > y = base.betaincinv( 0.4, 3.0, 3.0, true )\n    ~0.554\n    > y = base.betaincinv( 0.4, 1.0, 6.0 )\n    ~0.082\n    > y = base.betaincinv( 0.8, 1.0, 6.0 )\n    ~0.235\n    > y = base.betaincinv( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.betaincinv( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.betaincinv( 0.5, 1.0, NaN )\n    NaN\n    > y = base.betaincinv( 1.2, 1.0, 1.0 )\n    NaN\n    > y = base.betaincinv( -0.5, 1.0, 1.0 )\n    NaN\n    > y = base.betaincinv( 0.5, -2.0, 2.0 )\n    NaN\n    > y = base.betaincinv( 0.5, 0.0, 2.0 )\n    NaN\n    > y = base.betaincinv( 0.5, 2.0, -2.0 )\n    NaN\n    > y = base.betaincinv( 0.5, 2.0, 0.0 )\n    NaN\n\n    See Also\n    --------\n    base.beta, base.betainc, base.betaln\n","base.betaln":"\nbase.betaln( a, b )\n    Evaluates the natural logarithm of the beta function.\n\n    Parameters\n    ----------\n    a: number\n        First function parameter (nonnegative).\n\n    b: number\n        Second function parameter (nonnegative).\n\n    Returns\n    -------\n    out: number\n        Natural logarithm of the beta function.\n\n    Examples\n    --------\n    > var v = base.betaln( 0.0, 0.0 )\n    Infinity\n    > v = base.betaln( 1.0, 1.0 )\n    0.0\n    > v = base.betaln( -1.0, 2.0 )\n    NaN\n    > v = base.betaln( 5.0, 0.2 )\n    ~1.218\n    > v = base.betaln( 4.0, 1.0 )\n    ~-1.386\n    > v = base.betaln( NaN, 2.0 )\n    NaN\n\n    See Also\n    --------\n    base.beta, base.betainc, base.betaincinv\n","base.binet":"\nbase.binet( x )\n    Evaluates Binet's formula extended to real numbers.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function result.\n\n    Examples\n    --------\n    > var y = base.binet( 0.0 )\n    0.0\n    > y = base.binet( 1.0 )\n    1.0\n    > y = base.binet( 2.0 )\n    1.0\n    > y = base.binet( 3.0 )\n    2.0\n    > y = base.binet( 4.0 )\n    3.0\n    > y = base.binet( 5.0 )\n    ~5.0\n    > y = base.binet( NaN )\n    NaN\n\n    See Also\n    --------\n    base.fibonacci, base.negafibonacci\n","base.binomcoef":"\nbase.binomcoef( n, k )\n    Computes the binomial coefficient of two integers.\n\n    If `k < 0`, the function returns `0`.\n\n    The function returns `NaN` for non-integer `n` or `k`.\n\n    Parameters\n    ----------\n    n: integer\n        First input value.\n\n    k: integer\n        Second input value.\n\n    Returns\n    -------\n    out: number\n        Function value.\n\n    Examples\n    --------\n    > var v = base.binomcoef( 8, 2 )\n    28\n    > v = base.binomcoef( 0, 0 )\n    1\n    > v = base.binomcoef( -4, 2 )\n    10\n    > v = base.binomcoef( 5, 3 )\n    10\n    > v = base.binomcoef( NaN, 3 )\n    NaN\n    > v = base.binomcoef( 5, NaN )\n    NaN\n    > v = base.binomcoef( NaN, NaN )\n    NaN\n\n","base.binomcoefln":"\nbase.binomcoefln( n, k )\n    Computes the natural logarithm of the binomial coefficient of two integers.\n\n    If `k < 0`, the function returns negative infinity.\n\n    The function returns `NaN` for non-integer `n` or `k`.\n\n    Parameters\n    ----------\n    n: integer\n        First input value.\n\n    k: integer\n        Second input value.\n\n    Returns\n    -------\n    out: number\n        Natural logarithm of the binomial coefficient.\n\n    Examples\n    --------\n    > var v = base.binomcoefln( 8, 2 )\n    ~3.332\n    > v = base.binomcoefln( 0, 0 )\n    0.0\n    > v = base.binomcoefln( -4, 2 )\n    ~2.303\n    > v = base.binomcoefln( 88, 3 )\n    ~11.606\n    > v = base.binomcoefln( NaN, 3 )\n    NaN\n    > v = base.binomcoefln( 5, NaN )\n    NaN\n    > v = base.binomcoefln( NaN, NaN )\n    NaN\n\n","base.boxcox":"\nbase.boxcox( x, lambda )\n    Computes a one-parameter Box-Cox transformation.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    lambda: number\n        Power parameter.\n\n    Returns\n    -------\n    b: number\n        Function value.\n\n    Examples\n    --------\n    > var v = base.boxcox( 1.0, 2.5 )\n    0.0\n    > v = base.boxcox( 4.0, 2.5 )\n    12.4\n    > v = base.boxcox( 10.0, 2.5 )\n    ~126.0911\n    > v = base.boxcox( 2.0, 0.0 )\n    ~0.6931\n    > v = base.boxcox( -1.0, 2.5 )\n    NaN\n    > v = base.boxcox( 0.0, -1.0 )\n    -Infinity\n\n    See Also\n    --------\n    base.boxcoxinv, base.boxcox1p, base.boxcox1pinv","base.boxcox1p":"\nbase.boxcox1p( x, lambda )\n    Computes a one-parameter Box-Cox transformation of 1+x.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    lambda: number\n        Power parameter.\n\n    Returns\n    -------\n    b: number\n        Function value.\n\n    Examples\n    --------\n    > var v =  base.boxcox1p( 1.0, 2.5 )\n    ~1.8627\n    > v = base.boxcox1p( 4.0, 2.5 )\n    ~21.9607\n    > v = base.boxcox1p( 10.0, 2.5 )\n    ~160.1246\n    > v = base.boxcox1p( 2.0, 0.0 )\n    ~1.0986\n    > v = base.boxcox1p( -1.0, 2.5 )\n    -0.4\n    > v = base.boxcox1p( 0.0, -1.0 )\n    0.0\n    > v = base.boxcox1p( -1.0, -1.0 )\n    -Infinity\n\n    See Also\n    --------\n    base.boxcox, base.boxcox1pinv, base.boxcoxinv","base.boxcox1pinv":"\nbase.boxcox1pinv( y, lambda )\n    Computes the inverse of a one-parameter Box-Cox transformation for 1+x.\n\n    Parameters\n    ----------\n    y: number\n        Input value.\n\n    lambda: number\n        Power parameter.\n\n    Returns\n    -------\n    v: number\n        Function value.\n\n    Examples\n    --------\n    > var v = base.boxcox1pinv( 1.0, 2.5 )\n    ~0.6505\n    > v = base.boxcox1pinv( 4.0, 2.5 )\n    ~1.6095\n    > v = base.boxcox1pinv( 10.0, 2.5 )\n    ~2.6812\n    > v = base.boxcox1pinv( 2.0, 0.0 )\n    ~6.3891\n    > v = base.boxcox1pinv( -1.0, 2.5 )\n    NaN\n    > v = base.boxcox1pinv( 0.0, -1.0 )\n    0.0\n    > v = base.boxcox1pinv( 1.0, NaN )\n    NaN\n    > v = base.boxcox1pinv( NaN, 3.1 )\n    NaN\n\n    See Also\n    --------\n    base.boxcox, base.boxcox1p, base.boxcoxinv","base.boxcoxinv":"\nbase.boxcoxinv( y, lambda )\n    Computes the inverse of a one-parameter Box-Cox transformation.\n\n    Parameters\n    ----------\n    y: number\n        Input value.\n\n    lambda: number\n        Power parameter.\n\n    Returns\n    -------\n    b: number\n        Function value.\n\n    Examples\n    --------\n    > var v = base.boxcoxinv( 1.0, 2.5 )\n    ~1.6505\n    > v = base.boxcoxinv( 4.0, 2.5 )\n    ~2.6095\n    > v = base.boxcoxinv( 10.0, 2.5 )\n    ~3.6812\n    > v = base.boxcoxinv( 2.0, 0.0 )\n    ~7.3891\n    > v = base.boxcoxinv( -1.0, 2.5 )\n    NaN\n    > v = base.boxcoxinv( 0.0, -1.0 )\n    1.0\n    > v = base.boxcoxinv( 1.0, NaN )\n    NaN\n    > v = base.boxcoxinv( NaN, 3.1 )\n    NaN\n\n    See Also\n    --------\n    base.boxcox, base.boxcox1p, base.boxcox1pinv","base.cabs":"\nbase.cabs( z )\n    Computes the absolute value of a double-precision complex floating-point\n    number.\n\n    The absolute value of a complex number is its distance from zero.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    y: number\n        Absolute value.\n\n    Examples\n    --------\n    > var y = base.cabs( new Complex128( 5.0, 3.0 ) )\n    ~5.831\n\n    See Also\n    --------\n    base.cabs2, base.abs\n","base.cabs2":"\nbase.cabs2( z )\n    Computes the squared absolute value of a double-precision complex floating-\n    point number.\n\n    The absolute value of a complex number is its distance from zero.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    y: number\n        Squared absolute value.\n\n    Examples\n    --------\n    > var y = base.cabs2( new Complex128( 5.0, 3.0 ) )\n    34.0\n\n    See Also\n    --------\n    base.cabs, base.abs2\n","base.cabs2f":"\nbase.cabs2f( z )\n    Computes the squared absolute value of a single-precision complex floating-\n    point number.\n\n    The absolute value of a complex number is its distance from zero.\n\n    Parameters\n    ----------\n    z: Complex64\n        Complex number.\n\n    Returns\n    -------\n    y: number\n        Squared absolute value.\n\n    Examples\n    --------\n    > var y = base.cabs2f( new Complex64( 5.0, 3.0 ) )\n    34.0\n\n    See Also\n    --------\n    base.cabs2, base.cabsf, base.abs2f\n","base.cabsf":"\nbase.cabsf( z )\n    Computes the absolute value of a single-precision complex floating-point\n    number.\n\n    The absolute value of a complex number is its distance from zero.\n\n    Parameters\n    ----------\n    z: Complex64\n        Complex number.\n\n    Returns\n    -------\n    y: number\n        Absolute value.\n\n    Examples\n    --------\n    > var y = base.cabsf( new Complex64( 5.0, 3.0 ) )\n    ~5.831\n\n    See Also\n    --------\n    base.cabs, base.cabs2f, base.absf\n","base.cadd":"\nbase.cadd( z1, z2 )\n    Adds two double-precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    z1: Complex128\n        Complex number.\n\n    z2: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Result.\n\n    Examples\n    --------\n    > var z = new Complex128( 5.0, 3.0 )\n    <Complex128>\n    > var out = base.cadd( z, z )\n    <Complex128>\n    > var re = real( out )\n    10.0\n    > var im = imag( out )\n    6.0\n\n    See Also\n    --------\n    base.cdiv, base.cmul, base.csub\n","base.caddf":"\nbase.caddf( z1, z2 )\n    Adds two single-precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    z1: Complex64\n        Complex number.\n\n    z2: Complex64\n        Complex number.\n\n    Returns\n    -------\n    out: Complex64\n        Result.\n\n    Examples\n    --------\n    > var z = new Complex64( 5.0, 3.0 )\n    <Complex64>\n    > var out = base.caddf( z, z )\n    <Complex64>\n    > var re = realf( out )\n    10.0\n    > var im = imagf( out )\n    6.0\n\n    See Also\n    --------\n    base.cadd, base.cmulf, base.csubf\n","base.camelcase":"\nbase.camelcase( str )\n    Converts a string to camel case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Camel-cased string.\n\n    Examples\n    --------\n    > var out = base.camelcase( 'Hello World!' )\n    'helloWorld'\n    > out = base.camelcase( 'beep boop' )\n    'beepBoop'\n\n    See Also\n    --------\n    base.constantcase, base.lowercase, base.snakecase, base.uppercase","base.capitalize":"\nbase.capitalize( str )\n    Capitalizes the first character in a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Capitalized string.\n\n    Examples\n    --------\n    > var out = base.capitalize( 'beep' )\n    'Beep'\n    > out = base.capitalize( 'Boop' )\n    'Boop'\n\n    See Also\n    --------\n    base.lowercase, base.uppercase\n","base.cbrt":"\nbase.cbrt( x )\n    Computes the cube root of a double-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Cube root.\n\n    Examples\n    --------\n    > var y = base.cbrt( 64.0 )\n    4.0\n    > y = base.cbrt( 27.0 )\n    3.0\n    > y = base.cbrt( 0.0 )\n    0.0\n    > y = base.cbrt( -0.0 )\n    -0.0\n    > y = base.cbrt( -9.0 )\n    ~-2.08\n    > y = base.cbrt( NaN )\n    NaN\n\n    See Also\n    --------\n    base.pow, base.sqrt\n","base.cbrtf":"\nbase.cbrtf( x )\n    Computes the cube root of a single-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Cube root.\n\n    Examples\n    --------\n    > var y = base.cbrtf( 64.0 )\n    4.0\n    > y = base.cbrtf( 27.0 )\n    3.0\n    > y = base.cbrtf( 0.0 )\n    0.0\n    > y = base.cbrtf( -0.0 )\n    -0.0\n    > y = base.cbrtf( -9.0 )\n    ~-2.08\n    > y = base.cbrtf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cbrt, base.sqrtf\n","base.cceil":"\nbase.cceil( z )\n    Rounds each component of a double-precision complex floating-point number\n    toward positive infinity.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Result.\n\n    Examples\n    --------\n    > var v = base.cceil( new Complex128( -1.5, 2.5 ) )\n    <Complex128>\n    > var re = real( v )\n    -1.0\n    > var im = imag( v )\n    3.0\n\n    See Also\n    --------\n    base.cceiln, base.cfloor, base.cround\n","base.cceilf":"\nbase.cceilf( z )\n    Rounds a single-precision complex floating-point number toward positive\n    infinity.\n\n    Parameters\n    ----------\n    z: Complex64\n        Complex number.\n\n    Returns\n    -------\n    out: Complex64\n        Result.\n\n    Examples\n    --------\n    > var v = base.cceilf( new Complex64( -1.5, 2.5 ) )\n    <Complex64>\n    > var re = realf( v )\n    -1.0\n    > var im = imagf( v )\n    3.0\n\n    See Also\n    --------\n    base.cceil\n","base.cceiln":"\nbase.cceiln( z, n )\n    Rounds each component of a double-precision complex number to the nearest\n    multiple of `10^n` toward positive infinity.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    n: integer\n        Integer power of 10.\n\n    Returns\n    -------\n    out: Complex128\n        Real and imaginary components.\n\n    Examples\n    --------\n    > var out = base.cceiln( new Complex128( 5.555, -3.333 ), -2 )\n    <Complex128>\n    > var re = real( out )\n    5.56\n    > var im = imag( out )\n    -3.33\n\n    See Also\n    --------\n    base.cceil, base.cfloorn, base.croundn\n","base.ccis":"\nbase.ccis( z )\n    Evaluates the cis function for a double-precision complex floating-point\n    number.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Complex number.\n\n    Examples\n    --------\n    > var y = base.ccis( new Complex128( 0.0, 0.0 ) )\n    <Complex128>\n    > var re = real( y )\n    1.0\n    > var im = imag( y )\n    0.0\n    > y = base.ccis( new Complex128( 1.0, 0.0 ) )\n    <Complex128>\n    > re = real( y )\n    ~0.540\n    > im = imag( y )\n    ~0.841\n\n","base.cdiv":"\nbase.cdiv( z1, z2 )\n    Divides two double-precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    z1: Complex128\n        Complex number.\n\n    z2: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Result.\n\n    Examples\n    --------\n    > var z1 = new Complex128( -13.0, -1.0 )\n    <Complex128>\n    > var z2 = new Complex128( -2.0, 1.0 )\n    <Complex128>\n    > var y = base.cdiv( z1, z2 )\n    <Complex128>\n    > var re = real( y )\n    5.0\n    > var im = imag( y )\n    3.0\n\n    See Also\n    --------\n    base.cadd, base.cmul, base.csub\n","base.ceil":"\nbase.ceil( x )\n    Rounds a double-precision floating-point number toward positive infinity.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.ceil( 3.14 )\n    4.0\n    > y = base.ceil( -4.2 )\n    -4.0\n    > y = base.ceil( -4.6 )\n    -4.0\n    > y = base.ceil( 9.5 )\n    10.0\n    > y = base.ceil( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceiln, base.floor, base.round\n","base.ceil2":"\nbase.ceil2( x )\n    Rounds a numeric value to the nearest power of two toward positive infinity.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.ceil2( 3.14 )\n    4.0\n    > y = base.ceil2( -4.2 )\n    -4.0\n    > y = base.ceil2( -4.6 )\n    -4.0\n    > y = base.ceil2( 9.5 )\n    16.0\n    > y = base.ceil2( 13.0 )\n    16.0\n    > y = base.ceil2( -13.0 )\n    -8.0\n    > y = base.ceil2( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceil, base.ceil10, base.floor2, base.round2\n","base.ceil10":"\nbase.ceil10( x )\n    Rounds a numeric value to the nearest power of ten toward positive infinity.\n\n    The function may not return accurate results for subnormals due to a general\n    loss in precision.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.ceil10( 3.14 )\n    10.0\n    > y = base.ceil10( -4.2 )\n    -1.0\n    > y = base.ceil10( -4.6 )\n    -1.0\n    > y = base.ceil10( 9.5 )\n    10.0\n    > y = base.ceil10( 13.0 )\n    100.0\n    > y = base.ceil10( -13.0 )\n    -10.0\n    > y = base.ceil10( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceil, base.ceil2, base.floor10, base.round10\n","base.ceilb":"\nbase.ceilb( x, n, b )\n    Rounds a numeric value to the nearest multiple of `b^n` toward positive\n    infinity.\n\n    Due to floating-point rounding error, rounding may not be exact.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Integer power.\n\n    b: integer\n        Base.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    // Round to 4 decimal places:\n    > var y = base.ceilb( 3.14159, -4, 10 )\n    3.1416\n\n    // If `n = 0` or `b = 1`, standard round behavior:\n    > y = base.ceilb( 3.14159, 0, 2 )\n    4.0\n\n    // Round to nearest multiple of two toward positive infinity:\n    > y = base.ceilb( 5.0, 1, 2 )\n    6.0\n\n    See Also\n    --------\n    base.ceil, base.ceiln, base.floorb, base.roundb\n","base.ceilf":"\nbase.ceilf( x )\n    Rounds a single-precision floating-point number toward positive infinity.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.ceilf( 3.14 )\n    4.0\n    > y = base.ceilf( -4.2 )\n    -4.0\n    > y = base.ceilf( -4.6 )\n    -4.0\n    > y = base.ceilf( 9.5 )\n    10.0\n    > y = base.ceilf( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.floorf\n","base.ceiln":"\nbase.ceiln( x, n )\n    Rounds a numeric value to the nearest multiple of `10^n` toward positive\n    infinity.\n\n    When operating on floating-point numbers in bases other than `2`, rounding\n    to specified digits can be inexact.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Integer power of 10.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    // Round to 2 decimal places:\n    > var y = base.ceiln( 3.14159, -2 )\n    3.15\n\n    // If `n = 0`, standard round toward positive infinity behavior:\n    > y = base.ceiln( 3.14159, 0 )\n    4.0\n\n    // Round to nearest thousand:\n    > y = base.ceiln( 12368.0, 3 )\n    13000.0\n\n\n    See Also\n    --------\n    base.ceil, base.ceilb, base.floorn, base.roundn\n","base.ceilsd":"\nbase.ceilsd( x, n, b )\n    Rounds a numeric value to the nearest number toward positive infinity with\n    `n` significant figures.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Number of significant figures. Must be greater than 0.\n\n    b: integer\n        Base. Must be greater than 0.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.ceilsd( 3.14159, 5, 10 )\n    3.1416\n    > y = base.ceilsd( 3.14159, 1, 10 )\n    4.0\n    > y = base.ceilsd( 12368.0, 2, 10 )\n    13000.0\n    > y = base.ceilsd( 0.0313, 2, 2 )\n    0.046875\n\n    See Also\n    --------\n    base.ceil, base.floorsd, base.roundsd, base.truncsd\n","base.cexp":"\nbase.cexp( z )\n    Evaluates the exponential function for a double-precision complex floating-\n    point number.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Complex number.\n\n    Examples\n    --------\n    > var y = base.cexp( new Complex128( 0.0, 0.0 ) )\n    <Complex128>\n    > var re = real( y )\n    1.0\n    > var im = imag( y )\n    0.0\n    > y = base.cexp( new Complex128( 0.0, 1.0 ) )\n    <Complex128>\n    > re = real( y )\n    ~0.540\n    > im = imag( y )\n    ~0.841\n\n","base.cflipsign":"\nbase.cflipsign( z, y )\n    Returns a double-precision complex floating-point number with the same\n    magnitude as `z` and the sign of `y*z`.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    y: number\n        Number from which to derive the sign.\n\n    Returns\n    -------\n    out: Complex128\n        Result.\n\n    Examples\n    --------\n    > var v = base.cflipsign( new Complex128( -4.2, 5.5 ), -9.0 )\n    <Complex128>\n    > var re = real( v )\n    4.2\n    > var im = imag( v )\n    -5.5\n\n    See Also\n    --------\n    base.cneg, base.csignum\n","base.cflipsignf":"\nbase.cflipsignf( z, y )\n    Returns a single-precision complex floating-point number with the same\n    magnitude as `z` and the sign of `y*z`.\n\n    Parameters\n    ----------\n    z: Complex64\n        Complex number.\n\n    y: number\n        Number from which to derive the sign.\n\n    Returns\n    -------\n    out: Complex64\n        Result.\n\n    Examples\n    --------\n    > var v = base.cflipsignf( new Complex64( -4.0, 5.0 ), -9.0 )\n    <Complex64>\n    > var re = realf( v )\n    4.0\n    > var im = imagf( v )\n    -5.0\n\n    See Also\n    --------\n    base.cnegf, base.cflipsign\n","base.cfloor":"\nbase.cfloor( z )\n    Rounds a double-precision complex floating-point number toward negative\n    infinity.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Result.\n\n    Examples\n    --------\n    > var v = base.cfloor( new Complex128( 5.5, 3.3 ) )\n    <Complex128>\n    > var re = real( v )\n    5.0\n    > var im = imag( v )\n    3.0\n\n    See Also\n    --------\n    base.cceil, base.cfloorn, base.cround\n","base.cfloorn":"\nbase.cfloorn( z, n )\n    Rounds each component of a double-precision complex floating-point number\n    to the nearest multiple of `10^n` toward negative infinity.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    n: integer\n        Integer power of 10.\n\n    Returns\n    -------\n    z: Complex128\n        Result.\n\n    Examples\n    --------\n    > var v = base.cfloorn( new Complex128( 5.555, -3.333 ), -2 )\n    <Complex128>\n    > var re = real( v )\n    5.55\n    > var im = imag( v )\n    -3.34\n\n    See Also\n    --------\n    base.cceiln, base.cfloor, base.croundn\n","base.cidentity":"\nbase.cidentity( z )\n    Evaluates the identity function for a double-precision complex floating-\n    point number.\n\n    Parameters\n    ----------\n    z: Complex128\n        Input value.\n\n    Returns\n    -------\n    v: Complex128\n        Input value.\n\n    Examples\n    --------\n    > var v = base.cidentity( new Complex128( -1.0, 2.0 ) )\n    <Complex128>\n    > var re = real( v )\n    -1.0\n    > var img = imag( v )\n    2.0\n\n    See Also\n    --------\n    base.cidentityf, base.identity\n","base.cidentityf":"\nbase.cidentityf( z )\n    Evaluates the identity function for a single-precision complex floating-\n    point number.\n\n    Parameters\n    ----------\n    z: Complex64\n        Input value.\n\n    Returns\n    -------\n    v: Complex64\n        Input value.\n\n    Examples\n    --------\n    > var v = base.cidentityf( new Complex64( -1.0, 2.0 ) )\n    <Complex64>\n    > var re = realf( v )\n    -1.0\n    > var img = imagf( v )\n    2.0\n\n    See Also\n    --------\n    base.cidentity, base.identityf\n","base.cinv":"\nbase.cinv( z )\n    Computes the inverse of a double-precision complex floating-point number.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Result.\n\n    Examples\n    --------\n    > var v = base.cinv( new Complex128( 2.0, 4.0 ) )\n    <Complex128>\n    > var re = real( v )\n    0.1\n    > var im = imag( v )\n    -0.2\n\n    See Also\n    --------\n    base.cdiv\n","base.clamp":"\nbase.clamp( v, min, max )\n    Restricts a double-precision floating-point number to a specified range.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    v: number\n        Value to restrict.\n\n    min: number\n        Minimum value.\n\n    max: number\n        Maximum value.\n\n    Returns\n    -------\n    y: number\n        Restricted value.\n\n    Examples\n    --------\n    > var y = base.clamp( 3.14, 0.0, 5.0 )\n    3.14\n    > y = base.clamp( -3.14, 0.0, 5.0 )\n    0.0\n    > y = base.clamp( 3.14, 0.0, 3.0 )\n    3.0\n    > y = base.clamp( -0.0, 0.0, 5.0 )\n    0.0\n    > y = base.clamp( 0.0, -3.14, -0.0 )\n    -0.0\n    > y = base.clamp( NaN, 0.0, 5.0 )\n    NaN\n\n    See Also\n    --------\n    base.clampf, base.wrap\n","base.clampf":"\nbase.clampf( v, min, max )\n    Restricts a single-precision floating-point number to a specified range.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    v: number\n        Value to restrict.\n\n    min: number\n        Minimum value.\n\n    max: number\n        Maximum value.\n\n    Returns\n    -------\n    y: number\n        Restricted value.\n\n    Examples\n    --------\n    > var y = base.clampf( 3.14, 0.0, 5.0 )\n    3.14\n    > y = base.clampf( -3.14, 0.0, 5.0 )\n    0.0\n    > y = base.clampf( 3.14, 0.0, 3.0 )\n    3.0\n    > y = base.clampf( -0.0, 0.0, 5.0 )\n    0.0\n    > y = base.clampf( 0.0, -3.14, -0.0 )\n    -0.0\n    > y = base.clampf( NaN, 0.0, 5.0 )\n    NaN\n\n    See Also\n    --------\n    base.clamp\n","base.cmul":"\nbase.cmul( z1, z2 )\n    Multiplies two double-precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    z1: Complex128\n        Complex number.\n\n    z2: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Result.\n\n    Examples\n    --------\n    > var z1 = new Complex128( 5.0, 3.0 )\n    <Complex128>\n    > var z2 = new Complex128( -2.0, 1.0 )\n    <Complex128>\n    > var out = base.cmul( z1, z2 )\n    <Complex128>\n    > var re = real( out )\n    -13.0\n    > var im = imag( out )\n    -1.0\n\n    See Also\n    --------\n    base.cadd, base.cdiv, base.csub\n","base.cmulf":"\nbase.cmulf( z1, z2 )\n    Multiplies two single-precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    z1: Complex64\n        Complex number.\n\n    z2: Complex64\n        Complex number.\n\n    Returns\n    -------\n    out: Complex64\n        Result.\n\n    Examples\n    --------\n    > var z1 = new Complex64( 5.0, 3.0 )\n    <Complex64>\n    > var z2 = new Complex64( -2.0, 1.0 )\n    <Complex64>\n    > var out = base.cmulf( z1, z2 )\n    <Complex64>\n    > var re = realf( out )\n    -13.0\n    > var im = imagf( out )\n    -1.0\n\n    See Also\n    --------\n    base.caddf, base.cmul, base.csubf\n","base.cneg":"\nbase.cneg( z )\n    Negates a double-precision complex floating-point number.\n\n    Parameters\n    ----------\n    z: Complex128\n       Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Result.\n\n    Examples\n    --------\n    > var z = new Complex128( -4.2, 5.5 )\n    <Complex128>\n    > var v = base.cneg( z )\n    <Complex128>\n    > var re = real( v )\n    4.2\n    > var im = imag( v )\n    -5.5\n\n    See Also\n    --------\n    base.cabs\n","base.cnegf":"\nbase.cnegf( z )\n    Negates a single-precision complex floating-point number.\n\n    Parameters\n    ----------\n    z: Complex64\n       Complex number.\n\n    Returns\n    -------\n    out: Complex64\n        Result.\n\n    Examples\n    --------\n    > var z = new Complex64( -4.0, 5.0 )\n    <Complex64>\n    > var v = base.cnegf( z )\n    <Complex64>\n    > var re = realf( v )\n    4.0\n    > var im = imagf( v )\n    -5.0\n\n    See Also\n    --------\n    base.cneg, base.cabsf\n","base.codePointAt":"\nbase.codePointAt( str, idx, backward )\n    Returns a Unicode code point from a string at a specified position.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    idx: integer\n        Position. If less than `0`, the string position is determined relative\n        to the end of the input string.\n\n    backward: boolean\n        Backward iteration for low surrogates.\n\n    Returns\n    -------\n    out: integer\n        Unicode code point.\n\n    Examples\n    --------\n    > var out = base.codePointAt( 'last man standing', 4, false )\n    32\n    > out = base.codePointAt( 'presidential election', 8, true )\n    116\n    > out = base.codePointAt( 'अनुच्छेद', 2, false )\n    2369\n    > out = base.codePointAt( '🌷', 1, true )\n    127799\n","base.constantcase":"\nbase.constantcase( str )\n    Converts a string to constant case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Constant-cased string.\n\n    Examples\n    --------\n    > var out = base.constantcase( 'Hello World!' )\n    'HELLO_WORLD'\n    > out = base.constantcase( 'I am a tiny little teapot' )\n    'I_AM_A_TINY_LITTLE_TEAPOT'\n\n    See Also\n    --------\n    base.camelcase, base.lowercase, base.snakecase, base.uppercase","base.continuedFraction":"\nbase.continuedFraction( generator[, options] )\n    Evaluates the continued fraction approximation for the supplied series\n    generator using the modified Lentz algorithm.\n\n    `generator` can be either a function which returns an array with two\n    elements, the `a` and `b` terms of the fraction, or an ES6 Generator object.\n\n    By default, the function computes\n\n             a1\n        ---------------\n        b1 +     a2\n             ----------\n              b2 +   a3\n                  -----\n                  b3 + ...\n\n    To evaluate\n\n        b0 +\t a1\n        ---------------\n        b1 +\t a2\n             ----------\n             b2 +  a3\n                  -----\n                  b3 + ...\n\n    set the `keep` option to `true`.\n\n    Parameters\n    ----------\n    generator: Function\n        Function returning terms of continued fraction expansion.\n\n    options: Object (optional)\n        Options.\n\n    options.maxIter: integer (optional)\n         Maximum number of iterations. Default: `1000000`.\n\n    options.tolerance: number (optional)\n        Further terms are only added as long as the next term is greater than\n        current term times the tolerance. Default: `2.22e-16`.\n\n    options.keep: boolean (optional)\n        Boolean indicating whether to keep the `b0` term in the continued\n        fraction. Default: `false`.\n\n    Returns\n    -------\n    out: number\n       Value of continued fraction.\n\n    Examples\n    --------\n    // Continued fraction for (e-1)^(-1):\n    > function closure() {\n    ...    var i = 0;\n    ...    return function() {\n    ...        i += 1;\n    ...        return [ i, i ];\n    ...    };\n    ... };\n    > var gen = closure();\n    > var out = base.continuedFraction( gen )\n    ~0.582\n\n    // Using an ES6 generator:\n    > function* generator() {\n    ...     var i = 0;\n    ...     while ( true ) {\n    ...         i += 1;\n    ...         yield [ i, i ];\n    ...     }\n    ... };\n    > gen = generator();\n    > out = base.continuedFraction( gen )\n    ~0.582\n\n    // Set options:\n    > out = base.continuedFraction( generator(), { 'keep': true } )\n    ~1.718\n    > out = base.continuedFraction( generator(), { 'maxIter': 10 } )\n    ~0.582\n    > out = base.continuedFraction( generator(), { 'tolerance': 1e-1 } )\n    ~0.579\n\n","base.copysign":"\nbase.copysign( x, y )\n    Returns a double-precision floating-point number with the magnitude of `x`\n    and the sign of `y`.\n\n    Parameters\n    ----------\n    x: number\n        Number from which to derive a magnitude.\n\n    y: number\n        Number from which to derive a sign.\n\n    Returns\n    -------\n    z: number\n        Double-precision floating-point number.\n\n    Examples\n    --------\n    > var z = base.copysign( -3.14, 10.0 )\n    3.14\n    > z = base.copysign( 3.14, -1.0 )\n    -3.14\n    > z = base.copysign( 1.0, -0.0 )\n    -1.0\n    > z = base.copysign( -3.14, -0.0 )\n    -3.14\n    > z = base.copysign( -0.0, 1.0 )\n    0.0\n\n    See Also\n    --------\n    base.flipsign\n","base.copysignf":"\nbase.copysignf( x, y )\n    Returns a single-precision floating-point number with the magnitude of `x`\n    and the sign of `y`.\n\n    Parameters\n    ----------\n    x: number\n        Number from which to derive a magnitude.\n\n    y: number\n        Number from which to derive a sign.\n\n    Returns\n    -------\n    z: number\n        Single-precision floating-point number.\n\n    Examples\n    --------\n    > var z = base.copysignf( -3.0, 10.0 )\n    3.0\n    > z = base.copysignf( 3.0, -1.0 )\n    -3.0\n    > z = base.copysignf( 1.0, -0.0 )\n    -1.0\n    > z = base.copysignf( -3.0, -0.0 )\n    -3.0\n    > z = base.copysignf( -0.0, 1.0 )\n    0.0\n\n    See Also\n    --------\n    base.copysign, base.flipsignf\n","base.cos":"\nbase.cos( x )\n    Computes the cosine of a number.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Cosine.\n\n    Examples\n    --------\n    > var y = base.cos( 0.0 )\n    1.0\n    > y = base.cos( PI/4.0 )\n    ~0.707\n    > y = base.cos( -PI/6.0 )\n    ~0.866\n    > y = base.cos( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cospi, base.cosm1, base.sin, base.tan\n","base.cosd":"\nbase.cosd( x )\n    Computes the cosine of an angle measured in degrees.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in degrees).\n\n    Returns\n    -------\n    y: number\n        Cosine.\n\n    Examples\n    --------\n    > var y = base.cosd( 0.0 )\n    1.0\n    > y = base.cosd( 90.0 )\n    0.0\n    > y = base.cosd( 60.0 )\n    ~0.5\n    > y = base.cosd( NaN )\n    NaN\n\n    See Also\n    --------\n    base.tand\n","base.cosh":"\nbase.cosh( x )\n    Computes the hyperbolic cosine of a double-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Hyperbolic cosine.\n\n    Examples\n    --------\n    > var y = base.cosh( 0.0 )\n    1.0\n    > y = base.cosh( 2.0 )\n    ~3.762\n    > y = base.cosh( -2.0 )\n    ~3.762\n    > y = base.cosh( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cos, base.sinh, base.tanh\n","base.cosm1":"\nbase.cosm1( x )\n    Computes the cosine of a number minus one.\n\n    This function should be used instead of manually calculating `cos(x)-1` when\n    `x` is near unity.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Cosine minus one.\n\n    Examples\n    --------\n    > var y = base.cosm1( 0.0 )\n    0.0\n    > y = base.cosm1( PI/4.0 )\n    ~-0.293\n    > y = base.cosm1( -PI/6.0 )\n    ~-0.134\n    > y = base.cosm1( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cos\n","base.cospi":"\nbase.cospi( x )\n    Computes the value of `cos(πx)`.\n\n    This function computes `cos(πx)` more accurately than the obvious approach,\n    especially for large `x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.cospi( 0.0 )\n    1.0\n    > y = base.cospi( 0.5 )\n    0.0\n    > y = base.cospi( 0.1 )\n    ~0.951\n    > y = base.cospi( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cos\n","base.cot":"\nbase.cot( x )\n    Computes the cotangent of a number.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Cotangent.\n\n    Examples\n    --------\n    > var y = base.cot( 0.0 )\n    Infinity\n    > y = base.cot( -PI/4.0 )\n    ~-1.0\n    > y = base.cot( PI/4.0 )\n    ~1.0\n    > y = base.cot( NaN )\n    NaN\n\n    See Also\n    --------\n    base.csc, base.tan\n","base.cotd":"\nbase.cotd( x )\n    Computes the cotangent of an angle measured in degrees.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in degrees).\n\n    Returns\n    -------\n    y: number\n        Cotangent.\n\n    Examples\n    --------\n    > var y = base.cotd( 0.0 )\n    Infinity\n    > y = base.cotd( 90.0 )\n    0.0\n    > y = base.cotd( 60.0 )\n    ~0.58\n    > y = base.cotd( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cscd, base.secd, base.tand\n","base.coth":"\nbase.coth( x )\n    Computes the hyperbolic cotangent of a number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Hyperbolic cotangent.\n\n    Examples\n    --------\n    > var y = base.coth( 0.0 )\n    Infinity\n    > y = base.coth( -0.0 )\n    -Infinity\n    > y = base.coth( 2.0 )\n    ~1.0373\n    > y = base.coth( -2.0 )\n    ~-1.0373\n    > y = base.coth( +Infinity )\n    ~1\n    > y = base.coth( -Infinity )\n    ~-1\n    > y = base.coth( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acoth, base.cot, base.csch, base.tanh\n","base.covercos":"\nbase.covercos( x )\n    Computes the coversed cosine.\n\n    The coversed cosine is defined as `1 + sin(x)`.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Coversed cosine.\n\n    Examples\n    --------\n    > var y = base.covercos( 3.14 )\n    ~1.0016\n    > y = base.covercos( -4.2 )\n    ~1.8716\n    > y = base.covercos( -4.6 )\n    ~1.9937\n    > y = base.covercos( 9.5 )\n    ~0.9248\n    > y = base.covercos( -0.0 )\n    1.0\n\n    See Also\n    --------\n    base.coversin, base.vercos\n","base.coversin":"\nbase.coversin( x )\n    Computes the coversed sine.\n\n    The coversed sine is defined as `1 - sin(x)`.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Coversed sine.\n\n    Examples\n    --------\n    > var y = base.coversin( 3.14 )\n    ~0.9984\n    > y = base.coversin( -4.2 )\n    ~0.1284\n    > y = base.coversin( -4.6 )\n    ~0.0063\n    > y = base.coversin( 9.5 )\n    ~1.0752\n    > y = base.coversin( -0.0 )\n    1.0\n\n    See Also\n    --------\n    base.covercos, base.versin\n","base.cphase":"\nbase.cphase( z )\n    Computes the argument of a double-precision complex floating-point number\n    in radians.\n\n    The argument of a complex number, also known as the phase, is the angle of\n    the radius extending from the origin to the complex number plotted in the\n    complex plane and the positive real axis.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    phi: number\n        Argument.\n\n    Examples\n    --------\n    > var phi = base.cphase( new Complex128( 5.0, 3.0 ) )\n    ~0.5404\n\n    See Also\n    --------\n    base.cabs\n","base.cpolar":"\nbase.cpolar( z )\n    Returns the absolute value and phase of a double-precision complex\n    floating-point number.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Array<number>\n        Absolute value and phase, respectively.\n\n    Examples\n    --------\n    > var out = base.cpolar( new Complex128( 5.0, 3.0 ) )\n    [ ~5.83, ~0.5404 ]\n\n\nbase.cpolar.assign( z, out, stride, offset )\n    Returns the absolute value and phase of a double-precision complex\n    floating-point number and assigns results to a provided output array.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    out: Array|TypedArray|Object\n        Destination array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Absolute value and phase, respectively.\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var v = base.cpolar.assign( new Complex128( 5.0, 3.0 ), out, 1, 0 )\n    <Float64Array>[ ~5.83, ~0.5404 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.cabs, base.cphase","base.cpolar.assign":"\nbase.cpolar.assign( z, out, stride, offset )\n    Returns the absolute value and phase of a double-precision complex\n    floating-point number and assigns results to a provided output array.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    out: Array|TypedArray|Object\n        Destination array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Absolute value and phase, respectively.\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var v = base.cpolar.assign( new Complex128( 5.0, 3.0 ), out, 1, 0 )\n    <Float64Array>[ ~5.83, ~0.5404 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.cabs, base.cphase","base.cround":"\nbase.cround( z )\n    Rounds each component of a double-precision complex floating-point number\n    to the nearest integer.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Rounded complex number.\n\n    Examples\n    --------\n    > var v = base.cround( new Complex128( 5.5, 3.3 ) )\n    <Complex128>\n    > var re = real( v )\n    6.0\n    > var im = imag( v )\n    3.0\n\n    See Also\n    --------\n    base.cceil, base.cfloor, base.croundn\n","base.croundn":"\nbase.croundn( z, n )\n    Rounds each component of a double-precision complex floating-point number\n    to the nearest multiple of `10^n`.\n\n    When operating on floating-point numbers in bases other than `2`, rounding\n    to specified digits can be inexact.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    n: integer\n        Integer power of 10.\n\n    Returns\n    -------\n    out: Complex128\n        Result.\n\n    Examples\n    --------\n    > var v = base.croundn( new Complex128( 5.555, -3.336 ), -2 )\n    <Complex128>\n    > var re = real( v )\n    5.56\n    > var im = imag( v )\n    -3.34\n\n    See Also\n    --------\n    base.cceiln, base.cfloorn, base.cround\n","base.csc":"\nbase.csc( x )\n    Computes the cosecant of a number.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Cosecant.\n\n    Examples\n    --------\n    > var y = base.csc( 0.0 )\n    Infinity\n    > y = base.csc( PI/2.0 )\n    ~1.0\n    > y = base.csc( -PI/6.0 )\n    ~-2.0\n    > y = base.csc( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cot, base.sin","base.cscd":"\nbase.cscd( x )\n    Computes the cosecant of a degree.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in degrees).\n\n    Returns\n    -------\n    y: number\n        Cosecant.\n\n    Examples\n    --------\n    > var y = base.cscd( 1.0 )\n    ~57.30\n    > y = base.cscd( PI )\n    ~18.25\n    > y = base.cscd( -PI )\n    ~-18.25\n    > y = base.cscd( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cotd, base.secd\n","base.csch":"\nbase.csch( x )\n    Computes the hyperbolic cosecant of a number.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Hyperbolic cosecant.\n\n    Examples\n    --------\n    > var y = base.csch( +0.0 )\n    +Infinity\n    > var y = base.csch( -0.0 )\n    -Infinity\n    > var y = base.csch( +Infinity )\n    +0.0\n    > var y = base.csch( -Infinity )\n    -0.0\n    > y = base.csch( 2.0 )\n    ~0.2757\n    > y = base.csch( -2.0 )\n    ~-0.2757\n    > y = base.csch( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acsch, base.csc, base.coth, base.sinh\n","base.csignum":"\nbase.csignum( z )\n    Evaluates the signum function of a double-precision complex floating-point\n    number.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Result.\n\n    Examples\n    --------\n    > var v = base.csignum( new Complex128( -4.2, 5.5 ) )\n    <Complex128>\n    > var re = real( v )\n    -0.6069136033622302\n    > var im = imag( v )\n    0.79476781392673\n\n    See Also\n    --------\n    base.signum\n","base.csub":"\nbase.csub( z1, z2 )\n    Subtracts two double-precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    z1: Complex128\n        Complex number.\n\n    z2: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Result.\n\n    Examples\n    --------\n    > var z1 = new Complex128( 5.0, 3.0 )\n    <Complex128>\n    > var z2 = new Complex128( -2.0, 1.0 )\n    <Complex128>\n    > var out = base.csub( z1, z2 )\n    <Complex128>\n    > var re = real( out )\n    7.0\n    > var im = imag( out )\n    2.0\n\n    See Also\n    --------\n    base.cadd, base.cdiv, base.cmul\n","base.csubf":"\nbase.csubf( z1, z2 )\n    Subtracts two single-precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    z1: Complex64\n        Complex number.\n\n    z2: Complex64\n        Complex number.\n\n    Returns\n    -------\n    out: Complex64\n        Result.\n\n    Examples\n    --------\n    > var z1 = new Complex64( 5.0, 3.0 )\n    <Complex64>\n    > var z2 = new Complex64( -2.0, 1.0 )\n    <Complex64>\n    > var out = base.csubf( z1, z2 )\n    <Complex64>\n    > var re = realf( out )\n    7.0\n    > var im = imagf( out )\n    2.0\n\n    See Also\n    --------\n    base.caddf, base.cmulf, base.csub\n","base.deg2rad":"\nbase.deg2rad( x )\n    Converts an angle from degrees to radians.\n\n    Parameters\n    ----------\n    x: number\n        Angle in degrees.\n\n    Returns\n    -------\n    r: number\n        Angle in radians.\n\n    Examples\n    --------\n    > var r = base.deg2rad( 90.0 )\n    ~1.571\n    > r = base.deg2rad( -45.0 )\n    ~-0.785\n    > r = base.deg2rad( NaN )\n    NaN\n\n    See Also\n    --------\n    base.rad2deg\n","base.deg2radf":"\nbase.deg2radf( x )\n    Converts an angle from degrees to radians (single-precision).\n\n    Parameters\n    ----------\n    x: number\n        Angle in degrees.\n\n    Returns\n    -------\n    r: number\n        Angle in radians.\n\n    Examples\n    --------\n    > var r = base.deg2radf( 90.0 )\n    ~1.571\n    > r = base.deg2radf( -45.0 )\n    ~-0.785\n    > r = base.deg2radf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.deg2rad, base.rad2degf\n","base.digamma":"\nbase.digamma( x )\n    Evaluates the digamma function.\n\n    If `x` is zero or a negative integer, the function returns `NaN`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.digamma( -2.5 )\n    ~1.103\n    > y = base.digamma( 1.0 )\n    ~-0.577\n    > y = base.digamma( 10.0 )\n    ~2.252\n    > y = base.digamma( NaN )\n    NaN\n    > y = base.digamma( -1.0 )\n    NaN\n\n    See Also\n    --------\n    base.gamma, base.trigamma\n","base.diracDelta":"\nbase.diracDelta( x )\n    Evaluates the Dirac delta function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.diracDelta( 3.14 )\n    0.0\n    > y = base.diracDelta( 0.0 )\n    Infinity\n\n    See Also\n    --------\n    base.kroneckerDelta\n","base.div":"\nbase.div( x, y )\n    Divides two double-precision floating-point numbers `x` and `y`.\n\n    Parameters\n    ----------\n    x: number\n        First input value (dividend).\n\n    y: number\n        Second input value (divisor).\n\n    Returns\n    -------\n    z: number\n        Result.\n\n    Examples\n    --------\n    > var v = base.div( -1.0, 5.0 )\n    -0.2\n    > v = base.div( 2.0, 5.0 )\n    0.4\n    > v = base.div( 0.0, 5.0 )\n    0.0\n    > v = base.div( -0.0, 5.0 )\n    -0.0\n    > v = base.div( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.add, base.mul, base.sub\n","base.divf":"\nbase.divf( x, y )\n    Divides two single-precision floating-point numbers `x` and `y`.\n\n    Parameters\n    ----------\n    x: number\n        First input value (dividend).\n\n    y: number\n        Second input value (divisor).\n\n    Returns\n    -------\n    z: number\n        Result.\n\n    Examples\n    --------\n    > var v = base.divf( -1.0, 5.0 )\n    ~-0.2\n    > v = base.divf( 2.0, 5.0 )\n    ~0.4\n    > v = base.divf( 0.0, 5.0 )\n    0.0\n    > v = base.divf( -0.0, 5.0 )\n    -0.0\n    > v = base.divf( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.addf, base.div, base.mulf, base.subf\n","base.dotcase":"\nbase.dotcase( str )\n    Converts a string to dot case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Dot-cased string.\n\n    Examples\n    --------\n    > var out = base.dotcase( 'Hello World!' )\n    'hello.world'\n    > out = base.dotcase( 'I am a tiny little teapot' )\n    'i.am.a.tiny.little.teapot'\n\n    See Also\n    --------\n    base.camelcase, base.lowercase, base.snakecase, base.uppercase","base.dists.arcsine.Arcsine":"\nbase.dists.arcsine.Arcsine( [a, b] )\n    Returns an arcsine distribution object.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support. Must be less than `b`. Default: `0.0`.\n\n    b: number (optional)\n        Maximum support. Must be greater than `a`. Default: `1.0`.\n\n    Returns\n    -------\n    arcsine: Object\n        Distribution instance.\n\n    arcsine.a: number\n        Minimum support. If set, the value must be less than `b`.\n\n    arcsine.b: number\n        Maximum support. If set, the value must be greater than `a`.\n\n    arcsine.entropy: number\n        Read-only property which returns the differential entropy.\n\n    arcsine.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    arcsine.mean: number\n        Read-only property which returns the expected value.\n\n    arcsine.median: number\n        Read-only property which returns the median.\n\n    arcsine.mode: number\n        Read-only property which returns the mode.\n\n    arcsine.skewness: number\n        Read-only property which returns the skewness.\n\n    arcsine.stdev: number\n        Read-only property which returns the standard deviation.\n\n    arcsine.variance: number\n        Read-only property which returns the variance.\n\n    arcsine.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    arcsine.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    arcsine.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    arcsine.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    arcsine.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var arcsine = base.dists.arcsine.Arcsine( 0.0, 1.0 );\n    > arcsine.a\n    0.0\n    > arcsine.b\n    1.0\n    > arcsine.entropy\n    ~-0.242\n    > arcsine.kurtosis\n    -1.5\n    > arcsine.mean\n    0.5\n    > arcsine.median\n    0.5\n    > arcsine.mode\n    0.0\n    > arcsine.skewness\n    0.0\n    > arcsine.stdev\n    ~0.354\n    > arcsine.variance\n    0.125\n    > arcsine.cdf( 0.8 )\n    ~0.705\n    > arcsine.logcdf( 0.8 )\n    ~-0.35\n    > arcsine.logpdf( 0.4 )\n    ~-0.431\n    > arcsine.pdf( 0.8 )\n    ~0.796\n    > arcsine.quantile( 0.8 )\n    ~0.905\n\n","base.dists.arcsine.cdf":"\nbase.dists.arcsine.cdf( x, a, b )\n    Evaluates the cumulative distribution function (CDF) for an arcsine\n    distribution with minimum support `a` and maximum support `b` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.arcsine.cdf( 9.0, 0.0, 10.0 )\n    ~0.795\n    > y = base.dists.arcsine.cdf( 0.5, 0.0, 2.0 )\n    ~0.333\n    > y = base.dists.arcsine.cdf( PINF, 2.0, 4.0 )\n    1.0\n    > y = base.dists.arcsine.cdf( NINF, 2.0, 4.0 )\n    0.0\n    > y = base.dists.arcsine.cdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.arcsine.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.arcsine.cdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.arcsine.cdf( 2.0, 1.0, 0.0 )\n    NaN\n\n\nbase.dists.arcsine.cdf.factory( a, b )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an arcsine distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.arcsine.cdf.factory( 0.0, 10.0 );\n    > var y = mycdf( 0.5 )\n    ~0.144\n    > y = mycdf( 8.0 )\n    ~0.705\n\n","base.dists.arcsine.cdf.factory":"\nbase.dists.arcsine.cdf.factory( a, b )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an arcsine distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.arcsine.cdf.factory( 0.0, 10.0 );\n    > var y = mycdf( 0.5 )\n    ~0.144\n    > y = mycdf( 8.0 )\n    ~0.705","base.dists.arcsine.entropy":"\nbase.dists.arcsine.entropy( a, b )\n    Returns the differential entropy of an arcsine distribution (in nats).\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.arcsine.entropy( 0.0, 1.0 )\n    ~-0.242\n    > v = base.dists.arcsine.entropy( 4.0, 12.0 )\n    ~1.838\n    > v = base.dists.arcsine.entropy( 2.0, 8.0 )\n    ~1.55\n\n","base.dists.arcsine.kurtosis":"\nbase.dists.arcsine.kurtosis( a, b )\n    Returns the excess kurtosis of an arcsine distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.arcsine.kurtosis( 0.0, 1.0 )\n    -1.5\n    > v = base.dists.arcsine.kurtosis( 4.0, 12.0 )\n    -1.5\n    > v = base.dists.arcsine.kurtosis( 2.0, 8.0 )\n    -1.5\n\n","base.dists.arcsine.logcdf":"\nbase.dists.arcsine.logcdf( x, a, b )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for an\n    arcsine distribution with minimum support `a` and maximum support `b` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.arcsine.logcdf( 9.0, 0.0, 10.0 )\n    ~-0.229\n    > y = base.dists.arcsine.logcdf( 0.5, 0.0, 2.0 )\n    ~-1.1\n    > y = base.dists.arcsine.logcdf( PINF, 2.0, 4.0 )\n    0.0\n    > y = base.dists.arcsine.logcdf( NINF, 2.0, 4.0 )\n    -Infinity\n    > y = base.dists.arcsine.logcdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.arcsine.logcdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.arcsine.logcdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.arcsine.logcdf( 2.0, 1.0, 0.0 )\n    NaN\n\n\nbase.dists.arcsine.logcdf.factory( a, b )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of an arcsine distribution with minimum support\n    `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.arcsine.logcdf.factory( 0.0, 10.0 );\n    > var y = mylogcdf( 0.5 )\n    ~-1.941\n    > y = mylogcdf( 8.0 )\n    ~-0.35\n\n","base.dists.arcsine.logcdf.factory":"\nbase.dists.arcsine.logcdf.factory( a, b )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of an arcsine distribution with minimum support\n    `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.arcsine.logcdf.factory( 0.0, 10.0 );\n    > var y = mylogcdf( 0.5 )\n    ~-1.941\n    > y = mylogcdf( 8.0 )\n    ~-0.35","base.dists.arcsine.logpdf":"\nbase.dists.arcsine.logpdf( x, a, b )\n    Evaluates the logarithm of the probability density function (PDF) for an\n    arcsine distribution with minimum support `a` and maximum support `b` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.arcsine.logpdf( 2.0, 0.0, 4.0 )\n    ~-1.838\n    > y = base.dists.arcsine.logpdf( 5.0, 0.0, 4.0 )\n    -Infinity\n    > y = base.dists.arcsine.logpdf( 0.25, 0.0, 1.0 )\n    ~-0.308\n    > y = base.dists.arcsine.logpdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.arcsine.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.arcsine.logpdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.arcsine.logpdf( 2.0, 3.0, 1.0 )\n    NaN\n\n\nbase.dists.arcsine.logpdf.factory( a, b )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of an arcsine distribution with minimum support `a` and\n    maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.arcsine.logpdf.factory( 6.0, 7.0 );\n    > var y = mylogPDF( 7.0 )\n    Infinity\n    > y = mylogPDF( 5.0 )\n    -Infinity\n\n","base.dists.arcsine.logpdf.factory":"\nbase.dists.arcsine.logpdf.factory( a, b )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of an arcsine distribution with minimum support `a` and\n    maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.arcsine.logpdf.factory( 6.0, 7.0 );\n    > var y = mylogPDF( 7.0 )\n    Infinity\n    > y = mylogPDF( 5.0 )\n    -Infinity","base.dists.arcsine.mean":"\nbase.dists.arcsine.mean( a, b )\n    Returns the expected value of an arcsine distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.arcsine.mean( 0.0, 1.0 )\n    0.5\n    > v = base.dists.arcsine.mean( 4.0, 12.0 )\n    8.0\n    > v = base.dists.arcsine.mean( 2.0, 8.0 )\n    5.0\n\n","base.dists.arcsine.median":"\nbase.dists.arcsine.median( a, b )\n    Returns the median of an arcsine distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.arcsine.median( 0.0, 1.0 )\n    0.5\n    > v = base.dists.arcsine.median( 4.0, 12.0 )\n    8.0\n    > v = base.dists.arcsine.median( 2.0, 8.0 )\n    5.0\n\n","base.dists.arcsine.mode":"\nbase.dists.arcsine.mode( a, b )\n    Returns the mode of an arcsine distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.arcsine.mode( 0.0, 1.0 )\n    0.0\n    > v = base.dists.arcsine.mode( 4.0, 12.0 )\n    4.0\n    > v = base.dists.arcsine.mode( 2.0, 8.0 )\n    2.0\n\n","base.dists.arcsine.pdf":"\nbase.dists.arcsine.pdf( x, a, b )\n    Evaluates the probability density function (PDF) for an arcsine distribution\n    with minimum support `a` and maximum support `b` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.arcsine.pdf( 2.0, 0.0, 4.0 )\n    ~0.159\n    > y = base.dists.arcsine.pdf( 5.0, 0.0, 4.0 )\n    0.0\n    > y = base.dists.arcsine.pdf( 0.25, 0.0, 1.0 )\n    ~0.735\n    > y = base.dists.arcsine.pdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.arcsine.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.arcsine.pdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.arcsine.pdf( 2.0, 3.0, 1.0 )\n    NaN\n\n\nbase.dists.arcsine.pdf.factory( a, b )\n    Returns a function for evaluating the probability density function (PDF) of\n    an arcsine distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.arcsine.pdf.factory( 6.0, 7.0 );\n    > var y = myPDF( 7.0 )\n    Infinity\n    > y = myPDF( 5.0 )\n    0.0\n\n","base.dists.arcsine.pdf.factory":"\nbase.dists.arcsine.pdf.factory( a, b )\n    Returns a function for evaluating the probability density function (PDF) of\n    an arcsine distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.arcsine.pdf.factory( 6.0, 7.0 );\n    > var y = myPDF( 7.0 )\n    Infinity\n    > y = myPDF( 5.0 )\n    0.0","base.dists.arcsine.quantile":"\nbase.dists.arcsine.quantile( p, a, b )\n    Evaluates the quantile function for an arcsine distribution with minimum\n    support `a` and maximum support `b` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.arcsine.quantile( 0.8, 0.0, 1.0 )\n    ~0.905\n    > y = base.dists.arcsine.quantile( 0.5, 0.0, 10.0 )\n    ~5.0\n\n    > y = base.dists.arcsine.quantile( 1.1, 0.0, 1.0 )\n    NaN\n    > y = base.dists.arcsine.quantile( -0.2, 0.0, 1.0 )\n    NaN\n\n    > y = base.dists.arcsine.quantile( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.arcsine.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.arcsine.quantile( 0.0, 0.0, NaN )\n    NaN\n\n    > y = base.dists.arcsine.quantile( 0.5, 2.0, 1.0 )\n    NaN\n\n\nbase.dists.arcsine.quantile.factory( a, b )\n    Returns a function for evaluating the quantile function of an arcsine\n    distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.arcsine.quantile.factory( 0.0, 4.0 );\n    > var y = myQuantile( 0.8 )\n    ~3.618\n\n","base.dists.arcsine.quantile.factory":"\nbase.dists.arcsine.quantile.factory( a, b )\n    Returns a function for evaluating the quantile function of an arcsine\n    distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.arcsine.quantile.factory( 0.0, 4.0 );\n    > var y = myQuantile( 0.8 )\n    ~3.618","base.dists.arcsine.skewness":"\nbase.dists.arcsine.skewness( a, b )\n    Returns the skewness of an arcsine distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.arcsine.skewness( 0.0, 1.0 )\n    0.0\n    > v = base.dists.arcsine.skewness( 4.0, 12.0 )\n    0.0\n    > v = base.dists.arcsine.skewness( 2.0, 8.0 )\n    0.0\n\n","base.dists.arcsine.stdev":"\nbase.dists.arcsine.stdev( a, b )\n    Returns the standard deviation of an arcsine distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.arcsine.stdev( 0.0, 1.0 )\n    ~0.354\n    > v = base.dists.arcsine.stdev( 4.0, 12.0 )\n    ~2.828\n    > v = base.dists.arcsine.stdev( 2.0, 8.0 )\n    ~2.121\n\n","base.dists.arcsine.variance":"\nbase.dists.arcsine.variance( a, b )\n    Returns the variance of an arcsine distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.arcsine.variance( 0.0, 1.0 )\n    ~0.125\n    > v = base.dists.arcsine.variance( 4.0, 12.0 )\n    8.0\n    > v = base.dists.arcsine.variance( 2.0, 8.0 )\n    ~4.5\n\n","base.dists.bernoulli.Bernoulli":"\nbase.dists.bernoulli.Bernoulli( [p] )\n    Returns a Bernoulli distribution object.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability. Must be between `0` and `1`. Default: `0.5`.\n\n    Returns\n    -------\n    bernoulli: Object\n        Distribution instance.\n\n    bernoulli.p: number\n        Success probability. If set, the value must be between `0` and `1`.\n\n    bernoulli.entropy: number\n        Read-only property which returns the differential entropy.\n\n    bernoulli.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    bernoulli.mean: number\n        Read-only property which returns the expected value.\n\n    bernoulli.median: number\n        Read-only property which returns the median.\n\n    bernoulli.skewness: number\n        Read-only property which returns the skewness.\n\n    bernoulli.stdev: number\n        Read-only property which returns the standard deviation.\n\n    bernoulli.variance: number\n        Read-only property which returns the variance.\n\n    bernoulli.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    bernoulli.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    bernoulli.pmf: Function\n        Evaluates the probability mass function (PMF).\n\n    bernoulli.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var bernoulli = base.dists.bernoulli.Bernoulli( 0.6 );\n    > bernoulli.p\n    0.6\n    > bernoulli.entropy\n    ~0.673\n    > bernoulli.kurtosis\n    ~-1.833\n    > bernoulli.mean\n    0.6\n    > bernoulli.median\n    1.0\n    > bernoulli.skewness\n    ~-0.408\n    > bernoulli.stdev\n    ~0.49\n    > bernoulli.variance\n    ~0.24\n    > bernoulli.cdf( 0.5 )\n    0.4\n    > bernoulli.mgf( 3.0 )\n    ~12.451\n    > bernoulli.pmf( 0.0 )\n    0.4\n    > bernoulli.quantile( 0.7 )\n    1.0\n\n","base.dists.bernoulli.cdf":"\nbase.dists.bernoulli.cdf( x, p )\n    Evaluates the cumulative distribution function (CDF) for a Bernoulli\n    distribution with success probability `p` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.bernoulli.cdf( 0.5, 0.5 )\n    0.5\n    > y = base.dists.bernoulli.cdf( 0.8, 0.1 )\n    0.9\n    > y = base.dists.bernoulli.cdf( -1.0, 0.4 )\n    0.0\n    > y = base.dists.bernoulli.cdf( 1.5, 0.4 )\n    1.0\n    > y = base.dists.bernoulli.cdf( NaN, 0.5 )\n    NaN\n    > y = base.dists.bernoulli.cdf( 0.0, NaN )\n    NaN\n    // Invalid probability:\n    > y = base.dists.bernoulli.cdf( 2.0, 1.4 )\n    NaN\n\n\nbase.dists.bernoulli.cdf.factory( p )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Bernoulli distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.bernoulli.cdf.factory( 0.5 );\n    > var y = mycdf( 3.0 )\n    1.0\n    > y = mycdf( 0.7 )\n    0.5\n\n","base.dists.bernoulli.cdf.factory":"\nbase.dists.bernoulli.cdf.factory( p )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Bernoulli distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.bernoulli.cdf.factory( 0.5 );\n    > var y = mycdf( 3.0 )\n    1.0\n    > y = mycdf( 0.7 )\n    0.5","base.dists.bernoulli.entropy":"\nbase.dists.bernoulli.entropy( p )\n    Returns the entropy of a Bernoulli distribution with success probability\n    `p` (in nats).\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.bernoulli.entropy( 0.1 )\n    ~0.325\n    > v = base.dists.bernoulli.entropy( 0.5 )\n    ~0.693\n\n","base.dists.bernoulli.kurtosis":"\nbase.dists.bernoulli.kurtosis( p )\n    Returns the excess kurtosis of a Bernoulli distribution with success\n    probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.bernoulli.kurtosis( 0.1 )\n    ~5.111\n    > v = base.dists.bernoulli.kurtosis( 0.5 )\n    -2.0\n\n","base.dists.bernoulli.mean":"\nbase.dists.bernoulli.mean( p )\n    Returns the expected value of a Bernoulli distribution with success\n    probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.bernoulli.mean( 0.1 )\n    0.1\n    > v = base.dists.bernoulli.mean( 0.5 )\n    0.5\n\n","base.dists.bernoulli.median":"\nbase.dists.bernoulli.median( p )\n    Returns the median of a Bernoulli distribution with success probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: integer\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.bernoulli.median( 0.1 )\n    0\n    > v = base.dists.bernoulli.median( 0.8 )\n    1\n\n","base.dists.bernoulli.mgf":"\nbase.dists.bernoulli.mgf( t, p )\n    Evaluates the moment-generating function (MGF) for a Bernoulli\n    distribution with success probability `p` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.bernoulli.mgf( 0.2, 0.5 )\n    ~1.111\n    > y = base.dists.bernoulli.mgf( 0.4, 0.5 )\n    ~1.246\n    > y = base.dists.bernoulli.mgf( NaN, 0.0 )\n    NaN\n    > y = base.dists.bernoulli.mgf( 0.0, NaN )\n    NaN\n    > y = base.dists.bernoulli.mgf( -2.0, -1.0 )\n    NaN\n    > y = base.dists.bernoulli.mgf( 0.2, 2.0 )\n    NaN\n\n\nbase.dists.bernoulli.mgf.factory( p )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Bernoulli distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.bernoulli.mgf.factory( 0.8 );\n    > var y = mymgf( -0.2 )\n    ~0.855\n\n","base.dists.bernoulli.mgf.factory":"\nbase.dists.bernoulli.mgf.factory( p )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Bernoulli distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.bernoulli.mgf.factory( 0.8 );\n    > var y = mymgf( -0.2 )\n    ~0.855","base.dists.bernoulli.mode":"\nbase.dists.bernoulli.mode( p )\n    Returns the mode of a Bernoulli distribution with success probability `p`.\n\n    For `p = 0.5`, the mode is either `0` or `1`. This implementation returns\n    `0` for `p = 0.5`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: integer\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.bernoulli.mode( 0.1 )\n    0\n    > v = base.dists.bernoulli.mode( 0.8 )\n    1\n\n","base.dists.bernoulli.pmf":"\nbase.dists.bernoulli.pmf( x, p )\n    Evaluates the probability mass function (PMF) for a Bernoulli distribution\n    with success probability `p` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated PMF.\n\n    Examples\n    --------\n    > var y = base.dists.bernoulli.pmf( 1.0, 0.3 )\n    0.3\n    > y = base.dists.bernoulli.pmf( 0.0, 0.7 )\n    0.3\n    > y = base.dists.bernoulli.pmf( -1.0, 0.5 )\n    0.0\n    > y = base.dists.bernoulli.pmf( 0.0, NaN )\n    NaN\n    > y = base.dists.bernoulli.pmf( NaN, 0.5 )\n    NaN\n    // Invalid success probability:\n    > y = base.dists.bernoulli.pmf( 0.0, 1.5 )\n    NaN\n\n\nbase.dists.bernoulli.pmf.factory( p )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    Bernoulli distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var mypmf = base.dists.bernoulli.pmf.factory( 0.5 );\n    > var y = mypmf( 1.0 )\n    0.5\n    > y = mypmf( 0.0 )\n    0.5\n\n","base.dists.bernoulli.pmf.factory":"\nbase.dists.bernoulli.pmf.factory( p )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    Bernoulli distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var mypmf = base.dists.bernoulli.pmf.factory( 0.5 );\n    > var y = mypmf( 1.0 )\n    0.5\n    > y = mypmf( 0.0 )\n    0.5","base.dists.bernoulli.quantile":"\nbase.dists.bernoulli.quantile( r, p )\n    Evaluates the quantile function for a Bernoulli distribution with success\n    probability `p` at a probability `r`.\n\n    If `r < 0` or `r > 1`, the function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    r: number\n        Input probability.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.bernoulli.quantile( 0.8, 0.4 )\n    1\n    > y = base.dists.bernoulli.quantile( 0.5, 0.4 )\n    0\n    > y = base.dists.bernoulli.quantile( 0.9, 0.1 )\n    0\n\n    > y = base.dists.bernoulli.quantile( -0.2, 0.1 )\n    NaN\n\n    > y = base.dists.bernoulli.quantile( NaN, 0.8 )\n    NaN\n    > y = base.dists.bernoulli.quantile( 0.4, NaN )\n    NaN\n\n    > y = base.dists.bernoulli.quantile( 0.5, -1.0 )\n    NaN\n    > y = base.dists.bernoulli.quantile( 0.5, 1.5 )\n    NaN\n\n\nbase.dists.bernoulli.quantile.factory( p )\n    Returns a function for evaluating the quantile function of a Bernoulli\n    distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.bernoulli.quantile.factory( 0.4 );\n    > var y = myquantile( 0.4 )\n    0\n    > y = myquantile( 0.8 )\n    1\n    > y = myquantile( 1.0 )\n    1\n\n","base.dists.bernoulli.quantile.factory":"\nbase.dists.bernoulli.quantile.factory( p )\n    Returns a function for evaluating the quantile function of a Bernoulli\n    distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.bernoulli.quantile.factory( 0.4 );\n    > var y = myquantile( 0.4 )\n    0\n    > y = myquantile( 0.8 )\n    1\n    > y = myquantile( 1.0 )\n    1","base.dists.bernoulli.skewness":"\nbase.dists.bernoulli.skewness( p )\n    Returns the skewness of a Bernoulli distribution with success probability\n    `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.bernoulli.skewness( 0.1 )\n    ~2.667\n    > v = base.dists.bernoulli.skewness( 0.5 )\n    0.0\n\n","base.dists.bernoulli.stdev":"\nbase.dists.bernoulli.stdev( p )\n    Returns the standard deviation of a Bernoulli distribution with success\n    probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.bernoulli.stdev( 0.1 )\n    ~0.3\n    > v = base.dists.bernoulli.stdev( 0.5 )\n    0.5\n\n","base.dists.bernoulli.variance":"\nbase.dists.bernoulli.variance( p )\n    Returns the variance of a Bernoulli distribution with success probability\n    `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.bernoulli.variance( 0.1 )\n    ~0.09\n    > v = base.dists.bernoulli.variance( 0.5 )\n    0.25\n\n","base.dists.beta.Beta":"\nbase.dists.beta.Beta( [α, β] )\n    Returns a beta distribution object.\n\n    Parameters\n    ----------\n    α: number (optional)\n        First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n    β: number (optional)\n        Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    beta: Object\n        Distribution instance.\n\n    beta.alpha: number\n        First shape parameter. If set, the value must be greater than `0`.\n\n    beta.beta: number\n        Second shape parameter. If set, the value must be greater than `0`.\n\n    beta.entropy: number\n        Read-only property which returns the differential entropy.\n\n    beta.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    beta.mean: number\n        Read-only property which returns the expected value.\n\n    beta.median: number\n        Read-only property which returns the median.\n\n    beta.mode: number\n        Read-only property which returns the mode.\n\n    beta.skewness: number\n        Read-only property which returns the skewness.\n\n    beta.stdev: number\n        Read-only property which returns the standard deviation.\n\n    beta.variance: number\n        Read-only property which returns the variance.\n\n    beta.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    beta.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    beta.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    beta.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    beta.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    beta.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var beta = base.dists.beta.Beta( 1.0, 1.0 );\n    > beta.alpha\n    1.0\n    > beta.beta\n    1.0\n    > beta.entropy\n    0.0\n    > beta.kurtosis\n    -1.2\n    > beta.mean\n    0.5\n    > beta.median\n    0.5\n    > beta.mode\n    NaN\n    > beta.skewness\n    0.0\n    > beta.stdev\n    ~0.289\n    > beta.variance\n    ~0.0833\n    > beta.cdf( 0.8 )\n    0.8\n    > beta.logcdf( 0.8 )\n    ~-0.223\n    > beta.logpdf( 1.0 )\n    0.0\n    > beta.mgf( 3.14 )\n    ~7.0394\n    > beta.pdf( 1.0 )\n    1.0\n    > beta.quantile( 0.8 )\n    0.8\n\n","base.dists.beta.cdf":"\nbase.dists.beta.cdf( x, α, β )\n    Evaluates the cumulative distribution function (CDF) for a beta distribution\n    with first shape parameter `α` and second shape parameter `β` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.beta.cdf( 0.5, 1.0, 1.0 )\n    0.5\n    > y = base.dists.beta.cdf( 0.5, 2.0, 4.0 )\n    ~0.813\n    > y = base.dists.beta.cdf( 0.2, 2.0, 2.0 )\n    ~0.104\n    > y = base.dists.beta.cdf( 0.8, 4.0, 4.0 )\n    ~0.967\n    > y = base.dists.beta.cdf( -0.5, 4.0, 2.0 )\n    0.0\n    > y = base.dists.beta.cdf( 1.5, 4.0, 2.0 )\n    1.0\n\n    > y = base.dists.beta.cdf( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.beta.cdf( 2.0, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.beta.cdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.beta.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.beta.cdf( 0.0, 1.0, NaN )\n    NaN\n\n\nbase.dists.beta.cdf.factory( α, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a beta distribution with first shape parameter `α` and second shape\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.beta.cdf.factory( 0.5, 0.5 );\n    > var y = mycdf( 0.8 )\n    ~0.705\n    > y = mycdf( 0.3 )\n    ~0.369\n\n","base.dists.beta.cdf.factory":"\nbase.dists.beta.cdf.factory( α, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a beta distribution with first shape parameter `α` and second shape\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.beta.cdf.factory( 0.5, 0.5 );\n    > var y = mycdf( 0.8 )\n    ~0.705\n    > y = mycdf( 0.3 )\n    ~0.369","base.dists.beta.entropy":"\nbase.dists.beta.entropy( α, β )\n    Returns the differential entropy of a beta distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Differential entropy.\n\n    Examples\n    --------\n    > var v = base.dists.beta.entropy( 1.0, 1.0 )\n    0.0\n    > v = base.dists.beta.entropy( 4.0, 12.0 )\n    ~-0.869\n    > v = base.dists.beta.entropy( 8.0, 2.0 )\n    ~-0.795\n\n    > v = base.dists.beta.entropy( 1.0, -0.1 )\n    NaN\n    > v = base.dists.beta.entropy( -0.1, 1.0 )\n    NaN\n\n    > v = base.dists.beta.entropy( 2.0, NaN )\n    NaN\n    > v = base.dists.beta.entropy( NaN, 2.0 )\n    NaN\n\n","base.dists.beta.kurtosis":"\nbase.dists.beta.kurtosis( α, β )\n    Returns the excess kurtosis of a beta distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.beta.kurtosis( 1.0, 1.0 )\n    -1.2\n    > v = base.dists.beta.kurtosis( 4.0, 12.0 )\n    ~0.082\n    > v = base.dists.beta.kurtosis( 8.0, 2.0 )\n    ~0.490\n\n    > v = base.dists.beta.kurtosis( 1.0, -0.1 )\n    NaN\n    > v = base.dists.beta.kurtosis( -0.1, 1.0 )\n    NaN\n\n    > v = base.dists.beta.kurtosis( 2.0, NaN )\n    NaN\n    > v = base.dists.beta.kurtosis( NaN, 2.0 )\n    NaN\n\n","base.dists.beta.logcdf":"\nbase.dists.beta.logcdf( x, α, β )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a beta distribution with first shape parameter `α` and second\n    shape parameter `β` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.beta.logcdf( 0.5, 1.0, 1.0 )\n    ~-0.693\n    > y = base.dists.beta.logcdf( 0.5, 2.0, 4.0 )\n    ~-0.208\n    > y = base.dists.beta.logcdf( 0.2, 2.0, 2.0 )\n    ~-2.263\n    > y = base.dists.beta.logcdf( 0.8, 4.0, 4.0 )\n    ~-0.034\n    > y = base.dists.beta.logcdf( -0.5, 4.0, 2.0 )\n    -Infinity\n    > y = base.dists.beta.logcdf( 1.5, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.beta.logcdf( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.beta.logcdf( 2.0, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.beta.logcdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.beta.logcdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.beta.logcdf( 0.0, 1.0, NaN )\n    NaN\n\n\nbase.dists.beta.logcdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a beta distribution with first shape\n    parameter `α` and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.beta.logcdf.factory( 0.5, 0.5 );\n    > var y = mylogcdf( 0.8 )\n    ~-0.35\n    > y = mylogcdf( 0.3 )\n    ~-0.997\n\n","base.dists.beta.logcdf.factory":"\nbase.dists.beta.logcdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a beta distribution with first shape\n    parameter `α` and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.beta.logcdf.factory( 0.5, 0.5 );\n    > var y = mylogcdf( 0.8 )\n    ~-0.35\n    > y = mylogcdf( 0.3 )\n    ~-0.997","base.dists.beta.logpdf":"\nbase.dists.beta.logpdf( x, α, β )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a beta distribution with first shape parameter `α` and second shape\n    parameter `β` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Natural logarithm of the PDF.\n\n    Examples\n    --------\n    > var y = base.dists.beta.logpdf( 0.5, 1.0, 1.0 )\n    0.0\n    > y = base.dists.beta.logpdf( 0.5, 2.0, 4.0 )\n    ~0.223\n    > y = base.dists.beta.logpdf( 0.2, 2.0, 2.0 )\n    ~-0.041\n    > y = base.dists.beta.logpdf( 0.8, 4.0, 4.0 )\n    ~-0.556\n    > y = base.dists.beta.logpdf( -0.5, 4.0, 2.0 )\n    -Infinity\n    > y = base.dists.beta.logpdf( 1.5, 4.0, 2.0 )\n    -Infinity\n\n    > y = base.dists.beta.logpdf( 0.5, -1.0, 0.5 )\n    NaN\n    > y = base.dists.beta.logpdf( 0.5, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.beta.logpdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.beta.logpdf( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.dists.beta.logpdf( 0.5, 1.0, NaN )\n    NaN\n\n\nbase.dists.beta.logpdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a beta distribution with first shape parameter `α`\n    and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    fcn: Function\n        Function to evaluate the natural logarithm of the PDF.\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.beta.logpdf.factory( 0.5, 0.5 );\n    > var y = mylogpdf( 0.8 )\n    ~-0.228\n    > y = mylogpdf( 0.3 )\n    ~-0.364\n\n","base.dists.beta.logpdf.factory":"\nbase.dists.beta.logpdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a beta distribution with first shape parameter `α`\n    and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    fcn: Function\n        Function to evaluate the natural logarithm of the PDF.\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.beta.logpdf.factory( 0.5, 0.5 );\n    > var y = mylogpdf( 0.8 )\n    ~-0.228\n    > y = mylogpdf( 0.3 )\n    ~-0.364","base.dists.beta.mean":"\nbase.dists.beta.mean( α, β )\n    Returns the expected value of a beta distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.beta.mean( 1.0, 1.0 )\n    0.5\n    > v = base.dists.beta.mean( 4.0, 12.0 )\n    0.25\n    > v = base.dists.beta.mean( 8.0, 2.0 )\n    0.8\n\n","base.dists.beta.median":"\nbase.dists.beta.median( α, β )\n    Returns the median of a beta distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.beta.median( 1.0, 1.0 )\n    0.5\n    > v = base.dists.beta.median( 4.0, 12.0 )\n    ~0.239\n    > v = base.dists.beta.median( 8.0, 2.0 )\n    ~0.820\n\n    > v = base.dists.beta.median( 1.0, -0.1 )\n    NaN\n    > v = base.dists.beta.median( -0.1, 1.0 )\n    NaN\n\n    > v = base.dists.beta.median( 2.0, NaN )\n    NaN\n    > v = base.dists.beta.median( NaN, 2.0 )\n    NaN\n\n","base.dists.beta.mgf":"\nbase.dists.beta.mgf( t, α, β )\n    Evaluates the moment-generating function (MGF) for a beta distribution with\n    first shape parameter `α` and second shape parameter `β` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.beta.mgf( 0.5, 1.0, 1.0 )\n    ~1.297\n    > y = base.dists.beta.mgf( 0.5, 2.0, 4.0 )\n    ~1.186\n    > y = base.dists.beta.mgf( 3.0, 2.0, 2.0 )\n    ~5.575\n    > y = base.dists.beta.mgf( -0.8, 4.0, 4.0 )\n    ~0.676\n\n    > y = base.dists.beta.mgf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.beta.mgf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.beta.mgf( 0.0, 1.0, NaN )\n    NaN\n\n    > y = base.dists.beta.mgf( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.beta.mgf( 2.0, 0.0, 0.5 )\n    NaN\n\n    > y = base.dists.beta.mgf( 2.0, 0.5, -1.0 )\n    NaN\n    > y = base.dists.beta.mgf( 2.0, 0.5, 0.0 )\n    NaN\n\n\nbase.dists.beta.mgf.factory( α, β )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    beta distribution with first shape parameter `α` and second shape parameter\n    `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.beta.mgf.factory( 0.5, 0.5 );\n    > var y = myMGF( 0.8 )\n    ~1.552\n    > y = myMGF( 0.3 )\n    ~1.168\n\n","base.dists.beta.mgf.factory":"\nbase.dists.beta.mgf.factory( α, β )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    beta distribution with first shape parameter `α` and second shape parameter\n    `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.beta.mgf.factory( 0.5, 0.5 );\n    > var y = myMGF( 0.8 )\n    ~1.552\n    > y = myMGF( 0.3 )\n    ~1.168","base.dists.beta.mode":"\nbase.dists.beta.mode( α, β )\n    Returns the mode of a beta distribution.\n\n    If `α <= 1` or `β <= 1`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.beta.mode( 4.0, 12.0 )\n    ~0.214\n    > v = base.dists.beta.mode( 8.0, 2.0 )\n    ~0.875\n    > v = base.dists.beta.mode( 1.0, 1.0 )\n    NaN\n\n","base.dists.beta.pdf":"\nbase.dists.beta.pdf( x, α, β )\n    Evaluates the probability density function (PDF) for a beta distribution\n    with first shape parameter `α` and second shape parameter `β` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.beta.pdf( 0.5, 1.0, 1.0 )\n    1.0\n    > y = base.dists.beta.pdf( 0.5, 2.0, 4.0 )\n    1.25\n    > y = base.dists.beta.pdf( 0.2, 2.0, 2.0 )\n    ~0.96\n    > y = base.dists.beta.pdf( 0.8, 4.0, 4.0 )\n    ~0.573\n    > y = base.dists.beta.pdf( -0.5, 4.0, 2.0 )\n    0.0\n    > y = base.dists.beta.pdf( 1.5, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.beta.pdf( 0.5, -1.0, 0.5 )\n    NaN\n    > y = base.dists.beta.pdf( 0.5, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.beta.pdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.beta.pdf( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.dists.beta.pdf( 0.5, 1.0, NaN )\n    NaN\n\n\nbase.dists.beta.pdf.factory( α, β )\n    Returns a function for evaluating the probability density function (PDF) of\n    a beta distribution with first shape parameter `α` and second shape\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var mypdf = base.dists.beta.pdf.factory( 0.5, 0.5 );\n    > var y = mypdf( 0.8 )\n    ~0.796\n    > y = mypdf( 0.3 )\n    ~0.695\n\n","base.dists.beta.pdf.factory":"\nbase.dists.beta.pdf.factory( α, β )\n    Returns a function for evaluating the probability density function (PDF) of\n    a beta distribution with first shape parameter `α` and second shape\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var mypdf = base.dists.beta.pdf.factory( 0.5, 0.5 );\n    > var y = mypdf( 0.8 )\n    ~0.796\n    > y = mypdf( 0.3 )\n    ~0.695","base.dists.beta.quantile":"\nbase.dists.beta.quantile( p, α, β )\n    Evaluates the quantile function for a beta distribution with first shape\n    parameter `α` and second shape parameter `β` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input value (probability).\n\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.beta.quantile( 0.8, 2.0, 1.0 )\n    ~0.894\n    > y = base.dists.beta.quantile( 0.5, 4.0, 2.0 )\n    ~0.686\n    > y = base.dists.beta.quantile( 1.1, 1.0, 1.0 )\n    NaN\n    > y = base.dists.beta.quantile( -0.2, 1.0, 1.0 )\n    NaN\n\n    > y = base.dists.beta.quantile( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.beta.quantile( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.dists.beta.quantile( 0.5, 1.0, NaN )\n    NaN\n\n    > y = base.dists.beta.quantile( 0.5, -1.0, 1.0 )\n    NaN\n    > y = base.dists.beta.quantile( 0.5, 1.0, -1.0 )\n    NaN\n\n\nbase.dists.beta.quantile.factory( α, β )\n    Returns a function for evaluating the quantile function of a beta\n    distribution with first shape parameter `α` and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.beta.quantile.factory( 2.0, 2.0 );\n    > y = myquantile( 0.8 )\n    ~0.713\n    > y = myquantile( 0.4 )\n    ~0.433\n\n","base.dists.beta.quantile.factory":"\nbase.dists.beta.quantile.factory( α, β )\n    Returns a function for evaluating the quantile function of a beta\n    distribution with first shape parameter `α` and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.beta.quantile.factory( 2.0, 2.0 );\n    > y = myquantile( 0.8 )\n    ~0.713\n    > y = myquantile( 0.4 )\n    ~0.433","base.dists.beta.skewness":"\nbase.dists.beta.skewness( α, β )\n    Returns the skewness of a beta distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.beta.skewness( 1.0, 1.0 )\n    0.0\n    > v = base.dists.beta.skewness( 4.0, 12.0 )\n    ~0.529\n    > v = base.dists.beta.skewness( 8.0, 2.0 )\n    ~-0.829\n\n    > v = base.dists.beta.skewness( 1.0, -0.1 )\n    NaN\n    > v = base.dists.beta.skewness( -0.1, 1.0 )\n    NaN\n\n    > v = base.dists.beta.skewness( 2.0, NaN )\n    NaN\n    > v = base.dists.beta.skewness( NaN, 2.0 )\n    NaN\n\n","base.dists.beta.stdev":"\nbase.dists.beta.stdev( α, β )\n    Returns the standard deviation of a beta distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.beta.stdev( 1.0, 1.0 )\n    ~0.289\n    > v = base.dists.beta.stdev( 4.0, 12.0 )\n    ~0.105\n    > v = base.dists.beta.stdev( 8.0, 2.0 )\n    ~0.121\n\n    > v = base.dists.beta.stdev( 1.0, -0.1 )\n    NaN\n    > v = base.dists.beta.stdev( -0.1, 1.0 )\n    NaN\n\n    > v = base.dists.beta.stdev( 2.0, NaN )\n    NaN\n    > v = base.dists.beta.stdev( NaN, 2.0 )\n    NaN\n\n","base.dists.beta.variance":"\nbase.dists.beta.variance( α, β )\n    Returns the variance of a beta distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.beta.variance( 1.0, 1.0 )\n    ~0.083\n    > v = base.dists.beta.variance( 4.0, 12.0 )\n    ~0.011\n    > v = base.dists.beta.variance( 8.0, 2.0 )\n    ~0.015\n\n    > v = base.dists.beta.variance( 1.0, -0.1 )\n    NaN\n    > v = base.dists.beta.variance( -0.1, 1.0 )\n    NaN\n\n    > v = base.dists.beta.variance( 2.0, NaN )\n    NaN\n    > v = base.dists.beta.variance( NaN, 2.0 )\n    NaN\n\n","base.dists.betaprime.BetaPrime":"\nbase.dists.betaprime.BetaPrime( [α, β] )\n    Returns a beta prime distribution object.\n\n    Parameters\n    ----------\n    α: number (optional)\n        First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n    β: number (optional)\n        Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    betaprime: Object\n        Distribution instance.\n\n    betaprime.alpha: number\n        First shape parameter. If set, the value must be greater than `0`.\n\n    betaprime.beta: number\n        Second shape parameter. If set, the value must be greater than `0`.\n\n    betaprime.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    betaprime.mean: number\n        Read-only property which returns the expected value.\n\n    betaprime.mode: number\n        Read-only property which returns the mode.\n\n    betaprime.skewness: number\n        Read-only property which returns the skewness.\n\n    betaprime.stdev: number\n        Read-only property which returns the standard deviation.\n\n    betaprime.variance: number\n        Read-only property which returns the variance.\n\n    betaprime.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    betaprime.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    betaprime.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    betaprime.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    betaprime.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var betaprime = base.dists.betaprime.BetaPrime( 6.0, 5.0 );\n    > betaprime.alpha\n    6.0\n    > betaprime.beta\n    5.0\n    > betaprime.kurtosis\n    44.4\n    > betaprime.mean\n    1.5\n    > betaprime.mode\n    ~0.833\n    > betaprime.skewness\n    ~3.578\n    > betaprime.stdev\n    ~1.118\n    > betaprime.variance\n    1.25\n    > betaprime.cdf( 0.8 )\n    ~0.25\n    > betaprime.logcdf( 0.8 )\n    ~-1.387\n    > betaprime.logpdf( 1.0 )\n    ~-0.486\n    > betaprime.pdf( 1.0 )\n    ~0.615\n    > betaprime.quantile( 0.8 )\n    ~2.06\n\n","base.dists.betaprime.cdf":"\nbase.dists.betaprime.cdf( x, α, β )\n    Evaluates the cumulative distribution function (CDF) for a beta prime\n    distribution with first shape parameter `α` and second shape parameter `β`\n    at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.betaprime.cdf( 0.5, 1.0, 1.0 )\n    ~0.333\n    > y = base.dists.betaprime.cdf( 0.5, 2.0, 4.0 )\n    ~0.539\n    > y = base.dists.betaprime.cdf( 0.2, 2.0, 2.0 )\n    ~0.074\n    > y = base.dists.betaprime.cdf( 0.8, 4.0, 4.0 )\n    ~0.38\n    > y = base.dists.betaprime.cdf( -0.5, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.betaprime.cdf( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.betaprime.cdf( 2.0, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.betaprime.cdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.betaprime.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.betaprime.cdf( 0.0, 1.0, NaN )\n    NaN\n\n\nbase.dists.betaprime.cdf.factory( α, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a beta prime distribution with first shape parameter `α` and second shape\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.betaprime.cdf.factory( 0.5, 0.5 );\n    > var y = mycdf( 0.8 )\n    ~0.465\n    > y = mycdf( 0.3 )\n    ~0.319\n\n","base.dists.betaprime.cdf.factory":"\nbase.dists.betaprime.cdf.factory( α, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a beta prime distribution with first shape parameter `α` and second shape\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.betaprime.cdf.factory( 0.5, 0.5 );\n    > var y = mycdf( 0.8 )\n    ~0.465\n    > y = mycdf( 0.3 )\n    ~0.319","base.dists.betaprime.kurtosis":"\nbase.dists.betaprime.kurtosis( α, β )\n    Returns the excess kurtosis of a beta prime distribution.\n\n    If `α <= 0` or `β <= 4`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.betaprime.kurtosis( 2.0, 6.0 )\n    ~26.143\n    > v = base.dists.betaprime.kurtosis( 4.0, 12.0 )\n    ~5.764\n    > v = base.dists.betaprime.kurtosis( 8.0, 6.0 )\n    ~19.962\n\n    > v = base.dists.betaprime.kurtosis( 1.0, 2.8 )\n    NaN\n    > v = base.dists.betaprime.kurtosis( 1.0, -0.1 )\n    NaN\n    > v = base.dists.betaprime.kurtosis( -0.1, 5.0 )\n    NaN\n\n    > v = base.dists.betaprime.kurtosis( 2.0, NaN )\n    NaN\n    > v = base.dists.betaprime.kurtosis( NaN, 6.0 )\n    NaN\n\n","base.dists.betaprime.logcdf":"\nbase.dists.betaprime.logcdf( x, α, β )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a beta prime distribution with first shape parameter `α` and\n    second shape parameter `β` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.betaprime.logcdf( 0.5, 1.0, 1.0 )\n    ~-1.099\n    > y = base.dists.betaprime.logcdf( 0.5, 2.0, 4.0 )\n    ~-0.618\n    > y = base.dists.betaprime.logcdf( 0.2, 2.0, 2.0 )\n    ~-2.603\n    > y = base.dists.betaprime.logcdf( 0.8, 4.0, 4.0 )\n    ~-0.968\n    > y = base.dists.betaprime.logcdf( -0.5, 4.0, 2.0 )\n    -Infinity\n\n    > y = base.dists.betaprime.logcdf( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.betaprime.logcdf( 2.0, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.betaprime.logcdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.betaprime.logcdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.betaprime.logcdf( 0.0, 1.0, NaN )\n    NaN\n\n\nbase.dists.betaprime.logcdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a beta prime distribution with first shape\n    parameter `α` and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.betaprime.logcdf.factory( 0.5, 0.5 );\n    > var y = mylogcdf( 0.8 )\n    ~-0.767\n    > y = mylogcdf( 0.3 )\n    ~-1.143\n\n","base.dists.betaprime.logcdf.factory":"\nbase.dists.betaprime.logcdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a beta prime distribution with first shape\n    parameter `α` and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.betaprime.logcdf.factory( 0.5, 0.5 );\n    > var y = mylogcdf( 0.8 )\n    ~-0.767\n    > y = mylogcdf( 0.3 )\n    ~-1.143","base.dists.betaprime.logpdf":"\nbase.dists.betaprime.logpdf( x, α, β )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a beta prime distribution with first shape parameter `α` and second\n    shape parameter `β` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Natural logarithm of the PDF.\n\n    Examples\n    --------\n    > var y = base.dists.betaprime.logpdf( 0.5, 1.0, 1.0 )\n    ~-0.811\n    > y = base.dists.betaprime.logpdf( 0.5, 2.0, 4.0 )\n    ~-0.13\n    > y = base.dists.betaprime.logpdf( 0.2, 2.0, 2.0 )\n    ~-0.547\n    > y = base.dists.betaprime.logpdf( 0.8, 4.0, 4.0 )\n    ~-0.43\n    > y = base.dists.betaprime.logpdf( -0.5, 4.0, 2.0 )\n    -Infinity\n\n    > y = base.dists.betaprime.logpdf( 0.5, -1.0, 0.5 )\n    NaN\n    > y = base.dists.betaprime.logpdf( 0.5, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.betaprime.logpdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.betaprime.logpdf( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.dists.betaprime.logpdf( 0.5, 1.0, NaN )\n    NaN\n\n\nbase.dists.betaprime.logpdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a beta prime distribution with first shape\n    parameter `α` and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    fcn: Function\n        Function to evaluate the natural logarithm of the PDF.\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.betaprime.logpdf.factory( 0.5, 0.5 );\n    > var y = mylogpdf( 0.8 )\n    ~-1.62\n    > y = mylogpdf( 0.3 )\n    ~-0.805\n\n","base.dists.betaprime.logpdf.factory":"\nbase.dists.betaprime.logpdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a beta prime distribution with first shape\n    parameter `α` and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    fcn: Function\n        Function to evaluate the natural logarithm of the PDF.\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.betaprime.logpdf.factory( 0.5, 0.5 );\n    > var y = mylogpdf( 0.8 )\n    ~-1.62\n    > y = mylogpdf( 0.3 )\n    ~-0.805","base.dists.betaprime.mean":"\nbase.dists.betaprime.mean( α, β )\n    Returns the expected value of a beta prime distribution.\n\n    If `α <= 0` or `β <= 1`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.betaprime.mean( 1.0, 2.0 )\n    1.0\n    > v = base.dists.betaprime.mean( 4.0, 12.0 )\n    ~0.364\n    > v = base.dists.betaprime.mean( 8.0, 2.0 )\n    8.0\n\n","base.dists.betaprime.mode":"\nbase.dists.betaprime.mode( α, β )\n    Returns the mode of a beta prime distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.betaprime.mode( 1.0, 2.0 )\n    0.0\n    > v = base.dists.betaprime.mode( 4.0, 12.0 )\n    ~0.231\n    > v = base.dists.betaprime.mode( 8.0, 2.0 )\n    ~2.333\n\n","base.dists.betaprime.pdf":"\nbase.dists.betaprime.pdf( x, α, β )\n    Evaluates the probability density function (PDF) for a beta prime\n    distribution  with first shape parameter `α` and second shape parameter `β`\n    at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.betaprime.pdf( 0.5, 1.0, 1.0 )\n    ~0.444\n    > y = base.dists.betaprime.pdf( 0.5, 2.0, 4.0 )\n    ~0.878\n    > y = base.dists.betaprime.pdf( 0.2, 2.0, 2.0 )\n    ~0.579\n    > y = base.dists.betaprime.pdf( 0.8, 4.0, 4.0 )\n    ~0.65\n    > y = base.dists.betaprime.pdf( -0.5, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.betaprime.pdf( 0.5, -1.0, 0.5 )\n    NaN\n    > y = base.dists.betaprime.pdf( 0.5, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.betaprime.pdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.betaprime.pdf( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.dists.betaprime.pdf( 0.5, 1.0, NaN )\n    NaN\n\n\nbase.dists.betaprime.pdf.factory( α, β )\n    Returns a function for evaluating the probability density function (PDF) of\n    a beta prime distribution with first shape parameter `α` and second shape\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var mypdf = base.dists.betaprime.pdf.factory( 0.5, 0.5 );\n    > var y = mypdf( 0.8 )\n    ~0.198\n    > y = mypdf( 0.3 )\n    ~0.447\n\n","base.dists.betaprime.pdf.factory":"\nbase.dists.betaprime.pdf.factory( α, β )\n    Returns a function for evaluating the probability density function (PDF) of\n    a beta prime distribution with first shape parameter `α` and second shape\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var mypdf = base.dists.betaprime.pdf.factory( 0.5, 0.5 );\n    > var y = mypdf( 0.8 )\n    ~0.198\n    > y = mypdf( 0.3 )\n    ~0.447","base.dists.betaprime.quantile":"\nbase.dists.betaprime.quantile( p, α, β )\n    Evaluates the quantile function for a beta prime distribution with first\n    shape parameter `α` and second shape parameter `β` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input value (probability).\n\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.betaprime.quantile( 0.8, 2.0, 1.0 )\n    ~8.472\n    > y = base.dists.betaprime.quantile( 0.5, 4.0, 2.0 )\n    ~2.187\n    > y = base.dists.betaprime.quantile( 1.1, 1.0, 1.0 )\n    NaN\n    > y = base.dists.betaprime.quantile( -0.2, 1.0, 1.0 )\n    NaN\n\n    > y = base.dists.betaprime.quantile( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.betaprime.quantile( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.dists.betaprime.quantile( 0.5, 1.0, NaN )\n    NaN\n\n    > y = base.dists.betaprime.quantile( 0.5, -1.0, 1.0 )\n    NaN\n    > y = base.dists.betaprime.quantile( 0.5, 1.0, -1.0 )\n    NaN\n\n\nbase.dists.betaprime.quantile.factory( α, β )\n    Returns a function for evaluating the quantile function of a beta prime\n    distribution with first shape parameter `α` and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.betaprime.quantile.factory( 2.0, 2.0 );\n    > y = myQuantile( 0.8 )\n    ~2.483\n    > y = myQuantile( 0.4 )\n    ~0.763\n\n","base.dists.betaprime.quantile.factory":"\nbase.dists.betaprime.quantile.factory( α, β )\n    Returns a function for evaluating the quantile function of a beta prime\n    distribution with first shape parameter `α` and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.betaprime.quantile.factory( 2.0, 2.0 );\n    > y = myQuantile( 0.8 )\n    ~2.483\n    > y = myQuantile( 0.4 )\n    ~0.763","base.dists.betaprime.skewness":"\nbase.dists.betaprime.skewness( α, β )\n    Returns the skewness of a beta prime distribution.\n\n    If `α <= 0` or `β <= 3`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.betaprime.skewness( 2.0, 4.0 )\n    ~6.261\n    > v = base.dists.betaprime.skewness( 4.0, 12.0 )\n    ~1.724\n    > v = base.dists.betaprime.skewness( 8.0, 4.0 )\n    ~5.729\n\n    > v = base.dists.betaprime.skewness( 1.0, 2.8 )\n    NaN\n    > v = base.dists.betaprime.skewness( 1.0, -0.1 )\n    NaN\n    > v = base.dists.betaprime.skewness( -0.1, 4.0 )\n    NaN\n\n    > v = base.dists.betaprime.skewness( 2.0, NaN )\n    NaN\n    > v = base.dists.betaprime.skewness( NaN, 4.0 )\n    NaN\n\n","base.dists.betaprime.stdev":"\nbase.dists.betaprime.stdev( α, β )\n    Returns the standard deviation of a beta prime distribution.\n\n    If `α <= 0` or `β <= 2`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.betaprime.stdev( 1.0, 2.5 )\n    ~1.491\n    > v = base.dists.betaprime.stdev( 4.0, 12.0 )\n    ~0.223\n    > v = base.dists.betaprime.stdev( 8.0, 2.5 )\n    ~8.219\n\n    > v = base.dists.betaprime.stdev( 8.0, 1.0 )\n    NaN\n    > v = base.dists.betaprime.stdev( 1.0, -0.1 )\n    NaN\n    > v = base.dists.betaprime.stdev( -0.1, 3.0 )\n    NaN\n\n    > v = base.dists.betaprime.stdev( 2.0, NaN )\n    NaN\n    > v = base.dists.betaprime.stdev( NaN, 3.0 )\n    NaN\n\n","base.dists.betaprime.variance":"\nbase.dists.betaprime.variance( α, β )\n    Returns the variance of a beta prime distribution.\n\n    If `α <= 0` or `β <= 2`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.betaprime.variance( 1.0, 2.5 )\n    ~2.222\n    > v = base.dists.betaprime.variance( 4.0, 12.0 )\n    ~0.05\n    > v = base.dists.betaprime.variance( 8.0, 2.5 )\n    ~67.556\n\n    > v = base.dists.betaprime.variance( 8.0, 1.0 )\n    NaN\n    > v = base.dists.betaprime.variance( 1.0, -0.1 )\n    NaN\n    > v = base.dists.betaprime.variance( -0.1, 3.0 )\n    NaN\n\n    > v = base.dists.betaprime.variance( 2.0, NaN )\n    NaN\n    > v = base.dists.betaprime.variance( NaN, 3.0 )\n    NaN\n\n","base.dists.binomial.Binomial":"\nbase.dists.binomial.Binomial( [n, p] )\n    Returns a binomial distribution object.\n\n    Parameters\n    ----------\n    n: integer (optional)\n        Number of trials. Must be a positive integer. Default: `1`.\n\n    p: number (optional)\n        Success probability. Must be a number between `0` and `1`. Default:\n        `0.5`.\n\n    Returns\n    -------\n    binomial: Object\n        Distribution instance.\n\n    binomial.n: number\n        Number of trials. If set, the value must be a positive integer.\n\n    binomial.p: number\n        Success probability. If set, the value must be a number between `0` and\n        `1`.\n\n    binomial.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    binomial.mean: number\n        Read-only property which returns the expected value.\n\n    binomial.median: number\n        Read-only property which returns the median.\n\n    binomial.mode: number\n        Read-only property which returns the mode.\n\n    binomial.skewness: number\n        Read-only property which returns the skewness.\n\n    binomial.stdev: number\n        Read-only property which returns the standard deviation.\n\n    binomial.variance: number\n        Read-only property which returns the variance.\n\n    binomial.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    binomial.logpmf: Function\n        Evaluates the natural logarithm of the probability mass function (PMF).\n\n    binomial.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    binomial.pmf: Function\n        Evaluates the probability mass function (PMF).\n\n    binomial.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var binomial = base.dists.binomial.Binomial( 8, 0.5 );\n    > binomial.n\n    8.0\n    > binomial.p\n    0.5\n    > binomial.kurtosis\n    -0.25\n    > binomial.mean\n    4.0\n    > binomial.median\n    4.0\n    > binomial.mode\n    4.0\n    > binomial.skewness\n    0.0\n    > binomial.stdev\n    ~1.414\n    > binomial.variance\n    2.0\n    > binomial.cdf( 2.9 )\n    ~0.145\n    > binomial.logpmf( 3.0 )\n    ~-1.52\n    > binomial.mgf( 0.2 )\n    ~2.316\n    > binomial.pmf( 3.0 )\n    ~0.219\n    > binomial.quantile( 0.8 )\n    5.0\n\n","base.dists.binomial.cdf":"\nbase.dists.binomial.cdf( x, n, p )\n    Evaluates the cumulative distribution function (CDF) for a binomial\n    distribution with number of trials `n` and success probability `p` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.binomial.cdf( 3.0, 20, 0.2 )\n    ~0.411\n    > y = base.dists.binomial.cdf( 21.0, 20, 0.2 )\n    1.0\n    > y = base.dists.binomial.cdf( 5.0, 10, 0.4 )\n    ~0.834\n    > y = base.dists.binomial.cdf( 0.0, 10, 0.4 )\n    ~0.006\n    > y = base.dists.binomial.cdf( NaN, 20, 0.5 )\n    NaN\n    > y = base.dists.binomial.cdf( 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.binomial.cdf( 0.0, 20, NaN )\n    NaN\n    > y = base.dists.binomial.cdf( 2.0, 1.5, 0.5 )\n    NaN\n    > y = base.dists.binomial.cdf( 2.0, -2.0, 0.5 )\n    NaN\n    > y = base.dists.binomial.cdf( 2.0, 20, -1.0 )\n    NaN\n    > y = base.dists.binomial.cdf( 2.0, 20, 1.5 )\n    NaN\n\n\nbase.dists.binomial.cdf.factory( n, p )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a binomial distribution with number of trials `n` and success probability\n    `p`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.binomial.cdf.factory( 10, 0.5 );\n    > var y = mycdf( 3.0 )\n    ~0.172\n    > y = mycdf( 1.0 )\n    ~0.011\n\n","base.dists.binomial.cdf.factory":"\nbase.dists.binomial.cdf.factory( n, p )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a binomial distribution with number of trials `n` and success probability\n    `p`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.binomial.cdf.factory( 10, 0.5 );\n    > var y = mycdf( 3.0 )\n    ~0.172\n    > y = mycdf( 1.0 )\n    ~0.011","base.dists.binomial.entropy":"\nbase.dists.binomial.entropy( n, p )\n    Returns the entropy of a binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.binomial.entropy( 100, 0.1 )\n    ~2.511\n    > v = base.dists.binomial.entropy( 20, 0.5 )\n    ~2.223\n    > v = base.dists.binomial.entropy( 10.3, 0.5 )\n    NaN\n    > v = base.dists.binomial.entropy( 20, 1.1 )\n    NaN\n    > v = base.dists.binomial.entropy( 20, NaN )\n    NaN\n\n","base.dists.binomial.kurtosis":"\nbase.dists.binomial.kurtosis( n, p )\n    Returns the excess kurtosis of a binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.binomial.kurtosis( 100, 0.1 )\n    ~0.051\n    > v = base.dists.binomial.kurtosis( 20, 0.5 )\n    ~-0.1\n    > v = base.dists.binomial.kurtosis( 10.3, 0.5 )\n    NaN\n    > v = base.dists.binomial.kurtosis( 20, 1.1 )\n    NaN\n    > v = base.dists.binomial.kurtosis( 20, NaN )\n    NaN\n\n","base.dists.binomial.logpmf":"\nbase.dists.binomial.logpmf( x, n, p )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    binomial distribution with number of trials `n` and success probability `p`\n    at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPMF.\n\n    Examples\n    --------\n    > var y = base.dists.binomial.logpmf( 3.0, 20, 0.2 )\n    ~-1.583\n    > y = base.dists.binomial.logpmf( 21.0, 20, 0.2 )\n    -Infinity\n    > y = base.dists.binomial.logpmf( 5.0, 10, 0.4 )\n    ~-1.606\n    > y = base.dists.binomial.logpmf( 0.0, 10, 0.4 )\n    ~-5.108\n    > y = base.dists.binomial.logpmf( NaN, 20, 0.5 )\n    NaN\n    > y = base.dists.binomial.logpmf( 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.binomial.logpmf( 0.0, 20, NaN )\n    NaN\n    > y = base.dists.binomial.logpmf( 2.0, 1.5, 0.5 )\n    NaN\n    > y = base.dists.binomial.logpmf( 2.0, -2.0, 0.5 )\n    NaN\n    > y = base.dists.binomial.logpmf( 2.0, 20, -1.0 )\n    NaN\n    > y = base.dists.binomial.logpmf( 2.0, 20, 1.5 )\n    NaN\n\n\nbase.dists.binomial.logpmf.factory( n, p )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a binomial distribution with number of trials `n` and\n    success probability `p`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogpmf = base.dists.binomial.logpmf.factory( 10, 0.5 );\n    > var y = mylogpmf( 3.0 )\n    ~-2.144\n    > y = mylogpmf( 5.0 )\n    ~-1.402\n\n","base.dists.binomial.logpmf.factory":"\nbase.dists.binomial.logpmf.factory( n, p )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a binomial distribution with number of trials `n` and\n    success probability `p`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogpmf = base.dists.binomial.logpmf.factory( 10, 0.5 );\n    > var y = mylogpmf( 3.0 )\n    ~-2.144\n    > y = mylogpmf( 5.0 )\n    ~-1.402","base.dists.binomial.mean":"\nbase.dists.binomial.mean( n, p )\n    Returns the expected value of a binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.binomial.mean( 100, 0.1 )\n    10.0\n    > v = base.dists.binomial.mean( 20, 0.5 )\n    10.0\n    > v = base.dists.binomial.mean( 10.3, 0.5 )\n    NaN\n    > v = base.dists.binomial.mean( 20, 1.1 )\n    NaN\n    > v = base.dists.binomial.mean( 20, NaN )\n    NaN\n\n","base.dists.binomial.median":"\nbase.dists.binomial.median( n, p )\n    Returns the median of a binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.binomial.median( 100, 0.1 )\n    10\n    > v = base.dists.binomial.median( 20, 0.5 )\n    10\n    > v = base.dists.binomial.median( 10.3, 0.5 )\n    NaN\n    > v = base.dists.binomial.median( 20, 1.1 )\n    NaN\n    > v = base.dists.binomial.median( 20, NaN )\n    NaN\n\n","base.dists.binomial.mgf":"\nbase.dists.binomial.mgf( t, n, p )\n    Evaluates the moment-generating function (MGF) for a binomial distribution\n    with number of trials `n` and success probability `p` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.binomial.mgf( 0.5, 20, 0.2 )\n    ~11.471\n    > y = base.dists.binomial.mgf( 5.0, 20, 0.2 )\n    ~4.798e+29\n    > y = base.dists.binomial.mgf( 0.9, 10, 0.4 )\n    ~99.338\n    > y = base.dists.binomial.mgf( 0.0, 10, 0.4 )\n    1.0\n\n    > y = base.dists.binomial.mgf( NaN, 20, 0.5 )\n    NaN\n    > y = base.dists.binomial.mgf( 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.binomial.mgf( 0.0, 20, NaN )\n    NaN\n\n    > y = base.dists.binomial.mgf( 2.0, 1.5, 0.5 )\n    NaN\n    > y = base.dists.binomial.mgf( 2.0, -2.0, 0.5 )\n    NaN\n    > y = base.dists.binomial.mgf( 2.0, 20, -1.0 )\n    NaN\n    > y = base.dists.binomial.mgf( 2.0, 20, 1.5 )\n    NaN\n\n\nbase.dists.binomial.mgf.factory( n, p )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    binomial distribution with number of trials `n` and success probability `p`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.binomial.mgf.factory( 10, 0.5 );\n    > var y = myMGF( 0.3 )\n    ~5.013\n\n","base.dists.binomial.mgf.factory":"\nbase.dists.binomial.mgf.factory( n, p )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    binomial distribution with number of trials `n` and success probability `p`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.binomial.mgf.factory( 10, 0.5 );\n    > var y = myMGF( 0.3 )\n    ~5.013","base.dists.binomial.mode":"\nbase.dists.binomial.mode( n, p )\n    Returns the mode of a binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.binomial.mode( 100, 0.1 )\n    10\n    > v = base.dists.binomial.mode( 20, 0.5 )\n    10\n    > v = base.dists.binomial.mode( 10.3, 0.5 )\n    NaN\n    > v = base.dists.binomial.mode( 20, 1.1 )\n    NaN\n    > v = base.dists.binomial.mode( 20, NaN )\n    NaN\n\n","base.dists.binomial.pmf":"\nbase.dists.binomial.pmf( x, n, p )\n    Evaluates the probability mass function (PMF) for a binomial distribution\n    with number of trials `n` and success probability `p` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated PMF.\n\n    Examples\n    --------\n    > var y = base.dists.binomial.pmf( 3.0, 20, 0.2 )\n    ~0.205\n    > y = base.dists.binomial.pmf( 21.0, 20, 0.2 )\n    0.0\n    > y = base.dists.binomial.pmf( 5.0, 10, 0.4 )\n    ~0.201\n    > y = base.dists.binomial.pmf( 0.0, 10, 0.4 )\n    ~0.006\n    > y = base.dists.binomial.pmf( NaN, 20, 0.5 )\n    NaN\n    > y = base.dists.binomial.pmf( 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.binomial.pmf( 0.0, 20, NaN )\n    NaN\n    > y = base.dists.binomial.pmf( 2.0, 1.5, 0.5 )\n    NaN\n    > y = base.dists.binomial.pmf( 2.0, -2.0, 0.5 )\n    NaN\n    > y = base.dists.binomial.pmf( 2.0, 20, -1.0 )\n    NaN\n    > y = base.dists.binomial.pmf( 2.0, 20, 1.5 )\n    NaN\n\n\nbase.dists.binomial.pmf.factory( n, p )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    binomial distribution with number of trials `n` and success probability `p`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var mypmf = base.dists.binomial.pmf.factory( 10, 0.5 );\n    > var y = mypmf( 3.0 )\n    ~0.117\n    > y = mypmf( 5.0 )\n    ~0.246\n\n","base.dists.binomial.pmf.factory":"\nbase.dists.binomial.pmf.factory( n, p )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    binomial distribution with number of trials `n` and success probability `p`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var mypmf = base.dists.binomial.pmf.factory( 10, 0.5 );\n    > var y = mypmf( 3.0 )\n    ~0.117\n    > y = mypmf( 5.0 )\n    ~0.246","base.dists.binomial.quantile":"\nbase.dists.binomial.quantile( r, n, p )\n    Evaluates the quantile function for a binomial distribution with number of\n    trials `n` and success probability `p` at a probability `r`.\n\n    If `r < 0` or `r > 1`, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    r: number\n        Input probability.\n\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.binomial.quantile( 0.4, 20, 0.2 )\n    3\n    > y = base.dists.binomial.quantile( 0.8, 20, 0.2 )\n    5\n    > y = base.dists.binomial.quantile( 0.5, 10, 0.4 )\n    4\n    > y = base.dists.binomial.quantile( 0.0, 10, 0.4 )\n    0\n    > y = base.dists.binomial.quantile( 1.0, 10, 0.4 )\n    10\n\n    > y = base.dists.binomial.quantile( NaN, 20, 0.5 )\n    NaN\n    > y = base.dists.binomial.quantile( 0.2, NaN, 0.5 )\n    NaN\n    > y = base.dists.binomial.quantile( 0.2, 20, NaN )\n    NaN\n\n    > y = base.dists.binomial.quantile( 0.5, 1.5, 0.5 )\n    NaN\n    > y = base.dists.binomial.quantile( 0.5, -2.0, 0.5 )\n    NaN\n\n    > y = base.dists.binomial.quantile( 0.5, 20, -1.0 )\n    NaN\n    > y = base.dists.binomial.quantile( 0.5, 20, 1.5 )\n    NaN\n\n\nbase.dists.binomial.quantile.factory( n, p )\n    Returns a function for evaluating the quantile function of a binomial\n    distribution with number of trials `n` and success probability `p`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.binomial.quantile.factory( 10, 0.5 );\n    > var y = myquantile( 0.1 )\n    3\n    > y = myquantile( 0.9 )\n    7\n\n","base.dists.binomial.quantile.factory":"\nbase.dists.binomial.quantile.factory( n, p )\n    Returns a function for evaluating the quantile function of a binomial\n    distribution with number of trials `n` and success probability `p`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.binomial.quantile.factory( 10, 0.5 );\n    > var y = myquantile( 0.1 )\n    3\n    > y = myquantile( 0.9 )\n    7","base.dists.binomial.skewness":"\nbase.dists.binomial.skewness( n, p )\n    Returns the skewness of a binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.binomial.skewness( 100, 0.1 )\n    ~0.267\n    > v = base.dists.binomial.skewness( 20, 0.5 )\n    0.0\n    > v = base.dists.binomial.skewness( 10.3, 0.5 )\n    NaN\n    > v = base.dists.binomial.skewness( 20, 1.1 )\n    NaN\n    > v = base.dists.binomial.skewness( 20, NaN )\n    NaN\n\n","base.dists.binomial.stdev":"\nbase.dists.binomial.stdev( n, p )\n    Returns the standard deviation of a binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.binomial.stdev( 100, 0.1 )\n    3.0\n    > v = base.dists.binomial.stdev( 20, 0.5 )\n    ~2.236\n    > v = base.dists.binomial.stdev( 10.3, 0.5 )\n    NaN\n    > v = base.dists.binomial.stdev( 20, 1.1 )\n    NaN\n    > v = base.dists.binomial.stdev( 20, NaN )\n    NaN\n\n","base.dists.binomial.variance":"\nbase.dists.binomial.variance( n, p )\n    Returns the variance of a binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.binomial.variance( 100, 0.1 )\n    9\n    > v = base.dists.binomial.variance( 20, 0.5 )\n    5\n    > v = base.dists.binomial.variance( 10.3, 0.5 )\n    NaN\n    > v = base.dists.binomial.variance( 20, 1.1 )\n    NaN\n    > v = base.dists.binomial.variance( 20, NaN )\n    NaN\n\n","base.dists.cauchy.Cauchy":"\nbase.dists.cauchy.Cauchy( [x0, Ɣ] )\n    Returns a Cauchy distribution object.\n\n    Parameters\n    ----------\n    x0: number (optional)\n        Location parameter. Default: `0.0`.\n\n    Ɣ: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    cauchy: Object\n        Distribution instance.\n\n    cauchy.x0: number\n        Location parameter.\n\n    cauchy.gamma: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    cauchy.entropy: number\n        Read-only property which returns the differential entropy.\n\n    cauchy.median: number\n        Read-only property which returns the median.\n\n    cauchy.mode: number\n        Read-only property which returns the mode.\n\n    cauchy.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    cauchy.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    cauchy.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    cauchy.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    cauchy.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var cauchy = base.dists.cauchy.Cauchy( 0.0, 1.0 );\n    > cauchy.x0\n    0.0\n    > cauchy.gamma\n    1.0\n    > cauchy.entropy\n    ~2.531\n    > cauchy.median\n    0.0\n    > cauchy.mode\n    0.0\n    > cauchy.cdf( 0.8 )\n    ~0.715\n    > cauchy.logcdf( 1.0 )\n    ~-0.288\n    > cauchy.logpdf( 1.0 )\n    ~-1.838\n    > cauchy.pdf( 1.0 )\n    ~0.159\n    > cauchy.quantile( 0.8 )\n    ~1.376\n\n","base.dists.cauchy.cdf":"\nbase.dists.cauchy.cdf( x, x0, Ɣ )\n    Evaluates the cumulative distribution function (CDF) for a Cauchy\n    distribution with location parameter `x0` and scale parameter `Ɣ` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `Ɣ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.cauchy.cdf( 4.0, 0.0, 2.0 )\n    ~0.852\n    > y = base.dists.cauchy.cdf( 1.0, 0.0, 2.0 )\n    ~0.648\n    > y = base.dists.cauchy.cdf( 1.0, 3.0, 2.0 )\n    0.25\n    > y = base.dists.cauchy.cdf( NaN, 0.0, 2.0 )\n    NaN\n    > y = base.dists.cauchy.cdf( 1.0, 2.0, NaN )\n    NaN\n    > y = base.dists.cauchy.cdf( 1.0, NaN, 3.0 )\n    NaN\n\n\nbase.dists.cauchy.cdf.factory( x0, Ɣ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Cauchy distribution with location parameter `x0` and scale parameter\n    `Ɣ`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.cauchy.cdf.factory( 1.5, 3.0 );\n    > var y = myCDF( 1.0 )\n    ~0.447\n\n","base.dists.cauchy.cdf.factory":"\nbase.dists.cauchy.cdf.factory( x0, Ɣ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Cauchy distribution with location parameter `x0` and scale parameter\n    `Ɣ`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.cauchy.cdf.factory( 1.5, 3.0 );\n    > var y = myCDF( 1.0 )\n    ~0.447","base.dists.cauchy.entropy":"\nbase.dists.cauchy.entropy( x0, Ɣ )\n    Returns the differential entropy of a Cauchy distribution (in nats).\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `Ɣ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.cauchy.entropy( 10.0, 7.0 )\n    ~4.477\n    > v = base.dists.cauchy.entropy( 22.0, 0.5 )\n    ~1.838\n    > v = base.dists.cauchy.entropy( 10.3, -0.5 )\n    NaN\n\n","base.dists.cauchy.logcdf":"\nbase.dists.cauchy.logcdf( x, x0, Ɣ )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (logCDF) for a Cauchy distribution with location parameter `x0` and scale\n    parameter `Ɣ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `Ɣ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Natural logarithm of the CDF.\n\n    Examples\n    --------\n    > var y = base.dists.cauchy.logcdf( 4.0, 0.0, 2.0 )\n    ~-0.16\n    > y = base.dists.cauchy.logcdf( 1.0, 0.0, 2.0 )\n    ~-0.435\n    > y = base.dists.cauchy.logcdf( 1.0, 3.0, 2.0 )\n    ~-1.386\n    > y = base.dists.cauchy.logcdf( NaN, 0.0, 2.0 )\n    NaN\n    > y = base.dists.cauchy.logcdf( 1.0, 2.0, NaN )\n    NaN\n    > y = base.dists.cauchy.logcdf( 1.0, NaN, 3.0 )\n    NaN\n\n\nbase.dists.cauchy.logcdf.factory( x0, Ɣ )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (logCDF) of a Cauchy distribution with location\n    parameter `x0` and scale parameter `Ɣ`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Function to evaluate the natural logarithm of CDF.\n\n    Examples\n    --------\n    > var mylogCDF = base.dists.cauchy.logcdf.factory( 1.5, 3.0 );\n    > var y = mylogCDF( 1.0 )\n    ~-0.804\n\n","base.dists.cauchy.logcdf.factory":"\nbase.dists.cauchy.logcdf.factory( x0, Ɣ )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (logCDF) of a Cauchy distribution with location\n    parameter `x0` and scale parameter `Ɣ`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Function to evaluate the natural logarithm of CDF.\n\n    Examples\n    --------\n    > var mylogCDF = base.dists.cauchy.logcdf.factory( 1.5, 3.0 );\n    > var y = mylogCDF( 1.0 )\n    ~-0.804","base.dists.cauchy.logpdf":"\nbase.dists.cauchy.logpdf( x, x0, Ɣ )\n    Evaluates the natural logarithm of the probability density function (logPDF)\n    for a Cauchy distribution with location parameter `x0` and scale parameter\n    `Ɣ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `Ɣ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Natural logarithm of PDF.\n\n    Examples\n    --------\n    > var y = base.dists.cauchy.logpdf( 2.0, 1.0, 1.0 )\n    ~-1.838\n    > y = base.dists.cauchy.logpdf( 4.0, 3.0, 0.1 )\n    ~-3.457\n    > y = base.dists.cauchy.logpdf( 4.0, 3.0, 3.0 )\n    ~-2.349\n    > y = base.dists.cauchy.logpdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.cauchy.logpdf( 2.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.cauchy.logpdf( 2.0, 1.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.cauchy.logpdf( 2.0, 1.0, -2.0 )\n    NaN\n\n\nbase.dists.cauchy.logpdf.factory( x0, Ɣ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (logPDF) of a Cauchy distribution with location parameter\n    `x0` and scale parameter `Ɣ`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Function to evaluate the natural logarithm of the PDF.\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.cauchy.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogPDF( 10.0 )\n    ~-1.838\n\n","base.dists.cauchy.logpdf.factory":"\nbase.dists.cauchy.logpdf.factory( x0, Ɣ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (logPDF) of a Cauchy distribution with location parameter\n    `x0` and scale parameter `Ɣ`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Function to evaluate the natural logarithm of the PDF.\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.cauchy.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogPDF( 10.0 )\n    ~-1.838","base.dists.cauchy.median":"\nbase.dists.cauchy.median( x0, Ɣ )\n    Returns the median of a Cauchy distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `Ɣ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.cauchy.median( 10.0, 5.0 )\n    10.0\n    > v = base.dists.cauchy.median( 7.0, 0.5 )\n    7.0\n    > v = base.dists.cauchy.median( 10.3, -0.5 )\n    NaN\n\n","base.dists.cauchy.mode":"\nbase.dists.cauchy.mode( x0, Ɣ )\n    Returns the mode of a Cauchy distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `Ɣ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.cauchy.mode( 10.0, 5.0 )\n    10.0\n    > v = base.dists.cauchy.mode( 7.0, 0.5 )\n    7.0\n    > v = base.dists.cauchy.mode( 10.3, -0.5 )\n    NaN\n\n","base.dists.cauchy.pdf":"\nbase.dists.cauchy.pdf( x, x0, Ɣ )\n    Evaluates the probability density function (PDF) for a Cauchy distribution\n    with location parameter `x0` and scale parameter `Ɣ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `Ɣ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.cauchy.pdf( 2.0, 1.0, 1.0 )\n    ~0.159\n    > y = base.dists.cauchy.pdf( 4.0, 3.0, 0.1 )\n    ~0.0315\n    > y = base.dists.cauchy.pdf( 4.0, 3.0, 3.0 )\n    ~0.095\n    > y = base.dists.cauchy.pdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.cauchy.pdf( 2.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.cauchy.pdf( 2.0, 1.0, NaN )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.cauchy.pdf( 2.0, 1.0, -2.0 )\n    NaN\n\n\nbase.dists.cauchy.pdf.factory( x0, Ɣ )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Cauchy distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.cauchy.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    ~0.159\n\n","base.dists.cauchy.pdf.factory":"\nbase.dists.cauchy.pdf.factory( x0, Ɣ )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Cauchy distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.cauchy.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    ~0.159","base.dists.cauchy.quantile":"\nbase.dists.cauchy.quantile( p, x0, Ɣ )\n    Evaluates the quantile function for a Cauchy distribution with location\n    parameter `x0`  and scale parameter `Ɣ` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `Ɣ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.cauchy.quantile( 0.3, 2.0, 2.0 )\n    ~0.547\n    > y = base.dists.cauchy.quantile( 0.8, 10, 2.0 )\n    ~12.753\n    > y = base.dists.cauchy.quantile( 0.1, 10.0, 2.0 )\n    ~3.845\n\n    > y = base.dists.cauchy.quantile( 1.1, 0.0, 1.0 )\n    NaN\n    > y = base.dists.cauchy.quantile( -0.2, 0.0, 1.0 )\n    NaN\n\n    > y = base.dists.cauchy.quantile( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.cauchy.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.cauchy.quantile( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.cauchy.quantile( 0.5, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.cauchy.quantile.factory( x0, Ɣ )\n    Returns a function for evaluating the quantile function of a Cauchy\n    distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.cauchy.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    10.0\n\n","base.dists.cauchy.quantile.factory":"\nbase.dists.cauchy.quantile.factory( x0, Ɣ )\n    Returns a function for evaluating the quantile function of a Cauchy\n    distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.cauchy.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    10.0","base.dists.chi.cdf":"\nbase.dists.chi.cdf( x, k )\n    Evaluates the cumulative distribution function (CDF) for a chi distribution\n    with degrees of freedom `k` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.chi.cdf( 2.0, 3.0 )\n    ~0.739\n    > y = base.dists.chi.cdf( 1.0, 0.5 )\n    ~0.846\n    > y = base.dists.chi.cdf( -1.0, 4.0 )\n    0.0\n    > y = base.dists.chi.cdf( NaN, 1.0 )\n    NaN\n    > y = base.dists.chi.cdf( 0.0, NaN )\n    NaN\n\n    // Negative degrees of freedom:\n    > y = base.dists.chi.cdf( 2.0, -1.0 )\n    NaN\n\n    // Degenerate distribution when `k = 0`:\n    > y = base.dists.chi.cdf( 2.0, 0.0 )\n    1.0\n    > y = base.dists.chi.cdf( -2.0, 0.0 )\n    0.0\n    > y = base.dists.chi.cdf( 0.0, 0.0 )\n    0.0\n\nbase.dists.chi.cdf.factory( k )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a chi distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.chi.cdf.factory( 1.0 );\n    > var y = mycdf( 2.0 )\n    ~0.954\n    > y = mycdf( 1.2 )\n    ~0.77\n\n","base.dists.chi.cdf.factory":"\nbase.dists.chi.cdf.factory( k )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a chi distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.chi.cdf.factory( 1.0 );\n    > var y = mycdf( 2.0 )\n    ~0.954\n    > y = mycdf( 1.2 )\n    ~0.77","base.dists.chi.Chi":"\nbase.dists.chi.Chi( [k] )\n    Returns a chi distribution object.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    chi: Object\n        Distribution instance.\n\n    chi.k: number\n        Degrees of freedom. If set, the value must be greater than `0`.\n\n    chi.entropy: number\n        Read-only property which returns the differential entropy.\n\n    chi.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    chi.mean: number\n        Read-only property which returns the expected value.\n\n    chi.mode: number\n        Read-only property which returns the mode.\n\n    chi.skewness: number\n        Read-only property which returns the skewness.\n\n    chi.stdev: number\n        Read-only property which returns the standard deviation.\n\n    chi.variance: number\n        Read-only property which returns the variance.\n\n    chi.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    chi.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    chi.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    chi.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var chi = base.dists.chi.Chi( 6.0 );\n    > chi.k\n    6.0\n    > chi.entropy\n    ~1.04\n    > chi.kurtosis\n    ~0.025\n    > chi.mean\n    ~2.35\n    > chi.mode\n    ~2.236\n    > chi.skewness\n    ~0.318\n    > chi.stdev\n    ~0.691\n    > chi.variance\n    ~0.478\n    > chi.cdf( 1.0 )\n    ~0.014\n    > chi.logpdf( 1.5 )\n    ~-1.177\n    > chi.pdf( 1.5 )\n    ~0.308\n    > chi.quantile( 0.5 )\n    ~2.313\n\n","base.dists.chi.entropy":"\nbase.dists.chi.entropy( k )\n    Returns the differential entropy of a chi distribution (in nats).\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.chi.entropy( 11.0 )\n    ~1.056\n    > v = base.dists.chi.entropy( 1.5 )\n    ~0.878\n\n","base.dists.chi.kurtosis":"\nbase.dists.chi.kurtosis( k )\n    Returns the excess kurtosis of a chi distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.chi.kurtosis( 9.0 )\n    ~0.011\n    > v = base.dists.chi.kurtosis( 1.5 )\n    ~0.424\n\n","base.dists.chi.logpdf":"\nbase.dists.chi.logpdf( x, k )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a chi distribution with degrees of freedom `k` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.chi.logpdf( 0.3, 4.0 )\n    ~-4.35\n    > y = base.dists.chi.logpdf( 0.7, 0.7 )\n    ~-0.622\n    > y = base.dists.chi.logpdf( -1.0, 0.5 )\n    -Infinity\n    > y = base.dists.chi.logpdf( 0.0, NaN )\n    NaN\n    > y = base.dists.chi.logpdf( NaN, 2.0 )\n    NaN\n\n    // Negative degrees of freedom:\n    > y = base.dists.chi.logpdf( 2.0, -1.0 )\n    NaN\n\n    // Degenerate distribution when `k = 0`:\n    > y = base.dists.chi.logpdf( 2.0, 0.0, 2.0 )\n    -Infinity\n    > y = base.dists.chi.logpdf( 0.0, 0.0, 2.0 )\n    Infinity\n\n\nbase.dists.chi.logpdf.factory( k )\n    Returns a function for evaluating the natural logarithm of the  probability\n    density function (PDF) of a chi distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.chi.logpdf.factory( 6.0 );\n    > var y = mylogPDF( 3.0 )\n    ~-1.086\n\n","base.dists.chi.logpdf.factory":"\nbase.dists.chi.logpdf.factory( k )\n    Returns a function for evaluating the natural logarithm of the  probability\n    density function (PDF) of a chi distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.chi.logpdf.factory( 6.0 );\n    > var y = mylogPDF( 3.0 )\n    ~-1.086","base.dists.chi.mean":"\nbase.dists.chi.mean( k )\n    Returns the expected value of a chi distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.chi.mean( 11.0 )\n    ~3.242\n    > v = base.dists.chi.mean( 4.5 )\n    ~2.008\n\n","base.dists.chi.mode":"\nbase.dists.chi.mode( k )\n    Returns the mode of a chi distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.chi.mode( 11.0 )\n    ~3.162\n    > v = base.dists.chi.mode( 1.5 )\n    ~0.707\n\n","base.dists.chi.pdf":"\nbase.dists.chi.pdf( x, k )\n    Evaluates the probability density function (PDF) for a chi distribution with\n    degrees of freedom `k` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.chi.pdf( 0.3, 4.0 )\n    ~0.013\n    > y = base.dists.chi.pdf( 0.7, 0.7 )\n    ~0.537\n    > y = base.dists.chi.pdf( -1.0, 0.5 )\n    0.0\n    > y = base.dists.chi.pdf( 0.0, NaN )\n    NaN\n    > y = base.dists.chi.pdf( NaN, 2.0 )\n    NaN\n\n    // Negative degrees of freedom:\n    > y = base.dists.chi.pdf( 2.0, -1.0 )\n    NaN\n\n    // Degenerate distribution when `k = 0`:\n    > y = base.dists.chi.pdf( 2.0, 0.0, 2.0 )\n    0.0\n    > y = base.dists.chi.pdf( 0.0, 0.0, 2.0 )\n    Infinity\n\n\nbase.dists.chi.pdf.factory( k )\n    Returns a function for evaluating the probability density function (PDF) of\n    a chi distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.chi.pdf.factory( 6.0 );\n    > var y = myPDF( 3.0 )\n    ~0.337\n\n","base.dists.chi.pdf.factory":"\nbase.dists.chi.pdf.factory( k )\n    Returns a function for evaluating the probability density function (PDF) of\n    a chi distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.chi.pdf.factory( 6.0 );\n    > var y = myPDF( 3.0 )\n    ~0.337","base.dists.chi.quantile":"\nbase.dists.chi.quantile( p, k )\n    Evaluates the quantile function for a chi distribution with degrees of\n    freedom `k` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.chi.quantile( 0.8, 1.0 )\n    ~1.282\n    > y = base.dists.chi.quantile( 0.5, 4.0 )\n    ~1.832\n    > y = base.dists.chi.quantile( 0.8, 0.1 )\n    ~0.116\n    > y = base.dists.chi.quantile( -0.2, 0.5 )\n    NaN\n    > y = base.dists.chi.quantile( 1.1, 0.5 )\n    NaN\n    > y = base.dists.chi.quantile( NaN, 1.0 )\n    NaN\n    > y = base.dists.chi.quantile( 0.0, NaN )\n    NaN\n\n    // Negative degrees of freedom:\n    > y = base.dists.chi.quantile( 0.5, -1.0 )\n    NaN\n\n    // Degenerate distribution when `k = 0`:\n    > y = base.dists.chi.quantile( 0.3, 0.0 )\n    0.0\n    > y = base.dists.chi.quantile( 0.9, 0.0 )\n    0.0\n\n\nbase.dists.chi.quantile.factory( k )\n    Returns a function for evaluating the quantile function of a chi\n    distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.chi.quantile.factory( 2.0 );\n    > var y = myquantile( 0.3 )\n    ~0.845\n    > y = myquantile( 0.7 )\n    ~1.552\n\n","base.dists.chi.quantile.factory":"\nbase.dists.chi.quantile.factory( k )\n    Returns a function for evaluating the quantile function of a chi\n    distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.chi.quantile.factory( 2.0 );\n    > var y = myquantile( 0.3 )\n    ~0.845\n    > y = myquantile( 0.7 )\n    ~1.552","base.dists.chi.skewness":"\nbase.dists.chi.skewness( k )\n    Returns the skewness of a chi distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.chi.skewness( 11.0 )\n    ~0.225\n    > v = base.dists.chi.skewness( 1.5 )\n    ~0.763\n\n","base.dists.chi.stdev":"\nbase.dists.chi.stdev( k )\n    Returns the standard deviation of a chi distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.chi.stdev( 11.0 )\n    ~0.699\n    > v = base.dists.chi.stdev( 1.5 )\n    ~0.637\n\n","base.dists.chi.variance":"\nbase.dists.chi.variance( k )\n    Returns the variance of a chi distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.chi.variance( 11.0 )\n    ~0.488\n    > v = base.dists.chi.variance( 1.5 )\n    ~0.406\n\n","base.dists.chisquare.cdf":"\nbase.dists.chisquare.cdf( x, k )\n    Evaluates the cumulative distribution function (CDF) for a chi-squared\n    distribution with degrees of freedom `k` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.chisquare.cdf( 2.0, 3.0 )\n    ~0.428\n    > y = base.dists.chisquare.cdf( 1.0, 0.5 )\n    ~0.846\n    > y = base.dists.chisquare.cdf( -1.0, 4.0 )\n    0.0\n    > y = base.dists.chisquare.cdf( NaN, 1.0 )\n    NaN\n    > y = base.dists.chisquare.cdf( 0.0, NaN )\n    NaN\n\n    // Negative degrees of freedom:\n    > y = base.dists.chisquare.cdf( 2.0, -1.0 )\n    NaN\n\n    // Degenerate distribution when `k = 0`:\n    > y = base.dists.chisquare.cdf( 2.0, 0.0 )\n    1.0\n    > y = base.dists.chisquare.cdf( -2.0, 0.0 )\n    0.0\n    > y = base.dists.chisquare.cdf( 0.0, 0.0 )\n    0.0\n\nbase.dists.chisquare.cdf.factory( k )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a chi-squared distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.chisquare.cdf.factory( 1.0 );\n    > var y = mycdf( 2.0 )\n    ~0.843\n    > y = mycdf( 1.2 )\n    ~0.727\n\n","base.dists.chisquare.cdf.factory":"\nbase.dists.chisquare.cdf.factory( k )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a chi-squared distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.chisquare.cdf.factory( 1.0 );\n    > var y = mycdf( 2.0 )\n    ~0.843\n    > y = mycdf( 1.2 )\n    ~0.727","base.dists.chisquare.ChiSquare":"\nbase.dists.chisquare.ChiSquare( [k] )\n    Returns a  chi-squared distribution object.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    chisquare: Object\n        Distribution instance.\n\n    chisquare.k: number\n        Degrees of freedom. If set, the value must be greater than `0`.\n\n    chisquare.entropy: number\n        Read-only property which returns the differential entropy.\n\n    chisquare.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    chisquare.mean: number\n        Read-only property which returns the expected value.\n\n    chisquare.median: number\n        Read-only property which returns the median.\n\n    chisquare.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    chisquare.mode: number\n        Read-only property which returns the mode.\n\n    chisquare.skewness: number\n        Read-only property which returns the skewness.\n\n    chisquare.stdev: number\n        Read-only property which returns the standard deviation.\n\n    chisquare.variance: number\n        Read-only property which returns the variance.\n\n    chisquare.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    chisquare.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    chisquare.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var chisquare = base.dists.chisquare.ChiSquare( 6.0 );\n    > chisquare.k\n    6.0\n    > chisquare.entropy\n    ~2.541\n    > chisquare.kurtosis\n    2.0\n    > chisquare.mean\n    6.0\n    > chisquare.median\n    ~5.348\n    > chisquare.mode\n    4.0\n    > chisquare.skewness\n    ~1.155\n    > chisquare.stdev\n    ~3.464\n    > chisquare.variance\n    12.0\n    > chisquare.cdf( 3.0 )\n    ~0.191\n    > chisquare.mgf( 0.2 )\n    ~4.63\n    > chisquare.pdf( 1.5 )\n    ~0.066\n    > chisquare.quantile( 0.5 )\n    ~5.348\n\n","base.dists.chisquare.entropy":"\nbase.dists.chisquare.entropy( k )\n    Returns the differential entropy of a chi-squared distribution (in nats).\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.chisquare.entropy( 11.0 )\n    ~2.901\n    > v = base.dists.chisquare.entropy( 1.5 )\n    ~1.375\n\n","base.dists.chisquare.kurtosis":"\nbase.dists.chisquare.kurtosis( k )\n    Returns the excess kurtosis of a chi-squared distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.chisquare.kurtosis( 9.0 )\n    ~1.333\n    > v = base.dists.chisquare.kurtosis( 1.5 )\n    8.0\n\n","base.dists.chisquare.logpdf":"\nbase.dists.chisquare.logpdf( x, k )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a chi-squared distribution with degrees of freedom `k` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.chisquare.logpdf( 0.3, 4.0 )\n    ~-2.74\n    > y = base.dists.chisquare.logpdf( 0.7, 0.7 )\n    ~-1.295\n    > y = base.dists.chisquare.logpdf( -1.0, 0.5 )\n    -Infinity\n    > y = base.dists.chisquare.logpdf( 0.0, NaN )\n    NaN\n    > y = base.dists.chisquare.logpdf( NaN, 2.0 )\n    NaN\n\n    // Negative degrees of freedom:\n    > y = base.dists.chisquare.logpdf( 2.0, -1.0 )\n    NaN\n\n    // Degenerate distribution when `k = 0`:\n    > y = base.dists.chisquare.logpdf( 2.0, 0.0, 2.0 )\n    -Infinity\n    > y = base.dists.chisquare.logpdf( 0.0, 0.0, 2.0 )\n    Infinity\n\n\nbase.dists.chisquare.logpdf.factory( k )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a chi-squared distribution with degrees of freedom\n    `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var myLogPDF = base.dists.chisquare.logpdf.factory( 6.0 );\n    > var y = myLogPDF( 3.0 )\n    ~-2.075\n\n","base.dists.chisquare.logpdf.factory":"\nbase.dists.chisquare.logpdf.factory( k )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a chi-squared distribution with degrees of freedom\n    `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var myLogPDF = base.dists.chisquare.logpdf.factory( 6.0 );\n    > var y = myLogPDF( 3.0 )\n    ~-2.075","base.dists.chisquare.mean":"\nbase.dists.chisquare.mean( k )\n    Returns the expected value of a chi-squared distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.chisquare.mean( 11.0 )\n    11.0\n    > v = base.dists.chisquare.mean( 4.5 )\n    4.5\n\n","base.dists.chisquare.median":"\nbase.dists.chisquare.median( k )\n    Returns the median of a chi-squared distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var k = base.dists.chisquare.median( 9.0 )\n    ~8.343\n    > k = base.dists.chisquare.median( 2.0 )\n    ~1.386\n\n","base.dists.chisquare.mgf":"\nbase.dists.chisquare.mgf( t, k )\n    Evaluates the moment-generating function (MGF) for a chi-squared\n    distribution with degrees of freedom `k` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.chisquare.mgf( 0.4, 2 )\n    ~5.0\n    > y = base.dists.chisquare.mgf( -1.0, 5.0 )\n    ~0.0642\n    > y = base.dists.chisquare.mgf( 0.0, 10.0 )\n    1.0\n\n\nbase.dists.chisquare.mgf.factory( k )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    chi-squared distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.chisquare.mgf.factory( 1.0 );\n    > var y = mymgf( 0.2 )\n    ~1.291\n    > y = mymgf( 0.4 )\n    ~2.236\n\n","base.dists.chisquare.mgf.factory":"\nbase.dists.chisquare.mgf.factory( k )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    chi-squared distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.chisquare.mgf.factory( 1.0 );\n    > var y = mymgf( 0.2 )\n    ~1.291\n    > y = mymgf( 0.4 )\n    ~2.236","base.dists.chisquare.mode":"\nbase.dists.chisquare.mode( k )\n    Returns the mode of a chi-squared distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.chisquare.mode( 11.0 )\n    9.0\n    > v = base.dists.chisquare.mode( 1.5 )\n    0.0\n\n","base.dists.chisquare.pdf":"\nbase.dists.chisquare.pdf( x, k )\n    Evaluates the probability density function (PDF) for a chi-squared\n    distribution with degrees of freedom `k` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.chisquare.pdf( 0.3, 4.0 )\n    ~0.065\n    > y = base.dists.chisquare.pdf( 0.7, 0.7 )\n    ~0.274\n    > y = base.dists.chisquare.pdf( -1.0, 0.5 )\n    0.0\n    > y = base.dists.chisquare.pdf( 0.0, NaN )\n    NaN\n    > y = base.dists.chisquare.pdf( NaN, 2.0 )\n    NaN\n\n    // Negative degrees of freedom:\n    > y = base.dists.chisquare.pdf( 2.0, -1.0 )\n    NaN\n\n    // Degenerate distribution when `k = 0`:\n    > y = base.dists.chisquare.pdf( 2.0, 0.0, 2.0 )\n    0.0\n    > y = base.dists.chisquare.pdf( 0.0, 0.0, 2.0 )\n    Infinity\n\n\nbase.dists.chisquare.pdf.factory( k )\n    Returns a function for evaluating the probability density function (PDF) of\n    a chi-squared distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.chisquare.pdf.factory( 6.0 );\n    > var y = myPDF( 3.0 )\n    ~0.126\n\n","base.dists.chisquare.pdf.factory":"\nbase.dists.chisquare.pdf.factory( k )\n    Returns a function for evaluating the probability density function (PDF) of\n    a chi-squared distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.chisquare.pdf.factory( 6.0 );\n    > var y = myPDF( 3.0 )\n    ~0.126","base.dists.chisquare.quantile":"\nbase.dists.chisquare.quantile( p, k )\n    Evaluates the quantile function for a chi-squared distribution with degrees\n    of freedom `k` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.chisquare.quantile( 0.8, 1.0 )\n    ~1.642\n    > y = base.dists.chisquare.quantile( 0.5, 4.0 )\n    ~3.357\n    > y = base.dists.chisquare.quantile( 0.8, 0.1 )\n    ~0.014\n    > y = base.dists.chisquare.quantile( -0.2, 0.5 )\n    NaN\n    > y = base.dists.chisquare.quantile( 1.1, 0.5 )\n    NaN\n    > y = base.dists.chisquare.quantile( NaN, 1.0 )\n    NaN\n    > y = base.dists.chisquare.quantile( 0.0, NaN )\n    NaN\n\n    // Negative degrees of freedom:\n    > y = base.dists.chisquare.quantile( 0.5, -1.0 )\n    NaN\n\n    // Degenerate distribution when `k = 0`:\n    > y = base.dists.chisquare.quantile( 0.3, 0.0 )\n    0.0\n    > y = base.dists.chisquare.quantile( 0.9, 0.0 )\n    0.0\n\n\nbase.dists.chisquare.quantile.factory( k )\n    Returns a function for evaluating the quantile function of a chi-squared\n    distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.chisquare.quantile.factory( 2.0 );\n    > var y = myquantile( 0.3 )\n    ~0.713\n    > y = myquantile( 0.7 )\n    ~2.408\n\n","base.dists.chisquare.quantile.factory":"\nbase.dists.chisquare.quantile.factory( k )\n    Returns a function for evaluating the quantile function of a chi-squared\n    distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.chisquare.quantile.factory( 2.0 );\n    > var y = myquantile( 0.3 )\n    ~0.713\n    > y = myquantile( 0.7 )\n    ~2.408","base.dists.chisquare.skewness":"\nbase.dists.chisquare.skewness( k )\n    Returns the skewness of a chi-squared distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.chisquare.skewness( 11.0 )\n    ~0.853\n    > v = base.dists.chisquare.skewness( 1.5 )\n    ~2.309\n\n","base.dists.chisquare.stdev":"\nbase.dists.chisquare.stdev( k )\n    Returns the standard deviation of a chi-squared distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.chisquare.stdev( 11.0 )\n    ~4.69\n    > v = base.dists.chisquare.stdev( 1.5 )\n    ~1.732\n\n","base.dists.chisquare.variance":"\nbase.dists.chisquare.variance( k )\n    Returns the variance of a chi-squared distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.chisquare.variance( 11.0 )\n    22.0\n    > v = base.dists.chisquare.variance( 1.5 )\n    3.0\n\n","base.dists.cosine.cdf":"\nbase.dists.cosine.cdf( x, μ, s )\n    Evaluates the cumulative distribution function (CDF) for a raised cosine\n    distribution with location parameter `μ` and scale parameter `s` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.cdf( 2.0, 0.0, 3.0 )\n    ~0.971\n    > y = base.dists.cosine.cdf( 9.0, 10.0, 3.0 )\n    ~0.196\n\n    > y = base.dists.cosine.cdf( 2.0, 0.0, NaN )\n    NaN\n    > y = base.dists.cosine.cdf( 2.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.cdf( NaN, 0.0, 1.0 )\n    NaN\n\n    // Degenerate distribution centered at `μ` when `s = 0.0`:\n    > y = base.dists.cosine.cdf( 2.0, 8.0, 0.0 )\n    0.0\n    > y = base.dists.cosine.cdf( 8.0, 8.0, 0.0 )\n    1.0\n    > y = base.dists.cosine.cdf( 10.0, 8.0, 0.0 )\n    1.0\n\n\nbase.dists.cosine.cdf.factory( μ, s )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a raised cosine distribution with location parameter `μ` and scale\n    parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.cosine.cdf.factory( 3.0, 1.5 );\n    > var y = mycdf( 1.9 )\n    ~0.015\n\n","base.dists.cosine.cdf.factory":"\nbase.dists.cosine.cdf.factory( μ, s )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a raised cosine distribution with location parameter `μ` and scale\n    parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.cosine.cdf.factory( 3.0, 1.5 );\n    > var y = mycdf( 1.9 )\n    ~0.015","base.dists.cosine.Cosine":"\nbase.dists.cosine.Cosine( [μ, s] )\n    Returns a raised cosine distribution object.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter. Default: `0.0`.\n\n    s: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    cosine: Object\n        Distribution instance.\n\n    cosine.mu: number\n        Location parameter.\n\n    cosine.s: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    cosine.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    cosine.mean: number\n        Read-only property which returns the expected value.\n\n    cosine.median: number\n        Read-only property which returns the median.\n\n    cosine.mode: number\n        Read-only property which returns the mode.\n\n    cosine.skewness: number\n        Read-only property which returns the skewness.\n\n    cosine.stdev: number\n        Read-only property which returns the standard deviation.\n\n    cosine.variance: number\n        Read-only property which returns the variance.\n\n    cosine.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    cosine.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    cosine.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    cosine.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    cosine.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    cosine.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var cosine = base.dists.cosine.Cosine( -2.0, 3.0 );\n    > cosine.mu\n    -2.0\n    > cosine.s\n    3.0\n    > cosine.kurtosis\n    ~-0.594\n    > cosine.mean\n    -2.0\n    > cosine.median\n    -2.0\n    > cosine.mode\n    -2.0\n    > cosine.skewness\n    0.0\n    > cosine.stdev\n    ~1.085\n    > cosine.variance\n    ~1.176\n    > cosine.cdf( 0.5 )\n    ~0.996\n    > cosine.logcdf( 0.5 )\n    ~-0.004\n    > cosine.logpdf( -1.0 )\n    ~-1.386\n    > cosine.mgf( 0.2 )\n    ~0.686\n    > cosine.pdf( -2.0 )\n    ~0.333\n    > cosine.quantile( 0.9 )\n    ~-0.553\n\n","base.dists.cosine.kurtosis":"\nbase.dists.cosine.kurtosis( μ, s )\n    Returns the excess kurtosis of a raised cosine distribution with location\n    parameter `μ` and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.kurtosis( 0.0, 1.0 )\n    ~-0.594\n    > y = base.dists.cosine.kurtosis( 4.0, 2.0 )\n    ~-0.594\n    > y = base.dists.cosine.kurtosis( NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.kurtosis( 0.0, NaN )\n    NaN\n    > y = base.dists.cosine.kurtosis( 0.0, 0.0 )\n    NaN\n\n","base.dists.cosine.logcdf":"\nbase.dists.cosine.logcdf( x, μ, s )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a raised cosine distribution with location parameter `μ` and scale\n     parameter `s` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.logcdf( 2.0, 0.0, 3.0 )\n    ~-0.029\n    > y = base.dists.cosine.logcdf( 9.0, 10.0, 3.0 )\n    ~-1.632\n\n    > y = base.dists.cosine.logcdf( 2.0, 0.0, NaN )\n    NaN\n    > y = base.dists.cosine.logcdf( 2.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.logcdf( NaN, 0.0, 1.0 )\n    NaN\n\n    // Degenerate distribution centered at `μ` when `s = 0.0`:\n    > y = base.dists.cosine.logcdf( 2.0, 8.0, 0.0 )\n    -Infinity\n    > y = base.dists.cosine.logcdf( 8.0, 8.0, 0.0 )\n    0.0\n    > y = base.dists.cosine.logcdf( 10.0, 8.0, 0.0 )\n    0.0\n\n\nbase.dists.cosine.logcdf.factory( μ, s )\n    Returns a function for evaluating the natural logarithm of the  cumulative\n    distribution function (CDF) of a raised cosine distribution with location\n    parameter `μ` and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.cosine.logcdf.factory( 3.0, 1.5 );\n    > var y = mylogcdf( 1.9 )\n    ~-4.2\n\n","base.dists.cosine.logcdf.factory":"\nbase.dists.cosine.logcdf.factory( μ, s )\n    Returns a function for evaluating the natural logarithm of the  cumulative\n    distribution function (CDF) of a raised cosine distribution with location\n    parameter `μ` and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.cosine.logcdf.factory( 3.0, 1.5 );\n    > var y = mylogcdf( 1.9 )\n    ~-4.2","base.dists.cosine.logpdf":"\nbase.dists.cosine.logpdf( x, μ, s )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    raised cosine distribution with location parameter `μ` and scale parameter\n    `s` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.logpdf( 2.0, 0.0, 3.0 )\n    ~-2.485\n    > y = base.dists.cosine.logpdf( -1.0, 2.0, 4.0 )\n    ~-3.307\n    > y = base.dists.cosine.logpdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.cosine.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.logpdf( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.cosine.logpdf( 2.0, 0.0, -1.0 )\n    NaN\n\n    // Degenerate distribution at `s = 0.0`:\n    > y = base.dists.cosine.logpdf( 2.0, 8.0, 0.0 )\n    -Infinity\n    > y = base.dists.cosine.logpdf( 8.0, 8.0, 0.0 )\n    Infinity\n\n\nbase.dists.cosine.logpdf.factory( μ, s )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a raised cosine distribution with location parameter `μ`\n    and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.cosine.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogpdf( 10.0 )\n    ~-0.693\n\n","base.dists.cosine.logpdf.factory":"\nbase.dists.cosine.logpdf.factory( μ, s )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a raised cosine distribution with location parameter `μ`\n    and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.cosine.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogpdf( 10.0 )\n    ~-0.693","base.dists.cosine.mean":"\nbase.dists.cosine.mean( μ, s )\n    Returns the expected value of a raised cosine distribution with location\n    parameter `μ` and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.mean( 0.0, 1.0 )\n    0.0\n    > y = base.dists.cosine.mean( 4.0, 2.0 )\n    4.0\n    > y = base.dists.cosine.mean( NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.mean( 0.0, NaN )\n    NaN\n    > y = base.dists.cosine.mean( 0.0, 0.0 )\n    NaN\n\n","base.dists.cosine.median":"\nbase.dists.cosine.median( μ, s )\n    Returns the median of a raised cosine distribution with location parameter\n    `μ` and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.median( 0.0, 1.0 )\n    0.0\n    > y = base.dists.cosine.median( 4.0, 2.0 )\n    4.0\n    > y = base.dists.cosine.median( NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.median( 0.0, NaN )\n    NaN\n    > y = base.dists.cosine.median( 0.0, 0.0 )\n    NaN\n\n","base.dists.cosine.mgf":"\nbase.dists.cosine.mgf( t, μ, s )\n    Evaluates the moment-generating function (MGF) for a raised cosine\n    distribution with location parameter `μ` and scale parameter `s` at a value\n    `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.mgf( 2.0, 0.0, 3.0 )\n    ~7.234\n    > y = base.dists.cosine.mgf( 9.0, 10.0, 3.0 )\n    ~1.606e+47\n\n    > y = base.dists.cosine.mgf( 0.5, 0.0, NaN )\n    NaN\n    > y = base.dists.cosine.mgf( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.mgf( NaN, 0.0, 1.0 )\n    NaN\n\n\nbase.dists.cosine.mgf.factory( μ, s )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    raised cosine distribution with location parameter `μ` and scale parameter\n    `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.cosine.mgf.factory( 3.0, 1.5 );\n    > var y = mymgf( 1.9 )\n    ~495.57\n\n","base.dists.cosine.mgf.factory":"\nbase.dists.cosine.mgf.factory( μ, s )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    raised cosine distribution with location parameter `μ` and scale parameter\n    `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.cosine.mgf.factory( 3.0, 1.5 );\n    > var y = mymgf( 1.9 )\n    ~495.57","base.dists.cosine.mode":"\nbase.dists.cosine.mode( μ, s )\n    Returns the mode of a raised cosine distribution with location parameter `μ`\n    and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.mode( 0.0, 1.0 )\n    0.0\n    > y = base.dists.cosine.mode( 4.0, 2.0 )\n    4.0\n    > y = base.dists.cosine.mode( NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.mode( 0.0, NaN )\n    NaN\n    > y = base.dists.cosine.mode( 0.0, 0.0 )\n    NaN\n\n","base.dists.cosine.pdf":"\nbase.dists.cosine.pdf( x, μ, s )\n    Evaluates the probability density function (PDF) for a raised cosine\n    distribution with location parameter `μ` and scale parameter `s` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.pdf( 2.0, 0.0, 3.0 )\n    ~0.083\n    > y = base.dists.cosine.pdf( 2.4, 4.0, 2.0 )\n    ~0.048\n    > y = base.dists.cosine.pdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.cosine.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.pdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.cosine.pdf( 2.0, 0.0, -1.0 )\n    NaN\n    > y = base.dists.cosine.pdf( 2.0, 8.0, 0.0 )\n    0.0\n    > y = base.dists.cosine.pdf( 8.0, 8.0, 0.0 )\n    Infinity\n\n\nbase.dists.cosine.pdf.factory( μ, s )\n    Returns a function for evaluating the probability density function (PDF) of\n    a raised cosine distribution with location parameter `μ` and scale parameter\n    `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.cosine.pdf.factory( 0.0, 3.0 );\n    > var y = myPDF( 2.0 )\n    ~0.083\n\n","base.dists.cosine.pdf.factory":"\nbase.dists.cosine.pdf.factory( μ, s )\n    Returns a function for evaluating the probability density function (PDF) of\n    a raised cosine distribution with location parameter `μ` and scale parameter\n    `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.cosine.pdf.factory( 0.0, 3.0 );\n    > var y = myPDF( 2.0 )\n    ~0.083","base.dists.cosine.quantile":"\nbase.dists.cosine.quantile( p, μ, s )\n    Evaluates the quantile function for a raised cosine distribution with\n    location parameter `μ` and scale parameter `s` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.quantile( 0.8, 0.0, 1.0 )\n    ~0.327\n    > y = base.dists.cosine.quantile( 0.5, 4.0, 2.0 )\n    ~4.0\n\n    > y = base.dists.cosine.quantile( 1.1, 0.0, 1.0 )\n    NaN\n    > y = base.dists.cosine.quantile( -0.2, 0.0, 1.0 )\n    NaN\n\n    > y = base.dists.cosine.quantile( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.cosine.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.quantile( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.cosine.quantile( 0.5, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.cosine.quantile.factory( μ, s )\n    Returns a function for evaluating the quantile function of a raised cosine\n    distribution with location parameter `μ` and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.cosine.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.3 )\n    ~9.586\n\n","base.dists.cosine.quantile.factory":"\nbase.dists.cosine.quantile.factory( μ, s )\n    Returns a function for evaluating the quantile function of a raised cosine\n    distribution with location parameter `μ` and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.cosine.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.3 )\n    ~9.586","base.dists.cosine.skewness":"\nbase.dists.cosine.skewness( μ, s )\n    Returns the skewness of a raised cosine distribution with location parameter\n    `μ` and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.skewness( 0.0, 1.0 )\n    0.0\n    > y = base.dists.cosine.skewness( 4.0, 2.0 )\n    0.0\n    > y = base.dists.cosine.skewness( NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.skewness( 0.0, NaN )\n    NaN\n    > y = base.dists.cosine.skewness( 0.0, 0.0 )\n    NaN\n\n","base.dists.cosine.stdev":"\nbase.dists.cosine.stdev( μ, s )\n    Returns the standard deviation of a raised cosine distribution with location\n    parameter `μ` and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.stdev( 0.0, 1.0 )\n    ~0.362\n    > y = base.dists.cosine.stdev( 4.0, 2.0 )\n    ~0.723\n    > y = base.dists.cosine.stdev( NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.stdev( 0.0, NaN )\n    NaN\n    > y = base.dists.cosine.stdev( 0.0, 0.0 )\n    NaN\n\n","base.dists.cosine.variance":"\nbase.dists.cosine.variance( μ, s )\n    Returns the variance of a raised cosine distribution with location parameter\n    `μ` and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.variance( 0.0, 1.0 )\n    ~0.131\n    > y = base.dists.cosine.variance( 4.0, 2.0 )\n    ~0.523\n    > y = base.dists.cosine.variance( NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.variance( 0.0, NaN )\n    NaN\n    > y = base.dists.cosine.variance( 0.0, 0.0 )\n    NaN\n\n","base.dists.degenerate.cdf":"\nbase.dists.degenerate.cdf( x, μ )\n    Evaluates the cumulative distribution function (CDF) for a degenerate\n    distribution with mean value `μ`.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.degenerate.cdf( 2.0, 3.0 )\n    0.0\n    > y = base.dists.degenerate.cdf( 4.0, 3.0 )\n    1.0\n    > y = base.dists.degenerate.cdf( 3.0, 3.0 )\n    1.0\n    > y = base.dists.degenerate.cdf( NaN, 0.0 )\n    NaN\n    > y = base.dists.degenerate.cdf( 0.0, NaN )\n    NaN\n\n\nbase.dists.degenerate.cdf.factory( μ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a degenerate distribution centered at a provided mean value.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.degenerate.cdf.factory( 5.0 );\n    > var y = myCDF( 3.0 )\n    0.0\n    > y = myCDF( 6.0 )\n    1.0\n\n","base.dists.degenerate.cdf.factory":"\nbase.dists.degenerate.cdf.factory( μ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a degenerate distribution centered at a provided mean value.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.degenerate.cdf.factory( 5.0 );\n    > var y = myCDF( 3.0 )\n    0.0\n    > y = myCDF( 6.0 )\n    1.0","base.dists.degenerate.Degenerate":"\nbase.dists.degenerate.Degenerate( [μ] )\n    Returns a degenerate distribution object.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Constant value of distribution.\n\n    Returns\n    -------\n    degenerate: Object\n        Distribution instance.\n\n    degenerate.mu: number\n        Constant value of distribution.\n\n    degenerate.entropy: number\n        Read-only property which returns the differential entropy.\n\n    degenerate.mean: number\n        Read-only property which returns the expected value.\n\n    degenerate.median: number\n        Read-only property which returns the median.\n\n    degenerate.stdev: number\n        Read-only property which returns the standard deviation.\n\n    degenerate.variance: number\n        Read-only property which returns the variance.\n\n    degenerate.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    degenerate.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    degenerate.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    degenerate.logpmf: Function\n        Evaluates the natural logarithm of the probability mass function\n        (PMF).\n\n    degenerate.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    degenerate.pmf: Function\n        Evaluates the probability mass function (PMF).\n\n    degenerate.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    degenerate.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var degenerate = base.dists.degenerate.Degenerate( 2.0 );\n    > degenerate.mu\n    2.0\n    > degenerate.entropy\n    0.0\n    > degenerate.mean\n    2.0\n    > degenerate.mode\n    2.0\n    > degenerate.median\n    2.0\n    > degenerate.stdev\n    0.0\n    > degenerate.variance\n    0.0\n    > degenerate.cdf( 0.5 )\n    0.0\n    > degenerate.logcdf( 2.5 )\n    0.0\n    > degenerate.logpdf( 0.5 )\n    -Infinity\n    > degenerate.logpmf( 2.5 )\n    -Infinity\n    > degenerate.mgf( 0.2 )\n    ~1.492\n    > degenerate.pdf( 2.0 )\n    +Infinity\n    > degenerate.pmf( 2.0 )\n    1.0\n    > degenerate.quantile( 0.7 )\n    2.0\n\n","base.dists.degenerate.entropy":"\nbase.dists.degenerate.entropy( μ )\n    Returns the entropy of a degenerate distribution with constant value `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.degenerate.entropy( 20.0 )\n    0.0\n    > v = base.dists.degenerate.entropy( -10.0 )\n    0.0\n\n","base.dists.degenerate.logcdf":"\nbase.dists.degenerate.logcdf( x, μ )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (logCDF) for a degenerate distribution with mean `μ`.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Natural logarithm of the CDF.\n\n    Examples\n    --------\n    > var y = base.dists.degenerate.logcdf( 2.0, 3.0 )\n    -Infinity\n    > y = base.dists.degenerate.logcdf( 4.0, 3.0 )\n    0\n    > y = base.dists.degenerate.logcdf( 3.0, 3.0 )\n    0\n    > y = base.dists.degenerate.logcdf( NaN, 0.0 )\n    NaN\n    > y = base.dists.degenerate.logcdf( 0.0, NaN )\n    NaN\n\n\nbase.dists.degenerate.logcdf.factory( μ )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (logCDF) of a degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    logcdf: Function\n        Function to evaluate the natural logarithm of cumulative distribution\n        function (logCDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.degenerate.logcdf.factory( 5.0 );\n    > var y = mylogcdf( 3.0 )\n    -Infinity\n    > y = mylogcdf( 6.0 )\n    0\n\n","base.dists.degenerate.logcdf.factory":"\nbase.dists.degenerate.logcdf.factory( μ )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (logCDF) of a degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    logcdf: Function\n        Function to evaluate the natural logarithm of cumulative distribution\n        function (logCDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.degenerate.logcdf.factory( 5.0 );\n    > var y = mylogcdf( 3.0 )\n    -Infinity\n    > y = mylogcdf( 6.0 )\n    0","base.dists.degenerate.logpdf":"\nbase.dists.degenerate.logpdf( x, μ )\n    Evaluates the natural logarithm of the probability density function (logPDF)\n    for a degenerate distribution with mean `μ`.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Natural logarithm of the PDF.\n\n    Examples\n    --------\n    > var y = base.dists.degenerate.logpdf( 2.0, 3.0 )\n    -Infinity\n    > y = base.dists.degenerate.logpdf( 3.0, 3.0 )\n    Infinity\n    > y = base.dists.degenerate.logpdf( NaN, 0.0 )\n    NaN\n    > y = base.dists.degenerate.logpdf( 0.0, NaN )\n    NaN\n\n\nbase.dists.degenerate.logpdf.factory( μ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (logPDF) of a degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    logpdf: Function\n        Function to evaluate the natural logarithm of the PDF.\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.degenerate.logpdf.factory( 10.0 );\n    > var y = mylogPDF( 10.0 )\n    Infinity\n\n","base.dists.degenerate.logpdf.factory":"\nbase.dists.degenerate.logpdf.factory( μ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (logPDF) of a degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    logpdf: Function\n        Function to evaluate the natural logarithm of the PDF.\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.degenerate.logpdf.factory( 10.0 );\n    > var y = mylogPDF( 10.0 )\n    Infinity","base.dists.degenerate.logpmf":"\nbase.dists.degenerate.logpmf( x, μ )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    degenerate distribution with mean `μ`.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPMF.\n\n    Examples\n    --------\n    > var y = base.dists.degenerate.logpmf( 2.0, 3.0 )\n    -Infinity\n    > y = base.dists.degenerate.logpmf( 3.0, 3.0 )\n    0.0\n    > y = base.dists.degenerate.logpmf( NaN, 0.0 )\n    NaN\n    > y = base.dists.degenerate.logpmf( 0.0, NaN )\n    NaN\n\n\nbase.dists.degenerate.logpmf.factory( μ )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogPMF = base.dists.degenerate.logpmf.factory( 10.0 );\n    > var y = mylogPMF( 10.0 )\n    0.0\n\n","base.dists.degenerate.logpmf.factory":"\nbase.dists.degenerate.logpmf.factory( μ )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogPMF = base.dists.degenerate.logpmf.factory( 10.0 );\n    > var y = mylogPMF( 10.0 )\n    0.0","base.dists.degenerate.mean":"\nbase.dists.degenerate.mean( μ )\n    Returns the expected value of a degenerate distribution with constant value\n    `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.degenerate.mean( 20.0 )\n    20.0\n    > v = base.dists.degenerate.mean( -10.0 )\n    -10.0\n\n","base.dists.degenerate.median":"\nbase.dists.degenerate.median( μ )\n    Returns the median of a degenerate distribution with constant value `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.degenerate.median( 20.0 )\n    20.0\n    > v = base.dists.degenerate.median( -10.0 )\n    -10.0\n\n","base.dists.degenerate.mgf":"\nbase.dists.degenerate.mgf( x, μ )\n    Evaluates the moment-generating function (MGF) for a degenerate distribution\n    with mean `μ`.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.degenerate.mgf( 1.0, 1.0 )\n    ~2.718\n    > y = base.dists.degenerate.mgf( 2.0, 3.0 )\n    ~403.429\n    > y = base.dists.degenerate.mgf( NaN, 0.0 )\n    NaN\n    > y = base.dists.degenerate.mgf( 0.0, NaN )\n    NaN\n\n\nbase.dists.degenerate.mgf.factory( μ )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.degenerate.mgf.factory( 10.0 );\n    > var y = myMGF( 0.1 )\n    ~2.718\n\n","base.dists.degenerate.mgf.factory":"\nbase.dists.degenerate.mgf.factory( μ )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.degenerate.mgf.factory( 10.0 );\n    > var y = myMGF( 0.1 )\n    ~2.718","base.dists.degenerate.mode":"\nbase.dists.degenerate.mode( μ )\n    Returns the mode of a degenerate distribution with constant value `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.degenerate.mode( 20.0 )\n    20.0\n    > v = base.dists.degenerate.mode( -10.0 )\n    -10.0\n\n","base.dists.degenerate.pdf":"\nbase.dists.degenerate.pdf( x, μ )\n    Evaluates the probability density function (PDF) for a degenerate\n    distribution with mean `μ`.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.degenerate.pdf( 2.0, 3.0 )\n    0.0\n    > y = base.dists.degenerate.pdf( 3.0, 3.0 )\n    Infinity\n    > y = base.dists.degenerate.pdf( NaN, 0.0 )\n    NaN\n    > y = base.dists.degenerate.pdf( 0.0, NaN )\n    NaN\n\n\nbase.dists.degenerate.pdf.factory( μ )\n    Returns a function for evaluating the probability density function (PDF) of\n    a degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.degenerate.pdf.factory( 10.0 );\n    > var y = myPDF( 10.0 )\n    Infinity\n\n","base.dists.degenerate.pdf.factory":"\nbase.dists.degenerate.pdf.factory( μ )\n    Returns a function for evaluating the probability density function (PDF) of\n    a degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.degenerate.pdf.factory( 10.0 );\n    > var y = myPDF( 10.0 )\n    Infinity","base.dists.degenerate.pmf":"\nbase.dists.degenerate.pmf( x, μ )\n    Evaluates the probability mass function (PMF) for a degenerate distribution\n    with mean `μ`.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Evaluated PMF.\n\n    Examples\n    --------\n    > var y = base.dists.degenerate.pmf( 2.0, 3.0 )\n    0.0\n    > y = base.dists.degenerate.pmf( 3.0, 3.0 )\n    1.0\n    > y = base.dists.degenerate.pmf( NaN, 0.0 )\n    NaN\n    > y = base.dists.degenerate.pmf( 0.0, NaN )\n    NaN\n\n\nbase.dists.degenerate.pmf.factory( μ )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var myPMF = base.dists.degenerate.pmf.factory( 10.0 );\n    > var y = myPMF( 10.0 )\n    1.0\n\n","base.dists.degenerate.pmf.factory":"\nbase.dists.degenerate.pmf.factory( μ )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var myPMF = base.dists.degenerate.pmf.factory( 10.0 );\n    > var y = myPMF( 10.0 )\n    1.0","base.dists.degenerate.quantile":"\nbase.dists.degenerate.quantile( p, μ )\n    Evaluates the quantile function for a degenerate distribution with mean `μ`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.degenerate.quantile( 0.5, 2.0 )\n    2.0\n    > y = base.dists.degenerate.quantile( 0.9, 4.0 )\n    4.0\n    > y = base.dists.degenerate.quantile( 1.1, 0.0 )\n    NaN\n    > y = base.dists.degenerate.quantile( -0.2, 0.0 )\n    NaN\n    > y = base.dists.degenerate.quantile( NaN, 0.0 )\n    NaN\n    > y = base.dists.degenerate.quantile( 0.0, NaN )\n    NaN\n\n\nbase.dists.degenerate.quantile.factory( μ )\n    Returns a function for evaluating the quantile function of a degenerate\n    distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.degenerate.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    10.0\n\n","base.dists.degenerate.quantile.factory":"\nbase.dists.degenerate.quantile.factory( μ )\n    Returns a function for evaluating the quantile function of a degenerate\n    distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.degenerate.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    10.0","base.dists.degenerate.stdev":"\nbase.dists.degenerate.stdev( μ )\n    Returns the standard deviation of a degenerate distribution with constant\n    value `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.degenerate.stdev( 20.0 )\n    0.0\n    > v = base.dists.degenerate.stdev( -10.0 )\n    0.0\n\n","base.dists.degenerate.variance":"\nbase.dists.degenerate.variance( μ )\n    Returns the variance of a degenerate distribution with constant value `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.degenerate.variance( 20.0 )\n    0.0\n    > v = base.dists.degenerate.variance( -10.0 )\n    0.0\n\n","base.dists.discreteUniform.cdf":"\nbase.dists.discreteUniform.cdf( x, a, b )\n    Evaluates the cumulative distribution function (CDF) for a discrete uniform\n    distribution with minimum support `a` and maximum support `b` at a value\n    `x`.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.discreteUniform.cdf( 9.0, 0, 10 )\n    ~0.909\n    > y = base.dists.discreteUniform.cdf( 0.5, 0, 2 )\n    ~0.333\n    > y = base.dists.discreteUniform.cdf( PINF, 2, 4 )\n    1.0\n    > y = base.dists.discreteUniform.cdf( NINF, 2, 4 )\n    0.0\n    > y = base.dists.discreteUniform.cdf( NaN, 0, 1 )\n    NaN\n    > y = base.dists.discreteUniform.cdf( 0.0, NaN, 1 )\n    NaN\n    > y = base.dists.discreteUniform.cdf( 0.0, 0, NaN )\n    NaN\n    > y = base.dists.discreteUniform.cdf( 2.0, 1, 0 )\n    NaN\n\n\nbase.dists.discreteUniform.cdf.factory( a, b )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a discrete uniform distribution with minimum support `a` and maximum\n    support `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.discreteUniform.cdf.factory( 0, 10 );\n    > var y = mycdf( 0.5 )\n    ~0.091\n    > y = mycdf( 8.0 )\n    ~0.818\n\n","base.dists.discreteUniform.cdf.factory":"\nbase.dists.discreteUniform.cdf.factory( a, b )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a discrete uniform distribution with minimum support `a` and maximum\n    support `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.discreteUniform.cdf.factory( 0, 10 );\n    > var y = mycdf( 0.5 )\n    ~0.091\n    > y = mycdf( 8.0 )\n    ~0.818","base.dists.discreteUniform.DiscreteUniform":"\nbase.dists.discreteUniform.DiscreteUniform( [a, b] )\n    Returns a discrete uniform distribution object.\n\n    Parameters\n    ----------\n    a: integer (optional)\n        Minimum support. Must be an integer smaller than `b`. Default: `0`.\n\n    b: integer (optional)\n        Maximum support. Must be an integer greater than `a`. Default: `1`.\n\n    Returns\n    -------\n    discreteUniform: Object\n        Distribution instance.\n\n    discreteUniform.a: integer\n        Minimum support. If set, the value must be an integer smaller than or\n        equal to `b`.\n\n    discreteUniform.b: integer\n        Maximum support. If set, the value must be an integer greater than or\n        equal to `a`.\n\n    discreteUniform.entropy: number\n        Read-only property which returns the entropy.\n\n    discreteUniform.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    discreteUniform.mean: number\n        Read-only property which returns the expected value.\n\n    discreteUniform.median: number\n        Read-only property which returns the median.\n\n    discreteUniform.skewness: number\n        Read-only property which returns the skewness.\n\n    discreteUniform.stdev: number\n        Read-only property which returns the standard deviation.\n\n    discreteUniform.variance: number\n        Read-only property which returns the variance.\n\n    discreteUniform.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    discreteUniform.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    discreteUniform.logpmf: Function\n        Evaluates the natural logarithm of the probability mass function (PMF).\n\n    discreteUniform.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    discreteUniform.pmf: Function\n        Evaluates the probability mass function (PMF).\n\n    discreteUniform.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var discreteUniform = base.dists.discreteUniform.DiscreteUniform( -2, 2 );\n    > discreteUniform.a\n    -2\n    > discreteUniform.b\n    2\n    > discreteUniform.entropy\n    ~1.609\n    > discreteUniform.kurtosis\n    -1.3\n    > discreteUniform.mean\n    0.0\n    > discreteUniform.median\n    0.0\n    > discreteUniform.skewness\n    0.0\n    > discreteUniform.stdev\n    ~1.414\n    > discreteUniform.variance\n    2.0\n    > discreteUniform.cdf( 0.8 )\n    0.6\n    > discreteUniform.logcdf( 0.5 )\n    ~-0.511\n    > discreteUniform.logpmf( 1.0 )\n    ~-1.609\n    > discreteUniform.mgf( 0.8 )\n    ~1.766\n    > discreteUniform.pmf( 0.0 )\n    0.2\n    > discreteUniform.quantile( 0.8 )\n    2.0\n\n","base.dists.discreteUniform.entropy":"\nbase.dists.discreteUniform.entropy( a, b )\n    Returns the entropy of a discrete uniform distribution.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.discreteUniform.entropy( 0, 1 )\n    ~0.693\n    > v = base.dists.discreteUniform.entropy( 4, 12 )\n    ~2.197\n    > v = base.dists.discreteUniform.entropy( 2, 8 )\n    ~1.946\n\n","base.dists.discreteUniform.kurtosis":"\nbase.dists.discreteUniform.kurtosis( a, b )\n    Returns the excess kurtosis of a discrete uniform distribution.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.discreteUniform.kurtosis( 0, 1 )\n    -2.0\n    > v = base.dists.discreteUniform.kurtosis( 4, 12 )\n    ~-1.23\n    > v = base.dists.discreteUniform.kurtosis( -4, 8 )\n    ~-1.214\n\n","base.dists.discreteUniform.logcdf":"\nbase.dists.discreteUniform.logcdf( x, a, b )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a discrete uniform distribution with minimum support `a` and\n    maximum support `b` at a value `x`.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.discreteUniform.logcdf( 9.0, 0, 10 )\n    ~-0.095\n    > y = base.dists.discreteUniform.logcdf( 0.5, 0, 2 )\n    ~-1.099\n    > y = base.dists.discreteUniform.logcdf( PINF, 2, 4 )\n    0.0\n    > y = base.dists.discreteUniform.logcdf( NINF, 2, 4 )\n    -Infinity\n    > y = base.dists.discreteUniform.logcdf( NaN, 0, 1 )\n    NaN\n    > y = base.dists.discreteUniform.logcdf( 0.0, NaN, 1 )\n    NaN\n    > y = base.dists.discreteUniform.logcdf( 0.0, 0, NaN )\n    NaN\n    > y = base.dists.discreteUniform.logcdf( 2.0, 1, 0 )\n    NaN\n\n\nbase.dists.discreteUniform.logcdf.factory( a, b )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a discrete uniform distribution with minimum\n    support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myLogCDF = base.dists.discreteUniform.logcdf.factory( 0, 10 );\n    > var y = myLogCDF( 0.5 )\n    ~-2.398\n    > y = myLogCDF( 8.0 )\n    ~-0.201\n\n","base.dists.discreteUniform.logcdf.factory":"\nbase.dists.discreteUniform.logcdf.factory( a, b )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a discrete uniform distribution with minimum\n    support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myLogCDF = base.dists.discreteUniform.logcdf.factory( 0, 10 );\n    > var y = myLogCDF( 0.5 )\n    ~-2.398\n    > y = myLogCDF( 8.0 )\n    ~-0.201","base.dists.discreteUniform.logpmf":"\nbase.dists.discreteUniform.logpmf( x, a, b )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    discrete uniform distribution with minimum support `a` and maximum support\n    `b` at a value `x`.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPMF.\n\n    Examples\n    --------\n    > var y = base.dists.discreteUniform.logpmf( 2.0, 0, 4 )\n    ~-1.609\n    > y = base.dists.discreteUniform.logpmf( 5.0, 0, 4 )\n    -Infinity\n    > y = base.dists.discreteUniform.logpmf( 3.0, -4, 4 )\n    ~-2.197\n    > y = base.dists.discreteUniform.logpmf( NaN, 0, 1 )\n    NaN\n    > y = base.dists.discreteUniform.logpmf( 0.0, NaN, 1 )\n    NaN\n    > y = base.dists.discreteUniform.logpmf( 0.0, 0, NaN )\n    NaN\n    > y = base.dists.discreteUniform.logpmf( 2.0, 3, 1 )\n    NaN\n    > y = base.dists.discreteUniform.logpmf( 2.0, 1, 2.4 )\n    NaN\n\n\nbase.dists.discreteUniform.logpmf.factory( a, b )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a discrete uniform distribution with minimum support\n    `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var myLogPMF = base.dists.discreteUniform.logpmf.factory( 6, 7 );\n    > var y = myLogPMF( 7.0 )\n    ~-0.693\n    > y = myLogPMF( 5.0 )\n    -Infinity\n\n","base.dists.discreteUniform.logpmf.factory":"\nbase.dists.discreteUniform.logpmf.factory( a, b )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a discrete uniform distribution with minimum support\n    `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var myLogPMF = base.dists.discreteUniform.logpmf.factory( 6, 7 );\n    > var y = myLogPMF( 7.0 )\n    ~-0.693\n    > y = myLogPMF( 5.0 )\n    -Infinity","base.dists.discreteUniform.mean":"\nbase.dists.discreteUniform.mean( a, b )\n    Returns the expected value of a discrete uniform distribution.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.discreteUniform.mean( -2, 2 )\n    0.0\n    > v = base.dists.discreteUniform.mean( 4, 12 )\n    8.0\n    > v = base.dists.discreteUniform.mean( 2, 8 )\n    5.0\n\n","base.dists.discreteUniform.median":"\nbase.dists.discreteUniform.median( a, b )\n    Returns the median of a discrete uniform distribution.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.discreteUniform.median( -2, 2 )\n    0.0\n    > v = base.dists.discreteUniform.median( 4, 12 )\n    8.0\n    > v = base.dists.discreteUniform.median( 2, 8 )\n    5.0\n\n","base.dists.discreteUniform.mgf":"\nbase.dists.discreteUniform.mgf( t, a, b )\n    Evaluates the moment-generating function (MGF) for a discrete uniform\n    distribution with minimum support `a` and maximum support `b` at a value\n    `t`.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.discreteUniform.mgf( 2.0, 0, 4 )\n    ~689.475\n    > y = base.dists.discreteUniform.mgf( -0.2, 0, 4 )\n    ~0.697\n    > y = base.dists.discreteUniform.mgf( 2.0, 0, 1 )\n    ~4.195\n    > y = base.dists.discreteUniform.mgf( 0.5, 3, 2 )\n    NaN\n    > y = base.dists.discreteUniform.mgf( NaN, 0, 1  )\n    NaN\n    > y = base.dists.discreteUniform.mgf( 0.0, NaN, 1 )\n    NaN\n    > y = base.dists.discreteUniform.mgf( 0.0, 0, NaN )\n    NaN\n\n\nbase.dists.discreteUniform.mgf.factory( a, b )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a discrete uniform distribution with minimum support `a` and maximum\n    support `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.discreteUniform.mgf.factory( 6, 7 );\n    > var y = mymgf( 0.1 )\n    ~1.918\n    > y = mymgf( 1.1 )\n    ~1471.722\n\n","base.dists.discreteUniform.mgf.factory":"\nbase.dists.discreteUniform.mgf.factory( a, b )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a discrete uniform distribution with minimum support `a` and maximum\n    support `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.discreteUniform.mgf.factory( 6, 7 );\n    > var y = mymgf( 0.1 )\n    ~1.918\n    > y = mymgf( 1.1 )\n    ~1471.722","base.dists.discreteUniform.pmf":"\nbase.dists.discreteUniform.pmf( x, a, b )\n    Evaluates the probability mass function (PMF) for a discrete uniform\n    distribution with minimum support `a` and maximum support `b` at a value\n    `x`.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated PMF.\n\n    Examples\n    --------\n    > var y = base.dists.discreteUniform.pmf( 2.0, 0, 4 )\n    ~0.2\n    > y = base.dists.discreteUniform.pmf( 5.0, 0, 4 )\n    0.0\n    > y = base.dists.discreteUniform.pmf( 3.0, -4, 4 )\n    ~0.111\n    > y = base.dists.discreteUniform.pmf( NaN, 0, 1 )\n    NaN\n    > y = base.dists.discreteUniform.pmf( 0.0, NaN, 1 )\n    NaN\n    > y = base.dists.discreteUniform.pmf( 0.0, 0, NaN )\n    NaN\n    > y = base.dists.discreteUniform.pmf( 2.0, 3, 1 )\n    NaN\n    > y = base.dists.discreteUniform.pmf( 2.0, 1, 2.4 )\n    NaN\n\n\nbase.dists.discreteUniform.pmf.factory( a, b )\n    Returns a function for evaluating the probability mass function (PMF) of\n    a discrete uniform distribution with minimum support `a` and maximum support\n    `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var myPMF = base.dists.discreteUniform.pmf.factory( 6, 7 );\n    > var y = myPMF( 7.0 )\n    0.5\n    > y = myPMF( 5.0 )\n    0.0\n\n","base.dists.discreteUniform.pmf.factory":"\nbase.dists.discreteUniform.pmf.factory( a, b )\n    Returns a function for evaluating the probability mass function (PMF) of\n    a discrete uniform distribution with minimum support `a` and maximum support\n    `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var myPMF = base.dists.discreteUniform.pmf.factory( 6, 7 );\n    > var y = myPMF( 7.0 )\n    0.5\n    > y = myPMF( 5.0 )\n    0.0","base.dists.discreteUniform.quantile":"\nbase.dists.discreteUniform.quantile( p, a, b )\n    Evaluates the quantile function for a discrete uniform distribution with\n    minimum support `a` and maximum support `b` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    If provided `a > b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.discreteUniform.quantile( 0.8, 0, 1 )\n    1\n    > y = base.dists.discreteUniform.quantile( 0.5, 0.0, 10.0 )\n    5\n\n    > y = base.dists.discreteUniform.quantile( 1.1, 0, 4 )\n    NaN\n    > y = base.dists.discreteUniform.quantile( -0.2, 0, 4 )\n    NaN\n\n    > y = base.dists.discreteUniform.quantile( NaN, -2, 2 )\n    NaN\n    > y = base.dists.discreteUniform.quantile( 0.1, NaN, 2 )\n    NaN\n    > y = base.dists.discreteUniform.quantile( 0.1, -2, NaN )\n    NaN\n\n    > y = base.dists.discreteUniform.quantile( 0.5, 2, 1 )\n    NaN\n\n\nbase.dists.discreteUniform.quantile.factory( a, b )\n    Returns a function for evaluating the quantile function of a discrete\n    uniform distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.discreteUniform.quantile.factory( 0, 4 );\n    > var y = myQuantile( 0.8 )\n    4\n\n","base.dists.discreteUniform.quantile.factory":"\nbase.dists.discreteUniform.quantile.factory( a, b )\n    Returns a function for evaluating the quantile function of a discrete\n    uniform distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.discreteUniform.quantile.factory( 0, 4 );\n    > var y = myQuantile( 0.8 )\n    4","base.dists.discreteUniform.skewness":"\nbase.dists.discreteUniform.skewness( a, b )\n    Returns the skewness of a discrete uniform distribution.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.discreteUniform.skewness( -2, 2 )\n    0.0\n    > v = base.dists.discreteUniform.skewness( 4, 12 )\n    0.0\n    > v = base.dists.discreteUniform.skewness( 2, 8 )\n    0.0\n\n","base.dists.discreteUniform.stdev":"\nbase.dists.discreteUniform.stdev( a, b )\n    Returns the standard deviation of a discrete uniform distribution.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.discreteUniform.stdev( 0, 1 )\n    ~0.5\n    > v = base.dists.discreteUniform.stdev( 4, 12 )\n    ~2.582\n    > v = base.dists.discreteUniform.stdev( 2, 8 )\n    2.0\n\n","base.dists.discreteUniform.variance":"\nbase.dists.discreteUniform.variance( a, b )\n    Returns the variance of a discrete uniform distribution.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.discreteUniform.variance( 0, 1 )\n    ~0.25\n    > v = base.dists.discreteUniform.variance( 4, 12 )\n    ~6.667\n    > v = base.dists.discreteUniform.variance( 2, 8 )\n    4.0\n\n","base.dists.erlang.cdf":"\nbase.dists.erlang.cdf( x, k, λ )\n    Evaluates the cumulative distribution function (CDF) for an Erlang\n    distribution with shape parameter `k` and rate parameter `λ` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.erlang.cdf( 2.0, 1, 1.0 )\n    ~0.865\n    > y = base.dists.erlang.cdf( 2.0, 3, 1.0 )\n    ~0.323\n    > y = base.dists.erlang.cdf( 2.0, 2.5, 1.0 )\n    NaN\n    > y = base.dists.erlang.cdf( -1.0, 2, 2.0 )\n    0.0\n    > y = base.dists.erlang.cdf( PINF, 4, 2.0 )\n    1.0\n    > y = base.dists.erlang.cdf( NINF, 4, 2.0 )\n    0.0\n    > y = base.dists.erlang.cdf( NaN, 0, 1.0 )\n    NaN\n    > y = base.dists.erlang.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.erlang.cdf( 0.0, 0, NaN )\n    NaN\n    > y = base.dists.erlang.cdf( 2.0, -1, 1.0 )\n    NaN\n    > y = base.dists.erlang.cdf( 2.0, 1, -1.0 )\n    NaN\n\n\nbase.dists.erlang.cdf.factory( k, λ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.erlang.cdf.factory( 2, 0.5 );\n    > var y = mycdf( 6.0 )\n    ~0.801\n    > y = mycdf( 2.0 )\n    ~0.264\n\n","base.dists.erlang.cdf.factory":"\nbase.dists.erlang.cdf.factory( k, λ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.erlang.cdf.factory( 2, 0.5 );\n    > var y = mycdf( 6.0 )\n    ~0.801\n    > y = mycdf( 2.0 )\n    ~0.264","base.dists.erlang.entropy":"\nbase.dists.erlang.entropy( k, λ )\n    Returns the differential entropy of an Erlang distribution (in nats).\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a positive integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: integer\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.erlang.entropy( 1, 1.0 )\n    ~1.0\n    > v = base.dists.erlang.entropy( 4, 12.0 )\n    ~-0.462\n    > v = base.dists.erlang.entropy( 8, 2.0 )\n    ~1.723\n\n","base.dists.erlang.Erlang":"\nbase.dists.erlang.Erlang( [k, λ] )\n    Returns an Erlang distribution object.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Shape parameter. Must be a positive integer. Default: `1.0`.\n\n    λ: number (optional)\n        Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    erlang: Object\n        Distribution instance.\n\n    erlang.k: number\n        Shape parameter. If set, the value must be a positive integer.\n\n    erlang.lambda: number\n        Rate parameter. If set, the value must be greater than `0`.\n\n    erlang.entropy: number\n        Read-only property which returns the differential entropy.\n\n    erlang.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    erlang.mean: number\n        Read-only property which returns the expected value.\n\n    erlang.mode: number\n        Read-only property which returns the mode.\n\n    erlang.skewness: number\n        Read-only property which returns the skewness.\n\n    erlang.stdev: number\n        Read-only property which returns the standard deviation.\n\n    erlang.variance: number\n        Read-only property which returns the variance.\n\n    erlang.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    erlang.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    erlang.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    erlang.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    erlang.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var erlang = base.dists.erlang.Erlang( 6, 5.0 );\n    > erlang.k\n    6\n    > erlang.lambda\n    5.0\n    > erlang.entropy\n    ~0.647\n    > erlang.kurtosis\n    1.0\n    > erlang.mean\n    1.2\n    > erlang.mode\n    1.0\n    > erlang.skewness\n    ~0.816\n    > erlang.stdev\n    ~0.49\n    > erlang.variance\n    0.24\n    > erlang.cdf( 3.0 )\n    ~0.997\n    > erlang.logpdf( 3.0 )\n    ~-4.638\n    > erlang.mgf( -0.5 )\n    ~0.564\n    > erlang.pdf( 3.0 )\n    ~0.01\n    > erlang.quantile( 0.8 )\n    ~1.581\n\n","base.dists.erlang.kurtosis":"\nbase.dists.erlang.kurtosis( k, λ )\n    Returns the excess kurtosis of an Erlang distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a positive integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: integer\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.erlang.kurtosis( 1, 1.0 )\n    6.0\n    > v = base.dists.erlang.kurtosis( 4, 12.0 )\n    1.5\n    > v = base.dists.erlang.kurtosis( 8, 2.0 )\n    0.75\n\n","base.dists.erlang.logpdf":"\nbase.dists.erlang.logpdf( x, k, λ )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for an Erlang distribution with shape parameter `k` and rate parameter `λ`\n    at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.erlang.logpdf( 0.1, 1, 1.0 )\n    ~-0.1\n    > y = base.dists.erlang.logpdf( 0.5, 2, 2.5 )\n    ~-0.111\n    > y = base.dists.erlang.logpdf( -1.0, 4, 2.0 )\n    -Infinity\n    > y = base.dists.erlang.logpdf( NaN, 1, 1.0 )\n    NaN\n    > y = base.dists.erlang.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.erlang.logpdf( 0.0, 1, NaN )\n    NaN\n    > y = base.dists.erlang.logpdf( 2.0, -2, 0.5 )\n    NaN\n    > y = base.dists.erlang.logpdf( 2.0, 0.5, 0.5 )\n    NaN\n    > y = base.dists.erlang.logpdf( 2.0, 0.0, 2.0 )\n    -Infinity\n    > y = base.dists.erlang.logpdf( 0.0, 0.0, 2.0 )\n    Infinity\n    > y = base.dists.erlang.logpdf( 2.0, 1, 0.0 )\n    NaN\n    > y = base.dists.erlang.logpdf( 2.0, 1, -1.0 )\n    NaN\n\n\nbase.dists.erlang.logpdf.factory( k, λ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of an Erlang distribution with shape parameter `k`\n    and rate parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var myLogPDF = base.dists.erlang.logpdf.factory( 6.0, 7.0 );\n    > y = myLogPDF( 7.0 )\n    ~-32.382\n\n\n","base.dists.erlang.logpdf.factory":"\nbase.dists.erlang.logpdf.factory( k, λ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of an Erlang distribution with shape parameter `k`\n    and rate parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var myLogPDF = base.dists.erlang.logpdf.factory( 6.0, 7.0 );\n    > y = myLogPDF( 7.0 )\n    ~-32.382","base.dists.erlang.mean":"\nbase.dists.erlang.mean( k, λ )\n    Returns the expected value of an Erlang distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a positive integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: integer\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.erlang.mean( 1, 1.0 )\n    1.0\n    > v = base.dists.erlang.mean( 4, 12.0 )\n    ~0.333\n    > v = base.dists.erlang.mean( 8, 2.0 )\n    4.0\n\n","base.dists.erlang.mgf":"\nbase.dists.erlang.mgf( t, k, λ )\n    Evaluates the moment-generating function (MGF) for an Erlang distribution\n    with shape parameter `k` and rate parameter `λ` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.erlang.mgf( 0.3, 1, 1.0 )\n    ~1.429\n    > y = base.dists.erlang.mgf( 2.0, 2, 3.0 )\n    ~9.0\n    > y = base.dists.erlang.mgf( -1.0, 2, 2.0 )\n    ~0.444\n\n    > y = base.dists.erlang.mgf( NaN, 1, 1.0 )\n    NaN\n    > y = base.dists.erlang.mgf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.erlang.mgf( 0.0, 1, NaN )\n    NaN\n\n    > y = base.dists.erlang.mgf( 0.2, -2, 0.5 )\n    NaN\n    > y = base.dists.erlang.mgf( 0.2, 0.5, 0.5 )\n    NaN\n\n    > y = base.dists.erlang.mgf( 0.2, 1, 0.0 )\n    NaN\n    > y = base.dists.erlang.mgf( 0.2, 1, -5.0 )\n    NaN\n\n\nbase.dists.erlang.mgf.factory( k, λ )\n    Returns a function for evaluating the moment-generating function (MGF) of an\n    Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.erlang.mgf.factory( 2, 0.5 );\n    > var y = myMGF( 0.2 )\n    ~2.778\n    > y = myMGF( -0.5 )\n    0.25\n\n","base.dists.erlang.mgf.factory":"\nbase.dists.erlang.mgf.factory( k, λ )\n    Returns a function for evaluating the moment-generating function (MGF) of an\n    Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.erlang.mgf.factory( 2, 0.5 );\n    > var y = myMGF( 0.2 )\n    ~2.778\n    > y = myMGF( -0.5 )\n    0.25","base.dists.erlang.mode":"\nbase.dists.erlang.mode( k, λ )\n    Returns the mode of an Erlang distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a positive integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: integer\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.erlang.mode( 1, 1.0 )\n    0.0\n    > v = base.dists.erlang.mode( 4, 12.0 )\n    0.25\n    > v = base.dists.erlang.mode( 8, 2.0 )\n    3.5\n\n","base.dists.erlang.pdf":"\nbase.dists.erlang.pdf( x, k, λ )\n    Evaluates the probability density function (PDF) for an Erlang distribution\n    with shape parameter `k` and rate parameter `λ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.erlang.pdf( 0.1, 1, 1.0 )\n    ~0.905\n    > y = base.dists.erlang.pdf( 0.5, 2, 2.5 )\n    ~0.895\n    > y = base.dists.erlang.pdf( -1.0, 4, 2.0 )\n    0.0\n    > y = base.dists.erlang.pdf( NaN, 1, 1.0 )\n    NaN\n    > y = base.dists.erlang.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.erlang.pdf( 0.0, 1, NaN )\n    NaN\n    > y = base.dists.erlang.pdf( 2.0, -2, 0.5 )\n    NaN\n    > y = base.dists.erlang.pdf( 2.0, 0.5, 0.5 )\n    NaN\n    > y = base.dists.erlang.pdf( 2.0, 0.0, 2.0 )\n    0.0\n    > y = base.dists.erlang.pdf( 0.0, 0.0, 2.0 )\n    Infinity\n    > y = base.dists.erlang.pdf( 2.0, 1, 0.0 )\n    NaN\n    > y = base.dists.erlang.pdf( 2.0, 1, -1.0 )\n    NaN\n\n\nbase.dists.erlang.pdf.factory( k, λ )\n    Returns a function for evaluating the probability density function (PDF)\n    of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.erlang.pdf.factory( 6.0, 7.0 );\n    > y = myPDF( 7.0 )\n    ~8.639e-15\n\n\n","base.dists.erlang.pdf.factory":"\nbase.dists.erlang.pdf.factory( k, λ )\n    Returns a function for evaluating the probability density function (PDF)\n    of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.erlang.pdf.factory( 6.0, 7.0 );\n    > y = myPDF( 7.0 )\n    ~8.639e-15","base.dists.erlang.quantile":"\nbase.dists.erlang.quantile( p, k, λ )\n    Evaluates the quantile function for an Erlang distribution with shape\n    parameter `k` and rate parameter `λ` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive number for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.erlang.quantile( 0.8, 2, 1.0 )\n    ~2.994\n    > y = base.dists.erlang.quantile( 0.5, 4, 2.0 )\n    ~1.836\n\n    > y = base.dists.erlang.quantile( 1.1, 1, 1.0 )\n    NaN\n    > y = base.dists.erlang.quantile( -0.2, 1, 1.0 )\n    NaN\n\n    > y = base.dists.erlang.quantile( NaN, 1, 1.0 )\n    NaN\n    > y = base.dists.erlang.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.erlang.quantile( 0.0, 1, NaN )\n    NaN\n\n    // Non-integer shape parameter:\n    > y = base.dists.erlang.quantile( 0.5, 0.5, 1.0 )\n    NaN\n    // Non-positive shape parameter:\n    > y = base.dists.erlang.quantile( 0.5, -1, 1.0 )\n    NaN\n    // Non-positive rate parameter:\n    > y = base.dists.erlang.quantile( 0.5, 1, -1.0 )\n    NaN\n\n\nbase.dists.erlang.quantile.factory( k, λ )\n    Returns a function for evaluating the quantile function of an Erlang\n    distribution with shape parameter `k` and rate parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.erlang.quantile.factory( 10, 2.0 );\n    > var y = myQuantile( 0.4 )\n    ~4.452\n\n","base.dists.erlang.quantile.factory":"\nbase.dists.erlang.quantile.factory( k, λ )\n    Returns a function for evaluating the quantile function of an Erlang\n    distribution with shape parameter `k` and rate parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.erlang.quantile.factory( 10, 2.0 );\n    > var y = myQuantile( 0.4 )\n    ~4.452","base.dists.erlang.skewness":"\nbase.dists.erlang.skewness( k, λ )\n    Returns the skewness of an Erlang distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a positive integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: integer\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.erlang.skewness( 1, 1.0 )\n    2.0\n    > v = base.dists.erlang.skewness( 4, 12.0 )\n    1.0\n    > v = base.dists.erlang.skewness( 8, 2.0 )\n    ~0.707\n\n","base.dists.erlang.stdev":"\nbase.dists.erlang.stdev( k, λ )\n    Returns the standard deviation of an Erlang distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a positive integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: integer\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.erlang.stdev( 1, 1.0 )\n    1.0\n    > v = base.dists.erlang.stdev( 4, 12.0 )\n    ~0.167\n    > v = base.dists.erlang.stdev( 8, 2.0 )\n    ~1.414\n\n","base.dists.erlang.variance":"\nbase.dists.erlang.variance( k, λ )\n    Returns the variance of an Erlang distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a positive integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: integer\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.erlang.variance( 1, 1.0 )\n    1.0\n    > v = base.dists.erlang.variance( 4, 12.0 )\n    ~0.028\n    > v = base.dists.erlang.variance( 8, 2.0 )\n    2.0\n\n","base.dists.exponential.cdf":"\nbase.dists.exponential.cdf( x, λ )\n    Evaluates the cumulative distribution function (CDF) for an exponential\n    distribution with rate parameter `λ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.exponential.cdf( 2.0, 0.1 )\n    ~0.181\n    > y = base.dists.exponential.cdf( 1.0, 2.0 )\n    ~0.865\n    > y = base.dists.exponential.cdf( -1.0, 4.0 )\n    0.0\n    > y = base.dists.exponential.cdf( NaN, 1.0 )\n    NaN\n    > y = base.dists.exponential.cdf( 0.0, NaN )\n    NaN\n\n    // Negative rate parameter:\n    > y = base.dists.exponential.cdf( 2.0, -1.0 )\n    NaN\n\nbase.dists.exponential.cdf.factory( λ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    for an exponential distribution with rate parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.exponential.cdf.factory( 0.5 );\n    > var y = myCDF( 3.0 )\n    ~0.777\n\n","base.dists.exponential.cdf.factory":"\nbase.dists.exponential.cdf.factory( λ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    for an exponential distribution with rate parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.exponential.cdf.factory( 0.5 );\n    > var y = myCDF( 3.0 )\n    ~0.777","base.dists.exponential.entropy":"\nbase.dists.exponential.entropy( λ )\n    Returns the differential entropy of an exponential distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.exponential.entropy( 11.0 )\n    ~-1.398\n    > v = base.dists.exponential.entropy( 4.5 )\n    ~-0.504\n\n","base.dists.exponential.Exponential":"\nbase.dists.exponential.Exponential( [λ] )\n    Returns an exponential distribution object.\n\n    Parameters\n    ----------\n    λ: number (optional)\n        Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    exponential: Object\n        Distribution instance.\n\n    exponential.lambda: number\n        Rate parameter. If set, the value must be greater than `0`.\n\n    exponential.entropy: number\n        Read-only property which returns the differential entropy.\n\n    exponential.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    exponential.mean: number\n        Read-only property which returns the expected value.\n\n    exponential.median: number\n        Read-only property which returns the median.\n\n    exponential.mode: number\n        Read-only property which returns the mode.\n\n    exponential.skewness: number\n        Read-only property which returns the skewness.\n\n    exponential.stdev: number\n        Read-only property which returns the standard deviation.\n\n    exponential.variance: number\n        Read-only property which returns the variance.\n\n    exponential.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    exponential.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    exponential.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    exponential.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    exponential.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    exponential.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var exponential = base.dists.exponential.Exponential( 6.0 );\n    > exponential.lambda\n    6.0\n    > exponential.entropy\n    ~-0.792\n    > exponential.kurtosis\n    6.0\n    > exponential.mean\n    ~0.167\n    > exponential.median\n    ~0.116\n    > exponential.mode\n    0.0\n    > exponential.skewness\n    2.0\n    > exponential.stdev\n    ~0.167\n    > exponential.variance\n    ~0.028\n    > exponential.cdf( 1.0 )\n    ~0.998\n    > exponential.logcdf( 1.0 )\n    ~-0.002\n    > exponential.logpdf( 1.5 )\n    ~-7.208\n    > exponential.mgf( -0.5 )\n    ~0.923\n    > exponential.pdf( 1.5 )\n    ~0.001\n    > exponential.quantile( 0.5 )\n    ~0.116\n\n","base.dists.exponential.kurtosis":"\nbase.dists.exponential.kurtosis( λ )\n    Returns the excess kurtosis of an exponential distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.exponential.kurtosis( 11.0 )\n    6.0\n    > v = base.dists.exponential.kurtosis( 4.5 )\n    6.0\n\n","base.dists.exponential.logcdf":"\nbase.dists.exponential.logcdf( x, λ )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for an exponential distribution with rate parameter `λ` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.exponential.logcdf( 2.0, 0.1 )\n    ~-1.708\n    > y = base.dists.exponential.logcdf( 1.0, 2.0 )\n    ~-0.145\n    > y = base.dists.exponential.logcdf( -1.0, 4.0 )\n    -Infinity\n    > y = base.dists.exponential.logcdf( NaN, 1.0 )\n    NaN\n    > y = base.dists.exponential.logcdf( 0.0, NaN )\n    NaN\n\n    // Negative rate parameter:\n    > y = base.dists.exponential.logcdf( 2.0, -1.0 )\n    NaN\n\nbase.dists.exponential.logcdf.factory( λ )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) for an exponential distribution with rate\n    parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogCDF = base.dists.exponential.logcdf.factory( 0.5 );\n    > var y = mylogCDF( 3.0 )\n    ~-0.252\n\n","base.dists.exponential.logcdf.factory":"\nbase.dists.exponential.logcdf.factory( λ )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) for an exponential distribution with rate\n    parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogCDF = base.dists.exponential.logcdf.factory( 0.5 );\n    > var y = mylogCDF( 3.0 )\n    ~-0.252","base.dists.exponential.logpdf":"\nbase.dists.exponential.logpdf( x, λ )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for an exponential distribution with rate parameter `λ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.exponential.logpdf( 0.3, 4.0 )\n    ~0.186\n    > y = base.dists.exponential.logpdf( 2.0, 0.7 )\n    ~-1.757\n    > y = base.dists.exponential.logpdf( -1.0, 0.5 )\n    -Infinity\n    > y = base.dists.exponential.logpdf( 0, NaN )\n    NaN\n    > y = base.dists.exponential.logpdf( NaN, 2.0 )\n    NaN\n\n    // Negative rate:\n    > y = base.dists.exponential.logpdf( 2.0, -1.0 )\n    NaN\n\nbase.dists.exponential.logpdf.factory( λ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) for an exponential distribution with rate parameter\n    `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.exponential.logpdf.factory( 0.5 );\n    > var y = mylogpdf( 3.0 )\n    ~-2.193\n\n","base.dists.exponential.logpdf.factory":"\nbase.dists.exponential.logpdf.factory( λ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) for an exponential distribution with rate parameter\n    `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.exponential.logpdf.factory( 0.5 );\n    > var y = mylogpdf( 3.0 )\n    ~-2.193","base.dists.exponential.mean":"\nbase.dists.exponential.mean( λ )\n    Returns the expected value of an exponential distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.exponential.mean( 11.0 )\n    ~0.091\n    > v = base.dists.exponential.mean( 4.5 )\n    ~0.222\n\n","base.dists.exponential.median":"\nbase.dists.exponential.median( λ )\n    Returns the median of an exponential distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.exponential.median( 11.0 )\n    ~0.063\n    > v = base.dists.exponential.median( 4.5 )\n    ~0.154\n\n","base.dists.exponential.mgf":"\nbase.dists.exponential.mgf( t, λ )\n    Evaluates the moment-generating function (MGF) for an exponential\n    distribution with rate parameter `λ` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var v = base.dists.exponential.mgf( 2.0, 3.0 )\n    3.0\n    > v = base.dists.exponential.mgf( 0.4, 1.2 )\n    1.5\n    > v = base.dists.exponential.mgf( 0.8, 1.6 )\n    2.0\n    > v = base.dists.exponential.mgf( 4.0, 3.0 )\n    NaN\n    > v = base.dists.exponential.mgf( NaN, 3.0 )\n    NaN\n    > v = base.dists.exponential.mgf( 2.0, NaN )\n    NaN\n\n\nbase.dists.exponential.mgf.factory( λ )\n    Returns a function for evaluating the moment-generating function (MGF) for\n    an exponential distribution with rate parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    mg: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.exponential.mgf.factory( 4.0 );\n    > var y = myMGF( 3.0 )\n    4.0\n    > y = myMGF( 0.5 )\n    ~1.143\n\n","base.dists.exponential.mgf.factory":"\nbase.dists.exponential.mgf.factory( λ )\n    Returns a function for evaluating the moment-generating function (MGF) for\n    an exponential distribution with rate parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    mg: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.exponential.mgf.factory( 4.0 );\n    > var y = myMGF( 3.0 )\n    4.0\n    > y = myMGF( 0.5 )\n    ~1.143","base.dists.exponential.mode":"\nbase.dists.exponential.mode( λ )\n    Returns the mode of an exponential distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.exponential.mode( 11.0 )\n    0.0\n    > v = base.dists.exponential.mode( 4.5 )\n    0.0\n\n","base.dists.exponential.pdf":"\nbase.dists.exponential.pdf( x, λ )\n    Evaluates the probability density function (PDF) for an exponential\n    distribution with rate parameter `λ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.exponential.pdf( 0.3, 4.0 )\n    ~1.205\n    > y = base.dists.exponential.pdf( 2.0, 0.7 )\n    ~0.173\n    > y = base.dists.exponential.pdf( -1.0, 0.5 )\n    0.0\n    > y = base.dists.exponential.pdf( 0, NaN )\n    NaN\n    > y = base.dists.exponential.pdf( NaN, 2.0 )\n    NaN\n\n    // Negative rate:\n    > y = base.dists.exponential.pdf( 2.0, -1.0 )\n    NaN\n\nbase.dists.exponential.pdf.factory( λ )\n    Returns a function for evaluating the probability density function (PDF)\n    for an exponential distribution with rate parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.exponential.pdf.factory( 0.5 );\n    > var y = myPDF( 3.0 )\n    ~0.112\n\n","base.dists.exponential.pdf.factory":"\nbase.dists.exponential.pdf.factory( λ )\n    Returns a function for evaluating the probability density function (PDF)\n    for an exponential distribution with rate parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.exponential.pdf.factory( 0.5 );\n    > var y = myPDF( 3.0 )\n    ~0.112","base.dists.exponential.quantile":"\nbase.dists.exponential.quantile( p, λ )\n    Evaluates the quantile function for an exponential distribution with rate\n    parameter `λ` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.exponential.quantile( 0.8, 1.0 )\n    ~1.609\n    > y = base.dists.exponential.quantile( 0.5, 4.0 )\n    ~0.173\n    > y = base.dists.exponential.quantile( 0.5, 0.1 )\n    ~6.931\n\n    > y = base.dists.exponential.quantile( -0.2, 0.1 )\n    NaN\n\n    > y = base.dists.exponential.quantile( NaN, 1.0 )\n    NaN\n    > y = base.dists.exponential.quantile( 0.0, NaN )\n    NaN\n\n    // Negative rate parameter:\n    > y = base.dists.exponential.quantile( 0.5, -1.0 )\n    NaN\n\n\nbase.dists.exponential.quantile.factory( λ )\n    Returns a function for evaluating the quantile function for an exponential\n    distribution with rate parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.exponential.quantile.factory( 0.4 );\n    > var y = myQuantile( 0.4 )\n    ~1.277\n    > y = myQuantile( 1.0 )\n    Infinity\n\n","base.dists.exponential.quantile.factory":"\nbase.dists.exponential.quantile.factory( λ )\n    Returns a function for evaluating the quantile function for an exponential\n    distribution with rate parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.exponential.quantile.factory( 0.4 );\n    > var y = myQuantile( 0.4 )\n    ~1.277\n    > y = myQuantile( 1.0 )\n    Infinity","base.dists.exponential.skewness":"\nbase.dists.exponential.skewness( λ )\n    Returns the skewness of an exponential distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.exponential.skewness( 11.0 )\n    2.0\n    > v = base.dists.exponential.skewness( 4.5 )\n    2.0\n\n","base.dists.exponential.stdev":"\nbase.dists.exponential.stdev( λ )\n    Returns the standard deviation of an exponential distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.exponential.stdev( 9.0 )\n    ~0.11\n    > v = base.dists.exponential.stdev( 1.0 )\n    1.0\n\n","base.dists.exponential.variance":"\nbase.dists.exponential.variance( λ )\n    Returns the variance of an exponential distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.exponential.variance( 9.0 )\n    ~0.012\n    > v = base.dists.exponential.variance( 1.0 )\n    1.0\n\n","base.dists.f.cdf":"\nbase.dists.f.cdf( x, d1, d2 )\n    Evaluates the cumulative distribution function (CDF) for an F distribution\n    with numerator degrees of freedom `d1` and denominator degrees of freedom\n    `d2` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.f.cdf( 2.0, 1.0, 1.0 )\n    ~0.608\n    > var y = base.dists.f.cdf( 2.0, 8.0, 4.0 )\n    ~0.737\n    > var y = base.dists.f.cdf( -1.0, 2.0, 2.0 )\n    0.0\n    > var y = base.dists.f.cdf( PINF, 4.0, 2.0 )\n    1.0\n    > var y = base.dists.f.cdf( NINF, 4.0, 2.0 )\n    0.0\n\n    > var y = base.dists.f.cdf( NaN, 1.0, 1.0 )\n    NaN\n    > var y = base.dists.f.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > var y = base.dists.f.cdf( 0.0, 1.0, NaN )\n    NaN\n\n    > var y = base.dists.f.cdf( 2.0, 1.0, -1.0 )\n    NaN\n    > var y = base.dists.f.cdf( 2.0, -1.0, 1.0 )\n    NaN\n\n\nbase.dists.f.cdf.factory( d1, d2 )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an F distribution with numerator degrees of freedom `d1` and denominator\n    degrees of freedom `d2`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.f.cdf.factory( 10.0, 2.0 );\n    > var y = myCDF( 10.0 )\n    ~0.906\n    > y = myCDF( 8.0 )\n    ~0.884\n\n","base.dists.f.cdf.factory":"\nbase.dists.f.cdf.factory( d1, d2 )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an F distribution with numerator degrees of freedom `d1` and denominator\n    degrees of freedom `d2`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.f.cdf.factory( 10.0, 2.0 );\n    > var y = myCDF( 10.0 )\n    ~0.906\n    > y = myCDF( 8.0 )\n    ~0.884","base.dists.f.entropy":"\nbase.dists.f.entropy( d1, d2 )\n    Returns the differential entropy of an F distribution (in nats).\n\n    If `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n    If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.f.entropy( 3.0, 7.0 )\n    ~1.298\n    > v = base.dists.f.entropy( 4.0, 12.0 )\n    ~1.12\n    > v = base.dists.f.entropy( 8.0, 2.0 )\n    ~2.144\n\n","base.dists.f.F":"\nbase.dists.f.F( [d1, d2] )\n    Returns an F distribution object.\n\n    Parameters\n    ----------\n    d1: number (optional)\n        Numerator degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n    d2: number (optional)\n        Denominator degrees of freedom. Must be greater than `0`.\n        Default: `1.0`.\n\n    Returns\n    -------\n    f: Object\n        Distribution instance.\n\n    f.d1: number\n        Numerator degrees of freedom. If set, the value must be greater than\n        `0`.\n\n    f.d2: number\n        Denominator degrees of freedom. If set, the value must be greater than\n        `0`.\n\n    f.entropy: number\n        Read-only property which returns the differential entropy.\n\n    f.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    f.mean: number\n        Read-only property which returns the expected value.\n\n    f.mode: number\n        Read-only property which returns the mode.\n\n    f.skewness: number\n        Read-only property which returns the skewness.\n\n    f.stdev: number\n        Read-only property which returns the standard deviation.\n\n    f.variance: number\n        Read-only property which returns the variance.\n\n    f.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    f.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    f.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var f = base.dists.f.F( 6.0, 9.0 );\n    > f.d1\n    6.0\n    > f.d2\n    9.0\n    > f.entropy\n    ~1.134\n    > f.kurtosis\n    ~104.564\n    > f.mean\n    ~1.286\n    > f.mode\n    ~0.545\n    > f.skewness\n    ~4.535\n    > f.stdev\n    ~1.197\n    > f.variance\n    ~1.433\n    > f.cdf( 3.0 )\n    ~0.932\n    > f.pdf( 2.5 )\n    ~0.095\n    > f.quantile( 0.8 )\n    ~1.826\n\n","base.dists.f.kurtosis":"\nbase.dists.f.kurtosis( d1, d2 )\n    Returns the excess kurtosis of an F distribution.\n\n    If `d1 <= 0` or `d2 <= 8`, the function returns `NaN`.\n\n    If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.f.kurtosis( 3.0, 9.0 )\n    ~124.667\n    > v = base.dists.f.kurtosis( 4.0, 12.0 )\n    ~26.143\n    > v = base.dists.f.kurtosis( 8.0, 9.0 )\n    ~100.167\n\n","base.dists.f.mean":"\nbase.dists.f.mean( d1, d2 )\n    Returns the expected value of an F distribution.\n\n    If `d1 <= 0` or `d2 <= 2`, the function returns `NaN`.\n\n    If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.f.mean( 3.0, 5.0 )\n    ~1.667\n    > v = base.dists.f.mean( 4.0, 12.0 )\n    ~1.2\n    > v = base.dists.f.mean( 8.0, 4.0 )\n    2.0\n\n","base.dists.f.mode":"\nbase.dists.f.mode( d1, d2 )\n    Returns the mode of an F distribution.\n\n    If `d1 <= 2` or `d2 <= 0`, the function returns `NaN`.\n\n    If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.f.mode( 3.0, 5.0 )\n    ~0.238\n    > v = base.dists.f.mode( 4.0, 12.0 )\n    ~0.429\n    > v = base.dists.f.mode( 8.0, 4.0 )\n    0.5\n\n","base.dists.f.pdf":"\nbase.dists.f.pdf( x, d1, d2 )\n    Evaluates the probability density function (PDF) for an F distribution with\n    numerator degrees of freedom `d1` and denominator degrees of freedom `d2` at\n    a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.f.pdf( 2.0, 0.5, 1.0 )\n    ~0.057\n    > y = base.dists.f.pdf( 0.1, 1.0, 1.0 )\n    ~0.915\n    > y = base.dists.f.pdf( -1.0, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.f.pdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.f.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.f.pdf( 0.0, 1.0, NaN )\n    NaN\n\n    > y = base.dists.f.pdf( 2.0, 1.0, -1.0 )\n    NaN\n    > y = base.dists.f.pdf( 2.0, -1.0, 1.0 )\n    NaN\n\n\nbase.dists.f.pdf.factory( d1, d2 )\n    Returns a function for evaluating the probability density function (PDF) of\n    an F distribution with numerator degrees of freedom `d1` and denominator\n    degrees of freedom `d2`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.f.pdf.factory( 6.0, 7.0 );\n    > var y = myPDF( 7.0 )\n    ~0.004\n    > y = myPDF( 2.0 )\n    ~0.166\n\n","base.dists.f.pdf.factory":"\nbase.dists.f.pdf.factory( d1, d2 )\n    Returns a function for evaluating the probability density function (PDF) of\n    an F distribution with numerator degrees of freedom `d1` and denominator\n    degrees of freedom `d2`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.f.pdf.factory( 6.0, 7.0 );\n    > var y = myPDF( 7.0 )\n    ~0.004\n    > y = myPDF( 2.0 )\n    ~0.166","base.dists.f.quantile":"\nbase.dists.f.quantile( p, d1, d2 )\n    Evaluates the quantile function for an F distribution with numerator degrees\n    of freedom `d1` and denominator degrees of freedom `d2` at a probability\n    `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.f.quantile( 0.8, 1.0, 1.0 )\n    ~9.472\n    > y = base.dists.f.quantile( 0.5, 4.0, 2.0 )\n    ~1.207\n\n    > y = base.dists.f.quantile( 1.1, 1.0, 1.0 )\n    NaN\n    > y = base.dists.f.quantile( -0.2, 1.0, 1.0 )\n    NaN\n\n    > y = base.dists.f.quantile( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.f.quantile( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.dists.f.quantile( 0.5, 1.0, NaN )\n    NaN\n\n    > y = base.dists.f.quantile( 0.5, -1.0, 1.0 )\n    NaN\n    > y = base.dists.f.quantile( 0.5, 1.0, -1.0 )\n    NaN\n\n\nbase.dists.f.quantile.factory( d1, d2 )\n    Returns a function for evaluating the quantile function of an F distribution\n    with numerator degrees of freedom `d1` and denominator degrees of freedom\n    `d2`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.f.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.2 )\n    ~0.527\n    > y = myQuantile( 0.8 )\n    ~4.382\n\n","base.dists.f.quantile.factory":"\nbase.dists.f.quantile.factory( d1, d2 )\n    Returns a function for evaluating the quantile function of an F distribution\n    with numerator degrees of freedom `d1` and denominator degrees of freedom\n    `d2`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.f.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.2 )\n    ~0.527\n    > y = myQuantile( 0.8 )\n    ~4.382","base.dists.f.skewness":"\nbase.dists.f.skewness( d1, d2 )\n    Returns the skewness of an F distribution.\n\n    If `d1 <= 0` or `d2 <= 6`, the function returns `NaN`.\n\n    If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.f.skewness( 3.0, 7.0 )\n    11.0\n    > v = base.dists.f.skewness( 4.0, 12.0 )\n    ~3.207\n    > v = base.dists.f.skewness( 8.0, 7.0 )\n    ~10.088\n\n","base.dists.f.stdev":"\nbase.dists.f.stdev( d1, d2 )\n    Returns the standard deviation of an F distribution.\n\n    If `d1 <= 0` or `d2 <= 4`, the function returns `NaN`.\n\n    If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.f.stdev( 3.0, 5.0 )\n    ~3.333\n    > v = base.dists.f.stdev( 4.0, 12.0 )\n    ~1.122\n    > v = base.dists.f.stdev( 8.0, 5.0 )\n    ~2.764\n\n","base.dists.f.variance":"\nbase.dists.f.variance( d1, d2 )\n    Returns the variance of an F distribution.\n\n    If `d1 <= 0` or `d2 <= 4`, the function returns `NaN`.\n\n    If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.f.variance( 3.0, 5.0 )\n    ~11.111\n    > v = base.dists.f.variance( 4.0, 12.0 )\n    ~1.26\n    > v = base.dists.f.variance( 8.0, 5.0 )\n    ~7.639\n\n","base.dists.frechet.cdf":"\nbase.dists.frechet.cdf( x, α, s, m )\n    Evaluates the cumulative distribution function (CDF) for a Fréchet\n    distribution with shape parameter `α`, scale parameter `s`, and location\n    `m`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.cdf( 10.0, 2.0, 3.0, 0.0 )\n    ~0.914\n    > y = base.dists.frechet.cdf( -1.0, 2.0, 3.0, -3.0 )\n    ~0.105\n    > y = base.dists.frechet.cdf( 2.5, 2.0, 1.0, 2.0 )\n    ~0.018\n    > y = base.dists.frechet.cdf( NaN, 1.0, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.cdf( 0.0, NaN, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.cdf( 0.0, 1.0, NaN, 0.0 )\n    NaN\n    > y = base.dists.frechet.cdf( 0.0, 1.0, 1.0, NaN )\n    NaN\n    > y = base.dists.frechet.cdf( 0.0, -1.0, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.cdf( 0.0, 1.0, -1.0, 0.0 )\n    NaN\n\n\nbase.dists.frechet.cdf.factory( α, s, m )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n    location `m`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.frechet.cdf.factory( 3.0, 3.0, 5.0 );\n    > var y = myCDF( 10.0 )\n    ~0.806\n    > y = myCDF( 7.0 )\n    ~0.034\n\n","base.dists.frechet.cdf.factory":"\nbase.dists.frechet.cdf.factory( α, s, m )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n    location `m`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.frechet.cdf.factory( 3.0, 3.0, 5.0 );\n    > var y = myCDF( 10.0 )\n    ~0.806\n    > y = myCDF( 7.0 )\n    ~0.034","base.dists.frechet.entropy":"\nbase.dists.frechet.entropy( α, s, m )\n    Returns the differential entropy of a Fréchet distribution with shape\n    parameter `α`, scale parameter `s`, and location `m` (in nats).\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.entropy( 1.0, 1.0, 1.0 )\n    ~2.154\n    > y = base.dists.frechet.entropy( 4.0, 2.0, 1.0 )\n    ~1.028\n    > y = base.dists.frechet.entropy( NaN, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.entropy( 1.0, NaN, 0.0 )\n    NaN\n    > y = base.dists.frechet.entropy( 1.0, 1.0, NaN )\n    NaN\n\n","base.dists.frechet.Frechet":"\nbase.dists.frechet.Frechet( [α, s, m] )\n    Returns a Fréchet distribution object.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n    s: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    m: number (optional)\n        Location parameter. Default: `0.0`.\n\n    Returns\n    -------\n    frechet: Object\n        Distribution instance.\n\n    frechet.alpha: number\n        Shape parameter. If set, the value must be greater than `0`.\n\n    frechet.s: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    frechet.m: number\n        Location parameter.\n\n    frechet.entropy: number\n        Read-only property which returns the differential entropy.\n\n    frechet.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    frechet.mean: number\n        Read-only property which returns the expected value.\n\n    frechet.median: number\n        Read-only property which returns the median.\n\n    frechet.mode: number\n        Read-only property which returns the mode.\n\n    frechet.skewness: number\n        Read-only property which returns the skewness.\n\n    frechet.stdev: number\n        Read-only property which returns the standard deviation.\n\n    frechet.variance: number\n        Read-only property which returns the variance.\n\n    frechet.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    frechet.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    frechet.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    frechet.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    frechet.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var frechet = base.dists.frechet.Frechet( 1.0, 1.0, 0.0 );\n    > frechet.alpha\n    1.0\n    > frechet.s\n    1.0\n    > frechet.m\n    0.0\n    > frechet.entropy\n    ~2.154\n    > frechet.kurtosis\n    Infinity\n    > frechet.mean\n    Infinity\n    > frechet.median\n    ~1.443\n    > frechet.mode\n    0.5\n    > frechet.skewness\n    Infinity\n    > frechet.stdev\n    Infinity\n    > frechet.variance\n    Infinity\n    > frechet.cdf( 0.8 )\n    ~0.287\n    > frechet.logcdf( 0.8 )\n    -1.25\n    > frechet.logpdf( 0.8 )\n    ~-0.804\n    > frechet.pdf( 0.8 )\n    ~0.448\n    > frechet.quantile( 0.8 )\n    ~4.481\n\n","base.dists.frechet.kurtosis":"\nbase.dists.frechet.kurtosis( α, s, m )\n    Returns the excess kurtosis of a Fréchet distribution with shape parameter\n    `α`, scale parameter `s`, and location `m`.\n\n    If provided `0 < α <= 4` and `s > 0`, the function returns positive\n    infinity.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.kurtosis( 5.0, 2.0, 1.0 )\n    ~45.092\n    > var y = base.dists.frechet.kurtosis( 5.0, 10.0, -3.0 )\n    ~45.092\n    > y = base.dists.frechet.kurtosis( 3.5, 2.0, 1.0 )\n    Infinity\n    > y = base.dists.frechet.kurtosis( NaN, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.kurtosis( 1.0, NaN, 0.0 )\n    NaN\n    > y = base.dists.frechet.kurtosis( 1.0, 1.0, NaN )\n    NaN\n\n","base.dists.frechet.logcdf":"\nbase.dists.frechet.logcdf( x, α, s, m )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a Fréchet distribution with shape parameter `α`, scale parameter\n    `s`, and location `m`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.logcdf( 10.0, 2.0, 3.0, 0.0 )\n    ~-0.09\n    > y = base.dists.frechet.logcdf( -1.0, 2.0, 3.0, -3.0 )\n    ~-2.25\n    > y = base.dists.frechet.logcdf( 2.5, 2.0, 1.0, 2.0 )\n    -4.0\n    > y = base.dists.frechet.logcdf( NaN, 1.0, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.logcdf( 0.0, NaN, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.logcdf( 0.0, 1.0, NaN, 0.0 )\n    NaN\n    > y = base.dists.frechet.logcdf( 0.0, 1.0, 1.0, NaN )\n    NaN\n    > y = base.dists.frechet.logcdf( 0.0, -1.0, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.logcdf( 0.0, 1.0, -1.0, 0.0 )\n    NaN\n\n\nbase.dists.frechet.logcdf.factory( α, s, m )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Fréchet distribution with shape parameter\n    `α`, scale parameter `s`, and location `m`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.frechet.logcdf.factory( 3.0, 3.0, 5.0 );\n    > var y = mylogcdf( 10.0 )\n    ~-0.216\n    > y = mylogcdf( 7.0 )\n    ~-3.375\n\n","base.dists.frechet.logcdf.factory":"\nbase.dists.frechet.logcdf.factory( α, s, m )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Fréchet distribution with shape parameter\n    `α`, scale parameter `s`, and location `m`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.frechet.logcdf.factory( 3.0, 3.0, 5.0 );\n    > var y = mylogcdf( 10.0 )\n    ~-0.216\n    > y = mylogcdf( 7.0 )\n    ~-3.375","base.dists.frechet.logpdf":"\nbase.dists.frechet.logpdf( x, α, s, m )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n    location `m`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.logpdf( 10.0, 1.0, 3.0, 5.0 )\n    ~-2.72\n    > y = base.dists.frechet.logpdf( -2.0, 1.0, 3.0, -3.0 )\n    ~-1.901\n    > y = base.dists.frechet.logpdf( 0.0, 2.0, 1.0, -1.0 )\n    ~-0.307\n    > y = base.dists.frechet.logpdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.frechet.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.frechet.logpdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.frechet.logpdf( 0.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.frechet.logpdf.factory( α, s, m )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Fréchet distribution with shape parameter `α`, scale\n    parameter `s`, and location `m`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.frechet.logpdf.factory( 2.0, 3.0, 1.0 );\n    > var y = mylogPDF( 10.0 )\n    ~-3.812\n    > y = mylogPDF( 2.0 )\n    ~-6.11\n\n","base.dists.frechet.logpdf.factory":"\nbase.dists.frechet.logpdf.factory( α, s, m )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Fréchet distribution with shape parameter `α`, scale\n    parameter `s`, and location `m`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.frechet.logpdf.factory( 2.0, 3.0, 1.0 );\n    > var y = mylogPDF( 10.0 )\n    ~-3.812\n    > y = mylogPDF( 2.0 )\n    ~-6.11","base.dists.frechet.mean":"\nbase.dists.frechet.mean( α, s, m )\n    Returns the expected value of a Fréchet distribution with shape parameter\n    `α`, scale parameter `s`, and location `m`.\n\n    If provided `0 < α <= 1` and `s > 0`, the function returns positive\n    infinity.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Mean.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.mean( 4.0, 2.0, 1.0 )\n    ~3.451\n    > y = base.dists.frechet.mean( 0.5, 2.0, 1.0 )\n    Infinity\n    > y = base.dists.frechet.mean( NaN, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.mean( 1.0, NaN, 0.0 )\n    NaN\n    > y = base.dists.frechet.mean( 1.0, 1.0, NaN )\n    NaN\n\n","base.dists.frechet.median":"\nbase.dists.frechet.median( α, s, m )\n    Returns the median of a Fréchet distribution with shape parameter\n    `α`, scale parameter `s`, and location `m`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.median( 4.0, 2.0, 1.0 )\n    ~3.192\n    > var y = base.dists.frechet.median( 4.0, 2.0, -3.0 )\n    ~-0.808\n    > y = base.dists.frechet.median( 0.5, 2.0, 1.0 )\n    ~5.163\n    > y = base.dists.frechet.median( NaN, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.median( 1.0, NaN, 0.0 )\n    NaN\n    > y = base.dists.frechet.median( 1.0, 1.0, NaN )\n    NaN\n\n","base.dists.frechet.mode":"\nbase.dists.frechet.mode( α, s, m )\n    Returns the mode of a Fréchet distribution with shape parameter `α`, scale\n    parameter `s`, and location `m`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.mode( 4.0, 2.0, 1.0 )\n    ~2.891\n    > var y = base.dists.frechet.mode( 4.0, 2.0, -3.0 )\n    ~-1.109\n    > y = base.dists.frechet.mode( 0.5, 2.0, 1.0 )\n    ~1.222\n    > y = base.dists.frechet.mode( NaN, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.mode( 1.0, NaN, 0.0 )\n    NaN\n    > y = base.dists.frechet.mode( 1.0, 1.0, NaN )\n    NaN\n\n","base.dists.frechet.pdf":"\nbase.dists.frechet.pdf( x, α, s, m )\n    Evaluates the probability density function (PDF) for a Fréchet distribution\n    with shape parameter `α`, scale parameter `s`, and location `m`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.pdf( 10.0, 0.0, 3.0 )\n    ~0.965\n    > y = base.dists.frechet.pdf( -2.0, 0.0, 3.0 )\n    ~0.143\n    > y = base.dists.frechet.pdf( 0.0, 0.0, 1.0 )\n    ~0.368\n    > y = base.dists.frechet.pdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.frechet.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.frechet.pdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.frechet.pdf( 0.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.frechet.pdf.factory( α, s, m )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n    location `m`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.frechet.pdf.factory( 2.0, 3.0 );\n    > var y = myPDF( 10.0 )\n    ~0.933\n    > y = myPDF( 2.0 )\n    ~0.368\n\n","base.dists.frechet.pdf.factory":"\nbase.dists.frechet.pdf.factory( α, s, m )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n    location `m`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.frechet.pdf.factory( 2.0, 3.0 );\n    > var y = myPDF( 10.0 )\n    ~0.933\n    > y = myPDF( 2.0 )\n    ~0.368","base.dists.frechet.quantile":"\nbase.dists.frechet.quantile( p, α, s, m )\n    Evaluates the quantile function for a Fréchet distribution with shape\n    parameter `α`, scale parameter `s`, and location `m`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.quantile( 0.3, 10.0, 2.0, 3.0 )\n    ~4.963\n    > y = base.dists.frechet.quantile( 0.2, 3.0, 3.0, 3.0 )\n    ~5.56\n    > y = base.dists.frechet.quantile( 0.9, 1.0, 1.0, -3.0 )\n    ~6.491\n    > y = base.dists.frechet.quantile( NaN, 1.0, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.quantile( 0.0, NaN, 1.0, 0.0)\n    NaN\n    > y = base.dists.frechet.quantile( 0.0, 1.0, NaN, 0.0 )\n    NaN\n    > y = base.dists.frechet.quantile( 0.0, 1.0, 1.0, NaN )\n    NaN\n    > y = base.dists.frechet.quantile( 0.0, -1.0, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.quantile( 0.0, 1.0, -1.0, 0.0 )\n    NaN\n\n\nbase.dists.frechet.quantile.factory( α, s, m )\n    Returns a function for evaluating the quantile function of a Fréchet\n    distribution with shape parameter `α`, scale parameter `s`, and location\n    `m`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.frechet.quantile.factory( 2.0, 2.0, 3.0 );\n    > var y = myQuantile( 0.5 )\n    ~5.402\n    > y = myQuantile( 0.2 )\n    ~4.576\n\n","base.dists.frechet.quantile.factory":"\nbase.dists.frechet.quantile.factory( α, s, m )\n    Returns a function for evaluating the quantile function of a Fréchet\n    distribution with shape parameter `α`, scale parameter `s`, and location\n    `m`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.frechet.quantile.factory( 2.0, 2.0, 3.0 );\n    > var y = myQuantile( 0.5 )\n    ~5.402\n    > y = myQuantile( 0.2 )\n    ~4.576","base.dists.frechet.skewness":"\nbase.dists.frechet.skewness( α, s, m )\n    Returns the skewness of a Fréchet distribution with shape parameter `α`,\n    scale parameter `s`, and location `m`.\n\n    If provided `0 < α <= 3` and `s > 0`, the function returns positive\n    infinity.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.skewness( 4.0, 2.0, 1.0 )\n    ~5.605\n    > var y = base.dists.frechet.skewness( 4.0, 2.0, -3.0 )\n    ~5.605\n    > y = base.dists.frechet.skewness( 0.5, 2.0, 1.0 )\n    Infinity\n    > y = base.dists.frechet.skewness( NaN, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.skewness( 1.0, NaN, 0.0 )\n    NaN\n    > y = base.dists.frechet.skewness( 1.0, 1.0, NaN )\n    NaN\n\n","base.dists.frechet.stdev":"\nbase.dists.frechet.stdev( α, s, m )\n    Returns the standard deviation of a Fréchet distribution with shape\n    parameter `α`, scale parameter `s`, and location `m`.\n\n    If provided `0 < α <= 2` and `s > 0`, the function returns positive\n    infinity.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.stdev( 4.0, 2.0, 1.0 )\n    ~1.041\n    > var y = base.dists.frechet.stdev( 4.0, 2.0, -3.0 )\n    ~1.041\n    > y = base.dists.frechet.stdev( 0.5, 2.0, 1.0 )\n    Infinity\n    > y = base.dists.frechet.stdev( NaN, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.stdev( 1.0, NaN, 0.0 )\n    NaN\n    > y = base.dists.frechet.stdev( 1.0, 1.0, NaN )\n    NaN\n\n","base.dists.frechet.variance":"\nbase.dists.frechet.variance( α, s, m )\n    Returns the variance of a Fréchet distribution with shape parameter `α`,\n    scale parameter `s`, and location `m`.\n\n    If provided `0 < α <= 2` and `s > 0`, the function returns positive\n    infinity.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.variance( 4.0, 2.0, 1.0 )\n    ~1.083\n    > var y = base.dists.frechet.variance( 4.0, 2.0, -3.0 )\n    ~1.083\n    > y = base.dists.frechet.variance( 0.5, 2.0, 1.0 )\n    Infinity\n    > y = base.dists.frechet.variance( NaN, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.variance( 1.0, NaN, 0.0 )\n    NaN\n    > y = base.dists.frechet.variance( 1.0, 1.0, NaN )\n    NaN\n\n","base.dists.gamma.cdf":"\nbase.dists.gamma.cdf( x, α, β )\n    Evaluates the cumulative distribution function (CDF) for a gamma\n    distribution with shape parameter `α` and rate parameter `β` at a value `x`.\n\n    If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.gamma.cdf( 2.0, 1.0, 1.0 )\n    ~0.865\n    > y = base.dists.gamma.cdf( 2.0, 3.0, 1.0 )\n    ~0.323\n    > y = base.dists.gamma.cdf( -1.0, 2.0, 2.0 )\n    0.0\n    > y = base.dists.gamma.cdf( PINF, 4.0, 2.0 )\n    1.0\n    > y = base.dists.gamma.cdf( NINF, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.gamma.cdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.gamma.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gamma.cdf( 0.0, 0.0, NaN )\n    NaN\n\n    > y = base.dists.gamma.cdf( 2.0, -1.0, 1.0 )\n    NaN\n    > y = base.dists.gamma.cdf( 2.0, 1.0, -1.0 )\n    NaN\n\n    // Degenerate distribution centered at `0` when `α = 0.0`:\n    > y = base.dists.gamma.cdf( 2.0, 0.0, 2.0 )\n    1.0\n    > y = base.dists.gamma.cdf( -2.0, 0.0, 2.0 )\n    0.0\n    > y = base.dists.gamma.cdf( 0.0, 0.0, 2.0 )\n    0.0\n\n\nbase.dists.gamma.cdf.factory( α, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.gamma.cdf.factory( 2.0, 0.5 );\n    > var y = myCDF( 6.0 )\n    ~0.801\n    > y = myCDF( 2.0 )\n    ~0.264\n\n","base.dists.gamma.cdf.factory":"\nbase.dists.gamma.cdf.factory( α, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.gamma.cdf.factory( 2.0, 0.5 );\n    > var y = myCDF( 6.0 )\n    ~0.801\n    > y = myCDF( 2.0 )\n    ~0.264","base.dists.gamma.entropy":"\nbase.dists.gamma.entropy( α, β )\n    Returns the differential entropy of a gamma distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.gamma.entropy( 1.0, 1.0 )\n    1.0\n    > v = base.dists.gamma.entropy( 4.0, 12.0 )\n    ~-0.462\n    > v = base.dists.gamma.entropy( 8.0, 2.0 )\n    ~1.723\n\n","base.dists.gamma.Gamma":"\nbase.dists.gamma.Gamma( [α, β] )\n    Returns a gamma distribution object.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n    β: number (optional)\n        Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    gamma: Object\n        Distribution instance.\n\n    gamma.alpha: number\n        Shape parameter. If set, the value must be greater than `0`.\n\n    gamma.beta: number\n        Rate parameter. If set, the value must be greater than `0`.\n\n    gamma.entropy: number\n        Read-only property which returns the differential entropy.\n\n    gamma.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    gamma.mean: number\n        Read-only property which returns the expected value.\n\n    gamma.mode: number\n        Read-only property which returns the mode.\n\n    gamma.skewness: number\n        Read-only property which returns the skewness.\n\n    gamma.stdev: number\n        Read-only property which returns the standard deviation.\n\n    gamma.variance: number\n        Read-only property which returns the variance.\n\n    gamma.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    gamma.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    gamma.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    gamma.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    gamma.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    gamma.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var gamma = base.dists.gamma.Gamma( 6.0, 5.0 );\n    > gamma.alpha\n    6.0\n    > gamma.beta\n    5.0\n    > gamma.entropy\n    ~0.647\n    > gamma.kurtosis\n    1.0\n    > gamma.mean\n    1.2\n    > gamma.mode\n    1.0\n    > gamma.skewness\n    ~0.816\n    > gamma.stdev\n    ~0.49\n    > gamma.variance\n    0.24\n    > gamma.cdf( 0.8 )\n    ~0.215\n    > gamma.logcdf( 0.8 )\n    ~-1.538\n    > gamma.logpdf( 1.0 )\n    ~-0.131\n    > gamma.mgf( -0.5 )\n    ~0.564\n    > gamma.pdf( 1.0 )\n    ~0.877\n    > gamma.quantile( 0.8 )\n    ~1.581\n\n","base.dists.gamma.kurtosis":"\nbase.dists.gamma.kurtosis( α, β )\n    Returns the excess kurtosis of a gamma distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.gamma.kurtosis( 1.0, 1.0 )\n    6.0\n    > v = base.dists.gamma.kurtosis( 4.0, 12.0 )\n    1.5\n    > v = base.dists.gamma.kurtosis( 8.0, 2.0 )\n    0.75\n\n","base.dists.gamma.logcdf":"\nbase.dists.gamma.logcdf( x, α, β )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    gamma distribution with shape parameter `α` and rate parameter `β` at a\n    value `x`.\n\n    If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.gamma.logcdf( 2.0, 0.5, 1.0 )\n    ~-0.047\n    > y = base.dists.gamma.logcdf( 0.1, 1.0, 1.0 )\n    ~-2.352\n    > y = base.dists.gamma.logcdf( -1.0, 4.0, 2.0 )\n    -Infinity\n\n    > y = base.dists.gamma.logcdf( NaN, 0.6, 1.0 )\n    NaN\n    > y = base.dists.gamma.logcdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gamma.logcdf( 0.0, 1.0, NaN )\n    NaN\n\n    // Negative shape parameter:\n    > y = base.dists.gamma.logcdf( 2.0, -1.0, 1.0 )\n    NaN\n    // Non-positive rate parameter:\n    > y = base.dists.gamma.logcdf( 2.0, 1.0, -1.0 )\n    NaN\n\n\nbase.dists.gamma.logcdf.factory( α, β )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a gamma distribution with shape parameter `α`\n    and rate parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogCDF = base.dists.gamma.logcdf.factory( 6.0, 7.0 );\n    > var y = mylogCDF( 2.0 )\n    ~-0.006\n\n","base.dists.gamma.logcdf.factory":"\nbase.dists.gamma.logcdf.factory( α, β )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a gamma distribution with shape parameter `α`\n    and rate parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogCDF = base.dists.gamma.logcdf.factory( 6.0, 7.0 );\n    > var y = mylogCDF( 2.0 )\n    ~-0.006","base.dists.gamma.logpdf":"\nbase.dists.gamma.logpdf( x, α, β )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    gamma distribution with shape parameter `α` and rate parameter `β` at a\n    value `x`.\n\n    If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.gamma.logpdf( 2.0, 0.5, 1.0 )\n    ~-2.919\n    > y = base.dists.gamma.logpdf( 0.1, 1.0, 1.0 )\n    ~-0.1\n    > y = base.dists.gamma.logpdf( -1.0, 4.0, 2.0 )\n    -Infinity\n\n    > y = base.dists.gamma.logpdf( NaN, 0.6, 1.0 )\n    NaN\n    > y = base.dists.gamma.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gamma.logpdf( 0.0, 1.0, NaN )\n    NaN\n\n    // Negative shape parameter:\n    > y = base.dists.gamma.logpdf( 2.0, -1.0, 1.0 )\n    NaN\n    // Non-positive rate parameter:\n    > y = base.dists.gamma.logpdf( 2.0, 1.0, -1.0 )\n    NaN\n\n    // Degenerate distribution centered at `0.0` when `α = 0.0`:\n    > y = base.dists.gamma.logpdf( 2.0, 0.0, 2.0 )\n    -Infinity\n    > y = base.dists.gamma.logpdf( 0.0, 0.0, 2.0 )\n    Infinity\n\n\nbase.dists.gamma.logpdf.factory( α, β )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a gamma distribution with shape parameter `α` and rate\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.gamma.logpdf.factory( 6.0, 7.0 );\n    > var y = mylogPDF( 2.0 )\n    ~-3.646\n\n","base.dists.gamma.logpdf.factory":"\nbase.dists.gamma.logpdf.factory( α, β )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a gamma distribution with shape parameter `α` and rate\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.gamma.logpdf.factory( 6.0, 7.0 );\n    > var y = mylogPDF( 2.0 )\n    ~-3.646","base.dists.gamma.mean":"\nbase.dists.gamma.mean( α, β )\n    Returns the expected value of a gamma distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.gamma.mean( 1.0, 1.0 )\n    1.0\n    > v = base.dists.gamma.mean( 4.0, 12.0 )\n    ~0.333\n    > v = base.dists.gamma.mean( 8.0, 2.0 )\n    4.0\n\n","base.dists.gamma.mgf":"\nbase.dists.gamma.mgf( t, α, β )\n    Evaluates the moment-generating function (MGF) for a gamma distribution with\n    shape parameter `α` and rate parameter `β` at a value `t`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.gamma.mgf( 0.5, 0.5, 1.0 )\n    ~1.414\n    > y = base.dists.gamma.mgf( 0.1, 1.0, 1.0 )\n    ~1.111\n    > y = base.dists.gamma.mgf( -1.0, 4.0, 2.0 )\n    ~0.198\n\n    > y = base.dists.gamma.mgf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.gamma.mgf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gamma.mgf( 0.0, 1.0, NaN )\n    NaN\n\n    > y = base.dists.gamma.mgf( 2.0, 4.0, 1.0 )\n    NaN\n    > y = base.dists.gamma.mgf( 2.0, -0.5, 1.0 )\n    NaN\n    > y = base.dists.gamma.mgf( 2.0, 1.0, 0.0 )\n    NaN\n    > y = base.dists.gamma.mgf( 2.0, 1.0, -1.0 )\n    NaN\n\n\nbase.dists.gamma.mgf.factory( α, β )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    gamma distribution with shape parameter `α` and rate parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.gamma.mgf.factory( 3.0, 1.5 );\n    > var y = myMGF( 1.0 )\n    ~27.0\n    > y = myMGF( 0.5 )\n    ~3.375\n\n","base.dists.gamma.mgf.factory":"\nbase.dists.gamma.mgf.factory( α, β )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    gamma distribution with shape parameter `α` and rate parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.gamma.mgf.factory( 3.0, 1.5 );\n    > var y = myMGF( 1.0 )\n    ~27.0\n    > y = myMGF( 0.5 )\n    ~3.375","base.dists.gamma.mode":"\nbase.dists.gamma.mode( α, β )\n    Returns the mode of a gamma distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.gamma.mode( 1.0, 1.0 )\n    0.0\n    > v = base.dists.gamma.mode( 4.0, 12.0 )\n    0.25\n    > v = base.dists.gamma.mode( 8.0, 2.0 )\n    3.5\n\n","base.dists.gamma.pdf":"\nbase.dists.gamma.pdf( x, α, β )\n    Evaluates the probability density function (PDF) for a gamma distribution\n    with shape parameter `α` and rate parameter `β` at a value `x`.\n\n    If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.gamma.pdf( 2.0, 0.5, 1.0 )\n    ~0.054\n    > y = base.dists.gamma.pdf( 0.1, 1.0, 1.0 )\n    ~0.905\n    > y = base.dists.gamma.pdf( -1.0, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.gamma.pdf( NaN, 0.6, 1.0 )\n    NaN\n    > y = base.dists.gamma.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gamma.pdf( 0.0, 1.0, NaN )\n    NaN\n\n    // Negative shape parameter:\n    > y = base.dists.gamma.pdf( 2.0, -1.0, 1.0 )\n    NaN\n    // Non-positive rate parameter:\n    > y = base.dists.gamma.pdf( 2.0, 1.0, -1.0 )\n    NaN\n\n    // Degenerate distribution centered at `0.0` when `α = 0.0`:\n    > y = base.dists.gamma.pdf( 2.0, 0.0, 2.0 )\n    0.0\n    > y = base.dists.gamma.pdf( 0.0, 0.0, 2.0 )\n    Infinity\n\n\nbase.dists.gamma.pdf.factory( α, β )\n    Returns a function for evaluating the probability density function (PDF) of\n    a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.gamma.pdf.factory( 6.0, 7.0 );\n    > var y = myPDF( 2.0 )\n    ~0.026\n\n","base.dists.gamma.pdf.factory":"\nbase.dists.gamma.pdf.factory( α, β )\n    Returns a function for evaluating the probability density function (PDF) of\n    a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.gamma.pdf.factory( 6.0, 7.0 );\n    > var y = myPDF( 2.0 )\n    ~0.026","base.dists.gamma.quantile":"\nbase.dists.gamma.quantile( p, α, β )\n    Evaluates the quantile function for a gamma distribution with shape\n    parameter `α` and rate parameter `β` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.gamma.quantile( 0.8, 2.0, 1.0 )\n    ~2.994\n    > y = base.dists.gamma.quantile( 0.5, 4.0, 2.0 )\n    ~1.836\n\n    > y = base.dists.gamma.quantile( 1.1, 1.0, 1.0 )\n    NaN\n    > y = base.dists.gamma.quantile( -0.2, 1.0, 1.0 )\n    NaN\n\n    > y = base.dists.gamma.quantile( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.gamma.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gamma.quantile( 0.0, 1.0, NaN )\n    NaN\n\n    // Non-positive shape parameter:\n    > y = base.dists.gamma.quantile( 0.5, -1.0, 1.0 )\n    NaN\n    // Non-positive rate parameter:\n    > y = base.dists.gamma.quantile( 0.5, 1.0, -1.0 )\n    NaN\n\n    // Degenerate distribution centered at `0.0` when `α = 0.0`:\n    > y = base.dists.gamma.quantile( 0.3, 0.0, 2.0 )\n    0.0\n    > y = base.dists.gamma.quantile( 0.9, 0.0, 2.0 )\n    0.0\n\n\nbase.dists.gamma.quantile.factory( α, β )\n    Returns a function for evaluating the quantile function of a gamma\n    distribution with shape parameter `α` and rate parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.gamma.quantile.factory( 2.0, 2.0 );\n    > var y = myQuantile( 0.8 )\n    ~1.497\n    > y = myQuantile( 0.4 )\n    ~0.688\n\n","base.dists.gamma.quantile.factory":"\nbase.dists.gamma.quantile.factory( α, β )\n    Returns a function for evaluating the quantile function of a gamma\n    distribution with shape parameter `α` and rate parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.gamma.quantile.factory( 2.0, 2.0 );\n    > var y = myQuantile( 0.8 )\n    ~1.497\n    > y = myQuantile( 0.4 )\n    ~0.688","base.dists.gamma.skewness":"\nbase.dists.gamma.skewness( α, β )\n    Returns the skewness of a gamma distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.gamma.skewness( 1.0, 1.0 )\n    2.0\n    > v = base.dists.gamma.skewness( 4.0, 12.0 )\n    1.0\n    > v = base.dists.gamma.skewness( 8.0, 2.0 )\n    ~0.707\n\n","base.dists.gamma.stdev":"\nbase.dists.gamma.stdev( α, β )\n    Returns the standard deviation of a gamma distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.gamma.stdev( 1.0, 1.0 )\n    1.0\n    > v = base.dists.gamma.stdev( 4.0, 12.0 )\n    ~0.167\n    > v = base.dists.gamma.stdev( 8.0, 2.0 )\n    ~1.414\n\n","base.dists.gamma.variance":"\nbase.dists.gamma.variance( α, β )\n    Returns the variance of a gamma distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.gamma.variance( 1.0, 1.0 )\n    1.0\n    > v = base.dists.gamma.variance( 4.0, 12.0 )\n    ~0.028\n    > v = base.dists.gamma.variance( 8.0, 2.0 )\n    2.0\n\n","base.dists.geometric.cdf":"\nbase.dists.geometric.cdf( x, p )\n    Evaluates the cumulative distribution function (CDF) for a geometric\n    distribution with success probability `p` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.geometric.cdf( 2.0, 0.5 )\n    0.875\n    > y = base.dists.geometric.cdf( 2.0, 0.1 )\n    ~0.271\n    > y = base.dists.geometric.cdf( -1.0, 4.0 )\n    0.0\n    > y = base.dists.geometric.cdf( NaN, 0.5 )\n    NaN\n    > y = base.dists.geometric.cdf( 0.0, NaN )\n    NaN\n    // Invalid probability\n    > y = base.dists.geometric.cdf( 2.0, 1.4 )\n    NaN\n\n\nbase.dists.geometric.cdf.factory( p )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a geometric distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.geometric.cdf.factory( 0.5 );\n    > var y = mycdf( 3.0 )\n    0.9375\n    > y = mycdf( 1.0 )\n    0.75\n\n","base.dists.geometric.cdf.factory":"\nbase.dists.geometric.cdf.factory( p )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a geometric distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.geometric.cdf.factory( 0.5 );\n    > var y = mycdf( 3.0 )\n    0.9375\n    > y = mycdf( 1.0 )\n    0.75","base.dists.geometric.entropy":"\nbase.dists.geometric.entropy( p )\n    Returns the entropy of a geometric distribution with success probability\n    `p` (in nats).\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.geometric.entropy( 0.1 )\n    ~3.251\n    > v = base.dists.geometric.entropy( 0.5 )\n    ~1.386\n\n","base.dists.geometric.Geometric":"\nbase.dists.geometric.Geometric( [p] )\n    Returns a geometric distribution object.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability. Must be between `0` and `1`. Default: `0.5`.\n\n    Returns\n    -------\n    geometric: Object\n        Distribution instance.\n\n    geometric.p: number\n        Success probability. If set, the value must be between `0` and `1`.\n\n    geometric.entropy: number\n        Read-only property which returns the differential entropy.\n\n    geometric.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    geometric.mean: number\n        Read-only property which returns the expected value.\n\n    geometric.median: number\n        Read-only property which returns the median.\n\n    geometric.mode: number\n        Read-only property which returns the mode.\n\n    geometric.skewness: number\n        Read-only property which returns the skewness.\n\n    geometric.stdev: number\n        Read-only property which returns the standard deviation.\n\n    geometric.variance: number\n        Read-only property which returns the variance.\n\n    geometric.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    geometric.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    geometric.logpmf: Function\n        Evaluates the natural logarithm of the probability mass function (PMF).\n\n    geometric.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    geometric.pmf: Function\n        Evaluates the probability mass function (PMF).\n\n    geometric.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var geometric = base.dists.geometric.Geometric( 0.6 );\n    > geometric.p\n    0.6\n    > geometric.entropy\n    ~1.122\n    > geometric.kurtosis\n    ~6.9\n    > geometric.mean\n    ~0.667\n    > geometric.median\n    0.0\n    > geometric.mode\n    0.0\n    > geometric.skewness\n    ~2.214\n    > geometric.stdev\n    ~1.054\n    > geometric.variance\n    ~1.111\n    > geometric.cdf( 3.0 )\n    ~0.974\n    > geometric.logcdf( 3.0 )\n    ~-0.026\n    > geometric.logpmf( 4.0 )\n    ~-4.176\n    > geometric.mgf( 0.5 )\n    ~2.905\n    > geometric.pmf( 2.0 )\n    ~0.096\n    > geometric.quantile( 0.7 )\n    1.0\n\n","base.dists.geometric.kurtosis":"\nbase.dists.geometric.kurtosis( p )\n    Returns the excess kurtosis of a geometric distribution with success\n    probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.geometric.kurtosis( 0.1 )\n    ~6.011\n    > v = base.dists.geometric.kurtosis( 0.5 )\n    6.5\n\n","base.dists.geometric.logcdf":"\nbase.dists.geometric.logcdf( x, p )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    geometric distribution with success probability `p` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.geometric.logcdf( 2.0, 0.5 )\n    ~-0.134\n    > y = base.dists.geometric.logcdf( 2.0, 0.1 )\n    ~-1.306\n    > y = base.dists.geometric.logcdf( -1.0, 4.0 )\n    -Infinity\n    > y = base.dists.geometric.logcdf( NaN, 0.5 )\n    NaN\n    > y = base.dists.geometric.logcdf( 0.0, NaN )\n    NaN\n    // Invalid probability\n    > y = base.dists.geometric.logcdf( 2.0, 1.4 )\n    NaN\n\n\nbase.dists.geometric.logcdf.factory( p )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a geometric distribution with success\n    probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.geometric.logcdf.factory( 0.5 );\n    > var y = mylogcdf( 3.0 )\n    ~-0.065\n    > y = mylogcdf( 1.0 )\n    ~-0.288\n\n","base.dists.geometric.logcdf.factory":"\nbase.dists.geometric.logcdf.factory( p )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a geometric distribution with success\n    probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.geometric.logcdf.factory( 0.5 );\n    > var y = mylogcdf( 3.0 )\n    ~-0.065\n    > y = mylogcdf( 1.0 )\n    ~-0.288","base.dists.geometric.logpmf":"\nbase.dists.geometric.logpmf( x, p )\n    Evaluates the logarithm of the probability mass function (PMF) for a\n    geometric distribution with success probability `p` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPMF.\n\n    Examples\n    --------\n    > var y = base.dists.geometric.logpmf( 4.0, 0.3 )\n    ~-2.631\n    > y = base.dists.geometric.logpmf( 2.0, 0.7 )\n    ~-2.765\n    > y = base.dists.geometric.logpmf( -1.0, 0.5 )\n    -Infinity\n    > y = base.dists.geometric.logpmf( 0.0, NaN )\n    NaN\n    > y = base.dists.geometric.logpmf( NaN, 0.5 )\n    NaN\n    // Invalid success probability:\n    > y = base.dists.geometric.logpmf( 2.0, 1.5 )\n    NaN\n\n\nbase.dists.geometric.logpmf.factory( p )\n    Returns a function for evaluating the logarithm of the probability mass\n    function (PMF) of a geometric distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogpmf = base.dists.geometric.logpmf.factory( 0.5 );\n    > var y = mylogpmf( 3.0 )\n    ~-2.773\n    > y = mylogpmf( 1.0 )\n    ~-1.386\n\n","base.dists.geometric.logpmf.factory":"\nbase.dists.geometric.logpmf.factory( p )\n    Returns a function for evaluating the logarithm of the probability mass\n    function (PMF) of a geometric distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogpmf = base.dists.geometric.logpmf.factory( 0.5 );\n    > var y = mylogpmf( 3.0 )\n    ~-2.773\n    > y = mylogpmf( 1.0 )\n    ~-1.386","base.dists.geometric.mean":"\nbase.dists.geometric.mean( p )\n    Returns the expected value of a geometric distribution with success\n    probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.geometric.mean( 0.1 )\n    9.0\n    > v = base.dists.geometric.mean( 0.5 )\n    1.0\n\n","base.dists.geometric.median":"\nbase.dists.geometric.median( p )\n    Returns the median of a geometric distribution with success probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: integer\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.geometric.median( 0.1 )\n    6\n    > v = base.dists.geometric.median( 0.5 )\n    0\n\n","base.dists.geometric.mgf":"\nbase.dists.geometric.mgf( t, p )\n    Evaluates the moment-generating function (MGF) for a geometric\n    distribution with success probability `p` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If `t >= -ln(1-p)`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.geometric.mgf( 0.2, 0.5 )\n    ~1.569\n    > y = base.dists.geometric.mgf( 0.4, 0.5 )\n    ~2.936\n    // Case: t >= -ln(1-p)\n    > y = base.dists.geometric.mgf( 0.8, 0.5 )\n    NaN\n    > y = base.dists.geometric.mgf( NaN, 0.0 )\n    NaN\n    > y = base.dists.geometric.mgf( 0.0, NaN )\n    NaN\n    > y = base.dists.geometric.mgf( -2.0, -1.0 )\n    NaN\n    > y = base.dists.geometric.mgf( 0.2, 2.0 )\n    NaN\n\n\nbase.dists.geometric.mgf.factory( p )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    geometric distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.geometric.mgf.factory( 0.8 );\n    > var y = mymgf( -0.2 )\n    ~0.783\n\n","base.dists.geometric.mgf.factory":"\nbase.dists.geometric.mgf.factory( p )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    geometric distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.geometric.mgf.factory( 0.8 );\n    > var y = mymgf( -0.2 )\n    ~0.783","base.dists.geometric.mode":"\nbase.dists.geometric.mode( p )\n    Returns the mode of a geometric distribution with success probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: integer\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.geometric.mode( 0.1 )\n    0\n    > v = base.dists.geometric.mode( 0.5 )\n    0\n\n","base.dists.geometric.pmf":"\nbase.dists.geometric.pmf( x, p )\n    Evaluates the probability mass function (PMF) for a geometric distribution\n    with success probability `p` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated PMF.\n\n    Examples\n    --------\n    > var y = base.dists.geometric.pmf( 4.0, 0.3 )\n    ~0.072\n    > y = base.dists.geometric.pmf( 2.0, 0.7 )\n    ~0.063\n    > y = base.dists.geometric.pmf( -1.0, 0.5 )\n    0.0\n    > y = base.dists.geometric.pmf( 0.0, NaN )\n    NaN\n    > y = base.dists.geometric.pmf( NaN, 0.5 )\n    NaN\n    // Invalid success probability:\n    > y = base.dists.geometric.pmf( 2.0, 1.5 )\n    NaN\n\n\nbase.dists.geometric.pmf.factory( p )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    geometric distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var mypmf = base.dists.geometric.pmf.factory( 0.5 );\n    > var y = mypmf( 3.0 )\n    0.0625\n    > y = mypmf( 1.0 )\n    0.25\n\n","base.dists.geometric.pmf.factory":"\nbase.dists.geometric.pmf.factory( p )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    geometric distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var mypmf = base.dists.geometric.pmf.factory( 0.5 );\n    > var y = mypmf( 3.0 )\n    0.0625\n    > y = mypmf( 1.0 )\n    0.25","base.dists.geometric.quantile":"\nbase.dists.geometric.quantile( r, p )\n    Evaluates the quantile function for a geometric distribution with success\n    probability `p` at a probability `r`.\n\n    If `r < 0` or `r > 1`, the function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    r: number\n        Input probability.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.geometric.quantile( 0.8, 0.4 )\n    3\n    > y = base.dists.geometric.quantile( 0.5, 0.4 )\n    1\n    > y = base.dists.geometric.quantile( 0.9, 0.1 )\n    21\n\n    > y = base.dists.geometric.quantile( -0.2, 0.1 )\n    NaN\n\n    > y = base.dists.geometric.quantile( NaN, 0.8 )\n    NaN\n    > y = base.dists.geometric.quantile( 0.4, NaN )\n    NaN\n\n    > y = base.dists.geometric.quantile( 0.5, -1.0 )\n    NaN\n    > y = base.dists.geometric.quantile( 0.5, 1.5 )\n    NaN\n\n\nbase.dists.geometric.quantile.factory( p )\n    Returns a function for evaluating the quantile function of a geometric\n    distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.geometric.quantile.factory( 0.4 );\n    > var y = myquantile( 0.4 )\n    0\n    > y = myquantile( 0.8 )\n    3\n    > y = myquantile( 1.0 )\n    Infinity\n\n","base.dists.geometric.quantile.factory":"\nbase.dists.geometric.quantile.factory( p )\n    Returns a function for evaluating the quantile function of a geometric\n    distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.geometric.quantile.factory( 0.4 );\n    > var y = myquantile( 0.4 )\n    0\n    > y = myquantile( 0.8 )\n    3\n    > y = myquantile( 1.0 )\n    Infinity","base.dists.geometric.skewness":"\nbase.dists.geometric.skewness( p )\n    Returns the skewness of a geometric distribution with success probability\n    `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.geometric.skewness( 0.1 )\n    ~2.003\n    > v = base.dists.geometric.skewness( 0.5 )\n    ~2.121\n\n","base.dists.geometric.stdev":"\nbase.dists.geometric.stdev( p )\n    Returns the standard deviation of a geometric distribution with success\n    probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.geometric.stdev( 0.1 )\n    ~9.487\n    > v = base.dists.geometric.stdev( 0.5 )\n    ~1.414\n\n","base.dists.geometric.variance":"\nbase.dists.geometric.variance( p )\n    Returns the variance of a geometric distribution with success probability\n    `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.geometric.variance( 0.1 )\n    ~90.0\n    > v = base.dists.geometric.variance( 0.5 )\n    2.0\n\n","base.dists.gumbel.cdf":"\nbase.dists.gumbel.cdf( x, μ, β )\n    Evaluates the cumulative distribution function (CDF) for a Gumbel\n    distribution with location parameter `μ` and scale parameter `β` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.cdf( 10.0, 0.0, 3.0 )\n    ~0.965\n    > y = base.dists.gumbel.cdf( -2.0, 0.0, 3.0 )\n    ~0.143\n    > y = base.dists.gumbel.cdf( 0.0, 0.0, 1.0 )\n    ~0.368\n    > y = base.dists.gumbel.cdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.gumbel.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.cdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.gumbel.cdf( 0.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.gumbel.cdf.factory( μ, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Gumbel distribution with location parameter `μ` and scale parameter\n    `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.gumbel.cdf.factory( 2.0, 3.0 );\n    > var y = myCDF( 10.0 )\n    ~0.933\n    > y = myCDF( 2.0 )\n    ~0.368\n\n","base.dists.gumbel.cdf.factory":"\nbase.dists.gumbel.cdf.factory( μ, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Gumbel distribution with location parameter `μ` and scale parameter\n    `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.gumbel.cdf.factory( 2.0, 3.0 );\n    > var y = myCDF( 10.0 )\n    ~0.933\n    > y = myCDF( 2.0 )\n    ~0.368","base.dists.gumbel.entropy":"\nbase.dists.gumbel.entropy( μ, β )\n    Returns the differential entropy of a Gumbel distribution with location\n    parameter `μ` and scale parameter `β` (in nats).\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.entropy( 0.0, 1.0 )\n    ~1.577\n    > y = base.dists.gumbel.entropy( 4.0, 2.0 )\n    ~2.27\n    > y = base.dists.gumbel.entropy( NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.entropy( 0.0, NaN )\n    NaN\n    > y = base.dists.gumbel.entropy( 0.0, 0.0 )\n    NaN\n\n","base.dists.gumbel.Gumbel":"\nbase.dists.gumbel.Gumbel( [μ, β] )\n    Returns a Gumbel distribution object.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter. Default: `0.0`.\n\n    β: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    gumbel: Object\n        Distribution instance.\n\n    gumbel.mu: number\n        Location parameter.\n\n    gumbel.beta: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    gumbel.entropy: number\n        Read-only property which returns the differential entropy.\n\n    gumbel.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    gumbel.mean: number\n        Read-only property which returns the expected value.\n\n    gumbel.median: number\n        Read-only property which returns the median.\n\n    gumbel.mode: number\n        Read-only property which returns the mode.\n\n    gumbel.skewness: number\n        Read-only property which returns the skewness.\n\n    gumbel.stdev: number\n        Read-only property which returns the standard deviation.\n\n    gumbel.variance: number\n        Read-only property which returns the variance.\n\n    gumbel.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    gumbel.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    gumbel.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    gumbel.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    gumbel.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    gumbel.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var gumbel = base.dists.gumbel.Gumbel( -2.0, 3.0 );\n    > gumbel.mu\n    -2.0\n    > gumbel.beta\n    3.0\n    > gumbel.entropy\n    ~2.676\n    > gumbel.kurtosis\n    2.4\n    > gumbel.mean\n    ~-0.268\n    > gumbel.median\n    ~-0.9\n    > gumbel.mode\n    -2.0\n    > gumbel.skewness\n    ~1.14\n    > gumbel.stdev\n    ~3.848\n    > gumbel.variance\n    ~14.804\n    > gumbel.cdf( 0.8 )\n    ~0.675\n    > gumbel.logcdf( 0.8 )\n    ~-0.393\n    > gumbel.logpdf( 1.0 )\n    ~-2.466\n    > gumbel.mgf( 0.2 )\n    ~1.487\n    > gumbel.pdf( 1.0 )\n    ~0.085\n    > gumbel.quantile( 0.8 )\n    ~2.5\n\n","base.dists.gumbel.kurtosis":"\nbase.dists.gumbel.kurtosis( μ, β )\n    Returns the excess kurtosis of a Gumbel distribution with location parameter\n    `μ` and scale parameter `β`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.kurtosis( 0.0, 1.0 )\n    2.4\n    > y = base.dists.gumbel.kurtosis( 4.0, 2.0 )\n    2.4\n    > y = base.dists.gumbel.kurtosis( NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.kurtosis( 0.0, NaN )\n    NaN\n    > y = base.dists.gumbel.kurtosis( 0.0, 0.0 )\n    NaN\n\n","base.dists.gumbel.logcdf":"\nbase.dists.gumbel.logcdf( x, μ, β )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.logcdf( 10.0, 0.0, 3.0 )\n    ~-0.036\n    > y = base.dists.gumbel.logcdf( -2.0, 0.0, 3.0 )\n    ~-1.948\n    > y = base.dists.gumbel.logcdf( 0.0, 0.0, 1.0 )\n    ~-1.0\n    > y = base.dists.gumbel.logcdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.gumbel.logcdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.logcdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.gumbel.logcdf( 0.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.gumbel.logcdf.factory( μ, β )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Gumbel distribution with location parameter\n    `μ` and scale parameter `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myLCDF = base.dists.gumbel.logcdf.factory( 2.0, 3.0 );\n    > var y = myLCDF( 10.0 )\n    ~-0.069\n    > y = myLCDF( 2.0 )\n    ~-1.0\n\n","base.dists.gumbel.logcdf.factory":"\nbase.dists.gumbel.logcdf.factory( μ, β )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Gumbel distribution with location parameter\n    `μ` and scale parameter `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myLCDF = base.dists.gumbel.logcdf.factory( 2.0, 3.0 );\n    > var y = myLCDF( 10.0 )\n    ~-0.069\n    > y = myLCDF( 2.0 )\n    ~-1.0","base.dists.gumbel.logpdf":"\nbase.dists.gumbel.logpdf( x, μ, β )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.logpdf( 0.0, 0.0, 2.0 )\n    ~-1.693\n    > y = base.dists.gumbel.logpdf( 0.0, 0.0, 1.0 )\n    ~-1\n    > y = base.dists.gumbel.logpdf( 1.0, 3.0, 2.0 )\n    ~-2.411\n    > y = base.dists.gumbel.logpdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.gumbel.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.logpdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.gumbel.logpdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.gumbel.logpdf.factory( μ, β )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Gumbel distribution with location parameter `μ` and\n    scale parameter `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.gumbel.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogpdf( 10.0 )\n    ~-1.693\n    > y = mylogpdf( 12.0 )\n    ~-2.061\n\n","base.dists.gumbel.logpdf.factory":"\nbase.dists.gumbel.logpdf.factory( μ, β )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Gumbel distribution with location parameter `μ` and\n    scale parameter `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.gumbel.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogpdf( 10.0 )\n    ~-1.693\n    > y = mylogpdf( 12.0 )\n    ~-2.061","base.dists.gumbel.mean":"\nbase.dists.gumbel.mean( μ, β )\n    Returns the expected value of a Gumbel distribution with location parameter\n    `μ` and scale parameter `β`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.mean( 0.0, 1.0 )\n    ~0.577\n    > y = base.dists.gumbel.mean( 4.0, 2.0 )\n    ~5.154\n    > y = base.dists.gumbel.mean( NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.mean( 0.0, NaN )\n    NaN\n    > y = base.dists.gumbel.mean( 0.0, 0.0 )\n    NaN\n\n","base.dists.gumbel.median":"\nbase.dists.gumbel.median( μ, β )\n    Returns the median of a Gumbel distribution with location parameter `μ` and\n    scale parameter `β`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.median( 0.0, 1.0 )\n    ~0.367\n    > y = base.dists.gumbel.median( 4.0, 2.0 )\n    ~4.733\n    > y = base.dists.gumbel.median( NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.median( 0.0, NaN )\n    NaN\n    > y = base.dists.gumbel.median( 0.0, 0.0 )\n    NaN\n\n","base.dists.gumbel.mgf":"\nbase.dists.gumbel.mgf( t, μ, β )\n    Evaluates the moment-generating function (MGF) for a Gumbel distribution\n    with location parameter `μ` and scale parameter `β` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.mgf( -1.0, 0.0, 3.0 )\n    6.0\n    > y = base.dists.gumbel.mgf( 0.0, 0.0, 1.0 )\n    1.0\n    > y = base.dists.gumbel.mgf( 0.1, 0.0, 3.0 )\n    ~1.298\n\n    > y = base.dists.gumbel.mgf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.gumbel.mgf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.mgf( 0.0, 0.0, NaN )\n    NaN\n\n    // Case: `t >= 1/beta`\n    > y = base.dists.gumbel.mgf( 0.8, 0.0, 2.0 )\n    NaN\n\n    // Non-positive scale parameter:\n    > y = base.dists.gumbel.mgf( 0.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.gumbel.mgf.factory( μ, β )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Gumbel distribution with location parameter `μ` and scale parameter `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.gumbel.mgf.factory( 0.0, 3.0 );\n    > var y = myMGF( -1.5 )\n    ~52.343\n    > y = myMGF( -1.0 )\n    6.0\n\n","base.dists.gumbel.mgf.factory":"\nbase.dists.gumbel.mgf.factory( μ, β )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Gumbel distribution with location parameter `μ` and scale parameter `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.gumbel.mgf.factory( 0.0, 3.0 );\n    > var y = myMGF( -1.5 )\n    ~52.343\n    > y = myMGF( -1.0 )\n    6.0","base.dists.gumbel.mode":"\nbase.dists.gumbel.mode( μ, β )\n    Returns the mode of a Gumbel distribution with location parameter `μ` and\n    scale parameter `β`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.mode( 0.0, 1.0 )\n    0.0\n    > y = base.dists.gumbel.mode( 4.0, 2.0 )\n    4.0\n    > y = base.dists.gumbel.mode( NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.mode( 0.0, NaN )\n    NaN\n    > y = base.dists.gumbel.mode( 0.0, 0.0 )\n    NaN\n\n","base.dists.gumbel.pdf":"\nbase.dists.gumbel.pdf( x, μ, β )\n    Evaluates the probability density function (PDF) for a Gumbel distribution\n    with location parameter `μ` and scale parameter `β` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.pdf( 0.0, 0.0, 2.0 )\n    ~0.184\n    > y = base.dists.gumbel.pdf( 0.0, 0.0, 1.0 )\n    ~0.368\n    > y = base.dists.gumbel.pdf( 1.0, 3.0, 2.0 )\n    ~0.09\n    > y = base.dists.gumbel.pdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.gumbel.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.pdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.gumbel.pdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.gumbel.pdf.factory( μ, β )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Gumbel distribution with location parameter `μ` and scale parameter\n    `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.gumbel.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    ~0.184\n    > y = myPDF( 12.0 )\n    ~0.127\n\n","base.dists.gumbel.pdf.factory":"\nbase.dists.gumbel.pdf.factory( μ, β )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Gumbel distribution with location parameter `μ` and scale parameter\n    `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.gumbel.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    ~0.184\n    > y = myPDF( 12.0 )\n    ~0.127","base.dists.gumbel.quantile":"\nbase.dists.gumbel.quantile( p, μ, β )\n    Evaluates the quantile function for a Gumbel distribution with location\n    parameter `μ` and scale parameter `β` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.quantile( 0.8, 0.0, 1.0 )\n    ~1.5\n    > y = base.dists.gumbel.quantile( 0.5, 4.0, 2.0 )\n    ~4.733\n    > y = base.dists.gumbel.quantile( 0.5, 4.0, 4.0 )\n    ~5.466\n\n    > y = base.dists.gumbel.quantile( 1.1, 0.0, 1.0 )\n    NaN\n    > y = base.dists.gumbel.quantile( -0.2, 0.0, 1.0 )\n    NaN\n\n    > y = base.dists.gumbel.quantile( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.gumbel.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.quantile( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.gumbel.quantile( 0.5, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.gumbel.quantile.factory( μ, β )\n    Returns a function for evaluating the quantile function of a Gumbel\n    distribution with location parameter `μ` and scale parameter `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.gumbel.quantile.factory( 8.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    ~8.733\n    > y = myQuantile( 0.7 )\n    ~10.062\n\n","base.dists.gumbel.quantile.factory":"\nbase.dists.gumbel.quantile.factory( μ, β )\n    Returns a function for evaluating the quantile function of a Gumbel\n    distribution with location parameter `μ` and scale parameter `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.gumbel.quantile.factory( 8.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    ~8.733\n    > y = myQuantile( 0.7 )\n    ~10.062","base.dists.gumbel.skewness":"\nbase.dists.gumbel.skewness( μ, β )\n    Returns the skewness of a Gumbel distribution with location parameter `μ`\n    and scale parameter `β`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.skewness( 0.0, 1.0 )\n    ~1.14\n    > y = base.dists.gumbel.skewness( 4.0, 2.0 )\n    ~1.14\n    > y = base.dists.gumbel.skewness( NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.skewness( 0.0, NaN )\n    NaN\n    > y = base.dists.gumbel.skewness( 0.0, 0.0 )\n    NaN\n\n","base.dists.gumbel.stdev":"\nbase.dists.gumbel.stdev( μ, β )\n    Returns the standard deviation of a Gumbel distribution with location\n    parameter `μ` and scale parameter `β`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.stdev( 0.0, 1.0 )\n    ~1.283\n    > y = base.dists.gumbel.stdev( 4.0, 2.0 )\n    ~2.565\n    > y = base.dists.gumbel.stdev( NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.stdev( 0.0, NaN )\n    NaN\n    > y = base.dists.gumbel.stdev( 0.0, 0.0 )\n    NaN\n\n","base.dists.gumbel.variance":"\nbase.dists.gumbel.variance( μ, β )\n    Returns the variance of a Gumbel distribution with location parameter `μ`\n    and scale parameter `β`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.variance( 0.0, 1.0 )\n    ~1.645\n    > y = base.dists.gumbel.variance( 4.0, 2.0 )\n    ~6.58\n    > y = base.dists.gumbel.variance( NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.variance( 0.0, NaN )\n    NaN\n    > y = base.dists.gumbel.variance( 0.0, 0.0 )\n    NaN\n\n","base.dists.hypergeometric.cdf":"\nbase.dists.hypergeometric.cdf( x, N, K, n )\n    Evaluates the cumulative distribution function (CDF) for a hypergeometric\n    distribution with population size `N`, subpopulation size `K`, and number of\n    draws `n` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a population size `N`, subpopulation size `K` or draws `n` which\n    is not a nonnegative integer, the function returns `NaN`.\n\n    If the number of draws `n` or subpopulation size `K` exceeds population size\n     `N`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.hypergeometric.cdf( 1.0, 8, 4, 2 )\n    ~0.786\n    > y = base.dists.hypergeometric.cdf( 1.5, 8, 4, 2 )\n    ~0.786\n    > y = base.dists.hypergeometric.cdf( 2.0, 8, 4, 2 )\n    1.0\n    > y = base.dists.hypergeometric.cdf( 0, 8, 4, 2)\n    ~0.214\n\n    > y = base.dists.hypergeometric.cdf( NaN, 10, 5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.cdf( 0.0, NaN, 5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.cdf( 0.0, 10, NaN, 2 )\n    NaN\n    > y = base.dists.hypergeometric.cdf( 0.0, 10, 5, NaN )\n    NaN\n\n    > y = base.dists.hypergeometric.cdf( 2.0, 10.5, 5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.cdf( 2.0, 10, 1.5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.cdf( 2.0, 10, 5, -2.0 )\n    NaN\n    > y = base.dists.hypergeometric.cdf( 2.0, 10, 5, 12 )\n    NaN\n    > y = base.dists.hypergeometric.cdf( 2.0, 8, 3, 9 )\n    NaN\n\n\nbase.dists.hypergeometric.cdf.factory( N, K, n )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a hypergeometric distribution with population size `N`, subpopulation\n    size `K`, and number of draws `n`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.hypergeometric.cdf.factory( 30, 20, 5 );\n    > var y = myCDF( 4.0 )\n    ~0.891\n    > y = myCDF( 1.0 )\n    ~0.031\n\n","base.dists.hypergeometric.cdf.factory":"\nbase.dists.hypergeometric.cdf.factory( N, K, n )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a hypergeometric distribution with population size `N`, subpopulation\n    size `K`, and number of draws `n`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.hypergeometric.cdf.factory( 30, 20, 5 );\n    > var y = myCDF( 4.0 )\n    ~0.891\n    > y = myCDF( 1.0 )\n    ~0.031","base.dists.hypergeometric.Hypergeometric":"\nbase.dists.hypergeometric.Hypergeometric( [N, K, n] )\n    Returns a hypergeometric distribution object.\n\n    Parameters\n    ----------\n    N: integer (optional)\n        Population size. Must be a nonnegative integer larger than or equal to\n        `K` and `n`.\n\n    K: integer (optional)\n        Subpopulation size. Must be a nonnegative integer smaller than or equal\n        to `N`.\n\n    n: integer (optional)\n        Number of draws. Must be a nonnegative integer smaller than or equal to\n        `N`.\n\n    Returns\n    -------\n    hypergeometric: Object\n        Distribution instance.\n\n    hypergeometric.N: number\n        Population size. If set, the value must be a nonnegative integer larger\n        than or equal to `K` and `n`.\n\n    hypergeometric.K: number\n        Subpopulation size. If set, the value must be a nonnegative integer\n        smaller than or equal to `N`.\n\n    hypergeometric.n: number\n        Number of draws. If set, the value must be a nonnegative integer\n        smaller than or equal to `N`.\n\n    hypergeometric.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    hypergeometric.mean: number\n        Read-only property which returns the expected value.\n\n    hypergeometric.mode: number\n        Read-only property which returns the mode.\n\n    hypergeometric.skewness: number\n        Read-only property which returns the skewness.\n\n    hypergeometric.stdev: number\n        Read-only property which returns the standard deviation.\n\n    hypergeometric.variance: number\n        Read-only property which returns the variance.\n\n    hypergeometric.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    hypergeometric.logpmf: Function\n        Evaluates the natural logarithm of the probability mass function (PMF).\n\n    hypergeometric.pmf: Function\n        Evaluates the probability mass function (PMF).\n\n    hypergeometric.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var hypergeometric = base.dists.hypergeometric.Hypergeometric( 100, 70, 20 );\n    > hypergeometric.N\n    100.0\n    > hypergeometric.K\n    70.0\n    > hypergeometric.n\n    20.0\n    > hypergeometric.kurtosis\n    ~-0.063\n    > hypergeometric.mean\n    14.0\n    > hypergeometric.mode\n    14.0\n    > hypergeometric.skewness\n    ~-0.133\n    > hypergeometric.stdev\n    ~1.842\n    > hypergeometric.variance\n    ~3.394\n    > hypergeometric.cdf( 2.9 )\n    ~0.0\n    > hypergeometric.logpmf( 10 )\n    ~-3.806\n    > hypergeometric.pmf( 10 )\n    ~0.022\n    > hypergeometric.quantile( 0.8 )\n    16.0\n\n","base.dists.hypergeometric.kurtosis":"\nbase.dists.hypergeometric.kurtosis( N, K, n )\n    Returns the excess kurtosis of a hypergeometric distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a population size `N`, subpopulation size `K` or draws `n` which\n    is not a nonnegative integer, the function returns `NaN`.\n\n    If the number of draws `n` or subpopulation size `K` exceed population size\n    `N`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.hypergeometric.kurtosis( 16, 11, 4 )\n    ~-0.326\n    > v = base.dists.hypergeometric.kurtosis( 4, 2, 2 )\n    0.0\n\n    > v = base.dists.hypergeometric.kurtosis( 10, 5, 12 )\n    NaN\n    > v = base.dists.hypergeometric.kurtosis( 10.3, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.kurtosis( 10, 5.5, 4 )\n    NaN\n    > v = base.dists.hypergeometric.kurtosis( 10, 5, 4.5 )\n    NaN\n\n    > v = base.dists.hypergeometric.kurtosis( NaN, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.kurtosis( 20, NaN, 4 )\n    NaN\n    > v = base.dists.hypergeometric.kurtosis( 20, 10, NaN )\n    NaN\n\n","base.dists.hypergeometric.logpmf":"\nbase.dists.hypergeometric.logpmf( x, N, K, n )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    hypergeometric distribution with population size `N`, subpopulation size\n    `K`, and number of draws `n` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a population size `N`, subpopulation size `K`, or draws `n`\n    which is not a nonnegative integer, the function returns `NaN`.\n\n    If the number of draws `n` or the subpopulation size `K` exceed population\n    size `N`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPMF.\n\n    Examples\n    --------\n    > var y = base.dists.hypergeometric.logpmf( 1.0, 8, 4, 2 )\n    ~-0.56\n    > y = base.dists.hypergeometric.logpmf( 2.0, 8, 4, 2 )\n    ~-1.54\n    > y = base.dists.hypergeometric.logpmf( 0.0, 8, 4, 2 )\n    ~-1.54\n    > y = base.dists.hypergeometric.logpmf( 1.5, 8, 4, 2 )\n    -Infinity\n\n    > y = base.dists.hypergeometric.logpmf( NaN, 10, 5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.logpmf( 0.0, NaN, 5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.logpmf( 0.0, 10, NaN, 2 )\n    NaN\n    > y = base.dists.hypergeometric.logpmf( 0.0, 10, 5, NaN )\n    NaN\n\n    > y = base.dists.hypergeometric.logpmf( 2.0, 10.5, 5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.logpmf( 2.0, 5, 1.5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.logpmf( 2.0, 10, 5, -2.0 )\n    NaN\n    > y = base.dists.hypergeometric.logpmf( 2.0, 10, 5, 12 )\n    NaN\n    > y = base.dists.hypergeometric.logpmf( 2.0, 8, 3, 9 )\n    NaN\n\n\nbase.dists.hypergeometric.logpmf.factory( N, K, n )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a hypergeometric distribution with population size\n    `N`, subpopulation size `K`, and number of draws `n`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogPMF = base.dists.hypergeometric.logpmf.factory( 30, 20, 5 );\n    > var y = mylogPMF( 4.0 )\n    ~-1.079\n    > y = mylogPMF( 1.0 )\n    ~-3.524\n\n","base.dists.hypergeometric.logpmf.factory":"\nbase.dists.hypergeometric.logpmf.factory( N, K, n )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a hypergeometric distribution with population size\n    `N`, subpopulation size `K`, and number of draws `n`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogPMF = base.dists.hypergeometric.logpmf.factory( 30, 20, 5 );\n    > var y = mylogPMF( 4.0 )\n    ~-1.079\n    > y = mylogPMF( 1.0 )\n    ~-3.524","base.dists.hypergeometric.mean":"\nbase.dists.hypergeometric.mean( N, K, n )\n    Returns the expected value of a hypergeometric distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a population size `N`, subpopulation size `K` or draws `n` which\n    is not a nonnegative integer, the function returns `NaN`.\n\n    If the number of draws `n` or the subpopulation size `K` exceed population\n    size `N`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.hypergeometric.mean( 16, 11, 4 )\n    2.75\n    > v = base.dists.hypergeometric.mean( 2, 1, 1 )\n    0.5\n\n    > v = base.dists.hypergeometric.mean( 10, 5, 12 )\n    NaN\n    > v = base.dists.hypergeometric.mean( 10.3, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.mean( 10, 5.5, 4 )\n    NaN\n    > v = base.dists.hypergeometric.mean( 10, 5, 4.5 )\n    NaN\n\n    > v = base.dists.hypergeometric.mean( NaN, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.mean( 20, NaN, 4 )\n    NaN\n    > v = base.dists.hypergeometric.mean( 20, 10, NaN )\n    NaN\n\n","base.dists.hypergeometric.mode":"\nbase.dists.hypergeometric.mode( N, K, n )\n    Returns the mode of a hypergeometric distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a population size `N`, subpopulation size `K` or draws `n` which\n    is not a nonnegative integer, the function returns `NaN`.\n\n    If the number of draws `n` or the subpopulation size `K` exceed population\n    size `N`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.hypergeometric.mode( 16, 11, 4 )\n    3\n    > v = base.dists.hypergeometric.mode( 2, 1, 1 )\n    1\n\n    > v = base.dists.hypergeometric.mode( 10, 5, 12 )\n    NaN\n    > v = base.dists.hypergeometric.mode( 10.3, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.mode( 10, 5.5, 4 )\n    NaN\n    > v = base.dists.hypergeometric.mode( 10, 5, 4.5 )\n    NaN\n\n    > v = base.dists.hypergeometric.mode( NaN, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.mode( 20, NaN, 4 )\n    NaN\n    > v = base.dists.hypergeometric.mode( 20, 10, NaN )\n    NaN\n\n","base.dists.hypergeometric.pmf":"\nbase.dists.hypergeometric.pmf( x, N, K, n )\n    Evaluates the probability mass function (PMF) for a hypergeometric\n    distribution with population size `N`, subpopulation size `K`, and number of\n    draws `n` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a population size `N`, subpopulation size `K` or draws `n` which\n    is not a nonnegative integer, the function returns `NaN`.\n\n    If the number of draws `n` or the subpopulation size `K` exceed population\n    size `N`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    out: number\n        Evaluated PMF.\n\n    Examples\n    --------\n    > var y = base.dists.hypergeometric.pmf( 1.0, 8, 4, 2 )\n    ~0.571\n    > y = base.dists.hypergeometric.pmf( 2.0, 8, 4, 2 )\n    ~0.214\n    > y = base.dists.hypergeometric.pmf( 0.0, 8, 4, 2 )\n    ~0.214\n    > y = base.dists.hypergeometric.pmf( 1.5, 8, 4, 2 )\n    0.0\n\n    > y = base.dists.hypergeometric.pmf( NaN, 10, 5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.pmf( 0.0, NaN, 5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.pmf( 0.0, 10, NaN, 2 )\n    NaN\n    > y = base.dists.hypergeometric.pmf( 0.0, 10, 5, NaN )\n    NaN\n\n    > y = base.dists.hypergeometric.pmf( 2.0, 10.5, 5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.pmf( 2.0, 5, 1.5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.pmf( 2.0, 10, 5, -2.0 )\n    NaN\n    > y = base.dists.hypergeometric.pmf( 2.0, 10, 5, 12 )\n    NaN\n    > y = base.dists.hypergeometric.pmf( 2.0, 8, 3, 9 )\n    NaN\n\n\nbase.dists.hypergeometric.pmf.factory( N, K, n )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    hypergeometric distribution with population size `N`, subpopulation size\n    `K`, and number of draws `n`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var myPMF = base.dists.hypergeometric.pmf.factory( 30, 20, 5 );\n    > var y = myPMF( 4.0 )\n    ~0.34\n    > y = myPMF( 1.0 )\n    ~0.029\n\n","base.dists.hypergeometric.pmf.factory":"\nbase.dists.hypergeometric.pmf.factory( N, K, n )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    hypergeometric distribution with population size `N`, subpopulation size\n    `K`, and number of draws `n`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var myPMF = base.dists.hypergeometric.pmf.factory( 30, 20, 5 );\n    > var y = myPMF( 4.0 )\n    ~0.34\n    > y = myPMF( 1.0 )\n    ~0.029","base.dists.hypergeometric.quantile":"\nbase.dists.hypergeometric.quantile( p, N, K, n )\n    Evaluates the quantile function for a hypergeometric distribution with\n    population size `N`, subpopulation size `K`, and number of draws `n` at a\n    probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a population size `N`, subpopulation size `K` or draws `n` which\n    is not a nonnegative integer, the function returns `NaN`.\n\n    If the number of draws `n` or the subpopulation size `K` exceed population\n    size `N`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.hypergeometric.quantile( 0.4, 40, 20, 10 )\n    5\n    > y = base.dists.hypergeometric.quantile( 0.8, 60, 40, 20 )\n    15\n    > y = base.dists.hypergeometric.quantile( 0.5, 100, 10, 10 )\n    1\n    > y = base.dists.hypergeometric.quantile( 0.0, 100, 40, 20 )\n    0\n    > y = base.dists.hypergeometric.quantile( 1.0, 100, 40, 20 )\n    20\n\n    > y = base.dists.hypergeometric.quantile( NaN, 40, 20, 10 )\n    NaN\n    > y = base.dists.hypergeometric.quantile( 0.2, NaN, 20, 10 )\n    NaN\n    > y = base.dists.hypergeometric.quantile( 0.2, 40, NaN, 10 )\n    NaN\n    > y = base.dists.hypergeometric.quantile( 0.2, 40, 20, NaN )\n    NaN\n\n\nbase.dists.hypergeometric.quantile.factory( N, K, n )\n    Returns a function for evaluating the quantile function of a hypergeometric\n    distribution with population size `N`, subpopulation size `K`, and number of\n    draws `n`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.hypergeometric.quantile.factory( 100, 20, 10 );\n    > var y = myQuantile( 0.2 )\n    1\n    > y = myQuantile( 0.9 )\n    4\n\n","base.dists.hypergeometric.quantile.factory":"\nbase.dists.hypergeometric.quantile.factory( N, K, n )\n    Returns a function for evaluating the quantile function of a hypergeometric\n    distribution with population size `N`, subpopulation size `K`, and number of\n    draws `n`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.hypergeometric.quantile.factory( 100, 20, 10 );\n    > var y = myQuantile( 0.2 )\n    1\n    > y = myQuantile( 0.9 )\n    4","base.dists.hypergeometric.skewness":"\nbase.dists.hypergeometric.skewness( N, K, n )\n    Returns the skewness of a hypergeometric distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a population size `N`, subpopulation size `K` or draws `n` which\n    is not a nonnegative integer, the function returns `NaN`.\n\n    If the number of draws `n` or the subpopulation size `K` exceed population\n    size `N`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.hypergeometric.skewness( 16, 11, 4 )\n    ~-0.258\n    > v = base.dists.hypergeometric.skewness( 4, 2, 2 )\n    0.0\n\n    > v = base.dists.hypergeometric.skewness( 10, 5, 12 )\n    NaN\n    > v = base.dists.hypergeometric.skewness( 10.3, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.skewness( 10, 5.5, 4 )\n    NaN\n    > v = base.dists.hypergeometric.skewness( 10, 5, 4.5 )\n    NaN\n\n    > v = base.dists.hypergeometric.skewness( NaN, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.skewness( 20, NaN, 4 )\n    NaN\n    > v = base.dists.hypergeometric.skewness( 20, 10, NaN )\n    NaN\n\n","base.dists.hypergeometric.stdev":"\nbase.dists.hypergeometric.stdev( N, K, n )\n    Returns the standard deviation of a hypergeometric distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a population size `N`, subpopulation size `K` or draws `n` which\n    is not a nonnegative integer, the function returns `NaN`.\n\n    If the number of draws `n` or the subpopulation size `K` exceed population\n    size `N`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.hypergeometric.stdev( 16, 11, 4 )\n    ~0.829\n    > v = base.dists.hypergeometric.stdev( 2, 1, 1 )\n    0.5\n\n    > v = base.dists.hypergeometric.stdev( 10, 5, 12 )\n    NaN\n    > v = base.dists.hypergeometric.stdev( 10.3, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.stdev( 10, 5.5, 4 )\n    NaN\n    > v = base.dists.hypergeometric.stdev( 10, 5, 4.5 )\n    NaN\n\n    > v = base.dists.hypergeometric.stdev( NaN, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.stdev( 20, NaN, 4 )\n    NaN\n    > v = base.dists.hypergeometric.stdev( 20, 10, NaN )\n    NaN\n\n","base.dists.hypergeometric.variance":"\nbase.dists.hypergeometric.variance( N, K, n )\n    Returns the variance of a hypergeometric distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a population size `N`, subpopulation size `K` or draws `n` which\n    is not a nonnegative integer, the function returns `NaN`.\n\n    If the number of draws `n` or the subpopulation size `K` exceed population\n    size `N`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.hypergeometric.variance( 16, 11, 4 )\n    ~0.688\n    > v = base.dists.hypergeometric.variance( 2, 1, 1 )\n    0.25\n\n    > v = base.dists.hypergeometric.variance( 10, 5, 12 )\n    NaN\n    > v = base.dists.hypergeometric.variance( 10.3, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.variance( 10, 5.5, 4 )\n    NaN\n    > v = base.dists.hypergeometric.variance( 10, 5, 4.5 )\n    NaN\n\n    > v = base.dists.hypergeometric.variance( NaN, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.variance( 20, NaN, 4 )\n    NaN\n    > v = base.dists.hypergeometric.variance( 20, 10, NaN )\n    NaN\n\n","base.dists.invgamma.cdf":"\nbase.dists.invgamma.cdf( x, α, β )\n    Evaluates the cumulative distribution function (CDF) for an inverse gamma\n    distribution with shape parameter `α` and scale parameter `β` at a value\n    `x`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.invgamma.cdf( 2.0, 1.0, 1.0 )\n    ~0.607\n    > y = base.dists.invgamma.cdf( 2.0, 3.0, 1.0 )\n    ~0.986\n    > y = base.dists.invgamma.cdf( -1.0, 2.0, 2.0 )\n    0.0\n    > y = base.dists.invgamma.cdf( PINF, 4.0, 2.0 )\n    1.0\n    > y = base.dists.invgamma.cdf( NINF, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.invgamma.cdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.invgamma.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.invgamma.cdf( 0.0, 0.0, NaN )\n    NaN\n\n    > y = base.dists.invgamma.cdf( 2.0, -1.0, 1.0 )\n    NaN\n    > y = base.dists.invgamma.cdf( 2.0, 1.0, -1.0 )\n    NaN\n\n\nbase.dists.invgamma.cdf.factory( α, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an inverse gamma distribution with shape parameter `α` and scale\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.invgamma.cdf.factory( 2.0, 0.5 );\n    > var y = myCDF( 0.5 )\n    ~0.736\n    > y = myCDF( 2.0 )\n    ~0.974\n\n","base.dists.invgamma.cdf.factory":"\nbase.dists.invgamma.cdf.factory( α, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an inverse gamma distribution with shape parameter `α` and scale\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.invgamma.cdf.factory( 2.0, 0.5 );\n    > var y = myCDF( 0.5 )\n    ~0.736\n    > y = myCDF( 2.0 )\n    ~0.974","base.dists.invgamma.entropy":"\nbase.dists.invgamma.entropy( α, β )\n    Returns the differential entropy of an inverse gamma distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.invgamma.entropy( 1.0, 1.0 )\n    ~2.154\n    > v = base.dists.invgamma.entropy( 4.0, 12.0 )\n    ~1.996\n    > v = base.dists.invgamma.entropy( 8.0, 2.0 )\n    ~-0.922\n\n","base.dists.invgamma.InvGamma":"\nbase.dists.invgamma.InvGamma( [α, β] )\n    Returns an inverse gamma distribution object.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n    β: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    invgamma: Object\n        Distribution instance.\n\n    invgamma.alpha: number\n        Shape parameter. If set, the value must be greater than `0`.\n\n    invgamma.beta: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    invgamma.entropy: number\n        Read-only property which returns the differential entropy.\n\n    invgamma.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    invgamma.mean: number\n        Read-only property which returns the expected value.\n\n    invgamma.mode: number\n        Read-only property which returns the mode.\n\n    invgamma.skewness: number\n        Read-only property which returns the skewness.\n\n    invgamma.stdev: number\n        Read-only property which returns the standard deviation.\n\n    invgamma.variance: number\n        Read-only property which returns the variance.\n\n    invgamma.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    invgamma.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    invgamma.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    invgamma.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var invgamma = base.dists.invgamma.InvGamma( 6.0, 5.0 );\n    > invgamma.alpha\n    6.0\n    > invgamma.beta\n    5.0\n    > invgamma.entropy\n    ~0.454\n    > invgamma.kurtosis\n    19.0\n    > invgamma.mean\n    1.0\n    > invgamma.mode\n    ~0.714\n    > invgamma.skewness\n    ~2.667\n    > invgamma.stdev\n    0.5\n    > invgamma.variance\n    0.25\n    > invgamma.cdf( 0.8 )\n    ~0.406\n    > invgamma.pdf( 1.0 )\n    ~0.877\n    > invgamma.logpdf( 1.0 )\n    ~-0.131\n    > invgamma.quantile( 0.8 )\n    ~1.281\n\n","base.dists.invgamma.kurtosis":"\nbase.dists.invgamma.kurtosis( α, β )\n    Returns the excess kurtosis of an inverse gamma distribution.\n\n    If `α <= 4` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.invgamma.kurtosis( 7.0, 5.0 )\n    12.0\n    > v = base.dists.invgamma.kurtosis( 6.0, 12.0 )\n    19.0\n    > v = base.dists.invgamma.kurtosis( 8.0, 2.0 )\n    ~8.7\n\n","base.dists.invgamma.logpdf":"\nbase.dists.invgamma.logpdf( x, α, β )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for an inverse gamma distribution with shape parameter `α` and scale\n    parameter `β` at a value `x`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.invgamma.logpdf( 2.0, 0.5, 1.0 )\n    ~-2.112\n    > y = base.dists.invgamma.logpdf( 0.2, 1.0, 1.0 )\n    ~-1.781\n    > y = base.dists.invgamma.logpdf( -1.0, 4.0, 2.0 )\n    -Infinity\n\n    > y = base.dists.invgamma.logpdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.invgamma.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.invgamma.logpdf( 0.0, 1.0, NaN )\n    NaN\n\n    // Negative shape parameter:\n    > y = base.dists.invgamma.logpdf( 2.0, -1.0, 1.0 )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.invgamma.logpdf( 2.0, 1.0, -1.0 )\n    NaN\n\n\nbase.dists.invgamma.logpdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) for an inverse gamma distribution with shape\n    parameter `α` and scale parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.invgamma.logpdf.factory( 6.0, 7.0 );\n    > var y = mylogPDF( 2.0 )\n    ~-1.464\n\n","base.dists.invgamma.logpdf.factory":"\nbase.dists.invgamma.logpdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) for an inverse gamma distribution with shape\n    parameter `α` and scale parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.invgamma.logpdf.factory( 6.0, 7.0 );\n    > var y = mylogPDF( 2.0 )\n    ~-1.464","base.dists.invgamma.mean":"\nbase.dists.invgamma.mean( α, β )\n    Returns the expected value of an inverse gamma distribution.\n\n    If `α <= 1` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.invgamma.mean( 4.0, 12.0 )\n    4.0\n    > v = base.dists.invgamma.mean( 8.0, 2.0 )\n    ~0.286\n\n","base.dists.invgamma.mode":"\nbase.dists.invgamma.mode( α, β )\n    Returns the mode of an inverse gamma distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.invgamma.mode( 1.0, 1.0 )\n    0.5\n    > v = base.dists.invgamma.mode( 4.0, 12.0 )\n    2.4\n    > v = base.dists.invgamma.mode( 8.0, 2.0 )\n    ~0.222\n\n","base.dists.invgamma.pdf":"\nbase.dists.invgamma.pdf( x, α, β )\n    Evaluates the probability density function (PDF) for an inverse gamma\n    distribution with shape parameter `α` and scale parameter `β` at a value\n    `x`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.invgamma.pdf( 2.0, 0.5, 1.0 )\n    ~0.121\n    > y = base.dists.invgamma.pdf( 0.2, 1.0, 1.0 )\n    ~0.168\n    > y = base.dists.invgamma.pdf( -1.0, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.invgamma.pdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.invgamma.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.invgamma.pdf( 0.0, 1.0, NaN )\n    NaN\n\n    // Negative shape parameter:\n    > y = base.dists.invgamma.pdf( 2.0, -1.0, 1.0 )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.invgamma.pdf( 2.0, 1.0, -1.0 )\n    NaN\n\n\nbase.dists.invgamma.pdf.factory( α, β )\n    Returns a function for evaluating the probability density function (PDF)\n    of an inverse gamma distribution with shape parameter `α` and scale\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.invgamma.pdf.factory( 6.0, 7.0 );\n    > var y = myPDF( 2.0 )\n    ~0.231\n\n","base.dists.invgamma.pdf.factory":"\nbase.dists.invgamma.pdf.factory( α, β )\n    Returns a function for evaluating the probability density function (PDF)\n    of an inverse gamma distribution with shape parameter `α` and scale\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.invgamma.pdf.factory( 6.0, 7.0 );\n    > var y = myPDF( 2.0 )\n    ~0.231","base.dists.invgamma.quantile":"\nbase.dists.invgamma.quantile( p, α, β )\n    Evaluates the quantile function for an inverse gamma distribution with shape\n    parameter `α` and scale parameter `β` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.invgamma.quantile( 0.8, 2.0, 1.0 )\n    ~1.213\n    > y = base.dists.invgamma.quantile( 0.5, 4.0, 2.0 )\n    ~0.545\n    > y = base.dists.invgamma.quantile( 1.1, 1.0, 1.0 )\n    NaN\n    > y = base.dists.invgamma.quantile( -0.2, 1.0, 1.0 )\n    NaN\n\n    > y = base.dists.invgamma.quantile( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.invgamma.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.invgamma.quantile( 0.0, 1.0, NaN )\n    NaN\n\n    // Non-positive shape parameter:\n    > y = base.dists.invgamma.quantile( 0.5, -1.0, 1.0 )\n    NaN\n\n    // Non-positive rate parameter:\n    > y = base.dists.invgamma.quantile( 0.5, 1.0, -1.0 )\n    NaN\n\n\nbase.dists.invgamma.quantile.factory( α, β )\n    Returns a function for evaluating the quantile function of an inverse gamma\n    distribution with shape parameter `α` and scale parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.invgamma.quantile.factory( 2.0, 2.0 );\n    > var y = myQuantile( 0.8 )\n    ~2.426\n    > y = myQuantile( 0.4 )\n    ~0.989\n\n","base.dists.invgamma.quantile.factory":"\nbase.dists.invgamma.quantile.factory( α, β )\n    Returns a function for evaluating the quantile function of an inverse gamma\n    distribution with shape parameter `α` and scale parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.invgamma.quantile.factory( 2.0, 2.0 );\n    > var y = myQuantile( 0.8 )\n    ~2.426\n    > y = myQuantile( 0.4 )\n    ~0.989","base.dists.invgamma.skewness":"\nbase.dists.invgamma.skewness( α, β )\n    Returns the skewness of an inverse gamma distribution.\n\n    If `α <= 3` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.invgamma.skewness( 4.0, 12.0 )\n    ~5.657\n    > v = base.dists.invgamma.skewness( 8.0, 2.0 )\n    ~1.96\n\n","base.dists.invgamma.stdev":"\nbase.dists.invgamma.stdev( α, β )\n    Returns the standard deviation of an inverse gamma distribution.\n\n    If `α <= 2` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.invgamma.stdev( 5.0, 7.0 )\n    ~1.01\n    > v = base.dists.invgamma.stdev( 4.0, 12.0 )\n    ~2.828\n    > v = base.dists.invgamma.stdev( 8.0, 2.0 )\n    ~0.117\n\n","base.dists.invgamma.variance":"\nbase.dists.invgamma.variance( α, β )\n    Returns the variance of an inverse gamma distribution.\n\n    If `α <= 2` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.invgamma.variance( 5.0, 7.0 )\n    ~1.021\n    > v = base.dists.invgamma.variance( 4.0, 12.0 )\n    8.0\n    > v = base.dists.invgamma.variance( 8.0, 2.0 )\n    ~0.014\n\n","base.dists.kumaraswamy.cdf":"\nbase.dists.kumaraswamy.cdf( x, a, b )\n    Evaluates the cumulative distribution function (CDF) for Kumaraswamy's\n    double bounded distribution with first shape parameter `a` and second shape\n    parameter `b` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.kumaraswamy.cdf( 0.5, 1.0, 1.0 )\n    ~0.5\n    > y = base.dists.kumaraswamy.cdf( 0.5, 2.0, 4.0 )\n    ~0.684\n    > y = base.dists.kumaraswamy.cdf( 0.2, 2.0, 2.0 )\n    ~0.078\n    > y = base.dists.kumaraswamy.cdf( 0.8, 4.0, 4.0 )\n    ~0.878\n    > y = base.dists.kumaraswamy.cdf( -0.5, 4.0, 2.0 )\n    0.0\n    > y = base.dists.kumaraswamy.cdf( 1.5, 4.0, 2.0 )\n    1.0\n\n    > y = base.dists.kumaraswamy.cdf( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.kumaraswamy.cdf( 2.0, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.kumaraswamy.cdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.kumaraswamy.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.kumaraswamy.cdf( 0.0, 1.0, NaN )\n    NaN\n\n\nbase.dists.kumaraswamy.cdf.factory( a, b )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Kumaraswamy's double bounded distribution with first shape parameter\n    `a` and second shape parameter `b`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.kumaraswamy.cdf.factory( 0.5, 1.0 );\n    > var y = mycdf( 0.8 )\n    ~0.894\n    > y = mycdf( 0.3 )\n    ~0.548\n\n","base.dists.kumaraswamy.cdf.factory":"\nbase.dists.kumaraswamy.cdf.factory( a, b )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Kumaraswamy's double bounded distribution with first shape parameter\n    `a` and second shape parameter `b`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.kumaraswamy.cdf.factory( 0.5, 1.0 );\n    > var y = mycdf( 0.8 )\n    ~0.894\n    > y = mycdf( 0.3 )\n    ~0.548","base.dists.kumaraswamy.Kumaraswamy":"\nbase.dists.kumaraswamy.Kumaraswamy( [a, b] )\n    Returns a Kumaraswamy's double bounded distribution object.\n\n    Parameters\n    ----------\n    a: number (optional)\n        First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n    b: number (optional)\n        Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    kumaraswamy: Object\n        Distribution instance.\n\n    kumaraswamy.a: number\n        First shape parameter. If set, the value must be greater than `0`.\n\n    kumaraswamy.b: number\n        Second shape parameter. If set, the value must be greater than `0`.\n\n    kumaraswamy.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    kumaraswamy.mean: number\n        Read-only property which returns the expected value.\n\n    kumaraswamy.mode: number\n        Read-only property which returns the mode.\n\n    kumaraswamy.skewness: number\n        Read-only property which returns the skewness.\n\n    kumaraswamy.stdev: number\n        Read-only property which returns the standard deviation.\n\n    kumaraswamy.variance: number\n        Read-only property which returns the variance.\n\n    kumaraswamy.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    kumaraswamy.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    kumaraswamy.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var kumaraswamy = base.dists.kumaraswamy.Kumaraswamy( 6.0, 5.0 );\n    > kumaraswamy.a\n    6.0\n    > kumaraswamy.b\n    5.0\n    > kumaraswamy.kurtosis\n    ~3.194\n    > kumaraswamy.mean\n    ~0.696\n    > kumaraswamy.mode\n    ~0.746\n    > kumaraswamy.skewness\n    ~-0.605\n    > kumaraswamy.stdev\n    ~0.126\n    > kumaraswamy.variance\n    ~0.016\n    > kumaraswamy.cdf( 0.8 )\n    ~0.781\n    > kumaraswamy.pdf( 1.0 )\n    ~0.0\n    > kumaraswamy.quantile( 0.8 )\n    ~0.807\n\n","base.dists.kumaraswamy.kurtosis":"\nbase.dists.kumaraswamy.kurtosis( a, b )\n    Returns the excess kurtosis of a Kumaraswamy's double bounded distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.kumaraswamy.kurtosis( 1.0, 1.0 )\n    ~1.8\n    > v = base.dists.kumaraswamy.kurtosis( 4.0, 12.0 )\n    ~2.704\n    > v = base.dists.kumaraswamy.kurtosis( 16.0, 8.0 )\n    ~4.311\n\n","base.dists.kumaraswamy.logcdf":"\nbase.dists.kumaraswamy.logcdf( x, a, b )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for Kumaraswamy's double bounded distribution with first shape\n    parameter `a` and second shape parameter `b` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.kumaraswamy.logcdf( 0.5, 1.0, 1.0 )\n    ~-0.693\n    > y = base.dists.kumaraswamy.logcdf( 0.5, 2.0, 4.0 )\n    ~-0.38\n    > y = base.dists.kumaraswamy.logcdf( 0.2, 2.0, 2.0 )\n    ~-2.546\n    > y = base.dists.kumaraswamy.logcdf( 0.8, 4.0, 4.0 )\n    ~-0.13\n    > y = base.dists.kumaraswamy.logcdf( -0.5, 4.0, 2.0 )\n    -Infinity\n    > y = base.dists.kumaraswamy.logcdf( 1.5, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.kumaraswamy.logcdf( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.kumaraswamy.logcdf( 2.0, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.kumaraswamy.logcdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.kumaraswamy.logcdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.kumaraswamy.logcdf( 0.0, 1.0, NaN )\n    NaN\n\n\nbase.dists.kumaraswamy.logcdf.factory( a, b )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Kumaraswamy's double bounded distribution\n    with first shape parameter `a` and second shape parameter `b`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.kumaraswamy.logcdf.factory( 0.5, 1.0 );\n    > var y = mylogcdf( 0.8 )\n    ~-0.112\n    > y = mylogcdf( 0.3 )\n    ~-0.602\n\n","base.dists.kumaraswamy.logcdf.factory":"\nbase.dists.kumaraswamy.logcdf.factory( a, b )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Kumaraswamy's double bounded distribution\n    with first shape parameter `a` and second shape parameter `b`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.kumaraswamy.logcdf.factory( 0.5, 1.0 );\n    > var y = mylogcdf( 0.8 )\n    ~-0.112\n    > y = mylogcdf( 0.3 )\n    ~-0.602","base.dists.kumaraswamy.logpdf":"\nbase.dists.kumaraswamy.logpdf( x, a, b )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for Kumaraswamy's double bounded distribution with first shape parameter `a`\n    and second shape parameter `b` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.kumaraswamy.logpdf( 0.5, 1.0, 1.0 )\n    0.0\n    > y = base.dists.kumaraswamy.logpdf( 0.5, 2.0, 4.0 )\n    ~0.523\n    > y = base.dists.kumaraswamy.logpdf( 0.2, 2.0, 2.0 )\n    ~-0.264\n    > y = base.dists.kumaraswamy.logpdf( 0.8, 4.0, 4.0 )\n    ~0.522\n    > y = base.dists.kumaraswamy.logpdf( -0.5, 4.0, 2.0 )\n    -Infinity\n    > y = base.dists.kumaraswamy.logpdf( 1.5, 4.0, 2.0 )\n    -Infinity\n\n    > y = base.dists.kumaraswamy.logpdf( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.kumaraswamy.logpdf( 2.0, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.kumaraswamy.logpdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.kumaraswamy.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.kumaraswamy.logpdf( 0.0, 1.0, NaN )\n    NaN\n\n\nbase.dists.kumaraswamy.logpdf.factory( a, b )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a Kumaraswamy's double bounded distribution with\n    first shape parameter `a` and second shape parameter `b`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.kumaraswamy.logpdf.factory( 0.5, 1.0 );\n    > var y = mylogpdf( 0.8 )\n    ~-0.582\n    > y = mylogpdf( 0.3 )\n    ~-0.091\n\n","base.dists.kumaraswamy.logpdf.factory":"\nbase.dists.kumaraswamy.logpdf.factory( a, b )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a Kumaraswamy's double bounded distribution with\n    first shape parameter `a` and second shape parameter `b`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.kumaraswamy.logpdf.factory( 0.5, 1.0 );\n    > var y = mylogpdf( 0.8 )\n    ~-0.582\n    > y = mylogpdf( 0.3 )\n    ~-0.091","base.dists.kumaraswamy.mean":"\nbase.dists.kumaraswamy.mean( a, b )\n    Returns the mean of a Kumaraswamy's double bounded distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Mean.\n\n    Examples\n    --------\n    > var v = base.dists.kumaraswamy.mean( 1.5, 1.5 )\n    ~0.512\n    > v = base.dists.kumaraswamy.mean( 4.0, 12.0 )\n    ~0.481\n    > v = base.dists.kumaraswamy.mean( 16.0, 8.0 )\n    ~0.846\n\n","base.dists.kumaraswamy.median":"\nbase.dists.kumaraswamy.median( a, b )\n    Returns the median of a Kumaraswamy's double bounded distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.kumaraswamy.median( 1.0, 1.0 )\n    0.5\n    > v = base.dists.kumaraswamy.median( 4.0, 12.0 )\n    ~0.487\n    > v = base.dists.kumaraswamy.median( 16.0, 8.0 )\n    ~0.856\n\n","base.dists.kumaraswamy.mode":"\nbase.dists.kumaraswamy.mode( a, b )\n    Returns the mode of a Kumaraswamy's double bounded distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a < 1`, `b < 1`, or `a = b = 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.kumaraswamy.mode( 1.5, 1.5 )\n    ~0.543\n    > v = base.dists.kumaraswamy.mode( 4.0, 12.0 )\n    ~0.503\n    > v = base.dists.kumaraswamy.mode( 16.0, 8.0 )\n    ~0.875\n\n","base.dists.kumaraswamy.pdf":"\nbase.dists.kumaraswamy.pdf( x, a, b )\n    Evaluates the probability density function (PDF) for Kumaraswamy's double\n    bounded distribution with first shape parameter `a` and second shape\n    parameter `b` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.kumaraswamy.pdf( 0.5, 1.0, 1.0 )\n    1.0\n    > y = base.dists.kumaraswamy.pdf( 0.5, 2.0, 4.0 )\n    ~1.688\n    > y = base.dists.kumaraswamy.pdf( 0.2, 2.0, 2.0 )\n    ~0.768\n    > y = base.dists.kumaraswamy.pdf( 0.8, 4.0, 4.0 )\n    ~1.686\n    > y = base.dists.kumaraswamy.pdf( -0.5, 4.0, 2.0 )\n    0.0\n    > y = base.dists.kumaraswamy.pdf( 1.5, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.kumaraswamy.pdf( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.kumaraswamy.pdf( 2.0, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.kumaraswamy.pdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.kumaraswamy.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.kumaraswamy.pdf( 0.0, 1.0, NaN )\n    NaN\n\n\nbase.dists.kumaraswamy.pdf.factory( a, b )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Kumaraswamy's double bounded distribution with first shape parameter\n    `a` and second shape parameter `b`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var mypdf = base.dists.kumaraswamy.pdf.factory( 0.5, 1.0 );\n    > var y = mypdf( 0.8 )\n    ~0.559\n    > y = mypdf( 0.3 )\n    ~0.913\n\n","base.dists.kumaraswamy.pdf.factory":"\nbase.dists.kumaraswamy.pdf.factory( a, b )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Kumaraswamy's double bounded distribution with first shape parameter\n    `a` and second shape parameter `b`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var mypdf = base.dists.kumaraswamy.pdf.factory( 0.5, 1.0 );\n    > var y = mypdf( 0.8 )\n    ~0.559\n    > y = mypdf( 0.3 )\n    ~0.913","base.dists.kumaraswamy.quantile":"\nbase.dists.kumaraswamy.quantile( p, a, b )\n    Evaluates the quantile function for a Kumaraswamy's double bounded\n    distribution with first shape parameter `a` and second shape parameter `b`\n    at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.kumaraswamy.quantile( 0.5, 1.0, 1.0 )\n    0.5\n    > y = base.dists.kumaraswamy.quantile( 0.5, 2.0, 4.0 )\n    ~0.399\n    > y = base.dists.kumaraswamy.quantile( 0.2, 2.0, 2.0 )\n    ~0.325\n    > y = base.dists.kumaraswamy.quantile( 0.8, 4.0, 4.0 )\n    ~0.759\n\n    > y = base.dists.kumaraswamy.quantile( -0.5, 4.0, 2.0 )\n    NaN\n    > y = base.dists.kumaraswamy.quantile( 1.5, 4.0, 2.0 )\n    NaN\n\n    > y = base.dists.kumaraswamy.quantile( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.kumaraswamy.quantile( 2.0, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.kumaraswamy.quantile( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.kumaraswamy.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.kumaraswamy.quantile( 0.0, 1.0, NaN )\n    NaN\n\n\nbase.dists.kumaraswamy.quantile.factory( a, b )\n    Returns a function for evaluating the quantile function of a Kumaraswamy's\n    double bounded distribution with first shape parameter `a` and second shape\n    parameter `b`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.kumaraswamy.quantile.factory( 0.5, 1.0 );\n    > var y = myQuantile( 0.8 )\n    ~0.64\n    > y = myQuantile( 0.3 )\n    ~0.09\n\n","base.dists.kumaraswamy.quantile.factory":"\nbase.dists.kumaraswamy.quantile.factory( a, b )\n    Returns a function for evaluating the quantile function of a Kumaraswamy's\n    double bounded distribution with first shape parameter `a` and second shape\n    parameter `b`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.kumaraswamy.quantile.factory( 0.5, 1.0 );\n    > var y = myQuantile( 0.8 )\n    ~0.64\n    > y = myQuantile( 0.3 )\n    ~0.09","base.dists.kumaraswamy.skewness":"\nbase.dists.kumaraswamy.skewness( a, b )\n    Returns the skewness of a Kumaraswamy's double bounded distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.kumaraswamy.skewness( 1.0, 1.0 )\n    ~1.154e-15\n    > v = base.dists.kumaraswamy.skewness( 4.0, 12.0 )\n    ~-0.201\n    > v = base.dists.kumaraswamy.skewness( 16.0, 8.0 )\n    ~-0.94\n\n","base.dists.kumaraswamy.stdev":"\nbase.dists.kumaraswamy.stdev( a, b )\n    Returns the standard deviation of a Kumaraswamy's double bounded\n    distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.kumaraswamy.stdev( 1.0, 1.0 )\n    ~0.289\n    > v = base.dists.kumaraswamy.stdev( 4.0, 12.0 )\n    ~0.13\n    > v = base.dists.kumaraswamy.stdev( 16.0, 8.0 )\n    ~0.062\n\n","base.dists.kumaraswamy.variance":"\nbase.dists.kumaraswamy.variance( a, b )\n    Returns the variance of a Kumaraswamy's double bounded distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.kumaraswamy.variance( 1.0, 1.0 )\n    ~0.083\n    > v = base.dists.kumaraswamy.variance( 4.0, 12.0 )\n    ~0.017\n    > v = base.dists.kumaraswamy.variance( 16.0, 8.0 )\n    ~0.004\n\n","base.dists.laplace.cdf":"\nbase.dists.laplace.cdf( x, μ, b )\n    Evaluates the cumulative distribution function (CDF) for a Laplace\n    distribution with scale parameter `b` and location parameter `μ` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.cdf( 2.0, 0.0, 1.0 )\n    ~0.932\n    > y = base.dists.laplace.cdf( 5.0, 10.0, 3.0 )\n    ~0.094\n    > y = base.dists.laplace.cdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.laplace.cdf( 2, NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.cdf( 2.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.laplace.cdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.laplace.cdf.factory( μ, b )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Laplace distribution with scale parameter `b` and location parameter\n    `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.laplace.cdf.factory( 2.0, 3.0 );\n    > var y = myCDF( 10.0 )\n    ~0.965\n    > y = myCDF( 2.0 )\n    0.5\n\n","base.dists.laplace.cdf.factory":"\nbase.dists.laplace.cdf.factory( μ, b )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Laplace distribution with scale parameter `b` and location parameter\n    `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.laplace.cdf.factory( 2.0, 3.0 );\n    > var y = myCDF( 10.0 )\n    ~0.965\n    > y = myCDF( 2.0 )\n    0.5","base.dists.laplace.entropy":"\nbase.dists.laplace.entropy( μ, b )\n    Returns the differential entropy of a Laplace distribution with location\n    parameter `μ` and scale parameter `b`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Differential entropy.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.entropy( 0.0, 1.0 )\n    ~1.693\n    > y = base.dists.laplace.entropy( 4.0, 2.0 )\n    ~2.386\n    > y = base.dists.laplace.entropy( NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.entropy( 0.0, NaN )\n    NaN\n    > y = base.dists.laplace.entropy( 0.0, 0.0 )\n    NaN\n\n","base.dists.laplace.kurtosis":"\nbase.dists.laplace.kurtosis( μ, b )\n    Returns the excess kurtosis of a Laplace distribution with location\n    parameter `μ` and scale parameter `b`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.kurtosis( 0.0, 1.0 )\n    3.0\n    > y = base.dists.laplace.kurtosis( 4.0, 2.0 )\n    3.0\n    > y = base.dists.laplace.kurtosis( NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.kurtosis( 0.0, NaN )\n    NaN\n    > y = base.dists.laplace.kurtosis( 0.0, 0.0 )\n    NaN\n\n","base.dists.laplace.Laplace":"\nbase.dists.laplace.Laplace( [μ, b] )\n    Returns a Laplace distribution object.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter. Default: `0.0`.\n\n    b: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    laplace: Object\n        Distribution instance.\n\n    laplace.mu: number\n        Location parameter.\n\n    laplace.b: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    laplace.entropy: number\n        Read-only property which returns the differential entropy.\n\n    laplace.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    laplace.mean: number\n        Read-only property which returns the expected value.\n\n    laplace.median: number\n        Read-only property which returns the median.\n\n    laplace.mode: number\n        Read-only property which returns the mode.\n\n    laplace.skewness: number\n        Read-only property which returns the skewness.\n\n    laplace.stdev: number\n        Read-only property which returns the standard deviation.\n\n    laplace.variance: number\n        Read-only property which returns the variance.\n\n    laplace.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    laplace.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    laplace.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    laplace.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    laplace.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    laplace.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var laplace = base.dists.laplace.Laplace( -2.0, 3.0 );\n    > laplace.mu\n    -2.0\n    > laplace.b\n    3.0\n    > laplace.entropy\n    ~2.792\n    > laplace.kurtosis\n    3.0\n    > laplace.mean\n    -2.0\n    > laplace.median\n    -2.0\n    > laplace.mode\n    -2.0\n    > laplace.skewness\n    0.0\n    > laplace.stdev\n    ~4.243\n    > laplace.variance\n    18.0\n    > laplace.cdf( 0.8 )\n    ~0.803\n    > laplace.logcdf( 0.8 )\n    ~-0.219\n    > laplace.logpdf( 1.0 )\n    ~-2.792\n    > laplace.mgf( 0.2 )\n    ~1.047\n    > laplace.pdf( 2.0 )\n    ~0.044\n    > laplace.quantile( 0.9 )\n    ~2.828\n\n","base.dists.laplace.logcdf":"\nbase.dists.laplace.logcdf( x, μ, b )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    Laplace distribution with scale parameter `b` and location parameter `μ` at\n    a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.logcdf( 2.0, 0.0, 1.0 )\n    ~-0.07\n    > y = base.dists.laplace.logcdf( 5.0, 10.0, 3.0 )\n    ~-2.36\n    > y = base.dists.laplace.logcdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.laplace.logcdf( 2, NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.logcdf( 2.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.laplace.logcdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.laplace.logcdf.factory( μ, b )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Laplace distribution with scale parameter\n    `b` and location parameter `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.laplace.logcdf.factory( 2.0, 3.0 );\n    > var y = mylogcdf( 10.0 )\n    ~-0.035\n    > y = mylogcdf( 2.0 )\n    ~-0.693\n\n","base.dists.laplace.logcdf.factory":"\nbase.dists.laplace.logcdf.factory( μ, b )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Laplace distribution with scale parameter\n    `b` and location parameter `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.laplace.logcdf.factory( 2.0, 3.0 );\n    > var y = mylogcdf( 10.0 )\n    ~-0.035\n    > y = mylogcdf( 2.0 )\n    ~-0.693","base.dists.laplace.logpdf":"\nbase.dists.laplace.logpdf( x, μ, b )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    Laplace distribution with scale parameter `b` and location parameter `μ` at\n    a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.logpdf( 2.0, 0.0, 1.0 )\n    ~-2.693\n    > y = base.dists.laplace.logpdf( -1.0, 2.0, 3.0 )\n    ~-2.792\n    > y = base.dists.laplace.logpdf( 2.5, 2.0, 3.0 )\n    ~-1.958\n    > y = base.dists.laplace.logpdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.laplace.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.logpdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.laplace.logpdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.laplace.logpdf.factory( μ, b )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Laplace distribution with scale parameter `b` and\n    location parameter `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.laplace.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogPDF( 10.0 )\n    ~-1.386\n\n","base.dists.laplace.logpdf.factory":"\nbase.dists.laplace.logpdf.factory( μ, b )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Laplace distribution with scale parameter `b` and\n    location parameter `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.laplace.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogPDF( 10.0 )\n    ~-1.386","base.dists.laplace.mean":"\nbase.dists.laplace.mean( μ, b )\n    Returns the expected value of a Laplace distribution with location parameter\n    `μ` and scale parameter `b`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.mean( 0.0, 1.0 )\n    0.0\n    > y = base.dists.laplace.mean( 4.0, 2.0 )\n    4.0\n    > y = base.dists.laplace.mean( NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.mean( 0.0, NaN )\n    NaN\n    > y = base.dists.laplace.mean( 0.0, 0.0 )\n    NaN\n\n","base.dists.laplace.median":"\nbase.dists.laplace.median( μ, b )\n    Returns the median of a Laplace distribution with location parameter `μ` and\n    scale parameter `b`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.median( 0.0, 1.0 )\n    0.0\n    > y = base.dists.laplace.median( 4.0, 2.0 )\n    4.0\n    > y = base.dists.laplace.median( NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.median( 0.0, NaN )\n    NaN\n    > y = base.dists.laplace.median( 0.0, 0.0 )\n    NaN\n\n","base.dists.laplace.mgf":"\nbase.dists.laplace.mgf( t, μ, b )\n    Evaluates the moment-generating function (MGF) for a Laplace\n    distribution with scale parameter `b` and location parameter `μ` at a\n    value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.mgf( 0.5, 0.0, 1.0 )\n    ~1.333\n    > y = base.dists.laplace.mgf( 0.0, 0.0, 1.0 )\n    1.0\n    > y = base.dists.laplace.mgf( -1.0, 4.0, 0.2 )\n    ~0.019\n    > y = base.dists.laplace.mgf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.laplace.mgf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.mgf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.laplace.mgf( 1.0, 0.0, 2.0 )\n    NaN\n    > y = base.dists.laplace.mgf( -0.5, 0.0, 4.0 )\n    NaN\n    > y = base.dists.laplace.mgf( 2.0, 0.0, 0.0 )\n    NaN\n    > y = base.dists.laplace.mgf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.laplace.mgf.factory( μ, b )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a Laplace distribution with scale parameter `b` and location parameter\n    `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.laplace.mgf.factory( 4.0, 2.0 );\n    > var y = mymgf( 0.2 )\n    ~2.649\n    > y = mymgf( 0.4 )\n    ~13.758\n\n","base.dists.laplace.mgf.factory":"\nbase.dists.laplace.mgf.factory( μ, b )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a Laplace distribution with scale parameter `b` and location parameter\n    `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.laplace.mgf.factory( 4.0, 2.0 );\n    > var y = mymgf( 0.2 )\n    ~2.649\n    > y = mymgf( 0.4 )\n    ~13.758","base.dists.laplace.mode":"\nbase.dists.laplace.mode( μ, b )\n    Returns the mode of a Laplace distribution with location parameter `μ` and\n    scale parameter `b`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.mode( 0.0, 1.0 )\n    0.0\n    > y = base.dists.laplace.mode( 4.0, 2.0 )\n    4.0\n    > y = base.dists.laplace.mode( NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.mode( 0.0, NaN )\n    NaN\n    > y = base.dists.laplace.mode( 0.0, 0.0 )\n    NaN\n\n","base.dists.laplace.pdf":"\nbase.dists.laplace.pdf( x, μ, b )\n    Evaluates the probability density function (PDF) for a Laplace\n    distribution with scale parameter `b` and location parameter `μ` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.pdf( 2.0, 0.0, 1.0 )\n    ~0.068\n    > y = base.dists.laplace.pdf( -1.0, 2.0, 3.0 )\n    ~0.061\n    > y = base.dists.laplace.pdf( 2.5, 2.0, 3.0 )\n    ~0.141\n    > y = base.dists.laplace.pdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.laplace.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.pdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.laplace.pdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.laplace.pdf.factory( μ, b )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Laplace distribution with scale parameter `b` and location parameter\n    `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.laplace.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    0.25\n\n","base.dists.laplace.pdf.factory":"\nbase.dists.laplace.pdf.factory( μ, b )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Laplace distribution with scale parameter `b` and location parameter\n    `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.laplace.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    0.25","base.dists.laplace.quantile":"\nbase.dists.laplace.quantile( p, μ, b )\n    Evaluates the quantile function for a Laplace distribution with scale\n    parameter `b` and location parameter `μ` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.quantile( 0.8, 0.0, 1.0 )\n    ~0.916\n    > y = base.dists.laplace.quantile( 0.5, 4.0, 2.0 )\n    4.0\n\n    > y = base.dists.laplace.quantile( 1.1, 0.0, 1.0 )\n    NaN\n    > y = base.dists.laplace.quantile( -0.2, 0.0, 1.0 )\n    NaN\n\n    > y = base.dists.laplace.quantile( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.laplace.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.quantile( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.laplace.quantile( 0.5, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.laplace.quantile.factory( μ, b )\n    Returns a function for evaluating the quantile function of a Laplace\n    distribution with scale parameter `b` and location parameter `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.laplace.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    10.0\n    > y = myQuantile( 0.8 )\n    ~11.833\n\n","base.dists.laplace.quantile.factory":"\nbase.dists.laplace.quantile.factory( μ, b )\n    Returns a function for evaluating the quantile function of a Laplace\n    distribution with scale parameter `b` and location parameter `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.laplace.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    10.0\n    > y = myQuantile( 0.8 )\n    ~11.833","base.dists.laplace.skewness":"\nbase.dists.laplace.skewness( μ, b )\n    Returns the skewness of a Laplace distribution with location parameter `μ`\n    and scale parameter `b`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.skewness( 0.0, 1.0 )\n    0.0\n    > y = base.dists.laplace.skewness( 4.0, 2.0 )\n    0.0\n    > y = base.dists.laplace.skewness( NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.skewness( 0.0, NaN )\n    NaN\n    > y = base.dists.laplace.skewness( 0.0, 0.0 )\n    NaN\n\n","base.dists.laplace.stdev":"\nbase.dists.laplace.stdev( μ, b )\n    Returns the standard deviation of a Laplace distribution with location\n    parameter `μ` and scale parameter `b`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.stdev( 0.0, 1.0 )\n    ~1.414\n    > y = base.dists.laplace.stdev( 4.0, 2.0 )\n    ~2.828\n    > y = base.dists.laplace.stdev( NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.stdev( 0.0, NaN )\n    NaN\n    > y = base.dists.laplace.stdev( 0.0, 0.0 )\n    NaN\n\n","base.dists.laplace.variance":"\nbase.dists.laplace.variance( μ, b )\n    Returns the variance of a Laplace distribution with location parameter `μ`\n    and scale parameter `b`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.variance( 0.0, 1.0 )\n    2.0\n    > y = base.dists.laplace.variance( 4.0, 2.0 )\n    8.0\n    > y = base.dists.laplace.variance( NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.variance( 0.0, NaN )\n    NaN\n    > y = base.dists.laplace.variance( 0.0, 0.0 )\n    NaN\n\n","base.dists.levy.cdf":"\nbase.dists.levy.cdf( x, μ, c )\n    Evaluates the cumulative distribution function (CDF) for a Lévy distribution\n    with location parameter `μ` and scale parameter `c` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.levy.cdf( 2.0, 0.0, 1.0 )\n    ~0.48\n    > y = base.dists.levy.cdf( 12.0, 10.0, 3.0 )\n    ~0.221\n    > y = base.dists.levy.cdf( 9.0, 10.0, 3.0 )\n    0.0\n    > y = base.dists.levy.cdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.levy.cdf( 2, NaN, 1.0 )\n    NaN\n    > y = base.dists.levy.cdf( 2.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.levy.cdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.levy.cdf.factory( μ, c )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.levy.cdf.factory( 2.0, 3.0 );\n    > var y = myCDF( 10.0 )\n    ~0.54\n    > y = myCDF( 2.0 )\n    0.0\n\n","base.dists.levy.cdf.factory":"\nbase.dists.levy.cdf.factory( μ, c )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.levy.cdf.factory( 2.0, 3.0 );\n    > var y = myCDF( 10.0 )\n    ~0.54\n    > y = myCDF( 2.0 )\n    0.0","base.dists.levy.entropy":"\nbase.dists.levy.entropy( μ, c )\n    Returns the entropy of a Lévy distribution with location parameter `μ` and\n    scale parameter `c`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var y = base.dists.levy.entropy( 0.0, 1.0 )\n    ~3.324\n    > y = base.dists.levy.entropy( 4.0, 2.0 )\n    ~4.018\n    > y = base.dists.levy.entropy( NaN, 1.0 )\n    NaN\n    > y = base.dists.levy.entropy( 0.0, NaN )\n    NaN\n    > y = base.dists.levy.entropy( 0.0, 0.0 )\n    NaN\n\n","base.dists.levy.Levy":"\nbase.dists.levy.Levy( [μ, c] )\n    Returns a Lévy distribution object.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter. Default: `0.0`.\n\n    c: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    levy: Object\n        Distribution instance.\n\n    levy.mu: number\n        Location parameter.\n\n    levy.c: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    levy.entropy: number\n        Read-only property which returns the differential entropy.\n\n    levy.mean: number\n        Read-only property which returns the expected value.\n\n    levy.median: number\n        Read-only property which returns the median.\n\n    levy.mode: number\n        Read-only property which returns the mode.\n\n    levy.stdev: number\n        Read-only property which returns the standard deviation.\n\n    levy.variance: number\n        Read-only property which returns the variance.\n\n    levy.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    levy.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    levy.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    levy.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    levy.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var levy = base.dists.levy.Levy( -2.0, 3.0 );\n    > levy.mu\n    -2.0\n    > levy.c\n    3.0\n    > levy.entropy\n    ~4.423\n    > levy.mean\n    Infinity\n    > levy.median\n    ~4.594\n    > levy.mode\n    -1.0\n    > levy.stdev\n    Infinity\n    > levy.variance\n    Infinity\n    > levy.cdf( 0.8 )\n    ~0.3\n    > levy.logcdf( 0.8 )\n    ~-1.2\n    > levy.logpdf( 1.0 )\n    ~-2.518\n    > levy.pdf( 1.0 )\n    ~0.081\n    > levy.quantile( 0.8 )\n    ~44.74\n\n","base.dists.levy.logcdf":"\nbase.dists.levy.logcdf( x, μ, c )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    Lévy distribution with location parameter `μ` and scale parameter `c` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.levy.logcdf( 2.0, 0.0, 1.0 )\n    ~-0.735\n    > y = base.dists.levy.logcdf( 12.0, 10.0, 3.0 )\n    ~-1.51\n    > y = base.dists.levy.logcdf( 9.0, 10.0, 3.0 )\n    -Infinity\n    > y = base.dists.levy.logcdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.levy.logcdf( 2, NaN, 1.0 )\n    NaN\n    > y = base.dists.levy.logcdf( 2.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.levy.logcdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.levy.logcdf.factory( μ, c )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Lévy distribution with location parameter\n    `μ` and scale parameter `c`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.levy.logcdf.factory( 2.0, 3.0 );\n    > var y = mylogcdf( 10.0 )\n    ~-0.616\n    > y = mylogcdf( 2.0 )\n    -Infinity\n\n","base.dists.levy.logcdf.factory":"\nbase.dists.levy.logcdf.factory( μ, c )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Lévy distribution with location parameter\n    `μ` and scale parameter `c`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.levy.logcdf.factory( 2.0, 3.0 );\n    > var y = mylogcdf( 10.0 )\n    ~-0.616\n    > y = mylogcdf( 2.0 )\n    -Infinity","base.dists.levy.logpdf":"\nbase.dists.levy.logpdf( x, μ, c )\n    Evaluates the logarithm of the probability density function (PDF) for a Lévy\n    distribution with location parameter `μ` and scale parameter `c` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.levy.logpdf( 2.0, 0.0, 1.0 )\n    ~-2.209\n    > y = base.dists.levy.logpdf( -1.0, 4.0, 2.0 )\n    -Infinity\n    > y = base.dists.levy.logpdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.levy.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.levy.logpdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.levy.logpdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.levy.logpdf.factory( μ, c )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Lévy distribution with location parameter `μ` and scale\n    parameter `c`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.levy.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogPDF( 11.0 )\n    ~-1.572\n\n","base.dists.levy.logpdf.factory":"\nbase.dists.levy.logpdf.factory( μ, c )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Lévy distribution with location parameter `μ` and scale\n    parameter `c`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.levy.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogPDF( 11.0 )\n    ~-1.572","base.dists.levy.mean":"\nbase.dists.levy.mean( μ, c )\n    Returns the expected value of a Lévy distribution with location parameter\n    `μ` and scale parameter `c`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var y = base.dists.levy.mean( 0.0, 1.0 )\n    Infinity\n    > y = base.dists.levy.mean( 4.0, 3.0 )\n    Infinity\n    > y = base.dists.levy.mean( NaN, 1.0 )\n    NaN\n    > y = base.dists.levy.mean( 0.0, NaN )\n    NaN\n    > y = base.dists.levy.mean( 0.0, 0.0 )\n    NaN\n\n","base.dists.levy.median":"\nbase.dists.levy.median( μ, c )\n    Returns the median of a Lévy distribution with location parameter `μ` and\n    scale parameter `c`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var y = base.dists.levy.median( 0.0, 1.0 )\n    ~2.198\n    > y = base.dists.levy.median( 4.0, 3.0 )\n    ~10.594\n    > y = base.dists.levy.median( NaN, 1.0 )\n    NaN\n    > y = base.dists.levy.median( 0.0, NaN )\n    NaN\n    > y = base.dists.levy.median( 0.0, 0.0 )\n    NaN\n\n","base.dists.levy.mode":"\nbase.dists.levy.mode( μ, c )\n    Returns the mode of a Lévy distribution with location parameter `μ` and\n    scale parameter `c`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var y = base.dists.levy.mode( 0.0, 1.0 )\n    ~0.333\n    > y = base.dists.levy.mode( 4.0, 3.0 )\n    5.0\n    > y = base.dists.levy.mode( NaN, 1.0 )\n    NaN\n    > y = base.dists.levy.mode( 0.0, NaN )\n    NaN\n    > y = base.dists.levy.mode( 0.0, 0.0 )\n    NaN\n\n","base.dists.levy.pdf":"\nbase.dists.levy.pdf( x, μ, c )\n    Evaluates the probability density function (PDF) for a Lévy distribution\n    with location parameter `μ` and scale parameter `c` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.levy.pdf( 2.0, 0.0, 1.0 )\n    ~0.11\n    > y = base.dists.levy.pdf( -1.0, 4.0, 2.0 )\n    0.0\n    > y = base.dists.levy.pdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.levy.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.levy.pdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.levy.pdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.levy.pdf.factory( μ, c )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.levy.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 11.0 )\n    ~0.208\n\n","base.dists.levy.pdf.factory":"\nbase.dists.levy.pdf.factory( μ, c )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.levy.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 11.0 )\n    ~0.208","base.dists.levy.quantile":"\nbase.dists.levy.quantile( p, μ, c )\n    Evaluates the quantile function for a Lévy distribution with location\n    parameter `μ` and scale parameter `c` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.levy.quantile( 0.8, 0.0, 1.0 )\n    ~15.58\n    > y = base.dists.levy.quantile( 0.5, 4.0, 2.0 )\n    ~8.396\n\n    > y = base.dists.levy.quantile( 1.1, 0.0, 1.0 )\n    NaN\n    > y = base.dists.levy.quantile( -0.2, 0.0, 1.0 )\n    NaN\n\n    > y = base.dists.levy.quantile( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.levy.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.levy.quantile( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.levy.quantile( 0.5, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.levy.quantile.factory( μ, c )\n    Returns a function for evaluating the quantile function of a Lévy\n    distribution with location parameter `μ` and scale parameter `c`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.levy.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    ~14.396\n\n","base.dists.levy.quantile.factory":"\nbase.dists.levy.quantile.factory( μ, c )\n    Returns a function for evaluating the quantile function of a Lévy\n    distribution with location parameter `μ` and scale parameter `c`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.levy.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    ~14.396","base.dists.levy.stdev":"\nbase.dists.levy.stdev( μ, c )\n    Returns the standard deviation of a Lévy distribution with location\n    parameter `μ` and scale parameter `c`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var y = base.dists.levy.stdev( 0.0, 1.0 )\n    Infinity\n    > y = base.dists.levy.stdev( 4.0, 3.0 )\n    Infinity\n    > y = base.dists.levy.stdev( NaN, 1.0 )\n    NaN\n    > y = base.dists.levy.stdev( 0.0, NaN )\n    NaN\n    > y = base.dists.levy.stdev( 0.0, 0.0 )\n    NaN\n\n","base.dists.levy.variance":"\nbase.dists.levy.variance( μ, c )\n    Returns the variance of a Lévy distribution with location parameter `μ` and\n    scale parameter `c`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var y = base.dists.levy.variance( 0.0, 1.0 )\n    Infinity\n    > y = base.dists.levy.variance( 4.0, 3.0 )\n    Infinity\n    > y = base.dists.levy.variance( NaN, 1.0 )\n    NaN\n    > y = base.dists.levy.variance( 0.0, NaN )\n    NaN\n    > y = base.dists.levy.variance( 0.0, 0.0 )\n    NaN\n\n","base.dists.logistic.cdf":"\nbase.dists.logistic.cdf( x, μ, s )\n    Evaluates the cumulative distribution function (CDF) for a logistic\n    distribution with location parameter `μ` and scale parameter `s` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.cdf( 2.0, 0.0, 1.0 )\n    ~0.881\n    > y = base.dists.logistic.cdf( 5.0, 10.0, 3.0 )\n    ~0.159\n\n    > y = base.dists.logistic.cdf( 2.0, 0.0, NaN )\n    NaN\n    > y = base.dists.logistic.cdf( 2.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.cdf( NaN, 0.0, 1.0 )\n    NaN\n\n    // Degenerate distribution centered at `μ` when `s = 0.0`:\n    > y = base.dists.logistic.cdf( 2.0, 8.0, 0.0 )\n    0.0\n    > y = base.dists.logistic.cdf( 8.0, 8.0, 0.0 )\n    1.0\n    > y = base.dists.logistic.cdf( 10.0, 8.0, 0.0 )\n    1.0\n\n\nbase.dists.logistic.cdf.factory( μ, s )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a logistic distribution with location parameter `μ` and scale parameter\n    `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.logistic.cdf.factory( 3.0, 1.5 );\n    > var y = mycdf( 1.0 )\n    ~0.209\n\n","base.dists.logistic.cdf.factory":"\nbase.dists.logistic.cdf.factory( μ, s )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a logistic distribution with location parameter `μ` and scale parameter\n    `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.logistic.cdf.factory( 3.0, 1.5 );\n    > var y = mycdf( 1.0 )\n    ~0.209","base.dists.logistic.entropy":"\nbase.dists.logistic.entropy( μ, s )\n    Returns the entropy of a logistic distribution with location parameter `μ`\n    and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.entropy( 0.0, 1.0 )\n    2.0\n    > y = base.dists.logistic.entropy( 4.0, 2.0 )\n    ~2.693\n    > y = base.dists.logistic.entropy( NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.entropy( 0.0, NaN )\n    NaN\n    > y = base.dists.logistic.entropy( 0.0, 0.0 )\n    NaN\n\n","base.dists.logistic.kurtosis":"\nbase.dists.logistic.kurtosis( μ, s )\n    Returns the excess kurtosis of a logistic distribution with location\n    parameter `μ` and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.kurtosis( 0.0, 1.0 )\n    1.2\n    > y = base.dists.logistic.kurtosis( 4.0, 2.0 )\n    1.2\n    > y = base.dists.logistic.kurtosis( NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.kurtosis( 0.0, NaN )\n    NaN\n    > y = base.dists.logistic.kurtosis( 0.0, 0.0 )\n    NaN\n\n\n","base.dists.logistic.logcdf":"\nbase.dists.logistic.logcdf( x, μ, s )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    logistic distribution with location parameter `μ` and scale parameter `s` at\n    a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.logcdf( 2.0, 0.0, 1.0 )\n    ~-0.127\n    > y = base.dists.logistic.logcdf( 5.0, 10.0, 3.0 )\n    ~-1.84\n    > y = base.dists.logistic.logcdf( 2.0, 0.0, NaN )\n    NaN\n    > y = base.dists.logistic.logcdf( 2, NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.logcdf( NaN, 0.0, 1.0 )\n    NaN\n\n\nbase.dists.logistic.logcdf.factory( μ, s )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Logistic distribution with location\n    parameter `μ` and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.logistic.logcdf.factory( 3.0, 1.5 );\n    > var y = mylogcdf( 1.0 )\n    ~-1.567\n\n","base.dists.logistic.logcdf.factory":"\nbase.dists.logistic.logcdf.factory( μ, s )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Logistic distribution with location\n    parameter `μ` and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.logistic.logcdf.factory( 3.0, 1.5 );\n    > var y = mylogcdf( 1.0 )\n    ~-1.567","base.dists.logistic.Logistic":"\nbase.dists.logistic.Logistic( [μ, s] )\n    Returns a logistic distribution object.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter. Default: `0.0`.\n\n    s: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    logistic: Object\n        Distribution instance.\n\n    logistic.mu: number\n        Location parameter.\n\n    logistic.s: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    logistic.entropy: number\n        Read-only property which returns the differential entropy.\n\n    logistic.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    logistic.mean: number\n        Read-only property which returns the expected value.\n\n    logistic.median: number\n        Read-only property which returns the median.\n\n    logistic.mode: number\n        Read-only property which returns the mode.\n\n    logistic.skewness: number\n        Read-only property which returns the skewness.\n\n    logistic.stdev: number\n        Read-only property which returns the standard deviation.\n\n    logistic.variance: number\n        Read-only property which returns the variance.\n\n    logistic.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    logistic.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    logistic.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    logistic.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    logistic.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    logistic.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var logistic = base.dists.logistic.Logistic( -2.0, 3.0 );\n    > logistic.mu\n    -2.0\n    > logistic.s\n    3.0\n    > logistic.entropy\n    ~3.1\n    > logistic.kurtosis\n    1.2\n    > logistic.mean\n    -2.0\n    > logistic.median\n    -2.0\n    > logistic.mode\n    -2.0\n    > logistic.skewness\n    0.0\n    > logistic.stdev\n    ~5.441\n    > logistic.variance\n    ~29.609\n    > logistic.cdf( 0.8 )\n    ~0.718\n    > logistic.logcdf( 0.8 )\n    ~-0.332\n    > logistic.logpdf( 2.0 )\n    ~-2.9\n    > logistic.mgf( 0.2 )\n    ~1.329\n    > logistic.pdf( 2.0 )\n    ~0.055\n    > logistic.quantile( 0.9 )\n    ~4.592\n\n","base.dists.logistic.logpdf":"\nbase.dists.logistic.logpdf( x, μ, s )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    logistic distribution with location parameter `μ` and scale parameter `s` at\n    a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.logpdf( 2.0, 0.0, 1.0 )\n    ~-2.254\n    > y = base.dists.logistic.logpdf( -1.0, 4.0, 2.0 )\n    ~-3.351\n    > y = base.dists.logistic.logpdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.logistic.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.logpdf( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.logistic.logpdf( 2.0, 0.0, -1.0 )\n    NaN\n\n    // Degenerate distribution at `s = 0.0`:\n    > y = base.dists.logistic.logpdf( 2.0, 8.0, 0.0 )\n    -Infinity\n    > y = base.dists.logistic.logpdf( 8.0, 8.0, 0.0 )\n    Infinity\n\n\nbase.dists.logistic.logpdf.factory( μ, s )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Logistic distribution with location parameter `μ` and\n    scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.logistic.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogpdf( 10.0 )\n    ~-2.079\n\n","base.dists.logistic.logpdf.factory":"\nbase.dists.logistic.logpdf.factory( μ, s )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Logistic distribution with location parameter `μ` and\n    scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.logistic.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogpdf( 10.0 )\n    ~-2.079","base.dists.logistic.mean":"\nbase.dists.logistic.mean( μ, s )\n    Returns the expected value of a logistic distribution with location\n    parameter `μ` and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.mean( 0.0, 1.0 )\n    0.0\n    > y = base.dists.logistic.mean( 4.0, 2.0 )\n    4.0\n    > y = base.dists.logistic.mean( NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.mean( 0.0, NaN )\n    NaN\n    > y = base.dists.logistic.mean( 0.0, 0.0 )\n    NaN\n\n","base.dists.logistic.median":"\nbase.dists.logistic.median( μ, s )\n    Returns the median of a logistic distribution with location parameter `μ`\n    and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.median( 0.0, 1.0 )\n    0.0\n    > y = base.dists.logistic.median( 4.0, 2.0 )\n    4.0\n    > y = base.dists.logistic.median( NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.median( 0.0, NaN )\n    NaN\n    > y = base.dists.logistic.median( 0.0, 0.0 )\n    NaN\n\n","base.dists.logistic.mgf":"\nbase.dists.logistic.mgf( t, μ, s )\n    Evaluates the moment-generating function (MGF) for a logistic distribution\n    with location parameter `μ` and scale parameter `s` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.mgf( 0.9, 0.0, 1.0 )\n    ~9.15\n    > y = base.dists.logistic.mgf( 0.1, 4.0, 4.0 )\n    ~1.971\n    > y = base.dists.logistic.mgf( -0.2, 4.0, 4.0 )\n    ~1.921\n    > y = base.dists.logistic.mgf( 0.5, 0.0, -1.0 )\n    NaN\n    > y = base.dists.logistic.mgf( 0.5, 0.0, 4.0 )\n    Infinity\n    > y = base.dists.logistic.mgf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.logistic.mgf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.mgf( 0.0, 0.0, NaN )\n    NaN\n\n\nbase.dists.logistic.mgf.factory( μ, s )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a Logistic distribution with location parameter `μ` and scale parameter\n    `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.logistic.mgf.factory( 10.0, 0.5 );\n    > var y = mymgf( 0.5 )\n    ~164.846\n    > y = mymgf( 2.0 )\n    Infinity\n\n","base.dists.logistic.mgf.factory":"\nbase.dists.logistic.mgf.factory( μ, s )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a Logistic distribution with location parameter `μ` and scale parameter\n    `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.logistic.mgf.factory( 10.0, 0.5 );\n    > var y = mymgf( 0.5 )\n    ~164.846\n    > y = mymgf( 2.0 )\n    Infinity","base.dists.logistic.mode":"\nbase.dists.logistic.mode( μ, s )\n    Returns the mode of a logistic distribution with location parameter `μ` and\n    scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.mode( 0.0, 1.0 )\n    0.0\n    > y = base.dists.logistic.mode( 4.0, 2.0 )\n    4.0\n    > y = base.dists.logistic.mode( NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.mode( 0.0, NaN )\n    NaN\n    > y = base.dists.logistic.mode( 0.0, 0.0 )\n    NaN\n\n","base.dists.logistic.pdf":"\nbase.dists.logistic.pdf( x, μ, s )\n    Evaluates the probability density function (PDF) for a logistic distribution\n    with location parameter `μ` and scale parameter `s` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.pdf( 2.0, 0.0, 1.0 )\n    ~0.105\n    > y = base.dists.logistic.pdf( -1.0, 4.0, 2.0 )\n    ~0.035\n    > y = base.dists.logistic.pdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.logistic.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.pdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.logistic.pdf( 2.0, 0.0, -1.0 )\n    NaN\n    > y = base.dists.logistic.pdf( 2.0, 8.0, 0.0 )\n    0.0\n    > y = base.dists.logistic.pdf( 8.0, 8.0, 0.0 )\n    Infinity\n\n\nbase.dists.logistic.pdf.factory( μ, s )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Logistic distribution with location parameter `μ` and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.logistic.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    0.125\n\n","base.dists.logistic.pdf.factory":"\nbase.dists.logistic.pdf.factory( μ, s )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Logistic distribution with location parameter `μ` and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.logistic.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    0.125","base.dists.logistic.quantile":"\nbase.dists.logistic.quantile( p, μ, s )\n    Evaluates the quantile function for a logistic distribution with location\n    parameter `μ` and scale parameter `s` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.quantile( 0.8, 0.0, 1.0 )\n    ~1.386\n    > y = base.dists.logistic.quantile( 0.5, 4.0, 2.0 )\n    4\n\n    > y = base.dists.logistic.quantile( 1.1, 0.0, 1.0 )\n    NaN\n    > y = base.dists.logistic.quantile( -0.2, 0.0, 1.0 )\n    NaN\n\n    > y = base.dists.logistic.quantile( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.logistic.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.quantile( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.logistic.quantile( 0.5, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.logistic.quantile.factory( μ, s )\n    Returns a function for evaluating the quantile function of a logistic\n    distribution with location parameter `μ` and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.logistic.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    10.0\n\n","base.dists.logistic.quantile.factory":"\nbase.dists.logistic.quantile.factory( μ, s )\n    Returns a function for evaluating the quantile function of a logistic\n    distribution with location parameter `μ` and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.logistic.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    10.0","base.dists.logistic.skewness":"\nbase.dists.logistic.skewness( μ, s )\n    Returns the skewness of a logistic distribution with location parameter `μ`\n    and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.skewness( 0.0, 1.0 )\n    0.0\n    > y = base.dists.logistic.skewness( 4.0, 2.0 )\n    0.0\n    > y = base.dists.logistic.skewness( NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.skewness( 0.0, NaN )\n    NaN\n    > y = base.dists.logistic.skewness( 0.0, 0.0 )\n    NaN\n\n","base.dists.logistic.stdev":"\nbase.dists.logistic.stdev( μ, s )\n    Returns the standard deviation of a logistic distribution with location\n    parameter `μ` and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.stdev( 0.0, 1.0 )\n    ~1.814\n    > y = base.dists.logistic.stdev( 4.0, 2.0 )\n    ~3.628\n    > y = base.dists.logistic.stdev( NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.stdev( 0.0, NaN )\n    NaN\n    > y = base.dists.logistic.stdev( 0.0, 0.0 )\n    NaN\n\n","base.dists.logistic.variance":"\nbase.dists.logistic.variance( μ, s )\n    Returns the variance of a logistic distribution with location parameter `μ`\n    and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.variance( 0.0, 1.0 )\n    ~3.29\n    > y = base.dists.logistic.variance( 4.0, 2.0 )\n    ~13.159\n    > y = base.dists.logistic.variance( NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.variance( 0.0, NaN )\n    NaN\n    > y = base.dists.logistic.variance( 0.0, 0.0 )\n    NaN\n\n","base.dists.lognormal.cdf":"\nbase.dists.lognormal.cdf( x, μ, σ )\n    Evaluates the cumulative distribution function (CDF) for a lognormal\n    distribution with location parameter `μ` and scale parameter `σ` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.cdf( 2.0, 0.0, 1.0 )\n    ~0.756\n    > y = base.dists.lognormal.cdf( 5.0, 10.0, 3.0 )\n    ~0.003\n\n    > y = base.dists.lognormal.cdf( 2.0, 0.0, NaN )\n    NaN\n    > y = base.dists.lognormal.cdf( 2.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.cdf( NaN, 0.0, 1.0 )\n    NaN\n\n    // Non-positive scale parameter `σ`:\n    > y = base.dists.lognormal.cdf( 2.0, 0.0, -1.0 )\n    NaN\n    > y = base.dists.lognormal.cdf( 2.0, 0.0, 0.0 )\n    NaN\n\n\nbase.dists.lognormal.cdf.factory( μ, σ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a lognormal distribution with location parameter `μ` and scale parameter\n    `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.lognormal.cdf.factory( 3.0, 1.5 );\n    > var y = myCDF( 1.0 )\n    ~0.023\n    > y = myCDF( 4.0 )\n    ~0.141\n\n","base.dists.lognormal.cdf.factory":"\nbase.dists.lognormal.cdf.factory( μ, σ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a lognormal distribution with location parameter `μ` and scale parameter\n    `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.lognormal.cdf.factory( 3.0, 1.5 );\n    > var y = myCDF( 1.0 )\n    ~0.023\n    > y = myCDF( 4.0 )\n    ~0.141","base.dists.lognormal.entropy":"\nbase.dists.lognormal.entropy( μ, σ )\n    Returns the differential entropy of a lognormal distribution with location\n    `μ` and scale `σ` (in nats).\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.entropy( 0.0, 1.0 )\n    ~1.419\n    > y = base.dists.lognormal.entropy( 5.0, 2.0 )\n    ~7.112\n    > y = base.dists.lognormal.entropy( NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.entropy( 0.0, NaN )\n    NaN\n    > y = base.dists.lognormal.entropy( 0.0, 0.0 )\n    NaN\n\n","base.dists.lognormal.kurtosis":"\nbase.dists.lognormal.kurtosis( μ, σ )\n    Returns the excess kurtosis of a lognormal distribution with location `μ`\n    and scale `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Kurtosis.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.kurtosis( 0.0, 1.0 )\n    ~110.936\n    > y = base.dists.lognormal.kurtosis( 5.0, 2.0 )\n    ~9220556.977\n    > y = base.dists.lognormal.kurtosis( NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.kurtosis( 0.0, NaN )\n    NaN\n    > y = base.dists.lognormal.kurtosis( 0.0, 0.0 )\n    NaN\n\n","base.dists.lognormal.LogNormal":"\nbase.dists.lognormal.LogNormal( [μ, σ] )\n    Returns a lognormal distribution object.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter. Default: `0.0`.\n\n    σ: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    lognormal: Object\n        Distribution instance.\n\n    lognormal.mu: number\n        Location parameter.\n\n    lognormal.sigma: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    lognormal.entropy: number\n        Read-only property which returns the differential entropy.\n\n    lognormal.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    lognormal.mean: number\n        Read-only property which returns the expected value.\n\n    lognormal.median: number\n        Read-only property which returns the median.\n\n    lognormal.mode: number\n        Read-only property which returns the mode.\n\n    lognormal.skewness: number\n        Read-only property which returns the skewness.\n\n    lognormal.stdev: number\n        Read-only property which returns the standard deviation.\n\n    lognormal.variance: number\n        Read-only property which returns the variance.\n\n    lognormal.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    lognormal.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    lognormal.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    lognormal.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    lognormal.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var lognormal = base.dists.lognormal.LogNormal( -2.0, 3.0 );\n    > lognormal.mu\n    -2.0\n    > lognormal.sigma\n    3.0\n    > lognormal.entropy\n    ~0.518\n    > lognormal.kurtosis\n    4312295840576300\n    > lognormal.mean\n    ~12.182\n    > lognormal.median\n    ~0.135\n    > lognormal.mode\n    ~0.0\n    > lognormal.skewness\n    ~729551.383\n    > lognormal.stdev\n    ~1096.565\n    > lognormal.variance\n    ~1202455.871\n    > lognormal.cdf( 0.8 )\n    ~0.723\n    > lognormal.logcdf( 0.8 )\n    ~-4.334\n    > lognormal.logpdf( 2.0 )\n    ~-3.114\n    > lognormal.pdf( 2.0 )\n    ~0.044\n    > lognormal.quantile( 0.9 )\n    ~6.326\n\n","base.dists.lognormal.logcdf":"\nbase.dists.lognormal.logcdf( x, μ, σ )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a lognormal distribution with mean `μ` and standard deviation `σ`\n    at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Evaluated logcdf.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.logcdf( 2.0, 0.0, 1.0 )\n    ~-0.2799\n    > y = base.dists.lognormal.logcdf( 13.0, 4.0, 2.0 )\n    ~-1.442\n    > y = base.dists.lognormal.logcdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.lognormal.logcdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.logcdf( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative standard deviation:\n    > y = base.dists.lognormal.logcdf( 2.0, 0.0, -1.0 )\n    NaN\n\n    // Degenerate distribution centered at `μ` when `σ = 0.0`:\n    > y = base.dists.lognormal.logcdf( 2.0, 8.0, 0.0 )\n    -Infinity\n    > y = base.dists.lognormal.logcdf( 8.0, 8.0, 0.0 )\n    -Infinity\n\n\nbase.dists.lognormal.logcdf.factory( μ, σ )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a lognormal distribution with mean `μ` and\n    standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.lognormal.logcdf.factory( 10.0, 2.0 );\n    > var y = mylogcdf( 10.0 )\n    ~-9.732\n\n","base.dists.lognormal.logcdf.factory":"\nbase.dists.lognormal.logcdf.factory( μ, σ )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a lognormal distribution with mean `μ` and\n    standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.lognormal.logcdf.factory( 10.0, 2.0 );\n    > var y = mylogcdf( 10.0 )\n    ~-9.732","base.dists.lognormal.logpdf":"\nbase.dists.lognormal.logpdf( x, μ, σ )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a lognormal distribution with location parameter `μ` and scale parameter\n    `σ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.logpdf( 2.0, 0.0, 1.0 )\n    ~-1.852\n    > y = base.dists.lognormal.logpdf( 1.0, 0.0, 1.0 )\n    ~-0.919\n    > y = base.dists.lognormal.logpdf( 1.0, 3.0, 1.0 )\n    ~-5.419\n    > y = base.dists.lognormal.logpdf( -1.0, 4.0, 2.0 )\n    -Infinity\n\n    > y = base.dists.lognormal.logpdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.lognormal.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.logpdf( 0.0, 0.0, NaN )\n    NaN\n\n    // Non-positive scale parameter `σ`:\n    > y = base.dists.lognormal.logpdf( 2.0, 0.0, -1.0 )\n    NaN\n    > y = base.dists.lognormal.logpdf( 2.0, 0.0, 0.0 )\n    NaN\n\n\nbase.dists.lognormal.logpdf.factory( μ, σ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a lognormal distribution with location parameter\n    `μ` and scale parameter `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.lognormal.logpdf.factory( 4.0, 2.0 );\n    > var y = mylogPDF( 10.0 )\n    ~-4.275\n    > y = mylogPDF( 2.0 )\n    ~-3.672\n\n","base.dists.lognormal.logpdf.factory":"\nbase.dists.lognormal.logpdf.factory( μ, σ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a lognormal distribution with location parameter\n    `μ` and scale parameter `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.lognormal.logpdf.factory( 4.0, 2.0 );\n    > var y = mylogPDF( 10.0 )\n    ~-4.275\n    > y = mylogPDF( 2.0 )\n    ~-3.672","base.dists.lognormal.mean":"\nbase.dists.lognormal.mean( μ, σ )\n    Returns the expected value of a lognormal distribution with location `μ` and\n    scale `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.mean( 0.0, 1.0 )\n    ~1.649\n    > y = base.dists.lognormal.mean( 4.0, 2.0 )\n    ~403.429\n    > y = base.dists.lognormal.mean( NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.mean( 0.0, NaN )\n    NaN\n    > y = base.dists.lognormal.mean( 0.0, 0.0 )\n    NaN\n\n","base.dists.lognormal.median":"\nbase.dists.lognormal.median( μ, σ )\n    Returns the median of a lognormal distribution with location `μ` and scale\n    `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.median( 0.0, 1.0 )\n    1.0\n    > y = base.dists.lognormal.median( 5.0, 2.0 )\n    ~148.413\n    > y = base.dists.lognormal.median( NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.median( 0.0, NaN )\n    NaN\n    > y = base.dists.lognormal.median( 0.0, 0.0 )\n    NaN\n\n","base.dists.lognormal.mode":"\nbase.dists.lognormal.mode( μ, σ )\n    Returns the mode of a lognormal distribution with location `μ` and scale\n    `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.mode( 0.0, 1.0 )\n    ~0.368\n    > y = base.dists.lognormal.mode( 5.0, 2.0 )\n    ~2.718\n    > y = base.dists.lognormal.mode( NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.mode( 0.0, NaN )\n    NaN\n    > y = base.dists.lognormal.mode( 0.0, 0.0 )\n    NaN\n\n","base.dists.lognormal.pdf":"\nbase.dists.lognormal.pdf( x, μ, σ )\n    Evaluates the probability density function (PDF) for a lognormal\n    distribution with location parameter `μ` and scale parameter `σ` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.pdf( 2.0, 0.0, 1.0 )\n    ~0.157\n    > y = base.dists.lognormal.pdf( 1.0, 0.0, 1.0 )\n    ~0.399\n    > y = base.dists.lognormal.pdf( 1.0, 3.0, 1.0 )\n    ~0.004\n    > y = base.dists.lognormal.pdf( -1.0, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.lognormal.pdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.lognormal.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.pdf( 0.0, 0.0, NaN )\n    NaN\n\n    // Non-positive scale parameter `σ`:\n    > y = base.dists.lognormal.pdf( 2.0, 0.0, -1.0 )\n    NaN\n    > y = base.dists.lognormal.pdf( 2.0, 0.0, 0.0 )\n    NaN\n\n\nbase.dists.lognormal.pdf.factory( μ, σ )\n    Returns a function for evaluating the probability density function (PDF) of\n    a lognormal distribution with location parameter `μ` and scale parameter\n    `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.lognormal.pdf.factory( 4.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    ~0.014\n    > y = myPDF( 2.0 )\n    ~0.025\n\n","base.dists.lognormal.pdf.factory":"\nbase.dists.lognormal.pdf.factory( μ, σ )\n    Returns a function for evaluating the probability density function (PDF) of\n    a lognormal distribution with location parameter `μ` and scale parameter\n    `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.lognormal.pdf.factory( 4.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    ~0.014\n    > y = myPDF( 2.0 )\n    ~0.025","base.dists.lognormal.quantile":"\nbase.dists.lognormal.quantile( p, μ, σ )\n    Evaluates the quantile function for a lognormal distribution with location\n    parameter `μ` and scale parameter `σ` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.quantile( 0.8, 0.0, 1.0 )\n    ~2.32\n    > y = base.dists.lognormal.quantile( 0.5, 4.0, 2.0 )\n    ~54.598\n    > y = base.dists.lognormal.quantile( 1.1, 0.0, 1.0 )\n    NaN\n    > y = base.dists.lognormal.quantile( -0.2, 0.0, 1.0 )\n    NaN\n\n    > y = base.dists.lognormal.quantile( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.lognormal.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.quantile( 0.0, 0.0, NaN )\n    NaN\n\n    // Non-positive scale parameter `σ`:\n    > y = base.dists.lognormal.quantile( 0.5, 0.0, -1.0 )\n    NaN\n    > y = base.dists.lognormal.quantile( 0.5, 0.0, 0.0 )\n    NaN\n\n\nbase.dists.lognormal.quantile.factory( μ, σ )\n    Returns a function for evaluating the quantile function of a lognormal\n    distribution with location parameter `μ` and scale parameter `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.lognormal.quantile.factory( 4.0, 2.0 );\n    > var y = myQuantile( 0.2 )\n    ~10.143\n    > y = myQuantile( 0.8 )\n    ~293.901\n\n","base.dists.lognormal.quantile.factory":"\nbase.dists.lognormal.quantile.factory( μ, σ )\n    Returns a function for evaluating the quantile function of a lognormal\n    distribution with location parameter `μ` and scale parameter `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.lognormal.quantile.factory( 4.0, 2.0 );\n    > var y = myQuantile( 0.2 )\n    ~10.143\n    > y = myQuantile( 0.8 )\n    ~293.901","base.dists.lognormal.skewness":"\nbase.dists.lognormal.skewness( μ, σ )\n    Returns the skewness of a lognormal distribution with location `μ` and scale\n    `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.skewness( 0.0, 1.0 )\n    ~6.185\n    > y = base.dists.lognormal.skewness( 5.0, 2.0 )\n    ~414.359\n    > y = base.dists.lognormal.skewness( NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.skewness( 0.0, NaN )\n    NaN\n    > y = base.dists.lognormal.skewness( 0.0, 0.0 )\n    NaN\n\n","base.dists.lognormal.stdev":"\nbase.dists.lognormal.stdev( μ, σ )\n    Returns the standard deviation of a lognormal distribution with location `μ`\n    and scale `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.stdev( 0.0, 1.0 )\n    ~2.161\n    > y = base.dists.lognormal.stdev( 4.0, 2.0 )\n    ~2953.533\n    > y = base.dists.lognormal.stdev( NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.stdev( 0.0, NaN )\n    NaN\n    > y = base.dists.lognormal.stdev( 0.0, 0.0 )\n    NaN\n\n","base.dists.lognormal.variance":"\nbase.dists.lognormal.variance( μ, σ )\n    Returns the variance of a lognormal distribution with location `μ` and scale\n    `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.variance( 0.0, 1.0 )\n    ~4.671\n    > y = base.dists.lognormal.variance( 4.0, 2.0 )\n    ~8723355.729\n    > y = base.dists.lognormal.variance( NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.variance( 0.0, NaN )\n    NaN\n    > y = base.dists.lognormal.variance( 0.0, 0.0 )\n    NaN\n\n","base.dists.negativeBinomial.cdf":"\nbase.dists.negativeBinomial.cdf( x, r, p )\n    Evaluates the cumulative distribution function (CDF) for a negative binomial\n    distribution with number of successes until experiment is stopped `r` and\n    success probability `p` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a `r` which is not a positive number, the function returns\n    `NaN`.\n\n    If provided a success probability `p` outside of `[0,1]`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.negativeBinomial.cdf( 5.0, 20.0, 0.8 )\n    ~0.617\n    > y = base.dists.negativeBinomial.cdf( 21.0, 20.0, 0.5 )\n    ~0.622\n    > y = base.dists.negativeBinomial.cdf( 5.0, 10.0, 0.4 )\n    ~0.034\n    > y = base.dists.negativeBinomial.cdf( 0.0, 10.0, 0.9 )\n    ~0.349\n    > y = base.dists.negativeBinomial.cdf( 21.0, 15.5, 0.5 )\n    ~0.859\n    > y = base.dists.negativeBinomial.cdf( 5.0, 7.4, 0.4 )\n    ~0.131\n\n    > y = base.dists.negativeBinomial.cdf( 2.0, 0.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.cdf( 2.0, -2.0, 0.5 )\n    NaN\n\n    > y = base.dists.negativeBinomial.cdf( NaN, 20.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.cdf( 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.cdf( 0.0, 20.0, NaN )\n    NaN\n\n    > y = base.dists.negativeBinomial.cdf( 2.0, 20, -1.0 )\n    NaN\n    > y = base.dists.negativeBinomial.cdf( 2.0, 20, 1.5 )\n    NaN\n\n\nbase.dists.negativeBinomial.cdf.factory( r, p )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a negative binomial distribution with number of successes until\n    experiment is stopped `r` and success probability `p`.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.negativeBinomial.cdf.factory( 10, 0.5 );\n    > var y = myCDF( 3.0 )\n    ~0.046\n    > y = myCDF( 11.0 )\n    ~0.668\n\n","base.dists.negativeBinomial.cdf.factory":"\nbase.dists.negativeBinomial.cdf.factory( r, p )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a negative binomial distribution with number of successes until\n    experiment is stopped `r` and success probability `p`.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.negativeBinomial.cdf.factory( 10, 0.5 );\n    > var y = myCDF( 3.0 )\n    ~0.046\n    > y = myCDF( 11.0 )\n    ~0.668","base.dists.negativeBinomial.kurtosis":"\nbase.dists.negativeBinomial.kurtosis( r, p )\n    Returns the excess kurtosis of a negative binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a `r` which is not a positive number, the function returns\n    `NaN`.\n\n    If provided a success probability `p` outside of `[0,1]`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    r: integer\n        Number of failures until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.negativeBinomial.kurtosis( 100, 0.2 )\n    ~0.061\n    > v = base.dists.negativeBinomial.kurtosis( 20, 0.5 )\n    ~0.325\n\n","base.dists.negativeBinomial.logpmf":"\nbase.dists.negativeBinomial.logpmf( x, r, p )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    negative binomial distribution with number of successes until experiment is\n    stopped `r` and success probability `p` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a `r` which is not a positive number, the function returns\n    `NaN`.\n\n    If provided a success probability `p` outside of `[0,1]`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPMF.\n\n    Examples\n    --------\n    > var y = base.dists.negativeBinomial.logpmf( 5.0, 20.0, 0.8 )\n    ~-1.853\n    > y = base.dists.negativeBinomial.logpmf( 21.0, 20.0, 0.5 )\n    ~-2.818\n    > y = base.dists.negativeBinomial.logpmf( 5.0, 10.0, 0.4 )\n    ~-4.115\n    > y = base.dists.negativeBinomial.logpmf( 0.0, 10.0, 0.9 )\n    ~-1.054\n    > y = base.dists.negativeBinomial.logpmf( 21.0, 15.5, 0.5 )\n    ~-3.292\n    > y = base.dists.negativeBinomial.logpmf( 5.0, 7.4, 0.4 )\n    ~-2.976\n\n    > y = base.dists.negativeBinomial.logpmf( 2.0, 0.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.logpmf( 2.0, -2.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.logpmf( 2.0, 20, -1.0 )\n    NaN\n    > y = base.dists.negativeBinomial.logpmf( 2.0, 20, 1.5 )\n    NaN\n\n    > y = base.dists.negativeBinomial.logpmf( NaN, 20.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.logpmf( 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.logpmf( 0.0, 20.0, NaN )\n    NaN\n\n\nbase.dists.negativeBinomial.logpmf.factory( r, p )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a negative binomial distribution with number of\n    successes until experiment is stopped `r` and success probability `p`.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogPMF = base.dists.negativeBinomial.logpmf.factory( 10, 0.5 );\n    > var y = mylogPMF( 3.0 )\n    ~-3.617\n    > y = mylogPMF( 5.0 )\n    ~-2.795\n\n","base.dists.negativeBinomial.logpmf.factory":"\nbase.dists.negativeBinomial.logpmf.factory( r, p )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a negative binomial distribution with number of\n    successes until experiment is stopped `r` and success probability `p`.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogPMF = base.dists.negativeBinomial.logpmf.factory( 10, 0.5 );\n    > var y = mylogPMF( 3.0 )\n    ~-3.617\n    > y = mylogPMF( 5.0 )\n    ~-2.795","base.dists.negativeBinomial.mean":"\nbase.dists.negativeBinomial.mean( r, p )\n    Returns the expected value of a negative binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a `r` which is not a positive number, the function returns\n    `NaN`.\n\n    If provided a success probability `p` outside of `[0,1]`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    r: integer\n        Number of failures until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.negativeBinomial.mean( 100, 0.2 )\n    400\n    > v = base.dists.negativeBinomial.mean( 20, 0.5 )\n    20\n\n","base.dists.negativeBinomial.mgf":"\nbase.dists.negativeBinomial.mgf( x, r, p )\n    Evaluates the moment-generating function (MGF) for a negative binomial\n    distribution with number of successes until experiment is stopped `r` and\n    success probability `p` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a `r` which is not a positive number, the function returns\n    `NaN`.\n\n    If provided a success probability `p` outside of `[0,1]`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.negativeBinomial.mgf( 0.05, 20.0, 0.8 )\n    ~267.839\n    > y = base.dists.negativeBinomial.mgf( 0.1, 20.0, 0.1 )\n    ~9.347\n    > y = base.dists.negativeBinomial.mgf( 0.5, 10.0, 0.4 )\n    ~42822.023\n\n    > y = base.dists.negativeBinomial.mgf( 0.1, 0.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.mgf( 0.1, -2.0, 0.5 )\n    NaN\n\n    > y = base.dists.negativeBinomial.mgf( NaN, 20.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.mgf( 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.mgf( 0.0, 20.0, NaN )\n    NaN\n\n    > y = base.dists.negativeBinomial.mgf( 0.2, 20, -1.0 )\n    NaN\n    > y = base.dists.negativeBinomial.mgf( 0.2, 20, 1.5 )\n    NaN\n\n\nbase.dists.negativeBinomial.mgf.factory( r, p )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    negative binomial distribution with number of successes until experiment is\n    stopped `r` and success probability `p`.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.negativeBinomial.mgf.factory( 4.3, 0.4 );\n    > var y = myMGF( 0.2 )\n    ~4.696\n    > y = myMGF( 0.4 )\n    ~30.83\n\n","base.dists.negativeBinomial.mgf.factory":"\nbase.dists.negativeBinomial.mgf.factory( r, p )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    negative binomial distribution with number of successes until experiment is\n    stopped `r` and success probability `p`.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.negativeBinomial.mgf.factory( 4.3, 0.4 );\n    > var y = myMGF( 0.2 )\n    ~4.696\n    > y = myMGF( 0.4 )\n    ~30.83","base.dists.negativeBinomial.mode":"\nbase.dists.negativeBinomial.mode( r, p )\n    Returns the mode of a negative binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a `r` which is not a positive number, the function returns\n    `NaN`.\n\n    If provided a success probability `p` outside of `[0,1]`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    r: integer\n        Number of failures until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.negativeBinomial.mode( 100, 0.2 )\n    396\n    > v = base.dists.negativeBinomial.mode( 20, 0.5 )\n    19\n\n","base.dists.negativeBinomial.NegativeBinomial":"\nbase.dists.negativeBinomial.NegativeBinomial( [r, p] )\n    Returns a negative binomial distribution object.\n\n    Parameters\n    ----------\n    r: number (optional)\n        Number of successes until experiment is stopped. Must be a positive\n        number. Default: `1`.\n\n    p: number (optional)\n        Success probability. Must be a number between `0` and `1`. Default:\n        `0.5`.\n\n    Returns\n    -------\n    nbinomial: Object\n        Distribution instance.\n\n    nbinomial.r: number\n        Number of trials. If set, the value must be a positive number.\n\n    nbinomial.p: number\n        Success probability. If set, the value must be a number between `0` and\n        `1`.\n\n    nbinomial.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    nbinomial.mean: number\n        Read-only property which returns the expected value.\n\n    nbinomial.mode: number\n        Read-only property which returns the mode.\n\n    nbinomial.skewness: number\n        Read-only property which returns the skewness.\n\n    nbinomial.stdev: number\n        Read-only property which returns the standard deviation.\n\n    nbinomial.variance: number\n        Read-only property which returns the variance.\n\n    nbinomial.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    nbinomial.logpmf: Function\n        Evaluates the natural logarithm of the probability mass function (PMF).\n\n    nbinomial.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    nbinomial.pmf: Function\n        Evaluates the probability mass function (PMF).\n\n    nbinomial.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var nbinomial = base.dists.negativeBinomial.NegativeBinomial( 8.0, 0.5 );\n    > nbinomial.r\n    8.0\n    > nbinomial.p\n    0.5\n    > nbinomial.kurtosis\n    0.8125\n    > nbinomial.mean\n    8.0\n    > nbinomial.mode\n    7.0\n    > nbinomial.skewness\n    0.75\n    > nbinomial.stdev\n    4.0\n    > nbinomial.variance\n    16.0\n    > nbinomial.cdf( 2.9 )\n    ~0.055\n    > nbinomial.logpmf( 3.0 )\n    ~-2.837\n    > nbinomial.mgf( 0.2 )\n    ~36.675\n    > nbinomial.pmf( 3.0 )\n    ~0.059\n    > nbinomial.quantile( 0.8 )\n    11.0\n\n","base.dists.negativeBinomial.pmf":"\nbase.dists.negativeBinomial.pmf( x, r, p )\n    Evaluates the probability mass function (PMF) for a negative binomial\n    distribution with number of successes until experiment is stopped `r` and\n    success probability `p` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a `r` which is not a positive number, the function returns\n    `NaN`.\n\n    If provided a success probability `p` outside of `[0,1]`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated PMF.\n\n    Examples\n    --------\n    > var y = base.dists.negativeBinomial.pmf( 5.0, 20.0, 0.8 )\n    ~0.157\n    > y = base.dists.negativeBinomial.pmf( 21.0, 20.0, 0.5 )\n    ~0.06\n    > y = base.dists.negativeBinomial.pmf( 5.0, 10.0, 0.4 )\n    ~0.016\n    > y = base.dists.negativeBinomial.pmf( 0.0, 10.0, 0.9 )\n    ~0.349\n    > y = base.dists.negativeBinomial.pmf( 21.0, 15.5, 0.5 )\n    ~0.037\n    > y = base.dists.negativeBinomial.pmf( 5.0, 7.4, 0.4 )\n    ~0.051\n\n    > y = base.dists.negativeBinomial.pmf( 2.0, 0.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.pmf( 2.0, -2.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.pmf( 2.0, 20, -1.0 )\n    NaN\n    > y = base.dists.negativeBinomial.pmf( 2.0, 20, 1.5 )\n    NaN\n\n    > y = base.dists.negativeBinomial.pmf( NaN, 20.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.pmf( 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.pmf( 0.0, 20.0, NaN )\n    NaN\n\n\nbase.dists.negativeBinomial.pmf.factory( r, p )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    negative binomial distribution with number of successes until experiment is\n    stopped `r` and success probability `p`.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var myPMF = base.dists.negativeBinomial.pmf.factory( 10, 0.5 );\n    > var y = myPMF( 3.0 )\n    ~0.027\n    > y = myPMF( 5.0 )\n    ~0.061\n\n","base.dists.negativeBinomial.pmf.factory":"\nbase.dists.negativeBinomial.pmf.factory( r, p )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    negative binomial distribution with number of successes until experiment is\n    stopped `r` and success probability `p`.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var myPMF = base.dists.negativeBinomial.pmf.factory( 10, 0.5 );\n    > var y = myPMF( 3.0 )\n    ~0.027\n    > y = myPMF( 5.0 )\n    ~0.061","base.dists.negativeBinomial.quantile":"\nbase.dists.negativeBinomial.quantile( k, r, p )\n    Evaluates the quantile function for a negative binomial distribution with\n    number of successes until experiment is stopped `r` and success probability\n    `p` at a probability `k`.\n\n    If provided a `k` outside of `[0,1]`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a `r` which is not a positive number, the function returns\n    `NaN`.\n\n    If provided a success probability `p` outside of `[0,1]`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Input probability.\n\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.2 )\n    106\n    > y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.8 )\n    8\n    > y = base.dists.negativeBinomial.quantile( 0.5, 10.0, 0.4 )\n    14\n    > y = base.dists.negativeBinomial.quantile( 0.0, 10.0, 0.9 )\n    0\n\n    > y = base.dists.negativeBinomial.quantile( 1.1, 20.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.quantile( -0.1, 20.0, 0.5 )\n    NaN\n\n    > y = base.dists.negativeBinomial.quantile( 21.0, 15.5, 0.5 )\n    12\n    > y = base.dists.negativeBinomial.quantile( 5.0, 7.4, 0.4 )\n    10\n\n    > y = base.dists.negativeBinomial.quantile( 0.5, 0.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.quantile( 0.5, -2.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, -1.0 )\n    NaN\n    > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, 1.5 )\n    NaN\n\n    > y = base.dists.negativeBinomial.quantile( NaN, 20.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.quantile( 0.3, NaN, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, NaN )\n    NaN\n\n\nbase.dists.negativeBinomial.quantile.factory( r, p )\n    Returns a function for evaluating the quantile function of a negative\n    binomial distribution with number of successes until experiment is stopped\n    `r` and success probability `p`.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.negativeBinomial.quantile.factory( 10.0, 0.5 );\n    > var y = myQuantile( 0.1 )\n    5\n    > y = myQuantile( 0.9 )\n    16\n\n","base.dists.negativeBinomial.quantile.factory":"\nbase.dists.negativeBinomial.quantile.factory( r, p )\n    Returns a function for evaluating the quantile function of a negative\n    binomial distribution with number of successes until experiment is stopped\n    `r` and success probability `p`.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.negativeBinomial.quantile.factory( 10.0, 0.5 );\n    > var y = myQuantile( 0.1 )\n    5\n    > y = myQuantile( 0.9 )\n    16","base.dists.negativeBinomial.skewness":"\nbase.dists.negativeBinomial.skewness( r, p )\n    Returns the skewness of a negative binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a `r` which is not a positive number, the function returns\n    `NaN`.\n\n    If provided a success probability `p` outside of `[0,1]`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    r: integer\n        Number of failures until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.negativeBinomial.skewness( 100, 0.2 )\n    ~0.201\n    > v = base.dists.negativeBinomial.skewness( 20, 0.5 )\n    ~0.474\n\n","base.dists.negativeBinomial.stdev":"\nbase.dists.negativeBinomial.stdev( r, p )\n    Returns the standard deviation of a negative binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a `r` which is not a positive number, the function returns\n    `NaN`.\n\n    If provided a success probability `p` outside of `[0,1]`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    r: integer\n        Number of failures until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.negativeBinomial.stdev( 100, 0.2 )\n    ~44.721\n    > v = base.dists.negativeBinomial.stdev( 20, 0.5 )\n    ~6.325\n\n","base.dists.negativeBinomial.variance":"\nbase.dists.negativeBinomial.variance( r, p )\n    Returns the variance of a negative binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a `r` which is not a positive number, the function returns\n    `NaN`.\n\n    If provided a success probability `p` outside of `[0,1]`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    r: integer\n        Number of failures until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.negativeBinomial.variance( 100, 0.2 )\n    2000.0\n    > v = base.dists.negativeBinomial.variance( 20, 0.5 )\n    40.0\n\n","base.dists.normal.cdf":"\nbase.dists.normal.cdf( x, μ, σ )\n    Evaluates the cumulative distribution function (CDF) for a normal\n    distribution with mean `μ` and standard deviation `σ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.normal.cdf( 2.0, 0.0, 1.0 )\n    ~0.977\n    > y = base.dists.normal.cdf( -1.0, -1.0, 2.0 )\n    0.5\n    > y = base.dists.normal.cdf( -1.0, 4.0, 2.0 )\n    ~0.006\n    > y = base.dists.normal.cdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.normal.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.cdf( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative standard deviation:\n    > y = base.dists.normal.cdf( 2.0, 0.0, -1.0 )\n    NaN\n\n    // Degenerate distribution centered at `μ` when `σ = 0.0`:\n    > y = base.dists.normal.cdf( 2.0, 8.0, 0.0 )\n    0.0\n    > y = base.dists.normal.cdf( 8.0, 8.0, 0.0 )\n    1.0\n    > y = base.dists.normal.cdf( 10.0, 8.0, 0.0 )\n    1.0\n\n\nbase.dists.normal.cdf.factory( μ, σ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a normal distribution with mean `μ` and standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.normal.cdf.factory( 10.0, 2.0 );\n    > var y = myCDF( 10.0 )\n    0.5\n\n","base.dists.normal.cdf.factory":"\nbase.dists.normal.cdf.factory( μ, σ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a normal distribution with mean `μ` and standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.normal.cdf.factory( 10.0, 2.0 );\n    > var y = myCDF( 10.0 )\n    0.5","base.dists.normal.entropy":"\nbase.dists.normal.entropy( μ, σ )\n    Returns the differential entropy of a normal distribution with mean `μ` and\n    standard deviation `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var y = base.dists.normal.entropy( 0.0, 1.0 )\n    ~1.419\n    > y = base.dists.normal.entropy( 4.0, 3.0 )\n    ~2.518\n    > y = base.dists.normal.entropy( NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.entropy( 0.0, NaN )\n    NaN\n    > y = base.dists.normal.entropy( 0.0, 0.0 )\n    NaN\n\n","base.dists.normal.kurtosis":"\nbase.dists.normal.kurtosis( μ, σ )\n    Returns the excess kurtosis of a normal distribution with mean `μ` and\n    standard deviation `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var y = base.dists.normal.kurtosis( 0.0, 1.0 )\n    0.0\n    > y = base.dists.normal.kurtosis( 4.0, 3.0 )\n    0.0\n    > y = base.dists.normal.kurtosis( NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.kurtosis( 0.0, NaN )\n    NaN\n    > y = base.dists.normal.kurtosis( 0.0, 0.0 )\n    NaN\n\n","base.dists.normal.logcdf":"\nbase.dists.normal.logcdf( x, μ, σ )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a normal distribution with mean `μ` and standard deviation `σ` at\n    a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Evaluated logcdf.\n\n    Examples\n    --------\n    > var y = base.dists.normal.logcdf( 2.0, 0.0, 1.0 )\n    ~-0.023\n    > y = base.dists.normal.logcdf( -1.0, 4.0, 2.0 )\n    ~-5.082\n    > y = base.dists.normal.logcdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.normal.logcdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.logcdf( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative standard deviation:\n    > y = base.dists.normal.logcdf( 2.0, 0.0, -1.0 )\n    NaN\n\n    // Degenerate distribution centered at `μ` when `σ = 0.0`:\n    > y = base.dists.normal.logcdf( 2.0, 8.0, 0.0 )\n    -Infinity\n    > y = base.dists.normal.logcdf( 8.0, 8.0, 0.0 )\n    0.0\n\n\nbase.dists.normal.logcdf.factory( μ, σ )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a normal distribution with mean `μ` and\n    standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.normal.logcdf.factory( 10.0, 2.0 );\n    > var y = mylogcdf( 10.0 )\n    ~-0.693\n\n","base.dists.normal.logcdf.factory":"\nbase.dists.normal.logcdf.factory( μ, σ )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a normal distribution with mean `μ` and\n    standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.normal.logcdf.factory( 10.0, 2.0 );\n    > var y = mylogcdf( 10.0 )\n    ~-0.693","base.dists.normal.logpdf":"\nbase.dists.normal.logpdf( x, μ, σ )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a normal distribution with mean `μ` and standard deviation `σ` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.normal.logpdf( 2.0, 0.0, 1.0 )\n    ~-2.919\n    > y = base.dists.normal.logpdf( -1.0, 4.0, 2.0 )\n    ~-4.737\n    > y = base.dists.normal.logpdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.normal.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.logpdf( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative standard deviation:\n    > y = base.dists.normal.logpdf( 2.0, 0.0, -1.0 )\n    NaN\n\n    // Degenerate distribution centered at `μ` when `σ = 0.0`:\n    > y = base.dists.normal.logpdf( 2.0, 8.0, 0.0 )\n    -Infinity\n    > y = base.dists.normal.logpdf( 8.0, 8.0, 0.0 )\n    Infinity\n\n\nbase.dists.normal.logpdf.factory( μ, σ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a normal distribution with mean `μ` and standard\n    deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var myLogPDF = base.dists.normal.logpdf.factory( 10.0, 2.0 );\n    > var y = myLogPDF( 10.0 )\n    ~-1.612\n\n","base.dists.normal.logpdf.factory":"\nbase.dists.normal.logpdf.factory( μ, σ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a normal distribution with mean `μ` and standard\n    deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var myLogPDF = base.dists.normal.logpdf.factory( 10.0, 2.0 );\n    > var y = myLogPDF( 10.0 )\n    ~-1.612","base.dists.normal.mean":"\nbase.dists.normal.mean( μ, σ )\n    Returns the expected value of a normal distribution with mean `μ` and\n    standard deviation `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var y = base.dists.normal.mean( 0.0, 1.0 )\n    0.0\n    > y = base.dists.normal.mean( 4.0, 2.0 )\n    4.0\n    > y = base.dists.normal.mean( NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.mean( 0.0, NaN )\n    NaN\n    > y = base.dists.normal.mean( 0.0, 0.0 )\n    NaN\n\n","base.dists.normal.median":"\nbase.dists.normal.median( μ, σ )\n    Returns the median of a normal distribution with mean `μ` and standard\n    deviation `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var y = base.dists.normal.median( 0.0, 1.0 )\n    0.0\n    > y = base.dists.normal.median( 4.0, 2.0 )\n    4.0\n    > y = base.dists.normal.median( NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.median( 0.0, NaN )\n    NaN\n    > y = base.dists.normal.median( 0.0, 0.0 )\n    NaN\n\n","base.dists.normal.mgf":"\nbase.dists.normal.mgf( x, μ, σ )\n    Evaluates the moment-generating function (MGF) for a normal distribution\n    with mean `μ` and standard deviation `σ` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.normal.mgf( 2.0, 0.0, 1.0 )\n    ~7.389\n    > y = base.dists.normal.mgf( 0.0, 0.0, 1.0 )\n    1.0\n    > y = base.dists.normal.mgf( -1.0, 4.0, 2.0 )\n    ~0.1353\n    > y = base.dists.normal.mgf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.normal.mgf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.mgf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.normal.mgf( 2.0, 0.0, 0.0 )\n    NaN\n\n\nbase.dists.normal.mgf.factory( μ, σ )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    normal distribution with mean `μ` and standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.normal.mgf.factory( 4.0, 2.0 );\n    > var y = myMGF( 1.0 )\n    ~403.429\n    > y = myMGF( 0.5 )\n    ~12.182\n\n","base.dists.normal.mgf.factory":"\nbase.dists.normal.mgf.factory( μ, σ )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    normal distribution with mean `μ` and standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.normal.mgf.factory( 4.0, 2.0 );\n    > var y = myMGF( 1.0 )\n    ~403.429\n    > y = myMGF( 0.5 )\n    ~12.182","base.dists.normal.mode":"\nbase.dists.normal.mode( μ, σ )\n    Returns the mode of a normal distribution with mean `μ` and standard\n    deviation `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var y = base.dists.normal.mode( 0.0, 1.0 )\n    0.0\n    > y = base.dists.normal.mode( 4.0, 2.0 )\n    4.0\n    > y = base.dists.normal.mode( NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.mode( 0.0, NaN )\n    NaN\n    > y = base.dists.normal.mode( 0.0, 0.0 )\n    NaN\n\n","base.dists.normal.Normal":"\nbase.dists.normal.Normal( [μ, σ] )\n    Returns a normal distribution object.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean parameter. Default: `0.0`.\n\n    σ: number (optional)\n        Standard deviation. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    normal: Object\n        Distribution instance.\n\n    normal.mu: number\n        Mean parameter.\n\n    normal.sigma: number\n        Standard deviation. If set, the value must be greater than `0`.\n\n    normal.entropy: number\n        Read-only property which returns the differential entropy.\n\n    normal.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    normal.mean: number\n        Read-only property which returns the expected value.\n\n    normal.median: number\n        Read-only property which returns the median.\n\n    normal.mode: number\n        Read-only property which returns the mode.\n\n    normal.skewness: number\n        Read-only property which returns the skewness.\n\n    normal.stdev: number\n        Read-only property which returns the standard deviation.\n\n    normal.variance: number\n        Read-only property which returns the variance.\n\n    normal.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    normal.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    normal.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    normal.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    normal.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    normal.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var normal = base.dists.normal.Normal( -2.0, 3.0 );\n    > normal.mu\n    -2.0\n    > normal.sigma\n    3.0\n    > normal.entropy\n    ~2.518\n    > normal.kurtosis\n    0.0\n    > normal.mean\n    -2.0\n    > normal.median\n    -2.0\n    > normal.mode\n    -2.0\n    > normal.skewness\n    0.0\n    > normal.stdev\n    3.0\n    > normal.variance\n    9.0\n    > normal.cdf( 0.8 )\n    ~0.825\n    > normal.logcdf( 0.8 )\n    ~-0.193\n    > normal.logpdf( 2.0 )\n    ~-2.9\n    > normal.mgf( 0.2 )\n    ~0.803\n    > normal.pdf( 2.0 )\n    ~0.055\n    > normal.quantile( 0.9 )\n    ~1.845\n\n","base.dists.normal.pdf":"\nbase.dists.normal.pdf( x, μ, σ )\n    Evaluates the probability density function (PDF) for a normal distribution\n    with mean `μ` and standard deviation `σ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.normal.pdf( 2.0, 0.0, 1.0 )\n    ~0.054\n    > y = base.dists.normal.pdf( -1.0, 4.0, 2.0 )\n    ~0.009\n    > y = base.dists.normal.pdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.normal.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.pdf( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative standard deviation:\n    > y = base.dists.normal.pdf( 2.0, 0.0, -1.0 )\n    NaN\n\n    // Degenerate distribution centered at `μ` when `σ = 0.0`:\n    > y = base.dists.normal.pdf( 2.0, 8.0, 0.0 )\n    0.0\n    > y = base.dists.normal.pdf( 8.0, 8.0, 0.0 )\n    infinity\n\n\nbase.dists.normal.pdf.factory( μ, σ )\n    Returns a function for evaluating the probability density function (PDF) of\n    a normal distribution with mean `μ` and standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.normal.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    ~0.199\n\n","base.dists.normal.pdf.factory":"\nbase.dists.normal.pdf.factory( μ, σ )\n    Returns a function for evaluating the probability density function (PDF) of\n    a normal distribution with mean `μ` and standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.normal.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    ~0.199","base.dists.normal.quantile":"\nbase.dists.normal.quantile( p, μ, σ )\n    Evaluates the quantile function for a normal distribution with mean `μ` and\n    standard deviation `σ` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.normal.quantile( 0.8, 0.0, 1.0 )\n    ~0.842\n    > y = base.dists.normal.quantile( 0.5, 4.0, 2.0 )\n    4\n\n    > y = base.dists.normal.quantile( 1.1, 0.0, 1.0 )\n    NaN\n    > y = base.dists.normal.quantile( -0.2, 0.0, 1.0 )\n    NaN\n\n    > y = base.dists.normal.quantile( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.normal.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.quantile( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative standard deviation:\n    > y = base.dists.normal.quantile( 0.5, 0.0, -1.0 )\n    NaN\n\n    // Degenerate distribution centered at `μ` when `σ = 0.0`:\n    > y = base.dists.normal.quantile( 0.3, 8.0, 0.0 )\n    8.0\n    > y = base.dists.normal.quantile( 0.9, 8.0, 0.0 )\n    8.0\n\n\nbase.dists.normal.quantile.factory( μ, σ )\n    Returns a function for evaluating the quantile function\n    of a normal distribution with mean `μ` and standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.normal.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    10.0\n\n","base.dists.normal.quantile.factory":"\nbase.dists.normal.quantile.factory( μ, σ )\n    Returns a function for evaluating the quantile function\n    of a normal distribution with mean `μ` and standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.normal.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    10.0","base.dists.normal.skewness":"\nbase.dists.normal.skewness( μ, σ )\n    Returns the skewness of a normal distribution with mean `μ` and standard\n    deviation `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var y = base.dists.normal.skewness( 0.0, 1.0 )\n    0.0\n    > y = base.dists.normal.skewness( 4.0, 3.0 )\n    0.0\n    > y = base.dists.normal.skewness( NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.skewness( 0.0, NaN )\n    NaN\n    > y = base.dists.normal.skewness( 0.0, 0.0 )\n    NaN\n\n","base.dists.normal.stdev":"\nbase.dists.normal.stdev( μ, σ )\n    Returns the standard deviation of a normal distribution with mean `μ` and\n    standard deviation `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var y = base.dists.normal.stdev( 0.0, 1.0 )\n    1.0\n    > y = base.dists.normal.stdev( 4.0, 3.0 )\n    3.0\n    > y = base.dists.normal.stdev( NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.stdev( 0.0, NaN )\n    NaN\n    > y = base.dists.normal.stdev( 0.0, 0.0 )\n    NaN\n\n","base.dists.normal.variance":"\nbase.dists.normal.variance( μ, σ )\n    Returns the variance of a normal distribution with mean `μ` and standard\n    deviation `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var y = base.dists.normal.variance( 0.0, 1.0 )\n    1.0\n    > y = base.dists.normal.variance( 4.0, 3.0 )\n    9.0\n    > y = base.dists.normal.variance( NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.variance( 0.0, NaN )\n    NaN\n    > y = base.dists.normal.variance( 0.0, 0.0 )\n    NaN\n\n","base.dists.pareto1.cdf":"\nbase.dists.pareto1.cdf( x, α, β )\n    Evaluates the cumulative distribution function (CDF) for a Pareto (Type I)\n    distribution with shape parameter `α` and scale parameter `β` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.pareto1.cdf( 2.0, 1.0, 1.0 )\n    0.5\n    > y = base.dists.pareto1.cdf( 5.0, 2.0, 4.0 )\n    ~0.36\n    > y = base.dists.pareto1.cdf( 4.0, 2.0, 2.0 )\n    0.75\n    > y = base.dists.pareto1.cdf( 1.9, 2.0, 2.0 )\n    0.0\n    > y = base.dists.pareto1.cdf( PINF, 4.0, 2.0 )\n    1.0\n\n    > y = base.dists.pareto1.cdf( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.pareto1.cdf( 2.0, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.pareto1.cdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.pareto1.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.pareto1.cdf( 0.0, 1.0, NaN )\n    NaN\n\n\nbase.dists.pareto1.cdf.factory( α, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Pareto (Type I) distribution with shape parameter `α` and scale\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.pareto1.cdf.factory( 10.0, 2.0 );\n    > var y = myCDF( 3.0 )\n    ~0.983\n    > y = myCDF( 2.5 )\n    ~0.893\n\n","base.dists.pareto1.cdf.factory":"\nbase.dists.pareto1.cdf.factory( α, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Pareto (Type I) distribution with shape parameter `α` and scale\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.pareto1.cdf.factory( 10.0, 2.0 );\n    > var y = myCDF( 3.0 )\n    ~0.983\n    > y = myCDF( 2.5 )\n    ~0.893","base.dists.pareto1.entropy":"\nbase.dists.pareto1.entropy( α, β )\n    Returns the differential entropy of a Pareto (Type I) distribution\n    (in nats).\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Differential entropy.\n\n    Examples\n    --------\n    > var v = base.dists.pareto1.entropy( 0.8, 1.0 )\n    ~2.473\n    > v = base.dists.pareto1.entropy( 4.0, 12.0 )\n    ~2.349\n    > v = base.dists.pareto1.entropy( 8.0, 2.0 )\n    ~-0.261\n\n","base.dists.pareto1.kurtosis":"\nbase.dists.pareto1.kurtosis( α, β )\n    Returns the excess kurtosis of a Pareto (Type I) distribution.\n\n    If `α <= 4` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.pareto1.kurtosis( 5.0, 1.0 )\n    ~70.8\n    > v = base.dists.pareto1.kurtosis( 4.5, 12.0 )\n    ~146.444\n    > v = base.dists.pareto1.kurtosis( 8.0, 2.0 )\n    ~19.725\n\n","base.dists.pareto1.logcdf":"\nbase.dists.pareto1.logcdf( x, α, β )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a Pareto (Type I) distribution with shape parameter `α` and scale\n    parameter `β` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.pareto1.logcdf( 2.0, 1.0, 1.0 )\n    ~-0.693\n    > y = base.dists.pareto1.logcdf( 5.0, 2.0, 4.0 )\n    ~-1.022\n    > y = base.dists.pareto1.logcdf( 4.0, 2.0, 2.0 )\n    ~-0.288\n    > y = base.dists.pareto1.logcdf( 1.9, 2.0, 2.0 )\n    -Infinity\n    > y = base.dists.pareto1.logcdf( PINF, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.pareto1.logcdf( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.pareto1.logcdf( 2.0, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.pareto1.logcdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.pareto1.logcdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.pareto1.logcdf( 0.0, 1.0, NaN )\n    NaN\n\n\nbase.dists.pareto1.logcdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Pareto (Type I) distribution with shape\n    parameter `α` and scale parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogCDF = base.dists.pareto1.logcdf.factory( 10.0, 2.0 );\n    > var y = mylogCDF( 3.0 )\n    ~-0.017\n    > y = mylogCDF( 2.5 )\n    ~-0.114\n\n","base.dists.pareto1.logcdf.factory":"\nbase.dists.pareto1.logcdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Pareto (Type I) distribution with shape\n    parameter `α` and scale parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogCDF = base.dists.pareto1.logcdf.factory( 10.0, 2.0 );\n    > var y = mylogCDF( 3.0 )\n    ~-0.017\n    > y = mylogCDF( 2.5 )\n    ~-0.114","base.dists.pareto1.logpdf":"\nbase.dists.pareto1.logpdf( x, α, β )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a Pareto (Type I) distribution with shape parameter `α` and scale\n    parameter `β` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.pareto1.logpdf( 4.0, 1.0, 1.0 )\n    ~-2.773\n    > y = base.dists.pareto1.logpdf( 20.0, 1.0, 10.0 )\n    ~-3.689\n    > y = base.dists.pareto1.logpdf( 7.0, 2.0, 6.0 )\n    ~-1.561\n    > y = base.dists.pareto1.logpdf( 7.0, 6.0, 3.0 )\n    ~-5.238\n    > y = base.dists.pareto1.logpdf( 1.0, 4.0, 2.0 )\n    -Infinity\n    > y = base.dists.pareto1.logpdf( 1.5, 4.0, 2.0 )\n    -Infinity\n\n    > y = base.dists.pareto1.logpdf( 0.5, -1.0, 0.5 )\n    NaN\n    > y = base.dists.pareto1.logpdf( 0.5, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.pareto1.logpdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.pareto1.logpdf( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.dists.pareto1.logpdf( 0.5, 1.0, NaN )\n    NaN\n\n\nbase.dists.pareto1.logpdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a Pareto (Type I) distribution with shape\n    parameter `α` and scale parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.pareto1.logpdf.factory( 0.5, 0.5 );\n    > var y = mylogPDF( 0.8 )\n    ~-0.705\n    > y = mylogPDF( 2.0 )\n    ~-2.079\n\n","base.dists.pareto1.logpdf.factory":"\nbase.dists.pareto1.logpdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a Pareto (Type I) distribution with shape\n    parameter `α` and scale parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.pareto1.logpdf.factory( 0.5, 0.5 );\n    > var y = mylogPDF( 0.8 )\n    ~-0.705\n    > y = mylogPDF( 2.0 )\n    ~-2.079","base.dists.pareto1.mean":"\nbase.dists.pareto1.mean( α, β )\n    Returns the expected value of a Pareto (Type I) distribution.\n\n    If `0 < α <= 1`, the function returns `Infinity`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.pareto1.mean( 0.8, 1.0 )\n    Infinity\n    > v = base.dists.pareto1.mean( 4.0, 12.0 )\n    16.0\n    > v = base.dists.pareto1.mean( 8.0, 2.0 )\n    ~2.286\n\n","base.dists.pareto1.median":"\nbase.dists.pareto1.median( α, β )\n    Returns the median of a Pareto (Type I) distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.pareto1.median( 0.8, 1.0 )\n    ~2.378\n    > v = base.dists.pareto1.median( 4.0, 12.0 )\n    ~14.27\n    > v = base.dists.pareto1.median( 8.0, 2.0 )\n    ~2.181\n\n","base.dists.pareto1.mode":"\nbase.dists.pareto1.mode( α, β )\n    Returns the mode of a Pareto (Type I) distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.pareto1.mode( 0.8, 1.0 )\n    1.0\n    > v = base.dists.pareto1.mode( 4.0, 12.0 )\n    12.0\n    > v = base.dists.pareto1.mode( 8.0, 2.0 )\n    2.0\n\n","base.dists.pareto1.Pareto1":"\nbase.dists.pareto1.Pareto1( [α, β] )\n    Returns a Pareto (Type I) distribution object.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n    β: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    pareto1: Object\n        Distribution instance.\n\n    pareto1.alpha: number\n        Shape parameter. If set, the value must be greater than `0`.\n\n    pareto1.beta: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    pareto1.entropy: number\n        Read-only property which returns the differential entropy.\n\n    pareto1.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    pareto1.mean: number\n        Read-only property which returns the expected value.\n\n    pareto1.median: number\n        Read-only property which returns the median.\n\n    pareto1.mode: number\n        Read-only property which returns the mode.\n\n    pareto1.skewness: number\n        Read-only property which returns the skewness.\n\n    pareto1.variance: number\n        Read-only property which returns the variance.\n\n    pareto1.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    pareto1.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (logCDF).\n\n    pareto1.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (logPDF).\n\n    pareto1.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    pareto1.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var pareto1 = base.dists.pareto1.Pareto1( 6.0, 5.0 );\n    > pareto1.alpha\n    6.0\n    > pareto1.beta\n    5.0\n    > pareto1.entropy\n    ~0.984\n    > pareto1.kurtosis\n    ~35.667\n    > pareto1.mean\n    6.0\n    > pareto1.median\n    ~5.612\n    > pareto1.mode\n    5.0\n    > pareto1.skewness\n    ~3.81\n    > pareto1.variance\n    1.5\n    > pareto1.cdf( 7.0 )\n    ~0.867\n    > pareto1.logcdf( 7.0 )\n    ~-0.142\n    > pareto1.logpdf( 5.0 )\n    ~0.182\n    > pareto1.pdf( 5.0 )\n    1.2\n    > pareto1.quantile( 0.8 )\n    ~6.538\n\n","base.dists.pareto1.pdf":"\nbase.dists.pareto1.pdf( x, α, β )\n    Evaluates the probability density function (PDF) for a Pareto (Type I)\n    distribution with shape parameter `α` and scale parameter `β` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.pareto1.pdf( 4.0, 1.0, 1.0 )\n    ~0.063\n    > y = base.dists.pareto1.pdf( 20.0, 1.0, 10.0 )\n    0.025\n    > y = base.dists.pareto1.pdf( 7.0, 2.0, 6.0 )\n    ~0.21\n    > y = base.dists.pareto1.pdf( 7.0, 6.0, 3.0 )\n    ~0.005\n    > y = base.dists.pareto1.pdf( 1.0, 4.0, 2.0 )\n    0.0\n    > y = base.dists.pareto1.pdf( 1.5, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.pareto1.pdf( 0.5, -1.0, 0.5 )\n    NaN\n    > y = base.dists.pareto1.pdf( 0.5, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.pareto1.pdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.pareto1.pdf( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.dists.pareto1.pdf( 0.5, 1.0, NaN )\n    NaN\n\n\nbase.dists.pareto1.pdf.factory( α, β )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Pareto (Type I) distribution with shape parameter `α` and scale parameter\n    `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.pareto1.pdf.factory( 0.5, 0.5 );\n    > var y = myPDF( 0.8 )\n    ~0.494\n    > y = myPDF( 2.0 )\n    ~0.125\n\n","base.dists.pareto1.pdf.factory":"\nbase.dists.pareto1.pdf.factory( α, β )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Pareto (Type I) distribution with shape parameter `α` and scale parameter\n    `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.pareto1.pdf.factory( 0.5, 0.5 );\n    > var y = myPDF( 0.8 )\n    ~0.494\n    > y = myPDF( 2.0 )\n    ~0.125","base.dists.pareto1.quantile":"\nbase.dists.pareto1.quantile( p, α, β )\n    Evaluates the quantile function for a Pareto (Type I) distribution with\n    shape parameter `α` and scale parameter `β` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.pareto1.quantile( 0.8, 2.0, 1.0 )\n    ~2.236\n    > y = base.dists.pareto1.quantile( 0.8, 1.0, 10.0 )\n    ~50.0\n    > y = base.dists.pareto1.quantile( 0.1, 1.0, 10.0 )\n    ~11.111\n\n    > y = base.dists.pareto1.quantile( 1.1, 1.0, 1.0 )\n    NaN\n    > y = base.dists.pareto1.quantile( -0.2, 1.0, 1.0 )\n    NaN\n\n    > y = base.dists.pareto1.quantile( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.pareto1.quantile( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.dists.pareto1.quantile( 0.5, 1.0, NaN )\n    NaN\n\n    > y = base.dists.pareto1.quantile( 0.5, -1.0, 1.0 )\n    NaN\n    > y = base.dists.pareto1.quantile( 0.5, 1.0, -1.0 )\n    NaN\n\n\nbase.dists.pareto1.quantile.factory( α, β )\n    Returns a function for evaluating the quantile function of a Pareto (Type I)\n    distribution with shape parameter `α` and scale parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.pareto1.quantile.factory( 2.5, 0.5 );\n    > var y = myQuantile( 0.5 )\n    ~0.66\n    > y = myQuantile( 0.8 )\n    ~0.952\n\n","base.dists.pareto1.quantile.factory":"\nbase.dists.pareto1.quantile.factory( α, β )\n    Returns a function for evaluating the quantile function of a Pareto (Type I)\n    distribution with shape parameter `α` and scale parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.pareto1.quantile.factory( 2.5, 0.5 );\n    > var y = myQuantile( 0.5 )\n    ~0.66\n    > y = myQuantile( 0.8 )\n    ~0.952","base.dists.pareto1.skewness":"\nbase.dists.pareto1.skewness( α, β )\n    Returns the skewness of a Pareto (Type I) distribution.\n\n    If `α <= 3` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.pareto1.skewness( 3.5, 1.0 )\n    ~11.784\n    > v = base.dists.pareto1.skewness( 4.0, 12.0 )\n    ~7.071\n    > v = base.dists.pareto1.skewness( 8.0, 2.0 )\n    ~3.118\n\n","base.dists.pareto1.stdev":"\nbase.dists.pareto1.stdev( α, β )\n    Returns the standard deviation of a Pareto (Type I) distribution.\n\n    If `0 < α <= 2` and `β > 0`, the function returns positive infinity.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.pareto1.stdev( 0.8, 1.0 )\n    Infinity\n    > v = base.dists.pareto1.stdev( 4.0, 12.0 )\n    ~5.657\n    > v = base.dists.pareto1.stdev( 8.0, 2.0 )\n    ~0.33\n\n","base.dists.pareto1.variance":"\nbase.dists.pareto1.variance( α, β )\n    Returns the variance of a Pareto (Type I) distribution.\n\n    If `0 < α <= 2` and `β > 0`, the function returns positive infinity.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.pareto1.variance( 0.8, 1.0 )\n    Infinity\n    > v = base.dists.pareto1.variance( 4.0, 12.0 )\n    32.0\n    > v = base.dists.pareto1.variance( 8.0, 2.0 )\n    ~0.109\n\n","base.dists.poisson.cdf":"\nbase.dists.poisson.cdf( x, λ )\n    Evaluates the cumulative distribution function (CDF) for a Poisson\n    distribution with mean parameter `λ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.poisson.cdf( 2.0, 0.5 )\n    ~0.986\n    > y = base.dists.poisson.cdf( 2.0, 10.0 )\n    ~0.003\n    > y = base.dists.poisson.cdf( -1.0, 4.0 )\n    0.0\n    > y = base.dists.poisson.cdf( NaN, 1.0 )\n    NaN\n    > y = base.dists.poisson.cdf( 0.0, NaN )\n    NaN\n\n    // Negative mean parameter:\n    > y = base.dists.poisson.cdf( 2.0, -1.0 )\n    NaN\n\n    // Degenerate distribution at `λ = 0`:\n    > y = base.dists.poisson.cdf( -2.0, 0.0 )\n    0.0\n    > y = base.dists.poisson.cdf( 0.0, 0.0 )\n    1.0\n    > y = base.dists.poisson.cdf( 10.0, 0.0 )\n    1.0\n\n\nbase.dists.poisson.cdf.factory( λ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Poisson distribution with mean parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.poisson.cdf.factory( 5.0 );\n    > var y = mycdf( 3.0 )\n    ~0.265\n    > y = mycdf( 8.0 )\n    ~0.932\n\n","base.dists.poisson.cdf.factory":"\nbase.dists.poisson.cdf.factory( λ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Poisson distribution with mean parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.poisson.cdf.factory( 5.0 );\n    > var y = mycdf( 3.0 )\n    ~0.265\n    > y = mycdf( 8.0 )\n    ~0.932","base.dists.poisson.entropy":"\nbase.dists.poisson.entropy( λ )\n    Returns the entropy of a Poisson distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.poisson.entropy( 11.0 )\n    ~2.61\n    > v = base.dists.poisson.entropy( 4.5 )\n    ~2.149\n\n","base.dists.poisson.kurtosis":"\nbase.dists.poisson.kurtosis( λ )\n    Returns the excess kurtosis of a Poisson distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.poisson.kurtosis( 11.0 )\n    ~0.091\n    > v = base.dists.poisson.kurtosis( 4.5 )\n    ~0.222\n\n","base.dists.poisson.logpmf":"\nbase.dists.poisson.logpmf( x, λ )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    Poisson distribution with mean parameter `λ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPMF.\n\n    Examples\n    --------\n    > var y = base.dists.poisson.logpmf( 4.0, 3.0 )\n    ~-1.784\n    > y = base.dists.poisson.logpmf( 1.0, 3.0 )\n    ~-1.901\n    > y = base.dists.poisson.logpmf( -1.0, 2.0 )\n    -Infinity\n    > y = base.dists.poisson.logpmf( 0.0, NaN )\n    NaN\n    > y = base.dists.poisson.logpmf( NaN, 0.5 )\n    NaN\n\n    // Negative mean parameter:\n    > y = base.dists.poisson.logpmf( 2.0, -0.5 )\n    NaN\n\n    // Degenerate distribution at `λ = 0`:\n    > y = base.dists.poisson.logpmf( 2.0, 0.0 )\n    -Infinity\n    > y = base.dists.poisson.logpmf( 0.0, 0.0 )\n    0.0\n\n\nbase.dists.poisson.logpmf.factory( λ )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a Poisson distribution with mean parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogpmf = base.dists.poisson.logpmf.factory( 1.0 );\n    > var y = mylogpmf( 3.0 )\n    ~-2.792\n    > y = mylogpmf( 1.0 )\n    ~-1.0\n\n","base.dists.poisson.logpmf.factory":"\nbase.dists.poisson.logpmf.factory( λ )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a Poisson distribution with mean parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogpmf = base.dists.poisson.logpmf.factory( 1.0 );\n    > var y = mylogpmf( 3.0 )\n    ~-2.792\n    > y = mylogpmf( 1.0 )\n    ~-1.0","base.dists.poisson.mean":"\nbase.dists.poisson.mean( λ )\n    Returns the expected value of a Poisson distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.poisson.mean( 11.0 )\n    11.0\n    > v = base.dists.poisson.mean( 4.5 )\n    4.5\n\n","base.dists.poisson.median":"\nbase.dists.poisson.median( λ )\n    Returns the median of a Poisson distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: integer\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.poisson.median( 11.0 )\n    11\n    > v = base.dists.poisson.median( 4.5 )\n    4\n\n","base.dists.poisson.mgf":"\nbase.dists.poisson.mgf( x, λ )\n    Evaluates the moment-generating function (MGF) for a Poisson distribution\n    with mean parameter `λ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.poisson.mgf( 1.0, 1.5 )\n    ~13.163\n    > y = base.dists.poisson.mgf( 0.5, 0.5 )\n    ~1.383\n    > y = base.dists.poisson.mgf( NaN, 0.5 )\n    NaN\n    > y = base.dists.poisson.mgf( 0.0, NaN )\n    NaN\n    > y = base.dists.poisson.mgf( -2.0, -1.0 )\n    NaN\n\n\nbase.dists.poisson.mgf.factory( λ )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Poisson distribution with mean parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.poisson.mgf.factory( 2.0 );\n    > var y = myMGF( 0.1 )\n    ~1.234\n\n","base.dists.poisson.mgf.factory":"\nbase.dists.poisson.mgf.factory( λ )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Poisson distribution with mean parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.poisson.mgf.factory( 2.0 );\n    > var y = myMGF( 0.1 )\n    ~1.234","base.dists.poisson.mode":"\nbase.dists.poisson.mode( λ )\n    Returns the mode of a Poisson distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: integer\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.poisson.mode( 11.0 )\n    11\n    > v = base.dists.poisson.mode( 4.5 )\n    4\n\n","base.dists.poisson.pmf":"\nbase.dists.poisson.pmf( x, λ )\n    Evaluates the probability mass function (PMF) for a Poisson\n    distribution with mean parameter `λ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PMF.\n\n    Examples\n    --------\n    > var y = base.dists.poisson.pmf( 4.0, 3.0 )\n    ~0.168\n    > y = base.dists.poisson.pmf( 1.0, 3.0 )\n    ~0.149\n    > y = base.dists.poisson.pmf( -1.0, 2.0 )\n    0.0\n    > y = base.dists.poisson.pmf( 0.0, NaN )\n    NaN\n    > y = base.dists.poisson.pmf( NaN, 0.5 )\n    NaN\n\n    // Negative mean parameter:\n    > y = base.dists.poisson.pmf( 2.0, -0.5 )\n    NaN\n\n    // Degenerate distribution at `λ = 0`:\n    > y = base.dists.poisson.pmf( 2.0, 0.0 )\n    0.0\n    > y = base.dists.poisson.pmf( 0.0, 0.0 )\n    1.0\n\n\nbase.dists.poisson.pmf.factory( λ )\n    Returns a function for evaluating the probability mass function (PMF)\n    of a Poisson distribution with mean parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var mypmf = base.dists.poisson.pmf.factory( 1.0 );\n    > var y = mypmf( 3.0 )\n    ~0.061\n    > y = mypmf( 1.0 )\n    ~0.368\n\n","base.dists.poisson.pmf.factory":"\nbase.dists.poisson.pmf.factory( λ )\n    Returns a function for evaluating the probability mass function (PMF)\n    of a Poisson distribution with mean parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var mypmf = base.dists.poisson.pmf.factory( 1.0 );\n    > var y = mypmf( 3.0 )\n    ~0.061\n    > y = mypmf( 1.0 )\n    ~0.368","base.dists.poisson.Poisson":"\nbase.dists.poisson.Poisson( [λ] )\n    Returns a Poisson distribution object.\n\n    Parameters\n    ----------\n    λ: number (optional)\n        Mean parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    poisson: Object\n        Distribution instance.\n\n    poisson.lambda: number\n        Mean parameter. If set, the value must be greater than `0`.\n\n    poisson.entropy: number\n        Read-only property which returns the differential entropy.\n\n    poisson.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    poisson.mean: number\n        Read-only property which returns the expected value.\n\n    poisson.median: number\n        Read-only property which returns the median.\n\n    poisson.mode: number\n        Read-only property which returns the mode.\n\n    poisson.skewness: number\n        Read-only property which returns the skewness.\n\n    poisson.stdev: number\n        Read-only property which returns the standard deviation.\n\n    poisson.variance: number\n        Read-only property which returns the variance.\n\n    poisson.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    poisson.logpmf: Function\n        Evaluates the natural logarithm of the probability mass function (PMF).\n\n    poisson.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    poisson.pmf: Function\n        Evaluates the probability mass function (PMF).\n\n    poisson.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var poisson = base.dists.poisson.Poisson( 6.0 );\n    > poisson.lambda\n    6.0\n    > poisson.entropy\n    ~2.3\n    > poisson.kurtosis\n    ~0.167\n    > poisson.mean\n    6.0\n    > poisson.median\n    6.0\n    > poisson.mode\n    6.0\n    > poisson.skewness\n    ~0.408\n    > poisson.stdev\n    ~2.449\n    > poisson.variance\n    6.0\n    > poisson.cdf( 4.0 )\n    ~0.285\n    > poisson.logpmf( 2.0 )\n    ~-3.11\n    > poisson.mgf( 0.5 )\n    ~49.025\n    > poisson.pmf( 2.0 )\n    ~0.045\n    > poisson.quantile( 0.5 )\n    6.0\n\n","base.dists.poisson.quantile":"\nbase.dists.poisson.quantile( p, λ )\n    Evaluates the quantile function for a Poisson distribution with mean\n    parameter `λ` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.poisson.quantile( 0.5, 2.0 )\n    2\n    > y = base.dists.poisson.quantile( 0.9, 4.0 )\n    7\n    > y = base.dists.poisson.quantile( 0.1, 200.0 )\n    182\n\n    > y = base.dists.poisson.quantile( 1.1, 0.0 )\n    NaN\n    > y = base.dists.poisson.quantile( -0.2, 0.0 )\n    NaN\n\n    > y = base.dists.poisson.quantile( NaN, 0.5 )\n    NaN\n    > y = base.dists.poisson.quantile( 0.0, NaN )\n    NaN\n\n    // Negative mean parameter:\n    > y = base.dists.poisson.quantile( 2.0, -1.0 )\n    NaN\n\n    // Degenerate distribution at `λ = 0`:\n    > y = base.dists.poisson.quantile( 0.1, 0.0 )\n    0.0\n    > y = base.dists.poisson.quantile( 0.9, 0.0 )\n    0.0\n\n\nbase.dists.poisson.quantile.factory( λ )\n    Returns a function for evaluating the quantile function of a Poisson\n    distribution with mean parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.poisson.quantile.factory( 0.4 );\n    > var y = myQuantile( 0.4 )\n    0.0\n    > y = myQuantile( 1.0 )\n    Infinity\n\n","base.dists.poisson.quantile.factory":"\nbase.dists.poisson.quantile.factory( λ )\n    Returns a function for evaluating the quantile function of a Poisson\n    distribution with mean parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.poisson.quantile.factory( 0.4 );\n    > var y = myQuantile( 0.4 )\n    0.0\n    > y = myQuantile( 1.0 )\n    Infinity","base.dists.poisson.skewness":"\nbase.dists.poisson.skewness( λ )\n    Returns the skewness of a Poisson distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a nonpositive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.poisson.skewness( 11.0 )\n    ~0.302\n    > v = base.dists.poisson.skewness( 4.5 )\n    ~0.471\n\n","base.dists.poisson.stdev":"\nbase.dists.poisson.stdev( λ )\n    Returns the standard deviation of a Poisson distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.poisson.stdev( 11.0 )\n    ~3.317\n    > v = base.dists.poisson.stdev( 4.5 )\n    ~2.121\n\n","base.dists.poisson.variance":"\nbase.dists.poisson.variance( λ )\n    Returns the variance of a Poisson distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.poisson.variance( 11.0 )\n    11.0\n    > v = base.dists.poisson.variance( 4.5 )\n    4.5\n\n","base.dists.rayleigh.cdf":"\nbase.dists.rayleigh.cdf( x, sigma )\n    Evaluates the cumulative distribution function (CDF) for a Rayleigh\n    distribution with scale parameter `sigma` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `sigma`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.rayleigh.cdf( 2.0, 3.0 )\n    ~0.199\n    > y = base.dists.rayleigh.cdf( 1.0, 2.0 )\n    ~0.118\n    > y = base.dists.rayleigh.cdf( -1.0, 4.0 )\n    0.0\n    > y = base.dists.rayleigh.cdf( NaN, 1.0 )\n    NaN\n    > y = base.dists.rayleigh.cdf( 0.0, NaN )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.rayleigh.cdf( 2.0, -1.0 )\n    NaN\n\n    // Degenerate distribution when `sigma = 0.0`:\n    > y = base.dists.rayleigh.cdf( -2.0, 0.0 )\n    0.0\n    > y = base.dists.rayleigh.cdf( 0.0, 0.0 )\n    1.0\n    > y = base.dists.rayleigh.cdf( 2.0, 0.0 )\n    1.0\n\n\nbase.dists.rayleigh.cdf.factory( sigma )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Rayleigh distribution with scale parameter `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.rayleigh.cdf.factory( 0.5 );\n    > var y = myCDF( 1.0 )\n    ~0.865\n    > y = myCDF( 0.5 )\n    ~0.393\n\n","base.dists.rayleigh.cdf.factory":"\nbase.dists.rayleigh.cdf.factory( sigma )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Rayleigh distribution with scale parameter `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.rayleigh.cdf.factory( 0.5 );\n    > var y = myCDF( 1.0 )\n    ~0.865\n    > y = myCDF( 0.5 )\n    ~0.393","base.dists.rayleigh.entropy":"\nbase.dists.rayleigh.entropy( σ )\n    Returns the differential entropy of a Rayleigh distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.rayleigh.entropy( 11.0 )\n    ~3.34\n    > v = base.dists.rayleigh.entropy( 4.5 )\n    ~2.446\n\n","base.dists.rayleigh.kurtosis":"\nbase.dists.rayleigh.kurtosis( σ )\n    Returns the excess kurtosis of a Rayleigh distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.rayleigh.kurtosis( 11.0 )\n    ~0.245\n    > v = base.dists.rayleigh.kurtosis( 4.5 )\n    ~0.245\n\n","base.dists.rayleigh.logcdf":"\nbase.dists.rayleigh.logcdf( x, sigma )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    Rayleigh distribution with scale parameter `sigma` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `sigma`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.rayleigh.logcdf( 2.0, 3.0 )\n    ~-1.613\n    > y = base.dists.rayleigh.logcdf( 1.0, 2.0 )\n    ~-2.141\n    > y = base.dists.rayleigh.logcdf( -1.0, 4.0 )\n    -Infinity\n    > y = base.dists.rayleigh.logcdf( NaN, 1.0 )\n    NaN\n    > y = base.dists.rayleigh.logcdf( 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.rayleigh.logcdf( 2.0, -1.0 )\n    NaN\n\n\nbase.dists.rayleigh.logcdf.factory( sigma )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Rayleigh distribution with scale parameter\n    `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.rayleigh.logcdf.factory( 0.5 );\n    > var y = mylogcdf( 1.0 )\n    ~-0.145\n    > y = mylogcdf( 0.5 )\n    ~-0.933\n\n","base.dists.rayleigh.logcdf.factory":"\nbase.dists.rayleigh.logcdf.factory( sigma )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Rayleigh distribution with scale parameter\n    `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.rayleigh.logcdf.factory( 0.5 );\n    > var y = mylogcdf( 1.0 )\n    ~-0.145\n    > y = mylogcdf( 0.5 )\n    ~-0.933","base.dists.rayleigh.logpdf":"\nbase.dists.rayleigh.logpdf( x, sigma )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    Rayleigh distribution with scale parameter `sigma` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `sigma`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.rayleigh.logpdf( 0.3, 1.0 )\n    ~-1.249\n    > y = base.dists.rayleigh.logpdf( 2.0, 0.8 )\n    ~-1.986\n    > y = base.dists.rayleigh.logpdf( -1.0, 0.5 )\n    -Infinity\n    > y = base.dists.rayleigh.logpdf( 0.0, NaN )\n    NaN\n    > y = base.dists.rayleigh.logpdf( NaN, 2.0 )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.rayleigh.logpdf( 2.0, -1.0 )\n    NaN\n\n\nbase.dists.rayleigh.logpdf.factory( sigma )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Rayleigh distribution with scale parameter `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.rayleigh.logpdf.factory( 4.0 );\n    > var y = mylogpdf( 6.0 )\n    ~-2.106\n    > y = mylogpdf( 4.0 )\n    ~-1.886\n\n","base.dists.rayleigh.logpdf.factory":"\nbase.dists.rayleigh.logpdf.factory( sigma )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Rayleigh distribution with scale parameter `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.rayleigh.logpdf.factory( 4.0 );\n    > var y = mylogpdf( 6.0 )\n    ~-2.106\n    > y = mylogpdf( 4.0 )\n    ~-1.886","base.dists.rayleigh.mean":"\nbase.dists.rayleigh.mean( σ )\n    Returns the expected value of a Rayleigh distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.rayleigh.mean( 11.0 )\n    ~13.786\n    > v = base.dists.rayleigh.mean( 4.5 )\n    ~5.64\n\n","base.dists.rayleigh.median":"\nbase.dists.rayleigh.median( σ )\n    Returns the median of a Rayleigh distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.rayleigh.median( 11.0 )\n    ~12.952\n    > v = base.dists.rayleigh.median( 4.5 )\n    ~5.298\n\n","base.dists.rayleigh.mgf":"\nbase.dists.rayleigh.mgf( t, sigma )\n    Evaluates the moment-generating function (MGF) for a Rayleigh distribution\n    with scale parameter `sigma` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `sigma`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.rayleigh.mgf( 1.0, 3.0 )\n    ~678.508\n    > y = base.dists.rayleigh.mgf( 1.0, 2.0 )\n    ~38.65\n    > y = base.dists.rayleigh.mgf( -1.0, 4.0 )\n    ~-0.947\n    > y = base.dists.rayleigh.mgf( NaN, 1.0 )\n    NaN\n    > y = base.dists.rayleigh.mgf( 0.0, NaN )\n    NaN\n    > y = base.dists.rayleigh.mgf( 0.5, -1.0 )\n    NaN\n\n\nbase.dists.rayleigh.mgf.factory( sigma )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Rayleigh distribution with scale parameter `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.rayleigh.mgf.factory( 0.5 );\n    > var y = myMGF( 1.0 )\n    ~2.715\n    > y = myMGF( 0.5 )\n    ~1.888\n\n","base.dists.rayleigh.mgf.factory":"\nbase.dists.rayleigh.mgf.factory( sigma )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Rayleigh distribution with scale parameter `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.rayleigh.mgf.factory( 0.5 );\n    > var y = myMGF( 1.0 )\n    ~2.715\n    > y = myMGF( 0.5 )\n    ~1.888","base.dists.rayleigh.mode":"\nbase.dists.rayleigh.mode( σ )\n    Returns the mode of a Rayleigh distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.rayleigh.mode( 11.0 )\n    11.0\n    > v = base.dists.rayleigh.mode( 4.5 )\n    4.5\n\n","base.dists.rayleigh.pdf":"\nbase.dists.rayleigh.pdf( x, sigma )\n    Evaluates the probability density function (PDF) for a Rayleigh\n    distribution with scale parameter `sigma` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `sigma`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.rayleigh.pdf( 0.3, 1.0 )\n    ~0.287\n    > y = base.dists.rayleigh.pdf( 2.0, 0.8 )\n    ~0.137\n    > y = base.dists.rayleigh.pdf( -1.0, 0.5 )\n    0.0\n    > y = base.dists.rayleigh.pdf( 0.0, NaN )\n    NaN\n    > y = base.dists.rayleigh.pdf( NaN, 2.0 )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.rayleigh.pdf( 2.0, -1.0 )\n    NaN\n\n    // Degenerate distribution when `sigma = 0.0`:\n    > y = base.dists.rayleigh.pdf( -2.0, 0.0 )\n    0.0\n    > y = base.dists.rayleigh.pdf( 0.0, 0.0 )\n    Infinity\n    > y = base.dists.rayleigh.pdf( 2.0, 0.0 )\n    0.0\n\n\nbase.dists.rayleigh.pdf.factory( sigma )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Rayleigh distribution with scale parameter `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.rayleigh.pdf.factory( 4.0 );\n    > var y = myPDF( 6.0 )\n    ~0.122\n    > y = myPDF( 4.0 )\n    ~0.152\n\n","base.dists.rayleigh.pdf.factory":"\nbase.dists.rayleigh.pdf.factory( sigma )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Rayleigh distribution with scale parameter `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.rayleigh.pdf.factory( 4.0 );\n    > var y = myPDF( 6.0 )\n    ~0.122\n    > y = myPDF( 4.0 )\n    ~0.152","base.dists.rayleigh.quantile":"\nbase.dists.rayleigh.quantile( p, sigma )\n    Evaluates the quantile function for a Rayleigh distribution with scale\n    parameter `sigma` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative probability for `sigma`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.rayleigh.quantile( 0.8, 1.0 )\n    ~1.794\n    > y = base.dists.rayleigh.quantile( 0.5, 4.0 )\n    ~4.71\n\n    > y = base.dists.rayleigh.quantile( 1.1, 1.0 )\n    NaN\n    > y = base.dists.rayleigh.quantile( -0.2, 1.0 )\n    NaN\n\n    > y = base.dists.rayleigh.quantile( NaN, 1.0 )\n    NaN\n    > y = base.dists.rayleigh.quantile( 0.0, NaN )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.rayleigh.quantile( 0.5, -1.0 )\n    NaN\n\n\nbase.dists.rayleigh.quantile.factory( sigma )\n    Returns a function for evaluating the quantile function of a Rayleigh\n    distribution with scale parameter `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.rayleigh.quantile.factory( 0.4 );\n    > var y = myQuantile( 0.4 )\n    ~0.404\n    > y = myQuantile( 1.0 )\n    Infinity\n\n","base.dists.rayleigh.quantile.factory":"\nbase.dists.rayleigh.quantile.factory( sigma )\n    Returns a function for evaluating the quantile function of a Rayleigh\n    distribution with scale parameter `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.rayleigh.quantile.factory( 0.4 );\n    > var y = myQuantile( 0.4 )\n    ~0.404\n    > y = myQuantile( 1.0 )\n    Infinity","base.dists.rayleigh.Rayleigh":"\nbase.dists.rayleigh.Rayleigh( [σ] )\n    Returns a Rayleigh distribution object.\n\n    Parameters\n    ----------\n    σ: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    rayleigh: Object\n        Distribution instance.\n\n    rayleigh.sigma: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    rayleigh.entropy: number\n        Read-only property which returns the differential entropy.\n\n    rayleigh.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    rayleigh.mean: number\n        Read-only property which returns the expected value.\n\n    rayleigh.median: number\n        Read-only property which returns the median.\n\n    rayleigh.mode: number\n        Read-only property which returns the mode.\n\n    rayleigh.skewness: number\n        Read-only property which returns the skewness.\n\n    rayleigh.stdev: number\n        Read-only property which returns the standard deviation.\n\n    rayleigh.variance: number\n        Read-only property which returns the variance.\n\n    rayleigh.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    rayleigh.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    rayleigh.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    rayleigh.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    rayleigh.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    rayleigh.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var rayleigh = base.dists.rayleigh.Rayleigh( 6.0 );\n    > rayleigh.sigma\n    6.0\n    > rayleigh.entropy\n    ~2.734\n    > rayleigh.kurtosis\n    ~0.245\n    > rayleigh.mean\n    ~7.52\n    > rayleigh.median\n    ~7.064\n    > rayleigh.mode\n    6.0\n    > rayleigh.skewness\n    ~0.631\n    > rayleigh.stdev\n    ~3.931\n    > rayleigh.variance\n    ~15.451\n    > rayleigh.cdf( 1.0 )\n    ~0.014\n    > rayleigh.logcdf( 1.0 )\n    ~-4.284\n    > rayleigh.logpdf( 1.5 )\n    ~-3.209\n    > rayleigh.mgf( -0.5 )\n    ~-0.91\n    > rayleigh.pdf( 1.5 )\n    ~0.04\n    > rayleigh.quantile( 0.5 )\n    ~7.064\n\n","base.dists.rayleigh.skewness":"\nbase.dists.rayleigh.skewness( σ )\n    Returns the skewness of a Rayleigh distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.rayleigh.skewness( 11.0 )\n    ~0.631\n    > v = base.dists.rayleigh.skewness( 4.5 )\n    ~0.631\n\n","base.dists.rayleigh.stdev":"\nbase.dists.rayleigh.stdev( σ )\n    Returns the standard deviation of a Rayleigh distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.rayleigh.stdev( 9.0 )\n    ~5.896\n    > v = base.dists.rayleigh.stdev( 4.5 )\n    ~2.948\n\n","base.dists.rayleigh.variance":"\nbase.dists.rayleigh.variance( σ )\n    Returns the variance of a Rayleigh distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.rayleigh.variance( 9.0 )\n    ~34.765\n    > v = base.dists.rayleigh.variance( 4.5 )\n    ~8.691\n\n","base.dists.signrank.cdf":"\nbase.dists.signrank.cdf( x, n )\n    Evaluates the cumulative distribution function (CDF) for the distribution of\n    the Wilcoxon signed rank test statistic with `n` observations.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `x`, the function returns `NaN`.\n\n    If not provided a positive integer for `n`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Number of observations.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.signrank.cdf( 3, 7 )\n    ~0.039\n    > y = base.dists.signrank.cdf( 1.8, 3 )\n    ~0.375\n    > y = base.dists.signrank.cdf( -1.0, 40 )\n    0.0\n    > y = base.dists.signrank.cdf( NaN, 10 )\n    NaN\n    > y = base.dists.signrank.cdf( 0.0, NaN )\n    NaN\n\n\nbase.dists.signrank.cdf.factory( n )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of the distribution of the Wilcoxon signed rank test statistic.\n\n    Parameters\n    ----------\n    n: integer\n        Number of observations.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.signrank.cdf.factory( 8 );\n    > var y = myCDF( 5.7 )\n    ~0.055\n    > y = myCDF( 2.2 )\n    ~0.012\n\n","base.dists.signrank.cdf.factory":"\nbase.dists.signrank.cdf.factory( n )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of the distribution of the Wilcoxon signed rank test statistic.\n\n    Parameters\n    ----------\n    n: integer\n        Number of observations.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.signrank.cdf.factory( 8 );\n    > var y = myCDF( 5.7 )\n    ~0.055\n    > y = myCDF( 2.2 )\n    ~0.012","base.dists.signrank.pdf":"\nbase.dists.signrank.pdf( x, n )\n    Evaluates the probability density function (PDF) for the distribution of\n    the Wilcoxon signed rank test statistic with `n` observations.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `x`, the function returns `NaN`.\n\n    If not provided a positive integer for `n`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Number of observations.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.signrank.pdf( 3, 7 )\n    ~0.0156\n    > y = base.dists.signrank.pdf( 1.8, 3 )\n    0.0\n    > y = base.dists.signrank.pdf( -1.0, 40 )\n    0.0\n    > y = base.dists.signrank.pdf( NaN, 10 )\n    NaN\n    > y = base.dists.signrank.pdf( 0.0, NaN )\n    NaN\n\n\nbase.dists.signrank.pdf.factory( n )\n    Returns a function for evaluating the probability density function (PDF)\n    of the distribution of the Wilcoxon signed rank test statistic.\n\n    Parameters\n    ----------\n    n: integer\n        Number of observations.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.signrank.pdf.factory( 8 );\n    > var y = myPDF( 6.0 )\n    ~0.0156\n    > y = myPDF( 2.0 )\n    ~0.0039\n\n","base.dists.signrank.pdf.factory":"\nbase.dists.signrank.pdf.factory( n )\n    Returns a function for evaluating the probability density function (PDF)\n    of the distribution of the Wilcoxon signed rank test statistic.\n\n    Parameters\n    ----------\n    n: integer\n        Number of observations.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.signrank.pdf.factory( 8 );\n    > var y = myPDF( 6.0 )\n    ~0.0156\n    > y = myPDF( 2.0 )\n    ~0.0039","base.dists.signrank.quantile":"\nbase.dists.signrank.quantile( p, n )\n    Evaluates the quantile function for the Wilcoxon signed rank test statistic\n    with `n` observations at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a positive integer for `n`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    n: integer\n        Number of observations.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.signrank.quantile( 0.8, 5 )\n    11\n    > y = base.dists.signrank.quantile( 0.5, 4 )\n    5\n\n    > y = base.dists.signrank.quantile( 1.1, 5 )\n    NaN\n    > y = base.dists.signrank.quantile( -0.2, 5 )\n    NaN\n\n    > y = base.dists.signrank.quantile( NaN, 5 )\n    NaN\n    > y = base.dists.signrank.quantile( 0.0, NaN )\n    NaN\n\n\nbase.dists.signrank.quantile.factory( n )\n    Returns a function for evaluating the quantile function of the Wilcoxon\n    signed rank test statistic with `n` observations.\n\n    Parameters\n    ----------\n    n: integer\n        Number of observations.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.signrank.quantile.factory( 8 );\n    > var y = myQuantile( 0.4 )\n    16\n    > y = myQuantile( 1.0 )\n    36\n\n","base.dists.signrank.quantile.factory":"\nbase.dists.signrank.quantile.factory( n )\n    Returns a function for evaluating the quantile function of the Wilcoxon\n    signed rank test statistic with `n` observations.\n\n    Parameters\n    ----------\n    n: integer\n        Number of observations.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.signrank.quantile.factory( 8 );\n    > var y = myQuantile( 0.4 )\n    16\n    > y = myQuantile( 1.0 )\n    36","base.dists.studentizedRange.cdf":"\nbase.dists.studentizedRange.cdf( x, r, v[, nranges] )\n    Evaluates the cumulative distribution function (CDF) of a studentized range\n    distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `r < 2` or `v < 2`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    r: number\n        Sample size for range (same for each group).\n\n    v: number\n        Degrees of freedom.\n\n    nranges: integer\n        Number of groups whose maximum range is considered. Default: 1.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.studentizedRange.cdf( 0.5, 3.0, 2.0 )\n    ~0.0644\n\n    > y = base.dists.studentizedRange.cdf( 12.1, 17.0, 2.0 )\n    ~0.913\n\n\nbase.dists.studentizedRange.cdf.factory( r, v[, nranges] )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a studentized range distribution.\n\n    Parameters\n    ----------\n    r: number\n        Number of samples.\n\n    v: number\n        Degrees of freedom.\n\n    nranges: integer\n        Number of groups whose maximum range is considered. Default: 1.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.studentizedRange.cdf.factory( 3.0, 2.0 );\n    > var y = mycdf( 3.0 )\n    ~0.712\n    > y = mycdf( 1.0 )\n    ~0.216\n\n","base.dists.studentizedRange.cdf.factory":"\nbase.dists.studentizedRange.cdf.factory( r, v[, nranges] )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a studentized range distribution.\n\n    Parameters\n    ----------\n    r: number\n        Number of samples.\n\n    v: number\n        Degrees of freedom.\n\n    nranges: integer\n        Number of groups whose maximum range is considered. Default: 1.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.studentizedRange.cdf.factory( 3.0, 2.0 );\n    > var y = mycdf( 3.0 )\n    ~0.712\n    > y = mycdf( 1.0 )\n    ~0.216","base.dists.studentizedRange.quantile":"\nbase.dists.studentizedRange.quantile( p, r, v[, nranges] )\n    Evaluates the quantile function for a studentized range distribution.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `r < 2` or `v < 2`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    r: number\n        Sample size for range (same for each group).\n\n    v: number\n        Degrees of freedom.\n\n    nranges: integer\n        Number of groups whose maximum range is considered. Default: 1.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = quantile( 0.5, 3.0, 2.0 )\n     ~0.0644\n\n    > y = quantile( 0.9, 17.0, 2.0 )\n     ~0.913\n\n    > y = quantile( 0.5, 3.0, 2.0, 2 )\n     ~0.01\n\n    > y = base.dists.studentizedRange.quantile( -0.2, 3.0, 3.0 )\n    NaN\n\n    > y = base.dists.studentizedRange.quantile( NaN, 2.0, 2.0 )\n    NaN\n    > y = base.dists.studentizedRange.quantile( 0.0, NaN, 2.0 )\n    NaN\n\n    > y = base.dists.studentizedRange.quantile( 0.5, -1.0, 2.0 )\n    NaN\n\n\nbase.dists.studentizedRange.quantile.factory( r, v[, nranges] )\n    Returns a function for evaluating the quantile function of a studentized\n    range distribution.\n\n    Parameters\n    ----------\n    r: number\n        Sample size for range (same for each group).\n\n    v: number\n        Degrees of freedom.\n\n    nranges: integer\n        Number of groups whose maximum range is considered. Default: 1.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = quantile.factory( 3.0, 3.0 );\n    > var y = myQuantile( 0.5 )\n   ~1.791\n\n    > y = myQuantile( 0.8 )\n   ~3.245\n\n","base.dists.studentizedRange.quantile.factory":"\nbase.dists.studentizedRange.quantile.factory( r, v[, nranges] )\n    Returns a function for evaluating the quantile function of a studentized\n    range distribution.\n\n    Parameters\n    ----------\n    r: number\n        Sample size for range (same for each group).\n\n    v: number\n        Degrees of freedom.\n\n    nranges: integer\n        Number of groups whose maximum range is considered. Default: 1.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = quantile.factory( 3.0, 3.0 );\n    > var y = myQuantile( 0.5 )\n   ~1.791\n\n    > y = myQuantile( 0.8 )\n   ~3.245","base.dists.t.cdf":"\nbase.dists.t.cdf( x, v )\n    Evaluates the cumulative distribution function (CDF) for a Student's t\n    distribution with degrees of freedom `v` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a non-positive value for `v`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.t.cdf( 2.0, 0.1 )\n    ~0.611\n    > y = base.dists.t.cdf( 1.0, 2.0 )\n    ~0.789\n    > y = base.dists.t.cdf( -1.0, 4.0 )\n    ~0.187\n    > y = base.dists.t.cdf( NaN, 1.0 )\n    NaN\n    > y = base.dists.t.cdf( 0.0, NaN )\n    NaN\n    > y = base.dists.t.cdf( 2.0, -1.0 )\n    NaN\n\n\nbase.dists.t.cdf.factory( v )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Student's t distribution with degrees of freedom `v`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.t.cdf.factory( 0.5 );\n    > var y = mycdf( 3.0 )\n    ~0.816\n    > y = mycdf( 1.0 )\n    ~0.699\n\n","base.dists.t.cdf.factory":"\nbase.dists.t.cdf.factory( v )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Student's t distribution with degrees of freedom `v`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.t.cdf.factory( 0.5 );\n    > var y = mycdf( 3.0 )\n    ~0.816\n    > y = mycdf( 1.0 )\n    ~0.699","base.dists.t.entropy":"\nbase.dists.t.entropy( v )\n    Returns the differential entropy of a Student's t distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `v < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.t.entropy( 11.0 )\n    ~1.512\n    > v = base.dists.t.entropy( 4.5 )\n    ~1.652\n\n","base.dists.t.kurtosis":"\nbase.dists.t.kurtosis( v )\n    Returns the excess kurtosis of a Student's t distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `v <= 2`, the function returns `NaN`.\n\n    If provided `2 < v <= 4`, the function returns positive infinity.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.t.kurtosis( 11.0 )\n    ~0.857\n    > v = base.dists.t.kurtosis( 4.5 )\n    12.0\n\n","base.dists.t.logcdf":"\nbase.dists.t.logcdf( x, v )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a Student's t distribution with degrees of freedom `v` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a non-positive value for `v`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.t.logcdf( 2.0, 0.1 )\n    ~-0.493\n    > y = base.dists.t.logcdf( 1.0, 2.0 )\n    ~-0.237\n    > y = base.dists.t.logcdf( -1.0, 4.0 )\n    ~-1.677\n    > y = base.dists.t.logcdf( NaN, 1.0 )\n    NaN\n    > y = base.dists.t.logcdf( 0.0, NaN )\n    NaN\n    > y = base.dists.t.logcdf( 2.0, -1.0 )\n    NaN\n\n\nbase.dists.t.logcdf.factory( v )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Student's t distribution with degrees of\n    freedom `v`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.t.logcdf.factory( 0.5 );\n    > var y = mylogcdf( 3.0 )\n    ~-0.203\n    > y = mylogcdf( 1.0 )\n    ~-0.358\n\n","base.dists.t.logcdf.factory":"\nbase.dists.t.logcdf.factory( v )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Student's t distribution with degrees of\n    freedom `v`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.t.logcdf.factory( 0.5 );\n    > var y = mylogcdf( 3.0 )\n    ~-0.203\n    > y = mylogcdf( 1.0 )\n    ~-0.358","base.dists.t.logpdf":"\nbase.dists.t.logpdf( x, v )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a Student's t distribution with degrees of freedom `v` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a non-positive value for `v`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.t.logpdf( 0.3, 4.0 )\n    ~-1.036\n    > y = base.dists.t.logpdf( 2.0, 0.7 )\n    ~-2.841\n    > y = base.dists.t.logpdf( -1.0, 0.5 )\n    ~-2.134\n    > y = base.dists.t.logpdf( 0.0, NaN )\n    NaN\n    > y = base.dists.t.logpdf( NaN, 2.0 )\n    NaN\n    > y = base.dists.t.logpdf( 2.0, -1.0 )\n    NaN\n\n\nbase.dists.t.logpdf.factory( v )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a Student's t distribution with degrees of\n    freedom `v`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.t.logpdf.factory( 3.0 );\n    > var y = mylogPDF( 1.0 )\n    ~-1.576\n\n","base.dists.t.logpdf.factory":"\nbase.dists.t.logpdf.factory( v )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a Student's t distribution with degrees of\n    freedom `v`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.t.logpdf.factory( 3.0 );\n    > var y = mylogPDF( 1.0 )\n    ~-1.576","base.dists.t.mean":"\nbase.dists.t.mean( v )\n    Returns the expected value of a Student's t distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `v <= 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.t.mean( 11.0 )\n    0.0\n    > v = base.dists.t.mean( 4.5 )\n    0.0\n\n","base.dists.t.median":"\nbase.dists.t.median( v )\n    Returns the median of a Student's t distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `v < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.t.median( 11.0 )\n    0.0\n    > v = base.dists.t.median( 4.5 )\n    0.0\n\n","base.dists.t.mode":"\nbase.dists.t.mode( v )\n    Returns the mode of a Student's t distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `v < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.t.mode( 11.0 )\n    0.0\n    > v = base.dists.t.mode( 4.5 )\n    0.0\n\n","base.dists.t.pdf":"\nbase.dists.t.pdf( x, v )\n    Evaluates the probability density function (PDF) for a Student's t\n    distribution with degrees of freedom `v` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a non-positive value for `v`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.t.pdf( 0.3, 4.0 )\n    ~0.355\n    > y = base.dists.t.pdf( 2.0, 0.7 )\n    ~0.058\n    > y = base.dists.t.pdf( -1.0, 0.5 )\n    ~0.118\n    > y = base.dists.t.pdf( 0.0, NaN )\n    NaN\n    > y = base.dists.t.pdf( NaN, 2.0 )\n    NaN\n    > y = base.dists.t.pdf( 2.0, -1.0 )\n    NaN\n\n\nbase.dists.t.pdf.factory( v )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Student's t distribution with degrees of freedom `v`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.t.pdf.factory( 3.0 );\n    > var y = myPDF( 1.0 )\n    ~0.207\n\n","base.dists.t.pdf.factory":"\nbase.dists.t.pdf.factory( v )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Student's t distribution with degrees of freedom `v`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.t.pdf.factory( 3.0 );\n    > var y = myPDF( 1.0 )\n    ~0.207","base.dists.t.quantile":"\nbase.dists.t.quantile( p, v )\n    Evaluates the quantile function for a Student's t distribution with degrees\n    of freedom `v` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a non-positive value for `v`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.t.quantile( 0.8, 1.0 )\n    ~1.376\n    > y = base.dists.t.quantile( 0.1, 1.0 )\n    ~-3.078\n    > y = base.dists.t.quantile( 0.5, 0.1 )\n    0.0\n\n    > y = base.dists.t.quantile( -0.2, 0.1 )\n    NaN\n\n    > y = base.dists.t.quantile( NaN, 1.0 )\n    NaN\n    > y = base.dists.t.quantile( 0.0, NaN )\n    NaN\n\n    > y = base.dists.t.quantile( 0.5, -1.0 )\n    NaN\n\n\nbase.dists.t.quantile.factory( v )\n    Returns a function for evaluating the quantile function of a Student's t\n    distribution with degrees of freedom `v`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.t.quantile.factory( 4.0 );\n    > var y = myQuantile( 0.2 )\n    ~-0.941\n    > y = myQuantile( 0.9 )\n    ~1.533\n\n","base.dists.t.quantile.factory":"\nbase.dists.t.quantile.factory( v )\n    Returns a function for evaluating the quantile function of a Student's t\n    distribution with degrees of freedom `v`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.t.quantile.factory( 4.0 );\n    > var y = myQuantile( 0.2 )\n    ~-0.941\n    > y = myQuantile( 0.9 )\n    ~1.533","base.dists.t.skewness":"\nbase.dists.t.skewness( v )\n    Returns the skewness of a Student's t distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `v <= 3`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.t.skewness( 11.0 )\n    0.0\n    > v = base.dists.t.skewness( 4.5 )\n    0.0\n\n","base.dists.t.stdev":"\nbase.dists.t.stdev( v )\n    Returns the standard deviation of a Student's t distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `1 < v <= 2`, the function returns positive infinity.\n\n    If provided `v <= 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.t.stdev( 9.0 )\n    ~1.134\n    > v = base.dists.t.stdev( 4.5 )\n    ~1.342\n\n","base.dists.t.T":"\nbase.dists.t.T( [v] )\n    Returns a Student's t distribution object.\n\n    Parameters\n    ----------\n    v: number (optional)\n        Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    t: Object\n        Distribution instance.\n\n    t.v: number\n        Degrees of freedom. If set, the value must be greater than `0`.\n\n    t.entropy: number\n        Read-only property which returns the differential entropy.\n\n    t.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    t.mean: number\n        Read-only property which returns the expected value.\n\n    t.median: number\n        Read-only property which returns the median.\n\n    t.mode: number\n        Read-only property which returns the mode.\n\n    t.skewness: number\n        Read-only property which returns the skewness.\n\n    t.stdev: number\n        Read-only property which returns the standard deviation.\n\n    t.variance: number\n        Read-only property which returns the variance.\n\n    t.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    t.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    t.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    t.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    t.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var t = base.dists.t.T( 6.0 );\n    > t.v\n    6.0\n    > t.entropy\n    ~1.592\n    > t.kurtosis\n    3.0\n    > t.mean\n    0.0\n    > t.median\n    0.0\n    > t.mode\n    0.0\n    > t.skewness\n    0.0\n    > t.stdev\n    ~1.225\n    > t.variance\n    1.5\n    > t.cdf( 1.0 )\n    ~0.822\n    > t.logcdf( 1.0 )\n    ~-0.196\n    > t.logpdf( 1.5 )\n    ~-2.075\n    > t.pdf( 1.5 )\n    ~0.126\n    > t.quantile( 0.8 )\n    ~0.906\n\n","base.dists.t.variance":"\nbase.dists.t.variance( v )\n    Returns the variance of a Student's t distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `1 < v <= 2`, the function returns positive infinity.\n\n    If provided `v <= 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.t.variance( 9.0 )\n    ~1.286\n    > v = base.dists.t.variance( 4.5 )\n    ~1.8\n\n","base.dists.triangular.cdf":"\nbase.dists.triangular.cdf( x, a, b, c )\n    Evaluates the cumulative distribution function (CDF) for a triangular\n    distribution with minimum support `a`, maximum support `b`, and mode `c` at\n    a value `x`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.0 )\n    0.875\n    > y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.5 )\n    0.75\n    > y = base.dists.triangular.cdf( -10.0, -20.0, 0.0, -2.0 )\n    ~0.278\n    > y = base.dists.triangular.cdf( -2.0, -1.0, 1.0, 0.0 )\n    0.0\n    > y = base.dists.triangular.cdf( NaN, 0.0, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.cdf( 0.0, NaN, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.cdf( 0.0, 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.triangular.cdf( 2.0, 1.0, 0.0, NaN )\n    NaN\n    > y = base.dists.triangular.cdf( 2.0, 1.0, 0.0, 1.5 )\n    NaN\n\n\nbase.dists.triangular.cdf.factory( a, b, c )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a triangular distribution with minimum support `a`, maximum support `b`,\n    and mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.triangular.cdf.factory( 0.0, 10.0, 2.0 );\n    > var y = mycdf( 0.5 )\n    0.0125\n    > y = mycdf( 8.0 )\n    0.95\n\n\n","base.dists.triangular.cdf.factory":"\nbase.dists.triangular.cdf.factory( a, b, c )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a triangular distribution with minimum support `a`, maximum support `b`,\n    and mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.triangular.cdf.factory( 0.0, 10.0, 2.0 );\n    > var y = mycdf( 0.5 )\n    0.0125\n    > y = mycdf( 8.0 )\n    0.95","base.dists.triangular.entropy":"\nbase.dists.triangular.entropy( a, b, c )\n    Returns the differential entropy of a triangular distribution (in nats).\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.triangular.entropy( 0.0, 1.0, 0.8 )\n    ~-0.193\n    > v = base.dists.triangular.entropy( 4.0, 12.0, 5.0 )\n    ~1.886\n    > v = base.dists.triangular.entropy( 2.0, 8.0, 5.0 )\n    ~1.599\n\n","base.dists.triangular.kurtosis":"\nbase.dists.triangular.kurtosis( a, b, c )\n    Returns the excess kurtosis of a triangular distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.triangular.kurtosis( 0.0, 1.0, 0.8 )\n    -0.6\n    > v = base.dists.triangular.kurtosis( 4.0, 12.0, 5.0 )\n    -0.6\n    > v = base.dists.triangular.kurtosis( 2.0, 8.0, 5.0 )\n    -0.6\n\n","base.dists.triangular.logcdf":"\nbase.dists.triangular.logcdf( x, a, b, c )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a triangular distribution with minimum support `a`, maximum\n    support `b`, and mode `c` at a value `x`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.0 )\n    ~-0.134\n    > y = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.5 )\n    ~-0.288\n    > y = base.dists.triangular.logcdf( -10.0, -20.0, 0.0, -2.0 )\n    ~-1.281\n    > y = base.dists.triangular.logcdf( -2.0, -1.0, 1.0, 0.0 )\n    -Infinity\n    > y = base.dists.triangular.logcdf( NaN, 0.0, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.logcdf( 0.0, NaN, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.logcdf( 0.0, 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, NaN )\n    NaN\n    > y = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, 1.5 )\n    NaN\n\n\nbase.dists.triangular.logcdf.factory( a, b, c )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a triangular distribution with minimum\n    support `a`, maximum support `b`, and mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    cdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.triangular.logcdf.factory( 0.0, 10.0, 2.0 );\n    > var y = mylogcdf( 0.5 )\n    ~-4.382\n    > y = mylogcdf( 8.0 )\n    ~-0.051\n\n\n","base.dists.triangular.logcdf.factory":"\nbase.dists.triangular.logcdf.factory( a, b, c )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a triangular distribution with minimum\n    support `a`, maximum support `b`, and mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    cdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.triangular.logcdf.factory( 0.0, 10.0, 2.0 );\n    > var y = mylogcdf( 0.5 )\n    ~-4.382\n    > y = mylogcdf( 8.0 )\n    ~-0.051","base.dists.triangular.logpdf":"\nbase.dists.triangular.logpdf( x, a, b, c )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a triangular distribution with minimum support `a`, maximum support `b`,\n    and mode `c` at a value `x`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.0 )\n    ~-0.693\n    > y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.5 )\n    0.0\n    > y = base.dists.triangular.logpdf( -10.0, -20.0, 0.0, -2.0 )\n    ~-2.89\n    > y = base.dists.triangular.logpdf( -2.0, -1.0, 1.0, 0.0 )\n    -Infinity\n    > y = base.dists.triangular.logpdf( NaN, 0.0, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.logpdf( 0.0, NaN, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.logpdf( 0.0, 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, NaN )\n    NaN\n    > y = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, 1.5 )\n    NaN\n\n\nbase.dists.triangular.logpdf.factory( a, b, c )\n    Returns a function for evaluating the natural logarithm of the  probability\n    density function (PDF) of a triangular distribution with minimum support\n    `a`, maximum support `b`, and mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.triangular.logpdf.factory( 0.0, 10.0, 5.0 );\n    > var y = mylogpdf( 2.0 )\n    ~-2.526\n    > y = mylogpdf( 12.0 )\n    -Infinity\n\n\n","base.dists.triangular.logpdf.factory":"\nbase.dists.triangular.logpdf.factory( a, b, c )\n    Returns a function for evaluating the natural logarithm of the  probability\n    density function (PDF) of a triangular distribution with minimum support\n    `a`, maximum support `b`, and mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.triangular.logpdf.factory( 0.0, 10.0, 5.0 );\n    > var y = mylogpdf( 2.0 )\n    ~-2.526\n    > y = mylogpdf( 12.0 )\n    -Infinity","base.dists.triangular.mean":"\nbase.dists.triangular.mean( a, b, c )\n    Returns the expected value of a triangular distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.triangular.mean( 0.0, 1.0, 0.8 )\n    ~0.6\n    > v = base.dists.triangular.mean( 4.0, 12.0, 5.0 )\n    7.0\n    > v = base.dists.triangular.mean( 2.0, 8.0, 5.0 )\n    5.0\n\n","base.dists.triangular.median":"\nbase.dists.triangular.median( a, b, c )\n    Returns the median of a triangular distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.triangular.median( 0.0, 1.0, 0.8 )\n    ~0.632\n    > v = base.dists.triangular.median( 4.0, 12.0, 5.0 )\n    ~6.708\n    > v = base.dists.triangular.median( 2.0, 8.0, 5.0 )\n    5.0\n\n","base.dists.triangular.mgf":"\nbase.dists.triangular.mgf( t, a, b, c )\n    Evaluates the moment-generating function (MGF) for a triangular distribution\n    with minimum support `a`, maximum support `b`, and mode `c` at a value `t`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.0 )\n    ~1.021\n    > y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.5 )\n    ~1.111\n    > y = base.dists.triangular.mgf( -0.3, -20.0, 0.0, -2.0 )\n    ~24.334\n    > y = base.dists.triangular.mgf( -2.0, -1.0, 1.0, 0.0 )\n    ~1.381\n    > y = base.dists.triangular.mgf( NaN, 0.0, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.mgf( 0.0, NaN, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.mgf( 0.0, 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.triangular.mgf( 0.5, 1.0, 0.0, NaN )\n    NaN\n    > y = base.dists.triangular.mgf( 0.5, 1.0, 0.0, 1.5 )\n    NaN\n\n\nbase.dists.triangular.mgf.factory( a, b, c )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    triangular distribution with minimum support `a`, maximum support `b`, and\n    mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.triangular.mgf.factory( 0.0, 2.0, 1.0 );\n    > var y = mymgf( -1.0 )\n    ~0.3996\n    > y = mymgf( 2.0 )\n    ~10.205\n\n\n","base.dists.triangular.mgf.factory":"\nbase.dists.triangular.mgf.factory( a, b, c )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    triangular distribution with minimum support `a`, maximum support `b`, and\n    mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.triangular.mgf.factory( 0.0, 2.0, 1.0 );\n    > var y = mymgf( -1.0 )\n    ~0.3996\n    > y = mymgf( 2.0 )\n    ~10.205","base.dists.triangular.mode":"\nbase.dists.triangular.mode( a, b, c )\n    Returns the mode of a triangular distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.triangular.mode( 0.0, 1.0, 0.8 )\n    0.8\n    > v = base.dists.triangular.mode( 4.0, 12.0, 5.0 )\n    5.0\n    > v = base.dists.triangular.mode( 2.0, 8.0, 5.0 )\n    5.0\n\n","base.dists.triangular.pdf":"\nbase.dists.triangular.pdf( x, a, b, c )\n    Evaluates the probability density function (PDF) for a triangular\n    distribution with minimum support `a`, maximum support `b`, and mode `c` at\n    a value `x`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.0 )\n    0.5\n    > y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.5 )\n    1.0\n    > y = base.dists.triangular.pdf( -10.0, -20.0, 0.0, -2.0 )\n    ~0.056\n    > y = base.dists.triangular.pdf( -2.0, -1.0, 1.0, 0.0 )\n    0.0\n    > y = base.dists.triangular.pdf( NaN, 0.0, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.pdf( 0.0, NaN, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.pdf( 0.0, 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.triangular.pdf( 2.0, 1.0, 0.0, NaN )\n    NaN\n    > y = base.dists.triangular.pdf( 2.0, 1.0, 0.0, 1.5 )\n    NaN\n\n\nbase.dists.triangular.pdf.factory( a, b, c )\n    Returns a function for evaluating the probability density function (PDF) of\n    a triangular distribution with minimum support `a`, maximum support `b`, and\n    mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var mypdf = base.dists.triangular.pdf.factory( 0.0, 10.0, 5.0 );\n    > var y = mypdf( 2.0 )\n    0.08\n    > y = mypdf( 12.0 )\n    0.0\n\n\n","base.dists.triangular.pdf.factory":"\nbase.dists.triangular.pdf.factory( a, b, c )\n    Returns a function for evaluating the probability density function (PDF) of\n    a triangular distribution with minimum support `a`, maximum support `b`, and\n    mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var mypdf = base.dists.triangular.pdf.factory( 0.0, 10.0, 5.0 );\n    > var y = mypdf( 2.0 )\n    0.08\n    > y = mypdf( 12.0 )\n    0.0","base.dists.triangular.quantile":"\nbase.dists.triangular.quantile( p, a, b, c )\n    Evaluates the quantile function for a triangular distribution with minimum\n    support `a`, maximum support `b`, and mode `c` at a value `x`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.triangular.quantile( 0.9, -1.0, 1.0, 0.0 )\n    ~0.553\n    > y = base.dists.triangular.quantile( 0.1, -1.0, 1.0, 0.5 )\n    ~-0.452\n    > y = base.dists.triangular.quantile( 0.1, -20.0, 0.0, -2.0 )\n    -14.0\n    > y = base.dists.triangular.quantile( 0.8, 0.0, 20.0, 0.0 )\n    ~11.056\n\n    > y = base.dists.triangular.quantile( 1.1, -1.0, 1.0, 0.0 )\n    NaN\n    > y = base.dists.triangular.quantile( -0.1, -1.0, 1.0, 0.0 )\n    NaN\n\n    > y = base.dists.triangular.quantile( NaN, 0.0, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.quantile( 0.3, NaN, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.quantile( 0.3, 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.triangular.quantile( 0.3, 1.0, 0.0, NaN )\n    NaN\n\n    > y = base.dists.triangular.quantile( 0.3, 1.0, 0.0, 1.5 )\n    NaN\n\n\nbase.dists.triangular.quantile.factory( a, b, c )\n    Returns a function for evaluating the quantile function of a triangular\n    distribution with minimum support `a`, maximum support `b`, and mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.triangular.quantile.factory( 2.0, 4.0, 2.5 );\n    > var y = myquantile( 0.4 )\n    ~2.658\n    > y = myquantile( 0.8 )\n    ~3.225\n\n\n","base.dists.triangular.quantile.factory":"\nbase.dists.triangular.quantile.factory( a, b, c )\n    Returns a function for evaluating the quantile function of a triangular\n    distribution with minimum support `a`, maximum support `b`, and mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.triangular.quantile.factory( 2.0, 4.0, 2.5 );\n    > var y = myquantile( 0.4 )\n    ~2.658\n    > y = myquantile( 0.8 )\n    ~3.225","base.dists.triangular.skewness":"\nbase.dists.triangular.skewness( a, b, c )\n    Returns the skewness of a triangular distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.triangular.skewness( 0.0, 1.0, 0.8 )\n    ~-0.476\n    > v = base.dists.triangular.skewness( 4.0, 12.0, 5.0 )\n    ~0.532\n    > v = base.dists.triangular.skewness( 2.0, 8.0, 5.0 )\n    0.0\n\n","base.dists.triangular.stdev":"\nbase.dists.triangular.stdev( a, b, c )\n    Returns the standard deviation of a triangular distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.triangular.stdev( 0.0, 1.0, 0.8 )\n    ~0.216\n    > v = base.dists.triangular.stdev( 4.0, 12.0, 5.0 )\n    ~1.78\n    > v = base.dists.triangular.stdev( 2.0, 8.0, 5.0 )\n    ~1.225\n\n","base.dists.triangular.Triangular":"\nbase.dists.triangular.Triangular( [a, b, c] )\n    Returns a triangular distribution object.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support. Must be smaller than `b` and `c`. Default: `0.0`.\n\n    b: number (optional)\n        Maximum support. Must be greater than `a` and `c`. Default: `1.0`.\n\n    c: number (optional)\n        Mode. Must be greater than `a` and smaller than `b`. Default: `0.5`.\n\n    Returns\n    -------\n    triangular: Object\n        Distribution instance.\n\n    triangular.a: number\n        Minimum support. If set, the value must be smaller or equal to `b` and\n        `c`.\n\n    triangular.b: number\n        Maximum support. If set, the value must be greater than or equal to `a`\n        and `c`.\n\n    triangular.c: number\n        Mode. If set, the value must be greater than or equal to `a` and smaller\n        than or equal to `b`.\n\n    triangular.entropy: number\n        Read-only property which returns the differential entropy.\n\n    triangular.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    triangular.mean: number\n        Read-only property which returns the expected value.\n\n    triangular.median: number\n        Read-only property which returns the median.\n\n    triangular.mode: number\n        Read-only property which returns the mode.\n\n    triangular.skewness: number\n        Read-only property which returns the skewness.\n\n    triangular.stdev: number\n        Read-only property which returns the standard deviation.\n\n    triangular.variance: number\n        Read-only property which returns the variance.\n\n    triangular.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    triangular.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    triangular.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    triangular.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    triangular.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    triangular.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var triangular = base.dists.triangular.Triangular( 0.0, 1.0, 0.5 );\n    > triangular.a\n    0.0\n    > triangular.b\n    1.0\n    > triangular.c\n    0.5\n    > triangular.entropy\n    ~-0.193\n    > triangular.kurtosis\n    -0.6\n    > triangular.mean\n    0.5\n    > triangular.median\n    0.5\n    > triangular.mode\n    0.5\n    > triangular.skewness\n    0.0\n    > triangular.stdev\n    ~0.204\n    > triangular.variance\n    ~0.042\n    > triangular.cdf( 0.8 )\n    0.92\n    > triangular.logcdf( 0.8 )\n    ~-0.083\n    > triangular.logpdf( 0.8 )\n    ~-0.223\n    > triangular.mgf( 0.8 )\n    ~1.512\n    > triangular.pdf( 0.8 )\n    ~0.8\n    > triangular.quantile( 0.8 )\n    ~0.684\n\n","base.dists.triangular.variance":"\nbase.dists.triangular.variance( a, b, c )\n    Returns the variance of a triangular distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.triangular.variance( 0.0, 1.0, 0.8 )\n    ~0.047\n    > v = base.dists.triangular.variance( 4.0, 12.0, 5.0 )\n    ~3.167\n    > v = base.dists.triangular.variance( 2.0, 8.0, 5.0 )\n    ~1.5\n\n","base.dists.uniform.cdf":"\nbase.dists.uniform.cdf( x, a, b )\n    Evaluates the cumulative distribution function (CDF) for a uniform\n    distribution with minimum support `a` and maximum support `b` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.uniform.cdf( 9.0, 0.0, 10.0 )\n    0.9\n    > y = base.dists.uniform.cdf( 0.5, 0.0, 2.0 )\n    0.25\n    > y = base.dists.uniform.cdf( PINF, 2.0, 4.0 )\n    1.0\n    > y = base.dists.uniform.cdf( NINF, 2.0, 4.0 )\n    0.0\n    > y = base.dists.uniform.cdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.uniform.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.uniform.cdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.uniform.cdf( 2.0, 1.0, 0.0 )\n    NaN\n\n\nbase.dists.uniform.cdf.factory( a, b )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a uniform distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.uniform.cdf.factory( 0.0, 10.0 );\n    > var y = mycdf( 0.5 )\n    0.05\n    > y = mycdf( 8.0 )\n    0.8\n\n","base.dists.uniform.cdf.factory":"\nbase.dists.uniform.cdf.factory( a, b )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a uniform distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.uniform.cdf.factory( 0.0, 10.0 );\n    > var y = mycdf( 0.5 )\n    0.05\n    > y = mycdf( 8.0 )\n    0.8","base.dists.uniform.entropy":"\nbase.dists.uniform.entropy( a, b )\n    Returns the differential entropy of a uniform distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Differential entropy.\n\n    Examples\n    --------\n    > var v = base.dists.uniform.entropy( 0.0, 1.0 )\n    0.0\n    > v = base.dists.uniform.entropy( 4.0, 12.0 )\n    ~2.079\n    > v = base.dists.uniform.entropy( 2.0, 8.0 )\n    ~1.792\n\n","base.dists.uniform.kurtosis":"\nbase.dists.uniform.kurtosis( a, b )\n    Returns the excess kurtosis of a uniform distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.uniform.kurtosis( 0.0, 1.0 )\n    -1.2\n    > v = base.dists.uniform.kurtosis( 4.0, 12.0 )\n    -1.2\n    > v = base.dists.uniform.kurtosis( 2.0, 8.0 )\n    -1.2\n\n","base.dists.uniform.logcdf":"\nbase.dists.uniform.logcdf( x, a, b )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    uniform distribution with minimum support `a` and maximum support `b` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.uniform.logcdf( 9.0, 0.0, 10.0 )\n    ~-0.105\n    > y = base.dists.uniform.logcdf( 0.5, 0.0, 2.0 )\n    ~-1.386\n    > y = base.dists.uniform.logcdf( PINF, 2.0, 4.0 )\n    0.0\n    > y = base.dists.uniform.logcdf( NINF, 2.0, 4.0 )\n    -Infinity\n    > y = base.dists.uniform.logcdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.uniform.logcdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.uniform.logcdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.uniform.logcdf( 2.0, 1.0, 0.0 )\n    NaN\n\n\nbase.dists.uniform.logcdf.factory( a, b )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a uniform distribution with minimum support\n    `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.uniform.logcdf.factory( 0.0, 10.0 );\n    > var y = mylogcdf( 0.5 )\n    ~-2.996\n    > y = mylogcdf( 8.0 )\n    ~-0.223\n\n","base.dists.uniform.logcdf.factory":"\nbase.dists.uniform.logcdf.factory( a, b )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a uniform distribution with minimum support\n    `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.uniform.logcdf.factory( 0.0, 10.0 );\n    > var y = mylogcdf( 0.5 )\n    ~-2.996\n    > y = mylogcdf( 8.0 )\n    ~-0.223","base.dists.uniform.logpdf":"\nbase.dists.uniform.logpdf( x, a, b )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    uniform distribution with minimum support `a` and maximum support `b` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.uniform.logpdf( 2.0, 0.0, 4.0 )\n    ~-1.386\n    > y = base.dists.uniform.logpdf( 5.0, 0.0, 4.0 )\n    -infinity\n    > y = base.dists.uniform.logpdf( 0.25, 0.0, 1.0 )\n    0.0\n    > y = base.dists.uniform.logpdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.uniform.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.uniform.logpdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.uniform.logpdf( 2.0, 3.0, 1.0 )\n    NaN\n\n\nbase.dists.uniform.logpdf.factory( a, b )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a uniform distribution with minimum support `a` and\n    maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.uniform.logpdf.factory( 6.0, 7.0 );\n    > var y = mylogPDF( 7.0 )\n    0.0\n    > y = mylogPDF( 5.0 )\n    -infinity\n\n","base.dists.uniform.logpdf.factory":"\nbase.dists.uniform.logpdf.factory( a, b )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a uniform distribution with minimum support `a` and\n    maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.uniform.logpdf.factory( 6.0, 7.0 );\n    > var y = mylogPDF( 7.0 )\n    0.0\n    > y = mylogPDF( 5.0 )\n    -infinity","base.dists.uniform.mean":"\nbase.dists.uniform.mean( a, b )\n    Returns the expected value of a uniform distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.uniform.mean( 0.0, 1.0 )\n    0.5\n    > v = base.dists.uniform.mean( 4.0, 12.0 )\n    8.0\n    > v = base.dists.uniform.mean( 2.0, 8.0 )\n    5.0\n\n","base.dists.uniform.median":"\nbase.dists.uniform.median( a, b )\n    Returns the median of a uniform distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.uniform.median( 0.0, 1.0 )\n    0.5\n    > v = base.dists.uniform.median( 4.0, 12.0 )\n    8.0\n    > v = base.dists.uniform.median( 2.0, 8.0 )\n    5.0\n\n","base.dists.uniform.mgf":"\nbase.dists.uniform.mgf( t, a, b )\n    Evaluates the moment-generating function (MGF) for a uniform\n    distribution with minimum support `a` and maximum support `b` at a value\n    `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.uniform.mgf( 2.0, 0.0, 4.0 )\n    ~372.495\n    > y = base.dists.uniform.mgf( -0.2, 0.0, 4.0 )\n    ~0.688\n    > y = base.dists.uniform.mgf( 2.0, 0.0, 1.0 )\n    ~3.195\n    > y = base.dists.uniform.mgf( 0.5, 3.0, 2.0 )\n    NaN\n    > y = base.dists.uniform.mgf( 0.5, 3.0, 3.0 )\n    NaN\n    > y = base.dists.uniform.mgf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.uniform.mgf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.uniform.mgf( 0.0, 0.0, NaN )\n    NaN\n\n\nbase.dists.uniform.mgf.factory( a, b )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a uniform distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.uniform.mgf.factory( 6.0, 7.0 );\n    > var y = mymgf( 0.1 )\n    ~1.916\n    > y = mymgf( 1.1 )\n    ~1339.321\n\n","base.dists.uniform.mgf.factory":"\nbase.dists.uniform.mgf.factory( a, b )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a uniform distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.uniform.mgf.factory( 6.0, 7.0 );\n    > var y = mymgf( 0.1 )\n    ~1.916\n    > y = mymgf( 1.1 )\n    ~1339.321","base.dists.uniform.pdf":"\nbase.dists.uniform.pdf( x, a, b )\n    Evaluates the probability density function (PDF) for a uniform distribution\n    with minimum support `a` and maximum support `b` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.uniform.pdf( 2.0, 0.0, 4.0 )\n    0.25\n    > y = base.dists.uniform.pdf( 5.0, 0.0, 4.0 )\n    0.0\n    > y = base.dists.uniform.pdf( 0.25, 0.0, 1.0 )\n    1.0\n    > y = base.dists.uniform.pdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.uniform.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.uniform.pdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.uniform.pdf( 2.0, 3.0, 1.0 )\n    NaN\n\n\nbase.dists.uniform.pdf.factory( a, b )\n    Returns a function for evaluating the probability density function (PDF) of\n    a uniform distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.uniform.pdf.factory( 6.0, 7.0 );\n    > var y = myPDF( 7.0 )\n    1.0\n    > y = myPDF( 5.0 )\n    0.0\n\n","base.dists.uniform.pdf.factory":"\nbase.dists.uniform.pdf.factory( a, b )\n    Returns a function for evaluating the probability density function (PDF) of\n    a uniform distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.uniform.pdf.factory( 6.0, 7.0 );\n    > var y = myPDF( 7.0 )\n    1.0\n    > y = myPDF( 5.0 )\n    0.0","base.dists.uniform.quantile":"\nbase.dists.uniform.quantile( p, a, b )\n    Evaluates the quantile function for a uniform distribution with minimum\n    support `a` and maximum support `b` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.uniform.quantile( 0.8, 0.0, 1.0 )\n    0.8\n    > y = base.dists.uniform.quantile( 0.5, 0.0, 10.0 )\n    5.0\n\n    > y = base.dists.uniform.quantile( 1.1, 0.0, 1.0 )\n    NaN\n    > y = base.dists.uniform.quantile( -0.2, 0.0, 1.0 )\n    NaN\n\n    > y = base.dists.uniform.quantile( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.uniform.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.uniform.quantile( 0.0, 0.0, NaN )\n    NaN\n\n    > y = base.dists.uniform.quantile( 0.5, 2.0, 1.0 )\n    NaN\n\n\nbase.dists.uniform.quantile.factory( a, b )\n    Returns a function for evaluating the quantile function of a uniform\n    distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.uniform.quantile.factory( 0.0, 4.0 );\n    > var y = myQuantile( 0.8 )\n    3.2\n\n","base.dists.uniform.quantile.factory":"\nbase.dists.uniform.quantile.factory( a, b )\n    Returns a function for evaluating the quantile function of a uniform\n    distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.uniform.quantile.factory( 0.0, 4.0 );\n    > var y = myQuantile( 0.8 )\n    3.2","base.dists.uniform.skewness":"\nbase.dists.uniform.skewness( a, b )\n    Returns the skewness of a uniform distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.uniform.skewness( 0.0, 1.0 )\n    0.0\n    > v = base.dists.uniform.skewness( 4.0, 12.0 )\n    0.0\n    > v = base.dists.uniform.skewness( 2.0, 8.0 )\n    0.0\n\n","base.dists.uniform.stdev":"\nbase.dists.uniform.stdev( a, b )\n    Returns the standard deviation of a uniform distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.uniform.stdev( 0.0, 1.0 )\n    ~0.289\n    > v = base.dists.uniform.stdev( 4.0, 12.0 )\n    ~2.309\n    > v = base.dists.uniform.stdev( 2.0, 8.0 )\n    ~1.732\n\n","base.dists.uniform.Uniform":"\nbase.dists.uniform.Uniform( [a, b] )\n    Returns a uniform distribution object.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support. Must be smaller than `b`. Default: `0.0`.\n\n    b: number (optional)\n        Maximum support. Must be greater than `a`. Default: `1.0`.\n\n    Returns\n    -------\n    uniform: Object\n        Distribution instance.\n\n    uniform.a: number\n        Minimum support. If set, the value must be smaller than `b`.\n\n    uniform.b: number\n        Maximum support. If set, the value must be greater than `a`.\n\n    uniform.entropy: number\n        Read-only property which returns the differential entropy.\n\n    uniform.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    uniform.mean: number\n        Read-only property which returns the expected value.\n\n    uniform.median: number\n        Read-only property which returns the median.\n\n    uniform.skewness: number\n        Read-only property which returns the skewness.\n\n    uniform.stdev: number\n        Read-only property which returns the standard deviation.\n\n    uniform.variance: number\n        Read-only property which returns the variance.\n\n    uniform.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    uniform.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    uniform.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    uniform.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    uniform.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    uniform.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var uniform = base.dists.uniform.Uniform( 0.0, 1.0 );\n    > uniform.a\n    0.0\n    > uniform.b\n    1.0\n    > uniform.entropy\n    0.0\n    > uniform.kurtosis\n    -1.2\n    > uniform.mean\n    0.5\n    > uniform.median\n    0.5\n    > uniform.skewness\n    0.0\n    > uniform.stdev\n    ~0.289\n    > uniform.variance\n    ~0.083\n    > uniform.cdf( 0.8 )\n    0.8\n    > uniform.logcdf( 0.5 )\n    ~-0.693\n    > uniform.logpdf( 1.0 )\n    ~-0.0\n    > uniform.mgf( 0.8 )\n    ~1.532\n    > uniform.pdf( 0.8 )\n    1.0\n    > uniform.quantile( 0.8 )\n    0.8\n\n","base.dists.uniform.variance":"\nbase.dists.uniform.variance( a, b )\n    Returns the variance of a uniform distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.uniform.variance( 0.0, 1.0 )\n    ~0.083\n    > v = base.dists.uniform.variance( 4.0, 12.0 )\n    ~5.333\n    > v = base.dists.uniform.variance( 2.0, 8.0 )\n    3.0\n\n","base.dists.weibull.cdf":"\nbase.dists.weibull.cdf( x, k, λ )\n    Evaluates the cumulative distribution function (CDF) for a Weibull\n    distribution with shape parameter `k` and scale parameter `λ` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a non-positive value for `λ` or `k`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.weibull.cdf( 2.0, 1.0, 1.0 )\n    ~0.865\n    > y = base.dists.weibull.cdf( -1.0, 2.0, 2.0 )\n    0.0\n    > y = base.dists.weibull.cdf( PINF, 4.0, 2.0 )\n    1.0\n    > y = base.dists.weibull.cdf( NINF, 4.0, 2.0 )\n    0.0\n    > y = base.dists.weibull.cdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.weibull.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.weibull.cdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.weibull.cdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.weibull.cdf.factory( k, λ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.weibull.cdf.factory( 2.0, 10.0 );\n    > var y = myCDF( 12.0 )\n    ~0.763\n\n","base.dists.weibull.cdf.factory":"\nbase.dists.weibull.cdf.factory( k, λ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.weibull.cdf.factory( 2.0, 10.0 );\n    > var y = myCDF( 12.0 )\n    ~0.763","base.dists.weibull.entropy":"\nbase.dists.weibull.entropy( k, λ )\n    Returns the differential entropy of a Weibull distribution (in nats).\n\n    If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n    If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.weibull.entropy( 1.0, 1.0 )\n    1.0\n    > v = base.dists.weibull.entropy( 4.0, 12.0 )\n    ~2.532\n    > v = base.dists.weibull.entropy( 8.0, 2.0 )\n    ~0.119\n\n","base.dists.weibull.kurtosis":"\nbase.dists.weibull.kurtosis( k, λ )\n    Returns the excess kurtosis of a Weibull distribution.\n\n    If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n    If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.weibull.kurtosis( 1.0, 1.0 )\n    6.0\n    > v = base.dists.weibull.kurtosis( 4.0, 12.0 )\n    ~-0.252\n    > v = base.dists.weibull.kurtosis( 8.0, 2.0 )\n    ~0.328\n\n","base.dists.weibull.logcdf":"\nbase.dists.weibull.logcdf( x, k, λ )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.weibull.logcdf( 2.0, 1.0, 1.0 )\n    ~-0.145\n    > y = base.dists.weibull.logcdf( -1.0, 2.0, 2.0 )\n    -Infinity\n    > y = base.dists.weibull.logcdf( PINF, 4.0, 2.0 )\n    0.0\n    > y = base.dists.weibull.logcdf( NINF, 4.0, 2.0 )\n    -Infinity\n    > y = base.dists.weibull.logcdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.weibull.logcdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.weibull.logcdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.weibull.logcdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.weibull.logcdf.factory( k, λ)\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Weibull distribution with scale parameter\n    `λ` and shape parameter `k`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.weibull.logcdf.factory( 2.0, 10.0 );\n    > var y = mylogcdf( 12.0 )\n    ~-0.27\n\n","base.dists.weibull.logcdf.factory":"\nbase.dists.weibull.logcdf.factory( k, λ)\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Weibull distribution with scale parameter\n    `λ` and shape parameter `k`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.weibull.logcdf.factory( 2.0, 10.0 );\n    > var y = mylogcdf( 12.0 )\n    ~-0.27","base.dists.weibull.logpdf":"\nbase.dists.weibull.logpdf( x, k, λ )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.weibull.logpdf( 2.0, 1.0, 0.5 )\n    ~-3.307\n    > y = base.dists.weibull.logpdf( 0.1, 1.0, 1.0 )\n    ~-0.1\n    > y = base.dists.weibull.logpdf( -1.0, 4.0, 2.0 )\n    -Infinity\n    > y = base.dists.weibull.logpdf( NaN, 0.6, 1.0 )\n    NaN\n    > y = base.dists.weibull.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.weibull.logpdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.weibull.logpdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.weibull.logpdf.factory( k, λ )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Weibull distribution with shape parameter `k` and scale\n    parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylofpdf = base.dists.weibull.logpdf.factory( 7.0, 6.0 );\n    > y = mylofpdf( 7.0 )\n    ~-1.863\n\n","base.dists.weibull.logpdf.factory":"\nbase.dists.weibull.logpdf.factory( k, λ )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Weibull distribution with shape parameter `k` and scale\n    parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylofpdf = base.dists.weibull.logpdf.factory( 7.0, 6.0 );\n    > y = mylofpdf( 7.0 )\n    ~-1.863","base.dists.weibull.mean":"\nbase.dists.weibull.mean( k, λ )\n    Returns the expected value of a Weibull distribution.\n\n    If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n    If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.weibull.mean( 1.0, 1.0 )\n    1.0\n    > v = base.dists.weibull.mean( 4.0, 12.0 )\n    ~10.877\n    > v = base.dists.weibull.mean( 8.0, 2.0 )\n    ~1.883\n\n","base.dists.weibull.median":"\nbase.dists.weibull.median( k, λ )\n    Returns the median of a Weibull distribution.\n\n    If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n    If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.weibull.median( 1.0, 1.0 )\n    ~0.693\n    > v = base.dists.weibull.median( 4.0, 12.0 )\n    ~10.949\n    > v = base.dists.weibull.median( 8.0, 2.0 )\n    ~1.91\n\n","base.dists.weibull.mgf":"\nbase.dists.weibull.mgf( x, k, λ )\n    Evaluates the moment-generating function (MGF) for a Weibull distribution\n    with shape parameter `k` and scale parameter `λ` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a non-positive value for `λ` or `k`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.weibull.mgf( 1.0, 1.0, 0.5 )\n    ~2.0\n    > y = base.dists.weibull.mgf( -1.0, 4.0, 4.0 )\n    ~0.019\n\n    > y = base.dists.weibull.mgf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.weibull.mgf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.weibull.mgf( 0.0, 1.0, NaN )\n    NaN\n\n    > y = base.dists.weibull.mgf( 0.2, -1.0, 0.5 )\n    NaN\n    > y = base.dists.weibull.mgf( 0.2, 0.0, 0.5 )\n    NaN\n\n    > y = base.dists.weibull.mgf( 0.2, 0.5, -1.0 )\n    NaN\n    > y = base.dists.weibull.mgf( 0.2, 0.5, 0.0 )\n    NaN\n\n\nbase.dists.weibull.mgf.factory( k, λ )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.weibull.mgf.factory( 8.0, 10.0 );\n    > var y = myMGF( 0.8 )\n    ~3150.149\n    > y = myMGF( 0.08 )\n    ~2.137\n\n","base.dists.weibull.mgf.factory":"\nbase.dists.weibull.mgf.factory( k, λ )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.weibull.mgf.factory( 8.0, 10.0 );\n    > var y = myMGF( 0.8 )\n    ~3150.149\n    > y = myMGF( 0.08 )\n    ~2.137","base.dists.weibull.mode":"\nbase.dists.weibull.mode( k, λ )\n    Returns the mode of a Weibull distribution.\n\n    If `0 < k <= 1`, the function returns `0.0`.\n\n    If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n    If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.weibull.mode( 1.0, 1.0 )\n    0.0\n    > v = base.dists.weibull.mode( 4.0, 12.0 )\n    ~11.167\n    > v = base.dists.weibull.mode( 8.0, 2.0 )\n    ~1.967\n\n","base.dists.weibull.pdf":"\nbase.dists.weibull.pdf( x, k, λ )\n    Evaluates the probability density function (PDF) for a Weibull distribution\n    with shape parameter `k` and scale parameter `λ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.weibull.pdf( 2.0, 1.0, 0.5 )\n    ~0.037\n    > y = base.dists.weibull.pdf( 0.1, 1.0, 1.0 )\n    ~0.905\n    > y = base.dists.weibull.pdf( -1.0, 4.0, 2.0 )\n    0.0\n    > y = base.dists.weibull.pdf( NaN, 0.6, 1.0 )\n    NaN\n    > y = base.dists.weibull.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.weibull.pdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.weibull.pdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.weibull.pdf.factory( k, λ )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.weibull.pdf.factory( 7.0, 6.0 );\n    > var y = myPDF( 7.0 )\n    ~0.155\n\n","base.dists.weibull.pdf.factory":"\nbase.dists.weibull.pdf.factory( k, λ )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.weibull.pdf.factory( 7.0, 6.0 );\n    > var y = myPDF( 7.0 )\n    ~0.155","base.dists.weibull.quantile":"\nbase.dists.weibull.quantile( p, k, λ )\n    Evaluates the quantile function for a Weibull distribution with scale\n    parameter `k` and shape parameter `λ` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.weibull.quantile( 0.8, 1.0, 1.0 )\n    ~1.609\n    > y = base.dists.weibull.quantile( 0.5, 2.0, 4.0 )\n    ~3.33\n\n    > y = base.dists.weibull.quantile( 1.1, 1.0, 1.0 )\n    NaN\n    > y = base.dists.weibull.quantile( -0.2, 1.0, 1.0 )\n    NaN\n\n    > y = base.dists.weibull.quantile( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.weibull.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.weibull.quantile( 0.0, 0.0, NaN )\n    NaN\n\n    > y = base.dists.weibull.quantile( 0.5, 1.0, -1.0 )\n    NaN\n\n\nbase.dists.weibull.quantile.factory( k, λ )\n    Returns a function for evaluating the quantile function of a Weibull\n    distribution with scale parameter `k` and shape parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.weibull.quantile.factory( 2.0, 10.0 );\n    > var y = myQuantile( 0.4 )\n    ~7.147\n\n","base.dists.weibull.quantile.factory":"\nbase.dists.weibull.quantile.factory( k, λ )\n    Returns a function for evaluating the quantile function of a Weibull\n    distribution with scale parameter `k` and shape parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.weibull.quantile.factory( 2.0, 10.0 );\n    > var y = myQuantile( 0.4 )\n    ~7.147","base.dists.weibull.skewness":"\nbase.dists.weibull.skewness( k, λ )\n    Returns the skewness of a Weibull distribution.\n\n    If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n    If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.weibull.skewness( 1.0, 1.0 )\n    2.0\n    > v = base.dists.weibull.skewness( 4.0, 12.0 )\n    ~-0.087\n    > v = base.dists.weibull.skewness( 8.0, 2.0 )\n    ~-0.534\n\n","base.dists.weibull.stdev":"\nbase.dists.weibull.stdev( k, λ )\n    Returns the standard deviation of a Weibull distribution.\n\n    If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n    If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.weibull.stdev( 1.0, 1.0 )\n    1.0\n    > v = base.dists.weibull.stdev( 4.0, 12.0 )\n    ~3.051\n    > v = base.dists.weibull.stdev( 8.0, 2.0 )\n    ~0.279\n\n","base.dists.weibull.variance":"\nbase.dists.weibull.variance( k, λ )\n    Returns the variance of a Weibull distribution.\n\n    If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n    If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.weibull.variance( 1.0, 1.0 )\n    1.0\n    > v = base.dists.weibull.variance( 4.0, 12.0 )\n    ~9.311\n    > v = base.dists.weibull.variance( 8.0, 2.0 )\n    ~0.078\n\n","base.dists.weibull.Weibull":"\nbase.dists.weibull.Weibull( [k, λ] )\n    Returns a Weibull distribution object.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n    λ: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    weibull: Object\n        Distribution instance.\n\n    weibull.k: number\n        Shape parameter. If set, the value must be greater than `0`.\n\n    weibull.lambda: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    weibull.entropy: number\n        Read-only property which returns the differential entropy.\n\n    weibull.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    weibull.mean: number\n        Read-only property which returns the expected value.\n\n    weibull.median: number\n        Read-only property which returns the median.\n\n    weibull.mode: number\n        Read-only property which returns the mode.\n\n    weibull.skewness: number\n        Read-only property which returns the skewness.\n\n    weibull.stdev: number\n        Read-only property which returns the standard deviation.\n\n    weibull.variance: number\n        Read-only property which returns the variance.\n\n    weibull.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    weibull.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    weibull.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    weibull.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    weibull.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    weibull.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var weibull = base.dists.weibull.Weibull( 6.0, 5.0 );\n    > weibull.k\n    6.0\n    > weibull.lambda\n    5.0\n    > weibull.entropy\n    ~1.299\n    > weibull.kurtosis\n    ~0.035\n    > weibull.mean\n    ~4.639\n    > weibull.median\n    ~4.704\n    > weibull.mode\n    ~4.85\n    > weibull.skewness\n    ~-0.373\n    > weibull.stdev\n    ~0.899\n    > weibull.variance\n    ~0.808\n    > weibull.cdf( 3.0 )\n    ~0.046\n    > weibull.logcdf( 3.0 )\n    ~-3.088\n    > weibull.logpdf( 1.0 )\n    ~-7.865\n    > weibull.mgf( -0.5 )\n    ~0.075\n    > weibull.pdf( 3.0 )\n    ~0.089\n    > weibull.quantile( 0.8 )\n    ~5.413\n\n","base.ellipe":"\nbase.ellipe( m )\n    Computes the complete elliptic integral of the second kind.\n\n    Parameters\n    ----------\n    m: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.ellipe( 0.5 )\n    ~1.351\n    > y = base.ellipe( -1.0 )\n    ~1.910\n    > y = base.ellipe( 2.0 )\n    NaN\n    > y = base.ellipe( PINF )\n    NaN\n    > y = base.ellipe( NINF )\n    NaN\n    > y = base.ellipe( NaN )\n    NaN\n\n    See Also\n    --------\n    base.ellipj, base.ellipk\n","base.ellipj":"\nbase.ellipj( u, m )\n    Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n    amplitude am.\n\n    Parameters\n    ----------\n    u: number\n        Input value.\n\n    m: number\n        Modulus m, equivalent to k².\n\n    Returns\n    -------\n    out: Array\n        Jacobi elliptic functions and Jacobi amplitude.\n\n    Examples\n    --------\n    > var v = base.ellipj( 0.3, 0.5 )\n    [ ~0.293, ~0.956, ~0.978, ~0.298 ]\n    > v = base.ellipj( 0.0, 0.0 )\n    [ ~0.0, ~1.0, ~1.0, ~0.0 ]\n    > v = base.ellipj( Infinity, 1.0 )\n    [ ~1.0, ~0.0, ~0.0, ~1.571 ]\n    > v = base.ellipj( 0.0, -2.0)\n    [ ~0.0, ~1.0, ~1.0, NaN ]\n    > v = base.ellipj( NaN, NaN )\n    [ NaN, NaN, NaN, NaN ]\n\n\nbase.ellipj.assign( u, m, out, stride, offset )\n    Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n    amplitude am and assigns results to a provided output array.\n\n    Parameters\n    ----------\n    u: number\n        Input value.\n\n    m: number\n        Modulus m, equivalent to k².\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Jacobi elliptic functions and Jacobi amplitude.\n\n    Examples\n    --------\n    > var out = new Float64Array( 4 );\n    > var v = base.ellipj.assign( 0.3, 0.5, out, 1, 0 )\n    <Float64Array>[ ~0.293, ~0.956, ~0.978, ~0.298 ]\n    > var bool = ( v === out )\n    true\n\n\nbase.ellipj.sn( u, m )\n    Computes the Jacobi elliptic function sn.\n\n    Parameters\n    ----------\n    u: number\n        Input value.\n\n    m: number\n        Modulus m, equivalent to k².\n\n    Returns\n    -------\n    out: number\n        Jacobi elliptic function sn.\n\n    Examples\n    --------\n    > var v = base.ellipj.sn( 0.3, 0.5 )\n    ~0.293\n\n\nbase.ellipj.cn( u, m )\n    Computes the Jacobi elliptic functions cn.\n\n    Parameters\n    ----------\n    u: number\n        Input value.\n\n    m: number\n        Modulus m, equivalent to k².\n\n    Returns\n    -------\n    out: number\n        Jacobi elliptic function cn.\n\n    Examples\n    --------\n    > var v = base.ellipj.cn( 0.3, 0.5 )\n    ~0.956\n\n\nbase.ellipj.dn( u, m )\n    Computes the Jacobi elliptic function dn.\n\n    Parameters\n    ----------\n    u: number\n        Input value.\n\n    m: number\n        Modulus m, equivalent to k².\n\n    Returns\n    -------\n    out: number\n        Jacobi elliptic function dn.\n\n    Examples\n    --------\n    > var v = base.ellipj.dn( 0.3, 0.5 )\n    ~0.978\n\n\nbase.ellipj.am( u, m )\n    Computes the Jacobi amplitude am.\n\n    Parameters\n    ----------\n    u: number\n        Input value.\n\n    m: number\n        Modulus m, equivalent to k².\n\n    Returns\n    -------\n    out: number\n        Jacobi elliptic function am.\n\n    Examples\n    --------\n    > var v = base.ellipj.am( 0.3, 0.5 )\n    ~0.298\n\n    See Also\n    --------\n    base.ellipe, base.ellipk","base.ellipj.assign":"\nbase.ellipj.assign( u, m, out, stride, offset )\n    Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n    amplitude am and assigns results to a provided output array.\n\n    Parameters\n    ----------\n    u: number\n        Input value.\n\n    m: number\n        Modulus m, equivalent to k².\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Jacobi elliptic functions and Jacobi amplitude.\n\n    Examples\n    --------\n    > var out = new Float64Array( 4 );\n    > var v = base.ellipj.assign( 0.3, 0.5, out, 1, 0 )\n    <Float64Array>[ ~0.293, ~0.956, ~0.978, ~0.298 ]\n    > var bool = ( v === out )\n    true","base.ellipj.sn":"\nbase.ellipj.sn( u, m )\n    Computes the Jacobi elliptic function sn.\n\n    Parameters\n    ----------\n    u: number\n        Input value.\n\n    m: number\n        Modulus m, equivalent to k².\n\n    Returns\n    -------\n    out: number\n        Jacobi elliptic function sn.\n\n    Examples\n    --------\n    > var v = base.ellipj.sn( 0.3, 0.5 )\n    ~0.293","base.ellipj.cn":"\nbase.ellipj.cn( u, m )\n    Computes the Jacobi elliptic functions cn.\n\n    Parameters\n    ----------\n    u: number\n        Input value.\n\n    m: number\n        Modulus m, equivalent to k².\n\n    Returns\n    -------\n    out: number\n        Jacobi elliptic function cn.\n\n    Examples\n    --------\n    > var v = base.ellipj.cn( 0.3, 0.5 )\n    ~0.956","base.ellipj.dn":"\nbase.ellipj.dn( u, m )\n    Computes the Jacobi elliptic function dn.\n\n    Parameters\n    ----------\n    u: number\n        Input value.\n\n    m: number\n        Modulus m, equivalent to k².\n\n    Returns\n    -------\n    out: number\n        Jacobi elliptic function dn.\n\n    Examples\n    --------\n    > var v = base.ellipj.dn( 0.3, 0.5 )\n    ~0.978","base.ellipj.am":"\nbase.ellipj.am( u, m )\n    Computes the Jacobi amplitude am.\n\n    Parameters\n    ----------\n    u: number\n        Input value.\n\n    m: number\n        Modulus m, equivalent to k².\n\n    Returns\n    -------\n    out: number\n        Jacobi elliptic function am.\n\n    Examples\n    --------\n    > var v = base.ellipj.am( 0.3, 0.5 )\n    ~0.298\n\n    See Also\n    --------\n    base.ellipe, base.ellipk","base.ellipk":"\nbase.ellipk( m )\n    Computes the complete elliptic integral of the first kind.\n\n    Parameters\n    ----------\n    m: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.ellipk( 0.5 )\n    ~1.854\n    > y = base.ellipk( -1.0 )\n    ~1.311\n    > y = base.ellipk( 2.0 )\n    NaN\n    > y = base.ellipk( PINF )\n    NaN\n    > y = base.ellipk( NINF )\n    NaN\n    > y = base.ellipk( NaN )\n    NaN\n\n    See Also\n    --------\n    base.ellipe, base.ellipj\n","base.endsWith":"\nbase.endsWith( str, search, len )\n    Tests if a string ends with the characters of another string.\n\n    If provided an empty search string, the function always returns `true`.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search string.\n\n    len: integer\n        Substring length. Restricts the search to a substring within the input\n        string beginning from the leftmost character. If provided a negative\n        value, `len` indicates to ignore the last `len` characters, and is thus\n        equivalent to `str.length + len`. Default: str.length.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a string ends with the characters of another\n        string.\n\n    Examples\n    --------\n    > var bool = base.endsWith( 'beep', 'ep', 4 )\n    true\n    > bool = base.endsWith( 'Beep', 'op', 4 )\n    false\n    > bool = base.endsWith( 'Beep', 'ee', 3 )\n    true\n    > bool = base.endsWith( 'Beep', 'ee', -1 )\n    true\n    > bool = base.endsWith( 'beep', '', 4 )\n    true\n\n    See Also\n    --------\n    base.startsWith\n","base.epsdiff":"\nbase.epsdiff( x, y[, scale] )\n    Computes the relative difference of two real numbers in units of double-\n    precision floating-point epsilon.\n\n    By default, the function scales the absolute difference by dividing the\n    absolute difference by the maximum absolute value of `x` and `y`. To scale\n    by a different function, specify a scale function name.\n\n    The following `scale` functions are supported:\n\n    - 'max-abs': maximum absolute value of `x` and `y` (default).\n    - 'max': maximum value of `x` and `y`.\n    - 'min-abs': minimum absolute value of `x` and `y`.\n    - 'min': minimum value of `x` and `y`.\n    - 'mean-abs': arithmetic mean of the absolute values of `x` and `y`.\n    - 'mean': arithmetic mean of `x` and `y`.\n    - 'x': `x` (*noncommutative*).\n    - 'y': `y` (*noncommutative*).\n\n    To use a custom scale function, provide a function which accepts two numeric\n    arguments `x` and `y`.\n\n    If computing the relative difference in units of epsilon will result in\n    overflow, the function returns the maximum double-precision floating-point\n    number.\n\n    If the absolute difference of `x` and `y` is `0`, the relative difference is\n    always `0`.\n\n    If `|x| = |y| = infinity`, the function returns `NaN`.\n\n    If `|x| = |-y| = infinity`, the relative difference is `+infinity`.\n\n    If a `scale` function returns `0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    scale: string|Function (optional)\n        Scale function. Default: `'max-abs'`.\n\n    Returns\n    -------\n    out: number\n        Relative difference in units of double-precision floating-point epsilon.\n\n    Examples\n    --------\n    > var d = base.epsdiff( 12.15, 12.149999999999999 )\n    ~0.658\n    > d = base.epsdiff( 2.4341309458983933, 2.4341309458633909, 'mean-abs' )\n    ~64761.512\n\n    // Custom scale function:\n    > function scale( x, y ) { return ( x > y ) ? y : x; };\n    > d = base.epsdiff( 1.0000000000000002, 1.0000000000000100, scale )\n    ~44\n\n    See Also\n    --------\n    base.absdiff, base.reldiff\n","base.erf":"\nbase.erf( x )\n    Evaluates the error function.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    As the error function is an odd function (i.e., `erf(-x) == -erf(x)`), if\n    provided `-0`, the function returns `-0`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.erf( 2.0 )\n    ~0.9953\n    > y = base.erf( -1.0 )\n    ~-0.8427\n    > y = base.erf( -0.0 )\n    -0.0\n    > y = base.erf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.erfc, base.erfinv, base.erfcinv\n","base.erfc":"\nbase.erfc( x )\n    Evaluates the complementary error function.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.erfc( 2.0 )\n    ~0.0047\n    > y = base.erfc( -1.0 )\n    ~1.8427\n    > y = base.erfc( 0.0 )\n    1.0\n    > y = base.erfc( PINF )\n    0.0\n    > y = base.erfc( NINF )\n    2.0\n    > y = base.erfc( NaN )\n    NaN\n\n    See Also\n    --------\n    base.erf, base.erfinv, base.erfcinv, base.erfcx\n","base.erfcinv":"\nbase.erfcinv( x )\n    Evaluates the inverse complementary error function.\n\n    The domain of `x` is restricted to `[0,2]`. If `x` is outside this interval,\n    the function returns `NaN`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.erfcinv( 0.5 )\n    ~0.4769\n    > y = base.erfcinv( 0.8 )\n    ~0.1791\n    > y = base.erfcinv( 0.0 )\n    Infinity\n    > y = base.erfcinv( 2.0 )\n    -Infinity\n    > y = base.erfcinv( NaN )\n    NaN\n\n    See Also\n    --------\n    base.erf, base.erfc, base.erfinv, base.erfcx\n","base.erfcx":"\nbase.erfcx( x )\n    Evaluates the scaled complementary error function.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.erfcx( 1.0 )\n    ~0.4276\n    > y = base.erfcx( -1.0 )\n    ~5.01\n    > y = base.erfcx( 0.0 )\n    1.0\n    > y = base.erfcx( NaN )\n    NaN\n\n    See Also\n    --------\n    base.erfc, base.erfcinv, base.erf, base.erfinv","base.erfinv":"\nbase.erfinv( x )\n    Evaluates the inverse error function.\n\n    If `|x| > 1`, the function returns `NaN`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    As the inverse error function is an odd function (i.e., `erfinv(-x) ==\n    -erfinv(x)`), if provided `-0`, the function returns `-0`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.erfinv( 0.5 )\n    ~0.4769\n    > y = base.erfinv( 0.8 )\n    ~0.9062\n    > y = base.erfinv( 0.0 )\n    0.0\n    > y = base.erfinv( -0.0 )\n    -0.0\n    > y = base.erfinv( -1.0 )\n    -Infinity\n    > y = base.erfinv( 1.0 )\n    Infinity\n    > y = base.erfinv( NaN )\n    NaN\n\n    See Also\n    --------\n    base.erf, base.erfc, base.erfcinv\n","base.eta":"\nbase.eta( s )\n    Evaluates the Dirichlet eta function for a double-precision\n    floating-point number `s`.\n\n    Parameters\n    ----------\n    s: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.eta( 0.0 )\n    0.5\n    > y = base.eta( -1.0 )\n    0.25\n    > y = base.eta( 1.0 )\n    ~0.6931\n    > y = base.eta( 3.14 )\n    ~0.9096\n    > y = base.eta( NaN )\n    NaN\n\n","base.evalpoly":"\nbase.evalpoly( c, x )\n    Evaluates a polynomial using double-precision floating-point arithmetic.\n\n    Parameters\n    ----------\n    c: Array<number>\n        Polynomial coefficients sorted in ascending degree.\n\n    x: number\n        Value at which to evaluate the polynomial.\n\n    Returns\n    -------\n    out: number\n        Evaluated polynomial.\n\n    Examples\n    --------\n    > var arr = [ 3.0, 2.0, 1.0 ];\n\n    // 3*10^0 + 2*10^1 + 1*10^2\n    > var v = base.evalpoly( arr, 10.0 )\n    123.0\n\n\nbase.evalpoly.factory( c )\n    Returns a function for evaluating a polynomial using double-precision\n    floating-point arithmetic.\n\n    Parameters\n    ----------\n    c: Array<number>\n        Polynomial coefficients sorted in ascending degree.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a polynomial.\n\n    Examples\n    --------\n    > var f = base.evalpoly.factory( [ 3.0, 2.0, 1.0 ] );\n\n    // 3*10^0 + 2*10^1 + 1*10^2\n    > var v = f( 10.0 )\n    123.0\n\n    // 3*5^0 + 2*5^1 + 1*5^2\n    > v = f( 5.0 )\n    38.0\n\n    See Also\n    --------\n    base.evalrational\n","base.evalpoly.factory":"\nbase.evalpoly.factory( c )\n    Returns a function for evaluating a polynomial using double-precision\n    floating-point arithmetic.\n\n    Parameters\n    ----------\n    c: Array<number>\n        Polynomial coefficients sorted in ascending degree.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a polynomial.\n\n    Examples\n    --------\n    > var f = base.evalpoly.factory( [ 3.0, 2.0, 1.0 ] );\n\n    // 3*10^0 + 2*10^1 + 1*10^2\n    > var v = f( 10.0 )\n    123.0\n\n    // 3*5^0 + 2*5^1 + 1*5^2\n    > v = f( 5.0 )\n    38.0\n\n    See Also\n    --------\n    base.evalrational","base.evalrational":"\nbase.evalrational( P, Q, x )\n    Evaluates a rational function using double-precision floating-point\n    arithmetic.\n\n    A rational function `f(x)` is defined as\n\n               P(x)\n        f(x) = ----\n               Q(x)\n\n    where both `P(x)` and `Q(x)` are polynomials in `x`.\n\n    The coefficients for both `P` and `Q` should be sorted in ascending degree.\n\n    For polynomials of different degree, the coefficient array for the lower\n    degree polynomial should be padded with zeros.\n\n    Parameters\n    ----------\n    P: Array<number>\n        Numerator polynomial coefficients sorted in ascending degree.\n\n    Q: Array<number>\n        Denominator polynomial coefficients sorted in ascending degree.\n\n    x: number\n        Value at which to evaluate the rational function.\n\n    Returns\n    -------\n    out: number\n        Evaluated rational function.\n\n    Examples\n    --------\n    // 2x^3 + 4x^2 - 5x^1 - 6x^0\n    > var P = [ -6.0, -5.0, 4.0, 2.0 ];\n\n    // 0.5x^1 + 3x^0\n    > var Q = [ 3.0, 0.5, 0.0, 0.0 ]; // zero-padded\n\n    // Evaluate the rational function:\n    > var v = base.evalrational( P, Q, 6.0 )\n    90.0\n\n\nbase.evalrational.factory( P, Q )\n    Returns a function for evaluating a rational function using double-precision\n    floating-point arithmetic.\n\n    Parameters\n    ----------\n    P: Array<number>\n        Numerator polynomial coefficients sorted in ascending degree.\n\n    Q: Array<number>\n        Denominator polynomial coefficients sorted in ascending degree.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a rational function.\n\n    Examples\n    --------\n    > var P = [ 20.0, 8.0, 3.0 ];\n    > var Q = [ 10.0, 9.0, 1.0 ];\n    > var f = base.evalrational.factory( P, Q );\n\n    // (20*10^0 + 8*10^1 + 3*10^2) / (10*10^0 + 9*10^1 + 1*10^2):\n    > var v = f( 10.0 )\n    2.0\n\n    // (20*2^0 + 8*2^1 + 3*2^2) / (10*2^0 + 9*2^1 + 1*2^2):\n    > v = f( 2.0 )\n    1.5\n\n    See Also\n    --------\n    base.evalpoly\n","base.evalrational.factory":"\nbase.evalrational.factory( P, Q )\n    Returns a function for evaluating a rational function using double-precision\n    floating-point arithmetic.\n\n    Parameters\n    ----------\n    P: Array<number>\n        Numerator polynomial coefficients sorted in ascending degree.\n\n    Q: Array<number>\n        Denominator polynomial coefficients sorted in ascending degree.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a rational function.\n\n    Examples\n    --------\n    > var P = [ 20.0, 8.0, 3.0 ];\n    > var Q = [ 10.0, 9.0, 1.0 ];\n    > var f = base.evalrational.factory( P, Q );\n\n    // (20*10^0 + 8*10^1 + 3*10^2) / (10*10^0 + 9*10^1 + 1*10^2):\n    > var v = f( 10.0 )\n    2.0\n\n    // (20*2^0 + 8*2^1 + 3*2^2) / (10*2^0 + 9*2^1 + 1*2^2):\n    > v = f( 2.0 )\n    1.5\n\n    See Also\n    --------\n    base.evalpoly","base.exp":"\nbase.exp( x )\n    Evaluates the natural exponential function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.exp( 4.0 )\n    ~54.5982\n    > y = base.exp( -9.0 )\n    ~1.234e-4\n    > y = base.exp( 0.0 )\n    1.0\n    > y = base.exp( NaN )\n    NaN\n\n    See Also\n    --------\n    base.exp10, base.exp2, base.expm1, base.ln\n","base.exp2":"\nbase.exp2( x )\n    Evaluates the base 2 exponential function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.exp2( 3.0 )\n    8.0\n    > y = base.exp2( -9.0 )\n    ~0.002\n    > y = base.exp2( 0.0 )\n    1.0\n    > y = base.exp2( NaN )\n    NaN\n\n    See Also\n    --------\n    base.exp, base.exp10, base.log2\n","base.exp10":"\nbase.exp10( x )\n    Evaluates the base 10 exponential function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.exp10( 3.0 )\n    1000\n    > y = base.exp10( -9.0 )\n    1.0e-9\n    > y = base.exp10( 0.0 )\n    1.0\n    > y = base.exp10( NaN )\n    NaN\n\n    See Also\n    --------\n    base.exp, base.exp2, base.log10\n","base.expit":"\nbase.expit( x )\n    Evaluates the standard logistic function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.expit( 0.0 )\n    0.5\n    > y = base.expit( 1.0 )\n    ~0.731\n    > y = base.expit( -1.0 )\n    ~0.269\n    > y = base.expit( Infinity )\n    1.0\n    > y = base.expit( NaN )\n    NaN\n\n    See Also\n    --------\n    base.exp, base.logit","base.expm1":"\nbase.expm1( x )\n    Computes `exp(x)-1`, where `exp(x)` is the natural exponential function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.expm1( 0.2 )\n    ~0.221\n    > y = base.expm1( -9.0 )\n    ~-1.0\n    > y = base.expm1( 0.0 )\n    0.0\n    > y = base.expm1( NaN )\n    NaN\n\n    See Also\n    --------\n    base.exp, base.expm1rel\n","base.expm1rel":"\nbase.expm1rel( x )\n    Relative error exponential.\n\n    When `x` is near zero,\n\n        e^x - 1\n\n    can suffer catastrophic cancellation (i.e., significant loss of precision).\n    This function avoids the loss of precision when `x` is near zero.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.expm1rel( 0.0 )\n    1.0\n    > y = base.expm1rel( 1.0 )\n    ~1.718\n    > y = base.expm1rel( -1.0 )\n    ~0.632\n    > y = base.expm1rel( NaN )\n    NaN\n\t\n    See Also\n    --------\n    base.exp, base.expm1\n","base.exponent":"\nbase.exponent( x )\n    Returns an integer corresponding to the unbiased exponent of a double-\n    precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    Returns\n    -------\n    out: integer\n        Unbiased exponent.\n\n    Examples\n    --------\n    > var exponent = base.exponent( 3.14e-307 )\n    -1019\n    > exponent = base.exponent( -3.14 )\n    1\n    > exponent = base.exponent( 0.0 )\n    -1023\n    > exponent = base.exponent( NaN )\n    1024\n\n    See Also\n    --------\n    base.exponentf\n","base.exponentf":"\nbase.exponentf( x )\n    Returns an integer corresponding to the unbiased exponent of a single-\n    precision floating-point number.\n\n    Parameters\n    ----------\n    x: float\n        Single-precision floating-point number.\n\n    Returns\n    -------\n    out: integer\n        Unbiased exponent.\n\n    Examples\n    --------\n    > var exponent = base.exponentf( base.float64ToFloat32( 3.14e34 ) )\n    114\n    > exponent = base.exponentf( base.float64ToFloat32( 3.14e-34 ) )\n    -112\n    > exponent = base.exponentf( base.float64ToFloat32( -3.14 ) )\n    1\n    > exponent = base.exponentf( 0.0 )\n    -127\n    > exponent = base.exponentf( NaN )\n    128\n\n    See Also\n    --------\n    base.exponent\n","base.factorial":"\nbase.factorial( x )\n    Evaluates the factorial of `x`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Factorial.\n\n    Examples\n    --------\n    > var y = base.factorial( 3.0 )\n    6.0\n    > y = base.factorial( -1.5 )\n    ~-3.545\n    > y = base.factorial( -0.5 )\n    ~1.772\n    > y = base.factorial( 0.5 )\n    ~0.886\n    > y = base.factorial( -10.0 )\n    NaN\n    > y = base.factorial( 171.0 )\n    Infinity\n    > y = base.factorial( NaN )\n    NaN\n\n    See Also\n    --------\n    base.factorialln\n","base.factorial2":"\nbase.factorial2( n )\n    Evaluates the double factorial of `n`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Double factorial.\n\n    Examples\n    --------\n    > var y = base.factorial2( 3 )\n    3\n    > y = base.factorial2( 5 )\n    15\n    > y = base.factorial2( 6 )\n    48\n    > y = base.factorial2( 301 )\n    Infinity\n    > y = base.factorial2( NaN )\n    NaN\n\n    See Also\n    --------\n    base.factorial\n","base.factorialln":"\nbase.factorialln( x )\n    Evaluates the natural logarithm of the factorial of `x`.\n\n    For input values other than negative integers, the function returns\n\n      ln( x! ) = ln( Γ(x+1) )\n\n    where `Γ` is the Gamma function. For negative integers, the function returns\n    `NaN`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Natural logarithm of the factorial of `x`.\n\n    Examples\n    --------\n    > var y = base.factorialln( 3.0 )\n    ~1.792\n    > y = base.factorialln( 2.4 )\n    ~1.092\n    > y = base.factorialln( -1.0 )\n    NaN\n    > y = base.factorialln( -1.5 )\n    ~1.266\n    > y = base.factorialln( NaN )\n    NaN\n\n    See Also\n    --------\n    base.factorial\n","base.fallingFactorial":"\nbase.fallingFactorial( x, n )\n    Computes the falling factorial of `x` and `n`.\n\n    If not provided a nonnegative integer for `n`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        First function parameter.\n\n    n: integer\n        Second function parameter.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var v = base.fallingFactorial( 0.9, 5 )\n    ~0.644\n    > v = base.fallingFactorial( -9.0, 3 )\n    -990.0\n    > v = base.fallingFactorial( 0.0, 2 )\n    0.0\n    > v = base.fallingFactorial( 3.0, -2 )\n    NaN\n\n    See Also\n    --------\n    base.risingFactorial\n","base.fibonacci":"\nbase.fibonacci( n )\n    Computes the nth Fibonacci number.\n\n    Fibonacci numbers follow the recurrence relation\n\n      F_n = F_{n-1} + F_{n-2}\n\n    with seed values F_0 = 0 and F_1 = 1.\n\n    If `n` is greater than `78`, the function returns `NaN`, as larger Fibonacci\n    numbers cannot be accurately represented due to limitations of double-\n    precision floating-point format.\n\n    If not provided a nonnegative integer value, the function returns `NaN`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Input value.\n\n    Returns\n    -------\n    y: integer\n        Fibonacci number.\n\n    Examples\n    --------\n    > var y = base.fibonacci( 0 )\n    0\n    > y = base.fibonacci( 1 )\n    1\n    > y = base.fibonacci( 2 )\n    1\n    > y = base.fibonacci( 3 )\n    2\n    > y = base.fibonacci( 4 )\n    3\n    > y = base.fibonacci( 79 )\n    NaN\n    > y = base.fibonacci( NaN )\n    NaN\n\n    See Also\n    --------\n    base.binet, base.fibonacciIndex, base.lucas, base.negafibonacci\n","base.fibonacciIndex":"\nbase.fibonacciIndex( F )\n    Computes the Fibonacci number index.\n\n    If not provided a nonnegative integer value, the function returns `NaN`.\n\n    If provided `F <= 1` or `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    F: integer\n        Fibonacci number.\n\n    Returns\n    -------\n    n: number\n        Fibonacci number index.\n\n    Examples\n    --------\n    > var n = base.fibonacciIndex( 2 )\n    3\n    > n = base.fibonacciIndex( 3 )\n    4\n    > n = base.fibonacciIndex( 5 )\n    5\n    > n = base.fibonacciIndex( NaN )\n    NaN\n    > n = base.fibonacciIndex( 1 )\n    NaN\n\n    See Also\n    --------\n    base.fibonacci\n","base.fibpoly":"\nbase.fibpoly( n, x )\n    Evaluates a Fibonacci polynomial.\n\n    Parameters\n    ----------\n    n: integer\n        Fibonacci polynomial to evaluate.\n\n    x: number\n        Value at which to evaluate the Fibonacci polynomial.\n\n    Returns\n    -------\n    out: number\n        Evaluated Fibonacci polynomial.\n\n    Examples\n    --------\n    // 2^4 + 3*2^2 + 1\n    > var v = base.fibpoly( 5, 2.0 )\n    29.0\n\n\nbase.fibpoly.factory( n )\n    Returns a function for evaluating a Fibonacci polynomial.\n\n    Parameters\n    ----------\n    n: integer\n        Fibonacci polynomial to evaluate.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a Fibonacci polynomial.\n\n    Examples\n    --------\n    > var polyval = base.fibpoly.factory( 5 );\n\n    // 1^4 + 3*1^2 + 1\n    > var v = polyval( 1.0 )\n    5.0\n\n    // 2^4 + 3*2^2 + 1\n    > v = polyval( 2.0 )\n    29.0\n\n    See Also\n    --------\n    base.evalpoly, base.lucaspoly\n","base.fibpoly.factory":"\nbase.fibpoly.factory( n )\n    Returns a function for evaluating a Fibonacci polynomial.\n\n    Parameters\n    ----------\n    n: integer\n        Fibonacci polynomial to evaluate.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a Fibonacci polynomial.\n\n    Examples\n    --------\n    > var polyval = base.fibpoly.factory( 5 );\n\n    // 1^4 + 3*1^2 + 1\n    > var v = polyval( 1.0 )\n    5.0\n\n    // 2^4 + 3*2^2 + 1\n    > v = polyval( 2.0 )\n    29.0\n\n    See Also\n    --------\n    base.evalpoly, base.lucaspoly","base.firstCodePoint":"\nbase.firstCodePoint( str, n )\n    Returns the first `n` Unicode code points of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of Unicode code points to return.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.firstCodePoint( 'beep', 1 )\n    'b'\n    > out = base.firstCodePoint( 'Boop', 1 )\n    'B'\n    > out = base.firstCodePoint( 'foo bar', 5 )\n    'foo b'\n\n    See Also\n    --------\n    base.firstCodeUnit, base.firstGraphemeCluster, base.lastCodePoint, base.removeFirstCodePoint, firstChar\n","base.firstCodeUnit":"\nbase.firstCodeUnit( str, n )\n    Returns the first `n` UTF-16 code units of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of UTF-16 code units to return.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.firstCodeUnit( 'beep', 1 )\n    'b'\n    > out = base.firstCodeUnit( 'Boop', 1 )\n    'B'\n    > out = base.firstCodeUnit( 'foo bar', 5 )\n    'foo b'\n\n    See Also\n    --------\n    base.firstCodePoint, base.firstGraphemeCluster, base.last, base.removeFirst, firstChar\n","base.firstGraphemeCluster":"\nbase.firstGraphemeCluster( str, n )\n    Returns the first `n` grapheme clusters (i.e., user-perceived characters) of\n    a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of grapheme clusters to return.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.firstGraphemeCluster( 'beep', 1 )\n    'b'\n    > out = base.firstGraphemeCluster( 'Boop', 1 )\n    'B'\n    > out = base.firstGraphemeCluster( 'foo bar', 5 )\n    'foo b'\n\n    See Also\n    --------\n    base.firstCodeUnit, base.firstCodePoint, base.lastGraphemeCluster, base.removeFirstGraphemeCluster, firstChar\n","base.flipsign":"\nbase.flipsign( x, y )\n    Returns a double-precision floating-point number with the magnitude of `x`\n    and the sign of `x*y`.\n\n    The function only returns `-x` when `y` is a negative number.\n\n    According to the IEEE 754 standard, a `NaN` has a biased exponent equal to\n    `2047`, a significand greater than `0`, and a sign bit equal to either `1`\n    or `0`. In which case, `NaN` may not correspond to just one but many binary\n    representations. Accordingly, care should be taken to ensure that `y` is not\n    `NaN`; otherwise, behavior may be indeterminate.\n\n    Parameters\n    ----------\n    x: number\n        Number from which to derive a magnitude.\n\n    y: number\n        Number from which to derive a sign.\n\n    Returns\n    -------\n    z: number\n        Double-precision floating-point number.\n\n    Examples\n    --------\n    > var z = base.flipsign( -3.0, 10.0 )\n    -3.0\n    > z = base.flipsign( -3.0, -1.0 )\n    3.0\n    > z = base.flipsign( 1.0, -0.0 )\n    -1.0\n    > z = base.flipsign( -3.0, -0.0 )\n    3.0\n    > z = base.flipsign( -0.0, 1.0 )\n    -0.0\n    > z = base.flipsign( 0.0, -1.0 )\n    -0.0\n\n    See Also\n    --------\n    base.copysign\n","base.flipsignf":"\nbase.flipsignf( x, y )\n    Returns a single-precision floating-point number with the magnitude of `x`\n    and the sign of `x*y`.\n\n    The function only returns `-x` when `y` is a negative number.\n\n    According to the IEEE 754 standard, a `NaN` has a biased exponent equal to\n    `255`, a significand greater than `0`, and a sign bit equal to either `1` or\n    `0`. In which case, `NaN` may not correspond to just one but many binary\n    representations. Accordingly, care should be taken to ensure that `y` is not\n    `NaN`; otherwise, behavior may be indeterminate.\n\n    Parameters\n    ----------\n    x: number\n        Number from which to derive a magnitude.\n\n    y: number\n        Number from which to derive a sign.\n\n    Returns\n    -------\n    z: number\n        Single-precision floating-point number.\n\n    Examples\n    --------\n    > var z = base.flipsignf( -3.0, 10.0 )\n    -3.0\n    > z = base.flipsignf( -3.0, -1.0 )\n    3.0\n    > z = base.flipsignf( 1.0, -0.0 )\n    -1.0\n    > z = base.flipsignf( -3.0, -0.0 )\n    3.0\n    > z = base.flipsignf( -0.0, 1.0 )\n    -0.0\n    > z = base.flipsignf( 0.0, -1.0 )\n    -0.0\n\n    See Also\n    --------\n    base.copysignf, base.flipsign\n","base.float32ToInt32":"\nbase.float32ToInt32( x )\n    Converts a single-precision floating-point number to a signed 32-bit\n    integer.\n\n    Parameters\n    ----------\n    x: float\n        Single-precision floating-point number.\n\n    Returns\n    -------\n    out: integer\n        Signed 32-bit integer.\n\n    Examples\n    --------\n    > var y = base.float32ToInt32( base.float64ToFloat32( 4294967295.0 ) )\n    0\n    > y = base.float32ToInt32( base.float64ToFloat32( 3.14 ) )\n    3\n    > y = base.float32ToInt32( base.float64ToFloat32( -3.14 ) )\n    -3\n    > y = base.float32ToInt32( base.float64ToFloat32( NaN ) )\n    0\n    > y = base.float32ToInt32( FLOAT32_PINF )\n    0\n    > y = base.float32ToInt32( FLOAT32_NINF )\n    0\n\n    See Also\n    --------\n    base.float32ToUint32","base.float32ToUint32":"\nbase.float32ToUint32( x )\n    Converts a single-precision floating-point number to a unsigned 32-bit\n    integer.\n\n    Parameters\n    ----------\n    x: float\n        Single-precision floating-point number.\n\n    Returns\n    -------\n    out: integer\n        Unsigned 32-bit integer.\n\n    Examples\n    --------\n    > var y = base.float32ToUint32( base.float64ToFloat32( 4294967297.0 ) )\n    0\n    > y = base.float32ToUint32( base.float64ToFloat32( 3.14 ) )\n    3\n    > y = base.float32ToUint32( base.float64ToFloat32( -3.14 ) )\n    4294967293\n    > y = base.float32ToUint32( base.float64ToFloat32( NaN ) )\n    0\n    > y = base.float32ToUint32( FLOAT32_PINF )\n    0\n    > y = base.float32ToUint32( FLOAT32_NINF )\n    0\n\n    See Also\n    --------\n    base.float32ToInt32","base.float64ToFloat32":"\nbase.float64ToFloat32( x )\n    Converts a double-precision floating-point number to the nearest single-\n    precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    Returns\n    -------\n    out: float\n        Nearest single-precision floating-point number.\n\n    Examples\n    --------\n    > var y = base.float64ToFloat32( 1.337 )\n    1.3370000123977661\n","base.float64ToInt32":"\nbase.float64ToInt32( x )\n    Converts a double-precision floating-point number to a signed 32-bit\n    integer.\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    Returns\n    -------\n    out: integer\n        Signed 32-bit integer.\n\n    Examples\n    --------\n    > var y = base.float64ToInt32( 4294967295.0 )\n    -1\n    > y = base.float64ToInt32( 3.14 )\n    3\n    > y = base.float64ToInt32( -3.14 )\n    -3\n    > y = base.float64ToInt32( NaN )\n    0\n    > y = base.float64ToInt32( PINF )\n    0\n    > y = base.float64ToInt32( NINF )\n    0\n\n    See Also\n    --------\n    base.float64ToUint32","base.float64ToInt64Bytes":"\nbase.float64ToInt64Bytes( x )\n    Converts an integer-valued double-precision floating-point number to a\n    signed 64-bit integer byte array according to host byte order (endianness).\n\n    This function assumes that the input value is less than the maximum safe\n    double-precision floating-point integer plus one (i.e., `2**53`).\n\n    Parameters\n    ----------\n    x: integer\n        Integer-valued double-precision floating-point number.\n\n    Returns\n    -------\n    out: Uint8Array\n        Byte array.\n\n    Examples\n    --------\n    > var y = base.float64ToInt64Bytes( 4294967297.0 )\n    <Uint8Array>\n\n\nbase.float64ToInt64Bytes.assign( x, out, stride, offset )\n    Converts an integer-valued double-precision floating-point number to a\n    signed 64-bit integer byte array according to host byte order (endianness)\n    and assigns results to a provided output array.\n\n    This function assumes that the input value is less than the maximum safe\n    double-precision floating-point integer plus one (i.e., `2**53`).\n\n    Parameters\n    ----------\n    x: integer\n        Integer-valued double-precision floating-point number.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Output array.\n\n    Examples\n    --------\n    > var out = new Uint8Array( 16 );\n    > var y = base.float64ToInt64Bytes( 4294967297.0, out, 2, 1 )\n    <Uint8Array>\n\n    See Also\n    --------\n    base.float64ToInt32","base.float64ToInt64Bytes.assign":"\nbase.float64ToInt64Bytes.assign( x, out, stride, offset )\n    Converts an integer-valued double-precision floating-point number to a\n    signed 64-bit integer byte array according to host byte order (endianness)\n    and assigns results to a provided output array.\n\n    This function assumes that the input value is less than the maximum safe\n    double-precision floating-point integer plus one (i.e., `2**53`).\n\n    Parameters\n    ----------\n    x: integer\n        Integer-valued double-precision floating-point number.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Output array.\n\n    Examples\n    --------\n    > var out = new Uint8Array( 16 );\n    > var y = base.float64ToInt64Bytes( 4294967297.0, out, 2, 1 )\n    <Uint8Array>\n\n    See Also\n    --------\n    base.float64ToInt32","base.float64ToUint32":"\nbase.float64ToUint32( x )\n    Converts a double-precision floating-point number to a unsigned 32-bit\n    integer.\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    Returns\n    -------\n    out: integer\n        Unsigned 32-bit integer.\n\n    Examples\n    --------\n    > var y = base.float64ToUint32( 4294967297.0 )\n    1\n    > y = base.float64ToUint32( 3.14 )\n    3\n    > y = base.float64ToUint32( -3.14 )\n    4294967293\n    > y = base.float64ToUint32( NaN )\n    0\n    > y = base.float64ToUint32( PINF )\n    0\n    > y = base.float64ToUint32( NINF )\n    0\n\n    See Also\n    --------\n    base.float64ToInt32","base.floor":"\nbase.floor( x )\n    Rounds a double-precision floating-point number toward negative infinity.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.floor( 3.14 )\n    3.0\n    > y = base.floor( -4.2 )\n    -5.0\n    > y = base.floor( -4.6 )\n    -5.0\n    > y = base.floor( 9.5 )\n    9.0\n    > y = base.floor( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceil, base.round\n","base.floor2":"\nbase.floor2( x )\n    Rounds a numeric value to the nearest power of two toward negative infinity.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.floor2( 3.14 )\n    2.0\n    > y = base.floor2( -4.2 )\n    -8.0\n    > y = base.floor2( -4.6 )\n    -8.0\n    > y = base.floor2( 9.5 )\n    8.0\n    > y = base.floor2( 13.0 )\n    8.0\n    > y = base.floor2( -13.0 )\n    -16.0\n    > y = base.floor2( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceil2, base.floor, base.floor10, base.round2\n","base.floor10":"\nbase.floor10( x )\n    Rounds a numeric value to the nearest power of ten toward negative infinity.\n\n    The function may not return accurate results for subnormals due to a general\n    loss in precision.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.floor10( 3.14 )\n    1.0\n    > y = base.floor10( -4.2 )\n    -10.0\n    > y = base.floor10( -4.6 )\n    -10.0\n    > y = base.floor10( 9.5 )\n    1.0\n    > y = base.floor10( 13.0 )\n    10.0\n    > y = base.floor10( -13.0 )\n    -100.0\n    > y = base.floor10( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceil10, base.floor, base.floor2, base.round10\n","base.floorb":"\nbase.floorb( x, n, b )\n    Rounds a numeric value to the nearest multiple of `b^n` toward negative\n    infinity.\n\n    Due to floating-point rounding error, rounding may not be exact.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Integer power.\n\n    b: integer\n        Base.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    // Round to 4 decimal places:\n    > var y = base.floorb( 3.14159, -4, 10 )\n    3.1415\n\n    // If `n = 0` or `b = 1`, standard round behavior:\n    > y = base.floorb( 3.14159, 0, 2 )\n    3.0\n\n    // Round to nearest multiple of two toward negative infinity:\n    > y = base.floorb( 5.0, 1, 2 )\n    4.0\n\n    See Also\n    --------\n    base.ceilb, base.floor, base.floorn, base.roundb\n","base.floorf":"\nbase.floorf( x )\n    Rounds a single-precision floating-point number toward negative infinity.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.floorf( 3.14 )\n    3.0\n    > y = base.floorf( -4.2 )\n    -5.0\n    > y = base.floorf( -4.6 )\n    -5.0\n    > y = base.floorf( 9.5 )\n    9.0\n    > y = base.floorf( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceilf, base.floor\n","base.floorn":"\nbase.floorn( x, n )\n    Rounds a double-precision floating-point number to the nearest multiple of\n    `10^n` toward negative infinity.\n\n    When operating on floating-point numbers in bases other than `2`, rounding\n    to specified digits can be inexact.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Integer power of 10.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    // Round to 4 decimal places:\n    > var y = base.floorn( 3.14159, -4 )\n    3.1415\n\n    // If `n = 0`, standard round toward negative infinity behavior:\n    > y = base.floorn( 3.14159, 0 )\n    3.0\n\n    // Round to nearest thousand:\n    > y = base.floorn( 12368.0, 3 )\n    12000.0\n\n\n    See Also\n    --------\n    base.ceiln, base.floor, base.floorb, base.roundn\n","base.floorsd":"\nbase.floorsd( x, n, b )\n    Rounds a numeric value to the nearest number toward negative infinity with\n    `n` significant figures.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Number of significant figures. Must be greater than 0.\n\n    b: integer\n        Base. Must be greater than 0.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.floorsd( 3.14159, 5, 10 )\n    3.1415\n    > y = base.floorsd( 3.14159, 1, 10 )\n    3.0\n    > y = base.floorsd( 12368.0, 2, 10 )\n    12000.0\n    > y = base.floorsd( 0.0313, 2, 2 )\n    0.03125\n\n    See Also\n    --------\n    base.ceilsd, base.floor, base.roundsd, base.truncsd\n","base.forEachChar":"\nbase.forEachChar( str, clbk[, thisArg] )\n    Invokes a function for each UTF-16 code unit in a string.\n\n    When invoked, the provided function is provided three arguments:\n\n    - value: character.\n    - index: character index.\n    - str: input string.\n\n    Parameters\n    ----------\n    str: string\n        Input string over which to iterate.\n\n    clbk: Function\n        The function to invoke for each UTF-16 code unit in the input string.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: string\n        Input string.\n\n    Examples\n    --------\n    > var n = 0;\n    > function fcn() { n += 1; };\n    > base.forEachChar( 'hello world!', fcn );\n    > n\n    12\n\n    See Also\n    --------\n    base.forEachCodePoint, base.forEachGraphemeCluster, forEachChar\n","base.forEachCodePoint":"\nbase.forEachCodePoint( str, clbk[, thisArg] )\n    Invokes a function for each Unicode code point in a string.\n\n    When invoked, the provided function is provided three arguments:\n\n    - value: code point.\n    - index: starting code point index.\n    - str: input string.\n\n    Parameters\n    ----------\n    str: string\n        Input string over which to iterate.\n\n    clbk: Function\n        The function to invoke for each Unicode code point in the input string.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: string\n        Input string.\n\n    Examples\n    --------\n    > var n = 0;\n    > function fcn() { n += 1; };\n    > base.forEachCodePoint( 'hello world!', fcn );\n    > n\n    12\n\n    See Also\n    --------\n    base.forEachChar, base.forEachGraphemeCluster, forEachChar\n","base.forEachCodePointRight":"\nbase.forEachCodePointRight( str, clbk[, thisArg] )\n    Invokes a function for each Unicode code point in a string, iterating from\n    right to left.\n\n    When invoked, the provided function is provided three arguments:\n\n    - value: code point.\n    - index: starting code point index.\n    - str: input string.\n\n    Parameters\n    ----------\n    str: string\n        Input string over which to iterate.\n\n    clbk: Function\n        The function to invoke for each Unicode code point in the input string.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: string\n        Input string.\n\n    Examples\n    --------\n    > var n = 0;\n    > function fcn() { n += 1; };\n    > base.forEachCodePointRight( 'hello world!', fcn );\n    > n\n    12\n\n    See Also\n    --------\n    base.forEachCodePoint, base.forEachRight\n","base.forEachGraphemeCluster":"\nbase.forEachGraphemeCluster( str, clbk[, thisArg] )\n    Invokes a function for each grapheme cluster (i.e., user-perceived\n    character) in a string.\n\n    When invoked, the provided function is provided three arguments:\n\n    - value: grapheme cluster.\n    - index: starting grapheme cluster index.\n    - str: input string.\n\n    Parameters\n    ----------\n    str: string\n        Input string over which to iterate.\n\n    clbk: Function\n        The function to invoke for each grapheme cluster in the input string.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: string\n        Input string.\n\n    Examples\n    --------\n    > var n = 0;\n    > function fcn() { n += 1; };\n    > base.forEachGraphemeCluster( 'hello world!', fcn );\n    > n\n    12\n\n    See Also\n    --------\n    base.forEachChar, base.forEachCodePoint, forEachChar\n","base.forEachRight":"\nbase.forEachRight( str, clbk[, thisArg] )\n    Invokes a function for each UTF-16 code unit in a string, iterating from\n    right to left.\n\n    When invoked, the provided function is provided three arguments:\n\n    - value: character.\n    - index: character index.\n    - str: input string.\n\n    Parameters\n    ----------\n    str: string\n        Input string over which to iterate.\n\n    clbk: Function\n        Function to invoke for each UTF-16 code unit in the input string.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: string\n        Input string.\n\n    Examples\n    --------\n    > var n = 0;\n    > function fcn() { n += 1; };\n    > base.forEachRight( 'hello world!', fcn );\n    > n\n    12\n\n    See Also\n    --------\n    base.forEachChar, base.forEachCodePointRight\n","base.formatInterpolate":"\nbase.formatInterpolate( tokens, ...args )\n    Generate string from a token array by interpolating values.\n\n    Parameters\n    ----------\n    tokens: Array\n        Array of string parts and format identifier objects.\n\n    args: ...any\n        Variable values.\n\n    Returns\n    -------\n    out: string\n        Formatted string.\n\n    Examples\n    --------\n    > var out = base.formatInterpolate( [ 'beep ', { 'specifier': 's' } ], 'boop' )\n    'beep boop'\n    > out = base.formatInterpolate( [ 'baz ', { 'specifier': 'd', 'precision': 2 } ], 1 )\n    'baz 1.00'\n    > out = base.formatInterpolate( [ { 'specifier': 'u', 'width': 6 } ], 12 )\n    '    12'\n\n    See Also\n    --------\n    base.formatTokenize\n","base.formatTokenize":"\nbase.formatTokenize( str )\n    Tokenize a string into an array of string parts and format identifier\n    objects.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: Array\n        Array of string parts and format identifier objects.\n\n    Examples\n    --------\n    > var out = base.formatTokenize( 'Hello %s!' )\n    [ 'Hello ', {...}, '!' ]\n    > out = base.formatTokenize( '%s %s %d' )\n    [ {...}, ' ', {...}, ' ', {...}, ' ' ]\n    > out = base.formatTokenize( 'Pi: %.2f' )\n    [ 'Pi: ', {...} ]\n\n    See Also\n    --------\n    base.formatInterpolate\n","base.fresnel":"\nbase.fresnel( x )\n    Computes the Fresnel integrals S(x) and C(x).\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: Array<number>\n        S(x) and C(x).\n\n    Examples\n    --------\n    > var y = base.fresnel( 0.0 )\n    [ ~0.0, ~0.0 ]\n    > y = base.fresnel( 1.0 )\n    [ ~0.438, ~0.780 ]\n    > y = base.fresnel( PINF )\n    [ ~0.5, ~0.5 ]\n    > y = base.fresnel( NINF )\n    [ ~-0.5, ~-0.5 ]\n    > y = base.fresnel( NaN )\n    [ NaN, NaN ]\n\n\nbase.fresnel.assign( x, out, stride, offset )\n    Computes the Fresnel integrals S(x) and C(x) and assigns results to a\n    provided output array.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    out: Array<number>\n        Destination array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array<number>\n        S(x) and C(x).\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var v = base.fresnel.assign( 0.0, out, 1, 0 )\n    <Float64Array>[ ~0.0, ~0.0 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.fresnelc, base.fresnels","base.fresnel.assign":"\nbase.fresnel.assign( x, out, stride, offset )\n    Computes the Fresnel integrals S(x) and C(x) and assigns results to a\n    provided output array.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    out: Array<number>\n        Destination array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array<number>\n        S(x) and C(x).\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var v = base.fresnel.assign( 0.0, out, 1, 0 )\n    <Float64Array>[ ~0.0, ~0.0 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.fresnelc, base.fresnels","base.fresnelc":"\nbase.fresnelc( x )\n    Computes the Fresnel integral C(x).\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        C(x).\n\n    Examples\n    --------\n    > var y = base.fresnelc( 0.0 )\n    ~0.0\n    > y = base.fresnelc( 1.0 )\n    ~0.780\n    > y = base.fresnelc( PINF )\n    ~0.5\n    > y = base.fresnelc( NINF )\n    ~-0.5\n    > y = base.fresnelc( NaN )\n    NaN\n\n    See Also\n    --------\n    base.fresnel, base.fresnels\n","base.fresnels":"\nbase.fresnels( x )\n    Computes the Fresnel integral S(x).\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        S(x).\n\n    Examples\n    --------\n    > var y = base.fresnels( 0.0 )\n    ~0.0\n    > y = base.fresnels( 1.0 )\n    ~0.438\n    > y = base.fresnels( PINF )\n    ~0.5\n    > y = base.fresnels( NINF )\n    ~-0.5\n    > y = base.fresnels( NaN )\n    NaN\n\n    See Also\n    --------\n    base.fresnel, base.fresnelc\n","base.frexp":"\nbase.frexp( x )\n    Splits a double-precision floating-point number into a normalized fraction\n    and an integer power of two.\n\n    The first element of the returned array is the normalized fraction and the\n    second is the exponent. The normalized fraction and exponent satisfy the\n    relation\n\n      x = frac * 2^exp\n\n    If provided positive or negative zero, `NaN`, or positive or negative\n    infinity, the function returns a two-element array containing the input\n    value and an exponent equal to zero.\n\n    For all other numeric input values, the absolute value of the normalized\n    fraction resides on the interval [0.5,1).\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    out: Array<number>\n        A normalized fraction and an exponent.\n\n    Examples\n    --------\n    > var out = base.frexp( 4.0 )\n    [ 0.5, 3 ]\n    > out = base.frexp( 0.0 )\n    [ 0.0, 0 ]\n    > out = base.frexp( -0.0 )\n    [ -0.0, 0 ]\n    > out = base.frexp( NaN )\n    [ NaN, 0 ]\n    > out = base.frexp( PINF )\n    [ Infinity, 0 ]\n    > out = base.frexp( NINF )\n    [ -Infinity, 0 ]\n\n\nbase.frexp.assign( x, out, stride, offset )\n    Splits a double-precision floating-point number into a normalized fraction\n    and an integer power of two and assigns results to a provided output array.\n\n    The first element of the returned array is the normalized fraction and the\n    second is the exponent. The normalized fraction and exponent satisfy the\n    relation\n\n      x = frac * 2^exp\n\n    If provided positive or negative zero, `NaN`, or positive or negative\n    infinity, the function returns a two-element array containing the input\n    value and an exponent equal to zero.\n\n    For all other numeric input values, the absolute value of the normalized\n    fraction resides on the interval [0.5,1).\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    out: Array<number>\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array<number>\n        A normalized fraction and an exponent.\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var y = base.frexp.assign( 4.0, out, 1, 0 )\n    <Float64Array>[ 0.5, 3 ]\n    > var bool = ( y === out )\n    true\n\n    See Also\n    --------\n    base.ldexp\n","base.frexp.assign":"\nbase.frexp.assign( x, out, stride, offset )\n    Splits a double-precision floating-point number into a normalized fraction\n    and an integer power of two and assigns results to a provided output array.\n\n    The first element of the returned array is the normalized fraction and the\n    second is the exponent. The normalized fraction and exponent satisfy the\n    relation\n\n      x = frac * 2^exp\n\n    If provided positive or negative zero, `NaN`, or positive or negative\n    infinity, the function returns a two-element array containing the input\n    value and an exponent equal to zero.\n\n    For all other numeric input values, the absolute value of the normalized\n    fraction resides on the interval [0.5,1).\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    out: Array<number>\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array<number>\n        A normalized fraction and an exponent.\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var y = base.frexp.assign( 4.0, out, 1, 0 )\n    <Float64Array>[ 0.5, 3 ]\n    > var bool = ( y === out )\n    true\n\n    See Also\n    --------\n    base.ldexp","base.fromBinaryString":"\nbase.fromBinaryString( bstr )\n    Creates a double-precision floating-point number from a literal bit\n    representation.\n\n    Parameters\n    ----------\n    bstr: string\n        Literal bit representation.\n\n    Returns\n    -------\n    out: number\n        Double-precision floating-point number.\n\n    Examples\n    --------\n    > var bstr;\n    > bstr = '0100000000010000000000000000000000000000000000000000000000000000';\n    > var val = base.fromBinaryString( bstr )\n    4.0\n    > bstr = '0100000000001001001000011111101101010100010001000010110100011000';\n    > val = base.fromBinaryString( bstr )\n    3.141592653589793\n    > bstr = '1111111111100001110011001111001110000101111010111100100010100000';\n    > val = base.fromBinaryString( bstr )\n    -1.0e308\n\n    // The function handles subnormals:\n    > bstr = '1000000000000000000000000000000000000000000000000001100011010011';\n    > val = base.fromBinaryString( bstr )\n    -3.14e-320\n    > bstr = '0000000000000000000000000000000000000000000000000000000000000001';\n    > val = base.fromBinaryString( bstr )\n    5.0e-324\n\n    // The function handles special values:\n    > bstr = '0000000000000000000000000000000000000000000000000000000000000000';\n    > val = base.fromBinaryString( bstr )\n    0.0\n    > bstr = '1000000000000000000000000000000000000000000000000000000000000000';\n    > val = base.fromBinaryString( bstr )\n    -0.0\n    > bstr = '0111111111111000000000000000000000000000000000000000000000000000';\n    > val = base.fromBinaryString( bstr )\n    NaN\n    > bstr = '0111111111110000000000000000000000000000000000000000000000000000';\n    > val = base.fromBinaryString( bstr )\n    Infinity\n    > bstr = '1111111111110000000000000000000000000000000000000000000000000000';\n    > val = base.fromBinaryString( bstr )\n    -Infinity\n\n    See Also\n    --------\n    base.fromBinaryStringf, base.toBinaryString\n","base.fromBinaryStringf":"\nbase.fromBinaryStringf( bstr )\n    Creates a single-precision floating-point number from an IEEE 754 literal\n    bit representation.\n\n    Parameters\n    ----------\n    bstr: string\n        Literal bit representation.\n\n    Returns\n    -------\n    out: float\n        Single-precision floating-point number.\n\n    Examples\n    --------\n    > var bstr = '01000000100000000000000000000000';\n    > var val = base.fromBinaryStringf( bstr )\n    4.0\n    > bstr = '01000000010010010000111111011011';\n    > val = base.fromBinaryStringf( bstr )\n    ~3.14\n    > bstr = '11111111011011000011101000110011';\n    > val = base.fromBinaryStringf( bstr )\n    ~-3.14e+38\n\n    // The function handles subnormals:\n    > bstr = '10000000000000000000000000010110';\n    > val = base.fromBinaryStringf( bstr )\n    ~-3.08e-44\n    > bstr = '00000000000000000000000000000001';\n    > val = base.fromBinaryStringf( bstr )\n    ~1.40e-45\n\n    // The function handles special values:\n    > bstr = '00000000000000000000000000000000';\n    > val = base.fromBinaryStringf( bstr )\n    0.0\n    > bstr = '10000000000000000000000000000000';\n    > val = base.fromBinaryStringf( bstr )\n    -0.0\n    > bstr = '01111111110000000000000000000000';\n    > val = base.fromBinaryStringf( bstr )\n    NaN\n    > bstr = '01111111100000000000000000000000';\n    > val = base.fromBinaryStringf( bstr )\n    Infinity\n    > bstr = '11111111100000000000000000000000';\n    > val = base.fromBinaryStringf( bstr )\n    -Infinity\n\n    See Also\n    --------\n    base.toBinaryStringf, base.fromBinaryString\n","base.fromBinaryStringUint8":"\nbase.fromBinaryStringUint8( bstr )\n    Creates an unsigned 8-bit integer from a literal bit representation.\n\n    Parameters\n    ----------\n    bstr: string\n        Literal bit representation.\n\n    Returns\n    -------\n    out: integer\n        Unsigned 8-bit integer.\n\n    Examples\n    --------\n    > var bstr = '01010101';\n    > var val = base.fromBinaryStringUint8( bstr )\n    85\n    > bstr = '00000000';\n    > val = base.fromBinaryStringUint8( bstr )\n    0\n    > bstr = '00000010';\n    > val = base.fromBinaryStringUint8( bstr )\n    2\n    > bstr = '11111111';\n    > val = base.fromBinaryStringUint8( bstr )\n    255\n\n    See Also\n    --------\n    base.fromBinaryStringUint16, base.fromBinaryStringUint32, base.toBinaryStringUint8\n","base.fromBinaryStringUint16":"\nbase.fromBinaryStringUint16( bstr )\n    Creates an unsigned 16-bit integer from a literal bit representation.\n\n    Parameters\n    ----------\n    bstr: string\n        Literal bit representation.\n\n    Returns\n    -------\n    out: integer\n        Unsigned 16-bit integer.\n\n    Examples\n    --------\n    > var bstr = '0101010101010101';\n    > var val = base.fromBinaryStringUint16( bstr )\n    21845\n    > bstr = '0000000000000000';\n    > val = base.fromBinaryStringUint16( bstr )\n    0\n    > bstr = '0000000000000010';\n    > val = base.fromBinaryStringUint16( bstr )\n    2\n    > bstr = '1111111111111111';\n    > val = base.fromBinaryStringUint16( bstr )\n    65535\n\n    See Also\n    --------\n    base.toBinaryStringUint16, base.fromBinaryStringUint32, base.fromBinaryStringUint8\n","base.fromBinaryStringUint32":"\nbase.fromBinaryStringUint32( bstr )\n    Creates an unsigned 32-bit integer from a literal bit representation.\n\n    Parameters\n    ----------\n    bstr: string\n        Literal bit representation.\n\n    Returns\n    -------\n    out: integer\n        Unsigned 32-bit integer.\n\n    Examples\n    --------\n    > var bstr = '01010101010101010101010101010101';\n    > var val = base.fromBinaryStringUint32( bstr )\n    1431655765\n    > bstr = '00000000000000000000000000000000';\n    > val = base.fromBinaryStringUint32( bstr )\n    0\n    > bstr = '00000000000000000000000000000010';\n    > val = base.fromBinaryStringUint32( bstr )\n    2\n    > bstr = '11111111111111111111111111111111';\n    > val = base.fromBinaryStringUint32( bstr )\n    4294967295\n\n    See Also\n    --------\n    base.fromBinaryStringUint16, base.toBinaryStringUint32, base.fromBinaryStringUint8\n","base.fromInt64Bytes":"\nbase.fromInt64Bytes( bytes, stride, offset )\n    Converts a signed 64-bit integer byte array to a double-precision floating-\n    point number.\n\n    The function assumes host byte order (endianness).\n\n    Parameters\n    ----------\n    bytes: Array<number>|TypedArray|Object\n        Byte array.\n\n    stride: integer\n        Index stride.\n\n    offset: integer\n        Index offset.\n\n    Returns\n    -------\n    out: number\n        Number.\n\n    Examples\n    --------\n    > var bytes = new Uint8Array( [ 255, 255, 255, 255, 255, 255, 255, 255 ] );\n    > var y = base.fromInt64Bytes( bytes, 1, 0 )\n    -1.0\n\n    See Also\n    --------\n    base.float64ToInt64Bytes","base.fromWordf":"\nbase.fromWordf( word )\n    Creates a single-precision floating-point number from an unsigned integer\n    corresponding to an IEEE 754 binary representation.\n\n    Parameters\n    ----------\n    word: integer\n        Unsigned integer.\n\n    Returns\n    -------\n    out: float\n        Single-precision floating-point number.\n\n    Examples\n    --------\n    > var word = 1068180177; // => 0 01111111 01010110010001011010001\n    > var f32 = base.fromWordf( word ) // when printed, promoted to float64\n    1.3370000123977661\n\n    See Also\n    --------\n    base.fromWords\n","base.fromWords":"\nbase.fromWords( high, low )\n    Creates a double-precision floating-point number from a higher order word\n    (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n\n    Parameters\n    ----------\n    high: integer\n        Higher order word (unsigned 32-bit integer).\n\n    low: integer\n        Lower order word (unsigned 32-bit integer).\n\n    Returns\n    -------\n    out: number\n        Double-precision floating-point number.\n\n    Examples\n    --------\n    > var v = base.fromWords( 1774486211, 2479577218 )\n    3.14e201\n    > v = base.fromWords( 3221823995, 1413754136 )\n    -3.141592653589793\n    > v = base.fromWords( 0, 0 )\n    0.0\n    > v = base.fromWords( 2147483648, 0 )\n    -0.0\n    > v = base.fromWords( 2146959360, 0 )\n    NaN\n    > v = base.fromWords( 2146435072, 0 )\n    Infinity\n    > v = base.fromWords( 4293918720, 0 )\n    -Infinity\n\n    See Also\n    --------\n    base.fromWordf\n","base.gamma":"\nbase.gamma( x )\n    Evaluates the gamma function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.gamma( 4.0 )\n    6.0\n    > y = base.gamma( -1.5 )\n    ~2.363\n    > y = base.gamma( -0.5 )\n    ~-3.545\n    > y = base.gamma( 0.5 )\n    ~1.772\n    > y = base.gamma( 0.0 )\n    Infinity\n    > y = base.gamma( -0.0 )\n    -Infinity\n    > y = base.gamma( NaN )\n    NaN\n\n    See Also\n    --------\n    base.gamma1pm1, base.gammainc, base.gammaincinv, base.gammaln\n","base.gamma1pm1":"\nbase.gamma1pm1( x )\n    Computes `gamma(x+1) - 1` without cancellation errors, where `gamma(x)` is\n    the gamma function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.gamma1pm1( 0.2 )\n    ~-0.082\n    > y = base.gamma1pm1( -6.7 )\n    ~-0.991\n    > y = base.gamma1pm1( 0.0 )\n    0.0\n    > y = base.gamma1pm1( NaN )\n    NaN\n\n    See Also\n    --------\n    base.gamma, base.gammainc, base.gammaincinv, base.gammaln\n","base.gammaDeltaRatio":"\nbase.gammaDeltaRatio( z, delta )\n    Computes the ratio of two gamma functions.\n\n    The ratio is defined as: Γ(z) / Γ(z+Δ).\n\n    Parameters\n    ----------\n    z: number\n        First gamma parameter.\n\n    delta: number\n        Difference.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.gammaDeltaRatio( 2.0, 3.0 )\n    ~0.042\n    > y = base.gammaDeltaRatio( 4.0, 0.5 )\n    ~0.516\n    > y = base.gammaDeltaRatio( 100.0, 0.0 )\n    1.0\n    > y = base.gammaDeltaRatio( NaN, 3.0 )\n    NaN\n    > y = base.gammaDeltaRatio( 5.0, NaN )\n    NaN\n    > y = base.gammaDeltaRatio( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.gamma\n","base.gammainc":"\nbase.gammainc( x, s[, regularized[, upper]] )\n    Computes the regularized incomplete gamma function.\n\n    The `regularized` and `upper` parameters specify whether to evaluate the\n    non-regularized and/or upper incomplete gamma functions, respectively.\n\n    If provided `x < 0` or `s <= 0`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        First function parameter.\n\n    s: number\n        Second function parameter.\n\n    regularized: boolean (optional)\n        Boolean indicating whether the function should evaluate the regularized\n        or non-regularized incomplete gamma function. Default: `true`.\n\n    upper: boolean (optional)\n        Boolean indicating whether the function should return the upper tail of\n        the incomplete gamma function. Default: `false`.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.gammainc( 6.0, 2.0 )\n    ~0.9826\n    > y = base.gammainc( 1.0, 2.0, true, true )\n    ~0.7358\n    > y = base.gammainc( 7.0, 5.0 )\n    ~0.8270\n    > y = base.gammainc( 7.0, 5.0, false )\n    ~19.8482\n    > y = base.gammainc( NaN, 2.0 )\n    NaN\n    > y = base.gammainc( 6.0, NaN )\n    NaN\n\n    See Also\n    --------\n    base.gamma, base.gamma1pm1, base.gammaincinv, base.gammaln\n","base.gammaincinv":"\nbase.gammaincinv( p, a[, upper] )\n    Computes the inverse of the lower incomplete gamma function.\n\n    In contrast to a more commonly used definition, the first argument is the\n    probability `p` and the second argument is the scale factor `a`.\n\n    By default, the function inverts the lower regularized incomplete gamma\n    function, `P(x,a)`. To invert the upper function `Q(x,a)`, set the `upper`\n    argument to `true`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Probability.\n\n    a: number\n        Scale parameter.\n\n    upper: boolean (optional)\n        Boolean indicating if the function should invert the upper tail of the\n        incomplete gamma function; i.e., compute `xr` such that `Q(a,xr) = p`.\n        Default: `false`.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.gammaincinv( 0.5, 2.0 )\n    ~1.678\n    > y = base.gammaincinv( 0.1, 10.0 )\n    ~6.221\n    > y = base.gammaincinv( 0.75, 3.0 )\n    ~3.92\n    > y = base.gammaincinv( 0.75, 3.0, true )\n    ~1.727\n    > y = base.gammaincinv( 0.75, NaN )\n    NaN\n    > y = base.gammaincinv( NaN, 3.0 )\n    NaN\n\n    See Also\n    --------\n    base.gamma, base.gamma1pm1, base.gammainc, base.gammaln\n","base.gammaLanczosSum":"\nbase.gammaLanczosSum( x )\n    Calculates the Lanczos sum for the approximation of the gamma function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Lanczos sum.\n\n    Examples\n    --------\n    > var y = base.gammaLanczosSum( 4.0 )\n    ~950.366\n    > y = base.gammaLanczosSum( -1.5 )\n    ~1373366.245\n    > y = base.gammaLanczosSum( -0.5 )\n    ~-699841.735\n    > y = base.gammaLanczosSum( 0.5 )\n    ~96074.186\n    > y = base.gammaLanczosSum( 0.0 )\n    Infinity\n    > y = base.gammaLanczosSum( NaN )\n    NaN\n\n    See Also\n    --------\n    base.gamma, base.gammaLanczosSumExpGScaled\n","base.gammaLanczosSumExpGScaled":"\nbase.gammaLanczosSumExpGScaled( x )\n    Calculates the scaled Lanczos sum for the approximation of the gamma\n    function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Scaled Lanczos sum.\n\n    Examples\n    --------\n    > var y = base.gammaLanczosSumExpGScaled( 4.0 )\n    ~0.018\n    > y = base.gammaLanczosSumExpGScaled( -1.5 )\n    ~25.337\n    > y = base.gammaLanczosSumExpGScaled( -0.5 )\n    ~-12.911\n    > y = base.gammaLanczosSumExpGScaled( 0.5 )\n    ~1.772\n    > y = base.gammaLanczosSumExpGScaled( 0.0 )\n    Infinity\n    > y = base.gammaLanczosSumExpGScaled( NaN )\n    NaN\n\n    See Also\n    --------\n    base.gamma, base.gammaLanczosSum\n","base.gammaln":"\nbase.gammaln( x )\n    Evaluates the natural logarithm of the gamma function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Natural logarithm of the gamma function.\n\n    Examples\n    --------\n    > var y = base.gammaln( 1.0 )\n    0.0\n    > y = base.gammaln( 2.0 )\n    0.0\n    > y = base.gammaln( 4.0 )\n    ~1.792\n    > y = base.gammaln( -0.5 )\n    ~1.266\n    > y = base.gammaln( 0.5 )\n    ~0.572\n    > y = base.gammaln( 0.0 )\n    Infinity\n    > y = base.gammaln( NaN )\n    NaN\n\n    See Also\n    --------\n    base.gamma, base.gammainc, base.gammaincinv\n","base.gammasgn":"\nbase.gammasgn( x )\n    Computes the sign of the gamma function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Sign of the gamma function.\n\n    Examples\n    --------\n    > var y = base.gammasgn( 1.0 )\n    1.0\n    > y = base.gammasgn( -2.5 )\n    -1.0\n    > y = base.gammasgn( 0.0 )\n    0.0\n    > y = base.gammasgn( NaN )\n    NaN\n\n    See Also\n    --------\n    base.gamma","base.gcd":"\nbase.gcd( a, b )\n    Computes the greatest common divisor (gcd).\n\n    If both `a` and `b` are `0`, the function returns `0`.\n\n    Both `a` and `b` must have integer values; otherwise, the function returns\n    `NaN`.\n\n    Parameters\n    ----------\n    a: integer\n        First number.\n\n    b: integer\n        Second number.\n\n    Returns\n    -------\n    out: integer\n        Greatest common divisor.\n\n    Examples\n    --------\n    > var v = base.gcd( 48, 18 )\n    6\n\n    See Also\n    --------\n    base.lcm\n","base.getHighWord":"\nbase.getHighWord( x )\n    Returns an unsigned 32-bit integer corresponding to the more significant 32\n    bits of a double-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    out: integer\n        Higher order word (unsigned 32-bit integer).\n\n    Examples\n    --------\n    > var w = base.getHighWord( 3.14e201 )\n    1774486211\n\n    See Also\n    --------\n    base.getLowWord, base.setHighWord\n","base.getLowWord":"\nbase.getLowWord( x )\n    Returns an unsigned 32-bit integer corresponding to the less significant 32\n    bits of a double-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    out: integer\n        Lower order word (unsigned 32-bit integer).\n\n    Examples\n    --------\n    > var w = base.getLowWord( 3.14e201 )\n    2479577218\n\n    See Also\n    --------\n    base.getHighWord, base.setHighWord\n","base.hacovercos":"\nbase.hacovercos( x )\n    Computes the half-value coversed cosine.\n\n    The half-value coversed cosine is defined as `(1 + sin(x)) / 2`.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Half-value coversed cosine.\n\n    Examples\n    --------\n    > var y = base.hacovercos( 3.14 )\n    ~0.5008\n    > y = base.hacovercos( -4.2 )\n    ~0.9358\n    > y = base.hacovercos( -4.6 )\n    ~0.9968\n    > y = base.hacovercos( 9.5 )\n    ~0.4624\n    > y = base.hacovercos( -0.0 )\n    0.5\n\n    See Also\n    --------\n    base.hacoversin, base.havercos\n","base.hacoversin":"\nbase.hacoversin( x )\n    Computes the half-value coversed sine.\n\n    The half-value coversed sine is defined as `(1 - sin(x)) / 2`.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Half-value coversed sine.\n\n    Examples\n    --------\n    > var y = base.hacoversin( 3.14 )\n    ~0.4992\n    > y = base.hacoversin( -4.2 )\n    ~0.0642\n    > y = base.hacoversin( -4.6 )\n    ~0.0032\n    > y = base.hacoversin( 9.5 )\n    ~0.538\n    > y = base.hacoversin( -0.0 )\n    0.5\n\n    See Also\n    --------\n    base.hacovercos, base.haversin\n","base.havercos":"\nbase.havercos( x )\n    Computes the half-value versed cosine.\n\n    The half-value versed cosine is defined as `(1 + cos(x)) / 2`.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Half-value versed cosine.\n\n    Examples\n    --------\n    > var y = base.havercos( 3.14 )\n    ~0.0\n    > y = base.havercos( -4.2 )\n    ~0.2549\n    > y = base.havercos( -4.6 )\n    ~0.4439\n    > y = base.havercos( 9.5 )\n    ~0.0014\n    > y = base.havercos( -0.0 )\n    1.0\n\n    See Also\n    --------\n    base.haversin, base.vercos\n","base.haversin":"\nbase.haversin( x )\n    Computes the half-value versed sine.\n\n    The half-value versed sine is defined as `(1 - cos(x)) / 2`.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Half-value versed sine.\n\n    Examples\n    --------\n    > var y = base.haversin( 3.14 )\n    ~1.0\n    > y = base.haversin( -4.2 )\n    ~0.7451\n    > y = base.haversin( -4.6 )\n    ~0.5561\n    > y = base.haversin( 9.5 )\n    ~0.9986\n    > y = base.haversin( -0.0 )\n    0.0\n\n    See Also\n    --------\n    base.havercos, base.versin\n","base.headercase":"\nbase.headercase( str )\n    Converts a string to HTTP header case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        HTTP header-cased string.\n\n    Examples\n    --------\n    > var out = base.headercase( 'Hello World!' )\n    'Hello-World'\n    > out = base.headercase( 'beep boop' )\n    'Beep-Boop'\n\n    See Also\n    --------\n    base.camelcase, base.pascalcase, base.uppercase","base.heaviside":"\nbase.heaviside( x[, continuity] )\n    Evaluates the Heaviside function.\n\n    The `continuity` parameter may be one of the following:\n\n    - 'half-maximum': if `x == 0`, the function returns `0.5`.\n    - 'left-continuous': if `x == 0`, the function returns `0`.\n    - 'right-continuous': if `x == 0`, the function returns `1`.\n\n    By default, if `x == 0`, the function returns `NaN` (i.e., the function is\n    discontinuous).\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    continuity: string (optional)\n        Specifies how to handle `x == 0`. By default, if `x == 0`, the function\n        returns `NaN`.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.heaviside( 3.14 )\n    1.0\n    > y = base.heaviside( -3.14 )\n    0.0\n    > y = base.heaviside( 0.0 )\n    NaN\n    > y = base.heaviside( 0.0, 'half-maximum' )\n    0.5\n    > y = base.heaviside( 0.0, 'left-continuous' )\n    0.0\n    > y = base.heaviside( 0.0, 'right-continuous' )\n    1.0\n\n    See Also\n    --------\n    base.ramp\n","base.hermitepoly":"\nbase.hermitepoly( n, x )\n    Evaluates a physicist's Hermite polynomial.\n\n    Parameters\n    ----------\n    n: integer\n        Nonnegative polynomial degree.\n\n    x: number\n        Value at which to evaluate the polynomial.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.hermitepoly( 1, 0.5 )\n    1.0\n    > y = base.hermitepoly( -1, 0.5 )\n    NaN\n    > y = base.hermitepoly( 0, 0.5 )\n    1.0\n    > y = base.hermitepoly( 2, 0.5 )\n    -1.0\n\n\nbase.hermitepoly.factory( n )\n    Returns a function for evaluating a physicist's Hermite polynomial.\n\n    Parameters\n    ----------\n    n: integer\n        Nonnegative polynomial degree.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a physicist's Hermite polynomial.\n\n    Examples\n    --------\n    > var polyval = base.hermitepoly.factory( 2 );\n    > var v = polyval( 0.5 )\n    -1.0\n\n    See Also\n    --------\n    base.evalpoly, base.normhermitepoly\n","base.hermitepoly.factory":"\nbase.hermitepoly.factory( n )\n    Returns a function for evaluating a physicist's Hermite polynomial.\n\n    Parameters\n    ----------\n    n: integer\n        Nonnegative polynomial degree.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a physicist's Hermite polynomial.\n\n    Examples\n    --------\n    > var polyval = base.hermitepoly.factory( 2 );\n    > var v = polyval( 0.5 )\n    -1.0\n\n    See Also\n    --------\n    base.evalpoly, base.normhermitepoly","base.hypot":"\nbase.hypot( x, y )\n    Computes the hypotenuse avoiding overflow and underflow.\n\n    If either argument is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Hypotenuse.\n\n    Examples\n    --------\n    > var h = base.hypot( -5.0, 12.0 )\n    13.0\n    > h = base.hypot( NaN, 12.0 )\n    NaN\n    > h = base.hypot( -0.0, -0.0 )\n    0.0\n\n","base.hypotf":"\nbase.hypotf( x, y )\n    Computes the hypotenuse avoiding overflow and underflow (single-precision).\n\n    If either argument is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Hypotenuse.\n\n    Examples\n    --------\n    > var h = base.hypotf( -5.0, 12.0 )\n    13.0\n    > h = base.hypotf( NaN, 12.0 )\n    NaN\n    > h = base.hypotf( -0.0, -0.0 )\n    0.0\n\n    See Also\n    --------\n    base.hypot\n","base.identity":"\nbase.identity( x )\n    Evaluates the identity function for a double-precision floating-point number\n    `x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Input value.\n\n    Examples\n    --------\n    > var y = base.identity( -1.0 )\n    -1.0\n    > y = base.identity( 2.0 )\n    2.0\n    > y = base.identity( 0.0 )\n    0.0\n    > y = base.identity( -0.0 )\n    -0.0\n    > y = base.identity( NaN )\n    NaN\n\n","base.identityf":"\nbase.identityf( x )\n    Evaluates the identity function for a single-precision floating-point number\n    `x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Input value.\n\n    Examples\n    --------\n    > var y = base.identityf( -1.0 )\n    -1.0\n    > y = base.identityf( 2.0 )\n    2.0\n    > y = base.identityf( 0.0 )\n    0.0\n    > y = base.identityf( -0.0 )\n    -0.0\n    > y = base.identityf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.identityf\n","base.imul":"\nbase.imul( a, b )\n    Performs C-like multiplication of two signed 32-bit integers.\n\n    Parameters\n    ----------\n    a: integer\n        Signed 32-bit integer.\n\n    b: integer\n        Signed 32-bit integer.\n\n    Returns\n    -------\n    out: integer\n        Product.\n\n    Examples\n    --------\n    > var v = base.imul( -10|0, 4|0 )\n    -40\n\n    See Also\n    --------\n    base.imuldw\n","base.imuldw":"\nbase.imuldw( a, b )\n    Multiplies two signed 32-bit integers and returns an array of two signed 32-\n    bit integers which represents the signed 64-bit integer product.\n\n    When computing the product of 32-bit integer values in double-precision\n    floating-point format (the default JavaScript numeric data type), computing\n    the double word product is necessary in order to avoid exceeding the maximum\n    safe double-precision floating-point integer value.\n\n    Parameters\n    ----------\n    a: integer\n        Signed 32-bit integer.\n\n    b: integer\n        Signed 32-bit integer.\n\n    Returns\n    -------\n    out: Array<number>\n        Double word product (in big endian order; i.e., the first element\n        corresponds to the most significant bits and the second element to the\n        least significant bits).\n\n    Examples\n    --------\n    > var v = base.imuldw( 1, 10 )\n    [ 0, 10 ]\n\n\nbase.imuldw.assign( a, b, out, stride, offset )\n    Multiplies two signed 32-bit integers and assigns results representing the\n    signed 64-bit integer product to a provided output array.\n\n    When computing the product of 32-bit integer values in double-precision\n    floating-point format (the default JavaScript numeric data type), computing\n    the double word product is necessary in order to avoid exceeding the maximum\n    safe double-precision floating-point integer value.\n\n    Parameters\n    ----------\n    a: integer\n        Signed 32-bit integer.\n\n    b: integer\n        Signed 32-bit integer.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Double word product (in big endian order; i.e., the first element\n        corresponds to the most significant bits and the second element to the\n        least significant bits).\n\n    Examples\n    --------\n    > var out = [ 0, 0 ];\n    > var v = base.imuldw.assign( 1, 10, out, 1, 0 )\n    [ 0, 10 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.imul","base.imuldw.assign":"\nbase.imuldw.assign( a, b, out, stride, offset )\n    Multiplies two signed 32-bit integers and assigns results representing the\n    signed 64-bit integer product to a provided output array.\n\n    When computing the product of 32-bit integer values in double-precision\n    floating-point format (the default JavaScript numeric data type), computing\n    the double word product is necessary in order to avoid exceeding the maximum\n    safe double-precision floating-point integer value.\n\n    Parameters\n    ----------\n    a: integer\n        Signed 32-bit integer.\n\n    b: integer\n        Signed 32-bit integer.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Double word product (in big endian order; i.e., the first element\n        corresponds to the most significant bits and the second element to the\n        least significant bits).\n\n    Examples\n    --------\n    > var out = [ 0, 0 ];\n    > var v = base.imuldw.assign( 1, 10, out, 1, 0 )\n    [ 0, 10 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.imul","base.int2slice":"\nbase.int2slice( value, max, strict )\n    Converts an integer to a Slice object.\n\n    In strict mode, the function returns an error object if an input value\n    exceeds index bounds.\n\n    A returned error object is a plain object having the following properties:\n\n    - code: error code.\n\n    A returned error object may have one of the following error codes:\n\n    - ERR_SLICE_OUT_OF_BOUNDS: a slice exceeds index bounds.\n\n    Parameters\n    ----------\n    value: integer\n        Input value.\n\n    max: integer\n        Index upper bound (exclusive).\n\n    strict: boolean\n        Boolean indicating whether to enforce strict bounds checking.\n\n    Returns\n    -------\n    s: Slice|Object\n        Slice instance (or an error object).\n\n    Examples\n    --------\n    > var s = base.int2slice( -1, 5, false );\n    > s.start\n    4\n    > s.stop\n    5\n    > s.step\n    1\n\n    See Also\n    --------\n    base.seq2slice, base.str2slice\n","base.int32ToUint32":"\nbase.int32ToUint32( x )\n    Converts a signed 32-bit integer to an unsigned 32-bit integer.\n\n    Parameters\n    ----------\n    x: integer\n        Signed 32-bit integer.\n\n    Returns\n    -------\n    out: integer\n        Unsigned 32-bit integer.\n\n    Examples\n    --------\n    > var y = base.int32ToUint32( base.float64ToInt32( -32 ) )\n    4294967264\n    > y = base.int32ToUint32( base.float64ToInt32( 3 ) )\n    3\n\n    See Also\n    --------\n    base.uint32ToInt32\n","base.inv":"\nbase.inv( x )\n    Computes the multiplicative inverse of a double-precision floating-point\n    number `x`.\n\n    The multiplicative inverse is defined as `1/x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Multiplicative inverse.\n\n    Examples\n    --------\n    > var y = base.inv( -1.0 )\n    -1.0\n    > y = base.inv( 2.0 )\n    0.5\n    > y = base.inv( 0.0 )\n    Infinity\n    > y = base.inv( -0.0 )\n    -Infinity\n    > y = base.inv( NaN )\n    NaN\n\n    See Also\n    --------\n    base.pow\n","base.invcase":"\nbase.invcase( str )\n    Converts a string to inverse case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Inverse-cased string.\n\n    Examples\n    --------\n    > var out = base.invcase( 'Hello World!' )\n    'hELLO wORLD!'\n    > out = base.invcase( 'I am A tiny LITTLE teapot' )\n    'i AM a TINY little TEAPOT'\n\n    See Also\n    --------\n    base.lowercase, base.uppercase","base.invf":"\nbase.invf( x )\n    Computes the multiplicative inverse of a single-precision floating-point\n    number `x`.\n\n    The multiplicative inverse is defined as `1/x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Multiplicative inverse.\n\n    Examples\n    --------\n    > var y = base.invf( -1.0 )\n    -1.0\n    > y = base.invf( 2.0 )\n    0.5\n    > y = base.invf( 0.0 )\n    Infinity\n    > y = base.invf( -0.0 )\n    -Infinity\n    > y = base.invf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.inv\n","base.isComposite":"\nbase.isComposite( x )\n    Tests if a number is composite.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is a composite number.\n\n    Examples\n    --------\n    > var bool = base.isComposite( 10.0 )\n    true\n    > bool = base.isComposite( 11.0 )\n    false\n\n    See Also\n    --------\n    base.isInteger, base.isPrime\n","base.isCoprime":"\nbase.isCoprime( a, b )\n    Tests if two numbers are coprime.\n\n    Parameters\n    ----------\n    a: number\n        First value.\n\n    b: number\n        Second value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the values are coprime.\n\n    Examples\n    --------\n    > var bool = base.isCoprime( 14.0, 15.0 )\n    true\n    > bool = base.isCoprime( 14.0, 21.0 )\n    false\n\n    See Also\n    --------\n    base.isComposite, base.isPrime, base.gcd\n","base.isEven":"\nbase.isEven( x )\n    Tests if a finite numeric value is an even number.\n\n    The function assumes a finite number. If provided positive or negative\n    infinity, the function will return `true`, when, in fact, the result is\n    undefined.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is an even number.\n\n    Examples\n    --------\n    > var bool = base.isEven( 5.0 )\n    false\n    > bool = base.isEven( -2.0 )\n    true\n    > bool = base.isEven( 0.0 )\n    true\n    > bool = base.isEven( NaN )\n    false\n\n    See Also\n    --------\n    base.isOdd\n","base.isEvenInt32":"\nbase.isEvenInt32( x )\n    Tests if a 32-bit integer is even.\n\n    Parameters\n    ----------\n    x: integer\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is an even number.\n\n    Examples\n    --------\n    > var bool = base.isEvenInt32( 5 )\n    false\n    > bool = base.isEvenInt32( -2 )\n    true\n    > bool = base.isEvenInt32( 0 )\n    true\n\n    See Also\n    --------\n    base.isEven, base.isOddInt32\n","base.isFinite":"\nbase.isFinite( x )\n    Tests if a double-precision floating-point numeric value is finite.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is finite.\n\n    Examples\n    --------\n    > var bool = base.isFinite( 5.0 )\n    true\n    > bool = base.isFinite( -2.0e64 )\n    true\n    > bool = base.isFinite( PINF )\n    false\n    > bool = base.isFinite( NINF )\n    false\n\n    See Also\n    --------\n    base.isInfinite\n","base.isFinitef":"\nbase.isFinitef( x )\n    Tests if a single-precision floating-point numeric value is finite.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is finite.\n\n    Examples\n    --------\n    > var bool = base.isFinitef( 5.0 )\n    true\n    > bool = base.isFinitef( -1.0e38 )\n    true\n    > bool = base.isFinitef( FLOAT32_PINF )\n    false\n    > bool = base.isFinitef( FLOAT32_NINF )\n    false\n\n    See Also\n    --------\n    base.isInfinitef\n","base.isInfinite":"\nbase.isInfinite( x )\n    Tests if a double-precision floating-point numeric value is infinite.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is infinite.\n\n    Examples\n    --------\n    > var bool = base.isInfinite( PINF )\n    true\n    > bool = base.isInfinite( NINF )\n    true\n    > bool = base.isInfinite( 5.0 )\n    false\n    > bool = base.isInfinite( NaN )\n    false\n\n    See Also\n    --------\n    base.isFinite\n","base.isInfinitef":"\nbase.isInfinitef( x )\n    Tests if a single-precision floating-point numeric value is infinite.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is infinite.\n\n    Examples\n    --------\n    > var bool = base.isInfinitef( FLOAT32_PINF )\n    true\n    > bool = base.isInfinitef( FLOAT32_NINF )\n    true\n    > bool = base.isInfinitef( 5.0 )\n    false\n    > bool = base.isInfinitef( NaN )\n    false\n\n    See Also\n    --------\n    base.isFinitef\n","base.isInteger":"\nbase.isInteger( x )\n    Tests if a finite double-precision floating-point number is an integer.\n\n    The function assumes a finite number. If provided positive or negative\n    infinity, the function will return `true`, when, in fact, the result is\n    undefined.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is an integer.\n\n    Examples\n    --------\n    > var bool = base.isInteger( 1.0 )\n    true\n    > bool = base.isInteger( 3.14 )\n    false\n\n","base.isnan":"\nbase.isnan( x )\n     Tests if a double-precision floating-point numeric value is `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is `NaN`.\n\n    Examples\n    --------\n    > var bool = base.isnan( NaN )\n    true\n    > bool = base.isnan( 7.0 )\n    false\n\n    See Also\n    --------\n    base.isnanf\n","base.isnanf":"\nbase.isnanf( x )\n     Tests if a single-precision floating-point numeric value is `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is `NaN`.\n\n    Examples\n    --------\n    > var bool = base.isnanf( NaN )\n    true\n    > bool = base.isnanf( 7.0 )\n    false\n\n    See Also\n    --------\n    base.isnan\n","base.isNegativeFinite":"\nbase.isNegativeFinite( x )\n    Tests if a double-precision floating-point numeric value is a negative\n    finite number.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether the value is a negative finite number.\n\n    Examples\n    --------\n    > var bool = base.isNegativeFinite( -3.14 )\n    true\n    > bool = base.isNegativeFinite( -Infinity )\n    false\n    > bool = base.isNegativeFinite( 2.0 )\n    false\n    > bool = base.isNegativeFinite( NaN )\n    false\n    > bool = base.isNegativeFinite( -0.0 )\n    false\n\n    See Also\n    --------\n    base.isPositiveFinite, base.isNonNegativeFinite, base.isNonPositiveFinite\n","base.isNegativeInteger":"\nbase.isNegativeInteger( x )\n    Tests if a finite double-precision floating-point number is a negative\n    integer.\n\n    The function assumes a finite number. If provided negative infinity, the\n    function will return `true`, when, in fact, the result is undefined.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is a negative integer.\n\n    Examples\n    --------\n    > var bool = base.isNegativeInteger( -1.0 )\n    true\n    > bool = base.isNegativeInteger( 0.0 )\n    false\n    > bool = base.isNegativeInteger( 10.0 )\n    false\n\n    See Also\n    --------\n    base.isInteger, base.isNonNegativeInteger, base.isNonPositiveInteger, base.isPositiveInteger\n","base.isNegativeZero":"\nbase.isNegativeZero( x )\n    Tests if a double-precision floating-point numeric value is negative zero.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is negative zero.\n\n    Examples\n    --------\n    > var bool = base.isNegativeZero( -0.0 )\n    true\n    > bool = base.isNegativeZero( 0.0 )\n    false\n\n    See Also\n    --------\n    base.isPositiveZero\n","base.isNegativeZerof":"\nbase.isNegativeZerof( x )\n    Tests if a single-precision floating-point numeric value is negative zero.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is negative zero.\n\n    Examples\n    --------\n    > var bool = base.isNegativeZerof( -0.0 )\n    true\n    > bool = base.isNegativeZerof( 0.0 )\n    false\n\n    See Also\n    --------\n    base.isNegativeZero, base.isPositiveZerof\n","base.isNonNegativeFinite":"\nbase.isNonNegativeFinite( x )\n    Tests if a double-precision floating-point numeric value is a nonnegative\n    finite number.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is a nonnegative finite number.\n\n    Examples\n    --------\n    > var out = base.isNonNegativeFinite( 5.0 )\n    true\n    > out = base.isNonNegativeFinite( 3.14 )\n    true\n    > out = base.isNonNegativeFinite( 0.0 )\n    true\n    > out = base.isNonNegativeFinite( Infinity )\n    false\n    > out = base.isNonNegativeFinite( -3.14 )\n    false\n    > out = base.isNonNegativeFinite( NaN )\n    false\n\n    See Also\n    --------\n    base.isNegativeFinite, base.isPositiveFinite, base.isNonPositiveFinite\n","base.isNonNegativeInteger":"\nbase.isNonNegativeInteger( x )\n    Tests if a finite double-precision floating-point number is a nonnegative\n    integer.\n\n    The function assumes a finite number. If provided positive infinity, the\n    function will return `true`, when, in fact, the result is undefined.\n\n    The function does not distinguish between positive and negative zero.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is a nonnegative integer.\n\n    Examples\n    --------\n    > var bool = base.isNonNegativeInteger( 1.0 )\n    true\n    > bool = base.isNonNegativeInteger( 0.0 )\n    true\n    > bool = base.isNonNegativeInteger( -10.0 )\n    false\n\n    See Also\n    --------\n    base.isInteger, base.isNegativeInteger, base.isNonPositiveInteger, base.isPositiveInteger\n","base.isNonPositiveFinite":"\nbase.isNonPositiveFinite( x )\n    Tests if a double-precision floating-point numeric value is a nonpositive\n    finite number.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether the value is a nonpositive finite number.\n\n    Examples\n    --------\n    > var bool = base.isNonPositiveFinite( -3.14 )\n    true\n    > var bool = base.isNonPositiveFinite( 0.0 )\n    true\n    > var bool = base.isNonPositiveFinite( -Infinity )\n    false\n    > var bool = base.isNonPositiveFinite( 3.14 )\n    false\n    > var bool = base.isNonPositiveFinite( NaN )\n    false\n\n    See Also\n    --------\n    base.isNegativeFinite, base.isPositiveFinite, base.isNonNegativeFinite\n","base.isNonPositiveInteger":"\nbase.isNonPositiveInteger( x )\n    Tests if a finite double-precision floating-point number is a nonpositive\n    integer.\n\n    The function assumes a finite number. If provided negative infinity, the\n    function will return `true`, when, in fact, the result is undefined.\n\n    The function does not distinguish between positive and negative zero.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is a nonpositive integer.\n\n    Examples\n    --------\n    > var bool = base.isNonPositiveInteger( -1.0 )\n    true\n    > bool = base.isNonPositiveInteger( 0.0 )\n    true\n    > bool = base.isNonPositiveInteger( 10.0 )\n    false\n\n    See Also\n    --------\n    base.isInteger, base.isNegativeInteger, base.isNonNegativeInteger, base.isPositiveInteger\n","base.isOdd":"\nbase.isOdd( x )\n    Tests if a finite numeric value is an odd number.\n\n    The function assumes a finite number. If provided positive or negative\n    infinity, the function will return `true`, when, in fact, the result is\n    undefined.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is an odd number.\n\n    Examples\n    --------\n    > var bool = base.isOdd( 5.0 )\n    true\n    > bool = base.isOdd( -2.0 )\n    false\n    > bool = base.isOdd( 0.0 )\n    false\n    > bool = base.isOdd( NaN )\n    false\n\n    See Also\n    --------\n    base.isEven\n","base.isOddInt32":"\nbase.isOddInt32( x )\n    Tests if a 32-bit integer is odd.\n\n    Parameters\n    ----------\n    x: integer\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is an odd number.\n\n    Examples\n    --------\n    > var bool = base.isOddInt32( 5 )\n    true\n    > bool = base.isOddInt32( -2 )\n    false\n    > bool = base.isOddInt32( 0 )\n    false\n\n    See Also\n    --------\n    base.isEvenInt32, base.isOdd\n","base.isPositiveFinite":"\nbase.isPositiveFinite( x )\n    Tests if a double-precision floating-point numeric value is a positive\n    finite number.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is a positive finite number.\n\n    Examples\n    --------\n    > var bool = base.isPositiveFinite( 5.0 )\n    true\n    > bool = base.isPositiveFinite( 3.14 )\n    true\n    > bool = base.isPositiveFinite( 0.0 )\n    false\n    > bool = base.isPositiveFinite( Infinity )\n    false\n    > bool = base.isPositiveFinite( -3.14 )\n    false\n    > bool = base.isPositiveFinite( NaN )\n    false\n\n    See Also\n    --------\n    base.isNegativeFinite, base.isNonNegativeFinite, base.isNonPositiveFinite\n","base.isPositiveInteger":"\nbase.isPositiveInteger( x )\n    Tests if a finite double-precision floating-point number is a positive\n    integer.\n\n    The function assumes a finite number. If provided positive infinity, the\n    function will return `true`, when, in fact, the result is undefined.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is a positive integer.\n\n    Examples\n    --------\n    > var bool = base.isPositiveInteger( 1.0 )\n    true\n    > bool = base.isPositiveInteger( 0.0 )\n    false\n    > bool = base.isPositiveInteger( -10.0 )\n    false\n\n    See Also\n    --------\n    base.isInteger, base.isNegativeInteger, base.isNonNegativeInteger, base.isNonPositiveInteger\n","base.isPositiveZero":"\nbase.isPositiveZero( x )\n    Tests if a double-precision floating-point numeric value is positive zero.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is positive zero.\n\n    Examples\n    --------\n    > var bool = base.isPositiveZero( 0.0 )\n    true\n    > bool = base.isPositiveZero( -0.0 )\n    false\n\n    See Also\n    --------\n    base.isNegativeZero\n","base.isPositiveZerof":"\nbase.isPositiveZerof( x )\n    Tests if a single-precision floating-point numeric value is positive zero.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is positive zero.\n\n    Examples\n    --------\n    > var bool = base.isPositiveZerof( 0.0 )\n    true\n    > bool = base.isPositiveZerof( -0.0 )\n    false\n\n    See Also\n    --------\n    base.isNegativeZerof, base.isPositiveZero\n","base.isPow2Uint32":"\nbase.isPow2Uint32( x )\n    Tests whether an unsigned integer is a power of 2.\n\n    Parameters\n    ----------\n    x: integer\n        Unsigned integer.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is a power of 2.\n\n    Examples\n    --------\n    > var bool = base.isPow2Uint32( 2 )\n    true\n    > bool = base.isPow2Uint32( 5 )\n    false\n\n","base.isPrime":"\nbase.isPrime( x )\n    Tests if a number is prime.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is a prime number.\n\n    Examples\n    --------\n    > var bool = base.isPrime( 11.0 )\n    true\n    > bool = base.isPrime( 3.14 )\n    false\n\n    See Also\n    --------\n    base.isComposite, base.isInteger\n","base.isProbability":"\nbase.isProbability( x )\n    Tests if a double-precision floating-point number value is a probability.\n\n    A probability is defined as a number on the closed interval [0,1].\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is a probability.\n\n    Examples\n    --------\n    > var bool = base.isProbability( 0.5 )\n    true\n    > bool = base.isProbability( 3.14 )\n    false\n    > bool = base.isProbability( NaN )\n    false\n\n","base.isSafeInteger":"\nbase.isSafeInteger( x )\n    Tests if a finite double-precision floating-point number is a safe integer.\n\n    An integer valued number is \"safe\" when the number can be exactly\n    represented as a double-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is a safe integer.\n\n    Examples\n    --------\n    > var bool = base.isSafeInteger( 1.0 )\n    true\n    > bool = base.isSafeInteger( 2.0e200 )\n    false\n    > bool = base.isSafeInteger( 3.14 )\n    false\n\n","base.kebabcase":"\nbase.kebabcase( str )\n    Converts a string to kebab case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Kebab-cased string.\n\n    Examples\n    --------\n    > var out = base.kebabcase( 'Hello World!' )\n    'hello-world'\n    > out = base.kebabcase( 'I am a tiny little teapot' )\n    'i-am-a-tiny-little-teapot'\n\n    See Also\n    --------\n    base.camelcase, base.lowercase, base.pascalcase, base.snakecase, base.uppercase","base.kernelBetainc":"\nbase.kernelBetainc( x, a, b, regularized, upper )\n    Computes the kernel function for the regularized incomplete beta function.\n\n    The `regularized` and `upper` parameters specify whether to evaluate the\n    non-regularized and/or upper incomplete beta functions, respectively.\n\n    If provided `x < 0` or `x > 1`, the function returns `[ NaN, NaN ]`.\n\n    If provided `a < 0` or `b < 0`, the function returns `[ NaN, NaN ]`.\n\n    If provided `NaN` for `x`, `a`, or `b`, the function returns `[ NaN, NaN ]`.\n\n    Parameters\n    ----------\n    x: number\n        First function parameter.\n\n    a: number\n        Second function parameter.\n\n    b: number\n        Third function parameter.\n\n    regularized: boolean\n        Boolean indicating whether the function should evaluate the regularized\n        or non-regularized incomplete beta function.\n\n    upper: boolean\n        Boolean indicating whether the function should return the upper tail of\n        the incomplete beta function.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Function value and first derivative.\n\n    Examples\n    --------\n    > var out = base.kernelBetainc( 0.8, 1.0, 0.3, false, false )\n    [ ~1.277, ~0.926 ]\n    > out = base.kernelBetainc( 0.2, 1.0, 2.0, true, false )\n    [ 0.36, 1.6 ]\n\n\nbase.kernelBetainc.assign( x, a, b, regularized, upper, out, stride, offset )\n    Computes the kernel function for the regularized incomplete beta function.\n\n    The `regularized` and `upper` parameters specify whether to evaluate the\n    non-regularized and/or upper incomplete beta functions, respectively.\n\n    If provided `x < 0` or `x > 1`, the function returns `[ NaN, NaN ]`.\n\n    If provided `a < 0` or `b < 0`, the function returns `[ NaN, NaN ]`.\n\n    If provided `NaN` for `x`, `a`, or `b`, the function returns `[ NaN, NaN ]`.\n\n    Parameters\n    ----------\n    x: number\n        First function parameter.\n\n    a: number\n        Second function parameter.\n\n    b: number\n        Third function parameter.\n\n    regularized: boolean\n        Boolean indicating whether the function should evaluate the regularized\n        or non-regularized incomplete beta function.\n\n    upper: boolean\n        Boolean indicating whether the function should return the upper tail of\n        the incomplete beta function.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Function value and first derivative.\n\n    Examples\n    --------\n    > var out = [ 0.0, 0.0 ];\n    > var v = base.kernelBetainc.assign( 0.2, 1.0, 2.0, true, true, out, 1, 0 )\n    [ 0.64, 1.6 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.betainc\n","base.kernelBetainc.assign":"\nbase.kernelBetainc.assign( x, a, b, regularized, upper, out, stride, offset )\n    Computes the kernel function for the regularized incomplete beta function.\n\n    The `regularized` and `upper` parameters specify whether to evaluate the\n    non-regularized and/or upper incomplete beta functions, respectively.\n\n    If provided `x < 0` or `x > 1`, the function returns `[ NaN, NaN ]`.\n\n    If provided `a < 0` or `b < 0`, the function returns `[ NaN, NaN ]`.\n\n    If provided `NaN` for `x`, `a`, or `b`, the function returns `[ NaN, NaN ]`.\n\n    Parameters\n    ----------\n    x: number\n        First function parameter.\n\n    a: number\n        Second function parameter.\n\n    b: number\n        Third function parameter.\n\n    regularized: boolean\n        Boolean indicating whether the function should evaluate the regularized\n        or non-regularized incomplete beta function.\n\n    upper: boolean\n        Boolean indicating whether the function should return the upper tail of\n        the incomplete beta function.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Function value and first derivative.\n\n    Examples\n    --------\n    > var out = [ 0.0, 0.0 ];\n    > var v = base.kernelBetainc.assign( 0.2, 1.0, 2.0, true, true, out, 1, 0 )\n    [ 0.64, 1.6 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.betainc","base.kernelBetaincinv":"\nbase.kernelBetaincinv( a, b, p, q )\n    Computes the inverse of the lower incomplete beta function.\n\n    Probabilities `p` and `q` must satisfy `p = 1 - q`.\n\n    Parameters\n    ----------\n    a: number\n        First function parameter (a positive number).\n\n    b: number\n        Second function parameter (a positive number).\n\n    p: number\n        Probability.\n\n    q: number\n        Probability equal to `1-p`.\n\n    Returns\n    -------\n    out: Array\n        Two-element array holding function value `y` and `1-y`.\n\n    Examples\n    --------\n    > var y = base.kernelBetaincinv( 3.0, 3.0, 0.2, 0.8 )\n    [ ~0.327, ~0.673 ]\n    > y = base.kernelBetaincinv( 3.0, 3.0, 0.4, 0.6 )\n    [ ~0.446, ~0.554 ]\n    > y = base.kernelBetaincinv( 1.0, 6.0, 0.4, 0.6 )\n    [ ~0.082, ~0.918 ]\n    > y = base.kernelBetaincinv( 1.0, 6.0, 0.8, 0.2 )\n    [ ~0.235, ~0.765 ]\n\n    See Also\n    --------\n    base.betaincinv\n","base.kernelCos":"\nbase.kernelCos( x, y )\n    Computes the cosine of a double-precision floating-point number on the\n    interval [-π/4, π/4].\n\n    For increased accuracy, the number for which the cosine should be evaluated\n    can be supplied as a double-double number (i.e., a non-evaluated sum of two\n    double-precision floating-point numbers `x` and `y`).\n\n    The two numbers must satisfy `|y| < 0.5 * ulp( x )`.\n\n    If either argument is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    y: number\n        Tail of `x`.\n\n    Returns\n    -------\n    out: number\n        Cosine.\n\n    Examples\n    --------\n    > var out = base.kernelCos( 0.0, 0.0 )\n    ~1.0\n    > out = base.kernelCos( PI/6.0, 0.0 )\n    ~0.866\n    > out = base.kernelCos( 0.785, -1.144e-17 )\n    ~0.707\n    > out = base.kernelCos( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cos, base.kernelSin, base.kernelTan\n","base.kernelLog1p":"\nbase.kernelLog1p( f )\n    Computes `log(1+f) - f` for `1+f` in ~[sqrt(2)/2, sqrt(2)].\n\n    This function provides a common means for computing logarithms in base e.\n    Argument reduction and adding the final term of the polynomial must be done\n    by the caller for increased accuracy when different bases are used.\n\n    Parameters\n    ----------\n    f: number\n        Input value.\n\n    Returns\n    -------\n    out: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.kernelLog1p( 1.0 )\n    ~0.1931\n    > y = base.kernelLog1p( 1.4142135623730951 )\n    ~0.4672\n    > y = base.kernelLog1p( NaN )\n    NaN\n\n    See Also\n    --------\n    base.log1p\n","base.kernelSin":"\nbase.kernelSin( x, y )\n    Computes the sine of a double-precision floating-point number on [-π/4,π/4].\n\n    For increased accuracy, the number for which the cosine should be evaluated\n    can be supplied as a double-double number (i.e., a non-evaluated sum of two\n    double-precision floating-point numbers `x` and `y`).\n\n    The two numbers must satisfy `|y| < 0.5 * ulp( x )`.\n\n    If either argument is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    y: number\n        Tail of `x`.\n\n    Returns\n    -------\n    out: number\n        Sine.\n\n    Examples\n    --------\n    > var y = base.kernelSin( 0.0, 0.0 )\n    ~0.0\n    > y = base.kernelSin( PI/6.0, 0.0 )\n    ~0.5\n    > y = base.kernelSin( 0.619, 9.279e-18 )\n    ~0.58\n\n    > y = base.kernelSin( NaN, 0.0 )\n    NaN\n    > y = base.kernelSin( 2.0, NaN )\n    NaN\n    > y = base.kernelSin( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.kernelCos, base.kernelTan, base.sin\n","base.kernelTan":"\nbase.kernelTan( x, y, k )\n    Computes the tangent of a double-precision floating-point number on the\n    interval [-π/4, π/4].\n\n    For increased accuracy, the number for which the tangent should be evaluated\n    can be supplied as a double-double number (i.e., a non-evaluated sum of two\n    double-precision floating-point numbers `x` and `y`).\n\n    The numbers `x` and `y` must satisfy `|y| < 0.5 * ulp( x )`.\n\n    If either `x` or `y` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    y: number\n        Tail of `x`.\n\n    k: integer\n        If `k=1`, the function returns `tan(x+y)`. If `k=-1`, the function\n        returns the negative inverse `-1/tan(x+y)`.\n\n    Returns\n    -------\n    out: number\n        Tangent.\n\n    Examples\n    --------\n    > var out = base.kernelTan( PI/4.0, 0.0, 1 )\n    ~1.0\n    > out = base.kernelTan( PI/4.0, 0.0, -1 )\n    ~-1.0\n    > out = base.kernelTan( PI/6.0, 0.0, 1 )\n    ~0.577\n    > out = base.kernelTan( 0.664, 5.288e-17, 1 )\n    ~0.783\n\n    > out = base.kernelTan( NaN, 0.0, 1 )\n    NaN\n    > out = base.kernelTan( 3.0, NaN, 1 )\n    NaN\n    > out = base.kernelTan( 3.0, 0.0, NaN )\n    NaN\n\n    See Also\n    --------\n    base.kernelCos, base.kernelSin, base.tan\n","base.kroneckerDelta":"\nbase.kroneckerDelta( i, j )\n    Evaluates the Kronecker delta.\n\n    If `i == j`, the function returns `1`; otherwise, the function returns zero.\n\n    Parameters\n    ----------\n    i: number\n        Input value.\n\n    j: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.kroneckerDelta( 3.14, 0.0 )\n    0.0\n    > y = base.kroneckerDelta( 3.14, 3.14 )\n    1.0\n\n    See Also\n    --------\n    base.diracDelta\n","base.kroneckerDeltaf":"\nbase.kroneckerDeltaf( i, j )\n    Evaluates the Kronecker delta (single-precision).\n\n    If `i == j`, the function returns `1`; otherwise, the function returns zero.\n\n    Parameters\n    ----------\n    i: number\n        Input value.\n\n    j: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.kroneckerDeltaf( 3.14, 0.0 )\n    0.0\n    > y = base.kroneckerDeltaf( 3.14, 3.14 )\n    1.0\n\n    See Also\n    --------\n    base.kroneckerDelta\n","base.labs":"\nbase.labs( x )\n    Computes an absolute value of a signed 32-bit integer in two's complement\n    format.\n\n    Parameters\n    ----------\n    x: integer\n        Signed 32-bit integer.\n\n    Returns\n    -------\n    out: integer\n        Absolute value.\n\n    Examples\n    --------\n    > var v = base.labs( -1|0 )\n    1\n    > v = base.labs( 2|0 )\n    2\n    > v = base.labs( 0|0 )\n    0\n\n    See Also\n    --------\n    base.abs\n","base.last":"\nbase.last( str, n )\n    Returns the last `n` UTF-16 code units of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of UTF-16 code units to return.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.last( 'hello', 1 )\n    'o'\n    > out = base.last( 'JavaScript', 6 )\n    'Script'\n    > out = base.last( 'foo bar', 10 )\n    'foo bar'\n\n    See Also\n    --------\n    base.firstCodeUnit, base.lastCodePoint, base.lastGraphemeCluster\n","base.lastCodePoint":"\nbase.lastCodePoint( str, n )\n    Returns the last `n` Unicode code points of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of Unicode code points to return.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.lastCodePoint( 'hello world', 1 )\n    'd'\n    > out = base.lastCodePoint( 'JavaScript', 6 )\n    'Script'\n    > out = base.lastCodePoint( 'अनुच्छेद', 1 )\n    'द'\n\n    See Also\n    --------\n    base.firstCodePoint, base.lastGraphemeCluster, base.last\n","base.lastGraphemeCluster":"\nbase.lastGraphemeCluster( str, n )\n    Returns the last `n` grapheme clusters (i.e., user-perceived characters) of\n    a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of grapheme clusters to return.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.lastGraphemeCluster( 'beep', 1 )\n    'p'\n    > out = base.lastGraphemeCluster( 'Boop', 2 )\n    'op'\n    > out = base.lastGraphemeCluster( 'JavaScript', 6 )\n    'Script'\n\n    See Also\n    --------\n    base.firstGraphemeCluster, base.lastCodePoint, base.last\n","base.lcm":"\nbase.lcm( a, b )\n    Computes the least common multiple (lcm).\n\n    If either `a` or `b` is `0`, the function returns `0`.\n\n    Both `a` and `b` must have integer values; otherwise, the function returns\n    `NaN`.\n\n    Parameters\n    ----------\n    a: integer\n        First integer.\n\n    b: integer\n        Second integer.\n\n    Returns\n    -------\n    out: integer\n        Least common multiple.\n\n    Examples\n    --------\n    > var v = base.lcm( 21, 6 )\n    42\n\n    See Also\n    --------\n    base.gcd\n","base.ldexp":"\nbase.ldexp( frac, exp )\n    Multiplies a double-precision floating-point number by an integer power of\n    two; i.e., `x = frac * 2^exp`.\n\n    If `frac` equals positive or negative `zero`, `NaN`, or positive or negative\n    infinity, the function returns a value equal to `frac`.\n\n    Parameters\n    ----------\n    frac: number\n        Fraction.\n\n    exp: number\n        Exponent.\n\n    Returns\n    -------\n    out: number\n        Double-precision floating-point number equal to `frac * 2^exp`.\n\n    Examples\n    --------\n    > var x = base.ldexp( 0.5, 3 )\n    4.0\n    > x = base.ldexp( 4.0, -2 )\n    1.0\n    > x = base.ldexp( 0.0, 20 )\n    0.0\n    > x = base.ldexp( -0.0, 39 )\n    -0.0\n    > x = base.ldexp( NaN, -101 )\n    NaN\n    > x = base.ldexp( PINF, 11 )\n    Infinity\n    > x = base.ldexp( NINF, -118 )\n    -Infinity\n\n    See Also\n    --------\n    base.frexp\n","base.leftPad":"\nbase.leftPad( str, len, pad )\n    Left pads a string such that the padded string has a length of at least\n    `len`.\n\n    An output string is not guaranteed to have a length of exactly `len`, but to\n    have a length of at least `len`. To generate a padded string having a length\n    equal to `len`, post-process a padded string by trimming off excess\n    characters.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    len: integer\n        Minimum string length.\n\n    pad: string\n        String used to pad.\n\n    Returns\n    -------\n    out: string\n        Padded string.\n\n    Examples\n    --------\n    > var out = base.leftPad( 'a', 5, ' ' )\n    '    a'\n    > out = base.leftPad( 'beep', 10, 'b' )\n    'bbbbbbbeep'\n    > out = base.leftPad( 'boop', 12, 'beep' )\n    'beepbeepboop'\n\n    See Also\n    --------\n    base.rightPad\n","base.leftTrim":"\nbase.leftTrim( str )\n    Trims whitespace from the beginning of a string.\n\n    \"Whitespace\" is defined as the following characters:\n\n    - \\f\n    - \\n\n    - \\r\n    - \\t\n    - \\v\n    - \\u0020\n    - \\u00a0\n    - \\u1680\n    - \\u2000-\\u200a\n    - \\u2028\n    - \\u2029\n    - \\u202f\n    - \\u205f\n    - \\u3000\n    - \\ufeff\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Trimmed string.\n\n    Examples\n    --------\n    > var out = base.leftTrim( ' \\r\\n\\t  Beep \\t\\t\\n  ' )\n    'Beep \\t\\t\\n  '\n\n    See Also\n    --------\n    base.rightTrim, base.trim\n","base.ln":"\nbase.ln( x )\n    Evaluates the natural logarithm of a double-precision floating-point number.\n\n    For negative numbers, the natural logarithm is not defined.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.ln( 4.0 )\n    ~1.386\n    > y = base.ln( 0.0 )\n    -Infinity\n    > y = base.ln( PINF )\n    Infinity\n    > y = base.ln( NaN )\n    NaN\n    > y = base.ln( -4.0 )\n    NaN\n\n    See Also\n    --------\n    base.exp, base.log10, base.log1p, base.log2\n","base.log":"\nbase.log( x, b )\n    Computes the base `b` logarithm of a double-precision floating-point number.\n\n    For negative `b` or `x`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    b: number\n        Base.\n\n    Returns\n    -------\n    y: number\n        Logarithm (base `b`).\n\n    Examples\n    --------\n    > var y = base.log( 100.0, 10.0 )\n    2.0\n    > y = base.log( 16.0, 2.0 )\n    4.0\n    > y = base.log( 5.0, 1.0 )\n    Infinity\n    > y = base.log( NaN, 2.0 )\n    NaN\n    > y = base.log( 1.0, NaN )\n    NaN\n    > y = base.log( -4.0, 2.0 )\n    NaN\n    > y = base.log( 4.0, -2.0 )\n    NaN\n\n    See Also\n    --------\n    base.exp, base.ln, base.log10, base.log1p, base.log2\n","base.log1mexp":"\nbase.log1mexp( x )\n    Evaluates the natural logarithm of `1-exp(-|x|)`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.log1mexp( -10.0 )\n    ~-0.00005\n    > y = base.log1mexp( 0.0 )\n    -Infinity\n    > y = base.log1mexp( 5.0 )\n    ~-0.00676\n    > y = base.log1mexp( 10.0 )\n    ~-0.00005\n    > y = base.log1mexp( NaN )\n    NaN\n\n    See Also\n    --------\n    base.exp, base.ln, base.log1p, base.log1pexp","base.log1p":"\nbase.log1p( x )\n    Evaluates the natural logarithm of `1+x`.\n\n    For `x < -1`, the function returns `NaN`, as the natural logarithm is not\n    defined for negative numbers.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.log1p( 4.0 )\n    ~1.609\n    > y = base.log1p( -1.0 )\n    -Infinity\n    > y = base.log1p( 0.0 )\n    0.0\n    > y = base.log1p( -0.0 )\n    -0.0\n    > y = base.log1p( -2.0 )\n    NaN\n    > y = base.log1p( NaN )\n    NaN\n\n    See Also\n    --------\n    base.ln, base.log\n","base.log1pexp":"\nbase.log1pexp( x )\n    Evaluates the natural logarithm of `1+exp(x)`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.log1pexp( -10.0 )\n    ~0.000045\n    > y = base.log1pexp( 0.0 )\n    ~0.693147\n    > y = base.log1pexp( 5.0 )\n    ~5.006715\n    > y = base.log1pexp( 34.0 )\n    34.0\n    > y = base.log1pexp( NaN )\n    NaN\n\n    See Also\n    --------\n    base.exp, base.ln, base.log1mexp, base.log1p","base.log1pmx":"\nbase.log1pmx( x )\n    Evaluates `ln(1+x) - x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > base.log1pmx( 1.1 )\n    ~-0.358\n    > base.log1pmx( 0.99 )\n    ~-0.302\n    > base.log1pmx( -0.99 )\n    ~-3.615\n    > base.log1pmx( -1.1 )\n    NaN\n    > base.log1pmx( NaN )\n    NaN\n\n    See Also\n    --------\n    base.ln, base.log1p","base.log2":"\nbase.log2( x )\n    Evaluates the binary logarithm (base two).\n\n    For negative numbers, the binary logarithm is not defined.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.log2( 4.0 )\n    2.0\n    > y = base.log2( 8.0 )\n    3.0\n    > y = base.log2( 0.0 )\n    -Infinity\n    > y = base.log2( PINF )\n    Infinity\n    > y = base.log2( NaN )\n    NaN\n    > y = base.log2( -4.0 )\n    NaN\n\n    See Also\n    --------\n    base.exp2, base.ln, base.log\n","base.log10":"\nbase.log10( x )\n    Evaluates the common logarithm (base 10).\n\n    For negative numbers, the common logarithm is not defined.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.log10( 100.0 )\n    2.0\n    > y = base.log10( 8.0 )\n    ~0.903\n    > y = base.log10( 0.0 )\n    -Infinity\n    > y = base.log10( PINF )\n    Infinity\n    > y = base.log10( NaN )\n    NaN\n    > y = base.log10( -4.0 )\n    NaN\n\n    See Also\n    --------\n    base.exp10, base.ln, base.log\n","base.logaddexp":"\nbase.logaddexp( x, y )\n    Computes the natural logarithm of `exp(x) + exp(y)`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    y: number\n        Input value.\n\n    Returns\n    -------\n    v: number\n        Function value.\n\n    Examples\n    --------\n    > var v = base.logaddexp( 90.0, 90.0 )\n    ~90.6931\n    > v = base.logaddexp( -20.0, 90.0 )\n    90.0\n    > v = base.logaddexp( 0.0, -100.0 )\n    ~3.7201e-44\n    > v = base.logaddexp( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.exp, base.ln\n","base.logit":"\nbase.logit( p )\n    Evaluates the logit function.\n\n    Let `p` be the probability of some event. The logit function is defined as\n    the logarithm of the odds `p / (1-p)`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.logit( 0.2 )\n    ~-1.386\n    > y = base.logit( 0.9 )\n    ~2.197\n    > y = base.logit( -4.0 )\n    NaN\n    > y = base.logit( 1.5 )\n    NaN\n    > y = base.logit( NaN )\n    NaN\n\n","base.lowercase":"\nbase.lowercase( str )\n    Converts a string to lowercase.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Lowercase string.\n\n    Examples\n    --------\n    > var out = base.lowercase( 'bEEp' )\n    'beep'\n\n    See Also\n    --------\n    base.snakecase, base.uppercase\n","base.lucas":"\nbase.lucas( n )\n    Computes the nth Lucas number.\n\n    Lucas numbers follow the recurrence relation\n\n      L_n = L_{n-1} + L_{n-2}\n\n    with seed values L_0 = 2 and L_1 = 1.\n\n    If `n` is greater than `76`, the function returns `NaN`, as larger Lucas\n    numbers cannot be accurately represented due to limitations of double-\n    precision floating-point format.\n\n    If not provided a nonnegative integer value, the function returns `NaN`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Input value.\n\n    Returns\n    -------\n    y: integer\n        Lucas number.\n\n    Examples\n    --------\n    > var y = base.lucas( 0 )\n    2\n    > y = base.lucas( 1 )\n    1\n    > y = base.lucas( 2 )\n    3\n    > y = base.lucas( 3 )\n    4\n    > y = base.lucas( 4 )\n    7\n    > y = base.lucas( 77 )\n    NaN\n    > y = base.lucas( NaN )\n    NaN\n\n    See Also\n    --------\n    base.fibonacci, base.negalucas\n","base.lucaspoly":"\nbase.lucaspoly( n, x )\n    Evaluates a Lucas polynomial.\n\n    Parameters\n    ----------\n    n: integer\n        Lucas polynomial to evaluate.\n\n    x: number\n        Value at which to evaluate the Lucas polynomial.\n\n    Returns\n    -------\n    out: number\n        Evaluated Lucas polynomial.\n\n    Examples\n    --------\n    // 2^5 + 5*2^3 + 5*2\n    > var v = base.lucaspoly( 5, 2.0 )\n    82.0\n\n\nbase.lucaspoly.factory( n )\n    Returns a function for evaluating a Lucas polynomial.\n\n    Parameters\n    ----------\n    n: integer\n        Lucas polynomial to evaluate.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a Lucas polynomial.\n\n    Examples\n    --------\n    > var polyval = base.lucaspoly.factory( 5 );\n\n    // 1^5 + 5*1^2 + 5\n    > var v = polyval( 1.0 )\n    11.0\n\n    // 2^5 + 5*2^3 + 5*2\n    > v = polyval( 2.0 )\n    82.0\n\n    See Also\n    --------\n    base.evalpoly, base.fibpoly\n","base.lucaspoly.factory":"\nbase.lucaspoly.factory( n )\n    Returns a function for evaluating a Lucas polynomial.\n\n    Parameters\n    ----------\n    n: integer\n        Lucas polynomial to evaluate.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a Lucas polynomial.\n\n    Examples\n    --------\n    > var polyval = base.lucaspoly.factory( 5 );\n\n    // 1^5 + 5*1^2 + 5\n    > var v = polyval( 1.0 )\n    11.0\n\n    // 2^5 + 5*2^3 + 5*2\n    > v = polyval( 2.0 )\n    82.0\n\n    See Also\n    --------\n    base.evalpoly, base.fibpoly","base.max":"\nbase.max( x, y )\n    Returns the maximum value.\n\n    If any argument is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    > var v = base.max( 3.14, 4.2 )\n    4.2\n    > v = base.max( 3.14, NaN )\n    NaN\n    > v = base.max( +0.0, -0.0 )\n    +0.0\n\n    See Also\n    --------\n    base.maxabs, base.maxn, base.min\n","base.maxabs":"\nbase.maxabs( x, y )\n    Returns the maximum absolute value.\n\n    If any argument is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    > var v = base.maxabs( 3.14, -4.2 )\n    4.2\n    > v = base.maxabs( 3.14, NaN )\n    NaN\n    > v = base.maxabs( +0.0, -0.0 )\n    +0.0\n\n    See Also\n    --------\n    base.max, base.minabs\n","base.maxabsn":"\nbase.maxabsn( [x[, y[, ...args]]] )\n    Returns the maximum absolute value.\n\n    If any argument is `NaN`, the function returns `NaN`.\n\n    When an empty set is considered a subset of the extended reals (all real\n    numbers, including positive and negative infinity), negative infinity is the\n    least upper bound. Similar to zero being the identity element for the sum of\n    an empty set and to one being the identity element for the product of an\n    empty set, negative infinity is the identity element for the maximum, and\n    thus, if not provided any arguments, the function returns `+infinity` (i.e.,\n    the absolute value of `-infinity`).\n\n    Parameters\n    ----------\n    x: number (optional)\n        First number.\n\n    y: number (optional)\n        Second number.\n\n    args: ...number (optional)\n        Numbers.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    > var v = base.maxabsn( 3.14, -4.2 )\n    4.2\n    > v = base.maxabsn( 5.9, 3.14, 4.2 )\n    5.9\n    > v = base.maxabsn( 3.14, NaN )\n    NaN\n    > v = base.maxabsn( +0.0, -0.0 )\n    +0.0\n\n    See Also\n    --------\n    base.maxn, base.maxabs, base.minabsn\n","base.maxn":"\nbase.maxn( [x[, y[, ...args]]] )\n    Returns the maximum value.\n\n    If any argument is `NaN`, the function returns `NaN`.\n\n    When an empty set is considered a subset of the extended reals (all real\n    numbers, including positive and negative infinity), negative infinity is the\n    least upper bound. Similar to zero being the identity element for the sum of\n    an empty set and to one being the identity element for the product of an\n    empty set, negative infinity is the identity element for the maximum, and\n    thus, if not provided any arguments, the function returns negative infinity.\n\n    Parameters\n    ----------\n    x: number (optional)\n        First number.\n\n    y: number (optional)\n        Second number.\n\n    args: ...number (optional)\n        Numbers.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    > var v = base.maxn( 3.14, 4.2 )\n    4.2\n    > v = base.maxn( 5.9, 3.14, 4.2 )\n    5.9\n    > v = base.maxn( 3.14, NaN )\n    NaN\n    > v = base.maxn( +0.0, -0.0 )\n    +0.0\n\n    See Also\n    --------\n    base.max, base.maxabsn, base.minn\n","base.min":"\nbase.min( x, y )\n    Returns the minimum value.\n\n    If any argument is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    > var v = base.min( 3.14, 4.2 )\n    3.14\n    > v = base.min( 3.14, NaN )\n    NaN\n    > v = base.min( +0.0, -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.max, base.minabs, base.minn\n","base.minabs":"\nbase.minabs( x, y )\n    Returns the minimum absolute value.\n\n    If any argument is `NaN`, the function returns `NaN`.\n\n    When an empty set is considered a subset of the extended reals (all real\n    numbers, including positive and negative infinity), positive infinity is the\n    greatest upper bound. Similar to zero being the identity element for the sum\n    of an empty set and to one being the identity element for the product of an\n    empty set, positive infinity is the identity element for the minimum, and\n    thus, if not provided any arguments, the function returns positive infinity.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    > var v = base.minabs( 3.14, -4.2 )\n    3.14\n    > v = base.minabs( 3.14, NaN )\n    NaN\n    > v = base.minabs( +0.0, -0.0 )\n    +0.0\n\n    See Also\n    --------\n    base.maxabs, base.min\n","base.minabsn":"\nbase.minabsn( [x[, y[, ...args]]] )\n    Returns the minimum absolute value.\n\n    If any argument is `NaN`, the function returns `NaN`.\n\n    When an empty set is considered a subset of the extended reals (all real\n    numbers, including positive and negative infinity), positive infinity is the\n    greatest upper bound. Similar to zero being the identity element for the sum\n    of an empty set and to one being the identity element for the product of an\n    empty set, positive infinity is the identity element for the minimum, and\n    thus, if not provided any arguments, the function returns positive infinity.\n\n    Parameters\n    ----------\n    x: number (optional)\n        First number.\n\n    y: number (optional)\n        Second number.\n\n    args: ...number (optional)\n        Numbers.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    > var v = base.minabsn( 3.14, -4.2 )\n    3.14\n    > v = base.minabsn( 5.9, 3.14, 4.2 )\n    3.14\n    > v = base.minabsn( 3.14, NaN )\n    NaN\n    > v = base.minabsn( +0.0, -0.0 )\n    +0.0\n\n    See Also\n    --------\n    base.maxabsn, base.minn, base.minabs\n","base.minmax":"\nbase.minmax( x, y )\n    Returns the minimum and maximum values.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum values.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: Array<number>\n        Minimum and maximum values.\n\n    Examples\n    --------\n    > var v = base.minmax( 3.14, 4.2 )\n    [ 3.14, 4.2 ]\n    > v = base.minmax( 3.14, NaN )\n    [ NaN, NaN ]\n    > v = base.minmax( +0.0, -0.0 )\n    [ -0.0, +0.0 ]\n\n\nbase.minmax.assign( x, y, out, stride, offset )\n    Returns the minimum and maximum values and assigns results to a provided\n    output array.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum values.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    out: Array|TypedArray|Object\n        Output object.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Minimum and maximum values.\n\n    Examples\n    --------\n    > var out = [ 0.0, 0.0 ];\n    > var v = base.minmax.assign( 3.14, -1.5, out, 1, 0 )\n    [ -1.5, 3.14 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.max, base.min, base.minmaxabs","base.minmax.assign":"\nbase.minmax.assign( x, y, out, stride, offset )\n    Returns the minimum and maximum values and assigns results to a provided\n    output array.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum values.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    out: Array|TypedArray|Object\n        Output object.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Minimum and maximum values.\n\n    Examples\n    --------\n    > var out = [ 0.0, 0.0 ];\n    > var v = base.minmax.assign( 3.14, -1.5, out, 1, 0 )\n    [ -1.5, 3.14 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.max, base.min, base.minmaxabs","base.minmaxabs":"\nbase.minmaxabs( x, y )\n    Returns the minimum and maximum absolute values.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum absolute values.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: Array<number>\n        Minimum and maximum absolute values.\n\n    Examples\n    --------\n    > var v = base.minmaxabs( 3.14, 4.2 )\n    [ 3.14, 4.2 ]\n    > v = base.minmaxabs( -5.9, 3.14)\n    [ 3.14, 5.9 ]\n    > v = base.minmaxabs( 3.14, NaN )\n    [ NaN, NaN ]\n    > v = base.minmaxabs( +0.0, -0.0 )\n    [ 0.0, 0.0 ]\n\n\nbase.minmaxabs.assign( x, y, out, stride, offset )\n    Returns the minimum and maximum absolute values.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum absolute values.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    out: Array|TypedArray|Object\n        Output object.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Minimum and maximum absolute values.\n\n    Examples\n    --------\n    > var out = [ 0.0, 0.0 ];\n    > var v = base.minmaxabs.assign( 3.14, -3.14, out, 1, 0 )\n    [ 3.14, 3.14 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.maxabs, base.minabs, base.minmax\n","base.minmaxabs.assign":"\nbase.minmaxabs.assign( x, y, out, stride, offset )\n    Returns the minimum and maximum absolute values.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum absolute values.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    out: Array|TypedArray|Object\n        Output object.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Minimum and maximum absolute values.\n\n    Examples\n    --------\n    > var out = [ 0.0, 0.0 ];\n    > var v = base.minmaxabs.assign( 3.14, -3.14, out, 1, 0 )\n    [ 3.14, 3.14 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.maxabs, base.minabs, base.minmax","base.minmaxabsn":"\nbase.minmaxabsn( [x[, y[, ...args]]] )\n    Returns the minimum and maximum absolute values.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum absolute values.\n\n    When an empty set is considered a subset of the extended reals (all real\n    numbers, including positive and negative infinity), positive infinity is the\n    greatest lower bound and negative infinity is the least upper bound. Similar\n    to zero being the identity element for the sum of an empty set and to one\n    being the identity element for the product of an empty set, positive\n    infinity is the identity element for the minimum and negative infinity is\n    the identity element for the maximum, and thus, if not provided any\n    arguments, the function returns positive infinity for both the minimum and\n    maximum absolute values.\n\n    Parameters\n    ----------\n    x: number (optional)\n        First number.\n\n    y: number (optional)\n        Second number.\n\n    args: ...number (optional)\n        Numbers.\n\n    Returns\n    -------\n    out: Array<number>\n        Minimum and maximum absolute values.\n\n    Examples\n    --------\n    > var v = base.minmaxabsn( 3.14, 4.2 )\n    [ 3.14, 4.2 ]\n    > v = base.minmaxabsn( -5.9, 3.14, 4.2 )\n    [ 3.14, 5.9 ]\n    > v = base.minmaxabsn( 3.14, NaN )\n    [ NaN, NaN ]\n    > v = base.minmaxabsn( +0.0, -0.0 )\n    [ 0.0, 0.0 ]\n    > v = base.minmaxabsn( 3.14 )\n    [ 3.14, 3.14 ]\n\n\nbase.minmaxabsn.assign( [x[, y[, ...args]]], out, stride, offset )\n    Returns the minimum and maximum absolute values.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum absolute values.\n\n    Parameters\n    ----------\n    x: number (optional)\n        First number.\n\n    y: number (optional)\n        Second number.\n\n    args: ...number (optional)\n        Numbers.\n\n    out: Array|TypedArray|Object\n        Output object.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Minimum and maximum absolute values.\n\n    Examples\n    --------\n    > var out = [ 0.0, 0.0 ];\n    > var v = base.minmaxabsn.assign( 3.14, out, 1, 0 )\n    [ 3.14, 3.14 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.maxabsn, base.minabsn, base.minmaxn\n","base.minmaxabsn.assign":"\nbase.minmaxabsn.assign( [x[, y[, ...args]]], out, stride, offset )\n    Returns the minimum and maximum absolute values.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum absolute values.\n\n    Parameters\n    ----------\n    x: number (optional)\n        First number.\n\n    y: number (optional)\n        Second number.\n\n    args: ...number (optional)\n        Numbers.\n\n    out: Array|TypedArray|Object\n        Output object.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Minimum and maximum absolute values.\n\n    Examples\n    --------\n    > var out = [ 0.0, 0.0 ];\n    > var v = base.minmaxabsn.assign( 3.14, out, 1, 0 )\n    [ 3.14, 3.14 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.maxabsn, base.minabsn, base.minmaxn","base.minmaxn":"\nbase.minmaxn( [x[, y[, ...args]]] )\n    Returns the minimum and maximum values.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum values.\n\n    When an empty set is considered a subset of the extended reals (all real\n    numbers, including positive and negative infinity), positive infinity is the\n    greatest lower bound and negative infinity is the least upper bound. Similar\n    to zero being the identity element for the sum of an empty set and to one\n    being the identity element for the product of an empty set, positive\n    infinity is the identity element for the minimum and negative infinity is\n    the identity element for the maximum, and thus, if not provided any\n    arguments, the function returns positive infinity for the minimum value and\n    negative infinity for the maximum value.\n\n    Parameters\n    ----------\n    x: number (optional)\n        First number.\n\n    y: number (optional)\n        Second number.\n\n    args: ...number (optional)\n        Numbers.\n\n    Returns\n    -------\n    out: Array<number>\n        Minimum and maximum values.\n\n    Examples\n    --------\n    > var v = base.minmaxn( 3.14, 4.2 )\n    [ 3.14, 4.2 ]\n    > v = base.minmaxn( 5.9, 3.14, 4.2 )\n    [ 3.14, 5.9 ]\n    > v = base.minmaxn( 3.14, NaN )\n    [ NaN, NaN ]\n    > v = base.minmaxn( +0.0, -0.0 )\n    [ -0.0, +0.0 ]\n    > v = base.minmaxn( 3.14 )\n    [ 3.14, 3.14 ]\n\n\nbase.minmaxn.assign( [x[, y[, ...args]]], out, stride, offset )\n    Returns the minimum and maximum values and assigns results to a provided\n    output array.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum values.\n\n    Parameters\n    ----------\n    x: number (optional)\n        First number.\n\n    y: number (optional)\n        Second number.\n\n    args: ...number (optional)\n        Numbers.\n\n    out: Array|TypedArray|Object\n        Output object.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Minimum and maximum values.\n\n    Examples\n    --------\n    > var out = [ 0.0, 0.0 ];\n    > var v = base.minmaxn.assign( 3.14, -1.5, out, 1, 0 )\n    [ -1.5, 3.14 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.maxn, base.minn, base.minmaxabsn","base.minmaxn.assign":"\nbase.minmaxn.assign( [x[, y[, ...args]]], out, stride, offset )\n    Returns the minimum and maximum values and assigns results to a provided\n    output array.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum values.\n\n    Parameters\n    ----------\n    x: number (optional)\n        First number.\n\n    y: number (optional)\n        Second number.\n\n    args: ...number (optional)\n        Numbers.\n\n    out: Array|TypedArray|Object\n        Output object.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Minimum and maximum values.\n\n    Examples\n    --------\n    > var out = [ 0.0, 0.0 ];\n    > var v = base.minmaxn.assign( 3.14, -1.5, out, 1, 0 )\n    [ -1.5, 3.14 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.maxn, base.minn, base.minmaxabsn","base.minn":"\nbase.minn( [x[, y[, ...args]]] )\n    Returns the minimum value.\n\n    If any argument is `NaN`, the function returns `NaN`.\n\n    When an empty set is considered a subset of the extended reals (all real\n    numbers, including positive and negative infinity), positive infinity is the\n    greatest lower bound. Similar to zero being the identity element for the sum\n    of an empty set and to one being the identity element for the product of an\n    empty set, positive infinity is the identity element for the minimum, and\n    thus, if not provided any arguments, the function returns positive infinity.\n\n    Parameters\n    ----------\n    x: number (optional)\n        First number.\n\n    y: number (optional)\n        Second number.\n\n    args: ...number (optional)\n        Numbers.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    > var v = base.minn( 3.14, 4.2 )\n    3.14\n    > v = base.minn( 5.9, 3.14, 4.2 )\n    3.14\n    > v = base.minn( 3.14, NaN )\n    NaN\n    > v = base.minn( +0.0, -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.maxn, base.min, base.minabsn\n","base.modf":"\nbase.modf( x )\n    Decomposes a double-precision floating-point number into integral and\n    fractional parts, each having the same type and sign as the input value.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    out: Array<number>\n        Integral and fractional parts.\n\n    Examples\n    --------\n    > var parts = base.modf( 3.14 )\n    [ 3.0, 0.14000000000000012 ]\n    > parts = base.modf( 3.14 )\n    [ 3.0, 0.14000000000000012 ]\n    > parts = base.modf( +0.0 )\n    [ +0.0, +0.0 ]\n    > parts = base.modf( -0.0 )\n    [ -0.0, -0.0 ]\n    > parts = base.modf( PINF )\n    [ Infinity, +0.0 ]\n    > parts = base.modf( NINF )\n    [ -Infinity, -0.0 ]\n    > parts = base.modf( NaN )\n    [ NaN, NaN ]\n\n\nbase.modf.assign( x, out, stride, offset )\n    Decomposes a double-precision floating-point number into integral and\n    fractional parts, each having the same type and sign as the input value,\n    and assigns results to a provided output array.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Integral and fractional parts.\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var parts = base.modf.assign( 3.14, out, 1, 0 )\n    <Float64Array>[ 3.0, 0.14000000000000012 ]\n    > var bool = ( parts === out )\n    true\n","base.modf.assign":"\nbase.modf.assign( x, out, stride, offset )\n    Decomposes a double-precision floating-point number into integral and\n    fractional parts, each having the same type and sign as the input value,\n    and assigns results to a provided output array.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Integral and fractional parts.\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var parts = base.modf.assign( 3.14, out, 1, 0 )\n    <Float64Array>[ 3.0, 0.14000000000000012 ]\n    > var bool = ( parts === out )\n    true","base.mul":"\nbase.mul( x, y )\n    Multiplies two double-precision floating-point numbers `x` and `y`.\n\n    Parameters\n    ----------\n    x: number\n        First input value.\n\n    y: number\n        Second input value.\n\n    Returns\n    -------\n    z: number\n        Result.\n\n    Examples\n    --------\n    > var v = base.mul( -1.0, 5.0 )\n    -5.0\n    > v = base.mul( 2.0, 5.0 )\n    10.0\n    > v = base.mul( 0.0, 5.0 )\n    0.0\n    > v = base.mul( -0.0, 0.0 )\n    -0.0\n    > v = base.mul( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.add, base.div, base.sub\n","base.mulf":"\nbase.mulf( x, y )\n    Multiplies two single-precision floating-point numbers `x` and `y`.\n\n    Parameters\n    ----------\n    x: number\n        First input value.\n\n    y: number\n        Second input value.\n\n    Returns\n    -------\n    z: number\n        Result.\n\n    Examples\n    --------\n    > var v = base.mulf( -1.0, 5.0 )\n    -5.0\n    > v = base.mulf( 2.0, 5.0 )\n    10.0\n    > v = base.mulf( 0.0, 5.0 )\n    0.0\n    > v = base.mulf( -0.0, 0.0 )\n    -0.0\n    > v = base.mulf( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.addf, base.divf, base.mul, base.subf\n","base.ndarray":"\nbase.ndarray( dtype, buffer, shape, strides, offset, order )\n    Returns an ndarray.\n\n    Parameters\n    ----------\n    dtype: string\n        Underlying data type.\n\n    buffer: ArrayLikeObject|TypedArray|Buffer\n        Data buffer. A data buffer must be an array-like object (i.e., have a\n        `length` property). For data buffers which are not indexed collections\n        (i.e., collections which cannot support direct index access, such as\n        `buffer[ index ]`; e.g., Complex64Array, Complex128Array, etc), a data\n        buffer should provide `#.get( idx )` and `#.set( v[, idx] )` methods.\n        Note that, for `set` methods, the value to set should be the first\n        argument, followed by the linear index, similar to the native typed\n        array `set` method.\n\n    shape: ArrayLikeObject<integer>\n        Array shape.\n\n    strides: ArrayLikeObject<integer>\n        Array strides.\n\n    offset: integer\n        Index offset.\n\n    order: string\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran-style).\n\n    Returns\n    -------\n    ndarray: ndarray\n        ndarray instance.\n\n    Examples\n    --------\n    // Create a new instance...\n    > var b = [ 1, 2, 3, 4 ]; // underlying data buffer\n    > var d = [ 2, 2 ]; // shape\n    > var s = [ 2, 1 ]; // strides\n    > var o = 0; // index offset\n    > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' )\n    <ndarray>\n\n    // Get an element using subscripts:\n    > var v = arr.get( 1, 1 )\n    4\n\n    // Get an element using a linear index:\n    > v = arr.iget( 3 )\n    4\n\n    // Set an element using subscripts:\n    > arr.set( 1, 1, 40 );\n    > arr.get( 1, 1 )\n    40\n\n    // Set an element using a linear index:\n    > arr.iset( 3, 99 );\n    > arr.get( 1, 1 )\n    99\n\n\nbase.ndarray.prototype.byteLength\n    Size (in bytes) of the array (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of the array.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.byteLength\n    32\n\n\nbase.ndarray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.BYTES_PER_ELEMENT\n    8\n\n\nbase.ndarray.prototype.data\n    Pointer to the underlying data buffer.\n\n    Returns\n    -------\n    buf: ArrayLikeObject|TypedArray|Buffer\n        Underlying data buffer.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var buf = arr.data\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n\nbase.ndarray.prototype.dtype\n    Underlying data type.\n\n    Returns\n    -------\n    dtype: string\n        Underlying data type.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var dt = arr.dtype\n    'float64'\n\n\nbase.ndarray.prototype.flags\n    Meta information, such as information concerning the memory layout of the\n    array.\n\n    Returns\n    -------\n    flags: Object\n        Info object.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var fl = arr.flags\n    {...}\n\n\nbase.ndarray.prototype.length\n    Length of the array (i.e., number of elements).\n\n    Returns\n    -------\n    len: integer\n        Array length.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var len = arr.length\n    4\n\n\nbase.ndarray.prototype.ndims\n    Number of dimensions.\n\n    Returns\n    -------\n    ndims: integer\n        Number of dimensions.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var n = arr.ndims\n    2\n\n\nbase.ndarray.prototype.offset\n    Index offset which specifies the buffer index at which to start iterating\n    over array elements.\n\n    Returns\n    -------\n    offset: integer\n        Index offset.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.offset\n    0\n\n\nbase.ndarray.prototype.order: string\n    Array order.\n\n    The array order is either row-major (C-style) or column-major (Fortran-\n    style).\n\n    Returns\n    -------\n    order: string\n        Array order.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var ord = arr.order\n    'row-major'\n\n\nbase.ndarray.prototype.shape\n    Array shape.\n\n    Returns\n    -------\n    shape: Array\n        Array shape.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sh = arr.shape\n    [ 2, 2 ]\n\n\nbase.ndarray.prototype.strides\n    Index strides which specify how to access data along corresponding array\n    dimensions.\n\n    Returns\n    -------\n    strides: Array\n        Index strides.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var st = arr.strides\n    [ 2, 1 ]\n\n\nbase.ndarray.prototype.get( ...idx )\n    Returns an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.get( 1, 1 )\n    4.0\n\n\nbase.ndarray.prototype.iget( idx )\n    Returns an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the input argument is ignored and, for clarity,\n    should not be provided.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.iget( 3 )\n    4.0\n\n\nbase.ndarray.prototype.set( ...idx, v )\n    Sets an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: ndarray\n        ndarray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > arr.set( 1, 1, -4.0 );\n    > arr.get( 1, 1 )\n    -4.0\n\n\nbase.ndarray.prototype.iset( idx, v )\n    Sets an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the first, and only, argument should be the\n    value to set.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: ndarray\n        ndarray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > arr.iset( 3, -4.0 );\n    > arr.iget( 3 )\n    -4.0\n\n\nbase.ndarray.prototype.toString()\n    Serializes an ndarray as a string.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    str: string\n        Serialized ndarray string.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toString()\n    '...'\n\n\nbase.ndarray.prototype.toJSON()\n    Serializes an ndarray as a JSON object.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toJSON()\n    {...}\n\n    See Also\n    --------\n    array, ndarray\n","base.ndarray.prototype.byteLength":"\nbase.ndarray.prototype.byteLength\n    Size (in bytes) of the array (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of the array.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.byteLength\n    32","base.ndarray.prototype.BYTES_PER_ELEMENT":"\nbase.ndarray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.BYTES_PER_ELEMENT\n    8","base.ndarray.prototype.data":"\nbase.ndarray.prototype.data\n    Pointer to the underlying data buffer.\n\n    Returns\n    -------\n    buf: ArrayLikeObject|TypedArray|Buffer\n        Underlying data buffer.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var buf = arr.data\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]","base.ndarray.prototype.dtype":"\nbase.ndarray.prototype.dtype\n    Underlying data type.\n\n    Returns\n    -------\n    dtype: string\n        Underlying data type.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var dt = arr.dtype\n    'float64'","base.ndarray.prototype.flags":"\nbase.ndarray.prototype.flags\n    Meta information, such as information concerning the memory layout of the\n    array.\n\n    Returns\n    -------\n    flags: Object\n        Info object.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var fl = arr.flags\n    {...}","base.ndarray.prototype.length":"\nbase.ndarray.prototype.length\n    Length of the array (i.e., number of elements).\n\n    Returns\n    -------\n    len: integer\n        Array length.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var len = arr.length\n    4","base.ndarray.prototype.ndims":"\nbase.ndarray.prototype.ndims\n    Number of dimensions.\n\n    Returns\n    -------\n    ndims: integer\n        Number of dimensions.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var n = arr.ndims\n    2","base.ndarray.prototype.offset":"\nbase.ndarray.prototype.offset\n    Index offset which specifies the buffer index at which to start iterating\n    over array elements.\n\n    Returns\n    -------\n    offset: integer\n        Index offset.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.offset\n    0","base.ndarray.prototype.order: string":"\nbase.ndarray.prototype.order: string\n    Array order.\n\n    The array order is either row-major (C-style) or column-major (Fortran-\n    style).\n\n    Returns\n    -------\n    order: string\n        Array order.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var ord = arr.order\n    'row-major'","base.ndarray.prototype.shape":"\nbase.ndarray.prototype.shape\n    Array shape.\n\n    Returns\n    -------\n    shape: Array\n        Array shape.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sh = arr.shape\n    [ 2, 2 ]","base.ndarray.prototype.strides":"\nbase.ndarray.prototype.strides\n    Index strides which specify how to access data along corresponding array\n    dimensions.\n\n    Returns\n    -------\n    strides: Array\n        Index strides.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var st = arr.strides\n    [ 2, 1 ]","base.ndarray.prototype.get":"\nbase.ndarray.prototype.get( ...idx )\n    Returns an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.get( 1, 1 )\n    4.0","base.ndarray.prototype.iget":"\nbase.ndarray.prototype.iget( idx )\n    Returns an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the input argument is ignored and, for clarity,\n    should not be provided.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.iget( 3 )\n    4.0","base.ndarray.prototype.set":"\nbase.ndarray.prototype.set( ...idx, v )\n    Sets an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: ndarray\n        ndarray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > arr.set( 1, 1, -4.0 );\n    > arr.get( 1, 1 )\n    -4.0","base.ndarray.prototype.iset":"\nbase.ndarray.prototype.iset( idx, v )\n    Sets an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the first, and only, argument should be the\n    value to set.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: ndarray\n        ndarray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > arr.iset( 3, -4.0 );\n    > arr.iget( 3 )\n    -4.0","base.ndarray.prototype.toString":"\nbase.ndarray.prototype.toString()\n    Serializes an ndarray as a string.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    str: string\n        Serialized ndarray string.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toString()\n    '...'","base.ndarray.prototype.toJSON":"\nbase.ndarray.prototype.toJSON()\n    Serializes an ndarray as a JSON object.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toJSON()\n    {...}\n\n    See Also\n    --------\n    array, ndarray","base.ndarrayUnary":"\nbase.ndarrayUnary( arrays, fcn )\n    Applies a unary callback to elements in an input ndarray and assigns results\n    to elements in an output ndarray.\n\n    Each provided \"ndarray\" should be an object with the following properties:\n\n    - dtype: data type.\n    - data: data buffer.\n    - shape: dimensions.\n    - strides: stride lengths.\n    - offset: index offset.\n    - order: specifies whether an ndarray is row-major (C-style) or column-major\n    (Fortran-style).\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ndarray>\n        Array-like object containing one input ndarray and one output ndarray.\n\n    fcn: Function\n        Unary callback.\n\n    Examples\n    --------\n    // Define ndarray data and meta data...\n    > var xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var dtype = 'float64';\n    > var shape = [ 2, 2 ];\n    > var sx = [ 2, 1 ];\n    > var sy = [ 2, 1 ];\n    > var ox = 0;\n    > var oy = 0;\n    > var order = 'row-major';\n\n    // Using ndarrays...\n    > var x = ndarray( dtype, xbuf, shape, sx, ox, order );\n    > var y = ndarray( dtype, ybuf, shape, sy, oy, order );\n    > base.ndarrayUnary( [ x, y ], base.abs );\n    > y.data\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Using minimal ndarray-like objects...\n    > x = {\n    ...     'dtype': dtype,\n    ...     'data': xbuf,\n    ...     'shape': shape,\n    ...     'strides': sx,\n    ...     'offset': ox,\n    ...     'order': order\n    ... };\n    > y = {\n    ...     'dtype': dtype,\n    ...     'data': ybuf,\n    ...     'shape': shape,\n    ...     'strides': sy,\n    ...     'offset': oy,\n    ...     'order': order\n    ... };\n    > base.ndarrayUnary( [ x, y ], base.abs );\n    > y.data\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    See Also\n    --------\n    ndarrayDispatch\n","base.ndzeros":"\nbase.ndzeros( dtype, shape, order )\n    Returns a zero-filled ndarray having a specified shape and data type.\n\n    Parameters\n    ----------\n    dtype: string\n        Underlying data type. Must be a numeric data type or \"generic\".\n\n    shape: ArrayLikeObject<integer>\n        Array shape.\n\n    order: string\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran-style).\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var arr = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n    <ndarray>\n    > var sh = arr.shape\n    [ 2, 2 ]\n    > var dt = arr.dtype\n    'float64'\n\n    See Also\n    --------\n    base.ndarray, base.ndzerosLike\n","base.ndzerosLike":"\nbase.ndzerosLike( x )\n    Returns a zero-filled ndarray having the same shape and data type as a\n    provided input ndarray.\n\n    Along with data type, shape, and order, the function infers the \"class\" of\n    the returned ndarray from the provided ndarray. For example, if provided a\n    \"base\" ndarray, the function returns a base ndarray. If provided a non-base\n    ndarray, the function returns a non-base ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n    <ndarray>\n    > var sh = x.shape\n    [ 2, 2 ]\n    > var dt = x.dtype\n    'float64'\n    > var y = base.ndzerosLike( x )\n    <ndarray>\n    > sh = y.shape\n    [ 2, 2 ]\n    > dt = y.dtype\n    'float64'\n\n    See Also\n    --------\n    base.ndarray, base.ndzeros\n","base.negafibonacci":"\nbase.negafibonacci( n )\n    Computes the nth negaFibonacci number.\n\n    The negaFibonacci numbers follow the recurrence relation\n\n      F_{n-2} = F_{n} - F_{n-1}\n\n    with seed values F_0 = 0 and F_{-1} = 1.\n\n    If `|n|` is greater than `78`, the function returns `NaN` as larger\n    negaFibonacci numbers cannot be accurately represented due to limitations of\n    double-precision floating-point format.\n\n    If not provided a non-positive integer value, the function returns `NaN`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Input value.\n\n    Returns\n    -------\n    y: integer\n        NegaFibonacci number.\n\n    Examples\n    --------\n    > var y = base.negafibonacci( 0 )\n    0\n    > y = base.negafibonacci( -1 )\n    1\n    > y = base.negafibonacci( -2 )\n    -1\n    > y = base.negafibonacci( -3 )\n    2\n    > y = base.negafibonacci( -4 )\n    -3\n    > y = base.negafibonacci( -79 )\n    NaN\n    > y = base.negafibonacci( -80 )\n    NaN\n    > y = base.negafibonacci( NaN )\n    NaN\n\n    See Also\n    --------\n    base.fibonacci, base.negalucas\n","base.negalucas":"\nbase.negalucas( n )\n    Computes the nth negaLucas number.\n\n    The negaLucas numbers follow the recurrence relation\n\n      L_{n-2} = L_{n} - L_{n-1}\n\n    with seed values L_0 = 2 and L_{-1} = -1.\n\n    If `|n|` is greater than `76`, the function returns `NaN` as larger\n    negaLucas numbers cannot be accurately represented due to limitations of\n    double-precision floating-point format.\n\n    If not provided a non-positive integer value, the function returns `NaN`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Input value.\n\n    Returns\n    -------\n    y: integer\n        NegaLucas number.\n\n    Examples\n    --------\n    > var y = base.negalucas( 0 )\n    2\n    > y = base.negalucas( -1 )\n    -1\n    > y = base.negalucas( -2 )\n    3\n    > y = base.negalucas( -3 )\n    -4\n    > y = base.negalucas( -4 )\n    7\n    > y = base.negalucas( -77 )\n    NaN\n    > y = base.negalucas( -78 )\n    NaN\n    > y = base.negalucas( NaN )\n    NaN\n\n    See Also\n    --------\n    base.fibonacci, base.lucas, base.negafibonacci\n","base.nonfibonacci":"\nbase.nonfibonacci( n )\n    Computes the nth non-Fibonacci number.\n\n    If not provided a nonnegative integer value, the function returns `NaN`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Non-Fibonacci number.\n\n    Examples\n    --------\n    > var v = base.nonfibonacci( 1 )\n    4\n    > v = base.nonfibonacci( 2 )\n    6\n    > v = base.nonfibonacci( 3 )\n    7\n    > v = base.nonfibonacci( NaN )\n    NaN\n\n    See Also\n    --------\n    base.fibonacci\n","base.normalize":"\nbase.normalize( x )\n    Returns a normal number and exponent satisfying `x = y * 2^exp` as an array.\n\n    The first element of the returned array corresponds to `y` and the second to\n    `exp`.\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    Returns\n    -------\n    out: Array<number>\n        An array containing `y` and `exp`.\n\n    Examples\n    --------\n    > var out = base.normalize( 3.14e-319 )\n    [ 1.4141234400356668e-303, -52 ]\n    > var y = out[ 0 ];\n    > var exponent = out[ 1 ];\n    > var bool = ( y*base.pow(2.0, exponent) === 3.14e-319 )\n    true\n\n    // Special cases:\n    > out = base.normalize( 0.0 )\n    [ 0.0, 0 ];\n    > out = base.normalize( PINF )\n    [ Infinity, 0 ]\n    > out = base.normalize( NINF )\n    [ -Infinity, 0 ]\n    > out = base.normalize( NaN )\n    [ NaN, 0 ]\n\n\nbase.normalize.assign( x, out, stride, offset )\n    Returns a normal number and exponent satisfying `x = y * 2^exp` and assigns\n    results to a provided output array.\n\n    The first element of the returned array corresponds to `y` and the second to\n    `exp`.\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Output array.\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 )\n    > var v = base.normalize.assign( 3.14e-319, out, 1, 0 )\n    <Float64Array>[ 1.4141234400356668e-303, -52 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.normalizef\n","base.normalize.assign":"\nbase.normalize.assign( x, out, stride, offset )\n    Returns a normal number and exponent satisfying `x = y * 2^exp` and assigns\n    results to a provided output array.\n\n    The first element of the returned array corresponds to `y` and the second to\n    `exp`.\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Output array.\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 )\n    > var v = base.normalize.assign( 3.14e-319, out, 1, 0 )\n    <Float64Array>[ 1.4141234400356668e-303, -52 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.normalizef","base.normalizef":"\nbase.normalizef( x )\n    Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` as\n    an array.\n\n    The first element of the returned array corresponds to `y` and the second to\n    `exp`.\n\n    While the function accepts higher precision floating-point numbers, beware\n    that providing such numbers can be a source of subtle bugs as the relation\n    `x = y * 2^exp` may not hold.\n\n    Parameters\n    ----------\n    x: float\n        Single-precision floating-point number.\n\n    Returns\n    -------\n    out: Array<number>\n        An array containing `y` and `exp`.\n\n    Examples\n    --------\n    > var out = base.normalizef( base.float64ToFloat32( 1.401e-45 ) )\n    [ 1.1754943508222875e-38, -23 ]\n    > var y = out[ 0 ];\n    > var exp = out[ 1 ];\n    > var bool = ( y*base.pow(2,exp) === base.float64ToFloat32(1.401e-45) )\n    true\n\n    // Special cases:\n    > out = base.normalizef( FLOAT32_PINF )\n    [ Infinity, 0 ]\n    > out = base.normalizef( FLOAT32_NINF )\n    [ -Infinity, 0 ]\n    > out = base.normalizef( NaN )\n    [ NaN, 0 ]\n\n\nbase.normalizef.assign( x, out, stride, offset )\n    Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` and\n    assigns results to a provided output array.\n\n    The first element of the returned array corresponds to `y` and the second to\n    `exp`.\n\n    While the function accepts higher precision floating-point numbers, beware\n    that providing such numbers can be a source of subtle bugs as the relation\n    `x = y * 2^exp` may not hold.\n\n    Parameters\n    ----------\n    x: float\n        Single-precision floating-point number.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        An array containing `y` and `exp`.\n\n    Examples\n    --------\n    > out = new Float32Array( 2 );\n    > var v = base.normalizef.assign( base.float64ToFloat32( 1.401e-45 ), out, 1, 0 )\n    <Float32Array>[ 1.1754943508222875e-38, -23.0 ]\n    > bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.normalize","base.normalizef.assign":"\nbase.normalizef.assign( x, out, stride, offset )\n    Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` and\n    assigns results to a provided output array.\n\n    The first element of the returned array corresponds to `y` and the second to\n    `exp`.\n\n    While the function accepts higher precision floating-point numbers, beware\n    that providing such numbers can be a source of subtle bugs as the relation\n    `x = y * 2^exp` may not hold.\n\n    Parameters\n    ----------\n    x: float\n        Single-precision floating-point number.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        An array containing `y` and `exp`.\n\n    Examples\n    --------\n    > out = new Float32Array( 2 );\n    > var v = base.normalizef.assign( base.float64ToFloat32( 1.401e-45 ), out, 1, 0 )\n    <Float32Array>[ 1.1754943508222875e-38, -23.0 ]\n    > bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.normalize","base.normalizeSlice":"\nbase.normalizeSlice( slice, len, strict )\n    Returns a normalized Slice object.\n\n    In strict mode, the function returns an error object if an input slice\n    exceeds index bounds.\n\n    A returned error object is a plain object having the following properties:\n\n    - code: error code.\n\n    A returned error object may have one of the following error codes:\n\n    - ERR_SLICE_OUT_OF_BOUNDS: a slice exceeds index bounds.\n\n    Parameters\n    ----------\n    slice: Slice\n        Input slice object.\n\n    len: integer\n        Maximum number of elements allowed in the slice.\n\n    strict: boolean\n        Boolean indicating whether to enforce strict bounds checking.\n\n    Returns\n    -------\n    s: Slice|Object\n        Slice instance (or an error object).\n\n    Examples\n    --------\n    > var s1 = new Slice( 1, 10, 1 );\n    > var s2 = base.normalizeSlice( s1, 5, false );\n    > s2.start\n    1\n    > s2.stop\n    5\n    > s2.step\n    1\n    > s1 = new Slice( -2, null, -1 );\n    > s2 = base.normalizeSlice( s1, 10, false );\n    > s2.start\n    8\n    > s2.stop\n    null\n    > s2.step\n    -1\n\n    See Also\n    --------\n    base.normalizeMultiSlice\n","base.normhermitepoly":"\nbase.normhermitepoly( n, x )\n    Evaluates a normalized Hermite polynomial using double-precision floating-\n    point arithmetic.\n\n    Parameters\n    ----------\n    n: integer\n        Nonnegative polynomial degree.\n\n    x: number\n        Value at which to evaluate the polynomial.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.normhermitepoly( 1, 0.5 )\n    0.5\n    > y = base.normhermitepoly( -1, 0.5 )\n    NaN\n    > y = base.normhermitepoly( 0, 0.5 )\n    1.0\n    > y = base.normhermitepoly( 2, 0.5 )\n    -0.75\n\n\nbase.normhermitepoly.factory( n )\n    Returns a function for evaluating a normalized Hermite polynomial using\n    double-precision floating-point arithmetic.\n\n    Parameters\n    ----------\n    n: integer\n        Nonnegative polynomial degree.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a normalized Hermite polynomial.\n\n    Examples\n    --------\n    > var f = base.normhermitepoly.factory( 2 );\n    > var v = f( 0.5 )\n    -0.75\n\n    See Also\n    --------\n    base.evalpoly, base.hermitepoly\n","base.normhermitepoly.factory":"\nbase.normhermitepoly.factory( n )\n    Returns a function for evaluating a normalized Hermite polynomial using\n    double-precision floating-point arithmetic.\n\n    Parameters\n    ----------\n    n: integer\n        Nonnegative polynomial degree.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a normalized Hermite polynomial.\n\n    Examples\n    --------\n    > var f = base.normhermitepoly.factory( 2 );\n    > var v = f( 0.5 )\n    -0.75\n\n    See Also\n    --------\n    base.evalpoly, base.hermitepoly","base.pascalcase":"\nbase.pascalcase( str )\n    Converts a string to Pascal case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Pascal-cased string.\n\n    Examples\n    --------\n    > var out = base.pascalcase( 'Hello World!' )\n    'HelloWorld'\n    > out = base.pascalcase( 'beep boop' )\n    'BeepBoop'\n\n    See Also\n    --------\n    base.camelcase, base.lowercase, base.uppercase","base.pdiff":"\nbase.pdiff( x, y )\n    Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n    returns `0`.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Positive difference.\n\n    Examples\n    --------\n    > var v = base.pdiff( 5.9, 3.14 )\n    2.76\n    > v = base.pdiff( 3.14, 4.2 )\n    0.0\n    > v = base.pdiff( 3.14, NaN )\n    NaN\n    > v = base.pdiff( -0.0, +0.0 )\n    +0.0\n\n","base.pdifff":"\nbase.pdifff( x, y )\n    Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n    returns `0`.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Positive difference.\n\n    Examples\n    --------\n    > var v = base.pdifff( 5.9, 3.15 )\n    2.75\n    > v = base.pdifff( 3.14, 4.2 )\n    0.0\n    > v = base.pdifff( 3.14, NaN )\n    NaN\n    > v = base.pdifff( -0.0, +0.0 )\n    +0.0\n\n    See Also\n    --------\n    base.pdiff\n","base.percentEncode":"\nbase.percentEncode( str )\n    Percent-encodes a UTF-16 encoded string according to RFC 3986.\n\n    Parameters\n    ----------\n    str: string\n        UTF-16 encoded string.\n\n    Returns\n    -------\n    out: string\n        Percent-encoded string.\n\n    Examples\n    --------\n    > var out = base.percentEncode( '☃' )\n    '%E2%98%83'\n\n","base.polygamma":"\nbase.polygamma( n, x )\n    Evaluates the polygamma function of order `n`; i.e., the (n+1)th derivative\n    of the natural logarithm of the gamma function.\n\n    If `n` is not a nonnegative integer, the function returns `NaN`.\n\n    If `x` is zero or a negative integer, the function returns `NaN`.\n\n    If provided `NaN` as either parameter, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Derivative order.\n\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var v = base.polygamma( 3, 1.2 )\n    ~3.245\n    > v = base.polygamma( 5, 1.2 )\n    ~41.39\n    > v = base.polygamma( 3, -4.9 )\n    ~60014.239\n    > v = base.polygamma( -1, 5.3 )\n    NaN\n    > v = base.polygamma( 2, -1.0 )\n    Infinity\n\n    See Also\n    --------\n    base.trigamma, base.digamma, base.gamma\n","base.pow":"\nbase.pow( b, x )\n    Evaluates the exponential function `bˣ`.\n\n    Parameters\n    ----------\n    b: number\n        Base.\n\n    x: number\n        Exponent.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.pow( 2.0, 3.0 )\n    8.0\n    > y = base.pow( 4.0, 0.5 )\n    2.0\n    > y = base.pow( 100.0, 0.0 )\n    1.0\n    > y = base.pow( PI, 5.0 )\n    ~306.0197\n    > y = base.pow( PI, -0.2 )\n    ~0.7954\n    > y = base.pow( NaN, 3.0 )\n    NaN\n    > y = base.pow( 5.0, NaN )\n    NaN\n    > y = base.pow( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.exp, base.powm1\n","base.powm1":"\nbase.powm1( b, x )\n    Evaluates `bˣ - 1`.\n\n    When `b` is close to `1` and/or `x` is small, this function is more accurate\n    than naively computing `bˣ` and subtracting `1`.\n\n    Parameters\n    ----------\n    b: number\n        Base.\n\n    x: number\n        Exponent.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.powm1( 2.0, 3.0 )\n    7.0\n    > y = base.powm1( 4.0, 0.5 )\n    1.0\n    > y = base.powm1( 0.0, 100.0 )\n    -1.0\n    > y = base.powm1( 100.0, 0.0 )\n    0.0\n    > y = base.powm1( 0.0, 0.0 )\n    0.0\n    > y = base.powm1( PI, 5.0 )\n    ~305.0197\n    > y = base.powm1( NaN, 3.0 )\n    NaN\n    > y = base.powm1( 5.0, NaN )\n    NaN\n\n    See Also\n    --------\n    base.pow\n","base.rad2deg":"\nbase.rad2deg( x )\n    Converts an angle from radians to degrees.\n\n    Parameters\n    ----------\n    x: number\n        Angle in radians.\n\n    Returns\n    -------\n    d: number\n        Angle in degrees.\n\n    Examples\n    --------\n    > var d = base.rad2deg( PI/2.0 )\n    90.0\n    > d = base.rad2deg( -PI/4.0 )\n    -45.0\n    > d = base.rad2deg( NaN )\n    NaN\n\n    // Due to finite precision, canonical values may not be returned:\n    > d = base.rad2deg( PI/6.0 )\n    29.999999999999996\n\n    See Also\n    --------\n    base.deg2rad\n","base.rad2degf":"\nbase.rad2degf( x )\n    Converts an angle from radians to degrees (single-precision).\n\n    Parameters\n    ----------\n    x: number\n        Angle in radians.\n\n    Returns\n    -------\n    d: number\n        Angle in degrees.\n\n    Examples\n    --------\n    > var d = base.rad2degf( 3.141592653589793 / 2.0 )\n    90.0\n    > d = base.rad2degf( -3.141592653589793 / 4.0 )\n    -45.0\n    > d = base.rad2degf( NaN )\n    NaN\n\n    // Due to finite precision, canonical values may not be returned:\n    > d = base.rad2degf( 3.141592653589793 / 6.0 )\n    30.000001907348633\n\n    See Also\n    --------\n    base.rad2deg\n","base.ramp":"\nbase.ramp( x )\n    Evaluates the ramp function.\n\n    If `x >= 0`, the function returns `x`; otherwise, the function returns zero.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.ramp( 3.14 )\n    3.14\n    > y = base.ramp( -3.14 )\n    0.0\n\n    See Also\n    --------\n    base.heaviside\n","base.rampf":"\nbase.rampf( x )\n    Evaluates the ramp function (single-precision).\n\n    If `x >= 0`, the function returns `x`; otherwise, the function returns zero.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.rampf( 3.14 )\n    3.14\n    > y = base.rampf( -3.14 )\n    0.0\n\n    See Also\n    --------\n    base.ramp\n","base.random.arcsine":"\nbase.random.arcsine( a, b )\n    Returns a pseudorandom number drawn from an arcsine distribution.\n\n    If `a >= b`, the function returns `NaN`.\n\n    If `a` or `b` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.arcsine( 2.0, 5.0 )\n    <number>\n\n\nbase.random.arcsine.factory( [a, b, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an arcsine distribution.\n\n    If provided `a` and `b`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `a` and `b`, the returned PRNG requires that both `a` and\n    `b` be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.arcsine.factory();\n    > var r = rand( 0.0, 1.0 )\n    <number>\n    > r = rand( -2.0, 2.0 )\n    <number>\n\n    // Provide `a` and `b`:\n    > rand = base.random.arcsine.factory( 0.0, 1.0 );\n    > r = rand()\n    <number>\n    > r = rand()\n    <number>\n\n\nbase.random.arcsine.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.arcsine.NAME\n    'arcsine'\n\n\nbase.random.arcsine.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.arcsine.PRNG;\n\n\nbase.random.arcsine.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.arcsine.seed;\n\n\nbase.random.arcsine.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.arcsine.seedLength;\n\n\nbase.random.arcsine.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.arcsine.state\n    <Uint32Array>\n\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n\n    // Set the state:\n    > base.random.arcsine.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n\n\nbase.random.arcsine.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.arcsine.stateLength;\n\n\nbase.random.arcsine.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.arcsine.byteLength;\n\n\nbase.random.arcsine.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.arcsine.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.arcsine, random.iterators.arcsine, random.streams.arcsine, base.random.beta\n","base.random.arcsine.factory":"\nbase.random.arcsine.factory( [a, b, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an arcsine distribution.\n\n    If provided `a` and `b`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `a` and `b`, the returned PRNG requires that both `a` and\n    `b` be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.arcsine.factory();\n    > var r = rand( 0.0, 1.0 )\n    <number>\n    > r = rand( -2.0, 2.0 )\n    <number>\n\n    // Provide `a` and `b`:\n    > rand = base.random.arcsine.factory( 0.0, 1.0 );\n    > r = rand()\n    <number>\n    > r = rand()\n    <number>","base.random.arcsine.NAME":"\nbase.random.arcsine.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.arcsine.NAME\n    'arcsine'","base.random.arcsine.PRNG":"\nbase.random.arcsine.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.arcsine.PRNG;","base.random.arcsine.seed":"\nbase.random.arcsine.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.arcsine.seed;","base.random.arcsine.seedLength":"\nbase.random.arcsine.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.arcsine.seedLength;","base.random.arcsine.state":"\nbase.random.arcsine.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.arcsine.state\n    <Uint32Array>\n\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n\n    // Set the state:\n    > base.random.arcsine.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>","base.random.arcsine.stateLength":"\nbase.random.arcsine.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.arcsine.stateLength;","base.random.arcsine.byteLength":"\nbase.random.arcsine.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.arcsine.byteLength;","base.random.arcsine.toJSON":"\nbase.random.arcsine.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.arcsine.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.arcsine, random.iterators.arcsine, random.streams.arcsine, base.random.beta","base.random.bernoulli":"\nbase.random.bernoulli( p )\n    Returns a pseudorandom number drawn from a Bernoulli distribution.\n\n    If `p < 0` or `p > 1` or `p` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.bernoulli( 0.8 );\n\n\nbase.random.bernoulli.factory( [p, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Bernoulli distribution.\n\n    If provided `p`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `p`, the returned PRNG requires that `p` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.bernoulli.factory();\n    > var r = rand( 0.3 );\n    > r = rand( 0.59 );\n\n    // Provide `p`:\n    > rand = base.random.bernoulli.factory( 0.3 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.bernoulli.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.bernoulli.NAME\n    'bernoulli'\n\n\nbase.random.bernoulli.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.bernoulli.PRNG;\n\n\nbase.random.bernoulli.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.bernoulli.seed;\n\n\nbase.random.bernoulli.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.bernoulli.seedLength;\n\n\nbase.random.bernoulli.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.bernoulli( 0.3 )\n    <number>\n    > r = base.random.bernoulli( 0.3 )\n    <number>\n    > r = base.random.bernoulli( 0.3 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.bernoulli.state\n    <Uint32Array>\n\n    > r = base.random.bernoulli( 0.3 )\n    <number>\n    > r = base.random.bernoulli( 0.3 )\n    <number>\n\n    // Set the state:\n    > base.random.bernoulli.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.bernoulli( 0.3 )\n    <number>\n    > r = base.random.bernoulli( 0.3 )\n    <number>\n\n\nbase.random.bernoulli.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.bernoulli.stateLength;\n\n\nbase.random.bernoulli.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.bernoulli.byteLength;\n\n\nbase.random.bernoulli.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.bernoulli.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.bernoulli, random.iterators.bernoulli, random.streams.bernoulli, base.random.binomial\n","base.random.bernoulli.factory":"\nbase.random.bernoulli.factory( [p, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Bernoulli distribution.\n\n    If provided `p`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `p`, the returned PRNG requires that `p` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.bernoulli.factory();\n    > var r = rand( 0.3 );\n    > r = rand( 0.59 );\n\n    // Provide `p`:\n    > rand = base.random.bernoulli.factory( 0.3 );\n    > r = rand();\n    > r = rand();","base.random.bernoulli.NAME":"\nbase.random.bernoulli.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.bernoulli.NAME\n    'bernoulli'","base.random.bernoulli.PRNG":"\nbase.random.bernoulli.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.bernoulli.PRNG;","base.random.bernoulli.seed":"\nbase.random.bernoulli.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.bernoulli.seed;","base.random.bernoulli.seedLength":"\nbase.random.bernoulli.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.bernoulli.seedLength;","base.random.bernoulli.state":"\nbase.random.bernoulli.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.bernoulli( 0.3 )\n    <number>\n    > r = base.random.bernoulli( 0.3 )\n    <number>\n    > r = base.random.bernoulli( 0.3 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.bernoulli.state\n    <Uint32Array>\n\n    > r = base.random.bernoulli( 0.3 )\n    <number>\n    > r = base.random.bernoulli( 0.3 )\n    <number>\n\n    // Set the state:\n    > base.random.bernoulli.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.bernoulli( 0.3 )\n    <number>\n    > r = base.random.bernoulli( 0.3 )\n    <number>","base.random.bernoulli.stateLength":"\nbase.random.bernoulli.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.bernoulli.stateLength;","base.random.bernoulli.byteLength":"\nbase.random.bernoulli.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.bernoulli.byteLength;","base.random.bernoulli.toJSON":"\nbase.random.bernoulli.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.bernoulli.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.bernoulli, random.iterators.bernoulli, random.streams.bernoulli, base.random.binomial","base.random.beta":"\nbase.random.beta( α, β )\n    Returns a pseudorandom number drawn from a beta distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.beta( 2.0, 5.0 );\n\n\nbase.random.beta.factory( [α, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a beta distribution.\n\n    If provided `α` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `α` and `β`, the returned PRNG requires that both `α` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        First shape parameter.\n\n    β: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.beta.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `α` and `β`:\n    > rand = base.random.beta.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.beta.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.beta.NAME\n    'beta'\n\n\nbase.random.beta.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.beta.PRNG;\n\n\nbase.random.beta.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.beta.seed;\n\n\nbase.random.beta.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.beta.seedLength;\n\n\nbase.random.beta.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.beta( 2.0, 5.0 )\n    <number>\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.beta.state\n    <Uint32Array>\n\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.beta.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>\n\n\nbase.random.beta.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.beta.stateLength;\n\n\nbase.random.beta.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.beta.byteLength;\n\n\nbase.random.beta.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.beta.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.beta, random.iterators.beta, random.streams.beta\n","base.random.beta.factory":"\nbase.random.beta.factory( [α, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a beta distribution.\n\n    If provided `α` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `α` and `β`, the returned PRNG requires that both `α` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        First shape parameter.\n\n    β: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.beta.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `α` and `β`:\n    > rand = base.random.beta.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.beta.NAME":"\nbase.random.beta.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.beta.NAME\n    'beta'","base.random.beta.PRNG":"\nbase.random.beta.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.beta.PRNG;","base.random.beta.seed":"\nbase.random.beta.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.beta.seed;","base.random.beta.seedLength":"\nbase.random.beta.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.beta.seedLength;","base.random.beta.state":"\nbase.random.beta.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.beta( 2.0, 5.0 )\n    <number>\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.beta.state\n    <Uint32Array>\n\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.beta.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>","base.random.beta.stateLength":"\nbase.random.beta.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.beta.stateLength;","base.random.beta.byteLength":"\nbase.random.beta.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.beta.byteLength;","base.random.beta.toJSON":"\nbase.random.beta.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.beta.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.beta, random.iterators.beta, random.streams.beta","base.random.betaprime":"\nbase.random.betaprime( α, β )\n    Returns a pseudorandom number drawn from a beta prime distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.betaprime( 2.0, 5.0 );\n\n\nbase.random.betaprime.factory( [α, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a beta prime distribution.\n\n    If provided `α` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `α` and `β`, the returned PRNG requires that both `α` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        First shape parameter.\n\n    β: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.betaprime.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `α` and `β`:\n    > rand = base.random.betaprime.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.betaprime.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.betaprime.NAME\n    'betaprime'\n\n\nbase.random.betaprime.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.betaprime.PRNG;\n\n\nbase.random.betaprime.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.betaprime.seed;\n\n\nbase.random.betaprime.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.betaprime.seedLength;\n\n\nbase.random.betaprime.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.betaprime.state\n    <Uint32Array>\n\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.betaprime.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n\n\nbase.random.betaprime.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.betaprime.stateLength;\n\n\nbase.random.betaprime.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.betaprime.byteLength;\n\n\nbase.random.betaprime.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.betaprime.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.betaprime, random.iterators.betaprime, random.streams.betaprime\n","base.random.betaprime.factory":"\nbase.random.betaprime.factory( [α, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a beta prime distribution.\n\n    If provided `α` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `α` and `β`, the returned PRNG requires that both `α` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        First shape parameter.\n\n    β: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.betaprime.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `α` and `β`:\n    > rand = base.random.betaprime.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.betaprime.NAME":"\nbase.random.betaprime.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.betaprime.NAME\n    'betaprime'","base.random.betaprime.PRNG":"\nbase.random.betaprime.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.betaprime.PRNG;","base.random.betaprime.seed":"\nbase.random.betaprime.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.betaprime.seed;","base.random.betaprime.seedLength":"\nbase.random.betaprime.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.betaprime.seedLength;","base.random.betaprime.state":"\nbase.random.betaprime.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.betaprime.state\n    <Uint32Array>\n\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.betaprime.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>","base.random.betaprime.stateLength":"\nbase.random.betaprime.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.betaprime.stateLength;","base.random.betaprime.byteLength":"\nbase.random.betaprime.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.betaprime.byteLength;","base.random.betaprime.toJSON":"\nbase.random.betaprime.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.betaprime.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.betaprime, random.iterators.betaprime, random.streams.betaprime","base.random.binomial":"\nbase.random.binomial( n, p )\n    Returns a pseudorandom number drawn from a binomial distribution.\n\n    If `n` is not a positive integer or `p` is not a probability, the function\n    returns `NaN`.\n\n    If `n` or `p` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.binomial( 20, 0.8 );\n\n\nbase.random.binomial.factory( [n, p, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a binomial distribution.\n\n    If provided `n` and `p`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `n` and `p`, the returned PRNG requires that both `n` and\n    `p` be provided at each invocation.\n\n    Parameters\n    ----------\n    n: integer (optional)\n        Number of trials.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.binomial.factory();\n    > var r = rand( 20, 0.3 );\n    > r = rand( 10, 0.77 );\n\n    // Provide `n` and `p`:\n    > rand = base.random.binomial.factory( 10, 0.8 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.binomial.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.binomial.NAME\n    'binomial'\n\n\nbase.random.binomial.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.binomial.PRNG;\n\n\nbase.random.binomial.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.binomial.seed;\n\n\nbase.random.binomial.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.binomial.seedLength;\n\n\nbase.random.binomial.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.binomial( 20, 0.8 )\n    <number>\n    > r = base.random.binomial( 20, 0.8 )\n    <number>\n    > r = base.random.binomial( 20, 0.8 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.binomial.state\n    <Uint32Array>\n\n    > r = base.random.binomial( 20, 0.8 )\n    <number>\n    > r = base.random.binomial( 20, 0.8 )\n    <number>\n\n    // Set the state:\n    > base.random.binomial.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.binomial( 20, 0.8 )\n    <number>\n    > r = base.random.binomial( 20, 0.8 )\n    <number>\n\n\nbase.random.binomial.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.binomial.stateLength;\n\n\nbase.random.binomial.byteLength\n    Size of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.binomial.byteLength;\n\n\nbase.random.binomial.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.binomial.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.binomial, random.iterators.binomial, random.streams.binomial\n","base.random.binomial.factory":"\nbase.random.binomial.factory( [n, p, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a binomial distribution.\n\n    If provided `n` and `p`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `n` and `p`, the returned PRNG requires that both `n` and\n    `p` be provided at each invocation.\n\n    Parameters\n    ----------\n    n: integer (optional)\n        Number of trials.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.binomial.factory();\n    > var r = rand( 20, 0.3 );\n    > r = rand( 10, 0.77 );\n\n    // Provide `n` and `p`:\n    > rand = base.random.binomial.factory( 10, 0.8 );\n    > r = rand();\n    > r = rand();","base.random.binomial.NAME":"\nbase.random.binomial.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.binomial.NAME\n    'binomial'","base.random.binomial.PRNG":"\nbase.random.binomial.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.binomial.PRNG;","base.random.binomial.seed":"\nbase.random.binomial.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.binomial.seed;","base.random.binomial.seedLength":"\nbase.random.binomial.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.binomial.seedLength;","base.random.binomial.state":"\nbase.random.binomial.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.binomial( 20, 0.8 )\n    <number>\n    > r = base.random.binomial( 20, 0.8 )\n    <number>\n    > r = base.random.binomial( 20, 0.8 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.binomial.state\n    <Uint32Array>\n\n    > r = base.random.binomial( 20, 0.8 )\n    <number>\n    > r = base.random.binomial( 20, 0.8 )\n    <number>\n\n    // Set the state:\n    > base.random.binomial.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.binomial( 20, 0.8 )\n    <number>\n    > r = base.random.binomial( 20, 0.8 )\n    <number>","base.random.binomial.stateLength":"\nbase.random.binomial.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.binomial.stateLength;","base.random.binomial.byteLength":"\nbase.random.binomial.byteLength\n    Size of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.binomial.byteLength;","base.random.binomial.toJSON":"\nbase.random.binomial.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.binomial.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.binomial, random.iterators.binomial, random.streams.binomial","base.random.boxMuller":"\nbase.random.boxMuller()\n    Returns a pseudorandom number drawn from a standard normal distribution.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.boxMuller();\n\n\nbase.random.boxMuller.factory( [options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a standard normal distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.boxMuller.factory();\n    > r = rand();\n    > r = rand();\n\n\nbase.random.boxMuller.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.boxMuller.NAME\n    'box-muller'\n\n\nbase.random.boxMuller.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.boxMuller.PRNG;\n\n\nbase.random.boxMuller.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.boxMuller.seed;\n\n\nbase.random.boxMuller.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.boxMuller.seedLength;\n\n\nbase.random.boxMuller.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.boxMuller()\n    <number>\n    > r = base.random.boxMuller()\n    <number>\n    > r = base.random.boxMuller()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.boxMuller.state\n    <Uint32Array>\n\n    > r = base.random.boxMuller()\n    <number>\n    > r = base.random.boxMuller()\n    <number>\n\n    // Set the state:\n    > base.random.boxMuller.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.boxMuller()\n    <number>\n    > r = base.random.boxMuller()\n    <number>\n\n\nbase.random.boxMuller.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.boxMuller.stateLength;\n\n\nbase.random.boxMuller.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.boxMuller.byteLength;\n\n\nbase.random.boxMuller.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.boxMuller.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.iterators.boxMuller, random.streams.boxMuller\n","base.random.boxMuller.factory":"\nbase.random.boxMuller.factory( [options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a standard normal distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.boxMuller.factory();\n    > r = rand();\n    > r = rand();","base.random.boxMuller.NAME":"\nbase.random.boxMuller.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.boxMuller.NAME\n    'box-muller'","base.random.boxMuller.PRNG":"\nbase.random.boxMuller.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.boxMuller.PRNG;","base.random.boxMuller.seed":"\nbase.random.boxMuller.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.boxMuller.seed;","base.random.boxMuller.seedLength":"\nbase.random.boxMuller.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.boxMuller.seedLength;","base.random.boxMuller.state":"\nbase.random.boxMuller.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.boxMuller()\n    <number>\n    > r = base.random.boxMuller()\n    <number>\n    > r = base.random.boxMuller()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.boxMuller.state\n    <Uint32Array>\n\n    > r = base.random.boxMuller()\n    <number>\n    > r = base.random.boxMuller()\n    <number>\n\n    // Set the state:\n    > base.random.boxMuller.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.boxMuller()\n    <number>\n    > r = base.random.boxMuller()\n    <number>","base.random.boxMuller.stateLength":"\nbase.random.boxMuller.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.boxMuller.stateLength;","base.random.boxMuller.byteLength":"\nbase.random.boxMuller.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.boxMuller.byteLength;","base.random.boxMuller.toJSON":"\nbase.random.boxMuller.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.boxMuller.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.iterators.boxMuller, random.streams.boxMuller","base.random.cauchy":"\nbase.random.cauchy( x0, Ɣ )\n    Returns a pseudorandom number drawn from a Cauchy distribution.\n\n    If `x0` or `Ɣ` is `NaN` or `Ɣ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.cauchy( 2.0, 5.0 );\n\n\nbase.random.cauchy.factory( [x0, Ɣ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Cauchy distribution.\n\n    If provided `x0` and `Ɣ`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `x0` and `Ɣ`, the returned PRNG requires that both `x0` and\n    `Ɣ` be provided at each invocation.\n\n    Parameters\n    ----------\n    x0: number (optional)\n        Location parameter.\n\n    Ɣ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.cauchy.factory();\n    > var r = rand( 0.0, 1.5 );\n    > r = rand( -2.0, 2.0 );\n\n    // Provide `x0` and `Ɣ`:\n    > rand = base.random.cauchy.factory( 0.0, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.cauchy.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.cauchy.NAME\n    'cauchy'\n\n\nbase.random.cauchy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.cauchy.PRNG;\n\n\nbase.random.cauchy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.cauchy.seed;\n\n\nbase.random.cauchy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.cauchy.seedLength;\n\n\nbase.random.cauchy.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.cauchy.state\n    <Uint32Array>\n\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.cauchy.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n\n\nbase.random.cauchy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.cauchy.stateLength;\n\n\nbase.random.cauchy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.cauchy.byteLength;\n\n\nbase.random.cauchy.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.cauchy.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.cauchy, random.iterators.cauchy, random.streams.cauchy\n","base.random.cauchy.factory":"\nbase.random.cauchy.factory( [x0, Ɣ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Cauchy distribution.\n\n    If provided `x0` and `Ɣ`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `x0` and `Ɣ`, the returned PRNG requires that both `x0` and\n    `Ɣ` be provided at each invocation.\n\n    Parameters\n    ----------\n    x0: number (optional)\n        Location parameter.\n\n    Ɣ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.cauchy.factory();\n    > var r = rand( 0.0, 1.5 );\n    > r = rand( -2.0, 2.0 );\n\n    // Provide `x0` and `Ɣ`:\n    > rand = base.random.cauchy.factory( 0.0, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.cauchy.NAME":"\nbase.random.cauchy.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.cauchy.NAME\n    'cauchy'","base.random.cauchy.PRNG":"\nbase.random.cauchy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.cauchy.PRNG;","base.random.cauchy.seed":"\nbase.random.cauchy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.cauchy.seed;","base.random.cauchy.seedLength":"\nbase.random.cauchy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.cauchy.seedLength;","base.random.cauchy.state":"\nbase.random.cauchy.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.cauchy.state\n    <Uint32Array>\n\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.cauchy.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>","base.random.cauchy.stateLength":"\nbase.random.cauchy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.cauchy.stateLength;","base.random.cauchy.byteLength":"\nbase.random.cauchy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.cauchy.byteLength;","base.random.cauchy.toJSON":"\nbase.random.cauchy.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.cauchy.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.cauchy, random.iterators.cauchy, random.streams.cauchy","base.random.chi":"\nbase.random.chi( k )\n    Returns a pseudorandom number drawn from a chi distribution.\n\n    If `k <= 0` or `k` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.chi( 2 );\n\n\nbase.random.chi.factory( [k, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a chi distribution.\n\n    If provided `k`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `k`, the returned PRNG requires that `k` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.chi.factory();\n    > var r = rand( 5 );\n    > r = rand( 3.14 );\n\n    // Provide `k`:\n    > rand = base.random.chi.factory( 3 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.chi.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.chi.NAME\n    'chi'\n\n\nbase.random.chi.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.chi.PRNG;\n\n\nbase.random.chi.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.chi.seed;\n\n\nbase.random.chi.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.chi.seedLength;\n\n\nbase.random.chi.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.chi( 2 )\n    <number>\n    > r = base.random.chi( 2 )\n    <number>\n    > r = base.random.chi( 2 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.chi.state\n    <Uint32Array>\n\n    > r = base.random.chi( 2 )\n    <number>\n    > r = base.random.chi( 2 )\n    <number>\n\n    // Set the state:\n    > base.random.chi.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.chi( 2 )\n    <number>\n    > r = base.random.chi( 2 )\n    <number>\n\n\nbase.random.chi.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.chi.stateLength;\n\n\nbase.random.chi.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.chi.byteLength;\n\n\nbase.random.chi.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.chi.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.chi, random.iterators.chi, random.streams.chi\n","base.random.chi.factory":"\nbase.random.chi.factory( [k, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a chi distribution.\n\n    If provided `k`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `k`, the returned PRNG requires that `k` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.chi.factory();\n    > var r = rand( 5 );\n    > r = rand( 3.14 );\n\n    // Provide `k`:\n    > rand = base.random.chi.factory( 3 );\n    > r = rand();\n    > r = rand();","base.random.chi.NAME":"\nbase.random.chi.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.chi.NAME\n    'chi'","base.random.chi.PRNG":"\nbase.random.chi.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.chi.PRNG;","base.random.chi.seed":"\nbase.random.chi.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.chi.seed;","base.random.chi.seedLength":"\nbase.random.chi.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.chi.seedLength;","base.random.chi.state":"\nbase.random.chi.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.chi( 2 )\n    <number>\n    > r = base.random.chi( 2 )\n    <number>\n    > r = base.random.chi( 2 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.chi.state\n    <Uint32Array>\n\n    > r = base.random.chi( 2 )\n    <number>\n    > r = base.random.chi( 2 )\n    <number>\n\n    // Set the state:\n    > base.random.chi.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.chi( 2 )\n    <number>\n    > r = base.random.chi( 2 )\n    <number>","base.random.chi.stateLength":"\nbase.random.chi.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.chi.stateLength;","base.random.chi.byteLength":"\nbase.random.chi.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.chi.byteLength;","base.random.chi.toJSON":"\nbase.random.chi.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.chi.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.chi, random.iterators.chi, random.streams.chi","base.random.chisquare":"\nbase.random.chisquare( k )\n    Returns a pseudorandom number drawn from a chi-square distribution.\n\n    If `k <= 0` or `k` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.chisquare( 2 );\n\n\nbase.random.chisquare.factory( [k, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a chi-square distribution.\n\n    If provided `k`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `k`, the returned PRNG requires that `k` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.chisquare.factory();\n    > var r = rand( 5 );\n    > r = rand( 3.14 );\n\n    // Provide `k`:\n    > rand = base.random.chisquare.factory( 3 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.chisquare.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.chisquare.NAME\n    'chisquare'\n\n\nbase.random.chisquare.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.chisquare.PRNG;\n\n\nbase.random.chisquare.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.chisquare.seed;\n\n\nbase.random.chisquare.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.chisquare.seedLength;\n\n\nbase.random.chisquare.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.chisquare( 2 )\n    <number>\n    > r = base.random.chisquare( 2 )\n    <number>\n    > r = base.random.chisquare( 2 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.chisquare.state\n    <Uint32Array>\n\n    > r = base.random.chisquare( 2 )\n    <number>\n    > r = base.random.chisquare( 2 )\n    <number>\n\n    // Set the state:\n    > base.random.chisquare.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.chisquare( 2 )\n    <number>\n    > r = base.random.chisquare( 2 )\n    <number>\n\n\nbase.random.chisquare.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.chisquare.stateLength;\n\n\nbase.random.chisquare.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.chisquare.byteLength;\n\n\nbase.random.chisquare.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.chisquare.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.chisquare, random.iterators.chisquare, random.streams.chisquare\n","base.random.chisquare.factory":"\nbase.random.chisquare.factory( [k, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a chi-square distribution.\n\n    If provided `k`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `k`, the returned PRNG requires that `k` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.chisquare.factory();\n    > var r = rand( 5 );\n    > r = rand( 3.14 );\n\n    // Provide `k`:\n    > rand = base.random.chisquare.factory( 3 );\n    > r = rand();\n    > r = rand();","base.random.chisquare.NAME":"\nbase.random.chisquare.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.chisquare.NAME\n    'chisquare'","base.random.chisquare.PRNG":"\nbase.random.chisquare.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.chisquare.PRNG;","base.random.chisquare.seed":"\nbase.random.chisquare.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.chisquare.seed;","base.random.chisquare.seedLength":"\nbase.random.chisquare.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.chisquare.seedLength;","base.random.chisquare.state":"\nbase.random.chisquare.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.chisquare( 2 )\n    <number>\n    > r = base.random.chisquare( 2 )\n    <number>\n    > r = base.random.chisquare( 2 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.chisquare.state\n    <Uint32Array>\n\n    > r = base.random.chisquare( 2 )\n    <number>\n    > r = base.random.chisquare( 2 )\n    <number>\n\n    // Set the state:\n    > base.random.chisquare.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.chisquare( 2 )\n    <number>\n    > r = base.random.chisquare( 2 )\n    <number>","base.random.chisquare.stateLength":"\nbase.random.chisquare.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.chisquare.stateLength;","base.random.chisquare.byteLength":"\nbase.random.chisquare.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.chisquare.byteLength;","base.random.chisquare.toJSON":"\nbase.random.chisquare.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.chisquare.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.chisquare, random.iterators.chisquare, random.streams.chisquare","base.random.cosine":"\nbase.random.cosine( μ, s )\n    Returns a pseudorandom number drawn from a raised cosine distribution.\n\n    If `μ` or `s` is `NaN` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.cosine( 2.0, 5.0 );\n\n\nbase.random.cosine.factory( [μ, s, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a raised cosine distribution.\n\n    If provided `μ` and `s`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n    `s` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.cosine.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `s`:\n    > rand = base.random.cosine.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.cosine.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.cosine.NAME\n    'cosine'\n\n\nbase.random.cosine.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.cosine.PRNG;\n\n\nbase.random.cosine.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.cosine.seed;\n\n\nbase.random.cosine.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.cosine.seedLength;\n\n\nbase.random.cosine.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.cosine( 2.0, 5.0 )\n    <number>\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.cosine.state\n    <Uint32Array>\n\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.cosine.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>\n\n\nbase.random.cosine.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.cosine.stateLength;\n\n\nbase.random.cosine.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.cosine.byteLength;\n\n\nbase.random.cosine.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.cosine.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.cosine, random.iterators.cosine, random.streams.cosine\n","base.random.cosine.factory":"\nbase.random.cosine.factory( [μ, s, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a raised cosine distribution.\n\n    If provided `μ` and `s`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n    `s` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.cosine.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `s`:\n    > rand = base.random.cosine.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.cosine.NAME":"\nbase.random.cosine.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.cosine.NAME\n    'cosine'","base.random.cosine.PRNG":"\nbase.random.cosine.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.cosine.PRNG;","base.random.cosine.seed":"\nbase.random.cosine.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.cosine.seed;","base.random.cosine.seedLength":"\nbase.random.cosine.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.cosine.seedLength;","base.random.cosine.state":"\nbase.random.cosine.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.cosine( 2.0, 5.0 )\n    <number>\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.cosine.state\n    <Uint32Array>\n\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.cosine.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>","base.random.cosine.stateLength":"\nbase.random.cosine.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.cosine.stateLength;","base.random.cosine.byteLength":"\nbase.random.cosine.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.cosine.byteLength;","base.random.cosine.toJSON":"\nbase.random.cosine.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.cosine.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.cosine, random.iterators.cosine, random.streams.cosine","base.random.discreteUniform":"\nbase.random.discreteUniform( a, b )\n    Returns a pseudorandom number drawn from a discrete uniform distribution.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.discreteUniform( 2, 50 );\n\n\nbase.random.discreteUniform.factory( [a, b, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a discrete uniform distribution.\n\n    If provided `a` and `b`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `a` and `b`, the returned PRNG requires that both `a` and\n    `b` be provided at each invocation.\n\n    Parameters\n    ----------\n    a: integer (optional)\n        Minimum support.\n\n    b: integer (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom integers. If provided, the `state` and `seed`\n        options are ignored. In order to seed the returned pseudorandom number\n        generator, one must seed the provided `prng` (assuming the provided\n        `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n        properties specifying the minimum and maximum possible pseudorandom\n        integers.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.discreteUniform.factory();\n    > var r = rand( 0, 10 );\n    > r = rand( -20, 20 );\n\n    // Provide `a` and `b`:\n    > rand = base.random.discreteUniform.factory( 0, 10 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.discreteUniform.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.discreteUniform.NAME\n    'discrete-uniform'\n\n\nbase.random.discreteUniform.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.discreteUniform.PRNG;\n\n\nbase.random.discreteUniform.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.discreteUniform.seed;\n\n\nbase.random.discreteUniform.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.discreteUniform.seedLength;\n\n\nbase.random.discreteUniform.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.discreteUniform( 2, 50 )\n    <number>\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.discreteUniform.state\n    <Uint32Array>\n\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>\n\n    // Set the state:\n    > base.random.discreteUniform.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>\n\n\nbase.random.discreteUniform.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.discreteUniform.stateLength;\n\n\nbase.random.discreteUniform.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.discreteUniform.byteLength;\n\n\nbase.random.discreteUniform.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.discreteUniform.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.discreteUniform, random.iterators.discreteUniform, random.streams.discreteUniform\n","base.random.discreteUniform.factory":"\nbase.random.discreteUniform.factory( [a, b, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a discrete uniform distribution.\n\n    If provided `a` and `b`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `a` and `b`, the returned PRNG requires that both `a` and\n    `b` be provided at each invocation.\n\n    Parameters\n    ----------\n    a: integer (optional)\n        Minimum support.\n\n    b: integer (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom integers. If provided, the `state` and `seed`\n        options are ignored. In order to seed the returned pseudorandom number\n        generator, one must seed the provided `prng` (assuming the provided\n        `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n        properties specifying the minimum and maximum possible pseudorandom\n        integers.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.discreteUniform.factory();\n    > var r = rand( 0, 10 );\n    > r = rand( -20, 20 );\n\n    // Provide `a` and `b`:\n    > rand = base.random.discreteUniform.factory( 0, 10 );\n    > r = rand();\n    > r = rand();","base.random.discreteUniform.NAME":"\nbase.random.discreteUniform.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.discreteUniform.NAME\n    'discrete-uniform'","base.random.discreteUniform.PRNG":"\nbase.random.discreteUniform.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.discreteUniform.PRNG;","base.random.discreteUniform.seed":"\nbase.random.discreteUniform.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.discreteUniform.seed;","base.random.discreteUniform.seedLength":"\nbase.random.discreteUniform.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.discreteUniform.seedLength;","base.random.discreteUniform.state":"\nbase.random.discreteUniform.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.discreteUniform( 2, 50 )\n    <number>\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.discreteUniform.state\n    <Uint32Array>\n\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>\n\n    // Set the state:\n    > base.random.discreteUniform.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>","base.random.discreteUniform.stateLength":"\nbase.random.discreteUniform.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.discreteUniform.stateLength;","base.random.discreteUniform.byteLength":"\nbase.random.discreteUniform.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.discreteUniform.byteLength;","base.random.discreteUniform.toJSON":"\nbase.random.discreteUniform.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.discreteUniform.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.discreteUniform, random.iterators.discreteUniform, random.streams.discreteUniform","base.random.erlang":"\nbase.random.erlang( k, λ )\n    Returns a pseudorandom number drawn from an Erlang distribution.\n\n    If `k` is not a positive integer or `λ <= 0`, the function returns `NaN`.\n\n    If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: integer\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.erlang( 2, 5.0 );\n\n\nbase.random.erlang.factory( [k, λ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an Erlang distribution.\n\n    If provided `k` and `λ`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `k` and `λ`, the returned PRNG requires that both `k` and\n    `λ` be provided at each invocation.\n\n    Parameters\n    ----------\n    k: integer (optional)\n        Shape parameter.\n\n    λ: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.erlang.factory();\n    > var r = rand( 2, 1.0 );\n    > r = rand( 4, 3.14 );\n\n    // Provide `k` and `λ`:\n    > rand = base.random.erlang.factory( 2, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.erlang.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.erlang.NAME\n    'erlang'\n\n\nbase.random.erlang.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.erlang.PRNG;\n\n\nbase.random.erlang.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.erlang.seed;\n\n\nbase.random.erlang.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.erlang.seedLength;\n\n\nbase.random.erlang.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.erlang( 2, 5.0 )\n    <number>\n    > r = base.random.erlang( 2, 5.0 )\n    <number>\n    > r = base.random.erlang( 2, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.erlang.state\n    <Uint32Array>\n\n    > r = base.random.erlang( 2, 5.0 )\n    <number>\n    > r = base.random.erlang( 2, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.erlang.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.erlang( 2, 5.0 )\n    <number>\n    > r = base.random.erlang( 2, 5.0 )\n    <number>\n\n\nbase.random.erlang.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.erlang.stateLength;\n\n\nbase.random.erlang.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.erlang.byteLength;\n\n\nbase.random.erlang.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.erlang.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.erlang, random.iterators.erlang, random.streams.erlang\n","base.random.erlang.factory":"\nbase.random.erlang.factory( [k, λ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an Erlang distribution.\n\n    If provided `k` and `λ`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `k` and `λ`, the returned PRNG requires that both `k` and\n    `λ` be provided at each invocation.\n\n    Parameters\n    ----------\n    k: integer (optional)\n        Shape parameter.\n\n    λ: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.erlang.factory();\n    > var r = rand( 2, 1.0 );\n    > r = rand( 4, 3.14 );\n\n    // Provide `k` and `λ`:\n    > rand = base.random.erlang.factory( 2, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.erlang.NAME":"\nbase.random.erlang.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.erlang.NAME\n    'erlang'","base.random.erlang.PRNG":"\nbase.random.erlang.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.erlang.PRNG;","base.random.erlang.seed":"\nbase.random.erlang.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.erlang.seed;","base.random.erlang.seedLength":"\nbase.random.erlang.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.erlang.seedLength;","base.random.erlang.state":"\nbase.random.erlang.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.erlang( 2, 5.0 )\n    <number>\n    > r = base.random.erlang( 2, 5.0 )\n    <number>\n    > r = base.random.erlang( 2, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.erlang.state\n    <Uint32Array>\n\n    > r = base.random.erlang( 2, 5.0 )\n    <number>\n    > r = base.random.erlang( 2, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.erlang.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.erlang( 2, 5.0 )\n    <number>\n    > r = base.random.erlang( 2, 5.0 )\n    <number>","base.random.erlang.stateLength":"\nbase.random.erlang.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.erlang.stateLength;","base.random.erlang.byteLength":"\nbase.random.erlang.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.erlang.byteLength;","base.random.erlang.toJSON":"\nbase.random.erlang.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.erlang.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.erlang, random.iterators.erlang, random.streams.erlang","base.random.exponential":"\nbase.random.exponential( λ )\n    Returns a pseudorandom number drawn from an exponential distribution.\n\n    If `λ <= 0` or `λ` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.exponential( 7.9 );\n\n\nbase.random.exponential.factory( [λ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an exponential distribution.\n\n    If provided `λ`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    λ: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.exponential.factory();\n    > var r = rand( 5.0 );\n    > r = rand( 3.14 );\n\n    // Provide `λ`:\n    > rand = base.random.exponential.factory( 10.0 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.exponential.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.exponential.NAME\n    'exponential'\n\n\nbase.random.exponential.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.exponential.PRNG;\n\n\nbase.random.exponential.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.exponential.seed;\n\n\nbase.random.exponential.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.exponential.seedLength;\n\n\nbase.random.exponential.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.exponential( 7.9 )\n    <number>\n    > r = base.random.exponential( 7.9 )\n    <number>\n    > r = base.random.exponential( 7.9 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.exponential.state\n    <Uint32Array>\n\n    > r = base.random.exponential( 7.9 )\n    <number>\n    > r = base.random.exponential( 7.9 )\n    <number>\n\n    // Set the state:\n    > base.random.exponential.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.exponential( 7.9 )\n    <number>\n    > r = base.random.exponential( 7.9 )\n    <number>\n\n\nbase.random.exponential.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.exponential.stateLength;\n\n\nbase.random.exponential.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.exponential.byteLength;\n\n\nbase.random.exponential.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.exponential.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.exponential, random.iterators.exponential, random.streams.exponential\n","base.random.exponential.factory":"\nbase.random.exponential.factory( [λ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an exponential distribution.\n\n    If provided `λ`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    λ: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.exponential.factory();\n    > var r = rand( 5.0 );\n    > r = rand( 3.14 );\n\n    // Provide `λ`:\n    > rand = base.random.exponential.factory( 10.0 );\n    > r = rand();\n    > r = rand();","base.random.exponential.NAME":"\nbase.random.exponential.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.exponential.NAME\n    'exponential'","base.random.exponential.PRNG":"\nbase.random.exponential.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.exponential.PRNG;","base.random.exponential.seed":"\nbase.random.exponential.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.exponential.seed;","base.random.exponential.seedLength":"\nbase.random.exponential.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.exponential.seedLength;","base.random.exponential.state":"\nbase.random.exponential.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.exponential( 7.9 )\n    <number>\n    > r = base.random.exponential( 7.9 )\n    <number>\n    > r = base.random.exponential( 7.9 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.exponential.state\n    <Uint32Array>\n\n    > r = base.random.exponential( 7.9 )\n    <number>\n    > r = base.random.exponential( 7.9 )\n    <number>\n\n    // Set the state:\n    > base.random.exponential.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.exponential( 7.9 )\n    <number>\n    > r = base.random.exponential( 7.9 )\n    <number>","base.random.exponential.stateLength":"\nbase.random.exponential.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.exponential.stateLength;","base.random.exponential.byteLength":"\nbase.random.exponential.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.exponential.byteLength;","base.random.exponential.toJSON":"\nbase.random.exponential.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.exponential.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.exponential, random.iterators.exponential, random.streams.exponential","base.random.f":"\nbase.random.f( d1, d2 )\n    Returns a pseudorandom number drawn from an F distribution.\n\n    If `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n    If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    d1: number\n        Degrees of freedom.\n\n    d2: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.f( 2.0, 5.0 );\n\n\nbase.random.f.factory( [d1, d2, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an F distribution.\n\n    If provided `d1` and `d2`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `d1` and `d2`, the returned PRNG requires that both `d1` and\n    `d2` be provided at each invocation.\n\n    Parameters\n    ----------\n    d1: number (optional)\n        Degrees of freedom.\n\n    d2: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.f.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 3.0, 3.14 );\n\n    // Provide `d1` and `d2`:\n    > rand = base.random.f.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.f.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.f.NAME\n    'f'\n\n\nbase.random.f.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.f.PRNG;\n\n\nbase.random.f.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.f.seed;\n\n\nbase.random.f.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.f.seedLength;\n\n\nbase.random.f.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.f( 1.5, 1.5 )\n    <number>\n    > r = base.random.f( 1.5, 1.5 )\n    <number>\n    > r = base.random.f( 1.5, 1.5 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.f.state\n    <Uint32Array>\n\n    > r = base.random.f( 1.5, 1.5 )\n    <number>\n    > r = base.random.f( 1.5, 1.5 )\n    <number>\n\n    // Set the state:\n    > base.random.f.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.f( 1.5, 1.5 )\n    <number>\n    > r = base.random.f( 1.5, 1.5 )\n    <number>\n\n\nbase.random.f.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.f.stateLength;\n\n\nbase.random.f.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.f.byteLength;\n\n\nbase.random.f.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.f.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.f, random.iterators.f, random.streams.f\n","base.random.f.factory":"\nbase.random.f.factory( [d1, d2, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an F distribution.\n\n    If provided `d1` and `d2`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `d1` and `d2`, the returned PRNG requires that both `d1` and\n    `d2` be provided at each invocation.\n\n    Parameters\n    ----------\n    d1: number (optional)\n        Degrees of freedom.\n\n    d2: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.f.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 3.0, 3.14 );\n\n    // Provide `d1` and `d2`:\n    > rand = base.random.f.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.f.NAME":"\nbase.random.f.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.f.NAME\n    'f'","base.random.f.PRNG":"\nbase.random.f.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.f.PRNG;","base.random.f.seed":"\nbase.random.f.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.f.seed;","base.random.f.seedLength":"\nbase.random.f.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.f.seedLength;","base.random.f.state":"\nbase.random.f.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.f( 1.5, 1.5 )\n    <number>\n    > r = base.random.f( 1.5, 1.5 )\n    <number>\n    > r = base.random.f( 1.5, 1.5 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.f.state\n    <Uint32Array>\n\n    > r = base.random.f( 1.5, 1.5 )\n    <number>\n    > r = base.random.f( 1.5, 1.5 )\n    <number>\n\n    // Set the state:\n    > base.random.f.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.f( 1.5, 1.5 )\n    <number>\n    > r = base.random.f( 1.5, 1.5 )\n    <number>","base.random.f.stateLength":"\nbase.random.f.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.f.stateLength;","base.random.f.byteLength":"\nbase.random.f.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.f.byteLength;","base.random.f.toJSON":"\nbase.random.f.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.f.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.f, random.iterators.f, random.streams.f","base.random.frechet":"\nbase.random.frechet( α, s, m )\n    Returns a pseudorandom number drawn from a Fréchet distribution.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    If either `α`, `s`, or `m` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.frechet( 2.0, 5.0, 3.33 );\n\n\nbase.random.frechet.factory( [α, s, m, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a triangular distribution.\n\n    If provided `α`, `s`, and `m`, the returned PRNG returns random variates\n    drawn from the specified distribution.\n\n    If not provided `α`, `s`, and `m`, the returned PRNG requires that `α`, `s`,\n    and `m` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    m: number (optional)\n        Location parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.frechet.factory();\n    > var r = rand( 1.0, 1.0, 0.5 );\n    > r = rand( 2.0, 2.0, 1.0 );\n\n    // Provide `α`, `s`, and `m`:\n    > rand = base.random.frechet.factory( 1.0, 1.0, 0.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.frechet.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.frechet.NAME\n    'frechet'\n\n\nbase.random.frechet.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.frechet.PRNG;\n\n\nbase.random.frechet.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.frechet.seed;\n\n\nbase.random.frechet.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.frechet.seedLength;\n\n\nbase.random.frechet.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.frechet.state\n    <Uint32Array>\n\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n\n    // Set the state:\n    > base.random.frechet.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n\n\nbase.random.frechet.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.frechet.stateLength;\n\n\nbase.random.frechet.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.frechet.byteLength;\n\n\nbase.random.frechet.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.frechet.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.frechet, random.iterators.frechet, random.streams.frechet\n","base.random.frechet.factory":"\nbase.random.frechet.factory( [α, s, m, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a triangular distribution.\n\n    If provided `α`, `s`, and `m`, the returned PRNG returns random variates\n    drawn from the specified distribution.\n\n    If not provided `α`, `s`, and `m`, the returned PRNG requires that `α`, `s`,\n    and `m` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    m: number (optional)\n        Location parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.frechet.factory();\n    > var r = rand( 1.0, 1.0, 0.5 );\n    > r = rand( 2.0, 2.0, 1.0 );\n\n    // Provide `α`, `s`, and `m`:\n    > rand = base.random.frechet.factory( 1.0, 1.0, 0.5 );\n    > r = rand();\n    > r = rand();","base.random.frechet.NAME":"\nbase.random.frechet.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.frechet.NAME\n    'frechet'","base.random.frechet.PRNG":"\nbase.random.frechet.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.frechet.PRNG;","base.random.frechet.seed":"\nbase.random.frechet.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.frechet.seed;","base.random.frechet.seedLength":"\nbase.random.frechet.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.frechet.seedLength;","base.random.frechet.state":"\nbase.random.frechet.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.frechet.state\n    <Uint32Array>\n\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n\n    // Set the state:\n    > base.random.frechet.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>","base.random.frechet.stateLength":"\nbase.random.frechet.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.frechet.stateLength;","base.random.frechet.byteLength":"\nbase.random.frechet.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.frechet.byteLength;","base.random.frechet.toJSON":"\nbase.random.frechet.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.frechet.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.frechet, random.iterators.frechet, random.streams.frechet","base.random.gamma":"\nbase.random.gamma( α, β )\n    Returns a pseudorandom number drawn from a gamma distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.gamma( 2.0, 5.0 );\n\n\nbase.random.gamma.factory( [α, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a gamma distribution.\n\n    If provided `α` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `α` and `β`, the returned PRNG requires that both `α` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.gamma.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 3.14, 2.25 );\n\n    // Provide `α` and `β`:\n    > rand = base.random.gamma.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.gamma.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.gamma.NAME\n    'gamma'\n\n\nbase.random.gamma.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.gamma.PRNG;\n\n\nbase.random.gamma.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.gamma.seed;\n\n\nbase.random.gamma.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.gamma.seedLength;\n\n\nbase.random.gamma.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.gamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.gamma.state\n    <Uint32Array>\n\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.gamma.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>\n\n\nbase.random.gamma.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.gamma.stateLength;\n\n\nbase.random.gamma.byteLength\n    Size of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.gamma.byteLength;\n\n\nbase.random.gamma.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.gamma.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.gamma, random.iterators.gamma, random.streams.gamma\n","base.random.gamma.factory":"\nbase.random.gamma.factory( [α, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a gamma distribution.\n\n    If provided `α` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `α` and `β`, the returned PRNG requires that both `α` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.gamma.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 3.14, 2.25 );\n\n    // Provide `α` and `β`:\n    > rand = base.random.gamma.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.gamma.NAME":"\nbase.random.gamma.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.gamma.NAME\n    'gamma'","base.random.gamma.PRNG":"\nbase.random.gamma.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.gamma.PRNG;","base.random.gamma.seed":"\nbase.random.gamma.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.gamma.seed;","base.random.gamma.seedLength":"\nbase.random.gamma.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.gamma.seedLength;","base.random.gamma.state":"\nbase.random.gamma.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.gamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.gamma.state\n    <Uint32Array>\n\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.gamma.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>","base.random.gamma.stateLength":"\nbase.random.gamma.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.gamma.stateLength;","base.random.gamma.byteLength":"\nbase.random.gamma.byteLength\n    Size of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.gamma.byteLength;","base.random.gamma.toJSON":"\nbase.random.gamma.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.gamma.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.gamma, random.iterators.gamma, random.streams.gamma","base.random.geometric":"\nbase.random.geometric( p )\n    Returns a pseudorandom number drawn from a geometric distribution.\n\n    If `p < 0` or `p > 1` or `p` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.geometric( 0.8 );\n\n\nbase.random.geometric.factory( [p, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a geometric distribution.\n\n    If provided `p`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `p`, the returned PRNG requires that `p` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.geometric.factory();\n    > var r = rand( 0.3 );\n    > r = rand( 0.59 );\n\n    // Provide `p`:\n    > rand = base.random.geometric.factory( 0.3 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.geometric.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.geometric.NAME\n    'geometric'\n\n\nbase.random.geometric.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.geometric.PRNG;\n\n\nbase.random.geometric.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.geometric.seed;\n\n\nbase.random.geometric.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.geometric.seedLength;\n\n\nbase.random.geometric.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.geometric( 0.3 )\n    <number>\n    > r = base.random.geometric( 0.3 )\n    <number>\n    > r = base.random.geometric( 0.3 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.geometric.state\n    <Uint32Array>\n\n    > r = base.random.geometric( 0.3 )\n    <number>\n    > r = base.random.geometric( 0.3 )\n    <number>\n\n    // Set the state:\n    > base.random.geometric.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.geometric( 0.3 )\n    <number>\n    > r = base.random.geometric( 0.3 )\n    <number>\n\n\nbase.random.geometric.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.geometric.stateLength;\n\n\nbase.random.geometric.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.geometric.byteLength;\n\n\nbase.random.geometric.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.geometric.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.geometric, random.iterators.geometric, random.streams.geometric\n","base.random.geometric.factory":"\nbase.random.geometric.factory( [p, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a geometric distribution.\n\n    If provided `p`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `p`, the returned PRNG requires that `p` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.geometric.factory();\n    > var r = rand( 0.3 );\n    > r = rand( 0.59 );\n\n    // Provide `p`:\n    > rand = base.random.geometric.factory( 0.3 );\n    > r = rand();\n    > r = rand();","base.random.geometric.NAME":"\nbase.random.geometric.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.geometric.NAME\n    'geometric'","base.random.geometric.PRNG":"\nbase.random.geometric.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.geometric.PRNG;","base.random.geometric.seed":"\nbase.random.geometric.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.geometric.seed;","base.random.geometric.seedLength":"\nbase.random.geometric.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.geometric.seedLength;","base.random.geometric.state":"\nbase.random.geometric.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.geometric( 0.3 )\n    <number>\n    > r = base.random.geometric( 0.3 )\n    <number>\n    > r = base.random.geometric( 0.3 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.geometric.state\n    <Uint32Array>\n\n    > r = base.random.geometric( 0.3 )\n    <number>\n    > r = base.random.geometric( 0.3 )\n    <number>\n\n    // Set the state:\n    > base.random.geometric.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.geometric( 0.3 )\n    <number>\n    > r = base.random.geometric( 0.3 )\n    <number>","base.random.geometric.stateLength":"\nbase.random.geometric.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.geometric.stateLength;","base.random.geometric.byteLength":"\nbase.random.geometric.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.geometric.byteLength;","base.random.geometric.toJSON":"\nbase.random.geometric.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.geometric.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.geometric, random.iterators.geometric, random.streams.geometric","base.random.gumbel":"\nbase.random.gumbel( μ, β )\n    Returns a pseudorandom number drawn from a Gumbel distribution.\n\n    If `μ` or `β` is `NaN` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.gumbel( 2.0, 5.0 );\n\n\nbase.random.gumbel.factory( [μ, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Gumbel distribution.\n\n    If provided `μ` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `β`, the returned PRNG requires that both `μ` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.gumbel.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `β`:\n    > rand = base.random.gumbel.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.gumbel.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.gumbel.NAME\n    'gumbel'\n\n\nbase.random.gumbel.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.gumbel.PRNG;\n\n\nbase.random.gumbel.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.gumbel.seed;\n\n\nbase.random.gumbel.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.gumbel.seedLength;\n\n\nbase.random.gumbel.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.gumbel.state\n    <Uint32Array>\n\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.gumbel.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n\n\nbase.random.gumbel.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.gumbel.stateLength;\n\n\nbase.random.gumbel.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.gumbel.byteLength;\n\n\nbase.random.gumbel.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.gumbel.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.gumbel, random.iterators.gumbel, random.streams.gumbel\n","base.random.gumbel.factory":"\nbase.random.gumbel.factory( [μ, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Gumbel distribution.\n\n    If provided `μ` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `β`, the returned PRNG requires that both `μ` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.gumbel.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `β`:\n    > rand = base.random.gumbel.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.gumbel.NAME":"\nbase.random.gumbel.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.gumbel.NAME\n    'gumbel'","base.random.gumbel.PRNG":"\nbase.random.gumbel.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.gumbel.PRNG;","base.random.gumbel.seed":"\nbase.random.gumbel.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.gumbel.seed;","base.random.gumbel.seedLength":"\nbase.random.gumbel.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.gumbel.seedLength;","base.random.gumbel.state":"\nbase.random.gumbel.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.gumbel.state\n    <Uint32Array>\n\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.gumbel.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>","base.random.gumbel.stateLength":"\nbase.random.gumbel.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.gumbel.stateLength;","base.random.gumbel.byteLength":"\nbase.random.gumbel.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.gumbel.byteLength;","base.random.gumbel.toJSON":"\nbase.random.gumbel.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.gumbel.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.gumbel, random.iterators.gumbel, random.streams.gumbel","base.random.hypergeometric":"\nbase.random.hypergeometric( N, K, n )\n    Returns a pseudorandom number drawn from a hypergeometric distribution.\n\n    `N`, `K`, and `n` must all be nonnegative integers; otherwise, the function\n    returns `NaN`.\n\n    If `n > N` or `K > N`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.hypergeometric( 20, 10, 7 );\n\n\nbase.random.hypergeometric.factory( [N, K, n, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a hypergeometric distribution.\n\n    If provided `N`, `K`, and `n`, the returned PRNG returns random variates\n    drawn from the specified distribution.\n\n    If not provided `N`, `K`, and `n`, the returned PRNG requires that `N`, `K`,\n    and `n` be provided at each invocation.\n\n    Parameters\n    ----------\n    N: integer (optional)\n        Population size.\n\n    K: integer (optional)\n        Subpopulation size.\n\n    n: integer (optional)\n        Number of draws.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.hypergeometric.factory();\n    > var r = rand( 20, 10, 15 );\n    > r = rand( 20, 10, 7 );\n\n    // Provide `N`, `K`, and `n`:\n    > rand = base.random.hypergeometric.factory( 20, 10, 15 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.hypergeometric.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.hypergeometric.NAME\n    'hypergeometric'\n\n\nbase.random.hypergeometric.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.hypergeometric.PRNG;\n\n\nbase.random.hypergeometric.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.hypergeometric.seed;\n\n\nbase.random.hypergeometric.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.hypergeometric.seedLength;\n\n\nbase.random.hypergeometric.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.hypergeometric.state\n    <Uint32Array>\n\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n\n    // Set the state:\n    > base.random.hypergeometric.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n\n\nbase.random.hypergeometric.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.hypergeometric.stateLength;\n\n\nbase.random.hypergeometric.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.hypergeometric.byteLength;\n\n\nbase.random.hypergeometric.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.hypergeometric.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.hypergeometric, random.iterators.hypergeometric, random.streams.hypergeometric\n","base.random.hypergeometric.factory":"\nbase.random.hypergeometric.factory( [N, K, n, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a hypergeometric distribution.\n\n    If provided `N`, `K`, and `n`, the returned PRNG returns random variates\n    drawn from the specified distribution.\n\n    If not provided `N`, `K`, and `n`, the returned PRNG requires that `N`, `K`,\n    and `n` be provided at each invocation.\n\n    Parameters\n    ----------\n    N: integer (optional)\n        Population size.\n\n    K: integer (optional)\n        Subpopulation size.\n\n    n: integer (optional)\n        Number of draws.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.hypergeometric.factory();\n    > var r = rand( 20, 10, 15 );\n    > r = rand( 20, 10, 7 );\n\n    // Provide `N`, `K`, and `n`:\n    > rand = base.random.hypergeometric.factory( 20, 10, 15 );\n    > r = rand();\n    > r = rand();","base.random.hypergeometric.NAME":"\nbase.random.hypergeometric.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.hypergeometric.NAME\n    'hypergeometric'","base.random.hypergeometric.PRNG":"\nbase.random.hypergeometric.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.hypergeometric.PRNG;","base.random.hypergeometric.seed":"\nbase.random.hypergeometric.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.hypergeometric.seed;","base.random.hypergeometric.seedLength":"\nbase.random.hypergeometric.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.hypergeometric.seedLength;","base.random.hypergeometric.state":"\nbase.random.hypergeometric.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.hypergeometric.state\n    <Uint32Array>\n\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n\n    // Set the state:\n    > base.random.hypergeometric.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>","base.random.hypergeometric.stateLength":"\nbase.random.hypergeometric.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.hypergeometric.stateLength;","base.random.hypergeometric.byteLength":"\nbase.random.hypergeometric.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.hypergeometric.byteLength;","base.random.hypergeometric.toJSON":"\nbase.random.hypergeometric.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.hypergeometric.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.hypergeometric, random.iterators.hypergeometric, random.streams.hypergeometric","base.random.improvedZiggurat":"\nbase.random.improvedZiggurat()\n    Returns a pseudorandom number drawn from a standard normal distribution.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.improvedZiggurat();\n\n\nbase.random.improvedZiggurat.factory( [options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a standard normal distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.improvedZiggurat.factory();\n    > r = rand();\n    > r = rand();\n\n\nbase.random.improvedZiggurat.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.improvedZiggurat.NAME\n    'improved-ziggurat'\n\n\nbase.random.improvedZiggurat.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.improvedZiggurat.PRNG;\n\n\nbase.random.improvedZiggurat.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.improvedZiggurat.seed;\n\n\nbase.random.improvedZiggurat.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.improvedZiggurat.seedLength;\n\n\nbase.random.improvedZiggurat.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.improvedZiggurat()\n    <number>\n    > r = base.random.improvedZiggurat()\n    <number>\n    > r = base.random.improvedZiggurat()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.improvedZiggurat.state\n    <Uint32Array>\n\n    > r = base.random.improvedZiggurat()\n    <number>\n    > r = base.random.improvedZiggurat()\n    <number>\n\n    // Set the state:\n    > base.random.improvedZiggurat.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.improvedZiggurat()\n    <number>\n    > r = base.random.improvedZiggurat()\n    <number>\n\n\nbase.random.improvedZiggurat.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.improvedZiggurat.stateLength;\n\n\nbase.random.improvedZiggurat.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.improvedZiggurat.byteLength;\n\n\nbase.random.improvedZiggurat.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.improvedZiggurat.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.iterators.improvedZiggurat, random.streams.improvedZiggurat\n","base.random.improvedZiggurat.factory":"\nbase.random.improvedZiggurat.factory( [options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a standard normal distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.improvedZiggurat.factory();\n    > r = rand();\n    > r = rand();","base.random.improvedZiggurat.NAME":"\nbase.random.improvedZiggurat.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.improvedZiggurat.NAME\n    'improved-ziggurat'","base.random.improvedZiggurat.PRNG":"\nbase.random.improvedZiggurat.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.improvedZiggurat.PRNG;","base.random.improvedZiggurat.seed":"\nbase.random.improvedZiggurat.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.improvedZiggurat.seed;","base.random.improvedZiggurat.seedLength":"\nbase.random.improvedZiggurat.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.improvedZiggurat.seedLength;","base.random.improvedZiggurat.state":"\nbase.random.improvedZiggurat.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.improvedZiggurat()\n    <number>\n    > r = base.random.improvedZiggurat()\n    <number>\n    > r = base.random.improvedZiggurat()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.improvedZiggurat.state\n    <Uint32Array>\n\n    > r = base.random.improvedZiggurat()\n    <number>\n    > r = base.random.improvedZiggurat()\n    <number>\n\n    // Set the state:\n    > base.random.improvedZiggurat.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.improvedZiggurat()\n    <number>\n    > r = base.random.improvedZiggurat()\n    <number>","base.random.improvedZiggurat.stateLength":"\nbase.random.improvedZiggurat.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.improvedZiggurat.stateLength;","base.random.improvedZiggurat.byteLength":"\nbase.random.improvedZiggurat.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.improvedZiggurat.byteLength;","base.random.improvedZiggurat.toJSON":"\nbase.random.improvedZiggurat.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.improvedZiggurat.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.iterators.improvedZiggurat, random.streams.improvedZiggurat","base.random.invgamma":"\nbase.random.invgamma( α, β )\n    Returns a pseudorandom number drawn from an inverse gamma distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.invgamma( 2.0, 5.0 );\n\n\nbase.random.invgamma.factory( [α, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an inverse gamma distribution.\n\n    If provided `α` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `α` and `β`, the returned PRNG requires that both `α` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.invgamma.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 3.14, 2.25 );\n\n    // Provide `α` and `β`:\n    > rand = base.random.invgamma.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.invgamma.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.invgamma.NAME\n    'invgamma'\n\n\nbase.random.invgamma.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.invgamma.PRNG;\n\n\nbase.random.invgamma.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.invgamma.seed;\n\n\nbase.random.invgamma.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.invgamma.seedLength;\n\n\nbase.random.invgamma.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.invgamma.state\n    <Uint32Array>\n\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.invgamma.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n\n\nbase.random.invgamma.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.invgamma.stateLength;\n\n\nbase.random.invgamma.byteLength\n    Size of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.invgamma.byteLength;\n\n\nbase.random.invgamma.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.invgamma.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.invgamma, random.iterators.invgamma, random.streams.invgamma\n","base.random.invgamma.factory":"\nbase.random.invgamma.factory( [α, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an inverse gamma distribution.\n\n    If provided `α` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `α` and `β`, the returned PRNG requires that both `α` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.invgamma.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 3.14, 2.25 );\n\n    // Provide `α` and `β`:\n    > rand = base.random.invgamma.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.invgamma.NAME":"\nbase.random.invgamma.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.invgamma.NAME\n    'invgamma'","base.random.invgamma.PRNG":"\nbase.random.invgamma.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.invgamma.PRNG;","base.random.invgamma.seed":"\nbase.random.invgamma.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.invgamma.seed;","base.random.invgamma.seedLength":"\nbase.random.invgamma.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.invgamma.seedLength;","base.random.invgamma.state":"\nbase.random.invgamma.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.invgamma.state\n    <Uint32Array>\n\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.invgamma.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>","base.random.invgamma.stateLength":"\nbase.random.invgamma.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.invgamma.stateLength;","base.random.invgamma.byteLength":"\nbase.random.invgamma.byteLength\n    Size of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.invgamma.byteLength;","base.random.invgamma.toJSON":"\nbase.random.invgamma.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.invgamma.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.invgamma, random.iterators.invgamma, random.streams.invgamma","base.random.kumaraswamy":"\nbase.random.kumaraswamy( a, b )\n    Returns a pseudorandom number drawn from Kumaraswamy's double bounded\n    distribution.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    If `a` or `b` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.kumaraswamy( 2.0, 5.0 );\n\n\nbase.random.kumaraswamy.factory( [a, b, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from Kumaraswamy's double bounded distribution.\n\n    If provided `a` and `b`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `a` and `b`, the returned PRNG requires that both `a` and\n    `b` be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        First shape parameter.\n\n    b: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.kumaraswamy.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `a` and `b`:\n    > rand = base.random.kumaraswamy.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.kumaraswamy.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.kumaraswamy.NAME\n    'kumaraswamy'\n\n\nbase.random.kumaraswamy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.kumaraswamy.PRNG;\n\n\nbase.random.kumaraswamy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.kumaraswamy.seed;\n\n\nbase.random.kumaraswamy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.kumaraswamy.seedLength;\n\n\nbase.random.kumaraswamy.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.kumaraswamy.state\n    <Uint32Array>\n\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n\n    // Set the state:\n    > base.random.kumaraswamy.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n\n\nbase.random.kumaraswamy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.kumaraswamy.stateLength;\n\n\nbase.random.kumaraswamy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.kumaraswamy.byteLength;\n\n\nbase.random.kumaraswamy.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.kumaraswamy.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.kumaraswamy, random.iterators.kumaraswamy, random.streams.kumaraswamy\n","base.random.kumaraswamy.factory":"\nbase.random.kumaraswamy.factory( [a, b, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from Kumaraswamy's double bounded distribution.\n\n    If provided `a` and `b`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `a` and `b`, the returned PRNG requires that both `a` and\n    `b` be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        First shape parameter.\n\n    b: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.kumaraswamy.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `a` and `b`:\n    > rand = base.random.kumaraswamy.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.kumaraswamy.NAME":"\nbase.random.kumaraswamy.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.kumaraswamy.NAME\n    'kumaraswamy'","base.random.kumaraswamy.PRNG":"\nbase.random.kumaraswamy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.kumaraswamy.PRNG;","base.random.kumaraswamy.seed":"\nbase.random.kumaraswamy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.kumaraswamy.seed;","base.random.kumaraswamy.seedLength":"\nbase.random.kumaraswamy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.kumaraswamy.seedLength;","base.random.kumaraswamy.state":"\nbase.random.kumaraswamy.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.kumaraswamy.state\n    <Uint32Array>\n\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n\n    // Set the state:\n    > base.random.kumaraswamy.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>","base.random.kumaraswamy.stateLength":"\nbase.random.kumaraswamy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.kumaraswamy.stateLength;","base.random.kumaraswamy.byteLength":"\nbase.random.kumaraswamy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.kumaraswamy.byteLength;","base.random.kumaraswamy.toJSON":"\nbase.random.kumaraswamy.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.kumaraswamy.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.kumaraswamy, random.iterators.kumaraswamy, random.streams.kumaraswamy","base.random.laplace":"\nbase.random.laplace( μ, b )\n    Returns a pseudorandom number drawn from a Laplace distribution.\n\n    If `μ` or `b` is `NaN` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.laplace( 2.0, 5.0 );\n\n\nbase.random.laplace.factory( [μ, b, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Laplace distribution.\n\n    If provided `μ` and `b`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `b`, the returned PRNG requires that both `μ` and\n    `b` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    b: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.laplace.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `b`:\n    > rand = base.random.laplace.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.laplace.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.laplace.NAME\n    'laplace'\n\n\nbase.random.laplace.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.laplace.PRNG;\n\n\nbase.random.laplace.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.laplace.seed;\n\n\nbase.random.laplace.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.laplace.seedLength;\n\n\nbase.random.laplace.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.laplace( 2.0, 5.0 )\n    <number>\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.laplace.state\n    <Uint32Array>\n\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.laplace.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>\n\n\nbase.random.laplace.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.laplace.stateLength;\n\n\nbase.random.laplace.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.laplace.byteLength;\n\n\nbase.random.laplace.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.laplace.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.laplace, random.iterators.laplace, random.streams.laplace\n","base.random.laplace.factory":"\nbase.random.laplace.factory( [μ, b, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Laplace distribution.\n\n    If provided `μ` and `b`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `b`, the returned PRNG requires that both `μ` and\n    `b` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    b: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.laplace.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `b`:\n    > rand = base.random.laplace.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.laplace.NAME":"\nbase.random.laplace.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.laplace.NAME\n    'laplace'","base.random.laplace.PRNG":"\nbase.random.laplace.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.laplace.PRNG;","base.random.laplace.seed":"\nbase.random.laplace.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.laplace.seed;","base.random.laplace.seedLength":"\nbase.random.laplace.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.laplace.seedLength;","base.random.laplace.state":"\nbase.random.laplace.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.laplace( 2.0, 5.0 )\n    <number>\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.laplace.state\n    <Uint32Array>\n\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.laplace.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>","base.random.laplace.stateLength":"\nbase.random.laplace.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.laplace.stateLength;","base.random.laplace.byteLength":"\nbase.random.laplace.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.laplace.byteLength;","base.random.laplace.toJSON":"\nbase.random.laplace.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.laplace.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.laplace, random.iterators.laplace, random.streams.laplace","base.random.levy":"\nbase.random.levy( μ, c )\n    Returns a pseudorandom number drawn from a Lévy distribution.\n\n    If `μ` or `c` is `NaN` or `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.levy( 2.0, 5.0 );\n\n\nbase.random.levy.factory( [μ, c, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Lévy distribution.\n\n    If provided `μ` and `c`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `c`, the returned PRNG requires that both `μ` and\n    `c` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    c: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.levy.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `b`:\n    > rand = base.random.levy.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.levy.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.levy.NAME\n    'levy'\n\n\nbase.random.levy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.levy.PRNG;\n\n\nbase.random.levy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.levy.seed;\n\n\nbase.random.levy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.levy.seedLength;\n\n\nbase.random.levy.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.levy( 2.0, 5.0 )\n    <number>\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.levy.state\n    <Uint32Array>\n\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.levy.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>\n\n\nbase.random.levy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.levy.stateLength;\n\n\nbase.random.levy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.levy.byteLength;\n\n\nbase.random.levy.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.levy.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.levy, random.iterators.levy, random.streams.levy\n","base.random.levy.factory":"\nbase.random.levy.factory( [μ, c, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Lévy distribution.\n\n    If provided `μ` and `c`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `c`, the returned PRNG requires that both `μ` and\n    `c` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    c: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.levy.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `b`:\n    > rand = base.random.levy.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.levy.NAME":"\nbase.random.levy.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.levy.NAME\n    'levy'","base.random.levy.PRNG":"\nbase.random.levy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.levy.PRNG;","base.random.levy.seed":"\nbase.random.levy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.levy.seed;","base.random.levy.seedLength":"\nbase.random.levy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.levy.seedLength;","base.random.levy.state":"\nbase.random.levy.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.levy( 2.0, 5.0 )\n    <number>\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.levy.state\n    <Uint32Array>\n\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.levy.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>","base.random.levy.stateLength":"\nbase.random.levy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.levy.stateLength;","base.random.levy.byteLength":"\nbase.random.levy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.levy.byteLength;","base.random.levy.toJSON":"\nbase.random.levy.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.levy.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.levy, random.iterators.levy, random.streams.levy","base.random.logistic":"\nbase.random.logistic( μ, s )\n    Returns a pseudorandom number drawn from a logistic distribution.\n\n    If `μ` or `s` is `NaN` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.logistic( 2.0, 5.0 );\n\n\nbase.random.logistic.factory( [μ, s, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a logistic distribution.\n\n    If provided `μ` and `s`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n    `s` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.logistic.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `s`:\n    > rand = base.random.logistic.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.logistic.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.logistic.NAME\n    'logistic'\n\n\nbase.random.logistic.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.logistic.PRNG;\n\n\nbase.random.logistic.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.logistic.seed;\n\n\nbase.random.logistic.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.logistic.seedLength;\n\n\nbase.random.logistic.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.logistic( 2.0, 5.0 )\n    <number>\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.logistic.state\n    <Uint32Array>\n\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.logistic.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>\n\n\nbase.random.logistic.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.logistic.stateLength;\n\n\nbase.random.logistic.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.logistic.byteLength;\n\n\nbase.random.logistic.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.logistic.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.logistic, random.iterators.logistic, random.streams.logistic\n","base.random.logistic.factory":"\nbase.random.logistic.factory( [μ, s, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a logistic distribution.\n\n    If provided `μ` and `s`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n    `s` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.logistic.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `s`:\n    > rand = base.random.logistic.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.logistic.NAME":"\nbase.random.logistic.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.logistic.NAME\n    'logistic'","base.random.logistic.PRNG":"\nbase.random.logistic.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.logistic.PRNG;","base.random.logistic.seed":"\nbase.random.logistic.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.logistic.seed;","base.random.logistic.seedLength":"\nbase.random.logistic.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.logistic.seedLength;","base.random.logistic.state":"\nbase.random.logistic.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.logistic( 2.0, 5.0 )\n    <number>\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.logistic.state\n    <Uint32Array>\n\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.logistic.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>","base.random.logistic.stateLength":"\nbase.random.logistic.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.logistic.stateLength;","base.random.logistic.byteLength":"\nbase.random.logistic.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.logistic.byteLength;","base.random.logistic.toJSON":"\nbase.random.logistic.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.logistic.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.logistic, random.iterators.logistic, random.streams.logistic","base.random.lognormal":"\nbase.random.lognormal( μ, σ )\n    Returns a pseudorandom number drawn from a lognormal distribution.\n\n    If `μ` or `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.lognormal( 2.0, 5.0 );\n\n\nbase.random.lognormal.factory( [μ, σ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a lognormal distribution.\n\n    If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n    `σ` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter.\n\n    σ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.lognormal.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `σ`:\n    > rand = base.random.lognormal.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.lognormal.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.lognormal.NAME\n    'lognormal'\n\n\nbase.random.lognormal.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.lognormal.PRNG;\n\n\nbase.random.lognormal.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.lognormal.seed;\n\n\nbase.random.lognormal.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.lognormal.seedLength;\n\n\nbase.random.lognormal.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.lognormal.state\n    <Uint32Array>\n\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.lognormal.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n\n\nbase.random.lognormal.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.lognormal.stateLength;\n\n\nbase.random.lognormal.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.lognormal.byteLength;\n\n\nbase.random.lognormal.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.lognormal.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.lognormal, random.iterators.lognormal, random.streams.lognormal\n","base.random.lognormal.factory":"\nbase.random.lognormal.factory( [μ, σ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a lognormal distribution.\n\n    If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n    `σ` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter.\n\n    σ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.lognormal.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `σ`:\n    > rand = base.random.lognormal.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.lognormal.NAME":"\nbase.random.lognormal.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.lognormal.NAME\n    'lognormal'","base.random.lognormal.PRNG":"\nbase.random.lognormal.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.lognormal.PRNG;","base.random.lognormal.seed":"\nbase.random.lognormal.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.lognormal.seed;","base.random.lognormal.seedLength":"\nbase.random.lognormal.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.lognormal.seedLength;","base.random.lognormal.state":"\nbase.random.lognormal.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.lognormal.state\n    <Uint32Array>\n\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.lognormal.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>","base.random.lognormal.stateLength":"\nbase.random.lognormal.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.lognormal.stateLength;","base.random.lognormal.byteLength":"\nbase.random.lognormal.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.lognormal.byteLength;","base.random.lognormal.toJSON":"\nbase.random.lognormal.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.lognormal.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.lognormal, random.iterators.lognormal, random.streams.lognormal","base.random.minstd":"\nbase.random.minstd()\n    Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n\n    This pseudorandom number generator (PRNG) is a linear congruential\n    pseudorandom number generator (LCG) based on Park and Miller.\n\n    The generator has a period of approximately `2.1e9`.\n\n    An LCG is fast and uses little memory. On the other hand, because the\n    generator is a simple LCG, the generator has recognized shortcomings. By\n    today's PRNG standards, the generator's period is relatively short. More\n    importantly, the \"randomness quality\" of the generator's output is lacking.\n    These defects make the generator unsuitable, for example, in Monte Carlo\n    simulations and in cryptographic applications.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.minstd();\n\n\nbase.random.minstd.normalized()\n    Returns a pseudorandom number on the interval `[0,1)`.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.minstd.normalized();\n\n\nbase.random.minstd.factory( [options] )\n    Returns a linear congruential pseudorandom number generator (LCG).\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.minstd.factory();\n    > r = rand();\n    > r = rand();\n\n    // Provide a seed:\n    > rand = base.random.minstd.factory( { 'seed': 1234 } );\n    > r = rand()\n    20739838\n\n\nbase.random.minstd.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.minstd.NAME\n    'minstd'\n\n\nbase.random.minstd.MIN\n    Minimum possible value.\n\n    Examples\n    --------\n    > var v = base.random.minstd.MIN\n    1\n\n\nbase.random.minstd.MAX\n    Maximum possible value.\n\n    Examples\n    --------\n    > var v = base.random.minstd.MAX\n    2147483646\n\n\nbase.random.minstd.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.minstd.seed;\n\n\nbase.random.minstd.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.minstd.seedLength;\n\n\nbase.random.minstd.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.minstd()\n    <number>\n    > r = base.random.minstd()\n    <number>\n    > r = base.random.minstd()\n    <number>\n\n    // Get the current state:\n    > var state = base.random.minstd.state\n    <Int32Array>\n\n    > r = base.random.minstd()\n    <number>\n    > r = base.random.minstd()\n    <number>\n\n    // Set the state:\n    > base.random.minstd.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.minstd()\n    <number>\n    > r = base.random.minstd()\n    <number>\n\n\nbase.random.minstd.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.minstd.stateLength;\n\n\nbase.random.minstd.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.minstd.byteLength;\n\n\nbase.random.minstd.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.minstd.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.minstd, random.iterators.minstd, random.streams.minstd, base.random.minstdShuffle, base.random.mt19937, base.random.randi\n","base.random.minstd.normalized":"\nbase.random.minstd.normalized()\n    Returns a pseudorandom number on the interval `[0,1)`.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.minstd.normalized();","base.random.minstd.factory":"\nbase.random.minstd.factory( [options] )\n    Returns a linear congruential pseudorandom number generator (LCG).\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.minstd.factory();\n    > r = rand();\n    > r = rand();\n\n    // Provide a seed:\n    > rand = base.random.minstd.factory( { 'seed': 1234 } );\n    > r = rand()\n    20739838","base.random.minstd.NAME":"\nbase.random.minstd.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.minstd.NAME\n    'minstd'","base.random.minstd.MIN":"\nbase.random.minstd.MIN\n    Minimum possible value.\n\n    Examples\n    --------\n    > var v = base.random.minstd.MIN\n    1","base.random.minstd.MAX":"\nbase.random.minstd.MAX\n    Maximum possible value.\n\n    Examples\n    --------\n    > var v = base.random.minstd.MAX\n    2147483646","base.random.minstd.seed":"\nbase.random.minstd.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.minstd.seed;","base.random.minstd.seedLength":"\nbase.random.minstd.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.minstd.seedLength;","base.random.minstd.state":"\nbase.random.minstd.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.minstd()\n    <number>\n    > r = base.random.minstd()\n    <number>\n    > r = base.random.minstd()\n    <number>\n\n    // Get the current state:\n    > var state = base.random.minstd.state\n    <Int32Array>\n\n    > r = base.random.minstd()\n    <number>\n    > r = base.random.minstd()\n    <number>\n\n    // Set the state:\n    > base.random.minstd.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.minstd()\n    <number>\n    > r = base.random.minstd()\n    <number>","base.random.minstd.stateLength":"\nbase.random.minstd.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.minstd.stateLength;","base.random.minstd.byteLength":"\nbase.random.minstd.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.minstd.byteLength;","base.random.minstd.toJSON":"\nbase.random.minstd.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.minstd.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.minstd, random.iterators.minstd, random.streams.minstd, base.random.minstdShuffle, base.random.mt19937, base.random.randi","base.random.minstdShuffle":"\nbase.random.minstdShuffle()\n    Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n\n    This pseudorandom number generator (PRNG) is a linear congruential\n    pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n    Durham algorithm. The shuffle step considerably strengthens the \"randomness\n    quality\" of a simple LCG's output.\n\n    The generator has a period of approximately `2.1e9`.\n\n    An LCG is fast and uses little memory. On the other hand, because the\n    generator is a simple LCG, the generator has recognized shortcomings. By\n    today's PRNG standards, the generator's period is relatively short. In\n    general, this generator is unsuitable for Monte Carlo simulations and\n    cryptographic applications.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.minstdShuffle();\n\n\nbase.random.minstdShuffle.normalized()\n    Returns a pseudorandom number on the interval `[0,1)`.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.minstdShuffle.normalized();\n\n\nbase.random.minstdShuffle.factory( [options] )\n    Returns a linear congruential pseudorandom number generator (LCG) whose\n    output is shuffled.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.minstdShuffle.factory();\n    > r = rand();\n    > r = rand();\n\n    // Provide a seed:\n    > rand = base.random.minstdShuffle.factory( { 'seed': 1234 } );\n    > r = rand()\n    1421600654\n\n\nbase.random.minstdShuffle.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.minstdShuffle.NAME\n    'minstd-shuffle'\n\n\nbase.random.minstdShuffle.MIN\n    Minimum possible value.\n\n    Examples\n    --------\n    > var v = base.random.minstdShuffle.MIN\n    1\n\n\nbase.random.minstdShuffle.MAX\n    Maximum possible value.\n\n    Examples\n    --------\n    > var v = base.random.minstdShuffle.MAX\n    2147483646\n\n\nbase.random.minstdShuffle.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.minstdShuffle.seed;\n\n\nbase.random.minstdShuffle.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.minstdShuffle.seedLength;\n\n\nbase.random.minstdShuffle.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.minstdShuffle()\n    <number>\n    > r = base.random.minstdShuffle()\n    <number>\n    > r = base.random.minstdShuffle()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.minstdShuffle.state\n    <Int32Array>\n\n    > r = base.random.minstdShuffle()\n    <number>\n    > r = base.random.minstdShuffle()\n    <number>\n\n    // Set the state:\n    > base.random.minstdShuffle.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.minstdShuffle()\n    <number>\n    > r = base.random.minstdShuffle()\n    <number>\n\n\nbase.random.minstdShuffle.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.minstdShuffle.stateLength;\n\n\nbase.random.minstdShuffle.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.minstdShuffle.byteLength;\n\n\nbase.random.minstdShuffle.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.minstdShuffle.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstdShuffle, base.random.minstd, base.random.mt19937, base.random.randi\n","base.random.minstdShuffle.normalized":"\nbase.random.minstdShuffle.normalized()\n    Returns a pseudorandom number on the interval `[0,1)`.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.minstdShuffle.normalized();","base.random.minstdShuffle.factory":"\nbase.random.minstdShuffle.factory( [options] )\n    Returns a linear congruential pseudorandom number generator (LCG) whose\n    output is shuffled.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.minstdShuffle.factory();\n    > r = rand();\n    > r = rand();\n\n    // Provide a seed:\n    > rand = base.random.minstdShuffle.factory( { 'seed': 1234 } );\n    > r = rand()\n    1421600654","base.random.minstdShuffle.NAME":"\nbase.random.minstdShuffle.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.minstdShuffle.NAME\n    'minstd-shuffle'","base.random.minstdShuffle.MIN":"\nbase.random.minstdShuffle.MIN\n    Minimum possible value.\n\n    Examples\n    --------\n    > var v = base.random.minstdShuffle.MIN\n    1","base.random.minstdShuffle.MAX":"\nbase.random.minstdShuffle.MAX\n    Maximum possible value.\n\n    Examples\n    --------\n    > var v = base.random.minstdShuffle.MAX\n    2147483646","base.random.minstdShuffle.seed":"\nbase.random.minstdShuffle.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.minstdShuffle.seed;","base.random.minstdShuffle.seedLength":"\nbase.random.minstdShuffle.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.minstdShuffle.seedLength;","base.random.minstdShuffle.state":"\nbase.random.minstdShuffle.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.minstdShuffle()\n    <number>\n    > r = base.random.minstdShuffle()\n    <number>\n    > r = base.random.minstdShuffle()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.minstdShuffle.state\n    <Int32Array>\n\n    > r = base.random.minstdShuffle()\n    <number>\n    > r = base.random.minstdShuffle()\n    <number>\n\n    // Set the state:\n    > base.random.minstdShuffle.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.minstdShuffle()\n    <number>\n    > r = base.random.minstdShuffle()\n    <number>","base.random.minstdShuffle.stateLength":"\nbase.random.minstdShuffle.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.minstdShuffle.stateLength;","base.random.minstdShuffle.byteLength":"\nbase.random.minstdShuffle.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.minstdShuffle.byteLength;","base.random.minstdShuffle.toJSON":"\nbase.random.minstdShuffle.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.minstdShuffle.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstdShuffle, base.random.minstd, base.random.mt19937, base.random.randi","base.random.mt19937":"\nbase.random.mt19937()\n    Returns a pseudorandom integer on the interval `[0, 4294967295]`.\n\n    This pseudorandom number generator (PRNG) is a 32-bit Mersenne Twister\n    pseudorandom number generator.\n\n    The PRNG is *not* a cryptographically secure PRNG.\n\n    The PRNG has a period of 2^19937 - 1.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.mt19937();\n\n\nbase.random.mt19937.normalized()\n    Returns a pseudorandom number on the interval `[0,1)` with 53-bit precision.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.mt19937.normalized();\n\n\nbase.random.mt19937.factory( [options] )\n    Returns a 32-bit Mersenne Twister pseudorandom number generator.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.mt19937.factory();\n    > r = rand();\n    > r = rand();\n\n    // Provide a seed:\n    > rand = base.random.mt19937.factory( { 'seed': 1234 } );\n    > r = rand()\n    822569775\n\n\nbase.random.mt19937.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.mt19937.NAME\n    'mt19937'\n\n\nbase.random.mt19937.MIN\n    Minimum possible value.\n\n    Examples\n    --------\n    > var v = base.random.mt19937.MIN\n    0\n\n\nbase.random.mt19937.MAX\n    Maximum possible value.\n\n    Examples\n    --------\n    > var v = base.random.mt19937.MAX\n    4294967295\n\n\nbase.random.mt19937.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.mt19937.seed;\n\n\nbase.random.mt19937.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.mt19937.seedLength;\n\n\nbase.random.mt19937.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.mt19937()\n    <number>\n    > r = base.random.mt19937()\n    <number>\n    > r = base.random.mt19937()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.mt19937.state\n    <Uint32Array>\n\n    > r = base.random.mt19937()\n    <number>\n    > r = base.random.mt19937()\n    <number>\n\n    // Set the state:\n    > base.random.mt19937.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.mt19937()\n    <number>\n    > r = base.random.mt19937()\n    <number>\n\n\nbase.random.mt19937.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.mt19937.stateLength;\n\n\nbase.random.mt19937.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.mt19937.byteLength;\n\n\nbase.random.mt19937.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.mt19937.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.mt19937, random.iterators.mt19937, random.streams.mt19937, base.random.minstd, base.random.randi\n","base.random.mt19937.normalized":"\nbase.random.mt19937.normalized()\n    Returns a pseudorandom number on the interval `[0,1)` with 53-bit precision.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.mt19937.normalized();","base.random.mt19937.factory":"\nbase.random.mt19937.factory( [options] )\n    Returns a 32-bit Mersenne Twister pseudorandom number generator.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.mt19937.factory();\n    > r = rand();\n    > r = rand();\n\n    // Provide a seed:\n    > rand = base.random.mt19937.factory( { 'seed': 1234 } );\n    > r = rand()\n    822569775","base.random.mt19937.NAME":"\nbase.random.mt19937.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.mt19937.NAME\n    'mt19937'","base.random.mt19937.MIN":"\nbase.random.mt19937.MIN\n    Minimum possible value.\n\n    Examples\n    --------\n    > var v = base.random.mt19937.MIN\n    0","base.random.mt19937.MAX":"\nbase.random.mt19937.MAX\n    Maximum possible value.\n\n    Examples\n    --------\n    > var v = base.random.mt19937.MAX\n    4294967295","base.random.mt19937.seed":"\nbase.random.mt19937.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.mt19937.seed;","base.random.mt19937.seedLength":"\nbase.random.mt19937.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.mt19937.seedLength;","base.random.mt19937.state":"\nbase.random.mt19937.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.mt19937()\n    <number>\n    > r = base.random.mt19937()\n    <number>\n    > r = base.random.mt19937()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.mt19937.state\n    <Uint32Array>\n\n    > r = base.random.mt19937()\n    <number>\n    > r = base.random.mt19937()\n    <number>\n\n    // Set the state:\n    > base.random.mt19937.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.mt19937()\n    <number>\n    > r = base.random.mt19937()\n    <number>","base.random.mt19937.stateLength":"\nbase.random.mt19937.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.mt19937.stateLength;","base.random.mt19937.byteLength":"\nbase.random.mt19937.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.mt19937.byteLength;","base.random.mt19937.toJSON":"\nbase.random.mt19937.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.mt19937.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.mt19937, random.iterators.mt19937, random.streams.mt19937, base.random.minstd, base.random.randi","base.random.negativeBinomial":"\nbase.random.negativeBinomial( r, p )\n    Returns a pseudorandom number drawn from a negative binomial distribution.\n\n    If `p` is not in the interval `(0,1)`, the function returns `NaN`.\n\n    If `r` or `p` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.negativeBinomial( 20, 0.8 );\n\n\nbase.random.negativeBinomial.factory( [r, p, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a negative binomial distribution.\n\n    If provided `r` and `p`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `r` and `p`, the returned PRNG requires that both `r` and\n    `p` be provided at each invocation.\n\n    Parameters\n    ----------\n    r: number (optional)\n        Number of successes until experiment is stopped.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.negativeBinomial.factory();\n    > var r = rand( 20, 0.3 );\n    > r = rand( 10, 0.77 );\n\n    // Provide `r` and `p`:\n    > rand = base.random.negativeBinomial.factory( 10, 0.8 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.negativeBinomial.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.negativeBinomial.NAME\n    'negative-binomial'\n\n\nbase.random.negativeBinomial.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.negativeBinomial.PRNG;\n\n\nbase.random.negativeBinomial.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.negativeBinomial.seed;\n\n\nbase.random.negativeBinomial.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.negativeBinomial.seedLength;\n\n\nbase.random.negativeBinomial.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.negativeBinomial.state\n    <Uint32Array>\n\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n\n    // Set the state:\n    > base.random.negativeBinomial.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n\n\nbase.random.negativeBinomial.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.negativeBinomial.stateLength;\n\n\nbase.random.negativeBinomial.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.negativeBinomial.byteLength;\n\n\nbase.random.negativeBinomial.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.negativeBinomial.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.negativeBinomial, random.iterators.negativeBinomial, random.streams.negativeBinomial\n","base.random.negativeBinomial.factory":"\nbase.random.negativeBinomial.factory( [r, p, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a negative binomial distribution.\n\n    If provided `r` and `p`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `r` and `p`, the returned PRNG requires that both `r` and\n    `p` be provided at each invocation.\n\n    Parameters\n    ----------\n    r: number (optional)\n        Number of successes until experiment is stopped.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.negativeBinomial.factory();\n    > var r = rand( 20, 0.3 );\n    > r = rand( 10, 0.77 );\n\n    // Provide `r` and `p`:\n    > rand = base.random.negativeBinomial.factory( 10, 0.8 );\n    > r = rand();\n    > r = rand();","base.random.negativeBinomial.NAME":"\nbase.random.negativeBinomial.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.negativeBinomial.NAME\n    'negative-binomial'","base.random.negativeBinomial.PRNG":"\nbase.random.negativeBinomial.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.negativeBinomial.PRNG;","base.random.negativeBinomial.seed":"\nbase.random.negativeBinomial.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.negativeBinomial.seed;","base.random.negativeBinomial.seedLength":"\nbase.random.negativeBinomial.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.negativeBinomial.seedLength;","base.random.negativeBinomial.state":"\nbase.random.negativeBinomial.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.negativeBinomial.state\n    <Uint32Array>\n\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n\n    // Set the state:\n    > base.random.negativeBinomial.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>","base.random.negativeBinomial.stateLength":"\nbase.random.negativeBinomial.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.negativeBinomial.stateLength;","base.random.negativeBinomial.byteLength":"\nbase.random.negativeBinomial.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.negativeBinomial.byteLength;","base.random.negativeBinomial.toJSON":"\nbase.random.negativeBinomial.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.negativeBinomial.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.negativeBinomial, random.iterators.negativeBinomial, random.streams.negativeBinomial","base.random.normal":"\nbase.random.normal( μ, σ )\n    Returns a pseudorandom number drawn from a normal distribution.\n\n    If `μ` or `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.normal( 2.0, 5.0 );\n\n\nbase.random.normal.factory( [μ, σ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a normal distribution.\n\n    If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n    `σ` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    σ: number (optional)\n        Standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.normal.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `σ`:\n    > rand = base.random.normal.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.normal.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.normal.NAME\n    'normal'\n\n\nbase.random.normal.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.normal.PRNG;\n\n\nbase.random.normal.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.normal.seed;\n\n\nbase.random.normal.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.normal.seedLength;\n\n\nbase.random.normal.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.normal( 2.0, 5.0 )\n    <number>\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.normal.state\n    <Uint32Array>\n\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.normal.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>\n\n\nbase.random.normal.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.normal.stateLength;\n\n\nbase.random.normal.byteLength\n    Size of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.normal.byteLength;\n\n\nbase.random.normal.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.normal.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.normal, random.iterators.normal, random.streams.normal\n","base.random.normal.factory":"\nbase.random.normal.factory( [μ, σ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a normal distribution.\n\n    If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n    `σ` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    σ: number (optional)\n        Standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.normal.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `σ`:\n    > rand = base.random.normal.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.normal.NAME":"\nbase.random.normal.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.normal.NAME\n    'normal'","base.random.normal.PRNG":"\nbase.random.normal.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.normal.PRNG;","base.random.normal.seed":"\nbase.random.normal.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.normal.seed;","base.random.normal.seedLength":"\nbase.random.normal.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.normal.seedLength;","base.random.normal.state":"\nbase.random.normal.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.normal( 2.0, 5.0 )\n    <number>\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.normal.state\n    <Uint32Array>\n\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.normal.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>","base.random.normal.stateLength":"\nbase.random.normal.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.normal.stateLength;","base.random.normal.byteLength":"\nbase.random.normal.byteLength\n    Size of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.normal.byteLength;","base.random.normal.toJSON":"\nbase.random.normal.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.normal.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.normal, random.iterators.normal, random.streams.normal","base.random.pareto1":"\nbase.random.pareto1( α, β )\n    Returns a pseudorandom number drawn from a Pareto (Type I) distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.pareto1( 2.0, 5.0 );\n\n\nbase.random.pareto1.factory( [α, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Pareto (Type I) distribution.\n\n    If provided `α` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `α` and `β`, the returned PRNG requires that both `α` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.pareto1.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `α` and `β`:\n    > rand = base.random.pareto1.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.pareto1.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.pareto1.NAME\n    'pareto-type1'\n\n\nbase.random.pareto1.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.pareto1.PRNG;\n\n\nbase.random.pareto1.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.pareto1.seed;\n\n\nbase.random.pareto1.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.pareto1.seedLength;\n\n\nbase.random.pareto1.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.pareto1.state\n    <Uint32Array>\n\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.pareto1.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n\n\nbase.random.pareto1.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.pareto1.stateLength;\n\n\nbase.random.pareto1.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.pareto1.byteLength;\n\n\nbase.random.pareto1.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.pareto1.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.pareto1, random.iterators.pareto1, random.streams.pareto1\n","base.random.pareto1.factory":"\nbase.random.pareto1.factory( [α, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Pareto (Type I) distribution.\n\n    If provided `α` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `α` and `β`, the returned PRNG requires that both `α` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.pareto1.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `α` and `β`:\n    > rand = base.random.pareto1.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.pareto1.NAME":"\nbase.random.pareto1.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.pareto1.NAME\n    'pareto-type1'","base.random.pareto1.PRNG":"\nbase.random.pareto1.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.pareto1.PRNG;","base.random.pareto1.seed":"\nbase.random.pareto1.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.pareto1.seed;","base.random.pareto1.seedLength":"\nbase.random.pareto1.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.pareto1.seedLength;","base.random.pareto1.state":"\nbase.random.pareto1.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.pareto1.state\n    <Uint32Array>\n\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.pareto1.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>","base.random.pareto1.stateLength":"\nbase.random.pareto1.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.pareto1.stateLength;","base.random.pareto1.byteLength":"\nbase.random.pareto1.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.pareto1.byteLength;","base.random.pareto1.toJSON":"\nbase.random.pareto1.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.pareto1.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.pareto1, random.iterators.pareto1, random.streams.pareto1","base.random.poisson":"\nbase.random.poisson( λ )\n    Returns a pseudorandom number drawn from a Poisson distribution.\n\n    If `λ <= 0` or `λ` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.poisson( 7.9 );\n\n\nbase.random.poisson.factory( [λ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Poisson distribution.\n\n    If provided `λ`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    λ: number (optional)\n        Mean.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.poisson.factory();\n    > var r = rand( 4.0 );\n    > r = rand( 3.14 );\n\n    // Provide `λ`:\n    > rand = base.random.poisson.factory( 10.0 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.poisson.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.poisson.NAME\n    'poisson'\n\n\nbase.random.poisson.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.poisson.PRNG;\n\n\nbase.random.poisson.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.poisson.seed;\n\n\nbase.random.poisson.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.poisson.seedLength;\n\n\nbase.random.poisson.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.poisson( 10.0 )\n    <number>\n    > r = base.random.poisson( 10.0 )\n    <number>\n    > r = base.random.poisson( 10.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.poisson.state\n    <Uint32Array>\n\n    > r = base.random.poisson( 10.0 )\n    <number>\n    > r = base.random.poisson( 10.0 )\n    <number>\n\n    // Set the state:\n    > base.random.poisson.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.poisson( 10.0 )\n    <number>\n    > r = base.random.poisson( 10.0 )\n    <number>\n\n\nbase.random.poisson.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.poisson.stateLength;\n\n\nbase.random.poisson.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.poisson.byteLength;\n\n\nbase.random.poisson.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.poisson.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.poisson, random.iterators.poisson, random.streams.poisson\n","base.random.poisson.factory":"\nbase.random.poisson.factory( [λ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Poisson distribution.\n\n    If provided `λ`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    λ: number (optional)\n        Mean.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.poisson.factory();\n    > var r = rand( 4.0 );\n    > r = rand( 3.14 );\n\n    // Provide `λ`:\n    > rand = base.random.poisson.factory( 10.0 );\n    > r = rand();\n    > r = rand();","base.random.poisson.NAME":"\nbase.random.poisson.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.poisson.NAME\n    'poisson'","base.random.poisson.PRNG":"\nbase.random.poisson.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.poisson.PRNG;","base.random.poisson.seed":"\nbase.random.poisson.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.poisson.seed;","base.random.poisson.seedLength":"\nbase.random.poisson.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.poisson.seedLength;","base.random.poisson.state":"\nbase.random.poisson.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.poisson( 10.0 )\n    <number>\n    > r = base.random.poisson( 10.0 )\n    <number>\n    > r = base.random.poisson( 10.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.poisson.state\n    <Uint32Array>\n\n    > r = base.random.poisson( 10.0 )\n    <number>\n    > r = base.random.poisson( 10.0 )\n    <number>\n\n    // Set the state:\n    > base.random.poisson.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.poisson( 10.0 )\n    <number>\n    > r = base.random.poisson( 10.0 )\n    <number>","base.random.poisson.stateLength":"\nbase.random.poisson.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.poisson.stateLength;","base.random.poisson.byteLength":"\nbase.random.poisson.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.poisson.byteLength;","base.random.poisson.toJSON":"\nbase.random.poisson.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.poisson.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.poisson, random.iterators.poisson, random.streams.poisson","base.random.randi":"\nbase.random.randi()\n    Returns a pseudorandom number having an integer value.\n\n    The default underlying pseudorandom number generator (PRNG) *may* change in\n    the future. If exact reproducibility is required, either use the `factory`\n    method to explicitly specify a PRNG via the `name` option or use an\n    underlying PRNG directly.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.randi();\n\n\nbase.random.randi.factory( [options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers having integer values.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of the underlying pseudorandom number generator (PRNG). The\n        following PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underlying PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var randi = base.random.randi.factory();\n    > var r = randi();\n    > r = randi();\n\n    // Specify alternative PRNG:\n    > randi = base.random.randi.factory({ 'name': 'minstd' });\n    > r = randi();\n    > r = randi();\n\n\nbase.random.randi.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.randi.NAME\n    'randi'\n\n\nbase.random.randi.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.randi.PRNG;\n\n\nbase.random.randi.MIN\n    Minimum possible value (specific to underlying PRNG).\n\n    Examples\n    --------\n    > var v = base.random.randi.MIN;\n\n\nbase.random.randi.MAX\n    Maximum possible value (specific to underlying PRNG).\n\n    Examples\n    --------\n    > var v = base.random.randi.MAX;\n\n\nbase.random.randi.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.randi.seed;\n\n\nbase.random.randi.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.randi.seedLength;\n\n\nbase.random.randi.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.randi()\n    <number>\n    > r = base.random.randi()\n    <number>\n    > r = base.random.randi()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.randi.state;\n\n    > r = base.random.randi()\n    <number>\n    > r = base.random.randi()\n    <number>\n\n    // Set the state:\n    > base.random.randi.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.randi()\n    <number>\n    > r = base.random.randi()\n    <number>\n\n\nbase.random.randi.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.randi.stateLength;\n\n\nbase.random.randi.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.randi.byteLength;\n\n\nbase.random.randi.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.randi.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.iterators.randi, random.streams.randi, base.random.minstd, base.random.minstdShuffle, base.random.mt19937\n","base.random.randi.factory":"\nbase.random.randi.factory( [options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers having integer values.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of the underlying pseudorandom number generator (PRNG). The\n        following PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underlying PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var randi = base.random.randi.factory();\n    > var r = randi();\n    > r = randi();\n\n    // Specify alternative PRNG:\n    > randi = base.random.randi.factory({ 'name': 'minstd' });\n    > r = randi();\n    > r = randi();","base.random.randi.NAME":"\nbase.random.randi.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.randi.NAME\n    'randi'","base.random.randi.PRNG":"\nbase.random.randi.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.randi.PRNG;","base.random.randi.MIN":"\nbase.random.randi.MIN\n    Minimum possible value (specific to underlying PRNG).\n\n    Examples\n    --------\n    > var v = base.random.randi.MIN;","base.random.randi.MAX":"\nbase.random.randi.MAX\n    Maximum possible value (specific to underlying PRNG).\n\n    Examples\n    --------\n    > var v = base.random.randi.MAX;","base.random.randi.seed":"\nbase.random.randi.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.randi.seed;","base.random.randi.seedLength":"\nbase.random.randi.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.randi.seedLength;","base.random.randi.state":"\nbase.random.randi.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.randi()\n    <number>\n    > r = base.random.randi()\n    <number>\n    > r = base.random.randi()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.randi.state;\n\n    > r = base.random.randi()\n    <number>\n    > r = base.random.randi()\n    <number>\n\n    // Set the state:\n    > base.random.randi.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.randi()\n    <number>\n    > r = base.random.randi()\n    <number>","base.random.randi.stateLength":"\nbase.random.randi.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.randi.stateLength;","base.random.randi.byteLength":"\nbase.random.randi.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.randi.byteLength;","base.random.randi.toJSON":"\nbase.random.randi.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.randi.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.iterators.randi, random.streams.randi, base.random.minstd, base.random.minstdShuffle, base.random.mt19937","base.random.randn":"\nbase.random.randn()\n    Returns a pseudorandom number drawn from a standard normal distribution.\n\n    The default underlying pseudorandom number generator (PRNG) *may* change in\n    the future. If exact reproducibility is required, either use the `factory`\n    method to explicitly specify a PRNG via the `name` option or use an\n    underlying PRNG directly.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.randn();\n\n\nbase.random.randn.factory( [options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a standard normal distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of the underlying pseudorandom number generator (PRNG) that samples\n        from a standard normal distribution. The following PRNGs are supported:\n\n        - improved-ziggurat: improved ziggurat method.\n        - box-muller: Box-Muller transform.\n\n        Default: 'improved-ziggurat'.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underlying PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.randn.factory();\n    > var r = rand();\n    > r = rand();\n\n    // Specify alternative PRNG:\n    > var rand = base.random.randn.factory({ 'name': 'box-muller' });\n    > r = rand();\n    > r = rand();\n\n\nbase.random.randn.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.randn.NAME\n    'randn'\n\n\nbase.random.randn.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.randn.PRNG;\n\n\nbase.random.randn.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.randn.seed;\n\n\nbase.random.randn.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.randn.seedLength;\n\n\nbase.random.randn.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.randn()\n    <number>\n    > r = base.random.randn()\n    <number>\n    > r = base.random.randn()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.randn.state;\n\n    > r = base.random.randn()\n    <number>\n    > r = base.random.randn()\n    <number>\n\n    // Set the state:\n    > base.random.randn.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.randn()\n    <number>\n    > r = base.random.randn()\n    <number>\n\n\nbase.random.randn.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.randn.stateLength;\n\n\nbase.random.randn.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.randn.byteLength;\n\n\nbase.random.randn.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.randn.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.iterators.randn, random.streams.randn, base.random.improvedZiggurat, base.random.randu\n","base.random.randn.factory":"\nbase.random.randn.factory( [options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a standard normal distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of the underlying pseudorandom number generator (PRNG) that samples\n        from a standard normal distribution. The following PRNGs are supported:\n\n        - improved-ziggurat: improved ziggurat method.\n        - box-muller: Box-Muller transform.\n\n        Default: 'improved-ziggurat'.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underlying PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.randn.factory();\n    > var r = rand();\n    > r = rand();\n\n    // Specify alternative PRNG:\n    > var rand = base.random.randn.factory({ 'name': 'box-muller' });\n    > r = rand();\n    > r = rand();","base.random.randn.NAME":"\nbase.random.randn.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.randn.NAME\n    'randn'","base.random.randn.PRNG":"\nbase.random.randn.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.randn.PRNG;","base.random.randn.seed":"\nbase.random.randn.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.randn.seed;","base.random.randn.seedLength":"\nbase.random.randn.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.randn.seedLength;","base.random.randn.state":"\nbase.random.randn.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.randn()\n    <number>\n    > r = base.random.randn()\n    <number>\n    > r = base.random.randn()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.randn.state;\n\n    > r = base.random.randn()\n    <number>\n    > r = base.random.randn()\n    <number>\n\n    // Set the state:\n    > base.random.randn.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.randn()\n    <number>\n    > r = base.random.randn()\n    <number>","base.random.randn.stateLength":"\nbase.random.randn.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.randn.stateLength;","base.random.randn.byteLength":"\nbase.random.randn.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.randn.byteLength;","base.random.randn.toJSON":"\nbase.random.randn.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.randn.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.iterators.randn, random.streams.randn, base.random.improvedZiggurat, base.random.randu","base.random.randu":"\nbase.random.randu()\n    Returns a pseudorandom number drawn from a uniform distribution.\n\n    The default underlying pseudorandom number generator (PRNG) *may* change in\n    the future. If exact reproducibility is required, either use the `factory`\n    method to explicitly specify a PRNG via the `name` option or use an\n    underlying PRNG directly.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number on the interval `[0,1)`.\n\n    Examples\n    --------\n    > var r = base.random.randu();\n\n\nbase.random.randu.factory( [options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a uniform distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of the underlying pseudorandom number generator (PRNG). The\n        following PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underlying PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.randu.factory();\n    > var r = rand();\n    > r = rand();\n\n    // Specify alternative PRNG:\n    > var rand = base.random.randu.factory({ 'name': 'minstd' });\n    > r = rand();\n    > r = rand();\n\n\nbase.random.randu.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.randu.NAME\n    'randu'\n\n\nbase.random.randu.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.randu.PRNG;\n\n\nbase.random.randu.MIN\n    Minimum possible value (specific to underlying PRNG).\n\n    Examples\n    --------\n    > var v = base.random.randu.MIN;\n\n\nbase.random.randu.MAX\n    Maximum possible value (specific to underlying PRNG).\n\n    Examples\n    --------\n    > var v = base.random.randu.MAX;\n\n\nbase.random.randu.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.randu.seed;\n\n\nbase.random.randu.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.randu.seedLength;\n\n\nbase.random.randu.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.randu()\n    <number>\n    > r = base.random.randu()\n    <number>\n    > r = base.random.randu()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.randu.state;\n\n    > r = base.random.randu()\n    <number>\n    > r = base.random.randu()\n    <number>\n\n    // Set the state:\n    > base.random.randu.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.randu()\n    <number>\n    > r = base.random.randu()\n    <number>\n\n\nbase.random.randu.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.randu.stateLength;\n\n\nbase.random.randu.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.randu.byteLength;\n\n\nbase.random.randu.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.randu.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.randu, random.iterators.randu, random.streams.randu, base.random.discreteUniform, base.random.randn\n","base.random.randu.factory":"\nbase.random.randu.factory( [options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a uniform distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of the underlying pseudorandom number generator (PRNG). The\n        following PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underlying PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.randu.factory();\n    > var r = rand();\n    > r = rand();\n\n    // Specify alternative PRNG:\n    > var rand = base.random.randu.factory({ 'name': 'minstd' });\n    > r = rand();\n    > r = rand();","base.random.randu.NAME":"\nbase.random.randu.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.randu.NAME\n    'randu'","base.random.randu.PRNG":"\nbase.random.randu.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.randu.PRNG;","base.random.randu.MIN":"\nbase.random.randu.MIN\n    Minimum possible value (specific to underlying PRNG).\n\n    Examples\n    --------\n    > var v = base.random.randu.MIN;","base.random.randu.MAX":"\nbase.random.randu.MAX\n    Maximum possible value (specific to underlying PRNG).\n\n    Examples\n    --------\n    > var v = base.random.randu.MAX;","base.random.randu.seed":"\nbase.random.randu.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.randu.seed;","base.random.randu.seedLength":"\nbase.random.randu.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.randu.seedLength;","base.random.randu.state":"\nbase.random.randu.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.randu()\n    <number>\n    > r = base.random.randu()\n    <number>\n    > r = base.random.randu()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.randu.state;\n\n    > r = base.random.randu()\n    <number>\n    > r = base.random.randu()\n    <number>\n\n    // Set the state:\n    > base.random.randu.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.randu()\n    <number>\n    > r = base.random.randu()\n    <number>","base.random.randu.stateLength":"\nbase.random.randu.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.randu.stateLength;","base.random.randu.byteLength":"\nbase.random.randu.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.randu.byteLength;","base.random.randu.toJSON":"\nbase.random.randu.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.randu.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.randu, random.iterators.randu, random.streams.randu, base.random.discreteUniform, base.random.randn","base.random.rayleigh":"\nbase.random.rayleigh( σ )\n    Returns a pseudorandom number drawn from a Rayleigh distribution.\n\n    If `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.rayleigh( 2.5 );\n\n\nbase.random.rayleigh.factory( [σ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Rayleigh distribution.\n\n    If provided `σ`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `σ`, the returned PRNG requires that `σ` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    σ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.rayleigh.factory();\n    > var r = rand( 5.0 );\n    > r = rand( 10.0 );\n\n    // Provide `σ`:\n    > rand = base.random.rayleigh.factory( 5.0 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.rayleigh.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.rayleigh.NAME\n    'rayleigh'\n\n\nbase.random.rayleigh.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.rayleigh.PRNG;\n\n\nbase.random.rayleigh.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.rayleigh.seed;\n\n\nbase.random.rayleigh.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.rayleigh.seedLength;\n\n\nbase.random.rayleigh.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.rayleigh( 5.0 )\n    <number>\n    > r = base.random.rayleigh( 5.0 )\n    <number>\n    > r = base.random.rayleigh( 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.rayleigh.state\n    <Uint32Array>\n\n    > r = base.random.rayleigh( 5.0 )\n    <number>\n    > r = base.random.rayleigh( 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.rayleigh.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.rayleigh( 5.0 )\n    <number>\n    > r = base.random.rayleigh( 5.0 )\n    <number>\n\n\nbase.random.rayleigh.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.rayleigh.stateLength;\n\n\nbase.random.rayleigh.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.rayleigh.byteLength;\n\n\nbase.random.rayleigh.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.rayleigh.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.rayleigh, random.iterators.rayleigh, random.streams.rayleigh\n","base.random.rayleigh.factory":"\nbase.random.rayleigh.factory( [σ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Rayleigh distribution.\n\n    If provided `σ`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `σ`, the returned PRNG requires that `σ` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    σ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.rayleigh.factory();\n    > var r = rand( 5.0 );\n    > r = rand( 10.0 );\n\n    // Provide `σ`:\n    > rand = base.random.rayleigh.factory( 5.0 );\n    > r = rand();\n    > r = rand();","base.random.rayleigh.NAME":"\nbase.random.rayleigh.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.rayleigh.NAME\n    'rayleigh'","base.random.rayleigh.PRNG":"\nbase.random.rayleigh.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.rayleigh.PRNG;","base.random.rayleigh.seed":"\nbase.random.rayleigh.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.rayleigh.seed;","base.random.rayleigh.seedLength":"\nbase.random.rayleigh.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.rayleigh.seedLength;","base.random.rayleigh.state":"\nbase.random.rayleigh.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.rayleigh( 5.0 )\n    <number>\n    > r = base.random.rayleigh( 5.0 )\n    <number>\n    > r = base.random.rayleigh( 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.rayleigh.state\n    <Uint32Array>\n\n    > r = base.random.rayleigh( 5.0 )\n    <number>\n    > r = base.random.rayleigh( 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.rayleigh.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.rayleigh( 5.0 )\n    <number>\n    > r = base.random.rayleigh( 5.0 )\n    <number>","base.random.rayleigh.stateLength":"\nbase.random.rayleigh.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.rayleigh.stateLength;","base.random.rayleigh.byteLength":"\nbase.random.rayleigh.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.rayleigh.byteLength;","base.random.rayleigh.toJSON":"\nbase.random.rayleigh.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.rayleigh.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.rayleigh, random.iterators.rayleigh, random.streams.rayleigh","base.random.t":"\nbase.random.t( v )\n    Returns a pseudorandom number drawn from a Student's t distribution.\n\n    If `v <= 0` or `v` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.t( 2.0 );\n\n\nbase.random.t.factory( [v, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Student's t distribution.\n\n    If provided `v`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `v`, the returned PRNG requires that `v` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    v: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.t.factory();\n    > var r = rand( 5.0 );\n    > r = rand( 3.14 );\n\n    // Provide `v`:\n    > rand = base.random.t.factory( 5.0 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.t.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.t.NAME\n    't'\n\n\nbase.random.t.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.t.PRNG;\n\n\nbase.random.t.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.t.seed;\n\n\nbase.random.t.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.t.seedLength;\n\n\nbase.random.t.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.t( 10.0 )\n    <number>\n    > r = base.random.t( 10.0 )\n    <number>\n    > r = base.random.t( 10.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.t.state\n    <Uint32Array>\n\n    > r = base.random.t( 10.0 )\n    <number>\n    > r = base.random.t( 10.0 )\n    <number>\n\n    // Set the state:\n    > base.random.t.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.t( 10.0 )\n    <number>\n    > r = base.random.t( 10.0 )\n    <number>\n\n\nbase.random.t.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.t.stateLength;\n\n\nbase.random.t.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.t.byteLength;\n\n\nbase.random.t.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.t.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.t, random.iterators.t, random.streams.t\n","base.random.t.factory":"\nbase.random.t.factory( [v, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Student's t distribution.\n\n    If provided `v`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `v`, the returned PRNG requires that `v` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    v: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.t.factory();\n    > var r = rand( 5.0 );\n    > r = rand( 3.14 );\n\n    // Provide `v`:\n    > rand = base.random.t.factory( 5.0 );\n    > r = rand();\n    > r = rand();","base.random.t.NAME":"\nbase.random.t.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.t.NAME\n    't'","base.random.t.PRNG":"\nbase.random.t.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.t.PRNG;","base.random.t.seed":"\nbase.random.t.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.t.seed;","base.random.t.seedLength":"\nbase.random.t.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.t.seedLength;","base.random.t.state":"\nbase.random.t.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.t( 10.0 )\n    <number>\n    > r = base.random.t( 10.0 )\n    <number>\n    > r = base.random.t( 10.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.t.state\n    <Uint32Array>\n\n    > r = base.random.t( 10.0 )\n    <number>\n    > r = base.random.t( 10.0 )\n    <number>\n\n    // Set the state:\n    > base.random.t.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.t( 10.0 )\n    <number>\n    > r = base.random.t( 10.0 )\n    <number>","base.random.t.stateLength":"\nbase.random.t.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.t.stateLength;","base.random.t.byteLength":"\nbase.random.t.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.t.byteLength;","base.random.t.toJSON":"\nbase.random.t.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.t.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.t, random.iterators.t, random.streams.t","base.random.triangular":"\nbase.random.triangular( a, b, c )\n    Returns a pseudorandom number drawn from a triangular distribution.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.triangular( 2.0, 5.0, 3.33 );\n\n\nbase.random.triangular.factory( [a, b, c, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a triangular distribution.\n\n    If provided `a`, `b`, and `c`, the returned PRNG returns random variates\n    drawn from the specified distribution.\n\n    If not provided `a`, `b`, and `c`, the returned PRNG requires that `a`, `b`,\n    and `c` be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    c: number (optional)\n        Mode.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.triangular.factory();\n    > var r = rand( 0.0, 1.0, 0.5 );\n    > r = rand( -2.0, 2.0, 1.0 );\n\n    // Provide `a`, `b`, and `c`:\n    > rand = base.random.triangular.factory( 0.0, 1.0, 0.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.triangular.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.triangular.NAME\n    'triangular'\n\n\nbase.random.triangular.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.triangular.PRNG;\n\n\nbase.random.triangular.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.triangular.seed;\n\n\nbase.random.triangular.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.triangular.seedLength;\n\n\nbase.random.triangular.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.triangular.state\n    <Uint32Array>\n\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n\n    // Set the state:\n    > base.random.triangular.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n\n\nbase.random.triangular.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.triangular.stateLength;\n\n\nbase.random.triangular.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.triangular.byteLength;\n\n\nbase.random.triangular.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.triangular.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.triangular, random.iterators.triangular, random.streams.triangular\n","base.random.triangular.factory":"\nbase.random.triangular.factory( [a, b, c, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a triangular distribution.\n\n    If provided `a`, `b`, and `c`, the returned PRNG returns random variates\n    drawn from the specified distribution.\n\n    If not provided `a`, `b`, and `c`, the returned PRNG requires that `a`, `b`,\n    and `c` be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    c: number (optional)\n        Mode.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.triangular.factory();\n    > var r = rand( 0.0, 1.0, 0.5 );\n    > r = rand( -2.0, 2.0, 1.0 );\n\n    // Provide `a`, `b`, and `c`:\n    > rand = base.random.triangular.factory( 0.0, 1.0, 0.5 );\n    > r = rand();\n    > r = rand();","base.random.triangular.NAME":"\nbase.random.triangular.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.triangular.NAME\n    'triangular'","base.random.triangular.PRNG":"\nbase.random.triangular.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.triangular.PRNG;","base.random.triangular.seed":"\nbase.random.triangular.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.triangular.seed;","base.random.triangular.seedLength":"\nbase.random.triangular.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.triangular.seedLength;","base.random.triangular.state":"\nbase.random.triangular.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.triangular.state\n    <Uint32Array>\n\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n\n    // Set the state:\n    > base.random.triangular.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>","base.random.triangular.stateLength":"\nbase.random.triangular.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.triangular.stateLength;","base.random.triangular.byteLength":"\nbase.random.triangular.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.triangular.byteLength;","base.random.triangular.toJSON":"\nbase.random.triangular.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.triangular.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.triangular, random.iterators.triangular, random.streams.triangular","base.random.uniform":"\nbase.random.uniform( a, b )\n    Returns a pseudorandom number drawn from a continuous uniform distribution.\n\n    If `a >= b`, the function returns `NaN`.\n\n    If `a` or `b` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support (inclusive).\n\n    b: number\n        Maximum support (exclusive).\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.uniform( 2.0, 5.0 );\n\n\nbase.random.uniform.factory( [a, b, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a continuous uniform distribution.\n\n    If provided `a` and `b`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `a` and `b`, the returned PRNG requires that both `a` and\n    `b` be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support (inclusive).\n\n    b: number (optional)\n        Maximum support (exclusive).\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.uniform.factory();\n    > var r = rand( 0.0, 1.0 );\n    > r = rand( -2.0, 2.0 );\n\n    // Provide `a` and `b`:\n    > rand = base.random.uniform.factory( 0.0, 1.0 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.uniform.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.uniform.NAME\n    'uniform'\n\n\nbase.random.uniform.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.uniform.PRNG;\n\n\nbase.random.uniform.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.uniform.seed;\n\n\nbase.random.uniform.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.uniform.seedLength;\n\n\nbase.random.uniform.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.uniform( 2.0, 5.0 )\n    <number>\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.uniform.state\n    <Uint32Array>\n\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.uniform.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>\n\n\nbase.random.uniform.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.uniform.stateLength;\n\n\nbase.random.uniform.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.uniform.byteLength;\n\n\nbase.random.uniform.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.uniform.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.uniform, random.iterators.uniform, random.streams.uniform, base.random.discreteUniform, base.random.randu\n","base.random.uniform.factory":"\nbase.random.uniform.factory( [a, b, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a continuous uniform distribution.\n\n    If provided `a` and `b`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `a` and `b`, the returned PRNG requires that both `a` and\n    `b` be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support (inclusive).\n\n    b: number (optional)\n        Maximum support (exclusive).\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.uniform.factory();\n    > var r = rand( 0.0, 1.0 );\n    > r = rand( -2.0, 2.0 );\n\n    // Provide `a` and `b`:\n    > rand = base.random.uniform.factory( 0.0, 1.0 );\n    > r = rand();\n    > r = rand();","base.random.uniform.NAME":"\nbase.random.uniform.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.uniform.NAME\n    'uniform'","base.random.uniform.PRNG":"\nbase.random.uniform.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.uniform.PRNG;","base.random.uniform.seed":"\nbase.random.uniform.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.uniform.seed;","base.random.uniform.seedLength":"\nbase.random.uniform.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.uniform.seedLength;","base.random.uniform.state":"\nbase.random.uniform.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.uniform( 2.0, 5.0 )\n    <number>\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.uniform.state\n    <Uint32Array>\n\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.uniform.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>","base.random.uniform.stateLength":"\nbase.random.uniform.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.uniform.stateLength;","base.random.uniform.byteLength":"\nbase.random.uniform.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.uniform.byteLength;","base.random.uniform.toJSON":"\nbase.random.uniform.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.uniform.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.uniform, random.iterators.uniform, random.streams.uniform, base.random.discreteUniform, base.random.randu","base.random.weibull":"\nbase.random.weibull( k, λ )\n    Returns a pseudorandom number drawn from a Weibull distribution.\n\n    If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n    If either `λ` or `k` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Scale parameter.\n\n    λ: number\n        Shape parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.weibull( 2.0, 5.0 );\n\n\nbase.random.weibull.factory( [k, λ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Weibull distribution.\n\n    If provided `k` and `λ`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `k` and `λ`, the returned PRNG requires that both\n    `k` and `λ` be provided at each invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Scale parameter.\n\n    λ: number (optional)\n        Shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.weibull.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `λ` and `k`:\n    > rand = base.random.weibull.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.weibull.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.weibull.NAME\n    'weibull'\n\n\nbase.random.weibull.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.weibull.PRNG;\n\n\nbase.random.weibull.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.weibull.seed;\n\n\nbase.random.weibull.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.weibull.seedLength;\n\n\nbase.random.weibull.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.weibull( 2.0, 5.0 )\n    <number>\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.weibull.state\n    <Uint32Array>\n\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.weibull.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>\n\n\nbase.random.weibull.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.weibull.stateLength;\n\n\nbase.random.weibull.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.weibull.byteLength;\n\n\nbase.random.weibull.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.weibull.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.weibull, random.iterators.weibull, random.streams.weibull\n","base.random.weibull.factory":"\nbase.random.weibull.factory( [k, λ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Weibull distribution.\n\n    If provided `k` and `λ`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `k` and `λ`, the returned PRNG requires that both\n    `k` and `λ` be provided at each invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Scale parameter.\n\n    λ: number (optional)\n        Shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.weibull.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `λ` and `k`:\n    > rand = base.random.weibull.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.weibull.NAME":"\nbase.random.weibull.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.weibull.NAME\n    'weibull'","base.random.weibull.PRNG":"\nbase.random.weibull.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.weibull.PRNG;","base.random.weibull.seed":"\nbase.random.weibull.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.weibull.seed;","base.random.weibull.seedLength":"\nbase.random.weibull.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.weibull.seedLength;","base.random.weibull.state":"\nbase.random.weibull.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.weibull( 2.0, 5.0 )\n    <number>\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.weibull.state\n    <Uint32Array>\n\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.weibull.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>","base.random.weibull.stateLength":"\nbase.random.weibull.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.weibull.stateLength;","base.random.weibull.byteLength":"\nbase.random.weibull.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.weibull.byteLength;","base.random.weibull.toJSON":"\nbase.random.weibull.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.weibull.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.weibull, random.iterators.weibull, random.streams.weibull","base.rcbrt":"\nbase.rcbrt( x )\n    Computes the reciprocal cube root of a double-precision floating-point\n    number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Reciprocal cube root.\n\n    Examples\n    --------\n    > var y = base.rcbrt( 8.0 )\n    0.5\n    > y = base.rcbrt( 1000.0 )\n    0.1\n    > y = base.rcbrt( 0.0 )\n    Infinity\n    > y = base.rcbrt( PINF )\n    0.0\n    > y = base.rcbrt( -8.0 )\n    -0.5\n    > y = base.rcbrt( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cbrt\n","base.rcbrtf":"\nbase.rcbrtf( x )\n    Computes the reciprocal cube root of a single-precision floating-point\n    number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Reciprocal cube root.\n\n    Examples\n    --------\n    > var y = base.rcbrtf( 8.0 )\n    0.5\n    > y = base.rcbrtf( 1000.0 )\n    ~0.1\n    > y = base.rcbrtf( 0.0 )\n    Infinity\n    > y = base.rcbrtf( PINF )\n    0.0\n    > y = base.rcbrtf( -8.0 )\n    -0.5\n    > y = base.rcbrtf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.rcbrt, base.cbrtf\n","base.reldiff":"\nbase.reldiff( x, y[, scale] )\n    Computes the relative difference of two real numbers.\n\n    By default, the function scales the absolute difference by dividing the\n    absolute difference by the maximum absolute value of `x` and `y`. To scale\n    by a different function, specify a scale function name.\n\n    The following `scale` functions are supported:\n\n    - 'max-abs': maximum absolute value of `x` and `y` (default).\n    - 'max': maximum value of `x` and `y`.\n    - 'min-abs': minimum absolute value of `x` and `y`.\n    - 'min': minimum value of `x` and `y`.\n    - 'mean-abs': arithmetic mean of the absolute values of `x` and `y`.\n    - 'mean': arithmetic mean of `x` and `y`.\n    - 'x': `x` (*noncommutative*).\n    - 'y': `y` (*noncommutative*).\n\n    To use a custom scale function, provide a function which accepts two numeric\n    arguments `x` and `y`.\n\n    If the absolute difference of `x` and `y` is `0`, the relative difference is\n    always `0`.\n\n    If `|x| = |y| = infinity`, the function returns `NaN`.\n\n    If `|x| = |-y| = infinity`, the relative difference is `+infinity`.\n\n    If a `scale` function returns `0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    scale: string|Function (optional)\n        Scale function. Default: `'max-abs'`.\n\n    Returns\n    -------\n    out: number\n        Relative difference.\n\n    Examples\n    --------\n    > var d = base.reldiff( 2.0, 5.0 )\n    0.6\n    > d = base.reldiff( -1.0, 3.14 )\n    ~1.318\n    > d = base.reldiff( -2.0, 5.0, 'max-abs' )\n    1.4\n    > d = base.reldiff( -2.0, 5.0, 'max' )\n    1.4\n    > d = base.reldiff( -2.0, 5.0, 'min-abs' )\n    3.5\n    > d = base.reldiff( -2.0, 5.0, 'min' )\n    3.5\n    > d = base.reldiff( -2.0, 5.0, 'mean-abs' )\n    2.0\n    > d = base.reldiff( -2.0, 5.0, 'mean' )\n    ~4.667\n    > d = base.reldiff( -2.0, 5.0, 'x' )\n    3.5\n    > d = base.reldiff( 5.0, -2.0, 'x' )\n    1.4\n    > d = base.reldiff( -2.0, 5.0, 'y' )\n    1.4\n    > d = base.reldiff( 5.0, -2.0, 'y' )\n    3.5\n\n    // Custom scale function:\n    > function scale( x, y ) {\n    ...     var s;\n    ...\n    ...     x = base.abs( x );\n    ...     y = base.abs( y );\n    ...\n    ...     // Maximum absolute value:\n    ...     s = (x < y ) ? y : x;\n    ...\n    ...     // Scale in units of epsilon:\n    ...     return s * EPS;\n    ... };\n    > d = base.reldiff( 12.15, 12.149999999999999, scale )\n    ~0.658\n\n    See Also\n    --------\n    base.absdiff, base.epsdiff\n","base.removeFirst":"\nbase.removeFirst( str, n )\n    Removes the first `n` UTF-16 code units of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of UTF-16 code units to remove.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.removeFirst( 'beep', 1 )\n    'eep'\n    > out = base.removeFirst( 'Boop', 1 )\n    'oop'\n    > out = base.removeFirst( 'foo bar', 5 )\n    'ar'\n\n    See Also\n    --------\n    base.removeFirstCodePoint, base.removeFirstGraphemeCluster, base.removeLast\n","base.removeFirstCodePoint":"\nbase.removeFirstCodePoint( str, n )\n    Removes the first `n` Unicode code points of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of Unicode code points to remove.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.removeFirstCodePoint( 'beep', 1 )\n    'eep'\n    > out = base.removeFirstCodePoint( 'Boop', 1 )\n    'oop'\n    > out = base.removeFirstCodePoint( 'foo bar', 5 )\n    'ar'\n\n    See Also\n    --------\n    base.removeLastCodePoint, base.removeFirstGraphemeCluster, base.removeFirst\n","base.removeFirstGraphemeCluster":"\nbase.removeFirstGraphemeCluster( str, n )\n    Removes the first `n` grapheme clusters (i.e., user-perceived characters)\n    of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of grapheme clusters to remove.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.removeFirstGraphemeCluster( 'beep', 1 )\n    'eep'\n    > out = base.removeFirstGraphemeCluster( 'Boop', 1 )\n    'oop'\n    > out = base.removeFirstGraphemeCluster( 'foo bar', 5 )\n    'ar'\n\n    See Also\n    --------\n    base.removeFirstCodePoint, base.removeLastGraphemeCluster, base.removeFirst\n","base.removeLast":"\nbase.removeLast( str, n )\n    Removes the last `n` UTF-16 code units of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of UTF-16 code units to remove.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.removeLast( 'beep', 1 )\n    'bee'\n    > out = base.removeLast( 'Boop', 1 )\n    'Boo'\n    > out = base.removeLast( 'foo bar', 5 )\n    'fo'\n\n    See Also\n    --------\n    base.removeLastCodePoint, base.removeLastGraphemeCluster, base.removeFirst\n","base.removeLastCodePoint":"\nbase.removeLastCodePoint( str, n )\n    Removes the last `n` Unicode code points of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of Unicode code points to remove.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.removeLastCodePoint( 'beep', 1 )\n    'bee'\n    > out = base.removeLastCodePoint( 'Boop', 1 )\n    'Boo'\n    > out = base.removeLastCodePoint( 'foo bar', 5 )\n    'fo'\n\n    See Also\n    --------\n    base.removeFirstCodePoint, base.removeLastGraphemeCluster, base.removeLast\n","base.removeLastGraphemeCluster":"\nbase.removeLastGraphemeCluster( str, n )\n    Removes the last `n` grapheme clusters (i.e., user-perceived characters)\n    of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of grapheme clusters to remove.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.removeLastGraphemeCluster( 'beep', 1 )\n    'bee'\n    > out = base.removeLastGraphemeCluster( 'Boop', 1 )\n    'Boo'\n    > out = base.removeLastGraphemeCluster( 'foo bar', 5 )\n    'fo'\n\n    See Also\n    --------\n    base.removeFirstCodePoint, base.removeLastCodePoint, base.removeLast\n","base.rempio2":"\nbase.rempio2( x, y )\n    Computes `x - nπ/2 = r`.\n\n    The function returns `n` and stores the remainder `r` as the two numbers\n    `y[0]` and `y[1]`, such that `y[0] + y[1] = r`.\n\n    For input values larger than `2^20 * π/2` in magnitude, the function only\n    returns the last three binary digits of `n` and not the full result.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    y: Array|TypedArray|Object\n        Remainder elements.\n\n    Returns\n    -------\n    n: integer\n        Factor of `π/2`.\n\n    Examples\n    --------\n    > var y = [ 0.0, 0.0 ];\n    > var n = base.rempio2( 128.0, y )\n    81\n    > var y1 = y[ 0 ]\n    ~0.765\n    > var y2 = y[ 1 ]\n    ~3.618e-17\n\n\n","base.repeat":"\nbase.repeat( str, n )\n    Repeats a string `n` times and returns the concatenated result.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of repetitions.\n\n    Returns\n    -------\n    out: string\n        Repeated string.\n\n    Examples\n    --------\n    > var out = base.repeat( 'a', 5 )\n    'aaaaa'\n    > out = base.repeat( '', 100 )\n    ''\n    > out = base.repeat( 'beep', 0 )\n    ''\n\n","base.replace":"\nbase.replace( str, search, newval )\n    Replaces search occurrences with a replacement string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: RegExp\n        Search expression.\n\n    newval: string|Function\n        Replacement value or function.\n\n    Returns\n    -------\n    out: string\n        String containing replacement(s).\n\n    Examples\n    --------\n    > function replacer( match, p1 ) { return '/'+p1+'/'; };\n    > var str = 'Oranges and lemons';\n    > var out = base.replace( str, /([^\\s]+)/gi, replacer )\n    '/Oranges/ /and/ /lemons/'\n\n    // Replace only first match:\n    > out = base.replace( 'beep', /e/, 'o' )\n    'boep'\n\n    See Also\n    --------\n    base.replaceAfter, base.replaceBefore, base.replaceAfterLast, base.replaceBeforeLast\n","base.replaceAfter":"\nbase.replaceAfter( str, search, replacement, fromIndex )\n    Replaces the substring after the first occurrence of a specified search\n    string.\n\n    If unable to find a search string, the function returns the input string\n    unchanged.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search string.\n\n    replacement: string\n        Replacement string.\n\n    fromIndex: integer\n        Starting index (inclusive). If less than zero, the starting index is\n        resolved relative to the last string character, with the last string\n        character corresponding to `fromIndex = -1`.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.replaceAfter( 'beep boop', ' ', 'foo', 0 )\n    'beep foo'\n    > out = base.replaceAfter( 'beep boop', 'o', 'foo', 0 )\n    'beep bofoo'\n    > out = base.replaceAfter( 'Hello World!', 'o', 'foo', 5 )\n    'Hello Wofoo'\n    > out = base.replaceAfter( 'beep boop beep baz', 'beep', 'foo', 5 )\n    'beep boop beepfoo'\n\n    See Also\n    --------\n    base.replaceAfterLast, base.replaceBefore, base.replaceBeforeLast\n","base.replaceAfterLast":"\nbase.replaceAfterLast( str, search, replacement, fromIndex )\n    Replaces the substring after the last occurrence of a specified search\n    string.\n\n    If unable to find a search string, the function returns the input string\n    unchanged.\n\n    The function scans an input string from the starting index to the beginning\n    of the string (i.e., backward).\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search string.\n\n    replacement: string\n        Replacement string.\n\n    fromIndex: integer\n        Starting index (inclusive). If less than zero, the starting index is\n        resolved relative to the last string character, with the last string\n        character corresponding to `fromIndex = -1`.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var str = 'beep boop';\n    > var out = base.replaceAfterLast( str, ' ', 'foo', str.length )\n    'beep foo'\n    > out = base.replaceAfterLast( str, 'o', 'foo', str.length )\n    'beep boofoo'\n    > out = base.replaceAfterLast( 'Hello World!', 'o', 'foo', 5 )\n    'Hellofoo'\n\n    See Also\n    --------\n    base.replaceAfter, base.replaceBeforeLast, base.replaceBefore\n","base.replaceBefore":"\nbase.replaceBefore( str, search, replacement, fromIndex )\n    Replaces the substring before the first occurrence of a specified search\n    string.\n\n    If unable to find a search string, the function returns the input string\n    unchanged.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search string.\n\n    replacement: string\n        Replacement string.\n\n    fromIndex: integer\n        Starting index (inclusive). If less than zero, the starting index is\n        resolved relative to the last string character, with the last string\n        character corresponding to `fromIndex = -1`.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.replaceBefore( 'beep boop', ' ', 'foo', 0 )\n    'foo boop'\n    > out = base.replaceBefore( 'beep boop', 'o', 'foo', 0 )\n    'foooop'\n\n    See Also\n    --------\n    base.replaceAfter, base.replaceBeforeLast, base.replaceAfterLast\n","base.replaceBeforeLast":"\nbase.replaceBeforeLast( str, search, replacement, fromIndex )\n    Replaces the substring before the last occurrence of a specified search\n    string.\n\n    If unable to find a search string, the function returns the input string\n    unchanged.\n\n    The function scans an input string from the starting index to the beginning\n    of the string (i.e., backward).\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search string.\n\n    replacement: string\n        Replacement string.\n\n    fromIndex: integer\n        Starting index (inclusive). If less than zero, the starting index is\n        resolved relative to the last string character, with the last string\n        character corresponding to `fromIndex = -1`.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var str = 'beep boop';\n    > var out = base.replaceBeforeLast( str, ' ', 'foo', str.length )\n    'foo boop'\n    > out = base.replaceBeforeLast( str, 'o', 'foo', str.length )\n    'fooop'\n    > out = base.replaceBeforeLast( 'Hello World!', 'o', 'foo', 5 )\n    'fooo World!'\n\n    See Also\n    --------\n    base.replaceAfterLast, base.replaceAfter, base.replaceBefore\n","base.reverse":"\nbase.reverse( str )\n    Reverses the UTF-16 code units of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.reverse( 'beep' )\n    'peeb'\n    > out = base.reverse( 'Boop' )\n    'pooB'\n    > out = base.reverse( 'foo bar' )\n    'rab oof'\n\n    See Also\n    --------\n    base.reverseCodePoints, base.reverseGraphemeClusters\n","base.reverseCodePoints":"\nbase.reverseCodePoints( str )\n    Reverses the Unicode code points of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.reverseCodePoints( 'beep' )\n    'peeb'\n    > out = base.reverseCodePoints( 'Boop' )\n    'pooB'\n    > out = base.reverseCodePoints( 'foo bar' )\n    'rab oof'\n\n    See Also\n    --------\n    base.reverseGraphemeClusters, base.reverse\n","base.reverseGraphemeClusters":"\nbase.reverseGraphemeClusters( str )\n    Reverses the grapheme clusters (i.e., user-perceived characters) of a\n    string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.reverseGraphemeClusters( 'beep' )\n    'peeb'\n    > out = base.reverseGraphemeClusters( 'Boop' )\n    'pooB'\n    > out = base.reverseGraphemeClusters( 'foo bar' )\n    'rab oof'\n\n    See Also\n    --------\n    base.reverseCodePoints, base.reverse\n","base.rightPad":"\nbase.rightPad( str, len, pad )\n    Right pads a string such that the padded string has a length of at least\n    `len`.\n\n    An output string is not guaranteed to have a length of exactly `len`, but to\n    have a length of at least `len`. To generate a padded string having a length\n    equal to `len`, post-process a padded string by trimming off excess\n    characters.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    len: integer\n        Minimum string length.\n\n    pad: string\n        String used to pad.\n\n    Returns\n    -------\n    out: string\n        Padded string.\n\n    Examples\n    --------\n    > var out = base.rightPad( 'a', 5, ' ' )\n    'a    '\n    > out = base.rightPad( 'beep', 10, 'b' )\n    'beepbbbbbb'\n    > out = base.rightPad( 'boop', 12, 'beep' )\n    'boopbeepbeep'\n\n    See Also\n    --------\n    base.leftPad\n","base.rightTrim":"\nbase.rightTrim( str )\n    Trims whitespace from the end of a string.\n\n    \"Whitespace\" is defined as the following characters:\n\n    - \\f\n    - \\n\n    - \\r\n    - \\t\n    - \\v\n    - \\u0020\n    - \\u00a0\n    - \\u1680\n    - \\u2000-\\u200a\n    - \\u2028\n    - \\u2029\n    - \\u202f\n    - \\u205f\n    - \\u3000\n    - \\ufeff\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Trimmed string.\n\n    Examples\n    --------\n    > var out = base.rightTrim( ' \\t\\t\\n  Beep \\r\\n\\t  ' )\n    ' \\t\\t\\n  Beep'\n\n    See Also\n    --------\n    base.leftTrim\n","base.risingFactorial":"\nbase.risingFactorial( x, n )\n    Computes the rising factorial of `x` and `n`.\n\n    If provided a non-integer for `n`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        First function parameter.\n\n    n: integer\n        Second function parameter.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var v = base.risingFactorial( 0.9, 5 )\n    ~94.766\n    > v = base.risingFactorial( -9.0, 3 )\n    -504.0\n    > v = base.risingFactorial( 0.0, 2 )\n    0.0\n    > v = base.risingFactorial( 3.0, -2 )\n    0.5\n\n    See Also\n    --------\n    base.fallingFactorial\n","base.rotl32":"\nbase.rotl32( x, shift )\n    Performs a bitwise rotation to the left.\n\n    If `shift = 0`, the function returns `x`.\n\n    If `shift >= 32`, the function only considers the five least significant\n    bits of `shift` (i.e., `shift % 32`).\n\n    Parameters\n    ----------\n    x: integer\n        Unsigned 32-bit integer.\n\n    shift: integer\n        Number of bits to shift.\n\n    Returns\n    -------\n    out: integer\n        Unsigned 32-bit integer.\n\n    Examples\n    --------\n    > var x = 2147483649;\n    > var bStr = base.toBinaryStringUint32( x )\n    '10000000000000000000000000000001'\n    > var y = base.rotl32( x, 10 )\n    1536\n    > bstr = base.toBinaryStringUint32( y )\n    '00000000000000000000011000000000'\n\n    See Also\n    --------\n    base.rotr32\n","base.rotr32":"\nbase.rotr32( x, shift )\n    Performs a bitwise rotation to the right.\n\n    If `shift = 0`, the function returns `x`.\n\n    If `shift >= 32`, the function only considers the five least significant\n    bits of `shift` (i.e., `shift % 32`).\n\n    Parameters\n    ----------\n    x: integer\n        Unsigned 32-bit integer.\n\n    shift: integer\n        Number of bits to shift.\n\n    Returns\n    -------\n    out: integer\n        Unsigned 32-bit integer.\n\n    Examples\n    --------\n    > var x = 1;\n    > var bStr = base.toBinaryStringUint32( x )\n    '00000000000000000000000000000001'\n    > var y = base.rotr32( x, 10 )\n    4194304\n    > bstr = base.toBinaryStringUint32( y )\n    '00000000010000000000000000000000'\n\n    See Also\n    --------\n    base.rotl32\n","base.round":"\nbase.round( x )\n    Rounds a numeric value to the nearest integer.\n\n    Ties are rounded toward positive infinity.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.round( 3.14 )\n    3.0\n    > y = base.round( -4.2 )\n    -4.0\n    > y = base.round( -4.6 )\n    -5.0\n    > y = base.round( 9.5 )\n    10.0\n    > y = base.round( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceil, base.floor, base.roundn, base.trunc\n","base.round2":"\nbase.round2( x )\n    Rounds a numeric value to the nearest power of two on a linear scale.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.round2( 3.14 )\n    4.0\n    > y = base.round2( -4.2 )\n    -4.0\n    > y = base.round2( -4.6 )\n    -4.0\n    > y = base.round2( 9.5 )\n    8.0\n    > y = base.round2( 13.0 )\n    16.0\n    > y = base.round2( -13.0 )\n    -16.0\n    > y = base.round2( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceil2, base.floor2, base.round, base.round10\n","base.round10":"\nbase.round10( x )\n    Rounds a numeric value to the nearest power of ten on a linear scale.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.round10( 3.14 )\n    1.0\n    > y = base.round10( -4.2 )\n    -1.0\n    > y = base.round10( -4.6 )\n    -1.0\n    > y = base.round10( 9.5 )\n    10.0\n    > y = base.round10( 13.0 )\n    10.0\n    > y = base.round10( -13.0 )\n    -10.0\n    > y = base.round10( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceil10, base.floor10, base.round, base.round2\n","base.roundb":"\nbase.roundb( x, n, b )\n    Rounds a numeric value to the nearest multiple of `b^n` on a linear scale.\n\n    Due to floating-point rounding error, rounding may not be exact.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Integer power.\n\n    b: integer\n        Base.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    // Round to 2 decimal places:\n    > var y = base.roundb( 3.14159, -2, 10 )\n    3.14\n\n    // If `n = 0` or `b = 1`, standard round behavior:\n    > y = base.roundb( 3.14159, 0, 2 )\n    3.0\n\n    // Round to nearest multiple of two:\n    > y = base.roundb( 5.0, 1, 2 )\n    6.0\n\n    See Also\n    --------\n    base.ceilb, base.floorb, base.round, base.roundn\n","base.roundn":"\nbase.roundn( x, n )\n    Rounds a numeric value to the nearest multiple of `10^n`.\n\n    When operating on floating-point numbers in bases other than `2`, rounding\n    to specified digits can be inexact.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Integer power of 10.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    // Round to 2 decimal places:\n    > var y = base.roundn( 3.14159, -2 )\n    3.14\n\n    // If `n = 0`, standard round behavior:\n    > y = base.roundn( 3.14159, 0 )\n    3.0\n\n    // Round to nearest thousand:\n    > y = base.roundn( 12368.0, 3 )\n    12000.0\n\n\n    See Also\n    --------\n    base.ceiln, base.floorn, base.round, base.roundb\n","base.roundsd":"\nbase.roundsd( x, n[, b] )\n    Rounds a numeric value to the nearest number with `n` significant figures.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Number of significant figures. Must be greater than 0.\n\n    b: integer (optional)\n        Base. Must be greater than 0. Default: 10.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.roundsd( 3.14159, 3 )\n    3.14\n    > y = base.roundsd( 3.14159, 1 )\n    3.0\n    > y = base.roundsd( 12368.0, 2 )\n    12000.0\n    > y = base.roundsd( 0.0313, 2, 2 )\n    0.03125\n\n    See Also\n    --------\n    base.ceilsd, base.floorsd, base.round, base.truncsd\n","base.rsqrt":"\nbase.rsqrt( x )\n    Computes the reciprocal square root of a double-precision floating-point\n    number.\n\n    For `x < 0`, the reciprocal square root is not defined.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Reciprocal square root.\n\n    Examples\n    --------\n    > var y = base.rsqrt( 4.0 )\n    0.5\n    > y = base.rsqrt( 100.0 )\n    0.1\n    > y = base.rsqrt( 0.0 )\n    Infinity\n    > y = base.rsqrt( Infinity )\n    0.0\n    > y = base.rsqrt( -4.0 )\n    NaN\n    > y = base.rsqrt( NaN )\n    NaN\n\n    See Also\n    --------\n    base.sqrt\n","base.rsqrtf":"\nbase.rsqrtf( x )\n    Computes the reciprocal square root of a single-precision floating-point\n    number.\n\n    For `x < 0`, the reciprocal square root is not defined.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Reciprocal square root.\n\n    Examples\n    --------\n    > var y = base.rsqrtf( 4.0 )\n    0.5\n    > y = base.rsqrtf( 0.0 )\n    Infinity\n    > y = base.rsqrtf( Infinity )\n    0.0\n    > y = base.rsqrtf( -4.0 )\n    NaN\n    > y = base.rsqrtf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.rsqrt, base.sqrtf\n","base.sargs2multislice":"\nbase.sargs2multislice( str )\n    Creates a MultiSlice object from a comma-separated list of string-serialized\n    MultiSlice constructor arguments.\n\n    The function returns `null` if provided an invalid string.\n\n    Parameters\n    ----------\n    str: string\n        Input string containing constructor arguments.\n\n    Returns\n    -------\n    s: MultiSlice|null\n        MultiSlice instance (or null).\n\n    Examples\n    --------\n    > var s = new base.sargs2multislice( 'null,null,null' );\n    > s.data\n    [ null, null, null ]\n    > s = new base.sargs2multislice( '10,Slice(0,10,1),null' );\n    > s.data\n    [ 10, <Slice>, null ]\n\n    See Also\n    --------\n    base.args2multislice, base.seq2multislice\n","base.scalar2ndarray":"\nbase.scalar2ndarray( value, dtype, order )\n    Returns a zero-dimensional ndarray containing a provided scalar value.\n\n    If `value` is a number and `dtype` is a complex number data type, the\n    function returns a zero-dimensional ndarray containing a complex number\n    whose real component equals the provided scalar value and whose imaginary\n    component is zero.\n\n    Parameters\n    ----------\n    value: any\n        Scalar value.\n\n    dtype: string\n        Data type.\n\n    order: string\n        Memory layout (either 'row-major' or 'column-major').\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var x = base.scalar2ndarray( 1.0, 'float64', 'row-major' )\n    <ndarray>\n    > var sh = x.shape\n    []\n    > var dt = x.dtype\n    'float64'\n    > var v = x.get()\n    1.0\n\n    See Also\n    --------\n    array, base.ndarray, ndarray\n","base.secd":"\nbase.secd( x )\n    Computes the secant of an angle measured in degrees.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in degrees).\n\n    Returns\n    -------\n    y: number\n        Secant.\n\n    Examples\n    --------\n    > var y = base.secd( 1.0 )\n    ~1.0\n    > y = base.secd( PI )\n    ~1.0\n    > y = base.secd( -PI )\n    ~1.0\n    > y = base.secd( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cosd, base.cos\n","base.seq2multislice":"\nbase.seq2multislice( str, shape, strict )\n    Converts a multidimensional subsequence string to a MultiSlice object.\n\n    A multidimensional subsequence string is a comma-separated list of single-\n    dimension indexing expressions (i.e., integers and/or subsequence strings).\n\n    For example, the following\n\n      2\n      :\n      2:\n      :10\n      2:10\n      ::-1\n      10:2:-1\n      :2:\n      2:10:\n      2::2\n      :10:2\n      :, :, :\n      1, 2, 3\n      0:10, 1:20:2, ::-1\n      ...\n      :, ..., 2\n\n    are all valid multidimensional subsequence strings.\n\n    Providing a single nonnegative integer `i` as a single-dimension index\n    indexes the same elements as the subsequence `i:i+1`.\n\n    Providing a single negative integer `i` as a single-dimension index indexes\n    the same elements as the subsequence `n+i:n+i+i`, where `n` is the dimension\n    size.\n\n    While integers index the same elements as equivalent subsequences, providing\n    an integer as a single-dimension index indicates to reduce the number of\n    dimensions by one (e.g., if the provided shape corresponds to an array\n    having rank 2, then rank(A)-1 == rank(A['0,:'])).\n\n    In contrast, providing a subsequence indicates to retain a respective\n    dimension (e.g., if the provided shape corresponds to an array having rank\n    2, then rank(A) == rank(A[':,:'])).\n\n    A multidimensional subsequence string can only contain **one** ellipsis\n    ('...') operator. An ellipsis indicates to apply ':' to each dimension\n    necessary to index all dimensions (e.g., if A has rank 4, A['1:,...,2:5']\n    equals A['1:,:,:,2:5']).\n\n    Except in the case of providing a single ellipsis, the number of single-\n    dimension indexing expressions must equal the number of dimensions in the\n    input shape.\n\n    The function returns an error object if provided an invalid subsequence\n    string.\n\n    In strict mode, the function returns an error object if a single-dimension\n    index expression which exceeds index bounds.\n\n    A returned error object is a plain object having the following properties:\n\n    - code: error code.\n\n    A returned error object may have one of the following error codes:\n\n    - ERR_SLICE_INVALID_SUBSEQUENCE: a subsequence string is invalid.\n    - ERR_SLICE_INVALID_INCREMENT: a subsequence string must have a non-zero\n      increment.\n    - ERR_SLICE_OUT_OF_BOUNDS: a subsequence string resolves to a slice\n      exceeding index bounds.\n    - ERR_SLICE_TOO_MANY_DIMENSIONS: a subsequence string has more dimensions\n      than the provided shape.\n    - ERR_SLICE_INSUFFICIENT_DIMENSIONS: a subsequence string has too few\n      dimensions.\n    - ERR_SLICE_INVALID_ELLIPSIS: a subsequence string must only contain at most\n      one ellipsis.\n\n    Parameters\n    ----------\n    str: string\n        Subsequence string.\n\n    shape: Array<integer>\n        Maximum allowed slice shape.\n\n    strict: boolean\n        Boolean indicating whether to enforce strict bounds checking.\n\n    Returns\n    -------\n    s: MultiSlice|Object\n        MultiSlice instance or an error object.\n\n    Examples\n    --------\n    > var s = new base.seq2multislice( '1:10', [ 10 ], false );\n    > s.data\n    [ <Slice> ]\n    > s = new base.seq2multislice( '4,2:5:2,:', [ 10, 10, 10 ], false );\n    > s.data\n    [ 4, <Slice>, <Slice> ]\n\n    See Also\n    --------\n    base.seq2slice, base.sargs2multislice\n","base.seq2slice":"\nbase.seq2slice( str, len, strict )\n    Converts a subsequence string to a Slice object.\n\n    A subsequence string has the following format:\n\n      <start>:<stop>:<increment>\n\n    If an increment is not specified, the default increment is one. An increment\n    of zero is not allowed.\n\n    The start index is inclusive.\n\n    The stop index is exclusive.\n\n    Both start and stop indices are optional. If not provided, the start and\n    stop indices default to index extremes. Which extremes correspond to which\n    index depends on whether the increment is positive or negative.\n\n    Both start and stop indices can be negative; in which case, the\n    corresponding index is resolved by subtracting the respective value from the\n    provided length.\n\n    Both start and stop indices can use the 'end' keyword (e.g., 'end-2::2',\n    'end-3:', etc), which supports basic subtraction and division.\n\n    The 'end' keyword resolves to the provided length. Thus, ':-1' is equivalent\n    to ':end-1', ':-2' is equivalent to ':end-2', and so on and so forth. The\n    exception is when performing a division operation when the increment is less\n    than zero; in which case, 'end' is equal to 'len-1' in order to preserve\n    user expectations when 'end/d' equals a whole number and slicing from right-\n    to-left. The result from a division operation is rounded down to the nearest\n    integer value.\n\n    In non-strict mode, the resolved slice start is clamped to the slice index\n    bounds [0, len).\n\n    In non-strict mode, Tte resolved slice end is upper bound clamped to the\n    provided length (i.e., one greater than the last possible index).\n\n    When the increment is negative, the resolved slice end value may be `null`,\n    thus indicating that a non-empty slice should include the first index.\n\n    The function ensures that results satisfy the convention that ':n' combined\n    with 'n:' is equivalent to ':' (i.e., selecting all elements).\n\n    When the provided length is zero, the function always returns a slice object\n    equivalent to '0:0:<increment>'.\n\n    The function returns an error object if provided an invalid subsequence\n    string.\n\n    In strict mode, the function returns an error object if provided a\n    subsequence string which exceeds index bounds.\n\n    A returned error object is a plain object having the following properties:\n\n    - code: error code.\n\n    A returned error object may have one of the following error codes:\n\n    - ERR_SLICE_INVALID_SUBSEQUENCE: a subsequence string is invalid.\n    - ERR_SLICE_INVALID_INCREMENT: a subsequence string must have a non-zero\n      increment.\n    - ERR_SLICE_OUT_OF_BOUNDS: a subsequence string resolves to a slice\n      exceeding index bounds.\n\n    Parameters\n    ----------\n    str: string\n        Subsequence string.\n\n    len: integer\n        Maximum number of elements allowed in the slice.\n\n    strict: boolean\n        Boolean indicating whether to enforce strict bounds checking.\n\n    Returns\n    -------\n    s: Slice|Object\n        Slice instance or an error object.\n\n    Examples\n    --------\n    > var s = new base.seq2slice( '1:10', 10, false );\n    > s.start\n    1\n    > s.stop\n    10\n    > s.step\n    1\n    > s = new base.seq2slice( '2:5:2', 10, false );\n    > s.start\n    2\n    > s.stop\n    5\n    > s.step\n    2\n\n    See Also\n    --------\n    base.seq2multislice, base.slice2seq\n","base.setHighWord":"\nbase.setHighWord( x, high )\n    Sets the more significant 32 bits of a double-precision floating-point\n    number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    high: integer\n        Unsigned 32-bit integer to replace the higher order word of `x`.\n\n    Returns\n    -------\n    out: number\n        Double having the same lower order word as `x`.\n\n    Examples\n    --------\n    // Set the higher order bits of `+infinity` to return `1`:\n    > var high = 1072693248 >>> 0;\n    > var y = base.setHighWord( PINF, high )\n    1.0\n\n    See Also\n    --------\n    base.getHighWord, base.setLowWord\n","base.setLowWord":"\nbase.setLowWord( x, low )\n    Sets the less significant 32 bits of a double-precision floating-point\n    number.\n\n    Setting the lower order bits of `NaN` or positive or negative infinity will\n    return `NaN`, as `NaN` is defined as a double whose exponent bit sequence is\n    all ones and whose fraction can be any bit sequence except all zeros.\n    Positive and negative infinity are defined as doubles with an exponent bit\n    sequence equal to all ones and a fraction equal to all zeros. Hence,\n    changing the less significant bits of positive and negative infinity\n    converts each value to `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    low: integer\n        Unsigned 32-bit integer to replace the lower order word of `x`.\n\n    Returns\n    -------\n    out: number\n        Double having the same higher order word as `x`.\n\n    Examples\n    --------\n    > var low = 5 >>> 0;\n    > var x = 3.14e201;\n    > var y = base.setLowWord( x, low )\n    3.139998651394392e+201\n\n    // Special cases:\n    > var low = 12345678;\n    > var y = base.setLowWord( PINF, low )\n    NaN\n    > y = base.setLowWord( NINF, low )\n    NaN\n    > y = base.setLowWord( NaN, low )\n    NaN\n\n    See Also\n    --------\n    base.getLowWord, base.setHighWord\n","base.sici":"\nbase.sici( x )\n    Computes the sine and cosine integrals.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    out: Array<number>\n        Sine and cosine integrals.\n\n    Examples\n    --------\n    > var y = base.sici( 3.0 )\n    [ ~1.849, ~0.12 ]\n    > y = base.sici( 0.0 )\n    [ 0.0, -Infinity ]\n    > y = base.sici( -9.0 )\n    [ ~-1.665, ~0.055 ]\n    > y = base.sici( NaN )\n    [ NaN, NaN ]\n\n\nbase.sici.assign( x, out, stride, offset )\n    Computes the sine and cosine integrals and assigns results to a provided\n    output array.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Sine and cosine integrals.\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var y = base.sici.assign( 3.0, out, 1, 0 )\n    <Float64Array>[ ~1.849, ~0.12 ]\n    > var bool = ( y === out )\n    true\n","base.sici.assign":"\nbase.sici.assign( x, out, stride, offset )\n    Computes the sine and cosine integrals and assigns results to a provided\n    output array.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Sine and cosine integrals.\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var y = base.sici.assign( 3.0, out, 1, 0 )\n    <Float64Array>[ ~1.849, ~0.12 ]\n    > var bool = ( y === out )\n    true","base.signbit":"\nbase.signbit( x )\n    Returns a boolean indicating if the sign bit is on (true) or off (false).\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if sign bit is on or off.\n\n    Examples\n    --------\n    > var bool = base.signbit( 4.0 )\n    false\n    > bool = base.signbit( -9.14e-34 )\n    true\n    > bool = base.signbit( 0.0 )\n    false\n    > bool = base.signbit( -0.0 )\n    true\n\n    See Also\n    --------\n    base.signbitf\n","base.signbitf":"\nbase.signbitf( x )\n    Returns a boolean indicating if the sign bit is on (true) or off (false).\n\n    Parameters\n    ----------\n    x: float\n        Single-precision floating-point number.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if sign bit is on or off.\n\n    Examples\n    --------\n    > var bool = base.signbitf( base.float64ToFloat32( 4.0 ) )\n    false\n    > bool = base.signbitf( base.float64ToFloat32( -9.14e-34 ) )\n    true\n    > bool = base.signbitf( 0.0 )\n    false\n    > bool = base.signbitf( -0.0 )\n    true\n\n    See Also\n    --------\n    base.signbit\n","base.significandf":"\nbase.significandf( x )\n    Returns an integer corresponding to the significand of a single-precision\n    floating-point number.\n\n    Parameters\n    ----------\n    x: float\n        Single-precision floating-point number.\n\n    Returns\n    -------\n    out: integer\n        Significand.\n\n    Examples\n    --------\n    > var s = base.significandf( base.float64ToFloat32( 3.14e34 ) )\n    4293751\n    > s = base.significandf( base.float64ToFloat32( 3.14e-34 ) )\n    5288021\n    > s = base.significandf( base.float64ToFloat32( -3.14 ) )\n    4781507\n    > s = base.significandf( 0.0 )\n    0\n    > s = base.significandf( NaN )\n    4194304\n\n","base.signum":"\nbase.signum( x )\n    Evaluates the signum function for a double-precision floating-point number.\n\n    Value | Sign\n    ----- | -----\n    x > 0 |    +1\n    x < 0 |    -1\n        0 |     0\n       -0 |    -0\n      NaN |   NaN\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    sign: number\n        Function value.\n\n    Examples\n    --------\n    > var sign = base.signum( -5.0 )\n    -1.0\n    > sign = base.signum( 5.0 )\n    1.0\n    > sign = base.signum( -0.0 )\n    -0.0\n    > sign = base.signum( 0.0 )\n    0.0\n    > sign = base.signum( NaN )\n    NaN\n\n","base.signumf":"\nbase.signumf( x )\n    Evaluates the signum function for a single-precision floating-point number.\n\n    Value | Sign\n    ----- | -----\n    x > 0 |    +1\n    x < 0 |    -1\n        0 |     0\n       -0 |    -0\n      NaN |   NaN\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    sign: number\n        Function value.\n\n    Examples\n    --------\n    > var sign = base.signumf( -5.0 )\n    -1.0\n    > sign = base.signumf( 5.0 )\n    1.0\n    > sign = base.signumf( -0.0 )\n    -0.0\n    > sign = base.signumf( 0.0 )\n    0.0\n    > sign = base.signumf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.signum\n","base.sin":"\nbase.sin( x )\n    Computes the sine of a number.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Sine.\n\n    Examples\n    --------\n    > var y = base.sin( 0.0 )\n    ~0.0\n    > y = base.sin( PI/2.0 )\n    ~1.0\n    > y = base.sin( -PI/6.0 )\n    ~-0.5\n    > y = base.sin( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cos, base.sinpi, base.tan\n","base.sinc":"\nbase.sinc( x )\n    Computes the normalized cardinal sine of a number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Cardinal sine.\n\n    Examples\n    --------\n    > var y = base.sinc( 0.5 )\n    ~0.637\n    > y = base.sinc( -1.2 )\n    ~-0.156\n    > y = base.sinc( 0.0 )\n    1.0\n    > y = base.sinc( NaN )\n    NaN\n\n    See Also\n    --------\n    base.sin\n","base.sincos":"\nbase.sincos( x )\n    Simultaneously computes the sine and cosine of a number.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: Array<number>\n        Sine and cosine.\n\n    Examples\n    --------\n    > var y = base.sincos( 0.0 )\n    [ ~0.0, ~1.0 ]\n    > y = base.sincos( PI/2.0 )\n    [ ~1.0, ~0.0 ]\n    > y = base.sincos( -PI/6.0 )\n    [ ~-0.5, ~0.866 ]\n    > y = base.sincos( NaN )\n    [ NaN, NaN ]\n\n\nbase.sincos( x, out, stride, offset )\n    Simultaneously computes the sine and cosine of a number and assigns\n    results to a provided output array.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Sine and cosine.\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var v = base.sincos.assign( 0.0, out, 1, 0 )\n    <Float64Array>[ ~0.0, ~1.0 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.cos, base.sin, base.sincospi","base.sincospi":"\nbase.sincospi( x )\n    Simultaneously computes the sine and cosine of a number times π.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: Array<number>\n        Two-element array containing sin(πx) and cos(πx).\n\n    Examples\n    --------\n    > var y = base.sincospi( 0.0 )\n    [ 0.0, 1.0 ]\n    > y = base.sincospi( 0.5 )\n    [ 1.0, 0.0 ]\n    > y = base.sincospi( 0.1 )\n    [ ~0.309, ~0.951 ]\n    > y = base.sincospi( NaN )\n    [ NaN, NaN ]\n\n\nbase.sincospi.assign( x, out, stride, offset )\n    Simultaneously computes the sine and cosine of a number times π and\n    assigns results to a provided output array.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Two-element array containing sin(πx) and cos(πx).\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var v = base.sincospi.assign( 0.0, out, 1, 0 )\n    <Float64Array>[ 0.0, 1.0 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.cospi, base.sincos, base.sinpi","base.sincospi.assign":"\nbase.sincospi.assign( x, out, stride, offset )\n    Simultaneously computes the sine and cosine of a number times π and\n    assigns results to a provided output array.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Two-element array containing sin(πx) and cos(πx).\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var v = base.sincospi.assign( 0.0, out, 1, 0 )\n    <Float64Array>[ 0.0, 1.0 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.cospi, base.sincos, base.sinpi","base.sinh":"\nbase.sinh( x )\n    Computes the hyperbolic sine of a double-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Hyperbolic sine.\n\n    Examples\n    --------\n    > var y = base.sinh( 0.0 )\n    0.0\n    > y = base.sinh( 2.0 )\n    ~3.627\n    > y = base.sinh( -2.0 )\n    ~-3.627\n    > y = base.sinh( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cosh, base.sin, base.tanh\n","base.sinpi":"\nbase.sinpi( x )\n    Computes the value of `sin(πx)`.\n\n    The function computes `sin(πx)` more accurately than the obvious approach,\n    especially for large `x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.sinpi( 0.0 )\n    0.0\n    > y = base.sinpi( 0.5 )\n    1.0\n    > y = base.sinpi( 0.9 )\n    ~0.309\n    > y = base.sinpi( NaN )\n    NaN\n\n    See Also\n    --------\n    base.sin\n","base.slice2seq":"\nbase.slice2seq( slice )\n    Converts a Slice object to a subsequence string.\n\n    Parameters\n    ----------\n    slice: Slice\n        Input slice.\n\n    Returns\n    -------\n    out: string\n        Subsequence string.\n\n    Examples\n    --------\n    > var out = base.slice2seq( new Slice( 1, 10, 1 ) )\n    '1:10:1'\n    > out = base.slice2seq( new Slice( null, 10 ) )\n    ':10'\n\n    See Also\n    --------\n    base.seq2slice\n","base.sliceLength":"\nbase.sliceLength( slice )\n    Returns the number of elements in a normalized slice.\n\n    Parameters\n    ----------\n    slice: Slice\n        Input normalized slice object.\n\n    Returns\n    -------\n    len: integer\n        Number of elements.\n\n    Examples\n    --------\n    > var s = new Slice( 1, 10, 1 );\n    > base.sliceLength( s )\n    9\n\n    See Also\n    --------\n    base.sliceNonReducedDimensions, base.sliceReducedDimensions, base.sliceShape\n","base.sliceNonReducedDimensions":"\nbase.sliceNonReducedDimensions( slice )\n    Returns a list of non-reduced dimensions in an un-normalized multi-slice.\n\n    Parameters\n    ----------\n    slice: MultiSlice\n        Input slice object.\n\n    Returns\n    -------\n    out: Array<integer>\n        Dimension indices.\n\n    Examples\n    --------\n    > var s = new MultiSlice( 1, 3, null );\n    > var out = base.sliceNonReducedDimensions( s )\n    [ 2 ]\n\n    See Also\n    --------\n    base.sliceLength, base.sliceReducedDimensions, base.sliceShape\n","base.sliceReducedDimensions":"\nbase.sliceReducedDimensions( slice )\n    Returns a list of reduced dimensions in an un-normalized multi-slice.\n\n    Parameters\n    ----------\n    slice: MultiSlice\n        Input slice object.\n\n    Returns\n    -------\n    out: Array<integer>\n        Dimension indices.\n\n    Examples\n    --------\n    > var s = new MultiSlice( 1, 3, null );\n    > var out = base.sliceReducedDimensions( s )\n    [ 0, 1 ]\n\n    See Also\n    --------\n    base.sliceLength, base.sliceNonReducedDimensions, base.sliceShape\n","base.sliceShape":"\nbase.sliceShape( slice )\n    Returns the shape of a normalized multi-slice.\n\n    Parameters\n    ----------\n    slice: MultiSlice\n        Input normalized multi-slice object.\n\n    Returns\n    -------\n    sh: Array<integer>\n        Slice shape.\n\n    Examples\n    --------\n    > var s = new Slice( 1, 10, 1 );\n    > var ms = new MultiSlice( s, s );\n    > base.sliceShape( ms )\n    [ 9, 9 ]\n\n    See Also\n    --------\n    base.sliceLength, base.sliceNonReducedDimensions, base.sliceReducedDimensions\n","base.snakecase":"\nbase.snakecase( str )\n    Converts a string to snake case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Snake-cased string.\n\n    Examples\n    --------\n    > var out = base.snakecase( 'Hello World!' )\n    'hello_world'\n    > out = base.snakecase( 'I am a tiny little teapot' )\n    'i_am_a_tiny_little_teapot'\n\n    See Also\n    --------\n    base.camelcase, base.lowercase, base.stickycase, base.uppercase","base.spence":"\nbase.spence( x )\n    Evaluates Spence's function, which is also known as the dilogarithm.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.spence( 3.0 )\n    ~-1.437\n    > y = base.spence( 0.0 )\n    ~1.645\n    > y = base.spence( -9.0 )\n    NaN\n    > y = base.spence( NaN )\n    NaN\n\n","base.sqrt":"\nbase.sqrt( x )\n    Computes the principal square root of a double-precision floating-point\n    number.\n\n    For `x < 0`, the principal square root is not defined.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Principal square root.\n\n    Examples\n    --------\n    > var y = base.sqrt( 4.0 )\n    2.0\n    > y = base.sqrt( 9.0 )\n    3.0\n    > y = base.sqrt( 0.0 )\n    0.0\n    > y = base.sqrt( -4.0 )\n    NaN\n    > y = base.sqrt( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cbrt, base.rsqrt\n","base.sqrt1pm1":"\nbase.sqrt1pm1( x )\n    Computes the principal square root of `1+x` minus one.\n\n    This function is more accurate than the obvious approach for small `x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Square root of `1+x` minus one.\n\n    Examples\n    --------\n    > var y = base.sqrt1pm1( 3.0 )\n    1.0\n    > y = base.sqrt1pm1( 0.5 )\n    ~0.225\n    > y = base.sqrt1pm1( 0.02 )\n    ~0.01\n    > y = base.sqrt1pm1( -0.5 )\n    ~-0.293\n    > y = base.sqrt1pm1( -1.1 )\n    NaN\n    > y = base.sqrt1pm1( NaN )\n    NaN\n\n    See Also\n    --------\n    base.sqrt\n","base.sqrtf":"\nbase.sqrtf( x )\n    Computes the principal square root of a single-precision floating-point\n    number.\n\n    For `x < 0`, the principal square root is not defined.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Principal square root.\n\n    Examples\n    --------\n    > var y = base.sqrtf( 4.0 )\n    2.0\n    > y = base.sqrtf( 9.0 )\n    3.0\n    > y = base.sqrtf( 0.0 )\n    0.0\n    > y = base.sqrtf( -4.0 )\n    NaN\n    > y = base.sqrtf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cbrtf, base.rsqrtf, base.sqrt\n","base.sqrtpi":"\nbase.sqrtpi( x )\n    Computes the principal square root of the product of π and a positive\n    double-precision floating-point number.\n\n    For `x < 0`, the square root is not defined.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Principal square root of the product of π and the input value.\n\n    Examples\n    --------\n    > var y = base.sqrtpi( 4.0 )\n    ~3.5449\n    > y = base.sqrtpi( 10.0 )\n    ~5.60499\n    > y = base.sqrtpi( 0.0 )\n    0.0\n    > y = base.sqrtpi( -4.0 )\n    NaN\n    > y = base.sqrtpi( NaN )\n    NaN\n\n    See Also\n    --------\n    base.sqrt","base.startcase":"\nbase.startcase( str )\n    Capitalizes the first letter of each word in an input string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        String containing words where each first letter is capitalized.\n\n    Examples\n    --------\n    > var out = base.startcase( 'beep boop' )\n    'Beep Boop'\n\n    See Also\n    --------\n    base.capitalize, base.lowercase, base.uppercase\n","base.startsWith":"\nbase.startsWith( str, search, position )\n    Tests if a string starts with the characters of another string.\n\n    If provided an empty search string, the function always returns `true`.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search string.\n\n    position: integer\n        Position at which to start searching for `search`. If less than `0`, the\n        start position is determined relative to the end of the input string.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a string starts with the characters of\n        another string.\n\n    Examples\n    --------\n    > var bool = base.startsWith( 'Beep', 'Be', 0 )\n    true\n    > bool = base.startsWith( 'Beep', 'ep', 0 )\n    false\n    > bool = base.startsWith( 'Beep', 'ee', 1 )\n    true\n    > bool = base.startsWith( 'Beep', 'ee', -3 )\n    true\n    > bool = base.startsWith( 'Beep', '', 0 )\n    true\n\n    See Also\n    --------\n    base.endsWith\n","base.stickycase":"\nbase.stickycase( str[, p] )\n    Converts a string to sticky case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n \n    p: number\n        Probability of capitalization.\n\n    Returns\n    -------\n    out: string\n        Sticky-cased string.\n\n    Examples\n    --------\n    > var out = base.stickycase( 'Hello World!' )\n    <string>\n\n    > out = base.stickycase( 'I am a tiny little teapot' )\n    <string>\n    See Also\n    --------\n    base.camelcase, base.lowercase, base.snakecase, base.uppercase\n","base.strided.binary":"\nbase.strided.binary( arrays, shape, strides, fcn )\n    Applies a binary callback to strided input array elements and assigns\n    results to elements in a strided output array.\n\n    The `shape` and `strides` parameters determine which elements in the strided\n    input and output arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing two strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    fcn: Function\n        Binary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1 ];\n    > function f( x, y ) { return x + y; };\n    > base.strided.binary( [ x, y, z ], shape, strides, f );\n    > z\n    <Float64Array>[ 2.0, 4.0, 6.0, 8.0 ]\n\n\nbase.strided.binary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a binary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing two strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Binary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1 ];\n    > var offsets = [ 0, 0, 0 ];\n    > function f( x, y ) { return x + y; };\n    > base.strided.binary.ndarray( [ x, y, z ], shape, strides, offsets, f );\n    > z\n    <Float64Array>[ 2.0, 4.0, 6.0, 8.0 ]\n\n    See Also\n    --------\n    base.strided.dmap2, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap2, base.strided.ternary, base.strided.unary\n","base.strided.binary.ndarray":"\nbase.strided.binary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a binary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing two strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Binary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1 ];\n    > var offsets = [ 0, 0, 0 ];\n    > function f( x, y ) { return x + y; };\n    > base.strided.binary.ndarray( [ x, y, z ], shape, strides, offsets, f );\n    > z\n    <Float64Array>[ 2.0, 4.0, 6.0, 8.0 ]\n\n    See Also\n    --------\n    base.strided.dmap2, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap2, base.strided.ternary, base.strided.unary","base.strided.binaryDtypeSignatures":"\nbase.strided.binaryDtypeSignatures( dtypes1, dtypes2, dtypes3[, options] )\n    Generates a list of binary interface signatures from strided array data\n    types.\n\n    The function returns a strided array having a stride length of `3` (i.e.,\n    every `3` elements define a binary interface signature).\n\n    For each signature (i.e., set of three consecutive non-overlapping strided\n    array elements), the first two elements are the input data types and the\n    third element is the return data type.\n\n    All signatures follow type promotion rules.\n\n    Parameters\n    ----------\n    dtypes1: ArrayLike<any>\n        List of supported data types for the first input argument.\n\n    dtypes2: ArrayLike<any>\n        List of supported data types for the second input argument.\n\n    dtypes3: ArrayLike<any>\n        List of supported data types for the output value.\n\n    options: Object (optional)\n        Options.\n\n    options.enums: boolean (optional)\n        Boolean flag indicating whether to return signatures as a list of data\n        type enumeration constants. Default: false.\n\n    Returns\n    -------\n    out: Array\n        Strided array containing binary interface signatures.\n\n    Examples\n    --------\n    > var dt = strided.dataTypes();\n    > var out = base.strided.binaryDtypeSignatures( dt, dt, dt )\n    [...]\n\n    See Also\n    --------\n    base.strided.binarySignatureCallbacks\n","base.strided.binarySignatureCallbacks":"\nbase.strided.binarySignatureCallbacks( table, signatures )\n    Assigns callbacks to binary interfaces according to type promotion rules.\n\n    Parameters\n    ----------\n    table: Object\n        Object mapping callbacks to data types.\n\n    table.default: Function\n        Default callback.\n\n    table.complex64: Function\n        Callback to be invoked when input arrays promote to single-precision\n        complex floating-point numbers.\n\n    table.complex128: Function\n        Callback to be invoked when input arrays promote to double precision\n        complex floating-point numbers.\n\n    signatures: ArrayLike<any>\n        Strided array containing binary interface signatures.\n\n    Returns\n    -------\n    out: Array<Function>\n        List of callbacks, one per signature.\n\n    Examples\n    --------\n    > var dt = strided.dataTypes();\n    > var sigs = base.strided.binaryDtypeSignatures( dt, dt, dt );\n    > var t = {\n    ...     'default': base.add,\n    ...     'complex64': base.caddf,\n    ...     'complex128': base.cadd\n    ... };\n    > var out = base.strided.binarySignatureCallbacks( t, sigs )\n    [...]\n\n    See Also\n    --------\n    base.strided.binaryDtypeSignatures\n","base.strided.ccopy":"\nbase.strided.ccopy( N, x, strideX, y, strideY )\n    Copies values from one complex single-precision floating-point vector to\n    another complex single-precision floating-point vector.\n\n    The `N` and stride parameters determine how values from `x` are copied into\n    `y`.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Complex64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Complex64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n    > base.strided.ccopy( x.length, x, 1, y, 1 );\n    > var z = y.get( 0 );\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    2.0\n\n    // Advanced indexing:\n    > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n    > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.ccopy( 2, x, -2, y, 1 );\n    > z = y.get( 0 );\n    > re = realf( z )\n    5.0\n    > im = imagf( z )\n    6.0\n\n    // Using typed array views:\n    > var x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n    > var y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.ccopy( 2, x1, -2, y1, 1 );\n    > z = y0.get( 2 );\n    > re = realf( z )\n    7.0\n    > im = imagf( z )\n    8.0\n\n\nbase.strided.ccopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Copies values from one complex single-precision floating-point vector to\n    another complex single-precision floating-point vector using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Complex64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Complex64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n    > base.strided.ccopy.ndarray( x.length, x, 1, 0, y, 1, 0 );\n    > var z = y.get( 0 );\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    2.0\n\n    // Advanced indexing:\n    > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n    > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.ccopy.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\n    > z = y.get( y.length-1 );\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    4.0\n\n    See Also\n    --------\n    base.strided.cswap\n","base.strided.ccopy.ndarray":"\nbase.strided.ccopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Copies values from one complex single-precision floating-point vector to\n    another complex single-precision floating-point vector using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Complex64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Complex64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n    > base.strided.ccopy.ndarray( x.length, x, 1, 0, y, 1, 0 );\n    > var z = y.get( 0 );\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    2.0\n\n    // Advanced indexing:\n    > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n    > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.ccopy.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\n    > z = y.get( y.length-1 );\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    4.0\n\n    See Also\n    --------\n    base.strided.cswap","base.strided.cmap":"\nbase.strided.cmap( N, x, strideX, y, strideY, fcn )\n    Applies a unary function to a single-precision complex floating-point\n    strided input array and assigns results to a single-precision complex\n    floating-point strided output array.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Complex64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Complex64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n    > var x = new Complex64Array( xbuf );\n    > var y = new Complex64Array( x.length );\n    > base.strided.cmap( x.length, x, 1, y, 1, base.cidentityf );\n    > var v = y.get( 0 )\n    <Complex64>\n    > var re = real( v )\n    1.0\n    > var im = imag( v )\n    2.0\n\n    // Using `N` and stride parameters:\n    > y = new Complex64Array( x.length );\n    > base.strided.cmap( 2, x, 2, y, -1, base.cidentityf );\n    > v = y.get( 0 )\n    <Complex64>\n    > re = real( v )\n    5.0\n    > im = imag( v )\n    6.0\n\n    // Using view offsets:\n    > var x0 = new Complex64Array( xbuf );\n    > var y0 = new Complex64Array( x0.length );\n    > var x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.cmap( 2, x1, -2, y1, 1, base.cidentityf );\n    > v = y1.get( 0 )\n    <Complex64>\n    > re = real( v )\n    7.0\n    > im = imag( v )\n    8.0\n\n\nbase.strided.cmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n    Applies a unary function to a single-precision complex floating-point\n    strided input array and assigns results to a single-precision complex\n    floating-point strided output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Complex64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Complex64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n    > var x = new Complex64Array( xbuf );\n    > var y = new Complex64Array( x.length );\n    > base.strided.cmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentityf );\n    > var v = y.get( 0 )\n    <Complex64>\n    > var re = real( v )\n    1.0\n    > var im = imag( v )\n    2.0\n\n    // Advanced indexing:\n    > x = new Complex64Array( xbuf );\n    > y = new Complex64Array( x.length );\n    > base.strided.cmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentityf );\n    > v = y.get( y.length-1 )\n    <Complex64>\n    > re = real( v )\n    3.0\n    > im = imag( v )\n    4.0\n\n    See Also\n    --------\n    base.strided.zmap, base.strided.unary\n","base.strided.cmap.ndarray":"\nbase.strided.cmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n    Applies a unary function to a single-precision complex floating-point\n    strided input array and assigns results to a single-precision complex\n    floating-point strided output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Complex64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Complex64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n    > var x = new Complex64Array( xbuf );\n    > var y = new Complex64Array( x.length );\n    > base.strided.cmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentityf );\n    > var v = y.get( 0 )\n    <Complex64>\n    > var re = real( v )\n    1.0\n    > var im = imag( v )\n    2.0\n\n    // Advanced indexing:\n    > x = new Complex64Array( xbuf );\n    > y = new Complex64Array( x.length );\n    > base.strided.cmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentityf );\n    > v = y.get( y.length-1 )\n    <Complex64>\n    > re = real( v )\n    3.0\n    > im = imag( v )\n    4.0\n\n    See Also\n    --------\n    base.strided.zmap, base.strided.unary","base.strided.cswap":"\nbase.strided.cswap( N, x, strideX, y, strideY )\n    Interchanges two complex single-precision floating-point vectors.\n\n    The `N` and stride parameters determine how values from `x` are swapped with\n    values from `y`.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the vectors are unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Complex64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Complex64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n    > base.strided.cswap( x.length, x, 1, y, 1 );\n    > var z = y.get( 0 );\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    2.0\n    > z = x.get( 0 );\n    > re = realf( z )\n    6.0\n    > im = imagf( z )\n    7.0\n\n    // Advanced indexing:\n    > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n    > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.cswap( 2, x, -2, y, 1 );\n    > z = y.get( 0 );\n    > re = realf( z )\n    5.0\n    > im = imagf( z )\n    6.0\n    > z = x.get( 0 );\n    > re = realf( z )\n    0.0\n    > im = imagf( z )\n    0.0\n\n    // Using typed array views:\n    > var x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n    > var y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.cswap( 2, x1, -2, y1, 1 );\n    > z = y0.get( 2 );\n    > re = realf( z )\n    7.0\n    > im = imagf( z )\n    8.0\n    > z = x0.get( 1 );\n    > re = realf( z )\n    0.0\n    > im = imagf( z )\n    0.0\n\n\nbase.strided.cswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Interchanges two complex single-precision floating-point vectors using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Complex64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Complex64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n    > base.strided.cswap.ndarray( x.length, x, 1, 0, y, 1, 0 );\n    > var z = y.get( 0 );\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    2.0\n    > z = x.get( 0 );\n    > re = realf( z )\n    6.0\n    > im = imagf( z )\n    7.0\n\n    // Advanced indexing:\n    > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n    > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.cswap.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\n    > z = y.get( y.length-1 );\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    4.0\n    > z = x.get( 1 );\n    > re = realf( z )\n    0.0\n    > im = imagf( z )\n    0.0\n\n    See Also\n    --------\n    base.strided.ccopy\n","base.strided.cswap.ndarray":"\nbase.strided.cswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Interchanges two complex single-precision floating-point vectors using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Complex64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Complex64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n    > base.strided.cswap.ndarray( x.length, x, 1, 0, y, 1, 0 );\n    > var z = y.get( 0 );\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    2.0\n    > z = x.get( 0 );\n    > re = realf( z )\n    6.0\n    > im = imagf( z )\n    7.0\n\n    // Advanced indexing:\n    > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n    > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.cswap.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\n    > z = y.get( y.length-1 );\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    4.0\n    > z = x.get( 1 );\n    > re = realf( z )\n    0.0\n    > im = imagf( z )\n    0.0\n\n    See Also\n    --------\n    base.strided.ccopy","base.strided.cumax":"\nbase.strided.cumax( N, x, strideX, y, strideY )\n    Computes the cumulative maximum of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cumax( x.length, x, 1, y, 1 )\n    [ 1.0, 1.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cumax( N, x, 2, y, 2 )\n    [ -2.0, 0.0, 1.0, 0.0, 2.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.cumax( N, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 2.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 2.0, 2.0 ]\n\nbase.strided.cumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum of a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, 1.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cumax.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumin, base.strided.dcumax, base.strided.scumax\n","base.strided.cumax.ndarray":"\nbase.strided.cumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum of a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, 1.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cumax.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumin, base.strided.dcumax, base.strided.scumax","base.strided.cumaxabs":"\nbase.strided.cumaxabs( N, x, strideX, y, strideY )\n    Computes the cumulative maximum absolute value of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cumaxabs( x.length, x, 1, y, 1 )\n    [ 1.0, 2.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cumaxabs( N, x, 2, y, 2 )\n    [ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.cumaxabs( N, x1, 2, y1, 1 )\n    <Float64Array>[ 2.0, 2.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\nbase.strided.cumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum absolute value of a strided array using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, 2.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cumax, base.strided.cuminabs, base.strided.dcumaxabs, base.strided.scumaxabs\n","base.strided.cumaxabs.ndarray":"\nbase.strided.cumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum absolute value of a strided array using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, 2.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cumax, base.strided.cuminabs, base.strided.dcumaxabs, base.strided.scumaxabs","base.strided.cumin":"\nbase.strided.cumin( N, x, strideX, y, strideY )\n    Computes the cumulative minimum of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cumin( x.length, x, 1, y, 1 )\n    [ 1.0, -2.0, -2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cumin( N, x, 2, y, 2 )\n    [ -2.0, 0.0, -2.0, 0.0, -2.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.cumin( N, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, -2.0, -2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\nbase.strided.cumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum of a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, -2.0, -2.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumax, base.strided.dcumin, base.strided.scumin\n","base.strided.cumin.ndarray":"\nbase.strided.cumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum of a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, -2.0, -2.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumax, base.strided.dcumin, base.strided.scumin","base.strided.cuminabs":"\nbase.strided.cuminabs( N, x, strideX, y, strideY )\n    Computes the cumulative minimum absolute value of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cuminabs( x.length, x, 1, y, 1 )\n    [ 1.0, 1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cuminabs( N, x, 2, y, 2 )\n    [ 2.0, 0.0, 1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.cuminabs( N, x1, 2, y1, 1 )\n    <Float64Array>[ 2.0, 2.0, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 1.0 ]\n\nbase.strided.cuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum absolute value of a strided array using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, 1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cumaxabs, base.strided.cumin, base.strided.dcuminabs, base.strided.scuminabs\n","base.strided.cuminabs.ndarray":"\nbase.strided.cuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum absolute value of a strided array using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, 1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cumaxabs, base.strided.cumin, base.strided.dcuminabs, base.strided.scuminabs","base.strided.dabs":"\nbase.strided.dabs( N, x, strideX, y, strideY )\n    Computes the absolute value for each element in a double-precision floating-\n    point strided array `x` and assigns the results to elements in a double-\n    precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dabs( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dabs( N, x, 2, y, -1 )\n    <Float64Array>[ 3.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dabs( N, x1, -2, y1, 1 )\n    <Float64Array>[ 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the absolute value for each element in a double-precision floating-\n    point strided array `x` and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    strided.abs, base.strided.dabs2, base.strided.sabs\n","base.strided.dabs.ndarray":"\nbase.strided.dabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the absolute value for each element in a double-precision floating-\n    point strided array `x` and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    strided.abs, base.strided.dabs2, base.strided.sabs","base.strided.dabs2":"\nbase.strided.dabs2( N, x, strideX, y, strideY )\n    Computes the squared absolute value for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dabs2( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.0, 4.0, 9.0, 16.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dabs2( N, x, 2, y, -1 )\n    <Float64Array>[ 9.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dabs2( N, x1, -2, y1, 1 )\n    <Float64Array>[ 16.0, 4.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 16.0, 4.0 ]\n\n\nbase.strided.dabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the squared absolute value for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 4.0, 9.0, 16.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 16.0, 4.0 ]\n\n    See Also\n    --------\n    strided.abs2, base.strided.dabs, base.strided.sabs2\n","base.strided.dabs2.ndarray":"\nbase.strided.dabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the squared absolute value for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 4.0, 9.0, 16.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 16.0, 4.0 ]\n\n    See Also\n    --------\n    strided.abs2, base.strided.dabs, base.strided.sabs2","base.strided.dapx":"\nbase.strided.dapx( N, alpha, x, strideX )\n    Adds a scalar constant to each element in a double-precision floating-point\n    strided array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns the strided array unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dapx( x.length, 5.0, x, 1 )\n    <Float64Array>[ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dapx( 3, 5.0, x, 2 )\n    <Float64Array>[ 3.0, 1.0, 8.0, -5.0, 9.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dapx( 3, 5.0, x1, 2 )\n    <Float64Array>[ 3.0, 3.0, 1.0, 5.0, -1.0 ]\n    > x0\n    <Float64Array>[ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n\nbase.strided.dapx.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each element in a double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dapx.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float64Array>[ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.dapx.ndarray( 3, 5.0, x, 2, 1 )\n    <Float64Array>[ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n    See Also\n    --------\n    base.strided.gapx, base.strided.sapx\n","base.strided.dapx.ndarray":"\nbase.strided.dapx.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each element in a double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dapx.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float64Array>[ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.dapx.ndarray( 3, 5.0, x, 2, 1 )\n    <Float64Array>[ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n    See Also\n    --------\n    base.strided.gapx, base.strided.sapx","base.strided.dapxsum":"\nbase.strided.dapxsum( N, alpha, x, strideX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsum( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dapxsum( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dapxsum( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.dapxsum.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dapxsum.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumpw, base.strided.dsum, base.strided.gapxsum, base.strided.sapxsum\n","base.strided.dapxsum.ndarray":"\nbase.strided.dapxsum.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dapxsum.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumpw, base.strided.dsum, base.strided.gapxsum, base.strided.sapxsum","base.strided.dapxsumkbn":"\nbase.strided.dapxsumkbn( N, alpha, x, strideX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using an improved Kahan–Babuška\n    algorithm.\n\n    The `N` and stride parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumkbn( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dapxsumkbn( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dapxsumkbn( 3, 5.0, x1, 2)\n    14.0\n\n\nbase.strided.dapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using an improved Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.dsumkbn, base.strided.gapxsumkbn, base.strided.sapxsumkbn\n","base.strided.dapxsumkbn.ndarray":"\nbase.strided.dapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using an improved Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.dsumkbn, base.strided.gapxsumkbn, base.strided.sapxsumkbn","base.strided.dapxsumkbn2":"\nbase.strided.dapxsumkbn2( N, alpha, x, strideX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using a second-order iterative\n    Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumkbn2( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dapxsumkbn2( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dapxsumkbn2( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.dapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using a second-order iterative\n    Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.dsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsumkbn2\n","base.strided.dapxsumkbn2.ndarray":"\nbase.strided.dapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using a second-order iterative\n    Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.dsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsumkbn2","base.strided.dapxsumors":"\nbase.strided.dapxsumors( N, alpha, x, strideX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using ordinary recursive summation.\n\n    The `N` and stride parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumors( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dapxsumors( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dapxsumors( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.dapxsumors.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using ordinary recursive summation\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.dsumors, base.strided.gapxsumors, base.strided.sapxsumors\n","base.strided.dapxsumors.ndarray":"\nbase.strided.dapxsumors.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using ordinary recursive summation\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.dsumors, base.strided.gapxsumors, base.strided.sapxsumors","base.strided.dapxsumpw":"\nbase.strided.dapxsumpw( N, alpha, x, strideX )\n    Adds a scalar constant to each double-precision floating-point strided array\n    element and computes the sum using pairwise summation.\n\n    The `N` and stride parameters determine which elements in\n    the strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumpw( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dapxsumpw( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dapxsumpw( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.dapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a constant to each double-precision floating-point strided array\n    element and computes the sum using pairwise summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.dsumpw, base.strided.gapxsumpw, base.strided.sapxsumpw\n","base.strided.dapxsumpw.ndarray":"\nbase.strided.dapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a constant to each double-precision floating-point strided array\n    element and computes the sum using pairwise summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.dsumpw, base.strided.gapxsumpw, base.strided.sapxsumpw","base.strided.dasum":"\nbase.strided.dasum( N, x, stride )\n    Computes the sum of the absolute values.\n\n    The sum of absolute values corresponds to the *L1* norm.\n\n    The `N` and `stride` parameters determine which elements in `x` are used to\n    compute the sum.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the function returns `0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    sum: number\n        Sum of absolute values.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n    > var s = base.strided.dasum( x.length, x, 1 )\n    15.0\n\n    // Sum every other value:\n    > s = base.strided.dasum( 3, x, 2 )\n    9.0\n\n    // Use view offset; e.g., starting at 2nd element:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > s = base.strided.dasum( 3, x1, 2 )\n    12.0\n\n\nbase.strided.dasum.ndarray( N, x, stride, offset )\n    Computes the sum of absolute values using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    sum: number\n        Sum of absolute values.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n    > var s = base.strided.dasum.ndarray( x.length, x, 1, 0 )\n    15.0\n\n    // Sum the last three elements:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > s = base.strided.dasum.ndarray( 3, x, -1, x.length-1 )\n    15.0\n\n    See Also\n    --------\n    base.strided.daxpy, base.strided.gasum, base.strided.sasum, base.strided.dsum\n","base.strided.dasum.ndarray":"\nbase.strided.dasum.ndarray( N, x, stride, offset )\n    Computes the sum of absolute values using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    sum: number\n        Sum of absolute values.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n    > var s = base.strided.dasum.ndarray( x.length, x, 1, 0 )\n    15.0\n\n    // Sum the last three elements:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > s = base.strided.dasum.ndarray( 3, x, -1, x.length-1 )\n    15.0\n\n    See Also\n    --------\n    base.strided.daxpy, base.strided.gasum, base.strided.sasum, base.strided.dsum","base.strided.dasumpw":"\nbase.strided.dasumpw( N, x, strideX )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements using pairwise summation.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dasumpw( x.length, x, 1 )\n    5.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var stride = 2;\n    > base.strided.dasumpw( 3, x, stride )\n    5.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > stride = 2;\n    > base.strided.dasumpw( 3, x1, stride )\n    5.0\n\n\nbase.strided.dasumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements using pairwise summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dasumpw.ndarray( x.length, x, 1, 0 )\n    5.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dasumpw.ndarray( 3, x, 2, 1 )\n    5.0\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.dsumpw, base.strided.gasumpw, base.strided.sasumpw\n","base.strided.dasumpw.ndarray":"\nbase.strided.dasumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements using pairwise summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dasumpw.ndarray( x.length, x, 1, 0 )\n    5.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dasumpw.ndarray( 3, x, 2, 1 )\n    5.0\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.dsumpw, base.strided.gasumpw, base.strided.sasumpw","base.strided.daxpy":"\nbase.strided.daxpy( N, alpha, x, strideX, y, strideY )\n    Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > var alpha = 5.0;\n    > base.strided.daxpy( x.length, alpha, x, 1, y, 1 )\n    <Float64Array>[ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > base.strided.daxpy( 3, alpha, x, 2, y, -1 )\n    <Float64Array>[ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.daxpy( 3, 5.0, x1, -2, y1, 1 )\n    <Float64Array>[ 40.0, 31.0, 22.0 ]\n    > y0\n    <Float64Array>[ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.strided.daxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n    Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > var alpha = 5.0;\n    > base.strided.daxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.daxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.gaxpy, base.strided.saxpy\n","base.strided.daxpy.ndarray":"\nbase.strided.daxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n    Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > var alpha = 5.0;\n    > base.strided.daxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.daxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.gaxpy, base.strided.saxpy","base.strided.dcbrt":"\nbase.strided.dcbrt( N, x, strideX, y, strideY )\n    Computes the cube root of each element in a double-precision floating-point\n    strided array `x` and assigns the results to elements in a double-precision\n    floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dcbrt( x.length, x, 1, y, 1 )\n    <Float64Array>[ 0.0, 1.0, 2.0, 3.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dcbrt( N, x, 2, y, -1 )\n    <Float64Array>[ 2.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dcbrt( N, x1, -2, y1, 1 )\n    <Float64Array>[ 3.0, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.dcbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cube root of each element in a double-precision floating-point\n    strided array `x` and assigns the results to elements in a double-precision\n    floating-point strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dcbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, 1.0, 2.0, 3.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dcbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n    See Also\n    --------\n    strided.cbrt, base.strided.dsqrt, base.strided.scbrt\n","base.strided.dcbrt.ndarray":"\nbase.strided.dcbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cube root of each element in a double-precision floating-point\n    strided array `x` and assigns the results to elements in a double-precision\n    floating-point strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dcbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, 1.0, 2.0, 3.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dcbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n    See Also\n    --------\n    strided.cbrt, base.strided.dsqrt, base.strided.scbrt","base.strided.dceil":"\nbase.strided.dceil( N, x, strideX, y, strideY )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward positive infinity and assigns the results to elements in a double-\n    precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dceil( x.length, x, 1, y, 1 )\n    <Float64Array>[ 2.0, 3.0, -3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dceil( N, x, 2, y, -1 )\n    <Float64Array>[ -3.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dceil( N, x1, -2, y1, 1 )\n    <Float64Array>[ 4.0, 3.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.dceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward positive infinity and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 2.0, 3.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n    See Also\n    --------\n    strided.ceil, base.strided.dfloor, base.strided.dtrunc, base.strided.sceil\n","base.strided.dceil.ndarray":"\nbase.strided.dceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward positive infinity and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 2.0, 3.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n    See Also\n    --------\n    strided.ceil, base.strided.dfloor, base.strided.dtrunc, base.strided.sceil","base.strided.dcopy":"\nbase.strided.dcopy( N, x, strideX, y, strideY )\n    Copies values from `x` into `y`.\n\n    The `N` and stride parameters determine how values from `x` are copied into\n    `y`.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.dcopy( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.dcopy( 3, x, -2, y, 1 )\n    <Float64Array>[ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n    // Using typed array views:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dcopy( 3, x1, -2, y1, 1 )\n    <Float64Array>[ 6.0, 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.dcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Copies values from `x` into `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.dcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dswap, base.strided.gcopy, base.strided.scopy\n","base.strided.dcopy.ndarray":"\nbase.strided.dcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Copies values from `x` into `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.dcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dswap, base.strided.gcopy, base.strided.scopy","base.strided.dcumax":"\nbase.strided.dcumax( N, x, strideX, y, strideY )\n    Computes the cumulative maximum of double-precision floating-point strided\n    array elements.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumax( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.0, 1.0, 2.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcumax( 3, x, 2, y, 2 )\n    <Float64Array>[ -2.0, 0.0, 1.0, 0.0, 2.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dcumax( 3, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 2.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 2.0, 2.0 ]\n\n\nbase.strided.dcumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum of double-precision floating-point strided\n    array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 1.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumax, base.strided.dcumin, base.strided.scumax\n","base.strided.dcumax.ndarray":"\nbase.strided.dcumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum of double-precision floating-point strided\n    array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 1.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumax, base.strided.dcumin, base.strided.scumax","base.strided.dcumaxabs":"\nbase.strided.dcumaxabs( N, x, strideX, y, strideY )\n    Computes the cumulative maximum absolute value of double-precision floating-\n    point strided array elements.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumaxabs( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.0, 2.0, 2.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcumaxabs( 3, x, 2, y, 2 )\n    <Float64Array>[ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dcumaxabs( 3, x1, 2, y1, 1 )\n    <Float64Array>[ 2.0, 2.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n\nbase.strided.dcumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum absolute value of double-precision floating-\n    point strided array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cumaxabs, base.strided.dcumax, base.strided.dcuminabs, base.strided.scumaxabs\n","base.strided.dcumaxabs.ndarray":"\nbase.strided.dcumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum absolute value of double-precision floating-\n    point strided array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cumaxabs, base.strided.dcumax, base.strided.dcuminabs, base.strided.scumaxabs","base.strided.dcumin":"\nbase.strided.dcumin( N, x, strideX, y, strideY )\n    Computes the cumulative minimum of double-precision floating-point strided\n    array elements.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumin( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.0, -2.0, -2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcumin( 3, x, 2, y, 2 )\n    <Float64Array>[ -2.0, 0.0, -2.0, 0.0, -2.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dcumin( 3, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, -2.0, -2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n\nbase.strided.dcumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum of double-precision floating-point strided\n    array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -2.0, -2.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumin, base.strided.dcumax, base.strided.scumin\n","base.strided.dcumin.ndarray":"\nbase.strided.dcumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum of double-precision floating-point strided\n    array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -2.0, -2.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumin, base.strided.dcumax, base.strided.scumin","base.strided.dcuminabs":"\nbase.strided.dcuminabs( N, x, strideX, y, strideY )\n    Computes the cumulative minimum absolute value of double-precision floating-\n    point strided array elements.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcuminabs( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.0, 1.0, 1.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcuminabs( 3, x, 2, y, 2 )\n    <Float64Array>[ 2.0, 0.0, 1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dcuminabs( 3, x1, 2, y1, 1 )\n    <Float64Array>[ 2.0, 2.0, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 1.0 ]\n\n\nbase.strided.dcuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum absolute value of double-precision floating-\n    point strided array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cuminabs, base.strided.dcumaxabs, base.strided.dcumin, base.strided.scuminabs\n","base.strided.dcuminabs.ndarray":"\nbase.strided.dcuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum absolute value of double-precision floating-\n    point strided array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cuminabs, base.strided.dcumaxabs, base.strided.dcumin, base.strided.scuminabs","base.strided.dcusum":"\nbase.strided.dcusum( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements.\n\n    The `N` and stride parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusum( x.length, 0.0, x, 1, y, 1 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusum( 3, 0.0, x, 2, y, 2 )\n    <Float64Array>[ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dcusum( 3, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumpw, base.strided.gcusum, base.strided.scusum\n","base.strided.dcusum.ndarray":"\nbase.strided.dcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumpw, base.strided.gcusum, base.strided.scusum","base.strided.dcusumkbn":"\nbase.strided.dcusumkbn( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using an improved Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumkbn( x.length, 0.0, x, 1, y, 1 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumkbn( 3, 0.0, x, 2, y, 2 )\n    <Float64Array>[ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dcusumkbn( 3, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusumkbn, base.strided.scusumkbn\n","base.strided.dcusumkbn.ndarray":"\nbase.strided.dcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusumkbn, base.strided.scusumkbn","base.strided.dcusumkbn2":"\nbase.strided.dcusumkbn2( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of double-precision floating-point strided\n    array elements using a second-order iterative Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumkbn2( x.length, 0.0, x, 1, y, 1 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumkbn2( 3, 0.0, x, 2, y, 2 )\n    <Float64Array>[ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dcusumkbn2( 3, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of double-precision floating-point strided\n    array elements using a second-order iterative Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusumkbn2, base.strided.scusumkbn2\n","base.strided.dcusumkbn2.ndarray":"\nbase.strided.dcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of double-precision floating-point strided\n    array elements using a second-order iterative Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusumkbn2, base.strided.scusumkbn2","base.strided.dcusumors":"\nbase.strided.dcusumors( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using ordinary recursive summation.\n\n    The `N` and stride parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumors( x.length, 0.0, x, 1, y, 1 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumors( 3, 0.0, x, 2, y, 2 )\n    <Float64Array>[ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dcusumors( 3, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using ordinary recursive summation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusumors, base.strided.scusumors\n","base.strided.dcusumors.ndarray":"\nbase.strided.dcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using ordinary recursive summation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusumors, base.strided.scusumors","base.strided.dcusumpw":"\nbase.strided.dcusumpw( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using pairwise summation.\n\n    The `N` and stride parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumpw( x.length, 0.0, x, 1, y, 1 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumpw( 3, 0.0, x, 2, y, 2 )\n    <Float64Array>[ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dcusumpw( 3, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusumpw, base.strided.scusumpw\n","base.strided.dcusumpw.ndarray":"\nbase.strided.dcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusumpw, base.strided.scusumpw","base.strided.ddeg2rad":"\nbase.strided.ddeg2rad( N, x, strideX, y, strideY )\n    Converts each element in a double-precision floating-point strided array `x`\n    from degrees to radians and assigns the results to elements in a double-\n    precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.ddeg2rad( x.length, x, 1, y, 1 )\n    <Float64Array>[ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.ddeg2rad( N, x, 2, y, -1 )\n    <Float64Array>[ ~0.785, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.ddeg2rad( N, x1, -2, y1, 1 )\n    <Float64Array>[ ~1.047, ~0.524 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.ddeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Converts each element in a double-precision floating-point strided array `x`\n    from degrees to radians and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.ddeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.ddeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n    See Also\n    --------\n    strided.deg2rad, base.strided.sdeg2rad\n","base.strided.ddeg2rad.ndarray":"\nbase.strided.ddeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Converts each element in a double-precision floating-point strided array `x`\n    from degrees to radians and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.ddeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.ddeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n    See Also\n    --------\n    strided.deg2rad, base.strided.sdeg2rad","base.strided.ddot":"\nbase.strided.ddot( N, x, strideX, y, strideY )\n    Computes the dot product of two double-precision floating-point vectors.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: number\n        Dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var out = base.strided.ddot( x.length, x, 1, y, 1 )\n    -5.0\n\n    // Strides:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > out = base.strided.ddot( 3, x, 2, y, -1 )\n    9.0\n\n    // Using view offsets:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n    > out = base.strided.ddot( 3, x1, -2, y1, 1 )\n    128.0\n\n\nbase.strided.ddot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the dot product of two double-precision floating-point vectors\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing based on a starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: number\n        Dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var out = base.strided.ddot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    -5.0\n\n    // Strides:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > out = base.strided.ddot.ndarray( 3, x, 2, 0, y, 2, 0 )\n    9.0\n\n    // Using offset indices:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > out = base.strided.ddot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n    128.0\n\n    See Also\n    --------\n    base.strided.dsdot, base.strided.gdot, base.strided.sdot, base.strided.sdsdot, ddot\n","base.strided.ddot.ndarray":"\nbase.strided.ddot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the dot product of two double-precision floating-point vectors\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing based on a starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: number\n        Dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var out = base.strided.ddot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    -5.0\n\n    // Strides:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > out = base.strided.ddot.ndarray( 3, x, 2, 0, y, 2, 0 )\n    9.0\n\n    // Using offset indices:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > out = base.strided.ddot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n    128.0\n\n    See Also\n    --------\n    base.strided.dsdot, base.strided.gdot, base.strided.sdot, base.strided.sdsdot, ddot","base.strided.dfill":"\nbase.strided.dfill( N, alpha, x, strideX )\n    Fills a double-precision floating-point strided array with a specified\n    scalar value.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dfill( x.length, 5.0, x, 1 )\n    <Float64Array>[ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dfill( 3, 5.0, x, 2 )\n    <Float64Array>[ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dfill( 3, 5.0, x1, 2 )\n    <Float64Array>[ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n    > x0\n    <Float64Array>[ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.dfill.ndarray( N, alpha, x, strideX, offsetX )\n    Fills a double-precision floating-point strided array with a specified\n    scalar value using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dfill.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float64Array>[ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.dfill.ndarray( 3, 5.0, x, 2, 1 )\n    <Float64Array>[ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n    See Also\n    --------\n    base.strided.gfill, base.strided.sfill\n","base.strided.dfill.ndarray":"\nbase.strided.dfill.ndarray( N, alpha, x, strideX, offsetX )\n    Fills a double-precision floating-point strided array with a specified\n    scalar value using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dfill.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float64Array>[ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.dfill.ndarray( 3, 5.0, x, 2, 1 )\n    <Float64Array>[ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n    See Also\n    --------\n    base.strided.gfill, base.strided.sfill","base.strided.dfloor":"\nbase.strided.dfloor( N, x, strideX, y, strideY )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward negative infinity and assigns the results to elements in a double-\n    precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dfloor( x.length, x, 1, y, 1 )\n    <Float64Array>[ -2.0, 1.0, 3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dfloor( N, x, 2, y, -1 )\n    <Float64Array>[ 3.0, -2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dfloor( N, x1, -2, y1, 1 )\n    <Float64Array>[ 4.0, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 1.0 ]\n\n\nbase.strided.dfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward negative infinity and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ -2.0, 1.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dceil, base.strided.dtrunc, strided.floor, base.strided.sfloor\n","base.strided.dfloor.ndarray":"\nbase.strided.dfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward negative infinity and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ -2.0, 1.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dceil, base.strided.dtrunc, strided.floor, base.strided.sfloor","base.strided.dinv":"\nbase.strided.dinv( N, x, strideX, y, strideY )\n    Computes the multiplicative inverse for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dinv( x.length, x, 1, y, 1 )\n    <Float64Array>[ -0.05, -1.0, 0.5, 0.25 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dinv( N, x, 2, y, -1 )\n    <Float64Array>[ 0.5, -0.05, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dinv( N, x1, -2, y1, 1 )\n    <Float64Array>[ 0.25, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.dinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the multiplicative inverse for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ -0.05, -1.0, 0.5, 0.25 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n    See Also\n    --------\n    strided.inv, base.strided.sinv\n","base.strided.dinv.ndarray":"\nbase.strided.dinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the multiplicative inverse for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ -0.05, -1.0, 0.5, 0.25 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n    See Also\n    --------\n    strided.inv, base.strided.sinv","base.strided.dmap":"\nbase.strided.dmap( N, x, strideX, y, strideY, fcn )\n    Applies a unary function to a double-precision floating-point strided input\n    array and assigns results to a double-precision floating-point strided\n    output array.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap( x.length, x, 1, y, 1, base.identity )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap( 2, x, 2, y, -1, base.identity )\n    <Float64Array>[ 3.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmap( 2, x1, -2, y1, 1, base.identity )\n    <Float64Array>[ 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n    Applies a unary function to a double-precision floating-point strided input\n    array and assigns results to a double-precision floating-point strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identity )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identity )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.smap, base.strided.unary\n","base.strided.dmap.ndarray":"\nbase.strided.dmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n    Applies a unary function to a double-precision floating-point strided input\n    array and assigns results to a double-precision floating-point strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identity )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identity )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.smap, base.strided.unary","base.strided.dmap2":"\nbase.strided.dmap2( N, x, sx, y, sy, z, sz, fcn )\n    Applies a binary function to double-precision floating-point strided input\n    arrays and assigns results to a double-precision floating-point strided\n    output array.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    z: Float64Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float64Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap2( x.length, x, 1, y, 1, z, 1, base.add )\n    <Float64Array>[ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Using `N` and stride parameters:\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap2( 2, x, 2, y, -1, z, 1, base.add )\n    <Float64Array>[ 3.0, 4.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmap2( 2, x1, -2, y1, 1, z1, 1, base.add )\n    <Float64Array>[ 7.0, 6.0 ]\n    > z0\n    <Float64Array>[ 0.0, 0.0, 7.0, 6.0 ]\n\n\nbase.strided.dmap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Float64Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float64Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.add )\n    <Float64Array>[ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.add )\n    <Float64Array>[ 0.0, 6.0, 7.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.smap2, base.strided.binary\n","base.strided.dmap2.ndarray":"\nbase.strided.dmap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Float64Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float64Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.add )\n    <Float64Array>[ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.add )\n    <Float64Array>[ 0.0, 6.0, 7.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.smap2, base.strided.binary","base.strided.dmax":"\nbase.strided.dmax( N, x, strideX )\n    Computes the maximum value of a double-precision floating-point strided\n    array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmax( x.length, x, 1 )\n    2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dmax( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dmax( 3, x1, 2 )\n    2.0\n\n\nbase.strided.dmax.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a double-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmax.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dmax.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dnanmax, base.strided.max, base.strided.smax\n","base.strided.dmax.ndarray":"\nbase.strided.dmax.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a double-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmax.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dmax.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dnanmax, base.strided.max, base.strided.smax","base.strided.dmaxabs":"\nbase.strided.dmaxabs( N, x, strideX )\n    Computes the maximum absolute value of a double-precision floating-point\n    strided array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmaxabs( x.length, x, 1 )\n    2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dmaxabs( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dmaxabs( 3, x1, 2 )\n    2.0\n\n\nbase.strided.dmaxabs.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmaxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dmaxabs.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dminabs, base.strided.dnanmaxabs, base.strided.maxabs, base.strided.smaxabs\n","base.strided.dmaxabs.ndarray":"\nbase.strided.dmaxabs.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmaxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dmaxabs.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dminabs, base.strided.dnanmaxabs, base.strided.maxabs, base.strided.smaxabs","base.strided.dmaxabssorted":"\nbase.strided.dmaxabssorted( N, x, strideX )\n    Computes the maximum absolute value of a sorted double-precision floating-\n    point strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n    > base.strided.dmaxabssorted( x.length, x, 1 )\n    3.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dmaxabssorted( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dmaxabssorted( 3, x1, 2 )\n    3.0\n\n\nbase.strided.dmaxabssorted.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a sorted double-precision floating-\n    point strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n    > base.strided.dmaxabssorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.dmaxabssorted.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmaxabs, base.strided.dmaxsorted, base.strided.smaxabssorted\n","base.strided.dmaxabssorted.ndarray":"\nbase.strided.dmaxabssorted.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a sorted double-precision floating-\n    point strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n    > base.strided.dmaxabssorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.dmaxabssorted.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmaxabs, base.strided.dmaxsorted, base.strided.smaxabssorted","base.strided.dmaxsorted":"\nbase.strided.dmaxsorted( N, x, strideX )\n    Computes the maximum value of a sorted double-precision floating-point\n    strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dmaxsorted( x.length, x, 1 )\n    3.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dmaxsorted( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dmaxsorted( 3, x1, 2 )\n    3.0\n\n\nbase.strided.dmaxsorted.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dmaxsorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.dmaxsorted.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dminsorted, base.strided.maxsorted, base.strided.smaxsorted\n","base.strided.dmaxsorted.ndarray":"\nbase.strided.dmaxsorted.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dmaxsorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.dmaxsorted.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dminsorted, base.strided.maxsorted, base.strided.smaxsorted","base.strided.dmean":"\nbase.strided.dmean( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmean( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dmean( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmean( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.mean, base.strided.smean\n","base.strided.dmean.ndarray":"\nbase.strided.dmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.mean, base.strided.smean","base.strided.dmeankbn":"\nbase.strided.dmeankbn( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeankbn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dmeankbn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmeankbn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dmeankbn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeankbn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeankbn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.meankbn, base.strided.smeankbn\n","base.strided.dmeankbn.ndarray":"\nbase.strided.dmeankbn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeankbn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeankbn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.meankbn, base.strided.smeankbn","base.strided.dmeankbn2":"\nbase.strided.dmeankbn2( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a second-order iterative Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeankbn2( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dmeankbn2( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmeankbn2( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dmeankbn2.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeankbn2.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeankbn2.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.meankbn2, base.strided.smeankbn2\n","base.strided.dmeankbn2.ndarray":"\nbase.strided.dmeankbn2.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeankbn2.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeankbn2.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.meankbn2, base.strided.smeankbn2","base.strided.dmeanli":"\nbase.strided.dmeanli( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanli( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dmeanli( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmeanli( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dmeanli.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanli.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanli.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dmeanlipw, base.strided.smeanli\n","base.strided.dmeanli.ndarray":"\nbase.strided.dmeanli.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanli.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanli.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dmeanlipw, base.strided.smeanli","base.strided.dmeanlipw":"\nbase.strided.dmeanlipw( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm with pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanlipw( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dmeanlipw( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmeanlipw( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dmeanlipw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm with pairwise summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanlipw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanlipw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dmeanli, base.strided.dmeanpw, base.strided.smeanlipw\n","base.strided.dmeanlipw.ndarray":"\nbase.strided.dmeanlipw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm with pairwise summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanlipw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanlipw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dmeanli, base.strided.dmeanpw, base.strided.smeanlipw","base.strided.dmeanors":"\nbase.strided.dmeanors( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using ordinary recursive summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanors( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dmeanors( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmeanors( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dnanmeanors, base.strided.meanors, base.strided.smeanors\n","base.strided.dmeanors.ndarray":"\nbase.strided.dmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dnanmeanors, base.strided.meanors, base.strided.smeanors","base.strided.dmeanpn":"\nbase.strided.dmeanpn( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a two-pass error correction algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanpn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dmeanpn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmeanpn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a two-pass error correction algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dnanmeanpn, base.strided.meanpn, base.strided.smeanpn\n","base.strided.dmeanpn.ndarray":"\nbase.strided.dmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a two-pass error correction algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dnanmeanpn, base.strided.meanpn, base.strided.smeanpn","base.strided.dmeanpw":"\nbase.strided.dmeanpw( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanpw( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dmeanpw( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmeanpw( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dmeanpw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanpw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanpw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dnanmeanpw, base.strided.meanpw, base.strided.smeanpw\n","base.strided.dmeanpw.ndarray":"\nbase.strided.dmeanpw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanpw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanpw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dnanmeanpw, base.strided.meanpw, base.strided.smeanpw","base.strided.dmeanstdev":"\nbase.strided.dmeanstdev( N, c, x, strideX, out, strideOut )\n    Computes the mean and standard deviation of a double-precision floating-\n    point strided array.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns a mean and standard deviation equal to\n    `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanstdev( x.length, 1, x, 1, out, 1 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > out = new Float64Array( 2 );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanstdev( N, 1, x, 2, out, 1 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanstdev( N, 1, x1, 2, out, 1 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\nbase.strided.dmeanstdev.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the mean and standard deviation of a double-precision floating-\n    point strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanstdev.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanstdev.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dmeanvar, base.strided.dstdev\n","base.strided.dmeanstdev.ndarray":"\nbase.strided.dmeanstdev.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the mean and standard deviation of a double-precision floating-\n    point strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanstdev.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanstdev.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dmeanvar, base.strided.dstdev","base.strided.dmeanstdevpn":"\nbase.strided.dmeanstdevpn( N, c, x, strideX, out, strideOut )\n    Computes the mean and standard deviation of a double-precision floating-\n    point strided array using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns a mean and standard deviation equal to\n    `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanstdevpn( x.length, 1, x, 1, out, 1 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > out = new Float64Array( 2 );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanstdevpn( N, 1, x, 2, out, 1 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanstdevpn( N, 1, x1, 2, out, 1 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\nbase.strided.dmeanstdevpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the mean and standard deviation of a double-precision floating-\n    point strided array using a two-pass algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanstdevpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanstdevpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.dmeanstdev, base.strided.dmeanvarpn, base.strided.dstdevpn\n","base.strided.dmeanstdevpn.ndarray":"\nbase.strided.dmeanstdevpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the mean and standard deviation of a double-precision floating-\n    point strided array using a two-pass algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanstdevpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanstdevpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.dmeanstdev, base.strided.dmeanvarpn, base.strided.dstdevpn","base.strided.dmeanvar":"\nbase.strided.dmeanvar( N, c, x, strideX, out, strideOut )\n    Computes the mean and variance of a double-precision floating-point strided\n    array.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns a mean and variance equal to `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanvar( x.length, 1, x, 1, out, 1 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > out = new Float64Array( 2 );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanvar( N, 1, x, 2, out, 1 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanvar( N, 1, x1, 2, out, 1 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\nbase.strided.dmeanvar.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the mean and variance of a double-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanvar.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanvar.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dvariance\n","base.strided.dmeanvar.ndarray":"\nbase.strided.dmeanvar.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the mean and variance of a double-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanvar.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanvar.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dvariance","base.strided.dmeanvarpn":"\nbase.strided.dmeanvarpn( N, c, x, strideX, out, strideOut )\n    Computes the mean and variance of a double-precision floating-point strided\n    array using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns a mean and variance equal to `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanvarpn( x.length, 1, x, 1, out, 1 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > out = new Float64Array( 2 );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanvarpn( N, 1, x, 2, out, 1 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanvarpn( N, 1, x1, 2, out, 1 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\nbase.strided.dmeanvarpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the mean and variance of a double-precision floating-point strided\n    array using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanvarpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanvarpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.dmeanstdevpn, base.strided.dmeanvar, base.strided.dvariancepn\n","base.strided.dmeanvarpn.ndarray":"\nbase.strided.dmeanvarpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the mean and variance of a double-precision floating-point strided\n    array using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanvarpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanvarpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.dmeanstdevpn, base.strided.dmeanvar, base.strided.dvariancepn","base.strided.dmeanwd":"\nbase.strided.dmeanwd( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanwd( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dmeanwd( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmeanwd( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dnanmeanwd, base.strided.meanwd, base.strided.smeanwd\n","base.strided.dmeanwd.ndarray":"\nbase.strided.dmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dnanmeanwd, base.strided.meanwd, base.strided.smeanwd","base.strided.dmediansorted":"\nbase.strided.dmediansorted( N, x, strideX )\n    Computes the median value of a sorted double-precision floating-point\n    strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dmediansorted( x.length, x, 1 )\n    2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dmediansorted( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dmediansorted( 3, x1, 2 )\n    2.0\n\n\nbase.strided.dmediansorted.ndarray( N, x, strideX, offsetX )\n    Computes the median value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.dmediansorted.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.mediansorted, base.strided.smediansorted\n","base.strided.dmediansorted.ndarray":"\nbase.strided.dmediansorted.ndarray( N, x, strideX, offsetX )\n    Computes the median value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.dmediansorted.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.mediansorted, base.strided.smediansorted","base.strided.dmidrange":"\nbase.strided.dmidrange( N, x, strideX )\n    Computes the mid-range of a double-precision floating-point strided array.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Mid-range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmidrange( x.length, x, 1 )\n    0.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dmidrange( 3, x, 2 )\n    0.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dmidrange( 3, x1, 2 )\n    0.0\n\n\nbase.strided.dmidrange.ndarray( N, x, strideX, offsetX )\n    Computes the mid-range of a double-precision floating-point strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Mid-range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmidrange.ndarray( x.length, x, 1, 0 )\n    0.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dmidrange.ndarray( 3, x, 2, 1 )\n    0.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dmean, base.strided.dmin, base.strided.drange, base.strided.smidrange\n","base.strided.dmidrange.ndarray":"\nbase.strided.dmidrange.ndarray( N, x, strideX, offsetX )\n    Computes the mid-range of a double-precision floating-point strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Mid-range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmidrange.ndarray( x.length, x, 1, 0 )\n    0.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dmidrange.ndarray( 3, x, 2, 1 )\n    0.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dmean, base.strided.dmin, base.strided.drange, base.strided.smidrange","base.strided.dmin":"\nbase.strided.dmin( N, x, strideX )\n    Computes the minimum value of a double-precision floating-point strided\n    array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmin( x.length, x, 1 )\n    -2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dmin( 3, x, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmin( N, x1, stride )\n    -2.0\n\n\nbase.strided.dmin.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a double-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dmin.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dnanmin, base.strided.min, base.strided.smin\n","base.strided.dmin.ndarray":"\nbase.strided.dmin.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a double-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dmin.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dnanmin, base.strided.min, base.strided.smin","base.strided.dminabs":"\nbase.strided.dminabs( N, x, strideX )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dminabs( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dminabs( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dminabs( 3, x1, 2 )\n    1.0\n\n\nbase.strided.dminabs.ndarray( N, x, strideX, offsetX )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dminabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dminabs.ndarray( 3, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dmaxabs, base.strided.dnanminabs, base.strided.minabs, base.strided.sminabs\n","base.strided.dminabs.ndarray":"\nbase.strided.dminabs.ndarray( N, x, strideX, offsetX )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dminabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dminabs.ndarray( 3, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dmaxabs, base.strided.dnanminabs, base.strided.minabs, base.strided.sminabs","base.strided.dminsorted":"\nbase.strided.dminsorted( N, x, strideX )\n    Computes the minimum value of a sorted double-precision floating-point\n    strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dminsorted( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dminsorted( 3, x, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dminsorted( 3, x1, 2 )\n    -2.0\n\n\nbase.strided.dminsorted.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dminsorted.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.dminsorted.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dmaxsorted, base.strided.minsorted, base.strided.sminsorted\n","base.strided.dminsorted.ndarray":"\nbase.strided.dminsorted.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dminsorted.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.dminsorted.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dmaxsorted, base.strided.minsorted, base.strided.sminsorted","base.strided.dmskabs":"\nbase.strided.dmskabs( N, x, sx, m, sm, y, sy )\n    Computes the absolute value for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ 2.0, 1.0, 0.0, 5.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskabs( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ 5.0, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 5.0, 1.0 ]\n\n\nbase.strided.dmskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the absolute value for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 2.0, 1.0, 0.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 5.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dabs, base.strided.dmskabs2, base.strided.smskabs\n","base.strided.dmskabs.ndarray":"\nbase.strided.dmskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the absolute value for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 2.0, 1.0, 0.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 5.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dabs, base.strided.dmskabs2, base.strided.smskabs","base.strided.dmskabs2":"\nbase.strided.dmskabs2( N, x, sx, m, sm, y, sy )\n    Computes the squared absolute value for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point\n    strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs2( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ 4.0, 1.0, 0.0, 25.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs2( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, 4.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskabs2( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ 25.0, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 25.0, 1.0 ]\n\n\nbase.strided.dmskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the squared absolute value for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point\n    strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 4.0, 1.0, 0.0, 25.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 25.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dabs2, base.strided.dmskabs, base.strided.smskabs2\n","base.strided.dmskabs2.ndarray":"\nbase.strided.dmskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the squared absolute value for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point\n    strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 4.0, 1.0, 0.0, 25.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 25.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dabs2, base.strided.dmskabs, base.strided.smskabs2","base.strided.dmskcbrt":"\nbase.strided.dmskcbrt( N, x, sx, m, sm, y, sy )\n    Computes the cube root for each element in a double-precision floating-point\n    strided array `x` according to a strided mask array and assigns the results\n    to elements in a double-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskcbrt( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ 0.0, 1.0, 0.0, 3.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskcbrt( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskcbrt( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ 3.0, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.dmskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the cube root for each element in a double-precision floating-point\n    strided array `x` according to a strided mask array and assigns the results\n    to elements in a double-precision floating-point strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, 1.0, 0.0, 3.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dcbrt, base.strided.dmsksqrt, base.strided.smskcbrt\n","base.strided.dmskcbrt.ndarray":"\nbase.strided.dmskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the cube root for each element in a double-precision floating-point\n    strided array `x` according to a strided mask array and assigns the results\n    to elements in a double-precision floating-point strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, 1.0, 0.0, 3.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dcbrt, base.strided.dmsksqrt, base.strided.smskcbrt","base.strided.dmskceil":"\nbase.strided.dmskceil( N, x, sx, m, sm, y, sy )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward positive infinity according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskceil( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ 2.0, 3.0, 0.0, 4.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskceil( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskceil( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ 4.0, 3.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.dmskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward positive infinity according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 2.0, 3.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n    See Also\n    --------\n    base.strided.dceil, base.strided.dmskfloor, base.strided.dmsktrunc, base.strided.smskceil\n","base.strided.dmskceil.ndarray":"\nbase.strided.dmskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward positive infinity according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 2.0, 3.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n    See Also\n    --------\n    base.strided.dceil, base.strided.dmskfloor, base.strided.dmsktrunc, base.strided.smskceil","base.strided.dmskdeg2rad":"\nbase.strided.dmskdeg2rad( N, x, sx, m, sm, y, sy )\n    Converts each element in a double-precision floating-point strided array `x`\n    from degrees to radians according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskdeg2rad( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ 0.0, ~0.524, 0.0, ~1.047 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskdeg2rad( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ ~1.047, ~0.524 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.dmskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Converts each element in a double-precision floating-point strided array `x`\n    from degrees to radians according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, ~0.524, 0.0, ~1.047 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n    See Also\n    --------\n    base.strided.ddeg2rad, base.strided.dmskdeg2rad, base.strided.smskdeg2rad\n","base.strided.dmskdeg2rad.ndarray":"\nbase.strided.dmskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Converts each element in a double-precision floating-point strided array `x`\n    from degrees to radians according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, ~0.524, 0.0, ~1.047 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n    See Also\n    --------\n    base.strided.ddeg2rad, base.strided.dmskdeg2rad, base.strided.smskdeg2rad","base.strided.dmskfloor":"\nbase.strided.dmskfloor( N, x, sx, m, sm, y, sy )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward negative infinity according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskfloor( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskfloor( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskfloor( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dmskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward negative infinity according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dfloor, base.strided.dmskceil, base.strided.dmsktrunc, base.strided.smskfloor\n","base.strided.dmskfloor.ndarray":"\nbase.strided.dmskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward negative infinity according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dfloor, base.strided.dmskceil, base.strided.dmsktrunc, base.strided.smskfloor","base.strided.dmskinv":"\nbase.strided.dmskinv( N, x, sx, m, sm, y, sy )\n    Computes the multiplicative inverse for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskinv( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ -0.05, -1.0, 0.0, 0.25 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskinv( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, -0.05, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskinv( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ 0.25, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.dmskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the multiplicative inverse for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ -0.05, -1.0, 0.0, 0.25 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dinv, base.strided.smskinv\n","base.strided.dmskinv.ndarray":"\nbase.strided.dmskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the multiplicative inverse for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ -0.05, -1.0, 0.0, 0.25 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dinv, base.strided.smskinv","base.strided.dmskmap":"\nbase.strided.dmskmap( N, x, sx, m, sm, y, sy, fcn )\n    Applies a unary function to a double-precision floating-point strided input\n    array according to a strided mask array and assigns results to a double-\n    precision floating-point strided output array.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskmap( x.length, x, 1, m, 1, y, 1, base.identity )\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskmap( 2, x, 2, m, 2, y, -1, base.identity )\n    <Float64Array>[ 0.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\n    <Float64Array>[ 0.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, 2.0 ]\n\n\nbase.strided.dmskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n    Applies a unary function to a double-precision floating-point strided input\n    array according to a strided mask array and assigns results to a double-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n    <Float64Array>[ 0.0, 0.0, 4.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmap, base.strided.dmskmap2, base.strided.mskunary, base.strided.smskmap\n","base.strided.dmskmap.ndarray":"\nbase.strided.dmskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n    Applies a unary function to a double-precision floating-point strided input\n    array according to a strided mask array and assigns results to a double-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n    <Float64Array>[ 0.0, 0.0, 4.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmap, base.strided.dmskmap2, base.strided.mskunary, base.strided.smskmap","base.strided.dmskmap2":"\nbase.strided.dmskmap2( N, x, sx, y, sy, m, sm, z, sz, fcn )\n    Applies a binary function to double-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a double-\n    precision floating-point strided output array.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    z: Float64Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float64Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.dmskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.add )\n    <Float64Array>[ 2.0, 4.0, 0.0, 8.0 ]\n\n    // Using `N` and stride parameters:\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.add )\n    <Float64Array>[ 0.0, 3.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.add )\n    <Float64Array>[ 0.0, 6.0 ]\n    > z0\n    <Float64Array>[ 0.0, 0.0, 0.0, 6.0 ]\n\n\nbase.strided.dmskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n    Applies a binary function to double-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a double-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    z: Float64Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float64Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.dmskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.add )\n    <Float64Array>[ 2.0, 4.0, 0.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.dmskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.add )\n    <Float64Array>[ 0.0, 0.0, 7.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmap2, base.strided.dmskmap, base.strided.smskmap2\n","base.strided.dmskmap2.ndarray":"\nbase.strided.dmskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n    Applies a binary function to double-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a double-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    z: Float64Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float64Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.dmskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.add )\n    <Float64Array>[ 2.0, 4.0, 0.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.dmskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.add )\n    <Float64Array>[ 0.0, 0.0, 7.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmap2, base.strided.dmskmap, base.strided.smskmap2","base.strided.dmskmax":"\nbase.strided.dmskmax( N, x, strideX, mask, strideMask )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask.\n\n    The `N` and stride parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.dmskmax( x.length, x, 1, mask, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.dmskmax( 3, x, 2, mask, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dmskmax( 3, x1, 2, mask1, 2 )\n    2.0\n\n\nbase.strided.dmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.dmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dmskmin, base.strided.dnanmax, base.strided.dnanmskmax, base.strided.mskmax, base.strided.smskmax\n","base.strided.dmskmax.ndarray":"\nbase.strided.dmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.dmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dmskmin, base.strided.dnanmax, base.strided.dnanmskmax, base.strided.mskmax, base.strided.smskmax","base.strided.dmskmin":"\nbase.strided.dmskmin( N, x, strideX, mask, strideMask )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.dmskmin( x.length, x, 1, mask, 1 )\n    -2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.dmskmin( 3, x, 2, mask, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dmskmin( 3, x1, 2, mask1, 2 )\n    -2.0\n\n\nbase.strided.dmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.dmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dmskmax, base.strided.dnanmin, base.strided.dnanmskmin, base.strided.mskmin, base.strided.smskmin\n","base.strided.dmskmin.ndarray":"\nbase.strided.dmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.dmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dmskmax, base.strided.dnanmin, base.strided.dnanmskmin, base.strided.mskmin, base.strided.smskmin","base.strided.dmskramp":"\nbase.strided.dmskramp( N, x, sx, m, sm, y, sy )\n    Evaluates the ramp function for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskramp( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ 1.1, 2.5, 0.0, 4.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskramp( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, 1.1, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskramp( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ 4.0, 2.5 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.5 ]\n\n\nbase.strided.dmskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Evaluates the ramp function for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.1, 2.5, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.5 ]\n\n    See Also\n    --------\n    base.strided.dramp, base.strided.smskramp\n","base.strided.dmskramp.ndarray":"\nbase.strided.dmskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Evaluates the ramp function for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.1, 2.5, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.5 ]\n\n    See Also\n    --------\n    base.strided.dramp, base.strided.smskramp","base.strided.dmskrange":"\nbase.strided.dmskrange( N, x, strideX, mask, strideMask )\n    Computes the range of a double-precision floating-point strided array\n    according to a mask.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.dmskrange( x.length, x, 1, mask, 1 )\n    4.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.dmskrange( 3, x, 2, mask, 2 )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dmskrange( 3, x1, 2, mask1, 2 )\n    4.0\n\n\nbase.strided.dmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a double-precision floating-point strided array\n    according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.dmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.dmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dmskmax, base.strided.dmskmin, base.strided.dnanrange, base.strided.drange, base.strided.mskrange, base.strided.smskrange\n","base.strided.dmskrange.ndarray":"\nbase.strided.dmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a double-precision floating-point strided array\n    according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.dmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.dmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dmskmax, base.strided.dmskmin, base.strided.dnanrange, base.strided.drange, base.strided.mskrange, base.strided.smskrange","base.strided.dmskrsqrt":"\nbase.strided.dmskrsqrt( N, x, sx, m, sm, y, sy )\n    Computes the reciprocal square root for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskrsqrt( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ Infinity, 0.5, 0.0, ~0.289 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskrsqrt( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, Infinity, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ ~0.289, 0.5 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.dmskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the reciprocal square root for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ Infinity, 0.5, 0.0, ~0.289 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n    See Also\n    --------\n    base.strided.dmsksqrt, base.strided.dsqrt, base.strided.smskrsqrt\n","base.strided.dmskrsqrt.ndarray":"\nbase.strided.dmskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the reciprocal square root for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ Infinity, 0.5, 0.0, ~0.289 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n    See Also\n    --------\n    base.strided.dmsksqrt, base.strided.dsqrt, base.strided.smskrsqrt","base.strided.dmsksqrt":"\nbase.strided.dmsksqrt( N, x, sx, m, sm, y, sy )\n    Computes the principal square root for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsksqrt( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ 0.0, 2.0, 0.0, ~3.464 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsksqrt( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmsksqrt( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ ~3.464, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.dmsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the principal square root for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, 2.0, 0.0, ~3.464 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmskcbrt, base.strided.dmskrsqrt, base.strided.dsqrt, base.strided.smsksqrt\n","base.strided.dmsksqrt.ndarray":"\nbase.strided.dmsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the principal square root for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, 2.0, 0.0, ~3.464 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmskcbrt, base.strided.dmskrsqrt, base.strided.dsqrt, base.strided.smsksqrt","base.strided.dmsktrunc":"\nbase.strided.dmsktrunc( N, x, sx, m, sm, y, sy )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward zero according to a strided mask array and assigns the results to\n    elements in a double-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsktrunc( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsktrunc( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmsktrunc( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dmsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward zero according to a strided mask array and assigns the results to\n    elements in a double-precision floating-point strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmskceil, base.strided.dmskfloor, base.strided.dtrunc, base.strided.smsktrunc\n","base.strided.dmsktrunc.ndarray":"\nbase.strided.dmsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward zero according to a strided mask array and assigns the results to\n    elements in a double-precision floating-point strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmskceil, base.strided.dmskfloor, base.strided.dtrunc, base.strided.smsktrunc","base.strided.dnanasum":"\nbase.strided.dnanasum( N, x, strideX )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements, ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanasum( x.length, x, 1 )\n    5.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.dnanasum( 4, x, 2 )\n    5.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnanasum( 4, x1, 2 )\n    5.0\n\n\nbase.strided.dnanasum.ndarray( N, x, strideX, offsetX )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements, ignoring `NaN` values and using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanasum.ndarray( x.length, x, 1, 0 )\n    5.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnanasum.ndarray( 4, x, 2, 1 )\n    5.0\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.dasumpw","base.strided.dnanasum.ndarray":"\nbase.strided.dnanasum.ndarray( N, x, strideX, offsetX )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements, ignoring `NaN` values and using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanasum.ndarray( x.length, x, 1, 0 )\n    5.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnanasum.ndarray( 4, x, 2, 1 )\n    5.0\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.dasumpw","base.strided.dnanasumors":"\nbase.strided.dnanasumors( N, x, strideX )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements, ignoring `NaN` values and using ordinary\n    recursive summation.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanasumors( x.length, x, 1 )\n    5.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanasumors( N, x, stride )\n    5.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanasumors( N, x1, stride )\n    5.0\n\n\nbase.strided.dnanasumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements, ignoring `NaN` values and using ordinary\n    recursive summation alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanasumors.ndarray( x.length, x, 1, 0 )\n    5.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanasumors.ndarray( N, x, 2, 1 )\n    5.0\n\n    See Also\n    --------\n    base.strided.dnanasum\n","base.strided.dnanasumors.ndarray":"\nbase.strided.dnanasumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements, ignoring `NaN` values and using ordinary\n    recursive summation alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanasumors.ndarray( x.length, x, 1, 0 )\n    5.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanasumors.ndarray( N, x, 2, 1 )\n    5.0\n\n    See Also\n    --------\n    base.strided.dnanasum","base.strided.dnanmax":"\nbase.strided.dnanmax( N, x, strideX )\n    Computes the maximum value of a double-precision floating-point strided\n    array, ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmax( x.length, x, 1 )\n    2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > base.strided.dnanmax( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnanmax( 3, x1, 2 )\n    2.0\n\n\nbase.strided.dnanmax.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a double-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.dnanmax.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanmax.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dnanmin, base.strided.nanmax, base.strided.snanmax\n","base.strided.dnanmax.ndarray":"\nbase.strided.dnanmax.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a double-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.dnanmax.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanmax.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dnanmin, base.strided.nanmax, base.strided.snanmax","base.strided.dnanmaxabs":"\nbase.strided.dnanmaxabs( N, x, strideX )\n    Computes the maximum absolute value of a double-precision floating-point\n    strided array, ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmaxabs( x.length, x, 1 )\n    2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > base.strided.dnanmaxabs( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnanmaxabs( 3, x1, 2 )\n    2.0\n\n\nbase.strided.dnanmaxabs.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a double-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.dnanmaxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanmaxabs.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmaxabs, base.strided.dnanmax, base.strided.dnanminabs, base.strided.nanmaxabs, base.strided.snanmaxabs\n","base.strided.dnanmaxabs.ndarray":"\nbase.strided.dnanmaxabs.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a double-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.dnanmaxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanmaxabs.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmaxabs, base.strided.dnanmax, base.strided.dnanminabs, base.strided.nanmaxabs, base.strided.snanmaxabs","base.strided.dnanmean":"\nbase.strided.dnanmean( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmean( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanmean( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanmean( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dnanmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.nanmean, base.strided.snanmean\n","base.strided.dnanmean.ndarray":"\nbase.strided.dnanmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.nanmean, base.strided.snanmean","base.strided.dnanmeanors":"\nbase.strided.dnanmeanors( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanors( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanmeanors( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanmeanors( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dnanmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanors, base.strided.dnanmean, base.strided.nanmeanors, base.strided.snanmeanors\n","base.strided.dnanmeanors.ndarray":"\nbase.strided.dnanmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanors, base.strided.dnanmean, base.strided.nanmeanors, base.strided.snanmeanors","base.strided.dnanmeanpn":"\nbase.strided.dnanmeanpn( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction\n    algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanpn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanmeanpn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanmeanpn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dnanmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction algorithm\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.dnanmean, base.strided.nanmeanpn, base.strided.snanmeanpn\n","base.strided.dnanmeanpn.ndarray":"\nbase.strided.dnanmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction algorithm\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.dnanmean, base.strided.nanmeanpn, base.strided.snanmeanpn","base.strided.dnanmeanpw":"\nbase.strided.dnanmeanpw( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanpw( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanmeanpw( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanmeanpw( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dnanmeanpw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using pairwise summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanpw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmeanpw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpw, base.strided.dnanmean\n","base.strided.dnanmeanpw.ndarray":"\nbase.strided.dnanmeanpw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using pairwise summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanpw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmeanpw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpw, base.strided.dnanmean","base.strided.dnanmeanwd":"\nbase.strided.dnanmeanwd( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, using Welford's algorithm and ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanwd( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanmeanwd( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanmeanwd( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dnanmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanwd, base.strided.dnanmean, base.strided.nanmeanwd, base.strided.snanmeanwd\n","base.strided.dnanmeanwd.ndarray":"\nbase.strided.dnanmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanwd, base.strided.dnanmean, base.strided.nanmeanwd, base.strided.snanmeanwd","base.strided.dnanmin":"\nbase.strided.dnanmin( N, x, strideX )\n    Computes the minimum value of a double-precision floating-point strided\n    array, ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmin( x.length, x, 1 )\n    -2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > base.strided.dnanmin( 3, x, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnanmin( 3, x1, 2 )\n    -2.0\n\n\nbase.strided.dnanmin.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a double-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.dnanmin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanmin.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dnanmax, base.strided.nanmin, base.strided.snanmin\n","base.strided.dnanmin.ndarray":"\nbase.strided.dnanmin.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a double-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.dnanmin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanmin.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dnanmax, base.strided.nanmin, base.strided.snanmin","base.strided.dnanminabs":"\nbase.strided.dnanminabs( N, x, strideX )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array, ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanminabs( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > base.strided.dnanminabs( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnanminabs( 3, x1, 2 )\n    1.0\n\n\nbase.strided.dnanminabs.ndarray( N, x, strideX, offsetX )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.dnanminabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanminabs.ndarray( 3, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dminabs, base.strided.dnanmaxabs, base.strided.dnanmin, base.strided.nanminabs, base.strided.snanminabs\n","base.strided.dnanminabs.ndarray":"\nbase.strided.dnanminabs.ndarray( N, x, strideX, offsetX )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.dnanminabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanminabs.ndarray( 3, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dminabs, base.strided.dnanmaxabs, base.strided.dnanmin, base.strided.nanminabs, base.strided.snanminabs","base.strided.dnanmskmax":"\nbase.strided.dnanmskmax( N, x, strideX, mask, strideMask )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n    > base.strided.dnanmskmax( x.length, x, 1, mask, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmskmax( N, x, 2, mask, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dnanmskmax( N, x1, 2, mask1, 2 )\n    2.0\n\nbase.strided.dnanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.dnanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmskmax, base.strided.dnanmax, base.strided.dnanmskmin, base.strided.nanmskmax, base.strided.snanmskmax\n","base.strided.dnanmskmax.ndarray":"\nbase.strided.dnanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.dnanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmskmax, base.strided.dnanmax, base.strided.dnanmskmin, base.strided.nanmskmax, base.strided.snanmskmax","base.strided.dnanmskmin":"\nbase.strided.dnanmskmin( N, x, strideX, mask, strideMask )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n    > base.strided.dnanmskmin( x.length, x, 1, mask, 1 )\n    -2.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmskmin( N, x, 2, mask, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dnanmskmin( N, x1, 2, mask1, 2 )\n    -2.0\n\nbase.strided.dnanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.dnanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmskmin, base.strided.dnanmin, base.strided.dnanmskmax, base.strided.nanmskmin, base.strided.snanmskmin\n","base.strided.dnanmskmin.ndarray":"\nbase.strided.dnanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.dnanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmskmin, base.strided.dnanmin, base.strided.dnanmskmax, base.strided.nanmskmin, base.strided.snanmskmin","base.strided.dnanmskrange":"\nbase.strided.dnanmskrange( N, x, strideX, mask, strideMask )\n    Computes the range of a double-precision floating-point strided array\n    according to a mask, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n    > base.strided.dnanmskrange( x.length, x, 1, mask, 1 )\n    4.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmskrange( N, x, 2, mask, 2 )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dnanmskrange( N, x1, 2, mask1, 2 )\n    4.0\n\nbase.strided.dnanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a double-precision floating-point strided array\n    according to a mask, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.dnanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dmskrange, base.strided.dnanrange, base.strided.dnanmskmax, base.strided.dnanmskmin, base.strided.nanmskrange, base.strided.snanmskrange\n","base.strided.dnanmskrange.ndarray":"\nbase.strided.dnanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a double-precision floating-point strided array\n    according to a mask, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.dnanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dmskrange, base.strided.dnanrange, base.strided.dnanmskmax, base.strided.dnanmskmin, base.strided.nanmskrange, base.strided.snanmskrange","base.strided.dnannsum":"\nbase.strided.dnannsum( N, x, strideX, out, strideOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns a sum equal to `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsum( x.length, x, 1, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsum( 4, x, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsum( 4, x1, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n\nbase.strided.dnannsum.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsum.ndarray( x.length, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsum.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.dsum","base.strided.dnannsum.ndarray":"\nbase.strided.dnannsum.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsum.ndarray( x.length, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsum.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.dsum","base.strided.dnannsumkbn":"\nbase.strided.dnannsumkbn( N, x, strideX, out, strideOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns a sum equal to `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn( x.length, x, 1, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn( 4, x, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn( 4, x1, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n\nbase.strided.dnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn.ndarray( 4, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsum, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn, base.strided.gnannsumkbn\n","base.strided.dnannsumkbn.ndarray":"\nbase.strided.dnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn.ndarray( 4, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsum, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn, base.strided.gnannsumkbn","base.strided.dnannsumkbn2":"\nbase.strided.dnannsumkbn2( N, x, strideX, out, strideOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm.\n\n    The `N` and stride parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns a sum equal to `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn2( x.length, x, 1, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn2( 4, x, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn2( 4, x1, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n\nbase.strided.dnannsumkbn2.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn2.ndarray( 4, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn2.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn2\n","base.strided.dnannsumkbn2.ndarray":"\nbase.strided.dnannsumkbn2.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn2.ndarray( 4, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn2.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn2","base.strided.dnannsumors":"\nbase.strided.dnannsumors( N, x, strideX, out, strideOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation.\n\n    The `N` and stride parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns a sum equal to `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumors( x.length, x, 1, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumors( 4, x, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumors( 4, x1, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n\nbase.strided.dnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumpw, base.strided.dsumors\n","base.strided.dnannsumors.ndarray":"\nbase.strided.dnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumpw, base.strided.dsumors","base.strided.dnannsumpw":"\nbase.strided.dnannsumpw( N, x, strideX, out, strideOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation.\n\n    The `N` and stride parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns a sum equal to `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumpw( x.length, x, 1, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumpw( 4, x, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumpw( 4, x1, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n\nbase.strided.dnannsumpw.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for the strided array.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumpw.ndarray( x.length, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumpw.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dsumpw\n","base.strided.dnannsumpw.ndarray":"\nbase.strided.dnannsumpw.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for the strided array.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumpw.ndarray( x.length, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumpw.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dsumpw","base.strided.dnanrange":"\nbase.strided.dnanrange( N, x, strideX )\n    Computes the range of a double-precision floating-point strided array,\n    ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanrange( x.length, x, 1 )\n    4.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > base.strided.dnanrange( 3, x, 2 )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnanrange( 3, x1, 2 )\n    4.0\n\n\nbase.strided.dnanrange.ndarray( N, x, strideX, offsetX )\n    Computes the range of a double-precision floating-point strided array,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.dnanrange.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanrange.ndarray( 3, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dnanmax, base.strided.dnanmin, base.strided.drange, base.strided.nanrange, base.strided.snanrange\n","base.strided.dnanrange.ndarray":"\nbase.strided.dnanrange.ndarray( N, x, strideX, offsetX )\n    Computes the range of a double-precision floating-point strided array,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.dnanrange.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanrange.ndarray( 3, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dnanmax, base.strided.dnanmin, base.strided.drange, base.strided.nanrange, base.strided.snanrange","base.strided.dnanstdev":"\nbase.strided.dnanstdev( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdev( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanstdev( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanstdev( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dnanstdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanvariance, base.strided.dstdev, base.strided.nanstdev, base.strided.snanstdev\n","base.strided.dnanstdev.ndarray":"\nbase.strided.dnanstdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanvariance, base.strided.dstdev, base.strided.nanstdev, base.strided.snanstdev","base.strided.dnanstdevch":"\nbase.strided.dnanstdevch( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevch( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanstdevch( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanstdevch( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dnanstdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dnanvariancech, base.strided.dstdevch, base.strided.nanstdevch, base.strided.snanstdevch\n","base.strided.dnanstdevch.ndarray":"\nbase.strided.dnanstdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dnanvariancech, base.strided.dstdevch, base.strided.nanstdevch, base.strided.snanstdevch","base.strided.dnanstdevpn":"\nbase.strided.dnanstdevpn( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevpn( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanstdevpn( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanstdevpn( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dnanstdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.snanstdevpn\n","base.strided.dnanstdevpn.ndarray":"\nbase.strided.dnanstdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.snanstdevpn","base.strided.dnanstdevtk":"\nbase.strided.dnanstdevtk( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevtk( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanstdevtk( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanstdevtk( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dnanstdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.snanstdevtk\n","base.strided.dnanstdevtk.ndarray":"\nbase.strided.dnanstdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.snanstdevtk","base.strided.dnanstdevwd":"\nbase.strided.dnanstdevwd( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevwd( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanstdevwd( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanstdevwd( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dnanstdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.snanstdevwd\n","base.strided.dnanstdevwd.ndarray":"\nbase.strided.dnanstdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.snanstdevwd","base.strided.dnanstdevyc":"\nbase.strided.dnanstdevyc( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass algorithm proposed by\n    Youngs and Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevyc( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanstdevyc( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanstdevyc( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dnanstdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass algorithm proposed by\n    Youngs and Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.snanstdevyc\n","base.strided.dnanstdevyc.ndarray":"\nbase.strided.dnanstdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass algorithm proposed by\n    Youngs and Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.snanstdevyc","base.strided.dnansum":"\nbase.strided.dnansum( N, x, strideX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansum( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansum( 4, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnansum( 4, x1, 2 )\n    -1.0\n\n\nbase.strided.dnansum.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansum.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.dsum, base.strided.snansum, base.strided.gnansum\n","base.strided.dnansum.ndarray":"\nbase.strided.dnansum.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansum.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.dsum, base.strided.snansum, base.strided.gnansum","base.strided.dnansumkbn":"\nbase.strided.dnansumkbn( N, x, strideX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumkbn( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumkbn( 4, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnansumkbn( 4, x1, 2 )\n    -1.0\n\n\nbase.strided.dnansumkbn.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumkbn.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.snansumkbn\n","base.strided.dnansumkbn.ndarray":"\nbase.strided.dnansumkbn.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumkbn.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.snansumkbn","base.strided.dnansumkbn2":"\nbase.strided.dnansumkbn2( N, x, strideX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm.\n\n    The `N` and stride parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumkbn2( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumkbn2( 4, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnansumkbn2( 4, x1, 2 )\n    -1.0\n\n\nbase.strided.dnansumkbn2.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumkbn2.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.snansumkbn2\n","base.strided.dnansumkbn2.ndarray":"\nbase.strided.dnansumkbn2.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumkbn2.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.snansumkbn2","base.strided.dnansumors":"\nbase.strided.dnansumors( N, x, strideX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumors( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumors( 4, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnansumors( 4, x1, 2 )\n    -1.0\n\n\nbase.strided.dnansumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumors.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumpw, base.strided.dsumors, base.strided.gnansumors, base.strided.snansumors\n","base.strided.dnansumors.ndarray":"\nbase.strided.dnansumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumors.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumpw, base.strided.dsumors, base.strided.gnansumors, base.strided.snansumors","base.strided.dnansumpw":"\nbase.strided.dnansumpw( N, x, strideX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumpw( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumpw( 4, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnansumpw( 4, x1, 2 )\n    -1.0\n\n\nbase.strided.dnansumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumpw.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumors, base.strided.dsumpw, base.strided.gnansumpw, base.strided.snansumpw\n","base.strided.dnansumpw.ndarray":"\nbase.strided.dnansumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumpw.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumors, base.strided.dsumpw, base.strided.gnansumpw, base.strided.snansumpw","base.strided.dnanvariance":"\nbase.strided.dnanvariance( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariance( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanvariance( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanvariance( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dnanvariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dvariance, base.strided.nanvariance, base.strided.snanvariance\n","base.strided.dnanvariance.ndarray":"\nbase.strided.dnanvariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dvariance, base.strided.nanvariance, base.strided.snanvariance","base.strided.dnanvariancech":"\nbase.strided.dnanvariancech( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancech( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanvariancech( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanvariancech( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dnanvariancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvariancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancech, base.strided.dnanvariance, base.strided.nanvariancech, base.strided.snanvariancech\n","base.strided.dnanvariancech.ndarray":"\nbase.strided.dnanvariancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvariancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancech, base.strided.dnanvariance, base.strided.nanvariancech, base.strided.snanvariancech","base.strided.dnanvariancepn":"\nbase.strided.dnanvariancepn( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancepn( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanvariancepn( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanvariancepn( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dnanvariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancepn, base.strided.dnanvariance, base.strided.nanvariancepn, base.strided.snanvariancepn\n","base.strided.dnanvariancepn.ndarray":"\nbase.strided.dnanvariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancepn, base.strided.dnanvariance, base.strided.nanvariancepn, base.strided.snanvariancepn","base.strided.dnanvariancetk":"\nbase.strided.dnanvariancetk( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancetk( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanvariancetk( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanvariancetk( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dnanvariancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvariancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancetk, base.strided.dnanvariance, base.strided.nanvariancetk, base.strided.snanvariancetk\n","base.strided.dnanvariancetk.ndarray":"\nbase.strided.dnanvariancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvariancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancetk, base.strided.dnanvariance, base.strided.nanvariancetk, base.strided.snanvariancetk","base.strided.dnanvariancewd":"\nbase.strided.dnanvariancewd( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancewd( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanvariancewd( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanvariancewd( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dnanvariancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using Welford's algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvariancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancewd, base.strided.dnanvariance, base.strided.nanvariancewd, base.strided.snanvariancewd\n","base.strided.dnanvariancewd.ndarray":"\nbase.strided.dnanvariancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using Welford's algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvariancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancewd, base.strided.dnanvariance, base.strided.nanvariancewd, base.strided.snanvariancewd","base.strided.dnanvarianceyc":"\nbase.strided.dnanvarianceyc( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n    Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvarianceyc( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanvarianceyc( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanvarianceyc( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dnanvarianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n    Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvarianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvarianceyc, base.strided.dnanvariance, base.strided.nanvarianceyc, base.strided.snanvarianceyc\n","base.strided.dnanvarianceyc.ndarray":"\nbase.strided.dnanvarianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n    Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvarianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvarianceyc, base.strided.dnanvariance, base.strided.nanvarianceyc, base.strided.snanvarianceyc","base.strided.dnrm2":"\nbase.strided.dnrm2( N, x, stride )\n    Computes the L2-norm of a double-precision floating-point vector.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    nrm2: number\n        The L2-norm.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dnrm2( x.length, x, 1 )\n    3.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dnrm2( 3, x, 2 )\n    3.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnrm2( 3, x1, 2 )\n    3.0\n\n\nbase.strided.dnrm2.ndarray( N, x, stride, offset )\n    Computes the L2-norm of a double-precision floating-point vector using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    nrm2: number\n        The L2-norm.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dnrm2.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dnrm2.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.gnrm2, base.strided.snrm2\n","base.strided.dnrm2.ndarray":"\nbase.strided.dnrm2.ndarray( N, x, stride, offset )\n    Computes the L2-norm of a double-precision floating-point vector using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    nrm2: number\n        The L2-norm.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dnrm2.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dnrm2.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.gnrm2, base.strided.snrm2","base.strided.dramp":"\nbase.strided.dramp( N, x, strideX, y, strideY )\n    Evaluates the ramp function for each element in a double-precision floating-\n    point strided array `x` and assigns the results to elements in a double-\n    precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dramp( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.1, 2.5, 0.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dramp( N, x, 2, y, -1 )\n    <Float64Array>[ 0.0, 1.1, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dramp( N, x1, -2, y1, 1 )\n    <Float64Array>[ 4.0, 2.5 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.5 ]\n\n\nbase.strided.dramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Evaluates the ramp function for each element in a double-precision floating-\n    point strided array `x` and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.1, 2.5, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.5 ]\n\n    See Also\n    --------\n    strided.ramp, base.strided.sramp\n","base.strided.dramp.ndarray":"\nbase.strided.dramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Evaluates the ramp function for each element in a double-precision floating-\n    point strided array `x` and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.1, 2.5, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.5 ]\n\n    See Also\n    --------\n    strided.ramp, base.strided.sramp","base.strided.drange":"\nbase.strided.drange( N, x, strideX )\n    Computes the range of a double-precision floating-point strided array.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.drange( x.length, x, 1 )\n    4.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.drange( 3, x, 2 )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > stride = 2;\n    > base.strided.drange( 3, x1, 2 )\n    4.0\n\n\nbase.strided.drange.ndarray( N, x, strideX, offsetX )\n    Computes the range of a double-precision floating-point strided array using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.drange.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.drange.ndarray( 3, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dmin, base.strided.dnanrange, base.strided.range, base.strided.srange\n","base.strided.drange.ndarray":"\nbase.strided.drange.ndarray( N, x, strideX, offsetX )\n    Computes the range of a double-precision floating-point strided array using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.drange.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.drange.ndarray( 3, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dmin, base.strided.dnanrange, base.strided.range, base.strided.srange","base.strided.drev":"\nbase.strided.drev( N, x, strideX )\n    Reverses a double-precision floating-point strided array in-place.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.drev( x.length, x, 1 )\n    <Float64Array>[ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.drev( 3, x, 2 )\n    <Float64Array>[ 4.0, 1.0, 3.0, -5.0, -2.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.drev( 3, x1, 2 )\n    <Float64Array>[ -6.0, 3.0, -4.0, 5.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n\nbase.strided.drev.ndarray( N, x, strideX, offsetX )\n    Reverses a double-precision floating-point strided array in-place using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.drev.ndarray( x.length, x, 1, 0 )\n    <Float64Array>[ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.drev.ndarray( 3, x, 2, 1 )\n    <Float64Array>[ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.grev, base.strided.srev\n","base.strided.drev.ndarray":"\nbase.strided.drev.ndarray( N, x, strideX, offsetX )\n    Reverses a double-precision floating-point strided array in-place using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.drev.ndarray( x.length, x, 1, 0 )\n    <Float64Array>[ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.drev.ndarray( 3, x, 2, 1 )\n    <Float64Array>[ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.grev, base.strided.srev","base.strided.drsqrt":"\nbase.strided.drsqrt( N, x, strideX, y, strideY )\n    Computes the reciprocal square root for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.drsqrt( x.length, x, 1, y, 1 )\n    <Float64Array>[ Infinity, 0.5, ~0.333, ~0.289 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.drsqrt( N, x, 2, y, -1 )\n    <Float64Array>[ ~0.333, Infinity, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.drsqrt( N, x1, -2, y1, 1 )\n    <Float64Array>[ ~0.289, 0.5 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.drsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the reciprocal square root for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.drsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ Infinity, 0.5, ~0.333, ~0.289 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.drsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n    See Also\n    --------\n    base.strided.dsqrt, strided.rsqrt, base.strided.srsqrt\n","base.strided.drsqrt.ndarray":"\nbase.strided.drsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the reciprocal square root for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.drsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ Infinity, 0.5, ~0.333, ~0.289 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.drsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n    See Also\n    --------\n    base.strided.dsqrt, strided.rsqrt, base.strided.srsqrt","base.strided.dsapxsum":"\nbase.strided.dsapxsum( N, alpha, x, strideX )\n    Adds a scalar constant to each single-precision floating-point strided array\n    element, and computes the sum using extended accumulation and returning\n    an extended precision result.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsapxsum( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dsapxsum( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsapxsum( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.dsapxsum.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each single-precision floating-point strided array\n    element, and computes the sum using pairwise summation with extended\n    accumulation and alternative indexing semantics and returning an extended\n    precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.dssum, base.strided.sapxsum\n","base.strided.dsapxsum.ndarray":"\nbase.strided.dsapxsum.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each single-precision floating-point strided array\n    element, and computes the sum using pairwise summation with extended\n    accumulation and alternative indexing semantics and returning an extended\n    precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.dssum, base.strided.sapxsum","base.strided.dsapxsumpw":"\nbase.strided.dsapxsumpw( N, alpha, x, strideX )\n    Adds a constant to each single-precision floating-point strided array\n    element, and computes the sum using pairwise summation with extended\n    accumulation and returning an extended precision result.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsapxsumpw( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dsapxsumpw( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsapxsumpw( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.dsapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a constant to each single-precision floating-point strided array\n    element, and computes the sum using pairwise summation with extended\n    accumulation and alternative indexing semantics and returning an extended\n    precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumpw, base.strided.dsapxsum, base.strided.dssumpw, base.strided.sapxsumpw\n","base.strided.dsapxsumpw.ndarray":"\nbase.strided.dsapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a constant to each single-precision floating-point strided array\n    element, and computes the sum using pairwise summation with extended\n    accumulation and alternative indexing semantics and returning an extended\n    precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumpw, base.strided.dsapxsum, base.strided.dssumpw, base.strided.sapxsumpw","base.strided.dscal":"\nbase.strided.dscal( N, alpha, x, stride )\n    Multiplies a double-precision floating-point vector `x` by a constant\n    `alpha`.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dscal( x.length, 5.0, x, 1 )\n    <Float64Array>[ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dscal( 3, 5.0, x, 2 )\n    <Float64Array>[ -10.0, 1.0, 15.0, -5.0, 20.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dscal( 3, 5.0, x1, 2 )\n    <Float64Array>[ -10.0, 3.0, -20.0, 5.0, -30.0 ]\n    > x0\n    <Float64Array>[ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n\nbase.strided.dscal.ndarray( N, alpha, x, stride, offset )\n    Multiplies a double-precision floating-point vector `x` by a constant\n    `alpha` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dscal.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float64Array>[ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.dscal.ndarray( 3, 5.0, x, 2, 1 )\n    <Float64Array>[ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n    See Also\n    --------\n    base.strided.daxpy, base.strided.gscal, base.strided.sscal, base.strided.saxpy\n","base.strided.dscal.ndarray":"\nbase.strided.dscal.ndarray( N, alpha, x, stride, offset )\n    Multiplies a double-precision floating-point vector `x` by a constant\n    `alpha` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dscal.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float64Array>[ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.dscal.ndarray( 3, 5.0, x, 2, 1 )\n    <Float64Array>[ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n    See Also\n    --------\n    base.strided.daxpy, base.strided.gscal, base.strided.sscal, base.strided.saxpy","base.strided.dsdot":"\nbase.strided.dsdot( N, x, strideX, y, strideY )\n    Computes the dot product of two single-precision floating-point vectors with\n    extended accumulation and result.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0` the function returns `0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    dot: number\n        Dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var dot = base.strided.dsdot( x.length, x, 1, y, 1 )\n    -5.0\n\n    // Strides:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > dot = base.strided.dsdot( 3, x, 2, y, -1 )\n    9.0\n\n    // Using view offsets:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n    > dot = base.strided.dsdot( 3, x1, -2, y1, 1 )\n    128.0\n\n\nbase.strided.dsdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the dot product of two single-precision floating-point vectors\n    using alternative indexing semantics and with extended accumulation and\n    result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing based on a starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    dot: number\n        Dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var dot = base.strided.dsdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    -5.0\n\n    // Strides:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > dot = base.strided.dsdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n    9.0\n\n    // Using offset indices:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > dot = base.strided.dsdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n    128.0\n\n    References\n    ----------\n    - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n    Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n    Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n    NY, USA: Association for Computing Machinery: 324–25.\n    doi:10.1145/355841.355848.\n\n    See Also\n    --------\n    base.strided.ddot, base.strided.sdot, base.strided.sdsdot\n","base.strided.dsdot.ndarray":"\nbase.strided.dsdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the dot product of two single-precision floating-point vectors\n    using alternative indexing semantics and with extended accumulation and\n    result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing based on a starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    dot: number\n        Dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var dot = base.strided.dsdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    -5.0\n\n    // Strides:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > dot = base.strided.dsdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n    9.0\n\n    // Using offset indices:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > dot = base.strided.dsdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n    128.0\n\n    References\n    ----------\n    - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n    Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n    Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n    NY, USA: Association for Computing Machinery: 324–25.\n    doi:10.1145/355841.355848.\n\n    See Also\n    --------\n    base.strided.ddot, base.strided.sdot, base.strided.sdsdot","base.strided.dsem":"\nbase.strided.dsem( N, correction, x, stride )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsem( x.length, 1, x, 1 )\n    ~1.20185\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsem( N, 1, x, stride )\n    ~1.20185\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsem( N, 1, x1, stride )\n    ~1.20185\n\nbase.strided.dsem.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsem.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsem.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dstdev\n","base.strided.dsem.ndarray":"\nbase.strided.dsem.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsem.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsem.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dstdev","base.strided.dsemch":"\nbase.strided.dsemch( N, correction, x, stride )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemch( x.length, 1, x, 1 )\n    ~1.20185\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsemch( N, 1, x, stride )\n    ~1.20185\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsemch( N, 1, x1, stride )\n    ~1.20185\n\nbase.strided.dsemch.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass trial mean algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemch.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsemch.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dsem, base.strided.dstdevch\n","base.strided.dsemch.ndarray":"\nbase.strided.dsemch.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass trial mean algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemch.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsemch.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dsem, base.strided.dstdevch","base.strided.dsempn":"\nbase.strided.dsempn( N, correction, x, stride )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsempn( x.length, 1, x, 1 )\n    ~1.20185\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsempn( N, 1, x, stride )\n    ~1.20185\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsempn( N, 1, x1, stride )\n    ~1.20185\n\nbase.strided.dsempn.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a two-pass algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsempn.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsempn.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dsem, base.strided.dstdevpn\n","base.strided.dsempn.ndarray":"\nbase.strided.dsempn.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a two-pass algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsempn.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsempn.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dsem, base.strided.dstdevpn","base.strided.dsemtk":"\nbase.strided.dsemtk( N, correction, x, stride )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemtk( x.length, 1, x, 1 )\n    ~1.20185\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsemtk( N, 1, x, stride )\n    ~1.20185\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsemtk( N, 1, x1, stride )\n    ~1.20185\n\nbase.strided.dsemtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass textbook algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemtk.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsemtk.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dsem, base.strided.dstdevtk\n","base.strided.dsemtk.ndarray":"\nbase.strided.dsemtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass textbook algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemtk.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsemtk.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dsem, base.strided.dstdevtk","base.strided.dsemwd":"\nbase.strided.dsemwd( N, correction, x, stride )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemwd( x.length, 1, x, 1 )\n    ~1.20185\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsemwd( N, 1, x, stride )\n    ~1.20185\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsemwd( N, 1, x1, stride )\n    ~1.20185\n\nbase.strided.dsemwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using Welford's algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemwd.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsemwd.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dsem, base.strided.dstdevwd\n","base.strided.dsemwd.ndarray":"\nbase.strided.dsemwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using Welford's algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemwd.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsemwd.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dsem, base.strided.dstdevwd","base.strided.dsemyc":"\nbase.strided.dsemyc( N, correction, x, stride )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass algorithm proposed by Youngs and\n    Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemyc( x.length, 1, x, 1 )\n    ~1.20185\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsemyc( N, 1, x, stride )\n    ~1.20185\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsemyc( N, 1, x1, stride )\n    ~1.20185\n\nbase.strided.dsemyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass algorithm proposed by Youngs and Cramer\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemyc.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsemyc.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dsem, base.strided.dstdevyc\n","base.strided.dsemyc.ndarray":"\nbase.strided.dsemyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass algorithm proposed by Youngs and Cramer\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemyc.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsemyc.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dsem, base.strided.dstdevyc","base.strided.dsmean":"\nbase.strided.dsmean( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using extended accumulation and returning an extended precision\n    result.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmean( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsmean( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsmean( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dsmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using extended accumulation and alternative indexing semantics and\n    returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dsnanmean, base.strided.mean, base.strided.sdsmean, base.strided.smean\n","base.strided.dsmean.ndarray":"\nbase.strided.dsmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using extended accumulation and alternative indexing semantics and\n    returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dsnanmean, base.strided.mean, base.strided.sdsmean, base.strided.smean","base.strided.dsmeanors":"\nbase.strided.dsmeanors( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation with extended accumulation and\n    returning an extended precision result.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanors( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsmeanors( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsmeanors( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dsmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation with extended accumulation and\n    alternative indexing semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanors, base.strided.dsmean, base.strided.dsnanmeanors, base.strided.meanors, base.strided.smeanors\n","base.strided.dsmeanors.ndarray":"\nbase.strided.dsmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation with extended accumulation and\n    alternative indexing semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanors, base.strided.dsmean, base.strided.dsnanmeanors, base.strided.meanors, base.strided.smeanors","base.strided.dsmeanpn":"\nbase.strided.dsmeanpn( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a two-pass error correction algorithm with extended accumulation\n    and returning an extended precision result.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanpn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsmeanpn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsmeanpn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dsmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a two-pass error correction algorithm with extended accumulation\n    and alternative indexing semantics and returning an extended precision\n    result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.dsmean, base.strided.dsnanmeanpn, base.strided.meanpn, base.strided.smeanpn\n","base.strided.dsmeanpn.ndarray":"\nbase.strided.dsmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a two-pass error correction algorithm with extended accumulation\n    and alternative indexing semantics and returning an extended precision\n    result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.dsmean, base.strided.dsnanmeanpn, base.strided.meanpn, base.strided.smeanpn","base.strided.dsmeanpw":"\nbase.strided.dsmeanpw( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using pairwise summation with extended accumulation and returning an\n    extended precision result.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanpw( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsmeanpw( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsmeanpw( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dsmeanpw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using pairwise summation with extended accumulation and alternative\n    indexing semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanpw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsmeanpw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpw, base.strided.dsmean, base.strided.meanpw, base.strided.smeanpw\n","base.strided.dsmeanpw.ndarray":"\nbase.strided.dsmeanpw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using pairwise summation with extended accumulation and alternative\n    indexing semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanpw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsmeanpw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpw, base.strided.dsmean, base.strided.meanpw, base.strided.smeanpw","base.strided.dsmeanwd":"\nbase.strided.dsmeanwd( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using Welford's algorithm with extended accumulation and returning an\n    extended precision result.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanwd( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsmeanwd( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsmeanwd( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dsmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using Welford's algorithm with extended accumulation and alternative\n    indexing semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanwd, base.strided.dsmean, base.strided.dsnanmeanwd, base.strided.meanwd, base.strided.smeanwd\n","base.strided.dsmeanwd.ndarray":"\nbase.strided.dsmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using Welford's algorithm with extended accumulation and alternative\n    indexing semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanwd, base.strided.dsmean, base.strided.dsnanmeanwd, base.strided.meanwd, base.strided.smeanwd","base.strided.dsnanmean":"\nbase.strided.dsnanmean( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values, using extended accumulation, and returning an\n    extended precision result.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmean( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsnanmean( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsnanmean( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dsnanmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using extended accumulation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsnanmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.dsmean, base.strided.nanmean, base.strided.sdsnanmean, base.strided.snanmean\n","base.strided.dsnanmean.ndarray":"\nbase.strided.dsnanmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using extended accumulation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsnanmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.dsmean, base.strided.nanmean, base.strided.sdsnanmean, base.strided.snanmean","base.strided.dsnanmeanors":"\nbase.strided.dsnanmeanors( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values, using ordinary recursive summation with\n    extended accumulation, and returning an extended precision result.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmeanors( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsnanmeanors( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsnanmeanors( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dsnanmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation with\n    extended accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsnanmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanors, base.strided.dsmeanors, base.strided.dsnanmean, base.strided.nanmeanors, base.strided.sdsnanmean, base.strided.snanmeanors\n","base.strided.dsnanmeanors.ndarray":"\nbase.strided.dsnanmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation with\n    extended accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsnanmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanors, base.strided.dsmeanors, base.strided.dsnanmean, base.strided.nanmeanors, base.strided.sdsnanmean, base.strided.snanmeanors","base.strided.dsnanmeanpn":"\nbase.strided.dsnanmeanpn( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values, using a two-pass error correction algorithm\n    with extended accumulation, and returning an extended precision result.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmeanpn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsnanmeanpn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsnanmeanpn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dsnanmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction algorithm\n    with extended accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsnanmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanpn, base.strided.dsmeanpn, base.strided.dsnanmean, base.strided.nanmeanpn, base.strided.sdsnanmean, base.strided.snanmeanpn\n","base.strided.dsnanmeanpn.ndarray":"\nbase.strided.dsnanmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction algorithm\n    with extended accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsnanmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanpn, base.strided.dsmeanpn, base.strided.dsnanmean, base.strided.nanmeanpn, base.strided.sdsnanmean, base.strided.snanmeanpn","base.strided.dsnanmeanwd":"\nbase.strided.dsnanmeanwd( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values, using Welford's algorithm with extended\n    accumulation, and returning an extended precision result.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmeanwd( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsnanmeanwd( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsnanmeanwd( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dsnanmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm with extended\n    accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsnanmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanwd, base.strided.dsmeanwd, base.strided.dsnanmean, base.strided.nanmeanwd, base.strided.sdsnanmean, base.strided.snanmeanwd\n","base.strided.dsnanmeanwd.ndarray":"\nbase.strided.dsnanmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm with extended\n    accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsnanmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanwd, base.strided.dsmeanwd, base.strided.dsnanmean, base.strided.nanmeanwd, base.strided.sdsnanmean, base.strided.snanmeanwd","base.strided.dsnannsumors":"\nbase.strided.dsnannsumors( N, x, strideX, out, strideOut )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using ordinary recursive summation with extended\n    accumulation, and returning an extended precision result.\n\n    The `N` and stride parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns a sum equal to `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dsnannsumors( x.length, x, 1, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dsnannsumors( 4, x, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dsnannsumors( N, x1, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n\nbase.strided.dsnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using ordinary recursive summation with extended\n    accumulation and alternative indexing semantics, and returning an extended\n    precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dsnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dsnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsumors, base.strided.dsnansumors, base.strided.dssumors\n","base.strided.dsnannsumors.ndarray":"\nbase.strided.dsnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using ordinary recursive summation with extended\n    accumulation and alternative indexing semantics, and returning an extended\n    precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dsnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dsnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsumors, base.strided.dsnansumors, base.strided.dssumors","base.strided.dsnansum":"\nbase.strided.dsnansum( N, x, strideX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using extended accumulation, and returning an\n    extended precision result.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnansum( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.dsnansum( 4, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsnansum( 4, x1, 2 )\n    -1.0\n\n\nbase.strided.dsnansum.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using extended accumulation and alternative\n    indexing semantics, and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnansum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsnansum.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnanmean, base.strided.dssum, base.strided.sdsnansum, base.strided.snansum\n","base.strided.dsnansum.ndarray":"\nbase.strided.dsnansum.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using extended accumulation and alternative\n    indexing semantics, and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnansum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsnansum.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnanmean, base.strided.dssum, base.strided.sdsnansum, base.strided.snansum","base.strided.dsnansumors":"\nbase.strided.dsnansumors( N, x, strideX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using ordinary recursive summation with extended\n    accumulation, and returning an extended precision result.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnansumors( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.dsnansumors( 4, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsnansumors( 4, x1, 2 )\n    -1.0\n\n\nbase.strided.dsnansumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation with extended\n    accumulation and alternative indexing semantics, and returning an extended\n    precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnansumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dsnansumors.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnanmeanors, base.strided.dssum, base.strided.dssumors, base.strided.snansumors\n","base.strided.dsnansumors.ndarray":"\nbase.strided.dsnansumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation with extended\n    accumulation and alternative indexing semantics, and returning an extended\n    precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnansumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dsnansumors.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnanmeanors, base.strided.dssum, base.strided.dssumors, base.strided.snansumors","base.strided.dsnansumpw":"\nbase.strided.dsnansumpw( N, x, strideX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using pairwise summation with extended accumulation,\n    and returning an extended precision result.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnansumpw( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.dsnansumpw( 4, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsnansumpw( 4, x1, 2 )\n    -1.0\n\n\nbase.strided.dsnansumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using pairwise summation with extended accumulation\n    and alternative indexing semantics, and returning an extended precision\n    result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnansumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dsnansumpw.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumpw, base.strided.dssum, base.strided.dssumpw, base.strided.snansumpw\n","base.strided.dsnansumpw.ndarray":"\nbase.strided.dsnansumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using pairwise summation with extended accumulation\n    and alternative indexing semantics, and returning an extended precision\n    result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnansumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dsnansumpw.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumpw, base.strided.dssum, base.strided.dssumpw, base.strided.snansumpw","base.strided.dsort2hp":"\nbase.strided.dsort2hp( N, order, x, strideX, y, strideY )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using heapsort.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided arrays are sorted *in-place* (i.e., the input strided\n    arrays are *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2hp( x.length, 1, x, 1, y, 1 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float64Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsort2hp( N, -1, x, 2, y, 2 )\n    <Float64Array>[ 3.0, -2.0, 1.0, -4.0 ]\n    > y\n    <Float64Array>[ 2.0, 1.0, 0.0, 3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dsort2hp( N, 1, x1, 2, y1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.dsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using heapsort and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float64Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssort2hp\n","base.strided.dsort2hp.ndarray":"\nbase.strided.dsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using heapsort and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float64Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssort2hp","base.strided.dsort2ins":"\nbase.strided.dsort2ins( N, order, x, strideX, y, strideY )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using insertion sort.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^2).\n\n    The algorithm is efficient for *small* strided arrays (typically N <= 20)\n    and is particularly efficient for sorting strided arrays which are already\n    substantially sorted.\n\n    The algorithm is *stable*, meaning that the algorithm does *not* change the\n    order of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided arrays are sorted *in-place* (i.e., the input strided\n    arrays is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2ins( x.length, 1, x, 1, y, 1 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float64Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2ins( 2, -1, x, 2, y, 2 )\n    <Float64Array>[ 3.0, -2.0, 1.0, -4.0 ]\n    > y\n    <Float64Array>[ 2.0, 1.0, 0.0, 3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsort2ins( 2, 1, x1, 2, y1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.dsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using insertion sort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float64Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsortins, base.strided.gsort2ins, base.strided.ssort2ins\n","base.strided.dsort2ins.ndarray":"\nbase.strided.dsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using insertion sort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float64Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsortins, base.strided.gsort2ins, base.strided.ssort2ins","base.strided.dsort2sh":"\nbase.strided.dsort2sh( N, order, x, strideX, y, strideY )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using Shellsort.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^(4/3)).\n\n    The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided arrays are sorted *in-place* (i.e., the input strided\n    arrays are *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2sh( x.length, 1, x, 1, y, 1 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float64Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsort2sh( N, -1, x, 2, y, 2 )\n    <Float64Array>[ 3.0, -2.0, 1.0, -4.0 ]\n    > y\n    <Float64Array>[ 2.0, 1.0, 0.0, 3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dsort2sh( N, 1, x1, 2, y1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.dsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using Shellsort and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float64Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssort2sh\n","base.strided.dsort2sh.ndarray":"\nbase.strided.dsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using Shellsort and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float64Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssort2sh","base.strided.dsorthp":"\nbase.strided.dsorthp( N, order, x, stride )\n    Sorts a double-precision floating-point strided array using heapsort.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided array is sorted *in-place* (i.e., the input strided array\n    is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.dsorthp( x.length, 1, x, 1 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsorthp( N, -1, x, 2 )\n    <Float64Array>[ 3.0, -2.0, 1.0, -4.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dsorthp( N, 1, x1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.dsorthp.ndarray( N, order, x, stride, offset )\n    Sorts a double-precision floating-point strided array using heapsort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.dsorthp.ndarray( x.length, 1, x, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsorthp.ndarray( N, 1, x, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssorthp\n","base.strided.dsorthp.ndarray":"\nbase.strided.dsorthp.ndarray( N, order, x, stride, offset )\n    Sorts a double-precision floating-point strided array using heapsort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.dsorthp.ndarray( x.length, 1, x, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsorthp.ndarray( N, 1, x, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssorthp","base.strided.dsortins":"\nbase.strided.dsortins( N, order, x, stride )\n    Sorts a double-precision floating-point strided array using insertion sort.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^2).\n\n    The algorithm is efficient for *small* strided arrays (typically N <= 20)\n    and is particularly efficient for sorting strided arrays which are already\n    substantially sorted.\n\n    The algorithm is *stable*, meaning that the algorithm does *not* change the\n    order of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided array is sorted *in-place* (i.e., the input strided array\n    is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.dsortins( x.length, 1, x, 1 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsortins( N, -1, x, 2 )\n    <Float64Array>[ 3.0, -2.0, 1.0, -4.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dsortins( N, 1, x1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.dsortins.ndarray( N, order, x, stride, offset )\n    Sorts a double-precision floating-point strided array using insertion sort\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.dsortins.ndarray( x.length, 1, x, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsortins.ndarray( N, 1, x, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2ins, base.strided.gsortins, base.strided.ssortins\n","base.strided.dsortins.ndarray":"\nbase.strided.dsortins.ndarray( N, order, x, stride, offset )\n    Sorts a double-precision floating-point strided array using insertion sort\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.dsortins.ndarray( x.length, 1, x, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsortins.ndarray( N, 1, x, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2ins, base.strided.gsortins, base.strided.ssortins","base.strided.dsortsh":"\nbase.strided.dsortsh( N, order, x, stride )\n    Sorts a double-precision floating-point strided array using Shellsort.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^(4/3)).\n\n    The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided array is sorted *in-place* (i.e., the input strided array\n    is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.dsortsh( x.length, 1, x, 1 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsortsh( N, -1, x, 2 )\n    <Float64Array>[ 3.0, -2.0, 1.0, -4.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dsortsh( N, 1, x1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.dsortsh.ndarray( N, order, x, stride, offset )\n    Sorts a double-precision floating-point strided array using Shellsort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.dsortsh.ndarray( x.length, 1, x, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsortsh.ndarray( N, 1, x, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssortsh\n","base.strided.dsortsh.ndarray":"\nbase.strided.dsortsh.ndarray( N, order, x, stride, offset )\n    Sorts a double-precision floating-point strided array using Shellsort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.dsortsh.ndarray( x.length, 1, x, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsortsh.ndarray( N, 1, x, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssortsh","base.strided.dsqrt":"\nbase.strided.dsqrt( N, x, strideX, y, strideY )\n    Computes the principal square root for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dsqrt( x.length, x, 1, y, 1 )\n    <Float64Array>[ 0.0, 2.0, 3.0, ~3.464 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dsqrt( N, x, 2, y, -1 )\n    <Float64Array>[ 3.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dsqrt( N, x1, -2, y1, 1 )\n    <Float64Array>[ ~3.464, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.dsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the principal square root for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, 2.0, 3.0, ~3.464 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dcbrt, base.strided.drsqrt, strided.sqrt, base.strided.ssqrt\n","base.strided.dsqrt.ndarray":"\nbase.strided.dsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the principal square root for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, 2.0, 3.0, ~3.464 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dcbrt, base.strided.drsqrt, strided.sqrt, base.strided.ssqrt","base.strided.dssum":"\nbase.strided.dssum( N, x, strideX )\n    Computes the sum of single-precision floating-point strided array elements\n    using extended accumulation and returning an extended precision result.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dssum( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dssum( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dssum( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.dssum.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements\n    using extended accumulation and alternative indexing semantics and returning\n    an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dssum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dssum.ndarray(3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnansum, base.strided.sdssum, base.strided.ssum, base.strided.dsmean\n","base.strided.dssum.ndarray":"\nbase.strided.dssum.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements\n    using extended accumulation and alternative indexing semantics and returning\n    an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dssum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dssum.ndarray(3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnansum, base.strided.sdssum, base.strided.ssum, base.strided.dsmean","base.strided.dssumors":"\nbase.strided.dssumors( N, x, strideX )\n    Computes the sum of single-precision floating-point strided array elements\n    using ordinary recursive summation with extended accumulation and returning\n    an extended precision result.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dssumors( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dssumors( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dssumors( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.dssumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements\n    using ordinary recursive summation with extended accumulation and\n    alternative indexing semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dssumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dssumors.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnansumors, base.strided.dssum, base.strided.dsumors, base.strided.ssumors\n","base.strided.dssumors.ndarray":"\nbase.strided.dssumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements\n    using ordinary recursive summation with extended accumulation and\n    alternative indexing semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dssumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dssumors.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnansumors, base.strided.dssum, base.strided.dsumors, base.strided.ssumors","base.strided.dssumpw":"\nbase.strided.dssumpw( N, x, strideX )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation with extended accumulation and returning an\n    extended precision result.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dssumpw( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dssumpw( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dssumpw( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.dssumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation with extended accumulation and alternative indexing\n    semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dssumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dssumpw.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnansumpw, base.strided.dssum, base.strided.dsumpw, base.strided.ssumpw\n","base.strided.dssumpw.ndarray":"\nbase.strided.dssumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation with extended accumulation and alternative indexing\n    semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dssumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dssumpw.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnansumpw, base.strided.dssum, base.strided.dsumpw, base.strided.ssumpw","base.strided.dstdev":"\nbase.strided.dstdev( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdev( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dstdev( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dstdev( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dstdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dvariance, base.strided.sstdev, base.strided.stdev\n","base.strided.dstdev.ndarray":"\nbase.strided.dstdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dvariance, base.strided.sstdev, base.strided.stdev","base.strided.dstdevch":"\nbase.strided.dstdevch( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevch( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dstdevch( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dstdevch( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dstdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevch, base.strided.dstdev, base.strided.dvariancech, base.strided.sstdevch, base.strided.stdevch\n","base.strided.dstdevch.ndarray":"\nbase.strided.dstdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevch, base.strided.dstdev, base.strided.dvariancech, base.strided.sstdevch, base.strided.stdevch","base.strided.dstdevpn":"\nbase.strided.dstdevpn( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevpn( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dstdevpn( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dstdevpn( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dstdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevpn, base.strided.dstdev, base.strided.dvariancepn, base.strided.sstdevpn, base.strided.stdevpn\n","base.strided.dstdevpn.ndarray":"\nbase.strided.dstdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevpn, base.strided.dstdev, base.strided.dvariancepn, base.strided.sstdevpn, base.strided.stdevpn","base.strided.dstdevtk":"\nbase.strided.dstdevtk( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevtk( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dstdevtk( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dstdevtk( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dstdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass textbook algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevtk, base.strided.dstdev, base.strided.dvariancetk, base.strided.sstdevtk, base.strided.stdevtk\n","base.strided.dstdevtk.ndarray":"\nbase.strided.dstdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass textbook algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevtk, base.strided.dstdev, base.strided.dvariancetk, base.strided.sstdevtk, base.strided.stdevtk","base.strided.dstdevwd":"\nbase.strided.dstdevwd( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevwd( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dstdevwd( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dstdevwd( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dstdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevwd, base.strided.dstdev, base.strided.dvariancewd, base.strided.sstdevwd, base.strided.stdevwd\n","base.strided.dstdevwd.ndarray":"\nbase.strided.dstdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevwd, base.strided.dstdev, base.strided.dvariancewd, base.strided.sstdevwd, base.strided.stdevwd","base.strided.dstdevyc":"\nbase.strided.dstdevyc( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevyc( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dstdevyc( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dstdevyc( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dstdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevyc, base.strided.dstdev, base.strided.dvarianceyc, base.strided.sstdevyc, base.strided.stdevyc\n","base.strided.dstdevyc.ndarray":"\nbase.strided.dstdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevyc, base.strided.dstdev, base.strided.dvarianceyc, base.strided.sstdevyc, base.strided.stdevyc","base.strided.dsum":"\nbase.strided.dsum( N, x, strideX )\n    Computes the sum of double-precision floating-point strided array elements.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsum( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dsum( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsum( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.dsum.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsum.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.dmean, base.strided.dnansum, base.strided.ssum, base.strided.gsum\n","base.strided.dsum.ndarray":"\nbase.strided.dsum.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsum.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.dmean, base.strided.dnansum, base.strided.ssum, base.strided.gsum","base.strided.dsumkbn":"\nbase.strided.dsumkbn( N, x, strideX )\n    Computes the sum of double-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumkbn( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dsumkbn( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsumkbn( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.dsumkbn.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsumkbn.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn, base.strided.ssumkbn\n","base.strided.dsumkbn.ndarray":"\nbase.strided.dsumkbn.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsumkbn.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn, base.strided.ssumkbn","base.strided.dsumkbn2":"\nbase.strided.dsumkbn2( N, x, strideX )\n    Computes the sum of double-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumkbn2( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dsumkbn2( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsumkbn2( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.dsumkbn2.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsumkbn2.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn2, base.strided.dsum, base.strided.dsumkbn, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn2, base.strided.ssumkbn2\n","base.strided.dsumkbn2.ndarray":"\nbase.strided.dsumkbn2.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsumkbn2.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn2, base.strided.dsum, base.strided.dsumkbn, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn2, base.strided.ssumkbn2","base.strided.dsumors":"\nbase.strided.dsumors( N, x, stride )\n    Computes the sum of double-precision floating-point strided array elements\n    using ordinary recursive summation.\n\n    The `N` and `stride` parameters determine which elements in \n    the strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumors( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dsumors( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsumors( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.dsumors.ndarray( N, x, stride, offset )\n    Computes the sum of double-precision floating-point strided array elements\n    using ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsumors.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumors, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumpw, base.strided.gsumors, base.strided.ssumors\n","base.strided.dsumors.ndarray":"\nbase.strided.dsumors.ndarray( N, x, stride, offset )\n    Computes the sum of double-precision floating-point strided array elements\n    using ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsumors.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumors, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumpw, base.strided.gsumors, base.strided.ssumors","base.strided.dsumpw":"\nbase.strided.dsumpw( N, x, stride )\n    Computes the sum of double-precision floating-point strided array elements\n    using pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumpw( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dsumpw( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsumpw( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.dsumpw.ndarray( N, x, stride, offset )\n    Computes the sum of double-precision floating-point strided array elements\n    using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsumpw.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumpw, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.gsumpw, base.strided.ssumpw\n","base.strided.dsumpw.ndarray":"\nbase.strided.dsumpw.ndarray( N, x, stride, offset )\n    Computes the sum of double-precision floating-point strided array elements\n    using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsumpw.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumpw, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.gsumpw, base.strided.ssumpw","base.strided.dsvariance":"\nbase.strided.dsvariance( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    using extended accumulation and returning an extended precision result.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsvariance( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsvariance( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsvariance( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dsvariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using extended accumulation and alternative indexing semantics and\n    returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsvariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsvariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariance, base.strided.variance, base.strided.svariance\n","base.strided.dsvariance.ndarray":"\nbase.strided.dsvariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using extended accumulation and alternative indexing semantics and\n    returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsvariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsvariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariance, base.strided.variance, base.strided.svariance","base.strided.dsvariancepn":"\nbase.strided.dsvariancepn( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    using a two-pass algorithm with extended accumulation and returning an\n    extended precision result.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsvariancepn( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsvariancepn( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsvariancepn( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dsvariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using a two-pass algorithm with extended accumulation and alternative\n    indexing semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsvariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsvariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancepn, base.strided.dsvariance, base.strided.variancepn, base.strided.svariancepn\n","base.strided.dsvariancepn.ndarray":"\nbase.strided.dsvariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using a two-pass algorithm with extended accumulation and alternative\n    indexing semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsvariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsvariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancepn, base.strided.dsvariance, base.strided.variancepn, base.strided.svariancepn","base.strided.dswap":"\nbase.strided.dswap( N, x, strideX, y, strideY )\n    Interchanges two double-precision floating-point vectors.\n\n    The `N` and stride parameters determine how values from `x` are swapped\n    with values from `y`.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the vectors are unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Second input array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.dswap( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.dswap( 3, x, -2, y, 1 )\n    <Float64Array>[ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n    // Using typed array views:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dswap( 3, x1, -2, y1, 1 )\n    <Float64Array>[ 6.0, 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.dswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Interchanges two double-precision floating-point vectors using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Second input array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.dswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.dswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dcopy, base.strided.gswap, base.strided.sswap, dswap\n","base.strided.dswap.ndarray":"\nbase.strided.dswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Interchanges two double-precision floating-point vectors using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Second input array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.dswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.dswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dcopy, base.strided.gswap, base.strided.sswap, dswap","base.strided.dtrunc":"\nbase.strided.dtrunc( N, x, strideX, y, strideY )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward zero and assigns the results to elements in a double-precision\n    floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dtrunc( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.0, 2.0, -3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dtrunc( N, x, 2, y, -1 )\n    <Float64Array>[ -3.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dtrunc( N, x1, -2, y1, 1 )\n    <Float64Array>[ 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dtrunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward zero and assigns the results to elements in a double-precision\n    floating-point strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dtrunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dtrunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dceil, base.strided.dfloor, strided.trunc, base.strided.strunc\n","base.strided.dtrunc.ndarray":"\nbase.strided.dtrunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward zero and assigns the results to elements in a double-precision\n    floating-point strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dtrunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dtrunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dceil, base.strided.dfloor, strided.trunc, base.strided.strunc","base.strided.dtypeEnum2Str":"\nbase.strided.dtypeEnum2Str( dtype )\n    Returns the data type string associated with a strided array data type\n    enumeration constant.\n\n    Parameters\n    ----------\n    dtype: integer\n        Data type enumeration constant.\n\n    Returns\n    -------\n    out: string|null\n        Data type string.\n\n    Examples\n    --------\n    > var out = base.strided.dtypeEnum2Str( base.strided.dtypeStr2Enum( 'float64' ) )\n    'float64'\n\n    See Also\n    --------\n    base.strided.dtypeStr2Enum\n","base.strided.dtypeResolveEnum":"\nbase.strided.dtypeResolveEnum( dtype )\n    Returns the enumeration constant associated with a supported strided array\n    data type value.\n\n    Downstream consumers of this function should *not* rely on specific integer\n    values (e.g., `INT8 == 0`). Instead, the function should be used in an\n    opaque manner.\n\n    Parameters\n    ----------\n    dtype: any\n        Data type value.\n\n    Returns\n    -------\n    out: integer|null\n        Enumeration constant.\n\n    Examples\n    --------\n    > var out = base.strided.dtypeResolveEnum( 'float64' )\n    <number>\n    > out = base.strided.dtypeResolveEnum( base.strided.dtypeStr2Enum( 'float64' ) )\n    <number>\n\n    See Also\n    --------\n    base.strided.dtypeResolveStr\n","base.strided.dtypeResolveStr":"\nbase.strided.dtypeResolveStr( dtype )\n    Returns the data type string associated with a supported data type value.\n\n    Parameters\n    ----------\n    dtype: any\n        Data type value.\n\n    Returns\n    -------\n    out: string|null\n        Data type string.\n\n    Examples\n    --------\n    > var out = base.strided.dtypeResolveStr( 'float64' )\n    'float64'\n    > out = base.strided.dtypeResolveStr( base.strided.dtypeStr2Enum( 'float64' ) )\n    'float64'\n\n    See Also\n    --------\n    base.strided.dtypeResolveEnum\n","base.strided.dtypeStr2Enum":"\nbase.strided.dtypeStr2Enum( dtype )\n    Returns the enumeration constant associated with a strided array data type\n    string.\n\n    Downstream consumers of this function should *not* rely on specific integer\n    values (e.g., `INT8 == 0`). Instead, the function should be used in an\n    opaque manner.\n\n    Parameters\n    ----------\n    dtype: string\n        Data type string.\n\n    Returns\n    -------\n    out: integer|null\n        Enumeration constant.\n\n    Examples\n    --------\n    > var out = base.strided.dtypeStr2Enum( 'float64' )\n    <number>\n\n    See Also\n    --------\n    base.strided.dtypeEnum2Str\n","base.strided.dvariance":"\nbase.strided.dvariance( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariance( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dvariance( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dvariance( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dvariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariance, base.strided.dstdev, base.strided.dvarm, base.strided.svariance, base.strided.variance\n","base.strided.dvariance.ndarray":"\nbase.strided.dvariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariance, base.strided.dstdev, base.strided.dvarm, base.strided.svariance, base.strided.variance","base.strided.dvariancech":"\nbase.strided.dvariancech( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancech( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dvariancech( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dvariancech( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dvariancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass trial mean algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvariancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancech, base.strided.dstdevch, base.strided.dvariance, base.strided.svariancech, base.strided.variancech\n","base.strided.dvariancech.ndarray":"\nbase.strided.dvariancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass trial mean algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvariancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancech, base.strided.dstdevch, base.strided.dvariance, base.strided.svariancech, base.strided.variancech","base.strided.dvariancepn":"\nbase.strided.dvariancepn( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancepn( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dvariancepn( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dvariancepn( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dvariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.dvariance, base.strided.svariancepn, base.strided.variancepn\n","base.strided.dvariancepn.ndarray":"\nbase.strided.dvariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.dvariance, base.strided.svariancepn, base.strided.variancepn","base.strided.dvariancetk":"\nbase.strided.dvariancetk( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancetk( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dvariancetk( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dvariancetk( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dvariancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass textbook algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvariancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.dvariance, base.strided.svariancetk, base.strided.variancetk\n","base.strided.dvariancetk.ndarray":"\nbase.strided.dvariancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass textbook algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvariancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.dvariance, base.strided.svariancetk, base.strided.variancetk","base.strided.dvariancewd":"\nbase.strided.dvariancewd( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancewd( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dvariancewd( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dvariancewd( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dvariancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvariancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.dvariance, base.strided.svariancewd, base.strided.variancewd\n","base.strided.dvariancewd.ndarray":"\nbase.strided.dvariancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvariancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.dvariance, base.strided.svariancewd, base.strided.variancewd","base.strided.dvarianceyc":"\nbase.strided.dvarianceyc( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass algorithm proposed by Youngs and Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarianceyc( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dvarianceyc( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dvarianceyc( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dvarianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass algorithm proposed by Youngs and Cramer and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvarianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.dvariance, base.strided.svarianceyc, base.strided.varianceyc\n","base.strided.dvarianceyc.ndarray":"\nbase.strided.dvarianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass algorithm proposed by Youngs and Cramer and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvarianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.dvariance, base.strided.svarianceyc, base.strided.varianceyc","base.strided.dvarm":"\nbase.strided.dvarm( N, mean, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mean: number\n        Mean.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarm( x.length, 1.0/3.0, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvarm( N, 1.0/3.0, 1, x, 2 )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dvarm( N, 1.0/3.0, 1, x1, 2 )\n    ~4.3333\n\nbase.strided.dvarm.ndarray( N, mean, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mean: number\n        Mean.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarm.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvarm.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariance\n","base.strided.dvarm.ndarray":"\nbase.strided.dvarm.ndarray( N, mean, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mean: number\n        Mean.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarm.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvarm.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariance","base.strided.dvarmpn":"\nbase.strided.dvarmpn( N, mean, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using Neely's correction algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mean: number\n        Mean.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarmpn( x.length, 1.0/3.0, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvarmpn( N, 1.0/3.0, 1, x, 2 )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dvarmpn( N, 1.0/3.0, 1, x1, 2 )\n    ~4.3333\n\nbase.strided.dvarmpn.ndarray( N, mean, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using Neely's correction algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mean: number\n        Mean.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarmpn.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvarmpn.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvarm\n","base.strided.dvarmpn.ndarray":"\nbase.strided.dvarmpn.ndarray( N, mean, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using Neely's correction algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mean: number\n        Mean.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarmpn.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvarmpn.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvarm","base.strided.dvarmtk":"\nbase.strided.dvarmtk( N, mean, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using a one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mean: number\n        Mean.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarmtk( x.length, 1.0/3.0, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvarmtk( N, 1.0/3.0, 1, x, 2 )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dvarmtk( N, 1.0/3.0, 1, x1, 2 )\n    ~4.3333\n\nbase.strided.dvarmtk.ndarray( N, mean, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mean: number\n        Mean.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarmtk.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvarmtk.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvarm\n","base.strided.dvarmtk.ndarray":"\nbase.strided.dvarmtk.ndarray( N, mean, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mean: number\n        Mean.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarmtk.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvarmtk.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvarm","base.strided.gapx":"\nbase.strided.gapx( N, alpha, x, stride )\n    Adds a constant to each element in a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > var alpha = 5.0;\n    > base.strided.gapx( x.length, alpha, x, 1 )\n    [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > alpha = 5.0;\n    > var stride = 2;\n    > base.strided.gapx( N, alpha, x, stride )\n    [ 3.0, 1.0, 8.0, -5.0, 9.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > alpha = 5.0;\n    > stride = 2;\n    > base.strided.gapx( N, alpha, x1, stride )\n    <Float64Array>[ 3.0, 3.0, 1.0, 5.0, -1.0 ]\n    > x0\n    <Float64Array>[ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\nbase.strided.gapx.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each element in a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > var alpha = 5.0;\n    > base.strided.gapx.ndarray( x.length, alpha, x, 1, 0 )\n    [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > alpha = 5.0;\n    > var stride = 2;\n    > base.strided.gapx.ndarray( N, alpha, x, stride, 1 )\n    [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dapx, base.strided.sapx\n","base.strided.gapx.ndarray":"\nbase.strided.gapx.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each element in a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > var alpha = 5.0;\n    > base.strided.gapx.ndarray( x.length, alpha, x, 1, 0 )\n    [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > alpha = 5.0;\n    > var stride = 2;\n    > base.strided.gapx.ndarray( N, alpha, x, stride, 1 )\n    [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dapx, base.strided.sapx","base.strided.gapxsum":"\nbase.strided.gapxsum( N, alpha, x, stride )\n    Adds a constant to each strided array element and computes the sum.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsum( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gapxsum( N, 5.0, x, stride )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gapxsum( N, 5.0, x1, stride )\n    14.0\n\nbase.strided.gapxsum.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each strided array element and computes the sum using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gapxsum.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.gapxsumpw, base.strided.gsum, base.strided.sapxsum\n","base.strided.gapxsum.ndarray":"\nbase.strided.gapxsum.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each strided array element and computes the sum using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gapxsum.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.gapxsumpw, base.strided.gsum, base.strided.sapxsum","base.strided.gapxsumkbn":"\nbase.strided.gapxsumkbn( N, alpha, x, strideX )\n    Adds a scalar constant to each strided array element and computes the sum\n    using an improved Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumkbn( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and stride parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > base.strided.gapxsumkbn( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.gapxsumkbn( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.gapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each strided array element and computes the sum\n    using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > base.strided.gapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumkbn, base.strided.gapxsum, base.strided.gsumkbn, base.strided.sapxsumkbn\n","base.strided.gapxsumkbn.ndarray":"\nbase.strided.gapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each strided array element and computes the sum\n    using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > base.strided.gapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumkbn, base.strided.gapxsum, base.strided.gsumkbn, base.strided.sapxsumkbn","base.strided.gapxsumkbn2":"\nbase.strided.gapxsumkbn2( N, alpha, x, stride )\n    Adds a constant to each strided array element and computes the sum using a\n    second-order iterative Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumkbn2( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gapxsumkbn2( N, 5.0, x, stride )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gapxsumkbn2( N, 5.0, x1, stride )\n    14.0\n\nbase.strided.gapxsumkbn2.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each strided array element and computes the sum using a\n    second-order iterative Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gapxsumkbn2.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumkbn2, base.strided.gapxsum, base.strided.gsumkbn2, base.strided.sapxsumkbn2\n","base.strided.gapxsumkbn2.ndarray":"\nbase.strided.gapxsumkbn2.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each strided array element and computes the sum using a\n    second-order iterative Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gapxsumkbn2.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumkbn2, base.strided.gapxsum, base.strided.gsumkbn2, base.strided.sapxsumkbn2","base.strided.gapxsumors":"\nbase.strided.gapxsumors( N, alpha, x, stride )\n    Adds a constant to each strided array element and computes the sum using\n    ordinary recursive summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumors( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gapxsumors( N, 5.0, x, stride )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gapxsumors( N, 5.0, x1, stride )\n    14.0\n\nbase.strided.gapxsumors.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each strided array element and computes the sum using\n    ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gapxsumors.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumors, base.strided.gapxsum, base.strided.gsumors, base.strided.sapxsumors\n","base.strided.gapxsumors.ndarray":"\nbase.strided.gapxsumors.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each strided array element and computes the sum using\n    ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gapxsumors.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumors, base.strided.gapxsum, base.strided.gsumors, base.strided.sapxsumors","base.strided.gapxsumpw":"\nbase.strided.gapxsumpw( N, alpha, x, stride )\n    Adds a constant to each strided array element and computes the sum using\n    pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumpw( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gapxsumpw( N, 5.0, x, stride )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gapxsumpw( N, 5.0, x1, stride )\n    14.0\n\nbase.strided.gapxsumpw.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each strided array element and computes the sum using\n    pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumpw, base.strided.gapxsum, base.strided.gsumpw, base.strided.sapxsumpw\n","base.strided.gapxsumpw.ndarray":"\nbase.strided.gapxsumpw.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each strided array element and computes the sum using\n    pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumpw, base.strided.gapxsum, base.strided.gsumpw, base.strided.sapxsumpw","base.strided.gasum":"\nbase.strided.gasum( N, x, stride )\n    Computes the sum of the absolute values.\n\n    The sum of absolute values corresponds to the *L1* norm.\n\n    The `N` and `stride` parameters determine which elements in `x` are used to\n    compute the sum.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` or `stride` is less than or equal to `0`, the function returns `0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    sum: number\n        Sum of absolute values.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n    > var s = base.strided.gasum( x.length, x, 1 )\n    19.0\n\n    // Sum every other value:\n    > s = base.strided.gasum( 3, x, 2 )\n    10.0\n\n    // Use view offset; e.g., starting at 2nd element:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > s = base.strided.gasum( 3, x1, 2 )\n    12.0\n\n\nbase.strided.gasum.ndarray( N, x, stride, offset )\n    Computes the sum of absolute values using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    sum: number\n        Sum of absolute values.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n    > var s = base.strided.gasum.ndarray( x.length, x, 1, 0 )\n    19.0\n\n    // Sum the last three elements:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > s = base.strided.gasum.ndarray( 3, x, -1, x.length-1 )\n    15.0\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.sasum\n","base.strided.gasum.ndarray":"\nbase.strided.gasum.ndarray( N, x, stride, offset )\n    Computes the sum of absolute values using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    sum: number\n        Sum of absolute values.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n    > var s = base.strided.gasum.ndarray( x.length, x, 1, 0 )\n    19.0\n\n    // Sum the last three elements:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > s = base.strided.gasum.ndarray( 3, x, -1, x.length-1 )\n    15.0\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.sasum","base.strided.gasumpw":"\nbase.strided.gasumpw( N, x, stride )\n    Computes the sum of absolute values (L1 norm) of strided array elements\n    using pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.gasumpw( x.length, x, 1 )\n    5.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gasumpw( N, x, stride )\n    5.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gasumpw( N, x1, stride )\n    5.0\n\nbase.strided.gasumpw.ndarray( N, x, stride, offset )\n    Computes the sum of absolute values (L1 norm) of strided array elements\n    using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.gasumpw.ndarray( x.length, x, 1, 0 )\n    5.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gasumpw.ndarray( N, x, 2, 1 )\n    5.0\n\n    See Also\n    --------\n    base.strided.gasum, base.strided.dasumpw, base.strided.gsumpw, base.strided.sasumpw\n","base.strided.gasumpw.ndarray":"\nbase.strided.gasumpw.ndarray( N, x, stride, offset )\n    Computes the sum of absolute values (L1 norm) of strided array elements\n    using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.gasumpw.ndarray( x.length, x, 1, 0 )\n    5.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gasumpw.ndarray( N, x, 2, 1 )\n    5.0\n\n    See Also\n    --------\n    base.strided.gasum, base.strided.dasumpw, base.strided.gsumpw, base.strided.sasumpw","base.strided.gaxpy":"\nbase.strided.gaxpy( N, alpha, x, strideX, y, strideY )\n    Multiplies `x` by a constant `alpha` and adds the result to `y`.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n    > base.strided.gaxpy( x.length, 5.0, x, 1, y, 1 )\n    [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n    // Using `N` and stride parameters:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n    > base.strided.gaxpy( 3, 5.0, x, 2, y, -1 )\n    [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.gaxpy( 3, 5.0, x1, -2, y1, 1 )\n    <Float64Array>[ 40.0, 31.0, 22.0 ]\n    > y0\n    <Float64Array>[ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.strided.gaxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n    Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n    > base.strided.gaxpy.ndarray( x.length, 5.0, x, 1, 0, y, 1, 0 )\n    [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n    > base.strided.gaxpy.ndarray( 3, 5.0, x, 2, 1, y, -1, y.length-1 )\n    [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n    See Also\n    --------\n    base.strided.daxpy, base.strided.saxpy\n","base.strided.gaxpy.ndarray":"\nbase.strided.gaxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n    Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n    > base.strided.gaxpy.ndarray( x.length, 5.0, x, 1, 0, y, 1, 0 )\n    [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n    > base.strided.gaxpy.ndarray( 3, 5.0, x, 2, 1, y, -1, y.length-1 )\n    [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n    See Also\n    --------\n    base.strided.daxpy, base.strided.saxpy","base.strided.gcopy":"\nbase.strided.gcopy( N, x, strideX, y, strideY )\n    Copies values from `x` into `y`.\n\n    The `N` and stride parameters determine how values from `x` are copied into\n    `y`.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: ArrayLikeObject\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n    > base.strided.gcopy( x.length, x, 1, y, 1 )\n    [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n    > base.strided.gcopy( 3, x, -2, y, 1 )\n    [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n    // Using typed array views:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.gcopy( 3, x1, -2, y1, 1 )\n    <Float64Array>[ 6.0, 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.gcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Copies values from `x` into `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: ArrayLikeObject\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n    > base.strided.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n    > base.strided.gcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dcopy, base.strided.scopy\n","base.strided.gcopy.ndarray":"\nbase.strided.gcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Copies values from `x` into `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: ArrayLikeObject\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n    > base.strided.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n    > base.strided.gcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dcopy, base.strided.scopy","base.strided.gcusum":"\nbase.strided.gcusum( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of strided array elements.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusum( x.length, 0.0, x, 1, y, 1 )\n    [ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusum( N, 0.0, x, 2, y, 2 )\n    [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gcusum( N, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.gcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusum.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusumpw, base.strided.scusum\n","base.strided.gcusum.ndarray":"\nbase.strided.gcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusum.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusumpw, base.strided.scusum","base.strided.gcusumkbn":"\nbase.strided.gcusumkbn( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of strided array elements using an improved\n    Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Stride length for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumkbn( x.length, 0.0, x, 1, y, 1 )\n    [ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and stride parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumkbn( 3, 0.0, x, 2, y, 2 )\n    [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.gcusumkbn( 3, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.gcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using an improved\n    Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Stride length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumkbn, base.strided.gcusum, base.strided.gcusumkbn2, base.strided.scusumkbn\n","base.strided.gcusumkbn.ndarray":"\nbase.strided.gcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using an improved\n    Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Stride length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumkbn, base.strided.gcusum, base.strided.gcusumkbn2, base.strided.scusumkbn","base.strided.gcusumkbn2":"\nbase.strided.gcusumkbn2( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of strided array elements using a second-order\n    iterative Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumkbn2( x.length, 0.0, x, 1, y, 1 )\n    [ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumkbn2( N, 0.0, x, 2, y, 2 )\n    [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gcusumkbn2( N, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.gcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using a second-order\n    iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumkbn2.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumkbn2, base.strided.gcusum, base.strided.gcusumkbn, base.strided.scusumkbn2\n","base.strided.gcusumkbn2.ndarray":"\nbase.strided.gcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using a second-order\n    iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumkbn2.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumkbn2, base.strided.gcusum, base.strided.gcusumkbn, base.strided.scusumkbn2","base.strided.gcusumors":"\nbase.strided.gcusumors( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of strided array elements using ordinary\n    recursive summation.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumors( x.length, 0.0, x, 1, y, 1 )\n    [ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumors( N, 0.0, x, 2, y, 2 )\n    [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gcusumors( N, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.gcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using ordinary\n    recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumors.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumors, base.strided.gcusum, base.strided.gcusumpw, base.strided.scusumors\n","base.strided.gcusumors.ndarray":"\nbase.strided.gcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using ordinary\n    recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumors.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumors, base.strided.gcusum, base.strided.gcusumpw, base.strided.scusumors","base.strided.gcusumpw":"\nbase.strided.gcusumpw( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of strided array elements using pairwise\n    summation.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumpw( x.length, 0.0, x, 1, y, 1 )\n    [ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumpw( N, 0.0, x, 2, y, 2 )\n    [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gcusumpw( N, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.gcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using pairwise\n    summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumpw.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumpw, base.strided.gcusum, base.strided.scusumpw\n","base.strided.gcusumpw.ndarray":"\nbase.strided.gcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using pairwise\n    summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumpw.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumpw, base.strided.gcusum, base.strided.scusumpw","base.strided.gdot":"\nbase.strided.gdot( N, x, strideX, y, strideY )\n    Computes the dot product of two vectors.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: number\n        The dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n    > var y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n    > var out = base.strided.gdot( x.length, x, 1, y, 1 )\n    -5.0\n\n    // Strides:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n    > out = base.strided.gdot( 3, x, 2, y, -1 )\n    9.0\n\n    // Using view offsets:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n    > out = base.strided.gdot( 3, x1, -2, y1, 1 )\n    128.0\n\n\nbase.strided.gdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the dot product of two vectors using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing based on a starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: number\n        The dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n    > var y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n    > var out = base.strided.gdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    -5.0\n\n    // Strides:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n    > out = base.strided.gdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n    9.0\n\n    // Using offset indices:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n    > out = base.strided.gdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n    128.0\n\n    See Also\n    --------\n    base.strided.ddot, base.strided.sdot, gdot\n","base.strided.gdot.ndarray":"\nbase.strided.gdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the dot product of two vectors using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing based on a starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: number\n        The dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n    > var y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n    > var out = base.strided.gdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    -5.0\n\n    // Strides:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n    > out = base.strided.gdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n    9.0\n\n    // Using offset indices:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n    > out = base.strided.gdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n    128.0\n\n    See Also\n    --------\n    base.strided.ddot, base.strided.sdot, gdot","base.strided.gfill":"\nbase.strided.gfill( N, alpha, x, stride )\n    Fills a strided array with a specified scalar value.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: any\n        Constant.\n\n    x: ArrayLikeObject\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: ArrayLikeObject\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.gfill( x.length, 5.0, x, 1 )\n    [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gfill( N, 5.0, x, 2 )\n    [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gfill( N, 5.0, x1, 2 )\n    <Float64Array>[ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n    > x0\n    <Float64Array>[ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.gfill.ndarray( N, alpha, x, stride, offset )\n    Fills a strided array with a specified scalar value using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: any\n        Constant.\n\n    x: ArrayLikeObject\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: ArrayLikeObject\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.gfill.ndarray( x.length, 5.0, x, 1, 0 )\n    [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gfill.ndarray( N, 5.0, x, 2, 1 )\n    [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n    See Also\n    --------\n    base.strided.dfill, base.strided.sfill\n","base.strided.gfill.ndarray":"\nbase.strided.gfill.ndarray( N, alpha, x, stride, offset )\n    Fills a strided array with a specified scalar value using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: any\n        Constant.\n\n    x: ArrayLikeObject\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: ArrayLikeObject\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.gfill.ndarray( x.length, 5.0, x, 1, 0 )\n    [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gfill.ndarray( N, 5.0, x, 2, 1 )\n    [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n    See Also\n    --------\n    base.strided.dfill, base.strided.sfill","base.strided.gfillBy":"\nbase.strided.gfillBy( N, x, stride, clbk[, thisArg] )\n    Fills a strided array according to a provided callback function.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - aidx: array index.\n    - sidx: strided index (offset + aidx*stride).\n    - array: the input array.\n\n    The callback return value is used as the fill value for the current array\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    x: ArrayLikeObject\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function fill() { return 5.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.gfillBy( x.length, x, 1, fill )\n    [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gfillBy( N, x, 2, fill )\n    [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gfillBy( N, x1, 2, fill )\n    <Float64Array>[ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n    > x0\n    <Float64Array>[ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.gfillBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Fills a strided array according to a provided callback function and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    x: ArrayLikeObject\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function fill() { return 5.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.gfillBy.ndarray( x.length, x, 1, 0, fill )\n    [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gfillBy.ndarray( N, x, 2, 1, fill )\n    [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n    See Also\n    --------\n    base.strided.gfill\n","base.strided.gfillBy.ndarray":"\nbase.strided.gfillBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Fills a strided array according to a provided callback function and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    x: ArrayLikeObject\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function fill() { return 5.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.gfillBy.ndarray( x.length, x, 1, 0, fill )\n    [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gfillBy.ndarray( N, x, 2, 1, fill )\n    [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n    See Also\n    --------\n    base.strided.gfill","base.strided.gnannsumkbn":"\nbase.strided.gnannsumkbn( N, x, strideX, out, strideOut )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    an improved Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns a sum equal to `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > var out = [ 0.0, 0 ];\n    > base.strided.gnannsumkbn( x.length, x, 1, out, 1 )\n    [ 1.0, 3 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n    > out = [ 0.0, 0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gnannsumkbn( N, x, 2, out, 1 )\n    [ 1.0, 3 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > out = [ 0.0, 0 ];\n    > base.strided.gnannsumkbn( N, x1, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\nbase.strided.gnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > var out = [ 0.0, 0 ];\n    > base.strided.gnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\n    [ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > out = [ 0.0, 0 ];\n    > base.strided.gnannsumkbn.ndarray( N, x, 2, 1, out, 1, 0 )\n    [ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsumkbn\n","base.strided.gnannsumkbn.ndarray":"\nbase.strided.gnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > var out = [ 0.0, 0 ];\n    > base.strided.gnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\n    [ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > out = [ 0.0, 0 ];\n    > base.strided.gnannsumkbn.ndarray( N, x, 2, 1, out, 1, 0 )\n    [ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsumkbn","base.strided.gnansum":"\nbase.strided.gnansum( N, x, stride )\n    Computes the sum of strided array elements, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansum( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gnansum( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gnansum( N, x1, stride )\n    -1.0\n\nbase.strided.gnansum.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gnansum.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.snansum, base.strided.gsum, base.strided.nanmean\n","base.strided.gnansum.ndarray":"\nbase.strided.gnansum.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gnansum.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.snansum, base.strided.gsum, base.strided.nanmean","base.strided.gnansumkbn":"\nbase.strided.gnansumkbn( N, x, stride )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    an improved Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumkbn( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gnansumkbn( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gnansumkbn( N, x1, stride )\n    -1.0\n\nbase.strided.gnansumkbn.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gnansumkbn.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn, base.strided.snansumkbn\n","base.strided.gnansumkbn.ndarray":"\nbase.strided.gnansumkbn.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gnansumkbn.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn, base.strided.snansumkbn","base.strided.gnansumkbn2":"\nbase.strided.gnansumkbn2( N, x, stride )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    a second-order iterative Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumkbn2( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gnansumkbn2( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gnansumkbn2( N, x1, stride )\n    -1.0\n\nbase.strided.gnansumkbn2.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    a second-order iterative Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gnansumkbn2.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn2, base.strided.gnansum, base.strided.gnansumkbn, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn2, base.strided.snansumkbn2\n","base.strided.gnansumkbn2.ndarray":"\nbase.strided.gnansumkbn2.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    a second-order iterative Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gnansumkbn2.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn2, base.strided.gnansum, base.strided.gnansumkbn, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn2, base.strided.snansumkbn2","base.strided.gnansumors":"\nbase.strided.gnansumors( N, x, stride )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    ordinary recursive summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumors( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gnansumors( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gnansumors( N, x1, stride )\n    -1.0\n\nbase.strided.gnansumors.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gnansumors.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumors, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumpw, base.strided.gsumors, base.strided.snansumors\n","base.strided.gnansumors.ndarray":"\nbase.strided.gnansumors.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gnansumors.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumors, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumpw, base.strided.gsumors, base.strided.snansumors","base.strided.gnansumpw":"\nbase.strided.gnansumpw( N, x, stride )\n    Computes the sum of strided array elements, ignoring `NaN` values and\n    pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumpw( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gnansumpw( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gnansumpw( N, x1, stride )\n    -1.0\n\nbase.strided.gnansumpw.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gnansumpw.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumpw, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gsumpw, base.strided.snansumpw\n","base.strided.gnansumpw.ndarray":"\nbase.strided.gnansumpw.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gnansumpw.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumpw, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gsumpw, base.strided.snansumpw","base.strided.gnrm2":"\nbase.strided.gnrm2( N, x, stride )\n    Computes the L2-norm of a vector.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0` or `stride <= 0`, the function returns `0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The L2-norm.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gnrm2( x.length, x, 1 )\n    3.0\n\n    // Using `N` and stride parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > base.strided.gnrm2( 3, x, 2 )\n    3.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.gnrm2( 3, x1, 2 )\n    3.0\n\n\nbase.strided.gnrm2.ndarray( N, x, stride, offset )\n    Computes the L2-norm of a vector using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    nrm2: number\n        The L2-norm.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gnrm2.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > base.strided.gnrm2.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dnrm2, base.strided.snrm2\n","base.strided.gnrm2.ndarray":"\nbase.strided.gnrm2.ndarray( N, x, stride, offset )\n    Computes the L2-norm of a vector using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    nrm2: number\n        The L2-norm.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gnrm2.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > base.strided.gnrm2.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dnrm2, base.strided.snrm2","base.strided.grev":"\nbase.strided.grev( N, x, stride )\n    Reverses a strided array in-place.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: ArrayLikeObject\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.grev( x.length, x, 1 )\n    [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.grev( N, x, 2 )\n    [ 4.0, 1.0, 3.0, -5.0, -2.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.grev( N, x1, 2 )\n    <Float64Array>[ -6.0, 3.0, -4.0, 5.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n\nbase.strided.grev.ndarray( N, x, stride, offset )\n    Reverses a strided array in-place using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: ArrayLikeObject\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.grev.ndarray( x.length, x, 1, 0 )\n    [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.grev.ndarray( N, x, 2, 1 )\n    [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.drev, base.strided.srev\n","base.strided.grev.ndarray":"\nbase.strided.grev.ndarray( N, x, stride, offset )\n    Reverses a strided array in-place using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: ArrayLikeObject\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.grev.ndarray( x.length, x, 1, 0 )\n    [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.grev.ndarray( N, x, 2, 1 )\n    [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.drev, base.strided.srev","base.strided.gscal":"\nbase.strided.gscal( N, alpha, x, stride )\n    Multiplies a vector `x` by a constant `alpha`.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `stride <= 0`, the function returns `x` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > var alpha = 5.0;\n    > base.strided.gscal( x.length, alpha, x, 1 )\n    [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.gscal( 3, 5.0, x, 2 )\n    [ -10.0, 1.0, 15.0, -5.0, 20.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.gscal( 3, 5.0, x1, 2 )\n    <Float64Array>[ -10.0, 3.0, -20.0, 5.0, -30.0 ]\n    > x0\n    <Float64Array>[ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n\nbase.strided.gscal.ndarray( N, alpha, x, stride, offset )\n    Multiplies `x` by a constant `alpha` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.gscal.ndarray( x.length, 5.0, x, 1, 0 )\n    [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > base.strided.gscal.ndarray( 3, 5.0, x, 2, 1 )\n    [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n    See Also\n    --------\n    base.strided.dscal, base.strided.gaxpy, base.strided.sscal\n","base.strided.gscal.ndarray":"\nbase.strided.gscal.ndarray( N, alpha, x, stride, offset )\n    Multiplies `x` by a constant `alpha` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.gscal.ndarray( x.length, 5.0, x, 1, 0 )\n    [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > base.strided.gscal.ndarray( 3, 5.0, x, 2, 1 )\n    [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n    See Also\n    --------\n    base.strided.dscal, base.strided.gaxpy, base.strided.sscal","base.strided.gsort2hp":"\nbase.strided.gsort2hp( N, order, x, strideX, y, strideY )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using heapsort.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided arrays are sorted *in-place* (i.e., the input strided\n    arrays is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > base.strided.gsort2hp( x.length, 1, x, 1, y, 1 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    [ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsort2hp( N, -1, x, 2, y, 2 )\n    [ 3.0, -2.0, 1.0, -4.0 ]\n    > y\n    [ 2.0, 1.0, 0.0, 3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gsort2hp( N, 1, x1, 2, y1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.gsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using heapsort and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > base.strided.gsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    [ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    [ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssort2hp\n","base.strided.gsort2hp.ndarray":"\nbase.strided.gsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using heapsort and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > base.strided.gsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    [ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    [ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssort2hp","base.strided.gsort2ins":"\nbase.strided.gsort2ins( N, order, x, strideX, y, strideY )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using insertion sort.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^2).\n\n    The algorithm is efficient for *small* strided arrays (typically N <= 20)\n    and is particularly efficient for sorting strided arrays which are already\n    substantially sorted.\n\n    The algorithm is *stable*, meaning that the algorithm does *not* change the\n    order of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided arrays are sorted *in-place* (i.e., the input strided\n    arrays is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > base.strided.gsort2ins( x.length, 1, x, 1, y, 1 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    [ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsort2ins( N, -1, x, 2, y, 2 )\n    [ 3.0, -2.0, 1.0, -4.0 ]\n    > y\n    [ 2.0, 1.0, 0.0, 3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gsort2ins( N, 1, x1, 2, y1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.gsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using insertion sort and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > base.strided.gsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    [ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsort2ins.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    [ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2ins, base.strided.gsortins, base.strided.ssort2ins\n","base.strided.gsort2ins.ndarray":"\nbase.strided.gsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using insertion sort and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > base.strided.gsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    [ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsort2ins.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    [ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2ins, base.strided.gsortins, base.strided.ssort2ins","base.strided.gsort2sh":"\nbase.strided.gsort2sh( N, order, x, strideX, y, strideY )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using Shellsort.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^(4/3)).\n\n    The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided arrays are sorted *in-place* (i.e., the input strided\n    arrays is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > base.strided.gsort2sh( x.length, 1, x, 1, y, 1 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    [ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsort2sh( N, -1, x, 2, y, 2 )\n    [ 3.0, -2.0, 1.0, -4.0 ]\n    > y\n    [ 2.0, 1.0, 0.0, 3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gsort2sh( N, 1, x1, 2, y1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.gsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using Shellsort and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > base.strided.gsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    [ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    [ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssort2sh\n","base.strided.gsort2sh.ndarray":"\nbase.strided.gsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using Shellsort and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > base.strided.gsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    [ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    [ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssort2sh","base.strided.gsorthp":"\nbase.strided.gsorthp( N, order, x, stride )\n    Sorts a strided array using heapsort.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided array is sorted *in-place* (i.e., the input strided array\n    is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > base.strided.gsorthp( x.length, 1, x, 1 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsorthp( N, -1, x, 2 )\n    [ 3.0, -2.0, 1.0, -4.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gsorthp( N, 1, x1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.gsorthp.ndarray( N, order, x, stride, offset )\n    Sorts a strided array using heapsort and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > base.strided.gsorthp.ndarray( x.length, 1, x, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsorthp.ndarray( N, 1, x, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssorthp\n","base.strided.gsorthp.ndarray":"\nbase.strided.gsorthp.ndarray( N, order, x, stride, offset )\n    Sorts a strided array using heapsort and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > base.strided.gsorthp.ndarray( x.length, 1, x, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsorthp.ndarray( N, 1, x, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssorthp","base.strided.gsortins":"\nbase.strided.gsortins( N, order, x, stride )\n    Sorts a strided array using insertion sort.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^2).\n\n    The algorithm is efficient for *small* strided arrays (typically N <= 20)\n    and is particularly efficient for sorting strided arrays which are already\n    substantially sorted.\n\n    The algorithm is *stable*, meaning that the algorithm does *not* change the\n    order of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided array is sorted *in-place* (i.e., the input strided array\n    is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > base.strided.gsortins( x.length, 1, x, 1 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsortins( N, -1, x, 2 )\n    [ 3.0, -2.0, 1.0, -4.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gsortins( N, 1, x1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.gsortins.ndarray( N, order, x, stride, offset )\n    Sorts a strided array using insertion sort and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > base.strided.gsortins.ndarray( x.length, 1, x, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsortins.ndarray( N, 1, x, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsortins, base.strided.gsort2ins, base.strided.ssortins\n","base.strided.gsortins.ndarray":"\nbase.strided.gsortins.ndarray( N, order, x, stride, offset )\n    Sorts a strided array using insertion sort and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > base.strided.gsortins.ndarray( x.length, 1, x, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsortins.ndarray( N, 1, x, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsortins, base.strided.gsort2ins, base.strided.ssortins","base.strided.gsortsh":"\nbase.strided.gsortsh( N, order, x, stride )\n    Sorts a strided array using Shellsort.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^(4/3)).\n\n    The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided array is sorted *in-place* (i.e., the input strided array\n    is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > base.strided.gsortsh( x.length, 1, x, 1 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsortsh( N, -1, x, 2 )\n    [ 3.0, -2.0, 1.0, -4.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gsortsh( N, 1, x1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.gsortsh.ndarray( N, order, x, stride, offset )\n    Sorts a strided array using Shellsort and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > base.strided.gsortsh.ndarray( x.length, 1, x, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsortsh.ndarray( N, 1, x, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssortsh\n","base.strided.gsortsh.ndarray":"\nbase.strided.gsortsh.ndarray( N, order, x, stride, offset )\n    Sorts a strided array using Shellsort and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > base.strided.gsortsh.ndarray( x.length, 1, x, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsortsh.ndarray( N, 1, x, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssortsh","base.strided.gsum":"\nbase.strided.gsum( N, x, stride )\n    Computes the sum of strided array elements.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsum( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gsum( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gsum( N, x1, stride )\n    -1.0\n\nbase.strided.gsum.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsum.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsum, base.strided.gnansum, base.strided.ssum, base.strided.mean\n","base.strided.gsum.ndarray":"\nbase.strided.gsum.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsum.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsum, base.strided.gnansum, base.strided.ssum, base.strided.mean","base.strided.gsumkbn":"\nbase.strided.gsumkbn( N, x, stride )\n    Computes the sum of strided array elements using an improved Kahan–Babuška\n    algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumkbn( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gsumkbn( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gsumkbn( N, x1, stride )\n    -1.0\n\nbase.strided.gsumkbn.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements using an improved Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsumkbn.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn\n","base.strided.gsumkbn.ndarray":"\nbase.strided.gsumkbn.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements using an improved Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsumkbn.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn","base.strided.gsumkbn2":"\nbase.strided.gsumkbn2( N, x, stride )\n    Computes the sum of strided array elements using a second-order iterative\n    Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumkbn2( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gsumkbn2( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gsumkbn2( N, x1, stride )\n    -1.0\n\nbase.strided.gsumkbn2.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements using a second-order iterative\n    Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsumkbn2.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.gsum, base.strided.gsumkbn, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn2\n","base.strided.gsumkbn2.ndarray":"\nbase.strided.gsumkbn2.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements using a second-order iterative\n    Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsumkbn2.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.gsum, base.strided.gsumkbn, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn2","base.strided.gsumors":"\nbase.strided.gsumors( N, x, stride )\n    Computes the sum of strided array elements using ordinary recursive\n    summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumors( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gsumors( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gsumors( N, x1, stride )\n    -1.0\n\nbase.strided.gsumors.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements using ordinary recursive\n    summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsumors.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumors, base.strided.gnansumors, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumpw, base.strided.ssumors\n","base.strided.gsumors.ndarray":"\nbase.strided.gsumors.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements using ordinary recursive\n    summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsumors.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumors, base.strided.gnansumors, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumpw, base.strided.ssumors","base.strided.gsumpw":"\nbase.strided.gsumpw( N, x, stride )\n    Computes the sum of strided array elements using pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumpw( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gsumpw( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gsumpw( N, x1, stride )\n    -1.0\n\nbase.strided.gsumpw.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements using pairwise summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsumpw.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumpw, base.strided.gnansumpw, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.ssumpw\n","base.strided.gsumpw.ndarray":"\nbase.strided.gsumpw.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements using pairwise summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsumpw.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumpw, base.strided.gnansumpw, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.ssumpw","base.strided.gswap":"\nbase.strided.gswap( N, x, strideX, y, strideY )\n    Interchanges vectors `x` and `y`.\n\n    The `N` and stride parameters determine how values from `x` are swapped with\n    values from `y`.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the vectors are unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: ArrayLikeObject\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n    > base.strided.gswap( x.length, x, 1, y, 1 )\n    [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n    > base.strided.gswap( 3, x, -2, y, 1 )\n    [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n    // Using typed array views:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.gswap( 3, x1, -2, y1, 1 )\n    <Float64Array>[ 6.0, 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.gswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Interchanges vectors `x` and `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: ArrayLikeObject\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n    > base.strided.gswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n    > base.strided.gswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dswap, base.strided.gcopy, base.strided.sswap, gswap\n","base.strided.gswap.ndarray":"\nbase.strided.gswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Interchanges vectors `x` and `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: ArrayLikeObject\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n    > base.strided.gswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n    > base.strided.gswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dswap, base.strided.gcopy, base.strided.sswap, gswap","base.strided.mapBy":"\nbase.strided.mapBy( N, x, sx, y, sy, fcn, clbk[, thisArg] )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - indices: strided indices (offset + idx*stride).\n    - arrays: input and output arrays.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    fcn: Function\n        Unary function to apply to callback return values.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v * 2.0; };\n    > base.strided.mapBy( x.length, x, 1, y, 1, base.abs, clbk )\n    [ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > base.strided.mapBy( 2, x, 2, y, -1, base.abs, clbk )\n    [ 6.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.mapBy( 2, x1, -2, y1, 1, base.abs, clbk )\n    <Float64Array>[ 8.0, 4.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 8.0, 4.0 ]\n\n\nbase.strided.mapBy.ndarray( N, x, sx, ox, y, sy, oy, fcn, clbk[, thisArg] )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offsest parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply to callback return values.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v * 2.0; };\n    > base.strided.mapBy.ndarray( x.length, x, 1, 0, y, 1, 0, base.abs, clbk )\n    [ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > base.strided.mapBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.abs, clbk )\n    [ 0.0, 0.0, 8.0, 4.0 ]\n\n    See Also\n    --------\n    base.strided.mapBy2, base.strided.unary\n","base.strided.mapBy.ndarray":"\nbase.strided.mapBy.ndarray( N, x, sx, ox, y, sy, oy, fcn, clbk[, thisArg] )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offsest parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply to callback return values.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v * 2.0; };\n    > base.strided.mapBy.ndarray( x.length, x, 1, 0, y, 1, 0, base.abs, clbk )\n    [ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > base.strided.mapBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.abs, clbk )\n    [ 0.0, 0.0, 8.0, 4.0 ]\n\n    See Also\n    --------\n    base.strided.mapBy2, base.strided.unary","base.strided.mapBy2":"\nbase.strided.mapBy2( N, x, sx, y, sy, z, sz, fcn, clbk[, thisArg] )\n    Applies a binary function to each pair of elements retrieved from strided\n    input arrays according to a callback function and assigns results to a\n    strided output array.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided four arguments:\n\n    - values: input array elements.\n    - idx: iteration index.\n    - indices: strided array indices (offset + idx*stride).\n    - arrays: input and output arrays.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    fcn: Function\n        Binary function to apply to callback return values.\n\n    clbk: Function\n        Callback function which returns an array-like object containing two\n        values.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 1.0, 1.0, 2.0, 2.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\n    > base.strided.mapBy2( x.length, x, 1, y, 1, z, 1, base.add, clbk )\n    [ 4.0, -2.0, 10.0, -4.0 ]\n\n    // Using `N` and stride parameters:\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > base.strided.mapBy2( 2, x, 2, y, -1, z, -1, base.add, clbk )\n    [ 8.0, 4.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y0 = new Float64Array( [ 1.0, 1.0, 2.0, 2.0 ] );\n    > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > base.strided.mapBy2( 2, x1, -2, y1, 1, z1, 1, base.add, clbk )\n    <Float64Array>[ -4.0, 0.0 ]\n    > z0\n    <Float64Array>[ 0.0, 0.0, -4.0, 0.0 ]\n\n\nbase.strided.mapBy2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn, clbk[, thisArg] )\n    Applies a binary function to each pair of elements retrieved from strided\n    input arrays according to a callback function and assigns results to a\n    strided output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offsest parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    fcn: Function\n        Binary function to apply to callback return values.\n\n    clbk: Function\n        Callback function which returns an array-like object containing two\n        values.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 1.0, 1.0, 2.0, 2.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\n    > base.strided.mapBy2.ndarray( 4, x, 1, 0, y, 1, 0, z, 1, 0, base.add, clbk )\n    [ 4.0, -2.0, 10.0, -4.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 1.0, 1.0, 2.0, 2.0 ];\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > base.strided.mapBy2.ndarray( 2, x, 2, 1, y, -1, 3, z, 1, 0, base.add, clbk )\n    [ 0.0, -4.0, 0.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.mapBy, base.strided.binary\n","base.strided.mapBy2.ndarray":"\nbase.strided.mapBy2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn, clbk[, thisArg] )\n    Applies a binary function to each pair of elements retrieved from strided\n    input arrays according to a callback function and assigns results to a\n    strided output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offsest parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    fcn: Function\n        Binary function to apply to callback return values.\n\n    clbk: Function\n        Callback function which returns an array-like object containing two\n        values.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 1.0, 1.0, 2.0, 2.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\n    > base.strided.mapBy2.ndarray( 4, x, 1, 0, y, 1, 0, z, 1, 0, base.add, clbk )\n    [ 4.0, -2.0, 10.0, -4.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 1.0, 1.0, 2.0, 2.0 ];\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > base.strided.mapBy2.ndarray( 2, x, 2, 1, y, -1, 3, z, 1, 0, base.add, clbk )\n    [ 0.0, -4.0, 0.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.mapBy, base.strided.binary","base.strided.max":"\nbase.strided.max( N, x, stride )\n    Computes the maximum value of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.max( x.length, x, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.max( N, x, stride )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.max( N, x1, stride )\n    2.0\n\nbase.strided.max.ndarray( N, x, stride, offset )\n    Computes the maximum value of a strided array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.max.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.max.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.min, base.strided.nanmax, base.strided.smax\n","base.strided.max.ndarray":"\nbase.strided.max.ndarray( N, x, stride, offset )\n    Computes the maximum value of a strided array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.max.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.max.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.min, base.strided.nanmax, base.strided.smax","base.strided.maxabs":"\nbase.strided.maxabs( N, x, stride )\n    Computes the maximum absolute value of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.maxabs( x.length, x, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.maxabs( N, x, stride )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.maxabs( N, x1, stride )\n    2.0\n\nbase.strided.maxabs.ndarray( N, x, stride, offset )\n    Computes the maximum absolute value of a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.maxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.maxabs.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmaxabs, base.strided.max, base.strided.minabs, base.strided.nanmaxabs, base.strided.smaxabs\n","base.strided.maxabs.ndarray":"\nbase.strided.maxabs.ndarray( N, x, stride, offset )\n    Computes the maximum absolute value of a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.maxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.maxabs.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmaxabs, base.strided.max, base.strided.minabs, base.strided.nanmaxabs, base.strided.smaxabs","base.strided.maxBy":"\nbase.strided.maxBy( N, x, stride, clbk[, thisArg] )\n    Calculates the maximum value of a strided array via a callback function.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - aidx: array index.\n    - sidx: strided index (offset + aidx*stride).\n    - array: the input array.\n\n    The callback function should return a numeric value.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.maxBy( x.length, x, 1, accessor )\n    8.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.maxBy( N, x, 2, accessor )\n    8.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.maxBy( N, x1, 2, accessor )\n    -4.0\n\nbase.strided.maxBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the maximum value of a strided array via a callback function and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.maxBy.ndarray( x.length, x, 1, 0, accessor )\n    8.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.maxBy.ndarray( N, x, 2, 1, accessor )\n    -4.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.max, base.strided.minBy, base.strided.nanmaxBy, base.strided.smax\n","base.strided.maxBy.ndarray":"\nbase.strided.maxBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the maximum value of a strided array via a callback function and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.maxBy.ndarray( x.length, x, 1, 0, accessor )\n    8.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.maxBy.ndarray( N, x, 2, 1, accessor )\n    -4.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.max, base.strided.minBy, base.strided.nanmaxBy, base.strided.smax","base.strided.maxsorted":"\nbase.strided.maxsorted( N, x, stride )\n    Computes the maximum value of a sorted strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > base.strided.maxsorted( x.length, x, 1 )\n    3.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.maxsorted( N, x, stride )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.maxsorted( N, x1, stride )\n    3.0\n\nbase.strided.maxsorted.ndarray( N, x, stride, offset )\n    Computes the maximum value of a sorted strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > base.strided.maxsorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.maxsorted.ndarray( N, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmaxsorted, base.strided.max, base.strided.minsorted, base.strided.smaxsorted\n","base.strided.maxsorted.ndarray":"\nbase.strided.maxsorted.ndarray( N, x, stride, offset )\n    Computes the maximum value of a sorted strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > base.strided.maxsorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.maxsorted.ndarray( N, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmaxsorted, base.strided.max, base.strided.minsorted, base.strided.smaxsorted","base.strided.maxViewBufferIndex":"\nbase.strided.maxViewBufferIndex( N, stride, offset )\n    Returns the maximum accessible index based on a set of provided strided\n    array parameters.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    stride: integer\n        Stride length.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    idx: integer\n        Minimum accessible index.\n\n    Examples\n    --------\n    > var idx = base.strided.maxViewBufferIndex( 3, 2, 10 )\n    14\n\n","base.strided.mean":"\nbase.strided.mean( N, x, stride )\n    Computes the arithmetic mean of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.mean( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.mean( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.mean( N, x1, stride )\n    ~-0.3333\n\nbase.strided.mean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.mean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.nanmean, base.strided.smean\n","base.strided.mean.ndarray":"\nbase.strided.mean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.mean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.nanmean, base.strided.smean","base.strided.meankbn":"\nbase.strided.meankbn( N, x, stride )\n    Computes the arithmetic mean of a strided array using an improved Kahan–\n    Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.meankbn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.meankbn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.meankbn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.meankbn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using an improved Kahan–\n    Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meankbn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meankbn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeankbn, base.strided.mean, base.strided.smeankbn\n","base.strided.meankbn.ndarray":"\nbase.strided.meankbn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using an improved Kahan–\n    Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meankbn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meankbn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeankbn, base.strided.mean, base.strided.smeankbn","base.strided.meankbn2":"\nbase.strided.meankbn2( N, x, stride )\n    Computes the arithmetic mean of a strided array using a second-order\n    iterative Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.meankbn2( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.meankbn2( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.meankbn2( N, x1, stride )\n    ~-0.3333\n\nbase.strided.meankbn2.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using a second-order\n    iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meankbn2.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meankbn2.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeankbn2, base.strided.mean, base.strided.smeankbn2\n","base.strided.meankbn2.ndarray":"\nbase.strided.meankbn2.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using a second-order\n    iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meankbn2.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meankbn2.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeankbn2, base.strided.mean, base.strided.smeankbn2","base.strided.meanors":"\nbase.strided.meanors( N, x, stride )\n    Computes the arithmetic mean of a strided array using ordinary recursive\n    summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.meanors( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.meanors( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.meanors( N, x1, stride )\n    ~-0.3333\n\nbase.strided.meanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using ordinary recursive\n    summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanors, base.strided.mean, base.strided.nanmeanors, base.strided.smeanors\n","base.strided.meanors.ndarray":"\nbase.strided.meanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using ordinary recursive\n    summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanors, base.strided.mean, base.strided.nanmeanors, base.strided.smeanors","base.strided.meanpn":"\nbase.strided.meanpn( N, x, stride )\n    Computes the arithmetic mean of a strided array using a two-pass error\n    correction algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.meanpn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.meanpn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.meanpn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.meanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using a two-pass error\n    correction algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.mean, base.strided.nanmeanpn, base.strided.smeanpn\n","base.strided.meanpn.ndarray":"\nbase.strided.meanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using a two-pass error\n    correction algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.mean, base.strided.nanmeanpn, base.strided.smeanpn","base.strided.meanpw":"\nbase.strided.meanpw( N, x, stride )\n    Computes the arithmetic mean of a strided array using pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.meanpw( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.meanpw( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.meanpw( N, x1, stride )\n    ~-0.3333\n\nbase.strided.meanpw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using pairwise summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meanpw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meanpw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpw, base.strided.mean, base.strided.smeanpw\n","base.strided.meanpw.ndarray":"\nbase.strided.meanpw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using pairwise summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meanpw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meanpw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpw, base.strided.mean, base.strided.smeanpw","base.strided.meanwd":"\nbase.strided.meanwd( N, x, stride )\n    Computes the arithmetic mean of a strided array using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.meanwd( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.meanwd( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.meanwd( N, x1, stride )\n    ~-0.3333\n\nbase.strided.meanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using Welford's algorithm\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanwd, base.strided.mean, base.strided.nanmeanwd, base.strided.smeanwd\n","base.strided.meanwd.ndarray":"\nbase.strided.meanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using Welford's algorithm\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanwd, base.strided.mean, base.strided.nanmeanwd, base.strided.smeanwd","base.strided.mediansorted":"\nbase.strided.mediansorted( N, x, stride )\n    Computes the median value of a sorted strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > base.strided.mediansorted( x.length, x, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mediansorted( N, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.mediansorted( N, x1, 2 )\n    2.0\n\nbase.strided.mediansorted.ndarray( N, x, stride, offset )\n    Computes the median value of a sorted strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > base.strided.mediansorted.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mediansorted.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmediansorted, base.strided.mean, base.strided.smediansorted\n","base.strided.mediansorted.ndarray":"\nbase.strided.mediansorted.ndarray( N, x, stride, offset )\n    Computes the median value of a sorted strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > base.strided.mediansorted.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mediansorted.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmediansorted, base.strided.mean, base.strided.smediansorted","base.strided.metaDataProps":"\nbase.strided.metaDataProps( meta, dtypes, obj, bool )\n    Defines non-enumerable read-only properties which expose strided array\n    function meta data.\n\n    Parameters\n    ----------\n    meta: Object\n        Function meta data.\n\n    meta.nargs: integer\n        Total number of arguments (excluding offsets).\n\n    meta.nin: integer\n        Total number of input arrays.\n\n    meta.nout: integer\n        Total number of output arrays.\n\n    dtypes: ArrayLikeObject\n        List of strided array data types.\n\n    obj: Object|Function\n        Object on which to define properties.\n\n    bool: boolean\n        Boolean indicating whether the provided object should describe an\n        \"ndarray\" function interface.\n\n    Returns\n    -------\n    out: Object|Function\n        Object on which properties were defined.\n\n    Examples\n    --------\n    > var meta = { 'nargs': 7, 'nin': 1, 'nout': 1 };\n    > var dt = [ 'float64', 'float64' ];\n    > var obj = {};\n    > base.strided.metaDataProps( meta, dt, obj, false );\n    > obj.nargs\n    7\n    > obj.nin\n    1\n    > obj.nout\n    1\n    > obj.types\n    [...]\n\n","base.strided.min":"\nbase.strided.min( N, x, stride )\n    Computes the minimum value of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.min( x.length, x, 1 )\n    -2.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.min( N, x, stride )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.min( N, x1, stride )\n    -2.0\n\nbase.strided.min.ndarray( N, x, stride, offset )\n    Computes the minimum value of a strided array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.min.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.min.ndarray( N, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.max, base.strided.nanmin, base.strided.smin\n","base.strided.min.ndarray":"\nbase.strided.min.ndarray( N, x, stride, offset )\n    Computes the minimum value of a strided array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.min.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.min.ndarray( N, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.max, base.strided.nanmin, base.strided.smin","base.strided.minabs":"\nbase.strided.minabs( N, x, stride )\n    Computes the minimum absolute value of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.minabs( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.minabs( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.minabs( N, x1, stride )\n    1.0\n\nbase.strided.minabs.ndarray( N, x, stride, offset )\n    Computes the minimum absolute value of a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.minabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.minabs.ndarray( N, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dminabs, base.strided.maxabs, base.strided.min, base.strided.nanminabs, base.strided.sminabs\n","base.strided.minabs.ndarray":"\nbase.strided.minabs.ndarray( N, x, stride, offset )\n    Computes the minimum absolute value of a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.minabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.minabs.ndarray( N, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dminabs, base.strided.maxabs, base.strided.min, base.strided.nanminabs, base.strided.sminabs","base.strided.minBy":"\nbase.strided.minBy( N, x, stride, clbk[, thisArg] )\n    Calculates the minimum value of a strided array via a callback function.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - aidx: array index.\n    - sidx: strided index (offset + aidx*stride).\n    - array: the input array.\n\n    The callback function should return a numeric value.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.minBy( x.length, x, 1, accessor )\n    -10.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.minBy( N, x, 2, accessor )\n    -4.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.minBy( N, x1, 2, accessor )\n    -12.0\n\nbase.strided.minBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the minimum value of a strided array via a callback function and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.minBy.ndarray( x.length, x, 1, 0, accessor )\n    -10.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.minBy.ndarray( N, x, 2, 1, accessor )\n    -12.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.maxBy, base.strided.min, base.strided.nanminBy, base.strided.smin\n","base.strided.minBy.ndarray":"\nbase.strided.minBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the minimum value of a strided array via a callback function and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.minBy.ndarray( x.length, x, 1, 0, accessor )\n    -10.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.minBy.ndarray( N, x, 2, 1, accessor )\n    -12.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.maxBy, base.strided.min, base.strided.nanminBy, base.strided.smin","base.strided.minsorted":"\nbase.strided.minsorted( N, x, stride )\n    Computes the minimum value of a sorted strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > base.strided.minsorted( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.minsorted( N, x, stride )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.minsorted( N, x1, stride )\n    -2.0\n\nbase.strided.minsorted.ndarray( N, x, stride, offset )\n    Computes the minimum value of a sorted strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > base.strided.minsorted.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.minsorted.ndarray( N, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dminsorted, base.strided.maxsorted, base.strided.min, base.strided.sminsorted\n","base.strided.minsorted.ndarray":"\nbase.strided.minsorted.ndarray( N, x, stride, offset )\n    Computes the minimum value of a sorted strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > base.strided.minsorted.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.minsorted.ndarray( N, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dminsorted, base.strided.maxsorted, base.strided.min, base.strided.sminsorted","base.strided.minViewBufferIndex":"\nbase.strided.minViewBufferIndex( N, stride, offset )\n    Returns the minimum accessible index based on a set of provided strided\n    array parameters.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    stride: integer\n        Stride length.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    idx: integer\n        Minimum accessible index.\n\n    Examples\n    --------\n    > var idx = base.strided.minViewBufferIndex( 3, -2, 10 )\n    6\n\n    See Also\n    --------\n    base.strided.offsetView\n","base.strided.mskmax":"\nbase.strided.mskmax( N, x, strideX, mask, strideMask )\n    Computes the maximum value of a strided array according to a mask.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 4.0, 2.0 ];\n    > var mask = [ 0, 0, 1, 0 ];\n    > base.strided.mskmax( x.length, x, 1, mask, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mskmax( N, x, 2, mask, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.mskmax( N, x1, 2, mask1, 2 )\n    2.0\n\nbase.strided.mskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a strided array according to a mask and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n    > var mask = [ 0, 0, 0, 1 ];\n    > base.strided.mskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmskmax, base.strided.max, base.strided.mskmin, base.strided.nanmax, base.strided.smskmax\n","base.strided.mskmax.ndarray":"\nbase.strided.mskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a strided array according to a mask and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n    > var mask = [ 0, 0, 0, 1 ];\n    > base.strided.mskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmskmax, base.strided.max, base.strided.mskmin, base.strided.nanmax, base.strided.smskmax","base.strided.mskmin":"\nbase.strided.mskmin( N, x, strideX, mask, strideMask )\n    Computes the minimum value of a strided array according to a mask.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, -4.0, 2.0 ];\n    > var mask = [ 0, 0, 1, 0 ];\n    > base.strided.mskmin( x.length, x, 1, mask, 1 )\n    -2.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mskmin( N, x, 2, mask, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.mskmin( N, x1, 2, mask1, 2 )\n    -2.0\n\nbase.strided.mskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a strided array according to a mask and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, -4.0 ];\n    > var mask = [ 0, 0, 0, 1 ];\n    > base.strided.mskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmskmin, base.strided.min, base.strided.mskmax, base.strided.nanmin, base.strided.smskmin\n","base.strided.mskmin.ndarray":"\nbase.strided.mskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a strided array according to a mask and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, -4.0 ];\n    > var mask = [ 0, 0, 0, 1 ];\n    > base.strided.mskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmskmin, base.strided.min, base.strided.mskmax, base.strided.nanmin, base.strided.smskmin","base.strided.mskrange":"\nbase.strided.mskrange( N, x, strideX, mask, strideMask )\n    Computes the range of a strided array according to a mask.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 4.0, 2.0 ];\n    > var mask = [ 0, 0, 1, 0 ];\n    > base.strided.mskrange( x.length, x, 1, mask, 1 )\n    4.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mskrange( N, x, 2, mask, 2 )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.mskrange( N, x1, 2, mask1, 2 )\n    4.0\n\nbase.strided.mskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a strided array according to a mask and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n    > var mask = [ 0, 0, 0, 1 ];\n    > base.strided.mskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dmskrange, base.strided.range, base.strided.mskmax, base.strided.mskmin, base.strided.nanrange, base.strided.smskrange\n","base.strided.mskrange.ndarray":"\nbase.strided.mskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a strided array according to a mask and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n    > var mask = [ 0, 0, 0, 1 ];\n    > base.strided.mskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dmskrange, base.strided.range, base.strided.mskmax, base.strided.mskmin, base.strided.nanrange, base.strided.smskrange","base.strided.mskunary":"\nbase.strided.mskunary( arrays, shape, strides, fcn )\n    Applies a unary callback to elements in a strided input array according to\n    elements in a strided mask array and assigns results to elements in a\n    strided output array.\n\n    The `shape` and `strides` parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided input array, a strided mask\n        array, and one strided output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided arrays.\n\n    fcn: Function\n        Unary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1 ];\n    > base.strided.mskunary( [ x, m, y ], shape, strides, base.abs );\n    > y\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n\nbase.strided.mskunary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a unary callback to elements in a strided input array according to\n    elements in a strided mask array, and assigns results to elements in a\n    strided output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided input array, a strided mask\n        array, and one strided output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided arrays.\n\n    fcn: Function\n        Unary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1 ];\n    > var offsets = [ 0, 0, 0 ];\n    > base.strided.mskunary.ndarray( [ x, m, y ], shape, strides, offsets, base.abs );\n    > y\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    See Also\n    --------\n    base.strided.dmskmap, base.strided.smskmap, base.strided.unary\n","base.strided.mskunary.ndarray":"\nbase.strided.mskunary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a unary callback to elements in a strided input array according to\n    elements in a strided mask array, and assigns results to elements in a\n    strided output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided input array, a strided mask\n        array, and one strided output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided arrays.\n\n    fcn: Function\n        Unary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1 ];\n    > var offsets = [ 0, 0, 0 ];\n    > base.strided.mskunary.ndarray( [ x, m, y ], shape, strides, offsets, base.abs );\n    > y\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    See Also\n    --------\n    base.strided.dmskmap, base.strided.smskmap, base.strided.unary","base.strided.mskunaryDtypeSignatures":"\nbase.strided.mskunaryDtypeSignatures( dtypes1, dtypes2[, options] )\n    Generates a list of masked unary interface signatures from strided array\n    data types.\n\n    The function returns a strided array having a stride length of three (i.e.,\n    every three elements define a masked unary interface signature).\n\n    For each signature (i.e., set of three consecutive non-overlapping strided\n    array elements), the first element is the input data type, the second\n    element is the mask data type, and the last element is the return data type.\n\n    All signatures follow type promotion rules.\n\n    The mask array data type is always `uint8`.\n\n    Parameters\n    ----------\n    dtypes1: ArrayLike<any>\n        List of supported data types for the input argument.\n\n    dtypes2: ArrayLike<any>\n        List of supported data types for the output argument.\n\n    options: Object (optional)\n        Options.\n\n    options.enums: boolean (optional)\n        Boolean flag indicating whether to return signatures as a list of data\n        type enumeration constants. Default: false.\n\n    Returns\n    -------\n    out: Array\n        Strided array containing masked unary interface signatures.\n\n    Examples\n    --------\n    > var dt = strided.dataTypes();\n    > var out = base.strided.mskunaryDtypeSignatures( dt, dt )\n    [...]\n\n    See Also\n    --------\n    base.strided.mskunarySignatureCallbacks\n","base.strided.mskunarySignatureCallbacks":"\nbase.strided.mskunarySignatureCallbacks( table, signatures )\n    Assigns callbacks to masked unary interfaces according to type promotion\n    rules.\n\n    Parameters\n    ----------\n    table: Object\n        Object mapping callbacks to data types.\n\n    table.default: Function\n        Default callback.\n\n    table.complex64: Function\n        Callback to be invoked when input arrays promote to single-precision\n        complex floating-point numbers.\n\n    table.complex128: Function\n        Callback to be invoked when input arrays promote to double precision\n        complex floating-point numbers.\n\n    signatures: ArrayLike<any>\n        Strided array containing masked unary interface signatures.\n\n    Returns\n    -------\n    out: Array<Function>\n        List of callbacks, one per signature.\n\n    Examples\n    --------\n    > var dt = strided.dataTypes();\n    > var sigs = base.strided.mskunaryDtypeSignatures( dt, dt );\n    > var t = {\n    ...     'default': base.identity,\n    ...     'complex64': base.cidentityf,\n    ...     'complex128': base.cidentity\n    ... };\n    > var out = base.strided.mskunarySignatureCallbacks( t, sigs )\n    [...]\n\n    See Also\n    --------\n    base.strided.mskunaryDtypeSignatures\n","base.strided.nanmax":"\nbase.strided.nanmax( N, x, stride )\n    Computes the maximum value of a strided array, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmax( x.length, x, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanmax( N, x, stride )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanmax( N, x1, stride )\n    2.0\n\nbase.strided.nanmax.ndarray( N, x, stride, offset )\n    Computes the maximum value of a strided array, ignoring `NaN` values and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmax.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmax.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmax, base.strided.max, base.strided.nanmin, base.strided.snanmax\n","base.strided.nanmax.ndarray":"\nbase.strided.nanmax.ndarray( N, x, stride, offset )\n    Computes the maximum value of a strided array, ignoring `NaN` values and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmax.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmax.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmax, base.strided.max, base.strided.nanmin, base.strided.snanmax","base.strided.nanmaxabs":"\nbase.strided.nanmaxabs( N, x, stride )\n    Computes the maximum absolute value of a strided array, ignoring `NaN`\n    values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmaxabs( x.length, x, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanmaxabs( N, x, stride )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanmaxabs( N, x1, stride )\n    2.0\n\nbase.strided.nanmaxabs.ndarray( N, x, stride, offset )\n    Computes the maximum absolute value of a strided array, ignoring `NaN`\n    values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmaxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmaxabs.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmaxabs, base.strided.maxabs, base.strided.nanmax, base.strided.nanminabs, base.strided.snanmaxabs\n","base.strided.nanmaxabs.ndarray":"\nbase.strided.nanmaxabs.ndarray( N, x, stride, offset )\n    Computes the maximum absolute value of a strided array, ignoring `NaN`\n    values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmaxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmaxabs.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmaxabs, base.strided.maxabs, base.strided.nanmax, base.strided.nanminabs, base.strided.snanmaxabs","base.strided.nanmaxBy":"\nbase.strided.nanmaxBy( N, x, stride, clbk[, thisArg] )\n    Calculates the maximum value of a strided array via a callback function,\n    ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - aidx: array index.\n    - sidx: strided index (offset + aidx*stride).\n    - array: the input array.\n\n    The callback function should return a numeric value.\n\n    If the callback function returns `NaN`, the value is ignored.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n    > base.strided.nanmaxBy( x.length, x, 1, accessor )\n    8.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmaxBy( N, x, 2, accessor )\n    8.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanmaxBy( N, x1, 2, accessor )\n    -4.0\n\nbase.strided.nanmaxBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the maximum value of a strided array via a callback function,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n    > base.strided.nanmaxBy.ndarray( x.length, x, 1, 0, accessor )\n    8.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmaxBy.ndarray( N, x, 2, 1, accessor )\n    -4.0\n\n    See Also\n    --------\n    base.strided.dnanmax, base.strided.maxBy, base.strided.nanmax, base.strided.nanminBy, base.strided.snanmax\n","base.strided.nanmaxBy.ndarray":"\nbase.strided.nanmaxBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the maximum value of a strided array via a callback function,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n    > base.strided.nanmaxBy.ndarray( x.length, x, 1, 0, accessor )\n    8.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmaxBy.ndarray( N, x, 2, 1, accessor )\n    -4.0\n\n    See Also\n    --------\n    base.strided.dnanmax, base.strided.maxBy, base.strided.nanmax, base.strided.nanminBy, base.strided.snanmax","base.strided.nanmean":"\nbase.strided.nanmean( N, x, stride )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmean( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanmean( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanmean( N, x1, stride )\n    ~-0.3333\n\nbase.strided.nanmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.mean, base.strided.snanmean\n","base.strided.nanmean.ndarray":"\nbase.strided.nanmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.mean, base.strided.snanmean","base.strided.nanmeanors":"\nbase.strided.nanmeanors( N, x, stride )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using ordinary recursive summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmeanors( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanmeanors( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanmeanors( N, x1, stride )\n    ~-0.3333\n\nbase.strided.nanmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanors, base.strided.meanors, base.strided.nanmean, base.strided.snanmeanors\n","base.strided.nanmeanors.ndarray":"\nbase.strided.nanmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanors, base.strided.meanors, base.strided.nanmean, base.strided.snanmeanors","base.strided.nanmeanpn":"\nbase.strided.nanmeanpn( N, x, stride )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using a two-pass error correction algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmeanpn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanmeanpn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanmeanpn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.nanmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using a two-pass error correction algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanpn, base.strided.meanpn, base.strided.nanmean, base.strided.snanmeanpn\n","base.strided.nanmeanpn.ndarray":"\nbase.strided.nanmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using a two-pass error correction algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanpn, base.strided.meanpn, base.strided.nanmean, base.strided.snanmeanpn","base.strided.nanmeanwd":"\nbase.strided.nanmeanwd( N, x, stride )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmeanwd( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanmeanwd( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanmeanwd( N, x1, stride )\n    ~-0.3333\n\nbase.strided.nanmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanwd, base.strided.meanwd, base.strided.nanmean, base.strided.snanmeanwd\n","base.strided.nanmeanwd.ndarray":"\nbase.strided.nanmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanwd, base.strided.meanwd, base.strided.nanmean, base.strided.snanmeanwd","base.strided.nanmin":"\nbase.strided.nanmin( N, x, stride )\n    Computes the minimum value of a strided array, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmin( x.length, x, 1 )\n    -2.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanmin( N, x, stride )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanmin( N, x1, stride )\n    -2.0\n\nbase.strided.nanmin.ndarray( N, x, stride, offset )\n    Computes the minimum value of a strided array, ignoring `NaN` values and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmin.ndarray( N, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dnanmin, base.strided.min, base.strided.nanmax, base.strided.snanmin\n","base.strided.nanmin.ndarray":"\nbase.strided.nanmin.ndarray( N, x, stride, offset )\n    Computes the minimum value of a strided array, ignoring `NaN` values and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmin.ndarray( N, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dnanmin, base.strided.min, base.strided.nanmax, base.strided.snanmin","base.strided.nanminabs":"\nbase.strided.nanminabs( N, x, stride )\n    Computes the minimum absolute value of a strided array, ignoring `NaN`\n    values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanminabs( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanminabs( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanminabs( N, x1, stride )\n    1.0\n\nbase.strided.nanminabs.ndarray( N, x, stride, offset )\n    Computes the minimum absolute value of a strided array, ignoring `NaN`\n    values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanminabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanminabs.ndarray( N, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dnanminabs, base.strided.minabs, base.strided.nanmaxabs, base.strided.nanmin, base.strided.snanminabs\n","base.strided.nanminabs.ndarray":"\nbase.strided.nanminabs.ndarray( N, x, stride, offset )\n    Computes the minimum absolute value of a strided array, ignoring `NaN`\n    values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanminabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanminabs.ndarray( N, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dnanminabs, base.strided.minabs, base.strided.nanmaxabs, base.strided.nanmin, base.strided.snanminabs","base.strided.nanminBy":"\nbase.strided.nanminBy( N, x, stride, clbk[, thisArg] )\n    Calculates the minimum value of a strided array via a callback function,\n    ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - aidx: array index.\n    - sidx: strided index (offset + aidx*stride).\n    - array: the input array.\n\n    The callback function should return a numeric value.\n\n    If the callback function returns `NaN`, the value is ignored.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n    > base.strided.nanminBy( x.length, x, 1, accessor )\n    -10.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, NaN, -3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanminBy( N, x, 2, accessor )\n    -4.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanminBy( N, x1, 2, accessor )\n    -12.0\n\nbase.strided.nanminBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the minimum value of a strided array via a callback function,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n    > base.strided.nanminBy.ndarray( x.length, x, 1, 0, accessor )\n    -10.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanminBy.ndarray( N, x, 2, 1, accessor )\n    -12.0\n\n    See Also\n    --------\n    base.strided.dnanmin, base.strided.minBy, base.strided.nanmaxBy, base.strided.nanmin, base.strided.snanmin\n","base.strided.nanminBy.ndarray":"\nbase.strided.nanminBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the minimum value of a strided array via a callback function,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n    > base.strided.nanminBy.ndarray( x.length, x, 1, 0, accessor )\n    -10.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanminBy.ndarray( N, x, 2, 1, accessor )\n    -12.0\n\n    See Also\n    --------\n    base.strided.dnanmin, base.strided.minBy, base.strided.nanmaxBy, base.strided.nanmin, base.strided.snanmin","base.strided.nanmskmax":"\nbase.strided.nanmskmax( N, x, strideX, mask, strideMask )\n    Computes the maximum value of a strided array according to a mask and\n    ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\n    > var mask = [ 0, 0, 1, 0, 0 ];\n    > base.strided.nanmskmax( x.length, x, 1, mask, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmskmax( N, x, 2, mask, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanmskmax( N, x1, 2, mask1, 2 )\n    2.0\n\nbase.strided.nanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a strided array according to a mask,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n    > var mask = [ 0, 0, 0, 1, 0 ];\n    > base.strided.nanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmskmax, base.strided.mskmax, base.strided.nanmax, base.strided.nanmskmin, base.strided.snanmskmax\n","base.strided.nanmskmax.ndarray":"\nbase.strided.nanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a strided array according to a mask,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n    > var mask = [ 0, 0, 0, 1, 0 ];\n    > base.strided.nanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmskmax, base.strided.mskmax, base.strided.nanmax, base.strided.nanmskmin, base.strided.snanmskmax","base.strided.nanmskmin":"\nbase.strided.nanmskmin( N, x, strideX, mask, strideMask )\n    Computes the minimum value of a strided array according to a mask and\n    ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, -4.0, 2.0, NaN ];\n    > var mask = [ 0, 0, 1, 0, 0 ];\n    > base.strided.nanmskmin( x.length, x, 1, mask, 1 )\n    -2.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmskmin( N, x, 2, mask, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanmskmin( N, x1, 2, mask1, 2 )\n    -2.0\n\nbase.strided.nanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a strided array according to a mask, ignoring\n    `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, -4.0, NaN ];\n    > var mask = [ 0, 0, 0, 1, 0 ];\n    > base.strided.nanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dnanmskmin, base.strided.mskmin, base.strided.nanmin, base.strided.nanmskmax, base.strided.snanmskmin\n","base.strided.nanmskmin.ndarray":"\nbase.strided.nanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a strided array according to a mask, ignoring\n    `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, -4.0, NaN ];\n    > var mask = [ 0, 0, 0, 1, 0 ];\n    > base.strided.nanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dnanmskmin, base.strided.mskmin, base.strided.nanmin, base.strided.nanmskmax, base.strided.snanmskmin","base.strided.nanmskrange":"\nbase.strided.nanmskrange( N, x, strideX, mask, strideMask )\n    Computes the range of a strided array according to a mask and ignoring `NaN`\n    values.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\n    > var mask = [ 0, 0, 1, 0, 0 ];\n    > base.strided.nanmskrange( x.length, x, 1, mask, 1 )\n    4.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmskrange( N, x, 2, mask, 2 )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanmskrange( N, x1, 2, mask1, 2 )\n    4.0\n\nbase.strided.nanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a strided array according to a mask, ignoring `NaN`\n    values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n    > var mask = [ 0, 0, 0, 1, 0 ];\n    > base.strided.nanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dnanmskrange, base.strided.mskrange, base.strided.nanrange, base.strided.nanmskmax, base.strided.nanmskmin, base.strided.snanmskrange\n","base.strided.nanmskrange.ndarray":"\nbase.strided.nanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a strided array according to a mask, ignoring `NaN`\n    values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n    > var mask = [ 0, 0, 0, 1, 0 ];\n    > base.strided.nanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dnanmskrange, base.strided.mskrange, base.strided.nanrange, base.strided.nanmskmax, base.strided.nanmskmin, base.strided.snanmskrange","base.strided.nanrange":"\nbase.strided.nanrange( N, x, stride )\n    Computes the range of a strided array, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanrange( x.length, x, 1 )\n    4.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanrange( N, x, stride )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanrange( N, x1, stride )\n    4.0\n\nbase.strided.nanrange.ndarray( N, x, stride, offset )\n    Computes the range of a strided array, ignoring `NaN` values and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanrange.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanrange.ndarray( N, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dnanrange, base.strided.nanmax, base.strided.nanmin, base.strided.range, base.strided.snanrange\n","base.strided.nanrange.ndarray":"\nbase.strided.nanrange.ndarray( N, x, stride, offset )\n    Computes the range of a strided array, ignoring `NaN` values and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanrange.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanrange.ndarray( N, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dnanrange, base.strided.nanmax, base.strided.nanmin, base.strided.range, base.strided.snanrange","base.strided.nanrangeBy":"\nbase.strided.nanrangeBy( N, x, stride, clbk[, thisArg] )\n    Calculates the range of a strided array via a callback function, ignoring\n    `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - aidx: array index.\n    - sidx: strided index (offset + aidx*stride).\n    - array: the input array.\n\n    The callback function should return a numeric value.\n\n    If the callback function returns `NaN`, the value is ignored.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n    > base.strided.nanrangeBy( x.length, x, 1, accessor )\n    18.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0, 1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanrangeBy( N, x, 2, accessor )\n    14.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanrangeBy( N, x1, 2, accessor )\n    8.0\n\nbase.strided.nanrangeBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the range of a strided array via a callback function, ignoring\n    `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n    > base.strided.nanrangeBy.ndarray( x.length, x, 1, 0, accessor )\n    18.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanrangeBy.ndarray( N, x, 2, 1, accessor )\n    8.0\n\n    See Also\n    --------\n    base.strided.dnanrange, base.strided.nanmaxBy, base.strided.nanminBy, base.strided.nanrange, base.strided.rangeBy, base.strided.snanrange\n","base.strided.nanrangeBy.ndarray":"\nbase.strided.nanrangeBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the range of a strided array via a callback function, ignoring\n    `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n    > base.strided.nanrangeBy.ndarray( x.length, x, 1, 0, accessor )\n    18.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanrangeBy.ndarray( N, x, 2, 1, accessor )\n    8.0\n\n    See Also\n    --------\n    base.strided.dnanrange, base.strided.nanmaxBy, base.strided.nanminBy, base.strided.nanrange, base.strided.rangeBy, base.strided.snanrange","base.strided.nanstdev":"\nbase.strided.nanstdev( N, correction, x, stride )\n    Computes the standard deviation of a strided array ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdev( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdev( N, 1, x, 2 )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanstdev( N, 1, x1, 2 )\n    ~2.0817\n\nbase.strided.nanstdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.nanvariance, base.strided.snanstdev, base.strided.stdev\n","base.strided.nanstdev.ndarray":"\nbase.strided.nanstdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.nanvariance, base.strided.snanstdev, base.strided.stdev","base.strided.nanstdevch":"\nbase.strided.nanstdevch( N, correction, x, stride )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevch( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevch( N, 1, x, 2 )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanstdevch( N, 1, x1, 2 )\n    ~2.0817\n\nbase.strided.nanstdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass trial mean algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevch, base.strided.nanvariancech, base.strided.nanstdev, base.strided.snanstdevch, base.strided.stdevch\n","base.strided.nanstdevch.ndarray":"\nbase.strided.nanstdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass trial mean algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevch, base.strided.nanvariancech, base.strided.nanstdev, base.strided.snanstdevch, base.strided.stdevch","base.strided.nanstdevpn":"\nbase.strided.nanstdevpn( N, correction, x, stride )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevpn( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevpn( N, 1, x, 2 )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanstdevpn( N, 1, x1, 2 )\n    ~2.0817\n\nbase.strided.nanstdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevpn, base.strided.nanvariancepn, base.strided.nanstdev, base.strided.snanstdevpn, base.strided.stdevpn\n","base.strided.nanstdevpn.ndarray":"\nbase.strided.nanstdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevpn, base.strided.nanvariancepn, base.strided.nanstdev, base.strided.snanstdevpn, base.strided.stdevpn","base.strided.nanstdevtk":"\nbase.strided.nanstdevtk( N, correction, x, stride )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevtk( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevtk( N, 1, x, 2 )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanstdevtk( N, 1, x1, 2 )\n    ~2.0817\n\nbase.strided.nanstdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass textbook algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevtk, base.strided.nanvariancetk, base.strided.nanstdev, base.strided.snanstdevtk, base.strided.stdevtk\n","base.strided.nanstdevtk.ndarray":"\nbase.strided.nanstdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass textbook algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevtk, base.strided.nanvariancetk, base.strided.nanstdev, base.strided.snanstdevtk, base.strided.stdevtk","base.strided.nanstdevwd":"\nbase.strided.nanstdevwd( N, correction, x, stride )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevwd( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevwd( N, 1, x, 2 )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanstdevwd( N, 1, x1, 2 )\n    ~2.0817\n\nbase.strided.nanstdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevwd, base.strided.nanvariancewd, base.strided.nanstdev, base.strided.snanstdevwd, base.strided.stdevwd\n","base.strided.nanstdevwd.ndarray":"\nbase.strided.nanstdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevwd, base.strided.nanvariancewd, base.strided.nanstdev, base.strided.snanstdevwd, base.strided.stdevwd","base.strided.nanstdevyc":"\nbase.strided.nanstdevyc( N, correction, x, stride )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass algorithm proposed by Youngs and Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevyc( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevyc( N, 1, x, 2 )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanstdevyc( N, 1, x1, 2 )\n    ~2.0817\n\nbase.strided.nanstdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass algorithm proposed by Youngs and Cramer and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevyc, base.strided.nanvarianceyc, base.strided.nanstdev, base.strided.snanstdevyc, base.strided.stdevyc\n","base.strided.nanstdevyc.ndarray":"\nbase.strided.nanstdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass algorithm proposed by Youngs and Cramer and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevyc, base.strided.nanvarianceyc, base.strided.nanstdev, base.strided.snanstdevyc, base.strided.stdevyc","base.strided.nanvariance":"\nbase.strided.nanvariance( N, correction, x, stride )\n    Computes the variance of a strided array ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariance( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanvariance( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanvariance( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.nanvariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariance, base.strided.nanstdev, base.strided.snanvariance, base.strided.variance\n","base.strided.nanvariance.ndarray":"\nbase.strided.nanvariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariance, base.strided.nanstdev, base.strided.snanvariance, base.strided.variance","base.strided.nanvariancech":"\nbase.strided.nanvariancech( N, correction, x, stride )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancech( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanvariancech( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanvariancech( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.nanvariancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass trial mean algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvariancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancech, base.strided.nanstdevch, base.strided.nanvariance, base.strided.snanvariancech, base.strided.variancech\n","base.strided.nanvariancech.ndarray":"\nbase.strided.nanvariancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass trial mean algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvariancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancech, base.strided.nanstdevch, base.strided.nanvariance, base.strided.snanvariancech, base.strided.variancech","base.strided.nanvariancepn":"\nbase.strided.nanvariancepn( N, correction, x, stride )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancepn( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanvariancepn( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanvariancepn( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.nanvariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancepn, base.strided.nanstdevpn, base.strided.nanvariance, base.strided.snanvariancepn, base.strided.variancepn\n","base.strided.nanvariancepn.ndarray":"\nbase.strided.nanvariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancepn, base.strided.nanstdevpn, base.strided.nanvariance, base.strided.snanvariancepn, base.strided.variancepn","base.strided.nanvariancetk":"\nbase.strided.nanvariancetk( N, correction, x, stride )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancetk( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanvariancetk( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanvariancetk( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.nanvariancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass textbook algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvariancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancetk, base.strided.nanstdevtk, base.strided.nanvariance, base.strided.snanvariancetk, base.strided.variancetk\n","base.strided.nanvariancetk.ndarray":"\nbase.strided.nanvariancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass textbook algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvariancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancetk, base.strided.nanstdevtk, base.strided.nanvariance, base.strided.snanvariancetk, base.strided.variancetk","base.strided.nanvariancewd":"\nbase.strided.nanvariancewd( N, correction, x, stride )\n    Computes the variance of a strided array ignoring `NaN` values and using\n    Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancewd( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanvariancewd( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanvariancewd( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.nanvariancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using\n    Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvariancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancewd, base.strided.nanstdevwd, base.strided.nanvariance, base.strided.snanvariancewd, base.strided.variancewd\n","base.strided.nanvariancewd.ndarray":"\nbase.strided.nanvariancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using\n    Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvariancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancewd, base.strided.nanstdevwd, base.strided.nanvariance, base.strided.snanvariancewd, base.strided.variancewd","base.strided.nanvarianceyc":"\nbase.strided.nanvarianceyc( N, correction, x, stride )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass algorithm proposed by Youngs and Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvarianceyc( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanvarianceyc( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanvarianceyc( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.nanvarianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass algorithm proposed by Youngs and Cramer and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvarianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvarianceyc, base.strided.nanstdevyc, base.strided.nanvariance, base.strided.snanvarianceyc, base.strided.varianceyc\n","base.strided.nanvarianceyc.ndarray":"\nbase.strided.nanvarianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass algorithm proposed by Youngs and Cramer and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvarianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvarianceyc, base.strided.nanstdevyc, base.strided.nanvariance, base.strided.snanvarianceyc, base.strided.varianceyc","base.strided.nullary":"\nbase.strided.nullary( arrays, shape, strides, fcn )\n    Applies a nullary callback and assigns results to elements in a strided\n    output array.\n\n    The `shape` and `strides` parameters determine which elements in the strided\n    output array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride length for the strided output\n        array.\n\n    fcn: Function\n        Nullary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1 ];\n    > var fcn = constantFunction( 3.0 );\n    > base.strided.nullary( [ x ], shape, strides, fcn );\n    > x\n    <Float64Array>[ 3.0, 3.0, 3.0, 3.0 ]\n\n\nbase.strided.nullary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a nullary callback and assigns results to elements in a strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride length for the strided output\n        array.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting index (i.e., index offset) for\n        the strided output array.\n\n    fcn: Function\n        Nullary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1 ];\n    > var offsets = [ 0 ];\n    > var fcn = constantFunction( 3.0 );\n    > base.strided.nullary.ndarray( [ x ], shape, strides, offsets, fcn );\n    > x\n    <Float64Array>[ 3.0, 3.0, 3.0, 3.0 ]\n\n    See Also\n    --------\n    base.strided.binary, base.strided.quaternary, base.strided.quinary, base.strided.ternary, base.strided.unary\n","base.strided.nullary.ndarray":"\nbase.strided.nullary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a nullary callback and assigns results to elements in a strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride length for the strided output\n        array.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting index (i.e., index offset) for\n        the strided output array.\n\n    fcn: Function\n        Nullary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1 ];\n    > var offsets = [ 0 ];\n    > var fcn = constantFunction( 3.0 );\n    > base.strided.nullary.ndarray( [ x ], shape, strides, offsets, fcn );\n    > x\n    <Float64Array>[ 3.0, 3.0, 3.0, 3.0 ]\n\n    See Also\n    --------\n    base.strided.binary, base.strided.quaternary, base.strided.quinary, base.strided.ternary, base.strided.unary","base.strided.offsetView":"\nbase.strided.offsetView( x, offset )\n    Returns a typed array view having the same data type as a provided input\n    typed array and starting at a specified index offset.\n\n    Parameters\n    ----------\n    x: TypedArray\n        Input array.\n\n    offset: integer\n        Starting index of the view relative to the input array.\n\n    Returns\n    -------\n    out: TypedArray\n        Typed array view having the same data type as the input array.\n\n    Examples\n    --------\n    > var x = new Float64Array( 10 );\n    > var out = base.strided.offsetView( x, 0 )\n    <Float64Array>\n    > var bool = ( out.buffer === x.buffer )\n    true\n\n    See Also\n    --------\n    base.strided.minViewBufferIndex\n","base.strided.quaternary":"\nbase.strided.quaternary( arrays, shape, strides, fcn )\n    Applies a quaternary callback to strided input array elements and assigns\n    results to elements in a strided output array.\n\n    The `shape` and `strides` parameters determine which elements in the strided\n    input and output arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing four strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    fcn: Function\n        Quaternary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1, 1, 1 ];\n    > function f( x, y, z, w ) { return x + y + z + w; };\n    > base.strided.quaternary( [ x, y, z, w, u ], shape, strides, f );\n    > u\n    <Float64Array>[ 4.0, 8.0, 12.0, 16.0 ]\n\n\nbase.strided.quaternary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a quaternary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing four strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Quaternary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1, 1, 1 ];\n    > var offsets = [ 0, 0, 0, 0, 0 ];\n    > function f( x, y, z, w ) { return x + y + z + w; };\n    > base.strided.quaternary.ndarray( [ x, y, z, w, u ], shape, strides, offsets, f );\n    > u\n    <Float64Array>[ 4.0, 8.0, 12.0, 16.0 ]\n\n    See Also\n    --------\n    base.strided.binary, base.strided.nullary, base.strided.quinary, base.strided.ternary, base.strided.unary\n","base.strided.quaternary.ndarray":"\nbase.strided.quaternary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a quaternary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing four strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Quaternary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1, 1, 1 ];\n    > var offsets = [ 0, 0, 0, 0, 0 ];\n    > function f( x, y, z, w ) { return x + y + z + w; };\n    > base.strided.quaternary.ndarray( [ x, y, z, w, u ], shape, strides, offsets, f );\n    > u\n    <Float64Array>[ 4.0, 8.0, 12.0, 16.0 ]\n\n    See Also\n    --------\n    base.strided.binary, base.strided.nullary, base.strided.quinary, base.strided.ternary, base.strided.unary","base.strided.quinary":"\nbase.strided.quinary( arrays, shape, strides, fcn )\n    Applies a quinary callback to strided input array elements and assigns\n    results to elements in a strided output array.\n\n    The `shape` and `strides` parameters determine which elements in the strided\n    input and output arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing five strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    fcn: Function\n        Quinary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1, 1, 1, 1 ];\n    > function f( x, y, z, w, u ) { return x + y + z + w + u; };\n    > base.strided.quinary( [ x, y, z, w, u, v ], shape, strides, f );\n    > v\n    <Float64Array>[ 5.0, 10.0, 15.0, 20.0 ]\n\n\nbase.strided.quinary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a quinary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing five strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Quinary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1, 1, 1, 1 ];\n    > var offsets = [ 0, 0, 0, 0, 0, 0 ];\n    > function f( x, y, z, w, u ) { return x + y + z + w + u; };\n    > base.strided.quinary.ndarray( [ x, y, z, w, u, v ], shape, strides, offsets, f );\n    > v\n    <Float64Array>[ 5.0, 10.0, 15.0, 20.0 ]\n\n    See Also\n    --------\n    base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.ternary, base.strided.unary\n","base.strided.quinary.ndarray":"\nbase.strided.quinary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a quinary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing five strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Quinary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1, 1, 1, 1 ];\n    > var offsets = [ 0, 0, 0, 0, 0, 0 ];\n    > function f( x, y, z, w, u ) { return x + y + z + w + u; };\n    > base.strided.quinary.ndarray( [ x, y, z, w, u, v ], shape, strides, offsets, f );\n    > v\n    <Float64Array>[ 5.0, 10.0, 15.0, 20.0 ]\n\n    See Also\n    --------\n    base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.ternary, base.strided.unary","base.strided.range":"\nbase.strided.range( N, x, stride )\n    Computes the range of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.range( x.length, x, 1 )\n    4.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.range( N, x, stride )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.range( N, x1, stride )\n    4.0\n\nbase.strided.range.ndarray( N, x, stride, offset )\n    Computes the range of a strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.range.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.range.ndarray( N, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.drange, base.strided.max, base.strided.min, base.strided.nanrange, base.strided.srange\n","base.strided.range.ndarray":"\nbase.strided.range.ndarray( N, x, stride, offset )\n    Computes the range of a strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.range.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.range.ndarray( N, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.drange, base.strided.max, base.strided.min, base.strided.nanrange, base.strided.srange","base.strided.rangeBy":"\nbase.strided.rangeBy( N, x, stride, clbk[, thisArg] )\n    Calculates the range of a strided array via a callback function.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - aidx: array index.\n    - sidx: strided index (offset + aidx*stride).\n    - array: the input array.\n\n    The callback function should return a numeric value.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.rangeBy( x.length, x, 1, accessor )\n    18.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.rangeBy( N, x, 2, accessor )\n    12.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.rangeBy( N, x1, 2, accessor )\n    8.0\n\nbase.strided.rangeBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the range of a strided array via a callback function and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.rangeBy.ndarray( x.length, x, 1, 0, accessor )\n    18.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.rangeBy.ndarray( N, x, 2, 1, accessor )\n    8.0\n\n    See Also\n    --------\n    base.strided.drange, base.strided.maxBy, base.strided.minBy, base.strided.nanrangeBy, base.strided.range, base.strided.srange\n","base.strided.rangeBy.ndarray":"\nbase.strided.rangeBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the range of a strided array via a callback function and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.rangeBy.ndarray( x.length, x, 1, 0, accessor )\n    18.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.rangeBy.ndarray( N, x, 2, 1, accessor )\n    8.0\n\n    See Also\n    --------\n    base.strided.drange, base.strided.maxBy, base.strided.minBy, base.strided.nanrangeBy, base.strided.range, base.strided.srange","base.strided.reinterpretComplex":"\nbase.strided.reinterpretComplex( x, offset )\n    Returns a real-valued floating-point array view of a complex-valued\n    floating-point array having the same precision.\n\n    Parameters\n    ----------\n    x: Complex128Array|Complex64Array\n        Input array.\n\n    offset: integer\n        Starting index of the view relative to the input array.\n\n    Returns\n    -------\n    out: Float64Array|Float32Array\n        Real-valued floating-point array view.\n\n    Examples\n    --------\n    > var x = new Complex128Array( 10 );\n    > var out = base.strided.reinterpretComplex( x, 0 )\n    <Float64Array>\n    > var bool = ( out.buffer === x.buffer )\n    true\n    > x = new Complex64Array( 10 );\n    > out = base.strided.reinterpretComplex( x, 0 )\n    <Float32Array>\n    > bool = ( out.buffer === x.buffer )\n    true\n\n    See Also\n    --------\n    base.strided.reinterpretComplex128, base.strided.reinterpretComplex64\n","base.strided.reinterpretComplex64":"\nbase.strided.reinterpretComplex64( x, offset )\n    Returns a Float32Array view of a Complex64Array.\n\n    Parameters\n    ----------\n    x: Complex64Array\n        Input array.\n\n    offset: integer\n        Starting index of the view relative to the Complex64Array.\n\n    Returns\n    -------\n    out: Float32Array\n        Float32Array view.\n\n    Examples\n    --------\n    > var x = new Complex64Array( 10 );\n    > var out = base.strided.reinterpretComplex64( x, 0 )\n    <Float32Array>\n    > var bool = ( out.buffer === x.buffer )\n    true\n\n    See Also\n    --------\n    base.strided.reinterpretComplex, base.strided.reinterpretComplex128\n","base.strided.reinterpretComplex128":"\nbase.strided.reinterpretComplex128( x, offset )\n    Returns a Float64Array view of a Complex128Array.\n\n    Parameters\n    ----------\n    x: Complex128Array\n        Input array.\n\n    offset: integer\n        Starting index of the view relative to the Complex128Array.\n\n    Returns\n    -------\n    out: Float64Array\n        Float64Array view.\n\n    Examples\n    --------\n    > var x = new Complex128Array( 10 );\n    > var out = base.strided.reinterpretComplex128( x, 0 )\n    <Float64Array>\n    > var bool = ( out.buffer === x.buffer )\n    true\n\n    See Also\n    --------\n    base.strided.reinterpretComplex, base.strided.reinterpretComplex64\n","base.strided.sabs":"\nbase.strided.sabs( N, x, strideX, y, strideY )\n    Computes the absolute value for each element in a single-precision floating-\n    point strided array `x` and assigns the results to elements in a single-\n    precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sabs( x.length, x, 1, y, 1 )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sabs( N, x, 2, y, -1 )\n    <Float32Array>[ 3.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.sabs( N, x1, -2, y1, 1 )\n    <Float32Array>[ 4.0, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.sabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the absolute value for each element in a single-precision floating-\n    point strided array `x` and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    strided.abs, base.strided.dabs, base.strided.sabs2\n","base.strided.sabs.ndarray":"\nbase.strided.sabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the absolute value for each element in a single-precision floating-\n    point strided array `x` and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    strided.abs, base.strided.dabs, base.strided.sabs2","base.strided.sabs2":"\nbase.strided.sabs2( N, x, strideX, y, strideY )\n    Computes the squared absolute value for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sabs2( x.length, x, 1, y, 1 )\n    <Float32Array>[ 1.0, 4.0, 9.0, 16.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sabs2( N, x, 2, y, -1 )\n    <Float32Array>[ 9.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.sabs2( N, x1, -2, y1, 1 )\n    <Float32Array>[ 16.0, 4.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 16.0, 4.0 ]\n\n\nbase.strided.sabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the squared absolute value for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 4.0, 9.0, 16.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 16.0, 4.0 ]\n\n    See Also\n    --------\n    strided.abs2, base.strided.dabs2, base.strided.sabs\n","base.strided.sabs2.ndarray":"\nbase.strided.sabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the squared absolute value for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 4.0, 9.0, 16.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 16.0, 4.0 ]\n\n    See Also\n    --------\n    strided.abs2, base.strided.dabs2, base.strided.sabs","base.strided.sapx":"\nbase.strided.sapx( N, alpha, x, stride )\n    Adds a constant to each element in a single-precision floating-point strided\n    array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns the strided array unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sapx( x.length, 5.0, x, 1 )\n    <Float32Array>[ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sapx( 3, 5.0, x, 2 )\n    <Float32Array>[ 3.0, 1.0, 8.0, -5.0, 9.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sapx( 3, 5.0, x1, 2 )\n    <Float32Array>[ 3.0, 3.0, 1.0, 5.0, -1.0 ]\n    > x0\n    <Float32Array>[ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n\nbase.strided.sapx.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each element in a single-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sapx.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float32Array>[ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.sapx.ndarray( 3, 5.0, x, 2, 1 )\n    <Float32Array>[ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dapx, base.strided.gapx\n","base.strided.sapx.ndarray":"\nbase.strided.sapx.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each element in a single-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sapx.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float32Array>[ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.sapx.ndarray( 3, 5.0, x, 2, 1 )\n    <Float32Array>[ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dapx, base.strided.gapx","base.strided.sapxsum":"\nbase.strided.sapxsum( N, alpha, x, stride )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum.\n\n    The `N` and stride parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsum( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.sapxsum( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sapxsum( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.sapxsum.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sapxsum.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.gapxsum, base.strided.sapxsumpw, base.strided.ssum\n","base.strided.sapxsum.ndarray":"\nbase.strided.sapxsum.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sapxsum.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.gapxsum, base.strided.sapxsumpw, base.strided.ssum","base.strided.sapxsumkbn":"\nbase.strided.sapxsumkbn( N, alpha, x, stride )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using an improved Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumkbn( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.sapxsumkbn( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sapxsumkbn( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.sapxsumkbn.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumkbn, base.strided.gapxsumkbn, base.strided.sapxsum, base.strided.ssumkbn\n","base.strided.sapxsumkbn.ndarray":"\nbase.strided.sapxsumkbn.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumkbn, base.strided.gapxsumkbn, base.strided.sapxsum, base.strided.ssumkbn","base.strided.sapxsumkbn2":"\nbase.strided.sapxsumkbn2( N, alpha, x, stride )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using a second-order iterative Kahan–Babuška\n    algorithm.\n\n    The `N` and `stride` parameters determine which elements in the \n    strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumkbn2( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.sapxsumkbn2( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sapxsumkbn2( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.sapxsumkbn2.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsum, base.strided.ssumkbn2\n","base.strided.sapxsumkbn2.ndarray":"\nbase.strided.sapxsumkbn2.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsum, base.strided.ssumkbn2","base.strided.sapxsumors":"\nbase.strided.sapxsumors( N, alpha, x, stride )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using ordinary recursive summation.\n\n    The `N` and `stride` parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumors( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sapxsumors( N, 5.0, x, stride )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sapxsumors( N, 5.0, x1, stride )\n    14.0\n\n\nbase.strided.sapxsumors.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using ordinary recursive summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sapxsumors.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumors, base.strided.gapxsumors, base.strided.sapxsum, base.strided.ssumors\n","base.strided.sapxsumors.ndarray":"\nbase.strided.sapxsumors.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using ordinary recursive summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sapxsumors.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumors, base.strided.gapxsumors, base.strided.sapxsum, base.strided.ssumors","base.strided.sapxsumpw":"\nbase.strided.sapxsumpw( N, alpha, x, stride )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using pairwise summation.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumpw( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var stride = 2;\n    > base.strided.sapxsumpw( 3, 5.0, x, stride )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > stride = 2;\n    > base.strided.sapxsumpw( 3, 5.0, x1, stride )\n    14.0\n\n\nbase.strided.sapxsumpw.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using pairwise summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumpw, base.strided.gapxsumpw, base.strided.sapxsum, base.strided.ssumpw\n","base.strided.sapxsumpw.ndarray":"\nbase.strided.sapxsumpw.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using pairwise summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumpw, base.strided.gapxsumpw, base.strided.sapxsum, base.strided.ssumpw","base.strided.sasum":"\nbase.strided.sasum( N, x, stride )\n    Computes the sum of the absolute values.\n\n    The sum of absolute values corresponds to the *L1* norm.\n\n    The `N` and stride parameters determine which elements in `x` are used to\n    compute the sum.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the function returns `0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    sum: float\n        Sum of absolute values.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n    > var s = base.strided.sasum( x.length, x, 1 )\n    15.0\n\n    // Sum every other value:\n    > s = base.strided.sasum( 3, x, 2 )\n    9.0\n\n    // Use view offset; e.g., starting at 2nd element:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > s = base.strided.sasum( 3, x1, 2 )\n    12.0\n\n\nbase.strided.sasum.ndarray( N, x, stride, offset )\n    Computes the sum of absolute values using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    sum: float\n        Sum of absolute values.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n    > var s = base.strided.sasum.ndarray( x.length, x, 1, 0 )\n    15.0\n\n    // Sum the last three elements:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > s = base.strided.sasum.ndarray( 3, x, -1, x.length-1 )\n    15.0\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.gasum\n","base.strided.sasum.ndarray":"\nbase.strided.sasum.ndarray( N, x, stride, offset )\n    Computes the sum of absolute values using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    sum: float\n        Sum of absolute values.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n    > var s = base.strided.sasum.ndarray( x.length, x, 1, 0 )\n    15.0\n\n    // Sum the last three elements:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > s = base.strided.sasum.ndarray( 3, x, -1, x.length-1 )\n    15.0\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.gasum","base.strided.sasumpw":"\nbase.strided.sasumpw( N, x, stride )\n    Computes the sum of absolute values (L1 norm) of single-precision floating-\n    point strided array elements using pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in the strided \n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sasumpw( x.length, x, 1 )\n    5.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.sasumpw( 3, x, 2 )\n    5.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sasumpw( 3, x1, 2 )\n    5.0\n\n\nbase.strided.sasumpw.ndarray( N, x, stride, offset )\n    Computes the sum of absolute values (L1 norm) of single-precision floating-\n    point strided array elements using pairwise summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sasumpw.ndarray( x.length, x, 1, 0 )\n    5.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sasumpw.ndarray( 3, x, 2, 1 )\n    5.0\n\n    See Also\n    --------\n    base.strided.sasum, base.strided.dasumpw, base.strided.gasumpw, base.strided.ssumpw\n","base.strided.sasumpw.ndarray":"\nbase.strided.sasumpw.ndarray( N, x, stride, offset )\n    Computes the sum of absolute values (L1 norm) of single-precision floating-\n    point strided array elements using pairwise summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sasumpw.ndarray( x.length, x, 1, 0 )\n    5.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sasumpw.ndarray( 3, x, 2, 1 )\n    5.0\n\n    See Also\n    --------\n    base.strided.sasum, base.strided.dasumpw, base.strided.gasumpw, base.strided.ssumpw","base.strided.saxpy":"\nbase.strided.saxpy( N, alpha, x, strideX, y, strideY )\n    Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > var alpha = 5.0;\n    > base.strided.saxpy( x.length, alpha, x, 1, y, 1 )\n    <Float32Array>[ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > base.strided.saxpy( 3, alpha, x, 2, y, -1 )\n    <Float32Array>[ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.saxpy( 3, 5.0, x1, -2, y1, 1 )\n    <Float32Array>[ 40.0, 31.0, 22.0 ]\n    > y0\n    <Float32Array>[ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.strided.saxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n    Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > var alpha = 5.0;\n    > base.strided.saxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.saxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n    See Also\n    --------\n    base.strided.daxpy, base.strided.gaxpy\n","base.strided.saxpy.ndarray":"\nbase.strided.saxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n    Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > var alpha = 5.0;\n    > base.strided.saxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.saxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n    See Also\n    --------\n    base.strided.daxpy, base.strided.gaxpy","base.strided.scbrt":"\nbase.strided.scbrt( N, x, strideX, y, strideY )\n    Computes the cube root of each element in a single-precision floating-point \n    strided array `x` and assigns the results to elements in a single-precision \n    floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.scbrt( x.length, x, 1, y, 1 )\n    <Float32Array>[ 0.0, 1.0, 2.0, 3.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.scbrt( N, x, 2, y, -1 )\n    <Float32Array>[ 2.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.scbrt( N, x1, -2, y1, 1 )\n    <Float32Array>[ 3.0, 1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.scbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cube root of each element in a single-precision floating-point \n    strided array `x` and assigns the results to elements in a single-precision \n    floating-point strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.scbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, 1.0, 2.0, 3.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.scbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dcbrt, strided.cbrt, base.strided.ssqrt\n","base.strided.scbrt.ndarray":"\nbase.strided.scbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cube root of each element in a single-precision floating-point \n    strided array `x` and assigns the results to elements in a single-precision \n    floating-point strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.scbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, 1.0, 2.0, 3.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.scbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dcbrt, strided.cbrt, base.strided.ssqrt","base.strided.sceil":"\nbase.strided.sceil( N, x, strideX, y, strideY )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward positive infinity and assigns the results to elements in a single-\n    precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sceil( x.length, x, 1, y, 1 )\n    <Float32Array>[ 2.0, 3.0, -3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sceil( N, x, 2, y, -1 )\n    <Float32Array>[ -3.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.sceil( N, x1, -2, y1, 1 )\n    <Float32Array>[ 4.0, 3.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.sceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward positive infinity and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 2.0, 3.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n    See Also\n    --------\n    strided.ceil, base.strided.dceil, base.strided.sfloor, base.strided.strunc\n","base.strided.sceil.ndarray":"\nbase.strided.sceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward positive infinity and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 2.0, 3.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n    See Also\n    --------\n    strided.ceil, base.strided.dceil, base.strided.sfloor, base.strided.strunc","base.strided.scopy":"\nbase.strided.scopy( N, x, strideX, y, strideY )\n    Copies values from `x` into `y`.\n\n    The `N` and stride parameters determine how values from `x` are copied\n    into `y`.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.scopy( x.length, x, 1, y, 1 )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.scopy( 3, x, -2, y, 1 )\n    <Float32Array>[ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n    // Using typed array views:\n    > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.scopy( 3, x1, -2, y1, 1 )\n    <Float32Array>[ 6.0, 4.0, 2.0 ]\n    > y0\n    <Float32Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.scopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Copies values from `x` into `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.scopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dcopy, base.strided.gcopy, base.strided.sswap\n","base.strided.scopy.ndarray":"\nbase.strided.scopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Copies values from `x` into `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.scopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dcopy, base.strided.gcopy, base.strided.sswap","base.strided.scumax":"\nbase.strided.scumax( N, x, strideX, y, strideY )\n    Computes the cumulative maximum of single-precision floating-point strided\n    array elements.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scumax( x.length, x, 1, y, 1 )\n    <Float32Array>[ 1.0, 1.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scumax( 3, x, 2, y, 2 )\n    <Float32Array>[ -2.0, 0.0, 1.0, 0.0, 2.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float32Array( x0.length );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.scumax( 3, x1, 2, y1, 1 )\n    <Float32Array>[ -2.0, 2.0, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.0, -2.0, 2.0, 2.0 ]\n\n\nbase.strided.scumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum of single-precision floating-point strided\n    array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 1.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumax, base.strided.dcumax, base.strided.scumin\n","base.strided.scumax.ndarray":"\nbase.strided.scumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum of single-precision floating-point strided\n    array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 1.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumax, base.strided.dcumax, base.strided.scumin","base.strided.scumaxabs":"\nbase.strided.scumaxabs( N, x, strideX, y, strideY )\n    Computes the cumulative maximum absolute value of single-precision floating-\n    point strided array elements.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scumaxabs( x.length, x, 1, y, 1 )\n    <Float32Array>[ 1.0, 2.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.scumaxabs( N, x, 2, y, 2 )\n    <Float32Array>[ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float32Array( x0.length );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.scumaxabs( N, x1, 2, y1, 1 )\n    <Float32Array>[ 2.0, 2.0, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\nbase.strided.scumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum absolute value of single-precision floating-\n    point strided array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.scumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cumaxabs, base.strided.dcumaxabs, base.strided.scumax, base.strided.scuminabs\n","base.strided.scumaxabs.ndarray":"\nbase.strided.scumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum absolute value of single-precision floating-\n    point strided array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.scumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cumaxabs, base.strided.dcumaxabs, base.strided.scumax, base.strided.scuminabs","base.strided.scumin":"\nbase.strided.scumin( N, x, strideX, y, strideY )\n    Computes the cumulative minimum of single-precision floating-point strided\n    array elements.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scumin( x.length, x, 1, y, 1 )\n    <Float32Array>[ 1.0, -2.0, -2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.scumin( N, x, 2, y, 2 )\n    <Float32Array>[ -2.0, 0.0, -2.0, 0.0, -2.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float32Array( x0.length );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.scumin( N, x1, 2, y1, 1 )\n    <Float32Array>[ -2.0, -2.0, -2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\nbase.strided.scumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum of single-precision floating-point strided\n    array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -2.0, -2.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.scumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumin, base.strided.dcumin, base.strided.scumax\n","base.strided.scumin.ndarray":"\nbase.strided.scumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum of single-precision floating-point strided\n    array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -2.0, -2.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.scumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumin, base.strided.dcumin, base.strided.scumax","base.strided.scuminabs":"\nbase.strided.scuminabs( N, x, strideX, y, strideY )\n    Computes the cumulative minimum absolute value of single-precision floating-\n    point strided array elements.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scuminabs( x.length, x, 1, y, 1 )\n    <Float32Array>[ 1.0, 1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.scuminabs( N, x, 2, y, 2 )\n    <Float32Array>[ 2.0, 0.0, 1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float32Array( x0.length );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.scuminabs( N, x1, 2, y1, 1 )\n    <Float32Array>[ 2.0, 2.0, 1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 1.0 ]\n\nbase.strided.scuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum absolute value of single-precision floating-\n    point strided array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.scuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cuminabs, base.strided.dcuminabs, base.strided.scumaxabs, base.strided.scumin\n","base.strided.scuminabs.ndarray":"\nbase.strided.scuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum absolute value of single-precision floating-\n    point strided array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.scuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cuminabs, base.strided.dcuminabs, base.strided.scumaxabs, base.strided.scumin","base.strided.scusum":"\nbase.strided.scusum( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements.\n\n    The `N` and `stride` parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusum( x.length, 0.0, x, 1, y, 1 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusum( 3, 0.0, x, 2, y, 2 )\n    <Float32Array>[ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float32Array( x0.length );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.scusum( 3, 0.0, x1, 2, y1, 1 )\n    <Float32Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusum, base.strided.scusumpw\n","base.strided.scusum.ndarray":"\nbase.strided.scusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusum, base.strided.scusumpw","base.strided.scusumkbn":"\nbase.strided.scusumkbn( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using an improved Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumkbn( x.length, 0.0, x, 1, y, 1 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumkbn( 3, 0.0, x, 2, y, 2 )\n    <Float32Array>[ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float32Array( x0.length );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.scusumkbn( N, 0.0, x1, 2, y1, 1 )\n    <Float32Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumkbn, base.strided.gcusumkbn, base.strided.scusum, base.strided.scusumkbn2\n","base.strided.scusumkbn.ndarray":"\nbase.strided.scusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumkbn, base.strided.gcusumkbn, base.strided.scusum, base.strided.scusumkbn2","base.strided.scusumkbn2":"\nbase.strided.scusumkbn2( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of single-precision floating-point strided \n    array elements using a second-order iterative Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use \n    a typed array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumkbn2( x.length, 0.0, x, 1, y, 1 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumkbn2( 3, 0.0, x, 2, y, 2 )\n    <Float32Array>[ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float32Array( x0.length );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.scusumkbn2( N, 0.0, x1, 2, y1, 1 )\n    <Float32Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of single-precision floating-point strided\n    array elements using a second-order iterative Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameter supports indexing semantics\n    based on starting indices.\n\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n\n    See Also\n    --------\n    base.strided.dcusumkbn2, base.strided.gcusumkbn2, base.strided.scusum, base.strided.scusumkbn\n","base.strided.scusumkbn2.ndarray":"\nbase.strided.scusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of single-precision floating-point strided\n    array elements using a second-order iterative Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameter supports indexing semantics\n    based on starting indices.\n\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n\n    See Also\n    --------\n    base.strided.dcusumkbn2, base.strided.gcusumkbn2, base.strided.scusum, base.strided.scusumkbn","base.strided.scusumors":"\nbase.strided.scusumors( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using ordinary recursive summation.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n     are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumors( x.length, 0.0, x, 1, y, 1 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumors( 3, 0.0, x, 2, y, 2 )\n    <Float32Array>[ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float32Array( x0.length );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.scusumors( 3, 0.0, x1, 2, y1, 1 )\n    <Float32Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using ordinary recursive summation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumors, base.strided.gcusumors, base.strided.scusum\n","base.strided.scusumors.ndarray":"\nbase.strided.scusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using ordinary recursive summation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumors, base.strided.gcusumors, base.strided.scusum","base.strided.scusumpw":"\nbase.strided.scusumpw( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using pairwise summation.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumpw( x.length, 0.0, x, 1, y, 1 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumpw( 3, 0.0, x, 2, y, 2 )\n    <Float32Array>[ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float32Array( x0.length );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.scusumpw( 3, 0.0, x1, 2, y1, 1 )\n    <Float32Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumpw, base.strided.gcusumpw, base.strided.scusum\n","base.strided.scusumpw.ndarray":"\nbase.strided.scusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumpw, base.strided.gcusumpw, base.strided.scusum","base.strided.sdeg2rad":"\nbase.strided.sdeg2rad( N, x, strideX, y, strideY )\n    Converts each element in a single-precision floating-point strided array `x`\n    from degrees to radians and assigns the results to elements in a single-\n    precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sdeg2rad( x.length, x, 1, y, 1 )\n    <Float32Array>[ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sdeg2rad( N, x, 2, y, -1 )\n    <Float32Array>[ ~0.785, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.sdeg2rad( N, x1, -2, y1, 1 )\n    <Float32Array>[ ~1.047, ~0.524 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.sdeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Converts each element in a single-precision floating-point strided array `x`\n    from degrees to radians and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sdeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sdeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n    See Also\n    --------\n    base.strided.ddeg2rad, strided.deg2rad\n","base.strided.sdeg2rad.ndarray":"\nbase.strided.sdeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Converts each element in a single-precision floating-point strided array `x`\n    from degrees to radians and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sdeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sdeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n    See Also\n    --------\n    base.strided.ddeg2rad, strided.deg2rad","base.strided.sdot":"\nbase.strided.sdot( N, x, strideX, y, strideY )\n    Computes the dot product of two single-precision floating-point vectors.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: float\n        The dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var out = base.strided.sdot( x.length, x, 1, y, 1 )\n    -5.0\n\n    // Strides:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > out = base.strided.sdot( 3, x, 2, y, -1 )\n    9.0\n\n    // Using view offsets:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n    > out = base.strided.sdot( 3, x1, -2, y1, 1 )\n    128.0\n\n\nbase.strided.sdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the dot product of two single-precision floating-point vectors\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing based on a starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: float\n        The dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var out = base.strided.sdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    -5.0\n\n    // Strides:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > out = base.strided.sdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n    9.0\n\n    // Using offset indices:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > out = base.strided.sdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n    128.0\n\n    See Also\n    --------\n    base.strided.ddot, base.strided.dsdot, base.strided.sdsdot, sdot\n","base.strided.sdot.ndarray":"\nbase.strided.sdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the dot product of two single-precision floating-point vectors\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing based on a starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: float\n        The dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var out = base.strided.sdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    -5.0\n\n    // Strides:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > out = base.strided.sdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n    9.0\n\n    // Using offset indices:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > out = base.strided.sdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n    128.0\n\n    See Also\n    --------\n    base.strided.ddot, base.strided.dsdot, base.strided.sdsdot, sdot","base.strided.sdsapxsum":"\nbase.strided.sdsapxsum( N, alpha, x, stride )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using extended accumulation.\n\n    The `N` and `stride` parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsapxsum( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.sdsapxsum( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sdsapxsum( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.sdsapxsum.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using extended accumulation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sdsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dsapxsum, base.strided.sapxsum, base.strided.sdssum\n","base.strided.sdsapxsum.ndarray":"\nbase.strided.sdsapxsum.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using extended accumulation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sdsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dsapxsum, base.strided.sapxsum, base.strided.sdssum","base.strided.sdsapxsumpw":"\nbase.strided.sdsapxsumpw( N, alpha, x, stride )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using pairwise summation with extended\n    accumulation.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsapxsumpw( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.sdsapxsumpw( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sdsapxsumpw( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.sdsapxsumpw.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using pairwise summation with extended\n    accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sdsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dsapxsumpw, base.strided.sapxsumpw, base.strided.sdsapxsum, base.strided.sdssumpw","base.strided.sdsapxsumpw.ndarray":"\nbase.strided.sdsapxsumpw.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using pairwise summation with extended\n    accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sdsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dsapxsumpw, base.strided.sapxsumpw, base.strided.sdsapxsum, base.strided.sdssumpw","base.strided.sdsdot":"\nbase.strided.sdsdot( N, scalar, x, strideX, y, strideY )\n    Computes the dot product of two single-precision floating-point vectors with\n    extended accumulation.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0` the function returns the provided scalar constant.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    scalar: number\n        Scalar constant added to dot product.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: number\n        The dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var out = base.strided.sdsdot( x.length, 0.0, x, 1, y, 1 )\n    -5.0\n\n    // Strides:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > out = base.strided.sdsdot( 3, 0.0, x, 2, y, -1 )\n    9.0\n\n    // Using view offsets:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n    > out = base.strided.sdsdot( 3, 0.0, x1, -2, y1, 1 )\n    128.0\n\n\nbase.strided.sdsdot.ndarray( N, scalar, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the dot product of two single-precision floating-point vectors\n    using alternative indexing semantics and with extended accumulation.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing based on a starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    scalar: number\n        Scalar constant added to dot product.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: number\n        The dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var out = base.strided.sdsdot.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    -5.0\n\n    // Strides:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > out = base.strided.sdsdot.ndarray( 3, 0.0, x, 2, 0, y, 2, 0 )\n    9.0\n\n    // Using offset indices:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > out = base.strided.sdsdot.ndarray( 3, 0.0, x, -2, x.length-1, y, 1, 3 )\n    128.0\n\n    References\n    ----------\n    - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n    Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n    Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n    NY, USA: Association for Computing Machinery: 324–25.\n    doi:10.1145/355841.355848.\n\n    See Also\n    --------\n    base.strided.ddot, base.strided.dsdot, base.strided.sdot\n","base.strided.sdsdot.ndarray":"\nbase.strided.sdsdot.ndarray( N, scalar, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the dot product of two single-precision floating-point vectors\n    using alternative indexing semantics and with extended accumulation.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing based on a starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    scalar: number\n        Scalar constant added to dot product.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: number\n        The dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var out = base.strided.sdsdot.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    -5.0\n\n    // Strides:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > out = base.strided.sdsdot.ndarray( 3, 0.0, x, 2, 0, y, 2, 0 )\n    9.0\n\n    // Using offset indices:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > out = base.strided.sdsdot.ndarray( 3, 0.0, x, -2, x.length-1, y, 1, 3 )\n    128.0\n\n    References\n    ----------\n    - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n    Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n    Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n    NY, USA: Association for Computing Machinery: 324–25.\n    doi:10.1145/355841.355848.\n\n    See Also\n    --------\n    base.strided.ddot, base.strided.dsdot, base.strided.sdot","base.strided.sdsmean":"\nbase.strided.sdsmean( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using extended accumulation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsmean( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sdsmean( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sdsmean( N, x1, stride )\n    ~-0.3333\n\nbase.strided.sdsmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using extended accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sdsmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsnanmean, base.strided.smean\n","base.strided.sdsmean.ndarray":"\nbase.strided.sdsmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using extended accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sdsmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsnanmean, base.strided.smean","base.strided.sdsmeanors":"\nbase.strided.sdsmeanors( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation with extended accumulation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsmeanors( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sdsmeanors( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sdsmeanors( N, x1, stride )\n    ~-0.3333\n\nbase.strided.sdsmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation with extended accumulation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sdsmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.sdsmean, base.strided.sdsnanmeanors\n","base.strided.sdsmeanors.ndarray":"\nbase.strided.sdsmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation with extended accumulation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sdsmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.sdsmean, base.strided.sdsnanmeanors","base.strided.sdsnanmean":"\nbase.strided.sdsnanmean( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using extended accumulation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnanmean( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sdsnanmean( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sdsnanmean( N, x1, stride )\n    ~-0.3333\n\nbase.strided.sdsnanmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using extended accumulation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnanmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sdsnanmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.dsnanmean, base.strided.nanmean, base.strided.sdsmean, base.strided.snanmean\n","base.strided.sdsnanmean.ndarray":"\nbase.strided.sdsnanmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using extended accumulation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnanmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sdsnanmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.dsnanmean, base.strided.nanmean, base.strided.sdsmean, base.strided.snanmean","base.strided.sdsnanmeanors":"\nbase.strided.sdsnanmeanors( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation with\n    extended accumulation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnanmeanors( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sdsnanmeanors( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sdsnanmeanors( N, x1, stride )\n    ~-0.3333\n\nbase.strided.sdsnanmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation with\n    extended accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnanmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sdsnanmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.sdsmeanors, base.strided.sdsnanmean\n","base.strided.sdsnanmeanors.ndarray":"\nbase.strided.sdsnanmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation with\n    extended accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnanmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sdsnanmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.sdsmeanors, base.strided.sdsnanmean","base.strided.sdsnansum":"\nbase.strided.sdsnansum( N, x, stride )\n    Computes the sum of single-precision floating-point strided array\n    elements, ignore `NaN` values and using extended accumulation.\n\n    The `N` and `stride` parameters determine which elements in the\n    strided array are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnansum( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > var stride = 2;\n    > base.strided.sdsnansum( 4, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > stride = 2;\n    > base.strided.sdsnansum( 4, x1, stride )\n    -1.0\n\n\nbase.strided.sdsnansum.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using extended accumulation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnansum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.sdsnansum.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnansum, base.strided.dnansum, base.strided.gnansum, base.strided.sdssum, base.strided.snansum\n","base.strided.sdsnansum.ndarray":"\nbase.strided.sdsnansum.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using extended accumulation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnansum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.sdsnansum.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnansum, base.strided.dnansum, base.strided.gnansum, base.strided.sdssum, base.strided.snansum","base.strided.sdsnansumpw":"\nbase.strided.sdsnansumpw( N, x, stride )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation with extended\n    accumulation.\n\n    The `N` and `stride` parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnansumpw( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.sdsnansumpw( 4, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sdsnansumpw( 4, x1, 2 )\n    -1.0\n\n\nbase.strided.sdsnansumpw.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation with extended\n    accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnansumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.sdsnansumpw.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnansumpw, base.strided.dnansumpw, base.strided.gnansumpw, base.strided.sdsnansum, base.strided.sdssumpw, base.strided.snansumpw\n","base.strided.sdsnansumpw.ndarray":"\nbase.strided.sdsnansumpw.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation with extended\n    accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnansumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.sdsnansumpw.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnansumpw, base.strided.dnansumpw, base.strided.gnansumpw, base.strided.sdsnansum, base.strided.sdssumpw, base.strided.snansumpw","base.strided.sdssum":"\nbase.strided.sdssum( N, x, stride )\n    Computes the sum of single-precision floating-point strided array elements\n    using extended accumulation.\n\n    The `N` and stride parameters determine which elements in \n    the strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdssum( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var stride = 2;\n    > base.strided.sdssum( 3, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > stride = 2;\n    > base.strided.sdssum( 3, x1, stride )\n    -1.0\n\n\nbase.strided.sdssum.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements\n    using extended accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdssum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sdssum.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dssum, base.strided.dsum, base.strided.sdsnansum, base.strided.ssum, base.strided.gsum\n","base.strided.sdssum.ndarray":"\nbase.strided.sdssum.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements\n    using extended accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdssum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sdssum.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dssum, base.strided.dsum, base.strided.sdsnansum, base.strided.ssum, base.strided.gsum","base.strided.sdssumpw":"\nbase.strided.sdssumpw( N, x, stride )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation with extended accumulation.\n\n    The `N` and stride parameters determine which elements in the strided\n    array are accessed are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset,\n    use a typed array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdssumpw( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var stride = 2;\n    > base.strided.sdssumpw( 3, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > stride = 2;\n    > base.strided.sdssumpw( 3, x1, stride )\n    -1.0\n\n\nbase.strided.sdssumpw.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation with extended accumulation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdssumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sdssumpw.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dssumpw, base.strided.dsumpw, base.strided.sdsnansumpw, base.strided.sdssum, base.strided.ssumpw, base.strided.gsumpw\n","base.strided.sdssumpw.ndarray":"\nbase.strided.sdssumpw.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation with extended accumulation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdssumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sdssumpw.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dssumpw, base.strided.dsumpw, base.strided.sdsnansumpw, base.strided.sdssum, base.strided.ssumpw, base.strided.gsumpw","base.strided.sfill":"\nbase.strided.sfill( N, alpha, x, strideX )\n    Fills a single-precision floating-point strided array with a specified\n    scalar value.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sfill( x.length, 5.0, x, 1 )\n    <Float32Array>[ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sfill( 3, 5.0, x, 2 )\n    <Float32Array>[ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sfill( 3, 5.0, x1, 2 )\n    <Float32Array>[ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n    > x0\n    <Float32Array>[ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.sfill.ndarray( N, alpha, x, strideX, offsetX )\n    Fills a single-precision floating-point strided array with a specified\n    scalar value using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sfill.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float32Array>[ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.sfill.ndarray( 3, 5.0, x, 2, 1 )\n    <Float32Array>[ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n    See Also\n    --------\n    base.strided.dfill, base.strided.gfill\n","base.strided.sfill.ndarray":"\nbase.strided.sfill.ndarray( N, alpha, x, strideX, offsetX )\n    Fills a single-precision floating-point strided array with a specified\n    scalar value using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sfill.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float32Array>[ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.sfill.ndarray( 3, 5.0, x, 2, 1 )\n    <Float32Array>[ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n    See Also\n    --------\n    base.strided.dfill, base.strided.gfill","base.strided.sfloor":"\nbase.strided.sfloor( N, x, strideX, y, strideY )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward negative infinity and assigns the results to elements in a single-\n    precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sfloor( x.length, x, 1, y, 1 )\n    <Float32Array>[ -2.0, 1.0, 3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sfloor( N, x, 2, y, -1 )\n    <Float32Array>[ 3.0, -2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.sfloor( N, x1, -2, y1, 1 )\n    <Float32Array>[ 4.0, 1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 4.0, 1.0 ]\n\n\nbase.strided.sfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward negative infinity and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ -2.0, 1.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dfloor, strided.floor, base.strided.sceil, base.strided.strunc\n","base.strided.sfloor.ndarray":"\nbase.strided.sfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward negative infinity and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ -2.0, 1.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dfloor, strided.floor, base.strided.sceil, base.strided.strunc","base.strided.sinv":"\nbase.strided.sinv( N, x, strideX, y, strideY )\n    Computes the multiplicative inverse for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sinv( x.length, x, 1, y, 1 )\n    <Float32Array>[ ~-0.05, -1.0, 0.5, 0.25 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sinv( N, x, 2, y, -1 )\n    <Float32Array>[ 0.5, ~-0.05, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.sinv( N, x1, -2, y1, 1 )\n    <Float32Array>[ 0.25, -1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.sinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the multiplicative inverse for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ ~-0.05, -1.0, 0.5, 0.25 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dinv, strided.inv\n","base.strided.sinv.ndarray":"\nbase.strided.sinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the multiplicative inverse for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ ~-0.05, -1.0, 0.5, 0.25 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dinv, strided.inv","base.strided.smap":"\nbase.strided.smap( N, x, strideX, y, strideY, fcn )\n    Applies a unary function to a single-precision floating-point strided input\n    array and assigns results to a single-precision floating-point strided\n    output array.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap( x.length, x, 1, y, 1, base.identityf )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap( 2, x, 2, y, -1, base.identityf )\n    <Float32Array>[ 3.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smap( 2, x1, -2, y1, 1, base.identityf )\n    <Float32Array>[ 4.0, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n    Applies a unary function to a single-precision floating-point strided input\n    array and assigns results to a single-precision floating-point strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identityf )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identityf )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmap, base.strided.unary\n","base.strided.smap.ndarray":"\nbase.strided.smap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n    Applies a unary function to a single-precision floating-point strided input\n    array and assigns results to a single-precision floating-point strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identityf )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identityf )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmap, base.strided.unary","base.strided.smap2":"\nbase.strided.smap2( N, x, sx, y, sy, z, sz, fcn )\n    Applies a binary function to single-precision floating-point strided input\n    arrays and assigns results to a single-precision floating-point strided\n    output array.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    z: Float32Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float32Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap2( x.length, x, 1, y, 1, z, 1, base.addf )\n    <Float32Array>[ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Using `N` and stride parameters:\n    > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap2( 2, x, 2, y, -1, z, 1, base.addf )\n    <Float32Array>[ 3.0, 4.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smap2( 2, x1, -2, y1, 1, z1, 1, base.addf )\n    <Float32Array>[ 7.0, 6.0 ]\n    > z0\n    <Float32Array>[ 0.0, 0.0, 7.0, 6.0 ]\n\n\nbase.strided.smap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n    Applies a binary function to single-precision floating-point strided input\n    arrays and assigns results to a single-precision floating-point strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Float32Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float32Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.addf )\n    <Float32Array>[ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.addf )\n    <Float32Array>[ 0.0, 6.0, 7.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmap2, base.strided.binary\n","base.strided.smap2.ndarray":"\nbase.strided.smap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n    Applies a binary function to single-precision floating-point strided input\n    arrays and assigns results to a single-precision floating-point strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Float32Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float32Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.addf )\n    <Float32Array>[ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.addf )\n    <Float32Array>[ 0.0, 6.0, 7.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmap2, base.strided.binary","base.strided.smax":"\nbase.strided.smax( N, x, strideX )\n    Computes the maximum value of a single-precision floating-point strided\n    array.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smax( x.length, x, 1 )\n    2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.smax( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.smax( 3, x1, 2 )\n    2.0\n\n\nbase.strided.smax.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a single-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smax.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smax.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.max, base.strided.smin, base.strided.snanmax\n","base.strided.smax.ndarray":"\nbase.strided.smax.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a single-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smax.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smax.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.max, base.strided.smin, base.strided.snanmax","base.strided.smaxabs":"\nbase.strided.smaxabs( N, x, strideX )\n    Computes the maximum absolute value of a single-precision floating-point\n    strided array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smaxabs( x.length, x, 1 )\n    2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.smaxabs( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.smaxabs( 3, x1, 2 )\n    2.0\n\n\nbase.strided.smaxabs.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smaxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.smaxabs.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmaxabs, base.strided.maxabs, base.strided.smax, base.strided.sminabs, base.strided.snanmaxabs\n","base.strided.smaxabs.ndarray":"\nbase.strided.smaxabs.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smaxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.smaxabs.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmaxabs, base.strided.maxabs, base.strided.smax, base.strided.sminabs, base.strided.snanmaxabs","base.strided.smaxabssorted":"\nbase.strided.smaxabssorted( N, x, strideX )\n    Computes the maximum absolute value of a sorted single-precision floating-\n    point strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n    > base.strided.smaxabssorted( x.length, x, 1 )\n    3.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.smaxabssorted( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.smaxabssorted( 3, x1, 2 )\n    3.0\n\n\nbase.strided.smaxabssorted.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a sorted single-precision floating-\n    point strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n    > base.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.smaxabssorted.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmaxabssorted, base.strided.smaxabs, base.strided.smaxsorted\n","base.strided.smaxabssorted.ndarray":"\nbase.strided.smaxabssorted.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a sorted single-precision floating-\n    point strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n    > base.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.smaxabssorted.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmaxabssorted, base.strided.smaxabs, base.strided.smaxsorted","base.strided.smaxsorted":"\nbase.strided.smaxsorted( N, x, strideX )\n    Computes the maximum value of a sorted single-precision floating-point\n    strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.smaxsorted( x.length, x, 1 )\n    3.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.smaxsorted( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.smaxsorted( 3, x1, 2 )\n    3.0\n\n\nbase.strided.smaxsorted.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.smaxsorted.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmaxsorted, base.strided.maxsorted, base.strided.smax, base.strided.sminsorted\n","base.strided.smaxsorted.ndarray":"\nbase.strided.smaxsorted.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.smaxsorted.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmaxsorted, base.strided.maxsorted, base.strided.smax, base.strided.sminsorted","base.strided.smean":"\nbase.strided.smean( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smean( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.smean( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.smean( N, x1, stride )\n    ~-0.3333\n\nbase.strided.smean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsmean, base.strided.snanmean\n","base.strided.smean.ndarray":"\nbase.strided.smean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsmean, base.strided.snanmean","base.strided.smeankbn":"\nbase.strided.smeankbn( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeankbn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.smeankbn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.smeankbn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.smeankbn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeankbn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeankbn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeankbn, base.strided.meankbn, base.strided.smean\n","base.strided.smeankbn.ndarray":"\nbase.strided.smeankbn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeankbn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeankbn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeankbn, base.strided.meankbn, base.strided.smean","base.strided.smeankbn2":"\nbase.strided.smeankbn2( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a second-order iterative Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeankbn2( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.smeankbn2( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.smeankbn2( N, x1, stride )\n    ~-0.3333\n\nbase.strided.smeankbn2.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeankbn2.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeankbn2.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeankbn2, base.strided.meankbn2, base.strided.smean\n","base.strided.smeankbn2.ndarray":"\nbase.strided.smeankbn2.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeankbn2.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeankbn2.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeankbn2, base.strided.meankbn2, base.strided.smean","base.strided.smeanli":"\nbase.strided.smeanli( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanli( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.smeanli( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.smeanli( N, x1, stride )\n    ~-0.3333\n\nbase.strided.smeanli.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanli.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanli.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanli, base.strided.smean, base.strided.smeanlipw\n","base.strided.smeanli.ndarray":"\nbase.strided.smeanli.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanli.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanli.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanli, base.strided.smean, base.strided.smeanlipw","base.strided.smeanlipw":"\nbase.strided.smeanlipw( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm with pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanlipw( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.smeanlipw( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.smeanlipw( N, x1, stride )\n    ~-0.3333\n\nbase.strided.smeanlipw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm with pairwise summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanlipw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanlipw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanlipw, base.strided.smean, base.strided.smeanli\n","base.strided.smeanlipw.ndarray":"\nbase.strided.smeanlipw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm with pairwise summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanlipw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanlipw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanlipw, base.strided.smean, base.strided.smeanli","base.strided.smeanors":"\nbase.strided.smeanors( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanors( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.smeanors( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.smeanors( N, x1, stride )\n    ~-0.3333\n\nbase.strided.smeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanors, base.strided.meanors, base.strided.smean, base.strided.snanmeanors\n","base.strided.smeanors.ndarray":"\nbase.strided.smeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanors, base.strided.meanors, base.strided.smean, base.strided.snanmeanors","base.strided.smeanpn":"\nbase.strided.smeanpn( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a two-pass error correction algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanpn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.smeanpn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.smeanpn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.smeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a two-pass error correction algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.meanpn, base.strided.smean, base.strided.snanmeanpn\n","base.strided.smeanpn.ndarray":"\nbase.strided.smeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a two-pass error correction algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.meanpn, base.strided.smean, base.strided.snanmeanpn","base.strided.smeanpw":"\nbase.strided.smeanpw( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanpw( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.smeanpw( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.smeanpw( N, x1, stride )\n    ~-0.3333\n\nbase.strided.smeanpw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanpw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanpw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpw, base.strided.meanpw, base.strided.smean\n","base.strided.smeanpw.ndarray":"\nbase.strided.smeanpw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanpw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanpw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpw, base.strided.meanpw, base.strided.smean","base.strided.smeanwd":"\nbase.strided.smeanwd( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanwd( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.smeanwd( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.smeanwd( N, x1, stride )\n    ~-0.3333\n\nbase.strided.smeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanwd, base.strided.meanwd, base.strided.smean, base.strided.snanmeanwd\n","base.strided.smeanwd.ndarray":"\nbase.strided.smeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanwd, base.strided.meanwd, base.strided.smean, base.strided.snanmeanwd","base.strided.smediansorted":"\nbase.strided.smediansorted( N, x, stride )\n    Computes the median value of a sorted single-precision floating-point\n    strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.smediansorted( x.length, x, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smediansorted( N, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.smediansorted( N, x1, 2 )\n    2.0\n\nbase.strided.smediansorted.ndarray( N, x, stride, offset )\n    Computes the median value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.smediansorted.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smediansorted.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmediansorted, base.strided.mediansorted, base.strided.smean\n","base.strided.smediansorted.ndarray":"\nbase.strided.smediansorted.ndarray( N, x, stride, offset )\n    Computes the median value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.smediansorted.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smediansorted.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmediansorted, base.strided.mediansorted, base.strided.smean","base.strided.smidrange":"\nbase.strided.smidrange( N, x, strideX )\n    Computes the mid-range of a single-precision floating-point strided array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Mid-range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smidrange( x.length, x, 1 )\n    0.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.smidrange( 3, x, 2 )\n    0.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.smidrange( 3, x1, 2 )\n    0.0\n\n\nbase.strided.smidrange.ndarray( N, x, strideX, offsetX )\n    Computes the mid-range of a single-precision floating-point strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Mid-range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smidrange.ndarray( x.length, x, 1, 0 )\n    0.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.smidrange.ndarray( 3, x, 2, 1 )\n    0.0\n\n    See Also\n    --------\n    base.strided.dmidrange, base.strided.smax, base.strided.smean, base.strided.smin, base.strided.srange\n","base.strided.smidrange.ndarray":"\nbase.strided.smidrange.ndarray( N, x, strideX, offsetX )\n    Computes the mid-range of a single-precision floating-point strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Mid-range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smidrange.ndarray( x.length, x, 1, 0 )\n    0.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.smidrange.ndarray( 3, x, 2, 1 )\n    0.0\n\n    See Also\n    --------\n    base.strided.dmidrange, base.strided.smax, base.strided.smean, base.strided.smin, base.strided.srange","base.strided.smin":"\nbase.strided.smin( N, x, strideX )\n    Computes the minimum value of a single-precision floating-point strided\n    array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smin( x.length, x, 1 )\n    -2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.smin( 3, x, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.smin( 3, x1, 2 )\n    -2.0\n\n\nbase.strided.smin.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a single-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.smin.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.min, base.strided.smax, base.strided.snanmin\n","base.strided.smin.ndarray":"\nbase.strided.smin.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a single-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.smin.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.min, base.strided.smax, base.strided.snanmin","base.strided.sminabs":"\nbase.strided.sminabs( N, x, strideX )\n    Computes the minimum absolute value of a single-precision floating-point\n    strided array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sminabs( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.sminabs( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sminabs( 3, x1, 2 )\n    1.0\n\n\nbase.strided.sminabs.ndarray( N, x, strideX, offsetX )\n    Computes the minimum absolute value of a single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sminabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sminabs.ndarray( 3, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dminabs, base.strided.minabs, base.strided.smaxabs, base.strided.smin, base.strided.snanminabs\n","base.strided.sminabs.ndarray":"\nbase.strided.sminabs.ndarray( N, x, strideX, offsetX )\n    Computes the minimum absolute value of a single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sminabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sminabs.ndarray( 3, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dminabs, base.strided.minabs, base.strided.smaxabs, base.strided.smin, base.strided.snanminabs","base.strided.sminsorted":"\nbase.strided.sminsorted( N, x, stride )\n    Computes the minimum value of a sorted single-precision floating-point\n    strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.sminsorted( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sminsorted( N, x, stride )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sminsorted( N, x1, stride )\n    -2.0\n\nbase.strided.sminsorted.ndarray( N, x, stride, offset )\n    Computes the minimum value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.sminsorted.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sminsorted.ndarray( N, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dminsorted, base.strided.minsorted, base.strided.smaxsorted, base.strided.smin\n","base.strided.sminsorted.ndarray":"\nbase.strided.sminsorted.ndarray( N, x, stride, offset )\n    Computes the minimum value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.sminsorted.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sminsorted.ndarray( N, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dminsorted, base.strided.minsorted, base.strided.smaxsorted, base.strided.smin","base.strided.smskabs":"\nbase.strided.smskabs( N, x, sx, m, sm, y, sy )\n    Computes the absolute value for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ 2.0, 1.0, 0.0, 5.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskabs( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ 5.0, 1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 5.0, 1.0 ]\n\n\nbase.strided.smskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the absolute value for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 2.0, 1.0, 0.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 5.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dmskabs, base.strided.sabs, base.strided.smskabs2\n","base.strided.smskabs.ndarray":"\nbase.strided.smskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the absolute value for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 2.0, 1.0, 0.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 5.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dmskabs, base.strided.sabs, base.strided.smskabs2","base.strided.smskabs2":"\nbase.strided.smskabs2( N, x, sx, m, sm, y, sy )\n    Computes the squared absolute value for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point\n    strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs2( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ 4.0, 1.0, 0.0, 25.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs2( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, 4.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskabs2( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ 25.0, 1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 25.0, 1.0 ]\n\n\nbase.strided.smskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the squared absolute value for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point\n    strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 4.0, 1.0, 0.0, 25.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 25.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dmskabs2, base.strided.sabs2, base.strided.smskabs\n","base.strided.smskabs2.ndarray":"\nbase.strided.smskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the squared absolute value for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point\n    strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 4.0, 1.0, 0.0, 25.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 25.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dmskabs2, base.strided.sabs2, base.strided.smskabs","base.strided.smskcbrt":"\nbase.strided.smskcbrt( N, x, sx, m, sm, y, sy )\n    Computes the cube root for each element in a single-precision floating-point\n    strided array `x` according to a strided mask array and assigns the results\n    to elements in a single-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskcbrt( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ 0.0, 1.0, 0.0, 3.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskcbrt( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskcbrt( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ 3.0, 1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.smskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the cube root for each element in a single-precision floating-point\n    strided array `x` according to a strided mask array and assigns the results\n    to elements in a single-precision floating-point strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, 1.0, 0.0, 3.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dmskcbrt, base.strided.scbrt, base.strided.ssqrt\n","base.strided.smskcbrt.ndarray":"\nbase.strided.smskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the cube root for each element in a single-precision floating-point\n    strided array `x` according to a strided mask array and assigns the results\n    to elements in a single-precision floating-point strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, 1.0, 0.0, 3.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dmskcbrt, base.strided.scbrt, base.strided.ssqrt","base.strided.smskceil":"\nbase.strided.smskceil( N, x, sx, m, sm, y, sy )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward positive infinity according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskceil( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ 2.0, 3.0, 0.0, 4.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskceil( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskceil( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ 4.0, 3.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.smskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward positive infinity according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 2.0, 3.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n    See Also\n    --------\n    base.strided.dmskceil, base.strided.sceil, base.strided.smskfloor, base.strided.smsktrunc\n","base.strided.smskceil.ndarray":"\nbase.strided.smskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward positive infinity according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 2.0, 3.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n    See Also\n    --------\n    base.strided.dmskceil, base.strided.sceil, base.strided.smskfloor, base.strided.smsktrunc","base.strided.smskdeg2rad":"\nbase.strided.smskdeg2rad( N, x, sx, m, sm, y, sy )\n    Converts each element in a single-precision floating-point strided array `x`\n    from degrees to radians according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskdeg2rad( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ 0.0, ~0.524, 0.0, ~1.047 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskdeg2rad( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ ~1.047, ~0.524 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.smskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Converts each element in a single-precision floating-point strided array `x`\n    from degrees to radians according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, ~0.524, 0.0, ~1.047 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n    See Also\n    --------\n    base.strided.dmskdeg2rad, base.strided.sdeg2rad\n","base.strided.smskdeg2rad.ndarray":"\nbase.strided.smskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Converts each element in a single-precision floating-point strided array `x`\n    from degrees to radians according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, ~0.524, 0.0, ~1.047 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n    See Also\n    --------\n    base.strided.dmskdeg2rad, base.strided.sdeg2rad","base.strided.smskfloor":"\nbase.strided.smskfloor( N, x, sx, m, sm, y, sy )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward negative infinity according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskfloor( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskfloor( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskfloor( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ 4.0, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward negative infinity according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmskfloor, base.strided.sfloor, base.strided.smskceil, base.strided.smsktrunc\n","base.strided.smskfloor.ndarray":"\nbase.strided.smskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward negative infinity according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmskfloor, base.strided.sfloor, base.strided.smskceil, base.strided.smsktrunc","base.strided.smskinv":"\nbase.strided.smskinv( N, x, sx, m, sm, y, sy )\n    Computes the multiplicative inverse for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskinv( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ ~-0.05, -1.0, 0.0, 0.25 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskinv( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, ~-0.05, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskinv( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ 0.25, -1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.smskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the multiplicative inverse for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ ~-0.05, -1.0, 0.0, 0.25 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dinv, base.strided.dmskinv\n","base.strided.smskinv.ndarray":"\nbase.strided.smskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the multiplicative inverse for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ ~-0.05, -1.0, 0.0, 0.25 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dinv, base.strided.dmskinv","base.strided.smskmap":"\nbase.strided.smskmap( N, x, sx, m, sm, y, sy, fcn )\n    Applies a unary function to a single-precision floating-point strided input\n    array according to a strided mask array and assigns results to a single-\n    precision floating-point strided output array.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskmap( x.length, x, 1, m, 1, y, 1, base.identity )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskmap( 2, x, 2, m, 2, y, -1, base.identity )\n    <Float32Array>[ 0.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\n    <Float32Array>[ 0.0, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.0, 2.0 ]\n\n\nbase.strided.smskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n    Applies a unary function to a single-precision floating-point strided input\n    array according to a strided mask array and assigns results to a single-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n    <Float32Array>[ 0.0, 0.0, 4.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmskmap, base.strided.mskunary, base.strided.smap, base.strided.smskmap2\n","base.strided.smskmap.ndarray":"\nbase.strided.smskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n    Applies a unary function to a single-precision floating-point strided input\n    array according to a strided mask array and assigns results to a single-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n    <Float32Array>[ 0.0, 0.0, 4.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmskmap, base.strided.mskunary, base.strided.smap, base.strided.smskmap2","base.strided.smskmap2":"\nbase.strided.smskmap2( N, x, sx, y, sy, m, sm, z, sz, fcn )\n    Applies a binary function to single-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a single-\n    precision floating-point strided output array.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    z: Float32Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float32Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.smskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.addf )\n    <Float32Array>[ 2.0, 4.0, 0.0, 8.0 ]\n\n    // Using `N` and stride parameters:\n    > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.addf )\n    <Float32Array>[ 0.0, 3.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.addf )\n    <Float32Array>[ 0.0, 6.0 ]\n    > z0\n    <Float32Array>[ 0.0, 0.0, 0.0, 6.0 ]\n\n\nbase.strided.smskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n    Applies a binary function to single-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a single-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    z: Float32Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float32Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.smskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.addf )\n    <Float32Array>[ 2.0, 4.0, 0.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.smskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.addf )\n    <Float32Array>[ 0.0, 0.0, 7.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmskmap2, base.strided.smap2, base.strided.smskmap\n","base.strided.smskmap2.ndarray":"\nbase.strided.smskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n    Applies a binary function to single-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a single-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    z: Float32Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float32Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.smskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.addf )\n    <Float32Array>[ 2.0, 4.0, 0.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.smskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.addf )\n    <Float32Array>[ 0.0, 0.0, 7.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmskmap2, base.strided.smap2, base.strided.smskmap","base.strided.smskmax":"\nbase.strided.smskmax( N, x, strideX, mask, strideMask )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.smskmax( x.length, x, 1, mask, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.smskmax( 3, x, 2, mask, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > base.strided.smskmax( 3, x1, 2, mask1, 2 )\n    2.0\n\n\nbase.strided.smskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.smskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmskmax, base.strided.mskmax, base.strided.smax, base.strided.smskmin, base.strided.snanmax, base.strided.snanmskmax\n","base.strided.smskmax.ndarray":"\nbase.strided.smskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.smskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmskmax, base.strided.mskmax, base.strided.smax, base.strided.smskmin, base.strided.snanmax, base.strided.snanmskmax","base.strided.smskmin":"\nbase.strided.smskmin( N, x, strideX, mask, strideMask )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.smskmin( x.length, x, 1, mask, 1 )\n    -2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.smskmin( 3, x, 2, mask, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > base.strided.smskmin( 3, x1, 2, mask1, 2 )\n    -2.0\n\n\nbase.strided.smskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.smskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmskmin, base.strided.mskmin, base.strided.smin, base.strided.smskmax, base.strided.snanmin, base.strided.snanmskmin\n","base.strided.smskmin.ndarray":"\nbase.strided.smskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.smskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmskmin, base.strided.mskmin, base.strided.smin, base.strided.smskmax, base.strided.snanmin, base.strided.snanmskmin","base.strided.smskramp":"\nbase.strided.smskramp( N, x, sx, m, sm, y, sy )\n    Evaluates the ramp function for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskramp( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskramp( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskramp( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ 4.0, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Evaluates the ramp function for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmskramp, base.strided.sramp\n","base.strided.smskramp.ndarray":"\nbase.strided.smskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Evaluates the ramp function for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmskramp, base.strided.sramp","base.strided.smskrange":"\nbase.strided.smskrange( N, x, strideX, mask, strideMask )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.smskrange( x.length, x, 1, mask, 1 )\n    4.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.smskrange( 3, x, 2, mask, 2 )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > base.strided.smskrange( 3, x1, 2, mask1, 2 )\n    4.0\n\n\nbase.strided.smskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.smskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dmskrange, base.strided.mskrange, base.strided.smskmax, base.strided.smskmin, base.strided.snanrange, base.strided.srange\n","base.strided.smskrange.ndarray":"\nbase.strided.smskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.smskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dmskrange, base.strided.mskrange, base.strided.smskmax, base.strided.smskmin, base.strided.snanrange, base.strided.srange","base.strided.smskrsqrt":"\nbase.strided.smskrsqrt( N, x, sx, m, sm, y, sy )\n    Computes the reciprocal square root for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskrsqrt( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ Infinity, 0.5, 0.0, ~0.289 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskrsqrt( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, Infinity, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ ~0.289, 0.5 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.smskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the reciprocal square root for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ Infinity, 0.5, 0.0, ~0.289 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n    See Also\n    --------\n    base.strided.dmskrsqrt, base.strided.smsksqrt, base.strided.srsqrt\n","base.strided.smskrsqrt.ndarray":"\nbase.strided.smskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the reciprocal square root for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ Infinity, 0.5, 0.0, ~0.289 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n    See Also\n    --------\n    base.strided.dmskrsqrt, base.strided.smsksqrt, base.strided.srsqrt","base.strided.smsksqrt":"\nbase.strided.smsksqrt( N, x, sx, m, sm, y, sy )\n    Computes the principal square root for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsksqrt( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ 0.0, 2.0, 0.0, ~3.464 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsksqrt( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smsksqrt( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ ~3.464, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.smsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the principal square root for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, 2.0, 0.0, ~3.464 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmsksqrt, base.strided.smskcbrt, base.strided.smskrsqrt, base.strided.srsqrt\n","base.strided.smsksqrt.ndarray":"\nbase.strided.smsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the principal square root for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, 2.0, 0.0, ~3.464 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmsksqrt, base.strided.smskcbrt, base.strided.smskrsqrt, base.strided.srsqrt","base.strided.smsktrunc":"\nbase.strided.smsktrunc( N, x, sx, m, sm, y, sy )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward zero according to a strided mask array and assigns the results to\n    elements in a single-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsktrunc( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsktrunc( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smsktrunc( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ 4.0, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward zero according to a strided mask array and assigns the results to\n    elements in a single-precision floating-point strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmsktrunc, base.strided.smskceil, base.strided.smskfloor, base.strided.strunc\n","base.strided.smsktrunc.ndarray":"\nbase.strided.smsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward zero according to a strided mask array and assigns the results to\n    elements in a single-precision floating-point strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmsktrunc, base.strided.smskceil, base.strided.smskfloor, base.strided.strunc","base.strided.snanmax":"\nbase.strided.snanmax( N, x, strideX )\n    Computes the maximum value of a single-precision floating-point strided\n    array, ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmax( x.length, x, 1 )\n    2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > base.strided.snanmax( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.snanmax( 3, x1, 2 )\n    2.0\n\n\nbase.strided.snanmax.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a single-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.snanmax.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.snanmax.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmax, base.strided.nanmax, base.strided.smax, base.strided.snanmin\n","base.strided.snanmax.ndarray":"\nbase.strided.snanmax.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a single-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.snanmax.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.snanmax.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmax, base.strided.nanmax, base.strided.smax, base.strided.snanmin","base.strided.snanmaxabs":"\nbase.strided.snanmaxabs( N, x, strideX )\n    Computes the maximum absolute value of a single-precision floating-point\n    strided array, ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmaxabs( x.length, x, 1 )\n    2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > base.strided.snanmaxabs( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.snanmaxabs( 3, x1, 2 )\n    2.0\n\n\nbase.strided.snanmaxabs.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a single-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.snanmaxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.snanmaxabs.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmaxabs, base.strided.nanmaxabs, base.strided.smaxabs, base.strided.snanmax, base.strided.snanminabs\n","base.strided.snanmaxabs.ndarray":"\nbase.strided.snanmaxabs.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a single-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.snanmaxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.snanmaxabs.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmaxabs, base.strided.nanmaxabs, base.strided.smaxabs, base.strided.snanmax, base.strided.snanminabs","base.strided.snanmean":"\nbase.strided.snanmean( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmean( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.snanmean( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.snanmean( N, x1, stride )\n    ~-0.3333\n\nbase.strided.snanmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.smean, base.strided.nanmean\n","base.strided.snanmean.ndarray":"\nbase.strided.snanmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.smean, base.strided.nanmean","base.strided.snanmeanors":"\nbase.strided.snanmeanors( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmeanors( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.snanmeanors( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.snanmeanors( N, x1, stride )\n    ~-0.3333\n\nbase.strided.snanmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanors, base.strided.nanmeanors, base.strided.smeanors, base.strided.snanmean\n","base.strided.snanmeanors.ndarray":"\nbase.strided.snanmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanors, base.strided.nanmeanors, base.strided.smeanors, base.strided.snanmean","base.strided.snanmeanpn":"\nbase.strided.snanmeanpn( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction\n    algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmeanpn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.snanmeanpn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.snanmeanpn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.snanmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction algorithm\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanpn, base.strided.nanmeanpn, base.strided.smeanpn, base.strided.snanmean\n","base.strided.snanmeanpn.ndarray":"\nbase.strided.snanmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction algorithm\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanpn, base.strided.nanmeanpn, base.strided.smeanpn, base.strided.snanmean","base.strided.snanmeanwd":"\nbase.strided.snanmeanwd( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmeanwd( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.snanmeanwd( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.snanmeanwd( N, x1, stride )\n    ~-0.3333\n\nbase.strided.snanmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanwd, base.strided.nanmeanwd, base.strided.smeanwd, base.strided.snanmean\n","base.strided.snanmeanwd.ndarray":"\nbase.strided.snanmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanwd, base.strided.nanmeanwd, base.strided.smeanwd, base.strided.snanmean","base.strided.snanmin":"\nbase.strided.snanmin( N, x, strideX )\n    Computes the minimum value of a single-precision floating-point strided\n    array, ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmin( x.length, x, 1 )\n    -2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > base.strided.snanmin( 3, x, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.snanmin( 3, x1, 2 )\n    -2.0\n\n\nbase.strided.snanmin.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a single-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.snanmin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.snanmin.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dnanmin, base.strided.nanmin, base.strided.smin, base.strided.snanmax\n","base.strided.snanmin.ndarray":"\nbase.strided.snanmin.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a single-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.snanmin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.snanmin.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dnanmin, base.strided.nanmin, base.strided.smin, base.strided.snanmax","base.strided.snanminabs":"\nbase.strided.snanminabs( N, x, strideX )\n    Computes the minimum absolute value of a single-precision floating-point\n    strided array, ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanminabs( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > base.strided.snanminabs( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.snanminabs( 3, x1, 2 )\n    1.0\n\n\nbase.strided.snanminabs.ndarray( N, x, strideX, offsetX )\n    Computes the minimum absolute value of a single-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.snanminabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.snanminabs.ndarray( 3, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dnanminabs, base.strided.nanminabs, base.strided.sminabs, base.strided.snanmaxabs, base.strided.snanmin\n","base.strided.snanminabs.ndarray":"\nbase.strided.snanminabs.ndarray( N, x, strideX, offsetX )\n    Computes the minimum absolute value of a single-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.snanminabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.snanminabs.ndarray( 3, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dnanminabs, base.strided.nanminabs, base.strided.sminabs, base.strided.snanmaxabs, base.strided.snanmin","base.strided.snanmskmax":"\nbase.strided.snanmskmax( N, x, strideX, mask, strideMask )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n    > base.strided.snanmskmax( x.length, x, 1, mask, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmskmax( N, x, 2, mask, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.snanmskmax( N, x1, 2, mask1, 2 )\n    2.0\n\nbase.strided.snanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.snanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmskmax, base.strided.nanmskmax, base.strided.smskmax, base.strided.snanmax, base.strided.snanmskmin\n","base.strided.snanmskmax.ndarray":"\nbase.strided.snanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.snanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmskmax, base.strided.nanmskmax, base.strided.smskmax, base.strided.snanmax, base.strided.snanmskmin","base.strided.snanmskmin":"\nbase.strided.snanmskmin( N, x, strideX, mask, strideMask )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n    > base.strided.snanmskmin( x.length, x, 1, mask, 1 )\n    -2.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmskmin( N, x, 2, mask, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.snanmskmin( N, x1, 2, mask1, 2 )\n    -2.0\n\nbase.strided.snanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.snanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dnanmskmin, base.strided.nanmskmin, base.strided.smskmin, base.strided.snanmin, base.strided.snanmskmax\n","base.strided.snanmskmin.ndarray":"\nbase.strided.snanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.snanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dnanmskmin, base.strided.nanmskmin, base.strided.smskmin, base.strided.snanmin, base.strided.snanmskmax","base.strided.snanmskrange":"\nbase.strided.snanmskrange( N, x, strideX, mask, strideMask )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n    > base.strided.snanmskrange( x.length, x, 1, mask, 1 )\n    4.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmskrange( N, x, 2, mask, 2 )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.snanmskrange( N, x1, 2, mask1, 2 )\n    4.0\n\nbase.strided.snanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.snanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dnanmskrange, base.strided.nanmskrange, base.strided.smskrange, base.strided.snanrange, base.strided.snanmskmax, base.strided.snanmskmin\n","base.strided.snanmskrange.ndarray":"\nbase.strided.snanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.snanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dnanmskrange, base.strided.nanmskrange, base.strided.smskrange, base.strided.snanrange, base.strided.snanmskmax, base.strided.snanmskmin","base.strided.snanrange":"\nbase.strided.snanrange( N, x, strideX )\n    Computes the range of a single-precision floating-point strided array,\n    ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanrange( x.length, x, 1 )\n    4.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > base.strided.snanrange( 3, x, 2 )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.snanrange( 3, x1, 2 )\n    4.0\n\n\nbase.strided.snanrange.ndarray( N, x, strideX, offsetX )\n    Computes the range of a single-precision floating-point strided array,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.snanrange.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.snanrange.ndarray( 3, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dnanrange, base.strided.nanrange, base.strided.snanmax, base.strided.snanmin, base.strided.srange\n","base.strided.snanrange.ndarray":"\nbase.strided.snanrange.ndarray( N, x, strideX, offsetX )\n    Computes the range of a single-precision floating-point strided array,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.snanrange.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.snanrange.ndarray( 3, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dnanrange, base.strided.nanrange, base.strided.snanmax, base.strided.snanmin, base.strided.srange","base.strided.snanstdev":"\nbase.strided.snanstdev( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdev( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.snanstdev( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.snanstdev( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.snanstdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.nanstdev, base.strided.snanvariance, base.strided.sstdev\n","base.strided.snanstdev.ndarray":"\nbase.strided.snanstdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.nanstdev, base.strided.snanvariance, base.strided.sstdev","base.strided.snanstdevch":"\nbase.strided.snanstdevch( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevch( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.snanstdevch( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.snanstdevch( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.snanstdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevch, base.strided.nanstdevch, base.strided.snanstdev, base.strided.snanvariancech, base.strided.sstdevch\n","base.strided.snanstdevch.ndarray":"\nbase.strided.snanstdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevch, base.strided.nanstdevch, base.strided.snanstdev, base.strided.snanvariancech, base.strided.sstdevch","base.strided.snanstdevpn":"\nbase.strided.snanstdevpn( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevpn( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.snanstdevpn( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.snanstdevpn( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.snanstdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevpn, base.strided.nanstdevpn, base.strided.snanstdev, base.strided.snanvariancepn, base.strided.sstdevpn\n","base.strided.snanstdevpn.ndarray":"\nbase.strided.snanstdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevpn, base.strided.nanstdevpn, base.strided.snanstdev, base.strided.snanvariancepn, base.strided.sstdevpn","base.strided.snanstdevtk":"\nbase.strided.snanstdevtk( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevtk( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.snanstdevtk( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.snanstdevtk( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.snanstdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevtk, base.strided.nanstdevtk, base.strided.snanstdev, base.strided.snanvariancetk, base.strided.sstdevtk\n","base.strided.snanstdevtk.ndarray":"\nbase.strided.snanstdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevtk, base.strided.nanstdevtk, base.strided.snanstdev, base.strided.snanvariancetk, base.strided.sstdevtk","base.strided.snanstdevwd":"\nbase.strided.snanstdevwd( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevwd( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.snanstdevwd( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.snanstdevwd( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.snanstdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevwd, base.strided.nanstdevwd, base.strided.snanstdev, base.strided.snanvariancewd, base.strided.sstdevwd\n","base.strided.snanstdevwd.ndarray":"\nbase.strided.snanstdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevwd, base.strided.nanstdevwd, base.strided.snanstdev, base.strided.snanvariancewd, base.strided.sstdevwd","base.strided.snanstdevyc":"\nbase.strided.snanstdevyc( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass algorithm proposed by\n    Youngs and Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevyc( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.snanstdevyc( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.snanstdevyc( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.snanstdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass algorithm proposed by\n    Youngs and Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevyc, base.strided.nanstdevyc, base.strided.snanstdev, base.strided.snanvarianceyc, base.strided.sstdevyc\n","base.strided.snanstdevyc.ndarray":"\nbase.strided.snanstdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass algorithm proposed by\n    Youngs and Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevyc, base.strided.nanstdevyc, base.strided.snanstdev, base.strided.snanvarianceyc, base.strided.sstdevyc","base.strided.snansum":"\nbase.strided.snansum( N, x, stride )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansum( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.snansum( 4, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.snansum( 4, x1, 2 )\n    -1.0\n\n\nbase.strided.snansum.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.snansum.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.gnansum, base.strided.snanmean, base.strided.ssum\n","base.strided.snansum.ndarray":"\nbase.strided.snansum.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.snansum.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.gnansum, base.strided.snanmean, base.strided.ssum","base.strided.snansumkbn":"\nbase.strided.snansumkbn( N, x, stride )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in the strided \n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, \n    use a typed array view. \n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumkbn( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > var stride = 2;\n    > base.strided.snansumkbn( 4, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > stride = 2;\n    > base.strided.snansumkbn( 4, x1, stride )\n    -1.0\n\n\nbase.strided.snansumkbn.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.snansumkbn.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn, base.strided.gnansumkbn, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn\n","base.strided.snansumkbn.ndarray":"\nbase.strided.snansumkbn.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.snansumkbn.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn, base.strided.gnansumkbn, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn","base.strided.snansumkbn2":"\nbase.strided.snansumkbn2( N, x, stride )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset,\n    use a typed array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumkbn2( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > var stride = 2;\n    > base.strided.snansumkbn2( 4, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > stride = 2;\n    > base.strided.snansumkbn2( 4, x1, stride )\n    -1.0\n\n\nbase.strided.snansumkbn2.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.snansumkbn2.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn2, base.strided.gnansumkbn2, base.strided.snansum, base.strided.snansumkbn, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn2\n","base.strided.snansumkbn2.ndarray":"\nbase.strided.snansumkbn2.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.snansumkbn2.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn2, base.strided.gnansumkbn2, base.strided.snansum, base.strided.snansumkbn, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn2","base.strided.snansumors":"\nbase.strided.snansumors( N, x, strideX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumors( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > var stride = 2;\n    > base.strided.snansumors( 4, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > stride = 2;\n    > base.strided.snansumors( 4, x1, stride )\n    -1.0\n\n\nbase.strided.snansumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.snansumors.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumors, base.strided.gnansumors, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumpw, base.strided.ssumors\n","base.strided.snansumors.ndarray":"\nbase.strided.snansumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.snansumors.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumors, base.strided.gnansumors, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumpw, base.strided.ssumors","base.strided.snansumpw":"\nbase.strided.snansumpw( N, x, strideX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumpw( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.snansumpw( 4, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.snansumpw( 4, x1, 2 )\n    -1.0\n\n\nbase.strided.snansumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.snansumpw.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumpw, base.strided.gnansumpw, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.ssumpw\n","base.strided.snansumpw.ndarray":"\nbase.strided.snansumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.snansumpw.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumpw, base.strided.gnansumpw, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.ssumpw","base.strided.snanvariance":"\nbase.strided.snanvariance( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariance( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariance( N, 1, x, 2 )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.snanvariance( N, 1, x1, 2 )\n    ~4.3333\n\nbase.strided.snanvariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariance, base.strided.nanvariance, base.strided.snanstdev, base.strided.svariance\n","base.strided.snanvariance.ndarray":"\nbase.strided.snanvariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariance, base.strided.nanvariance, base.strided.snanstdev, base.strided.svariance","base.strided.snanvariancech":"\nbase.strided.snanvariancech( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancech( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancech( N, 1, x, 2 )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.snanvariancech( N, 1, x1, 2 )\n    ~4.3333\n\nbase.strided.snanvariancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancech, base.strided.nanvariancech, base.strided.snanstdevch, base.strided.snanvariance, base.strided.svariancech\n","base.strided.snanvariancech.ndarray":"\nbase.strided.snanvariancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancech, base.strided.nanvariancech, base.strided.snanstdevch, base.strided.snanvariance, base.strided.svariancech","base.strided.snanvariancepn":"\nbase.strided.snanvariancepn( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancepn( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancepn( N, 1, x, 2 )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.snanvariancepn( N, 1, x1, 2 )\n    ~4.3333\n\nbase.strided.snanvariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancepn, base.strided.nanvariancepn, base.strided.snanstdevpn, base.strided.snanvariance, base.strided.svariancepn\n","base.strided.snanvariancepn.ndarray":"\nbase.strided.snanvariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancepn, base.strided.nanvariancepn, base.strided.snanstdevpn, base.strided.snanvariance, base.strided.svariancepn","base.strided.snanvariancetk":"\nbase.strided.snanvariancetk( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancetk( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancetk( N, 1, x, 2 )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.snanvariancetk( N, 1, x1, 2 )\n    ~4.3333\n\nbase.strided.snanvariancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancetk, base.strided.nanvariancetk, base.strided.snanstdevtk, base.strided.snanvariance, base.strided.svariancetk\n","base.strided.snanvariancetk.ndarray":"\nbase.strided.snanvariancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancetk, base.strided.nanvariancetk, base.strided.snanstdevtk, base.strided.snanvariance, base.strided.svariancetk","base.strided.snanvariancewd":"\nbase.strided.snanvariancewd( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancewd( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancewd( N, 1, x, 2 )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.snanvariancewd( N, 1, x1, 2 )\n    ~4.3333\n\nbase.strided.snanvariancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using Welford's algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancewd, base.strided.nanvariancewd, base.strided.snanstdevwd, base.strided.snanvariance, base.strided.svariancewd\n","base.strided.snanvariancewd.ndarray":"\nbase.strided.snanvariancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using Welford's algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancewd, base.strided.nanvariancewd, base.strided.snanstdevwd, base.strided.snanvariance, base.strided.svariancewd","base.strided.snanvarianceyc":"\nbase.strided.snanvarianceyc( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n    Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvarianceyc( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvarianceyc( N, 1, x, 2 )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.snanvarianceyc( N, 1, x1, 2 )\n    ~4.3333\n\nbase.strided.snanvarianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n    Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvarianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvarianceyc, base.strided.nanvarianceyc, base.strided.snanstdevyc, base.strided.snanvariance, base.strided.svarianceyc\n","base.strided.snanvarianceyc.ndarray":"\nbase.strided.snanvarianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n    Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvarianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvarianceyc, base.strided.nanvarianceyc, base.strided.snanstdevyc, base.strided.snanvariance, base.strided.svarianceyc","base.strided.snrm2":"\nbase.strided.snrm2( N, x, stride )\n    Computes the L2-norm of a single-precision floating-point vector.\n\n    The `N` and `stride` parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0` the function returns `0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The L2-norm.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.snrm2( x.length, x, 1 )\n    3.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.snrm2( 3, x, 2 )\n    3.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.snrm2( 3, x1, 2 )\n    3.0\n\n\nbase.strided.snrm2.ndarray( N, x, stride, offset )\n    Computes the L2-norm of a single-precision floating-point vector using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The L2-norm.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.snrm2.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.snrm2.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dnrm2, base.strided.gnrm2\n","base.strided.snrm2.ndarray":"\nbase.strided.snrm2.ndarray( N, x, stride, offset )\n    Computes the L2-norm of a single-precision floating-point vector using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The L2-norm.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.snrm2.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.snrm2.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dnrm2, base.strided.gnrm2","base.strided.sramp":"\nbase.strided.sramp( N, x, strideX, y, strideY )\n    Evaluates the ramp function for each element in a single-precision floating-\n    point strided array `x` and assigns the results to elements in a single-\n    precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sramp( x.length, x, 1, y, 1 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sramp( N, x, 2, y, -1 )\n    <Float32Array>[ 0.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.sramp( N, x1, -2, y1, 1 )\n    <Float32Array>[ 4.0, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.sramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Evaluates the ramp function for each element in a single-precision floating-\n    point strided array `x` and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dramp, strided.ramp\n","base.strided.sramp.ndarray":"\nbase.strided.sramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Evaluates the ramp function for each element in a single-precision floating-\n    point strided array `x` and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dramp, strided.ramp","base.strided.srange":"\nbase.strided.srange( N, x, strideX )\n    Computes the range of a single-precision floating-point strided array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.srange( x.length, x, 1 )\n    4.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.srange( 3, x, 2 )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.srange( 3, x1, 2 )\n    4.0\n\n\nbase.strided.srange.ndarray( N, x, strideX, offsetX )\n    Computes the range of a single-precision floating-point strided array using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.srange.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.srange.ndarray( 3, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.drange, base.strided.smax, base.strided.smin, base.strided.snanrange, base.strided.range\n","base.strided.srange.ndarray":"\nbase.strided.srange.ndarray( N, x, strideX, offsetX )\n    Computes the range of a single-precision floating-point strided array using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.srange.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.srange.ndarray( 3, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.drange, base.strided.smax, base.strided.smin, base.strided.snanrange, base.strided.range","base.strided.srev":"\nbase.strided.srev( N, x, stride )\n    Reverses a single-precision floating-point strided array in-place.\n\n    The `N` and `stride` parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.srev( x.length, x, 1 )\n    <Float32Array>[ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.srev( 3, x, 2 )\n    <Float32Array>[ 4.0, 1.0, 3.0, -5.0, -2.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.srev( 3, x1, 2 )\n    <Float32Array>[ -6.0, 3.0, -4.0, 5.0, -2.0 ]\n    > x0\n    <Float32Array>[ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n\nbase.strided.srev.ndarray( N, x, stride, offset )\n    Reverses a single-precision floating-point strided array in-place using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.srev.ndarray( x.length, x, 1, 0 )\n    <Float32Array>[ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.srev.ndarray( 3, x, 2, 1 )\n    <Float32Array>[ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.drev, base.strided.grev\n","base.strided.srev.ndarray":"\nbase.strided.srev.ndarray( N, x, stride, offset )\n    Reverses a single-precision floating-point strided array in-place using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.srev.ndarray( x.length, x, 1, 0 )\n    <Float32Array>[ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.srev.ndarray( 3, x, 2, 1 )\n    <Float32Array>[ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.drev, base.strided.grev","base.strided.srsqrt":"\nbase.strided.srsqrt( N, x, strideX, y, strideY )\n    Computes the reciprocal square root for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.srsqrt( x.length, x, 1, y, 1 )\n    <Float32Array>[ 1.0, 0.5, ~0.333, ~0.289 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.srsqrt( N, x, 2, y, -1 )\n    <Float32Array>[ ~0.333, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.srsqrt( N, x1, -2, y1, 1 )\n    <Float32Array>[ ~0.289, 0.5 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.srsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the reciprocal square root for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.srsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 0.5, ~0.333, ~0.289 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.srsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n    See Also\n    --------\n    base.strided.drsqrt, strided.rsqrt, base.strided.ssqrt\n","base.strided.srsqrt.ndarray":"\nbase.strided.srsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the reciprocal square root for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.srsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 0.5, ~0.333, ~0.289 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.srsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n    See Also\n    --------\n    base.strided.drsqrt, strided.rsqrt, base.strided.ssqrt","base.strided.sscal":"\nbase.strided.sscal( N, alpha, x, stride )\n    Multiplies a single-precision floating-point vector `x` by a constant\n    `alpha`.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sscal( x.length, 5.0, x, 1 )\n    <Float32Array>[ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sscal( 3, 5.0, x, 2 )\n    <Float32Array>[ -10.0, 1.0, 15.0, -5.0, 20.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sscal( 3, 5.0, x1, 2 )\n    <Float32Array>[ -10.0, 3.0, -20.0, 5.0, -30.0 ]\n    > x0\n    <Float32Array>[ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n\nbase.strided.sscal.ndarray( N, alpha, x, stride, offset )\n    Multiplies a single-precision floating-point vector `x` by a constant\n    `alpha` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sscal.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float32Array>[ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.sscal.ndarray( 3, 5.0, x, 2, 1 )\n    <Float32Array>[ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n    See Also\n    --------\n    base.strided.daxpy, base.strided.dscal, base.strided.gscal, base.strided.saxpy\n","base.strided.sscal.ndarray":"\nbase.strided.sscal.ndarray( N, alpha, x, stride, offset )\n    Multiplies a single-precision floating-point vector `x` by a constant\n    `alpha` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sscal.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float32Array>[ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.sscal.ndarray( 3, 5.0, x, 2, 1 )\n    <Float32Array>[ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n    See Also\n    --------\n    base.strided.daxpy, base.strided.dscal, base.strided.gscal, base.strided.saxpy","base.strided.ssort2hp":"\nbase.strided.ssort2hp( N, order, x, strideX, y, strideY )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using heapsort.\n\n    The `N` and `stride` parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided arrays are sorted *in-place* (i.e., the input strided\n    arrays are *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2hp( x.length, 1, x, 1, y, 1 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float32Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2hp( 2, -1, x, 2, y, 2 )\n    <Float32Array>[ 3.0, -2.0, 1.0, -4.0 ]\n    > y\n    <Float32Array>[ 2.0, 1.0, 0.0, 3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n    > base.strided.ssort2hp( 2, 1, x1, 2, y1, 2 )\n    <Float32Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.ssort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using heapsort and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float32Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2hp.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float32Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2hp, base.strided.gsort2hp, base.strided.ssorthp\n","base.strided.ssort2hp.ndarray":"\nbase.strided.ssort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using heapsort and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float32Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2hp.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float32Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2hp, base.strided.gsort2hp, base.strided.ssorthp","base.strided.ssort2ins":"\nbase.strided.ssort2ins( N, order, x, strideX, y, strideY )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using insertion sort.\n\n    The `N` and stride parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function leaves the strided arrays\n    are unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^2).\n\n    The algorithm is efficient for *small* strided arrays (typically N <= 20)\n    and is particularly efficient for sorting strided arrays which are already\n    substantially sorted.\n\n    The algorithm is *stable*, meaning that the algorithm does *not* change the\n    order of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided arrays are sorted *in-place* (i.e., the input strided\n    arrays is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    x: Float32Array\n        First input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2ins( x.length, 1, x, 1, y, 1 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float32Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2ins( 2, -1, x, 2, y, 2 )\n    <Float32Array>[ 3.0, -2.0, 1.0, -4.0 ]\n    > y\n    <Float32Array>[ 2.0, 1.0, 0.0, 3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n    > base.strided.ssort2ins( 2, 1, x1, 2, y1, 2 )\n    <Float32Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.ssort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using insertion sort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float32Array\n        First input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float32Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float32Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2ins, base.strided.gsort2ins, base.strided.ssortins\n","base.strided.ssort2ins.ndarray":"\nbase.strided.ssort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using insertion sort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float32Array\n        First input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float32Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float32Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2ins, base.strided.gsort2ins, base.strided.ssortins","base.strided.ssort2sh":"\nbase.strided.ssort2sh( N, order, x, strideX, y, strideY )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using Shellsort.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^(4/3)).\n\n    The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided arrays are sorted *in-place* (i.e., the input strided\n    arrays are *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2sh( x.length, 1, x, 1, y, 1 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float32Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2sh( 2, -1, x, 2, y, 2 )\n    <Float32Array>[ 3.0, -2.0, 1.0, -4.0 ]\n    > y\n    <Float32Array>[ 2.0, 1.0, 0.0, 3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n    > base.strided.ssort2sh( 2, 1, x1, 2, y1, 2 )\n    <Float32Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.ssort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using Shellsort and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float32Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2sh.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float32Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2sh, base.strided.gsort2sh, base.strided.ssortsh\n","base.strided.ssort2sh.ndarray":"\nbase.strided.ssort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using Shellsort and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float32Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2sh.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float32Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2sh, base.strided.gsort2sh, base.strided.ssortsh","base.strided.ssorthp":"\nbase.strided.ssorthp( N, order, x, stride )\n    Sorts a single-precision floating-point strided array using heapsort.\n\n    The `N` and stride parameters determine which elements in the strided\n    array are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function returns the strided\n    array unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided array is sorted *in-place* (i.e., the input strided array\n    is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts the strided array in\n        decreasing order. If `order > 0`, the function sorts the strided array\n        in increasing order.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for the strided array.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array the strided array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssorthp( x.length, 1, x, 1 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssorthp( 2, -1, x, 2 )\n    <Float32Array>[ 3.0, -2.0, 1.0, -4.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.ssorthp( 2, 1, x1, 2 )\n    <Float32Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.ssorthp.ndarray( N, order, x, stride, offset )\n    Sorts a single-precision floating-point strided array using heapsort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts the strided array in\n        decreasing order. If `order > 0`, the function sorts the strided array\n        in increasing order.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for the strided array.\n\n    offset: integer\n        Starting index of the strided array.\n\n    Returns\n    -------\n    x: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssorthp.ndarray( x.length, 1, x, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssorthp.ndarray( 2, 1, x, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsorthp, base.strided.gsorthp, base.strided.ssort2hp\n","base.strided.ssorthp.ndarray":"\nbase.strided.ssorthp.ndarray( N, order, x, stride, offset )\n    Sorts a single-precision floating-point strided array using heapsort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts the strided array in\n        decreasing order. If `order > 0`, the function sorts the strided array\n        in increasing order.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for the strided array.\n\n    offset: integer\n        Starting index of the strided array.\n\n    Returns\n    -------\n    x: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssorthp.ndarray( x.length, 1, x, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssorthp.ndarray( 2, 1, x, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsorthp, base.strided.gsorthp, base.strided.ssort2hp","base.strided.ssortins":"\nbase.strided.ssortins( N, order, x, stride )\n    Sorts a single-precision floating-point strided array using insertion sort.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^2).\n\n    The algorithm is efficient for *small* strided arrays (typically N <= 20)\n    and is particularly efficient for sorting strided arrays which are already\n    substantially sorted.\n\n    The algorithm is *stable*, meaning that the algorithm does *not* change the\n    order of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided array is sorted *in-place* (i.e., the input strided array\n    is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortins( x.length, 1, x, 1 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortins( 2, -1, x, 2 )\n    <Float32Array>[ 3.0, -2.0, 1.0, -4.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.ssortins( 2, 1, x1, 2 )\n    <Float32Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.ssortins.ndarray( N, order, x, stride, offset )\n    Sorts a single-precision floating-point strided array using insertion sort\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortins.ndarray( x.length, 1, x, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortins.ndarray( 2, 1, x, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsortins, base.strided.gsortins, base.strided.ssort2ins\n","base.strided.ssortins.ndarray":"\nbase.strided.ssortins.ndarray( N, order, x, stride, offset )\n    Sorts a single-precision floating-point strided array using insertion sort\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortins.ndarray( x.length, 1, x, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortins.ndarray( 2, 1, x, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsortins, base.strided.gsortins, base.strided.ssort2ins","base.strided.ssortsh":"\nbase.strided.ssortsh( N, order, x, stride )\n    Sorts a single-precision floating-point strided array using Shellsort.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^(4/3)).\n\n    The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided array is sorted *in-place* (i.e., the input strided array\n    is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortsh( x.length, 1, x, 1 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortsh( 2, -1, x, 2 )\n    <Float32Array>[ 3.0, -2.0, 1.0, -4.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.ssortsh( 2, 1, x1, 2 )\n    <Float32Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.ssortsh.ndarray( N, order, x, stride, offset )\n    Sorts a single-precision floating-point strided array using Shellsort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortsh.ndarray( x.length, 1, x, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortsh.ndarray( 2, 1, x, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsortsh, base.strided.gsortsh, base.strided.ssort2sh\n","base.strided.ssortsh.ndarray":"\nbase.strided.ssortsh.ndarray( N, order, x, stride, offset )\n    Sorts a single-precision floating-point strided array using Shellsort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortsh.ndarray( x.length, 1, x, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortsh.ndarray( 2, 1, x, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsortsh, base.strided.gsortsh, base.strided.ssort2sh","base.strided.ssqrt":"\nbase.strided.ssqrt( N, x, strideX, y, strideY )\n    Computes the principal square root for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.ssqrt( x.length, x, 1, y, 1 )\n    <Float32Array>[ 0.0, 2.0, 3.0, ~3.464 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.ssqrt( N, x, 2, y, -1 )\n    <Float32Array>[ 3.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.ssqrt( N, x1, -2, y1, 1 )\n    <Float32Array>[ ~3.464, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.ssqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the principal square root for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.ssqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, 2.0, 3.0, ~3.464 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.ssqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dsqrt, base.strided.scbrt, strided.sqrt, base.strided.srsqrt\n","base.strided.ssqrt.ndarray":"\nbase.strided.ssqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the principal square root for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.ssqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, 2.0, 3.0, ~3.464 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.ssqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dsqrt, base.strided.scbrt, strided.sqrt, base.strided.srsqrt","base.strided.sstdev":"\nbase.strided.sstdev( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdev( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sstdev( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sstdev( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.sstdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdev, base.strided.snanstdev, base.strided.stdev, base.strided.svariance\n","base.strided.sstdev.ndarray":"\nbase.strided.sstdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdev, base.strided.snanstdev, base.strided.stdev, base.strided.svariance","base.strided.sstdevch":"\nbase.strided.sstdevch( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevch( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sstdevch( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sstdevch( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.sstdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevch, base.strided.snanstdevch, base.strided.sstdev, base.strided.stdevch, base.strided.svariancech\n","base.strided.sstdevch.ndarray":"\nbase.strided.sstdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevch, base.strided.snanstdevch, base.strided.sstdev, base.strided.stdevch, base.strided.svariancech","base.strided.sstdevpn":"\nbase.strided.sstdevpn( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevpn( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sstdevpn( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sstdevpn( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.sstdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevpn, base.strided.snanstdevpn, base.strided.sstdev, base.strided.stdevpn, base.strided.svariancepn\n","base.strided.sstdevpn.ndarray":"\nbase.strided.sstdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevpn, base.strided.snanstdevpn, base.strided.sstdev, base.strided.stdevpn, base.strided.svariancepn","base.strided.sstdevtk":"\nbase.strided.sstdevtk( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevtk( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sstdevtk( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sstdevtk( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.sstdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass textbook algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevtk, base.strided.snanstdevtk, base.strided.sstdev, base.strided.stdevtk, base.strided.svariancetk\n","base.strided.sstdevtk.ndarray":"\nbase.strided.sstdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass textbook algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevtk, base.strided.snanstdevtk, base.strided.sstdev, base.strided.stdevtk, base.strided.svariancetk","base.strided.sstdevwd":"\nbase.strided.sstdevwd( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevwd( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sstdevwd( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sstdevwd( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.sstdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevwd, base.strided.snanstdevwd, base.strided.sstdev, base.strided.stdevwd, base.strided.svariancewd\n","base.strided.sstdevwd.ndarray":"\nbase.strided.sstdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevwd, base.strided.snanstdevwd, base.strided.sstdev, base.strided.stdevwd, base.strided.svariancewd","base.strided.sstdevyc":"\nbase.strided.sstdevyc( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevyc( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sstdevyc( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sstdevyc( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.sstdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevyc, base.strided.snanstdevyc, base.strided.sstdev, base.strided.stdevyc, base.strided.svarianceyc\n","base.strided.sstdevyc.ndarray":"\nbase.strided.sstdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevyc, base.strided.snanstdevyc, base.strided.sstdev, base.strided.stdevyc, base.strided.svarianceyc","base.strided.ssum":"\nbase.strided.ssum( N, x, stride )\n    Computes the sum of single-precision floating-point strided array elements.\n\n    The `N` and `stride` parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssum( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.ssum( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.ssum( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.ssum.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.ssum.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsum, base.strided.smean, base.strided.snansum, base.strided.gsum\n","base.strided.ssum.ndarray":"\nbase.strided.ssum.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.ssum.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsum, base.strided.smean, base.strided.snansum, base.strided.gsum","base.strided.ssumkbn":"\nbase.strided.ssumkbn( N, x, stride )\n    Computes the sum of single-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumkbn( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.ssumkbn( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.ssumkbn( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.ssumkbn.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.ssumkbn.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumkbn, base.strided.gsumkbn, base.strided.snansumkbn, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors, base.strided.ssumpw\n","base.strided.ssumkbn.ndarray":"\nbase.strided.ssumkbn.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.ssumkbn.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumkbn, base.strided.gsumkbn, base.strided.snansumkbn, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors, base.strided.ssumpw","base.strided.ssumkbn2":"\nbase.strided.ssumkbn2( N, x, stride )\n    Computes the sum of single-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in  the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumkbn2( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.ssumkbn2( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.ssumkbn2( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.ssumkbn2.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.ssumkbn2.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumkbn2, base.strided.gsumkbn2, base.strided.snansumkbn2, base.strided.ssum, base.strided.ssumkbn, base.strided.ssumors, base.strided.ssumpw\n","base.strided.ssumkbn2.ndarray":"\nbase.strided.ssumkbn2.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.ssumkbn2.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumkbn2, base.strided.gsumkbn2, base.strided.snansumkbn2, base.strided.ssum, base.strided.ssumkbn, base.strided.ssumors, base.strided.ssumpw","base.strided.ssumors":"\nbase.strided.ssumors( N, x, strideX )\n    Computes the sum of single-precision floating-point strided array elements\n    using ordinary recursive summation.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumors( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.ssumors( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.ssumors( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.ssumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements\n    using ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.ssumors.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumors, base.strided.gsumors, base.strided.snansumors, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumpw\n","base.strided.ssumors.ndarray":"\nbase.strided.ssumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements\n    using ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.ssumors.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumors, base.strided.gsumors, base.strided.snansumors, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumpw","base.strided.ssumpw":"\nbase.strided.ssumpw( N, x, strideX )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumpw( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.ssumpw( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.ssumpw( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.ssumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.ssumpw.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumpw, base.strided.gsumpw, base.strided.snansumpw, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors\n","base.strided.ssumpw.ndarray":"\nbase.strided.ssumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.ssumpw.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumpw, base.strided.gsumpw, base.strided.snansumpw, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors","base.strided.sswap":"\nbase.strided.sswap( N, x, strideX, y, strideY )\n    Interchanges two single-precision floating-point vectors.\n\n    The `N` and stride parameters determine how values from `x` are swapped\n    with values from `y`.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the vectors are unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Second input array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.sswap( x.length, x, 1, y, 1 )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.sswap( 3, x, -2, y, 1 )\n    <Float32Array>[ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n    // Using typed array views:\n    > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.sswap( 3, x1, -2, y1, 1 )\n    <Float32Array>[ 6.0, 4.0, 2.0 ]\n    > y0\n    <Float32Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.sswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Interchanges two single-precision floating-point vectors using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Second input array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.sswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.sswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dswap, base.strided.gswap, base.strided.scopy, sswap\n","base.strided.sswap.ndarray":"\nbase.strided.sswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Interchanges two single-precision floating-point vectors using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Second input array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.sswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.sswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dswap, base.strided.gswap, base.strided.scopy, sswap","base.strided.stdev":"\nbase.strided.stdev( N, correction, x, stride )\n    Computes the standard deviation of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdev( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.stdev( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.stdev( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.stdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdev, base.strided.nanstdev, base.strided.sstdev, base.strided.variance\n","base.strided.stdev.ndarray":"\nbase.strided.stdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdev, base.strided.nanstdev, base.strided.sstdev, base.strided.variance","base.strided.stdevch":"\nbase.strided.stdevch( N, correction, x, stride )\n    Computes the standard deviation of a strided array using a one-pass trial\n    mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevch( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.stdevch( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.stdevch( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.stdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using a one-pass trial\n    mean algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevch, base.strided.nanstdevch, base.strided.sstdevch, base.strided.stdev, base.strided.variancech\n","base.strided.stdevch.ndarray":"\nbase.strided.stdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using a one-pass trial\n    mean algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevch, base.strided.nanstdevch, base.strided.sstdevch, base.strided.stdev, base.strided.variancech","base.strided.stdevpn":"\nbase.strided.stdevpn( N, correction, x, stride )\n    Computes the standard deviation of a strided array using a two-pass\n    algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevpn( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.stdevpn( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.stdevpn( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.stdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using a two-pass\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.sstdevpn, base.strided.stdev, base.strided.variancepn\n","base.strided.stdevpn.ndarray":"\nbase.strided.stdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using a two-pass\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.sstdevpn, base.strided.stdev, base.strided.variancepn","base.strided.stdevtk":"\nbase.strided.stdevtk( N, correction, x, stride )\n    Computes the standard deviation of a strided array using a one-pass textbook\n    algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevtk( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.stdevtk( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.stdevtk( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.stdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using a one-pass textbook\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.sstdevtk, base.strided.stdev, base.strided.variancetk\n","base.strided.stdevtk.ndarray":"\nbase.strided.stdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using a one-pass textbook\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.sstdevtk, base.strided.stdev, base.strided.variancetk","base.strided.stdevwd":"\nbase.strided.stdevwd( N, correction, x, stride )\n    Computes the standard deviation of a strided array using Welford's\n    algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevwd( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.stdevwd( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.stdevwd( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.stdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using Welford's algorithm\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.sstdevwd, base.strided.stdev, base.strided.variancewd\n","base.strided.stdevwd.ndarray":"\nbase.strided.stdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using Welford's algorithm\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.sstdevwd, base.strided.stdev, base.strided.variancewd","base.strided.stdevyc":"\nbase.strided.stdevyc( N, correction, x, stride )\n    Computes the standard deviation of a strided array using a one-pass\n    algorithm proposed by Youngs and Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevyc( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.stdevyc( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.stdevyc( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.stdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using a one-pass\n    algorithm proposed by Youngs and Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.sstdevyc, base.strided.stdev, base.strided.varianceyc\n","base.strided.stdevyc.ndarray":"\nbase.strided.stdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using a one-pass\n    algorithm proposed by Youngs and Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.sstdevyc, base.strided.stdev, base.strided.varianceyc","base.strided.strunc":"\nbase.strided.strunc( N, x, strideX, y, strideY )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward zero and assigns the results to elements in a single-precision\n    floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.strunc( x.length, x, 1, y, 1 )\n    <Float32Array>[ 1.0, 2.0, -3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.strunc( N, x, 2, y, -1 )\n    <Float32Array>[ -3.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.strunc( N, x1, -2, y1, 1 )\n    <Float32Array>[ 4.0, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.strunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward zero and assigns the results to elements in a single-precision\n    floating-point strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.strunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.strunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dtrunc, base.strided.sceil, base.strided.sfloor, strided.trunc\n","base.strided.strunc.ndarray":"\nbase.strided.strunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward zero and assigns the results to elements in a single-precision\n    floating-point strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.strunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.strunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dtrunc, base.strided.sceil, base.strided.sfloor, strided.trunc","base.strided.svariance":"\nbase.strided.svariance( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariance( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.svariance( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.svariance( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.svariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariance, base.strided.snanvariance, base.strided.sstdev, base.strided.variance\n","base.strided.svariance.ndarray":"\nbase.strided.svariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariance, base.strided.snanvariance, base.strided.sstdev, base.strided.variance","base.strided.svariancech":"\nbase.strided.svariancech( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancech( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.svariancech( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.svariancech( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.svariancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass trial mean algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svariancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancech, base.strided.snanvariancech, base.strided.sstdevch, base.strided.svariance, base.strided.variancech\n","base.strided.svariancech.ndarray":"\nbase.strided.svariancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass trial mean algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svariancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancech, base.strided.snanvariancech, base.strided.sstdevch, base.strided.svariance, base.strided.variancech","base.strided.svariancepn":"\nbase.strided.svariancepn( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancepn( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.svariancepn( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.svariancepn( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.svariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancepn, base.strided.snanvariancepn, base.strided.sstdevpn, base.strided.svariance, base.strided.variancepn\n","base.strided.svariancepn.ndarray":"\nbase.strided.svariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancepn, base.strided.snanvariancepn, base.strided.sstdevpn, base.strided.svariance, base.strided.variancepn","base.strided.svariancetk":"\nbase.strided.svariancetk( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancetk( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.svariancetk( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.svariancetk( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.svariancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass textbook algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svariancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancetk, base.strided.snanvariancetk, base.strided.sstdevtk, base.strided.svariance, base.strided.variancetk\n","base.strided.svariancetk.ndarray":"\nbase.strided.svariancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass textbook algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svariancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancetk, base.strided.snanvariancetk, base.strided.sstdevtk, base.strided.svariance, base.strided.variancetk","base.strided.svariancewd":"\nbase.strided.svariancewd( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancewd( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.svariancewd( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.svariancewd( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.svariancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svariancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancewd, base.strided.snanvariancewd, base.strided.sstdevwd, base.strided.svariance, base.strided.variancewd\n","base.strided.svariancewd.ndarray":"\nbase.strided.svariancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svariancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancewd, base.strided.snanvariancewd, base.strided.sstdevwd, base.strided.svariance, base.strided.variancewd","base.strided.svarianceyc":"\nbase.strided.svarianceyc( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass algorithm proposed by Youngs and Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svarianceyc( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.svarianceyc( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.svarianceyc( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.svarianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass algorithm proposed by Youngs and Cramer and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svarianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svarianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvarianceyc, base.strided.snanvarianceyc, base.strided.sstdevyc, base.strided.svariance, base.strided.varianceyc\n","base.strided.svarianceyc.ndarray":"\nbase.strided.svarianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass algorithm proposed by Youngs and Cramer and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svarianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svarianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvarianceyc, base.strided.snanvarianceyc, base.strided.sstdevyc, base.strided.svariance, base.strided.varianceyc","base.strided.ternary":"\nbase.strided.ternary( arrays, shape, strides, fcn )\n    Applies a ternary callback to strided input array elements and assigns\n    results to elements in a strided output array.\n\n    The `shape` and `strides` parameters determine which elements in the strided\n    input and output arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing three strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    fcn: Function\n        Ternary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1, 1 ];\n    > function f( x, y, z ) { return x + y + z; };\n    > base.strided.ternary( [ x, y, z, w ], shape, strides, f );\n    > w\n    <Float64Array>[ 3.0, 6.0, 9.0, 12.0 ]\n\n\nbase.strided.ternary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a ternary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing three strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Ternary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1, 1 ];\n    > var offsets = [ 0, 0, 0, 0 ];\n    > function f( x, y, z ) { return x + y + z; };\n    > base.strided.ternary.ndarray( [ x, y, z, w ], shape, strides, offsets, f );\n    > w\n    <Float64Array>[ 3.0, 6.0, 9.0, 12.0 ]\n\n    See Also\n    --------\n    base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.unary\n","base.strided.ternary.ndarray":"\nbase.strided.ternary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a ternary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing three strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Ternary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1, 1 ];\n    > var offsets = [ 0, 0, 0, 0 ];\n    > function f( x, y, z ) { return x + y + z; };\n    > base.strided.ternary.ndarray( [ x, y, z, w ], shape, strides, offsets, f );\n    > w\n    <Float64Array>[ 3.0, 6.0, 9.0, 12.0 ]\n\n    See Also\n    --------\n    base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.unary","base.strided.unary":"\nbase.strided.unary( arrays, shape, strides, fcn )\n    Applies a unary callback to elements in a strided input array and assigns\n    results to elements in a strided output array.\n\n    The `shape` and `strides` parameters determine which elements in the strided\n    input and output arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided input array and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    fcn: Function\n        Unary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1 ];\n    > base.strided.unary( [ x, y ], shape, strides, base.abs );\n    > y\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n\nbase.strided.unary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a unary callback to elements in a strided input array and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided input array and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Unary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1 ];\n    > var offsets = [ 0, 0 ];\n    > base.strided.unary.ndarray( [ x, y ], shape, strides, offsets, base.abs );\n    > y\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    See Also\n    --------\n    base.strided.unary, base.strided.dmap, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap, base.strided.ternary\n","base.strided.unary.ndarray":"\nbase.strided.unary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a unary callback to elements in a strided input array and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided input array and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Unary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1 ];\n    > var offsets = [ 0, 0 ];\n    > base.strided.unary.ndarray( [ x, y ], shape, strides, offsets, base.abs );\n    > y\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    See Also\n    --------\n    base.strided.unary, base.strided.dmap, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap, base.strided.ternary","base.strided.unaryBy":"\nbase.strided.unaryBy( arrays, shape, strides, fcn, clbk[, thisArg] )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array.\n\n    The shape and stride parameters determine which elements in the strided\n    input and output arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - indices: strided indices (offset + idx*stride).\n    - arrays: input and output arrays.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided input array and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    fcn: Function\n        Unary function to apply to callback return values.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > var sh = [ x.length ];\n    > var st = [ 1, 1 ];\n    > function clbk( v ) { return v * 2.0; };\n    > base.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\n    > y\n    [ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Using shape and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > sh = [ 2 ];\n    > st = [ 2, -1 ];\n    > base.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\n    > y\n    [ 6.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > sh = [ 2 ];\n    > st = [ -2, 1 ];\n    > base.strided.unaryBy( [ x1, y1 ], sh, st, base.abs, clbk );\n    > y1\n    <Float64Array>[ 8.0, 4.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 8.0, 4.0 ]\n\n\nbase.strided.unaryBy.ndarray( arrays, shape, strides, offsets, fcn, clbk[, thisArg] )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offsest parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided input array and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Unary function to apply to callback return values.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > var sh = [ x.length ];\n    > var st = [ 1, 1 ];\n    > var o = [ 0, 0 ];\n    > function clbk( v ) { return v * 2.0; };\n    > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n    > y\n    [ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > sh = [ 2 ];\n    > st = [ 2, -1 ];\n    > o = [ 1, y.length-1 ];\n    > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n    > y\n    [ 0.0, 0.0, 8.0, 4.0 ]\n\n    See Also\n    --------\n    base.strided.mapBy, base.strided.unary\n","base.strided.unaryBy.ndarray":"\nbase.strided.unaryBy.ndarray( arrays, shape, strides, offsets, fcn, clbk[, thisArg] )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offsest parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided input array and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Unary function to apply to callback return values.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > var sh = [ x.length ];\n    > var st = [ 1, 1 ];\n    > var o = [ 0, 0 ];\n    > function clbk( v ) { return v * 2.0; };\n    > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n    > y\n    [ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > sh = [ 2 ];\n    > st = [ 2, -1 ];\n    > o = [ 1, y.length-1 ];\n    > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n    > y\n    [ 0.0, 0.0, 8.0, 4.0 ]\n\n    See Also\n    --------\n    base.strided.mapBy, base.strided.unary","base.strided.unaryDtypeSignatures":"\nbase.strided.unaryDtypeSignatures( dtypes1, dtypes2[, options] )\n    Generates a list of unary interface signatures from strided array data\n    types.\n\n    The function returns a strided array having a stride length of two (i.e.,\n    every two elements define a unary interface signature).\n\n    For each signature (i.e., set of two consecutive non-overlapping strided\n    array elements), the first element is the input data type and the second\n    element is the return data type.\n\n    All signatures follow type promotion rules.\n\n    Parameters\n    ----------\n    dtypes1: ArrayLike<any>\n        List of supported data types for the input argument.\n\n    dtypes2: ArrayLike<any>\n        List of supported data types for the output argument.\n\n    options: Object (optional)\n        Options.\n\n    options.enums: boolean (optional)\n        Boolean flag indicating whether to return signatures as a list of data\n        type enumeration constants. Default: false.\n\n    Returns\n    -------\n    out: Array\n        Strided array containing unary interface signatures.\n\n    Examples\n    --------\n    > var dt = strided.dataTypes();\n    > var out = base.strided.unaryDtypeSignatures( dt, dt )\n    [...]\n\n    See Also\n    --------\n    base.strided.unarySignatureCallbacks\n","base.strided.unarySignatureCallbacks":"\nbase.strided.unarySignatureCallbacks( table, signatures )\n    Assigns callbacks to unary interfaces according to type promotion rules.\n\n    Parameters\n    ----------\n    table: Object\n        Object mapping callbacks to data types.\n\n    table.default: Function\n        Default callback.\n\n    table.complex64: Function\n        Callback to be invoked when input arrays promote to single-precision\n        complex floating-point numbers.\n\n    table.complex128: Function\n        Callback to be invoked when input arrays promote to double precision\n        complex floating-point numbers.\n\n    signatures: ArrayLike<any>\n        Strided array containing unary interface signatures.\n\n    Returns\n    -------\n    out: Array<Function>\n        List of callbacks, one per signature.\n\n    Examples\n    --------\n    > var dt = strided.dataTypes();\n    > var sigs = base.strided.unaryDtypeSignatures( dt, dt );\n    > var t = {\n    ...     'default': base.identity,\n    ...     'complex64': base.cidentityf,\n    ...     'complex128': base.cidentity\n    ... };\n    > var out = base.strided.unarySignatureCallbacks( t, sigs )\n    [...]\n\n    See Also\n    --------\n    base.strided.unaryDtypeSignatures\n","base.strided.variance":"\nbase.strided.variance( N, correction, x, stride )\n    Computes the variance of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variance( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.variance( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.variance( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.variance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.variance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariance, base.strided.nanvariance, base.strided.stdev, base.strided.svariance\n","base.strided.variance.ndarray":"\nbase.strided.variance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.variance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariance, base.strided.nanvariance, base.strided.stdev, base.strided.svariance","base.strided.variancech":"\nbase.strided.variancech( N, correction, x, stride )\n    Computes the variance of a strided array using a one-pass trial mean\n    algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancech( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.variancech( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.variancech( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.variancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using a one-pass trial mean\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.variancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancech, base.strided.nanvariancech, base.strided.stdevch, base.strided.variance\n","base.strided.variancech.ndarray":"\nbase.strided.variancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using a one-pass trial mean\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.variancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancech, base.strided.nanvariancech, base.strided.stdevch, base.strided.variance","base.strided.variancepn":"\nbase.strided.variancepn( N, correction, x, stride )\n    Computes the variance of a strided array using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancepn( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.variancepn( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.variancepn( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.variancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using a two-pass algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.variancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancepn, base.strided.nanvariancepn, base.strided.stdevpn, base.strided.variance\n","base.strided.variancepn.ndarray":"\nbase.strided.variancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using a two-pass algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.variancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancepn, base.strided.nanvariancepn, base.strided.stdevpn, base.strided.variance","base.strided.variancetk":"\nbase.strided.variancetk( N, correction, x, stride )\n    Computes the variance of a strided array using a one-pass textbook\n    algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancetk( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.variancetk( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.variancetk( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.variancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using a one-pass textbook algorithm\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.variancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancetk, base.strided.nanvariancetk, base.strided.stdevtk, base.strided.variance\n","base.strided.variancetk.ndarray":"\nbase.strided.variancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using a one-pass textbook algorithm\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.variancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancetk, base.strided.nanvariancetk, base.strided.stdevtk, base.strided.variance","base.strided.variancewd":"\nbase.strided.variancewd( N, correction, x, stride )\n    Computes the variance of a strided array using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancewd( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.variancewd( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.variancewd( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.variancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using Welford's algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.variancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancewd, base.strided.nanvariancewd, base.strided.stdevwd, base.strided.variance\n","base.strided.variancewd.ndarray":"\nbase.strided.variancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using Welford's algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.variancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancewd, base.strided.nanvariancewd, base.strided.stdevwd, base.strided.variance","base.strided.varianceyc":"\nbase.strided.varianceyc( N, correction, x, stride )\n    Computes the variance of a strided array using a one-pass algorithm proposed\n    by Youngs and Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.varianceyc( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.varianceyc( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.varianceyc( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.varianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using a one-pass algorithm proposed\n    by Youngs and Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.varianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.varianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvarianceyc, base.strided.nanvarianceyc, base.strided.stdevyc, base.strided.variance\n","base.strided.varianceyc.ndarray":"\nbase.strided.varianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using a one-pass algorithm proposed\n    by Youngs and Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.varianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.varianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvarianceyc, base.strided.nanvarianceyc, base.strided.stdevyc, base.strided.variance","base.strided.zmap":"\nbase.strided.zmap( N, x, strideX, y, strideY, fcn )\n    Applies a unary function to a double-precision complex floating-point\n    strided input array and assigns results to a double-precision complex\n    floating-point strided output array.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex128Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Complex128Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Complex128Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n    > var x = new Complex128Array( xbuf );\n    > var y = new Complex128Array( x.length );\n    > base.strided.zmap( x.length, x, 1, y, 1, base.cidentity );\n    > var v = y.get( 0 )\n    <Complex128>\n    > var re = real( v )\n    1.0\n    > var im = imag( v )\n    2.0\n\n    // Using `N` and stride parameters:\n    > y = new Complex128Array( x.length );\n    > base.strided.zmap( 2, x, 2, y, -1, base.cidentity );\n    > v = y.get( 0 )\n    <Complex128>\n    > re = real( v )\n    5.0\n    > im = imag( v )\n    6.0\n\n    // Using view offsets:\n    > var x0 = new Complex128Array( xbuf );\n    > var y0 = new Complex128Array( x0.length );\n    > var x1 = new Complex128Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Complex128Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.zmap( 2, x1, -2, y1, 1, base.cidentity );\n    > v = y1.get( 0 )\n    <Complex128>\n    > re = real( v )\n    7.0\n    > im = imag( v )\n    8.0\n\n\nbase.strided.zmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n    Applies a unary function to a double-precision complex floating-point\n    strided input array and assigns results to a double-precision complex\n    floating-point strided output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex128Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Complex128Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Complex128Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n    > var x = new Complex128Array( xbuf );\n    > var y = new Complex128Array( x.length );\n    > base.strided.zmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentity );\n    > var v = y.get( 0 )\n    <Complex128>\n    > var re = real( v )\n    1.0\n    > var im = imag( v )\n    2.0\n\n    // Advanced indexing:\n    > x = new Complex128Array( xbuf );\n    > y = new Complex128Array( x.length );\n    > base.strided.zmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentity );\n    > v = y.get( y.length-1 )\n    <Complex128>\n    > re = real( v )\n    3.0\n    > im = imag( v )\n    4.0\n\n    See Also\n    --------\n    base.strided.cmap, base.strided.unary\n","base.strided.zmap.ndarray":"\nbase.strided.zmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n    Applies a unary function to a double-precision complex floating-point\n    strided input array and assigns results to a double-precision complex\n    floating-point strided output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex128Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Complex128Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Complex128Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n    > var x = new Complex128Array( xbuf );\n    > var y = new Complex128Array( x.length );\n    > base.strided.zmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentity );\n    > var v = y.get( 0 )\n    <Complex128>\n    > var re = real( v )\n    1.0\n    > var im = imag( v )\n    2.0\n\n    // Advanced indexing:\n    > x = new Complex128Array( xbuf );\n    > y = new Complex128Array( x.length );\n    > base.strided.zmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentity );\n    > v = y.get( y.length-1 )\n    <Complex128>\n    > re = real( v )\n    3.0\n    > im = imag( v )\n    4.0\n\n    See Also\n    --------\n    base.strided.cmap, base.strided.unary","base.str2multislice":"\nbase.str2multislice( str )\n    Parses a string-serialized MultiSlice object.\n\n    The function returns `null` if provided an invalid string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    s: MultiSlice|null\n        MultiSlice instance (or null).\n\n    Examples\n    --------\n    > var s = new base.str2multislice( 'MultiSlice(null,null,null)' );\n    > s.data\n    [ null, null, null ]\n    > s = new base.str2multislice( 'MultiSlice(10,Slice(0,10,1),null)' );\n    > s.data\n    [ 10, <Slice>, null ]\n\n    See Also\n    --------\n    base.str2slice\n","base.str2slice":"\nbase.str2slice( str )\n    Parses a string-serialized Slice object.\n\n    The function returns `null` if provided an invalid string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    s: Slice|null\n        Slice instance (or null).\n\n    Examples\n    --------\n    > var s = new base.str2slice( 'Slice(1,10,1)' );\n    > s.start\n    1\n    > s.stop\n    10\n    > s.step\n    1\n    > s = new base.str2slice( 'Slice(2,5,2)' );\n    > s.start\n    2\n    > s.stop\n    5\n    > s.step\n    2\n\n    See Also\n    --------\n    base.str2multislice\n","base.sub":"\nbase.sub( x, y )\n    Subtracts two double-precision floating-point numbers `x` and `y`.\n\n    Parameters\n    ----------\n    x: number\n        First input value.\n\n    y: number\n        Second input value.\n\n    Returns\n    -------\n    z: number\n        Result.\n\n    Examples\n    --------\n    > var v = base.sub( -1.0, 5.0 )\n    -6.0\n    > v = base.sub( 2.0, 5.0 )\n    -3.0\n    > v = base.sub( 0.0, 5.0 )\n    -5.0\n    > v = base.sub( -0.0, 0.0 )\n    -0.0\n    > v = base.sub( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.add, base.div, base.mul\n","base.subf":"\nbase.subf( x, y )\n    Subtracts two single-precision floating-point numbers `x` and `y`.\n\n    Parameters\n    ----------\n    x: number\n        First input value.\n\n    y: number\n        Second input value.\n\n    Returns\n    -------\n    z: number\n        Result.\n\n    Examples\n    --------\n    > var v = base.subf( -1.0, 5.0 )\n    -6.0\n    > v = base.subf( 2.0, 5.0 )\n    -3.0\n    > v = base.subf( 0.0, 5.0 )\n    -5.0\n    > v = base.subf( -0.0, 0.0 )\n    -0.0\n    > v = base.subf( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.addf, base.divf, base.mulf, base.sub\n","base.sumSeries":"\nbase.sumSeries( generator[, options] )\n    Sum the elements of the series given by the supplied function.\n\n    Parameters\n    ----------\n    generator: Function\n        Series function.\n\n    options: Object (optional)\n        Options.\n\n    options.maxTerms: integer (optional)\n        Maximum number of terms to be added. Default: `1000000`.\n\n    options.tolerance: number (optional)\n        Further terms are only added as long as the next term is greater than\n        the current term times the tolerance. Default: `2.22e-16`.\n\n    options.initialValue: number (optional)\n        Initial value of the resulting sum. Default: `0`.\n\n    Returns\n    -------\n    out: number\n        Sum of series terms.\n\n    Examples\n    --------\n    // Using an ES6 generator function:\n    > function* geometricSeriesGenerator( x ) {\n    ...     var exponent = 0;\n    ...     while ( true ) {\n    ...         yield Math.pow( x, exponent );\n    ...         exponent += 1;\n    ...     }\n    ... };\n    > var gen = geometricSeriesGenerator( 0.9 );\n    > var out = base.sumSeries( gen )\n    10\n\n    // Using a closure:\n    > function geometricSeriesClosure( x ) {\n    ...     var exponent = -1;\n    ...     return function() {\n    ...         exponent += 1;\n    ...         return Math.pow( x, exponent );\n    ...     };\n    ... };\n    > gen = geometricSeriesClosure( 0.9 );\n    > out = base.sumSeries( gen )\n    10\n\n    // Setting an initial value for the sum:\n    > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'initialValue': 1 } )\n    3\n    // Changing the maximum number of terms to be summed:\n    > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'maxTerms': 10 } )\n    ~1.998 // Infinite sum is 2\n\n    // Adjusting the used tolerance:\n    > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'tolerance': 1e-3 } )\n    ~1.998\n\n","base.tan":"\nbase.tan( x )\n    Computes the tangent of a number.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Tangent.\n\n    Examples\n    --------\n    > var y = base.tan( 0.0 )\n    ~0.0\n    > y = base.tan( -PI/4.0 )\n    ~-1.0\n    > y = base.tan( PI/4.0 )\n    ~1.0\n    > y = base.tan( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cos, base.sin\n","base.tand":"\nbase.tand( x )\n    Computes the tangent of an angle measured in degrees.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in degrees).\n\n    Returns\n    -------\n    y: number\n        Tangent.\n\n    Examples\n    --------\n    > var y = base.tand( 0.0 )\n    0.0\n    > y = base.tand( 90.0 )\n    Infinity\n    > y = base.tand( 60.0 )\n    ~1.73\n    > y = base.tand( NaN )\n    NaN\n\n    See Also\n    --------\n    base.tan, base.cosd\n","base.tanh":"\nbase.tanh( x )\n    Computes the hyperbolic tangent of a double-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Hyperbolic tangent.\n\n    Examples\n    --------\n    > var y = base.tanh( 0.0 )\n    0.0\n    > var y = base.tanh( -0.0 )\n    -0.0\n    > y = base.tanh( 2.0 )\n    ~0.964\n    > y = base.tanh( -2.0 )\n    ~-0.964\n    > y = base.tanh( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cosh, base.sinh, base.tan\n","base.toBinaryString":"\nbase.toBinaryString( x )\n    Returns a string giving the literal bit representation of a double-precision\n    floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    Returns\n    -------\n    bstr: string\n        Bit representation.\n\n    Examples\n    --------\n    > var str = base.toBinaryString( 4.0 )\n    '0100000000010000000000000000000000000000000000000000000000000000'\n    > str = base.toBinaryString( PI )\n    '0100000000001001001000011111101101010100010001000010110100011000'\n    > str = base.toBinaryString( -1.0e308 )\n    '1111111111100001110011001111001110000101111010111100100010100000'\n    > str = base.toBinaryString( -3.14e-320 )\n    '1000000000000000000000000000000000000000000000000001100011010011'\n    > str = base.toBinaryString( 5.0e-324 )\n    '0000000000000000000000000000000000000000000000000000000000000001'\n    > str = base.toBinaryString( 0.0 )\n    '0000000000000000000000000000000000000000000000000000000000000000'\n    > str = base.toBinaryString( -0.0 )\n    '1000000000000000000000000000000000000000000000000000000000000000'\n    > str = base.toBinaryString( NaN )\n    '0111111111111000000000000000000000000000000000000000000000000000'\n    > str = base.toBinaryString( PINF )\n    '0111111111110000000000000000000000000000000000000000000000000000'\n    > str = base.toBinaryString( NINF )\n    '1111111111110000000000000000000000000000000000000000000000000000'\n\n    See Also\n    --------\n    base.fromBinaryString, base.toBinaryStringf\n","base.toBinaryStringf":"\nbase.toBinaryStringf( x )\n    Returns a string giving the literal bit representation of a single-precision\n    floating-point number.\n\n    Parameters\n    ----------\n    x: float\n        Single-precision floating-point number.\n\n    Returns\n    -------\n    str: string\n        Bit representation.\n\n    Examples\n    --------\n    > var str = base.toBinaryStringf( base.float64ToFloat32( 4.0 ) )\n    '01000000100000000000000000000000'\n    > str = base.toBinaryStringf( base.float64ToFloat32( PI ) )\n    '01000000010010010000111111011011'\n    > str = base.toBinaryStringf( base.float64ToFloat32( -1.0e38 ) )\n    '11111110100101100111011010011001'\n    > str = base.toBinaryStringf( base.float64ToFloat32( -3.14e-39 ) )\n    '10000000001000100011000100001011'\n    > str = base.toBinaryStringf( base.float64ToFloat32( 1.4e-45 ) )\n    '00000000000000000000000000000001'\n    > str = base.toBinaryStringf( 0.0 )\n    '00000000000000000000000000000000'\n    > str = base.toBinaryStringf( -0.0 )\n    '10000000000000000000000000000000'\n    > str = base.toBinaryStringf( NaN )\n    '01111111110000000000000000000000'\n    > str = base.toBinaryStringf( FLOAT32_PINF )\n    '01111111100000000000000000000000'\n    > str = base.toBinaryStringf( FLOAT32_NINF )\n    '11111111100000000000000000000000'\n\n    See Also\n    --------\n    base.fromBinaryStringf, base.toBinaryString\n","base.toBinaryStringUint8":"\nbase.toBinaryStringUint8( x )\n    Returns a string giving the literal bit representation of an unsigned 8-bit\n    integer.\n\n    Except for typed arrays, JavaScript does not provide native user support for\n    unsigned 8-bit integers. According to the ECMAScript standard, `number`\n    values correspond to double-precision floating-point numbers. While this\n    function is intended for unsigned 8-bit integers, the function will accept\n    floating-point values and represent the values as if they are unsigned 8-bit\n    integers. Accordingly, care should be taken to ensure that only nonnegative\n    integer values less than `256` (`2^8`) are provided.\n\n    Parameters\n    ----------\n    x: integer\n        Input value.\n\n    Returns\n    -------\n    str: string\n        Bit representation.\n\n    Examples\n    --------\n    > var a = new Uint8Array( [ 1, 4, 9 ] );\n    > var str = base.toBinaryStringUint8( a[ 0 ] )\n    '00000001'\n    > str = base.toBinaryStringUint8( a[ 1 ] )\n    '00000100'\n    > str = base.toBinaryStringUint8( a[ 2 ] )\n    '00001001'\n\n    See Also\n    --------\n    base.toBinaryString\n","base.toBinaryStringUint16":"\nbase.toBinaryStringUint16( x )\n    Returns a string giving the literal bit representation of an unsigned 16-bit\n    integer.\n\n    Except for typed arrays, JavaScript does not provide native user support for\n    unsigned 16-bit integers. According to the ECMAScript standard, `number`\n    values correspond to double-precision floating-point numbers. While this\n    function is intended for unsigned 16-bit integers, the function will accept\n    floating-point values and represent the values as if they are unsigned\n    16-bit integers. Accordingly, care should be taken to ensure that only\n    nonnegative integer values less than `65536` (`2^16`) are provided.\n\n    Parameters\n    ----------\n    x: integer\n        Input value.\n\n    Returns\n    -------\n    str: string\n        Bit representation.\n\n    Examples\n    --------\n    > var a = new Uint16Array( [ 1, 4, 9 ] );\n    > var str = base.toBinaryStringUint16( a[ 0 ] )\n    '0000000000000001'\n    > str = base.toBinaryStringUint16( a[ 1 ] )\n    '0000000000000100'\n    > str = base.toBinaryStringUint16( a[ 2 ] )\n    '0000000000001001'\n\n    See Also\n    --------\n    base.toBinaryString\n","base.toBinaryStringUint32":"\nbase.toBinaryStringUint32( x )\n    Returns a string giving the literal bit representation of an unsigned 32-bit\n    integer.\n\n    Except for typed arrays, JavaScript does not provide native user support for\n    unsigned 32-bit integers. According to the ECMAScript standard, `number`\n    values correspond to double-precision floating-point numbers. While this\n    function is intended for unsigned 32-bit integers, the function will accept\n    floating-point values and represent the values as if they are unsigned\n    32-bit integers. Accordingly, care should be taken to ensure that only\n    nonnegative integer values less than `4,294,967,296` (`2^32`) are provided.\n\n    Parameters\n    ----------\n    x: integer\n        Input value.\n\n    Returns\n    -------\n    str: string\n        Bit representation.\n\n    Examples\n    --------\n    > var a = new Uint32Array( [ 1, 4, 9 ] );\n    > var str = base.toBinaryStringUint32( a[ 0 ] )\n    '00000000000000000000000000000001'\n    > str = base.toBinaryStringUint32( a[ 1 ] )\n    '00000000000000000000000000000100'\n    > str = base.toBinaryStringUint32( a[ 2 ] )\n    '00000000000000000000000000001001'\n\n    See Also\n    --------\n    base.toBinaryString\n","base.toWordf":"\nbase.toWordf( x )\n    Returns an unsigned 32-bit integer corresponding to the IEEE 754 binary\n    representation of a single-precision floating-point number.\n\n    Parameters\n    ----------\n    x: float\n        Single-precision floating-point number.\n\n    Returns\n    -------\n    out: integer\n        Unsigned 32-bit integer.\n\n    Examples\n    --------\n    > var f32 = base.float64ToFloat32( 1.337 )\n    1.3370000123977661\n    > var w = base.toWordf( f32 )\n    1068180177\n\n    See Also\n    --------\n    base.fromWordf, base.toWords\n","base.toWords":"\nbase.toWords( x )\n    Splits a double-precision floating-point number into a higher order word\n    (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n\n    When provided a destination object, the function returns an array with two\n    elements: a higher order word and a lower order word, respectively. The\n    lower order word contains the less significant bits, while the higher order\n    word contains the more significant bits and includes the exponent and sign.\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    Returns\n    -------\n    out: Array<integer>\n        Higher and lower order words.\n\n    Examples\n    --------\n    > var w = base.toWords( 3.14e201 )\n    [ 1774486211, 2479577218 ]\n\n\nbase.toWords.assign( x, out, stride, offset )\n    Splits a double-precision floating-point number into a higher order word\n    (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer)\n    and assigns results to a provided output array.\n\n    When provided a destination object, the function returns an array with two\n    elements: a higher order word and a lower order word, respectively. The\n    lower order word contains the less significant bits, while the higher order\n    word contains the more significant bits and includes the exponent and sign.\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Higher and lower order words.\n\n    Examples\n    --------\n    > var out = new Uint32Array( 2 );\n    > var w = base.toWords.assign( 3.14e201, out, 1, 0 )\n    <Uint32Array>[ 1774486211, 2479577218 ]\n    > var bool = ( w === out )\n    true\n\n    See Also\n    --------\n    base.fromWords, base.toWordf","base.toWords.assign":"\nbase.toWords.assign( x, out, stride, offset )\n    Splits a double-precision floating-point number into a higher order word\n    (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer)\n    and assigns results to a provided output array.\n\n    When provided a destination object, the function returns an array with two\n    elements: a higher order word and a lower order word, respectively. The\n    lower order word contains the less significant bits, while the higher order\n    word contains the more significant bits and includes the exponent and sign.\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Higher and lower order words.\n\n    Examples\n    --------\n    > var out = new Uint32Array( 2 );\n    > var w = base.toWords.assign( 3.14e201, out, 1, 0 )\n    <Uint32Array>[ 1774486211, 2479577218 ]\n    > var bool = ( w === out )\n    true\n\n    See Also\n    --------\n    base.fromWords, base.toWordf","base.transpose":"\nbase.transpose( x )\n    Transposes a matrix (or a stack of matrices).\n\n    The returned ndarray is a *view* of the input ndarray. Accordingly, writing\n    to the original ndarray will mutate the returned ndarray and vice versa.\n    While powerful, this can lead to subtle bugs. In general, one should handle\n    the returned ndarray as read-only.\n\n    If provided an ndarray with fewer than two dimensions, the function raises\n    an exception.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n    <ndarray>\n    > var sh = x.shape\n    [ 2, 3 ]\n    > var y = base.transpose( x )\n    <ndarray>\n    > sh = y.shape\n    [ 3, 2 ]\n    > var bool = ( x.data === y.data )\n    true\n    > bool = ( x.get( 0, 1 ) === y.get( 1, 0 ) )\n    true\n\n    See Also\n    --------\n    ndarray\n","base.tribonacci":"\nbase.tribonacci( n )\n    Computes the nth Tribonacci number.\n\n    Tribonacci numbers follow the recurrence relation\n\n      F_n = F_{n-1} + F_{n-2} + F_{n-3}\n\n    with seed values F_0 = 0, F_1 = 0, and F_2 = 1.\n\n    If `n` is greater than `63`, the function returns `NaN`, as larger\n    Tribonacci numbers cannot be accurately represented due to limitations of\n    double-precision floating-point format.\n\n    If not provided a nonnegative integer value, the function returns `NaN`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Input value.\n\n    Returns\n    -------\n    y: integer\n        Tribonacci number.\n\n    Examples\n    --------\n    > var y = base.tribonacci( 0 )\n    0\n    > y = base.tribonacci( 1 )\n    0\n    > y = base.tribonacci( 2 )\n    1\n    > y = base.tribonacci( 3 )\n    1\n    > y = base.tribonacci( 4 )\n    2\n    > y = base.tribonacci( 64 )\n    NaN\n    > y = base.tribonacci( NaN )\n    NaN\n\n    See Also\n    --------\n    base.fibonacci\n","base.trigamma":"\nbase.trigamma( x )\n    Evaluates the trigamma function.\n\n    If `x` is `0` or a negative `integer`, the `function` returns `NaN`.\n\n    If provided `NaN`, the `function` returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.trigamma( -2.5 )\n    ~9.539\n    > y = base.trigamma( 1.0 )\n    ~1.645\n    > y = base.trigamma( 10.0 )\n    ~0.105\n    > y = base.trigamma( NaN )\n    NaN\n    > y = base.trigamma( -1.0 )\n    NaN\n\n    See Also\n    --------\n    base.digamma, base.gamma\n","base.trim":"\nbase.trim( str )\n    Trims whitespace from the beginning and end of a `string`.\n\n    \"Whitespace\" is defined as the following characters:\n\n    - \\f\n    - \\n\n    - \\r\n    - \\t\n    - \\v\n    - \\u0020\n    - \\u00a0\n    - \\u1680\n    - \\u2000-\\u200a\n    - \\u2028\n    - \\u2029\n    - \\u202f\n    - \\u205f\n    - \\u3000\n    - \\ufeff\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Trimmed string.\n\n    Examples\n    --------\n    > var out = base.trim( ' \\t\\t\\n  Beep \\r\\n\\t  ' )\n    'Beep'\n\n    See Also\n    --------\n    base.leftTrim, base.rightTrim\n","base.trunc":"\nbase.trunc( x )\n    Rounds a double-precision floating-point number toward zero.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.trunc( 3.14 )\n    3.0\n    > y = base.trunc( -4.2 )\n    -4.0\n    > y = base.trunc( -4.6 )\n    -4.0\n    > y = base.trunc( 9.5 )\n    9.0\n    > y = base.trunc( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceil, base.floor, base.round\n","base.trunc2":"\nbase.trunc2( x )\n    Rounds a numeric value to the nearest power of two toward zero.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.trunc2( 3.14 )\n    2.0\n    > y = base.trunc2( -4.2 )\n    -4.0\n    > y = base.trunc2( -4.6 )\n    -4.0\n    > y = base.trunc2( 9.5 )\n    8.0\n    > y = base.trunc2( 13.0 )\n    8.0\n    > y = base.trunc2( -13.0 )\n    -8.0\n    > y = base.trunc2( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceil2, base.floor2, base.round2, base.trunc, base.trunc10\n","base.trunc10":"\nbase.trunc10( x )\n    Rounds a numeric value to the nearest power of ten toward zero.\n\n    The function may not return accurate results for subnormals due to a general\n    loss in precision.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.trunc10( 3.14 )\n    1.0\n    > y = base.trunc10( -4.2 )\n    -1.0\n    > y = base.trunc10( -4.6 )\n    -1.0\n    > y = base.trunc10( 9.5 )\n    1.0\n    > y = base.trunc10( 13.0 )\n    10.0\n    > y = base.trunc10( -13.0 )\n    -10.0\n    > y = base.trunc10( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceil10, base.floor10, base.round10, base.trunc, base.trunc2\n","base.truncateMiddle":"\nbase.truncateMiddle( str, len, seq )\n    Truncates the middle UTF-16 code units of a string to return a string\n    having a specified length.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    len: integer\n        Output string length.\n\n    seq: string\n        Custom replacement sequence.\n\n    Returns\n    -------\n    out: string\n        Truncated string.\n\n    Examples\n    --------\n    > var str = 'beep boop';\n    > var out = base.truncateMiddle( str, 5, '...' )\n    'b...p'\n    > out = base.truncateMiddle( str, 5, '|' )\n    'be|op'\n","base.truncb":"\nbase.truncb( x, n, b )\n    Rounds a numeric value to the nearest multiple of `b^n` toward zero.\n\n    Due to floating-point rounding error, rounding may not be exact.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Integer power.\n\n    b: integer\n        Base.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    // Round to 4 decimal places:\n    > var y = base.truncb( 3.14159, -4, 10 )\n    3.1415\n\n    // If `n = 0` or `b = 1`, standard round behavior:\n    > y = base.truncb( 3.14159, 0, 2 )\n    3.0\n\n    // Round to nearest multiple of two toward zero:\n    > y = base.truncb( 5.0, 1, 2 )\n    4.0\n\n    See Also\n    --------\n    base.ceilb, base.floorb, base.roundb, base.trunc, base.truncn\n","base.truncf":"\nbase.truncf( x )\n    Rounds a single-precision floating-point number toward zero.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.truncf( 3.14 )\n    3.0\n    > y = base.truncf( -4.2 )\n    -4.0\n    > y = base.truncf( -4.6 )\n    -4.0\n    > y = base.truncf( 9.5 )\n    9.0\n    > y = base.truncf( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceilf, base.floorf, base.trunc\n","base.truncn":"\nbase.truncn( x, n )\n    Rounds a numeric value to the nearest multiple of `10^n` toward zero.\n\n    When operating on floating-point numbers in bases other than `2`, rounding\n    to specified digits can be inexact.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Integer power of 10.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    // Round to 4 decimal places:\n    > var y = base.truncn( 3.14159, -4 )\n    3.1415\n\n    // If `n = 0`, standard round behavior:\n    > y = base.truncn( 3.14159, 0 )\n    3.0\n\n    // Round to nearest thousand:\n    > y = base.truncn( 12368.0, 3 )\n    12000.0\n\n\n    See Also\n    --------\n    base.ceiln, base.floorn, base.roundn, base.trunc, base.truncb\n","base.truncsd":"\nbase.truncsd( x, n, b )\n    Rounds a numeric value to the nearest number toward zero with `n`\n    significant figures.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Number of significant figures. Must be greater than 0.\n\n    b: integer\n        Base. Must be greater than 0.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.truncsd( 3.14159, 5, 10 )\n    3.1415\n    > y = base.truncsd( 3.14159, 1, 10 )\n    3.0\n    > y = base.truncsd( 12368.0, 2, 10 )\n    12000.0\n    > y = base.truncsd( 0.0313, 2, 2 )\n    0.03125\n\n    See Also\n    --------\n    base.ceilsd, base.floorsd, base.roundsd, base.trunc\n","base.uint32ToInt32":"\nbase.uint32ToInt32( x )\n    Converts an unsigned 32-bit integer to a signed 32-bit integer.\n\n    Parameters\n    ----------\n    x: integer\n        Unsigned 32-bit integer.\n\n    Returns\n    -------\n    out: integer\n        Signed 32-bit integer.\n\n    Examples\n    --------\n    > var y = base.uint32ToInt32( base.float64ToUint32( 4294967295 ) )\n    -1\n    > y = base.uint32ToInt32( base.float64ToUint32( 3 ) )\n    3\n\n","base.umul":"\nbase.umul( a, b )\n    Performs C-like multiplication of two unsigned 32-bit integers.\n\n    Parameters\n    ----------\n    a: integer\n        Unsigned 32-bit integer.\n\n    b: integer\n        Unsigned 32-bit integer.\n\n    Returns\n    -------\n    out: integer\n        Product.\n\n    Examples\n    --------\n    > var v = base.umul( 10>>>0, 4>>>0 )\n    40\n\n    See Also\n    --------\n    base.imul\n","base.umuldw":"\nbase.umuldw( a, b )\n    Multiplies two unsigned 32-bit integers and returns an array of two unsigned\n    32-bit integers which represents the unsigned 64-bit integer product.\n\n    When computing the product of 32-bit integer values in double-precision\n    floating-point format (the default JavaScript numeric data type), computing\n    the double word product is necessary in order to avoid exceeding the maximum\n    safe double-precision floating-point integer value.\n\n    Parameters\n    ----------\n    a: integer\n        Unsigned 32-bit integer.\n\n    b: integer\n        Unsigned 32-bit integer.\n\n    Returns\n    -------\n    out: Array<number>\n        Double word product (in big endian order; i.e., the first element\n        corresponds to the most significant bits and the second element to the\n        least significant bits).\n\n    Examples\n    --------\n    > var v = base.umuldw( 1, 10 )\n    [ 0, 10 ]\n\n\nbase.umuldw.assign( a, b, out, stride, offset )\n    Multiplies two unsigned 32-bit integers and assigns results representing\n    the unsigned 64-bit integer product to a provided output array.\n\n    When computing the product of 32-bit integer values in double-precision\n    floating-point format (the default JavaScript numeric data type), computing\n    the double word product is necessary in order to avoid exceeding the maximum\n    safe double-precision floating-point integer value.\n\n    Parameters\n    ----------\n    a: integer\n        Unsigned 32-bit integer.\n\n    b: integer\n        Unsigned 32-bit integer.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Double word product (in big endian order; i.e., the first element\n        corresponds to the most significant bits and the second element to the\n        least significant bits).\n\n    Examples\n    --------\n    > var out = [ 0, 0 ];\n    > var v = base.umuldw.assign( 1, 10, out, 1, 0 )\n    [ 0, 10 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.imuldw, base.umul\n","base.umuldw.assign":"\nbase.umuldw.assign( a, b, out, stride, offset )\n    Multiplies two unsigned 32-bit integers and assigns results representing\n    the unsigned 64-bit integer product to a provided output array.\n\n    When computing the product of 32-bit integer values in double-precision\n    floating-point format (the default JavaScript numeric data type), computing\n    the double word product is necessary in order to avoid exceeding the maximum\n    safe double-precision floating-point integer value.\n\n    Parameters\n    ----------\n    a: integer\n        Unsigned 32-bit integer.\n\n    b: integer\n        Unsigned 32-bit integer.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Double word product (in big endian order; i.e., the first element\n        corresponds to the most significant bits and the second element to the\n        least significant bits).\n\n    Examples\n    --------\n    > var out = [ 0, 0 ];\n    > var v = base.umuldw.assign( 1, 10, out, 1, 0 )\n    [ 0, 10 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.imuldw, base.umul","base.uncapitalize":"\nbase.uncapitalize( str )\n    Lowercases the first character of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Uncapitalized string.\n\n    Examples\n    --------\n    > var out = base.uncapitalize( 'Beep' )\n    'beep'\n    > out = base.uncapitalize( 'bOOp' )\n    'bOOp'\n\n    See Also\n    --------\n    base.capitalize\n","base.uppercase":"\nbase.uppercase( str )\n    Converts a string to uppercase.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Uppercase string.\n\n    Examples\n    --------\n    > var out = base.uppercase( 'bEEp' )\n    'BEEP'\n\n    See Also\n    --------\n    base.lowercase\n","base.vercos":"\nbase.vercos( x )\n    Computes the versed cosine.\n\n    The versed cosine is defined as `1 + cos(x)`.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Versed cosine.\n\n    Examples\n    --------\n    > var y = base.vercos( 3.14 )\n    ~0.0\n    > y = base.vercos( -4.2 )\n    ~0.5097\n    > y = base.vercos( -4.6 )\n    ~0.8878\n    > y = base.vercos( 9.5 )\n    ~0.0028\n    > y = base.vercos( -0.0 )\n    2.0\n\n    See Also\n    --------\n    base.cos, base.versin\n","base.versin":"\nbase.versin( x )\n    Computes the versed sine.\n\n    The versed sine is defined as `1 - cos(x)`.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Versed sine.\n\n    Examples\n    --------\n    > var y = base.versin( 3.14 )\n    ~2.0\n    > y = base.versin( -4.2 )\n    ~1.490\n    > y = base.versin( -4.6 )\n    ~1.112\n    > y = base.versin( 9.5 )\n    ~1.997\n    > y = base.versin( -0.0 )\n    0.0\n\n    See Also\n    --------\n    base.cos, base.sin, base.vercos\n","base.wrap":"\nbase.wrap( v, min, max )\n    Wraps a value on the half-open interval `[min,max)`.\n\n    The function does not distinguish between positive and negative zero. Where\n    appropriate, the function returns positive zero.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    v: number\n        Value to wrap.\n\n    min: number\n        Minimum value.\n\n    max: number\n        Maximum value.\n\n    Returns\n    -------\n    y: number\n        Wrapped value.\n\n    Examples\n    --------\n    > var y = base.wrap( 3.14, 0.0, 5.0 )\n    3.14\n    > y = base.wrap( -3.14, 0.0, 5.0 )\n    ~1.86\n    > y = base.wrap( 3.14, 0.0, 3.0 )\n    ~0.14\n    > y = base.wrap( -0.0, 0.0, 5.0 )\n    0.0\n    > y = base.wrap( 0.0, -3.14, -0.0 )\n    -3.14\n    > y = base.wrap( NaN, 0.0, 5.0 )\n    NaN\n\n    See Also\n    --------\n    base.clamp\n","base.xlog1py":"\nbase.xlog1py( x, y )\n    Computes `x * ln(y+1)` so that the result is `0` if `x = 0`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    y: number\n        Input value.\n\n    Returns\n    -------\n    out: number\n        Function value.\n\n    Examples\n    --------\n    > var out = base.xlog1py( 3.0, 2.0 )\n    ~3.296\n    > out = base.xlog1py( 1.5, 5.9 )\n    ~2.897\n    > out = base.xlog1py( 0.9, 1.0 )\n    ~0.624\n    > out = base.xlog1py( 1.0, 0.0 )\n    0.0\n    > out = base.xlog1py( 0.0, -2.0 )\n    0.0\n    > out = base.xlog1py( 1.5, NaN )\n    NaN\n    > out = base.xlog1py( 0.0, NaN )\n    NaN\n    > out = base.xlog1py( NaN, 2.3 )\n    NaN\n\n    See Also\n    --------\n    base.log1p, base.xlogy\n","base.xlogy":"\nbase.xlogy( x, y )\n    Computes `x * ln(y)` so that the result is `0` if `x = 0`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    y: number\n        Input value.\n\n    Returns\n    -------\n    out: number\n        Function value.\n\n    Examples\n    --------\n    > var out = base.xlogy( 3.0, 2.0 )\n    ~2.079\n    > out = base.xlogy( 1.5, 5.9 )\n    ~2.662\n    > out = base.xlogy( 0.9, 1.0 )\n    0.0\n    > out = base.xlogy( 0.0, -2.0 )\n    0.0\n    > out = base.xlogy( 1.5, NaN )\n    NaN\n    > out = base.xlogy( 0.0, NaN )\n    NaN\n    > out = base.xlogy( NaN, 2.3 )\n    NaN\n\n    See Also\n    --------\n    base.ln, base.xlog1py\n","base.zeta":"\nbase.zeta( s )\n    Evaluates the Riemann zeta function as a function of a real variable `s`.\n\n    Parameters\n    ----------\n    s: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.zeta( 1.1 )\n    ~10.584\n    > y = base.zeta( -4.0 )\n    0.0\n    > y = base.zeta( 70.0 )\n    1.0\n    > y = base.zeta( 0.5 )\n    ~-1.46\n    > y = base.zeta( NaN )\n    NaN\n\n    // Evaluate at a pole:\n    > y = base.zeta( 1.0 )\n    NaN\n\n","BERNDT_CPS_WAGES_1985":"\nBERNDT_CPS_WAGES_1985()\n    Returns a random sample of 534 workers from the Current Population Survey\n    (CPS) from 1985, including their wages and and other characteristics.\n\n    Each array element has the following eleven fields:\n\n    - education: number of years of education.\n    - south: indicator variable for southern region (1 if a person lives in the\n    South; 0 if a person does not live in the South).\n    - gender: gender of the person.\n    - experience: number of years of work experience.\n    - union: indicator variable for union membership (1 if union member; 0 if\n    not a union member).\n    - wage: wage (in dollars per hour).\n    - age: age (in years).\n    - race: ethnicity/race (white, hispanic, and other).\n    - occupation: occupational category (management, sales, clerical, service,\n    professional, and other).\n    - sector: sector (other, manufacturing, or construction).\n    - married: marital status (0 if unmarried; 1 if married).\n\n    Based on residual plots, wages were log-transformed to stabilize the\n    variance.\n\n    Returns\n    -------\n    out: Array<Object>\n        CPS data.\n\n    Examples\n    --------\n    > var data = BERNDT_CPS_WAGES_1985()\n    [ {...}, {...}, ... ]\n\n    References\n    ----------\n    - Berndt, Ernst R. 1991. _The Practice of Econometrics_. Addison Wesley\n    Longman Publishing Co.\n\n","bifurcate":"\nbifurcate( collection, [options,] filter )\n    Splits values into two groups.\n\n    If an element in `filter` is truthy, then the corresponding element in the\n    input collection belongs to the first group; otherwise, the collection\n    element belongs to the second group.\n\n    If provided an empty collection, the function returns an empty array.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection to group. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Options.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `indices`, indices are returned; if\n        `*`, both indices and values are returned. Default: 'values'.\n\n    filter: Array|TypedArray|Object\n        A collection indicating which group an element in the input collection\n        belongs to. If an element in `filter` is truthy, the corresponding\n        element in `collection` belongs to the first group; otherwise, the\n        collection element belongs to the second group. If provided an object,\n        the object must be array-like (excluding strings and functions).\n\n    Returns\n    -------\n    out: Array<Array>|Array\n        Group results.\n\n    Examples\n    --------\n    > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n    > var f = [ true, true, false, true ];\n    > var out = bifurcate( collection, f )\n    [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n    > f = [ 1, 1, 0, 1 ];\n    > out = bifurcate( collection, f )\n    [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n    // Output group results as indices:\n    > f = [ true, true, false, true ];\n    > var opts = { 'returns': 'indices' };\n    > out = bifurcate( collection, opts, f )\n    [ [ 0, 1, 3 ], [ 2 ] ]\n\n    // Output group results as index-element pairs:\n    > opts = { 'returns': '*' };\n    > out = bifurcate( collection, opts, f )\n    [ [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], [ [2, 'foo'] ] ]\n\n    See Also\n    --------\n    bifurcateBy, bifurcateOwn, group\n","bifurcateBy":"\nbifurcateBy( collection, [options,] predicate )\n    Splits values into two groups according to a predicate function.\n\n    When invoked, the predicate function is provided two arguments:\n\n    - value: collection value.\n    - index: collection index.\n\n    If a predicate function returns a truthy value, a collection value is\n    placed in the first group; otherwise, a collection value is placed in the\n    second group.\n\n    If provided an empty collection, the function returns an empty array.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection to group. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Options.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `indices`, indices are returned; if\n        `*`, both indices and values are returned. Default: 'values'.\n\n    predicate: Function\n        Predicate function indicating which group an element in the input\n        collection belongs to.\n\n    Returns\n    -------\n    out: Array<Array>|Array\n        Group results.\n\n    Examples\n    --------\n    > function predicate( v ) { return v[ 0 ] === 'b'; };\n    > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n    > var out = bifurcateBy( collection, predicate )\n    [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n    // Output group results as indices:\n    > var opts = { 'returns': 'indices' };\n    > out = bifurcateBy( collection, opts, predicate )\n    [ [ 0, 1, 3 ], [ 2 ] ]\n\n    // Output group results as index-value pairs:\n    > opts = { 'returns': '*' };\n    > out = bifurcateBy( collection, opts, predicate )\n    [ [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], [ [2, 'foo' ] ] ]\n\n    See Also\n    --------\n    bifurcate, groupBy\n","bifurcateByAsync":"\nbifurcateByAsync( collection, [options,] predicate, done )\n    Splits values into two groups according to a predicate function.\n\n    When invoked, the predicate function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If the\n    predicate function accepts two arguments, the predicate function is\n    provided:\n\n    - value\n    - next\n\n    If the predicate function accepts three arguments, the predicate function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other predicate function signature, the predicate function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - group: value group.\n\n    If an predicate function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    If a predicate function calls the `next` callback with a truthy group value,\n    a collection value is placed in the first group; otherwise, a collection\n    value is placed in the second group.\n\n    If provided an empty collection, the function calls the `done` callback with\n    an empty array as the second argument.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `indices`, indices are returned; if\n        `*`, both indices and values are returned. Default: 'values'.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        Predicate function indicating which group an element in the input\n        collection belongs to.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function predicate( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > bifurcateByAsync( arr, predicate, done )\n    1000\n    2500\n    3000\n    [ [ 1000, 3000 ], [ 2500 ] ]\n\n    // Output group results as indices:\n    > var opts = { 'returns': 'indices' };\n    > bifurcateByAsync( arr, opts, predicate, done )\n    1000\n    2500\n    3000\n    [ [ 2, 0 ], [ 1 ] ]\n\n    // Output group results as index-value pairs:\n    > opts = { 'returns': '*' };\n    > bifurcateByAsync( arr, opts, predicate, done )\n    1000\n    2500\n    3000\n    [ [ [ 2, 1000 ], [ 0, 3000 ] ], [ [ 1, 2500 ] ] ]\n\n    // Limit number of concurrent invocations:\n    > function predicate( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 3000, 2500, 1000 ];\n    > bifurcateByAsync( arr, opts, predicate, done )\n    2500\n    3000\n    1000\n    [ [ 3000, 1000 ], [ 2500 ] ]\n\n    // Process sequentially:\n    > function predicate( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 3000, 2500, 1000 ];\n    > bifurcateByAsync( arr, opts, predicate, done )\n    3000\n    2500\n    1000\n    [ [ 3000, 1000 ], [ 2500 ] ]\n\n\nbifurcateByAsync.factory( [options,] predicate )\n    Returns a function which splits values into two groups according to an\n    predicate function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `indices`, indices are returned; if\n        `*`, both indices and values are returned. Default: 'values'.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        Predicate function indicating which group an element in the input\n        collection belongs to.\n\n    Returns\n    -------\n    out: Function\n        A function which splits values into two groups.\n\n    Examples\n    --------\n    > function predicate( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = bifurcateByAsync.factory( opts, predicate );\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    [ [ 3000, 1000 ], [ 2500 ] ]\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    [ [ 2000, 1000 ], [ 1500 ] ]\n\n    See Also\n    --------\n    bifurcateBy, groupByAsync\n","bifurcateByAsync.factory":"\nbifurcateByAsync.factory( [options,] predicate )\n    Returns a function which splits values into two groups according to an\n    predicate function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `indices`, indices are returned; if\n        `*`, both indices and values are returned. Default: 'values'.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        Predicate function indicating which group an element in the input\n        collection belongs to.\n\n    Returns\n    -------\n    out: Function\n        A function which splits values into two groups.\n\n    Examples\n    --------\n    > function predicate( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = bifurcateByAsync.factory( opts, predicate );\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    [ [ 3000, 1000 ], [ 2500 ] ]\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    [ [ 2000, 1000 ], [ 1500 ] ]\n\n    See Also\n    --------\n    bifurcateBy, groupByAsync","bifurcateIn":"\nbifurcateIn( obj, [options,] predicate )\n    Splits values into two groups according to a predicate function.\n\n    When invoked, the predicate function is provided two arguments:\n\n    - value: object value.\n    - key: object key.\n\n    If a predicate function returns a truthy value, a value is placed in the\n    first group; otherwise, a value is placed in the second group.\n\n    If provided an empty object with no prototype, the function returns an empty\n    array.\n\n    The function iterates over an object's own and inherited properties.\n\n    Key iteration order is *not* guaranteed, and, thus, result order is *not*\n    guaranteed.\n\n    Parameters\n    ----------\n    obj: Object|Array|TypedArray\n        Input object to group.\n\n    options: Object (optional)\n        Options.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `keys`, keys are returned; if `*`,\n        both keys and values are returned. Default: 'values'.\n\n    predicate: Function\n        Predicate function indicating which group a value in the input object\n        belongs to.\n\n    Returns\n    -------\n    out: Array<Array>|Array\n        Group results.\n\n    Examples\n    --------\n    > function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\n    > Foo.prototype = Object.create( null );\n    > Foo.prototype.c = 'foo';\n    > Foo.prototype.d = 'bar';\n    > var obj = new Foo();\n    > function predicate( v ) { return v[ 0 ] === 'b'; };\n    > var out = bifurcateIn( obj, predicate )\n    [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n    // Output group results as keys:\n    > var opts = { 'returns': 'keys' };\n    > out = bifurcateIn( obj, opts, predicate )\n    [ [ 'a', 'b', 'd' ], [ 'c' ] ]\n\n    // Output group results as key-value pairs:\n    > opts = { 'returns': '*' };\n    > out = bifurcateIn( obj, opts, predicate )\n    [ [ ['a', 'beep'], ['b', 'boop'], ['d', 'bar'] ], [ ['c', 'foo' ] ] ]\n\n    See Also\n    --------\n    bifurcate, bifurcateBy, bifurcateOwn, groupIn\n","bifurcateOwn":"\nbifurcateOwn( obj, [options,] predicate )\n    Splits values into two groups according to a predicate function.\n\n    When invoked, the predicate function is provided two arguments:\n\n    - value: object value.\n    - key: object key.\n\n    If a predicate function returns a truthy value, a value is placed in the\n    first group; otherwise, a value is placed in the second group.\n\n    If provided an empty object, the function returns an empty array.\n\n    The function iterates over an object's own properties.\n\n    Key iteration order is *not* guaranteed, and, thus, result order is *not*\n    guaranteed.\n\n    Parameters\n    ----------\n    obj: Object|Array|TypedArray\n        Input object to group.\n\n    options: Object (optional)\n        Options.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `keys`, keys are returned; if `*`,\n        both keys and values are returned. Default: 'values'.\n\n    predicate: Function\n        Predicate function indicating which group a value in the input object\n        belongs to.\n\n    Returns\n    -------\n    out: Array<Array>|Array\n        Group results.\n\n    Examples\n    --------\n    > function predicate( v ) { return v[ 0 ] === 'b'; };\n    > var obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\n    > var out = bifurcateOwn( obj, predicate )\n    [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n    // Output group results as keys:\n    > var opts = { 'returns': 'keys' };\n    > out = bifurcateOwn( obj, opts, predicate )\n    [ [ 'a', 'b', 'd' ], [ 'c' ] ]\n\n    // Output group results as key-value pairs:\n    > opts = { 'returns': '*' };\n    > out = bifurcateOwn( obj, opts, predicate )\n    [ [ ['a', 'beep'], ['b', 'boop'], ['d', 'bar'] ], [ ['c', 'foo' ] ] ]\n\n    See Also\n    --------\n    bifurcate, bifurcateBy, bifurcateIn, groupOwn\n","BigInt":"\nBigInt( value )\n    Returns a BigInt.\n\n    Unlike conventional constructors, this function does **not** support the\n    `new` keyword.\n\n    This function is only supported in environments which support BigInts.\n\n    Parameters\n    ----------\n    value: integer|string\n        Value of the BigInt.\n\n    Returns\n    -------\n    out: BigInt\n        BigInt.\n\n    Examples\n    --------\n    > var v = ( BigInt ) ? BigInt( '1' ) : null\n\n\nTODO: document properties/methods\n\n","binomialTest":"\nbinomialTest( x[, n][, options] )\n    Computes an exact test for the success probability in a Bernoulli\n    experiment.\n\n    The returned object comes with a `.print()` method which when invoked will\n    print a formatted output of the results of the hypothesis test.\n\n    Parameters\n    ----------\n    x: (number|Array<number>)\n        Number of successes or two-element array with successes and failures.\n\n    n: Array<number> (optional)\n        Total number of observations.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.alternative: string (optional)\n        Indicates whether the alternative hypothesis is that the mean of `x` is\n        larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n        `mu` (`two-sided`). Default: `'two-sided'`.\n\n    options.p: number (optional)\n        Hypothesized probability under the null hypothesis. Default: `0.5`.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Used significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Sample proportion.\n\n    out.ci: Array<number>\n        1-alpha confidence interval for the success probability.\n\n    out.nullValue: number\n        Assumed success probability under H0.\n\n    out.alternative: string\n        Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n    out.method: string\n        Name of test.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    > var out = binomialTest( 682, 925 )\n    {\n        'pValue': ~3.544e-49,\n        'statistic': ~0.737\n        // ...\n    }\n\n    > out = binomialTest( [ 682, 925 - 682 ] )\n    {\n        'pValue': ~3.544e-49,\n        'statistic': ~0.737\n        // ...\n    }\n\n    > out = binomialTest( 21, 40, {\n    ...     'p': 0.4,\n    ...     'alternative': 'greater'\n    ... })\n    {\n        'pValue': ~0.074,\n        'statistic': 0.525\n        // ...\n    }\n\n","Boolean":"\nBoolean( value )\n    Returns a boolean.\n\n    When invoked without `new`,\n\n    - if provided `false`, `null`, `undefined`, `-0`, `0`, `NaN`, or an empty\n      string, the function returns `false`.\n    - if provided any other value, including an empty object, an empty array,\n      the string `'false'`, or a `Boolean` object (including a `Boolean` object\n      whose value is `false`), the function returns `true`.\n\n    When invoked with `new`, the constructor returns a `Boolean` object, which\n    is an object wrapper for a primitive boolean value. The value of the\n    returned `Boolean` object follows the same conversion semantics as when the\n    constructor is invoked without `new`.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    out: boolean|Boolean\n        Boolean primitive or object.\n\n    Examples\n    --------\n    > var b = new Boolean( null )\n    <Boolean>\n    > b = Boolean( null )\n    false\n    > b = Boolean( [] )\n    true\n\nBoolean.prototype.toString()\n    Returns a string representing the `Boolean` object.\n\n    Returns\n    -------\n    out: string\n        String representation.\n\n    Examples\n    --------\n    > var b = new Boolean( true )\n    <Boolean>\n    > b.toString()\n    'true'\n\nBoolean.prototype.valueOf()\n    Returns the primitive value of a `Boolean` object.\n\n    Returns\n    -------\n    out: boolean\n        Boolean primitive.\n\n    Examples\n    --------\n    > var b = new Boolean( true )\n    <Boolean>\n    > b.valueOf()\n    true\n\n","Boolean.prototype.toString":"\nBoolean.prototype.toString()\n    Returns a string representing the `Boolean` object.\n\n    Returns\n    -------\n    out: string\n        String representation.\n\n    Examples\n    --------\n    > var b = new Boolean( true )\n    <Boolean>\n    > b.toString()\n    'true'","Boolean.prototype.valueOf":"\nBoolean.prototype.valueOf()\n    Returns the primitive value of a `Boolean` object.\n\n    Returns\n    -------\n    out: boolean\n        Boolean primitive.\n\n    Examples\n    --------\n    > var b = new Boolean( true )\n    <Boolean>\n    > b.valueOf()\n    true","BooleanArray":"\nBooleanArray()\n    A Boolean array.\n\n    Returns\n    -------\n    out: BooleanArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new BooleanArray()\n    <BooleanArray>\n\n\nBooleanArray( length )\n    Creates a boolean array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: BooleanArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 10 )\n    <BooleanArray>\n    > var len = arr.length\n    10\n\n\nBooleanArray( booleanarray )\n    Creates a boolean array from another boolean array.\n\n    Parameters\n    ----------\n    booleanarray: BooleanArray\n        Boolean array from which to generate another boolean array.\n\n    Returns\n    -------\n    out: BooleanArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new BooleanArray( [ true, false, false, true ] )\n    <BooleanArray>\n    > var arr2 = new BooleanArray( arr1 )\n    <BooleanArray>\n    > var len = arr2.length\n    4\n\n\nBooleanArray( typedarray )\n    Creates a boolean array from a typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate boolean array.\n\n    Returns\n    -------\n    out: BooleanArray\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new Uint8Array( [ 1, 0, 0, 1 ] )\n    <Uint8Array>\n    > var arr = new BooleanArray( buf )\n    <BooleanArray>\n    > var len = arr.length\n    4\n\n\nBooleanArray( obj )\n    Creates a boolean array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a boolean array.\n\n    Returns\n    -------\n    out: BooleanArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new BooleanArray( [ true, false, false, true ] )\n    <BooleanArray>\n    > var len = arr1.length\n    4\n    > var arr2 = new BooleanArray( [ {}, null, '', 4 ] );\n    > len = arr2.length\n    4\n\n\nBooleanArray( buffer[, byteOffset[, length]] )\n    Returns a boolean array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: BooleanArray\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 240 );\n    > var arr1 = new BooleanArray( buf )\n    <BooleanArray>\n    > var len = arr1.length\n    240\n    > var arr2 = new BooleanArray( buf, 8 )\n    <BooleanArray>\n    > len = arr2.length\n    232\n    > var arr3 = new BooleanArray( buf, 8, 20 )\n    <BooleanArray>\n    > len = arr3.length\n    20\n\n\nBooleanArray.from( src[, clbk[, thisArg]] )\n    Creates a new boolean array from an array-like object or an iterable.\n\n    A callback function is provided two arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    clbk: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: BooleanArray\n        A typed array.\n\n    Examples\n    --------\n    > function map( v ) { return !v };\n    > var src = [ true, false ];\n    > var arr = BooleanArray.from( src, map )\n    <BooleanArray>\n    > var len = arr.length\n    2\n    > var v = arr.get( 0 )\n    false\n    > v = arr.get( 1 )\n    true\n\n\nBooleanArray.of( element0[, element1[, ...elementN]] )\n    Creates a new boolean array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: bool\n        Array element.\n\n    element1: bool (optional)\n        Array element.\n\n    elementN: ...bool (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: BooleanArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = BooleanArray.of( true, false, false, true )\n    <BooleanArray>\n    > var len = arr.length\n    4\n\n\nBooleanArray.BYTES_PER_ELEMENT\n    The size of each array element in bytes.\n\n    Examples\n    --------\n    > var nbytes = BooleanArray.BYTES_PER_ELEMENT\n    1\n\n\nBooleanArray.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > var str = BooleanArray.name\n    'BooleanArray'\n\n\nBooleanArray.prototype.buffer\n    Pointer to the underlying data buffer.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 2 )\n    <BooleanArray>\n    > var buf = arr.buffer\n    <ArrayBuffer>\n\n\nBooleanArray.prototype.byteLength\n    Size of the array in bytes.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 10 )\n    <BooleanArray>\n    > var nbytes = arr.byteLength\n    10\n\n\nBooleanArray.prototype.byteOffset\n    Offset (in bytes) of the array from the start of its underlying\n    ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 10 )\n    <BooleanArray>\n    > var offset = arr.byteOffset\n    0\n    > var buf = new ArrayBuffer( 240 );\n    > arr = new BooleanArray( buf, 64 )\n    <BooleanArray>\n    > offset = arr.byteOffset\n    64\n\n\nBooleanArray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 10 )\n    <BooleanArray>\n    > arr.BYTES_PER_ELEMENT\n    1\n\n\nBooleanArray.prototype.length\n    The number of array elements.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 10 )\n    <BooleanArray>\n    > var len = arr.length\n    10\n\n\nBooleanArray.prototype.at( i )\n    Returns an array element located at integer position (index) `i`, with\n    support for noth nonnegative and negative integer positions.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n\n    Returns\n    -------\n    out: boolean|void\n        An array element.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, false, true ] )\n    <BooleanArray>\n    > var v = arr.at( 1 )\n    false\n    > v = arr.at( -1 )\n    true\n\n\nBooleanArray.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n    \n    start: integer\n        Source start index position.\n    \n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: BooleanArray\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, false, true ] )\n    <BooleanArray>\n    > arr.copyWithin( 0, 2 )\n    <BooleanArray>\n    > var v = arr.get( 0 )\n    false\n    > v = arr.get( 1 )\n    true\n\n\nBooleanArray.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var it = arr.entries();\n    > var v = it.next().value\n    [ 0, true ]\n    > v = it.next().value\n    [ 1, false ]\n    > v = it.next().value\n    [ 2, true ]\n    > var bool = it.next().done\n    true\n\n\nBooleanArray.prototype.every( predicate[, thisArg] )\n    Returns a boolean indicating whether all elements in the array pass a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all elements pass the test.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ true, true, true ] )\n    <BooleanArray>\n    > var bool = arr.every( predicate )\n    true\n\n\nBooleanArray.prototype.fill( value[, start[, end]] )\n    Returns a modified typed array filled with a fill value.\n\n    Parameters\n    ----------\n    value: boolean\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: BooleanArray\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new BooleanArray( 3 )\n    <BooleanArray>\n    > arr.fill( true );\n    > var v = arr.get( 0 )\n    true\n    > v = arr.get( 1 )\n    true\n    > v = arr.get( 2 )\n    true\n\n\nBooleanArray.prototype.filter( predicate[, thisArg] )\n    Returns a new array containing the elements of an array which pass a test\n    implemented by a predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: BooleanArray\n        A new typed array.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( v === true ); };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.filter( predicate )\n    <BooleanArray>\n    > var len = out.length\n    2\n    > var v = out.get( 0 )\n    true\n    > v = out.get( 1 )\n    true\n\n\nBooleanArray.prototype.find( predicate[, thisArg] )\n    Returns the first element in an array for which a predicate function returns\n    a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: boolean|void\n        Array element or `undefined`.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var v = arr.find( predicate )\n    true\n\n\nBooleanArray.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var idx = arr.findIndex( predicate )\n    0\n\n\nBooleanArray.prototype.findLast( predicate[, thisArg] )\n    Returns the last element in an array for which a predicate function returns\n    a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: boolean|void\n        Array element or `undefined`.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var v = arr.findLast( predicate )\n    true\n\n\nBooleanArray.prototype.findLastIndex( predicate[, thisArg] )\n    Returns the index of the last element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var idx = arr.findLastIndex( predicate )\n    2\n\n\nBooleanArray.prototype.forEach( clbk[, thisArg] )\n    Invokes a function once for each array element.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Examples\n    --------\n    > var str = '%';\n    > function clbk( v ) { str += v.toString() + '%'; };\n    > var arr = new BooleanArray( [ true, false, false, true ] )\n    <BooleanArray>\n    > arr.forEach( clbk );\n    > str\n    '%true%false%false%true%'\n\n\nBooleanArray.prototype.get( i )\n    Returns an array element located at integer position (index) `i`.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n\n    Returns\n    -------\n    out: boolean|void\n        Array element or `undefined`.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 10 )\n    <BooleanArray>\n    > arr.set( true, 0 );\n    > var v = arr.get( 0 )\n    true\n\n\nBooleanArray.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a provided value.\n\n    Parameters\n    ----------\n    searchElement: boolean\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true, true, true ] )\n    <BooleanArray>\n    > var bool = arr.includes( true )\n    true\n    > bool = arr.includes( false, 3 )\n    false\n\n\nBooleanArray.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the first index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: boolean\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true, true, true ] )\n    <BooleanArray>\n    > var idx = arr.indexOf( true )\n    0\n    > idx = arr.indexOf( false, 3 )\n    -1\n\n\nBooleanArray.prototype.join( [separator] )\n    Returns a new string by concatenating all array elements separated by a\n    separator string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        Separator string. Default: ','.\n\n    Returns\n    -------\n    out: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var str = arr.join()\n    'true,false,true'\n    > str = arr.join( '|' )\n    'true|false|true'\n\n\nBooleanArray.prototype.keys()\n    Returns an iterator for iterating over each index key in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array index keys.\n    \n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false ] )\n    <BooleanArray>\n    > var it = arr.keys();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().done\n    true\n\n\nBooleanArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the last index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: boolean\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: out.length-1.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, true, true, false, true ] )\n    <BooleanArray>\n    > var idx = arr.lastIndexOf( false )\n    3\n    > idx = arr.lastIndexOf( false, 2 )\n    -1\n\n\nBooleanArray.prototype.map( clbk[, thisArg] )\n    Returns a new array with each element being the result of a provided\n    callback function.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: BooleanArray\n        A new typed array.\n\n    Examples\n    --------\n    > function invert( v ) { return !v; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.map( invert )\n    <BooleanArray>\n    > var v = out.get( 0 )\n    false\n    > v = out.get( 1 )\n    true\n    > v = out.get( 2 )\n    false\n\n\nBooleanArray.prototype.reduce( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in order, passing\n    in the return value from the calculation on the preceding element and\n    returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.\n\n    initialValue: any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: any\n        Accumulated result.\n\n    Examples\n    --------\n    > function reducer( acc, v ) { return ( acc && v ); };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.reduce( reducer )\n    false\n\n\nBooleanArray.prototype.reduceRight( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in reverse order,\n    passing in the return value from the calculation on the preceding element\n    and returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.\n\n    initialValue: any (optional)\n        Initial accumulation value.\n    \n    Returns\n    -------\n    out: any\n        Accumulated result.\n    \n    Examples\n    --------\n    > function reducer( acc, v ) { return ( acc && v ); };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.reduceRight( reducer )\n    false\n\n\nBooleanArray.prototype.reverse()\n    Reverses the array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: BooleanArray\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, false ] )\n    <BooleanArray>\n    > arr.reverse();\n    > var v = arr.get( 0 )\n    false\n    > v = arr.get( 1 )\n    false\n    > v = arr.get( 2 )\n    true\n\n\nBooleanArray.prototype.set( v[, i] )\n    Sets one or more array elements.\n\n    If provided a single argument, the method sets array elements starting at\n    position (index) `i = 0`. To set elements starting elsewhere in the array,\n    provide an index argument `i`.\n\n    To set one or more array elements, provide an array-like object containing\n    truthy and falsy values.\n\n    Parameters\n    ----------\n    v: bool|BooleanArray|ArrayLikeObject\n        Boolean value or Boolean value array.\n\n    i: integer (optional)\n        Array index at which to start setting elements. Default: 0.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 2 )\n    <BooleanArray>\n    > arr.set( false );\n    > var v = arr.get( 0 )\n    false\n    > arr.set( true, 1 );\n    > v = arr.get( 1 )\n    true\n\n\nBooleanArray.prototype.slice( [start[, end]] )\n    Copies a portion of a typed array to a new typed array.\n\n    Parameters\n    ----------\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: BooleanArray\n        New typed array.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true, false, true ] )\n    <BooleanArray>\n    > var out = arr.slice( 1 )\n    <BooleanArray>\n    > var len = out.length\n    4\n    > var v = out.get( 0 )\n    false\n    > v = out.get( 1 )\n    true\n\n\nBooleanArray.prototype.some( predicate[, thisArg] )\n    Returns a boolean indicating whether at least one element passes a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one element passes the test.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ false, true, false ] )\n    <BooleanArray>\n    > var bool = arr.some( predicate )\n    true\n\n\nBooleanArray.prototype.sort( [compareFunction] )\n    Sorts an array in-place.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first boolean value for comparison.\n    - b: second boolean value for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Comparison function.\n\n    Returns\n    -------\n    out: BooleanArray\n        Modified array.\n\n    Examples\n    --------\n    > function compare( a, b ) { return a === true ? -1 : 1; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > arr.sort( compare );\n    > var v = arr.get( 0 )\n    true\n    > v = arr.get( 1 )\n    true\n    > v = arr.get( 2 )\n    false\n\n\nBooleanArray.prototype.subarray( [begin[, end]] )\n    Creates a new typed array view over the same underlying `ArrayBuffer` and\n    with the same underlying data type as the host array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: BooleanArray\n        New typed array view.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true, false, true ] )\n    <BooleanArray>\n    > var out = arr.subarray( 1, 3 )\n    <BooleanArray>\n    > var len = out.length\n    2\n    > var v = out.get( 0 )\n    false\n    > v = out.get( 1 )\n    true\n\n\nBooleanArray.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array (optional)\n        Locale identifier(s).\n    \n    options: Object (optional)\n        An object containing serialization options.\n    \n    Returns\n    -------\n    str: string\n        Local-specific string.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var str = arr.toLocaleString()\n    'true,false,true'\n\n\nBooleanArray.prototype.toReversed()\n    Returns a new typed array containing the elements in reversed order.\n\n    Returns\n    -------\n    out: BooleanArray\n        New typed array.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, false ] )\n    <BooleanArray>\n    > var out = arr.toReversed()\n    <BooleanArray>\n    > var v = out.get( 0 )\n    false\n    > v = out.get( 1 )\n    false\n    > v = out.get( 2 )\n    true\n\n\nBooleanArray.prototype.toSorted( [compareFunction] )\n    Returns a new typed array containing the elements in sorted order.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first boolean value for comparison.\n    - b: second boolean value for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Comparison function.\n\n    Returns\n    -------\n    out: BooleanArray\n        New typed array.\n\n    Examples\n    --------\n    > function compare( a, b ) { return a === true ? -1 : 1; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.toSorted( compare );\n    > var v = out.get( 0 )\n    true\n    > v = out.get( 1 )\n    true\n    > v = out.get( 2 )\n    false\n\n\nBooleanArray.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    out: string\n        String serialization of the array.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var str = arr.toString()\n    'true,false,true'\n\n\nBooleanArray.prototype.values()\n    Returns an iterator for iterating over each value in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array values.\n    \n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false ] )\n    <BooleanArray>\n    > var it = arr.values();\n    > var v = it.next().value\n    true\n    > v = it.next().value\n    false\n    > var bool = it.next().done\n    true\n\n\nBooleanArray.prototype.with( index, value )\n    Returns a new typed array with the element at a provided index replaced\n    with a provided value.\n\n    Parameters\n    ----------\n    index: integer\n        Element index.\n    \n    value: boolean\n        Element value.  \n\n    Returns\n    -------\n    out: BooleanArray\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.with( 0, false )\n    <BooleanArray>\n    > var v = out.get( 0 )\n    false\n\n\n    See Also\n    --------\n    ArrayBuffer","BooleanArray.from":"\nBooleanArray.from( src[, clbk[, thisArg]] )\n    Creates a new boolean array from an array-like object or an iterable.\n\n    A callback function is provided two arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    clbk: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: BooleanArray\n        A typed array.\n\n    Examples\n    --------\n    > function map( v ) { return !v };\n    > var src = [ true, false ];\n    > var arr = BooleanArray.from( src, map )\n    <BooleanArray>\n    > var len = arr.length\n    2\n    > var v = arr.get( 0 )\n    false\n    > v = arr.get( 1 )\n    true","BooleanArray.of":"\nBooleanArray.of( element0[, element1[, ...elementN]] )\n    Creates a new boolean array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: bool\n        Array element.\n\n    element1: bool (optional)\n        Array element.\n\n    elementN: ...bool (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: BooleanArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = BooleanArray.of( true, false, false, true )\n    <BooleanArray>\n    > var len = arr.length\n    4","BooleanArray.BYTES_PER_ELEMENT":"\nBooleanArray.BYTES_PER_ELEMENT\n    The size of each array element in bytes.\n\n    Examples\n    --------\n    > var nbytes = BooleanArray.BYTES_PER_ELEMENT\n    1","BooleanArray.name":"\nBooleanArray.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > var str = BooleanArray.name\n    'BooleanArray'","BooleanArray.prototype.buffer":"\nBooleanArray.prototype.buffer\n    Pointer to the underlying data buffer.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 2 )\n    <BooleanArray>\n    > var buf = arr.buffer\n    <ArrayBuffer>","BooleanArray.prototype.byteLength":"\nBooleanArray.prototype.byteLength\n    Size of the array in bytes.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 10 )\n    <BooleanArray>\n    > var nbytes = arr.byteLength\n    10","BooleanArray.prototype.byteOffset":"\nBooleanArray.prototype.byteOffset\n    Offset (in bytes) of the array from the start of its underlying\n    ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 10 )\n    <BooleanArray>\n    > var offset = arr.byteOffset\n    0\n    > var buf = new ArrayBuffer( 240 );\n    > arr = new BooleanArray( buf, 64 )\n    <BooleanArray>\n    > offset = arr.byteOffset\n    64","BooleanArray.prototype.BYTES_PER_ELEMENT":"\nBooleanArray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 10 )\n    <BooleanArray>\n    > arr.BYTES_PER_ELEMENT\n    1","BooleanArray.prototype.length":"\nBooleanArray.prototype.length\n    The number of array elements.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 10 )\n    <BooleanArray>\n    > var len = arr.length\n    10","BooleanArray.prototype.at":"\nBooleanArray.prototype.at( i )\n    Returns an array element located at integer position (index) `i`, with\n    support for noth nonnegative and negative integer positions.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n\n    Returns\n    -------\n    out: boolean|void\n        An array element.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, false, true ] )\n    <BooleanArray>\n    > var v = arr.at( 1 )\n    false\n    > v = arr.at( -1 )\n    true","BooleanArray.prototype.copyWithin":"\nBooleanArray.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n    \n    start: integer\n        Source start index position.\n    \n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: BooleanArray\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, false, true ] )\n    <BooleanArray>\n    > arr.copyWithin( 0, 2 )\n    <BooleanArray>\n    > var v = arr.get( 0 )\n    false\n    > v = arr.get( 1 )\n    true","BooleanArray.prototype.entries":"\nBooleanArray.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var it = arr.entries();\n    > var v = it.next().value\n    [ 0, true ]\n    > v = it.next().value\n    [ 1, false ]\n    > v = it.next().value\n    [ 2, true ]\n    > var bool = it.next().done\n    true","BooleanArray.prototype.every":"\nBooleanArray.prototype.every( predicate[, thisArg] )\n    Returns a boolean indicating whether all elements in the array pass a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all elements pass the test.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ true, true, true ] )\n    <BooleanArray>\n    > var bool = arr.every( predicate )\n    true","BooleanArray.prototype.fill":"\nBooleanArray.prototype.fill( value[, start[, end]] )\n    Returns a modified typed array filled with a fill value.\n\n    Parameters\n    ----------\n    value: boolean\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: BooleanArray\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new BooleanArray( 3 )\n    <BooleanArray>\n    > arr.fill( true );\n    > var v = arr.get( 0 )\n    true\n    > v = arr.get( 1 )\n    true\n    > v = arr.get( 2 )\n    true","BooleanArray.prototype.filter":"\nBooleanArray.prototype.filter( predicate[, thisArg] )\n    Returns a new array containing the elements of an array which pass a test\n    implemented by a predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: BooleanArray\n        A new typed array.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( v === true ); };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.filter( predicate )\n    <BooleanArray>\n    > var len = out.length\n    2\n    > var v = out.get( 0 )\n    true\n    > v = out.get( 1 )\n    true","BooleanArray.prototype.find":"\nBooleanArray.prototype.find( predicate[, thisArg] )\n    Returns the first element in an array for which a predicate function returns\n    a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: boolean|void\n        Array element or `undefined`.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var v = arr.find( predicate )\n    true","BooleanArray.prototype.findIndex":"\nBooleanArray.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var idx = arr.findIndex( predicate )\n    0","BooleanArray.prototype.findLast":"\nBooleanArray.prototype.findLast( predicate[, thisArg] )\n    Returns the last element in an array for which a predicate function returns\n    a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: boolean|void\n        Array element or `undefined`.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var v = arr.findLast( predicate )\n    true","BooleanArray.prototype.findLastIndex":"\nBooleanArray.prototype.findLastIndex( predicate[, thisArg] )\n    Returns the index of the last element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var idx = arr.findLastIndex( predicate )\n    2","BooleanArray.prototype.forEach":"\nBooleanArray.prototype.forEach( clbk[, thisArg] )\n    Invokes a function once for each array element.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Examples\n    --------\n    > var str = '%';\n    > function clbk( v ) { str += v.toString() + '%'; };\n    > var arr = new BooleanArray( [ true, false, false, true ] )\n    <BooleanArray>\n    > arr.forEach( clbk );\n    > str\n    '%true%false%false%true%'","BooleanArray.prototype.get":"\nBooleanArray.prototype.get( i )\n    Returns an array element located at integer position (index) `i`.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n\n    Returns\n    -------\n    out: boolean|void\n        Array element or `undefined`.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 10 )\n    <BooleanArray>\n    > arr.set( true, 0 );\n    > var v = arr.get( 0 )\n    true","BooleanArray.prototype.includes":"\nBooleanArray.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a provided value.\n\n    Parameters\n    ----------\n    searchElement: boolean\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true, true, true ] )\n    <BooleanArray>\n    > var bool = arr.includes( true )\n    true\n    > bool = arr.includes( false, 3 )\n    false","BooleanArray.prototype.indexOf":"\nBooleanArray.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the first index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: boolean\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true, true, true ] )\n    <BooleanArray>\n    > var idx = arr.indexOf( true )\n    0\n    > idx = arr.indexOf( false, 3 )\n    -1","BooleanArray.prototype.join":"\nBooleanArray.prototype.join( [separator] )\n    Returns a new string by concatenating all array elements separated by a\n    separator string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        Separator string. Default: ','.\n\n    Returns\n    -------\n    out: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var str = arr.join()\n    'true,false,true'\n    > str = arr.join( '|' )\n    'true|false|true'","BooleanArray.prototype.keys":"\nBooleanArray.prototype.keys()\n    Returns an iterator for iterating over each index key in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array index keys.\n    \n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false ] )\n    <BooleanArray>\n    > var it = arr.keys();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().done\n    true","BooleanArray.prototype.lastIndexOf":"\nBooleanArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the last index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: boolean\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: out.length-1.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, true, true, false, true ] )\n    <BooleanArray>\n    > var idx = arr.lastIndexOf( false )\n    3\n    > idx = arr.lastIndexOf( false, 2 )\n    -1","BooleanArray.prototype.map":"\nBooleanArray.prototype.map( clbk[, thisArg] )\n    Returns a new array with each element being the result of a provided\n    callback function.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: BooleanArray\n        A new typed array.\n\n    Examples\n    --------\n    > function invert( v ) { return !v; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.map( invert )\n    <BooleanArray>\n    > var v = out.get( 0 )\n    false\n    > v = out.get( 1 )\n    true\n    > v = out.get( 2 )\n    false","BooleanArray.prototype.reduce":"\nBooleanArray.prototype.reduce( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in order, passing\n    in the return value from the calculation on the preceding element and\n    returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.\n\n    initialValue: any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: any\n        Accumulated result.\n\n    Examples\n    --------\n    > function reducer( acc, v ) { return ( acc && v ); };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.reduce( reducer )\n    false","BooleanArray.prototype.reduceRight":"\nBooleanArray.prototype.reduceRight( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in reverse order,\n    passing in the return value from the calculation on the preceding element\n    and returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.\n\n    initialValue: any (optional)\n        Initial accumulation value.\n    \n    Returns\n    -------\n    out: any\n        Accumulated result.\n    \n    Examples\n    --------\n    > function reducer( acc, v ) { return ( acc && v ); };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.reduceRight( reducer )\n    false","BooleanArray.prototype.reverse":"\nBooleanArray.prototype.reverse()\n    Reverses the array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: BooleanArray\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, false ] )\n    <BooleanArray>\n    > arr.reverse();\n    > var v = arr.get( 0 )\n    false\n    > v = arr.get( 1 )\n    false\n    > v = arr.get( 2 )\n    true","BooleanArray.prototype.set":"\nBooleanArray.prototype.set( v[, i] )\n    Sets one or more array elements.\n\n    If provided a single argument, the method sets array elements starting at\n    position (index) `i = 0`. To set elements starting elsewhere in the array,\n    provide an index argument `i`.\n\n    To set one or more array elements, provide an array-like object containing\n    truthy and falsy values.\n\n    Parameters\n    ----------\n    v: bool|BooleanArray|ArrayLikeObject\n        Boolean value or Boolean value array.\n\n    i: integer (optional)\n        Array index at which to start setting elements. Default: 0.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 2 )\n    <BooleanArray>\n    > arr.set( false );\n    > var v = arr.get( 0 )\n    false\n    > arr.set( true, 1 );\n    > v = arr.get( 1 )\n    true","BooleanArray.prototype.slice":"\nBooleanArray.prototype.slice( [start[, end]] )\n    Copies a portion of a typed array to a new typed array.\n\n    Parameters\n    ----------\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: BooleanArray\n        New typed array.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true, false, true ] )\n    <BooleanArray>\n    > var out = arr.slice( 1 )\n    <BooleanArray>\n    > var len = out.length\n    4\n    > var v = out.get( 0 )\n    false\n    > v = out.get( 1 )\n    true","BooleanArray.prototype.some":"\nBooleanArray.prototype.some( predicate[, thisArg] )\n    Returns a boolean indicating whether at least one element passes a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one element passes the test.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ false, true, false ] )\n    <BooleanArray>\n    > var bool = arr.some( predicate )\n    true","BooleanArray.prototype.sort":"\nBooleanArray.prototype.sort( [compareFunction] )\n    Sorts an array in-place.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first boolean value for comparison.\n    - b: second boolean value for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Comparison function.\n\n    Returns\n    -------\n    out: BooleanArray\n        Modified array.\n\n    Examples\n    --------\n    > function compare( a, b ) { return a === true ? -1 : 1; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > arr.sort( compare );\n    > var v = arr.get( 0 )\n    true\n    > v = arr.get( 1 )\n    true\n    > v = arr.get( 2 )\n    false","BooleanArray.prototype.subarray":"\nBooleanArray.prototype.subarray( [begin[, end]] )\n    Creates a new typed array view over the same underlying `ArrayBuffer` and\n    with the same underlying data type as the host array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: BooleanArray\n        New typed array view.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true, false, true ] )\n    <BooleanArray>\n    > var out = arr.subarray( 1, 3 )\n    <BooleanArray>\n    > var len = out.length\n    2\n    > var v = out.get( 0 )\n    false\n    > v = out.get( 1 )\n    true","BooleanArray.prototype.toLocaleString":"\nBooleanArray.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array (optional)\n        Locale identifier(s).\n    \n    options: Object (optional)\n        An object containing serialization options.\n    \n    Returns\n    -------\n    str: string\n        Local-specific string.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var str = arr.toLocaleString()\n    'true,false,true'","BooleanArray.prototype.toReversed":"\nBooleanArray.prototype.toReversed()\n    Returns a new typed array containing the elements in reversed order.\n\n    Returns\n    -------\n    out: BooleanArray\n        New typed array.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, false ] )\n    <BooleanArray>\n    > var out = arr.toReversed()\n    <BooleanArray>\n    > var v = out.get( 0 )\n    false\n    > v = out.get( 1 )\n    false\n    > v = out.get( 2 )\n    true","BooleanArray.prototype.toSorted":"\nBooleanArray.prototype.toSorted( [compareFunction] )\n    Returns a new typed array containing the elements in sorted order.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first boolean value for comparison.\n    - b: second boolean value for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Comparison function.\n\n    Returns\n    -------\n    out: BooleanArray\n        New typed array.\n\n    Examples\n    --------\n    > function compare( a, b ) { return a === true ? -1 : 1; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.toSorted( compare );\n    > var v = out.get( 0 )\n    true\n    > v = out.get( 1 )\n    true\n    > v = out.get( 2 )\n    false","BooleanArray.prototype.toString":"\nBooleanArray.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    out: string\n        String serialization of the array.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var str = arr.toString()\n    'true,false,true'","BooleanArray.prototype.values":"\nBooleanArray.prototype.values()\n    Returns an iterator for iterating over each value in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array values.\n    \n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false ] )\n    <BooleanArray>\n    > var it = arr.values();\n    > var v = it.next().value\n    true\n    > v = it.next().value\n    false\n    > var bool = it.next().done\n    true","BooleanArray.prototype.with":"\nBooleanArray.prototype.with( index, value )\n    Returns a new typed array with the element at a provided index replaced\n    with a provided value.\n\n    Parameters\n    ----------\n    index: integer\n        Element index.\n    \n    value: boolean\n        Element value.  \n\n    Returns\n    -------\n    out: BooleanArray\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.with( 0, false )\n    <BooleanArray>\n    > var v = out.get( 0 )\n    false\n\n\n    See Also\n    --------\n    ArrayBuffer","broadcastArray":"\nbroadcastArray( x, shape )\n    Broadcasts an ndarray to a specified shape.\n\n    The returned array is a read-only view on the input array data buffer. The\n    view is typically *not* contiguous. As more than one element of a returned\n    view may refer to the same memory location, writing to the input array may\n    affect multiple elements. If you need to write to the input array, copy the\n    input array before broadcasting.\n\n    The function throws an error if a provided ndarray is incompatible with a\n    provided shape.\n\n    The function always returns a new ndarray instance even if the input ndarray\n    shape and the desired shape are the same.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    shape: ArrayLikeObject\n        Desired shape.\n\n    Returns\n    -------\n    out: ndarray\n        Broadcasted array.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n    <ndarray>\n    > var sh = x.shape\n    [ 2, 2 ]\n    > var y = broadcastArray( x, [ 3, 2, 2 ] )\n    <ndarray>\n    > sh = y.shape\n    [ 3, 2, 2 ]\n    > var v = y.get( 0, 0, 0 )\n    1\n    > v = y.get( 0, 0, 1 )\n    2\n    > v = y.get( 0, 1, 0 )\n    3\n    > v = y.get( 0, 1, 1 )\n    4\n    > v = y.get( 1, 0, 0 )\n    1\n    > v = y.get( 1, 1, 0 )\n    3\n    > v = y.get( 2, 0, 0 )\n    1\n    > v = y.get( 2, 1, 1 )\n    4\n\n    See Also\n    --------\n    array, broadcastArrays, ndarray, maybeBroadcastArray\n","broadcastArrays":"\nbroadcastArrays( ...arrays )\n    Broadcasts ndarrays to a common shape.\n\n    The function supports two (mutually exclusive) means of providing ndarray\n    arguments:\n\n    1. Providing a single array containing ndarray arguments.\n    2. Providing ndarray arguments as separate arguments.\n\n    The returned arrays are read-only views on their respective underlying\n    array data buffers. The views are typically **not** contiguous. As more\n    than one element of a returned view may refer to the same memory location,\n    writing to a view may affect multiple elements. If you need to write to an\n    input array, copy the array before broadcasting.\n\n    The function throws an error if provided broadcast-incompatible ndarrays.\n\n    The function always returns new ndarray instances even if an input ndarray\n    and the broadcasted shape are the same.\n\n    Parameters\n    ----------\n    arrays: ...ndarray|ArrayLikeObject<ndarray>\n        Array arguments.\n\n    Returns\n    -------\n    out: Array<ndarray>\n        Broadcasted arrays.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n    <ndarray>\n    > var sh = x.shape\n    [ 2, 2 ]\n    > var y = ndzeros( [ 3, 2, 2 ] )\n    <ndarray>\n    > var out = broadcastArrays( [ x, y ] )\n    [ <ndarray>, <ndarray> ]\n\n    // Retrieve the broadcasted \"x\" array:\n    > var bx = out[ 0 ]\n    <ndarray>\n    > sh = bx.shape\n    [ 3, 2, 2 ]\n\n    // Retrieve broadcasted elements...\n    > var v = bx.get( 0, 0, 0 )\n    1\n    > v = bx.get( 0, 0, 1 )\n    2\n    > v = bx.get( 0, 1, 0 )\n    3\n    > v = bx.get( 0, 1, 1 )\n    4\n    > v = bx.get( 1, 0, 0 )\n    1\n    > v = bx.get( 1, 1, 0 )\n    3\n    > v = bx.get( 2, 0, 0 )\n    1\n    > v = bx.get( 2, 1, 1 )\n    4\n\n    See Also\n    --------\n    array, broadcastArray, ndarray, maybeBroadcastArrays\n","Buffer":"\nBuffer\n    Buffer constructor.\n\n\nBuffer( size )\n    Allocates a buffer having a specified number of bytes.\n\n    Parameters\n    ----------\n    size: integer\n        Number of bytes to allocate.\n\n    Returns\n    -------\n    out: Buffer\n        Buffer instance.\n\n    Examples\n    --------\n    > var b = new Buffer( 4 )\n    <Buffer>\n\n\nBuffer( buffer )\n    Copies buffer data to a new Buffer instance.\n\n    Parameters\n    ----------\n    buffer: Buffer\n        Buffer to copy from.\n\n    Returns\n    -------\n    out: Buffer\n        Buffer instance.\n\n    Examples\n    --------\n    > var b1 = new Buffer( [ 1, 2, 3, 4 ] );\n    > var b2 = new Buffer( b1 )\n    <Buffer>[ 1, 2, 3, 4 ]\n\n\nBuffer( array )\n    Allocates a buffer using an array of octets.\n\n    Parameters\n    ----------\n    array: Array\n        Array of octets.\n\n    Returns\n    -------\n    out: Buffer\n        Buffer instance.\n\n    Examples\n    --------\n    > var b = new Buffer( [ 1, 2, 3, 4 ] )\n    <Buffer>[ 1, 2, 3, 4 ]\n\n\nBuffer( str[, encoding] )\n    Allocates a buffer containing a provided string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    encoding: string (optional)\n        Character encoding. Default: 'utf8'.\n\n    Returns\n    -------\n    out: Buffer\n        Buffer instance.\n\n    Examples\n    --------\n    > var b = new Buffer( 'beep boop' )\n    <Buffer>\n\n\nTODO: add methods and properties\n\n\n    See Also\n    --------\n    ArrayBuffer\n","buffer2json":"\nbuffer2json( buffer )\n    Returns a JSON representation of a buffer.\n\n    Parameters\n    ----------\n    buffer: Buffer\n        Buffer to serialize.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    out.type: string\n        Value type. The assigned value is always \"Buffer\".\n\n    out.data: Array\n        Buffer data.\n\n    Examples\n    --------\n    > var buf = new allocUnsafe( 2 );\n    > buf[ 0 ] = 1;\n    > buf[ 1 ] = 2;\n    > var json = buffer2json( buf )\n    { 'type': 'Buffer', 'data': [ 1, 2 ] }\n\n    See Also\n    --------\n    typedarray2json, reviveBuffer\n","BYTE_ORDER":"\nBYTE_ORDER\n    Platform byte order.\n\n    Possible values:\n\n    - 'little-endian'\n    - 'big-endian'\n    - 'mixed-endian'\n    - 'unknown'\n\n    Examples\n    --------\n    > BYTE_ORDER\n    <string>\n\n    See Also\n    --------\n    IS_BIG_ENDIAN, IS_LITTLE_ENDIAN\n","camelcase":"\ncamelcase( str )\n    Converts a string to camel case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Camel-cased string.\n\n    Examples\n    --------\n    > var out = camelcase( 'Hello World!' )\n    'helloWorld'\n    > out = camelcase( 'beep boop' )\n    'beepBoop'\n\n    See Also\n    --------\n    constantcase, kebabcase, pascalcase, snakecase","capitalize":"\ncapitalize( str )\n    Capitalizes the first character in a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Capitalized string.\n\n    Examples\n    --------\n    > var out = capitalize( 'beep' )\n    'Beep'\n    > out = capitalize( 'Boop' )\n    'Boop'\n\n    See Also\n    --------\n    uncapitalize, uppercase\n","capitalizeKeys":"\ncapitalizeKeys( obj )\n    Converts the first letter of each object key to uppercase.\n\n    The function only transforms own properties. Hence, the function does not\n    transform inherited properties.\n\n    The function shallow copies key values.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > var obj = { 'aa': 1, 'bb': 2 };\n    > var out = capitalizeKeys( obj )\n    { 'Aa': 1, 'Bb': 2 }\n\n    See Also\n    --------\n    uncapitalizeKeys, uppercaseKeys\n","CATALAN":"\nCATALAN\n    Catalan's constant.\n\n    Examples\n    --------\n    > CATALAN\n    0.915965594177219\n\n","CBRT_EPS":"\nCBRT_EPS\n    Cube root of double-precision floating-point epsilon.\n\n    Examples\n    --------\n    > CBRT_EPS\n    0.0000060554544523933395\n\n    See Also\n    --------\n    EPS, SQRT_EPS\n","CDC_NCHS_US_BIRTHS_1969_1988":"\nCDC_NCHS_US_BIRTHS_1969_1988()\n    Returns US birth data from 1969 to 1988, as provided by the Center for\n    Disease Control and Prevention's National Center for Health Statistics.\n\n    Returns\n    -------\n    out: Array<Object>\n        Birth data.\n\n    Examples\n    --------\n    > var data = CDC_NCHS_US_BIRTHS_1969_1988()\n    [ {...}, ... ]\n\n    See Also\n    --------\n    CDC_NCHS_US_BIRTHS_1994_2003, SSA_US_BIRTHS_2000_2014\n","CDC_NCHS_US_BIRTHS_1994_2003":"\nCDC_NCHS_US_BIRTHS_1994_2003()\n    Returns US birth data from 1994 to 2003, as provided by the Center for\n    Disease Control and Prevention's National Center for Health Statistics.\n\n    Returns\n    -------\n    out: Array<Object>\n        Birth data.\n\n    Examples\n    --------\n    > var data = CDC_NCHS_US_BIRTHS_1994_2003()\n    [ {...}, ... ]\n\n    See Also\n    --------\n    CDC_NCHS_US_BIRTHS_1969_1988, SSA_US_BIRTHS_2000_2014\n","CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013":"\nCDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n    Returns US infant mortality data, by race, from 1915 to 2013, as provided by\n    the Center for Disease Control and Prevention's National Center for Health\n    Statistics.\n\n    All birth data by race before 1980 are based on race of the child. Starting\n    in 1980, birth data by race are based on race of the mother. Birth data are\n    used to calculate infant mortality rate.\n\n    Returns\n    -------\n    out: Array<Object>\n        Infant mortality data.\n\n    Examples\n    --------\n    > var data = CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n    { 'black': [...], 'white': [...] }\n\n","chdir":"\nchdir( path )\n    Changes the current working directory.\n\n    If unable to set the current working directory (e.g., due to a non-existent\n    path), the function returns an error; otherwise, the function returns\n    `null`.\n\n    Parameters\n    ----------\n    path: string\n        Desired working directory.\n\n    Returns\n    -------\n    err: Error|null\n        Error object or null.\n\n    Examples\n    --------\n    > var err = chdir( '/path/to/current/working/directory' )\n\n    See Also\n    --------\n    cwd\n","chi2gof":"\nchi2gof( x, y[, ...args][, options] )\n    Performs a chi-square goodness-of-fit test.\n\n    A chi-square goodness-of-fit test is computed for the null hypothesis that\n    the values of `x` come from the discrete probability distribution specified\n    by `y`.\n\n    The second argument can either be expected frequencies, population\n    probabilities summing to one, or a discrete probability distribution name to\n    test against.\n\n    When providing a discrete probability distribution name, distribution\n    parameters *must* be supplied as additional arguments.\n\n    The function returns an object containing the test statistic, p-value, and\n    decision.\n\n    By default, the p-value is computed using a chi-square distribution with\n    `k-1` degrees of freedom, where `k` is the length of `x`.\n\n    If provided distribution arguments are estimated (e.g., via maximum\n    likelihood estimation), the degrees of freedom should be corrected. Set the\n    `ddof` option to use `k-1-n` degrees of freedom, where `n` is the degrees of\n    freedom adjustment.\n\n    The chi-square approximation may be incorrect if the observed or expected\n    frequencies in each category are too small. Common practice is to require\n    frequencies greater than five.\n\n    Instead of relying on chi-square approximation to calculate the p-value, one\n    can use Monte Carlo simulation. When the `simulate` option is `true`, the\n    simulation is performed by re-sampling from the discrete probability\n    distribution specified by `y`.\n\n    Parameters\n    ----------\n    x: ndarray|Array<number>|TypedArray\n        Observation frequencies.\n\n    y: ndarray|Array<number>|TypedArray|string\n        Expected frequencies, population probabilities, or a discrete\n        probability distribution name.\n\n    args: ...number (optional)\n        Distribution parameters. Distribution parameters will be passed to a\n        probability mass function (PMF) as arguments.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Significance level of the hypothesis test. Must be on the interval\n        [0,1]. Default: 0.05.\n\n    options.ddof: number (optional)\n        Delta degrees of freedom adjustment. Default: 0.\n\n    options.simulate: boolean (optional)\n        Boolean indicating whether to calculate p-values by Monte Carlo\n        simulation. The simulation is performed by re-sampling from the discrete\n        distribution specified by `y`. Default: false.\n\n    options.iterations: number (optional)\n        Number of Monte Carlo iterations. Default: 500.\n\n    Returns\n    -------\n    out: Object\n        Test results object.\n\n    out.alpha: number\n        Significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        Test p-value.\n\n    out.statistic: number\n        Test statistic.\n\n    out.df: number|null\n        Degrees of freedom.\n\n    out.method: string\n        Test name.\n\n    out.toString: Function\n        Serializes results as formatted output.\n\n    out.toJSON: Function\n        Serializes results as JSON.\n\n    Examples\n    --------\n    // Provide expected probabilities...\n    > var x = [ 89, 37, 30, 28, 2 ];\n    > var p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\n    > var out = chi2gof( x, p );\n    > var o = out.toJSON()\n    { 'pValue': ~0.0406, 'statistic': ~9.9901, ... }\n    > out.toString()\n\n    // Set significance level...\n    > var opts = { 'alpha': 0.01 };\n    > out = chi2gof( x, p, opts );\n    > out.toString()\n\n    // Calculate the test p-value via Monte Carlo simulation...\n    > x = [ 89, 37, 30, 28, 2 ];\n    > p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\n    > opts = { 'simulate': true, 'iterations': 1000 };\n    > out = chi2gof( x, p, opts );\n    > out.toString()\n\n    // Verify that data comes from Poisson distribution...\n    > var lambda = 3.0;\n    > var rpois = base.random.poisson.factory( lambda );\n    > var len = 400;\n    > x = [];\n    > for ( var i = 0; i < len; i++ ) { x.push( rpois() ); };\n\n    // Generate a frequency table...\n    > var freqs = new Int32Array( len );\n    > for ( i = 0; i < len; i++ ) { freqs[ x[ i ] ] += 1; };\n    > out = chi2gof( freqs, 'poisson', lambda );\n    > out.toString()\n\n","chi2test":"\nchi2test( x[, options] )\n    Performs a chi-square independence test.\n\n    For a two-way contingency table, the function computes a chi-square\n    independence test for the null hypothesis that the joint distribution of the\n    cell counts is the product of the row and column marginals (i.e. that the\n    row and column variables are independent).\n\n    The chi-square approximation may be incorrect if the observed or expected\n    frequencies in each category are too small. Common practice is to require\n    frequencies greater than five. The Yates' continuity correction is enabled\n    by default for 2x2 tables to account for this, although it tends to\n    over-correct.\n\n    The function returns an object containing the test statistic, p-value, and\n    decision.\n\n    Parameters\n    ----------\n    x: ndarray|Array<Collection<number>>\n        Two-way table of observed frequencies.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Significance level of the hypothesis test. Must be on the interval\n        [0,1]. Default: 0.05.\n\n    options.correct: boolean (optional)\n        Boolean indicating whether to use Yates' continuity correction when\n        provided a 2x2 contingency table. Default: true.\n\n    Returns\n    -------\n    out: Object\n        Test results object.\n\n    out.alpha: number\n        Significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        Test p-value.\n\n    out.statistic: number\n        Test statistic.\n\n    out.df: number\n        Degrees of freedom.\n\n    out.expected: ndarray\n        Expected frequencies.\n\n    out.method: string\n        Test name.\n\n    out.toString: Function\n        Serializes results as formatted output.\n\n    out.toJSON: Function\n        Serializes results as JSON.\n\n    Examples\n    --------\n    > var x = [ [ 20, 30 ], [ 30, 20 ] ];\n    > var out = chi2test( x );\n    > var o = out.toJSON()\n    { 'rejected': false, 'pValue': ~0.072, 'statistic': 3.24, ... }\n    > out.toString()\n\n    // Set significance level...\n    > var opts = { 'alpha': 0.1 };\n    > out = chi2test( x, opts );\n    > o = out.toJSON()\n    { 'rejected': true, 'pValue': ~0.072, 'statistic': 3.24, ... }\n    > out.toString()\n\n    // Disable Yates' continuity correction (primarily used with small counts):\n    > opts = { 'correct': false };\n    > out = chi2test( x, opts );\n    > out.toString()\n\n","circarray2iterator":"\ncircarray2iterator( src[, options][, mapFcn[, thisArg]] )\n    Returns an iterator which repeatedly iterates over the elements of an array-\n    like object.\n\n    When invoked, an input function is provided four arguments:\n\n    - value: iterated value.\n    - index: iterated value index.\n    - n: iteration count.\n    - src: source array-like object.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an array's `@@iterator` method, regardless of whether this method is\n    defined. To convert an array to an implementation defined iterator, invoke\n    this method directly.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Array-like object from which to create the iterator.\n\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    options.dir: integer (optional)\n        Iteration direction. If set to `-1`, an iterator iterates over elements\n        from right-to-left. Default: 1.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = circarray2iterator( [ 1, 2, 3, 4 ] );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    array2iterator, stridedarray2iterator\n","circularArrayStream":"\ncircularArrayStream( src[, options] )\n    Creates a readable stream from an array-like object which repeatedly\n    iterates over the provided value's elements.\n\n    In object mode, `null` is a reserved value. If an array contains `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or filter `null` values\n    prior to invocation.\n\n    In binary mode, if an array contains `undefined` values, the stream will\n    emit an error. Consider providing a custom serialization function or\n    filtering `undefined` values prior to invocation.\n\n    If a serialization function fails to return a string or Buffer, the stream\n    emits an error.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Source value.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing the stream.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize streamed\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    options.dir: integer (optional)\n        Iteration direction. If set to `-1`, a stream iterates over elements\n        from right-to-left. Default: 1.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 15 };\n    > var s = circularArrayStream( [ 1, 2, 3 ], opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\ncircularArrayStream.factory( [options] )\n    Returns a function for creating readable streams from array-like objects\n    which repeatedly iterate over the elements of provided values.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing streaming.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize streamed\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    options.dir: integer (optional)\n        Iteration direction. If set to `-1`, a stream iterates over elements\n        from right-to-left. Default: 1.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = circularArrayStream.factory( opts );\n\n\ncircularArrayStream.objectMode( src[, options] )\n    Returns an \"objectMode\" readable stream from an array-like object which\n    repeatedly iterates over a provided value's elements.\n\n    In object mode, `null` is a reserved value. If an array contains `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or filter `null` values\n    prior to invocation.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Source value.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before pausing streaming.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    options.dir: integer (optional)\n        Iteration direction. If set to `-1`, a stream iterates over elements\n        from right-to-left. Default: 1.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 15 };\n    > var s = circularArrayStream.objectMode( [ 1, 2, 3 ], opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    arrayStream, iteratorStream, stridedArrayStream\n","circularArrayStream.factory":"\ncircularArrayStream.factory( [options] )\n    Returns a function for creating readable streams from array-like objects\n    which repeatedly iterate over the elements of provided values.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing streaming.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize streamed\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    options.dir: integer (optional)\n        Iteration direction. If set to `-1`, a stream iterates over elements\n        from right-to-left. Default: 1.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = circularArrayStream.factory( opts );","circularArrayStream.objectMode":"\ncircularArrayStream.objectMode( src[, options] )\n    Returns an \"objectMode\" readable stream from an array-like object which\n    repeatedly iterates over a provided value's elements.\n\n    In object mode, `null` is a reserved value. If an array contains `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or filter `null` values\n    prior to invocation.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Source value.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before pausing streaming.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    options.dir: integer (optional)\n        Iteration direction. If set to `-1`, a stream iterates over elements\n        from right-to-left. Default: 1.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 15 };\n    > var s = circularArrayStream.objectMode( [ 1, 2, 3 ], opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    arrayStream, iteratorStream, stridedArrayStream","CircularBuffer":"\nCircularBuffer( buffer )\n    Circular buffer constructor.\n\n    Parameters\n    ----------\n    buffer: integer|ArrayLike\n        Buffer size or an array-like object to use as the underlying buffer.\n\n    Returns\n    -------\n    buf: Object\n        Circular buffer data structure.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.push( 'foo' );\n    > b.push( 'bar' );\n    > b.push( 'beep' );\n    > b.length\n    3\n    > b.count\n    3\n    > b.push( 'boop' )\n    'foo'\n\n\nCircularBuffer.prototype.clear()\n    Clears a buffer.\n\n    Returns\n    -------\n    out: Object\n        Circular buffer instance.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.push( 'foo' );\n    > b.push( 'bar' );\n    > b.push( 'beep' );\n    > b.count\n    3\n    > b.clear();\n    > b.count\n    0\n\n\nCircularBuffer.prototype.count\n    Read-only property returning the number of elements currently in the buffer.\n\n    Returns\n    -------\n    out: integer\n        Number of elements currently in the buffer.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.count\n    0\n    > b.push( 'foo' );\n    > b.count\n    1\n    > b.push( 'bar' );\n    > b.count\n    2\n\n\nCircularBuffer.prototype.full\n    Read-only property returning a boolean indicating whether a circular buffer\n    is full.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether a circular buffer is full.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.full\n    false\n    > b.push( 'foo' );\n    > b.push( 'bar' );\n    > b.push( 'beep' );\n    > b.full\n    true\n\n\nCircularBuffer.prototype.iterator( [niters] )\n    Returns an iterator for iterating over a circular buffer.\n\n    A returned iterator does not iterate over partially full buffers.\n\n    Parameters\n    ----------\n    niters: integer (optional)\n        Number of iterations. Default: infinity.\n\n    Returns\n    -------\n    out: Iterator\n        Iterator.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.push( 'foo' );\n    > b.push( 'bar' );\n    > b.push( 'beep' );\n    > b.push( 'boop' );\n    > var it = b.iterator( b.length );\n    > var v = it.next().value\n    'bar'\n    > v = it.next().value\n    'beep'\n    > v = it.next().value\n    'boop'\n    > var bool = it.next().done\n    true\n\n\nCircularBuffer.prototype.length\n    Read-only property returning the buffer length (i.e., capacity).\n\n    Returns\n    -------\n    out: integer\n        Buffer length.\n\n    Examples\n    --------\n    > var b = CircularBuffer( [ 0, 0, 0 ] );\n    > var len = b.length\n    3\n\n\nCircularBuffer.prototype.push( value )\n    Adds a value to a circular buffer.\n\n    Parameters\n    ----------\n    value: any\n        Value to add.\n\n    Returns\n    -------\n    out: any\n        Removed element (or undefined).\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.push( 'foo' )\n    undefined\n    > b.push( 'bar' )\n    undefined\n    > b.push( 'beep' )\n    undefined\n    > b.push( 'boop' )\n    'foo'\n\n\nCircularBuffer.prototype.toArray()\n    Returns an array of circular buffer values.\n\n    Returns\n    -------\n    out: Array\n        Circular buffer values.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.push( 'foo' );\n    > b.push( 'bar' );\n    > b.push( 'beep' );\n    > b.push( 'boop' );\n    > var vals = b.toArray()\n    [ 'bar', 'beep', 'boop' ]\n\n\nCircularBuffer.prototype.toJSON()\n    Serializes a circular buffer as JSON.\n\n    Returns\n    -------\n    out: Object\n        Serialized circular buffer.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.push( 'foo' );\n    > b.push( 'bar' );\n    > b.push( 'beep' );\n    > b.push( 'boop' );\n    > var o = b.toJSON()\n    {'type':'circular-buffer','length':3,'data':['bar','beep','boop']}\n\n    See Also\n    --------\n    FIFO, Stack\n","CircularBuffer.prototype.clear":"\nCircularBuffer.prototype.clear()\n    Clears a buffer.\n\n    Returns\n    -------\n    out: Object\n        Circular buffer instance.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.push( 'foo' );\n    > b.push( 'bar' );\n    > b.push( 'beep' );\n    > b.count\n    3\n    > b.clear();\n    > b.count\n    0","CircularBuffer.prototype.count":"\nCircularBuffer.prototype.count\n    Read-only property returning the number of elements currently in the buffer.\n\n    Returns\n    -------\n    out: integer\n        Number of elements currently in the buffer.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.count\n    0\n    > b.push( 'foo' );\n    > b.count\n    1\n    > b.push( 'bar' );\n    > b.count\n    2","CircularBuffer.prototype.full":"\nCircularBuffer.prototype.full\n    Read-only property returning a boolean indicating whether a circular buffer\n    is full.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether a circular buffer is full.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.full\n    false\n    > b.push( 'foo' );\n    > b.push( 'bar' );\n    > b.push( 'beep' );\n    > b.full\n    true","CircularBuffer.prototype.iterator":"\nCircularBuffer.prototype.iterator( [niters] )\n    Returns an iterator for iterating over a circular buffer.\n\n    A returned iterator does not iterate over partially full buffers.\n\n    Parameters\n    ----------\n    niters: integer (optional)\n        Number of iterations. Default: infinity.\n\n    Returns\n    -------\n    out: Iterator\n        Iterator.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.push( 'foo' );\n    > b.push( 'bar' );\n    > b.push( 'beep' );\n    > b.push( 'boop' );\n    > var it = b.iterator( b.length );\n    > var v = it.next().value\n    'bar'\n    > v = it.next().value\n    'beep'\n    > v = it.next().value\n    'boop'\n    > var bool = it.next().done\n    true","CircularBuffer.prototype.length":"\nCircularBuffer.prototype.length\n    Read-only property returning the buffer length (i.e., capacity).\n\n    Returns\n    -------\n    out: integer\n        Buffer length.\n\n    Examples\n    --------\n    > var b = CircularBuffer( [ 0, 0, 0 ] );\n    > var len = b.length\n    3","CircularBuffer.prototype.push":"\nCircularBuffer.prototype.push( value )\n    Adds a value to a circular buffer.\n\n    Parameters\n    ----------\n    value: any\n        Value to add.\n\n    Returns\n    -------\n    out: any\n        Removed element (or undefined).\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.push( 'foo' )\n    undefined\n    > b.push( 'bar' )\n    undefined\n    > b.push( 'beep' )\n    undefined\n    > b.push( 'boop' )\n    'foo'","CircularBuffer.prototype.toArray":"\nCircularBuffer.prototype.toArray()\n    Returns an array of circular buffer values.\n\n    Returns\n    -------\n    out: Array\n        Circular buffer values.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.push( 'foo' );\n    > b.push( 'bar' );\n    > b.push( 'beep' );\n    > b.push( 'boop' );\n    > var vals = b.toArray()\n    [ 'bar', 'beep', 'boop' ]","CircularBuffer.prototype.toJSON":"\nCircularBuffer.prototype.toJSON()\n    Serializes a circular buffer as JSON.\n\n    Returns\n    -------\n    out: Object\n        Serialized circular buffer.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.push( 'foo' );\n    > b.push( 'bar' );\n    > b.push( 'beep' );\n    > b.push( 'boop' );\n    > var o = b.toJSON()\n    {'type':'circular-buffer','length':3,'data':['bar','beep','boop']}\n\n    See Also\n    --------\n    FIFO, Stack","close":"\nclose( fd, clbk )\n    Asynchronously closes a file descriptor, so that the file descriptor no\n    longer refers to any file and may be reused.\n\n    Parameters\n    ----------\n    fd: integer\n        File descriptor.\n\n    clbk: Function\n        Callback to invoke upon closing a file descriptor.\n\n    Examples\n    --------\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     }\n    ... };\n    > var fd = open.sync( './beep/boop.js', 'r+' );\n    > if ( !isError( fd ) ) { close( fd, done ); };\n\n\nclose.sync( fd )\n    Synchronously closes a file descriptor.\n\n    Parameters\n    ----------\n    fd: integer\n        File descriptor.\n\n    Returns\n    -------\n    out: Error|void\n        If an error occurs, an error object; otherwise, undefined.\n\n    Examples\n    --------\n    > var fd = open.sync( './beep/boop.js', 'r+' );\n    > if ( !isError( fd ) ) { close.sync( fd ); };\n\n    See Also\n    --------\n    exists, open, readFile\n","close.sync":"\nclose.sync( fd )\n    Synchronously closes a file descriptor.\n\n    Parameters\n    ----------\n    fd: integer\n        File descriptor.\n\n    Returns\n    -------\n    out: Error|void\n        If an error occurs, an error object; otherwise, undefined.\n\n    Examples\n    --------\n    > var fd = open.sync( './beep/boop.js', 'r+' );\n    > if ( !isError( fd ) ) { close.sync( fd ); };\n\n    See Also\n    --------\n    exists, open, readFile","CMUDICT":"\nCMUDICT( [options] )\n    Returns datasets from the Carnegie Mellon Pronouncing Dictionary (CMUdict).\n\n    Data includes the following:\n\n    - dict: the main pronouncing dictionary.\n    - phones: manners of articulation for each sound.\n    - symbols: complete list of ARPABET symbols used by the dictionary.\n    - vp: verbal pronunciations of punctuation marks.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.data: string (optional)\n        Dataset name.\n\n    Returns\n    -------\n    out: Object|Array\n        CMUdict dataset.\n\n    Examples\n    --------\n    > var data = CMUDICT();\n    > var dict = data.dict\n    {...}\n    > var phones = data.phones\n    {...}\n    > var symbols = data.symbols\n    [...]\n    > var vp = data.vp\n    {...}\n\n","codePointAt":"\ncodePointAt( str, idx[, backward] )\n    Returns a Unicode code point from a string at a specified position.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    idx: integer\n        Position. If less than `0`, the string position is determined relative\n        to the end of the input string.\n\n    backward: boolean (optional)\n        Backward iteration for low surrogates. Default: false.\n\n    Returns\n    -------\n    out: integer\n        Unicode code point.\n\n    Examples\n    --------\n    > var out = codePointAt( 'last man standing', 4 )\n    32\n    > out = codePointAt( 'presidential election', 8, true )\n    116\n    > out = codePointAt( 'अनुच्छेद', 2 )\n    2369\n    > out = codePointAt( '🌷', 1, true )\n    127799\n\n    See Also\n    --------\n    fromCodePoint","commonKeys":"\ncommonKeys( obj1, obj2[, ...obj] )\n    Returns the common own property names of two or more objects.\n\n    Parameters\n    ----------\n    obj1: any\n        First object.\n\n    obj2: any\n        Second object.\n\n    obj: ...any (optional)\n        Additional objects.\n\n    Returns\n    -------\n    out: Array<string>\n        Common keys of objects.\n\n    Examples\n    --------\n    > var obj1 = { 'a': 1, 'b': 2 };\n    > var obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\n    > var keys = commonKeys( obj1, obj2 )\n    [ 'a', 'b' ]\n\n    See Also\n    --------\n    commonKeysIn, objectKeys","commonKeysIn":"\ncommonKeysIn( obj1, obj2[, ...obj] )\n    Returns the common own and inherited property names of two or more objects.\n\n    Parameters\n    ----------\n    obj1: any\n        First object.\n\n    obj2: any\n        Second object.\n\n    obj: ...any (optional)\n        Additional objects.\n\n    Returns\n    -------\n    out: Array<string>\n        Common keys.\n\n    Examples\n    --------\n    > var obj1 = { 'a': 1, 'b': 2 };\n    > var obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\n    > var keys = commonKeysIn( obj1, obj2 )\n    [ 'a', 'b' ]\n\n    See Also\n    --------\n    commonKeys, keysIn","complex":"\ncomplex( real, imag[, dtype] )\n    Creates a complex number.\n\n    The function supports the following data types:\n\n    - float64\n    - float32\n\n    Parameters\n    ----------\n    real: number\n        Real component.\n\n    imag: number\n        Imaginary component.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    z: Complex\n        Complex number.\n\n    Examples\n    --------\n    > var z = complex( 5.0, 3.0, 'float64' )\n    <Complex128>\n    > z = complex( 5.0, 3.0, 'float32' )\n    <Complex64>\n\n    See Also\n    --------\n    Complex128, Complex64\n","Complex64":"\nComplex64( real, imag )\n    64-bit complex number constructor.\n\n    Both the real and imaginary components are stored as single-precision\n    floating-point numbers.\n\n    Parameters\n    ----------\n    real: number\n        Real component.\n\n    imag: number\n        Imaginary component.\n\n    Returns\n    -------\n    z: Complex64\n        64-bit complex number.\n\n    z.re: number\n        Read-only property returning the real component.\n\n    z.im: number\n        Read-only property returning the imaginary component.\n\n    Examples\n    --------\n    > var z = new Complex64( 5.0, 3.0 )\n    <Complex64>\n    > z.re\n    5.0\n    > z.im\n    3.0\n\n\nComplex64.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n\n    Returns\n    -------\n    v: integer\n        Size (in bytes) of each component.\n\n    Examples\n    --------\n    > var s = Complex64.BYTES_PER_ELEMENT\n    4\n\n\nComplex64.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n\n    Returns\n    -------\n    s: integer\n        Size (in bytes) of each component.\n\n    Examples\n    --------\n    > var z = new Complex64( 5.0, 3.0 )\n    <Complex64>\n    > var s = z.BYTES_PER_ELEMENT\n    4\n\n\nComplex64.prototype.byteLength\n    Length (in bytes) of a complex number.\n\n    Returns\n    -------\n    len: integer\n        Length (in bytes) of a complex number.\n\n    Examples\n    --------\n    > var z = new Complex64( 5.0, 3.0 )\n    <Complex64>\n    > var s = z.byteLength\n    8\n\n    See Also\n    --------\n    complex, Complex128\n","Complex64.BYTES_PER_ELEMENT":"\nComplex64.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n\n    Returns\n    -------\n    v: integer\n        Size (in bytes) of each component.\n\n    Examples\n    --------\n    > var s = Complex64.BYTES_PER_ELEMENT\n    4","Complex64.prototype.BYTES_PER_ELEMENT":"\nComplex64.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n\n    Returns\n    -------\n    s: integer\n        Size (in bytes) of each component.\n\n    Examples\n    --------\n    > var z = new Complex64( 5.0, 3.0 )\n    <Complex64>\n    > var s = z.BYTES_PER_ELEMENT\n    4","Complex64.prototype.byteLength":"\nComplex64.prototype.byteLength\n    Length (in bytes) of a complex number.\n\n    Returns\n    -------\n    len: integer\n        Length (in bytes) of a complex number.\n\n    Examples\n    --------\n    > var z = new Complex64( 5.0, 3.0 )\n    <Complex64>\n    > var s = z.byteLength\n    8\n\n    See Also\n    --------\n    complex, Complex128","COMPLEX64_NAN":"\nCOMPLEX64_NAN\n    Canonical single-precision complex floating-point NaN.\n\n    Examples\n    --------\n    > COMPLEX64_NAN\n    <Complex64>\n\n    See Also\n    --------\n    COMPLEX128_NAN\n","COMPLEX64_NUM_BYTES":"\nCOMPLEX64_NUM_BYTES\n    Size (in bytes) of a 64-bit complex number.\n\n    Examples\n    --------\n    > COMPLEX64_NUM_BYTES\n    8\n\n    See Also\n    --------\n    COMPLEX128_NUM_BYTES, FLOAT32_NUM_BYTES\n","COMPLEX64_ZERO":"\nCOMPLEX64_ZERO\n    Single-precision complex floating-point zero.\n\n    Examples\n    --------\n    > COMPLEX64_ZERO\n    <Complex64>\n\n    See Also\n    --------\n    COMPLEX128_ZERO\n","Complex64Array":"\nComplex64Array()\n    A 64-bit complex number array.\n\n    Returns\n    -------\n    out: Complex64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Complex64Array()\n    <Complex64Array>\n\n\nComplex64Array( length )\n    Creates a 64-bit complex number array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: Complex64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 10 )\n    <Complex64Array>\n    > var len = arr.length\n    10\n\n\nComplex64Array( complexarray )\n    Creates a 64-bit complex number array from another complex number array.\n\n    Parameters\n    ----------\n    complexarray: Complex64Array\n        Complex array from which to generate another complex array.\n\n    Returns\n    -------\n    out: Complex64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var arr2 = new Complex64Array( arr1 )\n    <Complex64Array>\n    > var len = arr2.length\n    2\n\n\nComplex64Array( typedarray )\n    Creates a 64-bit complex number array from a typed array\n    containing interleaved real and imaginary components.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate complex array.\n\n    Returns\n    -------\n    out: Complex64Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new Float32Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Float32Array>\n    > var arr = new Complex64Array( buf )\n    <Complex64Array>\n    > var len = arr.length\n    2\n\n\nComplex64Array( obj )\n    Creates a 64-bit complex number array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a complex array.\n\n    Returns\n    -------\n    out: Complex64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var len = arr1.length\n    2\n    > var buf = [ new Complex64( 1.0, -1.0 ), new Complex64( 2.0, -2.0 )];\n    > var arr2 = new Complex64Array( buf )\n    <Complex64Array>\n    > len = arr2.length\n    2\n\n\nComplex64Array( buffer[, byteOffset[, length]] )\n    Returns a 64-bit complex number array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Complex64Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 240 );\n    > var arr1 = new Complex64Array( buf )\n    <Complex64Array>\n    > var len = arr1.length\n    30\n    > var arr2 = new Complex64Array( buf, 8 )\n    <Complex64Array>\n    > len = arr2.length\n    29\n    > var arr3 = new Complex64Array( buf, 8, 20 )\n    <Complex64Array>\n    > len = arr3.length\n    20\n\n\nComplex64Array.from( src[, clbk[, thisArg]] )\n    Creates a new 64-bit complex number array from an array-like object or an\n    iterable.\n\n    A callback function is provided two arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    clbk: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n    \n    Returns\n    -------\n    out: Complex64Array\n        A typed array.\n    \n    Examples\n    --------\n    > function clbkFcn( v ) { return v * 2.0 };\n    > var arr = Complex64Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\n    <Complex64Array>\n    > var len = arr.length\n    2\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    -2.0\n\n\nComplex64Array.of( element0[, element1[, ...elementN]] )\n    Creates a new 64-bit complex number array from a variable number of\n    arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Complex64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Complex64Array.of( 1.0, -1.0, 2.0, -2.0 )\n    <Complex64Array>\n    > var len = arr.length\n    2\n    > var z1 = new Complex64( 1.0, -1.0 );\n    > var z2 = new Complex64( 2.0, -2.0 );\n    > arr = Complex64Array.of( z1, z2 )\n    <Complex64Array>\n    > len = arr.length\n    2\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    -1.0\n\n\nComplex64Array.BYTES_PER_ELEMENT\n    The size of each array element in bytes.\n\n    Examples\n    --------\n    > var nbytes = Complex64Array.BYTES_PER_ELEMENT\n    8\n\n\nComplex64Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > var str = Complex64Array.name\n    'Complex64Array'\n\n\nComplex64Array.prototype.buffer\n    Pointer to the underlying data buffer.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 2 )\n    <Complex64Array>\n    > var buf = arr.buffer\n    <ArrayBuffer>\n\n\nComplex64Array.prototype.byteLength\n    Length of the array in bytes.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 10 )\n    <Complex64Array>\n    > var nbytes = arr.byteLength\n    80\n\n\nComplex64Array.prototype.byteOffset\n    Offset (in bytes) of the array from the start of its underlying\n    ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 5 )\n    <Complex64Array>\n    > var offset = arr.byteOffset\n    0\n    > var buf = new ArrayBuffer( 240 );\n    > arr = new Complex64Array( buf, 64 )\n    <Complex64Array>\n    > offset = arr.byteOffset\n    64\n\n\nComplex64Array.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 10 )\n    <Complex64Array>\n    > arr.BYTES_PER_ELEMENT\n    8\n\n\nComplex64Array.prototype.length\n    The number of array elements.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 10 )\n    <Complex64Array>\n    > var len = arr.length\n    10\n\n\nComplex64Array.prototype.at( i )\n    Returns an array element located at integer position (index) `i`, with\n    support for noth nonnegative and negative integer positions.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n\n    Returns\n    -------\n    out: Complex64|void\n        An array element.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var z = arr.at( 1 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    -2.0\n\n\nComplex64Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n    \n    start: integer\n        Source start index position.\n    \n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Complex64Array\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex64Array>\n    > arr.copyWithin( 0, 2 )\n    <Complex64Array>\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    -3.0\n\n\nComplex64Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var it = arr.entries();\n    > var v = it.next().value\n    [ 0, <Complex64> ]\n    > var re = realf( v[ 1 ] )\n    1.0\n    > var im = imagf( v[ 1 ] )\n    -1.0\n    > v = it.next().value\n    [ 1, <Complex64> ]\n    > re = realf( v[ 1 ] )\n    2.0\n    > im = imagf( v[ 1 ] )\n    -2.0\n    > v = it.next().value\n    [ 2, <Complex64> ]\n    > re = realf( v[ 1 ] )\n    3.0\n    > im = imagf( v[ 1 ] )\n    -3.0\n    > var bool = it.next().done\n    true\n\n\nComplex64Array.prototype.every( predicate[, thisArg] )\n    Returns a boolean indicating whether all elements in the array pass a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all elements pass the test.\n\n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) > 0.0 ); };\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var bool = arr.every( predicate )\n    true\n\n\nComplex64Array.prototype.fill( value[, start[, end]] )\n    Returns a modified typed array filled with a fill value.\n\n    Parameters\n    ----------\n    value: Complex64\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Complex64Array\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( 3 )\n    <Complex64Array>\n    > arr.fill( new Complex64( 1.0, 1.0 ) );\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    1.0\n    > z = arr.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    1.0\n    > im = imagf( z )\n    1.0\n    > z = arr.get( 2 )\n    <Complex64>\n    > re = realf( z )\n    1.0\n    > im = imagf( z )\n    1.0\n\n\nComplex64Array.prototype.filter( predicate[, thisArg] )\n    Returns a new array containing the elements of an array which pass a test\n    implemented by a predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Complex64Array\n        A new typed array.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var out = arr.filter( predicate )\n    <Complex64Array>\n    > var len = out.length\n    1\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    2.0\n\n\nComplex64Array.prototype.find( predicate[, thisArg] )\n    Returns the first element in an array for which a predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    out: Complex64|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var z = arr.find( predicate )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    1.0\n\n\nComplex64Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var idx = arr.findIndex( predicate )\n    0\n\n\nComplex64Array.prototype.findLast( predicate[, thisArg] )\n    Returns the last element in an array for which a predicate function returns\n    a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.  \n    \n    Returns\n    -------\n    out: Complex64|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var z = arr.findLast( predicate )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    2.0\n\n\nComplex64Array.prototype.findLastIndex( predicate[, thisArg] )\n    Returns the index of the last element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var idx = arr.findLastIndex( predicate )\n    1\n\n\nComplex64Array.prototype.forEach( clbk[, thisArg] )\n    Invokes a function once for each array element.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Examples\n    --------\n    > var str = '%';\n    > function clbk( v ) { str += v.toString() + '%'; };\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > arr.forEach( clbk );\n    > str\n    '%1 - 1i%2 - 2i%'\n\n\nComplex64Array.prototype.get( i )\n    Returns an array element located at integer position (index) `i`.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n    \n    Returns\n    -------\n    out: Complex64|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var z = arr.get( 1 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    -2.0\n\n\nComplex64Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a provided value.\n\n    Parameters\n    ----------\n    searchElement: Complex64\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n    \n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex64Array>\n    > var bool = arr.includes( new Complex64( 3.0, -3.0 ) )\n    true\n    > bool = arr.includes( new Complex64( 3.0, -3.0 ), 3 )\n    false\n\n\nComplex64Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the first index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: Complex64\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex64Array>\n    > var idx = arr.indexOf( new Complex64( 3.0, -3.0 ) )\n    2\n    > idx = arr.indexOf( new Complex64( 3.0, -3.0 ), 3 )\n    -1\n\n\nComplex64Array.prototype.join( [separator] )\n    Returns a new string by concatenating all array elements separated by a\n    separator string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        Separator string. Default: ','.\n    \n    Returns\n    -------\n    out: string\n        Array serialized as a string.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var str = arr.join()\n    '1 - 1i,2 - 2i'\n    > str = arr.join( '/' )\n    '1 - 1i/2 - 2i'\n\n\nComplex64Array.prototype.keys()\n    Returns an iterator for iterating over each index key in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array index keys.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var it = arr.keys();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().done\n    true\n\n\nComplex64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the last index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: Complex64\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: out.length-1.\n    \n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex64Array>\n    > var idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ) )\n    3\n    > idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ), 2 )\n    0\n\n\nComplex64Array.prototype.map( clbk[, thisArg] )\n    Returns a new array with each element being the result of a provided\n    callback function.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Complex64Array\n        A new typed array.\n    \n    Examples\n    --------\n    > function clbk( v ) { return v; };\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var out = arr.map( clbk )\n    <Complex64Array>\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    -1.0\n    > z = out.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    -2.0\n\n\nComplex64Array.prototype.reduce( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in order, passing\n    in the return value from the calculation on the preceding element and\n    returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.    \n\n    initialValue: any (optional)\n        Initial accumulation value.\n    \n    Returns\n    -------\n    out: any\n        Accumulated result.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var z = arr.reduce( base.caddf )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    -3.0\n\n\nComplex64Array.prototype.reduceRight( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in reverse order,\n    passing in the return value from the calculation on the preceding element\n    and returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.\n\n    initialValue: any (optional)\n        Initial accumulation value.\n    \n    Returns\n    -------\n    out: any\n        Accumulated result.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var z = arr.reduceRight( base.caddf )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    -3.0\n\n\nComplex64Array.prototype.reverse()\n    Reverses the array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Complex64Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > arr.reverse();\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    -3.0\n    > z = arr.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    -2.0\n    > z = arr.get( 2 )\n    <Complex64>\n    > re = realf( z )\n    1.0\n    > im = imagf( z )\n    -1.0\n\n\nComplex64Array.prototype.set( z[, i] )\n    Sets one or more array elements.\n\n    If provided a single argument, the method sets array elements starting at\n    position (index) `i = 0`. To set elements starting elsewhere in the array,\n    provide an index argument `i`.\n\n    To set one or more array elements, provide an array-like object containing\n    either complex numbers or interleaved real and imaginary components.\n\n    Parameters\n    ----------\n    z: Complex64|Complex64Array|ArrayLikeObject\n        Complex number or complex number array.\n\n    i: integer (optional)\n        Array index at which to start setting elements. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 2 )\n    <Complex64Array>\n    > arr.set( new Complex64( 1.0, -1.0 ) );\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    -1.0\n    > arr.set( new Complex64( 2.0, -2.0 ), 1 );\n    > z = arr.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    -2.0\n\n\nComplex64Array.prototype.slice( [start[, end]] )\n    Copies a portion of a typed array to a new typed array.\n\n    Parameters\n    ----------\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n    \n    Returns\n    -------\n    out: Complex64Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var out = arr.slice( 1 )\n    <Complex64Array>\n    > var len = out.length\n    2\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    -2.0\n    > z = out.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    -3.0\n\n\nComplex64Array.prototype.some( predicate[, thisArg] )\n    Returns a boolean indicating whether at least one element passes a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n    \n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one element passes the test.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var bool = arr.some( predicate )\n    true\n\n\nComplex64Array.prototype.sort( compareFunction )\n    Sorts an array in-place.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first element for comparison.\n    - b: second element for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFunction: Function\n        Comparison function.\n    \n    Returns\n    -------\n    out: Complex64Array\n        Modified array.\n    \n    Examples\n    --------\n    > function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\n    > var arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex64Array>\n    > arr.sort( compare );\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    -1.0\n    > z = arr.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    -2.0\n    > z = arr.get( 2 )\n    <Complex64>\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    -3.0\n\n\nComplex64Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array view over the same underlying `ArrayBuffer` and\n    with the same underlying data type as the host array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Complex64Array\n        New typed array view.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex64Array>\n    > var out = arr.subarray( 1, 3 )\n    <Complex64Array>\n    > var len = out.length\n    2\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    -2.0\n    > z = out.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    -3.0\n\n\nComplex64Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array (optional)\n        Locale identifier(s).\n    \n    options: Object (optional)\n        An object containing serialization options.\n    \n    Returns\n    -------\n    str: string\n        Local-specific string.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0 ] )\n    <Complex64Array>\n    > var str = arr.toLocaleString()\n    '1 + 1i,2 + 2i'\n\n\nComplex64Array.prototype.toReversed()\n    Returns a new typed array containing the elements in reversed order.\n\n    Returns\n    -------\n    out: Complex64Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\n    <Complex64Array>\n    > var out = arr.toReversed()\n    <Complex64Array>\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    3.0\n    > z = out.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    2.0\n    > z = out.get( 2 )\n    <Complex64>\n    > re = realf( z )\n    1.0\n    > im = imagf( z )\n    1.0\n\n\nComplex64Array.prototype.toSorted( compareFcn )\n    Returns a new typed array containing the elements in sorted order.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first element for comparison.\n    - b: second element for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFcn: Function\n        Comparison function.\n    \n    Returns\n    -------\n    out: Complex64Array\n        New typed array.\n    \n    Examples\n    --------\n    > function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\n    > var arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex64Array>\n    > var out = arr.toSorted( compare );\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    -1.0\n    > z = out.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    -2.0\n    > z = out.get( 2 )\n    <Complex64>\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    -3.0\n\n\nComplex64Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        String serialization of the array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\n    <Complex64Array>\n    > var str = arr.toString()\n    '1 + 1i,2 - 2i,3 + 3i'\n\n\nComplex64Array.prototype.values()\n    Returns an iterator for iterating over each value in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array values.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var it = arr.values();\n    > var v = it.next().value\n    <Complex64>\n    > var re = realf( v )\n    1.0\n    > var im = imagf( v )\n    -1.0\n    > v = it.next().value\n    <Complex64>\n    > re = realf( v )\n    2.0\n    > im = imagf( v )\n    -2.0\n    > var bool = it.next().done\n    true\n\n\nComplex64Array.prototype.with( index, value )\n    Returns a new typed array with the element at a provided index replaced\n    with a provided value.\n\n    Parameters\n    ----------\n    index: integer\n        Element index.\n    \n    value: Complex64\n        Element value.  \n\n    Returns\n    -------\n    out: Complex64Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n    <Complex64Array>\n    > var z = out.get( 1 )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    -3.0\n\n\n    See Also\n    --------\n    Complex128Array, complex, Complex64","Complex64Array.from":"\nComplex64Array.from( src[, clbk[, thisArg]] )\n    Creates a new 64-bit complex number array from an array-like object or an\n    iterable.\n\n    A callback function is provided two arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    clbk: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n    \n    Returns\n    -------\n    out: Complex64Array\n        A typed array.\n    \n    Examples\n    --------\n    > function clbkFcn( v ) { return v * 2.0 };\n    > var arr = Complex64Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\n    <Complex64Array>\n    > var len = arr.length\n    2\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    -2.0","Complex64Array.of":"\nComplex64Array.of( element0[, element1[, ...elementN]] )\n    Creates a new 64-bit complex number array from a variable number of\n    arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Complex64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Complex64Array.of( 1.0, -1.0, 2.0, -2.0 )\n    <Complex64Array>\n    > var len = arr.length\n    2\n    > var z1 = new Complex64( 1.0, -1.0 );\n    > var z2 = new Complex64( 2.0, -2.0 );\n    > arr = Complex64Array.of( z1, z2 )\n    <Complex64Array>\n    > len = arr.length\n    2\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    -1.0","Complex64Array.BYTES_PER_ELEMENT":"\nComplex64Array.BYTES_PER_ELEMENT\n    The size of each array element in bytes.\n\n    Examples\n    --------\n    > var nbytes = Complex64Array.BYTES_PER_ELEMENT\n    8","Complex64Array.name":"\nComplex64Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > var str = Complex64Array.name\n    'Complex64Array'","Complex64Array.prototype.buffer":"\nComplex64Array.prototype.buffer\n    Pointer to the underlying data buffer.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 2 )\n    <Complex64Array>\n    > var buf = arr.buffer\n    <ArrayBuffer>","Complex64Array.prototype.byteLength":"\nComplex64Array.prototype.byteLength\n    Length of the array in bytes.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 10 )\n    <Complex64Array>\n    > var nbytes = arr.byteLength\n    80","Complex64Array.prototype.byteOffset":"\nComplex64Array.prototype.byteOffset\n    Offset (in bytes) of the array from the start of its underlying\n    ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 5 )\n    <Complex64Array>\n    > var offset = arr.byteOffset\n    0\n    > var buf = new ArrayBuffer( 240 );\n    > arr = new Complex64Array( buf, 64 )\n    <Complex64Array>\n    > offset = arr.byteOffset\n    64","Complex64Array.prototype.BYTES_PER_ELEMENT":"\nComplex64Array.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 10 )\n    <Complex64Array>\n    > arr.BYTES_PER_ELEMENT\n    8","Complex64Array.prototype.length":"\nComplex64Array.prototype.length\n    The number of array elements.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 10 )\n    <Complex64Array>\n    > var len = arr.length\n    10","Complex64Array.prototype.at":"\nComplex64Array.prototype.at( i )\n    Returns an array element located at integer position (index) `i`, with\n    support for noth nonnegative and negative integer positions.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n\n    Returns\n    -------\n    out: Complex64|void\n        An array element.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var z = arr.at( 1 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    -2.0","Complex64Array.prototype.copyWithin":"\nComplex64Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n    \n    start: integer\n        Source start index position.\n    \n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Complex64Array\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex64Array>\n    > arr.copyWithin( 0, 2 )\n    <Complex64Array>\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    -3.0","Complex64Array.prototype.entries":"\nComplex64Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var it = arr.entries();\n    > var v = it.next().value\n    [ 0, <Complex64> ]\n    > var re = realf( v[ 1 ] )\n    1.0\n    > var im = imagf( v[ 1 ] )\n    -1.0\n    > v = it.next().value\n    [ 1, <Complex64> ]\n    > re = realf( v[ 1 ] )\n    2.0\n    > im = imagf( v[ 1 ] )\n    -2.0\n    > v = it.next().value\n    [ 2, <Complex64> ]\n    > re = realf( v[ 1 ] )\n    3.0\n    > im = imagf( v[ 1 ] )\n    -3.0\n    > var bool = it.next().done\n    true","Complex64Array.prototype.every":"\nComplex64Array.prototype.every( predicate[, thisArg] )\n    Returns a boolean indicating whether all elements in the array pass a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all elements pass the test.\n\n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) > 0.0 ); };\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var bool = arr.every( predicate )\n    true","Complex64Array.prototype.fill":"\nComplex64Array.prototype.fill( value[, start[, end]] )\n    Returns a modified typed array filled with a fill value.\n\n    Parameters\n    ----------\n    value: Complex64\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Complex64Array\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( 3 )\n    <Complex64Array>\n    > arr.fill( new Complex64( 1.0, 1.0 ) );\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    1.0\n    > z = arr.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    1.0\n    > im = imagf( z )\n    1.0\n    > z = arr.get( 2 )\n    <Complex64>\n    > re = realf( z )\n    1.0\n    > im = imagf( z )\n    1.0","Complex64Array.prototype.filter":"\nComplex64Array.prototype.filter( predicate[, thisArg] )\n    Returns a new array containing the elements of an array which pass a test\n    implemented by a predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Complex64Array\n        A new typed array.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var out = arr.filter( predicate )\n    <Complex64Array>\n    > var len = out.length\n    1\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    2.0","Complex64Array.prototype.find":"\nComplex64Array.prototype.find( predicate[, thisArg] )\n    Returns the first element in an array for which a predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    out: Complex64|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var z = arr.find( predicate )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    1.0","Complex64Array.prototype.findIndex":"\nComplex64Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var idx = arr.findIndex( predicate )\n    0","Complex64Array.prototype.findLast":"\nComplex64Array.prototype.findLast( predicate[, thisArg] )\n    Returns the last element in an array for which a predicate function returns\n    a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.  \n    \n    Returns\n    -------\n    out: Complex64|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var z = arr.findLast( predicate )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    2.0","Complex64Array.prototype.findLastIndex":"\nComplex64Array.prototype.findLastIndex( predicate[, thisArg] )\n    Returns the index of the last element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var idx = arr.findLastIndex( predicate )\n    1","Complex64Array.prototype.forEach":"\nComplex64Array.prototype.forEach( clbk[, thisArg] )\n    Invokes a function once for each array element.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Examples\n    --------\n    > var str = '%';\n    > function clbk( v ) { str += v.toString() + '%'; };\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > arr.forEach( clbk );\n    > str\n    '%1 - 1i%2 - 2i%'","Complex64Array.prototype.get":"\nComplex64Array.prototype.get( i )\n    Returns an array element located at integer position (index) `i`.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n    \n    Returns\n    -------\n    out: Complex64|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var z = arr.get( 1 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    -2.0","Complex64Array.prototype.includes":"\nComplex64Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a provided value.\n\n    Parameters\n    ----------\n    searchElement: Complex64\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n    \n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex64Array>\n    > var bool = arr.includes( new Complex64( 3.0, -3.0 ) )\n    true\n    > bool = arr.includes( new Complex64( 3.0, -3.0 ), 3 )\n    false","Complex64Array.prototype.indexOf":"\nComplex64Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the first index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: Complex64\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex64Array>\n    > var idx = arr.indexOf( new Complex64( 3.0, -3.0 ) )\n    2\n    > idx = arr.indexOf( new Complex64( 3.0, -3.0 ), 3 )\n    -1","Complex64Array.prototype.join":"\nComplex64Array.prototype.join( [separator] )\n    Returns a new string by concatenating all array elements separated by a\n    separator string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        Separator string. Default: ','.\n    \n    Returns\n    -------\n    out: string\n        Array serialized as a string.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var str = arr.join()\n    '1 - 1i,2 - 2i'\n    > str = arr.join( '/' )\n    '1 - 1i/2 - 2i'","Complex64Array.prototype.keys":"\nComplex64Array.prototype.keys()\n    Returns an iterator for iterating over each index key in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array index keys.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var it = arr.keys();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().done\n    true","Complex64Array.prototype.lastIndexOf":"\nComplex64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the last index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: Complex64\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: out.length-1.\n    \n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex64Array>\n    > var idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ) )\n    3\n    > idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ), 2 )\n    0","Complex64Array.prototype.map":"\nComplex64Array.prototype.map( clbk[, thisArg] )\n    Returns a new array with each element being the result of a provided\n    callback function.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Complex64Array\n        A new typed array.\n    \n    Examples\n    --------\n    > function clbk( v ) { return v; };\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var out = arr.map( clbk )\n    <Complex64Array>\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    -1.0\n    > z = out.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    -2.0","Complex64Array.prototype.reduce":"\nComplex64Array.prototype.reduce( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in order, passing\n    in the return value from the calculation on the preceding element and\n    returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.    \n\n    initialValue: any (optional)\n        Initial accumulation value.\n    \n    Returns\n    -------\n    out: any\n        Accumulated result.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var z = arr.reduce( base.caddf )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    -3.0","Complex64Array.prototype.reduceRight":"\nComplex64Array.prototype.reduceRight( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in reverse order,\n    passing in the return value from the calculation on the preceding element\n    and returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.\n\n    initialValue: any (optional)\n        Initial accumulation value.\n    \n    Returns\n    -------\n    out: any\n        Accumulated result.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var z = arr.reduceRight( base.caddf )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    -3.0","Complex64Array.prototype.reverse":"\nComplex64Array.prototype.reverse()\n    Reverses the array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Complex64Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > arr.reverse();\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    -3.0\n    > z = arr.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    -2.0\n    > z = arr.get( 2 )\n    <Complex64>\n    > re = realf( z )\n    1.0\n    > im = imagf( z )\n    -1.0","Complex64Array.prototype.set":"\nComplex64Array.prototype.set( z[, i] )\n    Sets one or more array elements.\n\n    If provided a single argument, the method sets array elements starting at\n    position (index) `i = 0`. To set elements starting elsewhere in the array,\n    provide an index argument `i`.\n\n    To set one or more array elements, provide an array-like object containing\n    either complex numbers or interleaved real and imaginary components.\n\n    Parameters\n    ----------\n    z: Complex64|Complex64Array|ArrayLikeObject\n        Complex number or complex number array.\n\n    i: integer (optional)\n        Array index at which to start setting elements. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 2 )\n    <Complex64Array>\n    > arr.set( new Complex64( 1.0, -1.0 ) );\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    -1.0\n    > arr.set( new Complex64( 2.0, -2.0 ), 1 );\n    > z = arr.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    -2.0","Complex64Array.prototype.slice":"\nComplex64Array.prototype.slice( [start[, end]] )\n    Copies a portion of a typed array to a new typed array.\n\n    Parameters\n    ----------\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n    \n    Returns\n    -------\n    out: Complex64Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var out = arr.slice( 1 )\n    <Complex64Array>\n    > var len = out.length\n    2\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    -2.0\n    > z = out.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    -3.0","Complex64Array.prototype.some":"\nComplex64Array.prototype.some( predicate[, thisArg] )\n    Returns a boolean indicating whether at least one element passes a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n    \n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one element passes the test.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var bool = arr.some( predicate )\n    true","Complex64Array.prototype.sort":"\nComplex64Array.prototype.sort( compareFunction )\n    Sorts an array in-place.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first element for comparison.\n    - b: second element for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFunction: Function\n        Comparison function.\n    \n    Returns\n    -------\n    out: Complex64Array\n        Modified array.\n    \n    Examples\n    --------\n    > function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\n    > var arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex64Array>\n    > arr.sort( compare );\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    -1.0\n    > z = arr.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    -2.0\n    > z = arr.get( 2 )\n    <Complex64>\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    -3.0","Complex64Array.prototype.subarray":"\nComplex64Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array view over the same underlying `ArrayBuffer` and\n    with the same underlying data type as the host array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Complex64Array\n        New typed array view.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex64Array>\n    > var out = arr.subarray( 1, 3 )\n    <Complex64Array>\n    > var len = out.length\n    2\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    -2.0\n    > z = out.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    -3.0","Complex64Array.prototype.toLocaleString":"\nComplex64Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array (optional)\n        Locale identifier(s).\n    \n    options: Object (optional)\n        An object containing serialization options.\n    \n    Returns\n    -------\n    str: string\n        Local-specific string.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0 ] )\n    <Complex64Array>\n    > var str = arr.toLocaleString()\n    '1 + 1i,2 + 2i'","Complex64Array.prototype.toReversed":"\nComplex64Array.prototype.toReversed()\n    Returns a new typed array containing the elements in reversed order.\n\n    Returns\n    -------\n    out: Complex64Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\n    <Complex64Array>\n    > var out = arr.toReversed()\n    <Complex64Array>\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    3.0\n    > z = out.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    2.0\n    > z = out.get( 2 )\n    <Complex64>\n    > re = realf( z )\n    1.0\n    > im = imagf( z )\n    1.0","Complex64Array.prototype.toSorted":"\nComplex64Array.prototype.toSorted( compareFcn )\n    Returns a new typed array containing the elements in sorted order.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first element for comparison.\n    - b: second element for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFcn: Function\n        Comparison function.\n    \n    Returns\n    -------\n    out: Complex64Array\n        New typed array.\n    \n    Examples\n    --------\n    > function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\n    > var arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex64Array>\n    > var out = arr.toSorted( compare );\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    -1.0\n    > z = out.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    -2.0\n    > z = out.get( 2 )\n    <Complex64>\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    -3.0","Complex64Array.prototype.toString":"\nComplex64Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        String serialization of the array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\n    <Complex64Array>\n    > var str = arr.toString()\n    '1 + 1i,2 - 2i,3 + 3i'","Complex64Array.prototype.values":"\nComplex64Array.prototype.values()\n    Returns an iterator for iterating over each value in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array values.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var it = arr.values();\n    > var v = it.next().value\n    <Complex64>\n    > var re = realf( v )\n    1.0\n    > var im = imagf( v )\n    -1.0\n    > v = it.next().value\n    <Complex64>\n    > re = realf( v )\n    2.0\n    > im = imagf( v )\n    -2.0\n    > var bool = it.next().done\n    true","Complex64Array.prototype.with":"\nComplex64Array.prototype.with( index, value )\n    Returns a new typed array with the element at a provided index replaced\n    with a provided value.\n\n    Parameters\n    ----------\n    index: integer\n        Element index.\n    \n    value: Complex64\n        Element value.  \n\n    Returns\n    -------\n    out: Complex64Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n    <Complex64Array>\n    > var z = out.get( 1 )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    -3.0\n\n\n    See Also\n    --------\n    Complex128Array, complex, Complex64","Complex128":"\nComplex128( real, imag )\n    128-bit complex number constructor.\n\n    Both the real and imaginary components are stored as double-precision\n    floating-point numbers.\n\n    Parameters\n    ----------\n    real: number\n        Real component.\n\n    imag: number\n        Imaginary component.\n\n    Returns\n    -------\n    z: Complex128\n        128-bit complex number.\n\n    z.re: number\n        Read-only property returning the real component.\n\n    z.im: number\n        Read-only property returning the imaginary component.\n\n\nComplex128.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n\n    Returns\n    -------\n    v: integer\n        Size (in bytes) of each component.\n\n    Examples\n    --------\n    > var s = Complex128.BYTES_PER_ELEMENT\n    8\n\n\nComplex128.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n\n    Returns\n    -------\n    s: integer\n        Size (in bytes) of each component.\n\n    Examples\n    --------\n    > var z = new Complex128( 5.0, 3.0 )\n    <Complex128>\n    > var s = z.BYTES_PER_ELEMENT\n    8\n\n\nComplex128.prototype.byteLength\n    Length (in bytes) of a complex number.\n\n    Returns\n    -------\n    len: integer\n        Length (in bytes) of a complex number.\n\n    Examples\n    --------\n    > var z = new Complex128( 5.0, 3.0 )\n    <Complex128>\n    > var s = z.byteLength\n    16\n\n    See Also\n    --------\n    complex, Complex64\n","Complex128.BYTES_PER_ELEMENT":"\nComplex128.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n\n    Returns\n    -------\n    v: integer\n        Size (in bytes) of each component.\n\n    Examples\n    --------\n    > var s = Complex128.BYTES_PER_ELEMENT\n    8","Complex128.prototype.BYTES_PER_ELEMENT":"\nComplex128.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n\n    Returns\n    -------\n    s: integer\n        Size (in bytes) of each component.\n\n    Examples\n    --------\n    > var z = new Complex128( 5.0, 3.0 )\n    <Complex128>\n    > var s = z.BYTES_PER_ELEMENT\n    8","Complex128.prototype.byteLength":"\nComplex128.prototype.byteLength\n    Length (in bytes) of a complex number.\n\n    Returns\n    -------\n    len: integer\n        Length (in bytes) of a complex number.\n\n    Examples\n    --------\n    > var z = new Complex128( 5.0, 3.0 )\n    <Complex128>\n    > var s = z.byteLength\n    16\n\n    See Also\n    --------\n    complex, Complex64","COMPLEX128_NAN":"\nCOMPLEX128_NAN\n    Canonical double-precision complex floating-point NaN.\n\n    Examples\n    --------\n    > COMPLEX128_NAN\n    <Complex128>\n\n    See Also\n    --------\n    COMPLEX64_NAN\n","COMPLEX128_NUM_BYTES":"\nCOMPLEX128_NUM_BYTES\n    Size (in bytes) of a 128-bit complex number.\n\n    Examples\n    --------\n    > COMPLEX128_NUM_BYTES\n    16\n\n    See Also\n    --------\n    COMPLEX64_NUM_BYTES, FLOAT64_NUM_BYTES\n","COMPLEX128_ZERO":"\nCOMPLEX128_ZERO\n    Double-precision complex floating-point zero.\n\n    Examples\n    --------\n    > COMPLEX128_ZERO\n    <Complex128>\n\n    See Also\n    --------\n    COMPLEX64_ZERO\n","Complex128Array":"\nComplex128Array()\n    A 128-bit complex number array.\n\n    Returns\n    -------\n    out: Complex128Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Complex128Array()\n    <Complex128Array>\n\n\nComplex128Array( length )\n    Creates a 128-bit complex number array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: Complex128Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 10 )\n    <Complex128Array>\n    > var len = arr.length\n    10\n\n\nComplex128Array( complexarray )\n    Creates a 64-bit complex number array from another complex number array.\n\n    Parameters\n    ----------\n    complexarray: Complex128Array\n        Complex array from which to generate another complex array.\n\n    Returns\n    -------\n    out: Complex128Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var arr2 = new Complex128Array( arr1 )\n    <Complex128Array>\n    > var len = arr2.length\n    2\n\n\nComplex128Array( typedarray )\n    Creates a 128-bit complex number array from a typed array\n    containing interleaved real and imaginary components.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate a complex array.\n\n    Returns\n    -------\n    out: Complex128Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new Float64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Float64Array>\n    > var arr = new Complex128Array( buf )\n    <Complex128Array>\n    > var len = arr.length\n    2\n\n\nComplex128Array( obj )\n    Creates a 128-bit complex number array from an array-like object or \n    iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a complex array.\n\n    Returns\n    -------\n    out: Complex128Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var len = arr1.length\n    2\n    > var buf = [ new Complex128( 1.0, -1.0 ), new Complex128( 2.0, -2.0 ) ];\n    > var arr2 = new Complex128Array( buf )\n    <Complex128Array>\n    > len = arr2.length\n    2\n\n\nComplex128Array( buffer[, byteOffset[, length]] )\n    Returns a 128-bit complex number array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Complex128Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 480 );\n    > var arr1 = new Complex128Array( buf )\n    <Complex128Array>\n    > var len = arr1.length\n    30\n    > var arr2 = new Complex128Array( buf, 16 )\n    <Complex128Array>\n    > len = arr2.length\n    29\n    > var arr3 = new Complex128Array( buf, 16, 20 )\n    <Complex128Array>\n    > len = arr3.length\n    20\n\n\nComplex128Array.from( src[, clbk[, thisArg]] )\n    Creates a new 128-bit complex number array from an array-like object or an\n    iterable.\n\n    A callback function is provided two arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    clbk: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n    \n    Returns\n    -------\n    out: Complex128Array\n        A typed array.\n    \n    Examples\n    --------\n    > function clbkFcn( v ) { return v * 2.0 };\n    > var arr = Complex128Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\n    <Complex128Array>\n    > var len = arr.length\n    2\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    -2.0\n\n\nComplex128Array.of( element0[, element1[, ...elementN]] )\n    Creates a new 128-bit complex number array from a variable number of\n    arguments.\n\n    Parameters\n    ----------\n    element0: number|ComplexLike\n        Array element.\n\n    element1: number |ComplexLike(optional)\n        Array element.\n\n    elementN: ...number|ComplexLike (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Complex128Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Complex128Array.of( 1.0, -1.0, 2.0, -2.0 )\n    <Complex128Array>\n    > var len = arr.length\n    2\n    > var z1 = new Complex128( 1.0, -1.0 );\n    > var z2 = new Complex128( 2.0, -2.0 );\n    > arr = Complex128Array.of( z1, z2 )\n    <Complex128Array>\n    > len = arr.length\n    2\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    -1.0\n\n\nComplex128Array.BYTES_PER_ELEMENT\n    The size of each array element in bytes.\n\n    Examples\n    --------\n    > var nbytes = Complex128Array.BYTES_PER_ELEMENT\n    16\n\n\nComplex128Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > var str = Complex128Array.name\n    'Complex128Array'\n\n\nComplex128Array.prototype.buffer\n    Pointer to the underlying data buffer.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 2 )\n    <Complex128Array>\n    > var buf = arr.buffer\n    <ArrayBuffer>\n\n\nComplex128Array.prototype.byteLength\n    Length of the array in bytes.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 10 )\n    <Complex128Array>\n    > var nbytes = arr.byteLength\n    160\n\n\nComplex128Array.prototype.byteOffset\n    Offset (in bytes) of the array from the start of its underlying\n    ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 10 )\n    <Complex128Array>\n    > var offset = arr.byteOffset\n    0\n    > var buf = new ArrayBuffer( 480 );\n    > arr = new Complex128Array( buf, 128 )\n    <Complex128Array>\n    > offset = arr.byteOffset\n    128\n\n\nComplex128Array.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 10 )\n    <Complex128Array>\n    > arr.BYTES_PER_ELEMENT\n    16\n\n\nComplex128Array.prototype.length\n    The number of array elements.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 10 )\n    <Complex128Array>\n    > var len = arr.length\n    10\n\n\nComplex128Array.prototype.at( i )\n    Returns an array element located at integer position (index) `i`, with\n    support for both nonnegative and negative integer positions.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n\n    Returns\n    -------\n    out: Complex128|void\n        An array element.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var z = arr.at( 1 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    -2.0\n\n\nComplex128Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n    \n    start: integer\n        Source start index position.\n    \n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Complex128Array\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex128Array>\n    > arr.copyWithin( 0, 2 )\n    <Complex128Array>\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    -3.0\n\n\nComplex128Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var it = arr.entries();\n    > var v = it.next().value\n    [ 0, <Complex128> ]\n    > var re = real( v[ 1 ] )\n    1.0\n    > var im = imag( v[ 1 ] )\n    -1.0\n    > v = it.next().value\n    [ 1, <Complex128> ]\n    > re = real( v[ 1 ] )\n    2.0\n    > im = imag( v[ 1 ] )\n    -2.0\n    > v = it.next().value\n    [ 2, <Complex128> ]\n    > re = real( v[ 1 ] )\n    3.0\n    > im = imag( v[ 1 ] )\n    -3.0\n    > var bool = it.next().done\n    true\n\n\nComplex128Array.prototype.every( predicate[, thisArg] )\n    Returns a boolean indicating whether all elements in the array pass a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all elements pass the test.\n\n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) > 0.0 ); };\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var bool = arr.every( predicate )\n    true\n\n\nComplex128Array.prototype.fill( value[, start[, end]] )\n    Returns a modified typed array filled with a fill value.\n\n    Parameters\n    ----------\n    value: Complex128\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Complex128Array\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( 3 )\n    <Complex128Array>\n    > arr.fill( new Complex128( 1.0, 1.0 ) );\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    1.0\n    > z = arr.get( 1 )\n    <Complex128>\n    > re = real( z )\n    1.0\n    > im = imag( z )\n    1.0\n    > z = arr.get( 2 )\n    <Complex128>\n    > re = real( z )\n    1.0\n    > im = imag( z )\n    1.0\n\n\nComplex128Array.prototype.filter( predicate[, thisArg] )\n    Returns a new array containing the elements of an array which pass a test\n    implemented by a predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Complex128Array\n        A new typed array.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var out = arr.filter( predicate )\n    <Complex128Array>\n    > var len = out.length\n    1\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    2.0\n\n\nComplex128Array.prototype.find( predicate[, thisArg] )\n    Returns the first element in an array for which a predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    out: Complex128|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var z = arr.find( predicate )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    1.0\n\n\nComplex128Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var idx = arr.findIndex( predicate )\n    0\n\n\nComplex128Array.prototype.findLast( predicate[, thisArg] )\n    Returns the last element in an array for which a predicate function returns\n    a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.  \n    \n    Returns\n    -------\n    out: Complex128|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var z = arr.findLast( predicate )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    2.0\n\n\nComplex128Array.prototype.findLastIndex( predicate[, thisArg] )\n    Returns the index of the last element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var idx = arr.findLastIndex( predicate )\n    1\n\n\nComplex128Array.prototype.forEach( clbk[, thisArg] )\n    Invokes a function once for each array element.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Examples\n    --------\n    > var str = '%';\n    > function clbk( v ) { str += v.toString() + '%'; };\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > arr.forEach( clbk );\n    > str\n    '%1 - 1i%2 - 2i%'\n\n\nComplex128Array.prototype.get( i )\n    Returns an array element located at integer position (index) `i`.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n    \n    Returns\n    -------\n    out: Complex128|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var z = arr.get( 1 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    -2.0\n\n\nComplex128Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a provided value.\n\n    Parameters\n    ----------\n    searchElement: Complex128\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n    \n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex128Array>\n    > var bool = arr.includes( new Complex128( 3.0, -3.0 ) )\n    true\n    > bool = arr.includes( new Complex128( 3.0, -3.0 ), 3 )\n    false\n\n\nComplex128Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the first index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: Complex128\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex128Array>\n    > var idx = arr.indexOf( new Complex128( 3.0, -3.0 ) )\n    2\n    > idx = arr.indexOf( new Complex128( 3.0, -3.0 ), 3 )\n    -1\n\n\nComplex128Array.prototype.join( [separator] )\n    Returns a new string by concatenating all array elements separated by a\n    separator string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        Separator string. Default: ','.\n    \n    Returns\n    -------\n    out: string\n        Array serialized as a string.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var str = arr.join()\n    '1 - 1i,2 - 2i'\n    > str = arr.join( '/' )\n    '1 - 1i/2 - 2i'\n\n\nComplex128Array.prototype.keys()\n    Returns an iterator for iterating over each index key in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array index keys.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var it = arr.keys();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().done\n    true\n\n\nComplex128Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the last index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: Complex128\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: out.length-1.\n    \n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex128Array>\n    > var idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ) )\n    3\n    > idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ), 2 )\n    0\n\n\nComplex128Array.prototype.map( clbk[, thisArg] )\n    Returns a new array with each element being the result of a provided\n    callback function.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Complex128Array\n        A new typed array.\n    \n    Examples\n    --------\n    > function clbk( v ) { return v; };\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var out = arr.map( clbk )\n    <Complex128Array>\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    -1.0\n    > z = out.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    -2.0\n\n\nComplex128Array.prototype.reduce( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in order, passing\n    in the return value from the calculation on the preceding element and\n    returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.    \n\n    initialValue: any (optional)\n        Initial accumulation value.\n    \n    Returns\n    -------\n    out: any\n        Accumulated result.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var z = arr.reduce( base.cadd )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    -3.0\n\n\nComplex128Array.prototype.reduceRight( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in reverse order,\n    passing in the return value from the calculation on the preceding element\n    and returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.\n\n    initialValue: any (optional)\n        Initial accumulation value.\n    \n    Returns\n    -------\n    out: any\n        Accumulated result.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var z = arr.reduceRight( base.cadd )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    -3.0\n\n\nComplex128Array.prototype.reverse()\n    Reverses the array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Complex128Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > arr.reverse();\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    -3.0\n    > z = arr.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    -2.0\n    > z = arr.get( 2 )\n    <Complex128>\n    > re = real( z )\n    1.0\n    > im = imag( z )\n    -1.0\n\n\nComplex128Array.prototype.set( z[, i] )\n    Sets one or more array elements.\n\n    If provided a single argument, the method sets array elements starting at\n    position (index) `i = 0`. To set elements starting elsewhere in the array,\n    provide an index argument `i`.\n\n    To set one or more array elements, provide an array-like object containing\n    either complex numbers or interleaved real and imaginary components.\n\n    Parameters\n    ----------\n    z: Complex128|Complex128Array|ArrayLikeObject\n        Complex number or complex number array.\n\n    i: integer (optional)\n        Array index at which to start setting elements. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 2 )\n    <Complex128Array>\n    > arr.set( new Complex128( 1.0, -1.0 ) );\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    -1.0\n    > arr.set( new Complex128( 2.0, -2.0 ), 1 );\n    > z = arr.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    -2.0\n\n\nComplex128Array.prototype.slice( [start[, end]] )\n    Copies a portion of a typed array to a new typed array.\n\n    Parameters\n    ----------\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n    \n    Returns\n    -------\n    out: Complex128Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var out = arr.slice( 1 )\n    <Complex128Array>\n    > var len = out.length\n    2\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    -2.0\n    > z = out.get( 1 )\n    <Complex128>\n    > re = real( z )\n    3.0\n    > im = imag( z )\n    -3.0\n\n\nComplex128Array.prototype.some( predicate[, thisArg] )\n    Returns a boolean indicating whether at least one element passes a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n    \n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one element passes the test.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var bool = arr.some( predicate )\n    true\n\n\nComplex128Array.prototype.sort( compareFunction )\n    Sorts an array in-place.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first element for comparison.\n    - b: second element for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFunction: Function\n        Comparison function.\n    \n    Returns\n    -------\n    out: Complex128Array\n        Modified array.\n    \n    Examples\n    --------\n    > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n    > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex128Array>\n    > arr.sort( compare );\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    -1.0\n    > z = arr.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    -2.0\n    > z = arr.get( 2 )\n    <Complex128>\n    > re = real( z )\n    3.0\n    > im = imag( z )\n    -3.0\n\n\nComplex128Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array view over the same underlying `ArrayBuffer` and\n    with the same underlying data type as the host array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Complex128Array\n        New typed array view.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex128Array>\n    > var out = arr.subarray( 1, 3 )\n    <Complex128Array>\n    > var len = out.length\n    2\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    -2.0\n    > z = out.get( 1 )\n    <Complex128>\n    > re = real( z )\n    3.0\n    > im = imag( z )\n    -3.0\n\n\nComplex128Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array (optional)\n        Locale identifier(s).\n    \n    options: Object (optional)\n        An object containing serialization options.\n    \n    Returns\n    -------\n    str: string\n        Local-specific string.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0 ] )\n    <Complex128Array>\n    > var str = arr.toLocaleString()\n    '1 + 1i,2 + 2i'\n\n\nComplex128Array.prototype.toReversed()\n    Returns a new typed array containing the elements in reversed order.\n\n    Returns\n    -------\n    out: Complex128Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\n    <Complex128Array>\n    > var out = arr.toReversed()\n    <Complex128Array>\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    3.0\n    > z = out.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    2.0\n    > z = out.get( 2 )\n    <Complex128>\n    > re = real( z )\n    1.0\n    > im = imag( z )\n    1.0\n\n\nComplex128Array.prototype.toSorted( compareFcn )\n    Returns a new typed array containing the elements in sorted order.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first element for comparison.\n    - b: second element for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFcn: Function\n        Comparison function.\n    \n    Returns\n    -------\n    out: Complex128Array\n        New typed array.\n    \n    Examples\n    --------\n    > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n    > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex128Array>\n    > var out = arr.toSorted( compare );\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    -1.0\n    > z = out.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    -2.0\n    > z = out.get( 2 )\n    <Complex128>\n    > re = real( z )\n    3.0\n    > im = imag( z )\n    -3.0\n\n\nComplex128Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        String serialization of the array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\n    <Complex128Array>\n    > var str = arr.toString()\n    '1 + 1i,2 - 2i,3 + 3i'\n\n\nComplex128Array.prototype.values()\n    Returns an iterator for iterating over each value in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array values.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var it = arr.values();\n    > var v = it.next().value\n    <Complex128>\n    > var re = real( v )\n    1.0\n    > var im = imag( v )\n    -1.0\n    > v = it.next().value\n    <Complex128>\n    > re = real( v )\n    2.0\n    > im = imag( v )\n    -2.0\n    > var bool = it.next().done\n    true\n\n\nComplex128Array.prototype.with( index, value )\n    Returns a new typed array with the element at a provided index replaced\n    with a provided value.\n\n    Parameters\n    ----------\n    index: integer\n        Element index.\n    \n    value: Complex128\n        Element value.  \n\n    Returns\n    -------\n    out: Complex128Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n    <Complex128Array>\n    > var z = out.get( 1 )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    -3.0\n\n\n    See Also\n    --------\n    Complex64Array, complex, Complex128","Complex128Array.from":"\nComplex128Array.from( src[, clbk[, thisArg]] )\n    Creates a new 128-bit complex number array from an array-like object or an\n    iterable.\n\n    A callback function is provided two arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    clbk: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n    \n    Returns\n    -------\n    out: Complex128Array\n        A typed array.\n    \n    Examples\n    --------\n    > function clbkFcn( v ) { return v * 2.0 };\n    > var arr = Complex128Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\n    <Complex128Array>\n    > var len = arr.length\n    2\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    -2.0","Complex128Array.of":"\nComplex128Array.of( element0[, element1[, ...elementN]] )\n    Creates a new 128-bit complex number array from a variable number of\n    arguments.\n\n    Parameters\n    ----------\n    element0: number|ComplexLike\n        Array element.\n\n    element1: number |ComplexLike(optional)\n        Array element.\n\n    elementN: ...number|ComplexLike (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Complex128Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Complex128Array.of( 1.0, -1.0, 2.0, -2.0 )\n    <Complex128Array>\n    > var len = arr.length\n    2\n    > var z1 = new Complex128( 1.0, -1.0 );\n    > var z2 = new Complex128( 2.0, -2.0 );\n    > arr = Complex128Array.of( z1, z2 )\n    <Complex128Array>\n    > len = arr.length\n    2\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    -1.0","Complex128Array.BYTES_PER_ELEMENT":"\nComplex128Array.BYTES_PER_ELEMENT\n    The size of each array element in bytes.\n\n    Examples\n    --------\n    > var nbytes = Complex128Array.BYTES_PER_ELEMENT\n    16","Complex128Array.name":"\nComplex128Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > var str = Complex128Array.name\n    'Complex128Array'","Complex128Array.prototype.buffer":"\nComplex128Array.prototype.buffer\n    Pointer to the underlying data buffer.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 2 )\n    <Complex128Array>\n    > var buf = arr.buffer\n    <ArrayBuffer>","Complex128Array.prototype.byteLength":"\nComplex128Array.prototype.byteLength\n    Length of the array in bytes.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 10 )\n    <Complex128Array>\n    > var nbytes = arr.byteLength\n    160","Complex128Array.prototype.byteOffset":"\nComplex128Array.prototype.byteOffset\n    Offset (in bytes) of the array from the start of its underlying\n    ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 10 )\n    <Complex128Array>\n    > var offset = arr.byteOffset\n    0\n    > var buf = new ArrayBuffer( 480 );\n    > arr = new Complex128Array( buf, 128 )\n    <Complex128Array>\n    > offset = arr.byteOffset\n    128","Complex128Array.prototype.BYTES_PER_ELEMENT":"\nComplex128Array.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 10 )\n    <Complex128Array>\n    > arr.BYTES_PER_ELEMENT\n    16","Complex128Array.prototype.length":"\nComplex128Array.prototype.length\n    The number of array elements.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 10 )\n    <Complex128Array>\n    > var len = arr.length\n    10","Complex128Array.prototype.at":"\nComplex128Array.prototype.at( i )\n    Returns an array element located at integer position (index) `i`, with\n    support for both nonnegative and negative integer positions.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n\n    Returns\n    -------\n    out: Complex128|void\n        An array element.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var z = arr.at( 1 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    -2.0","Complex128Array.prototype.copyWithin":"\nComplex128Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n    \n    start: integer\n        Source start index position.\n    \n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Complex128Array\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex128Array>\n    > arr.copyWithin( 0, 2 )\n    <Complex128Array>\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    -3.0","Complex128Array.prototype.entries":"\nComplex128Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var it = arr.entries();\n    > var v = it.next().value\n    [ 0, <Complex128> ]\n    > var re = real( v[ 1 ] )\n    1.0\n    > var im = imag( v[ 1 ] )\n    -1.0\n    > v = it.next().value\n    [ 1, <Complex128> ]\n    > re = real( v[ 1 ] )\n    2.0\n    > im = imag( v[ 1 ] )\n    -2.0\n    > v = it.next().value\n    [ 2, <Complex128> ]\n    > re = real( v[ 1 ] )\n    3.0\n    > im = imag( v[ 1 ] )\n    -3.0\n    > var bool = it.next().done\n    true","Complex128Array.prototype.every":"\nComplex128Array.prototype.every( predicate[, thisArg] )\n    Returns a boolean indicating whether all elements in the array pass a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all elements pass the test.\n\n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) > 0.0 ); };\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var bool = arr.every( predicate )\n    true","Complex128Array.prototype.fill":"\nComplex128Array.prototype.fill( value[, start[, end]] )\n    Returns a modified typed array filled with a fill value.\n\n    Parameters\n    ----------\n    value: Complex128\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Complex128Array\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( 3 )\n    <Complex128Array>\n    > arr.fill( new Complex128( 1.0, 1.0 ) );\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    1.0\n    > z = arr.get( 1 )\n    <Complex128>\n    > re = real( z )\n    1.0\n    > im = imag( z )\n    1.0\n    > z = arr.get( 2 )\n    <Complex128>\n    > re = real( z )\n    1.0\n    > im = imag( z )\n    1.0","Complex128Array.prototype.filter":"\nComplex128Array.prototype.filter( predicate[, thisArg] )\n    Returns a new array containing the elements of an array which pass a test\n    implemented by a predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Complex128Array\n        A new typed array.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var out = arr.filter( predicate )\n    <Complex128Array>\n    > var len = out.length\n    1\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    2.0","Complex128Array.prototype.find":"\nComplex128Array.prototype.find( predicate[, thisArg] )\n    Returns the first element in an array for which a predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    out: Complex128|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var z = arr.find( predicate )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    1.0","Complex128Array.prototype.findIndex":"\nComplex128Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var idx = arr.findIndex( predicate )\n    0","Complex128Array.prototype.findLast":"\nComplex128Array.prototype.findLast( predicate[, thisArg] )\n    Returns the last element in an array for which a predicate function returns\n    a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.  \n    \n    Returns\n    -------\n    out: Complex128|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var z = arr.findLast( predicate )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    2.0","Complex128Array.prototype.findLastIndex":"\nComplex128Array.prototype.findLastIndex( predicate[, thisArg] )\n    Returns the index of the last element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var idx = arr.findLastIndex( predicate )\n    1","Complex128Array.prototype.forEach":"\nComplex128Array.prototype.forEach( clbk[, thisArg] )\n    Invokes a function once for each array element.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Examples\n    --------\n    > var str = '%';\n    > function clbk( v ) { str += v.toString() + '%'; };\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > arr.forEach( clbk );\n    > str\n    '%1 - 1i%2 - 2i%'","Complex128Array.prototype.get":"\nComplex128Array.prototype.get( i )\n    Returns an array element located at integer position (index) `i`.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n    \n    Returns\n    -------\n    out: Complex128|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var z = arr.get( 1 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    -2.0","Complex128Array.prototype.includes":"\nComplex128Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a provided value.\n\n    Parameters\n    ----------\n    searchElement: Complex128\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n    \n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex128Array>\n    > var bool = arr.includes( new Complex128( 3.0, -3.0 ) )\n    true\n    > bool = arr.includes( new Complex128( 3.0, -3.0 ), 3 )\n    false","Complex128Array.prototype.indexOf":"\nComplex128Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the first index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: Complex128\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex128Array>\n    > var idx = arr.indexOf( new Complex128( 3.0, -3.0 ) )\n    2\n    > idx = arr.indexOf( new Complex128( 3.0, -3.0 ), 3 )\n    -1","Complex128Array.prototype.join":"\nComplex128Array.prototype.join( [separator] )\n    Returns a new string by concatenating all array elements separated by a\n    separator string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        Separator string. Default: ','.\n    \n    Returns\n    -------\n    out: string\n        Array serialized as a string.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var str = arr.join()\n    '1 - 1i,2 - 2i'\n    > str = arr.join( '/' )\n    '1 - 1i/2 - 2i'","Complex128Array.prototype.keys":"\nComplex128Array.prototype.keys()\n    Returns an iterator for iterating over each index key in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array index keys.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var it = arr.keys();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().done\n    true","Complex128Array.prototype.lastIndexOf":"\nComplex128Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the last index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: Complex128\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: out.length-1.\n    \n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex128Array>\n    > var idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ) )\n    3\n    > idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ), 2 )\n    0","Complex128Array.prototype.map":"\nComplex128Array.prototype.map( clbk[, thisArg] )\n    Returns a new array with each element being the result of a provided\n    callback function.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Complex128Array\n        A new typed array.\n    \n    Examples\n    --------\n    > function clbk( v ) { return v; };\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var out = arr.map( clbk )\n    <Complex128Array>\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    -1.0\n    > z = out.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    -2.0","Complex128Array.prototype.reduce":"\nComplex128Array.prototype.reduce( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in order, passing\n    in the return value from the calculation on the preceding element and\n    returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.    \n\n    initialValue: any (optional)\n        Initial accumulation value.\n    \n    Returns\n    -------\n    out: any\n        Accumulated result.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var z = arr.reduce( base.cadd )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    -3.0","Complex128Array.prototype.reduceRight":"\nComplex128Array.prototype.reduceRight( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in reverse order,\n    passing in the return value from the calculation on the preceding element\n    and returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.\n\n    initialValue: any (optional)\n        Initial accumulation value.\n    \n    Returns\n    -------\n    out: any\n        Accumulated result.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var z = arr.reduceRight( base.cadd )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    -3.0","Complex128Array.prototype.reverse":"\nComplex128Array.prototype.reverse()\n    Reverses the array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Complex128Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > arr.reverse();\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    -3.0\n    > z = arr.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    -2.0\n    > z = arr.get( 2 )\n    <Complex128>\n    > re = real( z )\n    1.0\n    > im = imag( z )\n    -1.0","Complex128Array.prototype.set":"\nComplex128Array.prototype.set( z[, i] )\n    Sets one or more array elements.\n\n    If provided a single argument, the method sets array elements starting at\n    position (index) `i = 0`. To set elements starting elsewhere in the array,\n    provide an index argument `i`.\n\n    To set one or more array elements, provide an array-like object containing\n    either complex numbers or interleaved real and imaginary components.\n\n    Parameters\n    ----------\n    z: Complex128|Complex128Array|ArrayLikeObject\n        Complex number or complex number array.\n\n    i: integer (optional)\n        Array index at which to start setting elements. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 2 )\n    <Complex128Array>\n    > arr.set( new Complex128( 1.0, -1.0 ) );\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    -1.0\n    > arr.set( new Complex128( 2.0, -2.0 ), 1 );\n    > z = arr.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    -2.0","Complex128Array.prototype.slice":"\nComplex128Array.prototype.slice( [start[, end]] )\n    Copies a portion of a typed array to a new typed array.\n\n    Parameters\n    ----------\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n    \n    Returns\n    -------\n    out: Complex128Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var out = arr.slice( 1 )\n    <Complex128Array>\n    > var len = out.length\n    2\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    -2.0\n    > z = out.get( 1 )\n    <Complex128>\n    > re = real( z )\n    3.0\n    > im = imag( z )\n    -3.0","Complex128Array.prototype.some":"\nComplex128Array.prototype.some( predicate[, thisArg] )\n    Returns a boolean indicating whether at least one element passes a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n    \n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one element passes the test.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var bool = arr.some( predicate )\n    true","Complex128Array.prototype.sort":"\nComplex128Array.prototype.sort( compareFunction )\n    Sorts an array in-place.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first element for comparison.\n    - b: second element for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFunction: Function\n        Comparison function.\n    \n    Returns\n    -------\n    out: Complex128Array\n        Modified array.\n    \n    Examples\n    --------\n    > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n    > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex128Array>\n    > arr.sort( compare );\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    -1.0\n    > z = arr.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    -2.0\n    > z = arr.get( 2 )\n    <Complex128>\n    > re = real( z )\n    3.0\n    > im = imag( z )\n    -3.0","Complex128Array.prototype.subarray":"\nComplex128Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array view over the same underlying `ArrayBuffer` and\n    with the same underlying data type as the host array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Complex128Array\n        New typed array view.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex128Array>\n    > var out = arr.subarray( 1, 3 )\n    <Complex128Array>\n    > var len = out.length\n    2\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    -2.0\n    > z = out.get( 1 )\n    <Complex128>\n    > re = real( z )\n    3.0\n    > im = imag( z )\n    -3.0","Complex128Array.prototype.toLocaleString":"\nComplex128Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array (optional)\n        Locale identifier(s).\n    \n    options: Object (optional)\n        An object containing serialization options.\n    \n    Returns\n    -------\n    str: string\n        Local-specific string.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0 ] )\n    <Complex128Array>\n    > var str = arr.toLocaleString()\n    '1 + 1i,2 + 2i'","Complex128Array.prototype.toReversed":"\nComplex128Array.prototype.toReversed()\n    Returns a new typed array containing the elements in reversed order.\n\n    Returns\n    -------\n    out: Complex128Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\n    <Complex128Array>\n    > var out = arr.toReversed()\n    <Complex128Array>\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    3.0\n    > z = out.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    2.0\n    > z = out.get( 2 )\n    <Complex128>\n    > re = real( z )\n    1.0\n    > im = imag( z )\n    1.0","Complex128Array.prototype.toSorted":"\nComplex128Array.prototype.toSorted( compareFcn )\n    Returns a new typed array containing the elements in sorted order.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first element for comparison.\n    - b: second element for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFcn: Function\n        Comparison function.\n    \n    Returns\n    -------\n    out: Complex128Array\n        New typed array.\n    \n    Examples\n    --------\n    > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n    > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex128Array>\n    > var out = arr.toSorted( compare );\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    -1.0\n    > z = out.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    -2.0\n    > z = out.get( 2 )\n    <Complex128>\n    > re = real( z )\n    3.0\n    > im = imag( z )\n    -3.0","Complex128Array.prototype.toString":"\nComplex128Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        String serialization of the array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\n    <Complex128Array>\n    > var str = arr.toString()\n    '1 + 1i,2 - 2i,3 + 3i'","Complex128Array.prototype.values":"\nComplex128Array.prototype.values()\n    Returns an iterator for iterating over each value in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array values.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var it = arr.values();\n    > var v = it.next().value\n    <Complex128>\n    > var re = real( v )\n    1.0\n    > var im = imag( v )\n    -1.0\n    > v = it.next().value\n    <Complex128>\n    > re = real( v )\n    2.0\n    > im = imag( v )\n    -2.0\n    > var bool = it.next().done\n    true","Complex128Array.prototype.with":"\nComplex128Array.prototype.with( index, value )\n    Returns a new typed array with the element at a provided index replaced\n    with a provided value.\n\n    Parameters\n    ----------\n    index: integer\n        Element index.\n    \n    value: Complex128\n        Element value.  \n\n    Returns\n    -------\n    out: Complex128Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n    <Complex128Array>\n    > var z = out.get( 1 )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    -3.0\n\n\n    See Also\n    --------\n    Complex64Array, complex, Complex128","complexarray":"\ncomplexarray( [dtype] )\n    Creates a complex typed array.\n\n    The function supports the following data types:\n\n    - complex128: double-precision complex floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n\n    The default typed array data type is `complex128`.\n\n    Parameters\n    ----------\n    dtype: string (optional)\n        Data type. Default: 'complex128'.\n\n    Returns\n    -------\n    out: ComplexArray\n        A complex number typed array.\n\n    Examples\n    --------\n    > var arr = complexarray()\n    <Complex128Array>\n    > arr = complexarray( 'complex64' )\n    <Complex64Array>\n\n\ncomplexarray( length[, dtype] )\n    Returns a complex number typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Array length.\n\n    dtype: string (optional)\n        Data type. Default: 'complex128'.\n\n    Returns\n    -------\n    out: ComplexArray\n        A complex number typed array.\n\n    Examples\n    --------\n    > var arr = complexarray( 5 )\n    <Complex128Array>\n    > arr = complexarray( 5, 'complex64' )\n    <Complex64Array>\n\n\ncomplexarray( complexarray[, dtype] )\n    Creates a complex number typed array from another complex number typed\n    array.\n\n    Parameters\n    ----------\n    complexarray: ComplexArray\n        Complex number typed array from which to generate another complex number\n        typed array.\n\n    dtype: string (optional)\n        Data type. Default: 'complex128'.\n\n    Returns\n    -------\n    out: ComplexArray\n        A complex number typed array.\n\n    Examples\n    --------\n    > var arr1 = complexarray( [ 0.5, 0.5, 0.5, 0.5 ] );\n    > var arr2 = complexarray( arr1, 'complex64' )\n    <Complex64Array>\n\n\ncomplexarray( obj[, dtype] )\n    Creates a complex number typed array from an array-like object or iterable.\n\n    If an array-like object contains interleaved real and imaginary components,\n    the array-like object must have a length which is a multiple of two.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate an array.\n\n    dtype: string (optional)\n        Data type. Default: 'complex128'.\n\n    Returns\n    -------\n    out: ComplexArray\n        A complex number typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 0.5, 0.5, 0.5, 0.5 ];\n    > var arr2 = complexarray( arr1, 'complex64' )\n    <Complex64Array>\n\n\ncomplexarray( buffer[, byteOffset[, length]][, dtype] )\n    Returns a complex number typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first array element.\n        Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    dtype: string (optional)\n        Data type. Default: 'complex128'.\n\n    Returns\n    -------\n    out: ComplexArray\n        A complex number typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 64 );\n    > var arr = complexarray( buf, 0, 8, 'complex64' )\n    <Complex64Array>\n\n    See Also\n    --------\n    typedarray, realarray\n","complexarrayCtors":"\ncomplexarrayCtors( dtype )\n    Returns a complex typed array constructor.\n\n    The function returns constructors for the following data types:\n\n    - complex64: single-precision floating-point complex numbers.\n    - complex128: double-precision floating-point complex numbers.\n\n    Parameters\n    ----------\n    dtype: string\n        Data type.\n\n    Returns\n    -------\n    out: Function|null\n        Complex typed array constructor.\n\n    Examples\n    --------\n    > var ctor = complexarrayCtors( 'complex64' )\n    <Function>\n    > ctor = complexarrayCtors( 'float32' )\n    null\n\n    See Also\n    --------\n    arrayCtors, typedarrayCtors, realarrayCtors\n","complexarrayDataTypes":"\ncomplexarrayDataTypes()\n    Returns a list of complex typed array data types.\n\n    Returns\n    -------\n    out: Array<string>\n        List of complex typed array data types.\n\n    Examples\n    --------\n    > var out = complexarrayDataTypes()\n    <Array>\n\n    See Also\n    --------\n    arrayDataTypes, typedarrayDataTypes, realarrayDataTypes, ndarrayDataTypes\n","complexCtors":"\ncomplexCtors( dtype )\n    Returns a complex number constructor.\n\n    The function returns constructors for the following data types:\n\n    - complex64: single-precision complex floating-point numbers.\n    - complex128: double-precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    dtype: string\n        Data type.\n\n    Returns\n    -------\n    out: Function|null\n        Constructor.\n\n    Examples\n    --------\n    > var ctor = complexCtors( 'complex128' )\n    <Function>\n    > ctor = complexCtors( 'complex' )\n    null\n\n    See Also\n    --------\n    complexarrayCtors\n","complexDataType":"\ncomplexDataType( value )\n    Returns the data type of a complex number object.\n\n    If provided an argument having an unknown or unsupported type, the function\n    returns `null`.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    out: string|null\n        Data type.\n\n    Examples\n    --------\n    > var v = new Complex128( 1.0, 2.0 );\n    > var dt = complexDataType( v )\n    'complex128'\n    > dt = complexDataType( 'beep' )\n    null\n\n    See Also\n    --------\n    arrayDataType\n","complexDataTypes":"\ncomplexDataTypes()\n    Returns a list of complex number data types.\n\n    The output array contains the following data types:\n\n    - complex64: single-precision complex floating-point numbers.\n    - complex128: double-precision complex floating-point numbers.\n\n    Returns\n    -------\n    out: Array<string>\n        List of complex number data types.\n\n    Examples\n    --------\n    > var out = complexDataTypes()\n    <Array>\n\n    See Also\n    --------\n    complexarrayDataTypes\n","complexPromotionRules":"\ncomplexPromotionRules( [dtype1, dtype2] )\n    Returns the complex number data type with the smallest size and closest\n    \"kind\" to which data types can be safely cast.\n\n    If not provided data types, the function returns a type promotion table.\n\n    If a data type to which data types can be safely cast does *not* exist (or\n    is not supported), the function returns `-1`.\n\n    If provided an unrecognized data type, the function returns `null`.\n\n    Parameters\n    ----------\n    dtype1: string (optional)\n        Data type.\n\n    dtype2: string (optional)\n        Data type.\n\n    Returns\n    -------\n    out: Object|string|integer|null\n        Promotion rule(s).\n\n    Examples\n    --------\n    > var out = complexPromotionRules( 'complex128', 'complex64' )\n    'complex128'\n\n    See Also\n    --------\n    arrayPromotionRules, ndarrayPromotionRules\n","compose":"\ncompose( ...f )\n    Function composition.\n\n    Returns a composite function. Starting from the right, the composite\n    function evaluates each function and passes the result as an argument\n    to the next function. The result of the leftmost function is the result\n    of the whole.\n\n    Notes:\n\n    - Only the rightmost function is explicitly permitted to accept multiple\n      arguments. All other functions are evaluated as unary functions.\n    - The function will throw if provided fewer than two input arguments.\n\n    Parameters\n    ----------\n    f: ...Function\n        Functions to compose.\n\n    Returns\n    -------\n    out: Function\n        Composite function.\n\n    Examples\n    --------\n    > function a( x ) {\n    ...    return 2 * x;\n    ... }\n    > function b( x ) {\n    ...    return x + 3;\n    ... }\n    > function c( x ) {\n    ...    return x / 5;\n    ... }\n    > var f = compose( c, b, a );\n    > var z = f( 6 )\n    3\n\n    See Also\n    --------\n    composeAsync\n","composeAsync":"\ncomposeAsync( ...f )\n    Function composition.\n\n    Returns a composite function. Starting from the right, the composite\n    function evaluates each function and passes the result as the first argument\n    of the next function. The result of the leftmost function is the result\n    of the whole.\n\n    The last argument for each provided function is a `next` callback which\n    should be invoked upon function completion. The callback accepts two\n    arguments:\n\n    - error: error argument.\n    - result: function result.\n\n    If a composed function calls the `next` callback with a truthy `error`\n    argument, the composite function suspends execution and immediately calls\n    the `done` callback for subsequent `error` handling.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Only the rightmost function is explicitly permitted to accept multiple\n    arguments. All other functions are evaluated as binary functions.\n\n    The function will throw if provided fewer than two input arguments.\n\n    Parameters\n    ----------\n    f: ...Function\n        Functions to compose.\n\n    Returns\n    -------\n    out: Function\n        Composite function.\n\n    Examples\n    --------\n    > function a( x, next ) {\n    ...    setTimeout( onTimeout, 0 );\n    ...    function onTimeout() {\n    ...        next( null, 2*x );\n    ...    }\n    ... };\n    > function b( x, next ) {\n    ...    setTimeout( onTimeout, 0 );\n    ...    function onTimeout() {\n    ...        next( null, x+3 );\n    ...    }\n    ... };\n    > function c( x, next ) {\n    ...    setTimeout( onTimeout, 0 );\n    ...    function onTimeout() {\n    ...        next( null, x/5 );\n    ...    }\n    ... };\n    > var f = composeAsync( c, b, a );\n    > function done( error, result ) {\n    ...    if ( error ) {\n    ...        throw error;\n    ...    }\n    ...    console.log( result );\n    ... };\n    > f( 6, done )\n    3\n\n    See Also\n    --------\n    compose\n","configdir":"\nconfigdir( [p] )\n    Returns a directory for user-specific configuration files.\n\n    On Windows platforms, the function first checks for a `LOCALAPPDATA`\n    environment variable before checking for an `APPDATA` environment variable.\n    This means that machine specific user configuration files have precedence\n    over roaming user configuration files.\n\n    On non-Windows platforms, if the function is unable to locate the current\n    user's `home` directory, the function returns `null`. Similarly, on Windows\n    platforms, if the function is unable to locate an application data\n    directory, the function also returns `null`.\n\n    Parameters\n    ----------\n    p: string (optional)\n        Path to append to a base directory.\n\n    Returns\n    -------\n    out: string|null\n        Directory.\n\n    Examples\n    --------\n    > var dir = configdir()\n    e.g., '/Users/<username>/Library/Preferences'\n    > dir = configdir( 'appname/config' )\n    e.g., '/Users/<username>/Library/Preferences/appname/config'\n\n    See Also\n    --------\n    homedir, tmpdir\n","conj":"\nconj( z )\n    Returns the complex conjugate of a double-precision complex floating-point\n    number.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Complex conjugate.\n\n    Examples\n    --------\n    > var z = new Complex128( 5.0, 3.0 );\n    > z.toString()\n    '5 + 3i'\n    > var v = conj( z );\n    > v.toString()\n    '5 - 3i'\n\n    See Also\n    --------\n    imag, real, reim\n","conjf":"\nconjf( z )\n    Returns the complex conjugate of a single-precision complex floating-point\n    number.\n\n    Parameters\n    ----------\n    z: Complex64\n        Complex number.\n\n    Returns\n    -------\n    out: Complex64\n        Complex conjugate.\n\n    Examples\n    --------\n    > var z = new Complex64( 5.0, 3.0 );\n    > z.toString()\n    '5 + 3i'\n    > var v = conjf( z );\n    > v.toString()\n    '5 - 3i'\n\n    See Also\n    --------\n    conj, imagf, realf, reimf\n","constantcase":"\nconstantcase( str )\n    Converts a string to constant case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Constant-cased string.\n\n    Examples\n    --------\n    > var out = constantcase( 'Hello World!' )\n    'HELLO_WORLD'\n    > out = constantcase( 'I am a tiny little teapot' )\n    'I_AM_A_TINY_LITTLE_TEAPOT'\n\n    See Also\n    --------\n    camelcase, kebabcase, pascalcase, snakecase","constantFunction":"\nconstantFunction( val )\n    Creates a function which always returns the same value.\n\n    Notes:\n\n    - When provided an object reference, the returned `function` always returns\n      the same reference.\n\n    Parameters\n    ----------\n    val: any\n        Value to always return.\n\n    Returns\n    -------\n    out: Function\n        Constant function.\n\n    Examples\n    --------\n    > var fcn = constantFunction( 3.14 );\n    > var v = fcn()\n    3.14\n    > v = fcn()\n    3.14\n    > v = fcn()\n    3.14\n\n    See Also\n    --------\n    argumentFunction, identity\n","constantStream":"\nconstantStream( value[, options] )\n    Returns a readable stream which always streams the same value.\n\n    In object mode, `null` is a reserved value. If provided `null`, the\n    returned stream will prematurely end.\n\n    Parameters\n    ----------\n    value: string|Buffer|Uint8Array|any\n        Value to stream.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing streaming.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = constantStream( 'beep', opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nconstantStream.factory( [value, ][options] )\n    Returns a function for creating readable streams which always stream the\n    same value.\n\n    If provided a value to stream, the returned function returns readable always\n    streams the provided value.\n\n    If not provided a value to stream, the returned function requires that a\n    value be provided at each invocation.\n\n    If provided only one argument and that argument is an object (either empty\n    or not containing any recognized options properties), the function treats\n    the argument as a value to be streamed, not as an options argument.\n\n    Parameters\n    ----------\n    value: string|Buffer|Uint8Array|any (optional)\n        Value to stream.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing streaming.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = constantStream.factory( opts );\n\n\nconstantStream.objectMode( value[, options] )\n    Returns an \"objectMode\" readable stream which always streams the same value.\n\n    In object mode, `null` is a reserved value. If provided `null`, the\n    returned stream will prematurely end.\n\n    Parameters\n    ----------\n    value: any\n        Value to stream.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before pausing streaming.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = constantStream.objectMode( 3.14, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    arrayStream, iteratorStream\n","constantStream.factory":"\nconstantStream.factory( [value, ][options] )\n    Returns a function for creating readable streams which always stream the\n    same value.\n\n    If provided a value to stream, the returned function returns readable always\n    streams the provided value.\n\n    If not provided a value to stream, the returned function requires that a\n    value be provided at each invocation.\n\n    If provided only one argument and that argument is an object (either empty\n    or not containing any recognized options properties), the function treats\n    the argument as a value to be streamed, not as an options argument.\n\n    Parameters\n    ----------\n    value: string|Buffer|Uint8Array|any (optional)\n        Value to stream.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing streaming.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = constantStream.factory( opts );","constantStream.objectMode":"\nconstantStream.objectMode( value[, options] )\n    Returns an \"objectMode\" readable stream which always streams the same value.\n\n    In object mode, `null` is a reserved value. If provided `null`, the\n    returned stream will prematurely end.\n\n    Parameters\n    ----------\n    value: any\n        Value to stream.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before pausing streaming.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = constantStream.objectMode( 3.14, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    arrayStream, iteratorStream","constructorName":"\nconstructorName( val )\n    Determines the name of a value's constructor.\n\n    Parameters\n    ----------\n    val: any\n        Input value.\n\n    Returns\n    -------\n    out: string\n        Name of a value's constructor.\n\n    Examples\n    --------\n    > var v = constructorName( 'a' )\n    'String'\n    > v = constructorName( {} )\n    'Object'\n    > v = constructorName( true )\n    'Boolean'\n\n    See Also\n    --------\n    functionName\n","contains":"\ncontains( val, searchValue[, position] )\n    Tests if an array-like value contains a search value.\n\n    When `val` is a string, the function checks whether the characters of the\n    search string are found in the input string. The search is case-sensitive.\n\n    When `val` is an array-like object, the function checks whether the input\n    array contains an element strictly equal to the specified search value.\n\n    For strings, this function is modeled after `String.prototype.includes`,\n    part of the ECMAScript 6 specification. This function is different from a\n    call to `String.prototype.includes.call` insofar as type-checking is\n    performed for all arguments.\n\n    The function does not distinguish between positive and negative zero.\n\n    If `position < 0`, the search is performed for the entire input array or\n    string.\n\n\n    Parameters\n    ----------\n    val: ArrayLike\n        Input value.\n\n    searchValue: any\n        Value to search for.\n\n    position: integer (optional)\n        Position at which to start searching for `searchValue`. Default: `0`.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an input value contains another value.\n\n    Examples\n    --------\n    > var bool = contains( 'Hello World', 'World' )\n    true\n    > bool = contains( 'Hello World', 'world' )\n    false\n    > bool = contains( [ 1, 2, 3, 4 ], 2 )\n    true\n    > bool = contains( [ NaN, 2, 3, 4 ], NaN )\n    true\n\n    // Supply a position:\n    > bool = contains( 'Hello World', 'Hello', 6 )\n    false\n    > bool = contains( [ true, NaN, false ], true, 1 )\n    false\n\n","convertArray":"\nconvertArray( arr, dtype )\n    Converts an input array to an array of a different data type.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject\n        Array to convert.\n\n    dtype: string\n        Output data type.\n\n    Returns\n    -------\n    out: Array|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var arr = [ 1.0, 2.0, 3.0, 4.0 ];\n    > var out = convertArray( arr, 'float32' )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    See Also\n    --------\n    convertArraySame\n","convertArraySame":"\nconvertArraySame( x, y )\n    Converts an input array to the same data type as a second input array.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Array to convert.\n\n    y: Array|TypedArray\n        Array having desired output data type.\n\n    Returns\n    -------\n    out: Array|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n    > var y = new Float32Array( 0 );\n    > var out = convertArraySame( x, y )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    See Also\n    --------\n    convertArray\n","convertPath":"\nconvertPath( from, to )\n    Converts between POSIX and Windows paths.\n\n    Parameters\n    ----------\n    from: string\n        Input path.\n\n    to: string\n        Output path convention: 'win32', 'mixed', or 'posix'.\n\n    Returns\n    -------\n    out: string\n        Converted path.\n\n    Examples\n    --------\n    > var out = convertPath( '/c/foo/bar/beep.c', 'win32' )\n    'c:\\\\foo\\\\bar\\\\beep.c'\n    > out = convertPath( '/c/foo/bar/beep.c', 'mixed' )\n    'c:/foo/bar/beep.c'\n    > out = convertPath( '/c/foo/bar/beep.c', 'posix' )\n    '/c/foo/bar/beep.c'\n    > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'win32' )\n    'C:\\\\\\\\foo\\\\bar\\\\beep.c'\n    > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'mixed' )\n    'C:/foo/bar/beep.c'\n    > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'posix' )\n    '/c/foo/bar/beep.c'\n\n","copy":"\ncopy( value[, level] )\n    Copy or deep clone a value to an arbitrary depth.\n\n    The implementation can handle circular references.\n\n    If a `Number`, `String`, or `Boolean` object is encountered, the value is\n    cloned as a primitive. This behavior is intentional.\n\n    For objects, the implementation only copies enumerable keys and their\n    associated property descriptors.\n\n    The implementation only checks whether basic `Objects`, `Arrays`, and class\n    instances are extensible, sealed, and/or frozen.\n\n    Functions are not cloned; their reference is copied.\n\n    The implementation supports custom error types which are `Error` instances\n    (e.g., ES2015 subclasses).\n\n    Support for copying class instances is inherently fragile. Any instances\n    with privileged access to variables (e.g., within closures) cannot be\n    cloned. This stated, basic copying of class instances is supported. Provided\n    an environment which supports ES5, the implementation is greedy and performs\n    a deep clone of any arbitrary class instance and its properties. The\n    implementation assumes that the concept of `level` applies only to the class\n    instance reference, but not to its internal state.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    level: integer (optional)\n         Copy depth. Default: Infinity.\n\n    Returns\n    -------\n    out: any\n        Value copy.\n\n    Examples\n    --------\n    > var value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\n    > var out = copy( value )\n    [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ]\n    > var bool = ( value[ 0 ].c === out[ 0 ].c )\n    false\n\n    // Set the `level` option to limit the copy depth:\n    > value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\n    > out = copy( value, 1 );\n    > bool = ( value[ 0 ] === out[ 0 ] )\n    true\n    > bool = ( value[ 0 ].c === out[ 0 ].c )\n    true\n\n\n    See Also\n    --------\n    merge\n","copyBuffer":"\ncopyBuffer( buffer )\n    Copies buffer data to a new Buffer instance.\n\n    Parameters\n    ----------\n    buffer: Buffer\n        Buffer to copy from.\n\n    Returns\n    -------\n    out: Buffer\n        Buffer instance.\n\n    Examples\n    --------\n    > var b1 = array2buffer( [ 1, 2, 3, 4 ] );\n    > var b2 = copyBuffer( b1 )\n    <Buffer>[ 1, 2, 3, 4 ]\n\n    See Also\n    --------\n    allocUnsafe, Buffer\n","countBy":"\ncountBy( collection, [options,] indicator )\n    Groups values according to an indicator function and returns group counts.\n\n    When invoked, the indicator function is provided two arguments:\n\n    - value: collection value.\n    - index: collection index.\n\n    The value returned by an indicator function should be a value which can be\n    serialized as an object key.\n\n    If provided an empty collection, the function returns an empty object.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection to group. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Options.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    indicator: Function\n        Indicator function specifying which group an element in the input\n        collection belongs to.\n\n    Returns\n    -------\n    out: Object\n        Group results.\n\n    Examples\n    --------\n    > function indicator( v ) {\n    ...     if ( v[ 0 ] === 'b' ) {\n    ...         return 'b';\n    ...     }\n    ...     return 'other';\n    ... };\n    > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n    > var out = countBy( collection, indicator )\n    { 'b': 3, 'other': 1 }\n\n    See Also\n    --------\n    group, groupBy\n","countByAsync":"\ncountByAsync( collection, [options,] indicator, done )\n    Groups values according to an indicator function and returns group counts.\n\n    When invoked, the indicator function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If the\n    indicator function accepts two arguments, the indicator function is\n    provided:\n\n    - value\n    - next\n\n    If the indicator function accepts three arguments, the indicator function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other indicator function signature, the indicator function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - group: value group.\n\n    If an indicator function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    If provided an empty collection, the function calls the `done` callback with\n    an empty object as the second argument.\n\n    The `group` returned by an indicator function should be a value which can be\n    serialized as an object key.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    indicator: Function\n        Indicator function specifying which group an element in the input\n        collection belongs to.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > countByAsync( arr, indicator, done )\n    1000\n    2500\n    3000\n    { \"even\": 2, \"odd\": 1 }\n\n    // Limit number of concurrent invocations:\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 3000, 2500, 1000 ];\n    > countByAsync( arr, opts, indicator, done )\n    2500\n    3000\n    1000\n    { \"even\": 2, \"odd\": 1 }\n\n    // Process sequentially:\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 3000, 2500, 1000 ];\n    > countByAsync( arr, opts, indicator, done )\n    3000\n    2500\n    1000\n    { \"even\": 2, \"odd\": 1 }\n\n\ncountByAsync.factory( [options,] indicator )\n    Returns a function which groups values according to an indicator function\n    and returns group counts.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    indicator: Function\n        Indicator function specifying which group an element in the input\n        collection belongs to.\n\n    Returns\n    -------\n    out: Function\n        A function which groups values and returns group counts.\n\n    Examples\n    --------\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = countByAsync.factory( opts, indicator );\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    { \"even\": 2, \"odd\": 1 }\n    > arr = [ 2000, 1500, 1000, 500 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    500\n    { \"even\": 2, \"odd\": 2 }\n\n    See Also\n    --------\n    countBy, groupByAsync, tabulateByAsync\n","countByAsync.factory":"\ncountByAsync.factory( [options,] indicator )\n    Returns a function which groups values according to an indicator function\n    and returns group counts.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    indicator: Function\n        Indicator function specifying which group an element in the input\n        collection belongs to.\n\n    Returns\n    -------\n    out: Function\n        A function which groups values and returns group counts.\n\n    Examples\n    --------\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = countByAsync.factory( opts, indicator );\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    { \"even\": 2, \"odd\": 1 }\n    > arr = [ 2000, 1500, 1000, 500 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    500\n    { \"even\": 2, \"odd\": 2 }\n\n    See Also\n    --------\n    countBy, groupByAsync, tabulateByAsync","currentYear":"\ncurrentYear()\n    Returns the current year.\n\n    Returns\n    -------\n    out: integer\n        Current year.\n\n    Examples\n    --------\n    > var y = currentYear()\n    <number>\n\n    See Also\n    --------\n    isCurrentYear\n","curry":"\ncurry( fcn[, arity][, thisArg] )\n    Transforms a function into a sequence of functions each accepting a single\n    argument.\n\n    Until return value resolution, each invocation returns a new partially\n    applied curry function.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to curry.\n\n    arity: integer (optional)\n        Number of parameters. Default: `fcn.length`.\n\n    thisArg: any (optional)\n        Evaluation context.\n\n    Returns\n    -------\n    out: Function\n        Curry function.\n\n    Examples\n    --------\n    > function add( x, y ) { return x + y; };\n    > var f = curry( add );\n    > var sum = f( 2 )( 3 )\n    5\n\n    // Supply arity:\n    > function add() { return arguments[ 0 ] + arguments[ 1 ]; };\n    > f = curry( add, 2 );\n    > sum = f( 2 )( 3 )\n    5\n\n    // Provide function context:\n    > var obj = {\n    ...     'name': 'Ada',\n    ...     'greet': function greet( word1, word2 ) {\n    ...        return word1 + ' ' + word2 + ', ' + this.name + '!'\n    ...     }\n    ... };\n    > f = curry( obj.greet, obj );\n    > var str = f( 'Hello' )( 'there' )\n    'Hello there, Ada!'\n\n    See Also\n    --------\n    curryRight, uncurry, uncurryRight\n","curryRight":"\ncurryRight( fcn[, arity][, thisArg] )\n    Transforms a function into a sequence of functions each accepting a single\n    argument.\n\n    Until return value resolution, each invocation returns a new partially\n    applied curry function.\n\n    This function applies arguments starting from the right.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to curry.\n\n    arity: integer (optional)\n        Number of parameters. Default: `fcn.length`.\n\n    thisArg: any (optional)\n        Evaluation context.\n\n    Returns\n    -------\n    out: Function\n        Curry function.\n\n    Examples\n    --------\n    > function add( x, y ) { return x + y; };\n    > var f = curryRight( add );\n    > var sum = f( 2 )( 3 )\n    5\n\n    // Supply arity:\n    > function add() { return arguments[ 0 ] + arguments[ 1 ]; };\n    > f = curryRight( add, 2 );\n    > sum = f( 2 )( 3 )\n    5\n\n    // Provide function context:\n    > var obj = {\n    ...     'name': 'Ada',\n    ...     'greet': function greet( word1, word2 ) {\n    ...         return word1 + ' ' + word2 + ', ' + this.name + '!'\n    ...     }\n    ... };\n    > f = curryRight( obj.greet, obj );\n    > var str = f( 'there' )( 'Hello' )\n    'Hello there, Ada!'\n\n    See Also\n    --------\n    curry, uncurry, uncurryRight\n","cwd":"\ncwd()\n    Returns the current working directory.\n\n    Returns\n    -------\n    path: string\n        Current working directory of the process.\n\n    Examples\n    --------\n    > var dir = cwd()\n    '/path/to/current/working/directory'\n\n    See Also\n    --------\n    chdir\n","DALE_CHALL_NEW":"\nDALE_CHALL_NEW()\n    Returns a list of familiar English words.\n\n    Returns\n    -------\n    out: Array<string>\n        List of familiar English words.\n\n    Examples\n    --------\n    > var list = DALE_CHALL_NEW()\n    [ 'a', 'able', 'aboard', 'about', 'above', ... ]\n\n    References\n    ----------\n    - Chall, Jeanne Sternlicht, and Edgar Dale. 1995. *Readability revisited:\n    the new Dale-Chall readability formula*. Brookline Books.\n    <https://books.google.com/books?id=2nbuAAAAMAAJ>.\n\n","datasets":"\ndatasets( name[, options] )\n    Returns a dataset.\n\n    The function forwards provided options to the dataset interface specified\n    by `name`.\n\n    Parameters\n    ----------\n    name: string\n        Dataset name.\n\n    options: Object (optional)\n        Function options.\n\n    Returns\n    -------\n    out: any\n        Dataset.\n\n    Examples\n    --------\n    > var out = datasets( 'MONTH_NAMES_EN' )\n    [ 'January', 'February', ... ]\n    > var opts = { 'data': 'cities' };\n    > out = datasets( 'MINARD_NAPOLEONS_MARCH', opts )\n    [ {...}, {...}, ... ]\n\n","DataView":"\nDataView( buffer[, byteOffset[, byteLength]] )\n    Returns a data view representing a provided array buffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer|SharedArrayBuffer\n        Array buffer.\n\n    byteOffset: integer (optional)\n        Offset (in bytes) to the first byte in the array buffer for the new view\n        to reference. Default: 0.\n\n    byteLength: integer (optional)\n        Number of elements in the byte array. If not provided, the view's length\n        will equal the buffer's length.\n\n    Returns\n    -------\n    out: DataView\n        A data view.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 5 )\n    <ArrayBuffer>\n    > var dv = new DataView( buf )\n    <DataView>\n\n\nDataView.prototype.buffer\n    Read-only property which returns the underyling array buffer.\n\n    Examples\n    --------\n    > var buf1 = new ArrayBuffer( 5 );\n    > var dv = new DataView( buf1 );\n    > var buf2 = dv.buffer\n    <ArrayBuffer>\n    > var b = ( buf1 === buf2 )\n    true\n\n\nDataView.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the view.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 5 );\n    > var dv = new DataView( buf );\n    > dv.byteLength\n    5\n\n\nDataView.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the view to the\n    start of the underlying array buffer.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 5 );\n    > var dv = new DataView( buf, 2 );\n    > dv.byteLength\n    3\n    > dv.byteOffset\n    2\n\n\nTODO: document properties/methods\n\n\n    See Also\n    --------\n    ArrayBuffer, typedarray\n","DataView.prototype.buffer":"\nDataView.prototype.buffer\n    Read-only property which returns the underyling array buffer.\n\n    Examples\n    --------\n    > var buf1 = new ArrayBuffer( 5 );\n    > var dv = new DataView( buf1 );\n    > var buf2 = dv.buffer\n    <ArrayBuffer>\n    > var b = ( buf1 === buf2 )\n    true","DataView.prototype.byteLength":"\nDataView.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the view.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 5 );\n    > var dv = new DataView( buf );\n    > dv.byteLength\n    5","DataView.prototype.byteOffset":"\nDataView.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the view to the\n    start of the underlying array buffer.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 5 );\n    > var dv = new DataView( buf, 2 );\n    > dv.byteLength\n    3\n    > dv.byteOffset\n    2","datespace":"\ndatespace( start, stop[, length][ , options] )\n    Generates an array of linearly spaced dates.\n\n    Parameters\n    ----------\n    start: number\n        Start time as either a `Date` object, Unix timestamp, JavaScript\n        timestamp, or date string.\n\n    stop: number\n        Stop time as either a `Date` object, Unix timestamp, JavaScript\n        timestamp, or date string.\n\n    length: integer (optional)\n        Length of output array. Default: `100`.\n\n    options: Object (optional)\n        Options.\n\n    options.round: string (optional)\n        Specifies how sub-millisecond times should be rounded:\n        [ 'floor', 'ceil', 'round' ]. Default: 'floor'.\n\n    Returns\n    -------\n    arr: Array\n        Array of dates.\n\n    Examples\n    --------\n    > var stop = '2014-12-02T07:00:54.973Z';\n    > var start = new Date( stop ) - 60000;\n    > var arr = datespace( start, stop, 6 )\n    [...]\n\n    // Equivalent of Math.ceil():\n    > var opts = { 'round': 'ceil' };\n    > arr = datespace( 1417503655000, 1417503655001, 3, opts )\n    [...]\n\n    See Also\n    --------\n    linspace, logspace\n","dayOfQuarter":"\ndayOfQuarter( [month[, day, year]] )\n    Returns the day of the quarter.\n\n    By default, the function returns the day of the quarter for the current date\n    (according to local time). To determine the day of the quarter for a\n    particular day, provide `month`, `day`, and `year` arguments.\n\n    A `month` may be either a month's integer value, three letter abbreviation,\n    or full name (case insensitive).\n\n    The function also accepts a `Date` object.\n\n    Parameters\n    ----------\n    month: string|integer|Date (optional)\n        Month (or `Date`).\n\n    day: integer (optional)\n        Day.\n\n    year: integer (optional)\n        Year.\n\n    Returns\n    -------\n    out: integer\n        Day of the quarter.\n\n    Examples\n    --------\n    > var day = dayOfQuarter()\n    <number>\n    > day = dayOfQuarter( new Date() )\n    <number>\n    > day = dayOfQuarter( 12, 31, 2017 )\n    92\n\n    // Other ways to supply month:\n    > day = dayOfQuarter( 'dec', 31, 2017 )\n    92\n    > day = dayOfQuarter( 'december', 31, 2017 )\n    92\n\n    See Also\n    --------\n    dayOfYear\n","dayOfYear":"\ndayOfYear( [month[, day, year]] )\n    Returns the day of the year.\n\n    By default, the function returns the day of the year for the current date\n    (according to local time). To determine the day of the year for a particular\n    day, provide `month`, `day`, and `year` arguments.\n\n    A `month` may be either a month's integer value, three letter abbreviation,\n    or full name (case insensitive).\n\n    The function also accepts a `Date` object.\n\n    Parameters\n    ----------\n    month: string|integer|Date (optional)\n        Month (or `Date`).\n\n    day: integer (optional)\n        Day.\n\n    year: integer (optional)\n        Year.\n\n    Returns\n    -------\n    out: integer\n        Day of the year.\n\n    Examples\n    --------\n    > var day = dayOfYear()\n    <number>\n    > day = dayOfYear( new Date() )\n    <number>\n    > day = dayOfYear( 12, 31, 2016 )\n    366\n\n    // Other ways to supply month:\n    > day = dayOfYear( 'dec', 31, 2016 )\n    366\n    > day = dayOfYear( 'december', 31, 2016 )\n    366\n\n    See Also\n    --------\n    dayOfQuarter\n","daysInMonth":"\ndaysInMonth( [month[, year]] )\n    Returns the number of days in a month.\n\n    By default, the function returns the number of days in the current month\n    of the current year (according to local time). To determine the number of\n    days for a particular month and year, provide `month` and `year` arguments.\n\n    A `month` may be either a month's integer value, three letter abbreviation,\n    or full name (case insensitive).\n\n    The function's return value is a generalization and does **not** take into\n    account inaccuracies due to daylight savings conventions, crossing\n    timezones, or other complications with time and dates.\n\n    Parameters\n    ----------\n    month: string|integer|Date (optional)\n        Month (or `Date`).\n\n    year: integer (optional)\n        Year.\n\n    Returns\n    -------\n    out: integer\n        Days in a month.\n\n    Examples\n    --------\n    > var num = daysInMonth()\n    <number>\n    > num = daysInMonth( 2 )\n    <number>\n    > num = daysInMonth( 2, 2016 )\n    29\n    > num = daysInMonth( 2, 2017 )\n    28\n\n    // Other ways to supply month:\n    > num = daysInMonth( 'feb', 2016 )\n    29\n    > num = daysInMonth( 'february', 2016 )\n    29\n\n    See Also\n    --------\n    daysInYear\n","daysInYear":"\ndaysInYear( [value] )\n    Returns the number of days in a year according to the Gregorian calendar.\n\n    By default, the function returns the number of days in the current year\n    (according to local time). To determine the number of days for a particular\n    year, provide either a year or a `Date` object.\n\n    The function's return value is a generalization and does **not** take into\n    account inaccuracies due to daylight savings conventions, crossing\n    timezones, or other complications with time and dates.\n\n    Parameters\n    ----------\n    value: integer|Date (optional)\n        Year or `Date` object.\n\n    Returns\n    -------\n    out: integer\n        Number of days in a year.\n\n    Examples\n    --------\n    > var num = daysInYear()\n    <number>\n    > num = daysInYear( 2016 )\n    366\n    > num = daysInYear( 2017 )\n    365\n\n    See Also\n    --------\n    daysInMonth\n","ddot":"\nddot( x, y[, dim] )\n    Computes the dot product of two double-precision floating-point vectors.\n\n    If provided at least one input array having more than one dimension, the\n    input arrays are broadcasted to a common shape.\n\n    For multi-dimensional input arrays, the function performs batched\n    computation, such that the function computes the dot product for each pair\n    of vectors in `x` and `y` according to the specified dimension index.\n\n    The size of the contracted dimension must be the same for both input arrays.\n\n    The function resolves the dimension index for which to compute the dot\n    product *before* broadcasting.\n\n    If provided empty vectors, the dot product is `0`.\n\n    Parameters\n    ----------\n    x: ndarray\n        First input array. Must have a 'float64' data type. Must have at least\n        one dimension and be broadcast-compatible with the second input array.\n\n    y: ndarray\n        Second input array. Must have a 'float64' data type. Must have at least\n        one dimension and be broadcast-compatible with the first input array.\n\n    dim: integer (optional)\n        Dimension index for which to compute the dot product. Must be a negative\n        integer. Negative indices are resolved relative to the last array\n        dimension, with the last dimension corresponding to `-1`. Default: -1.\n\n    Returns\n    -------\n    out: ndarray\n        The dot product. The output array has the same data type as the input\n        arrays and has a shape which is determined by broadcasting and excludes\n        the contracted dimension.\n\n    Examples\n    --------\n    > var xbuf = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var x = array( xbuf );\n    > var ybuf = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var y = array( ybuf );\n    > var z = ddot( x, y )\n    <ndarray>\n    > z.get()\n    -5.0\n\n    See Also\n    --------\n    base.strided.ddot, gdot, sdot\n","debugSinkStream":"\ndebugSinkStream( [options,] [clbk] )\n    Returns a writable stream for debugging stream pipelines.\n\n    If the `DEBUG` environment variable is not set, no data is logged.\n\n    Providing a `name` option is *strongly* encouraged, as the `DEBUG`\n    environment variable can be used to filter debuggers.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Debug namespace.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to encode strings as `Buffer` objects before writing\n        data to a returned stream. Default: true.\n\n    options.defaultEncoding: string (optional)\n        Default encoding when not explicitly specified when writing data.\n        Default: 'utf8'.\n\n    clbk: Function (optional)\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: WritableStream\n        Writable stream.\n\n    Examples\n    --------\n    > var s = debugSinkStream( { 'name': 'foo' } );\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();\n\n\ndebugSinkStream.factory( [options] )\n    Returns a function for creating writable streams for debugging stream\n    pipelines.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to encode strings as `Buffer` objects before writing\n        data to a returned stream. Default: true.\n\n    options.defaultEncoding: string (optional)\n        Default encoding when not explicitly specified when writing data.\n        Default: 'utf8'.\n\n    Returns\n    -------\n    createStream( name[, clbk] ): Function\n        Function for creating writable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = debugSinkStream.factory( opts );\n\n\ndebugSinkStream.objectMode( [options,] [clbk] )\n    Returns an \"objectMode\" writable stream for debugging stream pipelines.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Debug namespace.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to encode strings as `Buffer` objects before writing\n        data to a returned stream. Default: true.\n\n    options.defaultEncoding: string (optional)\n        Default encoding when not explicitly specified when writing data.\n        Default: 'utf8'.\n\n    clbk: Function (optional)\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: WritableStream\n        Writable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > var s = debugSinkStream.objectMode( { 'name': 'foo' } );\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();\n\n    See Also\n    --------\n    debugStream, inspectSinkStream\n","debugSinkStream.factory":"\ndebugSinkStream.factory( [options] )\n    Returns a function for creating writable streams for debugging stream\n    pipelines.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to encode strings as `Buffer` objects before writing\n        data to a returned stream. Default: true.\n\n    options.defaultEncoding: string (optional)\n        Default encoding when not explicitly specified when writing data.\n        Default: 'utf8'.\n\n    Returns\n    -------\n    createStream( name[, clbk] ): Function\n        Function for creating writable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = debugSinkStream.factory( opts );","debugSinkStream.objectMode":"\ndebugSinkStream.objectMode( [options,] [clbk] )\n    Returns an \"objectMode\" writable stream for debugging stream pipelines.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Debug namespace.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to encode strings as `Buffer` objects before writing\n        data to a returned stream. Default: true.\n\n    options.defaultEncoding: string (optional)\n        Default encoding when not explicitly specified when writing data.\n        Default: 'utf8'.\n\n    clbk: Function (optional)\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: WritableStream\n        Writable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > var s = debugSinkStream.objectMode( { 'name': 'foo' } );\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();\n\n    See Also\n    --------\n    debugStream, inspectSinkStream","debugStream":"\ndebugStream( [options,] [clbk] )\n    Returns a transform stream for debugging stream pipelines.\n\n    If the `DEBUG` environment variable is not set, no data is logged.\n\n    Providing a `name` option is *strongly* encouraged, as the `DEBUG`\n    environment variable can be used to filter debuggers.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Debug namespace.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    clbk: Function (optional)\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream.\n\n    Examples\n    --------\n    > var s = debugStream( { 'name': 'foo' } );\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();\n\n\ndebugStream.factory( [options] )\n    Returns a function for creating transform streams for debugging stream\n    pipelines.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    createStream( name[, clbk] ): Function\n        Function for creating transform streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = debugStream.factory( opts );\n\n\ndebugStream.objectMode( [options,] [clbk] )\n    Returns an \"objectMode\" transform stream for debugging stream pipelines.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Debug namespace.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    clbk: Function (optional)\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > var s = debugStream.objectMode( { 'name': 'foo' } );\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();\n\n    See Also\n    --------\n    debugSinkStream, inspectStream\n","debugStream.factory":"\ndebugStream.factory( [options] )\n    Returns a function for creating transform streams for debugging stream\n    pipelines.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    createStream( name[, clbk] ): Function\n        Function for creating transform streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = debugStream.factory( opts );","debugStream.objectMode":"\ndebugStream.objectMode( [options,] [clbk] )\n    Returns an \"objectMode\" transform stream for debugging stream pipelines.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Debug namespace.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    clbk: Function (optional)\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > var s = debugStream.objectMode( { 'name': 'foo' } );\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();\n\n    See Also\n    --------\n    debugSinkStream, inspectStream","decorateAfter":"\ndecorateAfter( fcn, arity, after[, thisArg] )\n    Decorates a provided function such that the function's return value is\n    provided as an argument to another function.\n\n    Decorators are intended to be transparent, meaning that, when interfacing\n    with an API, the decorated API should have the same signature (i.e., number\n    of parameters) as the decorated function.\n\n    Thus, a typical value for `arity` is `fcn.length`. This function does not\n    require equality, however, and the `arity` argument is allowed to diverge\n    from that of the decorated function. Specifying a differing `arity` does\n    *not* affect function evaluation behavior, as the returned function passes\n    all provided arguments to the decorated function.\n\n    If the `after` function returns `undefined`, the returned decorator returns\n    the return value of the decorated function `fcn`; otherwise, the returned\n    decorator returns the return value of `after`.\n\n    The returned decorator supports an `arity` less than or equal to `10` (i.e.,\n    the maximum arity of the returned function is `10`). For an arity greater\n    than `10`, the returned function has an arity equal to `0`. While this\n    violates strict notions of a decorator, for all practical purposes, this is\n    unlikely to be an issue, as the vast majority of functions have fewer than\n    `10` parameters and the need for explicitly checking function length is\n    relatively uncommon.\n\n    Common use cases for decorating a function with additional actions *after*\n    invocation include logging, capturing invocation statistics, and validating\n    return values.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to decorate.\n\n    arity: integer\n        Number of parameters.\n\n    after: Function\n        Function with which to invoke the return value of the decorated\n        function.\n\n    thisArg: any (optional)\n        Evaluation context for `after`.\n\n    Returns\n    -------\n    out: Function\n        Decorator function.\n\n    Examples\n    --------\n    > function f( v ) { return -v; };\n    > var fcn = decorateAfter( base.abs, 1, f );\n    > var v = fcn( -5 )\n    -5\n    > v = fcn( 5 )\n    -5\n\n\ndecorateAfter.factory( fcn, arity, after[, thisArg] )\n    Uses code generation to decorate a provided function such that the\n    function's return value is provided as an argument to another function.\n\n    Code generation may be problematic in browser contexts enforcing a strict\n    content security policy] (CSP). If running in or targeting an environment\n    with a CSP, avoid using code generation.\n\n    For non-native functions, the function supports returning a decorator whose\n    API exactly matches the API of the decorated function, including function\n    length and parameter names.\n\n    For native functions, due to how native functions serialize to strings, the\n    function generates placeholder parameter names, which are unlikely to match\n    the canonical parameter names. Using placeholder parameter names ensures\n    that the length of the decorator (i.e., number of parameters) matches the\n    decorated function and, except in scenarios involving function source code\n    inspection, will not affect runtime behavior.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to decorate.\n\n    arity: integer\n        Number of parameters.\n\n    after: Function\n        Function with which to invoke the return value of the decorated\n        function.\n\n    thisArg: any (optional)\n        Evaluation context for `after`.\n\n    Returns\n    -------\n    out: Function\n        Decorator function.\n\n    Examples\n    --------\n    > function f( v ) { return -v; };\n    > var fcn = decorateAfter.factory( base.abs, 1, f );\n    > var v = fcn( -5 )\n    -5\n    > v = fcn( 5 )\n    -5\n\n","decorateAfter.factory":"\ndecorateAfter.factory( fcn, arity, after[, thisArg] )\n    Uses code generation to decorate a provided function such that the\n    function's return value is provided as an argument to another function.\n\n    Code generation may be problematic in browser contexts enforcing a strict\n    content security policy] (CSP). If running in or targeting an environment\n    with a CSP, avoid using code generation.\n\n    For non-native functions, the function supports returning a decorator whose\n    API exactly matches the API of the decorated function, including function\n    length and parameter names.\n\n    For native functions, due to how native functions serialize to strings, the\n    function generates placeholder parameter names, which are unlikely to match\n    the canonical parameter names. Using placeholder parameter names ensures\n    that the length of the decorator (i.e., number of parameters) matches the\n    decorated function and, except in scenarios involving function source code\n    inspection, will not affect runtime behavior.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to decorate.\n\n    arity: integer\n        Number of parameters.\n\n    after: Function\n        Function with which to invoke the return value of the decorated\n        function.\n\n    thisArg: any (optional)\n        Evaluation context for `after`.\n\n    Returns\n    -------\n    out: Function\n        Decorator function.\n\n    Examples\n    --------\n    > function f( v ) { return -v; };\n    > var fcn = decorateAfter.factory( base.abs, 1, f );\n    > var v = fcn( -5 )\n    -5\n    > v = fcn( 5 )\n    -5","deepEqual":"\ndeepEqual( a, b )\n    Tests for deep equality between two values.\n\n    Parameters\n    ----------\n    a: any\n        First comparison value.\n\n    b: any\n        Second comparison value.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating if `a` is deep equal to `b`.\n\n    Examples\n    --------\n    > var bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, 3 ] )\n    true\n\n    > bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, '3' ] )\n    false\n\n    > bool = deepEqual( { 'a': 2 }, { 'a': [ 2 ] } )\n    false\n\n    See Also\n    --------\n    isStrictEqual, isSameValue\n","deepGet":"\ndeepGet( obj, path[, options] )\n    Returns a nested property value.\n\n    Parameters\n    ----------\n    obj: ObjectLike\n        Input object.\n\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    out: any\n        Nested property value.\n\n    Examples\n    --------\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var val = deepGet( obj, 'a.b.c' )\n    'd'\n\n    // Specify a custom separator via the `sep` option:\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var val = deepGet( obj, 'a/b/c', { 'sep': '/' } )\n    'd'\n\ndeepGet.factory( path[, options] )\n    Creates a reusable deep get function.\n\n    Parameters\n    ----------\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    out: Function\n        Deep get factory.\n\n    Examples\n    --------\n    > var dget = deepGet.factory( 'a/b/c', { 'sep': '/' } );\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var val = dget( obj )\n    'd'\n\n    See Also\n    --------\n    deepPluck, deepSet\n","deepGet.factory":"\ndeepGet.factory( path[, options] )\n    Creates a reusable deep get function.\n\n    Parameters\n    ----------\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    out: Function\n        Deep get factory.\n\n    Examples\n    --------\n    > var dget = deepGet.factory( 'a/b/c', { 'sep': '/' } );\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var val = dget( obj )\n    'd'\n\n    See Also\n    --------\n    deepPluck, deepSet","deepHasOwnProp":"\ndeepHasOwnProp( value, path[, options] )\n    Returns a boolean indicating whether an object contains a nested key path.\n\n    The function tests for \"own\" properties and will return `false` for\n    inherited properties.\n\n    Value arguments other than `null` or `undefined` are coerced to objects.\n\n    Key path array elements are coerced to strings.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object has a specified path.\n\n    Examples\n    --------\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var bool = deepHasOwnProp( obj, 'a.b.c' )\n    true\n\n    // Specify a custom separator via the `sep` option:\n    > obj = { 'a': { 'b': { 'c': 'd' } } };\n    > bool = deepHasOwnProp( obj, 'a/b/c', { 'sep': '/' } )\n    true\n\ndeepHasOwnProp.factory( path[, options] )\n    Returns a function which tests whether an object contains a nested key path.\n\n    The returned function tests for \"own\" properties and will return `false` for\n    inherited properties.\n\n    Parameters\n    ----------\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    out: Function\n        Function which tests whether an object contains a nested key path.\n\n    Examples\n    --------\n    > var has = deepHasOwnProp.factory( 'a/b/c', { 'sep': '/' } );\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var bool = has( obj )\n    true\n\n    See Also\n    --------\n    deepHasProp, hasOwnProp, deepGet, deepPluck, deepSet\n","deepHasOwnProp.factory":"\ndeepHasOwnProp.factory( path[, options] )\n    Returns a function which tests whether an object contains a nested key path.\n\n    The returned function tests for \"own\" properties and will return `false` for\n    inherited properties.\n\n    Parameters\n    ----------\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    out: Function\n        Function which tests whether an object contains a nested key path.\n\n    Examples\n    --------\n    > var has = deepHasOwnProp.factory( 'a/b/c', { 'sep': '/' } );\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var bool = has( obj )\n    true\n\n    See Also\n    --------\n    deepHasProp, hasOwnProp, deepGet, deepPluck, deepSet","deepHasProp":"\ndeepHasProp( value, path[, options] )\n    Returns a boolean indicating whether an object contains a nested key path,\n    either own or inherited.\n\n    Value arguments other than `null` or `undefined` are coerced to objects.\n\n    Key path array elements are coerced to strings.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object has a specified path.\n\n    Examples\n    --------\n    > function Foo() { return this; };\n    > Foo.prototype.b = { 'c': 'd' };\n    > var obj = { 'a': new Foo() };\n    > var bool = deepHasProp( obj, 'a.b.c' )\n    true\n\n    // Specify a custom separator via the `sep` option:\n    > bool = deepHasProp( obj, 'a/b/c', { 'sep': '/' } )\n    true\n\ndeepHasProp.factory( path[, options] )\n    Returns a function which tests whether an object contains a nested key path,\n    either own or inherited.\n\n    Parameters\n    ----------\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    out: Function\n        Function which tests whether an object contains a nested key path.\n\n    Examples\n    --------\n    > function Foo() { return this; };\n    > Foo.prototype.b = { 'c': 'd' };\n    > var has = deepHasProp.factory( 'a/b/c', { 'sep': '/' } );\n    > var obj = { 'a': new Foo() };\n    > var bool = has( obj )\n    true\n\n    See Also\n    --------\n    deepHasOwnProp, hasOwnProp, deepGet, deepPluck, deepSet\n","deepHasProp.factory":"\ndeepHasProp.factory( path[, options] )\n    Returns a function which tests whether an object contains a nested key path,\n    either own or inherited.\n\n    Parameters\n    ----------\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    out: Function\n        Function which tests whether an object contains a nested key path.\n\n    Examples\n    --------\n    > function Foo() { return this; };\n    > Foo.prototype.b = { 'c': 'd' };\n    > var has = deepHasProp.factory( 'a/b/c', { 'sep': '/' } );\n    > var obj = { 'a': new Foo() };\n    > var bool = has( obj )\n    true\n\n    See Also\n    --------\n    deepHasOwnProp, hasOwnProp, deepGet, deepPluck, deepSet","deepPluck":"\ndeepPluck( arr, path[, options] )\n    Extracts a nested property value from each element of an object array.\n\n    If a key path does not exist, the function sets the plucked value as\n    `undefined`.\n\n    Extracted values are not cloned.\n\n    Parameters\n    ----------\n    arr: Array\n        Source array.\n\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to return a new data structure. Default:\n        true.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    out: Array\n        Destination array.\n\n    Examples\n    --------\n    > var arr = [\n    ...     { 'a': { 'b': { 'c': 1 } } },\n    ...     { 'a': { 'b': { 'c': 2 } } }\n    ... ];\n    > var out = deepPluck( arr, 'a.b.c' )\n    [ 1, 2 ]\n    > arr = [\n    ...     { 'a': [ 0, 1, 2 ] },\n    ...     { 'a': [ 3, 4, 5 ] }\n    ... ];\n    > out = deepPluck( arr, [ 'a', 1 ] )\n    [ 1, 4 ]\n\n    See Also\n    --------\n    deepGet, deepSet\n","deepSet":"\ndeepSet( obj, path, value[, options] )\n    Sets a nested property value.\n\n    Parameters\n    ----------\n    obj: ObjectLike\n        Input object.\n\n    path: string|Array\n        Key path.\n\n    value: any\n        Value to set.\n\n    options: Object (optional)\n        Options.\n\n    options.create: boolean (optional)\n        Boolean indicating whether to create a path if the key path does not\n        already exist. Default: false.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if the property was successfully set.\n\n    Examples\n    --------\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var bool = deepSet( obj, 'a.b.c', 'beep' )\n    true\n\n    // Specify an alternative separator via the sep option:\n    > obj = { 'a': { 'b': { 'c': 'd' } } };\n    > bool = deepSet( obj, 'a/b/c', 'beep', { 'sep': '/' } );\n    > obj\n    { 'a': { 'b': { 'c': 'beep' } } }\n\n    // To create a key path which does not exist, set the create option to true:\n    > bool = deepSet( obj, 'a.e.c', 'boop', { 'create': true } );\n    > obj\n    { 'a': { 'b': { 'c': 'beep' }, 'e': { 'c': 'boop' } } }\n\n\ndeepSet.factory( path[, options] )\n    Creates a reusable deep set function.\n\n    Parameters\n    ----------\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.create: boolean (optional)\n        Boolean indicating whether to create a path if the key path does not\n        already exist. Default: false.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    out: Function\n        Deep get function.\n\n    Examples\n    --------\n    > var dset = deepSet.factory( 'a/b/c', {\n    ...     'create': true,\n    ...     'sep': '/'\n    ... });\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var bool = dset( obj, 'beep' )\n    true\n    > obj\n    { 'a': { 'b': { 'c': 'beep' } } }\n\n    See Also\n    --------\n    deepGet, deepPluck\n","deepSet.factory":"\ndeepSet.factory( path[, options] )\n    Creates a reusable deep set function.\n\n    Parameters\n    ----------\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.create: boolean (optional)\n        Boolean indicating whether to create a path if the key path does not\n        already exist. Default: false.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    out: Function\n        Deep get function.\n\n    Examples\n    --------\n    > var dset = deepSet.factory( 'a/b/c', {\n    ...     'create': true,\n    ...     'sep': '/'\n    ... });\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var bool = dset( obj, 'beep' )\n    true\n    > obj\n    { 'a': { 'b': { 'c': 'beep' } } }\n\n    See Also\n    --------\n    deepGet, deepPluck","defineMemoizedProperty":"\ndefineMemoizedProperty( obj, prop, descriptor )\n    Defines a memoized object property.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    descriptor: Object\n        Property descriptor.\n\n    descriptor.configurable: boolean (optional)\n        Boolean indicating if property descriptor can be changed and if the\n        property can be deleted from the provided object. Default: false.\n\n    descriptor.enumerable: boolean (optional)\n        Boolean indicating if the property shows up when enumerating object\n        properties. Default: false.\n\n    descriptor.writable: boolean (optional)\n        Boolean indicating if the value associated with the property can be\n        changed with an assignment operator. Default: false.\n\n    descriptor.value: Function\n        Synchronous function whose return value will be memoized and set as the\n        property value.\n\n    Examples\n    --------\n    > var obj = {};\n    > function foo() {\n    ...     return 'bar';\n    ... };\n    > defineMemoizedProperty( obj, 'foo', {\n    ...     'configurable': false,\n    ...     'enumerable': true,\n    ...     'writable': false,\n    ...     'value': foo\n    ... });\n    > obj.foo\n    'bar'\n\n    See Also\n    --------\n    setMemoizedReadOnly, defineProperty\n","defineProperties":"\ndefineProperties( obj, properties )\n    Defines (and/or modifies) object properties.\n\n    The second argument is an object whose own enumerable property values are\n    descriptors for the properties to be defined or modified.\n\n    Property descriptors come in two flavors: data descriptors and accessor\n    descriptors. A data descriptor is a property that has a value, which may or\n    may not be writable. An accessor descriptor is a property described by a\n    getter-setter function pair. A descriptor must be one of these two flavors\n    and cannot be both.\n\n    A property descriptor has the following optional properties:\n\n    - configurable: boolean indicating if property descriptor can be changed and\n    if the property can be deleted from the provided object. Default: false.\n\n    - enumerable: boolean indicating if the property shows up when enumerating\n    object properties. Default: false.\n\n    - writable: boolean indicating if the value associated with the property can\n    be changed with an assignment operator. Default: false.\n\n    - value: property value.\n\n    - get: function which serves as a getter for the property, or, if no getter,\n    undefined. When the property is accessed, a getter function is called\n    without arguments and with the `this` context set to the object through\n    which the property is accessed (which may not be the object on which the\n    property is defined due to inheritance). The return value will be used as\n    the property value. Default: undefined.\n\n    - set: function which serves as a setter for the property, or, if no setter,\n    undefined. When assigning a property value, a setter function is called with\n    one argument (the value being assigned to the property) and with the `this`\n    context set to the object through which the property is assigned. Default: undefined.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the properties.\n\n    properties: Object\n        Object with property descriptors.\n\n    Returns\n    -------\n    obj: Object\n        Object on which properties were defined (and/or modified).\n\n    Examples\n    --------\n    > var obj = {};\n    > defineProperties( obj, {\n    ...     'foo': {\n    ...         'value': 'bar',\n    ...         'writable': false,\n    ...         'configurable': false,\n    ...         'enumerable': true\n    ...     },\n    ...     'baz': {\n    ...         'value': 13\n    ...     }\n    ... });\n    > obj.foo\n    'bar'\n    > obj.baz\n    13\n\n    See Also\n    --------\n    defineProperty, setReadOnly\n","defineProperty":"\ndefineProperty( obj, prop, descriptor )\n    Defines (or modifies) an object property.\n\n    Property descriptors come in two flavors: data descriptors and accessor\n    descriptors. A data descriptor is a property that has a value, which may or\n    may not be writable. An accessor descriptor is a property described by a\n    getter-setter function pair. A descriptor must be one of these two flavors\n    and cannot be both.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    descriptor: Object\n        Property descriptor.\n\n    descriptor.configurable: boolean (optional)\n        Boolean indicating if property descriptor can be changed and if the\n        property can be deleted from the provided object. Default: false.\n\n    descriptor.enumerable: boolean (optional)\n        Boolean indicating if the property shows up when enumerating object\n        properties. Default: false.\n\n    descriptor.writable: boolean (optional)\n        Boolean indicating if the value associated with the property can be\n        changed with an assignment operator. Default: false.\n\n    descriptor.value: any (optional)\n        Property value.\n\n    descriptor.get: Function|void (optional)\n        Function which serves as a getter for the property, or, if no getter,\n        undefined. When the property is accessed, a getter function is called\n        without arguments and with the `this` context set to the object through\n        which the property is accessed (which may not be the object on which the\n        property is defined due to inheritance). The return value will be used\n        as the property value. Default: undefined.\n\n    descriptor.set: Function|void (optional)\n        Function which serves as a setter for the property, or, if no setter,\n        undefined. When assigning a property value, a setter function is called\n        with one argument (the value being assigned to the property) and with\n        the `this` context set to the object through which the property is\n        assigned. Default: undefined.\n\n    Returns\n    -------\n    obj: Object\n        Object on which the property was defined (or modified).\n\n    Examples\n    --------\n    > var obj = {};\n    > defineProperty( obj, 'foo', {\n    ...     'value': 'bar',\n    ...     'enumerable': true,\n    ...     'writable': false\n    ... });\n    > obj.foo = 'boop';\n    > obj\n    { 'foo': 'bar' }\n\n    See Also\n    --------\n    defineProperties, setReadOnly\n","dirname":"\ndirname( path )\n    Returns a directory name.\n\n    Parameters\n    ----------\n    path: string\n        Path.\n\n    Returns\n    -------\n    out: string\n        Directory name.\n\n    Examples\n    --------\n    > var dir = dirname( './foo/bar/index.js' )\n    './foo/bar'\n\n    See Also\n    --------\n    extname\n","dotcase":"\ndotcase( str )\n    Converts a string to dot case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Dot-cased string.\n\n    Examples\n    --------\n    > var out = dotcase( 'Hello World!' )\n    'hello.world'\n    > out = dotcase( 'beep boop' )\n    'beep.boop'\n\n    See Also\n    --------\n    camelcase, kebabcase, pascalcase, snakecase","DoublyLinkedList":"\nDoublyLinkedList()\n    Doubly linked list constructor.\n\n    Returns\n    -------\n    list: Object\n        Doubly linked list.\n\n    list.clear: Function\n        Clears the list.\n\n    list.first: Function\n        Returns the first list node. If the list is empty, the returned value is\n        `undefined`.\n\n    list.insert: Function\n        Inserts a value after a provided list node. For its third argument, the\n        method accepts a location: 'before' or 'after'. Default: 'after'.\n\n    list.iterator: Function\n        Returns an iterator for iterating over a list. If an environment\n        supports Symbol.iterator, the returned iterator is iterable. Note that,\n        in order to prevent confusion arising from list mutation during\n        iteration, a returned iterator **always** iterates over a list\n        \"snapshot\", which is defined as the list of list elements at the time\n        of the method's invocation. For its sole argument, the method accepts a\n        direction: 'forward' or 'reverse'. Default: 'forward'.\n\n    list.last: Function\n        Returns the last list node. If the list is empty, the returned value is\n        `undefined`.\n\n    list.length: integer\n        List length.\n\n    list.pop: Function\n        Removes and returns the last list value. If the list is empty, the\n        returned value is `undefined`.\n\n    list.push: Function\n        Adds a value to the end of the list.\n\n    list.remove: Function\n        Removes a list node from the list.\n\n    list.shift: Function\n        Removes and returns the first list value. If the list is empty, the\n        returned value is `undefined`.\n\n    list.toArray: Function\n        Returns an array of list values.\n\n    list.toJSON: Function\n        Serializes a list as JSON.\n\n    list.unshift: Function\n        Adds a value to the beginning of the list.\n\n    Examples\n    --------\n    > var list = DoublyLinkedList();\n    > list.push( 'foo' ).push( 'bar' );\n    > list.length\n    2\n    > list.pop()\n    'bar'\n    > list.length\n    1\n    > list.pop()\n    'foo'\n    > list.length\n    0\n\n    See Also\n    --------\n    LinkedList, Stack\n","doUntil":"\ndoUntil( fcn, predicate[, thisArg] )\n    Invokes a function until a test condition is true.\n\n    The condition is evaluated *after* executing the provided function; thus,\n    `fcn` *always* executes at least once.\n\n    When invoked, both the predicate function and the function to invoke are\n    provided a single argument:\n\n    - i: iteration number (starting from zero).\n\n    Parameters\n    ----------\n    fcn: Function\n        The function to invoke.\n\n    predicate: Function\n        The predicate function which indicates whether to stop invoking a\n        function.\n\n    thisArg: any (optional)\n        Execution context for the invoked function.\n\n    Examples\n    --------\n    > function predicate( i ) { return ( i >= 5 ); };\n    > function beep( i ) { console.log( 'boop: %d', i ); };\n    > doUntil( beep, predicate )\n    boop: 0\n    boop: 1\n    boop: 2\n    boop: 3\n    boop: 4\n\n    See Also\n    --------\n    doUntilAsync, doUntilEach, doWhile, until, whilst\n","doUntilAsync":"\ndoUntilAsync( fcn, predicate, done[, thisArg] )\n    Invokes a function until a test condition is true.\n\n    The condition is evaluated *after* executing the provided function; thus,\n    `fcn` *always* executes at least once.\n\n    The function to invoke is provided two arguments:\n\n    - i: iteration number (starting from zero).\n    - next: a callback which must be invoked before proceeding to the next\n      iteration.\n\n    The first argument of the `next` callback is an `error` argument. If `fcn`\n    calls the `next` callback with a truthy `error` argument, the function\n    suspends execution and immediately calls the `done` callback for subsequent\n    `error` handling.\n\n    The predicate function is provided two arguments:\n\n    - i: iteration number (starting from one).\n    - clbk: a callback indicating whether to invoke `fcn`.\n\n    The `clbk` function accepts two arguments:\n\n    - error: error argument.\n    - bool: test result.\n\n    If the test result is falsy, the function continues invoking `fcn`;\n    otherwise, the function invokes the `done` callback.\n\n    The `done` callback is invoked with an `error` argument and any arguments\n    passed to the final `next` callback.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Parameters\n    ----------\n    fcn: Function\n        The function to invoke.\n\n    predicate: Function\n        The predicate function which indicates whether to continue invoking a\n        function.\n\n    done: Function\n        Callback to invoke upon completion.\n\n    thisArg: any (optional)\n        Execution context for the invoked function.\n\n    Examples\n    --------\n    > function fcn( i, next ) {\n    ...     setTimeout( onTimeout, i );\n    ...     function onTimeout() {\n    ...         next( null, 'boop'+i );\n    ...     }\n    ... };\n    > function predicate( i, clbk ) { clbk( null, i >= 5 ); };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > doUntilAsync( fcn, predicate, done )\n    boop: 4\n\n    See Also\n    --------\n    doUntil, doWhileAsync, untilAsync, whileAsync\n","doUntilEach":"\ndoUntilEach( collection, fcn, predicate[, thisArg] )\n    Until a test condition is true, invokes a function for each element in a\n    collection.\n\n    The condition is evaluated *after* executing the provided function; thus,\n    `fcn` *always* executes at least once.\n\n    When invoked, both the predicate function and the function to apply are\n    provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    If provided an empty collection, both `value` and `index` are `undefined`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    predicate: Function\n        The predicate function which indicates whether to stop iterating over a\n        collection.\n\n    thisArg: any (optional)\n        Execution context for the applied function.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function predicate( v ) { return v !== v; };\n    > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n    > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n    > doUntilEach( arr, logger, predicate )\n    0: 1\n    1: 2\n    2: 3\n    3: 4\n    4: NaN\n\n    See Also\n    --------\n    doUntilEachRight, doWhileEach, untilEach\n","doUntilEachRight":"\ndoUntilEachRight( collection, fcn, predicate[, thisArg] )\n    Until a test condition is true, invokes a function for each element in a\n    collection, iterating from right to left.\n\n    The condition is evaluated *after* executing the provided function; thus,\n    `fcn` *always* executes at least once.\n\n    When invoked, both the predicate function and the function to apply are\n    provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    If provided an empty collection, both `value` and `index` are `undefined`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    predicate: Function\n        The predicate function which indicates whether to stop iterating over a\n        collection.\n\n    thisArg: any (optional)\n        Execution context for the applied function.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function predicate( v ) { return v !== v; };\n    > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n    > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n    > doUntilEachRight( arr, logger, predicate )\n    5: 5\n    4: 4\n    3: 3\n    2: 2\n    1: NaN\n\n    See Also\n    --------\n    doUntilEach, doWhileEachRight, untilEachRight\n","doWhile":"\ndoWhile( fcn, predicate[, thisArg] )\n    Invokes a function while a test condition is true.\n\n    The condition is evaluated *after* executing the provided function; thus,\n    `fcn` *always* executes at least once.\n\n    When invoked, both the predicate function and the function to invoke are\n    provided a single argument:\n\n    - i: iteration number (starting from zero).\n\n    Parameters\n    ----------\n    fcn: Function\n        The function to invoke.\n\n    predicate: Function\n        The predicate function which indicates whether to continue invoking a\n        function.\n\n    thisArg: any (optional)\n        Execution context for the invoked function.\n\n    Examples\n    --------\n    > function predicate( i ) { return ( i < 5 ); };\n    > function beep( i ) { console.log( 'boop: %d', i ); };\n    > doWhile( beep, predicate )\n    boop: 0\n    boop: 1\n    boop: 2\n    boop: 3\n    boop: 4\n\n    See Also\n    --------\n    doUntil, doWhileAsync, doWhileEach, until, whilst\n","doWhileAsync":"\ndoWhileAsync( fcn, predicate, done[, thisArg] )\n    Invokes a function while a test condition is true.\n\n    The condition is evaluated *after* executing the provided function; thus,\n    `fcn` *always* executes at least once.\n\n    The function to invoke is provided two arguments:\n\n    - i: iteration number (starting from zero).\n    - next: a callback which must be invoked before proceeding to the next\n      iteration.\n\n    The first argument of the `next` callback is an `error` argument. If `fcn`\n    calls the `next` callback with a truthy `error` argument, the function\n    suspends execution and immediately calls the `done` callback for subsequent\n    `error` handling.\n\n    The predicate function is provided two arguments:\n\n    - i: iteration number (starting from one).\n    - clbk: a callback indicating whether to invoke `fcn`.\n\n    The `clbk` function accepts two arguments:\n\n    - error: error argument.\n    - bool: test result.\n\n    If the test result is truthy, the function continues invoking `fcn`;\n    otherwise, the function invokes the `done` callback.\n\n    The `done` callback is invoked with an `error` argument and any arguments\n    passed to the final `next` callback.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Parameters\n    ----------\n    fcn: Function\n        The function to invoke.\n\n    predicate: Function\n        The predicate function which indicates whether to continue invoking a\n        function.\n\n    done: Function\n        Callback to invoke upon completion.\n\n    thisArg: any (optional)\n        Execution context for the invoked function.\n\n    Examples\n    --------\n    > function fcn( i, next ) {\n    ...     setTimeout( onTimeout, i );\n    ...     function onTimeout() {\n    ...         next( null, 'boop'+i );\n    ...     }\n    ... };\n    > function predicate( i, clbk ) { clbk( null, i < 5 ); };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > doWhileAsync( fcn, predicate, done )\n    boop: 4\n\n    See Also\n    --------\n    doUntilAsync, doWhile, untilAsync, whileAsync\n","doWhileEach":"\ndoWhileEach( collection, fcn, predicate[, thisArg] )\n    While a test condition is true, invokes a function for each element in a\n    collection.\n\n    The condition is evaluated *after* executing the provided function; thus,\n    `fcn` *always* executes at least once.\n\n    When invoked, both the predicate function and the function to apply are\n    provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    If provided an empty collection, both `value` and `index` are `undefined`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    predicate: Function\n        The predicate function which indicates whether to continue iterating\n        over a collection.\n\n    thisArg: any (optional)\n        Execution context for the applied function.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === v; };\n    > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n    > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n    > doWhileEach( arr, logger, predicate )\n    0: 1\n    1: 2\n    2: 3\n    3: 4\n    4: NaN\n\n    See Also\n    --------\n    doUntilEach, doWhileEachRight, whileEach\n","doWhileEachRight":"\ndoWhileEachRight( collection, fcn, predicate[, thisArg] )\n    While a test condition is true, invokes a function for each element in a\n    collection, iterating from right to left.\n\n    The condition is evaluated *after* executing the provided function; thus,\n    `fcn` *always* executes at least once.\n\n    When invoked, both the predicate function and the function to apply are\n    provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    If provided an empty collection, both `value` and `index` are `undefined`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    predicate: Function\n        The predicate function which indicates whether to continue iterating\n        over a collection.\n\n    thisArg: any (optional)\n        Execution context for the applied function.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === v; };\n    > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n    > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n    > doWhileEachRight( arr, logger, predicate )\n    5: 5\n    4: 4\n    3: 3\n    2: 2\n    1: NaN\n\n    See Also\n    --------\n    doUntilEachRight, doWhileEach, whileEachRight\n","dswap":"\ndswap( x, y[, dim] )\n    Interchanges two double-precision floating-point vectors.\n\n    For multi-dimensional input arrays, the function performs batched\n    computation, such that the function interchanges each pair of vectors in `x`\n    and `y` according to the specified dimension index.\n\n    Both input arrays must have the same shape.\n\n    Parameters\n    ----------\n    x: ndarray\n        First input array. Must have a 'float64' data type. Must have at least\n        one dimension and must have the same shape as the second input array.\n\n    y: ndarray\n        Second input array. Must have a 'float64' data type. Must have at least\n        one dimension and must have the same shape as the first input array.\n\n    dim: integer (optional)\n        Dimension index along which to interchange vectors. Must be a negative\n        integer. Negative indices are resolved relative to the last array\n        dimension, with the last dimension corresponding to `-1`. Default: -1.\n\n    Returns\n    -------\n    y: ndarray\n        The second input array `y`.\n\n    Examples\n    --------\n    > var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n    > var y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n    > dswap( x, y );\n    > x.data\n    <Float64Array>[ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n    > y.data\n    <Float64Array>[ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dswap, gswap, sswap\n","E":"\nE\n    Euler's number.\n\n    Examples\n    --------\n    > E\n    2.718281828459045\n\n","EMOJI":"\nEMOJI()\n    Returns an emoji database.\n\n    Returns\n    -------\n    out: Array\n        Emoji database.\n\n    Examples\n    --------\n    > var data = EMOJI()\n    [ {...}, ... ]\n\n    See Also\n    --------\n    EMOJI_CODE_PICTO, EMOJI_PICTO_CODE\n","EMOJI_CODE_PICTO":"\nEMOJI_CODE_PICTO()\n    Returns an object mapping emoji codes to pictographs.\n\n    Returns\n    -------\n    out: Object\n        An object mapping emoji codes to pictographs.\n\n    Examples\n    --------\n    > var out = EMOJI_CODE_PICTO()\n\n    See Also\n    --------\n    EMOJI, EMOJI_PICTO_CODE\n","EMOJI_PICTO_CODE":"\nEMOJI_PICTO_CODE()\n    Returns an object mapping emoji pictographs to codes.\n\n    Returns\n    -------\n    out: Object\n        An object mapping emoji pictographs to codes.\n\n    Examples\n    --------\n    > var out = EMOJI_PICTO_CODE()\n\n    See Also\n    --------\n    EMOJI, EMOJI_CODE_PICTO\n","emptyStream":"\nemptyStream( [options] )\n    Returns an \"empty\" readable stream.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var s = emptyStream();\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nemptyStream.factory( [options] )\n    Returns a function for creating empty readable streams.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true };\n    > var createStream = emptyStream.factory( opts );\n\n\nemptyStream.objectMode()\n    Returns an \"objectMode\" empty readable stream.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var s = emptyStream.objectMode();\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    constantStream\n","emptyStream.factory":"\nemptyStream.factory( [options] )\n    Returns a function for creating empty readable streams.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true };\n    > var createStream = emptyStream.factory( opts );","emptyStream.objectMode":"\nemptyStream.objectMode()\n    Returns an \"objectMode\" empty readable stream.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var s = emptyStream.objectMode();\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    constantStream","endsWith":"\nendsWith( str, search[, len] )\n    Tests if a string ends with the characters of another string.\n\n    If provided an empty search string, the function always returns `true`.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search string.\n\n    len: integer (optional)\n        Substring length. Restricts the search to a substring within the input\n        string beginning from the leftmost character. If provided a negative\n        value, `len` indicates to ignore the last `len` characters, returning\n        the same output as `str.length + len`. Default: `str.length`.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a string ends with the characters of another\n        string.\n\n    Examples\n    --------\n    > var bool = endsWith( 'beep', 'ep' )\n    true\n    > bool = endsWith( 'Beep', 'op' )\n    false\n    > bool = endsWith( 'Beep', 'ee', 3 )\n    true\n    > bool = endsWith( 'Beep', 'ee', -1 )\n    true\n    > bool = endsWith( 'beep', '' )\n    true\n\n    See Also\n    --------\n    startsWith\n","enumerableProperties":"\nenumerableProperties( value )\n    Returns an array of an object's own enumerable property names and symbols.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    props: Array\n        List of an object's own enumerable properties.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var props = enumerableProperties( obj )\n    [ 'beep' ]\n\n    See Also\n    --------\n    enumerablePropertiesIn, enumerablePropertySymbols, inheritedEnumerableProperties, objectKeys, nonEnumerableProperties, properties\n","enumerablePropertiesIn":"\nenumerablePropertiesIn( value )\n    Returns an array of an object's own and inherited enumerable property names\n    and symbols.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    props: Array\n        List of an object's own and inherited enumerable property names and\n        symbols.\n\n    Examples\n    --------\n    > var props = enumerablePropertiesIn( [] )\n\n    See Also\n    --------\n    enumerableProperties, enumerablePropertySymbolsIn, inheritedEnumerableProperties, keysIn, nonEnumerablePropertiesIn, propertiesIn\n","enumerablePropertySymbols":"\nenumerablePropertySymbols( value )\n    Returns an array of an object's own enumerable symbol properties.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's own enumerable symbol properties.\n\n    Examples\n    --------\n    > var obj = {};\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = true;\n    > desc.writable = true;\n    > desc.value = 'boop';\n    > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n    > defineProperty( obj, sym, desc );\n    > var symbols = enumerablePropertySymbols( obj )\n\n    See Also\n    --------\n    enumerablePropertySymbolsIn, inheritedEnumerablePropertySymbols, objectKeys, nonEnumerablePropertySymbols, propertySymbols\n","enumerablePropertySymbolsIn":"\nenumerablePropertySymbolsIn( value )\n    Returns an array of an object's own and inherited enumerable symbol\n    properties.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's own and inherited enumerable symbol properties.\n\n    Examples\n    --------\n    > var obj = {};\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = true;\n    > desc.writable = true;\n    > desc.value = 'boop';\n    > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n    > defineProperty( obj, sym, desc );\n    > var symbols = enumerablePropertySymbolsIn( obj )\n\n    See Also\n    --------\n    enumerablePropertySymbols, inheritedEnumerablePropertySymbols, keysIn, nonEnumerablePropertySymbolsIn, propertySymbolsIn\n","ENV":"\nENV\n    An object containing the user environment.\n\n    Examples\n    --------\n    > var user = ENV.USER\n    <string>\n\n    See Also\n    --------\n    ARGV\n","EPS":"\nEPS\n    Difference between one and the smallest value greater than one that can be\n    represented as a double-precision floating-point number.\n\n    Examples\n    --------\n    > EPS\n    2.220446049250313e-16\n\n    See Also\n    --------\n    FLOAT32_EPS\n","error2json":"\nerror2json( error )\n    Returns a JSON representation of an error object.\n\n    The following built-in error types are supported:\n\n    - Error\n    - URIError\n    - ReferenceError\n    - SyntaxError\n    - RangeError\n    - EvalError\n    - TypeError\n\n    The JSON object is guaranteed to have the following properties:\n\n    - type: error type.\n    - message: error message.\n\n    The only standardized cross-platform property is `message`. Depending on the\n    platform, the following properties *may* be present:\n\n    - name: error name.\n    - stack: stack trace.\n    - code: error code (Node.js system errors).\n    - errno: error code string (Node.js system errors).\n    - syscall: string representing the failed system call (Node.js system\n      errors).\n\n    The function also serializes all enumerable properties.\n\n    The implementation supports custom error types and sets the `type` field to\n    the closest built-in error type.\n\n    Parameters\n    ----------\n    error: Error\n        Error to serialize.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var err = new Error( 'beep' );\n    > var json = error2json( err )\n    <Object>\n\n    See Also\n    --------\n    reviveError\n","EULERGAMMA":"\nEULERGAMMA\n    The Euler-Mascheroni constant.\n\n    Examples\n    --------\n    > EULERGAMMA\n    0.5772156649015329\n\n","every":"\nevery( collection )\n    Tests whether all elements in a collection are truthy.\n\n    The function immediately returns upon encountering a falsy value.\n\n    If provided an empty collection, the function returns `true`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if all elements are truthy; otherwise, the\n        function returns `false`.\n\n    Examples\n    --------\n    > var arr = [ 1, 1, 1, 1, 1 ];\n    > var bool = every( arr )\n    true\n\n    See Also\n    --------\n    any, everyBy, forEach, none, some\n","everyBy":"\neveryBy( collection, predicate[, thisArg ] )\n    Tests whether all elements in a collection pass a test implemented by a\n    predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    The function immediately returns upon encountering a non-truthy return\n    value.\n\n    If provided an empty collection, the function returns `true`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns a truthy\n        value for all elements; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function positive( v ) { return ( v > 0 ); };\n    > var arr = [ 1, 2, 3, 4 ];\n    > var bool = everyBy( arr, positive )\n    true\n\n    See Also\n    --------\n    anyBy, everyByRight, forEach, noneBy, someBy\n","everyByAsync":"\neveryByAsync( collection, [options,] predicate, done )\n    Tests whether all elements in a collection pass a test implemented by a\n    predicate function.\n\n    When invoked, the predicate function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If the\n    predicate function accepts two arguments, the predicate function is\n    provided:\n\n    - value\n    - next\n\n    If the predicate function accepts three arguments, the predicate function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other predicate function signature, the predicate function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - result: test result.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    The function immediately returns upon encountering a non-truthy `result`\n    value and calls the `done` callback with `null` as the first argument and\n    `false` as the second argument.\n\n    If all elements succeed, the function calls the `done` callback with `null`\n    as the first argument and `true` as the second argument.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, true );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > everyByAsync( arr, predicate, done )\n    1000\n    2500\n    3000\n    true\n\n    // Limit number of concurrent invocations:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, true );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 3000, 2500, 1000 ];\n    > everyByAsync( arr, opts, predicate, done )\n    2500\n    3000\n    1000\n    true\n\n    // Process sequentially:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, true );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 3000, 2500, 1000 ];\n    > everyByAsync( arr, opts, predicate, done )\n    3000\n    2500\n    1000\n    true\n\n\neveryByAsync.factory( [options,] predicate )\n    Returns a function which tests whether all elements in a collection pass a\n    test implemented by a predicate function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, true );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = everyByAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n\n    See Also\n    --------\n    anyByAsync, everyBy, everyByRightAsync, forEachAsync, noneByAsync, someByAsync\n","everyByAsync.factory":"\neveryByAsync.factory( [options,] predicate )\n    Returns a function which tests whether all elements in a collection pass a\n    test implemented by a predicate function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, true );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = everyByAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n\n    See Also\n    --------\n    anyByAsync, everyBy, everyByRightAsync, forEachAsync, noneByAsync, someByAsync","everyByRight":"\neveryByRight( collection, predicate[, thisArg ] )\n    Tests whether all elements in a collection pass a test implemented by a\n    predicate function, iterating from right to left.\n\n    The predicate function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    The function immediately returns upon encountering a non-truthy return\n    value.\n\n    If provided an empty collection, the function returns `true`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns a truthy\n        value for all elements; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function positive( v ) { return ( v > 0 ); };\n    > var arr = [ 1, 2, 3, 4 ];\n    > var bool = everyByRight( arr, positive )\n    true\n\n    See Also\n    --------\n    anyBy, every, everyBy, forEachRight, noneByRight, someByRight\n","everyByRightAsync":"\neveryByRightAsync( collection, [options,] predicate, done )\n    Tests whether all elements in a collection pass a test implemented by a\n    predicate function, iterating from right to left.\n\n    When invoked, the predicate function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If the\n    predicate function accepts two arguments, the predicate function is\n    provided:\n\n    - value\n    - next\n\n    If the predicate function accepts three arguments, the predicate function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other predicate function signature, the predicate function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - result: test result.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    The function immediately returns upon encountering a non-truthy `result`\n    value and calls the `done` callback with `null` as the first argument and\n    `false` as the second argument.\n\n    If all elements succeed, the function calls the `done` callback with `null`\n    as the first argument and `true` as the second argument.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, true );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > everyByRightAsync( arr, predicate, done )\n    1000\n    2500\n    3000\n    true\n\n    // Limit number of concurrent invocations:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, true );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 1000, 2500, 3000 ];\n    > everyByRightAsync( arr, opts, predicate, done )\n    2500\n    3000\n    1000\n    true\n\n    // Process sequentially:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, true );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 1000, 2500, 3000 ];\n    > everyByRightAsync( arr, opts, predicate, done )\n    3000\n    2500\n    1000\n    true\n\n\neveryByRightAsync.factory( [options,] predicate )\n    Returns a function which tests whether all elements in a collection pass a\n    test implemented by a predicate function, iterating from right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, true );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = everyByRightAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n\n    See Also\n    --------\n    anyByRightAsync, everyByAsync, everyByRight, forEachRightAsync, noneByRightAsync, someByRightAsync\n","everyByRightAsync.factory":"\neveryByRightAsync.factory( [options,] predicate )\n    Returns a function which tests whether all elements in a collection pass a\n    test implemented by a predicate function, iterating from right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, true );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = everyByRightAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n\n    See Also\n    --------\n    anyByRightAsync, everyByAsync, everyByRight, forEachRightAsync, noneByRightAsync, someByRightAsync","everyInBy":"\neveryInBy( object, predicate[, thisArg ] )\n   Test whether all properties (own and inherited) of an object pass a\n   test implemented by a predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: object value.\n    - key: object key.\n    - object: the input object.\n\n    The function immediately returns upon encountering a non-truthy return\n    value.\n\n    If provided an empty object, the function returns `true`.\n\n    Parameters\n    ----------\n    object: Object\n        Input object over which to iterate.\n\n    predicate: Function\n        Test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns a truthy\n        value for all elements; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function positive( v ) { return ( v > 0 ); };\n    > var o = {a: 1, b: 2, c: 3};\n    > var bool = everyInBy( o, positive )\n    true\n\n    See Also\n    --------\n    anyInBy, noneInBy, someInBy, everyBy, everyOwnBy\n","everyOwnBy":"\neveryOwnBy( object, predicate[, thisArg ] )\n    Tests whether every own property of an object pass a test implemented by a\n    predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: property value.\n    - index: property key.\n    - object: the input object.\n\n    The function immediately returns upon encountering a non-truthy return\n    value.\n\n    If provided an empty object, the function returns `true`.\n\n    Parameters\n    ----------\n    object: Object\n        Input object.\n\n    predicate: Function\n        Test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns a truthy\n        value for all elements; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function positive( v ) { return ( v > 0 ); };\n    > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n    > var bool = everyOwnBy( obj, positive )\n    true\n\n    See Also\n    --------\n    anyOwnBy, everyInBy, noneOwnBy, someOwnBy, everyBy\n","evil":"\nevil( str )\n    Alias for `eval` global.\n\n    A reference to `eval` is treated differently by the compiler. For example,\n    when evaluating code containing block-scoped declarations  (e.g., `let`,\n    `const`, `function`, `class`), the compiler may throw an `error` complaining\n    that block-scoped declarations are not yet supported outside of\n    `strict mode`. One possible workaround is to include `\"use strict\";` in the\n    evaluated code.\n\n    Parameters\n    ----------\n    str: string\n        Code to evaluate.\n\n    Returns\n    -------\n    out: any\n        Returned value if applicable.\n\n    Examples\n    --------\n    > var v = evil( '5*4*3*2*1' )\n    120\n\n","EXEC_PATH":"\nEXEC_PATH\n    Absolute pathname of the executable which started the current Node.js\n    process.\n\n    Examples\n    --------\n    > EXEC_PATH\n    <string>\n\n","exists":"\nexists( path, clbk )\n    Asynchronously tests whether a path exists on the filesystem.\n\n    Parameters\n    ----------\n    path: string|Buffer\n        Path to test.\n\n    clbk: Function\n        Callback to invoke after testing for path existence. A callback may\n        accept a single argument, a boolean indicating whether a path exists, or\n        two arguments, an error argument and a boolean, matching the error-first\n        callback convention used in most asynchronous Node.js APIs.\n\n    Examples\n    --------\n    > function done( error, bool ) { console.log( bool ); };\n    > exists( './beep/boop', done );\n\n\nexists.sync( path )\n    Synchronously tests whether a path exists on the filesystem.\n\n    Parameters\n    ----------\n    path: string|Buffer\n        Path to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the path exists.\n\n    Examples\n    --------\n    > var bool = exists.sync( './beep/boop' )\n    <boolean>\n\n    See Also\n    --------\n    readFile, readDir\n","exists.sync":"\nexists.sync( path )\n    Synchronously tests whether a path exists on the filesystem.\n\n    Parameters\n    ----------\n    path: string|Buffer\n        Path to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the path exists.\n\n    Examples\n    --------\n    > var bool = exists.sync( './beep/boop' )\n    <boolean>\n\n    See Also\n    --------\n    readFile, readDir","expandAcronyms":"\nexpandAcronyms( str )\n    Expands acronyms in a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        String with expanded acronyms.\n\n    Examples\n    --------\n    > var str = 'LOL, this is fun. I am ROFL.';\n    > var out = expandAcronyms( str )\n    'laughing out loud, this is fun. I am rolling on the floor laughing.'\n\n    > str = 'brb, I need to check my mail. thx!';\n    > out = expandAcronyms( str )\n    'be right back, I need to check my mail. thanks!'\n\n    See Also\n    --------\n    expandContractions\n","expandContractions":"\nexpandContractions( str )\n    Expands all contractions to their formal equivalents.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        String with expanded contractions.\n\n    Examples\n    --------\n    > var str = 'I won\\'t be able to get y\\'all out of this one.';\n    > var out = expandContractions( str )\n    'I will not be able to get you all out of this one.'\n\n    > str = 'It oughtn\\'t to be my fault, because, you know, I didn\\'t know';\n    > out = expandContractions( str )\n    'It ought not to be my fault, because, you know, I did not know'\n\n","extname":"\nextname( filename )\n    Returns a filename extension.\n\n    Parameters\n    ----------\n    filename: string\n        Filename.\n\n    Returns\n    -------\n    ext: string\n        Filename extension.\n\n    Examples\n    --------\n    > var ext = extname( 'index.js' )\n    '.js'\n\n    See Also\n    --------\n    dirname\n","FancyArray":"\nFancyArray( dtype, buffer, shape, strides, offset, order[, options] )\n    Returns a FancyArray instance.\n\n    A FancyArray is an ndarray which supports slicing via indexing expressions.\n\n    A FancyArray is an ndarray instance and supports all ndarray options,\n    attributes, and methods. A FancyArray can be consumed by any API which\n    supports ndarray instances.\n\n    Indexing expressions provide a convenient and powerful means for creating\n    and operating on ndarray views; however, their use does entail a performance\n    cost. Indexing expressions are best suited for interactive use and\n    scripting. For performance critical applications, prefer equivalent\n    functional APIs supporting ndarray instances.\n\n    In older JavaScript environments which do not support Proxy objects, the use\n    of indexing expressions is not supported.\n\n    Parameters\n    ----------\n    dtype: string\n        Underlying data type.\n\n    buffer: ArrayLikeObject|TypedArray|Buffer\n        Data buffer. A data buffer must be an array-like object (i.e., have a\n        `length` property). For data buffers which are not indexed collections\n        (i.e., collections which cannot support direct index access, such as\n        `buffer[ index ]`; e.g., Complex64Array, Complex128Array, etc), a data\n        buffer should provide `#.get( idx )` and `#.set( v[, idx] )` methods.\n        Note that, for `set` methods, the value to set should be the first\n        argument, followed by the linear index, similar to the native typed\n        array `set` method.\n\n    shape: ArrayLikeObject<integer>\n        Array shape.\n\n    strides: ArrayLikeObject<integer>\n        Array strides.\n\n    offset: integer\n        Index offset.\n\n    order: string\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran-style).\n\n    options: Object (optional)\n        Options.\n\n    options.mode: string (optional)\n        Specifies how to handle indices which exceed array dimensions. If equal\n        to 'throw', an ndarray instance throws an error when an index exceeds\n        array dimensions. If equal to 'normalize', an ndarray instance\n        normalizes negative indices and throws an error when an index exceeds\n        array dimensions. If equal to 'wrap', an ndarray instance wraps around\n        indices exceeding array dimensions using modulo arithmetic. If equal to\n        'clamp', an ndarray instance sets an index exceeding array dimensions\n        to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n    options.submode: Array<string> (optional)\n        Specifies how to handle subscripts which exceed array dimensions. If a\n        mode for a corresponding dimension is equal to 'throw', an ndarray\n        instance throws an error when a subscript exceeds array dimensions. If\n        equal to 'normalize', an ndarray instance normalizes negative\n        subscripts and throws an error when a subscript exceeds array\n        dimensions. If equal to 'wrap', an ndarray instance wraps around\n        subscripts exceeding array dimensions using modulo arithmetic. If equal\n        to 'clamp', an ndarray instance sets a subscript exceeding array\n        dimensions to either `0` (minimum index) or the maximum index. If the\n        number of modes is fewer than the number of dimensions, the function\n        recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether an array should be read-only. Default: false.\n\n    Returns\n    -------\n    ndarray: FancyArray\n        FancyArray instance.\n\n    Examples\n    --------\n    // Create a new instance...\n    > var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\n    > var d = [ 2, 2 ]; // shape\n    > var s = [ 2, 1 ]; // strides\n    > var o = 0; // index offset\n    > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' )\n    <FancyArray>\n\n    // Get an element using subscripts:\n    > var v = arr.get( 1, 1 )\n    4.0\n\n    // Get an element using a linear index:\n    > v = arr.iget( 3 )\n    4.0\n\n    // Set an element using subscripts:\n    > arr.set( 1, 1, 40.0 );\n    > arr.get( 1, 1 )\n    40.0\n\n    // Set an element using a linear index:\n    > arr.iset( 3, 99.0 );\n    > arr.get( 1, 1 )\n    99.0\n\n\nFancyArray.prototype.byteLength\n    Size (in bytes) of the array (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of the array.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.byteLength\n    32\n\n\nFancyArray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.BYTES_PER_ELEMENT\n    8\n\n\nFancyArray.prototype.data\n    Pointer to the underlying data buffer.\n\n    Returns\n    -------\n    buf: ArrayLikeObject|TypedArray|Buffer\n        Underlying data buffer.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var buf = arr.data\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n\nFancyArray.prototype.dtype\n    Underlying data type.\n\n    Returns\n    -------\n    dtype: string\n        Underlying data type.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var dt = arr.dtype\n    'float64'\n\n\nFancyArray.prototype.flags\n    Meta information, such as information concerning the memory layout of the\n    array.\n\n    Returns\n    -------\n    flags: Object\n        Info object.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var fl = arr.flags\n    {...}\n\n\nFancyArray.prototype.length\n    Length of the array (i.e., number of elements).\n\n    Returns\n    -------\n    len: integer\n        Array length.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var len = arr.length\n    4\n\n\nFancyArray.prototype.ndims\n    Number of dimensions.\n\n    Returns\n    -------\n    ndims: integer\n        Number of dimensions.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var n = arr.ndims\n    2\n\n\nFancyArray.prototype.offset\n    Index offset which specifies the buffer index at which to start iterating\n    over array elements.\n\n    Returns\n    -------\n    offset: integer\n        Index offset.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.offset\n    0\n\n\nFancyArray.prototype.order\n    Array order.\n\n    The array order is either row-major (C-style) or column-major (Fortran-\n    style).\n\n    Returns\n    -------\n    order: string\n        Array order.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var ord = arr.order\n    'row-major'\n\n\nFancyArray.prototype.shape\n    Array shape.\n\n    Returns\n    -------\n    shape: Array\n        Array shape.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var sh = arr.shape\n    [ 2, 2 ]\n\n\nFancyArray.prototype.strides\n    Index strides which specify how to access data along corresponding array\n    dimensions.\n\n    Returns\n    -------\n    strides: Array\n        Index strides.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var st = arr.strides\n    [ 2, 1 ]\n\n\nFancyArray.prototype.get( ...idx )\n    Returns an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.get( 1, 1 )\n    4.0\n\n\nFancyArray.prototype.iget( idx )\n    Returns an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the input argument is ignored and, for clarity,\n    should not be provided.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.iget( 3 )\n    4.0\n\n\nFancyArray.prototype.set( ...idx, v )\n    Sets an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: FancyArray\n        FancyArray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > arr.set( 1, 1, -4.0 );\n    > arr.get( 1, 1 )\n    -4.0\n\n\nFancyArray.prototype.iset( idx, v )\n    Sets an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the first, and only, argument should be the\n    value to set.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: FancyArray\n        FancyArray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > arr.iset( 3, -4.0 );\n    > arr.iget( 3 )\n    -4.0\n\n\nFancyArray.prototype.toString()\n    Serializes a FancyArray as a string.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    str: string\n        Serialized ndarray string.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toString()\n    '...'\n\n\nFancyArray.prototype.toJSON()\n    Serializes a FancyArray as a JSON object.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toJSON()\n    {...}\n\n    See Also\n    --------\n    array, ndarray\n","FancyArray.prototype.byteLength":"\nFancyArray.prototype.byteLength\n    Size (in bytes) of the array (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of the array.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.byteLength\n    32","FancyArray.prototype.BYTES_PER_ELEMENT":"\nFancyArray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.BYTES_PER_ELEMENT\n    8","FancyArray.prototype.data":"\nFancyArray.prototype.data\n    Pointer to the underlying data buffer.\n\n    Returns\n    -------\n    buf: ArrayLikeObject|TypedArray|Buffer\n        Underlying data buffer.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var buf = arr.data\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]","FancyArray.prototype.dtype":"\nFancyArray.prototype.dtype\n    Underlying data type.\n\n    Returns\n    -------\n    dtype: string\n        Underlying data type.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var dt = arr.dtype\n    'float64'","FancyArray.prototype.flags":"\nFancyArray.prototype.flags\n    Meta information, such as information concerning the memory layout of the\n    array.\n\n    Returns\n    -------\n    flags: Object\n        Info object.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var fl = arr.flags\n    {...}","FancyArray.prototype.length":"\nFancyArray.prototype.length\n    Length of the array (i.e., number of elements).\n\n    Returns\n    -------\n    len: integer\n        Array length.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var len = arr.length\n    4","FancyArray.prototype.ndims":"\nFancyArray.prototype.ndims\n    Number of dimensions.\n\n    Returns\n    -------\n    ndims: integer\n        Number of dimensions.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var n = arr.ndims\n    2","FancyArray.prototype.offset":"\nFancyArray.prototype.offset\n    Index offset which specifies the buffer index at which to start iterating\n    over array elements.\n\n    Returns\n    -------\n    offset: integer\n        Index offset.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.offset\n    0","FancyArray.prototype.order":"\nFancyArray.prototype.order\n    Array order.\n\n    The array order is either row-major (C-style) or column-major (Fortran-\n    style).\n\n    Returns\n    -------\n    order: string\n        Array order.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var ord = arr.order\n    'row-major'","FancyArray.prototype.shape":"\nFancyArray.prototype.shape\n    Array shape.\n\n    Returns\n    -------\n    shape: Array\n        Array shape.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var sh = arr.shape\n    [ 2, 2 ]","FancyArray.prototype.strides":"\nFancyArray.prototype.strides\n    Index strides which specify how to access data along corresponding array\n    dimensions.\n\n    Returns\n    -------\n    strides: Array\n        Index strides.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var st = arr.strides\n    [ 2, 1 ]","FancyArray.prototype.get":"\nFancyArray.prototype.get( ...idx )\n    Returns an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.get( 1, 1 )\n    4.0","FancyArray.prototype.iget":"\nFancyArray.prototype.iget( idx )\n    Returns an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the input argument is ignored and, for clarity,\n    should not be provided.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.iget( 3 )\n    4.0","FancyArray.prototype.set":"\nFancyArray.prototype.set( ...idx, v )\n    Sets an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: FancyArray\n        FancyArray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > arr.set( 1, 1, -4.0 );\n    > arr.get( 1, 1 )\n    -4.0","FancyArray.prototype.iset":"\nFancyArray.prototype.iset( idx, v )\n    Sets an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the first, and only, argument should be the\n    value to set.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: FancyArray\n        FancyArray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > arr.iset( 3, -4.0 );\n    > arr.iget( 3 )\n    -4.0","FancyArray.prototype.toString":"\nFancyArray.prototype.toString()\n    Serializes a FancyArray as a string.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    str: string\n        Serialized ndarray string.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toString()\n    '...'","FancyArray.prototype.toJSON":"\nFancyArray.prototype.toJSON()\n    Serializes a FancyArray as a JSON object.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toJSON()\n    {...}\n\n    See Also\n    --------\n    array, ndarray","fastmath.abs":"\nfastmath.abs( x )\n    Computes an absolute value.\n\n    This implementation is not IEEE 754 compliant. If provided `-0`, the\n    function returns `-0`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    out: number\n        Absolute value.\n\n    Examples\n    --------\n    > var v = fastmath.abs( -1.0 )\n    1.0\n    > v = fastmath.abs( 2.0 )\n    2.0\n    > v = fastmath.abs( 0.0 )\n    0.0\n    > v = fastmath.abs( -0.0 )\n    -0.0\n    > v = fastmath.abs( NaN )\n    NaN\n\n    See Also\n    --------\n    base.abs\n","fastmath.acosh":"\nfastmath.acosh( x )\n    Computes the hyperbolic arccosine of a number.\n\n    The domain of `x` is restricted to `[1,+infinity)`. If `x < 1`, the function\n    will return `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    out: number\n        Hyperbolic arccosine (in radians).\n\n    Examples\n    --------\n    > var v = fastmath.acosh( 1.0 )\n    0.0\n    > v = fastmath.acosh( 2.0 )\n    ~1.317\n    > v = fastmath.acosh( NaN )\n    NaN\n\n    // The function overflows for large `x`:\n    > v = fastmath.acosh( 1.0e308 )\n    Infinity\n\n    See Also\n    --------\n    base.acosh\n","fastmath.ampbm":"\nfastmath.ampbm( x, y )\n    Computes the hypotenuse using the alpha max plus beta min algorithm.\n\n    The algorithm computes only an approximation.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Hypotenuse.\n\n    Examples\n    --------\n    > var h = fastmath.ampbm( 5.0, 12.0 )\n    ~13.514\n\n\nfastmath.ampbm.factory( alpha, beta, [nonnegative[, ints]] )\n    Returns a function to compute a hypotenuse using the alpha max plus beta min\n    algorithm.\n\n    Parameters\n    ----------\n    alpha: number\n        Alpha.\n\n    beta: number\n        Beta.\n\n    nonnegative: boolean (optional)\n        Boolean indicating whether input values are always nonnegative.\n\n    ints: boolean (optional)\n        Boolean indicating whether input values are always 32-bit integers.\n\n    Returns\n    -------\n    fcn: Function\n        Function to compute a hypotenuse.\n\n    Examples\n    --------\n    > var hypot = fastmath.ampbm.factory( 1.0, 0.5 )\n    <Function>\n\n    See Also\n    --------\n    base.hypot\n","fastmath.ampbm.factory":"\nfastmath.ampbm.factory( alpha, beta, [nonnegative[, ints]] )\n    Returns a function to compute a hypotenuse using the alpha max plus beta min\n    algorithm.\n\n    Parameters\n    ----------\n    alpha: number\n        Alpha.\n\n    beta: number\n        Beta.\n\n    nonnegative: boolean (optional)\n        Boolean indicating whether input values are always nonnegative.\n\n    ints: boolean (optional)\n        Boolean indicating whether input values are always 32-bit integers.\n\n    Returns\n    -------\n    fcn: Function\n        Function to compute a hypotenuse.\n\n    Examples\n    --------\n    > var hypot = fastmath.ampbm.factory( 1.0, 0.5 )\n    <Function>\n\n    See Also\n    --------\n    base.hypot","fastmath.asinh":"\nfastmath.asinh( x )\n    Computes the hyperbolic arcsine of a number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    out: number\n        Hyperbolic arcsine (in radians).\n\n    Examples\n    --------\n    > var v = fastmath.asinh( 0.0 )\n    0.0\n    > v = fastmath.asinh( 2.0 )\n    ~1.444\n    > v = fastmath.asinh( -2.0 )\n    ~-1.444\n    > v = fastmath.asinh( NaN )\n    NaN\n\n    // The function overflows for large `x`:\n    > v = fastmath.asinh( 1.0e200 )\n    Infinity\n\n    // The function underflows for small `x`:\n    > v = fastmath.asinh( 1.0e-50 )\n    0.0\n\n    See Also\n    --------\n    base.asinh\n","fastmath.atanh":"\nfastmath.atanh( x )\n    Computes the hyperbolic arctangent of a number.\n\n    The domain of `x` is restricted to `[-1,1]`. If `|x| > 1`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    out: number\n        Hyperbolic arctangent (in radians).\n\n    Examples\n    --------\n    > var v = fastmath.atanh( 0.0 )\n    0.0\n    > v = fastmath.atanh( 0.9 )\n    ~1.472\n    > v = fastmath.atanh( 1.0 )\n    Infinity\n    > v = fastmath.atanh( -1.0 )\n    -Infinity\n    > v = fastmath.atanh( NaN )\n    NaN\n\n    // The function underflows for small `x`:\n    > v = fastmath.atanh( 1.0e-17 )\n    0.0\n\n    See Also\n    --------\n    base.atanh\n","fastmath.hypot":"\nfastmath.hypot( x, y )\n    Computes the hypotenuse.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Hypotenuse.\n\n    Examples\n    --------\n    > var h = fastmath.hypot( -5.0, 12.0 )\n    13.0\n\n    // For a sufficiently large `x` and/or `y`, the function overflows:\n    > h = fastmath.hypot( 1.0e154, 1.0e154 )\n    Infinity\n\n    // For sufficiently small `x` and/or `y`, the function underflows:\n    > h = fastmath.hypot( 1e-200, 1.0e-200 )\n    0.0\n\n    See Also\n    --------\n    base.hypot\n","fastmath.log2Uint32":"\nfastmath.log2Uint32( x )\n    Returns an approximate binary logarithm (base two) of an unsigned 32-bit\n    integer `x`.\n\n    This function provides a performance boost when requiring only approximate\n    computations for integer arguments.\n\n    For high-precision applications, this function is never suitable.\n\n    Parameters\n    ----------\n    x: uinteger\n        Input value.\n\n    Returns\n    -------\n    out: uinteger\n        Integer binary logarithm (base two).\n\n    Examples\n    --------\n    > var v = fastmath.log2Uint32( 4 >>> 0 )\n    2\n    > v = fastmath.log2Uint32( 8 >>> 0 )\n    3\n    > v = fastmath.log2Uint32( 9 >>> 0 )\n    3\n\n    See Also\n    --------\n    base.log2\n","fastmath.max":"\nfastmath.max( x, y )\n    Returns the maximum value.\n\n    The function ignores the sign of `0` and does not check for `NaN` arguments.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    > var v = fastmath.max( 3.14, 4.2 )\n    4.2\n    > v = fastmath.max( 3.14, NaN )\n    NaN\n    > v = fastmath.max( NaN, 3.14 )\n    3.14\n    > v = fastmath.max( -0.0, +0.0 )\n    +0.0\n    > v = fastmath.max( +0.0, -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.max\n","fastmath.min":"\nfastmath.min( x, y )\n    Returns the minimum value.\n\n    The function ignores the sign of `0` and does not check for `NaN` arguments.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    > var v = fastmath.min( 3.14, 4.2 )\n    3.14\n    > v = fastmath.min( 3.14, NaN )\n    NaN\n    > v = fastmath.min( NaN, 3.14 )\n    3.14\n    > v = fastmath.min( -0.0, +0.0 )\n    +0.0\n    > v = fastmath.min( +0.0, -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.min\n","fastmath.powint":"\nfastmath.powint( x, y )\n    Evaluates the exponential function given a signed 32-bit integer exponent.\n\n    This function is not recommended for high-precision applications due to\n    error accumulation.\n\n    If provided a negative exponent, the function first computes the reciprocal\n    of the base and then evaluates the exponential function. This can introduce\n    significant error.\n\n    Parameters\n    ----------\n    x: number\n        Base.\n\n    y: integer\n        Signed 32-bit integer exponent.\n\n    Returns\n    -------\n    out: number\n        Function value.\n\n    Examples\n    --------\n    > var v = fastmath.powint( 2.0, 3 )\n    8.0\n    > v = fastmath.powint( 3.14, 0 )\n    1.0\n    > v = fastmath.powint( 2.0, -2 )\n    0.25\n    > v = fastmath.powint( 0.0, 0 )\n    1.0\n    > v = fastmath.powint( -3.14, 1 )\n    -3.14\n    > v = fastmath.powint( NaN, 0 )\n    NaN\n\n    See Also\n    --------\n    base.pow\n","fastmath.sqrtUint32":"\nfastmath.sqrtUint32( x )\n    Returns an approximate square root of an unsigned 32-bit integer `x`.\n\n    Prefer hardware `sqrt` over a software implementation.\n\n    When using a software `sqrt`, this function provides a performance boost\n    when an application requires only approximate computations for integer\n    arguments.\n\n    For applications requiring high-precision, this function is never suitable.\n\n    Parameters\n    ----------\n    x: uinteger\n        Input value.\n\n    Returns\n    -------\n    out: uinteger\n        Integer square root.\n\n    Examples\n    --------\n    > var v = fastmath.sqrtUint32( 9 >>> 0 )\n    3\n    > v = fastmath.sqrtUint32( 2 >>> 0 )\n    1\n    > v = fastmath.sqrtUint32( 3 >>> 0 )\n    1\n    > v = fastmath.sqrtUint32( 0 >>> 0 )\n    0\n\n    See Also\n    --------\n    base.sqrt\n","FEMALE_FIRST_NAMES_EN":"\nFEMALE_FIRST_NAMES_EN()\n    Returns a list of common female first names in English speaking countries.\n\n    Returns\n    -------\n    out: Array<string>\n        List of common female first names.\n\n    Examples\n    --------\n    > var list = FEMALE_FIRST_NAMES_EN()\n    [ 'Aaren', 'Aarika', 'Abagael', 'Abagail', ... ]\n\n    References\n    ----------\n    - Ward, Grady. 2002. \"Moby Word II.\" <http://www.gutenberg.org/files/3201/\n    3201.txt>.\n\n    See Also\n    --------\n    MALE_FIRST_NAMES_EN\n","FIFO":"\nFIFO()\n    First-in-first-out (FIFO) queue constructor.\n\n    Returns\n    -------\n    queue: Object\n        First-in-first-out queue.\n\n    queue.clear: Function\n        Clears the queue.\n\n    queue.first: Function\n        Returns the \"oldest\" queue value (i.e., the value which is \"first-out\").\n        If the queue is empty, the returned value is `undefined`.\n\n    queue.iterator: Function\n        Returns an iterator for iterating over a queue. If an environment\n        supports Symbol.iterator, the returned iterator is iterable. Note that,\n        in order to prevent confusion arising from queue mutation during\n        iteration, a returned iterator **always** iterates over a queue\n        \"snapshot\", which is defined as the list of queue elements at the time\n        of the method's invocation.\n\n    queue.last: Function\n        Returns the \"newest\" queue value (i.e., the value which is \"last-out\").\n        If the queue is empty, the returned value is `undefined`.\n\n    queue.length: integer\n        Queue length.\n\n    queue.pop: Function\n        Removes and returns the current \"first-out\" value from the queue. If the\n        queue is empty, the returned value is `undefined`.\n\n    queue.push: Function\n        Adds a value to the queue.\n\n    queue.toArray: Function\n        Returns an array of queue values.\n\n    queue.toJSON: Function\n        Serializes a queue as JSON.\n\n    Examples\n    --------\n    > var q = FIFO();\n    > q.push( 'foo' ).push( 'bar' );\n    > q.length\n    2\n    > q.pop()\n    'foo'\n    > q.length\n    1\n    > q.pop()\n    'bar'\n    > q.length\n    0\n\n    See Also\n    --------\n    Stack\n","filledarray":"\nfilledarray( [dtype] )\n    Creates a filled array.\n\n    Parameters\n    ----------\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = filledarray()\n    <Float64Array>\n    > arr = filledarray( 'float32' )\n    <Float32Array>\n\n\nfilledarray( value, length[, dtype] )\n    Returns a filled array having a specified length.\n\n    Parameters\n    ----------\n    value: any\n        Fill value.\n\n    length: integer\n        Array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = filledarray( 1.0, 5 )\n    <Float64Array>[ 1.0, 1.0, 1.0, 1.0, 1.0 ]\n    > arr = filledarray( 1, 5, 'int32' )\n    <Int32Array>[ 1, 1, 1, 1, 1 ]\n\n\nfilledarray( value, array[, dtype] )\n    Creates a filled array from another array (or array-like object).\n\n    Parameters\n    ----------\n    value: any\n        Fill value.\n\n    array: ArrayLikeObject\n        Array from which to generate another array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr1 = filledarray( 2.0, [ 0.5, 0.5, 0.5 ] )\n    <Float64Array>[ 2.0, 2.0, 2.0 ]\n    > var arr2 = filledarray( 1.0, arr1, 'float32' )\n    <Float32Array>[ 1.0, 1.0, 1.0 ]\n\n\nfilledarray( value, iterable[, dtype] )\n    Creates a filled array from an iterable.\n\n    Parameters\n    ----------\n    value: any\n        Fill value.\n\n    iterable: Iterable\n        Iterable from which to generate an array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr1 = iterConstant( 3.0, {'iter': 3} );\n    > var arr2 = filledarray( 1.0, arr1, 'float32' )\n    <Float32Array>[ 1.0, 1.0, 1.0 ]\n\n\nfilledarray( value, buffer[, byteOffset[, length]][, dtype] )\n    Returns a filled typed array view of an ArrayBuffer.\n\n    The 'generic' array data type is *not* supported.\n\n    Parameters\n    ----------\n    value: any\n        Fill value.\n\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 16 );\n    > var arr = filledarray( 1.0, buf, 0, 4, 'float32' )\n    <Float32Array>[ 1.0, 1.0, 1.0, 1.0 ]\n\n    See Also\n    --------\n    filledarrayBy, typedarray\n","filledarrayBy":"\nfilledarrayBy( [dtype] )\n    Creates a filled array.\n\n    Parameters\n    ----------\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = filledarrayBy()\n    <Float64Array>\n    > arr = filledarrayBy( 'float32' )\n    <Float32Array>\n\n\nfilledarrayBy( length[, dtype], clbk[, thisArg] )\n    Returns a filled array according to a provided callback function and having\n    a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > function clbk() { return 1.0; };\n    > var arr = filledarrayBy( 5, clbk )\n    <Float64Array>[ 1.0, 1.0, 1.0, 1.0, 1.0 ]\n    > arr = filledarrayBy( 5, 'int32', clbk )\n    <Int32Array>[ 1, 1, 1, 1, 1 ]\n\n\nfilledarrayBy( array[, dtype], clbk[, thisArg] )\n    Creates a filled array from another array (or array-like object) according\n    to a provided callback function.\n\n    Parameters\n    ----------\n    array: ArrayLikeObject\n        Array from which to generate another array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr1 = filledarrayBy( [ 0.5, 0.5, 0.5 ], constantFunction( 2.0 ) )\n    <Float64Array>[ 2.0, 2.0, 2.0 ]\n    > var arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\n    <Float32Array>[ 1.0, 1.0, 1.0 ]\n\n\nfilledarrayBy( iterable[, dtype], clbk[, thisArg] )\n    Creates a filled array from an iterable according to a provided callback\n    function.\n\n    Parameters\n    ----------\n    iterable: Iterable\n        Iterable from which to generate an array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr1 = iterConstant( 3.0, {'iter': 3} );\n    > var arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\n    <Float32Array>[ 1.0, 1.0, 1.0 ]\n\n\nfilledarrayBy( buffer[, byteOffset[, length]][, dtype], clbk[, thisArg] )\n    Returns a filled typed array view of an ArrayBuffer according to a provided\n    callback function.\n\n    The 'generic' array data type is *not* supported.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 16 );\n    > var arr = filledarrayBy( buf, 0, 4, 'float32', constantFunction( 1.0 ) )\n    <Float32Array>[ 1.0, 1.0, 1.0, 1.0 ]\n\n    See Also\n    --------\n    filledarray, typedarray\n","filterArguments":"\nfilterArguments( fcn, predicate[, thisArg] )\n    Returns a function that applies arguments to a provided function according\n    to a predicate function.\n\n    Only those arguments in which the predicate function returns a truthy value\n    are applied to a provided function.\n\n    The predicate function is provided the following arguments:\n\n    - value: argument value.\n    - index: argument index.\n\n    Parameters\n    ----------\n    fcn: Function\n        Input function.\n\n    predicate: Function\n        Predicate function.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Function\n        Function wrapper.\n\n    Examples\n    --------\n    > function foo( a, b ) { return [ a, b ]; };\n    > function predicate( v ) { return ( v !== 2 ); };\n    > var bar = filterArguments( foo, predicate );\n    > var out = bar( 1, 2, 3 )\n    [ 1, 3 ]\n\n    See Also\n    --------\n    maskArguments, rejectArguments, reorderArguments, reverseArguments\n","find":"\nfind( arr, [options,] clbk )\n    Finds elements in an array-like object that satisfy a test condition.\n\n    Parameters\n    ----------\n    arr: Array|TypedArray|string\n        Object from which elements will be tested.\n\n    options: Object (optional)\n        Options.\n\n    options.k: integer (optional)\n        Limits the number of returned elements. The sign determines the\n        direction in which to search. If set to a negative integer, the function\n        searches from last element to first element. Default: arr.length.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `indices`, indices are returned; if\n        `*`, both indices and values are returned. Default: 'indices'.\n\n    clbk: Function\n        Function invoked for each array element. If the return value is truthy,\n        the value is considered to have satisfied the test condition.\n\n    Returns\n    -------\n    out: Array\n        Array of indices, element values, or arrays of index-value pairs.\n\n    Examples\n    --------\n    > var data = [ 30, 20, 50, 60, 10 ];\n    > function condition( val ) { return val > 20; };\n    > var vals = find( data, condition )\n    [ 0, 2, 3 ]\n\n    // Limit number of results:\n    > data = [ 30, 20, 50, 60, 10 ];\n    > var opts = { 'k': 2, 'returns': 'values' };\n    > vals = find( data, opts, condition )\n    [ 30, 50 ]\n\n    // Return both indices and values as index-value pairs:\n    > data = [ 30, 20, 50, 60, 10 ];\n    > opts = { 'k': -2, 'returns': '*' };\n    > vals = find( data, opts, condition )\n    [ [ 3, 60 ], [ 2, 50 ] ]\n\n","firstChar":"\nfirstChar( str[, n][, options] )\n    Returns the first character(s) of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer (optional)\n        Number of characters to return. Default: 1.\n\n    options: Object (optional)\n        Options.\n\n    options.mode: string (optional)\n        Type of characters to return. The following modes are supported:\n\n        - grapheme: grapheme clusters. Appropriate for strings containing visual\n          characters which can span multiple Unicode code points (e.g., emoji).\n        - code_point: Unicode code points. Appropriate for strings containing\n          visual characters which are comprised of more than one Unicode code\n          unit (e.g., ideographic symbols and punctuation and mathematical\n          alphanumerics).\n        - code_unit': UTF-16 code units. Appropriate for strings containing\n          visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n          common characters, such as those from the Latin, Greek, and Cyrillic\n          alphabets).\n\n        Default: 'grapheme'.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = firstChar( 'beep' )\n    'b'\n    > out = firstChar( 'Boop', 1 )\n    'B'\n    > out = firstChar( 'foo bar', 5 )\n    'foo b'\n\n    See Also\n    --------\n    removeFirst, last\n","FIVETHIRTYEIGHT_FFQ":"\nFIVETHIRTYEIGHT_FFQ()\n    Returns FiveThirtyEight reader responses to a food frequency questionnaire\n    (FFQ).\n\n    Returns\n    -------\n    out: Array<Object>\n        FiveThirtyEight reader responses to a food frequency questionnaire\n        (FFQ).\n\n    Examples\n    --------\n    > var data = FIVETHIRTYEIGHT_FFQ()\n    [ {...}, ... ]\n\n    References\n    ----------\n    - Aschwanden, Christie. 2016. \"You Can't Trust What You Read About\n    Nutrition.\" <https://fivethirtyeight.com/features/you-cant-trust-what-you-\n    read-about-nutrition/>.\n\n    * If you use the data for publication or third party consumption, please\n    cite the listed reference.\n\n","flattenArray":"\nflattenArray( arr[, options] )\n    Flattens an array.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject\n        Input array.\n\n    options: Object (optional)\n        Options.\n\n    options.depth: integer (optional)\n        Maximum depth to flatten.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to deep copy array elements. Default: false.\n\n    Returns\n    -------\n    out: Array\n        Flattened array.\n\n    Examples\n    --------\n    > var arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n    > var out = flattenArray( arr )\n    [ 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n    // Set the maximum depth:\n    > arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n    > out = flattenArray( arr, { 'depth': 2 } )\n    [ 1, 2, 3, [ 4, [ 5 ], 6 ], 7, 8, 9 ]\n    > var bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n    true\n\n    // Deep copy:\n    > arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n    > out = flattenArray( arr, { 'depth': 2, 'copy': true } )\n    [ 1, 2, 3, [ 4, [ 5 ], 6 ], 7, 8, 9 ]\n    > bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n    false\n\n\nflattenArray.factory( dims[, options] )\n    Returns a function for flattening arrays having specified dimensions.\n\n    The returned function does not validate that input arrays actually have the\n    specified dimensions.\n\n    Parameters\n    ----------\n    dims: ArrayLike<integer>\n        Dimensions.\n\n    options: Object (optional)\n        Options.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to deep copy array elements. Default: false.\n\n    Returns\n    -------\n    fcn: Function\n        Flatten function.\n\n    Examples\n    --------\n    > var flatten = flattenArray.factory( [ 2, 2 ], {\n    ...     'copy': false\n    ... });\n    > var out = flatten( [ [ 1, 2 ], [ 3, 4 ] ] )\n    [ 1, 2, 3, 4 ]\n    > out = flatten( [ [ 5, 6 ], [ 7, 8 ] ] )\n    [ 5, 6, 7, 8 ]\n\n    See Also\n    --------\n    flattenObject\n","flattenArray.factory":"\nflattenArray.factory( dims[, options] )\n    Returns a function for flattening arrays having specified dimensions.\n\n    The returned function does not validate that input arrays actually have the\n    specified dimensions.\n\n    Parameters\n    ----------\n    dims: ArrayLike<integer>\n        Dimensions.\n\n    options: Object (optional)\n        Options.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to deep copy array elements. Default: false.\n\n    Returns\n    -------\n    fcn: Function\n        Flatten function.\n\n    Examples\n    --------\n    > var flatten = flattenArray.factory( [ 2, 2 ], {\n    ...     'copy': false\n    ... });\n    > var out = flatten( [ [ 1, 2 ], [ 3, 4 ] ] )\n    [ 1, 2, 3, 4 ]\n    > out = flatten( [ [ 5, 6 ], [ 7, 8 ] ] )\n    [ 5, 6, 7, 8 ]\n\n    See Also\n    --------\n    flattenObject","flattenObject":"\nflattenObject( obj[, options] )\n    Flattens an object.\n\n    Parameters\n    ----------\n    obj: ObjectLike\n        Object to flatten.\n\n    options: Object (optional)\n        Options.\n\n    options.depth: integer (optional)\n        Maximum depth to flatten.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to deep copy. Default: false.\n\n    options.flattenArrays: boolean (optional)\n        Boolean indicating whether to flatten arrays. Default: false.\n\n    options.delimiter: string (optional)\n        Key path delimiter. Default: '.'.\n\n    Returns\n    -------\n    out: ObjectLike\n        Flattened object.\n\n    Examples\n    --------\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var out = flattenObject( obj )\n    { 'a.b.c': 'd' }\n\n    // Set the `depth` option to flatten to a specified depth:\n    > obj = { 'a': { 'b': { 'c': 'd' } } };\n    > out = flattenObject( obj, { 'depth': 1 } )\n    { 'a.b': { 'c': 'd' } }\n    > var bool = ( obj.a.b === out[ 'a.b' ] )\n    true\n\n    // Set the `delimiter` option:\n    > obj = { 'a': { 'b': { 'c': 'd' } } };\n    > out = flattenObject( obj, { 'delimiter': '-|-' } )\n    { 'a-|-b-|-c': 'd' }\n\n    // Flatten arrays:\n    > obj = { 'a': { 'b': [ 1, 2, 3 ] } };\n    > out = flattenObject( obj, { 'flattenArrays': true } )\n    { 'a.b.0': 1, 'a.b.1': 2, 'a.b.2': 3 }\n\n\nflattenObject.factory( [options] )\n    Returns a function to flatten an object.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.depth: integer (optional)\n        Maximum depth to flatten.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to deep copy. Default: false.\n\n    options.flattenArrays: boolean (optional)\n        Boolean indicating whether to flatten arrays. Default: false.\n\n    options.delimiter: string (optional)\n        Key path delimiter. Default: '.'.\n\n    Returns\n    -------\n    fcn: Function\n        Flatten function.\n\n    Examples\n    --------\n    > var flatten = flattenObject.factory({\n    ...     'depth': 1,\n    ...     'copy': true,\n    ...     'delimiter': '|'\n    ... });\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var out = flatten( obj )\n    { 'a|b': { 'c': 'd' } }\n\n    See Also\n    --------\n    flattenArray\n","flattenObject.factory":"\nflattenObject.factory( [options] )\n    Returns a function to flatten an object.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.depth: integer (optional)\n        Maximum depth to flatten.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to deep copy. Default: false.\n\n    options.flattenArrays: boolean (optional)\n        Boolean indicating whether to flatten arrays. Default: false.\n\n    options.delimiter: string (optional)\n        Key path delimiter. Default: '.'.\n\n    Returns\n    -------\n    fcn: Function\n        Flatten function.\n\n    Examples\n    --------\n    > var flatten = flattenObject.factory({\n    ...     'depth': 1,\n    ...     'copy': true,\n    ...     'delimiter': '|'\n    ... });\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var out = flatten( obj )\n    { 'a|b': { 'c': 'd' } }\n\n    See Also\n    --------\n    flattenArray","flignerTest":"\nflignerTest( ...x[, options] )\n    Computes the Fligner-Killeen test for equal variances.\n\n    Parameters\n    ----------\n    x: ...Array\n        Measured values.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.groups: Array (optional)\n        Array of group indicators.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.method: string\n        Name of test.\n\n    out.df: Object\n        Degrees of freedom.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    // Data from Hollander & Wolfe (1973), p. 116:\n    > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n    > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n    > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n    > var out = flignerTest( x, y, z )\n\n    > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n    ...     3.8, 2.7, 4.0, 2.4,\n    ...     2.8, 3.4, 3.7, 2.2, 2.0\n    ... ];\n    > var groups = [\n    ...     'a', 'a', 'a', 'a', 'a',\n    ...     'b', 'b', 'b', 'b',\n    ...     'c', 'c', 'c', 'c', 'c'\n    ... ];\n    > out = flignerTest( arr, { 'groups': groups } )\n\n    See Also\n    --------\n    bartlettTest\n","FLOAT_WORD_ORDER":"\nFLOAT_WORD_ORDER\n    Platform float word order.\n\n    Possible values:\n\n    - 'little-endian'\n    - 'big-endian'\n    - 'unknown'\n\n    Examples\n    --------\n    > FLOAT_WORD_ORDER\n    <string>\n\n    See Also\n    --------\n    BYTE_ORDER\n","FLOAT16_CBRT_EPS":"\nFLOAT16_CBRT_EPS\n    Cube root of half-precision floating-point epsilon.\n\n    Examples\n    --------\n    > FLOAT16_CBRT_EPS\n    0.09921256574801247\n\n    See Also\n    --------\n    FLOAT16_EPS, FLOAT16_SQRT_EPS, FLOAT32_CBRT_EPS, CBRT_EPS\n","FLOAT16_EPS":"\nFLOAT16_EPS\n    Difference between one and the smallest value greater than one that can be\n    represented as a half-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT16_EPS\n    0.0009765625\n\n    See Also\n    --------\n    FLOAT32_EPS, EPS\n","FLOAT16_EXPONENT_BIAS":"\nFLOAT16_EXPONENT_BIAS\n    The bias of a half-precision floating-point number's exponent.\n\n    Examples\n    --------\n    > FLOAT16_EXPONENT_BIAS\n    15\n\n    See Also\n    --------\n    FLOAT32_EXPONENT_BIAS, FLOAT64_EXPONENT_BIAS\n","FLOAT16_MAX":"\nFLOAT16_MAX\n    Maximum half-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT16_MAX\n    65504.0\n\n    See Also\n    --------\n    FLOAT32_MAX, FLOAT64_MAX\n","FLOAT16_MAX_SAFE_INTEGER":"\nFLOAT16_MAX_SAFE_INTEGER\n    Maximum safe half-precision floating-point integer.\n\n    The maximum safe half-precision floating-point integer is given by\n    `2^11 - 1`.\n\n    Examples\n    --------\n    > FLOAT16_MAX_SAFE_INTEGER\n    2047\n\n    See Also\n    --------\n    FLOAT16_MIN_SAFE_INTEGER, FLOAT32_MAX_SAFE_INTEGER, FLOAT64_MAX_SAFE_INTEGER\n","FLOAT16_MIN_SAFE_INTEGER":"\nFLOAT16_MIN_SAFE_INTEGER\n    Minimum safe half-precision floating-point integer.\n\n    The minimum safe half-precision floating-point integer is given by\n    `-(2^11 - 1)`.\n\n    Examples\n    --------\n    > FLOAT16_MIN_SAFE_INTEGER\n    -2047\n\n    See Also\n    --------\n    FLOAT16_MAX_SAFE_INTEGER, FLOAT32_MIN_SAFE_INTEGER, FLOAT64_MIN_SAFE_INTEGER\n","FLOAT16_NINF":"\nFLOAT16_NINF\n    Half-precision floating-point negative infinity.\n\n    Examples\n    --------\n    > FLOAT16_NINF\n    -Infinity\n\n    See Also\n    --------\n    FLOAT16_PINF, FLOAT32_NINF, NINF\n","FLOAT16_NUM_BYTES":"\nFLOAT16_NUM_BYTES\n    Size (in bytes) of a half-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT16_NUM_BYTES\n    2\n\n    See Also\n    --------\n    FLOAT32_NUM_BYTES, FLOAT64_NUM_BYTES\n","FLOAT16_PINF":"\nFLOAT16_PINF\n    Half-precision floating-point positive infinity.\n\n    Examples\n    --------\n    > FLOAT16_PINF\n    Infinity\n\n    See Also\n    --------\n    FLOAT16_NINF, FLOAT32_PINF, PINF\n","FLOAT16_PRECISION":"\nFLOAT16_PRECISION\n    Effective number of bits in the significand of a half-precision floating-\n    point number.\n\n    The effective number of bits is `10` significand bits plus `1` hidden bit.\n\n    Examples\n    --------\n    > FLOAT16_PRECISION\n    11\n\n    See Also\n    --------\n    FLOAT32_PRECISION, FLOAT64_PRECISION\n","FLOAT16_SMALLEST_NORMAL":"\nFLOAT16_SMALLEST_NORMAL\n    Smallest positive normalized half-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT16_SMALLEST_NORMAL\n    6.103515625e-5\n\n    See Also\n    --------\n    FLOAT16_SMALLEST_SUBNORMAL, FLOAT32_SMALLEST_NORMAL, FLOAT64_SMALLEST_NORMAL\n","FLOAT16_SMALLEST_SUBNORMAL":"\nFLOAT16_SMALLEST_SUBNORMAL\n    Smallest positive denormalized half-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT16_SMALLEST_SUBNORMAL\n    5.960464477539063e-8\n\n    See Also\n    --------\n    FLOAT16_SMALLEST_NORMAL, FLOAT32_SMALLEST_SUBNORMAL, FLOAT64_SMALLEST_SUBNORMAL\n","FLOAT16_SQRT_EPS":"\nFLOAT16_SQRT_EPS\n    Square root of half-precision floating-point epsilon.\n\n    Examples\n    --------\n    > FLOAT16_SQRT_EPS\n    0.03125\n\n    See Also\n    --------\n    FLOAT16_EPS, FLOAT32_SQRT_EPS, SQRT_EPS\n","FLOAT32_ABS_MASK":"\nFLOAT32_ABS_MASK\n    Mask for excluding the sign bit of a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_ABS_MASK\n    2147483647\n    > base.toBinaryStringUint32( FLOAT32_ABS_MASK )\n    '01111111111111111111111111111111'\n\n    See Also\n    --------\n    FLOAT32_EXPONENT_MASK, FLOAT32_SIGN_MASK, FLOAT32_SIGNIFICAND_MASK\n","FLOAT32_CBRT_EPS":"\nFLOAT32_CBRT_EPS\n    Cube root of single-precision floating-point epsilon.\n\n    Examples\n    --------\n    > FLOAT32_CBRT_EPS\n    0.004921566694974899\n\n    See Also\n    --------\n    FLOAT32_EPS, FLOAT32_SQRT_EPS, CBRT_EPS\n","FLOAT32_E":"\nFLOAT32_E\n    Euler's number.\n\n    Examples\n    --------\n    > FLOAT32_E\n    2.7182817459106445\n\n    See Also\n    --------\n    E\n","FLOAT32_EPS":"\nFLOAT32_EPS\n    Difference between one and the smallest value greater than one that can be\n    represented as a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_EPS\n    1.1920928955078125e-7\n\n    See Also\n    --------\n    EPS\n","FLOAT32_EXPONENT_BIAS":"\nFLOAT32_EXPONENT_BIAS\n    The bias of a single-precision floating-point number's exponent.\n\n    Examples\n    --------\n    > FLOAT32_EXPONENT_BIAS\n    127\n\n    See Also\n    --------\n    FLOAT16_EXPONENT_BIAS, FLOAT64_EXPONENT_BIAS\n","FLOAT32_EXPONENT_MASK":"\nFLOAT32_EXPONENT_MASK\n    Mask for the exponent of a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_EXPONENT_MASK\n    2139095040\n    > base.toBinaryStringUint32( FLOAT32_EXPONENT_MASK )\n    '01111111100000000000000000000000'\n\n    See Also\n    --------\n    FLOAT32_SIGN_MASK, FLOAT32_SIGNIFICAND_MASK, FLOAT32_ABS_MASK\n","FLOAT32_FOURTH_PI":"\nFLOAT32_FOURTH_PI\n    One fourth times the mathematical constant `π`.\n\n    Examples\n    --------\n    > FLOAT32_FOURTH_PI\n    7.853981852531433e-1\n\n    See Also\n    --------\n    FLOAT32_HALF_PI, FLOAT32_PI, FLOAT32_TWO_PI\n","FLOAT32_HALF_LN_TWO":"\nFLOAT32_HALF_LN_TWO\n    One half times the natural logarithm of 2 as a single-precision\n    floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_HALF_LN_TWO\n    0.3465735912322998\n\n    See Also\n    --------\n    HALF_LN2\n","FLOAT32_HALF_PI":"\nFLOAT32_HALF_PI\n    One half times the mathematical constant `π`.\n\n    Examples\n    --------\n    > FLOAT32_HALF_PI\n    1.5707963705062866\n\n    See Also\n    --------\n    FLOAT32_FOURTH_PI, FLOAT32_PI, FLOAT32_TWO_PI\n","FLOAT32_LN_HALF":"\nFLOAT32_LN_HALF\n    Natural logarithm of `1/2` as a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_LN_HALF\n    -0.6931471824645996\n\n    See Also\n    --------\n    LN_HALF\n","FLOAT32_LN_PI":"\nFLOAT32_LN_PI\n    Natural logarithm of the mathematical constant `π` as a single-precision\n    floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_LN_PI\n    1.1447298526763916\n\n    See Also\n    --------\n    FLOAT32_PI, LN_PI\n","FLOAT32_LN_TEN":"\nFLOAT32_LN_TEN\n    Natural logarithm of `10` as a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_LN_TEN\n     2.3025851249694824\n\n    See Also\n    --------\n    FLOAT32_LN_TWO, LN10\n","FLOAT32_LN_TWO":"\nFLOAT32_LN_TWO\n    Natural logarithm of `2` as a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_LN_TWO\n    0.6931471824645996\n\n    See Also\n    --------\n    FLOAT32_LN_TEN, LN2\n","FLOAT32_MAX":"\nFLOAT32_MAX\n    Maximum single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_MAX\n    3.4028234663852886e+38\n\n    See Also\n    --------\n    FLOAT16_MAX, FLOAT64_MAX\n","FLOAT32_MAX_BASE2_EXPONENT":"\nFLOAT32_MAX_BASE2_EXPONENT\n    The maximum biased base 2 exponent for a single-precision floating-point\n    number.\n\n    Examples\n    --------\n    > FLOAT32_MAX_BASE2_EXPONENT\n    127\n\n    See Also\n    --------\n    FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE2_EXPONENT\n","FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL\n    The maximum biased base 2 exponent for a subnormal single-precision\n    floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL\n    -127\n\n    See Also\n    --------\n    FLOAT32_MAX_BASE2_EXPONENT, FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n","FLOAT32_MAX_BASE10_EXPONENT":"\nFLOAT32_MAX_BASE10_EXPONENT\n    The maximum base 10 exponent for a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_MAX_BASE10_EXPONENT\n    38\n\n    See Also\n    --------\n    FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE10_EXPONENT\n","FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL\n    The maximum base 10 exponent for a subnormal single-precision floating-point\n    number.\n\n    Examples\n    --------\n    > FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL\n    -38\n\n    See Also\n    --------\n    FLOAT32_MAX_BASE10_EXPONENT, FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n","FLOAT32_MAX_SAFE_FIBONACCI":"\nFLOAT32_MAX_SAFE_FIBONACCI\n    Maximum safe Fibonacci number when stored in single-precision floating-point\n    format.\n\n    Examples\n    --------\n    > FLOAT32_MAX_SAFE_FIBONACCI\n    14930352\n\n    See Also\n    --------\n    FLOAT64_MAX_SAFE_FIBONACCI\n","FLOAT32_MAX_SAFE_INTEGER":"\nFLOAT32_MAX_SAFE_INTEGER\n    Maximum safe single-precision floating-point integer.\n\n    The maximum safe single-precision floating-point integer is given by\n    `2^24 - 1`.\n\n    Examples\n    --------\n    > FLOAT32_MAX_SAFE_INTEGER\n    16777215\n\n    See Also\n    --------\n    FLOAT16_MAX_SAFE_INTEGER, FLOAT32_MIN_SAFE_INTEGER, FLOAT64_MAX_SAFE_INTEGER\n","FLOAT32_MAX_SAFE_NTH_FACTORIAL":"\nFLOAT32_MAX_SAFE_NTH_FACTORIAL\n    Maximum safe nth factorial when stored in single-precision floating-\n    point format.\n\n    Examples\n    --------\n    > FLOAT32_MAX_SAFE_NTH_FACTORIAL\n    34\n\n","FLOAT32_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT32_MAX_SAFE_NTH_FIBONACCI\n    Maximum safe nth Fibonacci number when stored in single-precision floating-\n    point format.\n\n    Examples\n    --------\n    > FLOAT32_MAX_SAFE_NTH_FIBONACCI\n    36\n\n    See Also\n    --------\n    FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT32_MAX_SAFE_NTH_LUCAS":"\nFLOAT32_MAX_SAFE_NTH_LUCAS\n    Maximum safe nth Lucas number when stored in single-precision floating-point\n    format.\n\n    Examples\n    --------\n    > FLOAT32_MAX_SAFE_NTH_LUCAS\n    34\n\n    See Also\n    --------\n    FLOAT64_MAX_SAFE_NTH_LUCAS\n","FLOAT32_MIN_BASE2_EXPONENT":"\nFLOAT32_MIN_BASE2_EXPONENT\n    The minimum biased base 2 exponent for a normalized single-precision\n    floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_MIN_BASE2_EXPONENT\n    -126\n\n    See Also\n    --------\n    FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL\n    The minimum biased base 2 exponent for a subnormal single-precision\n    floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL\n    -149\n\n    See Also\n    --------\n    FLOAT32_MIN_BASE2_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT32_MIN_BASE10_EXPONENT":"\nFLOAT32_MIN_BASE10_EXPONENT\n    The minimum base 10 exponent for a normal single-precision floating-\n    point number.\n\n    Examples\n    --------\n    > FLOAT32_MIN_BASE10_EXPONENT\n    -37\n\n    See Also\n    --------\n    FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT\n","FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL\n    The minimum base 10 exponent for a subnormal single-precision floating-\n    point number.\n\n    Examples\n    --------\n    > FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL\n    -45\n\n    See Also\n    --------\n    FLOAT32_MIN_BASE10_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT32_MIN_SAFE_INTEGER":"\nFLOAT32_MIN_SAFE_INTEGER\n    Minimum safe single-precision floating-point integer.\n\n    The minimum safe single-precision floating-point integer is given by\n    `-(2^24 - 1)`.\n\n    Examples\n    --------\n    > FLOAT32_MIN_SAFE_INTEGER\n    -16777215\n\n    See Also\n    --------\n    FLOAT16_MIN_SAFE_INTEGER, FLOAT32_MAX_SAFE_INTEGER, FLOAT64_MIN_SAFE_INTEGER\n","FLOAT32_NAN":"\nFLOAT32_NAN\n    Single-precision floating-point NaN.\n\n    Examples\n    --------\n    > FLOAT32_NAN\n    NaN\n\n    See Also\n    --------\n    NAN\n","FLOAT32_NINF":"\nFLOAT32_NINF\n    Single-precision floating-point negative infinity.\n\n    Examples\n    --------\n    > FLOAT32_NINF\n    -Infinity\n\n    See Also\n    --------\n    FLOAT32_PINF, NINF\n","FLOAT32_NUM_BYTES":"\nFLOAT32_NUM_BYTES\n    Size (in bytes) of a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_NUM_BYTES\n    4\n\n    See Also\n    --------\n    FLOAT16_NUM_BYTES, FLOAT64_NUM_BYTES\n","FLOAT32_PHI":"\nFLOAT32_PHI\n    Golden ratio.\n\n    Examples\n    --------\n    > FLOAT32_PHI\n    1.6180340051651\n\n    See Also\n    --------\n    PHI\n","FLOAT32_PI":"\nFLOAT32_PI\n    The mathematical constant `π`.\n\n    Examples\n    --------\n    > FLOAT32_PI\n    3.1415927410125732\n\n    See Also\n    --------\n    FLOAT32_FOURTH_PI, FLOAT32_HALF_PI, FLOAT32_TWO_PI\n","FLOAT32_PINF":"\nFLOAT32_PINF\n    Single-precision floating-point positive infinity.\n\n    Examples\n    --------\n    > FLOAT32_PINF\n    Infinity\n\n    See Also\n    --------\n    FLOAT32_NINF, PINF\n","FLOAT32_PRECISION":"\nFLOAT32_PRECISION\n    Effective number of bits in the significand of a single-precision floating-\n    point number.\n\n    The effective number of bits is `23` significand bits plus `1` hidden bit.\n\n    Examples\n    --------\n    > FLOAT32_PRECISION\n    24\n\n    See Also\n    --------\n    FLOAT16_PRECISION, FLOAT64_PRECISION\n","FLOAT32_SIGN_MASK":"\nFLOAT32_SIGN_MASK\n    Mask for the sign bit of a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_SIGN_MASK\n    2147483648\n    > base.toBinaryStringUint32( FLOAT32_SIGN_MASK )\n    '10000000000000000000000000000000'\n\n    See Also\n    --------\n    FLOAT32_EXPONENT_MASK, FLOAT32_SIGNIFICAND_MASK, FLOAT32_ABS_MASK\n","FLOAT32_SIGNIFICAND_MASK":"\nFLOAT32_SIGNIFICAND_MASK\n    Mask for the significand of a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_SIGNIFICAND_MASK\n    8388607\n    > base.toBinaryStringUint32( FLOAT32_SIGNIFICAND_MASK )\n    '00000000011111111111111111111111'\n\n    See Also\n    --------\n    FLOAT32_EXPONENT_MASK, FLOAT32_SIGN_MASK, FLOAT32_ABS_MASK\n","FLOAT32_SMALLEST_NORMAL":"\nFLOAT32_SMALLEST_NORMAL\n    Smallest positive normalized single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_SMALLEST_NORMAL\n    1.1754943508222875e-38\n\n    See Also\n    --------\n    FLOAT32_SMALLEST_SUBNORMAL, FLOAT64_SMALLEST_NORMAL\n","FLOAT32_SMALLEST_SUBNORMAL":"\nFLOAT32_SMALLEST_SUBNORMAL\n    Smallest positive denormalized single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_SMALLEST_SUBNORMAL\n    1.401298464324817e-45\n\n    See Also\n    --------\n    FLOAT32_SMALLEST_NORMAL, FLOAT64_SMALLEST_SUBNORMAL\n","FLOAT32_SQRT_EPS":"\nFLOAT32_SQRT_EPS\n    Square root of single-precision floating-point epsilon.\n\n    Examples\n    --------\n    > FLOAT32_SQRT_EPS\n    0.0003452669770922512\n\n    See Also\n    --------\n    FLOAT32_EPS, SQRT_EPS\n","FLOAT32_SQRT_HALF":"\nFLOAT32_SQRT_HALF\n    Square root of `1/2` as a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_SQRT_HALF\n    0.7071067690849304\n\n    See Also\n    --------\n    SQRT_HALF\n","FLOAT32_SQRT_HALF_PI":"\nFLOAT32_SQRT_HALF_PI\n    Square root of `π` divided by `2` as a single-precision \n    floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_SQRT_HALF_PI\n    1.2533141374588013\n\n    See Also\n    --------\n    SQRT_HALF_PI","FLOAT32_SQRT_PHI":"\nFLOAT32_SQRT_PHI\n    Square root of the golden ratio as a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_SQRT_PHI\n    1.272019624710083\n\n    See Also\n    --------\n    SQRT_PHI\n","FLOAT32_SQRT_PI":"\nFLOAT32_SQRT_PI\n    Square root of the mathematical constant `π` as a single-precision\n    floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_SQRT_PI\n    1.7724539041519165\n\n    See Also\n    --------\n    FLOAT32_PI, SQRT_PI\n","FLOAT32_SQRT_THREE":"\nFLOAT32_SQRT_THREE\n    Square root of `3` as a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_SQRT_THREE\n    1.7320507764816284\n\n    See Also\n    --------\n    FLOAT32_SQRT_TWO, SQRT_THREE\n","FLOAT32_SQRT_TWO":"\nFLOAT32_SQRT_TWO\n    Square root of `2` as a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_SQRT_TWO\n    1.4142135381698608\n\n    See Also\n    --------\n    FLOAT32_SQRT_THREE, SQRT_TWO\n","FLOAT32_SQRT_TWO_PI":"\nFLOAT32_SQRT_TWO_PI\n    Square root of the `π` times `2` as single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_SQRT_TWO_PI\n    2.5066282749176025\n\n    See Also\n    --------\n    FLOAT32_PI, FLOAT32_TWO_PI, SQRT_TWO_PI\n","FLOAT32_TWO_PI":"\nFLOAT32_TWO_PI\n    The mathematical constant `π` times `2`.\n\n    Examples\n    --------\n    > FLOAT32_TWO_PI\n    6.2831854820251465\n\n    See Also\n    --------\n    FLOAT32_FOURTH_PI, FLOAT32_HALF_PI, FLOAT32_PI\n","Float32Array":"\nFloat32Array()\n    A typed array constructor which returns a typed array representing an array\n    of single-precision floating-point numbers in the platform byte order.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Float32Array()\n    <Float32Array>\n\n\nFloat32Array( length )\n    Returns a typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( 5 )\n    <Float32Array>[ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat32Array( typedarray )\n    Creates a typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float64Array( [ 0.5, 0.5, 0.5 ] );\n    > var arr2 = new Float32Array( arr1 )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]\n\n\nFloat32Array( obj )\n    Creates a typed array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a typed array.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 0.5, 0.5, 0.5 ];\n    > var arr2 = new Float32Array( arr1 )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]\n\n\nFloat32Array( buffer[, byteOffset[, length]] )\n    Returns a typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 16 );\n    > var arr = new Float32Array( buf, 0, 4 )\n    <Float32Array>[ 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat32Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2.0; };\n    > var arr = Float32Array.from( [ 1.0, -1.0 ], mapFcn )\n    <Float32Array>[ 2.0, -2.0 ]\n\n\nFloat32Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Float32Array.of( 2.0, -2.0 )\n    <Float32Array>[ 2.0, -2.0 ]\n\n\nFloat32Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Float32Array.BYTES_PER_ELEMENT\n    4\n\n\nFloat32Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Float32Array.name\n    'Float32Array'\n\n\nFloat32Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>\n\n\nFloat32Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( 5 );\n    > arr.byteLength\n    20\n\n\nFloat32Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Float32Array( 5 );\n    > arr.byteOffset\n    0\n\n\nFloat32Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Float32Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    4\n\n\nFloat32Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Float32Array( 5 );\n    > arr.length\n    5\n\n\nFloat32Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Float32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    2.0\n    > arr[ 4 ]\n    -2.0\n\n\nFloat32Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1.0 ]\n    > it.next().value\n    [ 1, -1.0 ]\n    > it.next().done\n    true\n\n\nFloat32Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > function predicate( v ) { return ( v >= 0.0 ); };\n    > arr.every( predicate )\n    false\n\n\nFloat32Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Float32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > arr.fill( 2.0 );\n    > arr[ 0 ]\n    2.0\n    > arr[ 1 ]\n    2.0\n\n\nFloat32Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v >= 0.0 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2\n\n\nFloat32Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > var v = arr.find( predicate )\n    -1.0\n\n\nFloat32Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > var idx = arr.findIndex( predicate )\n    2\n\n\nFloat32Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:1 1:0 2:-1 '\n\n\nFloat32Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > var bool = arr.includes( 2.0 )\n    false\n    > bool = arr.includes( -1.0 )\n    true\n\n\nFloat32Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > var idx = arr.indexOf( 2.0 )\n    -1\n    > idx = arr.indexOf( -1.0 )\n    2\n\n\nFloat32Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > arr.join( '|' )\n    '1|0|-1'\n\n\nFloat32Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true\n\n\nFloat32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n    > var idx = arr.lastIndexOf( 2.0 )\n    -1\n    > idx = arr.lastIndexOf( 0.0 )\n    3\n\n\nFloat32Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( v ) { return v * 2.0; };\n    > var arr2 = arr1.map( fcn )\n    <Float32Array>[ 2.0, 0.0, -2.0 ]\n\n\nFloat32Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0.0 )\n    2.0\n\n\nFloat32Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0.0 )\n    2.0\n\n\nFloat32Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Float32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] )\n    <Float32Array>\n    > arr.reverse()\n    <Float32Array>[ -1.0, 0.0, 1.0 ]\n\n\nFloat32Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > arr.set( [ -2.0, 2.0 ], 1 );\n    > arr[ 1 ]\n    -2.0\n    > arr[ 2 ]\n    2.0\n\n\nFloat32Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    0.0\n    > arr2[ 1 ]\n    -1.0\n\n\nFloat32Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > arr.some( predicate )\n    true\n\n\nFloat32Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Float32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n    > arr.sort()\n    <Float32Array>[ -2.0, -1.0, 0.0, 1.0, 2.0 ]\n\n\nFloat32Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Float32Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Float32Array>[ 0.0, 2.0, -2.0 ]\n\n\nFloat32Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n    > arr.toLocaleString()\n    '1,-1,0'\n\n\nFloat32Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n    > arr.toString()\n    '1,-1,0'\n\n\nFloat32Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > it = arr.values();\n    > it.next().value\n    1.0\n    > it.next().value\n    -1.0\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Float32Array.from":"\nFloat32Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2.0; };\n    > var arr = Float32Array.from( [ 1.0, -1.0 ], mapFcn )\n    <Float32Array>[ 2.0, -2.0 ]","Float32Array.of":"\nFloat32Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Float32Array.of( 2.0, -2.0 )\n    <Float32Array>[ 2.0, -2.0 ]","Float32Array.BYTES_PER_ELEMENT":"\nFloat32Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Float32Array.BYTES_PER_ELEMENT\n    4","Float32Array.name":"\nFloat32Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Float32Array.name\n    'Float32Array'","Float32Array.prototype.buffer":"\nFloat32Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>","Float32Array.prototype.byteLength":"\nFloat32Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( 5 );\n    > arr.byteLength\n    20","Float32Array.prototype.byteOffset":"\nFloat32Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Float32Array( 5 );\n    > arr.byteOffset\n    0","Float32Array.prototype.BYTES_PER_ELEMENT":"\nFloat32Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Float32Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    4","Float32Array.prototype.length":"\nFloat32Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Float32Array( 5 );\n    > arr.length\n    5","Float32Array.prototype.copyWithin":"\nFloat32Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Float32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    2.0\n    > arr[ 4 ]\n    -2.0","Float32Array.prototype.entries":"\nFloat32Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1.0 ]\n    > it.next().value\n    [ 1, -1.0 ]\n    > it.next().done\n    true","Float32Array.prototype.every":"\nFloat32Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > function predicate( v ) { return ( v >= 0.0 ); };\n    > arr.every( predicate )\n    false","Float32Array.prototype.fill":"\nFloat32Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Float32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > arr.fill( 2.0 );\n    > arr[ 0 ]\n    2.0\n    > arr[ 1 ]\n    2.0","Float32Array.prototype.filter":"\nFloat32Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v >= 0.0 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2","Float32Array.prototype.find":"\nFloat32Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > var v = arr.find( predicate )\n    -1.0","Float32Array.prototype.findIndex":"\nFloat32Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > var idx = arr.findIndex( predicate )\n    2","Float32Array.prototype.forEach":"\nFloat32Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:1 1:0 2:-1 '","Float32Array.prototype.includes":"\nFloat32Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > var bool = arr.includes( 2.0 )\n    false\n    > bool = arr.includes( -1.0 )\n    true","Float32Array.prototype.indexOf":"\nFloat32Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > var idx = arr.indexOf( 2.0 )\n    -1\n    > idx = arr.indexOf( -1.0 )\n    2","Float32Array.prototype.join":"\nFloat32Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > arr.join( '|' )\n    '1|0|-1'","Float32Array.prototype.keys":"\nFloat32Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true","Float32Array.prototype.lastIndexOf":"\nFloat32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n    > var idx = arr.lastIndexOf( 2.0 )\n    -1\n    > idx = arr.lastIndexOf( 0.0 )\n    3","Float32Array.prototype.map":"\nFloat32Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( v ) { return v * 2.0; };\n    > var arr2 = arr1.map( fcn )\n    <Float32Array>[ 2.0, 0.0, -2.0 ]","Float32Array.prototype.reduce":"\nFloat32Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0.0 )\n    2.0","Float32Array.prototype.reduceRight":"\nFloat32Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0.0 )\n    2.0","Float32Array.prototype.reverse":"\nFloat32Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Float32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] )\n    <Float32Array>\n    > arr.reverse()\n    <Float32Array>[ -1.0, 0.0, 1.0 ]","Float32Array.prototype.set":"\nFloat32Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > arr.set( [ -2.0, 2.0 ], 1 );\n    > arr[ 1 ]\n    -2.0\n    > arr[ 2 ]\n    2.0","Float32Array.prototype.slice":"\nFloat32Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    0.0\n    > arr2[ 1 ]\n    -1.0","Float32Array.prototype.some":"\nFloat32Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > arr.some( predicate )\n    true","Float32Array.prototype.sort":"\nFloat32Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Float32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n    > arr.sort()\n    <Float32Array>[ -2.0, -1.0, 0.0, 1.0, 2.0 ]","Float32Array.prototype.subarray":"\nFloat32Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Float32Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Float32Array>[ 0.0, 2.0, -2.0 ]","Float32Array.prototype.toLocaleString":"\nFloat32Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n    > arr.toLocaleString()\n    '1,-1,0'","Float32Array.prototype.toString":"\nFloat32Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n    > arr.toString()\n    '1,-1,0'","Float32Array.prototype.values":"\nFloat32Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > it = arr.values();\n    > it.next().value\n    1.0\n    > it.next().value\n    -1.0\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","FLOAT64_EXPONENT_BIAS":"\nFLOAT64_EXPONENT_BIAS\n    The bias of a double-precision floating-point number's exponent.\n\n    Examples\n    --------\n    > FLOAT64_EXPONENT_BIAS\n    1023\n\n    See Also\n    --------\n    FLOAT16_EXPONENT_BIAS, FLOAT32_EXPONENT_BIAS\n","FLOAT64_HIGH_WORD_ABS_MASK":"\nFLOAT64_HIGH_WORD_ABS_MASK\n    High word mask for excluding the sign bit of a double-precision floating-\n    point number.\n\n    Examples\n    --------\n    > FLOAT64_HIGH_WORD_ABS_MASK\n    2147483647\n    > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_ABS_MASK )\n    '01111111111111111111111111111111'\n\n    See Also\n    --------\n    FLOAT64_HIGH_WORD_SIGN_MASK, FLOAT64_HIGH_WORD_EXPONENT_MASK, FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n","FLOAT64_HIGH_WORD_EXPONENT_MASK":"\nFLOAT64_HIGH_WORD_EXPONENT_MASK\n    High word mask for the exponent of a double-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT64_HIGH_WORD_EXPONENT_MASK\n    2146435072\n    > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_EXPONENT_MASK )\n    '01111111111100000000000000000000'\n\n    See Also\n    --------\n    FLOAT64_HIGH_WORD_SIGNIFICAND_MASK, FLOAT64_HIGH_WORD_SIGN_MASK, FLOAT64_HIGH_WORD_ABS_MASK\n","FLOAT64_HIGH_WORD_SIGN_MASK":"\nFLOAT64_HIGH_WORD_SIGN_MASK\n    High word mask for the sign bit of a double-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT64_HIGH_WORD_SIGN_MASK\n    2147483648\n    > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGN_MASK )\n    '10000000000000000000000000000000'\n\n    See Also\n    --------\n    FLOAT64_HIGH_WORD_EXPONENT_MASK, FLOAT64_HIGH_WORD_SIGNIFICAND_MASK, FLOAT64_HIGH_WORD_ABS_MASK\n","FLOAT64_HIGH_WORD_SIGNIFICAND_MASK":"\nFLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n    High word mask for the significand of a double-precision floating-point\n    number.\n\n    Examples\n    --------\n    > FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n    1048575\n    > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGNIFICAND_MASK )\n    '00000000000011111111111111111111'\n\n    See Also\n    --------\n    FLOAT64_HIGH_WORD_EXPONENT_MASK, FLOAT64_HIGH_WORD_SIGN_MASK, FLOAT64_HIGH_WORD_ABS_MASK\n","FLOAT64_MAX":"\nFLOAT64_MAX\n    Maximum double-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT64_MAX\n    1.7976931348623157e+308\n\n    See Also\n    --------\n    FLOAT16_MAX, FLOAT32_MAX\n","FLOAT64_MAX_BASE2_EXPONENT":"\nFLOAT64_MAX_BASE2_EXPONENT\n    The maximum biased base 2 exponent for a double-precision floating-point\n    number.\n\n    Examples\n    --------\n    > FLOAT64_MAX_BASE2_EXPONENT\n    1023\n\n    See Also\n    --------\n    FLOAT64_MAX_BASE10_EXPONENT, FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n    The maximum biased base 2 exponent for a subnormal double-precision\n    floating-point number.\n\n    Examples\n    --------\n    > FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n    -1023\n\n    See Also\n    --------\n    FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE2_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_BASE10_EXPONENT":"\nFLOAT64_MAX_BASE10_EXPONENT\n    The maximum base 10 exponent for a double-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT64_MAX_BASE10_EXPONENT\n    308\n\n    See Also\n    --------\n    FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE2_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT\n","FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n    The maximum base 10 exponent for a subnormal double-precision floating-point\n    number.\n\n    Examples\n    --------\n    > FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n    -308\n\n    See Also\n    --------\n    FLOAT64_MAX_BASE10_EXPONENT, FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_LN":"\nFLOAT64_MAX_LN\n    Natural logarithm of the maximum double-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT64_MAX_LN\n    709.782712893384\n\n    See Also\n    --------\n    FLOAT64_MIN_LN\n","FLOAT64_MAX_SAFE_FIBONACCI":"\nFLOAT64_MAX_SAFE_FIBONACCI\n    Maximum safe Fibonacci number when stored in double-precision floating-point\n    format.\n\n    Examples\n    --------\n    > FLOAT64_MAX_SAFE_FIBONACCI\n    8944394323791464\n\n    See Also\n    --------\n    FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT64_MAX_SAFE_INTEGER":"\nFLOAT64_MAX_SAFE_INTEGER\n    Maximum safe double-precision floating-point integer.\n\n    The maximum safe double-precision floating-point integer is given by\n    `2^53 - 1`.\n\n    Examples\n    --------\n    > FLOAT64_MAX_SAFE_INTEGER\n    9007199254740991\n\n    See Also\n    --------\n    FLOAT16_MAX_SAFE_INTEGER, FLOAT32_MAX_SAFE_INTEGER, FLOAT64_MIN_SAFE_INTEGER\n","FLOAT64_MAX_SAFE_LUCAS":"\nFLOAT64_MAX_SAFE_LUCAS\n    Maximum safe Lucas number when stored in double-precision floating-point\n    format.\n\n    Examples\n    --------\n    > FLOAT64_MAX_SAFE_LUCAS\n    7639424778862807\n\n    See Also\n    --------\n    FLOAT64_MAX_SAFE_FIBONACCI, FLOAT64_MAX_SAFE_NTH_LUCAS\n","FLOAT64_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT64_MAX_SAFE_NTH_FIBONACCI\n    Maximum safe nth Fibonacci number when stored in double-precision floating-\n    point format.\n\n    Examples\n    --------\n    > FLOAT64_MAX_SAFE_NTH_FIBONACCI\n    78\n\n    See Also\n    --------\n    FLOAT64_MAX_SAFE_FIBONACCI\n","FLOAT64_MAX_SAFE_NTH_LUCAS":"\nFLOAT64_MAX_SAFE_NTH_LUCAS\n    Maximum safe nth Lucas number when stored in double-precision floating-point\n    format.\n\n    Examples\n    --------\n    > FLOAT64_MAX_SAFE_NTH_LUCAS\n    76\n\n    See Also\n    --------\n    FLOAT64_MAX_SAFE_LUCAS, FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT64_MIN_BASE2_EXPONENT":"\nFLOAT64_MIN_BASE2_EXPONENT\n    The minimum biased base 2 exponent for a normalized double-precision\n    floating-point number.\n\n    Examples\n    --------\n    > FLOAT64_MIN_BASE2_EXPONENT\n    -1022\n\n    See Also\n    --------\n    FLOAT64_MAX_BASE2_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n    The minimum biased base 2 exponent for a subnormal double-precision\n    floating-point number.\n\n    Examples\n    --------\n    > FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n    -1074\n\n    See Also\n    --------\n    FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MIN_BASE10_EXPONENT":"\nFLOAT64_MIN_BASE10_EXPONENT\n    The minimum base 10 exponent for a normalized double-precision floating-\n    point number.\n\n    Examples\n    --------\n    > FLOAT64_MIN_BASE10_EXPONENT\n    -308\n\n    See Also\n    --------\n    FLOAT64_MAX_BASE10_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n    The minimum base 10 exponent for a subnormal double-precision floating-\n    point number.\n\n    Examples\n    --------\n    > FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n    -324\n\n    See Also\n    --------\n    FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_LN":"\nFLOAT64_MIN_LN\n    Natural logarithm of the smallest normalized double-precision floating-point\n    number.\n\n    Examples\n    --------\n    > FLOAT64_MIN_LN\n    -708.3964185322641\n\n    See Also\n    --------\n    FLOAT64_MAX_LN\n","FLOAT64_MIN_SAFE_INTEGER":"\nFLOAT64_MIN_SAFE_INTEGER\n    Minimum safe double-precision floating-point integer.\n\n    The minimum safe double-precision floating-point integer is given by\n    `-(2^53 - 1)`.\n\n    Examples\n    --------\n    > FLOAT64_MIN_SAFE_INTEGER\n    -9007199254740991\n\n    See Also\n    --------\n    FLOAT16_MIN_SAFE_INTEGER, FLOAT32_MIN_SAFE_INTEGER, FLOAT64_MAX_SAFE_INTEGER\n","FLOAT64_NUM_BYTES":"\nFLOAT64_NUM_BYTES\n    Size (in bytes) of a double-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT64_NUM_BYTES\n    8\n\n    See Also\n    --------\n    FLOAT16_NUM_BYTES, FLOAT32_NUM_BYTES\n","FLOAT64_PRECISION":"\nFLOAT64_PRECISION\n    Effective number of bits in the significand of a double-precision floating-\n    point number.\n\n    The effective number of bits is `52` significand bits plus `1` hidden bit.\n\n    Examples\n    --------\n    > FLOAT64_PRECISION\n    53\n\n    See Also\n    --------\n    FLOAT16_PRECISION, FLOAT32_PRECISION\n","FLOAT64_SMALLEST_NORMAL":"\nFLOAT64_SMALLEST_NORMAL\n    Smallest positive normalized double-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT64_SMALLEST_NORMAL\n    2.2250738585072014e-308\n\n    See Also\n    --------\n    FLOAT32_SMALLEST_NORMAL, FLOAT64_SMALLEST_SUBNORMAL\n","FLOAT64_SMALLEST_SUBNORMAL":"\nFLOAT64_SMALLEST_SUBNORMAL\n    Smallest positive denormalized double-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT64_SMALLEST_SUBNORMAL\n    4.940656458412465e-324\n\n    See Also\n    --------\n    FLOAT32_SMALLEST_SUBNORMAL, FLOAT64_SMALLEST_NORMAL\n","Float64Array":"\nFloat64Array()\n    A typed array constructor which returns a typed array representing an array\n    of double-precision floating-point numbers in the platform byte order.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Float64Array()\n    <Float64Array>\n\n\nFloat64Array( length )\n    Returns a typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 5 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat64Array( typedarray )\n    Creates a typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float32Array( [ 0.5, 0.5, 0.5 ] );\n    > var arr2 = new Float64Array( arr1 )\n    <Float64Array>[ 0.5, 0.5, 0.5 ]\n\n\nFloat64Array( obj )\n    Creates a typed array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a typed array.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 0.5, 0.5, 0.5 ];\n    > var arr2 = new Float64Array( arr1 )\n    <Float64Array>[ 0.5, 0.5, 0.5 ]\n\n\nFloat64Array( buffer[, byteOffset[, length]] )\n    Returns a typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 32 );\n    > var arr = new Float64Array( buf, 0, 4 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat64Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2.0; };\n    > var arr = Float64Array.from( [ 1.0, -1.0 ], mapFcn )\n    <Float64Array>[ 2.0, -2.0 ]\n\n\nFloat64Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Float64Array.of( 2.0, -2.0 )\n    <Float64Array>[ 2.0, -2.0 ]\n\n\nFloat64Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Float64Array.BYTES_PER_ELEMENT\n    8\n\n\nFloat64Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Float64Array.name\n    'Float64Array'\n\n\nFloat64Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>\n\n\nFloat64Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 5 );\n    > arr.byteLength\n    40\n\n\nFloat64Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 5 );\n    > arr.byteOffset\n    0\n\n\nFloat64Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    8\n\n\nFloat64Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 5 );\n    > arr.length\n    5\n\n\nFloat64Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Float64Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    2.0\n    > arr[ 4 ]\n    -2.0\n\n\nFloat64Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1.0 ]\n    > it.next().value\n    [ 1, -1.0 ]\n    > it.next().done\n    true\n\n\nFloat64Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > function predicate( v ) { return ( v >= 0.0 ); };\n    > arr.every( predicate )\n    false\n\n\nFloat64Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Float64Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > arr.fill( 2.0 );\n    > arr[ 0 ]\n    2.0\n    > arr[ 1 ]\n    2.0\n\n\nFloat64Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v >= 0.0 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2\n\n\nFloat64Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > var v = arr.find( predicate )\n    -1.0\n\n\nFloat64Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > var idx = arr.findIndex( predicate )\n    2\n\n\nFloat64Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:1 1:0 2:-1 '\n\n\nFloat64Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > var bool = arr.includes( 2.0 )\n    false\n    > bool = arr.includes( -1.0 )\n    true\n\n\nFloat64Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > var idx = arr.indexOf( 2.0 )\n    -1\n    > idx = arr.indexOf( -1.0 )\n    2\n\n\nFloat64Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > arr.join( '|' )\n    '1|0|-1'\n\n\nFloat64Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true\n\n\nFloat64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n    > var idx = arr.lastIndexOf( 2.0 )\n    -1\n    > idx = arr.lastIndexOf( 0.0 )\n    3\n\n\nFloat64Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( v ) { return v * 2.0; };\n    > var arr2 = arr1.map( fcn )\n    <Float64Array>[ 2.0, 0.0, -2.0 ]\n\n\nFloat64Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0.0 )\n    2.0\n\n\nFloat64Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0.0 )\n    2.0\n\n\nFloat64Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Float64Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] )\n    <Float64Array>\n    > arr.reverse()\n    <Float64Array>[ -1.0, 0.0, 1.0 ]\n\n\nFloat64Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > arr.set( [ -2.0, 2.0 ], 1 );\n    > arr[ 1 ]\n    -2.0\n    > arr[ 2 ]\n    2.0\n\n\nFloat64Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    0.0\n    > arr2[ 1 ]\n    -1.0\n\n\nFloat64Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > arr.some( predicate )\n    true\n\n\nFloat64Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Float64Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n    > arr.sort()\n    <Float64Array>[ -2.0, -1.0, 0.0, 1.0, 2.0 ]\n\n\nFloat64Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Float64Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Float64Array>[ 0.0, 2.0, -2.0 ]\n\n\nFloat64Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n    > arr.toLocaleString()\n    '1,-1,0'\n\n\nFloat64Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n    > arr.toString()\n    '1,-1,0'\n\n\nFloat64Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > it = arr.values();\n    > it.next().value\n    1.0\n    > it.next().value\n    -1.0\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Float64Array.from":"\nFloat64Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2.0; };\n    > var arr = Float64Array.from( [ 1.0, -1.0 ], mapFcn )\n    <Float64Array>[ 2.0, -2.0 ]","Float64Array.of":"\nFloat64Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Float64Array.of( 2.0, -2.0 )\n    <Float64Array>[ 2.0, -2.0 ]","Float64Array.BYTES_PER_ELEMENT":"\nFloat64Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Float64Array.BYTES_PER_ELEMENT\n    8","Float64Array.name":"\nFloat64Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Float64Array.name\n    'Float64Array'","Float64Array.prototype.buffer":"\nFloat64Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>","Float64Array.prototype.byteLength":"\nFloat64Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 5 );\n    > arr.byteLength\n    40","Float64Array.prototype.byteOffset":"\nFloat64Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 5 );\n    > arr.byteOffset\n    0","Float64Array.prototype.BYTES_PER_ELEMENT":"\nFloat64Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    8","Float64Array.prototype.length":"\nFloat64Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 5 );\n    > arr.length\n    5","Float64Array.prototype.copyWithin":"\nFloat64Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Float64Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    2.0\n    > arr[ 4 ]\n    -2.0","Float64Array.prototype.entries":"\nFloat64Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1.0 ]\n    > it.next().value\n    [ 1, -1.0 ]\n    > it.next().done\n    true","Float64Array.prototype.every":"\nFloat64Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > function predicate( v ) { return ( v >= 0.0 ); };\n    > arr.every( predicate )\n    false","Float64Array.prototype.fill":"\nFloat64Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Float64Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > arr.fill( 2.0 );\n    > arr[ 0 ]\n    2.0\n    > arr[ 1 ]\n    2.0","Float64Array.prototype.filter":"\nFloat64Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v >= 0.0 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2","Float64Array.prototype.find":"\nFloat64Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > var v = arr.find( predicate )\n    -1.0","Float64Array.prototype.findIndex":"\nFloat64Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > var idx = arr.findIndex( predicate )\n    2","Float64Array.prototype.forEach":"\nFloat64Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:1 1:0 2:-1 '","Float64Array.prototype.includes":"\nFloat64Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > var bool = arr.includes( 2.0 )\n    false\n    > bool = arr.includes( -1.0 )\n    true","Float64Array.prototype.indexOf":"\nFloat64Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > var idx = arr.indexOf( 2.0 )\n    -1\n    > idx = arr.indexOf( -1.0 )\n    2","Float64Array.prototype.join":"\nFloat64Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > arr.join( '|' )\n    '1|0|-1'","Float64Array.prototype.keys":"\nFloat64Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true","Float64Array.prototype.lastIndexOf":"\nFloat64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n    > var idx = arr.lastIndexOf( 2.0 )\n    -1\n    > idx = arr.lastIndexOf( 0.0 )\n    3","Float64Array.prototype.map":"\nFloat64Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( v ) { return v * 2.0; };\n    > var arr2 = arr1.map( fcn )\n    <Float64Array>[ 2.0, 0.0, -2.0 ]","Float64Array.prototype.reduce":"\nFloat64Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0.0 )\n    2.0","Float64Array.prototype.reduceRight":"\nFloat64Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0.0 )\n    2.0","Float64Array.prototype.reverse":"\nFloat64Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Float64Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] )\n    <Float64Array>\n    > arr.reverse()\n    <Float64Array>[ -1.0, 0.0, 1.0 ]","Float64Array.prototype.set":"\nFloat64Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > arr.set( [ -2.0, 2.0 ], 1 );\n    > arr[ 1 ]\n    -2.0\n    > arr[ 2 ]\n    2.0","Float64Array.prototype.slice":"\nFloat64Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    0.0\n    > arr2[ 1 ]\n    -1.0","Float64Array.prototype.some":"\nFloat64Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > arr.some( predicate )\n    true","Float64Array.prototype.sort":"\nFloat64Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Float64Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n    > arr.sort()\n    <Float64Array>[ -2.0, -1.0, 0.0, 1.0, 2.0 ]","Float64Array.prototype.subarray":"\nFloat64Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Float64Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Float64Array>[ 0.0, 2.0, -2.0 ]","Float64Array.prototype.toLocaleString":"\nFloat64Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n    > arr.toLocaleString()\n    '1,-1,0'","Float64Array.prototype.toString":"\nFloat64Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n    > arr.toString()\n    '1,-1,0'","Float64Array.prototype.values":"\nFloat64Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > it = arr.values();\n    > it.next().value\n    1.0\n    > it.next().value\n    -1.0\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","forEach":"\nforEach( collection, fcn[, thisArg] )\n    Invokes a function for each element in a collection.\n\n    When invoked, the input function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n    > var arr = [ 1, 2, 3, 4 ];\n    > forEach( arr, logger )\n    0: 1\n    1: 2\n    2: 3\n    3: 4\n\n    See Also\n    --------\n    forEachAsync, forEachRight\n","forEachAsync":"\nforEachAsync( collection, [options,] fcn, done )\n    Invokes a function once for each element in a collection.\n\n    When invoked, `fcn` is provided a maximum of four arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If `fcn`\n    accepts two arguments, `fcn` is provided:\n\n    - value\n    - next\n\n    If `fcn` accepts three arguments, `fcn` is provided:\n\n    - value\n    - index\n    - next\n\n    For every other `fcn` signature, `fcn` is provided all four arguments.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function onDuration( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next();\n    ...     }\n    ... };\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( 'Done.' );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > forEachAsync( arr, onDuration, done )\n    1000\n    2500\n    3000\n    Done.\n\n    // Limit number of concurrent invocations:\n    > function onDuration( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next();\n    ...     }\n    ... };\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( 'Done.' );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 3000, 2500, 1000 ];\n    > forEachAsync( arr, opts, onDuration, done )\n    2500\n    3000\n    1000\n    Done.\n\n    // Process sequentially:\n    > function onDuration( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next();\n    ...     }\n    ... };\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( 'Done.' );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 3000, 2500, 1000 ];\n    > forEachAsync( arr, opts, onDuration, done )\n    3000\n    2500\n    1000\n    Done.\n\n\nforEachAsync.factory( [options,] fcn )\n    Returns a function which invokes a function once for each element in a\n    collection.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function onDuration( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next();\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = forEachAsync.factory( opts, onDuration );\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( 'Done.' );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    Done.\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    Done.\n\n    See Also\n    --------\n    forEach, forEachRightAsync\n","forEachAsync.factory":"\nforEachAsync.factory( [options,] fcn )\n    Returns a function which invokes a function once for each element in a\n    collection.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function onDuration( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next();\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = forEachAsync.factory( opts, onDuration );\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( 'Done.' );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    Done.\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    Done.\n\n    See Also\n    --------\n    forEach, forEachRightAsync","forEachChar":"\nforEachChar( str, [options,] clbk[, thisArg] )\n    Invokes a function for each character in a string.\n\n    When invoked, the provided function is provided three arguments:\n\n    - value: character.\n    - index: starting character index.\n    - str: input string.\n\n    Parameters\n    ----------\n    str: string\n        Input string over which to iterate.\n\n    options: Object (optional)\n        Options.\n\n    options.mode: string (optional)\n        Type of characters over which to iterate. The following modes are\n        supported:\n\n        - grapheme: grapheme clusters. Appropriate for strings containing visual\n          characters which can span multiple Unicode code points (e.g., emoji).\n        - code_point: Unicode code points. Appropriate for strings containing\n          visual characters which are comprised of more than one Unicode code\n          unit (e.g., ideographic symbols and punctuation and mathematical\n          alphanumerics).\n        - code_unit': UTF-16 code units. Appropriate for strings containing\n          visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n          common characters, such as those from the Latin, Greek, and Cyrillic\n          alphabets).\n\n        Default: 'grapheme'.\n\n    clbk: Function\n        The function to invoke for each character in the input string.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: string\n        Input string.\n\n    Examples\n    --------\n    > var n = 0;\n    > function fcn() { n += 1; };\n    > forEachChar( 'hello world!', fcn );\n    > n\n    12\n\n    See Also\n    --------\n    forEach\n","forEachRight":"\nforEachRight( collection, fcn[, thisArg] )\n    Invokes a function for each element in a collection, iterating from right to\n    left.\n\n    When invoked, the input function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n    > var arr = [ 1, 2, 3, 4 ];\n    > forEachRight( arr, logger )\n    3: 4\n    2: 3\n    1: 2\n    0: 1\n\n    See Also\n    --------\n    forEach, forEachRightAsync\n","forEachRightAsync":"\nforEachRightAsync( collection, [options,] fcn, done )\n    Invokes a function once for each element in a collection, iterating from\n    right to left.\n\n    When invoked, `fcn` is provided a maximum of four arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If `fcn`\n    accepts two arguments, `fcn` is provided:\n\n    - value\n    - next\n\n    If `fcn` accepts three arguments, `fcn` is provided:\n\n    - value\n    - index\n    - next\n\n    For every other `fcn` signature, `fcn` is provided all four arguments.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function onDuration( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next();\n    ...     }\n    ... };\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( 'Done.' );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > forEachRightAsync( arr, onDuration, done )\n    1000\n    2500\n    3000\n    Done.\n\n    // Limit number of concurrent invocations:\n    > function onDuration( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next();\n    ...     }\n    ... };\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( 'Done.' );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 1000, 2500, 3000 ];\n    > forEachRightAsync( arr, opts, onDuration, done )\n    2500\n    3000\n    1000\n    Done.\n\n    // Process sequentially:\n    > function onDuration( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next();\n    ...     }\n    ... };\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( 'Done.' );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 1000, 2500, 3000 ];\n    > forEachRightAsync( arr, opts, onDuration, done )\n    3000\n    2500\n    1000\n    Done.\n\n\nforEachRightAsync.factory( [options,] fcn )\n    Returns a function which invokes a function once for each element in a\n    collection, iterating from right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function onDuration( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next();\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = forEachRightAsync.factory( opts, onDuration );\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( 'Done.' );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    Done.\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    Done.\n\n    See Also\n    --------\n    forEachAsync, forEachRight\n","forEachRightAsync.factory":"\nforEachRightAsync.factory( [options,] fcn )\n    Returns a function which invokes a function once for each element in a\n    collection, iterating from right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function onDuration( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next();\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = forEachRightAsync.factory( opts, onDuration );\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( 'Done.' );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    Done.\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    Done.\n\n    See Also\n    --------\n    forEachAsync, forEachRight","forIn":"\nforIn( obj, fcn[, thisArg] )\n    Invokes a function for each own and inherited enumerable property of an\n    object.\n\n    When invoked, the function is provided three arguments:\n\n    - value: object property value.\n    - key: object property.\n    - obj: the input object.\n\n    To terminate iteration before visiting all properties, the provided function\n    must explicitly return `false`.\n\n    Property iteration order is *not* guaranteed.\n\n    Parameters\n    ----------\n    obj: Object\n        Input object, including arrays, typed arrays, and other collections.\n\n    fcn: Function\n        The function to invoke for each own enumerable property.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Object\n        Input object.\n\n    Examples\n    --------\n    > function logger( v, k ) { console.log( '%s: %d', k, v ); };\n    > function Foo() { return this; };\n    > Foo.prototype.beep = 'boop';\n    > var obj = new Foo();\n    > forIn( obj, logger )\n    beep: boop\n\n    See Also\n    --------\n    forEach, forOwn\n","format":"\nformat( str, ...args )\n    Insert supplied variable values into a format string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    args: ...any\n        Variable values.\n\n    Returns\n    -------\n    out: string\n        Formatted string.\n\n    Examples\n    --------\n    > var out = format( 'Hello, %s!', 'World' )\n    'Hello, World!'\n\n    > out = format( '%s %s', 'Hello', 'World' )\n    'Hello World'\n\n    > out = format( 'Pi: %.2f', PI )\n    'Pi: 3.14'\n\n","forOwn":"\nforOwn( obj, fcn[, thisArg] )\n    Invokes a function for each own enumerable property of an object.\n\n    When invoked, the function is provided three arguments:\n\n    - value: object property value.\n    - key: object property.\n    - obj: the input object.\n\n    To terminate iteration before visiting all properties, the provided function\n    must explicitly return `false`.\n\n    The function determines the list of own enumerable properties *before*\n    invoking the provided function. Hence, any modifications made to the input\n    object *after* calling this function (such as adding and removing\n    properties) will *not* affect the list of visited properties.\n\n    Property iteration order is *not* guaranteed.\n\n    Parameters\n    ----------\n    obj: Object\n        Input object, including arrays, typed arrays, and other collections.\n\n    fcn: Function\n        The function to invoke for each own enumerable property.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Object\n        Input object.\n\n    Examples\n    --------\n    > function logger( v, k ) { console.log( '%s: %d', k, v ); };\n    > var obj = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\n    > forOwn( obj, logger )\n    a: 1\n    b: 2\n    c: 3\n    d: 4\n\n    See Also\n    --------\n    forEach, forIn\n","FOURTH_PI":"\nFOURTH_PI\n    One fourth times the mathematical constant `π`.\n\n    Examples\n    --------\n    > FOURTH_PI\n    7.85398163397448309616e-1\n\n    See Also\n    --------\n    PI\n","FOURTH_ROOT_EPS":"\nFOURTH_ROOT_EPS\n    Fourth root of double-precision floating-point epsilon.\n\n    Examples\n    --------\n    > FOURTH_ROOT_EPS\n    0.0001220703125\n\n    See Also\n    --------\n    EPS\n","FRB_SF_WAGE_RIGIDITY":"\nFRB_SF_WAGE_RIGIDITY()\n    Returns wage rates for U.S. workers that have not changed jobs within the\n    year.\n\n    Each array element has the following fields:\n\n    - date: collection date (month/day/year; e.g., 01/01/1980).\n    - all_workers: wage rates for hourly and non-hourly workers.\n    - hourly_workers: wage rates for hourly workers.\n    - non_hourly_workers: wage rates for non-hourly workers.\n    - less_than_high_school: wage rates for workers with less than a high school\n      education.\n    - high_school: wage rates for workers with a high school education.\n    - some_college: wage rates for workers with some college education.\n    - college: wage rates for workers with a college education.\n    - construction: wage rates for workers in the construction industry.\n    - finance: wage rates for workers in the finance industry.\n    - manufacturing: wage rates for workers in the manufacturing industry.\n\n    Returns\n    -------\n    out: Array<Object>\n        Wage rates.\n\n    Examples\n    --------\n    > var data = FRB_SF_WAGE_RIGIDITY()\n    [ {...}, {...}, ... ]\n\n    References\n    ----------\n    - Federal Reserve Bank of San Francisco. 2017. \"Wage Rigidity.\" <http://www.\n    frbsf.org/economic-research/indicators-data/nominal-wage-rigidity/>.\n\n","fromCodePoint":"\nfromCodePoint( ...pt )\n    Creates a string from a sequence of Unicode code points.\n\n    In addition to multiple arguments, the function also supports providing an\n    array-like object as a single argument containing a sequence of Unicode code\n    points.\n\n    Parameters\n    ----------\n    pt: ...integer\n        Sequence of Unicode code points.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = fromCodePoint( 9731 )\n    '☃'\n    > out = fromCodePoint( [ 9731 ] )\n    '☃'\n    > out = fromCodePoint( 97, 98, 99 )\n    'abc'\n    > out = fromCodePoint( [ 97, 98, 99 ] )\n    'abc'\n\n    See Also\n    --------\n    codePointAt\n","Function":"\nFunction( [...argNames,] body )\n    Returns a Function object.\n\n    Argument names must be strings corresponding to valid JavaScript parameters\n    (i.e., a plain identifier, or, in environments supporting such parameters, a\n    rest parameter or destructured parameter, optionally with a default).\n\n    Parameters\n    ----------\n    argNames: ...any (optional)\n        Parameter names.\n\n    body: string\n        Function body.\n\n    Returns\n    -------\n    fcn: Function\n        Function object.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f( 1, 2 )\n    3\n\n\nFunction.prototype.apply( thisArg, args )\n    Calls a function with a given `this` value and arguments provided as an\n    array (or array-like object).\n\n    Parameters\n    ----------\n    thisArg: any\n        Value to use as `this` when executing the function.\n\n    args: Array\n        Array of arguments to pass to the function.\n\n    Returns\n    -------\n    out: any\n        Function return value.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.apply( null, [ 1, 2 ] )\n    3\n\nFunction.prototype.call( thisArg, ...args )\n    Calls a function with a given `this` value and arguments provided\n    individually.\n\n    Parameters\n    ----------\n    thisArg: any\n        Value to use as `this` when executing the function.\n\n    args: ...any\n        Arguments to pass to the function.\n\n    Returns\n    -------\n    out: any\n        Function return value.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.call( null, 1, 2 )\n    3\n\nFunction.prototype.bind( thisArg, ...args )\n    Creates a new function which, when called, has its `this` keyword set to the\n    provided value, with a given sequence of arguments preceding any provided\n    when the new function is called.\n\n    Parameters\n    ----------\n    thisArg: any\n        Value to use as `this` when executing the function.\n\n    args: ...any\n        Arguments to pass to the function.\n\n    Returns\n    -------\n    fcn: Function\n        Bound function.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > var g = f.bind( null, 1 );\n    > g( 2 )\n    3\n\nFunction.prototype.toString()\n    Returns a string representation of the function.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.toString()\n    'function anonymous( x, y ) { return x + y; }'\n\nFunction.prototype.length\n    The number of arguments expected by the function.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.length\n    2\n\nFunction.prototype.name\n    The name of the function.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.name\n    'anonymous'\n\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.name = 'add';\n    > f.name\n    'add'\n\nFunction.prototype.prototype\n    The prototype of the function.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.prototype\n    {}\n\n","Function.prototype.apply":"\nFunction.prototype.apply( thisArg, args )\n    Calls a function with a given `this` value and arguments provided as an\n    array (or array-like object).\n\n    Parameters\n    ----------\n    thisArg: any\n        Value to use as `this` when executing the function.\n\n    args: Array\n        Array of arguments to pass to the function.\n\n    Returns\n    -------\n    out: any\n        Function return value.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.apply( null, [ 1, 2 ] )\n    3","Function.prototype.call":"\nFunction.prototype.call( thisArg, ...args )\n    Calls a function with a given `this` value and arguments provided\n    individually.\n\n    Parameters\n    ----------\n    thisArg: any\n        Value to use as `this` when executing the function.\n\n    args: ...any\n        Arguments to pass to the function.\n\n    Returns\n    -------\n    out: any\n        Function return value.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.call( null, 1, 2 )\n    3","Function.prototype.bind":"\nFunction.prototype.bind( thisArg, ...args )\n    Creates a new function which, when called, has its `this` keyword set to the\n    provided value, with a given sequence of arguments preceding any provided\n    when the new function is called.\n\n    Parameters\n    ----------\n    thisArg: any\n        Value to use as `this` when executing the function.\n\n    args: ...any\n        Arguments to pass to the function.\n\n    Returns\n    -------\n    fcn: Function\n        Bound function.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > var g = f.bind( null, 1 );\n    > g( 2 )\n    3","Function.prototype.toString":"\nFunction.prototype.toString()\n    Returns a string representation of the function.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.toString()\n    'function anonymous( x, y ) { return x + y; }'","Function.prototype.length":"\nFunction.prototype.length\n    The number of arguments expected by the function.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.length\n    2","Function.prototype.name":"\nFunction.prototype.name\n    The name of the function.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.name\n    'anonymous'\n\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.name = 'add';\n    > f.name\n    'add'","Function.prototype.prototype":"\nFunction.prototype.prototype\n    The prototype of the function.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.prototype\n    {}","function2string":"\nfunction2string( fcn )\n    Returns a string representing the source code of a provided function.\n\n    If called on built-in functions, functions created by `Function#bind()`, or\n    other non-JavaScript functions, the function returns a \"native\" function\n    string similar to the following:\n\n      \"function foo() { [native code] }\"\n\n    For intrinsic object methods and functions, `foo` is the initial name of the\n    function.\n\n    If called on a function created by the `Function` constructor, the function\n    returns the source code of a synthesized function declaration having the\n    name \"anonymous\" and using the provided parameters and function body.\n\n    Starting in ES2018, the ECMAScript specification requires that the returned\n    string contain the exact same source code as it was declared, including any\n    whitespace and/or comments. If the host is unable to access the source code,\n    the specification requires that the returned string be the native function\n    string.\n\n    Parameters\n    ----------\n    fcn: Function\n        Input function.\n\n    Returns\n    -------\n    out: string\n        String representing the function's source code.\n\n    Examples\n    --------\n    > function2string( base.erf )\n    <string>\n\n    See Also\n    --------\n    Function\n","functionName":"\nfunctionName( fcn )\n    Returns the name of a function.\n\n    If provided an anonymous function, the function returns an empty `string` or\n    the string `\"anonymous\"`.\n\n\n    Parameters\n    ----------\n    fcn: Function\n        Input function.\n\n    Returns\n    -------\n    out: string\n        Function name.\n\n    Examples\n    --------\n    > var v = functionName( String )\n    'String'\n    > v = functionName( function foo(){} )\n    'foo'\n    > v = functionName( function(){} )\n    '' || 'anonymous'\n\n    See Also\n    --------\n    constructorName\n","functionSequence":"\nfunctionSequence( ...fcn )\n    Returns a pipeline function.\n\n    Starting from the left, the pipeline function evaluates each function and\n    passes the result as an argument to the next function. The result of the\n    rightmost function is the result of the whole.\n\n    Only the leftmost function is explicitly permitted to accept multiple\n    arguments. All other functions are evaluated as unary functions.\n\n    Parameters\n    ----------\n    fcn: ...Function\n        Functions to evaluate in sequential order.\n\n    Returns\n    -------\n    out: Function\n        Pipeline function.\n\n    Examples\n    --------\n    > function a( x ) { return 2 * x; };\n    > function b( x ) { return x + 3; };\n    > function c( x ) { return x / 5; };\n    > var f = functionSequence( a, b, c );\n    > var z = f( 6 )\n    3\n\n    See Also\n    --------\n    compose, functionSequenceAsync\n","functionSequenceAsync":"\nfunctionSequenceAsync( ...fcn )\n    Returns a pipeline function.\n\n    Starting from the left, the pipeline function evaluates each function and\n    passes the result as the first argument of the next function. The result of\n    the rightmost function is the result of the whole.\n\n    The last argument for each provided function is a `next` callback which\n    should be invoked upon function completion. The callback accepts two\n    arguments:\n\n    - error: error argument.\n    - result: function result.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the pipeline function suspends execution and immediately calls the\n    `done` callback for subsequent `error` handling.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Only the leftmost function is explicitly permitted to accept multiple\n    arguments. All other functions are evaluated as binary functions.\n\n    The function will throw if provided fewer than two input arguments.\n\n    Parameters\n    ----------\n    fcn: ...Function\n        Functions to evaluate in sequential order.\n\n    Returns\n    -------\n    out: Function\n        Pipeline function.\n\n    Examples\n    --------\n    > function a( x, next ) {\n    ...    setTimeout( onTimeout, 0 );\n    ...    function onTimeout() {\n    ...        next( null, 2*x );\n    ...    }\n    ... };\n    > function b( x, next ) {\n    ...    setTimeout( onTimeout, 0 );\n    ...    function onTimeout() {\n    ...        next( null, x+3 );\n    ...    }\n    ... };\n    > function c( x, next ) {\n    ...    setTimeout( onTimeout, 0 );\n    ...    function onTimeout() {\n    ...        next( null, x/5 );\n    ...    }\n    ... };\n    > var f = functionSequenceAsync( a, b, c );\n    > function done( error, result ) {\n    ...    if ( error ) {\n    ...        throw error;\n    ...    }\n    ...    console.log( result );\n    ... };\n    > f( 6, done )\n    3\n\n    See Also\n    --------\n    composeAsync, functionSequence\n","GAMMA_LANCZOS_G":"\nGAMMA_LANCZOS_G\n    Arbitrary constant `g` to be used in Lanczos approximation functions.\n\n    Examples\n    --------\n    > GAMMA_LANCZOS_G\n    10.900511\n\n","gdot":"\ngdot( x, y )\n    Computes the dot product of two vectors.\n\n    In general, for best performance, especially for large vectors, provide\n    1-dimensional ndarrays whose underlying data type is either 'float64' or\n    'float32'.\n\n    If provided empty vectors, the function returns `0.0`.\n\n    Parameters\n    ----------\n    x: ndarray|ArrayLikeObject\n        First input array.\n\n    y: ndarray|ArrayLikeObject\n        Second input array.\n\n    Returns\n    -------\n    dot: number\n        The dot product.\n\n    Examples\n    --------\n    // Using ndarrays...\n    > var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n    > var y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n    > gdot( x, y )\n    -5.0\n\n    // Using array-like objects...\n    > x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n    > y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n    > gdot( x, y )\n    -5.0\n\n    See Also\n    --------\n    base.strided.gdot, ddot, sdot\n","getegid":"\ngetegid()\n    Returns the effective numeric group identity of the calling process.\n\n    The function only returns an effective group identity on POSIX platforms.\n    For all other platforms (e.g., Windows and Android), the function returns\n    `null`.\n\n    Returns\n    -------\n    id: integer|null\n        Effective numeric group identity.\n\n    Examples\n    --------\n    > var gid = getegid()\n\n    See Also\n    --------\n    geteuid, getgid, getuid\n","geteuid":"\ngeteuid()\n    Returns the effective numeric user identity of the calling process.\n\n    The function only returns an effective user identity on POSIX platforms. For\n    all other platforms (e.g., Windows and Android), the function returns\n    `null`.\n\n    Returns\n    -------\n    id: integer|null\n        Effective numeric user identity.\n\n    Examples\n    --------\n    > var uid = geteuid()\n\n    See Also\n    --------\n    getegid, getgid, getuid\n","getgid":"\ngetgid()\n    Returns the numeric group identity of the calling process.\n\n    The function only returns a group identity on POSIX platforms. For all other\n    platforms (e.g., Windows and Android), the function returns `null`.\n\n    Returns\n    -------\n    id: integer|null\n        Numeric group identity.\n\n    Examples\n    --------\n    > var gid = getgid()\n\n    See Also\n    --------\n    getegid, geteuid, getuid\n","getGlobal":"\ngetGlobal( [codegen] )\n    Returns the global object.\n\n    Parameters\n    ----------\n    codegen: boolean (optional)\n        Boolean indicating whether to use code generation to resolve the global\n        object. Code generation is the *most* reliable means for resolving the\n        global object; however, using code generation may violate content\n        security policies (CSPs). Default: false.\n\n    Returns\n    -------\n    global: Object\n        Global object.\n\n    Examples\n    --------\n    > var g = getGlobal()\n    {...}\n\n","getPrototypeOf":"\ngetPrototypeOf( value )\n    Returns the prototype of a provided object.\n\n    In contrast to the native `Object.getPrototypeOf`, this function does not\n    throw when provided `null` or `undefined`. Instead, similar to when provided\n    any value with *no* inherited properties, the function returns `null`.\n\n    Value arguments other than `null` or `undefined` are coerced to objects.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    out: Object|null\n        Prototype.\n\n    Examples\n    --------\n    > var proto = getPrototypeOf( {} )\n    {}\n\n    See Also\n    --------\n    isPrototypeOf\n","getuid":"\ngetuid()\n    Returns the numeric user identity of the calling process.\n\n    The function only returns a user identity on POSIX platforms. For all other\n    platforms (e.g., Windows and Android), the function returns `null`.\n\n    Returns\n    -------\n    id: integer|null\n        Numeric user identity.\n\n    Examples\n    --------\n    > var uid = getuid()\n\n    See Also\n    --------\n    getegid, geteuid, getgid\n","GLAISHER":"\nGLAISHER\n    Glaisher-Kinkelin constant.\n\n    Examples\n    --------\n    > GLAISHER\n    1.2824271291006226\n\n","graphemeClusters2iterator":"\ngraphemeClusters2iterator( src[, mapFcn[, thisArg]] )\n    Returns an iterator which iterates over each grapheme cluster in a string.\n\n    When invoked, an input function is provided three arguments:\n\n    - value: grapheme cluster.\n    - index: iterated value index.\n    - src: source string.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke a string's `@@iterator` method, regardless of whether this method is\n    defined. To convert a string to an implementation defined iterator, invoke\n    this method directly.\n\n    Parameters\n    ----------\n    src: string\n        String from which to create the iterator.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = graphemeClusters2iterator( '🌷🍕' );\n    > var v = it.next().value\n    '🌷'\n    > v = it.next().value\n    '🍕'\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    array2iterator, graphemeClusters2iteratorRight\n","graphemeClusters2iteratorRight":"\ngraphemeClusters2iteratorRight( src[, mapFcn[, thisArg]] )\n    Returns an iterator which iterates from right to left over each grapheme\n    cluster in a string.\n\n    When invoked, an input function is provided three arguments:\n\n    - value: grapheme cluster.\n    - index: iterated value index.\n    - src: source string.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke a string's `@@iterator` method, regardless of whether this method is\n    defined. To convert a string to an implementation defined iterator, invoke\n    this method directly.\n\n    Parameters\n    ----------\n    src: string\n        String from which to create the iterator.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = graphemeClusters2iteratorRight( '🌷🍕' );\n    > var v = it.next().value\n    '🍕'\n    > v = it.next().value\n    '🌷'\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    array2iteratorRight, graphemeClusters2iterator\n","group":"\ngroup( collection, [options,] groups )\n    Groups values as arrays associated with distinct keys.\n\n    If provided an empty collection, the function returns an empty object.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection to group. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Options.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `indices`, indices are returned; if\n        `*`, both indices and values are returned. Default: 'values'.\n\n    groups: Array|TypedArray|Object\n        A collection defining which group an element in the input collection\n        belongs to. Each value in `groups` should resolve to a value which can\n        be serialized as an object key. If provided an object, the object must\n        be array-like (excluding strings and functions).\n\n    Returns\n    -------\n    out: Object\n        Group results.\n\n    Examples\n    --------\n    > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n    > var groups = [ 'b', 'b', 'f', 'b' ];\n    > var out = group( collection, groups )\n    { 'b': [ 'beep', 'boop', 'bar' ], 'f': [ 'foo' ] }\n    > groups = [ 1, 1, 2, 1 ];\n    > out = group( collection, groups )\n    { '1': [ 'beep', 'boop', 'bar' ], '2': [ 'foo' ] }\n\n    // Output group results as indices:\n    > groups = [ 'b', 'b', 'f', 'b' ];\n    > var opts = { 'returns': 'indices' };\n    > out = group( collection, opts, groups )\n    { 'b': [ 0, 1, 3 ], 'f': [ 2 ] }\n\n    // Output group results as index-element pairs:\n    > opts = { 'returns': '*' };\n    > out = group( collection, opts, groups )\n    { 'b': [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], 'f': [ [2, 'foo'] ] }\n\n    See Also\n    --------\n    bifurcate, countBy, groupBy\n","groupBy":"\ngroupBy( collection, [options,] indicator )\n    Groups values according to an indicator function.\n\n    When invoked, the indicator function is provided two arguments:\n\n    - value: collection value.\n    - index: collection index.\n\n    The value returned by an indicator function should be a value which can be\n    serialized as an object key.\n\n    If provided an empty collection, the function returns an empty object.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection to group. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Options.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `indices`, indices are returned; if\n        `*`, both indices and values are returned. Default: 'values'.\n\n    indicator: Function\n        Indicator function specifying which group an element in the input\n        collection belongs to.\n\n    Returns\n    -------\n    out: Object\n        Group results.\n\n    Examples\n    --------\n    > function indicator( v ) {\n    ...     if ( v[ 0 ] === 'b' ) {\n    ...         return 'b';\n    ...     }\n    ...     return 'other';\n    ... };\n    > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n    > var out = groupBy( collection, indicator )\n    { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n    // Output group results as indices:\n    > var opts = { 'returns': 'indices' };\n    > out = groupBy( collection, opts, indicator )\n    { 'b': [ 0, 1, 3 ], 'other': [ 2 ] }\n\n    // Output group results as index-value pairs:\n    > opts = { 'returns': '*' };\n    > out = groupBy( collection, opts, indicator )\n    { 'b': [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], 'other': [ [2, 'foo' ] ] }\n\n    See Also\n    --------\n    bifurcateBy, countBy, group\n","groupByAsync":"\ngroupByAsync( collection, [options,] indicator, done )\n    Groups values according to an indicator function.\n\n    When invoked, the indicator function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If the\n    indicator function accepts two arguments, the indicator function is\n    provided:\n\n    - value\n    - next\n\n    If the indicator function accepts three arguments, the indicator function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other indicator function signature, the indicator function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - group: value group.\n\n    If an indicator function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    If provided an empty collection, the function calls the `done` callback with\n    an empty object as the second argument.\n\n    The `group` returned by an indicator function should be a value which can be\n    serialized as an object key.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `indices`, indices are returned; if\n        `*`, both indices and values are returned. Default: 'values'.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    indicator: Function\n        Indicator function specifying which group an element in the input\n        collection belongs to.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > groupByAsync( arr, indicator, done )\n    1000\n    2500\n    3000\n    { \"true\": [ 1000, 3000 ], \"false\": [ 2500 ] }\n\n    // Output group results as indices:\n    > var opts = { 'returns': 'indices' };\n    > groupByAsync( arr, opts, indicator, done )\n    1000\n    2500\n    3000\n    { \"true\": [ 2, 0 ], \"false\": [ 1 ] }\n\n    // Output group results as index-value pairs:\n    > opts = { 'returns': '*' };\n    > groupByAsync( arr, opts, indicator, done )\n    1000\n    2500\n    3000\n    { \"true\": [ [ 2, 1000 ], [ 0, 3000 ] ], \"false\": [ [ 1, 2500 ] ] }\n\n    // Limit number of concurrent invocations:\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 3000, 2500, 1000 ];\n    > groupByAsync( arr, opts, indicator, done )\n    2500\n    3000\n    1000\n    { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n\n    // Process sequentially:\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 3000, 2500, 1000 ];\n    > groupByAsync( arr, opts, indicator, done )\n    3000\n    2500\n    1000\n    { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n\n\ngroupByAsync.factory( [options,] indicator )\n    Returns a function which groups values according to an indicator function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `indices`, indices are returned; if\n        `*`, both indices and values are returned. Default: 'values'.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    indicator: Function\n        Indicator function specifying which group an element in the input\n        collection belongs to.\n\n    Returns\n    -------\n    out: Function\n        A group-by function.\n\n    Examples\n    --------\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = groupByAsync.factory( opts, indicator );\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    { \"true\": [ 2000, 1000 ], \"false\": [ 1500 ] }\n\n    See Also\n    --------\n    bifurcateByAsync, countByAsync, groupBy\n","groupByAsync.factory":"\ngroupByAsync.factory( [options,] indicator )\n    Returns a function which groups values according to an indicator function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `indices`, indices are returned; if\n        `*`, both indices and values are returned. Default: 'values'.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    indicator: Function\n        Indicator function specifying which group an element in the input\n        collection belongs to.\n\n    Returns\n    -------\n    out: Function\n        A group-by function.\n\n    Examples\n    --------\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = groupByAsync.factory( opts, indicator );\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    { \"true\": [ 2000, 1000 ], \"false\": [ 1500 ] }\n\n    See Also\n    --------\n    bifurcateByAsync, countByAsync, groupBy","groupIn":"\ngroupIn( obj, [options,] indicator )\n    Group values according to an indicator function.\n\n    When invoked, the indicator function is provided two arguments:\n\n    - value: object value.\n    - key: object key.\n\n    The value returned by an indicator function should be a value which can be\n    serialized as an object key.\n\n    If provided an empty object with no prototype, the function returns an empty\n    object.\n\n    The function iterates over an object's own and inherited properties.\n\n    Key iteration order is *not* guaranteed, and, thus, result order is *not*\n    guaranteed.\n\n    Parameters\n    ----------\n    obj: Object|Array|TypedArray\n        Input object to group.\n\n    options: Object (optional)\n        Options.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `keys`, keys are returned; if `*`,\n        both keys and values are returned. Default: 'values'.\n\n    indicator: Function\n        Indicator function indicating which group a value in the input object\n        belongs to.\n\n    Returns\n    -------\n    out: Object\n        Group results.\n\n    Examples\n    --------\n    > function indicator( v ) {\n    ...     if ( v[ 0 ] === 'b' ) {\n    ...         return 'b';\n    ...     }\n    ...     return 'other';\n    ... };\n    > function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\n    > Foo.prototype = Object.create( null );\n    > Foo.prototype.c = 'foo';\n    > Foo.prototype.d = 'bar';\n    > var obj = new Foo();\n    > var out = groupIn( obj, indicator )\n    { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n    // Output group results as keys:\n    > var opts = { 'returns': 'keys' };\n    > out = groupIn( obj, opts, indicator )\n    { 'b': [ 'a', 'b', 'd' ], 'other': [ 'c' ] }\n\n    // Output group results as key-value pairs:\n    > opts = { 'returns': '*' };\n    > out = groupIn( obj, opts, indicator )\n    { 'b': [['a','beep'], ['b','boop'], ['d','bar']], 'other': [['c','foo' ]] }\n\n    See Also\n    --------\n    bifurcateIn, groupBy, groupOwn\n","groupOwn":"\ngroupOwn( obj, [options,] indicator )\n    Group values according to an indicator function.\n\n    When invoked, the indicator function is provided two arguments:\n\n    - value: object value.\n    - key: object key.\n\n    The value returned by an indicator function should be a value which can be\n    serialized as an object key.\n\n    If provided an empty object, the function returns an empty object.\n\n    The function iterates over an object's own properties.\n\n    Key iteration order is *not* guaranteed, and, thus, result order is *not*\n    guaranteed.\n\n    Parameters\n    ----------\n    obj: Object|Array|TypedArray\n        Input object to group.\n\n    options: Object (optional)\n        Options.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `keys`, keys are returned; if `*`,\n        both keys and values are returned. Default: 'values'.\n\n    indicator: Function\n        Indicator function indicating which group a value in the input object\n        belongs to.\n\n    Returns\n    -------\n    out: Object\n        Group results.\n\n    Examples\n    --------\n    > function indicator( v ) {\n    ...     if ( v[ 0 ] === 'b' ) {\n    ...         return 'b';\n    ...     }\n    ...     return 'other';\n    ... };\n    > var obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\n    > var out = groupOwn( obj, indicator )\n    { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n    // Output group results as keys:\n    > var opts = { 'returns': 'keys' };\n    > out = groupOwn( obj, opts, indicator )\n    { 'b': [ 'a', 'b', 'd' ], 'other': [ 'c' ] }\n\n    // Output group results as key-value pairs:\n    > opts = { 'returns': '*' };\n    > out = groupOwn( obj, opts, indicator )\n    { 'b': [['a','beep'], ['b','boop'], ['d','bar']], 'other': [['c','foo' ]] }\n\n    See Also\n    --------\n    bifurcateOwn, group, groupBy\n","gswap":"\ngswap( x, y )\n    Interchanges two vectors.\n\n    In general, for best performance, especially for large vectors, provide\n    1-dimensional ndarrays whose underlying data type is either 'float64' or\n    'float32'.\n\n    Parameters\n    ----------\n    x: ndarray|ArrayLikeObject\n        First input array.\n\n    y: ndarray|ArrayLikeObject\n        Second input array.\n\n    Returns\n    -------\n    y: ndarray\n        The second input array `y`.\n\n    Examples\n    --------\n    // Using ndarrays...\n    > var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n    > var y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n    > gswap( x, y );\n    > x.data\n    <Float64Array>[ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n    > y.data\n    <Float64Array>[ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n    // Using array-like objects...\n    > x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n    > y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n    > gswap( x, y );\n    > x\n    [ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n    > y\n    [ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n    See Also\n    --------\n    base.strided.gswap, dswap, sswap\n","HALF_LN2":"\nHALF_LN2\n    One half times the natural logarithm of `2`.\n\n    Examples\n    --------\n    > HALF_LN2\n    3.46573590279972654709e-01\n\n    See Also\n    --------\n    LN2\n","HALF_PI":"\nHALF_PI\n    One half times the mathematical constant `π`.\n\n    Examples\n    --------\n    > HALF_PI\n    1.5707963267948966\n\n    See Also\n    --------\n    PI\n","HARRISON_BOSTON_HOUSE_PRICES":"\nHARRISON_BOSTON_HOUSE_PRICES()\n    Returns a dataset derived from information collected by the US Census\n    Service concerning housing in Boston, Massachusetts (1978).\n\n    The data consists of 14 attributes:\n\n    - crim: per capita crime rate by town.\n    - zn: proportion of residential land zoned for lots over 25,000 square feet.\n    - indus: proportion of non-retail business acres per town.\n    - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise).\n    - nox: nitric oxides concentration (parts per 10 million).\n    - rm: average number of rooms per dwelling.\n    - age: proportion of owner-occupied units built prior to 1940.\n    - dis: weighted distances to five Boston employment centers.\n    - rad: index of accessibility to radial highways.\n    - tax: full-value property-tax rate per $10,000.\n    - ptratio: pupil-teacher ratio by town.\n    - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town.\n    - lstat: percent lower status of the population.\n    - medv: median value of owner-occupied homes in $1000's.\n\n    The dataset can be used to predict two dependent variables: 1) nitrous oxide\n    level and 2) median home value.\n\n    The median home value field seems to be censored at 50.00 (corresponding to\n    a median value of $50,000). Censoring is suggested by the fact that the\n    highest median value of exactly $50,000 is reported in 16 cases, while 15\n    cases have values between $40,000 and $50,000. Values are rounded to the\n    nearest hundred. Harrison and Rubinfeld do not, however, mention any\n    censoring.\n\n    Additionally, as documented by Gilley and Pace (1996), the dataset contains\n    eight miscoded median values.\n\n    Returns\n    -------\n    out: Array<Object>\n        Boston house prices.\n\n    Examples\n    --------\n    > var data = HARRISON_BOSTON_HOUSE_PRICES()\n    [ {...}, {...}, ... ]\n\n    References\n    ----------\n    - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n    the demand for clean air.\" _Journal of Environmental Economics and\n    Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n    - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n    Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n    doi:10.1006/jeem.1996.0052.\n\n    See Also\n    --------\n    HARRISON_BOSTON_HOUSE_PRICES_CORRECTED, PACE_BOSTON_HOUSE_PRICES\n","HARRISON_BOSTON_HOUSE_PRICES_CORRECTED":"\nHARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n    Returns a (corrected) dataset derived from information collected by the US\n    Census Service concerning housing in Boston, Massachusetts (1978).\n\n    The data consists of 15 attributes:\n\n    - crim: per capita crime rate by town.\n    - zn: proportion of residential land zoned for lots over 25,000 square feet.\n    - indus: proportion of non-retail business acres per town.\n    - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise).\n    - nox: nitric oxides concentration (parts per 10 million).\n    - rm: average number of rooms per dwelling.\n    - age: proportion of owner-occupied units built prior to 1940.\n    - dis: weighted distances to five Boston employment centers.\n    - rad: index of accessibility to radial highways.\n    - tax: full-value property-tax rate per $10,000.\n    - ptratio: pupil-teacher ratio by town.\n    - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town\n    - lstat: percent lower status of the population.\n    - medv: median value of owner-occupied homes in $1000's.\n    - cmedv: corrected median value of owner-occupied homes in $1000's.\n\n    The dataset can be used to predict two dependent variables: 1) nitrous oxide\n    level and 2) median home value.\n\n    The median home value field seems to be censored at 50.00 (corresponding to\n    a median value of $50,000). Censoring is suggested by the fact that the\n    highest median value of exactly $50,000 is reported in 16 cases, while 15\n    cases have values between $40,000 and $50,000. Values are rounded to the\n    nearest hundred. Harrison and Rubinfeld do not, however, mention any\n    censoring.\n\n    The dataset contains eight corrections to miscoded median values, as\n    documented by Gilley and Pace (1996).\n\n    Returns\n    -------\n    out: Array<Object>\n        Boston house prices.\n\n    Examples\n    --------\n    > var data = HARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n    [ {...}, {...}, ... ]\n\n    References\n    ----------\n    - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n    the demand for clean air.\" _Journal of Environmental Economics and\n    Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n    - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n    Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n    doi:10.1006/jeem.1996.0052.\n\n    See Also\n    --------\n    HARRISON_BOSTON_HOUSE_PRICES, PACE_BOSTON_HOUSE_PRICES\n","hasArrayBufferSupport":"\nhasArrayBufferSupport()\n    Tests for native `ArrayBuffer` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `ArrayBuffer` support.\n\n    Examples\n    --------\n    > var bool = hasArrayBufferSupport()\n    <boolean>\n\n    See Also\n    --------\n    hasFloat32ArraySupport, hasFloat64ArraySupport, hasInt16ArraySupport, hasInt32ArraySupport, hasInt8ArraySupport, hasNodeBufferSupport, hasSharedArrayBufferSupport, hasUint16ArraySupport, hasUint32ArraySupport, hasUint8ArraySupport, hasUint8ClampedArraySupport\n","hasArrowFunctionSupport":"\nhasArrowFunctionSupport()\n    Tests whether an environment supports native arrow functions.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment support arrow functions.\n\n    Examples\n    --------\n    > var bool = hasArrowFunctionSupport()\n    <boolean>\n\n","hasAsyncAwaitSupport":"\nhasAsyncAwaitSupport()\n    Tests for native `async`/`await` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has native `async`/`await` support.\n\n    Examples\n    --------\n    > var bool = hasAsyncAwaitSupport()\n    <boolean>\n\n","hasAsyncIteratorSymbolSupport":"\nhasAsyncIteratorSymbolSupport()\n    Tests for native `Symbol.asyncIterator` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has native `Symbol.asyncIterator`\n        support.\n\n    Examples\n    --------\n    > var bool = hasAsyncIteratorSymbolSupport()\n    <boolean>\n\n    See Also\n    --------\n    hasIteratorSymbolSupport, hasSymbolSupport\n","hasAtobSupport":"\nhasAtobSupport()\n    Tests for native `atob` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `atob` support.\n\n    Examples\n    --------\n    > var bool = hasAtobSupport()\n    <boolean>\n\n    See Also\n    --------\n    hasBtoaSupport\n","hasBigInt64ArraySupport":"\nhasBigInt64ArraySupport()\n    Tests for native `BigInt64Array` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `BigInt64Array` support.\n\n    Examples\n    --------\n    > var bool = hasBigInt64ArraySupport()\n    <boolean>\n\n    See Also\n    --------\n    hasBigIntSupport, hasBigUint64ArraySupport\n","hasBigIntSupport":"\nhasBigIntSupport()\n    Tests for native `BigInt` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has native `BigInt` support.\n\n    Examples\n    --------\n    > var bool = hasBigIntSupport()\n    <boolean>\n\n","hasBigUint64ArraySupport":"\nhasBigUint64ArraySupport()\n    Tests for native `BigUint64Array` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `BigUint64Array` support.\n\n    Examples\n    --------\n    > var bool = hasBigUint64ArraySupport()\n    <boolean>\n\n    See Also\n    --------\n    hasBigIntSupport, hasBigInt64ArraySupport\n","hasBtoaSupport":"\nhasBtoaSupport()\n    Tests for native `btoa` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `btoa` support.\n\n    Examples\n    --------\n    > var bool = hasBtoaSupport()\n    <boolean>\n\n    See Also\n    --------\n    hasAtobSupport\n","hasClassSupport":"\nhasClassSupport()\n    Tests for native `class` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has native `class` support.\n\n    Examples\n    --------\n    > var bool = hasClassSupport()\n    <boolean>\n\n","hasDataViewSupport":"\nhasDataViewSupport()\n    Tests for native `DataView` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `DataView` support.\n\n    Examples\n    --------\n    > var bool = hasDataViewSupport()\n    <boolean>\n\n    See Also\n    --------\n    hasArrayBufferSupport\n","hasDefinePropertiesSupport":"\nhasDefinePropertiesSupport()\n    Tests for `Object.defineProperties` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Object.defineProperties`\n        support.\n\n    Examples\n    --------\n    > var bool = hasDefinePropertiesSupport()\n    <boolean>\n\n    See Also\n    --------\n    hasDefinePropertySupport\n","hasDefinePropertySupport":"\nhasDefinePropertySupport()\n    Tests for `Object.defineProperty` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Object.defineProperty`\n        support.\n\n    Examples\n    --------\n    > var bool = hasDefinePropertySupport()\n    <boolean>\n\n    See Also\n    --------\n    hasDefinePropertiesSupport\n","hasFloat32ArraySupport":"\nhasFloat32ArraySupport()\n    Tests for native `Float32Array` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Float32Array` support.\n\n    Examples\n    --------\n    > var bool = hasFloat32ArraySupport()\n    <boolean>\n\n","hasFloat64ArraySupport":"\nhasFloat64ArraySupport()\n    Tests for native `Float64Array` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Float64Array` support.\n\n    Examples\n    --------\n    > var bool = hasFloat64ArraySupport()\n    <boolean>\n\n","hasFunctionNameSupport":"\nhasFunctionNameSupport()\n    Tests for native function `name` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has function `name` support.\n\n    Examples\n    --------\n    > var bool = hasFunctionNameSupport()\n    <boolean>\n\n","hasGeneratorSupport":"\nhasGeneratorSupport()\n    Tests whether an environment supports native generator functions.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment support generator functions.\n\n    Examples\n    --------\n    > var bool = hasGeneratorSupport()\n    <boolean>\n\n","hasGlobalThisSupport":"\nhasGlobalThisSupport()\n    Tests for `globalThis` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `globalThis` support.\n\n    Examples\n    --------\n    > var bool = hasGlobalThisSupport()\n    <boolean>\n\n    See Also\n    --------\n    getGlobal\n","hasInt8ArraySupport":"\nhasInt8ArraySupport()\n    Tests for native `Int8Array` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Int8Array` support.\n\n    Examples\n    --------\n    > var bool = hasInt8ArraySupport()\n    <boolean>\n\n","hasInt16ArraySupport":"\nhasInt16ArraySupport()\n    Tests for native `Int16Array` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Int16Array` support.\n\n    Examples\n    --------\n    > var bool = hasInt16ArraySupport()\n    <boolean>\n\n","hasInt32ArraySupport":"\nhasInt32ArraySupport()\n    Tests for native `Int32Array` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Int32Array` support.\n\n    Examples\n    --------\n    > var bool = hasInt32ArraySupport()\n    <boolean>\n\n","hasIteratorSymbolSupport":"\nhasIteratorSymbolSupport()\n    Tests for native `Symbol.iterator` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has native `Symbol.iterator`\n        support.\n\n    Examples\n    --------\n    > var bool = hasIteratorSymbolSupport()\n    <boolean>\n\n    See Also\n    --------\n    hasAsyncIteratorSymbolSupport, hasSymbolSupport\n","hasMapSupport":"\nhasMapSupport()\n    Tests for native `Map` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Map` support.\n\n    Examples\n    --------\n    > var bool = hasMapSupport()\n    <boolean>\n\n","hasNodeBufferSupport":"\nhasNodeBufferSupport()\n    Tests for native `Buffer` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Buffer` support.\n\n    Examples\n    --------\n    > var bool = hasNodeBufferSupport()\n    <boolean>\n\n","hasOwnProp":"\nhasOwnProp( value, property )\n    Tests if an object has a specified property.\n\n    In contrast to the native `Object.prototype.hasOwnProperty`, this function\n    does not throw when provided `null` or `undefined`. Instead, the function\n    returns `false`.\n\n    Value arguments other than `null` or `undefined` are coerced to objects.\n\n    Property arguments are coerced to strings.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object has a specified property.\n\n    Examples\n    --------\n    > var beep = { 'boop': true };\n    > var bool = hasOwnProp( beep, 'boop' )\n    true\n    > bool = hasOwnProp( beep, 'bop' )\n    false\n\n    See Also\n    --------\n    hasProp\n","hasProp":"\nhasProp( value, property )\n    Tests if an object has a specified property, either own or inherited.\n\n    Value arguments other than `null` or `undefined` are coerced to objects.\n\n    Non-symbol property arguments are coerced to strings.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object has a specified property.\n\n    Examples\n    --------\n    > var beep = { 'boop': true };\n    > var bool = hasProp( beep, 'boop' )\n    true\n    > bool = hasProp( beep, 'toString' )\n    true\n    > bool = hasProp( beep, 'bop' )\n    false\n\n    See Also\n    --------\n    hasOwnProp\n","hasProxySupport":"\nhasProxySupport()\n    Tests whether an environment has native `Proxy` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has native `Proxy` support.\n\n    Examples\n    --------\n    > var bool = hasProxySupport()\n    <boolean>\n\n","hasSetSupport":"\nhasSetSupport()\n    Tests for native `Set` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has native `Set` support.\n\n    Examples\n    --------\n    > var bool = hasSetSupport()\n    <boolean>\n\n","hasSharedArrayBufferSupport":"\nhasSharedArrayBufferSupport()\n    Tests for native `SharedArrayBuffer` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `SharedArrayBuffer` support.\n\n    Examples\n    --------\n    > var bool = hasSharedArrayBufferSupport()\n    <boolean>\n\n    See Also\n    --------\n    hasArrayBufferSupport, hasFloat32ArraySupport, hasFloat64ArraySupport, hasInt16ArraySupport, hasInt32ArraySupport, hasInt8ArraySupport, hasNodeBufferSupport, hasUint16ArraySupport, hasUint32ArraySupport, hasUint8ArraySupport, hasUint8ClampedArraySupport\n","hasSymbolSupport":"\nhasSymbolSupport()\n    Tests for native `Symbol` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has native `Symbol` support.\n\n    Examples\n    --------\n    > var bool = hasSymbolSupport()\n    <boolean>\n\n    See Also\n    --------\n    hasIteratorSymbolSupport\n","hasToStringTagSupport":"\nhasToStringTagSupport()\n    Tests for native `toStringTag` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `toStringTag` support.\n\n    Examples\n    --------\n    > var bool = hasToStringTagSupport()\n    <boolean>\n\n","hasUint8ArraySupport":"\nhasUint8ArraySupport()\n    Tests for native `Uint8Array` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Uint8Array` support.\n\n    Examples\n    --------\n    > var bool = hasUint8ArraySupport()\n    <boolean>\n\n","hasUint8ClampedArraySupport":"\nhasUint8ClampedArraySupport()\n    Tests for native `Uint8ClampedArray` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Uint8ClampedArray` support.\n\n    Examples\n    --------\n    > var bool = hasUint8ClampedArraySupport()\n    <boolean>\n\n","hasUint16ArraySupport":"\nhasUint16ArraySupport()\n    Tests for native `Uint16Array` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Uint16Array` support.\n\n    Examples\n    --------\n    > var bool = hasUint16ArraySupport()\n    <boolean>\n\n","hasUint32ArraySupport":"\nhasUint32ArraySupport()\n    Tests for native `Uint32Array` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Uint32Array` support.\n\n    Examples\n    --------\n    > var bool = hasUint32ArraySupport()\n    <boolean>\n\n","hasUTF16SurrogatePairAt":"\nhasUTF16SurrogatePairAt( str, pos )\n    Tests if a position in a string marks the start of a UTF-16 surrogate pair.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    pos: integer\n        Position.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether surrogate pair exists at specified position.\n\n    Examples\n    --------\n    > var out = hasUTF16SurrogatePairAt( '🌷', 0 )\n    true\n    > out = hasUTF16SurrogatePairAt( '🌷', 1 )\n    false\n\n","hasWeakMapSupport":"\nhasWeakMapSupport()\n    Tests for native `WeakMap` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `WeakMap` support.\n\n    Examples\n    --------\n    > var bool = hasWeakMapSupport()\n    <boolean>\n\n","hasWeakSetSupport":"\nhasWeakSetSupport()\n    Tests for native `WeakSet` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `WeakSet` support.\n\n    Examples\n    --------\n    > var bool = hasWeakSetSupport()\n    <boolean>\n\n","hasWebAssemblySupport":"\nhasWebAssemblySupport()\n    Tests for native WebAssembly support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has native WebAssembly support.\n\n    Examples\n    --------\n    > var bool = hasWebAssemblySupport()\n    <boolean>\n\n","headercase":"\nheadercase( str )\n    Converts a string to HTTP header case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        HTTP header-cased string.\n\n    Examples\n    --------\n    > var out = headercase( 'Hello World!' )\n    'Hello-World'\n    > out = headercase( 'beep boop' )\n    'Beep-Boop'\n\n    See Also\n    --------\n    camelcase, kebabcase, pascalcase, snakecase","HERNDON_VENUS_SEMIDIAMETERS":"\nHERNDON_VENUS_SEMIDIAMETERS()\n    Returns fifteen observations of the vertical semidiameter of Venus, made by\n    Lieutenant Herndon, with the meridian circle at Washington, in the year\n    1846.\n\n    This dataset is a classic dataset commonly used in examples demonstrating\n    outlier detection.\n\n    Returns\n    -------\n    out: Array<number>\n        Observations.\n\n    Examples\n    --------\n    > var d = HERNDON_VENUS_SEMIDIAMETERS()\n    [ -0.30, -0.44, ..., 0.39, 0.10 ]\n\n    References\n    ----------\n    - Chauvenet, William. 1868. _A Manual of Spherical and Practical Astronomy_.\n    5th ed. Vol. 5. London, England: Trübner & Co.\n    - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n    Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n    of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n    - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n    Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n    00401706.1969.10490657.\n    - Tietjen, Gary L., and Roger H. Moore. 1972. \"Some Grubbs-Type Statistics\n    for the Detection of Several Outliers.\" _Technometrics_ 14 (3). Taylor &\n    Francis: 583–97. doi:10.1080/00401706.1972.10488948.\n\n","homedir":"\nhomedir()\n    Returns the current user's home directory.\n\n    If unable to locate a home directory, the function returns `null`.\n\n    Returns\n    -------\n    out: string|null\n        Home directory.\n\n    Examples\n    --------\n    > var home = homedir()\n    e.g., '/Users/<username>'\n\n    See Also\n    --------\n    configdir, tmpdir\n","HOURS_IN_DAY":"\nHOURS_IN_DAY\n    Number of hours in a day.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var days = 3.14;\n    > var hrs = days * HOURS_IN_DAY\n    75.36\n\n    See Also\n    --------\n    HOURS_IN_WEEK\n","HOURS_IN_WEEK":"\nHOURS_IN_WEEK\n    Number of hours in a week.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var wks = 3.14;\n    > var hrs = wks * HOURS_IN_WEEK\n    527.52\n\n    See Also\n    --------\n    HOURS_IN_DAY\n","hoursInMonth":"\nhoursInMonth( [month[, year]] )\n    Returns the number of hours in a month.\n\n    By default, the function returns the number of hours in the current month of\n    the current year (according to local time). To determine the number of hours\n    for a particular month and year, provide `month` and `year` arguments.\n\n    A `month` may be either a month's integer value, three letter abbreviation,\n    or full name (case insensitive).\n\n    The function's return value is a generalization and does **not** take into\n    account inaccuracies due to daylight savings conventions, crossing\n    timezones, or other complications with time and dates.\n\n    Parameters\n    ----------\n    month: string|Date|integer (optional)\n        Month.\n\n    year: integer (optional)\n        Year.\n\n    Returns\n    -------\n    out: integer\n        Hours in a month.\n\n    Examples\n    --------\n    > var num = hoursInMonth()\n    <number>\n    > num = hoursInMonth( 2 )\n    <number>\n    > num = hoursInMonth( 2, 2016 )\n    696\n    > num = hoursInMonth( 2, 2017 )\n    672\n\n    // Other ways to supply month:\n    > num = hoursInMonth( 'feb', 2016 )\n    696\n    > num = hoursInMonth( 'february', 2016 )\n    696\n\n    See Also\n    --------\n    hoursInYear\n","hoursInYear":"\nhoursInYear( [value] )\n    Returns the number of hours in a year according to the Gregorian calendar.\n\n    By default, the function returns the number of hours in the current year\n    (according to local time). To determine the number of hours for a particular\n    year, provide either a year or a `Date` object.\n\n    The function's return value is a generalization and does **not** take into\n    account inaccuracies due to daylight savings conventions, crossing\n    timezones, or other complications with time and dates.\n\n    Parameters\n    ----------\n    value: integer|Date (optional)\n        Year or `Date` object.\n\n    Returns\n    -------\n    out: integer\n        Number of hours in a year.\n\n    Examples\n    --------\n    > var num = hoursInYear()\n    <number>\n    > num = hoursInYear( 2016 )\n    8784\n    > num = hoursInYear( 2017 )\n    8760\n\n    See Also\n    --------\n    hoursInMonth\n","httpServer":"\nhttpServer( [options,] [requestListener] )\n    Returns a function to create an HTTP server.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.port: integer (optional)\n        Server port. Default: `0` (i.e., randomly assigned).\n\n    options.maxport: integer (optional)\n        Max server port when port hunting. Default: `maxport = port`.\n\n    options.hostname: string (optional)\n        Server hostname.\n\n    options.address: string (optional)\n        Server address. Default: `'127.0.0.1'`.\n\n    requestListener: Function (optional)\n        Request callback.\n\n    Returns\n    -------\n    createServer: Function\n        Function to create an HTTP server.\n\n    Examples\n    --------\n    // Basic usage:\n    > var createServer = httpServer()\n    <Function>\n\n    // Provide a request callback:\n    > function onRequest( request, response ) {\n    ...    console.log( request.url );\n    ...    response.end( 'OK' );\n    ... };\n    > createServer = httpServer( onRequest )\n    <Function>\n\n    // Specify a specific port:\n    > var opts = { 'port': 7331 };\n    > createServer = httpServer( opts )\n    <Function>\n\n\ncreateServer( done )\n    Creates an HTTP server.\n\n    Parameters\n    ----------\n    done: Function\n        Callback to invoke after creating a server.\n\n    Examples\n    --------\n    > function done( error, server ) {\n    ...    if ( error ) {\n    ...        throw error;\n    ...    }\n    ...    console.log( 'Success!' );\n    ...    server.close();\n    ... };\n    > var createServer = httpServer();\n    > createServer( done );\n\n","identity":"\nidentity( x )\n    Identity function.\n\n    Parameters\n    ----------\n    x: any\n        Input value.\n\n    Returns\n    -------\n    out: any\n        Input value.\n\n    Examples\n    --------\n    > var v = identity( 3.14 )\n    3.14\n\n    See Also\n    --------\n    constantFunction\n","ifelse":"\nifelse( bool, x, y )\n    If a condition is truthy, returns `x`; otherwise, returns `y`.\n\n    Parameters\n    ----------\n    bool: boolean\n        Condition.\n\n    x: any\n        Value to return if a condition is truthy.\n\n    y: any\n        Value to return if a condition is falsy.\n\n    Returns\n    -------\n    z: any\n        Either `x` or `y`.\n\n    Examples\n    --------\n    > var z = ifelse( true, 1.0, -1.0 )\n    1.0\n    > z = ifelse( false, 1.0, -1.0 )\n    -1.0\n\n    See Also\n    --------\n    ifelseAsync, ifthen\n","ifelseAsync":"\nifelseAsync( predicate, x, y, done )\n    If a predicate function returns a truthy value, returns `x`; otherwise,\n    returns `y`.\n\n    A predicate function is provided a single argument:\n\n    - clbk: callback to invoke upon predicate completion.\n\n    The callback function accepts two arguments:\n\n    - error: error object.\n    - bool: condition used to determine whether to invoke `x` or `y`.\n\n    The `done` callback is invoked upon function completion and is provided at\n    most two arguments:\n\n    - error: error object.\n    - result: either `x` or `y`.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function.\n\n    x: any\n        Value to return if a condition is truthy.\n\n    y: any\n        Value to return if a condition is falsy.\n\n    done: Function\n        Callback to invoke upon completion.\n\n    Examples\n    --------\n    > function predicate( clbk ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         clbk( null, true );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > ifelseAsync( predicate, 'beep', 'boop', done )\n    'beep'\n\n    See Also\n    --------\n    ifthenAsync, ifelse\n","ifthen":"\nifthen( bool, x, y )\n    If a condition is truthy, invoke `x`; otherwise, invoke `y`.\n\n    Parameters\n    ----------\n    bool: boolean\n        Condition.\n\n    x: Function\n        Function to invoke if a condition is truthy.\n\n    y: Function\n        Function to invoke if a condition is falsy.\n\n    Returns\n    -------\n    z: any\n        Return value of either `x` or `y`.\n\n    Examples\n    --------\n    > function x() { return 1.0; };\n    > function y() { return -1.0; };\n    > var z = ifthen( true, x, y )\n    1.0\n    > z = ifthen( false, x, y )\n    -1.0\n\n    See Also\n    --------\n    ifthenAsync, ifelse\n","ifthenAsync":"\nifthenAsync( predicate, x, y, done )\n    If a predicate function returns a truthy value, invokes `x`; otherwise,\n    invokes `y`.\n\n    The predicate function is provided a single argument:\n\n    - clbk: callback to invoke upon predicate function completion.\n\n    The predicate function callback accepts two arguments:\n\n    - error: error object.\n    - bool: condition used to determine whether to invoke `x` or `y`.\n\n    Both `x` and `y` are provided a single argument:\n\n    - clbk: callback to invoke upon function completion.\n\n    The callback function accepts any number of arguments, with the first\n    argument reserved for providing an error.\n\n    If the error argument is falsy, the `done` callback is invoked with its\n    first argument as `null` and all other provided arguments.\n\n    If the error argument is truthy, the `done` callback is invoked with only an\n    error argument.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function.\n\n    x: Function\n        Function to invoke if a condition is truthy.\n\n    y: Function\n        Function to invoke if a condition is falsy.\n\n    done: Function\n        Callback to invoke upon completion.\n\n    Examples\n    --------\n    > function predicate( clbk ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         clbk( null, false );\n    ...     }\n    ... };\n    > function x( clbk ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         clbk( null, 'beep' );\n    ...     }\n    ... };\n    > function y( clbk ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         clbk( null, 'boop' );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > ifthenAsync( predicate, x, y, done )\n    'boop'\n\n    See Also\n    --------\n    ifelseAsync, ifthen\n","imag":"\nimag( z )\n    Returns the imaginary component of a double-precision complex floating-point\n    number.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    im: number\n        Imaginary component.\n\n    Examples\n    --------\n    > var z = new Complex128( 5.0, 3.0 );\n    > var im = imag( z )\n    3.0\n\n    See Also\n    --------\n    real, reim\n","imagf":"\nimagf( z )\n    Returns the imaginary component of a single-precision complex floating-point\n    number.\n\n    Parameters\n    ----------\n    z: Complex64\n        Complex number.\n\n    Returns\n    -------\n    im: number\n        Imaginary component.\n\n    Examples\n    --------\n    > var z = new Complex64( 5.0, 3.0 );\n    > var im = imagf( z )\n    3.0\n\n    See Also\n    --------\n    imag, realf, reimf\n","IMG_ACANTHUS_MOLLIS":"\nIMG_ACANTHUS_MOLLIS()\n    Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n    print *Acanthus mollis*.\n\n    Returns\n    -------\n    out: Buffer\n        Image data.\n\n    Examples\n    --------\n    > var img = IMG_ACANTHUS_MOLLIS()\n    <Buffer>\n\n    References\n    ----------\n    - Blossfeldt, Karl. 1928. *Acanthus mollis*. <http://www.getty.edu/art/\n    collection/objects/35443/karl-blossfeldt-acanthus-mollis-german-1928/>.\n\n    * Digital image courtesy of the Getty's Open Content Program. While there\n    are no restrictions or conditions on the use of open content images, the\n    Getty would appreciate a gratis copy of any scholarly publications in which\n    the images are reproduced in order to maintain the collection bibliography.\n    Copies may be sent to the attention of:\n\n      Open Content Program\n      Registrar's Office\n      The J. Paul Getty Museum\n      1200 Getty Center Drive, Suite 1000\n      Los Angeles, CA 90049\n\n    See Also\n    --------\n    IMG_ALLIUM_OREOPHILUM\n","IMG_AIRPLANE_FROM_ABOVE":"\nIMG_AIRPLANE_FROM_ABOVE()\n    Returns a `Buffer` containing image data of Fédèle Azari's gelatin silver\n    print of an airplane, viewed from above looking down.\n\n    Returns\n    -------\n    out: Buffer\n        Image data.\n\n    Examples\n    --------\n    > var img = IMG_AIRPLANE_FROM_ABOVE()\n    <Buffer>\n\n    References\n    ----------\n    - Azari, Fédèle. 1929. (no title). <http://www.getty.edu/art/collection/\n    objects/134512/fedele-azari-airplane-viewed-from-above-looking-down-italian-\n    1914-1929/>.\n\n    * Digital image courtesy of the Getty's Open Content Program. While there\n    are no restrictions or conditions on the use of open content images, the\n    Getty would appreciate a gratis copy of any scholarly publications in which\n    the images are reproduced in order to maintain the collection bibliography.\n    Copies may be sent to the attention of:\n\n      Open Content Program\n      Registrar's Office\n      The J. Paul Getty Museum\n      1200 Getty Center Drive, Suite 1000\n      Los Angeles, CA 90049\n\n","IMG_ALLIUM_OREOPHILUM":"\nIMG_ALLIUM_OREOPHILUM()\n    Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n    print *Allium ostrowskianum*.\n\n    Returns\n    -------\n    out: Buffer\n        Image data.\n\n    Examples\n    --------\n    > var img = IMG_ALLIUM_OREOPHILUM()\n    <Buffer>\n\n    References\n    ----------\n    - Blossfeldt, Karl. 1928. *Allium ostrowskianum*. <http://www.getty.edu/art/\n    collection/objects/35448/karl-blossfeldt-allium-ostrowskianum-\n    knoblauchpflanze-german-1928/>.\n\n    * Digital image courtesy of the Getty's Open Content Program. While there\n    are no restrictions or conditions on the use of open content images, the\n    Getty would appreciate a gratis copy of any scholarly publications in which\n    the images are reproduced in order to maintain the collection bibliography.\n    Copies may be sent to the attention of:\n\n      Open Content Program\n      Registrar's Office\n      The J. Paul Getty Museum\n      1200 Getty Center Drive, Suite 1000\n      Los Angeles, CA 90049\n\n    See Also\n    --------\n    IMG_ACANTHUS_MOLLIS\n","IMG_BLACK_CANYON":"\nIMG_BLACK_CANYON()\n    Returns a `Buffer` containing image data of Timothy H. O'Sullivan's albumen\n    silver print *Black Cañon, Colorado River, From Camp 8, Looking Above*.\n\n    Returns\n    -------\n    out: Buffer\n        Image data.\n\n    Examples\n    --------\n    > var img = IMG_BLACK_CANYON()\n    <Buffer>\n\n    References\n    ----------\n    - O'Sullivan, Timothy H. 1871. *Black Cañon, Colorado River, From Camp 8,\n    Looking Above*. <http://www.getty.edu/art/collection/objects/40209/timothy-\n    h-o'sullivan-black-canon-colorado-river-from-camp-8-looking-above-american-\n    1871/>.\n\n    * Digital image courtesy of the Getty's Open Content Program. While there\n    are no restrictions or conditions on the use of open content images, the\n    Getty would appreciate a gratis copy of any scholarly publications in which\n    the images are reproduced in order to maintain the collection bibliography.\n    Copies may be sent to the attention of:\n\n      Open Content Program\n      Registrar's Office\n      The J. Paul Getty Museum\n      1200 Getty Center Drive, Suite 1000\n      Los Angeles, CA 90049\n\n","IMG_DUST_BOWL_HOME":"\nIMG_DUST_BOWL_HOME()\n    Returns a `Buffer` containing image data of Dorothea Lange's gelatin silver\n    print of an abandoned Dust Bowl home.\n\n    Returns\n    -------\n    out: Buffer\n        Image data.\n\n    Examples\n    --------\n    > var img = IMG_DUST_BOWL_HOME()\n    <Buffer>\n\n    References\n    ----------\n    - Lange, Dorothea. 1940. *Abandoned Dust Bowl Home*. <http://www.getty.edu/\n    art/collection/objects/128362/dorothea-lange-abandoned-dust-bowl-home-\n    american-about-1935-1940/>.\n\n    * Digital image courtesy of the Getty's Open Content Program. While there\n    are no restrictions or conditions on the use of open content images, the\n    Getty would appreciate a gratis copy of any scholarly publications in which\n    the images are reproduced in order to maintain the collection bibliography.\n    Copies may be sent to the attention of:\n\n      Open Content Program\n      Registrar's Office\n      The J. Paul Getty Museum\n      1200 Getty Center Drive, Suite 1000\n      Los Angeles, CA 90049\n\n","IMG_FRENCH_ALPINE_LANDSCAPE":"\nIMG_FRENCH_ALPINE_LANDSCAPE()\n    Returns a `Buffer` containing image data of Adolphe Braun's carbon print of\n    a French alpine landscape.\n\n    Returns\n    -------\n    out: Buffer\n        Image data.\n\n    Examples\n    --------\n    > var img = IMG_FRENCH_ALPINE_LANDSCAPE()\n    <Buffer>\n\n    References\n    ----------\n    - Braun, Adolphe. 1870. (no title). <http://www.getty.edu/art/collection/\n    objects/54324/adolphe-braun-alpine-landscape-french-1865-1870/>.\n\n    * Digital image courtesy of the Getty's Open Content Program. While there\n    are no restrictions or conditions on the use of open content images, the\n    Getty would appreciate a gratis copy of any scholarly publications in which\n    the images are reproduced in order to maintain the collection bibliography.\n    Copies may be sent to the attention of:\n\n      Open Content Program\n      Registrar's Office\n      The J. Paul Getty Museum\n      1200 Getty Center Drive, Suite 1000\n      Los Angeles, CA 90049\n\n","IMG_LOCOMOTION_HOUSE_CAT":"\nIMG_LOCOMOTION_HOUSE_CAT()\n    Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n    collotype of a house cat (24 views).\n\n    Returns\n    -------\n    out: Buffer\n        Image data.\n\n    Examples\n    --------\n    > var img = IMG_LOCOMOTION_HOUSE_CAT()\n    <Buffer>\n\n    References\n    ----------\n    - Muybridge, Eadweard J. 1887. *Animal Locomotion*. <http://www.getty.edu/\n    art/collection/objects/40918/eadweard-j-muybridge-animal-locomotion-american\n    -1887/>.\n\n    * Digital image courtesy of the Getty's Open Content Program. While there\n    are no restrictions or conditions on the use of open content images, the\n    Getty would appreciate a gratis copy of any scholarly publications in which\n    the images are reproduced in order to maintain the collection bibliography.\n    Copies may be sent to the attention of:\n\n      Open Content Program\n      Registrar's Office\n      The J. Paul Getty Museum\n      1200 Getty Center Drive, Suite 1000\n      Los Angeles, CA 90049\n\n    See Also\n    --------\n    IMG_LOCOMOTION_NUDE_MALE\n","IMG_LOCOMOTION_NUDE_MALE":"\nIMG_LOCOMOTION_NUDE_MALE()\n    Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n    collotype of a nude male moving in place (48 views).\n\n    Returns\n    -------\n    out: Buffer\n        Image data.\n\n    Examples\n    --------\n    > var img = IMG_LOCOMOTION_NUDE_MALE()\n    <Buffer>\n\n    References\n    ----------\n    - Muybridge, Eadweard J. 1887. *Animal Locomotion*. <http://www.getty.edu/\n    art/collection/objects/40918/eadweard-j-muybridge-animal-locomotion-american\n    -1887/>.\n\n    * Digital image courtesy of the Getty's Open Content Program. While there\n    are no restrictions or conditions on the use of open content images, the\n    Getty would appreciate a gratis copy of any scholarly publications in which\n    the images are reproduced in order to maintain the collection bibliography.\n    Copies may be sent to the attention of:\n\n      Open Content Program\n      Registrar's Office\n      The J. Paul Getty Museum\n      1200 Getty Center Drive, Suite 1000\n      Los Angeles, CA 90049\n\n    See Also\n    --------\n    IMG_LOCOMOTION_HOUSE_CAT\n","IMG_MARCH_PASTORAL":"\nIMG_MARCH_PASTORAL()\n    Returns a `Buffer` containing image data of Peter Henry Emerson's\n    photogravure of sheep in a pastoral setting.\n\n    Returns\n    -------\n    out: Buffer\n        Image data.\n\n    Examples\n    --------\n    > var img = IMG_MARCH_PASTORAL()\n    <Buffer>\n\n    References\n    ----------\n    - Emerson, Peter Henry. 1888. *A March Pastoral*. <http://www.getty.edu/art/\n    collection/objects/141994/peter-henry-emerson-a-march-pastoral-suffolk-\n    british-1888/>.\n\n    * Digital image courtesy of the Getty's Open Content Program. While there\n    are no restrictions or conditions on the use of open content images, the\n    Getty would appreciate a gratis copy of any scholarly publications in which\n    the images are reproduced in order to maintain the collection bibliography.\n    Copies may be sent to the attention of:\n\n      Open Content Program\n      Registrar's Office\n      The J. Paul Getty Museum\n      1200 Getty Center Drive, Suite 1000\n      Los Angeles, CA 90049\n\n","IMG_NAGASAKI_BOATS":"\nIMG_NAGASAKI_BOATS()\n    Returns a `Buffer` containing image data of Felice Beato's albumen silver\n    print of boats in a river in Nagasaki.\n\n    Returns\n    -------\n    out: Buffer\n        Image data.\n\n    Examples\n    --------\n    > var img = IMG_NAGASAKI_BOATS()\n    <Buffer>\n\n    References\n    ----------\n    - Beato, Felice. 1865. (no title). <http://www.getty.edu/art/collection/\n    objects/241797/felice-beato-boats-in-river-nagasaki-british-about-1865/>.\n\n    * Digital image courtesy of the Getty's Open Content Program. While there\n    are no restrictions or conditions on the use of open content images, the\n    Getty would appreciate a gratis copy of any scholarly publications in which\n    the images are reproduced in order to maintain the collection bibliography.\n    Copies may be sent to the attention of:\n\n      Open Content Program\n      Registrar's Office\n      The J. Paul Getty Museum\n      1200 Getty Center Drive, Suite 1000\n      Los Angeles, CA 90049\n\n","incrapcorr":"\nincrapcorr( [mx, my] )\n    Returns an accumulator function which incrementally computes the absolute\n    value of the sample Pearson product-moment correlation coefficient.\n\n    If provided values, the accumulator function returns an updated accumulated\n    value. If not provided values, the accumulator function returns the current\n    accumulated value.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    mx: number (optional)\n        Known mean.\n\n    my: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrapcorr();\n    > var ar = accumulator()\n    null\n    > ar = accumulator( 2.0, 1.0 )\n    0.0\n    > ar = accumulator( -5.0, 3.14 )\n    ~1.0\n    > ar = accumulator()\n    ~1.0\n\n    See Also\n    --------\n    incrmapcorr, incrpcorr, incrpcorr2\n","incrBinaryClassification":"\nincrBinaryClassification( N[, options] )\n    Returns an accumulator function which incrementally performs binary\n    classification using stochastic gradient descent (SGD).\n\n    If provided a feature vector and response value, the accumulator function\n    updates a binary classification model and returns updated model\n    coefficients.\n\n    If not provided a feature vector and response value, the accumulator\n    function returns the current model coefficients.\n\n    Stochastic gradient descent is sensitive to the scaling of the features. One\n    is advised to either scale each feature to `[0,1]` or `[-1,1]` or to\n    transform the features into z-scores with zero mean and unit variance. One\n    should keep in mind that the same scaling has to be applied to training data\n    in order to obtain accurate predictions.\n\n    In general, the more data provided to an accumulator, the more reliable the\n    model predictions.\n\n    Parameters\n    ----------\n    N: integer\n        Number of features.\n\n    options: Object (optional)\n        Function options.\n\n    options.intercept: boolean (optional)\n        Boolean indicating whether to include an intercept. Default: true.\n\n    options.lambda: number (optional)\n        Regularization parameter. Default: 1.0e-4.\n\n    options.learningRate: ArrayLike (optional)\n        Learning rate function and associated (optional) parameters. The first\n        array element specifies the learning rate function and must be one of\n        the following:\n\n        - ['constant', ...]: constant learning rate function. To set the\n        learning rate, provide a second array element. By default, when the\n        learn rate function is 'constant', the learning rate is set to 0.02.\n\n        - ['basic']: basic learning rate function according to the formula\n        `10/(10+t)` where `t` is the current iteration.\n\n        - ['invscaling', ...]: inverse scaling learning rate function according\n        to the formula `eta0/pow(t, power_t)` where `eta0` is the initial\n        learning rate and `power_t` is the exponent controlling how quickly the\n        learning rate decreases. To set the initial learning rate, provide a\n        second array element. By default, the initial learning rate is 0.02. To\n        set the exponent, provide a third array element. By default, the\n        exponent is 0.5.\n\n        - ['pegasos']: Pegasos learning rate function according to the formula\n        `1/(lambda*t)` where `t` is the current iteration and `lambda` is the\n        regularization parameter.\n\n        Default: ['basic'].\n\n    options.loss: string (optional)\n        Loss function. Must be one of the following:\n\n        - hinge: hinge loss function. Corresponds to a soft-margin linear\n        Support Vector Machine (SVM), which can handle non-linearly separable\n        data.\n\n        - log: logistic loss function. Corresponds to Logistic Regression.\n\n        - modifiedHuber: Huber loss function variant for classification.\n\n        - perceptron: hinge loss function without a margin. Corresponds to the\n        original Perceptron by Rosenblatt.\n\n        - squaredHinge: squared hinge loss function SVM (L2-SVM).\n\n        Default: 'log'.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    acc.predict: Function\n        Predicts response values for one ore more observation vectors. Provide a\n        second argument to specify the prediction type. Must be one of the\n        following: 'label', 'probability', or 'linear'. Default: 'label'.\n\n        Note that the probability prediction type is only compatible with 'log'\n        and 'modifiedHuber' loss functions.\n\n    Examples\n    --------\n    // Create an accumulator:\n    > var opts = {};\n    > opts.intercept = true;\n    > opts.lambda = 1.0e-5;\n    > var acc = incrBinaryClassification( 3, opts );\n\n    // Update the model:\n    > var buf = new Float64Array( [ 2.3, 1.0, 5.0 ] );\n    > var x = array( buf );\n    > var coefs = acc( x, 1 )\n    <ndarray>\n\n    // Create a new observation vector:\n    > buf = new Float64Array( [ 2.3, 5.3, 8.6 ] );\n    > x = array( buf );\n\n    // Predict the response value:\n    > var yhat = acc.predict( x )\n    <ndarray>\n\n    See Also\n    --------\n    incrSGDRegression\n","incrcount":"\nincrcount()\n    Returns an accumulator function which incrementally updates a count.\n\n    If provided a value, the accumulator function returns an updated count. If\n    not provided a value, the accumulator function returns the current count.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrcount();\n    > var v = accumulator()\n    0\n    > v = accumulator( 2.0 )\n    1\n    > v = accumulator( -5.0 )\n    2\n    > v = accumulator()\n    2\n\n    See Also\n    --------\n    incrmean, incrsum, incrsummary\n","incrcovariance":"\nincrcovariance( [mx, my] )\n    Returns an accumulator function which incrementally computes an unbiased\n    sample covariance.\n\n    If provided values, the accumulator function returns an updated unbiased\n    sample covariance. If not provided values, the accumulator function returns\n    the current unbiased sample covariance.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    mx: number (optional)\n        Known mean.\n\n    my: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrcovariance();\n    > var v = accumulator()\n    null\n    > v = accumulator( 2.0, 1.0 )\n    0.0\n    > v = accumulator( -5.0, 3.14 )\n    ~-7.49\n    > v = accumulator()\n    ~-7.49\n\n    See Also\n    --------\n    incrmcovariance, incrpcorr, incrvariance\n","incrcovmat":"\nincrcovmat( out[, means] )\n    Returns an accumulator function which incrementally computes an unbiased\n    sample covariance matrix.\n\n    If provided a data vector, the accumulator function returns an updated\n    unbiased sample covariance matrix. If not provided a data vector, the\n    accumulator function returns the current unbiased sample covariance matrix.\n\n    Parameters\n    ----------\n    out: integer|ndarray\n        Order of the covariance matrix or a square 2-dimensional ndarray for\n        storing the covariance matrix.\n\n    means: ndarray (optional)\n        Known means.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrcovmat( 2 );\n    > var out = accumulator()\n    <ndarray>\n    > var buf = new Float64Array( 2 );\n    > var shape = [ 2 ];\n    > var strides = [ 1 ];\n    > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n    > v.set( 0, 2.0 );\n    > v.set( 1, 1.0 );\n    > out = accumulator( v )\n    <ndarray>\n    > v.set( 0, -5.0 );\n    > v.set( 1, 3.14 );\n    > out = accumulator( v )\n    <ndarray>\n    > out = accumulator()\n    <ndarray>\n\n    See Also\n    --------\n    incrcovariance, incrpcorrmat\n","incrcv":"\nincrcv( [mean] )\n    Returns an accumulator function which incrementally computes the coefficient\n    of variation (CV).\n\n    If provided a value, the accumulator function returns an updated accumulated\n    value. If not provided a value, the accumulator function returns the current\n    accumulated value.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    mean: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrcv();\n    > var cv = accumulator()\n    null\n    > cv = accumulator( 2.0 )\n    0.0\n    > cv = accumulator( 1.0 )\n    ~0.47\n    > cv = accumulator()\n    ~0.47\n\n    See Also\n    --------\n    incrmean, incrmcv, incrstdev, incrvmr\n","increwmean":"\nincrewmean( α )\n    Returns an accumulator function which incrementally computes an\n    exponentially weighted mean, where α is a smoothing factor between 0 and 1.\n\n    If provided a value, the accumulator function returns an updated mean. If\n    not provided a value, the accumulator function returns the current mean.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    α: number\n        Smoothing factor (value between 0 and 1).\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = increwmean( 0.5 );\n    > var v = accumulator()\n    null\n    > v = accumulator( 2.0 )\n    2.0\n    > v = accumulator( -5.0 )\n    -1.5\n    > v = accumulator()\n    -1.5\n\n    See Also\n    --------\n    increwvariance, incrmean, incrmmean, incrwmean\n","increwstdev":"\nincrewstdev( α )\n    Returns an accumulator function which incrementally computes an\n    exponentially weighted standard deviation, where α is a smoothing factor\n    between 0 and 1.\n\n    If provided a value, the accumulator function returns an updated standard\n    deviation. If not provided a value, the accumulator function returns the\n    current standard deviation.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    α: number\n        Smoothing factor (value between 0 and 1).\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = increwstdev( 0.5 );\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    0.0\n    > s = accumulator( -5.0 )\n    3.5\n    > s = accumulator()\n    3.5\n\n    See Also\n    --------\n    increwvariance, incrmstdev, incrstdev\n","increwvariance":"\nincrewvariance( α )\n    Returns an accumulator function which incrementally computes an\n    exponentially weighted variance, where α is a smoothing factor between 0 and\n    1.\n\n    If provided a value, the accumulator function returns an updated variance.\n    If not provided a value, the accumulator function returns the current\n    variance.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    α: number\n        Smoothing factor (value between 0 and 1).\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = increwvariance( 0.5 );\n    > var v = accumulator()\n    null\n    > v = accumulator( 2.0 )\n    0.0\n    > v = accumulator( -5.0 )\n    12.25\n    > v = accumulator()\n    12.25\n\n    See Also\n    --------\n    increwmean, increwstdev, incrvariance, incrmvariance\n","incrgmean":"\nincrgmean()\n    Returns an accumulator function which incrementally computes a geometric\n    mean.\n\n    If provided a value, the accumulator function returns an updated geometric\n    mean. If not provided a value, the accumulator function returns the current\n    geometric mean.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    If provided a negative value, the accumulated value is `NaN` for all future\n    invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrgmean();\n    > var v = accumulator()\n    null\n    > v = accumulator( 2.0 )\n    2.0\n    > v = accumulator( 5.0 )\n    ~3.16\n    > v = accumulator()\n    ~3.16\n\n    See Also\n    --------\n    incrhmean, incrmean, incrmgmean, incrsummary\n","incrgrubbs":"\nincrgrubbs( [options] )\n    Returns an accumulator function which incrementally performs Grubbs' test\n    for detecting outliers.\n\n    Grubbs' test assumes that data is normally distributed. Accordingly, one\n    should first verify that the data can be reasonably approximated by a normal\n    distribution before applying the Grubbs' test.\n\n    If provided a value, the accumulator function returns updated test results.\n    If not provided a value, the accumulator function returns the current test\n    results.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the test statistic is `NaN` for all future invocations.\n\n    The accumulator must be provided *at least* three data points before\n    performing Grubbs' test. Until at least three data points are provided, the\n    accumulator returns `null`.\n\n    The accumulator function returns an object having the following fields:\n\n    - rejected: boolean indicating whether the null hypothesis should be\n    rejected.\n    - alpha: significance level.\n    - criticalValue: critical value.\n    - statistic: test statistic.\n    - df: degrees of freedom.\n    - mean: sample mean.\n    - sd: corrected sample standard deviation.\n    - min: minimum value.\n    - max: maximum value.\n    - alt: alternative hypothesis.\n    - method: method name.\n    - print: method for pretty-printing test output.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.alpha: number (optional)\n        Significance level. Default: 0.05.\n\n    options.alternative: string (optional)\n        Alternative hypothesis. The option may be one of the following values:\n\n        - 'two-sided': test whether the minimum or maximum value is an outlier.\n        - 'min': test whether the minimum value is an outlier.\n        - 'max': test whether the maximum value is an outlier.\n\n        Default: 'two-sided'.\n\n    options.init: integer (optional)\n        Number of data points the accumulator should use to compute initial\n        statistics *before* testing for an outlier. Until the accumulator is\n        provided the number of data points specified by this option, the\n        accumulator returns `null`. Default: 100.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var acc = incrgrubbs();\n    > var res = acc()\n    null\n    > for ( var i = 0; i < 200; i++ ) {\n    ...     res = acc( base.random.normal( 10.0, 5.0 ) );\n    ... };\n    > res.print()\n\n    References\n    ----------\n    - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n    Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n    of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n    - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n    Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n    00401706.1969.10490657.\n\n    See Also\n    --------\n    incrmgrubbs\n","incrhmean":"\nincrhmean()\n    Returns an accumulator function which incrementally computes a harmonic\n    mean.\n\n    If provided a value, the accumulator function returns an updated harmonic\n    mean. If not provided a value, the accumulator function returns the current\n    harmonic mean.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrhmean();\n    > var v = accumulator()\n    null\n    > v = accumulator( 2.0 )\n    2.0\n    > v = accumulator( 5.0 )\n    ~2.86\n    > v = accumulator()\n    ~2.86\n\n    See Also\n    --------\n    incrgmean, incrmean, incrmhmean, incrsummary\n","incrkmeans":"\nincrkmeans( k[, ndims][, options] )\n    Returns an accumulator function which incrementally partitions data into `k`\n    clusters.\n\n    If not provided initial centroids, the accumulator caches data vectors for\n    subsequent centroid initialization. Until an accumulator computes initial\n    centroids, an accumulator returns `null`.\n\n    Once an accumulator has initial centroids (either provided or computed), if\n    provided a data vector, the accumulator function returns updated cluster\n    results. If not provided a data vector, the accumulator function returns the\n    current cluster results.\n\n    Cluster results are comprised of the following:\n\n    - centroids: a `k x ndims` matrix containing centroid locations. Each\n      centroid is the component-wise mean of the data points assigned to a\n      centroid's corresponding cluster.\n    - stats: a `k x 4` matrix containing cluster statistics.\n\n    Cluster statistics consists of the following columns:\n\n    - 0: number of data points assigned to a cluster.\n    - 1: total within-cluster sum of squared distances.\n    - 2: arithmetic mean of squared distances.\n    - 3: corrected sample standard deviation of squared distances.\n\n    Because an accumulator incrementally partitions data, one should *not*\n    expect cluster statistics to match similar statistics had provided data been\n    analyzed via a batch algorithm. In an incremental context, data points which\n    would not be considered part of a particular cluster when analyzed via a\n    batch algorithm may contribute to that cluster's statistics when analyzed\n    incrementally.\n\n    In general, the more data provided to an accumulator, the more reliable the\n    cluster statistics.\n\n    Parameters\n    ----------\n    k: integer|ndarray\n        Number of clusters or a `k x ndims` matrix containing initial centroids.\n\n    ndims: integer (optional)\n        Number of dimensions. This argument must accompany an integer-valued\n        first argument.\n\n    options: Object (optional)\n        Function options.\n\n    options.metric: string (optional)\n        Distance metric. Must be one of the following: 'euclidean', 'cosine', or\n        'correlation'. Default: 'euclidean'.\n\n    options.init: ArrayLike (optional)\n        Centroid initialization method and associated (optional) parameters. The\n        first array element specifies the initialization method and must be one\n        of the following: 'kmeans++', 'sample', or 'forgy'. The second array\n        element specifies the number of data points to use when calculating\n        initial centroids. When performing kmeans++ initialization, the third\n        array element specifies the number of trials to perform when randomly\n        selecting candidate centroids. Typically, more trials is correlated with\n        initial centroids which lead to better clustering; however, a greater\n        number of trials increases computational overhead. Default: ['kmeans++',\n        k, 2+⌊ln(k)⌋ ].\n\n    options.normalize: boolean (optional)\n        Boolean indicating whether to normalize incoming data. This option is\n        only relevant for non-Euclidean distance metrics. If set to `true`, an\n        accumulator partitioning data based on cosine distance normalizes\n        provided data to unit Euclidean length. If set to `true`, an accumulator\n        partitioning data based on correlation distance first centers provided\n        data and then normalizes data dimensions to have zero mean and unit\n        variance. If this option is set to `false` and the metric is either\n        cosine or correlation distance, then incoming data *must* already be\n        normalized. Default: true.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy incoming data to prevent mutation\n        during normalization. Default: true.\n\n    options.seed: any (optional)\n        PRNG seed. Setting this option is useful when wanting reproducible\n        initial centroids.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    acc.predict: Function\n        Predicts centroid assignment for each data point in a provided matrix.\n        To specify an output vector, provide a 1-dimensional ndarray as the\n        first argument. Each element in the returned vector corresponds to a\n        predicted cluster index for a respective data point.\n\n    Examples\n    --------\n    > var accumulator = incrkmeans( 5, 2 );\n    > var buf = new Float64Array( 2 );\n    > var shape = [ 2 ];\n    > var strides = [ 1 ];\n    > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n    > v.set( 0, 2.0 );\n    > v.set( 1, 1.0 );\n    > out = accumulator( v );\n    > v.set( 0, -5.0 );\n    > v.set( 1, 3.14 );\n    > out = accumulator( v );\n\n","incrkurtosis":"\nincrkurtosis()\n    Returns an accumulator function which incrementally computes a corrected\n    sample excess kurtosis.\n\n    If provided a value, the accumulator function returns an updated corrected\n    sample excess kurtosis. If not provided a value, the accumulator function\n    returns the current corrected sample excess kurtosis.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrkurtosis();\n    > var v = accumulator( 2.0 )\n    null\n    > v = accumulator( 2.0 )\n    null\n    > v = accumulator( -4.0 )\n    null\n    > v = accumulator( -4.0 )\n    -6.0\n\n    See Also\n    --------\n    incrmean, incrskewness, incrstdev, incrsummary, incrvariance\n","incrmaape":"\nincrmaape()\n    Returns an accumulator function which incrementally computes the mean\n    arctangent absolute percentage error (MAAPE).\n\n    If provided input values, the accumulator function returns an updated mean\n    arctangent absolute percentage error. If not provided input values, the\n    accumulator function returns the current mean arctangent absolute percentage\n    error.\n\n    Note that, unlike the mean absolute percentage error (MAPE), the mean\n    arctangent absolute percentage error is expressed in radians on the interval\n    [0,π/2].\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmaape();\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    ~0.3218\n    > m = accumulator( 5.0, 2.0 )\n    ~0.6523\n    > m = accumulator()\n    ~0.6523\n\n    See Also\n    --------\n    incrmae, incrmape, incrmean, incrmmaape\n","incrmae":"\nincrmae()\n    Returns an accumulator function which incrementally computes the mean\n    absolute error (MAE).\n\n    If provided input values, the accumulator function returns an updated mean\n    absolute error. If not provided input values, the accumulator function\n    returns the current mean absolute error.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmae();\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    1.0\n    > m = accumulator( -5.0, 2.0 )\n    4.0\n    > m = accumulator()\n    4.0\n\n    See Also\n    --------\n    incrmape, incrme, incrmean, incrmmae\n","incrmapcorr":"\nincrmapcorr( W[, mx, my] )\n    Returns an accumulator function which incrementally computes a moving\n    sample absolute Pearson product-moment correlation coefficient.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving sample absolute correlation coefficient.\n\n    If provided values, the accumulator function returns an updated moving\n    sample absolute correlation coefficient. If not provided values, the\n    accumulator function returns the current moving sample absolute correlation\n    coefficient.\n\n    As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n    returned values are calculated from smaller sample sizes. Until the window\n    is full, each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    mx: number (optional)\n        Known mean.\n\n    my: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmapcorr( 3 );\n    > var ar = accumulator()\n    null\n    > ar = accumulator( 2.0, 1.0 )\n    0.0\n    > ar = accumulator( -5.0, 3.14 )\n    ~1.0\n    > ar = accumulator( 3.0, -1.0 )\n    ~0.925\n    > ar = accumulator( 5.0, -9.5 )\n    ~0.863\n    > ar = accumulator()\n    ~0.863\n\n    See Also\n    --------\n    incrapcorr, incrmpcorr, incrmpcorr2\n","incrmape":"\nincrmape()\n    Returns an accumulator function which incrementally computes the mean\n    absolute percentage error (MAPE).\n\n    If provided input values, the accumulator function returns an updated mean\n    absolute percentage error. If not provided input values, the accumulator\n    function returns the current mean absolute percentage error.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmape();\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    ~33.33\n    > m = accumulator( 5.0, 2.0 )\n    ~91.67\n    > m = accumulator()\n    ~91.67\n\n    See Also\n    --------\n    incrmaape, incrmae, incrmean, incrmmape\n","incrmax":"\nincrmax()\n    Returns an accumulator function which incrementally computes a maximum\n    value.\n\n    If provided a value, the accumulator function returns an updated maximum\n    value. If not provided a value, the accumulator function returns the current\n    maximum value.\n\n    If provided `NaN`, the maximum value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmax();\n    > var m = accumulator()\n    null\n    > m = accumulator( 3.14 )\n    3.14\n    > m = accumulator( -5.0 )\n    3.14\n    > m = accumulator( 10.1 )\n    10.1\n    > m = accumulator()\n    10.1\n\n    See Also\n    --------\n    incrmidrange, incrmin, incrmmax, incrrange, incrsummary\n","incrmaxabs":"\nincrmaxabs()\n    Returns an accumulator function which incrementally computes a maximum\n    absolute value.\n\n    If provided a value, the accumulator function returns an updated maximum\n    absolute value. If not provided a value, the accumulator function returns\n    the current maximum absolute value.\n\n    If provided `NaN`, the maximum value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmaxabs();\n    > var m = accumulator()\n    null\n    > m = accumulator( 3.14 )\n    3.14\n    > m = accumulator( -5.0 )\n    5.0\n    > m = accumulator( 10.1 )\n    10.1\n    > m = accumulator()\n    10.1\n\n    See Also\n    --------\n    incrmax, incrminabs, incrmmaxabs\n","incrmcovariance":"\nincrmcovariance( W[, mx, my] )\n    Returns an accumulator function which incrementally computes a moving\n    unbiased sample covariance.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving unbiased sample covariance.\n\n    If provided values, the accumulator function returns an updated moving\n    unbiased sample covariance. If not provided values, the accumulator function\n    returns the current moving unbiased sample covariance.\n\n    As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n    returned values are calculated from smaller sample sizes. Until the window\n    is full, each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    mx: number (optional)\n        Known mean.\n\n    my: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmcovariance( 3 );\n    > var v = accumulator()\n    null\n    > v = accumulator( 2.0, 1.0 )\n    0.0\n    > v = accumulator( -5.0, 3.14 )\n    ~-7.49\n    > v = accumulator( 3.0, -1.0 )\n    -8.35\n    > v = accumulator( 5.0, -9.5 )\n    -29.42\n    > v = accumulator()\n    -29.42\n\n    See Also\n    --------\n    incrcovariance, incrmpcorr, incrmvariance\n","incrmcv":"\nincrmcv( W[, mean] )\n    Returns an accumulator function which incrementally computes a moving\n    coefficient of variation (CV).\n\n    The `W` parameter defines the number of values over which to compute the\n    moving coefficient of variation.\n\n    If provided a value, the accumulator function returns an updated moving\n    coefficient of variation. If not provided a value, the accumulator function\n    returns the current moving coefficient of variation.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    mean: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmcv( 3 );\n    > var cv = accumulator()\n    null\n    > cv = accumulator( 2.0 )\n    0.0\n    > cv = accumulator( 1.0 )\n    ~0.47\n    > cv = accumulator( 3.0 )\n    0.5\n    > cv = accumulator( 7.0 )\n    ~0.83\n    > cv = accumulator()\n    ~0.83\n\n    See Also\n    --------\n    incrcv, incrmmean, incrmstdev, incrmvmr\n","incrmda":"\nincrmda()\n    Returns an accumulator function which incrementally computes the mean\n    directional accuracy (MDA).\n\n    If provided input values, the accumulator function returns an updated mean\n    directional accuracy. If not provided input values, the accumulator function\n    returns the current mean directional accuracy.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmda();\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    1.0\n    > m = accumulator( -5.0, 4.0 )\n    0.5\n    > m = accumulator()\n    0.5\n\n    See Also\n    --------\n    incrmape, incrmmda\n","incrme":"\nincrme()\n    Returns an accumulator function which incrementally computes the mean error\n    (ME).\n\n    If provided input values, the accumulator function returns an updated mean\n    error. If not provided input values, the accumulator function returns the\n    current mean error.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrme();\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    1.0\n    > m = accumulator( -5.0, 2.0 )\n    4.0\n    > m = accumulator()\n    4.0\n\n    See Also\n    --------\n    incrmae, incrmean, incrmme\n","incrmean":"\nincrmean()\n    Returns an accumulator function which incrementally computes an arithmetic\n    mean.\n\n    If provided a value, the accumulator function returns an updated mean. If\n    not provided a value, the accumulator function returns the current mean.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmean();\n    > var mu = accumulator()\n    null\n    > mu = accumulator( 2.0 )\n    2.0\n    > mu = accumulator( -5.0 )\n    -1.5\n    > mu = accumulator()\n    -1.5\n\n    See Also\n    --------\n    incrmidrange, incrmmean, incrstdev, incrsum, incrsummary, incrvariance\n","incrmeanabs":"\nincrmeanabs()\n    Returns an accumulator function which incrementally computes an arithmetic\n    mean of absolute values.\n\n    If provided a value, the accumulator function returns an updated mean. If\n    not provided a value, the accumulator function returns the current mean.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmeanabs();\n    > var mu = accumulator()\n    null\n    > mu = accumulator( 2.0 )\n    2.0\n    > mu = accumulator( -5.0 )\n    3.5\n    > mu = accumulator()\n    3.5\n\n    See Also\n    --------\n    incrmean, incrmmeanabs, incrsumabs\n","incrmeanabs2":"\nincrmeanabs2()\n    Returns an accumulator function which incrementally computes an arithmetic\n    mean of squared absolute values.\n\n    If provided a value, the accumulator function returns an updated mean. If\n    not provided a value, the accumulator function returns the current mean.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmeanabs2();\n    > var mu = accumulator()\n    null\n    > mu = accumulator( 2.0 )\n    4.0\n    > mu = accumulator( -5.0 )\n    14.5\n    > mu = accumulator()\n    14.5\n\n    See Also\n    --------\n    incrmean, incrmeanabs, incrmmeanabs2, incrsumabs2\n","incrmeanstdev":"\nincrmeanstdev( [out] )\n    Returns an accumulator function which incrementally computes an arithmetic\n    mean and corrected sample standard deviation.\n\n    If provided a value, the accumulator function returns updated accumulated\n    values. If not provided a value, the accumulator function returns the\n    current accumulated values.\n\n    If provided `NaN`, the accumulated values are equal to `NaN` for all future\n    invocations.\n\n    Parameters\n    ----------\n    out: Array|TypedArray (optional)\n        Output array.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmeanstdev();\n    > var ms = accumulator()\n    null\n    > ms = accumulator( 2.0 )\n    [ 2.0, 0.0 ]\n    > ms = accumulator( -5.0 )\n    [ -1.5, ~4.95 ]\n    > ms = accumulator( 3.0 )\n    [ 0.0, ~4.36 ]\n    > ms = accumulator( 5.0 )\n    [ 1.25, ~4.35 ]\n    > ms = accumulator()\n    [ 1.25, ~4.35 ]\n\n    See Also\n    --------\n    incrmean, incrmeanvar, incrmmeanstdev, incrstdev\n","incrmeanvar":"\nincrmeanvar( [out] )\n    Returns an accumulator function which incrementally computes an arithmetic\n    mean and unbiased sample variance.\n\n    If provided a value, the accumulator function returns updated accumulated\n    values. If not provided a value, the accumulator function returns the\n    current accumulated values.\n\n    If provided `NaN`, the accumulated values are equal to `NaN` for all future\n    invocations.\n\n    Parameters\n    ----------\n    out: Array|TypedArray (optional)\n        Output array.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmeanvar();\n    > var mv = accumulator()\n    null\n    > mv = accumulator( 2.0 )\n    [ 2.0, 0.0 ]\n    > mv = accumulator( -5.0 )\n    [ -1.5, 24.5 ]\n    > mv = accumulator( 3.0 )\n    [ 0.0, 19.0 ]\n    > mv = accumulator( 5.0 )\n    [ 1.25, ~18.92 ]\n    > mv = accumulator()\n    [ 1.25, ~18.92 ]\n\n    See Also\n    --------\n    incrmean, incrmeanstdev, incrmmeanvar, incrvariance\n","incrmgmean":"\nincrmgmean( W )\n    Returns an accumulator function which incrementally computes a moving\n    geometric mean.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving geometric mean.\n\n    If provided a value, the accumulator function returns an updated moving\n    geometric mean. If not provided a value, the accumulator function returns\n    the current moving geometric mean.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmgmean( 3 );\n    > var v = accumulator()\n    null\n    > v = accumulator( 2.0 )\n    2.0\n    > v = accumulator( 5.0 )\n    ~3.16\n    > v = accumulator( 3.0 )\n    ~3.11\n    > v = accumulator( 5.0 )\n    ~4.22\n    > v = accumulator()\n    ~4.22\n\n    See Also\n    --------\n    incrgmean, incrmhmean, incrmmean\n","incrmgrubbs":"\nincrmgrubbs( W[, options] )\n    Returns an accumulator function which incrementally performs a moving\n    Grubbs' test for detecting outliers.\n\n    Grubbs' test assumes that data is normally distributed. Accordingly, one\n    should first verify that the data can be reasonably approximated by a normal\n    distribution before applying the Grubbs' test.\n\n    The `W` parameter defines the number of values over which to perform Grubbs'\n    test. The minimum window size is 3.\n\n    If provided a value, the accumulator function returns updated test results.\n    If not provided a value, the accumulator function returns the current test\n    results.\n\n    Until provided `W` values, the accumulator function returns `null`.\n\n    The accumulator function returns an object having the following fields:\n\n    - rejected: boolean indicating whether the null hypothesis should be\n    rejected.\n    - alpha: significance level.\n    - criticalValue: critical value.\n    - statistic: test statistic.\n    - df: degrees of freedom.\n    - mean: sample mean.\n    - sd: corrected sample standard deviation.\n    - min: minimum value.\n    - max: maximum value.\n    - alt: alternative hypothesis.\n    - method: method name.\n    - print: method for pretty-printing test output.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    options: Object (optional)\n        Function options.\n\n    options.alpha: number (optional)\n        Significance level. Default: 0.05.\n\n    options.alternative: string (optional)\n        Alternative hypothesis. The option may be one of the following values:\n\n        - 'two-sided': test whether the minimum or maximum value is an outlier.\n        - 'min': test whether the minimum value is an outlier.\n        - 'max': test whether the maximum value is an outlier.\n\n        Default: 'two-sided'.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var acc = incrmgrubbs( 20 );\n    > var res = acc()\n    null\n    > for ( var i = 0; i < 200; i++ ) {\n    ...     res = acc( base.random.normal( 10.0, 5.0 ) );\n    ... };\n    > res.print()\n\n    References\n    ----------\n    - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n    Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n    of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n    - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n    Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n    00401706.1969.10490657.\n\n    See Also\n    --------\n    incrgrubbs\n","incrmhmean":"\nincrmhmean( W )\n    Returns an accumulator function which incrementally computes a moving\n    harmonic mean.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving harmonic mean.\n\n    If provided a value, the accumulator function returns an updated moving\n    harmonic mean. If not provided a value, the accumulator function returns the\n    current moving harmonic mean.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmhmean( 3 );\n    > var v = accumulator()\n    null\n    > v = accumulator( 2.0 )\n    2.0\n    > v = accumulator( 5.0 )\n    ~2.86\n    > v = accumulator( 3.0 )\n    ~2.90\n    > v = accumulator( 5.0 )\n    ~4.09\n    > v = accumulator()\n    ~4.09\n\n    See Also\n    --------\n    incrhmean, incrmgmean, incrmmean\n","incrmidrange":"\nincrmidrange()\n    Returns an accumulator function which incrementally computes a mid-range.\n\n    The mid-range is the arithmetic mean of maximum and minimum values.\n    Accordingly, the mid-range is the midpoint of the range and a measure of\n    central tendency.\n\n    If provided a value, the accumulator function returns an updated mid-range.\n    If not provided a value, the accumulator function returns the current mid-\n    range.\n\n    If provided `NaN`, the mid-range is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmidrange();\n    > var v = accumulator()\n    null\n    > v = accumulator( 3.14 )\n    3.14\n    > v = accumulator( -5.0 )\n    ~-0.93\n    > v = accumulator( 10.1 )\n    2.55\n    > v = accumulator()\n    2.55\n\n    See Also\n    --------\n    incrmean, incrmax, incrmin, incrrange, incrsummary\n","incrmin":"\nincrmin()\n    Returns an accumulator function which incrementally computes a minimum\n    value.\n\n    If provided a value, the accumulator function returns an updated minimum\n    value. If not provided a value, the accumulator function returns the current\n    minimum value.\n\n    If provided `NaN`, the minimum value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmin();\n    > var m = accumulator()\n    null\n    > m = accumulator( 3.14 )\n    3.14\n    > m = accumulator( -5.0 )\n    -5.0\n    > m = accumulator( 10.1 )\n    -5.0\n    > m = accumulator()\n    -5.0\n\n    See Also\n    --------\n    incrmax, incrmidrange, incrmmin, incrrange, incrsummary\n","incrminabs":"\nincrminabs()\n    Returns an accumulator function which incrementally computes a minimum\n    absolute value.\n\n    If provided a value, the accumulator function returns an updated minimum\n    absolute value. If not provided a value, the accumulator function returns\n    the current minimum absolute value.\n\n    If provided `NaN`, the minimum value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrminabs();\n    > var m = accumulator()\n    null\n    > m = accumulator( 3.14 )\n    3.14\n    > m = accumulator( -5.0 )\n    3.14\n    > m = accumulator( 10.1 )\n    3.14\n    > m = accumulator()\n    3.14\n\n    See Also\n    --------\n    incrmaxabs, incrmin, incrmminabs\n","incrminmax":"\nincrminmax( [out] )\n    Returns an accumulator function which incrementally computes a minimum and\n    maximum.\n\n    If provided a value, the accumulator function returns an updated minimum and\n    maximum. If not provided a value, the accumulator function returns the\n    current minimum and maximum.\n\n    If provided `NaN`, the minimum and maximum values are equal to `NaN` for all\n    future invocations.\n\n    Parameters\n    ----------\n    out: Array|TypedArray (optional)\n        Output array.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrminmax();\n    > var mm = accumulator()\n    null\n    > mm = accumulator( 2.0 )\n    [ 2.0, 2.0 ]\n    > mm = accumulator( -5.0 )\n    [ -5.0, 2.0 ]\n    > mm = accumulator( 3.0 )\n    [ -5.0, 3.0 ]\n    > mm = accumulator( 5.0 )\n    [ -5.0, 5.0 ]\n    > mm = accumulator()\n    [ -5.0, 5.0 ]\n\n    See Also\n    --------\n    incrmax, incrmin, incrmminmax, incrrange\n","incrminmaxabs":"\nincrminmaxabs( [out] )\n    Returns an accumulator function which incrementally computes a minimum and\n    maximum absolute value.\n\n    If provided a value, the accumulator function returns an updated minimum and\n    maximum. If not provided a value, the accumulator function returns the\n    current minimum and maximum.\n\n    If provided `NaN`, the minimum and maximum values are equal to `NaN` for all\n    future invocations.\n\n    Parameters\n    ----------\n    out: Array|TypedArray (optional)\n        Output array.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrminmaxabs();\n    > var mm = accumulator()\n    null\n    > mm = accumulator( 2.0 )\n    [ 2.0, 2.0 ]\n    > mm = accumulator( -5.0 )\n    [ 2.0, 5.0 ]\n    > mm = accumulator( 3.0 )\n    [ 2.0, 5.0 ]\n    > mm = accumulator( 5.0 )\n    [ 2.0, 5.0 ]\n    > mm = accumulator()\n    [ 2.0, 5.0 ]\n\n    See Also\n    --------\n    incrmaxabs, incrminabs, incrminmax, incrmminmaxabs\n","incrmmaape":"\nincrmmaape( W )\n    Returns an accumulator function which incrementally computes a moving\n    mean arctangent absolute percentage error (MAAPE).\n\n    The `W` parameter defines the number of values over which to compute the\n    moving mean arctangent absolute percentage error.\n\n    If provided input values, the accumulator function returns an updated moving\n    mean arctangent absolute percentage error. If not provided input values, the\n    accumulator function returns the current moving mean arctangent absolute\n    percentage error.\n\n    Note that, unlike the mean absolute percentage error (MAPE), the mean\n    arctangent absolute percentage error is expressed in radians on the interval\n    [0,π/2].\n\n    As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n    returned values are calculated from smaller sample sizes. Until the window\n    is full, each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmaape( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    ~0.32\n    > m = accumulator( 5.0, 2.0 )\n    ~0.65\n    > m = accumulator( 3.0, 2.0 )\n    ~0.59\n    > m = accumulator( 2.0, 5.0 )\n    ~0.66\n    > m = accumulator()\n    ~0.66\n\n    See Also\n    --------\n    incrmaape, incrmmape, incrmmpe, incrmmean\n","incrmmae":"\nincrmmae( W )\n    Returns an accumulator function which incrementally computes a moving\n    mean absolute error (MAE).\n\n    The `W` parameter defines the number of values over which to compute the\n    moving mean absolute error.\n\n    If provided a value, the accumulator function returns an updated moving\n    mean absolute error. If not provided a value, the accumulator function\n    returns the current moving mean absolute error.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmae( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    1.0\n    > m = accumulator( -5.0, 2.0 )\n    4.0\n    > m = accumulator( 3.0, 2.0 )\n    3.0\n    > m = accumulator( 5.0, -2.0 )\n    5.0\n    > m = accumulator()\n    5.0\n\n    See Also\n    --------\n    incrmae, incrmme, incrmmean\n","incrmmape":"\nincrmmape( W )\n    Returns an accumulator function which incrementally computes a moving\n    mean absolute percentage error (MAPE).\n\n    The `W` parameter defines the number of values over which to compute the\n    moving mean absolute percentage error.\n\n    If provided input values, the accumulator function returns an updated moving\n    mean absolute percentage error. If not provided input values, the\n    accumulator function returns the current moving mean absolute percentage\n    error.\n\n    As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n    returned values are calculated from smaller sample sizes. Until the window\n    is full, each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmape( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    ~33.33\n    > m = accumulator( 5.0, 2.0 )\n    ~91.67\n    > m = accumulator( 3.0, 2.0 )\n    ~77.78\n    > m = accumulator( 2.0, 5.0 )\n    ~86.67\n    > m = accumulator()\n    ~86.67\n\n    See Also\n    --------\n    incrmape, incrmmaape, incrmmpe, incrmmean\n","incrmmax":"\nincrmmax( W )\n    Returns an accumulator function which incrementally computes a moving\n    maximum value.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving maximum.\n\n    If provided a value, the accumulator function returns an updated moving\n    maximum. If not provided a value, the accumulator function returns the\n    current moving maximum.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmax( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0 )\n    2.0\n    > m = accumulator( -5.0 )\n    2.0\n    > m = accumulator( 3.0 )\n    3.0\n    > m = accumulator( 5.0 )\n    5.0\n    > m = accumulator()\n    5.0\n\n    See Also\n    --------\n    incrmax, incrmmidrange, incrmmin, incrmrange, incrmsummary\n","incrmmaxabs":"\nincrmmaxabs( W )\n    Returns an accumulator function which incrementally computes a moving\n    maximum absolute value.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving maximum absolute value.\n\n    If provided a value, the accumulator function returns an updated moving\n    maximum absolute value. If not provided a value, the accumulator function\n    returns the current moving maximum absolute value.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmaxabs( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0 )\n    2.0\n    > m = accumulator( -5.0 )\n    5.0\n    > m = accumulator( 3.0 )\n    5.0\n    > m = accumulator( 5.0 )\n    5.0\n    > m = accumulator()\n    5.0\n\n    See Also\n    --------\n    incrmaxabs, incrmmax, incrmminabs\n","incrmmda":"\nincrmmda( W )\n    Returns an accumulator function which incrementally computes a moving\n    mean directional accuracy (MDA).\n\n    The `W` parameter defines the number of values over which to compute the\n    moving mean directional accuracy.\n\n    If provided input values, the accumulator function returns an updated moving\n    mean directional accuracy. If not provided input values, the accumulator\n    function returns the current moving mean directional accuracy.\n\n    As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n    returned values are calculated from smaller sample sizes. Until the window\n    is full, each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmda( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    1.0\n    > m = accumulator( 5.0, 2.0 )\n    0.5\n    > m = accumulator( 3.0, 2.0 )\n    ~0.33\n    > m = accumulator( 4.0, 5.0 )\n    ~0.33\n    > m = accumulator()\n    ~0.33\n\n    See Also\n    --------\n    incrmda, incrmmape\n","incrmme":"\nincrmme( W )\n    Returns an accumulator function which incrementally computes a moving\n    mean error (ME).\n\n    The `W` parameter defines the number of values over which to compute the\n    moving mean error.\n\n    If provided a value, the accumulator function returns an updated moving\n    mean error. If not provided a value, the accumulator function returns the\n    current moving mean error.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmme( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    1.0\n    > m = accumulator( -5.0, 2.0 )\n    4.0\n    > m = accumulator( 3.0, 2.0 )\n    ~2.33\n    > m = accumulator( 5.0, -2.0 )\n    ~-0.33\n    > m = accumulator()\n    ~-0.33\n\n    See Also\n    --------\n    incrme, incrmmae, incrmmean\n","incrmmean":"\nincrmmean( W )\n    Returns an accumulator function which incrementally computes a moving\n    arithmetic mean.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving mean.\n\n    If provided a value, the accumulator function returns an updated moving\n    mean. If not provided a value, the accumulator function returns the current\n    moving mean.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmean( 3 );\n    > var mu = accumulator()\n    null\n    > mu = accumulator( 2.0 )\n    2.0\n    > mu = accumulator( -5.0 )\n    -1.5\n    > mu = accumulator( 3.0 )\n    0.0\n    > mu = accumulator( 5.0 )\n    1.0\n    > mu = accumulator()\n    1.0\n\n    See Also\n    --------\n    incrmean, incrmsum, incrmstdev, incrmsummary, incrmvariance\n","incrmmeanabs":"\nincrmmeanabs( W )\n    Returns an accumulator function which incrementally computes a moving\n    arithmetic mean of absolute values.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving mean.\n\n    If provided a value, the accumulator function returns an updated moving\n    mean. If not provided a value, the accumulator function returns the current\n    moving mean.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmeanabs( 3 );\n    > var mu = accumulator()\n    null\n    > mu = accumulator( 2.0 )\n    2.0\n    > mu = accumulator( -5.0 )\n    3.5\n    > mu = accumulator( 3.0 )\n    ~3.33\n    > mu = accumulator( 5.0 )\n    ~4.33\n    > mu = accumulator()\n    ~4.33\n\n    See Also\n    --------\n    incrmeanabs, incrmmean, incrmsumabs\n","incrmmeanabs2":"\nincrmmeanabs2( W )\n    Returns an accumulator function which incrementally computes a moving\n    arithmetic mean of squared absolute values.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving mean.\n\n    If provided a value, the accumulator function returns an updated moving\n    mean. If not provided a value, the accumulator function returns the current\n    moving mean.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmeanabs2( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0 )\n    4.0\n    > m = accumulator( -5.0 )\n    14.5\n    > m = accumulator( 3.0 )\n    ~12.67\n    > m = accumulator( 5.0 )\n    ~19.67\n    > m = accumulator()\n    ~19.67\n\n    See Also\n    --------\n    incrmeanabs2, incrmmeanabs, incrmsumabs2\n","incrmmeanstdev":"\nincrmmeanstdev( [out,] W )\n    Returns an accumulator function which incrementally computes a moving\n    arithmetic mean and corrected sample standard deviation.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving arithmetic mean and corrected sample standard deviation.\n\n    If provided a value, the accumulator function returns updated accumulated\n    values. If not provided a value, the accumulator function returns the\n    current moving accumulated values.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    accumulated values are calculated from smaller sample sizes. Until the\n    window is full, each returned accumulated value is calculated from all\n    provided values.\n\n    Parameters\n    ----------\n    out: Array|TypedArray (optional)\n        Output array.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmeanstdev( 3 );\n    > var v = accumulator()\n    null\n    > v = accumulator( 2.0 )\n    [ 2.0, 0.0 ]\n    > v = accumulator( -5.0 )\n    [ -1.5, ~4.95 ]\n    > v = accumulator( 3.0 )\n    [ 0.0, ~4.36 ]\n    > v = accumulator( 5.0 )\n    [ 1.0, ~5.29 ]\n    > v = accumulator()\n    [ 1.0, ~5.29 ]\n\n    See Also\n    --------\n    incrmeanstdev, incrmmean, incrmmeanvar, incrmstdev\n","incrmmeanvar":"\nincrmmeanvar( [out,] W )\n    Returns an accumulator function which incrementally computes a moving\n    arithmetic mean and unbiased sample variance.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving arithmetic mean and unbiased sample variance.\n\n    If provided a value, the accumulator function returns updated accumulated\n    values. If not provided a value, the accumulator function returns the\n    current moving accumulated values.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    accumulated values are calculated from smaller sample sizes. Until the\n    window is full, each returned accumulated value is calculated from all\n    provided values.\n\n    Parameters\n    ----------\n    out: Array|TypedArray (optional)\n        Output array.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmeanvar( 3 );\n    > var v = accumulator()\n    null\n    > v = accumulator( 2.0 )\n    [ 2.0, 0.0 ]\n    > v = accumulator( -5.0 )\n    [ -1.5, 24.5 ]\n    > v = accumulator( 3.0 )\n    [ 0.0, 19.0 ]\n    > v = accumulator( 5.0 )\n    [ 1.0, 28.0 ]\n    > v = accumulator()\n    [ 1.0, 28.0 ]\n\n    See Also\n    --------\n    incrmeanvar, incrmmean, incrmmeanstdev, incrmvariance\n","incrmmidrange":"\nincrmmidrange( W )\n    Returns an accumulator function which incrementally computes a moving mid-\n    range.\n\n    The mid-range is the arithmetic mean of maximum and minimum values.\n    Accordingly, the mid-range is the midpoint of the range and a measure of\n    central tendency.\n\n    The `W` parameter defines the number of values over which to compute\n    the moving mid-range.\n\n    If provided a value, the accumulator function returns an updated moving mid-\n    range. If not provided a value, the accumulator function returns the current\n    moving mid-range.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmidrange( 3 );\n    > var mr = accumulator()\n    null\n    > mr = accumulator( 2.0 )\n    2.0\n    > mr = accumulator( -5.0 )\n    -1.5\n    > mr = accumulator( 3.0 )\n    -1.0\n    > mr = accumulator( 5.0 )\n    0.0\n    > mr = accumulator()\n    0.0\n\n    See Also\n    --------\n    incrmmean, incrmmax, incrmmin, incrmrange\n","incrmmin":"\nincrmmin( W )\n    Returns an accumulator function which incrementally computes a moving\n    minimum value.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving minimum.\n\n    If provided a value, the accumulator function returns an updated moving\n    minimum. If not provided a value, the accumulator function returns the\n    current moving minimum.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmin( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0 )\n    2.0\n    > m = accumulator( -5.0 )\n    -5.0\n    > m = accumulator( 3.0 )\n    -5.0\n    > m = accumulator( 5.0 )\n    -5.0\n    > m = accumulator()\n    -5.0\n\n    See Also\n    --------\n    incrmin, incrmmax, incrmmidrange, incrmrange, incrmsummary\n","incrmminabs":"\nincrmminabs( W )\n    Returns an accumulator function which incrementally computes a moving\n    minimum absolute value.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving minimum absolute value.\n\n    If provided a value, the accumulator function returns an updated moving\n    minimum absolute value. If not provided a value, the accumulator function\n    returns the current moving minimum absolute value.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmminabs( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0 )\n    2.0\n    > m = accumulator( -5.0 )\n    2.0\n    > m = accumulator( 3.0 )\n    2.0\n    > m = accumulator( 5.0 )\n    3.0\n    > m = accumulator()\n    3.0\n\n    See Also\n    --------\n    incrminabs, incrmmaxabs, incrmmin\n","incrmminmax":"\nincrmminmax( [out,] W )\n    Returns an accumulator function which incrementally computes a moving\n    minimum and maximum.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving minimum and maximum.\n\n    If provided a value, the accumulator function returns an updated moving\n    minimum and maximum. If not provided a value, the accumulator function\n    returns the current moving minimum and maximum.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    minimum and maximum values are calculated from smaller sample sizes. Until\n    the window is full, each returned minimum and maximum is calculated from all\n    provided values.\n\n    Parameters\n    ----------\n    out: Array|TypedArray (optional)\n        Output array.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmminmax( 3 );\n    > var mm = accumulator()\n    null\n    > mm = accumulator( 2.0 )\n    [ 2.0, 2.0 ]\n    > mm = accumulator( -5.0 )\n    [ -5.0, 2.0 ]\n    > mm = accumulator( 3.0 )\n    [ -5.0, 3.0 ]\n    > mm = accumulator( 5.0 )\n    [ -5.0, 5.0 ]\n    > mm = accumulator()\n    [ -5.0, 5.0 ]\n\n    See Also\n    --------\n    incrmax, incrmin, incrmmax, incrminmax, incrmmin, incrmrange\n","incrmminmaxabs":"\nincrmminmaxabs( [out,] W )\n    Returns an accumulator function which incrementally computes moving minimum\n    and maximum absolute values.\n\n    The `W` parameter defines the number of values over which to compute moving\n    minimum and maximum absolute values.\n\n    If provided a value, the accumulator function returns an updated moving\n    minimum and maximum. If not provided a value, the accumulator function\n    returns the current moving minimum and maximum.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    minimum and maximum values are calculated from smaller sample sizes. Until\n    the window is full, each returned minimum and maximum is calculated from all\n    provided values.\n\n    Parameters\n    ----------\n    out: Array|TypedArray (optional)\n        Output array.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmminmaxabs( 3 );\n    > var mm = accumulator()\n    null\n    > mm = accumulator( 2.0 )\n    [ 2.0, 2.0 ]\n    > mm = accumulator( -5.0 )\n    [ 2.0, 5.0 ]\n    > mm = accumulator( 3.0 )\n    [ 2.0, 5.0 ]\n    > mm = accumulator( 5.0 )\n    [ 3.0, 5.0 ]\n    > mm = accumulator()\n    [ 3.0, 5.0 ]\n\n    See Also\n    --------\n    incrminmaxabs, incrmmax, incrmmaxabs, incrmmin, incrmminabs, incrmminmax\n","incrmmpe":"\nincrmmpe( W )\n    Returns an accumulator function which incrementally computes a moving\n    mean percentage error (MPE).\n\n    The `W` parameter defines the number of values over which to compute the\n    moving mean percentage error.\n\n    If provided input values, the accumulator function returns an updated moving\n    mean percentage error. If not provided input values, the accumulator\n    function returns the current moving mean percentage error.\n\n    As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n    returned values are calculated from smaller sample sizes. Until the window\n    is full, each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmpe( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    ~33.33\n    > m = accumulator( 5.0, 2.0 )\n    ~-58.33\n    > m = accumulator( 3.0, 2.0 )\n    ~-55.56\n    > m = accumulator( 2.0, 5.0 )\n    ~-46.67\n    > m = accumulator()\n    ~-46.67\n\n    See Also\n    --------\n    incrmmape, incrmme, incrmpe\n","incrmmse":"\nincrmmse( W )\n    Returns an accumulator function which incrementally computes a moving mean\n    squared error (MSE).\n\n    The `W` parameter defines the number of values over which to compute the\n    moving mean squared error.\n\n    If provided a value, the accumulator function returns an updated moving mean\n    squared error. If not provided a value, the accumulator function returns the\n    current moving mean squared error.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmse( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    1.0\n    > m = accumulator( -5.0, 2.0 )\n    25.0\n    > m = accumulator( 3.0, 2.0 )\n    17.0\n    > m = accumulator( 5.0, -2.0 )\n    33.0\n    > m = accumulator()\n    33.0\n\n    See Also\n    --------\n    incrmrmse, incrmrss, incrmse\n","incrmpcorr":"\nincrmpcorr( W[, mx, my] )\n    Returns an accumulator function which incrementally computes a moving\n    sample Pearson product-moment correlation coefficient.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving sample correlation coefficient.\n\n    If provided values, the accumulator function returns an updated moving\n    sample correlation coefficient. If not provided values, the accumulator\n    function returns the current moving sample correlation coefficient.\n\n    As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n    returned values are calculated from smaller sample sizes. Until the window\n    is full, each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    mx: number (optional)\n        Known mean.\n\n    my: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmpcorr( 3 );\n    > var r = accumulator()\n    null\n    > r = accumulator( 2.0, 1.0 )\n    0.0\n    > r = accumulator( -5.0, 3.14 )\n    ~-1.0\n    > r = accumulator( 3.0, -1.0 )\n    ~-0.925\n    > r = accumulator( 5.0, -9.5 )\n    ~-0.863\n    > r = accumulator()\n    ~-0.863\n\n    See Also\n    --------\n    incrmcovariance, incrmpcorrdist, incrpcorr\n","incrmpcorr2":"\nincrmpcorr2( W[, mx, my] )\n    Returns an accumulator function which incrementally computes a moving\n    squared sample Pearson product-moment correlation coefficient.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving squared sample correlation coefficient.\n\n    If provided values, the accumulator function returns an updated moving\n    squared sample correlation coefficient. If not provided values, the\n    accumulator function returns the current moving squared sample correlation\n    coefficient.\n\n    As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n    returned values are calculated from smaller sample sizes. Until the window\n    is full, each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    mx: number (optional)\n        Known mean.\n\n    my: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmpcorr2( 3 );\n    > var r2 = accumulator()\n    null\n    > r2 = accumulator( 2.0, 1.0 )\n    0.0\n    > r2 = accumulator( -5.0, 3.14 )\n    ~1.0\n    > r2 = accumulator( 3.0, -1.0 )\n    ~0.86\n    > r2 = accumulator( 5.0, -9.5 )\n    ~0.74\n    > r2 = accumulator()\n    ~0.74\n\n    See Also\n    --------\n    incrmapcorr, incrmpcorr, incrpcorr2\n","incrmpcorrdist":"\nincrmpcorrdist( W[, mx, my] )\n    Returns an accumulator function which incrementally computes a moving\n    sample Pearson product-moment correlation distance.\n\n    The correlation distance is defined as one minus the Pearson product-moment\n    correlation coefficient and, thus, resides on the interval [0,2].\n\n    However, due to limitations inherent in representing numeric values using\n    floating-point format (i.e., the inability to represent numeric values with\n    infinite precision), the correlation distance between perfectly correlated\n    random variables may *not* be `0` or `2`. In fact, the correlation distance\n    is *not* guaranteed to be strictly on the interval [0,2]. Any computed\n    distance should, however, be within floating-point roundoff error.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving sample correlation distance.\n\n    If provided values, the accumulator function returns an updated moving\n    sample correlation distance. If not provided values, the accumulator\n    function returns the current moving sample correlation distance.\n\n    As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n    returned values are calculated from smaller sample sizes. Until the window\n    is full, each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    mx: number (optional)\n        Known mean.\n\n    my: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmpcorrdist( 3 );\n    > var d = accumulator()\n    null\n    > d = accumulator( 2.0, 1.0 )\n    1.0\n    > d = accumulator( -5.0, 3.14 )\n    ~2.0\n    > d = accumulator( 3.0, -1.0 )\n    ~1.925\n    > d = accumulator( 5.0, -9.5 )\n    ~1.863\n    > d = accumulator()\n    ~1.863\n\n    See Also\n    --------\n    incrmpcorr, incrpcorrdist\n","incrmpe":"\nincrmpe()\n    Returns an accumulator function which incrementally computes the mean\n    percentage error (MPE).\n\n    If provided input values, the accumulator function returns an updated mean\n    percentage error. If not provided input values, the accumulator function\n    returns the current mean percentage error.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmpe();\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    ~33.33\n    > m = accumulator( 5.0, 2.0 )\n    ~-58.33\n    > m = accumulator()\n    ~-58.33\n\n    See Also\n    --------\n    incrmape, incrme, incrmmpe\n","incrmprod":"\nincrmprod( W )\n    Returns an accumulator function which incrementally computes a moving\n    product.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving product.\n\n    If provided a value, the accumulator function returns an updated moving\n    product. If not provided a value, the accumulator function returns the\n    current moving product.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    For accumulations over large windows or accumulations of large numbers, care\n    should be taken to prevent overflow. Note, however, that overflow/underflow\n    may be transient, as the accumulator does not use a double-precision\n    floating-point number to store an accumulated product. Instead, the\n    accumulator splits an accumulated product into a normalized fraction and\n    exponent and updates each component separately. Doing so guards against a\n    loss in precision.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmprod( 3 );\n    > var p = accumulator()\n    null\n    > p = accumulator( 2.0 )\n    2.0\n    > p = accumulator( -5.0 )\n    -10.0\n    > p = accumulator( 3.0 )\n    -30.0\n    > p = accumulator( 5.0 )\n    -75.0\n    > p = accumulator()\n    -75.0\n\n    See Also\n    --------\n    incrmsum, incrprod\n","incrmrange":"\nincrmrange( W )\n    Returns an accumulator function which incrementally computes a moving range.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving range.\n\n    If provided a value, the accumulator function returns an updated moving\n    range. If not provided a value, the accumulator function returns the current\n    moving range.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmrange( 3 );\n    > var r = accumulator()\n    null\n    > r = accumulator( 2.0 )\n    0.0\n    > r = accumulator( -5.0 )\n    7.0\n    > r = accumulator( 3.0 )\n    8.0\n    > r = accumulator( 5.0 )\n    10.0\n    > r = accumulator()\n    10.0\n\n    See Also\n    --------\n    incrmmax, incrmmean, incrmmin, incrmsummary, incrrange\n","incrmrmse":"\nincrmrmse( W )\n    Returns an accumulator function which incrementally computes a moving root\n    mean squared error (RMSE).\n\n    The `W` parameter defines the number of values over which to compute the\n    moving root mean squared error.\n\n    If provided a value, the accumulator function returns an updated moving root\n    mean squared error. If not provided a value, the accumulator function\n    returns the current moving root mean squared error.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmrmse( 3 );\n    > var r = accumulator()\n    null\n    > r = accumulator( 2.0, 3.0 )\n    1.0\n    > r = accumulator( -5.0, 2.0 )\n    5.0\n    > r = accumulator( 3.0, 2.0 )\n    ~4.12\n    > r = accumulator( 5.0, -2.0 )\n    ~5.74\n    > r = accumulator()\n    ~5.74\n\n    See Also\n    --------\n    incrmmse, incrmrss, incrrmse\n","incrmrss":"\nincrmrss( W )\n    Returns an accumulator function which incrementally computes a moving\n    residual sum of squares (RSS).\n\n    The `W` parameter defines the number of values over which to compute the\n    moving residual sum of squares.\n\n    If provided a value, the accumulator function returns an updated moving\n    residual sum of squares. If not provided a value, the accumulator function\n    returns the current moving residual sum of squares.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmrss( 3 );\n    > var r = accumulator()\n    null\n    > r = accumulator( 2.0, 3.0 )\n    1.0\n    > r = accumulator( -5.0, 2.0 )\n    50.0\n    > r = accumulator( 3.0, 2.0 )\n    51.0\n    > r = accumulator( 5.0, -2.0 )\n    99.0\n    > r = accumulator()\n    99.0\n\n    See Also\n    --------\n    incrrss, incrmmse, incrmrmse\n","incrmse":"\nincrmse()\n    Returns an accumulator function which incrementally computes the mean\n    squared error (MSE).\n\n    If provided input values, the accumulator function returns an updated mean\n    squared error. If not provided input values, the accumulator function\n    returns the current mean squared error.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmse();\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    1.0\n    > m = accumulator( -5.0, 2.0 )\n    25.0\n    > m = accumulator()\n    25.0\n\n    See Also\n    --------\n    incrmmse, incrrmse, incrrss\n","incrmstdev":"\nincrmstdev( W[, mean] )\n    Returns an accumulator function which incrementally computes a moving\n    corrected sample standard deviation.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving corrected sample standard deviation.\n\n    If provided a value, the accumulator function returns an updated moving\n    corrected sample standard deviation. If not provided a value, the\n    accumulator function returns the current moving corrected sample standard\n    deviation.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    mean: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmstdev( 3 );\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    0.0\n    > s = accumulator( -5.0 )\n    ~4.95\n    > s = accumulator( 3.0 )\n    ~4.36\n    > s = accumulator( 5.0 )\n    ~5.29\n    > s = accumulator()\n    ~5.29\n\n    See Also\n    --------\n    incrmmean, incrmsummary, incrmvariance, incrstdev\n","incrmsum":"\nincrmsum( W )\n    Returns an accumulator function which incrementally computes a moving sum.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving sum.\n\n    If provided a value, the accumulator function returns an updated moving sum.\n    If not provided a value, the accumulator function returns the current moving\n    sum.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmsum( 3 );\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    2.0\n    > s = accumulator( -5.0 )\n    -3.0\n    > s = accumulator( 3.0 )\n    0.0\n    > s = accumulator( 5.0 )\n    3.0\n    > s = accumulator()\n    3.0\n\n    See Also\n    --------\n    incrmmean, incrmsummary, incrsum\n","incrmsumabs":"\nincrmsumabs( W )\n    Returns an accumulator function which incrementally computes a moving sum of\n    absolute values.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving sum.\n\n    If provided a value, the accumulator function returns an updated moving sum.\n    If not provided a value, the accumulator function returns the current moving\n    sum.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmsumabs( 3 );\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    2.0\n    > s = accumulator( -5.0 )\n    7.0\n    > s = accumulator( 3.0 )\n    10.0\n    > s = accumulator( -5.0 )\n    13.0\n    > s = accumulator()\n    13.0\n\n    See Also\n    --------\n    incrmmeanabs, incrmsum, incrsum, incrsumabs\n","incrmsumabs2":"\nincrmsumabs2( W )\n    Returns an accumulator function which incrementally computes a moving sum of\n    squared absolute values.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving sum.\n\n    If provided a value, the accumulator function returns an updated moving sum.\n    If not provided a value, the accumulator function returns the current moving\n    sum.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmsumabs2( 3 );\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    4.0\n    > s = accumulator( -5.0 )\n    29.0\n    > s = accumulator( 3.0 )\n    38.0\n    > s = accumulator( -5.0 )\n    59.0\n    > s = accumulator()\n    59.0\n\n    See Also\n    --------\n    incrmmeanabs2, incrmsumabs, incrsumabs, incrsumabs2\n","incrmsummary":"\nincrmsummary( W )\n    Returns an accumulator function which incrementally computes a moving\n    statistical summary.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving statistical summary.\n\n    If provided a value, the accumulator function returns an updated moving\n    statistical summary. If not provided a value, the accumulator function\n    returns the current moving statistical summary.\n\n    The returned summary is an object containing the following fields:\n\n    - window: window size.\n    - sum: sum.\n    - mean: arithmetic mean.\n    - variance: unbiased sample variance.\n    - stdev: corrected sample standard deviation.\n    - min: minimum value.\n    - max: maximum value.\n    - range: range.\n    - midrange: arithmetic mean of the minimum and maximum values.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    summaries are calculated from smaller sample sizes. Until the window is\n    full, each returned summary is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmsummary( 3 );\n    > var s = accumulator()\n    {}\n    > s = accumulator( 2.0 )\n    {...}\n    > s = accumulator( -5.0 )\n    {...}\n    > s = accumulator()\n    {...}\n\n    See Also\n    --------\n    incrmmean, incrmstdev, incrmsum, incrmvariance, incrsummary\n","incrmsumprod":"\nincrmsumprod( W )\n    Returns an accumulator function which incrementally computes a moving sum of\n    products.\n\n    The `W` parameter defines the number of (x,y) pairs over which to compute\n    the moving sum of products.\n\n    If provided input values, the accumulator function returns an updated moving\n    sum. If not provided input values, the accumulator function returns the\n    current moving sum.\n\n    As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n    returned values are calculated from smaller sample sizes. Until the window\n    is full, each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmsumprod( 3 );\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0, 3.0 )\n    6.0\n    > s = accumulator( -5.0, 2.0 )\n    -4.0\n    > s = accumulator( 3.0, -2.0 )\n    -10.0\n    > s = accumulator( 5.0, 3.0 )\n    -1.0\n    > s = accumulator()\n    -1.0\n\n    See Also\n    --------\n    incrmprod, incrmsum, incrsumprod\n","incrmvariance":"\nincrmvariance( W[, mean] )\n    Returns an accumulator function which incrementally computes a moving\n    unbiased sample variance.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving unbiased sample variance.\n\n    If provided a value, the accumulator function returns an updated moving\n    unbiased sample variance. If not provided a value, the accumulator function\n    returns the current moving unbiased sample variance.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    mean: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmvariance( 3 );\n    > var s2 = accumulator()\n    null\n    > s2 = accumulator( 2.0 )\n    0.0\n    > s2 = accumulator( -5.0 )\n    24.5\n    > s2 = accumulator( 3.0 )\n    19.0\n    > s2 = accumulator( 5.0 )\n    28.0\n    > s2 = accumulator()\n    28.0\n\n    See Also\n    --------\n    incrmmean, incrmstdev, incrmsummary, incrvariance\n","incrmvmr":"\nincrmvmr( W[, mean] )\n    Returns an accumulator function which incrementally computes a moving\n    variance-to-mean (VMR).\n\n    The `W` parameter defines the number of values over which to compute the\n    moving variance-to-mean ratio.\n\n    If provided a value, the accumulator function returns an updated moving\n    variance-to-mean ratio. If not provided a value, the accumulator function\n    returns the current moving variance-to-mean ratio.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    mean: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmvmr( 3 );\n    > var F = accumulator()\n    null\n    > F = accumulator( 2.0 )\n    0.0\n    > F = accumulator( 1.0 )\n    ~0.33\n    > F = accumulator( 3.0 )\n    0.5\n    > F = accumulator( 7.0 )\n    ~2.55\n    > F = accumulator()\n    ~2.55\n\n    See Also\n    --------\n    incrmmean, incrmvariance, incrvmr\n","incrnancount":"\nincrnancount()\n    Returns an accumulator function which incrementally updates a count,\n    ignoring `NaN` values.\n\n    If provided a value, the accumulator function returns an updated count. If\n    not provided a value, the accumulator function returns the current count.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrnancount();\n    > var v = accumulator()\n    0\n    > v = accumulator( 2.0 )\n    1\n    > v = accumulator( -5.0 )\n    2\n    > v = accumulator()\n    2\n\n    See Also\n    --------\n    incrnansum\n","incrnansum":"\nincrnansum()\n    Returns an accumulator function which incrementally computes a sum, ignoring\n    `NaN` values.\n\n    If provided a value, the accumulator function returns an updated sum. If not\n    provided a value, the accumulator function returns the current sum.\n\n    For long running accumulations or accumulations of large numbers, care\n    should be taken to prevent overflow.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrnansum();\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    2.0\n    > s = accumulator( NaN )\n    2.0\n    > s = accumulator( -5.0 )\n    -3.0\n    > s = accumulator()\n    -3.0\n\n    See Also\n    --------\n    incrnansumabs, incrsum\n","incrnansumabs":"\nincrnansumabs()\n    Returns an accumulator function which incrementally computes a sum of\n    absolute values, ignoring NaN values.\n\n    If provided a value, the accumulator function returns an updated sum. If not\n    provided a value, the accumulator function returns the current sum.\n\n    For long running accumulations or accumulations of large numbers, care\n    should be taken to prevent overflow.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrnansumabs();\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    2.0\n    > s = accumulator( NaN )\n    2.0\n    > s = accumulator( -5.0 )\n    7.0\n    > s = accumulator()\n    7.0\n\n    See Also\n    --------\n    incrnansum, incrnansumabs2, incrsumabs\n","incrnansumabs2":"\nincrnansumabs2()\n    Returns an accumulator function which incrementally computes a sum of\n    squared absolute values, ignoring NaN values.\n\n    If provided a value, the accumulator function returns an updated sum. If not\n    provided a value, the accumulator function returns the current sum.\n\n    For long running accumulations or accumulations of large numbers, care\n    should be taken to prevent overflow.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrnansumabs2();\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    4.0\n    > s = accumulator( NaN )\n    4.0\n    > s = accumulator( -5.0 )\n    29.0\n    > s = accumulator()\n    29.0\n\n    See Also\n    --------\n    incrnansum, incrnansumabs, incrsumabs2\n","incrpcorr":"\nincrpcorr( [mx, my] )\n    Returns an accumulator function which incrementally computes a sample\n    Pearson product-moment correlation coefficient.\n\n    If provided values, the accumulator function returns an updated sample\n    correlation coefficient. If not provided values, the accumulator function\n    returns the current sample correlation coefficient.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    mx: number (optional)\n        Known mean.\n\n    my: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrpcorr();\n    > var r = accumulator()\n    null\n    > r = accumulator( 2.0, 1.0 )\n    0.0\n    > r = accumulator( -5.0, 3.14 )\n    ~-1.0\n    > r = accumulator()\n    ~-1.0\n\n    See Also\n    --------\n    incrcovariance, incrmpcorr, incrsummary\n","incrpcorr2":"\nincrpcorr2( [mx, my] )\n    Returns an accumulator function which incrementally computes the squared\n    sample Pearson product-moment correlation coefficient.\n\n    If provided values, the accumulator function returns an updated accumulated\n    value. If not provided values, the accumulator function returns the current\n    accumulated value.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    mx: number (optional)\n        Known mean.\n\n    my: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrpcorr2();\n    > var r2 = accumulator()\n    null\n    > r2 = accumulator( 2.0, 1.0 )\n    0.0\n    > r2 = accumulator( -5.0, 3.14 )\n    ~1.0\n    > r2 = accumulator()\n    ~1.0\n\n    See Also\n    --------\n    incrapcorr, incrmpcorr2, incrpcorr\n","incrpcorrdist":"\nincrpcorrdist( [mx, my] )\n    Returns an accumulator function which incrementally computes a sample\n    Pearson product-moment correlation distance.\n\n    The correlation distance is defined as one minus the Pearson product-moment\n    correlation coefficient and, thus, resides on the interval [0,2].\n\n    If provided values, the accumulator function returns an updated sample\n    correlation distance. If not provided values, the accumulator function\n    returns the current sample correlation distance.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    mx: number (optional)\n        Known mean.\n\n    my: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrpcorrdist();\n    > var d = accumulator()\n    null\n    > d = accumulator( 2.0, 1.0 )\n    1.0\n    > d = accumulator( -5.0, 3.14 )\n    ~2.0\n    > d = accumulator()\n    ~2.0\n\n    See Also\n    --------\n    incrcovariance, incrpcorr, incrsummary\n","incrpcorrdistmat":"\nincrpcorrdistmat( out[, means] )\n    Returns an accumulator function which incrementally computes a sample\n    Pearson product-moment correlation distance matrix.\n\n    If provided a data vector, the accumulator function returns an updated\n    sample correlation distance matrix. If not provided a data vector, the\n    accumulator function returns the current sample correlation distance matrix.\n\n    Due to limitations inherent in representing numeric values using floating-\n    point format (i.e., the inability to represent numeric values with infinite\n    precision), the correlation distance between perfectly correlated random\n    variables may *not* be `0` or `2`. In fact, the correlation distance is\n    *not* guaranteed to be strictly on the interval [0,2]. Any computed distance\n    should, however, be within floating-point roundoff error.\n\n    Parameters\n    ----------\n    out: integer|ndarray\n        Order of the correlation distance matrix or a square 2-dimensional\n        ndarray for storing the correlation distance matrix.\n\n    means: ndarray (optional)\n        Known means.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrpcorrdistmat( 2 );\n    > var out = accumulator()\n    <ndarray>\n    > var buf = new Float64Array( 2 );\n    > var shape = [ 2 ];\n    > var strides = [ 1 ];\n    > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n    > v.set( 0, 2.0 );\n    > v.set( 1, 1.0 );\n    > out = accumulator( v )\n    <ndarray>\n    > v.set( 0, -5.0 );\n    > v.set( 1, 3.14 );\n    > out = accumulator( v )\n    <ndarray>\n    > out = accumulator()\n    <ndarray>\n\n    See Also\n    --------\n    incrpcorrdist, incrpcorrmat\n","incrpcorrmat":"\nincrpcorrmat( out[, means] )\n    Returns an accumulator function which incrementally computes a sample\n    Pearson product-moment correlation matrix.\n\n    If provided a data vector, the accumulator function returns an updated\n    sample correlation matrix. If not provided a data vector, the accumulator\n    function returns the current sample correlation matrix.\n\n    Parameters\n    ----------\n    out: integer|ndarray\n        Order of the correlation matrix or a square 2-dimensional ndarray for\n        storing the correlation matrix.\n\n    means: ndarray (optional)\n        Known means.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrpcorrmat( 2 );\n    > var out = accumulator()\n    <ndarray>\n    > var buf = new Float64Array( 2 );\n    > var shape = [ 2 ];\n    > var strides = [ 1 ];\n    > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n    > v.set( 0, 2.0 );\n    > v.set( 1, 1.0 );\n    > out = accumulator( v )\n    <ndarray>\n    > v.set( 0, -5.0 );\n    > v.set( 1, 3.14 );\n    > out = accumulator( v )\n    <ndarray>\n    > out = accumulator()\n    <ndarray>\n\n    See Also\n    --------\n    incrcovmat, incrpcorr, incrpcorrdistmat\n","incrprod":"\nincrprod()\n    Returns an accumulator function which incrementally computes a product.\n\n    If provided a value, the accumulator function returns an updated product. If\n    not provided a value, the accumulator function returns the current product.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    For long running accumulations or accumulations of large numbers, care\n    should be taken to prevent overflow. Note, however, that overflow/underflow\n    may be transient, as the accumulator does not use a double-precision\n    floating-point number to store an accumulated product. Instead, the\n    accumulator splits an accumulated product into a normalized fraction and\n    exponent and updates each component separately. Doing so guards against a\n    loss in precision.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrprod();\n    > var v = accumulator()\n    null\n    > v = accumulator( 2.0 )\n    2.0\n    > v = accumulator( -5.0 )\n    -10.0\n    > v = accumulator()\n    -10.0\n\n    See Also\n    --------\n    incrmprod, incrsum, incrsummary\n","incrrange":"\nincrrange()\n    Returns an accumulator function which incrementally computes a range.\n\n    If provided a value, the accumulator function returns an updated range. If\n    not provided a value, the accumulator function returns the current range.\n\n    If provided `NaN`, the range is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrrange();\n    > var v = accumulator()\n    null\n    > v = accumulator( -2.0 )\n    0.0\n    > v = accumulator( 1.0 )\n    3.0\n    > v = accumulator( 3.0 )\n    5.0\n    > v = accumulator()\n    5.0\n\n    See Also\n    --------\n    incrmax, incrmean, incrmin, incrmrange, incrsummary\n","incrrmse":"\nincrrmse()\n    Returns an accumulator function which incrementally computes the root mean\n    squared error (RMSE).\n\n    If provided input values, the accumulator function returns an updated root\n    mean squared error. If not provided input values, the accumulator function\n    returns the current root mean squared error.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrrmse();\n    > var r = accumulator()\n    null\n    > r = accumulator( 2.0, 3.0 )\n    1.0\n    > r = accumulator( -5.0, 2.0 )\n    5.0\n    > r = accumulator()\n    5.0\n\n    See Also\n    --------\n    incrmrmse, incrmse, incrrss\n","incrrss":"\nincrrss()\n    Returns an accumulator function which incrementally computes the residual\n    sum of squares (RSS).\n\n    If provided input values, the accumulator function returns an updated\n    residual sum of squares. If not provided input values, the accumulator\n    function returns the current residual sum of squares.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrrss();\n    > var r = accumulator()\n    null\n    > r = accumulator( 2.0, 3.0 )\n    1.0\n    > r = accumulator( -5.0, 2.0 )\n    50.0\n    > r = accumulator()\n    50.0\n\n    See Also\n    --------\n    incrmrss, incrmse, incrrmse\n","incrskewness":"\nincrskewness()\n    Returns an accumulator function which incrementally computes a corrected\n    sample skewness.\n\n    If provided a value, the accumulator function returns an updated corrected\n    sample skewness. If not provided a value, the accumulator function returns\n    the current corrected sample skewness.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrskewness();\n    > var v = accumulator( 2.0 )\n    null\n    > v = accumulator( -5.0 )\n    null\n    > v = accumulator( -10.0 )\n    ~0.492\n    > v = accumulator()\n    ~0.492\n\n    See Also\n    --------\n    incrkurtosis, incrmean, incrstdev, incrsummary, incrvariance\n","incrspace":"\nincrspace( start, stop[, increment] )\n    Generates a linearly spaced numeric array using a provided increment.\n\n    If an `increment` is not provided, the default `increment` is `1`.\n\n    The output array is guaranteed to include the `start` value but does not\n    include the `stop` value.\n\n    Parameters\n    ----------\n    start: number\n        First array value.\n\n    stop: number\n        Array element bound.\n\n    increment: number (optional)\n        Increment. Default: `1`.\n\n    Returns\n    -------\n    arr: Array\n        Linearly spaced numeric array.\n\n    Examples\n    --------\n    > var arr = incrspace( 0, 11, 2 )\n    [ 0, 2, 4, 6, 8, 10 ]\n\n    See Also\n    --------\n    linspace, logspace\n","incrstdev":"\nincrstdev( [mean] )\n    Returns an accumulator function which incrementally computes a corrected\n    sample standard deviation.\n\n    If provided a value, the accumulator function returns an updated corrected\n    sample standard deviation. If not provided a value, the accumulator function\n    returns the current corrected sample standard deviation.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    mean: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrstdev();\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    0.0\n    > s = accumulator( -5.0 )\n    ~4.95\n    > s = accumulator()\n    ~4.95\n\n    See Also\n    --------\n    incrkurtosis, incrmean, incrmstdev, incrskewness, incrsummary, incrvariance\n","incrsum":"\nincrsum()\n    Returns an accumulator function which incrementally computes a sum.\n\n    If provided a value, the accumulator function returns an updated sum. If not\n    provided a value, the accumulator function returns the current sum.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    For long running accumulations or accumulations of large numbers, care\n    should be taken to prevent overflow.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrsum();\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    2.0\n    > s = accumulator( -5.0 )\n    -3.0\n    > s = accumulator()\n    -3.0\n\n    See Also\n    --------\n    incrcount, incrmean, incrmsum, incrprod, incrsummary\n","incrsumabs":"\nincrsumabs()\n    Returns an accumulator function which incrementally computes a sum of\n    absolute values.\n\n    If provided a value, the accumulator function returns an updated sum. If not\n    provided a value, the accumulator function returns the current sum.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    For long running accumulations or accumulations of large numbers, care\n    should be taken to prevent overflow.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrsumabs();\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    2.0\n    > s = accumulator( -5.0 )\n    7.0\n    > s = accumulator()\n    7.0\n\n    See Also\n    --------\n    incrmeanabs, incrmsumabs, incrsum\n","incrsumabs2":"\nincrsumabs2()\n    Returns an accumulator function which incrementally computes a sum of\n    squared absolute values.\n\n    If provided a value, the accumulator function returns an updated sum. If not\n    provided a value, the accumulator function returns the current sum.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    For long running accumulations or accumulations of large numbers, care\n    should be taken to prevent overflow.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrsumabs2();\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    4.0\n    > s = accumulator( -5.0 )\n    29.0\n    > s = accumulator()\n    29.0\n\n    See Also\n    --------\n    incrmeanabs2, incrmsumabs2, incrsumabs\n","incrsummary":"\nincrsummary()\n    Returns an accumulator function which incrementally computes a statistical\n    summary.\n\n    If provided a value, the accumulator function returns an updated summary. If\n    not provided a value, the accumulator function returns the current summary.\n\n    The returned summary is an object containing the following fields:\n\n    - count: count.\n    - max: maximum value.\n    - min: minimum value.\n    - range: range.\n    - midrange: mid-range.\n    - sum: sum.\n    - mean: arithmetic mean.\n    - variance: unbiased sample variance.\n    - stdev: corrected sample standard deviation.\n    - skewness: corrected sample skewness.\n    - kurtosis: corrected sample excess kurtosis.\n\n    For long running accumulations or accumulations of large numbers, care\n    should be taken to prevent overflow.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrsummary();\n    > var s = accumulator()\n    {}\n    > s = accumulator( 2.0 )\n    {...}\n    > s = accumulator( -5.0 )\n    {...}\n    > s = accumulator()\n    {...}\n\n    See Also\n    --------\n    incrcount, incrkurtosis, incrmax, incrmean, incrmidrange, incrmin, incrmsummary, incrrange, incrskewness, incrstdev, incrsum, incrvariance\n","incrsumprod":"\nincrsumprod()\n    Returns an accumulator function which incrementally computes a sum of\n    products.\n\n    If provided input values, the accumulator function returns an updated sum.\n    If not provided input values, the accumulator function returns the current\n    sum.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    For long running accumulations or accumulations of large numbers, care\n    should be taken to prevent overflow.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrsumprod();\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0, 3.0 )\n    6.0\n    > s = accumulator( -5.0, 2.0 )\n    -4.0\n    > s = accumulator()\n    -4.0\n\n    See Also\n    --------\n    incrmsumprod, incrprod, incrsum\n","incrvariance":"\nincrvariance( [mean] )\n    Returns an accumulator function which incrementally computes an unbiased\n    sample variance.\n\n    If provided a value, the accumulator function returns an updated unbiased\n    sample variance. If not provided a value, the accumulator function returns\n    the current unbiased sample variance.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    mean: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrvariance();\n    > var s2 = accumulator()\n    null\n    > s2 = accumulator( 2.0 )\n    0.0\n    > s2 = accumulator( -5.0 )\n    24.5\n    > s2 = accumulator()\n    24.5\n\n    See Also\n    --------\n    incrkurtosis, incrmean, incrmstdev, incrskewness, incrstdev, incrsummary\n","incrvmr":"\nincrvmr( [mean] )\n    Returns an accumulator function which incrementally computes a variance-to-\n    mean ratio (VMR).\n\n    If provided a value, the accumulator function returns an updated accumulated\n    value. If not provided a value, the accumulator function returns the current\n    accumulated value.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    mean: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrvmr();\n    > var D = accumulator()\n    null\n    > D = accumulator( 2.0 )\n    0.0\n    > D = accumulator( 1.0 )\n    ~0.33\n    > D = accumulator()\n    ~0.33\n\n    See Also\n    --------\n    incrmean, incrmvmr, incrvariance\n","incrwmean":"\nincrwmean()\n    Returns an accumulator function which incrementally computes a weighted\n    arithmetic mean.\n\n    If provided arguments, the accumulator function returns an updated weighted\n    mean. If not provided arguments, the accumulator function returns the\n    current weighted mean.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    The accumulator function accepts two arguments:\n\n    - x: value.\n    - w: weight.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrwmean();\n    > var mu = accumulator()\n    null\n    > mu = accumulator( 2.0, 1.0 )\n    2.0\n    > mu = accumulator( 2.0, 0.5 )\n    2.0\n    > mu = accumulator( 3.0, 1.5 )\n    2.5\n    > mu = accumulator()\n    2.5\n\n    See Also\n    --------\n    increwmean, incrmean, incrmmean\n","ind2sub":"\nind2sub( shape, idx[, options] )\n    Converts a linear index to an array of subscripts.\n\n    Parameters\n    ----------\n    shape: ArrayLike\n        Array shape.\n\n    idx: integer\n        Linear index.\n\n    options: Object (optional)\n        Options.\n\n    options.order: string (optional)\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran style). Default: 'row-major'.\n\n    options.mode: string (optional)\n        Specifies how to handle a linear index which exceeds array dimensions.\n        If equal to 'throw', the function throws an error when a linear index\n        exceeds array dimensions. If equal to 'normalize', the function\n        normalizes negative linear indices and throws an error when a linear\n        index exceeds array dimensions. If equal to 'wrap', the function wraps\n        around a linear index exceeding array dimensions using modulo\n        arithmetic. If equal to 'clamp', the function sets a linear index\n        exceeding array dimensions to either `0` (minimum linear index) or the\n        maximum linear index. Default: 'throw'.\n\n    Returns\n    -------\n    out: Array<integer>\n        Subscripts.\n\n    Examples\n    --------\n    > var d = [ 3, 3, 3 ];\n    > var s = ind2sub( d, 17 )\n    [ 1, 2, 2 ]\n\n\nind2sub.assign( shape, idx[, options], out )\n    Converts a linear index to an array of subscripts and assigns results to a\n    provided output array.\n\n    Parameters\n    ----------\n    shape: ArrayLike\n        Array shape.\n\n    idx: integer\n        Linear index.\n\n    options: Object (optional)\n        Options.\n\n    options.order: string (optional)\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran style). Default: 'row-major'.\n\n    options.mode: string (optional)\n        Specifies how to handle a linear index which exceeds array dimensions.\n        If equal to 'throw', the function throws an error when a linear index\n        exceeds array dimensions. If equal to 'normalize', the function\n        normalizes negative linear indices and throws an error when a linear\n        index exceeds array dimensions. If equal to 'wrap', the function wraps\n        around a linear index exceeding array dimensions using modulo\n        arithmetic. If equal to 'clamp', the function sets a linear index\n        exceeding array dimensions to either `0` (minimum linear index) or the\n        maximum linear index. Default: 'throw'.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Subscripts.\n\n    Examples\n    --------\n    > var d = [ 3, 3, 3 ];\n    > var out = [ 0, 0, 0 ];\n    > var s = ind2sub.assign( d, 17, out )\n    [ 1, 2, 2 ]\n    > var bool = ( s === out )\n    true\n\n    See Also\n    --------\n    array, ndarray, sub2ind\n","ind2sub.assign":"\nind2sub.assign( shape, idx[, options], out )\n    Converts a linear index to an array of subscripts and assigns results to a\n    provided output array.\n\n    Parameters\n    ----------\n    shape: ArrayLike\n        Array shape.\n\n    idx: integer\n        Linear index.\n\n    options: Object (optional)\n        Options.\n\n    options.order: string (optional)\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran style). Default: 'row-major'.\n\n    options.mode: string (optional)\n        Specifies how to handle a linear index which exceeds array dimensions.\n        If equal to 'throw', the function throws an error when a linear index\n        exceeds array dimensions. If equal to 'normalize', the function\n        normalizes negative linear indices and throws an error when a linear\n        index exceeds array dimensions. If equal to 'wrap', the function wraps\n        around a linear index exceeding array dimensions using modulo\n        arithmetic. If equal to 'clamp', the function sets a linear index\n        exceeding array dimensions to either `0` (minimum linear index) or the\n        maximum linear index. Default: 'throw'.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Subscripts.\n\n    Examples\n    --------\n    > var d = [ 3, 3, 3 ];\n    > var out = [ 0, 0, 0 ];\n    > var s = ind2sub.assign( d, 17, out )\n    [ 1, 2, 2 ]\n    > var bool = ( s === out )\n    true\n\n    See Also\n    --------\n    array, ndarray, sub2ind","indexOf":"\nindexOf( arr, searchElement[, fromIndex] )\n    Returns the first index at which a given element can be found.\n\n    Search is performed using *strict equality* comparison.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Array-like object.\n\n    searchElement: any\n        Element to find.\n\n    fromIndex: integer (optional)\n        Starting index (if negative, the start index is determined relative to\n        last element).\n\n    Returns\n    -------\n    out: integer\n        Index or -1.\n\n    Examples\n    --------\n    // Basic usage:\n    > var arr = [ 4, 3, 2, 1 ];\n    > var idx = indexOf( arr, 3 )\n    1\n    > arr = [ 4, 3, 2, 1 ];\n    > idx = indexOf( arr, 5 )\n    -1\n\n    // Using a `fromIndex`:\n    > arr = [ 1, 2, 3, 4, 5, 2, 6 ];\n    > idx = indexOf( arr, 2, 3 )\n    5\n\n    // `fromIndex` which exceeds `array` length:\n    > arr = [ 1, 2, 3, 4, 2, 5 ];\n    > idx = indexOf( arr, 2, 10 )\n    -1\n\n    // Negative `fromIndex`:\n    > arr = [ 1, 2, 3, 4, 5, 2, 6, 2 ];\n    > idx = indexOf( arr, 2, -4 )\n    5\n    > idx = indexOf( arr, 2, -1 )\n    7\n\n    // Negative `fromIndex` exceeding input `array` length:\n    > arr = [ 1, 2, 3, 4, 5, 2, 6 ];\n    > idx = indexOf( arr, 2, -10 )\n    1\n\n    // Array-like objects:\n    > var str = 'bebop';\n    > idx = indexOf( str, 'o' )\n    3\n\n","inherit":"\ninherit( ctor, superCtor )\n    Prototypical inheritance by replacing the prototype of one constructor with\n    the prototype of another constructor.\n\n    This function is not designed to work with ES2015/ES6 classes. For\n    ES2015/ES6 classes, use `class` with `extends`.\n\n    Parameters\n    ----------\n    ctor: Object|Function\n        Constructor which will inherit.\n\n    superCtor: Object|Function\n        Super (parent) constructor.\n\n    Returns\n    -------\n    out: Object|Function\n        Child constructor.\n\n    Examples\n    --------\n    // Create a parent constructor:\n    > function Foo() { return this; };\n    > Foo.prototype.beep = function beep() { return 'boop'; };\n\n    // Create a child constructor:\n    > function Bar() { Foo.call( this ); return this; };\n\n    // Setup inheritance:\n    > inherit( Bar, Foo );\n    > var bar = new Bar();\n    > var v = bar.beep()\n    'boop'\n\n","inheritedEnumerableProperties":"\ninheritedEnumerableProperties( value[, level] )\n    Returns an array of an object's inherited enumerable property names and\n    symbols.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    props: Array\n        List of an object's inherited enumerable properties.\n\n    Examples\n    --------\n    > var props = inheritedEnumerableProperties( {} )\n\n    See Also\n    --------\n    enumerableProperties, enumerablePropertiesIn, inheritedEnumerablePropertySymbols, inheritedKeys, inheritedNonEnumerableProperties, inheritedProperties\n","inheritedEnumerablePropertySymbols":"\ninheritedEnumerablePropertySymbols( value[, level] )\n    Returns an array of an object's inherited enumerable symbol properties.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's inherited enumerable symbol properties.\n\n    Examples\n    --------\n    > var symbols = inheritedEnumerablePropertySymbols( [] )\n\n    See Also\n    --------\n    enumerableProperties, enumerablePropertySymbols, inheritedKeys, nonEnumerablePropertySymbols, nonEnumerablePropertySymbolsIn, propertySymbols\n","inheritedKeys":"\ninheritedKeys( value[, level] )\n    Returns an array of an object's inherited enumerable property names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's inherited enumerable property names.\n\n    Examples\n    --------\n    > var keys = inheritedKeys( {} )\n\n    See Also\n    --------\n    objectKeys, keysIn, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedNonEnumerableProperties":"\ninheritedNonEnumerableProperties( value[, level] )\n    Returns an array of an object's inherited non-enumerable property names and\n    symbols.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    props: Array\n        List of an object's inherited non-enumerable properties.\n\n    Examples\n    --------\n    > var props = inheritedNonEnumerableProperties( {} )\n\n    See Also\n    --------\n    inheritedEnumerableProperties, inheritedNonEnumerablePropertyNames, inheritedNonEnumerablePropertySymbols, inheritedKeys, nonEnumerableProperties, nonEnumerablePropertiesIn, properties\n","inheritedNonEnumerablePropertyNames":"\ninheritedNonEnumerablePropertyNames( value[, level] )\n    Returns an array of an object's inherited non-enumerable property names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's inherited non-enumerable property names.\n\n    Examples\n    --------\n    > var keys = inheritedNonEnumerablePropertyNames( {} )\n\n    See Also\n    --------\n    inheritedNonEnumerableProperties, inheritedNonEnumerablePropertySymbols, objectKeys, nonEnumerablePropertyNames, nonEnumerablePropertyNamesIn, nonEnumerablePropertySymbols, propertyNames\n","inheritedNonEnumerablePropertySymbols":"\ninheritedNonEnumerablePropertySymbols( value[, level] )\n    Returns an array of an object's inherited non-enumerable symbol properties.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's inherited non-enumerable symbol properties.\n\n    Examples\n    --------\n    > var symbols = inheritedNonEnumerablePropertySymbols( [] )\n\n    See Also\n    --------\n    inheritedNonEnumerableProperties, inheritedNonEnumerablePropertyNames, nonEnumerableProperties, nonEnumerablePropertyNames, nonEnumerablePropertySymbols, nonEnumerablePropertySymbolsIn, propertySymbols\n","inheritedProperties":"\ninheritedProperties( value[, level] )\n    Returns an array of an object's inherited property names and symbols.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's inherited property names and symbols.\n\n    Examples\n    --------\n    > var symbols = inheritedProperties( [] )\n\n    See Also\n    --------\n    properties, propertiesIn, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedPropertyDescriptor":"\ninheritedPropertyDescriptor( value, property[, level] )\n    Returns a property descriptor for an object's inherited property.\n\n    If provided `null` or `undefined` or provided a non-existent property, the\n    function returns `null`.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    property: string|symbol\n        Property name.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    desc: Object|null\n        Property descriptor.\n\n    Examples\n    --------\n    > var desc = inheritedPropertyDescriptor( {}, 'toString' )\n    {...}\n\n    See Also\n    --------\n    propertyDescriptor, propertyDescriptorIn, inheritedKeys, inheritedPropertyDescriptors, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedPropertyDescriptors":"\ninheritedPropertyDescriptors( value[, level] )\n    Returns an object's inherited property descriptors.\n\n    If provided `null` or `undefined`, the function returns an empty object.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    desc: Object\n        An object's inherited property descriptors.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var desc = inheritedPropertyDescriptors( obj )\n    { 'foo': {...}, ... }\n\n    See Also\n    --------\n    propertyDescriptors, propertyDescriptorsIn, inheritedKeys, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedPropertyNames":"\ninheritedPropertyNames( value[, level] )\n    Returns an array of an object's inherited enumerable and non-enumerable\n    property names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's inherited enumerable and non-enumerable property\n        names.\n\n    Examples\n    --------\n    > var keys = inheritedPropertyNames( [] )\n\n    See Also\n    --------\n    inheritedKeys, inheritedPropertyDescriptors, inheritedPropertySymbols, propertyNames, propertyNamesIn\n","inheritedPropertySymbols":"\ninheritedPropertySymbols( value[, level] )\n    Returns an array of an object's inherited symbol properties.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's inherited symbol properties.\n\n    Examples\n    --------\n    > var symbols = inheritedPropertySymbols( [] )\n\n    See Also\n    --------\n    inheritedKeys, inheritedPropertyDescriptors, inheritedPropertyNames, propertySymbols, propertySymbolsIn\n","inheritedWritableProperties":"\ninheritedWritableProperties( value[, level] )\n    Returns an array of an object's inherited writable property names and\n    symbols.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    props: Array\n        List of an object's inherited writable properties.\n\n    Examples\n    --------\n    > var props = inheritedWritableProperties( {} )\n\n    See Also\n    --------\n    inheritedWritablePropertyNames, inheritedWritablePropertySymbols, writableProperties, writablePropertiesIn, properties\n","inheritedWritablePropertyNames":"\ninheritedWritablePropertyNames( value[, level] )\n    Returns an array of an object's inherited writable property names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's inherited writable property names.\n\n    Examples\n    --------\n    > var keys = inheritedWritablePropertyNames( {} )\n\n    See Also\n    --------\n    inheritedWritablePropertySymbols, writablePropertyNames, writablePropertyNamesIn, properties\n","inheritedWritablePropertySymbols":"\ninheritedWritablePropertySymbols( value[, level] )\n    Returns an array of an object's inherited writable symbol properties.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's inherited writable symbol properties.\n\n    Examples\n    --------\n    > var symbols = inheritedWritablePropertySymbols( [] )\n\n    See Also\n    --------\n    inheritedWritablePropertyNames, writablePropertySymbols, writablePropertySymbolsIn, properties\n","inmap":"\ninmap( collection, fcn[, thisArg] )\n    Invokes a function for each element in a collection and updates the\n    collection in-place.\n\n    When invoked, the input function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection. If provided an object, the object must be array-like\n        (excluding strings and functions).\n\n    fcn: Function\n        Function to invoke for each element in the input collection. The\n        function's return value is used to update the collection in-place.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function foo( v, i ) { return v * i; };\n    > var arr = [ 1.0, 2.0, 3.0 ];\n    > var out = inmap( arr, foo )\n    [ 0.0, 2.0, 6.0 ]\n    > var bool = ( out === arr )\n    true\n\n    See Also\n    --------\n    forEach, inmapRight, map\n","inmapAsync":"\ninmapAsync( collection, [options,] fcn, done )\n    Invokes a function once for each element in a collection and updates a\n    collection in-place.\n\n    When invoked, `fcn` is provided a maximum of four arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If `fcn`\n    accepts two arguments, `fcn` is provided:\n\n    - value\n    - next\n\n    If `fcn` accepts three arguments, `fcn` is provided:\n\n    - value\n    - index\n    - next\n\n    For every other `fcn` signature, `fcn` is provided all four arguments.\n\n    The `next` callback accepts two arguments:\n\n    - error: error argument.\n    - result: value used to update the collection.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling. Note, however, that the function\n    may have mutated an input collection during prior invocations, resulting in\n    a partially mutated collection.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function fcn( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, value*index );\n    ...     }\n    ... };\n    > function done( error, collection ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( collection === arr );\n    ...     console.log( collection );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > inmapAsync( arr, fcn, done )\n    1000\n    2500\n    3000\n    true\n    [ 0, 2500, 2000 ]\n\n    // Limit number of concurrent invocations:\n    > function fcn( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, value*index );\n    ...     }\n    ... };\n    > function done( error, collection ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( collection === arr );\n    ...     console.log( collection );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 3000, 2500, 1000 ];\n    > inmapAsync( arr, opts, fcn, done )\n    2500\n    3000\n    1000\n    true\n    [ 0, 2500, 2000 ]\n\n    // Process sequentially:\n    > function fcn( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, value*index );\n    ...     }\n    ... };\n    > function done( error, collection ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( collection === arr );\n    ...     console.log( collection );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 3000, 2500, 1000 ];\n    > inmapAsync( arr, opts, fcn, done )\n    3000\n    2500\n    1000\n    true\n    [ 0, 2500, 2000 ]\n\n\ninmapAsync.factory( [options,] fcn )\n    Returns a function which invokes a function once for each element in a\n    collection and updates a collection in-place.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function fcn( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, value*index );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = inmapAsync.factory( opts, fcn );\n    > function done( error, collection ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( collection === arr );\n    ...     console.log( collection );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    [ 0, 2500, 2000 ]\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n    [ 0, 1500, 2000 ]\n\n    See Also\n    --------\n    forEachAsync, inmapRightAsync, inmap\n","inmapAsync.factory":"\ninmapAsync.factory( [options,] fcn )\n    Returns a function which invokes a function once for each element in a\n    collection and updates a collection in-place.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function fcn( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, value*index );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = inmapAsync.factory( opts, fcn );\n    > function done( error, collection ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( collection === arr );\n    ...     console.log( collection );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    [ 0, 2500, 2000 ]\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n    [ 0, 1500, 2000 ]\n\n    See Also\n    --------\n    forEachAsync, inmapRightAsync, inmap","inmapRight":"\ninmapRight( collection, fcn[, thisArg] )\n    Invokes a function for each element in a collection and updates the\n    collection in-place, iterating from right to left.\n\n    When invoked, the input function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection. If provided an object, the object must be array-like\n        (excluding strings and functions).\n\n    fcn: Function\n        Function to invoke for each element in the input collection. The\n        function's return value is used to update the collection in-place.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function foo( v, i ) { console.log( '%s: %d', i, v ); return v * i; };\n    > var arr = [ 1.0, 2.0, 3.0 ];\n    > var out = inmapRight( arr, foo )\n    2: 3.0\n    1: 2.0\n    0: 1.0\n    [ 0.0, 2.0, 6.0 ]\n    > var bool = ( out === arr )\n    true\n\n    See Also\n    --------\n    forEachRight, inmap, mapRight\n","inmapRightAsync":"\ninmapRightAsync( collection, [options,] fcn, done )\n    Invokes a function once for each element in a collection and updates a\n    collection in-place, iterating from right to left.\n\n    When invoked, `fcn` is provided a maximum of four arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If `fcn`\n    accepts two arguments, `fcn` is provided:\n\n    - value\n    - next\n\n    If `fcn` accepts three arguments, `fcn` is provided:\n\n    - value\n    - index\n    - next\n\n    For every other `fcn` signature, `fcn` is provided all four arguments.\n\n    The `next` callback accepts two arguments:\n\n    - error: error argument.\n    - result: value used to update the collection.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling. Note, however, that the function\n    may have mutated an input collection during prior invocations, resulting in\n    a partially mutated collection.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function fcn( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, value*index );\n    ...     }\n    ... };\n    > function done( error, collection ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( collection === arr );\n    ...     console.log( collection );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > inmapRightAsync( arr, fcn, done )\n    1000\n    2500\n    3000\n    true\n    [ 0, 2500, 6000 ]\n\n    // Limit number of concurrent invocations:\n    > function fcn( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, value*index );\n    ...     }\n    ... };\n    > function done( error, collection ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( collection === arr );\n    ...     console.log( collection );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 1000, 2500, 3000 ];\n    > inmapRightAsync( arr, opts, fcn, done )\n    2500\n    3000\n    1000\n    true\n    [ 0, 2500, 6000 ]\n\n    // Process sequentially:\n    > function fcn( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, value*index );\n    ...     }\n    ... };\n    > function done( error, collection ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( collection === arr );\n    ...     console.log( collection );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 1000, 2500, 3000 ];\n    > inmapRightAsync( arr, opts, fcn, done )\n    3000\n    2500\n    1000\n    true\n    [ 0, 2500, 6000 ]\n\n\ninmapRightAsync.factory( [options,] fcn )\n    Returns a function which invokes a function once for each element in a\n    collection and updates a collection in-place, iterating from right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function fcn( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, value*index );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = inmapRightAsync.factory( opts, fcn );\n    > function done( error, collection ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( collection === arr );\n    ...     console.log( collection );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    [ 0, 2500, 6000 ]\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n    [ 0, 1500, 4000 ]\n\n    See Also\n    --------\n    forEachRightAsync, inmapAsync, inmapRight\n","inmapRightAsync.factory":"\ninmapRightAsync.factory( [options,] fcn )\n    Returns a function which invokes a function once for each element in a\n    collection and updates a collection in-place, iterating from right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function fcn( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, value*index );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = inmapRightAsync.factory( opts, fcn );\n    > function done( error, collection ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( collection === arr );\n    ...     console.log( collection );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    [ 0, 2500, 6000 ]\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n    [ 0, 1500, 4000 ]\n\n    See Also\n    --------\n    forEachRightAsync, inmapAsync, inmapRight","inspectSinkStream":"\ninspectSinkStream( [options,] clbk )\n    Returns a writable stream for inspecting stream data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to encode strings as `Buffer` objects before writing\n        data to a returned stream. Default: true.\n\n    options.defaultEncoding: string (optional)\n        Default encoding when not explicitly specified when writing data.\n        Default: 'utf8'.\n\n    clbk: Function\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: WritableStream\n        Writable stream.\n\n    Examples\n    --------\n    > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n    > var s = inspectSinkStream( clbk );\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();\n\n\ninspectSinkStream.factory( [options] )\n    Returns a function for creating writable streams for inspecting stream data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to encode strings as `Buffer` objects before writing\n        data to a returned stream. Default: true.\n\n    options.defaultEncoding: string (optional)\n        Default encoding when not explicitly specified when writing data.\n        Default: 'utf8'.\n\n    Returns\n    -------\n    createStream( clbk ): Function\n        Function for creating writable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = inspectSinkStream.factory( opts );\n    > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n    > var s = createStream( clbk );\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();\n\n\ninspectSinkStream.objectMode( [options,] clbk )\n    Returns an \"objectMode\" writable stream for inspecting stream data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to encode strings as `Buffer` objects before writing\n        data to a returned stream. Default: true.\n\n    options.defaultEncoding: string (optional)\n        Default encoding when not explicitly specified when writing data.\n        Default: 'utf8'.\n\n    clbk: Function\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: WritableStream\n        Writable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n    > var s = inspectSinkStream.objectMode( clbk );\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();\n\n    See Also\n    --------\n    debugSinkStream, inspectStream\n","inspectSinkStream.factory":"\ninspectSinkStream.factory( [options] )\n    Returns a function for creating writable streams for inspecting stream data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to encode strings as `Buffer` objects before writing\n        data to a returned stream. Default: true.\n\n    options.defaultEncoding: string (optional)\n        Default encoding when not explicitly specified when writing data.\n        Default: 'utf8'.\n\n    Returns\n    -------\n    createStream( clbk ): Function\n        Function for creating writable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = inspectSinkStream.factory( opts );\n    > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n    > var s = createStream( clbk );\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();","inspectSinkStream.objectMode":"\ninspectSinkStream.objectMode( [options,] clbk )\n    Returns an \"objectMode\" writable stream for inspecting stream data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to encode strings as `Buffer` objects before writing\n        data to a returned stream. Default: true.\n\n    options.defaultEncoding: string (optional)\n        Default encoding when not explicitly specified when writing data.\n        Default: 'utf8'.\n\n    clbk: Function\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: WritableStream\n        Writable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n    > var s = inspectSinkStream.objectMode( clbk );\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();\n\n    See Also\n    --------\n    debugSinkStream, inspectStream","inspectStream":"\ninspectStream( [options,] clbk )\n    Returns a transform stream for inspecting stream data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    clbk: Function\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream.\n\n    Examples\n    --------\n    > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n    > var s = inspectStream( clbk );\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();\n\n\ninspectStream.factory( [options] )\n    Returns a function for creating transform streams for inspecting stream\n    data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    createStream( clbk ): Function\n        Function for creating transform streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = inspectStream.factory( opts );\n    > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n    > var s = createStream( clbk );\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();\n\n\ninspectStream.objectMode( [options,] clbk )\n    Returns an \"objectMode\" transform stream for inspecting stream data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    clbk: Function\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n    > var s = inspectStream.objectMode( clbk );\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();\n\n    See Also\n    --------\n    debugStream\n","inspectStream.factory":"\ninspectStream.factory( [options] )\n    Returns a function for creating transform streams for inspecting stream\n    data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    createStream( clbk ): Function\n        Function for creating transform streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = inspectStream.factory( opts );\n    > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n    > var s = createStream( clbk );\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();","inspectStream.objectMode":"\ninspectStream.objectMode( [options,] clbk )\n    Returns an \"objectMode\" transform stream for inspecting stream data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    clbk: Function\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n    > var s = inspectStream.objectMode( clbk );\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();\n\n    See Also\n    --------\n    debugStream","instanceOf":"\ninstanceOf( value, constructor )\n    Tests whether a value has in its prototype chain a specified constructor as\n    a prototype property.\n\n    While the prototype of an `object` created using object literal notion is\n    `undefined`, the function returns `true` when provided an `object` literal\n    and the `Object` constructor. This maintains consistent behavior with the\n    `instanceof` operator.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    constructor: Function\n        Constructor.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is an instance of a provided constructor.\n\n    Examples\n    --------\n    > var bool = instanceOf( [], Array )\n    true\n    > bool = instanceOf( {}, Object )\n    true\n    > bool = instanceOf( null, Object )\n    false\n\n    See Also\n    --------\n    isPrototypeOf, constructorName, inherit, typeOf\n","INT8_MAX":"\nINT8_MAX\n    Maximum signed 8-bit integer.\n\n    The maximum signed 8-bit integer is given by `2^7 - 1`.\n\n    Examples\n    --------\n    > INT8_MAX\n    127\n\n    See Also\n    --------\n    INT8_MIN\n","INT8_MIN":"\nINT8_MIN\n    Minimum signed 8-bit integer.\n\n    The minimum signed 8-bit integer is given by `-(2^7)`.\n\n    Examples\n    --------\n    > INT8_MIN\n    -128\n\n    See Also\n    --------\n    INT8_MAX\n","INT8_NUM_BYTES":"\nINT8_NUM_BYTES\n    Size (in bytes) of an 8-bit signed integer.\n\n    Examples\n    --------\n    > INT8_NUM_BYTES\n    1\n\n    See Also\n    --------\n    INT16_NUM_BYTES, INT32_NUM_BYTES, UINT8_NUM_BYTES\n","Int8Array":"\nInt8Array()\n    A typed array constructor which returns a typed array representing an array\n    of twos-complement 8-bit signed integers in the platform byte order.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Int8Array()\n    <Int8Array>\n\n\nInt8Array( length )\n    Returns a typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( 5 )\n    <Int8Array>[ 0, 0, 0, 0, 0 ]\n\n\nInt8Array( typedarray )\n    Creates a typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n    > var arr2 = new Int8Array( arr1 )\n    <Int8Array>[ 5, 5, 5 ]\n\n\nInt8Array( obj )\n    Creates a typed array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a typed array.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 5.0, 5.0, 5.0 ];\n    > var arr2 = new Int8Array( arr1 )\n    <Int8Array>[ 5, 5, 5 ]\n\n\nInt8Array( buffer[, byteOffset[, length]] )\n    Returns a typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 4 );\n    > var arr = new Int8Array( buf, 0, 4 )\n    <Int8Array>[ 0, 0, 0, 0 ]\n\n\nInt8Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Int8Array.from( [ 1, 2 ], mapFcn )\n    <Int8Array>[ 2, 4 ]\n\n\nInt8Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Int8Array.of( 1, 2 )\n    <Int8Array>[ 1, 2 ]\n\n\nInt8Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Int8Array.BYTES_PER_ELEMENT\n    1\n\n\nInt8Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Int8Array.name\n    'Int8Array'\n\n\nInt8Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>\n\n\nInt8Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( 5 );\n    > arr.byteLength\n    5\n\n\nInt8Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Int8Array( 5 );\n    > arr.byteOffset\n    0\n\n\nInt8Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Int8Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    1\n\n\nInt8Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Int8Array( 5 );\n    > arr.length\n    5\n\n\nInt8Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Int8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2\n\n\nInt8Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true\n\n\nInt8Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false\n\n\nInt8Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Int8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3\n\n\nInt8Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2\n\n\nInt8Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3\n\n\nInt8Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2\n\n\nInt8Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '\n\n\nInt8Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true\n\n\nInt8Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2\n\n\nInt8Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'\n\n\nInt8Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true\n\n\nInt8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3\n\n\nInt8Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Int8Array>[ 2, 4, 6 ]\n\n\nInt8Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14\n\n\nInt8Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14\n\n\nInt8Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Int8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] )\n    <Int8Array>\n    > arr.reverse()\n    <Int8Array>[ 3, 2, 1 ]\n\n\nInt8Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4\n\n\nInt8Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3\n\n\nInt8Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true\n\n\nInt8Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Int8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Int8Array>[ 0, 1, 1, 2, 2 ]\n\n\nInt8Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int8Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Int8Array>[ 3, 4, 5 ]\n\n\nInt8Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'\n\n\nInt8Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'\n\n\nInt8Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Int8Array.from":"\nInt8Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Int8Array.from( [ 1, 2 ], mapFcn )\n    <Int8Array>[ 2, 4 ]","Int8Array.of":"\nInt8Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Int8Array.of( 1, 2 )\n    <Int8Array>[ 1, 2 ]","Int8Array.BYTES_PER_ELEMENT":"\nInt8Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Int8Array.BYTES_PER_ELEMENT\n    1","Int8Array.name":"\nInt8Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Int8Array.name\n    'Int8Array'","Int8Array.prototype.buffer":"\nInt8Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>","Int8Array.prototype.byteLength":"\nInt8Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( 5 );\n    > arr.byteLength\n    5","Int8Array.prototype.byteOffset":"\nInt8Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Int8Array( 5 );\n    > arr.byteOffset\n    0","Int8Array.prototype.BYTES_PER_ELEMENT":"\nInt8Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Int8Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    1","Int8Array.prototype.length":"\nInt8Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Int8Array( 5 );\n    > arr.length\n    5","Int8Array.prototype.copyWithin":"\nInt8Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Int8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2","Int8Array.prototype.entries":"\nInt8Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true","Int8Array.prototype.every":"\nInt8Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false","Int8Array.prototype.fill":"\nInt8Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Int8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3","Int8Array.prototype.filter":"\nInt8Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2","Int8Array.prototype.find":"\nInt8Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3","Int8Array.prototype.findIndex":"\nInt8Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2","Int8Array.prototype.forEach":"\nInt8Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '","Int8Array.prototype.includes":"\nInt8Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true","Int8Array.prototype.indexOf":"\nInt8Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2","Int8Array.prototype.join":"\nInt8Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'","Int8Array.prototype.keys":"\nInt8Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true","Int8Array.prototype.lastIndexOf":"\nInt8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3","Int8Array.prototype.map":"\nInt8Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Int8Array>[ 2, 4, 6 ]","Int8Array.prototype.reduce":"\nInt8Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14","Int8Array.prototype.reduceRight":"\nInt8Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14","Int8Array.prototype.reverse":"\nInt8Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Int8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] )\n    <Int8Array>\n    > arr.reverse()\n    <Int8Array>[ 3, 2, 1 ]","Int8Array.prototype.set":"\nInt8Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4","Int8Array.prototype.slice":"\nInt8Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3","Int8Array.prototype.some":"\nInt8Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true","Int8Array.prototype.sort":"\nInt8Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Int8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Int8Array>[ 0, 1, 1, 2, 2 ]","Int8Array.prototype.subarray":"\nInt8Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int8Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Int8Array>[ 3, 4, 5 ]","Int8Array.prototype.toLocaleString":"\nInt8Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'","Int8Array.prototype.toString":"\nInt8Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'","Int8Array.prototype.values":"\nInt8Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","INT16_MAX":"\nINT16_MAX\n    Maximum signed 16-bit integer.\n\n    The maximum signed 16-bit integer is given by `2^15 - 1`.\n\n    Examples\n    --------\n    > INT16_MAX\n    32767\n\n    See Also\n    --------\n    INT16_MIN\n","INT16_MIN":"\nINT16_MIN\n    Minimum signed 16-bit integer.\n\n    The minimum signed 16-bit integer is given by `-(2^15)`.\n\n    Examples\n    --------\n    > INT16_MIN\n    -32768\n\n    See Also\n    --------\n    INT16_MAX\n","INT16_NUM_BYTES":"\nINT16_NUM_BYTES\n    Size (in bytes) of a 16-bit signed integer.\n\n    Examples\n    --------\n    > INT16_NUM_BYTES\n    2\n\n    See Also\n    --------\n    INT32_NUM_BYTES, INT8_NUM_BYTES, UINT16_NUM_BYTES\n","Int16Array":"\nInt16Array()\n    A typed array constructor which returns a typed array representing an array\n    of twos-complement 16-bit signed integers in the platform byte order.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Int16Array()\n    <Int16Array>\n\n\nInt16Array( length )\n    Returns a typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( 5 )\n    <Int16Array>[ 0, 0, 0, 0, 0 ]\n\n\nInt16Array( typedarray )\n    Creates a typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n    > var arr2 = new Int16Array( arr1 )\n    <Int16Array>[ 5, 5, 5 ]\n\n\nInt16Array( obj )\n    Creates a typed array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a typed array.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 5.0, 5.0, 5.0 ];\n    > var arr2 = new Int16Array( arr1 )\n    <Int16Array>[ 5, 5, 5 ]\n\n\nInt16Array( buffer[, byteOffset[, length]] )\n    Returns a typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 8 );\n    > var arr = new Int16Array( buf, 0, 4 )\n    <Int16Array>[ 0, 0, 0, 0 ]\n\n\nInt16Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Int16Array.from( [ 1, 2 ], mapFcn )\n    <Int16Array>[ 2, 4 ]\n\n\nInt16Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Int16Array.of( 1, 2 )\n    <Int16Array>[ 1, 2 ]\n\n\nInt16Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Int16Array.BYTES_PER_ELEMENT\n    2\n\n\nInt16Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Int16Array.name\n    'Int16Array'\n\n\nInt16Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>\n\n\nInt16Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( 5 );\n    > arr.byteLength\n    10\n\n\nInt16Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Int16Array( 5 );\n    > arr.byteOffset\n    0\n\n\nInt16Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Int16Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    2\n\n\nInt16Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Int16Array( 5 );\n    > arr.length\n    5\n\n\nInt16Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Int16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2\n\n\nInt16Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true\n\n\nInt16Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false\n\n\nInt16Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Int16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3\n\n\nInt16Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2\n\n\nInt16Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3\n\n\nInt16Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2\n\n\nInt16Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '\n\n\nInt16Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true\n\n\nInt16Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2\n\n\nInt16Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'\n\n\nInt16Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true\n\n\nInt16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3\n\n\nInt16Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Int16Array>[ 2, 4, 6 ]\n\n\nInt16Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14\n\n\nInt16Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14\n\n\nInt16Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Int16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] )\n    <Int16Array>\n    > arr.reverse()\n    <Int16Array>[ 3, 2, 1 ]\n\n\nInt16Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4\n\n\nInt16Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3\n\n\nInt16Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true\n\n\nInt16Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Int16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Int16Array>[ 0, 1, 1, 2, 2 ]\n\n\nInt16Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int16Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Int16Array>[ 3, 4, 5 ]\n\n\nInt16Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'\n\n\nInt16Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'\n\n\nInt16Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Int16Array.from":"\nInt16Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Int16Array.from( [ 1, 2 ], mapFcn )\n    <Int16Array>[ 2, 4 ]","Int16Array.of":"\nInt16Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Int16Array.of( 1, 2 )\n    <Int16Array>[ 1, 2 ]","Int16Array.BYTES_PER_ELEMENT":"\nInt16Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Int16Array.BYTES_PER_ELEMENT\n    2","Int16Array.name":"\nInt16Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Int16Array.name\n    'Int16Array'","Int16Array.prototype.buffer":"\nInt16Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>","Int16Array.prototype.byteLength":"\nInt16Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( 5 );\n    > arr.byteLength\n    10","Int16Array.prototype.byteOffset":"\nInt16Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Int16Array( 5 );\n    > arr.byteOffset\n    0","Int16Array.prototype.BYTES_PER_ELEMENT":"\nInt16Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Int16Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    2","Int16Array.prototype.length":"\nInt16Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Int16Array( 5 );\n    > arr.length\n    5","Int16Array.prototype.copyWithin":"\nInt16Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Int16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2","Int16Array.prototype.entries":"\nInt16Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true","Int16Array.prototype.every":"\nInt16Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false","Int16Array.prototype.fill":"\nInt16Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Int16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3","Int16Array.prototype.filter":"\nInt16Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2","Int16Array.prototype.find":"\nInt16Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3","Int16Array.prototype.findIndex":"\nInt16Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2","Int16Array.prototype.forEach":"\nInt16Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '","Int16Array.prototype.includes":"\nInt16Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true","Int16Array.prototype.indexOf":"\nInt16Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2","Int16Array.prototype.join":"\nInt16Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'","Int16Array.prototype.keys":"\nInt16Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true","Int16Array.prototype.lastIndexOf":"\nInt16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3","Int16Array.prototype.map":"\nInt16Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Int16Array>[ 2, 4, 6 ]","Int16Array.prototype.reduce":"\nInt16Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14","Int16Array.prototype.reduceRight":"\nInt16Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14","Int16Array.prototype.reverse":"\nInt16Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Int16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] )\n    <Int16Array>\n    > arr.reverse()\n    <Int16Array>[ 3, 2, 1 ]","Int16Array.prototype.set":"\nInt16Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4","Int16Array.prototype.slice":"\nInt16Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3","Int16Array.prototype.some":"\nInt16Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true","Int16Array.prototype.sort":"\nInt16Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Int16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Int16Array>[ 0, 1, 1, 2, 2 ]","Int16Array.prototype.subarray":"\nInt16Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int16Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Int16Array>[ 3, 4, 5 ]","Int16Array.prototype.toLocaleString":"\nInt16Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'","Int16Array.prototype.toString":"\nInt16Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'","Int16Array.prototype.values":"\nInt16Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","INT32_MAX":"\nINT32_MAX\n    Maximum signed 32-bit integer.\n\n    The maximum signed 32-bit integer is given by `2^31 - 1`.\n\n    Examples\n    --------\n    > INT32_MAX\n    2147483647\n\n    See Also\n    --------\n    INT32_MIN\n","INT32_MIN":"\nINT32_MIN\n    Minimum signed 32-bit integer.\n\n    The minimum signed 32-bit integer is given by `-(2^31)`.\n\n    Examples\n    --------\n    > INT32_MIN\n    -2147483648\n\n    See Also\n    --------\n    INT32_MAX\n","INT32_NUM_BYTES":"\nINT32_NUM_BYTES\n    Size (in bytes) of a 32-bit signed integer.\n\n    Examples\n    --------\n    > INT32_NUM_BYTES\n    4\n\n    See Also\n    --------\n    INT16_NUM_BYTES, INT8_NUM_BYTES, UINT32_NUM_BYTES\n","Int32Array":"\nInt32Array()\n    A typed array constructor which returns a typed array representing an array\n    of twos-complement 32-bit signed integers in the platform byte order.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Int32Array()\n    <Int32Array>\n\n\nInt32Array( length )\n    Returns a typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( 5 )\n    <Int32Array>[ 0, 0, 0, 0, 0 ]\n\n\nInt32Array( typedarray )\n    Creates a typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int16Array( [ 5, 5, 5 ] );\n    > var arr2 = new Int32Array( arr1 )\n    <Int32Array>[ 5, 5, 5 ]\n\n\nInt32Array( obj )\n    Creates a typed array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a typed array.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 5.0, 5.0, 5.0 ];\n    > var arr2 = new Int32Array( arr1 )\n    <Int32Array>[ 5, 5, 5 ]\n\n\nInt32Array( buffer[, byteOffset[, length]] )\n    Returns a typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 16 );\n    > var arr = new Int32Array( buf, 0, 4 )\n    <Int32Array>[ 0, 0, 0, 0 ]\n\n\nInt32Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Int32Array.from( [ 1, 2 ], mapFcn )\n    <Int32Array>[ 2, 4 ]\n\n\nInt32Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Int32Array.of( 1, 2 )\n    <Int32Array>[ 1, 2 ]\n\n\nInt32Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Int32Array.BYTES_PER_ELEMENT\n    4\n\n\nInt32Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Int32Array.name\n    'Int32Array'\n\n\nInt32Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>\n\n\nInt32Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( 5 );\n    > arr.byteLength\n    20\n\n\nInt32Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Int32Array( 5 );\n    > arr.byteOffset\n    0\n\n\nInt32Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Int32Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    4\n\n\nInt32Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Int32Array( 5 );\n    > arr.length\n    5\n\n\nInt32Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Int32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2\n\n\nInt32Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true\n\n\nInt32Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false\n\n\nInt32Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Int32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3\n\n\nInt32Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2\n\n\nInt32Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3\n\n\nInt32Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2\n\n\nInt32Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '\n\n\nInt32Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true\n\n\nInt32Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2\n\n\nInt32Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'\n\n\nInt32Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true\n\n\nInt32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3\n\n\nInt32Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Int32Array>[ 2, 4, 6 ]\n\n\nInt32Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14\n\n\nInt32Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14\n\n\nInt32Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Int32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] )\n    <Int32Array>\n    > arr.reverse()\n    <Int32Array>[ 3, 2, 1 ]\n\n\nInt32Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4\n\n\nInt32Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3\n\n\nInt32Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true\n\n\nInt32Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Int32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Int32Array>[ 0, 1, 1, 2, 2 ]\n\n\nInt32Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int32Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Int32Array>[ 3, 4, 5 ]\n\n\nInt32Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'\n\n\nInt32Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'\n\n\nInt32Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Int32Array.from":"\nInt32Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Int32Array.from( [ 1, 2 ], mapFcn )\n    <Int32Array>[ 2, 4 ]","Int32Array.of":"\nInt32Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Int32Array.of( 1, 2 )\n    <Int32Array>[ 1, 2 ]","Int32Array.BYTES_PER_ELEMENT":"\nInt32Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Int32Array.BYTES_PER_ELEMENT\n    4","Int32Array.name":"\nInt32Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Int32Array.name\n    'Int32Array'","Int32Array.prototype.buffer":"\nInt32Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>","Int32Array.prototype.byteLength":"\nInt32Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( 5 );\n    > arr.byteLength\n    20","Int32Array.prototype.byteOffset":"\nInt32Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Int32Array( 5 );\n    > arr.byteOffset\n    0","Int32Array.prototype.BYTES_PER_ELEMENT":"\nInt32Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Int32Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    4","Int32Array.prototype.length":"\nInt32Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Int32Array( 5 );\n    > arr.length\n    5","Int32Array.prototype.copyWithin":"\nInt32Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Int32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2","Int32Array.prototype.entries":"\nInt32Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true","Int32Array.prototype.every":"\nInt32Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false","Int32Array.prototype.fill":"\nInt32Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Int32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3","Int32Array.prototype.filter":"\nInt32Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2","Int32Array.prototype.find":"\nInt32Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3","Int32Array.prototype.findIndex":"\nInt32Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2","Int32Array.prototype.forEach":"\nInt32Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '","Int32Array.prototype.includes":"\nInt32Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true","Int32Array.prototype.indexOf":"\nInt32Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2","Int32Array.prototype.join":"\nInt32Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'","Int32Array.prototype.keys":"\nInt32Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true","Int32Array.prototype.lastIndexOf":"\nInt32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3","Int32Array.prototype.map":"\nInt32Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Int32Array>[ 2, 4, 6 ]","Int32Array.prototype.reduce":"\nInt32Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14","Int32Array.prototype.reduceRight":"\nInt32Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14","Int32Array.prototype.reverse":"\nInt32Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Int32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] )\n    <Int32Array>\n    > arr.reverse()\n    <Int32Array>[ 3, 2, 1 ]","Int32Array.prototype.set":"\nInt32Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4","Int32Array.prototype.slice":"\nInt32Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3","Int32Array.prototype.some":"\nInt32Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true","Int32Array.prototype.sort":"\nInt32Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Int32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Int32Array>[ 0, 1, 1, 2, 2 ]","Int32Array.prototype.subarray":"\nInt32Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int32Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Int32Array>[ 3, 4, 5 ]","Int32Array.prototype.toLocaleString":"\nInt32Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'","Int32Array.prototype.toString":"\nInt32Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'","Int32Array.prototype.values":"\nInt32Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","IS_BIG_ENDIAN":"\nIS_BIG_ENDIAN\n    Boolean indicating if the environment is big endian.\n\n    Examples\n    --------\n    > IS_BIG_ENDIAN\n    <boolean>\n\n    See Also\n    --------\n    IS_LITTLE_ENDIAN\n","IS_BROWSER":"\nIS_BROWSER\n    Boolean indicating if the runtime is a web browser.\n\n    Examples\n    --------\n    > IS_BROWSER\n    <boolean>\n\n","IS_DARWIN":"\nIS_DARWIN\n    Boolean indicating if the current process is running on Darwin.\n\n    Examples\n    --------\n    > IS_DARWIN\n    <boolean>\n\n","IS_DOCKER":"\nIS_DOCKER\n    Boolean indicating if the process is running in a Docker container.\n\n    Examples\n    --------\n    > IS_DOCKER\n    <boolean>\n\n","IS_ELECTRON":"\nIS_ELECTRON\n    Boolean indicating if the runtime is Electron.\n\n    Examples\n    --------\n    > IS_ELECTRON\n    <boolean>\n\n    See Also\n    --------\n    IS_ELECTRON_MAIN, IS_ELECTRON_RENDERER\n","IS_ELECTRON_MAIN":"\nIS_ELECTRON_MAIN\n    Boolean indicating if the runtime is the main Electron process.\n\n    Examples\n    --------\n    > IS_ELECTRON_MAIN\n    <boolean>\n\n    See Also\n    --------\n    IS_ELECTRON, IS_ELECTRON_RENDERER\n","IS_ELECTRON_RENDERER":"\nIS_ELECTRON_RENDERER\n    Boolean indicating if the runtime is the Electron renderer process.\n\n    Examples\n    --------\n    > IS_ELECTRON_RENDERER\n    <boolean>\n\n    See Also\n    --------\n    IS_ELECTRON, IS_ELECTRON_MAIN\n","IS_LITTLE_ENDIAN":"\nIS_LITTLE_ENDIAN\n    Boolean indicating if the environment is little endian.\n\n    Examples\n    --------\n    > IS_LITTLE_ENDIAN\n    <boolean>\n\n    See Also\n    --------\n    IS_BIG_ENDIAN\n","IS_MOBILE":"\nIS_MOBILE\n    Boolean indicating if the current environment is a mobile device.\n\n    Examples\n    --------\n    > IS_MOBILE\n    <boolean>\n\n","IS_NODE":"\nIS_NODE\n    Boolean indicating if the runtime is Node.js.\n\n    Examples\n    --------\n    > IS_NODE\n    <boolean>\n\n","IS_TOUCH_DEVICE":"\nIS_TOUCH_DEVICE\n    Boolean indicating if the current environment is a touch device.\n\n    Examples\n    --------\n    > IS_TOUCH_DEVICE\n    <boolean>\n\n","IS_WEB_WORKER":"\nIS_WEB_WORKER\n    Boolean indicating if the runtime is a web worker.\n\n    Examples\n    --------\n    > IS_WEB_WORKER\n    <boolean>\n\n","IS_WINDOWS":"\nIS_WINDOWS\n    Boolean indicating if the current process is running on Windows.\n\n    Examples\n    --------\n    > IS_WINDOWS\n    <boolean>\n\n","isAbsoluteHttpURI":"\nisAbsoluteHttpURI( value )\n    Tests whether a value is an absolute HTTP(S) URI.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether a value is an absolute HTTP(S) URI.\n\n    Examples\n    --------\n    > var bool = isAbsoluteHttpURI( 'http://example.com/' )\n    true\n    > bool = isAbsoluteHttpURI( 'example.com' )\n    false\n    > bool = isAbsoluteHttpURI( 'foo@bar.com' )\n    false\n\n    See Also\n    --------\n    isAbsoluteURI","isAbsolutePath":"\nisAbsolutePath( value )\n    Tests if a value is an absolute path.\n\n    Function behavior is platform-specific. On Windows platforms, the function\n    is equal to `.win32()`. On POSIX platforms, the function is equal to\n    `.posix()`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is an absolute path.\n\n    Examples\n    --------\n    // Windows environment:\n    > var bool = isAbsolutePath( 'C:\\\\foo\\\\bar\\\\baz' )\n    true\n\n    // POSIX environment:\n    > bool = isAbsolutePath( '/foo/bar/baz' )\n    true\n\n\nisAbsolutePath.posix( value )\n    Tests if a value is a POSIX absolute path.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is a POSIX absolute path.\n\n    Examples\n    --------\n    > var bool = isAbsolutePath.posix( '/foo/bar/baz' )\n    true\n    > bool = isAbsolutePath.posix( 'foo/bar/baz' )\n    false\n\n\nisAbsolutePath.win32( value )\n    Tests if a value is a Windows absolute path.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is a Windows absolute path.\n\n    Examples\n    --------\n    > var bool = isAbsolutePath.win32( 'C:\\\\foo\\\\bar\\\\baz' )\n    true\n    > bool = isAbsolutePath.win32( 'foo\\\\bar\\\\baz' )\n    false\n\n    See Also\n    --------\n    isRelativePath\n","isAbsolutePath.posix":"\nisAbsolutePath.posix( value )\n    Tests if a value is a POSIX absolute path.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is a POSIX absolute path.\n\n    Examples\n    --------\n    > var bool = isAbsolutePath.posix( '/foo/bar/baz' )\n    true\n    > bool = isAbsolutePath.posix( 'foo/bar/baz' )\n    false","isAbsolutePath.win32":"\nisAbsolutePath.win32( value )\n    Tests if a value is a Windows absolute path.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is a Windows absolute path.\n\n    Examples\n    --------\n    > var bool = isAbsolutePath.win32( 'C:\\\\foo\\\\bar\\\\baz' )\n    true\n    > bool = isAbsolutePath.win32( 'foo\\\\bar\\\\baz' )\n    false\n\n    See Also\n    --------\n    isRelativePath","isAbsoluteURI":"\nisAbsoluteURI( value )\n    Tests whether a value is an absolute URI.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether a value is an absolute URI.\n\n    Examples\n    --------\n    > var bool = isAbsoluteURI( 'http://example.com/' )\n    true\n    > bool = isAbsoluteURI( 'example.com' )\n    false\n    > bool = isAbsoluteURI( 'foo@bar.com' )\n    false\n\n    See Also\n    --------\n    isRelativeURI","isAccessorArray":"\nisAccessorArray( value )\n    Tests if a value is an array-like object supporting the accessor (get/set)\n    protocol.\n\n    An accessor array is defined as an array, typed array, or an array-like\n    object (excluding strings and functions) having `get` and `set` methods for\n    accessing array elements.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an accessor array.\n\n    Examples\n    --------\n    > var bool = isAccessorArray( new Complex64Array( 10 ) )\n    true\n    > bool = isAccessorArray( [] )\n    false\n    > bool = isAccessorArray( { 'length': 0 } )\n    false\n    > bool = isAccessorArray( {} )\n    false\n\n    See Also\n    --------\n    isArrayLike, isArrayLikeObject, isCollection\n","isAccessorProperty":"\nisAccessorProperty( value, property )\n    Tests if an object's own property has an accessor descriptor.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own property has an accessor\n        descriptor.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.get = function getter() { return 'beep'; };\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isAccessorProperty( obj, 'boop' )\n    false\n    > bool = isAccessorProperty( obj, 'beep' )\n    true\n\n    See Also\n    --------\n    hasOwnProp, isAccessorPropertyIn, isDataProperty\n","isAccessorPropertyIn":"\nisAccessorPropertyIn( value, property )\n    Tests if an object's own or inherited property has an accessor descriptor.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own or inherited property has an\n        accessor descriptor.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.get = function getter() { return 'beep'; };\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isAccessorPropertyIn( obj, 'boop' )\n    false\n    > bool = isAccessorPropertyIn( obj, 'beep' )\n    true\n\n    See Also\n    --------\n    hasProp, isAccessorProperty, isDataPropertyIn\n","isAlphagram":"\nisAlphagram( value )\n    Tests if a value is an alphagram (i.e., a sequence of characters arranged in\n    alphabetical order).\n\n    The function first checks that an input value is a string before validating\n    that the value is an alphagram. For non-string values, the function returns\n    `false`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an alphagram.\n\n    Examples\n    --------\n    > var out = isAlphagram( 'beep' )\n    true\n    > out = isAlphagram( 'zba' )\n    false\n    > out = isAlphagram( '' )\n    false\n\n    See Also\n    --------\n    isAnagram\n","isAlphaNumeric":"\nisAlphaNumeric( str )\n    Tests whether a string contains only alphanumeric characters.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a string contains only alphanumeric\n        characters.\n\n    Examples\n    --------\n    > var bool = isAlphaNumeric( 'abc0123456789' )\n    true\n    > bool = isAlphaNumeric( 'abcdef' )\n    true\n    > bool = isAlphaNumeric( '0xff' )\n    true\n    > bool = isAlphaNumeric( '' )\n    false\n\n    See Also\n    --------\n    isDigitString\n","isAnagram":"\nisAnagram( str, value )\n    Tests if a value is an anagram.\n\n    Parameters\n    ----------\n    str: string\n        Comparison string.\n\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an anagram.\n\n    Examples\n    --------\n    > var str1 = 'I am a weakish speller';\n    > var str2 = 'William Shakespeare';\n    > var bool = isAnagram( str1, str2 )\n    true\n    > bool = isAnagram( 'bat', 'tabba' )\n    false\n\n    See Also\n    --------\n    isAlphagram\n","isArguments":"\nisArguments( value )\n    Tests if a value is an arguments object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an arguments object.\n\n    Examples\n    --------\n    > function foo() { return arguments; };\n    > var bool = isArguments( foo() )\n    true\n    > bool = isArguments( [] )\n    false\n\n","isArray":"\nisArray( value )\n    Tests if a value is an array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array.\n\n    Examples\n    --------\n    > var bool = isArray( [] )\n    true\n    > bool = isArray( {} )\n    false\n\n    See Also\n    --------\n    isArrayLike\n","isArrayArray":"\nisArrayArray( value )\n    Tests if a value is an array of arrays.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array of arrays.\n\n    Examples\n    --------\n    > var bool = isArrayArray( [ [], [] ] )\n    true\n    > bool = isArrayArray( [ {}, {} ] )\n    false\n    > bool = isArrayArray( [] )\n    false\n\n","isArrayBuffer":"\nisArrayBuffer( value )\n    Tests if a value is an ArrayBuffer.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an ArrayBuffer.\n\n    Examples\n    --------\n    > var bool = isArrayBuffer( new ArrayBuffer( 10 ) )\n    true\n    > bool = isArrayBuffer( [] )\n    false\n\n    See Also\n    --------\n    isSharedArrayBuffer, isTypedArray\n","isArrayBufferView":"\nisArrayBufferView( value )\n    Tests if a value is a `ArrayBuffer` view.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a `ArrayBuffer` view.\n\n    Examples\n    --------\n    > var bool = isArrayBufferView( new Int8Array() )\n    true\n    > bool = isArrayBufferView( [] )\n    false\n\n    See Also\n    --------\n    isDataView, isTypedArray\n","isArrayLength":"\nisArrayLength( value )\n    Tests if a value is a valid array length.\n\n    A valid length property for an Array instance is any integer value on the\n    interval [0, 2^32-1].\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a valid array length.\n\n    Examples\n    --------\n    > var bool = isArrayLength( 5 )\n    true\n    > bool = isArrayLength( 2.0e200 )\n    false\n    > bool = isArrayLength( -3.14 )\n    false\n    > bool = isArrayLength( null )\n    false\n\n    See Also\n    --------\n    isArray\n","isArrayLike":"\nisArrayLike( value )\n    Tests if a value is array-like.\n\n    If provided a string, the function returns `true`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is array-like.\n\n    Examples\n    --------\n    > var bool = isArrayLike( [] )\n    true\n    > bool = isArrayLike( { 'length': 10 } )\n    true\n    > bool = isArrayLike( 'beep' )\n    true\n    > bool = isArrayLike( null )\n    false\n\n    See Also\n    --------\n    isArray, isArrayLikeObject, isCollection\n","isArrayLikeObject":"\nisArrayLikeObject( value )\n    Tests if a value is an array-like object.\n\n    If provided a string, the function returns `false`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object.\n\n    Examples\n    --------\n    > var bool = isArrayLikeObject( [] )\n    true\n    > bool = isArrayLikeObject( { 'length': 10 } )\n    true\n    > bool = isArrayLikeObject( 'beep' )\n    false\n\n    See Also\n    --------\n    isArray, isArrayLike, isCollection\n","isArrowFunction":"\nisArrowFunction( value )\n    Tests if a value is an arrow function.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an arrow function.\n\n    Examples\n    --------\n    > function beep() {};\n    > var bool = isArrowFunction( beep )\n    false\n    > bool = isArrowFunction( {} )\n    false\n\n","isASCII":"\nisASCII( str )\n    Tests whether a character belongs to the ASCII character set and whether\n    this is true for all characters in a provided string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a string has all ASCII characters.\n\n    Examples\n    --------\n    > var str = 'beep boop';\n    > var bool = isASCII( str )\n    true\n    > bool = isASCII( fromCodePoint( 130 ) )\n    false\n\n    See Also\n    --------\n    isString\n","isBetween":"\nisBetween( value, a, b[, left, right] )\n    Tests if a value is between two values.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    a: any\n        Left comparison value.\n\n    b: any\n        Right comparison value.\n\n    left: string (optional)\n        Indicates whether the left comparison value is inclusive. Must be either\n        'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n    right: string (optional)\n        Indicates whether the right comparison value is inclusive. Must be\n        either 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is between two values.\n\n    Examples\n    --------\n    > var bool = isBetween( 3.14, 3.0, 4.0 )\n    true\n    > bool = isBetween( 3.0, 3.0, 4.0 )\n    true\n    > bool = isBetween( 4.0, 3.0, 4.0 )\n    true\n    > bool = isBetween( 3.0, 3.14, 4.0 )\n    false\n    > bool = isBetween( 3.14, 3.14, 4.0, 'open', 'closed' )\n    false\n    > bool = isBetween( 3.14, 3.0, 3.14, 'closed', 'open' )\n    false\n\n    See Also\n    --------\n    isBetweenArray\n","isBetweenArray":"\nisBetweenArray( value, a, b[, left, right] )\n    Tests if a value is an array-like object where every element is between two\n    values.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    a: any\n        Left comparison value.\n\n    b: any\n        Right comparison value.\n\n    left: string (optional)\n        Indicates whether the left comparison value is inclusive. Must be either\n        'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n    right: string (optional)\n        Indicates whether the right comparison value is inclusive. Must be\n        either 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object where every\n        element is between two values.\n\n    Examples\n    --------\n    > var arr = [ 3.0, 3.14, 4.0 ];\n    > var bool = isBetweenArray( arr, 3.0, 4.0 )\n    true\n    > bool = isBetweenArray( arr, 3.14, 4.0 )\n    false\n    > bool = isBetweenArray( arr, 3.0, 3.14 )\n    false\n    > bool = isBetweenArray( arr, 3.0, 4.0, 'open', 'closed' )\n    false\n    > bool = isBetweenArray( arr, 3.0, 4.0, 'closed', 'open' )\n    false\n\n    See Also\n    --------\n    isBetween\n","isBigInt":"\nisBigInt( value )\n    Tests if a value is a BigInt.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a BigInt.\n\n    Examples\n    --------\n    > var bool = isBigInt( BigInt( '1' ) )\n    true\n    > bool = isBigInt( Object( BigInt( '1' ) ) )\n    true\n    > bool = isBigInt( {} )\n    false\n    > bool = isBigInt( null )\n    false\n    > bool = isBigInt( true )\n    false\n\n","isBigInt64Array":"\nisBigInt64Array( value )\n    Tests if a value is a BigInt64Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a BigInt64Array.\n\n    Examples\n    --------\n    > var bool = isBigInt64Array( new BigInt64Array( 10 ) )\n    true\n    > bool = isBigInt64Array( [] )\n    false\n\n    See Also\n    --------\n    isBigUint64Array\n","isBigUint64Array":"\nisBigUint64Array( value )\n    Tests if a value is a BigUint64Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a BigUint64Array.\n\n    Examples\n    --------\n    > var bool = isBigUint64Array( new BigUint64Array( 10 ) )\n    true\n    > bool = isBigUint64Array( [] )\n    false\n\n    See Also\n    --------\n    isBigInt64Array\n","isBinaryString":"\nisBinaryString( value )\n    Tests if a value is a binary string.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a binary string.\n\n    Examples\n    --------\n    > var bool = isBinaryString( '1000101' )\n    true\n    > bool = isBinaryString( 'beep' )\n    false\n    > bool = isBinaryString( '' )\n    false\n\n    See Also\n    --------\n    isString\n","isBlankString":"\nisBlankString( value )\n    Tests if a value is a blank string (i.e., an empty string or a string\n    consisting only of whitespace characters).\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a blank string.\n\n    Examples\n    --------\n    > var bool = isBlankString( '   ' )\n    true\n    > bool = isBlankString( 'beep' )\n    false\n    > bool = isBlankString( null )\n    false\n\n    See Also\n    --------\n    isString, isEmptyString\n","isBoolean":"\nisBoolean( value )\n    Tests if a value is a boolean.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a boolean.\n\n    Examples\n    --------\n    > var bool = isBoolean( false )\n    true\n    > bool = isBoolean( new Boolean( false ) )\n    true\n\n\nisBoolean.isPrimitive( value )\n    Tests if a value is a boolean primitive.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a boolean primitive.\n\n    Examples\n    --------\n    > var bool = isBoolean.isPrimitive( true )\n    true\n    > bool = isBoolean.isPrimitive( false )\n    true\n    > bool = isBoolean.isPrimitive( new Boolean( true ) )\n    false\n\n\nisBoolean.isObject( value )\n    Tests if a value is a boolean object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a boolean object.\n\n    Examples\n    --------\n    > var bool = isBoolean.isObject( true )\n    false\n    > bool = isBoolean.isObject( new Boolean( false ) )\n    true\n\n","isBoolean.isPrimitive":"\nisBoolean.isPrimitive( value )\n    Tests if a value is a boolean primitive.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a boolean primitive.\n\n    Examples\n    --------\n    > var bool = isBoolean.isPrimitive( true )\n    true\n    > bool = isBoolean.isPrimitive( false )\n    true\n    > bool = isBoolean.isPrimitive( new Boolean( true ) )\n    false","isBoolean.isObject":"\nisBoolean.isObject( value )\n    Tests if a value is a boolean object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a boolean object.\n\n    Examples\n    --------\n    > var bool = isBoolean.isObject( true )\n    false\n    > bool = isBoolean.isObject( new Boolean( false ) )\n    true","isBooleanArray":"\nisBooleanArray( value )\n    Tests if a value is an array-like object of booleans.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object of booleans.\n\n    Examples\n    --------\n    > var bool = isBooleanArray( [ true, false, true ] )\n    true\n    > bool = isBooleanArray( [ true, 'abc', false ] )\n    false\n\n\nisBooleanArray.primitives( value )\n    Tests if a value is an array-like object containing only boolean primitives.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        boolean primitives.\n\n    Examples\n    --------\n    > var bool = isBooleanArray.primitives( [ true, false ] )\n    true\n    > bool = isBooleanArray.primitives( [ false, new Boolean( true ) ] )\n    false\n\n\nisBooleanArray.objects( value )\n    Tests if a value is an array-like object containing only Boolean objects.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        Boolean objects.\n\n    Examples\n    --------\n    > var bool = isBooleanArray.objects( [ new Boolean( false ), true ] )\n    false\n    > bool = isBooleanArray.objects( [ new Boolean( false ), new Boolean( true ) ] )\n    true\n\n","isBooleanArray.primitives":"\nisBooleanArray.primitives( value )\n    Tests if a value is an array-like object containing only boolean primitives.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        boolean primitives.\n\n    Examples\n    --------\n    > var bool = isBooleanArray.primitives( [ true, false ] )\n    true\n    > bool = isBooleanArray.primitives( [ false, new Boolean( true ) ] )\n    false","isBooleanArray.objects":"\nisBooleanArray.objects( value )\n    Tests if a value is an array-like object containing only Boolean objects.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        Boolean objects.\n\n    Examples\n    --------\n    > var bool = isBooleanArray.objects( [ new Boolean( false ), true ] )\n    false\n    > bool = isBooleanArray.objects( [ new Boolean( false ), new Boolean( true ) ] )\n    true","isBoxedPrimitive":"\nisBoxedPrimitive( value )\n    Tests if a value is a JavaScript boxed primitive.\n\n    Boxed primitive objects can be created with one of the following:\n\n    - new Boolean()\n    - new Number()\n    - new String()\n    - Object( Symbol() ) (ES6/ES2015)\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a JavaScript boxed primitive.\n\n    Examples\n    --------\n    > var bool = isBoxedPrimitive( new Boolean( false ) )\n    true\n    > bool = isBoxedPrimitive( true )\n    false\n\n    See Also\n    --------\n    isPrimitive\n","isBuffer":"\nisBuffer( value )\n    Tests if a value is a Buffer instance.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Buffer instance.\n\n    Examples\n    --------\n    > var bool = isBuffer( new Buffer( 'beep' ) )\n    true\n    > bool = isBuffer( new Buffer( [ 1, 2, 3, 4 ] ) )\n    true\n    > bool = isBuffer( {} )\n    false\n    > bool = isBuffer( [] )\n    false\n\n","isCamelcase":"\nisCamelcase( value )\n    Tests if a value is a camelcase string.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a camelcase string.\n\n    Examples\n    --------\n    > var bool = isCamelcase( 'helloWorld' )\n    true\n    > bool = isCamelcase( 'hello world' )\n    false\n\n    See Also\n    --------\n    isString, isConstantcase","isCapitalized":"\nisCapitalized( value )\n    Tests if a value is a string having an uppercase first character.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a string with an uppercase first\n        character.\n\n    Examples\n    --------\n    > var bool = isCapitalized( 'Hello' )\n    true\n    > bool = isCapitalized( 'world' )\n    false\n\n    See Also\n    --------\n    isString\n","isCentrosymmetricMatrix":"\nisCentrosymmetricMatrix( value )\n    Tests if a value is a matrix which is symmetric about its center.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a centrosymmetric matrix.\n\n    Examples\n    --------\n    > var buf = [ 2, 1, 1, 2 ];\n    > var M = ndarray( 'generic', buf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n    > var bool = isCentrosymmetricMatrix( M )\n    true\n    > bool = isCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isCentrosymmetricMatrix( 3.14 )\n    false\n    > bool = isCentrosymmetricMatrix( {} )\n    false\n\n    See Also\n    --------\n    isMatrixLike, isSquareMatrix, isSymmetricMatrix\n","isCircular":"\nisCircular( value )\n    Tests if an object-like value contains a circular reference.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an object-like value contains a circular\n        reference.\n\n    Examples\n    --------\n    > var obj = { 'beep': 'boop' };\n    > obj.self = obj;\n    > var bool = isCircular( obj )\n    true\n    > bool = isCircular( {} )\n    false\n    > bool = isCircular( null )\n    false\n\n    See Also\n    --------\n    isCircularArray, isCircularPlainObject\n","isCircularArray":"\nisCircularArray( value )\n    Tests if a value is an array containing a circular reference.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array containing a\n        circular reference.\n\n    Examples\n    --------\n    > var arr = [ 1, 2, 3 ];\n    > arr.push( arr );\n    > var bool = isCircularArray( arr )\n    true\n    > bool = isCircularArray( [] )\n    false\n    > bool = isCircularArray( null )\n    false\n\n    See Also\n    --------\n    isCircular, isCircularPlainObject\n","isCircularPlainObject":"\nisCircularPlainObject( value )\n    Tests if a value is a plain object containing a circular reference.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a plain object containing a\n        circular reference.\n\n    Examples\n    --------\n    > var obj = { 'beep': 'boop' };\n    > obj.self = obj;\n    > var bool = isCircularPlainObject( obj )\n    true\n    > bool = isCircularPlainObject( {} )\n    false\n    > bool = isCircularPlainObject( null )\n    false\n\n    See Also\n    --------\n    isCircular, isCircularArray\n","isClass":"\nisClass( value )\n    Tests if a value is a class.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a class.\n\n    Examples\n    --------\n    > var bool = isClass( class Person {} )\n    true\n    > bool = isClass( function Person() {} )\n    false\n    > bool = isClass( {} )\n    false\n    > bool = isClass( null )\n    false\n    > bool = isClass( true )\n    false\n","isCollection":"\nisCollection( value )\n    Tests if a value is a collection.\n\n    A collection is defined as an array, typed array, or an array-like object\n    (excluding strings and functions).\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a collection.\n\n    Examples\n    --------\n    > var bool = isCollection( [] )\n    true\n    > bool = isCollection( { 'length': 0 } )\n    true\n    > bool = isCollection( {} )\n    false\n\n    See Also\n    --------\n    isArrayLike, isArrayLikeObject\n","isComplex":"\nisComplex( value )\n    Tests if a value is a 64-bit or 128-bit complex number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 64-bit or 128-bit complex\n        number.\n\n    Examples\n    --------\n    > var bool = isComplex( new Complex64( 2.0, 2.0 ) )\n    true\n    > bool = isComplex( new Complex128( 3.0, 1.0 ) )\n    true\n    > bool = isComplex( 3.14 )\n    false\n    > bool = isComplex( {} )\n    false\n\n    See Also\n    --------\n    isComplex64, isComplex128\n","isComplex64":"\nisComplex64( value )\n    Tests if a value is a 64-bit complex number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 64-bit complex number.\n\n    Examples\n    --------\n    > var bool = isComplex64( new Complex64( 2.0, 2.0 ) )\n    true\n    > bool = isComplex64( new Complex128( 3.0, 1.0 ) )\n    false\n    > bool = isComplex64( 3.14 )\n    false\n    > bool = isComplex64( {} )\n    false\n\n    See Also\n    --------\n    isComplex, isComplex128\n","isComplex64Array":"\nisComplex64Array( value )\n    Tests if a value is a Complex64Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Complex64Array.\n\n    Examples\n    --------\n    > var bool = isComplex64Array( new Complex64Array( 10 ) )\n    true\n    > bool = isComplex64Array( [] )\n    false\n\n    See Also\n    --------\n    isComplex, isComplex64, isComplex128Array, isComplexTypedArray\n","isComplex64MatrixLike":"\nisComplex64MatrixLike( value )\n    Tests if a value is a 2-dimensional ndarray-like object containing single-\n    precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 2-dimensional ndarray-like\n        object containing single-precision complex floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n    > M.ndims = 2;\n    > M.shape = [ 2, 2 ];\n    > M.strides = [ 2, 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'complex64';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isComplex64MatrixLike( M )\n    true\n    > bool = isComplex64MatrixLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isComplex64MatrixLike( 3.14 )\n    false\n    > bool = isComplex64MatrixLike( {} )\n    false\n\n    See Also\n    --------\n    isComplex128MatrixLike, isndarrayLike, isMatrixLike\n","isComplex64ndarrayLike":"\nisComplex64ndarrayLike( value )\n    Tests if a value is an ndarray-like object containing single-precision\n    complex floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an ndarray-like object containing\n        single-precision complex floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n    > M.ndims = 2;\n    > M.shape = [ 2, 2 ];\n    > M.strides = [ 2, 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'complex64';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isComplex64ndarrayLike( M )\n    true\n    > bool = isComplex64ndarrayLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isComplex64ndarrayLike( 3.14 )\n    false\n    > bool = isComplex64ndarrayLike( {} )\n    false\n\n    See Also\n    --------\n    isComplex128ndarrayLike, isndarrayLike\n","isComplex64VectorLike":"\nisComplex64VectorLike( value )\n    Tests if a value is a 1-dimensional ndarray-like object containing single-\n    precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 1-dimensional ndarray-like\n        object containing single-precision complex floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n    > M.ndims = 1;\n    > M.shape = [ 4 ];\n    > M.strides = [ 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'complex64';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isComplex64VectorLike( M )\n    true\n    > bool = isComplex64VectorLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isComplex64VectorLike( 3.14 )\n    false\n    > bool = isComplex64VectorLike( {} )\n    false\n\n    See Also\n    --------\n    isComplex128VectorLike, isndarrayLike, isVectorLike\n","isComplex128":"\nisComplex128( value )\n    Tests if a value is a 128-bit complex number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 128-bit complex number.\n\n    Examples\n    --------\n    > var bool = isComplex128( new Complex128( 3.0, 1.0 ) )\n    true\n    > bool = isComplex128( new Complex64( 2.0, 2.0 ) )\n    false\n    > bool = isComplex128( 3.14 )\n    false\n    > bool = isComplex128( {} )\n    false\n\n    See Also\n    --------\n    isComplex, isComplex64\n","isComplex128Array":"\nisComplex128Array( value )\n    Tests if a value is a Complex128Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Complex128Array.\n\n    Examples\n    --------\n    > var bool = isComplex128Array( new Complex128Array( 10 ) )\n    true\n    > bool = isComplex128Array( [] )\n    false\n\n    See Also\n    --------\n    isComplex, isComplex128, isComplex64Array, isComplexTypedArray\n","isComplex128MatrixLike":"\nisComplex128MatrixLike( value )\n    Tests if a value is a 2-dimensional ndarray-like object containing double-\n    precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 2-dimensional ndarray-like\n        object containing double-precision complex floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n    > M.ndims = 2;\n    > M.shape = [ 2, 2 ];\n    > M.strides = [ 2, 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'complex128';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isComplex128MatrixLike( M )\n    true\n    > bool = isComplex128MatrixLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isComplex128MatrixLike( 3.14 )\n    false\n    > bool = isComplex128MatrixLike( {} )\n    false\n\n    See Also\n    --------\n    isComplex64MatrixLike, isndarrayLike, isMatrixLike\n","isComplex128ndarrayLike":"\nisComplex128ndarrayLike( value )\n    Tests if a value is an ndarray-like object containing double-precision\n    complex floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an ndarray-like object containing\n        double-precision complex floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n    > M.ndims = 2;\n    > M.shape = [ 2, 2 ];\n    > M.strides = [ 2, 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'complex128';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isComplex128ndarrayLike( M )\n    true\n    > bool = isComplex128ndarrayLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isComplex128ndarrayLike( 3.14 )\n    false\n    > bool = isComplex128ndarrayLike( {} )\n    false\n\n    See Also\n    --------\n    isComplex64ndarrayLike, isndarrayLike\n","isComplex128VectorLike":"\nisComplex128VectorLike( value )\n    Tests if a value is a 1-dimensional ndarray-like object containing double-\n    precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 1-dimensional ndarray-like\n        object containing double-precision complex floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n    > M.ndims = 1;\n    > M.shape = [ 4 ];\n    > M.strides = [ 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'complex128';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isComplex128VectorLike( M )\n    true\n    > bool = isComplex128VectorLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isComplex128VectorLike( 3.14 )\n    false\n    > bool = isComplex128VectorLike( {} )\n    false\n\n    See Also\n    --------\n    isComplex64VectorLike, isndarrayLike, isVectorLike\n","isComplexLike":"\nisComplexLike( value )\n    Tests if a value is a complex number-like object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a complex number-like object.\n\n    Examples\n    --------\n    > var bool = isComplexLike( new Complex64( 2.0, 2.0 ) )\n    true\n    > bool = isComplexLike( new Complex128( 3.0, 1.0 ) )\n    true\n    > bool = isComplexLike( 3.14 )\n    false\n    > bool = isComplexLike( {} )\n    false\n\n    See Also\n    --------\n    isComplex, isComplex64, isComplex128\n","isComplexTypedArray":"\nisComplexTypedArray( value )\n    Tests if a value is a complex typed array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a complex typed array.\n\n    Examples\n    --------\n    > var bool = isComplexTypedArray( new Complex64Array( 10 ) )\n    true\n\n    See Also\n    --------\n    isComplex, isComplex64Array, isComplex128Array\n","isComplexTypedArrayLike":"\nisComplexTypedArrayLike( value )\n    Tests if a value is complex-typed-array-like.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is complex-typed-array-like.\n\n    Examples\n    --------\n    > var bool = isComplexTypedArrayLike( new Complex128Array() )\n    true\n    > bool = isComplexTypedArrayLike({\n    ...    'length': 10,\n    ...    'byteOffset': 0,\n    ...    'byteLength': 10,\n    ...    'BYTES_PER_ELEMENT': 4,\n    ...    'get': function get() {},\n    ...    'set': function set() {}\n    ... })\n    true\n\n    See Also\n    --------\n    isComplexLike, isComplexTypedArray, isComplex64Array, isComplex128Array\n","isComposite":"\nisComposite( value )\n    Tests if a value is a composite number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a composite number.\n\n    Examples\n    --------\n    > var bool = isComposite( 4.0 )\n    true\n    > bool = isComposite( new Number( 4.0 ) )\n    true\n    > bool = isComposite( 3.14 )\n    false\n    > bool = isComposite( -4.0 )\n    false\n    > bool = isComposite( null )\n    false\n\n\nisComposite.isPrimitive( value )\n    Tests if a value is a number primitive which is a composite number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a\n        composite number.\n\n    Examples\n    --------\n    > var bool = isComposite.isPrimitive( 4.0 )\n    true\n    > bool = isComposite.isPrimitive( new Number( 4.0 ) )\n    false\n\n\nisComposite.isObject( value )\n    Tests if a value is a number object having a value which is a composite\n    number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a composite number.\n\n    Examples\n    --------\n    > var bool = isComposite.isObject( 4.0 )\n    false\n    > bool = isComposite.isObject( new Number( 4.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger, isNumber, isPrime\n","isComposite.isPrimitive":"\nisComposite.isPrimitive( value )\n    Tests if a value is a number primitive which is a composite number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a\n        composite number.\n\n    Examples\n    --------\n    > var bool = isComposite.isPrimitive( 4.0 )\n    true\n    > bool = isComposite.isPrimitive( new Number( 4.0 ) )\n    false","isComposite.isObject":"\nisComposite.isObject( value )\n    Tests if a value is a number object having a value which is a composite\n    number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a composite number.\n\n    Examples\n    --------\n    > var bool = isComposite.isObject( 4.0 )\n    false\n    > bool = isComposite.isObject( new Number( 4.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger, isNumber, isPrime","isConfigurableProperty":"\nisConfigurableProperty( value, property )\n    Tests if an object's own property is configurable.\n\n    A property is configurable if the property may be deleted or its descriptor\n    may be changed.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own property is configurable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = true;\n    > desc.writable = true;\n    > desc.value = true;\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isConfigurableProperty( obj, 'boop' )\n    true\n    > bool = isConfigurableProperty( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    isConfigurablePropertyIn, isEnumerableProperty, isReadableProperty, isWritableProperty\n","isConfigurablePropertyIn":"\nisConfigurablePropertyIn( value, property )\n    Tests if an object's own or inherited property is configurable.\n\n    A property is configurable if the property may be deleted or its descriptor\n    may be changed.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own or inherited property is\n        configurable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = true;\n    > desc.writable = true;\n    > desc.value = true;\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isConfigurablePropertyIn( obj, 'boop' )\n    true\n    > bool = isConfigurablePropertyIn( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    isConfigurableProperty, isEnumerablePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isConstantcase":"\nisConstantcase( value )\n    Tests if a value is a constantcase string.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a constantcase string.\n\n    Examples\n    --------\n    > var bool = isConstantcase( 'BEEP_BOOP' )\n    true\n    > bool = isConstantcase( 'BEEP and BOOP' )\n    false\n\n    See Also\n    --------\n    isString, isCamelcase","isCubeNumber":"\nisCubeNumber( value )\n    Tests if a value is a cube number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a cube number.\n\n    Examples\n    --------\n    > var bool = isCubeNumber( 8.0 )\n    true\n    > bool = isCubeNumber( new Number( 8.0 ) )\n    true\n    > bool = isCubeNumber( 3.14 )\n    false\n    > bool = isCubeNumber( -5.0 )\n    false\n    > bool = isCubeNumber( null )\n    false\n\n\nisCubeNumber.isPrimitive( value )\n    Tests if a value is a number primitive which is a cube number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a cube\n        number.\n\n    Examples\n    --------\n    > var bool = isCubeNumber.isPrimitive( 8.0 )\n    true\n    > bool = isCubeNumber.isPrimitive( new Number( 8.0 ) )\n    false\n\n\nisCubeNumber.isObject( value )\n    Tests if a value is a number object having a value which is a cube number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a cube number.\n\n    Examples\n    --------\n    > var bool = isCubeNumber.isObject( 8.0 )\n    false\n    > bool = isCubeNumber.isObject( new Number( 8.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger, isNumber, isSquareNumber\n","isCubeNumber.isPrimitive":"\nisCubeNumber.isPrimitive( value )\n    Tests if a value is a number primitive which is a cube number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a cube\n        number.\n\n    Examples\n    --------\n    > var bool = isCubeNumber.isPrimitive( 8.0 )\n    true\n    > bool = isCubeNumber.isPrimitive( new Number( 8.0 ) )\n    false","isCubeNumber.isObject":"\nisCubeNumber.isObject( value )\n    Tests if a value is a number object having a value which is a cube number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a cube number.\n\n    Examples\n    --------\n    > var bool = isCubeNumber.isObject( 8.0 )\n    false\n    > bool = isCubeNumber.isObject( new Number( 8.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger, isNumber, isSquareNumber","isCurrentYear":"\nisCurrentYear( value )\n    Tests if a value is the current year.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether a value is the current year.\n\n    Examples\n    --------\n    > var bool = isCurrentYear( new Date() )\n    true\n    > bool = isCurrentYear( currentYear() )\n    true\n    > bool = isCurrentYear( 2021 )\n    false\n    > bool = isCurrentYear( null )\n    false\n\n","isDataProperty":"\nisDataProperty( value, property )\n    Tests if an object's own property has a data descriptor.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own property has a data descriptor.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.get = function getter() { return 'beep'; };\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isDataProperty( obj, 'boop' )\n    true\n    > bool = isDataProperty( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    hasOwnProp, isAccessorProperty, isDataPropertyIn\n","isDataPropertyIn":"\nisDataPropertyIn( value, property )\n    Tests if an object's own or inherited property has a data descriptor.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own or inherited property has a data\n        descriptor.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.get = function getter() { return 'beep'; };\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isDataPropertyIn( obj, 'boop' )\n    true\n    > bool = isDataPropertyIn( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    hasProp, isAccessorPropertyIn, isDataProperty\n","isDataView":"\nisDataView( value )\n    Tests if a value is a DataView.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a DataView.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 10 );\n    > var bool = isDataView( new DataView( buf ) )\n    true\n    > bool = isDataView( [] )\n    false\n\n    See Also\n    --------\n    isArrayBuffer, isTypedArray\n","isDateObject":"\nisDateObject( value )\n    Tests if a value is a Date object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Date object.\n\n    Examples\n    --------\n    > var bool = isDateObject( new Date() )\n    true\n    > bool = isDateObject( '2017-01-01' )\n    false\n\n","isDateObjectArray":"\nisDateObjectArray( value )\n    Tests if a value is an array-like object containing only Date objects.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if value is an array-like object containing only Date\n        objects.\n\n    Examples\n    --------\n    > var bool = isDateObjectArray( [ new Date(), new Date() ] )\n    true\n    > bool = isDateObjectArray( [ {}, {} ] )\n    false\n    > bool = isDateObjectArray( [ new Date(), '2011-01-01' ] )\n    false\n    > bool = isDateObjectArray( [] )\n    false\n\n    See Also\n    --------\n    isDateObject\n","isDigitString":"\nisDigitString( str )\n    Tests whether a string contains only numeric digits.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a string contains only numeric digits.\n\n    Examples\n    --------\n    > var bool = isDigitString( '0123456789' )\n    true\n    > bool = isDigitString( 'abcdef' )\n    false\n    > bool = isDigitString( '0xff' )\n    false\n    > bool = isDigitString( '' )\n    false\n\n    See Also\n    --------\n    isHexString, isString\n","isDomainName":"\nisDomainName( value )\n    Tests if a value is a domain name.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a domain name.\n\n    Examples\n    --------\n    > var bool = isDomainName( 'example.com' )\n    true\n    > bool = isDomainName( 'foo@bar.com' )\n    false\n","isDurationString":"\nisDurationString( value )\n    Tests if a value is a duration string.\n\n    The function validates that a value is a string. For all other types, the\n    function returns `false`.\n\n    A duration string is a string containing a sequence of time units. A time\n    unit is a non-negative integer followed by a unit identifier. The following\n    unit identifiers are supported:\n\n    - d: days.\n    - h: hours.\n    - m: minutes.\n    - s: seconds.\n    - ms: milliseconds.\n\n    For example, the string `1m3s10ms` is a duration string containing three\n    time units: `1m` (1 minute), `3s` (3 seconds), and `10ms` (10 milliseconds).\n    The string `60m` is a duration string containing a single time unit: `60m`\n    (60 minutes). Time units must be supplied in descending order of magnitude\n    (i.e., days, hours, minutes, seconds, milliseconds).\n\n    Duration strings are case insensitive. For example, the string `1M3S10MS` is\n    equivalent to `1m3s10ms`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a duration string.\n\n    Examples\n    --------\n    > var bool = isDurationString( '1d' )\n    true\n    > bool = isDurationString( '1h' )\n    true\n    > bool = isDurationString( 'beep' )\n    false\n","isEmailAddress":"\nisEmailAddress( value )\n    Tests if a value is an email address.\n\n    Validation is not rigorous. *9* RFCs relate to email addresses, and\n    accounting for all of them is a fool's errand. The function performs the\n    simplest validation; i.e., requiring at least one `@` symbol.\n\n    For rigorous validation, send a confirmation email. If the email bounces,\n    consider the email invalid.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an email address.\n\n    Examples\n    --------\n    > var bool = isEmailAddress( 'beep@boop.com' )\n    true\n    > bool = isEmailAddress( 'beep' )\n    false\n    > bool = isEmailAddress( null )\n    false\n\n","isEmptyArray":"\nisEmptyArray( value )\n    Tests if a value is an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is an empty array.\n\n    Examples\n    --------\n    > var bool = isEmptyArray( [] )\n    true\n    > bool = isEmptyArray( [ 1, 2, 3 ] )\n    false\n    > bool = isEmptyArray( {} )\n    false\n\n    See Also\n    --------\n    isArray, isEmptyArrayLikeObject, isEmptyCollection\n","isEmptyArrayLikeObject":"\nisEmptyArrayLikeObject( value )\n    Tests if a value is an empty array-like object.\n\n    If provided a string, the function returns `false`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an empty array-like object.\n\n    Examples\n    --------\n    > var bool = isEmptyArrayLikeObject( [] )\n    true\n    > bool = isEmptyArrayLikeObject( { 'length': 0 } )\n    true\n    > bool = isEmptyArrayLikeObject( '' )\n    false\n\n    See Also\n    --------\n    isArrayLikeObject, isEmptyArray, isEmptyCollection\n","isEmptyCollection":"\nisEmptyCollection( value )\n    Tests if a value is an empty collection.\n\n    A collection is defined as an array, typed array, or an array-like object\n    (excluding strings and functions).\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is an empty collection.\n\n    Examples\n    --------\n    > var bool = isEmptyCollection( [] )\n    true\n    > bool = isEmptyCollection( { 'length': 0 } )\n    true\n    > bool = isEmptyCollection( [ 1, 2, 3 ] )\n    false\n    > bool = isEmptyCollection( {} )\n    false\n\n    See Also\n    --------\n    isCollection, isEmptyArray, isEmptyArrayLikeObject\n","isEmptyObject":"\nisEmptyObject( value )\n    Tests if a value is an empty object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is an empty object.\n\n    Examples\n    --------\n    > var bool = isEmptyObject( {} )\n    true\n    > bool = isEmptyObject( { 'beep': 'boop' } )\n    false\n    > bool = isEmptyObject( [] )\n    false\n\n    See Also\n    --------\n    isObject, isPlainObject\n","isEmptyString":"\nisEmptyString( value )\n    Tests if a value is an empty string.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is an empty string.\n\n    Examples\n    --------\n    > var bool = isEmptyString( '' )\n    true\n    > bool = isEmptyString( new String( '' ) )\n    true\n    > bool = isEmptyString( 'beep' )\n    false\n    > bool = isEmptyString( [] )\n    false\n\n\nisEmptyString.isPrimitive( value )\n    Tests if a value is an empty string primitive.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an empty string primitive.\n\n    Examples\n    --------\n    > var bool = isEmptyString.isPrimitive( '' )\n    true\n    > bool = isEmptyString.isPrimitive( new String( '' ) )\n    false\n\n\nisEmptyString.isObject( value )\n    Tests if a value is an empty `String` object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an empty `String` object.\n\n    Examples\n    --------\n    > var bool = isEmptyString.isObject( new String( '' ) )\n    true\n    > bool = isEmptyString.isObject( '' )\n    false\n\n    See Also\n    --------\n    isString\n","isEmptyString.isPrimitive":"\nisEmptyString.isPrimitive( value )\n    Tests if a value is an empty string primitive.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an empty string primitive.\n\n    Examples\n    --------\n    > var bool = isEmptyString.isPrimitive( '' )\n    true\n    > bool = isEmptyString.isPrimitive( new String( '' ) )\n    false","isEmptyString.isObject":"\nisEmptyString.isObject( value )\n    Tests if a value is an empty `String` object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an empty `String` object.\n\n    Examples\n    --------\n    > var bool = isEmptyString.isObject( new String( '' ) )\n    true\n    > bool = isEmptyString.isObject( '' )\n    false\n\n    See Also\n    --------\n    isString","isEnumerableProperty":"\nisEnumerableProperty( value, property )\n    Tests if an object's own property is enumerable.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own property is enumerable.\n\n    Examples\n    --------\n    > var beep = { 'boop': true };\n    > var bool = isEnumerableProperty( beep, 'boop' )\n    true\n    > bool = isEnumerableProperty( beep, 'hasOwnProperty' )\n    false\n\n    See Also\n    --------\n    isConfigurableProperty, isEnumerablePropertyIn, isNonEnumerableProperty, isReadableProperty, isWritableProperty\n","isEnumerablePropertyIn":"\nisEnumerablePropertyIn( value, property )\n    Tests if an object's own or inherited property is enumerable.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own or inherited property is\n        enumerable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = true;\n    > desc.enumerable = false;\n    > desc.writable = true;\n    > desc.value = true;\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isEnumerablePropertyIn( obj, 'boop' )\n    true\n    > bool = isEnumerablePropertyIn( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    isConfigurablePropertyIn, isEnumerableProperty, isNonEnumerablePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isEqualArray":"\nisEqualArray( v1, v2 )\n    Tests if two arguments are both generic arrays and have equal values.\n\n    The function performs strict equality comparison; thus, the function treats\n    `-0` and `+0` as equal and `NaNs` as distinct.\n\n    Parameters\n    ----------\n    v1: any\n        First input value.\n\n    v2: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are equal.\n\n    Examples\n    --------\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > var y = [ 1.0, 2.0, 3.0 ];\n    > var bool = isEqualArray( x, y )\n    true\n\n    > x = [ NaN, NaN, NaN ];\n    > y = [ NaN, NaN, NaN ];\n    > bool = isEqualArray( x, y )\n    false\n\n    See Also\n    --------\n    isArray, isSameArray\n","isError":"\nisError( value )\n    Tests if a value is an Error object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an Error object.\n\n    Examples\n    --------\n    > var bool = isError( new Error( 'beep' ) )\n    true\n    > bool = isError( {} )\n    false\n\n","isEvalError":"\nisEvalError( value )\n    Tests if a value is an EvalError object.\n\n    This function should *not* be considered robust. While the function should\n    always return `true` if provided an EvalError (or a descendant) object,\n    false positives may occur due to the fact that the EvalError constructor\n    inherits from Error and has no internal class of its own. Hence, EvalError\n    impersonation is possible.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an EvalError object.\n\n    Examples\n    --------\n    > var bool = isEvalError( new EvalError( 'beep' ) )\n    true\n    > bool = isEvalError( {} )\n    false\n\n    See Also\n    --------\n    isError\n","isEven":"\nisEven( value )\n    Tests if a value is an even number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether is an even number.\n\n    Examples\n    --------\n    > var bool = isEven( 4.0 )\n    true\n    > bool = isEven( new Number( 4.0 ) )\n    true\n    > bool = isEven( 3.0 )\n    false\n    > bool = isEven( -3.14 )\n    false\n    > bool = isEven( null )\n    false\n\n\nisEven.isPrimitive( value )\n    Tests if a value is a number primitive that is an even number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive that is an even\n        number.\n\n    Examples\n    --------\n    > var bool = isEven.isPrimitive( -4.0 )\n    true\n    > bool = isEven.isPrimitive( new Number( -4.0 ) )\n    false\n\n\nisEven.isObject( value )\n    Tests if a value is a number object that is an even number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object that is an even\n        number.\n\n    Examples\n    --------\n    > var bool = isEven.isObject( 4.0 )\n    false\n    > bool = isEven.isObject( new Number( 4.0 ) )\n    true\n\n    See Also\n    --------\n    isOdd\n","isEven.isPrimitive":"\nisEven.isPrimitive( value )\n    Tests if a value is a number primitive that is an even number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive that is an even\n        number.\n\n    Examples\n    --------\n    > var bool = isEven.isPrimitive( -4.0 )\n    true\n    > bool = isEven.isPrimitive( new Number( -4.0 ) )\n    false","isEven.isObject":"\nisEven.isObject( value )\n    Tests if a value is a number object that is an even number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object that is an even\n        number.\n\n    Examples\n    --------\n    > var bool = isEven.isObject( 4.0 )\n    false\n    > bool = isEven.isObject( new Number( 4.0 ) )\n    true\n\n    See Also\n    --------\n    isOdd","isFalsy":"\nisFalsy( value )\n    Tests if a value is a value which translates to `false` when evaluated in a\n    boolean context.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is falsy.\n\n    Examples\n    --------\n    > var bool = isFalsy( false )\n    true\n    > bool = isFalsy( '' )\n    true\n    > bool = isFalsy( 0 )\n    true\n    > bool = isFalsy( null )\n    true\n    > bool = isFalsy( void 0 )\n    true\n    > bool = isFalsy( NaN )\n    true\n    > bool = isFalsy( {} )\n    false\n    > bool = isFalsy( [] )\n    false\n\n    See Also\n    --------\n    isFalsyArray, isTruthy\n","isFalsyArray":"\nisFalsyArray( value )\n    Tests if a value is an array-like object containing only falsy values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only falsy values.\n\n    Examples\n    --------\n    > var bool = isFalsyArray( [ null, '' ] )\n    true\n    > bool = isFalsyArray( [ {}, [] ] )\n    false\n    > bool = isFalsyArray( [] )\n    false\n\n    See Also\n    --------\n    isFalsy, isTruthyArray\n","isFinite":"\nisFinite( value )\n    Tests if a value is a finite number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a finite number.\n\n    Examples\n    --------\n    > var bool = isFinite( 5.0 )\n    true\n    > bool = isFinite( new Number( 5.0 ) )\n    true\n    > bool = isFinite( 1.0/0.0 )\n    false\n    > bool = isFinite( null )\n    false\n\n\nisFinite.isPrimitive( value )\n    Tests if a value is a number primitive having a finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number primitive having a finite\n        value.\n\n    Examples\n    --------\n    > var bool = isFinite.isPrimitive( -3.0 )\n    true\n    > bool = isFinite.isPrimitive( new Number( -3.0 ) )\n    false\n\n\nisFinite.isObject( value )\n    Tests if a value is a number object having a finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number object having a finite\n        value.\n\n    Examples\n    --------\n    > var bool = isFinite.isObject( 3.0 )\n    false\n    > bool = isFinite.isObject( new Number( 3.0 ) )\n    true\n\n    See Also\n    --------\n    isFiniteArray, isInfinite\n","isFinite.isPrimitive":"\nisFinite.isPrimitive( value )\n    Tests if a value is a number primitive having a finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number primitive having a finite\n        value.\n\n    Examples\n    --------\n    > var bool = isFinite.isPrimitive( -3.0 )\n    true\n    > bool = isFinite.isPrimitive( new Number( -3.0 ) )\n    false","isFinite.isObject":"\nisFinite.isObject( value )\n    Tests if a value is a number object having a finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number object having a finite\n        value.\n\n    Examples\n    --------\n    > var bool = isFinite.isObject( 3.0 )\n    false\n    > bool = isFinite.isObject( new Number( 3.0 ) )\n    true\n\n    See Also\n    --------\n    isFiniteArray, isInfinite","isFiniteArray":"\nisFiniteArray( value )\n    Tests if a value is an array-like object of finite numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object of finite\n        numbers.\n\n    Examples\n    --------\n    > var bool = isFiniteArray( [ -3.0, new Number(0.0), 2.0 ] )\n    true\n    > bool = isFiniteArray( [ -3.0, 1.0/0.0 ] )\n    false\n\n\nisFiniteArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive finite\n    numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only primitive finite numbers.\n\n    Examples\n    --------\n    > var bool = isFiniteArray.primitives( [ -1.0, 10.0 ] )\n    true\n    > bool = isFiniteArray.primitives( [ -1.0, 0.0, 5.0 ] )\n    true\n    > bool = isFiniteArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false\n\n\nisFiniteArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having finite values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only number objects having finite values.\n\n    Examples\n    --------\n    > var bool = isFiniteArray.objects( [ new Number(1.0), new Number(3.0) ] )\n    true\n    > bool = isFiniteArray.objects( [ -1.0, 0.0, 3.0 ] )\n    false\n    > bool = isFiniteArray.objects( [ 3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isFinite, isInfinite\n","isFiniteArray.primitives":"\nisFiniteArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive finite\n    numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only primitive finite numbers.\n\n    Examples\n    --------\n    > var bool = isFiniteArray.primitives( [ -1.0, 10.0 ] )\n    true\n    > bool = isFiniteArray.primitives( [ -1.0, 0.0, 5.0 ] )\n    true\n    > bool = isFiniteArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false","isFiniteArray.objects":"\nisFiniteArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having finite values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only number objects having finite values.\n\n    Examples\n    --------\n    > var bool = isFiniteArray.objects( [ new Number(1.0), new Number(3.0) ] )\n    true\n    > bool = isFiniteArray.objects( [ -1.0, 0.0, 3.0 ] )\n    false\n    > bool = isFiniteArray.objects( [ 3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isFinite, isInfinite","isFloat32Array":"\nisFloat32Array( value )\n    Tests if a value is a Float32Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Float32Array.\n\n    Examples\n    --------\n    > var bool = isFloat32Array( new Float32Array( 10 ) )\n    true\n    > bool = isFloat32Array( [] )\n    false\n\n    See Also\n    --------\n    isFloat64Array\n","isFloat32MatrixLike":"\nisFloat32MatrixLike( value )\n    Tests if a value is a 2-dimensional ndarray-like object containing single-\n    precision floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 2-dimensional ndarray-like\n        object containing single-precision floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Float32Array( [ 0, 0, 0, 0 ] );\n    > M.ndims = 2;\n    > M.shape = [ 2, 2 ];\n    > M.strides = [ 2, 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'float32';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isFloat32MatrixLike( M )\n    true\n    > bool = isFloat32MatrixLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isFloat32MatrixLike( 3.14 )\n    false\n    > bool = isFloat32MatrixLike( {} )\n    false\n\n    See Also\n    --------\n    isFloat64MatrixLike, isndarrayLike, isMatrixLike\n","isFloat32ndarrayLike":"\nisFloat32ndarrayLike( value )\n    Tests if a value is an ndarray-like object containing single-precision\n    floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an ndarray-like object containing\n        single-precision floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Float32Array( [ 0, 0, 0, 0 ] );\n    > M.ndims = 2;\n    > M.shape = [ 2, 2 ];\n    > M.strides = [ 2, 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'float32';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isFloat32ndarrayLike( M )\n    true\n    > bool = isFloat32ndarrayLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isFloat32ndarrayLike( 3.14 )\n    false\n    > bool = isFloat32ndarrayLike( {} )\n    false\n\n    See Also\n    --------\n    isFloat64ndarrayLike, isndarrayLike\n","isFloat32VectorLike":"\nisFloat32VectorLike( value )\n    Tests if a value is a 1-dimensional ndarray-like object containing single-\n    precision floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 1-dimensional ndarray-like\n        object containing single-precision floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Float32Array( [ 0, 0, 0, 0 ] );\n    > M.ndims = 1;\n    > M.shape = [ 4 ];\n    > M.strides = [ 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'float32';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isFloat32VectorLike( M )\n    true\n    > bool = isFloat32VectorLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isFloat32VectorLike( 3.14 )\n    false\n    > bool = isFloat32VectorLike( {} )\n    false\n\n    See Also\n    --------\n    isFloat64VectorLike, isndarrayLike, isVectorLike\n","isFloat64Array":"\nisFloat64Array( value )\n    Tests if a value is a Float64Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Float64Array.\n\n    Examples\n    --------\n    > var bool = isFloat64Array( new Float64Array( 10 ) )\n    true\n    > bool = isFloat64Array( [] )\n    false\n\n    See Also\n    --------\n    isFloat32Array\n","isFloat64MatrixLike":"\nisFloat64MatrixLike( value )\n    Tests if a value is a 2-dimensional ndarray-like object containing double-\n    precision floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 2-dimensional ndarray-like\n        object containing double-precision floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Float64Array( [ 0, 0, 0, 0 ] );\n    > M.ndims = 2;\n    > M.shape = [ 2, 2 ];\n    > M.strides = [ 2, 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'float64';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isFloat64MatrixLike( M )\n    true\n    > bool = isFloat64MatrixLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isFloat64MatrixLike( 3.14 )\n    false\n    > bool = isFloat64MatrixLike( {} )\n    false\n\n    See Also\n    --------\n    isFloat32MatrixLike, isndarrayLike, isMatrixLike\n","isFloat64ndarrayLike":"\nisFloat64ndarrayLike( value )\n    Tests if a value is an ndarray-like object containing double-precision\n    floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an ndarray-like object containing\n        double-precision floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Float64Array( [ 0, 0, 0, 0 ] );\n    > M.ndims = 2;\n    > M.shape = [ 2, 2 ];\n    > M.strides = [ 2, 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'float64';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isFloat64ndarrayLike( M )\n    true\n    > bool = isFloat64ndarrayLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isFloat64ndarrayLike( 3.14 )\n    false\n    > bool = isFloat64ndarrayLike( {} )\n    false\n\n    See Also\n    --------\n    isFloat32ndarrayLike, isndarrayLike\n","isFloat64VectorLike":"\nisFloat64VectorLike( value )\n    Tests if a value is a 1-dimensional ndarray-like object containing double-\n    precision floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 1-dimensional ndarray-like\n        object containing double-precision floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Float64Array( [ 0, 0, 0, 0 ] );\n    > M.ndims = 1;\n    > M.shape = [ 4 ];\n    > M.strides = [ 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'float64';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isFloat64VectorLike( M )\n    true\n    > bool = isFloat64VectorLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isFloat64VectorLike( 3.14 )\n    false\n    > bool = isFloat64VectorLike( {} )\n    false\n\n    See Also\n    --------\n    isFloat32VectorLike, isndarrayLike, isVectorLike\n","isFunction":"\nisFunction( value )\n    Tests if a value is a function.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a function.\n\n    Examples\n    --------\n    > function beep() {};\n    > var bool = isFunction( beep )\n    true\n    > bool = isFunction( {} )\n    false\n\n","isFunctionArray":"\nisFunctionArray( value )\n    Tests if a value is an array-like object containing only functions.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        functions.\n\n    Examples\n    --------\n    > function beep() {};\n    > function boop() {};\n    > var bool = isFunctionArray( [ beep, boop ] )\n    true\n    > bool = isFunctionArray( [ {}, beep ] )\n    false\n    > bool = isFunctionArray( [] )\n    false\n\n    See Also\n    --------\n    isArray\n","isGeneratorObject":"\nisGeneratorObject( value )\n    Tests if a value is a generator object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a generator object.\n\n    Examples\n    --------\n    > function* generateID() {\n    ...     var idx = 0;\n    ...     while ( idx < idx+1 ) {\n    ...         yield idx;\n    ...         idx += 1;\n    ...     }\n    ... };\n    > var bool = isGeneratorObject( generateID() )\n    true\n    > bool = isGeneratorObject( generateID )\n    false\n    > bool = isGeneratorObject( {} )\n    false\n    > bool = isGeneratorObject( null )\n    false\n\n    See Also\n    --------\n    hasGeneratorSupport, isGeneratorObjectLike\n","isGeneratorObjectLike":"\nisGeneratorObjectLike( value )\n    Tests if a value is generator object-like.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is generator object-like.\n\n    Examples\n    --------\n    > var obj = {\n    ...     'next': function noop() {},\n    ...     'return': function noop() {},\n    ...     'throw': function noop() {}\n    ... };\n    > var bool = isGeneratorObjectLike( obj )\n    true\n    > bool = isGeneratorObjectLike( {} )\n    false\n    > bool = isGeneratorObjectLike( null )\n    false\n\n    See Also\n    --------\n    hasGeneratorSupport, isGeneratorObject\n","isgzipBuffer":"\nisgzipBuffer( value )\n    Tests if a value is a gzip buffer.\n\n    A gzip buffer is defined as either a Node.js Buffer or Uint8Array which\n    contains a 10-byte header, a body containing the compressed payload, and an\n    8-byte footer containing a CRC-32 checksum and the length of the original\n    uncompressed data, modulo 2^32.\n\n    This function only examines the 10-byte header to ensure the header includes\n    the expected magic number and compression method. The function does not\n    perform an integrity check.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a gzip buffer.\n\n    Examples\n    --------\n    > var buf = new Uint8Array( 20 );\n    > buf[ 0 ] = 31;  // 0x1f => magic number\n    > buf[ 1 ] = 139; // 0x8b\n    > buf[ 2 ] = 8;   // 0x08 => compression method\n    > var bool = isgzipBuffer( buf )\n    true\n    > bool = isgzipBuffer( [] )\n    false\n\n    See Also\n    --------\n    isBuffer, isUint8Array\n","isHexString":"\nisHexString( str )\n    Tests whether a string contains only hexadecimal digits.\n\n    The function does not recognize `x` (as in the standard `0x` prefix).\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a string contains only hexadecimal digits.\n\n    Examples\n    --------\n    > var bool = isHexString( '0123456789abcdefABCDEF' )\n    true\n    > bool = isHexString( '0xffffff' )\n    false\n    > bool = isHexString( 'x' )\n    false\n    > bool = isHexString( '' )\n    false\n\n    See Also\n    --------\n    isString\n","isInfinite":"\nisInfinite( value )\n    Tests if a value is an infinite number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an infinite number.\n\n    Examples\n    --------\n    > var bool = isInfinite( 1.0/0.0 )\n    true\n    > bool = isInfinite( new Number( -1.0/0.0 ) )\n    true\n    > bool = isInfinite( 5.0 )\n    false\n    > bool = isInfinite( '1.0/0.0' )\n    false\n\n\nisInfinite.isPrimitive( value )\n    Tests if a value is a number primitive having an infinite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number primitive having an\n        infinite value.\n\n    Examples\n    --------\n    > var bool = isInfinite.isPrimitive( -1.0/0.0 )\n    true\n    > bool = isInfinite.isPrimitive( new Number( -1.0/0.0 ) )\n    false\n\n\nisInfinite.isObject( value )\n    Tests if a value is a number object having an infinite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number object having an infinite\n        value.\n\n    Examples\n    --------\n    > var bool = isInfinite.isObject( 1.0/0.0 )\n    false\n    > bool = isInfinite.isObject( new Number( 1.0/0.0 ) )\n    true\n\n    See Also\n    --------\n    isFinite\n","isInfinite.isPrimitive":"\nisInfinite.isPrimitive( value )\n    Tests if a value is a number primitive having an infinite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number primitive having an\n        infinite value.\n\n    Examples\n    --------\n    > var bool = isInfinite.isPrimitive( -1.0/0.0 )\n    true\n    > bool = isInfinite.isPrimitive( new Number( -1.0/0.0 ) )\n    false","isInfinite.isObject":"\nisInfinite.isObject( value )\n    Tests if a value is a number object having an infinite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number object having an infinite\n        value.\n\n    Examples\n    --------\n    > var bool = isInfinite.isObject( 1.0/0.0 )\n    false\n    > bool = isInfinite.isObject( new Number( 1.0/0.0 ) )\n    true\n\n    See Also\n    --------\n    isFinite","isInheritedProperty":"\nisInheritedProperty( value, property )\n    Tests if an object has an inherited property.\n\n    Value arguments other than `null` or `undefined` are coerced to objects.\n\n    Non-symbol property arguments are coerced to strings.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object has an inherited property.\n\n    Examples\n    --------\n    > var beep = { 'boop': true };\n    > var bool = isInheritedProperty( beep, 'boop' )\n    false\n    > bool = isInheritedProperty( beep, 'toString' )\n    true\n    > bool = isInheritedProperty( beep, 'bop' )\n    false\n\n    See Also\n    --------\n    hasOwnProp, hasProp\n","isInt8Array":"\nisInt8Array( value )\n    Tests if a value is an Int8Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an Int8Array.\n\n    Examples\n    --------\n    > var bool = isInt8Array( new Int8Array( 10 ) )\n    true\n    > bool = isInt8Array( [] )\n    false\n\n    See Also\n    --------\n    isInt16Array, isInt32Array\n","isInt16Array":"\nisInt16Array( value )\n    Tests if a value is an Int16Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an Int16Array.\n\n    Examples\n    --------\n    > var bool = isInt16Array( new Int16Array( 10 ) )\n    true\n    > bool = isInt16Array( [] )\n    false\n\n    See Also\n    --------\n    isInt32Array, isInt8Array\n","isInt32Array":"\nisInt32Array( value )\n    Tests if a value is an Int32Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an Int32Array.\n\n    Examples\n    --------\n    > var bool = isInt32Array( new Int32Array( 10 ) )\n    true\n    > bool = isInt32Array( [] )\n    false\n\n    See Also\n    --------\n    isInt16Array, isInt8Array\n","isInteger":"\nisInteger( value )\n    Tests if a value is an integer.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an integer.\n\n    Examples\n    --------\n    > var bool = isInteger( 5.0 )\n    true\n    > bool = isInteger( new Number( 5.0 ) )\n    true\n    > bool = isInteger( -3.14 )\n    false\n    > bool = isInteger( null )\n    false\n\n\nisInteger.isPrimitive( value )\n    Tests if a value is a number primitive having an integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having an integer\n        value.\n\n    Examples\n    --------\n    > var bool = isInteger.isPrimitive( -3.0 )\n    true\n    > bool = isInteger.isPrimitive( new Number( -3.0 ) )\n    false\n\n\nisInteger.isObject( value )\n    Tests if a value is a number object having an integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having an integer\n        value.\n\n    Examples\n    --------\n    > var bool = isInteger.isObject( 3.0 )\n    false\n    > bool = isInteger.isObject( new Number( 3.0 ) )\n    true\n\n    See Also\n    --------\n    isNumber\n","isInteger.isPrimitive":"\nisInteger.isPrimitive( value )\n    Tests if a value is a number primitive having an integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having an integer\n        value.\n\n    Examples\n    --------\n    > var bool = isInteger.isPrimitive( -3.0 )\n    true\n    > bool = isInteger.isPrimitive( new Number( -3.0 ) )\n    false","isInteger.isObject":"\nisInteger.isObject( value )\n    Tests if a value is a number object having an integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having an integer\n        value.\n\n    Examples\n    --------\n    > var bool = isInteger.isObject( 3.0 )\n    false\n    > bool = isInteger.isObject( new Number( 3.0 ) )\n    true\n\n    See Also\n    --------\n    isNumber","isIntegerArray":"\nisIntegerArray( value )\n    Tests if a value is an array-like object of integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object of integer\n        values.\n\n    Examples\n    --------\n    > var bool = isIntegerArray( [ -3.0, new Number(0.0), 2.0 ] )\n    true\n    > bool = isIntegerArray( [ -3.0, '3.0' ] )\n    false\n\n\nisIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive integer\n    values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only primitive integer values.\n\n    Examples\n    --------\n    > var bool = isIntegerArray.primitives( [ -1.0, 10.0 ] )\n    true\n    > bool = isIntegerArray.primitives( [ -1.0, 0.0, 5.0 ] )\n    true\n    > bool = isIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false\n\n\nisIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only number objects having integer values.\n\n    Examples\n    --------\n    > var bool = isIntegerArray.objects( [ new Number(1.0), new Number(3.0) ] )\n    true\n    > bool = isIntegerArray.objects( [ -1.0, 0.0, 3.0 ] )\n    false\n    > bool = isIntegerArray.objects( [ 3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray\n","isIntegerArray.primitives":"\nisIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive integer\n    values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only primitive integer values.\n\n    Examples\n    --------\n    > var bool = isIntegerArray.primitives( [ -1.0, 10.0 ] )\n    true\n    > bool = isIntegerArray.primitives( [ -1.0, 0.0, 5.0 ] )\n    true\n    > bool = isIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false","isIntegerArray.objects":"\nisIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only number objects having integer values.\n\n    Examples\n    --------\n    > var bool = isIntegerArray.objects( [ new Number(1.0), new Number(3.0) ] )\n    true\n    > bool = isIntegerArray.objects( [ -1.0, 0.0, 3.0 ] )\n    false\n    > bool = isIntegerArray.objects( [ 3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray","isIterableLike":"\nisIterableLike( value )\n    Tests if a value is iterable-like.\n\n    In order to be iterable, an object must implement the @@iterator method,\n    which, when called, returns an iterator protocol-compliant object.\n\n    An iterator protocol-compliant object is an object having a `next` method\n    which adheres to the iterator protocol.\n\n    As full iterator compliance is impossible to achieve without evaluating an\n    iterator, this function checks *only* for interface compliance.\n\n    In environments lacking Symbol.iterator support, this function always\n    returns `false`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is iterable-like.\n\n    Examples\n    --------\n    > var bool = isIterableLike( [ 1, 2, 3 ] )\n    <boolean>\n    > bool = isIterableLike( {} )\n    false\n    > bool = isIterableLike( null )\n    false\n\n    See Also\n    --------\n    isIteratorLike\n","isIteratorLike":"\nisIteratorLike( value )\n    Tests if a value is iterator-like.\n\n    An iterator protocol-compliant object is an object having a `next` method\n    which adheres to the iterator protocol.\n\n    As full iterator compliance is impossible to achieve without evaluating an\n    iterator, this function checks *only* for interface compliance.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is iterator-like.\n\n    Examples\n    --------\n    > var obj = {\n    ...     'next': function noop() {}\n    ... };\n    > var bool = isIteratorLike( obj )\n    true\n    > bool = isIteratorLike( {} )\n    false\n    > bool = isIteratorLike( null )\n    false\n\n    See Also\n    --------\n    isIterableLike\n","isJSON":"\nisJSON( value )\n    Tests if a value is a parseable JSON string.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a parseable JSON string.\n\n    Examples\n    --------\n    > var bool = isJSON( '{\"a\":5}' )\n    true\n    > bool = isJSON( '{a\":5}' )\n    false\n\n","isKebabcase":"\nisKebabcase( value )\n    Tests if a value is a string in kebab case.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a string in kebab case.\n\n    Examples\n    --------\n    > var bool = isKebabcase( 'beep-boop' )\n    true\n    > bool = isKebabcase( 'BEEP_BOOP' )\n    false\n\n    See Also\n    --------\n    isString","isLeapYear":"\nisLeapYear( value )\n    Tests whether a value corresponds to a leap year in the Gregorian calendar.\n\n    A leap year is defined as any year which is exactly divisible by 4, except\n    for years which are exactly divisible by 100 and not by 400. In this\n    definition, 100 corresponds to years marking a new century, and 400\n    corresponds to the length of the *leap cycle*.\n\n    If not provided any arguments, the function returns a boolean indicating\n    if the current year (according to local time) is a leap year.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value corresponds to a leap year.\n\n    Examples\n    --------\n    > var bool = isLeapYear( new Date() )\n    <boolean>\n    > bool = isLeapYear( 1996 )\n    true\n    > bool = isLeapYear( 2001 )\n    false\n\n","isLocalhost":"\nisLocalhost( value )\n    Tests whether a value is a localhost hostname.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a localhost hostname.\n\n    Examples\n    --------\n    > var bool = isLocalhost( 'localhost' )\n    true\n    > bool = isLocalhost( '127.0.0.1' )\n    true\n    > bool = isLocalhost( 'stdlib.io' )\n    false\n","isLowercase":"\nisLowercase( value )\n    Tests if a value is a lowercase string.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a lowercase string.\n\n    Examples\n    --------\n    > var bool = isLowercase( 'hello' )\n    true\n    > bool = isLowercase( 'World' )\n    false\n\n    See Also\n    --------\n    isString, isUppercase\n","isMatrixLike":"\nisMatrixLike( value )\n    Tests if a value is a 2-dimensional ndarray-like object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 2-dimensional ndarray-like\n        object.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = [ 0, 0, 0, 0 ];\n    > M.ndims = 2;\n    > M.shape = [ 2, 2 ];\n    > M.strides = [ 2, 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'generic';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isMatrixLike( M )\n    true\n    > bool = isMatrixLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isMatrixLike( 3.14 )\n    false\n    > bool = isMatrixLike( {} )\n    false\n\n    See Also\n    --------\n    isArray, isArrayLike, isndarrayLike, isTypedArrayLike, isVectorLike\n","isMethod":"\nisMethod( value, property )\n    Tests if an object has a specified method name.\n\n    Value arguments other than `null` or `undefined` are coerced to objects.\n\n    Property arguments are coerced to strings.\n\n    The function only searches own properties.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object has a specified method name.\n\n    Examples\n    --------\n    > var beep = { 'boop': function beep() { return 'beep'; } };\n    > var bool = isMethod( beep, 'boop' )\n    true\n    > bool = isMethod( beep, 'toString' )\n    false\n\n    See Also\n    --------\n    hasOwnProp, isFunction, isMethodIn\n","isMethodIn":"\nisMethodIn( value, property )\n    Tests if an object has a specified method name, either own or inherited.\n\n    Value arguments other than `null` or `undefined` are coerced to objects.\n\n    Non-symbol property arguments are coerced to strings.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object has a specified method name.\n\n    Examples\n    --------\n    > var beep = { 'boop': true };\n    > var bool = isMethodIn( beep, 'toString' )\n    true\n    > bool = isMethodIn( beep, 'boop' )\n    false\n    > bool = isMethodIn( beep, 'bop' )\n    false\n\n    See Also\n    --------\n    hasProp, isFunction, isMethod\n","isMultiSlice":"\nisMultiSlice( value )\n    Tests if a value is a MultiSlice object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a MultiSlice object.\n\n    Examples\n    --------\n    > var bool = isMultiSlice( new MultiSlice() )\n    true\n    > bool = isMultiSlice( 3.14 )\n    false\n    > bool = isMultiSlice( {} )\n    false\n\n    See Also\n    --------\n    isSlice, MultiSlice\n","isNamedTypedTupleLike":"\nisNamedTypedTupleLike( value )\n    Tests if a value is named typed tuple-like.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is named typed tuple-like.\n\n    Examples\n    --------\n    > var Point = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = new Point();\n    > var bool = isNamedTypedTupleLike( p )\n    true\n    > bool = isNamedTypedTupleLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isNamedTypedTupleLike( 3.14 )\n    false\n    > bool = isNamedTypedTupleLike( {} )\n    false\n\n    See Also\n    --------\n    namedtypedtuple\n","isnan":"\nisnan( value )\n    Tests if a value is NaN.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is NaN.\n\n    Examples\n    --------\n    > var bool = isnan( NaN )\n    true\n    > bool = isnan( new Number( NaN ) )\n    true\n    > bool = isnan( 3.14 )\n    false\n    > bool = isnan( null )\n    false\n\n\nisnan.isPrimitive( value )\n    Tests if a value is a NaN number primitive.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a NaN number primitive.\n\n    Examples\n    --------\n    > var bool = isnan.isPrimitive( NaN )\n    true\n    > bool = isnan.isPrimitive( 3.14 )\n    false\n    > bool = isnan.isPrimitive( new Number( NaN ) )\n    false\n\n\nisnan.isObject( value )\n    Tests if a value is a number object having a value of NaN.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value of\n        NaN.\n\n    Examples\n    --------\n    > var bool = isnan.isObject( NaN )\n    false\n    > bool = isnan.isObject( new Number( NaN ) )\n    true\n\n    See Also\n    --------\n    isNumber\n","isnan.isPrimitive":"\nisnan.isPrimitive( value )\n    Tests if a value is a NaN number primitive.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a NaN number primitive.\n\n    Examples\n    --------\n    > var bool = isnan.isPrimitive( NaN )\n    true\n    > bool = isnan.isPrimitive( 3.14 )\n    false\n    > bool = isnan.isPrimitive( new Number( NaN ) )\n    false","isnan.isObject":"\nisnan.isObject( value )\n    Tests if a value is a number object having a value of NaN.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value of\n        NaN.\n\n    Examples\n    --------\n    > var bool = isnan.isObject( NaN )\n    false\n    > bool = isnan.isObject( new Number( NaN ) )\n    true\n\n    See Also\n    --------\n    isNumber","isNaNArray":"\nisNaNArray( value )\n    Tests if a value is an array-like object containing only NaN values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        NaN values.\n\n    Examples\n    --------\n    > var bool = isNaNArray( [ NaN, NaN, NaN ] )\n    true\n    > bool = isNaNArray( [ NaN, 2 ] )\n    false\n\n\nisNaNArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive NaN\n    values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive NaN values.\n\n    Examples\n    --------\n    > var bool = isNaNArray.primitives( [ NaN, new Number( NaN ) ] )\n    false\n    > bool = isNaNArray.primitives( [ NaN, NaN, NaN ] )\n    true\n\n\nisNaNArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having NaN values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having NaN values.\n\n    Examples\n    --------\n    > var bool = isNaNArray.objects( [ new Number( NaN ), new Number( NaN ) ] )\n    true\n    > bool = isNaNArray.objects( [ NaN, new Number( NaN ), new Number( NaN ) ] )\n    false\n    > bool = isNaNArray.objects( [ NaN, NaN, NaN ] )\n    false\n\n    See Also\n    --------\n    isnan\n","isNaNArray.primitives":"\nisNaNArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive NaN\n    values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive NaN values.\n\n    Examples\n    --------\n    > var bool = isNaNArray.primitives( [ NaN, new Number( NaN ) ] )\n    false\n    > bool = isNaNArray.primitives( [ NaN, NaN, NaN ] )\n    true","isNaNArray.objects":"\nisNaNArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having NaN values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having NaN values.\n\n    Examples\n    --------\n    > var bool = isNaNArray.objects( [ new Number( NaN ), new Number( NaN ) ] )\n    true\n    > bool = isNaNArray.objects( [ NaN, new Number( NaN ), new Number( NaN ) ] )\n    false\n    > bool = isNaNArray.objects( [ NaN, NaN, NaN ] )\n    false\n\n    See Also\n    --------\n    isnan","isNativeFunction":"\nisNativeFunction( value )\n    Tests if a value is a native function.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a native function.\n\n    Examples\n    --------\n    > var bool = isNativeFunction( Date )\n    true\n    > function beep() {};\n    > bool = isNativeFunction( beep )\n    false\n    > bool = isNativeFunction( {} )\n    false\n\n    See Also\n    --------\n    isFunction\n","isndarrayLike":"\nisndarrayLike( value )\n    Tests if a value is ndarray-like.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is ndarray-like.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = [ 0, 0, 0, 0 ];\n    > M.ndims = 2;\n    > M.shape = [ 2, 2 ];\n    > M.strides = [ 2, 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'generic';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isndarrayLike( M )\n    true\n    > bool = isndarrayLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isndarrayLike( 3.14 )\n    false\n    > bool = isndarrayLike( {} )\n    false\n\n    See Also\n    --------\n    isArray, isArrayLike, isMatrixLike, isTypedArrayLike, isVectorLike\n","isndarrayLikeWithDataType":"\nisndarrayLikeWithDataType( value, dtype )\n    Tests if a value is an ndarray-like object having a specified data type.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    dtype: any\n        Data type value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an ndarray-like object having a\n        specified data type.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = [ 0, 0, 0, 0 ];\n    > M.ndims = 2;\n    > M.shape = [ 2, 2 ];\n    > M.strides = [ 2, 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'generic';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isndarrayLikeWithDataType( M, 'generic' )\n    true\n    > bool = isndarrayLikeWithDataType( [ 1, 2, 3, 4 ], 'generic' )\n    false\n    > bool = isndarrayLikeWithDataType( 3.14, 'generic' )\n    false\n    > bool = isndarrayLikeWithDataType( {}, 'generic' )\n    false\n\n    See Also\n    --------\n    isndarrayLike\n","isNegativeFinite":"\nisNegativeFinite( value )\n    Tests if a value is a finite negative number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a finite negative number.\n\n    Examples\n    --------\n    > var bool = isNegativeFinite( -5.0 )\n    true\n    > bool = isNegativeFinite( new Number( -5.0 ) )\n    true\n    > bool = isNegativeFinite( -3.14 )\n    true\n    > bool = isNegativeFinite( 5.0 )\n    false\n    > bool = isNegativeFinite( null )\n    false\n    > bool = isNegativeFinite( -1.0/0.0 )\n    false\n    > bool = isNegativeFinite( new Number( -1.0/0.0 ) )\n    false\n\n\nisNegativeFinite.isPrimitive( value )\n    Tests if a value is a number primitive having a finite negative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number primitive having a finite\n        negative value.\n\n    Examples\n    --------\n    > var bool = isNegativeFinite.isPrimitive( -3.0 )\n    true\n    > bool = isNegativeFinite.isPrimitive( new Number( -3.0 ) )\n    false\n    > var bool = isNegativeFinite.isPrimitive( -1.0/0.0 )\n    false\n    > bool = isNegativeFinite.isPrimitive( new Number( -1.0/0.0 ) )\n    false\n\n\nisNegativeFinite.isObject( value )\n    Tests if a value is a number object having a finite negative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number object having a finite\n        negative value.\n\n    Examples\n    --------\n    > var bool = isNegativeFinite.isObject( -3.0 )\n    false\n    > bool = isNegativeFinite.isObject( new Number( -3.0 ) )\n    true\n    > bool = isNegativeFinite.isObject( -1.0/0.0 )\n    false\n    > bool = isNegativeFinite.isObject( new Number( -1.0/0.0 ) )\n    false\n\n    See Also\n    --------\n    isFinite, isNegativeNumber, isPositiveFinite\n","isNegativeFinite.isPrimitive":"\nisNegativeFinite.isPrimitive( value )\n    Tests if a value is a number primitive having a finite negative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number primitive having a finite\n        negative value.\n\n    Examples\n    --------\n    > var bool = isNegativeFinite.isPrimitive( -3.0 )\n    true\n    > bool = isNegativeFinite.isPrimitive( new Number( -3.0 ) )\n    false\n    > var bool = isNegativeFinite.isPrimitive( -1.0/0.0 )\n    false\n    > bool = isNegativeFinite.isPrimitive( new Number( -1.0/0.0 ) )\n    false","isNegativeFinite.isObject":"\nisNegativeFinite.isObject( value )\n    Tests if a value is a number object having a finite negative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number object having a finite\n        negative value.\n\n    Examples\n    --------\n    > var bool = isNegativeFinite.isObject( -3.0 )\n    false\n    > bool = isNegativeFinite.isObject( new Number( -3.0 ) )\n    true\n    > bool = isNegativeFinite.isObject( -1.0/0.0 )\n    false\n    > bool = isNegativeFinite.isObject( new Number( -1.0/0.0 ) )\n    false\n\n    See Also\n    --------\n    isFinite, isNegativeNumber, isPositiveFinite","isNegativeInteger":"\nisNegativeInteger( value )\n    Tests if a value is a negative integer.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a negative integer.\n\n    Examples\n    --------\n    > var bool = isNegativeInteger( -5.0 )\n    true\n    > bool = isNegativeInteger( new Number( -5.0 ) )\n    true\n    > bool = isNegativeInteger( 5.0 )\n    false\n    > bool = isNegativeInteger( -3.14 )\n    false\n    > bool = isNegativeInteger( null )\n    false\n\n\nisNegativeInteger.isPrimitive( value )\n    Tests if a value is a number primitive having a negative integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a negative\n        integer value.\n\n    Examples\n    --------\n    > var bool = isNegativeInteger.isPrimitive( -3.0 )\n    true\n    > bool = isNegativeInteger.isPrimitive( new Number( -3.0 ) )\n    false\n\n\nisNegativeInteger.isObject( value )\n    Tests if a value is a number object having a negative integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a negative\n        integer value.\n\n    Examples\n    --------\n    > var bool = isNegativeInteger.isObject( -3.0 )\n    false\n    > bool = isNegativeInteger.isObject( new Number( -3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger\n","isNegativeInteger.isPrimitive":"\nisNegativeInteger.isPrimitive( value )\n    Tests if a value is a number primitive having a negative integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a negative\n        integer value.\n\n    Examples\n    --------\n    > var bool = isNegativeInteger.isPrimitive( -3.0 )\n    true\n    > bool = isNegativeInteger.isPrimitive( new Number( -3.0 ) )\n    false","isNegativeInteger.isObject":"\nisNegativeInteger.isObject( value )\n    Tests if a value is a number object having a negative integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a negative\n        integer value.\n\n    Examples\n    --------\n    > var bool = isNegativeInteger.isObject( -3.0 )\n    false\n    > bool = isNegativeInteger.isObject( new Number( -3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger","isNegativeIntegerArray":"\nisNegativeIntegerArray( value )\n    Tests if a value is an array-like object containing only negative integers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        negative integers.\n\n    Examples\n    --------\n    > var bool = isNegativeIntegerArray( [ -3.0, new Number(-3.0) ] )\n    true\n    > bool = isNegativeIntegerArray( [ -3.0, '-3.0' ] )\n    false\n\n\nisNegativeIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only negative primitive\n    integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        negative primitive integer values.\n\n    Examples\n    --------\n    > var bool = isNegativeIntegerArray.primitives( [ -1.0, -10.0 ] )\n    true\n    > bool = isNegativeIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNegativeIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false\n\n\nisNegativeIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having negative integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having negative integer values.\n\n    Examples\n    --------\n    > var bool = isNegativeIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n    true\n    > bool = isNegativeIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNegativeIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray\n","isNegativeIntegerArray.primitives":"\nisNegativeIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only negative primitive\n    integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        negative primitive integer values.\n\n    Examples\n    --------\n    > var bool = isNegativeIntegerArray.primitives( [ -1.0, -10.0 ] )\n    true\n    > bool = isNegativeIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNegativeIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false","isNegativeIntegerArray.objects":"\nisNegativeIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having negative integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having negative integer values.\n\n    Examples\n    --------\n    > var bool = isNegativeIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n    true\n    > bool = isNegativeIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNegativeIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray","isNegativeNumber":"\nisNegativeNumber( value )\n    Tests if a value is a negative number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a negative number.\n\n    Examples\n    --------\n    > var bool = isNegativeNumber( -5.0 )\n    true\n    > bool = isNegativeNumber( new Number( -5.0 ) )\n    true\n    > bool = isNegativeNumber( -3.14 )\n    true\n    > bool = isNegativeNumber( 5.0 )\n    false\n    > bool = isNegativeNumber( null )\n    false\n\n\nisNegativeNumber.isPrimitive( value )\n    Tests if a value is a number primitive having a negative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a negative\n        value.\n\n    Examples\n    --------\n    > var bool = isNegativeNumber.isPrimitive( -3.0 )\n    true\n    > bool = isNegativeNumber.isPrimitive( new Number( -3.0 ) )\n    false\n\n\nisNegativeNumber.isObject( value )\n    Tests if a value is a number object having a negative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a negative\n        value.\n\n    Examples\n    --------\n    > var bool = isNegativeNumber.isObject( -3.0 )\n    false\n    > bool = isNegativeNumber.isObject( new Number( -3.0 ) )\n    true\n\n    See Also\n    --------\n    isNumber\n","isNegativeNumber.isPrimitive":"\nisNegativeNumber.isPrimitive( value )\n    Tests if a value is a number primitive having a negative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a negative\n        value.\n\n    Examples\n    --------\n    > var bool = isNegativeNumber.isPrimitive( -3.0 )\n    true\n    > bool = isNegativeNumber.isPrimitive( new Number( -3.0 ) )\n    false","isNegativeNumber.isObject":"\nisNegativeNumber.isObject( value )\n    Tests if a value is a number object having a negative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a negative\n        value.\n\n    Examples\n    --------\n    > var bool = isNegativeNumber.isObject( -3.0 )\n    false\n    > bool = isNegativeNumber.isObject( new Number( -3.0 ) )\n    true\n\n    See Also\n    --------\n    isNumber","isNegativeNumberArray":"\nisNegativeNumberArray( value )\n    Tests if a value is an array-like object containing only negative numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        negative numbers.\n\n    Examples\n    --------\n    > var bool = isNegativeNumberArray( [ -3.0, new Number(-3.0) ] )\n    true\n    > bool = isNegativeNumberArray( [ -3.0, '-3.0' ] )\n    false\n\n\nisNegativeNumberArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive negative\n    numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive negative numbers.\n\n    Examples\n    --------\n    > var bool = isNegativeNumberArray.primitives( [ -1.0, -10.0 ] )\n    true\n    > bool = isNegativeNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNegativeNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false\n\n\nisNegativeNumberArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having negative number values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having negative number values.\n\n    Examples\n    --------\n    > var bool = isNegativeNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n    true\n    > bool = isNegativeNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNegativeNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray\n","isNegativeNumberArray.primitives":"\nisNegativeNumberArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive negative\n    numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive negative numbers.\n\n    Examples\n    --------\n    > var bool = isNegativeNumberArray.primitives( [ -1.0, -10.0 ] )\n    true\n    > bool = isNegativeNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNegativeNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false","isNegativeNumberArray.objects":"\nisNegativeNumberArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having negative number values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having negative number values.\n\n    Examples\n    --------\n    > var bool = isNegativeNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n    true\n    > bool = isNegativeNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNegativeNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray","isNegativeZero":"\nisNegativeZero( value )\n    Tests if a value is negative zero.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is negative zero.\n\n    Examples\n    --------\n    > var bool = isNegativeZero( -0.0 )\n    true\n    > bool = isNegativeZero( new Number( -0.0 ) )\n    true\n    > bool = isNegativeZero( -3.14 )\n    false\n    > bool = isNegativeZero( 0.0 )\n    false\n    > bool = isNegativeZero( null )\n    false\n\n\nisNegativeZero.isPrimitive( value )\n    Tests if a value is a number primitive equal to negative zero.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number primitive equal to\n        negative zero.\n\n    Examples\n    --------\n    > var bool = isNegativeZero.isPrimitive( -0.0 )\n    true\n    > bool = isNegativeZero.isPrimitive( new Number( -0.0 ) )\n    false\n\n\nisNegativeZero.isObject( value )\n    Tests if a value is a number object having a value equal to negative zero.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number object having a value\n        equal to negative zero.\n\n    Examples\n    --------\n    > var bool = isNegativeZero.isObject( -0.0 )\n    false\n    > bool = isNegativeZero.isObject( new Number( -0.0 ) )\n    true\n\n    See Also\n    --------\n    isNumber, isPositiveZero\n","isNegativeZero.isPrimitive":"\nisNegativeZero.isPrimitive( value )\n    Tests if a value is a number primitive equal to negative zero.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number primitive equal to\n        negative zero.\n\n    Examples\n    --------\n    > var bool = isNegativeZero.isPrimitive( -0.0 )\n    true\n    > bool = isNegativeZero.isPrimitive( new Number( -0.0 ) )\n    false","isNegativeZero.isObject":"\nisNegativeZero.isObject( value )\n    Tests if a value is a number object having a value equal to negative zero.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number object having a value\n        equal to negative zero.\n\n    Examples\n    --------\n    > var bool = isNegativeZero.isObject( -0.0 )\n    false\n    > bool = isNegativeZero.isObject( new Number( -0.0 ) )\n    true\n\n    See Also\n    --------\n    isNumber, isPositiveZero","isNodeBuiltin":"\nisNodeBuiltin( str )\n    Tests whether a string matches a Node.js built-in module name.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a string matches a Node.js built-in module\n        name.\n\n    Examples\n    --------\n    > var bool = isNodeBuiltin( 'cluster' )\n    true\n    > bool = isNodeBuiltin( 'crypto' )\n    true\n    > bool = isNodeBuiltin( 'fs-extra' )\n    false\n    > bool = isNodeBuiltin( '' )\n    false\n\n","isNodeDuplexStreamLike":"\nisNodeDuplexStreamLike( value )\n    Tests if a value is Node duplex stream-like.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is Node duplex stream-like.\n\n    Examples\n    --------\n    > var Stream = require( 'stream' ).Duplex;\n    > s = new Stream();\n    > var bool = isNodeDuplexStreamLike( s )\n    true\n    > bool = isNodeDuplexStreamLike( {} )\n    false\n\n    See Also\n    --------\n    isNodeStreamLike\n","isNodeReadableStreamLike":"\nisNodeReadableStreamLike( value )\n    Tests if a value is Node readable stream-like.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is Node readable stream-like.\n\n    Examples\n    --------\n    > var Stream = require( 'stream' ).Readable;\n    > s = new Stream();\n    > var bool = isNodeReadableStreamLike( s )\n    true\n    > bool = isNodeReadableStreamLike( {} )\n    false\n\n    See Also\n    --------\n    isNodeStreamLike\n","isNodeREPL":"\nisNodeREPL()\n    Returns a boolean indicating if running in a Node.js REPL environment.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if running in a Node.js REPL environment.\n\n    Examples\n    --------\n    > var bool = isNodeREPL()\n    <boolean>\n\n","isNodeStreamLike":"\nisNodeStreamLike( value )\n    Tests if a value is Node stream-like.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is Node stream-like.\n\n    Examples\n    --------\n    > var Stream = require( 'stream' ).Stream;\n    > s = new Stream();\n    > var bool = isNodeStreamLike( s )\n    true\n    > bool = isNodeStreamLike( {} )\n    false\n\n","isNodeTransformStreamLike":"\nisNodeTransformStreamLike( value )\n    Tests if a value is Node transform stream-like.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is Node transform stream-like.\n\n    Examples\n    --------\n    > var Stream = require( 'stream' ).Transform;\n    > s = new Stream();\n    > var bool = isNodeTransformStreamLike( s )\n    true\n    > bool = isNodeTransformStreamLike( {} )\n    false\n\n    See Also\n    --------\n    isNodeStreamLike\n","isNodeWritableStreamLike":"\nisNodeWritableStreamLike( value )\n    Tests if a value is Node writable stream-like.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is Node writable stream-like.\n\n    Examples\n    --------\n    > var Stream = require( 'stream' ).Writable;\n    > s = new Stream();\n    > var bool = isNodeWritableStreamLike( s )\n    true\n    > bool = isNodeWritableStreamLike( {} )\n    false\n\n    See Also\n    --------\n    isNodeStreamLike\n","isNonConfigurableProperty":"\nisNonConfigurableProperty( value, property )\n    Tests if an object's own property is non-configurable.\n\n    A non-configurable property is a property which cannot be deleted and whose\n    descriptor cannot be changed.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own property is non-configurable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = true;\n    > desc.writable = true;\n    > desc.value = 'beep';\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isNonConfigurableProperty( obj, 'boop' )\n    false\n    > bool = isNonConfigurableProperty( obj, 'beep' )\n    true\n\n    See Also\n    --------\n    isConfigurableProperty, isEnumerableProperty, isNonConfigurablePropertyIn, isNonEnumerableProperty, isReadableProperty, isWritableProperty\n","isNonConfigurablePropertyIn":"\nisNonConfigurablePropertyIn( value, property )\n    Tests if an object's own or inherited property is non-configurable.\n\n    A non-configurable property is a property which cannot be deleted and whose\n    descriptor cannot be changed.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own or inherited property is non-\n        configurable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = true;\n    > desc.writable = true;\n    > desc.value = true;\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isNonConfigurablePropertyIn( obj, 'boop' )\n    false\n    > bool = isNonConfigurablePropertyIn( obj, 'beep' )\n    true\n\n    See Also\n    --------\n    isConfigurablePropertyIn, isEnumerablePropertyIn, isNonConfigurableProperty, isNonEnumerablePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isNonEnumerableProperty":"\nisNonEnumerableProperty( value, property )\n    Tests if an object's own property is non-enumerable.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own property is non-enumerable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.writable = true;\n    > desc.value = 'beep';\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isNonEnumerableProperty( obj, 'boop' )\n    false\n    > bool = isNonEnumerableProperty( obj, 'beep' )\n    true\n\n    See Also\n    --------\n    isConfigurableProperty, isEnumerableProperty, isNonConfigurableProperty, isNonEnumerablePropertyIn, isReadableProperty, isWritableProperty\n","isNonEnumerablePropertyIn":"\nisNonEnumerablePropertyIn( value, property )\n    Tests if an object's own or inherited property is non-enumerable.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own or inherited property is non-\n        enumerable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = true;\n    > desc.enumerable = false;\n    > desc.writable = true;\n    > desc.value = true;\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isNonEnumerablePropertyIn( obj, 'boop' )\n    false\n    > bool = isNonEnumerablePropertyIn( obj, 'beep' )\n    true\n\n    See Also\n    --------\n    isConfigurablePropertyIn, isEnumerablePropertyIn, isNonConfigurablePropertyIn, isNonEnumerableProperty, isReadablePropertyIn, isWritablePropertyIn\n","isNonNegativeFinite":"\nisNonNegativeFinite( value )\n    Tests if a value is a nonnegative finite number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a nonnegative finite number.\n\n    Examples\n    --------\n    > var bool = isNonNegativeFinite( 5.0 )\n    true\n    > bool = isNonNegativeFinite( new Number( 5.0 ) )\n    true\n    > bool = isNonNegativeFinite( 3.14 )\n    true\n    > bool = isNonNegativeFinite( -5.0 )\n    false\n    > bool = isNonNegativeFinite( null )\n    false\n    > bool = isNonNegativeFinite( PINF )\n    false\n\n\nisNonNegativeFinite.isPrimitive( value )\n    Tests if a value is a number primitive having a nonnegative finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonnegative finite value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeFinite.isPrimitive( 3.0 )\n    true\n    > bool = isNonNegativeFinite.isPrimitive( new Number( 3.0 ) )\n    false\n\n\nisNonNegativeFinite.isObject( value )\n    Tests if a value is a number object having a nonnegative finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a \n        nonnegative finite value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeFinite.isObject( 3.0 )\n    false\n    > bool = isNonNegativeFinite.isObject( new Number( 3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isFinite, isNonNegativeNumber, isNumber\n","isNonNegativeFinite.isPrimitive":"\nisNonNegativeFinite.isPrimitive( value )\n    Tests if a value is a number primitive having a nonnegative finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonnegative finite value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeFinite.isPrimitive( 3.0 )\n    true\n    > bool = isNonNegativeFinite.isPrimitive( new Number( 3.0 ) )\n    false","isNonNegativeFinite.isObject":"\nisNonNegativeFinite.isObject( value )\n    Tests if a value is a number object having a nonnegative finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a \n        nonnegative finite value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeFinite.isObject( 3.0 )\n    false\n    > bool = isNonNegativeFinite.isObject( new Number( 3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isFinite, isNonNegativeNumber, isNumber","isNonNegativeInteger":"\nisNonNegativeInteger( value )\n    Tests if a value is a nonnegative integer.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a nonnegative integer.\n\n    Examples\n    --------\n    > var bool = isNonNegativeInteger( 5.0 )\n    true\n    > bool = isNonNegativeInteger( new Number( 5.0 ) )\n    true\n    > bool = isNonNegativeInteger( 3.14 )\n    false\n    > bool = isNonNegativeInteger( -5.0 )\n    false\n    > bool = isNonNegativeInteger( null )\n    false\n\n\nisNonNegativeInteger.isPrimitive( value )\n    Tests if a value is a number primitive having a nonnegative integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonnegative integer value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeInteger.isPrimitive( 3.0 )\n    true\n    > bool = isNonNegativeInteger.isPrimitive( new Number( 3.0 ) )\n    false\n\n\nisNonNegativeInteger.isObject( value )\n    Tests if a value is a number object having a nonnegative integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a nonnegative\n        integer value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeInteger.isObject( 3.0 )\n    false\n    > bool = isNonNegativeInteger.isObject( new Number( 3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger, isNonNegativeNumber, isNumber\n","isNonNegativeInteger.isPrimitive":"\nisNonNegativeInteger.isPrimitive( value )\n    Tests if a value is a number primitive having a nonnegative integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonnegative integer value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeInteger.isPrimitive( 3.0 )\n    true\n    > bool = isNonNegativeInteger.isPrimitive( new Number( 3.0 ) )\n    false","isNonNegativeInteger.isObject":"\nisNonNegativeInteger.isObject( value )\n    Tests if a value is a number object having a nonnegative integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a nonnegative\n        integer value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeInteger.isObject( 3.0 )\n    false\n    > bool = isNonNegativeInteger.isObject( new Number( 3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger, isNonNegativeNumber, isNumber","isNonNegativeIntegerArray":"\nisNonNegativeIntegerArray( value )\n    Tests if a value is an array-like object containing only nonnegative\n    integers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        nonnegative integers.\n\n    Examples\n    --------\n    > var bool = isNonNegativeIntegerArray( [ 3.0, new Number(3.0) ] )\n    true\n    > bool = isNonNegativeIntegerArray( [ 3.0, '3.0' ] )\n    false\n\n\nisNonNegativeIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only nonnegative\n    primitive integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        nonnegative primitive integer values.\n\n    Examples\n    --------\n    > var bool = isNonNegativeIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n    true\n    > bool = isNonNegativeIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n    false\n\n\nisNonNegativeIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having nonnegative integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having nonnegative integer values.\n\n    Examples\n    --------\n    > var bool = isNonNegativeIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n    true\n    > bool = isNonNegativeIntegerArray.objects( [ 1.0, 0.0, 10.0 ] )\n    false\n    > bool = isNonNegativeIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray\n","isNonNegativeIntegerArray.primitives":"\nisNonNegativeIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only nonnegative\n    primitive integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        nonnegative primitive integer values.\n\n    Examples\n    --------\n    > var bool = isNonNegativeIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n    true\n    > bool = isNonNegativeIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n    false","isNonNegativeIntegerArray.objects":"\nisNonNegativeIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having nonnegative integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having nonnegative integer values.\n\n    Examples\n    --------\n    > var bool = isNonNegativeIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n    true\n    > bool = isNonNegativeIntegerArray.objects( [ 1.0, 0.0, 10.0 ] )\n    false\n    > bool = isNonNegativeIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray","isNonNegativeNumber":"\nisNonNegativeNumber( value )\n    Tests if a value is a nonnegative number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a nonnegative number.\n\n    Examples\n    --------\n    > var bool = isNonNegativeNumber( 5.0 )\n    true\n    > bool = isNonNegativeNumber( new Number( 5.0 ) )\n    true\n    > bool = isNonNegativeNumber( 3.14 )\n    true\n    > bool = isNonNegativeNumber( -5.0 )\n    false\n    > bool = isNonNegativeNumber( null )\n    false\n\n\nisNonNegativeNumber.isPrimitive( value )\n    Tests if a value is a number primitive having a nonnegative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonnegative value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeNumber.isPrimitive( 3.0 )\n    true\n    > bool = isNonNegativeNumber.isPrimitive( new Number( 3.0 ) )\n    false\n\n\nisNonNegativeNumber.isObject( value )\n    Tests if a value is a number object having a nonnegative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a nonnegative\n        value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeNumber.isObject( 3.0 )\n    false\n    > bool = isNonNegativeNumber.isObject( new Number( 3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isNonNegativeFinite, isNonNegativeInteger, isNumber\n","isNonNegativeNumber.isPrimitive":"\nisNonNegativeNumber.isPrimitive( value )\n    Tests if a value is a number primitive having a nonnegative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonnegative value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeNumber.isPrimitive( 3.0 )\n    true\n    > bool = isNonNegativeNumber.isPrimitive( new Number( 3.0 ) )\n    false","isNonNegativeNumber.isObject":"\nisNonNegativeNumber.isObject( value )\n    Tests if a value is a number object having a nonnegative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a nonnegative\n        value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeNumber.isObject( 3.0 )\n    false\n    > bool = isNonNegativeNumber.isObject( new Number( 3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isNonNegativeFinite, isNonNegativeInteger, isNumber","isNonNegativeNumberArray":"\nisNonNegativeNumberArray( value )\n    Tests if a value is an array-like object containing only nonnegative\n    numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        nonnegative numbers.\n\n    Examples\n    --------\n    > var bool = isNonNegativeNumberArray( [ 3.0, new Number(3.0) ] )\n    true\n    > bool = isNonNegativeNumberArray( [ 3.0, '3.0' ] )\n    false\n\n\nisNonNegativeNumberArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive\n    nonnegative numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive nonnegative numbers.\n\n    Examples\n    --------\n    > var bool = isNonNegativeNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n    true\n    > bool = isNonNegativeNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n    false\n\n\nisNonNegativeNumberArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having nonnegative number values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having nonnegative number values.\n\n    Examples\n    --------\n    > var bool = isNonNegativeNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n    true\n    > bool = isNonNegativeNumberArray.objects( [ 1.0, 0.0, 10.0 ] )\n    false\n    > bool = isNonNegativeNumberArray.objects( [ 3.0, new Number(1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray\n","isNonNegativeNumberArray.primitives":"\nisNonNegativeNumberArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive\n    nonnegative numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive nonnegative numbers.\n\n    Examples\n    --------\n    > var bool = isNonNegativeNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n    true\n    > bool = isNonNegativeNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n    false","isNonNegativeNumberArray.objects":"\nisNonNegativeNumberArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having nonnegative number values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having nonnegative number values.\n\n    Examples\n    --------\n    > var bool = isNonNegativeNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n    true\n    > bool = isNonNegativeNumberArray.objects( [ 1.0, 0.0, 10.0 ] )\n    false\n    > bool = isNonNegativeNumberArray.objects( [ 3.0, new Number(1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray","isNonPositiveFinite":"\nisNonPositiveFinite( value )\n    Tests if a value is a nonpositive finite number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a nonpositive finite number.\n\n    Examples\n    --------\n    > var bool = isNonPositiveFinite( -5.0 )\n    true\n    > bool = isNonPositiveFinite( new Number( -5.0 ) )\n    true\n    > bool = isNonPositiveFinite( -3.14 )\n    true\n    > bool = isNonPositiveFinite( 5.0 )\n    false\n    > bool = isNonPositiveFinite( null )\n    false\n\n\nisNonPositiveFinite.isPrimitive( value )\n    Tests if a value is a number primitive having a nonpositive finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonpositive finite value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveFinite.isPrimitive( -3.0 )\n    true\n    > bool = isNonPositiveFinite.isPrimitive( new Number( -3.0 ) )\n    false\n\n\nisNonPositiveFinite.isObject( value )\n    Tests if a value is a number object having a nonpositive finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a nonpositive\n        finite value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveFinite.isObject( -3.0 )\n    false\n    > bool = isNonPositiveFinite.isObject( new Number( -3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isFinite, isNonPositiveNumber\n","isNonPositiveFinite.isPrimitive":"\nisNonPositiveFinite.isPrimitive( value )\n    Tests if a value is a number primitive having a nonpositive finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonpositive finite value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveFinite.isPrimitive( -3.0 )\n    true\n    > bool = isNonPositiveFinite.isPrimitive( new Number( -3.0 ) )\n    false","isNonPositiveFinite.isObject":"\nisNonPositiveFinite.isObject( value )\n    Tests if a value is a number object having a nonpositive finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a nonpositive\n        finite value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveFinite.isObject( -3.0 )\n    false\n    > bool = isNonPositiveFinite.isObject( new Number( -3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isFinite, isNonPositiveNumber","isNonPositiveInteger":"\nisNonPositiveInteger( value )\n    Tests if a value is a nonpositive integer.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a nonpositive integer.\n\n    Examples\n    --------\n    > var bool = isNonPositiveInteger( -5.0 )\n    true\n    > bool = isNonPositiveInteger( new Number( -5.0 ) )\n    true\n    > bool = isNonPositiveInteger( 5.0 )\n    false\n    > bool = isNonPositiveInteger( -3.14 )\n    false\n    > bool = isNonPositiveInteger( null )\n    false\n\n\nisNonPositiveInteger.isPrimitive( value )\n    Tests if a value is a number primitive having a nonpositive integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonpositive integer value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveInteger.isPrimitive( -3.0 )\n    true\n    > bool = isNonPositiveInteger.isPrimitive( new Number( -3.0 ) )\n    false\n\n\nisNonPositiveInteger.isObject( value )\n    Tests if a value is a number object having a nonpositive integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a nonpositive\n        integer value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveInteger.isObject( -3.0 )\n    false\n    > bool = isNonPositiveInteger.isObject( new Number( -3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger\n","isNonPositiveInteger.isPrimitive":"\nisNonPositiveInteger.isPrimitive( value )\n    Tests if a value is a number primitive having a nonpositive integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonpositive integer value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveInteger.isPrimitive( -3.0 )\n    true\n    > bool = isNonPositiveInteger.isPrimitive( new Number( -3.0 ) )\n    false","isNonPositiveInteger.isObject":"\nisNonPositiveInteger.isObject( value )\n    Tests if a value is a number object having a nonpositive integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a nonpositive\n        integer value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveInteger.isObject( -3.0 )\n    false\n    > bool = isNonPositiveInteger.isObject( new Number( -3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger","isNonPositiveIntegerArray":"\nisNonPositiveIntegerArray( value )\n    Tests if a value is an array-like object containing only nonpositive\n    integers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        nonpositive integers.\n\n    Examples\n    --------\n    > var bool = isNonPositiveIntegerArray( [ -3.0, new Number(-3.0) ] )\n    true\n    > bool = isNonPositiveIntegerArray( [ -3.0, '-3.0' ] )\n    false\n\n\nisNonPositiveIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only nonpositive\n    primitive integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        nonpositive primitive integer values.\n\n    Examples\n    --------\n    > var bool = isNonPositiveIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n    true\n    > bool = isNonPositiveIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false\n\n\nisNonPositiveIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having nonpositive integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having nonpositive integer values.\n\n    Examples\n    --------\n    > var bool = isNonPositiveIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n    true\n    > bool = isNonPositiveIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNonPositiveIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray\n","isNonPositiveIntegerArray.primitives":"\nisNonPositiveIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only nonpositive\n    primitive integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        nonpositive primitive integer values.\n\n    Examples\n    --------\n    > var bool = isNonPositiveIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n    true\n    > bool = isNonPositiveIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false","isNonPositiveIntegerArray.objects":"\nisNonPositiveIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having nonpositive integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having nonpositive integer values.\n\n    Examples\n    --------\n    > var bool = isNonPositiveIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n    true\n    > bool = isNonPositiveIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNonPositiveIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray","isNonPositiveNumber":"\nisNonPositiveNumber( value )\n    Tests if a value is a nonpositive number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a nonpositive number.\n\n    Examples\n    --------\n    > var bool = isNonPositiveNumber( -5.0 )\n    true\n    > bool = isNonPositiveNumber( new Number( -5.0 ) )\n    true\n    > bool = isNonPositiveNumber( -3.14 )\n    true\n    > bool = isNonPositiveNumber( 5.0 )\n    false\n    > bool = isNonPositiveNumber( null )\n    false\n\n\nisNonPositiveNumber.isPrimitive( value )\n    Tests if a value is a number primitive having a nonpositive value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonpositive value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveNumber.isPrimitive( -3.0 )\n    true\n    > bool = isNonPositiveNumber.isPrimitive( new Number( -3.0 ) )\n    false\n\n\nisNonPositiveNumber.isObject( value )\n    Tests if a value is a number object having a nonpositive value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a nonpositive\n        value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveNumber.isObject( -3.0 )\n    false\n    > bool = isNonPositiveNumber.isObject( new Number( -3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isNumber\n","isNonPositiveNumber.isPrimitive":"\nisNonPositiveNumber.isPrimitive( value )\n    Tests if a value is a number primitive having a nonpositive value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonpositive value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveNumber.isPrimitive( -3.0 )\n    true\n    > bool = isNonPositiveNumber.isPrimitive( new Number( -3.0 ) )\n    false","isNonPositiveNumber.isObject":"\nisNonPositiveNumber.isObject( value )\n    Tests if a value is a number object having a nonpositive value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a nonpositive\n        value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveNumber.isObject( -3.0 )\n    false\n    > bool = isNonPositiveNumber.isObject( new Number( -3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isNumber","isNonPositiveNumberArray":"\nisNonPositiveNumberArray( value )\n    Tests if a value is an array-like object containing only nonpositive\n    numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        nonpositive numbers.\n\n    Examples\n    --------\n    > var bool = isNonPositiveNumberArray( [ -3.0, new Number(-3.0) ] )\n    true\n    > bool = isNonPositiveNumberArray( [ -3.0, '-3.0' ] )\n    false\n\n\nisNonPositiveNumberArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive\n    nonpositive numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive nonpositive numbers.\n\n    Examples\n    --------\n    > var bool = isNonPositiveNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n    true\n    > bool = isNonPositiveNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false\n\n\nisNonPositiveNumberArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having nonpositive number values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having nonpositive number values.\n\n    Examples\n    --------\n    > var bool = isNonPositiveNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n    true\n    > bool = isNonPositiveNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNonPositiveNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray\n","isNonPositiveNumberArray.primitives":"\nisNonPositiveNumberArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive\n    nonpositive numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive nonpositive numbers.\n\n    Examples\n    --------\n    > var bool = isNonPositiveNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n    true\n    > bool = isNonPositiveNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false","isNonPositiveNumberArray.objects":"\nisNonPositiveNumberArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having nonpositive number values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having nonpositive number values.\n\n    Examples\n    --------\n    > var bool = isNonPositiveNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n    true\n    > bool = isNonPositiveNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNonPositiveNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray","isNonSymmetricMatrix":"\nisNonSymmetricMatrix( value )\n    Tests if a value is a non-symmetric matrix.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a non-symmetric matrix.\n\n    Examples\n    --------\n    > var buf = [ 1, 2, 3, 4 ];\n    > var sh = [ 2, 2 ];\n    > var st = [ 2, 1 ];\n    > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n    > var bool = isNonSymmetricMatrix( M )\n    true\n    > bool = isNonSymmetricMatrix( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isNonSymmetricMatrix( 3.14 )\n    false\n    > bool = isNonSymmetricMatrix( {} )\n    false\n\n    See Also\n    --------\n    isMatrixLike, isSquareMatrix, isSymmetricMatrix\n","isNull":"\nisNull( value )\n    Tests if a value is null.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is null.\n\n    Examples\n    --------\n    > var bool = isNull( null )\n    true\n    > bool = isNull( true )\n    false\n\n    See Also\n    --------\n    isUndefined, isUndefinedOrNull\n","isNullArray":"\nisNullArray( value )\n    Tests if a value is an array-like object containing only null values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        null values.\n\n    Examples\n    --------\n    > var bool = isNullArray( [ null, null, null ] )\n    true\n    > bool = isNullArray( [ NaN, 2, null ] )\n    false\n\n    See Also\n    --------\n    isArray, isNull\n","isNumber":"\nisNumber( value )\n    Tests if a value is a number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number.\n\n    Examples\n    --------\n    > var bool = isNumber( 3.14 )\n    true\n    > bool = isNumber( new Number( 3.14 ) )\n    true\n    > bool = isNumber( NaN )\n    true\n    > bool = isNumber( null )\n    false\n\n\nisNumber.isPrimitive( value )\n    Tests if a value is a number primitive.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive.\n\n    Examples\n    --------\n    > var bool = isNumber.isPrimitive( 3.14 )\n    true\n    > bool = isNumber.isPrimitive( NaN )\n    true\n    > bool = isNumber.isPrimitive( new Number( 3.14 ) )\n    false\n\n\nisNumber.isObject( value )\n    Tests if a value is a `Number` object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a `Number` object.\n\n    Examples\n    --------\n    > var bool = isNumber.isObject( 3.14 )\n    false\n    > bool = isNumber.isObject( new Number( 3.14 ) )\n    true\n\n","isNumber.isPrimitive":"\nisNumber.isPrimitive( value )\n    Tests if a value is a number primitive.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive.\n\n    Examples\n    --------\n    > var bool = isNumber.isPrimitive( 3.14 )\n    true\n    > bool = isNumber.isPrimitive( NaN )\n    true\n    > bool = isNumber.isPrimitive( new Number( 3.14 ) )\n    false","isNumber.isObject":"\nisNumber.isObject( value )\n    Tests if a value is a `Number` object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a `Number` object.\n\n    Examples\n    --------\n    > var bool = isNumber.isObject( 3.14 )\n    false\n    > bool = isNumber.isObject( new Number( 3.14 ) )\n    true","isNumberArray":"\nisNumberArray( value )\n    Tests if a value is an array-like object containing only numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        numbers.\n\n    Examples\n    --------\n    > var bool = isNumberArray( [ 1, 2, 3 ] )\n    true\n    > bool = isNumberArray( [ '1', 2, 3 ] )\n    false\n\n\nisNumberArray.primitives( value )\n    Tests if a value is an array-like object containing only number primitives.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number primitives.\n\n    Examples\n    --------\n    > var arr = [ 1, 2, 3 ];\n    > var bool = isNumberArray.primitives( arr )\n    true\n    > arr = [ 1, new Number( 2 ) ];\n    > bool = isNumberArray.primitives( arr )\n    false\n\n\nisNumberArray.objects( value )\n    Tests if a value is an array-like object containing only `Number` objects.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        `Number` objects.\n\n    Examples\n    --------\n    > var arr = [ new Number( 1 ), new Number( 2 ) ];\n    > var bool = isNumberArray.objects( arr )\n    true\n    > arr = [ new Number( 1 ), 2 ];\n    > bool = isNumberArray.objects( arr )\n    false\n\n    See Also\n    --------\n    isArray, isNumber, isNumericArray\n","isNumberArray.primitives":"\nisNumberArray.primitives( value )\n    Tests if a value is an array-like object containing only number primitives.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number primitives.\n\n    Examples\n    --------\n    > var arr = [ 1, 2, 3 ];\n    > var bool = isNumberArray.primitives( arr )\n    true\n    > arr = [ 1, new Number( 2 ) ];\n    > bool = isNumberArray.primitives( arr )\n    false","isNumberArray.objects":"\nisNumberArray.objects( value )\n    Tests if a value is an array-like object containing only `Number` objects.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        `Number` objects.\n\n    Examples\n    --------\n    > var arr = [ new Number( 1 ), new Number( 2 ) ];\n    > var bool = isNumberArray.objects( arr )\n    true\n    > arr = [ new Number( 1 ), 2 ];\n    > bool = isNumberArray.objects( arr )\n    false\n\n    See Also\n    --------\n    isArray, isNumber, isNumericArray","isNumericArray":"\nisNumericArray( value )\n    Tests if a value is a numeric array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is a numeric array.\n\n    Examples\n    --------\n    > var bool = isNumericArray( new Int8Array( 10 ) )\n    true\n    > bool = isNumericArray( [ 1, 2, 3 ] )\n    true\n    > bool = isNumericArray( [ '1', '2', '3' ] )\n    false\n\n    See Also\n    --------\n    isArray, isNumberArray, isTypedArray\n\n","isObject":"\nisObject( value )\n    Tests if a value is an object; e.g., `{}`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an object.\n\n    Examples\n    --------\n    > var bool = isObject( {} )\n    true\n    > bool = isObject( true )\n    false\n\n    See Also\n    --------\n    isObjectLike, isPlainObject\n","isObjectArray":"\nisObjectArray( value )\n    Tests if a value is an array-like object containing only objects.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        objects.\n\n    Examples\n    --------\n    > var bool = isObjectArray( [ {}, new Number(3.0) ] )\n    true\n    > bool = isObjectArray( [ {}, { 'beep': 'boop' } ] )\n    true\n    > bool = isObjectArray( [ {}, '3.0' ] )\n    false\n\n    See Also\n    --------\n    isArray, isObject\n","isObjectLike":"\nisObjectLike( value )\n    Tests if a value is object-like.\n\n    Return values are the same as would be obtained using the built-in `typeof`\n    operator except that `null` is not considered an object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is object-like.\n\n    Examples\n    --------\n    > var bool = isObjectLike( {} )\n    true\n    > bool = isObjectLike( [] )\n    true\n    > bool = isObjectLike( null )\n    false\n\n    See Also\n    --------\n    isObject, isPlainObject\n","isOdd":"\nisOdd( value )\n    Tests if a value is an odd number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an odd number.\n\n    Examples\n    --------\n    > var bool = isOdd( 5.0 )\n    true\n    > bool = isOdd( new Number( 5.0 ) )\n    true\n    > bool = isOdd( 4.0 )\n    false\n    > bool = isOdd( new Number( 4.0 ) )\n    false\n    > bool = isOdd( -3.14 )\n    false\n    > bool = isOdd( null )\n    false\n\nisOdd.isPrimitive( value )\n    Tests if a value is a number primitive that is an odd number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive that is an odd\n        number.\n\n    Examples\n    --------\n    > var bool = isOdd.isPrimitive( -5.0 )\n    true\n    > bool = isOdd.isPrimitive( new Number( -5.0 ) )\n    false\n\n\nisOdd.isObject( value )\n    Tests if a value is a number object that has an odd number value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object that has an odd\n        number value.\n\n    Examples\n    --------\n    > var bool = isOdd.isObject( 5.0 )\n    false\n    > bool = isOdd.isObject( new Number( 5.0 ) )\n    true\n\n    See Also\n    --------\n    isEven\n","isOdd.isPrimitive":"\nisOdd.isPrimitive( value )\n    Tests if a value is a number primitive that is an odd number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive that is an odd\n        number.\n\n    Examples\n    --------\n    > var bool = isOdd.isPrimitive( -5.0 )\n    true\n    > bool = isOdd.isPrimitive( new Number( -5.0 ) )\n    false","isOdd.isObject":"\nisOdd.isObject( value )\n    Tests if a value is a number object that has an odd number value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object that has an odd\n        number value.\n\n    Examples\n    --------\n    > var bool = isOdd.isObject( 5.0 )\n    false\n    > bool = isOdd.isObject( new Number( 5.0 ) )\n    true\n\n    See Also\n    --------\n    isEven","isoWeeksInYear":"\nisoWeeksInYear( [year] )\n    Returns the number of ISO weeks in a year according to the Gregorian\n    calendar.\n\n    By default, the function returns the number of ISO weeks in the current year\n    (according to local time). To determine the number of ISO weeks for a\n    particular year, provide either a year or a `Date` object.\n\n    Parameters\n    ----------\n    year: integer (optional)\n        Year.\n\n    Returns\n    -------\n    out: integer\n        Number of ISO weeks in a year.\n\n    Examples\n    --------\n    > var num = isoWeeksInYear()\n    <number>\n    > num = isoWeeksInYear( 2015 )\n    53\n    > num = isoWeeksInYear( 2017 )\n    52\n\n","isPascalcase":"\nisPascalcase( value )\n    Tests if a value is a string in Pascal case.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a string in Pascal case.\n\n    Examples\n    --------\n    > var bool = isPascalcase( 'HelloWorld' )\n    true\n    > bool = isPascalcase( 'hello-world' )\n    false\n\n    See Also\n    --------\n    isString","isPersymmetricMatrix":"\nisPersymmetricMatrix( value )\n    Tests if a value is a square matrix which is symmetric about its\n    antidiagonal.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a persymmetric matrix.\n\n    Examples\n    --------\n    > var buf = [ 1, 2, 3, 1 ];\n    > var sh = [ 2, 2 ];\n    > var st = [ 2, 1 ];\n    > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n    > var bool = isPersymmetricMatrix( M )\n    true\n    > bool = isPersymmetricMatrix( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isPersymmetricMatrix( 3.14 )\n    false\n    > bool = isPersymmetricMatrix( {} )\n    false\n\n    See Also\n    --------\n    isMatrixLike, isSquareMatrix, isSymmetricMatrix\n","isPlainObject":"\nisPlainObject( value )\n    Tests if a value is a plain object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a plain object.\n\n    Examples\n    --------\n    > var bool = isPlainObject( {} )\n    true\n    > bool = isPlainObject( null )\n    false\n\n    See Also\n    --------\n    isObject\n","isPlainObjectArray":"\nisPlainObjectArray( value )\n    Tests if a value is an array-like object containing only plain objects.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        plain objects.\n\n    Examples\n    --------\n    > var bool = isPlainObjectArray( [ {}, { 'beep': 'boop' } ] )\n    true\n    > bool = isPlainObjectArray( [ {}, new Number(3.0) ] )\n    false\n    > bool = isPlainObjectArray( [ {}, '3.0' ] )\n    false\n\n    See Also\n    --------\n    isArray, isPlainObject\n","isPositiveFinite":"\nisPositiveFinite( value )\n    Tests if a value is a positive finite number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a positive finite number.\n\n    Examples\n    --------\n    > var bool = isPositiveFinite( 5.0 )\n    true\n    > bool = isPositiveFinite( new Number( 5.0 ) )\n    true\n    > bool = isPositiveFinite( 3.14 )\n    true\n    > bool = isPositiveFinite( -5.0 )\n    false\n    > var bool = isPositiveFinite( 1.0/0.0 )\n    false\n    > bool = isPositiveFinite( new Number( 1.0/0.0 ) )\n    false\n    > bool = isPositiveFinite( null )\n    false\n\n\nisPositiveFinite.isPrimitive( value )\n    Tests if a value is a number primitive having a positive finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is a number primitive having a positive\n        finite value.\n\n    Examples\n    --------\n    > var bool = isPositiveFinite.isPrimitive( 3.0 )\n    true\n    > var bool = isPositiveFinite.isPrimitive( 1.0/0.0 )\n    false\n    > bool = isPositiveFinite.isPrimitive( new Number( 3.0 ) )\n    false\n\n\nisPositiveFinite.isObject( value )\n    Tests if a value is a number object having a positive finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a positive\n        finite value.\n\n    Examples\n    --------\n    > var bool = isPositiveFinite.isObject( 3.0 )\n    false\n    > bool = isPositiveFinite.isObject( new Number( 3.0 ) )\n    true\n    > bool = isPositiveFinite.isObject( new Number( 1.0/0.0 ) )\n    false\n\n\n    See Also\n    --------\n    isFinite, isPositiveNumber\n","isPositiveFinite.isPrimitive":"\nisPositiveFinite.isPrimitive( value )\n    Tests if a value is a number primitive having a positive finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is a number primitive having a positive\n        finite value.\n\n    Examples\n    --------\n    > var bool = isPositiveFinite.isPrimitive( 3.0 )\n    true\n    > var bool = isPositiveFinite.isPrimitive( 1.0/0.0 )\n    false\n    > bool = isPositiveFinite.isPrimitive( new Number( 3.0 ) )\n    false","isPositiveFinite.isObject":"\nisPositiveFinite.isObject( value )\n    Tests if a value is a number object having a positive finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a positive\n        finite value.\n\n    Examples\n    --------\n    > var bool = isPositiveFinite.isObject( 3.0 )\n    false\n    > bool = isPositiveFinite.isObject( new Number( 3.0 ) )\n    true\n    > bool = isPositiveFinite.isObject( new Number( 1.0/0.0 ) )\n    false\n\n\n    See Also\n    --------\n    isFinite, isPositiveNumber","isPositiveInteger":"\nisPositiveInteger( value )\n    Tests if a value is a positive integer.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a positive integer.\n\n    Examples\n    --------\n    > var bool = isPositiveInteger( 5.0 )\n    true\n    > bool = isPositiveInteger( new Number( 5.0 ) )\n    true\n    > bool = isPositiveInteger( 3.14 )\n    false\n    > bool = isPositiveInteger( -5.0 )\n    false\n    > bool = isPositiveInteger( null )\n    false\n\n\nisPositiveInteger.isPrimitive( value )\n    Tests if a value is a number primitive having a positive integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        positive integer value.\n\n    Examples\n    --------\n    > var bool = isPositiveInteger.isPrimitive( 3.0 )\n    true\n    > bool = isPositiveInteger.isPrimitive( new Number( 3.0 ) )\n    false\n\n\nisPositiveInteger.isObject( value )\n    Tests if a value is a number object having a positive integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a positive\n        integer value.\n\n    Examples\n    --------\n    > var bool = isPositiveInteger.isObject( 3.0 )\n    false\n    > bool = isPositiveInteger.isObject( new Number( 3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger\n","isPositiveInteger.isPrimitive":"\nisPositiveInteger.isPrimitive( value )\n    Tests if a value is a number primitive having a positive integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        positive integer value.\n\n    Examples\n    --------\n    > var bool = isPositiveInteger.isPrimitive( 3.0 )\n    true\n    > bool = isPositiveInteger.isPrimitive( new Number( 3.0 ) )\n    false","isPositiveInteger.isObject":"\nisPositiveInteger.isObject( value )\n    Tests if a value is a number object having a positive integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a positive\n        integer value.\n\n    Examples\n    --------\n    > var bool = isPositiveInteger.isObject( 3.0 )\n    false\n    > bool = isPositiveInteger.isObject( new Number( 3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger","isPositiveIntegerArray":"\nisPositiveIntegerArray( value )\n    Tests if a value is an array-like object containing only positive integers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        positive integers.\n\n    Examples\n    --------\n    > var bool = isPositiveIntegerArray( [ 3.0, new Number(3.0) ] )\n    true\n    > bool = isPositiveIntegerArray( [ 3.0, '3.0' ] )\n    false\n\n\nisPositiveIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only positive primitive\n    integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        positive primitive integer values.\n\n    Examples\n    --------\n    > var bool = isPositiveIntegerArray.primitives( [ 1.0, 10.0 ] )\n    true\n    > bool = isPositiveIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n    false\n    > bool = isPositiveIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n    false\n\n\nisPositiveIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having positive integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having positive integer values.\n\n    Examples\n    --------\n    > var bool = isPositiveIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n    true\n    > bool = isPositiveIntegerArray.objects( [ 1.0, 2.0, 10.0 ] )\n    false\n    > bool = isPositiveIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray, isInteger, isPositiveInteger\n","isPositiveIntegerArray.primitives":"\nisPositiveIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only positive primitive\n    integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        positive primitive integer values.\n\n    Examples\n    --------\n    > var bool = isPositiveIntegerArray.primitives( [ 1.0, 10.0 ] )\n    true\n    > bool = isPositiveIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n    false\n    > bool = isPositiveIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n    false","isPositiveIntegerArray.objects":"\nisPositiveIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having positive integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having positive integer values.\n\n    Examples\n    --------\n    > var bool = isPositiveIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n    true\n    > bool = isPositiveIntegerArray.objects( [ 1.0, 2.0, 10.0 ] )\n    false\n    > bool = isPositiveIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray, isInteger, isPositiveInteger","isPositiveNumber":"\nisPositiveNumber( value )\n    Tests if a value is a positive number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a positive number.\n\n    Examples\n    --------\n    > var bool = isPositiveNumber( 5.0 )\n    true\n    > bool = isPositiveNumber( new Number( 5.0 ) )\n    true\n    > bool = isPositiveNumber( 3.14 )\n    true\n    > bool = isPositiveNumber( -5.0 )\n    false\n    > bool = isPositiveNumber( null )\n    false\n\n\nisPositiveNumber.isPrimitive( value )\n    Tests if a value is a number primitive having a positive value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a positive\n        value.\n\n    Examples\n    --------\n    > var bool = isPositiveNumber.isPrimitive( 3.0 )\n    true\n    > bool = isPositiveNumber.isPrimitive( new Number( 3.0 ) )\n    false\n\n\nisPositiveNumber.isObject( value )\n    Tests if a value is a number object having a positive value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a positive\n        value.\n\n    Examples\n    --------\n    > var bool = isPositiveNumber.isObject( 3.0 )\n    false\n    > bool = isPositiveNumber.isObject( new Number( 3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isNumber\n","isPositiveNumber.isPrimitive":"\nisPositiveNumber.isPrimitive( value )\n    Tests if a value is a number primitive having a positive value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a positive\n        value.\n\n    Examples\n    --------\n    > var bool = isPositiveNumber.isPrimitive( 3.0 )\n    true\n    > bool = isPositiveNumber.isPrimitive( new Number( 3.0 ) )\n    false","isPositiveNumber.isObject":"\nisPositiveNumber.isObject( value )\n    Tests if a value is a number object having a positive value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a positive\n        value.\n\n    Examples\n    --------\n    > var bool = isPositiveNumber.isObject( 3.0 )\n    false\n    > bool = isPositiveNumber.isObject( new Number( 3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isNumber","isPositiveNumberArray":"\nisPositiveNumberArray( value )\n    Tests if a value is an array-like object containing only positive numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        positive numbers.\n\n    Examples\n    --------\n    > var bool = isPositiveNumberArray( [ 3.0, new Number(3.0) ] )\n    true\n    > bool = isPositiveNumberArray( [ 3.0, '3.0' ] )\n    false\n\n\nisPositiveNumberArray.primitives( value )\n    Tests if a value is an array-like object containing only positive primitive\n    number values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        positive primitive number values.\n\n    Examples\n    --------\n    > var bool = isPositiveNumberArray.primitives( [ 1.0, 10.0 ] )\n    true\n    > bool = isPositiveNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n    false\n    > bool = isPositiveNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n    false\n\n\nisPositiveNumberArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having positive values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having positive values.\n\n    Examples\n    --------\n    > var bool = isPositiveNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n    true\n    > bool = isPositiveNumberArray.objects( [ 1.0, 2.0, 10.0 ] )\n    false\n    > bool = isPositiveNumberArray.objects( [ 3.0, new Number(1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray, isNumber, isPositiveNumber\n","isPositiveNumberArray.primitives":"\nisPositiveNumberArray.primitives( value )\n    Tests if a value is an array-like object containing only positive primitive\n    number values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        positive primitive number values.\n\n    Examples\n    --------\n    > var bool = isPositiveNumberArray.primitives( [ 1.0, 10.0 ] )\n    true\n    > bool = isPositiveNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n    false\n    > bool = isPositiveNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n    false","isPositiveNumberArray.objects":"\nisPositiveNumberArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having positive values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having positive values.\n\n    Examples\n    --------\n    > var bool = isPositiveNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n    true\n    > bool = isPositiveNumberArray.objects( [ 1.0, 2.0, 10.0 ] )\n    false\n    > bool = isPositiveNumberArray.objects( [ 3.0, new Number(1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray, isNumber, isPositiveNumber","isPositiveZero":"\nisPositiveZero( value )\n    Tests if a value is positive zero.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is positive zero.\n\n    Examples\n    --------\n    > var bool = isPositiveZero( 0.0 )\n    true\n    > bool = isPositiveZero( new Number( 0.0 ) )\n    true\n    > bool = isPositiveZero( -3.14 )\n    false\n    > bool = isPositiveZero( -0.0 )\n    false\n    > bool = isPositiveZero( null )\n    false\n\n\nisPositiveZero.isPrimitive( value )\n    Tests if a value is a number primitive equal to positive zero.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number primitive equal to\n        positive zero.\n\n    Examples\n    --------\n    > var bool = isPositiveZero.isPrimitive( 0.0 )\n    true\n    > bool = isPositiveZero.isPrimitive( new Number( 0.0 ) )\n    false\n\n\nisPositiveZero.isObject( value )\n    Tests if a value is a number object having a value equal to positive zero.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number object having a value\n        equal to positive zero.\n\n    Examples\n    --------\n    > var bool = isPositiveZero.isObject( 0.0 )\n    false\n    > bool = isPositiveZero.isObject( new Number( 0.0 ) )\n    true\n\n    See Also\n    --------\n    isNumber, isNegativeZero\n","isPositiveZero.isPrimitive":"\nisPositiveZero.isPrimitive( value )\n    Tests if a value is a number primitive equal to positive zero.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number primitive equal to\n        positive zero.\n\n    Examples\n    --------\n    > var bool = isPositiveZero.isPrimitive( 0.0 )\n    true\n    > bool = isPositiveZero.isPrimitive( new Number( 0.0 ) )\n    false","isPositiveZero.isObject":"\nisPositiveZero.isObject( value )\n    Tests if a value is a number object having a value equal to positive zero.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number object having a value\n        equal to positive zero.\n\n    Examples\n    --------\n    > var bool = isPositiveZero.isObject( 0.0 )\n    false\n    > bool = isPositiveZero.isObject( new Number( 0.0 ) )\n    true\n\n    See Also\n    --------\n    isNumber, isNegativeZero","isPrime":"\nisPrime( value )\n    Tests if a value is a prime number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a prime number.\n\n    Examples\n    --------\n    > var bool = isPrime( 5.0 )\n    true\n    > bool = isPrime( new Number( 5.0 ) )\n    true\n    > bool = isPrime( 3.14 )\n    false\n    > bool = isPrime( -5.0 )\n    false\n    > bool = isPrime( null )\n    false\n\n\nisPrime.isPrimitive( value )\n    Tests if a value is a number primitive which is a prime number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a prime\n        number.\n\n    Examples\n    --------\n    > var bool = isPrime.isPrimitive( 5.0 )\n    true\n    > bool = isPrime.isPrimitive( new Number( 5.0 ) )\n    false\n\n\nisPrime.isObject( value )\n    Tests if a value is a number object having a value which is a prime number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a prime number.\n\n    Examples\n    --------\n    > var bool = isPrime.isObject( 5.0 )\n    false\n    > bool = isPrime.isObject( new Number( 5.0 ) )\n    true\n\n\n    See Also\n    --------\n    isComposite, isInteger, isNumber\n","isPrime.isPrimitive":"\nisPrime.isPrimitive( value )\n    Tests if a value is a number primitive which is a prime number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a prime\n        number.\n\n    Examples\n    --------\n    > var bool = isPrime.isPrimitive( 5.0 )\n    true\n    > bool = isPrime.isPrimitive( new Number( 5.0 ) )\n    false","isPrime.isObject":"\nisPrime.isObject( value )\n    Tests if a value is a number object having a value which is a prime number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a prime number.\n\n    Examples\n    --------\n    > var bool = isPrime.isObject( 5.0 )\n    false\n    > bool = isPrime.isObject( new Number( 5.0 ) )\n    true\n\n\n    See Also\n    --------\n    isComposite, isInteger, isNumber","isPrimitive":"\nisPrimitive( value )\n    Tests if a value is a JavaScript primitive.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a JavaScript primitive.\n\n    Examples\n    --------\n    > var bool = isPrimitive( true )\n    true\n    > bool = isPrimitive( {} )\n    false\n\n    See Also\n    --------\n    isBoxedPrimitive\n","isPrimitiveArray":"\nisPrimitiveArray( value )\n    Tests if a value is an array-like object containing only JavaScript\n    primitives.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        JavaScript primitives.\n\n    Examples\n    --------\n    > var bool = isPrimitiveArray( [ '3', 2, null ] )\n    true\n    > bool = isPrimitiveArray( [ {}, 2, 1 ] )\n    false\n    > bool = isPrimitiveArray( [ new String('abc'), '3.0' ] )\n    false\n\n    See Also\n    --------\n    isArray, isPrimitive\n","isPRNGLike":"\nisPRNGLike( value )\n    Tests if a value is PRNG-like.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is PRNG-like.\n\n    Examples\n    --------\n    > var bool = isPRNGLike( base.random.randu )\n    true\n    > bool = isPRNGLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isPRNGLike( 3.14 )\n    false\n    > bool = isPRNGLike( {} )\n    false\n\n","isProbability":"\nisProbability( value )\n    Tests if a value is a probability.\n\n    A probability is defined as a numeric value on the interval [0,1].\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a probability.\n\n    Examples\n    --------\n    > var bool = isProbability( 0.5 )\n    true\n    > bool = isProbability( new Number( 0.5 ) )\n    true\n    > bool = isProbability( 3.14 )\n    false\n    > bool = isProbability( -5.0 )\n    false\n    > bool = isProbability( null )\n    false\n\n\nisProbability.isPrimitive( value )\n    Tests if a value is a number primitive which is a probability.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a\n        probability.\n\n    Examples\n    --------\n    > var bool = isProbability.isPrimitive( 0.3 )\n    true\n    > bool = isProbability.isPrimitive( new Number( 0.3 ) )\n    false\n\n\nisProbability.isObject( value )\n    Tests if a value is a number object having a value which is a probability.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a probability.\n\n    Examples\n    --------\n    > var bool = isProbability.isObject( 0.77 )\n    false\n    > bool = isProbability.isObject( new Number( 0.77 ) )\n    true\n\n\n    See Also\n    --------\n    isNumber\n","isProbability.isPrimitive":"\nisProbability.isPrimitive( value )\n    Tests if a value is a number primitive which is a probability.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a\n        probability.\n\n    Examples\n    --------\n    > var bool = isProbability.isPrimitive( 0.3 )\n    true\n    > bool = isProbability.isPrimitive( new Number( 0.3 ) )\n    false","isProbability.isObject":"\nisProbability.isObject( value )\n    Tests if a value is a number object having a value which is a probability.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a probability.\n\n    Examples\n    --------\n    > var bool = isProbability.isObject( 0.77 )\n    false\n    > bool = isProbability.isObject( new Number( 0.77 ) )\n    true\n\n\n    See Also\n    --------\n    isNumber","isProbabilityArray":"\nisProbabilityArray( value )\n    Tests if a value is an array-like object containing only probabilities.\n\n    A probability is defined as a numeric value on the interval [0,1].\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        probabilities.\n\n    Examples\n    --------\n    > var bool = isProbabilityArray( [ 0.5, new Number(0.8) ] )\n    true\n    > bool = isProbabilityArray( [ 0.8, 1.2 ] )\n    false\n    > bool = isProbabilityArray( [ 0.8, '0.2' ] )\n    false\n\n\nisProbabilityArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive\n    probabilities.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive probabilities.\n\n    Examples\n    --------\n    > var bool = isProbabilityArray.primitives( [ 1.0, 0.0, 0.5 ] )\n    true\n    > bool = isProbabilityArray.primitives( [ 0.3, new Number(0.4) ] )\n    false\n\n\nisProbabilityArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having probability values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having probability values.\n\n    Examples\n    --------\n    > var bool = isProbabilityArray.objects( [ new Number(0.7), new Number(1.0) ] )\n    true\n    > bool = isProbabilityArray.objects( [ 1.0, 0.0, new Number(0.7) ] )\n    false\n\n    See Also\n    --------\n    isArray, isProbability\n","isProbabilityArray.primitives":"\nisProbabilityArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive\n    probabilities.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive probabilities.\n\n    Examples\n    --------\n    > var bool = isProbabilityArray.primitives( [ 1.0, 0.0, 0.5 ] )\n    true\n    > bool = isProbabilityArray.primitives( [ 0.3, new Number(0.4) ] )\n    false","isProbabilityArray.objects":"\nisProbabilityArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having probability values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having probability values.\n\n    Examples\n    --------\n    > var bool = isProbabilityArray.objects( [ new Number(0.7), new Number(1.0) ] )\n    true\n    > bool = isProbabilityArray.objects( [ 1.0, 0.0, new Number(0.7) ] )\n    false\n\n    See Also\n    --------\n    isArray, isProbability","isPropertyKey":"\nisPropertyKey( value )\n    Tests whether a value is a property key.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether value is a property key.\n\n    Examples\n    --------\n    > var out = isPropertyKey( 'foo' )\n    true\n    > out = isPropertyKey( 1 )\n    true\n    > out = isPropertyKey( true )\n    false\n\n    See Also\n    --------\n    isString, isSymbol, isNonNegativeInteger, hasOwnProp, hasProp","isPrototypeOf":"\nisPrototypeOf( value, proto )\n    Tests if an object's prototype chain contains a provided prototype.\n\n    The function returns `false` if provided a primitive value.\n\n    This function is generally more robust than the `instanceof` operator (e.g.,\n    where inheritance is performed without using constructors).\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    proto: Object|Function\n        Prototype.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a provided prototype exists in a prototype chain.\n\n    Examples\n    --------\n    > function Foo() { return this; };\n    > function Bar() { return this; };\n    > inherit( Bar, Foo );\n    > var bar = new Bar();\n    > var bool = isPrototypeOf( bar, Foo.prototype )\n    true\n\n    See Also\n    --------\n    getPrototypeOf\n","isRaggedNestedArray":"\nisRaggedNestedArray( value )\n    Tests if a value is a ragged nested array. \n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a ragged nested array.\n\n    Examples\n    --------\n    > var bool = isRaggedNestedArray( [ [ 1, 2, 3 ], [ 4, 5 ] ] )\n    true\n    > bool = isRaggedNestedArray( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n    false\n    > bool = isRaggedNestedArray( 'beep' )\n    false\n\n","isRangeError":"\nisRangeError( value )\n    Tests if a value is a RangeError object.\n\n    This function should *not* be considered robust. While the function should\n    always return `true` if provided a RangeError (or a descendant) object,\n    false positives may occur due to the fact that the RangeError constructor\n    inherits from Error and has no internal class of its own. Hence, RangeError\n    impersonation is possible.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a RangeError object.\n\n    Examples\n    --------\n    > var bool = isRangeError( new RangeError( 'beep' ) )\n    true\n    > bool = isRangeError( {} )\n    false\n\n    See Also\n    --------\n    isError\n","isReadableProperty":"\nisReadableProperty( value, property )\n    Tests if an object's own property is readable.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own property is readable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.set = function setter( v ) { obj.boop = v; };\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isReadableProperty( obj, 'boop' )\n    true\n    > bool = isReadableProperty( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    isReadOnlyProperty, isReadWriteProperty, isReadablePropertyIn, isWritableProperty\n","isReadablePropertyIn":"\nisReadablePropertyIn( value, property )\n    Tests if an object's own or inherited property is readable.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own or inherited property is readable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.set = function setter( v ) { obj.boop = v; };\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isReadablePropertyIn( obj, 'boop' )\n    true\n    > bool = isReadablePropertyIn( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    isReadOnlyPropertyIn, isReadWritePropertyIn, isReadableProperty, isWritablePropertyIn\n","isReadOnlyProperty":"\nisReadOnlyProperty( value, property )\n    Tests if an object's own property is read-only.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own property is read-only.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = true;\n    > desc.writable = false;\n    > desc.value = true;\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isReadOnlyProperty( obj, 'boop' )\n    true\n    > bool = isReadOnlyProperty( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    isReadOnlyPropertyIn, isReadWriteProperty, isReadableProperty, isWritableProperty\n","isReadOnlyPropertyIn":"\nisReadOnlyPropertyIn( value, property )\n    Tests if an object's own or inherited property is read-only.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own or inherited property is read-\n        only.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = true;\n    > desc.writable = false;\n    > desc.value = true;\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isReadOnlyPropertyIn( obj, 'boop' )\n    true\n    > bool = isReadOnlyPropertyIn( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    isReadOnlyProperty, isReadWritePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isReadWriteProperty":"\nisReadWriteProperty( value, property )\n    Tests if an object's own property is readable and writable.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own property is readable and writable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.set = function setter( v ) { obj.boop = v; };\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isReadWriteProperty( obj, 'boop' )\n    true\n    > bool = isReadWriteProperty( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    isReadOnlyProperty, isReadWritePropertyIn, isReadableProperty, isWritableProperty\n","isReadWritePropertyIn":"\nisReadWritePropertyIn( value, property )\n    Tests if an object's own or inherited property is readable and writable.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own or inherited property is readable\n        and writable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.set = function setter( v ) { obj.boop = v; };\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isReadWritePropertyIn( obj, 'boop' )\n    true\n    > bool = isReadWritePropertyIn( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    isReadOnlyPropertyIn, isReadWriteProperty, isReadablePropertyIn, isWritablePropertyIn\n","isReferenceError":"\nisReferenceError( value )\n    Tests if a value is a ReferenceError object.\n\n    This function should *not* be considered robust. While the function should\n    always return `true` if provided a ReferenceError (or a descendant)\n    object, false positives may occur due to the fact that the ReferenceError\n    constructor inherits from Error and has no internal class of its own.\n    Hence, ReferenceError impersonation is possible.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a ReferenceError object.\n\n    Examples\n    --------\n    > var bool = isReferenceError( new ReferenceError( 'beep' ) )\n    true\n    > bool = isReferenceError( {} )\n    false\n\n    See Also\n    --------\n    isError\n","isRegExp":"\nisRegExp( value )\n    Tests if a value is a regular expression.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a regular expression.\n\n    Examples\n    --------\n    > var bool = isRegExp( /\\.+/ )\n    true\n    > bool = isRegExp( {} )\n    false\n\n","isRegExpString":"\nisRegExpString( value )\n    Tests if a value is a regular expression string.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a regular expression string.\n\n    Examples\n    --------\n    > var bool = isRegExpString( '/beep/' )\n    true\n    > bool = isRegExpString( 'beep' )\n    false\n    > bool = isRegExpString( '' )\n    false\n    > bool = isRegExpString( null )\n    false\n\n    See Also\n    --------\n    isRegExp\n","isRelativePath":"\nisRelativePath( value )\n    Tests if a value is a relative path.\n\n    Function behavior is platform-specific. On Windows platforms, the function\n    is equal to `.win32()`. On POSIX platforms, the function is equal to\n    `.posix()`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a relative path.\n\n    Examples\n    --------\n    // Windows environments:\n    > var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\n    true\n\n    // POSIX environments:\n    > bool = isRelativePath( './foo/bar/baz' )\n    true\n\n\nisRelativePath.posix( value )\n    Tests if a value is a POSIX relative path.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a POSIX relative path.\n\n    Examples\n    --------\n    > var bool = isRelativePath.posix( './foo/bar/baz' )\n    true\n    > bool = isRelativePath.posix( '/foo/../bar/baz' )\n    false\n\n\nisRelativePath.win32( value )\n    Tests if a value is a Windows relative path.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Windows relative path.\n\n    Examples\n    --------\n    > var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\n    true\n    > bool = isRelativePath( 'C:\\\\foo\\\\..\\\\bar\\\\baz' )\n    false\n\n    See Also\n    --------\n    isAbsolutePath\n","isRelativePath.posix":"\nisRelativePath.posix( value )\n    Tests if a value is a POSIX relative path.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a POSIX relative path.\n\n    Examples\n    --------\n    > var bool = isRelativePath.posix( './foo/bar/baz' )\n    true\n    > bool = isRelativePath.posix( '/foo/../bar/baz' )\n    false","isRelativePath.win32":"\nisRelativePath.win32( value )\n    Tests if a value is a Windows relative path.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Windows relative path.\n\n    Examples\n    --------\n    > var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\n    true\n    > bool = isRelativePath( 'C:\\\\foo\\\\..\\\\bar\\\\baz' )\n    false\n\n    See Also\n    --------\n    isAbsolutePath","isRelativeURI":"\nisRelativeURI( value )\n    Tests whether a value is a relative URI.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether a value is a relative URI.\n\n    Examples\n    --------\n    > var bool = isRelativeURI( '/images/example.png' )\n    true\n    > bool = isRelativeURI( 'http://www.example.com' )\n    false\n    > bool = isRelativeURI( null )\n    false\n\n    See Also\n    --------\n    isURI","isSafeInteger":"\nisSafeInteger( value )\n    Tests if a value is a safe integer.\n\n    An integer valued number is \"safe\" when the number can be exactly\n    represented as a double-precision floating-point number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a safe integer.\n\n    Examples\n    --------\n    > var bool = isSafeInteger( 5.0 )\n    true\n    > bool = isSafeInteger( new Number( 5.0 ) )\n    true\n    > bool = isSafeInteger( 2.0e200 )\n    false\n    > bool = isSafeInteger( -3.14 )\n    false\n    > bool = isSafeInteger( null )\n    false\n\n\nisSafeInteger.isPrimitive( value )\n    Tests if a value is a number primitive having a safe integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a safe\n        integer value.\n\n    Examples\n    --------\n    > var bool = isSafeInteger.isPrimitive( -3.0 )\n    true\n    > bool = isSafeInteger.isPrimitive( new Number( -3.0 ) )\n    false\n\n\nisSafeInteger.isObject( value )\n    Tests if a value is a `Number` object having a safe integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a `Number` object having a safe\n        integer value.\n\n    Examples\n    --------\n    > var bool = isSafeInteger.isObject( 3.0 )\n    false\n    > bool = isSafeInteger.isObject( new Number( 3.0 ) )\n    true\n\n    See Also\n    --------\n    isInteger, isNumber\n","isSafeInteger.isPrimitive":"\nisSafeInteger.isPrimitive( value )\n    Tests if a value is a number primitive having a safe integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a safe\n        integer value.\n\n    Examples\n    --------\n    > var bool = isSafeInteger.isPrimitive( -3.0 )\n    true\n    > bool = isSafeInteger.isPrimitive( new Number( -3.0 ) )\n    false","isSafeInteger.isObject":"\nisSafeInteger.isObject( value )\n    Tests if a value is a `Number` object having a safe integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a `Number` object having a safe\n        integer value.\n\n    Examples\n    --------\n    > var bool = isSafeInteger.isObject( 3.0 )\n    false\n    > bool = isSafeInteger.isObject( new Number( 3.0 ) )\n    true\n\n    See Also\n    --------\n    isInteger, isNumber","isSafeIntegerArray":"\nisSafeIntegerArray( value )\n    Tests if a value is an array-like object containing only safe integers.\n\n    An integer valued number is \"safe\" when the number can be exactly\n    represented as a double-precision floating-point number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing\n        only safe integers.\n\n    Examples\n    --------\n    > var arr = [ -3.0, new Number(0.0), 2.0 ];\n    > var bool = isSafeIntegerArray( arr )\n    true\n    > arr = [ -3.0, '3.0' ];\n    > bool = isSafeIntegerArray( arr )\n    false\n\n\nisSafeIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive safe\n    integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive safe integer values.\n\n    Examples\n    --------\n    > var arr = [ -1.0, 10.0 ];\n    > var bool = isSafeIntegerArray.primitives( arr )\n    true\n    > arr = [ -1.0, 0.0, 5.0 ];\n    > bool = isSafeIntegerArray.primitives( arr )\n    true\n    > arr = [ -3.0, new Number(-1.0) ];\n    > bool = isSafeIntegerArray.primitives( arr )\n    false\n\n\nisSafeIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only `Number` objects\n    having safe integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        `Number` objects having safe integer values.\n\n    Examples\n    --------\n    > var arr = [ new Number(1.0), new Number(3.0) ];\n    > var bool = isSafeIntegerArray.objects( arr )\n    true\n    > arr = [ -1.0, 0.0, 3.0 ];\n    > bool = isSafeIntegerArray.objects( arr )\n    false\n    > arr = [ 3.0, new Number(-1.0) ];\n    > bool = isSafeIntegerArray.objects( arr )\n    false\n\n    See Also\n    --------\n    isArray, isSafeInteger\n","isSafeIntegerArray.primitives":"\nisSafeIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive safe\n    integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive safe integer values.\n\n    Examples\n    --------\n    > var arr = [ -1.0, 10.0 ];\n    > var bool = isSafeIntegerArray.primitives( arr )\n    true\n    > arr = [ -1.0, 0.0, 5.0 ];\n    > bool = isSafeIntegerArray.primitives( arr )\n    true\n    > arr = [ -3.0, new Number(-1.0) ];\n    > bool = isSafeIntegerArray.primitives( arr )\n    false","isSafeIntegerArray.objects":"\nisSafeIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only `Number` objects\n    having safe integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        `Number` objects having safe integer values.\n\n    Examples\n    --------\n    > var arr = [ new Number(1.0), new Number(3.0) ];\n    > var bool = isSafeIntegerArray.objects( arr )\n    true\n    > arr = [ -1.0, 0.0, 3.0 ];\n    > bool = isSafeIntegerArray.objects( arr )\n    false\n    > arr = [ 3.0, new Number(-1.0) ];\n    > bool = isSafeIntegerArray.objects( arr )\n    false\n\n    See Also\n    --------\n    isArray, isSafeInteger","isSameArray":"\nisSameArray( v1, v2 )\n    Tests if two arguments are both generic arrays and have the same values.\n\n    The function differs from the `===` operator in that the function treats\n    `-0` and `+0` as distinct and `NaNs` as the same.\n\n    Parameters\n    ----------\n    v1: any\n        First input value.\n\n    v2: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are the same.\n\n    Examples\n    --------\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > var y = [ 1.0, 2.0, 3.0 ];\n    > var bool = isSameArray( x, y )\n    true\n\n    > x = [ NaN, NaN, NaN ];\n    > y = [ NaN, NaN, NaN ];\n    > bool = isSameArray( x, y )\n    true\n\n    See Also\n    --------\n    isArray, isEqualArray, isSameArrayLike, isSameValue\n","isSameArrayLike":"\nisSameArrayLike( v1, v2 )\n    Tests if two arguments are both array-like and have the same values.\n\n    The function differs from the `===` operator in that the function treats\n    `-0` and `+0` as distinct and `NaNs` as the same.\n\n    Parameters\n    ----------\n    v1: any\n        First input value.\n\n    v2: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are the same.\n\n    Examples\n    --------\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > var y = [ 1.0, 2.0, 3.0 ];\n    > var bool = isSameArrayLike( x, y )\n    true\n\n    > x = [ NaN, NaN, NaN ];\n    > y = [ NaN, NaN, NaN ];\n    > bool = isSameArrayLike( x, y )\n    true\n\n    See Also\n    --------\n    isArrayLike, isSameArray, isSameValue\n","isSameComplex64":"\nisSameComplex64( v1, v2 )\n    Tests if two arguments are both single-precision complex floating-point\n    numbers and have the same value.\n\n    The function differs from the `===` operator in that the function treats\n    `-0` and `+0` as distinct and `NaNs` as the same.\n\n    Parameters\n    ----------\n    v1: any\n        First input value.\n\n    v2: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are the same.\n\n    Examples\n    --------\n    > var x = new Complex64( 1.0, 2.0 );\n    > var y = new Complex64( 1.0, 2.0 );\n    > var bool = isSameComplex64( x, y )\n    true\n\n    > x = new Complex64( NaN, NaN );\n    > y = new Complex64( NaN, NaN );\n    > bool = isSameComplex64( x, y )\n    true\n\n    See Also\n    --------\n    isComplex64, isSameComplex128, isSameValue\n","isSameComplex64Array":"\nisSameComplex64Array( v1, v2 )\n    Tests if two arguments are both Complex64Arrays and have the same values.\n\n    The function differs from the `===` operator in that the function treats\n    `-0` and `+0` as distinct and `NaNs` as the same.\n\n    Parameters\n    ----------\n    v1: any\n        First input value.\n\n    v2: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are the same.\n\n    Examples\n    --------\n    > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var bool = isSameComplex64Array( x, y )\n    true\n\n    > x = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\n    > y = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\n    > bool = isSameComplex64Array( x, y )\n    true\n\n    See Also\n    --------\n    isComplex64Array, isSameComplex128Array, isSameFloat32Array, isSameValue\n","isSameComplex128":"\nisSameComplex128( v1, v2 )\n    Tests if two arguments are both double-precision complex floating-point\n    numbers and have the same value.\n\n    The function differs from the `===` operator in that the function treats\n    `-0` and `+0` as distinct and `NaNs` as the same.\n\n    Parameters\n    ----------\n    v1: any\n        First input value.\n\n    v2: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are the same.\n\n    Examples\n    --------\n    > var x = new Complex128( 1.0, 2.0 );\n    > var y = new Complex128( 1.0, 2.0 );\n    > var bool = isSameComplex128( x, y )\n    true\n\n    > x = new Complex128( NaN, NaN );\n    > y = new Complex128( NaN, NaN );\n    > bool = isSameComplex128( x, y )\n    true\n\n    See Also\n    --------\n    isComplex128, isSameComplex64, isSameValue\n","isSameComplex128Array":"\nisSameComplex128Array( v1, v2 )\n    Tests if two arguments are both Complex128Arrays and have the same values.\n\n    The function differs from the `===` operator in that the function treats\n    `-0` and `+0` as distinct and `NaNs` as the same.\n\n    Parameters\n    ----------\n    v1: any\n        First input value.\n\n    v2: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are the same.\n\n    Examples\n    --------\n    > var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var bool = isSameComplex128Array( x, y )\n    true\n\n    > x = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\n    > y = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\n    > bool = isSameComplex128Array( x, y )\n    true\n\n    See Also\n    --------\n    isComplex128Array, isSameComplex64Array, isSameFloat64Array, isSameValue\n","isSameDateObject":"\nisSameDateObject( d1, d2 )\n    Tests if two values are both Date objects corresponding \n    to the same date and time.\n\n    Parameters\n    ----------\n    d1: any\n        First input value.\n    d2: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether both values are Date objects \n        corresponding to the same date and time.\n\n    Examples\n    --------\n    > var d1 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\n    > var d2 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\n    > var bool = isSameDateObject( d1, d2 )\n    true\n    > var d1 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\n    > var d2 = new Date( 2024, 11, 31, 23, 59, 59, 78 );\n    > var bool = isSameDateObject( d1, d2 )\n    false\n \n    See Also\n    --------\n    isDateObject, isSameValue\n","isSameFloat32Array":"\nisSameFloat32Array( v1, v2 )\n    Tests if two arguments are both Float32Arrays and have the same values.\n\n    The function differs from the `===` operator in that the function treats\n    `-0` and `+0` as distinct and `NaNs` as the same.\n\n    Parameters\n    ----------\n    v1: any\n        First input value.\n\n    v2: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are the same.\n\n    Examples\n    --------\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > var y = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > var bool = isSameFloat32Array( x, y )\n    true\n\n    > x = new Float32Array( [ NaN, NaN, NaN ] );\n    > y = new Float32Array( [ NaN, NaN, NaN ] );\n    > bool = isSameFloat32Array( x, y )\n    true\n\n    See Also\n    --------\n    isSameFloat64Array, isSameValue\n","isSameFloat64Array":"\nisSameFloat64Array( v1, v2 )\n    Tests if two arguments are both Float64Arrays and have the same values.\n\n    The function differs from the `===` operator in that the function treats\n    `-0` and `+0` as distinct and `NaNs` as the same.\n\n    Parameters\n    ----------\n    v1: any\n        First input value.\n\n    v2: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are the same.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > var bool = isSameFloat64Array( x, y )\n    true\n\n    > x = new Float64Array( [ NaN, NaN, NaN ] );\n    > y = new Float64Array( [ NaN, NaN, NaN ] );\n    > bool = isSameFloat64Array( x, y )\n    true\n\n    See Also\n    --------\n    isSameFloat32Array, isSameValue\n","isSameNativeClass":"\nisSameNativeClass( a, b )\n    Tests if two arguments have the same native class.\n\n    Parameters\n    ----------\n    a: any\n        First input value.\n\n    b: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments have the same native class.\n\n    Examples\n    --------\n    > var bool = isSameNativeClass( 3.14, new Number( 3.14 ) )\n    true\n    > bool = isSameNativeClass( 'beep', 'boop' )\n    true\n    > bool = isSameNativeClass( {}, [] )\n    false\n\n    See Also\n    --------\n    isSameType, isSameValue, isStrictEqual\n","isSameType":"\nisSameType( a, b )\n    Tests if two arguments have the same type.\n\n    The function uses the `typeof` operator to test for the same type.\n\n    Parameters\n    ----------\n    a: any\n        First input value.\n\n    b: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments have the same type.\n\n    Examples\n    --------\n    > var bool = isSameType( true, true )\n    true\n    > bool = isSameType( {}, [] )\n    true\n    > bool = isSameType( 3.12, -3.12 )\n    true\n    > bool = isSameType( 0.0, '0.0' )\n    false\n\n    See Also\n    --------\n    isSameNativeClass, isSameValue, isStrictEqual\n","isSameValue":"\nisSameValue( a, b )\n    Tests if two arguments are the same value.\n\n    The function differs from the `===` operator in that the function treats\n    `-0` and `+0` as distinct and `NaNs` as the same.\n\n    Parameters\n    ----------\n    a: any\n        First input value.\n\n    b: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are the same value.\n\n    Examples\n    --------\n    > var bool = isSameValue( true, true )\n    true\n    > bool = isSameValue( {}, {} )\n    false\n    > bool = isSameValue( -0.0, -0.0 )\n    true\n    > bool = isSameValue( -0.0, 0.0 )\n    false\n    > bool = isSameValue( NaN, NaN )\n    true\n\n    See Also\n    --------\n    isSameValueZero, isStrictEqual\n","isSameValueZero":"\nisSameValueZero( a, b )\n    Tests if two arguments are the same value.\n\n    The function differs from the `===` operator in that the function treats\n    `NaNs` as the same.\n\n    Parameters\n    ----------\n    a: any\n        First input value.\n\n    b: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are the same value.\n\n    Examples\n    --------\n    > var bool = isSameValueZero( true, true )\n    true\n    > bool = isSameValueZero( {}, {} )\n    false\n    > bool = isSameValueZero( -0.0, -0.0 )\n    true\n    > bool = isSameValueZero( -0.0, 0.0 )\n    true\n    > bool = isSameValueZero( NaN, NaN )\n    true\n\n    See Also\n    --------\n    isSameValue, isStrictEqual\n","isSemVer":"\nisSemVer( value )\n    Tests if a value is a semantic version string.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether a provided value is a semantic version\n        string.\n\n    Examples\n    --------\n    > var bool = isSemVer( '1.0.0' )\n    true\n    > bool = isSemVer( '1.0.0-alpha.1' )\n    true\n    > bool = isSemVer( '0.1' )\n    false\n    > bool = isSemVer( null )\n    false\n","isSharedArrayBuffer":"\nisSharedArrayBuffer( value )\n    Tests if a value is a SharedArrayBuffer.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a SharedArrayBuffer.\n\n    Examples\n    --------\n    // Assuming an environment supports SharedArrayBuffer...\n    > var bool = isSharedArrayBuffer( new SharedArrayBuffer( 10 ) )\n    true\n    > bool = isSharedArrayBuffer( [] )\n    false\n\n    See Also\n    --------\n    isArrayBuffer, isTypedArray\n","isSkewCentrosymmetricMatrix":"\nisSkewCentrosymmetricMatrix( value )\n    Tests if a value is a skew-centrosymmetric matrix.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a skew-centrosymmetric matrix.\n\n    Examples\n    --------\n    > var buf = [ 2, 1, -1, -2 ];\n    > var sh = [ 2, 2 ];\n    > var st = [ 2, 1 ];\n    > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n    > var bool = isSkewCentrosymmetricMatrix( M )\n    true\n    > bool = isSkewCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isSkewCentrosymmetricMatrix( 3.14 )\n    false\n    > bool = isSkewCentrosymmetricMatrix( {} )\n    false\n\n    See Also\n    --------\n    isCentrosymmetricMatrix, isMatrixLike, isSkewSymmetricMatrix\n","isSkewPersymmetricMatrix":"\nisSkewPersymmetricMatrix( value )\n    Tests if a value is a skew-persymmetric matrix.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a skew-persymmetric matrix.\n\n    Examples\n    --------\n    > var buf = [ 1, 0, 0, -1 ];\n    > var sh = [ 2, 2 ];\n    > var st = [ 2, 1 ];\n    > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n    > var bool = isSkewPersymmetricMatrix( M )\n    true\n    > bool = isSkewPersymmetricMatrix( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isSkewPersymmetricMatrix( 3.14 )\n    false\n    > bool = isSkewPersymmetricMatrix( {} )\n    false\n\n    See Also\n    --------\n    isMatrixLike, isPersymmetricMatrix, isSkewSymmetricMatrix\n","isSkewSymmetricMatrix":"\nisSkewSymmetricMatrix( value )\n    Tests if a value is a skew-symmetric (or antisymmetric) matrix.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a skew-symmetric matrix.\n\n    Examples\n    --------\n    > var buf = [ 0, -1, 1, 0 ];\n    > var sh = [ 2, 2 ];\n    > var st = [ 2, 1 ];\n    > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n    > var bool = isSkewSymmetricMatrix( M )\n    true\n    > bool = isSkewSymmetricMatrix( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isSkewSymmetricMatrix( 3.14 )\n    false\n    > bool = isSkewSymmetricMatrix( {} )\n    false\n\n    See Also\n    --------\n    isMatrixLike, isSkewSymmetricMatrix, isSquareMatrix\n","isSlice":"\nisSlice( value )\n    Tests if a value is a Slice object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a Slice object.\n\n    Examples\n    --------\n    > var bool = isSlice( new Slice( 10 ) )\n    true\n    > bool = isSlice( 3.14 )\n    false\n    > bool = isSlice( {} )\n    false\n\n    See Also\n    --------\n    isMultiSlice, Slice\n","isSnakecase":"\nisSnakecase( value )\n    Tests if a value is a string in snake case.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a string in snake case.\n\n    Examples\n    --------\n    > var bool = isSnakecase( 'hello_world' )\n    true\n    > bool = isSnakecase( 'Hello World' )\n    false\n\n    See Also\n    --------\n    isString","isSquareMatrix":"\nisSquareMatrix( value )\n    Tests if a value is a 2-dimensional ndarray-like object having equal\n    dimensions.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 2-dimensional ndarray-like\n        object having equal dimensions.\n\n    Examples\n    --------\n    > var buf = [ 0, 0, 0, 0 ];\n    > var sh = [ 2, 2 ];\n    > var st = [ 2, 1 ];\n    > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n    > var bool = isSquareMatrix( M )\n    true\n    > bool = isSquareMatrix( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isSquareMatrix( 3.14 )\n    false\n    > bool = isSquareMatrix( {} )\n    false\n\n    See Also\n    --------\n    isMatrixLike, isSymmetricMatrix\n","isSquareNumber":"\nisSquareNumber( value )\n    Tests if a value is a square number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a square number.\n\n    Examples\n    --------\n    > var bool = isSquareNumber( 4.0 )\n    true\n    > bool = isSquareNumber( new Number( 4.0 ) )\n    true\n    > bool = isSquareNumber( 3.14 )\n    false\n    > bool = isSquareNumber( -5.0 )\n    false\n    > bool = isSquareNumber( null )\n    false\n\n\nisSquareNumber.isPrimitive( value )\n    Tests if a value is a number primitive which is a square number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a\n        square number.\n\n    Examples\n    --------\n    > var bool = isSquareNumber.isPrimitive( 4.0 )\n    true\n    > bool = isSquareNumber.isPrimitive( new Number( 4.0 ) )\n    false\n\n\nisSquareNumber.isObject( value )\n    Tests if a value is a number object having a value which is a square number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a square number.\n\n    Examples\n    --------\n    > var bool = isSquareNumber.isObject( 4.0 )\n    false\n    > bool = isSquareNumber.isObject( new Number( 4.0 ) )\n    true\n\n\n    See Also\n    --------\n    isCubeNumber, isInteger, isNumber, isTriangularNumber\n","isSquareNumber.isPrimitive":"\nisSquareNumber.isPrimitive( value )\n    Tests if a value is a number primitive which is a square number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a\n        square number.\n\n    Examples\n    --------\n    > var bool = isSquareNumber.isPrimitive( 4.0 )\n    true\n    > bool = isSquareNumber.isPrimitive( new Number( 4.0 ) )\n    false","isSquareNumber.isObject":"\nisSquareNumber.isObject( value )\n    Tests if a value is a number object having a value which is a square number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a square number.\n\n    Examples\n    --------\n    > var bool = isSquareNumber.isObject( 4.0 )\n    false\n    > bool = isSquareNumber.isObject( new Number( 4.0 ) )\n    true\n\n\n    See Also\n    --------\n    isCubeNumber, isInteger, isNumber, isTriangularNumber","isSquareTriangularNumber":"\nisSquareTriangularNumber( value )\n    Tests if a value is a square triangular number.\n\n    Return values are not reliable for numbers greater than 1125899906842624.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a square triangular number.\n\n    Examples\n    --------\n    > var bool = isSquareTriangularNumber( 36.0 )\n    true\n    > bool = isSquareTriangularNumber( new Number( 36.0 ) )\n    true\n    > bool = isSquareTriangularNumber( 3.14 )\n    false\n    > bool = isSquareTriangularNumber( -5.0 )\n    false\n    > bool = isSquareTriangularNumber( null )\n    false\n\n\nisSquareTriangularNumber.isPrimitive( value )\n    Tests if a value is a number primitive which is a square triangular number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a\n        square triangular number.\n\n    Examples\n    --------\n    > var bool = isSquareTriangularNumber.isPrimitive( 36.0 )\n    true\n    > bool = isSquareTriangularNumber.isPrimitive( new Number( 36.0 ) )\n    false\n\n\nisSquareTriangularNumber.isObject( value )\n    Tests if a value is a number object having a value which is a square\n    triangular number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a square triangular number.\n\n    Examples\n    --------\n    > var bool = isSquareTriangularNumber.isObject( 36.0 )\n    false\n    > bool = isSquareTriangularNumber.isObject( new Number( 36.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger, isNumber, isSquareNumber, isTriangularNumber\n","isSquareTriangularNumber.isPrimitive":"\nisSquareTriangularNumber.isPrimitive( value )\n    Tests if a value is a number primitive which is a square triangular number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a\n        square triangular number.\n\n    Examples\n    --------\n    > var bool = isSquareTriangularNumber.isPrimitive( 36.0 )\n    true\n    > bool = isSquareTriangularNumber.isPrimitive( new Number( 36.0 ) )\n    false","isSquareTriangularNumber.isObject":"\nisSquareTriangularNumber.isObject( value )\n    Tests if a value is a number object having a value which is a square\n    triangular number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a square triangular number.\n\n    Examples\n    --------\n    > var bool = isSquareTriangularNumber.isObject( 36.0 )\n    false\n    > bool = isSquareTriangularNumber.isObject( new Number( 36.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger, isNumber, isSquareNumber, isTriangularNumber","isStartcase":"\nisStartcase( value )\n    Tests if a value is a startcase string.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if value is a startcase string.\n\n    Examples\n    --------\n    > var bool = isStartcase( 'Beep Boop' )\n    true\n    > bool = isStartcase( 'Beep and Boop' )\n    false\n\n    See Also\n    --------\n    isString","isStrictEqual":"\nisStrictEqual( a, b )\n    Tests if two arguments are strictly equal.\n\n    The function differs from the `===` operator in that the function treats\n    `-0` and `+0` as distinct.\n\n    Parameters\n    ----------\n    a: any\n        First input value.\n\n    b: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are strictly equal.\n\n    Examples\n    --------\n    > var bool = isStrictEqual( true, true )\n    true\n    > bool = isStrictEqual( {}, {} )\n    false\n    > bool = isStrictEqual( -0.0, -0.0 )\n    true\n    > bool = isStrictEqual( -0.0, 0.0 )\n    false\n    > bool = isStrictEqual( NaN, NaN )\n    false\n\n    See Also\n    --------\n    isSameValue\n","isString":"\nisString( value )\n    Tests if a value is a string.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a string.\n\n    Examples\n    --------\n    > var bool = isString( 'beep' )\n    true\n    > bool = isString( new String( 'beep' ) )\n    true\n    > bool = isString( 5 )\n    false\n\n\nisString.isPrimitive( value )\n    Tests if a value is a string primitive.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a string primitive.\n\n    Examples\n    --------\n    > var bool = isString.isPrimitive( 'beep' )\n    true\n    > bool = isString.isPrimitive( new String( 'beep' ) )\n    false\n\n\nisString.isObject( value )\n    Tests if a value is a `String` object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a `String` object.\n\n    Examples\n    --------\n    > var bool = isString.isObject( new String( 'beep' ) )\n    true\n    > bool = isString.isObject( 'beep' )\n    false\n\n","isString.isPrimitive":"\nisString.isPrimitive( value )\n    Tests if a value is a string primitive.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a string primitive.\n\n    Examples\n    --------\n    > var bool = isString.isPrimitive( 'beep' )\n    true\n    > bool = isString.isPrimitive( new String( 'beep' ) )\n    false","isString.isObject":"\nisString.isObject( value )\n    Tests if a value is a `String` object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a `String` object.\n\n    Examples\n    --------\n    > var bool = isString.isObject( new String( 'beep' ) )\n    true\n    > bool = isString.isObject( 'beep' )\n    false","isStringArray":"\nisStringArray( value )\n    Tests if a value is an array of strings.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array of strings.\n\n    Examples\n    --------\n    > var bool = isStringArray( [ 'abc', 'def' ] )\n    true\n    > bool = isStringArray( [ 'abc', 123 ] )\n    false\n\n\nisStringArray.primitives( value )\n    Tests if a value is an array containing only string primitives.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array containing only string\n        primitives.\n\n    Examples\n    --------\n    > var arr = [ 'abc', 'def' ];\n    > var bool = isStringArray.primitives( arr )\n    true\n    > arr = [ 'abc', new String( 'def' ) ];\n    > bool = isStringArray.primitives( arr )\n    false\n\n\nisStringArray.objects( value )\n    Tests if a value is an array containing only `String` objects.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array containing only `String`\n        objects.\n\n    Examples\n    --------\n    > var arr = [ new String( 'ab' ), new String( 'cd' ) ];\n    > var bool = isStringArray.objects( arr )\n    true\n    > arr = [ new String( 'abc' ), 'def' ];\n    > bool = isStringArray.objects( arr )\n    false\n\n    See Also\n    --------\n    isArray, isString\n","isStringArray.primitives":"\nisStringArray.primitives( value )\n    Tests if a value is an array containing only string primitives.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array containing only string\n        primitives.\n\n    Examples\n    --------\n    > var arr = [ 'abc', 'def' ];\n    > var bool = isStringArray.primitives( arr )\n    true\n    > arr = [ 'abc', new String( 'def' ) ];\n    > bool = isStringArray.primitives( arr )\n    false","isStringArray.objects":"\nisStringArray.objects( value )\n    Tests if a value is an array containing only `String` objects.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array containing only `String`\n        objects.\n\n    Examples\n    --------\n    > var arr = [ new String( 'ab' ), new String( 'cd' ) ];\n    > var bool = isStringArray.objects( arr )\n    true\n    > arr = [ new String( 'abc' ), 'def' ];\n    > bool = isStringArray.objects( arr )\n    false\n\n    See Also\n    --------\n    isArray, isString","isSymbol":"\nisSymbol( value )\n    Tests if a value is a symbol.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a symbol.\n\n    Examples\n    --------\n    > var bool = isSymbol( Symbol( 'beep' ) )\n    true\n    > bool = isSymbol( Object( Symbol( 'beep' ) ) )\n    true\n    > bool = isSymbol( {} )\n    false\n    > bool = isSymbol( null )\n    false\n    > bool = isSymbol( true )\n    false\n\n","isSymbolArray":"\nisSymbolArray( value )\n    Tests if a value is an array-like object containing only symbols.\n\n    In pre-ES2015 environments, the function always returns `false`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only symbols.\n\n    Examples\n    --------\n    > var bool = isSymbolArray( [ Symbol( 'beep' ), Symbol( 'boop' ) ] )\n    true\n    > bool = isSymbolArray( Symbol( 'beep' ) )\n    false\n    > bool = isSymbolArray( [] )\n    false\n    > bool = isSymbolArray( {} )\n    false\n    > bool = isSymbolArray( null )\n    false\n    > bool = isSymbolArray( true )\n    false\n\n\nisSymbolArray.primitives( value )\n    Tests if a value is an array-like object containing only `symbol`\n    primitives.\n\n    In pre-ES2015 environments, the function always returns `false`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only `symbol` primitives.\n\n    Examples\n    --------\n    > var bool = isSymbolArray.primitives( [ Symbol( 'beep' ) ] )\n    true\n    > bool = isSymbolArray.primitives( [ Object( Symbol( 'beep' ) ) ] )\n    false\n    > bool = isSymbolArray.primitives( [] )\n    false\n    > bool = isSymbolArray.primitives( {} )\n    false\n    > bool = isSymbolArray.primitives( null )\n    false\n    > bool = isSymbolArray.primitives( true )\n    false\n\n\nisSymbolArray.objects( value )\n    Tests if a value is an array-like object containing only `Symbol`\n    objects.\n\n    In pre-ES2015 environments, the function always returns `false`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only `Symbol` objects.\n\n    Examples\n    --------\n    > var bool = isSymbolArray.objects( [ Object( Symbol( 'beep' ) ) ] )\n    true\n    > bool = isSymbolArray.objects( [ Symbol( 'beep' ) ] )\n    false\n    > bool = isSymbolArray.objects( [] )\n    false\n    > bool = isSymbolArray.objects( {} )\n    false\n    > bool = isSymbolArray.objects( null )\n    false\n    > bool = isSymbolArray.objects( true )\n    false\n\n    See Also\n    --------\n    isArray, isSymbol\n","isSymbolArray.primitives":"\nisSymbolArray.primitives( value )\n    Tests if a value is an array-like object containing only `symbol`\n    primitives.\n\n    In pre-ES2015 environments, the function always returns `false`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only `symbol` primitives.\n\n    Examples\n    --------\n    > var bool = isSymbolArray.primitives( [ Symbol( 'beep' ) ] )\n    true\n    > bool = isSymbolArray.primitives( [ Object( Symbol( 'beep' ) ) ] )\n    false\n    > bool = isSymbolArray.primitives( [] )\n    false\n    > bool = isSymbolArray.primitives( {} )\n    false\n    > bool = isSymbolArray.primitives( null )\n    false\n    > bool = isSymbolArray.primitives( true )\n    false","isSymbolArray.objects":"\nisSymbolArray.objects( value )\n    Tests if a value is an array-like object containing only `Symbol`\n    objects.\n\n    In pre-ES2015 environments, the function always returns `false`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only `Symbol` objects.\n\n    Examples\n    --------\n    > var bool = isSymbolArray.objects( [ Object( Symbol( 'beep' ) ) ] )\n    true\n    > bool = isSymbolArray.objects( [ Symbol( 'beep' ) ] )\n    false\n    > bool = isSymbolArray.objects( [] )\n    false\n    > bool = isSymbolArray.objects( {} )\n    false\n    > bool = isSymbolArray.objects( null )\n    false\n    > bool = isSymbolArray.objects( true )\n    false\n\n    See Also\n    --------\n    isArray, isSymbol","isSymmetricMatrix":"\nisSymmetricMatrix( value )\n    Tests if a value is a square matrix which equals its transpose.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a symmetric matrix.\n\n    Examples\n    --------\n    > var buf = [ 0, 1, 1, 2 ];\n    > var sh = [ 2, 2 ];\n    > var st = [ 2, 1 ];\n    > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n    > var bool = isSymmetricMatrix( M )\n    true\n    > bool = isSymmetricMatrix( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isSymmetricMatrix( 3.14 )\n    false\n    > bool = isSymmetricMatrix( {} )\n    false\n\n    See Also\n    --------\n    isMatrixLike, isNonSymmetricMatrix, isSquareMatrix\n","isSyntaxError":"\nisSyntaxError( value )\n    Tests if a value is a SyntaxError object.\n\n    This function should *not* be considered robust. While the function should\n    always return `true` if provided a SyntaxError (or a descendant) object,\n    false positives may occur due to the fact that the SyntaxError constructor\n    inherits from Error and has no internal class of its own. Hence, SyntaxError\n    impersonation is possible.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a SyntaxError object.\n\n    Examples\n    --------\n    > var bool = isSyntaxError( new SyntaxError( 'beep' ) )\n    true\n    > bool = isSyntaxError( {} )\n    false\n\n    See Also\n    --------\n    isError\n","isTriangularNumber":"\nisTriangularNumber( value )\n    Tests if a value is a triangular number.\n\n    Return values are not reliable for numbers greater than 1125899906842624.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a triangular number.\n\n    Examples\n    --------\n    > var bool = isTriangularNumber( 36.0 )\n    true\n    > bool = isTriangularNumber( new Number( 36.0 ) )\n    true\n    > bool = isTriangularNumber( 3.14 )\n    false\n    > bool = isTriangularNumber( -5.0 )\n    false\n    > bool = isTriangularNumber( null )\n    false\n\n\nisTriangularNumber.isPrimitive( value )\n    Tests if a value is a number primitive which is a triangular number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a\n        triangular number.\n\n    Examples\n    --------\n    > var bool = isTriangularNumber.isPrimitive( 36.0 )\n    true\n    > bool = isTriangularNumber.isPrimitive( new Number( 36.0 ) )\n    false\n\n\nisTriangularNumber.isObject( value )\n    Tests if a value is a number object having a value which is a triangular\n    number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a triangular number.\n\n    Examples\n    --------\n    > var bool = isTriangularNumber.isObject( 36.0 )\n    false\n    > bool = isTriangularNumber.isObject( new Number( 36.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger, isNumber, isSquareNumber, isSquareTriangularNumber\n","isTriangularNumber.isPrimitive":"\nisTriangularNumber.isPrimitive( value )\n    Tests if a value is a number primitive which is a triangular number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a\n        triangular number.\n\n    Examples\n    --------\n    > var bool = isTriangularNumber.isPrimitive( 36.0 )\n    true\n    > bool = isTriangularNumber.isPrimitive( new Number( 36.0 ) )\n    false","isTriangularNumber.isObject":"\nisTriangularNumber.isObject( value )\n    Tests if a value is a number object having a value which is a triangular\n    number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a triangular number.\n\n    Examples\n    --------\n    > var bool = isTriangularNumber.isObject( 36.0 )\n    false\n    > bool = isTriangularNumber.isObject( new Number( 36.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger, isNumber, isSquareNumber, isSquareTriangularNumber","isTruthy":"\nisTruthy( value )\n    Tests if a value is a value which translates to `true` when evaluated in a\n    boolean context.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is truthy.\n\n    Examples\n    --------\n     > var bool = isTruthy( true )\n    true\n    > bool = isTruthy( {} )\n    true\n    > bool = isTruthy( [] )\n    true\n    > bool = isTruthy( false )\n    false\n    > bool = isTruthy( '' )\n    false\n    > bool = isTruthy( 0 )\n    false\n    > bool = isTruthy( null )\n    false\n    > bool = isTruthy( void 0 )\n    false\n    > bool = isTruthy( NaN )\n    false\n\n    See Also\n    --------\n    isFalsy\n","isTruthyArray":"\nisTruthyArray( value )\n    Tests if a value is an array-like object containing only truthy values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only truthy values.\n\n    Examples\n    --------\n    > var bool = isTruthyArray( [ {}, [] ] )\n    true\n    > bool = isTruthyArray( [ null, '' ] )\n    false\n    > bool = isTruthyArray( [] )\n    false\n\n    See Also\n    --------\n    isFalsyArray, isTruthy\n","isTypedArray":"\nisTypedArray( value )\n    Tests if a value is a typed array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a typed array.\n\n    Examples\n    --------\n    > var bool = isTypedArray( new Int8Array( 10 ) )\n    true\n\n    See Also\n    --------\n    isArray, isTypedArrayLike\n","isTypedArrayLength":"\nisTypedArrayLength( value )\n    Tests if a value is a valid typed array length.\n\n    A valid length property for a typed array instance is any integer value on\n    the interval [0, 2^53-1].\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a valid typed array length.\n\n    Examples\n    --------\n    > var bool = isTypedArrayLength( 5 )\n    true\n    > bool = isTypedArrayLength( 2.0e200 )\n    false\n    > bool = isTypedArrayLength( -3.14 )\n    false\n    > bool = isTypedArrayLength( null )\n    false\n\n    See Also\n    --------\n    isArrayLength, isTypedArray\n","isTypedArrayLike":"\nisTypedArrayLike( value )\n    Tests if a value is typed-array-like.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is typed-array-like.\n\n    Examples\n    --------\n    > var bool = isTypedArrayLike( new Int16Array() )\n    true\n    > bool = isTypedArrayLike({\n    ...    'length': 10,\n    ...    'byteOffset': 0,\n    ...    'byteLength': 10,\n    ...    'BYTES_PER_ELEMENT': 4\n    ... })\n    true\n\n    See Also\n    --------\n    isTypedArray\n","isTypeError":"\nisTypeError( value )\n    Tests if a value is a TypeError object.\n\n    This function should *not* be considered robust. While the function should\n    always return `true` if provided a TypeError (or a descendant) object,\n    false positives may occur due to the fact that the TypeError constructor\n    inherits from Error and has no internal class of its own. Hence, TypeError\n    impersonation is possible.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a TypeError object.\n\n    Examples\n    --------\n    > var bool = isTypeError( new TypeError( 'beep' ) )\n    true\n    > bool = isTypeError( {} )\n    false\n\n    See Also\n    --------\n    isError\n","isUint8Array":"\nisUint8Array( value )\n    Tests if a value is a Uint8Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Uint8Array.\n\n    Examples\n    --------\n    > var bool = isUint8Array( new Uint8Array( 10 ) )\n    true\n    > bool = isUint8Array( [] )\n    false\n\n    See Also\n    --------\n    isTypedArray, isUint16Array, isUint32Array\n","isUint8ClampedArray":"\nisUint8ClampedArray( value )\n    Tests if a value is a Uint8ClampedArray.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Uint8ClampedArray.\n\n    Examples\n    --------\n    > var bool = isUint8ClampedArray( new Uint8ClampedArray( 10 ) )\n    true\n    > bool = isUint8ClampedArray( [] )\n    false\n\n    See Also\n    --------\n    isTypedArray, isUint8Array\n","isUint16Array":"\nisUint16Array( value )\n    Tests if a value is a Uint16Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Uint16Array.\n\n    Examples\n    --------\n    > var bool = isUint16Array( new Uint16Array( 10 ) )\n    true\n    > bool = isUint16Array( [] )\n    false\n\n    See Also\n    --------\n    isTypedArray, isUint32Array, isUint8Array\n","isUint32Array":"\nisUint32Array( value )\n    Tests if a value is a Uint32Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Uint32Array.\n\n    Examples\n    --------\n    > var bool = isUint32Array( new Uint32Array( 10 ) )\n    true\n    > bool = isUint32Array( [] )\n    false\n\n    See Also\n    --------\n    isTypedArray, isUint16Array, isUint8Array\n","isUNCPath":"\nisUNCPath( value )\n    Tests if a value is a UNC path.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a UNC path.\n\n    Examples\n    --------\n    > var bool = isUNCPath( '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz' )\n    true\n    > bool = isUNCPath( '/foo/bar/baz' )\n    false\n\n","isUndefined":"\nisUndefined( value )\n    Tests if a value is undefined.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is undefined.\n\n    Examples\n    --------\n    > var bool = isUndefined( void 0 )\n    true\n    > bool = isUndefined( null )\n    false\n\n    See Also\n    --------\n    isNull, isUndefinedOrNull\n","isUndefinedOrNull":"\nisUndefinedOrNull( value )\n    Tests if a value is undefined or null.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is undefined or null.\n\n    Examples\n    --------\n    > var bool = isUndefinedOrNull( void 0 )\n    true\n    > bool = isUndefinedOrNull( null )\n    true\n    > bool = isUndefinedOrNull( false )\n    false\n\n    See Also\n    --------\n    isNull, isUndefined\n","isUnityProbabilityArray":"\nisUnityProbabilityArray( value )\n    Tests if a value is an array of probabilities that sum to one.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array of probabilities that sum\n        to one.\n\n    Examples\n    --------\n    > var bool = isUnityProbabilityArray( [ 0.25, 0.5, 0.25 ] )\n    true\n    > bool = isUnityProbabilityArray( new Uint8Array( [ 0, 1 ] ) )\n    true\n    > bool = isUnityProbabilityArray( [ 0.4, 0.4, 0.4 ] )\n    false\n    > bool = isUnityProbabilityArray( [ 3.14, 0.0 ] )\n    false\n\n    See Also\n    --------\n    isProbability, isProbabilityArray\n","isUppercase":"\nisUppercase( value )\n    Tests if a value is an uppercase string.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an uppercase string.\n\n    Examples\n    --------\n    > var bool = isUppercase( 'HELLO' )\n    true\n    > bool = isUppercase( 'World' )\n    false\n\n    See Also\n    --------\n    isLowercase, isString\n","isURI":"\nisURI( value )\n    Tests if a value is a URI.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a URI.\n\n    Examples\n    --------\n    > var bool = isURI( 'http://google.com' )\n    true\n    > bool = isURI( 'http://localhost/' )\n    true\n    > bool = isURI( 'http://example.w3.org/path%20with%20spaces.html' )\n    true\n    > bool = isURI( 'ftp://ftp.is.co.za/rfc/rfc1808.txt' )\n    true\n\n    // No scheme:\n    > bool = isURI( '' )\n    false\n    > bool = isURI( 'foo@bar' )\n    false\n    > bool = isURI( '://foo/' )\n    false\n\n    // Illegal characters:\n    > bool = isURI( 'http://<foo>' )\n    false\n\n    // Invalid path:\n    > bool = isURI( 'http:////foo.html' )\n    false\n\n    // Incomplete hex escapes:\n    > bool = isURI( 'http://example.w3.org/%a' )\n    false\n\n","isURIError":"\nisURIError( value )\n    Tests if a value is a URIError object.\n\n    This function should *not* be considered robust. While the function should\n    always return `true` if provided a URIError (or a descendant) object,\n    false positives may occur due to the fact that the URIError constructor\n    inherits from Error and has no internal class of its own. Hence, URIError\n    impersonation is possible.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a URIError object.\n\n    Examples\n    --------\n    > var bool = isURIError( new URIError( 'beep' ) )\n    true\n    > bool = isURIError( {} )\n    false\n\n    See Also\n    --------\n    isError\n","isVectorLike":"\nisVectorLike( value )\n    Tests if a value is a 1-dimensional ndarray-like object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 1-dimensional ndarray-like\n        object.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = [ 0, 0, 0, 0 ];\n    > M.ndims = 1;\n    > M.shape = [ 4 ];\n    > M.strides = [ 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'generic';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isVectorLike( M )\n    true\n    > bool = isVectorLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isVectorLike( 3.14 )\n    false\n    > bool = isVectorLike( {} )\n    false\n\n    See Also\n    --------\n    isArray, isArrayLike, isMatrixLike, isndarrayLike, isTypedArrayLike\n","isWebAssemblyMemory":"\nisWebAssemblyMemory( value )\n    Tests if a value is a WebAssembly memory instance.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a WebAssembly memory instance.\n\n    Examples\n    --------\n    > var bool = isWebAssemblyMemory( {} )\n    false\n\n    See Also\n    --------\n    hasWebAssemblySupport\n","isWellFormedString":"\nisWellFormedString( str )\n    Tests if a string is well-formed.\n\n    Parameters\n    ----------\n    str: any\n        String to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether str is well-formed.\n\n    Examples\n    --------\n    > var bool = isWellFormedString( '' )\n    true\n\n    > bool = isWellFormedString( new String( '' ) )\n    true\n\n    > bool = isWellFormedString( '\\uDBFF' )\n    false\n\n    > bool = isWellFormedString( '\\uDBFFFF\\uDBFF' )\n    false\n\n    > bool = isWellFormedString( [] )\n    false\n\n    > bool = isWellFormedString( '-5' )\n    true\n\n    > bool = isWellFormedString( null )\n    false\n\n\nisWellFormedString.isPrimitive( str )\n    Tests if a string is a well-formed string primitive.\n\n    Parameters\n    ----------\n    str: any\n        String to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether str is a well-formed string primitive.\n\n    Examples\n    --------\n    > var bool = isWellFormedString.isPrimitive( '' )\n    true\n    > bool = isWellFormedString.isPrimitive( new String( '' ) )\n    false\n\n\nisWellFormedString.isObject( str )\n    Tests if a string is a well-formed string object.\n\n    Parameters\n    ----------\n    str: any\n        String to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether str is a well-formed string object.\n\n    Examples\n    --------\n    > var bool = isWellFormedString.isObject( '' )\n    false\n    > bool = isWellFormedString.isObject( new String( '' ) )\n    true\n\n","isWellFormedString.isPrimitive":"\nisWellFormedString.isPrimitive( str )\n    Tests if a string is a well-formed string primitive.\n\n    Parameters\n    ----------\n    str: any\n        String to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether str is a well-formed string primitive.\n\n    Examples\n    --------\n    > var bool = isWellFormedString.isPrimitive( '' )\n    true\n    > bool = isWellFormedString.isPrimitive( new String( '' ) )\n    false","isWellFormedString.isObject":"\nisWellFormedString.isObject( str )\n    Tests if a string is a well-formed string object.\n\n    Parameters\n    ----------\n    str: any\n        String to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether str is a well-formed string object.\n\n    Examples\n    --------\n    > var bool = isWellFormedString.isObject( '' )\n    false\n    > bool = isWellFormedString.isObject( new String( '' ) )\n    true","isWhitespace":"\nisWhitespace( str )\n    Tests whether a string contains only white space characters.\n\n    A white space character is defined as one of the 25 characters defined as a\n    white space (\"WSpace=Y\",\"WS\") character in the Unicode 9.0 character\n    database, as well as one related white space character without the Unicode\n    character property \"WSpace=Y\" (zero width non-breaking space which was\n    deprecated as of Unicode 3.2).\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a string contains only white space\n        characters.\n\n    Examples\n    --------\n    > var bool = isWhitespace( '       ' )\n    true\n    > bool = isWhitespace( 'abcdef' )\n    false\n    > bool = isWhitespace( '' )\n    false\n\n    See Also\n    --------\n    reWhitespace\n","isWritableProperty":"\nisWritableProperty( value, property )\n    Tests if an object's own property is writable.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own property is writable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.writable = false;\n    > desc.value = 'beep';\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isWritableProperty( obj, 'boop' )\n    true\n    > bool = isWritableProperty( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    isReadableProperty, isReadWriteProperty, isWritablePropertyIn, isWriteOnlyProperty\n","isWritablePropertyIn":"\nisWritablePropertyIn( value, property )\n    Tests if an object's own or inherited property is writable.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own or inherited property is writable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.writable = false;\n    > desc.value = 'beep';\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isWritablePropertyIn( obj, 'boop' )\n    true\n    > bool = isWritablePropertyIn( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    isReadablePropertyIn, isReadWritePropertyIn, isWritableProperty, isWriteOnlyPropertyIn\n","isWriteOnlyProperty":"\nisWriteOnlyProperty( value, property )\n    Tests if an object's own property is write-only.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own property is write-only.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = true;\n    > desc.set = function setter( v ) { obj.boop = v; };\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isWriteOnlyProperty( obj, 'boop' )\n    false\n    > bool = isWriteOnlyProperty( obj, 'beep' )\n    true\n\n    See Also\n    --------\n    isReadOnlyProperty, isReadWriteProperty, isWritableProperty, isWriteOnlyPropertyIn\n","isWriteOnlyPropertyIn":"\nisWriteOnlyPropertyIn( value, property )\n    Tests if an object's own or inherited property is write-only.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own or inherited property is write-\n        only.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = true;\n    > desc.set = function setter( v ) { obj.boop = v; };\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isWriteOnlyPropertyIn( obj, 'boop' )\n    false\n    > bool = isWriteOnlyPropertyIn( obj, 'beep' )\n    true\n\n    See Also\n    --------\n    isReadOnlyPropertyIn, isReadWritePropertyIn, isWritablePropertyIn, isWriteOnlyProperty\n","iterAbs":"\niterAbs( iterator )\n    Returns an iterator which iteratively computes the absolute value.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAbs( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.abs, iterAbs2\n","iterAbs2":"\niterAbs2( iterator )\n    Returns an iterator which iteratively computes the squared absolute value.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAbs2( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.abs2, iterAbs\n","iterAcos":"\niterAcos( iterator )\n    Returns an iterator which iteratively computes the arccosine.\n\n    The domain of arccosine is restricted to [-1,1]. If an iterated value is\n    outside of the domain, the returned iterator returns `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAcos( random.iterators.uniform( -1.0, 1.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.acos, iterAcosh, iterAsin, iterAtan\n","iterAcosh":"\niterAcosh( iterator )\n    Returns an iterator which iteratively computes the hyperbolic arccosine.\n\n    The domain of the hyperbolic arccosine is restricted to [1,+infinity). If an\n    iterated value is outside of the domain, the returned iterator returns\n    `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAcosh( random.iterators.uniform( 1.0, 10.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.acosh, iterAcos, iterAsinh, iterAtanh\n","iterAcot":"\niterAcot( iterator )\n    Returns an iterator which iteratively computes the inverse cotangent.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAcot( random.iterators.uniform( -5.0, 5.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.acot, iterAcos, iterAcoth, iterAsin, iterAtan\n","iterAcoth":"\niterAcoth( iterator )\n    Returns an iterator which iteratively computes the inverse hyperbolic\n    cotangent.\n\n    The domain of the inverse hyperbolic cotangent is restricted to (-inf,-1]\n    and [1,inf). If an iterated value is outside of the domain, the returned\n    iterator returns `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAcoth( random.iterators.uniform( 1.0, 10.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.acoth, iterAcosh, iterAcot, iterAsinh, iterAtanh\n","iterAcovercos":"\niterAcovercos( iterator )\n    Returns an iterator which iteratively computes the inverse coversed cosine.\n\n    The domain of inverse coversed cosine is restricted to [-2,0]. If an\n    iterated value is outside of the domain, the returned iterator returns\n    `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAcovercos( random.iterators.uniform( -2.0, 0.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.acovercos, iterAcoversin, iterAvercos, iterCovercos, iterVercos\n","iterAcoversin":"\niterAcoversin( iterator )\n    Returns an iterator which iteratively computes the inverse coversed sine.\n\n    The domain of inverse coversed sine is restricted to [0,2]. If an iterated\n    value is outside of the domain, the returned iterator returns `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAcoversin( random.iterators.uniform( 0.0, 2.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.acoversin, iterAcovercos, iterAversin, iterCoversin, iterVersin\n","iterAdd":"\niterAdd( iter0, ...iterator )\n    Returns an iterator which performs element-wise addition of two or more\n    iterators.\n\n    The length of the returned iterator is equal to the length of the shortest\n    provided iterator. In other words, the returned iterator ends once *one* of\n    the provided iterators ends.\n\n    If provided a numeric value as an iterator argument, the value is broadcast\n    as an infinite iterator which always returns the provided value.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iter0: Object\n        Input iterator.\n\n    iterator: ...Object\n        Iterators to add.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1.0, 2.0 ] );\n    > var it2 = array2iterator( [ 3.0, 4.0 ] );\n    > var it = iterAdd( it1, it2 );\n    > var v = it.next().value\n    4.0\n    > v = it.next().value\n    6.0\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterDivide, iterMultiply, iterSubtract\n","iterAdvance":"\niterAdvance( iterator[, n] )\n    Advances an entire iterator.\n\n    The function *eagerly* advances an input iterator `n` iterations or until\n    the input iterator finishes, whichever comes first.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator to advance.\n\n    n: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Input iterator.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n    > var it = iterAdvance( arr, 4 );\n    > var v = it.next().value\n    1\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterHead, iterSlice\n","iterAhavercos":"\niterAhavercos( iterator )\n    Returns an iterator which iteratively computes the inverse half-value versed\n    cosine.\n\n    The domain of inverse half-value versed cosine is restricted to [0,1]. If\n    an iterated value is outside of the domain, the returned iterator returns\n    `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAhavercos( random.iterators.uniform( 0.0, 1.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.ahavercos, iterAhaversin, iterHavercos, iterVercos\n","iterAhaversin":"\niterAhaversin( iterator )\n    Returns an iterator which iteratively computes the inverse half-value versed\n    sine.\n\n    The domain of inverse half-value versed sine is restricted to [-2,0]. If an\n    iterated value is outside of the domain, the returned iterator returns\n    `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAhaversin( random.iterators.uniform( 0.0, 1.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.ahaversin, iterAhavercos, iterHaversin, iterVersin\n","iterAny":"\niterAny( iterator )\n    Tests whether at least one iterated value is truthy.\n\n    The function immediately returns upon encountering a truthy value.\n\n    If provided an iterator which does not return any iterated values, the\n    function returns `false`.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if a value is truthy; otherwise, the\n        function returns `false`.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n    > var bool = iterAny( arr )\n    true\n\n    See Also\n    --------\n    iterAnyBy, iterEvery, iterForEach, iterNone, iterSome\n","iterAnyBy":"\niterAnyBy( iterator, predicate[, thisArg ] )\n    Tests whether at least one iterated value passes a test implemented by a\n    predicate function.\n\n    The predicate function is provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index.\n\n    The function immediately returns upon encountering a truthy return value.\n\n    If provided an iterator which does not return any iterated values, the\n    function returns `false`.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if a predicate function returns a truthy\n        value for any iterated value. Otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n    > function fcn( v ) { return ( v === 1 ); };\n    > var bool = iterAnyBy( arr, fcn )\n    true\n\n    See Also\n    --------\n    iterAny, iterEveryBy, iterForEach, iterNoneBy, iterSomeBy\n","iterAsin":"\niterAsin( iterator )\n    Returns an iterator which iteratively computes the arcsine.\n\n    The domain of arcsine is restricted to [-1,1]. If an iterated value is\n    outside of the domain, the returned iterator returns `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAsin( random.iterators.uniform( -1.0, 1.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.asin, iterAcos, iterAsinh, iterAtan\n","iterAsinh":"\niterAsinh( iterator )\n    Returns an iterator which iteratively computes the hyperbolic arcsine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAsinh( random.iterators.uniform( -2.0, 2.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.asinh, iterAcosh, iterAsin, iterAtanh\n","iterAtan":"\niterAtan( iterator )\n    Returns an iterator which iteratively computes the arctangent.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAtan( random.iterators.uniform( -2.0, 2.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.atan, iterAcos, iterAsin, iterAtanh\n","iterAtan2":"\niterAtan2( y, x )\n    Returns an iterator which iteratively computes the angle in the plane (in\n    radians) between the positive x-axis and the ray from (0,0) to the point\n    (x,y).\n\n    The length of the returned iterator is equal to the length of the shortest\n    provided iterator. In other words, the returned iterator ends once *one* of\n    the provided iterators ends.\n\n    If provided a numeric value as an iterator argument, the value is broadcast\n    as an infinite iterator which always returns the provided value.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    y: Object|number\n        Input iterator.\n\n    x: Object|number\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = random.iterators.uniform( -2.0, 2.0 );\n    > var y = random.iterators.uniform( -2.0, 2.0 );\n    > var it = iterAtan2( y, x );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.atan2, iterAtan\n","iterAtanh":"\niterAtanh( iterator )\n    Returns an iterator which iteratively computes the hyperbolic arctangent.\n\n    The domain of hyperbolic arctangent is restricted to [-1,1]. If an iterated\n    value is outside of the domain, the returned iterator returns `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAtanh( random.iterators.uniform( -1.0, 1.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.atanh, iterAcosh, iterAsinh, iterAtan\n","iterator2array":"\niterator2array( iterator[, out][, mapFcn[, thisArg]] )\n    Creates (or fills) an array from an iterator.\n\n    When invoked, an input function is provided two arguments:\n\n    - value: iterated value.\n    - index: iterated value index (zero-based).\n\n    If provided an output array, the function fills the output array with\n    iterated values.\n\n    Iteration stops when an output array is full or an iterator finishes;\n    whichever comes first.\n\n    Parameters\n    ----------\n    iterator: Object\n        Source iterator.\n\n    out: ArrayLikeObject (optional)\n        Output array-like object.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var opts = { 'iter': 10 };\n    > var arr = iterator2array( random.iterators.randu( opts ) )\n\n    See Also\n    --------\n    array2iterator, iterator2arrayview\n","iterator2arrayview":"\niterator2arrayview( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )\n    Fills an array-like object view with values returned from an iterator.\n\n    When invoked, an input function is provided three arguments:\n\n    - value: iterated value.\n    - index: destination index (zero-based).\n    - n: iteration index (zero-based).\n\n    Iteration stops when an output array view is full or an iterator finishes;\n    whichever comes first.\n\n    Parameters\n    ----------\n    iterator: Object\n        Source iterator.\n\n    dest: ArrayLikeObject\n        Output array-like object.\n\n    begin: integer (optional)\n        Starting index (inclusive). When negative, determined relative to the\n        last element. Default: 0.\n\n    end: integer (optional)\n        Ending index (non-inclusive). When negative, determined relative to the\n        last element. Default: dest.length.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var it = random.iterators.randu({ 'iter': 10 });\n    > var out = new Float64Array( 20 );\n    > var arr = iterator2arrayview( it, out, 5, 15 )\n\n    See Also\n    --------\n    iterator2array, arrayview2iterator, iterator2arrayviewRight\n","iterator2arrayviewRight":"\niterator2arrayviewRight( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )\n    Fills an array-like object view from right to left with values returned from\n    an iterator.\n\n    When invoked, an input function is provided three arguments:\n\n    - value: iterated value.\n    - index: destination index (zero-based).\n    - n: iteration index (zero-based).\n\n    Iteration stops when an output array view is full or an iterator finishes;\n    whichever comes first.\n\n    Parameters\n    ----------\n    iterator: Object\n        Source iterator.\n\n    dest: ArrayLikeObject\n        Output array-like object.\n\n    begin: integer (optional)\n        Starting index (inclusive). When negative, determined relative to the\n        last element. Default: 0.\n\n    end: integer (optional)\n        Ending index (non-inclusive). When negative, determined relative to the\n        last element. Default: dest.length.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var it = random.iterators.randu({ 'iter': 10 });\n    > var out = new Float64Array( 20 );\n    > var arr = iterator2arrayviewRight( it, out, 5, 15 )\n\n    See Also\n    --------\n    iterator2array, arrayview2iteratorRight, iterator2arrayview\n","iteratorStream":"\niteratorStream( iterator[, options] )\n    Creates a readable stream from an iterator.\n\n    In object mode, `null` is a reserved value. If an iterator generates `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or explicitly map `null`\n    values to a different value by wrapping the provided iterator with another\n    iterator.\n\n    In binary mode, if an iterator generates `undefined` values, the stream will\n    emit an error. Consider providing a custom serialization function or\n    explicitly map `undefined` values to a different value by wrapping the\n    provided iterator with another iterator.\n\n    If a serialization function fails to return a string or Buffer, the stream\n    emits an error.\n\n    Parameters\n    ----------\n    iterator: Object\n        Source iterator.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing iteration.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize iterated\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var it = random.iterators.randu( opts );\n    > var s = iteratorStream( it );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\niteratorStream.factory( [options] )\n    Returns a function for creating readable streams from iterators.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing iteration.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize iterated\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = iteratorStream.factory( opts );\n\n\niteratorStream.objectMode( iterator[, options] )\n    Returns an \"objectMode\" readable stream from an iterator.\n\n    In object mode, `null` is a reserved value. If an iterator generates `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or explicitly map `null`\n    values to a different value by wrapping the provided iterator with another\n    iterator.\n\n    Parameters\n    ----------\n    iterator: Object\n        Source iterator.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before pausing iteration.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var it = random.iterators.randu( opts );\n    > var s = iteratorStream.objectMode( it );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    arrayStream\n","iteratorStream.factory":"\niteratorStream.factory( [options] )\n    Returns a function for creating readable streams from iterators.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing iteration.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize iterated\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = iteratorStream.factory( opts );","iteratorStream.objectMode":"\niteratorStream.objectMode( iterator[, options] )\n    Returns an \"objectMode\" readable stream from an iterator.\n\n    In object mode, `null` is a reserved value. If an iterator generates `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or explicitly map `null`\n    values to a different value by wrapping the provided iterator with another\n    iterator.\n\n    Parameters\n    ----------\n    iterator: Object\n        Source iterator.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before pausing iteration.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var it = random.iterators.randu( opts );\n    > var s = iteratorStream.objectMode( it );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    arrayStream","IteratorSymbol":"\nIteratorSymbol\n    Iterator symbol.\n\n    This symbol specifies the default iterator for an object.\n\n    The symbol is only supported in ES6/ES2015+ environments. For non-supporting\n    environments, the value is `null`.\n\n    Examples\n    --------\n    > var s = IteratorSymbol\n\n    See Also\n    --------\n    Symbol\n","iterAvercos":"\niterAvercos( iterator )\n    Returns an iterator which iteratively computes the inverse versed cosine.\n\n    The domain of inverse versed cosine is restricted to [-2,0]. If an iterated\n    value is outside of the domain, the returned iterator returns `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAvercos( random.iterators.uniform( -2.0, 0.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.avercos, iterAversin, iterVersin\n","iterAversin":"\niterAversin( iterator )\n    Returns an iterator which iteratively computes the inverse versed sine.\n\n    The domain of inverse versed sine is restricted to [0,2]. If an iterated\n    value is outside of the domain, the returned iterator returns `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAversin( random.iterators.uniform( 0.0, 2.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.aversin, iterAvercos, iterVercos\n","iterawgn":"\niterawgn( iterator, sigma[, options] )\n    Returns an iterator which introduces additive white Gaussian noise (AWGN)\n    with standard deviation `sigma`.\n\n    If an environment supports Symbol.iterator and the provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    sigma: number\n        Standard deviation of the noise.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating pseudorandom numbers\n        drawn from a standard normal distribution. If provided, the `state` and\n        `seed` options are ignored. In order to seed the returned iterator, one\n        must seed the provided `prng` (assuming the provided `prng` is\n        seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function|null\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Pseudorandom random number generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var src = iterSineWave();\n    > var it = iterawgn( src, 0.5 );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterawln, iterawun\n","iterawln":"\niterawln( iterator, sigma[, options] )\n    Returns an iterator which introduces additive white Laplacian noise (AWLN)\n    with standard deviation `sigma`.\n\n    If an environment supports Symbol.iterator and the provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    sigma: number\n        Standard deviation of the noise.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval [0,1). If provided, the\n        `state` and `seed` options are ignored. In order to seed the returned\n        iterator, one must seed the provided `prng` (assuming the provided\n        `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Pseudorandom random number generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var src = iterSineWave();\n    > var it = iterawln( src, 0.5 );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterawgn, iterawun\n","iterawun":"\niterawun( iterator, sigma[, options] )\n    Returns an iterator which introduces additive white uniform noise (AWUN)\n    with standard deviation `sigma`.\n\n    If an environment supports Symbol.iterator and the provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    sigma: number\n        Standard deviation of the noise.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval [0,1). If provided, the\n        `state` and `seed` options are ignored. In order to seed the returned\n        iterator, one must seed the provided `prng` (assuming the provided\n        `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Pseudorandom random number generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var src = iterSineWave();\n    > var it = iterawun( src, 0.5 );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterawgn, iterawln\n","iterBartlettHannPulse":"\niterBartlettHannPulse( [options] )\n    Returns an iterator which generates a Bartlett-Hann pulse waveform.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Pulse period (i.e., the number of iterations until a waveform repeats).\n        Default: 100.\n\n    options.duration: integer (optional)\n        Pulse duration. Must be greater than 2. Default: options.period.\n\n    options.amplitude: number (optional)\n        Amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterBartlettHannPulse();\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterBartlettPulse, iterHannPulse, iterPulse, iterTriangleWave\n","iterBartlettPulse":"\niterBartlettPulse( [options] )\n    Returns an iterator which generates a Bartlett pulse waveform.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Pulse period (i.e., the number of iterations until a waveform repeats).\n        Default: 100.\n\n    options.duration: integer (optional)\n        Pulse duration. Must be greater than 2. Default: options.period.\n\n    options.amplitude: number (optional)\n        Amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterBartlettPulse();\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterBartlettHannPulse, iterPulse, iterTriangleWave\n","iterBesselj0":"\niterBesselj0( iterator )\n    Returns an iterator which iteratively evaluates the Bessel function of the\n    first kind of order zero.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterBesselj0( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.besselj0, iterBesselj1, iterBessely0, iterBessely1\n","iterBesselj1":"\niterBesselj1( iterator )\n    Returns an iterator which iteratively evaluates the Bessel function of the\n    first kind of order one.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterBesselj1( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.besselj1, iterBesselj0, iterBessely0, iterBessely1\n","iterBessely0":"\niterBessely0( iterator )\n    Returns an iterator which iteratively evaluates the Bessel function of the\n    second kind of order zero.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterBessely0( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.bessely0, iterBesselj0, iterBesselj1, iterBessely1\n","iterBessely1":"\niterBessely1( iterator )\n    Returns an iterator which iteratively evaluates the Bessel function of the\n    second kind of order one.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterBessely1( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.bessely1, iterBesselj0, iterBesselj1, iterBessely0\n","iterBeta":"\niterBeta( x, y )\n    Returns an iterator which iteratively evaluates the beta function.\n\n    The length of the returned iterator is equal to the length of the shortest\n    provided iterator. In other words, the returned iterator ends once *one* of\n    the provided iterators ends.\n\n    If provided a numeric value as an iterator argument, the value is broadcast\n    as an infinite iterator which always returns the provided value.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    x: Object|number\n        Input iterator.\n\n    y: Object|number\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = random.iterators.uniform( 0.0, 2.0 );\n    > var y = random.iterators.uniform( 0.0, 2.0 );\n    > var it = iterBeta( x, y );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.beta, iterBetaln\n","iterBetaln":"\niterBetaln( x, y )\n    Returns an iterator which iteratively evaluates the natural logarithm of the\n    beta function.\n\n    The length of the returned iterator is equal to the length of the shortest\n    provided iterator. In other words, the returned iterator ends once *one* of\n    the provided iterators ends.\n\n    If provided a numeric value as an iterator argument, the value is broadcast\n    as an infinite iterator which always returns the provided value.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    x: Object|number\n        Input iterator.\n\n    y: Object|number\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = random.iterators.uniform( 0.0, 2.0 );\n    > var y = random.iterators.uniform( 0.0, 2.0 );\n    > var it = iterBetaln( x, y );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.betaln, iterBeta\n","iterBinet":"\niterBinet( iterator )\n    Returns an iterator which iteratively evaluates Binet's formula extended to\n    real numbers.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterBinet( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.binet\n","iterCbrt":"\niterCbrt( iterator )\n    Returns an iterator which iteratively computes the cube root.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterCbrt( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.cbrt, iterPow, iterSqrt\n","iterCeil":"\niterCeil( iterator )\n    Returns an iterator which rounds each iterated value toward positive\n    infinity.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterCeil( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.ceil, iterFloor, iterRound\n","iterCeil2":"\niterCeil2( iterator )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    two toward positive infinity.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterCeil2( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.ceil2, iterCeil, iterCeil10, iterFloor2, iterRound2\n","iterCeil10":"\niterCeil10( iterator )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    10 toward positive infinity.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterCeil10( random.iterators.uniform( -100.0, 100.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.ceil10, iterCeil, iterCeil2, iterFloor10, iterRound10\n","iterCompositesSeq":"\niterCompositesSeq( [options] )\n    Returns an iterator which generates a sequence of composite numbers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterCompositesSeq();\n    > var v = it.next().value\n    4\n    > v = it.next().value\n    6\n    > v = it.next().value\n    8\n\n    See Also\n    --------\n    iterIntegersSeq, iterPositiveIntegersSeq, iterPrimesSeq\n","iterConcat":"\niterConcat( iter0, ...iterator )\n    Returns an iterator which iterates over the values of two or more iterators.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iter0: Object\n        Input iterator.\n\n    iterator: ...Object\n        Iterators to concatenate.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2 ] );\n    > var it2 = array2iterator( [ 3, 4 ] );\n    > var it = iterConcat( it1, it2 );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    2\n    > v = it.next().value\n    3\n    > v = it.next().value\n    4\n    > var bool = it.next().done\n    true\n\n","iterConstant":"\niterConstant( value[, options] )\n    Returns an iterator which always returns the same value.\n\n    When provided an object reference, the returned iterator always returns the\n    same reference.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    value: any\n        Value to return.\n\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterConstant( 3.14 );\n    > var v = it.next().value\n    3.14\n    > v = it.next().value\n    3.14\n\n    See Also\n    --------\n    constantFunction\n","iterContinuedFraction":"\niterContinuedFraction( iterator[, options] )\n    Evaluates the terms of a continued fraction.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Maximum number of iterations. Default: 1e308.\n\n    options.tol: number (optional)\n        Tolerance at which to terminate further evaluation of the continued\n        fraction. Default: floating-point epsilon.\n\n    Returns\n    -------\n    out: number|null\n        Result.\n\n    Examples\n    --------\n    > var terms = array2iterator( [ 3, 4, 12, 4 ] );\n    > var v = iterContinuedFraction( terms )\n    ~3.245\n\n    See Also\n    --------\n    iterContinuedFractionSeq\n","iterContinuedFractionSeq":"\niterContinuedFractionSeq( x[, options] )\n    Returns an iterator which generates a list of all continued fraction terms\n    which can be obtained given the precision of `x`.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Maximum number of iterations. Default: 1e308.\n\n    options.tol: number (optional)\n        Tolerance at which to terminate further evaluation of the continued\n        fraction. Default: floating-point epsilon.\n\n    options.returns: string (optional)\n        Specifies the type of result to return. Must be one of\n\n        - terms: return continued fraction terms\n        - convergents: return continued fraction convergents\n        - *: return both continued fraction terms and their associated\n          convergents as a two-element array.\n\n        Default: 'terms'.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    // Return continued fraction terms...\n    > var it = iterContinuedFractionSeq( 3.245 );\n    > var v = it.next().value\n    3\n    > v = it.next().value\n    4\n    > v = it.next().value\n    12\n    > v = it.next().value\n    4\n    > var bool = it.next().done\n    true\n\n    // Return continued fraction convergents...\n    > it = iterContinuedFractionSeq( 3.245, { 'returns': 'convergents' } );\n    > v = it.next().value\n    3.0\n    > v = it.next().value\n    3.25\n    > v = it.next().value\n    ~3.2449\n    > v = it.next().value\n    3.245\n    > bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterContinuedFraction\n","iterCos":"\niterCos( iterator )\n    Returns an iterator which iteratively computes the cosine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterCos( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.cos, iterCospi, iterSin, iterTan\n","iterCosh":"\niterCosh( iterator )\n    Returns an iterator which iteratively computes the hyperbolic cosine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -5.0, 5.0 );\n    > var it = iterCosh( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.cosh, iterCos, iterSinh, iterTanh\n","iterCosineWave":"\niterCosineWave( [options] )\n    Returns an iterator which generates a cosine wave.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Period (i.e., the number of iterations before a cosine wave repeats).\n        Default: 10.\n\n    options.amplitude: number (optional)\n        Peak amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterCosineWave();\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterPulse, iterSawtoothWave, iterSineWave, iterSquareWave, iterTriangleWave\n","iterCosm1":"\niterCosm1( iterator )\n    Returns an iterator which iteratively computes `cos(x) - 1`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 6.28 );\n    > var it = iterCosm1( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.cosm1, iterCos\n","iterCospi":"\niterCospi( iterator )\n    Returns an iterator which computes the cosine of each iterated value times\n    π.\n\n    Computes cos(πx) more accurately than cos(pi*x), especially for large x.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterCospi( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.cospi, iterCos\n","iterCounter":"\niterCounter( iterator )\n    Returns an iterator which iteratively computes the number of iterated\n    values.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterCounter( random.iterators.randu() );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    iterLength\n","iterCovercos":"\niterCovercos( iterator )\n    Returns an iterator which iteratively computes the coversed cosine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 6.28 );\n    > var it = iterCovercos( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.covercos, iterCoversin, iterVercos\n","iterCoversin":"\niterCoversin( iterator )\n    Returns an iterator which iteratively computes the coversed sine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 6.28 );\n    > var it = iterCoversin( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.coversin, iterCovercos, iterVersin\n","iterCubesSeq":"\niterCubesSeq( [options] )\n    Returns an iterator which generates a sequence of cubes.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 208063.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterCubesSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().value\n    8\n\n    See Also\n    --------\n    iterFourthPowersSeq, iterSquaresSeq\n","itercugmean":"\nitercugmean( iterator )\n    Returns an iterator which iteratively computes a cumulative geometric mean.\n\n    If provided a negative value, the iterated value is `NaN` for all future\n    invocations.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\n    > var it = itercugmean( arr );\n    > var v = it.next().value\n    2.0\n    > v = it.next().value\n    ~3.16\n    > v = it.next().value\n    ~3.11\n    > v = it.next().value\n    ~3.50\n\n    See Also\n    --------\n    itercuhmean, itercumean\n","itercuhmean":"\nitercuhmean( iterator )\n    Returns an iterator which iteratively computes a cumulative harmonic mean.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\n    > var it = itercuhmean( arr );\n    > var v = it.next().value\n    2.0\n    > v = it.next().value\n    ~2.86\n    > v = it.next().value\n    ~2.90\n    > v = it.next().value\n    ~3.24\n\n    See Also\n    --------\n    itercugmean, itercumean\n","itercumax":"\nitercumax( iterator )\n    Returns an iterator which iteratively computes a cumulative maximum value.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercumax( arr );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    2.0\n    > m = it.next().value\n    3.0\n    > m = it.next().value\n    5.0\n\n    See Also\n    --------\n    itercumidrange, itercumin, itercurange, itermax\n","itercumaxabs":"\nitercumaxabs( iterator )\n    Returns an iterator which iteratively computes a cumulative maximum absolute\n    value.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercumaxabs( arr );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    5.0\n    > m = it.next().value\n    5.0\n    > m = it.next().value\n    5.0\n\n    See Also\n    --------\n    itercumax, itercuminabs, itermaxabs\n","itercumean":"\nitercumean( iterator )\n    Returns an iterator which iteratively computes a cumulative arithmetic mean.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercumean( arr );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    -1.5\n    > m = it.next().value\n    0.0\n    > m = it.next().value\n    1.25\n\n    See Also\n    --------\n    itercumidrange, itercusum, itermean\n","itercumeanabs":"\nitercumeanabs( iterator )\n    Returns an iterator which iteratively computes a cumulative arithmetic mean\n    of absolute values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercumeanabs( arr );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    3.5\n    > m = it.next().value\n    ~3.33\n    > m = it.next().value\n    3.75\n\n    See Also\n    --------\n    itercumean, itercumeanabs2, itercusumabs, itermeanabs\n","itercumeanabs2":"\nitercumeanabs2( iterator )\n    Returns an iterator which iteratively computes a cumulative arithmetic mean\n    of squared absolute values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercumeanabs2( arr );\n    > var m = it.next().value\n    4.0\n    > m = it.next().value\n    14.5\n    > m = it.next().value\n    ~12.67\n    > m = it.next().value\n    15.75\n\n    See Also\n    --------\n    itercumean, itercumeanabs, itercusumabs2, itermeanabs2\n","itercumidrange":"\nitercumidrange( iterator )\n    Returns an iterator which iteratively computes a cumulative mid-range.\n\n    The mid-range is the arithmetic mean of maximum and minimum values.\n    Accordingly, the mid-range is the midpoint of the range and a measure of\n    central tendency.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercumidrange( arr );\n    > var v = it.next().value\n    2.0\n    > v = it.next().value\n    -1.5\n    > v = it.next().value\n    -1.0\n    > v = it.next().value\n    0.0\n\n    See Also\n    --------\n    itercumean, itercumax, itercumin, itercurange, itermidrange\n","itercumin":"\nitercumin( iterator )\n    Returns an iterator which iteratively computes a cumulative minimum value.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercumin( arr );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    -5.0\n    > m = it.next().value\n    -5.0\n    > m = it.next().value\n    -5.0\n\n    See Also\n    --------\n    itercumax, itercumidrange, itercurange, itermin\n","itercuminabs":"\nitercuminabs( iterator )\n    Returns an iterator which iteratively computes a cumulative minimum absolute\n    value.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercuminabs( arr );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    2.0\n    > m = it.next().value\n    2.0\n    > m = it.next().value\n    2.0\n\n    See Also\n    --------\n    itercumaxabs, itercumin, iterminabs\n","itercuprod":"\nitercuprod( iterator )\n    Returns an iterator which iteratively computes a cumulative product.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercuprod( arr );\n    > var p = it.next().value\n    2.0\n    > p = it.next().value\n    -10.0\n    > p = it.next().value\n    -30.0\n    > p = it.next().value\n    -150.0\n\n    See Also\n    --------\n    itercusum, iterprod\n","itercurange":"\nitercurange( iterator )\n    Returns an iterator which iteratively computes a cumulative range.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercurange( arr );\n    > var r = it.next().value\n    0.0\n    > r = it.next().value\n    7.0\n    > r = it.next().value\n    8.0\n    > r = it.next().value\n    10.0\n\n    See Also\n    --------\n    itercumax, itercumean, itercumin, iterrange\n","itercusum":"\nitercusum( iterator )\n    Returns an iterator which iteratively computes a cumulative sum.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercusum( arr );\n    > var s = it.next().value\n    2.0\n    > s = it.next().value\n    -3.0\n    > s = it.next().value\n    0.0\n    > s = it.next().value\n    5.0\n\n    See Also\n    --------\n    itercumean, itersum, itercuprod\n","itercusumabs":"\nitercusumabs( iterator )\n    Returns an iterator which iteratively computes a cumulative sum of absolute\n    values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercusumabs( arr );\n    > var s = it.next().value\n    2.0\n    > s = it.next().value\n    7.0\n    > s = it.next().value\n    10.0\n    > s = it.next().value\n    15.0\n\n    See Also\n    --------\n    itercumeanabs, itercusum, itersumabs\n","itercusumabs2":"\nitercusumabs2( iterator )\n    Returns an iterator which iteratively computes a cumulative sum of squared\n    absolute values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercusumabs2( arr );\n    > var s = it.next().value\n    4.0\n    > s = it.next().value\n    29.0\n    > s = it.next().value\n    38.0\n    > s = it.next().value\n    63.0\n\n    See Also\n    --------\n    itercumeanabs2, itercusumabs, itersumabs2\n","iterDatespace":"\niterDatespace( start, stop[, N][, options] )\n    Returns an iterator which returns evenly spaced dates over a specified\n    interval.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    start: integer|string|Date\n        Starting date either as a `Date` object, JavaScript timestamp, or a date\n        string (inclusive).\n\n    stop: integer|string|Date\n        Stopping value either as a `Date` object, JavaScript timestamp, or a\n        date string (inclusive).\n\n    N: integer (optional)\n        Number of values. Default: 100.\n\n    options: Object (optional)\n        Function options.\n\n    options.round: string (optional)\n        Specifies how sub-millisecond times should be rounded. Must be one of\n        the following: 'floor', 'ceil', or 'round'. Default: 'floor'.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var t1 = new Date();\n    > var it = iterDatespace( t1, new Date( t1.getTime()+86400000 ) );\n    > var v = it.next().value\n    <Date>\n    > v = it.next().value\n    <Date>\n\n    See Also\n    --------\n    iterator2array, iterIncrspace, iterLinspace, iterLogspace, iterStep\n","iterDedupe":"\niterDedupe( iterator[, limit] )\n    Returns an iterator which removes consecutive duplicated values.\n\n    `NaN` values are considered distinct.\n\n    Uniqueness is determined according to strict equality. Accordingly, objects\n    are *not* checked for deep equality.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    limit: integer (optional)\n        Number of allowed consecutive duplicates. Default: 1.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\n    > var it = iterDedupe( arr );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    2\n    > v = it.next().value\n    3\n\n    See Also\n    --------\n    iterDedupeBy, iterUnique\n","iterDedupeBy":"\niterDedupeBy( iterator, [limit,] fcn )\n    Returns an iterator which removes consecutive values that resolve to the\n    same value according to a provided function.\n\n    The provided function is provided five arguments:\n\n    - curr: current source iterated value.\n    - sprev: previous source iterated value.\n    - dprev: previous downstream iterated value.\n    - index: source iteration index (zero-based).\n    - acc: previous resolved value.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    limit: integer (optional)\n        Number of allowed consecutive duplicates. Default: 1.\n\n    fcn: Function\n        Function indicating whether an iterated value is a \"duplicate\".\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\n    > function fcn( v ) { return v; };\n    > var it = iterDedupeBy( arr, fcn );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    2\n    > v = it.next().value\n    3\n\n    See Also\n    --------\n    iterDedupe, iterUnique\n","iterDeg2rad":"\niterDeg2rad( iterator )\n    Returns an iterator which iteratively converts an angle from degrees to\n    radians.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -360.0, 360.0 );\n    > var it = iterDeg2rad( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.deg2rad, iterRad2deg\n","iterDigamma":"\niterDigamma( iterator )\n    Returns an iterator which iteratively evaluates the digamma function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.01, 5.0 );\n    > var it = iterDigamma( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.digamma, iterGamma, iterTrigamma\n","iterDiracComb":"\niterDiracComb( [options] )\n    Returns an iterator which generates a Dirac comb.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Period (i.e., the number of iterations before a waveform repeats).\n        Default: 10.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterDiracComb();\n    > var v = it.next().value\n    Infinity\n    > v = it.next().value\n    0.0\n\n    See Also\n    --------\n    iterPulse\n","iterDiracDelta":"\niterDiracDelta( iterator )\n    Returns an iterator which iteratively evaluates the Dirac delta function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterDiracDelta( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.diracDelta\n","iterDivide":"\niterDivide( iter0, ...iterator )\n    Returns an iterator which performs element-wise division of two or more\n    iterators.\n\n    The length of the returned iterator is equal to the length of the shortest\n    provided iterator. In other words, the returned iterator ends once *one* of\n    the provided iterators ends.\n\n    If provided a numeric value as an iterator argument, the value is broadcast\n    as an infinite iterator which always returns the provided value.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iter0: Object\n        Input iterator.\n\n    iterator: ...Object\n        Iterators whose values are used as divisors.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 3.0, 2.0 ] );\n    > var it2 = array2iterator( [ 1.0, 4.0 ] );\n    > var it = iterDivide( it1, it2 );\n    > var v = it.next().value\n    3.0\n    > v = it.next().value\n    0.5\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterAdd, iterDivide, iterMultiply\n","iterDoWhileEach":"\niterDoWhileEach( iterator, predicate, fcn[, thisArg] )\n    Returns an iterator which invokes a function for each iterated value before\n    returning the iterated value until either a predicate function returns false\n    or the iterator has iterated over all values.\n\n    The condition is evaluated *after* executing the provided function; thus,\n    `fcn` *always* executes at least once.\n\n    When invoked, both input functions are provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index (zero-based).\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    predicate: Function\n        Function which indicates whether to continue iterating.\n\n    fcn: Function\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === v };\n    > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n    > var it = iterDoWhileEach( random.iterators.randu(), predicate, f );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterDoUntilEach, iterUntilEach, iterWhileEach\n","iterEllipe":"\niterEllipe( iterator )\n    Returns an iterator which iteratively computes the complete elliptic\n    integral of the second kind.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -1.0, 1.0 );\n    > var it = iterEllipe( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.ellipe, iterEllipk\n","iterEllipk":"\niterEllipk( iterator )\n    Returns an iterator which iteratively computes the complete elliptic\n    integral of the first kind.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -1.0, 1.0 );\n    > var it = iterEllipk( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.ellipk, iterEllipe\n","iterEmpty":"\niterEmpty()\n    Returns an empty iterator.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterEmpty();\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterConstant\n","iterErf":"\niterErf( iterator )\n    Returns an iterator which iteratively evaluates the error function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterErf( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.erf, iterErfc, iterErfinv, iterErfcinv\n","iterErfc":"\niterErfc( iterator )\n    Returns an iterator which iteratively evaluates the complementary error\n    function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterErfc( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.erfc, iterErf, iterErfinv, iterErfcinv\n","iterErfcinv":"\niterErfcinv( iterator )\n    Returns an iterator which iteratively evaluates the inverse complementary\n    error function.\n\n    The domain of inverse complementary error function is restricted to [0,2].\n    If an iterated value is outside of the domain, the returned iterator returns\n    `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterErfcinv( random.iterators.uniform( 0.0, 2.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.erfcinv, iterErf, iterErfc, iterErfinv\n","iterErfinv":"\niterErfinv( iterator )\n    Returns an iterator which iteratively evaluates the inverse error function.\n\n    The domain of inverse error function is restricted to [-1,1]. If an iterated\n    value is outside of the domain, the returned iterator returns `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterErfinv( random.iterators.uniform( -1.0, 1.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.erfinv, iterErf, iterErfc, iterErfcinv\n","iterEta":"\niterEta( iterator )\n    Returns an iterator which iteratively evaluates the Dirichlet eta function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterEta( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.eta\n","iterEvenIntegersSeq":"\niterEvenIntegersSeq( [options] )\n    Returns an iterator which generates an interleaved sequence of even\n    integers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 9007199254740992.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterEvenIntegersSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    2\n    > v = it.next().value\n    -2\n\n    See Also\n    --------\n    iterIntegersSeq, iterOddIntegersSeq\n","iterEvery":"\niterEvery( iterator )\n    Tests whether all iterated values are truthy.\n\n    The function immediately returns upon encountering a falsy value.\n\n    If provided an iterator which does not return any iterated values, the\n    function returns `true`.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `false` if a value is falsy; otherwise, the\n        function returns `true`.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1, 1, 1, 1, 0 ] );\n    > var bool = iterEvery( arr )\n    false\n\n    See Also\n    --------\n    iterAny, iterEveryBy, iterForEach, iterNone, iterSome\n","iterEveryBy":"\niterEveryBy( iterator, predicate[, thisArg ] )\n    Tests whether every iterated value passes a test implemented by a predicate\n    function.\n\n    The predicate function is provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index.\n\n    The function immediately returns upon encountering a falsy return value.\n\n    If provided an iterator which does not return any iterated values, the\n    function returns `true`.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if a predicate function returns a truthy\n        value for all iterated values. Otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\n    > function fcn( v ) { return ( v > 0 ); };\n    > var bool = iterEveryBy( arr, fcn )\n    true\n\n    See Also\n    --------\n    iterAnyBy, iterEvery, iterForEach, iterNoneBy, iterSomeBy\n","iterExp":"\niterExp( iterator )\n    Returns an iterator which iteratively evaluates the natural exponential\n    function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterExp( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.exp, iterExp10, iterExp2, iterExpm1, iterLn\n","iterExp2":"\niterExp2( iterator )\n    Returns an iterator which iteratively evaluates the base `2` exponential\n    function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -50.0, 50.0 );\n    > var it = iterExp2( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.exp2, iterExp, iterExp10, iterLog2\n","iterExp10":"\niterExp10( iterator )\n    Returns an iterator which iteratively evaluates the base `10` exponential\n    function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -50.0, 50.0 );\n    > var it = iterExp10( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.exp10, iterExp, iterExp2, iterLog10\n","iterExpit":"\niterExpit( iterator )\n    Returns an iterator which iteratively evaluates the standard logistic\n    function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 1.0 );\n    > var it = iterExpit( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.expit, iterExp, iterLogit\n","iterExpm1":"\niterExpm1( iterator )\n    Returns an iterator which iteratively computes `exp(x) - 1`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -5.0, 5.0 );\n    > var it = iterExpm1( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.expm1, iterExp, iterExpm1rel\n","iterExpm1rel":"\niterExpm1rel( iterator )\n    Returns an iterator which iteratively evaluates the relative error\n    exponential.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -50.0, 50.0 );\n    > var it = iterExpm1rel( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.expm1rel, iterExp, iterExpm1\n","iterFactorial":"\niterFactorial( iterator )\n    Returns an iterator which iteratively evaluates the factorial function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterFactorial( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.factorial, iterFactorialln\n","iterFactorialln":"\niterFactorialln( iterator )\n    Returns an iterator which iteratively evaluates the natural logarithm of the\n    factorial function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterFactorialln( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.factorialln, iterFactorial\n","iterFactorialsSeq":"\niterFactorialsSeq( [options] )\n    Returns an iterator which generates a sequence of factorials.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterFactorialsSeq();\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    1\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    iterFactorial\n","iterFibonacciSeq":"\niterFibonacciSeq( [options] )\n    Returns an iterator which generates a Fibonacci sequence.\n\n    The returned iterator can only generate the first 79 Fibonacci numbers, as\n    larger Fibonacci numbers cannot be safely represented in double-precision\n    floating-point format.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 79.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterFibonacciSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n\n    See Also\n    --------\n    base.fibonacci, iterLucasSeq, iterNegaFibonacciSeq, iterNonFibonacciSeq\n","iterFifthPowersSeq":"\niterFifthPowersSeq( [options] )\n    Returns an iterator which generates a sequence of fifth powers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 9741.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterFifthPowersSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().value\n    32\n\n    See Also\n    --------\n    iterCubesSeq, iterFourthPowersSeq, iterSquaresSeq\n","iterFill":"\niterFill( iterator, value[, begin[, end]] )\n    Returns an iterator which replaces all values from a provided iterator from\n    a start index to an end index with a static value.\n\n    If `end` exceeds the length of the provided iterator, the returned iterator\n    replaces the subsequence of iterated values starting from `begin` until the\n    last iterated value of the provided iterator.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    value: any\n        Static value.\n\n    begin: integer (optional)\n        Start iteration index (zero-based and inclusive). Default: 0.\n\n    end: integer (optional)\n        End iteration index (zero-based and non-inclusive).\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterFill( random.iterators.randu(), 3.14, 0, 2 );\n    > var r = it.next().value\n    3.14\n    > r = it.next().value\n    3.14\n    > r = it.next().value\n    <number>\n\n","iterFilter":"\niterFilter( iterator, predicate[, thisArg] )\n    Returns an iterator which filters a provided iterator's values according to\n    a predicate function.\n\n    When invoked, the predicate function is provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index (zero-based).\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    predicate: Function\n        Predicate function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > function f( v ) { return ( v > 2 ); };\n    > var it1 = array2iterator( [ 1, 3, 2, 4 ] );\n    > var it2 = iterFilter( it1, f );\n    > var v = it2.next().value\n    3\n    > v = it2.next().value\n    4\n\n    See Also\n    --------\n    iterFilterMap, iterMap, iterReject\n","iterFilterMap":"\niterFilterMap( iterator, fcn[, thisArg] )\n    Returns an iterator which both filters and maps a provided iterator's\n    values.\n\n    When invoked, the callback function is provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index (zero-based).\n\n    If the callback returns `undefined`, the iterator invokes the function for\n    the next value of the provided iterator; otherwise, the iterator returns\n    the callback's return value.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    fcn: Function\n        Callback function which both filters and maps.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > function f( v ) { if ( v > 2 ) { return v * 10 }; };\n    > var it1 = array2iterator( [ 1, 3, 2, 4 ] );\n    > var it2 = iterFilterMap( it1, f );\n    > var v = it2.next().value\n    30\n    > v = it2.next().value\n    40\n\n    See Also\n    --------\n    iterFilter, iterMap\n","iterFirst":"\niterFirst( iterator )\n    Returns the first iterated value.\n\n    The function does *not* consume an entire iterator before returning.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    Returns\n    -------\n    v: any\n        The first iterated value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1, 0, 0, 0, 0 ] );\n    > var v = iterFirst( arr )\n    1\n\n    See Also\n    --------\n    iterHead, iterLast, iterNth\n","iterFlatTopPulse":"\niterFlatTopPulse( [options] )\n    Returns an iterator which generates a flat top pulse waveform.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Pulse period (i.e., the number of iterations until a waveform repeats).\n        Default: 100.\n\n    options.duration: integer (optional)\n        Pulse duration. Must be greater than 2. Default: options.period.\n\n    options.amplitude: number (optional)\n        Amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterFlatTopPulse();\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterPulse\n","iterFloor":"\niterFloor( iterator )\n    Returns an iterator which rounds each iterated value toward negative\n    infinity.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterFloor( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.floor, iterCeil, iterRound\n","iterFloor2":"\niterFloor2( iterator )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    two toward negative infinity.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterFloor2( random.iterators.uniform( -100.0, 100.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.floor2, iterCeil2, iterFloor, iterFloor10, iterRound2\n","iterFloor10":"\niterFloor10( iterator )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    10 toward negative infinity.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterFloor10( random.iterators.uniform( -100.0, 100.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.floor10, iterCeil10, iterFloor, iterFloor2, iterRound10\n","iterFlow":"\niterFlow( methods )\n    Returns a fluent interface iterator constructor with a customized prototype\n    based on provided methods.\n\n    The methods argument should be an object which maps constructor method names\n    to iterator functions.\n\n    Each iterator function should have the following function signature:\n\n      iterFcn( iterator, ...args )\n\n    When a fluent interface iterator method is invoked, the method invokes the\n    corresponding iterator function with an iterator and provided method\n    arguments.\n\n    If an iterator function returns an iterator, the corresponding fluent\n    interface method returns a new fluent interface instance; otherwise, the\n    corresponding fluent interface method returns the iterator function result.\n\n    The iterator function evaluation context is always `null`.\n\n    Iterator functions which return iterators are expected to return iterator\n    protocol-compliant objects (i.e., an object having a `next` method which\n    returns the next iterated value (if one exists) assigned to a `value`\n    property and a `done` property having a boolean value indicating whether the\n    iterator is finished).\n\n    If an environment supports `Symbol.iterator`, the returned constructor\n    returns iterators which are iterable.\n\n    Parameters\n    ----------\n    methods: Object\n        An object mapping method names to iterator functions.\n\n    Returns\n    -------\n    FluentIterator: Function\n        Fluent interface iterator constructor.\n\n    Examples\n    --------\n    > var o = {};\n    > o.head = iterHead;\n    > o.some = iterSome;\n    > var fiter = iterFlow( o )\n\n\nFluentIterator( iterator )\n    Returns a new fluent interface iterator from a source iterator.\n\n    Parameters\n    ----------\n    iterator: Object\n        Source iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Fluent interface iterator.\n\n    Examples\n    --------\n    > var o = {};\n    > o.head = iterHead;\n    > o.some = iterSome;\n    > var fiter = iterFlow( o );\n    > var it = fiter( array2iterator( [ 0, 0, 1, 1, 1 ] ) );\n    > var bool = it.head( 3 ).some( 2 )\n    false\n\n\nFluentIterator.prototype.next()\n    Returns the next iterated value.\n\n    Returns\n    -------\n    out: Object\n        Iterator protocol-compliant object.\n\n    out.value: any (optional)\n        Next iterated value (if one exists).\n\n    out.done: boolean\n        Boolean flag indicating whether the iterator is finished.\n\n    Examples\n    --------\n    > var o = {};\n    > o.head = iterHead;\n    > o.some = iterSome;\n    > var fiter = iterFlow( o );\n    > var it1 = fiter( array2iterator( [ 0, 0, 1, 1, 1 ] ) );\n    > var it2 = it1.head( 3 );\n    > var v = it2.next().value\n    0\n    > v = it2.next().value\n    0\n    > v = it2.next().value\n    1\n\n\nFluentIterator.prototype.return( [value] )\n    Finishes an iterator and returns a provided value.\n\n    Parameters\n    ----------\n    value: any (optional)\n        Value to return.\n\n    Returns\n    -------\n    out: Object\n        Iterator protocol-compliant object.\n\n    out.value: any (optional)\n        Next iterated value (if one exists).\n\n    out.done: boolean\n        Boolean flag indicating whether the iterator is finished.\n\n    Examples\n    --------\n    > var o = {};\n    > o.head = iterHead;\n    > o.some = iterSome;\n    > var fiter = iterFlow( o );\n    > var it1 = fiter( array2iterator( [ 0, 0, 1, 1, 1 ] ) );\n    > var it2 = it1.head( 3 );\n    > var v = it2.next().value\n    0\n    > var bool = it2.return().done\n    true\n    > v = it2.next().value\n    undefined\n\n    See Also\n    --------\n    iterPipeline\n","iterForEach":"\niterForEach( iterator, fcn[, thisArg] )\n    Returns an iterator which invokes a function for each iterated value before\n    returning the iterated value.\n\n    When invoked, the input function is provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index (zero-based).\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    fcn: Function\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n    > var it = iterForEach( random.iterators.randu(), f );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterMap\n","iterFourthPowersSeq":"\niterFourthPowersSeq( [options] )\n    Returns an iterator which generates a sequence of fourth powers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 9741.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterFourthPowersSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().value\n    16\n\n    See Also\n    --------\n    iterCubesSeq, iterFifthPowersSeq, iterSquaresSeq\n","iterFresnelc":"\niterFresnelc( iterator )\n    Returns an iterator which iteratively computes the Fresnel integral C(x).\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 10.0 );\n    > var it = iterFresnelc( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.fresnelc, iterFresnels\n","iterFresnels":"\niterFresnels( iterator )\n    Returns an iterator which iteratively computes the Fresnel integral S(x).\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 10.0 );\n    > var it = iterFresnels( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.fresnels, iterFresnelc\n","iterGamma":"\niterGamma( iterator )\n    Returns an iterator which iteratively evaluates the gamma function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterGamma( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.gamma, iterGamma1pm1, iterGammaln\n","iterGamma1pm1":"\niterGamma1pm1( iterator )\n    Returns an iterator which iteratively computes `gamma(x+1) - 1` without\n    cancellation errors for small `x`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -5.0, 5.0 );\n    > var it = iterGamma1pm1( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.gamma1pm1, iterGamma\n","iterGammaln":"\niterGammaln( iterator )\n    Returns an iterator which iteratively evaluates the natural logarithm of the\n    gamma function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterGammaln( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.gammaln, iterGamma\n","iterHacovercos":"\niterHacovercos( iterator )\n    Returns an iterator which iteratively computes the half-value coversed\n    cosine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 6.28 );\n    > var it = iterHacovercos( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.hacovercos, iterCovercos, iterHacoversin\n","iterHacoversin":"\niterHacoversin( iterator )\n    Returns an iterator which iteratively computes the half-value coversed sine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 6.28 );\n    > var it = iterHacoversin( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.hacoversin, iterCoversin, iterHacovercos\n","iterHannPulse":"\niterHannPulse( [options] )\n    Returns an iterator which generates a Hann pulse waveform.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Pulse period (i.e., the number of iterations until a waveform repeats).\n        Default: 100.\n\n    options.duration: integer (optional)\n        Pulse duration. Must be greater than 2. Default: options.period.\n\n    options.amplitude: number (optional)\n        Amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterHannPulse();\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterBartlettHannPulse, iterPulse, iterSineWave\n","iterHavercos":"\niterHavercos( iterator )\n    Returns an iterator which iteratively computes the half-value versed cosine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 6.28 );\n    > var it = iterHavercos( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.havercos, iterHaversin, iterVercos\n","iterHaversin":"\niterHaversin( iterator )\n    Returns an iterator which iteratively computes the half-value versed sine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 6.28 );\n    > var it = iterHaversin( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.haversin, iterHavercos, iterVersin\n","iterHead":"\niterHead( iterator, n )\n    Returns an iterator which returns the first `n` values of a provided\n    iterator.\n\n    If a provided iterator only generates `m` values and `m` is less than `n`,\n    the returned iterator only returns `m` values.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    n: integer\n        Number of values.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterHead( random.iterators.randu(), 5 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterFirst, iterSlice\n","iterIncrspace":"\niterIncrspace( start, stop[, increment] )\n    Returns an iterator which returns evenly spaced numbers according to a\n    specified increment.\n\n    Beware that values which follow the starting value are subject to floating-\n    point rounding errors.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    start: number\n        Starting value (inclusive).\n\n    stop: number\n        Stopping value (exclusive).\n\n    increment: number (optional)\n        Increment. Default: 1.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterIncrspace( 0, 101, 2 );\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    iterator2array, iterDatespace, iterLinspace, iterLogspace, iterStep, iterUnitspace\n","iterIntegersSeq":"\niterIntegersSeq( [options] )\n    Returns an iterator which generates an interleaved integer sequence.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 18014398509481984.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterIntegersSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().value\n    -1\n\n    See Also\n    --------\n    iterNegativeIntegersSeq, iterNonNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterPositiveIntegersSeq\n","iterIntersection":"\niterIntersection( iter0, ...iterator )\n    Returns an iterator which returns the intersection of two or more iterators.\n\n    Value \"uniqueness\" is determined according to strict equality.\n\n    A returned iterator internally buffers unique values and, thus, has O(N)\n    memory requirements, where `N` is the length of the first iterator.\n\n    Do *not* provide iterators having infinite length.\n\n    If an environment supports Symbol.iterator and all provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iter0: Object\n        Input iterator.\n\n    iterator: ...Object\n        Input iterators.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n    > var it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\n    > var it = iterIntersection( it1, it2 );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    2\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterIntersectionByHash, iterUnion, iterUnique\n","iterIntersectionByHash":"\niterIntersectionByHash( iter0, ...iterator, hashFcn[, thisArg] )\n    Returns an iterator which returns the intersection of two or more iterators\n    according to a hash function.\n\n    An iterated value is considered \"unique\" if the hash function returns a\n    unique hash value for that iterated value. Beware that this *may* result in\n    unexpected behavior. Namely, only the first iterated value mapping to a\n    particular hash function result is returned, even if subsequent values,\n    while mapping to the same hash, are different. Accordingly, iteration order\n    *does* matter.\n\n    A returned iterator internally buffers unique hashes, along with the *first*\n    iterated value resolving to a hash, and, thus, has O(N) memory requirements,\n    where `N` is the length of the first iterator.\n\n    Do *not* provide iterators having infinite length.\n\n    If an environment supports Symbol.iterator and all provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iter0: Object\n        Input iterator.\n\n    iterator: ...Object\n        Input iterators.\n\n    hashFcn: Function\n        Hash function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n    > var it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\n    > function f( v ) { return v.toString(); };\n    > var it = iterIntersectionByHash( it1, it2, f );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    2\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterIntersection, iterUniqueByHash\n","iterInv":"\niterInv( iterator )\n    Returns an iterator which iteratively computes the multiplicative inverse.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterInv( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.inv, iterPow\n","iterLanczosPulse":"\niterLanczosPulse( [options] )\n    Returns an iterator which generates a Lanczos pulse waveform.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Pulse period (i.e., the number of iterations until a waveform repeats).\n        Default: 100.\n\n    options.duration: integer (optional)\n        Pulse duration. Must be greater than 2. Default: options.period.\n\n    options.amplitude: number (optional)\n        Amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterLanczosPulse();\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterPulse, iterPeriodicSinc\n","iterLast":"\niterLast( iterator )\n    Consumes an entire iterator and returns the last iterated value.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    Returns\n    -------\n    v: any\n        The last iterated value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n    > var v = iterLast( arr )\n    1\n\n    See Also\n    --------\n    iterFirst, iterNth\n","iterLength":"\niterLength( iterator )\n    Consumes an entire iterator and returns the number of iterated values.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    Returns\n    -------\n    len: integer\n        Iterator length.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n    > var len = iterLength( arr )\n    5\n\n    See Also\n    --------\n    iterCounter\n","iterLinspace":"\niterLinspace( start, stop[, N] )\n    Returns an iterator which returns evenly spaced numbers over a specified\n    interval.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    start: number\n        Starting value (inclusive).\n\n    stop: number\n        Stopping value (inclusive).\n\n    N: integer (optional)\n        Number of values. Default: 100.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterLinspace( 0, 99, 100 );\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n\n    See Also\n    --------\n    iterator2array, iterDatespace, iterIncrspace, iterLogspace, iterStep, iterUnitspace\n","iterLn":"\niterLn( iterator )\n    Returns an iterator which iteratively evaluates the natural logarithm.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterLn( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.ln, iterExp, iterLog10, iterLog1p, iterLog2\n","iterLog":"\niterLog( x, b )\n    Returns an iterator which iteratively computes the base `b` logarithm.\n\n    For negative `b` or `x` iterated values, the returned iterator returns\n    `NaN`.\n\n    The length of the returned iterator is equal to the length of the shortest\n    provided iterator. In other words, the returned iterator ends once *one* of\n    the provided iterators ends.\n\n    If provided a numeric value as an iterator argument, the value is broadcast\n    as an infinite iterator which always returns the provided value.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    x: Object|number\n        Input iterator.\n\n    b: Object|number\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = random.iterators.uniform( 0.0, 100.0 );\n    > var y = random.iterators.uniform( 0.0, 10.0 );\n    > var it = iterLog( x, y );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.log, iterLog10, iterLog1p, iterLog2, iterPow\n","iterLog1mexp":"\niterLog1mexp( iterator )\n    Returns an iterator which iteratively evaluates the natural logarithm of\n    `1-exp(-|x|)`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterLog1mexp( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.log1mexp, iterLog, iterLog1p, iterLog1pexp, iterPow\n","iterLog1p":"\niterLog1p( iterator )\n    Returns an iterator which iteratively evaluates the natural logarithm of\n    `1+x`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterLog1p( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.log1p, iterLog, iterLog10, iterLog2, iterPow\n","iterLog1pexp":"\niterLog1pexp( iterator )\n    Returns an iterator which iteratively evaluates the natural logarithm of\n    `1+exp(x)`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterLog1pexp( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.log1pexp, iterLog, iterLog1p, iterLog1mexp, iterPow\n","iterLog2":"\niterLog2( iterator )\n    Returns an iterator which iteratively evaluates the binary logarithm.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterLog2( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.log2, iterLog, iterLog10, iterLog1p, iterPow\n","iterLog10":"\niterLog10( iterator )\n    Returns an iterator which iteratively evaluates the common logarithm\n    (logarithm with base 10).\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterLog10( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.log10, iterLog, iterLog1p, iterLog2, iterPow\n","iterLogit":"\niterLogit( iterator )\n    Returns an iterator which iteratively evaluates the logit function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 1.0 );\n    > var it = iterLogit( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.logit\n","iterLogspace":"\niterLogspace( start, stop[, N][, options] )\n    Returns an iterator which returns evenly spaced numbers on a log scale.\n\n    In linear space, the sequence starts at `base` raised to the power of\n    `start` and ends with `base` raised to the power of `stop`.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    start: number\n        Exponent of starting value.\n\n    stop: number\n        Exponent of stopping value.\n\n    N: integer (optional)\n        Number of values. Default: 100.\n\n    options: Object (optional)\n        Function options.\n\n    options.base: number (optional)\n        Base of log space. Default: 10.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterLogspace( 0, 3, 4 );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    10\n\n    See Also\n    --------\n    iterator2array, iterDatespace, iterIncrspace, iterLinspace, iterStep\n","iterLucasSeq":"\niterLucasSeq( [options] )\n    Returns an iterator which generates a Lucas sequence.\n\n    The returned iterator can only generate the first 77 Lucas numbers, as\n    larger Lucas numbers cannot be safely represented in double-precision\n    floating-point format.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 77.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterLucasSeq();\n    > var v = it.next().value\n    2\n    > v = it.next().value\n    1\n\n    See Also\n    --------\n    base.lucas, iterFibonacciSeq, iterNegaLucasSeq\n","iterMap":"\niterMap( iterator, fcn[, thisArg] )\n    Returns an iterator which invokes a function for each iterated value.\n\n    When invoked, the input function is provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index (zero-based).\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    fcn: Function\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > function f( v ) { return v * 10.0; };\n    > var it = iterMap( random.iterators.randu(), f );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterFilter, iterFilterMap, iterForEach, iterReject\n","iterMapN":"\niterMapN( iter0, ...iterator, fcn[, thisArg] )\n    Returns an iterator which transforms iterated values from two or more\n    iterators by applying the iterated values as arguments to a provided\n    function.\n\n    When invoked, the callback function is provided `N+1` arguments, where `N`\n    is the number of provided iterators and the last argument is the iteration\n    index:\n\n    - ...value: iterated values.\n    - index: iteration index (zero-based).\n\n    The length of the returned iterator is equal to the length of the shortest\n    provided iterator. In other words, the returned iterator ends once *one* of\n    the provided iterators ends.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iter0: Object\n        Input iterator.\n\n    iterator: ...Object\n        Iterators.\n\n    fcn: Function\n        Function to invoke with iterated values.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1.0, 2.0 ] );\n    > var it2 = array2iterator( [ 3.0, 4.0 ] );\n    > function fcn( x, y ) { return x + y; };\n    > var it = iterMapN( it1, it2, fcn );\n    > var v = it.next().value\n    4.0\n    > v = it.next().value\n    6.0\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterMap\n","itermax":"\nitermax( iterator )\n    Computes the maximum value of all iterated values.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Maximum value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var m = itermax( arr )\n    3.0\n\n    See Also\n    --------\n    itermidrange, itermin, itermmax, iterrange\n","itermaxabs":"\nitermaxabs( iterator )\n    Computes the maximum absolute value of all iterated values.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Maximum absolute value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var m = itermaxabs( arr )\n    4.0\n\n    See Also\n    --------\n    itermax, iterminabs, itermmaxabs\n","itermean":"\nitermean( iterator )\n    Computes an arithmetic mean over all iterated values.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Arithmetic mean.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var m = itermean( arr )\n    2.5\n\n    See Also\n    --------\n    itermidrange, itermmean, iterstdev, itersum, itervariance\n","itermeanabs":"\nitermeanabs( iterator )\n    Computes an arithmetic mean of absolute values for all iterated values.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Arithmetic mean of absolute values.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\n    > var m = itermeanabs( arr )\n    2.5\n\n    See Also\n    --------\n    itermean, itermmeanabs, itersumabs\n","itermeanabs2":"\nitermeanabs2( iterator )\n    Computes an arithmetic mean of squared absolute values for all iterated\n    values.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Arithmetic mean of squared absolute values.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\n    > var m = itermeanabs2( arr )\n    7.5\n\n    See Also\n    --------\n    itermean, itermeanabs, itermmeanabs2, itersumabs2\n","itermidrange":"\nitermidrange( iterator )\n    Computes the mid-range of all iterated values.\n\n    The mid-range is the arithmetic mean of maximum and minimum values.\n    Accordingly, the mid-range is the midpoint of the range and a measure of\n    central tendency.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Mid-range.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var v = itermidrange( arr )\n    -0.5\n\n    See Also\n    --------\n    itermean, itermax, itermin, iterrange\n","itermin":"\nitermin( iterator )\n    Computes the minimum value of all iterated values.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Minimum value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\n    > var m = itermin( arr )\n    -3.0\n\n    See Also\n    --------\n    itermax, itermidrange, itermmin, iterrange\n","iterminabs":"\niterminabs( iterator )\n    Computes the minimum absolute value of all iterated values.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Minimum absolute value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var m = iterminabs( arr )\n    1.0\n\n    See Also\n    --------\n    itermaxabs, itermin, itermminabs\n","itermmax":"\nitermmax( iterator, W )\n    Returns an iterator which iteratively computes a moving maximum value.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving maximum value.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermmax( arr, 3 );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    2.0\n    > m = it.next().value\n    3.0\n    > m = it.next().value\n    5.0\n\n    See Also\n    --------\n    itermax, itermmidrange, itermmin, itermrange\n","itermmaxabs":"\nitermmaxabs( iterator, W )\n    Returns an iterator which iteratively computes a moving maximum absolute\n    value.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving maximum absolute value.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermmaxabs( arr, 3 );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    5.0\n    > m = it.next().value\n    5.0\n    > m = it.next().value\n    5.0\n\n    See Also\n    --------\n    itermaxabs, itermmax, itermminabs\n","itermmean":"\nitermmean( iterator, W )\n    Returns an iterator which iteratively computes a moving arithmetic mean.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving mean.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermmean( arr, 3 );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    -1.5\n    > m = it.next().value\n    0.0\n    > m = it.next().value\n    1.0\n\n    See Also\n    --------\n    itermean, itermsum\n","itermmeanabs":"\nitermmeanabs( iterator, W )\n    Returns an iterator which iteratively computes a moving arithmetic mean of\n    absolute values.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving mean of absolute values.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermmeanabs( arr, 3 );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    3.5\n    > m = it.next().value\n    ~3.33\n    > m = it.next().value\n    ~4.33\n\n    See Also\n    --------\n    itermeanabs, itermmean, itermsumabs\n","itermmeanabs2":"\nitermmeanabs2( iterator, W )\n    Returns an iterator which iteratively computes a moving arithmetic mean of\n    squared absolute values.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving mean of squared absolute values.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermmeanabs2( arr, 3 );\n    > var m = it.next().value\n    4.0\n    > m = it.next().value\n    14.5\n    > m = it.next().value\n    ~12.67\n    > m = it.next().value\n    ~19.67\n\n    See Also\n    --------\n    itermeanabs2, itermmeanabs, itermsumabs2\n","itermmidrange":"\nitermmidrange( iterator, W )\n    Returns an iterator which iteratively computes a moving mid-range.\n\n    The mid-range is the arithmetic mean of maximum and minimum values.\n    Accordingly, the mid-range is the midpoint of the range and a measure of\n    central tendency.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving mid-range.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermmidrange( arr, 3 );\n    > var v = it.next().value\n    2.0\n    > v = it.next().value\n    -1.5\n    > v = it.next().value\n    -1.0\n    > v = it.next().value\n    0.0\n\n    See Also\n    --------\n    itermidrange, itermmean, itermmax, itermmin, itermrange\n","itermmin":"\nitermmin( iterator, W )\n    Returns an iterator which iteratively computes a moving minimum value.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving minimum value.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermmin( arr, 3 );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    -5.0\n    > m = it.next().value\n    -5.0\n    > m = it.next().value\n    -5.0\n\n    See Also\n    --------\n    itermin, itermmax, itermmidrange, itermrange\n","itermminabs":"\nitermminabs( iterator, W )\n    Returns an iterator which iteratively computes a moving minimum absolute\n    value.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving minimum absolute value.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermminabs( arr, 3 );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    2.0\n    > m = it.next().value\n    2.0\n    > m = it.next().value\n    3.0\n\n    See Also\n    --------\n    iterminabs, itermmaxabs, itermmin\n","iterMod":"\niterMod( iter0, ...iterator )\n    Returns an iterator which performs an element-wise modulo operation of two\n    or more iterators.\n\n    The length of the returned iterator is equal to the length of the shortest\n    provided iterator. In other words, the returned iterator ends once *one* of\n    the provided iterators ends.\n\n    If provided a numeric value as an iterator argument, the value is broadcast\n    as an infinite iterator which always returns the provided value.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iter0: Object\n        Input iterator.\n\n    iterator: ...Object\n        Iterators whose values are used as divisors.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 3.0, 2.0 ] );\n    > var it2 = array2iterator( [ 1.0, 4.0 ] );\n    > var it = iterMod( it1, it2 );\n    > var v = it.next().value\n    0.0\n    > v = it.next().value\n    2.0\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterDivide\n","itermprod":"\nitermprod( iterator, W )\n    Returns an iterator which iteratively computes a moving product.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving product.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermprod( arr, 3 );\n    > var p = it.next().value\n    2.0\n    > p = it.next().value\n    -10.0\n    > p = it.next().value\n    -30.0\n    > p = it.next().value\n    -75.0\n\n    See Also\n    --------\n    itermsum, iterprod\n","itermrange":"\nitermrange( iterator, W )\n    Returns an iterator which iteratively computes a moving range.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving range.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermrange( arr, 3 );\n    > var m = it.next().value\n    0.0\n    > m = it.next().value\n    7.0\n    > m = it.next().value\n    8.0\n    > m = it.next().value\n    10.0\n\n    See Also\n    --------\n    itermmax, itermmean, itermmin, iterrange\n","itermsum":"\nitermsum( iterator, W )\n    Returns an iterator which iteratively computes a moving sum.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving sum.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator and the provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermsum( arr, 3 );\n    > var s = it.next().value\n    2.0\n    > s = it.next().value\n    -3.0\n    > s = it.next().value\n    0.0\n    > s = it.next().value\n    3.0\n\n    See Also\n    --------\n    itermmean, itersum\n","itermsumabs":"\nitermsumabs( iterator, W )\n    Returns an iterator which iteratively computes a moving sum of absolute\n    values.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving sum.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermsumabs( arr, 3 );\n    > var s = it.next().value\n    2.0\n    > s = it.next().value\n    7.0\n    > s = it.next().value\n    10.0\n    > s = it.next().value\n    13.0\n\n    See Also\n    --------\n    itermmeanabs, itermsum, itersum, itersumabs\n","itermsumabs2":"\nitermsumabs2( iterator, W )\n    Returns an iterator which iteratively computes a moving sum of squared\n    absolute values.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving sum.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermsumabs2( arr, 3 );\n    > var s = it.next().value\n    4.0\n    > s = it.next().value\n    29.0\n    > s = it.next().value\n    38.0\n    > s = it.next().value\n    59.0\n\n    See Also\n    --------\n    itermmeanabs2, itermsumabs, itersumabs, itersumabs2\n","iterMultiply":"\niterMultiply( iter0, ...iterator )\n    Returns an iterator which performs element-wise multiplication of two or\n    more iterators.\n\n    The length of the returned iterator is equal to the length of the shortest\n    provided iterator. In other words, the returned iterator ends once *one* of\n    the provided iterators ends.\n\n    If provided a numeric value as an iterator argument, the value is broadcast\n    as an infinite iterator which always returns the provided value.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iter0: Object\n        Input iterator.\n\n    iterator: ...Object\n        Iterators to multiply.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1.0, 2.0 ] );\n    > var it2 = array2iterator( [ 3.0, 4.0 ] );\n    > var it = iterMultiply( it1, it2 );\n    > var v = it.next().value\n    3.0\n    > v = it.next().value\n    8.0\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterAdd, iterDivide, iterSubtract\n","iterNegaFibonacciSeq":"\niterNegaFibonacciSeq( [options] )\n    Returns an iterator which generates a negaFibonacci sequence.\n\n    The returned iterator can only generate the first 79 negaFibonacci numbers,\n    as larger negaFibonacci numbers cannot be safely represented in double-\n    precision floating-point format.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 79.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterNegaFibonacciSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n\n    See Also\n    --------\n    base.negafibonacci, iterFibonacciSeq, iterNonFibonacciSeq\n","iterNegaLucasSeq":"\niterNegaLucasSeq( [options] )\n    Returns an iterator which generates a negaLucas sequence.\n\n    The returned iterator can only generate the first 77 negaLucas numbers, as\n    larger negaLucas numbers cannot be safely represented in double-precision\n    floating-point format.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 77.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterNegaLucasSeq();\n    > var v = it.next().value\n    2\n    > v = it.next().value\n    -1\n\n    See Also\n    --------\n    base.negalucas, iterLucasSeq, iterNegaFibonacciSeq\n","iterNegativeEvenIntegersSeq":"\niterNegativeEvenIntegersSeq( [options] )\n    Returns an iterator which generates a sequence of negative even integers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 4503599627370496.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterNegativeEvenIntegersSeq();\n    > var v = it.next().value\n    -2\n    > v = it.next().value\n    -4\n\n    See Also\n    --------\n    iterEvenIntegersSeq, iterIntegersSeq, iterNegativeIntegersSeq, iterNegativeOddIntegersSeq, iterPositiveEvenIntegersSeq, iterNonPositiveEvenIntegersSeq\n","iterNegativeIntegersSeq":"\niterNegativeIntegersSeq( [options] )\n    Returns an iterator which generates a negative integer sequence.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 9007199254740991.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterNegativeIntegersSeq();\n    > var v = it.next().value\n    -1\n    > v = it.next().value\n    -2\n\n    See Also\n    --------\n    iterIntegersSeq, iterNonNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterPositiveIntegersSeq\n","iterNegativeOddIntegersSeq":"\niterNegativeOddIntegersSeq( [options] )\n    Returns an iterator which generates a sequence of negative odd integers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 4503599627370496.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterNegativeOddIntegersSeq();\n    > var v = it.next().value\n    -1\n    > v = it.next().value\n    -3\n\n    See Also\n    --------\n    iterOddIntegersSeq, iterIntegersSeq, iterNegativeIntegersSeq, iterNegativeEvenIntegersSeq, iterPositiveOddIntegersSeq\n","iterNone":"\niterNone( iterator )\n    Tests whether all iterated values are falsy.\n\n    The function immediately returns upon encountering a truthy value.\n\n    If provided an iterator which does not return any iterated values, the\n    function returns `true`.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `false` if a value is truthy; otherwise, the\n        function returns `true`.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n    > var bool = iterNone( arr )\n    false\n\n    See Also\n    --------\n    iterAny, iterEvery, iterForEach, iterNoneBy, iterSome\n","iterNoneBy":"\niterNoneBy( iterator, predicate[, thisArg ] )\n    Tests whether every iterated value fails a test implemented by a predicate\n    function.\n\n    The predicate function is provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index.\n\n    The function immediately returns upon encountering a truthy return value.\n\n    If provided an iterator which does not return any iterated values, the\n    function returns `true`.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if a predicate function returns a falsy\n        value for all iterated values. Otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\n    > function fcn( v ) { return ( v <= 0 ); };\n    > var bool = iterNoneBy( arr, fcn )\n    true\n\n    See Also\n    --------\n    iterAnyBy, iterEveryBy, iterForEach, iterNone, iterSomeBy\n","iterNonFibonacciSeq":"\niterNonFibonacciSeq( [options] )\n    Returns an iterator which generates a non-Fibonacci integer sequence.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterNonFibonacciSeq();\n    > var v = it.next().value\n    4\n    > v = it.next().value\n    6\n\n    See Also\n    --------\n    base.nonfibonacci, iterFibonacciSeq\n","iterNonNegativeEvenIntegersSeq":"\niterNonNegativeEvenIntegersSeq( [options] )\n    Returns an iterator which generates a sequence of nonnegative even integers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 4503599627370497.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterNonNegativeEvenIntegersSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    iterEvenIntegersSeq, iterIntegersSeq, iterNonNegativeIntegersSeq, iterNonPositiveEvenIntegersSeq, iterPositiveEvenIntegersSeq\n","iterNonNegativeIntegersSeq":"\niterNonNegativeIntegersSeq( [options] )\n    Returns an iterator which generates a nonnegative integer sequence.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 9007199254740992.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterNonNegativeIntegersSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n\n    See Also\n    --------\n    iterIntegersSeq, iterNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterPositiveIntegersSeq\n","iterNonPositiveEvenIntegersSeq":"\niterNonPositiveEvenIntegersSeq( [options] )\n    Returns an iterator which generates a sequence of nonpositive even integers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 4503599627370497.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterNonPositiveEvenIntegersSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    -2\n\n    See Also\n    --------\n    iterEvenIntegersSeq, iterIntegersSeq, iterNonNegativeEvenIntegersSeq, iterNonPositiveIntegersSeq, iterNegativeEvenIntegersSeq\n","iterNonPositiveIntegersSeq":"\niterNonPositiveIntegersSeq( [options] )\n    Returns an iterator which generates a nonpositive integer sequence.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 9007199254740992.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterNonPositiveIntegersSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    -1\n\n    See Also\n    --------\n    iterIntegersSeq, iterNegativeIntegersSeq, iterNonNegativeIntegersSeq, iterPositiveIntegersSeq\n","iterNonSquaresSeq":"\niterNonSquaresSeq( [options] )\n    Returns an iterator which generates a sequence of nonsquares.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 9007199349647256.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterNonSquaresSeq();\n    > var v = it.next().value\n    2\n    > v = it.next().value\n    3\n    > v = it.next().value\n    5\n\n    See Also\n    --------\n    iterCubesSeq, iterSquaresSeq\n","iterNth":"\niterNth( iterator, n )\n    Returns the nth iterated value.\n\n    If `n` exceeds the total number of iterations, the function returns\n    `undefined`.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    n: integer\n        Iteration number.\n\n    Returns\n    -------\n    v: any\n        The nth iterated value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 0, 0, 1, 0, 0 ] );\n    > var v = iterNth( arr, 3 )\n    1\n\n    See Also\n    --------\n    iterFirst, iterLast\n","iterOddIntegersSeq":"\niterOddIntegersSeq( [options] )\n    Returns an iterator which generates an interleaved sequence of odd integers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 9007199254740992.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterOddIntegersSeq();\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    -1\n    > v = it.next().value\n    3\n\n    See Also\n    --------\n    iterEvenIntegersSeq, iterIntegersSeq\n","iterPeriodicSinc":"\niterPeriodicSinc( n[, options] )\n    Returns an iterator which generates a periodic sinc waveform.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    n: integer\n        Order.\n\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Period (i.e., the number of iterations before a waveform repeats).\n        Default: 100.\n\n    options.amplitude: number (optional)\n        Peak amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterPeriodicSinc( 7 );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterSineWave\n","iterPipeline":"\niterPipeline( iterFcn[, ...iterFcn] )\n    Returns an iterator pipeline.\n\n    Parameters\n    ----------\n    iterFcn: Function|Array\n        Iterator function or an array of iterator functions.\n\n    iterFcn: ...Function (optional)\n        Iterator functions.\n\n    Returns\n    -------\n    fcn( src ): Function\n        Iterator pipeline which accepts a single argument, a source iterator.\n\n    Examples\n    --------\n    > var it1 = iterThunk( iterHead, 100 );\n    > function f( r ) { return ( r > 0.95 ); };\n    > var it2 = iterThunk( iterSomeBy, 5, f );\n    > var p = iterPipeline( it1, it2 );\n    > var bool = p( random.iterators.randu() )\n    <boolean>\n\n    See Also\n    --------\n    iterFlow, iterThunk\n","iterPop":"\niterPop( iterator[, clbk[, thisArg]] )\n    Returns an iterator which skips the last value of a provided iterator.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    clbk: Function (optional)\n        Callback to invoke with the skipped value.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2 ] );\n    > var it2 = iterPop( it1 );\n    > var v = it2.next().value\n    1\n    > var bool = it2.next().done\n    true\n\n    See Also\n    --------\n    iterPush, iterShift, iterSlice\n","iterPositiveEvenIntegersSeq":"\niterPositiveEvenIntegersSeq( [options] )\n    Returns an iterator which generates a sequence of positive even integers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 4503599627370496.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterPositiveEvenIntegersSeq();\n    > var v = it.next().value\n    2\n    > v = it.next().value\n    4\n\n    See Also\n    --------\n    iterEvenIntegersSeq, iterIntegersSeq, iterNegativeEvenIntegersSeq, iterNonNegativeEvenIntegersSeq, iterPositiveIntegersSeq, iterPositiveOddIntegersSeq\n","iterPositiveIntegersSeq":"\niterPositiveIntegersSeq( [options] )\n    Returns an iterator which generates a positive integer sequence.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 9007199254740991.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterPositiveIntegersSeq();\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    iterNonNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterNegativeIntegersSeq\n","iterPositiveOddIntegersSeq":"\niterPositiveOddIntegersSeq( [options] )\n    Returns an iterator which generates a sequence of positive odd integers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 4503599627370496.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterPositiveOddIntegersSeq();\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    3\n\n    See Also\n    --------\n    iterOddIntegersSeq, iterIntegersSeq, iterNegativeOddIntegersSeq, iterPositiveEvenIntegersSeq, iterPositiveIntegersSeq\n","iterPow":"\niterPow( base, exponent )\n    Returns an iterator which iteratively evaluates the exponential function.\n\n    The length of the returned iterator is equal to the length of the shortest\n    provided iterator. In other words, the returned iterator ends once *one* of\n    the provided iterators ends.\n\n    If provided a numeric value as an iterator argument, the value is broadcast\n    as an infinite iterator which always returns the provided value.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    base: Object|number\n        Input iterator.\n\n    exponent: Object|number\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = random.iterators.uniform( 0.0, 2.0 );\n    > var y = random.iterators.uniform( -2.0, 2.0 );\n    > var it = iterPow( x, y );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.pow, iterExp, iterLog\n","iterPrimesSeq":"\niterPrimesSeq( [options] )\n    Returns an iterator which generates a sequence of prime numbers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 245181918813464.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterPrimesSeq();\n    > var v = it.next().value\n    2\n    > v = it.next().value\n    3\n    > v = it.next().value\n    5\n\n    See Also\n    --------\n    iterCompositesSeq, iterIntegersSeq, iterPositiveIntegersSeq\n","iterprod":"\niterprod( iterator )\n    Computes the product of all iterated values.\n\n    For iterators which can generate many values or which may output large\n    numbers, care should be taken to prevent overflow.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Product.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var s = iterprod( arr )\n    24.0\n\n    See Also\n    --------\n    itermprod, itersum\n","iterPulse":"\niterPulse( [options] )\n    Returns an iterator which generates a pulse waveform.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Pulse period (i.e., the number of iterations until a waveform repeats).\n        Default: 10.\n\n    options.duration: integer (optional)\n        Pulse duration (i.e., the number of consecutive iterations of maximum\n        amplitude during one period). Default: floor(options.period/2).\n\n    options.min: number (optional)\n        Minimum amplitude. Default: 0.0.\n\n    options.max: number (optional)\n        Maximum amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterPulse();\n    > var v = it.next().value\n    1.0\n    > v = it.next().value\n    1.0\n\n    See Also\n    --------\n    iterSawtoothWave, iterSineWave, iterSquareWave, iterTriangleWave\n","iterPush":"\niterPush( iterator, ...items )\n    Returns an iterator which appends additional values to the end of a provided\n    iterator.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    items: ...any\n        Items to append.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2 ] );\n    > var it2 = iterPush( it1, 3, 4 );\n    > var v = it2.next().value\n    1\n    > v = it2.next().value\n    2\n    > v = it2.next().value\n    3\n    > v = it2.next().value\n    4\n    > var bool = it2.next().done\n    true\n\n    See Also\n    --------\n    iterConcat, iterUnshift\n","iterRad2deg":"\niterRad2deg( iterator )\n    Returns an iterator which iteratively converts an angle from radians to\n    degrees.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 6.28 );\n    > var it = iterRad2deg( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.rad2deg, iterDeg2rad\n","iterRamp":"\niterRamp( iterator )\n    Returns an iterator which iteratively evaluates the ramp function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterRamp( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.ramp\n","iterrange":"\niterrange( iterator )\n    Computes the range of all iterated values.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Range.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var v = iterrange( arr )\n    7.0\n\n    See Also\n    --------\n    itermax, itermean, itermin, itermrange\n","iterReject":"\niterReject( iterator, predicate[, thisArg] )\n    Returns an iterator which rejects a provided iterator's values according to\n    a predicate function.\n\n    When invoked, the predicate function is provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index (zero-based).\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    predicate: Function\n        Predicate function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > function f( v ) { return ( v > 2 ); };\n    > var it1 = array2iterator( [ 1, 3, 2, 4 ] );\n    > var it2 = iterReject( it1, f );\n    > var v = it2.next().value\n    1\n    > v = it2.next().value\n    2\n\n    See Also\n    --------\n    iterFilter, iterMap\n","iterReplicate":"\niterReplicate( iterator, n )\n    Returns an iterator which replicates each iterated value `n` times.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    n: integer\n        Number of times each iterated value is replicated.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2, 3, 4 ] );\n    > var it2 = iterReplicate( it1, 2 );\n    > var v = it2.next().value\n    1\n    > v = it2.next().value\n    1\n    > v = it2.next().value\n    2\n    > v = it2.next().value\n    2\n\n    See Also\n    --------\n    iterReplicateBy\n","iterReplicateBy":"\niterReplicateBy( iterator, fcn[, thisArg] )\n    Returns an iterator which replicates each iterated value according to a\n    provided function.\n\n    The callback function is provided three arguments:\n\n    - value: iterated value.\n    - index: source iteration index (zero-based).\n    - n: iteration index (zero-based).\n\n    The callback function is invoked *once* per iterated value of the provided\n    iterator.\n\n    The callback function *must* return an integer value. If the return value is\n    less than or equal to zero, the returned iterator skips an iterated value\n    and invokes the callback for the next iterated value of the provided\n    iterator.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    fcn: Function\n        Function which returns the number of times an iterated value should be\n        replicated.\n\n    thisArg: any (optional)\n        Callback function execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2, 3, 4 ] );\n    > function f( v, i ) { return i + 1; };\n    > var it2 = iterReplicateBy( it1, f );\n    > var v = it2.next().value\n    1\n    > v = it2.next().value\n    2\n    > v = it2.next().value\n    2\n    > v = it2.next().value\n    3\n    > v = it2.next().value\n    3\n    > v = it2.next().value\n    3\n    > v = it2.next().value\n    4\n\n    See Also\n    --------\n    iterReplicate\n","iterRound":"\niterRound( iterator )\n    Returns an iterator which rounds each iterated value to the nearest integer.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterRound( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.round, iterCeil, iterFloor, iterTrunc\n","iterRound2":"\niterRound2( iterator )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    two on a linear scale.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterRound2( random.iterators.uniform( -100.0, 100.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.round2, iterCeil2, iterFloor2, iterRound, iterRound10, iterTrunc2\n","iterRound10":"\niterRound10( iterator )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    10 on a linear scale.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterRound10( random.iterators.uniform( -100.0, 100.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.round10, iterCeil10, iterFloor10, iterRound, iterRound2, iterTrunc10\n","iterRsqrt":"\niterRsqrt( iterator )\n    Returns an iterator which iteratively computes the reciprocal (inverse)\n    square root.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterRsqrt( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.rsqrt, iterSqrt\n","iterSawtoothWave":"\niterSawtoothWave( [options] )\n    Returns an iterator which generates a sawtooth wave.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Period (i.e., the number of iterations before a waveform repeats).\n        Default: 10.\n\n    options.amplitude: number (optional)\n        Peak amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterSawtoothWave();\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterPulse, iterSineWave, iterSquareWave, iterTriangleWave\n","iterShift":"\niterShift( iterator[, clbk[, thisArg]] )\n    Returns an iterator which skips the first value of a provided iterator.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    clbk: Function (optional)\n        Callback to invoke with the skipped value.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2 ] );\n    > var it2 = iterShift( it1 );\n    > var v = it2.next().value\n    2\n    > var bool = it2.next().done\n    true\n\n    See Also\n    --------\n    iterPop, iterSlice, iterUnshift\n","iterSignum":"\niterSignum( iterator )\n    Returns an iterator which iteratively evaluates the signum function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterSignum( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.signum\n","iterSin":"\niterSin( iterator )\n    Returns an iterator which iteratively computes the sine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterSin( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.sin, iterCos, iterSinpi, iterTan\n","iterSinc":"\niterSinc( iterator )\n    Returns an iterator which iteratively computes the normalized cardinal sine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -5.0, 5.0 );\n    > var it = iterSinc( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.sinc, iterSin\n","iterSineWave":"\niterSineWave( [options] )\n    Returns an iterator which generates a sine wave.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Period (i.e., the number of iterations before a sine wave repeats).\n        Default: 10.\n\n    options.amplitude: number (optional)\n        Peak amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterSineWave();\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterCosineWave, iterPulse, iterSawtoothWave, iterSquareWave, iterTriangleWave\n","iterSinh":"\niterSinh( iterator )\n    Returns an iterator which iteratively evaluates the hyperbolic sine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -5.0, 5.0 );\n    > var it = iterSinh( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.sinh, iterCosh, iterTanh\n","iterSinpi":"\niterSinpi( iterator )\n    Returns an iterator which computes the sine of each iterated value times π.\n\n    Computes sin(πx) more accurately than sin(pi*x), especially for large x.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterSinpi( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.sinpi, iterSin\n","iterSlice":"\niterSlice( iterator[, begin[, end]] )\n    Returns an iterator which returns a subsequence of iterated values from a\n    provided iterator.\n\n    If `end` exceeds the length of the provided iterator, the returned iterator\n    returns the subsequence of iterated values starting from `begin` until the\n    last iterated value of the provided iterator.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    begin: integer (optional)\n        Start iteration index (zero-based and inclusive). Default: 0.\n\n    end: integer (optional)\n        End iteration index (zero-based and non-inclusive).\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterSlice( random.iterators.randu(), 5, 10 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterFirst, iterHead\n","iterSome":"\niterSome( iterator, n )\n    Tests whether at least `n` iterated values are truthy.\n\n    The function immediately returns upon finding `n` truthy values.\n\n    If provided an iterator which does not return any iterated values, the\n    function returns `false`.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    n: number\n        Minimum number of truthy elements.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if an iterator returns at least `n` truthy\n        elements; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\n    > var bool = iterSome( arr, 3 )\n    true\n\n    See Also\n    --------\n    iterAny, iterEvery, iterForEach, iterNone, iterSomeBy\n","iterSomeBy":"\niterSomeBy( iterator, n, predicate[, thisArg ] )\n    Tests whether at least `n` iterated values pass a test implemented by a\n    predicate function.\n\n    The predicate function is provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index.\n\n    The function immediately returns upon encountering `n` truthy return values.\n\n    If provided an iterator which does not return any iterated values, the\n    function returns `false`.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    n: integer\n        Minimum number of successful values.\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if a predicate function returns a truthy\n        value for at least `n` iterated values. Otherwise, the function returns\n        `false`.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1, 1, 0, 0, 1 ] );\n    > function fcn( v ) { return ( v > 0 ); };\n    > var bool = iterSomeBy( arr, 3, fcn )\n    true\n\n    See Also\n    --------\n    iterAnyBy, iterEveryBy, iterForEach, iterNoneBy, iterSome\n","iterSpence":"\niterSpence( iterator )\n    Returns an iterator which iteratively evaluates Spence's function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 100.0 );\n    > var it = iterSpence( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.spence\n","iterSqrt":"\niterSqrt( iterator )\n    Returns an iterator which iteratively computes the principal square root.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterSqrt( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.sqrt, iterCbrt, iterRsqrt\n","iterSqrt1pm1":"\niterSqrt1pm1( iterator )\n    Returns an iterator which iteratively computes `sqrt(1+x) - 1` more \n    accurately for small `x`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 100.0 );\n    > var it = iterSqrt1pm1( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.sqrt1pm1, iterSqrt\n","iterSquaredTriangularSeq":"\niterSquaredTriangularSeq( [options] )\n    Returns an iterator which generates a sequence of squared triangular\n    numbers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 11585.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterSquaredTriangularSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().value\n    9\n\n    See Also\n    --------\n    iterTriangularSeq\n","iterSquaresSeq":"\niterSquaresSeq( [options] )\n    Returns an iterator which generates a sequence of squares.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 94906265.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterSquaresSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().value\n    4\n\n    See Also\n    --------\n    iterCubesSeq, iterNonSquaresSeq\n","iterSquareWave":"\niterSquareWave( [options] )\n    Returns an iterator which generates a square wave.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Period (i.e., the number of iterations before a square wave repeats).\n        This must be an even integer in order to ensure a 50% duty cycle.\n        Default: 10.\n\n    options.min: number (optional)\n        Minimum amplitude. Default: -1.0.\n\n    options.max: number (optional)\n        Maximum amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterSquareWave();\n    > var v = it.next().value\n    1.0\n    > v = it.next().value\n    1.0\n\n    See Also\n    --------\n    iterPulse, iterSawtoothWave, iterSineWave, iterTriangleWave\n","iterstdev":"\niterstdev( iterator[, mean] )\n    Computes a correct sample standard deviation over all iterated values.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    mean: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    out: number|null\n        Corrected sample standard deviation.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0 ] );\n    > var m = iterstdev( arr )\n    ~4.95\n\n    See Also\n    --------\n    itermean, itervariance\n","iterStep":"\niterStep( start, increment[, N] )\n    Returns an iterator which returns a sequence of numbers according to a\n    specified increment.\n\n    Beware that values which follow the starting value are subject to floating-\n    point rounding errors.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    start: number\n        Starting value (inclusive).\n\n    increment: number\n        Increment.\n\n    N: number (optional)\n        Number of values. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterStep( 0, 2, 10 );\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    iterator2array, iterDatespace, iterIncrspace, iterLinspace, iterLogspace, iterUnitspace\n","iterStrided":"\niterStrided( iterator, stride[, offset[, eager]] )\n    Returns an iterator which steps by a specified amount.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    stride: integer\n        Stride (i.e., step amount).\n\n    offset: integer (optional)\n        Index of the first iterated value. Default: 0.\n\n    eager: boolean (optional)\n        Boolean indicating whether to eagerly advance the input iterator when\n        provided a non-zero offset. Default: false.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\n    > var it = iterStrided( arr, 2, 1 );\n    > var r = it.next().value\n    1\n    > r = it.next().value\n    3\n\n    See Also\n    --------\n    iterAdvance, iterNth, iterStridedBy\n","iterStridedBy":"\niterStridedBy( iterator, fcn[, offset[, eager]][, thisArg] )\n    Returns an iterator which steps according to a provided callback function.\n\n    When invoked, the input function is provided four arguments:\n\n    - value: iterated value.\n    - i: input iteration index (zero-based).\n    - n: output (strided) iteration index (zero-based).\n    - curr: current stride.\n\n    The return value of the input function specifies the next stride.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    fcn: Function\n        Stride function (i.e., a function which returns the step amount).\n\n    offset: integer (optional)\n        Index of the first iterated value. Default: 0.\n\n    eager: boolean (optional)\n        Boolean indicating whether to eagerly advance the input iterator when\n        provided a non-zero offset. Default: false.\n\n    thisArg: any (optional)\n        Stride function execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\n    > function stride( v, i ) { return (i % 10)+1; };\n    > var it = iterStridedBy( arr, stride );\n    > var r = it.next().value\n    0\n    > r = it.next().value\n    1\n    > r = it.next().value\n    3\n\n    See Also\n    --------\n    iterAdvance, iterNth, iterStrided\n","iterSubtract":"\niterSubtract( iter0, ...iterator )\n    Returns an iterator which performs element-wise subtraction of two or more\n    iterators.\n\n    The length of the returned iterator is equal to the length of the shortest\n    provided iterator. In other words, the returned iterator ends once *one* of\n    the provided iterators ends.\n\n    If provided a numeric value as an iterator argument, the value is broadcast\n    as an infinite iterator which always returns the provided value.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iter0: Object\n        Input iterator.\n\n    iterator: ...Object\n        Iterators to subtract.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1.0, 5.0 ] );\n    > var it2 = array2iterator( [ 3.0, 4.0 ] );\n    > var it = iterSubtract( it1, it2 );\n    > var v = it.next().value\n    -2.0\n    > v = it.next().value\n    1.0\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterAdd, iterDivide, iterMultiply\n","itersum":"\nitersum( iterator )\n    Computes the sum of all iterated values.\n\n    For iterators which can generate many values or which may output large\n    numbers, care should be taken to prevent overflow.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Sum.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var s = itersum( arr )\n    10.0\n\n    See Also\n    --------\n    itermean, itermsum, iterprod\n","itersumabs":"\nitersumabs( iterator )\n    Computes the sum of absolute values for all iterated values.\n\n    For iterators which can generate many values or which may output large\n    numbers, care should be taken to prevent overflow.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Sum of absolute values.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\n    > var s = itersumabs( arr )\n    10.0\n\n    See Also\n    --------\n    itermeanabs, itermsumabs, itersum\n","itersumabs2":"\nitersumabs2( iterator )\n    Computes the sum of squared absolute values for all iterated values.\n\n    For iterators which can generate many values or which may output large\n    numbers, care should be taken to prevent overflow.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Sum of squared absolute values.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\n    > var s = itersumabs2( arr )\n    30.0\n\n    See Also\n    --------\n    itermeanabs2, itermsumabs2, itersumabs\n","iterTan":"\niterTan( iterator )\n    Returns an iterator which iteratively evaluates the tangent.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -1.57, 1.57 );\n    > var it = iterTan( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.tan, iterCos, iterSin\n","iterTanh":"\niterTanh( iterator )\n    Returns an iterator which iteratively evaluates the hyperbolic tangent.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -4.0, 4.0 );\n    > var it = iterTanh( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.tanh, iterCosh, iterSinh, iterTan\n","iterThunk":"\niterThunk( iterFcn[, ...args] )\n    Returns an iterator \"thunk\".\n\n    A provided iterator function should have the following function signature:\n\n      iterFcn( iterator, ...args )\n\n    The returned function expects a single argument, an iterator.\n\n    This function is useful within the context of iterator pipelines as a means\n    to defer execution until a pipeline is ready for data flow.\n\n    Parameters\n    ----------\n    iterFcn: Function\n        Iterator function.\n\n    args: ...any (optional)\n        Function arguments.\n\n    Returns\n    -------\n    fcn( iter ): Function\n        Function which accepts a single argument, an iterator, and invokes a\n        previously provided iterator function with the provided iterator and any\n        previously provided arguments.\n\n    Examples\n    --------\n    > var fcn = iterThunk( iterSome, 3 );\n    > var arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\n    > var bool = fcn( arr )\n    true\n\n    See Also\n    --------\n    iterPipeline\n","iterTriangleWave":"\niterTriangleWave( [options] )\n    Returns an iterator which generates a triangle wave.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Period (i.e., the number of iterations before a waveform repeats).\n        Default: 10.\n\n    options.amplitude: number (optional)\n        Peak amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterTriangleWave();\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterPulse, iterSawtoothWave, iterSineWave, iterSquareWave\n","iterTriangularSeq":"\niterTriangularSeq( [options] )\n    Returns an iterator which generates a sequence of triangular numbers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 134217727.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterTriangularSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().value\n    3\n\n    See Also\n    --------\n    iterSquaredTriangularSeq\n","iterTribonnaciSeq":"\niterTribonnaciSeq( [options] )\n    Returns an iterator which generates a Tribonacci sequence.\n    \n    The returned iterator can only generate the first 64 Tribonacci numbers, as\n    larger Tribonacci numbers cannot be safely represented in double-precision\n    floating-point format.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 64.\n\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant\n        object has the next\n        iterated value (if one exists) and a\n        boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n\n    Examples\n    --------\n    > var it = iterTribonnaciSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    0\n\n    See Also\n    --------\n    base.tribonacci, base.fibonacci, iterLucasSeq\n","iterTrigamma":"\niterTrigamma( iterator )\n    Returns an iterator which iteratively evaluates the trigamma function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.01, 50.0 );\n    > var it = iterTrigamma( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.trigamma, iterDigamma, iterGamma\n","iterTrunc":"\niterTrunc( iterator )\n    Returns an iterator which rounds each iterated value toward zero.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterTrunc( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.trunc, iterCeil, iterFloor, iterRound\n","iterTrunc2":"\niterTrunc2( iterator )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    two toward zero.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterTrunc2( random.iterators.uniform( -100.0, 100.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.trunc2, iterCeil2, iterFloor2, iterRound2, iterTrunc\n","iterTrunc10":"\niterTrunc10( iterator )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    10 toward zero.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterTrunc10( random.iterators.uniform( -100.0, 100.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.trunc10, iterCeil10, iterFloor10, iterRound10, iterTrunc\n","iterUnion":"\niterUnion( iter0, ...iterator )\n    Returns an iterator which returns the union of two or more iterators.\n\n    Value \"uniqueness\" is determined according to strict equality.\n\n    A returned iterator internally buffers unique values and, thus, has O(N)\n    memory requirements, where `N` is the total number of source iterator\n    values.\n\n    If an environment supports Symbol.iterator and all provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iter0: Object\n        Input iterator.\n\n    iterator: ...Object\n        Input iterators.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n    > var it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\n    > var it = iterUnion( it1, it2 );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    2\n    > v = it.next().value\n    4\n    > v = it.next().value\n    5\n    > v = it.next().value\n    3\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterIntersection, iterUnique\n","iterUnique":"\niterUnique( iterator )\n    Returns an iterator which returns unique values.\n\n    Value \"uniqueness\" is determined according to strict equality.\n\n    A returned iterator internally buffers unique values and, thus, has O(N)\n    memory requirements.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n    > var it2 = iterUnique( it1 );\n    > var v = it2.next().value\n    1\n    > v = it2.next().value\n    2\n    > v = it2.next().value\n    4\n    > var bool = it2.next().done\n    true\n\n    See Also\n    --------\n    iterUniqueBy, iterUniqueByHash\n","iterUniqueBy":"\niterUniqueBy( iterator, predicate[, thisArg] )\n    Returns an iterator which returns unique values according to a predicate\n    function.\n\n    A returned iterator internally buffers unique values and, thus, has O(N)\n    memory requirements.\n\n    A predicate function is invoked for each iterated value against each value\n    in an internal buffer consisting of previously identified unique values.\n    Thus, as the number of unique values grows, so, too, does the number of\n    predicate function invocations per iterated value.\n\n    An iterated value is considered \"unique\" if the predicate function returns\n    truthy values for all comparisons of the iterated value with each value in\n    the internal buffer.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    predicate: Function\n        A binary function with parameters `a` and `b` corresponding to iterated\n        values. If the values are the same, the function should return `false`\n        (i.e., non-unique); otherwise, if the values are distinct, the function\n        should return `true` (i.e., unique).\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n    > function f( a, b ) { return ( a !== b ); };\n    > var it2 = iterUniqueBy( it1, f );\n    > var v = it2.next().value\n    1\n    > v = it2.next().value\n    2\n    > v = it2.next().value\n    4\n    > var bool = it2.next().done\n    true\n\n    See Also\n    --------\n    iterUnique, iterUniqueByHash\n","iterUniqueByHash":"\niterUniqueByHash( iterator, hashFcn[, thisArg] )\n    Returns an iterator which returns unique values according to a hash\n    function.\n\n    A returned iterator internally buffers unique hashes and, thus, has O(N)\n    memory requirements.\n\n    An iterated value is considered \"unique\" if the hash function returns a\n    unique hash value for that iterated value. Beware that this *may* result in\n    unexpected behavior. Namely, only the first iterated value mapping to a\n    particular hash function result is returned, even if subsequent values,\n    while mapping to the same hash, are different. Accordingly, iteration order\n    *does* matter.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    hashFcn: Function\n        Hash function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n    > function f( v ) { return v.toString(); };\n    > var it2 = iterUniqueByHash( it1, f );\n    > var v = it2.next().value\n    1\n    > v = it2.next().value\n    2\n    > v = it2.next().value\n    4\n    > var bool = it2.next().done\n    true\n\n    See Also\n    --------\n    iterUnique, iterUniqueBy\n","iterUnitspace":"\niterUnitspace( start[, stop] )\n    Returns an iterator which returns numbers incremented by one.\n\n    The iterator stops once the `stop` value is exceeded.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    start: number\n        Starting value (inclusive).\n\n    stop: number (optional)\n        Stopping value. Default: +infinity.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterUnitspace( 0, 99 );\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n\n    See Also\n    --------\n    iterator2array, iterIncrspace, iterLinspace, iterStep\n","iterUnshift":"\niterUnshift( iterator, ...items )\n    Returns an iterator which prepends values to the beginning of a provided\n    iterator.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    items: ...any\n        Items to prepend.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2 ] );\n    > var it2 = iterUnshift( it1, 3, 4 );\n    > var v = it2.next().value\n    3\n    > v = it2.next().value\n    4\n    > v = it2.next().value\n    1\n    > v = it2.next().value\n    2\n    > var bool = it2.next().done\n    true\n\n    See Also\n    --------\n    iterConcat, iterPush, iterShift\n","iterUntilEach":"\niterUntilEach( iterator, predicate, fcn[, thisArg] )\n    Returns an iterator which invokes a function for each iterated value before\n    returning the iterated value until either a predicate function returns true\n    or the iterator has iterated over all values.\n\n    When invoked, both input functions are provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index (zero-based).\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    predicate: Function\n        Function which indicates whether to continue iterating.\n\n    fcn: Function\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > function predicate( v ) { return v !== v };\n    > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n    > var it = iterUntilEach( random.iterators.randu(), predicate, f );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterWhileEach\n","itervariance":"\nitervariance( iterator[, mean] )\n    Computes an unbiased sample variance over all iterated values.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    mean: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    out: number|null\n        Unbiased sample variance.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0 ] );\n    > var s2 = itervariance( arr )\n    24.5\n\n    See Also\n    --------\n    itermean, iterstdev\n","iterVercos":"\niterVercos( iterator )\n    Returns an iterator which iteratively computes the versed cosine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 6.28 );\n    > var it = iterVercos( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.vercos, iterCos, iterSin, iterVersin\n","iterVersin":"\niterVersin( iterator )\n    Returns an iterator which iteratively computes the versed sine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 6.28 );\n    > var it = iterVersin( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.versin, iterCos, iterSin, iterVercos\n","iterWhileEach":"\niterWhileEach( iterator, predicate, fcn[, thisArg] )\n    Returns an iterator which invokes a function for each iterated value before\n    returning the iterated value until either a predicate function returns false\n    or the iterator has iterated over all values.\n\n    When invoked, both input functions are provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index (zero-based).\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    predicate: Function\n        Function which indicates whether to continue iterating.\n\n    fcn: Function\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === v };\n    > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n    > var it = iterWhileEach( random.iterators.randu(), predicate, f );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterUntilEach\n","iterZeta":"\niterZeta( iterator )\n    Returns an iterator which iteratively evaluates the Riemann zeta function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 1.1, 50.0 );\n    > var it = iterZeta( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.zeta\n","joinStream":"\njoinStream( [options] )\n    Returns a transform stream which joins streamed data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. Default: '\\n'.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream.\n\n    Examples\n    --------\n    > var s = joinStream();\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();\n\n\njoinStream.factory( [options] )\n    Returns a function for creating transform streams for joined streamed data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. Default: '\\n'.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    createStream: Function\n        Function for creating transform streams.\n\n    Examples\n    --------\n    > var opts = { 'highWaterMark': 64 };\n    > var createStream = joinStream.factory( opts );\n    > var s = createStream();\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();\n\n\njoinStream.objectMode( [options] )\n    Returns an \"objectMode\" transform stream for joining streamed data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. Default: '\\n'.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > var s = joinStream.objectMode();\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();\n\n    See Also\n    --------\n    splitStream\n","joinStream.factory":"\njoinStream.factory( [options] )\n    Returns a function for creating transform streams for joined streamed data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. Default: '\\n'.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    createStream: Function\n        Function for creating transform streams.\n\n    Examples\n    --------\n    > var opts = { 'highWaterMark': 64 };\n    > var createStream = joinStream.factory( opts );\n    > var s = createStream();\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();","joinStream.objectMode":"\njoinStream.objectMode( [options] )\n    Returns an \"objectMode\" transform stream for joining streamed data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. Default: '\\n'.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > var s = joinStream.objectMode();\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();\n\n    See Also\n    --------\n    splitStream","kde2d":"\nkde2d( x, y[, options] )\n    Two-dimensional kernel density estimation.\n\n    Parameters\n    ----------\n    x: Array<number>\n        Array of x values.\n\n    y: Array<number>\n        Array of y values.\n\n    options: Object (optional)\n        Function options.\n\n    options.h: number (optional)\n        Array of length two containing the bandwidth values for x and y.\n\n    options.n: number (optional)\n        Number of partitions on the x- and y-axes. Default: `25`.\n\n    options.xMin: number (optional)\n        Lower limit of x.\n\n    options.xMax: number (optional)\n        Upper limit of x.\n\n    options.yMin: number (optional)\n        Lower limit of y.\n\n    options.yMax: number (optional)\n        Upper limit of y.\n\n    options.kernel: string|Function\n        A string or function to specifying the used kernel function. Default:\n        `'gaussian'`.\n\n    Returns\n    -------\n    out: Object\n        Object containing the density estimates (`z`) along grid points (`x` and\n        `y` values).\n\n    Examples\n    --------\n    > var x = [ 1, 3, 5, 6, 21, 23, 16, 17, 20, 10 ];\n    > var y = [ 0.40, 0.20, 0.20, 0.15, 0.05, 0.55, 0.6, 0.33, 0.8, 0.41 ];\n    > var out = kde2d( x, y )\n    { 'x': [1, ... ], 'y': [0.05, ...], 'z': ndarray{Float64Array[0.031, ...] }\n\n","kebabcase":"\nkebabcase( str )\n    Converts a string to kebab case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Kebab-cased string.\n\n    Examples\n    --------\n    > var out = kebabcase( 'Hello World!' )\n    'hello-world'\n    > out = kebabcase( 'I am a tiny little teapot' )\n    'i-am-a-tiny-little-teapot'\n\n    See Also\n    --------\n    camelcase, constantcase, pascalcase, snakecase","keyBy":"\nkeyBy( collection, fcn[, thisArg] )\n    Converts a collection to an object whose keys are determined by a provided\n    function and whose values are the collection values.\n\n    When invoked, the input function is provided two arguments:\n\n    - value: collection value.\n    - index: collection index.\n\n    If more than one element in a collection resolves to the same key, the key\n    value is the collection element which last resolved to the key.\n\n    Object values are shallow copies.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Object\n        Output object.\n\n    Examples\n    --------\n    > function toKey( v ) { return v.a; };\n    > var arr = [ { 'a': 1 }, { 'a': 2 } ];\n    > keyBy( arr, toKey )\n    { '1': { 'a': 1 }, '2': { 'a': 2 } }\n\n    See Also\n    --------\n    forEach\n","keyByRight":"\nkeyByRight( collection, fcn[, thisArg] )\n    Converts a collection to an object whose keys are determined by a provided\n    function and whose values are the collection values, iterating from right to\n    left.\n\n    When invoked, the input function is provided two arguments:\n\n    - value: collection value.\n    - index: collection index.\n\n    If more than one element in a collection resolves to the same key, the key\n    value is the collection element which last resolved to the key.\n\n    Object values are shallow copies.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Object\n        Output object.\n\n    Examples\n    --------\n    > function toKey( v ) { return v.a; };\n    > var arr = [ { 'a': 1 }, { 'a': 2 } ];\n    > keyByRight( arr, toKey )\n    { '2': { 'a': 2 }, '1': { 'a': 1 } }\n\n    See Also\n    --------\n    forEachRight, keyBy\n","keysIn":"\nkeysIn( obj )\n    Returns an array of an object's own and inherited enumerable property\n    names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    Parameters\n    ----------\n    obj: any\n        Input value.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's own and inherited enumerable property names.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var keys = keysIn( obj )\n    e.g., [ 'beep', 'foo' ]\n\n    See Also\n    --------\n    objectEntriesIn, objectKeys, objectValuesIn\n","kruskalTest":"\nkruskalTest( ...x[, options] )\n    Computes the Kruskal-Wallis test for equal medians.\n\n    Parameters\n    ----------\n    x: ...Array\n        Measured values.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.groups: Array (optional)\n        Array of group indicators.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.method: string\n        Name of test.\n\n    out.df: Object\n        Degrees of freedom.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    // Data from Hollander & Wolfe (1973), p. 116:\n    > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n    > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n    > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n    > var out = kruskalTest( x, y, z )\n\n    > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n    ...     3.8, 2.7, 4.0, 2.4,\n    ...     2.8, 3.4, 3.7, 2.2, 2.0\n    ... ];\n    > var groups = [\n    ...     'a', 'a', 'a', 'a', 'a',\n    ...     'b', 'b', 'b', 'b',\n    ...     'c', 'c', 'c', 'c', 'c'\n    ... ];\n    > out = kruskalTest( arr, { 'groups': groups } )\n\n","kstest":"\nkstest( x, y[, ...params][, options] )\n    Computes a Kolmogorov-Smirnov goodness-of-fit test.\n\n    For a numeric array or typed array `x`, a Kolmogorov-Smirnov goodness-of-fit\n    is computed for the null hypothesis that the values of `x` come from the\n    distribution specified by `y`. `y` can be either a string with the name of\n    the distribution to test against, or a function.\n\n    In the latter case, `y` is expected to be the cumulative distribution\n    function (CDF) of the distribution to test against, with its first parameter\n    being the value at which to evaluate the CDF and the remaining parameters\n    constituting the parameters of the distribution. The parameters of the\n    distribution are passed as additional arguments after `y` from `kstest` to\n    the chosen CDF. The function returns an object holding the calculated test\n    statistic `statistic` and the `pValue` of the test.\n\n    The returned object comes with a `.print()` method which when invoked will\n    print a formatted output of the hypothesis test results.\n\n    Parameters\n    ----------\n    x: Array<number>\n        Input array holding numeric values.\n\n    y: Function|string\n        Either a CDF function or a string denoting the name of a distribution.\n\n    params: ...number (optional)\n        Distribution parameters passed to reference CDF.\n\n    options: Object (optional)\n        Function options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.sorted: boolean (optional)\n        Boolean indicating if the input array is already in sorted order.\n        Default: `false`.\n\n    options.alternative: string (optional)\n        Either `two-sided`, `less` or `greater`. Indicates whether the\n        alternative hypothesis is that the true distribution of `x` is not equal\n        to the reference distribution specified by `y` (`two-sided`), whether it\n        is `less` than the reference distribution or `greater` than the\n        reference distribution. Default: `'two-sided'`.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Used significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.alternative: string\n        Used test alternative. Either `two-sided`, `less` or `greater`.\n\n    out.method: string\n        Name of test.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    // Verify that data is drawn from a normal distribution:\n    > var rnorm = base.random.normal.factory({ 'seed': 4839 } );\n    > var x = new Array( 100 );\n    > for ( var i = 0; i < 100; i++ ) { x[ i ] = rnorm( 3.0, 1.0 ); }\n\n    // Test against N(0,1)\n    > var out = kstest( x, 'normal', 0.0, 1.0 )\n    { pValue: 0.0, statistic: 0.847, ... }\n\n    // Test against N(3,1)\n    > out = kstest( x, 'normal', 3.0, 1.0 )\n    { pValue: 0.6282, statistic: 0.0733, ... }\n\n    // Verify that data is drawn from a uniform distribution:\n    > runif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } )\n    > x = new Array( 100 );\n    > for ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\n    > out = kstest( x, 'uniform', 0.0, 1.0 )\n    { pValue: ~0.703, statistic: ~0.069, ... }\n\n    // Print output:\n    > out.print()\n    Kolmogorov-Smirnov goodness-of-fit test.\n\n    Null hypothesis: the CDF of `x` is equal equal to the reference CDF.\n\n        pValue: 0.7039\n        statistic: 0.0689\n\n    Test Decision: Fail to reject null in favor of alternative at 5%\n    significance level\n\n    // Set custom significance level:\n    > out = kstest( x, 'uniform', 0.0, 1.0, { 'alpha': 0.1 } )\n    { pValue: ~0.7039, statistic: ~0.069, ... }\n\n    // Carry out one-sided hypothesis tests:\n    > runif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } );\n    > x = new Array( 100 );\n    > for ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\n    > out = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'less' } )\n    { pValue: ~0.358, statistic: ~0.07, ... }\n    > out = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'greater' } )\n    { pValue: ~0.907, statistic: ~0.02, ... }\n\n    // Set `sorted` option to true when data is in increasing order:\n    > x = [ 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 ];\n    > out = kstest( x, 'uniform', 0.0, 1.0, { 'sorted': true } )\n    { pValue: ~1, statistic: 0.1, ... }\n\n","last":"\nlast( str[, n][, options] )\n    Returns the last character(s) of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer (optional)\n        Number of characters to return. Default: 1.\n\n    options: Object (optional)\n        Options.\n\n    options.mode: string (optional)\n        Type of characters to return. The following modes are supported:\n\n        - grapheme: grapheme clusters. Appropriate for strings containing visual\n          characters which can span multiple Unicode code points (e.g., emoji).\n        - code_point: Unicode code points. Appropriate for strings containing\n          visual characters which are comprised of more than one Unicode code\n          unit (e.g., ideographic symbols and punctuation and mathematical\n          alphanumerics).\n        - code_unit': UTF-16 code units. Appropriate for strings containing\n          visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n          common characters, such as those from the Latin, Greek, and Cyrillic\n          alphabets).\n\n        Default: 'grapheme'.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = last( 'beep' )\n    'p'\n    > out = last( 'Boop', 2 )\n    'op'\n    > out = last( 'foo bar', 3 )\n    'bar'\n\n    See Also\n    --------\n    firstChar\n","leveneTest":"\nleveneTest( x[, ...y[, options]] )\n    Computes Levene's test for equal variances.\n\n    Parameters\n    ----------\n    x: Array<number>\n        Measured values.\n\n    y: ...Array<number> (optional)\n        Measured values.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.groups: Array (optional)\n        Array of group indicators.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.method: string\n        Name of test.\n\n    out.df: Array\n        Degrees of freedom.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    // Data from Hollander & Wolfe (1973), p. 116:\n    > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n    > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n    > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n    > var out = leveneTest( x, y, z )\n\n    > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n    ...     3.8, 2.7, 4.0, 2.4,\n    ...     2.8, 3.4, 3.7, 2.2, 2.0\n    ... ];\n    > var groups = [\n    ...     'a', 'a', 'a', 'a', 'a',\n    ...     'b', 'b', 'b', 'b',\n    ...     'c', 'c', 'c', 'c', 'c'\n    ... ];\n    > out = leveneTest( arr, { 'groups': groups } )\n\n    See Also\n    --------\n    vartest, bartlettTest\n","LinkedList":"\nLinkedList()\n    Linked list constructor.\n\n    Returns\n    -------\n    list: Object\n        Linked list.\n\n    list.clear: Function\n        Clears the list.\n\n    list.first: Function\n        Returns the last node. If the list is empty, the returned value is\n        `undefined`.\n\n    list.insert: Function\n        Inserts a value after a provided list node.\n\n    list.iterator: Function\n        Returns an iterator for iterating over a list. If an environment\n        supports Symbol.iterator, the returned iterator is iterable. Note that,\n        in order to prevent confusion arising from list mutation during\n        iteration, a returned iterator **always** iterates over a list\n        \"snapshot\", which is defined as the list of list elements at the time\n        of the method's invocation.\n\n    list.last: Function\n        Returns the last list node. If the list is empty, the returned value is\n        `undefined`.\n\n    list.length: integer\n        List length.\n\n    list.pop: Function\n        Removes and returns the last list value. If the list is empty, the\n        returned value is `undefined`.\n\n    list.push: Function\n        Adds a value to the end of the list.\n\n    list.remove: Function\n        Removes a list node from the list.\n\n    list.shift: Function\n        Removes and returns the first list value. If the list is empty, the\n        returned value is `undefined`.\n\n    list.toArray: Function\n        Returns an array of list values.\n\n    list.toJSON: Function\n        Serializes a list as JSON.\n\n    list.unshift: Function\n        Adds a value to the beginning of the list.\n\n    Examples\n    --------\n    > var list = LinkedList();\n    > list.push( 'foo' ).push( 'bar' );\n    > list.length\n    2\n    > list.pop()\n    'bar'\n    > list.length\n    1\n    > list.pop()\n    'foo'\n    > list.length\n    0\n\n    See Also\n    --------\n    DoublyLinkedList, Stack\n","linspace":"\nlinspace( start, stop, length[, options] )\n    Generates a linearly spaced array over a specified interval.\n\n    If the specified length is zero, the function returns an empty array.\n\n    If the specified length is one, the function returns an array containing\n    `stop`, but not `start`, when `endpoint` is true; otherwise, the function\n    returns an array containing `start`, but not `stop`.\n\n    For real-valued `start` and `stop`, if `start` is less than `stop`, the\n    output array will contain ascending values, and, if `start` is greater than\n    `stop`, the output array will contain descending values.\n\n    When the output array length is greater than one and `endpoint` is true, the\n    output array is guaranteed to include the `start` and `stop` values. Beware,\n    however, that values between `start` and `stop` are subject to floating-\n    point rounding errors.\n\n    If both `start` and `stop` are real-valued, the output array data type may\n    be any floating-point data type or 'generic'. However, if either `start` or\n    `stop` are complex numbers, the output array type must be a complex\n    floating-point data type or 'generic'.\n\n    When writing to a complex floating-point output array, real-valued `start`\n    and `stop` values are treated as complex numbers having a real component\n    equaling the provided value and having an imaginary component equaling zero.\n\n    When generating linearly spaced complex floating-point numbers, the real and\n    imaginary components are generated separately.\n\n    Parameters\n    ----------\n    start: number|ComplexLike\n        Start of interval.\n\n    stop: number|ComplexLike\n        End of interval.\n\n    length: integer\n        Length of output array.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Must be a floating-point data type or 'generic'.\n         If both `start` and `stop` are the same type (either 'float64',\n         'complex64', or 'complex128'), the default output array data type is\n         the same type as the input values (either 'float64', 'complex64', or\n         'complex128', respectively). Otherwise, the default output array data\n         type is 'complex128'.\n\n    options.endpoint: boolean (optional)\n        Boolean indicating whether to include the `stop` value in the output\n        array. If false, the function generates `length + 1` linearly spaced\n        values over the interval `[start, stop]` and only writes `length` values\n        to the output array, thus excluding `stop` from the output array.\n        Accordingly, for a fixed `length`, the spacing between adjacent values\n        in the output array changes depending on the value of `endpoint`.\n        Default: true.\n\n    Returns\n    -------\n    arr: Array\n        Linearly spaced array.\n\n    Examples\n    --------\n    > var arr = linspace( 0.0, 100.0, 6 )\n    <Float64Array>[ 0.0, 20.0, 40.0, 60.0, 80.0, 100.0 ]\n    > arr = linspace( 0.0, 100.0, 5, { 'endpoint': false } )\n    <Float64Array>[ 0.0, 20.0, 40.0, 60.0, 80.0 ]\n    > arr = linspace( 0.0, 100.0, 6, { 'dtype': 'generic' } )\n    [ 0.0, 20.0, 40.0, 60.0, 80.0, 100.0 ]\n\n\nlinspace.assign( start, stop, out[, options] )\n    Generates a linearly spaced sequence over a specified interval and assigns\n    the results to a provided output array.\n\n    If the provided output array is empty, the function returns the provided\n    output array unchanged.\n\n    If the provided output array contains a single element, the function writes\n    the `stop` value, but not `start`, when `endpoint` is true; otherwise, the\n    function writes the `start` value, but not `stop`.\n\n    Parameters\n    ----------\n    start: number|ComplexLike\n        Start of interval.\n\n    stop: number|ComplexLike\n        End of interval.\n\n    out: ArrayLikeObject\n        Output array.\n\n    options: Object (optional)\n        Options.\n\n    options.endpoint: boolean (optional)\n        Boolean indicating whether to include the `stop` value in the output\n        array. If false, the function generates `N+1` linearly spaced values\n        (where `N` is the length of the provided output array) over the interval\n        `[start, stop]` and only writes `N` values to the output array, thus\n        excluding `stop` from the output array. Accordingly, for a fixed `N`,\n        the spacing between adjacent values in the output array changes\n        depending on the value of `endpoint`. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var arr = [ 0, 0, 0, 0, 0, 0 ];\n    > var out = linspace.assign( 0, 100, arr )\n    [ 0, 20, 40, 60, 80, 100 ]\n    > var bool = ( arr === out )\n    true\n    > arr = [ 0, 0, 0, 0, 0 ];\n    > out = linspace.assign( 0, 100, arr, { 'endpoint': false } )\n    [ 0, 20, 40, 60, 80 ]\n\n    See Also\n    --------\n    incrspace, logspace\n","linspace.assign":"\nlinspace.assign( start, stop, out[, options] )\n    Generates a linearly spaced sequence over a specified interval and assigns\n    the results to a provided output array.\n\n    If the provided output array is empty, the function returns the provided\n    output array unchanged.\n\n    If the provided output array contains a single element, the function writes\n    the `stop` value, but not `start`, when `endpoint` is true; otherwise, the\n    function writes the `start` value, but not `stop`.\n\n    Parameters\n    ----------\n    start: number|ComplexLike\n        Start of interval.\n\n    stop: number|ComplexLike\n        End of interval.\n\n    out: ArrayLikeObject\n        Output array.\n\n    options: Object (optional)\n        Options.\n\n    options.endpoint: boolean (optional)\n        Boolean indicating whether to include the `stop` value in the output\n        array. If false, the function generates `N+1` linearly spaced values\n        (where `N` is the length of the provided output array) over the interval\n        `[start, stop]` and only writes `N` values to the output array, thus\n        excluding `stop` from the output array. Accordingly, for a fixed `N`,\n        the spacing between adjacent values in the output array changes\n        depending on the value of `endpoint`. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var arr = [ 0, 0, 0, 0, 0, 0 ];\n    > var out = linspace.assign( 0, 100, arr )\n    [ 0, 20, 40, 60, 80, 100 ]\n    > var bool = ( arr === out )\n    true\n    > arr = [ 0, 0, 0, 0, 0 ];\n    > out = linspace.assign( 0, 100, arr, { 'endpoint': false } )\n    [ 0, 20, 40, 60, 80 ]\n\n    See Also\n    --------\n    incrspace, logspace","LIU_NEGATIVE_OPINION_WORDS_EN":"\nLIU_NEGATIVE_OPINION_WORDS_EN()\n    Returns a list of negative opinion words.\n\n    A word's appearance in a sentence does *not* necessarily imply a positive or\n    negative opinion.\n\n    The list includes misspelled words. Their presence is intentional, as such\n    misspellings frequently occur in social media content.\n\n    Returns\n    -------\n    out: Array<string>\n        List of negative opinion words.\n\n    Examples\n    --------\n    > var list = LIU_NEGATIVE_OPINION_WORDS_EN()\n    [ '2-faced', '2-faces', 'abnormal', 'abolish', ... ]\n\n    References\n    ----------\n    - Hu, Minqing, and Bing Liu. 2004. \"Mining and Summarizing Customer\n    Reviews.\" In *Proceedings of the Tenth Acm Sigkdd International Conference\n    on Knowledge Discovery and Data Mining*, 168–77. KDD '04. New York, NY, USA:\n    ACM. doi:10.1145/1014052.1014073.\n    - Liu, Bing, Minqing Hu, and Junsheng Cheng. 2005. \"Opinion Observer:\n    Analyzing and Comparing Opinions on the Web.\" In *Proceedings of the 14th\n    International Conference on World Wide Web*, 342–51. WWW '05. New York, NY,\n    USA: ACM. doi:10.1145/1060745.1060797.\n\n    * If you use the list for publication or third party consumption, please\n    cite one of the listed references.\n\n    See Also\n    --------\n    LIU_POSITIVE_OPINION_WORDS_EN\n","LIU_POSITIVE_OPINION_WORDS_EN":"\nLIU_POSITIVE_OPINION_WORDS_EN()\n    Returns a list of positive opinion words.\n\n    A word's appearance in a sentence does *not* necessarily imply a positive or\n    negative opinion.\n\n    The list includes misspelled words. Their presence is intentional, as such\n    misspellings frequently occur in social media content.\n\n    Returns\n    -------\n    out: Array<string>\n        List of positive opinion words.\n\n    Examples\n    --------\n    > var list = LIU_POSITIVE_OPINION_WORDS_EN()\n    [ 'a+', 'abound', 'abounds', 'abundance', ... ]\n\n    References\n    ----------\n    - Hu, Minqing, and Bing Liu. 2004. 'Mining and Summarizing Customer\n    Reviews.' In *Proceedings of the Tenth Acm Sigkdd International Conference\n    on Knowledge Discovery and Data Mining*, 168–77. KDD '04. New York, NY, USA:\n    ACM. doi:10.1145/1014052.1014073.\n    - Liu, Bing, Minqing Hu, and Junsheng Cheng. 2005. 'Opinion Observer:\n    Analyzing and Comparing Opinions on the Web.' In *Proceedings of the 14th\n    International Conference on World Wide Web*, 342–51. WWW '05. New York, NY,\n    USA: ACM. doi:10.1145/1060745.1060797.\n\n    * If you use the list for publication or third party consumption, please\n    cite one of the listed references.\n\n    See Also\n    --------\n    LIU_NEGATIVE_OPINION_WORDS_EN\n","LN_HALF":"\nLN_HALF\n    Natural logarithm of `1/2`.\n\n    Examples\n    --------\n    > LN_HALF\n    -0.6931471805599453\n\n","LN_PI":"\nLN_PI\n    Natural logarithm of the mathematical constant `π`.\n\n    Examples\n    --------\n    > LN_PI\n    1.1447298858494002\n\n    See Also\n    --------\n    PI\n","LN_SQRT_TWO_PI":"\nLN_SQRT_TWO_PI\n    Natural logarithm of the square root of `2π`.\n\n    Examples\n    --------\n    > LN_SQRT_TWO_PI\n    0.9189385332046728\n\n    See Also\n    --------\n    PI\n","LN_TWO_PI":"\nLN_TWO_PI\n    Natural logarithm of `2π`.\n\n    Examples\n    --------\n    > LN_TWO_PI\n    1.8378770664093456\n\n    See Also\n    --------\n    TWO_PI\n","LN2":"\nLN2\n    Natural logarithm of `2`.\n\n    Examples\n    --------\n    > LN2\n    0.6931471805599453\n\n    See Also\n    --------\n    LN10\n","LN10":"\nLN10\n    Natural logarithm of `10`.\n\n    Examples\n    --------\n    > LN10\n    2.302585092994046\n\n    See Also\n    --------\n    LN2\n","LOG2E":"\nLOG2E\n    Base 2 logarithm of Euler's number.\n\n    Examples\n    --------\n    > LOG2E\n    1.4426950408889634\n\n    See Also\n    --------\n    E, LOG10E\n","LOG10E":"\nLOG10E\n    Base 10 logarithm of Euler's number.\n\n    Examples\n    --------\n    > LOG10E\n    0.4342944819032518\n\n    See Also\n    --------\n    E, LOG2E\n","logspace":"\nlogspace( a, b[, length] )\n    Generates a logarithmically spaced numeric array between `10^a` and `10^b`.\n\n    If a `length` is not provided, the default output array length is `10`.\n\n    The output array includes the values `10^a` and `10^b`.\n\n    Parameters\n    ----------\n    a: number\n        Exponent of start value.\n\n    b: number\n        Exponent of end value.\n\n    length: integer (optional)\n        Length of output array. Default: `10`.\n\n    Returns\n    -------\n    arr: Array\n        Logarithmically spaced numeric array.\n\n    Examples\n    --------\n    > var arr = logspace( 0, 2, 6 )\n    [ 1, ~2.5, ~6.31, ~15.85, ~39.81, 100 ]\n\n    See Also\n    --------\n    incrspace, linspace\n","lowercase":"\nlowercase( str )\n    Converts a string to lowercase.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Lowercase string.\n\n    Examples\n    --------\n    > var out = lowercase( 'bEEp' )\n    'beep'\n\n    See Also\n    --------\n    uncapitalize, uppercase\n","lowercaseKeys":"\nlowercaseKeys( obj )\n    Converts each object key to lowercase.\n\n    The function only transforms own properties. Hence, the function does not\n    transform inherited properties.\n\n    The function shallow copies key values.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > var obj = { 'A': 1, 'B': 2 };\n    > var out = lowercaseKeys( obj )\n    { 'a': 1, 'b': 2 }\n\n    See Also\n    --------\n    uncapitalizeKeys, uppercaseKeys\n","lowess":"\nlowess( x, y[, options] )\n    Locally-weighted polynomial regression via the LOWESS algorithm.\n\n    Parameters\n    ----------\n    x: Array<number>\n        x-axis values (abscissa values).\n\n    y: Array<number>\n        Corresponding y-axis values (ordinate values).\n\n    options: Object (optional)\n        Function options.\n\n    options.f: number (optional)\n        Positive number specifying the smoothing span, i.e., the proportion of\n        points which influence smoothing at each value. Larger values\n        correspond to more smoothing. Default: `2/3`.\n\n    options.nsteps: number (optional)\n        Number of iterations in the robust fit (fewer iterations translates to\n        faster function execution). If set to zero, the nonrobust fit is\n        returned. Default: `3`.\n\n    options.delta: number (optional)\n        Nonnegative number which may be used to reduce the number of\n        computations. Default: 1/100th of the range of `x`.\n\n    options.sorted: boolean (optional)\n        Boolean indicating if the input array `x` is sorted. Default: `false`.\n\n    Returns\n    -------\n    out: Object\n        Object with ordered x-values and fitted values.\n\n    Examples\n    --------\n    > var x = new Float64Array( 100 );\n    > var y = new Float64Array( x.length );\n    > for ( var i = 0; i < x.length; i++ ) {\n    ...     x[ i ] = i;\n    ...     y[ i ] = ( 0.5*i ) + ( 10.0*base.random.randn() );\n    ... }\n    > var out = lowess( x, y );\n    > var yhat = out.y;\n\n    > var h = Plot( [ x, x ], [ y, yhat ] );\n    > h.lineStyle = [ 'none', '-' ];\n    > h.symbols = [ 'closed-circle', 'none' ];\n\n    > h.view( 'window' );\n\n","lpad":"\nlpad( str, len[, pad] )\n    Left pads a string such that the padded string has a length of at least\n    `len`.\n\n    An output string is not guaranteed to have a length of exactly `len`, but to\n    have a length of at least `len`. To generate a padded string having a length\n    equal to `len`, post-process a padded string by trimming off excess\n    characters.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    len: integer\n        Minimum string length.\n\n    pad: string (optional)\n        String used to pad. Default: ' '.\n\n    Returns\n    -------\n    out: string\n        Padded string.\n\n    Examples\n    --------\n    > var out = lpad( 'a', 5 )\n    '    a'\n    > out = lpad( 'beep', 10, 'b' )\n    'bbbbbbbeep'\n    > out = lpad( 'boop', 12, 'beep' )\n    'beepbeepboop'\n\n    See Also\n    --------\n    pad, rpad\n","ltrim":"\nltrim( str )\n    Trims whitespace from the beginning of a string.\n\n    \"Whitespace\" is defined as the following characters:\n\n    - \\f\n    - \\n\n    - \\r\n    - \\t\n    - \\v\n    - \\u0020\n    - \\u00a0\n    - \\u1680\n    - \\u2000-\\u200a\n    - \\u2028\n    - \\u2029\n    - \\u202f\n    - \\u205f\n    - \\u3000\n    - \\ufeff\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Trimmed string.\n\n    Examples\n    --------\n    > var out = ltrim( ' \\r\\n\\t  Beep \\t\\t\\n  ' )\n    'Beep \\t\\t\\n  '\n\n    See Also\n    --------\n    trim, rtrim\n","ltrimN":"\nltrimN( str, n[, chars] )\n    Trims `n` characters from the beginning of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of characters to trim.\n\n    chars: Array<string>|string (optional)\n        Characters to trim. Default: whitespace characters.\n\n    Returns\n    -------\n    out: string\n        Trimmed string.\n\n    Examples\n    --------\n    > var out = ltrimN( '  abc  ', 2 )\n    'abc  '\n    > var out = ltrimN( '!!!abc!!!', 2, '!' )\n    '!abc!!!'\n\n    See Also\n    --------\n    rtrimN, trim","MALE_FIRST_NAMES_EN":"\nMALE_FIRST_NAMES_EN()\n    Returns a list of common male first names in English speaking countries.\n\n    Returns\n    -------\n    out: Array<string>\n        List of common male first names.\n\n    Examples\n    --------\n    > var list = MALE_FIRST_NAMES_EN()\n    [ 'Aaron', 'Ab', 'Abba', 'Abbe', ... ]\n\n    References\n    ----------\n    - Ward, Grady. 2002. 'Moby Word II.' <http://www.gutenberg.org/files/3201/\n    3201.txt>.\n\n    See Also\n    --------\n    FEMALE_FIRST_NAMES_EN\n","map":"\nmap( arr, fcn[, thisArg] )\n    Applies a function to each element in an array and assigns the result to an\n    element in a new array.\n\n    The applied function is provided the following arguments:\n\n    - value: array element.\n    - index: element index.\n    - arr: input array.\n\n    The returned output array always has a \"generic\" data type. For example, if\n    provided an array-like object, the function returns a generic array. If\n    provided an ndarray, the function returns an ndarray having a \"generic\" data\n    type.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject|ndarray\n        Input array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.abs, 1 );\n    > var arr = [ -1, -2, -3, -4, -5, -6 ];\n    > var out = map( arr, f )\n    [ 1, 2, 3, 4, 5, 6 ]\n\n    // ndarray:\n    > arr = array( arr, { 'shape': [ 2, 3 ] } );\n    > out = map( arr, f );\n    > var v = out.get( 1, 1 )\n    5\n\n\nmap.assign( arr, out, fcn[, thisArg] )\n    Applies a function to each element in an array and assigns the result to an\n    element in an output array.\n\n    The applied function is provided the following arguments:\n\n    - value: array element.\n    - index: element index.\n    - arr: input array.\n\n    Input and output arrays must be either both array-like objects or both\n    ndarray-like objects.\n\n    If input and output arrays are array-like objects, the arrays must have the\n    same number of elements.\n\n    If input and output arrays are both ndarray-like objects, the arrays *must*\n    be broadcast compatible.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject|ndarray\n        Input array.\n\n    out: ArrayLikeObject|ndarray\n        Output array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.abs, 1 );\n    > var arr = [ -1, -2, -3, -4, -5, -6 ];\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > map.assign( arr, out, f );\n    > out\n    [ 1, 2, 3, 4, 5, 6 ]\n\n    // ndarray:\n    > var opts = { 'shape': [ 2, 3 ] };\n    > arr = array( arr, opts );\n    > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n    > map.assign( arr, out, f );\n    > var v = out.get( 1, 1 )\n    5\n\n    See Also\n    --------\n    mapRight, reduce\n","map.assign":"\nmap.assign( arr, out, fcn[, thisArg] )\n    Applies a function to each element in an array and assigns the result to an\n    element in an output array.\n\n    The applied function is provided the following arguments:\n\n    - value: array element.\n    - index: element index.\n    - arr: input array.\n\n    Input and output arrays must be either both array-like objects or both\n    ndarray-like objects.\n\n    If input and output arrays are array-like objects, the arrays must have the\n    same number of elements.\n\n    If input and output arrays are both ndarray-like objects, the arrays *must*\n    be broadcast compatible.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject|ndarray\n        Input array.\n\n    out: ArrayLikeObject|ndarray\n        Output array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.abs, 1 );\n    > var arr = [ -1, -2, -3, -4, -5, -6 ];\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > map.assign( arr, out, f );\n    > out\n    [ 1, 2, 3, 4, 5, 6 ]\n\n    // ndarray:\n    > var opts = { 'shape': [ 2, 3 ] };\n    > arr = array( arr, opts );\n    > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n    > map.assign( arr, out, f );\n    > var v = out.get( 1, 1 )\n    5\n\n    See Also\n    --------\n    mapRight, reduce","map2":"\nmap2( x, y, fcn[, thisArg] )\n    Applies a function to elements in two input arrays and assigns the results\n    to a new array.\n\n    The applied function is provided the following arguments:\n\n    - v1: element from first input array.\n    - v2: element from second input array.\n    - idx: element index.\n    - arrays: input arrays.\n\n    The returned output array always has a \"generic\" data type. For example, if\n    provided an array-like object, the function returns a generic array. If\n    provided an ndarray, the function returns an ndarray having a \"generic\" data\n    type.\n\n    Input arrays must be either both array-like objects or both ndarray-like\n    objects.\n\n    If input arrays are array-like objects, the arrays must have the same number\n    of elements.\n\n    If input arrays are ndarray-like objects, the arrays must be broadcast\n    compatible.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject|ndarray\n        First input array.\n\n    y: ArrayLikeObject|ndarray\n        Second input array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.add, 2 );\n    > var x = [ 1, 2, 3, 4, 5, 6 ];\n    > var y = [ 1, 1, 1, 1, 1, 1 ];\n    > var out = map2( x, y, f )\n    [ 2, 3, 4, 5, 6, 7 ]\n\n    // ndarray:\n    > x = array( x, { 'shape': [ 2, 3 ] } );\n    > y = array( y, { 'shape': [ 2, 3 ] } );\n    > out = map2( x, y, f );\n    > var v = out.get( 1, 1 )\n    6\n\n\nmap2.assign( x, y, out, fcn[, thisArg] )\n    Applies a function to elements in two input arrays and assigns the results\n    to an output array.\n\n    The applied function is provided the following arguments:\n\n    - v1: element from first input array.\n    - v2: element from second input array.\n    - idx: element index.\n    - arrays: input arrays.\n\n    Input and output arrays must be either all array-like objects or all\n    ndarray-like objects.\n\n    If input and output arrays are array-like objects, the arrays must have the\n    same number of elements.\n\n    If input and output arrays are ndarray-like objects, the arrays must be\n    broadcast compatible.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject|ndarray\n        First input array.\n\n    y: ArrayLikeObject|ndarray\n        Second input array.\n\n    out: ArrayLikeObject|ndarray\n        Output array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.add, 2 );\n    > var x = [ 1, 2, 3, 4, 5, 6 ];\n    > var y = [ 1, 1, 1, 1, 1, 1 ];\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > map2.assign( x, y, out, f );\n    > out\n    [ 2, 3, 4, 5, 6, 7 ]\n\n    // ndarray:\n    > var opts = { 'shape': [ 2, 3 ] };\n    > x = array( x, opts );\n    > y = array( y, opts );\n    > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n    > map2.assign( x, y, out, f );\n    > var v = out.get( 1, 1 )\n    6\n\n    See Also\n    --------\n    map\n","map2.assign":"\nmap2.assign( x, y, out, fcn[, thisArg] )\n    Applies a function to elements in two input arrays and assigns the results\n    to an output array.\n\n    The applied function is provided the following arguments:\n\n    - v1: element from first input array.\n    - v2: element from second input array.\n    - idx: element index.\n    - arrays: input arrays.\n\n    Input and output arrays must be either all array-like objects or all\n    ndarray-like objects.\n\n    If input and output arrays are array-like objects, the arrays must have the\n    same number of elements.\n\n    If input and output arrays are ndarray-like objects, the arrays must be\n    broadcast compatible.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject|ndarray\n        First input array.\n\n    y: ArrayLikeObject|ndarray\n        Second input array.\n\n    out: ArrayLikeObject|ndarray\n        Output array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.add, 2 );\n    > var x = [ 1, 2, 3, 4, 5, 6 ];\n    > var y = [ 1, 1, 1, 1, 1, 1 ];\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > map2.assign( x, y, out, f );\n    > out\n    [ 2, 3, 4, 5, 6, 7 ]\n\n    // ndarray:\n    > var opts = { 'shape': [ 2, 3 ] };\n    > x = array( x, opts );\n    > y = array( y, opts );\n    > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n    > map2.assign( x, y, out, f );\n    > var v = out.get( 1, 1 )\n    6\n\n    See Also\n    --------\n    map","map2d":"\nmap2d( arr, fcn[, thisArg] )\n    Applies a function to each nested element in an array of arrays and assigns\n    the result to a nested element in a new array of arrays.\n\n    The applied function is provided the following arguments:\n\n    - value: array element.\n    - indices: current array element indices.\n    - arr: input array.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject<ArrayLikeObject>\n        Input array of arrays.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array<Array>\n        Array of arrays.\n\n    Examples\n    --------\n    > var f = naryFunction( base.abs, 1 );\n    > var arr = [ [ -1, -2, -3 ], [ -4, -5, -6 ] ];\n    > var out = map2d( arr, f );\n    > out[ 0 ]\n    [ 1, 2, 3 ]\n    > out[ 1 ]\n    [ 4, 5, 6 ]\n\n    See Also\n    --------\n    map, map3d, map4d, map5d, reduce2d\n","map2Right":"\nmap2Right( x, y, fcn[, thisArg] )\n    Applies a function to elements in two input arrays while iterating from\n    right to left and assigns the results to a new array.\n\n    The applied function is provided the following arguments:\n\n    - v1: element from first input array.\n    - v2: element from second input array.\n    - idx: element index.\n    - arrays: input arrays.\n\n    The returned output array always has a \"generic\" data type. For example, if\n    provided an array-like object, the function returns a generic array. If\n    provided an ndarray, the function returns an ndarray having a \"generic\" data\n    type.\n\n    Input arrays must be either both array-like objects or both ndarray-like\n    objects.\n\n    If input arrays are array-like objects, the arrays must have the same number\n    of elements.\n\n    If input arrays are ndarray-like objects, the arrays must be broadcast\n    compatible.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject|ndarray\n        First input array.\n\n    y: ArrayLikeObject|ndarray\n        Second input array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.add, 2 );\n    > var x = [ 1, 2, 3, 4, 5, 6 ];\n    > var y = [ 1, 1, 1, 1, 1, 1 ];\n    > var out = map2Right( x, y, f )\n    [ 2, 3, 4, 5, 6, 7 ]\n\n    // ndarray:\n    > x = array( x, { 'shape': [ 2, 3 ] } );\n    > y = array( y, { 'shape': [ 2, 3 ] } );\n    > out = map2Right( x, y, f );\n    > var v = out.get( 1, 1 )\n    6\n\n\nmap2Right.assign( x, y, out, fcn[, thisArg] )\n    Applies a function to elements in two input arrays while iterating from\n    right to left and assigns the results to an output array.\n\n    The applied function is provided the following arguments:\n\n    - v1: element from first input array.\n    - v2: element from second input array.\n    - idx: element index.\n    - arrays: input arrays.\n\n    Input and output arrays must be either all array-like objects or all\n    ndarray-like objects.\n\n    If input and output arrays are array-like objects, the arrays must have the\n    same number of elements.\n\n    If input and output arrays are ndarray-like objects, the arrays must be\n    broadcast compatible.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject|ndarray\n        First input array.\n\n    y: ArrayLikeObject|ndarray\n        Second input array.\n\n    out: ArrayLikeObject|ndarray\n        Output array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.add, 2 );\n    > var x = [ 1, 2, 3, 4, 5, 6 ];\n    > var y = [ 1, 1, 1, 1, 1, 1 ];\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > map2Right.assign( x, y, out, f );\n    > out\n    [ 2, 3, 4, 5, 6, 7 ]\n\n    // ndarray:\n    > var opts = { 'shape': [ 2, 3 ] };\n    > x = array( x, opts );\n    > y = array( y, opts );\n    > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n    > map2Right.assign( x, y, out, f );\n    > var v = out.get( 1, 1 )\n    6\n\n    See Also\n    --------\n    mapRight, map2\n","map2Right.assign":"\nmap2Right.assign( x, y, out, fcn[, thisArg] )\n    Applies a function to elements in two input arrays while iterating from\n    right to left and assigns the results to an output array.\n\n    The applied function is provided the following arguments:\n\n    - v1: element from first input array.\n    - v2: element from second input array.\n    - idx: element index.\n    - arrays: input arrays.\n\n    Input and output arrays must be either all array-like objects or all\n    ndarray-like objects.\n\n    If input and output arrays are array-like objects, the arrays must have the\n    same number of elements.\n\n    If input and output arrays are ndarray-like objects, the arrays must be\n    broadcast compatible.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject|ndarray\n        First input array.\n\n    y: ArrayLikeObject|ndarray\n        Second input array.\n\n    out: ArrayLikeObject|ndarray\n        Output array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.add, 2 );\n    > var x = [ 1, 2, 3, 4, 5, 6 ];\n    > var y = [ 1, 1, 1, 1, 1, 1 ];\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > map2Right.assign( x, y, out, f );\n    > out\n    [ 2, 3, 4, 5, 6, 7 ]\n\n    // ndarray:\n    > var opts = { 'shape': [ 2, 3 ] };\n    > x = array( x, opts );\n    > y = array( y, opts );\n    > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n    > map2Right.assign( x, y, out, f );\n    > var v = out.get( 1, 1 )\n    6\n\n    See Also\n    --------\n    mapRight, map2","map3d":"\nmap3d( arr, fcn[, thisArg] )\n    Applies a function to each nested element in a three-dimensional nested\n    array and assigns the result to a nested element in a new three-dimensional\n    nested array.\n\n    The applied function is provided the following arguments:\n\n    - value: array element.\n    - indices: current array element indices.\n    - arr: input array.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject<ArrayLikeObject<ArrayLikeObject>>\n        Input three-dimensional nested array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array<Array<Array>>\n        Three-dimensional nested array.\n\n    Examples\n    --------\n    > var f = naryFunction( base.abs, 1 );\n    > var arr = [ [ [ -1, -2, -3 ] ], [ [ -4, -5, -6 ] ] ];\n    > var out = map3d( arr, f );\n    > out[ 0 ][ 0 ]\n    [ 1, 2, 3 ]\n    > out[ 1 ][ 0 ]\n    [ 4, 5, 6 ]\n\n    See Also\n    --------\n    map, map2d, map4d, map5d\n","map4d":"\nmap4d( arr, fcn[, thisArg] )\n    Applies a function to each nested element in a four-dimensional nested array\n    and assigns the result to a nested element in a new four-dimensional nested\n    array.\n\n    The applied function is provided the following arguments:\n\n    - value: array element.\n    - indices: current array element indices.\n    - arr: input array.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject<ArrayLikeObject>\n        Input four-dimensional nested array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array<Array<Array<Array>>>\n        Four-dimensional nested array.\n\n    Examples\n    --------\n    > var f = naryFunction( base.abs, 1 );\n    > var arr = [ [ [ [ -1, -2, -3 ] ] ], [ [ [ -4, -5, -6 ] ] ] ];\n    > var out = map4d( arr, f );\n    > out[ 0 ][ 0 ][ 0 ]\n    [ 1, 2, 3 ]\n    > out[ 1 ][ 0 ][ 0 ]\n    [ 4, 5, 6 ]\n\n    See Also\n    --------\n    map, map2d, map3d, map5d\n","map5d":"\nmap5d( arr, fcn[, thisArg] )\n    Applies a function to each nested element in a five-dimensional nested array\n    and assigns the result to a nested element in a new five-dimensional nested\n    array.\n\n    The applied function is provided the following arguments:\n\n    - value: array element.\n    - indices: current array element indices.\n    - arr: input array.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject<ArrayLikeObject>\n        Input five-dimensional nested array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array<Array<Array<Array<Array>>>>\n        Five-dimensional nested array.\n\n    Examples\n    --------\n    > var f = naryFunction( base.abs, 1 );\n    > var arr = [ [ [ [ [ -1, -2, -3 ] ] ] ], [ [ [ [ -4, -5, -6 ] ] ] ] ];\n    > var out = map5d( arr, f );\n    > out[ 0 ][ 0 ][ 0 ][ 0 ]\n    [ 1, 2, 3 ]\n    > out[ 1 ][ 0 ][ 0 ][ 0 ]\n    [ 4, 5, 6 ]\n\n    See Also\n    --------\n    map, map2d, map3d, map4d\n","mapArguments":"\nmapArguments( fcn, clbk[, thisArg] )\n    Returns a function that applies arguments to a provided function after\n    transforming arguments according to a callback function.\n\n    The callback function is provided the following arguments:\n\n    - value: argument value.\n    - index: argument index.\n\n    Parameters\n    ----------\n    fcn: Function\n        Input function.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Function\n        Function wrapper.\n\n    Examples\n    --------\n    > function foo( a, b, c ) { return [ a, b, c ]; };\n    > function clbk( v ) { return v * 2; };\n    > var bar = mapArguments( foo, clbk );\n    > var out = bar( 1, 2, 3 )\n    [ 2, 4, 6 ]\n\n    See Also\n    --------\n    filterArguments\n","mapFun":"\nmapFun( fcn, n[, thisArg] )\n    Invokes a function `n` times and returns an array of accumulated function\n    return values.\n\n    The invoked function is provided a single argument: the invocation index\n    (zero-based).\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke.\n\n    n: integer\n        Number of times to invoke a function.\n\n    thisArg: any (optional)\n        Function execution context.\n\n    Returns\n    -------\n    out: Array\n        Array of accumulated function return values.\n\n    Examples\n    --------\n    > function fcn( i ) { return i; };\n    > var arr = mapFun( fcn, 5 )\n    [ 0, 1, 2, 3, 4 ]\n\n    See Also\n    --------\n    mapFunAsync\n","mapFunAsync":"\nmapFunAsync( fcn, n, [options,] done )\n    Invokes a function `n` times and returns an array of accumulated function\n    return values.\n\n    For each iteration, the provided function is invoked with two arguments:\n\n    - index: invocation index (starting from zero).\n    - next: callback to be invoked upon function completion.\n\n    The `next` callback accepts two arguments:\n\n    - error: error argument.\n    - result: function result.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke.\n\n    n: integer\n        Number of times to invoke a function.\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to allow only one pending invocation at a\n        time. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    done: Function\n        A callback invoked upon executing a provided function `n` times or upon\n        encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function fcn( i, next ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         next( null, i );\n    ...     }\n    ... };\n    > function done( error, arr ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( arr );\n    ... };\n    > mapFunAsync( fcn, 10, done )\n    [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n    // Limit number of concurrent invocations:\n    > function fcn( i, next ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         next( null, i );\n    ...     }\n    ... };\n    > function done( error, arr ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( arr );\n    ... };\n    > var opts = { 'limit': 2 };\n    > mapFunAsync( fcn, 10, opts, done )\n    [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n    // Sequential invocation:\n    > function fcn( i, next ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         next( null, i );\n    ...     }\n    ... };\n    > function done( error, arr ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( arr );\n    ... };\n    > var opts = { 'series': true };\n    > mapFunAsync( fcn, 10, opts, done )\n    [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n\nmapFunAsync.factory( [options,] fcn )\n    Returns a function which invokes a function `n` times and returns an array\n    of accumulated function return values.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to allow only one pending invocation at a\n        time. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        Function to invoke.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function `n` times and returns an array of\n        accumulated function return values.\n\n    Examples\n    --------\n    > function fcn( i, next ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         next( null, i );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = mapFunAsync.factory( opts, fcn );\n    > function done( error, arr ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( arr );\n    ... };\n    > f( 10, done )\n    [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n    See Also\n    --------\n    mapFun\n","mapFunAsync.factory":"\nmapFunAsync.factory( [options,] fcn )\n    Returns a function which invokes a function `n` times and returns an array\n    of accumulated function return values.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to allow only one pending invocation at a\n        time. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        Function to invoke.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function `n` times and returns an array of\n        accumulated function return values.\n\n    Examples\n    --------\n    > function fcn( i, next ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         next( null, i );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = mapFunAsync.factory( opts, fcn );\n    > function done( error, arr ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( arr );\n    ... };\n    > f( 10, done )\n    [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n    See Also\n    --------\n    mapFun","mapKeys":"\nmapKeys( obj, transform )\n    Maps keys from one object to a new object having the same values.\n\n    The transform function is provided three arguments:\n\n    - key: object key.\n    - value: object value corresponding to `key`.\n    - obj: the input object.\n\n    The value returned by a transform function should be a value which can be\n    serialized as an object key.\n\n    The function only maps own properties. Hence, the function does not map\n    inherited properties.\n\n    The function shallow copies key values.\n\n    Key iteration order is *not* guaranteed.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    transform: Function\n        Transform function. Return values specify the keys of the output object.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > function transform( key, value ) { return key + value; };\n    > var obj = { 'a': 1, 'b': 2 };\n    > var out = mapKeys( obj, transform )\n    { 'a1': 1, 'b2': 2 }\n\n    See Also\n    --------\n    mapValues\n","mapKeysAsync":"\nmapKeysAsync( obj, [options,] transform, done )\n    Maps keys from one object to a new object having the same values.\n\n    When invoked, `transform` is provided a maximum of four arguments:\n\n    - key: object key.\n    - value: object value corresponding to `key`.\n    - obj: the input object.\n    - next: a callback to be invoked after processing an object `key`.\n\n    The actual number of provided arguments depends on function length. If\n    `transform` accepts two arguments, `transform` is provided:\n\n    - key\n    - next\n\n    If `transform` accepts three arguments, `transform` is provided:\n\n    - key\n    - value\n    - next\n\n    For every other `transform` signature, `transform` is provided all four\n    arguments.\n\n    The `next` callback accepts two arguments:\n\n    - error: error argument.\n    - key: transformed key.\n\n    If a `transform` function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    The key returned by a transform function should be a value which can be\n    serialized as an object key.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function only maps own properties. Hence, the function does not map\n    inherited properties.\n\n    The function shallow copies key values.\n\n    Key iteration and insertion order are *not* guaranteed.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each property sequentially.\n        Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    transform: Function\n        Transform function. Returned values specify the keys of the output\n        object.\n\n    done: Function\n        A callback invoked either upon processing all own properties or upon\n        encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function transform( key, value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         next( null, key+':'+value );\n    ...     }\n    ... };\n    > function done( error, out ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( out );\n    ... };\n    > var obj = { 'a': 1, 'b': 2 };\n    > mapKeysAsync( obj, transform, done )\n    { 'a:1': 1, 'b:2': 2 }\n\n    // Limit number of concurrent invocations:\n    > function transform( key, value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         next( null, key+':'+value );\n    ...     }\n    ... };\n    > function done( error, out ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( out );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n    > mapKeysAsync( obj, opts, transform, done )\n    { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n\n    // Process sequentially:\n    > function transform( key, value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         next( null, key+':'+value );\n    ...     }\n    ... };\n    > function done( error, out ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( out );\n    ... };\n    > var opts = { 'series': true };\n    > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n    > mapKeysAsync( obj, opts, transform, done )\n    { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n\n\nmapKeysAsync.factory( [options,] transform )\n    Returns a function which maps keys from one object to a new object having\n    the same values.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each property sequentially.\n        Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    transform: Function\n        Transform function. Returned values specify the keys of the output\n        object.\n\n    Returns\n    -------\n    out: Function\n        A function which maps keys from one object to a new object having the\n        same values.\n\n    Examples\n    --------\n    > function transform( key, value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         next( null, key+':'+value );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = mapKeysAsync.factory( opts, transform );\n    > function done( error, out ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( out );\n    ... };\n    > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n    > f( obj, done )\n    { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n    > obj = { 'beep': 'boop' };\n    > f( obj, done )\n    { 'beep:boop': 'beep' }\n\n    See Also\n    --------\n    mapKeys, mapValuesAsync\n","mapKeysAsync.factory":"\nmapKeysAsync.factory( [options,] transform )\n    Returns a function which maps keys from one object to a new object having\n    the same values.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each property sequentially.\n        Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    transform: Function\n        Transform function. Returned values specify the keys of the output\n        object.\n\n    Returns\n    -------\n    out: Function\n        A function which maps keys from one object to a new object having the\n        same values.\n\n    Examples\n    --------\n    > function transform( key, value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         next( null, key+':'+value );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = mapKeysAsync.factory( opts, transform );\n    > function done( error, out ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( out );\n    ... };\n    > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n    > f( obj, done )\n    { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n    > obj = { 'beep': 'boop' };\n    > f( obj, done )\n    { 'beep:boop': 'beep' }\n\n    See Also\n    --------\n    mapKeys, mapValuesAsync","mapReduce":"\nmapReduce( arr, initial, mapper, reducer[, thisArg] )\n    Performs a map-reduce operation for each element in an array and returns the\n    accumulated result.\n\n    When invoked, the mapping function is provided three arguments:\n\n    - value: array element.\n    - index: element index.\n    - arr: input array.\n\n    When invoked, the reducing function is provided four arguments:\n\n    - accumulator: accumulated value.\n    - value: result after applying the mapping function to the current array\n      element.\n    - index: element index.\n    - arr: input array.\n\n    If provided an empty array, the function returns the initial value.\n\n    When provided an ndarray, the function performs a single-pass map-reduce\n    operation over the entire input ndarray (i.e., higher-order ndarray\n    dimensions are flattened to a single-dimension).\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject|ndarray\n        Input array.\n\n    initial: any\n        Accumulator value used in the first invocation of the reduction\n        function.\n\n    mapper: Function\n        Mapping function.\n\n    reducer: Function\n        Reducing function.\n\n    thisArg: any (optional)\n        Execution context for the reducing function.\n\n    Returns\n    -------\n    out: any\n        Accumulated result.\n\n    Examples\n    --------\n    // array-like object:\n    > var f1 = naryFunction( base.abs, 1 );\n    > var f2 = naryFunction( base.add, 2 );\n    > var arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\n    > var out = mapReduce( arr, 0.0, f1, f2 )\n    21.0\n\n    // ndarray:\n    > arr = array( arr, { 'shape': [ 2, 3 ] } );\n    > out = mapReduce( arr, 0.0, f1, f2 )\n    21.0\n\n    See Also\n    --------\n    map, mapReduceRight, reduce\n","mapReduceRight":"\nmapReduceRight( arr, initial, mapper, reducer[, thisArg] )\n    Performs a map-reduce operation for each element in an array while iterating\n    from right to left and returns the accumulated result.\n\n    When invoked, the mapping function is provided three arguments:\n\n    - value: array element.\n    - index: element index.\n    - arr: input array.\n\n    When invoked, the reducing function is provided four arguments:\n\n    - accumulator: accumulated value.\n    - value: result after applying the mapping function to the current array\n      element.\n    - index: element index.\n    - arr: input array.\n\n    If provided an empty array, the function returns the initial value.\n\n    When provided an ndarray, the function performs a single-pass map-reduce\n    operation over the entire input ndarray (i.e., higher-order ndarray\n    dimensions are flattened to a single-dimension).\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject|ndarray\n        Input array.\n\n    initial: any\n        Accumulator value used in the first invocation of the reduction\n        function.\n\n    mapper: Function\n        Mapping function.\n\n    reducer: Function\n        Reducing function.\n\n    thisArg: any (optional)\n        Execution context for the reducing function.\n\n    Returns\n    -------\n    out: any\n        Accumulated result.\n\n    Examples\n    --------\n    // array-like object:\n    > var f1 = naryFunction( base.abs, 1 );\n    > var f2 = naryFunction( base.add, 2 );\n    > var arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\n    > var out = mapReduceRight( arr, 0.0, f1, f2 )\n    21.0\n\n    // ndarray:\n    > arr = array( arr, { 'shape': [ 2, 3 ] } );\n    > out = mapReduceRight( arr, 0.0, f1, f2 )\n    21.0\n\n    See Also\n    --------\n    mapRight, mapReduce, reduceRight\n","mapRight":"\nmapRight( arr, fcn[, thisArg] )\n    Applies a function to each element in an array and assigns the result to an\n    element in a new array, iterating from right to left.\n\n    The applied function is provided the following arguments:\n\n    - value: array element.\n    - index: element index.\n    - arr: input array.\n\n    The returned output array always has a \"generic\" data type. For example, if\n    provided an array-like object, the function returns a generic array. If\n    provided an ndarray, the function returns an ndarray having a \"generic\" data\n    type.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject|ndarray\n        Input array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.abs, 1 );\n    > var arr = [ -1, -2, -3, -4, -5, -6 ];\n    > var out = mapRight( arr, f )\n    [ 1, 2, 3, 4, 5, 6 ]\n\n    // ndarray:\n    > arr = array( arr, { 'shape': [ 2, 3 ] } );\n    > out = mapRight( arr, f );\n    > var v = out.get( 1, 1 )\n    5\n\n\nmapRight.assign( arr, out, fcn[, thisArg] )\n    Applies a function to each element in an array and assigns the result to an\n    element in an output array, iterating from right to left.\n\n    The applied function is provided the following arguments:\n\n    - value: array element.\n    - index: element index.\n    - arr: input array.\n\n    Input and output arrays must be either both array-like objects or both\n    ndarray-like objects.\n\n    If input and output arrays are array-like objects, the arrays must have the\n    same number of elements.\n\n    If input and output arrays are both ndarray-like objects, the arrays *must*\n    be broadcast compatible.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject|ndarray\n        Input array.\n\n    out: ArrayLikeObject|ndarray\n        Output array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.abs, 1 );\n    > var arr = [ -1, -2, -3, -4, -5, -6 ];\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > mapRight.assign( arr, out, f );\n    > out\n    [ 1, 2, 3, 4, 5, 6 ]\n\n    // ndarray:\n    > var opts = { 'shape': [ 2, 3 ] };\n    > arr = array( arr, opts );\n    > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n    > mapRight.assign( arr, out, f );\n    > var v = out.get( 1, 1 )\n    5\n\n    See Also\n    --------\n    map, reduce\n","mapRight.assign":"\nmapRight.assign( arr, out, fcn[, thisArg] )\n    Applies a function to each element in an array and assigns the result to an\n    element in an output array, iterating from right to left.\n\n    The applied function is provided the following arguments:\n\n    - value: array element.\n    - index: element index.\n    - arr: input array.\n\n    Input and output arrays must be either both array-like objects or both\n    ndarray-like objects.\n\n    If input and output arrays are array-like objects, the arrays must have the\n    same number of elements.\n\n    If input and output arrays are both ndarray-like objects, the arrays *must*\n    be broadcast compatible.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject|ndarray\n        Input array.\n\n    out: ArrayLikeObject|ndarray\n        Output array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.abs, 1 );\n    > var arr = [ -1, -2, -3, -4, -5, -6 ];\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > mapRight.assign( arr, out, f );\n    > out\n    [ 1, 2, 3, 4, 5, 6 ]\n\n    // ndarray:\n    > var opts = { 'shape': [ 2, 3 ] };\n    > arr = array( arr, opts );\n    > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n    > mapRight.assign( arr, out, f );\n    > var v = out.get( 1, 1 )\n    5\n\n    See Also\n    --------\n    map, reduce","mapValues":"\nmapValues( obj, transform )\n    Maps values from one object to a new object having the same keys.\n\n    The transform function is provided three arguments:\n\n    - value: object value corresponding to `key`.\n    - key: object key.\n    - obj: the input object.\n\n    The function only maps values from own properties. Hence, the function does\n    not map inherited properties.\n\n    The function shallow copies key values.\n\n    Key iteration order is *not* guaranteed.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    transform: Function\n        Transform function. Return values are the key values of the output\n        object.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > function transform( value, key ) { return key + value; };\n    > var obj = { 'a': 1, 'b': 2 };\n    > var out = mapValues( obj, transform )\n    { 'a': 'a1', 'b': 'b2' }\n\n    See Also\n    --------\n    mapKeys, omitBy, pickBy\n","mapValuesAsync":"\nmapValuesAsync( obj, [options,] transform, done )\n    Maps values from one object to a new object having the same keys.\n\n    When invoked, `transform` is provided a maximum of four arguments:\n\n    - value: object value corresponding to `key`.\n    - key: object key.\n    - obj: the input object.\n    - next: a callback to be invoked after processing an object `value`.\n\n    The actual number of provided arguments depends on function length. If\n    `transform` accepts two arguments, `transform` is provided:\n\n    - value\n    - next\n\n    If `transform` accepts three arguments, `transform` is provided:\n\n    - value\n    - key\n    - next\n\n    For every other `transform` signature, `transform` is provided all four\n    arguments.\n\n    The `next` callback accepts two arguments:\n\n    - error: error argument.\n    - value: transformed value.\n\n    If a `transform` function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function only maps values from own properties. Hence, the function does\n    not map inherited properties.\n\n    The function shallow copies key values.\n\n    Key iteration and insertion order are *not* guaranteed.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each property sequentially.\n        Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    transform: Function\n        Transform function. Return values are the key values of the output\n        object.\n\n    done: Function\n        A callback invoked either upon processing all own properties or upon\n        encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function transform( value, key, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         next( null, key+':'+value );\n    ...     }\n    ... };\n    > function done( error, out ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( out );\n    ... };\n    > var obj = { 'a': 1, 'b': 2 };\n    > mapValuesAsync( obj, transform, done )\n    { 'a': 'a:1', 'b': 'b:2' }\n\n    // Limit number of concurrent invocations:\n    > function transform( value, key, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         next( null, key+':'+value );\n    ...     }\n    ... };\n    > function done( error, out ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( out );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n    > mapValuesAsync( obj, opts, transform, done )\n    { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n\n    // Process sequentially:\n    > function transform( value, key, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         next( null, key+':'+value );\n    ...     }\n    ... };\n    > function done( error, out ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( out );\n    ... };\n    > var opts = { 'series': true };\n    > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n    > mapValuesAsync( obj, opts, transform, done )\n    { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n\n\nmapValuesAsync.factory( [options,] transform )\n    Returns a function which maps values from one object to a new object having\n    the same keys.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each property sequentially.\n        Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    transform: Function\n        Transform function. Return values are the key values of the output\n        object.\n\n    Returns\n    -------\n    out: Function\n        A function which maps values from one object to a new object having the\n        same keys.\n\n    Examples\n    --------\n    > function transform( value, key, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         next( null, key+':'+value );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = mapValuesAsync.factory( opts, transform );\n    > function done( error, out ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( out );\n    ... };\n    > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n    > f( obj, done )\n    { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n    > obj = { 'beep': 'boop' };\n    > f( obj, done )\n    { 'beep': 'beep:boop' }\n\n    See Also\n    --------\n    mapKeysAsync, mapValues\n","mapValuesAsync.factory":"\nmapValuesAsync.factory( [options,] transform )\n    Returns a function which maps values from one object to a new object having\n    the same keys.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each property sequentially.\n        Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    transform: Function\n        Transform function. Return values are the key values of the output\n        object.\n\n    Returns\n    -------\n    out: Function\n        A function which maps values from one object to a new object having the\n        same keys.\n\n    Examples\n    --------\n    > function transform( value, key, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         next( null, key+':'+value );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = mapValuesAsync.factory( opts, transform );\n    > function done( error, out ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( out );\n    ... };\n    > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n    > f( obj, done )\n    { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n    > obj = { 'beep': 'boop' };\n    > f( obj, done )\n    { 'beep': 'beep:boop' }\n\n    See Also\n    --------\n    mapKeysAsync, mapValues","maskArguments":"\nmaskArguments( fcn, mask[, thisArg] )\n    Returns a function that applies arguments to a provided function according\n    to a specified mask.\n\n    Only those arguments having a truthy mask value are applied to a provided\n    function.\n\n    Parameters\n    ----------\n    fcn: Function\n        Input function.\n\n    mask: ArrayLikeObject\n        Mask array.\n\n    thisArg: any (optional)\n        Function context.\n\n    Returns\n    -------\n    out: Function\n        Function wrapper.\n\n    Examples\n    --------\n    > function foo( a, b ) { return [ a, b ]; };\n    > var bar = maskArguments( foo, [ 1, 0, 1 ] );\n    > var out = bar( 1, 2, 3 )\n    [ 1, 3 ]\n\n    See Also\n    --------\n    filterArguments, rejectArguments, reorderArguments, reverseArguments\n","MAX_ARRAY_LENGTH":"\nMAX_ARRAY_LENGTH\n    Maximum length for a generic array.\n\n    Examples\n    --------\n    > MAX_ARRAY_LENGTH\n    4294967295\n\n    See Also\n    --------\n    MAX_TYPED_ARRAY_LENGTH\n","MAX_TYPED_ARRAY_LENGTH":"\nMAX_TYPED_ARRAY_LENGTH\n    Maximum length for a typed array.\n\n    Examples\n    --------\n    > MAX_TYPED_ARRAY_LENGTH\n    9007199254740991\n\n    See Also\n    --------\n    MAX_ARRAY_LENGTH\n","maybeBroadcastArray":"\nmaybeBroadcastArray( x, shape )\n    Broadcasts an ndarray to a specified shape if and only if the specified\n    shape differs from the provided ndarray's shape.\n\n    If a provided ndarray has the same shape as the specified shape, the\n    function returns the provided ndarray.\n\n    If a provided ndarray has a different (broadcast compatible) shape than the\n    specified shape, the function returns a new *read-only* ndarray view of the\n    provided ndarray's data. The view is typically *not* contiguous. As more\n    than one element of a returned view may refer to the same memory location,\n    writing to the input ndarray may affect multiple elements. If you need to\n    write to the input ndarray, copy the input ndarray before broadcasting.\n\n    The function throws an error if a provided ndarray is incompatible with a\n    provided shape.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    shape: ArrayLikeObject\n        Desired shape.\n\n    Returns\n    -------\n    out: ndarray\n        Broadcasted array.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n    <ndarray>\n    > var sh = x.shape\n    [ 2, 2 ]\n    > var y = maybeBroadcastArray( x, [ 3, 2, 2 ] )\n    <ndarray>\n    > sh = y.shape\n    [ 3, 2, 2 ]\n    > var v = y.get( 0, 0, 0 )\n    1\n    > v = y.get( 0, 0, 1 )\n    2\n    > v = y.get( 0, 1, 0 )\n    3\n    > v = y.get( 0, 1, 1 )\n    4\n    > v = y.get( 1, 0, 0 )\n    1\n    > v = y.get( 1, 1, 0 )\n    3\n    > v = y.get( 2, 0, 0 )\n    1\n    > v = y.get( 2, 1, 1 )\n    4\n\n    See Also\n    --------\n    array, ndarray, broadcastArray, maybeBroadcastArrays\n","maybeBroadcastArrays":"\nmaybeBroadcastArrays( ...arrays )\n    Broadcasts ndarrays to a common shape.\n\n    The function supports two (mutually exclusive) means of providing ndarray\n    arguments:\n\n    1. Providing a single array containing ndarray arguments.\n    2. Providing ndarray arguments as separate arguments.\n\n    If a provided ndarray has a shape matching the common shape, the function\n    returns the provided ndarray.\n\n    If a provided ndarray has a different (broadcast compatible) shape than the\n    common shape, the function returns a new *read-only* ndarray view of the\n    provided ndarray's data. The view is typically *not* contiguous. As more\n    than one element of a returned view may refer to the same memory location,\n    writing to a view may affect multiple elements. If you need to write to an\n    input ndarray, copy the input ndarray before broadcasting.\n\n    The function throws an error if a provided broadcast-incompatible ndarrays.\n\n    Parameters\n    ----------\n    arrays: ...ndarray|ArrayLikeObject<ndarray>\n        Array arguments.\n\n    Returns\n    -------\n    out: Array<ndarray>\n        Broadcasted arrays.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n    <ndarray>\n    > var sh = x.shape\n    [ 2, 2 ]\n    > var y = ndzeros( [ 3, 2, 2 ] )\n    <ndarray>\n    > var out = maybeBroadcastArrays( [ x, y ] )\n    [ <ndarray>, <ndarray> ]\n\n    // Retrieve the broadcasted \"x\" array:\n    > var bx = out[ 0 ]\n    <ndarray>\n    > sh = bx.shape\n    [ 3, 2, 2 ]\n\n    // Retrieve broadcasted elements...\n    > var v = bx.get( 0, 0, 0 )\n    1\n    > v = bx.get( 0, 0, 1 )\n    2\n    > v = bx.get( 0, 1, 0 )\n    3\n    > v = bx.get( 0, 1, 1 )\n    4\n    > v = bx.get( 1, 0, 0 )\n    1\n    > v = bx.get( 1, 1, 0 )\n    3\n    > v = bx.get( 2, 0, 0 )\n    1\n    > v = bx.get( 2, 1, 1 )\n    4\n\n    See Also\n    --------\n    array, ndarray, broadcastArrays, maybeBroadcastArray\n","memoize":"\nmemoize( fcn[, hashFunction] )\n    Returns a memoized function.\n\n    The function does not set the `length` property of the returned function.\n    Accordingly, the returned function `length` is always zero.\n\n    The evaluation context is always `null`.\n\n    The function serializes provided arguments as a string and stores results\n    using the string as an identifier. To use a custom hash function, provide a\n    hash function argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to memoize.\n\n    hashFunction: Function (optional)\n        Function to map a set of arguments to a single value identifying that\n        set.\n\n    Returns\n    -------\n    out: Function\n        Memoized function.\n\n    Examples\n    --------\n    > function factorial( n ) {\n    ...     var prod;\n    ...     var i;\n    ...     prod = 1;\n    ...     for ( i = n; i > 1; i-- ) {\n    ...         prod *= i;\n    ...     }\n    ...     return prod;\n    ... };\n    > var memoized = memoize( factorial );\n    > var v = memoized( 5 )\n    120\n    > v = memoized( 5 )\n    120\n\n","merge":"\nmerge( target, ...source )\n    Merges objects into a target object.\n\n    The target object is mutated.\n\n    Only plain objects are merged and extended. Other values/types are either\n    deep copied or assigned.\n\n    Support for deep merging class instances is inherently fragile.\n\n    `Number`, `String`, and `Boolean` objects are merged as primitives.\n\n    Functions are not deep copied.\n\n    Parameters\n    ----------\n    target: Object\n        Target object.\n\n    source: ...Object\n        Source objects (i.e., objects to be merged into the target object).\n\n    Returns\n    -------\n    out: Object\n        Merged (target) object.\n\n    Examples\n    --------\n    > var target = { 'a': 'beep' };\n    > var source = { 'a': 'boop', 'b': 'bap' };\n    > var out = merge( target, source )\n    { 'a': 'boop', 'b': 'bap' }\n    > var bool = ( out === target )\n    true\n\n\nmerge.factory( options )\n    Returns a function for merging and extending objects.\n\n    Parameters\n    ----------\n    options: Object\n        Options.\n\n    options.level: integer (optional)\n        Merge level. Default: Infinity.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to deep copy merged values. Deep copying\n        prevents shared references and source object mutation. Default: true.\n\n    options.override: boolean|Function (optional)\n        Defines the merge strategy. If `true`, source object values will always\n        override target object values. If `false`, source values never override\n        target values (useful for adding, but not overwriting, properties). To\n        define a custom merge strategy, provide a function. Default: true.\n\n    options.extend: boolean (optional)\n        Boolean indicating whether new properties can be added to the target\n        object. If `false`, only shared properties are merged. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function which can be used to merge objects.\n\n    Examples\n    --------\n    > var opts = {\n    ...     'level': 100,\n    ...     'copy': true,\n    ...     'override': true,\n    ...     'extend': true\n    ... };\n    > var merge = merge.factory( opts )\n    <Function>\n\n    // Set the `level` option to limit the merge depth:\n    > merge = merge.factory( { 'level': 2 } );\n    > var target = {\n    ...     '1': { 'a': 'beep', '2': { '3': null, 'b': [ 5, 6, 7 ] } }\n    ... };\n    > var source = {\n    ...     '1': { 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } }\n    ... };\n    > var out = merge( target, source )\n    { '1': { 'a': 'beep', 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } } }\n\n    // Set the `copy` option to `false` to allow shared references:\n    > merge = merge.factory( { 'copy': false } );\n    > target = {};\n    > source = { 'a': [ 1, 2, 3 ] };\n    > out = merge( target, source );\n    > var bool = ( out.a === source.a )\n    true\n\n    // Set the `override` option to `false` to preserve existing properties:\n    > merge = merge.factory( { 'override': false } );\n    > target = { 'a': 'beep', 'b': 'boop' };\n    > source = { 'a': null, 'c': 'bop' };\n    > out = merge( target, source )\n    { 'a': 'beep', 'b': 'boop', 'c': 'bop' }\n\n    // Define a custom merge strategy:\n    > function strategy( a, b, key ) {\n    ...     // a => target value\n    ...     // b => source value\n    ...     // key => object key\n    ...     if ( key === 'a' ) {\n    ...         return b;\n    ...     }\n    ...     if ( key === 'b' ) {\n    ...         return a;\n    ...     }\n    ...     return 'bebop';\n    ... };\n    > merge = merge.factory( { 'override': strategy } );\n    > target = { 'a': 'beep', 'b': 'boop', 'c': 1234 };\n    > source = { 'a': null, 'b': {}, 'c': 'bop' };\n    > out = merge( target, source )\n    { 'a': null, 'b': 'boop', 'c': 'bebop' }\n\n    // Prevent non-existent properties from being added to the target object:\n    > merge = merge.factory( { 'extend': false } );\n    > target = { 'a': 'beep', 'b': 'boop' };\n    > source = { 'b': 'hello', 'c': 'world' };\n    > out = merge( target, source )\n    { 'a': 'beep', 'b': 'hello' }\n\n    See Also\n    --------\n    copy\n","merge.factory":"\nmerge.factory( options )\n    Returns a function for merging and extending objects.\n\n    Parameters\n    ----------\n    options: Object\n        Options.\n\n    options.level: integer (optional)\n        Merge level. Default: Infinity.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to deep copy merged values. Deep copying\n        prevents shared references and source object mutation. Default: true.\n\n    options.override: boolean|Function (optional)\n        Defines the merge strategy. If `true`, source object values will always\n        override target object values. If `false`, source values never override\n        target values (useful for adding, but not overwriting, properties). To\n        define a custom merge strategy, provide a function. Default: true.\n\n    options.extend: boolean (optional)\n        Boolean indicating whether new properties can be added to the target\n        object. If `false`, only shared properties are merged. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function which can be used to merge objects.\n\n    Examples\n    --------\n    > var opts = {\n    ...     'level': 100,\n    ...     'copy': true,\n    ...     'override': true,\n    ...     'extend': true\n    ... };\n    > var merge = merge.factory( opts )\n    <Function>\n\n    // Set the `level` option to limit the merge depth:\n    > merge = merge.factory( { 'level': 2 } );\n    > var target = {\n    ...     '1': { 'a': 'beep', '2': { '3': null, 'b': [ 5, 6, 7 ] } }\n    ... };\n    > var source = {\n    ...     '1': { 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } }\n    ... };\n    > var out = merge( target, source )\n    { '1': { 'a': 'beep', 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } } }\n\n    // Set the `copy` option to `false` to allow shared references:\n    > merge = merge.factory( { 'copy': false } );\n    > target = {};\n    > source = { 'a': [ 1, 2, 3 ] };\n    > out = merge( target, source );\n    > var bool = ( out.a === source.a )\n    true\n\n    // Set the `override` option to `false` to preserve existing properties:\n    > merge = merge.factory( { 'override': false } );\n    > target = { 'a': 'beep', 'b': 'boop' };\n    > source = { 'a': null, 'c': 'bop' };\n    > out = merge( target, source )\n    { 'a': 'beep', 'b': 'boop', 'c': 'bop' }\n\n    // Define a custom merge strategy:\n    > function strategy( a, b, key ) {\n    ...     // a => target value\n    ...     // b => source value\n    ...     // key => object key\n    ...     if ( key === 'a' ) {\n    ...         return b;\n    ...     }\n    ...     if ( key === 'b' ) {\n    ...         return a;\n    ...     }\n    ...     return 'bebop';\n    ... };\n    > merge = merge.factory( { 'override': strategy } );\n    > target = { 'a': 'beep', 'b': 'boop', 'c': 1234 };\n    > source = { 'a': null, 'b': {}, 'c': 'bop' };\n    > out = merge( target, source )\n    { 'a': null, 'b': 'boop', 'c': 'bebop' }\n\n    // Prevent non-existent properties from being added to the target object:\n    > merge = merge.factory( { 'extend': false } );\n    > target = { 'a': 'beep', 'b': 'boop' };\n    > source = { 'b': 'hello', 'c': 'world' };\n    > out = merge( target, source )\n    { 'a': 'beep', 'b': 'hello' }\n\n    See Also\n    --------\n    copy","MILLISECONDS_IN_DAY":"\nMILLISECONDS_IN_DAY\n    Number of milliseconds in a day.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var days = 3.14;\n    > var ms = days * MILLISECONDS_IN_DAY\n    271296000\n\n","MILLISECONDS_IN_HOUR":"\nMILLISECONDS_IN_HOUR\n    Number of milliseconds in an hour.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var hrs = 3.14;\n    > var ms = hrs * MILLISECONDS_IN_HOUR\n    11304000\n\n","MILLISECONDS_IN_MINUTE":"\nMILLISECONDS_IN_MINUTE\n    Number of milliseconds in a minute.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies arising due to complications with time and dates.\n\n    Examples\n    --------\n    > var mins = 3.14;\n    > var ms = mins * MILLISECONDS_IN_MINUTE\n    188400\n\n","MILLISECONDS_IN_SECOND":"\nMILLISECONDS_IN_SECOND\n    Number of milliseconds in a second.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies arising due to complications with time and dates.\n\n    Examples\n    --------\n    > var secs = 3.14;\n    > var ms = secs * MILLISECONDS_IN_SECOND\n    3140\n\n","MILLISECONDS_IN_WEEK":"\nMILLISECONDS_IN_WEEK\n    Number of milliseconds in a week.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var weeks = 3.14;\n    > var ms = weeks * MILLISECONDS_IN_WEEK\n    1899072000\n\n","MINARD_NAPOLEONS_MARCH":"\nMINARD_NAPOLEONS_MARCH( [options] )\n    Returns data for Charles Joseph Minard's cartographic depiction of\n    Napoleon's Russian campaign of 1812.\n\n    Data includes the following:\n\n    - army: army size.\n    - cities: cities.\n    - labels: map labels.\n    - temperature: temperature during the army's return from Russia.\n    - rivers: river data.\n\n    Temperatures are on the Réaumur scale. Multiply each temperature by `1.25`\n    to convert to Celsius.\n\n    River data is formatted as GeoJSON.\n\n    River data is incomplete, with portions of rivers missing.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.data: string (optional)\n        Dataset name.\n\n    Returns\n    -------\n    out: Object|Array<Object>\n        Minard's data.\n\n    Examples\n    --------\n    > var data = MINARD_NAPOLEONS_MARCH();\n    > var army = data.army\n    [...]\n    > var cities = data.cities\n    [...]\n    > var labels = data.labels\n    [...]\n    > var river = data.river\n    {...}\n    > var t = data.temperature\n    [...]\n\n    References\n    ----------\n    - Minard, Charles Joseph. 1869. *Tableaux graphiques et cartes figuratives*.\n    Ecole nationale des ponts et chaussées.\n    - Wilkinson, Leland. 2005. *The Grammar of Graphics*. Springer-Verlag New\n    York. doi:10.1007/0-387-28695-0.\n\n","MINUTES_IN_DAY":"\nMINUTES_IN_DAY\n    Number of minutes in a day.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var days = 3.14;\n    > var mins = days * MINUTES_IN_DAY\n    4521.6\n\n","MINUTES_IN_HOUR":"\nMINUTES_IN_HOUR\n    Number of minutes in an hour.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var hrs = 3.14;\n    > var mins = hrs * MINUTES_IN_HOUR\n    188.4\n\n","MINUTES_IN_WEEK":"\nMINUTES_IN_WEEK\n    Number of minutes in a week.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var wks = 3.14;\n    > var mins = wks * MINUTES_IN_WEEK\n    31651.2\n\n","minutesInMonth":"\nminutesInMonth( [month[, year]] )\n    Returns the number of minutes in a month.\n\n    By default, the function returns the number of minutes in the current month\n    of the current year (according to local time). To determine the number of\n    minutes for a particular month and year, provide `month` and `year`\n    arguments.\n\n    A `month` may be either a month's integer value, three letter abbreviation,\n    or full name (case insensitive).\n\n    The function's return value is a generalization and does **not** take into\n    account inaccuracies due to daylight savings conventions, crossing\n    timezones, or other complications with time and dates.\n\n    Parameters\n    ----------\n    month: string|Date|integer (optional)\n        Month.\n\n    year: integer (optional)\n        Year.\n\n    Returns\n    -------\n    out: integer\n        Minutes in a month.\n\n    Examples\n    --------\n    > var num = minutesInMonth()\n    <number>\n    > num = minutesInMonth( 2 )\n    <number>\n    > num = minutesInMonth( 2, 2016 )\n    41760\n    > num = minutesInMonth( 2, 2017 )\n    40320\n\n    // Other ways to supply month:\n    > num = minutesInMonth( 'feb', 2016 )\n    41760\n    > num = minutesInMonth( 'february', 2016 )\n    41760\n\n    See Also\n    --------\n    minutesInYear\n","minutesInYear":"\nminutesInYear( [value] )\n    Returns the number of minutes in a year according to the Gregorian calendar.\n\n    By default, the function returns the number of minutes in the current year\n    (according to local time). To determine the number of minutes for a\n    particular year, provide either a year or a `Date` object.\n\n    The function's return value is a generalization and does **not** take into\n    account inaccuracies due to daylight savings conventions, crossing\n    timezones, or other complications with time and dates.\n\n    Parameters\n    ----------\n    value: integer|Date (optional)\n        Year or `Date` object.\n\n    Returns\n    -------\n    out: integer\n        Number of minutes in a year.\n\n    Examples\n    --------\n    > var num = minutesInYear()\n    <number>\n    > num = minutesInYear( 2016 )\n    527040\n    > num = minutesInYear( 2017 )\n    525600\n\n    See Also\n    --------\n    minutesInMonth\n","MOBY_DICK":"\nMOBY_DICK()\n    Returns the text of Moby Dick by Herman Melville.\n\n    Each array element has the following fields:\n\n    - chapter: book chapter (number or identifier).\n    - title: chapter title (if available; otherwise, empty).\n    - text: chapter text.\n\n    Returns\n    -------\n    out: Array<Object>\n        Book text.\n\n    Examples\n    --------\n    > var data = MOBY_DICK()\n    [ {...}, {...}, ... ]\n\n","MONTH_NAMES_EN":"\nMONTH_NAMES_EN()\n    Returns a list of month names (English).\n\n    Returns\n    -------\n    out: Array<string>\n        List of month names.\n\n    Examples\n    --------\n    > var list = MONTH_NAMES_EN()\n    [ 'January', 'February', 'March', 'April', ... ]\n\n","MONTHS_IN_YEAR":"\nMONTHS_IN_YEAR\n    Number of months in a year.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var yrs = 3.14;\n    > var mons = yrs * MONTHS_IN_YEAR\n    37.68\n\n","moveProperty":"\nmoveProperty( source, prop, target )\n    Moves a property from one object to another object.\n\n    The property is deleted from the source object and the property's descriptor\n    is preserved during transfer.\n\n    If a source property is not configurable, the function throws an error, as\n    the property cannot be deleted from the source object.\n\n    Parameters\n    ----------\n    source: Object\n        Source object.\n\n    prop: string\n        Property to move.\n\n    target: Object\n        Target object.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether operation was successful.\n\n    Examples\n    --------\n    > var obj1 = { 'a': 'b' };\n    > var obj2 = {};\n    > var bool = moveProperty( obj1, 'a', obj2 )\n    true\n    > bool = moveProperty( obj1, 'c', obj2 )\n    false\n\n","MultiSlice":"\nMultiSlice( ...slice )\n    Returns a multi-slice.\n\n    Parameters\n    ----------\n    ...slice: Slice|integer|null|undefined\n        Slice arguments.\n\n    Returns\n    -------\n    s: MultiSlice\n        MultiSlice instance.\n\n    Examples\n    --------\n    > var s = new Slice( 2, 10 );\n    > var ms = new MultiSlice( 2, s, 1 );\n\n\nMultiSlice.prototype.ndims\n    Read-only property returning the number of slice dimensions.\n\n    Returns\n    -------\n    ndims: integer\n        Number of slice dimensions.\n\n    Examples\n    --------\n    > var s = new Slice( 2, 10 );\n    > var ms = new MultiSlice( 2, s, 1 );\n    > ms.ndims\n    3\n\n\nMultiSlice.prototype.data\n    Read-only property returning the slice data.\n\n    Returns\n    -------\n    data: Array<Slice|integer|null>\n        Slice data.\n\n    Examples\n    --------\n    > var s = new Slice( 2, 10 );\n    > var ms = new MultiSlice( 2, s, 1 );\n    > ms.data\n    [ 2, <Slice>, 1 ]\n\n\nMultiSlice.prototype.toString()\n    Serializes a multi-slice as a string.\n\n    Returns\n    -------\n    str: string\n        Serialized multi-slice string.\n\n    Examples\n    --------\n    > var s = new Slice( 2, 10 );\n    > var ms = new MultiSlice( 2, s, 1 );\n    > ms.toString()\n    'MultiSlice(2,Slice(2,10,null),1)'\n\n\nMultiSlice.prototype.toJSON()\n    Serializes a multi-slice as a JSON object.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var s = new Slice( 2, 10, 1 );\n    > var ms = new MultiSlice( 2, s );\n    > ms.toJSON()\n    {'type':'MultiSlice','data':[2,{'type':'Slice','data':[2,10,1]}]}\n\n    See Also\n    --------\n    ndarray, Slice\n","MultiSlice.prototype.ndims":"\nMultiSlice.prototype.ndims\n    Read-only property returning the number of slice dimensions.\n\n    Returns\n    -------\n    ndims: integer\n        Number of slice dimensions.\n\n    Examples\n    --------\n    > var s = new Slice( 2, 10 );\n    > var ms = new MultiSlice( 2, s, 1 );\n    > ms.ndims\n    3","MultiSlice.prototype.data":"\nMultiSlice.prototype.data\n    Read-only property returning the slice data.\n\n    Returns\n    -------\n    data: Array<Slice|integer|null>\n        Slice data.\n\n    Examples\n    --------\n    > var s = new Slice( 2, 10 );\n    > var ms = new MultiSlice( 2, s, 1 );\n    > ms.data\n    [ 2, <Slice>, 1 ]","MultiSlice.prototype.toString":"\nMultiSlice.prototype.toString()\n    Serializes a multi-slice as a string.\n\n    Returns\n    -------\n    str: string\n        Serialized multi-slice string.\n\n    Examples\n    --------\n    > var s = new Slice( 2, 10 );\n    > var ms = new MultiSlice( 2, s, 1 );\n    > ms.toString()\n    'MultiSlice(2,Slice(2,10,null),1)'","MultiSlice.prototype.toJSON":"\nMultiSlice.prototype.toJSON()\n    Serializes a multi-slice as a JSON object.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var s = new Slice( 2, 10, 1 );\n    > var ms = new MultiSlice( 2, s );\n    > ms.toJSON()\n    {'type':'MultiSlice','data':[2,{'type':'Slice','data':[2,10,1]}]}\n\n    See Also\n    --------\n    ndarray, Slice","namedtypedtuple":"\nnamedtypedtuple( fields[, options] )\n    Returns a named typed tuple factory.\n\n    Named tuples assign a property name, and thus a meaning, to each position in\n    a tuple and allow for more readable, self-documenting code.\n\n    Named typed tuples can be used wherever typed arrays are used, with the\n    added benefit that they allow accessing fields by both field name and\n    position index.\n\n    Named typed tuples may be one the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754).\n    - float32: single-precision floating-point numbers (IEEE 754).\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n\n    Parameters\n    ----------\n    fields: Array<string>\n        Field (property) names.\n\n    options: Object (optional)\n        Function options.\n\n    options.dtype: string (optional)\n        Default tuple data type. If a data type is not provided to a named typed\n        tuple factory, this option specifies the underlying tuple data type.\n        Default: 'float64'.\n\n    options.name: string (optional)\n        Tuple name. Default: 'tuple'.\n\n    Returns\n    -------\n    factory: Function\n        Named typed tuple factory.\n\n    Examples\n    --------\n    > var opts = {};\n    > opts.name = 'Point';\n    > var factory = namedtypedtuple( [ 'x', 'y' ], opts );\n    > var tuple = factory();\n\n\nfactory()\n    Returns a named typed tuple of the default data type.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > p = factory();\n    > p.x\n    0.0\n    > p.y\n    0.0\n    > p[ 0 ]\n    0.0\n    > p[ 1 ]\n    0.0\n\n\nfactory( dtype )\n    Returns a named typed tuple of the specified data type.\n\n    Parameters\n    ----------\n    dtype: string\n        Tuple data type.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > p = factory( 'int32' );\n    > p.x\n    0\n    > p.y\n    0\n    > p[ 0 ]\n    0\n    > p[ 1 ]\n    0\n\n\nfactory( typedarray[, dtype] )\n    Creates a named typed tuple from a typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate a named typed tuple.\n\n    dtype: string (optional)\n        Tuple data type.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > p = factory( Float64Array[ 1.0, -1.0 ] );\n    > p.x\n    1.0\n    > p.y\n    -1.0\n    > p[ 0 ]\n    1.0\n    > p[ 1 ]\n    -1.0\n\n\nfactory( obj[, dtype] )\n    Creates a named typed tuple from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a named typed\n        tuple.\n\n    dtype: string (optional)\n        Tuple data type.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > p = factory( [ 1, -1 ], 'int32' );\n    > p.x\n    1\n    > p.y\n    -1\n    > p[ 0 ]\n    1\n    > p[ 1 ]\n    -1\n\n\nfactory( buffer[, byteOffset][, dtype] )\n    Returns a named typed tuple view of an ArrayBuffer.\n\n    The view length equals the number of tuple fields.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first tuple element.\n        Default: 0.\n\n    dtype: string (optional)\n        Tuple data type.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var buf = new ArrayBuffer( 16 );\n    > var p = factory( buf, 4, 'float32' );\n    > p.x\n    0.0\n    > p.y\n    0.0\n    > p[ 0 ]\n    0.0\n    > p[ 1 ]\n    0.0\n\n\nfactory.from( src[, map[, thisArg]] )\n    Creates a new named typed tuple from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n    - field: tuple field.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of tuple elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > function mapFcn( v ) { return v * 2.0; };\n    > var p = factory.from( [ 1.0, -1.0 ], mapFcn );\n    > p.x\n    2.0\n    > p.y\n    -2.0\n    > p[ 0 ]\n    2.0\n    > p[ 1 ]\n    -2.0\n\n\nfactory.fromObject( obj[, map[, thisArg]] )\n    Creates a new named typed tuple from an object containing tuple fields.\n\n    A callback is provided the following arguments:\n\n    - value: source object tuple field value.\n    - field: source object tuple field name.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    map: Function (optional)\n        Callback to invoke for each source object tuple field.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory.fromObject( { 'x': 2.0, 'y': -2.0 } );\n    > p.x\n    2.0\n    > p.y\n    -2.0\n    > p[ 0 ]\n    2.0\n    > p[ 1 ]\n    -2.0\n\n\nfactory.of( element0[, element1[, ...elementN]] )\n    Creates a new named typed tuple from a variable number of arguments.\n\n    The number of arguments *must* equal the number of tuple fields.\n\n    Parameters\n    ----------\n    element0: number\n        Tuple element.\n\n    element1: number (optional)\n        Tuple element.\n\n    elementN: number (optional)\n        Tuple elements.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory.of( 2.0, -2.0 );\n    > p.x\n    2.0\n    > p.y\n    -2.0\n    > p[ 0 ]\n    2.0\n    > p[ 1 ]\n    -2.0\n\n\ntuple.BYTES_PER_ELEMENT\n    Size (in bytes) of each tuple element.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > p.BYTES_PER_ELEMENT\n    8\n\n\ntuple.buffer\n    Pointer to the underlying data buffer.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > p.buffer\n    <ArrayBuffer>\n\n\ntuple.byteLength\n    Length (in bytes) of the tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > p.byteLength\n    16\n\n\ntuple.byteOffset\n    Offset (in bytes) of a tuple from the start of its underlying ArrayBuffer.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > p.byteOffset\n    0\n\n\ntuple.length\n    Tuple length (i.e., number of elements).\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > p.length\n    2\n\n\ntuple.name\n    Tuple name.\n\n    Examples\n    --------\n    > var opts = { 'name': 'Point' };\n    > var factory = namedtypedtuple( [ 'x', 'y' ], opts );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > p.name\n    'Point'\n\n\ntuple.fields\n    Returns the list of tuple fields.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > p.fields\n    [ 'x', 'y' ]\n\n\ntuple.orderedFields\n    Returns the list of tuple fields in index order.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > p[ 0 ]\n    1.0\n    > p.sort();\n    > p[ 0 ]\n    -1.0\n    > p.fields\n    [ 'x', 'y' ]\n    > p.orderedFields\n    [ 'y', 'x' ]\n\n\ntuple.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the tuple starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: tuple.length.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Modified tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n    > var p = factory( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n    > p.copyWithin( 3, 0, 2 );\n    > p.w\n    2.0\n    > p.v\n    -2.0\n\n\ntuple.entries()\n    Returns an iterator for iterating over tuple key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over tuple key-value pairs.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > it = p.entries();\n    > it.next().value\n    [ 0, 'x', 1.0 ]\n    > it.next().value\n    [ 1, 'y', -1.0 ]\n    > it.next().done\n    true\n\n\ntuple.every( predicate[, thisArg] )\n    Tests whether all tuple elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: tuple element.\n    - index: tuple index.\n    - field: tuple field name.\n    - tuple: tuple on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests tuple elements. If a predicate function\n        returns a truthy value, a tuple element passes; otherwise, a tuple\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all tuple elements pass.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > function predicate( v ) { return ( v >= 0.0 ); };\n    > p.every( predicate )\n    false\n\n\ntuple.fieldOf( searchElement[, fromIndex] )\n    Returns the field of the first tuple element strictly equal to a search\n    element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `undefined`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Tuple index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last tuple element.\n        Default: 0.\n\n    Returns\n    -------\n    field: string|undefined\n        Tuple field.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > var f = p.fieldOf( 2.0 )\n    undefined\n    > f = p.fieldOf( -1.0 )\n    'z'\n\n\ntuple.fill( value[, start[, end]] )\n    Fills a tuple from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last tuple element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last tuple element. Default: tuple.length.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Modified tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > p.fill( 2.0 );\n    > p.x\n    2.0\n    > p.y\n    2.0\n\n\ntuple.filter( predicate[, thisArg] )\n    Creates a new tuple which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: tuple element.\n    - index: tuple index.\n    - field: tuple field name.\n    - tuple: tuple on which the method is invoked.\n\n    The returned tuple has the same data type as the host tuple.\n\n    If a predicate function does not return a truthy value for any tuple\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters tuple elements. If a predicate function\n        returns a truthy value, a tuple element is included in the output tuple;\n        otherwise, a tuple element is not included in the output tuple.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    tuple: TypedArray\n        A new named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v >= 0.0 ); };\n    > var p2 = p1.filter( predicate );\n    > p2.fields\n    [ 'x', 'y' ]\n\n\ntuple.find( predicate[, thisArg] )\n    Returns the first tuple element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: tuple element.\n    - index: tuple index.\n    - field: tuple field name.\n    - tuple: tuple on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests tuple elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Tuple element.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > var v = p.find( predicate )\n    -1.0\n\n\ntuple.findField( predicate[, thisArg] )\n    Returns the field of the first tuple element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: tuple element.\n    - index: tuple index.\n    - field: tuple field name.\n    - tuple: tuple on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests tuple elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    field: string|undefined\n        Tuple field.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > var f = p.findField( predicate )\n    'z'\n\n\ntuple.findIndex( predicate[, thisArg] )\n    Returns the index of the first tuple element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: tuple element.\n    - index: tuple index.\n    - field: tuple field name.\n    - tuple: tuple on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests tuple elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Tuple index.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > var idx = p.findIndex( predicate )\n    2\n\n\ntuple.forEach( fcn[, thisArg] )\n    Invokes a callback for each tuple element.\n\n    A provided function is provided the following arguments:\n\n    - value: tuple element.\n    - index: tuple index.\n    - field: tuple field name.\n    - tuple: tuple on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each tuple element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1, 0, -1 ], 'int32' );\n    > var str = ' ';\n    > function fcn( v, i, f ) { str += f + '=' + v + ' '; };\n    > p.forEach( fcn );\n    > str\n    ' x=1 y=0 z=-1 '\n\n\ntuple.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether a tuple includes a search element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Tuple index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last tuple element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a tuple includes a search element.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > var bool = p.includes( 2.0 )\n    false\n    > bool = p.includes( -1.0 )\n    true\n\n\ntuple.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first tuple element strictly equal to a search\n    element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Tuple index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last tuple element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Tuple index.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > var idx = p.indexOf( 2.0 )\n    -1\n    > idx = p.indexOf( -1.0 )\n    2\n\n\ntuple.ind2key( ind )\n    Converts a tuple index to a field name.\n\n    If provided an out-of-bounds index, the method returns `undefined`.\n\n    Parameters\n    ----------\n    ind: integer\n        Tuple index. If less than zero, the method resolves the index relative\n        to the last tuple element.\n\n    Returns\n    -------\n    field: string|undefined\n        Field name.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > p.ind2key( 1 )\n    'y'\n    > p.ind2key( 100 )\n    undefined\n\n\ntuple.join( [separator] )\n    Serializes a tuple by joining all tuple elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating tuple elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Tuple serialized as a string.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1, 0, -1 ], 'int32' );\n    > p.join( '|' )\n    '1|0|-1'\n\n\ntuple.keys()\n    Returns an iterator for iterating over tuple keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over tuple keys.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > it = p.keys();\n    > it.next().value\n    [ 0, 'x' ]\n    > it.next().value\n    [ 1, 'y' ]\n    > it.next().done\n    true\n\n\ntuple.key2ind( field )\n    Converts a field name to a tuple index.\n\n    If provided an unknown field name, the method returns `-1`.\n\n    Parameters\n    ----------\n    field: string\n        Tuple field name.\n\n    Returns\n    -------\n    idx: integer\n        Tuple index.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > p.key2ind( 'y' )\n    1\n\n\ntuple.lastFieldOf( searchElement[, fromIndex] )\n    Returns the field of the last tuple element strictly equal to a search\n    element.\n\n    The method iterates from the last tuple element to the first tuple element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `undefined`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Tuple index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last tuple element.\n        Default: -1.\n\n    Returns\n    -------\n    field: string|undefined\n        Tuple field.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n    > var f = p.lastFieldOf( 2.0 )\n    undefined\n    > f = p.lastFieldOf( 0.0 )\n    'w'\n\n\ntuple.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last tuple element strictly equal to a search\n    element.\n\n    The method iterates from the last tuple element to the first tuple element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Tuple index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last tuple element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Tuple index.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n    > var idx = p.lastIndexOf( 2.0 )\n    -1\n    > idx = p.lastIndexOf( 0.0 )\n    3\n\n\ntuple.map( fcn[, thisArg] )\n    Maps each tuple element to an element in a new tuple.\n\n    A provided function is provided the following arguments:\n\n    - value: tuple element.\n    - index: tuple index.\n    - field: tuple field name.\n    - tuple: tuple on which the method is invoked.\n\n    The returned tuple has the same data type as the host tuple.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps tuple elements to elements in the new tuple.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    tuple: TypedArray\n        A new named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( v ) { return v * 2.0; };\n    > var p2 = p1.map( fcn );\n    > p2.x\n    2.0\n    > p2.y\n    0.0\n    > p2.z\n    -2.0\n\n\ntuple.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in a tuple and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current tuple element.\n    - index: index of the current tuple element.\n    - field: field name corresponding to the current tuple element.\n    - tuple: tuple on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first tuple element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first tuple element as the first argument and the second tuple\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = p.reduce( fcn, 0.0 )\n    2.0\n\n\ntuple.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in a tuple and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current tuple element.\n    - index: index of the current tuple element.\n    - field: field name corresponding to the current tuple element.\n    - tuple: tuple on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last tuple element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last tuple element as the first argument and the second-to-last\n    tuple element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = p.reduceRight( fcn, 0.0 )\n    2.0\n\n\ntuple.reverse()\n    Reverses a tuple *in-place*.\n\n    This method mutates the tuple on which the method is invoked.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Modified tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > p[ 0 ]\n    1.0\n    > p.x\n    1.0\n    > p.reverse();\n    > p[ 0 ]\n    -1.0\n    > p.x\n    1.0\n\n\ntuple.set( arr[, offset] )\n    Sets tuple elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing tuple values to set.\n\n    offset: integer (optional)\n        Tuple index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > p[ 1 ]\n    0.0\n    > p.y\n    0.0\n    > p.set( [ -2.0, 2.0 ], 1 );\n    > p[ 1 ]\n    -2.0\n    > p.y\n    -2.0\n    > p[ 2 ]\n    2.0\n    > p.z\n    2.0\n\n\ntuple.slice( [begin[, end]] )\n    Copies tuple elements to a new tuple with the same underlying data type as\n    the host tuple.\n\n    If the method is unable to resolve indices to a non-empty tuple subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last tuple element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last tuple element. Default: tuple.length.\n\n    Returns\n    -------\n    tuple: TypedArray\n        A new named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n    > p1.fields\n    [ 'x', 'y', 'z' ]\n    > var p2 = p1.slice( 1 );\n    > p2.fields\n    [ 'y', 'z' ]\n    > p2.y\n    0.0\n    > p2.z\n    -1.0\n\n\ntuple.some( predicate[, thisArg] )\n    Tests whether at least one tuple element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: tuple element.\n    - index: tuple index.\n    - field: tuple field name.\n    - tuple: tuple on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests tuple elements. If a predicate function\n        returns a truthy value, a tuple element passes; otherwise, a tuple\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one tuple element passes.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > p.some( predicate )\n    true\n\n\ntuple.sort( [compareFunction] )\n    Sorts a tuple *in-place*.\n\n    Sorting a tuple does *not* affect field assignments. Accessing a tuple field\n    before and after sorting will always return the same tuple element. However,\n    this behavior is generally not true when accessing tuple elements according\n    to tuple index. In summary, sorting affects index order but not field\n    assignments.\n\n    The comparison function is provided two tuple elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the tuple on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Modified tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n    > var p = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n    > p.sort();\n    > p.orderedFields\n    [ 'v', 'y', 'z', 'x', 'w' ]\n    > p[ 0 ]\n    -2.0\n    > p.x\n    1.0\n    > p[ 1 ]\n    -1.0\n    > p.y\n    -1.0\n    > p.key2ind( 'x' )\n    3\n\n\ntuple.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host tuple.\n\n    If the method is unable to resolve indices to a non-empty tuple subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last tuple element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last tuple element. Default: tuple.length.\n\n    Returns\n    -------\n    arr: TypedArray\n        A new typed array view.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n    > var p = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n    > var arr = p.subarray( 2 )\n    <Float64Array>[ 0.0, 2.0, -2.0 ]\n    > arr.length\n    3\n\n\ntuple.subtuple( [begin[, end]] )\n    Creates a new named typed tuple over the same underlying ArrayBuffer and\n    with the same underlying data type as the host tuple.\n\n    If the function is unable to resolve indices to a non-empty tuple\n    subsequence, the function returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last tuple element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last tuple element. Default: tuple.length.\n\n    Returns\n    -------\n    tuple: TypedArray|null\n        A new named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n    > var p1 = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n    > var p2 = p1.subtuple( 2 );\n    > p2.fields\n    [ 'z', 'w', 'v' ]\n    > p2[ 0 ]\n    0.0\n    > p2.z\n    0.0\n    > p2[ 1 ]\n    2.0\n    > p2.w\n    2.0\n    > p2[ 2 ]\n    -2.0\n    > p2.v\n    -2.0\n    > p2.length\n    3\n\n\ntuple.toJSON()\n    Serializes a tuple as JSON.\n\n    Returns\n    -------\n    obj: Object\n        A tuple JSON representation.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, -1.0, 0.0 ] );\n    > p.toJSON()\n    { 'x': 1.0, 'y': -1.0, 'z': 0.0 }\n\n\ntuple.toLocaleString( [locales[, options]] )\n    Serializes a tuple as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, -1.0, 0.0 ], 'int32' );\n    > p.toLocaleString()\n    '1,-1,0'\n\n\ntuple.toString()\n    Serializes a tuple as a string.\n\n    Returns\n    -------\n    str: string\n        A tuple string representation.\n\n    Examples\n    --------\n    > opts = { 'name': 'Point' };\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ], opts );\n    > var p = factory( [ 1.0, -1.0, 0.0 ] );\n    > p.toString()\n    'Point(x=1, y=-1, z=0)'\n\n\ntuple.values()\n    Returns an iterator for iterating over tuple elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over tuple elements.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > it = p.values();\n    > it.next().value\n    1.0\n    > it.next().value\n    -1.0\n    > it.next().done\n    true\n\n    See Also\n    --------\n    typedarray\n","NAN":"\nNAN\n    Double-precision floating-point NaN.\n\n    Examples\n    --------\n    > NAN\n    NaN\n\n    See Also\n    --------\n    FLOAT32_NAN\n","naryFunction":"\nnaryFunction( fcn, arity[, thisArg] )\n    Returns a function that applies a specified number of arguments to a\n    provided function.\n\n    The returned function *always* invokes the wrapped function with a specified\n    number of arguments, even when the returned function is provided fewer\n    arguments.\n\n    The value for the missing arguments is equal to `undefined`.\n\n    Parameters\n    ----------\n    fcn: Function\n        Input function.\n\n    arity: integer\n        Number of arguments.\n\n    thisArg: any (optional)\n        Function context.\n\n    Returns\n    -------\n    out: Function\n        Function wrapper.\n\n    Examples\n    --------\n    > function foo( a, b, c ) { return [ a, b, c ]; };\n    > var bar = naryFunction( foo, 2 );\n    > var out = bar( 1, 2, 3 )\n    [ 1, 2, undefined ]\n\n    See Also\n    --------\n    maskArguments, pickArguments\n","nativeClass":"\nnativeClass( value )\n    Returns a string value indicating a specification defined classification of\n    an object.\n\n    The function is *not* robust for ES2015+ environments. In ES2015+,\n    `Symbol.toStringTag` allows overriding the default description of an object.\n    While measures are taken to uncover the default description, such measures\n    can be thwarted. While this function remains useful for type-checking, be\n    aware that value impersonation is possible. Where possible, prefer functions\n    tailored to checking for particular value types, as specialized functions\n    are better equipped to address `Symbol.toStringTag`.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    out: string\n        String value indicating a specification defined classification of the\n        input value.\n\n    Examples\n    --------\n    > var str = nativeClass( 'a' )\n    '[object String]'\n    > str = nativeClass( 5 )\n    '[object Number]'\n    > function Beep(){};\n    > str = nativeClass( new Beep() )\n    '[object Object]'\n\n    See Also\n    --------\n    constructorName, typeOf\n","ndarray":"\nndarray( dtype, buffer, shape, strides, offset, order[, options] )\n    Returns an ndarray.\n\n    Parameters\n    ----------\n    dtype: string\n        Underlying data type.\n\n    buffer: ArrayLikeObject|TypedArray|Buffer\n        Data buffer. A data buffer must be an array-like object (i.e., have a\n        `length` property). For data buffers which are not indexed collections\n        (i.e., collections which cannot support direct index access, such as\n        `buffer[ index ]`; e.g., Complex64Array, Complex128Array, etc), a data\n        buffer should provide `#.get( idx )` and `#.set( v[, idx] )` methods.\n        Note that, for `set` methods, the value to set should be the first\n        argument, followed by the linear index, similar to the native typed\n        array `set` method.\n\n    shape: ArrayLikeObject<integer>\n        Array shape.\n\n    strides: ArrayLikeObject<integer>\n        Array strides.\n\n    offset: integer\n        Index offset.\n\n    order: string\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran-style).\n\n    options: Object (optional)\n        Options.\n\n    options.mode: string (optional)\n        Specifies how to handle indices which exceed array dimensions. If equal\n        to 'throw', an ndarray instance throws an error when an index exceeds\n        array dimensions. If equal to 'normalize', an ndarray instance\n        normalizes negative indices and throws an error when an index exceeds\n        array dimensions. If equal to 'wrap', an ndarray instance wraps around\n        indices exceeding array dimensions using modulo arithmetic. If equal to\n        'clamp', an ndarray instance sets an index exceeding array dimensions\n        to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n    options.submode: Array<string> (optional)\n        Specifies how to handle subscripts which exceed array dimensions. If a\n        mode for a corresponding dimension is equal to 'throw', an ndarray\n        instance throws an error when a subscript exceeds array dimensions. If\n        equal to 'normalize', an ndarray instance normalizes negative\n        subscripts and throws an error when a subscript exceeds array\n        dimensions. If equal to 'wrap', an ndarray instance wraps around\n        subscripts exceeding array dimensions using modulo arithmetic. If equal\n        to 'clamp', an ndarray instance sets a subscript exceeding array\n        dimensions to either `0` (minimum index) or the maximum index. If the\n        number of modes is fewer than the number of dimensions, the function\n        recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether an array should be read-only. Default: false.\n\n    Returns\n    -------\n    ndarray: ndarray\n        ndarray instance.\n\n    Examples\n    --------\n    // Create a new instance...\n    > var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\n    > var d = [ 2, 2 ]; // shape\n    > var s = [ 2, 1 ]; // strides\n    > var o = 0; // index offset\n    > var arr = ndarray( 'generic', b, d, s, o, 'row-major' )\n    <ndarray>\n\n    // Get an element using subscripts:\n    > var v = arr.get( 1, 1 )\n    4.0\n\n    // Get an element using a linear index:\n    > v = arr.iget( 3 )\n    4.0\n\n    // Set an element using subscripts:\n    > arr.set( 1, 1, 40.0 );\n    > arr.get( 1, 1 )\n    40.0\n\n    // Set an element using a linear index:\n    > arr.iset( 3, 99.0 );\n    > arr.get( 1, 1 )\n    99.0\n\n\nndarray.prototype.byteLength\n    Size (in bytes) of the array (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of the array.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.byteLength\n    32\n\n\nndarray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.BYTES_PER_ELEMENT\n    8\n\n\nndarray.prototype.data\n    Pointer to the underlying data buffer.\n\n    Returns\n    -------\n    buf: ArrayLikeObject|TypedArray|Buffer\n        Underlying data buffer.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var buf = arr.data\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n\nndarray.prototype.dtype\n    Underlying data type.\n\n    Returns\n    -------\n    dtype: string\n        Underlying data type.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var dt = arr.dtype\n    'float64'\n\n\nndarray.prototype.flags\n    Meta information, such as information concerning the memory layout of the\n    array.\n\n    Returns\n    -------\n    flags: Object\n        Info object.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var fl = arr.flags\n    {...}\n\n\nndarray.prototype.length\n    Length of the array (i.e., number of elements).\n\n    Returns\n    -------\n    len: integer\n        Array length.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var len = arr.length\n    4\n\n\nndarray.prototype.ndims\n    Number of dimensions.\n\n    Returns\n    -------\n    ndims: integer\n        Number of dimensions.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var n = arr.ndims\n    2\n\n\nndarray.prototype.offset\n    Index offset which specifies the buffer index at which to start iterating\n    over array elements.\n\n    Returns\n    -------\n    offset: integer\n        Index offset.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.offset\n    0\n\n\nndarray.prototype.order\n    Array order.\n\n    The array order is either row-major (C-style) or column-major (Fortran-\n    style).\n\n    Returns\n    -------\n    order: string\n        Array order.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var ord = arr.order\n    'row-major'\n\n\nndarray.prototype.shape\n    Array shape.\n\n    Returns\n    -------\n    shape: Array\n        Array shape.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sh = arr.shape\n    [ 2, 2 ]\n\n\nndarray.prototype.strides\n    Index strides which specify how to access data along corresponding array\n    dimensions.\n\n    Returns\n    -------\n    strides: Array\n        Index strides.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var st = arr.strides\n    [ 2, 1 ]\n\n\nndarray.prototype.get( ...idx )\n    Returns an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.get( 1, 1 )\n    4.0\n\n\nndarray.prototype.iget( idx )\n    Returns an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the input argument is ignored and, for clarity,\n    should not be provided.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.iget( 3 )\n    4.0\n\n\nndarray.prototype.set( ...idx, v )\n    Sets an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: ndarray\n        ndarray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > arr.set( 1, 1, -4.0 );\n    > arr.get( 1, 1 )\n    -4.0\n\n\nndarray.prototype.iset( idx, v )\n    Sets an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the first, and only, argument should be the\n    value to set.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: ndarray\n        ndarray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > arr.iset( 3, -4.0 );\n    > arr.iget( 3 )\n    -4.0\n\n\nndarray.prototype.toString()\n    Serializes an ndarray as a string.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    str: string\n        Serialized ndarray string.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toString()\n    '...'\n\n\nndarray.prototype.toJSON()\n    Serializes an ndarray as a JSON object.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toJSON()\n    {...}\n\n    See Also\n    --------\n    array, FancyArray\n","ndarray.prototype.byteLength":"\nndarray.prototype.byteLength\n    Size (in bytes) of the array (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of the array.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.byteLength\n    32","ndarray.prototype.BYTES_PER_ELEMENT":"\nndarray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.BYTES_PER_ELEMENT\n    8","ndarray.prototype.data":"\nndarray.prototype.data\n    Pointer to the underlying data buffer.\n\n    Returns\n    -------\n    buf: ArrayLikeObject|TypedArray|Buffer\n        Underlying data buffer.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var buf = arr.data\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]","ndarray.prototype.dtype":"\nndarray.prototype.dtype\n    Underlying data type.\n\n    Returns\n    -------\n    dtype: string\n        Underlying data type.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var dt = arr.dtype\n    'float64'","ndarray.prototype.flags":"\nndarray.prototype.flags\n    Meta information, such as information concerning the memory layout of the\n    array.\n\n    Returns\n    -------\n    flags: Object\n        Info object.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var fl = arr.flags\n    {...}","ndarray.prototype.length":"\nndarray.prototype.length\n    Length of the array (i.e., number of elements).\n\n    Returns\n    -------\n    len: integer\n        Array length.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var len = arr.length\n    4","ndarray.prototype.ndims":"\nndarray.prototype.ndims\n    Number of dimensions.\n\n    Returns\n    -------\n    ndims: integer\n        Number of dimensions.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var n = arr.ndims\n    2","ndarray.prototype.offset":"\nndarray.prototype.offset\n    Index offset which specifies the buffer index at which to start iterating\n    over array elements.\n\n    Returns\n    -------\n    offset: integer\n        Index offset.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.offset\n    0","ndarray.prototype.order":"\nndarray.prototype.order\n    Array order.\n\n    The array order is either row-major (C-style) or column-major (Fortran-\n    style).\n\n    Returns\n    -------\n    order: string\n        Array order.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var ord = arr.order\n    'row-major'","ndarray.prototype.shape":"\nndarray.prototype.shape\n    Array shape.\n\n    Returns\n    -------\n    shape: Array\n        Array shape.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sh = arr.shape\n    [ 2, 2 ]","ndarray.prototype.strides":"\nndarray.prototype.strides\n    Index strides which specify how to access data along corresponding array\n    dimensions.\n\n    Returns\n    -------\n    strides: Array\n        Index strides.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var st = arr.strides\n    [ 2, 1 ]","ndarray.prototype.get":"\nndarray.prototype.get( ...idx )\n    Returns an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.get( 1, 1 )\n    4.0","ndarray.prototype.iget":"\nndarray.prototype.iget( idx )\n    Returns an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the input argument is ignored and, for clarity,\n    should not be provided.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.iget( 3 )\n    4.0","ndarray.prototype.set":"\nndarray.prototype.set( ...idx, v )\n    Sets an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: ndarray\n        ndarray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > arr.set( 1, 1, -4.0 );\n    > arr.get( 1, 1 )\n    -4.0","ndarray.prototype.iset":"\nndarray.prototype.iset( idx, v )\n    Sets an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the first, and only, argument should be the\n    value to set.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: ndarray\n        ndarray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > arr.iset( 3, -4.0 );\n    > arr.iget( 3 )\n    -4.0","ndarray.prototype.toString":"\nndarray.prototype.toString()\n    Serializes an ndarray as a string.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    str: string\n        Serialized ndarray string.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toString()\n    '...'","ndarray.prototype.toJSON":"\nndarray.prototype.toJSON()\n    Serializes an ndarray as a JSON object.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toJSON()\n    {...}\n\n    See Also\n    --------\n    array, FancyArray","ndarray2array":"\nndarray2array( x )\n    Converts an ndarray to a generic array.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    Returns\n    -------\n    out: Array|Array<Array>\n        Generic array (which may include nested arrays).\n\n    Examples\n    --------\n    > var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > var out = ndarray2array( arr )\n    [ [ 1, 2 ], [ 3, 4 ] ]\n\n    See Also\n    --------\n    array, ndarray, ndarray2json\n","ndarray2fancy":"\nndarray2fancy( x[, options] )\n    Converts an ndarray to an object supporting fancy indexing.\n\n    An ndarray supporting fancy indexing is an ndarray which supports slicing\n    via indexing expressions for both retrieval and assignment.\n\n    A fancy ndarray can be consumed by any API which supports ndarray instances.\n\n    A fancy ndarray shares the *same* data as the provided input ndarray. Hence,\n    any mutations to the returned ndarray will affect the underlying input\n    ndarray and vice versa.\n\n    A fancy ndarray supports indexing using positive and negative integers (both\n    numeric literals and strings), Slice and MultiSlice instances, subsequence\n    expressions, mask ndarrays, boolean ndarrays, and integer ndarrays.\n\n    A fancy ndarray supports all properties and methods of the input ndarray,\n    and, thus, a fancy ndarray can be consumed by any API which supports\n    ndarray-like objects.\n\n    For operations returning a new ndarray (e.g., when slicing or invoking an\n    instance method), a fancy ndarray returns a new fancy ndarray having the\n    same configuration as specified by provided options.\n\n    Indexing expressions provide a convenient and powerful means for creating\n    and operating on ndarray views; however, their use does entail a performance\n    cost. Indexing expressions are best suited for interactive use and\n    scripting. For performance critical applications, prefer equivalent\n    functional APIs supporting ndarray instances.\n\n    Fancy ndarrays support broadcasting in which assigned scalars and ndarrays\n    are repeated (without additional memory allocation) to match the dimensions\n    of a target ndarray instance.\n\n    When assigning ndarrays to slices, the ndarray on the right-hand-side must\n    be broadcast-compatible with dimensions implied by the slice.\n\n    Fancy ndarrays support (mostly) safe casts (i.e., any cast which can be\n    performed without overflow or loss of precision, with the exception of\n    floating-point ndarrays which are also allowed to downcast from higher\n    precision to lower precision).\n\n    When attempting to perform an unsafe cast, fancy ndarrays will raise an\n    exception.\n\n    When assigning a real-valued scalar to a complex number ndarray, a fancy\n    ndarray will cast the real-valued scalar to a complex number argument having\n    an imaginary component equal to zero.\n\n    In older JavaScript environments which do not support Proxy objects, the use\n    of indexing expressions is not supported.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking. Default:\n        false.\n\n    options.cache: Object (optional)\n        Cache for resolving ndarray index objects. Must have a 'get' method\n        which accepts a single argument: a string identifier associated with an\n        ndarray index. If an ndarray index associated with a provided identifier\n        exists, the 'get' method should return an object having the following\n        properties:\n\n        - data: the underlying index ndarray.\n        - type: the index type. Must be either 'mask', 'bool', or 'int'.\n        - kind: the index kind. Must be either '', 'cartesian', or 'linear'.\n        - dtype: the data type of the underlying ndarray.\n\n        If an ndarray index is not associated with a provided identifier, the\n        'get' method should return `null`.\n\n        Default: `ndindex`.\n\n    Returns\n    -------\n    out: ndarray\n        Output ndarray supporting fancy indexing.\n\n    Examples\n    --------\n    // Create a normal ndarray...\n    > var b = [ 1.0, 2.0, 3.0, 4.0 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var x = ndarray( 'generic', b, d, s, o, 'row-major' );\n\n    // Convert to a fancy ndarray:\n    > var arr = ndarray2fancy( x );\n\n    // Get an element using subscripts:\n    > var v = arr.get( 1, 1 )\n    4.0\n\n    // Get an element using a linear index:\n    > v = arr.iget( 3 )\n    4.0\n\n    // Set an element using subscripts:\n    > arr.set( 1, 1, 40.0 );\n    > arr.get( 1, 1 )\n    40.0\n\n    // Set an element using a linear index:\n    > arr.iset( 3, 99.0 );\n    > arr.get( 1, 1 )\n    99.0\n\n\nndarray2fancy.factory( [options] )\n    Returns a function for converting an ndarray to an object supporting fancy\n    indexing.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking by default.\n        Default: false.\n\n    options.cache: Object (optional)\n        Cache for resolving ndarray index objects. Must have a 'get' method\n        which accepts a single argument: a string identifier associated with an\n        ndarray index. If an ndarray index associated with a provided identifier\n        exists, the 'get' method should return an object having the following\n        properties:\n\n        - data: the underlying index ndarray.\n        - type: the index type. Must be either 'mask', 'bool', or 'int'.\n        - kind: the index kind. Must be either '', 'cartesian', or 'linear'.\n        - dtype: the data type of the underlying ndarray.\n\n        If an ndarray index is not associated with a provided identifier, the\n        'get' method should return `null`.\n\n        Default: `ndindex`.\n\n    Returns\n    -------\n    fcn: Function\n        Function for converting an ndarray to an object supporting fancy\n        indexing.\n\n    Examples\n    --------\n    // Create a normal ndarray...\n    > var b = [ 1.0, 2.0, 3.0, 4.0 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var x = ndarray( 'generic', b, d, s, o, 'row-major' );\n\n    // Create a function for converting ndarrays to fancy ndarrays:\n    > var f = ndarray2fancy.factory();\n\n    // Convert the normal ndarray to a fancy ndarray:\n    > var y = f( x );\n\n\nndarray2fancy.idx( x[, options] )\n    Wraps a provided ndarray as an ndarray index object.\n\n    For documentation and usage, see `ndindex`.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.persist: boolean (optional)\n        Boolean indicating whether to continue persisting an index object after\n        first usage. Default: false.\n\n    options.kind: string (optional)\n        Specifies whether a provided ndarray is a specialized input ndarray\n        \"kind\". This option is only applicable for integer input ndarrays. Must\n        be one of the following:\n\n        - cartesian: a provided input ndarray contains Cartesian indices.\n        - linear: a provided input ndarray contains indices representing\n          locations in linear memory.\n\n        Default: ''.\n\n    Returns\n    -------\n    out: ndarrayIndex\n        ndarray index instance.\n\n    Examples\n    --------\n    > var opts = { 'dtype': 'int32' };\n    > var buf = new Int32Array( [ 1, 2, 3, 4 ] );\n    > var arr = array( buf, opts );\n    > var idx = ndarray2fancy.idx( arr );\n\n    See Also\n    --------\n    array2fancy, array, ndarray, FancyArray\n","ndarray2fancy.factory":"\nndarray2fancy.factory( [options] )\n    Returns a function for converting an ndarray to an object supporting fancy\n    indexing.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking by default.\n        Default: false.\n\n    options.cache: Object (optional)\n        Cache for resolving ndarray index objects. Must have a 'get' method\n        which accepts a single argument: a string identifier associated with an\n        ndarray index. If an ndarray index associated with a provided identifier\n        exists, the 'get' method should return an object having the following\n        properties:\n\n        - data: the underlying index ndarray.\n        - type: the index type. Must be either 'mask', 'bool', or 'int'.\n        - kind: the index kind. Must be either '', 'cartesian', or 'linear'.\n        - dtype: the data type of the underlying ndarray.\n\n        If an ndarray index is not associated with a provided identifier, the\n        'get' method should return `null`.\n\n        Default: `ndindex`.\n\n    Returns\n    -------\n    fcn: Function\n        Function for converting an ndarray to an object supporting fancy\n        indexing.\n\n    Examples\n    --------\n    // Create a normal ndarray...\n    > var b = [ 1.0, 2.0, 3.0, 4.0 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var x = ndarray( 'generic', b, d, s, o, 'row-major' );\n\n    // Create a function for converting ndarrays to fancy ndarrays:\n    > var f = ndarray2fancy.factory();\n\n    // Convert the normal ndarray to a fancy ndarray:\n    > var y = f( x );","ndarray2fancy.idx":"\nndarray2fancy.idx( x[, options] )\n    Wraps a provided ndarray as an ndarray index object.\n\n    For documentation and usage, see `ndindex`.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.persist: boolean (optional)\n        Boolean indicating whether to continue persisting an index object after\n        first usage. Default: false.\n\n    options.kind: string (optional)\n        Specifies whether a provided ndarray is a specialized input ndarray\n        \"kind\". This option is only applicable for integer input ndarrays. Must\n        be one of the following:\n\n        - cartesian: a provided input ndarray contains Cartesian indices.\n        - linear: a provided input ndarray contains indices representing\n          locations in linear memory.\n\n        Default: ''.\n\n    Returns\n    -------\n    out: ndarrayIndex\n        ndarray index instance.\n\n    Examples\n    --------\n    > var opts = { 'dtype': 'int32' };\n    > var buf = new Int32Array( [ 1, 2, 3, 4 ] );\n    > var arr = array( buf, opts );\n    > var idx = ndarray2fancy.idx( arr );\n\n    See Also\n    --------\n    array2fancy, array, ndarray, FancyArray","ndarray2json":"\nndarray2json( x )\n    Serializes an ndarray as a JSON object.\n\n    This function does *not* serialize data outside of the buffer region defined\n    by the ndarray view.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    Returns\n    -------\n    out: Object\n        JSON object.\n\n    Examples\n    --------\n    > var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > var out = ndarray2json( arr )\n    {...}\n\n    See Also\n    --------\n    array, ndarray, ndarray2array\n","ndarrayCastingModes":"\nndarrayCastingModes()\n    Returns a list of ndarray casting modes.\n\n    The output array contains the following modes:\n\n    - 'none': only allow casting between identical types.\n    - 'equiv': allow casting between identical and byte swapped types.\n    - 'safe': only allow \"safe\" casts.\n    - 'mostly-safe': allow \"safe\" casts and, for floating-point data types,\n      downcasts.\n    - 'same-kind': allow \"safe\" casts and casts within the same kind (e.g.,\n      between signed integers or between floats).\n    - 'unsafe': allow casting between all types (including between integers and\n      floats).\n\n    Returns\n    -------\n    out: Array<string>\n        List of ndarray casting modes.\n\n    Examples\n    --------\n    > var out = ndarrayCastingModes()\n    [ 'none', 'equiv', 'safe', 'mostly-safe', 'same-kind', 'unsafe' ]\n\n    See Also\n    --------\n    array, ndarray\n","ndarrayDataBuffer":"\nndarrayDataBuffer( x )\n    Returns the underlying data buffer of a provided ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Underlying data buffer.\n\n    Examples\n    --------\n    > var opts = { 'dtype': 'float64' };\n    > var out = ndarrayDataBuffer( ndzeros( [ 3, 3, 3 ], opts ) )\n    <Float64Array>\n\n    See Also\n    --------\n    array, ndarray, ndarrayDataType\n","ndarrayDataType":"\nndarrayDataType( x )\n    Returns the data type of a provided ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    Returns\n    -------\n    dt: string\n        Data type.\n\n    Examples\n    --------\n    > var opts = { 'dtype': 'float64' };\n    > var dt = ndarrayDataType( ndzeros( [ 3, 3, 3 ], opts ) )\n    'float64'\n\n    See Also\n    --------\n    array, ndarray, ndarrayDataTypes\n","ndarrayDataTypes":"\nndarrayDataTypes( [kind] )\n    Returns a list of ndarray data types.\n\n    When not provided a data type \"kind\", the function returns an array\n    containing the following data types:\n\n    - float32: single-precision floating-point numbers.\n    - float64: double-precision floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - complex128: double-precision complex floating-point numbers.\n    - bool: boolean values.\n    - generic: values of any type.\n    - int16: signed 16-bit integers.\n    - int32: signed 32-bit integers.\n    - int8: signed 8-bit integers.\n    - uint16: unsigned 16-bit integers.\n    - uint32: unsigned 32-bit integers.\n    - uint8: unsigned 8-bit integers.\n    - uint8c: unsigned clamped 8-bit integers.\n    - binary: binary.\n\n    The function supports the following data type \"kinds\":\n\n    - floating_point: floating-point data types.\n    - real_floating_point: real-valued floating-point data types.\n    - complex_floating_point: complex-valued floating-point data types.\n    - boolean: boolean data types.\n    - integer: integer data types.\n    - signed_integer: signed integer data types.\n    - unsigned_integer: unsigned integer data types.\n    - real: real-valued data types.\n    - numeric: numeric data types.\n    - typed: typed data types.\n    - all: all data types.\n\n    Additionally, the function supports extending the \"kinds\" listed above by\n    appending a '_and_generic' suffix to the kind name (e.g., real_and_generic).\n\n    Parameters\n    ----------\n    kind: string (optional)\n        Data type kind.\n\n    Returns\n    -------\n    out: Array<string>\n        List of ndarray data types.\n\n    Examples\n    --------\n    > var out = ndarrayDataTypes()\n    [...]\n    > out = ndarrayDataTypes( 'floating_point' )\n    [...]\n    > out = ndarrayDataTypes( 'floating_point_and_generic' )\n    [...]\n\n    See Also\n    --------\n    arrayDataTypes, array, ndarray, typedarrayDataTypes\n","ndarrayDispatch":"\nndarrayDispatch( fcns, types, data, nargs, nin, nout )\n    Returns an ndarray function interface which performs multiple dispatch.\n\n    An ndarray function interface has the following signature:\n\n      f( x, y, ... )\n\n    where\n\n    - x: ndarray.\n    - y: ndarray.\n    - ...: additional ndarrays.\n\n    The number of parameters is derived from `nargs`, the number of input\n    ndarrays is derived from `nin`, and the number of output ndarrays is derived\n    from `nout`.\n\n    Parameters\n    ----------\n    fcns: Function|ArrayLikeObject<Function>\n        List of ndarray functions. An ndarray function should have the following\n        signature:\n\n          f( arrays, data )\n\n        where\n\n        - arrays: array containing input and output ndarrays.\n        - data: ndarray function data (e.g., a callback).\n\n        For convenience, a single ndarray function may be provided which will be\n        invoked whenever the ndarray argument data types match a sequence of\n        types in `types`. Providing a single ndarray function is particularly\n        convenient for the case where, regardless of array data types,\n        traversing arrays remains the same, but the ndarray function `data`\n        differs (e.g., callbacks which differ based on the array data types).\n\n    types: ArrayLikeObject\n        One-dimensional list of ndarray argument data types.\n\n    data: ArrayLikeObject|null\n        ndarray function data (e.g., callbacks). If `null`, a returned ndarray\n        function interface does **not** provide a `data` argument to an invoked\n        ndarray function.\n\n    nargs: integer\n        Total number of ndarray function interface arguments.\n\n    nin: integer\n        Number of input ndarrays.\n\n    nout: integer\n        Number of output ndarrays.\n\n    Returns\n    -------\n    fcn: Function\n        ndarray function interface.\n\n    Examples\n    --------\n    // Define ndarray argument data types:\n    > var t = [ 'float64', 'float64', 'float32', 'float32' ];\n\n    // Define a list of ndarray function data (callbacks):\n    > var d = [ base.abs, base.absf ];\n\n    // Create an ndarray function interface for applying unary callbacks:\n    > var f = ndarrayDispatch( base.ndarrayUnary, t, d, 2, 1, 1 );\n\n    // Create an input ndarray:\n    > var xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var x = ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );\n\n    // Create an output ndarray:\n    > var ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var y = ndarray( 'float64', ybuf, [ 4 ], [ 1 ], 0, 'row-major' );\n\n    // Compute the element-wise absolute value:\n    > f( x, y );\n    > ybuf\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    See Also\n    --------\n    array, ndarray\n","ndarrayFlag":"\nndarrayFlag( x, name )\n    Returns a specified flag for a provided ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    name: string|symbol\n        Flag name.\n\n    Returns\n    -------\n    out: any\n        Flag value.\n\n    Examples\n    --------\n    > var out = ndarrayFlag( ndzeros( [ 3, 3, 3 ] ), 'READONLY' )\n    <boolean>\n\n    See Also\n    --------\n    array, ndarray, ndarrayFlags\n","ndarrayFlags":"\nndarrayFlags( x )\n    Returns the flags of a provided ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    Returns\n    -------\n    out: Object\n        Flags.\n\n    Examples\n    --------\n    > var out = ndarrayFlags( ndzeros( [ 3, 3, 3 ] ) )\n    {...}\n\n    See Also\n    --------\n    array, ndarray, ndarrayFlag\n","ndarrayIndexModes":"\nndarrayIndexModes()\n    Returns a list of ndarray index modes.\n\n    The output array contains the following modes:\n\n    - throw: specifies that a function should throw an error when an index is\n    outside a restricted interval.\n    - normalize: specifies that a function should normalize negative indices and\n    throw an error when an index is outside a restricted interval.\n    - wrap: specifies that a function should wrap around an index using modulo\n    arithmetic.\n    - clamp: specifies that a function should set an index less than zero to\n    zero (minimum index) and set an index greater than a maximum index value to\n    the maximum possible index.\n\n    Returns\n    -------\n    out: Array<string>\n        List of ndarray index modes.\n\n    Examples\n    --------\n    > var out = ndarrayIndexModes()\n    [ 'throw', 'normalize', 'clamp', 'wrap' ]\n\n    See Also\n    --------\n    array, ndarray\n","ndarraylike2ndarray":"\nndarraylike2ndarray( x[, options] )\n    Converts an ndarray-like object to an ndarray.\n\n    If provided a read-only ndarray, the function returns a read-only ndarray.\n\n    Parameters\n    ----------\n    x: ndarrayLike\n        Input ndarray-like object.\n\n    options: Object (optional)\n        Options.\n\n    options.mode: string (optional)\n        Specifies how to handle indices which exceed array dimensions. If equal\n        to 'throw', an ndarray instance throws an error when an index exceeds\n        array dimensions. If equal to 'normalize', an ndarray instance\n        normalizes negative indices and throws an error when an index exceeds\n        array dimensions. If equal to 'wrap', an ndarray instance wraps around\n        indices exceeding array dimensions using modulo arithmetic. If equal to\n        'clamp', an ndarray instance sets an index exceeding array dimensions\n        to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n    options.submode: Array<string> (optional)\n        Specifies how to handle subscripts which exceed array dimensions. If a\n        mode for a corresponding dimension is equal to 'throw', an ndarray\n        instance throws an error when a subscript exceeds array dimensions. If\n        equal to 'normalize', an ndarray instance normalizes negative\n        subscripts and throws an error when a subscript exceeds array\n        dimensions. If equal to 'wrap', an ndarray instance wraps around\n        subscripts exceeding array dimensions using modulo arithmetic. If equal\n        to 'clamp', an ndarray instance sets a subscript exceeding array\n        dimensions to either `0` (minimum index) or the maximum index. If the\n        number of modes is fewer than the number of dimensions, the function\n        recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether an array should be read-only.\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > var out = ndarraylike2ndarray( arr )\n    <ndarray>\n\n    See Also\n    --------\n    array, ndarray, ndemptyLike, ndzerosLike\n","ndarrayMinDataType":"\nndarrayMinDataType( value )\n    Returns the minimum ndarray data type of the closest \"kind\" necessary for\n    storing a provided scalar value.\n\n    The function does *not* provide precision guarantees for non-integer-valued\n    numbers. In other words, the function returns the smallest possible\n    floating-point (i.e., inexact) data type for storing numbers having\n    decimals.\n\n    Parameters\n    ----------\n    value: any\n        Scalar value.\n\n    Returns\n    -------\n    dt: string\n        ndarray data type.\n\n    Examples\n    --------\n    > var dt = ndarrayMinDataType( 3.141592653589793 )\n    'float32'\n    > dt = ndarrayMinDataType( 3 )\n    'uint8'\n    > dt = ndarrayMinDataType( -3 )\n    'int8'\n    > dt = ndarrayMinDataType( '-3' )\n    'generic'\n\n    See Also\n    --------\n    ndarrayDataTypes, ndarrayPromotionRules, ndarraySafeCasts\n","ndarrayMostlySafeCasts":"\nndarrayMostlySafeCasts( [dtype] )\n    Returns a list of ndarray data types to which a provided ndarray data type\n    can be safely cast and, for floating-point data types, can be downcast.\n\n    If not provided an ndarray data type, the function returns a casting table.\n\n    If provided an unrecognized ndarray data type, the function returns `null`.\n\n    Parameters\n    ----------\n    dtype: any (optional)\n        ndarray data type value.\n\n    Returns\n    -------\n    out: Object|Array<string>|null\n        ndarray data types to which a data type can be cast.\n\n    Examples\n    --------\n    > var out = ndarrayMostlySafeCasts( 'float32' )\n    <Array>\n\n    See Also\n    --------\n    ndarrayCastingModes, ndarrayDataTypes, ndarraySafeCasts, ndarraySameKindCasts\n","ndarrayNextDataType":"\nndarrayNextDataType( [dtype] )\n    Returns the next larger ndarray data type of the same kind.\n\n    If not provided a data type, the function returns a table.\n\n    If a data type does not have a next larger data type or the next larger type\n    is not supported, the function returns `-1`.\n\n    If provided an unrecognized data type, the function returns `null`.\n\n    Parameters\n    ----------\n    dtype: any (optional)\n        ndarray data type value.\n\n    Returns\n    -------\n    out: Object|string|integer|null\n        Next larger type(s).\n\n    Examples\n    --------\n    > var out = ndarrayNextDataType( 'float32' )\n    'float64'\n\n    See Also\n    --------\n    ndarrayDataTypes, ndarrayPromotionRules, ndarraySafeCasts\n","ndarrayOffset":"\nndarrayOffset( x )\n    Returns the index offset specifying the underlying buffer index of the first\n    iterated ndarray element.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    Returns\n    -------\n    n: integer\n        Index offset.\n\n    Examples\n    --------\n    > var n = ndarrayOffset( ndzeros( [ 3, 3, 3 ] ) )\n    0\n\n    See Also\n    --------\n    array, ndarray, ndarrayShape, ndarrayStrides\n","ndarrayOrder":"\nndarrayOrder( x )\n    Returns the layout order of a provided ndarray.\n\n    If unable to resolve a layout order, the function returns `null`.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    Returns\n    -------\n    out: string|null\n        Layout order.\n\n    Examples\n    --------\n    > var opts = { 'order': 'row-major' };\n    > var dt = ndarrayOrder( ndzeros( [ 3, 3, 3 ], opts ) )\n    'row-major'\n\n    See Also\n    --------\n    array, ndarray, ndarrayOrders, ndarrayShape, ndarrayStrides\n","ndarrayOrders":"\nndarrayOrders()\n    Returns a list of ndarray orders.\n\n    The output array contains the following orders:\n\n    - row-major: row-major (C-style) order.\n    - column-major: column-major (Fortran-style) order.\n\n    Returns\n    -------\n    out: Array<string>\n        List of ndarray orders.\n\n    Examples\n    --------\n    > var out = ndarrayOrders()\n    [ 'row-major', 'column-major' ]\n\n    See Also\n    --------\n    array, ndarray\n","ndarrayPromotionRules":"\nndarrayPromotionRules( [dtype1, dtype2] )\n    Returns the ndarray data type with the smallest size and closest \"kind\" to\n    which ndarray data types can be safely cast.\n\n    If not provided data types, the function returns a type promotion table.\n\n    If a data type to which data types can be safely cast does *not* exist (or\n    is not supported), the function returns `-1`.\n\n    If provided an unrecognized data type, the function returns `null`.\n\n    Parameters\n    ----------\n    dtype1: any (optional)\n        ndarray data type value.\n\n    dtype2: any (optional)\n        ndarray data type value.\n\n    Returns\n    -------\n    out: Object|string|integer|null\n        Promotion rule(s).\n\n    Examples\n    --------\n    > var out = ndarrayPromotionRules( 'float32', 'int32' )\n    'float64'\n\n    See Also\n    --------\n    ndarrayCastingModes, ndarrayDataTypes, ndarraySafeCasts\n","ndarraySafeCasts":"\nndarraySafeCasts( [dtype] )\n    Returns a list of ndarray data types to which a provided ndarray data type\n    can be safely cast.\n\n    If not provided an ndarray data type, the function returns a casting table.\n\n    If provided an unrecognized ndarray data type, the function returns `null`.\n\n    Parameters\n    ----------\n    dtype: any (optional)\n        ndarray data type value.\n\n    Returns\n    -------\n    out: Object|Array<string>|null\n        ndarray data types to which a data type can be safely cast.\n\n    Examples\n    --------\n    > var out = ndarraySafeCasts( 'float32' )\n    <Array>\n\n    See Also\n    --------\n    ndarrayCastingModes, ndarrayDataTypes, ndarraySameKindCasts\n","ndarraySameKindCasts":"\nndarraySameKindCasts( [dtype] )\n    Returns a list of ndarray data types to which a provided ndarray data type\n    can be safely cast or cast within the same \"kind\".\n\n    If not provided an ndarray data type, the function returns a casting table.\n\n    If provided an unrecognized ndarray data type, the function returns `null`.\n\n    Parameters\n    ----------\n    dtype: any (optional)\n        ndarray data type value.\n\n    Returns\n    -------\n    out: Object|Array<string>|null\n        ndarray data types to which a data type can be safely cast or cast\n        within the same \"kind\".\n\n    Examples\n    --------\n    > var out = ndarraySameKindCasts( 'float32' )\n    <Array>\n\n    See Also\n    --------\n    ndarrayCastingModes, ndarrayDataTypes, ndarraySafeCasts\n","ndarrayShape":"\nndarrayShape( x )\n    Returns the shape of a provided ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    Returns\n    -------\n    out: Array<integer>\n        Shape.\n\n    Examples\n    --------\n    > var out = ndarrayShape( ndzeros( [ 3, 3, 3 ] ) )\n    [ 3, 3, 3 ]\n\n    See Also\n    --------\n    array, ndarray, ndarrayOffset, ndarrayStrides\n","ndarrayStride":"\nndarrayStride( x, dim )\n    Returns the stride along a specified dimension for a provided ndarray.\n\n    A \"stride\" is the linear distance (i.e., number of elements) between\n    adjacent elements along a specified dimension.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    dim: integer\n        Dimension index. If less than zero, the index is resolved relative to\n        the last dimension, with the last dimension corresponding to the value\n        `-1`.\n\n    Returns\n    -------\n    out: integer\n        Stride.\n\n    Examples\n    --------\n    > var out = ndarrayStride( ndzeros( [ 3, 3, 3 ] ), 0 )\n    9\n\n    See Also\n    --------\n    array, ndarray, ndarrayOffset, ndarrayOrder, ndarrayShape, ndarrayStrides\n","ndarrayStrides":"\nndarrayStrides( x )\n    Returns the strides of a provided ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    Returns\n    -------\n    out: Array<integer>\n        Strides.\n\n    Examples\n    --------\n    > var out = ndarrayStrides( ndzeros( [ 3, 3, 3 ] ) )\n    [ 9, 3, 1 ]\n\n    See Also\n    --------\n    array, ndarray, ndarrayOffset, ndarrayOrder, ndarrayShape\n","ndat":"\nndat( x[, ...indices] )\n    Returns an ndarray element.\n\n    Negative indices are resolved relative to the last element along the\n    respective dimension, with the last element corresponding to `-1`.\n\n    If provided out-of-bounds indices, the function always returns `undefined`.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    indices: ...integer (optional)\n        Index arguments. The number of index arguments must equal the number of\n        dimensions.\n\n    Returns\n    -------\n    out: any\n        Element value.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > ndat( x, 0, 1 )\n    2\n    > ndat( x, 1, 0 )\n    3\n\n    See Also\n    --------\n    array, ndslice\n","ndempty":"\nndempty( shape[, options] )\n    Returns an uninitialized ndarray having a specified shape and data type.\n\n    In browser environments, the function always returns zero-filled ndarrays.\n\n    If `dtype` is 'generic', the function always returns a zero-filled ndarray.\n\n    For returned ndarrays whose underlying memory is *not* initialized, memory\n    contents are unknown and may contain *sensitive* data.\n\n    Parameters\n    ----------\n    shape: ArrayLikeObject<integer>|integer\n        Array shape.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Underlying data type. Default: 'float64'.\n\n    options.order: string (optional)\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran-style). Default: 'row-major'.\n\n    options.mode: string (optional)\n        Specifies how to handle indices which exceed array dimensions. If equal\n        to 'throw', an ndarray instance throws an error when an index exceeds\n        array dimensions. If equal to 'normalize', an ndarray instance\n        normalizes negative indices and throws an error when an index exceeds\n        array dimensions. If equal to 'wrap', an ndarray instance wraps around\n        indices exceeding array dimensions using modulo arithmetic. If equal to\n        'clamp', an ndarray instance sets an index exceeding array dimensions\n        to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n    options.submode: Array<string> (optional)\n        Specifies how to handle subscripts which exceed array dimensions. If a\n        mode for a corresponding dimension is equal to 'throw', an ndarray\n        instance throws an error when a subscript exceeds array dimensions. If\n        equal to 'normalize', an ndarray instance normalizes negative\n        subscripts and throws an error when a subscript exceeds array\n        dimensions. If equal to 'wrap', an ndarray instance wraps around\n        subscripts exceeding array dimensions using modulo arithmetic. If equal\n        to 'clamp', an ndarray instance sets a subscript exceeding array\n        dimensions to either `0` (minimum index) or the maximum index. If the\n        number of modes is fewer than the number of dimensions, the function\n        recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var arr = ndempty( [ 2, 2 ] )\n    <ndarray>\n    > var sh = arr.shape\n    [ 2, 2 ]\n    > var dt = arr.dtype\n    'float64'\n\n    See Also\n    --------\n    ndemptyLike, ndzeros\n","ndemptyLike":"\nndemptyLike( x[, options] )\n    Returns an uninitialized ndarray having the same shape and data type as a\n    provided input ndarray.\n\n    The function infers the following attributes from the input array:\n\n    - shape: array shape.\n    - dtype: underlying array data type.\n    - order: whether the array order is row-major (C-style) or column-major\n      (Fortran-style).\n\n    In browser environments, the function always returns zero-filled ndarrays.\n\n    If `dtype` is 'generic', the function always returns a zero-filled ndarray.\n\n    For returned ndarrays whose underlying memory is *not* initialized, memory\n    contents are unknown and may contain *sensitive* data.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    options: Object (optional)\n        Options.\n\n    options.shape: ArrayLikeObject<integer>|integer (optional)\n        Array shape. Overrides the input array's inferred shape.\n\n    options.dtype: string (optional)\n        Array data type. Overrides the input array's inferred data type.\n\n    options.order: string (optional)\n        Array order (either 'row-major' (C-style) or 'column-major' (Fortran-\n        style)). Overrides the input array's inferred order.\n\n    options.mode: string (optional)\n        Specifies how to handle indices which exceed array dimensions. If equal\n        to 'throw', an ndarray instance throws an error when an index exceeds\n        array dimensions. If equal to 'normalize', an ndarray instance\n        normalizes negative indices and throws an error when an index exceeds\n        array dimensions. If equal to 'wrap', an ndarray instance wraps around\n        indices exceeding array dimensions using modulo arithmetic. If equal to\n        'clamp', an ndarray instance sets an index exceeding array dimensions\n        to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n    options.submode: Array<string> (optional)\n        Specifies how to handle subscripts which exceed array dimensions. If a\n        mode for a corresponding dimension is equal to 'throw', an ndarray\n        instance throws an error when a subscript exceeds array dimensions. If\n        equal to 'normalize', an ndarray instance normalizes negative\n        subscripts and throws an error when a subscript exceeds array\n        dimensions. If equal to 'wrap', an ndarray instance wraps around\n        subscripts exceeding array dimensions using modulo arithmetic. If equal\n        to 'clamp', an ndarray instance sets a subscript exceeding array\n        dimensions to either `0` (minimum index) or the maximum index. If the\n        number of modes is fewer than the number of dimensions, the function\n        recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n    <ndarray>\n    > var sh = x.shape\n    [ 2, 2 ]\n    > var dt = x.dtype\n    'float64'\n    > var y = ndemptyLike( x )\n    <ndarray>\n    > sh = y.shape\n    [ 2, 2 ]\n    > dt = y.dtype\n    'float64'\n\n    See Also\n    --------\n    ndempty, ndzerosLike\n","ndfilter":"\nndfilter( x[, options], predicate[, thisArg] )\n    Returns a shallow copy of an ndarray containing only those elements which\n    pass a test implemented by a predicate function.\n\n    The predicate function is provided the following arguments:\n\n    - value: current array element.\n    - indices: current array element indices.\n    - arr: the input ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.dtype: string (optional)\n        Output ndarray data type. Overrides using the input array's inferred\n        data type.\n\n    options.order: string (optional)\n        Index iteration order. By default, the function iterates over elements\n        according to the layout order of the provided array. Accordingly, for\n        row-major input arrays, the last dimension indices increment fastest.\n        For column-major input arrays, the first dimension indices increment\n        fastest. To override the inferred order and ensure that indices\n        increment in a specific manner, regardless of the input array's layout\n        order, explicitly set the iteration order. Note, however, that iterating\n        according to an order which does not match that of the input array may,\n        in some circumstances, result in performance degradation due to cache\n        misses. Must be either 'row-major' or 'column-major'.\n\n    predicate: Function\n        Predicate function.\n\n    thisArg: any (optional)\n        Predicate function execution context.\n\n    Examples\n    --------\n    > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n    > function f( v ) { return v > 2.0; };\n    > var y = ndfilter( x, f );\n    > ndarray2array( y )\n    [ 3.0, 4.0 ]\n\n    See Also\n    --------\n    ndfilterMap, ndmap, ndreject, ndslice","ndfilterMap":"\nndfilterMap( x[, options], fcn[, thisArg] )\n    Filters and maps elements in an input ndarray to elements in a new output\n    ndarray according to a callback function.\n\n    The callback function is provided the following arguments:\n\n    - value: current array element.\n    - indices: current array element indices.\n    - arr: the input ndarray.\n\n    If a provided callback function returns `undefined`, the function skips the\n    respective ndarray element. If the callback function returns a value other\n    than `undefined`, the function stores the callback's return value in the\n    output ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.dtype: string (optional)\n        Output ndarray data type. Overrides using the input array's inferred\n        data type.\n\n    options.order: string (optional)\n        Index iteration order. By default, the function iterates over elements\n        according to the layout order of the provided array. Accordingly, for\n        row-major input arrays, the last dimension indices increment fastest.\n        For column-major input arrays, the first dimension indices increment\n        fastest. To override the inferred order and ensure that indices\n        increment in a specific manner, regardless of the input array's layout\n        order, explicitly set the iteration order. Note, however, that iterating\n        according to an order which does not match that of the input array may,\n        in some circumstances, result in performance degradation due to cache\n        misses. Must be either 'row-major' or 'column-major'.\n\n    fcn: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback function execution context.\n\n    Examples\n    --------\n    > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n    > function f( v ) { if ( v > 2.0 ) { return v * 10.0; } };\n    > var y = ndfilterMap( x, f );\n    > ndarray2array( y )\n    [ 30.0, 40.0 ]\n\n    See Also\n    --------\n    ndfilter, ndmap, ndreject, ndslice","ndforEach":"\nndforEach( x, fcn[, thisArg] )\n    Invokes a callback function once for each ndarray element.\n\n    The callback function is provided the following arguments:\n\n    - value: current array element.\n    - indices: current array element indices.\n    - arr: the input ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    fcn: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback function execution context.\n\n    Examples\n    --------\n    > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n    > function f( v ) { if ( v !== v ) { throw new Error( '...' ); } };\n    > ndforEach( x, f );\n\n    See Also\n    --------\n    ndmap","ndims":"\nndims( x )\n    Returns the number of ndarray dimensions.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    Returns\n    -------\n    n: integer\n        Number of dimensions.\n\n    Examples\n    --------\n    > var n = ndims( ndzeros( [ 3, 3, 3 ] ) )\n    3\n\n    See Also\n    --------\n    array, ndarray, numel, ndarrayShape\n","ndindex":"\nndindex( x[, options] )\n    Wraps a provided array as an ndarray index object.\n\n    ndarray index instances have no explicit functionality; however, they are\n    used by \"fancy\" ndarrays for element retrieval and assignment.\n\n    By default, an instance is invalidated and removed from an internal cache\n    immediately after a consumer resolves the underlying data associated with an\n    instance using the `get` static method. Immediate invalidation and cache\n    removal ensures that references to the underlying ndarray are not the source\n    of memory leaks.\n\n    Because instances leverage an internal cache implementing the Singleton\n    pattern, one must be sure to use the same constructor as consumers. If one\n    uses a different constructor, the consumer will *not* be able to resolve the\n    original wrapped ndarray, as the consumer will attempt to resolve an\n    instance in the wrong internal cache.\n\n    Because non-persisted instances are freed after first use, in order to avoid\n    holding onto memory and to allow garbage collection, one should avoid\n    scenarios in which an instance is never used.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.persist: boolean (optional)\n        Boolean indicating whether to continue persisting an index object after\n        first usage. Default: false.\n\n    options.kind: string (optional)\n        Specifies whether a provided ndarray is a specialized input ndarray\n        \"kind\". This option is only applicable for integer input ndarrays. Must\n        be one of the following:\n\n        - cartesian: a provided input ndarray contains Cartesian indices.\n        - linear: a provided input ndarray contains indices representing\n          locations in linear memory.\n\n        Default: ''.\n\n    Returns\n    -------\n    out: ndindex\n        Index instance.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n\n\nndindex.free( id )\n    Frees the instance associated with a provided identifier.\n\n    Parameters\n    ----------\n    id: string\n        Instance identifier.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an instance was successfully freed.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > ndindex.free( idx.id )\n    <boolean>\n\n\nndindex.get( id )\n    Returns the ndarray associated with the instance having a provided\n    identifier.\n\n    Parameters\n    ----------\n    id: string\n        Instance identifier.\n\n    Returns\n    -------\n    out: Object\n        Object containing ndarray data.\n\n    out.data: ndarray\n        The underlying ndarray associated with the provided identifier.\n\n    out.type: string\n        The type of ndarray index.\n\n    out.dtype: string\n        The data type of the underlying ndarray.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > ndindex.get( idx.id )\n    {...}\n\n\nndindex.cartesianIndex( x[, options] )\n    Returns an ndarray index containing Cartesian indices.\n\n    This is a convenience method for calling `ndindex` with `kind` set to\n    'cartesian'.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.persist: boolean (optional)\n        Boolean indicating whether to continue persisting an index object after\n        first usage. Default: false.\n\n    Returns\n    -------\n    out: ndindex\n        Index instance.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = ndindex.cartesianIndex( x );\n\n\nndindex.linearIndex( x[, options] )\n    Returns an ndarray index for indices representing locations in linear\n    memory.\n\n    This is a convenience method for calling `ndindex` with `kind` set to\n    'linear'.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.persist: boolean (optional)\n        Boolean indicating whether to continue persisting an index object after\n        first usage. Default: false.\n\n    Returns\n    -------\n    out: ndindex\n        Index instance.\n\n    Examples\n    --------\n    > var x = ndempty( [ 5 ], { 'dtype': 'int32' } );\n    > var idx = ndindex.linearIndex( x );\n\n\nndindex.prototype.data\n    Read-only property returning an ndarray view of the underlying index\n    ndarray.\n\n    Returns\n    -------\n    out: ndarray\n        Array data.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.data\n    <ndarray>\n\n\nndindex.prototype.dtype\n    Read-only property returning the underlying data type of the index ndarray.\n\n    Returns\n    -------\n    out: string\n        Array data type.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.dtype\n    'int32'\n\n\nndindex.prototype.id\n    Read-only property returning the unique identifier associated with an\n    instance.\n\n    Returns\n    -------\n    out: string\n        String identifier.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.id\n    <string>\n\n\nndindex.prototype.isCached\n    Read-only property returning a boolean indicating whether an ndarray index\n    is actively cached.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an ndarray index is actively cached.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.isCached\n    true\n\n\nndindex.prototype.kind\n    Read-only property returning the ndarray index kind.\n\n    Returns\n    -------\n    out: string\n        Index kind.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x, { 'kind': 'cartesian' } );\n    > idx.kind\n    'cartesian'\n\n\nndindex.prototype.type\n    Read-only property returning the ndarray index type.\n\n    Returns\n    -------\n    out: string\n        Index type.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.type\n    <string>\n\n\nndindex.prototype.toString()\n    Serializes an instance as a string.\n\n    Returns\n    -------\n    str: string\n        Serialized string.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.toString()\n    <string>\n\n\nndindex.prototype.toJSON()\n    Serializes an instance as a JSON object.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.toJSON()\n    { 'type': 'ndindex', ... }\n\n    See Also\n    --------\n    array, ndarray, FancyArray, ndslice, ndarray2fancy\n","ndindex.free":"\nndindex.free( id )\n    Frees the instance associated with a provided identifier.\n\n    Parameters\n    ----------\n    id: string\n        Instance identifier.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an instance was successfully freed.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > ndindex.free( idx.id )\n    <boolean>","ndindex.get":"\nndindex.get( id )\n    Returns the ndarray associated with the instance having a provided\n    identifier.\n\n    Parameters\n    ----------\n    id: string\n        Instance identifier.\n\n    Returns\n    -------\n    out: Object\n        Object containing ndarray data.\n\n    out.data: ndarray\n        The underlying ndarray associated with the provided identifier.\n\n    out.type: string\n        The type of ndarray index.\n\n    out.dtype: string\n        The data type of the underlying ndarray.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > ndindex.get( idx.id )\n    {...}","ndindex.cartesianIndex":"\nndindex.cartesianIndex( x[, options] )\n    Returns an ndarray index containing Cartesian indices.\n\n    This is a convenience method for calling `ndindex` with `kind` set to\n    'cartesian'.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.persist: boolean (optional)\n        Boolean indicating whether to continue persisting an index object after\n        first usage. Default: false.\n\n    Returns\n    -------\n    out: ndindex\n        Index instance.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = ndindex.cartesianIndex( x );","ndindex.linearIndex":"\nndindex.linearIndex( x[, options] )\n    Returns an ndarray index for indices representing locations in linear\n    memory.\n\n    This is a convenience method for calling `ndindex` with `kind` set to\n    'linear'.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.persist: boolean (optional)\n        Boolean indicating whether to continue persisting an index object after\n        first usage. Default: false.\n\n    Returns\n    -------\n    out: ndindex\n        Index instance.\n\n    Examples\n    --------\n    > var x = ndempty( [ 5 ], { 'dtype': 'int32' } );\n    > var idx = ndindex.linearIndex( x );","ndindex.prototype.data":"\nndindex.prototype.data\n    Read-only property returning an ndarray view of the underlying index\n    ndarray.\n\n    Returns\n    -------\n    out: ndarray\n        Array data.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.data\n    <ndarray>","ndindex.prototype.dtype":"\nndindex.prototype.dtype\n    Read-only property returning the underlying data type of the index ndarray.\n\n    Returns\n    -------\n    out: string\n        Array data type.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.dtype\n    'int32'","ndindex.prototype.id":"\nndindex.prototype.id\n    Read-only property returning the unique identifier associated with an\n    instance.\n\n    Returns\n    -------\n    out: string\n        String identifier.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.id\n    <string>","ndindex.prototype.isCached":"\nndindex.prototype.isCached\n    Read-only property returning a boolean indicating whether an ndarray index\n    is actively cached.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an ndarray index is actively cached.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.isCached\n    true","ndindex.prototype.kind":"\nndindex.prototype.kind\n    Read-only property returning the ndarray index kind.\n\n    Returns\n    -------\n    out: string\n        Index kind.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x, { 'kind': 'cartesian' } );\n    > idx.kind\n    'cartesian'","ndindex.prototype.type":"\nndindex.prototype.type\n    Read-only property returning the ndarray index type.\n\n    Returns\n    -------\n    out: string\n        Index type.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.type\n    <string>","ndindex.prototype.toString":"\nndindex.prototype.toString()\n    Serializes an instance as a string.\n\n    Returns\n    -------\n    str: string\n        Serialized string.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.toString()\n    <string>","ndindex.prototype.toJSON":"\nndindex.prototype.toJSON()\n    Serializes an instance as a JSON object.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.toJSON()\n    { 'type': 'ndindex', ... }\n\n    See Also\n    --------\n    array, ndarray, FancyArray, ndslice, ndarray2fancy","nditerColumnEntries":"\nnditerColumnEntries( x[, options] )\n    Returns an iterator which returns [index, column] pairs for each column in a\n    matrix (or stack of matrices).\n\n    Each returned index is a Cartesian index (i.e., an array of subscripts/\n    dimension indices). A dimension index equal to `null` indicates that all\n    values along the respective dimension are included in the returned ndarray.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    options: Object (optional)\n        Options.\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether returned ndarray views should be read-only.\n        If the input ndarray is read-only, setting this option to `false` raises\n        an exception. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > var it = nditerColumnEntries( x );\n    > var v = it.next().value;\n    > v[ 0 ]\n    [ null, 0 ]\n    > ndarray2array( v[ 1 ] )\n    [ 1, 3 ]\n    > v = it.next().value;\n    > v[ 0 ]\n    [ null, 1 ]\n    > ndarray2array( v[ 1 ] )\n    [ 2, 4 ]\n\n    See Also\n    --------\n    nditerColumns, nditerEntries, nditerRowEntries, ndslice\n","nditerColumns":"\nnditerColumns( x[, options] )\n    Returns an iterator which iterates over each column in a matrix (or stack of\n    matrices).\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray for which to create the iterator.\n\n    options: Object (optional)\n        Options.\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether returned ndarray views should be read-only.\n        If the input ndarray is read-only, setting this option to `false` raises\n        an exception. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > var it = nditerColumns( x );\n    > var v = it.next().value;\n    > ndarray2array( v )\n    [ 1, 3 ]\n    > v = it.next().value;\n    > ndarray2array( v )\n    [ 2, 4 ]\n\n    See Also\n    --------\n    nditerColumnEntries, nditerRows, ndslice\n","nditerEntries":"\nnditerEntries( x[, options] )\n    Returns an iterator which returns [index, value] pairs for each element in a\n    provided ndarray.\n\n    Each returned index is a Cartesian index (i.e., an array of subscripts/\n    dimension indices).\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    options: Object (optional)\n        Options.\n\n    options.order: string (optional)\n        Index iteration order. By default, the returned iterator returns values\n        according to the layout order of the provided array. Accordingly, for\n        row-major input arrays, the last dimension indices increment fastest.\n        For column-major input arrays, the first dimension indices increment\n        fastest. To override the inferred order and ensure that indices\n        increment in a specific manner, regardless of the input array's layout\n        order, explicitly set the iteration order. Note, however, that iterating\n        according to an order which does not match that of the input array may,\n        in some circumstances, result in performance degradation due to cache\n        misses. Must be either 'row-major' or 'column-major'.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > var it = nditerEntries( x );\n    > var v = it.next().value\n    [ [ 0, 0 ], 1 ]\n    > v = it.next().value\n    [ [ 0, 1 ], 2 ]\n\n    See Also\n    --------\n    ndarray, nditerIndices, nditerValues\n","nditerIndices":"\nnditerIndices( shape[, options] )\n    Returns an iterator which returns indices for use indexing into an ndarray\n    having a specified shape.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Input shape.\n\n    options: Object (optional)\n        Options.\n\n    options.order: string (optional)\n        Index iteration order. By default, the returned iterator iterates over\n        the last dimensions first, thus corresponding to iteration over\n        contiguous data stored in row-major order. Must be either 'row-major'\n        or 'column-major'.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > var it = nditerIndices( x.shape );\n    > var v = it.next().value\n    [ 0, 0 ]\n    > v = it.next().value\n    [ 0, 1 ]\n\n    See Also\n    --------\n    ndarray, nditerEntries, nditerValues\n","nditerInterleaveSubarrays":"\nnditerInterleaveSubarrays( arr, ndims )\n    Returns an iterator which iterates over interleaved subarrays.\n\n    For input ndarrays supporting read-only views, the function returns\n    *read-only* views of interleaved subarrays. As input ndarrays may be\n    broadcasted, a view is typically *not* contiguous. As more than one element\n    of a returned view may refer to the same memory location, writing to a view\n    may affect multiple elements. If you need to write to a subarray, copy the\n    subarray before attempting mutation.\n\n    The function throws an error if a provided broadcast-incompatible ndarrays.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    arr: ArrayLike<ndarray>\n        Input ndarrays. All ndarrays must be broadcast-compatible. After\n        broadcasting, each broadcasted input ndarray must have at least\n        `ndims+1` dimensions.\n\n    ndims: integer\n        Number of dimensions to stack after broadcasting.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n    > var it = nditerInterleaveSubarrays( [ x, x ], 2 );\n    > var v = it.next().value;\n    > ndarray2array( v )\n    [ [ 1, 2 ], [ 3, 4 ] ]\n\n    See Also\n    --------\n    nditerSubarrays, ndslice\n","nditerMatrices":"\nnditerMatrices( x[, options] )\n    Returns an iterator which iterates over each matrix in a stack of matrices.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray for which to create the iterator.\n\n    options: Object (optional)\n        Options.\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether returned ndarray views should be read-only.\n        If the input ndarray is read-only, setting this option to `false` raises\n        an exception. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n    > var it = nditerMatrices( x );\n    > var v = it.next().value;\n    > ndarray2array( v )\n    [ [ 1, 2 ], [ 3, 4 ] ]\n\n    See Also\n    --------\n    nditerColumns, nditerMatrixEntries, nditerRows, ndslice\n","nditerMatrixEntries":"\nnditerMatrixEntries( x[, options] )\n    Returns an iterator which returns [index, matrix] pairs for each matrix in a\n    stack of matrices.\n\n    Each returned index is a Cartesian index (i.e., an array of subscripts/\n    dimension indices). A dimension index equal to `null` indicates that all\n    values along the respective dimension are included in the returned ndarray.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    options: Object (optional)\n        Options.\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether returned ndarray views should be read-only.\n        If the input ndarray is read-only, setting this option to `false` raises\n        an exception. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n    > var it = nditerMatrixEntries( x );\n    > var v = it.next().value;\n    > v[ 0 ]\n    [ 0, null, null ]\n    > ndarray2array( v[ 1 ] )\n    [ [ 1, 2 ], [ 3, 4 ] ]\n\n    See Also\n    --------\n    nditerColumnEntries, nditerEntries, nditerMatrices, nditerRowEntries, ndslice\n","nditerRowEntries":"\nnditerRowEntries( x[, options] )\n    Returns an iterator which returns [index, row] pairs for each row in a\n    matrix (or stack of matrices).\n\n    Each returned index is a Cartesian index (i.e., an array of subscripts/\n    dimension indices). A dimension index equal to `null` indicates that all\n    values along the respective dimension are included in the returned ndarray.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    options: Object (optional)\n        Options.\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether returned ndarray views should be read-only.\n        If the input ndarray is read-only, setting this option to `false` raises\n        an exception. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > var it = nditerRowEntries( x );\n    > var v = it.next().value;\n    > v[ 0 ]\n    [ 0, null ]\n    > ndarray2array( v[ 1 ] )\n    [ 1, 2 ]\n    > v = it.next().value;\n    > v[ 0 ]\n    [ 1, null ]\n    > ndarray2array( v[ 1 ] )\n    [ 3, 4 ]\n\n    See Also\n    --------\n    nditerColumnEntries, nditerEntries, nditerRows, ndslice\n","nditerRows":"\nnditerRows( x[, options] )\n    Returns an iterator which iterates over each row in a matrix (or stack of\n    matrices).\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray for which to create the iterator.\n\n    options: Object (optional)\n        Options.\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether returned ndarray views should be read-only.\n        If the input ndarray is read-only, setting this option to `false` raises\n        an exception. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > var it = nditerRows( x );\n    > var v = it.next().value;\n    > ndarray2array( v )\n    [ 1, 2 ]\n    > v = it.next().value;\n    > ndarray2array( v )\n    [ 3, 4 ]\n\n    See Also\n    --------\n    nditerColumns, nditerRowEntries, ndslice\n","nditerSelectDimension":"\nnditerSelectDimension( x, dim[, options] )\n    Returns an iterator which iterates over each view along a specified\n    dimension.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray for which to create the iterator.\n\n    dim: integer\n        Dimension index. If less than zero, the index is resolved relative to\n        the last dimension, with the last dimension corresponding to the value\n        `-1`.\n\n    options: Object (optional)\n        Options.\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether returned ndarray views should be read-only.\n        If the input ndarray is read-only, setting this option to `false` raises\n        an exception. Default: true.\n\n    options.keepdim: boolean (optional)\n        Boolean indicating whether returned views should include the selected\n        dimension as a singleton dimension. Including the selected dimension as\n        a singleton dimension can be useful when wanting to ensure that returned\n        views remain broadcast compatible with the input ndarray. Default:\n        false.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n    > var it = nditerSelectDimension( x, 0 );\n    > var v = it.next().value;\n    > ndarray2array( v )\n    [ [ 1, 2 ], [ 3, 4 ] ]\n\n    See Also\n    --------\n    nditerColumns, nditerMatrices, nditerRows, ndslice\n","nditerStacks":"\nnditerStacks( x, dims[, options] )\n    Returns an iterator which iterates over each subarray in a stack of\n    subarrays according to a list of specified stack dimensions.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray for which to create the iterator. Must have at least\n        `dims.length+1` dimensions.\n\n    dims: Array<integer>\n        Indices of dimensions to stack. If a dimension index is less than zero,\n        the index is resolved relative to the last dimension, with the last\n        dimension corresponding to the value `-1`. The list of indices must be\n        unique and resolve to dimension indices sorted in ascending order.\n\n    options: Object (optional)\n        Options.\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether returned ndarray views should be read-only.\n        If the input ndarray is read-only, setting this option to `false` raises\n        an exception. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n    > var it = nditerStacks( x, [ 1, 2 ] );\n    > var v = it.next().value;\n    > ndarray2array( v )\n    [ [ 1, 2 ], [ 3, 4 ] ]\n\n    See Also\n    --------\n    nditerColumns, nditerMatrices, nditerRows, nditerSubarrays, ndslice\n","nditerSubarrays":"\nnditerSubarrays( x, ndims[, options] )\n    Returns an iterator which iterates over each subarray in a stack of\n    subarrays.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray for which to create the iterator. Must have at least\n        `ndims+1` dimensions.\n\n    ndims: integer\n        Number of dimensions to stack.\n\n    options: Object (optional)\n        Options.\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether returned ndarray views should be read-only.\n        If the input ndarray is read-only, setting this option to `false` raises\n        an exception. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n    > var it = nditerSubarrays( x, 2 );\n    > var v = it.next().value;\n    > ndarray2array( v )\n    [ [ 1, 2 ], [ 3, 4 ] ]\n\n    See Also\n    --------\n    nditerColumns, nditerMatrices, nditerRows, nditerStacks, ndslice\n","nditerValues":"\nnditerValues( x[, options] )\n    Returns an iterator which returns individual elements from a provided\n    ndarray.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    options: Object (optional)\n        Options.\n\n    options.order: string (optional)\n        Index iteration order. By default, the returned iterator returns values\n        according to the layout order of the provided array. Accordingly, for\n        row-major input arrays, the last dimension indices increment fastest.\n        For column-major input arrays, the first dimension indices increment\n        fastest. To override the inferred order and ensure that indices\n        increment in a specific manner, regardless of the input array's layout\n        order, explicitly set the iteration order. Note, however, that iterating\n        according to an order which does not match that of the input array may,\n        in some circumstances, result in performance degradation due to cache\n        misses. Must be either 'row-major' or 'column-major'.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > var it = nditerValues( x );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    ndarray, nditerEntries, nditerIndices\n","ndmap":"\nndmap( x[, options], fcn[, thisArg] )\n    Applies a callback function to elements in an input ndarray and assigns\n    results to elements in a new output ndarray.\n\n    The callback function is provided the following arguments:\n\n    - value: current array element.\n    - indices: current array element indices.\n    - arr: the input ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.dtype: string (optional)\n        Output ndarray data type. Overrides using the input array's inferred\n        data type.\n\n    fcn: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback function execution context.\n\n    Examples\n    --------\n    > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n    > function f( v ) { return v*10.0; };\n    > var y = ndmap( x, f );\n    > ndarray2array( y )\n    [ [ 10.0, 20.0 ], [ 30.0, 40.0 ] ]\n\n    See Also\n    --------\n    ndfilter, ndfilterMap, ndforEach, ndslice","ndreject":"\nndreject( x[, options], predicate[, thisArg] )\n    Returns a shallow copy of an ndarray containing only those elements which\n    fail a test implemented by a predicate function.\n\n    The predicate function is provided the following arguments:\n\n    - value: current array element.\n    - indices: current array element indices.\n    - arr: the input ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.dtype: string (optional)\n        Output ndarray data type. Overrides using the input array's inferred\n        data type.\n\n    options.order: string (optional)\n        Index iteration order. By default, the function iterates over elements\n        according to the layout order of the provided array. Accordingly, for\n        row-major input arrays, the last dimension indices increment fastest.\n        For column-major input arrays, the first dimension indices increment\n        fastest. To override the inferred order and ensure that indices\n        increment in a specific manner, regardless of the input array's layout\n        order, explicitly set the iteration order. Note, however, that iterating\n        according to an order which does not match that of the input array may,\n        in some circumstances, result in performance degradation due to cache\n        misses. Must be either 'row-major' or 'column-major'.\n\n    predicate: Function\n        Predicate function.\n\n    thisArg: any (optional)\n        Predicate function execution context.\n\n    Examples\n    --------\n    > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n    > function f( v ) { return v <= 2.0; };\n    > var y = ndreject( x, f );\n    > ndarray2array( y )\n    [ 3.0, 4.0 ]\n\n    See Also\n    --------\n    ndfilter, ndfilterMap, ndmap, ndslice","ndslice":"\nndslice( x, ...s[, options] )\n    Returns a read-only view of an input ndarray.\n\n    The function supports three (mutually exclusive) means of providing slice\n    arguments:\n\n    1. Providing a single MultiSlice object.\n    2. Providing a single array containing slice arguments.\n    3. Providing slice arguments as separate arguments.\n\n    An individual slice argument must be either a Slice, an integer, null, or\n    undefined.\n\n    In all cases, the number of slice dimensions must match the number of array\n    dimensions.\n\n    If providing a MultiSlice object or an array of slice arguments, no other\n    slice arguments should be provided.\n\n    Mixing function invocation styles (e.g., providing multiple MultiSlice\n    objects or providing an array of slice arguments followed by additional\n    slice arguments) is not supported.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    s: ...MultiSlice|Slice|null|undefined|integer|ArrayLike\n        Slice arguments.\n\n    options: Object (optional)\n        Options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking.\n        Default: true.\n\n    Returns\n    -------\n    out: ndarray\n        Output array view.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n    <ndarray>\n    > x.shape\n    [ 2, 2 ]\n    > var s = new MultiSlice( null, 1 )\n    <MultiSlice>\n    > var y = ndslice( x, s )\n    <ndarray>\n    > y.shape\n    [ 2 ]\n    > ndarray2array( y )\n    [ 2, 4 ]\n\n    See Also\n    --------\n    array, ndat, ndarray, ndsliceAssign, ndsliceDimension\n","ndsliceAssign":"\nndsliceAssign( x, y, ...s[, options] )\n    Assigns element values from a broadcasted input ndarray to corresponding\n    elements in an output ndarray view.\n\n    The function supports three (mutually exclusive) means of providing slice\n    arguments:\n\n    1. Providing a single MultiSlice object.\n    2. Providing a single array containing slice arguments.\n    3. Providing slice arguments as separate arguments.\n\n    An individual slice argument must be either a Slice, an integer, null, or\n    undefined.\n\n    In all cases, the number of slice dimensions must match the number of output\n    array dimensions.\n\n    If providing a MultiSlice object or an array of slice arguments, no other\n    slice arguments should be provided.\n\n    Mixing function invocation styles (e.g., providing multiple MultiSlice\n    objects or providing an array of slice arguments followed by additional\n    slice arguments) is not supported.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array. The input array must be broadcast compatible with the\n        output array view and must have a data type which can be safely cast to\n        the output array data type. Floating-point data types (both real and\n        complex) are allowed to downcast to a lower precision data type of the\n        same kind (e.g., element values from a 'float64' input array can be\n        assigned to corresponding elements in a 'float32' output array).\n\n    y: ndarray\n        Output array. The output array must be writable.\n\n    s: ...MultiSlice|Slice|null|undefined|integer|ArrayLike\n        Slice arguments.\n\n    options: Object (optional)\n        Options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking.\n        Default: true.\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var y = ndzeros( [ 2, 2 ] )\n    <ndarray>\n    > var x = scalar2ndarray( 3.0 )\n    <ndarray>\n    > var s = new MultiSlice( null, 1 )\n    <MultiSlice>\n    > var out = ndsliceAssign( x, y, s )\n    <ndarray>\n    > var bool = ( out === y )\n    true\n    > ndarray2array( y )\n    [ [ 0.0, 3.0 ], [ 0.0, 3.0 ] ]\n\n    See Also\n    --------\n    array, ndarray, ndslice\n","ndsliceDimension":"\nndsliceDimension( x, dim, slice[, options] )\n    Returns a read-only view of an input ndarray when sliced along a specified\n    dimension.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    dim: integer\n        Index of dimension to slice. If less than zero, the index is resolved\n        relative to the last dimension, with the last dimension corresponding to\n        the value `-1`.\n\n    slice: Slice|integer|null|undefined\n        Slice object or an integer. If provided `null` or `undefined`, the\n        returned view includes all elements along a specified dimension. If\n        provided an integer less than zero, the corresponding element along the\n        specified dimension is resolved relative to the last element along that\n        dimension. For negative integers, the last element corresponds to the\n        value `-1`.\n\n    options: Object (optional)\n        Options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking.\n        Default: true.\n\n    Returns\n    -------\n    out: ndarray\n        Output array view.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n    <ndarray>\n    > x.shape\n    [ 2, 2 ]\n    > var y = ndsliceDimension( x, 1, 1 )\n    <ndarray>\n    > y.shape\n    [ 2 ]\n    > ndarray2array( y )\n    [ 2, 4 ]\n\n    See Also\n    --------\n    array, ndarray, ndslice, ndsliceDimensionFrom, ndsliceDimensionTo\n","ndsliceDimensionFrom":"\nndsliceDimensionFrom( x, dim, start[, options] )\n    Returns a read-only shifted view of an input ndarray along a specified\n    dimension.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    dim: integer\n        Index of dimension to slice. If less than zero, the index is resolved\n        relative to the last dimension, with the last dimension corresponding to\n        the value `-1`.\n\n    start: integer\n        Starting index (inclusive). If less than zero, the corresponding element\n        along the specified dimension is resolved relative to the last element\n        along that dimension. For negative integers, the last element\n        corresponds to the value `-1`.\n\n    options: Object (optional)\n        Options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking.\n        Default: true.\n\n    Returns\n    -------\n    out: ndarray\n        Output array view.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n    <ndarray>\n    > x.shape\n    [ 2, 2 ]\n    > var y = ndsliceDimensionFrom( x, 1, 1 )\n    <ndarray>\n    > y.shape\n    [ 2, 1 ]\n    > ndarray2array( y )\n    [ [ 2 ], [ 4 ] ]\n\n    See Also\n    --------\n    array, ndarray, ndslice, ndsliceDimension, ndsliceDimensionTo, ndsliceFrom\n","ndsliceDimensionTo":"\nndsliceDimensionTo( x, dim, stop[, options] )\n    Returns a read-only truncated view of an input ndarray along a specified\n    dimension.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    dim: integer\n        Index of dimension to slice. If less than zero, the index is resolved\n        relative to the last dimension, with the last dimension corresponding to\n        the value `-1`.\n\n    stop: integer\n        Ending index (exclusive). If less than zero, the corresponding element\n        along the specified dimension is resolved relative to the last element\n        along that dimension. For negative integers, the last element\n        corresponds to the value `-1`.\n\n    options: Object (optional)\n        Options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking.\n        Default: true.\n\n    Returns\n    -------\n    out: ndarray\n        Output array view.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n    <ndarray>\n    > x.shape\n    [ 2, 2 ]\n    > var y = ndsliceDimensionTo( x, 1, 1 )\n    <ndarray>\n    > y.shape\n    [ 2, 1 ]\n    > ndarray2array( y )\n    [ [ 1 ], [ 3 ] ]\n\n    See Also\n    --------\n    array, ndarray, ndslice, ndsliceDimension, ndsliceDimensionFrom, ndsliceTo\n","ndsliceFrom":"\nndsliceFrom( x, ...start[, options] )\n    Returns a read-only shifted view of an input ndarray.\n\n    The function supports two (mutually exclusive) means of providing starting\n    indices:\n\n    1. Providing a single array containing start arguments.\n    2. Providing start arguments as separate arguments.\n\n    An individual start argument must be either an integer, null, or undefined.\n\n    In all cases, the number of start indices must match the number of array\n    dimensions.\n\n    If providing an array of start arguments, no other start arguments should be\n    provided.\n\n    Mixing function invocation styles (e.g., providing an array of start\n    arguments followed by additional start arguments) is not supported.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    start: ...null|void|integer\n        Starting indices (inclusive). If an element is either `null` or\n        `undefined`, the function returns a view containing all elements along\n        that dimension. A negative integer indicates to resolve a starting index\n        relative to the last element along a corresponding dimension, with the\n        last element having index `-1`.\n\n    options: Object (optional)\n        Options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking.\n        Default: true.\n\n    Returns\n    -------\n    out: ndarray\n        Output array view.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n    <ndarray>\n    > x.shape\n    [ 2, 2 ]\n    > var y = ndsliceFrom( x, 0, 1 )\n    <ndarray>\n    > y.shape\n    [ 2, 1 ]\n    > ndarray2array( y )\n    [ [ 2 ], [ 4 ] ]\n\n    See Also\n    --------\n    array, ndarray, ndslice, ndsliceDimensionFrom, ndsliceTo\n","ndsliceTo":"\nndsliceTo( x, ...stop[, options] )\n    Returns a read-only truncated view of an input ndarray.\n\n    The function supports two (mutually exclusive) means of providing ending\n    indices:\n\n    1. Providing a single array containing stop arguments.\n    2. Providing stop arguments as separate arguments.\n\n    An individual stop argument must be either an integer, null, or undefined.\n\n    In all cases, the number of stop indices must match the number of array\n    dimensions.\n\n    If providing an array of stop arguments, no other stop arguments should be\n    provided.\n\n    Mixing function invocation styles (e.g., providing an array of stop\n    arguments followed by additional stop arguments) is not supported.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    stop: ...null|void|integer\n        Ending indices (exclusive). If an ending index is either `null` or\n        `undefined`, the function returns a view containing all elements along\n        that dimension. A negative integer indicates to resolve an ending index\n        relative to the last element along a corresponding dimension, with the\n        last element having index `-1`.\n\n    options: Object (optional)\n        Options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking.\n        Default: true.\n\n    Returns\n    -------\n    out: ndarray\n        Output array view.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n    <ndarray>\n    > x.shape\n    [ 2, 2 ]\n    > var y = ndsliceTo( x, 1, 1 )\n    <ndarray>\n    > y.shape\n    [ 1, 1 ]\n    > ndarray2array( y )\n    [ [ 1 ] ]\n\n    See Also\n    --------\n    array, ndarray, ndslice, ndsliceDimensionTo, ndsliceFrom\n","ndzeros":"\nndzeros( shape[, options] )\n    Returns a zero-filled ndarray having a specified shape and data type.\n\n    Parameters\n    ----------\n    shape: ArrayLikeObject<integer>|integer\n        Array shape.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Underlying data type. Must be a numeric data type or \"generic\". Default:\n        'float64'.\n\n    options.order: string (optional)\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran-style). Default: 'row-major'.\n\n    options.mode: string (optional)\n        Specifies how to handle indices which exceed array dimensions. If equal\n        to 'throw', an ndarray instance throws an error when an index exceeds\n        array dimensions. If equal to 'normalize', an ndarray instance\n        normalizes negative indices and throws an error when an index exceeds\n        array dimensions. If equal to 'wrap', an ndarray instance wraps around\n        indices exceeding array dimensions using modulo arithmetic. If equal to\n        'clamp', an ndarray instance sets an index exceeding array dimensions\n        to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n    options.submode: Array<string> (optional)\n        Specifies how to handle subscripts which exceed array dimensions. If a\n        mode for a corresponding dimension is equal to 'throw', an ndarray\n        instance throws an error when a subscript exceeds array dimensions. If\n        equal to 'normalize', an ndarray instance normalizes negative\n        subscripts and throws an error when a subscript exceeds array\n        dimensions. If equal to 'wrap', an ndarray instance wraps around\n        subscripts exceeding array dimensions using modulo arithmetic. If equal\n        to 'clamp', an ndarray instance sets a subscript exceeding array\n        dimensions to either `0` (minimum index) or the maximum index. If the\n        number of modes is fewer than the number of dimensions, the function\n        recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether an array should be read-only. Default: false.\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var arr = ndzeros( [ 2, 2 ] )\n    <ndarray>\n    > var sh = arr.shape\n    [ 2, 2 ]\n    > var dt = arr.dtype\n    'float64'\n\n    See Also\n    --------\n    ndempty, ndzerosLike\n","ndzerosLike":"\nndzerosLike( x[, options] )\n    Returns a zero-filled ndarray having the same shape and data type as a\n    provided input ndarray.\n\n    The function infers the following attributes from the input array:\n\n    - shape: array shape.\n    - dtype: underlying array data type.\n    - order: whether the array order is row-major (C-style) or column-major\n      (Fortran-style).\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    options: Object (optional)\n        Options.\n\n    options.shape: ArrayLikeObject<integer>|integer (optional)\n        Array shape. Overrides the input array's inferred shape.\n\n    options.dtype: string (optional)\n        Array data type. Overrides the input array's inferred data type.\n\n    options.order: string (optional)\n        Array order (either 'row-major' (C-style) or 'column-major' (Fortran-\n        style)). Overrides the input array's inferred order.\n\n    options.mode: string (optional)\n        Specifies how to handle indices which exceed array dimensions. If equal\n        to 'throw', an ndarray instance throws an error when an index exceeds\n        array dimensions. If equal to 'normalize', an ndarray instance\n        normalizes negative indices and throws an error when an index exceeds\n        array dimensions. If equal to 'wrap', an ndarray instance wraps around\n        indices exceeding array dimensions using modulo arithmetic. If equal to\n        'clamp', an ndarray instance sets an index exceeding array dimensions\n        to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n    options.submode: Array<string> (optional)\n        Specifies how to handle subscripts which exceed array dimensions. If a\n        mode for a corresponding dimension is equal to 'throw', an ndarray\n        instance throws an error when a subscript exceeds array dimensions. If\n        equal to 'normalize', an ndarray instance normalizes negative\n        subscripts and throws an error when a subscript exceeds array\n        dimensions. If equal to 'wrap', an ndarray instance wraps around\n        subscripts exceeding array dimensions using modulo arithmetic. If equal\n        to 'clamp', an ndarray instance sets a subscript exceeding array\n        dimensions to either `0` (minimum index) or the maximum index. If the\n        number of modes is fewer than the number of dimensions, the function\n        recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether an array should be read-only. Default: false.\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n    <ndarray>\n    > var sh = x.shape\n    [ 2, 2 ]\n    > var dt = x.dtype\n    'float64'\n    > var y = ndzerosLike( x )\n    <ndarray>\n    > sh = y.shape\n    [ 2, 2 ]\n    > dt = y.dtype\n    'float64'\n\n    See Also\n    --------\n    ndemptyLike, ndzeros\n","nextGraphemeClusterBreak":"\nnextGraphemeClusterBreak( str[, fromIndex] )\n    Returns the next extended grapheme cluster break in a string after a\n    specified position.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    fromIndex: integer (optional)\n        Position. Default: 0.\n\n    Returns\n    -------\n    out: integer\n        Next extended grapheme cluster break position.\n\n    Examples\n    --------\n    > var out = nextGraphemeClusterBreak( 'last man standing', 4 )\n    5\n    > out = nextGraphemeClusterBreak( 'presidential election', 8 )\n    9\n    > out = nextGraphemeClusterBreak( 'अनुच्छेद', 1 )\n    3\n    > out = nextGraphemeClusterBreak( '🌷' )\n    -1\n\n    See Also\n    --------\n    numGraphemeClusters, prevGraphemeClusterBreak","nextTick":"\nnextTick( clbk[, ...args] )\n    Adds a callback to the \"next tick queue\".\n\n    The queue is fully drained after the current operation on the JavaScript\n    stack runs to completion and before the event loop is allowed to continue.\n\n    Parameters\n    ----------\n    clbk: Function\n        Callback to invoke.\n\n    ...args: any (optional)\n        Arguments to provide to the callback upon invocation.\n\n    Examples\n    --------\n    > function f() { console.log( 'beep' ); };\n    > nextTick( f )\n\n","NIGHTINGALES_ROSE":"\nNIGHTINGALES_ROSE()\n    Returns data for Nightingale's famous polar area diagram.\n\n    Returns\n    -------\n    out: Array<Object>\n        Nightingale's data.\n\n    Examples\n    --------\n    > var data = NIGHTINGALES_ROSE()\n    [{...}, {...}, ...]\n\n    References\n    ----------\n    - Nightingale, Florence. 1859. *A contribution to the sanitary history of\n    the British army during the late war with Russia*. London, United Kingdom:\n    John W. Parker and Son.<https://curiosity.lib.harvard.edu/contagion/\n    catalog/36-990101646750203941>.\n\n","NINF":"\nNINF\n    Double-precision floating-point negative infinity.\n\n    Examples\n    --------\n    > NINF\n    -Infinity\n\n    See Also\n    --------\n    FLOAT16_NINF, FLOAT32_NINF, PINF\n","NODE_VERSION":"\nNODE_VERSION\n    Node version.\n\n    Examples\n    --------\n    > NODE_VERSION\n    <string>\n\n","none":"\nnone( collection )\n    Tests whether all elements in a collection are falsy.\n\n    The function immediately returns upon encountering a truthy value.\n\n    If provided an empty collection, the function returns `true`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if all elements are falsy; otherwise, the\n        function returns `false`.\n\n    Examples\n    --------\n    > var arr = [ 0, 0, 0, 0, 0 ];\n    > var bool = none( arr )\n    true\n\n    See Also\n    --------\n    any, every, forEach, noneBy, some\n","noneBy":"\nnoneBy( collection, predicate[, thisArg ] )\n    Tests whether all elements in a collection fail a test implemented by a\n    predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    The function immediately returns upon encountering a truthy return value.\n\n    If provided an empty collection, the function returns `true`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns a falsy\n        value for all elements; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function negative( v ) { return ( v < 0 ); };\n    > var arr = [ 1, 2, 3, 4 ];\n    > var bool = noneBy( arr, negative )\n    true\n\n    See Also\n    --------\n    anyBy, everyBy, forEach, none, noneByRight, someBy\n","noneByAsync":"\nnoneByAsync( collection, [options,] predicate, done )\n    Tests whether all elements in a collection fail a test implemented by a\n    predicate function.\n\n    When invoked, the predicate function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If the\n    predicate function accepts two arguments, the predicate function is\n    provided:\n\n    - value\n    - next\n\n    If the predicate function accepts three arguments, the predicate function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other predicate function signature, the predicate function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - result: test result.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    The function immediately returns upon encountering a truthy `result` value\n    and calls the `done` callback with `null` as the first argument and `false`\n    as the second argument.\n\n    If all elements fail, the function calls the `done` callback with `null` as\n    the first argument and `true` as the second argument.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > noneByAsync( arr, predicate, done )\n    1000\n    2500\n    3000\n    true\n\n    // Limit number of concurrent invocations:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 3000, 2500, 1000 ];\n    > noneByAsync( arr, opts, predicate, done )\n    2500\n    3000\n    1000\n    true\n\n    // Process sequentially:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 3000, 2500, 1000 ];\n    > noneByAsync( arr, opts, predicate, done )\n    3000\n    2500\n    1000\n    true\n\n\nnoneByAsync.factory( [options,] predicate )\n    Returns a function which tests whether all elements in a collection fail a\n    test implemented by a predicate function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = noneByAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n\n    See Also\n    --------\n    anyByAsync, everyByAsync, forEachAsync, noneBy, noneByRightAsync, someByAsync\n","noneByAsync.factory":"\nnoneByAsync.factory( [options,] predicate )\n    Returns a function which tests whether all elements in a collection fail a\n    test implemented by a predicate function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = noneByAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n\n    See Also\n    --------\n    anyByAsync, everyByAsync, forEachAsync, noneBy, noneByRightAsync, someByAsync","noneByRight":"\nnoneByRight( collection, predicate[, thisArg ] )\n    Tests whether all elements in a collection fail a test implemented by a\n    predicate function, iterating from right to left.\n\n    The predicate function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    The function immediately returns upon encountering a truthy return value.\n\n    If provided an empty collection, the function returns `true`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns a falsy\n        value for all elements; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function positive( v ) { return ( v > 0 ); };\n    > var arr = [ -1, -2, -3, -4 ];\n    > var bool = noneByRight( arr, positive )\n    true\n\n    See Also\n    --------\n    anyByRight, everyByRight, forEachRight, none, noneBy, someByRight\n","noneByRightAsync":"\nnoneByRightAsync( collection, [options,] predicate, done )\n    Tests whether all elements in a collection fail a test implemented by a\n    predicate function, iterating from right to left.\n\n    When invoked, the predicate function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If the\n    predicate function accepts two arguments, the predicate function is\n    provided:\n\n    - value\n    - next\n\n    If the predicate function accepts three arguments, the predicate function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other predicate function signature, the predicate function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - result: test result.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    The function immediately returns upon encountering a truthy `result` value\n    and calls the `done` callback with `null` as the first argument and `false`\n    as the second argument.\n\n    If all elements fail, the function calls the `done` callback with `null` as\n    the first argument and `true` as the second argument.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > noneByRightAsync( arr, predicate, done )\n    1000\n    2500\n    3000\n    true\n\n    // Limit number of concurrent invocations:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 1000, 2500, 3000 ];\n    > noneByRightAsync( arr, opts, predicate, done )\n    2500\n    3000\n    1000\n    true\n\n    // Process sequentially:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 1000, 2500, 3000 ];\n    > noneByRightAsync( arr, opts, predicate, done )\n    3000\n    2500\n    1000\n    true\n\n\nnoneByRightAsync.factory( [options,] predicate )\n    Returns a function which tests whether all elements in a collection fail a\n    test implemented by a predicate function, iterating from right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = noneByRightAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n\n    See Also\n    --------\n    anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByAsync, noneByRight, someByRightAsync\n","noneByRightAsync.factory":"\nnoneByRightAsync.factory( [options,] predicate )\n    Returns a function which tests whether all elements in a collection fail a\n    test implemented by a predicate function, iterating from right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = noneByRightAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n\n    See Also\n    --------\n    anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByAsync, noneByRight, someByRightAsync","noneInBy":"\nnoneInBy( object, predicate[, thisArg ] )\n    Tests whether every property in an object fails a test implemented by a\n    predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: object value.\n    - key: object key.\n    - object: the input object.\n\n    The function immediately returns upon encountering a truthy return value.\n\n    If provided an empty object, the function returns `true`.\n\n    Parameters\n    ----------\n    object: Object\n        Input object over which to iterate.\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns a falsy\n        value for all properties; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function negative( v ) { return ( v < 0 ); };\n    > var obj = { 'a': 1, 'b': 2, 'c': 4 };\n    > var bool = noneInBy( obj, negative )\n    true\n\n    See Also\n    --------\n    anyInBy, everyInBy, forIn, noneBy, someInBy\n","nonEnumerableProperties":"\nnonEnumerableProperties( value )\n    Returns an array of an object's own non-enumerable property names and\n    symbols.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    props: Array\n        List of an object's own non-enumerable properties.\n\n    Examples\n    --------\n    > var obj = {};\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.writable = false;\n    > desc.value = 'boop';\n    > defineProperty( obj, 'beep', desc );\n    > var props = nonEnumerableProperties( obj )\n    [ 'beep' ]\n\n    See Also\n    --------\n    enumerableProperties, inheritedNonEnumerableProperties, nonEnumerablePropertiesIn, properties\n","nonEnumerablePropertiesIn":"\nnonEnumerablePropertiesIn( value )\n    Returns an array of an object's own and inherited non-enumerable property\n    names and symbols.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    props: Array\n        List of an object's own and inherited non-enumerable property names and\n        symbols.\n\n    Examples\n    --------\n    > var props = nonEnumerablePropertiesIn( [] )\n\n    See Also\n    --------\n    enumerablePropertiesIn, inheritedNonEnumerableProperties, nonEnumerableProperties, propertiesIn\n","nonEnumerablePropertyNames":"\nnonEnumerablePropertyNames( value )\n    Returns an array of an object's own non-enumerable property names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's own non-enumerable property names.\n\n    Examples\n    --------\n    > var obj = {};\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.writable = true;\n    > desc.value = 'boop';\n    > defineProperty( obj, 'beep', desc );\n    > var keys = nonEnumerablePropertyNames( obj )\n    e.g., [ 'beep', ... ]\n\n    See Also\n    --------\n    objectKeys, inheritedNonEnumerablePropertyNames, nonEnumerablePropertyNamesIn, nonEnumerablePropertySymbols, propertyNames\n","nonEnumerablePropertyNamesIn":"\nnonEnumerablePropertyNamesIn( value )\n    Returns an array of an object's own and inherited non-enumerable property\n    names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's own and inherited non-enumerable property names.\n\n    Examples\n    --------\n    > var obj = {};\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.writable = true;\n    > desc.value = 'boop';\n    > defineProperty( obj, 'beep', desc );\n    > var keys = nonEnumerablePropertyNamesIn( obj )\n    e.g., [ 'beep', ... ]\n\n    See Also\n    --------\n    keysIn, inheritedNonEnumerablePropertyNames, nonEnumerablePropertyNames, propertyNamesIn\n","nonEnumerablePropertySymbols":"\nnonEnumerablePropertySymbols( value )\n    Returns an array of an object's own non-enumerable symbol properties.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's own non-enumerable symbol properties.\n\n    Examples\n    --------\n    > var obj = {};\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.writable = true;\n    > desc.value = 'boop';\n    > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n    > defineProperty( obj, sym, desc );\n    > var symbols = nonEnumerablePropertySymbols( obj )\n\n    See Also\n    --------\n    enumerablePropertySymbols, inheritedNonEnumerablePropertySymbols, nonEnumerablePropertyNames, nonEnumerablePropertySymbolsIn, propertySymbols\n","nonEnumerablePropertySymbolsIn":"\nnonEnumerablePropertySymbolsIn( value )\n    Returns an array of an object's own and inherited non-enumerable symbol\n    properties.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's own and inherited non-enumerable symbol properties.\n\n    Examples\n    --------\n    > var obj = {};\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.writable = true;\n    > desc.value = 'boop';\n    > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n    > defineProperty( obj, sym, desc );\n    > var symbols = nonEnumerablePropertySymbolsIn( obj )\n\n    See Also\n    --------\n    enumerablePropertySymbolsIn, inheritedNonEnumerablePropertySymbols, nonEnumerablePropertyNamesIn, nonEnumerablePropertySymbols, propertySymbolsIn\n","noneOwnBy":"\nnoneOwnBy( object, predicate[, thisArg ] )\n    Tests whether every own property of an object fails a test implemented\n    by a predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: property value.\n    - index: property key.\n    - object: the input object.\n\n    The function immediately returns upon encountering a truthy return value.\n\n    If provided an empty object, the function returns `true`.\n\n    Parameters\n    ----------\n    object: Object\n        Input object.\n\n    predicate: Function\n        Test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns a falsy\n        value for all own properties; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function isUnderage( v ) { return ( v < 18 ); };\n    > var obj = { 'a': 11, 'b': 12, 'c': 22 };\n    > var bool = noneOwnBy( obj, isUnderage )\n    false\n\n    See Also\n    --------\n    anyOwnBy, everyOwnBy, forOwn, noneBy, someOwnBy\n","nonIndexKeys":"\nnonIndexKeys( obj )\n    Returns an array of an object's own enumerable property names which are not\n    integer indices.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    obj: any\n        Input value.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's own enumerable property names.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; this[0] = 3.14; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var keys = nonIndexKeys( obj )\n    e.g., [ 'beep' ]\n\n    See Also\n    --------\n    objectEntries, objectKeys, objectValues\n","noop":"\nnoop()\n    A function which does nothing.\n\n    Examples\n    --------\n    > noop();\n\n","now":"\nnow()\n    Returns the time in seconds since the epoch.\n\n    The Unix epoch is 00:00:00 UTC on 1 January 1970.\n\n    Returns\n    -------\n    out: integer\n        Time in seconds since the epoch.\n\n    Examples\n    --------\n    > var ts = now()\n    <number>\n\n","NUM_CPUS":"\nNUM_CPUS\n    Number of CPUs.\n\n    In browser environments, the number of CPUs is determined by querying the\n    hardware concurrency API.\n\n    In Node.js environments, the number of CPUs is determined via the `os`\n    module.\n\n    Examples\n    --------\n    > NUM_CPUS\n    <number>\n\n","num2words":"\nnum2words( value[, options] )\n    Converts a number to a word representation.\n\n    Parameters\n    ----------\n    value: integer\n        Input value.\n\n    options: Object (optional)\n        Options.\n\n    options.lang: string (optional)\n        Language code. Supported languages:\n\n        - en: English.\n        - de: German.\n\n        Default: `'en'`.\n\n    Returns\n    -------\n    out: string\n        Word representation of number.\n\n    Examples\n    --------\n    > var out = num2words( 123 )\n    'one hundred twenty-three'\n\n    > out = num2words( 16.31 )\n    'sixteen point three one'\n\n    > out = num2words( 123, { 'lang': 'de' } )\n    'einhundertdreiundzwanzig'\n\n","Number":"\nNumber( value )\n    Returns a Number object.\n\n    This constructor should be used sparingly. Always prefer number primitives.\n\n    Parameters\n    ----------\n    value: number\n        Value to wrap in a Number object.\n\n    Returns\n    -------\n    out: Number\n        Number object.\n\n    Examples\n    --------\n    > var v = new Number( 5 )\n    <Number>\n\n","numel":"\nnumel( x )\n    Returns the number of elements in an ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    Returns\n    -------\n    n: integer\n        Number of elements.\n\n    Examples\n    --------\n    > var n = numel( ndzeros( [ 3, 3, 3 ] ) )\n    27\n\n    See Also\n    --------\n    array, ndarray, numelDimension\n","numelDimension":"\nnumelDimension( x, dim )\n    Returns the size (i.e., number of elements) of a specified dimension for a\n    provided ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    dim: integer\n        Dimension index. If less than zero, the index is resolved relative to\n        the last dimension, with the last dimension corresponding to the value\n        `-1`.\n\n    Returns\n    -------\n    out: integer\n        Dimension size.\n\n    Examples\n    --------\n    > var out = numelDimension( ndzeros( [ 4, 2, 3 ] ), 0 )\n    4\n\n    See Also\n    --------\n    array, ndarray, numel\n","numGraphemeClusters":"\nnumGraphemeClusters( str )\n    Returns the number of grapheme clusters in a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Number of grapheme clusters.\n\n    Examples\n    --------\n    > var out = numGraphemeClusters( 'beep' )\n    4\n    > out = numGraphemeClusters( '🌷' )\n    1\n\n    See Also\n    --------\n    nextGraphemeClusterBreak\n","Object":"\nObject( value )\n    Returns an object.\n\n    If provided `null` or `undefined`, the function returns an empty object.\n\n    If provided an existing object, the function returns the input value\n    unchanged.\n\n    Otherwise, if provided any other value (e.g., a number, string, etc), the\n    function will return an object of the corresponding type.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    out: Object\n        Output object.\n\n    Examples\n    --------\n    > var o = new Object( null )\n    {}\n    > o = new Object( 5.0 )\n    <Number>\n    > o = new Object( 'beep' )\n    <String>\n\nObject.assign( target, ...sources )\n    Assigns enumerable and own properties from source objects to a target\n    object.\n\n    Parameters\n    ----------\n    target: Object\n        Target object.\n\n    sources: ...Object\n        Source objects.\n\n    Returns\n    -------\n    out: Object\n        Target object.\n\n    Examples\n    --------\n    > var o = Object.assign( {}, { 'a': 1 }, { 'b': 2 } )\n    { 'a': 1, 'b': 2 }\n\nObject.create( prototype, properties )\n    Creates a new object with a specified prototype object and properties.\n\n    Parameters\n    ----------\n    prototype: Object\n        Prototype object.\n\n    properties: Object\n        Properties object.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > var o = Object.create( {}, { 'a': { 'value': 1 } } )\n    { 'a': 1 }\n\nObject.defineProperties( obj, properties )\n    Defines properties for an object.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    properties: Object\n        Properties object.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.defineProperties( {}, { 'a': { 'value': 1 } } )\n    { 'a': 1 }\n\nObject.defineProperty( obj, key, descriptor )\n    Defines a property for an object.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    key: string\n        Property key.\n\n    descriptor: Object\n        Property descriptor.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.defineProperty( {}, 'a', {\n        'value': 1,\n        'enumerable': true,\n        'configurable': true,\n        'writable': false\n    })\n    { 'a': 1 }\n\nObject.entries( obj )\n    Returns an array of an object's own enumerable string-keyed property\n    [key, value] pairs.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Array\n        Array of [key, value] pairs.\n\n    Examples\n    --------\n    > var o = Object.entries( { 'a': 1, 'b': 2 } )\n    [ [ 'a', 1 ], [ 'b', 2 ] ]\n\nObject.freeze( obj )\n    Freezes an object.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.freeze( { 'a': 1 } )\n    { 'a': 1 }\n\nObject.getOwnPropertyDescriptor( obj, key )\n    Returns an object's own property descriptor.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    key: string\n        Property key.\n\n    Returns\n    -------\n    out: Object\n        Property descriptor.\n\n    Examples\n    --------\n    > var o = Object.getOwnPropertyDescriptor( { 'a': 1 }, 'a' )\n    { 'value': 1, 'enumerable': true, 'configurable': true, 'writable': true }\n\nObject.getOwnPropertyDescriptors( obj )\n    Returns an object's own property descriptors.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Object\n        Property descriptors.\n\n    Examples\n    --------\n    > var o = Object.getOwnPropertyDescriptors( { 'a': 1, 'b': 2 } )\n    {\n        'a': {\n            'value': 1,\n            'enumerable': true,\n            'configurable': true,\n            'writable': true\n        },\n        'b': {\n            'value': 2,\n            'enumerable': true,\n            'configurable': true,\n            'writable': true\n        }\n    }\n\nObject.getOwnPropertyNames( obj )\n    Returns an array of an object's own enumerable and non-enumerable\n    property names.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Array\n        Array of property names.\n\n    Examples\n    --------\n    > var o = Object.getOwnPropertyNames( { 'a': 1, 'b': 2 } )\n    [ 'a', 'b' ]\n\nObject.getOwnPropertySymbols( obj )\n    Returns an array of an object's own enumerable and non-enumerable\n    symbol property names.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Array\n        Array of symbol property names.\n\n    Examples\n    --------\n    > var o = Object.getOwnPropertySymbols( { 'a': 1, 'b': 2 } )\n    []\n\nObject.getPrototypeOf( obj )\n    Returns an object's prototype.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Object\n        Prototype.\n\n    Examples\n    --------\n    > var o = Object.getPrototypeOf( { 'a': 1, 'b': 2 } )\n    <Object>\n\nObject.hasOwn( obj, p )\n    Returns a boolean indicating whether an object has a property with the\n    specified name.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    p: string\n        Property name.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object has a property with the specified\n        name.\n\n    Examples\n    --------\n    > var o = Object.hasOwn( { 'a': 1, 'b': 2 }, 'a' )\n    true\n\nObject.is( value1, value2 )\n    Returns a boolean indicating whether two values are the same value.\n\n    Parameters\n    ----------\n    value1: any\n        First value.\n\n    value2: any\n        Second value.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether two values are the same value.\n\n    Examples\n    --------\n    > var o = Object.is( 1, 1 )\n    true\n    > var o = Object.is( 1, '1' )\n    false\n\nObject.isExtensible( obj )\n    Returns a boolean indicating whether an object is extensible.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object is extensible.\n\n    Examples\n    --------\n    > var o = Object.isExtensible( { 'a': 1 } )\n    true\n\nObject.isFrozen( obj )\n    Returns a boolean indicating whether an object is frozen.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object is frozen.\n\n    Examples\n    --------\n    > var o = Object.isFrozen( { 'a': 1 } )\n    false\n    > var o = Object.isFrozen( Object.freeze( { 'a': 1 } ) )\n    true\n\nObject.isSealed( obj )\n    Returns a boolean indicating whether an object is sealed.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object is sealed.\n\n    Examples\n    --------\n    > var o = Object.isSealed( { 'a': 1 } )\n    false\n    > var o = Object.isSealed( Object.seal( { 'a': 1 } ) )\n    true\n\nObject.keys( obj )\n    Returns an array of an object's own enumerable string-keyed property\n    names.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Array\n        Array of property names.\n\n    Examples\n    --------\n    > var o = Object.keys( { 'a': 1, 'b': 2 } )\n    [ 'a', 'b' ]\n\nObject.preventExtensions( obj )\n    Prevents the addition of new properties to an object.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.preventExtensions( { 'a': 1 } )\n    { 'a': 1 }\n    > o.b = 2;\n    > o\n    { 'a': 1 }\n\nObject.seal( obj )\n    Prevents the addition of new properties to an object and marks all\n    existing properties as non-configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.seal( { 'a': 1 } )\n    { 'a': 1 }\n    > o.b = 2;\n    > o\n    { 'a': 1 }\n    > delete o.a;\n    > o\n    { 'a': 1 }\n\nObject.setPrototypeOf( obj, proto )\n    Sets an object's prototype.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    proto: Object\n        Prototype.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.setPrototypeOf( { 'a': 1 }, { 'b': 2 } )\n    { 'a': 1 }\n    > o.b\n    2\n\nObject.values( obj )\n    Returns an array of an object's own enumerable property values.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Array\n        Array of property values.\n\n    Examples\n    --------\n    > var o = Object.values( { 'a': 1, 'b': 2 } )\n    [ 1, 2 ]\n\nObject.prototype.toLocaleString()\n    Returns a string representing the object.\n\n    Returns\n    -------\n    out: string\n        String representing the object.\n\n    Examples\n    --------\n    > var o = Object.prototype.toLocaleString.call( { 'a': 1, 'b': 2 } )\n    <string>\n\nObject.prototype.toString()\n    Returns a string representing the object.\n\n    Returns\n    -------\n    out: string\n        String representing the object.\n\n    Examples\n    --------\n    > var o = Object.prototype.toString.call( { 'a': 1, 'b': 2 } )\n    <string>\n\nObject.prototype.valueOf()\n    Returns the primitive value of the object.\n\n    Returns\n    -------\n    out: any\n        Primitive value of the object.\n\n    Examples\n    --------\n    > var o = Object.prototype.valueOf.call( { 'a': 1, 'b': 2 } )\n    {}\n\nObject.prototype.hasOwnProperty( p )\n    Returns a boolean indicating whether an object has a property with the\n    specified name.\n\n    Parameters\n    ----------\n    p: string\n        Property name.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object has a property with the specified\n        name.\n\n    Examples\n    --------\n    > var o = Object.prototype.hasOwnProperty.call( { 'a': 1, 'b': 2 }, 'a' )\n    true\n\nObject.prototype.isPrototypeOf( obj )\n    Returns a boolean indicating whether an object exists in another object's\n    prototype chain.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object exists in another object's\n        prototype chain.\n\n    Examples\n    --------\n    > var p = { 'a': 1 };\n    > var o = { '__proto__': p };\n    > var b = o.isPrototypeOf( p );\n    true\n\nObject.prototype.propertyIsEnumerable( p )\n    Returns a boolean indicating whether an object's property is enumerable.\n\n    Parameters\n    ----------\n    p: string\n        Property name.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object's property is enumerable.\n\n    Examples\n    --------\n    > var o = { 'a': 1, 'b': 2 };\n    > var bool = Object.prototype.propertyIsEnumerable.call( o, 'a' )\n    true\n\nObject.prototype.constructor\n    Property whose value is a reference to the constructor function that\n    created the instance object.\n\n    Examples\n    --------\n    > var o = new Object( null );\n    > var ctr = o.constructor;\n    <Object>\n\n","Object.assign":"\nObject.assign( target, ...sources )\n    Assigns enumerable and own properties from source objects to a target\n    object.\n\n    Parameters\n    ----------\n    target: Object\n        Target object.\n\n    sources: ...Object\n        Source objects.\n\n    Returns\n    -------\n    out: Object\n        Target object.\n\n    Examples\n    --------\n    > var o = Object.assign( {}, { 'a': 1 }, { 'b': 2 } )\n    { 'a': 1, 'b': 2 }","Object.create":"\nObject.create( prototype, properties )\n    Creates a new object with a specified prototype object and properties.\n\n    Parameters\n    ----------\n    prototype: Object\n        Prototype object.\n\n    properties: Object\n        Properties object.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > var o = Object.create( {}, { 'a': { 'value': 1 } } )\n    { 'a': 1 }","Object.defineProperties":"\nObject.defineProperties( obj, properties )\n    Defines properties for an object.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    properties: Object\n        Properties object.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.defineProperties( {}, { 'a': { 'value': 1 } } )\n    { 'a': 1 }","Object.defineProperty":"\nObject.defineProperty( obj, key, descriptor )\n    Defines a property for an object.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    key: string\n        Property key.\n\n    descriptor: Object\n        Property descriptor.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.defineProperty( {}, 'a', {\n        'value': 1,\n        'enumerable': true,\n        'configurable': true,\n        'writable': false\n    })\n    { 'a': 1 }","Object.entries":"\nObject.entries( obj )\n    Returns an array of an object's own enumerable string-keyed property\n    [key, value] pairs.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Array\n        Array of [key, value] pairs.\n\n    Examples\n    --------\n    > var o = Object.entries( { 'a': 1, 'b': 2 } )\n    [ [ 'a', 1 ], [ 'b', 2 ] ]","Object.freeze":"\nObject.freeze( obj )\n    Freezes an object.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.freeze( { 'a': 1 } )\n    { 'a': 1 }","Object.getOwnPropertyDescriptor":"\nObject.getOwnPropertyDescriptor( obj, key )\n    Returns an object's own property descriptor.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    key: string\n        Property key.\n\n    Returns\n    -------\n    out: Object\n        Property descriptor.\n\n    Examples\n    --------\n    > var o = Object.getOwnPropertyDescriptor( { 'a': 1 }, 'a' )\n    { 'value': 1, 'enumerable': true, 'configurable': true, 'writable': true }","Object.getOwnPropertyDescriptors":"\nObject.getOwnPropertyDescriptors( obj )\n    Returns an object's own property descriptors.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Object\n        Property descriptors.\n\n    Examples\n    --------\n    > var o = Object.getOwnPropertyDescriptors( { 'a': 1, 'b': 2 } )\n    {\n        'a': {\n            'value': 1,\n            'enumerable': true,\n            'configurable': true,\n            'writable': true\n        },\n        'b': {\n            'value': 2,\n            'enumerable': true,\n            'configurable': true,\n            'writable': true\n        }\n    }","Object.getOwnPropertyNames":"\nObject.getOwnPropertyNames( obj )\n    Returns an array of an object's own enumerable and non-enumerable\n    property names.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Array\n        Array of property names.\n\n    Examples\n    --------\n    > var o = Object.getOwnPropertyNames( { 'a': 1, 'b': 2 } )\n    [ 'a', 'b' ]","Object.getOwnPropertySymbols":"\nObject.getOwnPropertySymbols( obj )\n    Returns an array of an object's own enumerable and non-enumerable\n    symbol property names.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Array\n        Array of symbol property names.\n\n    Examples\n    --------\n    > var o = Object.getOwnPropertySymbols( { 'a': 1, 'b': 2 } )\n    []","Object.getPrototypeOf":"\nObject.getPrototypeOf( obj )\n    Returns an object's prototype.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Object\n        Prototype.\n\n    Examples\n    --------\n    > var o = Object.getPrototypeOf( { 'a': 1, 'b': 2 } )\n    <Object>","Object.hasOwn":"\nObject.hasOwn( obj, p )\n    Returns a boolean indicating whether an object has a property with the\n    specified name.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    p: string\n        Property name.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object has a property with the specified\n        name.\n\n    Examples\n    --------\n    > var o = Object.hasOwn( { 'a': 1, 'b': 2 }, 'a' )\n    true","Object.is":"\nObject.is( value1, value2 )\n    Returns a boolean indicating whether two values are the same value.\n\n    Parameters\n    ----------\n    value1: any\n        First value.\n\n    value2: any\n        Second value.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether two values are the same value.\n\n    Examples\n    --------\n    > var o = Object.is( 1, 1 )\n    true\n    > var o = Object.is( 1, '1' )\n    false","Object.isExtensible":"\nObject.isExtensible( obj )\n    Returns a boolean indicating whether an object is extensible.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object is extensible.\n\n    Examples\n    --------\n    > var o = Object.isExtensible( { 'a': 1 } )\n    true","Object.isFrozen":"\nObject.isFrozen( obj )\n    Returns a boolean indicating whether an object is frozen.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object is frozen.\n\n    Examples\n    --------\n    > var o = Object.isFrozen( { 'a': 1 } )\n    false\n    > var o = Object.isFrozen( Object.freeze( { 'a': 1 } ) )\n    true","Object.isSealed":"\nObject.isSealed( obj )\n    Returns a boolean indicating whether an object is sealed.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object is sealed.\n\n    Examples\n    --------\n    > var o = Object.isSealed( { 'a': 1 } )\n    false\n    > var o = Object.isSealed( Object.seal( { 'a': 1 } ) )\n    true","Object.keys":"\nObject.keys( obj )\n    Returns an array of an object's own enumerable string-keyed property\n    names.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Array\n        Array of property names.\n\n    Examples\n    --------\n    > var o = Object.keys( { 'a': 1, 'b': 2 } )\n    [ 'a', 'b' ]","Object.preventExtensions":"\nObject.preventExtensions( obj )\n    Prevents the addition of new properties to an object.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.preventExtensions( { 'a': 1 } )\n    { 'a': 1 }\n    > o.b = 2;\n    > o\n    { 'a': 1 }","Object.seal":"\nObject.seal( obj )\n    Prevents the addition of new properties to an object and marks all\n    existing properties as non-configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.seal( { 'a': 1 } )\n    { 'a': 1 }\n    > o.b = 2;\n    > o\n    { 'a': 1 }\n    > delete o.a;\n    > o\n    { 'a': 1 }","Object.setPrototypeOf":"\nObject.setPrototypeOf( obj, proto )\n    Sets an object's prototype.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    proto: Object\n        Prototype.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.setPrototypeOf( { 'a': 1 }, { 'b': 2 } )\n    { 'a': 1 }\n    > o.b\n    2","Object.values":"\nObject.values( obj )\n    Returns an array of an object's own enumerable property values.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Array\n        Array of property values.\n\n    Examples\n    --------\n    > var o = Object.values( { 'a': 1, 'b': 2 } )\n    [ 1, 2 ]","Object.prototype.toLocaleString":"\nObject.prototype.toLocaleString()\n    Returns a string representing the object.\n\n    Returns\n    -------\n    out: string\n        String representing the object.\n\n    Examples\n    --------\n    > var o = Object.prototype.toLocaleString.call( { 'a': 1, 'b': 2 } )\n    <string>","Object.prototype.toString":"\nObject.prototype.toString()\n    Returns a string representing the object.\n\n    Returns\n    -------\n    out: string\n        String representing the object.\n\n    Examples\n    --------\n    > var o = Object.prototype.toString.call( { 'a': 1, 'b': 2 } )\n    <string>","Object.prototype.valueOf":"\nObject.prototype.valueOf()\n    Returns the primitive value of the object.\n\n    Returns\n    -------\n    out: any\n        Primitive value of the object.\n\n    Examples\n    --------\n    > var o = Object.prototype.valueOf.call( { 'a': 1, 'b': 2 } )\n    {}","Object.prototype.hasOwnProperty":"\nObject.prototype.hasOwnProperty( p )\n    Returns a boolean indicating whether an object has a property with the\n    specified name.\n\n    Parameters\n    ----------\n    p: string\n        Property name.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object has a property with the specified\n        name.\n\n    Examples\n    --------\n    > var o = Object.prototype.hasOwnProperty.call( { 'a': 1, 'b': 2 }, 'a' )\n    true","Object.prototype.isPrototypeOf":"\nObject.prototype.isPrototypeOf( obj )\n    Returns a boolean indicating whether an object exists in another object's\n    prototype chain.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object exists in another object's\n        prototype chain.\n\n    Examples\n    --------\n    > var p = { 'a': 1 };\n    > var o = { '__proto__': p };\n    > var b = o.isPrototypeOf( p );\n    true","Object.prototype.propertyIsEnumerable":"\nObject.prototype.propertyIsEnumerable( p )\n    Returns a boolean indicating whether an object's property is enumerable.\n\n    Parameters\n    ----------\n    p: string\n        Property name.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object's property is enumerable.\n\n    Examples\n    --------\n    > var o = { 'a': 1, 'b': 2 };\n    > var bool = Object.prototype.propertyIsEnumerable.call( o, 'a' )\n    true","Object.prototype.constructor":"\nObject.prototype.constructor\n    Property whose value is a reference to the constructor function that\n    created the instance object.\n\n    Examples\n    --------\n    > var o = new Object( null );\n    > var ctr = o.constructor;\n    <Object>","objectEntries":"\nobjectEntries( obj )\n    Returns an array of an object's own enumerable property `[key, value]`\n    pairs.\n\n    Entry order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic return values.\n\n    Parameters\n    ----------\n    obj: ObjectLike\n        Input object.\n\n    Returns\n    -------\n    arr: Array\n        Array containing key-value pairs.\n\n    Examples\n    --------\n    > var obj = { 'beep': 'boop', 'foo': 'bar' };\n    > var entries = objectEntries( obj )\n    e.g., [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ]\n\n    See Also\n    --------\n    objectEntriesIn, objectFromEntries, objectKeys, objectValues\n","objectEntriesIn":"\nobjectEntriesIn( obj )\n    Returns an array of an object's own and inherited enumerable property\n    `[key, value]` pairs.\n\n    Entry order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic return values.\n\n    Parameters\n    ----------\n    obj: ObjectLike\n        Input object.\n\n    Returns\n    -------\n    arr: Array\n        Array containing key-value pairs.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var entries = objectEntriesIn( obj )\n    e.g., [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ]\n\n    See Also\n    --------\n    objectEntries, objectFromEntries, keysIn, objectValuesIn\n","objectFromEntries":"\nobjectFromEntries( entries )\n    Creates an object from an array of key-value pairs.\n\n    Parameters\n    ----------\n    entries: Array<Array>\n        Input object.\n\n    Returns\n    -------\n    out: Object\n        Object created from `[key, value]` pairs.\n\n    Examples\n    --------\n    > var entries = [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ];\n    > var obj = objectFromEntries( entries )\n    { 'beep': 'boop', 'foo': 'bar' }\n\n    See Also\n    --------\n    objectEntries\n","objectInverse":"\nobjectInverse( obj[, options] )\n    Inverts an object, such that keys become values and values become keys.\n\n    Beware when providing objects having values which are themselves objects.\n    The function relies on native object serialization (`#toString`) when\n    converting values to keys.\n\n    Insertion order is not guaranteed, as object key enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's keys, thus allowing for\n    deterministic inversion.\n\n    Parameters\n    ----------\n    obj: ObjectLike\n        Input object.\n\n    options: Object (optional)\n        Options.\n\n    options.duplicates: boolean (optional)\n        Boolean indicating whether to store keys mapped to duplicate values in\n        arrays. Default: `true`.\n\n    Returns\n    -------\n    out: Object\n        Inverted object.\n\n    Examples\n    --------\n    // Basic usage:\n    > var obj = { 'a': 'beep', 'b': 'boop' };\n    > var out = objectInverse( obj )\n    { 'beep': 'a', 'boop': 'b' }\n\n    // Duplicate values:\n    > obj = { 'a': 'beep', 'b': 'beep' };\n    > out = objectInverse( obj )\n    { 'beep': [ 'a', 'b' ] }\n\n    // Override duplicate values:\n    > obj = {};\n    > obj.a = 'beep';\n    > obj.b = 'boop';\n    > obj.c = 'beep';\n    > out = objectInverse( obj, { 'duplicates': false } )\n    { 'beep': 'c', 'boop': 'b' }\n\n    See Also\n    --------\n    objectInverseBy\n","objectInverseBy":"\nobjectInverseBy( obj, [options,] transform )\n    Inverts an object, such that keys become values and values become keys,\n    according to a transform function.\n\n    The transform function is provided three arguments:\n\n    - key: object key.\n    - value: object value corresponding to `key`.\n    - obj: the input object.\n\n    The value returned by a transform function should be a value which can be\n    serialized as an object key. Hence, beware when providing objects having\n    values which are themselves objects. The function relies on native object\n    serialization (`#toString`) when converting transform function return values\n    to keys.\n\n    Insertion order is not guaranteed, as object key enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's keys, thus allowing for\n    deterministic inversion.\n\n    Parameters\n    ----------\n    obj: ObjectLike\n        Input object.\n\n    options: Object (optional)\n        Options.\n\n    options.duplicates: boolean (optional)\n        Boolean indicating whether to store keys mapped to duplicate values in\n        arrays. Default: `true`.\n\n    transform: Function\n        Transform function.\n\n    Returns\n    -------\n    out: Object\n        Inverted object.\n\n    Examples\n    --------\n    // Basic usage:\n    > function transform( key, value ) { return key + value; };\n    > var obj = { 'a': 'beep', 'b': 'boop' };\n    > var out = objectInverseBy( obj, transform )\n    { 'abeep': 'a', 'bboop': 'b' }\n\n    // Duplicate values:\n    > function transform( key, value ) { return value; };\n    > obj = { 'a': 'beep', 'b': 'beep' };\n    > out = objectInverseBy( obj, transform )\n    { 'beep': [ 'a', 'b' ] }\n\n    // Override duplicate values:\n    > obj = {};\n    > obj.a = 'beep';\n    > obj.b = 'boop';\n    > obj.c = 'beep';\n    > out = objectInverseBy( obj, { 'duplicates': false }, transform )\n    { 'beep': 'c', 'boop': 'b' }\n\n    See Also\n    --------\n    objectInverse\n","objectKeys":"\nobjectKeys( value )\n    Returns an array of an object's own enumerable property names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's own enumerable property names.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var keys = objectKeys( obj )\n    [ 'beep' ]\n\n    See Also\n    --------\n    objectEntries, keysIn, nonIndexKeys, objectValues\n","objectValues":"\nobjectValues( obj )\n    Returns an array of an object's own enumerable property values.\n\n    Value order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    Parameters\n    ----------\n    obj: ObjectLike\n        Input object.\n\n    Returns\n    -------\n    values: Array\n        Value array.\n\n    Examples\n    --------\n    > var obj = { 'beep': 'boop', 'foo': 'bar' };\n    > var vals = objectValues( obj )\n    e.g., [ 'boop', 'bar' ]\n\n    See Also\n    --------\n    objectEntries, objectKeys\n","objectValuesIn":"\nobjectValuesIn( obj )\n    Returns an array of an object's own and inherited enumerable property\n    values.\n\n    Value order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    Parameters\n    ----------\n    obj: ObjectLike\n        Input object.\n\n    Returns\n    -------\n    values: Array\n        Value array.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var values = objectValuesIn( obj )\n    e.g., [ 'boop', 'bar' ]\n\n    See Also\n    --------\n    objectEntriesIn, keysIn, objectValues\n","omit":"\nomit( obj, keys )\n    Returns a partial object copy excluding specified keys.\n\n    The function returns a shallow copy.\n\n    The function ignores non-existent keys.\n\n    The function only copies own properties. Hence, the function never copies\n    inherited properties.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    keys: string|Array<string>\n        Keys to exclude.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > var obj1 = { 'a': 1, 'b': 2 };\n    > var obj2 = omit( obj1, 'b' )\n    { 'a': 1 }\n\n    See Also\n    --------\n    omitBy\n","omitBy":"\nomitBy( obj, predicate )\n    Returns a partial object copy excluding properties for which a predicate\n    returns a truthy value.\n\n    The function returns a shallow copy.\n\n    The function only copies own properties. Hence, the function never copies\n    inherited properties.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    predicate: Function\n        Predicate function.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > function predicate( key, value ) { return ( value > 1 ); };\n    > var obj1 = { 'a': 1, 'b': 2 };\n    > var obj2 = omitBy( obj1, predicate )\n    { 'a': 1 }\n\n    See Also\n    --------\n    omit\n","open":"\nopen( path[, flags[, mode]], clbk )\n    Asynchronously opens a file.\n\n    Some characters, such as <>:\"/\\|?*, are reserved under Windows.\n    Under NTFS, if the path contains a colon, Node.js will open a file system\n    stream.\n\n    Parameters\n    ----------\n    path: string|Buffer\n        Filename.\n\n    flags: string|number (optional)\n        File system flags. Default: 'r'.\n\n    mode: integer (optional)\n        File mode (permission and sticky bits). This sets the file mode, but\n        only if the file was created. On Windows, only the write permission can\n        be manipulated. Default: 0o666.\n\n    clbk: Function\n        Callback to invoke upon opening a file.\n\n    Examples\n    --------\n    > function onOpen( error, fd ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     } else {\n    ...         close.sync( fd );\n    ...     }\n    ... };\n    > open( './beep/boop.txt', onOpen );\n\n\nopen.sync( path[, flags[, mode]] )\n    Synchronously opens a file.\n\n    Parameters\n    ----------\n    path: string|Buffer\n        Filename.\n\n    flags: string|number (optional)\n        File system flags. Default: 'r'.\n\n    mode: integer (optional)\n        File mode (permission and sticky bits).  This sets the file mode, but\n        only if the file was created. On Windows, only the write permission can\n        be manipulated. Default: 0o666.\n\n    Returns\n    -------\n    fd: Error|integer\n        File descriptor.\n\n    Examples\n    --------\n    > var fd = open.sync( './beep/boop.txt' );\n    > if ( !isError( fd ) ) { close.sync( fd ); };\n\n    See Also\n    --------\n    close, exists, readFile\n","open.sync":"\nopen.sync( path[, flags[, mode]] )\n    Synchronously opens a file.\n\n    Parameters\n    ----------\n    path: string|Buffer\n        Filename.\n\n    flags: string|number (optional)\n        File system flags. Default: 'r'.\n\n    mode: integer (optional)\n        File mode (permission and sticky bits).  This sets the file mode, but\n        only if the file was created. On Windows, only the write permission can\n        be manipulated. Default: 0o666.\n\n    Returns\n    -------\n    fd: Error|integer\n        File descriptor.\n\n    Examples\n    --------\n    > var fd = open.sync( './beep/boop.txt' );\n    > if ( !isError( fd ) ) { close.sync( fd ); };\n\n    See Also\n    --------\n    close, exists, readFile","openURL":"\nopenURL( url )\n    Opens a URL in a user's default browser.\n\n    In a non-browser environment, the function returns an unreferenced child\n    process. In a browser environment, the function returns a reference to a\n    `window` object.\n\n    Parameters\n    ----------\n    url: string\n        URL to open.\n\n    Returns\n    -------\n    out: process|Window\n        Child process or `window` object.\n\n    Examples\n    --------\n    > var out = openURL( 'https://google.com' );\n\n","ordinalize":"\nordinalize( value[, options] )\n    Converts an integer to an ordinal string (e.g., `1st`, `2nd`, etc.).\n\n    Parameters\n    ----------\n    value: string|integer\n        Input value.\n\n    options: Object (optional)\n        Options.\n\n    options.lang: string (optional)\n        Language code. Supported languages:\n\n        - en: English.\n        - es: Spanish.\n        - fin: Finnish.\n        - fr: French.\n        - de: Dutch.\n        - it: Italian.\n        - pt: Portuguese.\n        - swe: Swedish.\n\n        Default: `'en'`.\n\n    options.suffixOnly: boolean (optional)\n        Boolean indicating whether to return only the suffix. Default: `false`.\n\n    options.gender: string (optional)\n       Grammatical gender (used if applicable); must be either 'masculine' or\n       'feminine'. Default: `'masculine'`.\n\n    Returns\n    -------\n    out: string\n        Ordinal string or suffix.\n\n    Examples\n    --------\n    > var out = ordinalize( '1' )\n    '1st'\n    > out = ordinalize( 2, { 'suffixOnly': true } )\n    'nd'\n    > out = ordinalize( '3', { 'lang': 'es' } )\n    '3º'\n\n","PACE_BOSTON_HOUSE_PRICES":"\nPACE_BOSTON_HOUSE_PRICES()\n    Returns a (corrected) dataset derived from information collected by the US\n    Census Service concerning housing in Boston, Massachusetts (1978).\n\n    The data consists of 21 attributes:\n\n    - obs: observation number.\n    - town: town name.\n    - town_id: town identifier.\n    - tract: tract identifier.\n    - lon: longitude.\n    - lat: latitude.\n    - medv: median value of owner-occupied homes in $1000's.\n    - cmedv: corrected median value of owner-occupied homes in $1000's.\n    - crim: per capita crime rate by town.\n    - zn: proportion of residential land zoned for lots over 25,000 square feet.\n    - indus: proportion of non-retail business acres per town.\n    - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise).\n    - nox: nitric oxides concentration (parts per 10 million).\n    - rm: average number of rooms per dwelling.\n    - age: proportion of owner-occupied units built prior to 1940.\n    - dis: weighted distances to five Boston employment centers.\n    - rad: index of accessibility to radial highways.\n    - tax: full-value property-tax rate per $10,000.\n    - ptratio: pupil-teacher ratio by town.\n    - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town.\n    - lstat: percent lower status of the population.\n\n    The dataset can be used to predict two dependent variables: 1) nitrous oxide\n    level and 2) median home value.\n\n    The median home value field seems to be censored at 50.00 (corresponding to\n    a median value of $50,000). Censoring is suggested by the fact that the\n    highest median value of exactly $50,000 is reported in 16 cases, while 15\n    cases have values between $40,000 and $50,000. Values are rounded to the\n    nearest hundred.\n\n    The dataset contains eight corrections to miscoded median values, as\n    documented by Gilley and Pace (1996).\n\n    The dataset augments the original dataset from Harrison and Rubinfeld (1978)\n    by including geo-referencing and spatial estimation for each observation.\n\n    Returns\n    -------\n    out: Array<Object>\n        Boston house prices.\n\n    Examples\n    --------\n    > var data = PACE_BOSTON_HOUSE_PRICES()\n    [ {...}, {...}, ... ]\n\n    References\n    ----------\n    - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n    the demand for clean air.\" _Journal of Environmental Economics and\n    Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n    - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n    Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n    doi:10.1006/jeem.1996.0052.\n    - Pace, R. Kelley, and Otis W. Gilley. 1997. \"Using the Spatial\n    Configuration of the Data to Improve Estimation.\" _The Journal of Real\n    Estate Finance and Economics_ 14 (3): 333–40. doi:10.1023/A:1007762613901.\n\n    See Also\n    --------\n    HARRISON_BOSTON_HOUSE_PRICES, HARRISON_BOSTON_HOUSE_PRICES_CORRECTED\n","pad":"\npad( str, len[, options] )\n    Pads a `string` such that the padded `string` has length `len`.\n\n    Any padding which does not evenly divide available space is trimmed such\n    that the returned string length is always `len`.\n\n    If `len < str.length`, the input string is trimmed.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    len: integer\n        Output string length.\n\n    options: Object (optional)\n        Options.\n\n    options.lpad: string (optional)\n        String used to left pad.\n\n    options.rpad: string (optional)\n        String used to right pad.\n\n    options.centerRight: boolean (optional)\n        Boolean indicating whether to center right in the event of a tie.\n        Default: `false` (i.e., center left).\n\n    Returns\n    -------\n    out: string\n        Padded string.\n\n    Examples\n    --------\n    // Standard usage:\n    > var out = pad( 'a', 5 )\n    'a    '\n\n    // Left pad:\n    > out = pad( 'a', 10, { 'lpad': 'b' } )\n    'bbbbbbbbba'\n\n    // Right pad:\n    > out = pad( 'a', 12, { 'rpad': 'b' } )\n    'abbbbbbbbbbb'\n\n    // Center an input string:\n    > var opts = { 'lpad': 'a', 'rpad': 'c' };\n    > out = pad( 'b', 11, opts )\n    'aaaaabccccc'\n\n    // Left center:\n    > opts.centerRight = false;\n    > out = pad( 'b', 10, opts )\n    'aaaabccccc'\n\n    // Right center:\n    > opts.centerRight = true;\n    > out = pad( 'b', 10, opts )\n    'aaaaabcccc'\n\n    // Output string always length `len`:\n    > opts = { 'lpad': 'boop', 'rpad': 'woot' };\n    > out = pad( 'beep', 10, opts )\n    'boobeepwoo'\n\n    // Pad right, trim right:\n    > out = pad( 'beep', 2 )\n    'be'\n\n    // Pad left, trim left:\n    > opts = { 'lpad': 'b' };\n    > out = pad( 'beep', 2, opts )\n    'ep'\n\n    // Pad both, trim both:\n    > opts = { 'lpad': '@', 'rpad': '!' };\n    > out = pad( 'beep', 2, opts )\n    'ee'\n\n    // Pad both, trim both starting from left:\n    > out = pad( 'abcdef', 3, opts )\n    'cde'\n\n    // Pad both, trim both starting from right:\n    > opts.centerRight = true;\n    > out = pad( 'abcdef', 3, opts )\n    'bcd'\n\n    See Also\n    --------\n    lpad, rpad\n","padjust":"\npadjust( pvals, method[, comparisons] )\n    Adjusts supplied p-values for multiple comparisons via a specified method.\n\n    The `method` parameter can be one of the following values:\n\n    - bh: Benjamini-Hochberg procedure controlling the False Discovery\n    Rate (FDR).\n    - bonferroni: Bonferroni correction fixing the family-wise error rate\n    by multiplying the p-values with the number of comparisons. The Bonferroni\n    correction is usually a too conservative adjustment compared to the others.\n    - by: Procedure by Benjamini & Yekutieli for controlling the False\n    Discovery Rate (FDR) under dependence.\n    - holm: Hommel's method controlling family-wise error rate. It is\n    uniformly more powerful than the Bonferroni correction.\n    - hommel: Hommel's method, which is valid when hypothesis tests are\n    independent. It is more expensive to compute than the other methods.\n\n    By default, the number of comparisons for which the p-values should be\n    corrected is equal to the number of provided p-values. Alternatively, it is\n    possible to set `comparisons` to a number greater than the length of\n    `pvals`. In that case, the methods assume `comparisons - pvals.length`\n    unobserved p-values that are greater than all observed p-values (for Holm's\n    method and the Bonferroni correction) or equal to `1` for the remaining\n    methods.\n\n    Parameters\n    ----------\n    pvals: Array<number>\n        P-values to be adjusted.\n\n    method: string\n        Correction method.\n\n    comparisons: integer (optional)\n        Number of comparisons. Default value: `pvals.length`.\n\n    Returns\n    -------\n    out: Array<number>\n        Array containing the corrected p-values.\n\n    Examples\n    --------\n    > var pvalues = [ 0.008, 0.03, 0.123, 0.6, 0.2 ];\n    > var out = padjust( pvalues, 'bh' )\n    [ 0.04, 0.075, ~0.205, 0.6, 0.25 ]\n\n    > out = padjust( pvalues, 'bonferroni' )\n    [ 0.04, 0.15, 0.615, 1.0, 1.0 ]\n\n    > out = padjust( pvalues, 'by' )\n    [ ~0.457, ~0.856, 1.0, 1.0, 1.0 ]\n\n    > out = padjust( pvalues, 'holm' )\n    [ 0.2, 0.6, 1.0, 1.0, 1.0 ]\n\n    > out = padjust( pvalues, 'hommel' )\n    [ 0.16, 0.6, 1.0, 1.0, 1.0 ]\n\n","papply":"\npapply( fcn, ...args )\n    Returns a function of smaller arity by partially applying arguments.\n\n    The implementation does not set the `length` property of the returned\n    function. Accordingly, the returned function `length` is always zero.\n\n    The evaluation context is always `null`.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to partially apply.\n\n    args: ...any\n        Arguments to partially apply.\n\n    Returns\n    -------\n    out: Function\n        Partially applied function.\n\n    Examples\n    --------\n    > function add( x, y ) { return x + y; };\n    > var add2 = papply( add, 2 );\n    > var sum = add2( 3 )\n    5\n\n    See Also\n    --------\n    papplyRight\n","papplyRight":"\npapplyRight( fcn, ...args )\n    Returns a function of smaller arity by partially applying arguments from the\n    right.\n\n    The implementation does not set the `length` property of the returned\n    function. Accordingly, the returned function `length` is always zero.\n\n    The evaluation context is always `null`.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to partially apply.\n\n    args: ...any\n        Arguments to partially apply.\n\n    Returns\n    -------\n    out: Function\n        Partially applied function.\n\n    Examples\n    --------\n    > function say( text, name ) { return text + ', ' + name + '.'; };\n    > var toGrace = papplyRight( say, 'Grace Hopper' );\n    > var str = toGrace( 'Hello' )\n    'Hello, Grace Hopper.'\n    > str = toGrace( 'Thank you' )\n    'Thank you, Grace Hopper.'\n\n    See Also\n    --------\n    papply\n","parallel":"\nparallel( files, [options,] clbk )\n    Executes scripts in parallel.\n\n    Relative file paths are resolved relative to the current working directory.\n\n    Ordered script output does not imply that scripts are executed in order. To\n    preserve script order, execute the scripts sequentially via some other\n    means.\n\n    Parameters\n    ----------\n    files: Array<string>\n        Script file paths.\n\n    options: Object (optional)\n        Options.\n\n    options.cmd: string (optional)\n        Executable file/command. Default: `'node'`.\n\n    options.concurrency: integer (optional)\n        Number of scripts to execute concurrently. Script concurrency cannot\n        exceed the number of scripts. By specifying a concurrency greater than\n        the number of workers, a worker may be executing more than `1` script at\n        any one time. While not likely to be advantageous for synchronous\n        scripts, setting a higher concurrency may be advantageous for scripts\n        performing asynchronous tasks. If the script concurrency is less than\n        the number of workers, the number of workers is reduced to match the\n        specified concurrency. Default: `options.workers`.\n\n    options.workers: integer (optional)\n        Number of workers. Default: number of CPUs minus `1`.\n\n    options.ordered: boolean (optional)\n        Boolean indicating whether to preserve the order of script output. By\n        default, the `stdio` output for each script is interleaved; i.e., the\n        `stdio` output from one script may be interleaved with the `stdio`\n        output from one or more other scripts. To preserve the `stdio` output\n        order for each script, set the `ordered` option to `true`. Default:\n        `false`.\n\n    options.uid: integer (optional)\n        Process user identity.\n\n    options.gid: integer (optional)\n        Process group identity.\n\n    options.maxBuffer: integer (optional)\n        Max child process `stdio` buffer size. This option is only applied when\n        `options.ordered = true`. Default: `200*1024*1024`.\n\n    clbk: Function\n        Callback to invoke after executing all scripts.\n\n    Examples\n    --------\n    > function done( error ) { if ( error ) { throw error; } };\n    > var files = [ './a.js', './b.js' ];\n    > parallel( files, done );\n\n    // Specify the number of workers:\n    > var opts = { 'workers': 8 };\n    > parallel( files, opts, done );\n\n","parseJSON":"\nparseJSON( str[, reviver] )\n    Attempts to parse a string as JSON.\n\n    Function behavior differs from `JSON.parse()` as follows:\n\n    - throws a `TypeError` if provided any value which is not a string.\n    - throws a `TypeError` if provided a `reviver` argument which is not a\n      function.\n    - returns, rather than throws, a `SyntaxError` if unable to parse a string\n      as JSON.\n\n    Parameters\n    ----------\n    str: string\n        String to parse.\n\n    reviver: Function (optional)\n        Transformation function.\n\n    Returns\n    -------\n    out: any|Error\n        Parsed value or an error.\n\n    Examples\n    --------\n    > var obj = parseJSON( '{\"beep\":\"boop\"}' )\n    { 'beep': 'boop' }\n\n    // Provide a reviver:\n    > function reviver( key, value ) {\n    ...     if ( key === '' ) { return value; }\n    ...     if ( key === 'beep' ) { return value; }\n    ... };\n    > var str = '{\"beep\":\"boop\",\"a\":\"b\"}';\n    > var out = parseJSON( str, reviver )\n    { 'beep': 'boop' }\n\n","pascalcase":"\npascalcase( str )\n    Converts a string to Pascal case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Pascal-cased string.\n\n    Examples\n    --------\n    > var out = pascalcase( 'Hello World!' )\n    'HelloWorld'\n    > out = pascalcase( 'beep boop' )\n    'BeepBoop'\n\n    See Also\n    --------\n    camelcase, constantcase, kebabcase, snakecase","PATH_DELIMITER":"\nPATH_DELIMITER\n    Platform-specific path delimiter.\n\n    Examples\n    --------\n    > PATH_DELIMITER\n    <string>\n\n    // POSIX environment:\n    > var path = '/usr/bin:/bin:/usr/sbin';\n    > var parts = path.split( PATH_DELIMITER )\n    [ '/usr/bin', '/bin', '/usr/sbin' ]\n\n    // Windows environment:\n    > path = 'C:\\\\Windows\\\\system32;C:\\\\Windows';\n    > parts = path.split( PATH_DELIMITER )\n    [ 'C:\\\\Windows\\system32', 'C:\\\\Windows' ]\n\n    See Also\n    --------\n    PATH_DELIMITER_POSIX, PATH_DELIMITER_WIN32\n","PATH_DELIMITER_POSIX":"\nPATH_DELIMITER_POSIX\n    POSIX path delimiter.\n\n    Examples\n    --------\n    > PATH_DELIMITER_POSIX\n    ':'\n    > var PATH = '/usr/bin:/bin:/usr/sbin:/sbin:/usr/local/bin';\n    > var paths = PATH.split( PATH_DELIMITER_POSIX )\n    [ '/usr/bin', '/bin', '/usr/sbin', '/sbin', '/usr/local/bin' ]\n\n    See Also\n    --------\n    PATH_DELIMITER, PATH_DELIMITER_WIN32\n","PATH_DELIMITER_WIN32":"\nPATH_DELIMITER_WIN32\n    Windows path delimiter.\n\n    Examples\n    --------\n    > PATH_DELIMITER_WIN32\n    ';'\n    > var PATH = 'C:\\\\Windows\\\\system32;C:\\\\Windows;C:\\\\Program Files\\\\node\\\\';\n    > var paths = PATH.split( PATH_DELIMITER_WIN32 )\n    [ 'C:\\\\Windows\\\\system32', 'C:\\\\Windows', 'C:\\\\Program Files\\\\node\\\\' ]\n\n    See Also\n    --------\n    PATH_DELIMITER, PATH_DELIMITER_POSIX\n","PATH_SEP":"\nPATH_SEP\n    Platform-specific path segment separator.\n\n    Examples\n    --------\n    > PATH_SEP\n    <string>\n\n    // Windows environment:\n    > var parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP )\n    [ 'foo', 'bar', 'baz' ]\n\n    // POSIX environment:\n    > parts = 'foo/bar/baz'.split( PATH_SEP )\n    [ 'foo', 'bar', 'baz' ]\n\n    See Also\n    --------\n    PATH_SEP_POSIX, PATH_SEP_WIN32\n","PATH_SEP_POSIX":"\nPATH_SEP_POSIX\n    POSIX path segment separator.\n\n    Examples\n    --------\n    > PATH_SEP_POSIX\n    '/'\n    > var parts = 'foo/bar/baz'.split( PATH_SEP_POSIX )\n    [ 'foo', 'bar', 'baz' ]\n\n    See Also\n    --------\n    PATH_SEP, PATH_SEP_WIN32\n","PATH_SEP_WIN32":"\nPATH_SEP_WIN32\n    Windows path segment separator.\n\n    Examples\n    --------\n    > PATH_SEP_WIN32\n    '\\\\'\n    > var parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP_WIN32 )\n    [ 'foo', 'bar', 'baz' ]\n\n    See Also\n    --------\n    PATH_SEP, PATH_SEP_POSIX\n","pcorrtest":"\npcorrtest( x, y[, options] )\n    Computes a Pearson product-moment correlation test between paired samples.\n\n    By default, the function performs a t-test for the null hypothesis that the\n    data in arrays or typed arrays `x` and `y` is not correlated. A test against\n    a different population correlation can be carried out by supplying the `rho`\n    option. In this case, a test using the Fisher's z transform is conducted.\n\n    The returned object comes with a `.print()` method which when invoked will\n    print a formatted output of the results of the hypothesis test.\n\n    Parameters\n    ----------\n    x: Array<number>\n        First data array.\n\n    y: Array<number>\n        Second data array.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Nnumber in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.alternative: string (optional)\n        Either `two-sided`, `less` or `greater`. Indicates whether the\n        alternative hypothesis is that `x` has a larger mean than `y`\n        (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n        the same (`two-sided`). Default: `'two-sided'`.\n\n    options.rho: number (optional)\n        Number denoting the correlation under the null hypothesis.\n        Default: `0`.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Used significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.ci: Array<number>\n        1-alpha confidence interval for the Pearson product-moment correlation\n        coefficient. The confidence interval is calculated using Fisher's\n        z-transform.\n\n    out.nullValue: number\n        Assumed correlation under H0 (equal to the supplied `rho` option).\n\n    out.alternative: string\n        Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n    out.method: string\n        Name of test.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    > var rho = 0.5;\n    > var x = new Array( 300 );\n    > var y = new Array( 300 );\n    > for ( var i = 0; i < 300; i++ ) {\n    ...    x[ i ] = base.random.normal( 0.0, 1.0 );\n    ...    y[ i ] = ( rho * x[ i ] ) + base.random.normal( 0.0,\n    ...    base.sqrt( 1.0 - (rho*rho) ) );\n    ... }\n    > var out = pcorrtest( x, y )\n    {\n        alpha: 0.05,\n        rejected: true,\n        pValue: 0,\n        statistic: 10.115805615994121,\n        ci: [ 0.4161679018930295, 0.5853122968949995 ],\n        alternative: 'two-sided',\n        method: 't-test for Pearson correlation coefficient',\n        nullValue: 0,\n        pcorr: 0.505582072355616,\n    }\n\n    // Print output:\n    > var table = out.print()\n    t-test for Pearson correlation coefficient\n\n    Alternative hypothesis: True correlation coefficient is not equal to 0\n\n        pValue: 0\n        statistic: 9.2106\n        95% confidence interval: [0.3776,0.5544]\n\n    Test Decision: Reject null in favor of alternative at 5% significance level\n\n","percentEncode":"\npercentEncode( str )\n    Percent-encodes a UTF-16 encoded string according to RFC 3986.\n\n    Parameters\n    ----------\n    str: string\n        UTF-16 encoded string.\n\n    Returns\n    -------\n    out: string\n        Percent-encoded string.\n\n    Examples\n    --------\n    > var out = percentEncode( '☃' )\n    '%E2%98%83'\n\n","PHI":"\nPHI\n    Golden ratio.\n\n    Examples\n    --------\n    > PHI\n    1.618033988749895\n\n","PI":"\nPI\n    The mathematical constant `π`.\n\n    Examples\n    --------\n    > PI\n    3.141592653589793\n\n    See Also\n    --------\n    TWO_PI\n","PI_SQUARED":"\nPI_SQUARED\n    Square of the mathematical constant `π`.\n\n    Examples\n    --------\n    > PI_SQUARED\n    9.869604401089358\n\n    See Also\n    --------\n    PI\n","pick":"\npick( obj, keys )\n    Returns a partial object copy containing only specified keys.\n\n    If a key does not exist as an own property in a source object, the key is\n    ignored.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    keys: string|Array<string>\n        Keys to copy.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > var obj1 = { 'a': 1, 'b': 2 };\n    > var obj2 = pick( obj1, 'b' )\n    { 'b': 2 }\n\n    See Also\n    --------\n    pickBy\n","pickArguments":"\npickArguments( fcn, indices[, thisArg] )\n    Returns a function that applies specified arguments to a provided function.\n\n    Parameters\n    ----------\n    fcn: Function\n        Input function.\n\n    indices: Array<integer>\n        Argument indices.\n\n    thisArg: any (optional)\n        Function context.\n\n    Returns\n    -------\n    out: Function\n        Function wrapper.\n\n    Examples\n    --------\n    > function foo( a, b ) { return [ a, b ]; };\n    > var bar = pickArguments( foo, [ 0, 2 ] );\n    > var out = bar( 1, 2, 3 )\n    [ 1, 3 ]\n\n    See Also\n    --------\n    reorderArguments, reverseArguments\n","pickBy":"\npickBy( obj, predicate )\n    Returns a partial object copy containing properties for which a predicate\n    returns a truthy value.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    predicate: Function\n        Predicate function.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > function predicate( key, value ) {\n    ...     return ( value > 1 );\n    ... };\n    > var obj1 = { 'a': 1, 'b': 2 };\n    > var obj2 = pickBy( obj1, predicate )\n    { 'b': 2 }\n\n    See Also\n    --------\n    pick\n","PINF":"\nPINF\n    Double-precision floating-point positive infinity.\n\n    Examples\n    --------\n    > PINF\n    Infinity\n\n    See Also\n    --------\n    NINF\n","pkg2alias":"\npkg2alias( pkg )\n    Returns the alias associated with a specified package name.\n\n    The function supports both internal and standalone package names.\n\n    Parameters\n    ----------\n    pkg: string\n        Package name.\n\n    Returns\n    -------\n    out: string|null\n        Alias.\n\n    Examples\n    --------\n    > var v = pkg2alias( '@stdlib/math/base/special/sin' )\n    <string>\n    > v = pkg2alias( '@stdlib/math-base-special-sin' )\n    <string>\n\n    See Also\n    --------\n    alias2pkg, aliases, pkg2related\n","pkg2related":"\npkg2related( pkg )\n    Returns package names related to a specified package name.\n\n    The function supports both internal and standalone package names.\n\n    Parameters\n    ----------\n    pkg: string\n        Package name.\n\n    Returns\n    -------\n    out: Array|null\n        Related package names.\n\n    Examples\n    --------\n    > var v = pkg2related( '@stdlib/math/base/special/sin' )\n    [...]\n    > v = pkg2related( '@stdlib/math-base-special-sin' )\n    [...]\n\n    See Also\n    --------\n    alias2related, aliases, pkg2alias\n","pkg2standalone":"\npkg2standalone( pkg )\n    Returns the standalone package name associated with a provided internal\n    package name.\n\n    Parameters\n    ----------\n    pkg: string\n        Package name.\n\n    Returns\n    -------\n    out: string|null\n        Standalone package name.\n\n    Examples\n    --------\n    > var v = pkg2standalone( '@stdlib/math/base/special/sin' )\n    '@stdlib/math-base-special-sin'\n\n    See Also\n    --------\n    alias2pkg, alias2standalone, aliases, pkg2alias, pkg2related\n","PLATFORM":"\nPLATFORM\n    Platform on which the current process is running.\n\n    Possible values:\n\n    - win32\n    - darwin\n    - linux\n    - freebsd\n    - sunos\n\n    Examples\n    --------\n    > PLATFORM\n    <string>\n\n    See Also\n    --------\n    ARCH\n","plot":"\nplot( [x, y,] [options] )\n    Returns a plot instance for creating 2-dimensional plots.\n\n    `x` and `y` arguments take precedence over `x` and `y` options.\n\n    Parameters\n    ----------\n    x: Array<Array>|Array<TypedArray> (optional)\n        An array of arrays containing x-coordinate values.\n\n    y: Array<Array>|Array<TypedArray> (optional)\n        An array of arrays containing y-coordinate values.\n\n    options: Object (optional)\n        Options.\n\n    options.autoRender: boolean (optional)\n        Boolean indicating whether to re-render on a 'change' event. Default:\n        false.\n\n    options.autoView: boolean (optional)\n        Boolean indicating whether to generate an updated view on a 'render'\n        event. Default: false.\n\n    options.colors: string|Array<string> (optional)\n        Data color(s). Default: 'category10'.\n\n    options.description: string (optional)\n        Plot description.\n\n    options.engine: string (optional)\n        Plot engine. Default: 'svg'.\n\n    options.height: number (optional)\n        Plot height (in pixels). Default: 400.\n\n    options.labels: Array|Array<string> (optional)\n        Data labels.\n\n    options.isDefined: Function (optional)\n        An accessor function indicating whether a datum is defined.\n\n    options.lineStyle: string|Array<string> (optional)\n        Data line style(s). Must be one of: '-', '--', ':', '-.', or 'none'.\n        Default: '-'.\n\n    options.lineOpacity: number|Array<number> (optional)\n        Data line opacity. Must be on the interval [0,1]. Default: 0.9.\n\n    options.lineWidth: integer|Array<integer> (optional)\n        Data line width (in pixels). Default: 2.\n\n    options.paddingBottom: integer (optional)\n        Bottom padding (in pixels). Default: 80.\n\n    options.paddingLeft: integer (optional)\n        Left padding (in pixels). Default: 90.\n\n    options.paddingRight: integer (optional)\n        Right padding (in pixels). Default: 20.\n\n    options.paddingTop: integer (optional)\n        Top padding (in pixels). Default: 80.\n\n    options.renderFormat: string (optional)\n        Plot render format. Must be one of 'vdom' or 'html'. Default: 'vdom'.\n\n    options.symbols: string|Array<string> (optional)\n        Data symbols. Must be one of 'closed-circle', 'open-circle', or 'none'.\n        Default: 'none'.\n\n    options.symbolsOpacity: number|Array<number> (optional)\n        Symbols opacity. Must be on the interval [0,1]. Default: 0.9.\n\n    options.symbolsSize: integer|Array<integer> (optional)\n        Symbols size (in pixels). Default: 6.\n\n    options.title: string (optional)\n        Plot title.\n\n    options.viewer: string (optional)\n        Plot viewer. Must be one of 'browser', 'terminal', 'stdout', 'window',\n        or 'none'. Default: 'none'.\n\n    options.width: number (optional)\n        Plot width (in pixels). Default: 400.\n\n    options.x: Array<Array>|Array<TypedArray> (optional)\n        x-coordinate values.\n\n    options.xAxisOrient: string (optional)\n        x-axis orientation. Must be either 'bottom' or 'top'. Default: 'bottom'.\n\n    options.xLabel: string (optional)\n        x-axis label. Default: 'x'.\n\n    options.xMax: number|null (optional)\n        Maximum value of the x-axis domain. If `null`, the maximum value is\n        calculated from the data. Default: null.\n\n    options.xMin: number|null (optional)\n        Minimum value of the x-axis domain. If `null`, the minimum value is\n        calculated from the data. Default: null.\n\n    options.xNumTicks: integer (optional)\n        Number of x-axis tick marks. Default: 5.\n\n    options.xRug: boolean|Array<boolean> (optional)\n        Boolean flag(s) indicating whether to render one or more rug plots along\n        the x-axis.\n\n    options.xRugOrient: string|Array<string> (optional)\n        x-axis rug plot orientation(s). Must be either 'bottom' or 'top'.\n        Default: 'bottom'.\n\n    options.xRugOpacity: number|Array<number> (optional)\n       x-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n    options.xRugSize: integer|Array<integer> (optional)\n       x-axis rug tick (tassel) size (in pixels). Default: 6.\n\n    options.xScale: string\n       x-axis scale. Default: 'linear'.\n\n    options.xTickFormat: string|null\n       x-axis tick format. Default: null.\n\n    options.y: Array<Array>|Array<TypedArray> (optional)\n        y-coordinate values.\n\n    options.yAxisOrient: string (optional)\n        x-axis orientation. Must be either 'left' or 'right'. Default: 'left'.\n\n    options.yLabel: string (optional)\n        y-axis label. Default: 'y'.\n\n    options.yMax: number|null (optional)\n        Maximum value of the y-axis domain. If `null`, the maximum value is\n        calculated from the data. Default: null.\n\n    options.yMin: number|null (optional)\n        Minimum value of the y-axis domain. If `null`, the minimum value is\n        calculated from the data. Default: null.\n\n    options.yNumTicks: integer (optional)\n        Number of x-axis tick marks. Default: 5.\n\n    options.yRug: boolean|Array<boolean> (optional)\n        Boolean flag(s) indicating whether to render one or more rug plots along\n        the y-axis.\n\n    options.yRugOrient: string|Array<string> (optional)\n        y-axis rug plot orientation(s). Must be either 'left' or 'right'.\n        Default: 'left'.\n\n    options.yRugOpacity: number|Array<number> (optional)\n       y-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n    options.yRugSize: integer|Array<integer> (optional)\n       y-axis rug tick (tassel) size (in pixels). Default: 6.\n\n    options.yScale: string\n       y-axis scale. Default: 'linear'.\n\n    options.yTickFormat: string|null\n       y-axis tick format. Default: null.\n\n    Returns\n    -------\n    plot: Plot\n        Plot instance.\n\n    plot.render()\n        Renders a plot as a virtual DOM tree.\n\n    plot.view( [viewer] )\n        Generates a plot view.\n\n    plot.x\n        x-coordinate values. An assigned value must be an array where each\n        element corresponds to a plotted dataset.\n\n    plot.y\n        y-coordinate values. An assigned value must be an array, where each\n        element corresponds to a plotted dataset.\n\n    plot.labels\n        Data labels. During plot creation, each plotted dataset is assigned a\n        label. If the number of labels is less than the number of plotted\n        datasets, labels are reused using modulo arithmetic.\n\n    plot.isDefined( d, i )\n        An accessor function which defines whether a datum is defined. This\n        accessor is used to define how missing values are encoded. The default\n        behavior is to ignore values which are `NaN`.\n\n    plot.colors\n        Data colors. To set the color all plotted datasets, provide a color\n        name. To specify the colors for each dataset, provide an array of\n        colors. During plot creation, each plotted dataset is assigned one of\n        the provided colors. If the number of colors is less than the number of\n        plotted datasets, colors are reused using modulo arithmetic. Lastly,\n        colors may also be specified by providing the name of a predefined color\n        scheme. The following schemes are supported: 'category10', 'category20',\n        'category20b', and 'category20c'.\n\n    plot.lineStyle\n        Data line style(s). The following line styles are supported: '-' (solid\n        line), '--' (dashed line), ':' (dotted line), '-.' (alternating dashes\n        and dots), and 'none' (no line). To specify the line style for each\n        dataset, provide an array of line styles. During plot creation, each\n        plotted dataset is assigned a line style. If the number of line styles\n        is less than the number of plotted datasets, line styles are reused\n        using modulo arithmetic.\n\n    plot.lineOpacity\n        Data line opacity, where an opacity of `0.0` make a line completely\n        transparent and an opacity of `1.0` makes a line completely opaque. To\n        specify the line opacity for each dataset, provide an array of\n        opacities. During plot creation, each plotted dataset is assigned an\n        opacity. If the number of opacities is less than the number of plotted\n        datasets, opacities are reused using modulo arithmetic.\n\n    plot.lineWidth\n        Data line width(s). To specify the line width for each dataset, provide\n        an array of widths. During plot creation, each plotted dataset is\n        assigned a line width. If the number of line widths is less than the\n        number of plotted datasets, line widths are reused using modulo\n        arithmetic.\n\n    plot.symbols\n        Data symbols. The following symbols are supported: 'closed-circle'\n        (closed circles), 'open-circle' (open circles), and 'none' (no symbols).\n        To specify the symbols used for each dataset, provide an array of\n        symbols. During plot creation, each plotted dataset is assigned a\n        symbol. If the number of symbols is less than the number of plotted\n        datasets, symbols are reused using modulo arithmetic.\n\n    plot.symbolSize\n        Symbols size. To specify the symbols size for each dataset, provide an\n        array of sizes. During plot creation, each plotted dataset is assigned\n        a symbols size. If the number of sizes is less than the number of\n        plotted datasets, sizes are reused using modulo arithmetic.\n\n    plot.symbolsOpacity\n        Symbols opacity, where an opacity of `0.0` makes a symbol completely\n        transparent and an opacity of `1.0` makes a symbol completely opaque. To\n        specify the opacity for each dataset, provide an array of opacities.\n        During plot creation, each plotted dataset is assigned an opacity. If\n        the number of opacities is less than the number of plotted datasets,\n        opacities are reused using modulo arithmetic.\n\n    plot.width\n        Plot width (in pixels).\n\n    plot.height\n        Plot height (in pixels).\n\n    plot.paddingLeft\n        Plot left padding (in pixels). Left padding is typically used to create\n        space for a left-oriented y-axis.\n\n    plot.paddingRight\n        Plot right padding (in pixels). Right padding is typically used to\n        create space for a right-oriented y-axis.\n\n    plot.paddingTop\n        Plot top padding (in pixels). Top padding is typically used to create\n        space for a title or top-oriented x-axis.\n\n    plot.paddingBottom\n        Plot bottom padding (in pixels). Bottom padding is typically used to\n        create space for a bottom-oriented x-axis.\n\n    plot.xMin\n        Minimum value of the x-axis domain. When retrieved, if the value has\n        been set to `null`, the returned value is computed from the `x` data.\n\n    plot.xMax\n        Maximum value of the x-axis domain. When retrieved, if the value has\n        been set to `null`, the returned value is computed from the `x` data.\n\n    plot.yMin\n        Minimum value of the y-axis domain. When retrieved, if the value has\n        been set to `null`, the returned value is computed from the `y` data.\n\n    plot.yMax\n        Maximum value of the y-axis domain. When retrieved, if the value has\n        been set to `null`, the returned value is computed from the `y` data.\n\n    plot.xScale\n        Scale function for mapping values to a coordinate along the x-axis. The\n        following `scales` are supported: 'linear' (linear scale) and 'time'\n        (time scale). When retrieved, the returned value is a scale function.\n\n    plot.yScale\n        Scale function for mapping values to a coordinate along the y-axis. The\n        following `scales` are supported: 'linear' (linear scale) and 'time'\n        (time scale). When retrieved, the returned value is a scale function.\n\n    plot.xTickFormat\n        x-axis tick format (e.g., '%H:%M'). When retrieved, if the value has not\n        been set to `null`, the returned value is a formatting function.\n\n    plot.yTickFormat\n        y-axis tick format (e.g., '%%'). When retrieved, if the value has not\n        been set to `null`, the returned value is a formatting function.\n\n    plot.xNumTicks\n        Number of x-axis tick marks. If the value is set to `null`, the number\n        of tick marks is computed internally.\n\n    plot.yNumTicks\n        Number of y-axis tick marks. If the value is set to `null`, the number\n        of tick marks is computed internally.\n\n    plot.xAxisOrient\n        x-axis orientation. The following orientations are supported: 'bottom'\n        and 'top'.\n\n    plot.yAxisOrient\n        y-axis orientation. The following orientations are supported: 'left' and\n        'right'.\n\n    plot.xRug\n        Boolean flag(s) indicating whether to display a rug plot along the x-\n        axis. To specify the flag for each dataset, provide an array of\n        booleans. During plot creation, each plotted dataset is assigned a flag.\n        If the number of flags is less than the number of plotted datasets,\n        flags are reused using modulo arithmetic.\n\n    plot.yRug\n        Boolean flag(s) indicating whether to display a rug plot along the y-\n        axis. To specify the flag for each dataset, provide an array of\n        booleans. During plot creation, each plotted dataset is assigned a flag.\n        If the number of flags is less than the number of plotted datasets,\n        flags are reused using modulo arithmetic.\n\n    plot.xRugOrient\n        x-axis rug orientation. The following orientations are supported:\n        'bottom' or 'top'. To specify the x-axis rug orientation for each\n        dataset, provide an array of orientations. During plot creation, each\n        plotted dataset is assigned an orientation. If the number of\n        orientations is less than the number of plotted datasets, orientations\n        are reused using modulo arithmetic.\n\n    plot.yRugOrient\n        y-axis rug orientation. The following orientations are supported: 'left'\n        or 'right'. To specify the y-axis rug orientation for each dataset,\n        provide an array of orientations. During plot creation, each plotted\n        dataset is assigned an orientation. If the number of orientations is\n        less than the number of plotted datasets, orientations are reused using\n        modulo arithmetic.\n\n    plot.xRugOpacity\n        x-axis rug opacity, where an opacity of `0.0` makes a rug completely\n        transparent and an opacity of `1.0` makes a rug completely opaque. To\n        specify the x-axis rug opacity for each dataset, provide an array of\n        opacities. During plot creation, each plotted dataset is assigned an\n        opacity. If the number of opacities is less than the number of plotted\n        datasets, opacities are reused using modulo arithmetic.\n\n    plot.yRugOpacity\n        y-axis rug opacity, where an opacity of `0.0` makes a rug completely\n        transparent and an opacity of `1.0` makes a rug completely opaque. To\n        specify the y-axis rug opacity for each dataset, provide an array of\n        opacities. During plot creation, each plotted dataset is assigned an\n        opacity. If the number of opacities is less than the number of plotted\n        datasets, opacities are reused using modulo arithmetic.\n\n    plot.xRugSize\n        x-axis rug tick (tassel) size. To specify the x-axis rug size for each\n        dataset, provide an array of sizes. During plot creation, each plotted\n        dataset is assigned a tick size. If the number of sizes is less than the\n        number of plotted datasets, sizes are reused using modulo arithmetic.\n\n    plot.yRugSize\n        y-axis rug tick (tassel) size. To specify the y-axis rug size for each\n        dataset, provide an array of sizes. During plot creation, each plotted\n        dataset is assigned a tick size. If the number of sizes is less than the\n        number of plotted datasets, sizes are reused using modulo arithmetic.\n\n    plot.description\n        Plot description.\n\n    plot.title\n        Plot title.\n\n    plot.xLabel\n        x-axis label.\n\n    plot.yLabel\n        y-axis label.\n\n    plot.engine\n        Plot rendering engine. The following engines are supported: 'svg'.\n\n    plot.renderFormat\n        Plot render format. The following formats are supported: 'vdom' and\n        'html'.\n\n    plot.autoRender\n        Rendering mode. If `true`, an instance renders on each 'change' event;\n        otherwise, rendering must be triggered manually.\n\n    plot.viewer\n        Plot viewer. The following viewers are supported: 'none', 'stdout',\n        'window', and 'browser'.\n\n    plot.autoView\n        Viewer mode. If `true`, an instance generates an updated view on each\n        'render' event; otherwise, generating a view must be triggered manually.\n\n    plot.graphWidth\n        Computed property corresponding to the expected graph width.\n\n    plot.graphHeight\n        Computed property corresponding to the expected graph height.\n\n    plot.xDomain\n        Computed property corresponding to the x-axis domain.\n\n    plot.yDomain\n        Computed property corresponding to the y-axis domain.\n\n    plot.xRange\n        Computed property corresponding to the x-axis range.\n\n    plot.yRange\n        Computed property correspond to the y-axis range.\n\n    plot.xPos\n        A function which maps values to x-axis coordinate values.\n\n    plot.yPos\n        A function which maps values to y-axis coordinate values.\n\n    Examples\n    --------\n    > var plot = plot()\n    <Plot>\n\n    // Provide plot data at instantiation:\n    > var x = [[0.10, 0.20, 0.30]];\n    > var y = [[0.52, 0.79, 0.64]];\n    > plot = plot( x, y )\n    <Plot>\n\n    See Also\n    --------\n    Plot\n","Plot":"\nPlot( [x, y,] [options] )\n    Returns a plot instance for creating 2-dimensional plots.\n\n    `x` and `y` arguments take precedence over `x` and `y` options.\n\n    Parameters\n    ----------\n    x: Array<Array>|Array<TypedArray> (optional)\n        An array of arrays containing x-coordinate values.\n\n    y: Array<Array>|Array<TypedArray> (optional)\n        An array of arrays containing y-coordinate values.\n\n    options: Object (optional)\n        Options.\n\n    options.autoRender: boolean (optional)\n        Boolean indicating whether to re-render on a 'change' event. Default:\n        false.\n\n    options.autoView: boolean (optional)\n        Boolean indicating whether to generate an updated view on a 'render'\n        event. Default: false.\n\n    options.colors: string|Array<string> (optional)\n        Data color(s). Default: 'category10'.\n\n    options.description: string (optional)\n        Plot description.\n\n    options.engine: string (optional)\n        Plot engine. Default: 'svg'.\n\n    options.height: number (optional)\n        Plot height (in pixels). Default: 400.\n\n    options.labels: Array|Array<string> (optional)\n        Data labels.\n\n    options.isDefined: Function (optional)\n        An accessor function indicating whether a datum is defined.\n\n    options.lineStyle: string|Array<string> (optional)\n        Data line style(s). Must be one of: '-', '--', ':', '-.', or 'none'.\n        Default: '-'.\n\n    options.lineOpacity: number|Array<number> (optional)\n        Data line opacity. Must be on the interval [0,1]. Default: 0.9.\n\n    options.lineWidth: integer|Array<integer> (optional)\n        Data line width (in pixels). Default: 2.\n\n    options.paddingBottom: integer (optional)\n        Bottom padding (in pixels). Default: 80.\n\n    options.paddingLeft: integer (optional)\n        Left padding (in pixels). Default: 90.\n\n    options.paddingRight: integer (optional)\n        Right padding (in pixels). Default: 20.\n\n    options.paddingTop: integer (optional)\n        Top padding (in pixels). Default: 80.\n\n    options.renderFormat: string (optional)\n        Plot render format. Must be one of 'vdom' or 'html'. Default: 'vdom'.\n\n    options.symbols: string|Array<string> (optional)\n        Data symbols. Must be one of 'closed-circle', 'open-circle', or 'none'.\n        Default: 'none'.\n\n    options.symbolsOpacity: number|Array<number> (optional)\n        Symbols opacity. Must be on the interval [0,1]. Default: 0.9.\n\n    options.symbolsSize: integer|Array<integer> (optional)\n        Symbols size (in pixels). Default: 6.\n\n    options.title: string (optional)\n        Plot title.\n\n    options.viewer: string (optional)\n        Plot viewer. Must be one of 'browser', 'terminal', 'stdout', 'window',\n        or 'none'. Default: 'none'.\n\n    options.width: number (optional)\n        Plot width (in pixels). Default: 400.\n\n    options.x: Array<Array>|Array<TypedArray> (optional)\n        x-coordinate values.\n\n    options.xAxisOrient: string (optional)\n        x-axis orientation. Must be either 'bottom' or 'top'. Default: 'bottom'.\n\n    options.xLabel: string (optional)\n        x-axis label. Default: 'x'.\n\n    options.xMax: number|null (optional)\n        Maximum value of the x-axis domain. If `null`, the maximum value is\n        calculated from the data. Default: null.\n\n    options.xMin: number|null (optional)\n        Minimum value of the x-axis domain. If `null`, the minimum value is\n        calculated from the data. Default: null.\n\n    options.xNumTicks: integer (optional)\n        Number of x-axis tick marks. Default: 5.\n\n    options.xRug: boolean|Array<boolean> (optional)\n        Boolean flag(s) indicating whether to render one or more rug plots along\n        the x-axis.\n\n    options.xRugOrient: string|Array<string> (optional)\n        x-axis rug plot orientation(s). Must be either 'bottom' or 'top'.\n        Default: 'bottom'.\n\n    options.xRugOpacity: number|Array<number> (optional)\n       x-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n    options.xRugSize: integer|Array<integer> (optional)\n       x-axis rug tick (tassel) size (in pixels). Default: 6.\n\n    options.xScale: string\n       x-axis scale. Default: 'linear'.\n\n    options.xTickFormat: string|null\n       x-axis tick format. Default: null.\n\n    options.y: Array<Array>|Array<TypedArray> (optional)\n        y-coordinate values.\n\n    options.yAxisOrient: string (optional)\n        x-axis orientation. Must be either 'left' or 'right'. Default: 'left'.\n\n    options.yLabel: string (optional)\n        y-axis label. Default: 'y'.\n\n    options.yMax: number|null (optional)\n        Maximum value of the y-axis domain. If `null`, the maximum value is\n        calculated from the data. Default: null.\n\n    options.yMin: number|null (optional)\n        Minimum value of the y-axis domain. If `null`, the minimum value is\n        calculated from the data. Default: null.\n\n    options.yNumTicks: integer (optional)\n        Number of x-axis tick marks. Default: 5.\n\n    options.yRug: boolean|Array<boolean> (optional)\n        Boolean flag(s) indicating whether to render one or more rug plots along\n        the y-axis.\n\n    options.yRugOrient: string|Array<string> (optional)\n        y-axis rug plot orientation(s). Must be either 'left' or 'right'.\n        Default: 'left'.\n\n    options.yRugOpacity: number|Array<number> (optional)\n       y-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n    options.yRugSize: integer|Array<integer> (optional)\n       y-axis rug tick (tassel) size (in pixels). Default: 6.\n\n    options.yScale: string\n       y-axis scale. Default: 'linear'.\n\n    options.yTickFormat: string|null\n       y-axis tick format. Default: null.\n\n    Returns\n    -------\n    plot: Plot\n        Plot instance.\n\n    plot.render()\n        Renders a plot as a virtual DOM tree.\n\n    plot.view( [viewer] )\n        Generates a plot view.\n\n    plot.x\n        x-coordinate values. An assigned value must be an array where each\n        element corresponds to a plotted dataset.\n\n    plot.y\n        y-coordinate values. An assigned value must be an array, where each\n        element corresponds to a plotted dataset.\n\n    plot.labels\n        Data labels. During plot creation, each plotted dataset is assigned a\n        label. If the number of labels is less than the number of plotted\n        datasets, labels are reused using modulo arithmetic.\n\n    plot.isDefined( d, i )\n        An accessor function which defines whether a datum is defined. This\n        accessor is used to define how missing values are encoded. The default\n        behavior is to ignore values which are `NaN`.\n\n    plot.colors\n        Data colors. To set the color all plotted datasets, provide a color\n        name. To specify the colors for each dataset, provide an array of\n        colors. During plot creation, each plotted dataset is assigned one of\n        the provided colors. If the number of colors is less than the number of\n        plotted datasets, colors are reused using modulo arithmetic. Lastly,\n        colors may also be specified by providing the name of a predefined color\n        scheme. The following schemes are supported: 'category10', 'category20',\n        'category20b', and 'category20c'.\n\n    plot.lineStyle\n        Data line style(s). The following line styles are supported: '-' (solid\n        line), '--' (dashed line), ':' (dotted line), '-.' (alternating dashes\n        and dots), and 'none' (no line). To specify the line style for each\n        dataset, provide an array of line styles. During plot creation, each\n        plotted dataset is assigned a line style. If the number of line styles\n        is less than the number of plotted datasets, line styles are reused\n        using modulo arithmetic.\n\n    plot.lineOpacity\n        Data line opacity, where an opacity of `0.0` make a line completely\n        transparent and an opacity of `1.0` makes a line completely opaque. To\n        specify the line opacity for each dataset, provide an array of\n        opacities. During plot creation, each plotted dataset is assigned an\n        opacity. If the number of opacities is less than the number of plotted\n        datasets, opacities are reused using modulo arithmetic.\n\n    plot.lineWidth\n        Data line width(s). To specify the line width for each dataset, provide\n        an array of widths. During plot creation, each plotted dataset is\n        assigned a line width. If the number of line widths is less than the\n        number of plotted datasets, line widths are reused using modulo\n        arithmetic.\n\n    plot.symbols\n        Data symbols. The following symbols are supported: 'closed-circle'\n        (closed circles), 'open-circle' (open circles), and 'none' (no symbols).\n        To specify the symbols used for each dataset, provide an array of\n        symbols. During plot creation, each plotted dataset is assigned a\n        symbol. If the number of symbols is less than the number of plotted\n        datasets, symbols are reused using modulo arithmetic.\n\n    plot.symbolSize\n        Symbols size. To specify the symbols size for each dataset, provide an\n        array of sizes. During plot creation, each plotted dataset is assigned\n        a symbols size. If the number of sizes is less than the number of\n        plotted datasets, sizes are reused using modulo arithmetic.\n\n    plot.symbolsOpacity\n        Symbols opacity, where an opacity of `0.0` makes a symbol completely\n        transparent and an opacity of `1.0` makes a symbol completely opaque. To\n        specify the opacity for each dataset, provide an array of opacities.\n        During plot creation, each plotted dataset is assigned an opacity. If\n        the number of opacities is less than the number of plotted datasets,\n        opacities are reused using modulo arithmetic.\n\n    plot.width\n        Plot width (in pixels).\n\n    plot.height\n        Plot height (in pixels).\n\n    plot.paddingLeft\n        Plot left padding (in pixels). Left padding is typically used to create\n        space for a left-oriented y-axis.\n\n    plot.paddingRight\n        Plot right padding (in pixels). Right padding is typically used to\n        create space for a right-oriented y-axis.\n\n    plot.paddingTop\n        Plot top padding (in pixels). Top padding is typically used to create\n        space for a title or top-oriented x-axis.\n\n    plot.paddingBottom\n        Plot bottom padding (in pixels). Bottom padding is typically used to\n        create space for a bottom-oriented x-axis.\n\n    plot.xMin\n        Minimum value of the x-axis domain. When retrieved, if the value has\n        been set to `null`, the returned value is computed from the `x` data.\n\n    plot.xMax\n        Maximum value of the x-axis domain. When retrieved, if the value has\n        been set to `null`, the returned value is computed from the `x` data.\n\n    plot.yMin\n        Minimum value of the y-axis domain. When retrieved, if the value has\n        been set to `null`, the returned value is computed from the `y` data.\n\n    plot.yMax\n        Maximum value of the y-axis domain. When retrieved, if the value has\n        been set to `null`, the returned value is computed from the `y` data.\n\n    plot.xScale\n        Scale function for mapping values to a coordinate along the x-axis. The\n        following `scales` are supported: 'linear' (linear scale) and 'time'\n        (time scale). When retrieved, the returned value is a scale function.\n\n    plot.yScale\n        Scale function for mapping values to a coordinate along the y-axis. The\n        following `scales` are supported: 'linear' (linear scale) and 'time'\n        (time scale). When retrieved, the returned value is a scale function.\n\n    plot.xTickFormat\n        x-axis tick format (e.g., '%H:%M'). When retrieved, if the value has not\n        been set to `null`, the returned value is a formatting function.\n\n    plot.yTickFormat\n        y-axis tick format (e.g., '%%'). When retrieved, if the value has not\n        been set to `null`, the returned value is a formatting function.\n\n    plot.xNumTicks\n        Number of x-axis tick marks. If the value is set to `null`, the number\n        of tick marks is computed internally.\n\n    plot.yNumTicks\n        Number of y-axis tick marks. If the value is set to `null`, the number\n        of tick marks is computed internally.\n\n    plot.xAxisOrient\n        x-axis orientation. The following orientations are supported: 'bottom'\n        and 'top'.\n\n    plot.yAxisOrient\n        y-axis orientation. The following orientations are supported: 'left' and\n        'right'.\n\n    plot.xRug\n        Boolean flag(s) indicating whether to display a rug plot along the x-\n        axis. To specify the flag for each dataset, provide an array of\n        booleans. During plot creation, each plotted dataset is assigned a flag.\n        If the number of flags is less than the number of plotted datasets,\n        flags are reused using modulo arithmetic.\n\n    plot.yRug\n        Boolean flag(s) indicating whether to display a rug plot along the y-\n        axis. To specify the flag for each dataset, provide an array of\n        booleans. During plot creation, each plotted dataset is assigned a flag.\n        If the number of flags is less than the number of plotted datasets,\n        flags are reused using modulo arithmetic.\n\n    plot.xRugOrient\n        x-axis rug orientation. The following orientations are supported:\n        'bottom' or 'top'. To specify the x-axis rug orientation for each\n        dataset, provide an array of orientations. During plot creation, each\n        plotted dataset is assigned an orientation. If the number of\n        orientations is less than the number of plotted datasets, orientations\n        are reused using modulo arithmetic.\n\n    plot.yRugOrient\n        y-axis rug orientation. The following orientations are supported: 'left'\n        or 'right'. To specify the y-axis rug orientation for each dataset,\n        provide an array of orientations. During plot creation, each plotted\n        dataset is assigned an orientation. If the number of orientations is\n        less than the number of plotted datasets, orientations are reused using\n        modulo arithmetic.\n\n    plot.xRugOpacity\n        x-axis rug opacity, where an opacity of `0.0` makes a rug completely\n        transparent and an opacity of `1.0` makes a rug completely opaque. To\n        specify the x-axis rug opacity for each dataset, provide an array of\n        opacities. During plot creation, each plotted dataset is assigned an\n        opacity. If the number of opacities is less than the number of plotted\n        datasets, opacities are reused using modulo arithmetic.\n\n    plot.yRugOpacity\n        y-axis rug opacity, where an opacity of `0.0` makes a rug completely\n        transparent and an opacity of `1.0` makes a rug completely opaque. To\n        specify the y-axis rug opacity for each dataset, provide an array of\n        opacities. During plot creation, each plotted dataset is assigned an\n        opacity. If the number of opacities is less than the number of plotted\n        datasets, opacities are reused using modulo arithmetic.\n\n    plot.xRugSize\n        x-axis rug tick (tassel) size. To specify the x-axis rug size for each\n        dataset, provide an array of sizes. During plot creation, each plotted\n        dataset is assigned a tick size. If the number of sizes is less than the\n        number of plotted datasets, sizes are reused using modulo arithmetic.\n\n    plot.yRugSize\n        y-axis rug tick (tassel) size. To specify the y-axis rug size for each\n        dataset, provide an array of sizes. During plot creation, each plotted\n        dataset is assigned a tick size. If the number of sizes is less than the\n        number of plotted datasets, sizes are reused using modulo arithmetic.\n\n    plot.description\n        Plot description.\n\n    plot.title\n        Plot title.\n\n    plot.xLabel\n        x-axis label.\n\n    plot.yLabel\n        y-axis label.\n\n    plot.engine\n        Plot rendering engine. The following engines are supported: 'svg'.\n\n    plot.renderFormat\n        Plot render format. The following formats are supported: 'vdom' and\n        'html'.\n\n    plot.autoRender\n        Rendering mode. If `true`, an instance renders on each 'change' event;\n        otherwise, rendering must be triggered manually.\n\n    plot.viewer\n        Plot viewer. The following viewers are supported: 'none', 'stdout',\n        'window', and 'browser'.\n\n    plot.autoView\n        Viewer mode. If `true`, an instance generates an updated view on each\n        'render' event; otherwise, generating a view must be triggered manually.\n\n    plot.graphWidth\n        Computed property corresponding to the expected graph width.\n\n    plot.graphHeight\n        Computed property corresponding to the expected graph height.\n\n    plot.xDomain\n        Computed property corresponding to the x-axis domain.\n\n    plot.yDomain\n        Computed property corresponding to the y-axis domain.\n\n    plot.xRange\n        Computed property corresponding to the x-axis range.\n\n    plot.yRange\n        Computed property correspond to the y-axis range.\n\n    plot.xPos\n        A function which maps values to x-axis coordinate values.\n\n    plot.yPos\n        A function which maps values to y-axis coordinate values.\n\n    Examples\n    --------\n    > var plot = Plot()\n    <Plot>\n\n    // Provide plot data at instantiation:\n    > var x = [[0.10, 0.20, 0.30]];\n    > var y = [[0.52, 0.79, 0.64]];\n    > plot = Plot( x, y )\n    <Plot>\n\n    See Also\n    --------\n    plot\n","pluck":"\npluck( arr, prop[, options] )\n    Extracts a property value from each element of an object array.\n\n    The function skips `null` and `undefined` array elements.\n\n    Extracted values are not cloned.\n\n    Parameters\n    ----------\n    arr: Array\n        Source array.\n\n    prop: string\n        Property to access.\n\n    options: Object (optional)\n        Options.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to return a new data structure. To mutate the\n        input data structure (e.g., when input values can be discarded or when\n        optimizing memory usage), set the `copy` option to `false`. Default:\n        true.\n\n    Returns\n    -------\n    out: Array\n        Destination array.\n\n    Examples\n    --------\n    > var arr = [\n    ...     { 'a': 1, 'b': 2 },\n    ...     { 'a': 0.5, 'b': 3 }\n    ... ];\n    > var out = pluck( arr, 'a' )\n    [ 1, 0.5 ]\n\n    > arr = [\n    ...     { 'a': 1, 'b': 2 },\n    ...     { 'a': 0.5, 'b': 3 }\n    ... ];\n    > out = pluck( arr, 'a', { 'copy': false } )\n    [ 1, 0.5 ]\n    > var bool = ( arr[ 0 ] === out[ 0 ] )\n    true\n\n    See Also\n    --------\n    deepPluck, pick\n","pop":"\npop( collection )\n    Removes and returns the last element of a collection.\n\n    The function returns an array with two elements: the shortened collection\n    and the removed element.\n\n    If the input collection is a typed array whose length is greater than `0`,\n    the first return value does not equal the input reference.\n\n    For purposes of generality, always treat the output collection as distinct\n    from the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        A collection. If the collection is an `Object`, the value should be\n        array-like.\n\n    Returns\n    -------\n    out: Array\n        Updated collection and the removed item.\n\n    Examples\n    --------\n    // Arrays:\n    > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > var out = pop( arr )\n    [ [ 1.0, 2.0, 3.0, 4.0 ], 5.0 ]\n\n    // Typed arrays:\n    > arr = new Float64Array( [ 1.0, 2.0 ] );\n    > out = pop( arr )\n    [ <Float64Array>[ 1.0 ], 2.0 ]\n\n    // Array-like object:\n    > arr = { 'length': 2, '0': 1.0, '1': 2.0 };\n    > out = pop( arr )\n    [ { 'length': 1, '0': 1.0 }, 2.0 ]\n\n    See Also\n    --------\n    push, shift, unshift\n","porterStemmer":"\nporterStemmer( word )\n    Extracts the stem of a given word.\n\n    Parameters\n    ----------\n    word: string\n        Input word.\n\n    Returns\n    -------\n    out: string\n        Word stem.\n\n    Examples\n    --------\n    > var out = porterStemmer( 'walking' )\n    'walk'\n    > out = porterStemmer( 'walked' )\n    'walk'\n    > out = porterStemmer( 'walks' )\n    'walk'\n    > out = porterStemmer( '' )\n    ''\n\n","prepend":"\nprepend( collection1, collection2 )\n    Adds the elements of one collection to the beginning of another collection.\n\n    If the input collection is a typed array, the output value does not equal\n    the input reference and the underlying `ArrayBuffer` may *not* be the same\n    as the `ArrayBuffer` belonging to the input view.\n\n    For purposes of generality, always treat the output collection as distinct\n    from the input collection.\n\n    Parameters\n    ----------\n    collection1: Array|TypedArray|Object\n        A collection. If the collection is an `Object`, the collection should be\n        array-like.\n\n    collection2: Array|TypedArray|Object\n        A collection containing the elements to add. If the collection is an\n        `Object`, the collection should be array-like.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Updated collection.\n\n    Examples\n    --------\n    // Arrays:\n    > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > arr = prepend( arr, [ 6.0, 7.0 ] )\n    [ 6.0, 7.0, 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Typed arrays:\n    > arr = new Float64Array( [ 1.0, 2.0 ] );\n    > arr = prepend( arr, [ 3.0, 4.0 ] )\n    <Float64Array>[ 3.0, 4.0, 1.0, 2.0 ]\n\n    // Array-like object:\n    > arr = { 'length': 1, '0': 1.0 };\n    > arr = prepend( arr, [ 2.0, 3.0 ] )\n    { 'length': 3, '0': 2.0, '1': 3.0, '2': 1.0 }\n\n    See Also\n    --------\n    append, unshift\n","prevGraphemeClusterBreak":"\nprevGraphemeClusterBreak( str[, fromIndex] )\n    Returns the previous extended grapheme cluster break in a string before a\n    specified position.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    fromIndex: integer (optional)\n        Position. Default: str.length-1.\n\n    Returns\n    -------\n    out: integer\n        Previous extended grapheme cluster break position.\n\n    Examples\n    --------\n    > var out = prevGraphemeClusterBreak( 'last man standing', 4 )\n    3\n    > out = prevGraphemeClusterBreak( 'presidential election', 8 )\n    7\n    > out = prevGraphemeClusterBreak( 'अनुच्छेद', 2 )\n    0\n    > out = prevGraphemeClusterBreak( '🌷', 1 )\n    -1\n\n    See Also\n    --------\n    numGraphemeClusters, nextGraphemeClusterBreak","PRIMES_100K":"\nPRIMES_100K()\n    Returns an array containing the first 100,000 prime numbers.\n\n    Returns\n    -------\n    out: Array<number>\n        List of primes.\n\n    Examples\n    --------\n    > var list = PRIMES_100K()\n    [ 2, 3, 5, ... ]\n\n    See Also\n    --------\n    iterPrimesSeq\n","properties":"\nproperties( value )\n    Returns an array of an object's own enumerable and non-enumerable property\n    names and symbols.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    props: Array\n        List of an object's own enumerable and non-enumerable properties.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var props = properties( obj )\n    [ 'beep' ]\n\n    See Also\n    --------\n    defineProperties, inheritedProperties, propertiesIn, propertyNames, propertySymbols\n","propertiesIn":"\npropertiesIn( value )\n    Returns an array of an object's own and inherited property names and\n    symbols.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    props: Array\n        List of an object's own and inherited property names and symbols.\n\n    Examples\n    --------\n    > var props = propertiesIn( [] )\n\n    See Also\n    --------\n    defineProperties, inheritedProperties, properties, propertyNamesIn, propertySymbolsIn\n","propertyDescriptor":"\npropertyDescriptor( value, property )\n    Returns a property descriptor for an object's own property.\n\n    If provided `null` or `undefined` or provided a non-existent property, the\n    function returns `null`.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    property: string|symbol\n        Property name.\n\n    Returns\n    -------\n    desc: Object|null\n        Property descriptor.\n\n    Examples\n    --------\n    > var obj = { 'a': 'b' };\n    > var desc = propertyDescriptor( obj, 'a' )\n    {...}\n\n    See Also\n    --------\n    hasOwnProp, defineProperty, propertyDescriptorIn, propertyDescriptors\n","propertyDescriptorIn":"\npropertyDescriptorIn( value, property )\n    Returns a property descriptor for an object's own or inherited property.\n\n    If provided `null` or `undefined` or provided a non-existent property, the\n    function returns `null`.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    property: string|symbol\n        Property name.\n\n    Returns\n    -------\n    desc: Object|null\n        Property descriptor.\n\n    Examples\n    --------\n    > var obj = { 'a': 'b' };\n    > var desc = propertyDescriptorIn( obj, 'a' )\n    {...}\n\n    See Also\n    --------\n    hasProp, defineProperty, propertyDescriptor, propertyDescriptorsIn\n","propertyDescriptors":"\npropertyDescriptors( value )\n    Returns an object's own property descriptors.\n\n    If provided `null` or `undefined`, the function returns an empty object.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    desc: Object\n        Property descriptors.\n\n    Examples\n    --------\n    > var obj = { 'a': 'b' };\n    > var desc = propertyDescriptors( obj )\n    { 'a': {...} }\n\n    See Also\n    --------\n    defineProperty, defineProperties, propertyDescriptor, propertyDescriptorsIn, propertyNames, propertySymbols\n","propertyDescriptorsIn":"\npropertyDescriptorsIn( value )\n    Returns an object's own and inherited property descriptors.\n\n    If provided `null` or `undefined`, the function returns an empty object.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    desc: Object\n        An object's own and inherited property descriptors.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var desc = propertyDescriptorsIn( obj )\n    { 'beep': {...}, 'foo': {...}, ... }\n\n    See Also\n    --------\n    defineProperties, propertyDescriptorIn, propertyDescriptors, propertyNamesIn, propertySymbolsIn\n","propertyNames":"\npropertyNames( value )\n    Returns an array of an object's own enumerable and non-enumerable property\n    names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's own enumerable and non-enumerable property names.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var keys = propertyNames( obj )\n    [ 'beep' ]\n\n    See Also\n    --------\n    objectKeys, nonEnumerablePropertyNames, propertyNamesIn, propertySymbols\n","propertyNamesIn":"\npropertyNamesIn( value )\n    Returns an array of an object's own and inherited enumerable and non-\n    enumerable property names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's own and inherited enumerable and non-enumerable\n        property names.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var keys = propertyNamesIn( obj )\n    e.g., [ 'beep', 'foo', ... ]\n\n    See Also\n    --------\n    objectKeys, nonEnumerablePropertyNamesIn, propertyNames, propertySymbolsIn\n","propertySymbols":"\npropertySymbols( value )\n    Returns an array of an object's own symbol properties.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's own symbol properties.\n\n    Examples\n    --------\n    > var s = propertySymbols( {} )\n\n    See Also\n    --------\n    propertyNames, propertySymbolsIn\n","propertySymbolsIn":"\npropertySymbolsIn( value )\n    Returns an array of an object's own and inherited symbol properties.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's own and inherited symbol properties.\n\n    Examples\n    --------\n    > var s = propertySymbolsIn( [] )\n\n    See Also\n    --------\n    propertyNamesIn, propertySymbols\n","Proxy":"\nProxy( target, handlers )\n    Returns a proxy object implementing custom behavior for specified object\n    operations.\n\n    The following \"traps\" are supported:\n\n    - getPrototypeOf( target )\n        Trap for `Object.getPrototypeOf()`. Can be used to intercept the\n        `instanceof` operator. The method must return an object or `null`.\n\n    - setPrototypeOf( target, prototype )\n        Trap for `Object.setPrototypeOf()`. The method must return a boolean\n        indicating if prototype successfully set.\n\n    - isExtensible( target )\n        Trap for `Object.isExtensible()`. The method must return a boolean.\n\n    - preventExtensions( target )\n        Trap for `Object.preventExtensions()`. The method must return a boolean.\n\n    - getOwnPropertyDescriptor( target, property )\n        Trap for `Object.getOwnPropertyDescriptor()`. The method must return an\n        object or `undefined`.\n\n    - defineProperty( target, property, descriptor )\n        Trap for `Object.defineProperty()`. The method must return a boolean\n        indicating whether the operation succeeded.\n\n    - has( target, property )\n        Trap for the `in` operator. The method must return a boolean.\n\n    - get( target, property, receiver )\n        Trap for retrieving property values. The method can return any value.\n\n    - set( target, property, value, receiver )\n        Trap for setting property values. The method should return a boolean\n        indicating whether assignment succeeded.\n\n    - deleteProperty( target, property )\n        Trap for the `delete` operator. The method must return a boolean\n        indicating whether operation succeeded.\n\n    - ownKeys( target )\n        Trap for `Object.keys`, `Object.getOwnPropertyNames()`, and\n        `Object.getOwnPropertySymbols()`. The method must return an enumerable\n        object.\n\n    - apply( target, thisArg, argumentsList )\n        Trap for a function call. The method can return any value.\n\n    - construct( target, argumentsList, newTarget )\n        Trap for the `new` operator. The method must return an object.\n\n    All traps are optional. If a trap is not defined, the default behavior is to\n    forward the operation to the target.\n\n    Parameters\n    ----------\n    target: Object\n        Object which the proxy virtualizes.\n\n    handlers: Object\n        Object whose properties are functions which define the behavior of the\n        proxy when performing operations.\n\n    Returns\n    -------\n    p: Object\n        Proxy object.\n\n    Examples\n    --------\n    > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n    > var h = { 'get': get };\n    > var p = new Proxy( {}, h );\n    > p.a = 3.14;\n    > p.a\n    6.28\n\n\nProxy.revocable( target, handlers )\n    Returns a revocable proxy object.\n\n    Parameters\n    ----------\n    target: Object\n        Object which the proxy virtualizes.\n\n    handlers: Object\n        Object whose properties are functions which define the behavior of the\n        proxy when performing operations.\n\n    Returns\n    -------\n    p: Object\n        Revocable proxy object.\n\n    p.proxy: Object\n        Proxy object.\n\n    p.revoke: Function\n        Invalidates a proxy, rendering a proxy object unusable.\n\n    Examples\n    --------\n    > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n    > var h = { 'get': get };\n    > var p = Proxy.revocable( {}, h );\n    > p.proxy.a = 3.14;\n    > p.proxy.a\n    6.28\n    > p.revoke();\n\n","Proxy.revocable":"\nProxy.revocable( target, handlers )\n    Returns a revocable proxy object.\n\n    Parameters\n    ----------\n    target: Object\n        Object which the proxy virtualizes.\n\n    handlers: Object\n        Object whose properties are functions which define the behavior of the\n        proxy when performing operations.\n\n    Returns\n    -------\n    p: Object\n        Revocable proxy object.\n\n    p.proxy: Object\n        Proxy object.\n\n    p.revoke: Function\n        Invalidates a proxy, rendering a proxy object unusable.\n\n    Examples\n    --------\n    > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n    > var h = { 'get': get };\n    > var p = Proxy.revocable( {}, h );\n    > p.proxy.a = 3.14;\n    > p.proxy.a\n    6.28\n    > p.revoke();","push":"\npush( collection, ...items )\n    Adds one or more elements to the end of a collection.\n\n    If the input collection is a typed array, the output value does not equal\n    the input reference and the underlying `ArrayBuffer` may *not* be the same\n    as the `ArrayBuffer` belonging to the input view.\n\n    For purposes of generality, always treat the output collection as distinct\n    from the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        A collection. If the collection is an `Object`, the collection should be\n        array-like.\n\n    items: ...any\n        Items to add.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Updated collection.\n\n    Examples\n    --------\n    // Arrays:\n    > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > arr = push( arr, 6.0, 7.0 )\n    [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]\n\n    // Typed arrays:\n    > arr = new Float64Array( [ 1.0, 2.0 ] );\n    > arr = push( arr, 3.0, 4.0 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Array-like object:\n    > arr = { 'length': 0 };\n    > arr = push( arr, 1.0, 2.0 )\n    { 'length': 2, '0': 1.0, '1': 2.0 }\n\n    See Also\n    --------\n    pop, shift, unshift\n","quarterOfYear":"\nquarterOfYear( [month] )\n    Returns the quarter of the year.\n\n    By default, the function returns the quarter of the year for the current\n    month in the current year (according to local time). To determine the\n    quarter for a particular month, provide either a month or a `Date`\n    object.\n\n    A `month` may be either a month's integer value, three letter abbreviation,\n    or full name (case insensitive).\n\n    Parameters\n    ----------\n    month: integer|string|Date (optional)\n        Month (or `Date`).\n\n    Returns\n    -------\n    out: integer\n        Quarter of the year.\n\n    Examples\n    --------\n    > var q = quarterOfYear( new Date() )\n    <number>\n    > q = quarterOfYear( 4 )\n    2\n    > q = quarterOfYear( 'June' )\n    2\n\n    // Other ways to supply month:\n    > q = quarterOfYear( 'April' )\n    2\n    > q = quarterOfYear( 'apr' )\n    2\n\n    See Also\n    --------\n    dayOfYear\n","random.array.arcsine":"\nrandom.array.arcsine( len, a, b[, options] )\n    Returns an array containing pseudorandom numbers drawn from an arcsine\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.arcsine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.arcsine.assign( a, b, out )\n    Fills an array with pseudorandom numbers drawn from an arcsine distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.arcsine.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.arcsine.factory( [a, b, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an arcsine distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.arcsine.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.arcsine.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.arcsine.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.arcsine.PRNG;\n\n\nrandom.array.arcsine.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.arcsine.seed;\n\n\nrandom.array.arcsine.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.arcsine.seedLength;\n\n\nrandom.array.arcsine.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.arcsine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.arcsine.state\n    <Uint32Array>\n\n    > out = random.array.arcsine( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.arcsine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.arcsine.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.arcsine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.arcsine.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.arcsine.stateLength;\n\n\nrandom.array.arcsine.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.arcsine.byteLength;\n\n    See Also\n    --------\n    base.random.arcsine, random.strided.arcsine\n","random.array.arcsine.assign":"\nrandom.array.arcsine.assign( a, b, out )\n    Fills an array with pseudorandom numbers drawn from an arcsine distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.arcsine.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.arcsine.factory":"\nrandom.array.arcsine.factory( [a, b, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an arcsine distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.arcsine.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.arcsine.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.arcsine.PRNG":"\nrandom.array.arcsine.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.arcsine.PRNG;","random.array.arcsine.seed":"\nrandom.array.arcsine.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.arcsine.seed;","random.array.arcsine.seedLength":"\nrandom.array.arcsine.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.arcsine.seedLength;","random.array.arcsine.state":"\nrandom.array.arcsine.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.arcsine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.arcsine.state\n    <Uint32Array>\n\n    > out = random.array.arcsine( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.arcsine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.arcsine.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.arcsine( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.arcsine.stateLength":"\nrandom.array.arcsine.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.arcsine.stateLength;","random.array.arcsine.byteLength":"\nrandom.array.arcsine.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.arcsine.byteLength;\n\n    See Also\n    --------\n    base.random.arcsine, random.strided.arcsine","random.array.bernoulli":"\nrandom.array.bernoulli( len, p[, options] )\n    Returns an array containing pseudorandom numbers drawn from a Bernoulli\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.bernoulli( 3, 0.5 )\n    <Float64Array>\n\n\nrandom.array.bernoulli.assign( p, out )\n    Fills an array with pseudorandom numbers drawn from a Bernoulli\n    distribution.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.bernoulli.assign( 0.5, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.bernoulli.factory( [p, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Bernoulli distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.bernoulli.factory();\n    > var out = fcn( 3, 0.5 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.bernoulli.factory( 0.5 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.bernoulli.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.bernoulli.PRNG;\n\n\nrandom.array.bernoulli.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.bernoulli.seed;\n\n\nrandom.array.bernoulli.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.bernoulli.seedLength;\n\n\nrandom.array.bernoulli.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.bernoulli( 3, 0.5 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.bernoulli.state\n    <Uint32Array>\n\n    > out = random.array.bernoulli( 3, 0.5 )\n    <Float64Array>\n    > out = random.array.bernoulli( 3, 0.5 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.bernoulli.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.bernoulli( 3, 0.5 )\n    <Float64Array>\n\n\nrandom.array.bernoulli.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.bernoulli.stateLength;\n\n\nrandom.array.bernoulli.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.bernoulli.byteLength;\n\n    See Also\n    --------\n    base.random.bernoulli, random.strided.bernoulli\n","random.array.bernoulli.assign":"\nrandom.array.bernoulli.assign( p, out )\n    Fills an array with pseudorandom numbers drawn from a Bernoulli\n    distribution.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.bernoulli.assign( 0.5, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.bernoulli.factory":"\nrandom.array.bernoulli.factory( [p, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Bernoulli distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.bernoulli.factory();\n    > var out = fcn( 3, 0.5 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.bernoulli.factory( 0.5 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.bernoulli.PRNG":"\nrandom.array.bernoulli.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.bernoulli.PRNG;","random.array.bernoulli.seed":"\nrandom.array.bernoulli.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.bernoulli.seed;","random.array.bernoulli.seedLength":"\nrandom.array.bernoulli.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.bernoulli.seedLength;","random.array.bernoulli.state":"\nrandom.array.bernoulli.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.bernoulli( 3, 0.5 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.bernoulli.state\n    <Uint32Array>\n\n    > out = random.array.bernoulli( 3, 0.5 )\n    <Float64Array>\n    > out = random.array.bernoulli( 3, 0.5 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.bernoulli.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.bernoulli( 3, 0.5 )\n    <Float64Array>","random.array.bernoulli.stateLength":"\nrandom.array.bernoulli.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.bernoulli.stateLength;","random.array.bernoulli.byteLength":"\nrandom.array.bernoulli.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.bernoulli.byteLength;\n\n    See Also\n    --------\n    base.random.bernoulli, random.strided.bernoulli","random.array.beta":"\nrandom.array.beta( len, alpha, beta[, options] )\n    Returns an array containing pseudorandom numbers drawn from a beta\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    alpha: number\n        First shape parameter.\n\n    beta: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.beta( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.beta.assign( alpha, beta, out )\n    Fills an array with pseudorandom numbers drawn from a beta distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        First shape parameter.\n\n    beta: number\n        Second shape parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.beta.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.beta.factory( [alpha, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a beta distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        First shape parameter.\n\n    beta: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.beta.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.beta.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.beta.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.beta.PRNG;\n\n\nrandom.array.beta.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.beta.seed;\n\n\nrandom.array.beta.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.beta.seedLength;\n\n\nrandom.array.beta.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.beta( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.beta.state\n    <Uint32Array>\n\n    > out = random.array.beta( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.beta( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.beta.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.beta( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.beta.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.beta.stateLength;\n\n\nrandom.array.beta.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.beta.byteLength;\n\n    See Also\n    --------\n    base.random.beta, random.strided.beta\n","random.array.beta.assign":"\nrandom.array.beta.assign( alpha, beta, out )\n    Fills an array with pseudorandom numbers drawn from a beta distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        First shape parameter.\n\n    beta: number\n        Second shape parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.beta.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.beta.factory":"\nrandom.array.beta.factory( [alpha, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a beta distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        First shape parameter.\n\n    beta: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.beta.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.beta.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.beta.PRNG":"\nrandom.array.beta.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.beta.PRNG;","random.array.beta.seed":"\nrandom.array.beta.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.beta.seed;","random.array.beta.seedLength":"\nrandom.array.beta.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.beta.seedLength;","random.array.beta.state":"\nrandom.array.beta.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.beta( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.beta.state\n    <Uint32Array>\n\n    > out = random.array.beta( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.beta( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.beta.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.beta( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.beta.stateLength":"\nrandom.array.beta.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.beta.stateLength;","random.array.beta.byteLength":"\nrandom.array.beta.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.beta.byteLength;\n\n    See Also\n    --------\n    base.random.beta, random.strided.beta","random.array.betaprime":"\nrandom.array.betaprime( len, alpha, beta[, options] )\n    Returns an array containing pseudorandom numbers drawn from a beta prime\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    alpha: number\n        First shape parameter.\n\n    beta: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.betaprime( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.betaprime.assign( alpha, beta, out )\n    Fills an array with pseudorandom numbers drawn from a beta prime\n    distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        First shape parameter.\n\n    beta: number\n        Second shape parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.betaprime.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.betaprime.factory( [alpha, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a beta prime distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        First shape parameter.\n\n    beta: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.betaprime.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.betaprime.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.betaprime.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.betaprime.PRNG;\n\n\nrandom.array.betaprime.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.betaprime.seed;\n\n\nrandom.array.betaprime.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.betaprime.seedLength;\n\n\nrandom.array.betaprime.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.betaprime( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.betaprime.state\n    <Uint32Array>\n\n    > out = random.array.betaprime( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.betaprime( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.betaprime.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.betaprime( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.betaprime.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.betaprime.stateLength;\n\n\nrandom.array.betaprime.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.betaprime.byteLength;\n\n    See Also\n    --------\n    base.random.betaprime, random.strided.betaprime\n","random.array.betaprime.assign":"\nrandom.array.betaprime.assign( alpha, beta, out )\n    Fills an array with pseudorandom numbers drawn from a beta prime\n    distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        First shape parameter.\n\n    beta: number\n        Second shape parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.betaprime.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.betaprime.factory":"\nrandom.array.betaprime.factory( [alpha, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a beta prime distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        First shape parameter.\n\n    beta: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.betaprime.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.betaprime.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.betaprime.PRNG":"\nrandom.array.betaprime.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.betaprime.PRNG;","random.array.betaprime.seed":"\nrandom.array.betaprime.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.betaprime.seed;","random.array.betaprime.seedLength":"\nrandom.array.betaprime.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.betaprime.seedLength;","random.array.betaprime.state":"\nrandom.array.betaprime.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.betaprime( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.betaprime.state\n    <Uint32Array>\n\n    > out = random.array.betaprime( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.betaprime( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.betaprime.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.betaprime( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.betaprime.stateLength":"\nrandom.array.betaprime.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.betaprime.stateLength;","random.array.betaprime.byteLength":"\nrandom.array.betaprime.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.betaprime.byteLength;\n\n    See Also\n    --------\n    base.random.betaprime, random.strided.betaprime","random.array.binomial":"\nrandom.array.binomial( len, n, p[, options] )\n    Returns an array containing pseudorandom numbers drawn from a binomial\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    n: number\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.binomial( 3, 17, 0.5 )\n    <Float64Array>\n\n\nrandom.array.binomial.assign( n, p, out )\n    Fills an array with pseudorandom numbers drawn from a binomial distribution.\n\n    Parameters\n    ----------\n    n: number\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.binomial.assign( 17, 0.5, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.binomial.factory( [n, p, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a binomial distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    n: number (optional)\n        Number of trials.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.binomial.factory();\n    > var out = fcn( 3, 17, 0.5 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.binomial.factory( 17, 0.5 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.binomial.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.binomial.PRNG;\n\n\nrandom.array.binomial.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.binomial.seed;\n\n\nrandom.array.binomial.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.binomial.seedLength;\n\n\nrandom.array.binomial.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.binomial( 3, 17, 0.5 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.binomial.state\n    <Uint32Array>\n\n    > out = random.array.binomial( 3, 17, 0.5 )\n    <Float64Array>\n    > out = random.array.binomial( 3, 17, 0.5 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.binomial.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.binomial( 3, 17, 0.5 )\n    <Float64Array>\n\n\nrandom.array.binomial.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.binomial.stateLength;\n\n\nrandom.array.binomial.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.binomial.byteLength;\n\n    See Also\n    --------\n    random.array.negativeBinomial, base.random.binomial\n","random.array.binomial.assign":"\nrandom.array.binomial.assign( n, p, out )\n    Fills an array with pseudorandom numbers drawn from a binomial distribution.\n\n    Parameters\n    ----------\n    n: number\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.binomial.assign( 17, 0.5, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.binomial.factory":"\nrandom.array.binomial.factory( [n, p, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a binomial distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    n: number (optional)\n        Number of trials.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.binomial.factory();\n    > var out = fcn( 3, 17, 0.5 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.binomial.factory( 17, 0.5 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.binomial.PRNG":"\nrandom.array.binomial.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.binomial.PRNG;","random.array.binomial.seed":"\nrandom.array.binomial.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.binomial.seed;","random.array.binomial.seedLength":"\nrandom.array.binomial.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.binomial.seedLength;","random.array.binomial.state":"\nrandom.array.binomial.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.binomial( 3, 17, 0.5 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.binomial.state\n    <Uint32Array>\n\n    > out = random.array.binomial( 3, 17, 0.5 )\n    <Float64Array>\n    > out = random.array.binomial( 3, 17, 0.5 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.binomial.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.binomial( 3, 17, 0.5 )\n    <Float64Array>","random.array.binomial.stateLength":"\nrandom.array.binomial.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.binomial.stateLength;","random.array.binomial.byteLength":"\nrandom.array.binomial.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.binomial.byteLength;\n\n    See Also\n    --------\n    random.array.negativeBinomial, base.random.binomial","random.array.cauchy":"\nrandom.array.cauchy( len, x0, gamma[, options] )\n    Returns an array containing pseudorandom numbers drawn from a Cauchy\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    x0: number\n        Location parameter.\n\n    gamma: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.cauchy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.cauchy.assign( x0, gamma, out )\n    Fills an array with pseudorandom numbers drawn from a Cauchy distribution.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    gamma: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.cauchy.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.cauchy.factory( [x0, gamma, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Cauchy distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    x0: number (optional)\n        Location parameter.\n\n    gamma: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.cauchy.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.cauchy.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.cauchy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.cauchy.PRNG;\n\n\nrandom.array.cauchy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.cauchy.seed;\n\n\nrandom.array.cauchy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.cauchy.seedLength;\n\n\nrandom.array.cauchy.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.cauchy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.cauchy.state\n    <Uint32Array>\n\n    > out = random.array.cauchy( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.cauchy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.cauchy.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.cauchy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.cauchy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.cauchy.stateLength;\n\n\nrandom.array.cauchy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.cauchy.byteLength;\n\n    See Also\n    --------\n    base.random.cauchy\n","random.array.cauchy.assign":"\nrandom.array.cauchy.assign( x0, gamma, out )\n    Fills an array with pseudorandom numbers drawn from a Cauchy distribution.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    gamma: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.cauchy.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.cauchy.factory":"\nrandom.array.cauchy.factory( [x0, gamma, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Cauchy distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    x0: number (optional)\n        Location parameter.\n\n    gamma: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.cauchy.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.cauchy.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.cauchy.PRNG":"\nrandom.array.cauchy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.cauchy.PRNG;","random.array.cauchy.seed":"\nrandom.array.cauchy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.cauchy.seed;","random.array.cauchy.seedLength":"\nrandom.array.cauchy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.cauchy.seedLength;","random.array.cauchy.state":"\nrandom.array.cauchy.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.cauchy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.cauchy.state\n    <Uint32Array>\n\n    > out = random.array.cauchy( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.cauchy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.cauchy.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.cauchy( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.cauchy.stateLength":"\nrandom.array.cauchy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.cauchy.stateLength;","random.array.cauchy.byteLength":"\nrandom.array.cauchy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.cauchy.byteLength;\n\n    See Also\n    --------\n    base.random.cauchy","random.array.chi":"\nrandom.array.chi( len, k[, options] )\n    Returns an array containing pseudorandom numbers drawn from a chi\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    k: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.chi( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.chi.assign( k, out )\n    Fills an array with pseudorandom numbers drawn from a chi distribution.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.chi.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.chi.factory( [k, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a chi distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.chi.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.chi.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.chi.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.chi.PRNG;\n\n\nrandom.array.chi.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.chi.seed;\n\n\nrandom.array.chi.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.chi.seedLength;\n\n\nrandom.array.chi.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.chi( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.chi.state\n    <Uint32Array>\n\n    > out = random.array.chi( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.chi( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.chi.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.chi( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.chi.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.chi.stateLength;\n\n\nrandom.array.chi.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.chi.byteLength;\n\n    See Also\n    --------\n    base.random.chi, random.strided.chi\n","random.array.chi.assign":"\nrandom.array.chi.assign( k, out )\n    Fills an array with pseudorandom numbers drawn from a chi distribution.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.chi.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.chi.factory":"\nrandom.array.chi.factory( [k, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a chi distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.chi.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.chi.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.chi.PRNG":"\nrandom.array.chi.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.chi.PRNG;","random.array.chi.seed":"\nrandom.array.chi.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.chi.seed;","random.array.chi.seedLength":"\nrandom.array.chi.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.chi.seedLength;","random.array.chi.state":"\nrandom.array.chi.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.chi( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.chi.state\n    <Uint32Array>\n\n    > out = random.array.chi( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.chi( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.chi.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.chi( 3, 2.0 )\n    <Float64Array>","random.array.chi.stateLength":"\nrandom.array.chi.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.chi.stateLength;","random.array.chi.byteLength":"\nrandom.array.chi.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.chi.byteLength;\n\n    See Also\n    --------\n    base.random.chi, random.strided.chi","random.array.chisquare":"\nrandom.array.chisquare( len, k[, options] )\n    Returns an array containing pseudorandom numbers drawn from a chi-square\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    k: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.chisquare( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.chisquare.assign( k, out )\n    Fills an array with pseudorandom numbers drawn from a chi-square\n    distribution.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.chisquare.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.chisquare.factory( [k, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a chi-square distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.chisquare.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.chisquare.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.chisquare.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.chisquare.PRNG;\n\n\nrandom.array.chisquare.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.chisquare.seed;\n\n\nrandom.array.chisquare.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.chisquare.seedLength;\n\n\nrandom.array.chisquare.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.chisquare( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.chisquare.state\n    <Uint32Array>\n\n    > out = random.array.chisquare( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.chisquare( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.chisquare.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.chisquare( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.chisquare.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.chisquare.stateLength;\n\n\nrandom.array.chisquare.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.chisquare.byteLength;\n\n    See Also\n    --------\n    base.random.chisquare, random.strided.chisquare\n","random.array.chisquare.assign":"\nrandom.array.chisquare.assign( k, out )\n    Fills an array with pseudorandom numbers drawn from a chi-square\n    distribution.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.chisquare.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.chisquare.factory":"\nrandom.array.chisquare.factory( [k, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a chi-square distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.chisquare.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.chisquare.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.chisquare.PRNG":"\nrandom.array.chisquare.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.chisquare.PRNG;","random.array.chisquare.seed":"\nrandom.array.chisquare.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.chisquare.seed;","random.array.chisquare.seedLength":"\nrandom.array.chisquare.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.chisquare.seedLength;","random.array.chisquare.state":"\nrandom.array.chisquare.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.chisquare( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.chisquare.state\n    <Uint32Array>\n\n    > out = random.array.chisquare( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.chisquare( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.chisquare.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.chisquare( 3, 2.0 )\n    <Float64Array>","random.array.chisquare.stateLength":"\nrandom.array.chisquare.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.chisquare.stateLength;","random.array.chisquare.byteLength":"\nrandom.array.chisquare.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.chisquare.byteLength;\n\n    See Also\n    --------\n    base.random.chisquare, random.strided.chisquare","random.array.cosine":"\nrandom.array.cosine( len, mu, s[, options] )\n    Returns an array containing pseudorandom numbers drawn from a raised cosine\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    mu: number\n        Mean.\n\n    s: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.cosine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.cosine.assign( mu, s, out )\n    Fills an array with pseudorandom numbers drawn from a raised cosine\n    distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Mean.\n\n    s: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.cosine.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.cosine.factory( [mu, s, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a raised cosine distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Mean.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.cosine.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.cosine.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.cosine.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.cosine.PRNG;\n\n\nrandom.array.cosine.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.cosine.seed;\n\n\nrandom.array.cosine.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.cosine.seedLength;\n\n\nrandom.array.cosine.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.cosine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.cosine.state\n    <Uint32Array>\n\n    > out = random.array.cosine( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.cosine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.cosine.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.cosine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.cosine.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.cosine.stateLength;\n\n\nrandom.array.cosine.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.cosine.byteLength;\n\n    See Also\n    --------\n    base.random.cosine, random.strided.cosine\n","random.array.cosine.assign":"\nrandom.array.cosine.assign( mu, s, out )\n    Fills an array with pseudorandom numbers drawn from a raised cosine\n    distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Mean.\n\n    s: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.cosine.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.cosine.factory":"\nrandom.array.cosine.factory( [mu, s, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a raised cosine distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Mean.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.cosine.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.cosine.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.cosine.PRNG":"\nrandom.array.cosine.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.cosine.PRNG;","random.array.cosine.seed":"\nrandom.array.cosine.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.cosine.seed;","random.array.cosine.seedLength":"\nrandom.array.cosine.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.cosine.seedLength;","random.array.cosine.state":"\nrandom.array.cosine.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.cosine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.cosine.state\n    <Uint32Array>\n\n    > out = random.array.cosine( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.cosine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.cosine.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.cosine( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.cosine.stateLength":"\nrandom.array.cosine.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.cosine.stateLength;","random.array.cosine.byteLength":"\nrandom.array.cosine.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.cosine.byteLength;\n\n    See Also\n    --------\n    base.random.cosine, random.strided.cosine","random.array.discreteUniform":"\nrandom.array.discreteUniform( len, a, b[, options] )\n    Returns an array containing pseudorandom numbers drawn from a discrete\n    uniform distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.discreteUniform( 3, -10, 10 )\n    <Float64Array>\n\n\nrandom.array.discreteUniform.assign( a, b, out )\n    Fills an array with pseudorandom numbers drawn from a discrete uniform\n    distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.discreteUniform.assign( -10, 10, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.discreteUniform.factory( [a, b, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a discrete uniform distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom integers. If provided, the `state` and `seed`\n        options are ignored. In order to seed the returned pseudorandom number\n        generator, one must seed the provided `prng` (assuming the provided\n        `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n        properties specifying the minimum and maximum possible pseudorandom\n        integers.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.discreteUniform.factory();\n    > var out = fcn( 3, -10, 10 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.discreteUniform.factory( -10, 10 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.discreteUniform.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.discreteUniform.PRNG;\n\n\nrandom.array.discreteUniform.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.discreteUniform.seed;\n\n\nrandom.array.discreteUniform.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.discreteUniform.seedLength;\n\n\nrandom.array.discreteUniform.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.discreteUniform( 3, -10, 10 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.discreteUniform.state\n    <Uint32Array>\n\n    > out = random.array.discreteUniform( 3, -10, 10 )\n    <Float64Array>\n    > out = random.array.discreteUniform( 3, -10, 10 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.discreteUniform.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.discreteUniform( 3, -10, 10 )\n    <Float64Array>\n\n\nrandom.array.discreteUniform.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.discreteUniform.stateLength;\n\n\nrandom.array.discreteUniform.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.discreteUniform.byteLength;\n\n    See Also\n    --------\n    random.array.uniform, base.random.discreteUniform, random.strided.discreteUniform\n","random.array.discreteUniform.assign":"\nrandom.array.discreteUniform.assign( a, b, out )\n    Fills an array with pseudorandom numbers drawn from a discrete uniform\n    distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.discreteUniform.assign( -10, 10, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.discreteUniform.factory":"\nrandom.array.discreteUniform.factory( [a, b, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a discrete uniform distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom integers. If provided, the `state` and `seed`\n        options are ignored. In order to seed the returned pseudorandom number\n        generator, one must seed the provided `prng` (assuming the provided\n        `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n        properties specifying the minimum and maximum possible pseudorandom\n        integers.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.discreteUniform.factory();\n    > var out = fcn( 3, -10, 10 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.discreteUniform.factory( -10, 10 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.discreteUniform.PRNG":"\nrandom.array.discreteUniform.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.discreteUniform.PRNG;","random.array.discreteUniform.seed":"\nrandom.array.discreteUniform.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.discreteUniform.seed;","random.array.discreteUniform.seedLength":"\nrandom.array.discreteUniform.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.discreteUniform.seedLength;","random.array.discreteUniform.state":"\nrandom.array.discreteUniform.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.discreteUniform( 3, -10, 10 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.discreteUniform.state\n    <Uint32Array>\n\n    > out = random.array.discreteUniform( 3, -10, 10 )\n    <Float64Array>\n    > out = random.array.discreteUniform( 3, -10, 10 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.discreteUniform.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.discreteUniform( 3, -10, 10 )\n    <Float64Array>","random.array.discreteUniform.stateLength":"\nrandom.array.discreteUniform.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.discreteUniform.stateLength;","random.array.discreteUniform.byteLength":"\nrandom.array.discreteUniform.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.discreteUniform.byteLength;\n\n    See Also\n    --------\n    random.array.uniform, base.random.discreteUniform, random.strided.discreteUniform","random.array.erlang":"\nrandom.array.erlang( len, k, lambda[, options] )\n    Returns an array containing pseudorandom numbers drawn from an Erlang\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    k: number\n        Shape parameter.\n\n    lambda: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.erlang( 3, 2, 5.0 )\n    <Float64Array>\n\n\nrandom.array.erlang.assign( k, lambda, out )\n    Fills an array with pseudorandom numbers drawn from an Erlang distribution.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    lambda: number\n        Rate parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.erlang.assign( 2, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.erlang.factory( [k, lambda, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an Erlang distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Shape parameter.\n\n    lambda: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.erlang.factory();\n    > var out = fcn( 3, 2, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.erlang.factory( 2, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.erlang.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.erlang.PRNG;\n\n\nrandom.array.erlang.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.erlang.seed;\n\n\nrandom.array.erlang.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.erlang.seedLength;\n\n\nrandom.array.erlang.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.erlang( 3, 2, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.erlang.state\n    <Uint32Array>\n\n    > out = random.array.erlang( 3, 2, 5.0 )\n    <Float64Array>\n    > out = random.array.erlang( 3, 2, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.erlang.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.erlang( 3, 2, 5.0 )\n    <Float64Array>\n\n\nrandom.array.erlang.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.erlang.stateLength;\n\n\nrandom.array.erlang.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.erlang.byteLength;\n\n    See Also\n    --------\n    base.random.erlang\n","random.array.erlang.assign":"\nrandom.array.erlang.assign( k, lambda, out )\n    Fills an array with pseudorandom numbers drawn from an Erlang distribution.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    lambda: number\n        Rate parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.erlang.assign( 2, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.erlang.factory":"\nrandom.array.erlang.factory( [k, lambda, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an Erlang distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Shape parameter.\n\n    lambda: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.erlang.factory();\n    > var out = fcn( 3, 2, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.erlang.factory( 2, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.erlang.PRNG":"\nrandom.array.erlang.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.erlang.PRNG;","random.array.erlang.seed":"\nrandom.array.erlang.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.erlang.seed;","random.array.erlang.seedLength":"\nrandom.array.erlang.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.erlang.seedLength;","random.array.erlang.state":"\nrandom.array.erlang.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.erlang( 3, 2, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.erlang.state\n    <Uint32Array>\n\n    > out = random.array.erlang( 3, 2, 5.0 )\n    <Float64Array>\n    > out = random.array.erlang( 3, 2, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.erlang.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.erlang( 3, 2, 5.0 )\n    <Float64Array>","random.array.erlang.stateLength":"\nrandom.array.erlang.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.erlang.stateLength;","random.array.erlang.byteLength":"\nrandom.array.erlang.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.erlang.byteLength;\n\n    See Also\n    --------\n    base.random.erlang","random.array.exponential":"\nrandom.array.exponential( len, lambda[, options] )\n    Returns an array containing pseudorandom numbers drawn from an exponential\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    lambda: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.exponential( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.exponential.assign( lambda, out )\n    Fills an array with pseudorandom numbers drawn from an exponential\n    distribution.\n\n    Parameters\n    ----------\n    lambda: number\n        Rate parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.exponential.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.exponential.factory( [lambda, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an exponential distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    lambda: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.exponential.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.exponential.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.exponential.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.exponential.PRNG;\n\n\nrandom.array.exponential.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.exponential.seed;\n\n\nrandom.array.exponential.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.exponential.seedLength;\n\n\nrandom.array.exponential.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.exponential( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.exponential.state\n    <Uint32Array>\n\n    > out = random.array.exponential( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.exponential( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.exponential.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.exponential( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.exponential.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.exponential.stateLength;\n\n\nrandom.array.exponential.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.exponential.byteLength;\n\n    See Also\n    --------\n    base.random.exponential, random.strided.exponential\n","random.array.exponential.assign":"\nrandom.array.exponential.assign( lambda, out )\n    Fills an array with pseudorandom numbers drawn from an exponential\n    distribution.\n\n    Parameters\n    ----------\n    lambda: number\n        Rate parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.exponential.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.exponential.factory":"\nrandom.array.exponential.factory( [lambda, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an exponential distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    lambda: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.exponential.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.exponential.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.exponential.PRNG":"\nrandom.array.exponential.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.exponential.PRNG;","random.array.exponential.seed":"\nrandom.array.exponential.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.exponential.seed;","random.array.exponential.seedLength":"\nrandom.array.exponential.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.exponential.seedLength;","random.array.exponential.state":"\nrandom.array.exponential.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.exponential( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.exponential.state\n    <Uint32Array>\n\n    > out = random.array.exponential( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.exponential( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.exponential.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.exponential( 3, 2.0 )\n    <Float64Array>","random.array.exponential.stateLength":"\nrandom.array.exponential.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.exponential.stateLength;","random.array.exponential.byteLength":"\nrandom.array.exponential.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.exponential.byteLength;\n\n    See Also\n    --------\n    base.random.exponential, random.strided.exponential","random.array.f":"\nrandom.array.f( len, d1, d2[, options] )\n    Returns an array containing pseudorandom numbers drawn from an F\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    d1: number\n        Degrees of freedom.\n\n    d2: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.f( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.f.assign( d1, d2, out )\n    Fills an array with pseudorandom numbers drawn from an F distribution.\n\n    Parameters\n    ----------\n    d1: number\n        Degrees of freedom.\n\n    d2: number\n        Degrees of freedom.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.f.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.f.factory( [d1, d2, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an F distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    d1: number (optional)\n        Degrees of freedom.\n\n    d2: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.f.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.f.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.f.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.f.PRNG;\n\n\nrandom.array.f.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.f.seed;\n\n\nrandom.array.f.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.f.seedLength;\n\n\nrandom.array.f.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.f( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.f.state\n    <Uint32Array>\n\n    > out = random.array.f( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.f( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.f.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.f( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.f.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.f.stateLength;\n\n\nrandom.array.f.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.f.byteLength;\n\n    See Also\n    --------\n    base.random.f\n","random.array.f.assign":"\nrandom.array.f.assign( d1, d2, out )\n    Fills an array with pseudorandom numbers drawn from an F distribution.\n\n    Parameters\n    ----------\n    d1: number\n        Degrees of freedom.\n\n    d2: number\n        Degrees of freedom.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.f.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.f.factory":"\nrandom.array.f.factory( [d1, d2, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an F distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    d1: number (optional)\n        Degrees of freedom.\n\n    d2: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.f.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.f.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.f.PRNG":"\nrandom.array.f.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.f.PRNG;","random.array.f.seed":"\nrandom.array.f.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.f.seed;","random.array.f.seedLength":"\nrandom.array.f.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.f.seedLength;","random.array.f.state":"\nrandom.array.f.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.f( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.f.state\n    <Uint32Array>\n\n    > out = random.array.f( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.f( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.f.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.f( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.f.stateLength":"\nrandom.array.f.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.f.stateLength;","random.array.f.byteLength":"\nrandom.array.f.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.f.byteLength;\n\n    See Also\n    --------\n    base.random.f","random.array.frechet":"\nrandom.array.frechet( len, alpha, s, m[, options] )\n    Returns an array containing pseudorandom numbers drawn from a Fréchet\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    alpha: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n\nrandom.array.frechet.assign( alpha, s, m, out )\n    Fills an array with pseudorandom numbers drawn from a Fréchet distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.frechet.assign( 2.0, 5.0, 3.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.frechet.factory( [alpha, s, m, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Fréchet distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        Shape parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    m: number (optional)\n        Location parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.frechet.factory();\n    > var out = fcn( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.frechet.factory( 2.0, 5.0, 3.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.frechet.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.frechet.PRNG;\n\n\nrandom.array.frechet.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.frechet.seed;\n\n\nrandom.array.frechet.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.frechet.seedLength;\n\n\nrandom.array.frechet.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.frechet.state\n    <Uint32Array>\n\n    > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n    > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.frechet.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n\nrandom.array.frechet.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.frechet.stateLength;\n\n\nrandom.array.frechet.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.frechet.byteLength;\n\n    See Also\n    --------\n    base.random.frechet\n","random.array.frechet.assign":"\nrandom.array.frechet.assign( alpha, s, m, out )\n    Fills an array with pseudorandom numbers drawn from a Fréchet distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.frechet.assign( 2.0, 5.0, 3.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.frechet.factory":"\nrandom.array.frechet.factory( [alpha, s, m, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Fréchet distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        Shape parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    m: number (optional)\n        Location parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.frechet.factory();\n    > var out = fcn( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.frechet.factory( 2.0, 5.0, 3.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.frechet.PRNG":"\nrandom.array.frechet.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.frechet.PRNG;","random.array.frechet.seed":"\nrandom.array.frechet.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.frechet.seed;","random.array.frechet.seedLength":"\nrandom.array.frechet.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.frechet.seedLength;","random.array.frechet.state":"\nrandom.array.frechet.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.frechet.state\n    <Uint32Array>\n\n    > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n    > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.frechet.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>","random.array.frechet.stateLength":"\nrandom.array.frechet.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.frechet.stateLength;","random.array.frechet.byteLength":"\nrandom.array.frechet.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.frechet.byteLength;\n\n    See Also\n    --------\n    base.random.frechet","random.array.gamma":"\nrandom.array.gamma( len, alpha, beta[, options] )\n    Returns an array containing pseudorandom numbers drawn from a gamma\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    alpha: number\n        Shape parameter.\n\n    beta: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.gamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.gamma.assign( alpha, beta, out )\n    Fills an array with pseudorandom numbers drawn from a gamma distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        Shape parameter.\n\n    beta: number\n        Rate parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.gamma.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.gamma.factory( [alpha, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a gamma distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        Shape parameter.\n\n    beta: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.gamma.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.gamma.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.gamma.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.gamma.PRNG;\n\n\nrandom.array.gamma.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.gamma.seed;\n\n\nrandom.array.gamma.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.gamma.seedLength;\n\n\nrandom.array.gamma.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.gamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.gamma.state\n    <Uint32Array>\n\n    > out = random.array.gamma( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.gamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.gamma.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.gamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.gamma.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.gamma.stateLength;\n\n\nrandom.array.gamma.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.gamma.byteLength;\n\n    See Also\n    --------\n    base.random.gamma, random.strided.gamma\n","random.array.gamma.assign":"\nrandom.array.gamma.assign( alpha, beta, out )\n    Fills an array with pseudorandom numbers drawn from a gamma distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        Shape parameter.\n\n    beta: number\n        Rate parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.gamma.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.gamma.factory":"\nrandom.array.gamma.factory( [alpha, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a gamma distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        Shape parameter.\n\n    beta: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.gamma.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.gamma.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.gamma.PRNG":"\nrandom.array.gamma.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.gamma.PRNG;","random.array.gamma.seed":"\nrandom.array.gamma.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.gamma.seed;","random.array.gamma.seedLength":"\nrandom.array.gamma.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.gamma.seedLength;","random.array.gamma.state":"\nrandom.array.gamma.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.gamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.gamma.state\n    <Uint32Array>\n\n    > out = random.array.gamma( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.gamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.gamma.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.gamma( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.gamma.stateLength":"\nrandom.array.gamma.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.gamma.stateLength;","random.array.gamma.byteLength":"\nrandom.array.gamma.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.gamma.byteLength;\n\n    See Also\n    --------\n    base.random.gamma, random.strided.gamma","random.array.geometric":"\nrandom.array.geometric( len, p[, options] )\n    Returns an array containing pseudorandom numbers drawn from a geometric\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.geometric( 3, 0.01 )\n    <Float64Array>\n\n\nrandom.array.geometric.assign( p, out )\n    Fills an array with pseudorandom numbers drawn from a geometric\n    distribution.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.geometric.assign( 0.01, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.geometric.factory( [p, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a geometric distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.geometric.factory();\n    > var out = fcn( 3, 0.01 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.geometric.factory( 0.01 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.geometric.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.geometric.PRNG;\n\n\nrandom.array.geometric.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.geometric.seed;\n\n\nrandom.array.geometric.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.geometric.seedLength;\n\n\nrandom.array.geometric.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.geometric( 3, 0.01 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.geometric.state\n    <Uint32Array>\n\n    > out = random.array.geometric( 3, 0.01 )\n    <Float64Array>\n    > out = random.array.geometric( 3, 0.01 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.geometric.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.geometric( 3, 0.01 )\n    <Float64Array>\n\n\nrandom.array.geometric.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.geometric.stateLength;\n\n\nrandom.array.geometric.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.geometric.byteLength;\n\n    See Also\n    --------\n    base.random.geometric, random.strided.geometric\n","random.array.geometric.assign":"\nrandom.array.geometric.assign( p, out )\n    Fills an array with pseudorandom numbers drawn from a geometric\n    distribution.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.geometric.assign( 0.01, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.geometric.factory":"\nrandom.array.geometric.factory( [p, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a geometric distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.geometric.factory();\n    > var out = fcn( 3, 0.01 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.geometric.factory( 0.01 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.geometric.PRNG":"\nrandom.array.geometric.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.geometric.PRNG;","random.array.geometric.seed":"\nrandom.array.geometric.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.geometric.seed;","random.array.geometric.seedLength":"\nrandom.array.geometric.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.geometric.seedLength;","random.array.geometric.state":"\nrandom.array.geometric.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.geometric( 3, 0.01 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.geometric.state\n    <Uint32Array>\n\n    > out = random.array.geometric( 3, 0.01 )\n    <Float64Array>\n    > out = random.array.geometric( 3, 0.01 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.geometric.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.geometric( 3, 0.01 )\n    <Float64Array>","random.array.geometric.stateLength":"\nrandom.array.geometric.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.geometric.stateLength;","random.array.geometric.byteLength":"\nrandom.array.geometric.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.geometric.byteLength;\n\n    See Also\n    --------\n    base.random.geometric, random.strided.geometric","random.array.gumbel":"\nrandom.array.gumbel( len, mu, beta[, options] )\n    Returns an array containing pseudorandom numbers drawn from a Gumbel\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    mu: number\n        Mean.\n\n    beta: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.gumbel( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.gumbel.assign( mu, beta, out )\n    Fills an array with pseudorandom numbers drawn from a Gumbel distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Mean.\n\n    beta: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.gumbel.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.gumbel.factory( [mu, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Gumbel distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Mean.\n\n    beta: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.gumbel.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.gumbel.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.gumbel.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.gumbel.PRNG;\n\n\nrandom.array.gumbel.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.gumbel.seed;\n\n\nrandom.array.gumbel.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.gumbel.seedLength;\n\n\nrandom.array.gumbel.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.gumbel( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.gumbel.state\n    <Uint32Array>\n\n    > out = random.array.gumbel( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.gumbel( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.gumbel.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.gumbel( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.gumbel.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.gumbel.stateLength;\n\n\nrandom.array.gumbel.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.gumbel.byteLength;\n\n    See Also\n    --------\n    base.random.gumbel\n","random.array.gumbel.assign":"\nrandom.array.gumbel.assign( mu, beta, out )\n    Fills an array with pseudorandom numbers drawn from a Gumbel distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Mean.\n\n    beta: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.gumbel.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.gumbel.factory":"\nrandom.array.gumbel.factory( [mu, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Gumbel distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Mean.\n\n    beta: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.gumbel.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.gumbel.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.gumbel.PRNG":"\nrandom.array.gumbel.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.gumbel.PRNG;","random.array.gumbel.seed":"\nrandom.array.gumbel.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.gumbel.seed;","random.array.gumbel.seedLength":"\nrandom.array.gumbel.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.gumbel.seedLength;","random.array.gumbel.state":"\nrandom.array.gumbel.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.gumbel( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.gumbel.state\n    <Uint32Array>\n\n    > out = random.array.gumbel( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.gumbel( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.gumbel.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.gumbel( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.gumbel.stateLength":"\nrandom.array.gumbel.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.gumbel.stateLength;","random.array.gumbel.byteLength":"\nrandom.array.gumbel.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.gumbel.byteLength;\n\n    See Also\n    --------\n    base.random.gumbel","random.array.hypergeometric":"\nrandom.array.hypergeometric( len, N, K, n[, options] )\n    Returns an array containing pseudorandom numbers drawn from a hypergeometric\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    N: number\n        Population size.\n\n    K: number\n        Subpopulation size.\n\n    n: number\n        Number of draws.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.hypergeometric( 3, 20, 10, 7 )\n    <Float64Array>\n\n\nrandom.array.hypergeometric.assign( N, K, n, out )\n    Fills an array with pseudorandom numbers drawn from a hypergeometric\n    distribution.\n\n    Parameters\n    ----------\n    N: number\n        Population size.\n\n    K: number\n        Subpopulation size.\n\n    n: number\n        Number of draws.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.hypergeometric.assign( 20, 10, 7, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.hypergeometric.factory( [N, K, n, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a hypergeometric distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    N: number (optional)\n        Population size.\n\n    K: number (optional)\n        Subpopulation size.\n\n    n: number (optional)\n        Number of draws.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.hypergeometric.factory();\n    > var out = fcn( 3, 20, 10, 7 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.hypergeometric.factory( 20, 10, 7 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.hypergeometric.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.hypergeometric.PRNG;\n\n\nrandom.array.hypergeometric.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.hypergeometric.seed;\n\n\nrandom.array.hypergeometric.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.hypergeometric.seedLength;\n\n\nrandom.array.hypergeometric.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.hypergeometric( 3, 20, 10, 7 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.hypergeometric.state\n    <Uint32Array>\n\n    > out = random.array.hypergeometric( 3, 20, 10, 7 )\n    <Float64Array>\n    > out = random.array.hypergeometric( 3, 20, 10, 7 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.hypergeometric.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.hypergeometric( 3, 20, 10, 7 )\n    <Float64Array>\n\n\nrandom.array.hypergeometric.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.hypergeometric.stateLength;\n\n\nrandom.array.hypergeometric.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.hypergeometric.byteLength;\n\n    See Also\n    --------\n    base.random.hypergeometric\n","random.array.hypergeometric.assign":"\nrandom.array.hypergeometric.assign( N, K, n, out )\n    Fills an array with pseudorandom numbers drawn from a hypergeometric\n    distribution.\n\n    Parameters\n    ----------\n    N: number\n        Population size.\n\n    K: number\n        Subpopulation size.\n\n    n: number\n        Number of draws.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.hypergeometric.assign( 20, 10, 7, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.hypergeometric.factory":"\nrandom.array.hypergeometric.factory( [N, K, n, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a hypergeometric distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    N: number (optional)\n        Population size.\n\n    K: number (optional)\n        Subpopulation size.\n\n    n: number (optional)\n        Number of draws.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.hypergeometric.factory();\n    > var out = fcn( 3, 20, 10, 7 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.hypergeometric.factory( 20, 10, 7 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.hypergeometric.PRNG":"\nrandom.array.hypergeometric.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.hypergeometric.PRNG;","random.array.hypergeometric.seed":"\nrandom.array.hypergeometric.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.hypergeometric.seed;","random.array.hypergeometric.seedLength":"\nrandom.array.hypergeometric.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.hypergeometric.seedLength;","random.array.hypergeometric.state":"\nrandom.array.hypergeometric.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.hypergeometric( 3, 20, 10, 7 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.hypergeometric.state\n    <Uint32Array>\n\n    > out = random.array.hypergeometric( 3, 20, 10, 7 )\n    <Float64Array>\n    > out = random.array.hypergeometric( 3, 20, 10, 7 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.hypergeometric.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.hypergeometric( 3, 20, 10, 7 )\n    <Float64Array>","random.array.hypergeometric.stateLength":"\nrandom.array.hypergeometric.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.hypergeometric.stateLength;","random.array.hypergeometric.byteLength":"\nrandom.array.hypergeometric.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.hypergeometric.byteLength;\n\n    See Also\n    --------\n    base.random.hypergeometric","random.array.invgamma":"\nrandom.array.invgamma( len, alpha, beta[, options] )\n    Returns an array containing pseudorandom numbers drawn from an inverse gamma\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    alpha: number\n        Shape parameter.\n\n    beta: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.invgamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.invgamma.assign( alpha, beta, out )\n    Fills an array with pseudorandom numbers drawn from an inverse gamma\n    distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        Shape parameter.\n\n    beta: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.invgamma.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.invgamma.factory( [alpha, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an inverse gamma distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        Shape parameter.\n\n    beta: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.invgamma.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.invgamma.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.invgamma.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.invgamma.PRNG;\n\n\nrandom.array.invgamma.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.invgamma.seed;\n\n\nrandom.array.invgamma.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.invgamma.seedLength;\n\n\nrandom.array.invgamma.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.invgamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.invgamma.state\n    <Uint32Array>\n\n    > out = random.array.invgamma( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.invgamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.invgamma.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.invgamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.invgamma.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.invgamma.stateLength;\n\n\nrandom.array.invgamma.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.invgamma.byteLength;\n\n    See Also\n    --------\n    base.random.invgamma, random.strided.invgamma\n","random.array.invgamma.assign":"\nrandom.array.invgamma.assign( alpha, beta, out )\n    Fills an array with pseudorandom numbers drawn from an inverse gamma\n    distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        Shape parameter.\n\n    beta: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.invgamma.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.invgamma.factory":"\nrandom.array.invgamma.factory( [alpha, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an inverse gamma distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        Shape parameter.\n\n    beta: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.invgamma.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.invgamma.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.invgamma.PRNG":"\nrandom.array.invgamma.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.invgamma.PRNG;","random.array.invgamma.seed":"\nrandom.array.invgamma.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.invgamma.seed;","random.array.invgamma.seedLength":"\nrandom.array.invgamma.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.invgamma.seedLength;","random.array.invgamma.state":"\nrandom.array.invgamma.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.invgamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.invgamma.state\n    <Uint32Array>\n\n    > out = random.array.invgamma( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.invgamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.invgamma.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.invgamma( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.invgamma.stateLength":"\nrandom.array.invgamma.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.invgamma.stateLength;","random.array.invgamma.byteLength":"\nrandom.array.invgamma.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.invgamma.byteLength;\n\n    See Also\n    --------\n    base.random.invgamma, random.strided.invgamma","random.array.kumaraswamy":"\nrandom.array.kumaraswamy( len, a, b[, options] )\n    Returns an array containing pseudorandom numbers drawn from Kumaraswamy's\n    double bounded distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.kumaraswamy.assign( a, b, out )\n    Fills an array with pseudorandom numbers drawn from Kumaraswamy's double\n    bounded distribution.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.kumaraswamy.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.kumaraswamy.factory( [a, b, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from Kumaraswamy's double bounded distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    a: number (optional)\n        First shape parameter.\n\n    b: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.kumaraswamy.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.kumaraswamy.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.kumaraswamy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.kumaraswamy.PRNG;\n\n\nrandom.array.kumaraswamy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.kumaraswamy.seed;\n\n\nrandom.array.kumaraswamy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.kumaraswamy.seedLength;\n\n\nrandom.array.kumaraswamy.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.kumaraswamy.state\n    <Uint32Array>\n\n    > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.kumaraswamy.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.kumaraswamy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.kumaraswamy.stateLength;\n\n\nrandom.array.kumaraswamy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.kumaraswamy.byteLength;\n\n    See Also\n    --------\n    base.random.kumaraswamy\n","random.array.kumaraswamy.assign":"\nrandom.array.kumaraswamy.assign( a, b, out )\n    Fills an array with pseudorandom numbers drawn from Kumaraswamy's double\n    bounded distribution.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.kumaraswamy.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.kumaraswamy.factory":"\nrandom.array.kumaraswamy.factory( [a, b, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from Kumaraswamy's double bounded distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    a: number (optional)\n        First shape parameter.\n\n    b: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.kumaraswamy.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.kumaraswamy.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.kumaraswamy.PRNG":"\nrandom.array.kumaraswamy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.kumaraswamy.PRNG;","random.array.kumaraswamy.seed":"\nrandom.array.kumaraswamy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.kumaraswamy.seed;","random.array.kumaraswamy.seedLength":"\nrandom.array.kumaraswamy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.kumaraswamy.seedLength;","random.array.kumaraswamy.state":"\nrandom.array.kumaraswamy.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.kumaraswamy.state\n    <Uint32Array>\n\n    > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.kumaraswamy.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.kumaraswamy.stateLength":"\nrandom.array.kumaraswamy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.kumaraswamy.stateLength;","random.array.kumaraswamy.byteLength":"\nrandom.array.kumaraswamy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.kumaraswamy.byteLength;\n\n    See Also\n    --------\n    base.random.kumaraswamy","random.array.laplace":"\nrandom.array.laplace( len, mu, b[, options] )\n    Returns an array containing pseudorandom numbers drawn from a Laplace\n    (double exponential) distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    mu: number\n        Mean.\n\n    b: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.laplace( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.laplace.assign( mu, b, out )\n    Fills an array with pseudorandom numbers drawn from a Laplace (double\n    exponential) distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Mean.\n\n    b: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.laplace.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.laplace.factory( [mu, b, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Laplace (double exponential) distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Mean.\n\n    b: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.laplace.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.laplace.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.laplace.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.laplace.PRNG;\n\n\nrandom.array.laplace.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.laplace.seed;\n\n\nrandom.array.laplace.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.laplace.seedLength;\n\n\nrandom.array.laplace.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.laplace( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.laplace.state\n    <Uint32Array>\n\n    > out = random.array.laplace( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.laplace( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.laplace.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.laplace( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.laplace.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.laplace.stateLength;\n\n\nrandom.array.laplace.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.laplace.byteLength;\n\n    See Also\n    --------\n    base.random.laplace\n","random.array.laplace.assign":"\nrandom.array.laplace.assign( mu, b, out )\n    Fills an array with pseudorandom numbers drawn from a Laplace (double\n    exponential) distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Mean.\n\n    b: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.laplace.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.laplace.factory":"\nrandom.array.laplace.factory( [mu, b, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Laplace (double exponential) distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Mean.\n\n    b: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.laplace.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.laplace.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.laplace.PRNG":"\nrandom.array.laplace.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.laplace.PRNG;","random.array.laplace.seed":"\nrandom.array.laplace.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.laplace.seed;","random.array.laplace.seedLength":"\nrandom.array.laplace.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.laplace.seedLength;","random.array.laplace.state":"\nrandom.array.laplace.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.laplace( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.laplace.state\n    <Uint32Array>\n\n    > out = random.array.laplace( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.laplace( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.laplace.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.laplace( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.laplace.stateLength":"\nrandom.array.laplace.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.laplace.stateLength;","random.array.laplace.byteLength":"\nrandom.array.laplace.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.laplace.byteLength;\n\n    See Also\n    --------\n    base.random.laplace","random.array.levy":"\nrandom.array.levy( len, mu, c[, options] )\n    Returns an array containing pseudorandom numbers drawn from a Lévy\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    mu: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.levy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.levy.assign( mu, c, out )\n    Fills an array with pseudorandom numbers drawn from a Lévy distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.levy.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.levy.factory( [mu, c, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Lévy distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Location parameter.\n\n    c: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.levy.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.levy.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.levy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.levy.PRNG;\n\n\nrandom.array.levy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.levy.seed;\n\n\nrandom.array.levy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.levy.seedLength;\n\n\nrandom.array.levy.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.levy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.levy.state\n    <Uint32Array>\n\n    > out = random.array.levy( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.levy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.levy.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.levy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.levy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.levy.stateLength;\n\n\nrandom.array.levy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.levy.byteLength;\n\n    See Also\n    --------\n    base.random.levy\n","random.array.levy.assign":"\nrandom.array.levy.assign( mu, c, out )\n    Fills an array with pseudorandom numbers drawn from a Lévy distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.levy.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.levy.factory":"\nrandom.array.levy.factory( [mu, c, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Lévy distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Location parameter.\n\n    c: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.levy.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.levy.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.levy.PRNG":"\nrandom.array.levy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.levy.PRNG;","random.array.levy.seed":"\nrandom.array.levy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.levy.seed;","random.array.levy.seedLength":"\nrandom.array.levy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.levy.seedLength;","random.array.levy.state":"\nrandom.array.levy.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.levy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.levy.state\n    <Uint32Array>\n\n    > out = random.array.levy( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.levy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.levy.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.levy( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.levy.stateLength":"\nrandom.array.levy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.levy.stateLength;","random.array.levy.byteLength":"\nrandom.array.levy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.levy.byteLength;\n\n    See Also\n    --------\n    base.random.levy","random.array.logistic":"\nrandom.array.logistic( len, mu, s[, options] )\n    Returns an array containing pseudorandom numbers drawn from a logistic\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    mu: number\n        Mean parameter.\n\n    s: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.logistic( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.logistic.assign( mu, s, out )\n    Fills an array with pseudorandom numbers drawn from a logistic distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Mean parameter.\n\n    s: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.logistic.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.logistic.factory( [mu, s, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a logistic distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Mean parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.logistic.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.logistic.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.logistic.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.logistic.PRNG;\n\n\nrandom.array.logistic.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.logistic.seed;\n\n\nrandom.array.logistic.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.logistic.seedLength;\n\n\nrandom.array.logistic.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.logistic( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.logistic.state\n    <Uint32Array>\n\n    > out = random.array.logistic( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.logistic( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.logistic.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.logistic( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.logistic.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.logistic.stateLength;\n\n\nrandom.array.logistic.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.logistic.byteLength;\n\n    See Also\n    --------\n    base.random.logistic\n","random.array.logistic.assign":"\nrandom.array.logistic.assign( mu, s, out )\n    Fills an array with pseudorandom numbers drawn from a logistic distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Mean parameter.\n\n    s: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.logistic.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.logistic.factory":"\nrandom.array.logistic.factory( [mu, s, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a logistic distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Mean parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.logistic.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.logistic.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.logistic.PRNG":"\nrandom.array.logistic.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.logistic.PRNG;","random.array.logistic.seed":"\nrandom.array.logistic.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.logistic.seed;","random.array.logistic.seedLength":"\nrandom.array.logistic.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.logistic.seedLength;","random.array.logistic.state":"\nrandom.array.logistic.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.logistic( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.logistic.state\n    <Uint32Array>\n\n    > out = random.array.logistic( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.logistic( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.logistic.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.logistic( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.logistic.stateLength":"\nrandom.array.logistic.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.logistic.stateLength;","random.array.logistic.byteLength":"\nrandom.array.logistic.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.logistic.byteLength;\n\n    See Also\n    --------\n    base.random.logistic","random.array.lognormal":"\nrandom.array.lognormal( len, mu, sigma[, options] )\n    Returns an array containing pseudorandom numbers drawn from a lognormal\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    mu: number\n        Location parameter.\n\n    sigma: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.lognormal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.lognormal.assign( mu, sigma, out )\n    Fills an array with pseudorandom numbers drawn from a lognormal\n    distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Location parameter.\n\n    sigma: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.lognormal.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.lognormal.factory( [mu, sigma, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a lognormal distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Location parameter.\n\n    sigma: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.lognormal.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.lognormal.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.lognormal.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.lognormal.PRNG;\n\n\nrandom.array.lognormal.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.lognormal.seed;\n\n\nrandom.array.lognormal.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.lognormal.seedLength;\n\n\nrandom.array.lognormal.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.lognormal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.lognormal.state\n    <Uint32Array>\n\n    > out = random.array.lognormal( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.lognormal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.lognormal.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.lognormal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.lognormal.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.lognormal.stateLength;\n\n\nrandom.array.lognormal.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.lognormal.byteLength;\n\n    See Also\n    --------\n    base.random.lognormal, random.strided.lognormal\n","random.array.lognormal.assign":"\nrandom.array.lognormal.assign( mu, sigma, out )\n    Fills an array with pseudorandom numbers drawn from a lognormal\n    distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Location parameter.\n\n    sigma: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.lognormal.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.lognormal.factory":"\nrandom.array.lognormal.factory( [mu, sigma, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a lognormal distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Location parameter.\n\n    sigma: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.lognormal.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.lognormal.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.lognormal.PRNG":"\nrandom.array.lognormal.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.lognormal.PRNG;","random.array.lognormal.seed":"\nrandom.array.lognormal.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.lognormal.seed;","random.array.lognormal.seedLength":"\nrandom.array.lognormal.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.lognormal.seedLength;","random.array.lognormal.state":"\nrandom.array.lognormal.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.lognormal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.lognormal.state\n    <Uint32Array>\n\n    > out = random.array.lognormal( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.lognormal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.lognormal.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.lognormal( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.lognormal.stateLength":"\nrandom.array.lognormal.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.lognormal.stateLength;","random.array.lognormal.byteLength":"\nrandom.array.lognormal.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.lognormal.byteLength;\n\n    See Also\n    --------\n    base.random.lognormal, random.strided.lognormal","random.array.minstd":"\nrandom.array.minstd( len[, options] )\n    Returns an array containing pseudorandom integers on the interval\n    `[1, 2147483646]`.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.minstd( 3 )\n    <Float64Array>\n\n\nrandom.array.minstd.normalized( len[, options] )\n    Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.minstd.normalized( 3 )\n    <Float64Array>\n\n\nrandom.array.minstd.factory( [options] )\n    Returns a function for creating arrays containing pseudorandom numbers\n    generated using a linear congruential pseudorandom number generator (LCG).\n\n    The returned function and its attached `normalized` method accept the\n    following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.idtype: string (optional)\n        Default output array data type when generating integers. Default:\n        'float64'.\n\n    options.ndtype: string (optional)\n        Default output array data type when generating normalized numbers.\n        Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.minstd.factory();\n    > var out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.minstd.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.minstd.PRNG;\n\n\nrandom.array.minstd.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.minstd.seed;\n\n\nrandom.array.minstd.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.minstd.seedLength;\n\n\nrandom.array.minstd.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.minstd( 3 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.minstd.state;\n\n    > out = random.array.minstd( 3 )\n    <Float64Array>\n    > out = random.array.minstd( 3 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.minstd.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.minstd( 3 )\n    <Float64Array>\n\n\nrandom.array.minstd.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.minstd.stateLength;\n\n\nrandom.array.minstd.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.minstd.byteLength;\n\n    See Also\n    --------\n    random.array.minstdShuffle, random.array.randu, base.random.minstd, random.strided.minstd\n","random.array.minstd.normalized":"\nrandom.array.minstd.normalized( len[, options] )\n    Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.minstd.normalized( 3 )\n    <Float64Array>","random.array.minstd.factory":"\nrandom.array.minstd.factory( [options] )\n    Returns a function for creating arrays containing pseudorandom numbers\n    generated using a linear congruential pseudorandom number generator (LCG).\n\n    The returned function and its attached `normalized` method accept the\n    following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.idtype: string (optional)\n        Default output array data type when generating integers. Default:\n        'float64'.\n\n    options.ndtype: string (optional)\n        Default output array data type when generating normalized numbers.\n        Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.minstd.factory();\n    > var out = fcn( 3 )\n    <Float64Array>","random.array.minstd.PRNG":"\nrandom.array.minstd.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.minstd.PRNG;","random.array.minstd.seed":"\nrandom.array.minstd.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.minstd.seed;","random.array.minstd.seedLength":"\nrandom.array.minstd.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.minstd.seedLength;","random.array.minstd.state":"\nrandom.array.minstd.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.minstd( 3 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.minstd.state;\n\n    > out = random.array.minstd( 3 )\n    <Float64Array>\n    > out = random.array.minstd( 3 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.minstd.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.minstd( 3 )\n    <Float64Array>","random.array.minstd.stateLength":"\nrandom.array.minstd.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.minstd.stateLength;","random.array.minstd.byteLength":"\nrandom.array.minstd.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.minstd.byteLength;\n\n    See Also\n    --------\n    random.array.minstdShuffle, random.array.randu, base.random.minstd, random.strided.minstd","random.array.minstdShuffle":"\nrandom.array.minstdShuffle( len[, options] )\n    Returns an array containing pseudorandom integers on the interval\n    `[1, 2147483646]`.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.minstdShuffle( 3 )\n    <Float64Array>\n\n\nrandom.array.minstdShuffle.normalized( len[, options] )\n    Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.minstdShuffle.normalized( 3 )\n    <Float64Array>\n\n\nrandom.array.minstdShuffle.factory( [options] )\n    Returns a function for creating arrays containing pseudorandom numbers\n    generated using a linear congruential pseudorandom number generator (LCG)\n    whose output is shuffled.\n\n    The returned function and its attached `normalized` method accept the\n    following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.idtype: string (optional)\n        Default output array data type when generating integers. Default:\n        'float64'.\n\n    options.ndtype: string (optional)\n        Default output array data type when generating normalized numbers.\n        Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.minstdShuffle.factory();\n    > var out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.minstdShuffle.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.minstdShuffle.PRNG;\n\n\nrandom.array.minstdShuffle.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.minstdShuffle.seed;\n\n\nrandom.array.minstdShuffle.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.minstdShuffle.seedLength;\n\n\nrandom.array.minstdShuffle.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.minstdShuffle( 3 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.minstdShuffle.state;\n\n    > out = random.array.minstdShuffle( 3 )\n    <Float64Array>\n    > out = random.array.minstdShuffle( 3 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.minstdShuffle.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.minstdShuffle( 3 )\n    <Float64Array>\n\n\nrandom.array.minstdShuffle.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.minstdShuffle.stateLength;\n\n\nrandom.array.minstdShuffle.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.minstdShuffle.byteLength;\n\n    See Also\n    --------\n    random.array.minstd, random.array.randu, base.random.minstdShuffle, random.strided.minstdShuffle\n","random.array.minstdShuffle.normalized":"\nrandom.array.minstdShuffle.normalized( len[, options] )\n    Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.minstdShuffle.normalized( 3 )\n    <Float64Array>","random.array.minstdShuffle.factory":"\nrandom.array.minstdShuffle.factory( [options] )\n    Returns a function for creating arrays containing pseudorandom numbers\n    generated using a linear congruential pseudorandom number generator (LCG)\n    whose output is shuffled.\n\n    The returned function and its attached `normalized` method accept the\n    following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.idtype: string (optional)\n        Default output array data type when generating integers. Default:\n        'float64'.\n\n    options.ndtype: string (optional)\n        Default output array data type when generating normalized numbers.\n        Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.minstdShuffle.factory();\n    > var out = fcn( 3 )\n    <Float64Array>","random.array.minstdShuffle.PRNG":"\nrandom.array.minstdShuffle.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.minstdShuffle.PRNG;","random.array.minstdShuffle.seed":"\nrandom.array.minstdShuffle.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.minstdShuffle.seed;","random.array.minstdShuffle.seedLength":"\nrandom.array.minstdShuffle.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.minstdShuffle.seedLength;","random.array.minstdShuffle.state":"\nrandom.array.minstdShuffle.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.minstdShuffle( 3 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.minstdShuffle.state;\n\n    > out = random.array.minstdShuffle( 3 )\n    <Float64Array>\n    > out = random.array.minstdShuffle( 3 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.minstdShuffle.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.minstdShuffle( 3 )\n    <Float64Array>","random.array.minstdShuffle.stateLength":"\nrandom.array.minstdShuffle.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.minstdShuffle.stateLength;","random.array.minstdShuffle.byteLength":"\nrandom.array.minstdShuffle.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.minstdShuffle.byteLength;\n\n    See Also\n    --------\n    random.array.minstd, random.array.randu, base.random.minstdShuffle, random.strided.minstdShuffle","random.array.mt19937":"\nrandom.array.mt19937( len[, options] )\n    Returns an array containing pseudorandom integers on the interval\n    `[0, 4294967295]`.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.mt19937( 3 )\n    <Float64Array>\n\n\nrandom.array.mt19937.normalized( len[, options] )\n    Returns an array containing pseudorandom numbers on the interval `[0, 1)`\n    with 53-bit precision.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.mt19937.normalized( 3 )\n    <Float64Array>\n\n\nrandom.array.mt19937.factory( [options] )\n    Returns a function for creating arrays containing pseudorandom numbers\n    generated using a 32-bit Mersenne Twister pseudorandom number generator.\n\n    The returned function and its attached `normalized` method accept the\n    following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.idtype: string (optional)\n        Default output array data type when generating integers. Default:\n        'float64'.\n\n    options.ndtype: string (optional)\n        Default output array data type when generating normalized numbers.\n        Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.mt19937.factory();\n    > var out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.mt19937.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.mt19937.PRNG;\n\n\nrandom.array.mt19937.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.mt19937.seed;\n\n\nrandom.array.mt19937.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.mt19937.seedLength;\n\n\nrandom.array.mt19937.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.mt19937( 3 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.mt19937.state;\n\n    > out = random.array.mt19937( 3 )\n    <Float64Array>\n    > out = random.array.mt19937( 3 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.mt19937.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.mt19937( 3 )\n    <Float64Array>\n\n\nrandom.array.mt19937.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.mt19937.stateLength;\n\n\nrandom.array.mt19937.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.mt19937.byteLength;\n\n    See Also\n    --------\n    random.array.randu, base.random.mt19937, random.strided.mt19937\n","random.array.mt19937.normalized":"\nrandom.array.mt19937.normalized( len[, options] )\n    Returns an array containing pseudorandom numbers on the interval `[0, 1)`\n    with 53-bit precision.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.mt19937.normalized( 3 )\n    <Float64Array>","random.array.mt19937.factory":"\nrandom.array.mt19937.factory( [options] )\n    Returns a function for creating arrays containing pseudorandom numbers\n    generated using a 32-bit Mersenne Twister pseudorandom number generator.\n\n    The returned function and its attached `normalized` method accept the\n    following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.idtype: string (optional)\n        Default output array data type when generating integers. Default:\n        'float64'.\n\n    options.ndtype: string (optional)\n        Default output array data type when generating normalized numbers.\n        Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.mt19937.factory();\n    > var out = fcn( 3 )\n    <Float64Array>","random.array.mt19937.PRNG":"\nrandom.array.mt19937.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.mt19937.PRNG;","random.array.mt19937.seed":"\nrandom.array.mt19937.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.mt19937.seed;","random.array.mt19937.seedLength":"\nrandom.array.mt19937.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.mt19937.seedLength;","random.array.mt19937.state":"\nrandom.array.mt19937.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.mt19937( 3 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.mt19937.state;\n\n    > out = random.array.mt19937( 3 )\n    <Float64Array>\n    > out = random.array.mt19937( 3 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.mt19937.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.mt19937( 3 )\n    <Float64Array>","random.array.mt19937.stateLength":"\nrandom.array.mt19937.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.mt19937.stateLength;","random.array.mt19937.byteLength":"\nrandom.array.mt19937.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.mt19937.byteLength;\n\n    See Also\n    --------\n    random.array.randu, base.random.mt19937, random.strided.mt19937","random.array.negativeBinomial":"\nrandom.array.negativeBinomial( len, r, p[, options] )\n    Returns an array containing pseudorandom numbers drawn from a negative\n    binomial distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.negativeBinomial( 3, 10, 0.5 )\n    <Float64Array>\n\n\nrandom.array.negativeBinomial.assign( r, p, out )\n    Fills an array with pseudorandom numbers drawn from a negative binomial\n    distribution.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.negativeBinomial.assign( 10, 0.5, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.negativeBinomial.factory( [r, p, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a negative binomial distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    r: number (optional)\n        Number of successes until experiment is stopped.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.negativeBinomial.factory();\n    > var out = fcn( 3, 10, 0.5 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.negativeBinomial.factory( 10, 0.5 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.negativeBinomial.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.negativeBinomial.PRNG;\n\n\nrandom.array.negativeBinomial.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.negativeBinomial.seed;\n\n\nrandom.array.negativeBinomial.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.negativeBinomial.seedLength;\n\n\nrandom.array.negativeBinomial.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.negativeBinomial( 3, 10, 0.5 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.negativeBinomial.state\n    <Uint32Array>\n\n    > out = random.array.negativeBinomial( 3, 10, 0.5 )\n    <Float64Array>\n    > out = random.array.negativeBinomial( 3, 10, 0.5 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.negativeBinomial.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.negativeBinomial( 3, 10, 0.5 )\n    <Float64Array>\n\n\nrandom.array.negativeBinomial.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.negativeBinomial.stateLength;\n\n\nrandom.array.negativeBinomial.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.negativeBinomial.byteLength;\n\n    See Also\n    --------\n    random.array.binomial, base.random.negativeBinomial\n","random.array.negativeBinomial.assign":"\nrandom.array.negativeBinomial.assign( r, p, out )\n    Fills an array with pseudorandom numbers drawn from a negative binomial\n    distribution.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.negativeBinomial.assign( 10, 0.5, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.negativeBinomial.factory":"\nrandom.array.negativeBinomial.factory( [r, p, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a negative binomial distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    r: number (optional)\n        Number of successes until experiment is stopped.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.negativeBinomial.factory();\n    > var out = fcn( 3, 10, 0.5 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.negativeBinomial.factory( 10, 0.5 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.negativeBinomial.PRNG":"\nrandom.array.negativeBinomial.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.negativeBinomial.PRNG;","random.array.negativeBinomial.seed":"\nrandom.array.negativeBinomial.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.negativeBinomial.seed;","random.array.negativeBinomial.seedLength":"\nrandom.array.negativeBinomial.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.negativeBinomial.seedLength;","random.array.negativeBinomial.state":"\nrandom.array.negativeBinomial.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.negativeBinomial( 3, 10, 0.5 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.negativeBinomial.state\n    <Uint32Array>\n\n    > out = random.array.negativeBinomial( 3, 10, 0.5 )\n    <Float64Array>\n    > out = random.array.negativeBinomial( 3, 10, 0.5 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.negativeBinomial.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.negativeBinomial( 3, 10, 0.5 )\n    <Float64Array>","random.array.negativeBinomial.stateLength":"\nrandom.array.negativeBinomial.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.negativeBinomial.stateLength;","random.array.negativeBinomial.byteLength":"\nrandom.array.negativeBinomial.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.negativeBinomial.byteLength;\n\n    See Also\n    --------\n    random.array.binomial, base.random.negativeBinomial","random.array.normal":"\nrandom.array.normal( len, mu, sigma[, options] )\n    Returns an array containing pseudorandom numbers drawn from a normal\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    mu: number\n        Mean.\n\n    sigma: number\n        Standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.normal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.normal.assign( mu, sigma, out )\n    Fills an array with pseudorandom numbers drawn from a normal distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Mean.\n\n    sigma: number\n        Standard deviation.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.normal.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.normal.factory( [mu, sigma, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a normal distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Mean.\n\n    sigma: number (optional)\n        Standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.normal.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.normal.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.normal.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.normal.PRNG;\n\n\nrandom.array.normal.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.normal.seed;\n\n\nrandom.array.normal.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.normal.seedLength;\n\n\nrandom.array.normal.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.normal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.normal.state\n    <Uint32Array>\n\n    > out = random.array.normal( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.normal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.normal.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.normal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.normal.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.normal.stateLength;\n\n\nrandom.array.normal.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.normal.byteLength;\n\n    See Also\n    --------\n    base.random.normal, random.strided.normal\n","random.array.normal.assign":"\nrandom.array.normal.assign( mu, sigma, out )\n    Fills an array with pseudorandom numbers drawn from a normal distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Mean.\n\n    sigma: number\n        Standard deviation.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.normal.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.normal.factory":"\nrandom.array.normal.factory( [mu, sigma, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a normal distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Mean.\n\n    sigma: number (optional)\n        Standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.normal.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.normal.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.normal.PRNG":"\nrandom.array.normal.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.normal.PRNG;","random.array.normal.seed":"\nrandom.array.normal.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.normal.seed;","random.array.normal.seedLength":"\nrandom.array.normal.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.normal.seedLength;","random.array.normal.state":"\nrandom.array.normal.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.normal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.normal.state\n    <Uint32Array>\n\n    > out = random.array.normal( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.normal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.normal.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.normal( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.normal.stateLength":"\nrandom.array.normal.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.normal.stateLength;","random.array.normal.byteLength":"\nrandom.array.normal.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.normal.byteLength;\n\n    See Also\n    --------\n    base.random.normal, random.strided.normal","random.array.pareto1":"\nrandom.array.pareto1( len, alpha, beta[, options] )\n    Returns an array containing pseudorandom numbers drawn from a Pareto (Type\n    I) distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    alpha: number\n        Shape parameter.\n\n    beta: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.pareto1( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.pareto1.assign( alpha, beta, out )\n    Fills an array with pseudorandom numbers drawn from a Pareto (Type I)\n    distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        Shape parameter.\n\n    beta: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.pareto1.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.pareto1.factory( [alpha, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Pareto (Type I) distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        Shape parameter.\n\n    beta: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.pareto1.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.pareto1.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.pareto1.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.pareto1.PRNG;\n\n\nrandom.array.pareto1.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.pareto1.seed;\n\n\nrandom.array.pareto1.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.pareto1.seedLength;\n\n\nrandom.array.pareto1.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.pareto1( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.pareto1.state\n    <Uint32Array>\n\n    > out = random.array.pareto1( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.pareto1( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.pareto1.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.pareto1( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.pareto1.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.pareto1.stateLength;\n\n\nrandom.array.pareto1.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.pareto1.byteLength;\n\n    See Also\n    --------\n    base.random.pareto1\n","random.array.pareto1.assign":"\nrandom.array.pareto1.assign( alpha, beta, out )\n    Fills an array with pseudorandom numbers drawn from a Pareto (Type I)\n    distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        Shape parameter.\n\n    beta: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.pareto1.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.pareto1.factory":"\nrandom.array.pareto1.factory( [alpha, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Pareto (Type I) distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        Shape parameter.\n\n    beta: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.pareto1.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.pareto1.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.pareto1.PRNG":"\nrandom.array.pareto1.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.pareto1.PRNG;","random.array.pareto1.seed":"\nrandom.array.pareto1.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.pareto1.seed;","random.array.pareto1.seedLength":"\nrandom.array.pareto1.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.pareto1.seedLength;","random.array.pareto1.state":"\nrandom.array.pareto1.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.pareto1( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.pareto1.state\n    <Uint32Array>\n\n    > out = random.array.pareto1( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.pareto1( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.pareto1.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.pareto1( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.pareto1.stateLength":"\nrandom.array.pareto1.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.pareto1.stateLength;","random.array.pareto1.byteLength":"\nrandom.array.pareto1.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.pareto1.byteLength;\n\n    See Also\n    --------\n    base.random.pareto1","random.array.poisson":"\nrandom.array.poisson( len, lambda[, options] )\n    Returns an array containing pseudorandom numbers drawn from a Poisson\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    lambda: number\n        Mean parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.poisson( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.poisson.assign( lambda, out )\n    Fills an array with pseudorandom numbers drawn from a Poisson distribution.\n\n    Parameters\n    ----------\n    lambda: number\n        Mean parameter.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.poisson.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.poisson.factory( [lambda, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Poisson distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    lambda: number (optional)\n        Mean parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.poisson.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.poisson.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.poisson.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.poisson.PRNG;\n\n\nrandom.array.poisson.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.poisson.seed;\n\n\nrandom.array.poisson.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.poisson.seedLength;\n\n\nrandom.array.poisson.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.poisson( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.poisson.state\n    <Uint32Array>\n\n    > out = random.array.poisson( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.poisson( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.poisson.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.poisson( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.poisson.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.poisson.stateLength;\n\n\nrandom.array.poisson.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.poisson.byteLength;\n\n    See Also\n    --------\n    base.random.poisson, random.strided.poisson\n","random.array.poisson.assign":"\nrandom.array.poisson.assign( lambda, out )\n    Fills an array with pseudorandom numbers drawn from a Poisson distribution.\n\n    Parameters\n    ----------\n    lambda: number\n        Mean parameter.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.poisson.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.poisson.factory":"\nrandom.array.poisson.factory( [lambda, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Poisson distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    lambda: number (optional)\n        Mean parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.poisson.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.poisson.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.poisson.PRNG":"\nrandom.array.poisson.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.poisson.PRNG;","random.array.poisson.seed":"\nrandom.array.poisson.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.poisson.seed;","random.array.poisson.seedLength":"\nrandom.array.poisson.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.poisson.seedLength;","random.array.poisson.state":"\nrandom.array.poisson.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.poisson( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.poisson.state\n    <Uint32Array>\n\n    > out = random.array.poisson( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.poisson( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.poisson.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.poisson( 3, 2.0 )\n    <Float64Array>","random.array.poisson.stateLength":"\nrandom.array.poisson.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.poisson.stateLength;","random.array.poisson.byteLength":"\nrandom.array.poisson.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.poisson.byteLength;\n\n    See Also\n    --------\n    base.random.poisson, random.strided.poisson","random.array.randu":"\nrandom.array.randu( len[, options] )\n    Returns an array containing uniformly distributed pseudorandom numbers\n    between 0 and 1.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.randu( 3 )\n    <Float64Array>\n\n\nrandom.array.randu.factory( [options] )\n    Returns a function for creating arrays containing uniformly distributed\n    pseudorandom numbers between 0 and 1.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: `'mt19937'`.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.randu.factory();\n    > var out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.randu.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.randu.PRNG;\n\n\nrandom.array.randu.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.randu.seed;\n\n\nrandom.array.randu.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.randu.seedLength;\n\n\nrandom.array.randu.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.randu( 3 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.randu.state;\n\n    > out = random.array.randu( 3 )\n    <Float64Array>\n    > out = random.array.randu( 3 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.randu.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.randu( 3 )\n    <Float64Array>\n\n\nrandom.array.randu.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.randu.stateLength;\n\n\nrandom.array.randu.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.randu.byteLength;\n\n    See Also\n    --------\n    random.array.uniform, base.random.randu, random.strided.randu\n","random.array.randu.factory":"\nrandom.array.randu.factory( [options] )\n    Returns a function for creating arrays containing uniformly distributed\n    pseudorandom numbers between 0 and 1.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: `'mt19937'`.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.randu.factory();\n    > var out = fcn( 3 )\n    <Float64Array>","random.array.randu.PRNG":"\nrandom.array.randu.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.randu.PRNG;","random.array.randu.seed":"\nrandom.array.randu.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.randu.seed;","random.array.randu.seedLength":"\nrandom.array.randu.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.randu.seedLength;","random.array.randu.state":"\nrandom.array.randu.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.randu( 3 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.randu.state;\n\n    > out = random.array.randu( 3 )\n    <Float64Array>\n    > out = random.array.randu( 3 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.randu.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.randu( 3 )\n    <Float64Array>","random.array.randu.stateLength":"\nrandom.array.randu.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.randu.stateLength;","random.array.randu.byteLength":"\nrandom.array.randu.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.randu.byteLength;\n\n    See Also\n    --------\n    random.array.uniform, base.random.randu, random.strided.randu","random.array.rayleigh":"\nrandom.array.rayleigh( len, sigma[, options] )\n    Returns an array containing pseudorandom numbers drawn from a Rayleigh\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    sigma: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.rayleigh( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.rayleigh.assign( sigma, out )\n    Fills an array with pseudorandom numbers drawn from a Rayleigh distribution.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.rayleigh.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.rayleigh.factory( [sigma, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Rayleigh distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    sigma: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.rayleigh.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.rayleigh.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.rayleigh.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.rayleigh.PRNG;\n\n\nrandom.array.rayleigh.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.rayleigh.seed;\n\n\nrandom.array.rayleigh.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.rayleigh.seedLength;\n\n\nrandom.array.rayleigh.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.rayleigh( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.rayleigh.state\n    <Uint32Array>\n\n    > out = random.array.rayleigh( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.rayleigh( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.rayleigh.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.rayleigh( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.rayleigh.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.rayleigh.stateLength;\n\n\nrandom.array.rayleigh.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.rayleigh.byteLength;\n\n    See Also\n    --------\n    base.random.rayleigh, random.strided.rayleigh\n","random.array.rayleigh.assign":"\nrandom.array.rayleigh.assign( sigma, out )\n    Fills an array with pseudorandom numbers drawn from a Rayleigh distribution.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.rayleigh.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.rayleigh.factory":"\nrandom.array.rayleigh.factory( [sigma, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Rayleigh distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    sigma: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.rayleigh.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.rayleigh.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.rayleigh.PRNG":"\nrandom.array.rayleigh.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.rayleigh.PRNG;","random.array.rayleigh.seed":"\nrandom.array.rayleigh.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.rayleigh.seed;","random.array.rayleigh.seedLength":"\nrandom.array.rayleigh.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.rayleigh.seedLength;","random.array.rayleigh.state":"\nrandom.array.rayleigh.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.rayleigh( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.rayleigh.state\n    <Uint32Array>\n\n    > out = random.array.rayleigh( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.rayleigh( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.rayleigh.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.rayleigh( 3, 2.0 )\n    <Float64Array>","random.array.rayleigh.stateLength":"\nrandom.array.rayleigh.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.rayleigh.stateLength;","random.array.rayleigh.byteLength":"\nrandom.array.rayleigh.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.rayleigh.byteLength;\n\n    See Also\n    --------\n    base.random.rayleigh, random.strided.rayleigh","random.array.t":"\nrandom.array.t( len, v[, options] )\n    Returns an array containing pseudorandom numbers drawn from a Student's t\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    v: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.t( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.t.assign( v, out )\n    Fills an array with pseudorandom numbers drawn from a Student's t\n    distribution.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.t.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.t.factory( [v, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Student's t distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    v: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.t.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.t.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.t.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.t.PRNG;\n\n\nrandom.array.t.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.t.seed;\n\n\nrandom.array.t.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.t.seedLength;\n\n\nrandom.array.t.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.t( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.t.state\n    <Uint32Array>\n\n    > out = random.array.t( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.t( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.t.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.t( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.t.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.t.stateLength;\n\n\nrandom.array.t.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.t.byteLength;\n\n    See Also\n    --------\n    base.random.t, random.strided.t\n","random.array.t.assign":"\nrandom.array.t.assign( v, out )\n    Fills an array with pseudorandom numbers drawn from a Student's t\n    distribution.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.t.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.t.factory":"\nrandom.array.t.factory( [v, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Student's t distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    v: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.t.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.t.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.t.PRNG":"\nrandom.array.t.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.t.PRNG;","random.array.t.seed":"\nrandom.array.t.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.t.seed;","random.array.t.seedLength":"\nrandom.array.t.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.t.seedLength;","random.array.t.state":"\nrandom.array.t.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.t( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.t.state\n    <Uint32Array>\n\n    > out = random.array.t( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.t( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.t.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.t( 3, 2.0 )\n    <Float64Array>","random.array.t.stateLength":"\nrandom.array.t.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.t.stateLength;","random.array.t.byteLength":"\nrandom.array.t.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.t.byteLength;\n\n    See Also\n    --------\n    base.random.t, random.strided.t","random.array.triangular":"\nrandom.array.triangular( len, a, b, c[, options] )\n    Returns an array containing pseudorandom numbers drawn from a triangular\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n\nrandom.array.triangular.assign( a, b, c, out )\n    Fills an array with pseudorandom numbers drawn from a triangular\n    distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.triangular.assign( 2.0, 5.0, 3.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.triangular.factory( [a, b, c, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a triangular distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    c: number (optional)\n        Mode.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.triangular.factory();\n    > var out = fcn( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.triangular.factory( 2.0, 5.0, 3.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.triangular.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.triangular.PRNG;\n\n\nrandom.array.triangular.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.triangular.seed;\n\n\nrandom.array.triangular.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.triangular.seedLength;\n\n\nrandom.array.triangular.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.triangular.state\n    <Uint32Array>\n\n    > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n    > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.triangular.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n\nrandom.array.triangular.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.triangular.stateLength;\n\n\nrandom.array.triangular.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.triangular.byteLength;\n\n    See Also\n    --------\n    base.random.triangular\n","random.array.triangular.assign":"\nrandom.array.triangular.assign( a, b, c, out )\n    Fills an array with pseudorandom numbers drawn from a triangular\n    distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.triangular.assign( 2.0, 5.0, 3.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.triangular.factory":"\nrandom.array.triangular.factory( [a, b, c, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a triangular distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    c: number (optional)\n        Mode.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.triangular.factory();\n    > var out = fcn( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.triangular.factory( 2.0, 5.0, 3.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.triangular.PRNG":"\nrandom.array.triangular.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.triangular.PRNG;","random.array.triangular.seed":"\nrandom.array.triangular.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.triangular.seed;","random.array.triangular.seedLength":"\nrandom.array.triangular.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.triangular.seedLength;","random.array.triangular.state":"\nrandom.array.triangular.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.triangular.state\n    <Uint32Array>\n\n    > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n    > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.triangular.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>","random.array.triangular.stateLength":"\nrandom.array.triangular.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.triangular.stateLength;","random.array.triangular.byteLength":"\nrandom.array.triangular.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.triangular.byteLength;\n\n    See Also\n    --------\n    base.random.triangular","random.array.uniform":"\nrandom.array.uniform( len, a, b[, options] )\n    Returns an array containing pseudorandom numbers drawn from a continuous\n    uniform distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.uniform( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.uniform.assign( a, b, out )\n    Fills an array with pseudorandom numbers drawn from a continuous uniform\n    distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.uniform.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.uniform.factory( [a, b, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a continuous uniform distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.uniform.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.uniform.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.uniform.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.uniform.PRNG;\n\n\nrandom.array.uniform.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.uniform.seed;\n\n\nrandom.array.uniform.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.uniform.seedLength;\n\n\nrandom.array.uniform.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.uniform( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.uniform.state\n    <Uint32Array>\n\n    > out = random.array.uniform( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.uniform( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.uniform.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.uniform( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.uniform.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.uniform.stateLength;\n\n\nrandom.array.uniform.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.uniform.byteLength;\n\n    See Also\n    --------\n    random.array.discreteUniform, base.random.uniform, random.strided.uniform\n","random.array.uniform.assign":"\nrandom.array.uniform.assign( a, b, out )\n    Fills an array with pseudorandom numbers drawn from a continuous uniform\n    distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.uniform.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.uniform.factory":"\nrandom.array.uniform.factory( [a, b, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a continuous uniform distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.uniform.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.uniform.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.uniform.PRNG":"\nrandom.array.uniform.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.uniform.PRNG;","random.array.uniform.seed":"\nrandom.array.uniform.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.uniform.seed;","random.array.uniform.seedLength":"\nrandom.array.uniform.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.uniform.seedLength;","random.array.uniform.state":"\nrandom.array.uniform.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.uniform( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.uniform.state\n    <Uint32Array>\n\n    > out = random.array.uniform( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.uniform( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.uniform.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.uniform( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.uniform.stateLength":"\nrandom.array.uniform.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.uniform.stateLength;","random.array.uniform.byteLength":"\nrandom.array.uniform.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.uniform.byteLength;\n\n    See Also\n    --------\n    random.array.discreteUniform, base.random.uniform, random.strided.uniform","random.array.weibull":"\nrandom.array.weibull( len, k, lambda[, options] )\n    Returns an array containing pseudorandom numbers drawn from a Weibull\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    k: number\n        Scale parameter.\n\n    lambda: number\n        Shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.weibull( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.weibull.assign( k, lambda, out )\n    Fills an array with pseudorandom numbers drawn from a Weibull distribution.\n\n    Parameters\n    ----------\n    k: number\n        Scale parameter.\n\n    lambda: number\n        Shape parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.weibull.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.weibull.factory( [k, lambda, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Weibull distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Scale parameter.\n\n    lambda: number (optional)\n        Shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.weibull.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.weibull.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.weibull.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.weibull.PRNG;\n\n\nrandom.array.weibull.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.weibull.seed;\n\n\nrandom.array.weibull.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.weibull.seedLength;\n\n\nrandom.array.weibull.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.weibull( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.weibull.state\n    <Uint32Array>\n\n    > out = random.array.weibull( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.weibull( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.weibull.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.weibull( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.weibull.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.weibull.stateLength;\n\n\nrandom.array.weibull.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.weibull.byteLength;\n\n    See Also\n    --------\n    base.random.weibull, random.strided.weibull\n","random.array.weibull.assign":"\nrandom.array.weibull.assign( k, lambda, out )\n    Fills an array with pseudorandom numbers drawn from a Weibull distribution.\n\n    Parameters\n    ----------\n    k: number\n        Scale parameter.\n\n    lambda: number\n        Shape parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.weibull.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.weibull.factory":"\nrandom.array.weibull.factory( [k, lambda, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Weibull distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Scale parameter.\n\n    lambda: number (optional)\n        Shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.weibull.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.weibull.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.weibull.PRNG":"\nrandom.array.weibull.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.weibull.PRNG;","random.array.weibull.seed":"\nrandom.array.weibull.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.weibull.seed;","random.array.weibull.seedLength":"\nrandom.array.weibull.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.weibull.seedLength;","random.array.weibull.state":"\nrandom.array.weibull.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.weibull( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.weibull.state\n    <Uint32Array>\n\n    > out = random.array.weibull( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.weibull( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.weibull.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.weibull( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.weibull.stateLength":"\nrandom.array.weibull.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.weibull.stateLength;","random.array.weibull.byteLength":"\nrandom.array.weibull.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.weibull.byteLength;\n\n    See Also\n    --------\n    base.random.weibull, random.strided.weibull","random.iterators.arcsine":"\nrandom.iterators.arcsine( a, b[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from an\n    arcsine distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.arcsine( 0.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.arcsine\n","random.iterators.bernoulli":"\nrandom.iterators.bernoulli( p[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Bernoulli distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.bernoulli( 0.3 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.bernoulli\n","random.iterators.beta":"\nrandom.iterators.beta( α, β[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    beta distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    The function throws an error if `α <= 0` or `β <= 0`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.beta( 1.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.beta\n","random.iterators.betaprime":"\nrandom.iterators.betaprime( α, β[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    beta prime distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    The function throws an error if `α <= 0` or `β <= 0`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.betaprime( 1.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.betaprime\n","random.iterators.binomial":"\nrandom.iterators.binomial( n, p[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    binomial distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.binomial( 10, 0.3 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.binomial\n","random.iterators.boxMuller":"\nrandom.iterators.boxMuller( [options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    standard normal distribution using the Box-Muller transform.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.boxMuller();\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.boxMuller\n","random.iterators.cauchy":"\nrandom.iterators.cauchy( x0, Ɣ[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Cauchy distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.seed: any\n        Pseudorandom number generator seed.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.cauchy( 0.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.cauchy\n","random.iterators.chi":"\nrandom.iterators.chi( k[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a chi\n    distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.chi( 1.5 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.chi\n","random.iterators.chisquare":"\nrandom.iterators.chisquare( k[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    chi-square distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.chisquare( 1.5 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.chisquare\n","random.iterators.cosine":"\nrandom.iterators.cosine( μ, s[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a raised\n    cosine distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.cosine( 0.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.cosine\n","random.iterators.discreteUniform":"\nrandom.iterators.discreteUniform( a, b[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    discrete uniform distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom integers. If provided, the `state` and `seed`\n        options are ignored. In order to seed the returned iterator, one must\n        seed the provided `prng` (assuming the provided `prng` is seedable). The\n        provided PRNG must have `MIN` and `MAX` properties specifying the\n        minimum and maximum possible pseudorandom integers.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.discreteUniform( 0, 3 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.discreteUniform\n","random.iterators.erlang":"\nrandom.iterators.erlang( k, λ[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from an Erlang\n    distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If `k` is not a positive integer or `λ <= 0`, the function throws an error.\n\n    Parameters\n    ----------\n    k: integer\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.erlang( 1, 1.5 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.erlang\n","random.iterators.exponential":"\nrandom.iterators.exponential( λ[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from an\n    exponential distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.exponential( 1.5 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.exponential\n","random.iterators.f":"\nrandom.iterators.f( d1, d2[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from an F\n    distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    The function throws an error if `d1 <= 0` or `d2 <= 0`.\n\n    Parameters\n    ----------\n    d1: number\n        Degrees of freedom.\n\n    d2: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.f( 1.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.f\n","random.iterators.frechet":"\nrandom.iterators.frechet( α, s, m[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Fréchet\n    distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    The function throws an error if `α <= 0` or `s <= 0`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.frechet( 1.0, 1.0, 0.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.frechet\n","random.iterators.gamma":"\nrandom.iterators.gamma( α, β[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a gamma\n    distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    The function throws an error if `α <= 0` or `β <= 0`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.gamma( 1.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.gamma\n","random.iterators.geometric":"\nrandom.iterators.geometric( p[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    geometric distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.geometric( 0.3 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.geometric\n","random.iterators.gumbel":"\nrandom.iterators.gumbel( μ, β[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Gumbel\n    distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.gumbel( 0.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.gumbel\n","random.iterators.hypergeometric":"\nrandom.iterators.hypergeometric( N, K, n[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    hypergeometric distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    `N`, `K`, and `n` must all be nonnegative integers; otherwise, the function\n    throws an error.\n\n    If `n > N` or `K > N`, the function throws an error.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.hypergeometric( 20, 10, 7 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.hypergeometric\n","random.iterators.improvedZiggurat":"\nrandom.iterators.improvedZiggurat( [options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    standard normal distribution using the Improved Ziggurat algorithm.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.improvedZiggurat();\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.improvedZiggurat\n","random.iterators.invgamma":"\nrandom.iterators.invgamma( α, β[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from an\n    inverse gamma distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    The function throws an error if `α <= 0` or `β <= 0`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.invgamma( 1.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.invgamma\n","random.iterators.kumaraswamy":"\nrandom.iterators.kumaraswamy( a, b[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Kumaraswamy's double bounded distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    The function throws an error if `a <= 0` or `b <= 0`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.kumaraswamy( 1.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.kumaraswamy\n","random.iterators.laplace":"\nrandom.iterators.laplace( μ, b[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Laplace\n    (double exponential) distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    b: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.laplace( 0.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.laplace\n","random.iterators.levy":"\nrandom.iterators.levy( μ, c[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Lévy\n    distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    c: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.levy( 0.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.levy\n","random.iterators.logistic":"\nrandom.iterators.logistic( μ, s[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    logistic distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    s: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.logistic( 0.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.logistic\n","random.iterators.lognormal":"\nrandom.iterators.lognormal( μ, σ[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    lognormal distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.lognormal( 0.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.lognormal\n","random.iterators.minstd":"\nrandom.iterators.minstd( [options] )\n    Returns an iterator for generating pseudorandom integers on the interval\n    `[1, 2147483646]`.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    This pseudorandom number generator (PRNG) is a linear congruential\n    pseudorandom number generator (LCG) based on Park and Miller.\n\n    The generator has a period of approximately `2.1e9`.\n\n    An LCG is fast and uses little memory. On the other hand, because the\n    generator is a simple LCG, the generator has recognized shortcomings. By\n    today's PRNG standards, the generator's period is relatively short. More\n    importantly, the \"randomness quality\" of the generator's output is lacking.\n    These defects make the generator unsuitable, for example, in Monte Carlo\n    simulations and in cryptographic applications.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing positive signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.seed: Int32Array\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer\n        Length of generator seed.\n\n    iterator.state: Int32Array\n        Generator state.\n\n    iterator.stateLength: integer\n        Length of generator state.\n\n    iterator.byteLength: integer\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.minstd();\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.minstd, random.iterators.minstdShuffle, random.iterators.mt19937, random.iterators.randi, random.iterators.randu\n","random.iterators.minstdShuffle":"\nrandom.iterators.minstdShuffle( [options] )\n    Returns an iterator for generating pseudorandom integers on the interval\n    `[1, 2147483646]`.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    This pseudorandom number generator (PRNG) is a linear congruential\n    pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n    Durham algorithm. The shuffle step considerably strengthens the \"randomness\n    quality\" of a simple LCG's output.\n\n    The generator has a period of approximately `2.1e9`.\n\n    An LCG is fast and uses little memory. On the other hand, because the\n    generator is a simple LCG, the generator has recognized shortcomings. By\n    today's PRNG standards, the generator's period is relatively short. In\n    general, this generator is unsuitable for Monte Carlo simulations and\n    cryptographic applications.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing positive signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.seed: Int32Array\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer\n        Length of generator seed.\n\n    iterator.state: Int32Array\n        Generator state.\n\n    iterator.stateLength: integer\n        Length of generator state.\n\n    iterator.byteLength: integer\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.minstdShuffle();\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.minstdShuffle, random.iterators.minstd, random.iterators.mt19937, random.iterators.randi, random.iterators.randu\n","random.iterators.mt19937":"\nrandom.iterators.mt19937( [options] )\n    Returns an iterator for generating pseudorandom integers on the interval\n    `[1, 4294967295]`.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    This pseudorandom number generator (PRNG) is a 32-bit Mersenne Twister\n    pseudorandom number generator.\n\n    The PRNG is *not* a cryptographically secure PRNG.\n\n    The PRNG has a period of 2^19937 - 1.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.seed: Uint32Array\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer\n        Length of generator seed.\n\n    iterator.state: Uint32Array\n        Generator state.\n\n    iterator.stateLength: integer\n        Length of generator state.\n\n    iterator.byteLength: integer\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.mt19937();\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.mt19937, random.iterators.minstd, random.iterators.minstdShuffle, random.iterators.randi, random.iterators.randu\n","random.iterators.negativeBinomial":"\nrandom.iterators.negativeBinomial( r, p[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    negative binomial distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.negativeBinomial( 10, 0.3 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.negativeBinomial\n","random.iterators.normal":"\nrandom.iterators.normal( μ, σ[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a normal\n    distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    σ: number\n        Standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.normal( 0.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.normal\n","random.iterators.pareto1":"\nrandom.iterators.pareto1( α, β[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Pareto\n    (Type I) distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    The function throws an error if `α <= 0` or `β <= 0`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.pareto1( 1.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.pareto1\n","random.iterators.poisson":"\nrandom.iterators.poisson( λ[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Poisson\n    distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    λ: number\n        Mean.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.poisson( 1.5 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.poisson\n","random.iterators.randi":"\nrandom.iterators.randi( [options] )\n    Create an iterator for generating pseudorandom numbers having integer\n    values.\n\n    The default underlying pseudorandom number generator (PRNG) *may* change in\n    the future. If exact reproducibility is required, either explicitly specify\n    a PRNG via the `name` option or use an underlying PRNG directly.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: `'mt19937'`.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: any\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer\n        Length of generator seed.\n\n    iterator.state: any\n        Generator state.\n\n    iterator.stateLength: integer\n        Length of generator state.\n\n    iterator.byteLength: integer\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.randi();\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.randi, random.iterators.randu\n","random.iterators.randn":"\nrandom.iterators.randn( [options] )\n    Create an iterator for generating pseudorandom numbers drawn from a standard\n    normal distribution.\n\n    The default underlying pseudorandom number generator (PRNG) *may* change in\n    the future. If exact reproducibility is required, either explicitly specify\n    a PRNG via the `name` option or use an underlying PRNG directly.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - improved-ziggurat: improved ziggurat method.\n        - box-muller: Box-Muller transform.\n\n        Default: `'improved-ziggurat'`.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.randn();\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.randn\n","random.iterators.randu":"\nrandom.iterators.randu( [options] )\n    Create an iterator for generating uniformly distributed pseudorandom numbers\n    between 0 and 1.\n\n    The default underlying pseudorandom number generator (PRNG) *may* change in\n    the future. If exact reproducibility is required, either explicitly specify\n    a PRNG via the `name` option or use an underlying PRNG directly.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: `'mt19937'`.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: any\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer\n        Length of generator seed.\n\n    iterator.state: any\n        Generator state.\n\n    iterator.stateLength: integer\n        Length of generator state.\n\n    iterator.byteLength: integer\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.randu();\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.randu, random.iterators.randi\n","random.iterators.rayleigh":"\nrandom.iterators.rayleigh( σ[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Rayleigh distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.rayleigh( 1.5 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.rayleigh\n","random.iterators.t":"\nrandom.iterators.t( v[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Student's t distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.t( 1.5 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.t\n","random.iterators.triangular":"\nrandom.iterators.triangular( a, b, c[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    triangular distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.triangular( 0.0, 1.0, 0.3 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.triangular\n","random.iterators.uniform":"\nrandom.iterators.uniform( a, b[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    continuous uniform distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.uniform( 0.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.uniform\n","random.iterators.weibull":"\nrandom.iterators.weibull( k, λ[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Weibull distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    The function throws an error if `k <= 0` or `λ <= 0`.\n\n    Parameters\n    ----------\n    k: number\n        Scale parameter.\n\n    λ: number\n        Shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.weibull( 1.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.weibull\n","random.streams.arcsine":"\nrandom.streams.arcsine( a, b[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from an\n    arcsine distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.arcsine( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.arcsine.factory( [a, b, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an arcsine distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.arcsine.factory( opts );\n\n\nrandom.streams.arcsine.objectMode( a, b[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an arcsine distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.arcsine.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.arcsine, random.iterators.arcsine\n","random.streams.arcsine.factory":"\nrandom.streams.arcsine.factory( [a, b, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an arcsine distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.arcsine.factory( opts );","random.streams.arcsine.objectMode":"\nrandom.streams.arcsine.objectMode( a, b[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an arcsine distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.arcsine.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.arcsine, random.iterators.arcsine","random.streams.bernoulli":"\nrandom.streams.bernoulli( p[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Bernoulli distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.bernoulli( 0.5, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.bernoulli.factory( [p, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Bernoulli distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.bernoulli.factory( opts );\n\n\nrandom.streams.bernoulli.objectMode( p[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Bernoulli distribution.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.bernoulli.objectMode( 0.3, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.bernoulli, random.iterators.bernoulli\n","random.streams.bernoulli.factory":"\nrandom.streams.bernoulli.factory( [p, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Bernoulli distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.bernoulli.factory( opts );","random.streams.bernoulli.objectMode":"\nrandom.streams.bernoulli.objectMode( p[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Bernoulli distribution.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.bernoulli.objectMode( 0.3, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.bernoulli, random.iterators.bernoulli","random.streams.beta":"\nrandom.streams.beta( α, β[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    beta distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.beta( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.beta.factory( [α, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a beta distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        First shape parameter.\n\n    β: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.beta.factory( opts );\n\n\nrandom.streams.beta.objectMode( α, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a beta distribution.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.beta.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.beta, random.iterators.beta\n","random.streams.beta.factory":"\nrandom.streams.beta.factory( [α, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a beta distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        First shape parameter.\n\n    β: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.beta.factory( opts );","random.streams.beta.objectMode":"\nrandom.streams.beta.objectMode( α, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a beta distribution.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.beta.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.beta, random.iterators.beta","random.streams.betaprime":"\nrandom.streams.betaprime( α, β[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    beta prime distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.betaprime( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.betaprime.factory( [α, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a beta prime distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        First shape parameter.\n\n    β: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.betaprime.factory( opts );\n\n\nrandom.streams.betaprime.objectMode( α, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a beta prime distribution.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.betaprime.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.betaprime, random.iterators.betaprime\n","random.streams.betaprime.factory":"\nrandom.streams.betaprime.factory( [α, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a beta prime distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        First shape parameter.\n\n    β: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.betaprime.factory( opts );","random.streams.betaprime.objectMode":"\nrandom.streams.betaprime.objectMode( α, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a beta prime distribution.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.betaprime.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.betaprime, random.iterators.betaprime","random.streams.binomial":"\nrandom.streams.binomial( n, p[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    binomial distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.binomial( 20, 0.5, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.binomial.factory( [n, p, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a binomial distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    n: integer (optional)\n        Number of trials.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.binomial.factory( opts );\n\n\nrandom.streams.binomial.objectMode( n, p[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a binomial distribution.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.binomial.objectMode( 20, 0.5, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.binomial, random.iterators.binomial\n","random.streams.binomial.factory":"\nrandom.streams.binomial.factory( [n, p, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a binomial distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    n: integer (optional)\n        Number of trials.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.binomial.factory( opts );","random.streams.binomial.objectMode":"\nrandom.streams.binomial.objectMode( n, p[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a binomial distribution.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.binomial.objectMode( 20, 0.5, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.binomial, random.iterators.binomial","random.streams.boxMuller":"\nrandom.streams.boxMuller( [options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    standard normal distribution using the Box-Muller transform.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.boxMuller( opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.boxMuller.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a standard normal distribution using the Box-Muller\n    transform.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.boxMuller.factory( opts );\n\n\nrandom.streams.boxMuller.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a standard normal distribution using the Box-Muller transform.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.boxMuller.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.boxMuller, random.iterators.boxMuller, random.streams.improvedZiggurat, random.streams.randn\n","random.streams.boxMuller.factory":"\nrandom.streams.boxMuller.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a standard normal distribution using the Box-Muller\n    transform.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.boxMuller.factory( opts );","random.streams.boxMuller.objectMode":"\nrandom.streams.boxMuller.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a standard normal distribution using the Box-Muller transform.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.boxMuller.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.boxMuller, random.iterators.boxMuller, random.streams.improvedZiggurat, random.streams.randn","random.streams.cauchy":"\nrandom.streams.cauchy( x0, γ[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Cauchy distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    γ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.cauchy( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.cauchy.factory( [x0, γ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Cauchy distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    x0: number (optional)\n        Location parameter.\n\n    γ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.cauchy.factory( opts );\n\n\nrandom.streams.cauchy.objectMode( x0, γ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Cauchy distribution.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    γ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.cauchy.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.cauchy, random.iterators.cauchy\n","random.streams.cauchy.factory":"\nrandom.streams.cauchy.factory( [x0, γ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Cauchy distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    x0: number (optional)\n        Location parameter.\n\n    γ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.cauchy.factory( opts );","random.streams.cauchy.objectMode":"\nrandom.streams.cauchy.objectMode( x0, γ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Cauchy distribution.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    γ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.cauchy.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.cauchy, random.iterators.cauchy","random.streams.chi":"\nrandom.streams.chi( k[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    chi distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.chi( 3.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.chi.factory( [k, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a chi distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.chi.factory( opts );\n\n\nrandom.streams.chi.objectMode( k[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a chi distribution.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.chi.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.chi, random.iterators.chi\n","random.streams.chi.factory":"\nrandom.streams.chi.factory( [k, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a chi distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.chi.factory( opts );","random.streams.chi.objectMode":"\nrandom.streams.chi.objectMode( k[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a chi distribution.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.chi.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.chi, random.iterators.chi","random.streams.chisquare":"\nrandom.streams.chisquare( k[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    chi-square distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.chisquare( 3.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.chisquare.factory( [k, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a chi-square distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.chisquare.factory( opts );\n\n\nrandom.streams.chisquare.objectMode( k[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a chi-square distribution.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.chisquare.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.chisquare, random.iterators.chisquare\n","random.streams.chisquare.factory":"\nrandom.streams.chisquare.factory( [k, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a chi-square distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.chisquare.factory( opts );","random.streams.chisquare.objectMode":"\nrandom.streams.chisquare.objectMode( k[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a chi-square distribution.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.chisquare.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.chisquare, random.iterators.chisquare","random.streams.cosine":"\nrandom.streams.cosine( μ, s[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    raised cosine distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.cosine( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.cosine.factory( [μ, s, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a raised cosine distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.cosine.factory( opts );\n\n\nrandom.streams.cosine.objectMode( μ, s[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a raised cosine distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.cosine.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.cosine, random.iterators.cosine\n","random.streams.cosine.factory":"\nrandom.streams.cosine.factory( [μ, s, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a raised cosine distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.cosine.factory( opts );","random.streams.cosine.objectMode":"\nrandom.streams.cosine.objectMode( μ, s[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a raised cosine distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.cosine.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.cosine, random.iterators.cosine","random.streams.discreteUniform":"\nrandom.streams.discreteUniform( a, b[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    discrete uniform distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.discreteUniform( 2, 5, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.discreteUniform.factory( [a, b, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a discrete uniform distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    a: integer (optional)\n        Minimum support.\n\n    b: integer (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.discreteUniform.factory( opts );\n\n\nrandom.streams.discreteUniform.objectMode( a, b[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a discrete uniform distribution.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.discreteUniform.objectMode( 2, 5, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.discreteUniform, random.iterators.discreteUniform\n","random.streams.discreteUniform.factory":"\nrandom.streams.discreteUniform.factory( [a, b, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a discrete uniform distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    a: integer (optional)\n        Minimum support.\n\n    b: integer (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.discreteUniform.factory( opts );","random.streams.discreteUniform.objectMode":"\nrandom.streams.discreteUniform.objectMode( a, b[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a discrete uniform distribution.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.discreteUniform.objectMode( 2, 5, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.discreteUniform, random.iterators.discreteUniform","random.streams.erlang":"\nrandom.streams.erlang( k, λ[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from an\n    Erlang distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    k: integer\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.erlang( 2, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.erlang.factory( [k, λ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an Erlang distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Shape parameter.\n\n    λ: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.erlang.factory( opts );\n\n\nrandom.streams.erlang.objectMode( k, λ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an Erlang distribution.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.erlang.objectMode( 2, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.erlang, random.iterators.erlang\n","random.streams.erlang.factory":"\nrandom.streams.erlang.factory( [k, λ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an Erlang distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Shape parameter.\n\n    λ: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.erlang.factory( opts );","random.streams.erlang.objectMode":"\nrandom.streams.erlang.objectMode( k, λ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an Erlang distribution.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.erlang.objectMode( 2, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.erlang, random.iterators.erlang","random.streams.exponential":"\nrandom.streams.exponential( λ[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from an\n    exponential distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.exponential( 3.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.exponential.factory( [λ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an exponential distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    λ: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.exponential.factory( opts );\n\n\nrandom.streams.exponential.objectMode( λ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an exponential distribution.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.exponential.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.exponential, random.iterators.exponential\n","random.streams.exponential.factory":"\nrandom.streams.exponential.factory( [λ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an exponential distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    λ: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.exponential.factory( opts );","random.streams.exponential.objectMode":"\nrandom.streams.exponential.objectMode( λ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an exponential distribution.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.exponential.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.exponential, random.iterators.exponential","random.streams.f":"\nrandom.streams.f( d1, d2[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from an\n    F distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    d1: number\n        Degrees of freedom.\n\n    d2: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.f( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.f.factory( [d1, d2, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an F distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    d1: number (optional)\n        Degrees of freedom.\n\n    d2: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.f.factory( opts );\n\n\nrandom.streams.f.objectMode( d1, d2[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an F distribution.\n\n    Parameters\n    ----------\n    d1: number\n        Degrees of freedom.\n\n    d2: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.f.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.f, random.iterators.f\n","random.streams.f.factory":"\nrandom.streams.f.factory( [d1, d2, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an F distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    d1: number (optional)\n        Degrees of freedom.\n\n    d2: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.f.factory( opts );","random.streams.f.objectMode":"\nrandom.streams.f.objectMode( d1, d2[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an F distribution.\n\n    Parameters\n    ----------\n    d1: number\n        Degrees of freedom.\n\n    d2: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.f.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.f, random.iterators.f","random.streams.frechet":"\nrandom.streams.frechet( α, s, m[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Fréchet distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.frechet( 2.0, 5.0, 3.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.frechet.factory( [α, s, m,][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Fréchet distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    m: number (optional)\n        Location parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.frechet.factory( opts );\n\n\nrandom.streams.frechet.objectMode( α, s, m[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Fréchet distribution.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.frechet.objectMode( 2.0, 5.0, 3.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.frechet, random.iterators.frechet\n","random.streams.frechet.factory":"\nrandom.streams.frechet.factory( [α, s, m,][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Fréchet distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    m: number (optional)\n        Location parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.frechet.factory( opts );","random.streams.frechet.objectMode":"\nrandom.streams.frechet.objectMode( α, s, m[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Fréchet distribution.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.frechet.objectMode( 2.0, 5.0, 3.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.frechet, random.iterators.frechet","random.streams.gamma":"\nrandom.streams.gamma( α, β[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    gamma distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.gamma( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.gamma.factory( [α, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a gamma distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.gamma.factory( opts );\n\n\nrandom.streams.gamma.objectMode( α, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a gamma distribution.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.gamma.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.gamma, random.iterators.gamma\n","random.streams.gamma.factory":"\nrandom.streams.gamma.factory( [α, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a gamma distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.gamma.factory( opts );","random.streams.gamma.objectMode":"\nrandom.streams.gamma.objectMode( α, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a gamma distribution.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.gamma.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.gamma, random.iterators.gamma","random.streams.geometric":"\nrandom.streams.geometric( p[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    geometric distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.geometric( 0.5, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.geometric.factory( [p, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a geometric distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.geometric.factory( opts );\n\n\nrandom.streams.geometric.objectMode( p[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a geometric distribution.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.geometric.objectMode( 0.3, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.geometric, random.iterators.geometric\n","random.streams.geometric.factory":"\nrandom.streams.geometric.factory( [p, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a geometric distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.geometric.factory( opts );","random.streams.geometric.objectMode":"\nrandom.streams.geometric.objectMode( p[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a geometric distribution.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.geometric.objectMode( 0.3, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.geometric, random.iterators.geometric","random.streams.gumbel":"\nrandom.streams.gumbel( μ, β[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Gumbel distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.gumbel( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.gumbel.factory( [μ, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Gumbel distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.gumbel.factory( opts );\n\n\nrandom.streams.gumbel.objectMode( μ, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Gumbel distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.gumbel.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.gumbel, random.iterators.gumbel\n","random.streams.gumbel.factory":"\nrandom.streams.gumbel.factory( [μ, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Gumbel distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.gumbel.factory( opts );","random.streams.gumbel.objectMode":"\nrandom.streams.gumbel.objectMode( μ, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Gumbel distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.gumbel.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.gumbel, random.iterators.gumbel","random.streams.hypergeometric":"\nrandom.streams.hypergeometric( N, K, n[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    hypergeometric distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.hypergeometric( 5, 3, 2, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.hypergeometric.factory( [N, K, n,][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a hypergeometric distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    N: integer (optional)\n        Population size.\n\n    K: integer (optional)\n        Subpopulation size.\n\n    n: integer (optional)\n        Number of draws.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.hypergeometric.factory( opts );\n\n\nrandom.streams.hypergeometric.objectMode( N, K, n[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a hypergeometric distribution.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.hypergeometric.objectMode( 5, 3, 2, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.hypergeometric, random.iterators.hypergeometric\n","random.streams.hypergeometric.factory":"\nrandom.streams.hypergeometric.factory( [N, K, n,][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a hypergeometric distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    N: integer (optional)\n        Population size.\n\n    K: integer (optional)\n        Subpopulation size.\n\n    n: integer (optional)\n        Number of draws.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.hypergeometric.factory( opts );","random.streams.hypergeometric.objectMode":"\nrandom.streams.hypergeometric.objectMode( N, K, n[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a hypergeometric distribution.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.hypergeometric.objectMode( 5, 3, 2, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.hypergeometric, random.iterators.hypergeometric","random.streams.improvedZiggurat":"\nrandom.streams.improvedZiggurat( [options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    standard normal distribution using the Improved Ziggurat algorithm.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.improvedZiggurat( opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.improvedZiggurat.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a standard normal distribution using the Improved\n    Ziggurat algorithm.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.improvedZiggurat.factory( opts );\n\n\nrandom.streams.improvedZiggurat.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a standard normal distribution using the Improved Ziggurat\n    algorithm.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.improvedZiggurat.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.improvedZiggurat, random.iterators.improvedZiggurat, random.streams.boxMuller, random.streams.randn\n","random.streams.improvedZiggurat.factory":"\nrandom.streams.improvedZiggurat.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a standard normal distribution using the Improved\n    Ziggurat algorithm.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.improvedZiggurat.factory( opts );","random.streams.improvedZiggurat.objectMode":"\nrandom.streams.improvedZiggurat.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a standard normal distribution using the Improved Ziggurat\n    algorithm.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.improvedZiggurat.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.improvedZiggurat, random.iterators.improvedZiggurat, random.streams.boxMuller, random.streams.randn","random.streams.invgamma":"\nrandom.streams.invgamma( α, β[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from an\n    inverse gamma distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.invgamma( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.invgamma.factory( [α, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an inverse gamma distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.invgamma.factory( opts );\n\n\nrandom.streams.invgamma.objectMode( α, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an inverse gamma distribution.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.invgamma.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.invgamma, random.iterators.invgamma\n","random.streams.invgamma.factory":"\nrandom.streams.invgamma.factory( [α, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an inverse gamma distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.invgamma.factory( opts );","random.streams.invgamma.objectMode":"\nrandom.streams.invgamma.objectMode( α, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an inverse gamma distribution.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.invgamma.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.invgamma, random.iterators.invgamma","random.streams.kumaraswamy":"\nrandom.streams.kumaraswamy( a, b[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Kumaraswamy's double bounded distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.kumaraswamy( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.kumaraswamy.factory( [a, b, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Kumaraswamy's double bounded distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        First shape parameter.\n\n    b: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.kumaraswamy.factory( opts );\n\n\nrandom.streams.kumaraswamy.objectMode( a, b[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Kumaraswamy's double bounded distribution.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.kumaraswamy.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.kumaraswamy, random.iterators.kumaraswamy\n","random.streams.kumaraswamy.factory":"\nrandom.streams.kumaraswamy.factory( [a, b, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Kumaraswamy's double bounded distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        First shape parameter.\n\n    b: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.kumaraswamy.factory( opts );","random.streams.kumaraswamy.objectMode":"\nrandom.streams.kumaraswamy.objectMode( a, b[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Kumaraswamy's double bounded distribution.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.kumaraswamy.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.kumaraswamy, random.iterators.kumaraswamy","random.streams.laplace":"\nrandom.streams.laplace( μ, b[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Laplace (double exponential) distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    b: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.laplace( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.laplace.factory( [μ, b, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Laplace (double exponential) distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    b: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.laplace.factory( opts );\n\n\nrandom.streams.laplace.objectMode( μ, b[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Laplace (double exponential) distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    b: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.laplace.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.laplace, random.iterators.laplace\n","random.streams.laplace.factory":"\nrandom.streams.laplace.factory( [μ, b, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Laplace (double exponential) distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    b: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.laplace.factory( opts );","random.streams.laplace.objectMode":"\nrandom.streams.laplace.objectMode( μ, b[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Laplace (double exponential) distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    b: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.laplace.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.laplace, random.iterators.laplace","random.streams.levy":"\nrandom.streams.levy( μ, c[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Lévy distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    c: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.levy( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.levy.factory( [μ, c, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Lévy distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    c: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.levy.factory( opts );\n\n\nrandom.streams.levy.objectMode( μ, c[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Lévy distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    c: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.levy.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.levy, random.iterators.levy\n","random.streams.levy.factory":"\nrandom.streams.levy.factory( [μ, c, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Lévy distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    c: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.levy.factory( opts );","random.streams.levy.objectMode":"\nrandom.streams.levy.objectMode( μ, c[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Lévy distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    c: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.levy.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.levy, random.iterators.levy","random.streams.logistic":"\nrandom.streams.logistic( μ, s[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    logistic distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    s: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.logistic( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.logistic.factory( [μ, s, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a logistic distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.logistic.factory( opts );\n\n\nrandom.streams.logistic.objectMode( μ, s[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a logistic distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    s: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.logistic.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.logistic, random.iterators.logistic\n","random.streams.logistic.factory":"\nrandom.streams.logistic.factory( [μ, s, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a logistic distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.logistic.factory( opts );","random.streams.logistic.objectMode":"\nrandom.streams.logistic.objectMode( μ, s[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a logistic distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    s: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.logistic.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.logistic, random.iterators.logistic","random.streams.lognormal":"\nrandom.streams.lognormal( μ, σ[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    lognormal distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.lognormal( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.lognormal.factory( [μ, σ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a lognormal distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter.\n\n    σ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.lognormal.factory( opts );\n\n\nrandom.streams.lognormal.objectMode( μ, σ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a lognormal distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.lognormal.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.lognormal, random.iterators.lognormal\n","random.streams.lognormal.factory":"\nrandom.streams.lognormal.factory( [μ, σ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a lognormal distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter.\n\n    σ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.lognormal.factory( opts );","random.streams.lognormal.objectMode":"\nrandom.streams.lognormal.objectMode( μ, σ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a lognormal distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.lognormal.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.lognormal, random.iterators.lognormal","random.streams.minstd":"\nrandom.streams.minstd( [options] )\n    Returns a readable stream for generating pseudorandom numbers on the\n    interval `[1, 2147483646]`.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    The underlying pseudorandom number generator (PRNG) is a linear congruential\n    pseudorandom number generator (LCG) based on Park and Miller.\n\n    The generator has a period of approximately `2.1e9`.\n\n    An LCG is fast and uses little memory. On the other hand, because the\n    generator is a simple LCG, the generator has recognized shortcomings. By\n    today's PRNG standards, the generator's period is relatively short. More\n    importantly, the \"randomness quality\" of the generator's output is lacking.\n    These defects make the generator unsuitable, for example, in Monte Carlo\n    simulations and in cryptographic applications.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.seed: Int32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Int32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.minstd( opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.minstd.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers on the interval `[1, 2147483646]`.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.minstd.factory( opts );\n\n\nrandom.streams.minstd.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    on the interval `[1, 2147483646]`.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.seed: Int32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Int32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.minstd.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.minstd, random.iterators.minstd, random.streams.minstdShuffle, random.streams.mt19937, random.streams.randi, random.streams.randu\n","random.streams.minstd.factory":"\nrandom.streams.minstd.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers on the interval `[1, 2147483646]`.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.minstd.factory( opts );","random.streams.minstd.objectMode":"\nrandom.streams.minstd.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    on the interval `[1, 2147483646]`.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.seed: Int32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Int32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.minstd.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.minstd, random.iterators.minstd, random.streams.minstdShuffle, random.streams.mt19937, random.streams.randi, random.streams.randu","random.streams.minstdShuffle":"\nrandom.streams.minstdShuffle( [options] )\n    Returns a readable stream for generating pseudorandom numbers on the\n    interval `[1, 2147483646]`.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    The underlying pseudorandom number generator (PRNG) is a linear congruential\n    pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n    Durham algorithm. The shuffle step considerably strengthens the \"randomness\n    quality\" of a simple LCG's output.\n\n    The generator has a period of approximately `2.1e9`.\n\n    An LCG is fast and uses little memory. On the other hand, because the\n    generator is a simple LCG, the generator has recognized shortcomings. By\n    today's PRNG standards, the generator's period is relatively short. In\n    general, this generator is unsuitable for Monte Carlo simulations and\n    cryptographic applications.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.seed: Int32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Int32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.minstdShuffle( opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.minstdShuffle.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers on the interval `[1, 2147483646]`.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.minstdShuffle.factory( opts );\n\n\nrandom.streams.minstdShuffle.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    on the interval `[1, 2147483646]`.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.seed: Int32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Int32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.minstdShuffle.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstd, random.streams.mt19937, random.streams.randi, random.streams.randu\n","random.streams.minstdShuffle.factory":"\nrandom.streams.minstdShuffle.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers on the interval `[1, 2147483646]`.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.minstdShuffle.factory( opts );","random.streams.minstdShuffle.objectMode":"\nrandom.streams.minstdShuffle.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    on the interval `[1, 2147483646]`.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.seed: Int32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Int32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.minstdShuffle.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstd, random.streams.mt19937, random.streams.randi, random.streams.randu","random.streams.mt19937":"\nrandom.streams.mt19937( [options] )\n    Returns a readable stream for generating pseudorandom numbers on the\n    interval `[1, 4294967295]`.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    The underlying pseudorandom number generator (PRNG) is a 32-bit Mersenne\n    Twister pseudorandom number generator.\n\n    The PRNG is *not* a cryptographically secure PRNG.\n\n    The PRNG has a period of 2^19937 - 1.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.mt19937( opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.mt19937.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers on the interval `[1, 4294967295]`.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.mt19937.factory( opts );\n\n\nrandom.streams.mt19937.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    on the interval `[1, 4294967295]`.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.mt19937.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.mt19937, random.iterators.mt19937, random.streams.minstd, random.streams.minstdShuffle, random.streams.randi, random.streams.randu\n","random.streams.mt19937.factory":"\nrandom.streams.mt19937.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers on the interval `[1, 4294967295]`.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.mt19937.factory( opts );","random.streams.mt19937.objectMode":"\nrandom.streams.mt19937.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    on the interval `[1, 4294967295]`.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.mt19937.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.mt19937, random.iterators.mt19937, random.streams.minstd, random.streams.minstdShuffle, random.streams.randi, random.streams.randu","random.streams.negativeBinomial":"\nrandom.streams.negativeBinomial( r, p[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    negative binomial distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.negativeBinomial( 20.0, 0.5, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.negativeBinomial.factory( [r, p, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a negative binomial distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    r: number (optional)\n        Number of successes until experiment is stopped.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.negativeBinomial.factory( opts );\n\n\nrandom.streams.negativeBinomial.objectMode( r, p[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a negative binomial distribution.\n\n    Parameters\n    ----------\n    r: integer\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.negativeBinomial.objectMode( 20.0, 0.5, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.negativeBinomial, random.iterators.negativeBinomial\n","random.streams.negativeBinomial.factory":"\nrandom.streams.negativeBinomial.factory( [r, p, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a negative binomial distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    r: number (optional)\n        Number of successes until experiment is stopped.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.negativeBinomial.factory( opts );","random.streams.negativeBinomial.objectMode":"\nrandom.streams.negativeBinomial.objectMode( r, p[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a negative binomial distribution.\n\n    Parameters\n    ----------\n    r: integer\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.negativeBinomial.objectMode( 20.0, 0.5, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.negativeBinomial, random.iterators.negativeBinomial","random.streams.normal":"\nrandom.streams.normal( μ, σ[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    normal distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    σ: number\n        Standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.normal( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.normal.factory( [μ, σ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a normal distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    σ: number (optional)\n        Standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.normal.factory( opts );\n\n\nrandom.streams.normal.objectMode( μ, σ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a normal distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    σ: number\n        Standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.normal.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.normal, random.iterators.normal\n","random.streams.normal.factory":"\nrandom.streams.normal.factory( [μ, σ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a normal distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    σ: number (optional)\n        Standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.normal.factory( opts );","random.streams.normal.objectMode":"\nrandom.streams.normal.objectMode( μ, σ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a normal distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    σ: number\n        Standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.normal.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.normal, random.iterators.normal","random.streams.pareto1":"\nrandom.streams.pareto1( α, β[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Pareto (Type I) distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.pareto1( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.pareto1.factory( [α, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Pareto (Type I) distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.pareto1.factory( opts );\n\n\nrandom.streams.pareto1.objectMode( α, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Pareto (Type I) distribution.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.pareto1.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.pareto1, random.iterators.pareto1\n","random.streams.pareto1.factory":"\nrandom.streams.pareto1.factory( [α, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Pareto (Type I) distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.pareto1.factory( opts );","random.streams.pareto1.objectMode":"\nrandom.streams.pareto1.objectMode( α, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Pareto (Type I) distribution.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.pareto1.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.pareto1, random.iterators.pareto1","random.streams.poisson":"\nrandom.streams.poisson( λ[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Poisson distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    λ: number\n        Mean.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.poisson( 3.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.poisson.factory( [λ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Poisson distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    λ: number (optional)\n        Mean.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.poisson.factory( opts );\n\n\nrandom.streams.poisson.objectMode( λ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Poisson distribution.\n\n    Parameters\n    ----------\n    λ: number\n        Mean.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.poisson.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.poisson, random.iterators.poisson\n","random.streams.poisson.factory":"\nrandom.streams.poisson.factory( [λ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Poisson distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    λ: number (optional)\n        Mean.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.poisson.factory( opts );","random.streams.poisson.objectMode":"\nrandom.streams.poisson.objectMode( λ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Poisson distribution.\n\n    Parameters\n    ----------\n    λ: number\n        Mean.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.poisson.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.poisson, random.iterators.poisson","random.streams.randi":"\nrandom.streams.randi( [options] )\n    Returns a readable stream for generating pseudorandom numbers having integer\n    values.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    The default underlying pseudorandom number generator (PRNG) *may* change in\n    the future. If exact reproducibility is required, either explicitly specify\n    a PRNG via the `name` option or use an underlying PRNG directly.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: any\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer\n        Length of generator seed.\n\n    stream.state: any\n        Generator state.\n\n    stream.stateLength: integer\n        Length of generator state.\n\n    stream.byteLength: integer\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.randi( opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.randi.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers having integer values.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.randi.factory( opts );\n\n\nrandom.streams.randi.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    having integer values.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: any\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer\n        Length of generator seed.\n\n    stream.state: any\n        Generator state.\n\n    stream.stateLength: integer\n        Length of generator state.\n\n    stream.byteLength: integer\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.randi.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.randi, random.iterators.randi, random.streams.randu\n","random.streams.randi.factory":"\nrandom.streams.randi.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers having integer values.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.randi.factory( opts );","random.streams.randi.objectMode":"\nrandom.streams.randi.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    having integer values.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: any\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer\n        Length of generator seed.\n\n    stream.state: any\n        Generator state.\n\n    stream.stateLength: integer\n        Length of generator state.\n\n    stream.byteLength: integer\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.randi.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.randi, random.iterators.randi, random.streams.randu","random.streams.randn":"\nrandom.streams.randn( [options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    standard normal distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    The default underlying pseudorandom number generator (PRNG) *may* change in\n    the future. If exact reproducibility is required, either explicitly specify\n    a PRNG via the `name` option or use an underlying PRNG directly.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - improved-ziggurat: improved ziggurat method.\n        - box-muller: Box-Muller transform.\n\n        Default: 'improved-ziggurat'.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.randn( opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.randn.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a standard normal distribution.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - improved-ziggurat: improved ziggurat method.\n        - box-muller: Box-Muller transform.\n\n        Default: 'improved-ziggurat'.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.randn.factory( opts );\n\n\nrandom.streams.randn.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a standard normal distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - improved-ziggurat: improved ziggurat method.\n        - box-muller: Box-Muller transform.\n\n        Default: 'improved-ziggurat'.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.randn.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.randn, random.iterators.randn, random.streams.boxMuller, random.streams.improvedZiggurat\n","random.streams.randn.factory":"\nrandom.streams.randn.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a standard normal distribution.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - improved-ziggurat: improved ziggurat method.\n        - box-muller: Box-Muller transform.\n\n        Default: 'improved-ziggurat'.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.randn.factory( opts );","random.streams.randn.objectMode":"\nrandom.streams.randn.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a standard normal distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - improved-ziggurat: improved ziggurat method.\n        - box-muller: Box-Muller transform.\n\n        Default: 'improved-ziggurat'.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.randn.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.randn, random.iterators.randn, random.streams.boxMuller, random.streams.improvedZiggurat","random.streams.randu":"\nrandom.streams.randu( [options] )\n    Returns a readable stream for generating uniformly distributed pseudorandom\n    numbers between 0 and 1.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    The default underlying pseudorandom number generator (PRNG) *may* change in\n    the future. If exact reproducibility is required, either explicitly specify\n    a PRNG via the `name` option or use an underlying PRNG directly.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: any\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer\n        Length of generator seed.\n\n    stream.state: any\n        Generator state.\n\n    stream.stateLength: integer\n        Length of generator state.\n\n    stream.byteLength: integer\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.randu( opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.randu.factory( [options] )\n    Returns a function for creating readable streams which generate uniformly\n    distributed pseudorandom numbers between 0 and 1.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.randu.factory( opts );\n\n\nrandom.streams.randu.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating uniformly distributed\n    pseudorandom numbers between 0 and 1.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: any\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer\n        Length of generator seed.\n\n    stream.state: any\n        Generator state.\n\n    stream.stateLength: integer\n        Length of generator state.\n\n    stream.byteLength: integer\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.randu.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.randu, random.iterators.randu, random.streams.randi\n","random.streams.randu.factory":"\nrandom.streams.randu.factory( [options] )\n    Returns a function for creating readable streams which generate uniformly\n    distributed pseudorandom numbers between 0 and 1.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.randu.factory( opts );","random.streams.randu.objectMode":"\nrandom.streams.randu.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating uniformly distributed\n    pseudorandom numbers between 0 and 1.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: any\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer\n        Length of generator seed.\n\n    stream.state: any\n        Generator state.\n\n    stream.stateLength: integer\n        Length of generator state.\n\n    stream.byteLength: integer\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.randu.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.randu, random.iterators.randu, random.streams.randi","random.streams.rayleigh":"\nrandom.streams.rayleigh( σ[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Rayleigh distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.rayleigh( 3.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.rayleigh.factory( [σ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Rayleigh distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    σ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.rayleigh.factory( opts );\n\n\nrandom.streams.rayleigh.objectMode( σ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Rayleigh distribution.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.rayleigh.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.rayleigh, random.iterators.rayleigh\n","random.streams.rayleigh.factory":"\nrandom.streams.rayleigh.factory( [σ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Rayleigh distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    σ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.rayleigh.factory( opts );","random.streams.rayleigh.objectMode":"\nrandom.streams.rayleigh.objectMode( σ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Rayleigh distribution.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.rayleigh.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.rayleigh, random.iterators.rayleigh","random.streams.t":"\nrandom.streams.t( v[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Student's t distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.t( 3.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.t.factory( [v, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Student's t distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    v: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.t.factory( opts );\n\n\nrandom.streams.t.objectMode( v[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Student's t distribution.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.t.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.t, random.iterators.t\n","random.streams.t.factory":"\nrandom.streams.t.factory( [v, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Student's t distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    v: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.t.factory( opts );","random.streams.t.objectMode":"\nrandom.streams.t.objectMode( v[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Student's t distribution.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.t.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.t, random.iterators.t","random.streams.triangular":"\nrandom.streams.triangular( a, b, c[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    triangular distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.triangular( 2.0, 5.0, 4.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.triangular.factory( [a, b, c, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a triangular distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    c: number (optional)\n        Mode.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.triangular.factory( opts );\n\n\nrandom.streams.triangular.objectMode( a, b, c[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a triangular distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.triangular.objectMode( 2.0, 5.0, 4.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.triangular, random.iterators.triangular\n","random.streams.triangular.factory":"\nrandom.streams.triangular.factory( [a, b, c, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a triangular distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    c: number (optional)\n        Mode.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.triangular.factory( opts );","random.streams.triangular.objectMode":"\nrandom.streams.triangular.objectMode( a, b, c[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a triangular distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.triangular.objectMode( 2.0, 5.0, 4.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.triangular, random.iterators.triangular","random.streams.uniform":"\nrandom.streams.uniform( a, b[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    uniform distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.uniform( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.uniform.factory( [a, b, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a uniform distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.uniform.factory( opts );\n\n\nrandom.streams.uniform.objectMode( a, b[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a uniform distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.uniform.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.uniform, random.iterators.uniform\n","random.streams.uniform.factory":"\nrandom.streams.uniform.factory( [a, b, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a uniform distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.uniform.factory( opts );","random.streams.uniform.objectMode":"\nrandom.streams.uniform.objectMode( a, b[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a uniform distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.uniform.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.uniform, random.iterators.uniform","random.streams.weibull":"\nrandom.streams.weibull( k, λ[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Weibull distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    k: number\n        Scale parameter.\n\n    λ: number\n        Shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.weibull( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.weibull.factory( [k, λ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Weibull distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Scale parameter.\n\n    λ: number (optional)\n        Shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.weibull.factory( opts );\n\n\nrandom.streams.weibull.objectMode( k, λ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Weibull distribution.\n\n    Parameters\n    ----------\n    k: number\n        Scale parameter.\n\n    λ: number\n        Shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.weibull.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.weibull, random.iterators.weibull\n","random.streams.weibull.factory":"\nrandom.streams.weibull.factory( [k, λ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Weibull distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Scale parameter.\n\n    λ: number (optional)\n        Shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.weibull.factory( opts );","random.streams.weibull.objectMode":"\nrandom.streams.weibull.objectMode( k, λ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Weibull distribution.\n\n    Parameters\n    ----------\n    k: number\n        Scale parameter.\n\n    λ: number\n        Shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.weibull.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.weibull, random.iterators.weibull","random.strided.arcsine":"\nrandom.strided.arcsine( N, a, sa, b, sb, out, so[, options] )\n    Fills a strided array with pseudorandom numbers drawn from an arcsine\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    a: ArrayLikeObject\n        Minimum support.\n\n    sa: integer\n        Index increment for `a`.\n\n    b: ArrayLikeObject\n        Maximum support.\n\n    sb: integer\n        Index increment for `b`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 0.0, 1.0, 5 );\n    > var b = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.arcsine( out.length, a, 1, b, 1, out, 1 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 0.0, 1.0, 6 );\n    > b = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.arcsine( 3, a, -2, b, 1, out, 1 )\n    [...]\n\n\nrandom.strided.arcsine.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from an arcsine\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    a: ArrayLikeObject\n        Minimum support.\n\n    sa: integer\n        Index increment for `a`.\n\n    oa: integer\n        Starting index for `a`.\n\n    b: ArrayLikeObject\n        Maximum support.\n\n    sb: integer\n        Index increment for `b`.\n\n    ob: integer\n        Starting index for `b`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 0.0, 1.0, 5 );\n    > var b = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.arcsine.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 0.0, 1.0, 6 );\n    > b = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.arcsine.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.arcsine, random.array.arcsine\n","random.strided.arcsine.ndarray":"\nrandom.strided.arcsine.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from an arcsine\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    a: ArrayLikeObject\n        Minimum support.\n\n    sa: integer\n        Index increment for `a`.\n\n    oa: integer\n        Starting index for `a`.\n\n    b: ArrayLikeObject\n        Maximum support.\n\n    sb: integer\n        Index increment for `b`.\n\n    ob: integer\n        Starting index for `b`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 0.0, 1.0, 5 );\n    > var b = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.arcsine.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 0.0, 1.0, 6 );\n    > b = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.arcsine.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.arcsine, random.array.arcsine","random.strided.bernoulli":"\nrandom.strided.bernoulli( N, p, sp, out, so )\n    Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    p: ArrayLikeObject\n        Success probability.\n\n    sp: integer\n        Index increment for `p`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.bernoulli.ndarray( N, p, sp, op, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    p: ArrayLikeObject\n        Success probability.\n\n    sp: integer\n        Index increment for `p`.\n\n    op: integer\n        Starting index for `p`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.bernoulli.ndarray( out.length, [ 0.5 ], 0, 0, out, 1, 0 )\n    [...]\n\n\nrandom.strided.bernoulli.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Bernoulli distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.bernoulli.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 0.5 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.bernoulli.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.bernoulli.PRNG;\n\n\nrandom.strided.bernoulli.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.bernoulli.seed;\n\n\nrandom.strided.bernoulli.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.bernoulli.seedLength;\n\n\nrandom.strided.bernoulli.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.bernoulli.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.bernoulli.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.bernoulli.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.bernoulli.stateLength;\n\n\nrandom.strided.bernoulli.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.bernoulli.byteLength;\n\n    See Also\n    --------\n    base.random.bernoulli, random.array.bernoulli\n","random.strided.bernoulli.ndarray":"\nrandom.strided.bernoulli.ndarray( N, p, sp, op, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    p: ArrayLikeObject\n        Success probability.\n\n    sp: integer\n        Index increment for `p`.\n\n    op: integer\n        Starting index for `p`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.bernoulli.ndarray( out.length, [ 0.5 ], 0, 0, out, 1, 0 )\n    [...]","random.strided.bernoulli.factory":"\nrandom.strided.bernoulli.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Bernoulli distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.bernoulli.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 0.5 ], 0, out, 1 )\n    [...]","random.strided.bernoulli.PRNG":"\nrandom.strided.bernoulli.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.bernoulli.PRNG;","random.strided.bernoulli.seed":"\nrandom.strided.bernoulli.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.bernoulli.seed;","random.strided.bernoulli.seedLength":"\nrandom.strided.bernoulli.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.bernoulli.seedLength;","random.strided.bernoulli.state":"\nrandom.strided.bernoulli.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.bernoulli.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.bernoulli.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n    [...]","random.strided.bernoulli.stateLength":"\nrandom.strided.bernoulli.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.bernoulli.stateLength;","random.strided.bernoulli.byteLength":"\nrandom.strided.bernoulli.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.bernoulli.byteLength;\n\n    See Also\n    --------\n    base.random.bernoulli, random.array.bernoulli","random.strided.beta":"\nrandom.strided.beta( N, alpha, sa, beta, sb, out, so[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a beta\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        First shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    beta: ArrayLikeObject\n        Second shape parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.beta( out.length, a, 1, b, 1, out, 1 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.beta( 3, a, -2, b, 1, out, 1 )\n    [...]\n\n\nrandom.strided.beta.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a beta\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        First shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    oa: integer\n        Starting index for `alpha`.\n\n    beta: ArrayLikeObject\n        Second shape parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    ob: integer\n        Starting index for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.beta.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.beta.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.beta, random.array.beta\n","random.strided.beta.ndarray":"\nrandom.strided.beta.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a beta\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        First shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    oa: integer\n        Starting index for `alpha`.\n\n    beta: ArrayLikeObject\n        Second shape parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    ob: integer\n        Starting index for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.beta.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.beta.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.beta, random.array.beta","random.strided.betaprime":"\nrandom.strided.betaprime( N, alpha, sa, beta, sb, out, so[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a beta prime\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        First shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    beta: ArrayLikeObject\n        Second shape parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.betaprime( out.length, a, 1, b, 1, out, 1 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.betaprime( 3, a, -2, b, 1, out, 1 )\n    [...]\n\n\nrandom.strided.betaprime.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a beta prime\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        First shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    oa: integer\n        Starting index for `alpha`.\n\n    beta: ArrayLikeObject\n        Second shape parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    ob: integer\n        Starting index for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.betaprime.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.betaprime.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.betaprime, random.array.betaprime\n","random.strided.betaprime.ndarray":"\nrandom.strided.betaprime.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a beta prime\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        First shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    oa: integer\n        Starting index for `alpha`.\n\n    beta: ArrayLikeObject\n        Second shape parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    ob: integer\n        Starting index for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.betaprime.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.betaprime.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.betaprime, random.array.betaprime","random.strided.chi":"\nrandom.strided.chi( N, k, sk, out, so )\n    Fills a strided array with pseudorandom numbers drawn from a chi\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    k: ArrayLikeObject\n        Degrees of freedom.\n\n    sk: integer\n        Index increment for `k`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.chi.ndarray( N, k, sk, ok, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a chi\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    k: ArrayLikeObject\n        Degrees of freedom.\n\n    sk: integer\n        Index increment for `k`.\n\n    ok: integer\n        Starting index for `k`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.chi.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]\n\n\nrandom.strided.chi.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a chi distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.chi.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.chi.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.chi.PRNG;\n\n\nrandom.strided.chi.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.chi.seed;\n\n\nrandom.strided.chi.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.chi.seedLength;\n\n\nrandom.strided.chi.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.chi.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.chi.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.chi.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.chi.stateLength;\n\n\nrandom.strided.chi.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.chi.byteLength;\n\n    See Also\n    --------\n    base.random.chi, random.array.chi\n","random.strided.chi.ndarray":"\nrandom.strided.chi.ndarray( N, k, sk, ok, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a chi\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    k: ArrayLikeObject\n        Degrees of freedom.\n\n    sk: integer\n        Index increment for `k`.\n\n    ok: integer\n        Starting index for `k`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.chi.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]","random.strided.chi.factory":"\nrandom.strided.chi.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a chi distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.chi.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.chi.PRNG":"\nrandom.strided.chi.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.chi.PRNG;","random.strided.chi.seed":"\nrandom.strided.chi.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.chi.seed;","random.strided.chi.seedLength":"\nrandom.strided.chi.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.chi.seedLength;","random.strided.chi.state":"\nrandom.strided.chi.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.chi.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.chi.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.chi.stateLength":"\nrandom.strided.chi.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.chi.stateLength;","random.strided.chi.byteLength":"\nrandom.strided.chi.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.chi.byteLength;\n\n    See Also\n    --------\n    base.random.chi, random.array.chi","random.strided.chisquare":"\nrandom.strided.chisquare( N, k, sk, out, so )\n    Fills a strided array with pseudorandom numbers drawn from a chi-square\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    k: ArrayLikeObject\n        Degrees of freedom.\n\n    sk: integer\n        Index increment for `k`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.chisquare.ndarray( N, k, sk, ok, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a chi-square\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    k: ArrayLikeObject\n        Degrees of freedom.\n\n    sk: integer\n        Index increment for `k`.\n\n    ok: integer\n        Starting index for `k`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.chisquare.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]\n\n\nrandom.strided.chisquare.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a chi-square distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.chisquare.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.chisquare.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.chisquare.PRNG;\n\n\nrandom.strided.chisquare.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.chisquare.seed;\n\n\nrandom.strided.chisquare.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.chisquare.seedLength;\n\n\nrandom.strided.chisquare.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.chisquare.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.chisquare.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.chisquare.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.chisquare.stateLength;\n\n\nrandom.strided.chisquare.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.chisquare.byteLength;\n\n    See Also\n    --------\n    base.random.chisquare, random.array.chisquare\n","random.strided.chisquare.ndarray":"\nrandom.strided.chisquare.ndarray( N, k, sk, ok, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a chi-square\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    k: ArrayLikeObject\n        Degrees of freedom.\n\n    sk: integer\n        Index increment for `k`.\n\n    ok: integer\n        Starting index for `k`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.chisquare.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]","random.strided.chisquare.factory":"\nrandom.strided.chisquare.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a chi-square distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.chisquare.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.chisquare.PRNG":"\nrandom.strided.chisquare.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.chisquare.PRNG;","random.strided.chisquare.seed":"\nrandom.strided.chisquare.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.chisquare.seed;","random.strided.chisquare.seedLength":"\nrandom.strided.chisquare.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.chisquare.seedLength;","random.strided.chisquare.state":"\nrandom.strided.chisquare.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.chisquare.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.chisquare.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.chisquare.stateLength":"\nrandom.strided.chisquare.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.chisquare.stateLength;","random.strided.chisquare.byteLength":"\nrandom.strided.chisquare.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.chisquare.byteLength;\n\n    See Also\n    --------\n    base.random.chisquare, random.array.chisquare","random.strided.cosine":"\nrandom.strided.cosine( N, mu, sm, s, ss, out, so[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a cosine\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mu: ArrayLikeObject\n        Mean.\n\n    sm: integer\n        Index increment for `mu`.\n\n    s: ArrayLikeObject\n        Scale parameter.\n\n    ss: integer\n        Index increment for `s`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var mu = linspace( 0.0, 1.0, 5 );\n    > var s = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.cosine( out.length, mu, 1, s, 1, out, 1 )\n    [...]\n\n    // Advanced indexing:\n    > mu = linspace( 0.0, 1.0, 6 );\n    > s = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.cosine( 3, mu, -2, s, 1, out, 1 )\n    [...]\n\n\nrandom.strided.cosine.ndarray( N, mu, sm, om, s, ss, os, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a cosine\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mu: ArrayLikeObject\n        Mean.\n\n    sm: integer\n        Index increment for `mu`.\n\n    om: integer\n        Starting index for `mu`.\n\n    s: ArrayLikeObject\n        Scale parameter.\n\n    ss: integer\n        Index increment for `s`.\n\n    os: integer\n        Starting index for `s`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var mu = linspace( 0.0, 1.0, 5 );\n    > var s = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.cosine.ndarray( out.length, mu, 1, 0, s, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > mu = linspace( 0.0, 1.0, 6 );\n    > s = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.cosine.ndarray( 3, mu, 2, 1, s, -1, s.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.cosine, random.array.cosine\n","random.strided.cosine.ndarray":"\nrandom.strided.cosine.ndarray( N, mu, sm, om, s, ss, os, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a cosine\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mu: ArrayLikeObject\n        Mean.\n\n    sm: integer\n        Index increment for `mu`.\n\n    om: integer\n        Starting index for `mu`.\n\n    s: ArrayLikeObject\n        Scale parameter.\n\n    ss: integer\n        Index increment for `s`.\n\n    os: integer\n        Starting index for `s`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var mu = linspace( 0.0, 1.0, 5 );\n    > var s = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.cosine.ndarray( out.length, mu, 1, 0, s, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > mu = linspace( 0.0, 1.0, 6 );\n    > s = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.cosine.ndarray( 3, mu, 2, 1, s, -1, s.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.cosine, random.array.cosine","random.strided.discreteUniform":"\nrandom.strided.discreteUniform( N, a, sa, b, sb, out, so[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a discrete\n    uniform distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    a: ArrayLikeObject\n        Minimum support.\n\n    sa: integer\n        Index increment for `a`.\n\n    b: ArrayLikeObject\n        Maximum support.\n\n    sb: integer\n        Index increment for `b`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = [ -10, -5, 0, 5, 10 ];\n    > var b = [ 20, 20, 20, 20, 20 ];\n    > var out = azeros( 5, 'generic' );\n    > random.strided.discreteUniform( out.length, a, 1, b, 1, out, 1 )\n    [...]\n\n    // Advanced indexing:\n    > a = [ -10, -5, 0, 5, 10, 15 ];\n    > b = [ 20, 20, 20, 20, 20, 20 ];\n    > out = azeros( 6, 'generic' );\n    > random.strided.discreteUniform( 3, a, -2, b, 1, out, 1 )\n    [...]\n\n\nrandom.strided.discreteUniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a discrete\n    uniform distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    a: ArrayLikeObject\n        Minimum support.\n\n    sa: integer\n        Index increment for `a`.\n\n    oa: integer\n        Starting index for `a`.\n\n    b: ArrayLikeObject\n        Maximum support.\n\n    sb: integer\n        Index increment for `b`.\n\n    ob: integer\n        Starting index for `b`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = [ -10, -5, 0, 5, 10 ];\n    > var b = [ 20, 20, 20, 20, 20 ];\n    > var out = azeros( 5, 'generic' );\n    > random.strided.discreteUniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = [ -10, -5, 0, 5, 10, 15 ];\n    > b = [ 20, 20, 20, 20, 20, 20 ];\n    > out = azeros( 6, 'generic' );\n    > random.strided.discreteUniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.discreteUniform, random.array.discreteUniform, random.strided.uniform\n","random.strided.discreteUniform.ndarray":"\nrandom.strided.discreteUniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a discrete\n    uniform distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    a: ArrayLikeObject\n        Minimum support.\n\n    sa: integer\n        Index increment for `a`.\n\n    oa: integer\n        Starting index for `a`.\n\n    b: ArrayLikeObject\n        Maximum support.\n\n    sb: integer\n        Index increment for `b`.\n\n    ob: integer\n        Starting index for `b`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = [ -10, -5, 0, 5, 10 ];\n    > var b = [ 20, 20, 20, 20, 20 ];\n    > var out = azeros( 5, 'generic' );\n    > random.strided.discreteUniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = [ -10, -5, 0, 5, 10, 15 ];\n    > b = [ 20, 20, 20, 20, 20, 20 ];\n    > out = azeros( 6, 'generic' );\n    > random.strided.discreteUniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.discreteUniform, random.array.discreteUniform, random.strided.uniform","random.strided.exponential":"\nrandom.strided.exponential( N, lambda, sl, out, so )\n    Fills a strided array with pseudorandom numbers drawn from an exponential\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    lambda: ArrayLikeObject\n        Rate parameter.\n\n    sl: integer\n        Index increment for `lambda`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.exponential.ndarray( N, lambda, sl, ol, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from an exponential\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    lambda: ArrayLikeObject\n        Rate parameter.\n\n    sl: integer\n        Index increment for `lambda`.\n\n    ol: integer\n        Starting index for `lambda`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.exponential.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]\n\n\nrandom.strided.exponential.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from an exponential distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.exponential.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.exponential.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.exponential.PRNG;\n\n\nrandom.strided.exponential.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.exponential.seed;\n\n\nrandom.strided.exponential.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.exponential.seedLength;\n\n\nrandom.strided.exponential.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.exponential.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.exponential.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.exponential.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.exponential.stateLength;\n\n\nrandom.strided.exponential.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.exponential.byteLength;\n\n    See Also\n    --------\n    base.random.exponential, random.array.exponential\n","random.strided.exponential.ndarray":"\nrandom.strided.exponential.ndarray( N, lambda, sl, ol, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from an exponential\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    lambda: ArrayLikeObject\n        Rate parameter.\n\n    sl: integer\n        Index increment for `lambda`.\n\n    ol: integer\n        Starting index for `lambda`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.exponential.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]","random.strided.exponential.factory":"\nrandom.strided.exponential.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from an exponential distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.exponential.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.exponential.PRNG":"\nrandom.strided.exponential.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.exponential.PRNG;","random.strided.exponential.seed":"\nrandom.strided.exponential.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.exponential.seed;","random.strided.exponential.seedLength":"\nrandom.strided.exponential.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.exponential.seedLength;","random.strided.exponential.state":"\nrandom.strided.exponential.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.exponential.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.exponential.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.exponential.stateLength":"\nrandom.strided.exponential.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.exponential.stateLength;","random.strided.exponential.byteLength":"\nrandom.strided.exponential.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.exponential.byteLength;\n\n    See Also\n    --------\n    base.random.exponential, random.array.exponential","random.strided.gamma":"\nrandom.strided.gamma( N, alpha, sa, beta, sb, out, so[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a gamma\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        Shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    beta: ArrayLikeObject\n        Rate parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.gamma( out.length, a, 1, b, 1, out, 1 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.gamma( 3, a, -2, b, 1, out, 1 )\n    [...]\n\n\nrandom.strided.gamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a gamma\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        Shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    oa: integer\n        Starting index for `alpha`.\n\n    beta: ArrayLikeObject\n        Rate parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    ob: integer\n        Starting index for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.gamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.gamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.gamma, random.array.gamma\n","random.strided.gamma.ndarray":"\nrandom.strided.gamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a gamma\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        Shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    oa: integer\n        Starting index for `alpha`.\n\n    beta: ArrayLikeObject\n        Rate parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    ob: integer\n        Starting index for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.gamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.gamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.gamma, random.array.gamma","random.strided.geometric":"\nrandom.strided.geometric( N, p, sp, out, so )\n    Fills a strided array with pseudorandom numbers drawn from a geometric\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    p: ArrayLikeObject\n        Success probability.\n\n    sp: integer\n        Index increment for `p`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.geometric.ndarray( N, p, sp, op, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a geometric\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    p: ArrayLikeObject\n        Success probability.\n\n    sp: integer\n        Index increment for `p`.\n\n    op: integer\n        Starting index for `p`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.geometric.ndarray( out.length, [ 0.01 ], 0, 0, out, 1, 0 )\n    [...]\n\n\nrandom.strided.geometric.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a geometric distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.geometric.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 0.01 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.geometric.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.geometric.PRNG;\n\n\nrandom.strided.geometric.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.geometric.seed;\n\n\nrandom.strided.geometric.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.geometric.seedLength;\n\n\nrandom.strided.geometric.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.geometric.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.geometric.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.geometric.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.geometric.stateLength;\n\n\nrandom.strided.geometric.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.geometric.byteLength;\n\n    See Also\n    --------\n    base.random.geometric, random.array.geometric\n","random.strided.geometric.ndarray":"\nrandom.strided.geometric.ndarray( N, p, sp, op, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a geometric\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    p: ArrayLikeObject\n        Success probability.\n\n    sp: integer\n        Index increment for `p`.\n\n    op: integer\n        Starting index for `p`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.geometric.ndarray( out.length, [ 0.01 ], 0, 0, out, 1, 0 )\n    [...]","random.strided.geometric.factory":"\nrandom.strided.geometric.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a geometric distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.geometric.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 0.01 ], 0, out, 1 )\n    [...]","random.strided.geometric.PRNG":"\nrandom.strided.geometric.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.geometric.PRNG;","random.strided.geometric.seed":"\nrandom.strided.geometric.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.geometric.seed;","random.strided.geometric.seedLength":"\nrandom.strided.geometric.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.geometric.seedLength;","random.strided.geometric.state":"\nrandom.strided.geometric.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.geometric.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.geometric.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n    [...]","random.strided.geometric.stateLength":"\nrandom.strided.geometric.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.geometric.stateLength;","random.strided.geometric.byteLength":"\nrandom.strided.geometric.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.geometric.byteLength;\n\n    See Also\n    --------\n    base.random.geometric, random.array.geometric","random.strided.invgamma":"\nrandom.strided.invgamma( N, alpha, sa, beta, sb, out, so[, options] )\n    Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        Shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    beta: ArrayLikeObject\n        Scale parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.invgamma( out.length, a, 1, b, 1, out, 1 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.invgamma( 3, a, -2, b, 1, out, 1 )\n    [...]\n\n\nrandom.strided.invgamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        Shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    oa: integer\n        Starting index for `alpha`.\n\n    beta: ArrayLikeObject\n        Scale parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    ob: integer\n        Starting index for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.invgamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.invgamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.invgamma, random.array.invgamma\n","random.strided.invgamma.ndarray":"\nrandom.strided.invgamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        Shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    oa: integer\n        Starting index for `alpha`.\n\n    beta: ArrayLikeObject\n        Scale parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    ob: integer\n        Starting index for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.invgamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.invgamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.invgamma, random.array.invgamma","random.strided.lognormal":"\nrandom.strided.lognormal( N, mu, sm, sigma, ss, out, so[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a lognormal\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mu: ArrayLikeObject\n        Location parameter.\n\n    sm: integer\n        Index increment for `mu`.\n\n    sigma: ArrayLikeObject\n        Scale parameter.\n\n    ss: integer\n        Index increment for `sigma`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var mu = linspace( 0.0, 1.0, 5 );\n    > var sigma = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.lognormal( out.length, mu, 1, sigma, 1, out, 1 )\n    [...]\n\n    // Advanced indexing:\n    > mu = linspace( 0.0, 1.0, 6 );\n    > sigma = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.lognormal( 3, mu, -2, sigma, 1, out, 1 )\n    [...]\n\n\nrandom.strided.lognormal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a lognormal\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mu: ArrayLikeObject\n        Location parameter.\n\n    sm: integer\n        Index increment for `mu`.\n\n    om: integer\n        Starting index for `mu`.\n\n    sigma: ArrayLikeObject\n        Scale parameter.\n\n    ss: integer\n        Index increment for `sigma`.\n\n    os: integer\n        Starting index for `sigma`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var mu = linspace( 0.0, 1.0, 5 );\n    > var sigma = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.lognormal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > mu = linspace( 0.0, 1.0, 6 );\n    > sigma = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.lognormal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.lognormal, random.array.lognormal\n","random.strided.lognormal.ndarray":"\nrandom.strided.lognormal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a lognormal\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mu: ArrayLikeObject\n        Location parameter.\n\n    sm: integer\n        Index increment for `mu`.\n\n    om: integer\n        Starting index for `mu`.\n\n    sigma: ArrayLikeObject\n        Scale parameter.\n\n    ss: integer\n        Index increment for `sigma`.\n\n    os: integer\n        Starting index for `sigma`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var mu = linspace( 0.0, 1.0, 5 );\n    > var sigma = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.lognormal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > mu = linspace( 0.0, 1.0, 6 );\n    > sigma = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.lognormal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.lognormal, random.array.lognormal","random.strided.minstd":"\nrandom.strided.minstd( N, out, so[, options] )\n    Fills a strided array with pseudorandom integers between 1 and 2147483646\n    (inclusive).\n\n    The `N` and stride parameters determine which elements in the provided\n    strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstd( out.length, out, 1 )\n    [...]\n\n\nrandom.strided.minstd.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom integers between 1 and 2147483646\n    (inclusive) using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstd.ndarray( out.length, out, 1, 0 )\n    [...]\n\n\nrandom.strided.minstd.normalized( N, out, so[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstd.normalized( out.length, out, 1 )\n    [...]\n\n\nrandom.strided.minstd.normalized.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1 using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstd.normalized.ndarray( out.length, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.minstd, random.array.minstd, random.strided.minstdShuffle, random.strided.randu\n","random.strided.minstd.ndarray":"\nrandom.strided.minstd.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom integers between 1 and 2147483646\n    (inclusive) using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstd.ndarray( out.length, out, 1, 0 )\n    [...]","random.strided.minstd.normalized":"\nrandom.strided.minstd.normalized( N, out, so[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstd.normalized( out.length, out, 1 )\n    [...]","random.strided.minstd.normalized.ndarray":"\nrandom.strided.minstd.normalized.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1 using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstd.normalized.ndarray( out.length, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.minstd, random.array.minstd, random.strided.minstdShuffle, random.strided.randu","random.strided.minstdShuffle":"\nrandom.strided.minstdShuffle( N, out, so[, options] )\n    Fills a strided array with pseudorandom integers between 1 and 2147483646\n    (inclusive).\n\n    The `N` and stride parameters determine which elements in the provided\n    strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstdShuffle( out.length, out, 1 )\n    [...]\n\n\nrandom.strided.minstdShuffle.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom integers between 1 and 2147483646\n    (inclusive) using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstdShuffle.ndarray( out.length, out, 1, 0 )\n    [...]\n\n\nrandom.strided.minstdShuffle.normalized( N, out, so[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstdShuffle.normalized( out.length, out, 1 )\n    [...]\n\n\nrandom.strided.minstdShuffle.normalized.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1 using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstdShuffle.normalized.ndarray( out.length, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.minstdShuffle, random.array.minstdShuffle, random.strided.minstd, random.strided.randu\n","random.strided.minstdShuffle.ndarray":"\nrandom.strided.minstdShuffle.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom integers between 1 and 2147483646\n    (inclusive) using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstdShuffle.ndarray( out.length, out, 1, 0 )\n    [...]","random.strided.minstdShuffle.normalized":"\nrandom.strided.minstdShuffle.normalized( N, out, so[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstdShuffle.normalized( out.length, out, 1 )\n    [...]","random.strided.minstdShuffle.normalized.ndarray":"\nrandom.strided.minstdShuffle.normalized.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1 using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstdShuffle.normalized.ndarray( out.length, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.minstdShuffle, random.array.minstdShuffle, random.strided.minstd, random.strided.randu","random.strided.mt19937":"\nrandom.strided.mt19937( N, out, so[, options] )\n    Fills a strided array with pseudorandom integers between 0 and 4294967295\n    (inclusive).\n\n    The `N` and stride parameters determine which elements in the provided\n    strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.mt19937( out.length, out, 1 )\n    [...]\n\n\nrandom.strided.mt19937.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom integers between 0 and 4294967295\n    (inclusive) using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.mt19937.ndarray( out.length, out, 1, 0 )\n    [...]\n\n\nrandom.strided.mt19937.normalized( N, out, so[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.mt19937.normalized( out.length, out, 1 )\n    [...]\n\n\nrandom.strided.mt19937.normalized.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1 using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.mt19937.normalized.ndarray( out.length, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.mt19937, random.array.mt19937, random.strided.randu\n","random.strided.mt19937.ndarray":"\nrandom.strided.mt19937.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom integers between 0 and 4294967295\n    (inclusive) using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.mt19937.ndarray( out.length, out, 1, 0 )\n    [...]","random.strided.mt19937.normalized":"\nrandom.strided.mt19937.normalized( N, out, so[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.mt19937.normalized( out.length, out, 1 )\n    [...]","random.strided.mt19937.normalized.ndarray":"\nrandom.strided.mt19937.normalized.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1 using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.mt19937.normalized.ndarray( out.length, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.mt19937, random.array.mt19937, random.strided.randu","random.strided.normal":"\nrandom.strided.normal( N, mu, sm, sigma, ss, out, so[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a normal\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mu: ArrayLikeObject\n        Mean.\n\n    sm: integer\n        Index increment for `mu`.\n\n    sigma: ArrayLikeObject\n        Standard deviation.\n\n    ss: integer\n        Index increment for `sigma`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var mu = linspace( 0.0, 1.0, 5 );\n    > var sigma = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.normal( out.length, mu, 1, sigma, 1, out, 1 )\n    [...]\n\n    // Advanced indexing:\n    > mu = linspace( 0.0, 1.0, 6 );\n    > sigma = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.normal( 3, mu, -2, sigma, 1, out, 1 )\n    [...]\n\n\nrandom.strided.normal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a normal\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mu: ArrayLikeObject\n        Mean.\n\n    sm: integer\n        Index increment for `mu`.\n\n    om: integer\n        Starting index for `mu`.\n\n    sigma: ArrayLikeObject\n        Standard deviation.\n\n    ss: integer\n        Index increment for `sigma`.\n\n    os: integer\n        Starting index for `sigma`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var mu = linspace( 0.0, 1.0, 5 );\n    > var sigma = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.normal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > mu = linspace( 0.0, 1.0, 6 );\n    > sigma = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.normal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.normal, random.array.normal\n","random.strided.normal.ndarray":"\nrandom.strided.normal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a normal\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mu: ArrayLikeObject\n        Mean.\n\n    sm: integer\n        Index increment for `mu`.\n\n    om: integer\n        Starting index for `mu`.\n\n    sigma: ArrayLikeObject\n        Standard deviation.\n\n    ss: integer\n        Index increment for `sigma`.\n\n    os: integer\n        Starting index for `sigma`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var mu = linspace( 0.0, 1.0, 5 );\n    > var sigma = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.normal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > mu = linspace( 0.0, 1.0, 6 );\n    > sigma = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.normal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.normal, random.array.normal","random.strided.poisson":"\nrandom.strided.poisson( N, lambda, sl, out, so )\n    Fills a strided array with pseudorandom numbers drawn from a Poisson\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    lambda: ArrayLikeObject\n        Mean parameter.\n\n    sl: integer\n        Index increment for `lambda`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.poisson.ndarray( N, lambda, sl, ol, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a Poisson\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    lambda: ArrayLikeObject\n        Mean parameter.\n\n    sl: integer\n        Index increment for `lambda`.\n\n    ol: integer\n        Starting index for `lambda`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.poisson.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]\n\n\nrandom.strided.poisson.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Poisson distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.poisson.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.poisson.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.poisson.PRNG;\n\n\nrandom.strided.poisson.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.poisson.seed;\n\n\nrandom.strided.poisson.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.poisson.seedLength;\n\n\nrandom.strided.poisson.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.poisson.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.poisson.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.poisson.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.poisson.stateLength;\n\n\nrandom.strided.poisson.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.poisson.byteLength;\n\n    See Also\n    --------\n    base.random.poisson, random.array.poisson\n","random.strided.poisson.ndarray":"\nrandom.strided.poisson.ndarray( N, lambda, sl, ol, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a Poisson\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    lambda: ArrayLikeObject\n        Mean parameter.\n\n    sl: integer\n        Index increment for `lambda`.\n\n    ol: integer\n        Starting index for `lambda`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.poisson.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]","random.strided.poisson.factory":"\nrandom.strided.poisson.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Poisson distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.poisson.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.poisson.PRNG":"\nrandom.strided.poisson.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.poisson.PRNG;","random.strided.poisson.seed":"\nrandom.strided.poisson.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.poisson.seed;","random.strided.poisson.seedLength":"\nrandom.strided.poisson.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.poisson.seedLength;","random.strided.poisson.state":"\nrandom.strided.poisson.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.poisson.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.poisson.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.poisson.stateLength":"\nrandom.strided.poisson.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.poisson.stateLength;","random.strided.poisson.byteLength":"\nrandom.strided.poisson.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.poisson.byteLength;\n\n    See Also\n    --------\n    base.random.poisson, random.array.poisson","random.strided.randu":"\nrandom.strided.randu( N, out, so[, options] )\n    Fills a strided array with uniformly distributed pseudorandom numbers\n    between 0 and 1.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: `'mt19937'`.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.randu( out.length, out, 1 )\n    [...]\n\n\nrandom.strided.randu.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with uniformly distributed pseudorandom numbers\n    between 0 and 1 using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: `'mt19937'`.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.randu.ndarray( out.length, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.randu, random.array.randu, random.strided.uniform\n","random.strided.randu.ndarray":"\nrandom.strided.randu.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with uniformly distributed pseudorandom numbers\n    between 0 and 1 using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: `'mt19937'`.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.randu.ndarray( out.length, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.randu, random.array.randu, random.strided.uniform","random.strided.rayleigh":"\nrandom.strided.rayleigh( N, sigma, ss, out, so )\n    Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sigma: ArrayLikeObject\n        Scale parameter.\n\n    ss: integer\n        Index increment for `sigma`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.rayleigh.ndarray( N, sigma, ss, os, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sigma: ArrayLikeObject\n        Scale parameter.\n\n    ss: integer\n        Index increment for `sigma`.\n\n    os: integer\n        Starting index for `sigma`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.rayleigh.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]\n\n\nrandom.strided.rayleigh.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Rayleigh distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.rayleigh.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.rayleigh.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.rayleigh.PRNG;\n\n\nrandom.strided.rayleigh.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.rayleigh.seed;\n\n\nrandom.strided.rayleigh.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.rayleigh.seedLength;\n\n\nrandom.strided.rayleigh.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.rayleigh.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.rayleigh.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.rayleigh.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.rayleigh.stateLength;\n\n\nrandom.strided.rayleigh.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.rayleigh.byteLength;\n\n    See Also\n    --------\n    base.random.rayleigh, random.array.rayleigh\n","random.strided.rayleigh.ndarray":"\nrandom.strided.rayleigh.ndarray( N, sigma, ss, os, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sigma: ArrayLikeObject\n        Scale parameter.\n\n    ss: integer\n        Index increment for `sigma`.\n\n    os: integer\n        Starting index for `sigma`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.rayleigh.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]","random.strided.rayleigh.factory":"\nrandom.strided.rayleigh.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Rayleigh distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.rayleigh.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.rayleigh.PRNG":"\nrandom.strided.rayleigh.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.rayleigh.PRNG;","random.strided.rayleigh.seed":"\nrandom.strided.rayleigh.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.rayleigh.seed;","random.strided.rayleigh.seedLength":"\nrandom.strided.rayleigh.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.rayleigh.seedLength;","random.strided.rayleigh.state":"\nrandom.strided.rayleigh.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.rayleigh.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.rayleigh.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.rayleigh.stateLength":"\nrandom.strided.rayleigh.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.rayleigh.stateLength;","random.strided.rayleigh.byteLength":"\nrandom.strided.rayleigh.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.rayleigh.byteLength;\n\n    See Also\n    --------\n    base.random.rayleigh, random.array.rayleigh","random.strided.t":"\nrandom.strided.t( N, v, sv, out, so )\n    Fills a strided array with pseudorandom numbers drawn from a Student's t-\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    v: ArrayLikeObject\n        Degrees of freedom.\n\n    sv: integer\n        Index increment for `v`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.t.ndarray( N, v, sv, ov, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a Student's t-\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    v: ArrayLikeObject\n        Degrees of freedom.\n\n    sv: integer\n        Index increment for `v`.\n\n    ov: integer\n        Starting index for `v`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.t.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]\n\n\nrandom.strided.t.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Student's t-distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.t.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.t.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.t.PRNG;\n\n\nrandom.strided.t.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.t.seed;\n\n\nrandom.strided.t.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.t.seedLength;\n\n\nrandom.strided.t.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.t.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.t.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.t.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.t.stateLength;\n\n\nrandom.strided.t.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.t.byteLength;\n\n    See Also\n    --------\n    base.random.t, random.array.t\n","random.strided.t.ndarray":"\nrandom.strided.t.ndarray( N, v, sv, ov, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a Student's t-\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    v: ArrayLikeObject\n        Degrees of freedom.\n\n    sv: integer\n        Index increment for `v`.\n\n    ov: integer\n        Starting index for `v`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.t.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]","random.strided.t.factory":"\nrandom.strided.t.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Student's t-distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.t.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.t.PRNG":"\nrandom.strided.t.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.t.PRNG;","random.strided.t.seed":"\nrandom.strided.t.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.t.seed;","random.strided.t.seedLength":"\nrandom.strided.t.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.t.seedLength;","random.strided.t.state":"\nrandom.strided.t.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.t.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.t.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.t.stateLength":"\nrandom.strided.t.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.t.stateLength;","random.strided.t.byteLength":"\nrandom.strided.t.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.t.byteLength;\n\n    See Also\n    --------\n    base.random.t, random.array.t","random.strided.uniform":"\nrandom.strided.uniform( N, a, sa, b, sb, out, so[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a continuous\n    uniform distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    a: ArrayLikeObject\n        Minimum support.\n\n    sa: integer\n        Index increment for `a`.\n\n    b: ArrayLikeObject\n        Maximum support.\n\n    sb: integer\n        Index increment for `b`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 0.0, 1.0, 5 );\n    > var b = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.uniform( out.length, a, 1, b, 1, out, 1 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 0.0, 1.0, 6 );\n    > b = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.uniform( 3, a, -2, b, 1, out, 1 )\n    [...]\n\n\nrandom.strided.uniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a continuous\n    uniform distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    a: ArrayLikeObject\n        Minimum support.\n\n    sa: integer\n        Index increment for `a`.\n\n    oa: integer\n        Starting index for `a`.\n\n    b: ArrayLikeObject\n        Maximum support.\n\n    sb: integer\n        Index increment for `b`.\n\n    ob: integer\n        Starting index for `b`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 0.0, 1.0, 5 );\n    > var b = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.uniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 0.0, 1.0, 6 );\n    > b = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.uniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.uniform, random.array.uniform, random.strided.discreteUniform\n","random.strided.uniform.ndarray":"\nrandom.strided.uniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a continuous\n    uniform distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    a: ArrayLikeObject\n        Minimum support.\n\n    sa: integer\n        Index increment for `a`.\n\n    oa: integer\n        Starting index for `a`.\n\n    b: ArrayLikeObject\n        Maximum support.\n\n    sb: integer\n        Index increment for `b`.\n\n    ob: integer\n        Starting index for `b`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 0.0, 1.0, 5 );\n    > var b = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.uniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 0.0, 1.0, 6 );\n    > b = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.uniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.uniform, random.array.uniform, random.strided.discreteUniform","random.strided.weibull":"\nrandom.strided.weibull( N, k, sk, lambda, sl, out, so[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a Weibull\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    k: ArrayLikeObject\n        Scale parameter.\n\n    sk: integer\n        Index increment for `k`.\n\n    lambda: ArrayLikeObject\n        Shape parameter.\n\n    sl: integer\n        Index increment for `lambda`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.weibull( out.length, a, 1, b, 1, out, 1 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.weibull( 3, a, -2, b, 1, out, 1 )\n    [...]\n\n\nrandom.strided.weibull.ndarray( N, k, sk, ok, lambda, sl, ol, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a Weibull\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    k: ArrayLikeObject\n        Scale parameter.\n\n    sk: integer\n        Index increment for `k`.\n\n    ok: integer\n        Starting index for `k`.\n\n    lambda: ArrayLikeObject\n        Shape parameter.\n\n    sl: integer\n        Index increment for `lambda`.\n\n    ol: integer\n        Starting index for `lambda`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.weibull.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.weibull.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.weibull, random.array.weibull\n","random.strided.weibull.ndarray":"\nrandom.strided.weibull.ndarray( N, k, sk, ok, lambda, sl, ol, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a Weibull\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    k: ArrayLikeObject\n        Scale parameter.\n\n    sk: integer\n        Index increment for `k`.\n\n    ok: integer\n        Starting index for `k`.\n\n    lambda: ArrayLikeObject\n        Shape parameter.\n\n    sl: integer\n        Index increment for `lambda`.\n\n    ol: integer\n        Starting index for `lambda`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.weibull.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.weibull.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.weibull, random.array.weibull","ranks":"\nranks( arr[, options] )\n    Computes the sample ranks for the values of an array-like object.\n\n    When all elements of the `array` are different, the ranks are uniquely\n    determined. When there are equal elements (called *ties*), the `method`\n    option determines how they are handled. The default, `'average'`, replaces\n    the ranks of the ties by their mean. Other possible options are `'min'` and\n    `'max'`, which replace the ranks of the ties by their minimum and maximum,\n    respectively. `'dense'` works like `'min'`, with the difference that the\n    next highest element after a tie is assigned the next smallest integer.\n    Finally, `ordinal` gives each element in `arr` a distinct rank, according to\n    the position they appear in.\n\n    The `missing` option is used to specify how to handle missing data.\n    By default, `NaN` or `null` are treated as missing values. `'last'`specifies\n    that missing values are placed last, `'first'` that the are assigned the\n    lowest ranks and `'remove'` means that they are removed from the array\n    before the ranks are calculated.\n\n    Parameters\n    ----------\n    arr: Array<number>\n        Input values.\n\n    options: Object (optional)\n        Function options.\n\n    options.method (optional)\n        Method name determining how ties are treated (`average`, `min`, `max`,\n        `dense`, or `ordinal`). Default: `'average'`.\n\n    options.missing (optional)\n        Determines where missing values go (`first`, `last`, or `remove`).\n        Default: `'last'`.\n\n    options.encoding (optional)\n        Array of values encoding missing values. Default: `[ null, NaN ]`.\n\n    Returns\n    -------\n    out: Array\n        Array containing the computed ranks for the elements of the input array.\n\n    Examples\n    --------\n    > var arr = [ 1.1, 2.0, 3.5, 0.0, 2.4 ] ;\n    > var out = ranks( arr )\n    [ 2, 3, 5, 1, 4 ]\n\n    // Ties are averaged:\n    > arr =  [ 2, 2, 1, 4, 3 ];\n    > out = ranks( arr )\n    [ 2.5, 2.5, 1, 5, 4 ]\n\n    // Missing values are placed last:\n    > arr = [ null, 2, 2, 1, 4, 3, NaN, NaN ];\n    > out = ranks( arr )\n    [ 6, 2.5, 2.5, 1, 5, 4, 7 ,8 ]\n\n","readDir":"\nreadDir( path, clbk )\n    Asynchronously reads the contents of a directory.\n\n    Parameters\n    ----------\n    path: string|Buffer\n        Directory path.\n\n    clbk: Function\n        Callback to invoke after reading directory contents.\n\n    Examples\n    --------\n    > function onRead( error, data ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     } else {\n    ...         console.log( data );\n    ...     }\n    ... };\n    > readDir( './beep/boop', onRead );\n\n\nreadDir.sync( path )\n    Synchronously reads the contents of a directory.\n\n    Parameters\n    ----------\n    path: string|Buffer\n        Directory path.\n\n    Returns\n    -------\n    out: Error|Array|Array<string>\n        Directory contents.\n\n    Examples\n    --------\n    > var out = readDir.sync( './beep/boop' );\n\n    See Also\n    --------\n    exists, readFile\n","readDir.sync":"\nreadDir.sync( path )\n    Synchronously reads the contents of a directory.\n\n    Parameters\n    ----------\n    path: string|Buffer\n        Directory path.\n\n    Returns\n    -------\n    out: Error|Array|Array<string>\n        Directory contents.\n\n    Examples\n    --------\n    > var out = readDir.sync( './beep/boop' );\n\n    See Also\n    --------\n    exists, readFile","readFile":"\nreadFile( file[, options], clbk )\n    Asynchronously reads the entire contents of a file.\n\n    If provided an encoding, the function returns a string. Otherwise, the\n    function returns a Buffer object.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. Default: null.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    clbk: Function\n        Callback to invoke upon reading file contents.\n\n    Examples\n    --------\n    > function onRead( error, data ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     } else {\n    ...         console.log( data );\n    ...     }\n    ... };\n    > readFile( './beep/boop.js', onRead );\n\n\nreadFile.sync( file[, options] )\n    Synchronously reads the entire contents of a file.\n\n    If provided an encoding, the function returns a string. Otherwise, the\n    function returns a Buffer object.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. Default: null.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    Returns\n    -------\n    out: Error|Buffer|string\n        File contents.\n\n    Examples\n    --------\n    > var out = readFile.sync( './beep/boop.js' );\n\n    See Also\n    --------\n    exists, open, readDir, readJSON, writeFile\n","readFile.sync":"\nreadFile.sync( file[, options] )\n    Synchronously reads the entire contents of a file.\n\n    If provided an encoding, the function returns a string. Otherwise, the\n    function returns a Buffer object.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. Default: null.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    Returns\n    -------\n    out: Error|Buffer|string\n        File contents.\n\n    Examples\n    --------\n    > var out = readFile.sync( './beep/boop.js' );\n\n    See Also\n    --------\n    exists, open, readDir, readJSON, writeFile","readFileList":"\nreadFileList( filepaths[, options], clbk )\n    Asynchronously reads the entire contents of each file in a file list.\n\n    If a provided an encoding, the function returns file contents as strings.\n    Otherwise, the function returns Buffer objects.\n\n    Each file is represented by an object with the following fields:\n\n    - file: file path.\n    - data: file contents as either a Buffer or string.\n\n    Parameters\n    ----------\n    filepaths: Array<string>\n        Filepaths.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. Default: null.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    clbk: Function\n        Callback to invoke upon reading file contents.\n\n    Examples\n    --------\n    > function onRead( error, data ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     } else {\n    ...         console.log( data );\n    ...     }\n    ... };\n    > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n    > readFileList( filepaths, onRead );\n\n\nreadFileList.sync( filepaths[, options] )\n    Synchronously reads the entire contents of each file in a file list.\n\n    If a provided an encoding, the function returns file contents as strings.\n    Otherwise, the function returns Buffer objects.\n\n    Parameters\n    ----------\n    filepaths: Array<string>\n        Filepaths.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. Default: null.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    Returns\n    -------\n    out: Error|Array|Array<string>\n        File contents.\n\n    out[ i ].file: string\n        File path.\n\n    out[ i ].data: Buffer|string\n        File contents.\n\n    Examples\n    --------\n    > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n    > var out = readFileList.sync( filepaths );\n\n","readFileList.sync":"\nreadFileList.sync( filepaths[, options] )\n    Synchronously reads the entire contents of each file in a file list.\n\n    If a provided an encoding, the function returns file contents as strings.\n    Otherwise, the function returns Buffer objects.\n\n    Parameters\n    ----------\n    filepaths: Array<string>\n        Filepaths.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. Default: null.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    Returns\n    -------\n    out: Error|Array|Array<string>\n        File contents.\n\n    out[ i ].file: string\n        File path.\n\n    out[ i ].data: Buffer|string\n        File contents.\n\n    Examples\n    --------\n    > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n    > var out = readFileList.sync( filepaths );","readJSON":"\nreadJSON( file[, options], clbk )\n    Asynchronously reads a file as JSON.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. If the encoding option is set to `utf8` and the file has a\n        UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n        attempting to parse as JSON. Default: null.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    options.reviver: Function (optional)\n        JSON transformation function.\n\n    clbk: Function\n        Callback to invoke upon reading file contents.\n\n    Examples\n    --------\n    > function onRead( error, data ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     } else {\n    ...         console.log( data );\n    ...     }\n    ... };\n    > readJSON( './beep/boop.json', onRead );\n\n\nreadJSON.sync( file[, options] )\n    Synchronously reads a file as JSON.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. If the encoding option is set to `utf8` and the file has a\n        UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n        attempting to parse as JSON. Default: null.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    options.reviver: Function (optional)\n        JSON transformation function.\n\n    Returns\n    -------\n    out: Error|JSON\n        File contents.\n\n    Examples\n    --------\n    > var out = readJSON.sync( './beep/boop.json' );\n\n    See Also\n    --------\n    readFile\n","readJSON.sync":"\nreadJSON.sync( file[, options] )\n    Synchronously reads a file as JSON.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. If the encoding option is set to `utf8` and the file has a\n        UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n        attempting to parse as JSON. Default: null.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    options.reviver: Function (optional)\n        JSON transformation function.\n\n    Returns\n    -------\n    out: Error|JSON\n        File contents.\n\n    Examples\n    --------\n    > var out = readJSON.sync( './beep/boop.json' );\n\n    See Also\n    --------\n    readFile","readWASM":"\nreadWASM( file[, options], clbk )\n    Asynchronously reads a file as WebAssembly.\n\n    The function returns file contents as a Uint8Array.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    options: Object (optional)\n        Options.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    clbk: Function\n        Callback to invoke upon reading file contents.\n\n    Examples\n    --------\n    > function onRead( error, data ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     } else {\n    ...         console.log( data );\n    ...     }\n    ... };\n    > readWASM( './beep/boop.wasm', onRead );\n\n\nreadWASM.sync( file[, options] )\n    Synchronously reads a file as WebAssembly.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    options: Object (optional)\n        Options.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    Returns\n    -------\n    out: Error|Uint8Array\n        File contents.\n\n    Examples\n    --------\n    > var out = readWASM.sync( './beep/boop.wasm' );\n\n    See Also\n    --------\n    readFile\n","readWASM.sync":"\nreadWASM.sync( file[, options] )\n    Synchronously reads a file as WebAssembly.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    options: Object (optional)\n        Options.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    Returns\n    -------\n    out: Error|Uint8Array\n        File contents.\n\n    Examples\n    --------\n    > var out = readWASM.sync( './beep/boop.wasm' );\n\n    See Also\n    --------\n    readFile","real":"\nreal( z )\n    Returns the real component of a double-precision complex floating-point\n    number.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    re: number\n        Real component.\n\n    Examples\n    --------\n    > var z = new Complex128( 5.0, 3.0 );\n    > var re = real( z )\n    5.0\n\n    See Also\n    --------\n    imag, reim\n","realarray":"\nrealarray( [dtype] )\n    Creates a typed array.\n\n    The function supports the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754).\n    - float32: single-precision floating-point numbers (IEEE 754).\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n\n    The default typed array data type is `float64`.\n\n    Parameters\n    ----------\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = realarray()\n    <Float64Array>\n    > arr = realarray( 'float32' )\n    <Float32Array>\n\n\nrealarray( length[, dtype] )\n    Returns a typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = realarray( 5 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n    > arr = realarray( 5, 'int32' )\n    <Int32Array>[ 0, 0, 0, 0, 0 ]\n\n\nrealarray( typedarray[, dtype] )\n    Creates a typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = realarray( [ 0.5, 0.5, 0.5 ] );\n    > var arr2 = realarray( arr1, 'float32' )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]\n\n\nrealarray( obj[, dtype] )\n    Creates a typed array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a typed array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 0.5, 0.5, 0.5 ];\n    > var arr2 = realarray( arr1, 'float32' )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]\n\n\nrealarray( buffer[, byteOffset[, length]][, dtype] )\n    Returns a typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 16 );\n    > var arr = realarray( buf, 0, 4, 'float32' )\n    <Float32Array>[ 0.0, 0.0, 0.0, 0.0 ]\n\n    See Also\n    --------\n    Float64Array, Float32Array, Int32Array, Uint32Array, Int16Array, Uint16Array, Int8Array, Uint8Array, Uint8ClampedArray\n","realarrayCtors":"\nrealarrayCtors( dtype )\n    Returns a typed array constructor.\n\n    The function returns constructors for the following data types:\n\n    - float32: single-precision floating-point numbers.\n    - float64: double-precision floating-point numbers.\n    - int16: signed 16-bit integers.\n    - int32: signed 32-bit integers.\n    - int8: signed 8-bit integers.\n    - uint16: unsigned 16-bit integers.\n    - uint32: unsigned 32-bit integers.\n    - uint8: unsigned 8-bit integers.\n    - uint8c: unsigned clamped 8-bit integers.\n\n    Parameters\n    ----------\n    dtype: string\n        Data type.\n\n    Returns\n    -------\n    out: Function|null\n        Typed array constructor.\n\n    Examples\n    --------\n    > var ctor = realarrayCtors( 'float64' )\n    <Function>\n    > ctor = realarrayCtors( 'float' )\n    null\n\n    See Also\n    --------\n    arrayCtors, complexarrayCtors\n","realarrayDataTypes":"\nrealarrayDataTypes()\n    Returns a list of typed array real-valued data types.\n\n    Returns\n    -------\n    out: Array<string>\n        List of typed array data types.\n\n    Examples\n    --------\n    > var out = realarrayDataTypes()\n    <Array>\n\n    See Also\n    --------\n    arrayDataTypes, complexarrayDataTypes\n","realf":"\nrealf( z )\n    Returns the real component of a single-precision complex floating-point\n    number.\n\n    Parameters\n    ----------\n    z: Complex64\n        Complex number.\n\n    Returns\n    -------\n    re: number\n        Real component.\n\n    Examples\n    --------\n    > var z = new Complex64( 5.0, 3.0 );\n    > var re = realf( z )\n    5.0\n\n    See Also\n    --------\n    imagf, real, reimf\n","realmax":"\nrealmax( dtype )\n    Returns the maximum finite value capable of being represented by a numeric\n    real type.\n\n    The following numeric real types are supported:\n\n    - float64: double-precision floating-point numbers.\n    - float32: single-precision floating-point numbers.\n    - float16: half-precision floating-point numbers.\n\n    Parameters\n    ----------\n    dtype: string\n        Numeric type.\n\n    Returns\n    -------\n    out: number\n        Maximum finite value.\n\n    Examples\n    --------\n    > var m = realmax( 'float16' )\n    65504.0\n    > m = realmax( 'float32' )\n    3.4028234663852886e+38\n\n    See Also\n    --------\n    realmin, typemax\n","realmin":"\nrealmin( dtype )\n    Returns the smallest positive normal value capable of being represented by a\n    numeric real type.\n\n    The following numeric real types are supported:\n\n    - float64: double-precision floating-point numbers.\n    - float32: single-precision floating-point numbers.\n    - float16: half-precision floating-point numbers.\n\n    Parameters\n    ----------\n    dtype: string\n        Numeric type.\n\n    Returns\n    -------\n    out: number\n        Smallest finite normal value.\n\n    Examples\n    --------\n    > var m = realmin( 'float16' )\n    0.00006103515625\n    > m = realmin( 'float32' )\n    1.1754943508222875e-38\n\n    See Also\n    --------\n    realmax, typemin\n","reBasename":"\nreBasename( [platform] )\n    Returns a regular expression to capture the last part of a path.\n\n    The regular expression is platform-dependent. If the current process is\n    running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n    `*.REGEXP_POSIX`.\n\n    Parameters\n    ----------\n    platform: string (optional)\n        Path platform (either `posix` or `win32`).\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reBasename()\n    <RegExp>\n    > var RE_POSIX = reBasename( 'posix' );\n    > var RE_WIN32 = reBasename( 'win32' );\n    > var str = RE.toString();\n    > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n    true\n\n\nreBasename.REGEXP\n    Regular expression to capture the last part of a POSIX path.\n\n    Examples\n    --------\n    > var RE = reBasename.REGEXP\n    <RegExp>\n\n\nreBasename.REGEXP_POSIX\n    Regular expression to capture the last part of a POSIX path.\n\n    Examples\n    --------\n    > var base = reBasename.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n    'index.js'\n\n\nreBasename.REGEXP_WIN32\n    Regular expression to capture the last part of a Windows path.\n\n    Examples\n    --------\n    > var base = reBasename.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    'index.js'\n\n    See Also\n    --------\n    reBasenamePosix, reBasenameWindows\n","reBasename.REGEXP":"\nreBasename.REGEXP\n    Regular expression to capture the last part of a POSIX path.\n\n    Examples\n    --------\n    > var RE = reBasename.REGEXP\n    <RegExp>","reBasename.REGEXP_POSIX":"\nreBasename.REGEXP_POSIX\n    Regular expression to capture the last part of a POSIX path.\n\n    Examples\n    --------\n    > var base = reBasename.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n    'index.js'","reBasename.REGEXP_WIN32":"\nreBasename.REGEXP_WIN32\n    Regular expression to capture the last part of a Windows path.\n\n    Examples\n    --------\n    > var base = reBasename.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    'index.js'\n\n    See Also\n    --------\n    reBasenamePosix, reBasenameWindows","reBasenamePosix":"\nreBasenamePosix()\n    Returns a regular expression to capture the last part of a POSIX path.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE_BASENAME_POSIX = reBasenamePosix();\n    > var base = RE_BASENAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n    'index.js'\n    > base = RE_BASENAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\n    '.gitignore'\n    > base = RE_BASENAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\n    'file.pdf'\n    > base = RE_BASENAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\n    'file'\n    > base = RE_BASENAME_POSIX.exec( 'index.js' )[ 1 ]\n    'index.js'\n    > base = RE_BASENAME_POSIX.exec( '.' )[ 1 ]\n    '.'\n    > base = RE_BASENAME_POSIX.exec( './' )[ 1 ]\n    '.'\n    > base = RE_BASENAME_POSIX.exec( '' )[ 1 ]\n    ''\n\n\nreBasenamePosix.REGEXP\n    Regular expression to capture the last part of a POSIX path.\n\n    Examples\n    --------\n    > var base = reBasenamePosix.REGEXP.exec( 'foo/bar/index.js' )[ 1 ]\n    'index.js'\n\n    See Also\n    --------\n    reBasename, reBasenameWindows\n","reBasenamePosix.REGEXP":"\nreBasenamePosix.REGEXP\n    Regular expression to capture the last part of a POSIX path.\n\n    Examples\n    --------\n    > var base = reBasenamePosix.REGEXP.exec( 'foo/bar/index.js' )[ 1 ]\n    'index.js'\n\n    See Also\n    --------\n    reBasename, reBasenameWindows","reBasenameWindows":"\nreBasenameWindows()\n    Returns a regular expression to capture the last part of a Windows path.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE_BASENAME_WINDOWS = reBasenameWindows();\n    > var base = RE_BASENAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    'index.js'\n    > base = RE_BASENAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n    '.gitignore'\n    > base = RE_BASENAME_WINDOWS.exec( 'foo\\\\file.pdf' )[ 1 ]\n    'file.pdf'\n    > base = RE_BASENAME_WINDOWS.exec( 'foo\\\\bar\\\\file' )[ 1 ]\n    'file'\n    > base = RE_BASENAME_WINDOWS.exec( 'index.js' )[ 1 ]\n    'index.js'\n    > base = RE_BASENAME_WINDOWS.exec( '.' )[ 1 ]\n    '.'\n    > base = RE_BASENAME_WINDOWS.exec( '' )[ 1 ]\n    ''\n\n\nreBasenameWindows.REGEXP\n    Regular expression to capture the last part of a Windows path.\n\n    Examples\n    --------\n    > var match = reBasenameWindows.REGEXP.exec( 'foo\\\\file.pdf' )[ 1 ]\n    'file.pdf'\n\n    See Also\n    --------\n    reBasename, reBasenamePosix\n","reBasenameWindows.REGEXP":"\nreBasenameWindows.REGEXP\n    Regular expression to capture the last part of a Windows path.\n\n    Examples\n    --------\n    > var match = reBasenameWindows.REGEXP.exec( 'foo\\\\file.pdf' )[ 1 ]\n    'file.pdf'\n\n    See Also\n    --------\n    reBasename, reBasenamePosix","reColorHexadecimal":"\nreColorHexadecimal( [mode] )\n    Returns a regular expression to match a hexadecimal color.\n\n    Parameters\n    ----------\n    mode: string (optional)\n        Color format (`full`, `shorthand`, or `either`).\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reColorHexadecimal();\n    > var bool = RE.test( 'ffffff' )\n    true\n    > bool = RE.test( '000' )\n    false\n    > bool = RE.test( 'beep' )\n    false\n\n\nreColorHexadecimal.REGEXP\n    Regular expression to match a full hexadecimal color.\n\n    Examples\n    --------\n    > var bool = reColorHexadecimal.REGEXP.test( 'ffffff' )\n    true\n    > bool = reColorHexadecimal.REGEXP.test( '000' )\n    false\n    > bool = reColorHexadecimal.REGEXP.test( 'beep' )\n    false\n\n\nreColorHexadecimal.REGEXP_SHORTHAND\n    Regular expression to match a shorthand hexadecimal color.\n\n    Examples\n    --------\n    > var bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'ffffff' )\n    false\n    > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( '000' )\n    true\n    > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'beep' )\n    false\n\n\nreColorHexadecimal.REGEXP_EITHER\n    Regular expression to match either a shorthand or full length hexadecimal\n    color.\n\n    Examples\n    --------\n    > var bool = reColorHexadecimal.REGEXP_EITHER.test( 'ffffff' )\n    true\n    > bool = reColorHexadecimal.REGEXP_EITHER.test( '000' )\n    true\n    > bool = reColorHexadecimal.REGEXP_EITHER.test( 'beep' )\n    false\n\n","reColorHexadecimal.REGEXP":"\nreColorHexadecimal.REGEXP\n    Regular expression to match a full hexadecimal color.\n\n    Examples\n    --------\n    > var bool = reColorHexadecimal.REGEXP.test( 'ffffff' )\n    true\n    > bool = reColorHexadecimal.REGEXP.test( '000' )\n    false\n    > bool = reColorHexadecimal.REGEXP.test( 'beep' )\n    false","reColorHexadecimal.REGEXP_SHORTHAND":"\nreColorHexadecimal.REGEXP_SHORTHAND\n    Regular expression to match a shorthand hexadecimal color.\n\n    Examples\n    --------\n    > var bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'ffffff' )\n    false\n    > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( '000' )\n    true\n    > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'beep' )\n    false","reColorHexadecimal.REGEXP_EITHER":"\nreColorHexadecimal.REGEXP_EITHER\n    Regular expression to match either a shorthand or full length hexadecimal\n    color.\n\n    Examples\n    --------\n    > var bool = reColorHexadecimal.REGEXP_EITHER.test( 'ffffff' )\n    true\n    > bool = reColorHexadecimal.REGEXP_EITHER.test( '000' )\n    true\n    > bool = reColorHexadecimal.REGEXP_EITHER.test( 'beep' )\n    false","reDecimalNumber":"\nreDecimalNumber( [options] )\n    Returns a regular expression to match a decimal number.\n\n    A leading digit is not required.\n\n    A decimal point and at least one trailing digit is required.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.flags: string (optional)\n        Regular expression flags. Default: ''.\n\n    options.capture: boolean (optional)\n        Boolean indicating whether to create a capture group for the match.\n        Default: false.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reDecimalNumber();\n    > var bool = RE.test( '1.234' )\n    true\n    > bool = RE.test( '-1.234' )\n    true\n    > bool = RE.test( '0.0' )\n    true\n    > bool = RE.test( '.0' )\n    true\n    > bool = RE.test( '0' )\n    false\n    > bool = RE.test( 'beep' )\n    false\n\n    // Create a RegExp to capture all decimal numbers:\n    > var re = reDecimalNumber({ 'flags': 'g' });\n    > var str = '1.234 5.6, 7.8';\n    > var out = str.match( re )\n    [ '1.234', '5.6', '7.8' ]\n\n\nreDecimalNumber.REGEXP\n    Regular expression to match a decimal number.\n\n    A leading digit is not required.\n\n    A decimal point and at least one trailing digit is required.\n\n    Examples\n    --------\n    > var RE = reDecimalNumber.REGEXP;\n    > var bool = RE.test( '1.234' )\n    true\n    > bool = RE.test( '-1.234' )\n    true\n\n\nreDecimalNumber.REGEXP_CAPTURE\n    Regular expression to capture a decimal number.\n\n    A leading digit is not required.\n\n    A decimal point and at least one trailing digit is required.\n\n    Examples\n    --------\n    > var RE = reDecimalNumber.REGEXP_CAPTURE;\n    > var str = '1.02';\n    > var out = replace( str, RE, '$1 x $1' )\n    '1.02 x 1.02'\n","reDecimalNumber.REGEXP":"\nreDecimalNumber.REGEXP\n    Regular expression to match a decimal number.\n\n    A leading digit is not required.\n\n    A decimal point and at least one trailing digit is required.\n\n    Examples\n    --------\n    > var RE = reDecimalNumber.REGEXP;\n    > var bool = RE.test( '1.234' )\n    true\n    > bool = RE.test( '-1.234' )\n    true","reDecimalNumber.REGEXP_CAPTURE":"\nreDecimalNumber.REGEXP_CAPTURE\n    Regular expression to capture a decimal number.\n\n    A leading digit is not required.\n\n    A decimal point and at least one trailing digit is required.\n\n    Examples\n    --------\n    > var RE = reDecimalNumber.REGEXP_CAPTURE;\n    > var str = '1.02';\n    > var out = replace( str, RE, '$1 x $1' )\n    '1.02 x 1.02'","reDirname":"\nreDirname( [platform] )\n    Returns a regular expression to capture a path dirname.\n\n    The regular expression is platform-dependent. If the current process is\n    running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n    `*.REGEXP_POSIX`.\n\n    Parameters\n    ----------\n    platform: string (optional)\n        Path platform (either `posix` or `win32`).\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reDirname()\n    <RegExp>\n    > var RE_POSIX = reDirname( 'posix' );\n    > var dir = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n    '/foo/bar'\n    > var RE_WIN32 = reDirname( 'win32' );\n    > dir = RE_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    'C:\\foo\\bar'\n    > var str = RE.toString();\n    > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n    true\n\n\nreDirname.REGEXP\n    Regular expression to capture a path dirname.\n\n    Examples\n    --------\n    > var RE = reDirname.REGEXP\n    <RegExp>\n\n\nreDirname.REGEXP_POSIX\n    Regular expression to capture a POSIX path dirname.\n\n    Examples\n    --------\n    > var dir = reDirname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n    '/foo/bar'\n\n\nreDirname.REGEXP_WIN32\n    Regular expression to capture a Windows path dirname.\n\n    Examples\n    --------\n    > var dir = reDirname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    'C:\\foo\\bar'\n\n    See Also\n    --------\n    reDirnamePosix, reDirnameWindows, dirname\n","reDirname.REGEXP":"\nreDirname.REGEXP\n    Regular expression to capture a path dirname.\n\n    Examples\n    --------\n    > var RE = reDirname.REGEXP\n    <RegExp>","reDirname.REGEXP_POSIX":"\nreDirname.REGEXP_POSIX\n    Regular expression to capture a POSIX path dirname.\n\n    Examples\n    --------\n    > var dir = reDirname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n    '/foo/bar'","reDirname.REGEXP_WIN32":"\nreDirname.REGEXP_WIN32\n    Regular expression to capture a Windows path dirname.\n\n    Examples\n    --------\n    > var dir = reDirname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    'C:\\foo\\bar'\n\n    See Also\n    --------\n    reDirnamePosix, reDirnameWindows, dirname","reDirnamePosix":"\nreDirnamePosix()\n    Returns a regular expression to capture a POSIX path dirname.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reDirnamePosix();\n    > var dir = RE.exec( '/foo/bar/index.js' )[ 1 ]\n    '/foo/bar'\n    > dir = RE.exec( './foo/bar/.gitignore' )[ 1 ]\n    './foo/bar'\n    > dir = RE.exec( 'foo/file.pdf' )[ 1 ]\n    'foo'\n    > dir = RE.exec( '/foo/bar/file' )[ 1 ]\n    '/foo/bar'\n    > dir = RE.exec( 'index.js' )[ 1 ]\n    ''\n    > dir = RE.exec( '.' )[ 1 ]\n    '.'\n    > dir = RE.exec( './' )[ 1 ]\n    '.'\n    > dir = RE.exec( '' )[ 1 ]\n    ''\n\n\nreDirnamePosix.REGEXP\n    Regular expression to capture a POSIX path dirname.\n\n    Examples\n    --------\n    > var ext = reDirnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n    '/foo/bar'\n\n    See Also\n    --------\n    reDirname, reDirnameWindows, dirname\n","reDirnamePosix.REGEXP":"\nreDirnamePosix.REGEXP\n    Regular expression to capture a POSIX path dirname.\n\n    Examples\n    --------\n    > var ext = reDirnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n    '/foo/bar'\n\n    See Also\n    --------\n    reDirname, reDirnameWindows, dirname","reDirnameWindows":"\nreDirnameWindows()\n    Returns a regular expression to capture a Windows path dirname.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reDirnameWindows();\n    > var dir = RE.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n    'foo\\bar'\n    > dir = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n    'C:\\foo\\bar'\n    > dir = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\n    'foo'\n    > dir = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\n    '\\foo\\bar'\n    > dir = RE.exec( 'index.js' )[ 1 ]\n    ''\n    > dir = RE.exec( '' )[ 1 ]\n    ''\n\n\nreDirnameWindows.REGEXP\n    Regular expression to capture a Windows path dirname.\n\n    Examples\n    --------\n    > var dir = reDirnameWindows.REGEXP.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n    'foo\\bar'\n\n    See Also\n    --------\n    reDirname, reDirnamePosix, dirname\n","reDirnameWindows.REGEXP":"\nreDirnameWindows.REGEXP\n    Regular expression to capture a Windows path dirname.\n\n    Examples\n    --------\n    > var dir = reDirnameWindows.REGEXP.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n    'foo\\bar'\n\n    See Also\n    --------\n    reDirname, reDirnamePosix, dirname","reduce":"\nreduce( arr, initial, reducer[, thisArg] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    When invoked, the reduction function is provided four arguments:\n\n    - accumulator: accumulated value.\n    - value: array element.\n    - index: element index.\n    - arr: input array.\n\n    If provided an empty array, the function returns the initial value.\n\n    When provided an ndarray, the function performs a reduction over the entire\n    input ndarray (i.e., higher-order ndarray dimensions are flattened to a\n    single-dimension).\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject|ndarray\n        Input array.\n\n    initial: any\n        Accumulator value used in the first invocation of the reduction\n        function.\n\n    reducer: Function\n        Function to invoke for each element in the input array.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: any\n        Accumulated result.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.add, 2 );\n    > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > var out = reduce( arr, 0.0, f )\n    21.0\n\n    // ndarray:\n    > arr = array( arr, { 'shape': [ 2, 3 ] } );\n    > out = reduce( arr, 0.0, f )\n    21.0\n\n    See Also\n    --------\n    forEach, map, reduceAsync, reduceRight\n","reduce2d":"\nreduce2d( arr, initial, reducer[, thisArg] )\n    Reduces the number of dimensions by one of a two-dimensional nested array by\n    applying a function against an accumulator and each element along the\n    innermost dimension and returning the accumulation results as a one-\n    dimensional array.\n\n    The applied function is provided the following arguments:\n\n    - accumulator: accumulated value.\n    - value: array element.\n    - indices: current array element indices.\n    - arr: input array.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject<ArrayLikeObject>\n        Input array of arrays.\n\n    initial: ArrayLikeObject\n        Initial values. Must have a length equal to the size of the outermost\n        input array dimension.\n\n    reducer: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array\n        Accumulation results.\n\n    Examples\n    --------\n    > var f = naryFunction( base.add, 2 );\n    > var arr = [ [ 1, 2, 3 ], [ 4, 5, 6 ] ];\n    > var out = reduce2d( arr, [ 0, 0 ], f )\n    [ 6, 15 ]\n\n    See Also\n    --------\n    map2d, reduce\n","reduceAsync":"\nreduceAsync( collection, initial, [options,] reducer, done )\n    Applies a function against an accumulator and each element in a collection\n    and returns the accumulated result.\n\n    When invoked, `reducer` is provided a maximum of five arguments:\n\n    - accumulator: accumulated value.\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If\n    `reducer` accepts three arguments, `reducer` is provided:\n\n    - accumulator\n    - value\n    - next\n\n    If `reducer` accepts four arguments, `reducer` is provided:\n\n    - accumulator\n    - value\n    - index\n    - next\n\n    For every other `reducer` signature, `reducer` is provided all five\n    arguments.\n\n    The `next` callback accepts two arguments:\n\n    - error: error argument.\n    - accumulator: accumulated value.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    If provided an empty collection, the function invokes the `done` callback\n    with the `initial` value as the second argument.\n\n    The function does not skip `undefined` elements.\n\n    When processing collection elements concurrently, *beware* of race\n    conditions when updating an accumulator. This is especially true when an\n    accumulator is a primitive (e.g., a number). In general, prefer object\n    accumulators.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    initial: any\n        Accumulator value used in the first invocation of the reduction\n        function.\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: true.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    reducer: Function\n        The function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function fcn( acc, value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         acc.sum += value;\n    ...         next( null, acc );\n    ...     }\n    ... };\n    > function done( error, acc ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( acc.sum );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > var acc = { 'sum': 0 };\n    > reduceAsync( arr, acc, fcn, done )\n    3000\n    2500\n    1000\n    6500\n\n    // Limit number of concurrent invocations:\n    > function fcn( acc, value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         acc.sum += value;\n    ...         next( null, acc );\n    ...     }\n    ... };\n    > function done( error, acc ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( acc.sum );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 3000, 2500, 1000 ];\n    > var acc = { 'sum': 0 };\n    > reduceAsync( arr, acc, opts, fcn, done )\n    2500\n    3000\n    1000\n    6500\n\n    // Process concurrently:\n    > function fcn( acc, value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         acc.sum += value;\n    ...         next( null, acc );\n    ...     }\n    ... };\n    > function done( error, acc ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( acc.sum );\n    ... };\n    > var opts = { 'series': false };\n    > var arr = [ 3000, 2500, 1000 ];\n    > var acc = { 'sum': 0 };\n    > reduceAsync( arr, acc, opts, fcn, done )\n    1000\n    2500\n    3000\n    6500\n\n\nreduceAsync.factory( [options,] fcn )\n    Returns a function which applies a function against an accumulator and each\n    element in a collection and returns the accumulated result.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: true.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function fcn( acc, value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         acc.sum += value;\n    ...         next( null, acc );\n    ...     }\n    ... };\n    > var opts = { 'series': false };\n    > var f = reduceAsync.factory( opts, fcn );\n    > function done( error, acc ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( acc.sum );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > var acc = { 'sum': 0 };\n    > f( arr, acc, done )\n    1000\n    2500\n    3000\n    6500\n    > acc = { 'sum': 0 };\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, acc, done )\n    1000\n    1500\n    2000\n    4500\n\n    See Also\n    --------\n    forEachAsync, reduce, reduceRightAsync\n","reduceAsync.factory":"\nreduceAsync.factory( [options,] fcn )\n    Returns a function which applies a function against an accumulator and each\n    element in a collection and returns the accumulated result.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: true.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function fcn( acc, value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         acc.sum += value;\n    ...         next( null, acc );\n    ...     }\n    ... };\n    > var opts = { 'series': false };\n    > var f = reduceAsync.factory( opts, fcn );\n    > function done( error, acc ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( acc.sum );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > var acc = { 'sum': 0 };\n    > f( arr, acc, done )\n    1000\n    2500\n    3000\n    6500\n    > acc = { 'sum': 0 };\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, acc, done )\n    1000\n    1500\n    2000\n    4500\n\n    See Also\n    --------\n    forEachAsync, reduce, reduceRightAsync","reduceRight":"\nreduceRight( arr, initial, reducer[, thisArg] )\n    Applies a function against an accumulator and each element in an array while\n    iterating from right to left and returns the accumulated result.\n\n    When invoked, the reduction function is provided four arguments:\n\n    - accumulator: accumulated value.\n    - value: array element.\n    - index: element index.\n    - arr: input array.\n\n    If provided an empty array, the function returns the initial value.\n\n    When provided an ndarray, the function performs a reduction over the entire\n    input ndarray (i.e., higher-order ndarray dimensions are flattened to a\n    single-dimension).\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject|ndarray\n        Input array.\n\n    initial: any\n        Accumulator value used in the first invocation of the reduction\n        function.\n\n    reducer: Function\n        Function to invoke for each element in the input array.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: any\n        Accumulated result.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.add, 2 );\n    > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > var out = reduceRight( arr, 0.0, f )\n    21.0\n\n    // ndarray:\n    > arr = array( arr, { 'shape': [ 2, 3 ] } );\n    > out = reduceRight( arr, 0.0, f )\n    21.0\n\n    See Also\n    --------\n    forEachRight, mapRight, reduce, reduceRightAsync\n","reduceRightAsync":"\nreduceRightAsync( collection, initial, [options,] reducer, done )\n    Applies a function against an accumulator and each element in a collection\n    and returns the accumulated result, iterating from right to left.\n\n    When invoked, `reducer` is provided a maximum of five arguments:\n\n    - accumulator: accumulated value.\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If\n    `reducer` accepts three arguments, `reducer` is provided:\n\n    - accumulator\n    - value\n    - next\n\n    If `reducer` accepts four arguments, `reducer` is provided:\n\n    - accumulator\n    - value\n    - index\n    - next\n\n    For every other `reducer` signature, `reducer` is provided all five\n    arguments.\n\n    The `next` callback accepts two arguments:\n\n    - error: error argument.\n    - accumulator: accumulated value.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    If provided an empty collection, the function invokes the `done` callback\n    with the `initial` value as the second argument.\n\n    The function does not skip `undefined` elements.\n\n    When processing collection elements concurrently, *beware* of race\n    conditions when updating an accumulator. This is especially true when an\n    accumulator is a primitive (e.g., a number). In general, prefer object\n    accumulators.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    initial: any\n        Accumulator value used in the first invocation of the reduction\n        function.\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: true.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    reducer: Function\n        The function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function fcn( acc, value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         acc.sum += value;\n    ...         next( null, acc );\n    ...     }\n    ... };\n    > function done( error, acc ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( acc.sum );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > var acc = { 'sum': 0 };\n    > reduceRightAsync( arr, acc, fcn, done )\n    3000\n    2500\n    1000\n    6500\n\n    // Limit number of concurrent invocations:\n    > function fcn( acc, value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         acc.sum += value;\n    ...         next( null, acc );\n    ...     }\n    ... };\n    > function done( error, acc ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( acc.sum );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 1000, 2500, 3000 ];\n    > var acc = { 'sum': 0 };\n    > reduceRightAsync( arr, acc, opts, fcn, done )\n    2500\n    3000\n    1000\n    6500\n\n    // Process concurrently:\n    > function fcn( acc, value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         acc.sum += value;\n    ...         next( null, acc );\n    ...     }\n    ... };\n    > function done( error, acc ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( acc.sum );\n    ... };\n    > var opts = { 'series': false };\n    > var arr = [ 1000, 2500, 3000 ];\n    > var acc = { 'sum': 0 };\n    > reduceRightAsync( arr, acc, opts, fcn, done )\n    1000\n    2500\n    3000\n    6500\n\n\nreduceRightAsync.factory( [options,] fcn )\n    Returns a function which applies a function against an accumulator and each\n    element in a collection and returns the accumulated result, iterating from\n    right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: true.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function fcn( acc, value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         acc.sum += value;\n    ...         next( null, acc );\n    ...     }\n    ... };\n    > var opts = { 'series': false };\n    > var f = reduceRightAsync.factory( opts, fcn );\n    > function done( error, acc ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( acc.sum );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > var acc = { 'sum': 0 };\n    > f( arr, acc, done )\n    1000\n    2500\n    3000\n    6500\n    > acc = { 'sum': 0 };\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, acc, done )\n    1000\n    1500\n    2000\n    4500\n\n    See Also\n    --------\n    forEachRightAsync, reduceAsync, reduceRight\n","reduceRightAsync.factory":"\nreduceRightAsync.factory( [options,] fcn )\n    Returns a function which applies a function against an accumulator and each\n    element in a collection and returns the accumulated result, iterating from\n    right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: true.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function fcn( acc, value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         acc.sum += value;\n    ...         next( null, acc );\n    ...     }\n    ... };\n    > var opts = { 'series': false };\n    > var f = reduceRightAsync.factory( opts, fcn );\n    > function done( error, acc ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( acc.sum );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > var acc = { 'sum': 0 };\n    > f( arr, acc, done )\n    1000\n    2500\n    3000\n    6500\n    > acc = { 'sum': 0 };\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, acc, done )\n    1000\n    1500\n    2000\n    4500\n\n    See Also\n    --------\n    forEachRightAsync, reduceAsync, reduceRight","reDurationString":"\nreDurationString()\n    Returns a regular expression to match a duration string.\n\n    A duration string is a string containing a sequence of time units. A time\n    unit is a nonnegative integer followed by a unit identifier. The following\n    unit identifiers are supported:\n\n    - d: days.\n    - h: hours.\n    - m: minutes.\n    - s: seconds.\n    - ms: milliseconds.\n\n    For example, the string `1m3s10ms` is a duration string containing three\n    time units: `1m` (1 minute), `3s` (3 seconds), and `10ms` (10 milliseconds).\n    The string `60m` is a duration string containing a single time unit: `60m`\n    (60 minutes). Time units must be supplied in descending order of magnitude\n    (i.e., days, hours, minutes, seconds, milliseconds).\n\n    Duration strings are case insensitive. For example, the string `1M3S10MS` is\n    equivalent to `1m3s10ms`.\n\n    The regular expression captures the following groups:\n\n    1. The days component.\n    2. The hours component.\n    3. The minutes component.\n    4. The seconds component.\n    5. The milliseconds component.\n\n    Returns\n    -------\n    re: RegExp: Regular expression\n        Regular expression to match a duration string.\n\n    Examples\n    --------\n    > var RE = reDurationString();\n    > var parts = RE.exec( '3d2ms' )\n    [...]\n    > parts = RE.exec( '4h3m20s' )\n    [...]\n\n\nreDurationString.REGEXP\n    Regular expression to match a duration string.\n\n    Examples\n    --------\n    > var bool = reDurationString.REGEXP.test( '3d2ms' )\n    true\n    > bool = reDurationString.REGEXP.test( 'foo' )\n    false\n","reDurationString.REGEXP":"\nreDurationString.REGEXP\n    Regular expression to match a duration string.\n\n    Examples\n    --------\n    > var bool = reDurationString.REGEXP.test( '3d2ms' )\n    true\n    > bool = reDurationString.REGEXP.test( 'foo' )\n    false","reEOL":"\nreEOL( [options] )\n    Regular expression to match a newline character sequence: /\\r?\\n/.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.flags: string (optional)\n        Regular expression flags. Default: ''.\n\n    options.capture: boolean (optional)\n        Boolean indicating whether to create a capture group for the match.\n        Default: false.\n\n    Returns\n    -------\n    regexp: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE_EOL = reEOL();\n    > var bool = RE_EOL.test( '\\n' )\n    true\n    > bool = RE_EOL.test( '\\r\\n' )\n    true\n    > bool = RE_EOL.test( '\\\\r\\\\n' )\n    false\n\nreEOL.REGEXP\n    Regular expression to match a newline character sequence: /\\r?\\n/.\n\n    Examples\n    --------\n    > var bool = reEOL.REGEXP.test( 'abc' )\n    false\n\nreEOL.REGEXP_CAPTURE\n    Regular expression to capture a newline character sequence: /\\r?\\n/.\n\n    Examples\n    --------\n    > var parts = reEOL.REGEXP_CAPTURE.exec( '\\n' )\n    [ '\\n', '\\n' ]\n\n","reEOL.REGEXP":"\nreEOL.REGEXP\n    Regular expression to match a newline character sequence: /\\r?\\n/.\n\n    Examples\n    --------\n    > var bool = reEOL.REGEXP.test( 'abc' )\n    false","reEOL.REGEXP_CAPTURE":"\nreEOL.REGEXP_CAPTURE\n    Regular expression to capture a newline character sequence: /\\r?\\n/.\n\n    Examples\n    --------\n    > var parts = reEOL.REGEXP_CAPTURE.exec( '\\n' )\n    [ '\\n', '\\n' ]","reExtendedLengthPath":"\nreExtendedLengthPath()\n    Returns a regular expression to test if a string is an extended-length path.\n\n    Extended-length paths are Windows paths which begin with `\\\\?\\`.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reExtendedLengthPath();\n    > var path = '\\\\\\\\?\\\\C:\\\\foo\\\\bar';\n    > var bool = RE.test( path )\n    true\n    > path = '\\\\\\\\?\\\\UNC\\\\server\\\\share';\n    > bool = RE.test( path )\n    true\n    > path = 'C:\\\\foo\\\\bar';\n    > bool = RE.test( path )\n    false\n    > path = '/c/foo/bar';\n    > bool = RE.test( path )\n    false\n    > path = '/foo/bar';\n    > bool = RE.test( path )\n    false\n\n\nreExtendedLengthPath.REGEXP\n    Regular expression to test if a string is an extended-length path.\n\n    Examples\n    --------\n    > var bool = reExtendedLengthPath.REGEXP.test( 'C:\\\\foo\\\\bar' )\n    false\n\n","reExtendedLengthPath.REGEXP":"\nreExtendedLengthPath.REGEXP\n    Regular expression to test if a string is an extended-length path.\n\n    Examples\n    --------\n    > var bool = reExtendedLengthPath.REGEXP.test( 'C:\\\\foo\\\\bar' )\n    false","reExtname":"\nreExtname( [platform] )\n    Returns a regular expression to capture a filename extension.\n\n    The regular expression is platform-dependent. If the current process is\n    running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n    `*.REGEXP_POSIX`.\n\n    Parameters\n    ----------\n    platform: string (optional)\n        Path platform (either `posix` or `win32`).\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reExtname()\n    <RegExp>\n    > var RE_POSIX = reExtname( 'posix' );\n    > var ext = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n    '.js'\n    > var RE_WIN32 = reExtname( 'win32' );\n    > ext = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    '.js'\n    > var str = RE.toString();\n    > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n    true\n\n\nreExtname.REGEXP\n    Regular expression to capture a filename extension.\n\n    Examples\n    --------\n    > var RE = reExtname.REGEXP\n    <RegExp>\n\n\nreExtname.REGEXP_POSIX\n    Regular expression to capture a POSIX filename extension.\n\n    Examples\n    --------\n    > var ext = reExtname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n    '.js'\n\n\nreExtname.REGEXP_WIN32\n    Regular expression to capture a Windows filename extension.\n\n    Examples\n    --------\n    > var ext = reExtname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    '.js'\n\n    See Also\n    --------\n    reExtnamePosix, reExtnameWindows, extname\n","reExtname.REGEXP":"\nreExtname.REGEXP\n    Regular expression to capture a filename extension.\n\n    Examples\n    --------\n    > var RE = reExtname.REGEXP\n    <RegExp>","reExtname.REGEXP_POSIX":"\nreExtname.REGEXP_POSIX\n    Regular expression to capture a POSIX filename extension.\n\n    Examples\n    --------\n    > var ext = reExtname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n    '.js'","reExtname.REGEXP_WIN32":"\nreExtname.REGEXP_WIN32\n    Regular expression to capture a Windows filename extension.\n\n    Examples\n    --------\n    > var ext = reExtname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    '.js'\n\n    See Also\n    --------\n    reExtnamePosix, reExtnameWindows, extname","reExtnamePosix":"\nreExtnamePosix\n    Returns a regular expression to capture a POSIX filename extension.\n\n    When executed against dotfile filenames (e.g., `.gitignore`), the regular\n    expression does not capture the basename as a filename extension.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reExtnamePosix();\n    > var ext = RE.exec( '/foo/bar/index.js' )[ 1 ]\n    '.js'\n    > ext = RE.exec( './foo/bar/.gitignore' )[ 1 ]\n    ''\n    > ext = RE.exec( 'foo/file.pdf' )[ 1 ]\n    '.pdf'\n    > ext = RE.exec( '/foo/bar/file' )[ 1 ]\n    ''\n    > ext = RE.exec( 'index.js' )[ 1 ]\n    '.js'\n    > ext = RE.exec( '.' )[ 1 ]\n    ''\n    > ext = RE.exec( './' )[ 1 ]\n    ''\n    > ext = RE.exec( '' )[ 1 ]\n    ''\n\n\nreExtnamePosix.REGEXP\n    Regular expression to capture a POSIX filename extension.\n\n    Examples\n    --------\n    > var ext = reExtnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n    '.js'\n\n    See Also\n    --------\n    reExtname, reExtnameWindows, extname\n","reExtnamePosix.REGEXP":"\nreExtnamePosix.REGEXP\n    Regular expression to capture a POSIX filename extension.\n\n    Examples\n    --------\n    > var ext = reExtnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n    '.js'\n\n    See Also\n    --------\n    reExtname, reExtnameWindows, extname","reExtnameWindows":"\nreExtnameWindows\n    Returns a regular expression to capture a Windows filename extension.\n\n    When executed against dotfile filenames (e.g., `.gitignore`), the regular\n    expression does not capture the basename as a filename extension.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reExtnameWindows();\n    > var ext = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    '.js'\n    > ext = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n    ''\n    > ext = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\n    '.pdf'\n    > ext = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\n    ''\n    > ext = RE.exec( 'beep\\\\boop.' )[ 1 ]\n    '.'\n    > ext = RE.exec( 'index.js' )[ 1 ]\n    '.js'\n    > ext = RE.exec( '' )[ 1 ]\n    ''\n\n\nreExtnameWindows.REGEXP\n    Regular expression to capture a Windows filename extension.\n\n    Examples\n    --------\n    > var ext = reExtnameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    '.js'\n\n    See Also\n    --------\n    reExtname, reExtnamePosix, extname\n","reExtnameWindows.REGEXP":"\nreExtnameWindows.REGEXP\n    Regular expression to capture a Windows filename extension.\n\n    Examples\n    --------\n    > var ext = reExtnameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    '.js'\n\n    See Also\n    --------\n    reExtname, reExtnamePosix, extname","reFilename":"\nreFilename( [platform] )\n    Regular expression to split a filename.\n\n    The regular expression is platform-dependent. If the current process is\n    running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n    `*.REGEXP_POSIX`.\n\n    Parameters\n    ----------\n    platform: string (optional)\n        Path platform (either `posix` or `win32`).\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reFilename()\n    <RegExp>\n    > var RE_POSIX = reFilename( 'posix' );\n    > var parts = RE_POSIX.exec( '/foo/bar/index.js' ).slice()\n    <Array>\n    > var RE_WIN32 = reFilename( 'win32' );\n    > parts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n    <Array>\n    > var str = RE.toString();\n    > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n    true\n\n\nreFilename.REGEXP\n    Regular expression to split a filename.\n\n    Examples\n    --------\n    > var RE = reFilename.REGEXP\n    <RegExp>\n\n\nreFilename.REGEXP_POSIX\n    Regular expression to split a POSIX filename.\n\n    When executed, the regular expression splits a POSIX filename into the\n    following parts:\n\n    - input value\n    - root\n    - dirname\n    - basename\n    - extname\n\n    Examples\n    --------\n    > var f = '/foo/bar/index.js';\n    > var parts = reFilename.REGEXP_POSIX.exec( f ).slice()\n    [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n\n\nreFilename.REGEXP_WIN32\n    Regular expression to split a Windows filename.\n\n    When executed, the regular expression splits a Windows filename into the\n    following parts:\n\n    - input value\n    - device\n    - slash\n    - dirname\n    - basename\n    - extname\n\n    Examples\n    --------\n    > var f = 'C:\\\\foo\\\\bar\\\\index.js';\n    > var parts = reFilename.REGEXP_WIN32.exec( f ).slice()\n    [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n    See Also\n    --------\n    reFilenamePosix, reFilenameWindows\n","reFilename.REGEXP":"\nreFilename.REGEXP\n    Regular expression to split a filename.\n\n    Examples\n    --------\n    > var RE = reFilename.REGEXP\n    <RegExp>","reFilename.REGEXP_POSIX":"\nreFilename.REGEXP_POSIX\n    Regular expression to split a POSIX filename.\n\n    When executed, the regular expression splits a POSIX filename into the\n    following parts:\n\n    - input value\n    - root\n    - dirname\n    - basename\n    - extname\n\n    Examples\n    --------\n    > var f = '/foo/bar/index.js';\n    > var parts = reFilename.REGEXP_POSIX.exec( f ).slice()\n    [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]","reFilename.REGEXP_WIN32":"\nreFilename.REGEXP_WIN32\n    Regular expression to split a Windows filename.\n\n    When executed, the regular expression splits a Windows filename into the\n    following parts:\n\n    - input value\n    - device\n    - slash\n    - dirname\n    - basename\n    - extname\n\n    Examples\n    --------\n    > var f = 'C:\\\\foo\\\\bar\\\\index.js';\n    > var parts = reFilename.REGEXP_WIN32.exec( f ).slice()\n    [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n    See Also\n    --------\n    reFilenamePosix, reFilenameWindows","reFilenamePosix":"\nreFilenamePosix()\n    Returns a regular expression to split a POSIX filename.\n\n    When executed, the regular expression splits a POSIX filename into the\n    following parts:\n\n    - input value\n    - root\n    - dirname\n    - basename\n    - extname\n\n    When executed against dotfile filenames (e.g., `.gitignore`), the regular\n    expression does not capture the basename as a filename extension.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reFilenamePosix();\n    > var parts = RE.exec( '/foo/bar/index.js' ).slice()\n    [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n    > parts = RE.exec( './foo/bar/.gitignore' ).slice()\n    [ './foo/bar/.gitignore', '', './foo/bar/', '.gitignore', '' ]\n    > parts = RE.exec( 'foo/file.pdf' ).slice()\n    [ 'foo/file.pdf', '', 'foo/', 'file.pdf', '.pdf' ]\n    > parts = RE.exec( '/foo/bar/file' ).slice()\n    [ '/foo/bar/file', '/', 'foo/bar/', 'file', '' ]\n    > parts = RE.exec( 'index.js' ).slice()\n    [ 'index.js', '', '', 'index.js', '.js' ]\n    > parts = RE.exec( '.' ).slice()\n    [ '.', '', '', '.', '' ]\n    > parts = RE.exec( './' ).slice()\n    [ './', '', ..., '.', '' ]\n    > parts = RE.exec( '' ).slice()\n    [ '', '', '', '', '' ]\n\n\nreFilenamePosix.REGEXP\n    Regular expression to split a POSIX filename.\n\n    Examples\n    --------\n    > var parts = reFilenamePosix.REGEXP.exec( '/foo/bar/index.js' ).slice()\n    [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n\n    See Also\n    --------\n    reFilename, reFilenameWindows\n","reFilenamePosix.REGEXP":"\nreFilenamePosix.REGEXP\n    Regular expression to split a POSIX filename.\n\n    Examples\n    --------\n    > var parts = reFilenamePosix.REGEXP.exec( '/foo/bar/index.js' ).slice()\n    [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n\n    See Also\n    --------\n    reFilename, reFilenameWindows","reFilenameWindows":"\nreFilenameWindows()\n    Returns a regular expression to split a Windows filename.\n\n    When executed, the regular expression splits a Windows filename into the\n    following parts:\n\n    - input value\n    - device\n    - slash\n    - dirname\n    - basename\n    - extname\n\n    When executed against dotfile filenames (e.g., `.gitignore`), the regular\n    expression does not capture the basename as a filename extension.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reFilenameWindows();\n    > var parts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n    [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n    > parts = RE.exec( '\\\\foo\\\\bar\\\\.gitignore' ).slice()\n    [ '\\\\foo\\\\bar\\\\.gitignore', '', '\\\\', 'foo\\\\bar\\\\', '.gitignore', '' ]\n    > parts = RE.exec( 'foo\\\\file.pdf' ).slice()\n    [ 'foo\\\\file.pdf', '', '', 'foo\\\\', 'file.pdf', '.pdf' ]\n    > parts = RE.exec( '\\\\foo\\\\bar\\\\file' ).slice()\n    [ '\\\\foo\\\\bar\\\\file', '', '\\\\', 'foo\\\\bar\\\\', 'file', '' ]\n    > parts = RE.exec( 'index.js' ).slice()\n    [ 'index.js', '', '', '', 'index.js', '.js' ]\n    > parts = RE.exec( '.' ).slice()\n    [ '.', '', '', '', '.', '' ]\n    > parts = RE.exec( './' ).slice()\n    [ './', '', ..., '.', '' ]\n    > parts = RE.exec( '' ).slice()\n    [ '', '', '', '', '', '' ]\n\n\nreFilenameWindows.REGEXP\n    Regular expression to split a Windows filename.\n\n    Examples\n    --------\n    > var parts = reFilenameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n    [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n    See Also\n    --------\n    reFilename, reFilenamePosix","reFilenameWindows.REGEXP":"\nreFilenameWindows.REGEXP\n    Regular expression to split a Windows filename.\n\n    Examples\n    --------\n    > var parts = reFilenameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n    [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n    See Also\n    --------\n    reFilename, reFilenamePosix","reFromString":"\nreFromString( str )\n    Parses a regular expression string and returns a new regular expression.\n\n    Provided strings should be properly escaped.\n\n    If unable to parse a string as a regular expression, the function returns\n    `null`.\n\n    Parameters\n    ----------\n    str: string\n        Regular expression string.\n\n    Returns\n    -------\n    out: RegExp|null\n        Regular expression or null.\n\n    Examples\n    --------\n    > var re = reFromString( '/beep/' )\n    /beep/\n    > re = reFromString( '/beep' )\n    null\n\n","reFunctionName":"\nreFunctionName()\n    Return a regular expression to capture a function name.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE_FUNCTION_NAME = reFunctionName();\n    > function beep() { return 'boop'; };\n    > var name = RE_FUNCTION_NAME.exec( beep.toString() )[ 1 ]\n    'beep'\n    > name = RE_FUNCTION_NAME.exec( function () {} )[ 1 ]\n    ''\n\n\nreFunctionName.REGEXP\n    Regular expression to capture a function name.\n\n    Examples\n    --------\n    > var str = reFunctionName.REGEXP.exec( Math.sqrt.toString() )[ 1 ]\n    'sqrt'\n\n    See Also\n    --------\n    functionName\n","reFunctionName.REGEXP":"\nreFunctionName.REGEXP\n    Regular expression to capture a function name.\n\n    Examples\n    --------\n    > var str = reFunctionName.REGEXP.exec( Math.sqrt.toString() )[ 1 ]\n    'sqrt'\n\n    See Also\n    --------\n    functionName","regexp2json":"\nregexp2json( re )\n    Returns a JSON representation of a regular expression.\n\n    Parameters\n    ----------\n    re: RegExp\n        Regular expression to serialize.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n        \n    out.type: string\n        Value type. The assigned value is always 'RegExp'.\n        \n    out.pattern: string\n        Regular expression pattern.\n        \n    out.flags: string\n        Regular expression flags.\n\n    Examples\n    --------\n    > var json = regexp2json( /ab+c/ )\n    {...}\n\n    See Also\n    --------\n    reviveRegExp    \n","reim":"\nreim( z )\n    Returns the real and imaginary components of a double-precision complex\n    floating-point number.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Float64Array\n        Array containing the real and imaginary components, respectively.\n\n    Examples\n    --------\n    > var z = new Complex128( 5.0, 3.0 );\n    > var out = reim( z )\n    <Float64Array>[ 5.0, 3.0 ]\n\n    See Also\n    --------\n    imag, real\n","reimf":"\nreimf( z )\n    Returns the real and imaginary components of a single-precision complex\n    floating-point number.\n\n    Parameters\n    ----------\n    z: Complex64\n        Complex number.\n\n    Returns\n    -------\n    out: Float32Array\n        Array containing the real and imaginary components, respectively.\n\n    Examples\n    --------\n    > var z = new Complex64( 5.0, 3.0 );\n    > var out = reimf( z )\n    <Float32Array>[ 5.0, 3.0 ]\n\n    See Also\n    --------\n    imagf, realf, reim\n","rejectArguments":"\nrejectArguments( fcn, predicate[, thisArg] )\n    Returns a function that applies arguments to a provided function according\n    to a predicate function.\n\n    Only those arguments in which the predicate function returns a falsy value\n    are applied to a provided function.\n\n    The predicate function is provided the following arguments:\n\n    - value: argument value.\n    - index: argument index.\n\n    Parameters\n    ----------\n    fcn: Function\n        Input function.\n\n    predicate: Function\n        Predicate function.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Function\n        Function wrapper.\n\n    Examples\n    --------\n    > function foo( a, b ) { return [ a, b ]; };\n    > function predicate( v ) { return ( v === 2 ); };\n    > var bar = rejectArguments( foo, predicate );\n    > var out = bar( 1, 2, 3 )\n    [ 1, 3 ]\n\n    See Also\n    --------\n    filterArguments, maskArguments\n","removeFirst":"\nremoveFirst( str[, n][, options] )\n    Removes the first character(s) of a `string`.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer (optional)\n        Number of characters to remove. Default: 1.\n\n    options: Object (optional)\n        Options.\n\n    options.mode: string (optional)\n        Type of characters to return. The following modes are supported:\n\n        - grapheme: grapheme clusters. Appropriate for strings containing visual\n          characters which can span multiple Unicode code points (e.g., emoji).\n        - code_point: Unicode code points. Appropriate for strings containing\n          visual characters which are comprised of more than one Unicode code\n          unit (e.g., ideographic symbols and punctuation and mathematical\n          alphanumerics).\n        - code_unit': UTF-16 code units. Appropriate for strings containing\n          visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n          common characters, such as those from the Latin, Greek, and Cyrillic\n          alphabets).\n\n        Default: 'grapheme'.\n\n    Returns\n    -------\n    out: string\n        Updated string.\n\n    Examples\n    --------\n    > var out = removeFirst( 'beep' )\n    'eep'\n    > out = removeFirst( 'Boop' )\n    'oop'\n    > out = removeFirst( 'foo bar', 4 )\n    'bar'\n\n    See Also\n    --------\n    removeLast\n","removeLast":"\nremoveLast( str[, n][, options] )\n    Removes the last character(s) of a `string`.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer (optional)\n        Number of characters to remove. Default: 1.\n\n    options: Object (optional)\n        Options.\n\n    options.mode: string (optional)\n        Type of characters to remove. The following modes are supported:\n\n        - grapheme: grapheme clusters. Appropriate for strings containing visual\n          characters which can span multiple Unicode code points (e.g., emoji).\n        - code_point: Unicode code points. Appropriate for strings containing\n          visual characters which are comprised of more than one Unicode code\n          unit (e.g., ideographic symbols and punctuation and mathematical\n          alphanumerics).\n        - code_unit': UTF-16 code units. Appropriate for strings containing\n          visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n          common characters, such as those from the Latin, Greek, and Cyrillic\n          alphabets).\n\n        Default: 'grapheme'.\n\n    Returns\n    -------\n    out: string\n        Updated string.\n\n    Examples\n    --------\n    > var out = removeLast( 'beep' )\n    'bee'\n    > out = removeLast( 'Boop' )\n    'Boo'\n    > out = removeLast( 'foo bar', 4 )\n    'foo'\n\n    See Also\n    --------\n    removeFirst\n","removePunctuation":"\nremovePunctuation( str )\n    Removes punctuation characters from a `string`.\n\n    The function removes the following characters:\n\n    - Apostrophe: `\n    - Braces : { }\n    - Brackets: [ ]\n    - Colon: :\n    - Comma: ,\n    - Exclamation Mark: !\n    - Fraction Slash: /\n    - Guillemets: < >\n    - Parentheses: ( )\n    - Period: .\n    - Semicolon: ;\n    - Tilde: ~\n    - Vertical Bar: |\n    - Question Mark: ?\n    - Quotation Marks: ' \"\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        String with punctuation characters removed.\n\n    Examples\n    --------\n    > var str = 'Sun Tzu said: \"A leader leads by example not by force.\"';\n    > var out = removePunctuation( str )\n    'Sun Tzu said A leader leads by example not by force'\n\n    > str = 'This function removes these characters: `{}[]:,!/<>().;~|?\\'\"';\n    > out = removePunctuation( str )\n    'This function removes these characters '\n\n","removeUTF8BOM":"\nremoveUTF8BOM( str )\n    Removes a UTF-8 byte order mark (BOM) from the beginning of a `string`.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        String with BOM removed.\n\n    Examples\n    --------\n    > var out = removeUTF8BOM( '\\ufeffbeep' )\n    'beep'\n\n","removeWords":"\nremoveWords( str, words[, ignoreCase] )\n    Removes all occurrences of the given words from a `string`.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    words: Array<string>\n        Array of words to be removed.\n\n    ignoreCase: boolean (optional)\n        Boolean indicating whether to perform a case-insensitive operation.\n        Default: `false`.\n\n    Returns\n    -------\n    out: string\n        String with words removed.\n\n    Examples\n    --------\n    > var out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ] )\n    'beep  Foo bar'\n\n    // Case-insensitive:\n    > out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ], true )\n    'beep   bar'\n\n","rename":"\nrename( oldPath, newPath, clbk )\n    Asynchronously renames a file.\n\n    The old path can specify a directory. In this case, the new path must either\n    not exist, or it must specify an empty directory.\n\n    The old pathname should not name an ancestor directory of the new pathname.\n\n    If the old path points to the pathname of a file that is not a directory,\n    the new path should not point to the pathname of a directory.\n\n    Write access permission is required for both the directory containing the\n    old path and the directory containing the new path.\n\n    If the link named by the new path exists, the new path is removed and the\n    old path is renamed to the new path. The link named by the new path will\n    remain visible to other threads throughout the renaming operation and refer\n    to either the file referred to by the new path or to the file referred to by\n    the old path before the operation began.\n\n    If the old path and the new path resolve to either the same existing\n    directory entry or to different directory entries for the same existing\n    file, no action is taken, and no error is returned.\n\n    If the old path points to a pathname of a symbolic link, the symbolic link\n    is renamed. If the new path points to a pathname of a symbolic link, the\n    symbolic link is removed.\n\n    If a link named by the new path exists and the file's link count becomes 0\n    when it is removed and no process has the file open, the space occupied by\n    the file is freed and the file is no longer accessible. If one or more\n    processes have the file open when the last link is removed, the link is\n    removed before the function returns, but the removal of file contents is\n    postponed until all references to the file are closed.\n\n    Parameters\n    ----------\n    oldPath: string|Buffer\n        Old path.\n\n    newPath: string|Buffer\n        New path.\n\n    clbk: Function\n        Callback to invoke upon renaming a file.\n\n    Examples\n    --------\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     }\n    ... };\n    > rename( './beep/boop.txt', './beep/foo.txt', done );\n\n\nrename.sync( oldPath, newPath )\n    Synchronously renames a file.\n\n    Parameters\n    ----------\n    oldPath: string|Buffer\n        Old path.\n\n    newPath: string|Buffer\n        New path.\n\n    Returns\n    -------\n    err: Error|null\n        Error object or null.\n\n    Examples\n    --------\n    > var err = rename.sync( './beep/boop.txt', './beep/foo.txt' );\n\n    See Also\n    --------\n    exists, readFile, writeFile, unlink\n","rename.sync":"\nrename.sync( oldPath, newPath )\n    Synchronously renames a file.\n\n    Parameters\n    ----------\n    oldPath: string|Buffer\n        Old path.\n\n    newPath: string|Buffer\n        New path.\n\n    Returns\n    -------\n    err: Error|null\n        Error object or null.\n\n    Examples\n    --------\n    > var err = rename.sync( './beep/boop.txt', './beep/foo.txt' );\n\n    See Also\n    --------\n    exists, readFile, writeFile, unlink","reNativeFunction":"\nreNativeFunction()\n    Returns a regular expression to match a native function.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reNativeFunction();\n    > var bool = RE.test( Date.toString() )\n    true\n    > bool = RE.test( (function noop() {}).toString() )\n    false\n\n\nreNativeFunction.REGEXP\n    Regular expression to match a native function.\n\n    Examples\n    --------\n    > var bool = reNativeFunction.REGEXP.test( Date.toString() )\n    true\n    > bool = reNativeFunction.REGEXP.test( (function noop() {}).toString() )\n    false\n\n    See Also\n    --------\n    reFunctionName, functionName\n","reNativeFunction.REGEXP":"\nreNativeFunction.REGEXP\n    Regular expression to match a native function.\n\n    Examples\n    --------\n    > var bool = reNativeFunction.REGEXP.test( Date.toString() )\n    true\n    > bool = reNativeFunction.REGEXP.test( (function noop() {}).toString() )\n    false\n\n    See Also\n    --------\n    reFunctionName, functionName","reorderArguments":"\nreorderArguments( fcn, indices[, thisArg] )\n    Returns a function that invokes a provided function with reordered\n    arguments.\n\n    Parameters\n    ----------\n    fcn: Function\n        Input function.\n\n    indices: Array<integer>\n        Argument indices.\n\n    thisArg: any (optional)\n        Function context.\n\n    Returns\n    -------\n    out: Function\n        Function with reordered arguments.\n\n    Examples\n    --------\n    > function foo( a, b, c ) { return [ a, b, c ]; };\n    > var bar = reorderArguments( foo, [ 2, 0, 1 ] );\n    > var out = bar( 1, 2, 3 )\n    [ 3, 1, 2 ]\n\n    See Also\n    --------\n    maskArguments, reverseArguments\n","repeat":"\nrepeat( str, n )\n    Repeats a string `n` times and returns the concatenated result.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of repetitions.\n\n    Returns\n    -------\n    out: string\n        Repeated string.\n\n    Examples\n    --------\n    > var out = repeat( 'a', 5 )\n    'aaaaa'\n    > out = repeat( '', 100 )\n    ''\n    > out = repeat( 'beep', 0 )\n    ''\n\n    See Also\n    --------\n    pad\n","replace":"\nreplace( str, search, newval )\n    Replaces search occurrences with a replacement string.\n\n    When provided a string as the search value, the function replaces *all*\n    occurrences. To remove only the first match, use a regular expression.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string|RegExp\n        Search expression.\n\n    newval: string|Function\n        Replacement value or function.\n\n    Returns\n    -------\n    out: string\n        String containing replacement(s).\n\n    Examples\n    --------\n    // Standard usage:\n    > var out = replace( 'beep', 'e', 'o' )\n    'boop'\n\n    // Replacer function:\n    > function replacer( match, p1 ) { return '/'+p1+'/'; };\n    > var str = 'Oranges and lemons';\n    > out = replace( str, /([^\\s]+)/gi, replacer )\n    '/Oranges/ /and/ /lemons/'\n\n    // Replace only first match:\n    > out = replace( 'beep', /e/, 'o' )\n    'boep'\n\n","replaceBefore":"\nreplaceBefore( str, search, replacement )\n    Replaces the substring before the first occurrence of a specified search\n    string. \n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search string.\n    \n    replacement: string\n        Replacement string.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var str = 'beep boop';\n    > var out = replaceBefore( str, ' ', 'foo' )\n    'foo boop'\n    > out = replaceBefore( str, 'o', 'foo' )\n    'foooop'\n\n","reRegExp":"\nreRegExp()\n    Returns a regular expression to parse a regular expression string.\n\n    Regular expression strings should be escaped.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reRegExp();\n    > var bool = RE.test( '/^beep$/' )\n    true\n    > bool = RE.test( '/boop' )\n    false\n\n    // Escape regular expression strings:\n    > bool = RE.test( '/^\\/([^\\/]+)\\/(.*)$/' )\n    false\n    > bool = RE.test( '/^\\\\/([^\\\\/]+)\\\\/(.*)$/' )\n    true\n\n\nreRegExp.REGEXP\n    Regular expression to parse a regular expression string.\n\n    Examples\n    --------\n    > var bool = reRegExp.REGEXP.test( '/^beep$/' )\n    true\n    > bool = reRegExp.REGEXP.test( '/boop' )\n    false\n\n    See Also\n    --------\n    reFromString\n","reRegExp.REGEXP":"\nreRegExp.REGEXP\n    Regular expression to parse a regular expression string.\n\n    Examples\n    --------\n    > var bool = reRegExp.REGEXP.test( '/^beep$/' )\n    true\n    > bool = reRegExp.REGEXP.test( '/boop' )\n    false\n\n    See Also\n    --------\n    reFromString","rescape":"\nrescape( str )\n    Escapes a regular expression string.\n\n    Parameters\n    ----------\n    str: string\n        Regular expression string.\n\n    Returns\n    -------\n    out: string\n        Escaped string.\n\n    Examples\n    --------\n    > var str = rescape( '[A-Z]*' )\n    '\\\\[A\\\\-Z\\\\]\\\\*'\n\n","reSemVer":"\nreSemVer()\n    Returns a regular expression to match a semantic version string.\n\n    Returns\n    -------\n    out: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE_SEMVER = reSemVer()\n    <RegExp>\n    > var bool = RE_SEMVER.test( '1.0.0' )\n    true\n    > bool = RE_SEMVER.test( '1.0.0-alpha.1' )\n    true\n    > bool = RE_SEMVER.test( 'abc' )\n    false\n    > bool = RE_SEMVER.test( '1.0.0-alpha.1+build.1' )\n    true\n\n\nreSemVer.REGEXP\n    Regular expression to match a semantic version string.\n\n    Examples\n    --------\n    > var bool = reSemVer.REGEXP.test( '1.0.0' )\n    true\n    > bool = reSemVer.REGEXP.test( '-1.0.0-alpha.1' )\n    false\n\n\n    See Also\n    --------\n    isSemVer","reSemVer.REGEXP":"\nreSemVer.REGEXP\n    Regular expression to match a semantic version string.\n\n    Examples\n    --------\n    > var bool = reSemVer.REGEXP.test( '1.0.0' )\n    true\n    > bool = reSemVer.REGEXP.test( '-1.0.0-alpha.1' )\n    false\n\n\n    See Also\n    --------\n    isSemVer","resolveParentPath":"\nresolveParentPath( path[, options], clbk )\n    Asynchronously resolves a path by walking parent directories.\n\n    If unable to resolve a path, the function returns `null` as the path result.\n\n    Parameters\n    ----------\n    path: string\n        Path to resolve.\n\n    options: Object (optional)\n        Options.\n\n    options.dir: string (optional)\n        Base directory from which to search. Default: current working directory.\n\n    clbk: Function\n        Callback to invoke after resolving a path.\n\n    Examples\n    --------\n    > function onPath( error, path ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     } else {\n    ...         console.log( path );\n    ...     }\n    ... };\n    > resolveParentPath( 'package.json', onPath );\n\n\nresolveParentPath.sync( path[, options] )\n    Synchronously resolves a path by walking parent directories.\n\n    Parameters\n    ----------\n    path: string\n        Path to resolve.\n\n    options: Object (optional)\n        Options.\n\n    options.dir: string (optional)\n        Base directory from which to search. Default: current working directory.\n\n    Returns\n    -------\n    out: string|null\n        Resolved path.\n\n    Examples\n    --------\n    > var out = resolveParentPath.sync( 'package.json' );\n\n    See Also\n    --------\n    resolveParentPathBy\n","resolveParentPath.sync":"\nresolveParentPath.sync( path[, options] )\n    Synchronously resolves a path by walking parent directories.\n\n    Parameters\n    ----------\n    path: string\n        Path to resolve.\n\n    options: Object (optional)\n        Options.\n\n    options.dir: string (optional)\n        Base directory from which to search. Default: current working directory.\n\n    Returns\n    -------\n    out: string|null\n        Resolved path.\n\n    Examples\n    --------\n    > var out = resolveParentPath.sync( 'package.json' );\n\n    See Also\n    --------\n    resolveParentPathBy","resolveParentPathBy":"\nresolveParentPathBy( path[, options], predicate, clbk )\n    Asynchronously resolves a path according to a predicate function by walking\n    parent directories.\n\n    When invoked, the predicate function is provided two arguments:\n\n    - path: a resolved path.\n    - next: a callback to be invoked after processing a resolved path.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - result: test result.\n\n    If a provided predicate function calls the `next` callback with a truthy\n    `error` argument, the function suspends execution and immediately calls the\n    `done` callback for subsequent `error` handling.\n\n    The function immediately returns upon encountering a non-falsy `result`\n    value and calls the `done` callback with `null` as the first argument and\n    the resolved path as the second argument.\n\n    If unable to resolve a path, the function returns `null` as the path result.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Parameters\n    ----------\n    path: string\n        Path to resolve.\n\n    options: Object (optional)\n        Options.\n\n    options.dir: string (optional)\n        Base directory from which to search. Default: current working directory.\n\n    predicate: Function\n        The test function to invoke for each resolved path.\n\n    clbk: Function\n        Callback to invoke after resolving a path.\n\n    Examples\n    --------\n    > function predicate( path, next ) {\n    ...     setTimeout( onTimeout, path );\n    ...     function onTimeout() {\n    ...         console.log( path );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function onPath( error, path ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     } else {\n    ...         console.log( path );\n    ...     }\n    ... };\n    > resolveParentPathBy( 'package.json', predicate, onPath );\n\n\nresolveParentPathBy.sync( path[, options], predicate )\n    Synchronously resolves a path according to a predicate function by walking\n    parent directories.\n\n    The predicate function is provided one argument:\n\n    - path: a resolved path.\n\n    The function immediately returns upon encountering a truthy return value.\n\n    If unable to resolve a path, the function returns `null` as the path result.\n\n    Parameters\n    ----------\n    path: string\n        Path to resolve.\n\n    options: Object (optional)\n        Options.\n\n    options.dir: string (optional)\n        Base directory from which to search. Default: current working directory.\n\n    predicate: Function\n        The test function to invoke for each resolved path.\n\n    Returns\n    -------\n    out: string|null\n        Resolved path.\n\n    Examples\n    --------\n    > function predicate() { return false; };\n    > var out = resolveParentPathBy.sync( 'package.json', predicate );\n\n    See Also\n    --------\n    resolveParentPath\n","resolveParentPathBy.sync":"\nresolveParentPathBy.sync( path[, options], predicate )\n    Synchronously resolves a path according to a predicate function by walking\n    parent directories.\n\n    The predicate function is provided one argument:\n\n    - path: a resolved path.\n\n    The function immediately returns upon encountering a truthy return value.\n\n    If unable to resolve a path, the function returns `null` as the path result.\n\n    Parameters\n    ----------\n    path: string\n        Path to resolve.\n\n    options: Object (optional)\n        Options.\n\n    options.dir: string (optional)\n        Base directory from which to search. Default: current working directory.\n\n    predicate: Function\n        The test function to invoke for each resolved path.\n\n    Returns\n    -------\n    out: string|null\n        Resolved path.\n\n    Examples\n    --------\n    > function predicate() { return false; };\n    > var out = resolveParentPathBy.sync( 'package.json', predicate );\n\n    See Also\n    --------\n    resolveParentPath","reUncPath":"\nreUncPath()\n    Return a regular expression to parse a UNC path.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reUncPath();\n    > var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\n    > var bool = RE.test( path )\n    true\n    > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\n    > bool = RE.test( path )\n    true\n    > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a';\n    > bool = RE.test( path )\n    true\n    > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz';\n    > bool = RE.test( path )\n    true\n    > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar';\n    > bool = RE.test( path )\n    true\n    > path = '\\\\\\\\server\\\\share\\\\foo';\n    > bool = RE.test( path )\n    true\n    > path = '\\\\\\\\server\\\\share';\n    > bool = RE.test( path )\n    true\n    > path = '\\\\\\\\server\\\\\\\\share';\n    > bool = RE.test( path )\n    false\n    > path = '\\\\\\\\\\\\\\\\server\\\\share';\n    > bool = RE.test( path )\n    false\n    > path = 'beep boop \\\\\\\\server\\\\share';\n    > bool = RE.test( path )\n    false\n    > path = '\\\\\\\\server';\n    > bool = RE.test( path )\n    false\n    > path = '\\\\';\n    > bool = RE.test( path )\n    false\n    > path = '';\n    > bool = RE.test( path )\n    false\n    > path = '\\\\\\\\server\\\\share\\\\';\n    > bool = RE.test( path )\n    false\n    > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:';\n    > bool = RE.test( path )\n    false\n    > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:';\n    > bool = RE.test( path )\n    false\n    > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::';\n    > bool = RE.test( path )\n    false\n    > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b:c';\n    > bool = RE.test( path )\n    false\n    > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\';\n    > bool = RE.test( path )\n    false\n    > path = '//server/share';\n    > bool = RE.test( path )\n    false\n    > path = '/foo/bar';\n    > bool = RE.test( path )\n    false\n    > path = 'foo/bar';\n    > bool = RE.test( path )\n    false\n    > path = './foo/bar';\n    > bool = RE.test( path )\n    false\n    > path = '/foo/../bar';\n    > bool = RE.test( path )\n    false\n\n\nreUncPath.REGEXP\n    Regular expression to parse a UNC path.\n\n    Examples\n    --------\n    > var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\n    > var bool = reUncPath.REGEXP.test( path )\n    true\n    > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\n    > bool = reUncPath.REGEXP.test( path )\n    true\n\n    See Also\n    --------\n    isUNCPath\n","reUncPath.REGEXP":"\nreUncPath.REGEXP\n    Regular expression to parse a UNC path.\n\n    Examples\n    --------\n    > var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\n    > var bool = reUncPath.REGEXP.test( path )\n    true\n    > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\n    > bool = reUncPath.REGEXP.test( path )\n    true\n\n    See Also\n    --------\n    isUNCPath","reUtf16SurrogatePair":"\nreUtf16SurrogatePair()\n    Returns a regular expression to match a UTF-16 surrogate pair.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reUtf16SurrogatePair();\n    > var bool = RE.test( 'abc\\uD800\\uDC00def' )\n    true\n    > bool = RE.test( 'abcdef' )\n    false\n\n\nreUtf16SurrogatePair.REGEXP\n    Regular expression to match a UTF-16 surrogate pair.\n\n    Examples\n    --------\n    > var RE = reUtf16SurrogatePair.REGEXP;\n    > var bool = RE.test( 'abc\\uD800\\uDC00def' )\n    true\n    > bool = RE.test( 'abcdef' )\n    false\n\n    See Also\n    --------\n    reUtf16UnpairedSurrogate","reUtf16SurrogatePair.REGEXP":"\nreUtf16SurrogatePair.REGEXP\n    Regular expression to match a UTF-16 surrogate pair.\n\n    Examples\n    --------\n    > var RE = reUtf16SurrogatePair.REGEXP;\n    > var bool = RE.test( 'abc\\uD800\\uDC00def' )\n    true\n    > bool = RE.test( 'abcdef' )\n    false\n\n    See Also\n    --------\n    reUtf16UnpairedSurrogate","reUtf16UnpairedSurrogate":"\nreUtf16UnpairedSurrogate()\n    Returns a regular expression to match an unpaired UTF-16 surrogate.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reUtf16UnpairedSurrogate();\n    > var bool = RE.test( 'abc' )\n    false\n    > bool = RE.test( '\\uD800' )\n    true\n\n\nreUtf16UnpairedSurrogate.REGEXP\n    Regular expression to match an unpaired UTF-16 surrogate.\n\n    Examples\n    --------\n    > var RE = reUtf16UnpairedSurrogate.REGEXP;\n    > var bool = RE.test( 'abc' )\n    false\n    > bool = RE.test( '\\uD800' )\n    true\n\n    See Also\n    --------\n    reUtf16SurrogatePair","reUtf16UnpairedSurrogate.REGEXP":"\nreUtf16UnpairedSurrogate.REGEXP\n    Regular expression to match an unpaired UTF-16 surrogate.\n\n    Examples\n    --------\n    > var RE = reUtf16UnpairedSurrogate.REGEXP;\n    > var bool = RE.test( 'abc' )\n    false\n    > bool = RE.test( '\\uD800' )\n    true\n\n    See Also\n    --------\n    reUtf16SurrogatePair","reverseArguments":"\nreverseArguments( fcn[, thisArg] )\n    Returns a function that invokes a provided function with arguments in\n    reverse order.\n\n    Parameters\n    ----------\n    fcn: Function\n        Input function.\n\n    thisArg: any (optional)\n        Function context.\n\n    Returns\n    -------\n    out: Function\n        Function with reversed arguments.\n\n    Examples\n    --------\n    > function foo( a, b, c ) { return [ a, b, c ]; };\n    > var bar = reverseArguments( foo );\n    > var out = bar( 1, 2, 3 )\n    [ 3, 2, 1 ]\n\n    See Also\n    --------\n    maskArguments, reorderArguments\n","reverseString":"\nreverseString( str[, options] )\n    Reverses a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    options: Object (optional)\n        Options.\n\n    options.mode: string (optional)\n        Type of characters to reverse. The following modes are supported:\n\n        - grapheme: grapheme clusters. Appropriate for strings containing visual\n          characters which can span multiple Unicode code points (e.g., emoji).\n        - code_point: Unicode code points. Appropriate for strings containing\n          visual characters which are comprised of more than one Unicode code\n          unit (e.g., ideographic symbols and punctuation and mathematical\n          alphanumerics).\n        - code_unit': UTF-16 code units. Appropriate for strings containing\n          visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n          common characters, such as those from the Latin, Greek, and Cyrillic\n          alphabets).\n\n        Default: 'grapheme'.\n\n    Returns\n    -------\n    out: string\n        Reversed string.\n\n    Examples\n    --------\n    > var out = reverseString( 'foo' )\n    'oof'\n    > out = reverseString( 'abcdef' )\n    'fedcba'\n\n","reviveBasePRNG":"\nreviveBasePRNG( key, value )\n    Revives a JSON-serialized pseudorandom number generator (PRNG).\n\n    Parameters\n    ----------\n    key: string\n        Key.\n\n    value: any\n        Value.\n\n    Returns\n    -------\n    out: any\n        Value or PRNG.\n\n    Examples\n    --------\n    > var str = JSON.stringify( base.random.mt19937 );\n    > var r = parseJSON( str, reviveBasePRNG )\n    <Function>\n\n","reviveBuffer":"\nreviveBuffer( key, value )\n    Revives a JSON-serialized Buffer.\n\n    The serialization format for a Buffer is an object having the following\n    fields:\n\n    - type: value type (Buffer).\n    - data: buffer data as an array of integers.\n\n    Parameters\n    ----------\n    key: string\n        Key.\n\n    value: any\n        Value.\n\n    Returns\n    -------\n    out: any\n        Value or Buffer.\n\n    Examples\n    --------\n    > var str = '{\"type\":\"Buffer\",\"data\":[5,3]}';\n    > var buf = parseJSON( str, reviveBuffer )\n    <Buffer>[ 5, 3 ]\n\n    See Also\n    --------\n    buffer2json\n","reviveComplex":"\nreviveComplex( key, value )\n    Revives a JSON-serialized complex number.\n\n    The serialization format for complex numbers is an object having the\n    following fields:\n\n    - type: complex number type (e.g., \"Complex128\", \"Complex64\").\n    - re: real component (number).\n    - im: imaginary component (number).\n\n    Parameters\n    ----------\n    key: string\n        Key.\n\n    value: any\n        Value.\n\n    Returns\n    -------\n    out: any\n        Value or complex number.\n\n    Examples\n    --------\n    > var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\n    > var z = parseJSON( str, reviveComplex )\n    <Complex128>\n\n    See Also\n    --------\n    Complex128, Complex64, reviveComplex128, reviveComplex64\n","reviveComplex64":"\nreviveComplex64( key, value )\n    Revives a JSON-serialized 64-bit complex number.\n\n    Parameters\n    ----------\n    key: string\n        Key.\n\n    value: any\n        Value.\n\n    Returns\n    -------\n    out: any\n        Value or complex number.\n\n    Examples\n    --------\n    > var str = '{\"type\":\"Complex64\",\"re\":5,\"im\":3}';\n    > var z = parseJSON( str, reviveComplex64 )\n    <Complex64>\n\n    See Also\n    --------\n    Complex64, reviveComplex128, reviveComplex\n","reviveComplex128":"\nreviveComplex128( key, value )\n    Revives a JSON-serialized 128-bit complex number.\n\n    Parameters\n    ----------\n    key: string\n        Key.\n\n    value: any\n        Value.\n\n    Returns\n    -------\n    out: any\n        Value or complex number.\n\n    Examples\n    --------\n    > var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\n    > var z = parseJSON( str, reviveComplex128 )\n    <Complex128>\n\n    See Also\n    --------\n    Complex128, reviveComplex64, reviveComplex\n","reviveError":"\nreviveError( key, value )\n    Revives a JSON-serialized error object.\n\n    The following built-in error types are supported:\n\n    - Error\n    - URIError\n    - ReferenceError\n    - SyntaxError\n    - RangeError\n    - EvalError\n    - TypeError\n\n    Parameters\n    ----------\n    key: string\n        Key.\n\n    value: any\n        Value.\n\n    Returns\n    -------\n    out: any\n        Value or error object.\n\n    Examples\n    --------\n    > var str = '{\"type\":\"TypeError\",\"message\":\"beep\"}';\n    > var err = JSON.parse( str, reviveError )\n    <TypeError>\n\n    See Also\n    --------\n    error2json\n","reviveRegExp":"\nreviveRegExp( key, value )\n    Revives a JSON-serialized regular expression.\n\n    The serialization format for a regular expression is an object having the\n    following fields:\n\n    - type: value type (RegExp).\n    - pattern: regular expression pattern.\n    - flags: regular expression flags.\n\n    Parameters\n    ----------\n    key: string\n        Key.\n\n    value: any\n        Value.\n\n    Returns\n    -------\n    out: any\n        Value or regular expression.\n\n    Examples\n    --------\n    > var str = '{\"type\":\"RegExp\",\"pattern\":\"ab+c\",\"flags\":\"\"}';\n    > var v = parseJSON( str, reviveRegExp )\n    <RegExp>\n\n    See Also\n    --------\n    regexp2json","reviveTypedArray":"\nreviveTypedArray( key, value )\n    Revives a JSON-serialized typed array.\n\n    The serialization format for typed array is an object having the following\n    fields:\n\n    - type: typed array type (e.g., \"Float64Array\", \"Int8Array\").\n    - data: typed array data as an array of numbers.\n\n    Parameters\n    ----------\n    key: string\n        Key.\n\n    value: any\n        Value.\n\n    Returns\n    -------\n    out: any\n        Value or typed array.\n\n    Examples\n    --------\n    > var str = '{\"type\":\"Float64Array\",\"data\":[5,3]}';\n    > var arr = parseJSON( str, reviveTypedArray )\n    <Float64Array>[ 5.0, 3.0 ]\n\n    See Also\n    --------\n    typedarray2json\n","reWhitespace":"\nreWhitespace( [options] )\n    Returns a regular expression to match a white space character.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.flags: string (optional)\n        Regular expression flags. Default: ''.\n\n    options.capture: boolean (optional)\n        Boolean indicating whether to wrap a regular expression matching a white\n        space character with a capture group. Default: false.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reWhitespace();\n    > var bool = RE.test( '\\n' )\n    true\n    > bool = RE.test( ' ' )\n    true\n    > bool = RE.test( 'a' )\n    false\n\n\nreWhitespace.REGEXP\n    Regular expression to match a white space character.\n\n    Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n    characters in the Unicode 9.0 character database.\n\n    Matches one related white space character without the Unicode character\n    property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n    of Unicode 3.2).\n\n    Examples\n    --------\n    > var RE = reWhitespace.REGEXP;\n    > var bool = RE.test( '\\n' )\n    true\n    > bool = RE.test( ' ' )\n    true\n    > bool = RE.test( 'a' )\n    false\n\n\nreWhitespace.REGEXP_CAPTURE\n    Regular expression to capture white space characters.\n\n    Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n    characters in the Unicode 9.0 character database.\n\n    Matches one related white space character without the Unicode character\n    property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n    of Unicode 3.2).\n\n    Examples\n    --------\n    > var RE = reWhitespace.REGEXP_CAPTURE;\n    > var str = 'Duplicate capture';\n    > var out = replace( str, RE, '$1$1' )\n    'Duplicate  capture'\n\n    See Also\n    --------\n    isWhitespace","reWhitespace.REGEXP":"\nreWhitespace.REGEXP\n    Regular expression to match a white space character.\n\n    Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n    characters in the Unicode 9.0 character database.\n\n    Matches one related white space character without the Unicode character\n    property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n    of Unicode 3.2).\n\n    Examples\n    --------\n    > var RE = reWhitespace.REGEXP;\n    > var bool = RE.test( '\\n' )\n    true\n    > bool = RE.test( ' ' )\n    true\n    > bool = RE.test( 'a' )\n    false","reWhitespace.REGEXP_CAPTURE":"\nreWhitespace.REGEXP_CAPTURE\n    Regular expression to capture white space characters.\n\n    Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n    characters in the Unicode 9.0 character database.\n\n    Matches one related white space character without the Unicode character\n    property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n    of Unicode 3.2).\n\n    Examples\n    --------\n    > var RE = reWhitespace.REGEXP_CAPTURE;\n    > var str = 'Duplicate capture';\n    > var out = replace( str, RE, '$1$1' )\n    'Duplicate  capture'\n\n    See Also\n    --------\n    isWhitespace","rpad":"\nrpad( str, len[, pad] )\n    Right pads a `string` such that the padded `string` has a length of at least\n    `len`.\n\n    An output string is not guaranteed to have a length of exactly `len`, but to\n    have a length of at least `len`. To generate a padded string having a length\n    equal to `len`, post-process a padded string by trimming off excess\n    characters.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    len: integer\n        Minimum string length.\n\n    pad: string (optional)\n        String used to pad. Default: ' '.\n\n    Returns\n    -------\n    out: string\n        Padded string.\n\n    Examples\n    --------\n    > var out = rpad( 'a', 5 )\n    'a    '\n    > out = rpad( 'beep', 10, 'p' )\n    'beeppppppp'\n    > out = rpad( 'beep', 12, 'boop' )\n    'beepboopboop'\n\n    See Also\n    --------\n    lpad, pad\n","rtrim":"\nrtrim( str )\n    Trims whitespace from the end of a string.\n\n    \"Whitespace\" is defined as the following characters:\n\n    - \\f\n    - \\n\n    - \\r\n    - \\t\n    - \\v\n    - \\u0020\n    - \\u00a0\n    - \\u1680\n    - \\u2000-\\u200a\n    - \\u2028\n    - \\u2029\n    - \\u202f\n    - \\u205f\n    - \\u3000\n    - \\ufeff\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Trimmed string.\n\n    Examples\n    --------\n    > var out = rtrim( ' \\t\\t\\n  Beep \\r\\n\\t  ' )\n    ' \\t\\t\\n  Beep'\n\n    See Also\n    --------\n    ltrim, trim\n","rtrimN":"\nrtrimN( str, n[, chars] )\n    Trims `n` characters from the end of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of characters to trim.\n\n    chars: Array<string>|string (optional)\n        Characters to trim. Default: whitespace characters.\n\n    Returns\n    -------\n    out: string\n        Trimmed string.\n\n    Examples\n    --------\n    > var out = rtrimN( '  abc  ', 2 )\n    '  abc'\n    > var out = rtrimN( '!!!abc!!!', 2, '!' )\n    '!!!abc!'\n\n    See Also\n    --------\n    ltrimN, trim","safeintmax":"\nsafeintmax( dtype )\n    Returns the maximum safe integer capable of being represented by a numeric\n    real type.\n\n    The following numeric real types are supported:\n\n    - float64: double-precision floating-point numbers.\n    - float32: single-precision floating-point numbers.\n    - float16: half-precision floating-point numbers.\n\n    Parameters\n    ----------\n    dtype: string\n        Numeric type.\n\n    Returns\n    -------\n    out: integer\n        Maximum safe integer.\n\n    Examples\n    --------\n    > var m = safeintmax( 'float16' )\n    2047\n    > m = safeintmax( 'float32' )\n    16777215\n\n    See Also\n    --------\n    safeintmin, realmax, typemax\n","safeintmin":"\nsafeintmin( dtype )\n    Returns the minimum safe integer capable of being represented by a numeric\n    real type.\n\n    The following numeric real types are supported:\n\n    - float64: double-precision floating-point numbers.\n    - float32: single-precision floating-point numbers.\n    - float16: half-precision floating-point numbers.\n\n    Parameters\n    ----------\n    dtype: string\n        Numeric type.\n\n    Returns\n    -------\n    out: integer\n        Minimum safe integer.\n\n    Examples\n    --------\n    > var m = safeintmin( 'float16' )\n    -2047\n    > m = safeintmin( 'float32' )\n    -16777215\n\n    See Also\n    --------\n    safeintmax, realmin, typemin\n","sample":"\nsample( x[, options] )\n    Samples elements from an array-like object.\n\n    Parameters\n    ----------\n    x: ArrayLike\n        Array-like object from which to sample.\n\n    options: Object (optional)\n        Options.\n\n    options.size: integer (optional)\n        Sample size. By default, the function returns an array having the same\n        length as `x`. Specify the `size` option to generate a sample of a\n        different size.\n\n    options.probs: Array<number> (optional)\n        Element probabilities. By default, the probability of sampling an\n        element is the same for all elements. To assign elements different\n        probabilities, set the `probs` option. The `probs` option must be a\n        numeric array consisting of nonnegative values which sum to one. When\n        sampling without replacement, note that the `probs` option denotes the\n        initial element probabilities which are then updated after each draw.\n\n    options.replace: boolean (optional)\n        Boolean indicating whether to sample with replacement. If the `replace`\n        option is set to `false`, the `size` option cannot be an integer larger\n        than the number of elements in `x`. Default: `true`.\n\n    Returns\n    -------\n    out: Array\n        Sample.\n\n    Examples\n    --------\n    > var out = sample( 'abc' )\n    e.g., [ 'a', 'a', 'b' ]\n    > out = sample( [ 3, 6, 9 ] )\n    e.g., [ 3, 9, 6 ]\n    > var bool = ( out.length === 3 )\n    true\n\n    > out = sample( [ 3, null, NaN, 'abc', function(){} ] )\n    e.g., [ 3, 'abc', null, 3, null ]\n\n    // Set sample size:\n    > out = sample( [ 3, 6, 9 ], { 'size': 10 } )\n    e.g., [ 6, 3, 9, 9, 9, 6, 9, 6, 9, 3 ]\n    > out = sample( [ 0, 1 ], { 'size': 20 } )\n    e.g., [ 0, 0, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 0 ]\n\n    // Draw without replacement:\n    > out = sample( [ 1, 2, 3, 4, 5, 6 ], { 'replace': false, 'size': 3 } )\n    e.g., [ 6, 1, 5 ]\n    > out = sample( [ 0, 1 ], { 'replace': false } )\n    e.g., [ 0, 1 ]\n\n    // Assigning non-uniform element probabilities:\n    > var x = [ 1, 2, 3, 4, 5, 6 ];\n    > var probs = [ 0.1, 0.1, 0.1, 0.1, 0.1, 0.5 ];\n    > out = sample( x, { 'probs': probs } )\n    e.g., [ 5, 6, 6, 5, 6, 4 ]\n    > out = sample( x, { 'probs': probs, 'size': 3, 'replace': false } )\n    e.g., [ 6, 4, 1 ]\n\n\nsample.factory( [pool, ][options] )\n    Returns a function to sample elements from an array-like object.\n\n    If provided an array-like object `pool`, the returned function will always\n    sample from the supplied object.\n\n    Parameters\n    ----------\n    pool: ArrayLike (optional)\n        Array-like object from which to sample.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer (optional)\n        Integer-valued seed.\n\n    options.size: integer (optional)\n        Sample size.\n\n    options.replace: boolean (optional)\n        Boolean indicating whether to sample with replacement. Default: `true`.\n\n    options.mutate: boolean (optional)\n        Boolean indicating whether to mutate the `pool` when sampling without\n        replacement. If a population from which to sample is provided, the\n        underlying `pool` remains by default constant for each function\n        invocation. To mutate the `pool` by permanently removing observations\n        when sampling without replacement, set the `mutate` option to `true`.\n        The returned function returns `null` after all population units are\n        exhausted. Default: `false`.\n\n    Returns\n    -------\n    fcn: Function\n        Function to sample elements from an array-like object.\n\n    Examples\n    --------\n    // Set a seed:\n    > var mysample = sample.factory({ 'seed': 232 } );\n    > var out = mysample( 'abcdefg' )\n    e.g., [ 'g', 'd', 'g', 'f', 'c', 'e', 'f' ]\n\n    // Provide `pool` and set a seed plus a default sample size:\n    > var pool = [ 1, 2, 3, 4, 5, 6 ];\n    > mysample = sample.factory( pool, { 'seed': 232, 'size': 2 } );\n    > out = mysample()\n    e.g., [ 6, 4 ]\n    > out = mysample()\n    e.g., [ 6, 5 ]\n\n    // Mutate the `pool`:\n    > var opts = { 'seed': 474, 'size': 3, 'mutate': true, 'replace': false };\n    > pool = [ 1, 2, 3, 4, 5, 6 ];\n    > mysample = sample.factory( pool, opts );\n    > out = mysample()\n    e.g., [ 4, 3, 6 ]\n    > out = mysample()\n    e.g., [ 1, 5, 2 ]\n    > out = mysample()\n    null\n\n    // Override default `size` parameter when invoking created function:\n    > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n    > out = mysample()\n    e.g., [ 1, 1 ]\n    > out = mysample({ 'size': 10 })\n    e.g, [ 0, 1, 1, 1, 0, 1, 0, 0, 1, 1 ]\n\n    // Sample with and without replacement:\n    > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n    > out = mysample()\n    e.g., [ 1, 1 ]\n    > out = mysample({ 'replace': false })\n    e.g., [ 0, 1 ] or [ 1, 0 ]\n    > out = mysample()\n    e.g., [ 1, 1 ]\n\n","sample.factory":"\nsample.factory( [pool, ][options] )\n    Returns a function to sample elements from an array-like object.\n\n    If provided an array-like object `pool`, the returned function will always\n    sample from the supplied object.\n\n    Parameters\n    ----------\n    pool: ArrayLike (optional)\n        Array-like object from which to sample.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer (optional)\n        Integer-valued seed.\n\n    options.size: integer (optional)\n        Sample size.\n\n    options.replace: boolean (optional)\n        Boolean indicating whether to sample with replacement. Default: `true`.\n\n    options.mutate: boolean (optional)\n        Boolean indicating whether to mutate the `pool` when sampling without\n        replacement. If a population from which to sample is provided, the\n        underlying `pool` remains by default constant for each function\n        invocation. To mutate the `pool` by permanently removing observations\n        when sampling without replacement, set the `mutate` option to `true`.\n        The returned function returns `null` after all population units are\n        exhausted. Default: `false`.\n\n    Returns\n    -------\n    fcn: Function\n        Function to sample elements from an array-like object.\n\n    Examples\n    --------\n    // Set a seed:\n    > var mysample = sample.factory({ 'seed': 232 } );\n    > var out = mysample( 'abcdefg' )\n    e.g., [ 'g', 'd', 'g', 'f', 'c', 'e', 'f' ]\n\n    // Provide `pool` and set a seed plus a default sample size:\n    > var pool = [ 1, 2, 3, 4, 5, 6 ];\n    > mysample = sample.factory( pool, { 'seed': 232, 'size': 2 } );\n    > out = mysample()\n    e.g., [ 6, 4 ]\n    > out = mysample()\n    e.g., [ 6, 5 ]\n\n    // Mutate the `pool`:\n    > var opts = { 'seed': 474, 'size': 3, 'mutate': true, 'replace': false };\n    > pool = [ 1, 2, 3, 4, 5, 6 ];\n    > mysample = sample.factory( pool, opts );\n    > out = mysample()\n    e.g., [ 4, 3, 6 ]\n    > out = mysample()\n    e.g., [ 1, 5, 2 ]\n    > out = mysample()\n    null\n\n    // Override default `size` parameter when invoking created function:\n    > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n    > out = mysample()\n    e.g., [ 1, 1 ]\n    > out = mysample({ 'size': 10 })\n    e.g, [ 0, 1, 1, 1, 0, 1, 0, 0, 1, 1 ]\n\n    // Sample with and without replacement:\n    > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n    > out = mysample()\n    e.g., [ 1, 1 ]\n    > out = mysample({ 'replace': false })\n    e.g., [ 0, 1 ] or [ 1, 0 ]\n    > out = mysample()\n    e.g., [ 1, 1 ]","SAVOY_STOPWORDS_FIN":"\nSAVOY_STOPWORDS_FIN()\n    Returns a list of Finnish stop words.\n\n    Returns\n    -------\n    out: Array<string>\n        List of stop words.\n\n    Examples\n    --------\n    > var list = SAVOY_STOPWORDS_FIN()\n    [ 'aiemmin', 'aika', 'aikaa', ... ]\n\n    References\n    ----------\n    - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n    <http://members.unine.ch/jacques.savoy/clef/>.\n\n","SAVOY_STOPWORDS_FR":"\nSAVOY_STOPWORDS_FR()\n    Returns a list of French stop words.\n\n    Returns\n    -------\n    out: Array<string>\n        List of stop words.\n\n    Examples\n    --------\n    > var list = SAVOY_STOPWORDS_FR()\n    [ 'a', 'à', 'â', 'abord', ... ]\n\n    References\n    ----------\n    - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n    <http://members.unine.ch/jacques.savoy/clef/>.\n\n","SAVOY_STOPWORDS_GER":"\nSAVOY_STOPWORDS_GER()\n    Returns a list of German stop words.\n\n    Returns\n    -------\n    out: Array<string>\n        List of stop words.\n\n    Examples\n    --------\n    > var list = SAVOY_STOPWORDS_GER()\n    [ 'a', 'ab', 'aber', 'ach', ... ]\n\n    References\n    ----------\n    - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n    <http://members.unine.ch/jacques.savoy/clef/>.\n\n","SAVOY_STOPWORDS_IT":"\nSAVOY_STOPWORDS_IT()\n    Returns a list of Italian stop words.\n\n    Returns\n    -------\n    out: Array<string>\n        List of stop words.\n\n    Examples\n    --------\n    > var list = SAVOY_STOPWORDS_IT()\n    [ 'a', 'abbastanza', 'accidenti', 'ad', ... ]\n\n    References\n    ----------\n    - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n    <http://members.unine.ch/jacques.savoy/clef/>.\n\n","SAVOY_STOPWORDS_POR":"\nSAVOY_STOPWORDS_POR()\n    Returns a list of Portuguese stop words.\n\n    Returns\n    -------\n    out: Array<string>\n        List of stop words.\n\n    Examples\n    --------\n    > var list = SAVOY_STOPWORDS_POR()\n    [ 'aiemmin', 'aika', 'aikaa', ... ]\n\n    References\n    ----------\n    - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n    <http://members.unine.ch/jacques.savoy/clef/>.\n\n","SAVOY_STOPWORDS_SP":"\nSAVOY_STOPWORDS_SP()\n    Returns a list of Spanish stop words.\n\n    Returns\n    -------\n    out: Array<string>\n        List of stop words.\n\n    Examples\n    --------\n    > var list = SAVOY_STOPWORDS_SP()\n    [ 'a', 'acuerdo', 'adelante', 'ademas', ... ]\n\n    References\n    ----------\n    - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n    <http://members.unine.ch/jacques.savoy/clef/>.\n\n","SAVOY_STOPWORDS_SWE":"\nSAVOY_STOPWORDS_SWE()\n    Returns a list of Swedish stop words.\n\n    Returns\n    -------\n    out: Array<string>\n        List of stop words.\n\n    Examples\n    --------\n    > var list = SAVOY_STOPWORDS_SWE()\n    [ 'aderton', 'adertonde', 'adjö', ... ]\n\n    References\n    ----------\n    - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n    <http://members.unine.ch/jacques.savoy/clef/>.\n\n","scalar2array":"\nscalar2array( value[, dtype] )\n    Returns a single-element array containing a provided scalar value.\n\n    If `value` is a number and `dtype` is a complex number data type, the\n    function returns a complex number array containing a complex number whose\n    real component equals the provided scalar value and whose imaginary\n    component is zero.\n\n    Parameters\n    ----------\n    value: any\n        Scalar value.\n\n    dtype: string (optional)\n        Data type. If not provided and `value`\n\n        - is a number, the default data type is the default real-valued\n          floating-point data type.\n        - is a boolean, the default data type is the default boolean data type.\n        - is a complex number object of a known complex data type, the data type\n          is the same as the provided value.\n        - is a complex number object of an unknown data type, the default data\n          type is the default complex-valued floating-point data type.\n        - is any other value type, the default data type is 'generic'.\n\n    Returns\n    -------\n    out: Array|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = scalar2array( 1.0 )\n    <Float64Array>[ 1.0 ]\n\n    See Also\n    --------\n    iterator2array\n","scalar2ndarray":"\nscalar2ndarray( value[, options] )\n    Returns a zero-dimensional ndarray containing a provided scalar value.\n\n    If `value` is a number and `options.dtype` is a complex number data type,\n    the function returns a zero-dimensional ndarray containing a complex number\n    whose real component equals the provided scalar value and whose imaginary\n    component is zero.\n\n    Parameters\n    ----------\n    value: any\n        Scalar value.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Data type. If not provided and `value`\n\n        - is a number, the default data type is the default real-valued\n          floating-point data type.\n        - is a boolean, the default data type is the default boolean data type.\n        - is a complex number object of a known complex data type, the data type\n          is the same as the provided value.\n        - is a complex number object of an unknown data type, the default data\n          type is the default complex-valued floating-point data type.\n        - is any other value type, the default data type is 'generic'.\n\n    options.order: string (optional)\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran-style). Default: 'row-major'.\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether an array should be read-only. Default: false.\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var x = scalar2ndarray( 1.0 )\n    <ndarray>\n    > var sh = x.shape\n    []\n    > var dt = x.dtype\n    'float64'\n    > var v = x.get()\n    1.0\n\n    See Also\n    --------\n    array, ndarray\n","sdot":"\nsdot( x, y[, dim] )\n    Computes the dot product of two single-precision floating-point vectors.\n\n    If provided at least one input array having more than one dimension, the\n    input arrays are broadcasted to a common shape.\n\n    For multi-dimensional input arrays, the function performs batched\n    computation, such that the function computes the dot product for each pair\n    of vectors in `x` and `y` according to the specified dimension index.\n\n    The size of the contracted dimension must be the same for both input arrays.\n\n    The function resolves the dimension index for which to compute the dot\n    product *before* broadcasting.\n\n    If provided empty vectors, the dot product is `0`.\n\n    Parameters\n    ----------\n    x: ndarray\n        First input array. Must have a 'float32' data type. Must have at least\n        one dimension and be broadcast-compatible with the second input array.\n\n    y: ndarray\n        Second input array. Must have a 'float32' data type. Must have at least\n        one dimension and be broadcast-compatible with the first input array.\n\n    dim: integer (optional)\n        Dimension index for which to compute the dot product. Must be a negative\n        integer. Negative indices are resolved relative to the last array\n        dimension, with the last dimension corresponding to `-1`. Default: -1.\n\n    Returns\n    -------\n    out: ndarray\n        The dot product. The output array has the same data type as the input\n        arrays and has a shape which is determined by broadcasting and excludes\n        the contracted dimension.\n\n    Examples\n    --------\n    > var xbuf = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var x = array( xbuf );\n    > var ybuf = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var y = array( ybuf );\n    > var z = sdot( x, y )\n    <ndarray>\n    > z.get()\n    -5.0\n\n    See Also\n    --------\n    base.strided.sdot, ddot, gdot\n","SECONDS_IN_DAY":"\nSECONDS_IN_DAY\n    Number of seconds in a day.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var days = 3.14;\n    > var secs = days * SECONDS_IN_DAY\n    271296\n\n","SECONDS_IN_HOUR":"\nSECONDS_IN_HOUR\n    Number of seconds in an hour.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var hrs = 3.14;\n    > var secs = hrs * SECONDS_IN_HOUR\n    11304\n\n","SECONDS_IN_MINUTE":"\nSECONDS_IN_MINUTE\n    Number of seconds in a minute.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies arising due to complications with time and dates.\n\n    Examples\n    --------\n    > var mins = 3.14;\n    > var secs = mins * SECONDS_IN_MINUTE\n    188.4\n\n","SECONDS_IN_WEEK":"\nSECONDS_IN_WEEK\n    Number of seconds in a week.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var wks = 3.14;\n    > var secs = wks * SECONDS_IN_WEEK\n    1899072\n\n","secondsInMonth":"\nsecondsInMonth( [month[, year]] )\n    Returns the number of seconds in a month.\n\n    By default, the function returns the number of seconds in the current month\n    of the current year (according to local time). To determine the number of\n    seconds for a particular month and year, provide `month` and `year`\n    arguments.\n\n    A `month` may be either a month's integer value, three letter abbreviation,\n    or full name (case insensitive).\n\n    The function's return value is a generalization and does **not** take into\n    account inaccuracies due to daylight savings conventions, crossing\n    timezones, or other complications with time and dates.\n\n    Parameters\n    ----------\n    month: string|Date|integer (optional)\n        Month.\n\n    year: integer (optional)\n        Year.\n\n    Returns\n    -------\n    out: integer\n        Seconds in a month.\n\n    Examples\n    --------\n    > var num = secondsInMonth()\n    <number>\n    > num = secondsInMonth( 2 )\n    <number>\n    > num = secondsInMonth( 2, 2016 )\n    2505600\n    > num = secondsInMonth( 2, 2017 )\n    2419200\n\n    // Other ways to supply month:\n    > num = secondsInMonth( 'feb', 2016 )\n    2505600\n    > num = secondsInMonth( 'february', 2016 )\n    2505600\n\n    See Also\n    --------\n    secondsInYear\n","secondsInYear":"\nsecondsInYear( [value] )\n    Returns the number of seconds in a year according to the Gregorian calendar.\n\n    By default, the function returns the number of seconds in the current year\n    (according to local time). To determine the number of seconds for a\n    particular year, provide either a year or a `Date` object.\n\n    The function's return value is a generalization and does **not** take into\n    account inaccuracies due to daylight savings conventions, crossing\n    timezones, or other complications with time and dates.\n\n    Parameters\n    ----------\n    value: integer|Date (optional)\n        Year or `Date` object.\n\n    Returns\n    -------\n    out: integer\n        Number of seconds in a year.\n\n    Examples\n    --------\n    > var num = secondsInYear()\n    <number>\n    > num = secondsInYear( 2016 )\n    31622400\n    > num = secondsInYear( 2017 )\n    31536000\n\n    See Also\n    --------\n    secondsInMonth\n","sentencize":"\nsentencize( str )\n    Splits a string into an array of sentences.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: Array\n        Array of sentences.\n\n    Examples\n    --------\n    > var out = sentencize( 'Hello Mrs. Maple, could you call me back?' )\n    [ 'Hello Mrs. Maple, could you call me back?' ]\n\n    > out = sentencize( 'Hello World! How are you?' )\n    [ 'Hello World!', 'How are you?' ]\n\n    See Also\n    --------\n    tokenize\n","seq2slice":"\nseq2slice( str, len, strict )\n    Converts a subsequence string to a Slice object.\n\n    A subsequence string has the following format:\n\n      <start>:<stop>:<increment>\n\n    If an increment is not specified, the default increment is one. An increment\n    of zero is not allowed.\n\n    The start index is inclusive.\n\n    The stop index is exclusive.\n\n    Both start and stop indices are optional. If not provided, the start and\n    stop indices default to index extremes. Which extremes correspond to which\n    index depends on whether the increment is positive or negative.\n\n    Both start and stop indices can be negative; in which case, the\n    corresponding index is resolved by subtracting the respective value from the\n    provided length.\n\n    Both start and stop indices can use the 'end' keyword (e.g., 'end-2::2',\n    'end-3:', etc), which supports basic subtraction and division.\n\n    The 'end' keyword resolves to the provided length. Thus, ':-1' is equivalent\n    to ':end-1', ':-2' is equivalent to ':end-2', and so on and so forth. The\n    exception is when performing a division operation when the increment is less\n    than zero; in which case, 'end' is equal to 'len-1' in order to preserve\n    user expectations when 'end/d' equals a whole number and slicing from right-\n    to-left. The result from a division operation is rounded down to the nearest\n    integer value.\n\n    In non-strict mode, the resolved slice start is clamped to the slice index\n    bounds [0, len).\n\n    In non-strict mode, Tte resolved slice end is upper bound clamped to the\n    provided length (i.e., one greater than the last possible index).\n\n    When the increment is negative, the resolved slice end value may be `null`,\n    thus indicating that a non-empty slice should include the first index.\n\n    The function ensures that results satisfy the convention that ':n' combined\n    with 'n:' is equivalent to ':' (i.e., selecting all elements).\n\n    When the provided length is zero, the function always returns a slice object\n    equivalent to '0:0:<increment>'.\n\n    Parameters\n    ----------\n    str: string\n        Subsequence string.\n\n    len: integer\n        Maximum number of elements allowed in the slice.\n\n    strict: boolean\n        Boolean indicating whether to enforce strict bounds checking.\n\n    Returns\n    -------\n    s: Slice\n        Slice instance.\n\n    Examples\n    --------\n    > var s = new seq2slice( '1:10', 10, false );\n    > s.start\n    1\n    > s.stop\n    10\n    > s.step\n    1\n    > s = new seq2slice( '2:5:2', 10, false );\n    > s.start\n    2\n    > s.stop\n    5\n    > s.step\n    2\n\n    See Also\n    --------\n    Slice\n","setConfigurableReadOnly":"\nsetConfigurableReadOnly( obj, prop, value )\n    Defines a configurable read-only property.\n\n    Configurable read-only properties are enumerable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    value: any\n        Value to set.\n\n    Examples\n    --------\n    > var obj = {};\n    > setConfigurableReadOnly( obj, 'foo', 'bar' );\n    > obj.foo = 'boop';\n    > obj\n    { 'foo': 'bar' }\n\n    See Also\n    --------\n    setConfigurableReadOnlyAccessor, setConfigurableReadWriteAccessor, defineProperty, setReadOnly\n","setConfigurableReadOnlyAccessor":"\nsetConfigurableReadOnlyAccessor( obj, prop, getter )\n    Defines a configurable read-only accessor.\n\n    Configurable read-only accessors are enumerable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    getter: Function\n        Get accessor.\n\n    Examples\n    --------\n    > var obj = {};\n    > function getter() { return 'bar'; };\n    > setConfigurableReadOnlyAccessor( obj, 'foo', getter );\n    > obj.foo\n    'bar'\n\n    See Also\n    --------\n    setConfigurableReadOnly, setConfigurableReadWriteAccessor, setConfigurableWriteOnlyAccessor, defineProperty, setReadOnlyAccessor\n","setConfigurableReadWriteAccessor":"\nsetConfigurableReadWriteAccessor( obj, prop, getter, setter )\n    Defines a configurable property having read-write accessors.\n\n    Configurable read-write accessors are enumerable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    getter: Function\n        Get accessor.\n\n    setter: Function\n        Set accessor.\n\n    Examples\n    --------\n    > var obj = {};\n    > var name = 'bar';\n    > function getter() { return name + ' foo'; };\n    > function setter( v ) { name = v; };\n    > setConfigurableReadWriteAccessor( obj, 'foo', getter, setter );\n    > obj.foo\n    'bar foo'\n    > obj.foo = 'beep';\n    > obj.foo\n    'beep foo'\n\n    See Also\n    --------\n    setConfigurableReadOnly, setConfigurableReadOnlyAccessor, setConfigurableWriteOnlyAccessor, defineProperty, setReadWriteAccessor\n","setConfigurableWriteOnlyAccessor":"\nsetConfigurableWriteOnlyAccessor( obj, prop, setter )\n    Defines a configurable write-only accessor.\n\n    Configurable write-only accessors are enumerable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    setter: Function\n        Set accessor.\n\n    Examples\n    --------\n    > var obj = {};\n    > var val = '';\n    > function setter( v ) { val = v; };\n    > setConfigurableWriteOnlyAccessor( obj, 'foo', setter );\n    > obj.foo = 'bar';\n    > val\n    'bar'\n\n    See Also\n    --------\n    setConfigurableReadOnly, setConfigurableReadOnlyAccessor, setConfigurableReadWriteAccessor, defineProperty, setWriteOnlyAccessor\n","setMemoizedConfigurableReadOnly":"\nsetMemoizedConfigurableReadOnly( obj, prop, fcn )\n    Defines a configurable memoized read-only object property.\n\n    Configurable read-only properties are enumerable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    fcn: Function\n        Synchronous function whose return value will be memoized and set as the\n        property value.\n\n    Examples\n    --------\n    > var obj = {};\n    > function foo() { return 'bar'; };\n    > setMemoizedConfigurableReadOnly( obj, 'foo', foo );\n    > obj.foo\n    'bar'\n\n    See Also\n    --------\n    setConfigurableReadOnly, setMemoizedReadOnly, setReadOnly\n","setMemoizedReadOnly":"\nsetMemoizedReadOnly( obj, prop, fcn )\n    Defines a memoized read-only object property.\n\n    Read-only properties are enumerable and non-configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    fcn: Function\n        Synchronous function whose return value will be memoized and set as the\n        property value.\n\n    Examples\n    --------\n    > var obj = {};\n    > function foo() { return 'bar'; };\n    > setMemoizedReadOnly( obj, 'foo', foo );\n    > obj.foo\n    'bar'\n\n    See Also\n    --------\n    defineMemoizedProperty, setReadOnly\n","setNonEnumerableProperty":"\nsetNonEnumerableProperty( obj, prop, value )\n    Defines a non-enumerable property.\n\n    Non-enumerable properties are writable and configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    value: any\n        Value to set.\n\n    Examples\n    --------\n    > var obj = {};\n    > setNonEnumerableProperty( obj, 'foo', 'bar' );\n    > obj.foo\n    'bar'\n    > objectKeys( obj )\n    []\n\n    See Also\n    --------\n    setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnly\n","setNonEnumerableReadOnly":"\nsetNonEnumerableReadOnly( obj, prop, value )\n    Defines a non-enumerable read-only property.\n\n    Non-enumerable read-only properties are non-configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    value: any\n        Value to set.\n\n    Examples\n    --------\n    > var obj = {};\n    > setNonEnumerableReadOnly( obj, 'foo', 'bar' );\n    > obj.foo = 'boop';\n    > obj\n    { 'foo': 'bar' }\n\n    See Also\n    --------\n    setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnly\n","setNonEnumerableReadOnlyAccessor":"\nsetNonEnumerableReadOnlyAccessor( obj, prop, getter )\n    Defines a non-enumerable read-only accessor.\n\n    Non-enumerable read-only accessors are non-configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    getter: Function\n        Get accessor.\n\n    Examples\n    --------\n    > var obj = {};\n    > function getter() { return 'bar'; };\n    > setNonEnumerableReadOnlyAccessor( obj, 'foo', getter );\n    > obj.foo\n    'bar'\n\n    See Also\n    --------\n    setNonEnumerableProperty, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnlyAccessor\n","setNonEnumerableReadWriteAccessor":"\nsetNonEnumerableReadWriteAccessor( obj, prop, getter, setter )\n    Defines a non-enumerable property having read-write accessors.\n\n    Non-enumerable read-write accessors are non-configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    getter: Function\n        Get accessor.\n\n    setter: Function\n        Set accessor.\n\n    Examples\n    --------\n    > var obj = {};\n    > var name = 'bar';\n    > function getter() { return name + ' foo'; };\n    > function setter( v ) { name = v; };\n    > setNonEnumerableReadWriteAccessor( obj, 'foo', getter, setter );\n    > obj.foo\n    'bar foo'\n    > obj.foo = 'beep';\n    > obj.foo\n    'beep foo'\n\n    See Also\n    --------\n    setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableWriteOnlyAccessor, setReadWriteAccessor\n","setNonEnumerableWriteOnlyAccessor":"\nsetNonEnumerableWriteOnlyAccessor( obj, prop, setter )\n    Defines a non-enumerable write-only accessor.\n\n    Non-enumerable write-only accessors are non-configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    setter: Function\n        Set accessor.\n\n    Examples\n    --------\n    > var obj = {};\n    > var val = '';\n    > function setter( v ) { val = v; };\n    > setNonEnumerableWriteOnlyAccessor( obj, 'foo', setter );\n    > obj.foo = 'bar';\n    > val\n    'bar'\n\n    See Also\n    --------\n    setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setWriteOnlyAccessor\n","setReadOnly":"\nsetReadOnly( obj, prop, value )\n    Defines a read-only property.\n\n    Read-only properties are enumerable and non-configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    value: any\n        Value to set.\n\n    Examples\n    --------\n    > var obj = {};\n    > setReadOnly( obj, 'foo', 'bar' );\n    > obj.foo = 'boop';\n    > obj\n    { 'foo': 'bar' }\n\n    See Also\n    --------\n    setReadOnlyAccessor, setReadWriteAccessor, setWriteOnlyAccessor\n","setReadOnlyAccessor":"\nsetReadOnlyAccessor( obj, prop, getter )\n    Defines a read-only accessor.\n\n    Read-only accessors are enumerable and non-configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    getter: Function\n        Get accessor.\n\n    Examples\n    --------\n    > var obj = {};\n    > function getter() { return 'bar'; };\n    > setReadOnlyAccessor( obj, 'foo', getter );\n    > obj.foo\n    'bar'\n\n    See Also\n    --------\n    setReadOnly, setReadWriteAccessor, setWriteOnlyAccessor\n","setReadWriteAccessor":"\nsetReadWriteAccessor( obj, prop, getter, setter )\n    Defines a property having read-write accessors.\n\n    Read-write accessors are enumerable and non-configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    getter: Function\n        Get accessor.\n\n    setter: Function\n        Set accessor.\n\n    Examples\n    --------\n    > var obj = {};\n    > var name = 'bar';\n    > function getter() { return name + ' foo'; };\n    > function setter( v ) { name = v; };\n    > setReadWriteAccessor( obj, 'foo', getter, setter );\n    > obj.foo\n    'bar foo'\n    > obj.foo = 'beep';\n    > obj.foo\n    'beep foo'\n\n    See Also\n    --------\n    setReadOnly, setReadOnlyAccessor, setWriteOnlyAccessor\n","setWriteOnlyAccessor":"\nsetWriteOnlyAccessor( obj, prop, setter )\n    Defines a write-only accessor.\n\n    Write-only accessors are enumerable and non-configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    setter: Function\n        Set accessor.\n\n    Examples\n    --------\n    > var obj = {};\n    > var val = '';\n    > function setter( v ) { val = v; };\n    > setWriteOnlyAccessor( obj, 'foo', setter );\n    > obj.foo = 'bar';\n    > val\n    'bar'\n\n    See Also\n    --------\n    setReadOnly, setReadOnlyAccessor, setReadWriteAccessor\n","SharedArrayBuffer":"\nSharedArrayBuffer( size )\n    Returns a shared array buffer having a specified number of bytes.\n\n    A shared array buffer behaves similarly to a non-shared array buffer, except\n    that a shared array buffer allows creating views of memory shared between\n    threads.\n\n    Buffer contents are initialized to 0.\n\n    If an environment does not support shared array buffers, the function throws\n    an error.\n\n    Parameters\n    ----------\n    size: integer\n        Number of bytes.\n\n    Returns\n    -------\n    out: SharedArrayBuffer\n        A shared array buffer.\n\n    Examples\n    --------\n    // Assuming an environment supports SharedArrayBuffers...\n    > var buf = new SharedArrayBuffer( 5 )\n    <SharedArrayBuffer>\n\n\nSharedArrayBuffer.length\n    Number of input arguments the constructor accepts.\n\n    Examples\n    --------\n    > SharedArrayBuffer.length\n    1\n\n\nSharedArrayBuffer.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the array buffer.\n\n    Examples\n    --------\n    // Assuming an environment supports SharedArrayBuffers...\n    > var buf = new SharedArrayBuffer( 5 );\n    > buf.byteLength\n    5\n\n\nSharedArrayBuffer.prototype.slice( [start[, end]] )\n    Copies the bytes of a shared array buffer to a new shared array buffer.\n\n    Parameters\n    ----------\n    start: integer (optional)\n        Index at which to start copying buffer contents (inclusive). If\n        negative, the index is relative to the end of the buffer.\n\n    end: integer (optional)\n        Index at which to stop copying buffer contents (exclusive). If negative,\n        the index is relative to the end of the buffer.\n\n    Returns\n    -------\n    out: SharedArrayBuffer\n        A new shared array buffer whose contents have been copied from the\n        calling shared array buffer.\n\n    Examples\n    --------\n    // Assuming an environment supports SharedArrayBuffers...\n    > var b1 = new SharedArrayBuffer( 10 );\n    > var b2 = b1.slice( 2, 6 );\n    > var bool = ( b1 === b2 )\n    false\n    > b2.byteLength\n    4\n\n    See Also\n    --------\n    Buffer, ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","SharedArrayBuffer.length":"\nSharedArrayBuffer.length\n    Number of input arguments the constructor accepts.\n\n    Examples\n    --------\n    > SharedArrayBuffer.length\n    1","SharedArrayBuffer.prototype.byteLength":"\nSharedArrayBuffer.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the array buffer.\n\n    Examples\n    --------\n    // Assuming an environment supports SharedArrayBuffers...\n    > var buf = new SharedArrayBuffer( 5 );\n    > buf.byteLength\n    5","SharedArrayBuffer.prototype.slice":"\nSharedArrayBuffer.prototype.slice( [start[, end]] )\n    Copies the bytes of a shared array buffer to a new shared array buffer.\n\n    Parameters\n    ----------\n    start: integer (optional)\n        Index at which to start copying buffer contents (inclusive). If\n        negative, the index is relative to the end of the buffer.\n\n    end: integer (optional)\n        Index at which to stop copying buffer contents (exclusive). If negative,\n        the index is relative to the end of the buffer.\n\n    Returns\n    -------\n    out: SharedArrayBuffer\n        A new shared array buffer whose contents have been copied from the\n        calling shared array buffer.\n\n    Examples\n    --------\n    // Assuming an environment supports SharedArrayBuffers...\n    > var b1 = new SharedArrayBuffer( 10 );\n    > var b2 = b1.slice( 2, 6 );\n    > var bool = ( b1 === b2 )\n    false\n    > b2.byteLength\n    4\n\n    See Also\n    --------\n    Buffer, ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","shift":"\nshift( collection )\n    Removes and returns the first element of a collection.\n\n    The function returns an array with two elements: the shortened collection\n    and the removed element.\n\n    If the input collection is a typed array whose length is greater than `0`,\n    the first return value does not equal the input reference.\n\n    For purposes of generality, always treat the output collection as distinct\n    from the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        A collection. If the collection is an `Object`, the value should be\n        array-like.\n\n    Returns\n    -------\n    out: Array\n        Updated collection and the removed item.\n\n    Examples\n    --------\n    // Arrays:\n    > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > var out = shift( arr )\n    [ [ 2.0, 3.0, 4.0, 5.0 ], 1.0 ]\n\n    // Typed arrays:\n    > arr = new Float64Array( [ 1.0, 2.0 ] );\n    > out = shift( arr )\n    [ <Float64Array>[ 2.0 ], 1.0 ]\n\n    // Array-like object:\n    > arr = { 'length': 2, '0': 1.0, '1': 2.0 };\n    > out = shift( arr )\n    [ { 'length': 1, '0': 2.0 }, 1.0 ]\n\n    See Also\n    --------\n    pop, push, unshift\n","shuffle":"\nshuffle( arr[, options] )\n    Shuffles elements of an array-like object.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Array-like object to shuffle.\n\n    options: Object (optional)\n        Options.\n\n    options.copy: string (optional)\n        String indicating whether to return a copy (`deep`,`shallow` or `none`).\n        Default: `'shallow'`.\n\n    Returns\n    -------\n    out: ArrayLike\n        Shuffled array-like object.\n\n    Examples\n    --------\n    > var data = [ 1, 2, 3 ];\n    > var out = shuffle( data )\n    e.g., [ 3, 1, 2 ]\n    > out = shuffle( data, { 'copy': 'none' } );\n    > var bool = ( data === out )\n    true\n\n\nshuffle.factory( [options] )\n    Returns a function to shuffle elements of array-like objects.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer (optional)\n        Integer-valued seed.\n\n    options.copy: string (optional)\n        String indicating whether to return a copy (`deep`,`shallow` or `none`).\n        Default: `'shallow'`.\n\n    Returns\n    -------\n    fcn: Function\n        Shuffle function.\n\n    Examples\n    --------\n    > var myshuffle = shuffle.factory();\n\n    // Set a seed:\n    > myshuffle = shuffle.factory({ 'seed': 239 });\n    > var arr = [ 0, 1, 2, 3, 4 ];\n    > var out = myshuffle( arr )\n    e.g., [ 3, 4, 1, 0, 2 ]\n\n    // Use a different copy strategy:\n    > myshuffle = shuffle.factory({ 'copy': 'none', 'seed': 867 });\n\n    // Created shuffle function mutates input array by default:\n    > arr = [ 1, 2, 3, 4, 5, 6 ];\n    > out = myshuffle( arr );\n    > var bool = ( arr === out )\n    true\n    // Default option can be overridden:\n    > arr = [ 1, 2, 3, 4 ];\n    > out = myshuffle( arr, { 'copy': 'shallow' } );\n    > bool = ( arr === out )\n    false\n\n    See Also\n    --------\n    sample\n","shuffle.factory":"\nshuffle.factory( [options] )\n    Returns a function to shuffle elements of array-like objects.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer (optional)\n        Integer-valued seed.\n\n    options.copy: string (optional)\n        String indicating whether to return a copy (`deep`,`shallow` or `none`).\n        Default: `'shallow'`.\n\n    Returns\n    -------\n    fcn: Function\n        Shuffle function.\n\n    Examples\n    --------\n    > var myshuffle = shuffle.factory();\n\n    // Set a seed:\n    > myshuffle = shuffle.factory({ 'seed': 239 });\n    > var arr = [ 0, 1, 2, 3, 4 ];\n    > var out = myshuffle( arr )\n    e.g., [ 3, 4, 1, 0, 2 ]\n\n    // Use a different copy strategy:\n    > myshuffle = shuffle.factory({ 'copy': 'none', 'seed': 867 });\n\n    // Created shuffle function mutates input array by default:\n    > arr = [ 1, 2, 3, 4, 5, 6 ];\n    > out = myshuffle( arr );\n    > var bool = ( arr === out )\n    true\n    // Default option can be overridden:\n    > arr = [ 1, 2, 3, 4 ];\n    > out = myshuffle( arr, { 'copy': 'shallow' } );\n    > bool = ( arr === out )\n    false\n\n    See Also\n    --------\n    sample","sizeOf":"\nsizeOf( dtype )\n    Returns the size (in bytes) of the canonical binary representation of a\n    specified numeric type.\n\n    The following numeric types are supported:\n\n    - float64: double-precision floating-point numbers.\n    - float32: single-precision floating-point numbers.\n    - float16: half-precision floating-point numbers.\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n    - complex128: 128-bit complex numbers.\n    - complex64: 64-bit complex numbers.\n\n    Parameters\n    ----------\n    dtype: string\n        Numeric type.\n\n    Returns\n    -------\n    out: number\n        Size (in bytes).\n\n    Examples\n    --------\n    > var s = sizeOf( 'int8' )\n    1\n    > s = sizeOf( 'uint32' )\n    4\n\n    See Also\n    --------\n    realmax, typemax\n","Slice":"\nSlice( [stop] )\n    Returns a Slice.\n\n    Parameters\n    ----------\n    stop: integer|null|undefined (optional)\n        Ending index (exclusive).\n\n    Returns\n    -------\n    s: Slice\n        Slice instance.\n\n    Examples\n    --------\n    > var s = new Slice();\n    > s = new Slice( 10 );\n\n\nSlice( start, stop[, step] )\n    Returns a Slice.\n\n    Parameters\n    ----------\n    start: integer|null|undefined\n        Starting index (inclusive).\n\n    stop: integer|null|undefined\n        Ending index (exclusive).\n\n    step: integer|null|undefined (optional)\n        Index increment. A numeric index increment argument should be a non-zero\n        integer value. Default: null.\n\n    Returns\n    -------\n    s: Slice\n        Slice instance.\n\n    Examples\n    --------\n    > var s = new Slice( 2, 10 );\n    > s = new Slice( 2, 10, 1 );\n\n\nSlice.prototype.start\n    Read-only property returning the starting slice index.\n\n    Returns\n    -------\n    start: integer|null\n        Starting index.\n\n    Examples\n    --------\n    > var s = new Slice( 10 );\n    > s.start\n    null\n    > s = new Slice( 2, 10 );\n    > s.start\n    2\n\n\nSlice.prototype.stop\n    Read-only property returning the ending slice index.\n\n    Returns\n    -------\n    stop: integer|null\n        Ending index.\n\n    Examples\n    --------\n    > var s = new Slice( 10 );\n    > s.stop\n    10\n    > s = new Slice( 2, 10 );\n    > s.stop\n    10\n\n\nSlice.prototype.step\n    Read-only property returning the index increment.\n\n    Returns\n    -------\n    step: integer|null\n        Index increment.\n\n    Examples\n    --------\n    > var s = new Slice( 10 );\n    > s.step\n    null\n    > s = new Slice( 2, 10 );\n    > s.step\n    null\n    > s = new Slice( 2, 10, 1 );\n    > s.step\n    1\n\n\nSlice.prototype.toString()\n    Serializes a Slice as a string.\n\n    Returns\n    -------\n    str: string\n        Serialized Slice string.\n\n    Examples\n    --------\n    > var s = new Slice( 10 );\n    > s.toString()\n    'Slice(null,10,null)'\n    > s = new Slice( 2, 10, 1 );\n    > s.toString()\n    'Slice(2,10,1)'\n\n\nSlice.prototype.toJSON()\n    Serializes a Slice as a JSON object.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var s = new Slice( 10 );\n    > s.toJSON()\n    { 'type': 'Slice', 'data': [ null, 10, null ] }\n    > s = new Slice( 2, 10, 1 );\n    > s.toJSON()\n    { 'type': 'Slice', 'data': [ 2, 10, 1 ] }\n\n    See Also\n    --------\n    ndarray, MultiSlice\n","Slice.prototype.start":"\nSlice.prototype.start\n    Read-only property returning the starting slice index.\n\n    Returns\n    -------\n    start: integer|null\n        Starting index.\n\n    Examples\n    --------\n    > var s = new Slice( 10 );\n    > s.start\n    null\n    > s = new Slice( 2, 10 );\n    > s.start\n    2","Slice.prototype.stop":"\nSlice.prototype.stop\n    Read-only property returning the ending slice index.\n\n    Returns\n    -------\n    stop: integer|null\n        Ending index.\n\n    Examples\n    --------\n    > var s = new Slice( 10 );\n    > s.stop\n    10\n    > s = new Slice( 2, 10 );\n    > s.stop\n    10","Slice.prototype.step":"\nSlice.prototype.step\n    Read-only property returning the index increment.\n\n    Returns\n    -------\n    step: integer|null\n        Index increment.\n\n    Examples\n    --------\n    > var s = new Slice( 10 );\n    > s.step\n    null\n    > s = new Slice( 2, 10 );\n    > s.step\n    null\n    > s = new Slice( 2, 10, 1 );\n    > s.step\n    1","Slice.prototype.toString":"\nSlice.prototype.toString()\n    Serializes a Slice as a string.\n\n    Returns\n    -------\n    str: string\n        Serialized Slice string.\n\n    Examples\n    --------\n    > var s = new Slice( 10 );\n    > s.toString()\n    'Slice(null,10,null)'\n    > s = new Slice( 2, 10, 1 );\n    > s.toString()\n    'Slice(2,10,1)'","Slice.prototype.toJSON":"\nSlice.prototype.toJSON()\n    Serializes a Slice as a JSON object.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var s = new Slice( 10 );\n    > s.toJSON()\n    { 'type': 'Slice', 'data': [ null, 10, null ] }\n    > s = new Slice( 2, 10, 1 );\n    > s.toJSON()\n    { 'type': 'Slice', 'data': [ 2, 10, 1 ] }\n\n    See Also\n    --------\n    ndarray, MultiSlice","snakecase":"\nsnakecase( str )\n    Converts a string to snake case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Snake-cased string.\n\n    Examples\n    --------\n    > var out = snakecase( 'Hello World!' )\n    'hello_world'\n    > out = snakecase( 'I am a tiny little teapot' )\n    'i_am_a_tiny_little_teapot'\n\n    See Also\n    --------\n    camelcase, constantcase, kebabcase, pascalcase","some":"\nsome( collection, n )\n    Tests whether at least `n` elements in a collection are truthy.\n\n    The function immediately returns upon finding `n` truthy elements.\n\n    If provided an empty collection, the function returns `false`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    n: number\n        Minimum number of truthy elements.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if a collection contains at least `n` truthy\n        elements; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > var arr = [ 0, 0, 1, 2, 3 ];\n    > var bool = some( arr, 3 )\n    true\n\n    See Also\n    --------\n    any, every, forEach, none, someBy\n","someBy":"\nsomeBy( collection, n, predicate[, thisArg ] )\n    Tests whether a collection contains at least `n` elements which pass a test\n    implemented by a predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    The function immediately returns upon finding `n` successful elements.\n\n    If provided an empty collection, the function returns `false`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    n: number\n        Minimum number of successful elements.\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if a collection contains at least `n`\n        successful elements; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function negative( v ) { return ( v < 0 ); };\n    > var arr = [ 1, 2, -3, 4, -1 ];\n    > var bool = someBy( arr, 2, negative )\n    true\n\n    See Also\n    --------\n    anyBy, everyBy, forEach, noneBy, someByAsync, someByRight\n","someByAsync":"\nsomeByAsync( collection, n, [options,] predicate, done )\n    Tests whether a collection contains at least `n` elements which pass a test\n    implemented by a predicate function.\n\n    When invoked, the predicate function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If the\n    predicate function accepts two arguments, the predicate function is\n    provided:\n\n    - value\n    - next\n\n    If the predicate function accepts three arguments, the predicate function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other predicate function signature, the predicate function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - result: test result.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    The function immediately returns upon receiving `n` non-falsy `result`\n    values and calls the `done` callback with `null` as the first argument and\n    `true` as the second argument.\n\n    If all elements fail, the function calls the `done` callback with `null`\n    as the first argument and `false` as the second argument.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    n: number\n        Minimum number of successful elements.\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > someByAsync( arr, 2, predicate, done )\n    1000\n    2500\n    3000\n    false\n\n    // Limit number of concurrent invocations:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 3000, 2500, 1000 ];\n    > someByAsync( arr, 2, opts, predicate, done )\n    2500\n    3000\n    1000\n    false\n\n    // Process sequentially:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 3000, 2500, 1000 ];\n    > someByAsync( arr, 2, opts, predicate, done )\n    3000\n    2500\n    1000\n    false\n\n\nsomeByAsync.factory( [options,] predicate )\n    Returns a function which tests whether a collection contains at least `n`\n    elements which pass a test implemented by a predicate function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = someByAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, 2, done )\n    3000\n    2500\n    1000\n    false\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, 2, done )\n    2000\n    1500\n    1000\n    false\n\n    See Also\n    --------\n    anyByAsync, everyByAsync, forEachAsync, noneByAsync, someBy, someByRightAsync\n","someByAsync.factory":"\nsomeByAsync.factory( [options,] predicate )\n    Returns a function which tests whether a collection contains at least `n`\n    elements which pass a test implemented by a predicate function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = someByAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, 2, done )\n    3000\n    2500\n    1000\n    false\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, 2, done )\n    2000\n    1500\n    1000\n    false\n\n    See Also\n    --------\n    anyByAsync, everyByAsync, forEachAsync, noneByAsync, someBy, someByRightAsync","someByRight":"\nsomeByRight( collection, n, predicate[, thisArg ] )\n    Tests whether a collection contains at least `n` elements which pass a test\n    implemented by a predicate function, iterating from right to left.\n\n    The predicate function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    The function immediately returns upon finding `n` successful elements.\n\n    If provided an empty collection, the function returns `false`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    n: number\n        Minimum number of successful elements.\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if a collection contains at least `n`\n        successful elements; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function negative( v ) { return ( v < 0 ); };\n    > var arr = [ -1, 1, -2, 3, 4 ];\n    > var bool = someByRight( arr, 2, negative )\n    true\n\n    See Also\n    --------\n    anyByRight, everyByRight, forEachRight, noneByRight, someBy, someByRightAsync\n","someByRightAsync":"\nsomeByRightAsync( collection, n, [options,] predicate, done )\n    Tests whether a collection contains at least `n` elements which pass a test\n    implemented by a predicate function, iterating from right to left.\n\n    When invoked, the predicate function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection value.\n\n    The actual number of provided arguments depends on function length. If the\n    predicate function accepts two arguments, the predicate function is\n    provided:\n\n    - value\n    - next\n\n    If the predicate function accepts three arguments, the predicate function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other predicate function signature, the predicate function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - result: test result.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    The function immediately returns upon receiving `n` non-falsy `result`\n    values and calls the `done` callback with `null` as the first argument and\n    `true` as the second argument.\n\n    If all elements fail, the function calls the `done` callback with `null`\n    as the first argument and `false` as the second argument.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    n: number\n        Minimum number of successful elements.\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > someByRightAsync( arr, 2, predicate, done )\n    1000\n    2500\n    3000\n    false\n\n    // Limit number of concurrent invocations:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 1000, 2500, 3000 ];\n    > someByRightAsync( arr, 2, opts, predicate, done )\n    2500\n    3000\n    1000\n    false\n\n    // Process sequentially:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 1000, 2500, 3000 ];\n    > someByRightAsync( arr, 2, opts, predicate, done )\n    3000\n    2500\n    1000\n    false\n\n\nsomeByRightAsync.factory( [options,] predicate )\n    Returns a function which tests whether a collection contains at least `n`\n    elements which pass a test implemented by a predicate function, iterating\n    from right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = someByRightAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, 2, done )\n    3000\n    2500\n    1000\n    false\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, 2, done )\n    2000\n    1500\n    1000\n    false\n\n    See Also\n    --------\n    anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByAsync, someByRight\n","someByRightAsync.factory":"\nsomeByRightAsync.factory( [options,] predicate )\n    Returns a function which tests whether a collection contains at least `n`\n    elements which pass a test implemented by a predicate function, iterating\n    from right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = someByRightAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, 2, done )\n    3000\n    2500\n    1000\n    false\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, 2, done )\n    2000\n    1500\n    1000\n    false\n\n    See Also\n    --------\n    anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByAsync, someByRight","someInBy":"\nsomeInBy( obj, n, predicate[, thisArg ] )\n    Tests whether an object contains at least `n` properties\n    (own and inherited) which pass a test\n    implemented by a predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: object value.\n    - key: object key.\n    - obj: the input object.\n\n    The function immediately returns upon finding `n` successful properties.\n\n    If provided an empty object, the function returns `false`.\n\n    Parameters\n    ----------\n    obj: Object\n        Input object over which to iterate.\n\n    n: number\n        Minimum number of successful properties.\n\n    predicate: Function\n        Test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if an object contains at least `n`\n        successful properties; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function negative( v ) { return ( v < 0 ); };\n    > var obj = { 'a': 1, 'b': 2, 'c': -3, 'd': 4, 'e': -1 };\n    > var bool = someInBy( obj, 2, negative )\n    true\n\n    See Also\n    --------\n    anyInBy, everyInBy, someBy, someOwnBy","someOwnBy":"\nsomeOwnBy( obj, n, predicate[, thisArg ] )\n    Tests whether some `own` properties of a provided object\n    satisfy a predicate function for at least `n` properties.\n\n    The predicate function is provided three arguments:\n\n    - value: object value.\n    - key: object key.\n    - obj: the input object.\n\n    The function immediately returns upon finding `n` successful properties.\n\n    If provided an empty object, the function returns `false`.\n\n    Parameters\n    ----------\n    obj: Object\n        Input object over which to iterate.\n\n    n: number\n        Minimum number of successful properties.\n\n    predicate: Function\n        Test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if an object's own properties satisfy a\n        predicate for at least `n` properties; otherwise, the function\n        returns `false`.\n\n    Examples\n    --------\n    > function negative( v ) { return ( v < 0 ); };\n    > var obj = { a: 1, b: 2, c: -3, d: 4, e: -1 };\n    > var bool = someOwnBy( obj, 2, negative )\n    true\n\n    See Also\n    --------\n    anyOwnBy, everyOwnBy, someBy, someInBy","SOTU":"\nSOTU( [options] )\n    Returns State of the Union (SOTU) addresses.\n\n    Each State of the Union address is represented by an object with the\n    following fields:\n\n    - year: speech year.\n    - name: President name.\n    - party: the President's political party.\n    - text: speech text.\n\n    The following political parties are recognized:\n\n    - Democratic\n    - Republican\n    - Democratic-Republican\n    - Federalist\n    - National Union\n    - Whig\n    - Whig & Democratic\n    - none\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.name: String|Array<string> (optional)\n        President name(s).\n\n    options.party: String|Array<string> (optional)\n        Political party (or parties).\n\n    options.year: integer|Array<integer> (optional)\n        Year(s).\n\n    options.range: Array<integer> (optional)\n        Two-element array specifying a year range.\n\n    Returns\n    -------\n    out: Array<Object>\n        State of the Union addresses.\n\n    Examples\n    --------\n    > var out = SOTU()\n    [ {...}, {...}, ... ]\n\n    // Retrieve addresses by one or more Presidents...\n    > var opts = { 'name': 'Barack Obama' };\n    > out = SOTU( opts )\n    [ {...}, {...}, ... ]\n\n    // Retrieve addresses by one or more political parties...\n    > opts = { 'party': [ 'Democratic', 'Federalist' ] };\n    > out = SOTU( opts )\n    [ {...}, {...}, ... ]\n\n    // Retrieve addresses from one or more years...\n    > opts = { 'year': [ 2008, 2009, 2011 ] };\n    > out = SOTU( opts )\n    [ {...}, {...}, {...} ]\n\n    // Retrieve addresses from a range of consecutive years...\n    > opts = { 'range': [ 2008, 2016 ] }\n    > out = SOTU( opts )\n    [ {...}, {...}, ... ]\n\n","SPACHE_REVISED":"\nSPACHE_REVISED()\n    Returns a list of simple American-English words (revised Spache).\n\n    Returns\n    -------\n    out: Array<string>\n        List of simple American-English words.\n\n    Examples\n    --------\n    > var list = SPACHE_REVISED()\n    [ 'a', 'able', 'about', 'above', ... ]\n\n    References\n    ----------\n    - Spache, George. 1953. \"A New Readability Formula for Primary-Grade Reading\n    Materials.\" *The Elementary School Journal* 53 (7): 410–13. doi:10.1086/\n    458513.\n    - Klare, George R. 1974. \"Assessing Readability.\" *Reading Research\n    Quarterly* 10 (1). Wiley, International Reading Association: 62–102.\n    <http://www.jstor.org/stable/747086>.\n    - Stone, Clarence R. 1956. \"Measuring Difficulty of Primary Reading\n    Material: A Constructive Criticism of Spache's Measure.\" *The Elementary\n    School Journal* 57 (1). University of Chicago Press: 36–41.\n    <http://www.jstor.org/stable/999700>.\n    - Perera, Katherine. 2012. \"The assessment of linguistic difficulty in\n    reading material.\" In *Linguistics and the Teacher*, edited by Ronald\n    Carter, 101–13. Routledge Library Editions: Education. Taylor & Francis.\n    <https://books.google.com/books?id=oNXFQ9Gn6XIC>.\n\n","SPAM_ASSASSIN":"\nSPAM_ASSASSIN()\n    Returns the Spam Assassin public mail corpus.\n\n    Each array element has the following fields:\n\n    - id: message id (relative to message group).\n    - group: message group.\n    - checksum: object containing checksum info.\n    - text: message text (including headers).\n\n    The message group may be one of the following:\n\n    - easy-ham-1: easier to detect non-spam e-mails (2500 messages).\n    - easy-ham-2: easier to detect non-spam e-mails collected at a later date\n      (1400 messages).\n    - hard-ham-1: harder to detect non-spam e-mails (250 messages).\n    - spam-1: spam e-mails (500 messages).\n    - spam-2: spam e-mails collected at a later date (1396 messages).\n\n    The checksum object contains the following fields:\n\n    - type: checksum type (e.g., MD5).\n    - value: checksum value.\n\n    Returns\n    -------\n    out: Array<Object>\n        Corpus.\n\n    Examples\n    --------\n    > var data = SPAM_ASSASSIN()\n    [ {...}, {...}, ... ]\n\n","SparklineBase":"\nSparklineBase( [data,] [options] )\n    Returns a Sparkline instance.\n\n    This constructor is a base Sparkline constructor from which constructors\n    tailored to generating particular types of Sparkline graphics should be\n    derived.\n\n    At a minimum, descendants should implement a private `_render()` method\n    which will be automatically invoked by the public `render()` method.\n\n    The `data` argument takes precedence over the `data` option.\n\n    Parameters\n    ----------\n    data: ArrayLike|ndarray (optional)\n        Sparkline data.\n\n    options: Object (optional)\n        Options.\n\n    options.autoRender: boolean (optional)\n        Boolean indicating whether to re-render on a 'change' event. Default:\n        false.\n\n    options.bufferSize: integer|null (optional)\n        Data buffer size. If provided, data is kept in a first-in first-out\n        (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n    options.data: ArrayLike|ndarray (optional)\n        Sparkline data.\n\n    options.description: string (optional)\n        Sparkline description.\n\n    options.isDefined: Function (optional)\n        An accessor function indicating whether a datum is defined.\n\n    options.label: string (optional)\n        Data label.\n\n    Returns\n    -------\n    sparkline: Sparkline\n        Sparkline instance.\n\n    sparkline.autoRender\n        Rendering mode. If `true`, an instance renders on each 'change' event;\n        otherwise, rendering must be triggered manually.\n\n    sparkline.bufferSize\n        Data buffer size.\n\n    sparkline.description\n        Sparkline description.\n\n    sparkline.data\n        Sparkline data.\n\n    sparkline.label\n        Data label.\n\n    sparkline.isDefined( d, i )\n        An accessor function which defines whether a datum is defined. This\n        accessor is used to define how missing values are encoded. The default\n        behavior is to ignore values which are `NaN`.\n\n    sparkline.render()\n        Renders a sparkline. This method calls `_render()` which must be\n        implemented by instances and child classes. The default behavior is\n        throw an error.\n\n    Examples\n    --------\n    > var sparkline = new SparklineBase()\n    <Sparkline>\n\n    // Provide sparkline data at instantiation:\n    > var data = [ 1, 2, 3 ];\n    > sparkline = new SparklineBase( data )\n    <Sparkline>\n\n    See Also\n    --------\n    plot, Plot, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeWinLossChartSparkline\n","sparsearray2iterator":"\nsparsearray2iterator( src[, mapFcn[, thisArg]] )\n    Returns an iterator which iterates over the elements of a sparse array-like\n    object.\n\n    The returned iterator skips elements which are undefined.\n\n    When invoked, an input function is provided three arguments:\n\n    - value: iterated value.\n    - index: iterated value index.\n    - src: source array-like object.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an array's `@@iterator` method, regardless of whether this method is\n    defined. To convert an array to an implementation defined iterator, invoke\n    this method directly.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Sparse array-like object from which to create the iterator.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = sparsearray2iterator( [ 1, , 3, 4 ] );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    3\n\n    See Also\n    --------\n    iterator2array, array2iterator, sparsearray2iteratorRight\n","sparsearray2iteratorRight":"\nsparsearray2iteratorRight( src[, mapFcn[, thisArg]] )\n    Returns an iterator which iterates from right to left over the elements of a\n    sparse array-like object.\n\n    The returned iterator skips elements which are undefined.\n\n    When invoked, an input function is provided three arguments:\n\n    - value: iterated value.\n    - index: iterated value index.\n    - src: source array-like object.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an array's `@@iterator` method, regardless of whether this method is\n    defined. To convert an array to an implementation defined iterator, invoke\n    this method directly.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Sparse array-like object from which to create the iterator.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = sparsearray2iteratorRight( [ 1, 2, , 4 ] );\n    > var v = it.next().value\n    4\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    iterator2array, array2iteratorRight, sparsearray2iterator\n","splitStream":"\nsplitStream( [options] )\n    Returns a transform stream which splits streamed data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Separator used to split streamed data. A separator may be either a\n        regular expression or a string. A separator which is a regular\n        expression containing a matching group will result in the separator\n        being retained in the output stream.Default: /\\r?\\n/.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.writableObjectMode: boolean (optional)\n        Specifies whether the writable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream.\n\n    Examples\n    --------\n    > var s = splitStream();\n    > s.write( 'a\\nb\\nc' );\n    > s.end();\n\n\nsplitStream.factory( [options] )\n    Returns a function for creating transform streams for splitting streamed\n    data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Separator used to split streamed data. A separator may be either a\n        regular expression or a string. A separator which is a regular\n        expression containing a matching group will result in the separator\n        being retained in the output stream. Default: /\\r?\\n/.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.writableObjectMode: boolean (optional)\n        Specifies whether the writable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    createStream: Function\n        Function for creating transform streams.\n\n    Examples\n    --------\n    > var opts = { 'highWaterMark': 64 };\n    > var createStream = splitStream.factory( opts );\n    > var s = createStream();\n    > s.write( 'a\\nb\\nc' );\n    > s.end();\n\n\nsplitStream.objectMode( [options] )\n    Returns an \"objectMode\" transform stream for splitting streamed data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Separator used to split streamed data. A separator may be either a\n        regular expression or a string. A separator which is a regular\n        expression containing a matching group will result in the separator\n        being retained in the output stream. Default: /\\r?\\n/.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.writableObjectMode: boolean (optional)\n        Specifies whether the writable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > var s = splitStream.objectMode();\n    > s.write( 'a\\nb\\c' );\n    > s.end();\n\n    See Also\n    --------\n    joinStream\n","splitStream.factory":"\nsplitStream.factory( [options] )\n    Returns a function for creating transform streams for splitting streamed\n    data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Separator used to split streamed data. A separator may be either a\n        regular expression or a string. A separator which is a regular\n        expression containing a matching group will result in the separator\n        being retained in the output stream. Default: /\\r?\\n/.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.writableObjectMode: boolean (optional)\n        Specifies whether the writable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    createStream: Function\n        Function for creating transform streams.\n\n    Examples\n    --------\n    > var opts = { 'highWaterMark': 64 };\n    > var createStream = splitStream.factory( opts );\n    > var s = createStream();\n    > s.write( 'a\\nb\\nc' );\n    > s.end();","splitStream.objectMode":"\nsplitStream.objectMode( [options] )\n    Returns an \"objectMode\" transform stream for splitting streamed data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Separator used to split streamed data. A separator may be either a\n        regular expression or a string. A separator which is a regular\n        expression containing a matching group will result in the separator\n        being retained in the output stream. Default: /\\r?\\n/.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.writableObjectMode: boolean (optional)\n        Specifies whether the writable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > var s = splitStream.objectMode();\n    > s.write( 'a\\nb\\c' );\n    > s.end();\n\n    See Also\n    --------\n    joinStream","SQRT_EPS":"\nSQRT_EPS\n    Square root of double-precision floating-point epsilon.\n\n    Examples\n    --------\n    > SQRT_EPS\n    0.14901161193847656e-7\n\n    See Also\n    --------\n    EPS\n","SQRT_HALF":"\nSQRT_HALF\n    Square root of `1/2`.\n\n    Examples\n    --------\n    > SQRT_HALF\n    0.7071067811865476\n\n    See Also\n    --------\n    LN_HALF\n","SQRT_HALF_PI":"\nSQRT_HALF_PI\n    Square root of the mathematical constant `π` divided by `2`.\n\n    Examples\n    --------\n    > SQRT_HALF_PI\n    1.2533141373155003\n\n    See Also\n    --------\n    PI\n","SQRT_PHI":"\nSQRT_PHI\n    Square root of the golden ratio.\n\n    Examples\n    --------\n    > SQRT_PHI\n    1.272019649514069\n\n    See Also\n    --------\n    PHI\n","SQRT_PI":"\nSQRT_PI\n    Square root of the mathematical constant `π`.\n\n    Examples\n    --------\n    > SQRT_PI\n    1.7724538509055160\n\n    See Also\n    --------\n    PI\n","SQRT_THREE":"\nSQRT_THREE\n    Square root of `3`.\n\n    Examples\n    --------\n    > SQRT_THREE\n    1.7320508075688772\n\n","SQRT_TWO":"\nSQRT_TWO\n    Square root of `2`.\n\n    Examples\n    --------\n    > SQRT_TWO\n    1.4142135623730951\n\n    See Also\n    --------\n    LN2\n","SQRT_TWO_PI":"\nSQRT_TWO_PI\n    Square root of the mathematical constant `π` times `2`.\n\n    Examples\n    --------\n    > SQRT_TWO_PI\n    2.5066282746310007\n\n    See Also\n    --------\n    TWO_PI\n","SSA_US_BIRTHS_2000_2014":"\nSSA_US_BIRTHS_2000_2014()\n    Returns US birth data from 2000 to 2014, as provided by the Social Security\n    Administration.\n\n    Returns\n    -------\n    out: Array<Object>\n        Birth data.\n\n    Examples\n    --------\n    > var data = SSA_US_BIRTHS_2000_2014()\n    [ {...}, ... ]\n\n    See Also\n    --------\n    CDC_NCHS_US_BIRTHS_1969_1988, CDC_NCHS_US_BIRTHS_1994_2003\n","sswap":"\nsswap( x, y[, dim] )\n    Interchanges two single-precision floating-point vectors.\n\n    For multi-dimensional input arrays, the function performs batched\n    computation, such that the function interchanges each pair of vectors in `x`\n    and `y` according to the specified dimension index.\n\n    Both input arrays must have the same shape.\n\n    Parameters\n    ----------\n    x: ndarray\n        First input array. Must have a 'float32' data type. Must have at least\n        one dimension and must have the same shape as the second input array.\n\n    y: ndarray\n        Second input array. Must have a 'float32' data type. Must have at least\n        one dimension and must have the same shape as the first input array.\n\n    dim: integer (optional)\n        Dimension index along which to interchange vectors. Must be a negative\n        integer. Negative indices are resolved relative to the last array\n        dimension, with the last dimension corresponding to `-1`. Default: -1.\n\n    Returns\n    -------\n    y: ndarray\n        The second input array `y`.\n\n    Examples\n    --------\n    > var x = array( new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n    > var y = array( new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n    > sswap( x, y );\n    > x.data\n    <Float32Array>[ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n    > y.data\n    <Float32Array>[ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n    See Also\n    --------\n    base.strided.sswap, dswap, gswap\n","Stack":"\nStack()\n    Stack constructor.\n\n    A stack is also referred to as a \"last-in-first-out\" queue.\n\n    Returns\n    -------\n    stack: Object\n        Stack data structure.\n\n    stack.clear: Function\n        Clears the stack.\n\n    stack.first: Function\n        Returns the \"newest\" stack value (i.e., the value which is \"first-out\").\n        If the stack is empty, the returned value is `undefined`.\n\n    stack.iterator: Function\n        Returns an iterator for iterating over a stack. If an environment\n        supports Symbol.iterator, the returned iterator is iterable. Note that,\n        in order to prevent confusion arising from stack mutation during\n        iteration, a returned iterator **always** iterates over a stack\n        \"snapshot\", which is defined as the list of stack elements at the time\n        of the method's invocation.\n\n    stack.last: Function\n        Returns the \"oldest\" stack value (i.e., the value which is \"last-out\").\n        If the stack is empty, the returned value is `undefined`.\n\n    stack.length: integer\n        Stack length.\n\n    stack.pop: Function\n        Removes and returns the current \"first-out\" value from the stack. If the\n        stack is empty, the returned value is `undefined`.\n\n    stack.push: Function\n        Adds a value to the stack.\n\n    stack.toArray: Function\n        Returns an array of stack values.\n\n    stack.toJSON: Function\n        Serializes a stack as JSON.\n\n    Examples\n    --------\n    > var s = Stack();\n    > s.push( 'foo' ).push( 'bar' );\n    > s.length\n    2\n    > s.pop()\n    'bar'\n    > s.length\n    1\n    > s.pop()\n    'foo'\n    > s.length\n    0\n\n    See Also\n    --------\n    FIFO\n","standalone2pkg":"\nstandalone2pkg( pkg )\n    Returns the internal package name associated with a provided standalone\n    package name.\n\n    Parameters\n    ----------\n    pkg: string\n        Standalone package name.\n\n    Returns\n    -------\n    out: string|null\n        Internal package name.\n\n    Examples\n    --------\n    > var v = standalone2pkg( '@stdlib/math-base-special-sin' )\n    '@stdlib/math/base/special/sin'\n\n    See Also\n    --------\n    alias2standalone, pkg2alias, pkg2standalone\n","STANDARD_CARD_DECK":"\nSTANDARD_CARD_DECK()\n    Returns a string array containing two or three letter abbreviations for each\n    card in a standard 52-card deck.\n\n    Abbreviation format: <card><suit>\n\n    Cards: A, 2, 3, 4, 5, 6, 7, 8, 9, 10, J, Q, K, where\n\n    - A: ace\n    - J: jack\n    - Q: queen\n    - K: king\n\n    Suit abbreviations:\n\n    - C: clubs\n    - D: diamonds\n    - H: hearts\n    - S: spades\n\n    Returns\n    -------\n    out: Array<string>\n        List of cards.\n\n    Examples\n    --------\n    > var list = STANDARD_CARD_DECK()\n    [ 'AC', '2C', '3C', ... ]\n\n","startcase":"\nstartcase( str )\n    Capitalizes the first letter of each word in an input string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        String containing words where each first letter is capitalized.\n\n    Examples\n    --------\n    > var out = startcase( 'beep boop' )\n    'Beep Boop'\n\n    See Also\n    --------\n    lowercase, uppercase\n","startsWith":"\nstartsWith( str, search[, position] )\n    Tests if a string starts with the characters of another string.\n\n    If provided an empty search string, the function always returns `true`.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search string.\n\n    position: integer (optional)\n        Position at which to start searching for `search`. If less than `0`, the\n        start position is determined relative to the end of the input string.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a string starts with the characters of\n        another string.\n\n    Examples\n    --------\n    > var bool = startsWith( 'Beep', 'Be' )\n    true\n    > bool = startsWith( 'Beep', 'ep' )\n    false\n    > bool = startsWith( 'Beep', 'ee', 1 )\n    true\n    > bool = startsWith( 'Beep', 'ee', -3 )\n    true\n    > bool = startsWith( 'Beep', '' )\n    true\n\n    See Also\n    --------\n    endsWith\n","STOPWORDS_EN":"\nSTOPWORDS_EN()\n    Returns a list of English stop words.\n\n    Returns\n    -------\n    out: Array<string>\n        List of stop words.\n\n    Examples\n    --------\n    > var list = STOPWORDS_EN()\n    [ 'a', 'about', 'above', 'across', ... ]\n\n","strided.abs":"\nstrided.abs( N, dtypeX, x, strideX, dtypeY, y, strideY )\n    Computes the absolute value for each element in a strided array `x` and\n    assigns the results to elements in a strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs( x.length, 'float64', x, 1, 'float64', y, 1 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs( 2, x, 2, y, -1 )\n    <Float64Array>[ 3.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.abs( 2, 'float64', x1, -2, 'float64', y1, 1 )\n    <Float64Array>[ 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nstrided.abs.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the absolute value for each element in a strided array `x` and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    strided.abs2, base.strided.dabs, base.strided.sabs\n","strided.abs.ndarray":"\nstrided.abs.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the absolute value for each element in a strided array `x` and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    strided.abs2, base.strided.dabs, base.strided.sabs","strided.abs2":"\nstrided.abs2( N, dtypeX, x, strideX, dtypeY, y, strideY )\n    Computes the squared absolute value for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs2( x.length, 'float64', x, 1, 'float64', y, 1 )\n    <Float64Array>[ 4.0, 1.0, 9.0, 25.0 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs2( 2, 'float64', x, 2, 'float64', y, -1 )\n    <Float64Array>[ 9.0, 4.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.abs2( 2, 'float64', x1, -2, 'float64', y1, 1 )\n    <Float64Array>[ 25.0, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 25.0, 1.0 ]\n\n\nstrided.abs2.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the squared absolute value for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs2.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 4.0, 1.0, 9.0, 25.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs2.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 25.0, 1.0 ]\n\n    See Also\n    --------\n    strided.abs, base.strided.dabs2, base.strided.sabs2\n","strided.abs2.ndarray":"\nstrided.abs2.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the squared absolute value for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs2.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 4.0, 1.0, 9.0, 25.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs2.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 25.0, 1.0 ]\n\n    See Also\n    --------\n    strided.abs, base.strided.dabs2, base.strided.sabs2","strided.abs2By":"\nstrided.abs2By( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the squared absolute value of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -1.0, -2.0, -3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.abs2By( x.length, x, 1, y, 1, clbk )\n    [ 1.0, 4.0, 9.0, 16.0 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.abs2By( 2, x, 2, y, -1, clbk )\n    [ 9.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.abs2By( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ 16.0, 4.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 16.0, 4.0 ]\n\n\nstrided.abs2By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the squared absolute value of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -1.0, -2.0, -3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.abs2By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 1.0, 4.0, 9.0, 16.0 ]\n\n    // Advanced indexing:\n    > x = [ -1.0, -2.0, -3.0, -4.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.abs2By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, 16.0, 4.0 ]\n\n    See Also\n    --------\n    strided.absBy, strided.abs2\n","strided.abs2By.ndarray":"\nstrided.abs2By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the squared absolute value of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -1.0, -2.0, -3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.abs2By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 1.0, 4.0, 9.0, 16.0 ]\n\n    // Advanced indexing:\n    > x = [ -1.0, -2.0, -3.0, -4.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.abs2By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, 16.0, 4.0 ]\n\n    See Also\n    --------\n    strided.absBy, strided.abs2","strided.absBy":"\nstrided.absBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the absolute value of each element retrieved from a strided input\n    array `x` via a callback function and assigns each result to an element in a\n    strided output array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v * 2.0; };\n    > strided.absBy( x.length, x, 1, y, 1, clbk )\n    [ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.absBy( 2, x, 2, y, -1, clbk )\n    [ 6.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.absBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ 8.0, 4.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 8.0, 4.0 ]\n\n\nstrided.absBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the absolute value of each element retrieved from a strided input\n    array `x` via a callback function and assigns each result to an element in a\n    strided output array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v * 2.0; };\n    > strided.absBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.absBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, 8.0, 4.0 ]\n\n    See Also\n    --------\n    strided.abs, strided.abs2By\n","strided.absBy.ndarray":"\nstrided.absBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the absolute value of each element retrieved from a strided input\n    array `x` via a callback function and assigns each result to an element in a\n    strided output array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v * 2.0; };\n    > strided.absBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.absBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, 8.0, 4.0 ]\n\n    See Also\n    --------\n    strided.abs, strided.abs2By","strided.acosBy":"\nstrided.acosBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the arccosine of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 0.707, 0.866, -0.707 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acosBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, ~0.786, ~0.524, ~2.356 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acosBy( 2, x, 2, y, -1, clbk )\n    [ ~0.524, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 0.707, 0.866, -0.707 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.acosBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~2.356, ~0.786 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~2.356, ~0.786 ]\n\n\nstrided.acosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the arccosine of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 0.707, 0.866, -0.707 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~0.786, ~0.524, ~2.356 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 0.707, 0.866, -0.707 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~2.356, ~0.786 ]\n\n","strided.acosBy.ndarray":"\nstrided.acosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the arccosine of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 0.707, 0.866, -0.707 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~0.786, ~0.524, ~2.356 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 0.707, 0.866, -0.707 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~2.356, ~0.786 ]","strided.acoshBy":"\nstrided.acoshBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the hyperbolic arccosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 1.5, 2.0, 2.5 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acoshBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, ~0.962, ~1.317, ~1.567 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acoshBy( 2, x, 2, y, -1, clbk )\n    [ ~1.317, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 1.5, 2.0, 2.5 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.acoshBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~1.567, ~0.962 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~1.567, ~0.962 ]\n\n\nstrided.acoshBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the hyperbolic arccosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 1.5, 2.0, 2.5 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acoshBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~0.962, ~1.317, ~1.567 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 1.5, 2.0, 2.5 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acoshBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~1.567, ~0.962 ]\n\n","strided.acoshBy.ndarray":"\nstrided.acoshBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the hyperbolic arccosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 1.5, 2.0, 2.5 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acoshBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~0.962, ~1.317, ~1.567 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 1.5, 2.0, 2.5 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acoshBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~1.567, ~0.962 ]","strided.acotBy":"\nstrided.acotBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the inverse cotangent of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -2.5, -1.5, -0.5, 0.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acotBy( x.length, x, 1, y, 1, clbk )\n    [ ~-0.381, ~-0.588, ~-1.107, ~1.571 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acotBy( 2, x, 2, y, -1, clbk )\n    [ ~-1.107, ~-0.381, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -2.5, -1.5, -0.5, 0.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.acotBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~1.571, ~-0.588 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~1.571, ~-0.588 ]\n\n\nstrided.acotBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse cotangent of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -2.5, -1.5, -0.5, 0.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acotBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ ~-0.381, ~-0.588, ~-1.107, ~1.571 ]\n\n    // Advanced indexing:\n    > x = [ -2.5, -1.5, -0.5, 0.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acotBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~1.571, ~-0.588 ]\n\n","strided.acotBy.ndarray":"\nstrided.acotBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse cotangent of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -2.5, -1.5, -0.5, 0.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acotBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ ~-0.381, ~-0.588, ~-1.107, ~1.571 ]\n\n    // Advanced indexing:\n    > x = [ -2.5, -1.5, -0.5, 0.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acotBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~1.571, ~-0.588 ]","strided.acothBy":"\nstrided.acothBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the inverse hyperbolic cotangent of each element retrieved from an\n    input strided array `x` via a callback function and assigns each result to\n    an element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -5.0, -4.0, -3.0, -1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acothBy( x.length, x, 1, y, 1, clbk )\n    [ ~-0.203, ~-0.255, ~-0.347, -Infinity ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acothBy( 2, x, 2, y, -1, clbk )\n    [ ~-0.347, ~-0.203, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -5.0, -4.0, -3.0, -1.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.acothBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ -Infinity, ~-0.255 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, -Infinity, ~-0.255 ]\n\n\nstrided.acothBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse hyperbolic cotangent of each element retrieved from an\n    input strided array `x` via a callback function and assigns each result to\n    an element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -5.0, -4.0, -3.0, -1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acothBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ ~-0.203, ~-0.255, ~-0.347, -Infinity ]\n\n    // Advanced indexing:\n    > x = [ -5.0, -4.0, -3.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acothBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, -Infinity, ~-0.255 ]\n\n","strided.acothBy.ndarray":"\nstrided.acothBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse hyperbolic cotangent of each element retrieved from an\n    input strided array `x` via a callback function and assigns each result to\n    an element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -5.0, -4.0, -3.0, -1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acothBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ ~-0.203, ~-0.255, ~-0.347, -Infinity ]\n\n    // Advanced indexing:\n    > x = [ -5.0, -4.0, -3.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acothBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, -Infinity, ~-0.255 ]","strided.acovercosBy":"\nstrided.acovercosBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the inverse coversed cosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acovercosBy( x.length, x, 1, y, 1, clbk )\n    [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acovercosBy( 2, x, 2, y, -1, clbk )\n    [ ~0.524, ~1.571, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, -1.57, -0.5, -1.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.acovercosBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ 0.0, ~-0.607 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, ~-0.607 ]\n\n\nstrided.acovercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse coversed cosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acovercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -1.57, -0.5, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acovercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, 0.0, ~-0.607 ]\n\n","strided.acovercosBy.ndarray":"\nstrided.acovercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse coversed cosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acovercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -1.57, -0.5, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acovercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, 0.0, ~-0.607 ]","strided.acoversinBy":"\nstrided.acoversinBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the inverse coversed sine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acoversinBy( x.length, x, 1, y, 1, clbk )\n    [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acoversinBy( 2, x, 2, y, -1, clbk )\n    [ ~0.524, ~1.571, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.acoversinBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ 0.0, ~-0.607 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, ~-0.607 ]\n\n\nstrided.acoversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse coversed sine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acoversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.57, 0.5, 1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acoversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, 0.0, ~-0.607 ]\n\n","strided.acoversinBy.ndarray":"\nstrided.acoversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse coversed sine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acoversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.57, 0.5, 1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acoversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, 0.0, ~-0.607 ]","strided.add":"\nstrided.add( N, dx, x, sx, dy, y, sy, dz, z, sz )\n    Adds each element in a strided array `x` to a corresponding element in a\n    strided array `y` and assigns the results to elements in a strided array\n    `z`.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dx: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    dy: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    dz: any\n        Data type for `z`.\n\n    z: ArrayLikeObject\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    Returns\n    -------\n    z: ArrayLikeObject\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var dt = 'float64';\n    > strided.add( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\n    <Float64Array>[ -1.0, 3.0, 6.0, -1.0 ]\n\n    // Using `N` and stride parameters:\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.add( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\n    <Float64Array>[ 1.0, 4.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > strided.add( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\n    <Float64Array>[ -2.0, 5.0 ]\n    > z0\n    <Float64Array>[ 0.0, 0.0, -2.0, 5.0 ]\n\n\nstrided.add.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n    Adds each element in a strided array `x` to a corresponding element in a\n    strided array `y` and assigns the results to elements in a strided array\n    `z` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dx: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    dy: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    dz: any\n        Data type for `z`.\n\n    z: ArrayLikeObject\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    Returns\n    -------\n    z: ArrayLikeObject\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var dt = 'float64';\n    > strided.add.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n    <Float64Array>[ -1.0, 3.0, 6.0, -1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.add.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n    <Float64Array>[ 0.0, 5.0, -2.0, 0.0 ]\n\n    See Also\n    --------\n    strided.mul, strided.sub\n","strided.add.ndarray":"\nstrided.add.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n    Adds each element in a strided array `x` to a corresponding element in a\n    strided array `y` and assigns the results to elements in a strided array\n    `z` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dx: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    dy: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    dz: any\n        Data type for `z`.\n\n    z: ArrayLikeObject\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    Returns\n    -------\n    z: ArrayLikeObject\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var dt = 'float64';\n    > strided.add.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n    <Float64Array>[ -1.0, 3.0, 6.0, -1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.add.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n    <Float64Array>[ 0.0, 5.0, -2.0, 0.0 ]\n\n    See Also\n    --------\n    strided.mul, strided.sub","strided.addBy":"\nstrided.addBy( N, x, sx, y, sy, z, sz, clbk[, thisArg] )\n    Performs element-wise addition of two strided arrays via a callback function\n    and assigns each result to an element in an output strided array.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided four arguments:\n\n    - values: input array elements.\n    - idx: iteration index.\n    - indices: strided array indices (offset + idx*stride).\n    - arrays: input and output arrays.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n    > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( values ) { return values; };\n    > strided.addBy( x.length, x, 1, y, 1, z, 1, clbk )\n    [ 12.0, 14.0, 16.0, 18.0 ]\n\n    // Using `N` and stride parameters:\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.addBy( 2, x, 2, y, -1, z, 1, clbk )\n    [ 13.0, 14.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\n    > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > strided.addBy( 2, x1, -2, y1, 1, z1, 1, clbk )\n    <Float64Array>[ 17.0, 16.0 ]\n    > z0\n    <Float64Array>[ 0.0, 0.0, 17.0, 16.0 ]\n\n\nstrided.addBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n    Performs element-wise addition of two strided arrays via a callback function\n    and assigns each result to an element in an output strided array using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n    > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( values ) { return values; };\n    > strided.addBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n    [ 12.0, 14.0, 16.0, 18.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0 ];\n    > y = [ 11.0, 12.0, 13.0, 14.0 ];\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > var oy = y.length - 1;\n    > var oz = z.length - 1;\n    > strided.addBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n    [ 0.0, 0.0, 17.0, 16.0 ]\n\n    See Also\n    --------\n    strided.add, strided.mulBy, strided.subBy\n","strided.addBy.ndarray":"\nstrided.addBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n    Performs element-wise addition of two strided arrays via a callback function\n    and assigns each result to an element in an output strided array using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n    > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( values ) { return values; };\n    > strided.addBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n    [ 12.0, 14.0, 16.0, 18.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0 ];\n    > y = [ 11.0, 12.0, 13.0, 14.0 ];\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > var oy = y.length - 1;\n    > var oz = z.length - 1;\n    > strided.addBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n    [ 0.0, 0.0, 17.0, 16.0 ]\n\n    See Also\n    --------\n    strided.add, strided.mulBy, strided.subBy","strided.ahavercosBy":"\nstrided.ahavercosBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the inverse half-value versed cosine of each element retrieved from\n    an input strided array `x` via a callback function and assigns each result\n    to an element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.ahavercosBy( x.length, x, 1, y, 1, clbk )\n    [ ~3.142, ~1.571, 0.0, ~2.094 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.ahavercosBy( 2, x, 2, y, -1, clbk )\n    [ 0.0, ~3.142, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 0.5, 1.0, 0.25 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.ahavercosBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~2.094, ~1.571 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~2.094, ~1.571 ]\n\n\nstrided.ahavercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse half-value versed cosine of each element retrieved from\n    an input strided array `x` via a callback function and assigns each result\n    to an element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.ahavercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ ~3.142, ~1.571, 0.0, ~2.094 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 0.5, 1.0, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.ahavercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~2.094, ~1.571 ]\n\n    See Also\n    --------\n    strided.ahaversinBy\n","strided.ahavercosBy.ndarray":"\nstrided.ahavercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse half-value versed cosine of each element retrieved from\n    an input strided array `x` via a callback function and assigns each result\n    to an element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.ahavercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ ~3.142, ~1.571, 0.0, ~2.094 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 0.5, 1.0, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.ahavercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~2.094, ~1.571 ]\n\n    See Also\n    --------\n    strided.ahaversinBy","strided.ahaversinBy":"\nstrided.ahaversinBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the inverse half-value versed sine of each element retrieved from\n    an input strided array `x` via a callback function and assigns each result\n    to an element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.ahaversinBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, ~1.571, ~3.142, ~1.047 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.ahaversinBy( 2, x, 2, y, -1, clbk )\n    [ ~3.142, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 0.5, 1.0, 0.25 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.ahaversinBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~1.047, ~1.571 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~1.047, ~1.571 ]\n\n\nstrided.ahaversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse half-value versed sine of each element retrieved from\n    an input strided array `x` via a callback function and assigns each result\n    to an element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.ahaversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~1.571, ~3.142, ~1.047 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 0.5, 1.0, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.ahaversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~1.047, ~1.571 ]\n\n    See Also\n    --------\n    strided.ahavercosBy\n","strided.ahaversinBy.ndarray":"\nstrided.ahaversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse half-value versed sine of each element retrieved from\n    an input strided array `x` via a callback function and assigns each result\n    to an element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.ahaversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~1.571, ~3.142, ~1.047 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 0.5, 1.0, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.ahaversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~1.047, ~1.571 ]\n\n    See Also\n    --------\n    strided.ahavercosBy","strided.asinBy":"\nstrided.asinBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the arcsine of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.asinBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, ~-0.524, ~1.571, ~-0.253 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.asinBy( 2, x, 2, y, -1, clbk )\n    [ ~1.571, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, -0.5, 1.0, -0.25 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.asinBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~-0.253, ~-0.524 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~-0.253, ~-0.524 ]\n\n\nstrided.asinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the arcsine of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.asinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~-0.524, ~1.571, ~-0.253 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -0.5, 1.0, -0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.asinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.253, ~-0.524 ]\n\n    See Also\n    --------\n    strided.asinhBy\n","strided.asinBy.ndarray":"\nstrided.asinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the arcsine of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.asinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~-0.524, ~1.571, ~-0.253 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -0.5, 1.0, -0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.asinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.253, ~-0.524 ]\n\n    See Also\n    --------\n    strided.asinhBy","strided.asinhBy":"\nstrided.asinhBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the hyperbolic arcsine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.0, 2.0, -2.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.asinhBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, 0.0, ~1.444, ~-1.444 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.asinhBy( 2, x, 2, y, -1, clbk )\n    [ ~1.444, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, -0.0, 2.0, -2.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.asinhBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~-1.444, 0.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~-1.444, 0.0 ]\n\n\nstrided.asinhBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the hyperbolic arcsine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.0, 2.0, -2.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.asinhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, 0.0, ~1.444, ~-1.444 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -0.0, 2.0, -2.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.asinhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-1.444, 0.0 ]\n\n    See Also\n    --------\n    strided.asinBy\n","strided.asinhBy.ndarray":"\nstrided.asinhBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the hyperbolic arcsine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.0, 2.0, -2.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.asinhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, 0.0, ~1.444, ~-1.444 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -0.0, 2.0, -2.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.asinhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-1.444, 0.0 ]\n\n    See Also\n    --------\n    strided.asinBy","strided.atanBy":"\nstrided.atanBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the arctangent of each element retrieved from an input strided\n    array `x` via a callback function and assigns each result to an element in\n    an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.5, 1.0, -1.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.atanBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, ~-0.464, ~0.785, ~-0.896 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.atanBy( 2, x, 2, y, -1, clbk )\n    [ ~0.785, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, -0.5, 1.0, -1.25 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.atanBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~-0.896, ~-0.464 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~-0.896, ~-0.464 ]\n\n\nstrided.atanBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the arctangent of each element retrieved from an input strided\n    array `x` via a callback function and assigns each result to an element in\n    an output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.5, 1.0, -1.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.atanBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~-0.464, ~0.785, ~-0.896 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -0.5, 1.0, -1.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.atanBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.896, ~-0.464 ]\n\n    See Also\n    --------\n    strided.atanhBy\n","strided.atanBy.ndarray":"\nstrided.atanBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the arctangent of each element retrieved from an input strided\n    array `x` via a callback function and assigns each result to an element in\n    an output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.5, 1.0, -1.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.atanBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~-0.464, ~0.785, ~-0.896 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -0.5, 1.0, -1.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.atanBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.896, ~-0.464 ]\n\n    See Also\n    --------\n    strided.atanhBy","strided.atanhBy":"\nstrided.atanhBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the hyperbolic arctangent of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.atanhBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, ~-0.549, Infinity, ~-0.255 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.atanhBy( 2, x, 2, y, -1, clbk )\n    [ Infinity, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, -0.5, 1.0, -0.25 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.atanhBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~-0.255, ~-0.549 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~-0.255, ~-0.549 ]\n\n\nstrided.atanhBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the hyperbolic arctangent of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.atanhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~-0.549, Infinity, ~-0.255 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -0.5, 1.0, -0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.atanhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.255, ~-0.549 ]\n\n    See Also\n    --------\n    strided.atanBy\n","strided.atanhBy.ndarray":"\nstrided.atanhBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the hyperbolic arctangent of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.atanhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~-0.549, Infinity, ~-0.255 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -0.5, 1.0, -0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.atanhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.255, ~-0.549 ]\n\n    See Also\n    --------\n    strided.atanBy","strided.avercosBy":"\nstrided.avercosBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the inverse versed cosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.avercosBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.avercosBy( 2, x, 2, y, -1, clbk )\n    [ ~1.047, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, -1.57, -0.5, -1.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.avercosBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~1.571, ~2.177 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~1.571, ~2.177 ]\n\n\nstrided.avercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse versed cosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.avercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -1.57, -0.5, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.avercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~1.571, ~2.177 ]\n\n","strided.avercosBy.ndarray":"\nstrided.avercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse versed cosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.avercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -1.57, -0.5, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.avercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~1.571, ~2.177 ]","strided.aversinBy":"\nstrided.aversinBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the inverse versed sine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.aversinBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.aversinBy( 2, x, 2, y, -1, clbk )\n    [ ~1.047, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.aversinBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~1.571, ~2.177 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~1.571, ~2.177 ]\n\n\nstrided.aversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse versed sine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.aversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.57, 0.5, 1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.aversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~1.571, ~2.177 ]\n\n","strided.aversinBy.ndarray":"\nstrided.aversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse versed sine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.aversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.57, 0.5, 1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.aversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~1.571, ~2.177 ]","strided.besselj0By":"\nstrided.besselj0By( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the Bessel function of the first kind of order zero for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.besselj0By( x.length, x, 1, y, 1, clbk )\n    [ 1.0, ~0.765, ~0.998, ~0.984 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.besselj0By( 2, x, 2, y, -1, clbk )\n    [ ~0.998, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.besselj0By( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~0.984, ~0.765 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~0.984, ~0.765 ]\n\n\nstrided.besselj0By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the Bessel function of the first kind of order zero for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.besselj0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 1.0, ~0.765, ~0.998, ~0.984 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.besselj0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~0.984, ~0.765 ]\n\n    See Also\n    --------\n    strided.besselj1By, strided.bessely0By, strided.bessely1By\n","strided.besselj0By.ndarray":"\nstrided.besselj0By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the Bessel function of the first kind of order zero for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.besselj0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 1.0, ~0.765, ~0.998, ~0.984 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.besselj0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~0.984, ~0.765 ]\n\n    See Also\n    --------\n    strided.besselj1By, strided.bessely0By, strided.bessely1By","strided.besselj1By":"\nstrided.besselj1By( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the Bessel function of the first kind of order one for each element\n    retrieved from an input strided array `x` via a callback function and\n    assigns each result to an element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.besselj1By( x.length, x, 1, y, 1, clbk )\n    [ 0.0, ~0.44, ~0.05, ~0.124 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.besselj1By( 2, x, 2, y, -1, clbk )\n    [ ~0.05, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.besselj1By( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~0.124, ~0.44 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~0.124, ~0.44 ]\n\n\nstrided.besselj1By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the Bessel function of the first kind of order one for each element\n    retrieved from an input strided array `x` via a callback function and\n    assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.besselj1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~0.44, ~0.05, ~0.124 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.besselj1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~0.124, ~0.44 ]\n\n    See Also\n    --------\n    strided.besselj0By, strided.bessely0By, strided.bessely1By\n","strided.besselj1By.ndarray":"\nstrided.besselj1By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the Bessel function of the first kind of order one for each element\n    retrieved from an input strided array `x` via a callback function and\n    assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.besselj1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~0.44, ~0.05, ~0.124 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.besselj1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~0.124, ~0.44 ]\n\n    See Also\n    --------\n    strided.besselj0By, strided.bessely0By, strided.bessely1By","strided.bessely0By":"\nstrided.bessely0By( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the Bessel function of the second kind of order zero for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.bessely0By( x.length, x, 1, y, 1, clbk )\n    [ -Infinity, ~0.088, ~-1.534, ~-0.932 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.bessely0By( 2, x, 2, y, -1, clbk )\n    [ ~-1.534, -Infinity, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.bessely0By( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~-0.932, ~0.088 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~-0.932, ~0.088 ]\n\n\nstrided.bessely0By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the Bessel function of the second kind of order zero for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.bessely0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ -Infinity, ~0.088, ~-1.534, ~-0.932 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.bessely0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.932, ~0.088 ]\n\n    See Also\n    --------\n    strided.besselj0By, strided.besselj1By, strided.bessely1By\n","strided.bessely0By.ndarray":"\nstrided.bessely0By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the Bessel function of the second kind of order zero for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.bessely0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ -Infinity, ~0.088, ~-1.534, ~-0.932 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.bessely0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.932, ~0.088 ]\n\n    See Also\n    --------\n    strided.besselj0By, strided.besselj1By, strided.bessely1By","strided.bessely1By":"\nstrided.bessely1By( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the Bessel function of the second kind of order one for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.bessely1By( x.length, x, 1, y, 1, clbk )\n    [ -Infinity, ~-0.781, ~-6.459, ~-2.704 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.bessely1By( 2, x, 2, y, -1, clbk )\n    [ ~-6.459, -Infinity, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.bessely1By( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~-2.704, ~-0.781 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~-2.704, ~-0.781 ]\n\n\nstrided.bessely1By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the Bessel function of the second kind of order one for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.bessely1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ -Infinity, ~-0.781, ~-6.459, ~-2.704 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.bessely1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-2.704, ~-0.781 ]\n\n    See Also\n    --------\n    strided.besselj0By, strided.besselj1By, strided.bessely0By\n","strided.bessely1By.ndarray":"\nstrided.bessely1By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the Bessel function of the second kind of order one for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.bessely1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ -Infinity, ~-0.781, ~-6.459, ~-2.704 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.bessely1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-2.704, ~-0.781 ]\n\n    See Also\n    --------\n    strided.besselj0By, strided.besselj1By, strided.bessely0By","strided.binetBy":"\nstrided.binetBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Evaluates Binet's formula extended to real numbers for each element\n    retrieved from an input strided array `x` via a callback function and\n    assigns each result to an element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.binetBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, 1.0, 1.0, 2.0 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.binetBy( 2, x, 2, y, -1, clbk )\n    [ 1.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.binetBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ 2.0, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 2.0, 1.0 ]\n\n\nstrided.binetBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Evaluates Binet's formula extended to real numbers for each element\n    retrieved from an input strided array `x` via a callback function and\n    assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.binetBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, 1.0, 1.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 2.0, 3.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.binetBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, 2.0, 1.0 ]\n\n","strided.binetBy.ndarray":"\nstrided.binetBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Evaluates Binet's formula extended to real numbers for each element\n    retrieved from an input strided array `x` via a callback function and\n    assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.binetBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, 1.0, 1.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 2.0, 3.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.binetBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, 2.0, 1.0 ]","strided.cbrt":"\nstrided.cbrt( N, dtypeX, x, strideX, dtypeY, y, strideY )\n    Computes the cube root of each element in a strided array `x` and assigns\n    the results to elements in a strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.cbrt( x.length, 'float64', x, 1, 'float64', y, 1 )\n    <Float64Array>[ 0.0, 1.0, 2.0, 3.0 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.cbrt( 2, 'float64', x, 2, 'float64', y, -1 )\n    <Float64Array>[ 2.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.cbrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\n    <Float64Array>[ 3.0, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n\nstrided.cbrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the cube root of each element in a strided array `x` and assigns\n    the results to elements in a strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.cbrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 0.0, 1.0, 2.0, 3.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.cbrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dcbrt, base.strided.scbrt, strided.sqrt\n","strided.cbrt.ndarray":"\nstrided.cbrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the cube root of each element in a strided array `x` and assigns\n    the results to elements in a strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.cbrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 0.0, 1.0, 2.0, 3.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.cbrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dcbrt, base.strided.scbrt, strided.sqrt","strided.cbrtBy":"\nstrided.cbrtBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the cube root of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 9.0, -27.0, 81.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.cbrtBy( x.length, x, 1, y, 1, clbk )\n    [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.cbrtBy( 2, x, 2, y, -1, clbk )\n    [ -3.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.cbrtBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~4.327, ~2.08 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~4.327, ~2.08 ]\n\n\nstrided.cbrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the cube root of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 9.0, -27.0, 81.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.cbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 9.0, -27.0, 81.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.cbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~4.327, ~2.08 ]\n\n    See Also\n    --------\n    strided.cbrt\n","strided.cbrtBy.ndarray":"\nstrided.cbrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the cube root of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 9.0, -27.0, 81.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.cbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 9.0, -27.0, 81.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.cbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~4.327, ~2.08 ]\n\n    See Also\n    --------\n    strided.cbrt","strided.ceil":"\nstrided.ceil( N, dtypeX, x, strideX, dtypeY, y, strideY )\n    Rounds each element in a strided array `x` toward positive infinity and\n    assigns the results to elements in a strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ceil( x.length, 'float64', x, 1, 'float64', y, 1 )\n    <Float64Array>[ 2.0, 3.0, -3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ceil( 2, 'float64', x, 2, 'float64', y, -1 )\n    <Float64Array>[ -3.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.ceil( 2, 'float64', x1, -2, 'float64', y1, 1 )\n    <Float64Array>[ 4.0, 3.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n\nstrided.ceil.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Rounds each element in a strided array `x` toward positive infinity and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ceil.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 2.0, 3.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ceil.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n    See Also\n    --------\n    base.strided.dceil, strided.floor, strided.trunc, base.strided.sceil\n","strided.ceil.ndarray":"\nstrided.ceil.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Rounds each element in a strided array `x` toward positive infinity and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ceil.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 2.0, 3.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ceil.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n    See Also\n    --------\n    base.strided.dceil, strided.floor, strided.trunc, base.strided.sceil","strided.cosBy":"\nstrided.cosBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the cosine for each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.cosBy( x.length, x, 1, y, 1, clbk )\n    [ 1.0, ~-1.0, ~-1.0, ~-0.839 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.cosBy( 2, x, 2, y, -1, clbk )\n    [ ~-1.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 3.14, -3.14, 10.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.cosBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~-0.839, ~-1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~-0.839, ~-1.0 ]\n\n\nstrided.cosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the cosine for each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.cosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 1.0, ~-1.0, ~-1.0, ~-0.839 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 3.14, -3.14, 10.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.cosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.839, ~-1.0 ]\n\n","strided.cosBy.ndarray":"\nstrided.cosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the cosine for each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.cosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 1.0, ~-1.0, ~-1.0, ~-0.839 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 3.14, -3.14, 10.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.cosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.839, ~-1.0 ]","strided.deg2rad":"\nstrided.deg2rad( N, dtypeX, x, strideX, dtypeY, y, strideY )\n    Converts each element in a strided array `x` from degrees to radians and\n    assigns the results to elements in a strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.deg2rad( x.length, 'float64', x, 1, 'float64', y, 1 )\n    <Float64Array>[ 0.0, ~0.524, ~0.785, ~1.571 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.deg2rad( 2, 'float64', x, 2, 'float64', y, -1 )\n    <Float64Array>[ ~0.785, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.deg2rad( 2, 'float64', x1, -2, 'float64', y1, 1 )\n    <Float64Array>[ ~1.571, ~0.524 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~1.571, ~0.524 ]\n\n\nstrided.deg2rad.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Converts each element in a strided array `x` from degrees to radians and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.deg2rad.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 0.0, ~0.524, ~0.785, ~1.571 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.deg2rad.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~1.571, ~0.524 ]\n\n    See Also\n    --------\n    base.strided.ddeg2rad, base.strided.sdeg2rad\n","strided.deg2rad.ndarray":"\nstrided.deg2rad.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Converts each element in a strided array `x` from degrees to radians and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.deg2rad.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 0.0, ~0.524, ~0.785, ~1.571 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.deg2rad.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~1.571, ~0.524 ]\n\n    See Also\n    --------\n    base.strided.ddeg2rad, base.strided.sdeg2rad","strided.dataTypes":"\nstrided.dataTypes()\n    Returns a list of strided array data types.\n\n    The output array contains the following data types:\n\n    - binary: binary.\n    - bool: boolean values.\n    - complex64: single-precision complex floating-point numbers.\n    - complex128: double-precision complex floating-point numbers.\n    - float32: single-precision floating-point numbers.\n    - float64: double-precision floating-point numbers.\n    - generic: values of any type.\n    - int16: signed 16-bit integers.\n    - int32: signed 32-bit integers.\n    - int8: signed 8-bit integers.\n    - uint16: unsigned 16-bit integers.\n    - uint32: unsigned 32-bit integers.\n    - uint8: unsigned 8-bit integers.\n    - uint8c: unsigned clamped 8-bit integers.\n\n    Returns\n    -------\n    out: Array<string>\n        List of strided array data types.\n\n    Examples\n    --------\n    > var out = strided.dataTypes()\n    <Array>\n\n","strided.dcbrtBy":"\nstrided.dcbrtBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the cube root of each element retrieved from an input double-\n    precision floating-point strided array via a callback function and assigns\n    each result to an element in an output double-precision floating-point\n    strided array.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - indices: strided array indices (offset + idx*stride).\n    - arrays: input and output arrays.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Float64Array\n        Destination array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > function clbk( v ) { return v; };\n    > strided.dcbrtBy( x.length, x, 1, y, 1, clbk )\n    <Float64Array>[ 1.0, ~2.08, -3.0, ~4.327 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.dcbrtBy( 2, x, 2, y, -1, clbk )\n    <Float64Array>[ -3.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.dcbrtBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~4.327, ~2.08 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~4.327, ~2.08 ]\n\n\nstrided.dcbrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the cube root of each element retrieved from an input double-\n    precision floating-point strided array via a callback function and assigns\n    each result to an element in an output double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - indices: strided array indices (offset + idx*stride).\n    - arrays: input and output arrays.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Float64Array\n        Destination array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > function clbk( v ) { return v; };\n    > strided.dcbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    <Float64Array>[ 1.0, ~2.08, -3.0, ~4.327 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.dcbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    <Float64Array>[ 0.0, 0.0, ~4.327, ~2.08 ]\n\n    See Also\n    --------\n    strided.cbrt\n","strided.dcbrtBy.ndarray":"\nstrided.dcbrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the cube root of each element retrieved from an input double-\n    precision floating-point strided array via a callback function and assigns\n    each result to an element in an output double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - indices: strided array indices (offset + idx*stride).\n    - arrays: input and output arrays.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Float64Array\n        Destination array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > function clbk( v ) { return v; };\n    > strided.dcbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    <Float64Array>[ 1.0, ~2.08, -3.0, ~4.327 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.dcbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    <Float64Array>[ 0.0, 0.0, ~4.327, ~2.08 ]\n\n    See Also\n    --------\n    strided.cbrt","strided.dispatch":"\nstrided.dispatch( fcns, types, data, nargs, nin, nout )\n    Returns a strided array function interface which performs multiple dispatch.\n\n    Without offsets, a strided array function interface has the following\n    signature:\n\n      f( N, dtypeX, x, strideX, dtypeY, y, strideY, ... )\n\n    where\n\n    - N: number of indexed elements.\n    - dtypeX: data type for `x`.\n    - x: strided array.\n    - strideX: index increment for `x`.\n    - dtypeY: data type for `y`.\n    - y: strided array.\n    - strideY: index increment for `y`.\n    - ...: additional strided arrays, data types, and associated strides.\n\n    The number of parameters is derived from `nargs`, the number of input\n    strided arrays is derived from `nin`, and the number of output strided\n    arrays is derived from `nout`.\n\n    Without offsets, the number of parameters must obey the following relation:\n\n      nargs = 3*(nout+nin) + 1\n\n    With offsets, the number of parameters must obey the following relation:\n\n      nargs = 4*(nout+nin) + 1\n\n    With offsets, a strided array function interface has the following\n    signature:\n\n      f( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY, ... )\n\n    where\n\n    - N: number of indexed elements.\n    - dtypeX: data type for `x`.\n    - x: strided array.\n    - strideX: index increment for `x`.\n    - offsetX: starting index for `x`.\n    - dtypeY: data type for `y`.\n    - y: strided array.\n    - strideY: index increment for `y`.\n    - offsetY: starting index for `y`.\n    - ...: additional strided arrays and associated data types, strides, and\n      offsets.\n\n    The choice of which strided array function interface to return depends on\n    the use case. The former is suitable for typed array views; while the latter\n    affords alternative indexing semantics more suitable for n-dimensional\n    arrays (ndarrays).\n\n    Parameters\n    ----------\n    fcns: Function|ArrayLikeObject<Function>\n        List of strided array functions. Without offsets, a strided array\n        function should have the following signature:\n\n          f( arrays, shape, strides, data )\n\n        where\n\n        - arrays: array containing strided input and output arrays.\n        - shape: array containing a single element, the number of indexed\n          elements.\n        - strides: array containing the stride lengths for the strided input and\n          output arrays.\n        - data: strided array function data (e.g., a callback).\n\n        With offsets, a strided array function should have the following\n        signature:\n\n          f( arrays, shape, strides, offsets, data )\n\n        where\n\n        - offsets: array containing the starting indices (i.e., index offsets)\n          for the strided input and output arrays.\n\n        For convenience, a single strided array function may be provided which\n        will be invoked whenever the strided array argument data types match a\n        sequence of types in `types`. Providing a single strided array function\n        is particularly convenient for the case where, regardless of array data\n        types, traversing arrays remains the same, but the strided array\n        function `data` differs (e.g., callbacks which differ based on the array\n        data types).\n\n    types: ArrayLikeObject\n        One-dimensional list of strided array argument data types.\n\n    data: ArrayLikeObject|null\n        Strided array function data (e.g., callbacks). If `null`, a returned\n        strided array function interface does **not** provide a `data` argument\n        to an invoked strided array function.\n\n    nargs: integer\n        Total number of strided array function interface arguments (including\n        data types, strides, and offsets).\n\n    nin: integer\n        Number of input strided arrays.\n\n    nout: integer\n        Number of output strided arrays.\n\n    Returns\n    -------\n    fcn: Function\n        Strided array function interface.\n\n    Examples\n    --------\n    // Define strided array argument data types:\n    > var t = [ 'float64', 'float64', 'float32', 'float32' ];\n\n    // Define a list of strided array function data (callbacks):\n    > var d = [ base.abs, base.absf ];\n\n    // Create a strided array function interface for applying unary callbacks:\n    > var f = strided.dispatch( base.strided.unary, t, d, 7, 1, 1 );\n\n    // Create an input strided array:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n    // Create an output strided array:\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n    // Compute the element-wise absolute value:\n    > f( x.length, 'float64', x, 1, 'float64', y, 1 );\n    > y\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Create a strided array function interface supporting offsets:\n    > f = strided.dispatch( base.strided.unary.ndarray, t, d, 9, 1, 1 );\n\n    // Create an input strided array:\n    > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n    // Create an output strided array:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n    // Compute the element-wise absolute value starting from the third element:\n    > f( 2, 'float64', x, 1, 2, 'float64', y, 1, 2 );\n    > y\n    <Float64Array>[ 0.0, 0.0, 3.0, 4.0 ]\n\n","strided.dispatchBy":"\nstrided.dispatchBy( fcns, types, data, nargs, nin, nout )\n    Returns a strided array function interface which accepts a callback function\n    and performs multiple dispatch.\n\n    Without offsets, a strided array function interface has the following\n    signature:\n\n      f( N, dx, x, sx, dy, y, sy, ..., clbk[, thisArg] )\n\n    where\n\n    - N: number of indexed elements.\n    - dx: data type for `x`.\n    - x: strided array.\n    - sx: index increment for `x`.\n    - dy: data type for `y`.\n    - y: strided array.\n    - sy: index increment for `y`.\n    - ...: additional strided arrays, data types, and associated strides.\n    - clbk: callback function.\n    - thisArg: callback function execution context.\n\n    The number of parameters is derived from `nargs`, the number of input\n    strided arrays is derived from `nin`, and the number of output strided\n    arrays is derived from `nout`.\n\n    Without offsets, the number of parameters must obey the following relation:\n\n      nargs = 3*(nout+nin) + 2\n\n    With offsets, the number of parameters must obey the following relation:\n\n      nargs = 4*(nout+nin) + 2\n\n    With offsets, a strided array function interface has the following\n    signature:\n\n      f( N, dx, x, sx, ox, dy, y, sy, oy, ..., clbk[, thisArg] )\n\n    where\n\n    - N: number of indexed elements.\n    - dx: data type for `x`.\n    - x: strided array.\n    - sx: index increment for `x`.\n    - ox: starting index for `x`.\n    - dy: data type for `y`.\n    - y: strided array.\n    - sy: index increment for `y`.\n    - oy: starting index for `y`.\n    - ...: additional strided arrays and associated data types, strides, and\n      offsets.\n    - clbk: callback function.\n    - thisArg: callback function execution context.\n\n    The choice of which strided array function interface to return depends on\n    the use case. The former is suitable for typed array views; while the latter\n    affords alternative indexing semantics more suitable for n-dimensional\n    arrays (ndarrays).\n\n    Parameters\n    ----------\n    fcns: Function|ArrayLikeObject<Function>\n        List of strided array functions. Without offsets, a strided array\n        function should have the following signature:\n\n          f( arrays, shape, strides, data, clbk, thisArg )\n\n        where\n\n        - arrays: array containing strided input and output arrays.\n        - shape: array containing a single element, the number of indexed\n          elements.\n        - strides: array containing the stride lengths for the strided input and\n          output arrays.\n        - data: strided array function data (e.g., a callback).\n        - clbk: callback function.\n        - thisArg: callback function execution context.\n\n        With offsets, a strided array function should have the following\n        signature:\n\n          f( arrays, shape, strides, offsets, data, clbk, thisArg )\n\n        where\n\n        - offsets: array containing the starting indices (i.e., index offsets)\n          for the strided input and output arrays.\n\n        For convenience, a single strided array function may be provided which\n        will be invoked whenever the strided array argument data types match a\n        sequence of types in `types`. Providing a single strided array function\n        is particularly convenient for the case where, regardless of array data\n        types, traversing arrays remains the same, but the strided array\n        function `data` differs (e.g., callbacks which differ based on the array\n        data types).\n\n    types: ArrayLikeObject\n        One-dimensional list of strided array argument data types.\n\n    data: ArrayLikeObject|null\n        Strided array function data (e.g., callbacks). If `null`, a returned\n        strided array function interface does **not** provide a `data` argument\n        to an invoked strided array function.\n\n    nargs: integer\n        Total number of strided array function interface arguments (including\n        data types, strides, offsets, and the callback function).\n\n    nin: integer\n        Number of input strided arrays.\n\n    nout: integer\n        Number of output strided arrays.\n\n    Returns\n    -------\n    fcn: Function\n        Strided array function interface.\n\n    Examples\n    --------\n    // Define strided array argument data types:\n    > var t = [ 'float64', 'float64', 'float32', 'float32' ];\n\n    // Define a list of strided array function data (callbacks):\n    > var d = [ base.abs, base.absf ];\n\n    // Create a strided array function interface for applying unary callbacks:\n    > var f = strided.dispatchBy( base.strided.unaryBy, t, d, 8, 1, 1 );\n\n    // Create an input strided array:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n    // Create an output strided array:\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n    // Compute the element-wise absolute value:\n    > f( x.length, 'float64', x, 1, 'float64', y, 1, base.identity );\n    > y\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Create a strided array function interface supporting offsets:\n    > f = strided.dispatchBy( base.strided.unary.ndarray, t, d, 10, 1, 1 );\n\n    // Create an input strided array:\n    > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n    // Create an output strided array:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n    // Compute the element-wise absolute value starting from the third element:\n    > f( 2, 'float64', x, 1, 2, 'float64', y, 1, 2, base.identity );\n    > y\n    <Float64Array>[ 0.0, 0.0, 3.0, 4.0 ]\n\n    See Also\n    --------\n    strided.dispatch\n","strided.floor":"\nstrided.floor( N, dtypeX, x, strideX, dtypeY, y, strideY )\n    Rounds each element in a strided array `x` toward negative infinity and\n    assigns the results to elements in a strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.floor( x.length, 'float64', x, 1, 'float64', y, 1 )\n    <Float64Array>[ -2.0, 2.0, -4.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.floor( 2, 'float64', x, 2, 'float64', y, -1 )\n    <Float64Array>[ -4.0, -2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.floor( 2, 'float64', x1, -2, 'float64', y1, 1 )\n    <Float64Array>[ 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nstrided.floor.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Rounds each element in a strided array `x` toward negative infinity and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.floor.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ -2.0, 2.0, -4.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.floor.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    strided.ceil, base.strided.dfloor, strided.trunc, base.strided.sfloor\n","strided.floor.ndarray":"\nstrided.floor.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Rounds each element in a strided array `x` toward negative infinity and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.floor.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ -2.0, 2.0, -4.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.floor.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    strided.ceil, base.strided.dfloor, strided.trunc, base.strided.sfloor","strided.inv":"\nstrided.inv( N, dtypeX, x, strideX, dtypeY, y, strideY )\n    Computes the multiplicative inverse for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.inv( x.length, 'float64', x, 1, 'float64', y, 1 )\n    <Float64Array>[ -0.05, -1.0, 0.5, 0.25 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.inv( 2, 'float64', x, 2, 'float64', y, -1 )\n    <Float64Array>[ 0.5, -0.05, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.inv( 2, 'float64', x1, -2, 'float64', y1, 1 )\n    <Float64Array>[ 0.25, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n\nstrided.inv.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the multiplicative inverse for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.inv.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ -0.05, -1.0, 0.5, 0.25 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.inv.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dinv, base.strided.sinv\n","strided.inv.ndarray":"\nstrided.inv.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the multiplicative inverse for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.inv.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ -0.05, -1.0, 0.5, 0.25 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.inv.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dinv, base.strided.sinv","strided.mul":"\nstrided.mul( N, dx, x, sx, dy, y, sy, dz, z, sz )\n    Multiplies each element in a strided array `x` to a corresponding element in\n    a strided array `y` and assigns the results to elements in a strided array\n    `z`.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dx: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    dy: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    dz: any\n        Data type for `z`.\n\n    z: ArrayLikeObject\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    Returns\n    -------\n    z: ArrayLikeObject\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var dt = 'float64';\n    > strided.mul( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\n    <Float64Array>[ -2.0, 2.0, 9.0, -20.0 ]\n\n    // Using `N` and stride parameters:\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.mul( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\n    <Float64Array>[ -6.0, 3.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > strided.mul( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\n    <Float64Array>[ -15.0, 4.0 ]\n    > z0\n    <Float64Array>[ 0.0, 0.0, -15.0, 4.0 ]\n\n\nstrided.mul.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n    Multiplies each element in a strided array `x` to a corresponding element in\n    a strided array `y` and assigns the results to elements in a strided array\n    `z` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dx: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    dy: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    dz: any\n        Data type for `z`.\n\n    z: ArrayLikeObject\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    Returns\n    -------\n    z: ArrayLikeObject\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var dt = 'float64';\n    > strided.mul.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n    <Float64Array>[ -2.0, 2.0, 9.0, -20.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.mul.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n    <Float64Array>[ 0.0, 4.0, -15.0, 0.0 ]\n\n    See Also\n    --------\n    strided.add, strided.sub\n","strided.mul.ndarray":"\nstrided.mul.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n    Multiplies each element in a strided array `x` to a corresponding element in\n    a strided array `y` and assigns the results to elements in a strided array\n    `z` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dx: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    dy: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    dz: any\n        Data type for `z`.\n\n    z: ArrayLikeObject\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    Returns\n    -------\n    z: ArrayLikeObject\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var dt = 'float64';\n    > strided.mul.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n    <Float64Array>[ -2.0, 2.0, 9.0, -20.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.mul.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n    <Float64Array>[ 0.0, 4.0, -15.0, 0.0 ]\n\n    See Also\n    --------\n    strided.add, strided.sub","strided.mulBy":"\nstrided.mulBy( N, x, sx, y, sy, z, sz, clbk[, thisArg] )\n    Performs element-wise multiplication of two strided arrays via a callback\n    function and assigns each result to an element in an output strided array.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided four arguments:\n\n    - values: input array elements.\n    - idx: iteration index.\n    - indices: strided array indices (offset + idx*stride).\n    - arrays: input and output arrays.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n    > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( values ) { return values; };\n    > strided.mulBy( x.length, x, 1, y, 1, z, 1, clbk )\n    [ 11.0, 24.0, 39.0, 56.0 ]\n\n    // Using `N` and stride parameters:\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.mulBy( 2, x, 2, y, -1, z, 1, clbk )\n    [ 12.0, 33.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\n    > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > strided.mulBy( 2, x1, -2, y1, 1, z1, 1, clbk )\n    <Float64Array>[ 52.0, 28.0 ]\n    > z0\n    <Float64Array>[ 0.0, 0.0, 52.0, 28.0 ]\n\n\nstrided.mulBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n    Performs element-wise multiplication of two strided arrays via a callback\n    function and assigns each result to an element in an output strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n    > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( values ) { return values; };\n    > strided.mulBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n    [ 11.0, 24.0, 39.0, 56.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0 ];\n    > y = [ 11.0, 12.0, 13.0, 14.0 ];\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > var oy = y.length - 1;\n    > var oz = z.length - 1;\n    > strided.mulBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n    [ 0.0, 0.0, 52.0, 28.0 ]\n\n    See Also\n    --------\n    strided.mul, strided.addBy, strided.subBy\n","strided.mulBy.ndarray":"\nstrided.mulBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n    Performs element-wise multiplication of two strided arrays via a callback\n    function and assigns each result to an element in an output strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n    > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( values ) { return values; };\n    > strided.mulBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n    [ 11.0, 24.0, 39.0, 56.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0 ];\n    > y = [ 11.0, 12.0, 13.0, 14.0 ];\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > var oy = y.length - 1;\n    > var oz = z.length - 1;\n    > strided.mulBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n    [ 0.0, 0.0, 52.0, 28.0 ]\n\n    See Also\n    --------\n    strided.mul, strided.addBy, strided.subBy","strided.ramp":"\nstrided.ramp( N, dtypeX, x, strideX, dtypeY, y, strideY )\n    Evaluates the ramp function for each element in a strided array `x` and\n    assigns the results to elements in a strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ramp( x.length, 'float64', x, 1, 'float64', y, 1 )\n    <Float64Array>[ 1.1, 2.5, 0.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ramp( 2, 'float64', x, 2, 'float64', y, -1 )\n    <Float64Array>[ 0.0, 1.1, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.ramp( 2, 'float64', x1, -2, 'float64', y1, 1 )\n    <Float64Array>[ 4.0, 2.5 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.5 ]\n\n\nstrided.ramp.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Evaluates the ramp function for each element in a strided array `x` and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ramp.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 1.1, 2.5, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ramp.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.5 ]\n\n    See Also\n    --------\n    base.strided.dramp, base.strided.sramp\n","strided.ramp.ndarray":"\nstrided.ramp.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Evaluates the ramp function for each element in a strided array `x` and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ramp.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 1.1, 2.5, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ramp.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.5 ]\n\n    See Also\n    --------\n    base.strided.dramp, base.strided.sramp","strided.rsqrt":"\nstrided.rsqrt( N, dtypeX, x, strideX, dtypeY, y, strideY )\n    Computes the reciprocal square root for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.rsqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\n    <Float64Array>[ Infinity, 0.5, ~0.333, ~0.289 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.rsqrt( 2, 'float64', x, 2, 'float64', y, -1 )\n    <Float64Array>[ ~0.333, Infinity, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.rsqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\n    <Float64Array>[ ~0.289, 0.5 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nstrided.rsqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the reciprocal square root for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.rsqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ Infinity, 0.5, ~0.333, ~0.289 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.rsqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n    See Also\n    --------\n    base.strided.drsqrt, strided.sqrt, base.strided.srsqrt\n","strided.rsqrt.ndarray":"\nstrided.rsqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the reciprocal square root for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.rsqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ Infinity, 0.5, ~0.333, ~0.289 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.rsqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n    See Also\n    --------\n    base.strided.drsqrt, strided.sqrt, base.strided.srsqrt","strided.sinBy":"\nstrided.sinBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the sine of each element retrieved from an input strided array `x`\n    via a callback function and assigns each result to an element in an output\n    strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.sinBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, ~0.002, ~-0.002, ~-0.544 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.sinBy( 2, x, 2, y, -1, clbk )\n    [ ~-0.002, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 3.14, -3.14, 10.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.sinBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~-0.544, ~0.002 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~-0.544, ~0.002 ]\n\n\nstrided.sinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the sine of each element retrieved from an input strided array `x`\n    via a callback function and assigns each result to an element in an output\n    strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.sinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~0.002, ~-0.002, ~-0.544 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 3.14, -3.14, 10.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.sinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.544, ~0.002 ]\n\n","strided.sinBy.ndarray":"\nstrided.sinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the sine of each element retrieved from an input strided array `x`\n    via a callback function and assigns each result to an element in an output\n    strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.sinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~0.002, ~-0.002, ~-0.544 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 3.14, -3.14, 10.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.sinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.544, ~0.002 ]","strided.sqrt":"\nstrided.sqrt( N, dtypeX, x, strideX, dtypeY, y, strideY )\n    Computes the principal square root for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.sqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\n    <Float64Array>[ 0.0, 2.0, 3.0, ~3.464 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.sqrt( 2, 'float64', x, 2, 'float64', y, -1 )\n    <Float64Array>[ 3.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.sqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\n    <Float64Array>[ ~3.464, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nstrided.sqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the principal square root for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.sqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 0.0, 2.0, 3.0, ~3.464 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.sqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n    See Also\n    --------\n    strided.cbrt, base.strided.dsqrt, strided.rsqrt, base.strided.ssqrt\n","strided.sqrt.ndarray":"\nstrided.sqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the principal square root for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.sqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 0.0, 2.0, 3.0, ~3.464 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.sqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n    See Also\n    --------\n    strided.cbrt, base.strided.dsqrt, strided.rsqrt, base.strided.ssqrt","strided.sqrtBy":"\nstrided.sqrtBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the principal square root for each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 122.0, 50.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.sqrtBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, 1.0, ~11.045, ~7.071 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.sqrtBy( 2, x, 2, y, -1, clbk )\n    [ ~11.045, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 1.0, 122.0, 50.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.sqrtBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~7.071, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~7.071, 1.0 ]\n\n\nstrided.sqrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the principal square root for each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 122.0, 50.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.sqrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, 1.0, ~11.045, ~7.071 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 122.0, 50.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.sqrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~7.071, 1.0 ]\n\n    See Also\n    --------\n    strided.sqrt\n","strided.sqrtBy.ndarray":"\nstrided.sqrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the principal square root for each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 122.0, 50.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.sqrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, 1.0, ~11.045, ~7.071 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 122.0, 50.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.sqrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~7.071, 1.0 ]\n\n    See Also\n    --------\n    strided.sqrt","strided.sub":"\nstrided.sub( N, dx, x, sx, dy, y, sy, dz, z, sz )\n    Subtracts each element in a strided array `x` to a corresponding element in\n    a strided array `y` and assigns the results to elements in a strided array\n    `z`.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dx: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    dy: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    dz: any\n        Data type for `z`.\n\n    z: ArrayLikeObject\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    Returns\n    -------\n    z: ArrayLikeObject\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var dt = 'float64';\n    > strided.sub( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\n    <Float64Array>[ -3.0, -1.0, 0.0, -9.0 ]\n\n    // Using `N` and stride parameters:\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.sub( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\n    <Float64Array>[ -5.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > strided.sub( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\n    <Float64Array>[ -8.0, -3.0 ]\n    > z0\n    <Float64Array>[ 0.0, 0.0, -8.0, -3.0 ]\n\n\nstrided.sub.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n    Subtracts each element in a strided array `x` to a corresponding element in\n    a strided array `y` and assigns the results to elements in a strided array\n    `z` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dx: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    dy: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    dz: any\n        Data type for `z`.\n\n    z: ArrayLikeObject\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    Returns\n    -------\n    z: ArrayLikeObject\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var dt = 'float64';\n    > strided.sub.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n    <Float64Array>[ -3.0, -1.0, 0.0, -9.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.sub.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n    <Float64Array>[ 0.0, -3.0, -8.0, 0.0 ]\n\n    See Also\n    --------\n    strided.add, strided.mul\n","strided.sub.ndarray":"\nstrided.sub.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n    Subtracts each element in a strided array `x` to a corresponding element in\n    a strided array `y` and assigns the results to elements in a strided array\n    `z` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dx: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    dy: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    dz: any\n        Data type for `z`.\n\n    z: ArrayLikeObject\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    Returns\n    -------\n    z: ArrayLikeObject\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var dt = 'float64';\n    > strided.sub.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n    <Float64Array>[ -3.0, -1.0, 0.0, -9.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.sub.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n    <Float64Array>[ 0.0, -3.0, -8.0, 0.0 ]\n\n    See Also\n    --------\n    strided.add, strided.mul","strided.subBy":"\nstrided.subBy( N, x, sx, y, sy, z, sz, clbk[, thisArg] )\n    Performs element-wise subtraction of two strided arrays via a callback\n    function and assigns each result to an element in an output strided array.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided four arguments:\n\n    - values: input array elements.\n    - idx: iteration index.\n    - indices: strided array indices (offset + idx*stride).\n    - arrays: input and output arrays.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 11.0, 12.0, 13.0, 14.0 ];\n    > var y = [ 8.0, 7.0, 6.0, 5.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( values ) { return values; };\n    > strided.subBy( x.length, x, 1, y, 1, z, 1, clbk )\n    [ 3.0, 5.0, 7.0, 9.0 ]\n\n    // Using `N` and stride parameters:\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.subBy( 2, x, 2, y, -1, z, 1, clbk )\n    [ 4.0, 5.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\n    > var y0 = new Float64Array( [ 8.0, 7.0, 6.0, 5.0 ] );\n    > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > strided.subBy( 2, x1, -2, y1, 1, z1, 1, clbk )\n    <Float64Array>[ 8.0, 7.0 ]\n    > z0\n    <Float64Array>[ 0.0, 0.0, 8.0, 7.0 ]\n\n\nstrided.subBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n    Performs element-wise subtraction of two strided arrays via a callback\n    function and assigns each result to an element in an output strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 11.0, 12.0, 13.0, 14.0 ];\n    > var y = [ 8.0, 7.0, 6.0, 5.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( values ) { return values; };\n    > strided.subBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n    [ 3.0, 5.0, 7.0, 9.0 ]\n\n    // Advanced indexing:\n    > x = [ 11.0, 12.0, 13.0, 14.0 ];\n    > y = [ 8.0, 7.0, 6.0, 5.0 ];\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > var oy = y.length - 1;\n    > var oz = z.length - 1;\n    > strided.subBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n    [ 0.0, 0.0, 8.0, 7.0 ]\n\n    See Also\n    --------\n    strided.sub, strided.addBy, strided.mulBy\n","strided.subBy.ndarray":"\nstrided.subBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n    Performs element-wise subtraction of two strided arrays via a callback\n    function and assigns each result to an element in an output strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 11.0, 12.0, 13.0, 14.0 ];\n    > var y = [ 8.0, 7.0, 6.0, 5.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( values ) { return values; };\n    > strided.subBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n    [ 3.0, 5.0, 7.0, 9.0 ]\n\n    // Advanced indexing:\n    > x = [ 11.0, 12.0, 13.0, 14.0 ];\n    > y = [ 8.0, 7.0, 6.0, 5.0 ];\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > var oy = y.length - 1;\n    > var oz = z.length - 1;\n    > strided.subBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n    [ 0.0, 0.0, 8.0, 7.0 ]\n\n    See Also\n    --------\n    strided.sub, strided.addBy, strided.mulBy","strided.trunc":"\nstrided.trunc( N, dtypeX, x, strideX, dtypeY, y, strideY )\n    Rounds each element in a strided array `x` toward zero and assigns the\n    results to elements in a strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.trunc( x.length, 'float64', x, 1, 'float64', y, 1 )\n    <Float64Array>[ 1.0, 2.0, -3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.trunc( 2, 'float64', x, 2, 'float64', y, -1 )\n    <Float64Array>[ -3.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.trunc( 2, 'float64', x1, -2, 'float64', y1, 1 )\n    <Float64Array>[ 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nstrided.trunc.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Rounds each element in a strided array `x` toward zero and assigns the\n    results to elements in a strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.trunc.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.trunc.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    strided.ceil, base.strided.dtrunc, strided.floor, base.strided.strunc\n","strided.trunc.ndarray":"\nstrided.trunc.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Rounds each element in a strided array `x` toward zero and assigns the\n    results to elements in a strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.trunc.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.trunc.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    strided.ceil, base.strided.dtrunc, strided.floor, base.strided.strunc","stridedarray2iterator":"\nstridedarray2iterator( N, src, stride, offset[, mapFcn[, thisArg]] )\n    Returns an iterator which iterates over elements of an array-like object\n    according to specified stride parameters.\n\n    When invoked, an input function is provided four arguments:\n\n    - value: iterated value.\n    - index: iterated value index.\n    - n: iteration count (zero-based).\n    - src: source array-like object.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an array's `@@iterator` method, regardless of whether this method is\n    defined. To convert an array to an implementation defined iterator, invoke\n    this method directly.\n\n    Parameters\n    ----------\n    N: integer\n        Number of values to iterate.\n\n    src: ArrayLikeObject\n        Array-like object from which to create the iterator.\n\n    stride: integer\n        Stride length.\n\n    offset: integer\n        Starting index.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = stridedarray2iterator( 2, [ 1, 2, 3, 4 ], -2, 3 );\n    > var v = it.next().value\n    4\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    iterator2array, array2iterator\n","stridedArrayStream":"\nstridedArrayStream( N, buffer, stride, offset[, options] )\n    Creates a readable stream from a strided array-like object.\n\n    In object mode, `null` is a reserved value. If an array contains `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or filter `null` values\n    prior to invocation.\n\n    In binary mode, if an array contains `undefined` values, the stream will\n    emit an error. Consider providing a custom serialization function or\n    filtering `undefined` values prior to invocation.\n\n    If a serialization function fails to return a string or Buffer, the stream\n    emits an error.\n\n    Parameters\n    ----------\n    N: integer\n        Number of values to stream.\n\n    buffer: ArrayLikeObject\n        Array-like object from which to create the stream.\n\n    stride: integer\n        Stride length.\n\n    offset: integer\n        Starting index.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing the stream.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize streamed\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var s = stridedArrayStream( 3, [ 1, 2, 3 ], 1, 0 );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nstridedArrayStream.factory( [options] )\n    Returns a function for creating readable streams from array-like objects.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing streaming.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize streamed\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = stridedArrayStream.factory( opts );\n\n\nstridedArrayStream.objectMode( N, buffer, stride, offset[, options] )\n    Returns an \"objectMode\" readable stream from a strided array-like object.\n\n    In object mode, `null` is a reserved value. If an array contains `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or filter `null` values\n    prior to invocation.\n\n    Parameters\n    ----------\n    N: integer\n        Number of values to stream.\n\n    buffer: ArrayLikeObject\n        Array-like object from which to create the stream.\n\n    stride: integer\n        Stride length.\n\n    offset: integer\n        Starting index.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before pausing streaming.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var s = stridedArrayStream.objectMode( 3, [ 1, 2, 3 ], 1, 0 );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    arrayStream\n","stridedArrayStream.factory":"\nstridedArrayStream.factory( [options] )\n    Returns a function for creating readable streams from array-like objects.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing streaming.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize streamed\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = stridedArrayStream.factory( opts );","stridedArrayStream.objectMode":"\nstridedArrayStream.objectMode( N, buffer, stride, offset[, options] )\n    Returns an \"objectMode\" readable stream from a strided array-like object.\n\n    In object mode, `null` is a reserved value. If an array contains `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or filter `null` values\n    prior to invocation.\n\n    Parameters\n    ----------\n    N: integer\n        Number of values to stream.\n\n    buffer: ArrayLikeObject\n        Array-like object from which to create the stream.\n\n    stride: integer\n        Stride length.\n\n    offset: integer\n        Starting index.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before pausing streaming.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var s = stridedArrayStream.objectMode( 3, [ 1, 2, 3 ], 1, 0 );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    arrayStream","string2buffer":"\nstring2buffer( str[, encoding] )\n    Allocates a buffer containing a provided string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    encoding: string (optional)\n        Character encoding. Default: 'utf8'.\n\n    Returns\n    -------\n    out: Buffer\n        Buffer instance.\n\n    Examples\n    --------\n    > var b = string2buffer( 'beep boop' )\n    <Buffer>\n    > b = string2buffer( '7468697320697320612074c3a97374', 'hex' );\n    > b.toString()\n    'this is a tést'\n\n    See Also\n    --------\n    Buffer, array2buffer, arraybuffer2buffer, copyBuffer\n","sub2ind":"\nsub2ind( shape, ...subscript[, options] )\n    Converts subscripts to a linear index.\n\n    Parameters\n    ----------\n    shape: ArrayLike\n        Array shape.\n\n    subscript: ...integer\n        Subscripts.\n\n    options: Object (optional)\n        Options.\n\n    options.order: string (optional)\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran style). Default: 'row-major'.\n\n    options.mode: string|Array<string> (optional)\n        Specifies how to handle subscripts which exceed array dimensions. If\n        equal to 'throw', the function throws an error when a subscript exceeds\n        array dimensions. If equal to 'normalize', the function normalizes\n        negative subscripts and throws an error when a subscript exceeds array\n        dimensions. If equal to 'wrap', the function wraps around subscripts\n        exceeding array dimensions using modulo arithmetic. If equal to\n        'clamp', the function sets subscripts exceeding array dimensions to\n        either `0` (minimum index) or the maximum index along a particular\n        dimension. If provided a mode array, each array element specifies the\n        mode for a corresponding array dimension. If provided fewer modes than\n        dimensions, the function recycles modes using modulo arithmetic.\n        Default: [ 'throw' ].\n\n    Returns\n    -------\n    idx: integer\n        Linear index.\n\n    Examples\n    --------\n    > var d = [ 3, 3, 3 ];\n    > var idx = sub2ind( d, 1, 2, 2 )\n    17\n\n    See Also\n    --------\n    array, ndarray, ind2sub\n","substringAfter":"\nsubstringAfter( str, search[, fromIndex] )\n    Returns the part of a string after a specified substring.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search string.\n\n    fromIndex: integer (optional)\n        Index from which to start the search. Default: `0`.\n\n    Returns\n    -------\n    out: string\n        Substring.\n\n    Examples\n    --------\n    > var out = substringAfter( 'Hello World!', 'World' )\n    '!'\n    > out = substringAfter( 'Hello World!', 'Hello ' )\n    'World!'\n    > out = substringAfter( 'Hello World!', 'l', 5 )\n    'd!'\n\n    See Also\n    --------\n    substringBefore, substringBeforeLast, substringAfterLast","substringAfterLast":"\nsubstringAfterLast( str, search[, fromIndex] )\n    Returns the part of a string after the last occurrence of a specified\n    substring.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search value.\n\n    fromIndex: integer (optional)\n        Index of last character to be considered beginning of a match.\n        Default: `str.length`.\n\n    Returns\n    -------\n    out: string\n        Substring.\n\n    Examples\n    --------\n    > var out = substringAfterLast( 'beep boop beep baz', 'beep' )\n    ' baz'\n    > out = substringAfterLast( 'Hello World!', 'Hello ' )\n    'World!'\n    > out = substringAfterLast( 'Hello World!', 'o', 5 )\n    ' World!'\n\n    See Also\n    --------\n    substringBefore, substringBeforeLast, substringAfter","substringBefore":"\nsubstringBefore( str, search )\n    Returns the part of a string before a specified substring.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search string.\n\n    Returns\n    -------\n    out: string\n        Substring.\n\n    Examples\n    --------\n    > var str = 'beep boop';\n    > var out = substringBefore( str, ' ' )\n    'beep'\n    > out = substringBefore( str, 'o' )\n    'beep b'\n\n    See Also\n    --------\n    substringBeforeLast, substringAfter, substringAfterLast","substringBeforeLast":"\nsubstringBeforeLast( str, search )\n    Returns the part of a string before the last occurrence of a specified\n    substring.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search value.\n\n    Returns\n    -------\n    out: string\n        Substring.\n\n    Examples\n    --------\n    > var str = 'Beep Boop Beep';\n    > var out = substringBeforeLast( str, 'Beep' )\n    'Beep Boop '\n    > out = substringBeforeLast( str, 'Boop' )\n    'Beep '\n\n    See Also\n    --------\n    substringBefore, substringAfter, substringAfterLast","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n    Returns a dataset consisting of labeled wireless sensor network data set\n    collected from a multi-hop wireless sensor network deployment using TelosB\n    motes.\n\n    Humidity and temperature measurements were collected at 5 second intervals\n    over a six hour period on July 10, 2010.\n\n    Temperature is in degrees Celsius.\n\n    Humidity is temperature corrected relative humidity, ranging from 0-100%.\n\n    The label '0' denotes normal data, and the label '1' denotes an introduced\n    event.\n\n    If a mote was an indoor sensor, the corresponding indicator is '1'. If a\n    mote was an outdoor sensor, the indoor indicator is '0'.\n\n    Returns\n    -------\n    out: Array<Object>\n        Sensor data.\n\n    Examples\n    --------\n    > var data = SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n    [{...}, {...}, ...]\n\n    References\n    ----------\n    - Suthaharan, Shan, Mohammed Alzahrani, Sutharshan Rajasegarar, Christopher\n    Leckie, and Marimuthu Palaniswami. 2010. \"Labelled data collection for\n    anomaly detection in wireless sensor networks.\" In _Proceedings of the Sixth\n    International Conference on Intelligent Sensors, Sensor Networks and\n    Information Processing (ISSNIP 2010)_. Brisbane, Australia: IEEE.\n\n    * If you use the data for publication or third party consumption, please\n    cite the listed reference.\n\n    See Also\n    --------\n    SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK\n","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n    Returns a dataset consisting of labeled wireless sensor network data set\n    collected from a simple single-hop wireless sensor network deployment using\n    TelosB motes.\n\n    Humidity and temperature measurements were collected at 5 second intervals\n    over a six hour period on May 9, 2010.\n\n    Temperature is in degrees Celsius.\n\n    Humidity is temperature corrected relative humidity, ranging from 0-100%.\n\n    The label '0' denotes normal data, and the label '1' denotes an introduced\n    event.\n\n    If a mote was an indoor sensor, the corresponding indicator is '1'. If a\n    mote was an outdoor sensor, the indoor indicator is '0'.\n\n    Returns\n    -------\n    out: Array<Object>\n        Sensor data.\n\n    Examples\n    --------\n    > var data = SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n    [{...}, {...}, ...]\n\n    References\n    ----------\n    - Suthaharan, Shan, Mohammed Alzahrani, Sutharshan Rajasegarar, Christopher\n    Leckie, and Marimuthu Palaniswami. 2010. \"Labelled data collection for\n    anomaly detection in wireless sensor networks.\" In _Proceedings of the Sixth\n    International Conference on Intelligent Sensors, Sensor Networks and\n    Information Processing (ISSNIP 2010)_. Brisbane, Australia: IEEE.\n\n    * If you use the data for publication or third party consumption, please\n    cite the listed reference.\n\n    See Also\n    --------\n    SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK\n","Symbol":"\nSymbol( [description] )\n    Returns a symbol.\n\n    Unlike conventional constructors, this function does **not** support the\n    `new` keyword.\n\n    This function is only supported in environments which support symbols.\n\n    Parameters\n    ----------\n    description: string (optional)\n        Symbol description which can be used for debugging but not to access the\n        symbol itself.\n\n    Returns\n    -------\n    out: symbol\n        Symbol.\n\n    Examples\n    --------\n    > var s = ( Symbol ) ? Symbol( 'beep' ) : null\n\n","tabulate":"\ntabulate( collection )\n    Generates a frequency table.\n\n    The table is an array of arrays where each sub-array corresponds to a unique\n    value in the input collection. Each sub-array is structured as follows:\n\n    - 0: unique value.\n    - 1: value count.\n    - 2: frequency percentage.\n\n    If provided an empty collection, the function returns an empty array.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection to tabulate. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    Returns\n    -------\n    out: Array<Array>|Array\n        Frequency table.\n\n    Examples\n    --------\n    > var collection = [ 'beep', 'boop', 'foo', 'beep' ];\n    > var out = tabulate( collection )\n    [ [ 'beep', 2, 0.5 ], [ 'boop', 1, 0.25 ], [ 'foo', 1, 0.25 ] ]\n\n    See Also\n    --------\n    countBy, groupBy, tabulateBy\n","tabulateBy":"\ntabulateBy( collection, [options,] indicator )\n    Generates a frequency table according to an indicator function.\n\n    When invoked, the indicator function is provided two arguments:\n\n    - value: collection value.\n    - index: collection index.\n\n    The table is an array of arrays where each sub-array corresponds to a unique\n    value in the input collection. Each sub-array is structured as follows:\n\n    - 0: unique value.\n    - 1: value count.\n    - 2: frequency percentage.\n\n    If provided an empty collection, the function returns an empty array.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection to tabulate. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Options.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    indicator: Function\n        Indicator function specifying how to categorize a collection element.\n\n    Returns\n    -------\n    out: Array<Array>|Array\n        Frequency table.\n\n    Examples\n    --------\n    > function indicator( value ) { return value[ 0 ]; };\n    > var collection = [ 'beep', 'boop', 'foo', 'beep' ];\n    > var out = tabulateBy( collection, indicator )\n    [ [ 'b', 3, 0.75 ], [ 'f', 1, 0.25 ] ]\n\n    See Also\n    --------\n    countBy, groupBy, tabulate\n","tabulateByAsync":"\ntabulateByAsync( collection, [options,] indicator, done )\n    Generates a frequency table according to an indicator function.\n\n    The table is an array of arrays where each sub-array corresponds to a unique\n    value in the input collection. Each sub-array is structured as follows:\n\n    - 0: unique value.\n    - 1: value count.\n    - 2: frequency percentage.\n\n    When invoked, the indicator function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If the\n    indicator function accepts two arguments, the indicator function is\n    provided:\n\n    - value\n    - next\n\n    If the indicator function accepts three arguments, the indicator function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other indicator function signature, the indicator function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - group: value group.\n\n    If an indicator function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    If provided an empty collection, the function calls the `done` callback with\n    an empty array as the second argument.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    indicator: Function\n        Indicator function specifying how to categorize a collection element.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000, 750 ];\n    > tabulateByAsync( arr, indicator, done )\n    750\n    1000\n    2500\n    3000\n    [ [ 'odd', 2, 0.5 ], [ 'even', 2, 0.5 ] ]\n\n    // Limit number of concurrent invocations:\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 3000, 2500, 1000, 750 ];\n    > tabulateByAsync( arr, opts, indicator, done )\n    2500\n    3000\n    1000\n    750\n    [ [ 'odd', 2, 0.5 ], [ 'even', 2, 0.5 ] ]\n\n    // Process sequentially:\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 3000, 2500, 1000, 750 ];\n    > tabulateByAsync( arr, opts, indicator, done )\n    3000\n    2500\n    1000\n    750\n    [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n\ntabulateByAsync.factory( [options,] indicator )\n    Returns a function which generates a frequency table according to an\n    indicator function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    indicator: Function\n        Indicator function specifying how to categorize a collection element.\n\n    Returns\n    -------\n    out: Function\n        A function which generates a frequency table according to an indicator\n        function.\n\n    Examples\n    --------\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = tabulateByAsync.factory( opts, indicator );\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000, 750 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    750\n    [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n    > arr = [ 2000, 1500, 1000, 750 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    750\n    [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n    See Also\n    --------\n    countByAsync, groupByAsync, tabulateBy\n","tabulateByAsync.factory":"\ntabulateByAsync.factory( [options,] indicator )\n    Returns a function which generates a frequency table according to an\n    indicator function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    indicator: Function\n        Indicator function specifying how to categorize a collection element.\n\n    Returns\n    -------\n    out: Function\n        A function which generates a frequency table according to an indicator\n        function.\n\n    Examples\n    --------\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = tabulateByAsync.factory( opts, indicator );\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000, 750 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    750\n    [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n    > arr = [ 2000, 1500, 1000, 750 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    750\n    [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n    See Also\n    --------\n    countByAsync, groupByAsync, tabulateBy","thunk":"\nthunk( fcn[, ...args] )\n    Returns a thunk.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to convert to a thunk.\n\n    args: ...any (optional)\n        Function arguments.\n\n    Returns\n    -------\n    out: Function\n        Thunk.\n\n    Examples\n    --------\n    > var fcn = thunk( base.add, 2, 3 );\n    > var v = fcn()\n    5\n    > v = fcn()\n    5\n\n","tic":"\ntic()\n    Returns a high-resolution time.\n\n    The returned array has the following format: `[seconds, nanoseconds]`.\n\n    Returns\n    -------\n    out: Array<integer>\n        High resolution time.\n\n    Examples\n    --------\n    > var t = tic()\n    [ <number>, <number> ]\n\n    See Also\n    --------\n    toc\n","timeit":"\ntimeit( code, [options,] clbk )\n    Times a snippet.\n\n    If the `asynchronous` option is set to `true`, the implementation assumes\n    that `before`, `after`, and `code` snippets are all asynchronous.\n    Accordingly, these snippets should invoke a `next( [error] )` callback\n    once complete. The implementation wraps the snippet within a function\n    accepting two arguments: `state` and `next`.\n\n    The `state` parameter is simply an empty object which allows the `before`,\n    `after`, and `code` snippets to share state.\n\n    Notes:\n\n    - Snippets always run in strict mode.\n    - Always verify results. Doing so prevents the compiler from performing dead\n      code elimination and other optimization techniques, which would render\n      timing results meaningless.\n    - Executed code is not sandboxed and has access to the global state. You are\n      strongly advised against timing untrusted code. To time untrusted code,\n      do so in an isolated environment (e.g., a separate process with restricted\n      access to both global state and the host environment).\n    - Wrapping asynchronous code does add overhead, but, in most cases, the\n      overhead should be negligible compared to the execution cost of the timed\n      snippet.\n    - When the `asynchronous` option is `true`, ensure that the main `code`\n      snippet is actually asynchronous. If a snippet releases the zalgo, an\n      error complaining about exceeding the maximum call stack size is highly\n      likely.\n    - While many benchmark frameworks calculate various statistics over raw\n      timing results (e.g., mean and standard deviation), do not do this.\n      Instead, consider the fastest time an approximate lower bound for how fast\n      an environment can execute a snippet. Slower times are more likely\n      attributable to other processes interfering with timing accuracy rather\n      than attributable to variability in JavaScript's speed. In which case, the\n      minimum time is most likely the only result of interest. When considering\n      all raw timing results, apply common sense rather than statistics.\n\n    Parameters\n    ----------\n    code: string\n         Snippet to time.\n\n    options: Object (optional)\n        Options.\n\n    options.before: string (optional)\n        Setup code. Default: `''`.\n\n    options.after: string (optional)\n        Cleanup code. Default: `''`.\n\n    options.iterations: integer|null (optional)\n        Number of iterations. If `null`, the number of iterations is determined\n        by trying successive powers of `10` until the total time is at least\n        `0.1` seconds. Default: `1e6`.\n\n    options.repeats: integer (optional)\n        Number of repeats. Default: `3`.\n\n    options.asynchronous: boolean (optional)\n        Boolean indicating whether a snippet is asynchronous. Default: `false`.\n\n    clbk: Function\n        Callback to invoke upon completion.\n\n    Examples\n    --------\n    > var code = 'var x = Math.pow( Math.random(), 3 );';\n    > code += 'if ( x !== x ) {';\n    > code += 'throw new Error( \\'Something went wrong.\\' );';\n    > code += '}';\n    > function done( error, results ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.dir( results );\n    ... };\n    > timeit( code, done )\n    e.g.,\n    {\n        \"iterations\": 1000000,\n        \"repeats\": 3,\n        \"min\": [ 0, 135734733 ],    // [seconds,nanoseconds]\n        \"elapsed\": 0.135734733,     // seconds\n        \"rate\": 7367311.062526641,  // iterations/second\n        \"times\": [                  // raw timing results\n            [ 0, 145641393 ],\n            [ 0, 135734733 ],\n            [ 0, 140462721 ]\n        ]\n    }\n\n","tmpdir":"\ntmpdir()\n    Returns the directory for storing temporary files.\n\n    Returns\n    -------\n    dir: string\n        Directory for temporary files.\n\n    Examples\n    --------\n    > var dir = tmpdir()\n    e.g., '/path/to/temporary/files/directory'\n\n    See Also\n    --------\n    configdir, homedir\n","toc":"\ntoc( time )\n    Returns a high-resolution time difference, where `time` is a two-element\n    array with format `[seconds, nanoseconds]`.\n\n    Similar to `time`, the returned array has format `[seconds, nanoseconds]`.\n\n    Parameters\n    ----------\n    time: Array<integer>\n        High-resolution time.\n\n    Returns\n    -------\n    out: Array<integer>\n        High resolution time difference.\n\n    Examples\n    --------\n    > var start = tic();\n    > var delta = toc( start )\n    [ <number>, <number> ]\n\n    See Also\n    --------\n    tic\n","tokenize":"\ntokenize( str[, keepWhitespace] )\n    Tokenizes a string.\n\n    To include whitespace characters (spaces, tabs, line breaks) in the output\n    array, set `keepWhitespace` to `true`.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    keepWhitespace: boolean (optional)\n        Boolean indicating whether whitespace characters should be returned as\n        part of the token array. Default: `false`.\n\n    Returns\n    -------\n    out: Array\n        Array of tokens.\n\n    Examples\n    --------\n    > var out = tokenize( 'Hello Mrs. Maple, could you call me back?' )\n    [ 'Hello', 'Mrs.', 'Maple', ',', 'could', 'you', 'call', 'me', 'back', '?' ]\n\n    > out = tokenize( 'Hello World!', true )\n    [ 'Hello', ' ', 'World', '!' ]\n\n","transformStream":"\ntransformStream( [options] )\n    Returns a transform stream.\n\n    If a transform function is not provided, the returned stream will be a\n    simple pass through stream.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.transform: Function (optional)\n        Callback to invoke upon receiving a new chunk.\n\n    options.flush: Function (optional)\n        Callback to invoke after receiving all chunks and prior to a stream\n        closing.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to decode strings into Buffer objects when writing.\n        Default: true.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream.\n\n    Examples\n    --------\n    > var s = transformStream();\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();\n\n\ntransformStream.factory( [options] )\n    Returns a function for creating transform streams.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to decode strings into Buffer objects when writing.\n        Default: true.\n\n    Returns\n    -------\n    createStream( transform[, flush] ): Function\n        Function for creating transform streams.\n\n    Examples\n    --------\n    > var opts = { 'highWaterMark': 64 };\n    > var createStream = transformStream.factory( opts );\n    > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n    > var s = createStream( fcn );\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();\n\n\ntransformStream.objectMode( [options] )\n    Returns an \"objectMode\" transform stream.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.transform: Function (optional)\n        Callback to invoke upon receiving a new chunk.\n\n    options.flush: Function (optional)\n        Callback to invoke after receiving all chunks and prior to a stream\n        closing.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to decode strings into Buffer objects when writing.\n        Default: true.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > var s = transformStream.objectMode();\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();\n\n\ntransformStream.ctor( [options] )\n    Returns a custom transform stream constructor.\n\n    If provided `transform` and `flush` options, these methods are bound to the\n    constructor prototype.\n\n    If not provided a transform function, the returned constructor creates\n    simple pass through streams.\n\n    The returned constructor accepts the same options as the constructor\n    factory, *except* for the `transform` and `flush` options, which are not\n    supported.\n\n    Any options provided to the constructor *override* options provided to the\n    constructor factory.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.transform: Function (optional)\n        Callback to invoke upon receiving a new chunk.\n\n    options.flush: Function (optional)\n        Callback to invoke after receiving all chunks and prior to a stream\n        closing.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to decode strings into Buffer objects when writing.\n        Default: true.\n\n    Returns\n    -------\n    ctor: Function\n        Custom transform stream constructor.\n\n    Examples\n    --------\n    > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n    > var opts = { 'highWaterMark': 64, 'transform': fcn };\n    > var customStream = transformStream.ctor( opts );\n    > var s = customStream();\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();\n\n","transformStream.factory":"\ntransformStream.factory( [options] )\n    Returns a function for creating transform streams.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to decode strings into Buffer objects when writing.\n        Default: true.\n\n    Returns\n    -------\n    createStream( transform[, flush] ): Function\n        Function for creating transform streams.\n\n    Examples\n    --------\n    > var opts = { 'highWaterMark': 64 };\n    > var createStream = transformStream.factory( opts );\n    > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n    > var s = createStream( fcn );\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();","transformStream.objectMode":"\ntransformStream.objectMode( [options] )\n    Returns an \"objectMode\" transform stream.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.transform: Function (optional)\n        Callback to invoke upon receiving a new chunk.\n\n    options.flush: Function (optional)\n        Callback to invoke after receiving all chunks and prior to a stream\n        closing.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to decode strings into Buffer objects when writing.\n        Default: true.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > var s = transformStream.objectMode();\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();","transformStream.ctor":"\ntransformStream.ctor( [options] )\n    Returns a custom transform stream constructor.\n\n    If provided `transform` and `flush` options, these methods are bound to the\n    constructor prototype.\n\n    If not provided a transform function, the returned constructor creates\n    simple pass through streams.\n\n    The returned constructor accepts the same options as the constructor\n    factory, *except* for the `transform` and `flush` options, which are not\n    supported.\n\n    Any options provided to the constructor *override* options provided to the\n    constructor factory.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.transform: Function (optional)\n        Callback to invoke upon receiving a new chunk.\n\n    options.flush: Function (optional)\n        Callback to invoke after receiving all chunks and prior to a stream\n        closing.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to decode strings into Buffer objects when writing.\n        Default: true.\n\n    Returns\n    -------\n    ctor: Function\n        Custom transform stream constructor.\n\n    Examples\n    --------\n    > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n    > var opts = { 'highWaterMark': 64, 'transform': fcn };\n    > var customStream = transformStream.ctor( opts );\n    > var s = customStream();\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();","trim":"\ntrim( str )\n    Trims whitespace from the beginning and end of a `string`.\n\n    \"Whitespace\" is defined as the following characters:\n\n    - \\f\n    - \\n\n    - \\r\n    - \\t\n    - \\v\n    - \\u0020\n    - \\u00a0\n    - \\u1680\n    - \\u2000-\\u200a\n    - \\u2028\n    - \\u2029\n    - \\u202f\n    - \\u205f\n    - \\u3000\n    - \\ufeff\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Trimmed string.\n\n    Examples\n    --------\n    > var out = trim( ' \\t\\t\\n  Beep \\r\\n\\t  ' )\n    'Beep'\n\n    See Also\n    --------\n    ltrim, pad, rtrim\n","truncate":"\ntruncate( str, len[, ending] )\n    Truncates a string to a specified length.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    len: integer\n        Output string length.\n\n    ending: string (optional)\n        Custom ending. Default: '...'.\n\n    Returns\n    -------\n    out: string\n        Truncated string.\n\n    Examples\n    --------\n    > var str = 'beep boop';\n    > var out = truncate( str, 5 )\n    'be...'\n\n    > out = truncate( str, 5, '|' )\n    'beep|'\n\n    See Also\n    --------\n    truncateMiddle","truncateMiddle":"\ntruncateMiddle( str, len[, seq] )\n    Truncates a string in the middle to a specified length.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    len: integer\n        Output string length.\n\n    seq: string (optional)\n        Custom replacement sequence. Default: '...'.\n\n    Returns\n    -------\n    out: string\n        Truncated string.\n\n    Examples\n    --------\n    > var str = 'beep boop';\n    > var out = truncateMiddle( str, 5 )\n    'b...p'\n\n    > out = truncateMiddle( str, 5, '|' )\n    'be|op'\n\n    See Also\n    --------\n    truncate","trycatch":"\ntrycatch( x, y )\n    If a function does not throw, returns the function return value; otherwise,\n    returns `y`.\n\n    Parameters\n    ----------\n    x: Function\n        Function to try invoking.\n\n    y: any\n        Value to return if a function throws an error.\n\n    Returns\n    -------\n    z: any\n        Either the return value of `x` or the provided argument `y`.\n\n    Examples\n    --------\n    > function x() {\n    ...     if ( base.random.randu() < 0.5 ) {\n    ...         throw new Error( 'beep' );\n    ...     }\n    ...     return 1.0;\n    ... };\n    > var z = trycatch( x, -1.0 )\n    <number>\n\n    See Also\n    --------\n    trycatchAsync, trythen\n","trycatchAsync":"\ntrycatchAsync( x, y, done )\n    If a function does not return an error, invokes a callback with the function\n    result; otherwise, invokes a callback with a value `y`.\n\n    A function `x` is provided a single argument:\n\n    - clbk: callback to invoke upon function completion.\n\n    The callback function accepts two arguments:\n\n    - error: error object.\n    - result: function result.\n\n    The `done` callback is invoked upon function completion and is provided two\n    arguments:\n\n    - error: error object.\n    - result: either the result of `x` or the provided argument `y`.\n\n    If `x` invokes `clbk` with an error argument, the function invokes the\n    `done` callback with both the error and the argument `y`.\n\n    If `x` does not invoke `clbk` with an error argument, the function invokes\n    the `done` callback with a first argument equal to `null` and the function\n    `result`.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Parameters\n    ----------\n    x: Function\n        Function to invoke.\n\n    y: any\n        Value to return if `x` returns an error.\n\n    done: Function\n        Callback to invoke upon completion.\n\n    Examples\n    --------\n    > function x( clbk ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         clbk( new Error( 'beep' ) );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         // process error...\n    ...     }\n    ...     console.log( result );\n    ... };\n    > trycatchAsync( x, 'boop', done )\n    'boop'\n\n    See Also\n    --------\n    trycatch, trythenAsync\n","tryFunction":"\ntryFunction( fcn[, thisArg] )\n    Wraps a function in a try/catch block.\n\n    If provided an asynchronous function, the returned function only traps\n    errors which occur during the current event loop tick.\n\n    If a function throws a literal, the literal is serialized as a string and\n    returned as an `Error` object.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to wrap.\n\n    thisArg: any (optional)\n        Function context.\n\n    Returns\n    -------\n    out: Function\n        Wrapped function.\n\n    Examples\n    --------\n    > function fcn() { throw new Error( 'beep boop' ); };\n    > var f = tryFunction( fcn );\n    > var out = f();\n    > out.message\n    'beep boop'\n\n","tryRequire":"\ntryRequire( id )\n    Wraps `require` in a `try/catch` block.\n\n    This function traps and returns any errors encountered when attempting to\n    require a module.\n\n    Use caution when attempting to resolve a relative path or a local module.\n    This function attempts to resolve a module from its current path. Thus, the\n    function is unable to resolve anything which is not along its search path.\n    For local requires, use an absolute file path.\n\n    Parameters\n    ----------\n    id: string\n        Module id.\n\n    Returns\n    -------\n    out: any|Error\n        Resolved module or an `Error`.\n\n    Examples\n    --------\n    > var out = tryRequire( '_unknown_module_id_' )\n    <Error>\n\n","trythen":"\ntrythen( x, y )\n    If a function does not throw, returns the function return value; otherwise,\n    returns the value returned by a second function `y`.\n\n    The function `y` is provided a single argument:\n\n    - error: the error thrown by `x`.\n\n    Parameters\n    ----------\n    x: Function\n        Function to try invoking.\n\n    y: Function\n        Function to invoke if an initial function throws an error.\n\n    Returns\n    -------\n    z: any\n        The return value of either `x` or `y`.\n\n    Examples\n    --------\n    > function x() {\n    ...     if ( base.random.randu() < 0.5 ) {\n    ...         throw new Error( 'beep' );\n    ...     }\n    ...     return 1.0;\n    ... };\n    > function y() {\n    ...     return -1.0;\n    ... };\n    > var z = trythen( x, y )\n    <number>\n\n    See Also\n    --------\n    trycatch, trythenAsync\n","trythenAsync":"\ntrythenAsync( x, y, done )\n    If a function does not return an error, invokes a callback with the function\n    result; otherwise, invokes a second function `y`.\n\n    A function `x` is provided a single argument:\n\n    - clbk: callback to invoke upon function completion.\n\n    The callback function accepts any number of arguments, with the first\n    argument reserved for providing an error.\n\n    If the error argument is falsy, the function invokes a `done` callback with\n    its first argument as `null` and all other provided arguments.\n\n    If the error argument is truthy, the function invokes a function `y`. The\n    number of arguments provided to `y` depends on the function's length. If `y`\n    is a unary function, `y` is provided a single argument:\n\n    - clbk: callback to invoke upon function completion.\n\n    Otherwise, `y` is provided two arguments:\n\n    - error: the error from `x`.\n    - clbk: callback to invoke upon function completion.\n\n    The callback function accepts any number of arguments, with the first\n    argument reserved for providing an error.\n\n    If the error argument is falsy, the `done` callback is invoked with its\n    first argument equal to `null` and all other arguments provided by `y`.\n\n    If the error argument is truthy, the `done` callback is invoked with only\n    the error argument provided by `y`.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Parameters\n    ----------\n    x: Function\n        Function to invoke.\n\n    y: Function\n        Function to invoke if `x` returns an error.\n\n    done: Function\n        Callback to invoke upon completion.\n\n    Examples\n    --------\n    > function x( clbk ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         clbk( new Error( 'beep' ) );\n    ...     }\n    ... };\n    > function y( clbk ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         clbk( null, 'boop' );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > trythenAsync( x, y, done )\n    'boop'\n\n    See Also\n    --------\n    trycatchAsync, trythen\n","ttest":"\nttest( x[, y][, options] )\n    Computes a one-sample or paired Student's t test.\n\n    When no `y` is supplied, the function performs a one-sample t-test for the\n    null hypothesis that the data in array or typed array `x` is drawn from a\n    normal distribution with mean zero and unknown variance.\n\n    When array or typed array `y` is supplied, the function tests whether the\n    differences `x - y` come from a normal distribution with mean zero and\n    unknown variance via the paired t-test.\n\n    The returned object comes with a `.print()` method which when invoked will\n    print a formatted output of the results of the hypothesis test.\n\n    Parameters\n    ----------\n    x: Array<number>\n        Data array.\n\n    y: Array<number> (optional)\n        Paired data array.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.alternative: string (optional)\n        Indicates whether the alternative hypothesis is that the mean of `x` is\n        larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n        `mu` (`two-sided`). Default: `'two-sided'`.\n\n    options.mu: number (optional)\n        Hypothesized true mean under the null hypothesis. Set this option to\n        test whether the data comes from a distribution with the specified `mu`.\n        Default: `0`.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Used significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.ci: Array<number>\n        1-alpha confidence interval for the mean.\n\n    out.nullValue: number\n        Assumed mean under H0 (or difference in means when `y` is supplied).\n\n    out.alternative: string\n        Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n    out.df: number\n        Degrees of freedom.\n\n    out.mean: number\n        Sample mean of `x` or `x - y`, respectively.\n\n    out.sd: number\n        Standard error of the mean.\n\n    out.method: string\n        Name of test.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    // One-sample t-test:\n    > var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 5776 } );\n    > var x = new Array( 100 );\n    > for ( var i = 0; i < x.length; i++ ) {\n    ...     x[ i ] = rnorm();\n    ... }\n    > var out = ttest( x )\n    {\n        rejected: false,\n        pValue: ~0.722,\n        statistic: ~0.357,\n        ci: [~-0.333,~0.479],\n        // ...\n    }\n\n    // Paired t-test:\n    > rnorm = base.random.normal.factory( 1.0, 2.0, { 'seed': 786 } );\n    > x = new Array( 100 );\n    > var y = new Array( 100 );\n    > for ( i = 0; i < x.length; i++ ) {\n    ...     x[ i ] = rnorm();\n    ...     y[ i ] = rnorm();\n    ... }\n    > out = ttest( x, y )\n    {\n        rejected: false,\n        pValue: ~0.191,\n        statistic: ~1.315,\n        ci: [ ~-0.196, ~0.964 ],\n        // ...\n    }\n\n    // Print formatted output:\n    > var table = out.print()\n    Paired t-test\n\n    Alternative hypothesis: True difference in means is not equal to 0\n\n        pValue: 0.1916\n        statistic: 1.3148\n        df: 99\n        95% confidence interval: [-0.1955,0.9635]\n\n    Test Decision: Fail to reject null in favor of alternative at 5%\n    significance level\n\n    // Choose custom significance level:\n    > var arr = [ 2, 4, 3, 1, 0 ];\n    > out = ttest( arr, { 'alpha': 0.01 } );\n    > table = out.print()\n    One-sample t-test\n\n    Alternative hypothesis: True mean is not equal to 0\n\n        pValue: 0.0474\n        statistic: 2.8284\n        df: 4\n        99% confidence interval: [-1.2556,5.2556]\n\n    Test Decision: Fail to reject null in favor of alternative at 1%\n    significance level\n\n    // Test for a mean equal to five:\n    > arr = [ 4, 4, 6, 6, 5 ];\n    > out = ttest( arr, { 'mu': 5 } )\n    {\n        rejected: false,\n        pValue: 1,\n        statistic: 0,\n        ci: [ ~3.758, ~6.242 ],\n        // ...\n    }\n\n    // Perform one-sided tests:\n    > arr = [ 4, 4, 6, 6, 5 ];\n    > out = ttest( arr, { 'alternative': 'less' } );\n    > table = out.print()\n    One-sample t-test\n\n    Alternative hypothesis: True mean is less than 0\n\n        pValue: 0.9998\n        statistic: 11.1803\n        df: 4\n        95% confidence interval: [-Infinity,5.9534]\n\n    Test Decision: Fail to reject null in favor of alternative at 5%\n    significance level\n\n    > out = ttest( arr, { 'alternative': 'greater' } );\n    > table = out.print()\n    One-sample t-test\n\n    Alternative hypothesis: True mean is greater than 0\n\n        pValue: 0.0002\n        statistic: 11.1803\n        df: 4\n        95% confidence interval: [4.0466,Infinity]\n\n    Test Decision: Reject null in favor of alternative at 5% significance level\n\n    See Also\n    --------\n    ttest2\n","ttest2":"\nttest2( x, y[, options] )\n    Computes a two-sample Student's t test.\n\n    By default, the function performs a two-sample t-test for the null\n    hypothesis that the data in arrays or typed arrays `x` and `y` is\n    independently drawn from normal distributions with equal means.\n\n    The returned object comes with a `.print()` method which when invoked will\n    print a formatted output of the results of the hypothesis test.\n\n    Parameters\n    ----------\n    x: Array<number>\n        First data array.\n\n    y: Array<number>\n        Second data array.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.alternative: string (optional)\n        Either `two-sided`, `less` or `greater`. Indicates whether the\n        alternative hypothesis is that `x` has a larger mean than `y`\n        (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n        the same (`two-sided`). Default: `'two-sided'`.\n\n    options.difference: number (optional)\n        Number denoting the difference in means under the null hypothesis.\n        Default: `0`.\n\n    options.variance: string (optional)\n        String indicating if the test should be conducted under the assumption\n        that the unknown variances of the normal distributions are `equal` or\n        `unequal`. As a default choice, the function carries out the Welch test\n        (using the Satterthwaite approximation for the degrees of freedom),\n        which does not have the requirement that the variances of the underlying\n        distributions are equal. If the equal variances assumption seems\n        warranted, set the option to `equal`. Default: `unequal`.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Used significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.ci: Array<number>\n        1-alpha confidence interval for the mean.\n\n    out.nullValue: number\n        Assumed difference in means under H0.\n\n    out.xmean: number\n        Sample mean of `x`.\n\n    out.ymean: number\n        Sample mean of `y`.\n\n    out.alternative: string\n        Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n    out.df: number\n        Degrees of freedom.\n\n    out.method: string\n        Name of test.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    // Student's sleep data:\n    > var x = [ 0.7, -1.6, -0.2, -1.2, -0.1, 3.4, 3.7, 0.8, 0.0, 2.0 ];\n    > var y = [ 1.9, 0.8, 1.1, 0.1, -0.1, 4.4, 5.5, 1.6, 4.6, 3.4 ];\n    > var out = ttest2( x, y )\n    {\n        rejected: false,\n        pValue: ~0.079,\n        statistic: ~-1.861,\n        ci: [ ~-3.365, ~0.205 ],\n        // ...\n    }\n\n    // Print table output:\n    > var table = out.print()\n    Welch two-sample t-test\n\n    Alternative hypothesis: True difference in means is not equal to 0\n\n        pValue: 0.0794\n        statistic: -1.8608\n        95% confidence interval: [-3.3655,0.2055]\n\n    Test Decision: Fail to reject null in favor of alternative at 5%\n    significance level\n\n    // Choose a different significance level than `0.05`:\n    > out = ttest2( x, y, { 'alpha': 0.1 } );\n    > table = out.print()\n    Welch two-sample t-test\n\n    Alternative hypothesis: True difference in means is not equal to 0\n\n        pValue: 0.0794\n        statistic: -1.8608\n        90% confidence interval: [-3.0534,-0.1066]\n\n    Test Decision: Reject null in favor of alternative at 10% significance level\n\n    // Perform one-sided tests:\n    > out = ttest2( x, y, { 'alternative': 'less' } );\n    > table = out.print()\n    Welch two-sample t-test\n\n    Alternative hypothesis: True difference in means is less than 0\n\n        pValue: 0.0397\n        statistic: -1.8608\n        df: 17.7765\n        95% confidence interval: [-Infinity,-0.1066]\n\n    Test Decision: Reject null in favor of alternative at 5% significance level\n\n    > out = ttest2( x, y, { 'alternative': 'greater' } );\n    > table = out.print()\n    Welch two-sample t-test\n\n    Alternative hypothesis: True difference in means is greater than 0\n\n        pValue: 0.9603\n        statistic: -1.8608\n        df: 17.7765\n        95% confidence interval: [-3.0534,Infinity]\n\n    Test Decision: Fail to reject null in favor of alternative at 5%\n    significance level\n\n    // Run tests with equal variances assumption:\n    > x = [ 2, 3, 1, 4 ];\n    > y = [ 1, 2, 3, 1, 2, 5, 3, 4 ];\n    > out = ttest2( x, y, { 'variance': 'equal' } );\n    > table = out.print()\n    Two-sample t-test\n\n    Alternative hypothesis: True difference in means is not equal to 0\n\n        pValue: 0.8848\n        statistic: -0.1486\n        df: 10\n        95% confidence interval: [-1.9996,1.7496]\n\n    Test Decision: Fail to reject null in favor of alternative at 5%\n    significance level\n\n    // Test for a difference in means besides zero:\n    > var rnorm = base.random.normal.factory({ 'seed': 372 } );\n    > x = new Array( 100 );\n    > for ( i = 0; i < x.length; i++ ) {\n    ...     x[ i ] = rnorm( 2.0, 3.0 );\n    ... }\n    > y = new Array( 100 );\n    > for ( i = 0; i < x.length; i++ ) {\n    ...     y[ i ] = rnorm( 1.0, 3.0 );\n    ... }\n    > out = ttest2( x, y, { 'difference': 1.0, 'variance': 'equal' } )\n    {\n        rejected: false,\n        pValue: ~0.642,\n        statistic: ~-0.466,\n        ci: [ ~-0.0455, ~1.646 ],\n        // ...\n    }\n\n    See Also\n    --------\n    ttest\n","TWO_PI":"\nTWO_PI\n    The mathematical constant `π` times `2`.\n\n    Examples\n    --------\n    > TWO_PI\n    6.283185307179586\n\n    See Also\n    --------\n    PI\n","typedarray":"\ntypedarray( [dtype] )\n    Creates a typed array.\n\n    Parameters\n    ----------\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = typedarray()\n    <Float64Array>\n    > arr = typedarray( 'float32' )\n    <Float32Array>\n\n\ntypedarray( length[, dtype] )\n    Returns a typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = typedarray( 5 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n    > arr = typedarray( 5, 'int32' )\n    <Int32Array>[ 0, 0, 0, 0, 0 ]\n\n\ntypedarray( typedarray[, dtype] )\n    Creates a typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = typedarray( [ 0.5, 0.5, 0.5 ] );\n    > var arr2 = typedarray( arr1, 'float32' )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]\n\n\ntypedarray( obj[, dtype] )\n    Creates a typed array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a typed array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 0.5, 0.5, 0.5 ];\n    > var arr2 = typedarray( arr1, 'float32' )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]\n\n\ntypedarray( buffer[, byteOffset[, length]][, dtype] )\n    Returns a typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 16 );\n    > var arr = typedarray( buf, 0, 4, 'float32' )\n    <Float32Array>[ 0.0, 0.0, 0.0, 0.0 ]\n\n    See Also\n    --------\n    Complex128Array, Complex64Array, Float64Array, Float32Array, Int32Array, Uint32Array, Int16Array, Uint16Array, Int8Array, Uint8Array, Uint8ClampedArray\n","typedarray2json":"\ntypedarray2json( arr )\n    Returns a JSON representation of a typed array.\n\n    The following typed array types are supported:\n\n    - Float64Array\n    - Float32Array\n    - Int32Array\n    - Uint32Array\n    - Int16Array\n    - Uint16Array\n    - Int8Array\n    - Uint8Array\n    - Uint8ClampedArray\n    - Complex64Array\n    - Complex128Array\n    - BooleanArray\n\n    The returned JSON object has the following properties:\n\n    - type: typed array type.\n    - data: typed array data as a generic array.\n\n    The implementation supports custom typed arrays and sets the `type` field to\n    the closest known typed array type.\n\n    Parameters\n    ----------\n    arr: TypedArray\n        Typed array to serialize.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 2 );\n    > arr[ 0 ] = 5.0;\n    > arr[ 1 ] = 3.0;\n    > var json = typedarray2json( arr )\n    { 'type': 'Float64Array', 'data': [ 5.0, 3.0 ] }\n\n    See Also\n    --------\n    reviveTypedArray\n","typedarrayCtors":"\ntypedarrayCtors( dtype )\n    Returns a typed array constructor.\n\n    The function returns constructors for the following data types:\n\n    - float32: single-precision floating-point numbers.\n    - float64: double-precision floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - complex128: double-precision complex floating-point numbers.\n    - bool: boolean values.\n    - int16: signed 16-bit integers.\n    - int32: signed 32-bit integers.\n    - int8: signed 8-bit integers.\n    - uint16: unsigned 16-bit integers.\n    - uint32: unsigned 32-bit integers.\n    - uint8: unsigned 8-bit integers.\n    - uint8c: unsigned clamped 8-bit integers.\n\n    Parameters\n    ----------\n    dtype: string\n        Data type.\n\n    Returns\n    -------\n    out: Function|null\n        Typed array constructor.\n\n    Examples\n    --------\n    > var ctor = typedarrayCtors( 'float64' )\n    <Function>\n    > ctor = typedarrayCtors( 'float' )\n    null\n\n    See Also\n    --------\n    arrayCtors\n","typedarrayDataTypes":"\ntypedarrayDataTypes()\n    Returns a list of typed array data types.\n\n    Returns\n    -------\n    out: Array<string>\n        List of typed array data types.\n\n    Examples\n    --------\n    > var out = typedarrayDataTypes()\n    <Array>\n\n    See Also\n    --------\n    arrayDataTypes, ndarrayDataTypes\n","typedarraypool":"\ntypedarraypool( [dtype] )\n    Returns an uninitialized typed array from a typed array memory pool.\n\n    Memory is **uninitialized**, which means that the contents of a returned\n    typed array may contain sensitive contents.\n\n    Parameters\n    ----------\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr = typedarraypool()\n    <Float64Array>[]\n    > arr = typedarraypool( 'float32' )\n    <Float32Array>[]\n\n\ntypedarraypool( length[, dtype] )\n    Returns an uninitialized typed array having a specified length from a typed\n    array memory pool.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr = typedarraypool( 5 )\n    <Float64Array>\n    > arr = typedarraypool( 5, 'int32' )\n    <Int32Array>\n\n\ntypedarraypool( typedarray[, dtype] )\n    Creates a pooled typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr1 = typedarraypool( [ 0.5, 0.5, 0.5 ] );\n    > var arr2 = typedarraypool( arr1, 'float32' )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool( obj[, dtype] )\n    Creates a pooled typed array from an array-like object.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object from which to generate a typed array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr1 = [ 0.5, 0.5, 0.5 ];\n    > var arr2 = typedarraypool( arr1, 'float32' )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.malloc( [dtype] )\n    Returns an uninitialized typed array from a typed array memory pool.\n\n    This method shares the same security vulnerabilities mentioned above.\n\n    Parameters\n    ----------\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr = typedarraypool.malloc()\n    <Float64Array>\n    > arr = typedarraypool.malloc( 'float32' )\n    <Float32Array>\n\n\ntypedarraypool.malloc( length[, dtype] )\n    Returns a typed array having a specified length from a typed array memory\n    pool.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr = typedarraypool.malloc( 5 )\n    <Float64Array>\n    > arr = typedarraypool.malloc( 5, 'int32' )\n    <Int32Array>\n\n\ntypedarraypool.malloc( typedarray[, dtype] )\n    Creates a pooled typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr1 = typedarraypool.malloc( [ 0.5, 0.5, 0.5 ] );\n    > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.malloc( obj[, dtype] )\n    Creates a pooled typed array from an array-like object.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object from which to generate a typed array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr1 = [ 0.5, 0.5, 0.5 ];\n    > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.calloc( [dtype] )\n    Returns a zero-initialized typed array from a typed array memory pool.\n\n    Parameters\n    ----------\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr = typedarraypool.calloc()\n    <Float64Array>[]\n    > arr = typedarraypool.calloc( 'float32' )\n    <Float32Array>[]\n\n\ntypedarraypool.calloc( length[, dtype] )\n    Returns a zero-initialized typed array having a specified length from a\n    typed array memory pool.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr = typedarraypool.calloc( 5 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n    > arr = typedarraypool.calloc( 5, 'int32' )\n    <Int32Array>[ 0, 0, 0, 0, 0 ]\n\n\ntypedarraypool.free( buf )\n    Frees a typed array or typed array buffer for use in a future allocation.\n\n    Parameters\n    ----------\n    buf: TypedArray|ArrayBuffer\n        Typed array or typed array buffer to free.\n\n    Examples\n    --------\n    > var arr = typedarraypool( 5 )\n    <Float64Array>\n    > typedarraypool.free( arr );\n\n\ntypedarraypool.clear()\n    Clears the typed array pool allowing garbage collection of previously\n    allocated (and currently free) array buffers.\n\n    Examples\n    --------\n    > var arr = typedarraypool( 5 )\n    <Float64Array>\n    > typedarraypool.free( arr );\n    > typedarraypool.clear();\n\n\ntypedarraypool.highWaterMark\n    Read-only property returning the pool's high water mark.\n\n    Once a high water mark is reached, typed array allocation fails.\n\n    Examples\n    --------\n    > typedarraypool.highWaterMark\n    <number>\n\n\ntypedarraypool.nbytes\n    Read-only property returning the total number of allocated bytes.\n\n    The returned value is the total accumulated value. Hence, anytime a pool\n    must allocate a new array buffer (i.e., more memory), the pool increments\n    this value.\n\n    The only time this value is decremented is when a pool is cleared.\n\n    This behavior means that, while allocated buffers which are never freed may,\n    in fact, be garbage collected, they continue to count against the high water\n    mark limit.\n\n    Accordingly, you should *always* free allocated buffers in order to prevent\n    the pool from believing that non-freed buffers are continually in use.\n\n    Examples\n    --------\n    > var arr = typedarraypool( 5 )\n    <Float64Array>\n    > typedarraypool.nbytes\n    <number>\n\n\ntypedarraypool.factory( [options] )\n    Creates a typed array pool.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.highWaterMark: integer (optional)\n        Maximum total memory (in bytes) which can be allocated.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating typed arrays from a typed array memory pool.\n\n    Examples\n    --------\n    > var pool = typedarraypool.factory();\n    > var arr1 = pool( 3, 'float64' )\n    <Float64Array>\n\n    See Also\n    --------\n    typedarray\n","typedarraypool.malloc":"\ntypedarraypool.malloc( [dtype] )\n    Returns an uninitialized typed array from a typed array memory pool.\n\n    This method shares the same security vulnerabilities mentioned above.\n\n    Parameters\n    ----------\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr = typedarraypool.malloc()\n    <Float64Array>\n    > arr = typedarraypool.malloc( 'float32' )\n    <Float32Array>typedarraypool.malloc( length[, dtype] )\n    Returns a typed array having a specified length from a typed array memory\n    pool.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr = typedarraypool.malloc( 5 )\n    <Float64Array>\n    > arr = typedarraypool.malloc( 5, 'int32' )\n    <Int32Array>typedarraypool.malloc( typedarray[, dtype] )\n    Creates a pooled typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr1 = typedarraypool.malloc( [ 0.5, 0.5, 0.5 ] );\n    > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]typedarraypool.malloc( obj[, dtype] )\n    Creates a pooled typed array from an array-like object.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object from which to generate a typed array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr1 = [ 0.5, 0.5, 0.5 ];\n    > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]","typedarraypool.calloc":"\ntypedarraypool.calloc( [dtype] )\n    Returns a zero-initialized typed array from a typed array memory pool.\n\n    Parameters\n    ----------\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr = typedarraypool.calloc()\n    <Float64Array>[]\n    > arr = typedarraypool.calloc( 'float32' )\n    <Float32Array>[]typedarraypool.calloc( length[, dtype] )\n    Returns a zero-initialized typed array having a specified length from a\n    typed array memory pool.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr = typedarraypool.calloc( 5 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n    > arr = typedarraypool.calloc( 5, 'int32' )\n    <Int32Array>[ 0, 0, 0, 0, 0 ]","typedarraypool.free":"\ntypedarraypool.free( buf )\n    Frees a typed array or typed array buffer for use in a future allocation.\n\n    Parameters\n    ----------\n    buf: TypedArray|ArrayBuffer\n        Typed array or typed array buffer to free.\n\n    Examples\n    --------\n    > var arr = typedarraypool( 5 )\n    <Float64Array>\n    > typedarraypool.free( arr );","typedarraypool.clear":"\ntypedarraypool.clear()\n    Clears the typed array pool allowing garbage collection of previously\n    allocated (and currently free) array buffers.\n\n    Examples\n    --------\n    > var arr = typedarraypool( 5 )\n    <Float64Array>\n    > typedarraypool.free( arr );\n    > typedarraypool.clear();","typedarraypool.highWaterMark":"\ntypedarraypool.highWaterMark\n    Read-only property returning the pool's high water mark.\n\n    Once a high water mark is reached, typed array allocation fails.\n\n    Examples\n    --------\n    > typedarraypool.highWaterMark\n    <number>","typedarraypool.nbytes":"\ntypedarraypool.nbytes\n    Read-only property returning the total number of allocated bytes.\n\n    The returned value is the total accumulated value. Hence, anytime a pool\n    must allocate a new array buffer (i.e., more memory), the pool increments\n    this value.\n\n    The only time this value is decremented is when a pool is cleared.\n\n    This behavior means that, while allocated buffers which are never freed may,\n    in fact, be garbage collected, they continue to count against the high water\n    mark limit.\n\n    Accordingly, you should *always* free allocated buffers in order to prevent\n    the pool from believing that non-freed buffers are continually in use.\n\n    Examples\n    --------\n    > var arr = typedarraypool( 5 )\n    <Float64Array>\n    > typedarraypool.nbytes\n    <number>","typedarraypool.factory":"\ntypedarraypool.factory( [options] )\n    Creates a typed array pool.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.highWaterMark: integer (optional)\n        Maximum total memory (in bytes) which can be allocated.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating typed arrays from a typed array memory pool.\n\n    Examples\n    --------\n    > var pool = typedarraypool.factory();\n    > var arr1 = pool( 3, 'float64' )\n    <Float64Array>\n\n    See Also\n    --------\n    typedarray","typemax":"\ntypemax( dtype )\n    Returns the maximum value of a specified numeric type.\n\n    The following numeric types are supported:\n\n    - float64: double-precision floating-point numbers.\n    - float32: single-precision floating-point numbers.\n    - float16: half-precision floating-point numbers.\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n\n    Parameters\n    ----------\n    dtype: string\n        Numeric type.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    > var m = typemax( 'int8' )\n    127\n    > m = typemax( 'uint32' )\n    4294967295\n\n    See Also\n    --------\n    realmax, typemin\n","typemin":"\ntypemin( dtype )\n    Returns the minimum value of a specified numeric type.\n\n    The following numeric types are supported:\n\n    - float64: double-precision floating-point numbers.\n    - float32: single-precision floating-point numbers.\n    - float16: half-precision floating-point numbers.\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n\n    Parameters\n    ----------\n    dtype: string\n        Numeric type.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    > var m = typemin( 'int8' )\n    -128\n    > m = typemin( 'uint32' )\n    0\n\n    See Also\n    --------\n    realmin, typemax\n","typeOf":"\ntypeOf( value )\n    Determines a value's type.\n\n    The following values are not natively provided in older JavaScript engines:\n\n    - Map\n    - Set\n    - WeakMap\n    - WeakSet\n    - Symbol\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    out: string\n        The value's type.\n\n    Examples\n    --------\n    // Built-ins:\n    > var t = typeOf( 'a' )\n    'string'\n    > t = typeOf( 5 )\n    'number'\n    > t = typeOf( NaN )\n    'number'\n    > t = typeOf( true )\n    'boolean'\n    > t = typeOf( false )\n    'boolean'\n    > t = typeOf( null )\n    'null'\n    > t = typeOf( undefined )\n    'undefined'\n    > t = typeOf( [] )\n    'array'\n    > t = typeOf( {} )\n    'object'\n    > t = typeOf( function noop() {} )\n    'function'\n    > t = typeOf( Symbol( 'beep' ) )\n    'symbol'\n    > t = typeOf( /.+/ )\n    'regexp'\n    > t = typeOf( new String( 'beep' ) )\n    'string'\n    > t = typeOf( new Number( 5 ) )\n    'number'\n    > t = typeOf( new Boolean( false ) )\n    'boolean'\n    > t = typeOf( new Array() )\n    'array'\n    > t = typeOf( new Object() )\n    'object'\n    > t = typeOf( new Int8Array( 10 ) )\n    'int8array'\n    > t = typeOf( new Uint8Array( 10 ) )\n    'uint8array'\n    > t = typeOf( new Uint8ClampedArray( 10 ) )\n    'uint8clampedarray'\n    > t = typeOf( new Int16Array( 10 ) )\n    'int16array'\n    > t = typeOf( new Uint16Array( 10 ) )\n    'uint16array'\n    > t = typeOf( new Int32Array( 10 ) )\n    'int32array'\n    > t = typeOf( new Uint32Array( 10 ) )\n    'uint32array'\n    > t = typeOf( new Float32Array( 10 ) )\n    'float32array'\n    > t = typeOf( new Float64Array( 10 ) )\n    'float64array'\n    > t = typeOf( new ArrayBuffer( 10 ) )\n    'arraybuffer'\n    > t = typeOf( new Date() )\n    'date'\n    > t = typeOf( new RegExp( '.+' ) )\n    'regexp'\n    > t = typeOf( new Map() )\n    'map'\n    > t = typeOf( new Set() )\n    'set'\n    > t = typeOf( new WeakMap() )\n    'weakmap'\n    > t = typeOf( new WeakSet() )\n    'weakset'\n    > t = typeOf( new Error( 'beep' ) )\n    'error'\n    > t = typeOf( new TypeError( 'beep' ) )\n    'typeerror'\n    > t = typeOf( new SyntaxError( 'beep' ) )\n    'syntaxerror'\n    > t = typeOf( new ReferenceError( 'beep' ) )\n    'referenceerror'\n    > t = typeOf( new URIError( 'beep' ) )\n    'urierror'\n    > t = typeOf( new RangeError( 'beep' ) )\n    'rangeerror'\n    > t = typeOf( new EvalError( 'beep' ) )\n    'evalerror'\n    > t = typeOf( Math )\n    'math'\n    > t = typeOf( JSON )\n    'json'\n\n    // Arguments object:\n    > function beep() { return arguments; };\n    > t = typeOf( beep() )\n    'arguments'\n\n    // Node.js Buffer object:\n    > t = typeOf( new Buffer( 10 ) )\n    'buffer'\n\n    // Custom constructor:\n    > function Person() { return this };\n    > t = typeOf( new Person() )\n    'person'\n\n    // Anonymous constructor:\n    > var Foo = function () { return this; };\n    > t = typeOf( new Foo() )\n    '' || 'foo'\n\n    See Also\n    --------\n    constructorName, nativeClass\n","UINT8_MAX":"\nUINT8_MAX\n    Maximum unsigned 8-bit integer.\n\n    The maximum unsigned 8-bit integer is given by `2^8 - 1`.\n\n    Examples\n    --------\n    > UINT8_MAX\n    255\n\n    See Also\n    --------\n    INT8_MAX\n","UINT8_NUM_BYTES":"\nUINT8_NUM_BYTES\n    Size (in bytes) of an 8-bit unsigned integer.\n\n    Examples\n    --------\n    > UINT8_NUM_BYTES\n    1\n\n    See Also\n    --------\n    INT8_NUM_BYTES, UINT16_NUM_BYTES, UINT32_NUM_BYTES\n","Uint8Array":"\nUint8Array()\n    A typed array constructor which returns a typed array representing an array\n    of 8-bit unsigned integers in the platform byte order.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array()\n    <Uint8Array>\n\n\nUint8Array( length )\n    Returns a typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( 5 )\n    <Uint8Array>[ 0, 0, 0, 0, 0 ]\n\n\nUint8Array( typedarray )\n    Creates a typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n    > var arr2 = new Uint8Array( arr1 )\n    <Uint8Array>[ 5, 5, 5 ]\n\n\nUint8Array( obj )\n    Creates a typed array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a typed array.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 5.0, 5.0, 5.0 ];\n    > var arr2 = new Uint8Array( arr1 )\n    <Uint8Array>[ 5, 5, 5 ]\n\n\nUint8Array( buffer[, byteOffset[, length]] )\n    Returns a typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 4 );\n    > var arr = new Uint8Array( buf, 0, 4 )\n    <Uint8Array>[ 0, 0, 0, 0 ]\n\n\nUint8Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Uint8Array.from( [ 1, 2 ], mapFcn )\n    <Uint8Array>[ 2, 4 ]\n\n\nUint8Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Uint8Array.of( 1, 2 )\n    <Uint8Array>[ 1, 2 ]\n\n\nUint8Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Uint8Array.BYTES_PER_ELEMENT\n    1\n\n\nUint8Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Uint8Array.name\n    'Uint8Array'\n\n\nUint8Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>\n\n\nUint8Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( 5 );\n    > arr.byteLength\n    5\n\n\nUint8Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( 5 );\n    > arr.byteOffset\n    0\n\n\nUint8Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    1\n\n\nUint8Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( 5 );\n    > arr.length\n    5\n\n\nUint8Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Uint8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2\n\n\nUint8Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true\n\n\nUint8Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false\n\n\nUint8Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Uint8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3\n\n\nUint8Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2\n\n\nUint8Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3\n\n\nUint8Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2\n\n\nUint8Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '\n\n\nUint8Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true\n\n\nUint8Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2\n\n\nUint8Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'\n\n\nUint8Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true\n\n\nUint8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3\n\n\nUint8Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Uint8Array>[ 2, 4, 6 ]\n\n\nUint8Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14\n\n\nUint8Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14\n\n\nUint8Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Uint8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] )\n    <Uint8Array>\n    > arr.reverse()\n    <Uint8Array>[ 3, 2, 1 ]\n\n\nUint8Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4\n\n\nUint8Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3\n\n\nUint8Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true\n\n\nUint8Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Uint8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Uint8Array>[ 0, 1, 1, 2, 2 ]\n\n\nUint8Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint8Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Uint8Array>[ 3, 4, 5 ]\n\n\nUint8Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'\n\n\nUint8Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'\n\n\nUint8Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8ClampedArray\n","Uint8Array.from":"\nUint8Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Uint8Array.from( [ 1, 2 ], mapFcn )\n    <Uint8Array>[ 2, 4 ]","Uint8Array.of":"\nUint8Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Uint8Array.of( 1, 2 )\n    <Uint8Array>[ 1, 2 ]","Uint8Array.BYTES_PER_ELEMENT":"\nUint8Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Uint8Array.BYTES_PER_ELEMENT\n    1","Uint8Array.name":"\nUint8Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Uint8Array.name\n    'Uint8Array'","Uint8Array.prototype.buffer":"\nUint8Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>","Uint8Array.prototype.byteLength":"\nUint8Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( 5 );\n    > arr.byteLength\n    5","Uint8Array.prototype.byteOffset":"\nUint8Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( 5 );\n    > arr.byteOffset\n    0","Uint8Array.prototype.BYTES_PER_ELEMENT":"\nUint8Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    1","Uint8Array.prototype.length":"\nUint8Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( 5 );\n    > arr.length\n    5","Uint8Array.prototype.copyWithin":"\nUint8Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Uint8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2","Uint8Array.prototype.entries":"\nUint8Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true","Uint8Array.prototype.every":"\nUint8Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false","Uint8Array.prototype.fill":"\nUint8Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Uint8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3","Uint8Array.prototype.filter":"\nUint8Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2","Uint8Array.prototype.find":"\nUint8Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3","Uint8Array.prototype.findIndex":"\nUint8Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2","Uint8Array.prototype.forEach":"\nUint8Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '","Uint8Array.prototype.includes":"\nUint8Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true","Uint8Array.prototype.indexOf":"\nUint8Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2","Uint8Array.prototype.join":"\nUint8Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'","Uint8Array.prototype.keys":"\nUint8Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true","Uint8Array.prototype.lastIndexOf":"\nUint8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3","Uint8Array.prototype.map":"\nUint8Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Uint8Array>[ 2, 4, 6 ]","Uint8Array.prototype.reduce":"\nUint8Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14","Uint8Array.prototype.reduceRight":"\nUint8Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14","Uint8Array.prototype.reverse":"\nUint8Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Uint8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] )\n    <Uint8Array>\n    > arr.reverse()\n    <Uint8Array>[ 3, 2, 1 ]","Uint8Array.prototype.set":"\nUint8Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4","Uint8Array.prototype.slice":"\nUint8Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3","Uint8Array.prototype.some":"\nUint8Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true","Uint8Array.prototype.sort":"\nUint8Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Uint8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Uint8Array>[ 0, 1, 1, 2, 2 ]","Uint8Array.prototype.subarray":"\nUint8Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint8Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Uint8Array>[ 3, 4, 5 ]","Uint8Array.prototype.toLocaleString":"\nUint8Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'","Uint8Array.prototype.toString":"\nUint8Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'","Uint8Array.prototype.values":"\nUint8Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8ClampedArray","Uint8ClampedArray":"\nUint8ClampedArray()\n    A typed array constructor which returns a typed array representing an array\n    of 8-bit unsigned integers in the platform byte order clamped to 0-255.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray()\n    <Uint8ClampedArray>\n\n\nUint8ClampedArray( length )\n    Returns a typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( 5 )\n    <Uint8ClampedArray>[ 0, 0, 0, 0, 0 ]\n\n\nUint8ClampedArray( typedarray )\n    Creates a typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n    > var arr2 = new Uint8ClampedArray( arr1 )\n    <Uint8ClampedArray>[ 5, 5, 5 ]\n\n\nUint8ClampedArray( obj )\n    Creates a typed array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a typed array.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 5.0, 5.0, 5.0 ];\n    > var arr2 = new Uint8ClampedArray( arr1 )\n    <Uint8ClampedArray>[ 5, 5, 5 ]\n\n\nUint8ClampedArray( buffer[, byteOffset[, length]] )\n    Returns a typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 4 );\n    > var arr = new Uint8ClampedArray( buf, 0, 4 )\n    <Uint8ClampedArray>[ 0, 0, 0, 0 ]\n\n\nUint8ClampedArray.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Uint8ClampedArray.from( [ 1, 2 ], mapFcn )\n    <Uint8ClampedArray>[ 2, 4 ]\n\n\nUint8ClampedArray.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Uint8ClampedArray.of( 1, 2 )\n    <Uint8ClampedArray>[ 1, 2 ]\n\n\nUint8ClampedArray.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Uint8ClampedArray.BYTES_PER_ELEMENT\n    1\n\n\nUint8ClampedArray.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Uint8ClampedArray.name\n    'Uint8ClampedArray'\n\n\nUint8ClampedArray.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( 5 );\n    > arr.buffer\n    <ArrayBuffer>\n\n\nUint8ClampedArray.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( 5 );\n    > arr.byteLength\n    5\n\n\nUint8ClampedArray.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( 5 );\n    > arr.byteOffset\n    0\n\n\nUint8ClampedArray.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( 5 );\n    > arr.BYTES_PER_ELEMENT\n    1\n\n\nUint8ClampedArray.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( 5 );\n    > arr.length\n    5\n\n\nUint8ClampedArray.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2\n\n\nUint8ClampedArray.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true\n\n\nUint8ClampedArray.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false\n\n\nUint8ClampedArray.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3\n\n\nUint8ClampedArray.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2\n\n\nUint8ClampedArray.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3\n\n\nUint8ClampedArray.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2\n\n\nUint8ClampedArray.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '\n\n\nUint8ClampedArray.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true\n\n\nUint8ClampedArray.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2\n\n\nUint8ClampedArray.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'\n\n\nUint8ClampedArray.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true\n\n\nUint8ClampedArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3\n\n\nUint8ClampedArray.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Uint8ClampedArray>[ 2, 4, 6 ]\n\n\nUint8ClampedArray.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14\n\n\nUint8ClampedArray.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14\n\n\nUint8ClampedArray.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] )\n    <Uint8ClampedArray>\n    > arr.reverse()\n    <Uint8ClampedArray>[ 3, 2, 1 ]\n\n\nUint8ClampedArray.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4\n\n\nUint8ClampedArray.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3\n\n\nUint8ClampedArray.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true\n\n\nUint8ClampedArray.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Uint8ClampedArray>[ 0, 1, 1, 2, 2 ]\n\n\nUint8ClampedArray.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Uint8ClampedArray>[ 3, 4, 5 ]\n\n\nUint8ClampedArray.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'\n\n\nUint8ClampedArray.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'\n\n\nUint8ClampedArray.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array\n","Uint8ClampedArray.from":"\nUint8ClampedArray.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Uint8ClampedArray.from( [ 1, 2 ], mapFcn )\n    <Uint8ClampedArray>[ 2, 4 ]","Uint8ClampedArray.of":"\nUint8ClampedArray.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Uint8ClampedArray.of( 1, 2 )\n    <Uint8ClampedArray>[ 1, 2 ]","Uint8ClampedArray.BYTES_PER_ELEMENT":"\nUint8ClampedArray.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Uint8ClampedArray.BYTES_PER_ELEMENT\n    1","Uint8ClampedArray.name":"\nUint8ClampedArray.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Uint8ClampedArray.name\n    'Uint8ClampedArray'","Uint8ClampedArray.prototype.buffer":"\nUint8ClampedArray.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( 5 );\n    > arr.buffer\n    <ArrayBuffer>","Uint8ClampedArray.prototype.byteLength":"\nUint8ClampedArray.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( 5 );\n    > arr.byteLength\n    5","Uint8ClampedArray.prototype.byteOffset":"\nUint8ClampedArray.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( 5 );\n    > arr.byteOffset\n    0","Uint8ClampedArray.prototype.BYTES_PER_ELEMENT":"\nUint8ClampedArray.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( 5 );\n    > arr.BYTES_PER_ELEMENT\n    1","Uint8ClampedArray.prototype.length":"\nUint8ClampedArray.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( 5 );\n    > arr.length\n    5","Uint8ClampedArray.prototype.copyWithin":"\nUint8ClampedArray.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2","Uint8ClampedArray.prototype.entries":"\nUint8ClampedArray.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true","Uint8ClampedArray.prototype.every":"\nUint8ClampedArray.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false","Uint8ClampedArray.prototype.fill":"\nUint8ClampedArray.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3","Uint8ClampedArray.prototype.filter":"\nUint8ClampedArray.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2","Uint8ClampedArray.prototype.find":"\nUint8ClampedArray.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3","Uint8ClampedArray.prototype.findIndex":"\nUint8ClampedArray.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2","Uint8ClampedArray.prototype.forEach":"\nUint8ClampedArray.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '","Uint8ClampedArray.prototype.includes":"\nUint8ClampedArray.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true","Uint8ClampedArray.prototype.indexOf":"\nUint8ClampedArray.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2","Uint8ClampedArray.prototype.join":"\nUint8ClampedArray.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'","Uint8ClampedArray.prototype.keys":"\nUint8ClampedArray.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true","Uint8ClampedArray.prototype.lastIndexOf":"\nUint8ClampedArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3","Uint8ClampedArray.prototype.map":"\nUint8ClampedArray.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Uint8ClampedArray>[ 2, 4, 6 ]","Uint8ClampedArray.prototype.reduce":"\nUint8ClampedArray.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14","Uint8ClampedArray.prototype.reduceRight":"\nUint8ClampedArray.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14","Uint8ClampedArray.prototype.reverse":"\nUint8ClampedArray.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] )\n    <Uint8ClampedArray>\n    > arr.reverse()\n    <Uint8ClampedArray>[ 3, 2, 1 ]","Uint8ClampedArray.prototype.set":"\nUint8ClampedArray.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4","Uint8ClampedArray.prototype.slice":"\nUint8ClampedArray.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3","Uint8ClampedArray.prototype.some":"\nUint8ClampedArray.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true","Uint8ClampedArray.prototype.sort":"\nUint8ClampedArray.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Uint8ClampedArray>[ 0, 1, 1, 2, 2 ]","Uint8ClampedArray.prototype.subarray":"\nUint8ClampedArray.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Uint8ClampedArray>[ 3, 4, 5 ]","Uint8ClampedArray.prototype.toLocaleString":"\nUint8ClampedArray.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'","Uint8ClampedArray.prototype.toString":"\nUint8ClampedArray.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'","Uint8ClampedArray.prototype.values":"\nUint8ClampedArray.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array","UINT16_MAX":"\nUINT16_MAX\n    Maximum unsigned 16-bit integer.\n\n    The maximum unsigned 16-bit integer is given by `2^16 - 1`.\n\n    Examples\n    --------\n    > UINT16_MAX\n    65535\n\n    See Also\n    --------\n    INT16_MAX\n","UINT16_NUM_BYTES":"\nUINT16_NUM_BYTES\n    Size (in bytes) of a 16-bit unsigned integer.\n\n    Examples\n    --------\n    > UINT16_NUM_BYTES\n    2\n\n    See Also\n    --------\n    INT16_NUM_BYTES, UINT32_NUM_BYTES, UINT8_NUM_BYTES\n","Uint16Array":"\nUint16Array()\n    A typed array constructor which returns a typed array representing an array\n    of 16-bit unsigned integers in the platform byte order.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array()\n    <Uint16Array>\n\n\nUint16Array( length )\n    Returns a typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( 5 )\n    <Uint16Array>[ 0, 0, 0, 0, 0 ]\n\n\nUint16Array( typedarray )\n    Creates a typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n    > var arr2 = new Uint16Array( arr1 )\n    <Uint16Array>[ 5, 5, 5 ]\n\n\nUint16Array( obj )\n    Creates a typed array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a typed array.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 5.0, 5.0, 5.0 ];\n    > var arr2 = new Uint16Array( arr1 )\n    <Uint16Array>[ 5, 5, 5 ]\n\n\nUint16Array( buffer[, byteOffset[, length]] )\n    Returns a typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 8 );\n    > var arr = new Uint16Array( buf, 0, 4 )\n    <Uint16Array>[ 0, 0, 0, 0 ]\n\n\nUint16Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Uint16Array.from( [ 1, 2 ], mapFcn )\n    <Uint16Array>[ 2, 4 ]\n\n\nUint16Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Uint16Array.of( 1, 2 )\n    <Uint16Array>[ 1, 2 ]\n\n\nUint16Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Uint16Array.BYTES_PER_ELEMENT\n    2\n\n\nUint16Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Uint16Array.name\n    'Uint16Array'\n\n\nUint16Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>\n\n\nUint16Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( 5 );\n    > arr.byteLength\n    10\n\n\nUint16Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( 5 );\n    > arr.byteOffset\n    0\n\n\nUint16Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    2\n\n\nUint16Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( 5 );\n    > arr.length\n    5\n\n\nUint16Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Uint16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2\n\n\nUint16Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true\n\n\nUint16Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false\n\n\nUint16Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Uint16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3\n\n\nUint16Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2\n\n\nUint16Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3\n\n\nUint16Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2\n\n\nUint16Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '\n\n\nUint16Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true\n\n\nUint16Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2\n\n\nUint16Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'\n\n\nUint16Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true\n\n\nUint16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3\n\n\nUint16Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Uint16Array>[ 2, 4, 6 ]\n\n\nUint16Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14\n\n\nUint16Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14\n\n\nUint16Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Uint16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] )\n    <Uint16Array>\n    > arr.reverse()\n    <Uint16Array>[ 3, 2, 1 ]\n\n\nUint16Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4\n\n\nUint16Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3\n\n\nUint16Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true\n\n\nUint16Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Uint16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Uint16Array>[ 0, 1, 1, 2, 2 ]\n\n\nUint16Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint16Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Uint16Array>[ 3, 4, 5 ]\n\n\nUint16Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'\n\n\nUint16Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'\n\n\nUint16Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Uint16Array.from":"\nUint16Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Uint16Array.from( [ 1, 2 ], mapFcn )\n    <Uint16Array>[ 2, 4 ]","Uint16Array.of":"\nUint16Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Uint16Array.of( 1, 2 )\n    <Uint16Array>[ 1, 2 ]","Uint16Array.BYTES_PER_ELEMENT":"\nUint16Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Uint16Array.BYTES_PER_ELEMENT\n    2","Uint16Array.name":"\nUint16Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Uint16Array.name\n    'Uint16Array'","Uint16Array.prototype.buffer":"\nUint16Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>","Uint16Array.prototype.byteLength":"\nUint16Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( 5 );\n    > arr.byteLength\n    10","Uint16Array.prototype.byteOffset":"\nUint16Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( 5 );\n    > arr.byteOffset\n    0","Uint16Array.prototype.BYTES_PER_ELEMENT":"\nUint16Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    2","Uint16Array.prototype.length":"\nUint16Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( 5 );\n    > arr.length\n    5","Uint16Array.prototype.copyWithin":"\nUint16Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Uint16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2","Uint16Array.prototype.entries":"\nUint16Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true","Uint16Array.prototype.every":"\nUint16Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false","Uint16Array.prototype.fill":"\nUint16Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Uint16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3","Uint16Array.prototype.filter":"\nUint16Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2","Uint16Array.prototype.find":"\nUint16Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3","Uint16Array.prototype.findIndex":"\nUint16Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2","Uint16Array.prototype.forEach":"\nUint16Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '","Uint16Array.prototype.includes":"\nUint16Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true","Uint16Array.prototype.indexOf":"\nUint16Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2","Uint16Array.prototype.join":"\nUint16Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'","Uint16Array.prototype.keys":"\nUint16Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true","Uint16Array.prototype.lastIndexOf":"\nUint16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3","Uint16Array.prototype.map":"\nUint16Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Uint16Array>[ 2, 4, 6 ]","Uint16Array.prototype.reduce":"\nUint16Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14","Uint16Array.prototype.reduceRight":"\nUint16Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14","Uint16Array.prototype.reverse":"\nUint16Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Uint16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] )\n    <Uint16Array>\n    > arr.reverse()\n    <Uint16Array>[ 3, 2, 1 ]","Uint16Array.prototype.set":"\nUint16Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4","Uint16Array.prototype.slice":"\nUint16Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3","Uint16Array.prototype.some":"\nUint16Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true","Uint16Array.prototype.sort":"\nUint16Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Uint16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Uint16Array>[ 0, 1, 1, 2, 2 ]","Uint16Array.prototype.subarray":"\nUint16Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint16Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Uint16Array>[ 3, 4, 5 ]","Uint16Array.prototype.toLocaleString":"\nUint16Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'","Uint16Array.prototype.toString":"\nUint16Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'","Uint16Array.prototype.values":"\nUint16Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint32Array, Uint8Array, Uint8ClampedArray","UINT32_MAX":"\nUINT32_MAX\n    Maximum unsigned 32-bit integer.\n\n    The maximum unsigned 32-bit integer is given by `2^32 - 1`.\n\n    Examples\n    --------\n    > UINT32_MAX\n    4294967295\n\n    See Also\n    --------\n    INT32_MAX\n","UINT32_NUM_BYTES":"\nUINT32_NUM_BYTES\n    Size (in bytes) of a 32-bit unsigned integer.\n\n    Examples\n    --------\n    > UINT32_NUM_BYTES\n    4\n\n    See Also\n    --------\n    INT32_NUM_BYTES, UINT16_NUM_BYTES, UINT8_NUM_BYTES\n","Uint32Array":"\nUint32Array()\n    A typed array constructor which returns a typed array representing an array\n    of 32-bit unsigned integers in the platform byte order.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array()\n    <Uint32Array>\n\n\nUint32Array( length )\n    Returns a typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( 5 )\n    <Uint32Array>[ 0, 0, 0, 0, 0 ]\n\n\nUint32Array( typedarray )\n    Creates a typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n    > var arr2 = new Uint32Array( arr1 )\n    <Uint32Array>[ 5, 5, 5 ]\n\n\nUint32Array( obj )\n    Creates a typed array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a typed array.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 5.0, 5.0, 5.0 ];\n    > var arr2 = new Uint32Array( arr1 )\n    <Uint32Array>[ 5, 5, 5 ]\n\n\nUint32Array( buffer[, byteOffset[, length]] )\n    Returns a typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 16 );\n    > var arr = new Uint32Array( buf, 0, 4 )\n    <Uint32Array>[ 0, 0, 0, 0 ]\n\n\nUint32Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Uint32Array.from( [ 1, 2 ], mapFcn )\n    <Uint32Array>[ 2, 4 ]\n\n\nUint32Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Uint32Array.of( 1, 2 )\n    <Uint32Array>[ 1, 2 ]\n\n\nUint32Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Uint32Array.BYTES_PER_ELEMENT\n    4\n\n\nUint32Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Uint32Array.name\n    'Uint32Array'\n\n\nUint32Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>\n\n\nUint32Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( 5 );\n    > arr.byteLength\n    20\n\n\nUint32Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( 5 );\n    > arr.byteOffset\n    0\n\n\nUint32Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    4\n\n\nUint32Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( 5 );\n    > arr.length\n    5\n\n\nUint32Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Uint32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2\n\n\nUint32Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true\n\n\nUint32Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false\n\n\nUint32Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Uint32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3\n\n\nUint32Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2\n\n\nUint32Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3\n\n\nUint32Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2\n\n\nUint32Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '\n\n\nUint32Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true\n\n\nUint32Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2\n\n\nUint32Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'\n\n\nUint32Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true\n\n\nUint32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3\n\n\nUint32Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Uint32Array>[ 2, 4, 6 ]\n\n\nUint32Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14\n\n\nUint32Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14\n\n\nUint32Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Uint32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] )\n    <Uint32Array>\n    > arr.reverse()\n    <Uint32Array>[ 3, 2, 1 ]\n\n\nUint32Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4\n\n\nUint32Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3\n\n\nUint32Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true\n\n\nUint32Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Uint32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Uint32Array>[ 0, 1, 1, 2, 2 ]\n\n\nUint32Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint32Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Uint32Array>[ 3, 4, 5 ]\n\n\nUint32Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'\n\n\nUint32Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'\n\n\nUint32Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint8Array, Uint8ClampedArray\n","Uint32Array.from":"\nUint32Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Uint32Array.from( [ 1, 2 ], mapFcn )\n    <Uint32Array>[ 2, 4 ]","Uint32Array.of":"\nUint32Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Uint32Array.of( 1, 2 )\n    <Uint32Array>[ 1, 2 ]","Uint32Array.BYTES_PER_ELEMENT":"\nUint32Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Uint32Array.BYTES_PER_ELEMENT\n    4","Uint32Array.name":"\nUint32Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Uint32Array.name\n    'Uint32Array'","Uint32Array.prototype.buffer":"\nUint32Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>","Uint32Array.prototype.byteLength":"\nUint32Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( 5 );\n    > arr.byteLength\n    20","Uint32Array.prototype.byteOffset":"\nUint32Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( 5 );\n    > arr.byteOffset\n    0","Uint32Array.prototype.BYTES_PER_ELEMENT":"\nUint32Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    4","Uint32Array.prototype.length":"\nUint32Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( 5 );\n    > arr.length\n    5","Uint32Array.prototype.copyWithin":"\nUint32Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Uint32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2","Uint32Array.prototype.entries":"\nUint32Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true","Uint32Array.prototype.every":"\nUint32Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false","Uint32Array.prototype.fill":"\nUint32Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Uint32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3","Uint32Array.prototype.filter":"\nUint32Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2","Uint32Array.prototype.find":"\nUint32Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3","Uint32Array.prototype.findIndex":"\nUint32Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2","Uint32Array.prototype.forEach":"\nUint32Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '","Uint32Array.prototype.includes":"\nUint32Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true","Uint32Array.prototype.indexOf":"\nUint32Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2","Uint32Array.prototype.join":"\nUint32Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'","Uint32Array.prototype.keys":"\nUint32Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true","Uint32Array.prototype.lastIndexOf":"\nUint32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3","Uint32Array.prototype.map":"\nUint32Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Uint32Array>[ 2, 4, 6 ]","Uint32Array.prototype.reduce":"\nUint32Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14","Uint32Array.prototype.reduceRight":"\nUint32Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14","Uint32Array.prototype.reverse":"\nUint32Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Uint32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] )\n    <Uint32Array>\n    > arr.reverse()\n    <Uint32Array>[ 3, 2, 1 ]","Uint32Array.prototype.set":"\nUint32Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4","Uint32Array.prototype.slice":"\nUint32Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3","Uint32Array.prototype.some":"\nUint32Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true","Uint32Array.prototype.sort":"\nUint32Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Uint32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Uint32Array>[ 0, 1, 1, 2, 2 ]","Uint32Array.prototype.subarray":"\nUint32Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint32Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Uint32Array>[ 3, 4, 5 ]","Uint32Array.prototype.toLocaleString":"\nUint32Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'","Uint32Array.prototype.toString":"\nUint32Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'","Uint32Array.prototype.values":"\nUint32Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint8Array, Uint8ClampedArray","umask":"\numask( [mask,] [options] )\n    Returns the current process mask, if not provided a mask; otherwise, sets\n    the process mask and returns the previous mask.\n\n    A mask is a set of bits, each of which restricts how its corresponding\n    permission is set for newly created files.\n\n    On POSIX platforms, each file has a set of attributes that control who can\n    read, write, or execute that file. Upon creating a file, file permissions\n    must be set to an initial setting. The process mask restricts those\n    permission settings.\n\n    If the mask contains a bit set to \"1\", the corresponding initial file\n    permission is disabled. If the mask contains a bit set to \"0\", the\n    corresponding permission is left to be determined by the requesting process\n    and the system.\n\n    The process mask is thus a filter that removes permissions as a file is\n    created; i.e., each bit set to a \"1\" removes its corresponding permission.\n\n    In octal representation, a mask is a four digit number, e.g., 0077,\n    comprised as follows:\n\n    - 0: special permissions (setuid, setgid, sticky bit)\n    - 0: (u)ser/owner permissions\n    - 7: (g)roup permissions\n    - 7: (o)thers/non-group permissions\n\n    Octal codes correspond to the following permissions:\n\n    - 0: read, write, execute\n    - 1: read, write\n    - 2: read, execute\n    - 3: read\n    - 4: write, execute\n    - 5: write\n    - 6: execute\n    - 7: no permissions\n\n    If provided fewer than four digits, the mask is left-padded with zeros.\n\n    Note, however, that only the last three digits (i.e., the file permissions\n    digits) of the mask are actually used when the mask is applied.\n\n    Permissions can be represented using the following symbolic form:\n\n        u=rwx,g=rwx,o=rwx\n\n    where\n\n    - u: user permissions\n    - g: group permissions\n    - o: other/non-group permissions\n    - r: read\n    - w: write\n    - x: execute\n\n    When setting permissions using symbolic notation, the function accepts a\n    mask expression of the form:\n\n        [<classes>]<operator><symbols>\n\n    where \"classes\" may be a combination of\n\n    - u: user\n    - g: group\n    - o: other/non-group\n    - a: all\n\n    \"symbols\" may be a combination of\n\n    - r: read\n    - w: write\n    - x: execute\n    - X: special execute\n    - s: setuid/gid on execution\n    - t: sticky\n\n    and \"operator\" may be one of\n\n    - +: enable\n    - -: disable\n    - =: enable specified and disable unspecified permissions\n\n    For example,\n\n    - u-w: disable user write permissions\n    - u+w: enable user write permissions\n    - u=w: enable user write permissions and disable user read and execute\n\n    To specify multiple changes, provide a comma-separated list of mask\n    expressions. For example,\n\n        u+rwx,g-x,o=r\n\n    would enable user read, write, and execute permissions, disable group\n    execute permissions, enable other read permissions, and disable other\n    write and execute permissions.\n\n    The `a` class indicates \"all\", which is the same as specifying \"ugo\". This\n    is the default class if a class is omitted when specifying permissions. For\n    example, `+x` is equivalent to `a+x` which is equivalent to `ugo+x` which\n    is equivalent to `u+x,g+x,o+x` and enables execution for all classes.\n\n    Parameters\n    ----------\n    mask: integer|string (optional)\n        Mask or mask expression. If the mask is a string, the mask is assumed to\n        be in symbolic notation.\n\n    options: Object (optional)\n        Options.\n\n    options.symbolic: boolean (optional)\n        Boolean indicating whether to return the mask using symbolic notation.\n\n    Returns\n    -------\n    mask: integer|string\n        Process mask. If provided a mask, the returned value is the previous\n        mask; otherwise, the returned value is the current process mask.\n\n    Examples\n    --------\n    > var mask = umask()\n    <number>\n    > mask = umask( { 'symbolic': true } )\n    <string>\n\n","uncapitalize":"\nuncapitalize( str )\n    Lowercases the first character of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Uncapitalized string.\n\n    Examples\n    --------\n    > var out = uncapitalize( 'Beep' )\n    'beep'\n    > out = uncapitalize( 'bOOp' )\n    'bOOp'\n\n    See Also\n    --------\n    capitalize, lowercase\n","uncapitalizeKeys":"\nuncapitalizeKeys( obj )\n    Converts the first letter of each object key to lowercase.\n\n    The function only transforms own properties. Hence, the function does not\n    transform inherited properties.\n\n    The function shallow copies key values.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > var obj = { 'AA': 1, 'BB': 2 };\n    > var out = uncapitalizeKeys( obj )\n    { 'aA': 1, 'bB': 2 }\n\n    See Also\n    --------\n    capitalizeKeys, lowercaseKeys\n","uncurry":"\nuncurry( fcn[, arity, ][thisArg] )\n    Transforms a curried function into a function invoked with multiple\n    arguments.\n\n    Parameters\n    ----------\n    fcn: Function\n        Curried function.\n\n    arity: integer (optional)\n        Number of parameters.\n\n    thisArg: any (optional)\n        Evaluation context.\n\n    Returns\n    -------\n    out: Function\n        Uncurried function.\n\n    Examples\n    --------\n    > function addX( x ) {\n    ...     return function addY( y ) {\n    ...         return x + y;\n    ...     };\n    ... };\n    > var fcn = uncurry( addX );\n    > var sum = fcn( 2, 3 )\n    5\n\n    // To enforce a fixed number of parameters, provide an `arity` argument:\n    > function add( x ) {\n    ...     return function add( y ) {\n    ...         return x + y;\n    ...     };\n    ... };\n    > fcn = uncurry( add, 2 );\n    > sum = fcn( 9 )\n    <Error>\n\n    // To specify an execution context, provide a `thisArg` argument:\n    > function addX( x ) {\n    ...     this.x = x;\n    ...     return addY;\n    ... };\n    > function addY( y ) {\n    ...     return this.x + y;\n    ... };\n    > fcn = uncurry( addX, {} );\n    > sum = fcn( 2, 3 )\n    5\n\n    See Also\n    --------\n    curry, uncurryRight\n","uncurryRight":"\nuncurryRight( fcn[, arity, ][thisArg] )\n    Transforms a curried function into a function invoked with multiple\n    arguments.\n\n    Provided arguments are applied starting from the right.\n\n    Parameters\n    ----------\n    fcn: Function\n        Curried function.\n\n    arity: integer (optional)\n        Number of parameters.\n\n    thisArg: any (optional)\n        Evaluation context.\n\n    Returns\n    -------\n    out: Function\n        Uncurried function.\n\n    Examples\n    --------\n    > function addX( x ) {\n    ...     return function addY( y ) {\n    ...         return x + y;\n    ...     };\n    ... };\n    > var fcn = uncurryRight( addX );\n    > var sum = fcn( 3, 2 )\n    5\n\n    // To enforce a fixed number of parameters, provide an `arity` argument:\n    > function add( y ) {\n    ...     return function add( x ) {\n    ...         return x + y;\n    ...     };\n    ... };\n    > fcn = uncurryRight( add, 2 );\n    > sum = fcn( 9 )\n    <Error>\n\n    // To specify an execution context, provide a `thisArg` argument:\n    > function addY( y ) {\n    ...     this.y = y;\n    ...     return addX;\n    ... };\n    > function addX( x ) {\n    ...     return x + this.y;\n    ... };\n    > fcn = uncurryRight( addY, {} );\n    > sum = fcn( 3, 2 )\n    5\n\n    See Also\n    --------\n    curry, curryRight, uncurry\n","UNICODE_MAX":"\nUNICODE_MAX\n    Maximum Unicode code point.\n\n    Examples\n    --------\n    > UNICODE_MAX\n    1114111\n\n    See Also\n    --------\n    UNICODE_MAX_BMP\n","UNICODE_MAX_BMP":"\nUNICODE_MAX_BMP\n    Maximum Unicode code point in the Basic Multilingual Plane (BMP).\n\n    Examples\n    --------\n    > UNICODE_MAX_BMP\n    65535\n\n    See Also\n    --------\n    UNICODE_MAX\n","UnicodeColumnChartSparkline":"\nUnicodeColumnChartSparkline( [data,] [options] )\n    Returns a sparkline column chart instance.\n\n    The `data` argument takes precedence over the `data` option.\n\n    Parameters\n    ----------\n    data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options: Object (optional)\n        Options.\n\n    options.autoRender: boolean (optional)\n        Boolean indicating whether to re-render on a 'change' event. Default:\n        false.\n\n    options.bufferSize: integer|null (optional)\n        Data buffer size. If provided, data is kept in a first-in first-out\n        (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n    options.data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options.description: string (optional)\n        Chart description.\n\n    options.infinities: boolean (optional)\n        Boolean indicating whether to encode infinite values. Default: false.\n\n    options.isDefined: Function (optional)\n        An accessor function indicating whether a datum is defined.\n\n    options.label: string (optional)\n        Data label.\n\n    options.yMax: number|null (optional)\n        Maximum value of the y-axis domain. If `null`, the value is computed\n        from the data. Default: null.\n\n    options.yMin: number|null (optional)\n        Minimum value of the y-axis domain. If `null`, the value is computed\n        from the data. Default: null.\n\n    Returns\n    -------\n    chart: ColumnChart\n        Column chart instance.\n\n    chart.autoRender\n        Rendering mode. If `true`, an instance renders on each 'change' event;\n        otherwise, rendering must be triggered manually.\n\n    chart.bufferSize\n        Data buffer size.\n\n    chart.description\n        Chart description.\n\n    chart.data\n        Chart data.\n\n    chart.label\n        Data label.\n\n    chart.infinities\n        Indicates whether to encode infinite values.\n\n    chart.isDefined( d, i )\n        An accessor function which defines whether a datum is defined. This\n        accessor is used to define how missing values are encoded. The default\n        behavior is to ignore values which are `NaN`.\n\n    chart.render()\n        Renders a column chart sparkline.\n\n    chart.yMax\n        Maximum value of the y-axis domain. If set to `null`, when accessed, the\n        returned value is computed from the data.\n\n    chart.yMin\n        Minimum value of the y-axis domain. If set to `null`, when accessed, the\n        returned value is computed from the data.\n\n    Examples\n    --------\n    > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n    > var chart = new UnicodeColumnChartSparkline( data );\n    > chart.render()\n    '▁█▅▃▆▆▅'\n\n    See Also\n    --------\n    plot, Plot, UnicodeSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeLineChartSparkline":"\nUnicodeLineChartSparkline( [data,] [options] )\n    Returns a sparkline line chart instance.\n\n    The `data` argument takes precedence over the `data` option.\n\n    Parameters\n    ----------\n    data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options: Object (optional)\n        Options.\n\n    options.autoRender: boolean (optional)\n        Boolean indicating whether to re-render on a 'change' event. Default:\n        false.\n\n    options.bufferSize: integer|null (optional)\n        Data buffer size. If provided, data is kept in a first-in first-out\n        (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n    options.data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options.description: string (optional)\n        Chart description.\n\n    options.infinities: boolean (optional)\n        Boolean indicating whether to encode infinite values. Default: false.\n\n    options.isDefined: Function (optional)\n        An accessor function indicating whether a datum is defined.\n\n    options.label: string (optional)\n        Data label.\n\n    options.yMax: number|null (optional)\n        Maximum value of the y-axis domain. If `null`, the value is computed\n        from the data. Default: null.\n\n    options.yMin: number|null (optional)\n        Minimum value of the y-axis domain. If `null`, the value is computed\n        from the data. Default: null.\n\n    Returns\n    -------\n    chart: LineChart\n        Line chart instance.\n\n    chart.autoRender\n        Rendering mode. If `true`, an instance renders on each 'change' event;\n        otherwise, rendering must be triggered manually.\n\n    chart.bufferSize\n        Data buffer size.\n\n    chart.description\n        Chart description.\n\n    chart.data\n        Chart data.\n\n    chart.label\n        Data label.\n\n    chart.infinities\n        Indicates whether to encode infinite values.\n\n    chart.isDefined( d, i )\n        An accessor function which defines whether a datum is defined. This\n        accessor is used to define how missing values are encoded. The default\n        behavior is to ignore values which are `NaN`.\n\n    chart.render()\n        Renders a line chart sparkline.\n\n    chart.yMax\n        Maximum value of the y-axis domain. If set to `null`, when accessed, the\n        returned value is computed from the data.\n\n    chart.yMin\n        Minimum value of the y-axis domain. If set to `null`, when accessed, the\n        returned value is computed from the data.\n\n    Examples\n    --------\n    > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n    > var chart = new UnicodeLineChartSparkline( data );\n    > chart.render()\n    '⡈⠑⠢⠔⠒⠒⠒'\n\n    See Also\n    --------\n    plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeSparkline":"\nUnicodeSparkline( [data,] [options] )\n    Returns a Unicode sparkline instance.\n\n    The following chart types are supported:\n\n    - column: column chart (e.g., ▃▆▂▄▁▅▅).\n    - line: line chart (e.g., ⡈⠑⠢⠔⠒⠒⠒).\n    - tristate: tristate chart (e.g., ▄▀──▀▄▄▀).\n    - up-down: up/down chart (e.g., ↓↑↑↑↑↓↓↑).\n    - win-loss: win/loss chart (e.g., ┌╵└┴╵╷╷╵).\n\n    The `data` argument takes precedence over the `data` option.\n\n    Parameters\n    ----------\n    data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options: Object (optional)\n        Options.\n\n    options.autoRender: boolean (optional)\n        Boolean indicating whether to re-render on a 'change' event. Default:\n        false.\n\n    options.bufferSize: integer|null (optional)\n        Data buffer size. If provided, data is kept in a first-in first-out\n        (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n    options.data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options.description: string (optional)\n        Chart description.\n\n    options.infinities: boolean (optional)\n        Boolean indicating whether to encode infinite values. Default: false.\n\n    options.isDefined: Function (optional)\n        An accessor function indicating whether a datum is defined.\n\n    options.label: string (optional)\n        Data label.\n\n    options.type: string (optional)\n        Chart type. Default: 'column'.\n\n    options.yMax: number|null (optional)\n        Maximum value of the y-axis domain. If `null`, the value is computed\n        from the data. Default: null.\n\n    options.yMin: number|null (optional)\n        Minimum value of the y-axis domain. If `null`, the value is computed\n        from the data. Default: null.\n\n    Returns\n    -------\n    chart: ColumnChart\n        Column chart instance.\n\n    chart.autoRender\n        Rendering mode. If `true`, an instance renders on each 'change' event;\n        otherwise, rendering must be triggered manually.\n\n    chart.bufferSize\n        Data buffer size.\n\n    chart.description\n        Chart description.\n\n    chart.data\n        Chart data.\n\n    chart.label\n        Data label.\n\n    chart.infinities\n        Indicates whether to encode infinite values.\n\n    chart.isDefined( d, i )\n        An accessor function which defines whether a datum is defined. This\n        accessor is used to define how missing values are encoded. The default\n        behavior is to ignore values which are `NaN`.\n\n    chart.render()\n        Renders a column chart sparkline.\n\n    chart.type\n        Chart type.\n\n    chart.yMax\n        Maximum value of the y-axis domain. If set to `null`, when accessed, the\n        returned value is computed from the data.\n\n    chart.yMin\n        Minimum value of the y-axis domain. If set to `null`, when accessed, the\n        returned value is computed from the data.\n\n    Examples\n    --------\n    > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n    > var chart = new UnicodeSparkline( data );\n    > chart.render()\n    '▁█▅▃▆▆▅'\n    > chart.type = 'line';\n    > chart.render()\n    '⡈⠑⠢⠔⠒⠒⠒'\n\n    See Also\n    --------\n    plot, Plot, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeTristateChartSparkline":"\nUnicodeTristateChartSparkline( [data,] [options] )\n    Returns a sparkline tristate chart instance.\n\n    In a tristate chart, negative values are encoded as lower blocks, positive\n    values are encoded as upper blocks, and values equal to zero are encoded as\n    middle lines.\n\n    The `data` argument takes precedence over the `data` option.\n\n    Parameters\n    ----------\n    data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options: Object (optional)\n        Options.\n\n    options.autoRender: boolean (optional)\n        Boolean indicating whether to re-render on a 'change' event. Default:\n        false.\n\n    options.bufferSize: integer|null (optional)\n        Data buffer size. If provided, data is kept in a first-in first-out\n        (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n    options.data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options.description: string (optional)\n        Chart description.\n\n    options.isDefined: Function (optional)\n        An accessor function indicating whether a datum is defined.\n\n    options.label: string (optional)\n        Data label.\n\n    Returns\n    -------\n    chart: TristateChart\n        Tristate chart instance.\n\n    chart.autoRender\n        Rendering mode. If `true`, an instance renders on each 'change' event;\n        otherwise, rendering must be triggered manually.\n\n    chart.bufferSize\n        Data buffer size.\n\n    chart.description\n        Chart description.\n\n    chart.data\n        Chart data.\n\n    chart.label\n        Data label.\n\n    chart.isDefined( d, i )\n        An accessor function which defines whether a datum is defined. This\n        accessor is used to define how missing values are encoded. The default\n        behavior is to ignore values which are `NaN`.\n\n    chart.render()\n        Renders a tristate chart sparkline.\n\n    Examples\n    --------\n    > var data = [ -1, 1, 0, 0, 1, -1, -1, 1 ];\n    > var chart = new UnicodeTristateChartSparkline( data );\n    > chart.render()\n    '▄▀──▀▄▄▀'\n\n    See Also\n    --------\n    plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeUpDownChartSparkline":"\nUnicodeUpDownChartSparkline( [data,] [options] )\n    Returns a sparkline up/down chart instance.\n\n    Glyphs:\n\n    | Value | Glyph |\n    |:-----:|:-----:|\n    |   1   |   ↑   |\n    |   -1  |   ↓   |\n\n    If provided any other value other than 1 or -1, the value is encoded as a\n    missing value.\n\n    The `data` argument takes precedence over the `data` option.\n\n    Parameters\n    ----------\n    data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options: Object (optional)\n        Options.\n\n    options.autoRender: boolean (optional)\n        Boolean indicating whether to re-render on a 'change' event. Default:\n        false.\n\n    options.bufferSize: integer|null (optional)\n        Data buffer size. If provided, data is kept in a first-in first-out\n        (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n    options.data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options.description: string (optional)\n        Chart description.\n\n    options.isDefined: Function (optional)\n        An accessor function indicating whether a datum is defined.\n\n    options.label: string (optional)\n        Data label.\n\n    Returns\n    -------\n    chart: UpDownChart\n        Chart instance.\n\n    chart.autoRender\n        Rendering mode. If `true`, an instance renders on each 'change' event;\n        otherwise, rendering must be triggered manually.\n\n    chart.bufferSize\n        Data buffer size.\n\n    chart.description\n        Chart description.\n\n    chart.data\n        Chart data.\n\n    chart.label\n        Data label.\n\n    chart.isDefined( d, i )\n        An accessor function which defines whether a datum is defined. This\n        accessor is used to define how missing values are encoded. The default\n        behavior is to ignore any values which are not 1 or -1.\n\n    chart.render()\n        Renders an up/down chart sparkline.\n\n    Examples\n    --------\n    > var data = [ -1, 1, 1, 1, 1, -1, -1, 1 ];\n    > var chart = new UnicodeUpDownChartSparkline( data );\n    > chart.render()\n    '↓↑↑↑↑↓↓↑'\n\n    See Also\n    --------\n    plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeWinLossChartSparkline":"\nUnicodeWinLossChartSparkline( [data,] [options] )\n    Returns a sparkline win/loss chart instance.\n\n    Glyphs:\n\n    | Value | Glyph |\n    |:-----:|:-----:|\n    |   1   |   ╵   |\n    |   -1  |   ╷   |\n    |   2   |   └   |\n    |   -2  |   ┌   |\n\n    If a `2` or `-2` is preceded by a `2` or `-2`,\n\n    | Value | Glyph |\n    |:-----:|:-----:|\n    |   2   |   ┴   |\n    |   -2  |   ┬   |\n\n    Based on the win/loss analogy,\n\n    - 1: win away\n    - 2: win at home\n    - -1: loss away\n    - -2: loss at home\n\n    If provided any value other than 1, -1, 2, or -2, the value is encoded as a\n    missing value.\n\n    The `data` argument takes precedence over the `data` option.\n\n    Parameters\n    ----------\n    data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options: Object (optional)\n        Options.\n\n    options.autoRender: boolean (optional)\n        Boolean indicating whether to re-render on a 'change' event. Default:\n        false.\n\n    options.bufferSize: integer|null (optional)\n        Data buffer size. If provided, data is kept in a first-in first-out\n        (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n    options.data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options.description: string (optional)\n        Chart description.\n\n    options.isDefined: Function (optional)\n        An accessor function indicating whether a datum is defined.\n\n    options.label: string (optional)\n        Data label.\n\n    Returns\n    -------\n    chart: WinLossChart\n        Chart instance.\n\n    chart.autoRender\n        Rendering mode. If `true`, an instance renders on each 'change' event;\n        otherwise, rendering must be triggered manually.\n\n    chart.bufferSize\n        Data buffer size.\n\n    chart.description\n        Chart description.\n\n    chart.data\n        Chart data.\n\n    chart.label\n        Data label.\n\n    chart.isDefined( d, i )\n        An accessor function which defines whether a datum is defined. This\n        accessor is used to define how missing values are encoded. The default\n        behavior is to ignore any values which are not 1, -1, 2, or -2.\n\n    chart.render()\n        Renders a win/loss chart sparkline.\n\n    Examples\n    --------\n    > var data = [ -2, 1, 2, 2, 1, -1, -1, 1 ];\n    > var chart = new UnicodeWinLossChartSparkline( data );\n    > chart.render()\n    '┌╵└┴╵╷╷╵'\n\n    See Also\n    --------\n    plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline\n","unlink":"\nunlink( path, clbk )\n    Asynchronously removes a directory entry.\n\n    If a provided path is a symbolic link, the function removes the symbolic\n    link named by the path and does not affect any file or directory named by\n    the contents of the symbolic link.\n\n    Otherwise, the function removes the link named by the provided path and\n    decrements the link count of the file referenced by the link.\n\n    When a file's link count becomes 0 and no process has the file open, the\n    space occupied by the file is freed and the file is no longer accessible.\n\n    If one or more processes have the file open when the last link is removed,\n    the link is removed before the function returns; however, the removal of\n    file contents is postponed until all references to the file are closed.\n\n    If the path refers to a socket, FIFO, or device, processes which have the\n    object open may continue to use it.\n\n    The path argument should *not* be a directory. To remove a directory, use\n    rmdir().\n\n    Parameters\n    ----------\n    path: string|Buffer|integer\n        Entry path.\n\n    clbk: Function\n        Callback to invoke upon removing an entry.\n\n    Examples\n    --------\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     }\n    ... };\n    > unlink( './beep/boop.txt', done );\n\n\nunlink.sync( path )\n    Synchronously removes a directory entry.\n\n   Parameters\n    ----------\n    path: string|Buffer|integer\n        Entry path.\n\n    Returns\n    -------\n    out: Error|null\n        Error object or null.\n\n    Examples\n    --------\n    > var out = unlink.sync( './beep/boop.txt' );\n\n    See Also\n    --------\n    exists\n","unlink.sync":"\nunlink.sync( path )\n    Synchronously removes a directory entry.\n\n   Parameters\n    ----------\n    path: string|Buffer|integer\n        Entry path.\n\n    Returns\n    -------\n    out: Error|null\n        Error object or null.\n\n    Examples\n    --------\n    > var out = unlink.sync( './beep/boop.txt' );\n\n    See Also\n    --------\n    exists","unshift":"\nunshift( collection, ...items )\n    Adds one or more elements to the beginning of a collection.\n\n    If the input collection is a typed array, the output value does not equal\n    the input reference and the underlying `ArrayBuffer` may *not* be the same\n    as the `ArrayBuffer` belonging to the input view.\n\n    For purposes of generality, always treat the output collection as distinct\n    from the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        A collection. If the collection is an `Object`, the collection should be\n        array-like.\n\n    items: ...any\n        Items to add.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Updated collection.\n\n    Examples\n    --------\n    // Arrays:\n    > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > arr = unshift( arr, 6.0, 7.0 )\n    [ 6.0, 7.0, 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Typed arrays:\n    > arr = new Float64Array( [ 1.0, 2.0 ] );\n    > arr = unshift( arr, 3.0, 4.0 )\n    <Float64Array>[ 3.0, 4.0, 1.0, 2.0 ]\n\n    // Array-like object:\n    > arr = { 'length': 1, '0': 1.0 };\n    > arr = unshift( arr, 2.0, 3.0 )\n    { 'length': 3, '0': 2.0, '1': 3.0, '2': 1.0 }\n\n    See Also\n    --------\n    pop, push, shift\n","until":"\nuntil( predicate, fcn[, thisArg] )\n    Invokes a function until a test condition is true.\n\n    When invoked, both the predicate function and the function to invoke are\n    provided a single argument:\n\n    - i: iteration number (starting from zero).\n\n    Parameters\n    ----------\n    predicate: Function\n        The predicate function which indicates whether to stop invoking a\n        function.\n\n    fcn: Function\n        The function to invoke.\n\n    thisArg: any (optional)\n        Execution context for the invoked function.\n\n    Examples\n    --------\n    > function predicate( i ) { return ( i >= 5 ); };\n    > function beep( i ) { console.log( 'boop: %d', i ); };\n    > until( predicate, beep )\n    boop: 0\n    boop: 1\n    boop: 2\n    boop: 3\n    boop: 4\n\n    See Also\n    --------\n    doUntil, doWhile, untilAsync, untilEach, whilst\n","untilAsync":"\nuntilAsync( predicate, fcn, done[, thisArg] )\n    Invokes a function until a test condition is true.\n\n    The predicate function is provided two arguments:\n\n    - i: iteration number (starting from zero).\n    - clbk: a callback indicating whether to invoke `fcn`.\n\n    The `clbk` function accepts two arguments:\n\n    - error: error argument.\n    - bool: test result.\n\n    If the test result is falsy, the function invokes `fcn`; otherwise, the\n    function invokes the `done` callback.\n\n    The function to invoke is provided two arguments:\n\n    - i: iteration number (starting from zero).\n    - next: a callback which must be invoked before proceeding to the next\n      iteration.\n\n    The first argument of the `next` callback is an `error` argument. If `fcn`\n    calls the `next` callback with a truthy `error` argument, the function\n    suspends execution and immediately calls the `done` callback for subsequent\n    `error` handling.\n\n    The `done` callback is invoked with an `error` argument and any arguments\n    passed to the final `next` callback.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Parameters\n    ----------\n    predicate: Function\n        The predicate function which indicates whether to continue invoking a\n        function.\n\n    fcn: Function\n        The function to invoke.\n\n    done: Function\n        Callback to invoke upon completion.\n\n    thisArg: any (optional)\n        Execution context for the invoked function.\n\n    Examples\n    --------\n    > function predicate( i, clbk ) { clbk( null, i >= 5 ); };\n    > function fcn( i, next ) {\n    ...     setTimeout( onTimeout, i );\n    ...     function onTimeout() {\n    ...         next( null, 'boop'+i );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > untilAsync( predicate, fcn, done )\n    boop: 4\n\n    See Also\n    --------\n    doUntilAsync, doWhileAsync, until, whileAsync\n","untilEach":"\nuntilEach( collection, predicate, fcn[, thisArg] )\n    Until a test condition is true, invokes a function for each element in a\n    collection.\n\n    When invoked, both the predicate function and the function to apply are\n    provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    predicate: Function\n        The predicate function which indicates whether to stop iterating over a\n        collection.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    thisArg: any (optional)\n        Execution context for the applied function.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function predicate( v ) { return v !== v; };\n    > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n    > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n    > untilEach( arr, predicate, logger )\n    0: 1\n    1: 2\n    2: 3\n    3: 4\n\n    See Also\n    --------\n    untilEachRight, whileEach\n","untilEachRight":"\nuntilEachRight( collection, predicate, fcn[, thisArg] )\n    Until a test condition is true, invokes a function for each element in a\n    collection, iterating from right to left.\n\n    When invoked, both the predicate function and the function to apply are\n    provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    predicate: Function\n        The predicate function which indicates whether to stop iterating over a\n        collection.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    thisArg: any (optional)\n        Execution context for the applied function.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function predicate( v ) { return v !== v; };\n    > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n    > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n    > untilEachRight( arr, predicate, logger )\n    5: 5\n    4: 4\n    3: 3\n    2: 2\n\n    See Also\n    --------\n    untilEach, whileEachRight\n","unzip":"\nunzip( arr[, idx] )\n    Unzips a zipped array (i.e., a nested array of tuples).\n\n    Parameters\n    ----------\n    arr: Array\n        Zipped array.\n\n    idx: Array<number> (optional)\n        Array of indices specifying which tuple elements to unzip.\n\n    Returns\n    -------\n    out: Array\n        Array of unzipped arrays.\n\n    Examples\n    --------\n    // Basic usage:\n    > var arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\n    > var out = unzip( arr )\n    [ [ 1, 2 ], [ 'a', 'b' ], [ 3, 4 ] ]\n\n    // Provide indices:\n    > arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\n    > out = unzip( arr, [ 0, 2 ] )\n    [ [ 1, 2 ], [ 3, 4 ] ]\n\n    See Also\n    --------\n    zip\n","uppercase":"\nuppercase( str )\n    Converts a string to uppercase.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Uppercase string.\n\n    Examples\n    --------\n    > var out = uppercase( 'bEEp' )\n    'BEEP'\n\n    See Also\n    --------\n    capitalize, lowercase\n","uppercaseKeys":"\nuppercaseKeys( obj )\n    Converts each object key to uppercase.\n\n    The function only transforms own properties. Hence, the function does not\n    transform inherited properties.\n\n    The function shallow copies key values.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > var obj = { 'a': 1, 'b': 2 };\n    > var out = uppercaseKeys( obj )\n    { 'A': 1, 'B': 2 }\n\n    See Also\n    --------\n    capitalizeKeys, lowercaseKeys\n","US_STATES_ABBR":"\nUS_STATES_ABBR()\n    Returns a list of US state two-letter abbreviations in alphabetical order\n    according to state name.\n\n    Returns\n    -------\n    out: Array<string>\n        List of US state two-letter abbreviations.\n\n    Examples\n    --------\n    > var list = US_STATES_ABBR()\n    [ 'AL', 'AK', 'AZ', 'AR', ... ]\n\n    See Also\n    --------\n    US_STATES_CAPITALS, US_STATES_NAMES\n","US_STATES_CAPITALS":"\nUS_STATES_CAPITALS()\n    Returns a list of US state capitals in alphabetical order according to state\n    name.\n\n    Returns\n    -------\n    out: Array<string>\n        List of US state capitals.\n\n    Examples\n    --------\n    > var list = US_STATES_CAPITALS()\n    [ 'Montgomery', 'Juneau', 'Phoenix', ... ]\n\n    See Also\n    --------\n    US_STATES_ABBR, US_STATES_CAPITALS_NAMES, US_STATES_NAMES, US_STATES_NAMES_CAPITALS\n","US_STATES_CAPITALS_NAMES":"\nUS_STATES_CAPITALS_NAMES()\n    Returns an object mapping US state capitals to state names.\n\n    Returns\n    -------\n    out: Object\n        An object mapping US state capitals to state names.\n\n    Examples\n    --------\n    > var out = US_STATES_CAPITALS_NAMES()\n    { 'Montgomery': 'Alabama', 'Juneau': 'Alaska', ... }\n\n    See Also\n    --------\n    US_STATES_CAPITALS, US_STATES_NAMES, US_STATES_NAMES_CAPITALS\n","US_STATES_NAMES":"\nUS_STATES_NAMES()\n    Returns a list of US state names in alphabetical order.\n\n    Returns\n    -------\n    out: Array<string>\n        List of US state names.\n\n    Examples\n    --------\n    > var list = US_STATES_NAMES()\n    [ 'Alabama', 'Alaska', 'Arizona', ... ]\n\n    See Also\n    --------\n    US_STATES_ABBR, US_STATES_CAPITALS, US_STATES_CAPITALS_NAMES, US_STATES_NAMES_CAPITALS\n","US_STATES_NAMES_CAPITALS":"\nUS_STATES_NAMES_CAPITALS()\n    Returns an object mapping US state names to state capitals.\n\n    Returns\n    -------\n    out: Object\n        An object mapping US state names to state capitals.\n\n    Examples\n    --------\n    > var out = US_STATES_NAMES_CAPITALS()\n    { 'Alabama': 'Montgomery', 'Alaska': 'Juneau', ... }\n\n    See Also\n    --------\n    US_STATES_CAPITALS, US_STATES_NAMES, US_STATES_NAMES_CAPITALS\n","utf16ToUTF8Array":"\nutf16ToUTF8Array( str )\n    Converts a UTF-16 encoded string to an array of integers using UTF-8\n    encoding.\n\n    The following byte sequences are used to represent a character. The sequence\n    depends on the code point:\n\n        0x00000000 - 0x0000007F:\n            0xxxxxxx\n\n        0x00000080 - 0x000007FF:\n            110xxxxx 10xxxxxx\n\n        0x00000800 - 0x0000FFFF:\n            1110xxxx 10xxxxxx 10xxxxxx\n\n        0x00010000 - 0x001FFFFF:\n            11110xxx 10xxxxxx 10xxxxxx 10xxxxxx\n\n    The `x` bit positions correspond to code point bits.\n\n    Only the shortest possible multi-byte sequence which can represent a code\n    point is used.\n\n    Parameters\n    ----------\n    str: string\n        UTF-16 encoded string.\n\n    Returns\n    -------\n    out: Array\n        Array of integers.\n\n    Examples\n    --------\n    > var str = '☃';\n    > var out = utf16ToUTF8Array( str )\n    [ 226, 152, 131 ]\n\n","vartest":"\nvartest( x, y[, options] )\n    Computes a two-sample F-test for equal variances.\n\n    The returned object comes with a `.print()` method which when invoked will\n    print a formatted output of the results of the hypothesis test.\n\n    Parameters\n    ----------\n    x: Array<number>\n        First data array.\n\n    y: Array<number>\n        Second data array.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.alternative: string (optional)\n        Either `two-sided`, `less` or `greater`.\n\n    options.ratio: number (optional)\n        Positive number denoting the ratio of the two population variances under\n        the null hypothesis. Default: `1`.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Used significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.ci: Array<number>\n        1-alpha confidence interval for the ratio of variances.\n\n    out.nullValue: number\n        Assumed ratio of variances under H0.\n\n    out.xvar: number\n        Sample variance of `x`.\n\n    out.yvar: number\n        Sample variance of `y`.\n\n    out.alternative: string\n        Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n    out.dfX: number\n        Numerator degrees of freedom.\n\n    out.dfY: number\n        Denominator degrees of freedom.\n\n    out.method: string\n        Name of test.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    > var x = [ 610, 610, 550, 590, 565, 570 ];\n    > var y = [ 560, 550, 580, 550, 560, 590, 550, 590 ];\n    > var out = vartest( x, y )\n    {\n        rejected: false,\n        pValue: ~0.399,\n        statistic: ~1.976,\n        ci: [ ~0.374, ~13.542 ],\n        // ...\n    }\n\n    // Print table output:\n    > var table = out.print()\n    F test for comparing two variances\n\n    Alternative hypothesis: True ratio in variances is not equal to 1\n\n        pValue: 0.3992\n        statistic: 1.976\n        variance of x: 617.5 (df of x: 5)\n        variance of y: 312.5 (df of y: 7)\n        95% confidence interval: [0.3739,13.5417]\n\n    Test Decision: Fail to reject null in favor of alternative at 5%\n    significance level\n\n    See Also\n    --------\n    bartlettTest\n","waterfall":"\nwaterfall( fcns, clbk[, thisArg] )\n    Executes functions in series, passing the results of one function as\n    arguments to the next function.\n\n    The last argument applied to each waterfall function is a callback. The\n    callback should be invoked upon a series function completion. The first\n    argument is reserved as an error argument (which can be `null`). Any results\n    which should be passed to the next function in the series should be provided\n    beginning with the second argument.\n\n    If any function calls the provided callback with a truthy `error` argument,\n    the waterfall suspends execution and immediately calls the completion\n    callback for subsequent error handling.\n\n    Execution is *not* guaranteed to be asynchronous. To ensure asynchrony, wrap\n    the completion callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Parameters\n    ----------\n    fcns: Array<Function>\n        Array of functions.\n\n    clbk: Function\n        Callback to invoke upon completion.\n\n    thisArg: any (optional)\n        Function context.\n\n    Examples\n    --------\n    > function foo( next ) { next( null, 'beep' ); };\n    > function bar( str, next ) { console.log( str ); next(); };\n    > function done( error ) { if ( error ) { throw error; } };\n    > var fcns = [ foo, bar ];\n    > waterfall( fcns, done );\n\n\nwaterfall.factory( fcns, clbk[, thisArg] )\n    Returns a reusable waterfall function.\n\n    Parameters\n    ----------\n    fcns: Array<Function>\n        Array of functions.\n\n    clbk: Function\n        Callback to invoke upon completion.\n\n    thisArg: any (optional)\n        Function context.\n\n    Returns\n    -------\n    fcn: Function\n        Waterfall function.\n\n    Examples\n    --------\n    > function foo( next ) { next( null, 'beep' ); };\n    > function bar( str, next ) { console.log( str ); next(); };\n    > function done( error ) { if ( error ) { throw error; } };\n    > var fcns = [ foo, bar ];\n    > var waterfall = waterfall.factory( fcns, done );\n    > waterfall();\n    > waterfall();\n    > waterfall();\n\n","waterfall.factory":"\nwaterfall.factory( fcns, clbk[, thisArg] )\n    Returns a reusable waterfall function.\n\n    Parameters\n    ----------\n    fcns: Array<Function>\n        Array of functions.\n\n    clbk: Function\n        Callback to invoke upon completion.\n\n    thisArg: any (optional)\n        Function context.\n\n    Returns\n    -------\n    fcn: Function\n        Waterfall function.\n\n    Examples\n    --------\n    > function foo( next ) { next( null, 'beep' ); };\n    > function bar( str, next ) { console.log( str ); next(); };\n    > function done( error ) { if ( error ) { throw error; } };\n    > var fcns = [ foo, bar ];\n    > var waterfall = waterfall.factory( fcns, done );\n    > waterfall();\n    > waterfall();\n    > waterfall();","WebAssemblyMemory":"\nWebAssemblyMemory( descriptor )\n    WebAssembly memory constructor.\n\n    Parameters\n    ----------\n    descriptor: Object\n        Memory descriptor object.\n\n    descriptor.initial: integer\n        Initial memory size in units of WebAssembly pages (i.e., 64KiB).\n\n    descriptor.maximum: integer (optional)\n        Maximum memory size in units of WebAssembly pages (i.e., 64KiB).\n\n    descriptor.shared: boolean (optional)\n        Boolean indicating whether the memory is shared. Default: false.\n\n    Returns\n    -------\n    out: Memory\n        WebAssembly memory instance.\n\n    Examples\n    --------\n    > var mem = new WebAssemblyMemory( { 'initial': 0 } )\n    <Memory>\n\n\nWebAssemblyMemory.prototype.buffer\n    Read-only property which returns the ArrayBuffer (or SharedArrayBuffer)\n    referenced by the memory instance.\n\n    Examples\n    --------\n    > var mem = new WebAssemblyMemory( { 'initial': 0 } );\n    > mem.buffer\n    <ArrayBuffer>\n\n\nWebAssemblyMemory.prototype.grow( delta )\n    Increases the size of the memory instance by a specified number of\n    WebAssembly pages (i.e., 64KiB).\n\n    Upon increasing the size, the previous ArrayBuffer is detached, thus\n    invalidating any typed arrays which were views over the previous\n    ArrayBuffer.\n\n    Detachment means that the previous ArrayBuffer byte length becomes zero, and\n    it no longer has bytes accessible to JavaScript.\n\n    ArrayBuffer detachment applies even when `delta` is zero.\n\n    Detachment only applies for non-shared memory instances. For a shared memory\n    instance, the initial buffer (which is a SharedArrayBuffer) will not become\n    detached and, instead, its length will not be updated.\n\n    Accesses to the `buffer` property after growing a SharedArrayBuffer will\n    yield a larger SharedArrayBuffer which may access a larger span of memory\n    than the buffer before growing memory.\n\n    Every SharedArrayBuffer accessed via the `buffer` property will always refer\n    to the start of the same memory address range and thus manipulate the same\n    data.\n\n    Parameters\n    ----------\n    delta: integer\n        Number of WebAssembly pages (i.e., 64KiB) by which to grow the\n        underlying memory.\n\n    Returns\n    -------\n    out: integer\n        Size of the previous memory (in units of pages).\n\n    Examples\n    --------\n    > var mem = new WebAssemblyMemory( { 'initial': 0 } );\n    > mem.grow( 1 )\n    <number>\n\n","WebAssemblyMemory.prototype.buffer":"\nWebAssemblyMemory.prototype.buffer\n    Read-only property which returns the ArrayBuffer (or SharedArrayBuffer)\n    referenced by the memory instance.\n\n    Examples\n    --------\n    > var mem = new WebAssemblyMemory( { 'initial': 0 } );\n    > mem.buffer\n    <ArrayBuffer>","WebAssemblyMemory.prototype.grow":"\nWebAssemblyMemory.prototype.grow( delta )\n    Increases the size of the memory instance by a specified number of\n    WebAssembly pages (i.e., 64KiB).\n\n    Upon increasing the size, the previous ArrayBuffer is detached, thus\n    invalidating any typed arrays which were views over the previous\n    ArrayBuffer.\n\n    Detachment means that the previous ArrayBuffer byte length becomes zero, and\n    it no longer has bytes accessible to JavaScript.\n\n    ArrayBuffer detachment applies even when `delta` is zero.\n\n    Detachment only applies for non-shared memory instances. For a shared memory\n    instance, the initial buffer (which is a SharedArrayBuffer) will not become\n    detached and, instead, its length will not be updated.\n\n    Accesses to the `buffer` property after growing a SharedArrayBuffer will\n    yield a larger SharedArrayBuffer which may access a larger span of memory\n    than the buffer before growing memory.\n\n    Every SharedArrayBuffer accessed via the `buffer` property will always refer\n    to the start of the same memory address range and thus manipulate the same\n    data.\n\n    Parameters\n    ----------\n    delta: integer\n        Number of WebAssembly pages (i.e., 64KiB) by which to grow the\n        underlying memory.\n\n    Returns\n    -------\n    out: integer\n        Size of the previous memory (in units of pages).\n\n    Examples\n    --------\n    > var mem = new WebAssemblyMemory( { 'initial': 0 } );\n    > mem.grow( 1 )\n    <number>","whileAsync":"\nwhileAsync( predicate, fcn, done[, thisArg] )\n    Invokes a function while a test condition is true.\n\n    The predicate function is provided two arguments:\n\n    - i: iteration number (starting from zero).\n    - clbk: a callback indicating whether to invoke `fcn`.\n\n    The `clbk` function accepts two arguments:\n\n    - error: error argument.\n    - bool: test result.\n\n    If the test result is truthy, the function invokes `fcn`; otherwise, the\n    function invokes the `done` callback.\n\n    The function to invoke is provided two arguments:\n\n    - i: iteration number (starting from zero).\n    - next: a callback which must be invoked before proceeding to the next\n      iteration.\n\n    The first argument of the `next` callback is an `error` argument. If `fcn`\n    calls the `next` callback with a truthy `error` argument, the function\n    suspends execution and immediately calls the `done` callback for subsequent\n    `error` handling.\n\n    The `done` callback is invoked with an `error` argument and any arguments\n    passed to the final `next` callback.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Parameters\n    ----------\n    predicate: Function\n        The predicate function which indicates whether to continue invoking a\n        function.\n\n    fcn: Function\n        The function to invoke.\n\n    done: Function\n        Callback to invoke upon completion.\n\n    thisArg: any (optional)\n        Execution context for the invoked function.\n\n    Examples\n    --------\n    > function predicate( i, clbk ) { clbk( null, i < 5 ); };\n    > function fcn( i, next ) {\n    ...     setTimeout( onTimeout, i );\n    ...     function onTimeout() {\n    ...         next( null, 'boop'+i );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > whileAsync( predicate, fcn, done )\n    boop: 4\n\n    See Also\n    --------\n    doUntilAsync, doWhileAsync, untilAsync, whilst\n","whileEach":"\nwhileEach( collection, predicate, fcn[, thisArg] )\n    While a test condition is true, invokes a function for each element in a\n    collection.\n\n    When invoked, both the predicate function and the function to apply are\n    provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    predicate: Function\n        The predicate function which indicates whether to continue iterating\n        over a collection.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    thisArg: any (optional)\n        Execution context for the applied function.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === v; };\n    > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n    > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n    > whileEach( arr, predicate, logger )\n    0: 1\n    1: 2\n    2: 3\n    3: 4\n\n    See Also\n    --------\n    untilEach, whileEachRight\n","whileEachRight":"\nwhileEachRight( collection, predicate, fcn[, thisArg] )\n    While a test condition is true, invokes a function for each element in a\n    collection, iterating from right to left.\n\n    When invoked, both the predicate function and the function to apply are\n    provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    predicate: Function\n        The predicate function which indicates whether to continue iterating\n        over a collection.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    thisArg: any (optional)\n        Execution context for the applied function.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === v; };\n    > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n    > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n    > whileEachRight( arr, predicate, logger )\n    5: 5\n    4: 4\n    3: 3\n    2: 2\n\n    See Also\n    --------\n    whileEach, untilEachRight\n","whilst":"\nwhilst( predicate, fcn[, thisArg] )\n    Invokes a function while a test condition is true.\n\n    When invoked, both the predicate function and the function to invoke are\n    provided a single argument:\n\n    - i: iteration number (starting from zero).\n\n    Parameters\n    ----------\n    predicate: Function\n        The predicate function which indicates whether to continue invoking a\n        function.\n\n    fcn: Function\n        The function to invoke.\n\n    thisArg: any (optional)\n        Execution context for the invoked function.\n\n    Examples\n    --------\n    > function predicate( i ) { return ( i < 5 ); };\n    > function beep( i ) { console.log( 'boop: %d', i ); };\n    > whilst( predicate, beep )\n    boop: 0\n    boop: 1\n    boop: 2\n    boop: 3\n    boop: 4\n\n    See Also\n    --------\n    doUntil, doWhile, until, whileAsync, whileEach\n","wilcoxon":"\nwilcoxon( x[, y][, options] )\n    Computes a one-sample or paired Wilcoxon signed rank test.\n\n    When no `y` is supplied, the function performs a one-sample  Wilcoxon signed\n    rank test for the null hypothesis that the data is drawn from a symmetric\n    distribution around zero.\n\n    When `y` is supplied, the function tests whether the\n    differences `x - y` come from a symmetric distribution around zero.\n\n    If `x` has less than fifty elements, an exact p-value is computed if there\n    are no zero values or ties. Otherwise, a normal approximation is used.\n\n    The returned object comes with a `.print()` method which when invoked will\n    print a formatted output of the results of the hypothesis test.\n\n    Parameters\n    ----------\n    x: Array<number>|TypedArray\n        Data array.\n\n    y: Array<number>|TypedArray (optional)\n        Paired data array.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.alternative: string (optional)\n        Indicates whether the alternative hypothesis is that the mean of `x` is\n        larger than `mu` (`greater`), smaller than `mu` (`less`), or equal to\n        `mu` (`two-sided`). Default: `'two-sided'`.\n\n    options.correction: boolean (optional)\n        Determines whether to apply continuity correction adjusting the Wilcoxon\n        rank statistic by 0.5 towards the mean when using the normal\n        approximation. Default: `true`.\n\n    options.exact: boolean (optional)\n        Determines whether to force use of the exact distribution instead of a\n        normal approximation when there are more than fifty data points.\n        Default: `false`.\n\n    options.mu: number (optional)\n        Hypothesized true location under the null hypothesis. Set this option to\n        test whether the data comes from a distribution with the specified `mu`.\n        Default: `0`.\n\n    options.zeroMethod: string (optional)\n        Method governing how zero-differences are handled (`pratt`, `wilcox`, or\n        `zsplit`). When set to `pratt`, differences of zero are used to\n        calculate ranks but their ranks are then dropped. When set to `wilcox`,\n        all zero-differences are discarded. When set to `zsplit`, differences of\n        zero are used to rank and their ranks are then split between positive\n        and negative ones. Default: `'wilcox'`.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Used significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.nullValue: number\n        Assumed location parameter under H0.\n\n    out.alternative: string\n        Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n    out.method: string\n        Name of test.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    // One-sample test:\n    > var arr = [ 6, 8, 14, 16, 23, 24, 28, 29, 41, -48, 49, 56, 60, -67, 75 ];\n    > var out = wilcoxon( x )\n    {\n        'rejected': true,\n        'alpha': 0.05,\n        'pValue': 0.04125976562499978,\n        'statistic': 96\n        // ...\n    }\n\n    // Paired test:\n    > runif = base.random.discreteUniform.factory( 1, 5, { 'seed': 786 });\n    > var x = new Array( 100 );\n    > var y = new Array( 100 );\n    > for ( i = 0; i < x.length; i++ ) {\n    ...     x[ i ] = runif();\n    ...     y[ i ] = runif();\n    ... }\n    > out = wilcoxon( x, y )\n    {\n        'rejected': false,\n        'alpha': 0.05,\n        'pValue': 0.21759090963694638,\n        'statistic': 2702.5,\n        // ...\n    }\n\n    // Print formatted output:\n    > var table = out.print()\n    Paired Wilcoxon signed rank test\n\n    Alternative hypothesis: Median of the difference `x - y` is not equal to 0\n\n        pValue: 0.2176\n        statistic: 2702.5\n\n    Test Decision: Fail to reject null in favor of alternative at 5% significance level\n\n\n    // Choose custom significance level:\n    > out = wilcoxon( arr, { 'alpha': 0.01 });\n    > table = out.print()\n    One-Sample Wilcoxon signed rank test\n\n    Alternative hypothesis: Median of `x` is not equal to 0\n\n        pValue: 0.0413\n        statistic: 96\n\n    Test Decision: Fail to reject null in favor of alternative at 1% significance level\n\n\n    // Test for a median equal to ten:\n    > out = wilcoxon( arr, { 'mu': 10 })\n    {\n        'rejected': false,\n        'alpha': 0.05,\n        'pValue': 0.11169650413134602,\n        'statistic': 88.5,\n        'nullValue': 10,\n        // ...\n    }\n\n    // Perform one-sided tests:\n    > out = wilcoxon( arr, { 'alternative': 'less' });\n    > table = out.print()\n    One-Sample Wilcoxon signed rank test\n\n    Alternative hypothesis: Median of `x` is less than 0\n\n        pValue: 0.9823\n        statistic: 96\n\n    Test Decision: Fail to reject null in favor of alternative at 5% significance level\n\n\n    > out = wilcoxon( arr, { 'alternative': 'greater' });\n    > table = out.print()\n    One-Sample Wilcoxon signed rank test\n\n    Alternative hypothesis: Median of `x` is greater than 0\n\n        pValue: 0.0206\n        statistic: 96\n\n    Test Decision: Reject null in favor of alternative at 5% significance level\n\n    See Also\n    --------\n    ttest, ztest\n","writableProperties":"\nwritableProperties( value )\n    Returns an array of an object's own writable property names and symbols.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    props: Array\n        List of an object's own writable properties.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var props = writableProperties( obj )\n    [ 'beep' ]\n\n    See Also\n    --------\n    inheritedWritableProperties, writablePropertiesIn, properties\n","writablePropertiesIn":"\nwritablePropertiesIn( value )\n    Returns an array of an object's own and inherited writable property names\n    and symbols.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    props: Array\n        List of an object's own and inherited writable property names and\n        symbols.\n\n    Examples\n    --------\n    > var props = writablePropertiesIn( [] )\n\n    See Also\n    --------\n    inheritedWritableProperties, writableProperties, propertiesIn\n","writablePropertyNames":"\nwritablePropertyNames( value )\n    Returns an array of an object's own writable property names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's own writable property names.\n\n    Examples\n    --------\n    > var obj = { 'a': 'b' };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = true;\n    > desc.writable = false;\n    > desc.value = 'boop';\n    > defineProperty( obj, 'beep', desc );\n    > var keys = writablePropertyNames( obj )\n    [ 'a' ]\n\n    See Also\n    --------\n    inheritedWritablePropertyNames, writableProperties, writablePropertyNamesIn, writablePropertySymbols, propertyNames\n","writablePropertyNamesIn":"\nwritablePropertyNamesIn( value )\n    Returns an array of an object's own and inherited writable property names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's own and inherited writable property names.\n\n    Examples\n    --------\n    > var obj = { 'a': 'b' };\n    > var desc = {};\n    > desc.configurable = true;\n    > desc.enumerable = true;\n    > desc.writable = false;\n    > desc.value = 'boop';\n    > defineProperty( obj, 'beep', desc );\n    > var keys = writablePropertyNamesIn( obj )\n    e.g., [ 'a', ... ]\n\n    See Also\n    --------\n    inheritedWritablePropertyNames, writablePropertiesIn, writablePropertyNames, writablePropertySymbolsIn, propertyNamesIn\n","writablePropertySymbols":"\nwritablePropertySymbols( value )\n    Returns an array of an object's own writable symbol properties.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's own writable symbol properties.\n\n    Examples\n    --------\n    > var obj = {};\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.writable = true;\n    > desc.value = 'boop';\n    > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n    > defineProperty( obj, sym, desc );\n    > var symbols = writablePropertySymbols( obj )\n\n    See Also\n    --------\n    inheritedWritablePropertySymbols, writableProperties, writablePropertyNames, writablePropertySymbolsIn, propertySymbols\n","writablePropertySymbolsIn":"\nwritablePropertySymbolsIn( value )\n    Returns an array of an object's own and inherited writable symbol\n    properties.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's own and inherited writable symbol properties.\n\n    Examples\n    --------\n    > var obj = {};\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.writable = true;\n    > desc.value = 'boop';\n    > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n    > defineProperty( obj, sym, desc );\n    > var symbols = writablePropertySymbolsIn( obj )\n\n    See Also\n    --------\n    inheritedWritablePropertySymbols, writablePropertiesIn, writablePropertyNamesIn, writablePropertySymbols, propertySymbolsIn\n","writeFile":"\nwriteFile( file, data[, options], clbk )\n    Asynchronously writes data to a file.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    data: string|Buffer\n        Data to write.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. The encoding option is ignored if the data argument is a\n        buffer. Default: 'utf8'.\n\n    options.flag: string (optional)\n        Flag. Default: 'w'.\n\n    options.mode: integer (optional)\n        Mode. Default: 0o666.\n\n    clbk: Function\n        Callback to invoke upon writing data to a file.\n\n    Examples\n    --------\n    > function onWrite( error ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     }\n    ... };\n    > writeFile( './beep/boop.txt', 'beep boop', onWrite );\n\n\nwriteFile.sync( file, data[, options] )\n    Synchronously writes data to a file.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    data: string|Buffer\n        Data to write.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. The encoding option is ignored if the data argument is a\n        buffer. Default: 'utf8'.\n\n    options.flag: string (optional)\n        Flag. Default: 'w'.\n\n    options.mode: integer (optional)\n        Mode. Default: 0o666.\n\n    Returns\n    -------\n    err: Error|null\n        Error object or null.\n\n    Examples\n    --------\n    > var err = writeFile.sync( './beep/boop.txt', 'beep boop' );\n\n    See Also\n    --------\n    exists, readFile\n","writeFile.sync":"\nwriteFile.sync( file, data[, options] )\n    Synchronously writes data to a file.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    data: string|Buffer\n        Data to write.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. The encoding option is ignored if the data argument is a\n        buffer. Default: 'utf8'.\n\n    options.flag: string (optional)\n        Flag. Default: 'w'.\n\n    options.mode: integer (optional)\n        Mode. Default: 0o666.\n\n    Returns\n    -------\n    err: Error|null\n        Error object or null.\n\n    Examples\n    --------\n    > var err = writeFile.sync( './beep/boop.txt', 'beep boop' );\n\n    See Also\n    --------\n    exists, readFile","zip":"\nzip( ...arr[, options] )\n    Generates array tuples from input arrays.\n\n    Parameters\n    ----------\n    arr: ...Array\n        Input arrays to be zipped.\n\n    options: Object (optional)\n        Options.\n\n    options.trunc: boolean (optional)\n        Boolean indicating whether to truncate arrays longer than the shortest\n        input array. Default: `true`.\n\n    options.fill: any (optional)\n        Fill value used for arrays of unequal length. Default: `null`.\n\n    options.arrays: boolean (optional)\n        Boolean indicating whether an input array should be interpreted as an\n        array of arrays to be zipped. Default: `false`.\n\n    Returns\n    -------\n    out: Array\n        Array of arrays.\n\n    Examples\n    --------\n    // Basic usage:\n    > var out = zip( [ 1, 2 ], [ 'a', 'b' ] )\n    [ [ 1, 'a' ], [ 2, 'b' ] ]\n\n    // Turn off truncation:\n    > var opts = { 'trunc': false };\n    > out = zip( [ 1, 2, 3 ], [ 'a', 'b' ], opts )\n    [ [ 1, 'a' ], [ 2, 'b' ], [ 3, null ] ]\n\n    See Also\n    --------\n    unzip\n","ztest":"\nztest( x, sigma[, options] )\n    Computes a one-sample z-test.\n\n    The function performs a one-sample z-test for the null hypothesis that the\n    data in array or typed array `x` is drawn from a normal distribution with\n    mean zero and standard deviation `sigma`.\n\n    The returned object comes with a `.print()` method which when invoked will\n    print a formatted output of the results of the hypothesis test.\n\n    Parameters\n    ----------\n    x: Array<number>\n        Data array.\n\n    sigma: number\n        Known standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.alternative: string (optional)\n        Indicates whether the alternative hypothesis is that the mean of `x` is\n        larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n        `mu` (`two-sided`). Default: `'two-sided'`.\n\n    options.mu: number (optional)\n        Hypothesized true mean under the null hypothesis. Set this option to\n        test whether the data comes from a distribution with the specified `mu`.\n        Default: `0`.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Used significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.ci: Array<number>\n        1-alpha confidence interval for mean.\n\n    out.nullValue: number\n        Assumed mean value under H0.\n\n    out.sd: number\n        Standard error.\n\n    out.alternative: string\n        Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n    out.method: string\n        Name of test (`One-Sample z-test`).\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    // One-sample z-test:\n    > var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 212 } );\n    > var x = new Array( 100 );\n    > for ( var i = 0; i < x.length; i++ ) {\n    ...     x[ i ] = rnorm();\n    ... }\n    > var out = ztest( x, 2.0 )\n    {\n        alpha: 0.05,\n        rejected: false,\n        pValue: ~0.180,\n        statistic: ~-1.34,\n        ci: [ ~-0.66, ~0.124 ],\n        ...\n    }\n\n    // Choose custom significance level and print output:\n    > arr = [ 2, 4, 3, 1, 0 ];\n    > out = ztest( arr, 2.0, { 'alpha': 0.01 } );\n    > table = out.print()\n    One-sample z-test\n\n    Alternative hypothesis: True mean is not equal to 0\n\n        pValue: 0.0253\n        statistic: 2.2361\n        99% confidence interval: [-0.3039,4.3039]\n\n    Test Decision: Fail to reject null in favor of alternative at 1%\n    significance level\n\n\n    // Test for a mean equal to five:\n    > var arr = [ 4, 4, 6, 6, 5 ];\n    > out = ztest( arr, 1.0, { 'mu': 5 } )\n    {\n        rejected: false,\n        pValue: 1,\n        statistic: 0,\n        ci: [ ~4.123, ~5.877 ],\n        // ...\n    }\n\n    // Perform one-sided tests:\n    > arr = [ 4, 4, 6, 6, 5 ];\n    > out = ztest( arr, 1.0, { 'alternative': 'less' } )\n    {\n        alpha: 0.05,\n        rejected: false,\n        pValue: 1,\n        statistic: 11.180339887498949,\n        ci: [ -Infinity, 5.735600904580115 ],\n        // ...\n    }\n    > out = ztest( arr, 1.0, { 'alternative': 'greater' } )\n    {\n        alpha: 0.05,\n        rejected: true,\n        pValue: 0,\n        statistic: 11.180339887498949,\n        ci: [ 4.264399095419885, Infinity ],\n        //...\n    }\n\n    See Also\n    --------\n    ztest2\n","ztest2":"\nztest2( x, y, sigmax, sigmay[, options] )\n    Computes a two-sample z-test.\n\n    By default, the function performs a two-sample z-test for the null\n    hypothesis that the data in arrays or typed arrays `x` and `y` is\n    independently drawn from normal distributions with equal means and known\n    standard deviations `sigmax` and `sigmay`.\n\n    The returned object comes with a `.print()` method which when invoked will\n    print a formatted output of the results of the hypothesis test.\n\n    Parameters\n    ----------\n    x: Array<number>\n        First data array.\n\n    y: Array<number>\n        Second data array.\n\n    sigmax: number\n        Known standard deviation of first group.\n\n    sigmay: number\n        Known standard deviation of second group.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.alternative: string (optional)\n        Either `two-sided`, `less` or `greater`. Indicates whether the\n        alternative hypothesis is that `x` has a larger mean than `y`\n        (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n        the same (`two-sided`). Default: `'two-sided'`.\n\n    options.difference: number (optional)\n        Number denoting the difference in means under the null hypothesis.\n        Default: `0`.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Used significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.ci: Array<number>\n        1-alpha confidence interval for the mean.\n\n    out.nullValue: number\n        Assumed difference in means under H0.\n\n    out.xmean: number\n        Sample mean of `x`.\n\n    out.ymean: number\n        Sample mean of `y`.\n\n    out.alternative: string\n        Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n    out.method: string\n        Name of test.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    // Drawn from Normal(0,2):\n    > var x = [ -0.21, 0.14, 1.65, 2.11, -1.86, -0.29, 1.48, 0.81, 0.86, 1.04 ];\n\n    // Drawn from Normal(1,2):\n    > var y = [ -1.53, -2.93, 2.34, -1.15, 2.7, -0.12, 4.22, 1.66, 3.43, 4.66 ];\n    > var out = ztest2( x, y, 2.0, 2.0 )\n    {\n        alpha: 0.05,\n        rejected: false,\n        pValue: ~0.398,\n        statistic: ~-0.844\n        ci: [ ~-2.508, ~0.988 ],\n        alternative: 'two-sided',\n        method: 'Two-sample z-test',\n        nullValue: 0,\n        xmean: ~0.573,\n        ymean: ~1.328\n    }\n\n    // Print table output:\n    > var table = out.print()\n    Two-sample z-test\n\n    Alternative hypothesis: True difference in means is not equal to 0\n\n        pValue: 0.3986\n        statistic: -0.8441\n        95% confidence interval: [-2.508,0.998]\n\n    Test Decision: Fail to reject null in favor of alternative at 5%\n    significance level\n\n    // Choose a different significance level than `0.05`:\n    > out = ztest2( x, y, 2.0, 2.0, { 'alpha': 0.4 } );\n    > table = out.print()\n    Two-sample z-test\n\n    Alternative hypothesis: True difference in means is not equal to 0\n\n        pValue: 0.3986\n        statistic: -0.8441\n        60% confidence interval: [-1.5078,-0.0022]\n\n    Test Decision: Reject null in favor of alternative at 40% significance level\n\n    // Perform one-sided tests:\n    > out = ztest2( x, y, 2.0, 2.0, { 'alternative': 'less' } );\n    > table = out.print()\n    Two-sample z-test\n\n    Alternative hypothesis: True difference in means is less than 0\n\n        pValue: 0.1993\n        statistic: -0.8441\n        95% confidence interval: [-Infinity,0.7162]\n\n    Test Decision: Fail to reject null in favor of alternative at 5%\n    significance level\n\n\n    > out = ztest2( x, y, 2.0, 2.0, { 'alternative': 'greater' } );\n    > table = out.print()\n    Two-sample z-test\n\n    Alternative hypothesis: True difference in means is greater than 0\n\n        pValue: 0.8007\n        statistic: -0.8441\n        95% confidence interval: [-2.2262,Infinity]\n\n    Test Decision: Fail to reject null in favor of alternative at 5%\n    significance level\n\n    // Test for a difference in means besides zero:\n    > var rnorm = base.random.normal.factory({ 'seed': 372 } );\n    > x = new Array( 100 );\n    > for ( i = 0; i < x.length; i++ ) {\n    ...     x[ i ] = rnorm( 2.0, 1.0 );\n    ... }\n    > y = new Array( 100 );\n    ... for ( i = 0; i < x.length; i++ ) {\n    ...     y[ i ] = rnorm( 0.0, 2.0 );\n    ... }\n    > out = ztest2( x, y, 1.0, 2.0, { 'difference': 2.0 } )\n    {\n        rejected: false,\n        pValue: ~0.35,\n        statistic: ~-0.935\n        ci: [ ~1.353, ~2.229 ],\n        // ...\n    }\n\n    See Also\n    --------\n    ztest\n"}
+{"abs":"\nabs( x[, options] )\n    Computes the absolute value.\n\n    If provided a number, the function returns a number.\n\n    If provided an ndarray or array-like object, the function performs element-\n    wise computation.\n\n    If provided an array-like object, the function returns an array-like object\n    having the same length and data type as `x`.\n\n    If provided an ndarray, the function returns an ndarray having the same\n    shape and data type as `x`.\n\n    Parameters\n    ----------\n    x: ndarray|ArrayLikeObject|number\n        Input value.\n\n    options: Object (optional)\n        Options.\n\n    options.order: string (optional)\n        Output array order (either row-major (C-style) or column-major (Fortran-\n        style)). Only applicable when the input array is an ndarray. By default,\n        the output array order is inferred from the input array.\n\n    options.dtype: string (optional)\n        Output array data type. Only applicable when the input array is either\n        an ndarray or array-like object. By default, the output array data type\n        is inferred from the input array.\n\n    Returns\n    -------\n    y: ndarray|ArrayLikeObject|number\n        Results.\n\n    Examples\n    --------\n    // Provide a number:\n    > var y = abs( -1.0 )\n    1.0\n\n    // Provide an array-like object:\n    > var x = new Float64Array( [ -1.0, -2.0 ] );\n    > y = abs( x )\n    <Float64Array>[ 1.0, 2.0 ]\n\n    > x = [ -1.0, -2.0 ];\n    > y = abs( x )\n    [ 1.0, 2.0 ]\n\n    // Provide an ndarray:\n    > x = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] );\n    > y = abs( x )\n    <ndarray>\n    > y.get( 0, 1 )\n    2.0\n\n\nabs.assign( x, y )\n    Computes the absolute value and assigns results to a provided output array.\n\n    Parameters\n    ----------\n    x: ndarray|ArrayLikeObject\n        Input array.\n\n    y: ndarray|ArrayLikeObject\n        Output array. Must be the same data \"kind\" (i.e., ndarray or array-like\n        object) as the input array.\n\n    Returns\n    -------\n    y: ndarray|ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Provide an array-like object:\n    > var x = new Float64Array( [ -1.0, -2.0 ] );\n    > var y = new Float64Array( x.length );\n    > var out = abs.assign( x, y )\n    <Float64Array>[ 1.0, 2.0 ]\n    > var bool = ( out === y )\n    true\n\n    > x = [ -1.0, -2.0 ];\n    > y = [ 0.0, 0.0 ];\n    > out = abs.assign( x, y )\n    [ 1.0, 2.0 ]\n    > bool = ( out === y )\n    true\n\n    // Provide an ndarray:\n    > x = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] );\n    > y = array( [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ] );\n    > out = abs.assign( x, y )\n    <ndarray>\n    > out.get( 0, 1 )\n    2.0\n    > bool = ( out === y )\n    true\n\n","abs.assign":"\nabs.assign( x, y )\n    Computes the absolute value and assigns results to a provided output array.\n\n    Parameters\n    ----------\n    x: ndarray|ArrayLikeObject\n        Input array.\n\n    y: ndarray|ArrayLikeObject\n        Output array. Must be the same data \"kind\" (i.e., ndarray or array-like\n        object) as the input array.\n\n    Returns\n    -------\n    y: ndarray|ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Provide an array-like object:\n    > var x = new Float64Array( [ -1.0, -2.0 ] );\n    > var y = new Float64Array( x.length );\n    > var out = abs.assign( x, y )\n    <Float64Array>[ 1.0, 2.0 ]\n    > var bool = ( out === y )\n    true\n\n    > x = [ -1.0, -2.0 ];\n    > y = [ 0.0, 0.0 ];\n    > out = abs.assign( x, y )\n    [ 1.0, 2.0 ]\n    > bool = ( out === y )\n    true\n\n    // Provide an ndarray:\n    > x = array( [ [ -1.0, -2.0 ], [ -3.0, -4.0 ] ] );\n    > y = array( [ [ 0.0, 0.0 ], [ 0.0, 0.0 ] ] );\n    > out = abs.assign( x, y )\n    <ndarray>\n    > out.get( 0, 1 )\n    2.0\n    > bool = ( out === y )\n    true","acartesianPower":"\nacartesianPower( x, n )\n    Returns the Cartesian power.\n\n    If provided an empty array, the function returns an empty array.\n\n    If `n` is less than or equal to zero, the function returns an empty array.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    n: integer\n        Power.\n\n    Returns\n    -------\n    out: Array<Array>\n        Cartesian product.\n\n    Examples\n    --------\n    > var x = [ 1, 2 ];\n    > var out = acartesianPower( x, 2 )\n    [ [ 1, 1 ], [ 1, 2 ], [ 2, 1 ], [ 2, 2 ] ]\n\n    See Also\n    --------\n    acartesianProduct, acartesianSquare\n","acartesianProduct":"\nacartesianProduct( x1, x2 )\n    Returns the Cartesian product.\n\n    If provided one or more empty arrays, the function returns an empty array.\n\n    Parameters\n    ----------\n    x1: ArrayLikeObject\n        First input array.\n\n    x2: ArrayLikeObject\n        Second input array.\n\n    Returns\n    -------\n    out: Array<Array>\n        Cartesian product.\n\n    Examples\n    --------\n    > var x1 = [ 1, 2 ];\n    > var x2 = [ 3, 4 ];\n    > var out = acartesianProduct( x1, x2 )\n    [ [ 1, 3 ], [ 1, 4 ], [ 2, 3 ], [ 2, 4 ] ]\n\n    See Also\n    --------\n    acartesianPower, acartesianSquare\n","acartesianSquare":"\nacartesianSquare( x )\n    Returns the Cartesian square.\n\n    If provided an empty array, the function returns an empty array.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    Returns\n    -------\n    out: Array<Array>\n        Cartesian product.\n\n    Examples\n    --------\n    > var out = acartesianSquare( [ 1, 2 ] )\n    [ [ 1, 1 ], [ 1, 2 ], [ 2, 1 ], [ 2, 2 ] ]\n\n    See Also\n    --------\n    acartesianPower, acartesianProduct\n","acronym":"\nacronym( str[, options] )\n    Generates an acronym for a given string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    options: Object (optional)\n        Options.\n\n    options.stopwords: Array<string> (optional)\n        Array of custom stop words.\n\n    Returns\n    -------\n    out: string\n        Acronym for the given string.\n\n    Examples\n    --------\n    > var out = acronym( 'the quick brown fox' )\n    'QBF'\n    > out = acronym( 'Hard-boiled eggs' )\n    'HBE'\n","aempty":"\naempty( length[, dtype] )\n    Creates an uninitialized array having a specified length.\n\n    In browser environments, the function always returns zero-filled arrays.\n\n    If `dtype` is 'generic', the function always returns a zero-filled array.\n\n    In Node.js versions >=3.0.0, the underlying memory of returned typed arrays\n    is *not* initialized. Memory contents are unknown and may contain\n    *sensitive* data.\n\n    Parameters\n    ----------\n    length: integer\n        Array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = aempty( 2 )\n    <Float64Array>\n    > arr = aempty( 2, 'float32' )\n    <Float32Array>\n\n    See Also\n    --------\n    aemptyLike, afull, aones, azeros, ndempty\n","aemptyLike":"\naemptyLike( x[, dtype] )\n    Creates an uninitialized array having the same length and data type as a\n    provided input array.\n\n    In browser environments, the function always returns zero-filled arrays.\n\n    If `dtype` is 'generic', the function always returns a zero-filled array.\n\n    In Node.js versions >=3.0.0, the underlying memory of returned typed arrays\n    is *not* initialized. Memory contents are unknown and may contain\n    *sensitive* data.\n\n    Parameters\n    ----------\n    x: TypedArray|Array\n        Input array.\n\n    dtype: string (optional)\n        Data type. If not provided, the output array data type is inferred from\n        the input array.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var x = new Float64Array( 2 );\n    > var arr = aemptyLike( x )\n    <Float64Array>\n    > arr = aemptyLike( x, 'float32' )\n    <Float32Array>\n\n    See Also\n    --------\n    aempty, afullLike, aonesLike, azerosLike, ndemptyLike\n","AFINN_96":"\nAFINN_96()\n    Returns a list of English words rated for valence.\n\n    The returned list contains 1468 English words (and phrases) rated for\n    valence. Negative words have a negative valence [-5,0). Positive words have\n    a positive valence (0,5]. Neutral words have a valence of 0.\n\n    A few notes:\n\n    - The list is an earlier version of AFINN-111.\n    - The list includes misspelled words. Their presence is intentional, as such\n      misspellings frequently occur in social media content.\n    - All words are lowercase.\n    - Some \"words\" are phrases; e.g., \"cashing in\", \"cool stuff\".\n    - Words may contain apostrophes; e.g., \"can't stand\".\n    - Words may contain dashes; e.g., \"cover-up\", \"made-up\".\n\n    Returns\n    -------\n    out: Array<Array>\n        List of English words and their valence.\n\n    Examples\n    --------\n    > var list = AFINN_96()\n    [ [ 'abandon', -2 ], [ 'abandons', -2 ], [ 'abandoned', -2 ], ... ]\n\n    References\n    ----------\n    - Nielsen, Finn Årup. 2011. \"A new ANEW: Evaluation of a word list for\n    sentiment analysis in microblogs.\" In *Proceedings of the ESWC2011 Workshop\n    on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n    718:93–98. CEUR Workshop Proceedings. <http://ceur-ws.org/Vol-718/paper_16.\n    pdf>.\n\n    * If you use the list for publication or third party consumption, please\n    cite the listed reference.\n\n    See Also\n    --------\n    AFINN_111\n","AFINN_111":"\nAFINN_111()\n    Returns a list of English words rated for valence.\n\n    The returned list contains 2477 English words (and phrases) rated for\n    valence. Negative words have a negative valence [-5,0). Positive words have\n    a positive valence (0,5]. Neutral words have a valence of 0.\n\n    A few notes:\n\n    - The list includes misspelled words. Their presence is intentional, as such\n      misspellings frequently occur in social media content.\n    - All words are lowercase.\n    - Words may contain numbers; e.g., \"n00b\".\n    - Some \"words\" are phrases; e.g., \"cool stuff\", \"not good\".\n    - Words may contain apostrophes; e.g., \"can't stand\".\n    - Words may contain diaeresis; e.g., \"naïve\".\n    - Words may contain dashes; e.g., \"self-deluded\", \"self-confident\".\n\n    Returns\n    -------\n    out: Array<Array>\n        List of English words and their valence.\n\n    Examples\n    --------\n    > var list = AFINN_111()\n    [ [ 'abandon', -2 ], [ 'abandoned', -2 ], [ 'abandons', -2 ], ... ]\n\n    References\n    ----------\n    - Nielsen, Finn Årup. 2011. \"A new ANEW: Evaluation of a word list for\n    sentiment analysis in microblogs.\" In *Proceedings of the ESWC2011 Workshop\n    on 'Making Sense of Microposts': Big Things Come in Small Packages.*,\n    718:93–98. CEUR Workshop Proceedings. <http://ceur-ws.org/Vol-718/paper_16.\n    pdf>.\n\n    * If you use the list for publication or third party consumption, please\n    cite the listed reference.\n\n    See Also\n    --------\n    AFINN_96\n","afull":"\nafull( length, value[, dtype] )\n    Returns a filled array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Array length.\n\n    value: any\n        Fill value.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = afull( 2, 1.0 )\n    <Float64Array>[ 1.0, 1.0 ]\n    > arr = afull( 2, 1.0, 'float32' )\n    <Float32Array>[ 1.0, 1.0 ]\n\n    See Also\n    --------\n    afullLike, aones, azeros\n","afullLike":"\nafullLike( x[, dtype] )\n    Returns a filled array having the same length and data type as a provided\n    input array.\n\n    Parameters\n    ----------\n    x: TypedArray|Array\n        Input array.\n\n    dtype: string (optional)\n        Data type. If not provided, the output array data type is inferred from\n        the input array.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var x = new Float64Array( 2 );\n    > var y = afullLike( x, 1.0 )\n    <Float64Array>[ 1.0, 1.0 ]\n    > y = afullLike( x, 1.0, 'float32' )\n    <Float32Array>[ 1.0, 1.0 ]\n\n    See Also\n    --------\n    afull, aonesLike, azerosLike\n","alias2pkg":"\nalias2pkg( alias )\n    Returns the package name associated with a provided alias.\n\n    Parameters\n    ----------\n    alias: string\n        Alias.\n\n    Returns\n    -------\n    out: string|null\n        Package name.\n\n    Examples\n    --------\n    > var v = alias2pkg( 'base.sin' )\n    '@stdlib/math/base/special/sin'\n\n    See Also\n    --------\n    alias2related, aliases, pkg2alias\n","alias2related":"\nalias2related( alias )\n    Returns aliases related to a specified alias.\n\n    Parameters\n    ----------\n    alias: string\n        Alias.\n\n    Returns\n    -------\n    out: Array|null\n        Related aliases.\n\n    Examples\n    --------\n    > var v = alias2related( 'base.sin' )\n    [...]\n\n    See Also\n    --------\n    alias2pkg, aliases, pkg2related\n","alias2standalone":"\nalias2standalone( alias )\n    Returns the standalone package name associated with a provided alias.\n\n    Parameters\n    ----------\n    alias: string\n        Alias.\n\n    Returns\n    -------\n    out: string|null\n        Standalone package name.\n\n    Examples\n    --------\n    > var v = alias2standalone( 'base.sin' )\n    '@stdlib/math-base-special-sin'\n\n    See Also\n    --------\n    alias2pkg, alias2related, aliases, pkg2alias, pkg2standalone\n","aliases":"\naliases( [namespace] )\n    Returns a list of standard library aliases.\n\n    Parameters\n    ----------\n    namespace: string (optional)\n        Namespace filter.\n\n    Returns\n    -------\n    out: Array\n        List of aliases.\n\n    Examples\n    --------\n    > var o = aliases()\n    [...]\n    > o = aliases( '@stdlib/math/base/special' )\n    [...]\n\n    See Also\n    --------\n    alias2pkg, alias2related, pkg2alias\n","allocUnsafe":"\nallocUnsafe( size )\n    Allocates a buffer having a specified number of bytes.\n\n    The underlying memory of returned buffers is not initialized. Memory\n    contents are unknown and may contain sensitive data.\n\n    When the size is less than half a buffer pool size, memory is allocated from\n    the buffer pool for faster allocation of Buffer instances.\n\n    Parameters\n    ----------\n    size: integer\n        Number of bytes to allocate.\n\n    Returns\n    -------\n    out: Buffer\n        Buffer instance.\n\n    Examples\n    --------\n    > var buf = allocUnsafe( 100 )\n    <Buffer>\n\n    See Also\n    --------\n    Buffer, array2buffer, arraybuffer2buffer, copyBuffer, string2buffer\n","amskfilter":"\namskfilter( x, mask )\n    Returns a new array by applying a mask to a provided input array.\n\n    If a mask array element is truthy, the corresponding element in `x` is\n    included in the output array; otherwise, the corresponding element in `x` is\n    \"masked\" and thus excluded from the output array.\n\n    Parameters\n    ----------\n    x: Array|TypedArray|Object\n        Input array.\n\n    mask: Array|TypedArray|Object\n        Mask array.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Output array.\n\n    Examples\n    --------\n    > var x = [ 1, 2, 3, 4 ];\n    > var y = amskfilter( x, [ 0, 1, 0, 1 ] )\n    [ 2, 4 ]\n\n    See Also\n    --------\n    amskreject\n","amskput":"\namskput( x, mask, values[, options] )\n    Replaces elements of an array with provided values according to a provided\n    mask array.\n\n    In broadcasting modes, the function supports broadcasting a values array\n    containing a single element against the number of falsy values in the mask\n    array.\n\n    In repeat mode, the function supports recycling elements in a values array\n    to satisfy the number of falsy values in the mask array.\n\n    The function mutates the input array.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    mask: ArrayLikeObject\n        Mask array. If a mask array element is falsy, the corresponding element\n        in `x` is *replaced*; otherwise, the corresponding element in `x` is\n        \"masked\" and thus left unchanged.\n\n    values: ArrayLikeObject\n        Values to set.\n\n    options: Object (optional)\n        Function options.\n\n    options.mode: string (optional)\n        String specifying behavior when the number of values to set does not\n        equal the number of falsy mask values. The function supports the\n        following modes:\n\n        - 'strict': specifies that the function must raise an exception when the\n        number of values does not *exactly* equal the number of falsy mask\n        values.\n        - 'non_strict': specifies that the function must raise an exception when\n        the function is provided insufficient values to satisfy the mask array.\n        - 'strict_broadcast': specifies that the function must broadcast a\n        single-element values array and otherwise raise an exception when the\n        number of values does not **exactly** equal the number of falsy mask\n        values.\n        - 'broadcast': specifies that the function must broadcast a single-\n        element values array and otherwise raise an exception when the function\n        is provided insufficient values to satisfy the mask array.\n        - 'repeat': specifies that the function must reuse provided values when\n        replacing elements in `x` in order to satisfy the mask array.\n\n        Default: 'repeat'.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Input array.\n\n    Examples\n    --------\n    > var x = [ 1, 2, 3, 4 ];\n    > var out = amskput( x, [ 1, 0, 1, 0 ], [ 20, 40 ] )\n    [ 1, 20, 3, 40 ]\n    > var bool = ( out === x )\n    true\n\n    See Also\n    --------\n    aplace, aput, atake\n","amskreject":"\namskreject( x, mask )\n    Returns a new array by applying a mask to a provided input array.\n\n    If a mask array element is falsy, the corresponding element in `x` is\n    included in the output array; otherwise, the corresponding element in `x` is\n    \"masked\" and thus excluded from the output array.\n\n    Parameters\n    ----------\n    x: Array|TypedArray|Object\n        Input array.\n\n    mask: Array|TypedArray|Object\n        Mask array.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Output array.\n\n    Examples\n    --------\n    > var x = [ 1, 2, 3, 4 ];\n    > var y = amskreject( x, [ 0, 1, 0, 1 ] )\n    [ 1, 3 ]\n\n    See Also\n    --------\n    amskfilter\n","anans":"\nanans( length[, dtype] )\n    Returns an array filled with NaNs and having a specified length.\n\n    The function supports the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754)\n    - float32: single-precision floating-point numbers (IEEE 754)\n    - complex128: double-precision complex floating-point numbers\n    - complex64: single-precision complex floating-point numbers\n    - generic: generic JavaScript values\n\n    The default array data type is `float64`.\n\n    Parameters\n    ----------\n    length: integer\n        Array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = anans( 2 )\n    <Float64Array>[ NaN, NaN ]\n    > arr = anans( 2, 'float32' )\n    <Float32Array>[ NaN, NaN ]\n\n    See Also\n    --------\n    afull, anansLike, aones, azeros\n","anansLike":"\nanansLike( x[, dtype] )\n    Returns an array filled with NaNs and having the same length and data type\n    as a provided input array.\n\n    The function supports the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754).\n    - float32: single-precision floating-point numbers (IEEE 754).\n    - complex128: double-precision complex floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - generic: generic JavaScript values.\n\n    Parameters\n    ----------\n    x: TypedArray|Array\n        Input array.\n\n    dtype: string (optional)\n        Data type. If not provided, the output array data type is inferred from\n        the input array.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var x = new Float64Array( 2 );\n    > var y = anansLike( x )\n    <Float64Array>[ NaN, NaN ]\n    > y = anansLike( x, 'float32' )\n    <Float32Array>[ NaN, NaN ]\n\n    See Also\n    --------\n    afullLike, anans, aonesLike, azerosLike\n","anova1":"\nanova1( x, factor[, options] )\n    Performs a one-way analysis of variance.\n\n    Parameters\n    ----------\n    x: Array<number>\n        Measured values.\n\n    factor: Array\n        Array of treatments.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.method: string\n        Name of test.\n\n    out.means: Object\n        Group means alongside sample sizes and standard errors.\n\n    out.treatment: Object\n        Treatment results.\n\n    out.treatment.df: number\n        Treatment degrees of freedom.\n\n    out.treatment.ss: number\n        Treatment sum of squares.\n\n    out.treatment.ms: number\n        Treatment mean sum of squares.\n\n    out.error: Object\n        Error results.\n\n    out.error.df: number\n        Error degrees of freedom.\n\n    out.error.ss: number\n        Error sum of squares.\n\n    out.error.ms: number\n        Error mean sum of squares.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    > var x = [1, 3, 5, 2, 4, 6, 8, 7, 10, 11, 12, 15];\n    > var f = [\n    ... 'control', 'treatA', 'treatB', 'treatC', 'control',\n    ... 'treatA', 'treatB', 'treatC', 'control', 'treatA', 'treatB', 'treatC'\n    ... ];\n    > var out = anova1( x, f )\n    {...}\n\n","ANSCOMBES_QUARTET":"\nANSCOMBES_QUARTET()\n    Returns Anscombe's quartet.\n\n    Anscombe's quartet is a set of 4 datasets which all have nearly identical\n    simple statistical properties but vary considerably when graphed. Anscombe\n    created the datasets to demonstrate why graphical data exploration should\n    precede statistical data analysis and to show the effect of outliers on\n    statistical properties.\n\n    Returns\n    -------\n    out: Array<Array>\n        Anscombe's quartet.\n\n    Examples\n    --------\n    > var d = ANSCOMBES_QUARTET()\n    [[[10,8.04],...],[[10,9.14],...],[[10,7.46],...],[[8,6.58],...]]\n\n    References\n    ----------\n    - Anscombe, Francis J. 1973. \"Graphs in Statistical Analysis.\" *The American\n    Statistician* 27 (1). [American Statistical Association, Taylor & Francis,\n    Ltd.]: 17–21. <http://www.jstor.org/stable/2682899>.\n\n","any":"\nany( collection )\n    Tests whether at least one element in a collection is truthy.\n\n    The function immediately returns upon encountering a truthy value.\n\n    If provided an empty collection, the function returns `false`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if an element is truthy; otherwise, the\n        function returns `false`.\n\n    Examples\n    --------\n    > var arr = [ 0, 0, 0, 0, 1 ];\n    > var bool = any( arr )\n    true\n\n    See Also\n    --------\n    anyBy, every, forEach, none, some\n","anyBy":"\nanyBy( collection, predicate[, thisArg ] )\n    Tests whether at least one element in a collection passes a test implemented\n    by a predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    The function immediately returns upon encountering a truthy return value.\n\n    If provided an empty collection, the function returns `false`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns `true` for\n        any element; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function negative( v ) { return ( v < 0 ); };\n    > var arr = [ 1, 2, 3, 4, -1 ];\n    > var bool = anyBy( arr, negative )\n    true\n\n    See Also\n    --------\n    anyByAsync, anyByRight, everyBy, forEach, noneBy, someBy\n","anyByAsync":"\nanyByAsync( collection, [options,] predicate, done )\n    Tests whether at least one element in a collection passes a test implemented\n    by a predicate function.\n\n    When invoked, the predicate function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If the\n    predicate function accepts two arguments, the predicate function is\n    provided:\n\n    - value\n    - next\n\n    If the predicate function accepts three arguments, the predicate function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other predicate function signature, the predicate function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - result: test result.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    The function immediately returns upon encountering a non-falsy `result`\n    value and calls the `done` callback with `null` as the first argument and\n    `true` as the second argument.\n\n    If all elements fail, the function calls the `done` callback with `null`\n    as the first argument and `false` as the second argument.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > anyByAsync( arr, predicate, done )\n    1000\n    2500\n    3000\n    false\n\n    // Limit number of concurrent invocations:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 3000, 2500, 1000 ];\n    > anyByAsync( arr, opts, predicate, done )\n    2500\n    3000\n    1000\n    false\n\n    // Process sequentially:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 3000, 2500, 1000 ];\n    > anyByAsync( arr, opts, predicate, done )\n    3000\n    2500\n    1000\n    false\n\n\nanyByAsync.factory( [options,] predicate )\n    Returns a function which tests whether at least one element in a collection\n    passes a test implemented by a predicate function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = anyByAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    false\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    false\n\n    See Also\n    --------\n    anyBy, anyByRightAsync, everyByAsync, forEachAsync, noneByAsync, someByAsync\n","anyByAsync.factory":"\nanyByAsync.factory( [options,] predicate )\n    Returns a function which tests whether at least one element in a collection\n    passes a test implemented by a predicate function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = anyByAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    false\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    false\n\n    See Also\n    --------\n    anyBy, anyByRightAsync, everyByAsync, forEachAsync, noneByAsync, someByAsync","anyByRight":"\nanyByRight( collection, predicate[, thisArg ] )\n    Tests whether at least one element in a collection passes a test implemented\n    by a predicate function, iterating from right to left.\n\n    The predicate function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    The function immediately returns upon encountering a truthy return value.\n\n    If provided an empty collection, the function returns `false`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns `true` for\n        any element; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function negative( v ) { return ( v < 0 ); };\n    > var arr = [ -1, 1, 2, 3, 4 ];\n    > var bool = anyByRight( arr, negative )\n    true\n\n    See Also\n    --------\n    anyBy, anyByRightAsync, everyByRight, forEachRight, noneByRight, someByRight\n","anyByRightAsync":"\nanyByRightAsync( collection, [options,] predicate, done )\n    Tests whether at least one element in a collection passes a test implemented\n    by a predicate function, iterating from right to left.\n\n    When invoked, the predicate function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If the\n    predicate function accepts two arguments, the predicate function is\n    provided:\n\n    - value\n    - next\n\n    If the predicate function accepts three arguments, the predicate function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other predicate function signature, the predicate function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - result: test result.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    The function immediately returns upon encountering a non-falsy `result`\n    value and calls the `done` callback with `null` as the first argument and\n    `true` as the second argument.\n\n    If all elements fail, the function calls the `done` callback with `null`\n    as the first argument and `false` as the second argument.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > anyByRightAsync( arr, predicate, done )\n    1000\n    2500\n    3000\n    false\n\n    // Limit number of concurrent invocations:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 1000, 2500, 3000 ];\n    > anyByRightAsync( arr, opts, predicate, done )\n    2500\n    3000\n    1000\n    false\n\n    // Process sequentially:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 1000, 2500, 3000 ];\n    > anyByRightAsync( arr, opts, predicate, done )\n    3000\n    2500\n    1000\n    false\n\n\nanyByRightAsync.factory( [options,] predicate )\n    Returns a function which tests whether at least one element in a collection\n    passes a test implemented by a predicate function, iterating from right to\n    left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = anyByRightAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    false\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    false\n\n    See Also\n    --------\n    anyByAsync, anyByRight, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByRightAsync\n","anyByRightAsync.factory":"\nanyByRightAsync.factory( [options,] predicate )\n    Returns a function which tests whether at least one element in a collection\n    passes a test implemented by a predicate function, iterating from right to\n    left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = anyByRightAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    false\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    false\n\n    See Also\n    --------\n    anyByAsync, anyByRight, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByRightAsync","anyInBy":"\nanyInBy( object, predicate[, thisArg ] )\n    Tests whether at least one value in an object passes a test implemented by\n    a predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: the value of the current property being processed in the object\n    - key: the key of the current property being processed in the object\n    - object: the input object\n\n    The function immediately returns upon encountering a truthy return value.\n\n    If provided an empty object, the function returns `false`.\n\n    Parameters\n    ----------\n    object: Object\n        Input object over which to iterate. It must be non-null.\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns `true` for\n        any value; otherwise, it returns `false`.\n\n    Examples\n    --------\n    > function isNegative(value) { return value < 0 }\n    > var obj = { a: 1, b: -2, c: 3, d: 4 }\n    > var result = anyInBy(obj, isNegative)\n    true\n\n    See Also\n    --------\n    anyBy, anyOwnBy, everyInBy, someInBy","anyOwnBy":"\nanyOwnBy( object, predicate[, thisArg ] )\n    Tests whether at least one own property of an object passes a\n    test implemented by a predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: property value.\n    - index: property key.\n    - object: the input object.\n\n    The function immediately returns upon encountering a truthy return\n    value.\n\n    If provided an empty object, the function returns `false`.\n\n    Parameters\n    ----------\n    object: Object\n        Input object.\n\n    predicate: Function\n        Test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns a truthy\n        value for one own property; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function positive( v ) { return ( v > 0 ); };\n    > var obj = { 'a': -1, 'b': 2, 'c': -3 };\n    > var bool = anyOwnBy( obj, positive )\n    true\n\n    See Also\n    --------\n    anyBy, anyInBy, everyOwnBy, someOwnBy\n","aones":"\naones( length[, dtype] )\n    Returns an array filled with ones and having a specified length.\n\n    The function supports the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754).\n    - float32: single-precision floating-point numbers (IEEE 754).\n    - complex128: double-precision complex floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n    - generic: generic JavaScript values.\n\n    The default array data type is `float64`.\n\n    Parameters\n    ----------\n    length: integer\n        Array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = aones( 2 )\n    <Float64Array>[ 1.0, 1.0 ]\n    > arr = aones( 2, 'float32' )\n    <Float32Array>[ 1.0, 1.0 ]\n\n    See Also\n    --------\n    afull, anans, aonesLike, azeros\n","aonesLike":"\naonesLike( x[, dtype] )\n    Returns an array filled with ones and having the same length and data type\n    as a provided input array.\n\n    The function supports the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754).\n    - float32: single-precision floating-point numbers (IEEE 754).\n    - complex128: double-precision complex floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n    - generic: generic JavaScript values.\n\n    Parameters\n    ----------\n    x: TypedArray|Array\n        Input array.\n\n    dtype: string (optional)\n        Data type. If not provided, the output array data type is inferred from\n        the input array.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var x = new Float64Array( 2 );\n    > var y = aonesLike( x )\n    <Float64Array>[ 1.0, 1.0 ]\n    > y = aonesLike( x, 'float32' )\n    <Float32Array>[ 1.0, 1.0 ]\n\n    See Also\n    --------\n    afullLike, anansLike, aones, azerosLike\n","aoneTo":"\naoneTo( n[, dtype] )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from one.\n\n    The function supports the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754).\n    - float32: single-precision floating-point numbers (IEEE 754).\n    - complex128: double-precision complex floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n    - generic: generic JavaScript values.\n\n    The default array data type is `float64`.\n\n    If `n` is equal to zero, the function returns an empty array.\n\n    Parameters\n    ----------\n    n: integer\n        Number of elements.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = aoneTo( 2 )\n    <Float64Array>[ 1.0, 2.0 ]\n    > arr = aoneTo( 2, 'float32' )\n    <Float32Array>[ 1.0, 2.0 ]\n\n    See Also\n    --------\n    afull, aones, aoneToLike, azeroTo\n","aoneToLike":"\naoneToLike( x[, dtype] )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from one and having the same length and data type as a provided\n    input array.\n\n    The function supports the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754).\n    - float32: single-precision floating-point numbers (IEEE 754).\n    - complex128: double-precision complex floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n    - generic: generic JavaScript values.\n\n    Parameters\n    ----------\n    x: TypedArray|Array\n        Input array.\n\n    dtype: string (optional)\n        Data type. If not provided, the output array data type is inferred from\n        the input array.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = aoneToLike( [ 0, 0 ] )\n    [ 1, 2 ]\n    > arr = aoneToLike( [ 0, 0 ], 'float32' )\n    <Float32Array>[ 1.0, 2.0 ]\n\n    See Also\n    --------\n    afullLike, aonesLike, aoneTo, azeroToLike\n","APERY":"\nAPERY\n    Apéry's constant.\n\n    Examples\n    --------\n    > APERY\n    1.2020569031595942\n\n","aplace":"\naplace( x, mask, values[, options] )\n    Replaces elements of an array with provided values according to a provided\n    mask array.\n\n    In broadcasting modes, the function supports broadcasting a values array\n    containing a single element against the number of truthy values in the mask\n    array.\n\n    In repeat mode, the function supports recycling elements in a values array\n    to satisfy the number of truthy values in the mask array.\n\n    The function mutates the input array.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    mask: ArrayLikeObject\n        Mask array. If a mask array element is truthy, the corresponding element\n        in `x` is *replaced*; otherwise, the corresponding element in `x` is\n        \"masked\" and thus left unchanged.\n\n    values: ArrayLikeObject\n        Values to set.\n\n    options: Object (optional)\n        Function options.\n\n    options.mode: string (optional)\n        String specifying behavior when the number of values to set does not\n        equal the number of truthy mask values. The function supports the\n        following modes:\n\n        - 'strict': specifies that the function must raise an exception when the\n        number of values does not *exactly* equal the number of truthy mask\n        values.\n        - 'non_strict': specifies that the function must raise an exception when\n        the function is provided insufficient values to satisfy the mask array.\n        - 'strict_broadcast': specifies that the function must broadcast a\n        single-element values array and otherwise raise an exception when the\n        number of values does not **exactly** equal the number of truthy mask\n        values.\n        - 'broadcast': specifies that the function must broadcast a single-\n        element values array and otherwise raise an exception when the function\n        is provided insufficient values to satisfy the mask array.\n        - 'repeat': specifies that the function must reuse provided values when\n        replacing elements in `x` in order to satisfy the mask array.\n\n        Default: 'repeat'.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Input array.\n\n    Examples\n    --------\n    > var x = [ 1, 2, 3, 4 ];\n    > var out = aplace( x, [ 0, 1, 0, 1 ], [ 20, 40 ] )\n    [ 1, 20, 3, 40 ]\n    > var bool = ( out === x )\n    true\n\n    See Also\n    --------\n    amskput, aput, atake\n","append":"\nappend( collection1, collection2 )\n    Adds the elements of one collection to the end of another collection.\n\n    If the input collection is a typed array, the output value does not equal\n    the input reference and the underlying `ArrayBuffer` may *not* be the same\n    as the `ArrayBuffer` belonging to the input view.\n\n    For purposes of generality, always treat the output collection as distinct\n    from the input collection.\n\n    Parameters\n    ----------\n    collection1: Array|TypedArray|Object\n        A collection. If the collection is an `Object`, the collection should be\n        array-like.\n\n    collection2: Array|TypedArray|Object\n        A collection containing the elements to add. If the collection is an\n        `Object`, the collection should be array-like.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Updated collection.\n\n    Examples\n    --------\n    // Arrays:\n    > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > arr = append( arr, [ 6.0, 7.0 ] )\n    [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]\n\n    // Typed arrays:\n    > arr = new Float64Array( [ 1.0, 2.0 ] );\n    > arr = append( arr, [ 3.0, 4.0 ] )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Array-like object:\n    > arr = { 'length': 0 };\n    > arr = append( arr, [ 1.0, 2.0 ] )\n    { 'length': 2, '0': 1.0, '1': 2.0 }\n\n    See Also\n    --------\n    prepend, push\n","aput":"\naput( x, indices, values[, options] )\n    Replaces specified elements of an array with provided values.\n\n    The function supports broadcasting a `values` array containing a single\n    element against an `indices` array containing one or more elements.\n\n    The function mutates the input array.\n\n    Because each index is only validated at the time of replacing a particular\n    element, mutation may occur even when one or more indices are out-of-bounds,\n    including when the index mode indicates to raise an exception.\n\n    If `indices` is an empty array, the function returns the input array\n    unchanged.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    indices: ArrayLikeObject<integer>\n        List of element indices.\n\n    values: ArrayLikeObject\n        Values to set. When `indices` contains one or more elements, `values`\n        must be broadcast compatible with `indices` (i.e., must have either one\n        element or the same number of elements as `indices`).\n\n    options: Object (optional)\n        Function options.\n\n    options.mode: string (optional)\n        Specifies how to handle an index outside the interval [0, max], where\n        `max` is the maximum possible array index. If equal to 'throw', the\n        function throws an error. If equal to 'normalize', the function throws\n        an error if provided an out-of-bounds normalized index. If equal to\n        'wrap', the function wraps around an index using modulo arithmetic. If\n        equal to 'clamp', the function sets an index to either 0 (minimum index)\n        or the maximum index. Default: 'normalize'.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Input array.\n\n    Examples\n    --------\n    > var x = [ 1, 2, 3, 4 ];\n    > var out = aput( x, [ 1, 3 ], [ 20, 40 ] )\n    [ 1, 20, 3, 40 ]\n    > var bool = ( out === x )\n    true\n\n    See Also\n    --------\n    amskput, aplace, atake\n","ARCH":"\nARCH\n    Operating system CPU architecture for which the JavaScript runtime binary\n    was compiled.\n\n    Current possible values:\n\n    - arm\n    - arm64\n    - ia32\n    - mips\n    - mipsel\n    - ppc\n    - ppc64\n    - s390\n    - s390x\n    - x32\n    - x64\n\n    Examples\n    --------\n    > ARCH\n    <string>\n\n    See Also\n    --------\n    PLATFORM\n","argumentFunction":"\nargumentFunction( idx )\n    Returns a function which always returns a specified argument.\n\n    The input argument corresponds to the zero-based index of the argument to\n    return.\n\n    Parameters\n    ----------\n    idx: integer\n        Argument index to return (zero-based).\n\n    Returns\n    -------\n    out: Function\n        Argument function.\n\n    Examples\n    --------\n    > var argn = argumentFunction( 1 );\n    > var v = argn( 3.14, -3.14, 0.0 )\n    -3.14\n    > v = argn( -1.0, -0.0, 1.0 )\n    -0.0\n    > v = argn( 'beep', 'boop', 'bop' )\n    'boop'\n    > v = argn( 'beep' )\n    undefined\n\n    See Also\n    --------\n    constantFunction, identity\n","ARGV":"\nARGV\n    An array containing command-line arguments passed when launching the calling\n    process.\n\n    The first element is the absolute pathname of the executable that started\n    the calling process.\n\n    The second element is the path of the executed file.\n\n    Any additional elements are additional command-line arguments.\n\n    In browser environments, the array is empty.\n\n    Examples\n    --------\n    > var execPath = ARGV[ 0 ]\n    e.g., /usr/local/bin/node\n\n    See Also\n    --------\n    ENV\n","array":"\narray( [buffer,] [options] )\n    Returns a multidimensional array.\n\n    Parameters\n    ----------\n    buffer: Array|TypedArray|Buffer|ndarray (optional)\n        Data source.\n\n    options: Object (optional)\n        Options.\n\n    options.buffer: Array|TypedArray|Buffer|ndarray (optional)\n        Data source. If provided along with a `buffer` argument, the argument\n        takes precedence.\n\n    options.dtype: string (optional)\n        Underlying storage data type. If not specified and a data source is\n        provided, the data type is inferred from the provided data source. If an\n        input data source is not of the same type, this option specifies the\n        data type to which to cast the input data. For non-ndarray generic array\n        data sources, the function casts generic array data elements to the\n        default data type. In order to prevent this cast, the `dtype` option\n        must be explicitly set to `'generic'`. Any time a cast is required, the\n        `copy` option is set to `true`, as memory must be copied from the data\n        source to an output data buffer. Default: 'float64'.\n\n    options.order: string (optional)\n        Specifies the memory layout of the data source as either row-major (C-\n        style) or column-major (Fortran-style). The option may be one of the\n        following values:\n\n        - 'row-major': the order of the returned array is row-major.\n        - 'column-major': the order of the returned array is column-major.\n        - 'any': if a data source is column-major and not row-major, the order\n          of the returned array is column-major; otherwise, the order of the\n          returned array is row-major.\n        - 'same': the order of the returned array matches the order of an input\n          data source.\n\n        Note that specifying an order which differs from the order of a\n        provided data source does *not* entail a conversion from one memory\n        layout to another. In short, this option is descriptive, not\n        prescriptive. Default: 'row-major'.\n\n    options.shape: Array<integer> (optional)\n        Array shape (dimensions). If a shape is not specified, the function\n        attempts to infer a shape based on a provided data source. For example,\n        if provided a nested array, the function resolves nested array\n        dimensions. If provided a multidimensional array data source, the\n        function uses the array's associated shape. For most use cases, such\n        inference suffices. For the remaining use cases, specifying a shape is\n        necessary. For example, provide a shape to create a multidimensional\n        array view over a linear data buffer, ignoring any existing shape meta\n        data associated with a provided data source.\n\n    options.flatten: boolean (optional)\n        Boolean indicating whether to automatically flatten generic array data\n        sources. If an array shape is not specified, the shape is inferred from\n        the dimensions of nested arrays prior to flattening. If a use case\n        requires partial flattening, partially flatten prior to invoking this\n        function and set the option value to `false` to prevent further\n        flattening during invocation. Default: true.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to (shallow) copy source data to a new data\n        buffer. The function does *not* perform a deep copy. To prevent\n        undesired shared changes in state for generic arrays containing objects,\n        perform a deep copy prior to invoking this function. Default: false.\n\n    options.ndmin: integer (optional)\n        Specifies the minimum number of dimensions. If an array shape has fewer\n        dimensions than required by `ndmin`, the function prepends singleton\n        dimensions to the array shape in order to satisfy the dimensions\n        requirement. Default: 0.\n\n    options.casting: string (optional)\n        Specifies the casting rule used to determine acceptable casts. The\n        option may be one of the following values:\n\n        - 'none': only allow casting between identical types.\n        - 'equiv': allow casting between identical and byte swapped types.\n        - 'safe': only allow \"safe\" casts.\n        - 'mostly-safe': allow \"safe casts\" and, for floating-point data types,\n          downcasts.\n        - 'same-kind': allow \"safe\" casts and casts within the same kind (e.g.,\n          between signed integers or between floats).\n        - 'unsafe': allow casting between all types (including between integers\n          and floats).\n\n        Default: 'safe'.\n\n    options.codegen: boolean (optional)\n        Boolean indicating whether to use code generation. Code generation can\n        boost performance, but may be problematic in browser contexts enforcing\n        a strict content security policy (CSP). Default: true.\n\n    options.mode: string (optional)\n        Specifies how to handle indices which exceed array dimensions. The\n        option may be one of the following values:\n\n        - 'throw': an ndarray instance throws an error when an index exceeds\n          array dimensions.\n        - 'normalize': an ndarray instance normalizes negative indices and\n          throws an error when an index exceeds array dimensions.\n        - 'wrap': an ndarray instance wraps around indices exceeding array\n          dimensions using modulo arithmetic.\n        - 'clamp', an ndarray instance sets an index exceeding array dimensions\n          to either `0` (minimum index) or the maximum index.\n\n        Default: 'throw'.\n\n    options.submode: Array<string> (optional)\n        Specifies how to handle subscripts which exceed array dimensions. If a\n        mode for a corresponding dimension is equal to\n\n        - 'throw': an ndarray instance throws an error when a subscript exceeds\n          array dimensions.\n        - 'normalize': an ndarray instance normalizes negative subscripts and\n          throws an error when a subscript exceeds array dimensions.\n        - 'wrap': an ndarray instance wraps around subscripts exceeding array\n          dimensions using modulo arithmetic.\n        - 'clamp': an ndarray instance sets a subscript exceeding array\n          dimensions to either `0` (minimum index) or the maximum index.\n\n        If the number of modes is fewer than the number of dimensions, the\n        function recycles modes using modulo arithmetic.\n\n        Default: [ options.mode ].\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether an array should be read-only. Default: false.\n\n    Returns\n    -------\n    out: ndarray\n        Multidimensional array.\n\n    Examples\n    --------\n    // Create a 2x2 matrix:\n    > var arr = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] )\n    <ndarray>\n\n    // Get an element using subscripts:\n    > var v = arr.get( 1, 1 )\n    4.0\n\n    // Get an element using a linear index:\n    > v = arr.iget( 3 )\n    4.0\n\n    // Set an element using subscripts:\n    > arr.set( 1, 1, 40.0 );\n    > arr.get( 1, 1 )\n    40.0\n\n    // Set an element using a linear index:\n    > arr.iset( 3, 99.0 );\n    > arr.get( 1, 1 )\n    99.0\n\n    See Also\n    --------\n    ndarray\n","array2buffer":"\narray2buffer( arr )\n    Allocates a buffer using an octet array.\n\n    Parameters\n    ----------\n    arr: Array<integer>\n        Array (or array-like object) of octets from which to copy.\n\n    Returns\n    -------\n    out: Buffer\n        Buffer instance.\n\n    Examples\n    --------\n    > var buf = array2buffer( [ 1, 2, 3, 4 ] )\n    <Buffer>[ 1, 2, 3, 4 ]\n\n    See Also\n    --------\n    Buffer, arraybuffer2buffer, copyBuffer, string2buffer\n","array2fancy":"\narray2fancy( x[, options] )\n    Converts an array to an object supporting fancy indexing.\n\n    An array supporting fancy indexing is an array which supports slicing via\n    indexing expressions for both retrieval and assignment.\n\n    A fancy array shares the *same* data as the provided input array. Hence, any\n    mutations to the returned array will affect the underlying input array and\n    vice versa.\n\n    For operations returning a new array (e.g., when slicing or invoking an\n    instance method), a fancy array returns a new fancy array having the same\n    configuration as specified by provided options.\n\n    A fancy array supports indexing using positive and negative integers (both\n    numeric literals and strings), Slice instances, subsequence expressions,\n    mask arrays, boolean arrays, and integer arrays.\n\n    A fancy array supports all properties and methods of the input array, and,\n    thus, a fancy array can be consumed by any API which supports array-like\n    objects.\n\n    Indexing expressions provide a convenient and powerful means for creating\n    and operating on array views; however, their use does entail a performance\n    cost. Indexing expressions are best suited for interactive use (e.g., in the\n    REPL) and scripting. For performance critical applications, prefer\n    equivalent functional APIs supporting array-like objects.\n\n    Fancy arrays support broadcasting in which assigned scalars and single-\n    element arrays are repeated (without additional memory allocation) to match\n    the length of a target array instance.\n\n    Fancy array broadcasting follows the same rules as for ndarrays.\n\n    Consequently, when assigning arrays to slices, the array on the right-hand-\n    side must be broadcast-compatible with number of elements in the slice.\n\n    Fancy arrays support (mostly) safe casts (i.e., any cast which can be\n    performed without overflow or loss of precision, with the exception of\n    floating-point arrays which are also allowed to downcast from higher\n    precision to lower precision).\n\n    When attempting to perform an unsafe cast, fancy arrays will raise an\n    exception.\n\n    When assigning a real-valued scalar to a complex number array (e.g.,\n    Complex128Array or Complex64Array), a fancy array will cast the real-valued\n    scalar to a complex number argument having an imaginary component equal to\n    zero.\n\n    In older JavaScript environments which do not support Proxy objects, the use\n    of indexing expressions is not supported.\n\n    Parameters\n    ----------\n    x: Array|TypedArray|Object\n        Input array.\n\n    options: Object (optional)\n        Function options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking. Default:\n        false.\n\n    options.cache: Object (optional)\n        Cache for resolving array index objects. Must have a 'get' method which\n        accepts a single argument: a string identifier associated with an array\n        index. If an array index associated with a provided identifier exists,\n        the 'get' method should return an object having the following\n        properties:\n\n        - data: the underlying index array.\n        - type: the index type. Must be either 'mask', 'bool', or 'int'.\n        - dtype: the data type of the underlying array.\n\n        If an array index is not associated with a provided identifier, the\n        'get' method should return `null`.\n\n        Default: `ArrayIndex`.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Output array supporting fancy indexing.\n\n    Examples\n    --------\n    > var y = array2fancy( [ 1, 2, 3, 4 ] );\n    > y[ '1::2' ]\n    [ 2, 4 ]\n    > y[ '::-1' ]\n    [ 4, 3, 2, 1 ]\n\n\narray2fancy.factory( [options] )\n    Returns a function for converting an array to an object supporting fancy\n    indexing.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking by default.\n        Default: false.\n\n    options.cache: Object (optional)\n        Cache for resolving array index objects. Must have a 'get' method which\n        accepts a single argument: a string identifier associated with an array\n        index. If an array index associated with a provided identifier exists,\n        the 'get' method should return an object having the following\n        properties:\n\n        - data: the underlying index array.\n        - type: the index type. Must be either 'mask', 'bool', or 'int'.\n        - dtype: the data type of the underlying array.\n\n        If an array index is not associated with a provided identifier, the\n        'get' method should return `null`.\n\n        Default: `ArrayIndex`.\n\n    Returns\n    -------\n    fcn: Function\n        Function for converting an array to an object supporting fancy indexing.\n\n    Examples\n    --------\n    > var f = array2fancy.factory();\n    > var y = f( [ 1, 2, 3, 4 ] );\n    > y[ '1::2' ]\n    [ 2, 4 ]\n    > y[ '::-1' ]\n    [ 4, 3, 2, 1 ]\n\n\narray2fancy.idx( x[, options] )\n    Wraps a provided array as an array index object.\n\n    For documentation and usage, see `ArrayIndex`.\n\n    Parameters\n    ----------\n    x: Array|TypedArray|Object\n        Input array.\n\n    options: Object (optional)\n        Function options.\n\n    options.persist: boolean (optional)\n        Boolean indicating whether to continue persisting an index object after\n        first usage. Default: false.\n\n    Returns\n    -------\n    out: ArrayIndex\n        ArrayIndex instance.\n\n    Examples\n    --------\n    > var idx = array2fancy.idx( [ 1, 2, 3, 4 ] );\n\n    See Also\n    --------\n    aslice, FancyArray\n","array2fancy.factory":"\narray2fancy.factory( [options] )\n    Returns a function for converting an array to an object supporting fancy\n    indexing.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking by default.\n        Default: false.\n\n    options.cache: Object (optional)\n        Cache for resolving array index objects. Must have a 'get' method which\n        accepts a single argument: a string identifier associated with an array\n        index. If an array index associated with a provided identifier exists,\n        the 'get' method should return an object having the following\n        properties:\n\n        - data: the underlying index array.\n        - type: the index type. Must be either 'mask', 'bool', or 'int'.\n        - dtype: the data type of the underlying array.\n\n        If an array index is not associated with a provided identifier, the\n        'get' method should return `null`.\n\n        Default: `ArrayIndex`.\n\n    Returns\n    -------\n    fcn: Function\n        Function for converting an array to an object supporting fancy indexing.\n\n    Examples\n    --------\n    > var f = array2fancy.factory();\n    > var y = f( [ 1, 2, 3, 4 ] );\n    > y[ '1::2' ]\n    [ 2, 4 ]\n    > y[ '::-1' ]\n    [ 4, 3, 2, 1 ]","array2fancy.idx":"\narray2fancy.idx( x[, options] )\n    Wraps a provided array as an array index object.\n\n    For documentation and usage, see `ArrayIndex`.\n\n    Parameters\n    ----------\n    x: Array|TypedArray|Object\n        Input array.\n\n    options: Object (optional)\n        Function options.\n\n    options.persist: boolean (optional)\n        Boolean indicating whether to continue persisting an index object after\n        first usage. Default: false.\n\n    Returns\n    -------\n    out: ArrayIndex\n        ArrayIndex instance.\n\n    Examples\n    --------\n    > var idx = array2fancy.idx( [ 1, 2, 3, 4 ] );\n\n    See Also\n    --------\n    aslice, FancyArray","array2iterator":"\narray2iterator( src[, mapFcn[, thisArg]] )\n    Returns an iterator which iterates over the elements of an array-like\n    object.\n\n    When invoked, an input function is provided three arguments:\n\n    - value: iterated value.\n    - index: iterated value index.\n    - src: source array-like object.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an array's `@@iterator` method, regardless of whether this method is\n    defined. To convert an array to an implementation defined iterator, invoke\n    this method directly.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Array-like object from which to create the iterator.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = array2iterator( [ 1, 2, 3, 4 ] );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    iterator2array, circarray2iterator, array2iteratorRight, stridedarray2iterator\n","array2iteratorRight":"\narray2iteratorRight( src[, mapFcn[, thisArg]] )\n    Returns an iterator which iterates from right to left over the elements of\n    an array-like object.\n\n    When invoked, an input function is provided three arguments:\n\n    - value: iterated value.\n    - index: iterated value index.\n    - src: source array-like object.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an array's `@@iterator` method, regardless of whether this method is\n    defined. To convert an array to an implementation defined iterator, invoke\n    this method directly.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Array-like object from which to create the iterator.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = array2iteratorRight( [ 1, 2, 3, 4 ] );\n    > var v = it.next().value\n    4\n    > v = it.next().value\n    3\n\n    See Also\n    --------\n    iterator2array, array2iterator\n","ArrayBuffer":"\nArrayBuffer( size )\n    Returns an array buffer having a specified number of bytes.\n\n    Buffer contents are initialized to 0.\n\n    Parameters\n    ----------\n    size: integer\n        Number of bytes.\n\n    Returns\n    -------\n    out: ArrayBuffer\n        An array buffer.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 5 )\n    <ArrayBuffer>\n\n\nArrayBuffer.length\n    Number of input arguments the constructor accepts.\n\n    Examples\n    --------\n    > ArrayBuffer.length\n    1\n\n\nArrayBuffer.isView( arr )\n    Returns a boolean indicating if provided an array buffer view.\n\n    Parameters\n    ----------\n    arr: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an input argument is a buffer view.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 10 );\n    > ArrayBuffer.isView( arr )\n    true\n\n\nArrayBuffer.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the array buffer.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 5 );\n    > buf.byteLength\n    5\n\n\nArrayBuffer.prototype.slice( [start[, end]] )\n    Copies the bytes of an array buffer to a new array buffer.\n\n    Parameters\n    ----------\n    start: integer (optional)\n        Index at which to start copying buffer contents (inclusive). If\n        negative, the index is relative to the end of the buffer.\n\n    end: integer (optional)\n        Index at which to stop copying buffer contents (exclusive). If negative,\n        the index is relative to the end of the buffer.\n\n    Returns\n    -------\n    out: ArrayBuffer\n        A new array buffer whose contents have been copied from the calling\n        array buffer.\n\n    Examples\n    --------\n    > var b1 = new ArrayBuffer( 10 );\n    > var b2 = b1.slice( 2, 6 );\n    > var bool = ( b1 === b2 )\n    false\n    > b2.byteLength\n    4\n\n    See Also\n    --------\n    Buffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, SharedArrayBuffer, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","ArrayBuffer.length":"\nArrayBuffer.length\n    Number of input arguments the constructor accepts.\n\n    Examples\n    --------\n    > ArrayBuffer.length\n    1","ArrayBuffer.isView":"\nArrayBuffer.isView( arr )\n    Returns a boolean indicating if provided an array buffer view.\n\n    Parameters\n    ----------\n    arr: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an input argument is a buffer view.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 10 );\n    > ArrayBuffer.isView( arr )\n    true","ArrayBuffer.prototype.byteLength":"\nArrayBuffer.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the array buffer.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 5 );\n    > buf.byteLength\n    5","ArrayBuffer.prototype.slice":"\nArrayBuffer.prototype.slice( [start[, end]] )\n    Copies the bytes of an array buffer to a new array buffer.\n\n    Parameters\n    ----------\n    start: integer (optional)\n        Index at which to start copying buffer contents (inclusive). If\n        negative, the index is relative to the end of the buffer.\n\n    end: integer (optional)\n        Index at which to stop copying buffer contents (exclusive). If negative,\n        the index is relative to the end of the buffer.\n\n    Returns\n    -------\n    out: ArrayBuffer\n        A new array buffer whose contents have been copied from the calling\n        array buffer.\n\n    Examples\n    --------\n    > var b1 = new ArrayBuffer( 10 );\n    > var b2 = b1.slice( 2, 6 );\n    > var bool = ( b1 === b2 )\n    false\n    > b2.byteLength\n    4\n\n    See Also\n    --------\n    Buffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, SharedArrayBuffer, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","arraybuffer2buffer":"\narraybuffer2buffer( buf[, byteOffset[, length]] )\n    Allocates a buffer from an ArrayBuffer.\n\n    The behavior of this function varies across Node.js versions due to changes\n    in the underlying Node.js APIs:\n\n    - <3.0.0: the function copies ArrayBuffer bytes to a new Buffer instance.\n    - >=3.0.0 and <5.10.0: if provided a byte offset, the function copies\n      ArrayBuffer bytes to a new Buffer instance; otherwise, the function\n      returns a view of an ArrayBuffer without copying the underlying memory.\n    - <6.0.0: if provided an empty ArrayBuffer, the function returns an empty\n      Buffer which is not an ArrayBuffer view.\n    - >=6.0.0: the function returns a view of an ArrayBuffer without copying\n      the underlying memory.\n\n    Parameters\n    ----------\n    buf: ArrayBuffer\n        Input array buffer.\n\n    byteOffset: integer (optional)\n        Index offset specifying the location of the first byte.\n\n    length: integer (optional)\n        Number of bytes to expose from the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Buffer\n        Buffer instance.\n\n    Examples\n    --------\n    > var ab = new ArrayBuffer( 10 )\n    <ArrayBuffer>\n    > var buf = arraybuffer2buffer( ab )\n    <Buffer>\n    > var len = buf.length\n    10\n    > buf = arraybuffer2buffer( ab, 2, 6 )\n    <Buffer>\n    > len = buf.length\n    6\n\n    See Also\n    --------\n    Buffer, array2buffer, copyBuffer, string2buffer\n","arrayCtors":"\narrayCtors( dtype )\n    Returns an array constructor.\n\n    The function returns constructors for the following data types:\n\n    - float32: single-precision floating-point numbers.\n    - float64: double-precision floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - complex128: double-precision complex floating-point numbers.\n    - bool: boolean values.\n    - generic: values of any type.\n    - int16: signed 16-bit integers.\n    - int32: signed 32-bit integers.\n    - int8: signed 8-bit integers.\n    - uint16: unsigned 16-bit integers.\n    - uint32: unsigned 32-bit integers.\n    - uint8: unsigned 8-bit integers.\n    - uint8c: unsigned clamped 8-bit integers.\n\n    Parameters\n    ----------\n    dtype: string\n        Data type.\n\n    Returns\n    -------\n    out: Function|null\n        Constructor.\n\n    Examples\n    --------\n    > var ctor = arrayCtors( 'float64' )\n    <Function>\n    > ctor = arrayCtors( 'float' )\n    null\n\n    See Also\n    --------\n    typedarrayCtors\n","arrayDataType":"\narrayDataType( array )\n    Returns the data type of an array.\n\n    If provided an argument having an unknown or unsupported type, the function\n    returns `null`.\n\n    Parameters\n    ----------\n    array: any\n        Input value.\n\n    Returns\n    -------\n    out: string|null\n        Data type.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 10 );\n    > var dt = arrayDataType( arr )\n    'float64'\n    > dt = arrayDataType( 'beep' )\n    null\n\n    See Also\n    --------\n    arrayDataTypes\n","arrayDataTypes":"\narrayDataTypes( [kind] )\n    Returns a list of array data types.\n\n    When not provided a data type \"kind\", the function returns an array\n    containing the following data types:\n\n    - float32: single-precision floating-point numbers.\n    - float64: double-precision floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - complex128: double-precision complex floating-point numbers.\n    - bool: boolean values.\n    - generic: values of any type.\n    - int16: signed 16-bit integers.\n    - int32: signed 32-bit integers.\n    - int8: signed 8-bit integers.\n    - uint16: unsigned 16-bit integers.\n    - uint32: unsigned 32-bit integers.\n    - uint8: unsigned 8-bit integers.\n    - uint8c: unsigned clamped 8-bit integers.\n\n    The function supports the following data type \"kinds\":\n\n    - floating_point: floating-point data types.\n    - real_floating_point: real-valued floating-point data types.\n    - complex_floating_point: complex-valued floating-point data types.\n    - boolean: boolean data types.\n    - integer: integer data types.\n    - signed_integer: signed integer data types.\n    - unsigned_integer: unsigned integer data types.\n    - real: real-valued data types.\n    - numeric: numeric data types.\n    - typed: \"typed\" data types.\n    - all: all data types.\n\n    Additionally, the function supports extending the \"kinds\" listed above by\n    appending a '_and_generic' suffix to the kind name (e.g., real_and_generic).\n\n    Parameters\n    ----------\n    kind: string (optional)\n        Data type kind.\n\n    Returns\n    -------\n    out: Array<string>\n        List of array data types.\n\n    Examples\n    --------\n    > var out = arrayDataTypes()\n    [...]\n    > out = arrayDataTypes( 'floating_point' )\n    [...]\n    > out = arrayDataTypes( 'floating_point_and_generic' )\n    [...]\n\n    See Also\n    --------\n    typedarrayDataTypes, ndarrayDataTypes\n","ArrayIndex":"\nArrayIndex( x[, options] )\n    Wraps a provided array as an array index object.\n\n    Array index instances have no explicit functionality; however, they are used\n    by \"fancy\" arrays for element retrieval and assignment.\n\n    By default, an instance is invalidated and removed from an internal cache\n    immediately after a consumer resolves the underlying data associated with an\n    instance using the `get` static method. Immediate invalidation and cache\n    removal ensures that references to the underlying array are not the source\n    of memory leaks.\n\n    Because instances leverage an internal cache implementing the Singleton\n    pattern, one must be sure to use the same constructor as consumers. If one\n    uses a different constructor, the consumer will *not* be able to resolve the\n    original wrapped array, as the consumer will attempt to resolve an instance\n    in the wrong internal cache.\n\n    Because non-persisted instances are freed after first use, in order to avoid\n    holding onto memory and to allow garbage collection, one should avoid\n    scenarios in which an instance is never used.\n\n    Parameters\n    ----------\n    x: Array|TypedArray|Object\n        Input array.\n\n    options: Object (optional)\n        Function options.\n\n    options.persist: boolean (optional)\n        Boolean indicating whether to continue persisting an index object after\n        first usage. Default: false.\n\n    Returns\n    -------\n    out: ArrayIndex\n        ArrayIndex instance.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n\n\nArrayIndex.free( id )\n    Frees the instance associated with a provided identifier.\n\n    Parameters\n    ----------\n    id: string\n        Instance identifier.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an instance was successfully freed.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > ArrayIndex.free( idx.id )\n    <boolean>\n\n\nArrayIndex.get( id )\n    Returns the array associated with the instance having a provided identifier.\n\n    Parameters\n    ----------\n    id: string\n        Instance identifier.\n\n    Returns\n    -------\n    out: Object\n        Object containing array data.\n\n    out.data: Array|TypedArray|Object\n        The underlying array associated with the provided identifier.\n\n    out.type: string\n        The type of array index.\n\n    out.dtype: string\n        The data type of the underlying array.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > ArrayIndex.get( idx.id )\n    {...}\n\n\nArrayIndex.prototype.data\n    Read-only property returning the underlying index array.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Array data.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.data\n    [ 1, 2, 3, 4 ]\n\n\nArrayIndex.prototype.dtype\n    Read-only property returning the underlying data type of the index array.\n\n    Returns\n    -------\n    out: string\n        Array data type.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.dtype\n    'generic'\n\n\nArrayIndex.prototype.id\n    Read-only property returning the unique identifier associated with an\n    instance.\n\n    Returns\n    -------\n    out: string\n        String identifier.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.id\n    <string>\n\n\nArrayIndex.prototype.isCached\n    Read-only property returning a boolean indicating whether an array index is\n    actively cached.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an array index is actively cached.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.isCached\n    true\n\n\nArrayIndex.prototype.type\n    Read-only property returning the array index type.\n\n    Returns\n    -------\n    out: string\n        Array index type.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.type\n    <string>\n\n\nArrayIndex.prototype.toString()\n    Serializes an instance as a string.\n\n    Returns\n    -------\n    str: string\n        Serialized string.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.toString()\n    <string>\n\n\nArrayIndex.prototype.toJSON()\n    Serializes an instance as a JSON object.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.toJSON()\n    { 'type': 'ArrayIndex', 'data': [ 1, 2, 3, 4 ] }\n\n    See Also\n    --------\n    array2fancy\n","ArrayIndex.free":"\nArrayIndex.free( id )\n    Frees the instance associated with a provided identifier.\n\n    Parameters\n    ----------\n    id: string\n        Instance identifier.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an instance was successfully freed.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > ArrayIndex.free( idx.id )\n    <boolean>","ArrayIndex.get":"\nArrayIndex.get( id )\n    Returns the array associated with the instance having a provided identifier.\n\n    Parameters\n    ----------\n    id: string\n        Instance identifier.\n\n    Returns\n    -------\n    out: Object\n        Object containing array data.\n\n    out.data: Array|TypedArray|Object\n        The underlying array associated with the provided identifier.\n\n    out.type: string\n        The type of array index.\n\n    out.dtype: string\n        The data type of the underlying array.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > ArrayIndex.get( idx.id )\n    {...}","ArrayIndex.prototype.data":"\nArrayIndex.prototype.data\n    Read-only property returning the underlying index array.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Array data.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.data\n    [ 1, 2, 3, 4 ]","ArrayIndex.prototype.dtype":"\nArrayIndex.prototype.dtype\n    Read-only property returning the underlying data type of the index array.\n\n    Returns\n    -------\n    out: string\n        Array data type.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.dtype\n    'generic'","ArrayIndex.prototype.id":"\nArrayIndex.prototype.id\n    Read-only property returning the unique identifier associated with an\n    instance.\n\n    Returns\n    -------\n    out: string\n        String identifier.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.id\n    <string>","ArrayIndex.prototype.isCached":"\nArrayIndex.prototype.isCached\n    Read-only property returning a boolean indicating whether an array index is\n    actively cached.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an array index is actively cached.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.isCached\n    true","ArrayIndex.prototype.type":"\nArrayIndex.prototype.type\n    Read-only property returning the array index type.\n\n    Returns\n    -------\n    out: string\n        Array index type.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.type\n    <string>","ArrayIndex.prototype.toString":"\nArrayIndex.prototype.toString()\n    Serializes an instance as a string.\n\n    Returns\n    -------\n    str: string\n        Serialized string.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.toString()\n    <string>","ArrayIndex.prototype.toJSON":"\nArrayIndex.prototype.toJSON()\n    Serializes an instance as a JSON object.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var idx = new ArrayIndex( [ 1, 2, 3, 4 ] );\n    > idx.toJSON()\n    { 'type': 'ArrayIndex', 'data': [ 1, 2, 3, 4 ] }\n\n    See Also\n    --------\n    array2fancy","arrayMinDataType":"\narrayMinDataType( value )\n    Returns the minimum array data type of the closest \"kind\" necessary for\n    storing a provided scalar value.\n\n    The function does *not* provide precision guarantees for non-integer-valued\n    numbers. In other words, the function returns the smallest possible\n    floating-point (i.e., inexact) data type for storing numbers having\n    decimals.\n\n    Parameters\n    ----------\n    value: any\n        Scalar value.\n\n    Returns\n    -------\n    dt: string\n        Array data type.\n\n    Examples\n    --------\n    > var dt = arrayMinDataType( 3.141592653589793 )\n    'float32'\n    > dt = arrayMinDataType( 3 )\n    'uint8'\n    > dt = arrayMinDataType( -3 )\n    'int8'\n    > dt = arrayMinDataType( '-3' )\n    'generic'\n\n    See Also\n    --------\n    arrayDataTypes, arrayPromotionRules, arraySafeCasts\n","arrayMostlySafeCasts":"\narrayMostlySafeCasts( [dtype] )\n    Returns a list of array data types to which a provided array data type can\n    be safely cast and, for floating-point data types, can be downcast.\n\n    If not provided an array data type, the function returns a casting table.\n\n    If provided an unrecognized array data type, the function returns `null`.\n\n    Parameters\n    ----------\n    dtype: any (optional)\n        Array data type value.\n\n    Returns\n    -------\n    out: Object|Array<string>|null\n        Array data types to which a data type can be cast.\n\n    Examples\n    --------\n    > var out = arrayMostlySafeCasts( 'float32' )\n    <Array>\n\n    See Also\n    --------\n    convertArray, convertArraySame, arrayDataTypes, arraySafeCasts, arraySameKindCasts, ndarrayMostlySafeCasts\n","arrayNextDataType":"\narrayNextDataType( [dtype] )\n    Returns the next larger array data type of the same kind.\n\n    If not provided a data type, the function returns a table.\n\n    If a data type does not have a next larger data type or the next larger type\n    is not supported, the function returns `-1`.\n\n    If provided an unrecognized data type, the function returns `null`.\n\n    Parameters\n    ----------\n    dtype: string (optional)\n        Array data type.\n\n    Returns\n    -------\n    out: Object|string|integer|null\n        Next larger type(s).\n\n    Examples\n    --------\n    > var out = arrayNextDataType( 'float32' )\n    'float64'\n\n    See Also\n    --------\n    arrayDataType, arrayDataTypes\n","arrayPromotionRules":"\narrayPromotionRules( [dtype1, dtype2] )\n    Returns the array data type with the smallest size and closest \"kind\" to\n    which array data types can be safely cast.\n\n    If not provided data types, the function returns a type promotion table.\n\n    If a data type to which data types can be safely cast does *not* exist (or\n    is not supported), the function returns `-1`.\n\n    If provided an unrecognized data type, the function returns `null`.\n\n    Parameters\n    ----------\n    dtype1: any (optional)\n        Array data type.\n\n    dtype2: any (optional)\n        Array data type.\n\n    Returns\n    -------\n    out: Object|string|integer|null\n        Promotion rule(s).\n\n    Examples\n    --------\n    > var out = arrayPromotionRules( 'float32', 'int32' )\n    'float64'\n\n    See Also\n    --------\n    arrayDataTypes, arraySafeCasts, ndarrayPromotionRules\n","arraySafeCasts":"\narraySafeCasts( [dtype] )\n    Returns a list of array data types to which a provided array data type can\n    be safely cast.\n\n    If not provided an array data type, the function returns a casting table.\n\n    If provided an unrecognized array data type, the function returns `null`.\n\n    Parameters\n    ----------\n    dtype: any (optional)\n        Array data type.\n\n    Returns\n    -------\n    out: Object|Array<string>|null\n        Array data types to which a data type can be safely cast.\n\n    Examples\n    --------\n    > var out = arraySafeCasts( 'float32' )\n    <Array>\n\n    See Also\n    --------\n    convertArray, convertArraySame, arrayDataTypes, arrayMostlySafeCasts, arraySameKindCasts, ndarraySafeCasts\n","arraySameKindCasts":"\narraySameKindCasts( [dtype] )\n    Returns a list of array data types to which a provided array data type can\n    be safely cast or cast within the same \"kind\".\n\n    If not provided an array data type, the function returns a casting table.\n\n    If provided an unrecognized array data type, the function returns `null`.\n\n    Parameters\n    ----------\n    dtype: any (optional)\n        Array data type.\n\n    Returns\n    -------\n    out: Object|Array<string>|null\n        Array data types to which a data type can be safely cast or cast within\n        the same \"kind\".\n\n    Examples\n    --------\n    > var out = arraySameKindCasts( 'float32' )\n    <Array>\n\n    See Also\n    --------\n    convertArray, convertArraySame, arrayDataTypes, arraySafeCasts, ndarraySameKindCasts\n","arrayShape":"\narrayShape( arr )\n    Determines array dimensions.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject\n        Input array.\n\n    Returns\n    -------\n    out: Array\n        Array shape.\n\n    Examples\n    --------\n    > var out = arrayShape( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n    [ 2, 3 ]\n\n    See Also\n    --------\n    ndarray\n","arrayStream":"\narrayStream( src[, options] )\n    Creates a readable stream from an array-like object.\n\n    In object mode, `null` is a reserved value. If an array contains `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or filter `null` values\n    prior to invocation.\n\n    In binary mode, if an array contains `undefined` values, the stream will\n    emit an error. Consider providing a custom serialization function or\n    filtering `undefined` values prior to invocation.\n\n    If a serialization function fails to return a string or Buffer, the stream\n    emits an error.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Source value.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing the stream.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize streamed\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    options.dir: integer (optional)\n        Iteration direction. If set to `-1`, a stream iterates over elements\n        from right-to-left. Default: 1.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var s = arrayStream( [ 1, 2, 3 ] );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\narrayStream.factory( [options] )\n    Returns a function for creating readable streams from array-like objects.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing streaming.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize streamed\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    options.dir: integer (optional)\n        Iteration direction. If set to `-1`, a stream iterates over elements\n        from right-to-left. Default: 1.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = arrayStream.factory( opts );\n\n\narrayStream.objectMode( src[, options] )\n    Returns an \"objectMode\" readable stream from an array-like object.\n\n    In object mode, `null` is a reserved value. If an array contains `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or filter `null` values\n    prior to invocation.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Source value.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before pausing streaming.\n\n    options.dir: integer (optional)\n        Iteration direction. If set to `-1`, a stream iterates over elements\n        from right-to-left. Default: 1.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var s = arrayStream.objectMode( [ 1, 2, 3 ] );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    circularArrayStream, iteratorStream, stridedArrayStream\n","arrayStream.factory":"\narrayStream.factory( [options] )\n    Returns a function for creating readable streams from array-like objects.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing streaming.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize streamed\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    options.dir: integer (optional)\n        Iteration direction. If set to `-1`, a stream iterates over elements\n        from right-to-left. Default: 1.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = arrayStream.factory( opts );","arrayStream.objectMode":"\narrayStream.objectMode( src[, options] )\n    Returns an \"objectMode\" readable stream from an array-like object.\n\n    In object mode, `null` is a reserved value. If an array contains `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or filter `null` values\n    prior to invocation.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Source value.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before pausing streaming.\n\n    options.dir: integer (optional)\n        Iteration direction. If set to `-1`, a stream iterates over elements\n        from right-to-left. Default: 1.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var s = arrayStream.objectMode( [ 1, 2, 3 ] );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    circularArrayStream, iteratorStream, stridedArrayStream","arrayview2iterator":"\narrayview2iterator( src[, begin[, end]][, mapFcn[, thisArg]] )\n    Returns an iterator which iterates over the elements of an array-like object\n    view.\n\n    When invoked, an input function is provided four arguments:\n\n    - value: iterated value.\n    - index: iterated value index.\n    - n: iteration count (zero-based).\n    - src: source array-like object.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an array's `@@iterator` method, regardless of whether this method is\n    defined. To convert an array to an implementation defined iterator, invoke\n    this method directly.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Array-like object from which to create the iterator.\n\n    begin: integer (optional)\n        Starting index (inclusive). When negative, determined relative to the\n        last element. Default: 0.\n\n    end: integer (optional)\n        Ending index (non-inclusive). When negative, determined relative to the\n        last element. Default: src.length.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = arrayview2iterator( [ 1, 2, 3, 4 ], 1, 3 );\n    > var v = it.next().value\n    2\n    > v = it.next().value\n    3\n\n    See Also\n    --------\n    iterator2array, array2iterator, stridedarray2iterator, arrayview2iteratorRight\n","arrayview2iteratorRight":"\narrayview2iteratorRight( src[, begin[, end]][, mapFcn[, thisArg]] )\n    Returns an iterator which iterates from right to left over the elements of\n    an array-like object view.\n\n    When invoked, an input function is provided four arguments:\n\n    - value: iterated value.\n    - index: iterated value index.\n    - n: iteration count (zero-based).\n    - src: source array-like object.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an array's `@@iterator` method, regardless of whether this method is\n    defined. To convert an array to an implementation defined iterator, invoke\n    this method directly.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Array-like object from which to create the iterator.\n\n    begin: integer (optional)\n        Starting index (inclusive). When negative, determined relative to the\n        last element. Default: 0.\n\n    end: integer (optional)\n        Ending index (non-inclusive). When negative, determined relative to the\n        last element. Default: src.length.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = arrayview2iteratorRight( [ 1, 2, 3, 4 ], 1, 3 );\n    > var v = it.next().value\n    3\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    iterator2array, array2iteratorRight, stridedarray2iterator, arrayview2iterator\n","aslice":"\naslice( x[, start[, end]] )\n    Returns a shallow copy of a portion of an array.\n\n    If provided an array-like object having a `slice` method, the function\n    defers execution to that method and assumes that the method has the\n    following signature:\n\n      x.slice( start, end )\n\n    If provided an array-like object without a `slice` method, the function\n    copies input array elements to a new generic array.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    start: integer (optional)\n        Starting index (inclusive). Default: 0.\n\n    end: integer (optional)\n        Ending index (exclusive). Default: x.length.\n\n    Returns\n    -------\n    out: Array|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var out = aslice( [ 1, 2, 3, 4 ] )\n    [ 1, 2, 3, 4 ]\n    > out = aslice( [ 1, 2, 3, 4 ], 1 )\n    [ 2, 3, 4 ]\n    > out = aslice( [ 1, 2, 3, 4 ], 1, 3 )\n    [ 2, 3 ]\n\n    See Also\n    --------\n    atake\n","AsyncIteratorSymbol":"\nAsyncIteratorSymbol\n    Async iterator symbol.\n\n    This symbol specifies the default async iterator for an object.\n\n    The symbol is only supported in ES2018+ environments. For non-supporting\n    environments, the value is `null`.\n\n    Examples\n    --------\n    > var s = AsyncIteratorSymbol\n\n    See Also\n    --------\n    Symbol, IteratorSymbol\n","atake":"\natake( x, indices[, options] )\n    Takes elements from an array.\n\n    If `indices` is an empty array, the function returns an empty array.\n\n    Parameters\n    ----------\n    x: Array|TypedArray|Object\n        Input array.\n\n    indices: ArrayLikeObject<integer>\n        List of element indices.\n\n    options: Object (optional)\n        Function options.\n\n    options.mode: string (optional)\n        Specifies how to handle an index outside the interval [0, max], where\n        `max` is the maximum possible array index. If equal to 'throw', the\n        function throws an error. If equal to 'normalize', the function throws\n        an error if provided an out-of-bounds normalized index. If equal to\n        'wrap', the function wraps around an index using modulo arithmetic. If\n        equal to 'clamp', the function sets an index to either 0 (minimum index)\n        or the maximum index. Default: 'normalize'.\n\n    Returns\n    -------\n    out: Array|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = [ 1, 2, 3, 4 ];\n    > var y = atake( x, [ 1, 3 ] )\n    [ 2, 4 ]\n\n    See Also\n    --------\n    aput, aslice\n","azeros":"\nazeros( length[, dtype] )\n    Returns a zero-filled array having a specified length.\n\n    The function supports the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754).\n    - float32: single-precision floating-point numbers (IEEE 754).\n    - complex128: double-precision complex floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n    - generic: generic JavaScript values.\n\n    The default array data type is `float64`.\n\n    Parameters\n    ----------\n    length: integer\n        Array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = azeros( 2 )\n    <Float64Array>[ 0.0, 0.0 ]\n    > arr = azeros( 2, 'float32' )\n    <Float32Array>[ 0.0, 0.0 ]\n\n    See Also\n    --------\n    aempty, afull, anans, aones, azerosLike, ndzeros\n","azerosLike":"\nazerosLike( x[, dtype] )\n    Returns a zero-filled array having the same length and data type as a\n    provided input array.\n\n    The function supports the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754).\n    - float32: single-precision floating-point numbers (IEEE 754).\n    - complex128: double-precision complex floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n    - generic: generic JavaScript values.\n\n    Parameters\n    ----------\n    x: TypedArray|Array\n        Input array.\n\n    dtype: string (optional)\n        Data type. If not provided, the output array data type is inferred from\n        the input array.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var x = new Float64Array( 2 );\n    > var y = azerosLike( x )\n    <Float64Array>[ 0.0, 0.0 ]\n    > y = azerosLike( x, 'float32' )\n    <Float32Array>[ 0.0, 0.0 ]\n\n    See Also\n    --------\n    aemptyLike, afullLike, anansLike, aonesLike, azeros, ndzerosLike\n","azeroTo":"\nazeroTo( n[, dtype] )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from zero.\n\n    The function supports the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754).\n    - float32: single-precision floating-point numbers (IEEE 754).\n    - complex128: double-precision complex floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n    - generic: generic JavaScript values.\n\n    The default array data type is `float64`.\n\n    If `n` is equal to zero, the function returns an empty array.\n\n    Parameters\n    ----------\n    n: integer\n        Number of elements.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = azeroTo( 2 )\n    <Float64Array>[ 0.0, 1.0 ]\n    > arr = azeroTo( 2, 'float32' )\n    <Float32Array>[ 0.0, 1.0 ]\n\n    See Also\n    --------\n    aempty, afull, aoneTo, azeroToLike, azeros\n","azeroToLike":"\nazeroToLike( x[, dtype] )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from zero and having the same length and data type as a provided\n    input array.\n\n    The function supports the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754).\n    - float32: single-precision floating-point numbers (IEEE 754).\n    - complex128: double-precision complex floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n    - generic: generic JavaScript values.\n\n    Parameters\n    ----------\n    x: TypedArray|Array\n        Input array.\n\n    dtype: string (optional)\n        Data type. If not provided, the output array data type is inferred from\n        the input array.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = azeroToLike( [ 0, 0 ] )\n    [ 0, 1 ]\n    > arr = azeroToLike( [ 0, 0 ], 'float32' )\n    <Float32Array>[ 0.0, 1.0 ]\n\n    See Also\n    --------\n    aemptyLike, afullLike, anansLike, aoneToLike, aonesLike, azeroTo, azerosLike\n","bartlettTest":"\nbartlettTest( ...x[, options] )\n    Computes Bartlett’s test for equal variances.\n\n    Parameters\n    ----------\n    x: ...Array\n        Measured values.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.groups: Array (optional)\n        Array of group indicators.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.method: string\n        Name of test.\n\n    out.df: Object\n        Degrees of freedom.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    // Data from Hollander & Wolfe (1973), p. 116:\n    > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n    > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n    > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n    > var out = bartlettTest( x, y, z )\n\n    > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n    ...     3.8, 2.7, 4.0, 2.4,\n    ...     2.8, 3.4, 3.7, 2.2, 2.0\n    ... ];\n    > var groups = [\n    ...     'a', 'a', 'a', 'a', 'a',\n    ...     'b', 'b', 'b', 'b',\n    ...     'c', 'c', 'c', 'c', 'c'\n    ... ];\n    > out = bartlettTest( arr, { 'groups': groups } )\n\n    See Also\n    --------\n    vartest, leveneTest\n","base.abs":"\nbase.abs( x )\n    Computes the absolute value of a double-precision floating-point number `x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Absolute value.\n\n    Examples\n    --------\n    > var y = base.abs( -1.0 )\n    1.0\n    > y = base.abs( 2.0 )\n    2.0\n    > y = base.abs( 0.0 )\n    0.0\n    > y = base.abs( -0.0 )\n    0.0\n    > y = base.abs( NaN )\n    NaN\n\n    See Also\n    --------\n    base.abs2, base.absf, base.labs\n","base.abs2":"\nbase.abs2( x )\n    Computes the squared absolute value of a double-precision floating-point\n    `x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Squared absolute value.\n\n    Examples\n    --------\n    > var y = base.abs2( -1.0 )\n    1.0\n    > y = base.abs2( 2.0 )\n    4.0\n    > y = base.abs2( 0.0 )\n    0.0\n    > y = base.abs2( -0.0 )\n    0.0\n    > y = base.abs2( NaN )\n    NaN\n\n    See Also\n    --------\n    base.abs, base.abs2f\n","base.abs2f":"\nbase.abs2f( x )\n    Computes the squared absolute value of a single-precision floating-point\n    `x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Squared absolute value.\n\n    Examples\n    --------\n    > var y = base.abs2f( -1.0 )\n    1.0\n    > y = base.abs2f( 2.0 )\n    4.0\n    > y = base.abs2f( 0.0 )\n    0.0\n    > y = base.abs2f( -0.0 )\n    0.0\n    > y = base.abs2f( NaN )\n    NaN\n\n    See Also\n    --------\n    base.abs2, base.absf\n","base.absdiff":"\nbase.absdiff( x, y )\n    Computes the absolute difference.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Absolute difference.\n\n    Examples\n    --------\n    > var d = base.absdiff( 2.0, 5.0 )\n    3.0\n    > d = base.absdiff( -1.0, 3.14 )\n    ~4.14\n    > d = base.absdiff( 10.1, -2.05 )\n    ~12.15\n    > d = base.absdiff( -0.0, 0.0 )\n    +0.0\n    > d = base.absdiff( NaN, 5.0 )\n    NaN\n    > d = base.absdiff( PINF, NINF )\n    Infinity\n    > d = base.absdiff( PINF, PINF )\n    NaN\n\n    See Also\n    --------\n    base.reldiff, base.epsdiff\n","base.absf":"\nbase.absf( x )\n    Computes the absolute value of a single-precision floating-point number `x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Absolute value.\n\n    Examples\n    --------\n    > var y = base.absf( -1.0 )\n    1.0\n    > y = base.absf( 2.0 )\n    2.0\n    > y = base.absf( 0.0 )\n    0.0\n    > y = base.absf( -0.0 )\n    0.0\n    > y = base.absf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.abs, base.abs2f, base.labs\n","base.acartesianPower":"\nbase.acartesianPower( x, n )\n    Returns the Cartesian power.\n\n    If provided an empty array, the function returns an empty array.\n\n    If `n` is less than or equal to zero, the function returns an empty array.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    n: integer\n        Power.\n\n    Returns\n    -------\n    out: Array<Array>\n        Cartesian product.\n\n    Examples\n    --------\n    > var x = [ 1, 2 ];\n    > var out = base.acartesianPower( x, 2 )\n    [ [ 1, 1 ], [ 1, 2 ], [ 2, 1 ], [ 2, 2 ] ]\n\n    See Also\n    --------\n    acartesianPower, base.acartesianProduct, base.acartesianSquare\n","base.acartesianProduct":"\nbase.acartesianProduct( x1, x2 )\n    Returns the Cartesian product.\n\n    If provided one or more empty arrays, the function returns an empty array.\n\n    Parameters\n    ----------\n    x1: ArrayLikeObject\n        First input array.\n\n    x2: ArrayLikeObject\n        Second input array.\n\n    Returns\n    -------\n    out: Array<Array>\n        Cartesian product.\n\n    Examples\n    --------\n    > var x1 = [ 1, 2 ];\n    > var x2 = [ 3, 4 ];\n    > var out = base.acartesianProduct( x1, x2 )\n    [ [ 1, 3 ], [ 1, 4 ], [ 2, 3 ], [ 2, 4 ] ]\n\n    See Also\n    --------\n    acartesianProduct, base.acartesianPower, base.acartesianSquare\n","base.acartesianSquare":"\nbase.acartesianSquare( x )\n    Returns the Cartesian square.\n\n    If provided an empty array, the function returns an empty array.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    Returns\n    -------\n    out: Array<Array>\n        Cartesian product.\n\n    Examples\n    --------\n    > var x = [ 1, 2 ];\n    > var out = base.acartesianSquare( x )\n    [ [ 1, 1 ], [ 1, 2 ], [ 2, 1 ], [ 2, 2 ] ]\n\n    See Also\n    --------\n    acartesianSquare, base.acartesianPower, base.acartesianProduct\n","base.acos":"\nbase.acos( x )\n    Compute the arccosine of a double-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arccosine (in radians).\n\n    Examples\n    --------\n    > var y = base.acos( 1.0 )\n    0.0\n    > y = base.acos( 0.707 )\n    ~0.7855\n    > y = base.acos( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acosh, base.asin, base.atan\n","base.acosd":"\nbase.acosd( x )\n    Computes the arccosine (in degrees) of a double-precision floating-point \n    number.\n\n    If `|x| > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arccosine (in degrees).\n\n    Examples\n    --------\n    > var y = base.acosd( 0.0 )\n    90.0\n    > y = base.acosd( PI/6.0 )\n    ~58.43\n    > y = base.acosd( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acos, base.acosh, base.asind, base.atand\n","base.acosf":"\nbase.acosf( x )\n    Computes the arccosine of a single-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arccosine (in radians).\n\n    Examples\n    --------\n    > var y = base.acosf( 1.0 )\n    0.0\n    > y = base.acosf( 0.707 )\n    ~0.7855\n    > y = base.acosf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acos, base.acosh, base.asinf, base.atanf\n","base.acosh":"\nbase.acosh( x )\n    Computes the hyperbolic arccosine of a double-precision floating-point\n    number.\n\n    If `x < 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Hyperbolic arccosine.\n\n    Examples\n    --------\n    > var y = base.acosh( 1.0 )\n    0.0\n    > y = base.acosh( 2.0 )\n    ~1.317\n    > y = base.acosh( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acos, base.asinh, base.atanh\n","base.acot":"\nbase.acot( x )\n    Computes the inverse cotangent of a double-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Inverse cotangent (in radians).\n\n    Examples\n    --------\n    > var y = base.acot( 2.0 )\n    ~0.4636\n    > y = base.acot( 0.0 )\n    ~1.5708\n    > y = base.acot( 0.5 )\n    ~1.1071\n    > y = base.acot( 1.0 )\n    ~0.7854\n    > y = base.acot( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acoth, base.atan, base.cot\n","base.acotd":"\nbase.acotd( x )\n    Computes the arccotangent (in degrees) of a double-precision floating-point\n    number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arccotangent (in degrees).\n\n    Examples\n    --------\n    > var y = base.acotd( 0.0 )\n    90.0\n    > y = base.acotd( PI/6.0 )\n    ~62.36\n    > y = base.acotd( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acot, base.acoth, base.atand, base.cotd\n","base.acotf":"\nbase.acotf( x )\n    Computes the inverse cotangent of a single-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Inverse cotangent (in radians).\n\n    Examples\n    --------\n    > var y = base.acotf( 2.0 )\n    ~0.4636\n    > y = base.acotf( 0.0 )\n    ~1.5708\n    > y = base.acotf( 0.5 )\n    ~1.1071\n    > y = base.acotf( 1.0 )\n    ~0.7854\n    > y = base.acotf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acot, base.acoth, base.atanf\n","base.acoth":"\nbase.acoth( x )\n    Computes the inverse hyperbolic cotangent of a double-precision floating-\n    point number.\n\n    The domain of the inverse hyperbolic cotangent is the union of the intervals\n    (-inf,-1] and [1,inf).\n\n    If provided a value on the open interval (-1,1), the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Inverse hyperbolic cotangent.\n\n    Examples\n    --------\n    > var y = base.acoth( 2.0 )\n    ~0.5493\n    > y = base.acoth( 0.0 )\n    NaN\n    > y = base.acoth( 0.5 )\n    NaN\n    > y = base.acoth( 1.0 )\n    Infinity\n    > y = base.acoth( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acosh, base.acot, base.asinh, base.atanh\n","base.acovercos":"\nbase.acovercos( x )\n    Computes the inverse coversed cosine.\n\n    The inverse coversed cosine is defined as `asin(1+x)`.\n\n    If `x < -2`, `x > 0`, or `x` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Inverse coversed cosine.\n\n    Examples\n    --------\n    > var y = base.acovercos( -1.5 )\n    ~-0.5236\n    > y = base.acovercos( -0.0 )\n    ~1.5708\n\n    See Also\n    --------\n    base.acoversin, base.avercos, base.covercos, base.vercos\n","base.acoversin":"\nbase.acoversin( x )\n    Computes the inverse coversed sine.\n\n    The inverse coversed sine is defined as `asin(1-x)`.\n\n    If `x < 0`, `x > 2`, or `x` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Inverse coversed sine.\n\n    Examples\n    --------\n    > var y = base.acoversin( 1.5 )\n    ~-0.5236\n    > y = base.acoversin( 0.0 )\n    ~1.5708\n\n    See Also\n    --------\n    base.acovercos, base.aversin, base.coversin, base.versin\n","base.acsc":"\nbase.acsc( x )\n    Computes the arccosecant of a number.\n\n    If `|x| < 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arccosecant (in radians).\n\n    Examples\n    --------\n    > var y = base.acsc( 1.0 )\n    ~1.57\n    > y = base.acsc( PI )\n    ~0.32\n    > y = base.acsc( -PI )\n    ~-0.32\n    > y = base.acsc( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acot, base.acsch, base.asec, base.asin, base.csc\n","base.acscd":"\nbase.acscd( x )\n    Computes the arccosecant of (in degrees) a double-precision floating-point\n    number.\n\n    If `x` does not satisy `x >= 1` or `x <= -1`, the function returns NaN.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arccosecant (in degrees).\n\n    Examples\n    --------\n    > var y = base.acscd( 0.0 )\n    NaN\n    > y = base.acscd( PI/6.0 )\n    NaN\n    > y = base.acscd( 1 )\n    90.0\n    > y = base.acscd( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acsc, base.acsch, base.asecd, base.asind, base.cscd\n","base.acscdf":"\nbase.acscdf( x )\n    Computes the arccosecant (in degrees) of a single-precision floating-point\n    number.\n\n    If `x` does not satisy `x >= 1` or `x <= -1`, the function returns NaN.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arccosecant (in degrees).\n\n    Examples\n    --------\n    > var y = base.acscdf( 0.0 )\n    NaN\n    > y = base.acscdf( 3.1415927410125732 / 6.0 )\n    NaN\n    > y = base.acscdf( 1.0 )\n    90.0\n    > y = base.acscdf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acsc, base.acsch, base.asecdf, base.asindf\n","base.acscf":"\nbase.acscf( x )\n    Computes the arccosecant of a single-precision floating-point number.\n\n    If `|x| < 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arccosecant (in radians).\n\n    Examples\n    --------\n    > var y = base.acscf( 1.0 )\n    ~1.57\n    > y = base.acscf( 3.141592653589793 )\n    ~0.32\n    > y = base.acscf( -3.141592653589793 )\n    ~-0.32\n    > y = base.acscf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acsc, base.acsch, base.asecf, base.asinf\n","base.acsch":"\nbase.acsch( x )\n    Computes the hyperbolic arccosecant of a number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Hyperbolic arccosecant.\n\n    Examples\n    --------\n    > var y = base.acsch( 0.0 )\n    Infinity\n    > y = base.acsch( -1.0 )\n    ~-0.881\n    > y = base.acsch( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acoth, base.acsc, base.asech, base.asinh, base.csc, base.csch\n","base.add":"\nbase.add( x, y )\n    Computes the sum of two double-precision floating-point numbers `x` and `y`.\n\n    Parameters\n    ----------\n    x: number\n        First input value.\n\n    y: number\n        Second input value.\n\n    Returns\n    -------\n    z: number\n        Sum.\n\n    Examples\n    --------\n    > var v = base.add( -1.0, 5.0 )\n    4.0\n    > v = base.add( 2.0, 5.0 )\n    7.0\n    > v = base.add( 0.0, 5.0 )\n    5.0\n    > v = base.add( -0.0, 0.0 )\n    0.0\n    > v = base.add( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.div, base.mul, base.sub\n","base.add3":"\nbase.add3( x, y, z )\n    Computes the sum of three double-precision floating-point numbers.\n\n    Parameters\n    ----------\n    x: number\n        First input value.\n\n    y: number\n        Second input value.\n\n    z: number\n        Third input value.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    > var v = base.add3( -1.0, 5.0, 2.0 )\n    6.0\n    > v = base.add3( 2.0, 5.0, 2.0 )\n    9.0\n    > v = base.add3( 0.0, 5.0, 2.0 )\n    7.0\n    > v = base.add3( -0.0, 0.0, -0.0 )\n    0.0\n    > v = base.add3( NaN, NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.add\n","base.add4":"\nbase.add4( x, y, z, w )\n    Computes the sum of four double-precision floating-point numbers.\n\n    Parameters\n    ----------\n    x: number\n        First input value.\n\n    y: number\n        Second input value.\n\n    z: number\n        Third input value.\n\n    w: number\n        Fourth input value.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    > var v = base.add4( -1.0, 5.0, 2.0, -3.0 )\n    3.0\n    > v = base.add4( 2.0, 5.0, 2.0, -3.0 )\n    6.0\n    > v = base.add4( 0.0, 5.0, 2.0, -3.0 )\n    4.0\n    > v = base.add4( -0.0, 0.0, -0.0, -0.0 )\n    0.0\n    > v = base.add4( NaN, NaN, NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.add\n","base.add5":"\nbase.add5( x, y, z, w, u )\n    Computes the sum of five double-precision floating-point numbers.\n\n    Parameters\n    ----------\n    x: number\n        First input value.\n\n    y: number\n        Second input value.\n\n    z: number\n        Third input value.\n\n    w: number\n        Fourth input value.\n\n    u: number\n        Fifth input value.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    > var v = base.add5( -1.0, 5.0, 2.0, -3.0, 4.0 )\n    7.0\n    > v = base.add5( 2.0, 5.0, 2.0, -3.0, 4.0 )\n    10.0\n    > v = base.add5( 0.0, 5.0, 2.0, -3.0, 4.0 )\n    8.0\n    > v = base.add5( -0.0, 0.0, -0.0, -0.0, -0.0 )\n    0.0\n    > v = base.add5( NaN, NaN, NaN, NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.add\n","base.addf":"\nbase.addf( x, y )\n    Computes the sum of two single-precision floating-point numbers `x` and `y`.\n\n    Parameters\n    ----------\n    x: number\n        First input value.\n\n    y: number\n        Second input value.\n\n    Returns\n    -------\n    z: number\n        Sum.\n\n    Examples\n    --------\n    > var v = base.addf( -1.0, 5.0 )\n    4.0\n    > v = base.addf( 2.0, 5.0 )\n    7.0\n    > v = base.addf( 0.0, 5.0 )\n    5.0\n    > v = base.addf( -0.0, 0.0 )\n    0.0\n    > v = base.addf( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.add, base.divf, base.mulf, base.subf\n","base.afilled":"\nbase.afilled( value, len )\n    Returns a filled \"generic\" array.\n\n    Parameters\n    ----------\n    value: any\n        Fill value.\n\n    len: integer\n        Array length.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.afilled( 0.0, 3 )\n    [ 0.0, 0.0, 0.0 ]\n\n","base.afilled2d":"\nbase.afilled2d( value, shape )\n    Returns a filled two-dimensional nested array.\n\n    Parameters\n    ----------\n    value: any\n        Fill value.\n\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.afilled2d( 0.0, [ 1, 3 ] )\n    [ [ 0.0, 0.0, 0.0 ] ]\n\n","base.afilled2dBy":"\nbase.afilled2dBy( shape, clbk[, thisArg] )\n    Returns a filled two-dimensional nested array according to a provided\n    callback function.\n\n    The callback function is provided one argument:\n\n    - indices: current array element indices.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function clbk() { return 1.0; };\n    > var out = base.afilled2dBy( [ 1, 3 ], clbk )\n    [ [ 1.0, 1.0, 1.0 ] ]\n\n    See Also\n    --------\n    base.afilled2d\n","base.afilled3d":"\nbase.afilled3d( value, shape )\n    Returns a filled three-dimensional nested array.\n\n    Parameters\n    ----------\n    value: any\n        Fill value.\n\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.afilled3d( 0.0, [ 1, 1, 3 ] )\n    [ [ [ 0.0, 0.0, 0.0 ] ] ]\n\n","base.afilled3dBy":"\nbase.afilled3dBy( shape, clbk[, thisArg] )\n    Returns a filled three-dimensional nested array according to a provided\n    callback function.\n\n    The callback function is provided one argument:\n\n    - indices: current array element indices.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function clbk() { return 1.0; };\n    > var out = base.afilled3dBy( [ 1, 1, 3 ], clbk )\n    [ [ [ 1.0, 1.0, 1.0 ] ] ]\n\n    See Also\n    --------\n    base.afilled3d\n","base.afilled4d":"\nbase.afilled4d( value, shape )\n    Returns a filled four-dimensional nested array.\n\n    Parameters\n    ----------\n    value: any\n        Fill value.\n\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.afilled4d( 0.0, [ 1, 1, 1, 3 ] )\n    [ [ [ [ 0.0, 0.0, 0.0 ] ] ] ]\n\n","base.afilled4dBy":"\nbase.afilled4dBy( shape, clbk[, thisArg] )\n    Returns a filled four-dimensional nested array according to a provided\n    callback function.\n\n    The callback function is provided one argument:\n\n    - indices: current array element indices.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function clbk() { return 1.0; };\n    > var out = base.afilled4dBy( [ 1, 1, 1, 3 ], clbk )\n    [ [ [ [ 1.0, 1.0, 1.0 ] ] ] ]\n\n    See Also\n    --------\n    base.afilled4d\n","base.afilled5d":"\nbase.afilled5d( value, shape )\n    Returns a filled five-dimensional nested array.\n\n    Parameters\n    ----------\n    value: any\n        Fill value.\n\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.afilled5d( 0.0, [ 1, 1, 1, 1, 3 ] )\n    [ [ [ [ [ 0.0, 0.0, 0.0 ] ] ] ] ]\n\n","base.afilled5dBy":"\nbase.afilled5dBy( shape, clbk[, thisArg] )\n    Returns a filled five-dimensional nested array according to a provided\n    callback function.\n\n    The callback function is provided one argument:\n\n    - indices: current array element indices.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function clbk() { return 1.0; };\n    > var out = base.afilled5dBy( [ 1, 1, 1, 1, 3 ], clbk )\n    [ [ [ [ [ 1.0, 1.0, 1.0 ] ] ] ] ]\n\n    See Also\n    --------\n    base.afilled5d\n","base.afilledBy":"\nbase.afilledBy( len, clbk[, thisArg] )\n    Returns a filled \"generic\" array according to a provided callback function.\n\n    Parameters\n    ----------\n    len: integer\n        Array length.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function clbk() { return 1.0; };\n    > var out = base.afilledBy( 3, clbk )\n    [ 1.0, 1.0, 1.0 ]\n\n    See Also\n    --------\n    base.afilled\n","base.afillednd":"\nbase.afillednd( value, shape )\n    Returns a filled n-dimensional nested array.\n\n    Parameters\n    ----------\n    value: any\n        Fill value.\n\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.afillednd( 0.0, [ 1, 3 ] )\n    [ [ 0.0, 0.0, 0.0 ] ]\n\n","base.afilledndBy":"\nbase.afilledndBy( shape, clbk[, thisArg] )\n    Returns a filled n-dimensional nested array according to a callback\n    function.\n\n    The callback function is provided one argument:\n\n    - indices: current array element indices.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function clbk() { return 1.0; };\n    > var out = base.afilledndBy( [ 1, 3 ], clbk )\n    [ [ 1.0, 1.0, 1.0 ] ]\n\n    See Also\n    --------\n    base.afillednd\n","base.afilter":"\nbase.afilter( x, predicate[, thisArg] )\n    Returns a shallow copy of an array containing only those elements which pass\n    a test implemented by a predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the input array.\n\n    If provided an array-like object having a `filter` method , the function\n    defers execution to that method and assumes that the method has the\n    following signature:\n\n      x.filter( predicate, thisArg )\n\n    If provided an array-like object without a `filter` method, the function\n    performs a linear scan and always returns a generic array.\n\n    Parameters\n    ----------\n    x: Array|TypedArray|Object\n        Input array.\n\n    predicate: Function\n        Predicate function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Output array.\n\n    Examples\n    --------\n    > function f( v ) { return ( v > 0 ); };\n    > var x = [ 1, -2, -3, 4 ];\n    > var out = base.afilter( x, f )\n    [ 1, 4 ]\n\n","base.afirst":"\nbase.afirst( arr )\n    Returns the first element of an array-like object.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject\n        Input array.\n\n    Returns\n    -------\n    out: any\n        First element.\n\n    Examples\n    --------\n    > var out = base.afirst( [ 1, 2, 3 ] )\n    1\n\n","base.aflatten":"\nbase.aflatten( x, shape, colexicographic )\n    Flattens an n-dimensional nested array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    Returns\n    -------\n    out: Array\n        Flattened array.\n\n    Examples\n    --------\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = base.aflatten( x, [ 2, 2 ], false )\n    [ 1, 2, 3, 4 ]\n    > out = base.aflatten( x, [ 2, 2 ], true )\n    [ 1, 3, 2, 4 ]\n\n\nbase.aflatten.assign( x, shape, colexicographic, out, stride, offset )\n    Flattens an n-dimensional nested array and assigns elements to a provided\n    output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten.assign( x, [ 2, 2 ], false, out, 1, 0 )\n    [ 1, 2, 3, 4 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten.assign( x, [ 2, 2 ], true, out, 1, 0 );\n    > out\n    [ 1, 3, 2, 4 ]\n\n    See Also\n    --------\n    base.aflattenBy\n","base.aflatten.assign":"\nbase.aflatten.assign( x, shape, colexicographic, out, stride, offset )\n    Flattens an n-dimensional nested array and assigns elements to a provided\n    output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten.assign( x, [ 2, 2 ], false, out, 1, 0 )\n    [ 1, 2, 3, 4 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten.assign( x, [ 2, 2 ], true, out, 1, 0 );\n    > out\n    [ 1, 3, 2, 4 ]\n\n    See Also\n    --------\n    base.aflattenBy","base.aflatten2d":"\nbase.aflatten2d( x, shape, colexicographic )\n    Flattens a two-dimensional nested array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    Returns\n    -------\n    out: Array\n        Flattened array.\n\n    Examples\n    --------\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = base.aflatten2d( x, [ 2, 2 ], false )\n    [ 1, 2, 3, 4 ]\n    > out = base.aflatten2d( x, [ 2, 2 ], true )\n    [ 1, 3, 2, 4 ]\n\n\nbase.aflatten2d.assign( x, shape, colexicographic, out, stride, offset )\n    Flattens a two-dimensional nested array and assigns elements to a provided\n    output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten2d.assign( x, [ 2, 2 ], false, out, 1, 0 )\n    [ 1, 2, 3, 4 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten2d.assign( x, [ 2, 2 ], true, out, 1, 0 );\n    > out\n    [ 1, 3, 2, 4 ]\n\n    See Also\n    --------\n    base.aflatten2dBy\n","base.aflatten2d.assign":"\nbase.aflatten2d.assign( x, shape, colexicographic, out, stride, offset )\n    Flattens a two-dimensional nested array and assigns elements to a provided\n    output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten2d.assign( x, [ 2, 2 ], false, out, 1, 0 )\n    [ 1, 2, 3, 4 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten2d.assign( x, [ 2, 2 ], true, out, 1, 0 );\n    > out\n    [ 1, 3, 2, 4 ]\n\n    See Also\n    --------\n    base.aflatten2dBy","base.aflatten2dBy":"\nbase.aflatten2dBy( x, shape, colex, clbk[, thisArg] )\n    Flattens a two-dimensional nested array according to a callback function.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Flattened array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = base.aflatten2dBy( x, [ 2, 2 ], false, fcn )\n    [ 2, 4, 6, 8 ]\n    > out = base.aflatten2dBy( x, [ 2, 2 ], true, fcn )\n    [ 2, 6, 4, 8 ]\n\n\nbase.aflatten2dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n    Flattens a two-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten2dBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\n    [ 2, 4, 6, 8 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten2dBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\n    > out\n    [ 2, 6, 4, 8 ]\n\n    See Also\n    --------\n    base.aflatten2d\n","base.aflatten2dBy.assign":"\nbase.aflatten2dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n    Flattens a two-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten2dBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\n    [ 2, 4, 6, 8 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten2dBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\n    > out\n    [ 2, 6, 4, 8 ]\n\n    See Also\n    --------\n    base.aflatten2d","base.aflatten3d":"\nbase.aflatten3d( x, shape, colexicographic )\n    Flattens a three-dimensional nested array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    Returns\n    -------\n    out: Array\n        Flattened array.\n\n    Examples\n    --------\n    > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n    > var out = base.aflatten3d( x, [ 2, 1, 2 ], false )\n    [ 1, 2, 3, 4 ]\n    > out = base.aflatten3d( x, [ 2, 1, 2 ], true )\n    [ 1, 3, 2, 4 ]\n\n\nbase.aflatten3d.assign( x, shape, colexicographic, out, stride, offset )\n    Flattens a three-dimensional nested array and assigns elements to a provided\n    output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten3d.assign( x, [ 2, 1, 2 ], false, out, 1, 0 )\n    [ 1, 2, 3, 4 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten3d.assign( x, [ 2, 1, 2 ], true, out, 1, 0 );\n    > out\n    [ 1, 3, 2, 4 ]\n\n    See Also\n    --------\n    base.aflatten3dBy\n","base.aflatten3d.assign":"\nbase.aflatten3d.assign( x, shape, colexicographic, out, stride, offset )\n    Flattens a three-dimensional nested array and assigns elements to a provided\n    output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten3d.assign( x, [ 2, 1, 2 ], false, out, 1, 0 )\n    [ 1, 2, 3, 4 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten3d.assign( x, [ 2, 1, 2 ], true, out, 1, 0 );\n    > out\n    [ 1, 3, 2, 4 ]\n\n    See Also\n    --------\n    base.aflatten3dBy","base.aflatten3dBy":"\nbase.aflatten3dBy( x, shape, colex, clbk[, thisArg] )\n    Flattens a three-dimensional nested array according to a callback function.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Flattened array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n    > var out = base.aflatten3dBy( x, [ 2, 1, 2 ], false, fcn )\n    [ 2, 4, 6, 8 ]\n    > out = base.aflatten3dBy( x, [ 2, 1, 2 ], true, fcn )\n    [ 2, 6, 4, 8 ]\n\n\nbase.aflatten3dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n    Flattens a three-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten3dBy.assign( x, [ 2, 1, 2 ], false, out, 1, 0, fcn )\n    [ 2, 4, 6, 8 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten3dBy.assign( x, [ 2, 1, 2 ], true, out, 1, 0, fcn );\n    > out\n    [ 2, 6, 4, 8 ]\n\n    See Also\n    --------\n    base.aflatten3d\n","base.aflatten3dBy.assign":"\nbase.aflatten3dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n    Flattens a three-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ [ 1, 2 ] ], [ [ 3, 4 ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten3dBy.assign( x, [ 2, 1, 2 ], false, out, 1, 0, fcn )\n    [ 2, 4, 6, 8 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten3dBy.assign( x, [ 2, 1, 2 ], true, out, 1, 0, fcn );\n    > out\n    [ 2, 6, 4, 8 ]\n\n    See Also\n    --------\n    base.aflatten3d","base.aflatten4d":"\nbase.aflatten4d( x, shape, colexicographic )\n    Flattens a four-dimensional nested array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    Returns\n    -------\n    out: Array\n        Flattened array.\n\n    Examples\n    --------\n    > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n    > var out = base.aflatten4d( x, [ 2, 1, 1, 2 ], false )\n    [ 1, 2, 3, 4 ]\n    > out = base.aflatten4d( x, [ 2, 1, 1, 2 ], true )\n    [ 1, 3, 2, 4 ]\n\n\nbase.aflatten4d.assign( x, shape, colexicographic, out, stride, offset )\n    Flattens a four-dimensional nested array and assigns elements to a provided\n    output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0 )\n    [ 1, 2, 3, 4 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0 );\n    > out\n    [ 1, 3, 2, 4 ]\n\n    See Also\n    --------\n    base.aflatten4dBy\n","base.aflatten4d.assign":"\nbase.aflatten4d.assign( x, shape, colexicographic, out, stride, offset )\n    Flattens a four-dimensional nested array and assigns elements to a provided\n    output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0 )\n    [ 1, 2, 3, 4 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten4d.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0 );\n    > out\n    [ 1, 3, 2, 4 ]\n\n    See Also\n    --------\n    base.aflatten4dBy","base.aflatten4dBy":"\nbase.aflatten4dBy( x, shape, colex, clbk[, thisArg] )\n    Flattens a four-dimensional nested array according to a callback function.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Flattened array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n    > var out = base.aflatten4dBy( x, [ 2, 1, 1, 2 ], false, fcn )\n    [ 2, 4, 6, 8 ]\n    > out = base.aflatten4dBy( x, [ 2, 1, 1, 2 ], true, fcn )\n    [ 2, 6, 4, 8 ]\n\n\nbase.aflatten4dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n    Flattens a four-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0, fcn )\n    [ 2, 4, 6, 8 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0, fcn );\n    > out\n    [ 2, 6, 4, 8 ]\n\n    See Also\n    --------\n    base.aflatten4d\n","base.aflatten4dBy.assign":"\nbase.aflatten4dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n    Flattens a four-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ [ [ 1, 2 ] ] ], [ [ [ 3, 4 ] ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], false, out, 1, 0, fcn )\n    [ 2, 4, 6, 8 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten4dBy.assign( x, [ 2, 1, 1, 2 ], true, out, 1, 0, fcn );\n    > out\n    [ 2, 6, 4, 8 ]\n\n    See Also\n    --------\n    base.aflatten4d","base.aflatten5d":"\nbase.aflatten5d( x, shape, colexicographic )\n    Flattens a five-dimensional nested array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    Returns\n    -------\n    out: Array\n        Flattened array.\n\n    Examples\n    --------\n    > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n    > var out = base.aflatten5d( x, [ 2, 1, 1, 1, 2 ], false )\n    [ 1, 2, 3, 4 ]\n    > out = base.aflatten5d( x, [ 2, 1, 1, 1, 2 ], true )\n    [ 1, 3, 2, 4 ]\n\n\nbase.aflatten5d.assign( x, shape, colexicographic, out, stride, offset )\n    Flattens a five-dimensional nested array and assigns elements to a provided\n    output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0 )\n    [ 1, 2, 3, 4 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0 );\n    > out\n    [ 1, 3, 2, 4 ]\n\n    See Also\n    --------\n    base.aflatten5dBy\n","base.aflatten5d.assign":"\nbase.aflatten5d.assign( x, shape, colexicographic, out, stride, offset )\n    Flattens a five-dimensional nested array and assigns elements to a provided\n    output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colexicographic: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0 )\n    [ 1, 2, 3, 4 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten5d.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0 );\n    > out\n    [ 1, 3, 2, 4 ]\n\n    See Also\n    --------\n    base.aflatten5dBy","base.aflatten5dBy":"\nbase.aflatten5dBy( x, shape, colex, clbk[, thisArg] )\n    Flattens a five-dimensional nested array according to a callback function.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Flattened array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n    > var out = base.aflatten5dBy( x, [ 2, 1, 1, 1, 2 ], false, fcn )\n    [ 2, 4, 6, 8 ]\n    > out = base.aflatten5dBy( x, [ 2, 1, 1, 1, 2 ], true, fcn )\n    [ 2, 6, 4, 8 ]\n\n\nbase.aflatten5dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n    Flattens a five-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0, fcn )\n    [ 2, 4, 6, 8 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0, fcn );\n    > out\n    [ 2, 6, 4, 8 ]\n\n    See Also\n    --------\n    base.aflatten5d\n","base.aflatten5dBy.assign":"\nbase.aflatten5dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n    Flattens a five-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ [ [ [ 1, 2 ] ] ] ], [ [ [ [ 3, 4 ] ] ] ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], false, out, 1, 0, fcn )\n    [ 2, 4, 6, 8 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflatten5dBy.assign( x, [ 2, 1, 1, 1, 2 ], true, out, 1, 0, fcn );\n    > out\n    [ 2, 6, 4, 8 ]\n\n    See Also\n    --------\n    base.aflatten5d","base.aflattenBy":"\nbase.aflattenBy( x, shape, colex, clbk[, thisArg] )\n    Flattens an n-dimensional nested array according to a callback function.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Flattened array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = base.aflattenBy( x, [ 2, 2 ], false, fcn )\n    [ 2, 4, 6, 8 ]\n    > out = base.aflattenBy( x, [ 2, 2 ], true, fcn )\n    [ 2, 6, 4, 8 ]\n\n\nbase.aflattenBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n    Flattens an n-dimensional nested array according to a callback function and\n    assigns elements to a provided output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflattenBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\n    [ 2, 4, 6, 8 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflattenBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\n    > out\n    [ 2, 6, 4, 8 ]\n\n    See Also\n    --------\n    base.aflatten\n","base.aflattenBy.assign":"\nbase.aflattenBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )\n    Flattens an n-dimensional nested array according to a callback function and\n    assigns elements to a provided output array.\n\n    The function assumes that all nested arrays have the same length (i.e., the\n    input array is *not* a ragged array).\n\n    The callback function is provided the following arguments:\n\n    - value: nested array element.\n    - indices: element indices (in lexicographic order).\n    - arr: the input array.\n\n    Parameters\n    ----------\n    x: Array\n        Input array.\n\n    shape: Array<integer>\n        Array shape.\n\n    colex: boolean\n        Specifies whether to flatten array values in colexicographic order.\n\n    out: Collection\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > function fcn( v ) { return v * 2; };\n    > var x = [ [ 1, 2 ], [ 3, 4 ] ];\n    > var out = [ 0, 0, 0, 0 ];\n    > var v = base.aflattenBy.assign( x, [ 2, 2 ], false, out, 1, 0, fcn )\n    [ 2, 4, 6, 8 ]\n    > var bool = ( v === out )\n    true\n    > out = [ 0, 0, 0, 0 ];\n    > base.aflattenBy.assign( x, [ 2, 2 ], true, out, 1, 0, fcn );\n    > out\n    [ 2, 6, 4, 8 ]\n\n    See Also\n    --------\n    base.aflatten","base.afliplr2d":"\nbase.afliplr2d( x )\n    Reverses the order of elements along the last dimension of a two-dimensional\n    nested input array.\n\n    The function does *not* perform a deep copy of nested array elements.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input nested array.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.afliplr2d( [ [ 1, 2 ], [ 3, 4 ] ] )\n    [ [ 2, 1 ], [ 4, 3 ] ]\n\n    See Also\n    --------\n    base.afliplr3d, base.afliplr4d, base.afliplr5d\n","base.afliplr3d":"\nbase.afliplr3d( x )\n    Reverses the order of elements along the last dimension of a three-\n    dimensional nested input array.\n\n    The function does *not* perform a deep copy of nested array elements.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input nested array.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.afliplr3d( [ [ [ 1, 2 ], [ 3, 4 ] ] ] )\n    [ [ [ 2, 1 ], [ 4, 3 ] ] ]\n\n    See Also\n    --------\n    base.afliplr2d, base.afliplr4d, base.afliplr5d\n","base.afliplr4d":"\nbase.afliplr4d( x )\n    Reverses the order of elements along the last dimension of a four-\n    dimensional nested input array.\n\n    The function does *not* perform a deep copy of nested array elements.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input nested array.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.afliplr4d( [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] )\n    [ [ [ [ 2, 1 ], [ 4, 3 ] ] ] ]\n\n    See Also\n    --------\n    base.afliplr2d, base.afliplr3d, base.afliplr5d\n","base.afliplr5d":"\nbase.afliplr5d( x )\n    Reverses the order of elements along the last dimension of a five-\n    dimensional nested input array.\n\n    The function does *not* perform a deep copy of nested array elements.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input nested array.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.afliplr5d( [ [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] ] )\n    [ [ [ [ [ 2, 1 ], [ 4, 3 ] ] ] ] ]\n\n    See Also\n    --------\n    base.afliplr2d, base.afliplr3d, base.afliplr4d\n","base.aflipud2d":"\nbase.aflipud2d( x )\n    Reverses the order of elements along the first dimension of a two-\n    dimensional nested input array.\n\n    The function does *not* perform a deep copy of nested array elements.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input nested array.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.aflipud2d( [ [ 1, 2 ], [ 3, 4 ] ] )\n    [ [ 3, 4 ], [ 1, 2 ] ]\n\n    See Also\n    --------\n    base.aflipud3d, base.aflipud4d, base.aflipud5d\n","base.aflipud3d":"\nbase.aflipud3d( x )\n    Reverses the order of elements along the second-to-last dimension of a\n    three-dimensional nested input array.\n\n    The function does *not* perform a deep copy of nested array elements.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input nested array.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.aflipud3d( [ [ [ 1, 2 ], [ 3, 4 ] ] ] )\n    [ [ [ 3, 4 ], [ 1, 2 ] ] ]\n\n    See Also\n    --------\n    base.aflipud2d, base.aflipud4d, base.aflipud5d\n","base.aflipud4d":"\nbase.aflipud4d( x )\n    Reverses the order of elements along the second-to-last dimension of a four-\n    dimensional nested input array.\n\n    The function does *not* perform a deep copy of nested array elements.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input nested array.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.aflipud4d( [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] )\n    [ [ [ [ 3, 4 ], [ 1, 2 ] ] ] ]\n\n    See Also\n    --------\n    base.aflipud2d, base.aflipud3d, base.aflipud5d\n","base.aflipud5d":"\nbase.aflipud5d( x )\n    Reverses the order of elements along the second-to-last dimension of a five-\n    dimensional nested input array.\n\n    The function does *not* perform a deep copy of nested array elements.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Input nested array.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.aflipud5d( [ [ [ [ [ 1, 2 ], [ 3, 4 ] ] ] ] ] )\n    [ [ [ [ [ 3, 4 ], [ 1, 2 ] ] ] ] ]\n\n    See Also\n    --------\n    base.aflipud2d, base.aflipud3d, base.aflipud4d\n","base.ahavercos":"\nbase.ahavercos( x )\n    Computes the inverse half-value versed cosine.\n\n    The inverse half-value versed cosine is defined as `2*acos(sqrt(x))`.\n\n    If `x < 0`, `x > 1`, or `x` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Inverse half-value versed cosine.\n\n    Examples\n    --------\n    > var y = base.ahavercos( 0.5 )\n    ~1.5708\n    > y = base.ahavercos( 0.0 )\n    ~3.1416\n\n    See Also\n    --------\n    base.ahaversin, base.havercos, base.vercos\n","base.ahaversin":"\nbase.ahaversin( x )\n    Computes the inverse half-value versed sine.\n\n    The inverse half-value versed sine is defined as `2*asin(sqrt(x))`.\n\n    If `x < 0`, `x > 1`, or `x` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Inverse half-value versed sine.\n\n    Examples\n    --------\n    > var y = base.ahaversin( 0.5 )\n    ~1.5708\n    > y = base.ahaversin( 0.0 )\n    0.0\n\n    See Also\n    --------\n    base.ahavercos, base.haversin, base.versin\n","base.altcase":"\nbase.altcase( str )\n    Converts a string to alternate case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Alternate-cased string.\n\n    Examples\n    --------\n    > var out = base.altcase( 'Hello World!' )\n    'hElLo wOrLd!'\n    > out = base.altcase( 'I am a tiny little teapot' )\n    'i aM A TiNy lItTlE TeApOt'\n\n    See Also\n    --------\n    base.lowercase, base.uppercase","base.aones":"\nbase.aones( len )\n    Returns a \"generic\" array filled with ones.\n\n    Parameters\n    ----------\n    len: integer\n        Array length.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.aones( 3 )\n    [ 1.0, 1.0, 1.0 ]\n\n    See Also\n    --------\n    base.azeros, base.aones2d, base.aones3d, base.aones4d, base.aones5d, base.aonesnd\n","base.aones2d":"\nbase.aones2d( shape )\n    Returns a two-dimensional nested array filled with ones.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.aones2d( [ 1, 3 ] )\n    [ [ 1.0, 1.0, 1.0 ] ]\n\n    See Also\n    --------\n    base.azeros2d, base.aones, base.aones3d, base.aones4d, base.aones5d, base.aonesnd\n","base.aones3d":"\nbase.aones3d( shape )\n    Returns a three-dimensional nested array filled with ones.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.aones3d( [ 1, 1, 3 ] )\n    [ [ [ 1.0, 1.0, 1.0 ] ] ]\n\n    See Also\n    --------\n    base.azeros3d, base.aones, base.aones2d, base.aones4d, base.aones5d, base.aonesnd\n","base.aones4d":"\nbase.aones4d( shape )\n    Returns a four-dimensional nested array filled with ones.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.aones4d( [ 1, 1, 1, 3 ] )\n    [ [ [ [ 1.0, 1.0, 1.0 ] ] ] ]\n\n    See Also\n    --------\n    base.azeros4d, base.aones, base.aones2d, base.aones3d, base.aones5d, base.aonesnd\n","base.aones5d":"\nbase.aones5d( shape )\n    Returns a five-dimensional nested array filled with ones.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.aones5d( [ 1, 1, 1, 1, 3 ] )\n    [ [ [ [ [ 1.0, 1.0, 1.0 ] ] ] ] ]\n\n    See Also\n    --------\n    base.azeros5d, base.aones, base.aones2d, base.aones3d, base.aones4d, base.aonesnd\n","base.aonesnd":"\nbase.aonesnd( shape )\n    Returns an n-dimensional nested array filled with ones.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.aonesnd( [ 1, 3 ] )\n    [ [ 1.0, 1.0, 1.0 ] ]\n\n    See Also\n    --------\n    base.azerosnd, base.aones, base.aones2d, base.aones3d, base.aones4d, base.aones5d\n","base.aoneTo":"\nbase.aoneTo( n )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from one.\n\n    If `n` is a non-integer value greater than zero, the function returns an\n    array having `ceil(n)` elements.\n\n    If `n` is less than or equal to zero, the function returns an empty array.\n\n    Parameters\n    ----------\n    n: number\n        Number of elements.\n\n    Returns\n    -------\n    out: Array\n        Linearly spaced numeric array.\n\n    Examples\n    --------\n    > var arr = base.aoneTo( 6 )\n    [ 1, 2, 3, 4, 5, 6 ]\n\n\nbase.aoneTo.assign( out, stride, offset )\n    Fills an array with linearly spaced numeric elements which increment by 1\n    starting from one.\n\n    Parameters\n    ----------\n    out: ArrayLikeObject\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > base.aoneTo.assign( out, -1, out.length-1 );\n    > out\n    [ 6, 5, 4, 3, 2, 1 ]\n\n    See Also\n    --------\n    base.azeroTo, base.aones\n","base.aoneTo.assign":"\nbase.aoneTo.assign( out, stride, offset )\n    Fills an array with linearly spaced numeric elements which increment by 1\n    starting from one.\n\n    Parameters\n    ----------\n    out: ArrayLikeObject\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > base.aoneTo.assign( out, -1, out.length-1 );\n    > out\n    [ 6, 5, 4, 3, 2, 1 ]\n\n    See Also\n    --------\n    base.azeroTo, base.aones","base.args2multislice":"\nbase.args2multislice( args )\n    Creates a MultiSlice object from a list of MultiSlice constructor arguments.\n\n    Parameters\n    ----------\n    args: Array<Slice|integer|null|undefined>\n        Constructor arguments.\n\n    Returns\n    -------\n    s: MultiSlice\n        MultiSlice instance.\n\n    Examples\n    --------\n    > var args = [ null, null, null ];\n    > var s = new base.args2multislice( args );\n    > s.data\n    [ null, null, null ]\n    > args = [ 10, new Slice( 0, 10, 1 ), null ];\n    > s = new base.args2multislice( args );\n    > s.data\n    [ 10, <Slice>, null ]\n\n","base.asec":"\nbase.asec( x )\n    Computes the inverse (arc) secant of a number.\n\n    If `x > -1` and `x < 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Inverse (arc) secant.\n\n    Examples\n    --------\n    > var y = base.asec( 1.0 )\n    0.0\n    > y = base.asec( 2.0 )\n    ~1.0472\n    > y = base.asec( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acot, base.acsc, base.asech, base.acos\n","base.asecd":"\nbase.asecd( x )\n    Computes the arcsecant (in degrees) of a double-precision floating-point\n    number.\n\n    If `x` does not satisy `x >= 1` or `x <= -1`, the function returns NaN.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arcsecant (in degrees).\n\n    Examples\n    --------\n    > var y = base.asecd( 0.0 )\n    NaN\n    > y = base.asecd( 2 )\n    ~60.0\n    > y = base.asecd( NaN )\n    NaN\n\n    See Also\n    --------\n    base.asec, base.asech, base.acosd, base.secd\n","base.asecdf":"\nbase.asecdf( x )\n    Computes the arcsecant (in degrees) of a single-precision floating-point\n    number.\n\n    If `x` does not satisy `x >= 1` or `x <= -1`, the function returns NaN.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arcsecant (in degrees).\n\n    Examples\n    --------\n    > var y = base.asecdf( 2.0 )\n    ~60.0\n    > y = base.asecdf( 0.0 )\n    NaN\n    > y = base.asecdf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.asec, base.asech\n","base.asecf":"\nbase.asecf( x )\n    Computes the inverse (arc) secant of a single-precision\n    floating-point number.\n\n    If `x > -1` and `x < 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Inverse (arc) secant.\n\n    Examples\n    --------\n    > var y = base.asecf( 1.0 )\n    0.0\n    > y = base.asecf( 2.0 )\n    ~1.0472\n    > y = base.asecf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.asec, base.asech, base.acosf\n","base.asech":"\nbase.asech( x )\n    Computes the hyperbolic arcsecant of a number.\n\n    If `x < 0` or `x > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Hyperbolic arcsecant.\n\n    Examples\n    --------\n    > var y = base.asech( 1.0 )\n    0.0\n    > y = base.asech( 0.5 )\n    ~1.317\n    > y = base.asech( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acosh, base.asec, base.asech, base.acoth\n","base.asin":"\nbase.asin( x )\n    Computes the arcsine of a double-precision floating-point number.\n\n    If `|x| > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arcsine (in radians).\n\n    Examples\n    --------\n    > var y = base.asin( 0.0 )\n    0.0\n    > y = base.asin( -PI/6.0 )\n    ~-0.551\n    > y = base.asin( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acos, base.asinh, base.atan\n","base.asind":"\nbase.asind( x )\n    Computes the arcsine (in degrees) of a double-precision floating-point\n    number.\n\n    If `|x| > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arcsine (in degrees).\n\n    Examples\n    --------\n    > var y = base.asind( 0.0 )\n    0.0\n    > y = base.asind( PI / 6.0 )\n    ~31.57\n    > y = base.asind( NaN )\n    NaN\n\n    See Also\n    --------\n    base.asin, base.asinh, base.atand\n","base.asindf":"\nbase.asindf( x )\n    Computes the arcsine (in degrees) of a single-precision floating-point\n    number.\n\n    If `|x| > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arcsine (in degrees).\n\n    Examples\n    --------\n    > var y = base.asindf( 0.0 )\n    0.0\n    > y = base.asindf( 3.1415927410125732 / 6.0 )\n    ~31.57\n    > y = base.asindf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.asinf, base.asind\n","base.asinf":"\nbase.asinf( x )\n    Computes the arcsine of a single-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arcsine (in radians).\n\n    Examples\n    --------\n    > var y = base.asinf( 0.0 )\n    0.0\n    > y = base.asinf( -3.14/6.0 )\n    ~-0.551\n    > y = base.asinf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.asin, base.asindf\n","base.asinh":"\nbase.asinh( x )\n    Computes the hyperbolic arcsine of a double-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Hyperbolic arcsine.\n\n    Examples\n    --------\n    > var y = base.asinh( 0.0 )\n    0.0\n    > y = base.asinh( 2.0 )\n    ~1.444\n    > y = base.asinh( -2.0 )\n    ~-1.444\n    > y = base.asinh( NaN )\n    NaN\n    > y = base.asinh( NINF )\n    -Infinity\n    > y = base.asinh( PINF )\n    Infinity\n\n    See Also\n    --------\n    base.acosh, base.asin, base.atanh\n","base.atan":"\nbase.atan( x )\n    Computes the arctangent of a double-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arctangent (in radians).\n\n    Examples\n    --------\n    > var y = base.atan( 0.0 )\n    ~0.0\n    > y = base.atan( -PI/2.0 )\n    ~-1.004\n    > y = base.atan( PI/2.0 )\n    ~1.004\n    > y = base.atan( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acos, base.asin, base.atanh\n","base.atan2":"\nbase.atan2( y, x )\n    Computes the angle in the plane (in radians) between the positive x-axis and\n    the ray from (0,0) to the point (x,y).\n\n    Parameters\n    ----------\n    y: number\n        Coordinate along y-axis.\n\n    x: number\n        Coordinate along x-axis.\n\n    Returns\n    -------\n    out: number\n        Angle (in radians).\n\n    Examples\n    --------\n    > var v = base.atan2( 2.0, 2.0 )\n    ~0.785\n    > v = base.atan2( 6.0, 2.0 )\n    ~1.249\n    > v = base.atan2( -1.0, -1.0 )\n    ~-2.356\n    > v = base.atan2( 3.0, 0.0 )\n    ~1.571\n    > v = base.atan2( -2.0, 0.0 )\n    ~-1.571\n    > v = base.atan2( 0.0, 0.0 )\n    0.0\n    > v = base.atan2( 3.0, NaN )\n    NaN\n    > v = base.atan2( NaN, 2.0 )\n    NaN\n\n    See Also\n    --------\n    base.atan\n","base.atand":"\nbase.atand( x )\n    Computes the arctangent (in degrees) of a double-precision floating-point\n    number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arctangent (in degrees).\n\n    Examples\n    --------\n    > var y = base.atand( 0.0 )\n    0.0\n    > y = base.atand( PI/6.0 )\n    ~27.64\n    > y = base.atand( NaN )\n    NaN\n\n    See Also\n    --------\n    base.atan, base.atanh, base.acosd\n","base.atanf":"\nbase.atanf( x )\n    Computes the arctangent of a single-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Arctangent (in radians).\n\n    Examples\n    --------\n    > var y = base.atanf( 0.0 )\n    0.0\n    > y = base.atanf( -3.14/4.0 )\n    ~-0.666\n    > y = base.atanf( 3.14/4.0 )\n    ~0.666\n    > y = base.atanf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.atan, base.atanh, base.acosf\n","base.atanh":"\nbase.atanh( x )\n    Computes the hyperbolic arctangent of a double-precision floating-point\n    number.\n\n    If `|x| > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Hyperbolic arctangent.\n\n    Examples\n    --------\n    > var y = base.atanh( 0.0 )\n    0.0\n    > y = base.atanh( 0.9 )\n    ~1.472\n    > y = base.atanh( 1.0 )\n    Infinity\n    > y = base.atanh( -1.0 )\n    -Infinity\n    > y = base.atanh( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acosh, base.asinh, base.atan\n","base.avercos":"\nbase.avercos( x )\n    Computes the inverse versed cosine.\n\n    The inverse versed cosine is defined as `acos(1+x)`.\n\n    If `x < -2`, `x > 0`, or `x` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Inverse versed cosine.\n\n    Examples\n    --------\n    > var y = base.avercos( -1.5 )\n    ~2.0944\n    > y = base.avercos( -0.0 )\n    0.0\n\n    See Also\n    --------\n    base.aversin, base.versin\n","base.aversin":"\nbase.aversin( x )\n    Computes the inverse versed sine.\n\n    The inverse versed sine is defined as `acos(1-x)`.\n\n    If `x < 0`, `x > 2`, or `x` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Inverse versed sine.\n\n    Examples\n    --------\n    > var y = base.aversin( 1.5 )\n    ~2.0944\n    > y = base.aversin( 0.0 )\n    0.0\n\n    See Also\n    --------\n    base.avercos, base.vercos\n","base.azeros":"\nbase.azeros( len )\n    Returns a zero-filled \"generic\" array.\n\n    Parameters\n    ----------\n    len: integer\n        Array length.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.azeros( 3 )\n    [ 0.0, 0.0, 0.0 ]\n\n    See Also\n    --------\n    base.aones, base.azeros2d, base.azeros3d, base.azeros4d, base.azeros5d, base.azerosnd\n","base.azeros2d":"\nbase.azeros2d( shape )\n    Returns a zero-filled two-dimensional nested array.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.azeros2d( [ 1, 3 ] )\n    [ [ 0.0, 0.0, 0.0 ] ]\n\n    See Also\n    --------\n    base.azeros, base.aones2d, base.azeros3d, base.azeros4d, base.azeros5d, base.azerosnd\n","base.azeros3d":"\nbase.azeros3d( shape )\n    Returns a zero-filled three-dimensional nested array.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.azeros3d( [ 1, 1, 3 ] )\n    [ [ [ 0.0, 0.0, 0.0 ] ] ]\n\n    See Also\n    --------\n    base.azeros, base.aones3d, base.azeros2d, base.azeros4d, base.azeros5d, base.azerosnd\n","base.azeros4d":"\nbase.azeros4d( shape )\n    Returns a zero-filled four-dimensional nested array.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.azeros4d( [ 1, 1, 1, 3 ] )\n    [ [ [ [ 0.0, 0.0, 0.0 ] ] ] ]\n\n    See Also\n    --------\n    base.azeros, base.aones4d, base.azeros2d, base.azeros3d, base.azeros5d, base.azerosnd\n","base.azeros5d":"\nbase.azeros5d( shape )\n    Returns a zero-filled five-dimensional nested array.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.azeros5d( [ 1, 1, 1, 1, 3 ] )\n    [ [ [ [ [ 0.0, 0.0, 0.0 ] ] ] ] ]\n\n    See Also\n    --------\n    base.azeros, base.aones5d, base.azeros2d, base.azeros3d, base.azeros4d, base.azerosnd\n","base.azerosnd":"\nbase.azerosnd( shape )\n    Returns a zero-filled n-dimensional nested array.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Array shape.\n\n    Returns\n    -------\n    out: Array\n        Output array.\n\n    Examples\n    --------\n    > var out = base.azerosnd( [ 1, 3 ] )\n    [ [ 0.0, 0.0, 0.0 ] ]\n\n    See Also\n    --------\n    base.azeros, base.aonesnd, base.azeros2d, base.azeros3d, base.azeros4d, base.azeros5d\n","base.azeroTo":"\nbase.azeroTo( n )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from zero.\n\n    If `n` is a non-integer value greater than zero, the function returns an\n    array having `ceil(n)` elements.\n\n    If `n` is less than or equal to zero, the function returns an empty array.\n\n    Parameters\n    ----------\n    n: number\n        Number of elements.\n\n    Returns\n    -------\n    out: Array\n        Linearly spaced numeric array.\n\n    Examples\n    --------\n    > var arr = base.azeroTo( 6 )\n    [ 0, 1, 2, 3, 4, 5 ]\n\n\nbase.azeroTo.assign( out, stride, offset )\n    Fills an array with linearly spaced numeric elements which increment by 1\n    starting from zero.\n\n    Parameters\n    ----------\n    out: ArrayLikeObject\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > base.azeroTo.assign( out, -1, out.length-1 );\n    > out\n    [ 5, 4, 3, 2, 1, 0 ]\n\n    See Also\n    --------\n    base.aoneTo\n","base.azeroTo.assign":"\nbase.azeroTo.assign( out, stride, offset )\n    Fills an array with linearly spaced numeric elements which increment by 1\n    starting from zero.\n\n    Parameters\n    ----------\n    out: ArrayLikeObject\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > base.azeroTo.assign( out, -1, out.length-1 );\n    > out\n    [ 5, 4, 3, 2, 1, 0 ]\n\n    See Also\n    --------\n    base.aoneTo","base.bernoulli":"\nbase.bernoulli( n )\n    Computes the nth Bernoulli number.\n\n    If not provided a nonnegative integer value, the function returns `NaN`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Bernoulli number.\n\n    Examples\n    --------\n    > var y = base.bernoulli( 0 )\n    1.0\n    > y = base.bernoulli( 1 )\n    0.5\n    > y = base.bernoulli( 2 )\n    ~0.167\n    > y = base.bernoulli( 3 )\n    0.0\n    > y = base.bernoulli( 4 )\n    ~-0.033\n    > y = base.bernoulli( 5 )\n    0.0\n    > y = base.bernoulli( 20 )\n    ~-529.124\n    > y = base.bernoulli( 260 )\n    -Infinity\n    > y = base.bernoulli( 262 )\n    Infinity\n    > y = base.bernoulli( NaN )\n    NaN\n\n","base.besselj0":"\nbase.besselj0( x )\n    Computes the Bessel function of the first kind of order zero.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.besselj0( 0.0 )\n    1.0\n    > y = base.besselj0( 1.0 )\n    ~0.765\n    > y = base.besselj0( PINF )\n    0.0\n    > y = base.besselj0( NINF )\n    0.0\n    > y = base.besselj0( NaN )\n    NaN\n\n    See Also\n    --------\n    base.besselj1, base.bessely0, base.bessely1\n","base.besselj1":"\nbase.besselj1( x )\n    Computes the Bessel function of the first kind of order one.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.besselj1( 0.0 )\n    0.0\n    > y = base.besselj1( 1.0 )\n    ~0.440\n    > y = base.besselj1( PINF )\n    0.0\n    > y = base.besselj1( NINF )\n    0.0\n    > y = base.besselj1( NaN )\n    NaN\n\n    See Also\n    --------\n    base.besselj0, base.bessely0, base.bessely1\n","base.bessely0":"\nbase.bessely0( x )\n    Computes the Bessel function of the second kind of order zero.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.bessely0( 0.0 )\n    -Infinity\n    > y = base.bessely0( 1.0 )\n    ~0.088\n    > y = base.bessely0( -1.0 )\n    NaN\n    > y = base.bessely0( PINF )\n    0.0\n    > y = base.bessely0( NINF )\n    NaN\n    > y = base.bessely0( NaN )\n    NaN\n\n    See Also\n    --------\n    base.besselj0, base.besselj1, base.bessely1\n","base.bessely1":"\nbase.bessely1( x )\n    Computes the Bessel function of the second kind of order one.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.bessely1( 0.0 )\n    -Infinity\n    > y = base.bessely1( 1.0 )\n    ~-0.781\n    > y = base.bessely1( -1.0 )\n    NaN\n    > y = base.bessely1( PINF )\n    0.0\n    > y = base.bessely1( NINF )\n    NaN\n    > y = base.bessely1( NaN )\n    NaN\n\n    See Also\n    --------\n    base.besselj0, base.besselj1, base.bessely0\n","base.beta":"\nbase.beta( x, y )\n    Evaluates the beta function.\n\n    Parameters\n    ----------\n    x: number\n        First function parameter (nonnegative).\n\n    y: number\n        Second function parameter (nonnegative).\n\n    Returns\n    -------\n    out: number\n        Evaluated beta function.\n\n    Examples\n    --------\n    > var v = base.beta( 0.0, 0.5 )\n    Infinity\n    > v = base.beta( 1.0, 1.0 )\n    1.0\n    > v = base.beta( -1.0, 2.0 )\n    NaN\n    > v = base.beta( 5.0, 0.2 )\n    ~3.382\n    > v = base.beta( 4.0, 1.0 )\n    0.25\n    > v = base.beta( NaN, 2.0 )\n    NaN\n\n    See Also\n    --------\n    base.betainc, base.betaincinv, base.betaln\n","base.betainc":"\nbase.betainc( x, a, b[, regularized[, upper]] )\n    Computes the regularized incomplete beta function.\n\n    The `regularized` and `upper` parameters specify whether to evaluate the\n    non-regularized and/or upper incomplete beta functions, respectively.\n\n    If provided `x < 0` or `x > 1`, the function returns `NaN`.\n\n    If provided `a < 0` or `b < 0`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        First function parameter.\n\n    a: number\n        Second function parameter.\n\n    b: number\n        Third function parameter.\n\n    regularized: boolean (optional)\n        Boolean indicating whether the function should evaluate the regularized\n        or non-regularized incomplete beta function. Default: `true`.\n\n    upper: boolean (optional)\n        Boolean indicating whether the function should return the upper tail of\n        the incomplete beta function. Default: `false`.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.betainc( 0.5, 2.0, 2.0 )\n    0.5\n    > y = base.betainc( 0.5, 2.0, 2.0, false )\n    ~0.083\n    > y = base.betainc( 0.2, 1.0, 2.0 )\n    0.36\n    > y = base.betainc( 0.2, 1.0, 2.0, true, true )\n    0.64\n    > y = base.betainc( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.betainc( 0.8, NaN, 1.0 )\n    NaN\n    > y = base.betainc( 0.8, 1.0, NaN )\n    NaN\n    > y = base.betainc( 1.5, 1.0, 1.0 )\n    NaN\n    > y = base.betainc( -0.5, 1.0, 1.0 )\n    NaN\n    > y = base.betainc( 0.5, -2.0, 2.0 )\n    NaN\n    > y = base.betainc( 0.5, 2.0, -2.0 )\n    NaN\n\n    See Also\n    --------\n    base.beta, base.betaincinv, base.betaln\n","base.betaincinv":"\nbase.betaincinv( p, a, b[, upper] )\n    Computes the inverse of the lower incomplete beta function.\n\n    In contrast to a more commonly used definition, the first argument is the\n    probability `p` and the second and third arguments are `a` and `b`,\n    respectively.\n\n    By default, the function inverts the lower regularized incomplete beta\n    function. To invert the upper function, set the `upper` argument to `true`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Probability.\n\n    a: number\n        Second function parameter.\n\n    b: number\n        Third function parameter.\n\n    upper: boolean (optional)\n        Boolean indicating if the function should invert the upper tail of the\n        incomplete beta function. Default: `false`.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.betaincinv( 0.2, 3.0, 3.0 )\n    ~0.327\n    > y = base.betaincinv( 0.4, 3.0, 3.0 )\n    ~0.446\n    > y = base.betaincinv( 0.4, 3.0, 3.0, true )\n    ~0.554\n    > y = base.betaincinv( 0.4, 1.0, 6.0 )\n    ~0.082\n    > y = base.betaincinv( 0.8, 1.0, 6.0 )\n    ~0.235\n    > y = base.betaincinv( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.betaincinv( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.betaincinv( 0.5, 1.0, NaN )\n    NaN\n    > y = base.betaincinv( 1.2, 1.0, 1.0 )\n    NaN\n    > y = base.betaincinv( -0.5, 1.0, 1.0 )\n    NaN\n    > y = base.betaincinv( 0.5, -2.0, 2.0 )\n    NaN\n    > y = base.betaincinv( 0.5, 0.0, 2.0 )\n    NaN\n    > y = base.betaincinv( 0.5, 2.0, -2.0 )\n    NaN\n    > y = base.betaincinv( 0.5, 2.0, 0.0 )\n    NaN\n\n    See Also\n    --------\n    base.beta, base.betainc, base.betaln\n","base.betaln":"\nbase.betaln( a, b )\n    Evaluates the natural logarithm of the beta function.\n\n    Parameters\n    ----------\n    a: number\n        First function parameter (nonnegative).\n\n    b: number\n        Second function parameter (nonnegative).\n\n    Returns\n    -------\n    out: number\n        Natural logarithm of the beta function.\n\n    Examples\n    --------\n    > var v = base.betaln( 0.0, 0.0 )\n    Infinity\n    > v = base.betaln( 1.0, 1.0 )\n    0.0\n    > v = base.betaln( -1.0, 2.0 )\n    NaN\n    > v = base.betaln( 5.0, 0.2 )\n    ~1.218\n    > v = base.betaln( 4.0, 1.0 )\n    ~-1.386\n    > v = base.betaln( NaN, 2.0 )\n    NaN\n\n    See Also\n    --------\n    base.beta, base.betainc, base.betaincinv\n","base.binet":"\nbase.binet( x )\n    Evaluates Binet's formula extended to real numbers.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function result.\n\n    Examples\n    --------\n    > var y = base.binet( 0.0 )\n    0.0\n    > y = base.binet( 1.0 )\n    1.0\n    > y = base.binet( 2.0 )\n    1.0\n    > y = base.binet( 3.0 )\n    2.0\n    > y = base.binet( 4.0 )\n    3.0\n    > y = base.binet( 5.0 )\n    ~5.0\n    > y = base.binet( NaN )\n    NaN\n\n    See Also\n    --------\n    base.fibonacci, base.negafibonacci\n","base.binomcoef":"\nbase.binomcoef( n, k )\n    Computes the binomial coefficient of two integers.\n\n    If `k < 0`, the function returns `0`.\n\n    The function returns `NaN` for non-integer `n` or `k`.\n\n    Parameters\n    ----------\n    n: integer\n        First input value.\n\n    k: integer\n        Second input value.\n\n    Returns\n    -------\n    out: number\n        Function value.\n\n    Examples\n    --------\n    > var v = base.binomcoef( 8, 2 )\n    28\n    > v = base.binomcoef( 0, 0 )\n    1\n    > v = base.binomcoef( -4, 2 )\n    10\n    > v = base.binomcoef( 5, 3 )\n    10\n    > v = base.binomcoef( NaN, 3 )\n    NaN\n    > v = base.binomcoef( 5, NaN )\n    NaN\n    > v = base.binomcoef( NaN, NaN )\n    NaN\n\n","base.binomcoefln":"\nbase.binomcoefln( n, k )\n    Computes the natural logarithm of the binomial coefficient of two integers.\n\n    If `k < 0`, the function returns negative infinity.\n\n    The function returns `NaN` for non-integer `n` or `k`.\n\n    Parameters\n    ----------\n    n: integer\n        First input value.\n\n    k: integer\n        Second input value.\n\n    Returns\n    -------\n    out: number\n        Natural logarithm of the binomial coefficient.\n\n    Examples\n    --------\n    > var v = base.binomcoefln( 8, 2 )\n    ~3.332\n    > v = base.binomcoefln( 0, 0 )\n    0.0\n    > v = base.binomcoefln( -4, 2 )\n    ~2.303\n    > v = base.binomcoefln( 88, 3 )\n    ~11.606\n    > v = base.binomcoefln( NaN, 3 )\n    NaN\n    > v = base.binomcoefln( 5, NaN )\n    NaN\n    > v = base.binomcoefln( NaN, NaN )\n    NaN\n\n","base.boxcox":"\nbase.boxcox( x, lambda )\n    Computes a one-parameter Box-Cox transformation.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    lambda: number\n        Power parameter.\n\n    Returns\n    -------\n    b: number\n        Function value.\n\n    Examples\n    --------\n    > var v = base.boxcox( 1.0, 2.5 )\n    0.0\n    > v = base.boxcox( 4.0, 2.5 )\n    12.4\n    > v = base.boxcox( 10.0, 2.5 )\n    ~126.0911\n    > v = base.boxcox( 2.0, 0.0 )\n    ~0.6931\n    > v = base.boxcox( -1.0, 2.5 )\n    NaN\n    > v = base.boxcox( 0.0, -1.0 )\n    -Infinity\n\n    See Also\n    --------\n    base.boxcoxinv, base.boxcox1p, base.boxcox1pinv","base.boxcox1p":"\nbase.boxcox1p( x, lambda )\n    Computes a one-parameter Box-Cox transformation of 1+x.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    lambda: number\n        Power parameter.\n\n    Returns\n    -------\n    b: number\n        Function value.\n\n    Examples\n    --------\n    > var v =  base.boxcox1p( 1.0, 2.5 )\n    ~1.8627\n    > v = base.boxcox1p( 4.0, 2.5 )\n    ~21.9607\n    > v = base.boxcox1p( 10.0, 2.5 )\n    ~160.1246\n    > v = base.boxcox1p( 2.0, 0.0 )\n    ~1.0986\n    > v = base.boxcox1p( -1.0, 2.5 )\n    -0.4\n    > v = base.boxcox1p( 0.0, -1.0 )\n    0.0\n    > v = base.boxcox1p( -1.0, -1.0 )\n    -Infinity\n\n    See Also\n    --------\n    base.boxcox, base.boxcox1pinv, base.boxcoxinv","base.boxcox1pinv":"\nbase.boxcox1pinv( y, lambda )\n    Computes the inverse of a one-parameter Box-Cox transformation for 1+x.\n\n    Parameters\n    ----------\n    y: number\n        Input value.\n\n    lambda: number\n        Power parameter.\n\n    Returns\n    -------\n    v: number\n        Function value.\n\n    Examples\n    --------\n    > var v = base.boxcox1pinv( 1.0, 2.5 )\n    ~0.6505\n    > v = base.boxcox1pinv( 4.0, 2.5 )\n    ~1.6095\n    > v = base.boxcox1pinv( 10.0, 2.5 )\n    ~2.6812\n    > v = base.boxcox1pinv( 2.0, 0.0 )\n    ~6.3891\n    > v = base.boxcox1pinv( -1.0, 2.5 )\n    NaN\n    > v = base.boxcox1pinv( 0.0, -1.0 )\n    0.0\n    > v = base.boxcox1pinv( 1.0, NaN )\n    NaN\n    > v = base.boxcox1pinv( NaN, 3.1 )\n    NaN\n\n    See Also\n    --------\n    base.boxcox, base.boxcox1p, base.boxcoxinv","base.boxcoxinv":"\nbase.boxcoxinv( y, lambda )\n    Computes the inverse of a one-parameter Box-Cox transformation.\n\n    Parameters\n    ----------\n    y: number\n        Input value.\n\n    lambda: number\n        Power parameter.\n\n    Returns\n    -------\n    b: number\n        Function value.\n\n    Examples\n    --------\n    > var v = base.boxcoxinv( 1.0, 2.5 )\n    ~1.6505\n    > v = base.boxcoxinv( 4.0, 2.5 )\n    ~2.6095\n    > v = base.boxcoxinv( 10.0, 2.5 )\n    ~3.6812\n    > v = base.boxcoxinv( 2.0, 0.0 )\n    ~7.3891\n    > v = base.boxcoxinv( -1.0, 2.5 )\n    NaN\n    > v = base.boxcoxinv( 0.0, -1.0 )\n    1.0\n    > v = base.boxcoxinv( 1.0, NaN )\n    NaN\n    > v = base.boxcoxinv( NaN, 3.1 )\n    NaN\n\n    See Also\n    --------\n    base.boxcox, base.boxcox1p, base.boxcox1pinv","base.cabs":"\nbase.cabs( z )\n    Computes the absolute value of a double-precision complex floating-point\n    number.\n\n    The absolute value of a complex number is its distance from zero.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    y: number\n        Absolute value.\n\n    Examples\n    --------\n    > var y = base.cabs( new Complex128( 5.0, 3.0 ) )\n    ~5.831\n\n    See Also\n    --------\n    base.cabs2, base.abs\n","base.cabs2":"\nbase.cabs2( z )\n    Computes the squared absolute value of a double-precision complex floating-\n    point number.\n\n    The absolute value of a complex number is its distance from zero.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    y: number\n        Squared absolute value.\n\n    Examples\n    --------\n    > var y = base.cabs2( new Complex128( 5.0, 3.0 ) )\n    34.0\n\n    See Also\n    --------\n    base.cabs, base.abs2\n","base.cabs2f":"\nbase.cabs2f( z )\n    Computes the squared absolute value of a single-precision complex floating-\n    point number.\n\n    The absolute value of a complex number is its distance from zero.\n\n    Parameters\n    ----------\n    z: Complex64\n        Complex number.\n\n    Returns\n    -------\n    y: number\n        Squared absolute value.\n\n    Examples\n    --------\n    > var y = base.cabs2f( new Complex64( 5.0, 3.0 ) )\n    34.0\n\n    See Also\n    --------\n    base.cabs2, base.cabsf, base.abs2f\n","base.cabsf":"\nbase.cabsf( z )\n    Computes the absolute value of a single-precision complex floating-point\n    number.\n\n    The absolute value of a complex number is its distance from zero.\n\n    Parameters\n    ----------\n    z: Complex64\n        Complex number.\n\n    Returns\n    -------\n    y: number\n        Absolute value.\n\n    Examples\n    --------\n    > var y = base.cabsf( new Complex64( 5.0, 3.0 ) )\n    ~5.831\n\n    See Also\n    --------\n    base.cabs, base.cabs2f, base.absf\n","base.cadd":"\nbase.cadd( z1, z2 )\n    Adds two double-precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    z1: Complex128\n        Complex number.\n\n    z2: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Result.\n\n    Examples\n    --------\n    > var z = new Complex128( 5.0, 3.0 )\n    <Complex128>\n    > var out = base.cadd( z, z )\n    <Complex128>\n    > var re = real( out )\n    10.0\n    > var im = imag( out )\n    6.0\n\n    See Also\n    --------\n    base.cdiv, base.cmul, base.csub\n","base.caddf":"\nbase.caddf( z1, z2 )\n    Adds two single-precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    z1: Complex64\n        Complex number.\n\n    z2: Complex64\n        Complex number.\n\n    Returns\n    -------\n    out: Complex64\n        Result.\n\n    Examples\n    --------\n    > var z = new Complex64( 5.0, 3.0 )\n    <Complex64>\n    > var out = base.caddf( z, z )\n    <Complex64>\n    > var re = realf( out )\n    10.0\n    > var im = imagf( out )\n    6.0\n\n    See Also\n    --------\n    base.cadd, base.cmulf, base.csubf\n","base.camelcase":"\nbase.camelcase( str )\n    Converts a string to camel case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Camel-cased string.\n\n    Examples\n    --------\n    > var out = base.camelcase( 'Hello World!' )\n    'helloWorld'\n    > out = base.camelcase( 'beep boop' )\n    'beepBoop'\n\n    See Also\n    --------\n    base.constantcase, base.lowercase, base.snakecase, base.uppercase","base.capitalize":"\nbase.capitalize( str )\n    Capitalizes the first character in a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Capitalized string.\n\n    Examples\n    --------\n    > var out = base.capitalize( 'beep' )\n    'Beep'\n    > out = base.capitalize( 'Boop' )\n    'Boop'\n\n    See Also\n    --------\n    base.lowercase, base.uppercase\n","base.cbrt":"\nbase.cbrt( x )\n    Computes the cube root of a double-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Cube root.\n\n    Examples\n    --------\n    > var y = base.cbrt( 64.0 )\n    4.0\n    > y = base.cbrt( 27.0 )\n    3.0\n    > y = base.cbrt( 0.0 )\n    0.0\n    > y = base.cbrt( -0.0 )\n    -0.0\n    > y = base.cbrt( -9.0 )\n    ~-2.08\n    > y = base.cbrt( NaN )\n    NaN\n\n    See Also\n    --------\n    base.pow, base.sqrt\n","base.cbrtf":"\nbase.cbrtf( x )\n    Computes the cube root of a single-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Cube root.\n\n    Examples\n    --------\n    > var y = base.cbrtf( 64.0 )\n    4.0\n    > y = base.cbrtf( 27.0 )\n    3.0\n    > y = base.cbrtf( 0.0 )\n    0.0\n    > y = base.cbrtf( -0.0 )\n    -0.0\n    > y = base.cbrtf( -9.0 )\n    ~-2.08\n    > y = base.cbrtf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cbrt, base.sqrtf\n","base.cceil":"\nbase.cceil( z )\n    Rounds each component of a double-precision complex floating-point number\n    toward positive infinity.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Result.\n\n    Examples\n    --------\n    > var v = base.cceil( new Complex128( -1.5, 2.5 ) )\n    <Complex128>\n    > var re = real( v )\n    -1.0\n    > var im = imag( v )\n    3.0\n\n    See Also\n    --------\n    base.cceiln, base.cfloor, base.cround\n","base.cceilf":"\nbase.cceilf( z )\n    Rounds a single-precision complex floating-point number toward positive\n    infinity.\n\n    Parameters\n    ----------\n    z: Complex64\n        Complex number.\n\n    Returns\n    -------\n    out: Complex64\n        Result.\n\n    Examples\n    --------\n    > var v = base.cceilf( new Complex64( -1.5, 2.5 ) )\n    <Complex64>\n    > var re = realf( v )\n    -1.0\n    > var im = imagf( v )\n    3.0\n\n    See Also\n    --------\n    base.cceil\n","base.cceiln":"\nbase.cceiln( z, n )\n    Rounds each component of a double-precision complex number to the nearest\n    multiple of `10^n` toward positive infinity.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    n: integer\n        Integer power of 10.\n\n    Returns\n    -------\n    out: Complex128\n        Real and imaginary components.\n\n    Examples\n    --------\n    > var out = base.cceiln( new Complex128( 5.555, -3.333 ), -2 )\n    <Complex128>\n    > var re = real( out )\n    5.56\n    > var im = imag( out )\n    -3.33\n\n    See Also\n    --------\n    base.cceil, base.cfloorn, base.croundn\n","base.ccis":"\nbase.ccis( z )\n    Evaluates the cis function for a double-precision complex floating-point\n    number.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Complex number.\n\n    Examples\n    --------\n    > var y = base.ccis( new Complex128( 0.0, 0.0 ) )\n    <Complex128>\n    > var re = real( y )\n    1.0\n    > var im = imag( y )\n    0.0\n    > y = base.ccis( new Complex128( 1.0, 0.0 ) )\n    <Complex128>\n    > re = real( y )\n    ~0.540\n    > im = imag( y )\n    ~0.841\n\n","base.cdiv":"\nbase.cdiv( z1, z2 )\n    Divides two double-precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    z1: Complex128\n        Complex number.\n\n    z2: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Result.\n\n    Examples\n    --------\n    > var z1 = new Complex128( -13.0, -1.0 )\n    <Complex128>\n    > var z2 = new Complex128( -2.0, 1.0 )\n    <Complex128>\n    > var y = base.cdiv( z1, z2 )\n    <Complex128>\n    > var re = real( y )\n    5.0\n    > var im = imag( y )\n    3.0\n\n    See Also\n    --------\n    base.cadd, base.cmul, base.csub\n","base.ceil":"\nbase.ceil( x )\n    Rounds a double-precision floating-point number toward positive infinity.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.ceil( 3.14 )\n    4.0\n    > y = base.ceil( -4.2 )\n    -4.0\n    > y = base.ceil( -4.6 )\n    -4.0\n    > y = base.ceil( 9.5 )\n    10.0\n    > y = base.ceil( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceiln, base.floor, base.round\n","base.ceil2":"\nbase.ceil2( x )\n    Rounds a numeric value to the nearest power of two toward positive infinity.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.ceil2( 3.14 )\n    4.0\n    > y = base.ceil2( -4.2 )\n    -4.0\n    > y = base.ceil2( -4.6 )\n    -4.0\n    > y = base.ceil2( 9.5 )\n    16.0\n    > y = base.ceil2( 13.0 )\n    16.0\n    > y = base.ceil2( -13.0 )\n    -8.0\n    > y = base.ceil2( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceil, base.ceil10, base.floor2, base.round2\n","base.ceil10":"\nbase.ceil10( x )\n    Rounds a numeric value to the nearest power of ten toward positive infinity.\n\n    The function may not return accurate results for subnormals due to a general\n    loss in precision.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.ceil10( 3.14 )\n    10.0\n    > y = base.ceil10( -4.2 )\n    -1.0\n    > y = base.ceil10( -4.6 )\n    -1.0\n    > y = base.ceil10( 9.5 )\n    10.0\n    > y = base.ceil10( 13.0 )\n    100.0\n    > y = base.ceil10( -13.0 )\n    -10.0\n    > y = base.ceil10( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceil, base.ceil2, base.floor10, base.round10\n","base.ceilb":"\nbase.ceilb( x, n, b )\n    Rounds a numeric value to the nearest multiple of `b^n` toward positive\n    infinity.\n\n    Due to floating-point rounding error, rounding may not be exact.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Integer power.\n\n    b: integer\n        Base.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    // Round to 4 decimal places:\n    > var y = base.ceilb( 3.14159, -4, 10 )\n    3.1416\n\n    // If `n = 0` or `b = 1`, standard round behavior:\n    > y = base.ceilb( 3.14159, 0, 2 )\n    4.0\n\n    // Round to nearest multiple of two toward positive infinity:\n    > y = base.ceilb( 5.0, 1, 2 )\n    6.0\n\n    See Also\n    --------\n    base.ceil, base.ceiln, base.floorb, base.roundb\n","base.ceilf":"\nbase.ceilf( x )\n    Rounds a single-precision floating-point number toward positive infinity.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.ceilf( 3.14 )\n    4.0\n    > y = base.ceilf( -4.2 )\n    -4.0\n    > y = base.ceilf( -4.6 )\n    -4.0\n    > y = base.ceilf( 9.5 )\n    10.0\n    > y = base.ceilf( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.floorf\n","base.ceiln":"\nbase.ceiln( x, n )\n    Rounds a numeric value to the nearest multiple of `10^n` toward positive\n    infinity.\n\n    When operating on floating-point numbers in bases other than `2`, rounding\n    to specified digits can be inexact.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Integer power of 10.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    // Round to 2 decimal places:\n    > var y = base.ceiln( 3.14159, -2 )\n    3.15\n\n    // If `n = 0`, standard round toward positive infinity behavior:\n    > y = base.ceiln( 3.14159, 0 )\n    4.0\n\n    // Round to nearest thousand:\n    > y = base.ceiln( 12368.0, 3 )\n    13000.0\n\n\n    See Also\n    --------\n    base.ceil, base.ceilb, base.floorn, base.roundn\n","base.ceilsd":"\nbase.ceilsd( x, n, b )\n    Rounds a numeric value to the nearest number toward positive infinity with\n    `n` significant figures.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Number of significant figures. Must be greater than 0.\n\n    b: integer\n        Base. Must be greater than 0.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.ceilsd( 3.14159, 5, 10 )\n    3.1416\n    > y = base.ceilsd( 3.14159, 1, 10 )\n    4.0\n    > y = base.ceilsd( 12368.0, 2, 10 )\n    13000.0\n    > y = base.ceilsd( 0.0313, 2, 2 )\n    0.046875\n\n    See Also\n    --------\n    base.ceil, base.floorsd, base.roundsd, base.truncsd\n","base.cexp":"\nbase.cexp( z )\n    Evaluates the exponential function for a double-precision complex floating-\n    point number.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Complex number.\n\n    Examples\n    --------\n    > var y = base.cexp( new Complex128( 0.0, 0.0 ) )\n    <Complex128>\n    > var re = real( y )\n    1.0\n    > var im = imag( y )\n    0.0\n    > y = base.cexp( new Complex128( 0.0, 1.0 ) )\n    <Complex128>\n    > re = real( y )\n    ~0.540\n    > im = imag( y )\n    ~0.841\n\n","base.cflipsign":"\nbase.cflipsign( z, y )\n    Returns a double-precision complex floating-point number with the same\n    magnitude as `z` and the sign of `y*z`.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    y: number\n        Number from which to derive the sign.\n\n    Returns\n    -------\n    out: Complex128\n        Result.\n\n    Examples\n    --------\n    > var v = base.cflipsign( new Complex128( -4.2, 5.5 ), -9.0 )\n    <Complex128>\n    > var re = real( v )\n    4.2\n    > var im = imag( v )\n    -5.5\n\n    See Also\n    --------\n    base.cneg, base.csignum\n","base.cflipsignf":"\nbase.cflipsignf( z, y )\n    Returns a single-precision complex floating-point number with the same\n    magnitude as `z` and the sign of `y*z`.\n\n    Parameters\n    ----------\n    z: Complex64\n        Complex number.\n\n    y: number\n        Number from which to derive the sign.\n\n    Returns\n    -------\n    out: Complex64\n        Result.\n\n    Examples\n    --------\n    > var v = base.cflipsignf( new Complex64( -4.0, 5.0 ), -9.0 )\n    <Complex64>\n    > var re = realf( v )\n    4.0\n    > var im = imagf( v )\n    -5.0\n\n    See Also\n    --------\n    base.cnegf, base.cflipsign\n","base.cfloor":"\nbase.cfloor( z )\n    Rounds a double-precision complex floating-point number toward negative\n    infinity.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Result.\n\n    Examples\n    --------\n    > var v = base.cfloor( new Complex128( 5.5, 3.3 ) )\n    <Complex128>\n    > var re = real( v )\n    5.0\n    > var im = imag( v )\n    3.0\n\n    See Also\n    --------\n    base.cceil, base.cfloorn, base.cround\n","base.cfloorn":"\nbase.cfloorn( z, n )\n    Rounds each component of a double-precision complex floating-point number\n    to the nearest multiple of `10^n` toward negative infinity.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    n: integer\n        Integer power of 10.\n\n    Returns\n    -------\n    z: Complex128\n        Result.\n\n    Examples\n    --------\n    > var v = base.cfloorn( new Complex128( 5.555, -3.333 ), -2 )\n    <Complex128>\n    > var re = real( v )\n    5.55\n    > var im = imag( v )\n    -3.34\n\n    See Also\n    --------\n    base.cceiln, base.cfloor, base.croundn\n","base.cidentity":"\nbase.cidentity( z )\n    Evaluates the identity function for a double-precision complex floating-\n    point number.\n\n    Parameters\n    ----------\n    z: Complex128\n        Input value.\n\n    Returns\n    -------\n    v: Complex128\n        Input value.\n\n    Examples\n    --------\n    > var v = base.cidentity( new Complex128( -1.0, 2.0 ) )\n    <Complex128>\n    > var re = real( v )\n    -1.0\n    > var img = imag( v )\n    2.0\n\n    See Also\n    --------\n    base.cidentityf, base.identity\n","base.cidentityf":"\nbase.cidentityf( z )\n    Evaluates the identity function for a single-precision complex floating-\n    point number.\n\n    Parameters\n    ----------\n    z: Complex64\n        Input value.\n\n    Returns\n    -------\n    v: Complex64\n        Input value.\n\n    Examples\n    --------\n    > var v = base.cidentityf( new Complex64( -1.0, 2.0 ) )\n    <Complex64>\n    > var re = realf( v )\n    -1.0\n    > var img = imagf( v )\n    2.0\n\n    See Also\n    --------\n    base.cidentity, base.identityf\n","base.cinv":"\nbase.cinv( z )\n    Computes the inverse of a double-precision complex floating-point number.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Result.\n\n    Examples\n    --------\n    > var v = base.cinv( new Complex128( 2.0, 4.0 ) )\n    <Complex128>\n    > var re = real( v )\n    0.1\n    > var im = imag( v )\n    -0.2\n\n    See Also\n    --------\n    base.cdiv\n","base.clamp":"\nbase.clamp( v, min, max )\n    Restricts a double-precision floating-point number to a specified range.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    v: number\n        Value to restrict.\n\n    min: number\n        Minimum value.\n\n    max: number\n        Maximum value.\n\n    Returns\n    -------\n    y: number\n        Restricted value.\n\n    Examples\n    --------\n    > var y = base.clamp( 3.14, 0.0, 5.0 )\n    3.14\n    > y = base.clamp( -3.14, 0.0, 5.0 )\n    0.0\n    > y = base.clamp( 3.14, 0.0, 3.0 )\n    3.0\n    > y = base.clamp( -0.0, 0.0, 5.0 )\n    0.0\n    > y = base.clamp( 0.0, -3.14, -0.0 )\n    -0.0\n    > y = base.clamp( NaN, 0.0, 5.0 )\n    NaN\n\n    See Also\n    --------\n    base.clampf, base.wrap\n","base.clampf":"\nbase.clampf( v, min, max )\n    Restricts a single-precision floating-point number to a specified range.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    v: number\n        Value to restrict.\n\n    min: number\n        Minimum value.\n\n    max: number\n        Maximum value.\n\n    Returns\n    -------\n    y: number\n        Restricted value.\n\n    Examples\n    --------\n    > var y = base.clampf( 3.14, 0.0, 5.0 )\n    3.14\n    > y = base.clampf( -3.14, 0.0, 5.0 )\n    0.0\n    > y = base.clampf( 3.14, 0.0, 3.0 )\n    3.0\n    > y = base.clampf( -0.0, 0.0, 5.0 )\n    0.0\n    > y = base.clampf( 0.0, -3.14, -0.0 )\n    -0.0\n    > y = base.clampf( NaN, 0.0, 5.0 )\n    NaN\n\n    See Also\n    --------\n    base.clamp\n","base.cmul":"\nbase.cmul( z1, z2 )\n    Multiplies two double-precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    z1: Complex128\n        Complex number.\n\n    z2: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Result.\n\n    Examples\n    --------\n    > var z1 = new Complex128( 5.0, 3.0 )\n    <Complex128>\n    > var z2 = new Complex128( -2.0, 1.0 )\n    <Complex128>\n    > var out = base.cmul( z1, z2 )\n    <Complex128>\n    > var re = real( out )\n    -13.0\n    > var im = imag( out )\n    -1.0\n\n    See Also\n    --------\n    base.cadd, base.cdiv, base.csub\n","base.cmulf":"\nbase.cmulf( z1, z2 )\n    Multiplies two single-precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    z1: Complex64\n        Complex number.\n\n    z2: Complex64\n        Complex number.\n\n    Returns\n    -------\n    out: Complex64\n        Result.\n\n    Examples\n    --------\n    > var z1 = new Complex64( 5.0, 3.0 )\n    <Complex64>\n    > var z2 = new Complex64( -2.0, 1.0 )\n    <Complex64>\n    > var out = base.cmulf( z1, z2 )\n    <Complex64>\n    > var re = realf( out )\n    -13.0\n    > var im = imagf( out )\n    -1.0\n\n    See Also\n    --------\n    base.caddf, base.cmul, base.csubf\n","base.cneg":"\nbase.cneg( z )\n    Negates a double-precision complex floating-point number.\n\n    Parameters\n    ----------\n    z: Complex128\n       Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Result.\n\n    Examples\n    --------\n    > var z = new Complex128( -4.2, 5.5 )\n    <Complex128>\n    > var v = base.cneg( z )\n    <Complex128>\n    > var re = real( v )\n    4.2\n    > var im = imag( v )\n    -5.5\n\n    See Also\n    --------\n    base.cabs\n","base.cnegf":"\nbase.cnegf( z )\n    Negates a single-precision complex floating-point number.\n\n    Parameters\n    ----------\n    z: Complex64\n       Complex number.\n\n    Returns\n    -------\n    out: Complex64\n        Result.\n\n    Examples\n    --------\n    > var z = new Complex64( -4.0, 5.0 )\n    <Complex64>\n    > var v = base.cnegf( z )\n    <Complex64>\n    > var re = realf( v )\n    4.0\n    > var im = imagf( v )\n    -5.0\n\n    See Also\n    --------\n    base.cneg, base.cabsf\n","base.codePointAt":"\nbase.codePointAt( str, idx, backward )\n    Returns a Unicode code point from a string at a specified position.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    idx: integer\n        Position. If less than `0`, the string position is determined relative\n        to the end of the input string.\n\n    backward: boolean\n        Backward iteration for low surrogates.\n\n    Returns\n    -------\n    out: integer\n        Unicode code point.\n\n    Examples\n    --------\n    > var out = base.codePointAt( 'last man standing', 4, false )\n    32\n    > out = base.codePointAt( 'presidential election', 8, true )\n    116\n    > out = base.codePointAt( 'अनुच्छेद', 2, false )\n    2369\n    > out = base.codePointAt( '🌷', 1, true )\n    127799\n","base.constantcase":"\nbase.constantcase( str )\n    Converts a string to constant case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Constant-cased string.\n\n    Examples\n    --------\n    > var out = base.constantcase( 'Hello World!' )\n    'HELLO_WORLD'\n    > out = base.constantcase( 'I am a tiny little teapot' )\n    'I_AM_A_TINY_LITTLE_TEAPOT'\n\n    See Also\n    --------\n    base.camelcase, base.lowercase, base.snakecase, base.uppercase","base.continuedFraction":"\nbase.continuedFraction( generator[, options] )\n    Evaluates the continued fraction approximation for the supplied series\n    generator using the modified Lentz algorithm.\n\n    `generator` can be either a function which returns an array with two\n    elements, the `a` and `b` terms of the fraction, or an ES6 Generator object.\n\n    By default, the function computes\n\n             a1\n        ---------------\n        b1 +     a2\n             ----------\n              b2 +   a3\n                  -----\n                  b3 + ...\n\n    To evaluate\n\n        b0 +\t a1\n        ---------------\n        b1 +\t a2\n             ----------\n             b2 +  a3\n                  -----\n                  b3 + ...\n\n    set the `keep` option to `true`.\n\n    Parameters\n    ----------\n    generator: Function\n        Function returning terms of continued fraction expansion.\n\n    options: Object (optional)\n        Options.\n\n    options.maxIter: integer (optional)\n         Maximum number of iterations. Default: `1000000`.\n\n    options.tolerance: number (optional)\n        Further terms are only added as long as the next term is greater than\n        current term times the tolerance. Default: `2.22e-16`.\n\n    options.keep: boolean (optional)\n        Boolean indicating whether to keep the `b0` term in the continued\n        fraction. Default: `false`.\n\n    Returns\n    -------\n    out: number\n       Value of continued fraction.\n\n    Examples\n    --------\n    // Continued fraction for (e-1)^(-1):\n    > function closure() {\n    ...    var i = 0;\n    ...    return function() {\n    ...        i += 1;\n    ...        return [ i, i ];\n    ...    };\n    ... };\n    > var gen = closure();\n    > var out = base.continuedFraction( gen )\n    ~0.582\n\n    // Using an ES6 generator:\n    > function* generator() {\n    ...     var i = 0;\n    ...     while ( true ) {\n    ...         i += 1;\n    ...         yield [ i, i ];\n    ...     }\n    ... };\n    > gen = generator();\n    > out = base.continuedFraction( gen )\n    ~0.582\n\n    // Set options:\n    > out = base.continuedFraction( generator(), { 'keep': true } )\n    ~1.718\n    > out = base.continuedFraction( generator(), { 'maxIter': 10 } )\n    ~0.582\n    > out = base.continuedFraction( generator(), { 'tolerance': 1e-1 } )\n    ~0.579\n\n","base.copysign":"\nbase.copysign( x, y )\n    Returns a double-precision floating-point number with the magnitude of `x`\n    and the sign of `y`.\n\n    Parameters\n    ----------\n    x: number\n        Number from which to derive a magnitude.\n\n    y: number\n        Number from which to derive a sign.\n\n    Returns\n    -------\n    z: number\n        Double-precision floating-point number.\n\n    Examples\n    --------\n    > var z = base.copysign( -3.14, 10.0 )\n    3.14\n    > z = base.copysign( 3.14, -1.0 )\n    -3.14\n    > z = base.copysign( 1.0, -0.0 )\n    -1.0\n    > z = base.copysign( -3.14, -0.0 )\n    -3.14\n    > z = base.copysign( -0.0, 1.0 )\n    0.0\n\n    See Also\n    --------\n    base.flipsign\n","base.copysignf":"\nbase.copysignf( x, y )\n    Returns a single-precision floating-point number with the magnitude of `x`\n    and the sign of `y`.\n\n    Parameters\n    ----------\n    x: number\n        Number from which to derive a magnitude.\n\n    y: number\n        Number from which to derive a sign.\n\n    Returns\n    -------\n    z: number\n        Single-precision floating-point number.\n\n    Examples\n    --------\n    > var z = base.copysignf( -3.0, 10.0 )\n    3.0\n    > z = base.copysignf( 3.0, -1.0 )\n    -3.0\n    > z = base.copysignf( 1.0, -0.0 )\n    -1.0\n    > z = base.copysignf( -3.0, -0.0 )\n    -3.0\n    > z = base.copysignf( -0.0, 1.0 )\n    0.0\n\n    See Also\n    --------\n    base.copysign, base.flipsignf\n","base.cos":"\nbase.cos( x )\n    Computes the cosine of a number.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Cosine.\n\n    Examples\n    --------\n    > var y = base.cos( 0.0 )\n    1.0\n    > y = base.cos( PI/4.0 )\n    ~0.707\n    > y = base.cos( -PI/6.0 )\n    ~0.866\n    > y = base.cos( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cospi, base.cosm1, base.sin, base.tan\n","base.cosd":"\nbase.cosd( x )\n    Computes the cosine of an angle measured in degrees.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in degrees).\n\n    Returns\n    -------\n    y: number\n        Cosine.\n\n    Examples\n    --------\n    > var y = base.cosd( 0.0 )\n    1.0\n    > y = base.cosd( 90.0 )\n    0.0\n    > y = base.cosd( 60.0 )\n    ~0.5\n    > y = base.cosd( NaN )\n    NaN\n\n    See Also\n    --------\n    base.tand\n","base.cosh":"\nbase.cosh( x )\n    Computes the hyperbolic cosine of a double-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Hyperbolic cosine.\n\n    Examples\n    --------\n    > var y = base.cosh( 0.0 )\n    1.0\n    > y = base.cosh( 2.0 )\n    ~3.762\n    > y = base.cosh( -2.0 )\n    ~3.762\n    > y = base.cosh( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cos, base.sinh, base.tanh\n","base.cosm1":"\nbase.cosm1( x )\n    Computes the cosine of a number minus one.\n\n    This function should be used instead of manually calculating `cos(x)-1` when\n    `x` is near unity.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Cosine minus one.\n\n    Examples\n    --------\n    > var y = base.cosm1( 0.0 )\n    0.0\n    > y = base.cosm1( PI/4.0 )\n    ~-0.293\n    > y = base.cosm1( -PI/6.0 )\n    ~-0.134\n    > y = base.cosm1( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cos\n","base.cospi":"\nbase.cospi( x )\n    Computes the value of `cos(πx)`.\n\n    This function computes `cos(πx)` more accurately than the obvious approach,\n    especially for large `x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.cospi( 0.0 )\n    1.0\n    > y = base.cospi( 0.5 )\n    0.0\n    > y = base.cospi( 0.1 )\n    ~0.951\n    > y = base.cospi( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cos\n","base.cot":"\nbase.cot( x )\n    Computes the cotangent of a number.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Cotangent.\n\n    Examples\n    --------\n    > var y = base.cot( 0.0 )\n    Infinity\n    > y = base.cot( -PI/4.0 )\n    ~-1.0\n    > y = base.cot( PI/4.0 )\n    ~1.0\n    > y = base.cot( NaN )\n    NaN\n\n    See Also\n    --------\n    base.csc, base.tan\n","base.cotd":"\nbase.cotd( x )\n    Computes the cotangent of an angle measured in degrees.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in degrees).\n\n    Returns\n    -------\n    y: number\n        Cotangent.\n\n    Examples\n    --------\n    > var y = base.cotd( 0.0 )\n    Infinity\n    > y = base.cotd( 90.0 )\n    0.0\n    > y = base.cotd( 60.0 )\n    ~0.58\n    > y = base.cotd( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cscd, base.secd, base.tand\n","base.coth":"\nbase.coth( x )\n    Computes the hyperbolic cotangent of a number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Hyperbolic cotangent.\n\n    Examples\n    --------\n    > var y = base.coth( 0.0 )\n    Infinity\n    > y = base.coth( -0.0 )\n    -Infinity\n    > y = base.coth( 2.0 )\n    ~1.0373\n    > y = base.coth( -2.0 )\n    ~-1.0373\n    > y = base.coth( +Infinity )\n    ~1\n    > y = base.coth( -Infinity )\n    ~-1\n    > y = base.coth( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acoth, base.cot, base.csch, base.tanh\n","base.covercos":"\nbase.covercos( x )\n    Computes the coversed cosine.\n\n    The coversed cosine is defined as `1 + sin(x)`.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Coversed cosine.\n\n    Examples\n    --------\n    > var y = base.covercos( 3.14 )\n    ~1.0016\n    > y = base.covercos( -4.2 )\n    ~1.8716\n    > y = base.covercos( -4.6 )\n    ~1.9937\n    > y = base.covercos( 9.5 )\n    ~0.9248\n    > y = base.covercos( -0.0 )\n    1.0\n\n    See Also\n    --------\n    base.coversin, base.vercos\n","base.coversin":"\nbase.coversin( x )\n    Computes the coversed sine.\n\n    The coversed sine is defined as `1 - sin(x)`.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Coversed sine.\n\n    Examples\n    --------\n    > var y = base.coversin( 3.14 )\n    ~0.9984\n    > y = base.coversin( -4.2 )\n    ~0.1284\n    > y = base.coversin( -4.6 )\n    ~0.0063\n    > y = base.coversin( 9.5 )\n    ~1.0752\n    > y = base.coversin( -0.0 )\n    1.0\n\n    See Also\n    --------\n    base.covercos, base.versin\n","base.cphase":"\nbase.cphase( z )\n    Computes the argument of a double-precision complex floating-point number\n    in radians.\n\n    The argument of a complex number, also known as the phase, is the angle of\n    the radius extending from the origin to the complex number plotted in the\n    complex plane and the positive real axis.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    phi: number\n        Argument.\n\n    Examples\n    --------\n    > var phi = base.cphase( new Complex128( 5.0, 3.0 ) )\n    ~0.5404\n\n    See Also\n    --------\n    base.cabs\n","base.cpolar":"\nbase.cpolar( z )\n    Returns the absolute value and phase of a double-precision complex\n    floating-point number.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Array<number>\n        Absolute value and phase, respectively.\n\n    Examples\n    --------\n    > var out = base.cpolar( new Complex128( 5.0, 3.0 ) )\n    [ ~5.83, ~0.5404 ]\n\n\nbase.cpolar.assign( z, out, stride, offset )\n    Returns the absolute value and phase of a double-precision complex\n    floating-point number and assigns results to a provided output array.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    out: Array|TypedArray|Object\n        Destination array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Absolute value and phase, respectively.\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var v = base.cpolar.assign( new Complex128( 5.0, 3.0 ), out, 1, 0 )\n    <Float64Array>[ ~5.83, ~0.5404 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.cabs, base.cphase","base.cpolar.assign":"\nbase.cpolar.assign( z, out, stride, offset )\n    Returns the absolute value and phase of a double-precision complex\n    floating-point number and assigns results to a provided output array.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    out: Array|TypedArray|Object\n        Destination array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Absolute value and phase, respectively.\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var v = base.cpolar.assign( new Complex128( 5.0, 3.0 ), out, 1, 0 )\n    <Float64Array>[ ~5.83, ~0.5404 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.cabs, base.cphase","base.cround":"\nbase.cround( z )\n    Rounds each component of a double-precision complex floating-point number\n    to the nearest integer.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Rounded complex number.\n\n    Examples\n    --------\n    > var v = base.cround( new Complex128( 5.5, 3.3 ) )\n    <Complex128>\n    > var re = real( v )\n    6.0\n    > var im = imag( v )\n    3.0\n\n    See Also\n    --------\n    base.cceil, base.cfloor, base.croundn\n","base.croundn":"\nbase.croundn( z, n )\n    Rounds each component of a double-precision complex floating-point number\n    to the nearest multiple of `10^n`.\n\n    When operating on floating-point numbers in bases other than `2`, rounding\n    to specified digits can be inexact.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    n: integer\n        Integer power of 10.\n\n    Returns\n    -------\n    out: Complex128\n        Result.\n\n    Examples\n    --------\n    > var v = base.croundn( new Complex128( 5.555, -3.336 ), -2 )\n    <Complex128>\n    > var re = real( v )\n    5.56\n    > var im = imag( v )\n    -3.34\n\n    See Also\n    --------\n    base.cceiln, base.cfloorn, base.cround\n","base.csc":"\nbase.csc( x )\n    Computes the cosecant of a number.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Cosecant.\n\n    Examples\n    --------\n    > var y = base.csc( 0.0 )\n    Infinity\n    > y = base.csc( PI/2.0 )\n    ~1.0\n    > y = base.csc( -PI/6.0 )\n    ~-2.0\n    > y = base.csc( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cot, base.sin","base.cscd":"\nbase.cscd( x )\n    Computes the cosecant of a degree.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in degrees).\n\n    Returns\n    -------\n    y: number\n        Cosecant.\n\n    Examples\n    --------\n    > var y = base.cscd( 1.0 )\n    ~57.30\n    > y = base.cscd( PI )\n    ~18.25\n    > y = base.cscd( -PI )\n    ~-18.25\n    > y = base.cscd( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cotd, base.secd\n","base.csch":"\nbase.csch( x )\n    Computes the hyperbolic cosecant of a number.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Hyperbolic cosecant.\n\n    Examples\n    --------\n    > var y = base.csch( +0.0 )\n    +Infinity\n    > var y = base.csch( -0.0 )\n    -Infinity\n    > var y = base.csch( +Infinity )\n    +0.0\n    > var y = base.csch( -Infinity )\n    -0.0\n    > y = base.csch( 2.0 )\n    ~0.2757\n    > y = base.csch( -2.0 )\n    ~-0.2757\n    > y = base.csch( NaN )\n    NaN\n\n    See Also\n    --------\n    base.acsch, base.csc, base.coth, base.sinh\n","base.csignum":"\nbase.csignum( z )\n    Evaluates the signum function of a double-precision complex floating-point\n    number.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Result.\n\n    Examples\n    --------\n    > var v = base.csignum( new Complex128( -4.2, 5.5 ) )\n    <Complex128>\n    > var re = real( v )\n    -0.6069136033622302\n    > var im = imag( v )\n    0.79476781392673\n\n    See Also\n    --------\n    base.signum\n","base.csub":"\nbase.csub( z1, z2 )\n    Subtracts two double-precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    z1: Complex128\n        Complex number.\n\n    z2: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Result.\n\n    Examples\n    --------\n    > var z1 = new Complex128( 5.0, 3.0 )\n    <Complex128>\n    > var z2 = new Complex128( -2.0, 1.0 )\n    <Complex128>\n    > var out = base.csub( z1, z2 )\n    <Complex128>\n    > var re = real( out )\n    7.0\n    > var im = imag( out )\n    2.0\n\n    See Also\n    --------\n    base.cadd, base.cdiv, base.cmul\n","base.csubf":"\nbase.csubf( z1, z2 )\n    Subtracts two single-precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    z1: Complex64\n        Complex number.\n\n    z2: Complex64\n        Complex number.\n\n    Returns\n    -------\n    out: Complex64\n        Result.\n\n    Examples\n    --------\n    > var z1 = new Complex64( 5.0, 3.0 )\n    <Complex64>\n    > var z2 = new Complex64( -2.0, 1.0 )\n    <Complex64>\n    > var out = base.csubf( z1, z2 )\n    <Complex64>\n    > var re = realf( out )\n    7.0\n    > var im = imagf( out )\n    2.0\n\n    See Also\n    --------\n    base.caddf, base.cmulf, base.csub\n","base.deg2rad":"\nbase.deg2rad( x )\n    Converts an angle from degrees to radians.\n\n    Parameters\n    ----------\n    x: number\n        Angle in degrees.\n\n    Returns\n    -------\n    r: number\n        Angle in radians.\n\n    Examples\n    --------\n    > var r = base.deg2rad( 90.0 )\n    ~1.571\n    > r = base.deg2rad( -45.0 )\n    ~-0.785\n    > r = base.deg2rad( NaN )\n    NaN\n\n    See Also\n    --------\n    base.rad2deg\n","base.deg2radf":"\nbase.deg2radf( x )\n    Converts an angle from degrees to radians (single-precision).\n\n    Parameters\n    ----------\n    x: number\n        Angle in degrees.\n\n    Returns\n    -------\n    r: number\n        Angle in radians.\n\n    Examples\n    --------\n    > var r = base.deg2radf( 90.0 )\n    ~1.571\n    > r = base.deg2radf( -45.0 )\n    ~-0.785\n    > r = base.deg2radf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.deg2rad, base.rad2degf\n","base.digamma":"\nbase.digamma( x )\n    Evaluates the digamma function.\n\n    If `x` is zero or a negative integer, the function returns `NaN`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.digamma( -2.5 )\n    ~1.103\n    > y = base.digamma( 1.0 )\n    ~-0.577\n    > y = base.digamma( 10.0 )\n    ~2.252\n    > y = base.digamma( NaN )\n    NaN\n    > y = base.digamma( -1.0 )\n    NaN\n\n    See Also\n    --------\n    base.gamma, base.trigamma\n","base.diracDelta":"\nbase.diracDelta( x )\n    Evaluates the Dirac delta function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.diracDelta( 3.14 )\n    0.0\n    > y = base.diracDelta( 0.0 )\n    Infinity\n\n    See Also\n    --------\n    base.kroneckerDelta\n","base.div":"\nbase.div( x, y )\n    Divides two double-precision floating-point numbers `x` and `y`.\n\n    Parameters\n    ----------\n    x: number\n        First input value (dividend).\n\n    y: number\n        Second input value (divisor).\n\n    Returns\n    -------\n    z: number\n        Result.\n\n    Examples\n    --------\n    > var v = base.div( -1.0, 5.0 )\n    -0.2\n    > v = base.div( 2.0, 5.0 )\n    0.4\n    > v = base.div( 0.0, 5.0 )\n    0.0\n    > v = base.div( -0.0, 5.0 )\n    -0.0\n    > v = base.div( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.add, base.mul, base.sub\n","base.divf":"\nbase.divf( x, y )\n    Divides two single-precision floating-point numbers `x` and `y`.\n\n    Parameters\n    ----------\n    x: number\n        First input value (dividend).\n\n    y: number\n        Second input value (divisor).\n\n    Returns\n    -------\n    z: number\n        Result.\n\n    Examples\n    --------\n    > var v = base.divf( -1.0, 5.0 )\n    ~-0.2\n    > v = base.divf( 2.0, 5.0 )\n    ~0.4\n    > v = base.divf( 0.0, 5.0 )\n    0.0\n    > v = base.divf( -0.0, 5.0 )\n    -0.0\n    > v = base.divf( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.addf, base.div, base.mulf, base.subf\n","base.dotcase":"\nbase.dotcase( str )\n    Converts a string to dot case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Dot-cased string.\n\n    Examples\n    --------\n    > var out = base.dotcase( 'Hello World!' )\n    'hello.world'\n    > out = base.dotcase( 'I am a tiny little teapot' )\n    'i.am.a.tiny.little.teapot'\n\n    See Also\n    --------\n    base.camelcase, base.lowercase, base.snakecase, base.uppercase","base.dists.arcsine.Arcsine":"\nbase.dists.arcsine.Arcsine( [a, b] )\n    Returns an arcsine distribution object.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support. Must be less than `b`. Default: `0.0`.\n\n    b: number (optional)\n        Maximum support. Must be greater than `a`. Default: `1.0`.\n\n    Returns\n    -------\n    arcsine: Object\n        Distribution instance.\n\n    arcsine.a: number\n        Minimum support. If set, the value must be less than `b`.\n\n    arcsine.b: number\n        Maximum support. If set, the value must be greater than `a`.\n\n    arcsine.entropy: number\n        Read-only property which returns the differential entropy.\n\n    arcsine.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    arcsine.mean: number\n        Read-only property which returns the expected value.\n\n    arcsine.median: number\n        Read-only property which returns the median.\n\n    arcsine.mode: number\n        Read-only property which returns the mode.\n\n    arcsine.skewness: number\n        Read-only property which returns the skewness.\n\n    arcsine.stdev: number\n        Read-only property which returns the standard deviation.\n\n    arcsine.variance: number\n        Read-only property which returns the variance.\n\n    arcsine.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    arcsine.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    arcsine.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    arcsine.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    arcsine.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var arcsine = base.dists.arcsine.Arcsine( 0.0, 1.0 );\n    > arcsine.a\n    0.0\n    > arcsine.b\n    1.0\n    > arcsine.entropy\n    ~-0.242\n    > arcsine.kurtosis\n    -1.5\n    > arcsine.mean\n    0.5\n    > arcsine.median\n    0.5\n    > arcsine.mode\n    0.0\n    > arcsine.skewness\n    0.0\n    > arcsine.stdev\n    ~0.354\n    > arcsine.variance\n    0.125\n    > arcsine.cdf( 0.8 )\n    ~0.705\n    > arcsine.logcdf( 0.8 )\n    ~-0.35\n    > arcsine.logpdf( 0.4 )\n    ~-0.431\n    > arcsine.pdf( 0.8 )\n    ~0.796\n    > arcsine.quantile( 0.8 )\n    ~0.905\n\n","base.dists.arcsine.cdf":"\nbase.dists.arcsine.cdf( x, a, b )\n    Evaluates the cumulative distribution function (CDF) for an arcsine\n    distribution with minimum support `a` and maximum support `b` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.arcsine.cdf( 9.0, 0.0, 10.0 )\n    ~0.795\n    > y = base.dists.arcsine.cdf( 0.5, 0.0, 2.0 )\n    ~0.333\n    > y = base.dists.arcsine.cdf( PINF, 2.0, 4.0 )\n    1.0\n    > y = base.dists.arcsine.cdf( NINF, 2.0, 4.0 )\n    0.0\n    > y = base.dists.arcsine.cdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.arcsine.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.arcsine.cdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.arcsine.cdf( 2.0, 1.0, 0.0 )\n    NaN\n\n\nbase.dists.arcsine.cdf.factory( a, b )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an arcsine distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.arcsine.cdf.factory( 0.0, 10.0 );\n    > var y = mycdf( 0.5 )\n    ~0.144\n    > y = mycdf( 8.0 )\n    ~0.705\n\n","base.dists.arcsine.cdf.factory":"\nbase.dists.arcsine.cdf.factory( a, b )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an arcsine distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.arcsine.cdf.factory( 0.0, 10.0 );\n    > var y = mycdf( 0.5 )\n    ~0.144\n    > y = mycdf( 8.0 )\n    ~0.705","base.dists.arcsine.entropy":"\nbase.dists.arcsine.entropy( a, b )\n    Returns the differential entropy of an arcsine distribution (in nats).\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.arcsine.entropy( 0.0, 1.0 )\n    ~-0.242\n    > v = base.dists.arcsine.entropy( 4.0, 12.0 )\n    ~1.838\n    > v = base.dists.arcsine.entropy( 2.0, 8.0 )\n    ~1.55\n\n","base.dists.arcsine.kurtosis":"\nbase.dists.arcsine.kurtosis( a, b )\n    Returns the excess kurtosis of an arcsine distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.arcsine.kurtosis( 0.0, 1.0 )\n    -1.5\n    > v = base.dists.arcsine.kurtosis( 4.0, 12.0 )\n    -1.5\n    > v = base.dists.arcsine.kurtosis( 2.0, 8.0 )\n    -1.5\n\n","base.dists.arcsine.logcdf":"\nbase.dists.arcsine.logcdf( x, a, b )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for an\n    arcsine distribution with minimum support `a` and maximum support `b` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.arcsine.logcdf( 9.0, 0.0, 10.0 )\n    ~-0.229\n    > y = base.dists.arcsine.logcdf( 0.5, 0.0, 2.0 )\n    ~-1.1\n    > y = base.dists.arcsine.logcdf( PINF, 2.0, 4.0 )\n    0.0\n    > y = base.dists.arcsine.logcdf( NINF, 2.0, 4.0 )\n    -Infinity\n    > y = base.dists.arcsine.logcdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.arcsine.logcdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.arcsine.logcdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.arcsine.logcdf( 2.0, 1.0, 0.0 )\n    NaN\n\n\nbase.dists.arcsine.logcdf.factory( a, b )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of an arcsine distribution with minimum support\n    `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.arcsine.logcdf.factory( 0.0, 10.0 );\n    > var y = mylogcdf( 0.5 )\n    ~-1.941\n    > y = mylogcdf( 8.0 )\n    ~-0.35\n\n","base.dists.arcsine.logcdf.factory":"\nbase.dists.arcsine.logcdf.factory( a, b )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of an arcsine distribution with minimum support\n    `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.arcsine.logcdf.factory( 0.0, 10.0 );\n    > var y = mylogcdf( 0.5 )\n    ~-1.941\n    > y = mylogcdf( 8.0 )\n    ~-0.35","base.dists.arcsine.logpdf":"\nbase.dists.arcsine.logpdf( x, a, b )\n    Evaluates the logarithm of the probability density function (PDF) for an\n    arcsine distribution with minimum support `a` and maximum support `b` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.arcsine.logpdf( 2.0, 0.0, 4.0 )\n    ~-1.838\n    > y = base.dists.arcsine.logpdf( 5.0, 0.0, 4.0 )\n    -Infinity\n    > y = base.dists.arcsine.logpdf( 0.25, 0.0, 1.0 )\n    ~-0.308\n    > y = base.dists.arcsine.logpdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.arcsine.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.arcsine.logpdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.arcsine.logpdf( 2.0, 3.0, 1.0 )\n    NaN\n\n\nbase.dists.arcsine.logpdf.factory( a, b )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of an arcsine distribution with minimum support `a` and\n    maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.arcsine.logpdf.factory( 6.0, 7.0 );\n    > var y = mylogPDF( 7.0 )\n    Infinity\n    > y = mylogPDF( 5.0 )\n    -Infinity\n\n","base.dists.arcsine.logpdf.factory":"\nbase.dists.arcsine.logpdf.factory( a, b )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of an arcsine distribution with minimum support `a` and\n    maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.arcsine.logpdf.factory( 6.0, 7.0 );\n    > var y = mylogPDF( 7.0 )\n    Infinity\n    > y = mylogPDF( 5.0 )\n    -Infinity","base.dists.arcsine.mean":"\nbase.dists.arcsine.mean( a, b )\n    Returns the expected value of an arcsine distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.arcsine.mean( 0.0, 1.0 )\n    0.5\n    > v = base.dists.arcsine.mean( 4.0, 12.0 )\n    8.0\n    > v = base.dists.arcsine.mean( 2.0, 8.0 )\n    5.0\n\n","base.dists.arcsine.median":"\nbase.dists.arcsine.median( a, b )\n    Returns the median of an arcsine distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.arcsine.median( 0.0, 1.0 )\n    0.5\n    > v = base.dists.arcsine.median( 4.0, 12.0 )\n    8.0\n    > v = base.dists.arcsine.median( 2.0, 8.0 )\n    5.0\n\n","base.dists.arcsine.mode":"\nbase.dists.arcsine.mode( a, b )\n    Returns the mode of an arcsine distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.arcsine.mode( 0.0, 1.0 )\n    0.0\n    > v = base.dists.arcsine.mode( 4.0, 12.0 )\n    4.0\n    > v = base.dists.arcsine.mode( 2.0, 8.0 )\n    2.0\n\n","base.dists.arcsine.pdf":"\nbase.dists.arcsine.pdf( x, a, b )\n    Evaluates the probability density function (PDF) for an arcsine distribution\n    with minimum support `a` and maximum support `b` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.arcsine.pdf( 2.0, 0.0, 4.0 )\n    ~0.159\n    > y = base.dists.arcsine.pdf( 5.0, 0.0, 4.0 )\n    0.0\n    > y = base.dists.arcsine.pdf( 0.25, 0.0, 1.0 )\n    ~0.735\n    > y = base.dists.arcsine.pdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.arcsine.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.arcsine.pdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.arcsine.pdf( 2.0, 3.0, 1.0 )\n    NaN\n\n\nbase.dists.arcsine.pdf.factory( a, b )\n    Returns a function for evaluating the probability density function (PDF) of\n    an arcsine distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.arcsine.pdf.factory( 6.0, 7.0 );\n    > var y = myPDF( 7.0 )\n    Infinity\n    > y = myPDF( 5.0 )\n    0.0\n\n","base.dists.arcsine.pdf.factory":"\nbase.dists.arcsine.pdf.factory( a, b )\n    Returns a function for evaluating the probability density function (PDF) of\n    an arcsine distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.arcsine.pdf.factory( 6.0, 7.0 );\n    > var y = myPDF( 7.0 )\n    Infinity\n    > y = myPDF( 5.0 )\n    0.0","base.dists.arcsine.quantile":"\nbase.dists.arcsine.quantile( p, a, b )\n    Evaluates the quantile function for an arcsine distribution with minimum\n    support `a` and maximum support `b` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.arcsine.quantile( 0.8, 0.0, 1.0 )\n    ~0.905\n    > y = base.dists.arcsine.quantile( 0.5, 0.0, 10.0 )\n    ~5.0\n\n    > y = base.dists.arcsine.quantile( 1.1, 0.0, 1.0 )\n    NaN\n    > y = base.dists.arcsine.quantile( -0.2, 0.0, 1.0 )\n    NaN\n\n    > y = base.dists.arcsine.quantile( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.arcsine.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.arcsine.quantile( 0.0, 0.0, NaN )\n    NaN\n\n    > y = base.dists.arcsine.quantile( 0.5, 2.0, 1.0 )\n    NaN\n\n\nbase.dists.arcsine.quantile.factory( a, b )\n    Returns a function for evaluating the quantile function of an arcsine\n    distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.arcsine.quantile.factory( 0.0, 4.0 );\n    > var y = myQuantile( 0.8 )\n    ~3.618\n\n","base.dists.arcsine.quantile.factory":"\nbase.dists.arcsine.quantile.factory( a, b )\n    Returns a function for evaluating the quantile function of an arcsine\n    distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.arcsine.quantile.factory( 0.0, 4.0 );\n    > var y = myQuantile( 0.8 )\n    ~3.618","base.dists.arcsine.skewness":"\nbase.dists.arcsine.skewness( a, b )\n    Returns the skewness of an arcsine distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.arcsine.skewness( 0.0, 1.0 )\n    0.0\n    > v = base.dists.arcsine.skewness( 4.0, 12.0 )\n    0.0\n    > v = base.dists.arcsine.skewness( 2.0, 8.0 )\n    0.0\n\n","base.dists.arcsine.stdev":"\nbase.dists.arcsine.stdev( a, b )\n    Returns the standard deviation of an arcsine distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.arcsine.stdev( 0.0, 1.0 )\n    ~0.354\n    > v = base.dists.arcsine.stdev( 4.0, 12.0 )\n    ~2.828\n    > v = base.dists.arcsine.stdev( 2.0, 8.0 )\n    ~2.121\n\n","base.dists.arcsine.variance":"\nbase.dists.arcsine.variance( a, b )\n    Returns the variance of an arcsine distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.arcsine.variance( 0.0, 1.0 )\n    ~0.125\n    > v = base.dists.arcsine.variance( 4.0, 12.0 )\n    8.0\n    > v = base.dists.arcsine.variance( 2.0, 8.0 )\n    ~4.5\n\n","base.dists.bernoulli.Bernoulli":"\nbase.dists.bernoulli.Bernoulli( [p] )\n    Returns a Bernoulli distribution object.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability. Must be between `0` and `1`. Default: `0.5`.\n\n    Returns\n    -------\n    bernoulli: Object\n        Distribution instance.\n\n    bernoulli.p: number\n        Success probability. If set, the value must be between `0` and `1`.\n\n    bernoulli.entropy: number\n        Read-only property which returns the differential entropy.\n\n    bernoulli.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    bernoulli.mean: number\n        Read-only property which returns the expected value.\n\n    bernoulli.median: number\n        Read-only property which returns the median.\n\n    bernoulli.skewness: number\n        Read-only property which returns the skewness.\n\n    bernoulli.stdev: number\n        Read-only property which returns the standard deviation.\n\n    bernoulli.variance: number\n        Read-only property which returns the variance.\n\n    bernoulli.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    bernoulli.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    bernoulli.pmf: Function\n        Evaluates the probability mass function (PMF).\n\n    bernoulli.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var bernoulli = base.dists.bernoulli.Bernoulli( 0.6 );\n    > bernoulli.p\n    0.6\n    > bernoulli.entropy\n    ~0.673\n    > bernoulli.kurtosis\n    ~-1.833\n    > bernoulli.mean\n    0.6\n    > bernoulli.median\n    1.0\n    > bernoulli.skewness\n    ~-0.408\n    > bernoulli.stdev\n    ~0.49\n    > bernoulli.variance\n    ~0.24\n    > bernoulli.cdf( 0.5 )\n    0.4\n    > bernoulli.mgf( 3.0 )\n    ~12.451\n    > bernoulli.pmf( 0.0 )\n    0.4\n    > bernoulli.quantile( 0.7 )\n    1.0\n\n","base.dists.bernoulli.cdf":"\nbase.dists.bernoulli.cdf( x, p )\n    Evaluates the cumulative distribution function (CDF) for a Bernoulli\n    distribution with success probability `p` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.bernoulli.cdf( 0.5, 0.5 )\n    0.5\n    > y = base.dists.bernoulli.cdf( 0.8, 0.1 )\n    0.9\n    > y = base.dists.bernoulli.cdf( -1.0, 0.4 )\n    0.0\n    > y = base.dists.bernoulli.cdf( 1.5, 0.4 )\n    1.0\n    > y = base.dists.bernoulli.cdf( NaN, 0.5 )\n    NaN\n    > y = base.dists.bernoulli.cdf( 0.0, NaN )\n    NaN\n    // Invalid probability:\n    > y = base.dists.bernoulli.cdf( 2.0, 1.4 )\n    NaN\n\n\nbase.dists.bernoulli.cdf.factory( p )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Bernoulli distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.bernoulli.cdf.factory( 0.5 );\n    > var y = mycdf( 3.0 )\n    1.0\n    > y = mycdf( 0.7 )\n    0.5\n\n","base.dists.bernoulli.cdf.factory":"\nbase.dists.bernoulli.cdf.factory( p )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Bernoulli distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.bernoulli.cdf.factory( 0.5 );\n    > var y = mycdf( 3.0 )\n    1.0\n    > y = mycdf( 0.7 )\n    0.5","base.dists.bernoulli.entropy":"\nbase.dists.bernoulli.entropy( p )\n    Returns the entropy of a Bernoulli distribution with success probability\n    `p` (in nats).\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.bernoulli.entropy( 0.1 )\n    ~0.325\n    > v = base.dists.bernoulli.entropy( 0.5 )\n    ~0.693\n\n","base.dists.bernoulli.kurtosis":"\nbase.dists.bernoulli.kurtosis( p )\n    Returns the excess kurtosis of a Bernoulli distribution with success\n    probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.bernoulli.kurtosis( 0.1 )\n    ~5.111\n    > v = base.dists.bernoulli.kurtosis( 0.5 )\n    -2.0\n\n","base.dists.bernoulli.mean":"\nbase.dists.bernoulli.mean( p )\n    Returns the expected value of a Bernoulli distribution with success\n    probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.bernoulli.mean( 0.1 )\n    0.1\n    > v = base.dists.bernoulli.mean( 0.5 )\n    0.5\n\n","base.dists.bernoulli.median":"\nbase.dists.bernoulli.median( p )\n    Returns the median of a Bernoulli distribution with success probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: integer\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.bernoulli.median( 0.1 )\n    0\n    > v = base.dists.bernoulli.median( 0.8 )\n    1\n\n","base.dists.bernoulli.mgf":"\nbase.dists.bernoulli.mgf( t, p )\n    Evaluates the moment-generating function (MGF) for a Bernoulli\n    distribution with success probability `p` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.bernoulli.mgf( 0.2, 0.5 )\n    ~1.111\n    > y = base.dists.bernoulli.mgf( 0.4, 0.5 )\n    ~1.246\n    > y = base.dists.bernoulli.mgf( NaN, 0.0 )\n    NaN\n    > y = base.dists.bernoulli.mgf( 0.0, NaN )\n    NaN\n    > y = base.dists.bernoulli.mgf( -2.0, -1.0 )\n    NaN\n    > y = base.dists.bernoulli.mgf( 0.2, 2.0 )\n    NaN\n\n\nbase.dists.bernoulli.mgf.factory( p )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Bernoulli distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.bernoulli.mgf.factory( 0.8 );\n    > var y = mymgf( -0.2 )\n    ~0.855\n\n","base.dists.bernoulli.mgf.factory":"\nbase.dists.bernoulli.mgf.factory( p )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Bernoulli distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.bernoulli.mgf.factory( 0.8 );\n    > var y = mymgf( -0.2 )\n    ~0.855","base.dists.bernoulli.mode":"\nbase.dists.bernoulli.mode( p )\n    Returns the mode of a Bernoulli distribution with success probability `p`.\n\n    For `p = 0.5`, the mode is either `0` or `1`. This implementation returns\n    `0` for `p = 0.5`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: integer\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.bernoulli.mode( 0.1 )\n    0\n    > v = base.dists.bernoulli.mode( 0.8 )\n    1\n\n","base.dists.bernoulli.pmf":"\nbase.dists.bernoulli.pmf( x, p )\n    Evaluates the probability mass function (PMF) for a Bernoulli distribution\n    with success probability `p` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated PMF.\n\n    Examples\n    --------\n    > var y = base.dists.bernoulli.pmf( 1.0, 0.3 )\n    0.3\n    > y = base.dists.bernoulli.pmf( 0.0, 0.7 )\n    0.3\n    > y = base.dists.bernoulli.pmf( -1.0, 0.5 )\n    0.0\n    > y = base.dists.bernoulli.pmf( 0.0, NaN )\n    NaN\n    > y = base.dists.bernoulli.pmf( NaN, 0.5 )\n    NaN\n    // Invalid success probability:\n    > y = base.dists.bernoulli.pmf( 0.0, 1.5 )\n    NaN\n\n\nbase.dists.bernoulli.pmf.factory( p )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    Bernoulli distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var mypmf = base.dists.bernoulli.pmf.factory( 0.5 );\n    > var y = mypmf( 1.0 )\n    0.5\n    > y = mypmf( 0.0 )\n    0.5\n\n","base.dists.bernoulli.pmf.factory":"\nbase.dists.bernoulli.pmf.factory( p )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    Bernoulli distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var mypmf = base.dists.bernoulli.pmf.factory( 0.5 );\n    > var y = mypmf( 1.0 )\n    0.5\n    > y = mypmf( 0.0 )\n    0.5","base.dists.bernoulli.quantile":"\nbase.dists.bernoulli.quantile( r, p )\n    Evaluates the quantile function for a Bernoulli distribution with success\n    probability `p` at a probability `r`.\n\n    If `r < 0` or `r > 1`, the function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    r: number\n        Input probability.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.bernoulli.quantile( 0.8, 0.4 )\n    1\n    > y = base.dists.bernoulli.quantile( 0.5, 0.4 )\n    0\n    > y = base.dists.bernoulli.quantile( 0.9, 0.1 )\n    0\n\n    > y = base.dists.bernoulli.quantile( -0.2, 0.1 )\n    NaN\n\n    > y = base.dists.bernoulli.quantile( NaN, 0.8 )\n    NaN\n    > y = base.dists.bernoulli.quantile( 0.4, NaN )\n    NaN\n\n    > y = base.dists.bernoulli.quantile( 0.5, -1.0 )\n    NaN\n    > y = base.dists.bernoulli.quantile( 0.5, 1.5 )\n    NaN\n\n\nbase.dists.bernoulli.quantile.factory( p )\n    Returns a function for evaluating the quantile function of a Bernoulli\n    distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.bernoulli.quantile.factory( 0.4 );\n    > var y = myquantile( 0.4 )\n    0\n    > y = myquantile( 0.8 )\n    1\n    > y = myquantile( 1.0 )\n    1\n\n","base.dists.bernoulli.quantile.factory":"\nbase.dists.bernoulli.quantile.factory( p )\n    Returns a function for evaluating the quantile function of a Bernoulli\n    distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.bernoulli.quantile.factory( 0.4 );\n    > var y = myquantile( 0.4 )\n    0\n    > y = myquantile( 0.8 )\n    1\n    > y = myquantile( 1.0 )\n    1","base.dists.bernoulli.skewness":"\nbase.dists.bernoulli.skewness( p )\n    Returns the skewness of a Bernoulli distribution with success probability\n    `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.bernoulli.skewness( 0.1 )\n    ~2.667\n    > v = base.dists.bernoulli.skewness( 0.5 )\n    0.0\n\n","base.dists.bernoulli.stdev":"\nbase.dists.bernoulli.stdev( p )\n    Returns the standard deviation of a Bernoulli distribution with success\n    probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.bernoulli.stdev( 0.1 )\n    ~0.3\n    > v = base.dists.bernoulli.stdev( 0.5 )\n    0.5\n\n","base.dists.bernoulli.variance":"\nbase.dists.bernoulli.variance( p )\n    Returns the variance of a Bernoulli distribution with success probability\n    `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.bernoulli.variance( 0.1 )\n    ~0.09\n    > v = base.dists.bernoulli.variance( 0.5 )\n    0.25\n\n","base.dists.beta.Beta":"\nbase.dists.beta.Beta( [α, β] )\n    Returns a beta distribution object.\n\n    Parameters\n    ----------\n    α: number (optional)\n        First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n    β: number (optional)\n        Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    beta: Object\n        Distribution instance.\n\n    beta.alpha: number\n        First shape parameter. If set, the value must be greater than `0`.\n\n    beta.beta: number\n        Second shape parameter. If set, the value must be greater than `0`.\n\n    beta.entropy: number\n        Read-only property which returns the differential entropy.\n\n    beta.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    beta.mean: number\n        Read-only property which returns the expected value.\n\n    beta.median: number\n        Read-only property which returns the median.\n\n    beta.mode: number\n        Read-only property which returns the mode.\n\n    beta.skewness: number\n        Read-only property which returns the skewness.\n\n    beta.stdev: number\n        Read-only property which returns the standard deviation.\n\n    beta.variance: number\n        Read-only property which returns the variance.\n\n    beta.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    beta.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    beta.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    beta.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    beta.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    beta.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var beta = base.dists.beta.Beta( 1.0, 1.0 );\n    > beta.alpha\n    1.0\n    > beta.beta\n    1.0\n    > beta.entropy\n    0.0\n    > beta.kurtosis\n    -1.2\n    > beta.mean\n    0.5\n    > beta.median\n    0.5\n    > beta.mode\n    NaN\n    > beta.skewness\n    0.0\n    > beta.stdev\n    ~0.289\n    > beta.variance\n    ~0.0833\n    > beta.cdf( 0.8 )\n    0.8\n    > beta.logcdf( 0.8 )\n    ~-0.223\n    > beta.logpdf( 1.0 )\n    0.0\n    > beta.mgf( 3.14 )\n    ~7.0394\n    > beta.pdf( 1.0 )\n    1.0\n    > beta.quantile( 0.8 )\n    0.8\n\n","base.dists.beta.cdf":"\nbase.dists.beta.cdf( x, α, β )\n    Evaluates the cumulative distribution function (CDF) for a beta distribution\n    with first shape parameter `α` and second shape parameter `β` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.beta.cdf( 0.5, 1.0, 1.0 )\n    0.5\n    > y = base.dists.beta.cdf( 0.5, 2.0, 4.0 )\n    ~0.813\n    > y = base.dists.beta.cdf( 0.2, 2.0, 2.0 )\n    ~0.104\n    > y = base.dists.beta.cdf( 0.8, 4.0, 4.0 )\n    ~0.967\n    > y = base.dists.beta.cdf( -0.5, 4.0, 2.0 )\n    0.0\n    > y = base.dists.beta.cdf( 1.5, 4.0, 2.0 )\n    1.0\n\n    > y = base.dists.beta.cdf( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.beta.cdf( 2.0, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.beta.cdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.beta.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.beta.cdf( 0.0, 1.0, NaN )\n    NaN\n\n\nbase.dists.beta.cdf.factory( α, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a beta distribution with first shape parameter `α` and second shape\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.beta.cdf.factory( 0.5, 0.5 );\n    > var y = mycdf( 0.8 )\n    ~0.705\n    > y = mycdf( 0.3 )\n    ~0.369\n\n","base.dists.beta.cdf.factory":"\nbase.dists.beta.cdf.factory( α, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a beta distribution with first shape parameter `α` and second shape\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.beta.cdf.factory( 0.5, 0.5 );\n    > var y = mycdf( 0.8 )\n    ~0.705\n    > y = mycdf( 0.3 )\n    ~0.369","base.dists.beta.entropy":"\nbase.dists.beta.entropy( α, β )\n    Returns the differential entropy of a beta distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Differential entropy.\n\n    Examples\n    --------\n    > var v = base.dists.beta.entropy( 1.0, 1.0 )\n    0.0\n    > v = base.dists.beta.entropy( 4.0, 12.0 )\n    ~-0.869\n    > v = base.dists.beta.entropy( 8.0, 2.0 )\n    ~-0.795\n\n    > v = base.dists.beta.entropy( 1.0, -0.1 )\n    NaN\n    > v = base.dists.beta.entropy( -0.1, 1.0 )\n    NaN\n\n    > v = base.dists.beta.entropy( 2.0, NaN )\n    NaN\n    > v = base.dists.beta.entropy( NaN, 2.0 )\n    NaN\n\n","base.dists.beta.kurtosis":"\nbase.dists.beta.kurtosis( α, β )\n    Returns the excess kurtosis of a beta distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.beta.kurtosis( 1.0, 1.0 )\n    -1.2\n    > v = base.dists.beta.kurtosis( 4.0, 12.0 )\n    ~0.082\n    > v = base.dists.beta.kurtosis( 8.0, 2.0 )\n    ~0.490\n\n    > v = base.dists.beta.kurtosis( 1.0, -0.1 )\n    NaN\n    > v = base.dists.beta.kurtosis( -0.1, 1.0 )\n    NaN\n\n    > v = base.dists.beta.kurtosis( 2.0, NaN )\n    NaN\n    > v = base.dists.beta.kurtosis( NaN, 2.0 )\n    NaN\n\n","base.dists.beta.logcdf":"\nbase.dists.beta.logcdf( x, α, β )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a beta distribution with first shape parameter `α` and second\n    shape parameter `β` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.beta.logcdf( 0.5, 1.0, 1.0 )\n    ~-0.693\n    > y = base.dists.beta.logcdf( 0.5, 2.0, 4.0 )\n    ~-0.208\n    > y = base.dists.beta.logcdf( 0.2, 2.0, 2.0 )\n    ~-2.263\n    > y = base.dists.beta.logcdf( 0.8, 4.0, 4.0 )\n    ~-0.034\n    > y = base.dists.beta.logcdf( -0.5, 4.0, 2.0 )\n    -Infinity\n    > y = base.dists.beta.logcdf( 1.5, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.beta.logcdf( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.beta.logcdf( 2.0, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.beta.logcdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.beta.logcdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.beta.logcdf( 0.0, 1.0, NaN )\n    NaN\n\n\nbase.dists.beta.logcdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a beta distribution with first shape\n    parameter `α` and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.beta.logcdf.factory( 0.5, 0.5 );\n    > var y = mylogcdf( 0.8 )\n    ~-0.35\n    > y = mylogcdf( 0.3 )\n    ~-0.997\n\n","base.dists.beta.logcdf.factory":"\nbase.dists.beta.logcdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a beta distribution with first shape\n    parameter `α` and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.beta.logcdf.factory( 0.5, 0.5 );\n    > var y = mylogcdf( 0.8 )\n    ~-0.35\n    > y = mylogcdf( 0.3 )\n    ~-0.997","base.dists.beta.logpdf":"\nbase.dists.beta.logpdf( x, α, β )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a beta distribution with first shape parameter `α` and second shape\n    parameter `β` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Natural logarithm of the PDF.\n\n    Examples\n    --------\n    > var y = base.dists.beta.logpdf( 0.5, 1.0, 1.0 )\n    0.0\n    > y = base.dists.beta.logpdf( 0.5, 2.0, 4.0 )\n    ~0.223\n    > y = base.dists.beta.logpdf( 0.2, 2.0, 2.0 )\n    ~-0.041\n    > y = base.dists.beta.logpdf( 0.8, 4.0, 4.0 )\n    ~-0.556\n    > y = base.dists.beta.logpdf( -0.5, 4.0, 2.0 )\n    -Infinity\n    > y = base.dists.beta.logpdf( 1.5, 4.0, 2.0 )\n    -Infinity\n\n    > y = base.dists.beta.logpdf( 0.5, -1.0, 0.5 )\n    NaN\n    > y = base.dists.beta.logpdf( 0.5, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.beta.logpdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.beta.logpdf( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.dists.beta.logpdf( 0.5, 1.0, NaN )\n    NaN\n\n\nbase.dists.beta.logpdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a beta distribution with first shape parameter `α`\n    and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    fcn: Function\n        Function to evaluate the natural logarithm of the PDF.\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.beta.logpdf.factory( 0.5, 0.5 );\n    > var y = mylogpdf( 0.8 )\n    ~-0.228\n    > y = mylogpdf( 0.3 )\n    ~-0.364\n\n","base.dists.beta.logpdf.factory":"\nbase.dists.beta.logpdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a beta distribution with first shape parameter `α`\n    and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    fcn: Function\n        Function to evaluate the natural logarithm of the PDF.\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.beta.logpdf.factory( 0.5, 0.5 );\n    > var y = mylogpdf( 0.8 )\n    ~-0.228\n    > y = mylogpdf( 0.3 )\n    ~-0.364","base.dists.beta.mean":"\nbase.dists.beta.mean( α, β )\n    Returns the expected value of a beta distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.beta.mean( 1.0, 1.0 )\n    0.5\n    > v = base.dists.beta.mean( 4.0, 12.0 )\n    0.25\n    > v = base.dists.beta.mean( 8.0, 2.0 )\n    0.8\n\n","base.dists.beta.median":"\nbase.dists.beta.median( α, β )\n    Returns the median of a beta distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.beta.median( 1.0, 1.0 )\n    0.5\n    > v = base.dists.beta.median( 4.0, 12.0 )\n    ~0.239\n    > v = base.dists.beta.median( 8.0, 2.0 )\n    ~0.820\n\n    > v = base.dists.beta.median( 1.0, -0.1 )\n    NaN\n    > v = base.dists.beta.median( -0.1, 1.0 )\n    NaN\n\n    > v = base.dists.beta.median( 2.0, NaN )\n    NaN\n    > v = base.dists.beta.median( NaN, 2.0 )\n    NaN\n\n","base.dists.beta.mgf":"\nbase.dists.beta.mgf( t, α, β )\n    Evaluates the moment-generating function (MGF) for a beta distribution with\n    first shape parameter `α` and second shape parameter `β` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.beta.mgf( 0.5, 1.0, 1.0 )\n    ~1.297\n    > y = base.dists.beta.mgf( 0.5, 2.0, 4.0 )\n    ~1.186\n    > y = base.dists.beta.mgf( 3.0, 2.0, 2.0 )\n    ~5.575\n    > y = base.dists.beta.mgf( -0.8, 4.0, 4.0 )\n    ~0.676\n\n    > y = base.dists.beta.mgf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.beta.mgf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.beta.mgf( 0.0, 1.0, NaN )\n    NaN\n\n    > y = base.dists.beta.mgf( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.beta.mgf( 2.0, 0.0, 0.5 )\n    NaN\n\n    > y = base.dists.beta.mgf( 2.0, 0.5, -1.0 )\n    NaN\n    > y = base.dists.beta.mgf( 2.0, 0.5, 0.0 )\n    NaN\n\n\nbase.dists.beta.mgf.factory( α, β )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    beta distribution with first shape parameter `α` and second shape parameter\n    `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.beta.mgf.factory( 0.5, 0.5 );\n    > var y = myMGF( 0.8 )\n    ~1.552\n    > y = myMGF( 0.3 )\n    ~1.168\n\n","base.dists.beta.mgf.factory":"\nbase.dists.beta.mgf.factory( α, β )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    beta distribution with first shape parameter `α` and second shape parameter\n    `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.beta.mgf.factory( 0.5, 0.5 );\n    > var y = myMGF( 0.8 )\n    ~1.552\n    > y = myMGF( 0.3 )\n    ~1.168","base.dists.beta.mode":"\nbase.dists.beta.mode( α, β )\n    Returns the mode of a beta distribution.\n\n    If `α <= 1` or `β <= 1`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.beta.mode( 4.0, 12.0 )\n    ~0.214\n    > v = base.dists.beta.mode( 8.0, 2.0 )\n    ~0.875\n    > v = base.dists.beta.mode( 1.0, 1.0 )\n    NaN\n\n","base.dists.beta.pdf":"\nbase.dists.beta.pdf( x, α, β )\n    Evaluates the probability density function (PDF) for a beta distribution\n    with first shape parameter `α` and second shape parameter `β` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.beta.pdf( 0.5, 1.0, 1.0 )\n    1.0\n    > y = base.dists.beta.pdf( 0.5, 2.0, 4.0 )\n    1.25\n    > y = base.dists.beta.pdf( 0.2, 2.0, 2.0 )\n    ~0.96\n    > y = base.dists.beta.pdf( 0.8, 4.0, 4.0 )\n    ~0.573\n    > y = base.dists.beta.pdf( -0.5, 4.0, 2.0 )\n    0.0\n    > y = base.dists.beta.pdf( 1.5, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.beta.pdf( 0.5, -1.0, 0.5 )\n    NaN\n    > y = base.dists.beta.pdf( 0.5, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.beta.pdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.beta.pdf( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.dists.beta.pdf( 0.5, 1.0, NaN )\n    NaN\n\n\nbase.dists.beta.pdf.factory( α, β )\n    Returns a function for evaluating the probability density function (PDF) of\n    a beta distribution with first shape parameter `α` and second shape\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var mypdf = base.dists.beta.pdf.factory( 0.5, 0.5 );\n    > var y = mypdf( 0.8 )\n    ~0.796\n    > y = mypdf( 0.3 )\n    ~0.695\n\n","base.dists.beta.pdf.factory":"\nbase.dists.beta.pdf.factory( α, β )\n    Returns a function for evaluating the probability density function (PDF) of\n    a beta distribution with first shape parameter `α` and second shape\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var mypdf = base.dists.beta.pdf.factory( 0.5, 0.5 );\n    > var y = mypdf( 0.8 )\n    ~0.796\n    > y = mypdf( 0.3 )\n    ~0.695","base.dists.beta.quantile":"\nbase.dists.beta.quantile( p, α, β )\n    Evaluates the quantile function for a beta distribution with first shape\n    parameter `α` and second shape parameter `β` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input value (probability).\n\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.beta.quantile( 0.8, 2.0, 1.0 )\n    ~0.894\n    > y = base.dists.beta.quantile( 0.5, 4.0, 2.0 )\n    ~0.686\n    > y = base.dists.beta.quantile( 1.1, 1.0, 1.0 )\n    NaN\n    > y = base.dists.beta.quantile( -0.2, 1.0, 1.0 )\n    NaN\n\n    > y = base.dists.beta.quantile( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.beta.quantile( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.dists.beta.quantile( 0.5, 1.0, NaN )\n    NaN\n\n    > y = base.dists.beta.quantile( 0.5, -1.0, 1.0 )\n    NaN\n    > y = base.dists.beta.quantile( 0.5, 1.0, -1.0 )\n    NaN\n\n\nbase.dists.beta.quantile.factory( α, β )\n    Returns a function for evaluating the quantile function of a beta\n    distribution with first shape parameter `α` and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.beta.quantile.factory( 2.0, 2.0 );\n    > y = myquantile( 0.8 )\n    ~0.713\n    > y = myquantile( 0.4 )\n    ~0.433\n\n","base.dists.beta.quantile.factory":"\nbase.dists.beta.quantile.factory( α, β )\n    Returns a function for evaluating the quantile function of a beta\n    distribution with first shape parameter `α` and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.beta.quantile.factory( 2.0, 2.0 );\n    > y = myquantile( 0.8 )\n    ~0.713\n    > y = myquantile( 0.4 )\n    ~0.433","base.dists.beta.skewness":"\nbase.dists.beta.skewness( α, β )\n    Returns the skewness of a beta distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.beta.skewness( 1.0, 1.0 )\n    0.0\n    > v = base.dists.beta.skewness( 4.0, 12.0 )\n    ~0.529\n    > v = base.dists.beta.skewness( 8.0, 2.0 )\n    ~-0.829\n\n    > v = base.dists.beta.skewness( 1.0, -0.1 )\n    NaN\n    > v = base.dists.beta.skewness( -0.1, 1.0 )\n    NaN\n\n    > v = base.dists.beta.skewness( 2.0, NaN )\n    NaN\n    > v = base.dists.beta.skewness( NaN, 2.0 )\n    NaN\n\n","base.dists.beta.stdev":"\nbase.dists.beta.stdev( α, β )\n    Returns the standard deviation of a beta distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.beta.stdev( 1.0, 1.0 )\n    ~0.289\n    > v = base.dists.beta.stdev( 4.0, 12.0 )\n    ~0.105\n    > v = base.dists.beta.stdev( 8.0, 2.0 )\n    ~0.121\n\n    > v = base.dists.beta.stdev( 1.0, -0.1 )\n    NaN\n    > v = base.dists.beta.stdev( -0.1, 1.0 )\n    NaN\n\n    > v = base.dists.beta.stdev( 2.0, NaN )\n    NaN\n    > v = base.dists.beta.stdev( NaN, 2.0 )\n    NaN\n\n","base.dists.beta.variance":"\nbase.dists.beta.variance( α, β )\n    Returns the variance of a beta distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.beta.variance( 1.0, 1.0 )\n    ~0.083\n    > v = base.dists.beta.variance( 4.0, 12.0 )\n    ~0.011\n    > v = base.dists.beta.variance( 8.0, 2.0 )\n    ~0.015\n\n    > v = base.dists.beta.variance( 1.0, -0.1 )\n    NaN\n    > v = base.dists.beta.variance( -0.1, 1.0 )\n    NaN\n\n    > v = base.dists.beta.variance( 2.0, NaN )\n    NaN\n    > v = base.dists.beta.variance( NaN, 2.0 )\n    NaN\n\n","base.dists.betaprime.BetaPrime":"\nbase.dists.betaprime.BetaPrime( [α, β] )\n    Returns a beta prime distribution object.\n\n    Parameters\n    ----------\n    α: number (optional)\n        First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n    β: number (optional)\n        Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    betaprime: Object\n        Distribution instance.\n\n    betaprime.alpha: number\n        First shape parameter. If set, the value must be greater than `0`.\n\n    betaprime.beta: number\n        Second shape parameter. If set, the value must be greater than `0`.\n\n    betaprime.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    betaprime.mean: number\n        Read-only property which returns the expected value.\n\n    betaprime.mode: number\n        Read-only property which returns the mode.\n\n    betaprime.skewness: number\n        Read-only property which returns the skewness.\n\n    betaprime.stdev: number\n        Read-only property which returns the standard deviation.\n\n    betaprime.variance: number\n        Read-only property which returns the variance.\n\n    betaprime.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    betaprime.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    betaprime.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    betaprime.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    betaprime.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var betaprime = base.dists.betaprime.BetaPrime( 6.0, 5.0 );\n    > betaprime.alpha\n    6.0\n    > betaprime.beta\n    5.0\n    > betaprime.kurtosis\n    44.4\n    > betaprime.mean\n    1.5\n    > betaprime.mode\n    ~0.833\n    > betaprime.skewness\n    ~3.578\n    > betaprime.stdev\n    ~1.118\n    > betaprime.variance\n    1.25\n    > betaprime.cdf( 0.8 )\n    ~0.25\n    > betaprime.logcdf( 0.8 )\n    ~-1.387\n    > betaprime.logpdf( 1.0 )\n    ~-0.486\n    > betaprime.pdf( 1.0 )\n    ~0.615\n    > betaprime.quantile( 0.8 )\n    ~2.06\n\n","base.dists.betaprime.cdf":"\nbase.dists.betaprime.cdf( x, α, β )\n    Evaluates the cumulative distribution function (CDF) for a beta prime\n    distribution with first shape parameter `α` and second shape parameter `β`\n    at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.betaprime.cdf( 0.5, 1.0, 1.0 )\n    ~0.333\n    > y = base.dists.betaprime.cdf( 0.5, 2.0, 4.0 )\n    ~0.539\n    > y = base.dists.betaprime.cdf( 0.2, 2.0, 2.0 )\n    ~0.074\n    > y = base.dists.betaprime.cdf( 0.8, 4.0, 4.0 )\n    ~0.38\n    > y = base.dists.betaprime.cdf( -0.5, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.betaprime.cdf( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.betaprime.cdf( 2.0, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.betaprime.cdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.betaprime.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.betaprime.cdf( 0.0, 1.0, NaN )\n    NaN\n\n\nbase.dists.betaprime.cdf.factory( α, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a beta prime distribution with first shape parameter `α` and second shape\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.betaprime.cdf.factory( 0.5, 0.5 );\n    > var y = mycdf( 0.8 )\n    ~0.465\n    > y = mycdf( 0.3 )\n    ~0.319\n\n","base.dists.betaprime.cdf.factory":"\nbase.dists.betaprime.cdf.factory( α, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a beta prime distribution with first shape parameter `α` and second shape\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.betaprime.cdf.factory( 0.5, 0.5 );\n    > var y = mycdf( 0.8 )\n    ~0.465\n    > y = mycdf( 0.3 )\n    ~0.319","base.dists.betaprime.kurtosis":"\nbase.dists.betaprime.kurtosis( α, β )\n    Returns the excess kurtosis of a beta prime distribution.\n\n    If `α <= 0` or `β <= 4`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.betaprime.kurtosis( 2.0, 6.0 )\n    ~26.143\n    > v = base.dists.betaprime.kurtosis( 4.0, 12.0 )\n    ~5.764\n    > v = base.dists.betaprime.kurtosis( 8.0, 6.0 )\n    ~19.962\n\n    > v = base.dists.betaprime.kurtosis( 1.0, 2.8 )\n    NaN\n    > v = base.dists.betaprime.kurtosis( 1.0, -0.1 )\n    NaN\n    > v = base.dists.betaprime.kurtosis( -0.1, 5.0 )\n    NaN\n\n    > v = base.dists.betaprime.kurtosis( 2.0, NaN )\n    NaN\n    > v = base.dists.betaprime.kurtosis( NaN, 6.0 )\n    NaN\n\n","base.dists.betaprime.logcdf":"\nbase.dists.betaprime.logcdf( x, α, β )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a beta prime distribution with first shape parameter `α` and\n    second shape parameter `β` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.betaprime.logcdf( 0.5, 1.0, 1.0 )\n    ~-1.099\n    > y = base.dists.betaprime.logcdf( 0.5, 2.0, 4.0 )\n    ~-0.618\n    > y = base.dists.betaprime.logcdf( 0.2, 2.0, 2.0 )\n    ~-2.603\n    > y = base.dists.betaprime.logcdf( 0.8, 4.0, 4.0 )\n    ~-0.968\n    > y = base.dists.betaprime.logcdf( -0.5, 4.0, 2.0 )\n    -Infinity\n\n    > y = base.dists.betaprime.logcdf( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.betaprime.logcdf( 2.0, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.betaprime.logcdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.betaprime.logcdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.betaprime.logcdf( 0.0, 1.0, NaN )\n    NaN\n\n\nbase.dists.betaprime.logcdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a beta prime distribution with first shape\n    parameter `α` and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.betaprime.logcdf.factory( 0.5, 0.5 );\n    > var y = mylogcdf( 0.8 )\n    ~-0.767\n    > y = mylogcdf( 0.3 )\n    ~-1.143\n\n","base.dists.betaprime.logcdf.factory":"\nbase.dists.betaprime.logcdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a beta prime distribution with first shape\n    parameter `α` and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.betaprime.logcdf.factory( 0.5, 0.5 );\n    > var y = mylogcdf( 0.8 )\n    ~-0.767\n    > y = mylogcdf( 0.3 )\n    ~-1.143","base.dists.betaprime.logpdf":"\nbase.dists.betaprime.logpdf( x, α, β )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a beta prime distribution with first shape parameter `α` and second\n    shape parameter `β` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Natural logarithm of the PDF.\n\n    Examples\n    --------\n    > var y = base.dists.betaprime.logpdf( 0.5, 1.0, 1.0 )\n    ~-0.811\n    > y = base.dists.betaprime.logpdf( 0.5, 2.0, 4.0 )\n    ~-0.13\n    > y = base.dists.betaprime.logpdf( 0.2, 2.0, 2.0 )\n    ~-0.547\n    > y = base.dists.betaprime.logpdf( 0.8, 4.0, 4.0 )\n    ~-0.43\n    > y = base.dists.betaprime.logpdf( -0.5, 4.0, 2.0 )\n    -Infinity\n\n    > y = base.dists.betaprime.logpdf( 0.5, -1.0, 0.5 )\n    NaN\n    > y = base.dists.betaprime.logpdf( 0.5, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.betaprime.logpdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.betaprime.logpdf( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.dists.betaprime.logpdf( 0.5, 1.0, NaN )\n    NaN\n\n\nbase.dists.betaprime.logpdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a beta prime distribution with first shape\n    parameter `α` and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    fcn: Function\n        Function to evaluate the natural logarithm of the PDF.\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.betaprime.logpdf.factory( 0.5, 0.5 );\n    > var y = mylogpdf( 0.8 )\n    ~-1.62\n    > y = mylogpdf( 0.3 )\n    ~-0.805\n\n","base.dists.betaprime.logpdf.factory":"\nbase.dists.betaprime.logpdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a beta prime distribution with first shape\n    parameter `α` and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    fcn: Function\n        Function to evaluate the natural logarithm of the PDF.\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.betaprime.logpdf.factory( 0.5, 0.5 );\n    > var y = mylogpdf( 0.8 )\n    ~-1.62\n    > y = mylogpdf( 0.3 )\n    ~-0.805","base.dists.betaprime.mean":"\nbase.dists.betaprime.mean( α, β )\n    Returns the expected value of a beta prime distribution.\n\n    If `α <= 0` or `β <= 1`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.betaprime.mean( 1.0, 2.0 )\n    1.0\n    > v = base.dists.betaprime.mean( 4.0, 12.0 )\n    ~0.364\n    > v = base.dists.betaprime.mean( 8.0, 2.0 )\n    8.0\n\n","base.dists.betaprime.mode":"\nbase.dists.betaprime.mode( α, β )\n    Returns the mode of a beta prime distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.betaprime.mode( 1.0, 2.0 )\n    0.0\n    > v = base.dists.betaprime.mode( 4.0, 12.0 )\n    ~0.231\n    > v = base.dists.betaprime.mode( 8.0, 2.0 )\n    ~2.333\n\n","base.dists.betaprime.pdf":"\nbase.dists.betaprime.pdf( x, α, β )\n    Evaluates the probability density function (PDF) for a beta prime\n    distribution  with first shape parameter `α` and second shape parameter `β`\n    at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.betaprime.pdf( 0.5, 1.0, 1.0 )\n    ~0.444\n    > y = base.dists.betaprime.pdf( 0.5, 2.0, 4.0 )\n    ~0.878\n    > y = base.dists.betaprime.pdf( 0.2, 2.0, 2.0 )\n    ~0.579\n    > y = base.dists.betaprime.pdf( 0.8, 4.0, 4.0 )\n    ~0.65\n    > y = base.dists.betaprime.pdf( -0.5, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.betaprime.pdf( 0.5, -1.0, 0.5 )\n    NaN\n    > y = base.dists.betaprime.pdf( 0.5, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.betaprime.pdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.betaprime.pdf( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.dists.betaprime.pdf( 0.5, 1.0, NaN )\n    NaN\n\n\nbase.dists.betaprime.pdf.factory( α, β )\n    Returns a function for evaluating the probability density function (PDF) of\n    a beta prime distribution with first shape parameter `α` and second shape\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var mypdf = base.dists.betaprime.pdf.factory( 0.5, 0.5 );\n    > var y = mypdf( 0.8 )\n    ~0.198\n    > y = mypdf( 0.3 )\n    ~0.447\n\n","base.dists.betaprime.pdf.factory":"\nbase.dists.betaprime.pdf.factory( α, β )\n    Returns a function for evaluating the probability density function (PDF) of\n    a beta prime distribution with first shape parameter `α` and second shape\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var mypdf = base.dists.betaprime.pdf.factory( 0.5, 0.5 );\n    > var y = mypdf( 0.8 )\n    ~0.198\n    > y = mypdf( 0.3 )\n    ~0.447","base.dists.betaprime.quantile":"\nbase.dists.betaprime.quantile( p, α, β )\n    Evaluates the quantile function for a beta prime distribution with first\n    shape parameter `α` and second shape parameter `β` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input value (probability).\n\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.betaprime.quantile( 0.8, 2.0, 1.0 )\n    ~8.472\n    > y = base.dists.betaprime.quantile( 0.5, 4.0, 2.0 )\n    ~2.187\n    > y = base.dists.betaprime.quantile( 1.1, 1.0, 1.0 )\n    NaN\n    > y = base.dists.betaprime.quantile( -0.2, 1.0, 1.0 )\n    NaN\n\n    > y = base.dists.betaprime.quantile( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.betaprime.quantile( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.dists.betaprime.quantile( 0.5, 1.0, NaN )\n    NaN\n\n    > y = base.dists.betaprime.quantile( 0.5, -1.0, 1.0 )\n    NaN\n    > y = base.dists.betaprime.quantile( 0.5, 1.0, -1.0 )\n    NaN\n\n\nbase.dists.betaprime.quantile.factory( α, β )\n    Returns a function for evaluating the quantile function of a beta prime\n    distribution with first shape parameter `α` and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.betaprime.quantile.factory( 2.0, 2.0 );\n    > y = myQuantile( 0.8 )\n    ~2.483\n    > y = myQuantile( 0.4 )\n    ~0.763\n\n","base.dists.betaprime.quantile.factory":"\nbase.dists.betaprime.quantile.factory( α, β )\n    Returns a function for evaluating the quantile function of a beta prime\n    distribution with first shape parameter `α` and second shape parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.betaprime.quantile.factory( 2.0, 2.0 );\n    > y = myQuantile( 0.8 )\n    ~2.483\n    > y = myQuantile( 0.4 )\n    ~0.763","base.dists.betaprime.skewness":"\nbase.dists.betaprime.skewness( α, β )\n    Returns the skewness of a beta prime distribution.\n\n    If `α <= 0` or `β <= 3`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.betaprime.skewness( 2.0, 4.0 )\n    ~6.261\n    > v = base.dists.betaprime.skewness( 4.0, 12.0 )\n    ~1.724\n    > v = base.dists.betaprime.skewness( 8.0, 4.0 )\n    ~5.729\n\n    > v = base.dists.betaprime.skewness( 1.0, 2.8 )\n    NaN\n    > v = base.dists.betaprime.skewness( 1.0, -0.1 )\n    NaN\n    > v = base.dists.betaprime.skewness( -0.1, 4.0 )\n    NaN\n\n    > v = base.dists.betaprime.skewness( 2.0, NaN )\n    NaN\n    > v = base.dists.betaprime.skewness( NaN, 4.0 )\n    NaN\n\n","base.dists.betaprime.stdev":"\nbase.dists.betaprime.stdev( α, β )\n    Returns the standard deviation of a beta prime distribution.\n\n    If `α <= 0` or `β <= 2`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.betaprime.stdev( 1.0, 2.5 )\n    ~1.491\n    > v = base.dists.betaprime.stdev( 4.0, 12.0 )\n    ~0.223\n    > v = base.dists.betaprime.stdev( 8.0, 2.5 )\n    ~8.219\n\n    > v = base.dists.betaprime.stdev( 8.0, 1.0 )\n    NaN\n    > v = base.dists.betaprime.stdev( 1.0, -0.1 )\n    NaN\n    > v = base.dists.betaprime.stdev( -0.1, 3.0 )\n    NaN\n\n    > v = base.dists.betaprime.stdev( 2.0, NaN )\n    NaN\n    > v = base.dists.betaprime.stdev( NaN, 3.0 )\n    NaN\n\n","base.dists.betaprime.variance":"\nbase.dists.betaprime.variance( α, β )\n    Returns the variance of a beta prime distribution.\n\n    If `α <= 0` or `β <= 2`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.betaprime.variance( 1.0, 2.5 )\n    ~2.222\n    > v = base.dists.betaprime.variance( 4.0, 12.0 )\n    ~0.05\n    > v = base.dists.betaprime.variance( 8.0, 2.5 )\n    ~67.556\n\n    > v = base.dists.betaprime.variance( 8.0, 1.0 )\n    NaN\n    > v = base.dists.betaprime.variance( 1.0, -0.1 )\n    NaN\n    > v = base.dists.betaprime.variance( -0.1, 3.0 )\n    NaN\n\n    > v = base.dists.betaprime.variance( 2.0, NaN )\n    NaN\n    > v = base.dists.betaprime.variance( NaN, 3.0 )\n    NaN\n\n","base.dists.binomial.Binomial":"\nbase.dists.binomial.Binomial( [n, p] )\n    Returns a binomial distribution object.\n\n    Parameters\n    ----------\n    n: integer (optional)\n        Number of trials. Must be a positive integer. Default: `1`.\n\n    p: number (optional)\n        Success probability. Must be a number between `0` and `1`. Default:\n        `0.5`.\n\n    Returns\n    -------\n    binomial: Object\n        Distribution instance.\n\n    binomial.n: number\n        Number of trials. If set, the value must be a positive integer.\n\n    binomial.p: number\n        Success probability. If set, the value must be a number between `0` and\n        `1`.\n\n    binomial.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    binomial.mean: number\n        Read-only property which returns the expected value.\n\n    binomial.median: number\n        Read-only property which returns the median.\n\n    binomial.mode: number\n        Read-only property which returns the mode.\n\n    binomial.skewness: number\n        Read-only property which returns the skewness.\n\n    binomial.stdev: number\n        Read-only property which returns the standard deviation.\n\n    binomial.variance: number\n        Read-only property which returns the variance.\n\n    binomial.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    binomial.logpmf: Function\n        Evaluates the natural logarithm of the probability mass function (PMF).\n\n    binomial.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    binomial.pmf: Function\n        Evaluates the probability mass function (PMF).\n\n    binomial.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var binomial = base.dists.binomial.Binomial( 8, 0.5 );\n    > binomial.n\n    8.0\n    > binomial.p\n    0.5\n    > binomial.kurtosis\n    -0.25\n    > binomial.mean\n    4.0\n    > binomial.median\n    4.0\n    > binomial.mode\n    4.0\n    > binomial.skewness\n    0.0\n    > binomial.stdev\n    ~1.414\n    > binomial.variance\n    2.0\n    > binomial.cdf( 2.9 )\n    ~0.145\n    > binomial.logpmf( 3.0 )\n    ~-1.52\n    > binomial.mgf( 0.2 )\n    ~2.316\n    > binomial.pmf( 3.0 )\n    ~0.219\n    > binomial.quantile( 0.8 )\n    5.0\n\n","base.dists.binomial.cdf":"\nbase.dists.binomial.cdf( x, n, p )\n    Evaluates the cumulative distribution function (CDF) for a binomial\n    distribution with number of trials `n` and success probability `p` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.binomial.cdf( 3.0, 20, 0.2 )\n    ~0.411\n    > y = base.dists.binomial.cdf( 21.0, 20, 0.2 )\n    1.0\n    > y = base.dists.binomial.cdf( 5.0, 10, 0.4 )\n    ~0.834\n    > y = base.dists.binomial.cdf( 0.0, 10, 0.4 )\n    ~0.006\n    > y = base.dists.binomial.cdf( NaN, 20, 0.5 )\n    NaN\n    > y = base.dists.binomial.cdf( 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.binomial.cdf( 0.0, 20, NaN )\n    NaN\n    > y = base.dists.binomial.cdf( 2.0, 1.5, 0.5 )\n    NaN\n    > y = base.dists.binomial.cdf( 2.0, -2.0, 0.5 )\n    NaN\n    > y = base.dists.binomial.cdf( 2.0, 20, -1.0 )\n    NaN\n    > y = base.dists.binomial.cdf( 2.0, 20, 1.5 )\n    NaN\n\n\nbase.dists.binomial.cdf.factory( n, p )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a binomial distribution with number of trials `n` and success probability\n    `p`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.binomial.cdf.factory( 10, 0.5 );\n    > var y = mycdf( 3.0 )\n    ~0.172\n    > y = mycdf( 1.0 )\n    ~0.011\n\n","base.dists.binomial.cdf.factory":"\nbase.dists.binomial.cdf.factory( n, p )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a binomial distribution with number of trials `n` and success probability\n    `p`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.binomial.cdf.factory( 10, 0.5 );\n    > var y = mycdf( 3.0 )\n    ~0.172\n    > y = mycdf( 1.0 )\n    ~0.011","base.dists.binomial.entropy":"\nbase.dists.binomial.entropy( n, p )\n    Returns the entropy of a binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.binomial.entropy( 100, 0.1 )\n    ~2.511\n    > v = base.dists.binomial.entropy( 20, 0.5 )\n    ~2.223\n    > v = base.dists.binomial.entropy( 10.3, 0.5 )\n    NaN\n    > v = base.dists.binomial.entropy( 20, 1.1 )\n    NaN\n    > v = base.dists.binomial.entropy( 20, NaN )\n    NaN\n\n","base.dists.binomial.kurtosis":"\nbase.dists.binomial.kurtosis( n, p )\n    Returns the excess kurtosis of a binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.binomial.kurtosis( 100, 0.1 )\n    ~0.051\n    > v = base.dists.binomial.kurtosis( 20, 0.5 )\n    ~-0.1\n    > v = base.dists.binomial.kurtosis( 10.3, 0.5 )\n    NaN\n    > v = base.dists.binomial.kurtosis( 20, 1.1 )\n    NaN\n    > v = base.dists.binomial.kurtosis( 20, NaN )\n    NaN\n\n","base.dists.binomial.logpmf":"\nbase.dists.binomial.logpmf( x, n, p )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    binomial distribution with number of trials `n` and success probability `p`\n    at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPMF.\n\n    Examples\n    --------\n    > var y = base.dists.binomial.logpmf( 3.0, 20, 0.2 )\n    ~-1.583\n    > y = base.dists.binomial.logpmf( 21.0, 20, 0.2 )\n    -Infinity\n    > y = base.dists.binomial.logpmf( 5.0, 10, 0.4 )\n    ~-1.606\n    > y = base.dists.binomial.logpmf( 0.0, 10, 0.4 )\n    ~-5.108\n    > y = base.dists.binomial.logpmf( NaN, 20, 0.5 )\n    NaN\n    > y = base.dists.binomial.logpmf( 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.binomial.logpmf( 0.0, 20, NaN )\n    NaN\n    > y = base.dists.binomial.logpmf( 2.0, 1.5, 0.5 )\n    NaN\n    > y = base.dists.binomial.logpmf( 2.0, -2.0, 0.5 )\n    NaN\n    > y = base.dists.binomial.logpmf( 2.0, 20, -1.0 )\n    NaN\n    > y = base.dists.binomial.logpmf( 2.0, 20, 1.5 )\n    NaN\n\n\nbase.dists.binomial.logpmf.factory( n, p )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a binomial distribution with number of trials `n` and\n    success probability `p`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogpmf = base.dists.binomial.logpmf.factory( 10, 0.5 );\n    > var y = mylogpmf( 3.0 )\n    ~-2.144\n    > y = mylogpmf( 5.0 )\n    ~-1.402\n\n","base.dists.binomial.logpmf.factory":"\nbase.dists.binomial.logpmf.factory( n, p )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a binomial distribution with number of trials `n` and\n    success probability `p`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogpmf = base.dists.binomial.logpmf.factory( 10, 0.5 );\n    > var y = mylogpmf( 3.0 )\n    ~-2.144\n    > y = mylogpmf( 5.0 )\n    ~-1.402","base.dists.binomial.mean":"\nbase.dists.binomial.mean( n, p )\n    Returns the expected value of a binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.binomial.mean( 100, 0.1 )\n    10.0\n    > v = base.dists.binomial.mean( 20, 0.5 )\n    10.0\n    > v = base.dists.binomial.mean( 10.3, 0.5 )\n    NaN\n    > v = base.dists.binomial.mean( 20, 1.1 )\n    NaN\n    > v = base.dists.binomial.mean( 20, NaN )\n    NaN\n\n","base.dists.binomial.median":"\nbase.dists.binomial.median( n, p )\n    Returns the median of a binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.binomial.median( 100, 0.1 )\n    10\n    > v = base.dists.binomial.median( 20, 0.5 )\n    10\n    > v = base.dists.binomial.median( 10.3, 0.5 )\n    NaN\n    > v = base.dists.binomial.median( 20, 1.1 )\n    NaN\n    > v = base.dists.binomial.median( 20, NaN )\n    NaN\n\n","base.dists.binomial.mgf":"\nbase.dists.binomial.mgf( t, n, p )\n    Evaluates the moment-generating function (MGF) for a binomial distribution\n    with number of trials `n` and success probability `p` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.binomial.mgf( 0.5, 20, 0.2 )\n    ~11.471\n    > y = base.dists.binomial.mgf( 5.0, 20, 0.2 )\n    ~4.798e+29\n    > y = base.dists.binomial.mgf( 0.9, 10, 0.4 )\n    ~99.338\n    > y = base.dists.binomial.mgf( 0.0, 10, 0.4 )\n    1.0\n\n    > y = base.dists.binomial.mgf( NaN, 20, 0.5 )\n    NaN\n    > y = base.dists.binomial.mgf( 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.binomial.mgf( 0.0, 20, NaN )\n    NaN\n\n    > y = base.dists.binomial.mgf( 2.0, 1.5, 0.5 )\n    NaN\n    > y = base.dists.binomial.mgf( 2.0, -2.0, 0.5 )\n    NaN\n    > y = base.dists.binomial.mgf( 2.0, 20, -1.0 )\n    NaN\n    > y = base.dists.binomial.mgf( 2.0, 20, 1.5 )\n    NaN\n\n\nbase.dists.binomial.mgf.factory( n, p )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    binomial distribution with number of trials `n` and success probability `p`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.binomial.mgf.factory( 10, 0.5 );\n    > var y = myMGF( 0.3 )\n    ~5.013\n\n","base.dists.binomial.mgf.factory":"\nbase.dists.binomial.mgf.factory( n, p )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    binomial distribution with number of trials `n` and success probability `p`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.binomial.mgf.factory( 10, 0.5 );\n    > var y = myMGF( 0.3 )\n    ~5.013","base.dists.binomial.mode":"\nbase.dists.binomial.mode( n, p )\n    Returns the mode of a binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.binomial.mode( 100, 0.1 )\n    10\n    > v = base.dists.binomial.mode( 20, 0.5 )\n    10\n    > v = base.dists.binomial.mode( 10.3, 0.5 )\n    NaN\n    > v = base.dists.binomial.mode( 20, 1.1 )\n    NaN\n    > v = base.dists.binomial.mode( 20, NaN )\n    NaN\n\n","base.dists.binomial.pmf":"\nbase.dists.binomial.pmf( x, n, p )\n    Evaluates the probability mass function (PMF) for a binomial distribution\n    with number of trials `n` and success probability `p` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated PMF.\n\n    Examples\n    --------\n    > var y = base.dists.binomial.pmf( 3.0, 20, 0.2 )\n    ~0.205\n    > y = base.dists.binomial.pmf( 21.0, 20, 0.2 )\n    0.0\n    > y = base.dists.binomial.pmf( 5.0, 10, 0.4 )\n    ~0.201\n    > y = base.dists.binomial.pmf( 0.0, 10, 0.4 )\n    ~0.006\n    > y = base.dists.binomial.pmf( NaN, 20, 0.5 )\n    NaN\n    > y = base.dists.binomial.pmf( 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.binomial.pmf( 0.0, 20, NaN )\n    NaN\n    > y = base.dists.binomial.pmf( 2.0, 1.5, 0.5 )\n    NaN\n    > y = base.dists.binomial.pmf( 2.0, -2.0, 0.5 )\n    NaN\n    > y = base.dists.binomial.pmf( 2.0, 20, -1.0 )\n    NaN\n    > y = base.dists.binomial.pmf( 2.0, 20, 1.5 )\n    NaN\n\n\nbase.dists.binomial.pmf.factory( n, p )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    binomial distribution with number of trials `n` and success probability `p`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var mypmf = base.dists.binomial.pmf.factory( 10, 0.5 );\n    > var y = mypmf( 3.0 )\n    ~0.117\n    > y = mypmf( 5.0 )\n    ~0.246\n\n","base.dists.binomial.pmf.factory":"\nbase.dists.binomial.pmf.factory( n, p )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    binomial distribution with number of trials `n` and success probability `p`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var mypmf = base.dists.binomial.pmf.factory( 10, 0.5 );\n    > var y = mypmf( 3.0 )\n    ~0.117\n    > y = mypmf( 5.0 )\n    ~0.246","base.dists.binomial.quantile":"\nbase.dists.binomial.quantile( r, n, p )\n    Evaluates the quantile function for a binomial distribution with number of\n    trials `n` and success probability `p` at a probability `r`.\n\n    If `r < 0` or `r > 1`, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    r: number\n        Input probability.\n\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.binomial.quantile( 0.4, 20, 0.2 )\n    3\n    > y = base.dists.binomial.quantile( 0.8, 20, 0.2 )\n    5\n    > y = base.dists.binomial.quantile( 0.5, 10, 0.4 )\n    4\n    > y = base.dists.binomial.quantile( 0.0, 10, 0.4 )\n    0\n    > y = base.dists.binomial.quantile( 1.0, 10, 0.4 )\n    10\n\n    > y = base.dists.binomial.quantile( NaN, 20, 0.5 )\n    NaN\n    > y = base.dists.binomial.quantile( 0.2, NaN, 0.5 )\n    NaN\n    > y = base.dists.binomial.quantile( 0.2, 20, NaN )\n    NaN\n\n    > y = base.dists.binomial.quantile( 0.5, 1.5, 0.5 )\n    NaN\n    > y = base.dists.binomial.quantile( 0.5, -2.0, 0.5 )\n    NaN\n\n    > y = base.dists.binomial.quantile( 0.5, 20, -1.0 )\n    NaN\n    > y = base.dists.binomial.quantile( 0.5, 20, 1.5 )\n    NaN\n\n\nbase.dists.binomial.quantile.factory( n, p )\n    Returns a function for evaluating the quantile function of a binomial\n    distribution with number of trials `n` and success probability `p`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.binomial.quantile.factory( 10, 0.5 );\n    > var y = myquantile( 0.1 )\n    3\n    > y = myquantile( 0.9 )\n    7\n\n","base.dists.binomial.quantile.factory":"\nbase.dists.binomial.quantile.factory( n, p )\n    Returns a function for evaluating the quantile function of a binomial\n    distribution with number of trials `n` and success probability `p`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.binomial.quantile.factory( 10, 0.5 );\n    > var y = myquantile( 0.1 )\n    3\n    > y = myquantile( 0.9 )\n    7","base.dists.binomial.skewness":"\nbase.dists.binomial.skewness( n, p )\n    Returns the skewness of a binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.binomial.skewness( 100, 0.1 )\n    ~0.267\n    > v = base.dists.binomial.skewness( 20, 0.5 )\n    0.0\n    > v = base.dists.binomial.skewness( 10.3, 0.5 )\n    NaN\n    > v = base.dists.binomial.skewness( 20, 1.1 )\n    NaN\n    > v = base.dists.binomial.skewness( 20, NaN )\n    NaN\n\n","base.dists.binomial.stdev":"\nbase.dists.binomial.stdev( n, p )\n    Returns the standard deviation of a binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.binomial.stdev( 100, 0.1 )\n    3.0\n    > v = base.dists.binomial.stdev( 20, 0.5 )\n    ~2.236\n    > v = base.dists.binomial.stdev( 10.3, 0.5 )\n    NaN\n    > v = base.dists.binomial.stdev( 20, 1.1 )\n    NaN\n    > v = base.dists.binomial.stdev( 20, NaN )\n    NaN\n\n","base.dists.binomial.variance":"\nbase.dists.binomial.variance( n, p )\n    Returns the variance of a binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a number of trials `n` which is not a nonnegative integer, the\n    function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.binomial.variance( 100, 0.1 )\n    9\n    > v = base.dists.binomial.variance( 20, 0.5 )\n    5\n    > v = base.dists.binomial.variance( 10.3, 0.5 )\n    NaN\n    > v = base.dists.binomial.variance( 20, 1.1 )\n    NaN\n    > v = base.dists.binomial.variance( 20, NaN )\n    NaN\n\n","base.dists.cauchy.Cauchy":"\nbase.dists.cauchy.Cauchy( [x0, Ɣ] )\n    Returns a Cauchy distribution object.\n\n    Parameters\n    ----------\n    x0: number (optional)\n        Location parameter. Default: `0.0`.\n\n    Ɣ: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    cauchy: Object\n        Distribution instance.\n\n    cauchy.x0: number\n        Location parameter.\n\n    cauchy.gamma: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    cauchy.entropy: number\n        Read-only property which returns the differential entropy.\n\n    cauchy.median: number\n        Read-only property which returns the median.\n\n    cauchy.mode: number\n        Read-only property which returns the mode.\n\n    cauchy.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    cauchy.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    cauchy.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    cauchy.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    cauchy.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var cauchy = base.dists.cauchy.Cauchy( 0.0, 1.0 );\n    > cauchy.x0\n    0.0\n    > cauchy.gamma\n    1.0\n    > cauchy.entropy\n    ~2.531\n    > cauchy.median\n    0.0\n    > cauchy.mode\n    0.0\n    > cauchy.cdf( 0.8 )\n    ~0.715\n    > cauchy.logcdf( 1.0 )\n    ~-0.288\n    > cauchy.logpdf( 1.0 )\n    ~-1.838\n    > cauchy.pdf( 1.0 )\n    ~0.159\n    > cauchy.quantile( 0.8 )\n    ~1.376\n\n","base.dists.cauchy.cdf":"\nbase.dists.cauchy.cdf( x, x0, Ɣ )\n    Evaluates the cumulative distribution function (CDF) for a Cauchy\n    distribution with location parameter `x0` and scale parameter `Ɣ` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `Ɣ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.cauchy.cdf( 4.0, 0.0, 2.0 )\n    ~0.852\n    > y = base.dists.cauchy.cdf( 1.0, 0.0, 2.0 )\n    ~0.648\n    > y = base.dists.cauchy.cdf( 1.0, 3.0, 2.0 )\n    0.25\n    > y = base.dists.cauchy.cdf( NaN, 0.0, 2.0 )\n    NaN\n    > y = base.dists.cauchy.cdf( 1.0, 2.0, NaN )\n    NaN\n    > y = base.dists.cauchy.cdf( 1.0, NaN, 3.0 )\n    NaN\n\n\nbase.dists.cauchy.cdf.factory( x0, Ɣ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Cauchy distribution with location parameter `x0` and scale parameter\n    `Ɣ`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.cauchy.cdf.factory( 1.5, 3.0 );\n    > var y = myCDF( 1.0 )\n    ~0.447\n\n","base.dists.cauchy.cdf.factory":"\nbase.dists.cauchy.cdf.factory( x0, Ɣ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Cauchy distribution with location parameter `x0` and scale parameter\n    `Ɣ`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.cauchy.cdf.factory( 1.5, 3.0 );\n    > var y = myCDF( 1.0 )\n    ~0.447","base.dists.cauchy.entropy":"\nbase.dists.cauchy.entropy( x0, Ɣ )\n    Returns the differential entropy of a Cauchy distribution (in nats).\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `Ɣ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.cauchy.entropy( 10.0, 7.0 )\n    ~4.477\n    > v = base.dists.cauchy.entropy( 22.0, 0.5 )\n    ~1.838\n    > v = base.dists.cauchy.entropy( 10.3, -0.5 )\n    NaN\n\n","base.dists.cauchy.logcdf":"\nbase.dists.cauchy.logcdf( x, x0, Ɣ )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (logCDF) for a Cauchy distribution with location parameter `x0` and scale\n    parameter `Ɣ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `Ɣ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Natural logarithm of the CDF.\n\n    Examples\n    --------\n    > var y = base.dists.cauchy.logcdf( 4.0, 0.0, 2.0 )\n    ~-0.16\n    > y = base.dists.cauchy.logcdf( 1.0, 0.0, 2.0 )\n    ~-0.435\n    > y = base.dists.cauchy.logcdf( 1.0, 3.0, 2.0 )\n    ~-1.386\n    > y = base.dists.cauchy.logcdf( NaN, 0.0, 2.0 )\n    NaN\n    > y = base.dists.cauchy.logcdf( 1.0, 2.0, NaN )\n    NaN\n    > y = base.dists.cauchy.logcdf( 1.0, NaN, 3.0 )\n    NaN\n\n\nbase.dists.cauchy.logcdf.factory( x0, Ɣ )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (logCDF) of a Cauchy distribution with location\n    parameter `x0` and scale parameter `Ɣ`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Function to evaluate the natural logarithm of CDF.\n\n    Examples\n    --------\n    > var mylogCDF = base.dists.cauchy.logcdf.factory( 1.5, 3.0 );\n    > var y = mylogCDF( 1.0 )\n    ~-0.804\n\n","base.dists.cauchy.logcdf.factory":"\nbase.dists.cauchy.logcdf.factory( x0, Ɣ )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (logCDF) of a Cauchy distribution with location\n    parameter `x0` and scale parameter `Ɣ`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Function to evaluate the natural logarithm of CDF.\n\n    Examples\n    --------\n    > var mylogCDF = base.dists.cauchy.logcdf.factory( 1.5, 3.0 );\n    > var y = mylogCDF( 1.0 )\n    ~-0.804","base.dists.cauchy.logpdf":"\nbase.dists.cauchy.logpdf( x, x0, Ɣ )\n    Evaluates the natural logarithm of the probability density function (logPDF)\n    for a Cauchy distribution with location parameter `x0` and scale parameter\n    `Ɣ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `Ɣ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Natural logarithm of PDF.\n\n    Examples\n    --------\n    > var y = base.dists.cauchy.logpdf( 2.0, 1.0, 1.0 )\n    ~-1.838\n    > y = base.dists.cauchy.logpdf( 4.0, 3.0, 0.1 )\n    ~-3.457\n    > y = base.dists.cauchy.logpdf( 4.0, 3.0, 3.0 )\n    ~-2.349\n    > y = base.dists.cauchy.logpdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.cauchy.logpdf( 2.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.cauchy.logpdf( 2.0, 1.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.cauchy.logpdf( 2.0, 1.0, -2.0 )\n    NaN\n\n\nbase.dists.cauchy.logpdf.factory( x0, Ɣ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (logPDF) of a Cauchy distribution with location parameter\n    `x0` and scale parameter `Ɣ`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Function to evaluate the natural logarithm of the PDF.\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.cauchy.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogPDF( 10.0 )\n    ~-1.838\n\n","base.dists.cauchy.logpdf.factory":"\nbase.dists.cauchy.logpdf.factory( x0, Ɣ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (logPDF) of a Cauchy distribution with location parameter\n    `x0` and scale parameter `Ɣ`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Function to evaluate the natural logarithm of the PDF.\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.cauchy.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogPDF( 10.0 )\n    ~-1.838","base.dists.cauchy.median":"\nbase.dists.cauchy.median( x0, Ɣ )\n    Returns the median of a Cauchy distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `Ɣ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.cauchy.median( 10.0, 5.0 )\n    10.0\n    > v = base.dists.cauchy.median( 7.0, 0.5 )\n    7.0\n    > v = base.dists.cauchy.median( 10.3, -0.5 )\n    NaN\n\n","base.dists.cauchy.mode":"\nbase.dists.cauchy.mode( x0, Ɣ )\n    Returns the mode of a Cauchy distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `Ɣ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.cauchy.mode( 10.0, 5.0 )\n    10.0\n    > v = base.dists.cauchy.mode( 7.0, 0.5 )\n    7.0\n    > v = base.dists.cauchy.mode( 10.3, -0.5 )\n    NaN\n\n","base.dists.cauchy.pdf":"\nbase.dists.cauchy.pdf( x, x0, Ɣ )\n    Evaluates the probability density function (PDF) for a Cauchy distribution\n    with location parameter `x0` and scale parameter `Ɣ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `Ɣ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.cauchy.pdf( 2.0, 1.0, 1.0 )\n    ~0.159\n    > y = base.dists.cauchy.pdf( 4.0, 3.0, 0.1 )\n    ~0.0315\n    > y = base.dists.cauchy.pdf( 4.0, 3.0, 3.0 )\n    ~0.095\n    > y = base.dists.cauchy.pdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.cauchy.pdf( 2.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.cauchy.pdf( 2.0, 1.0, NaN )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.cauchy.pdf( 2.0, 1.0, -2.0 )\n    NaN\n\n\nbase.dists.cauchy.pdf.factory( x0, Ɣ )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Cauchy distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.cauchy.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    ~0.159\n\n","base.dists.cauchy.pdf.factory":"\nbase.dists.cauchy.pdf.factory( x0, Ɣ )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Cauchy distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.cauchy.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    ~0.159","base.dists.cauchy.quantile":"\nbase.dists.cauchy.quantile( p, x0, Ɣ )\n    Evaluates the quantile function for a Cauchy distribution with location\n    parameter `x0`  and scale parameter `Ɣ` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `Ɣ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.cauchy.quantile( 0.3, 2.0, 2.0 )\n    ~0.547\n    > y = base.dists.cauchy.quantile( 0.8, 10, 2.0 )\n    ~12.753\n    > y = base.dists.cauchy.quantile( 0.1, 10.0, 2.0 )\n    ~3.845\n\n    > y = base.dists.cauchy.quantile( 1.1, 0.0, 1.0 )\n    NaN\n    > y = base.dists.cauchy.quantile( -0.2, 0.0, 1.0 )\n    NaN\n\n    > y = base.dists.cauchy.quantile( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.cauchy.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.cauchy.quantile( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.cauchy.quantile( 0.5, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.cauchy.quantile.factory( x0, Ɣ )\n    Returns a function for evaluating the quantile function of a Cauchy\n    distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.cauchy.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    10.0\n\n","base.dists.cauchy.quantile.factory":"\nbase.dists.cauchy.quantile.factory( x0, Ɣ )\n    Returns a function for evaluating the quantile function of a Cauchy\n    distribution with location parameter `x0` and scale parameter `Ɣ`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.cauchy.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    10.0","base.dists.chi.cdf":"\nbase.dists.chi.cdf( x, k )\n    Evaluates the cumulative distribution function (CDF) for a chi distribution\n    with degrees of freedom `k` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.chi.cdf( 2.0, 3.0 )\n    ~0.739\n    > y = base.dists.chi.cdf( 1.0, 0.5 )\n    ~0.846\n    > y = base.dists.chi.cdf( -1.0, 4.0 )\n    0.0\n    > y = base.dists.chi.cdf( NaN, 1.0 )\n    NaN\n    > y = base.dists.chi.cdf( 0.0, NaN )\n    NaN\n\n    // Negative degrees of freedom:\n    > y = base.dists.chi.cdf( 2.0, -1.0 )\n    NaN\n\n    // Degenerate distribution when `k = 0`:\n    > y = base.dists.chi.cdf( 2.0, 0.0 )\n    1.0\n    > y = base.dists.chi.cdf( -2.0, 0.0 )\n    0.0\n    > y = base.dists.chi.cdf( 0.0, 0.0 )\n    0.0\n\nbase.dists.chi.cdf.factory( k )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a chi distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.chi.cdf.factory( 1.0 );\n    > var y = mycdf( 2.0 )\n    ~0.954\n    > y = mycdf( 1.2 )\n    ~0.77\n\n","base.dists.chi.cdf.factory":"\nbase.dists.chi.cdf.factory( k )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a chi distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.chi.cdf.factory( 1.0 );\n    > var y = mycdf( 2.0 )\n    ~0.954\n    > y = mycdf( 1.2 )\n    ~0.77","base.dists.chi.Chi":"\nbase.dists.chi.Chi( [k] )\n    Returns a chi distribution object.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    chi: Object\n        Distribution instance.\n\n    chi.k: number\n        Degrees of freedom. If set, the value must be greater than `0`.\n\n    chi.entropy: number\n        Read-only property which returns the differential entropy.\n\n    chi.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    chi.mean: number\n        Read-only property which returns the expected value.\n\n    chi.mode: number\n        Read-only property which returns the mode.\n\n    chi.skewness: number\n        Read-only property which returns the skewness.\n\n    chi.stdev: number\n        Read-only property which returns the standard deviation.\n\n    chi.variance: number\n        Read-only property which returns the variance.\n\n    chi.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    chi.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    chi.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    chi.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var chi = base.dists.chi.Chi( 6.0 );\n    > chi.k\n    6.0\n    > chi.entropy\n    ~1.04\n    > chi.kurtosis\n    ~0.025\n    > chi.mean\n    ~2.35\n    > chi.mode\n    ~2.236\n    > chi.skewness\n    ~0.318\n    > chi.stdev\n    ~0.691\n    > chi.variance\n    ~0.478\n    > chi.cdf( 1.0 )\n    ~0.014\n    > chi.logpdf( 1.5 )\n    ~-1.177\n    > chi.pdf( 1.5 )\n    ~0.308\n    > chi.quantile( 0.5 )\n    ~2.313\n\n","base.dists.chi.entropy":"\nbase.dists.chi.entropy( k )\n    Returns the differential entropy of a chi distribution (in nats).\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.chi.entropy( 11.0 )\n    ~1.056\n    > v = base.dists.chi.entropy( 1.5 )\n    ~0.878\n\n","base.dists.chi.kurtosis":"\nbase.dists.chi.kurtosis( k )\n    Returns the excess kurtosis of a chi distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.chi.kurtosis( 9.0 )\n    ~0.011\n    > v = base.dists.chi.kurtosis( 1.5 )\n    ~0.424\n\n","base.dists.chi.logpdf":"\nbase.dists.chi.logpdf( x, k )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a chi distribution with degrees of freedom `k` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.chi.logpdf( 0.3, 4.0 )\n    ~-4.35\n    > y = base.dists.chi.logpdf( 0.7, 0.7 )\n    ~-0.622\n    > y = base.dists.chi.logpdf( -1.0, 0.5 )\n    -Infinity\n    > y = base.dists.chi.logpdf( 0.0, NaN )\n    NaN\n    > y = base.dists.chi.logpdf( NaN, 2.0 )\n    NaN\n\n    // Negative degrees of freedom:\n    > y = base.dists.chi.logpdf( 2.0, -1.0 )\n    NaN\n\n    // Degenerate distribution when `k = 0`:\n    > y = base.dists.chi.logpdf( 2.0, 0.0, 2.0 )\n    -Infinity\n    > y = base.dists.chi.logpdf( 0.0, 0.0, 2.0 )\n    Infinity\n\n\nbase.dists.chi.logpdf.factory( k )\n    Returns a function for evaluating the natural logarithm of the  probability\n    density function (PDF) of a chi distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.chi.logpdf.factory( 6.0 );\n    > var y = mylogPDF( 3.0 )\n    ~-1.086\n\n","base.dists.chi.logpdf.factory":"\nbase.dists.chi.logpdf.factory( k )\n    Returns a function for evaluating the natural logarithm of the  probability\n    density function (PDF) of a chi distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.chi.logpdf.factory( 6.0 );\n    > var y = mylogPDF( 3.0 )\n    ~-1.086","base.dists.chi.mean":"\nbase.dists.chi.mean( k )\n    Returns the expected value of a chi distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.chi.mean( 11.0 )\n    ~3.242\n    > v = base.dists.chi.mean( 4.5 )\n    ~2.008\n\n","base.dists.chi.mode":"\nbase.dists.chi.mode( k )\n    Returns the mode of a chi distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.chi.mode( 11.0 )\n    ~3.162\n    > v = base.dists.chi.mode( 1.5 )\n    ~0.707\n\n","base.dists.chi.pdf":"\nbase.dists.chi.pdf( x, k )\n    Evaluates the probability density function (PDF) for a chi distribution with\n    degrees of freedom `k` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.chi.pdf( 0.3, 4.0 )\n    ~0.013\n    > y = base.dists.chi.pdf( 0.7, 0.7 )\n    ~0.537\n    > y = base.dists.chi.pdf( -1.0, 0.5 )\n    0.0\n    > y = base.dists.chi.pdf( 0.0, NaN )\n    NaN\n    > y = base.dists.chi.pdf( NaN, 2.0 )\n    NaN\n\n    // Negative degrees of freedom:\n    > y = base.dists.chi.pdf( 2.0, -1.0 )\n    NaN\n\n    // Degenerate distribution when `k = 0`:\n    > y = base.dists.chi.pdf( 2.0, 0.0, 2.0 )\n    0.0\n    > y = base.dists.chi.pdf( 0.0, 0.0, 2.0 )\n    Infinity\n\n\nbase.dists.chi.pdf.factory( k )\n    Returns a function for evaluating the probability density function (PDF) of\n    a chi distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.chi.pdf.factory( 6.0 );\n    > var y = myPDF( 3.0 )\n    ~0.337\n\n","base.dists.chi.pdf.factory":"\nbase.dists.chi.pdf.factory( k )\n    Returns a function for evaluating the probability density function (PDF) of\n    a chi distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.chi.pdf.factory( 6.0 );\n    > var y = myPDF( 3.0 )\n    ~0.337","base.dists.chi.quantile":"\nbase.dists.chi.quantile( p, k )\n    Evaluates the quantile function for a chi distribution with degrees of\n    freedom `k` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.chi.quantile( 0.8, 1.0 )\n    ~1.282\n    > y = base.dists.chi.quantile( 0.5, 4.0 )\n    ~1.832\n    > y = base.dists.chi.quantile( 0.8, 0.1 )\n    ~0.116\n    > y = base.dists.chi.quantile( -0.2, 0.5 )\n    NaN\n    > y = base.dists.chi.quantile( 1.1, 0.5 )\n    NaN\n    > y = base.dists.chi.quantile( NaN, 1.0 )\n    NaN\n    > y = base.dists.chi.quantile( 0.0, NaN )\n    NaN\n\n    // Negative degrees of freedom:\n    > y = base.dists.chi.quantile( 0.5, -1.0 )\n    NaN\n\n    // Degenerate distribution when `k = 0`:\n    > y = base.dists.chi.quantile( 0.3, 0.0 )\n    0.0\n    > y = base.dists.chi.quantile( 0.9, 0.0 )\n    0.0\n\n\nbase.dists.chi.quantile.factory( k )\n    Returns a function for evaluating the quantile function of a chi\n    distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.chi.quantile.factory( 2.0 );\n    > var y = myquantile( 0.3 )\n    ~0.845\n    > y = myquantile( 0.7 )\n    ~1.552\n\n","base.dists.chi.quantile.factory":"\nbase.dists.chi.quantile.factory( k )\n    Returns a function for evaluating the quantile function of a chi\n    distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.chi.quantile.factory( 2.0 );\n    > var y = myquantile( 0.3 )\n    ~0.845\n    > y = myquantile( 0.7 )\n    ~1.552","base.dists.chi.skewness":"\nbase.dists.chi.skewness( k )\n    Returns the skewness of a chi distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.chi.skewness( 11.0 )\n    ~0.225\n    > v = base.dists.chi.skewness( 1.5 )\n    ~0.763\n\n","base.dists.chi.stdev":"\nbase.dists.chi.stdev( k )\n    Returns the standard deviation of a chi distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.chi.stdev( 11.0 )\n    ~0.699\n    > v = base.dists.chi.stdev( 1.5 )\n    ~0.637\n\n","base.dists.chi.variance":"\nbase.dists.chi.variance( k )\n    Returns the variance of a chi distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.chi.variance( 11.0 )\n    ~0.488\n    > v = base.dists.chi.variance( 1.5 )\n    ~0.406\n\n","base.dists.chisquare.cdf":"\nbase.dists.chisquare.cdf( x, k )\n    Evaluates the cumulative distribution function (CDF) for a chi-squared\n    distribution with degrees of freedom `k` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.chisquare.cdf( 2.0, 3.0 )\n    ~0.428\n    > y = base.dists.chisquare.cdf( 1.0, 0.5 )\n    ~0.846\n    > y = base.dists.chisquare.cdf( -1.0, 4.0 )\n    0.0\n    > y = base.dists.chisquare.cdf( NaN, 1.0 )\n    NaN\n    > y = base.dists.chisquare.cdf( 0.0, NaN )\n    NaN\n\n    // Negative degrees of freedom:\n    > y = base.dists.chisquare.cdf( 2.0, -1.0 )\n    NaN\n\n    // Degenerate distribution when `k = 0`:\n    > y = base.dists.chisquare.cdf( 2.0, 0.0 )\n    1.0\n    > y = base.dists.chisquare.cdf( -2.0, 0.0 )\n    0.0\n    > y = base.dists.chisquare.cdf( 0.0, 0.0 )\n    0.0\n\nbase.dists.chisquare.cdf.factory( k )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a chi-squared distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.chisquare.cdf.factory( 1.0 );\n    > var y = mycdf( 2.0 )\n    ~0.843\n    > y = mycdf( 1.2 )\n    ~0.727\n\n","base.dists.chisquare.cdf.factory":"\nbase.dists.chisquare.cdf.factory( k )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a chi-squared distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.chisquare.cdf.factory( 1.0 );\n    > var y = mycdf( 2.0 )\n    ~0.843\n    > y = mycdf( 1.2 )\n    ~0.727","base.dists.chisquare.ChiSquare":"\nbase.dists.chisquare.ChiSquare( [k] )\n    Returns a  chi-squared distribution object.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    chisquare: Object\n        Distribution instance.\n\n    chisquare.k: number\n        Degrees of freedom. If set, the value must be greater than `0`.\n\n    chisquare.entropy: number\n        Read-only property which returns the differential entropy.\n\n    chisquare.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    chisquare.mean: number\n        Read-only property which returns the expected value.\n\n    chisquare.median: number\n        Read-only property which returns the median.\n\n    chisquare.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    chisquare.mode: number\n        Read-only property which returns the mode.\n\n    chisquare.skewness: number\n        Read-only property which returns the skewness.\n\n    chisquare.stdev: number\n        Read-only property which returns the standard deviation.\n\n    chisquare.variance: number\n        Read-only property which returns the variance.\n\n    chisquare.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    chisquare.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    chisquare.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var chisquare = base.dists.chisquare.ChiSquare( 6.0 );\n    > chisquare.k\n    6.0\n    > chisquare.entropy\n    ~2.541\n    > chisquare.kurtosis\n    2.0\n    > chisquare.mean\n    6.0\n    > chisquare.median\n    ~5.348\n    > chisquare.mode\n    4.0\n    > chisquare.skewness\n    ~1.155\n    > chisquare.stdev\n    ~3.464\n    > chisquare.variance\n    12.0\n    > chisquare.cdf( 3.0 )\n    ~0.191\n    > chisquare.mgf( 0.2 )\n    ~4.63\n    > chisquare.pdf( 1.5 )\n    ~0.066\n    > chisquare.quantile( 0.5 )\n    ~5.348\n\n","base.dists.chisquare.entropy":"\nbase.dists.chisquare.entropy( k )\n    Returns the differential entropy of a chi-squared distribution (in nats).\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.chisquare.entropy( 11.0 )\n    ~2.901\n    > v = base.dists.chisquare.entropy( 1.5 )\n    ~1.375\n\n","base.dists.chisquare.kurtosis":"\nbase.dists.chisquare.kurtosis( k )\n    Returns the excess kurtosis of a chi-squared distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.chisquare.kurtosis( 9.0 )\n    ~1.333\n    > v = base.dists.chisquare.kurtosis( 1.5 )\n    8.0\n\n","base.dists.chisquare.logpdf":"\nbase.dists.chisquare.logpdf( x, k )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a chi-squared distribution with degrees of freedom `k` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.chisquare.logpdf( 0.3, 4.0 )\n    ~-2.74\n    > y = base.dists.chisquare.logpdf( 0.7, 0.7 )\n    ~-1.295\n    > y = base.dists.chisquare.logpdf( -1.0, 0.5 )\n    -Infinity\n    > y = base.dists.chisquare.logpdf( 0.0, NaN )\n    NaN\n    > y = base.dists.chisquare.logpdf( NaN, 2.0 )\n    NaN\n\n    // Negative degrees of freedom:\n    > y = base.dists.chisquare.logpdf( 2.0, -1.0 )\n    NaN\n\n    // Degenerate distribution when `k = 0`:\n    > y = base.dists.chisquare.logpdf( 2.0, 0.0, 2.0 )\n    -Infinity\n    > y = base.dists.chisquare.logpdf( 0.0, 0.0, 2.0 )\n    Infinity\n\n\nbase.dists.chisquare.logpdf.factory( k )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a chi-squared distribution with degrees of freedom\n    `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var myLogPDF = base.dists.chisquare.logpdf.factory( 6.0 );\n    > var y = myLogPDF( 3.0 )\n    ~-2.075\n\n","base.dists.chisquare.logpdf.factory":"\nbase.dists.chisquare.logpdf.factory( k )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a chi-squared distribution with degrees of freedom\n    `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var myLogPDF = base.dists.chisquare.logpdf.factory( 6.0 );\n    > var y = myLogPDF( 3.0 )\n    ~-2.075","base.dists.chisquare.mean":"\nbase.dists.chisquare.mean( k )\n    Returns the expected value of a chi-squared distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.chisquare.mean( 11.0 )\n    11.0\n    > v = base.dists.chisquare.mean( 4.5 )\n    4.5\n\n","base.dists.chisquare.median":"\nbase.dists.chisquare.median( k )\n    Returns the median of a chi-squared distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var k = base.dists.chisquare.median( 9.0 )\n    ~8.343\n    > k = base.dists.chisquare.median( 2.0 )\n    ~1.386\n\n","base.dists.chisquare.mgf":"\nbase.dists.chisquare.mgf( t, k )\n    Evaluates the moment-generating function (MGF) for a chi-squared\n    distribution with degrees of freedom `k` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.chisquare.mgf( 0.4, 2 )\n    ~5.0\n    > y = base.dists.chisquare.mgf( -1.0, 5.0 )\n    ~0.0642\n    > y = base.dists.chisquare.mgf( 0.0, 10.0 )\n    1.0\n\n\nbase.dists.chisquare.mgf.factory( k )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    chi-squared distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.chisquare.mgf.factory( 1.0 );\n    > var y = mymgf( 0.2 )\n    ~1.291\n    > y = mymgf( 0.4 )\n    ~2.236\n\n","base.dists.chisquare.mgf.factory":"\nbase.dists.chisquare.mgf.factory( k )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    chi-squared distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.chisquare.mgf.factory( 1.0 );\n    > var y = mymgf( 0.2 )\n    ~1.291\n    > y = mymgf( 0.4 )\n    ~2.236","base.dists.chisquare.mode":"\nbase.dists.chisquare.mode( k )\n    Returns the mode of a chi-squared distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.chisquare.mode( 11.0 )\n    9.0\n    > v = base.dists.chisquare.mode( 1.5 )\n    0.0\n\n","base.dists.chisquare.pdf":"\nbase.dists.chisquare.pdf( x, k )\n    Evaluates the probability density function (PDF) for a chi-squared\n    distribution with degrees of freedom `k` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.chisquare.pdf( 0.3, 4.0 )\n    ~0.065\n    > y = base.dists.chisquare.pdf( 0.7, 0.7 )\n    ~0.274\n    > y = base.dists.chisquare.pdf( -1.0, 0.5 )\n    0.0\n    > y = base.dists.chisquare.pdf( 0.0, NaN )\n    NaN\n    > y = base.dists.chisquare.pdf( NaN, 2.0 )\n    NaN\n\n    // Negative degrees of freedom:\n    > y = base.dists.chisquare.pdf( 2.0, -1.0 )\n    NaN\n\n    // Degenerate distribution when `k = 0`:\n    > y = base.dists.chisquare.pdf( 2.0, 0.0, 2.0 )\n    0.0\n    > y = base.dists.chisquare.pdf( 0.0, 0.0, 2.0 )\n    Infinity\n\n\nbase.dists.chisquare.pdf.factory( k )\n    Returns a function for evaluating the probability density function (PDF) of\n    a chi-squared distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.chisquare.pdf.factory( 6.0 );\n    > var y = myPDF( 3.0 )\n    ~0.126\n\n","base.dists.chisquare.pdf.factory":"\nbase.dists.chisquare.pdf.factory( k )\n    Returns a function for evaluating the probability density function (PDF) of\n    a chi-squared distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.chisquare.pdf.factory( 6.0 );\n    > var y = myPDF( 3.0 )\n    ~0.126","base.dists.chisquare.quantile":"\nbase.dists.chisquare.quantile( p, k )\n    Evaluates the quantile function for a chi-squared distribution with degrees\n    of freedom `k` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.chisquare.quantile( 0.8, 1.0 )\n    ~1.642\n    > y = base.dists.chisquare.quantile( 0.5, 4.0 )\n    ~3.357\n    > y = base.dists.chisquare.quantile( 0.8, 0.1 )\n    ~0.014\n    > y = base.dists.chisquare.quantile( -0.2, 0.5 )\n    NaN\n    > y = base.dists.chisquare.quantile( 1.1, 0.5 )\n    NaN\n    > y = base.dists.chisquare.quantile( NaN, 1.0 )\n    NaN\n    > y = base.dists.chisquare.quantile( 0.0, NaN )\n    NaN\n\n    // Negative degrees of freedom:\n    > y = base.dists.chisquare.quantile( 0.5, -1.0 )\n    NaN\n\n    // Degenerate distribution when `k = 0`:\n    > y = base.dists.chisquare.quantile( 0.3, 0.0 )\n    0.0\n    > y = base.dists.chisquare.quantile( 0.9, 0.0 )\n    0.0\n\n\nbase.dists.chisquare.quantile.factory( k )\n    Returns a function for evaluating the quantile function of a chi-squared\n    distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.chisquare.quantile.factory( 2.0 );\n    > var y = myquantile( 0.3 )\n    ~0.713\n    > y = myquantile( 0.7 )\n    ~2.408\n\n","base.dists.chisquare.quantile.factory":"\nbase.dists.chisquare.quantile.factory( k )\n    Returns a function for evaluating the quantile function of a chi-squared\n    distribution with degrees of freedom `k`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.chisquare.quantile.factory( 2.0 );\n    > var y = myquantile( 0.3 )\n    ~0.713\n    > y = myquantile( 0.7 )\n    ~2.408","base.dists.chisquare.skewness":"\nbase.dists.chisquare.skewness( k )\n    Returns the skewness of a chi-squared distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.chisquare.skewness( 11.0 )\n    ~0.853\n    > v = base.dists.chisquare.skewness( 1.5 )\n    ~2.309\n\n","base.dists.chisquare.stdev":"\nbase.dists.chisquare.stdev( k )\n    Returns the standard deviation of a chi-squared distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.chisquare.stdev( 11.0 )\n    ~4.69\n    > v = base.dists.chisquare.stdev( 1.5 )\n    ~1.732\n\n","base.dists.chisquare.variance":"\nbase.dists.chisquare.variance( k )\n    Returns the variance of a chi-squared distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `k < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.chisquare.variance( 11.0 )\n    22.0\n    > v = base.dists.chisquare.variance( 1.5 )\n    3.0\n\n","base.dists.cosine.cdf":"\nbase.dists.cosine.cdf( x, μ, s )\n    Evaluates the cumulative distribution function (CDF) for a raised cosine\n    distribution with location parameter `μ` and scale parameter `s` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.cdf( 2.0, 0.0, 3.0 )\n    ~0.971\n    > y = base.dists.cosine.cdf( 9.0, 10.0, 3.0 )\n    ~0.196\n\n    > y = base.dists.cosine.cdf( 2.0, 0.0, NaN )\n    NaN\n    > y = base.dists.cosine.cdf( 2.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.cdf( NaN, 0.0, 1.0 )\n    NaN\n\n    // Degenerate distribution centered at `μ` when `s = 0.0`:\n    > y = base.dists.cosine.cdf( 2.0, 8.0, 0.0 )\n    0.0\n    > y = base.dists.cosine.cdf( 8.0, 8.0, 0.0 )\n    1.0\n    > y = base.dists.cosine.cdf( 10.0, 8.0, 0.0 )\n    1.0\n\n\nbase.dists.cosine.cdf.factory( μ, s )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a raised cosine distribution with location parameter `μ` and scale\n    parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.cosine.cdf.factory( 3.0, 1.5 );\n    > var y = mycdf( 1.9 )\n    ~0.015\n\n","base.dists.cosine.cdf.factory":"\nbase.dists.cosine.cdf.factory( μ, s )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a raised cosine distribution with location parameter `μ` and scale\n    parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.cosine.cdf.factory( 3.0, 1.5 );\n    > var y = mycdf( 1.9 )\n    ~0.015","base.dists.cosine.Cosine":"\nbase.dists.cosine.Cosine( [μ, s] )\n    Returns a raised cosine distribution object.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter. Default: `0.0`.\n\n    s: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    cosine: Object\n        Distribution instance.\n\n    cosine.mu: number\n        Location parameter.\n\n    cosine.s: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    cosine.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    cosine.mean: number\n        Read-only property which returns the expected value.\n\n    cosine.median: number\n        Read-only property which returns the median.\n\n    cosine.mode: number\n        Read-only property which returns the mode.\n\n    cosine.skewness: number\n        Read-only property which returns the skewness.\n\n    cosine.stdev: number\n        Read-only property which returns the standard deviation.\n\n    cosine.variance: number\n        Read-only property which returns the variance.\n\n    cosine.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    cosine.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    cosine.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    cosine.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    cosine.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    cosine.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var cosine = base.dists.cosine.Cosine( -2.0, 3.0 );\n    > cosine.mu\n    -2.0\n    > cosine.s\n    3.0\n    > cosine.kurtosis\n    ~-0.594\n    > cosine.mean\n    -2.0\n    > cosine.median\n    -2.0\n    > cosine.mode\n    -2.0\n    > cosine.skewness\n    0.0\n    > cosine.stdev\n    ~1.085\n    > cosine.variance\n    ~1.176\n    > cosine.cdf( 0.5 )\n    ~0.996\n    > cosine.logcdf( 0.5 )\n    ~-0.004\n    > cosine.logpdf( -1.0 )\n    ~-1.386\n    > cosine.mgf( 0.2 )\n    ~0.686\n    > cosine.pdf( -2.0 )\n    ~0.333\n    > cosine.quantile( 0.9 )\n    ~-0.553\n\n","base.dists.cosine.kurtosis":"\nbase.dists.cosine.kurtosis( μ, s )\n    Returns the excess kurtosis of a raised cosine distribution with location\n    parameter `μ` and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.kurtosis( 0.0, 1.0 )\n    ~-0.594\n    > y = base.dists.cosine.kurtosis( 4.0, 2.0 )\n    ~-0.594\n    > y = base.dists.cosine.kurtosis( NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.kurtosis( 0.0, NaN )\n    NaN\n    > y = base.dists.cosine.kurtosis( 0.0, 0.0 )\n    NaN\n\n","base.dists.cosine.logcdf":"\nbase.dists.cosine.logcdf( x, μ, s )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a raised cosine distribution with location parameter `μ` and scale\n     parameter `s` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.logcdf( 2.0, 0.0, 3.0 )\n    ~-0.029\n    > y = base.dists.cosine.logcdf( 9.0, 10.0, 3.0 )\n    ~-1.632\n\n    > y = base.dists.cosine.logcdf( 2.0, 0.0, NaN )\n    NaN\n    > y = base.dists.cosine.logcdf( 2.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.logcdf( NaN, 0.0, 1.0 )\n    NaN\n\n    // Degenerate distribution centered at `μ` when `s = 0.0`:\n    > y = base.dists.cosine.logcdf( 2.0, 8.0, 0.0 )\n    -Infinity\n    > y = base.dists.cosine.logcdf( 8.0, 8.0, 0.0 )\n    0.0\n    > y = base.dists.cosine.logcdf( 10.0, 8.0, 0.0 )\n    0.0\n\n\nbase.dists.cosine.logcdf.factory( μ, s )\n    Returns a function for evaluating the natural logarithm of the  cumulative\n    distribution function (CDF) of a raised cosine distribution with location\n    parameter `μ` and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.cosine.logcdf.factory( 3.0, 1.5 );\n    > var y = mylogcdf( 1.9 )\n    ~-4.2\n\n","base.dists.cosine.logcdf.factory":"\nbase.dists.cosine.logcdf.factory( μ, s )\n    Returns a function for evaluating the natural logarithm of the  cumulative\n    distribution function (CDF) of a raised cosine distribution with location\n    parameter `μ` and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.cosine.logcdf.factory( 3.0, 1.5 );\n    > var y = mylogcdf( 1.9 )\n    ~-4.2","base.dists.cosine.logpdf":"\nbase.dists.cosine.logpdf( x, μ, s )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    raised cosine distribution with location parameter `μ` and scale parameter\n    `s` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.logpdf( 2.0, 0.0, 3.0 )\n    ~-2.485\n    > y = base.dists.cosine.logpdf( -1.0, 2.0, 4.0 )\n    ~-3.307\n    > y = base.dists.cosine.logpdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.cosine.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.logpdf( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.cosine.logpdf( 2.0, 0.0, -1.0 )\n    NaN\n\n    // Degenerate distribution at `s = 0.0`:\n    > y = base.dists.cosine.logpdf( 2.0, 8.0, 0.0 )\n    -Infinity\n    > y = base.dists.cosine.logpdf( 8.0, 8.0, 0.0 )\n    Infinity\n\n\nbase.dists.cosine.logpdf.factory( μ, s )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a raised cosine distribution with location parameter `μ`\n    and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.cosine.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogpdf( 10.0 )\n    ~-0.693\n\n","base.dists.cosine.logpdf.factory":"\nbase.dists.cosine.logpdf.factory( μ, s )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a raised cosine distribution with location parameter `μ`\n    and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.cosine.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogpdf( 10.0 )\n    ~-0.693","base.dists.cosine.mean":"\nbase.dists.cosine.mean( μ, s )\n    Returns the expected value of a raised cosine distribution with location\n    parameter `μ` and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.mean( 0.0, 1.0 )\n    0.0\n    > y = base.dists.cosine.mean( 4.0, 2.0 )\n    4.0\n    > y = base.dists.cosine.mean( NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.mean( 0.0, NaN )\n    NaN\n    > y = base.dists.cosine.mean( 0.0, 0.0 )\n    NaN\n\n","base.dists.cosine.median":"\nbase.dists.cosine.median( μ, s )\n    Returns the median of a raised cosine distribution with location parameter\n    `μ` and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.median( 0.0, 1.0 )\n    0.0\n    > y = base.dists.cosine.median( 4.0, 2.0 )\n    4.0\n    > y = base.dists.cosine.median( NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.median( 0.0, NaN )\n    NaN\n    > y = base.dists.cosine.median( 0.0, 0.0 )\n    NaN\n\n","base.dists.cosine.mgf":"\nbase.dists.cosine.mgf( t, μ, s )\n    Evaluates the moment-generating function (MGF) for a raised cosine\n    distribution with location parameter `μ` and scale parameter `s` at a value\n    `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.mgf( 2.0, 0.0, 3.0 )\n    ~7.234\n    > y = base.dists.cosine.mgf( 9.0, 10.0, 3.0 )\n    ~1.606e+47\n\n    > y = base.dists.cosine.mgf( 0.5, 0.0, NaN )\n    NaN\n    > y = base.dists.cosine.mgf( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.mgf( NaN, 0.0, 1.0 )\n    NaN\n\n\nbase.dists.cosine.mgf.factory( μ, s )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    raised cosine distribution with location parameter `μ` and scale parameter\n    `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.cosine.mgf.factory( 3.0, 1.5 );\n    > var y = mymgf( 1.9 )\n    ~495.57\n\n","base.dists.cosine.mgf.factory":"\nbase.dists.cosine.mgf.factory( μ, s )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    raised cosine distribution with location parameter `μ` and scale parameter\n    `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.cosine.mgf.factory( 3.0, 1.5 );\n    > var y = mymgf( 1.9 )\n    ~495.57","base.dists.cosine.mode":"\nbase.dists.cosine.mode( μ, s )\n    Returns the mode of a raised cosine distribution with location parameter `μ`\n    and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.mode( 0.0, 1.0 )\n    0.0\n    > y = base.dists.cosine.mode( 4.0, 2.0 )\n    4.0\n    > y = base.dists.cosine.mode( NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.mode( 0.0, NaN )\n    NaN\n    > y = base.dists.cosine.mode( 0.0, 0.0 )\n    NaN\n\n","base.dists.cosine.pdf":"\nbase.dists.cosine.pdf( x, μ, s )\n    Evaluates the probability density function (PDF) for a raised cosine\n    distribution with location parameter `μ` and scale parameter `s` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.pdf( 2.0, 0.0, 3.0 )\n    ~0.083\n    > y = base.dists.cosine.pdf( 2.4, 4.0, 2.0 )\n    ~0.048\n    > y = base.dists.cosine.pdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.cosine.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.pdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.cosine.pdf( 2.0, 0.0, -1.0 )\n    NaN\n    > y = base.dists.cosine.pdf( 2.0, 8.0, 0.0 )\n    0.0\n    > y = base.dists.cosine.pdf( 8.0, 8.0, 0.0 )\n    Infinity\n\n\nbase.dists.cosine.pdf.factory( μ, s )\n    Returns a function for evaluating the probability density function (PDF) of\n    a raised cosine distribution with location parameter `μ` and scale parameter\n    `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.cosine.pdf.factory( 0.0, 3.0 );\n    > var y = myPDF( 2.0 )\n    ~0.083\n\n","base.dists.cosine.pdf.factory":"\nbase.dists.cosine.pdf.factory( μ, s )\n    Returns a function for evaluating the probability density function (PDF) of\n    a raised cosine distribution with location parameter `μ` and scale parameter\n    `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.cosine.pdf.factory( 0.0, 3.0 );\n    > var y = myPDF( 2.0 )\n    ~0.083","base.dists.cosine.quantile":"\nbase.dists.cosine.quantile( p, μ, s )\n    Evaluates the quantile function for a raised cosine distribution with\n    location parameter `μ` and scale parameter `s` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.quantile( 0.8, 0.0, 1.0 )\n    ~0.327\n    > y = base.dists.cosine.quantile( 0.5, 4.0, 2.0 )\n    ~4.0\n\n    > y = base.dists.cosine.quantile( 1.1, 0.0, 1.0 )\n    NaN\n    > y = base.dists.cosine.quantile( -0.2, 0.0, 1.0 )\n    NaN\n\n    > y = base.dists.cosine.quantile( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.cosine.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.quantile( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.cosine.quantile( 0.5, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.cosine.quantile.factory( μ, s )\n    Returns a function for evaluating the quantile function of a raised cosine\n    distribution with location parameter `μ` and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.cosine.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.3 )\n    ~9.586\n\n","base.dists.cosine.quantile.factory":"\nbase.dists.cosine.quantile.factory( μ, s )\n    Returns a function for evaluating the quantile function of a raised cosine\n    distribution with location parameter `μ` and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.cosine.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.3 )\n    ~9.586","base.dists.cosine.skewness":"\nbase.dists.cosine.skewness( μ, s )\n    Returns the skewness of a raised cosine distribution with location parameter\n    `μ` and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.skewness( 0.0, 1.0 )\n    0.0\n    > y = base.dists.cosine.skewness( 4.0, 2.0 )\n    0.0\n    > y = base.dists.cosine.skewness( NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.skewness( 0.0, NaN )\n    NaN\n    > y = base.dists.cosine.skewness( 0.0, 0.0 )\n    NaN\n\n","base.dists.cosine.stdev":"\nbase.dists.cosine.stdev( μ, s )\n    Returns the standard deviation of a raised cosine distribution with location\n    parameter `μ` and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.stdev( 0.0, 1.0 )\n    ~0.362\n    > y = base.dists.cosine.stdev( 4.0, 2.0 )\n    ~0.723\n    > y = base.dists.cosine.stdev( NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.stdev( 0.0, NaN )\n    NaN\n    > y = base.dists.cosine.stdev( 0.0, 0.0 )\n    NaN\n\n","base.dists.cosine.variance":"\nbase.dists.cosine.variance( μ, s )\n    Returns the variance of a raised cosine distribution with location parameter\n    `μ` and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var y = base.dists.cosine.variance( 0.0, 1.0 )\n    ~0.131\n    > y = base.dists.cosine.variance( 4.0, 2.0 )\n    ~0.523\n    > y = base.dists.cosine.variance( NaN, 1.0 )\n    NaN\n    > y = base.dists.cosine.variance( 0.0, NaN )\n    NaN\n    > y = base.dists.cosine.variance( 0.0, 0.0 )\n    NaN\n\n","base.dists.degenerate.cdf":"\nbase.dists.degenerate.cdf( x, μ )\n    Evaluates the cumulative distribution function (CDF) for a degenerate\n    distribution with mean value `μ`.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.degenerate.cdf( 2.0, 3.0 )\n    0.0\n    > y = base.dists.degenerate.cdf( 4.0, 3.0 )\n    1.0\n    > y = base.dists.degenerate.cdf( 3.0, 3.0 )\n    1.0\n    > y = base.dists.degenerate.cdf( NaN, 0.0 )\n    NaN\n    > y = base.dists.degenerate.cdf( 0.0, NaN )\n    NaN\n\n\nbase.dists.degenerate.cdf.factory( μ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a degenerate distribution centered at a provided mean value.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.degenerate.cdf.factory( 5.0 );\n    > var y = myCDF( 3.0 )\n    0.0\n    > y = myCDF( 6.0 )\n    1.0\n\n","base.dists.degenerate.cdf.factory":"\nbase.dists.degenerate.cdf.factory( μ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a degenerate distribution centered at a provided mean value.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.degenerate.cdf.factory( 5.0 );\n    > var y = myCDF( 3.0 )\n    0.0\n    > y = myCDF( 6.0 )\n    1.0","base.dists.degenerate.Degenerate":"\nbase.dists.degenerate.Degenerate( [μ] )\n    Returns a degenerate distribution object.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Constant value of distribution.\n\n    Returns\n    -------\n    degenerate: Object\n        Distribution instance.\n\n    degenerate.mu: number\n        Constant value of distribution.\n\n    degenerate.entropy: number\n        Read-only property which returns the differential entropy.\n\n    degenerate.mean: number\n        Read-only property which returns the expected value.\n\n    degenerate.median: number\n        Read-only property which returns the median.\n\n    degenerate.stdev: number\n        Read-only property which returns the standard deviation.\n\n    degenerate.variance: number\n        Read-only property which returns the variance.\n\n    degenerate.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    degenerate.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    degenerate.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    degenerate.logpmf: Function\n        Evaluates the natural logarithm of the probability mass function\n        (PMF).\n\n    degenerate.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    degenerate.pmf: Function\n        Evaluates the probability mass function (PMF).\n\n    degenerate.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    degenerate.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var degenerate = base.dists.degenerate.Degenerate( 2.0 );\n    > degenerate.mu\n    2.0\n    > degenerate.entropy\n    0.0\n    > degenerate.mean\n    2.0\n    > degenerate.mode\n    2.0\n    > degenerate.median\n    2.0\n    > degenerate.stdev\n    0.0\n    > degenerate.variance\n    0.0\n    > degenerate.cdf( 0.5 )\n    0.0\n    > degenerate.logcdf( 2.5 )\n    0.0\n    > degenerate.logpdf( 0.5 )\n    -Infinity\n    > degenerate.logpmf( 2.5 )\n    -Infinity\n    > degenerate.mgf( 0.2 )\n    ~1.492\n    > degenerate.pdf( 2.0 )\n    +Infinity\n    > degenerate.pmf( 2.0 )\n    1.0\n    > degenerate.quantile( 0.7 )\n    2.0\n\n","base.dists.degenerate.entropy":"\nbase.dists.degenerate.entropy( μ )\n    Returns the entropy of a degenerate distribution with constant value `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.degenerate.entropy( 20.0 )\n    0.0\n    > v = base.dists.degenerate.entropy( -10.0 )\n    0.0\n\n","base.dists.degenerate.logcdf":"\nbase.dists.degenerate.logcdf( x, μ )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (logCDF) for a degenerate distribution with mean `μ`.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Natural logarithm of the CDF.\n\n    Examples\n    --------\n    > var y = base.dists.degenerate.logcdf( 2.0, 3.0 )\n    -Infinity\n    > y = base.dists.degenerate.logcdf( 4.0, 3.0 )\n    0\n    > y = base.dists.degenerate.logcdf( 3.0, 3.0 )\n    0\n    > y = base.dists.degenerate.logcdf( NaN, 0.0 )\n    NaN\n    > y = base.dists.degenerate.logcdf( 0.0, NaN )\n    NaN\n\n\nbase.dists.degenerate.logcdf.factory( μ )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (logCDF) of a degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    logcdf: Function\n        Function to evaluate the natural logarithm of cumulative distribution\n        function (logCDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.degenerate.logcdf.factory( 5.0 );\n    > var y = mylogcdf( 3.0 )\n    -Infinity\n    > y = mylogcdf( 6.0 )\n    0\n\n","base.dists.degenerate.logcdf.factory":"\nbase.dists.degenerate.logcdf.factory( μ )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (logCDF) of a degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    logcdf: Function\n        Function to evaluate the natural logarithm of cumulative distribution\n        function (logCDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.degenerate.logcdf.factory( 5.0 );\n    > var y = mylogcdf( 3.0 )\n    -Infinity\n    > y = mylogcdf( 6.0 )\n    0","base.dists.degenerate.logpdf":"\nbase.dists.degenerate.logpdf( x, μ )\n    Evaluates the natural logarithm of the probability density function (logPDF)\n    for a degenerate distribution with mean `μ`.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Natural logarithm of the PDF.\n\n    Examples\n    --------\n    > var y = base.dists.degenerate.logpdf( 2.0, 3.0 )\n    -Infinity\n    > y = base.dists.degenerate.logpdf( 3.0, 3.0 )\n    Infinity\n    > y = base.dists.degenerate.logpdf( NaN, 0.0 )\n    NaN\n    > y = base.dists.degenerate.logpdf( 0.0, NaN )\n    NaN\n\n\nbase.dists.degenerate.logpdf.factory( μ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (logPDF) of a degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    logpdf: Function\n        Function to evaluate the natural logarithm of the PDF.\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.degenerate.logpdf.factory( 10.0 );\n    > var y = mylogPDF( 10.0 )\n    Infinity\n\n","base.dists.degenerate.logpdf.factory":"\nbase.dists.degenerate.logpdf.factory( μ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (logPDF) of a degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    logpdf: Function\n        Function to evaluate the natural logarithm of the PDF.\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.degenerate.logpdf.factory( 10.0 );\n    > var y = mylogPDF( 10.0 )\n    Infinity","base.dists.degenerate.logpmf":"\nbase.dists.degenerate.logpmf( x, μ )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    degenerate distribution with mean `μ`.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPMF.\n\n    Examples\n    --------\n    > var y = base.dists.degenerate.logpmf( 2.0, 3.0 )\n    -Infinity\n    > y = base.dists.degenerate.logpmf( 3.0, 3.0 )\n    0.0\n    > y = base.dists.degenerate.logpmf( NaN, 0.0 )\n    NaN\n    > y = base.dists.degenerate.logpmf( 0.0, NaN )\n    NaN\n\n\nbase.dists.degenerate.logpmf.factory( μ )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogPMF = base.dists.degenerate.logpmf.factory( 10.0 );\n    > var y = mylogPMF( 10.0 )\n    0.0\n\n","base.dists.degenerate.logpmf.factory":"\nbase.dists.degenerate.logpmf.factory( μ )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogPMF = base.dists.degenerate.logpmf.factory( 10.0 );\n    > var y = mylogPMF( 10.0 )\n    0.0","base.dists.degenerate.mean":"\nbase.dists.degenerate.mean( μ )\n    Returns the expected value of a degenerate distribution with constant value\n    `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.degenerate.mean( 20.0 )\n    20.0\n    > v = base.dists.degenerate.mean( -10.0 )\n    -10.0\n\n","base.dists.degenerate.median":"\nbase.dists.degenerate.median( μ )\n    Returns the median of a degenerate distribution with constant value `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.degenerate.median( 20.0 )\n    20.0\n    > v = base.dists.degenerate.median( -10.0 )\n    -10.0\n\n","base.dists.degenerate.mgf":"\nbase.dists.degenerate.mgf( x, μ )\n    Evaluates the moment-generating function (MGF) for a degenerate distribution\n    with mean `μ`.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.degenerate.mgf( 1.0, 1.0 )\n    ~2.718\n    > y = base.dists.degenerate.mgf( 2.0, 3.0 )\n    ~403.429\n    > y = base.dists.degenerate.mgf( NaN, 0.0 )\n    NaN\n    > y = base.dists.degenerate.mgf( 0.0, NaN )\n    NaN\n\n\nbase.dists.degenerate.mgf.factory( μ )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.degenerate.mgf.factory( 10.0 );\n    > var y = myMGF( 0.1 )\n    ~2.718\n\n","base.dists.degenerate.mgf.factory":"\nbase.dists.degenerate.mgf.factory( μ )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.degenerate.mgf.factory( 10.0 );\n    > var y = myMGF( 0.1 )\n    ~2.718","base.dists.degenerate.mode":"\nbase.dists.degenerate.mode( μ )\n    Returns the mode of a degenerate distribution with constant value `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.degenerate.mode( 20.0 )\n    20.0\n    > v = base.dists.degenerate.mode( -10.0 )\n    -10.0\n\n","base.dists.degenerate.pdf":"\nbase.dists.degenerate.pdf( x, μ )\n    Evaluates the probability density function (PDF) for a degenerate\n    distribution with mean `μ`.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.degenerate.pdf( 2.0, 3.0 )\n    0.0\n    > y = base.dists.degenerate.pdf( 3.0, 3.0 )\n    Infinity\n    > y = base.dists.degenerate.pdf( NaN, 0.0 )\n    NaN\n    > y = base.dists.degenerate.pdf( 0.0, NaN )\n    NaN\n\n\nbase.dists.degenerate.pdf.factory( μ )\n    Returns a function for evaluating the probability density function (PDF) of\n    a degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.degenerate.pdf.factory( 10.0 );\n    > var y = myPDF( 10.0 )\n    Infinity\n\n","base.dists.degenerate.pdf.factory":"\nbase.dists.degenerate.pdf.factory( μ )\n    Returns a function for evaluating the probability density function (PDF) of\n    a degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.degenerate.pdf.factory( 10.0 );\n    > var y = myPDF( 10.0 )\n    Infinity","base.dists.degenerate.pmf":"\nbase.dists.degenerate.pmf( x, μ )\n    Evaluates the probability mass function (PMF) for a degenerate distribution\n    with mean `μ`.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Evaluated PMF.\n\n    Examples\n    --------\n    > var y = base.dists.degenerate.pmf( 2.0, 3.0 )\n    0.0\n    > y = base.dists.degenerate.pmf( 3.0, 3.0 )\n    1.0\n    > y = base.dists.degenerate.pmf( NaN, 0.0 )\n    NaN\n    > y = base.dists.degenerate.pmf( 0.0, NaN )\n    NaN\n\n\nbase.dists.degenerate.pmf.factory( μ )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var myPMF = base.dists.degenerate.pmf.factory( 10.0 );\n    > var y = myPMF( 10.0 )\n    1.0\n\n","base.dists.degenerate.pmf.factory":"\nbase.dists.degenerate.pmf.factory( μ )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    degenerate distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var myPMF = base.dists.degenerate.pmf.factory( 10.0 );\n    > var y = myPMF( 10.0 )\n    1.0","base.dists.degenerate.quantile":"\nbase.dists.degenerate.quantile( p, μ )\n    Evaluates the quantile function for a degenerate distribution with mean `μ`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.degenerate.quantile( 0.5, 2.0 )\n    2.0\n    > y = base.dists.degenerate.quantile( 0.9, 4.0 )\n    4.0\n    > y = base.dists.degenerate.quantile( 1.1, 0.0 )\n    NaN\n    > y = base.dists.degenerate.quantile( -0.2, 0.0 )\n    NaN\n    > y = base.dists.degenerate.quantile( NaN, 0.0 )\n    NaN\n    > y = base.dists.degenerate.quantile( 0.0, NaN )\n    NaN\n\n\nbase.dists.degenerate.quantile.factory( μ )\n    Returns a function for evaluating the quantile function of a degenerate\n    distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.degenerate.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    10.0\n\n","base.dists.degenerate.quantile.factory":"\nbase.dists.degenerate.quantile.factory( μ )\n    Returns a function for evaluating the quantile function of a degenerate\n    distribution with mean `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.degenerate.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    10.0","base.dists.degenerate.stdev":"\nbase.dists.degenerate.stdev( μ )\n    Returns the standard deviation of a degenerate distribution with constant\n    value `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.degenerate.stdev( 20.0 )\n    0.0\n    > v = base.dists.degenerate.stdev( -10.0 )\n    0.0\n\n","base.dists.degenerate.variance":"\nbase.dists.degenerate.variance( μ )\n    Returns the variance of a degenerate distribution with constant value `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Constant value of distribution.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.degenerate.variance( 20.0 )\n    0.0\n    > v = base.dists.degenerate.variance( -10.0 )\n    0.0\n\n","base.dists.discreteUniform.cdf":"\nbase.dists.discreteUniform.cdf( x, a, b )\n    Evaluates the cumulative distribution function (CDF) for a discrete uniform\n    distribution with minimum support `a` and maximum support `b` at a value\n    `x`.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.discreteUniform.cdf( 9.0, 0, 10 )\n    ~0.909\n    > y = base.dists.discreteUniform.cdf( 0.5, 0, 2 )\n    ~0.333\n    > y = base.dists.discreteUniform.cdf( PINF, 2, 4 )\n    1.0\n    > y = base.dists.discreteUniform.cdf( NINF, 2, 4 )\n    0.0\n    > y = base.dists.discreteUniform.cdf( NaN, 0, 1 )\n    NaN\n    > y = base.dists.discreteUniform.cdf( 0.0, NaN, 1 )\n    NaN\n    > y = base.dists.discreteUniform.cdf( 0.0, 0, NaN )\n    NaN\n    > y = base.dists.discreteUniform.cdf( 2.0, 1, 0 )\n    NaN\n\n\nbase.dists.discreteUniform.cdf.factory( a, b )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a discrete uniform distribution with minimum support `a` and maximum\n    support `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.discreteUniform.cdf.factory( 0, 10 );\n    > var y = mycdf( 0.5 )\n    ~0.091\n    > y = mycdf( 8.0 )\n    ~0.818\n\n","base.dists.discreteUniform.cdf.factory":"\nbase.dists.discreteUniform.cdf.factory( a, b )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a discrete uniform distribution with minimum support `a` and maximum\n    support `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.discreteUniform.cdf.factory( 0, 10 );\n    > var y = mycdf( 0.5 )\n    ~0.091\n    > y = mycdf( 8.0 )\n    ~0.818","base.dists.discreteUniform.DiscreteUniform":"\nbase.dists.discreteUniform.DiscreteUniform( [a, b] )\n    Returns a discrete uniform distribution object.\n\n    Parameters\n    ----------\n    a: integer (optional)\n        Minimum support. Must be an integer smaller than `b`. Default: `0`.\n\n    b: integer (optional)\n        Maximum support. Must be an integer greater than `a`. Default: `1`.\n\n    Returns\n    -------\n    discreteUniform: Object\n        Distribution instance.\n\n    discreteUniform.a: integer\n        Minimum support. If set, the value must be an integer smaller than or\n        equal to `b`.\n\n    discreteUniform.b: integer\n        Maximum support. If set, the value must be an integer greater than or\n        equal to `a`.\n\n    discreteUniform.entropy: number\n        Read-only property which returns the entropy.\n\n    discreteUniform.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    discreteUniform.mean: number\n        Read-only property which returns the expected value.\n\n    discreteUniform.median: number\n        Read-only property which returns the median.\n\n    discreteUniform.skewness: number\n        Read-only property which returns the skewness.\n\n    discreteUniform.stdev: number\n        Read-only property which returns the standard deviation.\n\n    discreteUniform.variance: number\n        Read-only property which returns the variance.\n\n    discreteUniform.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    discreteUniform.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    discreteUniform.logpmf: Function\n        Evaluates the natural logarithm of the probability mass function (PMF).\n\n    discreteUniform.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    discreteUniform.pmf: Function\n        Evaluates the probability mass function (PMF).\n\n    discreteUniform.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var discreteUniform = base.dists.discreteUniform.DiscreteUniform( -2, 2 );\n    > discreteUniform.a\n    -2\n    > discreteUniform.b\n    2\n    > discreteUniform.entropy\n    ~1.609\n    > discreteUniform.kurtosis\n    -1.3\n    > discreteUniform.mean\n    0.0\n    > discreteUniform.median\n    0.0\n    > discreteUniform.skewness\n    0.0\n    > discreteUniform.stdev\n    ~1.414\n    > discreteUniform.variance\n    2.0\n    > discreteUniform.cdf( 0.8 )\n    0.6\n    > discreteUniform.logcdf( 0.5 )\n    ~-0.511\n    > discreteUniform.logpmf( 1.0 )\n    ~-1.609\n    > discreteUniform.mgf( 0.8 )\n    ~1.766\n    > discreteUniform.pmf( 0.0 )\n    0.2\n    > discreteUniform.quantile( 0.8 )\n    2.0\n\n","base.dists.discreteUniform.entropy":"\nbase.dists.discreteUniform.entropy( a, b )\n    Returns the entropy of a discrete uniform distribution.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.discreteUniform.entropy( 0, 1 )\n    ~0.693\n    > v = base.dists.discreteUniform.entropy( 4, 12 )\n    ~2.197\n    > v = base.dists.discreteUniform.entropy( 2, 8 )\n    ~1.946\n\n","base.dists.discreteUniform.kurtosis":"\nbase.dists.discreteUniform.kurtosis( a, b )\n    Returns the excess kurtosis of a discrete uniform distribution.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.discreteUniform.kurtosis( 0, 1 )\n    -2.0\n    > v = base.dists.discreteUniform.kurtosis( 4, 12 )\n    ~-1.23\n    > v = base.dists.discreteUniform.kurtosis( -4, 8 )\n    ~-1.214\n\n","base.dists.discreteUniform.logcdf":"\nbase.dists.discreteUniform.logcdf( x, a, b )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a discrete uniform distribution with minimum support `a` and\n    maximum support `b` at a value `x`.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.discreteUniform.logcdf( 9.0, 0, 10 )\n    ~-0.095\n    > y = base.dists.discreteUniform.logcdf( 0.5, 0, 2 )\n    ~-1.099\n    > y = base.dists.discreteUniform.logcdf( PINF, 2, 4 )\n    0.0\n    > y = base.dists.discreteUniform.logcdf( NINF, 2, 4 )\n    -Infinity\n    > y = base.dists.discreteUniform.logcdf( NaN, 0, 1 )\n    NaN\n    > y = base.dists.discreteUniform.logcdf( 0.0, NaN, 1 )\n    NaN\n    > y = base.dists.discreteUniform.logcdf( 0.0, 0, NaN )\n    NaN\n    > y = base.dists.discreteUniform.logcdf( 2.0, 1, 0 )\n    NaN\n\n\nbase.dists.discreteUniform.logcdf.factory( a, b )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a discrete uniform distribution with minimum\n    support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myLogCDF = base.dists.discreteUniform.logcdf.factory( 0, 10 );\n    > var y = myLogCDF( 0.5 )\n    ~-2.398\n    > y = myLogCDF( 8.0 )\n    ~-0.201\n\n","base.dists.discreteUniform.logcdf.factory":"\nbase.dists.discreteUniform.logcdf.factory( a, b )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a discrete uniform distribution with minimum\n    support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myLogCDF = base.dists.discreteUniform.logcdf.factory( 0, 10 );\n    > var y = myLogCDF( 0.5 )\n    ~-2.398\n    > y = myLogCDF( 8.0 )\n    ~-0.201","base.dists.discreteUniform.logpmf":"\nbase.dists.discreteUniform.logpmf( x, a, b )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    discrete uniform distribution with minimum support `a` and maximum support\n    `b` at a value `x`.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPMF.\n\n    Examples\n    --------\n    > var y = base.dists.discreteUniform.logpmf( 2.0, 0, 4 )\n    ~-1.609\n    > y = base.dists.discreteUniform.logpmf( 5.0, 0, 4 )\n    -Infinity\n    > y = base.dists.discreteUniform.logpmf( 3.0, -4, 4 )\n    ~-2.197\n    > y = base.dists.discreteUniform.logpmf( NaN, 0, 1 )\n    NaN\n    > y = base.dists.discreteUniform.logpmf( 0.0, NaN, 1 )\n    NaN\n    > y = base.dists.discreteUniform.logpmf( 0.0, 0, NaN )\n    NaN\n    > y = base.dists.discreteUniform.logpmf( 2.0, 3, 1 )\n    NaN\n    > y = base.dists.discreteUniform.logpmf( 2.0, 1, 2.4 )\n    NaN\n\n\nbase.dists.discreteUniform.logpmf.factory( a, b )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a discrete uniform distribution with minimum support\n    `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var myLogPMF = base.dists.discreteUniform.logpmf.factory( 6, 7 );\n    > var y = myLogPMF( 7.0 )\n    ~-0.693\n    > y = myLogPMF( 5.0 )\n    -Infinity\n\n","base.dists.discreteUniform.logpmf.factory":"\nbase.dists.discreteUniform.logpmf.factory( a, b )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a discrete uniform distribution with minimum support\n    `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var myLogPMF = base.dists.discreteUniform.logpmf.factory( 6, 7 );\n    > var y = myLogPMF( 7.0 )\n    ~-0.693\n    > y = myLogPMF( 5.0 )\n    -Infinity","base.dists.discreteUniform.mean":"\nbase.dists.discreteUniform.mean( a, b )\n    Returns the expected value of a discrete uniform distribution.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.discreteUniform.mean( -2, 2 )\n    0.0\n    > v = base.dists.discreteUniform.mean( 4, 12 )\n    8.0\n    > v = base.dists.discreteUniform.mean( 2, 8 )\n    5.0\n\n","base.dists.discreteUniform.median":"\nbase.dists.discreteUniform.median( a, b )\n    Returns the median of a discrete uniform distribution.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.discreteUniform.median( -2, 2 )\n    0.0\n    > v = base.dists.discreteUniform.median( 4, 12 )\n    8.0\n    > v = base.dists.discreteUniform.median( 2, 8 )\n    5.0\n\n","base.dists.discreteUniform.mgf":"\nbase.dists.discreteUniform.mgf( t, a, b )\n    Evaluates the moment-generating function (MGF) for a discrete uniform\n    distribution with minimum support `a` and maximum support `b` at a value\n    `t`.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.discreteUniform.mgf( 2.0, 0, 4 )\n    ~689.475\n    > y = base.dists.discreteUniform.mgf( -0.2, 0, 4 )\n    ~0.697\n    > y = base.dists.discreteUniform.mgf( 2.0, 0, 1 )\n    ~4.195\n    > y = base.dists.discreteUniform.mgf( 0.5, 3, 2 )\n    NaN\n    > y = base.dists.discreteUniform.mgf( NaN, 0, 1  )\n    NaN\n    > y = base.dists.discreteUniform.mgf( 0.0, NaN, 1 )\n    NaN\n    > y = base.dists.discreteUniform.mgf( 0.0, 0, NaN )\n    NaN\n\n\nbase.dists.discreteUniform.mgf.factory( a, b )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a discrete uniform distribution with minimum support `a` and maximum\n    support `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.discreteUniform.mgf.factory( 6, 7 );\n    > var y = mymgf( 0.1 )\n    ~1.918\n    > y = mymgf( 1.1 )\n    ~1471.722\n\n","base.dists.discreteUniform.mgf.factory":"\nbase.dists.discreteUniform.mgf.factory( a, b )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a discrete uniform distribution with minimum support `a` and maximum\n    support `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.discreteUniform.mgf.factory( 6, 7 );\n    > var y = mymgf( 0.1 )\n    ~1.918\n    > y = mymgf( 1.1 )\n    ~1471.722","base.dists.discreteUniform.pmf":"\nbase.dists.discreteUniform.pmf( x, a, b )\n    Evaluates the probability mass function (PMF) for a discrete uniform\n    distribution with minimum support `a` and maximum support `b` at a value\n    `x`.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated PMF.\n\n    Examples\n    --------\n    > var y = base.dists.discreteUniform.pmf( 2.0, 0, 4 )\n    ~0.2\n    > y = base.dists.discreteUniform.pmf( 5.0, 0, 4 )\n    0.0\n    > y = base.dists.discreteUniform.pmf( 3.0, -4, 4 )\n    ~0.111\n    > y = base.dists.discreteUniform.pmf( NaN, 0, 1 )\n    NaN\n    > y = base.dists.discreteUniform.pmf( 0.0, NaN, 1 )\n    NaN\n    > y = base.dists.discreteUniform.pmf( 0.0, 0, NaN )\n    NaN\n    > y = base.dists.discreteUniform.pmf( 2.0, 3, 1 )\n    NaN\n    > y = base.dists.discreteUniform.pmf( 2.0, 1, 2.4 )\n    NaN\n\n\nbase.dists.discreteUniform.pmf.factory( a, b )\n    Returns a function for evaluating the probability mass function (PMF) of\n    a discrete uniform distribution with minimum support `a` and maximum support\n    `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var myPMF = base.dists.discreteUniform.pmf.factory( 6, 7 );\n    > var y = myPMF( 7.0 )\n    0.5\n    > y = myPMF( 5.0 )\n    0.0\n\n","base.dists.discreteUniform.pmf.factory":"\nbase.dists.discreteUniform.pmf.factory( a, b )\n    Returns a function for evaluating the probability mass function (PMF) of\n    a discrete uniform distribution with minimum support `a` and maximum support\n    `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var myPMF = base.dists.discreteUniform.pmf.factory( 6, 7 );\n    > var y = myPMF( 7.0 )\n    0.5\n    > y = myPMF( 5.0 )\n    0.0","base.dists.discreteUniform.quantile":"\nbase.dists.discreteUniform.quantile( p, a, b )\n    Evaluates the quantile function for a discrete uniform distribution with\n    minimum support `a` and maximum support `b` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    If provided `a > b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.discreteUniform.quantile( 0.8, 0, 1 )\n    1\n    > y = base.dists.discreteUniform.quantile( 0.5, 0.0, 10.0 )\n    5\n\n    > y = base.dists.discreteUniform.quantile( 1.1, 0, 4 )\n    NaN\n    > y = base.dists.discreteUniform.quantile( -0.2, 0, 4 )\n    NaN\n\n    > y = base.dists.discreteUniform.quantile( NaN, -2, 2 )\n    NaN\n    > y = base.dists.discreteUniform.quantile( 0.1, NaN, 2 )\n    NaN\n    > y = base.dists.discreteUniform.quantile( 0.1, -2, NaN )\n    NaN\n\n    > y = base.dists.discreteUniform.quantile( 0.5, 2, 1 )\n    NaN\n\n\nbase.dists.discreteUniform.quantile.factory( a, b )\n    Returns a function for evaluating the quantile function of a discrete\n    uniform distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.discreteUniform.quantile.factory( 0, 4 );\n    > var y = myQuantile( 0.8 )\n    4\n\n","base.dists.discreteUniform.quantile.factory":"\nbase.dists.discreteUniform.quantile.factory( a, b )\n    Returns a function for evaluating the quantile function of a discrete\n    uniform distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.discreteUniform.quantile.factory( 0, 4 );\n    > var y = myQuantile( 0.8 )\n    4","base.dists.discreteUniform.skewness":"\nbase.dists.discreteUniform.skewness( a, b )\n    Returns the skewness of a discrete uniform distribution.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.discreteUniform.skewness( -2, 2 )\n    0.0\n    > v = base.dists.discreteUniform.skewness( 4, 12 )\n    0.0\n    > v = base.dists.discreteUniform.skewness( 2, 8 )\n    0.0\n\n","base.dists.discreteUniform.stdev":"\nbase.dists.discreteUniform.stdev( a, b )\n    Returns the standard deviation of a discrete uniform distribution.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.discreteUniform.stdev( 0, 1 )\n    ~0.5\n    > v = base.dists.discreteUniform.stdev( 4, 12 )\n    ~2.582\n    > v = base.dists.discreteUniform.stdev( 2, 8 )\n    2.0\n\n","base.dists.discreteUniform.variance":"\nbase.dists.discreteUniform.variance( a, b )\n    Returns the variance of a discrete uniform distribution.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.discreteUniform.variance( 0, 1 )\n    ~0.25\n    > v = base.dists.discreteUniform.variance( 4, 12 )\n    ~6.667\n    > v = base.dists.discreteUniform.variance( 2, 8 )\n    4.0\n\n","base.dists.erlang.cdf":"\nbase.dists.erlang.cdf( x, k, λ )\n    Evaluates the cumulative distribution function (CDF) for an Erlang\n    distribution with shape parameter `k` and rate parameter `λ` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.erlang.cdf( 2.0, 1, 1.0 )\n    ~0.865\n    > y = base.dists.erlang.cdf( 2.0, 3, 1.0 )\n    ~0.323\n    > y = base.dists.erlang.cdf( 2.0, 2.5, 1.0 )\n    NaN\n    > y = base.dists.erlang.cdf( -1.0, 2, 2.0 )\n    0.0\n    > y = base.dists.erlang.cdf( PINF, 4, 2.0 )\n    1.0\n    > y = base.dists.erlang.cdf( NINF, 4, 2.0 )\n    0.0\n    > y = base.dists.erlang.cdf( NaN, 0, 1.0 )\n    NaN\n    > y = base.dists.erlang.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.erlang.cdf( 0.0, 0, NaN )\n    NaN\n    > y = base.dists.erlang.cdf( 2.0, -1, 1.0 )\n    NaN\n    > y = base.dists.erlang.cdf( 2.0, 1, -1.0 )\n    NaN\n\n\nbase.dists.erlang.cdf.factory( k, λ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.erlang.cdf.factory( 2, 0.5 );\n    > var y = mycdf( 6.0 )\n    ~0.801\n    > y = mycdf( 2.0 )\n    ~0.264\n\n","base.dists.erlang.cdf.factory":"\nbase.dists.erlang.cdf.factory( k, λ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.erlang.cdf.factory( 2, 0.5 );\n    > var y = mycdf( 6.0 )\n    ~0.801\n    > y = mycdf( 2.0 )\n    ~0.264","base.dists.erlang.entropy":"\nbase.dists.erlang.entropy( k, λ )\n    Returns the differential entropy of an Erlang distribution (in nats).\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a positive integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: integer\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.erlang.entropy( 1, 1.0 )\n    ~1.0\n    > v = base.dists.erlang.entropy( 4, 12.0 )\n    ~-0.462\n    > v = base.dists.erlang.entropy( 8, 2.0 )\n    ~1.723\n\n","base.dists.erlang.Erlang":"\nbase.dists.erlang.Erlang( [k, λ] )\n    Returns an Erlang distribution object.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Shape parameter. Must be a positive integer. Default: `1.0`.\n\n    λ: number (optional)\n        Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    erlang: Object\n        Distribution instance.\n\n    erlang.k: number\n        Shape parameter. If set, the value must be a positive integer.\n\n    erlang.lambda: number\n        Rate parameter. If set, the value must be greater than `0`.\n\n    erlang.entropy: number\n        Read-only property which returns the differential entropy.\n\n    erlang.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    erlang.mean: number\n        Read-only property which returns the expected value.\n\n    erlang.mode: number\n        Read-only property which returns the mode.\n\n    erlang.skewness: number\n        Read-only property which returns the skewness.\n\n    erlang.stdev: number\n        Read-only property which returns the standard deviation.\n\n    erlang.variance: number\n        Read-only property which returns the variance.\n\n    erlang.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    erlang.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    erlang.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    erlang.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    erlang.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var erlang = base.dists.erlang.Erlang( 6, 5.0 );\n    > erlang.k\n    6\n    > erlang.lambda\n    5.0\n    > erlang.entropy\n    ~0.647\n    > erlang.kurtosis\n    1.0\n    > erlang.mean\n    1.2\n    > erlang.mode\n    1.0\n    > erlang.skewness\n    ~0.816\n    > erlang.stdev\n    ~0.49\n    > erlang.variance\n    0.24\n    > erlang.cdf( 3.0 )\n    ~0.997\n    > erlang.logpdf( 3.0 )\n    ~-4.638\n    > erlang.mgf( -0.5 )\n    ~0.564\n    > erlang.pdf( 3.0 )\n    ~0.01\n    > erlang.quantile( 0.8 )\n    ~1.581\n\n","base.dists.erlang.kurtosis":"\nbase.dists.erlang.kurtosis( k, λ )\n    Returns the excess kurtosis of an Erlang distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a positive integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: integer\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.erlang.kurtosis( 1, 1.0 )\n    6.0\n    > v = base.dists.erlang.kurtosis( 4, 12.0 )\n    1.5\n    > v = base.dists.erlang.kurtosis( 8, 2.0 )\n    0.75\n\n","base.dists.erlang.logpdf":"\nbase.dists.erlang.logpdf( x, k, λ )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for an Erlang distribution with shape parameter `k` and rate parameter `λ`\n    at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.erlang.logpdf( 0.1, 1, 1.0 )\n    ~-0.1\n    > y = base.dists.erlang.logpdf( 0.5, 2, 2.5 )\n    ~-0.111\n    > y = base.dists.erlang.logpdf( -1.0, 4, 2.0 )\n    -Infinity\n    > y = base.dists.erlang.logpdf( NaN, 1, 1.0 )\n    NaN\n    > y = base.dists.erlang.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.erlang.logpdf( 0.0, 1, NaN )\n    NaN\n    > y = base.dists.erlang.logpdf( 2.0, -2, 0.5 )\n    NaN\n    > y = base.dists.erlang.logpdf( 2.0, 0.5, 0.5 )\n    NaN\n    > y = base.dists.erlang.logpdf( 2.0, 0.0, 2.0 )\n    -Infinity\n    > y = base.dists.erlang.logpdf( 0.0, 0.0, 2.0 )\n    Infinity\n    > y = base.dists.erlang.logpdf( 2.0, 1, 0.0 )\n    NaN\n    > y = base.dists.erlang.logpdf( 2.0, 1, -1.0 )\n    NaN\n\n\nbase.dists.erlang.logpdf.factory( k, λ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of an Erlang distribution with shape parameter `k`\n    and rate parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var myLogPDF = base.dists.erlang.logpdf.factory( 6.0, 7.0 );\n    > y = myLogPDF( 7.0 )\n    ~-32.382\n\n\n","base.dists.erlang.logpdf.factory":"\nbase.dists.erlang.logpdf.factory( k, λ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of an Erlang distribution with shape parameter `k`\n    and rate parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var myLogPDF = base.dists.erlang.logpdf.factory( 6.0, 7.0 );\n    > y = myLogPDF( 7.0 )\n    ~-32.382","base.dists.erlang.mean":"\nbase.dists.erlang.mean( k, λ )\n    Returns the expected value of an Erlang distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a positive integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: integer\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.erlang.mean( 1, 1.0 )\n    1.0\n    > v = base.dists.erlang.mean( 4, 12.0 )\n    ~0.333\n    > v = base.dists.erlang.mean( 8, 2.0 )\n    4.0\n\n","base.dists.erlang.mgf":"\nbase.dists.erlang.mgf( t, k, λ )\n    Evaluates the moment-generating function (MGF) for an Erlang distribution\n    with shape parameter `k` and rate parameter `λ` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.erlang.mgf( 0.3, 1, 1.0 )\n    ~1.429\n    > y = base.dists.erlang.mgf( 2.0, 2, 3.0 )\n    ~9.0\n    > y = base.dists.erlang.mgf( -1.0, 2, 2.0 )\n    ~0.444\n\n    > y = base.dists.erlang.mgf( NaN, 1, 1.0 )\n    NaN\n    > y = base.dists.erlang.mgf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.erlang.mgf( 0.0, 1, NaN )\n    NaN\n\n    > y = base.dists.erlang.mgf( 0.2, -2, 0.5 )\n    NaN\n    > y = base.dists.erlang.mgf( 0.2, 0.5, 0.5 )\n    NaN\n\n    > y = base.dists.erlang.mgf( 0.2, 1, 0.0 )\n    NaN\n    > y = base.dists.erlang.mgf( 0.2, 1, -5.0 )\n    NaN\n\n\nbase.dists.erlang.mgf.factory( k, λ )\n    Returns a function for evaluating the moment-generating function (MGF) of an\n    Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.erlang.mgf.factory( 2, 0.5 );\n    > var y = myMGF( 0.2 )\n    ~2.778\n    > y = myMGF( -0.5 )\n    0.25\n\n","base.dists.erlang.mgf.factory":"\nbase.dists.erlang.mgf.factory( k, λ )\n    Returns a function for evaluating the moment-generating function (MGF) of an\n    Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.erlang.mgf.factory( 2, 0.5 );\n    > var y = myMGF( 0.2 )\n    ~2.778\n    > y = myMGF( -0.5 )\n    0.25","base.dists.erlang.mode":"\nbase.dists.erlang.mode( k, λ )\n    Returns the mode of an Erlang distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a positive integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: integer\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.erlang.mode( 1, 1.0 )\n    0.0\n    > v = base.dists.erlang.mode( 4, 12.0 )\n    0.25\n    > v = base.dists.erlang.mode( 8, 2.0 )\n    3.5\n\n","base.dists.erlang.pdf":"\nbase.dists.erlang.pdf( x, k, λ )\n    Evaluates the probability density function (PDF) for an Erlang distribution\n    with shape parameter `k` and rate parameter `λ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.erlang.pdf( 0.1, 1, 1.0 )\n    ~0.905\n    > y = base.dists.erlang.pdf( 0.5, 2, 2.5 )\n    ~0.895\n    > y = base.dists.erlang.pdf( -1.0, 4, 2.0 )\n    0.0\n    > y = base.dists.erlang.pdf( NaN, 1, 1.0 )\n    NaN\n    > y = base.dists.erlang.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.erlang.pdf( 0.0, 1, NaN )\n    NaN\n    > y = base.dists.erlang.pdf( 2.0, -2, 0.5 )\n    NaN\n    > y = base.dists.erlang.pdf( 2.0, 0.5, 0.5 )\n    NaN\n    > y = base.dists.erlang.pdf( 2.0, 0.0, 2.0 )\n    0.0\n    > y = base.dists.erlang.pdf( 0.0, 0.0, 2.0 )\n    Infinity\n    > y = base.dists.erlang.pdf( 2.0, 1, 0.0 )\n    NaN\n    > y = base.dists.erlang.pdf( 2.0, 1, -1.0 )\n    NaN\n\n\nbase.dists.erlang.pdf.factory( k, λ )\n    Returns a function for evaluating the probability density function (PDF)\n    of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.erlang.pdf.factory( 6.0, 7.0 );\n    > y = myPDF( 7.0 )\n    ~8.639e-15\n\n\n","base.dists.erlang.pdf.factory":"\nbase.dists.erlang.pdf.factory( k, λ )\n    Returns a function for evaluating the probability density function (PDF)\n    of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.erlang.pdf.factory( 6.0, 7.0 );\n    > y = myPDF( 7.0 )\n    ~8.639e-15","base.dists.erlang.quantile":"\nbase.dists.erlang.quantile( p, k, λ )\n    Evaluates the quantile function for an Erlang distribution with shape\n    parameter `k` and rate parameter `λ` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a nonnegative integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive number for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.erlang.quantile( 0.8, 2, 1.0 )\n    ~2.994\n    > y = base.dists.erlang.quantile( 0.5, 4, 2.0 )\n    ~1.836\n\n    > y = base.dists.erlang.quantile( 1.1, 1, 1.0 )\n    NaN\n    > y = base.dists.erlang.quantile( -0.2, 1, 1.0 )\n    NaN\n\n    > y = base.dists.erlang.quantile( NaN, 1, 1.0 )\n    NaN\n    > y = base.dists.erlang.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.erlang.quantile( 0.0, 1, NaN )\n    NaN\n\n    // Non-integer shape parameter:\n    > y = base.dists.erlang.quantile( 0.5, 0.5, 1.0 )\n    NaN\n    // Non-positive shape parameter:\n    > y = base.dists.erlang.quantile( 0.5, -1, 1.0 )\n    NaN\n    // Non-positive rate parameter:\n    > y = base.dists.erlang.quantile( 0.5, 1, -1.0 )\n    NaN\n\n\nbase.dists.erlang.quantile.factory( k, λ )\n    Returns a function for evaluating the quantile function of an Erlang\n    distribution with shape parameter `k` and rate parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.erlang.quantile.factory( 10, 2.0 );\n    > var y = myQuantile( 0.4 )\n    ~4.452\n\n","base.dists.erlang.quantile.factory":"\nbase.dists.erlang.quantile.factory( k, λ )\n    Returns a function for evaluating the quantile function of an Erlang\n    distribution with shape parameter `k` and rate parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.erlang.quantile.factory( 10, 2.0 );\n    > var y = myQuantile( 0.4 )\n    ~4.452","base.dists.erlang.skewness":"\nbase.dists.erlang.skewness( k, λ )\n    Returns the skewness of an Erlang distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a positive integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: integer\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.erlang.skewness( 1, 1.0 )\n    2.0\n    > v = base.dists.erlang.skewness( 4, 12.0 )\n    1.0\n    > v = base.dists.erlang.skewness( 8, 2.0 )\n    ~0.707\n\n","base.dists.erlang.stdev":"\nbase.dists.erlang.stdev( k, λ )\n    Returns the standard deviation of an Erlang distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a positive integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: integer\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.erlang.stdev( 1, 1.0 )\n    1.0\n    > v = base.dists.erlang.stdev( 4, 12.0 )\n    ~0.167\n    > v = base.dists.erlang.stdev( 8, 2.0 )\n    ~1.414\n\n","base.dists.erlang.variance":"\nbase.dists.erlang.variance( k, λ )\n    Returns the variance of an Erlang distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a positive integer for `k`, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: integer\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.erlang.variance( 1, 1.0 )\n    1.0\n    > v = base.dists.erlang.variance( 4, 12.0 )\n    ~0.028\n    > v = base.dists.erlang.variance( 8, 2.0 )\n    2.0\n\n","base.dists.exponential.cdf":"\nbase.dists.exponential.cdf( x, λ )\n    Evaluates the cumulative distribution function (CDF) for an exponential\n    distribution with rate parameter `λ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.exponential.cdf( 2.0, 0.1 )\n    ~0.181\n    > y = base.dists.exponential.cdf( 1.0, 2.0 )\n    ~0.865\n    > y = base.dists.exponential.cdf( -1.0, 4.0 )\n    0.0\n    > y = base.dists.exponential.cdf( NaN, 1.0 )\n    NaN\n    > y = base.dists.exponential.cdf( 0.0, NaN )\n    NaN\n\n    // Negative rate parameter:\n    > y = base.dists.exponential.cdf( 2.0, -1.0 )\n    NaN\n\nbase.dists.exponential.cdf.factory( λ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    for an exponential distribution with rate parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.exponential.cdf.factory( 0.5 );\n    > var y = myCDF( 3.0 )\n    ~0.777\n\n","base.dists.exponential.cdf.factory":"\nbase.dists.exponential.cdf.factory( λ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    for an exponential distribution with rate parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.exponential.cdf.factory( 0.5 );\n    > var y = myCDF( 3.0 )\n    ~0.777","base.dists.exponential.entropy":"\nbase.dists.exponential.entropy( λ )\n    Returns the differential entropy of an exponential distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.exponential.entropy( 11.0 )\n    ~-1.398\n    > v = base.dists.exponential.entropy( 4.5 )\n    ~-0.504\n\n","base.dists.exponential.Exponential":"\nbase.dists.exponential.Exponential( [λ] )\n    Returns an exponential distribution object.\n\n    Parameters\n    ----------\n    λ: number (optional)\n        Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    exponential: Object\n        Distribution instance.\n\n    exponential.lambda: number\n        Rate parameter. If set, the value must be greater than `0`.\n\n    exponential.entropy: number\n        Read-only property which returns the differential entropy.\n\n    exponential.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    exponential.mean: number\n        Read-only property which returns the expected value.\n\n    exponential.median: number\n        Read-only property which returns the median.\n\n    exponential.mode: number\n        Read-only property which returns the mode.\n\n    exponential.skewness: number\n        Read-only property which returns the skewness.\n\n    exponential.stdev: number\n        Read-only property which returns the standard deviation.\n\n    exponential.variance: number\n        Read-only property which returns the variance.\n\n    exponential.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    exponential.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    exponential.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    exponential.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    exponential.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    exponential.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var exponential = base.dists.exponential.Exponential( 6.0 );\n    > exponential.lambda\n    6.0\n    > exponential.entropy\n    ~-0.792\n    > exponential.kurtosis\n    6.0\n    > exponential.mean\n    ~0.167\n    > exponential.median\n    ~0.116\n    > exponential.mode\n    0.0\n    > exponential.skewness\n    2.0\n    > exponential.stdev\n    ~0.167\n    > exponential.variance\n    ~0.028\n    > exponential.cdf( 1.0 )\n    ~0.998\n    > exponential.logcdf( 1.0 )\n    ~-0.002\n    > exponential.logpdf( 1.5 )\n    ~-7.208\n    > exponential.mgf( -0.5 )\n    ~0.923\n    > exponential.pdf( 1.5 )\n    ~0.001\n    > exponential.quantile( 0.5 )\n    ~0.116\n\n","base.dists.exponential.kurtosis":"\nbase.dists.exponential.kurtosis( λ )\n    Returns the excess kurtosis of an exponential distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.exponential.kurtosis( 11.0 )\n    6.0\n    > v = base.dists.exponential.kurtosis( 4.5 )\n    6.0\n\n","base.dists.exponential.logcdf":"\nbase.dists.exponential.logcdf( x, λ )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for an exponential distribution with rate parameter `λ` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.exponential.logcdf( 2.0, 0.1 )\n    ~-1.708\n    > y = base.dists.exponential.logcdf( 1.0, 2.0 )\n    ~-0.145\n    > y = base.dists.exponential.logcdf( -1.0, 4.0 )\n    -Infinity\n    > y = base.dists.exponential.logcdf( NaN, 1.0 )\n    NaN\n    > y = base.dists.exponential.logcdf( 0.0, NaN )\n    NaN\n\n    // Negative rate parameter:\n    > y = base.dists.exponential.logcdf( 2.0, -1.0 )\n    NaN\n\nbase.dists.exponential.logcdf.factory( λ )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) for an exponential distribution with rate\n    parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogCDF = base.dists.exponential.logcdf.factory( 0.5 );\n    > var y = mylogCDF( 3.0 )\n    ~-0.252\n\n","base.dists.exponential.logcdf.factory":"\nbase.dists.exponential.logcdf.factory( λ )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) for an exponential distribution with rate\n    parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogCDF = base.dists.exponential.logcdf.factory( 0.5 );\n    > var y = mylogCDF( 3.0 )\n    ~-0.252","base.dists.exponential.logpdf":"\nbase.dists.exponential.logpdf( x, λ )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for an exponential distribution with rate parameter `λ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.exponential.logpdf( 0.3, 4.0 )\n    ~0.186\n    > y = base.dists.exponential.logpdf( 2.0, 0.7 )\n    ~-1.757\n    > y = base.dists.exponential.logpdf( -1.0, 0.5 )\n    -Infinity\n    > y = base.dists.exponential.logpdf( 0, NaN )\n    NaN\n    > y = base.dists.exponential.logpdf( NaN, 2.0 )\n    NaN\n\n    // Negative rate:\n    > y = base.dists.exponential.logpdf( 2.0, -1.0 )\n    NaN\n\nbase.dists.exponential.logpdf.factory( λ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) for an exponential distribution with rate parameter\n    `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.exponential.logpdf.factory( 0.5 );\n    > var y = mylogpdf( 3.0 )\n    ~-2.193\n\n","base.dists.exponential.logpdf.factory":"\nbase.dists.exponential.logpdf.factory( λ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) for an exponential distribution with rate parameter\n    `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.exponential.logpdf.factory( 0.5 );\n    > var y = mylogpdf( 3.0 )\n    ~-2.193","base.dists.exponential.mean":"\nbase.dists.exponential.mean( λ )\n    Returns the expected value of an exponential distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.exponential.mean( 11.0 )\n    ~0.091\n    > v = base.dists.exponential.mean( 4.5 )\n    ~0.222\n\n","base.dists.exponential.median":"\nbase.dists.exponential.median( λ )\n    Returns the median of an exponential distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.exponential.median( 11.0 )\n    ~0.063\n    > v = base.dists.exponential.median( 4.5 )\n    ~0.154\n\n","base.dists.exponential.mgf":"\nbase.dists.exponential.mgf( t, λ )\n    Evaluates the moment-generating function (MGF) for an exponential\n    distribution with rate parameter `λ` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var v = base.dists.exponential.mgf( 2.0, 3.0 )\n    3.0\n    > v = base.dists.exponential.mgf( 0.4, 1.2 )\n    1.5\n    > v = base.dists.exponential.mgf( 0.8, 1.6 )\n    2.0\n    > v = base.dists.exponential.mgf( 4.0, 3.0 )\n    NaN\n    > v = base.dists.exponential.mgf( NaN, 3.0 )\n    NaN\n    > v = base.dists.exponential.mgf( 2.0, NaN )\n    NaN\n\n\nbase.dists.exponential.mgf.factory( λ )\n    Returns a function for evaluating the moment-generating function (MGF) for\n    an exponential distribution with rate parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    mg: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.exponential.mgf.factory( 4.0 );\n    > var y = myMGF( 3.0 )\n    4.0\n    > y = myMGF( 0.5 )\n    ~1.143\n\n","base.dists.exponential.mgf.factory":"\nbase.dists.exponential.mgf.factory( λ )\n    Returns a function for evaluating the moment-generating function (MGF) for\n    an exponential distribution with rate parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    mg: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.exponential.mgf.factory( 4.0 );\n    > var y = myMGF( 3.0 )\n    4.0\n    > y = myMGF( 0.5 )\n    ~1.143","base.dists.exponential.mode":"\nbase.dists.exponential.mode( λ )\n    Returns the mode of an exponential distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.exponential.mode( 11.0 )\n    0.0\n    > v = base.dists.exponential.mode( 4.5 )\n    0.0\n\n","base.dists.exponential.pdf":"\nbase.dists.exponential.pdf( x, λ )\n    Evaluates the probability density function (PDF) for an exponential\n    distribution with rate parameter `λ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.exponential.pdf( 0.3, 4.0 )\n    ~1.205\n    > y = base.dists.exponential.pdf( 2.0, 0.7 )\n    ~0.173\n    > y = base.dists.exponential.pdf( -1.0, 0.5 )\n    0.0\n    > y = base.dists.exponential.pdf( 0, NaN )\n    NaN\n    > y = base.dists.exponential.pdf( NaN, 2.0 )\n    NaN\n\n    // Negative rate:\n    > y = base.dists.exponential.pdf( 2.0, -1.0 )\n    NaN\n\nbase.dists.exponential.pdf.factory( λ )\n    Returns a function for evaluating the probability density function (PDF)\n    for an exponential distribution with rate parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.exponential.pdf.factory( 0.5 );\n    > var y = myPDF( 3.0 )\n    ~0.112\n\n","base.dists.exponential.pdf.factory":"\nbase.dists.exponential.pdf.factory( λ )\n    Returns a function for evaluating the probability density function (PDF)\n    for an exponential distribution with rate parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.exponential.pdf.factory( 0.5 );\n    > var y = myPDF( 3.0 )\n    ~0.112","base.dists.exponential.quantile":"\nbase.dists.exponential.quantile( p, λ )\n    Evaluates the quantile function for an exponential distribution with rate\n    parameter `λ` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.exponential.quantile( 0.8, 1.0 )\n    ~1.609\n    > y = base.dists.exponential.quantile( 0.5, 4.0 )\n    ~0.173\n    > y = base.dists.exponential.quantile( 0.5, 0.1 )\n    ~6.931\n\n    > y = base.dists.exponential.quantile( -0.2, 0.1 )\n    NaN\n\n    > y = base.dists.exponential.quantile( NaN, 1.0 )\n    NaN\n    > y = base.dists.exponential.quantile( 0.0, NaN )\n    NaN\n\n    // Negative rate parameter:\n    > y = base.dists.exponential.quantile( 0.5, -1.0 )\n    NaN\n\n\nbase.dists.exponential.quantile.factory( λ )\n    Returns a function for evaluating the quantile function for an exponential\n    distribution with rate parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.exponential.quantile.factory( 0.4 );\n    > var y = myQuantile( 0.4 )\n    ~1.277\n    > y = myQuantile( 1.0 )\n    Infinity\n\n","base.dists.exponential.quantile.factory":"\nbase.dists.exponential.quantile.factory( λ )\n    Returns a function for evaluating the quantile function for an exponential\n    distribution with rate parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.exponential.quantile.factory( 0.4 );\n    > var y = myQuantile( 0.4 )\n    ~1.277\n    > y = myQuantile( 1.0 )\n    Infinity","base.dists.exponential.skewness":"\nbase.dists.exponential.skewness( λ )\n    Returns the skewness of an exponential distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.exponential.skewness( 11.0 )\n    2.0\n    > v = base.dists.exponential.skewness( 4.5 )\n    2.0\n\n","base.dists.exponential.stdev":"\nbase.dists.exponential.stdev( λ )\n    Returns the standard deviation of an exponential distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.exponential.stdev( 9.0 )\n    ~0.11\n    > v = base.dists.exponential.stdev( 1.0 )\n    1.0\n\n","base.dists.exponential.variance":"\nbase.dists.exponential.variance( λ )\n    Returns the variance of an exponential distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.exponential.variance( 9.0 )\n    ~0.012\n    > v = base.dists.exponential.variance( 1.0 )\n    1.0\n\n","base.dists.f.cdf":"\nbase.dists.f.cdf( x, d1, d2 )\n    Evaluates the cumulative distribution function (CDF) for an F distribution\n    with numerator degrees of freedom `d1` and denominator degrees of freedom\n    `d2` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.f.cdf( 2.0, 1.0, 1.0 )\n    ~0.608\n    > var y = base.dists.f.cdf( 2.0, 8.0, 4.0 )\n    ~0.737\n    > var y = base.dists.f.cdf( -1.0, 2.0, 2.0 )\n    0.0\n    > var y = base.dists.f.cdf( PINF, 4.0, 2.0 )\n    1.0\n    > var y = base.dists.f.cdf( NINF, 4.0, 2.0 )\n    0.0\n\n    > var y = base.dists.f.cdf( NaN, 1.0, 1.0 )\n    NaN\n    > var y = base.dists.f.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > var y = base.dists.f.cdf( 0.0, 1.0, NaN )\n    NaN\n\n    > var y = base.dists.f.cdf( 2.0, 1.0, -1.0 )\n    NaN\n    > var y = base.dists.f.cdf( 2.0, -1.0, 1.0 )\n    NaN\n\n\nbase.dists.f.cdf.factory( d1, d2 )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an F distribution with numerator degrees of freedom `d1` and denominator\n    degrees of freedom `d2`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.f.cdf.factory( 10.0, 2.0 );\n    > var y = myCDF( 10.0 )\n    ~0.906\n    > y = myCDF( 8.0 )\n    ~0.884\n\n","base.dists.f.cdf.factory":"\nbase.dists.f.cdf.factory( d1, d2 )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an F distribution with numerator degrees of freedom `d1` and denominator\n    degrees of freedom `d2`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.f.cdf.factory( 10.0, 2.0 );\n    > var y = myCDF( 10.0 )\n    ~0.906\n    > y = myCDF( 8.0 )\n    ~0.884","base.dists.f.entropy":"\nbase.dists.f.entropy( d1, d2 )\n    Returns the differential entropy of an F distribution (in nats).\n\n    If `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n    If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.f.entropy( 3.0, 7.0 )\n    ~1.298\n    > v = base.dists.f.entropy( 4.0, 12.0 )\n    ~1.12\n    > v = base.dists.f.entropy( 8.0, 2.0 )\n    ~2.144\n\n","base.dists.f.F":"\nbase.dists.f.F( [d1, d2] )\n    Returns an F distribution object.\n\n    Parameters\n    ----------\n    d1: number (optional)\n        Numerator degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n    d2: number (optional)\n        Denominator degrees of freedom. Must be greater than `0`.\n        Default: `1.0`.\n\n    Returns\n    -------\n    f: Object\n        Distribution instance.\n\n    f.d1: number\n        Numerator degrees of freedom. If set, the value must be greater than\n        `0`.\n\n    f.d2: number\n        Denominator degrees of freedom. If set, the value must be greater than\n        `0`.\n\n    f.entropy: number\n        Read-only property which returns the differential entropy.\n\n    f.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    f.mean: number\n        Read-only property which returns the expected value.\n\n    f.mode: number\n        Read-only property which returns the mode.\n\n    f.skewness: number\n        Read-only property which returns the skewness.\n\n    f.stdev: number\n        Read-only property which returns the standard deviation.\n\n    f.variance: number\n        Read-only property which returns the variance.\n\n    f.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    f.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    f.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var f = base.dists.f.F( 6.0, 9.0 );\n    > f.d1\n    6.0\n    > f.d2\n    9.0\n    > f.entropy\n    ~1.134\n    > f.kurtosis\n    ~104.564\n    > f.mean\n    ~1.286\n    > f.mode\n    ~0.545\n    > f.skewness\n    ~4.535\n    > f.stdev\n    ~1.197\n    > f.variance\n    ~1.433\n    > f.cdf( 3.0 )\n    ~0.932\n    > f.pdf( 2.5 )\n    ~0.095\n    > f.quantile( 0.8 )\n    ~1.826\n\n","base.dists.f.kurtosis":"\nbase.dists.f.kurtosis( d1, d2 )\n    Returns the excess kurtosis of an F distribution.\n\n    If `d1 <= 0` or `d2 <= 8`, the function returns `NaN`.\n\n    If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.f.kurtosis( 3.0, 9.0 )\n    ~124.667\n    > v = base.dists.f.kurtosis( 4.0, 12.0 )\n    ~26.143\n    > v = base.dists.f.kurtosis( 8.0, 9.0 )\n    ~100.167\n\n","base.dists.f.mean":"\nbase.dists.f.mean( d1, d2 )\n    Returns the expected value of an F distribution.\n\n    If `d1 <= 0` or `d2 <= 2`, the function returns `NaN`.\n\n    If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.f.mean( 3.0, 5.0 )\n    ~1.667\n    > v = base.dists.f.mean( 4.0, 12.0 )\n    ~1.2\n    > v = base.dists.f.mean( 8.0, 4.0 )\n    2.0\n\n","base.dists.f.mode":"\nbase.dists.f.mode( d1, d2 )\n    Returns the mode of an F distribution.\n\n    If `d1 <= 2` or `d2 <= 0`, the function returns `NaN`.\n\n    If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.f.mode( 3.0, 5.0 )\n    ~0.238\n    > v = base.dists.f.mode( 4.0, 12.0 )\n    ~0.429\n    > v = base.dists.f.mode( 8.0, 4.0 )\n    0.5\n\n","base.dists.f.pdf":"\nbase.dists.f.pdf( x, d1, d2 )\n    Evaluates the probability density function (PDF) for an F distribution with\n    numerator degrees of freedom `d1` and denominator degrees of freedom `d2` at\n    a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.f.pdf( 2.0, 0.5, 1.0 )\n    ~0.057\n    > y = base.dists.f.pdf( 0.1, 1.0, 1.0 )\n    ~0.915\n    > y = base.dists.f.pdf( -1.0, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.f.pdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.f.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.f.pdf( 0.0, 1.0, NaN )\n    NaN\n\n    > y = base.dists.f.pdf( 2.0, 1.0, -1.0 )\n    NaN\n    > y = base.dists.f.pdf( 2.0, -1.0, 1.0 )\n    NaN\n\n\nbase.dists.f.pdf.factory( d1, d2 )\n    Returns a function for evaluating the probability density function (PDF) of\n    an F distribution with numerator degrees of freedom `d1` and denominator\n    degrees of freedom `d2`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.f.pdf.factory( 6.0, 7.0 );\n    > var y = myPDF( 7.0 )\n    ~0.004\n    > y = myPDF( 2.0 )\n    ~0.166\n\n","base.dists.f.pdf.factory":"\nbase.dists.f.pdf.factory( d1, d2 )\n    Returns a function for evaluating the probability density function (PDF) of\n    an F distribution with numerator degrees of freedom `d1` and denominator\n    degrees of freedom `d2`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.f.pdf.factory( 6.0, 7.0 );\n    > var y = myPDF( 7.0 )\n    ~0.004\n    > y = myPDF( 2.0 )\n    ~0.166","base.dists.f.quantile":"\nbase.dists.f.quantile( p, d1, d2 )\n    Evaluates the quantile function for an F distribution with numerator degrees\n    of freedom `d1` and denominator degrees of freedom `d2` at a probability\n    `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.f.quantile( 0.8, 1.0, 1.0 )\n    ~9.472\n    > y = base.dists.f.quantile( 0.5, 4.0, 2.0 )\n    ~1.207\n\n    > y = base.dists.f.quantile( 1.1, 1.0, 1.0 )\n    NaN\n    > y = base.dists.f.quantile( -0.2, 1.0, 1.0 )\n    NaN\n\n    > y = base.dists.f.quantile( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.f.quantile( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.dists.f.quantile( 0.5, 1.0, NaN )\n    NaN\n\n    > y = base.dists.f.quantile( 0.5, -1.0, 1.0 )\n    NaN\n    > y = base.dists.f.quantile( 0.5, 1.0, -1.0 )\n    NaN\n\n\nbase.dists.f.quantile.factory( d1, d2 )\n    Returns a function for evaluating the quantile function of an F distribution\n    with numerator degrees of freedom `d1` and denominator degrees of freedom\n    `d2`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.f.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.2 )\n    ~0.527\n    > y = myQuantile( 0.8 )\n    ~4.382\n\n","base.dists.f.quantile.factory":"\nbase.dists.f.quantile.factory( d1, d2 )\n    Returns a function for evaluating the quantile function of an F distribution\n    with numerator degrees of freedom `d1` and denominator degrees of freedom\n    `d2`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.f.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.2 )\n    ~0.527\n    > y = myQuantile( 0.8 )\n    ~4.382","base.dists.f.skewness":"\nbase.dists.f.skewness( d1, d2 )\n    Returns the skewness of an F distribution.\n\n    If `d1 <= 0` or `d2 <= 6`, the function returns `NaN`.\n\n    If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.f.skewness( 3.0, 7.0 )\n    11.0\n    > v = base.dists.f.skewness( 4.0, 12.0 )\n    ~3.207\n    > v = base.dists.f.skewness( 8.0, 7.0 )\n    ~10.088\n\n","base.dists.f.stdev":"\nbase.dists.f.stdev( d1, d2 )\n    Returns the standard deviation of an F distribution.\n\n    If `d1 <= 0` or `d2 <= 4`, the function returns `NaN`.\n\n    If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.f.stdev( 3.0, 5.0 )\n    ~3.333\n    > v = base.dists.f.stdev( 4.0, 12.0 )\n    ~1.122\n    > v = base.dists.f.stdev( 8.0, 5.0 )\n    ~2.764\n\n","base.dists.f.variance":"\nbase.dists.f.variance( d1, d2 )\n    Returns the variance of an F distribution.\n\n    If `d1 <= 0` or `d2 <= 4`, the function returns `NaN`.\n\n    If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    d1: number\n        Numerator degrees of freedom.\n\n    d2: number\n        Denominator degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.f.variance( 3.0, 5.0 )\n    ~11.111\n    > v = base.dists.f.variance( 4.0, 12.0 )\n    ~1.26\n    > v = base.dists.f.variance( 8.0, 5.0 )\n    ~7.639\n\n","base.dists.frechet.cdf":"\nbase.dists.frechet.cdf( x, α, s, m )\n    Evaluates the cumulative distribution function (CDF) for a Fréchet\n    distribution with shape parameter `α`, scale parameter `s`, and location\n    `m`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.cdf( 10.0, 2.0, 3.0, 0.0 )\n    ~0.914\n    > y = base.dists.frechet.cdf( -1.0, 2.0, 3.0, -3.0 )\n    ~0.105\n    > y = base.dists.frechet.cdf( 2.5, 2.0, 1.0, 2.0 )\n    ~0.018\n    > y = base.dists.frechet.cdf( NaN, 1.0, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.cdf( 0.0, NaN, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.cdf( 0.0, 1.0, NaN, 0.0 )\n    NaN\n    > y = base.dists.frechet.cdf( 0.0, 1.0, 1.0, NaN )\n    NaN\n    > y = base.dists.frechet.cdf( 0.0, -1.0, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.cdf( 0.0, 1.0, -1.0, 0.0 )\n    NaN\n\n\nbase.dists.frechet.cdf.factory( α, s, m )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n    location `m`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.frechet.cdf.factory( 3.0, 3.0, 5.0 );\n    > var y = myCDF( 10.0 )\n    ~0.806\n    > y = myCDF( 7.0 )\n    ~0.034\n\n","base.dists.frechet.cdf.factory":"\nbase.dists.frechet.cdf.factory( α, s, m )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n    location `m`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.frechet.cdf.factory( 3.0, 3.0, 5.0 );\n    > var y = myCDF( 10.0 )\n    ~0.806\n    > y = myCDF( 7.0 )\n    ~0.034","base.dists.frechet.entropy":"\nbase.dists.frechet.entropy( α, s, m )\n    Returns the differential entropy of a Fréchet distribution with shape\n    parameter `α`, scale parameter `s`, and location `m` (in nats).\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.entropy( 1.0, 1.0, 1.0 )\n    ~2.154\n    > y = base.dists.frechet.entropy( 4.0, 2.0, 1.0 )\n    ~1.028\n    > y = base.dists.frechet.entropy( NaN, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.entropy( 1.0, NaN, 0.0 )\n    NaN\n    > y = base.dists.frechet.entropy( 1.0, 1.0, NaN )\n    NaN\n\n","base.dists.frechet.Frechet":"\nbase.dists.frechet.Frechet( [α, s, m] )\n    Returns a Fréchet distribution object.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n    s: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    m: number (optional)\n        Location parameter. Default: `0.0`.\n\n    Returns\n    -------\n    frechet: Object\n        Distribution instance.\n\n    frechet.alpha: number\n        Shape parameter. If set, the value must be greater than `0`.\n\n    frechet.s: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    frechet.m: number\n        Location parameter.\n\n    frechet.entropy: number\n        Read-only property which returns the differential entropy.\n\n    frechet.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    frechet.mean: number\n        Read-only property which returns the expected value.\n\n    frechet.median: number\n        Read-only property which returns the median.\n\n    frechet.mode: number\n        Read-only property which returns the mode.\n\n    frechet.skewness: number\n        Read-only property which returns the skewness.\n\n    frechet.stdev: number\n        Read-only property which returns the standard deviation.\n\n    frechet.variance: number\n        Read-only property which returns the variance.\n\n    frechet.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    frechet.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    frechet.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    frechet.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    frechet.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var frechet = base.dists.frechet.Frechet( 1.0, 1.0, 0.0 );\n    > frechet.alpha\n    1.0\n    > frechet.s\n    1.0\n    > frechet.m\n    0.0\n    > frechet.entropy\n    ~2.154\n    > frechet.kurtosis\n    Infinity\n    > frechet.mean\n    Infinity\n    > frechet.median\n    ~1.443\n    > frechet.mode\n    0.5\n    > frechet.skewness\n    Infinity\n    > frechet.stdev\n    Infinity\n    > frechet.variance\n    Infinity\n    > frechet.cdf( 0.8 )\n    ~0.287\n    > frechet.logcdf( 0.8 )\n    -1.25\n    > frechet.logpdf( 0.8 )\n    ~-0.804\n    > frechet.pdf( 0.8 )\n    ~0.448\n    > frechet.quantile( 0.8 )\n    ~4.481\n\n","base.dists.frechet.kurtosis":"\nbase.dists.frechet.kurtosis( α, s, m )\n    Returns the excess kurtosis of a Fréchet distribution with shape parameter\n    `α`, scale parameter `s`, and location `m`.\n\n    If provided `0 < α <= 4` and `s > 0`, the function returns positive\n    infinity.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.kurtosis( 5.0, 2.0, 1.0 )\n    ~45.092\n    > var y = base.dists.frechet.kurtosis( 5.0, 10.0, -3.0 )\n    ~45.092\n    > y = base.dists.frechet.kurtosis( 3.5, 2.0, 1.0 )\n    Infinity\n    > y = base.dists.frechet.kurtosis( NaN, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.kurtosis( 1.0, NaN, 0.0 )\n    NaN\n    > y = base.dists.frechet.kurtosis( 1.0, 1.0, NaN )\n    NaN\n\n","base.dists.frechet.logcdf":"\nbase.dists.frechet.logcdf( x, α, s, m )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a Fréchet distribution with shape parameter `α`, scale parameter\n    `s`, and location `m`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.logcdf( 10.0, 2.0, 3.0, 0.0 )\n    ~-0.09\n    > y = base.dists.frechet.logcdf( -1.0, 2.0, 3.0, -3.0 )\n    ~-2.25\n    > y = base.dists.frechet.logcdf( 2.5, 2.0, 1.0, 2.0 )\n    -4.0\n    > y = base.dists.frechet.logcdf( NaN, 1.0, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.logcdf( 0.0, NaN, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.logcdf( 0.0, 1.0, NaN, 0.0 )\n    NaN\n    > y = base.dists.frechet.logcdf( 0.0, 1.0, 1.0, NaN )\n    NaN\n    > y = base.dists.frechet.logcdf( 0.0, -1.0, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.logcdf( 0.0, 1.0, -1.0, 0.0 )\n    NaN\n\n\nbase.dists.frechet.logcdf.factory( α, s, m )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Fréchet distribution with shape parameter\n    `α`, scale parameter `s`, and location `m`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.frechet.logcdf.factory( 3.0, 3.0, 5.0 );\n    > var y = mylogcdf( 10.0 )\n    ~-0.216\n    > y = mylogcdf( 7.0 )\n    ~-3.375\n\n","base.dists.frechet.logcdf.factory":"\nbase.dists.frechet.logcdf.factory( α, s, m )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Fréchet distribution with shape parameter\n    `α`, scale parameter `s`, and location `m`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.frechet.logcdf.factory( 3.0, 3.0, 5.0 );\n    > var y = mylogcdf( 10.0 )\n    ~-0.216\n    > y = mylogcdf( 7.0 )\n    ~-3.375","base.dists.frechet.logpdf":"\nbase.dists.frechet.logpdf( x, α, s, m )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n    location `m`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.logpdf( 10.0, 1.0, 3.0, 5.0 )\n    ~-2.72\n    > y = base.dists.frechet.logpdf( -2.0, 1.0, 3.0, -3.0 )\n    ~-1.901\n    > y = base.dists.frechet.logpdf( 0.0, 2.0, 1.0, -1.0 )\n    ~-0.307\n    > y = base.dists.frechet.logpdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.frechet.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.frechet.logpdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.frechet.logpdf( 0.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.frechet.logpdf.factory( α, s, m )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Fréchet distribution with shape parameter `α`, scale\n    parameter `s`, and location `m`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.frechet.logpdf.factory( 2.0, 3.0, 1.0 );\n    > var y = mylogPDF( 10.0 )\n    ~-3.812\n    > y = mylogPDF( 2.0 )\n    ~-6.11\n\n","base.dists.frechet.logpdf.factory":"\nbase.dists.frechet.logpdf.factory( α, s, m )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Fréchet distribution with shape parameter `α`, scale\n    parameter `s`, and location `m`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.frechet.logpdf.factory( 2.0, 3.0, 1.0 );\n    > var y = mylogPDF( 10.0 )\n    ~-3.812\n    > y = mylogPDF( 2.0 )\n    ~-6.11","base.dists.frechet.mean":"\nbase.dists.frechet.mean( α, s, m )\n    Returns the expected value of a Fréchet distribution with shape parameter\n    `α`, scale parameter `s`, and location `m`.\n\n    If provided `0 < α <= 1` and `s > 0`, the function returns positive\n    infinity.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Mean.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.mean( 4.0, 2.0, 1.0 )\n    ~3.451\n    > y = base.dists.frechet.mean( 0.5, 2.0, 1.0 )\n    Infinity\n    > y = base.dists.frechet.mean( NaN, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.mean( 1.0, NaN, 0.0 )\n    NaN\n    > y = base.dists.frechet.mean( 1.0, 1.0, NaN )\n    NaN\n\n","base.dists.frechet.median":"\nbase.dists.frechet.median( α, s, m )\n    Returns the median of a Fréchet distribution with shape parameter\n    `α`, scale parameter `s`, and location `m`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.median( 4.0, 2.0, 1.0 )\n    ~3.192\n    > var y = base.dists.frechet.median( 4.0, 2.0, -3.0 )\n    ~-0.808\n    > y = base.dists.frechet.median( 0.5, 2.0, 1.0 )\n    ~5.163\n    > y = base.dists.frechet.median( NaN, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.median( 1.0, NaN, 0.0 )\n    NaN\n    > y = base.dists.frechet.median( 1.0, 1.0, NaN )\n    NaN\n\n","base.dists.frechet.mode":"\nbase.dists.frechet.mode( α, s, m )\n    Returns the mode of a Fréchet distribution with shape parameter `α`, scale\n    parameter `s`, and location `m`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.mode( 4.0, 2.0, 1.0 )\n    ~2.891\n    > var y = base.dists.frechet.mode( 4.0, 2.0, -3.0 )\n    ~-1.109\n    > y = base.dists.frechet.mode( 0.5, 2.0, 1.0 )\n    ~1.222\n    > y = base.dists.frechet.mode( NaN, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.mode( 1.0, NaN, 0.0 )\n    NaN\n    > y = base.dists.frechet.mode( 1.0, 1.0, NaN )\n    NaN\n\n","base.dists.frechet.pdf":"\nbase.dists.frechet.pdf( x, α, s, m )\n    Evaluates the probability density function (PDF) for a Fréchet distribution\n    with shape parameter `α`, scale parameter `s`, and location `m`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.pdf( 10.0, 0.0, 3.0 )\n    ~0.965\n    > y = base.dists.frechet.pdf( -2.0, 0.0, 3.0 )\n    ~0.143\n    > y = base.dists.frechet.pdf( 0.0, 0.0, 1.0 )\n    ~0.368\n    > y = base.dists.frechet.pdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.frechet.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.frechet.pdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.frechet.pdf( 0.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.frechet.pdf.factory( α, s, m )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n    location `m`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.frechet.pdf.factory( 2.0, 3.0 );\n    > var y = myPDF( 10.0 )\n    ~0.933\n    > y = myPDF( 2.0 )\n    ~0.368\n\n","base.dists.frechet.pdf.factory":"\nbase.dists.frechet.pdf.factory( α, s, m )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n    location `m`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.frechet.pdf.factory( 2.0, 3.0 );\n    > var y = myPDF( 10.0 )\n    ~0.933\n    > y = myPDF( 2.0 )\n    ~0.368","base.dists.frechet.quantile":"\nbase.dists.frechet.quantile( p, α, s, m )\n    Evaluates the quantile function for a Fréchet distribution with shape\n    parameter `α`, scale parameter `s`, and location `m`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.quantile( 0.3, 10.0, 2.0, 3.0 )\n    ~4.963\n    > y = base.dists.frechet.quantile( 0.2, 3.0, 3.0, 3.0 )\n    ~5.56\n    > y = base.dists.frechet.quantile( 0.9, 1.0, 1.0, -3.0 )\n    ~6.491\n    > y = base.dists.frechet.quantile( NaN, 1.0, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.quantile( 0.0, NaN, 1.0, 0.0)\n    NaN\n    > y = base.dists.frechet.quantile( 0.0, 1.0, NaN, 0.0 )\n    NaN\n    > y = base.dists.frechet.quantile( 0.0, 1.0, 1.0, NaN )\n    NaN\n    > y = base.dists.frechet.quantile( 0.0, -1.0, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.quantile( 0.0, 1.0, -1.0, 0.0 )\n    NaN\n\n\nbase.dists.frechet.quantile.factory( α, s, m )\n    Returns a function for evaluating the quantile function of a Fréchet\n    distribution with shape parameter `α`, scale parameter `s`, and location\n    `m`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.frechet.quantile.factory( 2.0, 2.0, 3.0 );\n    > var y = myQuantile( 0.5 )\n    ~5.402\n    > y = myQuantile( 0.2 )\n    ~4.576\n\n","base.dists.frechet.quantile.factory":"\nbase.dists.frechet.quantile.factory( α, s, m )\n    Returns a function for evaluating the quantile function of a Fréchet\n    distribution with shape parameter `α`, scale parameter `s`, and location\n    `m`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.frechet.quantile.factory( 2.0, 2.0, 3.0 );\n    > var y = myQuantile( 0.5 )\n    ~5.402\n    > y = myQuantile( 0.2 )\n    ~4.576","base.dists.frechet.skewness":"\nbase.dists.frechet.skewness( α, s, m )\n    Returns the skewness of a Fréchet distribution with shape parameter `α`,\n    scale parameter `s`, and location `m`.\n\n    If provided `0 < α <= 3` and `s > 0`, the function returns positive\n    infinity.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.skewness( 4.0, 2.0, 1.0 )\n    ~5.605\n    > var y = base.dists.frechet.skewness( 4.0, 2.0, -3.0 )\n    ~5.605\n    > y = base.dists.frechet.skewness( 0.5, 2.0, 1.0 )\n    Infinity\n    > y = base.dists.frechet.skewness( NaN, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.skewness( 1.0, NaN, 0.0 )\n    NaN\n    > y = base.dists.frechet.skewness( 1.0, 1.0, NaN )\n    NaN\n\n","base.dists.frechet.stdev":"\nbase.dists.frechet.stdev( α, s, m )\n    Returns the standard deviation of a Fréchet distribution with shape\n    parameter `α`, scale parameter `s`, and location `m`.\n\n    If provided `0 < α <= 2` and `s > 0`, the function returns positive\n    infinity.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.stdev( 4.0, 2.0, 1.0 )\n    ~1.041\n    > var y = base.dists.frechet.stdev( 4.0, 2.0, -3.0 )\n    ~1.041\n    > y = base.dists.frechet.stdev( 0.5, 2.0, 1.0 )\n    Infinity\n    > y = base.dists.frechet.stdev( NaN, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.stdev( 1.0, NaN, 0.0 )\n    NaN\n    > y = base.dists.frechet.stdev( 1.0, 1.0, NaN )\n    NaN\n\n","base.dists.frechet.variance":"\nbase.dists.frechet.variance( α, s, m )\n    Returns the variance of a Fréchet distribution with shape parameter `α`,\n    scale parameter `s`, and location `m`.\n\n    If provided `0 < α <= 2` and `s > 0`, the function returns positive\n    infinity.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var y = base.dists.frechet.variance( 4.0, 2.0, 1.0 )\n    ~1.083\n    > var y = base.dists.frechet.variance( 4.0, 2.0, -3.0 )\n    ~1.083\n    > y = base.dists.frechet.variance( 0.5, 2.0, 1.0 )\n    Infinity\n    > y = base.dists.frechet.variance( NaN, 1.0, 0.0 )\n    NaN\n    > y = base.dists.frechet.variance( 1.0, NaN, 0.0 )\n    NaN\n    > y = base.dists.frechet.variance( 1.0, 1.0, NaN )\n    NaN\n\n","base.dists.gamma.cdf":"\nbase.dists.gamma.cdf( x, α, β )\n    Evaluates the cumulative distribution function (CDF) for a gamma\n    distribution with shape parameter `α` and rate parameter `β` at a value `x`.\n\n    If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.gamma.cdf( 2.0, 1.0, 1.0 )\n    ~0.865\n    > y = base.dists.gamma.cdf( 2.0, 3.0, 1.0 )\n    ~0.323\n    > y = base.dists.gamma.cdf( -1.0, 2.0, 2.0 )\n    0.0\n    > y = base.dists.gamma.cdf( PINF, 4.0, 2.0 )\n    1.0\n    > y = base.dists.gamma.cdf( NINF, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.gamma.cdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.gamma.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gamma.cdf( 0.0, 0.0, NaN )\n    NaN\n\n    > y = base.dists.gamma.cdf( 2.0, -1.0, 1.0 )\n    NaN\n    > y = base.dists.gamma.cdf( 2.0, 1.0, -1.0 )\n    NaN\n\n    // Degenerate distribution centered at `0` when `α = 0.0`:\n    > y = base.dists.gamma.cdf( 2.0, 0.0, 2.0 )\n    1.0\n    > y = base.dists.gamma.cdf( -2.0, 0.0, 2.0 )\n    0.0\n    > y = base.dists.gamma.cdf( 0.0, 0.0, 2.0 )\n    0.0\n\n\nbase.dists.gamma.cdf.factory( α, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.gamma.cdf.factory( 2.0, 0.5 );\n    > var y = myCDF( 6.0 )\n    ~0.801\n    > y = myCDF( 2.0 )\n    ~0.264\n\n","base.dists.gamma.cdf.factory":"\nbase.dists.gamma.cdf.factory( α, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.gamma.cdf.factory( 2.0, 0.5 );\n    > var y = myCDF( 6.0 )\n    ~0.801\n    > y = myCDF( 2.0 )\n    ~0.264","base.dists.gamma.entropy":"\nbase.dists.gamma.entropy( α, β )\n    Returns the differential entropy of a gamma distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.gamma.entropy( 1.0, 1.0 )\n    1.0\n    > v = base.dists.gamma.entropy( 4.0, 12.0 )\n    ~-0.462\n    > v = base.dists.gamma.entropy( 8.0, 2.0 )\n    ~1.723\n\n","base.dists.gamma.Gamma":"\nbase.dists.gamma.Gamma( [α, β] )\n    Returns a gamma distribution object.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n    β: number (optional)\n        Rate parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    gamma: Object\n        Distribution instance.\n\n    gamma.alpha: number\n        Shape parameter. If set, the value must be greater than `0`.\n\n    gamma.beta: number\n        Rate parameter. If set, the value must be greater than `0`.\n\n    gamma.entropy: number\n        Read-only property which returns the differential entropy.\n\n    gamma.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    gamma.mean: number\n        Read-only property which returns the expected value.\n\n    gamma.mode: number\n        Read-only property which returns the mode.\n\n    gamma.skewness: number\n        Read-only property which returns the skewness.\n\n    gamma.stdev: number\n        Read-only property which returns the standard deviation.\n\n    gamma.variance: number\n        Read-only property which returns the variance.\n\n    gamma.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    gamma.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    gamma.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    gamma.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    gamma.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    gamma.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var gamma = base.dists.gamma.Gamma( 6.0, 5.0 );\n    > gamma.alpha\n    6.0\n    > gamma.beta\n    5.0\n    > gamma.entropy\n    ~0.647\n    > gamma.kurtosis\n    1.0\n    > gamma.mean\n    1.2\n    > gamma.mode\n    1.0\n    > gamma.skewness\n    ~0.816\n    > gamma.stdev\n    ~0.49\n    > gamma.variance\n    0.24\n    > gamma.cdf( 0.8 )\n    ~0.215\n    > gamma.logcdf( 0.8 )\n    ~-1.538\n    > gamma.logpdf( 1.0 )\n    ~-0.131\n    > gamma.mgf( -0.5 )\n    ~0.564\n    > gamma.pdf( 1.0 )\n    ~0.877\n    > gamma.quantile( 0.8 )\n    ~1.581\n\n","base.dists.gamma.kurtosis":"\nbase.dists.gamma.kurtosis( α, β )\n    Returns the excess kurtosis of a gamma distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.gamma.kurtosis( 1.0, 1.0 )\n    6.0\n    > v = base.dists.gamma.kurtosis( 4.0, 12.0 )\n    1.5\n    > v = base.dists.gamma.kurtosis( 8.0, 2.0 )\n    0.75\n\n","base.dists.gamma.logcdf":"\nbase.dists.gamma.logcdf( x, α, β )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    gamma distribution with shape parameter `α` and rate parameter `β` at a\n    value `x`.\n\n    If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.gamma.logcdf( 2.0, 0.5, 1.0 )\n    ~-0.047\n    > y = base.dists.gamma.logcdf( 0.1, 1.0, 1.0 )\n    ~-2.352\n    > y = base.dists.gamma.logcdf( -1.0, 4.0, 2.0 )\n    -Infinity\n\n    > y = base.dists.gamma.logcdf( NaN, 0.6, 1.0 )\n    NaN\n    > y = base.dists.gamma.logcdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gamma.logcdf( 0.0, 1.0, NaN )\n    NaN\n\n    // Negative shape parameter:\n    > y = base.dists.gamma.logcdf( 2.0, -1.0, 1.0 )\n    NaN\n    // Non-positive rate parameter:\n    > y = base.dists.gamma.logcdf( 2.0, 1.0, -1.0 )\n    NaN\n\n\nbase.dists.gamma.logcdf.factory( α, β )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a gamma distribution with shape parameter `α`\n    and rate parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogCDF = base.dists.gamma.logcdf.factory( 6.0, 7.0 );\n    > var y = mylogCDF( 2.0 )\n    ~-0.006\n\n","base.dists.gamma.logcdf.factory":"\nbase.dists.gamma.logcdf.factory( α, β )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a gamma distribution with shape parameter `α`\n    and rate parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogCDF = base.dists.gamma.logcdf.factory( 6.0, 7.0 );\n    > var y = mylogCDF( 2.0 )\n    ~-0.006","base.dists.gamma.logpdf":"\nbase.dists.gamma.logpdf( x, α, β )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    gamma distribution with shape parameter `α` and rate parameter `β` at a\n    value `x`.\n\n    If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.gamma.logpdf( 2.0, 0.5, 1.0 )\n    ~-2.919\n    > y = base.dists.gamma.logpdf( 0.1, 1.0, 1.0 )\n    ~-0.1\n    > y = base.dists.gamma.logpdf( -1.0, 4.0, 2.0 )\n    -Infinity\n\n    > y = base.dists.gamma.logpdf( NaN, 0.6, 1.0 )\n    NaN\n    > y = base.dists.gamma.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gamma.logpdf( 0.0, 1.0, NaN )\n    NaN\n\n    // Negative shape parameter:\n    > y = base.dists.gamma.logpdf( 2.0, -1.0, 1.0 )\n    NaN\n    // Non-positive rate parameter:\n    > y = base.dists.gamma.logpdf( 2.0, 1.0, -1.0 )\n    NaN\n\n    // Degenerate distribution centered at `0.0` when `α = 0.0`:\n    > y = base.dists.gamma.logpdf( 2.0, 0.0, 2.0 )\n    -Infinity\n    > y = base.dists.gamma.logpdf( 0.0, 0.0, 2.0 )\n    Infinity\n\n\nbase.dists.gamma.logpdf.factory( α, β )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a gamma distribution with shape parameter `α` and rate\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.gamma.logpdf.factory( 6.0, 7.0 );\n    > var y = mylogPDF( 2.0 )\n    ~-3.646\n\n","base.dists.gamma.logpdf.factory":"\nbase.dists.gamma.logpdf.factory( α, β )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a gamma distribution with shape parameter `α` and rate\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.gamma.logpdf.factory( 6.0, 7.0 );\n    > var y = mylogPDF( 2.0 )\n    ~-3.646","base.dists.gamma.mean":"\nbase.dists.gamma.mean( α, β )\n    Returns the expected value of a gamma distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.gamma.mean( 1.0, 1.0 )\n    1.0\n    > v = base.dists.gamma.mean( 4.0, 12.0 )\n    ~0.333\n    > v = base.dists.gamma.mean( 8.0, 2.0 )\n    4.0\n\n","base.dists.gamma.mgf":"\nbase.dists.gamma.mgf( t, α, β )\n    Evaluates the moment-generating function (MGF) for a gamma distribution with\n    shape parameter `α` and rate parameter `β` at a value `t`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.gamma.mgf( 0.5, 0.5, 1.0 )\n    ~1.414\n    > y = base.dists.gamma.mgf( 0.1, 1.0, 1.0 )\n    ~1.111\n    > y = base.dists.gamma.mgf( -1.0, 4.0, 2.0 )\n    ~0.198\n\n    > y = base.dists.gamma.mgf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.gamma.mgf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gamma.mgf( 0.0, 1.0, NaN )\n    NaN\n\n    > y = base.dists.gamma.mgf( 2.0, 4.0, 1.0 )\n    NaN\n    > y = base.dists.gamma.mgf( 2.0, -0.5, 1.0 )\n    NaN\n    > y = base.dists.gamma.mgf( 2.0, 1.0, 0.0 )\n    NaN\n    > y = base.dists.gamma.mgf( 2.0, 1.0, -1.0 )\n    NaN\n\n\nbase.dists.gamma.mgf.factory( α, β )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    gamma distribution with shape parameter `α` and rate parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.gamma.mgf.factory( 3.0, 1.5 );\n    > var y = myMGF( 1.0 )\n    ~27.0\n    > y = myMGF( 0.5 )\n    ~3.375\n\n","base.dists.gamma.mgf.factory":"\nbase.dists.gamma.mgf.factory( α, β )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    gamma distribution with shape parameter `α` and rate parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.gamma.mgf.factory( 3.0, 1.5 );\n    > var y = myMGF( 1.0 )\n    ~27.0\n    > y = myMGF( 0.5 )\n    ~3.375","base.dists.gamma.mode":"\nbase.dists.gamma.mode( α, β )\n    Returns the mode of a gamma distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.gamma.mode( 1.0, 1.0 )\n    0.0\n    > v = base.dists.gamma.mode( 4.0, 12.0 )\n    0.25\n    > v = base.dists.gamma.mode( 8.0, 2.0 )\n    3.5\n\n","base.dists.gamma.pdf":"\nbase.dists.gamma.pdf( x, α, β )\n    Evaluates the probability density function (PDF) for a gamma distribution\n    with shape parameter `α` and rate parameter `β` at a value `x`.\n\n    If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.gamma.pdf( 2.0, 0.5, 1.0 )\n    ~0.054\n    > y = base.dists.gamma.pdf( 0.1, 1.0, 1.0 )\n    ~0.905\n    > y = base.dists.gamma.pdf( -1.0, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.gamma.pdf( NaN, 0.6, 1.0 )\n    NaN\n    > y = base.dists.gamma.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gamma.pdf( 0.0, 1.0, NaN )\n    NaN\n\n    // Negative shape parameter:\n    > y = base.dists.gamma.pdf( 2.0, -1.0, 1.0 )\n    NaN\n    // Non-positive rate parameter:\n    > y = base.dists.gamma.pdf( 2.0, 1.0, -1.0 )\n    NaN\n\n    // Degenerate distribution centered at `0.0` when `α = 0.0`:\n    > y = base.dists.gamma.pdf( 2.0, 0.0, 2.0 )\n    0.0\n    > y = base.dists.gamma.pdf( 0.0, 0.0, 2.0 )\n    Infinity\n\n\nbase.dists.gamma.pdf.factory( α, β )\n    Returns a function for evaluating the probability density function (PDF) of\n    a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.gamma.pdf.factory( 6.0, 7.0 );\n    > var y = myPDF( 2.0 )\n    ~0.026\n\n","base.dists.gamma.pdf.factory":"\nbase.dists.gamma.pdf.factory( α, β )\n    Returns a function for evaluating the probability density function (PDF) of\n    a gamma distribution with shape parameter `α` and rate parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.gamma.pdf.factory( 6.0, 7.0 );\n    > var y = myPDF( 2.0 )\n    ~0.026","base.dists.gamma.quantile":"\nbase.dists.gamma.quantile( p, α, β )\n    Evaluates the quantile function for a gamma distribution with shape\n    parameter `α` and rate parameter `β` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If `α < 0` or `β <= 0`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.gamma.quantile( 0.8, 2.0, 1.0 )\n    ~2.994\n    > y = base.dists.gamma.quantile( 0.5, 4.0, 2.0 )\n    ~1.836\n\n    > y = base.dists.gamma.quantile( 1.1, 1.0, 1.0 )\n    NaN\n    > y = base.dists.gamma.quantile( -0.2, 1.0, 1.0 )\n    NaN\n\n    > y = base.dists.gamma.quantile( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.gamma.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gamma.quantile( 0.0, 1.0, NaN )\n    NaN\n\n    // Non-positive shape parameter:\n    > y = base.dists.gamma.quantile( 0.5, -1.0, 1.0 )\n    NaN\n    // Non-positive rate parameter:\n    > y = base.dists.gamma.quantile( 0.5, 1.0, -1.0 )\n    NaN\n\n    // Degenerate distribution centered at `0.0` when `α = 0.0`:\n    > y = base.dists.gamma.quantile( 0.3, 0.0, 2.0 )\n    0.0\n    > y = base.dists.gamma.quantile( 0.9, 0.0, 2.0 )\n    0.0\n\n\nbase.dists.gamma.quantile.factory( α, β )\n    Returns a function for evaluating the quantile function of a gamma\n    distribution with shape parameter `α` and rate parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.gamma.quantile.factory( 2.0, 2.0 );\n    > var y = myQuantile( 0.8 )\n    ~1.497\n    > y = myQuantile( 0.4 )\n    ~0.688\n\n","base.dists.gamma.quantile.factory":"\nbase.dists.gamma.quantile.factory( α, β )\n    Returns a function for evaluating the quantile function of a gamma\n    distribution with shape parameter `α` and rate parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.gamma.quantile.factory( 2.0, 2.0 );\n    > var y = myQuantile( 0.8 )\n    ~1.497\n    > y = myQuantile( 0.4 )\n    ~0.688","base.dists.gamma.skewness":"\nbase.dists.gamma.skewness( α, β )\n    Returns the skewness of a gamma distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.gamma.skewness( 1.0, 1.0 )\n    2.0\n    > v = base.dists.gamma.skewness( 4.0, 12.0 )\n    1.0\n    > v = base.dists.gamma.skewness( 8.0, 2.0 )\n    ~0.707\n\n","base.dists.gamma.stdev":"\nbase.dists.gamma.stdev( α, β )\n    Returns the standard deviation of a gamma distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.gamma.stdev( 1.0, 1.0 )\n    1.0\n    > v = base.dists.gamma.stdev( 4.0, 12.0 )\n    ~0.167\n    > v = base.dists.gamma.stdev( 8.0, 2.0 )\n    ~1.414\n\n","base.dists.gamma.variance":"\nbase.dists.gamma.variance( α, β )\n    Returns the variance of a gamma distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.gamma.variance( 1.0, 1.0 )\n    1.0\n    > v = base.dists.gamma.variance( 4.0, 12.0 )\n    ~0.028\n    > v = base.dists.gamma.variance( 8.0, 2.0 )\n    2.0\n\n","base.dists.geometric.cdf":"\nbase.dists.geometric.cdf( x, p )\n    Evaluates the cumulative distribution function (CDF) for a geometric\n    distribution with success probability `p` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.geometric.cdf( 2.0, 0.5 )\n    0.875\n    > y = base.dists.geometric.cdf( 2.0, 0.1 )\n    ~0.271\n    > y = base.dists.geometric.cdf( -1.0, 4.0 )\n    0.0\n    > y = base.dists.geometric.cdf( NaN, 0.5 )\n    NaN\n    > y = base.dists.geometric.cdf( 0.0, NaN )\n    NaN\n    // Invalid probability\n    > y = base.dists.geometric.cdf( 2.0, 1.4 )\n    NaN\n\n\nbase.dists.geometric.cdf.factory( p )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a geometric distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.geometric.cdf.factory( 0.5 );\n    > var y = mycdf( 3.0 )\n    0.9375\n    > y = mycdf( 1.0 )\n    0.75\n\n","base.dists.geometric.cdf.factory":"\nbase.dists.geometric.cdf.factory( p )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a geometric distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.geometric.cdf.factory( 0.5 );\n    > var y = mycdf( 3.0 )\n    0.9375\n    > y = mycdf( 1.0 )\n    0.75","base.dists.geometric.entropy":"\nbase.dists.geometric.entropy( p )\n    Returns the entropy of a geometric distribution with success probability\n    `p` (in nats).\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.geometric.entropy( 0.1 )\n    ~3.251\n    > v = base.dists.geometric.entropy( 0.5 )\n    ~1.386\n\n","base.dists.geometric.Geometric":"\nbase.dists.geometric.Geometric( [p] )\n    Returns a geometric distribution object.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability. Must be between `0` and `1`. Default: `0.5`.\n\n    Returns\n    -------\n    geometric: Object\n        Distribution instance.\n\n    geometric.p: number\n        Success probability. If set, the value must be between `0` and `1`.\n\n    geometric.entropy: number\n        Read-only property which returns the differential entropy.\n\n    geometric.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    geometric.mean: number\n        Read-only property which returns the expected value.\n\n    geometric.median: number\n        Read-only property which returns the median.\n\n    geometric.mode: number\n        Read-only property which returns the mode.\n\n    geometric.skewness: number\n        Read-only property which returns the skewness.\n\n    geometric.stdev: number\n        Read-only property which returns the standard deviation.\n\n    geometric.variance: number\n        Read-only property which returns the variance.\n\n    geometric.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    geometric.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    geometric.logpmf: Function\n        Evaluates the natural logarithm of the probability mass function (PMF).\n\n    geometric.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    geometric.pmf: Function\n        Evaluates the probability mass function (PMF).\n\n    geometric.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var geometric = base.dists.geometric.Geometric( 0.6 );\n    > geometric.p\n    0.6\n    > geometric.entropy\n    ~1.122\n    > geometric.kurtosis\n    ~6.9\n    > geometric.mean\n    ~0.667\n    > geometric.median\n    0.0\n    > geometric.mode\n    0.0\n    > geometric.skewness\n    ~2.214\n    > geometric.stdev\n    ~1.054\n    > geometric.variance\n    ~1.111\n    > geometric.cdf( 3.0 )\n    ~0.974\n    > geometric.logcdf( 3.0 )\n    ~-0.026\n    > geometric.logpmf( 4.0 )\n    ~-4.176\n    > geometric.mgf( 0.5 )\n    ~2.905\n    > geometric.pmf( 2.0 )\n    ~0.096\n    > geometric.quantile( 0.7 )\n    1.0\n\n","base.dists.geometric.kurtosis":"\nbase.dists.geometric.kurtosis( p )\n    Returns the excess kurtosis of a geometric distribution with success\n    probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.geometric.kurtosis( 0.1 )\n    ~6.011\n    > v = base.dists.geometric.kurtosis( 0.5 )\n    6.5\n\n","base.dists.geometric.logcdf":"\nbase.dists.geometric.logcdf( x, p )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    geometric distribution with success probability `p` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.geometric.logcdf( 2.0, 0.5 )\n    ~-0.134\n    > y = base.dists.geometric.logcdf( 2.0, 0.1 )\n    ~-1.306\n    > y = base.dists.geometric.logcdf( -1.0, 4.0 )\n    -Infinity\n    > y = base.dists.geometric.logcdf( NaN, 0.5 )\n    NaN\n    > y = base.dists.geometric.logcdf( 0.0, NaN )\n    NaN\n    // Invalid probability\n    > y = base.dists.geometric.logcdf( 2.0, 1.4 )\n    NaN\n\n\nbase.dists.geometric.logcdf.factory( p )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a geometric distribution with success\n    probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.geometric.logcdf.factory( 0.5 );\n    > var y = mylogcdf( 3.0 )\n    ~-0.065\n    > y = mylogcdf( 1.0 )\n    ~-0.288\n\n","base.dists.geometric.logcdf.factory":"\nbase.dists.geometric.logcdf.factory( p )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a geometric distribution with success\n    probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.geometric.logcdf.factory( 0.5 );\n    > var y = mylogcdf( 3.0 )\n    ~-0.065\n    > y = mylogcdf( 1.0 )\n    ~-0.288","base.dists.geometric.logpmf":"\nbase.dists.geometric.logpmf( x, p )\n    Evaluates the logarithm of the probability mass function (PMF) for a\n    geometric distribution with success probability `p` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPMF.\n\n    Examples\n    --------\n    > var y = base.dists.geometric.logpmf( 4.0, 0.3 )\n    ~-2.631\n    > y = base.dists.geometric.logpmf( 2.0, 0.7 )\n    ~-2.765\n    > y = base.dists.geometric.logpmf( -1.0, 0.5 )\n    -Infinity\n    > y = base.dists.geometric.logpmf( 0.0, NaN )\n    NaN\n    > y = base.dists.geometric.logpmf( NaN, 0.5 )\n    NaN\n    // Invalid success probability:\n    > y = base.dists.geometric.logpmf( 2.0, 1.5 )\n    NaN\n\n\nbase.dists.geometric.logpmf.factory( p )\n    Returns a function for evaluating the logarithm of the probability mass\n    function (PMF) of a geometric distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogpmf = base.dists.geometric.logpmf.factory( 0.5 );\n    > var y = mylogpmf( 3.0 )\n    ~-2.773\n    > y = mylogpmf( 1.0 )\n    ~-1.386\n\n","base.dists.geometric.logpmf.factory":"\nbase.dists.geometric.logpmf.factory( p )\n    Returns a function for evaluating the logarithm of the probability mass\n    function (PMF) of a geometric distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogpmf = base.dists.geometric.logpmf.factory( 0.5 );\n    > var y = mylogpmf( 3.0 )\n    ~-2.773\n    > y = mylogpmf( 1.0 )\n    ~-1.386","base.dists.geometric.mean":"\nbase.dists.geometric.mean( p )\n    Returns the expected value of a geometric distribution with success\n    probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.geometric.mean( 0.1 )\n    9.0\n    > v = base.dists.geometric.mean( 0.5 )\n    1.0\n\n","base.dists.geometric.median":"\nbase.dists.geometric.median( p )\n    Returns the median of a geometric distribution with success probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: integer\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.geometric.median( 0.1 )\n    6\n    > v = base.dists.geometric.median( 0.5 )\n    0\n\n","base.dists.geometric.mgf":"\nbase.dists.geometric.mgf( t, p )\n    Evaluates the moment-generating function (MGF) for a geometric\n    distribution with success probability `p` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If `t >= -ln(1-p)`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.geometric.mgf( 0.2, 0.5 )\n    ~1.569\n    > y = base.dists.geometric.mgf( 0.4, 0.5 )\n    ~2.936\n    // Case: t >= -ln(1-p)\n    > y = base.dists.geometric.mgf( 0.8, 0.5 )\n    NaN\n    > y = base.dists.geometric.mgf( NaN, 0.0 )\n    NaN\n    > y = base.dists.geometric.mgf( 0.0, NaN )\n    NaN\n    > y = base.dists.geometric.mgf( -2.0, -1.0 )\n    NaN\n    > y = base.dists.geometric.mgf( 0.2, 2.0 )\n    NaN\n\n\nbase.dists.geometric.mgf.factory( p )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    geometric distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.geometric.mgf.factory( 0.8 );\n    > var y = mymgf( -0.2 )\n    ~0.783\n\n","base.dists.geometric.mgf.factory":"\nbase.dists.geometric.mgf.factory( p )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    geometric distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.geometric.mgf.factory( 0.8 );\n    > var y = mymgf( -0.2 )\n    ~0.783","base.dists.geometric.mode":"\nbase.dists.geometric.mode( p )\n    Returns the mode of a geometric distribution with success probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: integer\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.geometric.mode( 0.1 )\n    0\n    > v = base.dists.geometric.mode( 0.5 )\n    0\n\n","base.dists.geometric.pmf":"\nbase.dists.geometric.pmf( x, p )\n    Evaluates the probability mass function (PMF) for a geometric distribution\n    with success probability `p` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated PMF.\n\n    Examples\n    --------\n    > var y = base.dists.geometric.pmf( 4.0, 0.3 )\n    ~0.072\n    > y = base.dists.geometric.pmf( 2.0, 0.7 )\n    ~0.063\n    > y = base.dists.geometric.pmf( -1.0, 0.5 )\n    0.0\n    > y = base.dists.geometric.pmf( 0.0, NaN )\n    NaN\n    > y = base.dists.geometric.pmf( NaN, 0.5 )\n    NaN\n    // Invalid success probability:\n    > y = base.dists.geometric.pmf( 2.0, 1.5 )\n    NaN\n\n\nbase.dists.geometric.pmf.factory( p )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    geometric distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var mypmf = base.dists.geometric.pmf.factory( 0.5 );\n    > var y = mypmf( 3.0 )\n    0.0625\n    > y = mypmf( 1.0 )\n    0.25\n\n","base.dists.geometric.pmf.factory":"\nbase.dists.geometric.pmf.factory( p )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    geometric distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var mypmf = base.dists.geometric.pmf.factory( 0.5 );\n    > var y = mypmf( 3.0 )\n    0.0625\n    > y = mypmf( 1.0 )\n    0.25","base.dists.geometric.quantile":"\nbase.dists.geometric.quantile( r, p )\n    Evaluates the quantile function for a geometric distribution with success\n    probability `p` at a probability `r`.\n\n    If `r < 0` or `r > 1`, the function returns `NaN`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    r: number\n        Input probability.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.geometric.quantile( 0.8, 0.4 )\n    3\n    > y = base.dists.geometric.quantile( 0.5, 0.4 )\n    1\n    > y = base.dists.geometric.quantile( 0.9, 0.1 )\n    21\n\n    > y = base.dists.geometric.quantile( -0.2, 0.1 )\n    NaN\n\n    > y = base.dists.geometric.quantile( NaN, 0.8 )\n    NaN\n    > y = base.dists.geometric.quantile( 0.4, NaN )\n    NaN\n\n    > y = base.dists.geometric.quantile( 0.5, -1.0 )\n    NaN\n    > y = base.dists.geometric.quantile( 0.5, 1.5 )\n    NaN\n\n\nbase.dists.geometric.quantile.factory( p )\n    Returns a function for evaluating the quantile function of a geometric\n    distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.geometric.quantile.factory( 0.4 );\n    > var y = myquantile( 0.4 )\n    0\n    > y = myquantile( 0.8 )\n    3\n    > y = myquantile( 1.0 )\n    Infinity\n\n","base.dists.geometric.quantile.factory":"\nbase.dists.geometric.quantile.factory( p )\n    Returns a function for evaluating the quantile function of a geometric\n    distribution with success probability `p`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.geometric.quantile.factory( 0.4 );\n    > var y = myquantile( 0.4 )\n    0\n    > y = myquantile( 0.8 )\n    3\n    > y = myquantile( 1.0 )\n    Infinity","base.dists.geometric.skewness":"\nbase.dists.geometric.skewness( p )\n    Returns the skewness of a geometric distribution with success probability\n    `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.geometric.skewness( 0.1 )\n    ~2.003\n    > v = base.dists.geometric.skewness( 0.5 )\n    ~2.121\n\n","base.dists.geometric.stdev":"\nbase.dists.geometric.stdev( p )\n    Returns the standard deviation of a geometric distribution with success\n    probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.geometric.stdev( 0.1 )\n    ~9.487\n    > v = base.dists.geometric.stdev( 0.5 )\n    ~1.414\n\n","base.dists.geometric.variance":"\nbase.dists.geometric.variance( p )\n    Returns the variance of a geometric distribution with success probability\n    `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.geometric.variance( 0.1 )\n    ~90.0\n    > v = base.dists.geometric.variance( 0.5 )\n    2.0\n\n","base.dists.gumbel.cdf":"\nbase.dists.gumbel.cdf( x, μ, β )\n    Evaluates the cumulative distribution function (CDF) for a Gumbel\n    distribution with location parameter `μ` and scale parameter `β` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.cdf( 10.0, 0.0, 3.0 )\n    ~0.965\n    > y = base.dists.gumbel.cdf( -2.0, 0.0, 3.0 )\n    ~0.143\n    > y = base.dists.gumbel.cdf( 0.0, 0.0, 1.0 )\n    ~0.368\n    > y = base.dists.gumbel.cdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.gumbel.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.cdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.gumbel.cdf( 0.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.gumbel.cdf.factory( μ, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Gumbel distribution with location parameter `μ` and scale parameter\n    `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.gumbel.cdf.factory( 2.0, 3.0 );\n    > var y = myCDF( 10.0 )\n    ~0.933\n    > y = myCDF( 2.0 )\n    ~0.368\n\n","base.dists.gumbel.cdf.factory":"\nbase.dists.gumbel.cdf.factory( μ, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Gumbel distribution with location parameter `μ` and scale parameter\n    `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.gumbel.cdf.factory( 2.0, 3.0 );\n    > var y = myCDF( 10.0 )\n    ~0.933\n    > y = myCDF( 2.0 )\n    ~0.368","base.dists.gumbel.entropy":"\nbase.dists.gumbel.entropy( μ, β )\n    Returns the differential entropy of a Gumbel distribution with location\n    parameter `μ` and scale parameter `β` (in nats).\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.entropy( 0.0, 1.0 )\n    ~1.577\n    > y = base.dists.gumbel.entropy( 4.0, 2.0 )\n    ~2.27\n    > y = base.dists.gumbel.entropy( NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.entropy( 0.0, NaN )\n    NaN\n    > y = base.dists.gumbel.entropy( 0.0, 0.0 )\n    NaN\n\n","base.dists.gumbel.Gumbel":"\nbase.dists.gumbel.Gumbel( [μ, β] )\n    Returns a Gumbel distribution object.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter. Default: `0.0`.\n\n    β: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    gumbel: Object\n        Distribution instance.\n\n    gumbel.mu: number\n        Location parameter.\n\n    gumbel.beta: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    gumbel.entropy: number\n        Read-only property which returns the differential entropy.\n\n    gumbel.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    gumbel.mean: number\n        Read-only property which returns the expected value.\n\n    gumbel.median: number\n        Read-only property which returns the median.\n\n    gumbel.mode: number\n        Read-only property which returns the mode.\n\n    gumbel.skewness: number\n        Read-only property which returns the skewness.\n\n    gumbel.stdev: number\n        Read-only property which returns the standard deviation.\n\n    gumbel.variance: number\n        Read-only property which returns the variance.\n\n    gumbel.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    gumbel.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    gumbel.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    gumbel.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    gumbel.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    gumbel.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var gumbel = base.dists.gumbel.Gumbel( -2.0, 3.0 );\n    > gumbel.mu\n    -2.0\n    > gumbel.beta\n    3.0\n    > gumbel.entropy\n    ~2.676\n    > gumbel.kurtosis\n    2.4\n    > gumbel.mean\n    ~-0.268\n    > gumbel.median\n    ~-0.9\n    > gumbel.mode\n    -2.0\n    > gumbel.skewness\n    ~1.14\n    > gumbel.stdev\n    ~3.848\n    > gumbel.variance\n    ~14.804\n    > gumbel.cdf( 0.8 )\n    ~0.675\n    > gumbel.logcdf( 0.8 )\n    ~-0.393\n    > gumbel.logpdf( 1.0 )\n    ~-2.466\n    > gumbel.mgf( 0.2 )\n    ~1.487\n    > gumbel.pdf( 1.0 )\n    ~0.085\n    > gumbel.quantile( 0.8 )\n    ~2.5\n\n","base.dists.gumbel.kurtosis":"\nbase.dists.gumbel.kurtosis( μ, β )\n    Returns the excess kurtosis of a Gumbel distribution with location parameter\n    `μ` and scale parameter `β`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.kurtosis( 0.0, 1.0 )\n    2.4\n    > y = base.dists.gumbel.kurtosis( 4.0, 2.0 )\n    2.4\n    > y = base.dists.gumbel.kurtosis( NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.kurtosis( 0.0, NaN )\n    NaN\n    > y = base.dists.gumbel.kurtosis( 0.0, 0.0 )\n    NaN\n\n","base.dists.gumbel.logcdf":"\nbase.dists.gumbel.logcdf( x, μ, β )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.logcdf( 10.0, 0.0, 3.0 )\n    ~-0.036\n    > y = base.dists.gumbel.logcdf( -2.0, 0.0, 3.0 )\n    ~-1.948\n    > y = base.dists.gumbel.logcdf( 0.0, 0.0, 1.0 )\n    ~-1.0\n    > y = base.dists.gumbel.logcdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.gumbel.logcdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.logcdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.gumbel.logcdf( 0.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.gumbel.logcdf.factory( μ, β )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Gumbel distribution with location parameter\n    `μ` and scale parameter `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myLCDF = base.dists.gumbel.logcdf.factory( 2.0, 3.0 );\n    > var y = myLCDF( 10.0 )\n    ~-0.069\n    > y = myLCDF( 2.0 )\n    ~-1.0\n\n","base.dists.gumbel.logcdf.factory":"\nbase.dists.gumbel.logcdf.factory( μ, β )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Gumbel distribution with location parameter\n    `μ` and scale parameter `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myLCDF = base.dists.gumbel.logcdf.factory( 2.0, 3.0 );\n    > var y = myLCDF( 10.0 )\n    ~-0.069\n    > y = myLCDF( 2.0 )\n    ~-1.0","base.dists.gumbel.logpdf":"\nbase.dists.gumbel.logpdf( x, μ, β )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.logpdf( 0.0, 0.0, 2.0 )\n    ~-1.693\n    > y = base.dists.gumbel.logpdf( 0.0, 0.0, 1.0 )\n    ~-1\n    > y = base.dists.gumbel.logpdf( 1.0, 3.0, 2.0 )\n    ~-2.411\n    > y = base.dists.gumbel.logpdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.gumbel.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.logpdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.gumbel.logpdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.gumbel.logpdf.factory( μ, β )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Gumbel distribution with location parameter `μ` and\n    scale parameter `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.gumbel.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogpdf( 10.0 )\n    ~-1.693\n    > y = mylogpdf( 12.0 )\n    ~-2.061\n\n","base.dists.gumbel.logpdf.factory":"\nbase.dists.gumbel.logpdf.factory( μ, β )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Gumbel distribution with location parameter `μ` and\n    scale parameter `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.gumbel.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogpdf( 10.0 )\n    ~-1.693\n    > y = mylogpdf( 12.0 )\n    ~-2.061","base.dists.gumbel.mean":"\nbase.dists.gumbel.mean( μ, β )\n    Returns the expected value of a Gumbel distribution with location parameter\n    `μ` and scale parameter `β`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.mean( 0.0, 1.0 )\n    ~0.577\n    > y = base.dists.gumbel.mean( 4.0, 2.0 )\n    ~5.154\n    > y = base.dists.gumbel.mean( NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.mean( 0.0, NaN )\n    NaN\n    > y = base.dists.gumbel.mean( 0.0, 0.0 )\n    NaN\n\n","base.dists.gumbel.median":"\nbase.dists.gumbel.median( μ, β )\n    Returns the median of a Gumbel distribution with location parameter `μ` and\n    scale parameter `β`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.median( 0.0, 1.0 )\n    ~0.367\n    > y = base.dists.gumbel.median( 4.0, 2.0 )\n    ~4.733\n    > y = base.dists.gumbel.median( NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.median( 0.0, NaN )\n    NaN\n    > y = base.dists.gumbel.median( 0.0, 0.0 )\n    NaN\n\n","base.dists.gumbel.mgf":"\nbase.dists.gumbel.mgf( t, μ, β )\n    Evaluates the moment-generating function (MGF) for a Gumbel distribution\n    with location parameter `μ` and scale parameter `β` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.mgf( -1.0, 0.0, 3.0 )\n    6.0\n    > y = base.dists.gumbel.mgf( 0.0, 0.0, 1.0 )\n    1.0\n    > y = base.dists.gumbel.mgf( 0.1, 0.0, 3.0 )\n    ~1.298\n\n    > y = base.dists.gumbel.mgf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.gumbel.mgf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.mgf( 0.0, 0.0, NaN )\n    NaN\n\n    // Case: `t >= 1/beta`\n    > y = base.dists.gumbel.mgf( 0.8, 0.0, 2.0 )\n    NaN\n\n    // Non-positive scale parameter:\n    > y = base.dists.gumbel.mgf( 0.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.gumbel.mgf.factory( μ, β )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Gumbel distribution with location parameter `μ` and scale parameter `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.gumbel.mgf.factory( 0.0, 3.0 );\n    > var y = myMGF( -1.5 )\n    ~52.343\n    > y = myMGF( -1.0 )\n    6.0\n\n","base.dists.gumbel.mgf.factory":"\nbase.dists.gumbel.mgf.factory( μ, β )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Gumbel distribution with location parameter `μ` and scale parameter `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.gumbel.mgf.factory( 0.0, 3.0 );\n    > var y = myMGF( -1.5 )\n    ~52.343\n    > y = myMGF( -1.0 )\n    6.0","base.dists.gumbel.mode":"\nbase.dists.gumbel.mode( μ, β )\n    Returns the mode of a Gumbel distribution with location parameter `μ` and\n    scale parameter `β`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.mode( 0.0, 1.0 )\n    0.0\n    > y = base.dists.gumbel.mode( 4.0, 2.0 )\n    4.0\n    > y = base.dists.gumbel.mode( NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.mode( 0.0, NaN )\n    NaN\n    > y = base.dists.gumbel.mode( 0.0, 0.0 )\n    NaN\n\n","base.dists.gumbel.pdf":"\nbase.dists.gumbel.pdf( x, μ, β )\n    Evaluates the probability density function (PDF) for a Gumbel distribution\n    with location parameter `μ` and scale parameter `β` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.pdf( 0.0, 0.0, 2.0 )\n    ~0.184\n    > y = base.dists.gumbel.pdf( 0.0, 0.0, 1.0 )\n    ~0.368\n    > y = base.dists.gumbel.pdf( 1.0, 3.0, 2.0 )\n    ~0.09\n    > y = base.dists.gumbel.pdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.gumbel.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.pdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.gumbel.pdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.gumbel.pdf.factory( μ, β )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Gumbel distribution with location parameter `μ` and scale parameter\n    `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.gumbel.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    ~0.184\n    > y = myPDF( 12.0 )\n    ~0.127\n\n","base.dists.gumbel.pdf.factory":"\nbase.dists.gumbel.pdf.factory( μ, β )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Gumbel distribution with location parameter `μ` and scale parameter\n    `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.gumbel.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    ~0.184\n    > y = myPDF( 12.0 )\n    ~0.127","base.dists.gumbel.quantile":"\nbase.dists.gumbel.quantile( p, μ, β )\n    Evaluates the quantile function for a Gumbel distribution with location\n    parameter `μ` and scale parameter `β` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.quantile( 0.8, 0.0, 1.0 )\n    ~1.5\n    > y = base.dists.gumbel.quantile( 0.5, 4.0, 2.0 )\n    ~4.733\n    > y = base.dists.gumbel.quantile( 0.5, 4.0, 4.0 )\n    ~5.466\n\n    > y = base.dists.gumbel.quantile( 1.1, 0.0, 1.0 )\n    NaN\n    > y = base.dists.gumbel.quantile( -0.2, 0.0, 1.0 )\n    NaN\n\n    > y = base.dists.gumbel.quantile( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.gumbel.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.quantile( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.gumbel.quantile( 0.5, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.gumbel.quantile.factory( μ, β )\n    Returns a function for evaluating the quantile function of a Gumbel\n    distribution with location parameter `μ` and scale parameter `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.gumbel.quantile.factory( 8.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    ~8.733\n    > y = myQuantile( 0.7 )\n    ~10.062\n\n","base.dists.gumbel.quantile.factory":"\nbase.dists.gumbel.quantile.factory( μ, β )\n    Returns a function for evaluating the quantile function of a Gumbel\n    distribution with location parameter `μ` and scale parameter `β`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.gumbel.quantile.factory( 8.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    ~8.733\n    > y = myQuantile( 0.7 )\n    ~10.062","base.dists.gumbel.skewness":"\nbase.dists.gumbel.skewness( μ, β )\n    Returns the skewness of a Gumbel distribution with location parameter `μ`\n    and scale parameter `β`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.skewness( 0.0, 1.0 )\n    ~1.14\n    > y = base.dists.gumbel.skewness( 4.0, 2.0 )\n    ~1.14\n    > y = base.dists.gumbel.skewness( NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.skewness( 0.0, NaN )\n    NaN\n    > y = base.dists.gumbel.skewness( 0.0, 0.0 )\n    NaN\n\n","base.dists.gumbel.stdev":"\nbase.dists.gumbel.stdev( μ, β )\n    Returns the standard deviation of a Gumbel distribution with location\n    parameter `μ` and scale parameter `β`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.stdev( 0.0, 1.0 )\n    ~1.283\n    > y = base.dists.gumbel.stdev( 4.0, 2.0 )\n    ~2.565\n    > y = base.dists.gumbel.stdev( NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.stdev( 0.0, NaN )\n    NaN\n    > y = base.dists.gumbel.stdev( 0.0, 0.0 )\n    NaN\n\n","base.dists.gumbel.variance":"\nbase.dists.gumbel.variance( μ, β )\n    Returns the variance of a Gumbel distribution with location parameter `μ`\n    and scale parameter `β`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var y = base.dists.gumbel.variance( 0.0, 1.0 )\n    ~1.645\n    > y = base.dists.gumbel.variance( 4.0, 2.0 )\n    ~6.58\n    > y = base.dists.gumbel.variance( NaN, 1.0 )\n    NaN\n    > y = base.dists.gumbel.variance( 0.0, NaN )\n    NaN\n    > y = base.dists.gumbel.variance( 0.0, 0.0 )\n    NaN\n\n","base.dists.hypergeometric.cdf":"\nbase.dists.hypergeometric.cdf( x, N, K, n )\n    Evaluates the cumulative distribution function (CDF) for a hypergeometric\n    distribution with population size `N`, subpopulation size `K`, and number of\n    draws `n` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a population size `N`, subpopulation size `K` or draws `n` which\n    is not a nonnegative integer, the function returns `NaN`.\n\n    If the number of draws `n` or subpopulation size `K` exceeds population size\n     `N`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.hypergeometric.cdf( 1.0, 8, 4, 2 )\n    ~0.786\n    > y = base.dists.hypergeometric.cdf( 1.5, 8, 4, 2 )\n    ~0.786\n    > y = base.dists.hypergeometric.cdf( 2.0, 8, 4, 2 )\n    1.0\n    > y = base.dists.hypergeometric.cdf( 0, 8, 4, 2)\n    ~0.214\n\n    > y = base.dists.hypergeometric.cdf( NaN, 10, 5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.cdf( 0.0, NaN, 5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.cdf( 0.0, 10, NaN, 2 )\n    NaN\n    > y = base.dists.hypergeometric.cdf( 0.0, 10, 5, NaN )\n    NaN\n\n    > y = base.dists.hypergeometric.cdf( 2.0, 10.5, 5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.cdf( 2.0, 10, 1.5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.cdf( 2.0, 10, 5, -2.0 )\n    NaN\n    > y = base.dists.hypergeometric.cdf( 2.0, 10, 5, 12 )\n    NaN\n    > y = base.dists.hypergeometric.cdf( 2.0, 8, 3, 9 )\n    NaN\n\n\nbase.dists.hypergeometric.cdf.factory( N, K, n )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a hypergeometric distribution with population size `N`, subpopulation\n    size `K`, and number of draws `n`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.hypergeometric.cdf.factory( 30, 20, 5 );\n    > var y = myCDF( 4.0 )\n    ~0.891\n    > y = myCDF( 1.0 )\n    ~0.031\n\n","base.dists.hypergeometric.cdf.factory":"\nbase.dists.hypergeometric.cdf.factory( N, K, n )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a hypergeometric distribution with population size `N`, subpopulation\n    size `K`, and number of draws `n`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.hypergeometric.cdf.factory( 30, 20, 5 );\n    > var y = myCDF( 4.0 )\n    ~0.891\n    > y = myCDF( 1.0 )\n    ~0.031","base.dists.hypergeometric.Hypergeometric":"\nbase.dists.hypergeometric.Hypergeometric( [N, K, n] )\n    Returns a hypergeometric distribution object.\n\n    Parameters\n    ----------\n    N: integer (optional)\n        Population size. Must be a nonnegative integer larger than or equal to\n        `K` and `n`.\n\n    K: integer (optional)\n        Subpopulation size. Must be a nonnegative integer smaller than or equal\n        to `N`.\n\n    n: integer (optional)\n        Number of draws. Must be a nonnegative integer smaller than or equal to\n        `N`.\n\n    Returns\n    -------\n    hypergeometric: Object\n        Distribution instance.\n\n    hypergeometric.N: number\n        Population size. If set, the value must be a nonnegative integer larger\n        than or equal to `K` and `n`.\n\n    hypergeometric.K: number\n        Subpopulation size. If set, the value must be a nonnegative integer\n        smaller than or equal to `N`.\n\n    hypergeometric.n: number\n        Number of draws. If set, the value must be a nonnegative integer\n        smaller than or equal to `N`.\n\n    hypergeometric.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    hypergeometric.mean: number\n        Read-only property which returns the expected value.\n\n    hypergeometric.mode: number\n        Read-only property which returns the mode.\n\n    hypergeometric.skewness: number\n        Read-only property which returns the skewness.\n\n    hypergeometric.stdev: number\n        Read-only property which returns the standard deviation.\n\n    hypergeometric.variance: number\n        Read-only property which returns the variance.\n\n    hypergeometric.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    hypergeometric.logpmf: Function\n        Evaluates the natural logarithm of the probability mass function (PMF).\n\n    hypergeometric.pmf: Function\n        Evaluates the probability mass function (PMF).\n\n    hypergeometric.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var hypergeometric = base.dists.hypergeometric.Hypergeometric( 100, 70, 20 );\n    > hypergeometric.N\n    100.0\n    > hypergeometric.K\n    70.0\n    > hypergeometric.n\n    20.0\n    > hypergeometric.kurtosis\n    ~-0.063\n    > hypergeometric.mean\n    14.0\n    > hypergeometric.mode\n    14.0\n    > hypergeometric.skewness\n    ~-0.133\n    > hypergeometric.stdev\n    ~1.842\n    > hypergeometric.variance\n    ~3.394\n    > hypergeometric.cdf( 2.9 )\n    ~0.0\n    > hypergeometric.logpmf( 10 )\n    ~-3.806\n    > hypergeometric.pmf( 10 )\n    ~0.022\n    > hypergeometric.quantile( 0.8 )\n    16.0\n\n","base.dists.hypergeometric.kurtosis":"\nbase.dists.hypergeometric.kurtosis( N, K, n )\n    Returns the excess kurtosis of a hypergeometric distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a population size `N`, subpopulation size `K` or draws `n` which\n    is not a nonnegative integer, the function returns `NaN`.\n\n    If the number of draws `n` or subpopulation size `K` exceed population size\n    `N`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.hypergeometric.kurtosis( 16, 11, 4 )\n    ~-0.326\n    > v = base.dists.hypergeometric.kurtosis( 4, 2, 2 )\n    0.0\n\n    > v = base.dists.hypergeometric.kurtosis( 10, 5, 12 )\n    NaN\n    > v = base.dists.hypergeometric.kurtosis( 10.3, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.kurtosis( 10, 5.5, 4 )\n    NaN\n    > v = base.dists.hypergeometric.kurtosis( 10, 5, 4.5 )\n    NaN\n\n    > v = base.dists.hypergeometric.kurtosis( NaN, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.kurtosis( 20, NaN, 4 )\n    NaN\n    > v = base.dists.hypergeometric.kurtosis( 20, 10, NaN )\n    NaN\n\n","base.dists.hypergeometric.logpmf":"\nbase.dists.hypergeometric.logpmf( x, N, K, n )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    hypergeometric distribution with population size `N`, subpopulation size\n    `K`, and number of draws `n` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a population size `N`, subpopulation size `K`, or draws `n`\n    which is not a nonnegative integer, the function returns `NaN`.\n\n    If the number of draws `n` or the subpopulation size `K` exceed population\n    size `N`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPMF.\n\n    Examples\n    --------\n    > var y = base.dists.hypergeometric.logpmf( 1.0, 8, 4, 2 )\n    ~-0.56\n    > y = base.dists.hypergeometric.logpmf( 2.0, 8, 4, 2 )\n    ~-1.54\n    > y = base.dists.hypergeometric.logpmf( 0.0, 8, 4, 2 )\n    ~-1.54\n    > y = base.dists.hypergeometric.logpmf( 1.5, 8, 4, 2 )\n    -Infinity\n\n    > y = base.dists.hypergeometric.logpmf( NaN, 10, 5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.logpmf( 0.0, NaN, 5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.logpmf( 0.0, 10, NaN, 2 )\n    NaN\n    > y = base.dists.hypergeometric.logpmf( 0.0, 10, 5, NaN )\n    NaN\n\n    > y = base.dists.hypergeometric.logpmf( 2.0, 10.5, 5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.logpmf( 2.0, 5, 1.5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.logpmf( 2.0, 10, 5, -2.0 )\n    NaN\n    > y = base.dists.hypergeometric.logpmf( 2.0, 10, 5, 12 )\n    NaN\n    > y = base.dists.hypergeometric.logpmf( 2.0, 8, 3, 9 )\n    NaN\n\n\nbase.dists.hypergeometric.logpmf.factory( N, K, n )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a hypergeometric distribution with population size\n    `N`, subpopulation size `K`, and number of draws `n`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogPMF = base.dists.hypergeometric.logpmf.factory( 30, 20, 5 );\n    > var y = mylogPMF( 4.0 )\n    ~-1.079\n    > y = mylogPMF( 1.0 )\n    ~-3.524\n\n","base.dists.hypergeometric.logpmf.factory":"\nbase.dists.hypergeometric.logpmf.factory( N, K, n )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a hypergeometric distribution with population size\n    `N`, subpopulation size `K`, and number of draws `n`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogPMF = base.dists.hypergeometric.logpmf.factory( 30, 20, 5 );\n    > var y = mylogPMF( 4.0 )\n    ~-1.079\n    > y = mylogPMF( 1.0 )\n    ~-3.524","base.dists.hypergeometric.mean":"\nbase.dists.hypergeometric.mean( N, K, n )\n    Returns the expected value of a hypergeometric distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a population size `N`, subpopulation size `K` or draws `n` which\n    is not a nonnegative integer, the function returns `NaN`.\n\n    If the number of draws `n` or the subpopulation size `K` exceed population\n    size `N`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.hypergeometric.mean( 16, 11, 4 )\n    2.75\n    > v = base.dists.hypergeometric.mean( 2, 1, 1 )\n    0.5\n\n    > v = base.dists.hypergeometric.mean( 10, 5, 12 )\n    NaN\n    > v = base.dists.hypergeometric.mean( 10.3, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.mean( 10, 5.5, 4 )\n    NaN\n    > v = base.dists.hypergeometric.mean( 10, 5, 4.5 )\n    NaN\n\n    > v = base.dists.hypergeometric.mean( NaN, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.mean( 20, NaN, 4 )\n    NaN\n    > v = base.dists.hypergeometric.mean( 20, 10, NaN )\n    NaN\n\n","base.dists.hypergeometric.mode":"\nbase.dists.hypergeometric.mode( N, K, n )\n    Returns the mode of a hypergeometric distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a population size `N`, subpopulation size `K` or draws `n` which\n    is not a nonnegative integer, the function returns `NaN`.\n\n    If the number of draws `n` or the subpopulation size `K` exceed population\n    size `N`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.hypergeometric.mode( 16, 11, 4 )\n    3\n    > v = base.dists.hypergeometric.mode( 2, 1, 1 )\n    1\n\n    > v = base.dists.hypergeometric.mode( 10, 5, 12 )\n    NaN\n    > v = base.dists.hypergeometric.mode( 10.3, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.mode( 10, 5.5, 4 )\n    NaN\n    > v = base.dists.hypergeometric.mode( 10, 5, 4.5 )\n    NaN\n\n    > v = base.dists.hypergeometric.mode( NaN, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.mode( 20, NaN, 4 )\n    NaN\n    > v = base.dists.hypergeometric.mode( 20, 10, NaN )\n    NaN\n\n","base.dists.hypergeometric.pmf":"\nbase.dists.hypergeometric.pmf( x, N, K, n )\n    Evaluates the probability mass function (PMF) for a hypergeometric\n    distribution with population size `N`, subpopulation size `K`, and number of\n    draws `n` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a population size `N`, subpopulation size `K` or draws `n` which\n    is not a nonnegative integer, the function returns `NaN`.\n\n    If the number of draws `n` or the subpopulation size `K` exceed population\n    size `N`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    out: number\n        Evaluated PMF.\n\n    Examples\n    --------\n    > var y = base.dists.hypergeometric.pmf( 1.0, 8, 4, 2 )\n    ~0.571\n    > y = base.dists.hypergeometric.pmf( 2.0, 8, 4, 2 )\n    ~0.214\n    > y = base.dists.hypergeometric.pmf( 0.0, 8, 4, 2 )\n    ~0.214\n    > y = base.dists.hypergeometric.pmf( 1.5, 8, 4, 2 )\n    0.0\n\n    > y = base.dists.hypergeometric.pmf( NaN, 10, 5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.pmf( 0.0, NaN, 5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.pmf( 0.0, 10, NaN, 2 )\n    NaN\n    > y = base.dists.hypergeometric.pmf( 0.0, 10, 5, NaN )\n    NaN\n\n    > y = base.dists.hypergeometric.pmf( 2.0, 10.5, 5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.pmf( 2.0, 5, 1.5, 2 )\n    NaN\n    > y = base.dists.hypergeometric.pmf( 2.0, 10, 5, -2.0 )\n    NaN\n    > y = base.dists.hypergeometric.pmf( 2.0, 10, 5, 12 )\n    NaN\n    > y = base.dists.hypergeometric.pmf( 2.0, 8, 3, 9 )\n    NaN\n\n\nbase.dists.hypergeometric.pmf.factory( N, K, n )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    hypergeometric distribution with population size `N`, subpopulation size\n    `K`, and number of draws `n`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var myPMF = base.dists.hypergeometric.pmf.factory( 30, 20, 5 );\n    > var y = myPMF( 4.0 )\n    ~0.34\n    > y = myPMF( 1.0 )\n    ~0.029\n\n","base.dists.hypergeometric.pmf.factory":"\nbase.dists.hypergeometric.pmf.factory( N, K, n )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    hypergeometric distribution with population size `N`, subpopulation size\n    `K`, and number of draws `n`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var myPMF = base.dists.hypergeometric.pmf.factory( 30, 20, 5 );\n    > var y = myPMF( 4.0 )\n    ~0.34\n    > y = myPMF( 1.0 )\n    ~0.029","base.dists.hypergeometric.quantile":"\nbase.dists.hypergeometric.quantile( p, N, K, n )\n    Evaluates the quantile function for a hypergeometric distribution with\n    population size `N`, subpopulation size `K`, and number of draws `n` at a\n    probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a population size `N`, subpopulation size `K` or draws `n` which\n    is not a nonnegative integer, the function returns `NaN`.\n\n    If the number of draws `n` or the subpopulation size `K` exceed population\n    size `N`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.hypergeometric.quantile( 0.4, 40, 20, 10 )\n    5\n    > y = base.dists.hypergeometric.quantile( 0.8, 60, 40, 20 )\n    15\n    > y = base.dists.hypergeometric.quantile( 0.5, 100, 10, 10 )\n    1\n    > y = base.dists.hypergeometric.quantile( 0.0, 100, 40, 20 )\n    0\n    > y = base.dists.hypergeometric.quantile( 1.0, 100, 40, 20 )\n    20\n\n    > y = base.dists.hypergeometric.quantile( NaN, 40, 20, 10 )\n    NaN\n    > y = base.dists.hypergeometric.quantile( 0.2, NaN, 20, 10 )\n    NaN\n    > y = base.dists.hypergeometric.quantile( 0.2, 40, NaN, 10 )\n    NaN\n    > y = base.dists.hypergeometric.quantile( 0.2, 40, 20, NaN )\n    NaN\n\n\nbase.dists.hypergeometric.quantile.factory( N, K, n )\n    Returns a function for evaluating the quantile function of a hypergeometric\n    distribution with population size `N`, subpopulation size `K`, and number of\n    draws `n`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.hypergeometric.quantile.factory( 100, 20, 10 );\n    > var y = myQuantile( 0.2 )\n    1\n    > y = myQuantile( 0.9 )\n    4\n\n","base.dists.hypergeometric.quantile.factory":"\nbase.dists.hypergeometric.quantile.factory( N, K, n )\n    Returns a function for evaluating the quantile function of a hypergeometric\n    distribution with population size `N`, subpopulation size `K`, and number of\n    draws `n`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.hypergeometric.quantile.factory( 100, 20, 10 );\n    > var y = myQuantile( 0.2 )\n    1\n    > y = myQuantile( 0.9 )\n    4","base.dists.hypergeometric.skewness":"\nbase.dists.hypergeometric.skewness( N, K, n )\n    Returns the skewness of a hypergeometric distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a population size `N`, subpopulation size `K` or draws `n` which\n    is not a nonnegative integer, the function returns `NaN`.\n\n    If the number of draws `n` or the subpopulation size `K` exceed population\n    size `N`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.hypergeometric.skewness( 16, 11, 4 )\n    ~-0.258\n    > v = base.dists.hypergeometric.skewness( 4, 2, 2 )\n    0.0\n\n    > v = base.dists.hypergeometric.skewness( 10, 5, 12 )\n    NaN\n    > v = base.dists.hypergeometric.skewness( 10.3, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.skewness( 10, 5.5, 4 )\n    NaN\n    > v = base.dists.hypergeometric.skewness( 10, 5, 4.5 )\n    NaN\n\n    > v = base.dists.hypergeometric.skewness( NaN, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.skewness( 20, NaN, 4 )\n    NaN\n    > v = base.dists.hypergeometric.skewness( 20, 10, NaN )\n    NaN\n\n","base.dists.hypergeometric.stdev":"\nbase.dists.hypergeometric.stdev( N, K, n )\n    Returns the standard deviation of a hypergeometric distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a population size `N`, subpopulation size `K` or draws `n` which\n    is not a nonnegative integer, the function returns `NaN`.\n\n    If the number of draws `n` or the subpopulation size `K` exceed population\n    size `N`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.hypergeometric.stdev( 16, 11, 4 )\n    ~0.829\n    > v = base.dists.hypergeometric.stdev( 2, 1, 1 )\n    0.5\n\n    > v = base.dists.hypergeometric.stdev( 10, 5, 12 )\n    NaN\n    > v = base.dists.hypergeometric.stdev( 10.3, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.stdev( 10, 5.5, 4 )\n    NaN\n    > v = base.dists.hypergeometric.stdev( 10, 5, 4.5 )\n    NaN\n\n    > v = base.dists.hypergeometric.stdev( NaN, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.stdev( 20, NaN, 4 )\n    NaN\n    > v = base.dists.hypergeometric.stdev( 20, 10, NaN )\n    NaN\n\n","base.dists.hypergeometric.variance":"\nbase.dists.hypergeometric.variance( N, K, n )\n    Returns the variance of a hypergeometric distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a population size `N`, subpopulation size `K` or draws `n` which\n    is not a nonnegative integer, the function returns `NaN`.\n\n    If the number of draws `n` or the subpopulation size `K` exceed population\n    size `N`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.hypergeometric.variance( 16, 11, 4 )\n    ~0.688\n    > v = base.dists.hypergeometric.variance( 2, 1, 1 )\n    0.25\n\n    > v = base.dists.hypergeometric.variance( 10, 5, 12 )\n    NaN\n    > v = base.dists.hypergeometric.variance( 10.3, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.variance( 10, 5.5, 4 )\n    NaN\n    > v = base.dists.hypergeometric.variance( 10, 5, 4.5 )\n    NaN\n\n    > v = base.dists.hypergeometric.variance( NaN, 10, 4 )\n    NaN\n    > v = base.dists.hypergeometric.variance( 20, NaN, 4 )\n    NaN\n    > v = base.dists.hypergeometric.variance( 20, 10, NaN )\n    NaN\n\n","base.dists.invgamma.cdf":"\nbase.dists.invgamma.cdf( x, α, β )\n    Evaluates the cumulative distribution function (CDF) for an inverse gamma\n    distribution with shape parameter `α` and scale parameter `β` at a value\n    `x`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.invgamma.cdf( 2.0, 1.0, 1.0 )\n    ~0.607\n    > y = base.dists.invgamma.cdf( 2.0, 3.0, 1.0 )\n    ~0.986\n    > y = base.dists.invgamma.cdf( -1.0, 2.0, 2.0 )\n    0.0\n    > y = base.dists.invgamma.cdf( PINF, 4.0, 2.0 )\n    1.0\n    > y = base.dists.invgamma.cdf( NINF, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.invgamma.cdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.invgamma.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.invgamma.cdf( 0.0, 0.0, NaN )\n    NaN\n\n    > y = base.dists.invgamma.cdf( 2.0, -1.0, 1.0 )\n    NaN\n    > y = base.dists.invgamma.cdf( 2.0, 1.0, -1.0 )\n    NaN\n\n\nbase.dists.invgamma.cdf.factory( α, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an inverse gamma distribution with shape parameter `α` and scale\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.invgamma.cdf.factory( 2.0, 0.5 );\n    > var y = myCDF( 0.5 )\n    ~0.736\n    > y = myCDF( 2.0 )\n    ~0.974\n\n","base.dists.invgamma.cdf.factory":"\nbase.dists.invgamma.cdf.factory( α, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an inverse gamma distribution with shape parameter `α` and scale\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.invgamma.cdf.factory( 2.0, 0.5 );\n    > var y = myCDF( 0.5 )\n    ~0.736\n    > y = myCDF( 2.0 )\n    ~0.974","base.dists.invgamma.entropy":"\nbase.dists.invgamma.entropy( α, β )\n    Returns the differential entropy of an inverse gamma distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.invgamma.entropy( 1.0, 1.0 )\n    ~2.154\n    > v = base.dists.invgamma.entropy( 4.0, 12.0 )\n    ~1.996\n    > v = base.dists.invgamma.entropy( 8.0, 2.0 )\n    ~-0.922\n\n","base.dists.invgamma.InvGamma":"\nbase.dists.invgamma.InvGamma( [α, β] )\n    Returns an inverse gamma distribution object.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n    β: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    invgamma: Object\n        Distribution instance.\n\n    invgamma.alpha: number\n        Shape parameter. If set, the value must be greater than `0`.\n\n    invgamma.beta: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    invgamma.entropy: number\n        Read-only property which returns the differential entropy.\n\n    invgamma.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    invgamma.mean: number\n        Read-only property which returns the expected value.\n\n    invgamma.mode: number\n        Read-only property which returns the mode.\n\n    invgamma.skewness: number\n        Read-only property which returns the skewness.\n\n    invgamma.stdev: number\n        Read-only property which returns the standard deviation.\n\n    invgamma.variance: number\n        Read-only property which returns the variance.\n\n    invgamma.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    invgamma.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    invgamma.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    invgamma.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var invgamma = base.dists.invgamma.InvGamma( 6.0, 5.0 );\n    > invgamma.alpha\n    6.0\n    > invgamma.beta\n    5.0\n    > invgamma.entropy\n    ~0.454\n    > invgamma.kurtosis\n    19.0\n    > invgamma.mean\n    1.0\n    > invgamma.mode\n    ~0.714\n    > invgamma.skewness\n    ~2.667\n    > invgamma.stdev\n    0.5\n    > invgamma.variance\n    0.25\n    > invgamma.cdf( 0.8 )\n    ~0.406\n    > invgamma.pdf( 1.0 )\n    ~0.877\n    > invgamma.logpdf( 1.0 )\n    ~-0.131\n    > invgamma.quantile( 0.8 )\n    ~1.281\n\n","base.dists.invgamma.kurtosis":"\nbase.dists.invgamma.kurtosis( α, β )\n    Returns the excess kurtosis of an inverse gamma distribution.\n\n    If `α <= 4` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.invgamma.kurtosis( 7.0, 5.0 )\n    12.0\n    > v = base.dists.invgamma.kurtosis( 6.0, 12.0 )\n    19.0\n    > v = base.dists.invgamma.kurtosis( 8.0, 2.0 )\n    ~8.7\n\n","base.dists.invgamma.logpdf":"\nbase.dists.invgamma.logpdf( x, α, β )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for an inverse gamma distribution with shape parameter `α` and scale\n    parameter `β` at a value `x`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.invgamma.logpdf( 2.0, 0.5, 1.0 )\n    ~-2.112\n    > y = base.dists.invgamma.logpdf( 0.2, 1.0, 1.0 )\n    ~-1.781\n    > y = base.dists.invgamma.logpdf( -1.0, 4.0, 2.0 )\n    -Infinity\n\n    > y = base.dists.invgamma.logpdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.invgamma.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.invgamma.logpdf( 0.0, 1.0, NaN )\n    NaN\n\n    // Negative shape parameter:\n    > y = base.dists.invgamma.logpdf( 2.0, -1.0, 1.0 )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.invgamma.logpdf( 2.0, 1.0, -1.0 )\n    NaN\n\n\nbase.dists.invgamma.logpdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) for an inverse gamma distribution with shape\n    parameter `α` and scale parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.invgamma.logpdf.factory( 6.0, 7.0 );\n    > var y = mylogPDF( 2.0 )\n    ~-1.464\n\n","base.dists.invgamma.logpdf.factory":"\nbase.dists.invgamma.logpdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) for an inverse gamma distribution with shape\n    parameter `α` and scale parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.invgamma.logpdf.factory( 6.0, 7.0 );\n    > var y = mylogPDF( 2.0 )\n    ~-1.464","base.dists.invgamma.mean":"\nbase.dists.invgamma.mean( α, β )\n    Returns the expected value of an inverse gamma distribution.\n\n    If `α <= 1` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.invgamma.mean( 4.0, 12.0 )\n    4.0\n    > v = base.dists.invgamma.mean( 8.0, 2.0 )\n    ~0.286\n\n","base.dists.invgamma.mode":"\nbase.dists.invgamma.mode( α, β )\n    Returns the mode of an inverse gamma distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.invgamma.mode( 1.0, 1.0 )\n    0.5\n    > v = base.dists.invgamma.mode( 4.0, 12.0 )\n    2.4\n    > v = base.dists.invgamma.mode( 8.0, 2.0 )\n    ~0.222\n\n","base.dists.invgamma.pdf":"\nbase.dists.invgamma.pdf( x, α, β )\n    Evaluates the probability density function (PDF) for an inverse gamma\n    distribution with shape parameter `α` and scale parameter `β` at a value\n    `x`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.invgamma.pdf( 2.0, 0.5, 1.0 )\n    ~0.121\n    > y = base.dists.invgamma.pdf( 0.2, 1.0, 1.0 )\n    ~0.168\n    > y = base.dists.invgamma.pdf( -1.0, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.invgamma.pdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.invgamma.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.invgamma.pdf( 0.0, 1.0, NaN )\n    NaN\n\n    // Negative shape parameter:\n    > y = base.dists.invgamma.pdf( 2.0, -1.0, 1.0 )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.invgamma.pdf( 2.0, 1.0, -1.0 )\n    NaN\n\n\nbase.dists.invgamma.pdf.factory( α, β )\n    Returns a function for evaluating the probability density function (PDF)\n    of an inverse gamma distribution with shape parameter `α` and scale\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.invgamma.pdf.factory( 6.0, 7.0 );\n    > var y = myPDF( 2.0 )\n    ~0.231\n\n","base.dists.invgamma.pdf.factory":"\nbase.dists.invgamma.pdf.factory( α, β )\n    Returns a function for evaluating the probability density function (PDF)\n    of an inverse gamma distribution with shape parameter `α` and scale\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.invgamma.pdf.factory( 6.0, 7.0 );\n    > var y = myPDF( 2.0 )\n    ~0.231","base.dists.invgamma.quantile":"\nbase.dists.invgamma.quantile( p, α, β )\n    Evaluates the quantile function for an inverse gamma distribution with shape\n    parameter `α` and scale parameter `β` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.invgamma.quantile( 0.8, 2.0, 1.0 )\n    ~1.213\n    > y = base.dists.invgamma.quantile( 0.5, 4.0, 2.0 )\n    ~0.545\n    > y = base.dists.invgamma.quantile( 1.1, 1.0, 1.0 )\n    NaN\n    > y = base.dists.invgamma.quantile( -0.2, 1.0, 1.0 )\n    NaN\n\n    > y = base.dists.invgamma.quantile( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.invgamma.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.invgamma.quantile( 0.0, 1.0, NaN )\n    NaN\n\n    // Non-positive shape parameter:\n    > y = base.dists.invgamma.quantile( 0.5, -1.0, 1.0 )\n    NaN\n\n    // Non-positive rate parameter:\n    > y = base.dists.invgamma.quantile( 0.5, 1.0, -1.0 )\n    NaN\n\n\nbase.dists.invgamma.quantile.factory( α, β )\n    Returns a function for evaluating the quantile function of an inverse gamma\n    distribution with shape parameter `α` and scale parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.invgamma.quantile.factory( 2.0, 2.0 );\n    > var y = myQuantile( 0.8 )\n    ~2.426\n    > y = myQuantile( 0.4 )\n    ~0.989\n\n","base.dists.invgamma.quantile.factory":"\nbase.dists.invgamma.quantile.factory( α, β )\n    Returns a function for evaluating the quantile function of an inverse gamma\n    distribution with shape parameter `α` and scale parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.invgamma.quantile.factory( 2.0, 2.0 );\n    > var y = myQuantile( 0.8 )\n    ~2.426\n    > y = myQuantile( 0.4 )\n    ~0.989","base.dists.invgamma.skewness":"\nbase.dists.invgamma.skewness( α, β )\n    Returns the skewness of an inverse gamma distribution.\n\n    If `α <= 3` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.invgamma.skewness( 4.0, 12.0 )\n    ~5.657\n    > v = base.dists.invgamma.skewness( 8.0, 2.0 )\n    ~1.96\n\n","base.dists.invgamma.stdev":"\nbase.dists.invgamma.stdev( α, β )\n    Returns the standard deviation of an inverse gamma distribution.\n\n    If `α <= 2` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.invgamma.stdev( 5.0, 7.0 )\n    ~1.01\n    > v = base.dists.invgamma.stdev( 4.0, 12.0 )\n    ~2.828\n    > v = base.dists.invgamma.stdev( 8.0, 2.0 )\n    ~0.117\n\n","base.dists.invgamma.variance":"\nbase.dists.invgamma.variance( α, β )\n    Returns the variance of an inverse gamma distribution.\n\n    If `α <= 2` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.invgamma.variance( 5.0, 7.0 )\n    ~1.021\n    > v = base.dists.invgamma.variance( 4.0, 12.0 )\n    8.0\n    > v = base.dists.invgamma.variance( 8.0, 2.0 )\n    ~0.014\n\n","base.dists.kumaraswamy.cdf":"\nbase.dists.kumaraswamy.cdf( x, a, b )\n    Evaluates the cumulative distribution function (CDF) for Kumaraswamy's\n    double bounded distribution with first shape parameter `a` and second shape\n    parameter `b` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.kumaraswamy.cdf( 0.5, 1.0, 1.0 )\n    ~0.5\n    > y = base.dists.kumaraswamy.cdf( 0.5, 2.0, 4.0 )\n    ~0.684\n    > y = base.dists.kumaraswamy.cdf( 0.2, 2.0, 2.0 )\n    ~0.078\n    > y = base.dists.kumaraswamy.cdf( 0.8, 4.0, 4.0 )\n    ~0.878\n    > y = base.dists.kumaraswamy.cdf( -0.5, 4.0, 2.0 )\n    0.0\n    > y = base.dists.kumaraswamy.cdf( 1.5, 4.0, 2.0 )\n    1.0\n\n    > y = base.dists.kumaraswamy.cdf( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.kumaraswamy.cdf( 2.0, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.kumaraswamy.cdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.kumaraswamy.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.kumaraswamy.cdf( 0.0, 1.0, NaN )\n    NaN\n\n\nbase.dists.kumaraswamy.cdf.factory( a, b )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Kumaraswamy's double bounded distribution with first shape parameter\n    `a` and second shape parameter `b`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.kumaraswamy.cdf.factory( 0.5, 1.0 );\n    > var y = mycdf( 0.8 )\n    ~0.894\n    > y = mycdf( 0.3 )\n    ~0.548\n\n","base.dists.kumaraswamy.cdf.factory":"\nbase.dists.kumaraswamy.cdf.factory( a, b )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Kumaraswamy's double bounded distribution with first shape parameter\n    `a` and second shape parameter `b`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.kumaraswamy.cdf.factory( 0.5, 1.0 );\n    > var y = mycdf( 0.8 )\n    ~0.894\n    > y = mycdf( 0.3 )\n    ~0.548","base.dists.kumaraswamy.Kumaraswamy":"\nbase.dists.kumaraswamy.Kumaraswamy( [a, b] )\n    Returns a Kumaraswamy's double bounded distribution object.\n\n    Parameters\n    ----------\n    a: number (optional)\n        First shape parameter. Must be greater than `0`. Default: `1.0`.\n\n    b: number (optional)\n        Second shape parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    kumaraswamy: Object\n        Distribution instance.\n\n    kumaraswamy.a: number\n        First shape parameter. If set, the value must be greater than `0`.\n\n    kumaraswamy.b: number\n        Second shape parameter. If set, the value must be greater than `0`.\n\n    kumaraswamy.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    kumaraswamy.mean: number\n        Read-only property which returns the expected value.\n\n    kumaraswamy.mode: number\n        Read-only property which returns the mode.\n\n    kumaraswamy.skewness: number\n        Read-only property which returns the skewness.\n\n    kumaraswamy.stdev: number\n        Read-only property which returns the standard deviation.\n\n    kumaraswamy.variance: number\n        Read-only property which returns the variance.\n\n    kumaraswamy.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    kumaraswamy.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    kumaraswamy.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var kumaraswamy = base.dists.kumaraswamy.Kumaraswamy( 6.0, 5.0 );\n    > kumaraswamy.a\n    6.0\n    > kumaraswamy.b\n    5.0\n    > kumaraswamy.kurtosis\n    ~3.194\n    > kumaraswamy.mean\n    ~0.696\n    > kumaraswamy.mode\n    ~0.746\n    > kumaraswamy.skewness\n    ~-0.605\n    > kumaraswamy.stdev\n    ~0.126\n    > kumaraswamy.variance\n    ~0.016\n    > kumaraswamy.cdf( 0.8 )\n    ~0.781\n    > kumaraswamy.pdf( 1.0 )\n    ~0.0\n    > kumaraswamy.quantile( 0.8 )\n    ~0.807\n\n","base.dists.kumaraswamy.kurtosis":"\nbase.dists.kumaraswamy.kurtosis( a, b )\n    Returns the excess kurtosis of a Kumaraswamy's double bounded distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.kumaraswamy.kurtosis( 1.0, 1.0 )\n    ~1.8\n    > v = base.dists.kumaraswamy.kurtosis( 4.0, 12.0 )\n    ~2.704\n    > v = base.dists.kumaraswamy.kurtosis( 16.0, 8.0 )\n    ~4.311\n\n","base.dists.kumaraswamy.logcdf":"\nbase.dists.kumaraswamy.logcdf( x, a, b )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for Kumaraswamy's double bounded distribution with first shape\n    parameter `a` and second shape parameter `b` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.kumaraswamy.logcdf( 0.5, 1.0, 1.0 )\n    ~-0.693\n    > y = base.dists.kumaraswamy.logcdf( 0.5, 2.0, 4.0 )\n    ~-0.38\n    > y = base.dists.kumaraswamy.logcdf( 0.2, 2.0, 2.0 )\n    ~-2.546\n    > y = base.dists.kumaraswamy.logcdf( 0.8, 4.0, 4.0 )\n    ~-0.13\n    > y = base.dists.kumaraswamy.logcdf( -0.5, 4.0, 2.0 )\n    -Infinity\n    > y = base.dists.kumaraswamy.logcdf( 1.5, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.kumaraswamy.logcdf( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.kumaraswamy.logcdf( 2.0, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.kumaraswamy.logcdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.kumaraswamy.logcdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.kumaraswamy.logcdf( 0.0, 1.0, NaN )\n    NaN\n\n\nbase.dists.kumaraswamy.logcdf.factory( a, b )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Kumaraswamy's double bounded distribution\n    with first shape parameter `a` and second shape parameter `b`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.kumaraswamy.logcdf.factory( 0.5, 1.0 );\n    > var y = mylogcdf( 0.8 )\n    ~-0.112\n    > y = mylogcdf( 0.3 )\n    ~-0.602\n\n","base.dists.kumaraswamy.logcdf.factory":"\nbase.dists.kumaraswamy.logcdf.factory( a, b )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Kumaraswamy's double bounded distribution\n    with first shape parameter `a` and second shape parameter `b`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.kumaraswamy.logcdf.factory( 0.5, 1.0 );\n    > var y = mylogcdf( 0.8 )\n    ~-0.112\n    > y = mylogcdf( 0.3 )\n    ~-0.602","base.dists.kumaraswamy.logpdf":"\nbase.dists.kumaraswamy.logpdf( x, a, b )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for Kumaraswamy's double bounded distribution with first shape parameter `a`\n    and second shape parameter `b` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.kumaraswamy.logpdf( 0.5, 1.0, 1.0 )\n    0.0\n    > y = base.dists.kumaraswamy.logpdf( 0.5, 2.0, 4.0 )\n    ~0.523\n    > y = base.dists.kumaraswamy.logpdf( 0.2, 2.0, 2.0 )\n    ~-0.264\n    > y = base.dists.kumaraswamy.logpdf( 0.8, 4.0, 4.0 )\n    ~0.522\n    > y = base.dists.kumaraswamy.logpdf( -0.5, 4.0, 2.0 )\n    -Infinity\n    > y = base.dists.kumaraswamy.logpdf( 1.5, 4.0, 2.0 )\n    -Infinity\n\n    > y = base.dists.kumaraswamy.logpdf( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.kumaraswamy.logpdf( 2.0, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.kumaraswamy.logpdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.kumaraswamy.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.kumaraswamy.logpdf( 0.0, 1.0, NaN )\n    NaN\n\n\nbase.dists.kumaraswamy.logpdf.factory( a, b )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a Kumaraswamy's double bounded distribution with\n    first shape parameter `a` and second shape parameter `b`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.kumaraswamy.logpdf.factory( 0.5, 1.0 );\n    > var y = mylogpdf( 0.8 )\n    ~-0.582\n    > y = mylogpdf( 0.3 )\n    ~-0.091\n\n","base.dists.kumaraswamy.logpdf.factory":"\nbase.dists.kumaraswamy.logpdf.factory( a, b )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a Kumaraswamy's double bounded distribution with\n    first shape parameter `a` and second shape parameter `b`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.kumaraswamy.logpdf.factory( 0.5, 1.0 );\n    > var y = mylogpdf( 0.8 )\n    ~-0.582\n    > y = mylogpdf( 0.3 )\n    ~-0.091","base.dists.kumaraswamy.mean":"\nbase.dists.kumaraswamy.mean( a, b )\n    Returns the mean of a Kumaraswamy's double bounded distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Mean.\n\n    Examples\n    --------\n    > var v = base.dists.kumaraswamy.mean( 1.5, 1.5 )\n    ~0.512\n    > v = base.dists.kumaraswamy.mean( 4.0, 12.0 )\n    ~0.481\n    > v = base.dists.kumaraswamy.mean( 16.0, 8.0 )\n    ~0.846\n\n","base.dists.kumaraswamy.median":"\nbase.dists.kumaraswamy.median( a, b )\n    Returns the median of a Kumaraswamy's double bounded distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.kumaraswamy.median( 1.0, 1.0 )\n    0.5\n    > v = base.dists.kumaraswamy.median( 4.0, 12.0 )\n    ~0.487\n    > v = base.dists.kumaraswamy.median( 16.0, 8.0 )\n    ~0.856\n\n","base.dists.kumaraswamy.mode":"\nbase.dists.kumaraswamy.mode( a, b )\n    Returns the mode of a Kumaraswamy's double bounded distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a < 1`, `b < 1`, or `a = b = 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.kumaraswamy.mode( 1.5, 1.5 )\n    ~0.543\n    > v = base.dists.kumaraswamy.mode( 4.0, 12.0 )\n    ~0.503\n    > v = base.dists.kumaraswamy.mode( 16.0, 8.0 )\n    ~0.875\n\n","base.dists.kumaraswamy.pdf":"\nbase.dists.kumaraswamy.pdf( x, a, b )\n    Evaluates the probability density function (PDF) for Kumaraswamy's double\n    bounded distribution with first shape parameter `a` and second shape\n    parameter `b` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.kumaraswamy.pdf( 0.5, 1.0, 1.0 )\n    1.0\n    > y = base.dists.kumaraswamy.pdf( 0.5, 2.0, 4.0 )\n    ~1.688\n    > y = base.dists.kumaraswamy.pdf( 0.2, 2.0, 2.0 )\n    ~0.768\n    > y = base.dists.kumaraswamy.pdf( 0.8, 4.0, 4.0 )\n    ~1.686\n    > y = base.dists.kumaraswamy.pdf( -0.5, 4.0, 2.0 )\n    0.0\n    > y = base.dists.kumaraswamy.pdf( 1.5, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.kumaraswamy.pdf( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.kumaraswamy.pdf( 2.0, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.kumaraswamy.pdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.kumaraswamy.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.kumaraswamy.pdf( 0.0, 1.0, NaN )\n    NaN\n\n\nbase.dists.kumaraswamy.pdf.factory( a, b )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Kumaraswamy's double bounded distribution with first shape parameter\n    `a` and second shape parameter `b`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var mypdf = base.dists.kumaraswamy.pdf.factory( 0.5, 1.0 );\n    > var y = mypdf( 0.8 )\n    ~0.559\n    > y = mypdf( 0.3 )\n    ~0.913\n\n","base.dists.kumaraswamy.pdf.factory":"\nbase.dists.kumaraswamy.pdf.factory( a, b )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Kumaraswamy's double bounded distribution with first shape parameter\n    `a` and second shape parameter `b`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var mypdf = base.dists.kumaraswamy.pdf.factory( 0.5, 1.0 );\n    > var y = mypdf( 0.8 )\n    ~0.559\n    > y = mypdf( 0.3 )\n    ~0.913","base.dists.kumaraswamy.quantile":"\nbase.dists.kumaraswamy.quantile( p, a, b )\n    Evaluates the quantile function for a Kumaraswamy's double bounded\n    distribution with first shape parameter `a` and second shape parameter `b`\n    at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.kumaraswamy.quantile( 0.5, 1.0, 1.0 )\n    0.5\n    > y = base.dists.kumaraswamy.quantile( 0.5, 2.0, 4.0 )\n    ~0.399\n    > y = base.dists.kumaraswamy.quantile( 0.2, 2.0, 2.0 )\n    ~0.325\n    > y = base.dists.kumaraswamy.quantile( 0.8, 4.0, 4.0 )\n    ~0.759\n\n    > y = base.dists.kumaraswamy.quantile( -0.5, 4.0, 2.0 )\n    NaN\n    > y = base.dists.kumaraswamy.quantile( 1.5, 4.0, 2.0 )\n    NaN\n\n    > y = base.dists.kumaraswamy.quantile( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.kumaraswamy.quantile( 2.0, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.kumaraswamy.quantile( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.kumaraswamy.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.kumaraswamy.quantile( 0.0, 1.0, NaN )\n    NaN\n\n\nbase.dists.kumaraswamy.quantile.factory( a, b )\n    Returns a function for evaluating the quantile function of a Kumaraswamy's\n    double bounded distribution with first shape parameter `a` and second shape\n    parameter `b`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.kumaraswamy.quantile.factory( 0.5, 1.0 );\n    > var y = myQuantile( 0.8 )\n    ~0.64\n    > y = myQuantile( 0.3 )\n    ~0.09\n\n","base.dists.kumaraswamy.quantile.factory":"\nbase.dists.kumaraswamy.quantile.factory( a, b )\n    Returns a function for evaluating the quantile function of a Kumaraswamy's\n    double bounded distribution with first shape parameter `a` and second shape\n    parameter `b`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.kumaraswamy.quantile.factory( 0.5, 1.0 );\n    > var y = myQuantile( 0.8 )\n    ~0.64\n    > y = myQuantile( 0.3 )\n    ~0.09","base.dists.kumaraswamy.skewness":"\nbase.dists.kumaraswamy.skewness( a, b )\n    Returns the skewness of a Kumaraswamy's double bounded distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.kumaraswamy.skewness( 1.0, 1.0 )\n    ~1.154e-15\n    > v = base.dists.kumaraswamy.skewness( 4.0, 12.0 )\n    ~-0.201\n    > v = base.dists.kumaraswamy.skewness( 16.0, 8.0 )\n    ~-0.94\n\n","base.dists.kumaraswamy.stdev":"\nbase.dists.kumaraswamy.stdev( a, b )\n    Returns the standard deviation of a Kumaraswamy's double bounded\n    distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.kumaraswamy.stdev( 1.0, 1.0 )\n    ~0.289\n    > v = base.dists.kumaraswamy.stdev( 4.0, 12.0 )\n    ~0.13\n    > v = base.dists.kumaraswamy.stdev( 16.0, 8.0 )\n    ~0.062\n\n","base.dists.kumaraswamy.variance":"\nbase.dists.kumaraswamy.variance( a, b )\n    Returns the variance of a Kumaraswamy's double bounded distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.kumaraswamy.variance( 1.0, 1.0 )\n    ~0.083\n    > v = base.dists.kumaraswamy.variance( 4.0, 12.0 )\n    ~0.017\n    > v = base.dists.kumaraswamy.variance( 16.0, 8.0 )\n    ~0.004\n\n","base.dists.laplace.cdf":"\nbase.dists.laplace.cdf( x, μ, b )\n    Evaluates the cumulative distribution function (CDF) for a Laplace\n    distribution with scale parameter `b` and location parameter `μ` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.cdf( 2.0, 0.0, 1.0 )\n    ~0.932\n    > y = base.dists.laplace.cdf( 5.0, 10.0, 3.0 )\n    ~0.094\n    > y = base.dists.laplace.cdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.laplace.cdf( 2, NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.cdf( 2.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.laplace.cdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.laplace.cdf.factory( μ, b )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Laplace distribution with scale parameter `b` and location parameter\n    `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.laplace.cdf.factory( 2.0, 3.0 );\n    > var y = myCDF( 10.0 )\n    ~0.965\n    > y = myCDF( 2.0 )\n    0.5\n\n","base.dists.laplace.cdf.factory":"\nbase.dists.laplace.cdf.factory( μ, b )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Laplace distribution with scale parameter `b` and location parameter\n    `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.laplace.cdf.factory( 2.0, 3.0 );\n    > var y = myCDF( 10.0 )\n    ~0.965\n    > y = myCDF( 2.0 )\n    0.5","base.dists.laplace.entropy":"\nbase.dists.laplace.entropy( μ, b )\n    Returns the differential entropy of a Laplace distribution with location\n    parameter `μ` and scale parameter `b`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Differential entropy.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.entropy( 0.0, 1.0 )\n    ~1.693\n    > y = base.dists.laplace.entropy( 4.0, 2.0 )\n    ~2.386\n    > y = base.dists.laplace.entropy( NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.entropy( 0.0, NaN )\n    NaN\n    > y = base.dists.laplace.entropy( 0.0, 0.0 )\n    NaN\n\n","base.dists.laplace.kurtosis":"\nbase.dists.laplace.kurtosis( μ, b )\n    Returns the excess kurtosis of a Laplace distribution with location\n    parameter `μ` and scale parameter `b`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.kurtosis( 0.0, 1.0 )\n    3.0\n    > y = base.dists.laplace.kurtosis( 4.0, 2.0 )\n    3.0\n    > y = base.dists.laplace.kurtosis( NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.kurtosis( 0.0, NaN )\n    NaN\n    > y = base.dists.laplace.kurtosis( 0.0, 0.0 )\n    NaN\n\n","base.dists.laplace.Laplace":"\nbase.dists.laplace.Laplace( [μ, b] )\n    Returns a Laplace distribution object.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter. Default: `0.0`.\n\n    b: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    laplace: Object\n        Distribution instance.\n\n    laplace.mu: number\n        Location parameter.\n\n    laplace.b: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    laplace.entropy: number\n        Read-only property which returns the differential entropy.\n\n    laplace.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    laplace.mean: number\n        Read-only property which returns the expected value.\n\n    laplace.median: number\n        Read-only property which returns the median.\n\n    laplace.mode: number\n        Read-only property which returns the mode.\n\n    laplace.skewness: number\n        Read-only property which returns the skewness.\n\n    laplace.stdev: number\n        Read-only property which returns the standard deviation.\n\n    laplace.variance: number\n        Read-only property which returns the variance.\n\n    laplace.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    laplace.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    laplace.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    laplace.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    laplace.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    laplace.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var laplace = base.dists.laplace.Laplace( -2.0, 3.0 );\n    > laplace.mu\n    -2.0\n    > laplace.b\n    3.0\n    > laplace.entropy\n    ~2.792\n    > laplace.kurtosis\n    3.0\n    > laplace.mean\n    -2.0\n    > laplace.median\n    -2.0\n    > laplace.mode\n    -2.0\n    > laplace.skewness\n    0.0\n    > laplace.stdev\n    ~4.243\n    > laplace.variance\n    18.0\n    > laplace.cdf( 0.8 )\n    ~0.803\n    > laplace.logcdf( 0.8 )\n    ~-0.219\n    > laplace.logpdf( 1.0 )\n    ~-2.792\n    > laplace.mgf( 0.2 )\n    ~1.047\n    > laplace.pdf( 2.0 )\n    ~0.044\n    > laplace.quantile( 0.9 )\n    ~2.828\n\n","base.dists.laplace.logcdf":"\nbase.dists.laplace.logcdf( x, μ, b )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    Laplace distribution with scale parameter `b` and location parameter `μ` at\n    a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.logcdf( 2.0, 0.0, 1.0 )\n    ~-0.07\n    > y = base.dists.laplace.logcdf( 5.0, 10.0, 3.0 )\n    ~-2.36\n    > y = base.dists.laplace.logcdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.laplace.logcdf( 2, NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.logcdf( 2.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.laplace.logcdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.laplace.logcdf.factory( μ, b )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Laplace distribution with scale parameter\n    `b` and location parameter `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.laplace.logcdf.factory( 2.0, 3.0 );\n    > var y = mylogcdf( 10.0 )\n    ~-0.035\n    > y = mylogcdf( 2.0 )\n    ~-0.693\n\n","base.dists.laplace.logcdf.factory":"\nbase.dists.laplace.logcdf.factory( μ, b )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Laplace distribution with scale parameter\n    `b` and location parameter `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.laplace.logcdf.factory( 2.0, 3.0 );\n    > var y = mylogcdf( 10.0 )\n    ~-0.035\n    > y = mylogcdf( 2.0 )\n    ~-0.693","base.dists.laplace.logpdf":"\nbase.dists.laplace.logpdf( x, μ, b )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    Laplace distribution with scale parameter `b` and location parameter `μ` at\n    a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.logpdf( 2.0, 0.0, 1.0 )\n    ~-2.693\n    > y = base.dists.laplace.logpdf( -1.0, 2.0, 3.0 )\n    ~-2.792\n    > y = base.dists.laplace.logpdf( 2.5, 2.0, 3.0 )\n    ~-1.958\n    > y = base.dists.laplace.logpdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.laplace.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.logpdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.laplace.logpdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.laplace.logpdf.factory( μ, b )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Laplace distribution with scale parameter `b` and\n    location parameter `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.laplace.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogPDF( 10.0 )\n    ~-1.386\n\n","base.dists.laplace.logpdf.factory":"\nbase.dists.laplace.logpdf.factory( μ, b )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Laplace distribution with scale parameter `b` and\n    location parameter `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.laplace.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogPDF( 10.0 )\n    ~-1.386","base.dists.laplace.mean":"\nbase.dists.laplace.mean( μ, b )\n    Returns the expected value of a Laplace distribution with location parameter\n    `μ` and scale parameter `b`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.mean( 0.0, 1.0 )\n    0.0\n    > y = base.dists.laplace.mean( 4.0, 2.0 )\n    4.0\n    > y = base.dists.laplace.mean( NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.mean( 0.0, NaN )\n    NaN\n    > y = base.dists.laplace.mean( 0.0, 0.0 )\n    NaN\n\n","base.dists.laplace.median":"\nbase.dists.laplace.median( μ, b )\n    Returns the median of a Laplace distribution with location parameter `μ` and\n    scale parameter `b`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.median( 0.0, 1.0 )\n    0.0\n    > y = base.dists.laplace.median( 4.0, 2.0 )\n    4.0\n    > y = base.dists.laplace.median( NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.median( 0.0, NaN )\n    NaN\n    > y = base.dists.laplace.median( 0.0, 0.0 )\n    NaN\n\n","base.dists.laplace.mgf":"\nbase.dists.laplace.mgf( t, μ, b )\n    Evaluates the moment-generating function (MGF) for a Laplace\n    distribution with scale parameter `b` and location parameter `μ` at a\n    value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.mgf( 0.5, 0.0, 1.0 )\n    ~1.333\n    > y = base.dists.laplace.mgf( 0.0, 0.0, 1.0 )\n    1.0\n    > y = base.dists.laplace.mgf( -1.0, 4.0, 0.2 )\n    ~0.019\n    > y = base.dists.laplace.mgf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.laplace.mgf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.mgf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.laplace.mgf( 1.0, 0.0, 2.0 )\n    NaN\n    > y = base.dists.laplace.mgf( -0.5, 0.0, 4.0 )\n    NaN\n    > y = base.dists.laplace.mgf( 2.0, 0.0, 0.0 )\n    NaN\n    > y = base.dists.laplace.mgf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.laplace.mgf.factory( μ, b )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a Laplace distribution with scale parameter `b` and location parameter\n    `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.laplace.mgf.factory( 4.0, 2.0 );\n    > var y = mymgf( 0.2 )\n    ~2.649\n    > y = mymgf( 0.4 )\n    ~13.758\n\n","base.dists.laplace.mgf.factory":"\nbase.dists.laplace.mgf.factory( μ, b )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a Laplace distribution with scale parameter `b` and location parameter\n    `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.laplace.mgf.factory( 4.0, 2.0 );\n    > var y = mymgf( 0.2 )\n    ~2.649\n    > y = mymgf( 0.4 )\n    ~13.758","base.dists.laplace.mode":"\nbase.dists.laplace.mode( μ, b )\n    Returns the mode of a Laplace distribution with location parameter `μ` and\n    scale parameter `b`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.mode( 0.0, 1.0 )\n    0.0\n    > y = base.dists.laplace.mode( 4.0, 2.0 )\n    4.0\n    > y = base.dists.laplace.mode( NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.mode( 0.0, NaN )\n    NaN\n    > y = base.dists.laplace.mode( 0.0, 0.0 )\n    NaN\n\n","base.dists.laplace.pdf":"\nbase.dists.laplace.pdf( x, μ, b )\n    Evaluates the probability density function (PDF) for a Laplace\n    distribution with scale parameter `b` and location parameter `μ` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.pdf( 2.0, 0.0, 1.0 )\n    ~0.068\n    > y = base.dists.laplace.pdf( -1.0, 2.0, 3.0 )\n    ~0.061\n    > y = base.dists.laplace.pdf( 2.5, 2.0, 3.0 )\n    ~0.141\n    > y = base.dists.laplace.pdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.laplace.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.pdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.laplace.pdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.laplace.pdf.factory( μ, b )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Laplace distribution with scale parameter `b` and location parameter\n    `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.laplace.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    0.25\n\n","base.dists.laplace.pdf.factory":"\nbase.dists.laplace.pdf.factory( μ, b )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Laplace distribution with scale parameter `b` and location parameter\n    `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.laplace.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    0.25","base.dists.laplace.quantile":"\nbase.dists.laplace.quantile( p, μ, b )\n    Evaluates the quantile function for a Laplace distribution with scale\n    parameter `b` and location parameter `μ` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.quantile( 0.8, 0.0, 1.0 )\n    ~0.916\n    > y = base.dists.laplace.quantile( 0.5, 4.0, 2.0 )\n    4.0\n\n    > y = base.dists.laplace.quantile( 1.1, 0.0, 1.0 )\n    NaN\n    > y = base.dists.laplace.quantile( -0.2, 0.0, 1.0 )\n    NaN\n\n    > y = base.dists.laplace.quantile( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.laplace.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.quantile( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.laplace.quantile( 0.5, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.laplace.quantile.factory( μ, b )\n    Returns a function for evaluating the quantile function of a Laplace\n    distribution with scale parameter `b` and location parameter `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.laplace.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    10.0\n    > y = myQuantile( 0.8 )\n    ~11.833\n\n","base.dists.laplace.quantile.factory":"\nbase.dists.laplace.quantile.factory( μ, b )\n    Returns a function for evaluating the quantile function of a Laplace\n    distribution with scale parameter `b` and location parameter `μ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.laplace.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    10.0\n    > y = myQuantile( 0.8 )\n    ~11.833","base.dists.laplace.skewness":"\nbase.dists.laplace.skewness( μ, b )\n    Returns the skewness of a Laplace distribution with location parameter `μ`\n    and scale parameter `b`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.skewness( 0.0, 1.0 )\n    0.0\n    > y = base.dists.laplace.skewness( 4.0, 2.0 )\n    0.0\n    > y = base.dists.laplace.skewness( NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.skewness( 0.0, NaN )\n    NaN\n    > y = base.dists.laplace.skewness( 0.0, 0.0 )\n    NaN\n\n","base.dists.laplace.stdev":"\nbase.dists.laplace.stdev( μ, b )\n    Returns the standard deviation of a Laplace distribution with location\n    parameter `μ` and scale parameter `b`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.stdev( 0.0, 1.0 )\n    ~1.414\n    > y = base.dists.laplace.stdev( 4.0, 2.0 )\n    ~2.828\n    > y = base.dists.laplace.stdev( NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.stdev( 0.0, NaN )\n    NaN\n    > y = base.dists.laplace.stdev( 0.0, 0.0 )\n    NaN\n\n","base.dists.laplace.variance":"\nbase.dists.laplace.variance( μ, b )\n    Returns the variance of a Laplace distribution with location parameter `μ`\n    and scale parameter `b`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var y = base.dists.laplace.variance( 0.0, 1.0 )\n    2.0\n    > y = base.dists.laplace.variance( 4.0, 2.0 )\n    8.0\n    > y = base.dists.laplace.variance( NaN, 1.0 )\n    NaN\n    > y = base.dists.laplace.variance( 0.0, NaN )\n    NaN\n    > y = base.dists.laplace.variance( 0.0, 0.0 )\n    NaN\n\n","base.dists.levy.cdf":"\nbase.dists.levy.cdf( x, μ, c )\n    Evaluates the cumulative distribution function (CDF) for a Lévy distribution\n    with location parameter `μ` and scale parameter `c` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.levy.cdf( 2.0, 0.0, 1.0 )\n    ~0.48\n    > y = base.dists.levy.cdf( 12.0, 10.0, 3.0 )\n    ~0.221\n    > y = base.dists.levy.cdf( 9.0, 10.0, 3.0 )\n    0.0\n    > y = base.dists.levy.cdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.levy.cdf( 2, NaN, 1.0 )\n    NaN\n    > y = base.dists.levy.cdf( 2.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.levy.cdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.levy.cdf.factory( μ, c )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.levy.cdf.factory( 2.0, 3.0 );\n    > var y = myCDF( 10.0 )\n    ~0.54\n    > y = myCDF( 2.0 )\n    0.0\n\n","base.dists.levy.cdf.factory":"\nbase.dists.levy.cdf.factory( μ, c )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.levy.cdf.factory( 2.0, 3.0 );\n    > var y = myCDF( 10.0 )\n    ~0.54\n    > y = myCDF( 2.0 )\n    0.0","base.dists.levy.entropy":"\nbase.dists.levy.entropy( μ, c )\n    Returns the entropy of a Lévy distribution with location parameter `μ` and\n    scale parameter `c`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var y = base.dists.levy.entropy( 0.0, 1.0 )\n    ~3.324\n    > y = base.dists.levy.entropy( 4.0, 2.0 )\n    ~4.018\n    > y = base.dists.levy.entropy( NaN, 1.0 )\n    NaN\n    > y = base.dists.levy.entropy( 0.0, NaN )\n    NaN\n    > y = base.dists.levy.entropy( 0.0, 0.0 )\n    NaN\n\n","base.dists.levy.Levy":"\nbase.dists.levy.Levy( [μ, c] )\n    Returns a Lévy distribution object.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter. Default: `0.0`.\n\n    c: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    levy: Object\n        Distribution instance.\n\n    levy.mu: number\n        Location parameter.\n\n    levy.c: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    levy.entropy: number\n        Read-only property which returns the differential entropy.\n\n    levy.mean: number\n        Read-only property which returns the expected value.\n\n    levy.median: number\n        Read-only property which returns the median.\n\n    levy.mode: number\n        Read-only property which returns the mode.\n\n    levy.stdev: number\n        Read-only property which returns the standard deviation.\n\n    levy.variance: number\n        Read-only property which returns the variance.\n\n    levy.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    levy.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    levy.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    levy.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    levy.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var levy = base.dists.levy.Levy( -2.0, 3.0 );\n    > levy.mu\n    -2.0\n    > levy.c\n    3.0\n    > levy.entropy\n    ~4.423\n    > levy.mean\n    Infinity\n    > levy.median\n    ~4.594\n    > levy.mode\n    -1.0\n    > levy.stdev\n    Infinity\n    > levy.variance\n    Infinity\n    > levy.cdf( 0.8 )\n    ~0.3\n    > levy.logcdf( 0.8 )\n    ~-1.2\n    > levy.logpdf( 1.0 )\n    ~-2.518\n    > levy.pdf( 1.0 )\n    ~0.081\n    > levy.quantile( 0.8 )\n    ~44.74\n\n","base.dists.levy.logcdf":"\nbase.dists.levy.logcdf( x, μ, c )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    Lévy distribution with location parameter `μ` and scale parameter `c` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.levy.logcdf( 2.0, 0.0, 1.0 )\n    ~-0.735\n    > y = base.dists.levy.logcdf( 12.0, 10.0, 3.0 )\n    ~-1.51\n    > y = base.dists.levy.logcdf( 9.0, 10.0, 3.0 )\n    -Infinity\n    > y = base.dists.levy.logcdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.levy.logcdf( 2, NaN, 1.0 )\n    NaN\n    > y = base.dists.levy.logcdf( 2.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.levy.logcdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.levy.logcdf.factory( μ, c )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Lévy distribution with location parameter\n    `μ` and scale parameter `c`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.levy.logcdf.factory( 2.0, 3.0 );\n    > var y = mylogcdf( 10.0 )\n    ~-0.616\n    > y = mylogcdf( 2.0 )\n    -Infinity\n\n","base.dists.levy.logcdf.factory":"\nbase.dists.levy.logcdf.factory( μ, c )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Lévy distribution with location parameter\n    `μ` and scale parameter `c`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.levy.logcdf.factory( 2.0, 3.0 );\n    > var y = mylogcdf( 10.0 )\n    ~-0.616\n    > y = mylogcdf( 2.0 )\n    -Infinity","base.dists.levy.logpdf":"\nbase.dists.levy.logpdf( x, μ, c )\n    Evaluates the logarithm of the probability density function (PDF) for a Lévy\n    distribution with location parameter `μ` and scale parameter `c` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.levy.logpdf( 2.0, 0.0, 1.0 )\n    ~-2.209\n    > y = base.dists.levy.logpdf( -1.0, 4.0, 2.0 )\n    -Infinity\n    > y = base.dists.levy.logpdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.levy.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.levy.logpdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.levy.logpdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.levy.logpdf.factory( μ, c )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Lévy distribution with location parameter `μ` and scale\n    parameter `c`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.levy.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogPDF( 11.0 )\n    ~-1.572\n\n","base.dists.levy.logpdf.factory":"\nbase.dists.levy.logpdf.factory( μ, c )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Lévy distribution with location parameter `μ` and scale\n    parameter `c`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.levy.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogPDF( 11.0 )\n    ~-1.572","base.dists.levy.mean":"\nbase.dists.levy.mean( μ, c )\n    Returns the expected value of a Lévy distribution with location parameter\n    `μ` and scale parameter `c`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var y = base.dists.levy.mean( 0.0, 1.0 )\n    Infinity\n    > y = base.dists.levy.mean( 4.0, 3.0 )\n    Infinity\n    > y = base.dists.levy.mean( NaN, 1.0 )\n    NaN\n    > y = base.dists.levy.mean( 0.0, NaN )\n    NaN\n    > y = base.dists.levy.mean( 0.0, 0.0 )\n    NaN\n\n","base.dists.levy.median":"\nbase.dists.levy.median( μ, c )\n    Returns the median of a Lévy distribution with location parameter `μ` and\n    scale parameter `c`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var y = base.dists.levy.median( 0.0, 1.0 )\n    ~2.198\n    > y = base.dists.levy.median( 4.0, 3.0 )\n    ~10.594\n    > y = base.dists.levy.median( NaN, 1.0 )\n    NaN\n    > y = base.dists.levy.median( 0.0, NaN )\n    NaN\n    > y = base.dists.levy.median( 0.0, 0.0 )\n    NaN\n\n","base.dists.levy.mode":"\nbase.dists.levy.mode( μ, c )\n    Returns the mode of a Lévy distribution with location parameter `μ` and\n    scale parameter `c`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var y = base.dists.levy.mode( 0.0, 1.0 )\n    ~0.333\n    > y = base.dists.levy.mode( 4.0, 3.0 )\n    5.0\n    > y = base.dists.levy.mode( NaN, 1.0 )\n    NaN\n    > y = base.dists.levy.mode( 0.0, NaN )\n    NaN\n    > y = base.dists.levy.mode( 0.0, 0.0 )\n    NaN\n\n","base.dists.levy.pdf":"\nbase.dists.levy.pdf( x, μ, c )\n    Evaluates the probability density function (PDF) for a Lévy distribution\n    with location parameter `μ` and scale parameter `c` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.levy.pdf( 2.0, 0.0, 1.0 )\n    ~0.11\n    > y = base.dists.levy.pdf( -1.0, 4.0, 2.0 )\n    0.0\n    > y = base.dists.levy.pdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.levy.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.levy.pdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.levy.pdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.levy.pdf.factory( μ, c )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.levy.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 11.0 )\n    ~0.208\n\n","base.dists.levy.pdf.factory":"\nbase.dists.levy.pdf.factory( μ, c )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Lévy distribution with location parameter `μ` and scale parameter `c`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.levy.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 11.0 )\n    ~0.208","base.dists.levy.quantile":"\nbase.dists.levy.quantile( p, μ, c )\n    Evaluates the quantile function for a Lévy distribution with location\n    parameter `μ` and scale parameter `c` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.levy.quantile( 0.8, 0.0, 1.0 )\n    ~15.58\n    > y = base.dists.levy.quantile( 0.5, 4.0, 2.0 )\n    ~8.396\n\n    > y = base.dists.levy.quantile( 1.1, 0.0, 1.0 )\n    NaN\n    > y = base.dists.levy.quantile( -0.2, 0.0, 1.0 )\n    NaN\n\n    > y = base.dists.levy.quantile( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.levy.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.levy.quantile( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.levy.quantile( 0.5, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.levy.quantile.factory( μ, c )\n    Returns a function for evaluating the quantile function of a Lévy\n    distribution with location parameter `μ` and scale parameter `c`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.levy.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    ~14.396\n\n","base.dists.levy.quantile.factory":"\nbase.dists.levy.quantile.factory( μ, c )\n    Returns a function for evaluating the quantile function of a Lévy\n    distribution with location parameter `μ` and scale parameter `c`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.levy.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    ~14.396","base.dists.levy.stdev":"\nbase.dists.levy.stdev( μ, c )\n    Returns the standard deviation of a Lévy distribution with location\n    parameter `μ` and scale parameter `c`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var y = base.dists.levy.stdev( 0.0, 1.0 )\n    Infinity\n    > y = base.dists.levy.stdev( 4.0, 3.0 )\n    Infinity\n    > y = base.dists.levy.stdev( NaN, 1.0 )\n    NaN\n    > y = base.dists.levy.stdev( 0.0, NaN )\n    NaN\n    > y = base.dists.levy.stdev( 0.0, 0.0 )\n    NaN\n\n","base.dists.levy.variance":"\nbase.dists.levy.variance( μ, c )\n    Returns the variance of a Lévy distribution with location parameter `μ` and\n    scale parameter `c`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var y = base.dists.levy.variance( 0.0, 1.0 )\n    Infinity\n    > y = base.dists.levy.variance( 4.0, 3.0 )\n    Infinity\n    > y = base.dists.levy.variance( NaN, 1.0 )\n    NaN\n    > y = base.dists.levy.variance( 0.0, NaN )\n    NaN\n    > y = base.dists.levy.variance( 0.0, 0.0 )\n    NaN\n\n","base.dists.logistic.cdf":"\nbase.dists.logistic.cdf( x, μ, s )\n    Evaluates the cumulative distribution function (CDF) for a logistic\n    distribution with location parameter `μ` and scale parameter `s` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.cdf( 2.0, 0.0, 1.0 )\n    ~0.881\n    > y = base.dists.logistic.cdf( 5.0, 10.0, 3.0 )\n    ~0.159\n\n    > y = base.dists.logistic.cdf( 2.0, 0.0, NaN )\n    NaN\n    > y = base.dists.logistic.cdf( 2.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.cdf( NaN, 0.0, 1.0 )\n    NaN\n\n    // Degenerate distribution centered at `μ` when `s = 0.0`:\n    > y = base.dists.logistic.cdf( 2.0, 8.0, 0.0 )\n    0.0\n    > y = base.dists.logistic.cdf( 8.0, 8.0, 0.0 )\n    1.0\n    > y = base.dists.logistic.cdf( 10.0, 8.0, 0.0 )\n    1.0\n\n\nbase.dists.logistic.cdf.factory( μ, s )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a logistic distribution with location parameter `μ` and scale parameter\n    `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.logistic.cdf.factory( 3.0, 1.5 );\n    > var y = mycdf( 1.0 )\n    ~0.209\n\n","base.dists.logistic.cdf.factory":"\nbase.dists.logistic.cdf.factory( μ, s )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a logistic distribution with location parameter `μ` and scale parameter\n    `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.logistic.cdf.factory( 3.0, 1.5 );\n    > var y = mycdf( 1.0 )\n    ~0.209","base.dists.logistic.entropy":"\nbase.dists.logistic.entropy( μ, s )\n    Returns the entropy of a logistic distribution with location parameter `μ`\n    and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.entropy( 0.0, 1.0 )\n    2.0\n    > y = base.dists.logistic.entropy( 4.0, 2.0 )\n    ~2.693\n    > y = base.dists.logistic.entropy( NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.entropy( 0.0, NaN )\n    NaN\n    > y = base.dists.logistic.entropy( 0.0, 0.0 )\n    NaN\n\n","base.dists.logistic.kurtosis":"\nbase.dists.logistic.kurtosis( μ, s )\n    Returns the excess kurtosis of a logistic distribution with location\n    parameter `μ` and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.kurtosis( 0.0, 1.0 )\n    1.2\n    > y = base.dists.logistic.kurtosis( 4.0, 2.0 )\n    1.2\n    > y = base.dists.logistic.kurtosis( NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.kurtosis( 0.0, NaN )\n    NaN\n    > y = base.dists.logistic.kurtosis( 0.0, 0.0 )\n    NaN\n\n\n","base.dists.logistic.logcdf":"\nbase.dists.logistic.logcdf( x, μ, s )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    logistic distribution with location parameter `μ` and scale parameter `s` at\n    a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.logcdf( 2.0, 0.0, 1.0 )\n    ~-0.127\n    > y = base.dists.logistic.logcdf( 5.0, 10.0, 3.0 )\n    ~-1.84\n    > y = base.dists.logistic.logcdf( 2.0, 0.0, NaN )\n    NaN\n    > y = base.dists.logistic.logcdf( 2, NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.logcdf( NaN, 0.0, 1.0 )\n    NaN\n\n\nbase.dists.logistic.logcdf.factory( μ, s )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Logistic distribution with location\n    parameter `μ` and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.logistic.logcdf.factory( 3.0, 1.5 );\n    > var y = mylogcdf( 1.0 )\n    ~-1.567\n\n","base.dists.logistic.logcdf.factory":"\nbase.dists.logistic.logcdf.factory( μ, s )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Logistic distribution with location\n    parameter `μ` and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.logistic.logcdf.factory( 3.0, 1.5 );\n    > var y = mylogcdf( 1.0 )\n    ~-1.567","base.dists.logistic.Logistic":"\nbase.dists.logistic.Logistic( [μ, s] )\n    Returns a logistic distribution object.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter. Default: `0.0`.\n\n    s: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    logistic: Object\n        Distribution instance.\n\n    logistic.mu: number\n        Location parameter.\n\n    logistic.s: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    logistic.entropy: number\n        Read-only property which returns the differential entropy.\n\n    logistic.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    logistic.mean: number\n        Read-only property which returns the expected value.\n\n    logistic.median: number\n        Read-only property which returns the median.\n\n    logistic.mode: number\n        Read-only property which returns the mode.\n\n    logistic.skewness: number\n        Read-only property which returns the skewness.\n\n    logistic.stdev: number\n        Read-only property which returns the standard deviation.\n\n    logistic.variance: number\n        Read-only property which returns the variance.\n\n    logistic.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    logistic.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    logistic.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    logistic.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    logistic.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    logistic.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var logistic = base.dists.logistic.Logistic( -2.0, 3.0 );\n    > logistic.mu\n    -2.0\n    > logistic.s\n    3.0\n    > logistic.entropy\n    ~3.1\n    > logistic.kurtosis\n    1.2\n    > logistic.mean\n    -2.0\n    > logistic.median\n    -2.0\n    > logistic.mode\n    -2.0\n    > logistic.skewness\n    0.0\n    > logistic.stdev\n    ~5.441\n    > logistic.variance\n    ~29.609\n    > logistic.cdf( 0.8 )\n    ~0.718\n    > logistic.logcdf( 0.8 )\n    ~-0.332\n    > logistic.logpdf( 2.0 )\n    ~-2.9\n    > logistic.mgf( 0.2 )\n    ~1.329\n    > logistic.pdf( 2.0 )\n    ~0.055\n    > logistic.quantile( 0.9 )\n    ~4.592\n\n","base.dists.logistic.logpdf":"\nbase.dists.logistic.logpdf( x, μ, s )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    logistic distribution with location parameter `μ` and scale parameter `s` at\n    a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.logpdf( 2.0, 0.0, 1.0 )\n    ~-2.254\n    > y = base.dists.logistic.logpdf( -1.0, 4.0, 2.0 )\n    ~-3.351\n    > y = base.dists.logistic.logpdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.logistic.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.logpdf( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.logistic.logpdf( 2.0, 0.0, -1.0 )\n    NaN\n\n    // Degenerate distribution at `s = 0.0`:\n    > y = base.dists.logistic.logpdf( 2.0, 8.0, 0.0 )\n    -Infinity\n    > y = base.dists.logistic.logpdf( 8.0, 8.0, 0.0 )\n    Infinity\n\n\nbase.dists.logistic.logpdf.factory( μ, s )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Logistic distribution with location parameter `μ` and\n    scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.logistic.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogpdf( 10.0 )\n    ~-2.079\n\n","base.dists.logistic.logpdf.factory":"\nbase.dists.logistic.logpdf.factory( μ, s )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Logistic distribution with location parameter `μ` and\n    scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.logistic.logpdf.factory( 10.0, 2.0 );\n    > var y = mylogpdf( 10.0 )\n    ~-2.079","base.dists.logistic.mean":"\nbase.dists.logistic.mean( μ, s )\n    Returns the expected value of a logistic distribution with location\n    parameter `μ` and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.mean( 0.0, 1.0 )\n    0.0\n    > y = base.dists.logistic.mean( 4.0, 2.0 )\n    4.0\n    > y = base.dists.logistic.mean( NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.mean( 0.0, NaN )\n    NaN\n    > y = base.dists.logistic.mean( 0.0, 0.0 )\n    NaN\n\n","base.dists.logistic.median":"\nbase.dists.logistic.median( μ, s )\n    Returns the median of a logistic distribution with location parameter `μ`\n    and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.median( 0.0, 1.0 )\n    0.0\n    > y = base.dists.logistic.median( 4.0, 2.0 )\n    4.0\n    > y = base.dists.logistic.median( NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.median( 0.0, NaN )\n    NaN\n    > y = base.dists.logistic.median( 0.0, 0.0 )\n    NaN\n\n","base.dists.logistic.mgf":"\nbase.dists.logistic.mgf( t, μ, s )\n    Evaluates the moment-generating function (MGF) for a logistic distribution\n    with location parameter `μ` and scale parameter `s` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.mgf( 0.9, 0.0, 1.0 )\n    ~9.15\n    > y = base.dists.logistic.mgf( 0.1, 4.0, 4.0 )\n    ~1.971\n    > y = base.dists.logistic.mgf( -0.2, 4.0, 4.0 )\n    ~1.921\n    > y = base.dists.logistic.mgf( 0.5, 0.0, -1.0 )\n    NaN\n    > y = base.dists.logistic.mgf( 0.5, 0.0, 4.0 )\n    Infinity\n    > y = base.dists.logistic.mgf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.logistic.mgf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.mgf( 0.0, 0.0, NaN )\n    NaN\n\n\nbase.dists.logistic.mgf.factory( μ, s )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a Logistic distribution with location parameter `μ` and scale parameter\n    `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.logistic.mgf.factory( 10.0, 0.5 );\n    > var y = mymgf( 0.5 )\n    ~164.846\n    > y = mymgf( 2.0 )\n    Infinity\n\n","base.dists.logistic.mgf.factory":"\nbase.dists.logistic.mgf.factory( μ, s )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a Logistic distribution with location parameter `μ` and scale parameter\n    `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.logistic.mgf.factory( 10.0, 0.5 );\n    > var y = mymgf( 0.5 )\n    ~164.846\n    > y = mymgf( 2.0 )\n    Infinity","base.dists.logistic.mode":"\nbase.dists.logistic.mode( μ, s )\n    Returns the mode of a logistic distribution with location parameter `μ` and\n    scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.mode( 0.0, 1.0 )\n    0.0\n    > y = base.dists.logistic.mode( 4.0, 2.0 )\n    4.0\n    > y = base.dists.logistic.mode( NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.mode( 0.0, NaN )\n    NaN\n    > y = base.dists.logistic.mode( 0.0, 0.0 )\n    NaN\n\n","base.dists.logistic.pdf":"\nbase.dists.logistic.pdf( x, μ, s )\n    Evaluates the probability density function (PDF) for a logistic distribution\n    with location parameter `μ` and scale parameter `s` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.pdf( 2.0, 0.0, 1.0 )\n    ~0.105\n    > y = base.dists.logistic.pdf( -1.0, 4.0, 2.0 )\n    ~0.035\n    > y = base.dists.logistic.pdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.logistic.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.pdf( 0.0, 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.logistic.pdf( 2.0, 0.0, -1.0 )\n    NaN\n    > y = base.dists.logistic.pdf( 2.0, 8.0, 0.0 )\n    0.0\n    > y = base.dists.logistic.pdf( 8.0, 8.0, 0.0 )\n    Infinity\n\n\nbase.dists.logistic.pdf.factory( μ, s )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Logistic distribution with location parameter `μ` and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.logistic.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    0.125\n\n","base.dists.logistic.pdf.factory":"\nbase.dists.logistic.pdf.factory( μ, s )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Logistic distribution with location parameter `μ` and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.logistic.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    0.125","base.dists.logistic.quantile":"\nbase.dists.logistic.quantile( p, μ, s )\n    Evaluates the quantile function for a logistic distribution with location\n    parameter `μ` and scale parameter `s` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.quantile( 0.8, 0.0, 1.0 )\n    ~1.386\n    > y = base.dists.logistic.quantile( 0.5, 4.0, 2.0 )\n    4\n\n    > y = base.dists.logistic.quantile( 1.1, 0.0, 1.0 )\n    NaN\n    > y = base.dists.logistic.quantile( -0.2, 0.0, 1.0 )\n    NaN\n\n    > y = base.dists.logistic.quantile( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.logistic.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.quantile( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.logistic.quantile( 0.5, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.logistic.quantile.factory( μ, s )\n    Returns a function for evaluating the quantile function of a logistic\n    distribution with location parameter `μ` and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.logistic.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    10.0\n\n","base.dists.logistic.quantile.factory":"\nbase.dists.logistic.quantile.factory( μ, s )\n    Returns a function for evaluating the quantile function of a logistic\n    distribution with location parameter `μ` and scale parameter `s`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.logistic.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    10.0","base.dists.logistic.skewness":"\nbase.dists.logistic.skewness( μ, s )\n    Returns the skewness of a logistic distribution with location parameter `μ`\n    and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.skewness( 0.0, 1.0 )\n    0.0\n    > y = base.dists.logistic.skewness( 4.0, 2.0 )\n    0.0\n    > y = base.dists.logistic.skewness( NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.skewness( 0.0, NaN )\n    NaN\n    > y = base.dists.logistic.skewness( 0.0, 0.0 )\n    NaN\n\n","base.dists.logistic.stdev":"\nbase.dists.logistic.stdev( μ, s )\n    Returns the standard deviation of a logistic distribution with location\n    parameter `μ` and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.stdev( 0.0, 1.0 )\n    ~1.814\n    > y = base.dists.logistic.stdev( 4.0, 2.0 )\n    ~3.628\n    > y = base.dists.logistic.stdev( NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.stdev( 0.0, NaN )\n    NaN\n    > y = base.dists.logistic.stdev( 0.0, 0.0 )\n    NaN\n\n","base.dists.logistic.variance":"\nbase.dists.logistic.variance( μ, s )\n    Returns the variance of a logistic distribution with location parameter `μ`\n    and scale parameter `s`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var y = base.dists.logistic.variance( 0.0, 1.0 )\n    ~3.29\n    > y = base.dists.logistic.variance( 4.0, 2.0 )\n    ~13.159\n    > y = base.dists.logistic.variance( NaN, 1.0 )\n    NaN\n    > y = base.dists.logistic.variance( 0.0, NaN )\n    NaN\n    > y = base.dists.logistic.variance( 0.0, 0.0 )\n    NaN\n\n","base.dists.lognormal.cdf":"\nbase.dists.lognormal.cdf( x, μ, σ )\n    Evaluates the cumulative distribution function (CDF) for a lognormal\n    distribution with location parameter `μ` and scale parameter `σ` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.cdf( 2.0, 0.0, 1.0 )\n    ~0.756\n    > y = base.dists.lognormal.cdf( 5.0, 10.0, 3.0 )\n    ~0.003\n\n    > y = base.dists.lognormal.cdf( 2.0, 0.0, NaN )\n    NaN\n    > y = base.dists.lognormal.cdf( 2.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.cdf( NaN, 0.0, 1.0 )\n    NaN\n\n    // Non-positive scale parameter `σ`:\n    > y = base.dists.lognormal.cdf( 2.0, 0.0, -1.0 )\n    NaN\n    > y = base.dists.lognormal.cdf( 2.0, 0.0, 0.0 )\n    NaN\n\n\nbase.dists.lognormal.cdf.factory( μ, σ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a lognormal distribution with location parameter `μ` and scale parameter\n    `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.lognormal.cdf.factory( 3.0, 1.5 );\n    > var y = myCDF( 1.0 )\n    ~0.023\n    > y = myCDF( 4.0 )\n    ~0.141\n\n","base.dists.lognormal.cdf.factory":"\nbase.dists.lognormal.cdf.factory( μ, σ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a lognormal distribution with location parameter `μ` and scale parameter\n    `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.lognormal.cdf.factory( 3.0, 1.5 );\n    > var y = myCDF( 1.0 )\n    ~0.023\n    > y = myCDF( 4.0 )\n    ~0.141","base.dists.lognormal.entropy":"\nbase.dists.lognormal.entropy( μ, σ )\n    Returns the differential entropy of a lognormal distribution with location\n    `μ` and scale `σ` (in nats).\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.entropy( 0.0, 1.0 )\n    ~1.419\n    > y = base.dists.lognormal.entropy( 5.0, 2.0 )\n    ~7.112\n    > y = base.dists.lognormal.entropy( NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.entropy( 0.0, NaN )\n    NaN\n    > y = base.dists.lognormal.entropy( 0.0, 0.0 )\n    NaN\n\n","base.dists.lognormal.kurtosis":"\nbase.dists.lognormal.kurtosis( μ, σ )\n    Returns the excess kurtosis of a lognormal distribution with location `μ`\n    and scale `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Kurtosis.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.kurtosis( 0.0, 1.0 )\n    ~110.936\n    > y = base.dists.lognormal.kurtosis( 5.0, 2.0 )\n    ~9220556.977\n    > y = base.dists.lognormal.kurtosis( NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.kurtosis( 0.0, NaN )\n    NaN\n    > y = base.dists.lognormal.kurtosis( 0.0, 0.0 )\n    NaN\n\n","base.dists.lognormal.LogNormal":"\nbase.dists.lognormal.LogNormal( [μ, σ] )\n    Returns a lognormal distribution object.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter. Default: `0.0`.\n\n    σ: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    lognormal: Object\n        Distribution instance.\n\n    lognormal.mu: number\n        Location parameter.\n\n    lognormal.sigma: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    lognormal.entropy: number\n        Read-only property which returns the differential entropy.\n\n    lognormal.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    lognormal.mean: number\n        Read-only property which returns the expected value.\n\n    lognormal.median: number\n        Read-only property which returns the median.\n\n    lognormal.mode: number\n        Read-only property which returns the mode.\n\n    lognormal.skewness: number\n        Read-only property which returns the skewness.\n\n    lognormal.stdev: number\n        Read-only property which returns the standard deviation.\n\n    lognormal.variance: number\n        Read-only property which returns the variance.\n\n    lognormal.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    lognormal.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    lognormal.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    lognormal.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    lognormal.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var lognormal = base.dists.lognormal.LogNormal( -2.0, 3.0 );\n    > lognormal.mu\n    -2.0\n    > lognormal.sigma\n    3.0\n    > lognormal.entropy\n    ~0.518\n    > lognormal.kurtosis\n    4312295840576300\n    > lognormal.mean\n    ~12.182\n    > lognormal.median\n    ~0.135\n    > lognormal.mode\n    ~0.0\n    > lognormal.skewness\n    ~729551.383\n    > lognormal.stdev\n    ~1096.565\n    > lognormal.variance\n    ~1202455.871\n    > lognormal.cdf( 0.8 )\n    ~0.723\n    > lognormal.logcdf( 0.8 )\n    ~-4.334\n    > lognormal.logpdf( 2.0 )\n    ~-3.114\n    > lognormal.pdf( 2.0 )\n    ~0.044\n    > lognormal.quantile( 0.9 )\n    ~6.326\n\n","base.dists.lognormal.logcdf":"\nbase.dists.lognormal.logcdf( x, μ, σ )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a lognormal distribution with mean `μ` and standard deviation `σ`\n    at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Evaluated logcdf.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.logcdf( 2.0, 0.0, 1.0 )\n    ~-0.2799\n    > y = base.dists.lognormal.logcdf( 13.0, 4.0, 2.0 )\n    ~-1.442\n    > y = base.dists.lognormal.logcdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.lognormal.logcdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.logcdf( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative standard deviation:\n    > y = base.dists.lognormal.logcdf( 2.0, 0.0, -1.0 )\n    NaN\n\n    // Degenerate distribution centered at `μ` when `σ = 0.0`:\n    > y = base.dists.lognormal.logcdf( 2.0, 8.0, 0.0 )\n    -Infinity\n    > y = base.dists.lognormal.logcdf( 8.0, 8.0, 0.0 )\n    -Infinity\n\n\nbase.dists.lognormal.logcdf.factory( μ, σ )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a lognormal distribution with mean `μ` and\n    standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.lognormal.logcdf.factory( 10.0, 2.0 );\n    > var y = mylogcdf( 10.0 )\n    ~-9.732\n\n","base.dists.lognormal.logcdf.factory":"\nbase.dists.lognormal.logcdf.factory( μ, σ )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a lognormal distribution with mean `μ` and\n    standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.lognormal.logcdf.factory( 10.0, 2.0 );\n    > var y = mylogcdf( 10.0 )\n    ~-9.732","base.dists.lognormal.logpdf":"\nbase.dists.lognormal.logpdf( x, μ, σ )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a lognormal distribution with location parameter `μ` and scale parameter\n    `σ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.logpdf( 2.0, 0.0, 1.0 )\n    ~-1.852\n    > y = base.dists.lognormal.logpdf( 1.0, 0.0, 1.0 )\n    ~-0.919\n    > y = base.dists.lognormal.logpdf( 1.0, 3.0, 1.0 )\n    ~-5.419\n    > y = base.dists.lognormal.logpdf( -1.0, 4.0, 2.0 )\n    -Infinity\n\n    > y = base.dists.lognormal.logpdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.lognormal.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.logpdf( 0.0, 0.0, NaN )\n    NaN\n\n    // Non-positive scale parameter `σ`:\n    > y = base.dists.lognormal.logpdf( 2.0, 0.0, -1.0 )\n    NaN\n    > y = base.dists.lognormal.logpdf( 2.0, 0.0, 0.0 )\n    NaN\n\n\nbase.dists.lognormal.logpdf.factory( μ, σ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a lognormal distribution with location parameter\n    `μ` and scale parameter `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.lognormal.logpdf.factory( 4.0, 2.0 );\n    > var y = mylogPDF( 10.0 )\n    ~-4.275\n    > y = mylogPDF( 2.0 )\n    ~-3.672\n\n","base.dists.lognormal.logpdf.factory":"\nbase.dists.lognormal.logpdf.factory( μ, σ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a lognormal distribution with location parameter\n    `μ` and scale parameter `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.lognormal.logpdf.factory( 4.0, 2.0 );\n    > var y = mylogPDF( 10.0 )\n    ~-4.275\n    > y = mylogPDF( 2.0 )\n    ~-3.672","base.dists.lognormal.mean":"\nbase.dists.lognormal.mean( μ, σ )\n    Returns the expected value of a lognormal distribution with location `μ` and\n    scale `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.mean( 0.0, 1.0 )\n    ~1.649\n    > y = base.dists.lognormal.mean( 4.0, 2.0 )\n    ~403.429\n    > y = base.dists.lognormal.mean( NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.mean( 0.0, NaN )\n    NaN\n    > y = base.dists.lognormal.mean( 0.0, 0.0 )\n    NaN\n\n","base.dists.lognormal.median":"\nbase.dists.lognormal.median( μ, σ )\n    Returns the median of a lognormal distribution with location `μ` and scale\n    `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.median( 0.0, 1.0 )\n    1.0\n    > y = base.dists.lognormal.median( 5.0, 2.0 )\n    ~148.413\n    > y = base.dists.lognormal.median( NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.median( 0.0, NaN )\n    NaN\n    > y = base.dists.lognormal.median( 0.0, 0.0 )\n    NaN\n\n","base.dists.lognormal.mode":"\nbase.dists.lognormal.mode( μ, σ )\n    Returns the mode of a lognormal distribution with location `μ` and scale\n    `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.mode( 0.0, 1.0 )\n    ~0.368\n    > y = base.dists.lognormal.mode( 5.0, 2.0 )\n    ~2.718\n    > y = base.dists.lognormal.mode( NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.mode( 0.0, NaN )\n    NaN\n    > y = base.dists.lognormal.mode( 0.0, 0.0 )\n    NaN\n\n","base.dists.lognormal.pdf":"\nbase.dists.lognormal.pdf( x, μ, σ )\n    Evaluates the probability density function (PDF) for a lognormal\n    distribution with location parameter `μ` and scale parameter `σ` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.pdf( 2.0, 0.0, 1.0 )\n    ~0.157\n    > y = base.dists.lognormal.pdf( 1.0, 0.0, 1.0 )\n    ~0.399\n    > y = base.dists.lognormal.pdf( 1.0, 3.0, 1.0 )\n    ~0.004\n    > y = base.dists.lognormal.pdf( -1.0, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.lognormal.pdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.lognormal.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.pdf( 0.0, 0.0, NaN )\n    NaN\n\n    // Non-positive scale parameter `σ`:\n    > y = base.dists.lognormal.pdf( 2.0, 0.0, -1.0 )\n    NaN\n    > y = base.dists.lognormal.pdf( 2.0, 0.0, 0.0 )\n    NaN\n\n\nbase.dists.lognormal.pdf.factory( μ, σ )\n    Returns a function for evaluating the probability density function (PDF) of\n    a lognormal distribution with location parameter `μ` and scale parameter\n    `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.lognormal.pdf.factory( 4.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    ~0.014\n    > y = myPDF( 2.0 )\n    ~0.025\n\n","base.dists.lognormal.pdf.factory":"\nbase.dists.lognormal.pdf.factory( μ, σ )\n    Returns a function for evaluating the probability density function (PDF) of\n    a lognormal distribution with location parameter `μ` and scale parameter\n    `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.lognormal.pdf.factory( 4.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    ~0.014\n    > y = myPDF( 2.0 )\n    ~0.025","base.dists.lognormal.quantile":"\nbase.dists.lognormal.quantile( p, μ, σ )\n    Evaluates the quantile function for a lognormal distribution with location\n    parameter `μ` and scale parameter `σ` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.quantile( 0.8, 0.0, 1.0 )\n    ~2.32\n    > y = base.dists.lognormal.quantile( 0.5, 4.0, 2.0 )\n    ~54.598\n    > y = base.dists.lognormal.quantile( 1.1, 0.0, 1.0 )\n    NaN\n    > y = base.dists.lognormal.quantile( -0.2, 0.0, 1.0 )\n    NaN\n\n    > y = base.dists.lognormal.quantile( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.lognormal.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.quantile( 0.0, 0.0, NaN )\n    NaN\n\n    // Non-positive scale parameter `σ`:\n    > y = base.dists.lognormal.quantile( 0.5, 0.0, -1.0 )\n    NaN\n    > y = base.dists.lognormal.quantile( 0.5, 0.0, 0.0 )\n    NaN\n\n\nbase.dists.lognormal.quantile.factory( μ, σ )\n    Returns a function for evaluating the quantile function of a lognormal\n    distribution with location parameter `μ` and scale parameter `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.lognormal.quantile.factory( 4.0, 2.0 );\n    > var y = myQuantile( 0.2 )\n    ~10.143\n    > y = myQuantile( 0.8 )\n    ~293.901\n\n","base.dists.lognormal.quantile.factory":"\nbase.dists.lognormal.quantile.factory( μ, σ )\n    Returns a function for evaluating the quantile function of a lognormal\n    distribution with location parameter `μ` and scale parameter `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.lognormal.quantile.factory( 4.0, 2.0 );\n    > var y = myQuantile( 0.2 )\n    ~10.143\n    > y = myQuantile( 0.8 )\n    ~293.901","base.dists.lognormal.skewness":"\nbase.dists.lognormal.skewness( μ, σ )\n    Returns the skewness of a lognormal distribution with location `μ` and scale\n    `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.skewness( 0.0, 1.0 )\n    ~6.185\n    > y = base.dists.lognormal.skewness( 5.0, 2.0 )\n    ~414.359\n    > y = base.dists.lognormal.skewness( NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.skewness( 0.0, NaN )\n    NaN\n    > y = base.dists.lognormal.skewness( 0.0, 0.0 )\n    NaN\n\n","base.dists.lognormal.stdev":"\nbase.dists.lognormal.stdev( μ, σ )\n    Returns the standard deviation of a lognormal distribution with location `μ`\n    and scale `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.stdev( 0.0, 1.0 )\n    ~2.161\n    > y = base.dists.lognormal.stdev( 4.0, 2.0 )\n    ~2953.533\n    > y = base.dists.lognormal.stdev( NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.stdev( 0.0, NaN )\n    NaN\n    > y = base.dists.lognormal.stdev( 0.0, 0.0 )\n    NaN\n\n","base.dists.lognormal.variance":"\nbase.dists.lognormal.variance( μ, σ )\n    Returns the variance of a lognormal distribution with location `μ` and scale\n    `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var y = base.dists.lognormal.variance( 0.0, 1.0 )\n    ~4.671\n    > y = base.dists.lognormal.variance( 4.0, 2.0 )\n    ~8723355.729\n    > y = base.dists.lognormal.variance( NaN, 1.0 )\n    NaN\n    > y = base.dists.lognormal.variance( 0.0, NaN )\n    NaN\n    > y = base.dists.lognormal.variance( 0.0, 0.0 )\n    NaN\n\n","base.dists.negativeBinomial.cdf":"\nbase.dists.negativeBinomial.cdf( x, r, p )\n    Evaluates the cumulative distribution function (CDF) for a negative binomial\n    distribution with number of successes until experiment is stopped `r` and\n    success probability `p` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a `r` which is not a positive number, the function returns\n    `NaN`.\n\n    If provided a success probability `p` outside of `[0,1]`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.negativeBinomial.cdf( 5.0, 20.0, 0.8 )\n    ~0.617\n    > y = base.dists.negativeBinomial.cdf( 21.0, 20.0, 0.5 )\n    ~0.622\n    > y = base.dists.negativeBinomial.cdf( 5.0, 10.0, 0.4 )\n    ~0.034\n    > y = base.dists.negativeBinomial.cdf( 0.0, 10.0, 0.9 )\n    ~0.349\n    > y = base.dists.negativeBinomial.cdf( 21.0, 15.5, 0.5 )\n    ~0.859\n    > y = base.dists.negativeBinomial.cdf( 5.0, 7.4, 0.4 )\n    ~0.131\n\n    > y = base.dists.negativeBinomial.cdf( 2.0, 0.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.cdf( 2.0, -2.0, 0.5 )\n    NaN\n\n    > y = base.dists.negativeBinomial.cdf( NaN, 20.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.cdf( 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.cdf( 0.0, 20.0, NaN )\n    NaN\n\n    > y = base.dists.negativeBinomial.cdf( 2.0, 20, -1.0 )\n    NaN\n    > y = base.dists.negativeBinomial.cdf( 2.0, 20, 1.5 )\n    NaN\n\n\nbase.dists.negativeBinomial.cdf.factory( r, p )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a negative binomial distribution with number of successes until\n    experiment is stopped `r` and success probability `p`.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.negativeBinomial.cdf.factory( 10, 0.5 );\n    > var y = myCDF( 3.0 )\n    ~0.046\n    > y = myCDF( 11.0 )\n    ~0.668\n\n","base.dists.negativeBinomial.cdf.factory":"\nbase.dists.negativeBinomial.cdf.factory( r, p )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a negative binomial distribution with number of successes until\n    experiment is stopped `r` and success probability `p`.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.negativeBinomial.cdf.factory( 10, 0.5 );\n    > var y = myCDF( 3.0 )\n    ~0.046\n    > y = myCDF( 11.0 )\n    ~0.668","base.dists.negativeBinomial.kurtosis":"\nbase.dists.negativeBinomial.kurtosis( r, p )\n    Returns the excess kurtosis of a negative binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a `r` which is not a positive number, the function returns\n    `NaN`.\n\n    If provided a success probability `p` outside of `[0,1]`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    r: integer\n        Number of failures until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.negativeBinomial.kurtosis( 100, 0.2 )\n    ~0.061\n    > v = base.dists.negativeBinomial.kurtosis( 20, 0.5 )\n    ~0.325\n\n","base.dists.negativeBinomial.logpmf":"\nbase.dists.negativeBinomial.logpmf( x, r, p )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    negative binomial distribution with number of successes until experiment is\n    stopped `r` and success probability `p` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a `r` which is not a positive number, the function returns\n    `NaN`.\n\n    If provided a success probability `p` outside of `[0,1]`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPMF.\n\n    Examples\n    --------\n    > var y = base.dists.negativeBinomial.logpmf( 5.0, 20.0, 0.8 )\n    ~-1.853\n    > y = base.dists.negativeBinomial.logpmf( 21.0, 20.0, 0.5 )\n    ~-2.818\n    > y = base.dists.negativeBinomial.logpmf( 5.0, 10.0, 0.4 )\n    ~-4.115\n    > y = base.dists.negativeBinomial.logpmf( 0.0, 10.0, 0.9 )\n    ~-1.054\n    > y = base.dists.negativeBinomial.logpmf( 21.0, 15.5, 0.5 )\n    ~-3.292\n    > y = base.dists.negativeBinomial.logpmf( 5.0, 7.4, 0.4 )\n    ~-2.976\n\n    > y = base.dists.negativeBinomial.logpmf( 2.0, 0.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.logpmf( 2.0, -2.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.logpmf( 2.0, 20, -1.0 )\n    NaN\n    > y = base.dists.negativeBinomial.logpmf( 2.0, 20, 1.5 )\n    NaN\n\n    > y = base.dists.negativeBinomial.logpmf( NaN, 20.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.logpmf( 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.logpmf( 0.0, 20.0, NaN )\n    NaN\n\n\nbase.dists.negativeBinomial.logpmf.factory( r, p )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a negative binomial distribution with number of\n    successes until experiment is stopped `r` and success probability `p`.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogPMF = base.dists.negativeBinomial.logpmf.factory( 10, 0.5 );\n    > var y = mylogPMF( 3.0 )\n    ~-3.617\n    > y = mylogPMF( 5.0 )\n    ~-2.795\n\n","base.dists.negativeBinomial.logpmf.factory":"\nbase.dists.negativeBinomial.logpmf.factory( r, p )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a negative binomial distribution with number of\n    successes until experiment is stopped `r` and success probability `p`.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogPMF = base.dists.negativeBinomial.logpmf.factory( 10, 0.5 );\n    > var y = mylogPMF( 3.0 )\n    ~-3.617\n    > y = mylogPMF( 5.0 )\n    ~-2.795","base.dists.negativeBinomial.mean":"\nbase.dists.negativeBinomial.mean( r, p )\n    Returns the expected value of a negative binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a `r` which is not a positive number, the function returns\n    `NaN`.\n\n    If provided a success probability `p` outside of `[0,1]`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    r: integer\n        Number of failures until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.negativeBinomial.mean( 100, 0.2 )\n    400\n    > v = base.dists.negativeBinomial.mean( 20, 0.5 )\n    20\n\n","base.dists.negativeBinomial.mgf":"\nbase.dists.negativeBinomial.mgf( x, r, p )\n    Evaluates the moment-generating function (MGF) for a negative binomial\n    distribution with number of successes until experiment is stopped `r` and\n    success probability `p` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a `r` which is not a positive number, the function returns\n    `NaN`.\n\n    If provided a success probability `p` outside of `[0,1]`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.negativeBinomial.mgf( 0.05, 20.0, 0.8 )\n    ~267.839\n    > y = base.dists.negativeBinomial.mgf( 0.1, 20.0, 0.1 )\n    ~9.347\n    > y = base.dists.negativeBinomial.mgf( 0.5, 10.0, 0.4 )\n    ~42822.023\n\n    > y = base.dists.negativeBinomial.mgf( 0.1, 0.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.mgf( 0.1, -2.0, 0.5 )\n    NaN\n\n    > y = base.dists.negativeBinomial.mgf( NaN, 20.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.mgf( 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.mgf( 0.0, 20.0, NaN )\n    NaN\n\n    > y = base.dists.negativeBinomial.mgf( 0.2, 20, -1.0 )\n    NaN\n    > y = base.dists.negativeBinomial.mgf( 0.2, 20, 1.5 )\n    NaN\n\n\nbase.dists.negativeBinomial.mgf.factory( r, p )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    negative binomial distribution with number of successes until experiment is\n    stopped `r` and success probability `p`.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.negativeBinomial.mgf.factory( 4.3, 0.4 );\n    > var y = myMGF( 0.2 )\n    ~4.696\n    > y = myMGF( 0.4 )\n    ~30.83\n\n","base.dists.negativeBinomial.mgf.factory":"\nbase.dists.negativeBinomial.mgf.factory( r, p )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    negative binomial distribution with number of successes until experiment is\n    stopped `r` and success probability `p`.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.negativeBinomial.mgf.factory( 4.3, 0.4 );\n    > var y = myMGF( 0.2 )\n    ~4.696\n    > y = myMGF( 0.4 )\n    ~30.83","base.dists.negativeBinomial.mode":"\nbase.dists.negativeBinomial.mode( r, p )\n    Returns the mode of a negative binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a `r` which is not a positive number, the function returns\n    `NaN`.\n\n    If provided a success probability `p` outside of `[0,1]`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    r: integer\n        Number of failures until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.negativeBinomial.mode( 100, 0.2 )\n    396\n    > v = base.dists.negativeBinomial.mode( 20, 0.5 )\n    19\n\n","base.dists.negativeBinomial.NegativeBinomial":"\nbase.dists.negativeBinomial.NegativeBinomial( [r, p] )\n    Returns a negative binomial distribution object.\n\n    Parameters\n    ----------\n    r: number (optional)\n        Number of successes until experiment is stopped. Must be a positive\n        number. Default: `1`.\n\n    p: number (optional)\n        Success probability. Must be a number between `0` and `1`. Default:\n        `0.5`.\n\n    Returns\n    -------\n    nbinomial: Object\n        Distribution instance.\n\n    nbinomial.r: number\n        Number of trials. If set, the value must be a positive number.\n\n    nbinomial.p: number\n        Success probability. If set, the value must be a number between `0` and\n        `1`.\n\n    nbinomial.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    nbinomial.mean: number\n        Read-only property which returns the expected value.\n\n    nbinomial.mode: number\n        Read-only property which returns the mode.\n\n    nbinomial.skewness: number\n        Read-only property which returns the skewness.\n\n    nbinomial.stdev: number\n        Read-only property which returns the standard deviation.\n\n    nbinomial.variance: number\n        Read-only property which returns the variance.\n\n    nbinomial.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    nbinomial.logpmf: Function\n        Evaluates the natural logarithm of the probability mass function (PMF).\n\n    nbinomial.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    nbinomial.pmf: Function\n        Evaluates the probability mass function (PMF).\n\n    nbinomial.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var nbinomial = base.dists.negativeBinomial.NegativeBinomial( 8.0, 0.5 );\n    > nbinomial.r\n    8.0\n    > nbinomial.p\n    0.5\n    > nbinomial.kurtosis\n    0.8125\n    > nbinomial.mean\n    8.0\n    > nbinomial.mode\n    7.0\n    > nbinomial.skewness\n    0.75\n    > nbinomial.stdev\n    4.0\n    > nbinomial.variance\n    16.0\n    > nbinomial.cdf( 2.9 )\n    ~0.055\n    > nbinomial.logpmf( 3.0 )\n    ~-2.837\n    > nbinomial.mgf( 0.2 )\n    ~36.675\n    > nbinomial.pmf( 3.0 )\n    ~0.059\n    > nbinomial.quantile( 0.8 )\n    11.0\n\n","base.dists.negativeBinomial.pmf":"\nbase.dists.negativeBinomial.pmf( x, r, p )\n    Evaluates the probability mass function (PMF) for a negative binomial\n    distribution with number of successes until experiment is stopped `r` and\n    success probability `p` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a `r` which is not a positive number, the function returns\n    `NaN`.\n\n    If provided a success probability `p` outside of `[0,1]`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated PMF.\n\n    Examples\n    --------\n    > var y = base.dists.negativeBinomial.pmf( 5.0, 20.0, 0.8 )\n    ~0.157\n    > y = base.dists.negativeBinomial.pmf( 21.0, 20.0, 0.5 )\n    ~0.06\n    > y = base.dists.negativeBinomial.pmf( 5.0, 10.0, 0.4 )\n    ~0.016\n    > y = base.dists.negativeBinomial.pmf( 0.0, 10.0, 0.9 )\n    ~0.349\n    > y = base.dists.negativeBinomial.pmf( 21.0, 15.5, 0.5 )\n    ~0.037\n    > y = base.dists.negativeBinomial.pmf( 5.0, 7.4, 0.4 )\n    ~0.051\n\n    > y = base.dists.negativeBinomial.pmf( 2.0, 0.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.pmf( 2.0, -2.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.pmf( 2.0, 20, -1.0 )\n    NaN\n    > y = base.dists.negativeBinomial.pmf( 2.0, 20, 1.5 )\n    NaN\n\n    > y = base.dists.negativeBinomial.pmf( NaN, 20.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.pmf( 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.pmf( 0.0, 20.0, NaN )\n    NaN\n\n\nbase.dists.negativeBinomial.pmf.factory( r, p )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    negative binomial distribution with number of successes until experiment is\n    stopped `r` and success probability `p`.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var myPMF = base.dists.negativeBinomial.pmf.factory( 10, 0.5 );\n    > var y = myPMF( 3.0 )\n    ~0.027\n    > y = myPMF( 5.0 )\n    ~0.061\n\n","base.dists.negativeBinomial.pmf.factory":"\nbase.dists.negativeBinomial.pmf.factory( r, p )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    negative binomial distribution with number of successes until experiment is\n    stopped `r` and success probability `p`.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var myPMF = base.dists.negativeBinomial.pmf.factory( 10, 0.5 );\n    > var y = myPMF( 3.0 )\n    ~0.027\n    > y = myPMF( 5.0 )\n    ~0.061","base.dists.negativeBinomial.quantile":"\nbase.dists.negativeBinomial.quantile( k, r, p )\n    Evaluates the quantile function for a negative binomial distribution with\n    number of successes until experiment is stopped `r` and success probability\n    `p` at a probability `k`.\n\n    If provided a `k` outside of `[0,1]`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a `r` which is not a positive number, the function returns\n    `NaN`.\n\n    If provided a success probability `p` outside of `[0,1]`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Input probability.\n\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.2 )\n    106\n    > y = base.dists.negativeBinomial.quantile( 0.9, 20.0, 0.8 )\n    8\n    > y = base.dists.negativeBinomial.quantile( 0.5, 10.0, 0.4 )\n    14\n    > y = base.dists.negativeBinomial.quantile( 0.0, 10.0, 0.9 )\n    0\n\n    > y = base.dists.negativeBinomial.quantile( 1.1, 20.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.quantile( -0.1, 20.0, 0.5 )\n    NaN\n\n    > y = base.dists.negativeBinomial.quantile( 21.0, 15.5, 0.5 )\n    12\n    > y = base.dists.negativeBinomial.quantile( 5.0, 7.4, 0.4 )\n    10\n\n    > y = base.dists.negativeBinomial.quantile( 0.5, 0.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.quantile( 0.5, -2.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, -1.0 )\n    NaN\n    > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, 1.5 )\n    NaN\n\n    > y = base.dists.negativeBinomial.quantile( NaN, 20.0, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.quantile( 0.3, NaN, 0.5 )\n    NaN\n    > y = base.dists.negativeBinomial.quantile( 0.3, 20.0, NaN )\n    NaN\n\n\nbase.dists.negativeBinomial.quantile.factory( r, p )\n    Returns a function for evaluating the quantile function of a negative\n    binomial distribution with number of successes until experiment is stopped\n    `r` and success probability `p`.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.negativeBinomial.quantile.factory( 10.0, 0.5 );\n    > var y = myQuantile( 0.1 )\n    5\n    > y = myQuantile( 0.9 )\n    16\n\n","base.dists.negativeBinomial.quantile.factory":"\nbase.dists.negativeBinomial.quantile.factory( r, p )\n    Returns a function for evaluating the quantile function of a negative\n    binomial distribution with number of successes until experiment is stopped\n    `r` and success probability `p`.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.negativeBinomial.quantile.factory( 10.0, 0.5 );\n    > var y = myQuantile( 0.1 )\n    5\n    > y = myQuantile( 0.9 )\n    16","base.dists.negativeBinomial.skewness":"\nbase.dists.negativeBinomial.skewness( r, p )\n    Returns the skewness of a negative binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a `r` which is not a positive number, the function returns\n    `NaN`.\n\n    If provided a success probability `p` outside of `[0,1]`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    r: integer\n        Number of failures until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.negativeBinomial.skewness( 100, 0.2 )\n    ~0.201\n    > v = base.dists.negativeBinomial.skewness( 20, 0.5 )\n    ~0.474\n\n","base.dists.negativeBinomial.stdev":"\nbase.dists.negativeBinomial.stdev( r, p )\n    Returns the standard deviation of a negative binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a `r` which is not a positive number, the function returns\n    `NaN`.\n\n    If provided a success probability `p` outside of `[0,1]`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    r: integer\n        Number of failures until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.negativeBinomial.stdev( 100, 0.2 )\n    ~44.721\n    > v = base.dists.negativeBinomial.stdev( 20, 0.5 )\n    ~6.325\n\n","base.dists.negativeBinomial.variance":"\nbase.dists.negativeBinomial.variance( r, p )\n    Returns the variance of a negative binomial distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a `r` which is not a positive number, the function returns\n    `NaN`.\n\n    If provided a success probability `p` outside of `[0,1]`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    r: integer\n        Number of failures until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.negativeBinomial.variance( 100, 0.2 )\n    2000.0\n    > v = base.dists.negativeBinomial.variance( 20, 0.5 )\n    40.0\n\n","base.dists.normal.cdf":"\nbase.dists.normal.cdf( x, μ, σ )\n    Evaluates the cumulative distribution function (CDF) for a normal\n    distribution with mean `μ` and standard deviation `σ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.normal.cdf( 2.0, 0.0, 1.0 )\n    ~0.977\n    > y = base.dists.normal.cdf( -1.0, -1.0, 2.0 )\n    0.5\n    > y = base.dists.normal.cdf( -1.0, 4.0, 2.0 )\n    ~0.006\n    > y = base.dists.normal.cdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.normal.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.cdf( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative standard deviation:\n    > y = base.dists.normal.cdf( 2.0, 0.0, -1.0 )\n    NaN\n\n    // Degenerate distribution centered at `μ` when `σ = 0.0`:\n    > y = base.dists.normal.cdf( 2.0, 8.0, 0.0 )\n    0.0\n    > y = base.dists.normal.cdf( 8.0, 8.0, 0.0 )\n    1.0\n    > y = base.dists.normal.cdf( 10.0, 8.0, 0.0 )\n    1.0\n\n\nbase.dists.normal.cdf.factory( μ, σ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a normal distribution with mean `μ` and standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.normal.cdf.factory( 10.0, 2.0 );\n    > var y = myCDF( 10.0 )\n    0.5\n\n","base.dists.normal.cdf.factory":"\nbase.dists.normal.cdf.factory( μ, σ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a normal distribution with mean `μ` and standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.normal.cdf.factory( 10.0, 2.0 );\n    > var y = myCDF( 10.0 )\n    0.5","base.dists.normal.entropy":"\nbase.dists.normal.entropy( μ, σ )\n    Returns the differential entropy of a normal distribution with mean `μ` and\n    standard deviation `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var y = base.dists.normal.entropy( 0.0, 1.0 )\n    ~1.419\n    > y = base.dists.normal.entropy( 4.0, 3.0 )\n    ~2.518\n    > y = base.dists.normal.entropy( NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.entropy( 0.0, NaN )\n    NaN\n    > y = base.dists.normal.entropy( 0.0, 0.0 )\n    NaN\n\n","base.dists.normal.kurtosis":"\nbase.dists.normal.kurtosis( μ, σ )\n    Returns the excess kurtosis of a normal distribution with mean `μ` and\n    standard deviation `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var y = base.dists.normal.kurtosis( 0.0, 1.0 )\n    0.0\n    > y = base.dists.normal.kurtosis( 4.0, 3.0 )\n    0.0\n    > y = base.dists.normal.kurtosis( NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.kurtosis( 0.0, NaN )\n    NaN\n    > y = base.dists.normal.kurtosis( 0.0, 0.0 )\n    NaN\n\n","base.dists.normal.logcdf":"\nbase.dists.normal.logcdf( x, μ, σ )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a normal distribution with mean `μ` and standard deviation `σ` at\n    a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Evaluated logcdf.\n\n    Examples\n    --------\n    > var y = base.dists.normal.logcdf( 2.0, 0.0, 1.0 )\n    ~-0.023\n    > y = base.dists.normal.logcdf( -1.0, 4.0, 2.0 )\n    ~-5.082\n    > y = base.dists.normal.logcdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.normal.logcdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.logcdf( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative standard deviation:\n    > y = base.dists.normal.logcdf( 2.0, 0.0, -1.0 )\n    NaN\n\n    // Degenerate distribution centered at `μ` when `σ = 0.0`:\n    > y = base.dists.normal.logcdf( 2.0, 8.0, 0.0 )\n    -Infinity\n    > y = base.dists.normal.logcdf( 8.0, 8.0, 0.0 )\n    0.0\n\n\nbase.dists.normal.logcdf.factory( μ, σ )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a normal distribution with mean `μ` and\n    standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.normal.logcdf.factory( 10.0, 2.0 );\n    > var y = mylogcdf( 10.0 )\n    ~-0.693\n\n","base.dists.normal.logcdf.factory":"\nbase.dists.normal.logcdf.factory( μ, σ )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a normal distribution with mean `μ` and\n    standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.normal.logcdf.factory( 10.0, 2.0 );\n    > var y = mylogcdf( 10.0 )\n    ~-0.693","base.dists.normal.logpdf":"\nbase.dists.normal.logpdf( x, μ, σ )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a normal distribution with mean `μ` and standard deviation `σ` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.normal.logpdf( 2.0, 0.0, 1.0 )\n    ~-2.919\n    > y = base.dists.normal.logpdf( -1.0, 4.0, 2.0 )\n    ~-4.737\n    > y = base.dists.normal.logpdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.normal.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.logpdf( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative standard deviation:\n    > y = base.dists.normal.logpdf( 2.0, 0.0, -1.0 )\n    NaN\n\n    // Degenerate distribution centered at `μ` when `σ = 0.0`:\n    > y = base.dists.normal.logpdf( 2.0, 8.0, 0.0 )\n    -Infinity\n    > y = base.dists.normal.logpdf( 8.0, 8.0, 0.0 )\n    Infinity\n\n\nbase.dists.normal.logpdf.factory( μ, σ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a normal distribution with mean `μ` and standard\n    deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var myLogPDF = base.dists.normal.logpdf.factory( 10.0, 2.0 );\n    > var y = myLogPDF( 10.0 )\n    ~-1.612\n\n","base.dists.normal.logpdf.factory":"\nbase.dists.normal.logpdf.factory( μ, σ )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a normal distribution with mean `μ` and standard\n    deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var myLogPDF = base.dists.normal.logpdf.factory( 10.0, 2.0 );\n    > var y = myLogPDF( 10.0 )\n    ~-1.612","base.dists.normal.mean":"\nbase.dists.normal.mean( μ, σ )\n    Returns the expected value of a normal distribution with mean `μ` and\n    standard deviation `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var y = base.dists.normal.mean( 0.0, 1.0 )\n    0.0\n    > y = base.dists.normal.mean( 4.0, 2.0 )\n    4.0\n    > y = base.dists.normal.mean( NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.mean( 0.0, NaN )\n    NaN\n    > y = base.dists.normal.mean( 0.0, 0.0 )\n    NaN\n\n","base.dists.normal.median":"\nbase.dists.normal.median( μ, σ )\n    Returns the median of a normal distribution with mean `μ` and standard\n    deviation `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var y = base.dists.normal.median( 0.0, 1.0 )\n    0.0\n    > y = base.dists.normal.median( 4.0, 2.0 )\n    4.0\n    > y = base.dists.normal.median( NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.median( 0.0, NaN )\n    NaN\n    > y = base.dists.normal.median( 0.0, 0.0 )\n    NaN\n\n","base.dists.normal.mgf":"\nbase.dists.normal.mgf( x, μ, σ )\n    Evaluates the moment-generating function (MGF) for a normal distribution\n    with mean `μ` and standard deviation `σ` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.normal.mgf( 2.0, 0.0, 1.0 )\n    ~7.389\n    > y = base.dists.normal.mgf( 0.0, 0.0, 1.0 )\n    1.0\n    > y = base.dists.normal.mgf( -1.0, 4.0, 2.0 )\n    ~0.1353\n    > y = base.dists.normal.mgf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.normal.mgf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.mgf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.normal.mgf( 2.0, 0.0, 0.0 )\n    NaN\n\n\nbase.dists.normal.mgf.factory( μ, σ )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    normal distribution with mean `μ` and standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.normal.mgf.factory( 4.0, 2.0 );\n    > var y = myMGF( 1.0 )\n    ~403.429\n    > y = myMGF( 0.5 )\n    ~12.182\n\n","base.dists.normal.mgf.factory":"\nbase.dists.normal.mgf.factory( μ, σ )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    normal distribution with mean `μ` and standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.normal.mgf.factory( 4.0, 2.0 );\n    > var y = myMGF( 1.0 )\n    ~403.429\n    > y = myMGF( 0.5 )\n    ~12.182","base.dists.normal.mode":"\nbase.dists.normal.mode( μ, σ )\n    Returns the mode of a normal distribution with mean `μ` and standard\n    deviation `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var y = base.dists.normal.mode( 0.0, 1.0 )\n    0.0\n    > y = base.dists.normal.mode( 4.0, 2.0 )\n    4.0\n    > y = base.dists.normal.mode( NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.mode( 0.0, NaN )\n    NaN\n    > y = base.dists.normal.mode( 0.0, 0.0 )\n    NaN\n\n","base.dists.normal.Normal":"\nbase.dists.normal.Normal( [μ, σ] )\n    Returns a normal distribution object.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean parameter. Default: `0.0`.\n\n    σ: number (optional)\n        Standard deviation. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    normal: Object\n        Distribution instance.\n\n    normal.mu: number\n        Mean parameter.\n\n    normal.sigma: number\n        Standard deviation. If set, the value must be greater than `0`.\n\n    normal.entropy: number\n        Read-only property which returns the differential entropy.\n\n    normal.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    normal.mean: number\n        Read-only property which returns the expected value.\n\n    normal.median: number\n        Read-only property which returns the median.\n\n    normal.mode: number\n        Read-only property which returns the mode.\n\n    normal.skewness: number\n        Read-only property which returns the skewness.\n\n    normal.stdev: number\n        Read-only property which returns the standard deviation.\n\n    normal.variance: number\n        Read-only property which returns the variance.\n\n    normal.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    normal.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    normal.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    normal.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    normal.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    normal.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var normal = base.dists.normal.Normal( -2.0, 3.0 );\n    > normal.mu\n    -2.0\n    > normal.sigma\n    3.0\n    > normal.entropy\n    ~2.518\n    > normal.kurtosis\n    0.0\n    > normal.mean\n    -2.0\n    > normal.median\n    -2.0\n    > normal.mode\n    -2.0\n    > normal.skewness\n    0.0\n    > normal.stdev\n    3.0\n    > normal.variance\n    9.0\n    > normal.cdf( 0.8 )\n    ~0.825\n    > normal.logcdf( 0.8 )\n    ~-0.193\n    > normal.logpdf( 2.0 )\n    ~-2.9\n    > normal.mgf( 0.2 )\n    ~0.803\n    > normal.pdf( 2.0 )\n    ~0.055\n    > normal.quantile( 0.9 )\n    ~1.845\n\n","base.dists.normal.pdf":"\nbase.dists.normal.pdf( x, μ, σ )\n    Evaluates the probability density function (PDF) for a normal distribution\n    with mean `μ` and standard deviation `σ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.normal.pdf( 2.0, 0.0, 1.0 )\n    ~0.054\n    > y = base.dists.normal.pdf( -1.0, 4.0, 2.0 )\n    ~0.009\n    > y = base.dists.normal.pdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.normal.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.pdf( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative standard deviation:\n    > y = base.dists.normal.pdf( 2.0, 0.0, -1.0 )\n    NaN\n\n    // Degenerate distribution centered at `μ` when `σ = 0.0`:\n    > y = base.dists.normal.pdf( 2.0, 8.0, 0.0 )\n    0.0\n    > y = base.dists.normal.pdf( 8.0, 8.0, 0.0 )\n    infinity\n\n\nbase.dists.normal.pdf.factory( μ, σ )\n    Returns a function for evaluating the probability density function (PDF) of\n    a normal distribution with mean `μ` and standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.normal.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    ~0.199\n\n","base.dists.normal.pdf.factory":"\nbase.dists.normal.pdf.factory( μ, σ )\n    Returns a function for evaluating the probability density function (PDF) of\n    a normal distribution with mean `μ` and standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.normal.pdf.factory( 10.0, 2.0 );\n    > var y = myPDF( 10.0 )\n    ~0.199","base.dists.normal.quantile":"\nbase.dists.normal.quantile( p, μ, σ )\n    Evaluates the quantile function for a normal distribution with mean `μ` and\n    standard deviation `σ` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.normal.quantile( 0.8, 0.0, 1.0 )\n    ~0.842\n    > y = base.dists.normal.quantile( 0.5, 4.0, 2.0 )\n    4\n\n    > y = base.dists.normal.quantile( 1.1, 0.0, 1.0 )\n    NaN\n    > y = base.dists.normal.quantile( -0.2, 0.0, 1.0 )\n    NaN\n\n    > y = base.dists.normal.quantile( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.normal.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.quantile( 0.0, 0.0, NaN )\n    NaN\n\n    // Negative standard deviation:\n    > y = base.dists.normal.quantile( 0.5, 0.0, -1.0 )\n    NaN\n\n    // Degenerate distribution centered at `μ` when `σ = 0.0`:\n    > y = base.dists.normal.quantile( 0.3, 8.0, 0.0 )\n    8.0\n    > y = base.dists.normal.quantile( 0.9, 8.0, 0.0 )\n    8.0\n\n\nbase.dists.normal.quantile.factory( μ, σ )\n    Returns a function for evaluating the quantile function\n    of a normal distribution with mean `μ` and standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.normal.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    10.0\n\n","base.dists.normal.quantile.factory":"\nbase.dists.normal.quantile.factory( μ, σ )\n    Returns a function for evaluating the quantile function\n    of a normal distribution with mean `μ` and standard deviation `σ`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.normal.quantile.factory( 10.0, 2.0 );\n    > var y = myQuantile( 0.5 )\n    10.0","base.dists.normal.skewness":"\nbase.dists.normal.skewness( μ, σ )\n    Returns the skewness of a normal distribution with mean `μ` and standard\n    deviation `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var y = base.dists.normal.skewness( 0.0, 1.0 )\n    0.0\n    > y = base.dists.normal.skewness( 4.0, 3.0 )\n    0.0\n    > y = base.dists.normal.skewness( NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.skewness( 0.0, NaN )\n    NaN\n    > y = base.dists.normal.skewness( 0.0, 0.0 )\n    NaN\n\n","base.dists.normal.stdev":"\nbase.dists.normal.stdev( μ, σ )\n    Returns the standard deviation of a normal distribution with mean `μ` and\n    standard deviation `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var y = base.dists.normal.stdev( 0.0, 1.0 )\n    1.0\n    > y = base.dists.normal.stdev( 4.0, 3.0 )\n    3.0\n    > y = base.dists.normal.stdev( NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.stdev( 0.0, NaN )\n    NaN\n    > y = base.dists.normal.stdev( 0.0, 0.0 )\n    NaN\n\n","base.dists.normal.variance":"\nbase.dists.normal.variance( μ, σ )\n    Returns the variance of a normal distribution with mean `μ` and standard\n    deviation `σ`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var y = base.dists.normal.variance( 0.0, 1.0 )\n    1.0\n    > y = base.dists.normal.variance( 4.0, 3.0 )\n    9.0\n    > y = base.dists.normal.variance( NaN, 1.0 )\n    NaN\n    > y = base.dists.normal.variance( 0.0, NaN )\n    NaN\n    > y = base.dists.normal.variance( 0.0, 0.0 )\n    NaN\n\n","base.dists.pareto1.cdf":"\nbase.dists.pareto1.cdf( x, α, β )\n    Evaluates the cumulative distribution function (CDF) for a Pareto (Type I)\n    distribution with shape parameter `α` and scale parameter `β` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.pareto1.cdf( 2.0, 1.0, 1.0 )\n    0.5\n    > y = base.dists.pareto1.cdf( 5.0, 2.0, 4.0 )\n    ~0.36\n    > y = base.dists.pareto1.cdf( 4.0, 2.0, 2.0 )\n    0.75\n    > y = base.dists.pareto1.cdf( 1.9, 2.0, 2.0 )\n    0.0\n    > y = base.dists.pareto1.cdf( PINF, 4.0, 2.0 )\n    1.0\n\n    > y = base.dists.pareto1.cdf( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.pareto1.cdf( 2.0, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.pareto1.cdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.pareto1.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.pareto1.cdf( 0.0, 1.0, NaN )\n    NaN\n\n\nbase.dists.pareto1.cdf.factory( α, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Pareto (Type I) distribution with shape parameter `α` and scale\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.pareto1.cdf.factory( 10.0, 2.0 );\n    > var y = myCDF( 3.0 )\n    ~0.983\n    > y = myCDF( 2.5 )\n    ~0.893\n\n","base.dists.pareto1.cdf.factory":"\nbase.dists.pareto1.cdf.factory( α, β )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Pareto (Type I) distribution with shape parameter `α` and scale\n    parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.pareto1.cdf.factory( 10.0, 2.0 );\n    > var y = myCDF( 3.0 )\n    ~0.983\n    > y = myCDF( 2.5 )\n    ~0.893","base.dists.pareto1.entropy":"\nbase.dists.pareto1.entropy( α, β )\n    Returns the differential entropy of a Pareto (Type I) distribution\n    (in nats).\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Differential entropy.\n\n    Examples\n    --------\n    > var v = base.dists.pareto1.entropy( 0.8, 1.0 )\n    ~2.473\n    > v = base.dists.pareto1.entropy( 4.0, 12.0 )\n    ~2.349\n    > v = base.dists.pareto1.entropy( 8.0, 2.0 )\n    ~-0.261\n\n","base.dists.pareto1.kurtosis":"\nbase.dists.pareto1.kurtosis( α, β )\n    Returns the excess kurtosis of a Pareto (Type I) distribution.\n\n    If `α <= 4` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.pareto1.kurtosis( 5.0, 1.0 )\n    ~70.8\n    > v = base.dists.pareto1.kurtosis( 4.5, 12.0 )\n    ~146.444\n    > v = base.dists.pareto1.kurtosis( 8.0, 2.0 )\n    ~19.725\n\n","base.dists.pareto1.logcdf":"\nbase.dists.pareto1.logcdf( x, α, β )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a Pareto (Type I) distribution with shape parameter `α` and scale\n    parameter `β` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.pareto1.logcdf( 2.0, 1.0, 1.0 )\n    ~-0.693\n    > y = base.dists.pareto1.logcdf( 5.0, 2.0, 4.0 )\n    ~-1.022\n    > y = base.dists.pareto1.logcdf( 4.0, 2.0, 2.0 )\n    ~-0.288\n    > y = base.dists.pareto1.logcdf( 1.9, 2.0, 2.0 )\n    -Infinity\n    > y = base.dists.pareto1.logcdf( PINF, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.pareto1.logcdf( 2.0, -1.0, 0.5 )\n    NaN\n    > y = base.dists.pareto1.logcdf( 2.0, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.pareto1.logcdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.pareto1.logcdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.pareto1.logcdf( 0.0, 1.0, NaN )\n    NaN\n\n\nbase.dists.pareto1.logcdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Pareto (Type I) distribution with shape\n    parameter `α` and scale parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogCDF = base.dists.pareto1.logcdf.factory( 10.0, 2.0 );\n    > var y = mylogCDF( 3.0 )\n    ~-0.017\n    > y = mylogCDF( 2.5 )\n    ~-0.114\n\n","base.dists.pareto1.logcdf.factory":"\nbase.dists.pareto1.logcdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Pareto (Type I) distribution with shape\n    parameter `α` and scale parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogCDF = base.dists.pareto1.logcdf.factory( 10.0, 2.0 );\n    > var y = mylogCDF( 3.0 )\n    ~-0.017\n    > y = mylogCDF( 2.5 )\n    ~-0.114","base.dists.pareto1.logpdf":"\nbase.dists.pareto1.logpdf( x, α, β )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a Pareto (Type I) distribution with shape parameter `α` and scale\n    parameter `β` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.pareto1.logpdf( 4.0, 1.0, 1.0 )\n    ~-2.773\n    > y = base.dists.pareto1.logpdf( 20.0, 1.0, 10.0 )\n    ~-3.689\n    > y = base.dists.pareto1.logpdf( 7.0, 2.0, 6.0 )\n    ~-1.561\n    > y = base.dists.pareto1.logpdf( 7.0, 6.0, 3.0 )\n    ~-5.238\n    > y = base.dists.pareto1.logpdf( 1.0, 4.0, 2.0 )\n    -Infinity\n    > y = base.dists.pareto1.logpdf( 1.5, 4.0, 2.0 )\n    -Infinity\n\n    > y = base.dists.pareto1.logpdf( 0.5, -1.0, 0.5 )\n    NaN\n    > y = base.dists.pareto1.logpdf( 0.5, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.pareto1.logpdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.pareto1.logpdf( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.dists.pareto1.logpdf( 0.5, 1.0, NaN )\n    NaN\n\n\nbase.dists.pareto1.logpdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a Pareto (Type I) distribution with shape\n    parameter `α` and scale parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.pareto1.logpdf.factory( 0.5, 0.5 );\n    > var y = mylogPDF( 0.8 )\n    ~-0.705\n    > y = mylogPDF( 2.0 )\n    ~-2.079\n\n","base.dists.pareto1.logpdf.factory":"\nbase.dists.pareto1.logpdf.factory( α, β )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a Pareto (Type I) distribution with shape\n    parameter `α` and scale parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.pareto1.logpdf.factory( 0.5, 0.5 );\n    > var y = mylogPDF( 0.8 )\n    ~-0.705\n    > y = mylogPDF( 2.0 )\n    ~-2.079","base.dists.pareto1.mean":"\nbase.dists.pareto1.mean( α, β )\n    Returns the expected value of a Pareto (Type I) distribution.\n\n    If `0 < α <= 1`, the function returns `Infinity`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.pareto1.mean( 0.8, 1.0 )\n    Infinity\n    > v = base.dists.pareto1.mean( 4.0, 12.0 )\n    16.0\n    > v = base.dists.pareto1.mean( 8.0, 2.0 )\n    ~2.286\n\n","base.dists.pareto1.median":"\nbase.dists.pareto1.median( α, β )\n    Returns the median of a Pareto (Type I) distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.pareto1.median( 0.8, 1.0 )\n    ~2.378\n    > v = base.dists.pareto1.median( 4.0, 12.0 )\n    ~14.27\n    > v = base.dists.pareto1.median( 8.0, 2.0 )\n    ~2.181\n\n","base.dists.pareto1.mode":"\nbase.dists.pareto1.mode( α, β )\n    Returns the mode of a Pareto (Type I) distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.pareto1.mode( 0.8, 1.0 )\n    1.0\n    > v = base.dists.pareto1.mode( 4.0, 12.0 )\n    12.0\n    > v = base.dists.pareto1.mode( 8.0, 2.0 )\n    2.0\n\n","base.dists.pareto1.Pareto1":"\nbase.dists.pareto1.Pareto1( [α, β] )\n    Returns a Pareto (Type I) distribution object.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n    β: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    pareto1: Object\n        Distribution instance.\n\n    pareto1.alpha: number\n        Shape parameter. If set, the value must be greater than `0`.\n\n    pareto1.beta: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    pareto1.entropy: number\n        Read-only property which returns the differential entropy.\n\n    pareto1.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    pareto1.mean: number\n        Read-only property which returns the expected value.\n\n    pareto1.median: number\n        Read-only property which returns the median.\n\n    pareto1.mode: number\n        Read-only property which returns the mode.\n\n    pareto1.skewness: number\n        Read-only property which returns the skewness.\n\n    pareto1.variance: number\n        Read-only property which returns the variance.\n\n    pareto1.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    pareto1.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (logCDF).\n\n    pareto1.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (logPDF).\n\n    pareto1.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    pareto1.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var pareto1 = base.dists.pareto1.Pareto1( 6.0, 5.0 );\n    > pareto1.alpha\n    6.0\n    > pareto1.beta\n    5.0\n    > pareto1.entropy\n    ~0.984\n    > pareto1.kurtosis\n    ~35.667\n    > pareto1.mean\n    6.0\n    > pareto1.median\n    ~5.612\n    > pareto1.mode\n    5.0\n    > pareto1.skewness\n    ~3.81\n    > pareto1.variance\n    1.5\n    > pareto1.cdf( 7.0 )\n    ~0.867\n    > pareto1.logcdf( 7.0 )\n    ~-0.142\n    > pareto1.logpdf( 5.0 )\n    ~0.182\n    > pareto1.pdf( 5.0 )\n    1.2\n    > pareto1.quantile( 0.8 )\n    ~6.538\n\n","base.dists.pareto1.pdf":"\nbase.dists.pareto1.pdf( x, α, β )\n    Evaluates the probability density function (PDF) for a Pareto (Type I)\n    distribution with shape parameter `α` and scale parameter `β` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.pareto1.pdf( 4.0, 1.0, 1.0 )\n    ~0.063\n    > y = base.dists.pareto1.pdf( 20.0, 1.0, 10.0 )\n    0.025\n    > y = base.dists.pareto1.pdf( 7.0, 2.0, 6.0 )\n    ~0.21\n    > y = base.dists.pareto1.pdf( 7.0, 6.0, 3.0 )\n    ~0.005\n    > y = base.dists.pareto1.pdf( 1.0, 4.0, 2.0 )\n    0.0\n    > y = base.dists.pareto1.pdf( 1.5, 4.0, 2.0 )\n    0.0\n\n    > y = base.dists.pareto1.pdf( 0.5, -1.0, 0.5 )\n    NaN\n    > y = base.dists.pareto1.pdf( 0.5, 0.5, -1.0 )\n    NaN\n\n    > y = base.dists.pareto1.pdf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.pareto1.pdf( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.dists.pareto1.pdf( 0.5, 1.0, NaN )\n    NaN\n\n\nbase.dists.pareto1.pdf.factory( α, β )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Pareto (Type I) distribution with shape parameter `α` and scale parameter\n    `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.pareto1.pdf.factory( 0.5, 0.5 );\n    > var y = myPDF( 0.8 )\n    ~0.494\n    > y = myPDF( 2.0 )\n    ~0.125\n\n","base.dists.pareto1.pdf.factory":"\nbase.dists.pareto1.pdf.factory( α, β )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Pareto (Type I) distribution with shape parameter `α` and scale parameter\n    `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.pareto1.pdf.factory( 0.5, 0.5 );\n    > var y = myPDF( 0.8 )\n    ~0.494\n    > y = myPDF( 2.0 )\n    ~0.125","base.dists.pareto1.quantile":"\nbase.dists.pareto1.quantile( p, α, β )\n    Evaluates the quantile function for a Pareto (Type I) distribution with\n    shape parameter `α` and scale parameter `β` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.pareto1.quantile( 0.8, 2.0, 1.0 )\n    ~2.236\n    > y = base.dists.pareto1.quantile( 0.8, 1.0, 10.0 )\n    ~50.0\n    > y = base.dists.pareto1.quantile( 0.1, 1.0, 10.0 )\n    ~11.111\n\n    > y = base.dists.pareto1.quantile( 1.1, 1.0, 1.0 )\n    NaN\n    > y = base.dists.pareto1.quantile( -0.2, 1.0, 1.0 )\n    NaN\n\n    > y = base.dists.pareto1.quantile( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.pareto1.quantile( 0.5, NaN, 1.0 )\n    NaN\n    > y = base.dists.pareto1.quantile( 0.5, 1.0, NaN )\n    NaN\n\n    > y = base.dists.pareto1.quantile( 0.5, -1.0, 1.0 )\n    NaN\n    > y = base.dists.pareto1.quantile( 0.5, 1.0, -1.0 )\n    NaN\n\n\nbase.dists.pareto1.quantile.factory( α, β )\n    Returns a function for evaluating the quantile function of a Pareto (Type I)\n    distribution with shape parameter `α` and scale parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.pareto1.quantile.factory( 2.5, 0.5 );\n    > var y = myQuantile( 0.5 )\n    ~0.66\n    > y = myQuantile( 0.8 )\n    ~0.952\n\n","base.dists.pareto1.quantile.factory":"\nbase.dists.pareto1.quantile.factory( α, β )\n    Returns a function for evaluating the quantile function of a Pareto (Type I)\n    distribution with shape parameter `α` and scale parameter `β`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.pareto1.quantile.factory( 2.5, 0.5 );\n    > var y = myQuantile( 0.5 )\n    ~0.66\n    > y = myQuantile( 0.8 )\n    ~0.952","base.dists.pareto1.skewness":"\nbase.dists.pareto1.skewness( α, β )\n    Returns the skewness of a Pareto (Type I) distribution.\n\n    If `α <= 3` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.pareto1.skewness( 3.5, 1.0 )\n    ~11.784\n    > v = base.dists.pareto1.skewness( 4.0, 12.0 )\n    ~7.071\n    > v = base.dists.pareto1.skewness( 8.0, 2.0 )\n    ~3.118\n\n","base.dists.pareto1.stdev":"\nbase.dists.pareto1.stdev( α, β )\n    Returns the standard deviation of a Pareto (Type I) distribution.\n\n    If `0 < α <= 2` and `β > 0`, the function returns positive infinity.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.pareto1.stdev( 0.8, 1.0 )\n    Infinity\n    > v = base.dists.pareto1.stdev( 4.0, 12.0 )\n    ~5.657\n    > v = base.dists.pareto1.stdev( 8.0, 2.0 )\n    ~0.33\n\n","base.dists.pareto1.variance":"\nbase.dists.pareto1.variance( α, β )\n    Returns the variance of a Pareto (Type I) distribution.\n\n    If `0 < α <= 2` and `β > 0`, the function returns positive infinity.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.pareto1.variance( 0.8, 1.0 )\n    Infinity\n    > v = base.dists.pareto1.variance( 4.0, 12.0 )\n    32.0\n    > v = base.dists.pareto1.variance( 8.0, 2.0 )\n    ~0.109\n\n","base.dists.poisson.cdf":"\nbase.dists.poisson.cdf( x, λ )\n    Evaluates the cumulative distribution function (CDF) for a Poisson\n    distribution with mean parameter `λ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.poisson.cdf( 2.0, 0.5 )\n    ~0.986\n    > y = base.dists.poisson.cdf( 2.0, 10.0 )\n    ~0.003\n    > y = base.dists.poisson.cdf( -1.0, 4.0 )\n    0.0\n    > y = base.dists.poisson.cdf( NaN, 1.0 )\n    NaN\n    > y = base.dists.poisson.cdf( 0.0, NaN )\n    NaN\n\n    // Negative mean parameter:\n    > y = base.dists.poisson.cdf( 2.0, -1.0 )\n    NaN\n\n    // Degenerate distribution at `λ = 0`:\n    > y = base.dists.poisson.cdf( -2.0, 0.0 )\n    0.0\n    > y = base.dists.poisson.cdf( 0.0, 0.0 )\n    1.0\n    > y = base.dists.poisson.cdf( 10.0, 0.0 )\n    1.0\n\n\nbase.dists.poisson.cdf.factory( λ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Poisson distribution with mean parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.poisson.cdf.factory( 5.0 );\n    > var y = mycdf( 3.0 )\n    ~0.265\n    > y = mycdf( 8.0 )\n    ~0.932\n\n","base.dists.poisson.cdf.factory":"\nbase.dists.poisson.cdf.factory( λ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Poisson distribution with mean parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.poisson.cdf.factory( 5.0 );\n    > var y = mycdf( 3.0 )\n    ~0.265\n    > y = mycdf( 8.0 )\n    ~0.932","base.dists.poisson.entropy":"\nbase.dists.poisson.entropy( λ )\n    Returns the entropy of a Poisson distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.poisson.entropy( 11.0 )\n    ~2.61\n    > v = base.dists.poisson.entropy( 4.5 )\n    ~2.149\n\n","base.dists.poisson.kurtosis":"\nbase.dists.poisson.kurtosis( λ )\n    Returns the excess kurtosis of a Poisson distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a non-positive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.poisson.kurtosis( 11.0 )\n    ~0.091\n    > v = base.dists.poisson.kurtosis( 4.5 )\n    ~0.222\n\n","base.dists.poisson.logpmf":"\nbase.dists.poisson.logpmf( x, λ )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    Poisson distribution with mean parameter `λ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPMF.\n\n    Examples\n    --------\n    > var y = base.dists.poisson.logpmf( 4.0, 3.0 )\n    ~-1.784\n    > y = base.dists.poisson.logpmf( 1.0, 3.0 )\n    ~-1.901\n    > y = base.dists.poisson.logpmf( -1.0, 2.0 )\n    -Infinity\n    > y = base.dists.poisson.logpmf( 0.0, NaN )\n    NaN\n    > y = base.dists.poisson.logpmf( NaN, 0.5 )\n    NaN\n\n    // Negative mean parameter:\n    > y = base.dists.poisson.logpmf( 2.0, -0.5 )\n    NaN\n\n    // Degenerate distribution at `λ = 0`:\n    > y = base.dists.poisson.logpmf( 2.0, 0.0 )\n    -Infinity\n    > y = base.dists.poisson.logpmf( 0.0, 0.0 )\n    0.0\n\n\nbase.dists.poisson.logpmf.factory( λ )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a Poisson distribution with mean parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogpmf = base.dists.poisson.logpmf.factory( 1.0 );\n    > var y = mylogpmf( 3.0 )\n    ~-2.792\n    > y = mylogpmf( 1.0 )\n    ~-1.0\n\n","base.dists.poisson.logpmf.factory":"\nbase.dists.poisson.logpmf.factory( λ )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a Poisson distribution with mean parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    logpmf: Function\n        Logarithm of probability mass function (PMF).\n\n    Examples\n    --------\n    > var mylogpmf = base.dists.poisson.logpmf.factory( 1.0 );\n    > var y = mylogpmf( 3.0 )\n    ~-2.792\n    > y = mylogpmf( 1.0 )\n    ~-1.0","base.dists.poisson.mean":"\nbase.dists.poisson.mean( λ )\n    Returns the expected value of a Poisson distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.poisson.mean( 11.0 )\n    11.0\n    > v = base.dists.poisson.mean( 4.5 )\n    4.5\n\n","base.dists.poisson.median":"\nbase.dists.poisson.median( λ )\n    Returns the median of a Poisson distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: integer\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.poisson.median( 11.0 )\n    11\n    > v = base.dists.poisson.median( 4.5 )\n    4\n\n","base.dists.poisson.mgf":"\nbase.dists.poisson.mgf( x, λ )\n    Evaluates the moment-generating function (MGF) for a Poisson distribution\n    with mean parameter `λ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.poisson.mgf( 1.0, 1.5 )\n    ~13.163\n    > y = base.dists.poisson.mgf( 0.5, 0.5 )\n    ~1.383\n    > y = base.dists.poisson.mgf( NaN, 0.5 )\n    NaN\n    > y = base.dists.poisson.mgf( 0.0, NaN )\n    NaN\n    > y = base.dists.poisson.mgf( -2.0, -1.0 )\n    NaN\n\n\nbase.dists.poisson.mgf.factory( λ )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Poisson distribution with mean parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.poisson.mgf.factory( 2.0 );\n    > var y = myMGF( 0.1 )\n    ~1.234\n\n","base.dists.poisson.mgf.factory":"\nbase.dists.poisson.mgf.factory( λ )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Poisson distribution with mean parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.poisson.mgf.factory( 2.0 );\n    > var y = myMGF( 0.1 )\n    ~1.234","base.dists.poisson.mode":"\nbase.dists.poisson.mode( λ )\n    Returns the mode of a Poisson distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: integer\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.poisson.mode( 11.0 )\n    11\n    > v = base.dists.poisson.mode( 4.5 )\n    4\n\n","base.dists.poisson.pmf":"\nbase.dists.poisson.pmf( x, λ )\n    Evaluates the probability mass function (PMF) for a Poisson\n    distribution with mean parameter `λ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PMF.\n\n    Examples\n    --------\n    > var y = base.dists.poisson.pmf( 4.0, 3.0 )\n    ~0.168\n    > y = base.dists.poisson.pmf( 1.0, 3.0 )\n    ~0.149\n    > y = base.dists.poisson.pmf( -1.0, 2.0 )\n    0.0\n    > y = base.dists.poisson.pmf( 0.0, NaN )\n    NaN\n    > y = base.dists.poisson.pmf( NaN, 0.5 )\n    NaN\n\n    // Negative mean parameter:\n    > y = base.dists.poisson.pmf( 2.0, -0.5 )\n    NaN\n\n    // Degenerate distribution at `λ = 0`:\n    > y = base.dists.poisson.pmf( 2.0, 0.0 )\n    0.0\n    > y = base.dists.poisson.pmf( 0.0, 0.0 )\n    1.0\n\n\nbase.dists.poisson.pmf.factory( λ )\n    Returns a function for evaluating the probability mass function (PMF)\n    of a Poisson distribution with mean parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var mypmf = base.dists.poisson.pmf.factory( 1.0 );\n    > var y = mypmf( 3.0 )\n    ~0.061\n    > y = mypmf( 1.0 )\n    ~0.368\n\n","base.dists.poisson.pmf.factory":"\nbase.dists.poisson.pmf.factory( λ )\n    Returns a function for evaluating the probability mass function (PMF)\n    of a Poisson distribution with mean parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    pmf: Function\n        Probability mass function (PMF).\n\n    Examples\n    --------\n    > var mypmf = base.dists.poisson.pmf.factory( 1.0 );\n    > var y = mypmf( 3.0 )\n    ~0.061\n    > y = mypmf( 1.0 )\n    ~0.368","base.dists.poisson.Poisson":"\nbase.dists.poisson.Poisson( [λ] )\n    Returns a Poisson distribution object.\n\n    Parameters\n    ----------\n    λ: number (optional)\n        Mean parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    poisson: Object\n        Distribution instance.\n\n    poisson.lambda: number\n        Mean parameter. If set, the value must be greater than `0`.\n\n    poisson.entropy: number\n        Read-only property which returns the differential entropy.\n\n    poisson.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    poisson.mean: number\n        Read-only property which returns the expected value.\n\n    poisson.median: number\n        Read-only property which returns the median.\n\n    poisson.mode: number\n        Read-only property which returns the mode.\n\n    poisson.skewness: number\n        Read-only property which returns the skewness.\n\n    poisson.stdev: number\n        Read-only property which returns the standard deviation.\n\n    poisson.variance: number\n        Read-only property which returns the variance.\n\n    poisson.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    poisson.logpmf: Function\n        Evaluates the natural logarithm of the probability mass function (PMF).\n\n    poisson.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    poisson.pmf: Function\n        Evaluates the probability mass function (PMF).\n\n    poisson.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var poisson = base.dists.poisson.Poisson( 6.0 );\n    > poisson.lambda\n    6.0\n    > poisson.entropy\n    ~2.3\n    > poisson.kurtosis\n    ~0.167\n    > poisson.mean\n    6.0\n    > poisson.median\n    6.0\n    > poisson.mode\n    6.0\n    > poisson.skewness\n    ~0.408\n    > poisson.stdev\n    ~2.449\n    > poisson.variance\n    6.0\n    > poisson.cdf( 4.0 )\n    ~0.285\n    > poisson.logpmf( 2.0 )\n    ~-3.11\n    > poisson.mgf( 0.5 )\n    ~49.025\n    > poisson.pmf( 2.0 )\n    ~0.045\n    > poisson.quantile( 0.5 )\n    6.0\n\n","base.dists.poisson.quantile":"\nbase.dists.poisson.quantile( p, λ )\n    Evaluates the quantile function for a Poisson distribution with mean\n    parameter `λ` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.poisson.quantile( 0.5, 2.0 )\n    2\n    > y = base.dists.poisson.quantile( 0.9, 4.0 )\n    7\n    > y = base.dists.poisson.quantile( 0.1, 200.0 )\n    182\n\n    > y = base.dists.poisson.quantile( 1.1, 0.0 )\n    NaN\n    > y = base.dists.poisson.quantile( -0.2, 0.0 )\n    NaN\n\n    > y = base.dists.poisson.quantile( NaN, 0.5 )\n    NaN\n    > y = base.dists.poisson.quantile( 0.0, NaN )\n    NaN\n\n    // Negative mean parameter:\n    > y = base.dists.poisson.quantile( 2.0, -1.0 )\n    NaN\n\n    // Degenerate distribution at `λ = 0`:\n    > y = base.dists.poisson.quantile( 0.1, 0.0 )\n    0.0\n    > y = base.dists.poisson.quantile( 0.9, 0.0 )\n    0.0\n\n\nbase.dists.poisson.quantile.factory( λ )\n    Returns a function for evaluating the quantile function of a Poisson\n    distribution with mean parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.poisson.quantile.factory( 0.4 );\n    > var y = myQuantile( 0.4 )\n    0.0\n    > y = myQuantile( 1.0 )\n    Infinity\n\n","base.dists.poisson.quantile.factory":"\nbase.dists.poisson.quantile.factory( λ )\n    Returns a function for evaluating the quantile function of a Poisson\n    distribution with mean parameter `λ`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.poisson.quantile.factory( 0.4 );\n    > var y = myQuantile( 0.4 )\n    0.0\n    > y = myQuantile( 1.0 )\n    Infinity","base.dists.poisson.skewness":"\nbase.dists.poisson.skewness( λ )\n    Returns the skewness of a Poisson distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a nonpositive value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.poisson.skewness( 11.0 )\n    ~0.302\n    > v = base.dists.poisson.skewness( 4.5 )\n    ~0.471\n\n","base.dists.poisson.stdev":"\nbase.dists.poisson.stdev( λ )\n    Returns the standard deviation of a Poisson distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.poisson.stdev( 11.0 )\n    ~3.317\n    > v = base.dists.poisson.stdev( 4.5 )\n    ~2.121\n\n","base.dists.poisson.variance":"\nbase.dists.poisson.variance( λ )\n    Returns the variance of a Poisson distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `λ`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.poisson.variance( 11.0 )\n    11.0\n    > v = base.dists.poisson.variance( 4.5 )\n    4.5\n\n","base.dists.rayleigh.cdf":"\nbase.dists.rayleigh.cdf( x, sigma )\n    Evaluates the cumulative distribution function (CDF) for a Rayleigh\n    distribution with scale parameter `sigma` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `sigma`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.rayleigh.cdf( 2.0, 3.0 )\n    ~0.199\n    > y = base.dists.rayleigh.cdf( 1.0, 2.0 )\n    ~0.118\n    > y = base.dists.rayleigh.cdf( -1.0, 4.0 )\n    0.0\n    > y = base.dists.rayleigh.cdf( NaN, 1.0 )\n    NaN\n    > y = base.dists.rayleigh.cdf( 0.0, NaN )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.rayleigh.cdf( 2.0, -1.0 )\n    NaN\n\n    // Degenerate distribution when `sigma = 0.0`:\n    > y = base.dists.rayleigh.cdf( -2.0, 0.0 )\n    0.0\n    > y = base.dists.rayleigh.cdf( 0.0, 0.0 )\n    1.0\n    > y = base.dists.rayleigh.cdf( 2.0, 0.0 )\n    1.0\n\n\nbase.dists.rayleigh.cdf.factory( sigma )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Rayleigh distribution with scale parameter `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.rayleigh.cdf.factory( 0.5 );\n    > var y = myCDF( 1.0 )\n    ~0.865\n    > y = myCDF( 0.5 )\n    ~0.393\n\n","base.dists.rayleigh.cdf.factory":"\nbase.dists.rayleigh.cdf.factory( sigma )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Rayleigh distribution with scale parameter `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.rayleigh.cdf.factory( 0.5 );\n    > var y = myCDF( 1.0 )\n    ~0.865\n    > y = myCDF( 0.5 )\n    ~0.393","base.dists.rayleigh.entropy":"\nbase.dists.rayleigh.entropy( σ )\n    Returns the differential entropy of a Rayleigh distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.rayleigh.entropy( 11.0 )\n    ~3.34\n    > v = base.dists.rayleigh.entropy( 4.5 )\n    ~2.446\n\n","base.dists.rayleigh.kurtosis":"\nbase.dists.rayleigh.kurtosis( σ )\n    Returns the excess kurtosis of a Rayleigh distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.rayleigh.kurtosis( 11.0 )\n    ~0.245\n    > v = base.dists.rayleigh.kurtosis( 4.5 )\n    ~0.245\n\n","base.dists.rayleigh.logcdf":"\nbase.dists.rayleigh.logcdf( x, sigma )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    Rayleigh distribution with scale parameter `sigma` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `sigma`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.rayleigh.logcdf( 2.0, 3.0 )\n    ~-1.613\n    > y = base.dists.rayleigh.logcdf( 1.0, 2.0 )\n    ~-2.141\n    > y = base.dists.rayleigh.logcdf( -1.0, 4.0 )\n    -Infinity\n    > y = base.dists.rayleigh.logcdf( NaN, 1.0 )\n    NaN\n    > y = base.dists.rayleigh.logcdf( 0.0, NaN )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.rayleigh.logcdf( 2.0, -1.0 )\n    NaN\n\n\nbase.dists.rayleigh.logcdf.factory( sigma )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Rayleigh distribution with scale parameter\n    `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.rayleigh.logcdf.factory( 0.5 );\n    > var y = mylogcdf( 1.0 )\n    ~-0.145\n    > y = mylogcdf( 0.5 )\n    ~-0.933\n\n","base.dists.rayleigh.logcdf.factory":"\nbase.dists.rayleigh.logcdf.factory( sigma )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Rayleigh distribution with scale parameter\n    `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.rayleigh.logcdf.factory( 0.5 );\n    > var y = mylogcdf( 1.0 )\n    ~-0.145\n    > y = mylogcdf( 0.5 )\n    ~-0.933","base.dists.rayleigh.logpdf":"\nbase.dists.rayleigh.logpdf( x, sigma )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    Rayleigh distribution with scale parameter `sigma` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `sigma`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.rayleigh.logpdf( 0.3, 1.0 )\n    ~-1.249\n    > y = base.dists.rayleigh.logpdf( 2.0, 0.8 )\n    ~-1.986\n    > y = base.dists.rayleigh.logpdf( -1.0, 0.5 )\n    -Infinity\n    > y = base.dists.rayleigh.logpdf( 0.0, NaN )\n    NaN\n    > y = base.dists.rayleigh.logpdf( NaN, 2.0 )\n    NaN\n    // Negative scale parameter:\n    > y = base.dists.rayleigh.logpdf( 2.0, -1.0 )\n    NaN\n\n\nbase.dists.rayleigh.logpdf.factory( sigma )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Rayleigh distribution with scale parameter `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.rayleigh.logpdf.factory( 4.0 );\n    > var y = mylogpdf( 6.0 )\n    ~-2.106\n    > y = mylogpdf( 4.0 )\n    ~-1.886\n\n","base.dists.rayleigh.logpdf.factory":"\nbase.dists.rayleigh.logpdf.factory( sigma )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Rayleigh distribution with scale parameter `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.rayleigh.logpdf.factory( 4.0 );\n    > var y = mylogpdf( 6.0 )\n    ~-2.106\n    > y = mylogpdf( 4.0 )\n    ~-1.886","base.dists.rayleigh.mean":"\nbase.dists.rayleigh.mean( σ )\n    Returns the expected value of a Rayleigh distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.rayleigh.mean( 11.0 )\n    ~13.786\n    > v = base.dists.rayleigh.mean( 4.5 )\n    ~5.64\n\n","base.dists.rayleigh.median":"\nbase.dists.rayleigh.median( σ )\n    Returns the median of a Rayleigh distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.rayleigh.median( 11.0 )\n    ~12.952\n    > v = base.dists.rayleigh.median( 4.5 )\n    ~5.298\n\n","base.dists.rayleigh.mgf":"\nbase.dists.rayleigh.mgf( t, sigma )\n    Evaluates the moment-generating function (MGF) for a Rayleigh distribution\n    with scale parameter `sigma` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `sigma`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.rayleigh.mgf( 1.0, 3.0 )\n    ~678.508\n    > y = base.dists.rayleigh.mgf( 1.0, 2.0 )\n    ~38.65\n    > y = base.dists.rayleigh.mgf( -1.0, 4.0 )\n    ~-0.947\n    > y = base.dists.rayleigh.mgf( NaN, 1.0 )\n    NaN\n    > y = base.dists.rayleigh.mgf( 0.0, NaN )\n    NaN\n    > y = base.dists.rayleigh.mgf( 0.5, -1.0 )\n    NaN\n\n\nbase.dists.rayleigh.mgf.factory( sigma )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Rayleigh distribution with scale parameter `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.rayleigh.mgf.factory( 0.5 );\n    > var y = myMGF( 1.0 )\n    ~2.715\n    > y = myMGF( 0.5 )\n    ~1.888\n\n","base.dists.rayleigh.mgf.factory":"\nbase.dists.rayleigh.mgf.factory( sigma )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Rayleigh distribution with scale parameter `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.rayleigh.mgf.factory( 0.5 );\n    > var y = myMGF( 1.0 )\n    ~2.715\n    > y = myMGF( 0.5 )\n    ~1.888","base.dists.rayleigh.mode":"\nbase.dists.rayleigh.mode( σ )\n    Returns the mode of a Rayleigh distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.rayleigh.mode( 11.0 )\n    11.0\n    > v = base.dists.rayleigh.mode( 4.5 )\n    4.5\n\n","base.dists.rayleigh.pdf":"\nbase.dists.rayleigh.pdf( x, sigma )\n    Evaluates the probability density function (PDF) for a Rayleigh\n    distribution with scale parameter `sigma` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `sigma`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.rayleigh.pdf( 0.3, 1.0 )\n    ~0.287\n    > y = base.dists.rayleigh.pdf( 2.0, 0.8 )\n    ~0.137\n    > y = base.dists.rayleigh.pdf( -1.0, 0.5 )\n    0.0\n    > y = base.dists.rayleigh.pdf( 0.0, NaN )\n    NaN\n    > y = base.dists.rayleigh.pdf( NaN, 2.0 )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.rayleigh.pdf( 2.0, -1.0 )\n    NaN\n\n    // Degenerate distribution when `sigma = 0.0`:\n    > y = base.dists.rayleigh.pdf( -2.0, 0.0 )\n    0.0\n    > y = base.dists.rayleigh.pdf( 0.0, 0.0 )\n    Infinity\n    > y = base.dists.rayleigh.pdf( 2.0, 0.0 )\n    0.0\n\n\nbase.dists.rayleigh.pdf.factory( sigma )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Rayleigh distribution with scale parameter `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.rayleigh.pdf.factory( 4.0 );\n    > var y = myPDF( 6.0 )\n    ~0.122\n    > y = myPDF( 4.0 )\n    ~0.152\n\n","base.dists.rayleigh.pdf.factory":"\nbase.dists.rayleigh.pdf.factory( sigma )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Rayleigh distribution with scale parameter `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.rayleigh.pdf.factory( 4.0 );\n    > var y = myPDF( 6.0 )\n    ~0.122\n    > y = myPDF( 4.0 )\n    ~0.152","base.dists.rayleigh.quantile":"\nbase.dists.rayleigh.quantile( p, sigma )\n    Evaluates the quantile function for a Rayleigh distribution with scale\n    parameter `sigma` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative probability for `sigma`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.rayleigh.quantile( 0.8, 1.0 )\n    ~1.794\n    > y = base.dists.rayleigh.quantile( 0.5, 4.0 )\n    ~4.71\n\n    > y = base.dists.rayleigh.quantile( 1.1, 1.0 )\n    NaN\n    > y = base.dists.rayleigh.quantile( -0.2, 1.0 )\n    NaN\n\n    > y = base.dists.rayleigh.quantile( NaN, 1.0 )\n    NaN\n    > y = base.dists.rayleigh.quantile( 0.0, NaN )\n    NaN\n\n    // Negative scale parameter:\n    > y = base.dists.rayleigh.quantile( 0.5, -1.0 )\n    NaN\n\n\nbase.dists.rayleigh.quantile.factory( sigma )\n    Returns a function for evaluating the quantile function of a Rayleigh\n    distribution with scale parameter `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.rayleigh.quantile.factory( 0.4 );\n    > var y = myQuantile( 0.4 )\n    ~0.404\n    > y = myQuantile( 1.0 )\n    Infinity\n\n","base.dists.rayleigh.quantile.factory":"\nbase.dists.rayleigh.quantile.factory( sigma )\n    Returns a function for evaluating the quantile function of a Rayleigh\n    distribution with scale parameter `sigma`.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.rayleigh.quantile.factory( 0.4 );\n    > var y = myQuantile( 0.4 )\n    ~0.404\n    > y = myQuantile( 1.0 )\n    Infinity","base.dists.rayleigh.Rayleigh":"\nbase.dists.rayleigh.Rayleigh( [σ] )\n    Returns a Rayleigh distribution object.\n\n    Parameters\n    ----------\n    σ: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    rayleigh: Object\n        Distribution instance.\n\n    rayleigh.sigma: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    rayleigh.entropy: number\n        Read-only property which returns the differential entropy.\n\n    rayleigh.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    rayleigh.mean: number\n        Read-only property which returns the expected value.\n\n    rayleigh.median: number\n        Read-only property which returns the median.\n\n    rayleigh.mode: number\n        Read-only property which returns the mode.\n\n    rayleigh.skewness: number\n        Read-only property which returns the skewness.\n\n    rayleigh.stdev: number\n        Read-only property which returns the standard deviation.\n\n    rayleigh.variance: number\n        Read-only property which returns the variance.\n\n    rayleigh.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    rayleigh.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    rayleigh.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    rayleigh.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    rayleigh.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    rayleigh.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var rayleigh = base.dists.rayleigh.Rayleigh( 6.0 );\n    > rayleigh.sigma\n    6.0\n    > rayleigh.entropy\n    ~2.734\n    > rayleigh.kurtosis\n    ~0.245\n    > rayleigh.mean\n    ~7.52\n    > rayleigh.median\n    ~7.064\n    > rayleigh.mode\n    6.0\n    > rayleigh.skewness\n    ~0.631\n    > rayleigh.stdev\n    ~3.931\n    > rayleigh.variance\n    ~15.451\n    > rayleigh.cdf( 1.0 )\n    ~0.014\n    > rayleigh.logcdf( 1.0 )\n    ~-4.284\n    > rayleigh.logpdf( 1.5 )\n    ~-3.209\n    > rayleigh.mgf( -0.5 )\n    ~-0.91\n    > rayleigh.pdf( 1.5 )\n    ~0.04\n    > rayleigh.quantile( 0.5 )\n    ~7.064\n\n","base.dists.rayleigh.skewness":"\nbase.dists.rayleigh.skewness( σ )\n    Returns the skewness of a Rayleigh distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.rayleigh.skewness( 11.0 )\n    ~0.631\n    > v = base.dists.rayleigh.skewness( 4.5 )\n    ~0.631\n\n","base.dists.rayleigh.stdev":"\nbase.dists.rayleigh.stdev( σ )\n    Returns the standard deviation of a Rayleigh distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.rayleigh.stdev( 9.0 )\n    ~5.896\n    > v = base.dists.rayleigh.stdev( 4.5 )\n    ~2.948\n\n","base.dists.rayleigh.variance":"\nbase.dists.rayleigh.variance( σ )\n    Returns the variance of a Rayleigh distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `σ < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.rayleigh.variance( 9.0 )\n    ~34.765\n    > v = base.dists.rayleigh.variance( 4.5 )\n    ~8.691\n\n","base.dists.signrank.cdf":"\nbase.dists.signrank.cdf( x, n )\n    Evaluates the cumulative distribution function (CDF) for the distribution of\n    the Wilcoxon signed rank test statistic with `n` observations.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `x`, the function returns `NaN`.\n\n    If not provided a positive integer for `n`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Number of observations.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.signrank.cdf( 3, 7 )\n    ~0.039\n    > y = base.dists.signrank.cdf( 1.8, 3 )\n    ~0.375\n    > y = base.dists.signrank.cdf( -1.0, 40 )\n    0.0\n    > y = base.dists.signrank.cdf( NaN, 10 )\n    NaN\n    > y = base.dists.signrank.cdf( 0.0, NaN )\n    NaN\n\n\nbase.dists.signrank.cdf.factory( n )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of the distribution of the Wilcoxon signed rank test statistic.\n\n    Parameters\n    ----------\n    n: integer\n        Number of observations.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.signrank.cdf.factory( 8 );\n    > var y = myCDF( 5.7 )\n    ~0.055\n    > y = myCDF( 2.2 )\n    ~0.012\n\n","base.dists.signrank.cdf.factory":"\nbase.dists.signrank.cdf.factory( n )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of the distribution of the Wilcoxon signed rank test statistic.\n\n    Parameters\n    ----------\n    n: integer\n        Number of observations.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.signrank.cdf.factory( 8 );\n    > var y = myCDF( 5.7 )\n    ~0.055\n    > y = myCDF( 2.2 )\n    ~0.012","base.dists.signrank.pdf":"\nbase.dists.signrank.pdf( x, n )\n    Evaluates the probability density function (PDF) for the distribution of\n    the Wilcoxon signed rank test statistic with `n` observations.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a negative value for `x`, the function returns `NaN`.\n\n    If not provided a positive integer for `n`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Number of observations.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.signrank.pdf( 3, 7 )\n    ~0.0156\n    > y = base.dists.signrank.pdf( 1.8, 3 )\n    0.0\n    > y = base.dists.signrank.pdf( -1.0, 40 )\n    0.0\n    > y = base.dists.signrank.pdf( NaN, 10 )\n    NaN\n    > y = base.dists.signrank.pdf( 0.0, NaN )\n    NaN\n\n\nbase.dists.signrank.pdf.factory( n )\n    Returns a function for evaluating the probability density function (PDF)\n    of the distribution of the Wilcoxon signed rank test statistic.\n\n    Parameters\n    ----------\n    n: integer\n        Number of observations.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.signrank.pdf.factory( 8 );\n    > var y = myPDF( 6.0 )\n    ~0.0156\n    > y = myPDF( 2.0 )\n    ~0.0039\n\n","base.dists.signrank.pdf.factory":"\nbase.dists.signrank.pdf.factory( n )\n    Returns a function for evaluating the probability density function (PDF)\n    of the distribution of the Wilcoxon signed rank test statistic.\n\n    Parameters\n    ----------\n    n: integer\n        Number of observations.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.signrank.pdf.factory( 8 );\n    > var y = myPDF( 6.0 )\n    ~0.0156\n    > y = myPDF( 2.0 )\n    ~0.0039","base.dists.signrank.quantile":"\nbase.dists.signrank.quantile( p, n )\n    Evaluates the quantile function for the Wilcoxon signed rank test statistic\n    with `n` observations at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If not provided a positive integer for `n`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    n: integer\n        Number of observations.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.signrank.quantile( 0.8, 5 )\n    11\n    > y = base.dists.signrank.quantile( 0.5, 4 )\n    5\n\n    > y = base.dists.signrank.quantile( 1.1, 5 )\n    NaN\n    > y = base.dists.signrank.quantile( -0.2, 5 )\n    NaN\n\n    > y = base.dists.signrank.quantile( NaN, 5 )\n    NaN\n    > y = base.dists.signrank.quantile( 0.0, NaN )\n    NaN\n\n\nbase.dists.signrank.quantile.factory( n )\n    Returns a function for evaluating the quantile function of the Wilcoxon\n    signed rank test statistic with `n` observations.\n\n    Parameters\n    ----------\n    n: integer\n        Number of observations.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.signrank.quantile.factory( 8 );\n    > var y = myQuantile( 0.4 )\n    16\n    > y = myQuantile( 1.0 )\n    36\n\n","base.dists.signrank.quantile.factory":"\nbase.dists.signrank.quantile.factory( n )\n    Returns a function for evaluating the quantile function of the Wilcoxon\n    signed rank test statistic with `n` observations.\n\n    Parameters\n    ----------\n    n: integer\n        Number of observations.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.signrank.quantile.factory( 8 );\n    > var y = myQuantile( 0.4 )\n    16\n    > y = myQuantile( 1.0 )\n    36","base.dists.studentizedRange.cdf":"\nbase.dists.studentizedRange.cdf( x, r, v[, nranges] )\n    Evaluates the cumulative distribution function (CDF) of a studentized range\n    distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `r < 2` or `v < 2`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    r: number\n        Sample size for range (same for each group).\n\n    v: number\n        Degrees of freedom.\n\n    nranges: integer\n        Number of groups whose maximum range is considered. Default: 1.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.studentizedRange.cdf( 0.5, 3.0, 2.0 )\n    ~0.0644\n\n    > y = base.dists.studentizedRange.cdf( 12.1, 17.0, 2.0 )\n    ~0.913\n\n\nbase.dists.studentizedRange.cdf.factory( r, v[, nranges] )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a studentized range distribution.\n\n    Parameters\n    ----------\n    r: number\n        Number of samples.\n\n    v: number\n        Degrees of freedom.\n\n    nranges: integer\n        Number of groups whose maximum range is considered. Default: 1.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.studentizedRange.cdf.factory( 3.0, 2.0 );\n    > var y = mycdf( 3.0 )\n    ~0.712\n    > y = mycdf( 1.0 )\n    ~0.216\n\n","base.dists.studentizedRange.cdf.factory":"\nbase.dists.studentizedRange.cdf.factory( r, v[, nranges] )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a studentized range distribution.\n\n    Parameters\n    ----------\n    r: number\n        Number of samples.\n\n    v: number\n        Degrees of freedom.\n\n    nranges: integer\n        Number of groups whose maximum range is considered. Default: 1.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.studentizedRange.cdf.factory( 3.0, 2.0 );\n    > var y = mycdf( 3.0 )\n    ~0.712\n    > y = mycdf( 1.0 )\n    ~0.216","base.dists.studentizedRange.quantile":"\nbase.dists.studentizedRange.quantile( p, r, v[, nranges] )\n    Evaluates the quantile function for a studentized range distribution.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `r < 2` or `v < 2`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    r: number\n        Sample size for range (same for each group).\n\n    v: number\n        Degrees of freedom.\n\n    nranges: integer\n        Number of groups whose maximum range is considered. Default: 1.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = quantile( 0.5, 3.0, 2.0 )\n     ~0.0644\n\n    > y = quantile( 0.9, 17.0, 2.0 )\n     ~0.913\n\n    > y = quantile( 0.5, 3.0, 2.0, 2 )\n     ~0.01\n\n    > y = base.dists.studentizedRange.quantile( -0.2, 3.0, 3.0 )\n    NaN\n\n    > y = base.dists.studentizedRange.quantile( NaN, 2.0, 2.0 )\n    NaN\n    > y = base.dists.studentizedRange.quantile( 0.0, NaN, 2.0 )\n    NaN\n\n    > y = base.dists.studentizedRange.quantile( 0.5, -1.0, 2.0 )\n    NaN\n\n\nbase.dists.studentizedRange.quantile.factory( r, v[, nranges] )\n    Returns a function for evaluating the quantile function of a studentized\n    range distribution.\n\n    Parameters\n    ----------\n    r: number\n        Sample size for range (same for each group).\n\n    v: number\n        Degrees of freedom.\n\n    nranges: integer\n        Number of groups whose maximum range is considered. Default: 1.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = quantile.factory( 3.0, 3.0 );\n    > var y = myQuantile( 0.5 )\n   ~1.791\n\n    > y = myQuantile( 0.8 )\n   ~3.245\n\n","base.dists.studentizedRange.quantile.factory":"\nbase.dists.studentizedRange.quantile.factory( r, v[, nranges] )\n    Returns a function for evaluating the quantile function of a studentized\n    range distribution.\n\n    Parameters\n    ----------\n    r: number\n        Sample size for range (same for each group).\n\n    v: number\n        Degrees of freedom.\n\n    nranges: integer\n        Number of groups whose maximum range is considered. Default: 1.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = quantile.factory( 3.0, 3.0 );\n    > var y = myQuantile( 0.5 )\n   ~1.791\n\n    > y = myQuantile( 0.8 )\n   ~3.245","base.dists.t.cdf":"\nbase.dists.t.cdf( x, v )\n    Evaluates the cumulative distribution function (CDF) for a Student's t\n    distribution with degrees of freedom `v` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a non-positive value for `v`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.t.cdf( 2.0, 0.1 )\n    ~0.611\n    > y = base.dists.t.cdf( 1.0, 2.0 )\n    ~0.789\n    > y = base.dists.t.cdf( -1.0, 4.0 )\n    ~0.187\n    > y = base.dists.t.cdf( NaN, 1.0 )\n    NaN\n    > y = base.dists.t.cdf( 0.0, NaN )\n    NaN\n    > y = base.dists.t.cdf( 2.0, -1.0 )\n    NaN\n\n\nbase.dists.t.cdf.factory( v )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Student's t distribution with degrees of freedom `v`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.t.cdf.factory( 0.5 );\n    > var y = mycdf( 3.0 )\n    ~0.816\n    > y = mycdf( 1.0 )\n    ~0.699\n\n","base.dists.t.cdf.factory":"\nbase.dists.t.cdf.factory( v )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Student's t distribution with degrees of freedom `v`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.t.cdf.factory( 0.5 );\n    > var y = mycdf( 3.0 )\n    ~0.816\n    > y = mycdf( 1.0 )\n    ~0.699","base.dists.t.entropy":"\nbase.dists.t.entropy( v )\n    Returns the differential entropy of a Student's t distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `v < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.t.entropy( 11.0 )\n    ~1.512\n    > v = base.dists.t.entropy( 4.5 )\n    ~1.652\n\n","base.dists.t.kurtosis":"\nbase.dists.t.kurtosis( v )\n    Returns the excess kurtosis of a Student's t distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `v <= 2`, the function returns `NaN`.\n\n    If provided `2 < v <= 4`, the function returns positive infinity.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.t.kurtosis( 11.0 )\n    ~0.857\n    > v = base.dists.t.kurtosis( 4.5 )\n    12.0\n\n","base.dists.t.logcdf":"\nbase.dists.t.logcdf( x, v )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a Student's t distribution with degrees of freedom `v` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a non-positive value for `v`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.t.logcdf( 2.0, 0.1 )\n    ~-0.493\n    > y = base.dists.t.logcdf( 1.0, 2.0 )\n    ~-0.237\n    > y = base.dists.t.logcdf( -1.0, 4.0 )\n    ~-1.677\n    > y = base.dists.t.logcdf( NaN, 1.0 )\n    NaN\n    > y = base.dists.t.logcdf( 0.0, NaN )\n    NaN\n    > y = base.dists.t.logcdf( 2.0, -1.0 )\n    NaN\n\n\nbase.dists.t.logcdf.factory( v )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Student's t distribution with degrees of\n    freedom `v`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.t.logcdf.factory( 0.5 );\n    > var y = mylogcdf( 3.0 )\n    ~-0.203\n    > y = mylogcdf( 1.0 )\n    ~-0.358\n\n","base.dists.t.logcdf.factory":"\nbase.dists.t.logcdf.factory( v )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Student's t distribution with degrees of\n    freedom `v`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.t.logcdf.factory( 0.5 );\n    > var y = mylogcdf( 3.0 )\n    ~-0.203\n    > y = mylogcdf( 1.0 )\n    ~-0.358","base.dists.t.logpdf":"\nbase.dists.t.logpdf( x, v )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a Student's t distribution with degrees of freedom `v` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a non-positive value for `v`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.t.logpdf( 0.3, 4.0 )\n    ~-1.036\n    > y = base.dists.t.logpdf( 2.0, 0.7 )\n    ~-2.841\n    > y = base.dists.t.logpdf( -1.0, 0.5 )\n    ~-2.134\n    > y = base.dists.t.logpdf( 0.0, NaN )\n    NaN\n    > y = base.dists.t.logpdf( NaN, 2.0 )\n    NaN\n    > y = base.dists.t.logpdf( 2.0, -1.0 )\n    NaN\n\n\nbase.dists.t.logpdf.factory( v )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a Student's t distribution with degrees of\n    freedom `v`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.t.logpdf.factory( 3.0 );\n    > var y = mylogPDF( 1.0 )\n    ~-1.576\n\n","base.dists.t.logpdf.factory":"\nbase.dists.t.logpdf.factory( v )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a Student's t distribution with degrees of\n    freedom `v`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.t.logpdf.factory( 3.0 );\n    > var y = mylogPDF( 1.0 )\n    ~-1.576","base.dists.t.mean":"\nbase.dists.t.mean( v )\n    Returns the expected value of a Student's t distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `v <= 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.t.mean( 11.0 )\n    0.0\n    > v = base.dists.t.mean( 4.5 )\n    0.0\n\n","base.dists.t.median":"\nbase.dists.t.median( v )\n    Returns the median of a Student's t distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `v < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.t.median( 11.0 )\n    0.0\n    > v = base.dists.t.median( 4.5 )\n    0.0\n\n","base.dists.t.mode":"\nbase.dists.t.mode( v )\n    Returns the mode of a Student's t distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `v < 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.t.mode( 11.0 )\n    0.0\n    > v = base.dists.t.mode( 4.5 )\n    0.0\n\n","base.dists.t.pdf":"\nbase.dists.t.pdf( x, v )\n    Evaluates the probability density function (PDF) for a Student's t\n    distribution with degrees of freedom `v` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a non-positive value for `v`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.t.pdf( 0.3, 4.0 )\n    ~0.355\n    > y = base.dists.t.pdf( 2.0, 0.7 )\n    ~0.058\n    > y = base.dists.t.pdf( -1.0, 0.5 )\n    ~0.118\n    > y = base.dists.t.pdf( 0.0, NaN )\n    NaN\n    > y = base.dists.t.pdf( NaN, 2.0 )\n    NaN\n    > y = base.dists.t.pdf( 2.0, -1.0 )\n    NaN\n\n\nbase.dists.t.pdf.factory( v )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Student's t distribution with degrees of freedom `v`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.t.pdf.factory( 3.0 );\n    > var y = myPDF( 1.0 )\n    ~0.207\n\n","base.dists.t.pdf.factory":"\nbase.dists.t.pdf.factory( v )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Student's t distribution with degrees of freedom `v`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.t.pdf.factory( 3.0 );\n    > var y = myPDF( 1.0 )\n    ~0.207","base.dists.t.quantile":"\nbase.dists.t.quantile( p, v )\n    Evaluates the quantile function for a Student's t distribution with degrees\n    of freedom `v` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a non-positive value for `v`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.t.quantile( 0.8, 1.0 )\n    ~1.376\n    > y = base.dists.t.quantile( 0.1, 1.0 )\n    ~-3.078\n    > y = base.dists.t.quantile( 0.5, 0.1 )\n    0.0\n\n    > y = base.dists.t.quantile( -0.2, 0.1 )\n    NaN\n\n    > y = base.dists.t.quantile( NaN, 1.0 )\n    NaN\n    > y = base.dists.t.quantile( 0.0, NaN )\n    NaN\n\n    > y = base.dists.t.quantile( 0.5, -1.0 )\n    NaN\n\n\nbase.dists.t.quantile.factory( v )\n    Returns a function for evaluating the quantile function of a Student's t\n    distribution with degrees of freedom `v`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.t.quantile.factory( 4.0 );\n    > var y = myQuantile( 0.2 )\n    ~-0.941\n    > y = myQuantile( 0.9 )\n    ~1.533\n\n","base.dists.t.quantile.factory":"\nbase.dists.t.quantile.factory( v )\n    Returns a function for evaluating the quantile function of a Student's t\n    distribution with degrees of freedom `v`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.t.quantile.factory( 4.0 );\n    > var y = myQuantile( 0.2 )\n    ~-0.941\n    > y = myQuantile( 0.9 )\n    ~1.533","base.dists.t.skewness":"\nbase.dists.t.skewness( v )\n    Returns the skewness of a Student's t distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `v <= 3`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.t.skewness( 11.0 )\n    0.0\n    > v = base.dists.t.skewness( 4.5 )\n    0.0\n\n","base.dists.t.stdev":"\nbase.dists.t.stdev( v )\n    Returns the standard deviation of a Student's t distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `1 < v <= 2`, the function returns positive infinity.\n\n    If provided `v <= 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.t.stdev( 9.0 )\n    ~1.134\n    > v = base.dists.t.stdev( 4.5 )\n    ~1.342\n\n","base.dists.t.T":"\nbase.dists.t.T( [v] )\n    Returns a Student's t distribution object.\n\n    Parameters\n    ----------\n    v: number (optional)\n        Degrees of freedom. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    t: Object\n        Distribution instance.\n\n    t.v: number\n        Degrees of freedom. If set, the value must be greater than `0`.\n\n    t.entropy: number\n        Read-only property which returns the differential entropy.\n\n    t.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    t.mean: number\n        Read-only property which returns the expected value.\n\n    t.median: number\n        Read-only property which returns the median.\n\n    t.mode: number\n        Read-only property which returns the mode.\n\n    t.skewness: number\n        Read-only property which returns the skewness.\n\n    t.stdev: number\n        Read-only property which returns the standard deviation.\n\n    t.variance: number\n        Read-only property which returns the variance.\n\n    t.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    t.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    t.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    t.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    t.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var t = base.dists.t.T( 6.0 );\n    > t.v\n    6.0\n    > t.entropy\n    ~1.592\n    > t.kurtosis\n    3.0\n    > t.mean\n    0.0\n    > t.median\n    0.0\n    > t.mode\n    0.0\n    > t.skewness\n    0.0\n    > t.stdev\n    ~1.225\n    > t.variance\n    1.5\n    > t.cdf( 1.0 )\n    ~0.822\n    > t.logcdf( 1.0 )\n    ~-0.196\n    > t.logpdf( 1.5 )\n    ~-2.075\n    > t.pdf( 1.5 )\n    ~0.126\n    > t.quantile( 0.8 )\n    ~0.906\n\n","base.dists.t.variance":"\nbase.dists.t.variance( v )\n    Returns the variance of a Student's t distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `1 < v <= 2`, the function returns positive infinity.\n\n    If provided `v <= 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.t.variance( 9.0 )\n    ~1.286\n    > v = base.dists.t.variance( 4.5 )\n    ~1.8\n\n","base.dists.triangular.cdf":"\nbase.dists.triangular.cdf( x, a, b, c )\n    Evaluates the cumulative distribution function (CDF) for a triangular\n    distribution with minimum support `a`, maximum support `b`, and mode `c` at\n    a value `x`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.0 )\n    0.875\n    > y = base.dists.triangular.cdf( 0.5, -1.0, 1.0, 0.5 )\n    0.75\n    > y = base.dists.triangular.cdf( -10.0, -20.0, 0.0, -2.0 )\n    ~0.278\n    > y = base.dists.triangular.cdf( -2.0, -1.0, 1.0, 0.0 )\n    0.0\n    > y = base.dists.triangular.cdf( NaN, 0.0, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.cdf( 0.0, NaN, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.cdf( 0.0, 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.triangular.cdf( 2.0, 1.0, 0.0, NaN )\n    NaN\n    > y = base.dists.triangular.cdf( 2.0, 1.0, 0.0, 1.5 )\n    NaN\n\n\nbase.dists.triangular.cdf.factory( a, b, c )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a triangular distribution with minimum support `a`, maximum support `b`,\n    and mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.triangular.cdf.factory( 0.0, 10.0, 2.0 );\n    > var y = mycdf( 0.5 )\n    0.0125\n    > y = mycdf( 8.0 )\n    0.95\n\n\n","base.dists.triangular.cdf.factory":"\nbase.dists.triangular.cdf.factory( a, b, c )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a triangular distribution with minimum support `a`, maximum support `b`,\n    and mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.triangular.cdf.factory( 0.0, 10.0, 2.0 );\n    > var y = mycdf( 0.5 )\n    0.0125\n    > y = mycdf( 8.0 )\n    0.95","base.dists.triangular.entropy":"\nbase.dists.triangular.entropy( a, b, c )\n    Returns the differential entropy of a triangular distribution (in nats).\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.triangular.entropy( 0.0, 1.0, 0.8 )\n    ~-0.193\n    > v = base.dists.triangular.entropy( 4.0, 12.0, 5.0 )\n    ~1.886\n    > v = base.dists.triangular.entropy( 2.0, 8.0, 5.0 )\n    ~1.599\n\n","base.dists.triangular.kurtosis":"\nbase.dists.triangular.kurtosis( a, b, c )\n    Returns the excess kurtosis of a triangular distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.triangular.kurtosis( 0.0, 1.0, 0.8 )\n    -0.6\n    > v = base.dists.triangular.kurtosis( 4.0, 12.0, 5.0 )\n    -0.6\n    > v = base.dists.triangular.kurtosis( 2.0, 8.0, 5.0 )\n    -0.6\n\n","base.dists.triangular.logcdf":"\nbase.dists.triangular.logcdf( x, a, b, c )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a triangular distribution with minimum support `a`, maximum\n    support `b`, and mode `c` at a value `x`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.0 )\n    ~-0.134\n    > y = base.dists.triangular.logcdf( 0.5, -1.0, 1.0, 0.5 )\n    ~-0.288\n    > y = base.dists.triangular.logcdf( -10.0, -20.0, 0.0, -2.0 )\n    ~-1.281\n    > y = base.dists.triangular.logcdf( -2.0, -1.0, 1.0, 0.0 )\n    -Infinity\n    > y = base.dists.triangular.logcdf( NaN, 0.0, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.logcdf( 0.0, NaN, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.logcdf( 0.0, 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, NaN )\n    NaN\n    > y = base.dists.triangular.logcdf( 2.0, 1.0, 0.0, 1.5 )\n    NaN\n\n\nbase.dists.triangular.logcdf.factory( a, b, c )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a triangular distribution with minimum\n    support `a`, maximum support `b`, and mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    cdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.triangular.logcdf.factory( 0.0, 10.0, 2.0 );\n    > var y = mylogcdf( 0.5 )\n    ~-4.382\n    > y = mylogcdf( 8.0 )\n    ~-0.051\n\n\n","base.dists.triangular.logcdf.factory":"\nbase.dists.triangular.logcdf.factory( a, b, c )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a triangular distribution with minimum\n    support `a`, maximum support `b`, and mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    cdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.triangular.logcdf.factory( 0.0, 10.0, 2.0 );\n    > var y = mylogcdf( 0.5 )\n    ~-4.382\n    > y = mylogcdf( 8.0 )\n    ~-0.051","base.dists.triangular.logpdf":"\nbase.dists.triangular.logpdf( x, a, b, c )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a triangular distribution with minimum support `a`, maximum support `b`,\n    and mode `c` at a value `x`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.0 )\n    ~-0.693\n    > y = base.dists.triangular.logpdf( 0.5, -1.0, 1.0, 0.5 )\n    0.0\n    > y = base.dists.triangular.logpdf( -10.0, -20.0, 0.0, -2.0 )\n    ~-2.89\n    > y = base.dists.triangular.logpdf( -2.0, -1.0, 1.0, 0.0 )\n    -Infinity\n    > y = base.dists.triangular.logpdf( NaN, 0.0, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.logpdf( 0.0, NaN, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.logpdf( 0.0, 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, NaN )\n    NaN\n    > y = base.dists.triangular.logpdf( 2.0, 1.0, 0.0, 1.5 )\n    NaN\n\n\nbase.dists.triangular.logpdf.factory( a, b, c )\n    Returns a function for evaluating the natural logarithm of the  probability\n    density function (PDF) of a triangular distribution with minimum support\n    `a`, maximum support `b`, and mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.triangular.logpdf.factory( 0.0, 10.0, 5.0 );\n    > var y = mylogpdf( 2.0 )\n    ~-2.526\n    > y = mylogpdf( 12.0 )\n    -Infinity\n\n\n","base.dists.triangular.logpdf.factory":"\nbase.dists.triangular.logpdf.factory( a, b, c )\n    Returns a function for evaluating the natural logarithm of the  probability\n    density function (PDF) of a triangular distribution with minimum support\n    `a`, maximum support `b`, and mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogpdf = base.dists.triangular.logpdf.factory( 0.0, 10.0, 5.0 );\n    > var y = mylogpdf( 2.0 )\n    ~-2.526\n    > y = mylogpdf( 12.0 )\n    -Infinity","base.dists.triangular.mean":"\nbase.dists.triangular.mean( a, b, c )\n    Returns the expected value of a triangular distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.triangular.mean( 0.0, 1.0, 0.8 )\n    ~0.6\n    > v = base.dists.triangular.mean( 4.0, 12.0, 5.0 )\n    7.0\n    > v = base.dists.triangular.mean( 2.0, 8.0, 5.0 )\n    5.0\n\n","base.dists.triangular.median":"\nbase.dists.triangular.median( a, b, c )\n    Returns the median of a triangular distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.triangular.median( 0.0, 1.0, 0.8 )\n    ~0.632\n    > v = base.dists.triangular.median( 4.0, 12.0, 5.0 )\n    ~6.708\n    > v = base.dists.triangular.median( 2.0, 8.0, 5.0 )\n    5.0\n\n","base.dists.triangular.mgf":"\nbase.dists.triangular.mgf( t, a, b, c )\n    Evaluates the moment-generating function (MGF) for a triangular distribution\n    with minimum support `a`, maximum support `b`, and mode `c` at a value `t`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.0 )\n    ~1.021\n    > y = base.dists.triangular.mgf( 0.5, -1.0, 1.0, 0.5 )\n    ~1.111\n    > y = base.dists.triangular.mgf( -0.3, -20.0, 0.0, -2.0 )\n    ~24.334\n    > y = base.dists.triangular.mgf( -2.0, -1.0, 1.0, 0.0 )\n    ~1.381\n    > y = base.dists.triangular.mgf( NaN, 0.0, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.mgf( 0.0, NaN, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.mgf( 0.0, 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.triangular.mgf( 0.5, 1.0, 0.0, NaN )\n    NaN\n    > y = base.dists.triangular.mgf( 0.5, 1.0, 0.0, 1.5 )\n    NaN\n\n\nbase.dists.triangular.mgf.factory( a, b, c )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    triangular distribution with minimum support `a`, maximum support `b`, and\n    mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.triangular.mgf.factory( 0.0, 2.0, 1.0 );\n    > var y = mymgf( -1.0 )\n    ~0.3996\n    > y = mymgf( 2.0 )\n    ~10.205\n\n\n","base.dists.triangular.mgf.factory":"\nbase.dists.triangular.mgf.factory( a, b, c )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    triangular distribution with minimum support `a`, maximum support `b`, and\n    mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.triangular.mgf.factory( 0.0, 2.0, 1.0 );\n    > var y = mymgf( -1.0 )\n    ~0.3996\n    > y = mymgf( 2.0 )\n    ~10.205","base.dists.triangular.mode":"\nbase.dists.triangular.mode( a, b, c )\n    Returns the mode of a triangular distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.triangular.mode( 0.0, 1.0, 0.8 )\n    0.8\n    > v = base.dists.triangular.mode( 4.0, 12.0, 5.0 )\n    5.0\n    > v = base.dists.triangular.mode( 2.0, 8.0, 5.0 )\n    5.0\n\n","base.dists.triangular.pdf":"\nbase.dists.triangular.pdf( x, a, b, c )\n    Evaluates the probability density function (PDF) for a triangular\n    distribution with minimum support `a`, maximum support `b`, and mode `c` at\n    a value `x`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.0 )\n    0.5\n    > y = base.dists.triangular.pdf( 0.5, -1.0, 1.0, 0.5 )\n    1.0\n    > y = base.dists.triangular.pdf( -10.0, -20.0, 0.0, -2.0 )\n    ~0.056\n    > y = base.dists.triangular.pdf( -2.0, -1.0, 1.0, 0.0 )\n    0.0\n    > y = base.dists.triangular.pdf( NaN, 0.0, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.pdf( 0.0, NaN, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.pdf( 0.0, 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.triangular.pdf( 2.0, 1.0, 0.0, NaN )\n    NaN\n    > y = base.dists.triangular.pdf( 2.0, 1.0, 0.0, 1.5 )\n    NaN\n\n\nbase.dists.triangular.pdf.factory( a, b, c )\n    Returns a function for evaluating the probability density function (PDF) of\n    a triangular distribution with minimum support `a`, maximum support `b`, and\n    mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var mypdf = base.dists.triangular.pdf.factory( 0.0, 10.0, 5.0 );\n    > var y = mypdf( 2.0 )\n    0.08\n    > y = mypdf( 12.0 )\n    0.0\n\n\n","base.dists.triangular.pdf.factory":"\nbase.dists.triangular.pdf.factory( a, b, c )\n    Returns a function for evaluating the probability density function (PDF) of\n    a triangular distribution with minimum support `a`, maximum support `b`, and\n    mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var mypdf = base.dists.triangular.pdf.factory( 0.0, 10.0, 5.0 );\n    > var y = mypdf( 2.0 )\n    0.08\n    > y = mypdf( 12.0 )\n    0.0","base.dists.triangular.quantile":"\nbase.dists.triangular.quantile( p, a, b, c )\n    Evaluates the quantile function for a triangular distribution with minimum\n    support `a`, maximum support `b`, and mode `c` at a value `x`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.triangular.quantile( 0.9, -1.0, 1.0, 0.0 )\n    ~0.553\n    > y = base.dists.triangular.quantile( 0.1, -1.0, 1.0, 0.5 )\n    ~-0.452\n    > y = base.dists.triangular.quantile( 0.1, -20.0, 0.0, -2.0 )\n    -14.0\n    > y = base.dists.triangular.quantile( 0.8, 0.0, 20.0, 0.0 )\n    ~11.056\n\n    > y = base.dists.triangular.quantile( 1.1, -1.0, 1.0, 0.0 )\n    NaN\n    > y = base.dists.triangular.quantile( -0.1, -1.0, 1.0, 0.0 )\n    NaN\n\n    > y = base.dists.triangular.quantile( NaN, 0.0, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.quantile( 0.3, NaN, 1.0, 0.5 )\n    NaN\n    > y = base.dists.triangular.quantile( 0.3, 0.0, NaN, 0.5 )\n    NaN\n    > y = base.dists.triangular.quantile( 0.3, 1.0, 0.0, NaN )\n    NaN\n\n    > y = base.dists.triangular.quantile( 0.3, 1.0, 0.0, 1.5 )\n    NaN\n\n\nbase.dists.triangular.quantile.factory( a, b, c )\n    Returns a function for evaluating the quantile function of a triangular\n    distribution with minimum support `a`, maximum support `b`, and mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.triangular.quantile.factory( 2.0, 4.0, 2.5 );\n    > var y = myquantile( 0.4 )\n    ~2.658\n    > y = myquantile( 0.8 )\n    ~3.225\n\n\n","base.dists.triangular.quantile.factory":"\nbase.dists.triangular.quantile.factory( a, b, c )\n    Returns a function for evaluating the quantile function of a triangular\n    distribution with minimum support `a`, maximum support `b`, and mode `c`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myquantile = base.dists.triangular.quantile.factory( 2.0, 4.0, 2.5 );\n    > var y = myquantile( 0.4 )\n    ~2.658\n    > y = myquantile( 0.8 )\n    ~3.225","base.dists.triangular.skewness":"\nbase.dists.triangular.skewness( a, b, c )\n    Returns the skewness of a triangular distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.triangular.skewness( 0.0, 1.0, 0.8 )\n    ~-0.476\n    > v = base.dists.triangular.skewness( 4.0, 12.0, 5.0 )\n    ~0.532\n    > v = base.dists.triangular.skewness( 2.0, 8.0, 5.0 )\n    0.0\n\n","base.dists.triangular.stdev":"\nbase.dists.triangular.stdev( a, b, c )\n    Returns the standard deviation of a triangular distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.triangular.stdev( 0.0, 1.0, 0.8 )\n    ~0.216\n    > v = base.dists.triangular.stdev( 4.0, 12.0, 5.0 )\n    ~1.78\n    > v = base.dists.triangular.stdev( 2.0, 8.0, 5.0 )\n    ~1.225\n\n","base.dists.triangular.Triangular":"\nbase.dists.triangular.Triangular( [a, b, c] )\n    Returns a triangular distribution object.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support. Must be smaller than `b` and `c`. Default: `0.0`.\n\n    b: number (optional)\n        Maximum support. Must be greater than `a` and `c`. Default: `1.0`.\n\n    c: number (optional)\n        Mode. Must be greater than `a` and smaller than `b`. Default: `0.5`.\n\n    Returns\n    -------\n    triangular: Object\n        Distribution instance.\n\n    triangular.a: number\n        Minimum support. If set, the value must be smaller or equal to `b` and\n        `c`.\n\n    triangular.b: number\n        Maximum support. If set, the value must be greater than or equal to `a`\n        and `c`.\n\n    triangular.c: number\n        Mode. If set, the value must be greater than or equal to `a` and smaller\n        than or equal to `b`.\n\n    triangular.entropy: number\n        Read-only property which returns the differential entropy.\n\n    triangular.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    triangular.mean: number\n        Read-only property which returns the expected value.\n\n    triangular.median: number\n        Read-only property which returns the median.\n\n    triangular.mode: number\n        Read-only property which returns the mode.\n\n    triangular.skewness: number\n        Read-only property which returns the skewness.\n\n    triangular.stdev: number\n        Read-only property which returns the standard deviation.\n\n    triangular.variance: number\n        Read-only property which returns the variance.\n\n    triangular.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    triangular.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    triangular.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    triangular.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    triangular.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    triangular.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var triangular = base.dists.triangular.Triangular( 0.0, 1.0, 0.5 );\n    > triangular.a\n    0.0\n    > triangular.b\n    1.0\n    > triangular.c\n    0.5\n    > triangular.entropy\n    ~-0.193\n    > triangular.kurtosis\n    -0.6\n    > triangular.mean\n    0.5\n    > triangular.median\n    0.5\n    > triangular.mode\n    0.5\n    > triangular.skewness\n    0.0\n    > triangular.stdev\n    ~0.204\n    > triangular.variance\n    ~0.042\n    > triangular.cdf( 0.8 )\n    0.92\n    > triangular.logcdf( 0.8 )\n    ~-0.083\n    > triangular.logpdf( 0.8 )\n    ~-0.223\n    > triangular.mgf( 0.8 )\n    ~1.512\n    > triangular.pdf( 0.8 )\n    ~0.8\n    > triangular.quantile( 0.8 )\n    ~0.684\n\n","base.dists.triangular.variance":"\nbase.dists.triangular.variance( a, b, c )\n    Returns the variance of a triangular distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.triangular.variance( 0.0, 1.0, 0.8 )\n    ~0.047\n    > v = base.dists.triangular.variance( 4.0, 12.0, 5.0 )\n    ~3.167\n    > v = base.dists.triangular.variance( 2.0, 8.0, 5.0 )\n    ~1.5\n\n","base.dists.uniform.cdf":"\nbase.dists.uniform.cdf( x, a, b )\n    Evaluates the cumulative distribution function (CDF) for a uniform\n    distribution with minimum support `a` and maximum support `b` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.uniform.cdf( 9.0, 0.0, 10.0 )\n    0.9\n    > y = base.dists.uniform.cdf( 0.5, 0.0, 2.0 )\n    0.25\n    > y = base.dists.uniform.cdf( PINF, 2.0, 4.0 )\n    1.0\n    > y = base.dists.uniform.cdf( NINF, 2.0, 4.0 )\n    0.0\n    > y = base.dists.uniform.cdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.uniform.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.uniform.cdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.uniform.cdf( 2.0, 1.0, 0.0 )\n    NaN\n\n\nbase.dists.uniform.cdf.factory( a, b )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a uniform distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.uniform.cdf.factory( 0.0, 10.0 );\n    > var y = mycdf( 0.5 )\n    0.05\n    > y = mycdf( 8.0 )\n    0.8\n\n","base.dists.uniform.cdf.factory":"\nbase.dists.uniform.cdf.factory( a, b )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a uniform distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mycdf = base.dists.uniform.cdf.factory( 0.0, 10.0 );\n    > var y = mycdf( 0.5 )\n    0.05\n    > y = mycdf( 8.0 )\n    0.8","base.dists.uniform.entropy":"\nbase.dists.uniform.entropy( a, b )\n    Returns the differential entropy of a uniform distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Differential entropy.\n\n    Examples\n    --------\n    > var v = base.dists.uniform.entropy( 0.0, 1.0 )\n    0.0\n    > v = base.dists.uniform.entropy( 4.0, 12.0 )\n    ~2.079\n    > v = base.dists.uniform.entropy( 2.0, 8.0 )\n    ~1.792\n\n","base.dists.uniform.kurtosis":"\nbase.dists.uniform.kurtosis( a, b )\n    Returns the excess kurtosis of a uniform distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.uniform.kurtosis( 0.0, 1.0 )\n    -1.2\n    > v = base.dists.uniform.kurtosis( 4.0, 12.0 )\n    -1.2\n    > v = base.dists.uniform.kurtosis( 2.0, 8.0 )\n    -1.2\n\n","base.dists.uniform.logcdf":"\nbase.dists.uniform.logcdf( x, a, b )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    uniform distribution with minimum support `a` and maximum support `b` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.uniform.logcdf( 9.0, 0.0, 10.0 )\n    ~-0.105\n    > y = base.dists.uniform.logcdf( 0.5, 0.0, 2.0 )\n    ~-1.386\n    > y = base.dists.uniform.logcdf( PINF, 2.0, 4.0 )\n    0.0\n    > y = base.dists.uniform.logcdf( NINF, 2.0, 4.0 )\n    -Infinity\n    > y = base.dists.uniform.logcdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.uniform.logcdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.uniform.logcdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.uniform.logcdf( 2.0, 1.0, 0.0 )\n    NaN\n\n\nbase.dists.uniform.logcdf.factory( a, b )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a uniform distribution with minimum support\n    `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.uniform.logcdf.factory( 0.0, 10.0 );\n    > var y = mylogcdf( 0.5 )\n    ~-2.996\n    > y = mylogcdf( 8.0 )\n    ~-0.223\n\n","base.dists.uniform.logcdf.factory":"\nbase.dists.uniform.logcdf.factory( a, b )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a uniform distribution with minimum support\n    `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.uniform.logcdf.factory( 0.0, 10.0 );\n    > var y = mylogcdf( 0.5 )\n    ~-2.996\n    > y = mylogcdf( 8.0 )\n    ~-0.223","base.dists.uniform.logpdf":"\nbase.dists.uniform.logpdf( x, a, b )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    uniform distribution with minimum support `a` and maximum support `b` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.uniform.logpdf( 2.0, 0.0, 4.0 )\n    ~-1.386\n    > y = base.dists.uniform.logpdf( 5.0, 0.0, 4.0 )\n    -infinity\n    > y = base.dists.uniform.logpdf( 0.25, 0.0, 1.0 )\n    0.0\n    > y = base.dists.uniform.logpdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.uniform.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.uniform.logpdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.uniform.logpdf( 2.0, 3.0, 1.0 )\n    NaN\n\n\nbase.dists.uniform.logpdf.factory( a, b )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a uniform distribution with minimum support `a` and\n    maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.uniform.logpdf.factory( 6.0, 7.0 );\n    > var y = mylogPDF( 7.0 )\n    0.0\n    > y = mylogPDF( 5.0 )\n    -infinity\n\n","base.dists.uniform.logpdf.factory":"\nbase.dists.uniform.logpdf.factory( a, b )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a uniform distribution with minimum support `a` and\n    maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylogPDF = base.dists.uniform.logpdf.factory( 6.0, 7.0 );\n    > var y = mylogPDF( 7.0 )\n    0.0\n    > y = mylogPDF( 5.0 )\n    -infinity","base.dists.uniform.mean":"\nbase.dists.uniform.mean( a, b )\n    Returns the expected value of a uniform distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.uniform.mean( 0.0, 1.0 )\n    0.5\n    > v = base.dists.uniform.mean( 4.0, 12.0 )\n    8.0\n    > v = base.dists.uniform.mean( 2.0, 8.0 )\n    5.0\n\n","base.dists.uniform.median":"\nbase.dists.uniform.median( a, b )\n    Returns the median of a uniform distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.uniform.median( 0.0, 1.0 )\n    0.5\n    > v = base.dists.uniform.median( 4.0, 12.0 )\n    8.0\n    > v = base.dists.uniform.median( 2.0, 8.0 )\n    5.0\n\n","base.dists.uniform.mgf":"\nbase.dists.uniform.mgf( t, a, b )\n    Evaluates the moment-generating function (MGF) for a uniform\n    distribution with minimum support `a` and maximum support `b` at a value\n    `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    t: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.uniform.mgf( 2.0, 0.0, 4.0 )\n    ~372.495\n    > y = base.dists.uniform.mgf( -0.2, 0.0, 4.0 )\n    ~0.688\n    > y = base.dists.uniform.mgf( 2.0, 0.0, 1.0 )\n    ~3.195\n    > y = base.dists.uniform.mgf( 0.5, 3.0, 2.0 )\n    NaN\n    > y = base.dists.uniform.mgf( 0.5, 3.0, 3.0 )\n    NaN\n    > y = base.dists.uniform.mgf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.uniform.mgf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.uniform.mgf( 0.0, 0.0, NaN )\n    NaN\n\n\nbase.dists.uniform.mgf.factory( a, b )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a uniform distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.uniform.mgf.factory( 6.0, 7.0 );\n    > var y = mymgf( 0.1 )\n    ~1.916\n    > y = mymgf( 1.1 )\n    ~1339.321\n\n","base.dists.uniform.mgf.factory":"\nbase.dists.uniform.mgf.factory( a, b )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a uniform distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var mymgf = base.dists.uniform.mgf.factory( 6.0, 7.0 );\n    > var y = mymgf( 0.1 )\n    ~1.916\n    > y = mymgf( 1.1 )\n    ~1339.321","base.dists.uniform.pdf":"\nbase.dists.uniform.pdf( x, a, b )\n    Evaluates the probability density function (PDF) for a uniform distribution\n    with minimum support `a` and maximum support `b` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.uniform.pdf( 2.0, 0.0, 4.0 )\n    0.25\n    > y = base.dists.uniform.pdf( 5.0, 0.0, 4.0 )\n    0.0\n    > y = base.dists.uniform.pdf( 0.25, 0.0, 1.0 )\n    1.0\n    > y = base.dists.uniform.pdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.uniform.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.uniform.pdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.uniform.pdf( 2.0, 3.0, 1.0 )\n    NaN\n\n\nbase.dists.uniform.pdf.factory( a, b )\n    Returns a function for evaluating the probability density function (PDF) of\n    a uniform distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.uniform.pdf.factory( 6.0, 7.0 );\n    > var y = myPDF( 7.0 )\n    1.0\n    > y = myPDF( 5.0 )\n    0.0\n\n","base.dists.uniform.pdf.factory":"\nbase.dists.uniform.pdf.factory( a, b )\n    Returns a function for evaluating the probability density function (PDF) of\n    a uniform distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.uniform.pdf.factory( 6.0, 7.0 );\n    > var y = myPDF( 7.0 )\n    1.0\n    > y = myPDF( 5.0 )\n    0.0","base.dists.uniform.quantile":"\nbase.dists.uniform.quantile( p, a, b )\n    Evaluates the quantile function for a uniform distribution with minimum\n    support `a` and maximum support `b` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.uniform.quantile( 0.8, 0.0, 1.0 )\n    0.8\n    > y = base.dists.uniform.quantile( 0.5, 0.0, 10.0 )\n    5.0\n\n    > y = base.dists.uniform.quantile( 1.1, 0.0, 1.0 )\n    NaN\n    > y = base.dists.uniform.quantile( -0.2, 0.0, 1.0 )\n    NaN\n\n    > y = base.dists.uniform.quantile( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.uniform.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.uniform.quantile( 0.0, 0.0, NaN )\n    NaN\n\n    > y = base.dists.uniform.quantile( 0.5, 2.0, 1.0 )\n    NaN\n\n\nbase.dists.uniform.quantile.factory( a, b )\n    Returns a function for evaluating the quantile function of a uniform\n    distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.uniform.quantile.factory( 0.0, 4.0 );\n    > var y = myQuantile( 0.8 )\n    3.2\n\n","base.dists.uniform.quantile.factory":"\nbase.dists.uniform.quantile.factory( a, b )\n    Returns a function for evaluating the quantile function of a uniform\n    distribution with minimum support `a` and maximum support `b`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.uniform.quantile.factory( 0.0, 4.0 );\n    > var y = myQuantile( 0.8 )\n    3.2","base.dists.uniform.skewness":"\nbase.dists.uniform.skewness( a, b )\n    Returns the skewness of a uniform distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.uniform.skewness( 0.0, 1.0 )\n    0.0\n    > v = base.dists.uniform.skewness( 4.0, 12.0 )\n    0.0\n    > v = base.dists.uniform.skewness( 2.0, 8.0 )\n    0.0\n\n","base.dists.uniform.stdev":"\nbase.dists.uniform.stdev( a, b )\n    Returns the standard deviation of a uniform distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.uniform.stdev( 0.0, 1.0 )\n    ~0.289\n    > v = base.dists.uniform.stdev( 4.0, 12.0 )\n    ~2.309\n    > v = base.dists.uniform.stdev( 2.0, 8.0 )\n    ~1.732\n\n","base.dists.uniform.Uniform":"\nbase.dists.uniform.Uniform( [a, b] )\n    Returns a uniform distribution object.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support. Must be smaller than `b`. Default: `0.0`.\n\n    b: number (optional)\n        Maximum support. Must be greater than `a`. Default: `1.0`.\n\n    Returns\n    -------\n    uniform: Object\n        Distribution instance.\n\n    uniform.a: number\n        Minimum support. If set, the value must be smaller than `b`.\n\n    uniform.b: number\n        Maximum support. If set, the value must be greater than `a`.\n\n    uniform.entropy: number\n        Read-only property which returns the differential entropy.\n\n    uniform.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    uniform.mean: number\n        Read-only property which returns the expected value.\n\n    uniform.median: number\n        Read-only property which returns the median.\n\n    uniform.skewness: number\n        Read-only property which returns the skewness.\n\n    uniform.stdev: number\n        Read-only property which returns the standard deviation.\n\n    uniform.variance: number\n        Read-only property which returns the variance.\n\n    uniform.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    uniform.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    uniform.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    uniform.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    uniform.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    uniform.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var uniform = base.dists.uniform.Uniform( 0.0, 1.0 );\n    > uniform.a\n    0.0\n    > uniform.b\n    1.0\n    > uniform.entropy\n    0.0\n    > uniform.kurtosis\n    -1.2\n    > uniform.mean\n    0.5\n    > uniform.median\n    0.5\n    > uniform.skewness\n    0.0\n    > uniform.stdev\n    ~0.289\n    > uniform.variance\n    ~0.083\n    > uniform.cdf( 0.8 )\n    0.8\n    > uniform.logcdf( 0.5 )\n    ~-0.693\n    > uniform.logpdf( 1.0 )\n    ~-0.0\n    > uniform.mgf( 0.8 )\n    ~1.532\n    > uniform.pdf( 0.8 )\n    1.0\n    > uniform.quantile( 0.8 )\n    0.8\n\n","base.dists.uniform.variance":"\nbase.dists.uniform.variance( a, b )\n    Returns the variance of a uniform distribution.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `a >= b`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.uniform.variance( 0.0, 1.0 )\n    ~0.083\n    > v = base.dists.uniform.variance( 4.0, 12.0 )\n    ~5.333\n    > v = base.dists.uniform.variance( 2.0, 8.0 )\n    3.0\n\n","base.dists.weibull.cdf":"\nbase.dists.weibull.cdf( x, k, λ )\n    Evaluates the cumulative distribution function (CDF) for a Weibull\n    distribution with shape parameter `k` and scale parameter `λ` at a value\n    `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a non-positive value for `λ` or `k`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated CDF.\n\n    Examples\n    --------\n    > var y = base.dists.weibull.cdf( 2.0, 1.0, 1.0 )\n    ~0.865\n    > y = base.dists.weibull.cdf( -1.0, 2.0, 2.0 )\n    0.0\n    > y = base.dists.weibull.cdf( PINF, 4.0, 2.0 )\n    1.0\n    > y = base.dists.weibull.cdf( NINF, 4.0, 2.0 )\n    0.0\n    > y = base.dists.weibull.cdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.weibull.cdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.weibull.cdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.weibull.cdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.weibull.cdf.factory( k, λ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.weibull.cdf.factory( 2.0, 10.0 );\n    > var y = myCDF( 12.0 )\n    ~0.763\n\n","base.dists.weibull.cdf.factory":"\nbase.dists.weibull.cdf.factory( k, λ )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    cdf: Function\n        Cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var myCDF = base.dists.weibull.cdf.factory( 2.0, 10.0 );\n    > var y = myCDF( 12.0 )\n    ~0.763","base.dists.weibull.entropy":"\nbase.dists.weibull.entropy( k, λ )\n    Returns the differential entropy of a Weibull distribution (in nats).\n\n    If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n    If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Entropy.\n\n    Examples\n    --------\n    > var v = base.dists.weibull.entropy( 1.0, 1.0 )\n    1.0\n    > v = base.dists.weibull.entropy( 4.0, 12.0 )\n    ~2.532\n    > v = base.dists.weibull.entropy( 8.0, 2.0 )\n    ~0.119\n\n","base.dists.weibull.kurtosis":"\nbase.dists.weibull.kurtosis( k, λ )\n    Returns the excess kurtosis of a Weibull distribution.\n\n    If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n    If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Excess kurtosis.\n\n    Examples\n    --------\n    > var v = base.dists.weibull.kurtosis( 1.0, 1.0 )\n    6.0\n    > v = base.dists.weibull.kurtosis( 4.0, 12.0 )\n    ~-0.252\n    > v = base.dists.weibull.kurtosis( 8.0, 2.0 )\n    ~0.328\n\n","base.dists.weibull.logcdf":"\nbase.dists.weibull.logcdf( x, k, λ )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logCDF.\n\n    Examples\n    --------\n    > var y = base.dists.weibull.logcdf( 2.0, 1.0, 1.0 )\n    ~-0.145\n    > y = base.dists.weibull.logcdf( -1.0, 2.0, 2.0 )\n    -Infinity\n    > y = base.dists.weibull.logcdf( PINF, 4.0, 2.0 )\n    0.0\n    > y = base.dists.weibull.logcdf( NINF, 4.0, 2.0 )\n    -Infinity\n    > y = base.dists.weibull.logcdf( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.weibull.logcdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.weibull.logcdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.weibull.logcdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.weibull.logcdf.factory( k, λ)\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Weibull distribution with scale parameter\n    `λ` and shape parameter `k`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.weibull.logcdf.factory( 2.0, 10.0 );\n    > var y = mylogcdf( 12.0 )\n    ~-0.27\n\n","base.dists.weibull.logcdf.factory":"\nbase.dists.weibull.logcdf.factory( k, λ)\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Weibull distribution with scale parameter\n    `λ` and shape parameter `k`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    logcdf: Function\n        Logarithm of cumulative distribution function (CDF).\n\n    Examples\n    --------\n    > var mylogcdf = base.dists.weibull.logcdf.factory( 2.0, 10.0 );\n    > var y = mylogcdf( 12.0 )\n    ~-0.27","base.dists.weibull.logpdf":"\nbase.dists.weibull.logpdf( x, k, λ )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n    value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated logPDF.\n\n    Examples\n    --------\n    > var y = base.dists.weibull.logpdf( 2.0, 1.0, 0.5 )\n    ~-3.307\n    > y = base.dists.weibull.logpdf( 0.1, 1.0, 1.0 )\n    ~-0.1\n    > y = base.dists.weibull.logpdf( -1.0, 4.0, 2.0 )\n    -Infinity\n    > y = base.dists.weibull.logpdf( NaN, 0.6, 1.0 )\n    NaN\n    > y = base.dists.weibull.logpdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.weibull.logpdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.weibull.logpdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.weibull.logpdf.factory( k, λ )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Weibull distribution with shape parameter `k` and scale\n    parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylofpdf = base.dists.weibull.logpdf.factory( 7.0, 6.0 );\n    > y = mylofpdf( 7.0 )\n    ~-1.863\n\n","base.dists.weibull.logpdf.factory":"\nbase.dists.weibull.logpdf.factory( k, λ )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Weibull distribution with shape parameter `k` and scale\n    parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    logpdf: Function\n        Logarithm of probability density function (PDF).\n\n    Examples\n    --------\n    > var mylofpdf = base.dists.weibull.logpdf.factory( 7.0, 6.0 );\n    > y = mylofpdf( 7.0 )\n    ~-1.863","base.dists.weibull.mean":"\nbase.dists.weibull.mean( k, λ )\n    Returns the expected value of a Weibull distribution.\n\n    If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n    If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Expected value.\n\n    Examples\n    --------\n    > var v = base.dists.weibull.mean( 1.0, 1.0 )\n    1.0\n    > v = base.dists.weibull.mean( 4.0, 12.0 )\n    ~10.877\n    > v = base.dists.weibull.mean( 8.0, 2.0 )\n    ~1.883\n\n","base.dists.weibull.median":"\nbase.dists.weibull.median( k, λ )\n    Returns the median of a Weibull distribution.\n\n    If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n    If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Median.\n\n    Examples\n    --------\n    > var v = base.dists.weibull.median( 1.0, 1.0 )\n    ~0.693\n    > v = base.dists.weibull.median( 4.0, 12.0 )\n    ~10.949\n    > v = base.dists.weibull.median( 8.0, 2.0 )\n    ~1.91\n\n","base.dists.weibull.mgf":"\nbase.dists.weibull.mgf( x, k, λ )\n    Evaluates the moment-generating function (MGF) for a Weibull distribution\n    with shape parameter `k` and scale parameter `λ` at a value `t`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a non-positive value for `λ` or `k`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated MGF.\n\n    Examples\n    --------\n    > var y = base.dists.weibull.mgf( 1.0, 1.0, 0.5 )\n    ~2.0\n    > y = base.dists.weibull.mgf( -1.0, 4.0, 4.0 )\n    ~0.019\n\n    > y = base.dists.weibull.mgf( NaN, 1.0, 1.0 )\n    NaN\n    > y = base.dists.weibull.mgf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.weibull.mgf( 0.0, 1.0, NaN )\n    NaN\n\n    > y = base.dists.weibull.mgf( 0.2, -1.0, 0.5 )\n    NaN\n    > y = base.dists.weibull.mgf( 0.2, 0.0, 0.5 )\n    NaN\n\n    > y = base.dists.weibull.mgf( 0.2, 0.5, -1.0 )\n    NaN\n    > y = base.dists.weibull.mgf( 0.2, 0.5, 0.0 )\n    NaN\n\n\nbase.dists.weibull.mgf.factory( k, λ )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.weibull.mgf.factory( 8.0, 10.0 );\n    > var y = myMGF( 0.8 )\n    ~3150.149\n    > y = myMGF( 0.08 )\n    ~2.137\n\n","base.dists.weibull.mgf.factory":"\nbase.dists.weibull.mgf.factory( k, λ )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    mgf: Function\n        Moment-generating function (MGF).\n\n    Examples\n    --------\n    > var myMGF = base.dists.weibull.mgf.factory( 8.0, 10.0 );\n    > var y = myMGF( 0.8 )\n    ~3150.149\n    > y = myMGF( 0.08 )\n    ~2.137","base.dists.weibull.mode":"\nbase.dists.weibull.mode( k, λ )\n    Returns the mode of a Weibull distribution.\n\n    If `0 < k <= 1`, the function returns `0.0`.\n\n    If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n    If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Mode.\n\n    Examples\n    --------\n    > var v = base.dists.weibull.mode( 1.0, 1.0 )\n    0.0\n    > v = base.dists.weibull.mode( 4.0, 12.0 )\n    ~11.167\n    > v = base.dists.weibull.mode( 8.0, 2.0 )\n    ~1.967\n\n","base.dists.weibull.pdf":"\nbase.dists.weibull.pdf( x, k, λ )\n    Evaluates the probability density function (PDF) for a Weibull distribution\n    with shape parameter `k` and scale parameter `λ` at a value `x`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated PDF.\n\n    Examples\n    --------\n    > var y = base.dists.weibull.pdf( 2.0, 1.0, 0.5 )\n    ~0.037\n    > y = base.dists.weibull.pdf( 0.1, 1.0, 1.0 )\n    ~0.905\n    > y = base.dists.weibull.pdf( -1.0, 4.0, 2.0 )\n    0.0\n    > y = base.dists.weibull.pdf( NaN, 0.6, 1.0 )\n    NaN\n    > y = base.dists.weibull.pdf( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.weibull.pdf( 0.0, 0.0, NaN )\n    NaN\n    > y = base.dists.weibull.pdf( 2.0, 0.0, -1.0 )\n    NaN\n\n\nbase.dists.weibull.pdf.factory( k, λ )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.weibull.pdf.factory( 7.0, 6.0 );\n    > var y = myPDF( 7.0 )\n    ~0.155\n\n","base.dists.weibull.pdf.factory":"\nbase.dists.weibull.pdf.factory( k, λ )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    pdf: Function\n        Probability density function (PDF).\n\n    Examples\n    --------\n    > var myPDF = base.dists.weibull.pdf.factory( 7.0, 6.0 );\n    > var y = myPDF( 7.0 )\n    ~0.155","base.dists.weibull.quantile":"\nbase.dists.weibull.quantile( p, k, λ )\n    Evaluates the quantile function for a Weibull distribution with scale\n    parameter `k` and shape parameter `λ` at a probability `p`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided a nonpositive value for `λ` or `k`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input probability.\n\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Evaluated quantile function.\n\n    Examples\n    --------\n    > var y = base.dists.weibull.quantile( 0.8, 1.0, 1.0 )\n    ~1.609\n    > y = base.dists.weibull.quantile( 0.5, 2.0, 4.0 )\n    ~3.33\n\n    > y = base.dists.weibull.quantile( 1.1, 1.0, 1.0 )\n    NaN\n    > y = base.dists.weibull.quantile( -0.2, 1.0, 1.0 )\n    NaN\n\n    > y = base.dists.weibull.quantile( NaN, 0.0, 1.0 )\n    NaN\n    > y = base.dists.weibull.quantile( 0.0, NaN, 1.0 )\n    NaN\n    > y = base.dists.weibull.quantile( 0.0, 0.0, NaN )\n    NaN\n\n    > y = base.dists.weibull.quantile( 0.5, 1.0, -1.0 )\n    NaN\n\n\nbase.dists.weibull.quantile.factory( k, λ )\n    Returns a function for evaluating the quantile function of a Weibull\n    distribution with scale parameter `k` and shape parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.weibull.quantile.factory( 2.0, 10.0 );\n    > var y = myQuantile( 0.4 )\n    ~7.147\n\n","base.dists.weibull.quantile.factory":"\nbase.dists.weibull.quantile.factory( k, λ )\n    Returns a function for evaluating the quantile function of a Weibull\n    distribution with scale parameter `k` and shape parameter `λ`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    quantile: Function\n        Quantile function.\n\n    Examples\n    --------\n    > var myQuantile = base.dists.weibull.quantile.factory( 2.0, 10.0 );\n    > var y = myQuantile( 0.4 )\n    ~7.147","base.dists.weibull.skewness":"\nbase.dists.weibull.skewness( k, λ )\n    Returns the skewness of a Weibull distribution.\n\n    If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n    If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Skewness.\n\n    Examples\n    --------\n    > var v = base.dists.weibull.skewness( 1.0, 1.0 )\n    2.0\n    > v = base.dists.weibull.skewness( 4.0, 12.0 )\n    ~-0.087\n    > v = base.dists.weibull.skewness( 8.0, 2.0 )\n    ~-0.534\n\n","base.dists.weibull.stdev":"\nbase.dists.weibull.stdev( k, λ )\n    Returns the standard deviation of a Weibull distribution.\n\n    If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n    If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Standard deviation.\n\n    Examples\n    --------\n    > var v = base.dists.weibull.stdev( 1.0, 1.0 )\n    1.0\n    > v = base.dists.weibull.stdev( 4.0, 12.0 )\n    ~3.051\n    > v = base.dists.weibull.stdev( 8.0, 2.0 )\n    ~0.279\n\n","base.dists.weibull.variance":"\nbase.dists.weibull.variance( k, λ )\n    Returns the variance of a Weibull distribution.\n\n    If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n    If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Scale parameter.\n\n    Returns\n    -------\n    out: number\n        Variance.\n\n    Examples\n    --------\n    > var v = base.dists.weibull.variance( 1.0, 1.0 )\n    1.0\n    > v = base.dists.weibull.variance( 4.0, 12.0 )\n    ~9.311\n    > v = base.dists.weibull.variance( 8.0, 2.0 )\n    ~0.078\n\n","base.dists.weibull.Weibull":"\nbase.dists.weibull.Weibull( [k, λ] )\n    Returns a Weibull distribution object.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Shape parameter. Must be greater than `0`. Default: `1.0`.\n\n    λ: number (optional)\n        Scale parameter. Must be greater than `0`. Default: `1.0`.\n\n    Returns\n    -------\n    weibull: Object\n        Distribution instance.\n\n    weibull.k: number\n        Shape parameter. If set, the value must be greater than `0`.\n\n    weibull.lambda: number\n        Scale parameter. If set, the value must be greater than `0`.\n\n    weibull.entropy: number\n        Read-only property which returns the differential entropy.\n\n    weibull.kurtosis: number\n        Read-only property which returns the excess kurtosis.\n\n    weibull.mean: number\n        Read-only property which returns the expected value.\n\n    weibull.median: number\n        Read-only property which returns the median.\n\n    weibull.mode: number\n        Read-only property which returns the mode.\n\n    weibull.skewness: number\n        Read-only property which returns the skewness.\n\n    weibull.stdev: number\n        Read-only property which returns the standard deviation.\n\n    weibull.variance: number\n        Read-only property which returns the variance.\n\n    weibull.cdf: Function\n        Evaluates the cumulative distribution function (CDF).\n\n    weibull.logcdf: Function\n        Evaluates the natural logarithm of the cumulative distribution function\n        (CDF).\n\n    weibull.logpdf: Function\n        Evaluates the natural logarithm of the probability density function\n        (PDF).\n\n    weibull.mgf: Function\n        Evaluates the moment-generating function (MGF).\n\n    weibull.pdf: Function\n        Evaluates the probability density function (PDF).\n\n    weibull.quantile: Function\n        Evaluates the quantile function at probability `p`.\n\n    Examples\n    --------\n    > var weibull = base.dists.weibull.Weibull( 6.0, 5.0 );\n    > weibull.k\n    6.0\n    > weibull.lambda\n    5.0\n    > weibull.entropy\n    ~1.299\n    > weibull.kurtosis\n    ~0.035\n    > weibull.mean\n    ~4.639\n    > weibull.median\n    ~4.704\n    > weibull.mode\n    ~4.85\n    > weibull.skewness\n    ~-0.373\n    > weibull.stdev\n    ~0.899\n    > weibull.variance\n    ~0.808\n    > weibull.cdf( 3.0 )\n    ~0.046\n    > weibull.logcdf( 3.0 )\n    ~-3.088\n    > weibull.logpdf( 1.0 )\n    ~-7.865\n    > weibull.mgf( -0.5 )\n    ~0.075\n    > weibull.pdf( 3.0 )\n    ~0.089\n    > weibull.quantile( 0.8 )\n    ~5.413\n\n","base.ellipe":"\nbase.ellipe( m )\n    Computes the complete elliptic integral of the second kind.\n\n    Parameters\n    ----------\n    m: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.ellipe( 0.5 )\n    ~1.351\n    > y = base.ellipe( -1.0 )\n    ~1.910\n    > y = base.ellipe( 2.0 )\n    NaN\n    > y = base.ellipe( PINF )\n    NaN\n    > y = base.ellipe( NINF )\n    NaN\n    > y = base.ellipe( NaN )\n    NaN\n\n    See Also\n    --------\n    base.ellipj, base.ellipk\n","base.ellipj":"\nbase.ellipj( u, m )\n    Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n    amplitude am.\n\n    Parameters\n    ----------\n    u: number\n        Input value.\n\n    m: number\n        Modulus m, equivalent to k².\n\n    Returns\n    -------\n    out: Array\n        Jacobi elliptic functions and Jacobi amplitude.\n\n    Examples\n    --------\n    > var v = base.ellipj( 0.3, 0.5 )\n    [ ~0.293, ~0.956, ~0.978, ~0.298 ]\n    > v = base.ellipj( 0.0, 0.0 )\n    [ ~0.0, ~1.0, ~1.0, ~0.0 ]\n    > v = base.ellipj( Infinity, 1.0 )\n    [ ~1.0, ~0.0, ~0.0, ~1.571 ]\n    > v = base.ellipj( 0.0, -2.0)\n    [ ~0.0, ~1.0, ~1.0, NaN ]\n    > v = base.ellipj( NaN, NaN )\n    [ NaN, NaN, NaN, NaN ]\n\n\nbase.ellipj.assign( u, m, out, stride, offset )\n    Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n    amplitude am and assigns results to a provided output array.\n\n    Parameters\n    ----------\n    u: number\n        Input value.\n\n    m: number\n        Modulus m, equivalent to k².\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Jacobi elliptic functions and Jacobi amplitude.\n\n    Examples\n    --------\n    > var out = new Float64Array( 4 );\n    > var v = base.ellipj.assign( 0.3, 0.5, out, 1, 0 )\n    <Float64Array>[ ~0.293, ~0.956, ~0.978, ~0.298 ]\n    > var bool = ( v === out )\n    true\n\n\nbase.ellipj.sn( u, m )\n    Computes the Jacobi elliptic function sn.\n\n    Parameters\n    ----------\n    u: number\n        Input value.\n\n    m: number\n        Modulus m, equivalent to k².\n\n    Returns\n    -------\n    out: number\n        Jacobi elliptic function sn.\n\n    Examples\n    --------\n    > var v = base.ellipj.sn( 0.3, 0.5 )\n    ~0.293\n\n\nbase.ellipj.cn( u, m )\n    Computes the Jacobi elliptic functions cn.\n\n    Parameters\n    ----------\n    u: number\n        Input value.\n\n    m: number\n        Modulus m, equivalent to k².\n\n    Returns\n    -------\n    out: number\n        Jacobi elliptic function cn.\n\n    Examples\n    --------\n    > var v = base.ellipj.cn( 0.3, 0.5 )\n    ~0.956\n\n\nbase.ellipj.dn( u, m )\n    Computes the Jacobi elliptic function dn.\n\n    Parameters\n    ----------\n    u: number\n        Input value.\n\n    m: number\n        Modulus m, equivalent to k².\n\n    Returns\n    -------\n    out: number\n        Jacobi elliptic function dn.\n\n    Examples\n    --------\n    > var v = base.ellipj.dn( 0.3, 0.5 )\n    ~0.978\n\n\nbase.ellipj.am( u, m )\n    Computes the Jacobi amplitude am.\n\n    Parameters\n    ----------\n    u: number\n        Input value.\n\n    m: number\n        Modulus m, equivalent to k².\n\n    Returns\n    -------\n    out: number\n        Jacobi elliptic function am.\n\n    Examples\n    --------\n    > var v = base.ellipj.am( 0.3, 0.5 )\n    ~0.298\n\n    See Also\n    --------\n    base.ellipe, base.ellipk","base.ellipj.assign":"\nbase.ellipj.assign( u, m, out, stride, offset )\n    Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n    amplitude am and assigns results to a provided output array.\n\n    Parameters\n    ----------\n    u: number\n        Input value.\n\n    m: number\n        Modulus m, equivalent to k².\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Jacobi elliptic functions and Jacobi amplitude.\n\n    Examples\n    --------\n    > var out = new Float64Array( 4 );\n    > var v = base.ellipj.assign( 0.3, 0.5, out, 1, 0 )\n    <Float64Array>[ ~0.293, ~0.956, ~0.978, ~0.298 ]\n    > var bool = ( v === out )\n    true","base.ellipj.sn":"\nbase.ellipj.sn( u, m )\n    Computes the Jacobi elliptic function sn.\n\n    Parameters\n    ----------\n    u: number\n        Input value.\n\n    m: number\n        Modulus m, equivalent to k².\n\n    Returns\n    -------\n    out: number\n        Jacobi elliptic function sn.\n\n    Examples\n    --------\n    > var v = base.ellipj.sn( 0.3, 0.5 )\n    ~0.293","base.ellipj.cn":"\nbase.ellipj.cn( u, m )\n    Computes the Jacobi elliptic functions cn.\n\n    Parameters\n    ----------\n    u: number\n        Input value.\n\n    m: number\n        Modulus m, equivalent to k².\n\n    Returns\n    -------\n    out: number\n        Jacobi elliptic function cn.\n\n    Examples\n    --------\n    > var v = base.ellipj.cn( 0.3, 0.5 )\n    ~0.956","base.ellipj.dn":"\nbase.ellipj.dn( u, m )\n    Computes the Jacobi elliptic function dn.\n\n    Parameters\n    ----------\n    u: number\n        Input value.\n\n    m: number\n        Modulus m, equivalent to k².\n\n    Returns\n    -------\n    out: number\n        Jacobi elliptic function dn.\n\n    Examples\n    --------\n    > var v = base.ellipj.dn( 0.3, 0.5 )\n    ~0.978","base.ellipj.am":"\nbase.ellipj.am( u, m )\n    Computes the Jacobi amplitude am.\n\n    Parameters\n    ----------\n    u: number\n        Input value.\n\n    m: number\n        Modulus m, equivalent to k².\n\n    Returns\n    -------\n    out: number\n        Jacobi elliptic function am.\n\n    Examples\n    --------\n    > var v = base.ellipj.am( 0.3, 0.5 )\n    ~0.298\n\n    See Also\n    --------\n    base.ellipe, base.ellipk","base.ellipk":"\nbase.ellipk( m )\n    Computes the complete elliptic integral of the first kind.\n\n    Parameters\n    ----------\n    m: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.ellipk( 0.5 )\n    ~1.854\n    > y = base.ellipk( -1.0 )\n    ~1.311\n    > y = base.ellipk( 2.0 )\n    NaN\n    > y = base.ellipk( PINF )\n    NaN\n    > y = base.ellipk( NINF )\n    NaN\n    > y = base.ellipk( NaN )\n    NaN\n\n    See Also\n    --------\n    base.ellipe, base.ellipj\n","base.endsWith":"\nbase.endsWith( str, search, len )\n    Tests if a string ends with the characters of another string.\n\n    If provided an empty search string, the function always returns `true`.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search string.\n\n    len: integer\n        Substring length. Restricts the search to a substring within the input\n        string beginning from the leftmost character. If provided a negative\n        value, `len` indicates to ignore the last `len` characters, and is thus\n        equivalent to `str.length + len`. Default: str.length.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a string ends with the characters of another\n        string.\n\n    Examples\n    --------\n    > var bool = base.endsWith( 'beep', 'ep', 4 )\n    true\n    > bool = base.endsWith( 'Beep', 'op', 4 )\n    false\n    > bool = base.endsWith( 'Beep', 'ee', 3 )\n    true\n    > bool = base.endsWith( 'Beep', 'ee', -1 )\n    true\n    > bool = base.endsWith( 'beep', '', 4 )\n    true\n\n    See Also\n    --------\n    base.startsWith\n","base.epsdiff":"\nbase.epsdiff( x, y[, scale] )\n    Computes the relative difference of two real numbers in units of double-\n    precision floating-point epsilon.\n\n    By default, the function scales the absolute difference by dividing the\n    absolute difference by the maximum absolute value of `x` and `y`. To scale\n    by a different function, specify a scale function name.\n\n    The following `scale` functions are supported:\n\n    - 'max-abs': maximum absolute value of `x` and `y` (default).\n    - 'max': maximum value of `x` and `y`.\n    - 'min-abs': minimum absolute value of `x` and `y`.\n    - 'min': minimum value of `x` and `y`.\n    - 'mean-abs': arithmetic mean of the absolute values of `x` and `y`.\n    - 'mean': arithmetic mean of `x` and `y`.\n    - 'x': `x` (*noncommutative*).\n    - 'y': `y` (*noncommutative*).\n\n    To use a custom scale function, provide a function which accepts two numeric\n    arguments `x` and `y`.\n\n    If computing the relative difference in units of epsilon will result in\n    overflow, the function returns the maximum double-precision floating-point\n    number.\n\n    If the absolute difference of `x` and `y` is `0`, the relative difference is\n    always `0`.\n\n    If `|x| = |y| = infinity`, the function returns `NaN`.\n\n    If `|x| = |-y| = infinity`, the relative difference is `+infinity`.\n\n    If a `scale` function returns `0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    scale: string|Function (optional)\n        Scale function. Default: `'max-abs'`.\n\n    Returns\n    -------\n    out: number\n        Relative difference in units of double-precision floating-point epsilon.\n\n    Examples\n    --------\n    > var d = base.epsdiff( 12.15, 12.149999999999999 )\n    ~0.658\n    > d = base.epsdiff( 2.4341309458983933, 2.4341309458633909, 'mean-abs' )\n    ~64761.512\n\n    // Custom scale function:\n    > function scale( x, y ) { return ( x > y ) ? y : x; };\n    > d = base.epsdiff( 1.0000000000000002, 1.0000000000000100, scale )\n    ~44\n\n    See Also\n    --------\n    base.absdiff, base.reldiff\n","base.erf":"\nbase.erf( x )\n    Evaluates the error function.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    As the error function is an odd function (i.e., `erf(-x) == -erf(x)`), if\n    provided `-0`, the function returns `-0`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.erf( 2.0 )\n    ~0.9953\n    > y = base.erf( -1.0 )\n    ~-0.8427\n    > y = base.erf( -0.0 )\n    -0.0\n    > y = base.erf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.erfc, base.erfinv, base.erfcinv\n","base.erfc":"\nbase.erfc( x )\n    Evaluates the complementary error function.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.erfc( 2.0 )\n    ~0.0047\n    > y = base.erfc( -1.0 )\n    ~1.8427\n    > y = base.erfc( 0.0 )\n    1.0\n    > y = base.erfc( PINF )\n    0.0\n    > y = base.erfc( NINF )\n    2.0\n    > y = base.erfc( NaN )\n    NaN\n\n    See Also\n    --------\n    base.erf, base.erfinv, base.erfcinv, base.erfcx\n","base.erfcinv":"\nbase.erfcinv( x )\n    Evaluates the inverse complementary error function.\n\n    The domain of `x` is restricted to `[0,2]`. If `x` is outside this interval,\n    the function returns `NaN`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.erfcinv( 0.5 )\n    ~0.4769\n    > y = base.erfcinv( 0.8 )\n    ~0.1791\n    > y = base.erfcinv( 0.0 )\n    Infinity\n    > y = base.erfcinv( 2.0 )\n    -Infinity\n    > y = base.erfcinv( NaN )\n    NaN\n\n    See Also\n    --------\n    base.erf, base.erfc, base.erfinv, base.erfcx\n","base.erfcx":"\nbase.erfcx( x )\n    Evaluates the scaled complementary error function.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.erfcx( 1.0 )\n    ~0.4276\n    > y = base.erfcx( -1.0 )\n    ~5.01\n    > y = base.erfcx( 0.0 )\n    1.0\n    > y = base.erfcx( NaN )\n    NaN\n\n    See Also\n    --------\n    base.erfc, base.erfcinv, base.erf, base.erfinv","base.erfinv":"\nbase.erfinv( x )\n    Evaluates the inverse error function.\n\n    If `|x| > 1`, the function returns `NaN`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    As the inverse error function is an odd function (i.e., `erfinv(-x) ==\n    -erfinv(x)`), if provided `-0`, the function returns `-0`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.erfinv( 0.5 )\n    ~0.4769\n    > y = base.erfinv( 0.8 )\n    ~0.9062\n    > y = base.erfinv( 0.0 )\n    0.0\n    > y = base.erfinv( -0.0 )\n    -0.0\n    > y = base.erfinv( -1.0 )\n    -Infinity\n    > y = base.erfinv( 1.0 )\n    Infinity\n    > y = base.erfinv( NaN )\n    NaN\n\n    See Also\n    --------\n    base.erf, base.erfc, base.erfcinv\n","base.eta":"\nbase.eta( s )\n    Evaluates the Dirichlet eta function for a double-precision\n    floating-point number `s`.\n\n    Parameters\n    ----------\n    s: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.eta( 0.0 )\n    0.5\n    > y = base.eta( -1.0 )\n    0.25\n    > y = base.eta( 1.0 )\n    ~0.6931\n    > y = base.eta( 3.14 )\n    ~0.9096\n    > y = base.eta( NaN )\n    NaN\n\n","base.evalpoly":"\nbase.evalpoly( c, x )\n    Evaluates a polynomial using double-precision floating-point arithmetic.\n\n    Parameters\n    ----------\n    c: Array<number>\n        Polynomial coefficients sorted in ascending degree.\n\n    x: number\n        Value at which to evaluate the polynomial.\n\n    Returns\n    -------\n    out: number\n        Evaluated polynomial.\n\n    Examples\n    --------\n    > var arr = [ 3.0, 2.0, 1.0 ];\n\n    // 3*10^0 + 2*10^1 + 1*10^2\n    > var v = base.evalpoly( arr, 10.0 )\n    123.0\n\n\nbase.evalpoly.factory( c )\n    Returns a function for evaluating a polynomial using double-precision\n    floating-point arithmetic.\n\n    Parameters\n    ----------\n    c: Array<number>\n        Polynomial coefficients sorted in ascending degree.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a polynomial.\n\n    Examples\n    --------\n    > var f = base.evalpoly.factory( [ 3.0, 2.0, 1.0 ] );\n\n    // 3*10^0 + 2*10^1 + 1*10^2\n    > var v = f( 10.0 )\n    123.0\n\n    // 3*5^0 + 2*5^1 + 1*5^2\n    > v = f( 5.0 )\n    38.0\n\n    See Also\n    --------\n    base.evalrational\n","base.evalpoly.factory":"\nbase.evalpoly.factory( c )\n    Returns a function for evaluating a polynomial using double-precision\n    floating-point arithmetic.\n\n    Parameters\n    ----------\n    c: Array<number>\n        Polynomial coefficients sorted in ascending degree.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a polynomial.\n\n    Examples\n    --------\n    > var f = base.evalpoly.factory( [ 3.0, 2.0, 1.0 ] );\n\n    // 3*10^0 + 2*10^1 + 1*10^2\n    > var v = f( 10.0 )\n    123.0\n\n    // 3*5^0 + 2*5^1 + 1*5^2\n    > v = f( 5.0 )\n    38.0\n\n    See Also\n    --------\n    base.evalrational","base.evalrational":"\nbase.evalrational( P, Q, x )\n    Evaluates a rational function using double-precision floating-point\n    arithmetic.\n\n    A rational function `f(x)` is defined as\n\n               P(x)\n        f(x) = ----\n               Q(x)\n\n    where both `P(x)` and `Q(x)` are polynomials in `x`.\n\n    The coefficients for both `P` and `Q` should be sorted in ascending degree.\n\n    For polynomials of different degree, the coefficient array for the lower\n    degree polynomial should be padded with zeros.\n\n    Parameters\n    ----------\n    P: Array<number>\n        Numerator polynomial coefficients sorted in ascending degree.\n\n    Q: Array<number>\n        Denominator polynomial coefficients sorted in ascending degree.\n\n    x: number\n        Value at which to evaluate the rational function.\n\n    Returns\n    -------\n    out: number\n        Evaluated rational function.\n\n    Examples\n    --------\n    // 2x^3 + 4x^2 - 5x^1 - 6x^0\n    > var P = [ -6.0, -5.0, 4.0, 2.0 ];\n\n    // 0.5x^1 + 3x^0\n    > var Q = [ 3.0, 0.5, 0.0, 0.0 ]; // zero-padded\n\n    // Evaluate the rational function:\n    > var v = base.evalrational( P, Q, 6.0 )\n    90.0\n\n\nbase.evalrational.factory( P, Q )\n    Returns a function for evaluating a rational function using double-precision\n    floating-point arithmetic.\n\n    Parameters\n    ----------\n    P: Array<number>\n        Numerator polynomial coefficients sorted in ascending degree.\n\n    Q: Array<number>\n        Denominator polynomial coefficients sorted in ascending degree.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a rational function.\n\n    Examples\n    --------\n    > var P = [ 20.0, 8.0, 3.0 ];\n    > var Q = [ 10.0, 9.0, 1.0 ];\n    > var f = base.evalrational.factory( P, Q );\n\n    // (20*10^0 + 8*10^1 + 3*10^2) / (10*10^0 + 9*10^1 + 1*10^2):\n    > var v = f( 10.0 )\n    2.0\n\n    // (20*2^0 + 8*2^1 + 3*2^2) / (10*2^0 + 9*2^1 + 1*2^2):\n    > v = f( 2.0 )\n    1.5\n\n    See Also\n    --------\n    base.evalpoly\n","base.evalrational.factory":"\nbase.evalrational.factory( P, Q )\n    Returns a function for evaluating a rational function using double-precision\n    floating-point arithmetic.\n\n    Parameters\n    ----------\n    P: Array<number>\n        Numerator polynomial coefficients sorted in ascending degree.\n\n    Q: Array<number>\n        Denominator polynomial coefficients sorted in ascending degree.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a rational function.\n\n    Examples\n    --------\n    > var P = [ 20.0, 8.0, 3.0 ];\n    > var Q = [ 10.0, 9.0, 1.0 ];\n    > var f = base.evalrational.factory( P, Q );\n\n    // (20*10^0 + 8*10^1 + 3*10^2) / (10*10^0 + 9*10^1 + 1*10^2):\n    > var v = f( 10.0 )\n    2.0\n\n    // (20*2^0 + 8*2^1 + 3*2^2) / (10*2^0 + 9*2^1 + 1*2^2):\n    > v = f( 2.0 )\n    1.5\n\n    See Also\n    --------\n    base.evalpoly","base.exp":"\nbase.exp( x )\n    Evaluates the natural exponential function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.exp( 4.0 )\n    ~54.5982\n    > y = base.exp( -9.0 )\n    ~1.234e-4\n    > y = base.exp( 0.0 )\n    1.0\n    > y = base.exp( NaN )\n    NaN\n\n    See Also\n    --------\n    base.exp10, base.exp2, base.expm1, base.ln\n","base.exp2":"\nbase.exp2( x )\n    Evaluates the base 2 exponential function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.exp2( 3.0 )\n    8.0\n    > y = base.exp2( -9.0 )\n    ~0.002\n    > y = base.exp2( 0.0 )\n    1.0\n    > y = base.exp2( NaN )\n    NaN\n\n    See Also\n    --------\n    base.exp, base.exp10, base.log2\n","base.exp10":"\nbase.exp10( x )\n    Evaluates the base 10 exponential function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.exp10( 3.0 )\n    1000\n    > y = base.exp10( -9.0 )\n    1.0e-9\n    > y = base.exp10( 0.0 )\n    1.0\n    > y = base.exp10( NaN )\n    NaN\n\n    See Also\n    --------\n    base.exp, base.exp2, base.log10\n","base.expit":"\nbase.expit( x )\n    Evaluates the standard logistic function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.expit( 0.0 )\n    0.5\n    > y = base.expit( 1.0 )\n    ~0.731\n    > y = base.expit( -1.0 )\n    ~0.269\n    > y = base.expit( Infinity )\n    1.0\n    > y = base.expit( NaN )\n    NaN\n\n    See Also\n    --------\n    base.exp, base.logit","base.expm1":"\nbase.expm1( x )\n    Computes `exp(x)-1`, where `exp(x)` is the natural exponential function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.expm1( 0.2 )\n    ~0.221\n    > y = base.expm1( -9.0 )\n    ~-1.0\n    > y = base.expm1( 0.0 )\n    0.0\n    > y = base.expm1( NaN )\n    NaN\n\n    See Also\n    --------\n    base.exp, base.expm1rel\n","base.expm1rel":"\nbase.expm1rel( x )\n    Relative error exponential.\n\n    When `x` is near zero,\n\n        e^x - 1\n\n    can suffer catastrophic cancellation (i.e., significant loss of precision).\n    This function avoids the loss of precision when `x` is near zero.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.expm1rel( 0.0 )\n    1.0\n    > y = base.expm1rel( 1.0 )\n    ~1.718\n    > y = base.expm1rel( -1.0 )\n    ~0.632\n    > y = base.expm1rel( NaN )\n    NaN\n\t\n    See Also\n    --------\n    base.exp, base.expm1\n","base.exponent":"\nbase.exponent( x )\n    Returns an integer corresponding to the unbiased exponent of a double-\n    precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    Returns\n    -------\n    out: integer\n        Unbiased exponent.\n\n    Examples\n    --------\n    > var exponent = base.exponent( 3.14e-307 )\n    -1019\n    > exponent = base.exponent( -3.14 )\n    1\n    > exponent = base.exponent( 0.0 )\n    -1023\n    > exponent = base.exponent( NaN )\n    1024\n\n    See Also\n    --------\n    base.exponentf\n","base.exponentf":"\nbase.exponentf( x )\n    Returns an integer corresponding to the unbiased exponent of a single-\n    precision floating-point number.\n\n    Parameters\n    ----------\n    x: float\n        Single-precision floating-point number.\n\n    Returns\n    -------\n    out: integer\n        Unbiased exponent.\n\n    Examples\n    --------\n    > var exponent = base.exponentf( base.float64ToFloat32( 3.14e34 ) )\n    114\n    > exponent = base.exponentf( base.float64ToFloat32( 3.14e-34 ) )\n    -112\n    > exponent = base.exponentf( base.float64ToFloat32( -3.14 ) )\n    1\n    > exponent = base.exponentf( 0.0 )\n    -127\n    > exponent = base.exponentf( NaN )\n    128\n\n    See Also\n    --------\n    base.exponent\n","base.factorial":"\nbase.factorial( x )\n    Evaluates the factorial of `x`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Factorial.\n\n    Examples\n    --------\n    > var y = base.factorial( 3.0 )\n    6.0\n    > y = base.factorial( -1.5 )\n    ~-3.545\n    > y = base.factorial( -0.5 )\n    ~1.772\n    > y = base.factorial( 0.5 )\n    ~0.886\n    > y = base.factorial( -10.0 )\n    NaN\n    > y = base.factorial( 171.0 )\n    Infinity\n    > y = base.factorial( NaN )\n    NaN\n\n    See Also\n    --------\n    base.factorialln\n","base.factorial2":"\nbase.factorial2( n )\n    Evaluates the double factorial of `n`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Double factorial.\n\n    Examples\n    --------\n    > var y = base.factorial2( 3 )\n    3\n    > y = base.factorial2( 5 )\n    15\n    > y = base.factorial2( 6 )\n    48\n    > y = base.factorial2( 301 )\n    Infinity\n    > y = base.factorial2( NaN )\n    NaN\n\n    See Also\n    --------\n    base.factorial\n","base.factorialln":"\nbase.factorialln( x )\n    Evaluates the natural logarithm of the factorial of `x`.\n\n    For input values other than negative integers, the function returns\n\n      ln( x! ) = ln( Γ(x+1) )\n\n    where `Γ` is the Gamma function. For negative integers, the function returns\n    `NaN`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Natural logarithm of the factorial of `x`.\n\n    Examples\n    --------\n    > var y = base.factorialln( 3.0 )\n    ~1.792\n    > y = base.factorialln( 2.4 )\n    ~1.092\n    > y = base.factorialln( -1.0 )\n    NaN\n    > y = base.factorialln( -1.5 )\n    ~1.266\n    > y = base.factorialln( NaN )\n    NaN\n\n    See Also\n    --------\n    base.factorial\n","base.fallingFactorial":"\nbase.fallingFactorial( x, n )\n    Computes the falling factorial of `x` and `n`.\n\n    If not provided a nonnegative integer for `n`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        First function parameter.\n\n    n: integer\n        Second function parameter.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var v = base.fallingFactorial( 0.9, 5 )\n    ~0.644\n    > v = base.fallingFactorial( -9.0, 3 )\n    -990.0\n    > v = base.fallingFactorial( 0.0, 2 )\n    0.0\n    > v = base.fallingFactorial( 3.0, -2 )\n    NaN\n\n    See Also\n    --------\n    base.risingFactorial\n","base.fibonacci":"\nbase.fibonacci( n )\n    Computes the nth Fibonacci number.\n\n    Fibonacci numbers follow the recurrence relation\n\n      F_n = F_{n-1} + F_{n-2}\n\n    with seed values F_0 = 0 and F_1 = 1.\n\n    If `n` is greater than `78`, the function returns `NaN`, as larger Fibonacci\n    numbers cannot be accurately represented due to limitations of double-\n    precision floating-point format.\n\n    If not provided a nonnegative integer value, the function returns `NaN`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Input value.\n\n    Returns\n    -------\n    y: integer\n        Fibonacci number.\n\n    Examples\n    --------\n    > var y = base.fibonacci( 0 )\n    0\n    > y = base.fibonacci( 1 )\n    1\n    > y = base.fibonacci( 2 )\n    1\n    > y = base.fibonacci( 3 )\n    2\n    > y = base.fibonacci( 4 )\n    3\n    > y = base.fibonacci( 79 )\n    NaN\n    > y = base.fibonacci( NaN )\n    NaN\n\n    See Also\n    --------\n    base.binet, base.fibonacciIndex, base.lucas, base.negafibonacci\n","base.fibonacciIndex":"\nbase.fibonacciIndex( F )\n    Computes the Fibonacci number index.\n\n    If not provided a nonnegative integer value, the function returns `NaN`.\n\n    If provided `F <= 1` or `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    F: integer\n        Fibonacci number.\n\n    Returns\n    -------\n    n: number\n        Fibonacci number index.\n\n    Examples\n    --------\n    > var n = base.fibonacciIndex( 2 )\n    3\n    > n = base.fibonacciIndex( 3 )\n    4\n    > n = base.fibonacciIndex( 5 )\n    5\n    > n = base.fibonacciIndex( NaN )\n    NaN\n    > n = base.fibonacciIndex( 1 )\n    NaN\n\n    See Also\n    --------\n    base.fibonacci\n","base.fibpoly":"\nbase.fibpoly( n, x )\n    Evaluates a Fibonacci polynomial.\n\n    Parameters\n    ----------\n    n: integer\n        Fibonacci polynomial to evaluate.\n\n    x: number\n        Value at which to evaluate the Fibonacci polynomial.\n\n    Returns\n    -------\n    out: number\n        Evaluated Fibonacci polynomial.\n\n    Examples\n    --------\n    // 2^4 + 3*2^2 + 1\n    > var v = base.fibpoly( 5, 2.0 )\n    29.0\n\n\nbase.fibpoly.factory( n )\n    Returns a function for evaluating a Fibonacci polynomial.\n\n    Parameters\n    ----------\n    n: integer\n        Fibonacci polynomial to evaluate.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a Fibonacci polynomial.\n\n    Examples\n    --------\n    > var polyval = base.fibpoly.factory( 5 );\n\n    // 1^4 + 3*1^2 + 1\n    > var v = polyval( 1.0 )\n    5.0\n\n    // 2^4 + 3*2^2 + 1\n    > v = polyval( 2.0 )\n    29.0\n\n    See Also\n    --------\n    base.evalpoly, base.lucaspoly\n","base.fibpoly.factory":"\nbase.fibpoly.factory( n )\n    Returns a function for evaluating a Fibonacci polynomial.\n\n    Parameters\n    ----------\n    n: integer\n        Fibonacci polynomial to evaluate.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a Fibonacci polynomial.\n\n    Examples\n    --------\n    > var polyval = base.fibpoly.factory( 5 );\n\n    // 1^4 + 3*1^2 + 1\n    > var v = polyval( 1.0 )\n    5.0\n\n    // 2^4 + 3*2^2 + 1\n    > v = polyval( 2.0 )\n    29.0\n\n    See Also\n    --------\n    base.evalpoly, base.lucaspoly","base.firstCodePoint":"\nbase.firstCodePoint( str, n )\n    Returns the first `n` Unicode code points of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of Unicode code points to return.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.firstCodePoint( 'beep', 1 )\n    'b'\n    > out = base.firstCodePoint( 'Boop', 1 )\n    'B'\n    > out = base.firstCodePoint( 'foo bar', 5 )\n    'foo b'\n\n    See Also\n    --------\n    base.firstCodeUnit, base.firstGraphemeCluster, base.lastCodePoint, base.removeFirstCodePoint, firstChar\n","base.firstCodeUnit":"\nbase.firstCodeUnit( str, n )\n    Returns the first `n` UTF-16 code units of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of UTF-16 code units to return.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.firstCodeUnit( 'beep', 1 )\n    'b'\n    > out = base.firstCodeUnit( 'Boop', 1 )\n    'B'\n    > out = base.firstCodeUnit( 'foo bar', 5 )\n    'foo b'\n\n    See Also\n    --------\n    base.firstCodePoint, base.firstGraphemeCluster, base.last, base.removeFirst, firstChar\n","base.firstGraphemeCluster":"\nbase.firstGraphemeCluster( str, n )\n    Returns the first `n` grapheme clusters (i.e., user-perceived characters) of\n    a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of grapheme clusters to return.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.firstGraphemeCluster( 'beep', 1 )\n    'b'\n    > out = base.firstGraphemeCluster( 'Boop', 1 )\n    'B'\n    > out = base.firstGraphemeCluster( 'foo bar', 5 )\n    'foo b'\n\n    See Also\n    --------\n    base.firstCodeUnit, base.firstCodePoint, base.lastGraphemeCluster, base.removeFirstGraphemeCluster, firstChar\n","base.flipsign":"\nbase.flipsign( x, y )\n    Returns a double-precision floating-point number with the magnitude of `x`\n    and the sign of `x*y`.\n\n    The function only returns `-x` when `y` is a negative number.\n\n    According to the IEEE 754 standard, a `NaN` has a biased exponent equal to\n    `2047`, a significand greater than `0`, and a sign bit equal to either `1`\n    or `0`. In which case, `NaN` may not correspond to just one but many binary\n    representations. Accordingly, care should be taken to ensure that `y` is not\n    `NaN`; otherwise, behavior may be indeterminate.\n\n    Parameters\n    ----------\n    x: number\n        Number from which to derive a magnitude.\n\n    y: number\n        Number from which to derive a sign.\n\n    Returns\n    -------\n    z: number\n        Double-precision floating-point number.\n\n    Examples\n    --------\n    > var z = base.flipsign( -3.0, 10.0 )\n    -3.0\n    > z = base.flipsign( -3.0, -1.0 )\n    3.0\n    > z = base.flipsign( 1.0, -0.0 )\n    -1.0\n    > z = base.flipsign( -3.0, -0.0 )\n    3.0\n    > z = base.flipsign( -0.0, 1.0 )\n    -0.0\n    > z = base.flipsign( 0.0, -1.0 )\n    -0.0\n\n    See Also\n    --------\n    base.copysign\n","base.flipsignf":"\nbase.flipsignf( x, y )\n    Returns a single-precision floating-point number with the magnitude of `x`\n    and the sign of `x*y`.\n\n    The function only returns `-x` when `y` is a negative number.\n\n    According to the IEEE 754 standard, a `NaN` has a biased exponent equal to\n    `255`, a significand greater than `0`, and a sign bit equal to either `1` or\n    `0`. In which case, `NaN` may not correspond to just one but many binary\n    representations. Accordingly, care should be taken to ensure that `y` is not\n    `NaN`; otherwise, behavior may be indeterminate.\n\n    Parameters\n    ----------\n    x: number\n        Number from which to derive a magnitude.\n\n    y: number\n        Number from which to derive a sign.\n\n    Returns\n    -------\n    z: number\n        Single-precision floating-point number.\n\n    Examples\n    --------\n    > var z = base.flipsignf( -3.0, 10.0 )\n    -3.0\n    > z = base.flipsignf( -3.0, -1.0 )\n    3.0\n    > z = base.flipsignf( 1.0, -0.0 )\n    -1.0\n    > z = base.flipsignf( -3.0, -0.0 )\n    3.0\n    > z = base.flipsignf( -0.0, 1.0 )\n    -0.0\n    > z = base.flipsignf( 0.0, -1.0 )\n    -0.0\n\n    See Also\n    --------\n    base.copysignf, base.flipsign\n","base.float32ToInt32":"\nbase.float32ToInt32( x )\n    Converts a single-precision floating-point number to a signed 32-bit\n    integer.\n\n    Parameters\n    ----------\n    x: float\n        Single-precision floating-point number.\n\n    Returns\n    -------\n    out: integer\n        Signed 32-bit integer.\n\n    Examples\n    --------\n    > var y = base.float32ToInt32( base.float64ToFloat32( 4294967295.0 ) )\n    0\n    > y = base.float32ToInt32( base.float64ToFloat32( 3.14 ) )\n    3\n    > y = base.float32ToInt32( base.float64ToFloat32( -3.14 ) )\n    -3\n    > y = base.float32ToInt32( base.float64ToFloat32( NaN ) )\n    0\n    > y = base.float32ToInt32( FLOAT32_PINF )\n    0\n    > y = base.float32ToInt32( FLOAT32_NINF )\n    0\n\n    See Also\n    --------\n    base.float32ToUint32","base.float32ToUint32":"\nbase.float32ToUint32( x )\n    Converts a single-precision floating-point number to a unsigned 32-bit\n    integer.\n\n    Parameters\n    ----------\n    x: float\n        Single-precision floating-point number.\n\n    Returns\n    -------\n    out: integer\n        Unsigned 32-bit integer.\n\n    Examples\n    --------\n    > var y = base.float32ToUint32( base.float64ToFloat32( 4294967297.0 ) )\n    0\n    > y = base.float32ToUint32( base.float64ToFloat32( 3.14 ) )\n    3\n    > y = base.float32ToUint32( base.float64ToFloat32( -3.14 ) )\n    4294967293\n    > y = base.float32ToUint32( base.float64ToFloat32( NaN ) )\n    0\n    > y = base.float32ToUint32( FLOAT32_PINF )\n    0\n    > y = base.float32ToUint32( FLOAT32_NINF )\n    0\n\n    See Also\n    --------\n    base.float32ToInt32","base.float64ToFloat32":"\nbase.float64ToFloat32( x )\n    Converts a double-precision floating-point number to the nearest single-\n    precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    Returns\n    -------\n    out: float\n        Nearest single-precision floating-point number.\n\n    Examples\n    --------\n    > var y = base.float64ToFloat32( 1.337 )\n    1.3370000123977661\n","base.float64ToInt32":"\nbase.float64ToInt32( x )\n    Converts a double-precision floating-point number to a signed 32-bit\n    integer.\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    Returns\n    -------\n    out: integer\n        Signed 32-bit integer.\n\n    Examples\n    --------\n    > var y = base.float64ToInt32( 4294967295.0 )\n    -1\n    > y = base.float64ToInt32( 3.14 )\n    3\n    > y = base.float64ToInt32( -3.14 )\n    -3\n    > y = base.float64ToInt32( NaN )\n    0\n    > y = base.float64ToInt32( PINF )\n    0\n    > y = base.float64ToInt32( NINF )\n    0\n\n    See Also\n    --------\n    base.float64ToUint32","base.float64ToInt64Bytes":"\nbase.float64ToInt64Bytes( x )\n    Converts an integer-valued double-precision floating-point number to a\n    signed 64-bit integer byte array according to host byte order (endianness).\n\n    This function assumes that the input value is less than the maximum safe\n    double-precision floating-point integer plus one (i.e., `2**53`).\n\n    Parameters\n    ----------\n    x: integer\n        Integer-valued double-precision floating-point number.\n\n    Returns\n    -------\n    out: Uint8Array\n        Byte array.\n\n    Examples\n    --------\n    > var y = base.float64ToInt64Bytes( 4294967297.0 )\n    <Uint8Array>\n\n\nbase.float64ToInt64Bytes.assign( x, out, stride, offset )\n    Converts an integer-valued double-precision floating-point number to a\n    signed 64-bit integer byte array according to host byte order (endianness)\n    and assigns results to a provided output array.\n\n    This function assumes that the input value is less than the maximum safe\n    double-precision floating-point integer plus one (i.e., `2**53`).\n\n    Parameters\n    ----------\n    x: integer\n        Integer-valued double-precision floating-point number.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Output array.\n\n    Examples\n    --------\n    > var out = new Uint8Array( 16 );\n    > var y = base.float64ToInt64Bytes( 4294967297.0, out, 2, 1 )\n    <Uint8Array>\n\n    See Also\n    --------\n    base.float64ToInt32","base.float64ToInt64Bytes.assign":"\nbase.float64ToInt64Bytes.assign( x, out, stride, offset )\n    Converts an integer-valued double-precision floating-point number to a\n    signed 64-bit integer byte array according to host byte order (endianness)\n    and assigns results to a provided output array.\n\n    This function assumes that the input value is less than the maximum safe\n    double-precision floating-point integer plus one (i.e., `2**53`).\n\n    Parameters\n    ----------\n    x: integer\n        Integer-valued double-precision floating-point number.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Output array.\n\n    Examples\n    --------\n    > var out = new Uint8Array( 16 );\n    > var y = base.float64ToInt64Bytes( 4294967297.0, out, 2, 1 )\n    <Uint8Array>\n\n    See Also\n    --------\n    base.float64ToInt32","base.float64ToUint32":"\nbase.float64ToUint32( x )\n    Converts a double-precision floating-point number to a unsigned 32-bit\n    integer.\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    Returns\n    -------\n    out: integer\n        Unsigned 32-bit integer.\n\n    Examples\n    --------\n    > var y = base.float64ToUint32( 4294967297.0 )\n    1\n    > y = base.float64ToUint32( 3.14 )\n    3\n    > y = base.float64ToUint32( -3.14 )\n    4294967293\n    > y = base.float64ToUint32( NaN )\n    0\n    > y = base.float64ToUint32( PINF )\n    0\n    > y = base.float64ToUint32( NINF )\n    0\n\n    See Also\n    --------\n    base.float64ToInt32","base.floor":"\nbase.floor( x )\n    Rounds a double-precision floating-point number toward negative infinity.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.floor( 3.14 )\n    3.0\n    > y = base.floor( -4.2 )\n    -5.0\n    > y = base.floor( -4.6 )\n    -5.0\n    > y = base.floor( 9.5 )\n    9.0\n    > y = base.floor( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceil, base.round\n","base.floor2":"\nbase.floor2( x )\n    Rounds a numeric value to the nearest power of two toward negative infinity.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.floor2( 3.14 )\n    2.0\n    > y = base.floor2( -4.2 )\n    -8.0\n    > y = base.floor2( -4.6 )\n    -8.0\n    > y = base.floor2( 9.5 )\n    8.0\n    > y = base.floor2( 13.0 )\n    8.0\n    > y = base.floor2( -13.0 )\n    -16.0\n    > y = base.floor2( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceil2, base.floor, base.floor10, base.round2\n","base.floor10":"\nbase.floor10( x )\n    Rounds a numeric value to the nearest power of ten toward negative infinity.\n\n    The function may not return accurate results for subnormals due to a general\n    loss in precision.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.floor10( 3.14 )\n    1.0\n    > y = base.floor10( -4.2 )\n    -10.0\n    > y = base.floor10( -4.6 )\n    -10.0\n    > y = base.floor10( 9.5 )\n    1.0\n    > y = base.floor10( 13.0 )\n    10.0\n    > y = base.floor10( -13.0 )\n    -100.0\n    > y = base.floor10( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceil10, base.floor, base.floor2, base.round10\n","base.floorb":"\nbase.floorb( x, n, b )\n    Rounds a numeric value to the nearest multiple of `b^n` toward negative\n    infinity.\n\n    Due to floating-point rounding error, rounding may not be exact.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Integer power.\n\n    b: integer\n        Base.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    // Round to 4 decimal places:\n    > var y = base.floorb( 3.14159, -4, 10 )\n    3.1415\n\n    // If `n = 0` or `b = 1`, standard round behavior:\n    > y = base.floorb( 3.14159, 0, 2 )\n    3.0\n\n    // Round to nearest multiple of two toward negative infinity:\n    > y = base.floorb( 5.0, 1, 2 )\n    4.0\n\n    See Also\n    --------\n    base.ceilb, base.floor, base.floorn, base.roundb\n","base.floorf":"\nbase.floorf( x )\n    Rounds a single-precision floating-point number toward negative infinity.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.floorf( 3.14 )\n    3.0\n    > y = base.floorf( -4.2 )\n    -5.0\n    > y = base.floorf( -4.6 )\n    -5.0\n    > y = base.floorf( 9.5 )\n    9.0\n    > y = base.floorf( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceilf, base.floor\n","base.floorn":"\nbase.floorn( x, n )\n    Rounds a double-precision floating-point number to the nearest multiple of\n    `10^n` toward negative infinity.\n\n    When operating on floating-point numbers in bases other than `2`, rounding\n    to specified digits can be inexact.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Integer power of 10.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    // Round to 4 decimal places:\n    > var y = base.floorn( 3.14159, -4 )\n    3.1415\n\n    // If `n = 0`, standard round toward negative infinity behavior:\n    > y = base.floorn( 3.14159, 0 )\n    3.0\n\n    // Round to nearest thousand:\n    > y = base.floorn( 12368.0, 3 )\n    12000.0\n\n\n    See Also\n    --------\n    base.ceiln, base.floor, base.floorb, base.roundn\n","base.floorsd":"\nbase.floorsd( x, n, b )\n    Rounds a numeric value to the nearest number toward negative infinity with\n    `n` significant figures.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Number of significant figures. Must be greater than 0.\n\n    b: integer\n        Base. Must be greater than 0.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.floorsd( 3.14159, 5, 10 )\n    3.1415\n    > y = base.floorsd( 3.14159, 1, 10 )\n    3.0\n    > y = base.floorsd( 12368.0, 2, 10 )\n    12000.0\n    > y = base.floorsd( 0.0313, 2, 2 )\n    0.03125\n\n    See Also\n    --------\n    base.ceilsd, base.floor, base.roundsd, base.truncsd\n","base.forEachChar":"\nbase.forEachChar( str, clbk[, thisArg] )\n    Invokes a function for each UTF-16 code unit in a string.\n\n    When invoked, the provided function is provided three arguments:\n\n    - value: character.\n    - index: character index.\n    - str: input string.\n\n    Parameters\n    ----------\n    str: string\n        Input string over which to iterate.\n\n    clbk: Function\n        The function to invoke for each UTF-16 code unit in the input string.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: string\n        Input string.\n\n    Examples\n    --------\n    > var n = 0;\n    > function fcn() { n += 1; };\n    > base.forEachChar( 'hello world!', fcn );\n    > n\n    12\n\n    See Also\n    --------\n    base.forEachCodePoint, base.forEachGraphemeCluster, forEachChar\n","base.forEachCodePoint":"\nbase.forEachCodePoint( str, clbk[, thisArg] )\n    Invokes a function for each Unicode code point in a string.\n\n    When invoked, the provided function is provided three arguments:\n\n    - value: code point.\n    - index: starting code point index.\n    - str: input string.\n\n    Parameters\n    ----------\n    str: string\n        Input string over which to iterate.\n\n    clbk: Function\n        The function to invoke for each Unicode code point in the input string.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: string\n        Input string.\n\n    Examples\n    --------\n    > var n = 0;\n    > function fcn() { n += 1; };\n    > base.forEachCodePoint( 'hello world!', fcn );\n    > n\n    12\n\n    See Also\n    --------\n    base.forEachChar, base.forEachGraphemeCluster, forEachChar\n","base.forEachCodePointRight":"\nbase.forEachCodePointRight( str, clbk[, thisArg] )\n    Invokes a function for each Unicode code point in a string, iterating from\n    right to left.\n\n    When invoked, the provided function is provided three arguments:\n\n    - value: code point.\n    - index: starting code point index.\n    - str: input string.\n\n    Parameters\n    ----------\n    str: string\n        Input string over which to iterate.\n\n    clbk: Function\n        The function to invoke for each Unicode code point in the input string.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: string\n        Input string.\n\n    Examples\n    --------\n    > var n = 0;\n    > function fcn() { n += 1; };\n    > base.forEachCodePointRight( 'hello world!', fcn );\n    > n\n    12\n\n    See Also\n    --------\n    base.forEachCodePoint, base.forEachRight\n","base.forEachGraphemeCluster":"\nbase.forEachGraphemeCluster( str, clbk[, thisArg] )\n    Invokes a function for each grapheme cluster (i.e., user-perceived\n    character) in a string.\n\n    When invoked, the provided function is provided three arguments:\n\n    - value: grapheme cluster.\n    - index: starting grapheme cluster index.\n    - str: input string.\n\n    Parameters\n    ----------\n    str: string\n        Input string over which to iterate.\n\n    clbk: Function\n        The function to invoke for each grapheme cluster in the input string.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: string\n        Input string.\n\n    Examples\n    --------\n    > var n = 0;\n    > function fcn() { n += 1; };\n    > base.forEachGraphemeCluster( 'hello world!', fcn );\n    > n\n    12\n\n    See Also\n    --------\n    base.forEachChar, base.forEachCodePoint, forEachChar\n","base.forEachRight":"\nbase.forEachRight( str, clbk[, thisArg] )\n    Invokes a function for each UTF-16 code unit in a string, iterating from\n    right to left.\n\n    When invoked, the provided function is provided three arguments:\n\n    - value: character.\n    - index: character index.\n    - str: input string.\n\n    Parameters\n    ----------\n    str: string\n        Input string over which to iterate.\n\n    clbk: Function\n        Function to invoke for each UTF-16 code unit in the input string.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: string\n        Input string.\n\n    Examples\n    --------\n    > var n = 0;\n    > function fcn() { n += 1; };\n    > base.forEachRight( 'hello world!', fcn );\n    > n\n    12\n\n    See Also\n    --------\n    base.forEachChar, base.forEachCodePointRight\n","base.formatInterpolate":"\nbase.formatInterpolate( tokens, ...args )\n    Generate string from a token array by interpolating values.\n\n    Parameters\n    ----------\n    tokens: Array\n        Array of string parts and format identifier objects.\n\n    args: ...any\n        Variable values.\n\n    Returns\n    -------\n    out: string\n        Formatted string.\n\n    Examples\n    --------\n    > var out = base.formatInterpolate( [ 'beep ', { 'specifier': 's' } ], 'boop' )\n    'beep boop'\n    > out = base.formatInterpolate( [ 'baz ', { 'specifier': 'd', 'precision': 2 } ], 1 )\n    'baz 1.00'\n    > out = base.formatInterpolate( [ { 'specifier': 'u', 'width': 6 } ], 12 )\n    '    12'\n\n    See Also\n    --------\n    base.formatTokenize\n","base.formatTokenize":"\nbase.formatTokenize( str )\n    Tokenize a string into an array of string parts and format identifier\n    objects.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: Array\n        Array of string parts and format identifier objects.\n\n    Examples\n    --------\n    > var out = base.formatTokenize( 'Hello %s!' )\n    [ 'Hello ', {...}, '!' ]\n    > out = base.formatTokenize( '%s %s %d' )\n    [ {...}, ' ', {...}, ' ', {...}, ' ' ]\n    > out = base.formatTokenize( 'Pi: %.2f' )\n    [ 'Pi: ', {...} ]\n\n    See Also\n    --------\n    base.formatInterpolate\n","base.fresnel":"\nbase.fresnel( x )\n    Computes the Fresnel integrals S(x) and C(x).\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: Array<number>\n        S(x) and C(x).\n\n    Examples\n    --------\n    > var y = base.fresnel( 0.0 )\n    [ ~0.0, ~0.0 ]\n    > y = base.fresnel( 1.0 )\n    [ ~0.438, ~0.780 ]\n    > y = base.fresnel( PINF )\n    [ ~0.5, ~0.5 ]\n    > y = base.fresnel( NINF )\n    [ ~-0.5, ~-0.5 ]\n    > y = base.fresnel( NaN )\n    [ NaN, NaN ]\n\n\nbase.fresnel.assign( x, out, stride, offset )\n    Computes the Fresnel integrals S(x) and C(x) and assigns results to a\n    provided output array.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    out: Array<number>\n        Destination array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array<number>\n        S(x) and C(x).\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var v = base.fresnel.assign( 0.0, out, 1, 0 )\n    <Float64Array>[ ~0.0, ~0.0 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.fresnelc, base.fresnels","base.fresnel.assign":"\nbase.fresnel.assign( x, out, stride, offset )\n    Computes the Fresnel integrals S(x) and C(x) and assigns results to a\n    provided output array.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    out: Array<number>\n        Destination array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array<number>\n        S(x) and C(x).\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var v = base.fresnel.assign( 0.0, out, 1, 0 )\n    <Float64Array>[ ~0.0, ~0.0 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.fresnelc, base.fresnels","base.fresnelc":"\nbase.fresnelc( x )\n    Computes the Fresnel integral C(x).\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        C(x).\n\n    Examples\n    --------\n    > var y = base.fresnelc( 0.0 )\n    ~0.0\n    > y = base.fresnelc( 1.0 )\n    ~0.780\n    > y = base.fresnelc( PINF )\n    ~0.5\n    > y = base.fresnelc( NINF )\n    ~-0.5\n    > y = base.fresnelc( NaN )\n    NaN\n\n    See Also\n    --------\n    base.fresnel, base.fresnels\n","base.fresnels":"\nbase.fresnels( x )\n    Computes the Fresnel integral S(x).\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        S(x).\n\n    Examples\n    --------\n    > var y = base.fresnels( 0.0 )\n    ~0.0\n    > y = base.fresnels( 1.0 )\n    ~0.438\n    > y = base.fresnels( PINF )\n    ~0.5\n    > y = base.fresnels( NINF )\n    ~-0.5\n    > y = base.fresnels( NaN )\n    NaN\n\n    See Also\n    --------\n    base.fresnel, base.fresnelc\n","base.frexp":"\nbase.frexp( x )\n    Splits a double-precision floating-point number into a normalized fraction\n    and an integer power of two.\n\n    The first element of the returned array is the normalized fraction and the\n    second is the exponent. The normalized fraction and exponent satisfy the\n    relation\n\n      x = frac * 2^exp\n\n    If provided positive or negative zero, `NaN`, or positive or negative\n    infinity, the function returns a two-element array containing the input\n    value and an exponent equal to zero.\n\n    For all other numeric input values, the absolute value of the normalized\n    fraction resides on the interval [0.5,1).\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    out: Array<number>\n        A normalized fraction and an exponent.\n\n    Examples\n    --------\n    > var out = base.frexp( 4.0 )\n    [ 0.5, 3 ]\n    > out = base.frexp( 0.0 )\n    [ 0.0, 0 ]\n    > out = base.frexp( -0.0 )\n    [ -0.0, 0 ]\n    > out = base.frexp( NaN )\n    [ NaN, 0 ]\n    > out = base.frexp( PINF )\n    [ Infinity, 0 ]\n    > out = base.frexp( NINF )\n    [ -Infinity, 0 ]\n\n\nbase.frexp.assign( x, out, stride, offset )\n    Splits a double-precision floating-point number into a normalized fraction\n    and an integer power of two and assigns results to a provided output array.\n\n    The first element of the returned array is the normalized fraction and the\n    second is the exponent. The normalized fraction and exponent satisfy the\n    relation\n\n      x = frac * 2^exp\n\n    If provided positive or negative zero, `NaN`, or positive or negative\n    infinity, the function returns a two-element array containing the input\n    value and an exponent equal to zero.\n\n    For all other numeric input values, the absolute value of the normalized\n    fraction resides on the interval [0.5,1).\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    out: Array<number>\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array<number>\n        A normalized fraction and an exponent.\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var y = base.frexp.assign( 4.0, out, 1, 0 )\n    <Float64Array>[ 0.5, 3 ]\n    > var bool = ( y === out )\n    true\n\n    See Also\n    --------\n    base.ldexp\n","base.frexp.assign":"\nbase.frexp.assign( x, out, stride, offset )\n    Splits a double-precision floating-point number into a normalized fraction\n    and an integer power of two and assigns results to a provided output array.\n\n    The first element of the returned array is the normalized fraction and the\n    second is the exponent. The normalized fraction and exponent satisfy the\n    relation\n\n      x = frac * 2^exp\n\n    If provided positive or negative zero, `NaN`, or positive or negative\n    infinity, the function returns a two-element array containing the input\n    value and an exponent equal to zero.\n\n    For all other numeric input values, the absolute value of the normalized\n    fraction resides on the interval [0.5,1).\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    out: Array<number>\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array<number>\n        A normalized fraction and an exponent.\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var y = base.frexp.assign( 4.0, out, 1, 0 )\n    <Float64Array>[ 0.5, 3 ]\n    > var bool = ( y === out )\n    true\n\n    See Also\n    --------\n    base.ldexp","base.fromBinaryString":"\nbase.fromBinaryString( bstr )\n    Creates a double-precision floating-point number from a literal bit\n    representation.\n\n    Parameters\n    ----------\n    bstr: string\n        Literal bit representation.\n\n    Returns\n    -------\n    out: number\n        Double-precision floating-point number.\n\n    Examples\n    --------\n    > var bstr;\n    > bstr = '0100000000010000000000000000000000000000000000000000000000000000';\n    > var val = base.fromBinaryString( bstr )\n    4.0\n    > bstr = '0100000000001001001000011111101101010100010001000010110100011000';\n    > val = base.fromBinaryString( bstr )\n    3.141592653589793\n    > bstr = '1111111111100001110011001111001110000101111010111100100010100000';\n    > val = base.fromBinaryString( bstr )\n    -1.0e308\n\n    // The function handles subnormals:\n    > bstr = '1000000000000000000000000000000000000000000000000001100011010011';\n    > val = base.fromBinaryString( bstr )\n    -3.14e-320\n    > bstr = '0000000000000000000000000000000000000000000000000000000000000001';\n    > val = base.fromBinaryString( bstr )\n    5.0e-324\n\n    // The function handles special values:\n    > bstr = '0000000000000000000000000000000000000000000000000000000000000000';\n    > val = base.fromBinaryString( bstr )\n    0.0\n    > bstr = '1000000000000000000000000000000000000000000000000000000000000000';\n    > val = base.fromBinaryString( bstr )\n    -0.0\n    > bstr = '0111111111111000000000000000000000000000000000000000000000000000';\n    > val = base.fromBinaryString( bstr )\n    NaN\n    > bstr = '0111111111110000000000000000000000000000000000000000000000000000';\n    > val = base.fromBinaryString( bstr )\n    Infinity\n    > bstr = '1111111111110000000000000000000000000000000000000000000000000000';\n    > val = base.fromBinaryString( bstr )\n    -Infinity\n\n    See Also\n    --------\n    base.fromBinaryStringf, base.toBinaryString\n","base.fromBinaryStringf":"\nbase.fromBinaryStringf( bstr )\n    Creates a single-precision floating-point number from an IEEE 754 literal\n    bit representation.\n\n    Parameters\n    ----------\n    bstr: string\n        Literal bit representation.\n\n    Returns\n    -------\n    out: float\n        Single-precision floating-point number.\n\n    Examples\n    --------\n    > var bstr = '01000000100000000000000000000000';\n    > var val = base.fromBinaryStringf( bstr )\n    4.0\n    > bstr = '01000000010010010000111111011011';\n    > val = base.fromBinaryStringf( bstr )\n    ~3.14\n    > bstr = '11111111011011000011101000110011';\n    > val = base.fromBinaryStringf( bstr )\n    ~-3.14e+38\n\n    // The function handles subnormals:\n    > bstr = '10000000000000000000000000010110';\n    > val = base.fromBinaryStringf( bstr )\n    ~-3.08e-44\n    > bstr = '00000000000000000000000000000001';\n    > val = base.fromBinaryStringf( bstr )\n    ~1.40e-45\n\n    // The function handles special values:\n    > bstr = '00000000000000000000000000000000';\n    > val = base.fromBinaryStringf( bstr )\n    0.0\n    > bstr = '10000000000000000000000000000000';\n    > val = base.fromBinaryStringf( bstr )\n    -0.0\n    > bstr = '01111111110000000000000000000000';\n    > val = base.fromBinaryStringf( bstr )\n    NaN\n    > bstr = '01111111100000000000000000000000';\n    > val = base.fromBinaryStringf( bstr )\n    Infinity\n    > bstr = '11111111100000000000000000000000';\n    > val = base.fromBinaryStringf( bstr )\n    -Infinity\n\n    See Also\n    --------\n    base.toBinaryStringf, base.fromBinaryString\n","base.fromBinaryStringUint8":"\nbase.fromBinaryStringUint8( bstr )\n    Creates an unsigned 8-bit integer from a literal bit representation.\n\n    Parameters\n    ----------\n    bstr: string\n        Literal bit representation.\n\n    Returns\n    -------\n    out: integer\n        Unsigned 8-bit integer.\n\n    Examples\n    --------\n    > var bstr = '01010101';\n    > var val = base.fromBinaryStringUint8( bstr )\n    85\n    > bstr = '00000000';\n    > val = base.fromBinaryStringUint8( bstr )\n    0\n    > bstr = '00000010';\n    > val = base.fromBinaryStringUint8( bstr )\n    2\n    > bstr = '11111111';\n    > val = base.fromBinaryStringUint8( bstr )\n    255\n\n    See Also\n    --------\n    base.fromBinaryStringUint16, base.fromBinaryStringUint32, base.toBinaryStringUint8\n","base.fromBinaryStringUint16":"\nbase.fromBinaryStringUint16( bstr )\n    Creates an unsigned 16-bit integer from a literal bit representation.\n\n    Parameters\n    ----------\n    bstr: string\n        Literal bit representation.\n\n    Returns\n    -------\n    out: integer\n        Unsigned 16-bit integer.\n\n    Examples\n    --------\n    > var bstr = '0101010101010101';\n    > var val = base.fromBinaryStringUint16( bstr )\n    21845\n    > bstr = '0000000000000000';\n    > val = base.fromBinaryStringUint16( bstr )\n    0\n    > bstr = '0000000000000010';\n    > val = base.fromBinaryStringUint16( bstr )\n    2\n    > bstr = '1111111111111111';\n    > val = base.fromBinaryStringUint16( bstr )\n    65535\n\n    See Also\n    --------\n    base.toBinaryStringUint16, base.fromBinaryStringUint32, base.fromBinaryStringUint8\n","base.fromBinaryStringUint32":"\nbase.fromBinaryStringUint32( bstr )\n    Creates an unsigned 32-bit integer from a literal bit representation.\n\n    Parameters\n    ----------\n    bstr: string\n        Literal bit representation.\n\n    Returns\n    -------\n    out: integer\n        Unsigned 32-bit integer.\n\n    Examples\n    --------\n    > var bstr = '01010101010101010101010101010101';\n    > var val = base.fromBinaryStringUint32( bstr )\n    1431655765\n    > bstr = '00000000000000000000000000000000';\n    > val = base.fromBinaryStringUint32( bstr )\n    0\n    > bstr = '00000000000000000000000000000010';\n    > val = base.fromBinaryStringUint32( bstr )\n    2\n    > bstr = '11111111111111111111111111111111';\n    > val = base.fromBinaryStringUint32( bstr )\n    4294967295\n\n    See Also\n    --------\n    base.fromBinaryStringUint16, base.toBinaryStringUint32, base.fromBinaryStringUint8\n","base.fromInt64Bytes":"\nbase.fromInt64Bytes( bytes, stride, offset )\n    Converts a signed 64-bit integer byte array to a double-precision floating-\n    point number.\n\n    The function assumes host byte order (endianness).\n\n    Parameters\n    ----------\n    bytes: Array<number>|TypedArray|Object\n        Byte array.\n\n    stride: integer\n        Index stride.\n\n    offset: integer\n        Index offset.\n\n    Returns\n    -------\n    out: number\n        Number.\n\n    Examples\n    --------\n    > var bytes = new Uint8Array( [ 255, 255, 255, 255, 255, 255, 255, 255 ] );\n    > var y = base.fromInt64Bytes( bytes, 1, 0 )\n    -1.0\n\n    See Also\n    --------\n    base.float64ToInt64Bytes","base.fromWordf":"\nbase.fromWordf( word )\n    Creates a single-precision floating-point number from an unsigned integer\n    corresponding to an IEEE 754 binary representation.\n\n    Parameters\n    ----------\n    word: integer\n        Unsigned integer.\n\n    Returns\n    -------\n    out: float\n        Single-precision floating-point number.\n\n    Examples\n    --------\n    > var word = 1068180177; // => 0 01111111 01010110010001011010001\n    > var f32 = base.fromWordf( word ) // when printed, promoted to float64\n    1.3370000123977661\n\n    See Also\n    --------\n    base.fromWords\n","base.fromWords":"\nbase.fromWords( high, low )\n    Creates a double-precision floating-point number from a higher order word\n    (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n\n    Parameters\n    ----------\n    high: integer\n        Higher order word (unsigned 32-bit integer).\n\n    low: integer\n        Lower order word (unsigned 32-bit integer).\n\n    Returns\n    -------\n    out: number\n        Double-precision floating-point number.\n\n    Examples\n    --------\n    > var v = base.fromWords( 1774486211, 2479577218 )\n    3.14e201\n    > v = base.fromWords( 3221823995, 1413754136 )\n    -3.141592653589793\n    > v = base.fromWords( 0, 0 )\n    0.0\n    > v = base.fromWords( 2147483648, 0 )\n    -0.0\n    > v = base.fromWords( 2146959360, 0 )\n    NaN\n    > v = base.fromWords( 2146435072, 0 )\n    Infinity\n    > v = base.fromWords( 4293918720, 0 )\n    -Infinity\n\n    See Also\n    --------\n    base.fromWordf\n","base.gamma":"\nbase.gamma( x )\n    Evaluates the gamma function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.gamma( 4.0 )\n    6.0\n    > y = base.gamma( -1.5 )\n    ~2.363\n    > y = base.gamma( -0.5 )\n    ~-3.545\n    > y = base.gamma( 0.5 )\n    ~1.772\n    > y = base.gamma( 0.0 )\n    Infinity\n    > y = base.gamma( -0.0 )\n    -Infinity\n    > y = base.gamma( NaN )\n    NaN\n\n    See Also\n    --------\n    base.gamma1pm1, base.gammainc, base.gammaincinv, base.gammaln\n","base.gamma1pm1":"\nbase.gamma1pm1( x )\n    Computes `gamma(x+1) - 1` without cancellation errors, where `gamma(x)` is\n    the gamma function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.gamma1pm1( 0.2 )\n    ~-0.082\n    > y = base.gamma1pm1( -6.7 )\n    ~-0.991\n    > y = base.gamma1pm1( 0.0 )\n    0.0\n    > y = base.gamma1pm1( NaN )\n    NaN\n\n    See Also\n    --------\n    base.gamma, base.gammainc, base.gammaincinv, base.gammaln\n","base.gammaDeltaRatio":"\nbase.gammaDeltaRatio( z, delta )\n    Computes the ratio of two gamma functions.\n\n    The ratio is defined as: Γ(z) / Γ(z+Δ).\n\n    Parameters\n    ----------\n    z: number\n        First gamma parameter.\n\n    delta: number\n        Difference.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.gammaDeltaRatio( 2.0, 3.0 )\n    ~0.042\n    > y = base.gammaDeltaRatio( 4.0, 0.5 )\n    ~0.516\n    > y = base.gammaDeltaRatio( 100.0, 0.0 )\n    1.0\n    > y = base.gammaDeltaRatio( NaN, 3.0 )\n    NaN\n    > y = base.gammaDeltaRatio( 5.0, NaN )\n    NaN\n    > y = base.gammaDeltaRatio( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.gamma\n","base.gammainc":"\nbase.gammainc( x, s[, regularized[, upper]] )\n    Computes the regularized incomplete gamma function.\n\n    The `regularized` and `upper` parameters specify whether to evaluate the\n    non-regularized and/or upper incomplete gamma functions, respectively.\n\n    If provided `x < 0` or `s <= 0`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        First function parameter.\n\n    s: number\n        Second function parameter.\n\n    regularized: boolean (optional)\n        Boolean indicating whether the function should evaluate the regularized\n        or non-regularized incomplete gamma function. Default: `true`.\n\n    upper: boolean (optional)\n        Boolean indicating whether the function should return the upper tail of\n        the incomplete gamma function. Default: `false`.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.gammainc( 6.0, 2.0 )\n    ~0.9826\n    > y = base.gammainc( 1.0, 2.0, true, true )\n    ~0.7358\n    > y = base.gammainc( 7.0, 5.0 )\n    ~0.8270\n    > y = base.gammainc( 7.0, 5.0, false )\n    ~19.8482\n    > y = base.gammainc( NaN, 2.0 )\n    NaN\n    > y = base.gammainc( 6.0, NaN )\n    NaN\n\n    See Also\n    --------\n    base.gamma, base.gamma1pm1, base.gammaincinv, base.gammaln\n","base.gammaincinv":"\nbase.gammaincinv( p, a[, upper] )\n    Computes the inverse of the lower incomplete gamma function.\n\n    In contrast to a more commonly used definition, the first argument is the\n    probability `p` and the second argument is the scale factor `a`.\n\n    By default, the function inverts the lower regularized incomplete gamma\n    function, `P(x,a)`. To invert the upper function `Q(x,a)`, set the `upper`\n    argument to `true`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    If provided `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Probability.\n\n    a: number\n        Scale parameter.\n\n    upper: boolean (optional)\n        Boolean indicating if the function should invert the upper tail of the\n        incomplete gamma function; i.e., compute `xr` such that `Q(a,xr) = p`.\n        Default: `false`.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.gammaincinv( 0.5, 2.0 )\n    ~1.678\n    > y = base.gammaincinv( 0.1, 10.0 )\n    ~6.221\n    > y = base.gammaincinv( 0.75, 3.0 )\n    ~3.92\n    > y = base.gammaincinv( 0.75, 3.0, true )\n    ~1.727\n    > y = base.gammaincinv( 0.75, NaN )\n    NaN\n    > y = base.gammaincinv( NaN, 3.0 )\n    NaN\n\n    See Also\n    --------\n    base.gamma, base.gamma1pm1, base.gammainc, base.gammaln\n","base.gammaLanczosSum":"\nbase.gammaLanczosSum( x )\n    Calculates the Lanczos sum for the approximation of the gamma function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Lanczos sum.\n\n    Examples\n    --------\n    > var y = base.gammaLanczosSum( 4.0 )\n    ~950.366\n    > y = base.gammaLanczosSum( -1.5 )\n    ~1373366.245\n    > y = base.gammaLanczosSum( -0.5 )\n    ~-699841.735\n    > y = base.gammaLanczosSum( 0.5 )\n    ~96074.186\n    > y = base.gammaLanczosSum( 0.0 )\n    Infinity\n    > y = base.gammaLanczosSum( NaN )\n    NaN\n\n    See Also\n    --------\n    base.gamma, base.gammaLanczosSumExpGScaled\n","base.gammaLanczosSumExpGScaled":"\nbase.gammaLanczosSumExpGScaled( x )\n    Calculates the scaled Lanczos sum for the approximation of the gamma\n    function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Scaled Lanczos sum.\n\n    Examples\n    --------\n    > var y = base.gammaLanczosSumExpGScaled( 4.0 )\n    ~0.018\n    > y = base.gammaLanczosSumExpGScaled( -1.5 )\n    ~25.337\n    > y = base.gammaLanczosSumExpGScaled( -0.5 )\n    ~-12.911\n    > y = base.gammaLanczosSumExpGScaled( 0.5 )\n    ~1.772\n    > y = base.gammaLanczosSumExpGScaled( 0.0 )\n    Infinity\n    > y = base.gammaLanczosSumExpGScaled( NaN )\n    NaN\n\n    See Also\n    --------\n    base.gamma, base.gammaLanczosSum\n","base.gammaln":"\nbase.gammaln( x )\n    Evaluates the natural logarithm of the gamma function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Natural logarithm of the gamma function.\n\n    Examples\n    --------\n    > var y = base.gammaln( 1.0 )\n    0.0\n    > y = base.gammaln( 2.0 )\n    0.0\n    > y = base.gammaln( 4.0 )\n    ~1.792\n    > y = base.gammaln( -0.5 )\n    ~1.266\n    > y = base.gammaln( 0.5 )\n    ~0.572\n    > y = base.gammaln( 0.0 )\n    Infinity\n    > y = base.gammaln( NaN )\n    NaN\n\n    See Also\n    --------\n    base.gamma, base.gammainc, base.gammaincinv\n","base.gammasgn":"\nbase.gammasgn( x )\n    Computes the sign of the gamma function.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Sign of the gamma function.\n\n    Examples\n    --------\n    > var y = base.gammasgn( 1.0 )\n    1.0\n    > y = base.gammasgn( -2.5 )\n    -1.0\n    > y = base.gammasgn( 0.0 )\n    0.0\n    > y = base.gammasgn( NaN )\n    NaN\n\n    See Also\n    --------\n    base.gamma","base.gcd":"\nbase.gcd( a, b )\n    Computes the greatest common divisor (gcd).\n\n    If both `a` and `b` are `0`, the function returns `0`.\n\n    Both `a` and `b` must have integer values; otherwise, the function returns\n    `NaN`.\n\n    Parameters\n    ----------\n    a: integer\n        First number.\n\n    b: integer\n        Second number.\n\n    Returns\n    -------\n    out: integer\n        Greatest common divisor.\n\n    Examples\n    --------\n    > var v = base.gcd( 48, 18 )\n    6\n\n    See Also\n    --------\n    base.lcm\n","base.getHighWord":"\nbase.getHighWord( x )\n    Returns an unsigned 32-bit integer corresponding to the more significant 32\n    bits of a double-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    out: integer\n        Higher order word (unsigned 32-bit integer).\n\n    Examples\n    --------\n    > var w = base.getHighWord( 3.14e201 )\n    1774486211\n\n    See Also\n    --------\n    base.getLowWord, base.setHighWord\n","base.getLowWord":"\nbase.getLowWord( x )\n    Returns an unsigned 32-bit integer corresponding to the less significant 32\n    bits of a double-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    out: integer\n        Lower order word (unsigned 32-bit integer).\n\n    Examples\n    --------\n    > var w = base.getLowWord( 3.14e201 )\n    2479577218\n\n    See Also\n    --------\n    base.getHighWord, base.setHighWord\n","base.hacovercos":"\nbase.hacovercos( x )\n    Computes the half-value coversed cosine.\n\n    The half-value coversed cosine is defined as `(1 + sin(x)) / 2`.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Half-value coversed cosine.\n\n    Examples\n    --------\n    > var y = base.hacovercos( 3.14 )\n    ~0.5008\n    > y = base.hacovercos( -4.2 )\n    ~0.9358\n    > y = base.hacovercos( -4.6 )\n    ~0.9968\n    > y = base.hacovercos( 9.5 )\n    ~0.4624\n    > y = base.hacovercos( -0.0 )\n    0.5\n\n    See Also\n    --------\n    base.hacoversin, base.havercos\n","base.hacoversin":"\nbase.hacoversin( x )\n    Computes the half-value coversed sine.\n\n    The half-value coversed sine is defined as `(1 - sin(x)) / 2`.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Half-value coversed sine.\n\n    Examples\n    --------\n    > var y = base.hacoversin( 3.14 )\n    ~0.4992\n    > y = base.hacoversin( -4.2 )\n    ~0.0642\n    > y = base.hacoversin( -4.6 )\n    ~0.0032\n    > y = base.hacoversin( 9.5 )\n    ~0.538\n    > y = base.hacoversin( -0.0 )\n    0.5\n\n    See Also\n    --------\n    base.hacovercos, base.haversin\n","base.havercos":"\nbase.havercos( x )\n    Computes the half-value versed cosine.\n\n    The half-value versed cosine is defined as `(1 + cos(x)) / 2`.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Half-value versed cosine.\n\n    Examples\n    --------\n    > var y = base.havercos( 3.14 )\n    ~0.0\n    > y = base.havercos( -4.2 )\n    ~0.2549\n    > y = base.havercos( -4.6 )\n    ~0.4439\n    > y = base.havercos( 9.5 )\n    ~0.0014\n    > y = base.havercos( -0.0 )\n    1.0\n\n    See Also\n    --------\n    base.haversin, base.vercos\n","base.haversin":"\nbase.haversin( x )\n    Computes the half-value versed sine.\n\n    The half-value versed sine is defined as `(1 - cos(x)) / 2`.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Half-value versed sine.\n\n    Examples\n    --------\n    > var y = base.haversin( 3.14 )\n    ~1.0\n    > y = base.haversin( -4.2 )\n    ~0.7451\n    > y = base.haversin( -4.6 )\n    ~0.5561\n    > y = base.haversin( 9.5 )\n    ~0.9986\n    > y = base.haversin( -0.0 )\n    0.0\n\n    See Also\n    --------\n    base.havercos, base.versin\n","base.headercase":"\nbase.headercase( str )\n    Converts a string to HTTP header case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        HTTP header-cased string.\n\n    Examples\n    --------\n    > var out = base.headercase( 'Hello World!' )\n    'Hello-World'\n    > out = base.headercase( 'beep boop' )\n    'Beep-Boop'\n\n    See Also\n    --------\n    base.camelcase, base.pascalcase, base.uppercase","base.heaviside":"\nbase.heaviside( x[, continuity] )\n    Evaluates the Heaviside function.\n\n    The `continuity` parameter may be one of the following:\n\n    - 'half-maximum': if `x == 0`, the function returns `0.5`.\n    - 'left-continuous': if `x == 0`, the function returns `0`.\n    - 'right-continuous': if `x == 0`, the function returns `1`.\n\n    By default, if `x == 0`, the function returns `NaN` (i.e., the function is\n    discontinuous).\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    continuity: string (optional)\n        Specifies how to handle `x == 0`. By default, if `x == 0`, the function\n        returns `NaN`.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.heaviside( 3.14 )\n    1.0\n    > y = base.heaviside( -3.14 )\n    0.0\n    > y = base.heaviside( 0.0 )\n    NaN\n    > y = base.heaviside( 0.0, 'half-maximum' )\n    0.5\n    > y = base.heaviside( 0.0, 'left-continuous' )\n    0.0\n    > y = base.heaviside( 0.0, 'right-continuous' )\n    1.0\n\n    See Also\n    --------\n    base.ramp\n","base.hermitepoly":"\nbase.hermitepoly( n, x )\n    Evaluates a physicist's Hermite polynomial.\n\n    Parameters\n    ----------\n    n: integer\n        Nonnegative polynomial degree.\n\n    x: number\n        Value at which to evaluate the polynomial.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.hermitepoly( 1, 0.5 )\n    1.0\n    > y = base.hermitepoly( -1, 0.5 )\n    NaN\n    > y = base.hermitepoly( 0, 0.5 )\n    1.0\n    > y = base.hermitepoly( 2, 0.5 )\n    -1.0\n\n\nbase.hermitepoly.factory( n )\n    Returns a function for evaluating a physicist's Hermite polynomial.\n\n    Parameters\n    ----------\n    n: integer\n        Nonnegative polynomial degree.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a physicist's Hermite polynomial.\n\n    Examples\n    --------\n    > var polyval = base.hermitepoly.factory( 2 );\n    > var v = polyval( 0.5 )\n    -1.0\n\n    See Also\n    --------\n    base.evalpoly, base.normhermitepoly\n","base.hermitepoly.factory":"\nbase.hermitepoly.factory( n )\n    Returns a function for evaluating a physicist's Hermite polynomial.\n\n    Parameters\n    ----------\n    n: integer\n        Nonnegative polynomial degree.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a physicist's Hermite polynomial.\n\n    Examples\n    --------\n    > var polyval = base.hermitepoly.factory( 2 );\n    > var v = polyval( 0.5 )\n    -1.0\n\n    See Also\n    --------\n    base.evalpoly, base.normhermitepoly","base.hypot":"\nbase.hypot( x, y )\n    Computes the hypotenuse avoiding overflow and underflow.\n\n    If either argument is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Hypotenuse.\n\n    Examples\n    --------\n    > var h = base.hypot( -5.0, 12.0 )\n    13.0\n    > h = base.hypot( NaN, 12.0 )\n    NaN\n    > h = base.hypot( -0.0, -0.0 )\n    0.0\n\n","base.hypotf":"\nbase.hypotf( x, y )\n    Computes the hypotenuse avoiding overflow and underflow (single-precision).\n\n    If either argument is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Hypotenuse.\n\n    Examples\n    --------\n    > var h = base.hypotf( -5.0, 12.0 )\n    13.0\n    > h = base.hypotf( NaN, 12.0 )\n    NaN\n    > h = base.hypotf( -0.0, -0.0 )\n    0.0\n\n    See Also\n    --------\n    base.hypot\n","base.identity":"\nbase.identity( x )\n    Evaluates the identity function for a double-precision floating-point number\n    `x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Input value.\n\n    Examples\n    --------\n    > var y = base.identity( -1.0 )\n    -1.0\n    > y = base.identity( 2.0 )\n    2.0\n    > y = base.identity( 0.0 )\n    0.0\n    > y = base.identity( -0.0 )\n    -0.0\n    > y = base.identity( NaN )\n    NaN\n\n","base.identityf":"\nbase.identityf( x )\n    Evaluates the identity function for a single-precision floating-point number\n    `x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Input value.\n\n    Examples\n    --------\n    > var y = base.identityf( -1.0 )\n    -1.0\n    > y = base.identityf( 2.0 )\n    2.0\n    > y = base.identityf( 0.0 )\n    0.0\n    > y = base.identityf( -0.0 )\n    -0.0\n    > y = base.identityf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.identityf\n","base.imul":"\nbase.imul( a, b )\n    Performs C-like multiplication of two signed 32-bit integers.\n\n    Parameters\n    ----------\n    a: integer\n        Signed 32-bit integer.\n\n    b: integer\n        Signed 32-bit integer.\n\n    Returns\n    -------\n    out: integer\n        Product.\n\n    Examples\n    --------\n    > var v = base.imul( -10|0, 4|0 )\n    -40\n\n    See Also\n    --------\n    base.imuldw\n","base.imuldw":"\nbase.imuldw( a, b )\n    Multiplies two signed 32-bit integers and returns an array of two signed 32-\n    bit integers which represents the signed 64-bit integer product.\n\n    When computing the product of 32-bit integer values in double-precision\n    floating-point format (the default JavaScript numeric data type), computing\n    the double word product is necessary in order to avoid exceeding the maximum\n    safe double-precision floating-point integer value.\n\n    Parameters\n    ----------\n    a: integer\n        Signed 32-bit integer.\n\n    b: integer\n        Signed 32-bit integer.\n\n    Returns\n    -------\n    out: Array<number>\n        Double word product (in big endian order; i.e., the first element\n        corresponds to the most significant bits and the second element to the\n        least significant bits).\n\n    Examples\n    --------\n    > var v = base.imuldw( 1, 10 )\n    [ 0, 10 ]\n\n\nbase.imuldw.assign( a, b, out, stride, offset )\n    Multiplies two signed 32-bit integers and assigns results representing the\n    signed 64-bit integer product to a provided output array.\n\n    When computing the product of 32-bit integer values in double-precision\n    floating-point format (the default JavaScript numeric data type), computing\n    the double word product is necessary in order to avoid exceeding the maximum\n    safe double-precision floating-point integer value.\n\n    Parameters\n    ----------\n    a: integer\n        Signed 32-bit integer.\n\n    b: integer\n        Signed 32-bit integer.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Double word product (in big endian order; i.e., the first element\n        corresponds to the most significant bits and the second element to the\n        least significant bits).\n\n    Examples\n    --------\n    > var out = [ 0, 0 ];\n    > var v = base.imuldw.assign( 1, 10, out, 1, 0 )\n    [ 0, 10 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.imul","base.imuldw.assign":"\nbase.imuldw.assign( a, b, out, stride, offset )\n    Multiplies two signed 32-bit integers and assigns results representing the\n    signed 64-bit integer product to a provided output array.\n\n    When computing the product of 32-bit integer values in double-precision\n    floating-point format (the default JavaScript numeric data type), computing\n    the double word product is necessary in order to avoid exceeding the maximum\n    safe double-precision floating-point integer value.\n\n    Parameters\n    ----------\n    a: integer\n        Signed 32-bit integer.\n\n    b: integer\n        Signed 32-bit integer.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Double word product (in big endian order; i.e., the first element\n        corresponds to the most significant bits and the second element to the\n        least significant bits).\n\n    Examples\n    --------\n    > var out = [ 0, 0 ];\n    > var v = base.imuldw.assign( 1, 10, out, 1, 0 )\n    [ 0, 10 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.imul","base.int2slice":"\nbase.int2slice( value, max, strict )\n    Converts an integer to a Slice object.\n\n    In strict mode, the function returns an error object if an input value\n    exceeds index bounds.\n\n    A returned error object is a plain object having the following properties:\n\n    - code: error code.\n\n    A returned error object may have one of the following error codes:\n\n    - ERR_SLICE_OUT_OF_BOUNDS: a slice exceeds index bounds.\n\n    Parameters\n    ----------\n    value: integer\n        Input value.\n\n    max: integer\n        Index upper bound (exclusive).\n\n    strict: boolean\n        Boolean indicating whether to enforce strict bounds checking.\n\n    Returns\n    -------\n    s: Slice|Object\n        Slice instance (or an error object).\n\n    Examples\n    --------\n    > var s = base.int2slice( -1, 5, false );\n    > s.start\n    4\n    > s.stop\n    5\n    > s.step\n    1\n\n    See Also\n    --------\n    base.seq2slice, base.str2slice\n","base.int32ToUint32":"\nbase.int32ToUint32( x )\n    Converts a signed 32-bit integer to an unsigned 32-bit integer.\n\n    Parameters\n    ----------\n    x: integer\n        Signed 32-bit integer.\n\n    Returns\n    -------\n    out: integer\n        Unsigned 32-bit integer.\n\n    Examples\n    --------\n    > var y = base.int32ToUint32( base.float64ToInt32( -32 ) )\n    4294967264\n    > y = base.int32ToUint32( base.float64ToInt32( 3 ) )\n    3\n\n    See Also\n    --------\n    base.uint32ToInt32\n","base.inv":"\nbase.inv( x )\n    Computes the multiplicative inverse of a double-precision floating-point\n    number `x`.\n\n    The multiplicative inverse is defined as `1/x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Multiplicative inverse.\n\n    Examples\n    --------\n    > var y = base.inv( -1.0 )\n    -1.0\n    > y = base.inv( 2.0 )\n    0.5\n    > y = base.inv( 0.0 )\n    Infinity\n    > y = base.inv( -0.0 )\n    -Infinity\n    > y = base.inv( NaN )\n    NaN\n\n    See Also\n    --------\n    base.pow\n","base.invcase":"\nbase.invcase( str )\n    Converts a string to inverse case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Inverse-cased string.\n\n    Examples\n    --------\n    > var out = base.invcase( 'Hello World!' )\n    'hELLO wORLD!'\n    > out = base.invcase( 'I am A tiny LITTLE teapot' )\n    'i AM a TINY little TEAPOT'\n\n    See Also\n    --------\n    base.lowercase, base.uppercase","base.invf":"\nbase.invf( x )\n    Computes the multiplicative inverse of a single-precision floating-point\n    number `x`.\n\n    The multiplicative inverse is defined as `1/x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Multiplicative inverse.\n\n    Examples\n    --------\n    > var y = base.invf( -1.0 )\n    -1.0\n    > y = base.invf( 2.0 )\n    0.5\n    > y = base.invf( 0.0 )\n    Infinity\n    > y = base.invf( -0.0 )\n    -Infinity\n    > y = base.invf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.inv\n","base.isComposite":"\nbase.isComposite( x )\n    Tests if a number is composite.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is a composite number.\n\n    Examples\n    --------\n    > var bool = base.isComposite( 10.0 )\n    true\n    > bool = base.isComposite( 11.0 )\n    false\n\n    See Also\n    --------\n    base.isInteger, base.isPrime\n","base.isCoprime":"\nbase.isCoprime( a, b )\n    Tests if two numbers are coprime.\n\n    Parameters\n    ----------\n    a: number\n        First value.\n\n    b: number\n        Second value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the values are coprime.\n\n    Examples\n    --------\n    > var bool = base.isCoprime( 14.0, 15.0 )\n    true\n    > bool = base.isCoprime( 14.0, 21.0 )\n    false\n\n    See Also\n    --------\n    base.isComposite, base.isPrime, base.gcd\n","base.isEven":"\nbase.isEven( x )\n    Tests if a finite numeric value is an even number.\n\n    The function assumes a finite number. If provided positive or negative\n    infinity, the function will return `true`, when, in fact, the result is\n    undefined.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is an even number.\n\n    Examples\n    --------\n    > var bool = base.isEven( 5.0 )\n    false\n    > bool = base.isEven( -2.0 )\n    true\n    > bool = base.isEven( 0.0 )\n    true\n    > bool = base.isEven( NaN )\n    false\n\n    See Also\n    --------\n    base.isOdd\n","base.isEvenInt32":"\nbase.isEvenInt32( x )\n    Tests if a 32-bit integer is even.\n\n    Parameters\n    ----------\n    x: integer\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is an even number.\n\n    Examples\n    --------\n    > var bool = base.isEvenInt32( 5 )\n    false\n    > bool = base.isEvenInt32( -2 )\n    true\n    > bool = base.isEvenInt32( 0 )\n    true\n\n    See Also\n    --------\n    base.isEven, base.isOddInt32\n","base.isFinite":"\nbase.isFinite( x )\n    Tests if a double-precision floating-point numeric value is finite.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is finite.\n\n    Examples\n    --------\n    > var bool = base.isFinite( 5.0 )\n    true\n    > bool = base.isFinite( -2.0e64 )\n    true\n    > bool = base.isFinite( PINF )\n    false\n    > bool = base.isFinite( NINF )\n    false\n\n    See Also\n    --------\n    base.isInfinite\n","base.isFinitef":"\nbase.isFinitef( x )\n    Tests if a single-precision floating-point numeric value is finite.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is finite.\n\n    Examples\n    --------\n    > var bool = base.isFinitef( 5.0 )\n    true\n    > bool = base.isFinitef( -1.0e38 )\n    true\n    > bool = base.isFinitef( FLOAT32_PINF )\n    false\n    > bool = base.isFinitef( FLOAT32_NINF )\n    false\n\n    See Also\n    --------\n    base.isInfinitef\n","base.isInfinite":"\nbase.isInfinite( x )\n    Tests if a double-precision floating-point numeric value is infinite.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is infinite.\n\n    Examples\n    --------\n    > var bool = base.isInfinite( PINF )\n    true\n    > bool = base.isInfinite( NINF )\n    true\n    > bool = base.isInfinite( 5.0 )\n    false\n    > bool = base.isInfinite( NaN )\n    false\n\n    See Also\n    --------\n    base.isFinite\n","base.isInfinitef":"\nbase.isInfinitef( x )\n    Tests if a single-precision floating-point numeric value is infinite.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is infinite.\n\n    Examples\n    --------\n    > var bool = base.isInfinitef( FLOAT32_PINF )\n    true\n    > bool = base.isInfinitef( FLOAT32_NINF )\n    true\n    > bool = base.isInfinitef( 5.0 )\n    false\n    > bool = base.isInfinitef( NaN )\n    false\n\n    See Also\n    --------\n    base.isFinitef\n","base.isInteger":"\nbase.isInteger( x )\n    Tests if a finite double-precision floating-point number is an integer.\n\n    The function assumes a finite number. If provided positive or negative\n    infinity, the function will return `true`, when, in fact, the result is\n    undefined.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is an integer.\n\n    Examples\n    --------\n    > var bool = base.isInteger( 1.0 )\n    true\n    > bool = base.isInteger( 3.14 )\n    false\n\n","base.isnan":"\nbase.isnan( x )\n     Tests if a double-precision floating-point numeric value is `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is `NaN`.\n\n    Examples\n    --------\n    > var bool = base.isnan( NaN )\n    true\n    > bool = base.isnan( 7.0 )\n    false\n\n    See Also\n    --------\n    base.isnanf\n","base.isnanf":"\nbase.isnanf( x )\n     Tests if a single-precision floating-point numeric value is `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is `NaN`.\n\n    Examples\n    --------\n    > var bool = base.isnanf( NaN )\n    true\n    > bool = base.isnanf( 7.0 )\n    false\n\n    See Also\n    --------\n    base.isnan\n","base.isNegativeFinite":"\nbase.isNegativeFinite( x )\n    Tests if a double-precision floating-point numeric value is a negative\n    finite number.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether the value is a negative finite number.\n\n    Examples\n    --------\n    > var bool = base.isNegativeFinite( -3.14 )\n    true\n    > bool = base.isNegativeFinite( -Infinity )\n    false\n    > bool = base.isNegativeFinite( 2.0 )\n    false\n    > bool = base.isNegativeFinite( NaN )\n    false\n    > bool = base.isNegativeFinite( -0.0 )\n    false\n\n    See Also\n    --------\n    base.isPositiveFinite, base.isNonNegativeFinite, base.isNonPositiveFinite\n","base.isNegativeInteger":"\nbase.isNegativeInteger( x )\n    Tests if a finite double-precision floating-point number is a negative\n    integer.\n\n    The function assumes a finite number. If provided negative infinity, the\n    function will return `true`, when, in fact, the result is undefined.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is a negative integer.\n\n    Examples\n    --------\n    > var bool = base.isNegativeInteger( -1.0 )\n    true\n    > bool = base.isNegativeInteger( 0.0 )\n    false\n    > bool = base.isNegativeInteger( 10.0 )\n    false\n\n    See Also\n    --------\n    base.isInteger, base.isNonNegativeInteger, base.isNonPositiveInteger, base.isPositiveInteger\n","base.isNegativeZero":"\nbase.isNegativeZero( x )\n    Tests if a double-precision floating-point numeric value is negative zero.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is negative zero.\n\n    Examples\n    --------\n    > var bool = base.isNegativeZero( -0.0 )\n    true\n    > bool = base.isNegativeZero( 0.0 )\n    false\n\n    See Also\n    --------\n    base.isPositiveZero\n","base.isNegativeZerof":"\nbase.isNegativeZerof( x )\n    Tests if a single-precision floating-point numeric value is negative zero.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is negative zero.\n\n    Examples\n    --------\n    > var bool = base.isNegativeZerof( -0.0 )\n    true\n    > bool = base.isNegativeZerof( 0.0 )\n    false\n\n    See Also\n    --------\n    base.isNegativeZero, base.isPositiveZerof\n","base.isNonNegativeFinite":"\nbase.isNonNegativeFinite( x )\n    Tests if a double-precision floating-point numeric value is a nonnegative\n    finite number.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is a nonnegative finite number.\n\n    Examples\n    --------\n    > var out = base.isNonNegativeFinite( 5.0 )\n    true\n    > out = base.isNonNegativeFinite( 3.14 )\n    true\n    > out = base.isNonNegativeFinite( 0.0 )\n    true\n    > out = base.isNonNegativeFinite( Infinity )\n    false\n    > out = base.isNonNegativeFinite( -3.14 )\n    false\n    > out = base.isNonNegativeFinite( NaN )\n    false\n\n    See Also\n    --------\n    base.isNegativeFinite, base.isPositiveFinite, base.isNonPositiveFinite\n","base.isNonNegativeInteger":"\nbase.isNonNegativeInteger( x )\n    Tests if a finite double-precision floating-point number is a nonnegative\n    integer.\n\n    The function assumes a finite number. If provided positive infinity, the\n    function will return `true`, when, in fact, the result is undefined.\n\n    The function does not distinguish between positive and negative zero.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is a nonnegative integer.\n\n    Examples\n    --------\n    > var bool = base.isNonNegativeInteger( 1.0 )\n    true\n    > bool = base.isNonNegativeInteger( 0.0 )\n    true\n    > bool = base.isNonNegativeInteger( -10.0 )\n    false\n\n    See Also\n    --------\n    base.isInteger, base.isNegativeInteger, base.isNonPositiveInteger, base.isPositiveInteger\n","base.isNonPositiveFinite":"\nbase.isNonPositiveFinite( x )\n    Tests if a double-precision floating-point numeric value is a nonpositive\n    finite number.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether the value is a nonpositive finite number.\n\n    Examples\n    --------\n    > var bool = base.isNonPositiveFinite( -3.14 )\n    true\n    > var bool = base.isNonPositiveFinite( 0.0 )\n    true\n    > var bool = base.isNonPositiveFinite( -Infinity )\n    false\n    > var bool = base.isNonPositiveFinite( 3.14 )\n    false\n    > var bool = base.isNonPositiveFinite( NaN )\n    false\n\n    See Also\n    --------\n    base.isNegativeFinite, base.isPositiveFinite, base.isNonNegativeFinite\n","base.isNonPositiveInteger":"\nbase.isNonPositiveInteger( x )\n    Tests if a finite double-precision floating-point number is a nonpositive\n    integer.\n\n    The function assumes a finite number. If provided negative infinity, the\n    function will return `true`, when, in fact, the result is undefined.\n\n    The function does not distinguish between positive and negative zero.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is a nonpositive integer.\n\n    Examples\n    --------\n    > var bool = base.isNonPositiveInteger( -1.0 )\n    true\n    > bool = base.isNonPositiveInteger( 0.0 )\n    true\n    > bool = base.isNonPositiveInteger( 10.0 )\n    false\n\n    See Also\n    --------\n    base.isInteger, base.isNegativeInteger, base.isNonNegativeInteger, base.isPositiveInteger\n","base.isOdd":"\nbase.isOdd( x )\n    Tests if a finite numeric value is an odd number.\n\n    The function assumes a finite number. If provided positive or negative\n    infinity, the function will return `true`, when, in fact, the result is\n    undefined.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is an odd number.\n\n    Examples\n    --------\n    > var bool = base.isOdd( 5.0 )\n    true\n    > bool = base.isOdd( -2.0 )\n    false\n    > bool = base.isOdd( 0.0 )\n    false\n    > bool = base.isOdd( NaN )\n    false\n\n    See Also\n    --------\n    base.isEven\n","base.isOddInt32":"\nbase.isOddInt32( x )\n    Tests if a 32-bit integer is odd.\n\n    Parameters\n    ----------\n    x: integer\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is an odd number.\n\n    Examples\n    --------\n    > var bool = base.isOddInt32( 5 )\n    true\n    > bool = base.isOddInt32( -2 )\n    false\n    > bool = base.isOddInt32( 0 )\n    false\n\n    See Also\n    --------\n    base.isEvenInt32, base.isOdd\n","base.isPositiveFinite":"\nbase.isPositiveFinite( x )\n    Tests if a double-precision floating-point numeric value is a positive\n    finite number.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is a positive finite number.\n\n    Examples\n    --------\n    > var bool = base.isPositiveFinite( 5.0 )\n    true\n    > bool = base.isPositiveFinite( 3.14 )\n    true\n    > bool = base.isPositiveFinite( 0.0 )\n    false\n    > bool = base.isPositiveFinite( Infinity )\n    false\n    > bool = base.isPositiveFinite( -3.14 )\n    false\n    > bool = base.isPositiveFinite( NaN )\n    false\n\n    See Also\n    --------\n    base.isNegativeFinite, base.isNonNegativeFinite, base.isNonPositiveFinite\n","base.isPositiveInteger":"\nbase.isPositiveInteger( x )\n    Tests if a finite double-precision floating-point number is a positive\n    integer.\n\n    The function assumes a finite number. If provided positive infinity, the\n    function will return `true`, when, in fact, the result is undefined.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is a positive integer.\n\n    Examples\n    --------\n    > var bool = base.isPositiveInteger( 1.0 )\n    true\n    > bool = base.isPositiveInteger( 0.0 )\n    false\n    > bool = base.isPositiveInteger( -10.0 )\n    false\n\n    See Also\n    --------\n    base.isInteger, base.isNegativeInteger, base.isNonNegativeInteger, base.isNonPositiveInteger\n","base.isPositiveZero":"\nbase.isPositiveZero( x )\n    Tests if a double-precision floating-point numeric value is positive zero.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is positive zero.\n\n    Examples\n    --------\n    > var bool = base.isPositiveZero( 0.0 )\n    true\n    > bool = base.isPositiveZero( -0.0 )\n    false\n\n    See Also\n    --------\n    base.isNegativeZero\n","base.isPositiveZerof":"\nbase.isPositiveZerof( x )\n    Tests if a single-precision floating-point numeric value is positive zero.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is positive zero.\n\n    Examples\n    --------\n    > var bool = base.isPositiveZerof( 0.0 )\n    true\n    > bool = base.isPositiveZerof( -0.0 )\n    false\n\n    See Also\n    --------\n    base.isNegativeZerof, base.isPositiveZero\n","base.isPow2Uint32":"\nbase.isPow2Uint32( x )\n    Tests whether an unsigned integer is a power of 2.\n\n    Parameters\n    ----------\n    x: integer\n        Unsigned integer.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is a power of 2.\n\n    Examples\n    --------\n    > var bool = base.isPow2Uint32( 2 )\n    true\n    > bool = base.isPow2Uint32( 5 )\n    false\n\n","base.isPrime":"\nbase.isPrime( x )\n    Tests if a number is prime.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is a prime number.\n\n    Examples\n    --------\n    > var bool = base.isPrime( 11.0 )\n    true\n    > bool = base.isPrime( 3.14 )\n    false\n\n    See Also\n    --------\n    base.isComposite, base.isInteger\n","base.isProbability":"\nbase.isProbability( x )\n    Tests if a double-precision floating-point number value is a probability.\n\n    A probability is defined as a number on the closed interval [0,1].\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is a probability.\n\n    Examples\n    --------\n    > var bool = base.isProbability( 0.5 )\n    true\n    > bool = base.isProbability( 3.14 )\n    false\n    > bool = base.isProbability( NaN )\n    false\n\n","base.isSafeInteger":"\nbase.isSafeInteger( x )\n    Tests if a finite double-precision floating-point number is a safe integer.\n\n    An integer valued number is \"safe\" when the number can be exactly\n    represented as a double-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the value is a safe integer.\n\n    Examples\n    --------\n    > var bool = base.isSafeInteger( 1.0 )\n    true\n    > bool = base.isSafeInteger( 2.0e200 )\n    false\n    > bool = base.isSafeInteger( 3.14 )\n    false\n\n","base.kebabcase":"\nbase.kebabcase( str )\n    Converts a string to kebab case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Kebab-cased string.\n\n    Examples\n    --------\n    > var out = base.kebabcase( 'Hello World!' )\n    'hello-world'\n    > out = base.kebabcase( 'I am a tiny little teapot' )\n    'i-am-a-tiny-little-teapot'\n\n    See Also\n    --------\n    base.camelcase, base.lowercase, base.pascalcase, base.snakecase, base.uppercase","base.kernelBetainc":"\nbase.kernelBetainc( x, a, b, regularized, upper )\n    Computes the kernel function for the regularized incomplete beta function.\n\n    The `regularized` and `upper` parameters specify whether to evaluate the\n    non-regularized and/or upper incomplete beta functions, respectively.\n\n    If provided `x < 0` or `x > 1`, the function returns `[ NaN, NaN ]`.\n\n    If provided `a < 0` or `b < 0`, the function returns `[ NaN, NaN ]`.\n\n    If provided `NaN` for `x`, `a`, or `b`, the function returns `[ NaN, NaN ]`.\n\n    Parameters\n    ----------\n    x: number\n        First function parameter.\n\n    a: number\n        Second function parameter.\n\n    b: number\n        Third function parameter.\n\n    regularized: boolean\n        Boolean indicating whether the function should evaluate the regularized\n        or non-regularized incomplete beta function.\n\n    upper: boolean\n        Boolean indicating whether the function should return the upper tail of\n        the incomplete beta function.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Function value and first derivative.\n\n    Examples\n    --------\n    > var out = base.kernelBetainc( 0.8, 1.0, 0.3, false, false )\n    [ ~1.277, ~0.926 ]\n    > out = base.kernelBetainc( 0.2, 1.0, 2.0, true, false )\n    [ 0.36, 1.6 ]\n\n\nbase.kernelBetainc.assign( x, a, b, regularized, upper, out, stride, offset )\n    Computes the kernel function for the regularized incomplete beta function.\n\n    The `regularized` and `upper` parameters specify whether to evaluate the\n    non-regularized and/or upper incomplete beta functions, respectively.\n\n    If provided `x < 0` or `x > 1`, the function returns `[ NaN, NaN ]`.\n\n    If provided `a < 0` or `b < 0`, the function returns `[ NaN, NaN ]`.\n\n    If provided `NaN` for `x`, `a`, or `b`, the function returns `[ NaN, NaN ]`.\n\n    Parameters\n    ----------\n    x: number\n        First function parameter.\n\n    a: number\n        Second function parameter.\n\n    b: number\n        Third function parameter.\n\n    regularized: boolean\n        Boolean indicating whether the function should evaluate the regularized\n        or non-regularized incomplete beta function.\n\n    upper: boolean\n        Boolean indicating whether the function should return the upper tail of\n        the incomplete beta function.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Function value and first derivative.\n\n    Examples\n    --------\n    > var out = [ 0.0, 0.0 ];\n    > var v = base.kernelBetainc.assign( 0.2, 1.0, 2.0, true, true, out, 1, 0 )\n    [ 0.64, 1.6 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.betainc\n","base.kernelBetainc.assign":"\nbase.kernelBetainc.assign( x, a, b, regularized, upper, out, stride, offset )\n    Computes the kernel function for the regularized incomplete beta function.\n\n    The `regularized` and `upper` parameters specify whether to evaluate the\n    non-regularized and/or upper incomplete beta functions, respectively.\n\n    If provided `x < 0` or `x > 1`, the function returns `[ NaN, NaN ]`.\n\n    If provided `a < 0` or `b < 0`, the function returns `[ NaN, NaN ]`.\n\n    If provided `NaN` for `x`, `a`, or `b`, the function returns `[ NaN, NaN ]`.\n\n    Parameters\n    ----------\n    x: number\n        First function parameter.\n\n    a: number\n        Second function parameter.\n\n    b: number\n        Third function parameter.\n\n    regularized: boolean\n        Boolean indicating whether the function should evaluate the regularized\n        or non-regularized incomplete beta function.\n\n    upper: boolean\n        Boolean indicating whether the function should return the upper tail of\n        the incomplete beta function.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Function value and first derivative.\n\n    Examples\n    --------\n    > var out = [ 0.0, 0.0 ];\n    > var v = base.kernelBetainc.assign( 0.2, 1.0, 2.0, true, true, out, 1, 0 )\n    [ 0.64, 1.6 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.betainc","base.kernelBetaincinv":"\nbase.kernelBetaincinv( a, b, p, q )\n    Computes the inverse of the lower incomplete beta function.\n\n    Probabilities `p` and `q` must satisfy `p = 1 - q`.\n\n    Parameters\n    ----------\n    a: number\n        First function parameter (a positive number).\n\n    b: number\n        Second function parameter (a positive number).\n\n    p: number\n        Probability.\n\n    q: number\n        Probability equal to `1-p`.\n\n    Returns\n    -------\n    out: Array\n        Two-element array holding function value `y` and `1-y`.\n\n    Examples\n    --------\n    > var y = base.kernelBetaincinv( 3.0, 3.0, 0.2, 0.8 )\n    [ ~0.327, ~0.673 ]\n    > y = base.kernelBetaincinv( 3.0, 3.0, 0.4, 0.6 )\n    [ ~0.446, ~0.554 ]\n    > y = base.kernelBetaincinv( 1.0, 6.0, 0.4, 0.6 )\n    [ ~0.082, ~0.918 ]\n    > y = base.kernelBetaincinv( 1.0, 6.0, 0.8, 0.2 )\n    [ ~0.235, ~0.765 ]\n\n    See Also\n    --------\n    base.betaincinv\n","base.kernelCos":"\nbase.kernelCos( x, y )\n    Computes the cosine of a double-precision floating-point number on the\n    interval [-π/4, π/4].\n\n    For increased accuracy, the number for which the cosine should be evaluated\n    can be supplied as a double-double number (i.e., a non-evaluated sum of two\n    double-precision floating-point numbers `x` and `y`).\n\n    The two numbers must satisfy `|y| < 0.5 * ulp( x )`.\n\n    If either argument is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    y: number\n        Tail of `x`.\n\n    Returns\n    -------\n    out: number\n        Cosine.\n\n    Examples\n    --------\n    > var out = base.kernelCos( 0.0, 0.0 )\n    ~1.0\n    > out = base.kernelCos( PI/6.0, 0.0 )\n    ~0.866\n    > out = base.kernelCos( 0.785, -1.144e-17 )\n    ~0.707\n    > out = base.kernelCos( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cos, base.kernelSin, base.kernelTan\n","base.kernelLog1p":"\nbase.kernelLog1p( f )\n    Computes `log(1+f) - f` for `1+f` in ~[sqrt(2)/2, sqrt(2)].\n\n    This function provides a common means for computing logarithms in base e.\n    Argument reduction and adding the final term of the polynomial must be done\n    by the caller for increased accuracy when different bases are used.\n\n    Parameters\n    ----------\n    f: number\n        Input value.\n\n    Returns\n    -------\n    out: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.kernelLog1p( 1.0 )\n    ~0.1931\n    > y = base.kernelLog1p( 1.4142135623730951 )\n    ~0.4672\n    > y = base.kernelLog1p( NaN )\n    NaN\n\n    See Also\n    --------\n    base.log1p\n","base.kernelSin":"\nbase.kernelSin( x, y )\n    Computes the sine of a double-precision floating-point number on [-π/4,π/4].\n\n    For increased accuracy, the number for which the cosine should be evaluated\n    can be supplied as a double-double number (i.e., a non-evaluated sum of two\n    double-precision floating-point numbers `x` and `y`).\n\n    The two numbers must satisfy `|y| < 0.5 * ulp( x )`.\n\n    If either argument is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    y: number\n        Tail of `x`.\n\n    Returns\n    -------\n    out: number\n        Sine.\n\n    Examples\n    --------\n    > var y = base.kernelSin( 0.0, 0.0 )\n    ~0.0\n    > y = base.kernelSin( PI/6.0, 0.0 )\n    ~0.5\n    > y = base.kernelSin( 0.619, 9.279e-18 )\n    ~0.58\n\n    > y = base.kernelSin( NaN, 0.0 )\n    NaN\n    > y = base.kernelSin( 2.0, NaN )\n    NaN\n    > y = base.kernelSin( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.kernelCos, base.kernelTan, base.sin\n","base.kernelTan":"\nbase.kernelTan( x, y, k )\n    Computes the tangent of a double-precision floating-point number on the\n    interval [-π/4, π/4].\n\n    For increased accuracy, the number for which the tangent should be evaluated\n    can be supplied as a double-double number (i.e., a non-evaluated sum of two\n    double-precision floating-point numbers `x` and `y`).\n\n    The numbers `x` and `y` must satisfy `|y| < 0.5 * ulp( x )`.\n\n    If either `x` or `y` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    y: number\n        Tail of `x`.\n\n    k: integer\n        If `k=1`, the function returns `tan(x+y)`. If `k=-1`, the function\n        returns the negative inverse `-1/tan(x+y)`.\n\n    Returns\n    -------\n    out: number\n        Tangent.\n\n    Examples\n    --------\n    > var out = base.kernelTan( PI/4.0, 0.0, 1 )\n    ~1.0\n    > out = base.kernelTan( PI/4.0, 0.0, -1 )\n    ~-1.0\n    > out = base.kernelTan( PI/6.0, 0.0, 1 )\n    ~0.577\n    > out = base.kernelTan( 0.664, 5.288e-17, 1 )\n    ~0.783\n\n    > out = base.kernelTan( NaN, 0.0, 1 )\n    NaN\n    > out = base.kernelTan( 3.0, NaN, 1 )\n    NaN\n    > out = base.kernelTan( 3.0, 0.0, NaN )\n    NaN\n\n    See Also\n    --------\n    base.kernelCos, base.kernelSin, base.tan\n","base.kroneckerDelta":"\nbase.kroneckerDelta( i, j )\n    Evaluates the Kronecker delta.\n\n    If `i == j`, the function returns `1`; otherwise, the function returns zero.\n\n    Parameters\n    ----------\n    i: number\n        Input value.\n\n    j: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.kroneckerDelta( 3.14, 0.0 )\n    0.0\n    > y = base.kroneckerDelta( 3.14, 3.14 )\n    1.0\n\n    See Also\n    --------\n    base.diracDelta\n","base.kroneckerDeltaf":"\nbase.kroneckerDeltaf( i, j )\n    Evaluates the Kronecker delta (single-precision).\n\n    If `i == j`, the function returns `1`; otherwise, the function returns zero.\n\n    Parameters\n    ----------\n    i: number\n        Input value.\n\n    j: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.kroneckerDeltaf( 3.14, 0.0 )\n    0.0\n    > y = base.kroneckerDeltaf( 3.14, 3.14 )\n    1.0\n\n    See Also\n    --------\n    base.kroneckerDelta\n","base.labs":"\nbase.labs( x )\n    Computes an absolute value of a signed 32-bit integer in two's complement\n    format.\n\n    Parameters\n    ----------\n    x: integer\n        Signed 32-bit integer.\n\n    Returns\n    -------\n    out: integer\n        Absolute value.\n\n    Examples\n    --------\n    > var v = base.labs( -1|0 )\n    1\n    > v = base.labs( 2|0 )\n    2\n    > v = base.labs( 0|0 )\n    0\n\n    See Also\n    --------\n    base.abs\n","base.last":"\nbase.last( str, n )\n    Returns the last `n` UTF-16 code units of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of UTF-16 code units to return.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.last( 'hello', 1 )\n    'o'\n    > out = base.last( 'JavaScript', 6 )\n    'Script'\n    > out = base.last( 'foo bar', 10 )\n    'foo bar'\n\n    See Also\n    --------\n    base.firstCodeUnit, base.lastCodePoint, base.lastGraphemeCluster\n","base.lastCodePoint":"\nbase.lastCodePoint( str, n )\n    Returns the last `n` Unicode code points of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of Unicode code points to return.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.lastCodePoint( 'hello world', 1 )\n    'd'\n    > out = base.lastCodePoint( 'JavaScript', 6 )\n    'Script'\n    > out = base.lastCodePoint( 'अनुच्छेद', 1 )\n    'द'\n\n    See Also\n    --------\n    base.firstCodePoint, base.lastGraphemeCluster, base.last\n","base.lastGraphemeCluster":"\nbase.lastGraphemeCluster( str, n )\n    Returns the last `n` grapheme clusters (i.e., user-perceived characters) of\n    a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of grapheme clusters to return.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.lastGraphemeCluster( 'beep', 1 )\n    'p'\n    > out = base.lastGraphemeCluster( 'Boop', 2 )\n    'op'\n    > out = base.lastGraphemeCluster( 'JavaScript', 6 )\n    'Script'\n\n    See Also\n    --------\n    base.firstGraphemeCluster, base.lastCodePoint, base.last\n","base.lcm":"\nbase.lcm( a, b )\n    Computes the least common multiple (lcm).\n\n    If either `a` or `b` is `0`, the function returns `0`.\n\n    Both `a` and `b` must have integer values; otherwise, the function returns\n    `NaN`.\n\n    Parameters\n    ----------\n    a: integer\n        First integer.\n\n    b: integer\n        Second integer.\n\n    Returns\n    -------\n    out: integer\n        Least common multiple.\n\n    Examples\n    --------\n    > var v = base.lcm( 21, 6 )\n    42\n\n    See Also\n    --------\n    base.gcd\n","base.ldexp":"\nbase.ldexp( frac, exp )\n    Multiplies a double-precision floating-point number by an integer power of\n    two; i.e., `x = frac * 2^exp`.\n\n    If `frac` equals positive or negative `zero`, `NaN`, or positive or negative\n    infinity, the function returns a value equal to `frac`.\n\n    Parameters\n    ----------\n    frac: number\n        Fraction.\n\n    exp: number\n        Exponent.\n\n    Returns\n    -------\n    out: number\n        Double-precision floating-point number equal to `frac * 2^exp`.\n\n    Examples\n    --------\n    > var x = base.ldexp( 0.5, 3 )\n    4.0\n    > x = base.ldexp( 4.0, -2 )\n    1.0\n    > x = base.ldexp( 0.0, 20 )\n    0.0\n    > x = base.ldexp( -0.0, 39 )\n    -0.0\n    > x = base.ldexp( NaN, -101 )\n    NaN\n    > x = base.ldexp( PINF, 11 )\n    Infinity\n    > x = base.ldexp( NINF, -118 )\n    -Infinity\n\n    See Also\n    --------\n    base.frexp\n","base.leftPad":"\nbase.leftPad( str, len, pad )\n    Left pads a string such that the padded string has a length of at least\n    `len`.\n\n    An output string is not guaranteed to have a length of exactly `len`, but to\n    have a length of at least `len`. To generate a padded string having a length\n    equal to `len`, post-process a padded string by trimming off excess\n    characters.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    len: integer\n        Minimum string length.\n\n    pad: string\n        String used to pad.\n\n    Returns\n    -------\n    out: string\n        Padded string.\n\n    Examples\n    --------\n    > var out = base.leftPad( 'a', 5, ' ' )\n    '    a'\n    > out = base.leftPad( 'beep', 10, 'b' )\n    'bbbbbbbeep'\n    > out = base.leftPad( 'boop', 12, 'beep' )\n    'beepbeepboop'\n\n    See Also\n    --------\n    base.rightPad\n","base.leftTrim":"\nbase.leftTrim( str )\n    Trims whitespace from the beginning of a string.\n\n    \"Whitespace\" is defined as the following characters:\n\n    - \\f\n    - \\n\n    - \\r\n    - \\t\n    - \\v\n    - \\u0020\n    - \\u00a0\n    - \\u1680\n    - \\u2000-\\u200a\n    - \\u2028\n    - \\u2029\n    - \\u202f\n    - \\u205f\n    - \\u3000\n    - \\ufeff\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Trimmed string.\n\n    Examples\n    --------\n    > var out = base.leftTrim( ' \\r\\n\\t  Beep \\t\\t\\n  ' )\n    'Beep \\t\\t\\n  '\n\n    See Also\n    --------\n    base.rightTrim, base.trim\n","base.ln":"\nbase.ln( x )\n    Evaluates the natural logarithm of a double-precision floating-point number.\n\n    For negative numbers, the natural logarithm is not defined.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.ln( 4.0 )\n    ~1.386\n    > y = base.ln( 0.0 )\n    -Infinity\n    > y = base.ln( PINF )\n    Infinity\n    > y = base.ln( NaN )\n    NaN\n    > y = base.ln( -4.0 )\n    NaN\n\n    See Also\n    --------\n    base.exp, base.log10, base.log1p, base.log2\n","base.log":"\nbase.log( x, b )\n    Computes the base `b` logarithm of a double-precision floating-point number.\n\n    For negative `b` or `x`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    b: number\n        Base.\n\n    Returns\n    -------\n    y: number\n        Logarithm (base `b`).\n\n    Examples\n    --------\n    > var y = base.log( 100.0, 10.0 )\n    2.0\n    > y = base.log( 16.0, 2.0 )\n    4.0\n    > y = base.log( 5.0, 1.0 )\n    Infinity\n    > y = base.log( NaN, 2.0 )\n    NaN\n    > y = base.log( 1.0, NaN )\n    NaN\n    > y = base.log( -4.0, 2.0 )\n    NaN\n    > y = base.log( 4.0, -2.0 )\n    NaN\n\n    See Also\n    --------\n    base.exp, base.ln, base.log10, base.log1p, base.log2\n","base.log1mexp":"\nbase.log1mexp( x )\n    Evaluates the natural logarithm of `1-exp(-|x|)`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.log1mexp( -10.0 )\n    ~-0.00005\n    > y = base.log1mexp( 0.0 )\n    -Infinity\n    > y = base.log1mexp( 5.0 )\n    ~-0.00676\n    > y = base.log1mexp( 10.0 )\n    ~-0.00005\n    > y = base.log1mexp( NaN )\n    NaN\n\n    See Also\n    --------\n    base.exp, base.ln, base.log1p, base.log1pexp","base.log1p":"\nbase.log1p( x )\n    Evaluates the natural logarithm of `1+x`.\n\n    For `x < -1`, the function returns `NaN`, as the natural logarithm is not\n    defined for negative numbers.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.log1p( 4.0 )\n    ~1.609\n    > y = base.log1p( -1.0 )\n    -Infinity\n    > y = base.log1p( 0.0 )\n    0.0\n    > y = base.log1p( -0.0 )\n    -0.0\n    > y = base.log1p( -2.0 )\n    NaN\n    > y = base.log1p( NaN )\n    NaN\n\n    See Also\n    --------\n    base.ln, base.log\n","base.log1pexp":"\nbase.log1pexp( x )\n    Evaluates the natural logarithm of `1+exp(x)`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.log1pexp( -10.0 )\n    ~0.000045\n    > y = base.log1pexp( 0.0 )\n    ~0.693147\n    > y = base.log1pexp( 5.0 )\n    ~5.006715\n    > y = base.log1pexp( 34.0 )\n    34.0\n    > y = base.log1pexp( NaN )\n    NaN\n\n    See Also\n    --------\n    base.exp, base.ln, base.log1mexp, base.log1p","base.log1pmx":"\nbase.log1pmx( x )\n    Evaluates `ln(1+x) - x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > base.log1pmx( 1.1 )\n    ~-0.358\n    > base.log1pmx( 0.99 )\n    ~-0.302\n    > base.log1pmx( -0.99 )\n    ~-3.615\n    > base.log1pmx( -1.1 )\n    NaN\n    > base.log1pmx( NaN )\n    NaN\n\n    See Also\n    --------\n    base.ln, base.log1p","base.log2":"\nbase.log2( x )\n    Evaluates the binary logarithm (base two).\n\n    For negative numbers, the binary logarithm is not defined.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.log2( 4.0 )\n    2.0\n    > y = base.log2( 8.0 )\n    3.0\n    > y = base.log2( 0.0 )\n    -Infinity\n    > y = base.log2( PINF )\n    Infinity\n    > y = base.log2( NaN )\n    NaN\n    > y = base.log2( -4.0 )\n    NaN\n\n    See Also\n    --------\n    base.exp2, base.ln, base.log\n","base.log10":"\nbase.log10( x )\n    Evaluates the common logarithm (base 10).\n\n    For negative numbers, the common logarithm is not defined.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.log10( 100.0 )\n    2.0\n    > y = base.log10( 8.0 )\n    ~0.903\n    > y = base.log10( 0.0 )\n    -Infinity\n    > y = base.log10( PINF )\n    Infinity\n    > y = base.log10( NaN )\n    NaN\n    > y = base.log10( -4.0 )\n    NaN\n\n    See Also\n    --------\n    base.exp10, base.ln, base.log\n","base.logaddexp":"\nbase.logaddexp( x, y )\n    Computes the natural logarithm of `exp(x) + exp(y)`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    y: number\n        Input value.\n\n    Returns\n    -------\n    v: number\n        Function value.\n\n    Examples\n    --------\n    > var v = base.logaddexp( 90.0, 90.0 )\n    ~90.6931\n    > v = base.logaddexp( -20.0, 90.0 )\n    90.0\n    > v = base.logaddexp( 0.0, -100.0 )\n    ~3.7201e-44\n    > v = base.logaddexp( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.exp, base.ln\n","base.logit":"\nbase.logit( p )\n    Evaluates the logit function.\n\n    Let `p` be the probability of some event. The logit function is defined as\n    the logarithm of the odds `p / (1-p)`.\n\n    If `p < 0` or `p > 1`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.logit( 0.2 )\n    ~-1.386\n    > y = base.logit( 0.9 )\n    ~2.197\n    > y = base.logit( -4.0 )\n    NaN\n    > y = base.logit( 1.5 )\n    NaN\n    > y = base.logit( NaN )\n    NaN\n\n","base.lowercase":"\nbase.lowercase( str )\n    Converts a string to lowercase.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Lowercase string.\n\n    Examples\n    --------\n    > var out = base.lowercase( 'bEEp' )\n    'beep'\n\n    See Also\n    --------\n    base.snakecase, base.uppercase\n","base.lucas":"\nbase.lucas( n )\n    Computes the nth Lucas number.\n\n    Lucas numbers follow the recurrence relation\n\n      L_n = L_{n-1} + L_{n-2}\n\n    with seed values L_0 = 2 and L_1 = 1.\n\n    If `n` is greater than `76`, the function returns `NaN`, as larger Lucas\n    numbers cannot be accurately represented due to limitations of double-\n    precision floating-point format.\n\n    If not provided a nonnegative integer value, the function returns `NaN`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Input value.\n\n    Returns\n    -------\n    y: integer\n        Lucas number.\n\n    Examples\n    --------\n    > var y = base.lucas( 0 )\n    2\n    > y = base.lucas( 1 )\n    1\n    > y = base.lucas( 2 )\n    3\n    > y = base.lucas( 3 )\n    4\n    > y = base.lucas( 4 )\n    7\n    > y = base.lucas( 77 )\n    NaN\n    > y = base.lucas( NaN )\n    NaN\n\n    See Also\n    --------\n    base.fibonacci, base.negalucas\n","base.lucaspoly":"\nbase.lucaspoly( n, x )\n    Evaluates a Lucas polynomial.\n\n    Parameters\n    ----------\n    n: integer\n        Lucas polynomial to evaluate.\n\n    x: number\n        Value at which to evaluate the Lucas polynomial.\n\n    Returns\n    -------\n    out: number\n        Evaluated Lucas polynomial.\n\n    Examples\n    --------\n    // 2^5 + 5*2^3 + 5*2\n    > var v = base.lucaspoly( 5, 2.0 )\n    82.0\n\n\nbase.lucaspoly.factory( n )\n    Returns a function for evaluating a Lucas polynomial.\n\n    Parameters\n    ----------\n    n: integer\n        Lucas polynomial to evaluate.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a Lucas polynomial.\n\n    Examples\n    --------\n    > var polyval = base.lucaspoly.factory( 5 );\n\n    // 1^5 + 5*1^2 + 5\n    > var v = polyval( 1.0 )\n    11.0\n\n    // 2^5 + 5*2^3 + 5*2\n    > v = polyval( 2.0 )\n    82.0\n\n    See Also\n    --------\n    base.evalpoly, base.fibpoly\n","base.lucaspoly.factory":"\nbase.lucaspoly.factory( n )\n    Returns a function for evaluating a Lucas polynomial.\n\n    Parameters\n    ----------\n    n: integer\n        Lucas polynomial to evaluate.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a Lucas polynomial.\n\n    Examples\n    --------\n    > var polyval = base.lucaspoly.factory( 5 );\n\n    // 1^5 + 5*1^2 + 5\n    > var v = polyval( 1.0 )\n    11.0\n\n    // 2^5 + 5*2^3 + 5*2\n    > v = polyval( 2.0 )\n    82.0\n\n    See Also\n    --------\n    base.evalpoly, base.fibpoly","base.max":"\nbase.max( x, y )\n    Returns the maximum value.\n\n    If any argument is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    > var v = base.max( 3.14, 4.2 )\n    4.2\n    > v = base.max( 3.14, NaN )\n    NaN\n    > v = base.max( +0.0, -0.0 )\n    +0.0\n\n    See Also\n    --------\n    base.maxabs, base.maxn, base.min\n","base.maxabs":"\nbase.maxabs( x, y )\n    Returns the maximum absolute value.\n\n    If any argument is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    > var v = base.maxabs( 3.14, -4.2 )\n    4.2\n    > v = base.maxabs( 3.14, NaN )\n    NaN\n    > v = base.maxabs( +0.0, -0.0 )\n    +0.0\n\n    See Also\n    --------\n    base.max, base.minabs\n","base.maxabsn":"\nbase.maxabsn( [x[, y[, ...args]]] )\n    Returns the maximum absolute value.\n\n    If any argument is `NaN`, the function returns `NaN`.\n\n    When an empty set is considered a subset of the extended reals (all real\n    numbers, including positive and negative infinity), negative infinity is the\n    least upper bound. Similar to zero being the identity element for the sum of\n    an empty set and to one being the identity element for the product of an\n    empty set, negative infinity is the identity element for the maximum, and\n    thus, if not provided any arguments, the function returns `+infinity` (i.e.,\n    the absolute value of `-infinity`).\n\n    Parameters\n    ----------\n    x: number (optional)\n        First number.\n\n    y: number (optional)\n        Second number.\n\n    args: ...number (optional)\n        Numbers.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    > var v = base.maxabsn( 3.14, -4.2 )\n    4.2\n    > v = base.maxabsn( 5.9, 3.14, 4.2 )\n    5.9\n    > v = base.maxabsn( 3.14, NaN )\n    NaN\n    > v = base.maxabsn( +0.0, -0.0 )\n    +0.0\n\n    See Also\n    --------\n    base.maxn, base.maxabs, base.minabsn\n","base.maxn":"\nbase.maxn( [x[, y[, ...args]]] )\n    Returns the maximum value.\n\n    If any argument is `NaN`, the function returns `NaN`.\n\n    When an empty set is considered a subset of the extended reals (all real\n    numbers, including positive and negative infinity), negative infinity is the\n    least upper bound. Similar to zero being the identity element for the sum of\n    an empty set and to one being the identity element for the product of an\n    empty set, negative infinity is the identity element for the maximum, and\n    thus, if not provided any arguments, the function returns negative infinity.\n\n    Parameters\n    ----------\n    x: number (optional)\n        First number.\n\n    y: number (optional)\n        Second number.\n\n    args: ...number (optional)\n        Numbers.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    > var v = base.maxn( 3.14, 4.2 )\n    4.2\n    > v = base.maxn( 5.9, 3.14, 4.2 )\n    5.9\n    > v = base.maxn( 3.14, NaN )\n    NaN\n    > v = base.maxn( +0.0, -0.0 )\n    +0.0\n\n    See Also\n    --------\n    base.max, base.maxabsn, base.minn\n","base.min":"\nbase.min( x, y )\n    Returns the minimum value.\n\n    If any argument is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    > var v = base.min( 3.14, 4.2 )\n    3.14\n    > v = base.min( 3.14, NaN )\n    NaN\n    > v = base.min( +0.0, -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.max, base.minabs, base.minn\n","base.minabs":"\nbase.minabs( x, y )\n    Returns the minimum absolute value.\n\n    If any argument is `NaN`, the function returns `NaN`.\n\n    When an empty set is considered a subset of the extended reals (all real\n    numbers, including positive and negative infinity), positive infinity is the\n    greatest upper bound. Similar to zero being the identity element for the sum\n    of an empty set and to one being the identity element for the product of an\n    empty set, positive infinity is the identity element for the minimum, and\n    thus, if not provided any arguments, the function returns positive infinity.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    > var v = base.minabs( 3.14, -4.2 )\n    3.14\n    > v = base.minabs( 3.14, NaN )\n    NaN\n    > v = base.minabs( +0.0, -0.0 )\n    +0.0\n\n    See Also\n    --------\n    base.maxabs, base.min\n","base.minabsn":"\nbase.minabsn( [x[, y[, ...args]]] )\n    Returns the minimum absolute value.\n\n    If any argument is `NaN`, the function returns `NaN`.\n\n    When an empty set is considered a subset of the extended reals (all real\n    numbers, including positive and negative infinity), positive infinity is the\n    greatest upper bound. Similar to zero being the identity element for the sum\n    of an empty set and to one being the identity element for the product of an\n    empty set, positive infinity is the identity element for the minimum, and\n    thus, if not provided any arguments, the function returns positive infinity.\n\n    Parameters\n    ----------\n    x: number (optional)\n        First number.\n\n    y: number (optional)\n        Second number.\n\n    args: ...number (optional)\n        Numbers.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    > var v = base.minabsn( 3.14, -4.2 )\n    3.14\n    > v = base.minabsn( 5.9, 3.14, 4.2 )\n    3.14\n    > v = base.minabsn( 3.14, NaN )\n    NaN\n    > v = base.minabsn( +0.0, -0.0 )\n    +0.0\n\n    See Also\n    --------\n    base.maxabsn, base.minn, base.minabs\n","base.minmax":"\nbase.minmax( x, y )\n    Returns the minimum and maximum values.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum values.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: Array<number>\n        Minimum and maximum values.\n\n    Examples\n    --------\n    > var v = base.minmax( 3.14, 4.2 )\n    [ 3.14, 4.2 ]\n    > v = base.minmax( 3.14, NaN )\n    [ NaN, NaN ]\n    > v = base.minmax( +0.0, -0.0 )\n    [ -0.0, +0.0 ]\n\n\nbase.minmax.assign( x, y, out, stride, offset )\n    Returns the minimum and maximum values and assigns results to a provided\n    output array.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum values.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    out: Array|TypedArray|Object\n        Output object.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Minimum and maximum values.\n\n    Examples\n    --------\n    > var out = [ 0.0, 0.0 ];\n    > var v = base.minmax.assign( 3.14, -1.5, out, 1, 0 )\n    [ -1.5, 3.14 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.max, base.min, base.minmaxabs","base.minmax.assign":"\nbase.minmax.assign( x, y, out, stride, offset )\n    Returns the minimum and maximum values and assigns results to a provided\n    output array.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum values.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    out: Array|TypedArray|Object\n        Output object.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Minimum and maximum values.\n\n    Examples\n    --------\n    > var out = [ 0.0, 0.0 ];\n    > var v = base.minmax.assign( 3.14, -1.5, out, 1, 0 )\n    [ -1.5, 3.14 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.max, base.min, base.minmaxabs","base.minmaxabs":"\nbase.minmaxabs( x, y )\n    Returns the minimum and maximum absolute values.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum absolute values.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: Array<number>\n        Minimum and maximum absolute values.\n\n    Examples\n    --------\n    > var v = base.minmaxabs( 3.14, 4.2 )\n    [ 3.14, 4.2 ]\n    > v = base.minmaxabs( -5.9, 3.14)\n    [ 3.14, 5.9 ]\n    > v = base.minmaxabs( 3.14, NaN )\n    [ NaN, NaN ]\n    > v = base.minmaxabs( +0.0, -0.0 )\n    [ 0.0, 0.0 ]\n\n\nbase.minmaxabs.assign( x, y, out, stride, offset )\n    Returns the minimum and maximum absolute values.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum absolute values.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    out: Array|TypedArray|Object\n        Output object.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Minimum and maximum absolute values.\n\n    Examples\n    --------\n    > var out = [ 0.0, 0.0 ];\n    > var v = base.minmaxabs.assign( 3.14, -3.14, out, 1, 0 )\n    [ 3.14, 3.14 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.maxabs, base.minabs, base.minmax\n","base.minmaxabs.assign":"\nbase.minmaxabs.assign( x, y, out, stride, offset )\n    Returns the minimum and maximum absolute values.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum absolute values.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    out: Array|TypedArray|Object\n        Output object.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Minimum and maximum absolute values.\n\n    Examples\n    --------\n    > var out = [ 0.0, 0.0 ];\n    > var v = base.minmaxabs.assign( 3.14, -3.14, out, 1, 0 )\n    [ 3.14, 3.14 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.maxabs, base.minabs, base.minmax","base.minmaxabsn":"\nbase.minmaxabsn( [x[, y[, ...args]]] )\n    Returns the minimum and maximum absolute values.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum absolute values.\n\n    When an empty set is considered a subset of the extended reals (all real\n    numbers, including positive and negative infinity), positive infinity is the\n    greatest lower bound and negative infinity is the least upper bound. Similar\n    to zero being the identity element for the sum of an empty set and to one\n    being the identity element for the product of an empty set, positive\n    infinity is the identity element for the minimum and negative infinity is\n    the identity element for the maximum, and thus, if not provided any\n    arguments, the function returns positive infinity for both the minimum and\n    maximum absolute values.\n\n    Parameters\n    ----------\n    x: number (optional)\n        First number.\n\n    y: number (optional)\n        Second number.\n\n    args: ...number (optional)\n        Numbers.\n\n    Returns\n    -------\n    out: Array<number>\n        Minimum and maximum absolute values.\n\n    Examples\n    --------\n    > var v = base.minmaxabsn( 3.14, 4.2 )\n    [ 3.14, 4.2 ]\n    > v = base.minmaxabsn( -5.9, 3.14, 4.2 )\n    [ 3.14, 5.9 ]\n    > v = base.minmaxabsn( 3.14, NaN )\n    [ NaN, NaN ]\n    > v = base.minmaxabsn( +0.0, -0.0 )\n    [ 0.0, 0.0 ]\n    > v = base.minmaxabsn( 3.14 )\n    [ 3.14, 3.14 ]\n\n\nbase.minmaxabsn.assign( [x[, y[, ...args]]], out, stride, offset )\n    Returns the minimum and maximum absolute values.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum absolute values.\n\n    Parameters\n    ----------\n    x: number (optional)\n        First number.\n\n    y: number (optional)\n        Second number.\n\n    args: ...number (optional)\n        Numbers.\n\n    out: Array|TypedArray|Object\n        Output object.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Minimum and maximum absolute values.\n\n    Examples\n    --------\n    > var out = [ 0.0, 0.0 ];\n    > var v = base.minmaxabsn.assign( 3.14, out, 1, 0 )\n    [ 3.14, 3.14 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.maxabsn, base.minabsn, base.minmaxn\n","base.minmaxabsn.assign":"\nbase.minmaxabsn.assign( [x[, y[, ...args]]], out, stride, offset )\n    Returns the minimum and maximum absolute values.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum absolute values.\n\n    Parameters\n    ----------\n    x: number (optional)\n        First number.\n\n    y: number (optional)\n        Second number.\n\n    args: ...number (optional)\n        Numbers.\n\n    out: Array|TypedArray|Object\n        Output object.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Minimum and maximum absolute values.\n\n    Examples\n    --------\n    > var out = [ 0.0, 0.0 ];\n    > var v = base.minmaxabsn.assign( 3.14, out, 1, 0 )\n    [ 3.14, 3.14 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.maxabsn, base.minabsn, base.minmaxn","base.minmaxn":"\nbase.minmaxn( [x[, y[, ...args]]] )\n    Returns the minimum and maximum values.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum values.\n\n    When an empty set is considered a subset of the extended reals (all real\n    numbers, including positive and negative infinity), positive infinity is the\n    greatest lower bound and negative infinity is the least upper bound. Similar\n    to zero being the identity element for the sum of an empty set and to one\n    being the identity element for the product of an empty set, positive\n    infinity is the identity element for the minimum and negative infinity is\n    the identity element for the maximum, and thus, if not provided any\n    arguments, the function returns positive infinity for the minimum value and\n    negative infinity for the maximum value.\n\n    Parameters\n    ----------\n    x: number (optional)\n        First number.\n\n    y: number (optional)\n        Second number.\n\n    args: ...number (optional)\n        Numbers.\n\n    Returns\n    -------\n    out: Array<number>\n        Minimum and maximum values.\n\n    Examples\n    --------\n    > var v = base.minmaxn( 3.14, 4.2 )\n    [ 3.14, 4.2 ]\n    > v = base.minmaxn( 5.9, 3.14, 4.2 )\n    [ 3.14, 5.9 ]\n    > v = base.minmaxn( 3.14, NaN )\n    [ NaN, NaN ]\n    > v = base.minmaxn( +0.0, -0.0 )\n    [ -0.0, +0.0 ]\n    > v = base.minmaxn( 3.14 )\n    [ 3.14, 3.14 ]\n\n\nbase.minmaxn.assign( [x[, y[, ...args]]], out, stride, offset )\n    Returns the minimum and maximum values and assigns results to a provided\n    output array.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum values.\n\n    Parameters\n    ----------\n    x: number (optional)\n        First number.\n\n    y: number (optional)\n        Second number.\n\n    args: ...number (optional)\n        Numbers.\n\n    out: Array|TypedArray|Object\n        Output object.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Minimum and maximum values.\n\n    Examples\n    --------\n    > var out = [ 0.0, 0.0 ];\n    > var v = base.minmaxn.assign( 3.14, -1.5, out, 1, 0 )\n    [ -1.5, 3.14 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.maxn, base.minn, base.minmaxabsn","base.minmaxn.assign":"\nbase.minmaxn.assign( [x[, y[, ...args]]], out, stride, offset )\n    Returns the minimum and maximum values and assigns results to a provided\n    output array.\n\n    If any argument is `NaN`, the function returns `NaN` for both the minimum\n    and maximum values.\n\n    Parameters\n    ----------\n    x: number (optional)\n        First number.\n\n    y: number (optional)\n        Second number.\n\n    args: ...number (optional)\n        Numbers.\n\n    out: Array|TypedArray|Object\n        Output object.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Minimum and maximum values.\n\n    Examples\n    --------\n    > var out = [ 0.0, 0.0 ];\n    > var v = base.minmaxn.assign( 3.14, -1.5, out, 1, 0 )\n    [ -1.5, 3.14 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.maxn, base.minn, base.minmaxabsn","base.minn":"\nbase.minn( [x[, y[, ...args]]] )\n    Returns the minimum value.\n\n    If any argument is `NaN`, the function returns `NaN`.\n\n    When an empty set is considered a subset of the extended reals (all real\n    numbers, including positive and negative infinity), positive infinity is the\n    greatest lower bound. Similar to zero being the identity element for the sum\n    of an empty set and to one being the identity element for the product of an\n    empty set, positive infinity is the identity element for the minimum, and\n    thus, if not provided any arguments, the function returns positive infinity.\n\n    Parameters\n    ----------\n    x: number (optional)\n        First number.\n\n    y: number (optional)\n        Second number.\n\n    args: ...number (optional)\n        Numbers.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    > var v = base.minn( 3.14, 4.2 )\n    3.14\n    > v = base.minn( 5.9, 3.14, 4.2 )\n    3.14\n    > v = base.minn( 3.14, NaN )\n    NaN\n    > v = base.minn( +0.0, -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.maxn, base.min, base.minabsn\n","base.modf":"\nbase.modf( x )\n    Decomposes a double-precision floating-point number into integral and\n    fractional parts, each having the same type and sign as the input value.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    out: Array<number>\n        Integral and fractional parts.\n\n    Examples\n    --------\n    > var parts = base.modf( 3.14 )\n    [ 3.0, 0.14000000000000012 ]\n    > parts = base.modf( 3.14 )\n    [ 3.0, 0.14000000000000012 ]\n    > parts = base.modf( +0.0 )\n    [ +0.0, +0.0 ]\n    > parts = base.modf( -0.0 )\n    [ -0.0, -0.0 ]\n    > parts = base.modf( PINF )\n    [ Infinity, +0.0 ]\n    > parts = base.modf( NINF )\n    [ -Infinity, -0.0 ]\n    > parts = base.modf( NaN )\n    [ NaN, NaN ]\n\n\nbase.modf.assign( x, out, stride, offset )\n    Decomposes a double-precision floating-point number into integral and\n    fractional parts, each having the same type and sign as the input value,\n    and assigns results to a provided output array.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Integral and fractional parts.\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var parts = base.modf.assign( 3.14, out, 1, 0 )\n    <Float64Array>[ 3.0, 0.14000000000000012 ]\n    > var bool = ( parts === out )\n    true\n","base.modf.assign":"\nbase.modf.assign( x, out, stride, offset )\n    Decomposes a double-precision floating-point number into integral and\n    fractional parts, each having the same type and sign as the input value,\n    and assigns results to a provided output array.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Integral and fractional parts.\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var parts = base.modf.assign( 3.14, out, 1, 0 )\n    <Float64Array>[ 3.0, 0.14000000000000012 ]\n    > var bool = ( parts === out )\n    true","base.mul":"\nbase.mul( x, y )\n    Multiplies two double-precision floating-point numbers `x` and `y`.\n\n    Parameters\n    ----------\n    x: number\n        First input value.\n\n    y: number\n        Second input value.\n\n    Returns\n    -------\n    z: number\n        Result.\n\n    Examples\n    --------\n    > var v = base.mul( -1.0, 5.0 )\n    -5.0\n    > v = base.mul( 2.0, 5.0 )\n    10.0\n    > v = base.mul( 0.0, 5.0 )\n    0.0\n    > v = base.mul( -0.0, 0.0 )\n    -0.0\n    > v = base.mul( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.add, base.div, base.sub\n","base.mulf":"\nbase.mulf( x, y )\n    Multiplies two single-precision floating-point numbers `x` and `y`.\n\n    Parameters\n    ----------\n    x: number\n        First input value.\n\n    y: number\n        Second input value.\n\n    Returns\n    -------\n    z: number\n        Result.\n\n    Examples\n    --------\n    > var v = base.mulf( -1.0, 5.0 )\n    -5.0\n    > v = base.mulf( 2.0, 5.0 )\n    10.0\n    > v = base.mulf( 0.0, 5.0 )\n    0.0\n    > v = base.mulf( -0.0, 0.0 )\n    -0.0\n    > v = base.mulf( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.addf, base.divf, base.mul, base.subf\n","base.ndarray":"\nbase.ndarray( dtype, buffer, shape, strides, offset, order )\n    Returns an ndarray.\n\n    Parameters\n    ----------\n    dtype: string\n        Underlying data type.\n\n    buffer: ArrayLikeObject|TypedArray|Buffer\n        Data buffer. A data buffer must be an array-like object (i.e., have a\n        `length` property). For data buffers which are not indexed collections\n        (i.e., collections which cannot support direct index access, such as\n        `buffer[ index ]`; e.g., Complex64Array, Complex128Array, etc), a data\n        buffer should provide `#.get( idx )` and `#.set( v[, idx] )` methods.\n        Note that, for `set` methods, the value to set should be the first\n        argument, followed by the linear index, similar to the native typed\n        array `set` method.\n\n    shape: ArrayLikeObject<integer>\n        Array shape.\n\n    strides: ArrayLikeObject<integer>\n        Array strides.\n\n    offset: integer\n        Index offset.\n\n    order: string\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran-style).\n\n    Returns\n    -------\n    ndarray: ndarray\n        ndarray instance.\n\n    Examples\n    --------\n    // Create a new instance...\n    > var b = [ 1, 2, 3, 4 ]; // underlying data buffer\n    > var d = [ 2, 2 ]; // shape\n    > var s = [ 2, 1 ]; // strides\n    > var o = 0; // index offset\n    > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' )\n    <ndarray>\n\n    // Get an element using subscripts:\n    > var v = arr.get( 1, 1 )\n    4\n\n    // Get an element using a linear index:\n    > v = arr.iget( 3 )\n    4\n\n    // Set an element using subscripts:\n    > arr.set( 1, 1, 40 );\n    > arr.get( 1, 1 )\n    40\n\n    // Set an element using a linear index:\n    > arr.iset( 3, 99 );\n    > arr.get( 1, 1 )\n    99\n\n\nbase.ndarray.prototype.byteLength\n    Size (in bytes) of the array (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of the array.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.byteLength\n    32\n\n\nbase.ndarray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.BYTES_PER_ELEMENT\n    8\n\n\nbase.ndarray.prototype.data\n    Pointer to the underlying data buffer.\n\n    Returns\n    -------\n    buf: ArrayLikeObject|TypedArray|Buffer\n        Underlying data buffer.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var buf = arr.data\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n\nbase.ndarray.prototype.dtype\n    Underlying data type.\n\n    Returns\n    -------\n    dtype: string\n        Underlying data type.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var dt = arr.dtype\n    'float64'\n\n\nbase.ndarray.prototype.flags\n    Meta information, such as information concerning the memory layout of the\n    array.\n\n    Returns\n    -------\n    flags: Object\n        Info object.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var fl = arr.flags\n    {...}\n\n\nbase.ndarray.prototype.length\n    Length of the array (i.e., number of elements).\n\n    Returns\n    -------\n    len: integer\n        Array length.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var len = arr.length\n    4\n\n\nbase.ndarray.prototype.ndims\n    Number of dimensions.\n\n    Returns\n    -------\n    ndims: integer\n        Number of dimensions.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var n = arr.ndims\n    2\n\n\nbase.ndarray.prototype.offset\n    Index offset which specifies the buffer index at which to start iterating\n    over array elements.\n\n    Returns\n    -------\n    offset: integer\n        Index offset.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.offset\n    0\n\n\nbase.ndarray.prototype.order: string\n    Array order.\n\n    The array order is either row-major (C-style) or column-major (Fortran-\n    style).\n\n    Returns\n    -------\n    order: string\n        Array order.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var ord = arr.order\n    'row-major'\n\n\nbase.ndarray.prototype.shape\n    Array shape.\n\n    Returns\n    -------\n    shape: Array\n        Array shape.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sh = arr.shape\n    [ 2, 2 ]\n\n\nbase.ndarray.prototype.strides\n    Index strides which specify how to access data along corresponding array\n    dimensions.\n\n    Returns\n    -------\n    strides: Array\n        Index strides.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var st = arr.strides\n    [ 2, 1 ]\n\n\nbase.ndarray.prototype.get( ...idx )\n    Returns an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.get( 1, 1 )\n    4.0\n\n\nbase.ndarray.prototype.iget( idx )\n    Returns an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the input argument is ignored and, for clarity,\n    should not be provided.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.iget( 3 )\n    4.0\n\n\nbase.ndarray.prototype.set( ...idx, v )\n    Sets an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: ndarray\n        ndarray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > arr.set( 1, 1, -4.0 );\n    > arr.get( 1, 1 )\n    -4.0\n\n\nbase.ndarray.prototype.iset( idx, v )\n    Sets an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the first, and only, argument should be the\n    value to set.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: ndarray\n        ndarray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > arr.iset( 3, -4.0 );\n    > arr.iget( 3 )\n    -4.0\n\n\nbase.ndarray.prototype.toString()\n    Serializes an ndarray as a string.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    str: string\n        Serialized ndarray string.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toString()\n    '...'\n\n\nbase.ndarray.prototype.toJSON()\n    Serializes an ndarray as a JSON object.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toJSON()\n    {...}\n\n    See Also\n    --------\n    array, ndarray\n","base.ndarray.prototype.byteLength":"\nbase.ndarray.prototype.byteLength\n    Size (in bytes) of the array (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of the array.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.byteLength\n    32","base.ndarray.prototype.BYTES_PER_ELEMENT":"\nbase.ndarray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.BYTES_PER_ELEMENT\n    8","base.ndarray.prototype.data":"\nbase.ndarray.prototype.data\n    Pointer to the underlying data buffer.\n\n    Returns\n    -------\n    buf: ArrayLikeObject|TypedArray|Buffer\n        Underlying data buffer.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var buf = arr.data\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]","base.ndarray.prototype.dtype":"\nbase.ndarray.prototype.dtype\n    Underlying data type.\n\n    Returns\n    -------\n    dtype: string\n        Underlying data type.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var dt = arr.dtype\n    'float64'","base.ndarray.prototype.flags":"\nbase.ndarray.prototype.flags\n    Meta information, such as information concerning the memory layout of the\n    array.\n\n    Returns\n    -------\n    flags: Object\n        Info object.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var fl = arr.flags\n    {...}","base.ndarray.prototype.length":"\nbase.ndarray.prototype.length\n    Length of the array (i.e., number of elements).\n\n    Returns\n    -------\n    len: integer\n        Array length.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var len = arr.length\n    4","base.ndarray.prototype.ndims":"\nbase.ndarray.prototype.ndims\n    Number of dimensions.\n\n    Returns\n    -------\n    ndims: integer\n        Number of dimensions.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var n = arr.ndims\n    2","base.ndarray.prototype.offset":"\nbase.ndarray.prototype.offset\n    Index offset which specifies the buffer index at which to start iterating\n    over array elements.\n\n    Returns\n    -------\n    offset: integer\n        Index offset.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.offset\n    0","base.ndarray.prototype.order: string":"\nbase.ndarray.prototype.order: string\n    Array order.\n\n    The array order is either row-major (C-style) or column-major (Fortran-\n    style).\n\n    Returns\n    -------\n    order: string\n        Array order.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var ord = arr.order\n    'row-major'","base.ndarray.prototype.shape":"\nbase.ndarray.prototype.shape\n    Array shape.\n\n    Returns\n    -------\n    shape: Array\n        Array shape.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sh = arr.shape\n    [ 2, 2 ]","base.ndarray.prototype.strides":"\nbase.ndarray.prototype.strides\n    Index strides which specify how to access data along corresponding array\n    dimensions.\n\n    Returns\n    -------\n    strides: Array\n        Index strides.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var st = arr.strides\n    [ 2, 1 ]","base.ndarray.prototype.get":"\nbase.ndarray.prototype.get( ...idx )\n    Returns an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.get( 1, 1 )\n    4.0","base.ndarray.prototype.iget":"\nbase.ndarray.prototype.iget( idx )\n    Returns an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the input argument is ignored and, for clarity,\n    should not be provided.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.iget( 3 )\n    4.0","base.ndarray.prototype.set":"\nbase.ndarray.prototype.set( ...idx, v )\n    Sets an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: ndarray\n        ndarray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > arr.set( 1, 1, -4.0 );\n    > arr.get( 1, 1 )\n    -4.0","base.ndarray.prototype.iset":"\nbase.ndarray.prototype.iset( idx, v )\n    Sets an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the first, and only, argument should be the\n    value to set.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: ndarray\n        ndarray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'float64', b, d, s, o, 'row-major' );\n    > arr.iset( 3, -4.0 );\n    > arr.iget( 3 )\n    -4.0","base.ndarray.prototype.toString":"\nbase.ndarray.prototype.toString()\n    Serializes an ndarray as a string.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    str: string\n        Serialized ndarray string.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toString()\n    '...'","base.ndarray.prototype.toJSON":"\nbase.ndarray.prototype.toJSON()\n    Serializes an ndarray as a JSON object.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = base.ndarray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toJSON()\n    {...}\n\n    See Also\n    --------\n    array, ndarray","base.ndarrayUnary":"\nbase.ndarrayUnary( arrays, fcn )\n    Applies a unary callback to elements in an input ndarray and assigns results\n    to elements in an output ndarray.\n\n    Each provided \"ndarray\" should be an object with the following properties:\n\n    - dtype: data type.\n    - data: data buffer.\n    - shape: dimensions.\n    - strides: stride lengths.\n    - offset: index offset.\n    - order: specifies whether an ndarray is row-major (C-style) or column-major\n    (Fortran-style).\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ndarray>\n        Array-like object containing one input ndarray and one output ndarray.\n\n    fcn: Function\n        Unary callback.\n\n    Examples\n    --------\n    // Define ndarray data and meta data...\n    > var xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var dtype = 'float64';\n    > var shape = [ 2, 2 ];\n    > var sx = [ 2, 1 ];\n    > var sy = [ 2, 1 ];\n    > var ox = 0;\n    > var oy = 0;\n    > var order = 'row-major';\n\n    // Using ndarrays...\n    > var x = ndarray( dtype, xbuf, shape, sx, ox, order );\n    > var y = ndarray( dtype, ybuf, shape, sy, oy, order );\n    > base.ndarrayUnary( [ x, y ], base.abs );\n    > y.data\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Using minimal ndarray-like objects...\n    > x = {\n    ...     'dtype': dtype,\n    ...     'data': xbuf,\n    ...     'shape': shape,\n    ...     'strides': sx,\n    ...     'offset': ox,\n    ...     'order': order\n    ... };\n    > y = {\n    ...     'dtype': dtype,\n    ...     'data': ybuf,\n    ...     'shape': shape,\n    ...     'strides': sy,\n    ...     'offset': oy,\n    ...     'order': order\n    ... };\n    > base.ndarrayUnary( [ x, y ], base.abs );\n    > y.data\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    See Also\n    --------\n    ndarrayDispatch\n","base.ndzeros":"\nbase.ndzeros( dtype, shape, order )\n    Returns a zero-filled ndarray having a specified shape and data type.\n\n    Parameters\n    ----------\n    dtype: string\n        Underlying data type. Must be a numeric data type or \"generic\".\n\n    shape: ArrayLikeObject<integer>\n        Array shape.\n\n    order: string\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran-style).\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var arr = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n    <ndarray>\n    > var sh = arr.shape\n    [ 2, 2 ]\n    > var dt = arr.dtype\n    'float64'\n\n    See Also\n    --------\n    base.ndarray, base.ndzerosLike\n","base.ndzerosLike":"\nbase.ndzerosLike( x )\n    Returns a zero-filled ndarray having the same shape and data type as a\n    provided input ndarray.\n\n    Along with data type, shape, and order, the function infers the \"class\" of\n    the returned ndarray from the provided ndarray. For example, if provided a\n    \"base\" ndarray, the function returns a base ndarray. If provided a non-base\n    ndarray, the function returns a non-base ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n    <ndarray>\n    > var sh = x.shape\n    [ 2, 2 ]\n    > var dt = x.dtype\n    'float64'\n    > var y = base.ndzerosLike( x )\n    <ndarray>\n    > sh = y.shape\n    [ 2, 2 ]\n    > dt = y.dtype\n    'float64'\n\n    See Also\n    --------\n    base.ndarray, base.ndzeros\n","base.negafibonacci":"\nbase.negafibonacci( n )\n    Computes the nth negaFibonacci number.\n\n    The negaFibonacci numbers follow the recurrence relation\n\n      F_{n-2} = F_{n} - F_{n-1}\n\n    with seed values F_0 = 0 and F_{-1} = 1.\n\n    If `|n|` is greater than `78`, the function returns `NaN` as larger\n    negaFibonacci numbers cannot be accurately represented due to limitations of\n    double-precision floating-point format.\n\n    If not provided a non-positive integer value, the function returns `NaN`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Input value.\n\n    Returns\n    -------\n    y: integer\n        NegaFibonacci number.\n\n    Examples\n    --------\n    > var y = base.negafibonacci( 0 )\n    0\n    > y = base.negafibonacci( -1 )\n    1\n    > y = base.negafibonacci( -2 )\n    -1\n    > y = base.negafibonacci( -3 )\n    2\n    > y = base.negafibonacci( -4 )\n    -3\n    > y = base.negafibonacci( -79 )\n    NaN\n    > y = base.negafibonacci( -80 )\n    NaN\n    > y = base.negafibonacci( NaN )\n    NaN\n\n    See Also\n    --------\n    base.fibonacci, base.negalucas\n","base.negalucas":"\nbase.negalucas( n )\n    Computes the nth negaLucas number.\n\n    The negaLucas numbers follow the recurrence relation\n\n      L_{n-2} = L_{n} - L_{n-1}\n\n    with seed values L_0 = 2 and L_{-1} = -1.\n\n    If `|n|` is greater than `76`, the function returns `NaN` as larger\n    negaLucas numbers cannot be accurately represented due to limitations of\n    double-precision floating-point format.\n\n    If not provided a non-positive integer value, the function returns `NaN`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Input value.\n\n    Returns\n    -------\n    y: integer\n        NegaLucas number.\n\n    Examples\n    --------\n    > var y = base.negalucas( 0 )\n    2\n    > y = base.negalucas( -1 )\n    -1\n    > y = base.negalucas( -2 )\n    3\n    > y = base.negalucas( -3 )\n    -4\n    > y = base.negalucas( -4 )\n    7\n    > y = base.negalucas( -77 )\n    NaN\n    > y = base.negalucas( -78 )\n    NaN\n    > y = base.negalucas( NaN )\n    NaN\n\n    See Also\n    --------\n    base.fibonacci, base.lucas, base.negafibonacci\n","base.nonfibonacci":"\nbase.nonfibonacci( n )\n    Computes the nth non-Fibonacci number.\n\n    If not provided a nonnegative integer value, the function returns `NaN`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Non-Fibonacci number.\n\n    Examples\n    --------\n    > var v = base.nonfibonacci( 1 )\n    4\n    > v = base.nonfibonacci( 2 )\n    6\n    > v = base.nonfibonacci( 3 )\n    7\n    > v = base.nonfibonacci( NaN )\n    NaN\n\n    See Also\n    --------\n    base.fibonacci\n","base.normalize":"\nbase.normalize( x )\n    Returns a normal number and exponent satisfying `x = y * 2^exp` as an array.\n\n    The first element of the returned array corresponds to `y` and the second to\n    `exp`.\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    Returns\n    -------\n    out: Array<number>\n        An array containing `y` and `exp`.\n\n    Examples\n    --------\n    > var out = base.normalize( 3.14e-319 )\n    [ 1.4141234400356668e-303, -52 ]\n    > var y = out[ 0 ];\n    > var exponent = out[ 1 ];\n    > var bool = ( y*base.pow(2.0, exponent) === 3.14e-319 )\n    true\n\n    // Special cases:\n    > out = base.normalize( 0.0 )\n    [ 0.0, 0 ];\n    > out = base.normalize( PINF )\n    [ Infinity, 0 ]\n    > out = base.normalize( NINF )\n    [ -Infinity, 0 ]\n    > out = base.normalize( NaN )\n    [ NaN, 0 ]\n\n\nbase.normalize.assign( x, out, stride, offset )\n    Returns a normal number and exponent satisfying `x = y * 2^exp` and assigns\n    results to a provided output array.\n\n    The first element of the returned array corresponds to `y` and the second to\n    `exp`.\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Output array.\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 )\n    > var v = base.normalize.assign( 3.14e-319, out, 1, 0 )\n    <Float64Array>[ 1.4141234400356668e-303, -52 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.normalizef\n","base.normalize.assign":"\nbase.normalize.assign( x, out, stride, offset )\n    Returns a normal number and exponent satisfying `x = y * 2^exp` and assigns\n    results to a provided output array.\n\n    The first element of the returned array corresponds to `y` and the second to\n    `exp`.\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Output array.\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 )\n    > var v = base.normalize.assign( 3.14e-319, out, 1, 0 )\n    <Float64Array>[ 1.4141234400356668e-303, -52 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.normalizef","base.normalizef":"\nbase.normalizef( x )\n    Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` as\n    an array.\n\n    The first element of the returned array corresponds to `y` and the second to\n    `exp`.\n\n    While the function accepts higher precision floating-point numbers, beware\n    that providing such numbers can be a source of subtle bugs as the relation\n    `x = y * 2^exp` may not hold.\n\n    Parameters\n    ----------\n    x: float\n        Single-precision floating-point number.\n\n    Returns\n    -------\n    out: Array<number>\n        An array containing `y` and `exp`.\n\n    Examples\n    --------\n    > var out = base.normalizef( base.float64ToFloat32( 1.401e-45 ) )\n    [ 1.1754943508222875e-38, -23 ]\n    > var y = out[ 0 ];\n    > var exp = out[ 1 ];\n    > var bool = ( y*base.pow(2,exp) === base.float64ToFloat32(1.401e-45) )\n    true\n\n    // Special cases:\n    > out = base.normalizef( FLOAT32_PINF )\n    [ Infinity, 0 ]\n    > out = base.normalizef( FLOAT32_NINF )\n    [ -Infinity, 0 ]\n    > out = base.normalizef( NaN )\n    [ NaN, 0 ]\n\n\nbase.normalizef.assign( x, out, stride, offset )\n    Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` and\n    assigns results to a provided output array.\n\n    The first element of the returned array corresponds to `y` and the second to\n    `exp`.\n\n    While the function accepts higher precision floating-point numbers, beware\n    that providing such numbers can be a source of subtle bugs as the relation\n    `x = y * 2^exp` may not hold.\n\n    Parameters\n    ----------\n    x: float\n        Single-precision floating-point number.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        An array containing `y` and `exp`.\n\n    Examples\n    --------\n    > out = new Float32Array( 2 );\n    > var v = base.normalizef.assign( base.float64ToFloat32( 1.401e-45 ), out, 1, 0 )\n    <Float32Array>[ 1.1754943508222875e-38, -23.0 ]\n    > bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.normalize","base.normalizef.assign":"\nbase.normalizef.assign( x, out, stride, offset )\n    Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` and\n    assigns results to a provided output array.\n\n    The first element of the returned array corresponds to `y` and the second to\n    `exp`.\n\n    While the function accepts higher precision floating-point numbers, beware\n    that providing such numbers can be a source of subtle bugs as the relation\n    `x = y * 2^exp` may not hold.\n\n    Parameters\n    ----------\n    x: float\n        Single-precision floating-point number.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        An array containing `y` and `exp`.\n\n    Examples\n    --------\n    > out = new Float32Array( 2 );\n    > var v = base.normalizef.assign( base.float64ToFloat32( 1.401e-45 ), out, 1, 0 )\n    <Float32Array>[ 1.1754943508222875e-38, -23.0 ]\n    > bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.normalize","base.normalizeSlice":"\nbase.normalizeSlice( slice, len, strict )\n    Returns a normalized Slice object.\n\n    In strict mode, the function returns an error object if an input slice\n    exceeds index bounds.\n\n    A returned error object is a plain object having the following properties:\n\n    - code: error code.\n\n    A returned error object may have one of the following error codes:\n\n    - ERR_SLICE_OUT_OF_BOUNDS: a slice exceeds index bounds.\n\n    Parameters\n    ----------\n    slice: Slice\n        Input slice object.\n\n    len: integer\n        Maximum number of elements allowed in the slice.\n\n    strict: boolean\n        Boolean indicating whether to enforce strict bounds checking.\n\n    Returns\n    -------\n    s: Slice|Object\n        Slice instance (or an error object).\n\n    Examples\n    --------\n    > var s1 = new Slice( 1, 10, 1 );\n    > var s2 = base.normalizeSlice( s1, 5, false );\n    > s2.start\n    1\n    > s2.stop\n    5\n    > s2.step\n    1\n    > s1 = new Slice( -2, null, -1 );\n    > s2 = base.normalizeSlice( s1, 10, false );\n    > s2.start\n    8\n    > s2.stop\n    null\n    > s2.step\n    -1\n\n    See Also\n    --------\n    base.normalizeMultiSlice\n","base.normhermitepoly":"\nbase.normhermitepoly( n, x )\n    Evaluates a normalized Hermite polynomial using double-precision floating-\n    point arithmetic.\n\n    Parameters\n    ----------\n    n: integer\n        Nonnegative polynomial degree.\n\n    x: number\n        Value at which to evaluate the polynomial.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.normhermitepoly( 1, 0.5 )\n    0.5\n    > y = base.normhermitepoly( -1, 0.5 )\n    NaN\n    > y = base.normhermitepoly( 0, 0.5 )\n    1.0\n    > y = base.normhermitepoly( 2, 0.5 )\n    -0.75\n\n\nbase.normhermitepoly.factory( n )\n    Returns a function for evaluating a normalized Hermite polynomial using\n    double-precision floating-point arithmetic.\n\n    Parameters\n    ----------\n    n: integer\n        Nonnegative polynomial degree.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a normalized Hermite polynomial.\n\n    Examples\n    --------\n    > var f = base.normhermitepoly.factory( 2 );\n    > var v = f( 0.5 )\n    -0.75\n\n    See Also\n    --------\n    base.evalpoly, base.hermitepoly\n","base.normhermitepoly.factory":"\nbase.normhermitepoly.factory( n )\n    Returns a function for evaluating a normalized Hermite polynomial using\n    double-precision floating-point arithmetic.\n\n    Parameters\n    ----------\n    n: integer\n        Nonnegative polynomial degree.\n\n    Returns\n    -------\n    fcn: Function\n        Function for evaluating a normalized Hermite polynomial.\n\n    Examples\n    --------\n    > var f = base.normhermitepoly.factory( 2 );\n    > var v = f( 0.5 )\n    -0.75\n\n    See Also\n    --------\n    base.evalpoly, base.hermitepoly","base.pascalcase":"\nbase.pascalcase( str )\n    Converts a string to Pascal case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Pascal-cased string.\n\n    Examples\n    --------\n    > var out = base.pascalcase( 'Hello World!' )\n    'HelloWorld'\n    > out = base.pascalcase( 'beep boop' )\n    'BeepBoop'\n\n    See Also\n    --------\n    base.camelcase, base.lowercase, base.uppercase","base.pdiff":"\nbase.pdiff( x, y )\n    Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n    returns `0`.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Positive difference.\n\n    Examples\n    --------\n    > var v = base.pdiff( 5.9, 3.14 )\n    2.76\n    > v = base.pdiff( 3.14, 4.2 )\n    0.0\n    > v = base.pdiff( 3.14, NaN )\n    NaN\n    > v = base.pdiff( -0.0, +0.0 )\n    +0.0\n\n","base.pdifff":"\nbase.pdifff( x, y )\n    Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n    returns `0`.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Positive difference.\n\n    Examples\n    --------\n    > var v = base.pdifff( 5.9, 3.15 )\n    2.75\n    > v = base.pdifff( 3.14, 4.2 )\n    0.0\n    > v = base.pdifff( 3.14, NaN )\n    NaN\n    > v = base.pdifff( -0.0, +0.0 )\n    +0.0\n\n    See Also\n    --------\n    base.pdiff\n","base.percentEncode":"\nbase.percentEncode( str )\n    Percent-encodes a UTF-16 encoded string according to RFC 3986.\n\n    Parameters\n    ----------\n    str: string\n        UTF-16 encoded string.\n\n    Returns\n    -------\n    out: string\n        Percent-encoded string.\n\n    Examples\n    --------\n    > var out = base.percentEncode( '☃' )\n    '%E2%98%83'\n\n","base.polygamma":"\nbase.polygamma( n, x )\n    Evaluates the polygamma function of order `n`; i.e., the (n+1)th derivative\n    of the natural logarithm of the gamma function.\n\n    If `n` is not a nonnegative integer, the function returns `NaN`.\n\n    If `x` is zero or a negative integer, the function returns `NaN`.\n\n    If provided `NaN` as either parameter, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Derivative order.\n\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var v = base.polygamma( 3, 1.2 )\n    ~3.245\n    > v = base.polygamma( 5, 1.2 )\n    ~41.39\n    > v = base.polygamma( 3, -4.9 )\n    ~60014.239\n    > v = base.polygamma( -1, 5.3 )\n    NaN\n    > v = base.polygamma( 2, -1.0 )\n    Infinity\n\n    See Also\n    --------\n    base.trigamma, base.digamma, base.gamma\n","base.pow":"\nbase.pow( b, x )\n    Evaluates the exponential function `bˣ`.\n\n    Parameters\n    ----------\n    b: number\n        Base.\n\n    x: number\n        Exponent.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.pow( 2.0, 3.0 )\n    8.0\n    > y = base.pow( 4.0, 0.5 )\n    2.0\n    > y = base.pow( 100.0, 0.0 )\n    1.0\n    > y = base.pow( PI, 5.0 )\n    ~306.0197\n    > y = base.pow( PI, -0.2 )\n    ~0.7954\n    > y = base.pow( NaN, 3.0 )\n    NaN\n    > y = base.pow( 5.0, NaN )\n    NaN\n    > y = base.pow( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.exp, base.powm1\n","base.powm1":"\nbase.powm1( b, x )\n    Evaluates `bˣ - 1`.\n\n    When `b` is close to `1` and/or `x` is small, this function is more accurate\n    than naively computing `bˣ` and subtracting `1`.\n\n    Parameters\n    ----------\n    b: number\n        Base.\n\n    x: number\n        Exponent.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.powm1( 2.0, 3.0 )\n    7.0\n    > y = base.powm1( 4.0, 0.5 )\n    1.0\n    > y = base.powm1( 0.0, 100.0 )\n    -1.0\n    > y = base.powm1( 100.0, 0.0 )\n    0.0\n    > y = base.powm1( 0.0, 0.0 )\n    0.0\n    > y = base.powm1( PI, 5.0 )\n    ~305.0197\n    > y = base.powm1( NaN, 3.0 )\n    NaN\n    > y = base.powm1( 5.0, NaN )\n    NaN\n\n    See Also\n    --------\n    base.pow\n","base.rad2deg":"\nbase.rad2deg( x )\n    Converts an angle from radians to degrees.\n\n    Parameters\n    ----------\n    x: number\n        Angle in radians.\n\n    Returns\n    -------\n    d: number\n        Angle in degrees.\n\n    Examples\n    --------\n    > var d = base.rad2deg( PI/2.0 )\n    90.0\n    > d = base.rad2deg( -PI/4.0 )\n    -45.0\n    > d = base.rad2deg( NaN )\n    NaN\n\n    // Due to finite precision, canonical values may not be returned:\n    > d = base.rad2deg( PI/6.0 )\n    29.999999999999996\n\n    See Also\n    --------\n    base.deg2rad\n","base.rad2degf":"\nbase.rad2degf( x )\n    Converts an angle from radians to degrees (single-precision).\n\n    Parameters\n    ----------\n    x: number\n        Angle in radians.\n\n    Returns\n    -------\n    d: number\n        Angle in degrees.\n\n    Examples\n    --------\n    > var d = base.rad2degf( 3.141592653589793 / 2.0 )\n    90.0\n    > d = base.rad2degf( -3.141592653589793 / 4.0 )\n    -45.0\n    > d = base.rad2degf( NaN )\n    NaN\n\n    // Due to finite precision, canonical values may not be returned:\n    > d = base.rad2degf( 3.141592653589793 / 6.0 )\n    30.000001907348633\n\n    See Also\n    --------\n    base.rad2deg\n","base.ramp":"\nbase.ramp( x )\n    Evaluates the ramp function.\n\n    If `x >= 0`, the function returns `x`; otherwise, the function returns zero.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.ramp( 3.14 )\n    3.14\n    > y = base.ramp( -3.14 )\n    0.0\n\n    See Also\n    --------\n    base.heaviside\n","base.rampf":"\nbase.rampf( x )\n    Evaluates the ramp function (single-precision).\n\n    If `x >= 0`, the function returns `x`; otherwise, the function returns zero.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.rampf( 3.14 )\n    3.14\n    > y = base.rampf( -3.14 )\n    0.0\n\n    See Also\n    --------\n    base.ramp\n","base.random.arcsine":"\nbase.random.arcsine( a, b )\n    Returns a pseudorandom number drawn from an arcsine distribution.\n\n    If `a >= b`, the function returns `NaN`.\n\n    If `a` or `b` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.arcsine( 2.0, 5.0 )\n    <number>\n\n\nbase.random.arcsine.factory( [a, b, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an arcsine distribution.\n\n    If provided `a` and `b`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `a` and `b`, the returned PRNG requires that both `a` and\n    `b` be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.arcsine.factory();\n    > var r = rand( 0.0, 1.0 )\n    <number>\n    > r = rand( -2.0, 2.0 )\n    <number>\n\n    // Provide `a` and `b`:\n    > rand = base.random.arcsine.factory( 0.0, 1.0 );\n    > r = rand()\n    <number>\n    > r = rand()\n    <number>\n\n\nbase.random.arcsine.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.arcsine.NAME\n    'arcsine'\n\n\nbase.random.arcsine.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.arcsine.PRNG;\n\n\nbase.random.arcsine.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.arcsine.seed;\n\n\nbase.random.arcsine.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.arcsine.seedLength;\n\n\nbase.random.arcsine.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.arcsine.state\n    <Uint32Array>\n\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n\n    // Set the state:\n    > base.random.arcsine.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n\n\nbase.random.arcsine.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.arcsine.stateLength;\n\n\nbase.random.arcsine.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.arcsine.byteLength;\n\n\nbase.random.arcsine.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.arcsine.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.arcsine, random.iterators.arcsine, random.streams.arcsine, base.random.beta\n","base.random.arcsine.factory":"\nbase.random.arcsine.factory( [a, b, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an arcsine distribution.\n\n    If provided `a` and `b`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `a` and `b`, the returned PRNG requires that both `a` and\n    `b` be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.arcsine.factory();\n    > var r = rand( 0.0, 1.0 )\n    <number>\n    > r = rand( -2.0, 2.0 )\n    <number>\n\n    // Provide `a` and `b`:\n    > rand = base.random.arcsine.factory( 0.0, 1.0 );\n    > r = rand()\n    <number>\n    > r = rand()\n    <number>","base.random.arcsine.NAME":"\nbase.random.arcsine.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.arcsine.NAME\n    'arcsine'","base.random.arcsine.PRNG":"\nbase.random.arcsine.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.arcsine.PRNG;","base.random.arcsine.seed":"\nbase.random.arcsine.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.arcsine.seed;","base.random.arcsine.seedLength":"\nbase.random.arcsine.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.arcsine.seedLength;","base.random.arcsine.state":"\nbase.random.arcsine.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.arcsine.state\n    <Uint32Array>\n\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n\n    // Set the state:\n    > base.random.arcsine.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>\n    > r = base.random.arcsine( 2.0, 4.0 )\n    <number>","base.random.arcsine.stateLength":"\nbase.random.arcsine.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.arcsine.stateLength;","base.random.arcsine.byteLength":"\nbase.random.arcsine.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.arcsine.byteLength;","base.random.arcsine.toJSON":"\nbase.random.arcsine.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.arcsine.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.arcsine, random.iterators.arcsine, random.streams.arcsine, base.random.beta","base.random.bernoulli":"\nbase.random.bernoulli( p )\n    Returns a pseudorandom number drawn from a Bernoulli distribution.\n\n    If `p < 0` or `p > 1` or `p` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.bernoulli( 0.8 );\n\n\nbase.random.bernoulli.factory( [p, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Bernoulli distribution.\n\n    If provided `p`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `p`, the returned PRNG requires that `p` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.bernoulli.factory();\n    > var r = rand( 0.3 );\n    > r = rand( 0.59 );\n\n    // Provide `p`:\n    > rand = base.random.bernoulli.factory( 0.3 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.bernoulli.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.bernoulli.NAME\n    'bernoulli'\n\n\nbase.random.bernoulli.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.bernoulli.PRNG;\n\n\nbase.random.bernoulli.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.bernoulli.seed;\n\n\nbase.random.bernoulli.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.bernoulli.seedLength;\n\n\nbase.random.bernoulli.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.bernoulli( 0.3 )\n    <number>\n    > r = base.random.bernoulli( 0.3 )\n    <number>\n    > r = base.random.bernoulli( 0.3 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.bernoulli.state\n    <Uint32Array>\n\n    > r = base.random.bernoulli( 0.3 )\n    <number>\n    > r = base.random.bernoulli( 0.3 )\n    <number>\n\n    // Set the state:\n    > base.random.bernoulli.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.bernoulli( 0.3 )\n    <number>\n    > r = base.random.bernoulli( 0.3 )\n    <number>\n\n\nbase.random.bernoulli.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.bernoulli.stateLength;\n\n\nbase.random.bernoulli.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.bernoulli.byteLength;\n\n\nbase.random.bernoulli.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.bernoulli.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.bernoulli, random.iterators.bernoulli, random.streams.bernoulli, base.random.binomial\n","base.random.bernoulli.factory":"\nbase.random.bernoulli.factory( [p, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Bernoulli distribution.\n\n    If provided `p`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `p`, the returned PRNG requires that `p` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.bernoulli.factory();\n    > var r = rand( 0.3 );\n    > r = rand( 0.59 );\n\n    // Provide `p`:\n    > rand = base.random.bernoulli.factory( 0.3 );\n    > r = rand();\n    > r = rand();","base.random.bernoulli.NAME":"\nbase.random.bernoulli.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.bernoulli.NAME\n    'bernoulli'","base.random.bernoulli.PRNG":"\nbase.random.bernoulli.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.bernoulli.PRNG;","base.random.bernoulli.seed":"\nbase.random.bernoulli.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.bernoulli.seed;","base.random.bernoulli.seedLength":"\nbase.random.bernoulli.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.bernoulli.seedLength;","base.random.bernoulli.state":"\nbase.random.bernoulli.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.bernoulli( 0.3 )\n    <number>\n    > r = base.random.bernoulli( 0.3 )\n    <number>\n    > r = base.random.bernoulli( 0.3 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.bernoulli.state\n    <Uint32Array>\n\n    > r = base.random.bernoulli( 0.3 )\n    <number>\n    > r = base.random.bernoulli( 0.3 )\n    <number>\n\n    // Set the state:\n    > base.random.bernoulli.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.bernoulli( 0.3 )\n    <number>\n    > r = base.random.bernoulli( 0.3 )\n    <number>","base.random.bernoulli.stateLength":"\nbase.random.bernoulli.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.bernoulli.stateLength;","base.random.bernoulli.byteLength":"\nbase.random.bernoulli.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.bernoulli.byteLength;","base.random.bernoulli.toJSON":"\nbase.random.bernoulli.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.bernoulli.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.bernoulli, random.iterators.bernoulli, random.streams.bernoulli, base.random.binomial","base.random.beta":"\nbase.random.beta( α, β )\n    Returns a pseudorandom number drawn from a beta distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.beta( 2.0, 5.0 );\n\n\nbase.random.beta.factory( [α, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a beta distribution.\n\n    If provided `α` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `α` and `β`, the returned PRNG requires that both `α` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        First shape parameter.\n\n    β: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.beta.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `α` and `β`:\n    > rand = base.random.beta.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.beta.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.beta.NAME\n    'beta'\n\n\nbase.random.beta.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.beta.PRNG;\n\n\nbase.random.beta.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.beta.seed;\n\n\nbase.random.beta.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.beta.seedLength;\n\n\nbase.random.beta.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.beta( 2.0, 5.0 )\n    <number>\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.beta.state\n    <Uint32Array>\n\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.beta.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>\n\n\nbase.random.beta.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.beta.stateLength;\n\n\nbase.random.beta.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.beta.byteLength;\n\n\nbase.random.beta.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.beta.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.beta, random.iterators.beta, random.streams.beta\n","base.random.beta.factory":"\nbase.random.beta.factory( [α, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a beta distribution.\n\n    If provided `α` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `α` and `β`, the returned PRNG requires that both `α` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        First shape parameter.\n\n    β: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.beta.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `α` and `β`:\n    > rand = base.random.beta.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.beta.NAME":"\nbase.random.beta.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.beta.NAME\n    'beta'","base.random.beta.PRNG":"\nbase.random.beta.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.beta.PRNG;","base.random.beta.seed":"\nbase.random.beta.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.beta.seed;","base.random.beta.seedLength":"\nbase.random.beta.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.beta.seedLength;","base.random.beta.state":"\nbase.random.beta.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.beta( 2.0, 5.0 )\n    <number>\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.beta.state\n    <Uint32Array>\n\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.beta.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>\n    > r = base.random.beta( 2.0, 5.0 )\n    <number>","base.random.beta.stateLength":"\nbase.random.beta.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.beta.stateLength;","base.random.beta.byteLength":"\nbase.random.beta.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.beta.byteLength;","base.random.beta.toJSON":"\nbase.random.beta.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.beta.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.beta, random.iterators.beta, random.streams.beta","base.random.betaprime":"\nbase.random.betaprime( α, β )\n    Returns a pseudorandom number drawn from a beta prime distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.betaprime( 2.0, 5.0 );\n\n\nbase.random.betaprime.factory( [α, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a beta prime distribution.\n\n    If provided `α` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `α` and `β`, the returned PRNG requires that both `α` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        First shape parameter.\n\n    β: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.betaprime.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `α` and `β`:\n    > rand = base.random.betaprime.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.betaprime.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.betaprime.NAME\n    'betaprime'\n\n\nbase.random.betaprime.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.betaprime.PRNG;\n\n\nbase.random.betaprime.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.betaprime.seed;\n\n\nbase.random.betaprime.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.betaprime.seedLength;\n\n\nbase.random.betaprime.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.betaprime.state\n    <Uint32Array>\n\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.betaprime.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n\n\nbase.random.betaprime.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.betaprime.stateLength;\n\n\nbase.random.betaprime.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.betaprime.byteLength;\n\n\nbase.random.betaprime.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.betaprime.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.betaprime, random.iterators.betaprime, random.streams.betaprime\n","base.random.betaprime.factory":"\nbase.random.betaprime.factory( [α, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a beta prime distribution.\n\n    If provided `α` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `α` and `β`, the returned PRNG requires that both `α` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        First shape parameter.\n\n    β: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.betaprime.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `α` and `β`:\n    > rand = base.random.betaprime.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.betaprime.NAME":"\nbase.random.betaprime.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.betaprime.NAME\n    'betaprime'","base.random.betaprime.PRNG":"\nbase.random.betaprime.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.betaprime.PRNG;","base.random.betaprime.seed":"\nbase.random.betaprime.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.betaprime.seed;","base.random.betaprime.seedLength":"\nbase.random.betaprime.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.betaprime.seedLength;","base.random.betaprime.state":"\nbase.random.betaprime.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.betaprime.state\n    <Uint32Array>\n\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.betaprime.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>\n    > r = base.random.betaprime( 2.0, 5.0 )\n    <number>","base.random.betaprime.stateLength":"\nbase.random.betaprime.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.betaprime.stateLength;","base.random.betaprime.byteLength":"\nbase.random.betaprime.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.betaprime.byteLength;","base.random.betaprime.toJSON":"\nbase.random.betaprime.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.betaprime.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.betaprime, random.iterators.betaprime, random.streams.betaprime","base.random.binomial":"\nbase.random.binomial( n, p )\n    Returns a pseudorandom number drawn from a binomial distribution.\n\n    If `n` is not a positive integer or `p` is not a probability, the function\n    returns `NaN`.\n\n    If `n` or `p` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.binomial( 20, 0.8 );\n\n\nbase.random.binomial.factory( [n, p, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a binomial distribution.\n\n    If provided `n` and `p`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `n` and `p`, the returned PRNG requires that both `n` and\n    `p` be provided at each invocation.\n\n    Parameters\n    ----------\n    n: integer (optional)\n        Number of trials.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.binomial.factory();\n    > var r = rand( 20, 0.3 );\n    > r = rand( 10, 0.77 );\n\n    // Provide `n` and `p`:\n    > rand = base.random.binomial.factory( 10, 0.8 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.binomial.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.binomial.NAME\n    'binomial'\n\n\nbase.random.binomial.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.binomial.PRNG;\n\n\nbase.random.binomial.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.binomial.seed;\n\n\nbase.random.binomial.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.binomial.seedLength;\n\n\nbase.random.binomial.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.binomial( 20, 0.8 )\n    <number>\n    > r = base.random.binomial( 20, 0.8 )\n    <number>\n    > r = base.random.binomial( 20, 0.8 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.binomial.state\n    <Uint32Array>\n\n    > r = base.random.binomial( 20, 0.8 )\n    <number>\n    > r = base.random.binomial( 20, 0.8 )\n    <number>\n\n    // Set the state:\n    > base.random.binomial.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.binomial( 20, 0.8 )\n    <number>\n    > r = base.random.binomial( 20, 0.8 )\n    <number>\n\n\nbase.random.binomial.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.binomial.stateLength;\n\n\nbase.random.binomial.byteLength\n    Size of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.binomial.byteLength;\n\n\nbase.random.binomial.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.binomial.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.binomial, random.iterators.binomial, random.streams.binomial\n","base.random.binomial.factory":"\nbase.random.binomial.factory( [n, p, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a binomial distribution.\n\n    If provided `n` and `p`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `n` and `p`, the returned PRNG requires that both `n` and\n    `p` be provided at each invocation.\n\n    Parameters\n    ----------\n    n: integer (optional)\n        Number of trials.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.binomial.factory();\n    > var r = rand( 20, 0.3 );\n    > r = rand( 10, 0.77 );\n\n    // Provide `n` and `p`:\n    > rand = base.random.binomial.factory( 10, 0.8 );\n    > r = rand();\n    > r = rand();","base.random.binomial.NAME":"\nbase.random.binomial.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.binomial.NAME\n    'binomial'","base.random.binomial.PRNG":"\nbase.random.binomial.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.binomial.PRNG;","base.random.binomial.seed":"\nbase.random.binomial.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.binomial.seed;","base.random.binomial.seedLength":"\nbase.random.binomial.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.binomial.seedLength;","base.random.binomial.state":"\nbase.random.binomial.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.binomial( 20, 0.8 )\n    <number>\n    > r = base.random.binomial( 20, 0.8 )\n    <number>\n    > r = base.random.binomial( 20, 0.8 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.binomial.state\n    <Uint32Array>\n\n    > r = base.random.binomial( 20, 0.8 )\n    <number>\n    > r = base.random.binomial( 20, 0.8 )\n    <number>\n\n    // Set the state:\n    > base.random.binomial.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.binomial( 20, 0.8 )\n    <number>\n    > r = base.random.binomial( 20, 0.8 )\n    <number>","base.random.binomial.stateLength":"\nbase.random.binomial.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.binomial.stateLength;","base.random.binomial.byteLength":"\nbase.random.binomial.byteLength\n    Size of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.binomial.byteLength;","base.random.binomial.toJSON":"\nbase.random.binomial.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.binomial.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.binomial, random.iterators.binomial, random.streams.binomial","base.random.boxMuller":"\nbase.random.boxMuller()\n    Returns a pseudorandom number drawn from a standard normal distribution.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.boxMuller();\n\n\nbase.random.boxMuller.factory( [options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a standard normal distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.boxMuller.factory();\n    > r = rand();\n    > r = rand();\n\n\nbase.random.boxMuller.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.boxMuller.NAME\n    'box-muller'\n\n\nbase.random.boxMuller.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.boxMuller.PRNG;\n\n\nbase.random.boxMuller.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.boxMuller.seed;\n\n\nbase.random.boxMuller.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.boxMuller.seedLength;\n\n\nbase.random.boxMuller.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.boxMuller()\n    <number>\n    > r = base.random.boxMuller()\n    <number>\n    > r = base.random.boxMuller()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.boxMuller.state\n    <Uint32Array>\n\n    > r = base.random.boxMuller()\n    <number>\n    > r = base.random.boxMuller()\n    <number>\n\n    // Set the state:\n    > base.random.boxMuller.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.boxMuller()\n    <number>\n    > r = base.random.boxMuller()\n    <number>\n\n\nbase.random.boxMuller.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.boxMuller.stateLength;\n\n\nbase.random.boxMuller.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.boxMuller.byteLength;\n\n\nbase.random.boxMuller.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.boxMuller.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.iterators.boxMuller, random.streams.boxMuller\n","base.random.boxMuller.factory":"\nbase.random.boxMuller.factory( [options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a standard normal distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.boxMuller.factory();\n    > r = rand();\n    > r = rand();","base.random.boxMuller.NAME":"\nbase.random.boxMuller.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.boxMuller.NAME\n    'box-muller'","base.random.boxMuller.PRNG":"\nbase.random.boxMuller.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.boxMuller.PRNG;","base.random.boxMuller.seed":"\nbase.random.boxMuller.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.boxMuller.seed;","base.random.boxMuller.seedLength":"\nbase.random.boxMuller.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.boxMuller.seedLength;","base.random.boxMuller.state":"\nbase.random.boxMuller.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.boxMuller()\n    <number>\n    > r = base.random.boxMuller()\n    <number>\n    > r = base.random.boxMuller()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.boxMuller.state\n    <Uint32Array>\n\n    > r = base.random.boxMuller()\n    <number>\n    > r = base.random.boxMuller()\n    <number>\n\n    // Set the state:\n    > base.random.boxMuller.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.boxMuller()\n    <number>\n    > r = base.random.boxMuller()\n    <number>","base.random.boxMuller.stateLength":"\nbase.random.boxMuller.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.boxMuller.stateLength;","base.random.boxMuller.byteLength":"\nbase.random.boxMuller.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.boxMuller.byteLength;","base.random.boxMuller.toJSON":"\nbase.random.boxMuller.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.boxMuller.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.iterators.boxMuller, random.streams.boxMuller","base.random.cauchy":"\nbase.random.cauchy( x0, Ɣ )\n    Returns a pseudorandom number drawn from a Cauchy distribution.\n\n    If `x0` or `Ɣ` is `NaN` or `Ɣ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.cauchy( 2.0, 5.0 );\n\n\nbase.random.cauchy.factory( [x0, Ɣ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Cauchy distribution.\n\n    If provided `x0` and `Ɣ`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `x0` and `Ɣ`, the returned PRNG requires that both `x0` and\n    `Ɣ` be provided at each invocation.\n\n    Parameters\n    ----------\n    x0: number (optional)\n        Location parameter.\n\n    Ɣ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.cauchy.factory();\n    > var r = rand( 0.0, 1.5 );\n    > r = rand( -2.0, 2.0 );\n\n    // Provide `x0` and `Ɣ`:\n    > rand = base.random.cauchy.factory( 0.0, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.cauchy.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.cauchy.NAME\n    'cauchy'\n\n\nbase.random.cauchy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.cauchy.PRNG;\n\n\nbase.random.cauchy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.cauchy.seed;\n\n\nbase.random.cauchy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.cauchy.seedLength;\n\n\nbase.random.cauchy.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.cauchy.state\n    <Uint32Array>\n\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.cauchy.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n\n\nbase.random.cauchy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.cauchy.stateLength;\n\n\nbase.random.cauchy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.cauchy.byteLength;\n\n\nbase.random.cauchy.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.cauchy.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.cauchy, random.iterators.cauchy, random.streams.cauchy\n","base.random.cauchy.factory":"\nbase.random.cauchy.factory( [x0, Ɣ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Cauchy distribution.\n\n    If provided `x0` and `Ɣ`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `x0` and `Ɣ`, the returned PRNG requires that both `x0` and\n    `Ɣ` be provided at each invocation.\n\n    Parameters\n    ----------\n    x0: number (optional)\n        Location parameter.\n\n    Ɣ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.cauchy.factory();\n    > var r = rand( 0.0, 1.5 );\n    > r = rand( -2.0, 2.0 );\n\n    // Provide `x0` and `Ɣ`:\n    > rand = base.random.cauchy.factory( 0.0, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.cauchy.NAME":"\nbase.random.cauchy.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.cauchy.NAME\n    'cauchy'","base.random.cauchy.PRNG":"\nbase.random.cauchy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.cauchy.PRNG;","base.random.cauchy.seed":"\nbase.random.cauchy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.cauchy.seed;","base.random.cauchy.seedLength":"\nbase.random.cauchy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.cauchy.seedLength;","base.random.cauchy.state":"\nbase.random.cauchy.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.cauchy.state\n    <Uint32Array>\n\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.cauchy.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>\n    > r = base.random.cauchy( 2.0, 5.0 )\n    <number>","base.random.cauchy.stateLength":"\nbase.random.cauchy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.cauchy.stateLength;","base.random.cauchy.byteLength":"\nbase.random.cauchy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.cauchy.byteLength;","base.random.cauchy.toJSON":"\nbase.random.cauchy.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.cauchy.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.cauchy, random.iterators.cauchy, random.streams.cauchy","base.random.chi":"\nbase.random.chi( k )\n    Returns a pseudorandom number drawn from a chi distribution.\n\n    If `k <= 0` or `k` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.chi( 2 );\n\n\nbase.random.chi.factory( [k, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a chi distribution.\n\n    If provided `k`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `k`, the returned PRNG requires that `k` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.chi.factory();\n    > var r = rand( 5 );\n    > r = rand( 3.14 );\n\n    // Provide `k`:\n    > rand = base.random.chi.factory( 3 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.chi.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.chi.NAME\n    'chi'\n\n\nbase.random.chi.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.chi.PRNG;\n\n\nbase.random.chi.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.chi.seed;\n\n\nbase.random.chi.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.chi.seedLength;\n\n\nbase.random.chi.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.chi( 2 )\n    <number>\n    > r = base.random.chi( 2 )\n    <number>\n    > r = base.random.chi( 2 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.chi.state\n    <Uint32Array>\n\n    > r = base.random.chi( 2 )\n    <number>\n    > r = base.random.chi( 2 )\n    <number>\n\n    // Set the state:\n    > base.random.chi.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.chi( 2 )\n    <number>\n    > r = base.random.chi( 2 )\n    <number>\n\n\nbase.random.chi.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.chi.stateLength;\n\n\nbase.random.chi.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.chi.byteLength;\n\n\nbase.random.chi.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.chi.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.chi, random.iterators.chi, random.streams.chi\n","base.random.chi.factory":"\nbase.random.chi.factory( [k, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a chi distribution.\n\n    If provided `k`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `k`, the returned PRNG requires that `k` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.chi.factory();\n    > var r = rand( 5 );\n    > r = rand( 3.14 );\n\n    // Provide `k`:\n    > rand = base.random.chi.factory( 3 );\n    > r = rand();\n    > r = rand();","base.random.chi.NAME":"\nbase.random.chi.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.chi.NAME\n    'chi'","base.random.chi.PRNG":"\nbase.random.chi.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.chi.PRNG;","base.random.chi.seed":"\nbase.random.chi.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.chi.seed;","base.random.chi.seedLength":"\nbase.random.chi.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.chi.seedLength;","base.random.chi.state":"\nbase.random.chi.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.chi( 2 )\n    <number>\n    > r = base.random.chi( 2 )\n    <number>\n    > r = base.random.chi( 2 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.chi.state\n    <Uint32Array>\n\n    > r = base.random.chi( 2 )\n    <number>\n    > r = base.random.chi( 2 )\n    <number>\n\n    // Set the state:\n    > base.random.chi.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.chi( 2 )\n    <number>\n    > r = base.random.chi( 2 )\n    <number>","base.random.chi.stateLength":"\nbase.random.chi.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.chi.stateLength;","base.random.chi.byteLength":"\nbase.random.chi.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.chi.byteLength;","base.random.chi.toJSON":"\nbase.random.chi.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.chi.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.chi, random.iterators.chi, random.streams.chi","base.random.chisquare":"\nbase.random.chisquare( k )\n    Returns a pseudorandom number drawn from a chi-square distribution.\n\n    If `k <= 0` or `k` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.chisquare( 2 );\n\n\nbase.random.chisquare.factory( [k, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a chi-square distribution.\n\n    If provided `k`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `k`, the returned PRNG requires that `k` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.chisquare.factory();\n    > var r = rand( 5 );\n    > r = rand( 3.14 );\n\n    // Provide `k`:\n    > rand = base.random.chisquare.factory( 3 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.chisquare.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.chisquare.NAME\n    'chisquare'\n\n\nbase.random.chisquare.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.chisquare.PRNG;\n\n\nbase.random.chisquare.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.chisquare.seed;\n\n\nbase.random.chisquare.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.chisquare.seedLength;\n\n\nbase.random.chisquare.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.chisquare( 2 )\n    <number>\n    > r = base.random.chisquare( 2 )\n    <number>\n    > r = base.random.chisquare( 2 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.chisquare.state\n    <Uint32Array>\n\n    > r = base.random.chisquare( 2 )\n    <number>\n    > r = base.random.chisquare( 2 )\n    <number>\n\n    // Set the state:\n    > base.random.chisquare.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.chisquare( 2 )\n    <number>\n    > r = base.random.chisquare( 2 )\n    <number>\n\n\nbase.random.chisquare.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.chisquare.stateLength;\n\n\nbase.random.chisquare.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.chisquare.byteLength;\n\n\nbase.random.chisquare.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.chisquare.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.chisquare, random.iterators.chisquare, random.streams.chisquare\n","base.random.chisquare.factory":"\nbase.random.chisquare.factory( [k, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a chi-square distribution.\n\n    If provided `k`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `k`, the returned PRNG requires that `k` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.chisquare.factory();\n    > var r = rand( 5 );\n    > r = rand( 3.14 );\n\n    // Provide `k`:\n    > rand = base.random.chisquare.factory( 3 );\n    > r = rand();\n    > r = rand();","base.random.chisquare.NAME":"\nbase.random.chisquare.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.chisquare.NAME\n    'chisquare'","base.random.chisquare.PRNG":"\nbase.random.chisquare.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.chisquare.PRNG;","base.random.chisquare.seed":"\nbase.random.chisquare.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.chisquare.seed;","base.random.chisquare.seedLength":"\nbase.random.chisquare.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.chisquare.seedLength;","base.random.chisquare.state":"\nbase.random.chisquare.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.chisquare( 2 )\n    <number>\n    > r = base.random.chisquare( 2 )\n    <number>\n    > r = base.random.chisquare( 2 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.chisquare.state\n    <Uint32Array>\n\n    > r = base.random.chisquare( 2 )\n    <number>\n    > r = base.random.chisquare( 2 )\n    <number>\n\n    // Set the state:\n    > base.random.chisquare.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.chisquare( 2 )\n    <number>\n    > r = base.random.chisquare( 2 )\n    <number>","base.random.chisquare.stateLength":"\nbase.random.chisquare.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.chisquare.stateLength;","base.random.chisquare.byteLength":"\nbase.random.chisquare.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.chisquare.byteLength;","base.random.chisquare.toJSON":"\nbase.random.chisquare.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.chisquare.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.chisquare, random.iterators.chisquare, random.streams.chisquare","base.random.cosine":"\nbase.random.cosine( μ, s )\n    Returns a pseudorandom number drawn from a raised cosine distribution.\n\n    If `μ` or `s` is `NaN` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.cosine( 2.0, 5.0 );\n\n\nbase.random.cosine.factory( [μ, s, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a raised cosine distribution.\n\n    If provided `μ` and `s`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n    `s` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.cosine.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `s`:\n    > rand = base.random.cosine.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.cosine.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.cosine.NAME\n    'cosine'\n\n\nbase.random.cosine.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.cosine.PRNG;\n\n\nbase.random.cosine.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.cosine.seed;\n\n\nbase.random.cosine.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.cosine.seedLength;\n\n\nbase.random.cosine.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.cosine( 2.0, 5.0 )\n    <number>\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.cosine.state\n    <Uint32Array>\n\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.cosine.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>\n\n\nbase.random.cosine.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.cosine.stateLength;\n\n\nbase.random.cosine.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.cosine.byteLength;\n\n\nbase.random.cosine.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.cosine.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.cosine, random.iterators.cosine, random.streams.cosine\n","base.random.cosine.factory":"\nbase.random.cosine.factory( [μ, s, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a raised cosine distribution.\n\n    If provided `μ` and `s`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n    `s` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.cosine.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `s`:\n    > rand = base.random.cosine.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.cosine.NAME":"\nbase.random.cosine.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.cosine.NAME\n    'cosine'","base.random.cosine.PRNG":"\nbase.random.cosine.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.cosine.PRNG;","base.random.cosine.seed":"\nbase.random.cosine.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.cosine.seed;","base.random.cosine.seedLength":"\nbase.random.cosine.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.cosine.seedLength;","base.random.cosine.state":"\nbase.random.cosine.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.cosine( 2.0, 5.0 )\n    <number>\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.cosine.state\n    <Uint32Array>\n\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.cosine.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>\n    > r = base.random.cosine( 2.0, 5.0 )\n    <number>","base.random.cosine.stateLength":"\nbase.random.cosine.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.cosine.stateLength;","base.random.cosine.byteLength":"\nbase.random.cosine.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.cosine.byteLength;","base.random.cosine.toJSON":"\nbase.random.cosine.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.cosine.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.cosine, random.iterators.cosine, random.streams.cosine","base.random.discreteUniform":"\nbase.random.discreteUniform( a, b )\n    Returns a pseudorandom number drawn from a discrete uniform distribution.\n\n    If `a > b`, the function returns `NaN`.\n\n    If `a` or `b` is not an integer value, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.discreteUniform( 2, 50 );\n\n\nbase.random.discreteUniform.factory( [a, b, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a discrete uniform distribution.\n\n    If provided `a` and `b`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `a` and `b`, the returned PRNG requires that both `a` and\n    `b` be provided at each invocation.\n\n    Parameters\n    ----------\n    a: integer (optional)\n        Minimum support.\n\n    b: integer (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom integers. If provided, the `state` and `seed`\n        options are ignored. In order to seed the returned pseudorandom number\n        generator, one must seed the provided `prng` (assuming the provided\n        `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n        properties specifying the minimum and maximum possible pseudorandom\n        integers.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.discreteUniform.factory();\n    > var r = rand( 0, 10 );\n    > r = rand( -20, 20 );\n\n    // Provide `a` and `b`:\n    > rand = base.random.discreteUniform.factory( 0, 10 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.discreteUniform.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.discreteUniform.NAME\n    'discrete-uniform'\n\n\nbase.random.discreteUniform.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.discreteUniform.PRNG;\n\n\nbase.random.discreteUniform.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.discreteUniform.seed;\n\n\nbase.random.discreteUniform.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.discreteUniform.seedLength;\n\n\nbase.random.discreteUniform.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.discreteUniform( 2, 50 )\n    <number>\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.discreteUniform.state\n    <Uint32Array>\n\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>\n\n    // Set the state:\n    > base.random.discreteUniform.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>\n\n\nbase.random.discreteUniform.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.discreteUniform.stateLength;\n\n\nbase.random.discreteUniform.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.discreteUniform.byteLength;\n\n\nbase.random.discreteUniform.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.discreteUniform.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.discreteUniform, random.iterators.discreteUniform, random.streams.discreteUniform\n","base.random.discreteUniform.factory":"\nbase.random.discreteUniform.factory( [a, b, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a discrete uniform distribution.\n\n    If provided `a` and `b`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `a` and `b`, the returned PRNG requires that both `a` and\n    `b` be provided at each invocation.\n\n    Parameters\n    ----------\n    a: integer (optional)\n        Minimum support.\n\n    b: integer (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom integers. If provided, the `state` and `seed`\n        options are ignored. In order to seed the returned pseudorandom number\n        generator, one must seed the provided `prng` (assuming the provided\n        `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n        properties specifying the minimum and maximum possible pseudorandom\n        integers.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.discreteUniform.factory();\n    > var r = rand( 0, 10 );\n    > r = rand( -20, 20 );\n\n    // Provide `a` and `b`:\n    > rand = base.random.discreteUniform.factory( 0, 10 );\n    > r = rand();\n    > r = rand();","base.random.discreteUniform.NAME":"\nbase.random.discreteUniform.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.discreteUniform.NAME\n    'discrete-uniform'","base.random.discreteUniform.PRNG":"\nbase.random.discreteUniform.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.discreteUniform.PRNG;","base.random.discreteUniform.seed":"\nbase.random.discreteUniform.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.discreteUniform.seed;","base.random.discreteUniform.seedLength":"\nbase.random.discreteUniform.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.discreteUniform.seedLength;","base.random.discreteUniform.state":"\nbase.random.discreteUniform.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.discreteUniform( 2, 50 )\n    <number>\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.discreteUniform.state\n    <Uint32Array>\n\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>\n\n    // Set the state:\n    > base.random.discreteUniform.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>\n    > r = base.random.discreteUniform( 2, 50 )\n    <number>","base.random.discreteUniform.stateLength":"\nbase.random.discreteUniform.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.discreteUniform.stateLength;","base.random.discreteUniform.byteLength":"\nbase.random.discreteUniform.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.discreteUniform.byteLength;","base.random.discreteUniform.toJSON":"\nbase.random.discreteUniform.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.discreteUniform.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.discreteUniform, random.iterators.discreteUniform, random.streams.discreteUniform","base.random.erlang":"\nbase.random.erlang( k, λ )\n    Returns a pseudorandom number drawn from an Erlang distribution.\n\n    If `k` is not a positive integer or `λ <= 0`, the function returns `NaN`.\n\n    If `k` or `λ` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: integer\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.erlang( 2, 5.0 );\n\n\nbase.random.erlang.factory( [k, λ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an Erlang distribution.\n\n    If provided `k` and `λ`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `k` and `λ`, the returned PRNG requires that both `k` and\n    `λ` be provided at each invocation.\n\n    Parameters\n    ----------\n    k: integer (optional)\n        Shape parameter.\n\n    λ: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.erlang.factory();\n    > var r = rand( 2, 1.0 );\n    > r = rand( 4, 3.14 );\n\n    // Provide `k` and `λ`:\n    > rand = base.random.erlang.factory( 2, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.erlang.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.erlang.NAME\n    'erlang'\n\n\nbase.random.erlang.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.erlang.PRNG;\n\n\nbase.random.erlang.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.erlang.seed;\n\n\nbase.random.erlang.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.erlang.seedLength;\n\n\nbase.random.erlang.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.erlang( 2, 5.0 )\n    <number>\n    > r = base.random.erlang( 2, 5.0 )\n    <number>\n    > r = base.random.erlang( 2, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.erlang.state\n    <Uint32Array>\n\n    > r = base.random.erlang( 2, 5.0 )\n    <number>\n    > r = base.random.erlang( 2, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.erlang.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.erlang( 2, 5.0 )\n    <number>\n    > r = base.random.erlang( 2, 5.0 )\n    <number>\n\n\nbase.random.erlang.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.erlang.stateLength;\n\n\nbase.random.erlang.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.erlang.byteLength;\n\n\nbase.random.erlang.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.erlang.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.erlang, random.iterators.erlang, random.streams.erlang\n","base.random.erlang.factory":"\nbase.random.erlang.factory( [k, λ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an Erlang distribution.\n\n    If provided `k` and `λ`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `k` and `λ`, the returned PRNG requires that both `k` and\n    `λ` be provided at each invocation.\n\n    Parameters\n    ----------\n    k: integer (optional)\n        Shape parameter.\n\n    λ: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.erlang.factory();\n    > var r = rand( 2, 1.0 );\n    > r = rand( 4, 3.14 );\n\n    // Provide `k` and `λ`:\n    > rand = base.random.erlang.factory( 2, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.erlang.NAME":"\nbase.random.erlang.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.erlang.NAME\n    'erlang'","base.random.erlang.PRNG":"\nbase.random.erlang.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.erlang.PRNG;","base.random.erlang.seed":"\nbase.random.erlang.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.erlang.seed;","base.random.erlang.seedLength":"\nbase.random.erlang.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.erlang.seedLength;","base.random.erlang.state":"\nbase.random.erlang.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.erlang( 2, 5.0 )\n    <number>\n    > r = base.random.erlang( 2, 5.0 )\n    <number>\n    > r = base.random.erlang( 2, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.erlang.state\n    <Uint32Array>\n\n    > r = base.random.erlang( 2, 5.0 )\n    <number>\n    > r = base.random.erlang( 2, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.erlang.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.erlang( 2, 5.0 )\n    <number>\n    > r = base.random.erlang( 2, 5.0 )\n    <number>","base.random.erlang.stateLength":"\nbase.random.erlang.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.erlang.stateLength;","base.random.erlang.byteLength":"\nbase.random.erlang.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.erlang.byteLength;","base.random.erlang.toJSON":"\nbase.random.erlang.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.erlang.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.erlang, random.iterators.erlang, random.streams.erlang","base.random.exponential":"\nbase.random.exponential( λ )\n    Returns a pseudorandom number drawn from an exponential distribution.\n\n    If `λ <= 0` or `λ` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.exponential( 7.9 );\n\n\nbase.random.exponential.factory( [λ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an exponential distribution.\n\n    If provided `λ`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    λ: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.exponential.factory();\n    > var r = rand( 5.0 );\n    > r = rand( 3.14 );\n\n    // Provide `λ`:\n    > rand = base.random.exponential.factory( 10.0 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.exponential.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.exponential.NAME\n    'exponential'\n\n\nbase.random.exponential.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.exponential.PRNG;\n\n\nbase.random.exponential.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.exponential.seed;\n\n\nbase.random.exponential.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.exponential.seedLength;\n\n\nbase.random.exponential.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.exponential( 7.9 )\n    <number>\n    > r = base.random.exponential( 7.9 )\n    <number>\n    > r = base.random.exponential( 7.9 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.exponential.state\n    <Uint32Array>\n\n    > r = base.random.exponential( 7.9 )\n    <number>\n    > r = base.random.exponential( 7.9 )\n    <number>\n\n    // Set the state:\n    > base.random.exponential.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.exponential( 7.9 )\n    <number>\n    > r = base.random.exponential( 7.9 )\n    <number>\n\n\nbase.random.exponential.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.exponential.stateLength;\n\n\nbase.random.exponential.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.exponential.byteLength;\n\n\nbase.random.exponential.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.exponential.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.exponential, random.iterators.exponential, random.streams.exponential\n","base.random.exponential.factory":"\nbase.random.exponential.factory( [λ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an exponential distribution.\n\n    If provided `λ`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    λ: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.exponential.factory();\n    > var r = rand( 5.0 );\n    > r = rand( 3.14 );\n\n    // Provide `λ`:\n    > rand = base.random.exponential.factory( 10.0 );\n    > r = rand();\n    > r = rand();","base.random.exponential.NAME":"\nbase.random.exponential.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.exponential.NAME\n    'exponential'","base.random.exponential.PRNG":"\nbase.random.exponential.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.exponential.PRNG;","base.random.exponential.seed":"\nbase.random.exponential.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.exponential.seed;","base.random.exponential.seedLength":"\nbase.random.exponential.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.exponential.seedLength;","base.random.exponential.state":"\nbase.random.exponential.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.exponential( 7.9 )\n    <number>\n    > r = base.random.exponential( 7.9 )\n    <number>\n    > r = base.random.exponential( 7.9 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.exponential.state\n    <Uint32Array>\n\n    > r = base.random.exponential( 7.9 )\n    <number>\n    > r = base.random.exponential( 7.9 )\n    <number>\n\n    // Set the state:\n    > base.random.exponential.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.exponential( 7.9 )\n    <number>\n    > r = base.random.exponential( 7.9 )\n    <number>","base.random.exponential.stateLength":"\nbase.random.exponential.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.exponential.stateLength;","base.random.exponential.byteLength":"\nbase.random.exponential.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.exponential.byteLength;","base.random.exponential.toJSON":"\nbase.random.exponential.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.exponential.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.exponential, random.iterators.exponential, random.streams.exponential","base.random.f":"\nbase.random.f( d1, d2 )\n    Returns a pseudorandom number drawn from an F distribution.\n\n    If `d1 <= 0` or `d2 <= 0`, the function returns `NaN`.\n\n    If `d1` or `d2` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    d1: number\n        Degrees of freedom.\n\n    d2: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.f( 2.0, 5.0 );\n\n\nbase.random.f.factory( [d1, d2, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an F distribution.\n\n    If provided `d1` and `d2`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `d1` and `d2`, the returned PRNG requires that both `d1` and\n    `d2` be provided at each invocation.\n\n    Parameters\n    ----------\n    d1: number (optional)\n        Degrees of freedom.\n\n    d2: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.f.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 3.0, 3.14 );\n\n    // Provide `d1` and `d2`:\n    > rand = base.random.f.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.f.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.f.NAME\n    'f'\n\n\nbase.random.f.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.f.PRNG;\n\n\nbase.random.f.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.f.seed;\n\n\nbase.random.f.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.f.seedLength;\n\n\nbase.random.f.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.f( 1.5, 1.5 )\n    <number>\n    > r = base.random.f( 1.5, 1.5 )\n    <number>\n    > r = base.random.f( 1.5, 1.5 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.f.state\n    <Uint32Array>\n\n    > r = base.random.f( 1.5, 1.5 )\n    <number>\n    > r = base.random.f( 1.5, 1.5 )\n    <number>\n\n    // Set the state:\n    > base.random.f.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.f( 1.5, 1.5 )\n    <number>\n    > r = base.random.f( 1.5, 1.5 )\n    <number>\n\n\nbase.random.f.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.f.stateLength;\n\n\nbase.random.f.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.f.byteLength;\n\n\nbase.random.f.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.f.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.f, random.iterators.f, random.streams.f\n","base.random.f.factory":"\nbase.random.f.factory( [d1, d2, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an F distribution.\n\n    If provided `d1` and `d2`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `d1` and `d2`, the returned PRNG requires that both `d1` and\n    `d2` be provided at each invocation.\n\n    Parameters\n    ----------\n    d1: number (optional)\n        Degrees of freedom.\n\n    d2: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.f.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 3.0, 3.14 );\n\n    // Provide `d1` and `d2`:\n    > rand = base.random.f.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.f.NAME":"\nbase.random.f.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.f.NAME\n    'f'","base.random.f.PRNG":"\nbase.random.f.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.f.PRNG;","base.random.f.seed":"\nbase.random.f.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.f.seed;","base.random.f.seedLength":"\nbase.random.f.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.f.seedLength;","base.random.f.state":"\nbase.random.f.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.f( 1.5, 1.5 )\n    <number>\n    > r = base.random.f( 1.5, 1.5 )\n    <number>\n    > r = base.random.f( 1.5, 1.5 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.f.state\n    <Uint32Array>\n\n    > r = base.random.f( 1.5, 1.5 )\n    <number>\n    > r = base.random.f( 1.5, 1.5 )\n    <number>\n\n    // Set the state:\n    > base.random.f.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.f( 1.5, 1.5 )\n    <number>\n    > r = base.random.f( 1.5, 1.5 )\n    <number>","base.random.f.stateLength":"\nbase.random.f.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.f.stateLength;","base.random.f.byteLength":"\nbase.random.f.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.f.byteLength;","base.random.f.toJSON":"\nbase.random.f.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.f.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.f, random.iterators.f, random.streams.f","base.random.frechet":"\nbase.random.frechet( α, s, m )\n    Returns a pseudorandom number drawn from a Fréchet distribution.\n\n    If provided `α <= 0` or `s <= 0`, the function returns `NaN`.\n\n    If either `α`, `s`, or `m` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.frechet( 2.0, 5.0, 3.33 );\n\n\nbase.random.frechet.factory( [α, s, m, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a triangular distribution.\n\n    If provided `α`, `s`, and `m`, the returned PRNG returns random variates\n    drawn from the specified distribution.\n\n    If not provided `α`, `s`, and `m`, the returned PRNG requires that `α`, `s`,\n    and `m` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    m: number (optional)\n        Location parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.frechet.factory();\n    > var r = rand( 1.0, 1.0, 0.5 );\n    > r = rand( 2.0, 2.0, 1.0 );\n\n    // Provide `α`, `s`, and `m`:\n    > rand = base.random.frechet.factory( 1.0, 1.0, 0.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.frechet.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.frechet.NAME\n    'frechet'\n\n\nbase.random.frechet.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.frechet.PRNG;\n\n\nbase.random.frechet.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.frechet.seed;\n\n\nbase.random.frechet.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.frechet.seedLength;\n\n\nbase.random.frechet.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.frechet.state\n    <Uint32Array>\n\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n\n    // Set the state:\n    > base.random.frechet.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n\n\nbase.random.frechet.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.frechet.stateLength;\n\n\nbase.random.frechet.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.frechet.byteLength;\n\n\nbase.random.frechet.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.frechet.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.frechet, random.iterators.frechet, random.streams.frechet\n","base.random.frechet.factory":"\nbase.random.frechet.factory( [α, s, m, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a triangular distribution.\n\n    If provided `α`, `s`, and `m`, the returned PRNG returns random variates\n    drawn from the specified distribution.\n\n    If not provided `α`, `s`, and `m`, the returned PRNG requires that `α`, `s`,\n    and `m` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    m: number (optional)\n        Location parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.frechet.factory();\n    > var r = rand( 1.0, 1.0, 0.5 );\n    > r = rand( 2.0, 2.0, 1.0 );\n\n    // Provide `α`, `s`, and `m`:\n    > rand = base.random.frechet.factory( 1.0, 1.0, 0.5 );\n    > r = rand();\n    > r = rand();","base.random.frechet.NAME":"\nbase.random.frechet.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.frechet.NAME\n    'frechet'","base.random.frechet.PRNG":"\nbase.random.frechet.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.frechet.PRNG;","base.random.frechet.seed":"\nbase.random.frechet.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.frechet.seed;","base.random.frechet.seedLength":"\nbase.random.frechet.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.frechet.seedLength;","base.random.frechet.state":"\nbase.random.frechet.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.frechet.state\n    <Uint32Array>\n\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n\n    // Set the state:\n    > base.random.frechet.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.frechet( 1.0, 1.0, 0.5 )\n    <number>","base.random.frechet.stateLength":"\nbase.random.frechet.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.frechet.stateLength;","base.random.frechet.byteLength":"\nbase.random.frechet.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.frechet.byteLength;","base.random.frechet.toJSON":"\nbase.random.frechet.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.frechet.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.frechet, random.iterators.frechet, random.streams.frechet","base.random.gamma":"\nbase.random.gamma( α, β )\n    Returns a pseudorandom number drawn from a gamma distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.gamma( 2.0, 5.0 );\n\n\nbase.random.gamma.factory( [α, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a gamma distribution.\n\n    If provided `α` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `α` and `β`, the returned PRNG requires that both `α` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.gamma.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 3.14, 2.25 );\n\n    // Provide `α` and `β`:\n    > rand = base.random.gamma.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.gamma.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.gamma.NAME\n    'gamma'\n\n\nbase.random.gamma.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.gamma.PRNG;\n\n\nbase.random.gamma.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.gamma.seed;\n\n\nbase.random.gamma.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.gamma.seedLength;\n\n\nbase.random.gamma.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.gamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.gamma.state\n    <Uint32Array>\n\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.gamma.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>\n\n\nbase.random.gamma.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.gamma.stateLength;\n\n\nbase.random.gamma.byteLength\n    Size of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.gamma.byteLength;\n\n\nbase.random.gamma.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.gamma.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.gamma, random.iterators.gamma, random.streams.gamma\n","base.random.gamma.factory":"\nbase.random.gamma.factory( [α, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a gamma distribution.\n\n    If provided `α` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `α` and `β`, the returned PRNG requires that both `α` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.gamma.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 3.14, 2.25 );\n\n    // Provide `α` and `β`:\n    > rand = base.random.gamma.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.gamma.NAME":"\nbase.random.gamma.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.gamma.NAME\n    'gamma'","base.random.gamma.PRNG":"\nbase.random.gamma.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.gamma.PRNG;","base.random.gamma.seed":"\nbase.random.gamma.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.gamma.seed;","base.random.gamma.seedLength":"\nbase.random.gamma.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.gamma.seedLength;","base.random.gamma.state":"\nbase.random.gamma.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.gamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.gamma.state\n    <Uint32Array>\n\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.gamma.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.gamma( 2.0, 5.0 )\n    <number>","base.random.gamma.stateLength":"\nbase.random.gamma.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.gamma.stateLength;","base.random.gamma.byteLength":"\nbase.random.gamma.byteLength\n    Size of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.gamma.byteLength;","base.random.gamma.toJSON":"\nbase.random.gamma.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.gamma.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.gamma, random.iterators.gamma, random.streams.gamma","base.random.geometric":"\nbase.random.geometric( p )\n    Returns a pseudorandom number drawn from a geometric distribution.\n\n    If `p < 0` or `p > 1` or `p` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.geometric( 0.8 );\n\n\nbase.random.geometric.factory( [p, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a geometric distribution.\n\n    If provided `p`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `p`, the returned PRNG requires that `p` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.geometric.factory();\n    > var r = rand( 0.3 );\n    > r = rand( 0.59 );\n\n    // Provide `p`:\n    > rand = base.random.geometric.factory( 0.3 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.geometric.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.geometric.NAME\n    'geometric'\n\n\nbase.random.geometric.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.geometric.PRNG;\n\n\nbase.random.geometric.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.geometric.seed;\n\n\nbase.random.geometric.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.geometric.seedLength;\n\n\nbase.random.geometric.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.geometric( 0.3 )\n    <number>\n    > r = base.random.geometric( 0.3 )\n    <number>\n    > r = base.random.geometric( 0.3 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.geometric.state\n    <Uint32Array>\n\n    > r = base.random.geometric( 0.3 )\n    <number>\n    > r = base.random.geometric( 0.3 )\n    <number>\n\n    // Set the state:\n    > base.random.geometric.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.geometric( 0.3 )\n    <number>\n    > r = base.random.geometric( 0.3 )\n    <number>\n\n\nbase.random.geometric.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.geometric.stateLength;\n\n\nbase.random.geometric.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.geometric.byteLength;\n\n\nbase.random.geometric.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.geometric.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.geometric, random.iterators.geometric, random.streams.geometric\n","base.random.geometric.factory":"\nbase.random.geometric.factory( [p, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a geometric distribution.\n\n    If provided `p`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `p`, the returned PRNG requires that `p` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.geometric.factory();\n    > var r = rand( 0.3 );\n    > r = rand( 0.59 );\n\n    // Provide `p`:\n    > rand = base.random.geometric.factory( 0.3 );\n    > r = rand();\n    > r = rand();","base.random.geometric.NAME":"\nbase.random.geometric.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.geometric.NAME\n    'geometric'","base.random.geometric.PRNG":"\nbase.random.geometric.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.geometric.PRNG;","base.random.geometric.seed":"\nbase.random.geometric.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.geometric.seed;","base.random.geometric.seedLength":"\nbase.random.geometric.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.geometric.seedLength;","base.random.geometric.state":"\nbase.random.geometric.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.geometric( 0.3 )\n    <number>\n    > r = base.random.geometric( 0.3 )\n    <number>\n    > r = base.random.geometric( 0.3 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.geometric.state\n    <Uint32Array>\n\n    > r = base.random.geometric( 0.3 )\n    <number>\n    > r = base.random.geometric( 0.3 )\n    <number>\n\n    // Set the state:\n    > base.random.geometric.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.geometric( 0.3 )\n    <number>\n    > r = base.random.geometric( 0.3 )\n    <number>","base.random.geometric.stateLength":"\nbase.random.geometric.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.geometric.stateLength;","base.random.geometric.byteLength":"\nbase.random.geometric.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.geometric.byteLength;","base.random.geometric.toJSON":"\nbase.random.geometric.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.geometric.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.geometric, random.iterators.geometric, random.streams.geometric","base.random.gumbel":"\nbase.random.gumbel( μ, β )\n    Returns a pseudorandom number drawn from a Gumbel distribution.\n\n    If `μ` or `β` is `NaN` or `β <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.gumbel( 2.0, 5.0 );\n\n\nbase.random.gumbel.factory( [μ, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Gumbel distribution.\n\n    If provided `μ` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `β`, the returned PRNG requires that both `μ` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.gumbel.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `β`:\n    > rand = base.random.gumbel.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.gumbel.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.gumbel.NAME\n    'gumbel'\n\n\nbase.random.gumbel.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.gumbel.PRNG;\n\n\nbase.random.gumbel.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.gumbel.seed;\n\n\nbase.random.gumbel.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.gumbel.seedLength;\n\n\nbase.random.gumbel.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.gumbel.state\n    <Uint32Array>\n\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.gumbel.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n\n\nbase.random.gumbel.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.gumbel.stateLength;\n\n\nbase.random.gumbel.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.gumbel.byteLength;\n\n\nbase.random.gumbel.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.gumbel.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.gumbel, random.iterators.gumbel, random.streams.gumbel\n","base.random.gumbel.factory":"\nbase.random.gumbel.factory( [μ, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Gumbel distribution.\n\n    If provided `μ` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `β`, the returned PRNG requires that both `μ` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.gumbel.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `β`:\n    > rand = base.random.gumbel.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.gumbel.NAME":"\nbase.random.gumbel.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.gumbel.NAME\n    'gumbel'","base.random.gumbel.PRNG":"\nbase.random.gumbel.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.gumbel.PRNG;","base.random.gumbel.seed":"\nbase.random.gumbel.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.gumbel.seed;","base.random.gumbel.seedLength":"\nbase.random.gumbel.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.gumbel.seedLength;","base.random.gumbel.state":"\nbase.random.gumbel.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.gumbel.state\n    <Uint32Array>\n\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.gumbel.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>\n    > r = base.random.gumbel( 2.0, 5.0 )\n    <number>","base.random.gumbel.stateLength":"\nbase.random.gumbel.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.gumbel.stateLength;","base.random.gumbel.byteLength":"\nbase.random.gumbel.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.gumbel.byteLength;","base.random.gumbel.toJSON":"\nbase.random.gumbel.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.gumbel.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.gumbel, random.iterators.gumbel, random.streams.gumbel","base.random.hypergeometric":"\nbase.random.hypergeometric( N, K, n )\n    Returns a pseudorandom number drawn from a hypergeometric distribution.\n\n    `N`, `K`, and `n` must all be nonnegative integers; otherwise, the function\n    returns `NaN`.\n\n    If `n > N` or `K > N`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.hypergeometric( 20, 10, 7 );\n\n\nbase.random.hypergeometric.factory( [N, K, n, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a hypergeometric distribution.\n\n    If provided `N`, `K`, and `n`, the returned PRNG returns random variates\n    drawn from the specified distribution.\n\n    If not provided `N`, `K`, and `n`, the returned PRNG requires that `N`, `K`,\n    and `n` be provided at each invocation.\n\n    Parameters\n    ----------\n    N: integer (optional)\n        Population size.\n\n    K: integer (optional)\n        Subpopulation size.\n\n    n: integer (optional)\n        Number of draws.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.hypergeometric.factory();\n    > var r = rand( 20, 10, 15 );\n    > r = rand( 20, 10, 7 );\n\n    // Provide `N`, `K`, and `n`:\n    > rand = base.random.hypergeometric.factory( 20, 10, 15 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.hypergeometric.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.hypergeometric.NAME\n    'hypergeometric'\n\n\nbase.random.hypergeometric.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.hypergeometric.PRNG;\n\n\nbase.random.hypergeometric.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.hypergeometric.seed;\n\n\nbase.random.hypergeometric.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.hypergeometric.seedLength;\n\n\nbase.random.hypergeometric.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.hypergeometric.state\n    <Uint32Array>\n\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n\n    // Set the state:\n    > base.random.hypergeometric.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n\n\nbase.random.hypergeometric.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.hypergeometric.stateLength;\n\n\nbase.random.hypergeometric.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.hypergeometric.byteLength;\n\n\nbase.random.hypergeometric.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.hypergeometric.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.hypergeometric, random.iterators.hypergeometric, random.streams.hypergeometric\n","base.random.hypergeometric.factory":"\nbase.random.hypergeometric.factory( [N, K, n, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a hypergeometric distribution.\n\n    If provided `N`, `K`, and `n`, the returned PRNG returns random variates\n    drawn from the specified distribution.\n\n    If not provided `N`, `K`, and `n`, the returned PRNG requires that `N`, `K`,\n    and `n` be provided at each invocation.\n\n    Parameters\n    ----------\n    N: integer (optional)\n        Population size.\n\n    K: integer (optional)\n        Subpopulation size.\n\n    n: integer (optional)\n        Number of draws.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.hypergeometric.factory();\n    > var r = rand( 20, 10, 15 );\n    > r = rand( 20, 10, 7 );\n\n    // Provide `N`, `K`, and `n`:\n    > rand = base.random.hypergeometric.factory( 20, 10, 15 );\n    > r = rand();\n    > r = rand();","base.random.hypergeometric.NAME":"\nbase.random.hypergeometric.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.hypergeometric.NAME\n    'hypergeometric'","base.random.hypergeometric.PRNG":"\nbase.random.hypergeometric.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.hypergeometric.PRNG;","base.random.hypergeometric.seed":"\nbase.random.hypergeometric.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.hypergeometric.seed;","base.random.hypergeometric.seedLength":"\nbase.random.hypergeometric.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.hypergeometric.seedLength;","base.random.hypergeometric.state":"\nbase.random.hypergeometric.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.hypergeometric.state\n    <Uint32Array>\n\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n\n    // Set the state:\n    > base.random.hypergeometric.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>\n    > r = base.random.hypergeometric( 20, 10, 15 )\n    <number>","base.random.hypergeometric.stateLength":"\nbase.random.hypergeometric.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.hypergeometric.stateLength;","base.random.hypergeometric.byteLength":"\nbase.random.hypergeometric.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.hypergeometric.byteLength;","base.random.hypergeometric.toJSON":"\nbase.random.hypergeometric.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.hypergeometric.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.hypergeometric, random.iterators.hypergeometric, random.streams.hypergeometric","base.random.improvedZiggurat":"\nbase.random.improvedZiggurat()\n    Returns a pseudorandom number drawn from a standard normal distribution.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.improvedZiggurat();\n\n\nbase.random.improvedZiggurat.factory( [options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a standard normal distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.improvedZiggurat.factory();\n    > r = rand();\n    > r = rand();\n\n\nbase.random.improvedZiggurat.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.improvedZiggurat.NAME\n    'improved-ziggurat'\n\n\nbase.random.improvedZiggurat.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.improvedZiggurat.PRNG;\n\n\nbase.random.improvedZiggurat.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.improvedZiggurat.seed;\n\n\nbase.random.improvedZiggurat.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.improvedZiggurat.seedLength;\n\n\nbase.random.improvedZiggurat.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.improvedZiggurat()\n    <number>\n    > r = base.random.improvedZiggurat()\n    <number>\n    > r = base.random.improvedZiggurat()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.improvedZiggurat.state\n    <Uint32Array>\n\n    > r = base.random.improvedZiggurat()\n    <number>\n    > r = base.random.improvedZiggurat()\n    <number>\n\n    // Set the state:\n    > base.random.improvedZiggurat.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.improvedZiggurat()\n    <number>\n    > r = base.random.improvedZiggurat()\n    <number>\n\n\nbase.random.improvedZiggurat.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.improvedZiggurat.stateLength;\n\n\nbase.random.improvedZiggurat.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.improvedZiggurat.byteLength;\n\n\nbase.random.improvedZiggurat.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.improvedZiggurat.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.iterators.improvedZiggurat, random.streams.improvedZiggurat\n","base.random.improvedZiggurat.factory":"\nbase.random.improvedZiggurat.factory( [options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a standard normal distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.improvedZiggurat.factory();\n    > r = rand();\n    > r = rand();","base.random.improvedZiggurat.NAME":"\nbase.random.improvedZiggurat.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.improvedZiggurat.NAME\n    'improved-ziggurat'","base.random.improvedZiggurat.PRNG":"\nbase.random.improvedZiggurat.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.improvedZiggurat.PRNG;","base.random.improvedZiggurat.seed":"\nbase.random.improvedZiggurat.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.improvedZiggurat.seed;","base.random.improvedZiggurat.seedLength":"\nbase.random.improvedZiggurat.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.improvedZiggurat.seedLength;","base.random.improvedZiggurat.state":"\nbase.random.improvedZiggurat.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.improvedZiggurat()\n    <number>\n    > r = base.random.improvedZiggurat()\n    <number>\n    > r = base.random.improvedZiggurat()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.improvedZiggurat.state\n    <Uint32Array>\n\n    > r = base.random.improvedZiggurat()\n    <number>\n    > r = base.random.improvedZiggurat()\n    <number>\n\n    // Set the state:\n    > base.random.improvedZiggurat.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.improvedZiggurat()\n    <number>\n    > r = base.random.improvedZiggurat()\n    <number>","base.random.improvedZiggurat.stateLength":"\nbase.random.improvedZiggurat.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.improvedZiggurat.stateLength;","base.random.improvedZiggurat.byteLength":"\nbase.random.improvedZiggurat.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.improvedZiggurat.byteLength;","base.random.improvedZiggurat.toJSON":"\nbase.random.improvedZiggurat.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.improvedZiggurat.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.iterators.improvedZiggurat, random.streams.improvedZiggurat","base.random.invgamma":"\nbase.random.invgamma( α, β )\n    Returns a pseudorandom number drawn from an inverse gamma distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.invgamma( 2.0, 5.0 );\n\n\nbase.random.invgamma.factory( [α, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an inverse gamma distribution.\n\n    If provided `α` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `α` and `β`, the returned PRNG requires that both `α` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.invgamma.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 3.14, 2.25 );\n\n    // Provide `α` and `β`:\n    > rand = base.random.invgamma.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.invgamma.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.invgamma.NAME\n    'invgamma'\n\n\nbase.random.invgamma.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.invgamma.PRNG;\n\n\nbase.random.invgamma.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.invgamma.seed;\n\n\nbase.random.invgamma.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.invgamma.seedLength;\n\n\nbase.random.invgamma.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.invgamma.state\n    <Uint32Array>\n\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.invgamma.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n\n\nbase.random.invgamma.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.invgamma.stateLength;\n\n\nbase.random.invgamma.byteLength\n    Size of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.invgamma.byteLength;\n\n\nbase.random.invgamma.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.invgamma.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.invgamma, random.iterators.invgamma, random.streams.invgamma\n","base.random.invgamma.factory":"\nbase.random.invgamma.factory( [α, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an inverse gamma distribution.\n\n    If provided `α` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `α` and `β`, the returned PRNG requires that both `α` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.invgamma.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 3.14, 2.25 );\n\n    // Provide `α` and `β`:\n    > rand = base.random.invgamma.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.invgamma.NAME":"\nbase.random.invgamma.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.invgamma.NAME\n    'invgamma'","base.random.invgamma.PRNG":"\nbase.random.invgamma.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.invgamma.PRNG;","base.random.invgamma.seed":"\nbase.random.invgamma.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.invgamma.seed;","base.random.invgamma.seedLength":"\nbase.random.invgamma.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.invgamma.seedLength;","base.random.invgamma.state":"\nbase.random.invgamma.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.invgamma.state\n    <Uint32Array>\n\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.invgamma.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>\n    > r = base.random.invgamma( 2.0, 5.0 )\n    <number>","base.random.invgamma.stateLength":"\nbase.random.invgamma.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.invgamma.stateLength;","base.random.invgamma.byteLength":"\nbase.random.invgamma.byteLength\n    Size of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.invgamma.byteLength;","base.random.invgamma.toJSON":"\nbase.random.invgamma.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.invgamma.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.invgamma, random.iterators.invgamma, random.streams.invgamma","base.random.kumaraswamy":"\nbase.random.kumaraswamy( a, b )\n    Returns a pseudorandom number drawn from Kumaraswamy's double bounded\n    distribution.\n\n    If `a <= 0` or `b <= 0`, the function returns `NaN`.\n\n    If `a` or `b` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.kumaraswamy( 2.0, 5.0 );\n\n\nbase.random.kumaraswamy.factory( [a, b, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from Kumaraswamy's double bounded distribution.\n\n    If provided `a` and `b`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `a` and `b`, the returned PRNG requires that both `a` and\n    `b` be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        First shape parameter.\n\n    b: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.kumaraswamy.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `a` and `b`:\n    > rand = base.random.kumaraswamy.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.kumaraswamy.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.kumaraswamy.NAME\n    'kumaraswamy'\n\n\nbase.random.kumaraswamy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.kumaraswamy.PRNG;\n\n\nbase.random.kumaraswamy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.kumaraswamy.seed;\n\n\nbase.random.kumaraswamy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.kumaraswamy.seedLength;\n\n\nbase.random.kumaraswamy.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.kumaraswamy.state\n    <Uint32Array>\n\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n\n    // Set the state:\n    > base.random.kumaraswamy.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n\n\nbase.random.kumaraswamy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.kumaraswamy.stateLength;\n\n\nbase.random.kumaraswamy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.kumaraswamy.byteLength;\n\n\nbase.random.kumaraswamy.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.kumaraswamy.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.kumaraswamy, random.iterators.kumaraswamy, random.streams.kumaraswamy\n","base.random.kumaraswamy.factory":"\nbase.random.kumaraswamy.factory( [a, b, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from Kumaraswamy's double bounded distribution.\n\n    If provided `a` and `b`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `a` and `b`, the returned PRNG requires that both `a` and\n    `b` be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        First shape parameter.\n\n    b: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.kumaraswamy.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `a` and `b`:\n    > rand = base.random.kumaraswamy.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.kumaraswamy.NAME":"\nbase.random.kumaraswamy.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.kumaraswamy.NAME\n    'kumaraswamy'","base.random.kumaraswamy.PRNG":"\nbase.random.kumaraswamy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.kumaraswamy.PRNG;","base.random.kumaraswamy.seed":"\nbase.random.kumaraswamy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.kumaraswamy.seed;","base.random.kumaraswamy.seedLength":"\nbase.random.kumaraswamy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.kumaraswamy.seedLength;","base.random.kumaraswamy.state":"\nbase.random.kumaraswamy.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.kumaraswamy.state\n    <Uint32Array>\n\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n\n    // Set the state:\n    > base.random.kumaraswamy.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>\n    > r = base.random.kumaraswamy( 1.5, 1.5 )\n    <number>","base.random.kumaraswamy.stateLength":"\nbase.random.kumaraswamy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.kumaraswamy.stateLength;","base.random.kumaraswamy.byteLength":"\nbase.random.kumaraswamy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.kumaraswamy.byteLength;","base.random.kumaraswamy.toJSON":"\nbase.random.kumaraswamy.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.kumaraswamy.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.kumaraswamy, random.iterators.kumaraswamy, random.streams.kumaraswamy","base.random.laplace":"\nbase.random.laplace( μ, b )\n    Returns a pseudorandom number drawn from a Laplace distribution.\n\n    If `μ` or `b` is `NaN` or `b <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    b: number\n        Scale parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.laplace( 2.0, 5.0 );\n\n\nbase.random.laplace.factory( [μ, b, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Laplace distribution.\n\n    If provided `μ` and `b`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `b`, the returned PRNG requires that both `μ` and\n    `b` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    b: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.laplace.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `b`:\n    > rand = base.random.laplace.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.laplace.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.laplace.NAME\n    'laplace'\n\n\nbase.random.laplace.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.laplace.PRNG;\n\n\nbase.random.laplace.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.laplace.seed;\n\n\nbase.random.laplace.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.laplace.seedLength;\n\n\nbase.random.laplace.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.laplace( 2.0, 5.0 )\n    <number>\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.laplace.state\n    <Uint32Array>\n\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.laplace.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>\n\n\nbase.random.laplace.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.laplace.stateLength;\n\n\nbase.random.laplace.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.laplace.byteLength;\n\n\nbase.random.laplace.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.laplace.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.laplace, random.iterators.laplace, random.streams.laplace\n","base.random.laplace.factory":"\nbase.random.laplace.factory( [μ, b, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Laplace distribution.\n\n    If provided `μ` and `b`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `b`, the returned PRNG requires that both `μ` and\n    `b` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    b: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.laplace.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `b`:\n    > rand = base.random.laplace.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.laplace.NAME":"\nbase.random.laplace.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.laplace.NAME\n    'laplace'","base.random.laplace.PRNG":"\nbase.random.laplace.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.laplace.PRNG;","base.random.laplace.seed":"\nbase.random.laplace.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.laplace.seed;","base.random.laplace.seedLength":"\nbase.random.laplace.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.laplace.seedLength;","base.random.laplace.state":"\nbase.random.laplace.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.laplace( 2.0, 5.0 )\n    <number>\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.laplace.state\n    <Uint32Array>\n\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.laplace.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>\n    > r = base.random.laplace( 2.0, 5.0 )\n    <number>","base.random.laplace.stateLength":"\nbase.random.laplace.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.laplace.stateLength;","base.random.laplace.byteLength":"\nbase.random.laplace.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.laplace.byteLength;","base.random.laplace.toJSON":"\nbase.random.laplace.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.laplace.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.laplace, random.iterators.laplace, random.streams.laplace","base.random.levy":"\nbase.random.levy( μ, c )\n    Returns a pseudorandom number drawn from a Lévy distribution.\n\n    If `μ` or `c` is `NaN` or `c <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    c: number\n        Scale parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.levy( 2.0, 5.0 );\n\n\nbase.random.levy.factory( [μ, c, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Lévy distribution.\n\n    If provided `μ` and `c`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `c`, the returned PRNG requires that both `μ` and\n    `c` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    c: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.levy.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `b`:\n    > rand = base.random.levy.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.levy.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.levy.NAME\n    'levy'\n\n\nbase.random.levy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.levy.PRNG;\n\n\nbase.random.levy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.levy.seed;\n\n\nbase.random.levy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.levy.seedLength;\n\n\nbase.random.levy.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.levy( 2.0, 5.0 )\n    <number>\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.levy.state\n    <Uint32Array>\n\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.levy.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>\n\n\nbase.random.levy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.levy.stateLength;\n\n\nbase.random.levy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.levy.byteLength;\n\n\nbase.random.levy.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.levy.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.levy, random.iterators.levy, random.streams.levy\n","base.random.levy.factory":"\nbase.random.levy.factory( [μ, c, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Lévy distribution.\n\n    If provided `μ` and `c`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `c`, the returned PRNG requires that both `μ` and\n    `c` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    c: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.levy.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `b`:\n    > rand = base.random.levy.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.levy.NAME":"\nbase.random.levy.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.levy.NAME\n    'levy'","base.random.levy.PRNG":"\nbase.random.levy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.levy.PRNG;","base.random.levy.seed":"\nbase.random.levy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.levy.seed;","base.random.levy.seedLength":"\nbase.random.levy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.levy.seedLength;","base.random.levy.state":"\nbase.random.levy.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.levy( 2.0, 5.0 )\n    <number>\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.levy.state\n    <Uint32Array>\n\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.levy.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>\n    > r = base.random.levy( 2.0, 5.0 )\n    <number>","base.random.levy.stateLength":"\nbase.random.levy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.levy.stateLength;","base.random.levy.byteLength":"\nbase.random.levy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.levy.byteLength;","base.random.levy.toJSON":"\nbase.random.levy.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.levy.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.levy, random.iterators.levy, random.streams.levy","base.random.logistic":"\nbase.random.logistic( μ, s )\n    Returns a pseudorandom number drawn from a logistic distribution.\n\n    If `μ` or `s` is `NaN` or `s <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    s: number\n        Scale parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.logistic( 2.0, 5.0 );\n\n\nbase.random.logistic.factory( [μ, s, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a logistic distribution.\n\n    If provided `μ` and `s`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n    `s` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.logistic.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `s`:\n    > rand = base.random.logistic.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.logistic.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.logistic.NAME\n    'logistic'\n\n\nbase.random.logistic.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.logistic.PRNG;\n\n\nbase.random.logistic.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.logistic.seed;\n\n\nbase.random.logistic.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.logistic.seedLength;\n\n\nbase.random.logistic.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.logistic( 2.0, 5.0 )\n    <number>\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.logistic.state\n    <Uint32Array>\n\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.logistic.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>\n\n\nbase.random.logistic.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.logistic.stateLength;\n\n\nbase.random.logistic.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.logistic.byteLength;\n\n\nbase.random.logistic.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.logistic.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.logistic, random.iterators.logistic, random.streams.logistic\n","base.random.logistic.factory":"\nbase.random.logistic.factory( [μ, s, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a logistic distribution.\n\n    If provided `μ` and `s`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `s`, the returned PRNG requires that both `μ` and\n    `s` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.logistic.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `s`:\n    > rand = base.random.logistic.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.logistic.NAME":"\nbase.random.logistic.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.logistic.NAME\n    'logistic'","base.random.logistic.PRNG":"\nbase.random.logistic.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.logistic.PRNG;","base.random.logistic.seed":"\nbase.random.logistic.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.logistic.seed;","base.random.logistic.seedLength":"\nbase.random.logistic.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.logistic.seedLength;","base.random.logistic.state":"\nbase.random.logistic.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.logistic( 2.0, 5.0 )\n    <number>\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.logistic.state\n    <Uint32Array>\n\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.logistic.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>\n    > r = base.random.logistic( 2.0, 5.0 )\n    <number>","base.random.logistic.stateLength":"\nbase.random.logistic.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.logistic.stateLength;","base.random.logistic.byteLength":"\nbase.random.logistic.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.logistic.byteLength;","base.random.logistic.toJSON":"\nbase.random.logistic.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.logistic.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.logistic, random.iterators.logistic, random.streams.logistic","base.random.lognormal":"\nbase.random.lognormal( μ, σ )\n    Returns a pseudorandom number drawn from a lognormal distribution.\n\n    If `μ` or `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.lognormal( 2.0, 5.0 );\n\n\nbase.random.lognormal.factory( [μ, σ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a lognormal distribution.\n\n    If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n    `σ` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter.\n\n    σ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.lognormal.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `σ`:\n    > rand = base.random.lognormal.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.lognormal.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.lognormal.NAME\n    'lognormal'\n\n\nbase.random.lognormal.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.lognormal.PRNG;\n\n\nbase.random.lognormal.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.lognormal.seed;\n\n\nbase.random.lognormal.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.lognormal.seedLength;\n\n\nbase.random.lognormal.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.lognormal.state\n    <Uint32Array>\n\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.lognormal.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n\n\nbase.random.lognormal.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.lognormal.stateLength;\n\n\nbase.random.lognormal.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.lognormal.byteLength;\n\n\nbase.random.lognormal.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.lognormal.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.lognormal, random.iterators.lognormal, random.streams.lognormal\n","base.random.lognormal.factory":"\nbase.random.lognormal.factory( [μ, σ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a lognormal distribution.\n\n    If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n    `σ` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter.\n\n    σ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.lognormal.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `σ`:\n    > rand = base.random.lognormal.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.lognormal.NAME":"\nbase.random.lognormal.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.lognormal.NAME\n    'lognormal'","base.random.lognormal.PRNG":"\nbase.random.lognormal.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.lognormal.PRNG;","base.random.lognormal.seed":"\nbase.random.lognormal.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.lognormal.seed;","base.random.lognormal.seedLength":"\nbase.random.lognormal.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.lognormal.seedLength;","base.random.lognormal.state":"\nbase.random.lognormal.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.lognormal.state\n    <Uint32Array>\n\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.lognormal.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>\n    > r = base.random.lognormal( 2.0, 5.0 )\n    <number>","base.random.lognormal.stateLength":"\nbase.random.lognormal.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.lognormal.stateLength;","base.random.lognormal.byteLength":"\nbase.random.lognormal.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.lognormal.byteLength;","base.random.lognormal.toJSON":"\nbase.random.lognormal.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.lognormal.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.lognormal, random.iterators.lognormal, random.streams.lognormal","base.random.minstd":"\nbase.random.minstd()\n    Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n\n    This pseudorandom number generator (PRNG) is a linear congruential\n    pseudorandom number generator (LCG) based on Park and Miller.\n\n    The generator has a period of approximately `2.1e9`.\n\n    An LCG is fast and uses little memory. On the other hand, because the\n    generator is a simple LCG, the generator has recognized shortcomings. By\n    today's PRNG standards, the generator's period is relatively short. More\n    importantly, the \"randomness quality\" of the generator's output is lacking.\n    These defects make the generator unsuitable, for example, in Monte Carlo\n    simulations and in cryptographic applications.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.minstd();\n\n\nbase.random.minstd.normalized()\n    Returns a pseudorandom number on the interval `[0,1)`.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.minstd.normalized();\n\n\nbase.random.minstd.factory( [options] )\n    Returns a linear congruential pseudorandom number generator (LCG).\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.minstd.factory();\n    > r = rand();\n    > r = rand();\n\n    // Provide a seed:\n    > rand = base.random.minstd.factory( { 'seed': 1234 } );\n    > r = rand()\n    20739838\n\n\nbase.random.minstd.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.minstd.NAME\n    'minstd'\n\n\nbase.random.minstd.MIN\n    Minimum possible value.\n\n    Examples\n    --------\n    > var v = base.random.minstd.MIN\n    1\n\n\nbase.random.minstd.MAX\n    Maximum possible value.\n\n    Examples\n    --------\n    > var v = base.random.minstd.MAX\n    2147483646\n\n\nbase.random.minstd.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.minstd.seed;\n\n\nbase.random.minstd.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.minstd.seedLength;\n\n\nbase.random.minstd.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.minstd()\n    <number>\n    > r = base.random.minstd()\n    <number>\n    > r = base.random.minstd()\n    <number>\n\n    // Get the current state:\n    > var state = base.random.minstd.state\n    <Int32Array>\n\n    > r = base.random.minstd()\n    <number>\n    > r = base.random.minstd()\n    <number>\n\n    // Set the state:\n    > base.random.minstd.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.minstd()\n    <number>\n    > r = base.random.minstd()\n    <number>\n\n\nbase.random.minstd.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.minstd.stateLength;\n\n\nbase.random.minstd.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.minstd.byteLength;\n\n\nbase.random.minstd.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.minstd.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.minstd, random.iterators.minstd, random.streams.minstd, base.random.minstdShuffle, base.random.mt19937, base.random.randi\n","base.random.minstd.normalized":"\nbase.random.minstd.normalized()\n    Returns a pseudorandom number on the interval `[0,1)`.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.minstd.normalized();","base.random.minstd.factory":"\nbase.random.minstd.factory( [options] )\n    Returns a linear congruential pseudorandom number generator (LCG).\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.minstd.factory();\n    > r = rand();\n    > r = rand();\n\n    // Provide a seed:\n    > rand = base.random.minstd.factory( { 'seed': 1234 } );\n    > r = rand()\n    20739838","base.random.minstd.NAME":"\nbase.random.minstd.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.minstd.NAME\n    'minstd'","base.random.minstd.MIN":"\nbase.random.minstd.MIN\n    Minimum possible value.\n\n    Examples\n    --------\n    > var v = base.random.minstd.MIN\n    1","base.random.minstd.MAX":"\nbase.random.minstd.MAX\n    Maximum possible value.\n\n    Examples\n    --------\n    > var v = base.random.minstd.MAX\n    2147483646","base.random.minstd.seed":"\nbase.random.minstd.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.minstd.seed;","base.random.minstd.seedLength":"\nbase.random.minstd.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.minstd.seedLength;","base.random.minstd.state":"\nbase.random.minstd.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.minstd()\n    <number>\n    > r = base.random.minstd()\n    <number>\n    > r = base.random.minstd()\n    <number>\n\n    // Get the current state:\n    > var state = base.random.minstd.state\n    <Int32Array>\n\n    > r = base.random.minstd()\n    <number>\n    > r = base.random.minstd()\n    <number>\n\n    // Set the state:\n    > base.random.minstd.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.minstd()\n    <number>\n    > r = base.random.minstd()\n    <number>","base.random.minstd.stateLength":"\nbase.random.minstd.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.minstd.stateLength;","base.random.minstd.byteLength":"\nbase.random.minstd.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.minstd.byteLength;","base.random.minstd.toJSON":"\nbase.random.minstd.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.minstd.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.minstd, random.iterators.minstd, random.streams.minstd, base.random.minstdShuffle, base.random.mt19937, base.random.randi","base.random.minstdShuffle":"\nbase.random.minstdShuffle()\n    Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n\n    This pseudorandom number generator (PRNG) is a linear congruential\n    pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n    Durham algorithm. The shuffle step considerably strengthens the \"randomness\n    quality\" of a simple LCG's output.\n\n    The generator has a period of approximately `2.1e9`.\n\n    An LCG is fast and uses little memory. On the other hand, because the\n    generator is a simple LCG, the generator has recognized shortcomings. By\n    today's PRNG standards, the generator's period is relatively short. In\n    general, this generator is unsuitable for Monte Carlo simulations and\n    cryptographic applications.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.minstdShuffle();\n\n\nbase.random.minstdShuffle.normalized()\n    Returns a pseudorandom number on the interval `[0,1)`.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.minstdShuffle.normalized();\n\n\nbase.random.minstdShuffle.factory( [options] )\n    Returns a linear congruential pseudorandom number generator (LCG) whose\n    output is shuffled.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.minstdShuffle.factory();\n    > r = rand();\n    > r = rand();\n\n    // Provide a seed:\n    > rand = base.random.minstdShuffle.factory( { 'seed': 1234 } );\n    > r = rand()\n    1421600654\n\n\nbase.random.minstdShuffle.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.minstdShuffle.NAME\n    'minstd-shuffle'\n\n\nbase.random.minstdShuffle.MIN\n    Minimum possible value.\n\n    Examples\n    --------\n    > var v = base.random.minstdShuffle.MIN\n    1\n\n\nbase.random.minstdShuffle.MAX\n    Maximum possible value.\n\n    Examples\n    --------\n    > var v = base.random.minstdShuffle.MAX\n    2147483646\n\n\nbase.random.minstdShuffle.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.minstdShuffle.seed;\n\n\nbase.random.minstdShuffle.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.minstdShuffle.seedLength;\n\n\nbase.random.minstdShuffle.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.minstdShuffle()\n    <number>\n    > r = base.random.minstdShuffle()\n    <number>\n    > r = base.random.minstdShuffle()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.minstdShuffle.state\n    <Int32Array>\n\n    > r = base.random.minstdShuffle()\n    <number>\n    > r = base.random.minstdShuffle()\n    <number>\n\n    // Set the state:\n    > base.random.minstdShuffle.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.minstdShuffle()\n    <number>\n    > r = base.random.minstdShuffle()\n    <number>\n\n\nbase.random.minstdShuffle.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.minstdShuffle.stateLength;\n\n\nbase.random.minstdShuffle.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.minstdShuffle.byteLength;\n\n\nbase.random.minstdShuffle.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.minstdShuffle.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstdShuffle, base.random.minstd, base.random.mt19937, base.random.randi\n","base.random.minstdShuffle.normalized":"\nbase.random.minstdShuffle.normalized()\n    Returns a pseudorandom number on the interval `[0,1)`.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.minstdShuffle.normalized();","base.random.minstdShuffle.factory":"\nbase.random.minstdShuffle.factory( [options] )\n    Returns a linear congruential pseudorandom number generator (LCG) whose\n    output is shuffled.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.minstdShuffle.factory();\n    > r = rand();\n    > r = rand();\n\n    // Provide a seed:\n    > rand = base.random.minstdShuffle.factory( { 'seed': 1234 } );\n    > r = rand()\n    1421600654","base.random.minstdShuffle.NAME":"\nbase.random.minstdShuffle.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.minstdShuffle.NAME\n    'minstd-shuffle'","base.random.minstdShuffle.MIN":"\nbase.random.minstdShuffle.MIN\n    Minimum possible value.\n\n    Examples\n    --------\n    > var v = base.random.minstdShuffle.MIN\n    1","base.random.minstdShuffle.MAX":"\nbase.random.minstdShuffle.MAX\n    Maximum possible value.\n\n    Examples\n    --------\n    > var v = base.random.minstdShuffle.MAX\n    2147483646","base.random.minstdShuffle.seed":"\nbase.random.minstdShuffle.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.minstdShuffle.seed;","base.random.minstdShuffle.seedLength":"\nbase.random.minstdShuffle.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.minstdShuffle.seedLength;","base.random.minstdShuffle.state":"\nbase.random.minstdShuffle.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.minstdShuffle()\n    <number>\n    > r = base.random.minstdShuffle()\n    <number>\n    > r = base.random.minstdShuffle()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.minstdShuffle.state\n    <Int32Array>\n\n    > r = base.random.minstdShuffle()\n    <number>\n    > r = base.random.minstdShuffle()\n    <number>\n\n    // Set the state:\n    > base.random.minstdShuffle.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.minstdShuffle()\n    <number>\n    > r = base.random.minstdShuffle()\n    <number>","base.random.minstdShuffle.stateLength":"\nbase.random.minstdShuffle.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.minstdShuffle.stateLength;","base.random.minstdShuffle.byteLength":"\nbase.random.minstdShuffle.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.minstdShuffle.byteLength;","base.random.minstdShuffle.toJSON":"\nbase.random.minstdShuffle.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.minstdShuffle.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstdShuffle, base.random.minstd, base.random.mt19937, base.random.randi","base.random.mt19937":"\nbase.random.mt19937()\n    Returns a pseudorandom integer on the interval `[0, 4294967295]`.\n\n    This pseudorandom number generator (PRNG) is a 32-bit Mersenne Twister\n    pseudorandom number generator.\n\n    The PRNG is *not* a cryptographically secure PRNG.\n\n    The PRNG has a period of 2^19937 - 1.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.mt19937();\n\n\nbase.random.mt19937.normalized()\n    Returns a pseudorandom number on the interval `[0,1)` with 53-bit precision.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.mt19937.normalized();\n\n\nbase.random.mt19937.factory( [options] )\n    Returns a 32-bit Mersenne Twister pseudorandom number generator.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.mt19937.factory();\n    > r = rand();\n    > r = rand();\n\n    // Provide a seed:\n    > rand = base.random.mt19937.factory( { 'seed': 1234 } );\n    > r = rand()\n    822569775\n\n\nbase.random.mt19937.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.mt19937.NAME\n    'mt19937'\n\n\nbase.random.mt19937.MIN\n    Minimum possible value.\n\n    Examples\n    --------\n    > var v = base.random.mt19937.MIN\n    0\n\n\nbase.random.mt19937.MAX\n    Maximum possible value.\n\n    Examples\n    --------\n    > var v = base.random.mt19937.MAX\n    4294967295\n\n\nbase.random.mt19937.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.mt19937.seed;\n\n\nbase.random.mt19937.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.mt19937.seedLength;\n\n\nbase.random.mt19937.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.mt19937()\n    <number>\n    > r = base.random.mt19937()\n    <number>\n    > r = base.random.mt19937()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.mt19937.state\n    <Uint32Array>\n\n    > r = base.random.mt19937()\n    <number>\n    > r = base.random.mt19937()\n    <number>\n\n    // Set the state:\n    > base.random.mt19937.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.mt19937()\n    <number>\n    > r = base.random.mt19937()\n    <number>\n\n\nbase.random.mt19937.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.mt19937.stateLength;\n\n\nbase.random.mt19937.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.mt19937.byteLength;\n\n\nbase.random.mt19937.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.mt19937.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.mt19937, random.iterators.mt19937, random.streams.mt19937, base.random.minstd, base.random.randi\n","base.random.mt19937.normalized":"\nbase.random.mt19937.normalized()\n    Returns a pseudorandom number on the interval `[0,1)` with 53-bit precision.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.mt19937.normalized();","base.random.mt19937.factory":"\nbase.random.mt19937.factory( [options] )\n    Returns a 32-bit Mersenne Twister pseudorandom number generator.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.mt19937.factory();\n    > r = rand();\n    > r = rand();\n\n    // Provide a seed:\n    > rand = base.random.mt19937.factory( { 'seed': 1234 } );\n    > r = rand()\n    822569775","base.random.mt19937.NAME":"\nbase.random.mt19937.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.mt19937.NAME\n    'mt19937'","base.random.mt19937.MIN":"\nbase.random.mt19937.MIN\n    Minimum possible value.\n\n    Examples\n    --------\n    > var v = base.random.mt19937.MIN\n    0","base.random.mt19937.MAX":"\nbase.random.mt19937.MAX\n    Maximum possible value.\n\n    Examples\n    --------\n    > var v = base.random.mt19937.MAX\n    4294967295","base.random.mt19937.seed":"\nbase.random.mt19937.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.mt19937.seed;","base.random.mt19937.seedLength":"\nbase.random.mt19937.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.mt19937.seedLength;","base.random.mt19937.state":"\nbase.random.mt19937.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.mt19937()\n    <number>\n    > r = base.random.mt19937()\n    <number>\n    > r = base.random.mt19937()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.mt19937.state\n    <Uint32Array>\n\n    > r = base.random.mt19937()\n    <number>\n    > r = base.random.mt19937()\n    <number>\n\n    // Set the state:\n    > base.random.mt19937.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.mt19937()\n    <number>\n    > r = base.random.mt19937()\n    <number>","base.random.mt19937.stateLength":"\nbase.random.mt19937.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.mt19937.stateLength;","base.random.mt19937.byteLength":"\nbase.random.mt19937.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.mt19937.byteLength;","base.random.mt19937.toJSON":"\nbase.random.mt19937.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.mt19937.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.mt19937, random.iterators.mt19937, random.streams.mt19937, base.random.minstd, base.random.randi","base.random.negativeBinomial":"\nbase.random.negativeBinomial( r, p )\n    Returns a pseudorandom number drawn from a negative binomial distribution.\n\n    If `p` is not in the interval `(0,1)`, the function returns `NaN`.\n\n    If `r` or `p` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.negativeBinomial( 20, 0.8 );\n\n\nbase.random.negativeBinomial.factory( [r, p, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a negative binomial distribution.\n\n    If provided `r` and `p`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `r` and `p`, the returned PRNG requires that both `r` and\n    `p` be provided at each invocation.\n\n    Parameters\n    ----------\n    r: number (optional)\n        Number of successes until experiment is stopped.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.negativeBinomial.factory();\n    > var r = rand( 20, 0.3 );\n    > r = rand( 10, 0.77 );\n\n    // Provide `r` and `p`:\n    > rand = base.random.negativeBinomial.factory( 10, 0.8 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.negativeBinomial.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.negativeBinomial.NAME\n    'negative-binomial'\n\n\nbase.random.negativeBinomial.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.negativeBinomial.PRNG;\n\n\nbase.random.negativeBinomial.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.negativeBinomial.seed;\n\n\nbase.random.negativeBinomial.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.negativeBinomial.seedLength;\n\n\nbase.random.negativeBinomial.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.negativeBinomial.state\n    <Uint32Array>\n\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n\n    // Set the state:\n    > base.random.negativeBinomial.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n\n\nbase.random.negativeBinomial.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.negativeBinomial.stateLength;\n\n\nbase.random.negativeBinomial.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.negativeBinomial.byteLength;\n\n\nbase.random.negativeBinomial.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.negativeBinomial.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.negativeBinomial, random.iterators.negativeBinomial, random.streams.negativeBinomial\n","base.random.negativeBinomial.factory":"\nbase.random.negativeBinomial.factory( [r, p, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a negative binomial distribution.\n\n    If provided `r` and `p`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `r` and `p`, the returned PRNG requires that both `r` and\n    `p` be provided at each invocation.\n\n    Parameters\n    ----------\n    r: number (optional)\n        Number of successes until experiment is stopped.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.negativeBinomial.factory();\n    > var r = rand( 20, 0.3 );\n    > r = rand( 10, 0.77 );\n\n    // Provide `r` and `p`:\n    > rand = base.random.negativeBinomial.factory( 10, 0.8 );\n    > r = rand();\n    > r = rand();","base.random.negativeBinomial.NAME":"\nbase.random.negativeBinomial.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.negativeBinomial.NAME\n    'negative-binomial'","base.random.negativeBinomial.PRNG":"\nbase.random.negativeBinomial.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.negativeBinomial.PRNG;","base.random.negativeBinomial.seed":"\nbase.random.negativeBinomial.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.negativeBinomial.seed;","base.random.negativeBinomial.seedLength":"\nbase.random.negativeBinomial.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.negativeBinomial.seedLength;","base.random.negativeBinomial.state":"\nbase.random.negativeBinomial.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.negativeBinomial.state\n    <Uint32Array>\n\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n\n    // Set the state:\n    > base.random.negativeBinomial.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>\n    > r = base.random.negativeBinomial( 20, 0.3 )\n    <number>","base.random.negativeBinomial.stateLength":"\nbase.random.negativeBinomial.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.negativeBinomial.stateLength;","base.random.negativeBinomial.byteLength":"\nbase.random.negativeBinomial.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.negativeBinomial.byteLength;","base.random.negativeBinomial.toJSON":"\nbase.random.negativeBinomial.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.negativeBinomial.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.negativeBinomial, random.iterators.negativeBinomial, random.streams.negativeBinomial","base.random.normal":"\nbase.random.normal( μ, σ )\n    Returns a pseudorandom number drawn from a normal distribution.\n\n    If `μ` or `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    σ: number\n        Standard deviation.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.normal( 2.0, 5.0 );\n\n\nbase.random.normal.factory( [μ, σ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a normal distribution.\n\n    If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n    `σ` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    σ: number (optional)\n        Standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.normal.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `σ`:\n    > rand = base.random.normal.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.normal.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.normal.NAME\n    'normal'\n\n\nbase.random.normal.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.normal.PRNG;\n\n\nbase.random.normal.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.normal.seed;\n\n\nbase.random.normal.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.normal.seedLength;\n\n\nbase.random.normal.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.normal( 2.0, 5.0 )\n    <number>\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.normal.state\n    <Uint32Array>\n\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.normal.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>\n\n\nbase.random.normal.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.normal.stateLength;\n\n\nbase.random.normal.byteLength\n    Size of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.normal.byteLength;\n\n\nbase.random.normal.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.normal.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.normal, random.iterators.normal, random.streams.normal\n","base.random.normal.factory":"\nbase.random.normal.factory( [μ, σ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a normal distribution.\n\n    If provided `μ` and `σ`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `μ` and `σ`, the returned PRNG requires that both `μ` and\n    `σ` be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    σ: number (optional)\n        Standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.normal.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `μ` and `σ`:\n    > rand = base.random.normal.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.normal.NAME":"\nbase.random.normal.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.normal.NAME\n    'normal'","base.random.normal.PRNG":"\nbase.random.normal.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.normal.PRNG;","base.random.normal.seed":"\nbase.random.normal.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.normal.seed;","base.random.normal.seedLength":"\nbase.random.normal.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.normal.seedLength;","base.random.normal.state":"\nbase.random.normal.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.normal( 2.0, 5.0 )\n    <number>\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.normal.state\n    <Uint32Array>\n\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.normal.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>\n    > r = base.random.normal( 2.0, 5.0 )\n    <number>","base.random.normal.stateLength":"\nbase.random.normal.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.normal.stateLength;","base.random.normal.byteLength":"\nbase.random.normal.byteLength\n    Size of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.normal.byteLength;","base.random.normal.toJSON":"\nbase.random.normal.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.normal.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.normal, random.iterators.normal, random.streams.normal","base.random.pareto1":"\nbase.random.pareto1( α, β )\n    Returns a pseudorandom number drawn from a Pareto (Type I) distribution.\n\n    If `α <= 0` or `β <= 0`, the function returns `NaN`.\n\n    If `α` or `β` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.pareto1( 2.0, 5.0 );\n\n\nbase.random.pareto1.factory( [α, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Pareto (Type I) distribution.\n\n    If provided `α` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `α` and `β`, the returned PRNG requires that both `α` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.pareto1.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `α` and `β`:\n    > rand = base.random.pareto1.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.pareto1.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.pareto1.NAME\n    'pareto-type1'\n\n\nbase.random.pareto1.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.pareto1.PRNG;\n\n\nbase.random.pareto1.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.pareto1.seed;\n\n\nbase.random.pareto1.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.pareto1.seedLength;\n\n\nbase.random.pareto1.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.pareto1.state\n    <Uint32Array>\n\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.pareto1.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n\n\nbase.random.pareto1.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.pareto1.stateLength;\n\n\nbase.random.pareto1.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.pareto1.byteLength;\n\n\nbase.random.pareto1.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.pareto1.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.pareto1, random.iterators.pareto1, random.streams.pareto1\n","base.random.pareto1.factory":"\nbase.random.pareto1.factory( [α, β, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Pareto (Type I) distribution.\n\n    If provided `α` and `β`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `α` and `β`, the returned PRNG requires that both `α` and\n    `β` be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.pareto1.factory();\n    > var r = rand( 1.5, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `α` and `β`:\n    > rand = base.random.pareto1.factory( 1.5, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.pareto1.NAME":"\nbase.random.pareto1.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.pareto1.NAME\n    'pareto-type1'","base.random.pareto1.PRNG":"\nbase.random.pareto1.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.pareto1.PRNG;","base.random.pareto1.seed":"\nbase.random.pareto1.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.pareto1.seed;","base.random.pareto1.seedLength":"\nbase.random.pareto1.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.pareto1.seedLength;","base.random.pareto1.state":"\nbase.random.pareto1.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.pareto1.state\n    <Uint32Array>\n\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.pareto1.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>\n    > r = base.random.pareto1( 2.0, 5.0 )\n    <number>","base.random.pareto1.stateLength":"\nbase.random.pareto1.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.pareto1.stateLength;","base.random.pareto1.byteLength":"\nbase.random.pareto1.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.pareto1.byteLength;","base.random.pareto1.toJSON":"\nbase.random.pareto1.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.pareto1.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.pareto1, random.iterators.pareto1, random.streams.pareto1","base.random.poisson":"\nbase.random.poisson( λ )\n    Returns a pseudorandom number drawn from a Poisson distribution.\n\n    If `λ <= 0` or `λ` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    λ: number\n        Mean.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.poisson( 7.9 );\n\n\nbase.random.poisson.factory( [λ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Poisson distribution.\n\n    If provided `λ`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    λ: number (optional)\n        Mean.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.poisson.factory();\n    > var r = rand( 4.0 );\n    > r = rand( 3.14 );\n\n    // Provide `λ`:\n    > rand = base.random.poisson.factory( 10.0 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.poisson.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.poisson.NAME\n    'poisson'\n\n\nbase.random.poisson.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.poisson.PRNG;\n\n\nbase.random.poisson.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.poisson.seed;\n\n\nbase.random.poisson.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.poisson.seedLength;\n\n\nbase.random.poisson.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.poisson( 10.0 )\n    <number>\n    > r = base.random.poisson( 10.0 )\n    <number>\n    > r = base.random.poisson( 10.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.poisson.state\n    <Uint32Array>\n\n    > r = base.random.poisson( 10.0 )\n    <number>\n    > r = base.random.poisson( 10.0 )\n    <number>\n\n    // Set the state:\n    > base.random.poisson.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.poisson( 10.0 )\n    <number>\n    > r = base.random.poisson( 10.0 )\n    <number>\n\n\nbase.random.poisson.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.poisson.stateLength;\n\n\nbase.random.poisson.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.poisson.byteLength;\n\n\nbase.random.poisson.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.poisson.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.poisson, random.iterators.poisson, random.streams.poisson\n","base.random.poisson.factory":"\nbase.random.poisson.factory( [λ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Poisson distribution.\n\n    If provided `λ`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `λ`, the returned PRNG requires that `λ` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    λ: number (optional)\n        Mean.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.poisson.factory();\n    > var r = rand( 4.0 );\n    > r = rand( 3.14 );\n\n    // Provide `λ`:\n    > rand = base.random.poisson.factory( 10.0 );\n    > r = rand();\n    > r = rand();","base.random.poisson.NAME":"\nbase.random.poisson.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.poisson.NAME\n    'poisson'","base.random.poisson.PRNG":"\nbase.random.poisson.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.poisson.PRNG;","base.random.poisson.seed":"\nbase.random.poisson.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.poisson.seed;","base.random.poisson.seedLength":"\nbase.random.poisson.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.poisson.seedLength;","base.random.poisson.state":"\nbase.random.poisson.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.poisson( 10.0 )\n    <number>\n    > r = base.random.poisson( 10.0 )\n    <number>\n    > r = base.random.poisson( 10.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.poisson.state\n    <Uint32Array>\n\n    > r = base.random.poisson( 10.0 )\n    <number>\n    > r = base.random.poisson( 10.0 )\n    <number>\n\n    // Set the state:\n    > base.random.poisson.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.poisson( 10.0 )\n    <number>\n    > r = base.random.poisson( 10.0 )\n    <number>","base.random.poisson.stateLength":"\nbase.random.poisson.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.poisson.stateLength;","base.random.poisson.byteLength":"\nbase.random.poisson.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.poisson.byteLength;","base.random.poisson.toJSON":"\nbase.random.poisson.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.poisson.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.poisson, random.iterators.poisson, random.streams.poisson","base.random.randi":"\nbase.random.randi()\n    Returns a pseudorandom number having an integer value.\n\n    The default underlying pseudorandom number generator (PRNG) *may* change in\n    the future. If exact reproducibility is required, either use the `factory`\n    method to explicitly specify a PRNG via the `name` option or use an\n    underlying PRNG directly.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.randi();\n\n\nbase.random.randi.factory( [options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers having integer values.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of the underlying pseudorandom number generator (PRNG). The\n        following PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underlying PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var randi = base.random.randi.factory();\n    > var r = randi();\n    > r = randi();\n\n    // Specify alternative PRNG:\n    > randi = base.random.randi.factory({ 'name': 'minstd' });\n    > r = randi();\n    > r = randi();\n\n\nbase.random.randi.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.randi.NAME\n    'randi'\n\n\nbase.random.randi.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.randi.PRNG;\n\n\nbase.random.randi.MIN\n    Minimum possible value (specific to underlying PRNG).\n\n    Examples\n    --------\n    > var v = base.random.randi.MIN;\n\n\nbase.random.randi.MAX\n    Maximum possible value (specific to underlying PRNG).\n\n    Examples\n    --------\n    > var v = base.random.randi.MAX;\n\n\nbase.random.randi.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.randi.seed;\n\n\nbase.random.randi.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.randi.seedLength;\n\n\nbase.random.randi.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.randi()\n    <number>\n    > r = base.random.randi()\n    <number>\n    > r = base.random.randi()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.randi.state;\n\n    > r = base.random.randi()\n    <number>\n    > r = base.random.randi()\n    <number>\n\n    // Set the state:\n    > base.random.randi.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.randi()\n    <number>\n    > r = base.random.randi()\n    <number>\n\n\nbase.random.randi.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.randi.stateLength;\n\n\nbase.random.randi.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.randi.byteLength;\n\n\nbase.random.randi.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.randi.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.iterators.randi, random.streams.randi, base.random.minstd, base.random.minstdShuffle, base.random.mt19937\n","base.random.randi.factory":"\nbase.random.randi.factory( [options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers having integer values.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of the underlying pseudorandom number generator (PRNG). The\n        following PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underlying PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var randi = base.random.randi.factory();\n    > var r = randi();\n    > r = randi();\n\n    // Specify alternative PRNG:\n    > randi = base.random.randi.factory({ 'name': 'minstd' });\n    > r = randi();\n    > r = randi();","base.random.randi.NAME":"\nbase.random.randi.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.randi.NAME\n    'randi'","base.random.randi.PRNG":"\nbase.random.randi.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.randi.PRNG;","base.random.randi.MIN":"\nbase.random.randi.MIN\n    Minimum possible value (specific to underlying PRNG).\n\n    Examples\n    --------\n    > var v = base.random.randi.MIN;","base.random.randi.MAX":"\nbase.random.randi.MAX\n    Maximum possible value (specific to underlying PRNG).\n\n    Examples\n    --------\n    > var v = base.random.randi.MAX;","base.random.randi.seed":"\nbase.random.randi.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.randi.seed;","base.random.randi.seedLength":"\nbase.random.randi.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.randi.seedLength;","base.random.randi.state":"\nbase.random.randi.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.randi()\n    <number>\n    > r = base.random.randi()\n    <number>\n    > r = base.random.randi()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.randi.state;\n\n    > r = base.random.randi()\n    <number>\n    > r = base.random.randi()\n    <number>\n\n    // Set the state:\n    > base.random.randi.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.randi()\n    <number>\n    > r = base.random.randi()\n    <number>","base.random.randi.stateLength":"\nbase.random.randi.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.randi.stateLength;","base.random.randi.byteLength":"\nbase.random.randi.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.randi.byteLength;","base.random.randi.toJSON":"\nbase.random.randi.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.randi.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.iterators.randi, random.streams.randi, base.random.minstd, base.random.minstdShuffle, base.random.mt19937","base.random.randn":"\nbase.random.randn()\n    Returns a pseudorandom number drawn from a standard normal distribution.\n\n    The default underlying pseudorandom number generator (PRNG) *may* change in\n    the future. If exact reproducibility is required, either use the `factory`\n    method to explicitly specify a PRNG via the `name` option or use an\n    underlying PRNG directly.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.randn();\n\n\nbase.random.randn.factory( [options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a standard normal distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of the underlying pseudorandom number generator (PRNG) that samples\n        from a standard normal distribution. The following PRNGs are supported:\n\n        - improved-ziggurat: improved ziggurat method.\n        - box-muller: Box-Muller transform.\n\n        Default: 'improved-ziggurat'.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underlying PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.randn.factory();\n    > var r = rand();\n    > r = rand();\n\n    // Specify alternative PRNG:\n    > var rand = base.random.randn.factory({ 'name': 'box-muller' });\n    > r = rand();\n    > r = rand();\n\n\nbase.random.randn.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.randn.NAME\n    'randn'\n\n\nbase.random.randn.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.randn.PRNG;\n\n\nbase.random.randn.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.randn.seed;\n\n\nbase.random.randn.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.randn.seedLength;\n\n\nbase.random.randn.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.randn()\n    <number>\n    > r = base.random.randn()\n    <number>\n    > r = base.random.randn()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.randn.state;\n\n    > r = base.random.randn()\n    <number>\n    > r = base.random.randn()\n    <number>\n\n    // Set the state:\n    > base.random.randn.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.randn()\n    <number>\n    > r = base.random.randn()\n    <number>\n\n\nbase.random.randn.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.randn.stateLength;\n\n\nbase.random.randn.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.randn.byteLength;\n\n\nbase.random.randn.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.randn.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.iterators.randn, random.streams.randn, base.random.improvedZiggurat, base.random.randu\n","base.random.randn.factory":"\nbase.random.randn.factory( [options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a standard normal distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of the underlying pseudorandom number generator (PRNG) that samples\n        from a standard normal distribution. The following PRNGs are supported:\n\n        - improved-ziggurat: improved ziggurat method.\n        - box-muller: Box-Muller transform.\n\n        Default: 'improved-ziggurat'.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underlying PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.randn.factory();\n    > var r = rand();\n    > r = rand();\n\n    // Specify alternative PRNG:\n    > var rand = base.random.randn.factory({ 'name': 'box-muller' });\n    > r = rand();\n    > r = rand();","base.random.randn.NAME":"\nbase.random.randn.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.randn.NAME\n    'randn'","base.random.randn.PRNG":"\nbase.random.randn.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.randn.PRNG;","base.random.randn.seed":"\nbase.random.randn.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.randn.seed;","base.random.randn.seedLength":"\nbase.random.randn.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.randn.seedLength;","base.random.randn.state":"\nbase.random.randn.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.randn()\n    <number>\n    > r = base.random.randn()\n    <number>\n    > r = base.random.randn()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.randn.state;\n\n    > r = base.random.randn()\n    <number>\n    > r = base.random.randn()\n    <number>\n\n    // Set the state:\n    > base.random.randn.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.randn()\n    <number>\n    > r = base.random.randn()\n    <number>","base.random.randn.stateLength":"\nbase.random.randn.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.randn.stateLength;","base.random.randn.byteLength":"\nbase.random.randn.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.randn.byteLength;","base.random.randn.toJSON":"\nbase.random.randn.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.randn.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.iterators.randn, random.streams.randn, base.random.improvedZiggurat, base.random.randu","base.random.randu":"\nbase.random.randu()\n    Returns a pseudorandom number drawn from a uniform distribution.\n\n    The default underlying pseudorandom number generator (PRNG) *may* change in\n    the future. If exact reproducibility is required, either use the `factory`\n    method to explicitly specify a PRNG via the `name` option or use an\n    underlying PRNG directly.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number on the interval `[0,1)`.\n\n    Examples\n    --------\n    > var r = base.random.randu();\n\n\nbase.random.randu.factory( [options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a uniform distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of the underlying pseudorandom number generator (PRNG). The\n        following PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underlying PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.randu.factory();\n    > var r = rand();\n    > r = rand();\n\n    // Specify alternative PRNG:\n    > var rand = base.random.randu.factory({ 'name': 'minstd' });\n    > r = rand();\n    > r = rand();\n\n\nbase.random.randu.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.randu.NAME\n    'randu'\n\n\nbase.random.randu.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.randu.PRNG;\n\n\nbase.random.randu.MIN\n    Minimum possible value (specific to underlying PRNG).\n\n    Examples\n    --------\n    > var v = base.random.randu.MIN;\n\n\nbase.random.randu.MAX\n    Maximum possible value (specific to underlying PRNG).\n\n    Examples\n    --------\n    > var v = base.random.randu.MAX;\n\n\nbase.random.randu.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.randu.seed;\n\n\nbase.random.randu.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.randu.seedLength;\n\n\nbase.random.randu.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.randu()\n    <number>\n    > r = base.random.randu()\n    <number>\n    > r = base.random.randu()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.randu.state;\n\n    > r = base.random.randu()\n    <number>\n    > r = base.random.randu()\n    <number>\n\n    // Set the state:\n    > base.random.randu.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.randu()\n    <number>\n    > r = base.random.randu()\n    <number>\n\n\nbase.random.randu.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.randu.stateLength;\n\n\nbase.random.randu.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.randu.byteLength;\n\n\nbase.random.randu.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.randu.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.randu, random.iterators.randu, random.streams.randu, base.random.discreteUniform, base.random.randn\n","base.random.randu.factory":"\nbase.random.randu.factory( [options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a uniform distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of the underlying pseudorandom number generator (PRNG). The\n        following PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underlying PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.randu.factory();\n    > var r = rand();\n    > r = rand();\n\n    // Specify alternative PRNG:\n    > var rand = base.random.randu.factory({ 'name': 'minstd' });\n    > r = rand();\n    > r = rand();","base.random.randu.NAME":"\nbase.random.randu.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.randu.NAME\n    'randu'","base.random.randu.PRNG":"\nbase.random.randu.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.randu.PRNG;","base.random.randu.MIN":"\nbase.random.randu.MIN\n    Minimum possible value (specific to underlying PRNG).\n\n    Examples\n    --------\n    > var v = base.random.randu.MIN;","base.random.randu.MAX":"\nbase.random.randu.MAX\n    Maximum possible value (specific to underlying PRNG).\n\n    Examples\n    --------\n    > var v = base.random.randu.MAX;","base.random.randu.seed":"\nbase.random.randu.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.randu.seed;","base.random.randu.seedLength":"\nbase.random.randu.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.randu.seedLength;","base.random.randu.state":"\nbase.random.randu.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.randu()\n    <number>\n    > r = base.random.randu()\n    <number>\n    > r = base.random.randu()\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.randu.state;\n\n    > r = base.random.randu()\n    <number>\n    > r = base.random.randu()\n    <number>\n\n    // Set the state:\n    > base.random.randu.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.randu()\n    <number>\n    > r = base.random.randu()\n    <number>","base.random.randu.stateLength":"\nbase.random.randu.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.randu.stateLength;","base.random.randu.byteLength":"\nbase.random.randu.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.randu.byteLength;","base.random.randu.toJSON":"\nbase.random.randu.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.randu.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.randu, random.iterators.randu, random.streams.randu, base.random.discreteUniform, base.random.randn","base.random.rayleigh":"\nbase.random.rayleigh( σ )\n    Returns a pseudorandom number drawn from a Rayleigh distribution.\n\n    If `σ` is `NaN` or `σ <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.rayleigh( 2.5 );\n\n\nbase.random.rayleigh.factory( [σ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Rayleigh distribution.\n\n    If provided `σ`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `σ`, the returned PRNG requires that `σ` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    σ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.rayleigh.factory();\n    > var r = rand( 5.0 );\n    > r = rand( 10.0 );\n\n    // Provide `σ`:\n    > rand = base.random.rayleigh.factory( 5.0 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.rayleigh.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.rayleigh.NAME\n    'rayleigh'\n\n\nbase.random.rayleigh.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.rayleigh.PRNG;\n\n\nbase.random.rayleigh.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.rayleigh.seed;\n\n\nbase.random.rayleigh.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.rayleigh.seedLength;\n\n\nbase.random.rayleigh.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.rayleigh( 5.0 )\n    <number>\n    > r = base.random.rayleigh( 5.0 )\n    <number>\n    > r = base.random.rayleigh( 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.rayleigh.state\n    <Uint32Array>\n\n    > r = base.random.rayleigh( 5.0 )\n    <number>\n    > r = base.random.rayleigh( 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.rayleigh.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.rayleigh( 5.0 )\n    <number>\n    > r = base.random.rayleigh( 5.0 )\n    <number>\n\n\nbase.random.rayleigh.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.rayleigh.stateLength;\n\n\nbase.random.rayleigh.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.rayleigh.byteLength;\n\n\nbase.random.rayleigh.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.rayleigh.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.rayleigh, random.iterators.rayleigh, random.streams.rayleigh\n","base.random.rayleigh.factory":"\nbase.random.rayleigh.factory( [σ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Rayleigh distribution.\n\n    If provided `σ`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `σ`, the returned PRNG requires that `σ` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    σ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.rayleigh.factory();\n    > var r = rand( 5.0 );\n    > r = rand( 10.0 );\n\n    // Provide `σ`:\n    > rand = base.random.rayleigh.factory( 5.0 );\n    > r = rand();\n    > r = rand();","base.random.rayleigh.NAME":"\nbase.random.rayleigh.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.rayleigh.NAME\n    'rayleigh'","base.random.rayleigh.PRNG":"\nbase.random.rayleigh.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.rayleigh.PRNG;","base.random.rayleigh.seed":"\nbase.random.rayleigh.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.rayleigh.seed;","base.random.rayleigh.seedLength":"\nbase.random.rayleigh.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.rayleigh.seedLength;","base.random.rayleigh.state":"\nbase.random.rayleigh.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.rayleigh( 5.0 )\n    <number>\n    > r = base.random.rayleigh( 5.0 )\n    <number>\n    > r = base.random.rayleigh( 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.rayleigh.state\n    <Uint32Array>\n\n    > r = base.random.rayleigh( 5.0 )\n    <number>\n    > r = base.random.rayleigh( 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.rayleigh.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.rayleigh( 5.0 )\n    <number>\n    > r = base.random.rayleigh( 5.0 )\n    <number>","base.random.rayleigh.stateLength":"\nbase.random.rayleigh.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.rayleigh.stateLength;","base.random.rayleigh.byteLength":"\nbase.random.rayleigh.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.rayleigh.byteLength;","base.random.rayleigh.toJSON":"\nbase.random.rayleigh.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.rayleigh.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.rayleigh, random.iterators.rayleigh, random.streams.rayleigh","base.random.t":"\nbase.random.t( v )\n    Returns a pseudorandom number drawn from a Student's t distribution.\n\n    If `v <= 0` or `v` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.t( 2.0 );\n\n\nbase.random.t.factory( [v, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Student's t distribution.\n\n    If provided `v`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `v`, the returned PRNG requires that `v` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    v: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.t.factory();\n    > var r = rand( 5.0 );\n    > r = rand( 3.14 );\n\n    // Provide `v`:\n    > rand = base.random.t.factory( 5.0 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.t.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.t.NAME\n    't'\n\n\nbase.random.t.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.t.PRNG;\n\n\nbase.random.t.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.t.seed;\n\n\nbase.random.t.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.t.seedLength;\n\n\nbase.random.t.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.t( 10.0 )\n    <number>\n    > r = base.random.t( 10.0 )\n    <number>\n    > r = base.random.t( 10.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.t.state\n    <Uint32Array>\n\n    > r = base.random.t( 10.0 )\n    <number>\n    > r = base.random.t( 10.0 )\n    <number>\n\n    // Set the state:\n    > base.random.t.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.t( 10.0 )\n    <number>\n    > r = base.random.t( 10.0 )\n    <number>\n\n\nbase.random.t.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.t.stateLength;\n\n\nbase.random.t.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.t.byteLength;\n\n\nbase.random.t.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.t.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.t, random.iterators.t, random.streams.t\n","base.random.t.factory":"\nbase.random.t.factory( [v, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Student's t distribution.\n\n    If provided `v`, the returned PRNG returns random variates drawn from the\n    specified distribution.\n\n    If not provided `v`, the returned PRNG requires that `v` be provided at each\n    invocation.\n\n    Parameters\n    ----------\n    v: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.t.factory();\n    > var r = rand( 5.0 );\n    > r = rand( 3.14 );\n\n    // Provide `v`:\n    > rand = base.random.t.factory( 5.0 );\n    > r = rand();\n    > r = rand();","base.random.t.NAME":"\nbase.random.t.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.t.NAME\n    't'","base.random.t.PRNG":"\nbase.random.t.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.t.PRNG;","base.random.t.seed":"\nbase.random.t.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.t.seed;","base.random.t.seedLength":"\nbase.random.t.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.t.seedLength;","base.random.t.state":"\nbase.random.t.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.t( 10.0 )\n    <number>\n    > r = base.random.t( 10.0 )\n    <number>\n    > r = base.random.t( 10.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.t.state\n    <Uint32Array>\n\n    > r = base.random.t( 10.0 )\n    <number>\n    > r = base.random.t( 10.0 )\n    <number>\n\n    // Set the state:\n    > base.random.t.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.t( 10.0 )\n    <number>\n    > r = base.random.t( 10.0 )\n    <number>","base.random.t.stateLength":"\nbase.random.t.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.t.stateLength;","base.random.t.byteLength":"\nbase.random.t.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.t.byteLength;","base.random.t.toJSON":"\nbase.random.t.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.t.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.t, random.iterators.t, random.streams.t","base.random.triangular":"\nbase.random.triangular( a, b, c )\n    Returns a pseudorandom number drawn from a triangular distribution.\n\n    If the condition `a <= c <= b` is not satisfied, the function returns `NaN`.\n\n    If either `a`, `b`, or `c` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    Returns\n    -------\n    r: integer\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.triangular( 2.0, 5.0, 3.33 );\n\n\nbase.random.triangular.factory( [a, b, c, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a triangular distribution.\n\n    If provided `a`, `b`, and `c`, the returned PRNG returns random variates\n    drawn from the specified distribution.\n\n    If not provided `a`, `b`, and `c`, the returned PRNG requires that `a`, `b`,\n    and `c` be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    c: number (optional)\n        Mode.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.triangular.factory();\n    > var r = rand( 0.0, 1.0, 0.5 );\n    > r = rand( -2.0, 2.0, 1.0 );\n\n    // Provide `a`, `b`, and `c`:\n    > rand = base.random.triangular.factory( 0.0, 1.0, 0.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.triangular.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.triangular.NAME\n    'triangular'\n\n\nbase.random.triangular.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.triangular.PRNG;\n\n\nbase.random.triangular.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.triangular.seed;\n\n\nbase.random.triangular.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.triangular.seedLength;\n\n\nbase.random.triangular.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.triangular.state\n    <Uint32Array>\n\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n\n    // Set the state:\n    > base.random.triangular.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n\n\nbase.random.triangular.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.triangular.stateLength;\n\n\nbase.random.triangular.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.triangular.byteLength;\n\n\nbase.random.triangular.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.triangular.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.triangular, random.iterators.triangular, random.streams.triangular\n","base.random.triangular.factory":"\nbase.random.triangular.factory( [a, b, c, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a triangular distribution.\n\n    If provided `a`, `b`, and `c`, the returned PRNG returns random variates\n    drawn from the specified distribution.\n\n    If not provided `a`, `b`, and `c`, the returned PRNG requires that `a`, `b`,\n    and `c` be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    c: number (optional)\n        Mode.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.triangular.factory();\n    > var r = rand( 0.0, 1.0, 0.5 );\n    > r = rand( -2.0, 2.0, 1.0 );\n\n    // Provide `a`, `b`, and `c`:\n    > rand = base.random.triangular.factory( 0.0, 1.0, 0.5 );\n    > r = rand();\n    > r = rand();","base.random.triangular.NAME":"\nbase.random.triangular.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.triangular.NAME\n    'triangular'","base.random.triangular.PRNG":"\nbase.random.triangular.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.triangular.PRNG;","base.random.triangular.seed":"\nbase.random.triangular.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.triangular.seed;","base.random.triangular.seedLength":"\nbase.random.triangular.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.triangular.seedLength;","base.random.triangular.state":"\nbase.random.triangular.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.triangular.state\n    <Uint32Array>\n\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n\n    // Set the state:\n    > base.random.triangular.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>\n    > r = base.random.triangular( 0.0, 1.0, 0.5 )\n    <number>","base.random.triangular.stateLength":"\nbase.random.triangular.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.triangular.stateLength;","base.random.triangular.byteLength":"\nbase.random.triangular.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.triangular.byteLength;","base.random.triangular.toJSON":"\nbase.random.triangular.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.triangular.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.triangular, random.iterators.triangular, random.streams.triangular","base.random.uniform":"\nbase.random.uniform( a, b )\n    Returns a pseudorandom number drawn from a continuous uniform distribution.\n\n    If `a >= b`, the function returns `NaN`.\n\n    If `a` or `b` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support (inclusive).\n\n    b: number\n        Maximum support (exclusive).\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.uniform( 2.0, 5.0 );\n\n\nbase.random.uniform.factory( [a, b, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a continuous uniform distribution.\n\n    If provided `a` and `b`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `a` and `b`, the returned PRNG requires that both `a` and\n    `b` be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support (inclusive).\n\n    b: number (optional)\n        Maximum support (exclusive).\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.uniform.factory();\n    > var r = rand( 0.0, 1.0 );\n    > r = rand( -2.0, 2.0 );\n\n    // Provide `a` and `b`:\n    > rand = base.random.uniform.factory( 0.0, 1.0 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.uniform.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.uniform.NAME\n    'uniform'\n\n\nbase.random.uniform.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.uniform.PRNG;\n\n\nbase.random.uniform.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.uniform.seed;\n\n\nbase.random.uniform.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.uniform.seedLength;\n\n\nbase.random.uniform.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.uniform( 2.0, 5.0 )\n    <number>\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.uniform.state\n    <Uint32Array>\n\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.uniform.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>\n\n\nbase.random.uniform.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.uniform.stateLength;\n\n\nbase.random.uniform.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.uniform.byteLength;\n\n\nbase.random.uniform.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.uniform.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.uniform, random.iterators.uniform, random.streams.uniform, base.random.discreteUniform, base.random.randu\n","base.random.uniform.factory":"\nbase.random.uniform.factory( [a, b, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a continuous uniform distribution.\n\n    If provided `a` and `b`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `a` and `b`, the returned PRNG requires that both `a` and\n    `b` be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support (inclusive).\n\n    b: number (optional)\n        Maximum support (exclusive).\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.uniform.factory();\n    > var r = rand( 0.0, 1.0 );\n    > r = rand( -2.0, 2.0 );\n\n    // Provide `a` and `b`:\n    > rand = base.random.uniform.factory( 0.0, 1.0 );\n    > r = rand();\n    > r = rand();","base.random.uniform.NAME":"\nbase.random.uniform.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.uniform.NAME\n    'uniform'","base.random.uniform.PRNG":"\nbase.random.uniform.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.uniform.PRNG;","base.random.uniform.seed":"\nbase.random.uniform.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.uniform.seed;","base.random.uniform.seedLength":"\nbase.random.uniform.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.uniform.seedLength;","base.random.uniform.state":"\nbase.random.uniform.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.uniform( 2.0, 5.0 )\n    <number>\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.uniform.state\n    <Uint32Array>\n\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.uniform.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>\n    > r = base.random.uniform( 2.0, 5.0 )\n    <number>","base.random.uniform.stateLength":"\nbase.random.uniform.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.uniform.stateLength;","base.random.uniform.byteLength":"\nbase.random.uniform.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.uniform.byteLength;","base.random.uniform.toJSON":"\nbase.random.uniform.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.uniform.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.uniform, random.iterators.uniform, random.streams.uniform, base.random.discreteUniform, base.random.randu","base.random.weibull":"\nbase.random.weibull( k, λ )\n    Returns a pseudorandom number drawn from a Weibull distribution.\n\n    If `k <= 0` or `λ <= 0`, the function returns `NaN`.\n\n    If either `λ` or `k` is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    k: number\n        Scale parameter.\n\n    λ: number\n        Shape parameter.\n\n    Returns\n    -------\n    r: number\n        Pseudorandom number.\n\n    Examples\n    --------\n    > var r = base.random.weibull( 2.0, 5.0 );\n\n\nbase.random.weibull.factory( [k, λ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Weibull distribution.\n\n    If provided `k` and `λ`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `k` and `λ`, the returned PRNG requires that both\n    `k` and `λ` be provided at each invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Scale parameter.\n\n    λ: number (optional)\n        Shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.weibull.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `λ` and `k`:\n    > rand = base.random.weibull.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();\n\n\nbase.random.weibull.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.weibull.NAME\n    'weibull'\n\n\nbase.random.weibull.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.weibull.PRNG;\n\n\nbase.random.weibull.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.weibull.seed;\n\n\nbase.random.weibull.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.weibull.seedLength;\n\n\nbase.random.weibull.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.weibull( 2.0, 5.0 )\n    <number>\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.weibull.state\n    <Uint32Array>\n\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.weibull.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>\n\n\nbase.random.weibull.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.weibull.stateLength;\n\n\nbase.random.weibull.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.weibull.byteLength;\n\n\nbase.random.weibull.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.weibull.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.weibull, random.iterators.weibull, random.streams.weibull\n","base.random.weibull.factory":"\nbase.random.weibull.factory( [k, λ, ][options] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Weibull distribution.\n\n    If provided `k` and `λ`, the returned PRNG returns random variates drawn\n    from the specified distribution.\n\n    If not provided `k` and `λ`, the returned PRNG requires that both\n    `k` and `λ` be provided at each invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Scale parameter.\n\n    λ: number (optional)\n        Shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    rand: Function\n        Pseudorandom number generator (PRNG).\n\n    Examples\n    --------\n    // Basic usage:\n    > var rand = base.random.weibull.factory();\n    > var r = rand( 0.1, 1.5 );\n    > r = rand( 2.0, 3.14 );\n\n    // Provide `λ` and `k`:\n    > rand = base.random.weibull.factory( 0.1, 1.5 );\n    > r = rand();\n    > r = rand();","base.random.weibull.NAME":"\nbase.random.weibull.NAME\n    Generator name.\n\n    Examples\n    --------\n    > var str = base.random.weibull.NAME\n    'weibull'","base.random.weibull.PRNG":"\nbase.random.weibull.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = base.random.weibull.PRNG;","base.random.weibull.seed":"\nbase.random.weibull.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = base.random.weibull.seed;","base.random.weibull.seedLength":"\nbase.random.weibull.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = base.random.weibull.seedLength;","base.random.weibull.state":"\nbase.random.weibull.state\n    Generator state.\n\n    Examples\n    --------\n    > var r = base.random.weibull( 2.0, 5.0 )\n    <number>\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>\n\n    // Get a copy of the current state:\n    > var state = base.random.weibull.state\n    <Uint32Array>\n\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>\n\n    // Set the state:\n    > base.random.weibull.state = state;\n\n    // Replay the last two pseudorandom numbers:\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>\n    > r = base.random.weibull( 2.0, 5.0 )\n    <number>","base.random.weibull.stateLength":"\nbase.random.weibull.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = base.random.weibull.stateLength;","base.random.weibull.byteLength":"\nbase.random.weibull.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = base.random.weibull.byteLength;","base.random.weibull.toJSON":"\nbase.random.weibull.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var o = base.random.weibull.toJSON()\n    { 'type': 'PRNG', 'name': '...', 'state': {...}, 'params': [] }\n\n    See Also\n    --------\n    random.array.weibull, random.iterators.weibull, random.streams.weibull","base.rcbrt":"\nbase.rcbrt( x )\n    Computes the reciprocal cube root of a double-precision floating-point\n    number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Reciprocal cube root.\n\n    Examples\n    --------\n    > var y = base.rcbrt( 8.0 )\n    0.5\n    > y = base.rcbrt( 1000.0 )\n    0.1\n    > y = base.rcbrt( 0.0 )\n    Infinity\n    > y = base.rcbrt( PINF )\n    0.0\n    > y = base.rcbrt( -8.0 )\n    -0.5\n    > y = base.rcbrt( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cbrt\n","base.rcbrtf":"\nbase.rcbrtf( x )\n    Computes the reciprocal cube root of a single-precision floating-point\n    number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Reciprocal cube root.\n\n    Examples\n    --------\n    > var y = base.rcbrtf( 8.0 )\n    0.5\n    > y = base.rcbrtf( 1000.0 )\n    ~0.1\n    > y = base.rcbrtf( 0.0 )\n    Infinity\n    > y = base.rcbrtf( PINF )\n    0.0\n    > y = base.rcbrtf( -8.0 )\n    -0.5\n    > y = base.rcbrtf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.rcbrt, base.cbrtf\n","base.reldiff":"\nbase.reldiff( x, y[, scale] )\n    Computes the relative difference of two real numbers.\n\n    By default, the function scales the absolute difference by dividing the\n    absolute difference by the maximum absolute value of `x` and `y`. To scale\n    by a different function, specify a scale function name.\n\n    The following `scale` functions are supported:\n\n    - 'max-abs': maximum absolute value of `x` and `y` (default).\n    - 'max': maximum value of `x` and `y`.\n    - 'min-abs': minimum absolute value of `x` and `y`.\n    - 'min': minimum value of `x` and `y`.\n    - 'mean-abs': arithmetic mean of the absolute values of `x` and `y`.\n    - 'mean': arithmetic mean of `x` and `y`.\n    - 'x': `x` (*noncommutative*).\n    - 'y': `y` (*noncommutative*).\n\n    To use a custom scale function, provide a function which accepts two numeric\n    arguments `x` and `y`.\n\n    If the absolute difference of `x` and `y` is `0`, the relative difference is\n    always `0`.\n\n    If `|x| = |y| = infinity`, the function returns `NaN`.\n\n    If `|x| = |-y| = infinity`, the relative difference is `+infinity`.\n\n    If a `scale` function returns `0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    scale: string|Function (optional)\n        Scale function. Default: `'max-abs'`.\n\n    Returns\n    -------\n    out: number\n        Relative difference.\n\n    Examples\n    --------\n    > var d = base.reldiff( 2.0, 5.0 )\n    0.6\n    > d = base.reldiff( -1.0, 3.14 )\n    ~1.318\n    > d = base.reldiff( -2.0, 5.0, 'max-abs' )\n    1.4\n    > d = base.reldiff( -2.0, 5.0, 'max' )\n    1.4\n    > d = base.reldiff( -2.0, 5.0, 'min-abs' )\n    3.5\n    > d = base.reldiff( -2.0, 5.0, 'min' )\n    3.5\n    > d = base.reldiff( -2.0, 5.0, 'mean-abs' )\n    2.0\n    > d = base.reldiff( -2.0, 5.0, 'mean' )\n    ~4.667\n    > d = base.reldiff( -2.0, 5.0, 'x' )\n    3.5\n    > d = base.reldiff( 5.0, -2.0, 'x' )\n    1.4\n    > d = base.reldiff( -2.0, 5.0, 'y' )\n    1.4\n    > d = base.reldiff( 5.0, -2.0, 'y' )\n    3.5\n\n    // Custom scale function:\n    > function scale( x, y ) {\n    ...     var s;\n    ...\n    ...     x = base.abs( x );\n    ...     y = base.abs( y );\n    ...\n    ...     // Maximum absolute value:\n    ...     s = (x < y ) ? y : x;\n    ...\n    ...     // Scale in units of epsilon:\n    ...     return s * EPS;\n    ... };\n    > d = base.reldiff( 12.15, 12.149999999999999, scale )\n    ~0.658\n\n    See Also\n    --------\n    base.absdiff, base.epsdiff\n","base.removeFirst":"\nbase.removeFirst( str, n )\n    Removes the first `n` UTF-16 code units of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of UTF-16 code units to remove.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.removeFirst( 'beep', 1 )\n    'eep'\n    > out = base.removeFirst( 'Boop', 1 )\n    'oop'\n    > out = base.removeFirst( 'foo bar', 5 )\n    'ar'\n\n    See Also\n    --------\n    base.removeFirstCodePoint, base.removeFirstGraphemeCluster, base.removeLast\n","base.removeFirstCodePoint":"\nbase.removeFirstCodePoint( str, n )\n    Removes the first `n` Unicode code points of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of Unicode code points to remove.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.removeFirstCodePoint( 'beep', 1 )\n    'eep'\n    > out = base.removeFirstCodePoint( 'Boop', 1 )\n    'oop'\n    > out = base.removeFirstCodePoint( 'foo bar', 5 )\n    'ar'\n\n    See Also\n    --------\n    base.removeLastCodePoint, base.removeFirstGraphemeCluster, base.removeFirst\n","base.removeFirstGraphemeCluster":"\nbase.removeFirstGraphemeCluster( str, n )\n    Removes the first `n` grapheme clusters (i.e., user-perceived characters)\n    of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of grapheme clusters to remove.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.removeFirstGraphemeCluster( 'beep', 1 )\n    'eep'\n    > out = base.removeFirstGraphemeCluster( 'Boop', 1 )\n    'oop'\n    > out = base.removeFirstGraphemeCluster( 'foo bar', 5 )\n    'ar'\n\n    See Also\n    --------\n    base.removeFirstCodePoint, base.removeLastGraphemeCluster, base.removeFirst\n","base.removeLast":"\nbase.removeLast( str, n )\n    Removes the last `n` UTF-16 code units of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of UTF-16 code units to remove.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.removeLast( 'beep', 1 )\n    'bee'\n    > out = base.removeLast( 'Boop', 1 )\n    'Boo'\n    > out = base.removeLast( 'foo bar', 5 )\n    'fo'\n\n    See Also\n    --------\n    base.removeLastCodePoint, base.removeLastGraphemeCluster, base.removeFirst\n","base.removeLastCodePoint":"\nbase.removeLastCodePoint( str, n )\n    Removes the last `n` Unicode code points of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of Unicode code points to remove.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.removeLastCodePoint( 'beep', 1 )\n    'bee'\n    > out = base.removeLastCodePoint( 'Boop', 1 )\n    'Boo'\n    > out = base.removeLastCodePoint( 'foo bar', 5 )\n    'fo'\n\n    See Also\n    --------\n    base.removeFirstCodePoint, base.removeLastGraphemeCluster, base.removeLast\n","base.removeLastGraphemeCluster":"\nbase.removeLastGraphemeCluster( str, n )\n    Removes the last `n` grapheme clusters (i.e., user-perceived characters)\n    of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of grapheme clusters to remove.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.removeLastGraphemeCluster( 'beep', 1 )\n    'bee'\n    > out = base.removeLastGraphemeCluster( 'Boop', 1 )\n    'Boo'\n    > out = base.removeLastGraphemeCluster( 'foo bar', 5 )\n    'fo'\n\n    See Also\n    --------\n    base.removeFirstCodePoint, base.removeLastCodePoint, base.removeLast\n","base.rempio2":"\nbase.rempio2( x, y )\n    Computes `x - nπ/2 = r`.\n\n    The function returns `n` and stores the remainder `r` as the two numbers\n    `y[0]` and `y[1]`, such that `y[0] + y[1] = r`.\n\n    For input values larger than `2^20 * π/2` in magnitude, the function only\n    returns the last three binary digits of `n` and not the full result.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    y: Array|TypedArray|Object\n        Remainder elements.\n\n    Returns\n    -------\n    n: integer\n        Factor of `π/2`.\n\n    Examples\n    --------\n    > var y = [ 0.0, 0.0 ];\n    > var n = base.rempio2( 128.0, y )\n    81\n    > var y1 = y[ 0 ]\n    ~0.765\n    > var y2 = y[ 1 ]\n    ~3.618e-17\n\n\n","base.repeat":"\nbase.repeat( str, n )\n    Repeats a string `n` times and returns the concatenated result.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of repetitions.\n\n    Returns\n    -------\n    out: string\n        Repeated string.\n\n    Examples\n    --------\n    > var out = base.repeat( 'a', 5 )\n    'aaaaa'\n    > out = base.repeat( '', 100 )\n    ''\n    > out = base.repeat( 'beep', 0 )\n    ''\n\n","base.replace":"\nbase.replace( str, search, newval )\n    Replaces search occurrences with a replacement string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: RegExp\n        Search expression.\n\n    newval: string|Function\n        Replacement value or function.\n\n    Returns\n    -------\n    out: string\n        String containing replacement(s).\n\n    Examples\n    --------\n    > function replacer( match, p1 ) { return '/'+p1+'/'; };\n    > var str = 'Oranges and lemons';\n    > var out = base.replace( str, /([^\\s]+)/gi, replacer )\n    '/Oranges/ /and/ /lemons/'\n\n    // Replace only first match:\n    > out = base.replace( 'beep', /e/, 'o' )\n    'boep'\n\n    See Also\n    --------\n    base.replaceAfter, base.replaceBefore, base.replaceAfterLast, base.replaceBeforeLast\n","base.replaceAfter":"\nbase.replaceAfter( str, search, replacement, fromIndex )\n    Replaces the substring after the first occurrence of a specified search\n    string.\n\n    If unable to find a search string, the function returns the input string\n    unchanged.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search string.\n\n    replacement: string\n        Replacement string.\n\n    fromIndex: integer\n        Starting index (inclusive). If less than zero, the starting index is\n        resolved relative to the last string character, with the last string\n        character corresponding to `fromIndex = -1`.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.replaceAfter( 'beep boop', ' ', 'foo', 0 )\n    'beep foo'\n    > out = base.replaceAfter( 'beep boop', 'o', 'foo', 0 )\n    'beep bofoo'\n    > out = base.replaceAfter( 'Hello World!', 'o', 'foo', 5 )\n    'Hello Wofoo'\n    > out = base.replaceAfter( 'beep boop beep baz', 'beep', 'foo', 5 )\n    'beep boop beepfoo'\n\n    See Also\n    --------\n    base.replaceAfterLast, base.replaceBefore, base.replaceBeforeLast\n","base.replaceAfterLast":"\nbase.replaceAfterLast( str, search, replacement, fromIndex )\n    Replaces the substring after the last occurrence of a specified search\n    string.\n\n    If unable to find a search string, the function returns the input string\n    unchanged.\n\n    The function scans an input string from the starting index to the beginning\n    of the string (i.e., backward).\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search string.\n\n    replacement: string\n        Replacement string.\n\n    fromIndex: integer\n        Starting index (inclusive). If less than zero, the starting index is\n        resolved relative to the last string character, with the last string\n        character corresponding to `fromIndex = -1`.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var str = 'beep boop';\n    > var out = base.replaceAfterLast( str, ' ', 'foo', str.length )\n    'beep foo'\n    > out = base.replaceAfterLast( str, 'o', 'foo', str.length )\n    'beep boofoo'\n    > out = base.replaceAfterLast( 'Hello World!', 'o', 'foo', 5 )\n    'Hellofoo'\n\n    See Also\n    --------\n    base.replaceAfter, base.replaceBeforeLast, base.replaceBefore\n","base.replaceBefore":"\nbase.replaceBefore( str, search, replacement, fromIndex )\n    Replaces the substring before the first occurrence of a specified search\n    string.\n\n    If unable to find a search string, the function returns the input string\n    unchanged.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search string.\n\n    replacement: string\n        Replacement string.\n\n    fromIndex: integer\n        Starting index (inclusive). If less than zero, the starting index is\n        resolved relative to the last string character, with the last string\n        character corresponding to `fromIndex = -1`.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.replaceBefore( 'beep boop', ' ', 'foo', 0 )\n    'foo boop'\n    > out = base.replaceBefore( 'beep boop', 'o', 'foo', 0 )\n    'foooop'\n\n    See Also\n    --------\n    base.replaceAfter, base.replaceBeforeLast, base.replaceAfterLast\n","base.replaceBeforeLast":"\nbase.replaceBeforeLast( str, search, replacement, fromIndex )\n    Replaces the substring before the last occurrence of a specified search\n    string.\n\n    If unable to find a search string, the function returns the input string\n    unchanged.\n\n    The function scans an input string from the starting index to the beginning\n    of the string (i.e., backward).\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search string.\n\n    replacement: string\n        Replacement string.\n\n    fromIndex: integer\n        Starting index (inclusive). If less than zero, the starting index is\n        resolved relative to the last string character, with the last string\n        character corresponding to `fromIndex = -1`.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var str = 'beep boop';\n    > var out = base.replaceBeforeLast( str, ' ', 'foo', str.length )\n    'foo boop'\n    > out = base.replaceBeforeLast( str, 'o', 'foo', str.length )\n    'fooop'\n    > out = base.replaceBeforeLast( 'Hello World!', 'o', 'foo', 5 )\n    'fooo World!'\n\n    See Also\n    --------\n    base.replaceAfterLast, base.replaceAfter, base.replaceBefore\n","base.reverse":"\nbase.reverse( str )\n    Reverses the UTF-16 code units of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.reverse( 'beep' )\n    'peeb'\n    > out = base.reverse( 'Boop' )\n    'pooB'\n    > out = base.reverse( 'foo bar' )\n    'rab oof'\n\n    See Also\n    --------\n    base.reverseCodePoints, base.reverseGraphemeClusters\n","base.reverseCodePoints":"\nbase.reverseCodePoints( str )\n    Reverses the Unicode code points of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.reverseCodePoints( 'beep' )\n    'peeb'\n    > out = base.reverseCodePoints( 'Boop' )\n    'pooB'\n    > out = base.reverseCodePoints( 'foo bar' )\n    'rab oof'\n\n    See Also\n    --------\n    base.reverseGraphemeClusters, base.reverse\n","base.reverseGraphemeClusters":"\nbase.reverseGraphemeClusters( str )\n    Reverses the grapheme clusters (i.e., user-perceived characters) of a\n    string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = base.reverseGraphemeClusters( 'beep' )\n    'peeb'\n    > out = base.reverseGraphemeClusters( 'Boop' )\n    'pooB'\n    > out = base.reverseGraphemeClusters( 'foo bar' )\n    'rab oof'\n\n    See Also\n    --------\n    base.reverseCodePoints, base.reverse\n","base.rightPad":"\nbase.rightPad( str, len, pad )\n    Right pads a string such that the padded string has a length of at least\n    `len`.\n\n    An output string is not guaranteed to have a length of exactly `len`, but to\n    have a length of at least `len`. To generate a padded string having a length\n    equal to `len`, post-process a padded string by trimming off excess\n    characters.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    len: integer\n        Minimum string length.\n\n    pad: string\n        String used to pad.\n\n    Returns\n    -------\n    out: string\n        Padded string.\n\n    Examples\n    --------\n    > var out = base.rightPad( 'a', 5, ' ' )\n    'a    '\n    > out = base.rightPad( 'beep', 10, 'b' )\n    'beepbbbbbb'\n    > out = base.rightPad( 'boop', 12, 'beep' )\n    'boopbeepbeep'\n\n    See Also\n    --------\n    base.leftPad\n","base.rightTrim":"\nbase.rightTrim( str )\n    Trims whitespace from the end of a string.\n\n    \"Whitespace\" is defined as the following characters:\n\n    - \\f\n    - \\n\n    - \\r\n    - \\t\n    - \\v\n    - \\u0020\n    - \\u00a0\n    - \\u1680\n    - \\u2000-\\u200a\n    - \\u2028\n    - \\u2029\n    - \\u202f\n    - \\u205f\n    - \\u3000\n    - \\ufeff\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Trimmed string.\n\n    Examples\n    --------\n    > var out = base.rightTrim( ' \\t\\t\\n  Beep \\r\\n\\t  ' )\n    ' \\t\\t\\n  Beep'\n\n    See Also\n    --------\n    base.leftTrim\n","base.risingFactorial":"\nbase.risingFactorial( x, n )\n    Computes the rising factorial of `x` and `n`.\n\n    If provided a non-integer for `n`, the function returns `NaN`.\n\n    If provided `NaN` as any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        First function parameter.\n\n    n: integer\n        Second function parameter.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var v = base.risingFactorial( 0.9, 5 )\n    ~94.766\n    > v = base.risingFactorial( -9.0, 3 )\n    -504.0\n    > v = base.risingFactorial( 0.0, 2 )\n    0.0\n    > v = base.risingFactorial( 3.0, -2 )\n    0.5\n\n    See Also\n    --------\n    base.fallingFactorial\n","base.rotl32":"\nbase.rotl32( x, shift )\n    Performs a bitwise rotation to the left.\n\n    If `shift = 0`, the function returns `x`.\n\n    If `shift >= 32`, the function only considers the five least significant\n    bits of `shift` (i.e., `shift % 32`).\n\n    Parameters\n    ----------\n    x: integer\n        Unsigned 32-bit integer.\n\n    shift: integer\n        Number of bits to shift.\n\n    Returns\n    -------\n    out: integer\n        Unsigned 32-bit integer.\n\n    Examples\n    --------\n    > var x = 2147483649;\n    > var bStr = base.toBinaryStringUint32( x )\n    '10000000000000000000000000000001'\n    > var y = base.rotl32( x, 10 )\n    1536\n    > bstr = base.toBinaryStringUint32( y )\n    '00000000000000000000011000000000'\n\n    See Also\n    --------\n    base.rotr32\n","base.rotr32":"\nbase.rotr32( x, shift )\n    Performs a bitwise rotation to the right.\n\n    If `shift = 0`, the function returns `x`.\n\n    If `shift >= 32`, the function only considers the five least significant\n    bits of `shift` (i.e., `shift % 32`).\n\n    Parameters\n    ----------\n    x: integer\n        Unsigned 32-bit integer.\n\n    shift: integer\n        Number of bits to shift.\n\n    Returns\n    -------\n    out: integer\n        Unsigned 32-bit integer.\n\n    Examples\n    --------\n    > var x = 1;\n    > var bStr = base.toBinaryStringUint32( x )\n    '00000000000000000000000000000001'\n    > var y = base.rotr32( x, 10 )\n    4194304\n    > bstr = base.toBinaryStringUint32( y )\n    '00000000010000000000000000000000'\n\n    See Also\n    --------\n    base.rotl32\n","base.round":"\nbase.round( x )\n    Rounds a numeric value to the nearest integer.\n\n    Ties are rounded toward positive infinity.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.round( 3.14 )\n    3.0\n    > y = base.round( -4.2 )\n    -4.0\n    > y = base.round( -4.6 )\n    -5.0\n    > y = base.round( 9.5 )\n    10.0\n    > y = base.round( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceil, base.floor, base.roundn, base.trunc\n","base.round2":"\nbase.round2( x )\n    Rounds a numeric value to the nearest power of two on a linear scale.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.round2( 3.14 )\n    4.0\n    > y = base.round2( -4.2 )\n    -4.0\n    > y = base.round2( -4.6 )\n    -4.0\n    > y = base.round2( 9.5 )\n    8.0\n    > y = base.round2( 13.0 )\n    16.0\n    > y = base.round2( -13.0 )\n    -16.0\n    > y = base.round2( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceil2, base.floor2, base.round, base.round10\n","base.round10":"\nbase.round10( x )\n    Rounds a numeric value to the nearest power of ten on a linear scale.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.round10( 3.14 )\n    1.0\n    > y = base.round10( -4.2 )\n    -1.0\n    > y = base.round10( -4.6 )\n    -1.0\n    > y = base.round10( 9.5 )\n    10.0\n    > y = base.round10( 13.0 )\n    10.0\n    > y = base.round10( -13.0 )\n    -10.0\n    > y = base.round10( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceil10, base.floor10, base.round, base.round2\n","base.roundb":"\nbase.roundb( x, n, b )\n    Rounds a numeric value to the nearest multiple of `b^n` on a linear scale.\n\n    Due to floating-point rounding error, rounding may not be exact.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Integer power.\n\n    b: integer\n        Base.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    // Round to 2 decimal places:\n    > var y = base.roundb( 3.14159, -2, 10 )\n    3.14\n\n    // If `n = 0` or `b = 1`, standard round behavior:\n    > y = base.roundb( 3.14159, 0, 2 )\n    3.0\n\n    // Round to nearest multiple of two:\n    > y = base.roundb( 5.0, 1, 2 )\n    6.0\n\n    See Also\n    --------\n    base.ceilb, base.floorb, base.round, base.roundn\n","base.roundn":"\nbase.roundn( x, n )\n    Rounds a numeric value to the nearest multiple of `10^n`.\n\n    When operating on floating-point numbers in bases other than `2`, rounding\n    to specified digits can be inexact.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Integer power of 10.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    // Round to 2 decimal places:\n    > var y = base.roundn( 3.14159, -2 )\n    3.14\n\n    // If `n = 0`, standard round behavior:\n    > y = base.roundn( 3.14159, 0 )\n    3.0\n\n    // Round to nearest thousand:\n    > y = base.roundn( 12368.0, 3 )\n    12000.0\n\n\n    See Also\n    --------\n    base.ceiln, base.floorn, base.round, base.roundb\n","base.roundsd":"\nbase.roundsd( x, n[, b] )\n    Rounds a numeric value to the nearest number with `n` significant figures.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Number of significant figures. Must be greater than 0.\n\n    b: integer (optional)\n        Base. Must be greater than 0. Default: 10.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.roundsd( 3.14159, 3 )\n    3.14\n    > y = base.roundsd( 3.14159, 1 )\n    3.0\n    > y = base.roundsd( 12368.0, 2 )\n    12000.0\n    > y = base.roundsd( 0.0313, 2, 2 )\n    0.03125\n\n    See Also\n    --------\n    base.ceilsd, base.floorsd, base.round, base.truncsd\n","base.rsqrt":"\nbase.rsqrt( x )\n    Computes the reciprocal square root of a double-precision floating-point\n    number.\n\n    For `x < 0`, the reciprocal square root is not defined.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Reciprocal square root.\n\n    Examples\n    --------\n    > var y = base.rsqrt( 4.0 )\n    0.5\n    > y = base.rsqrt( 100.0 )\n    0.1\n    > y = base.rsqrt( 0.0 )\n    Infinity\n    > y = base.rsqrt( Infinity )\n    0.0\n    > y = base.rsqrt( -4.0 )\n    NaN\n    > y = base.rsqrt( NaN )\n    NaN\n\n    See Also\n    --------\n    base.sqrt\n","base.rsqrtf":"\nbase.rsqrtf( x )\n    Computes the reciprocal square root of a single-precision floating-point\n    number.\n\n    For `x < 0`, the reciprocal square root is not defined.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Reciprocal square root.\n\n    Examples\n    --------\n    > var y = base.rsqrtf( 4.0 )\n    0.5\n    > y = base.rsqrtf( 0.0 )\n    Infinity\n    > y = base.rsqrtf( Infinity )\n    0.0\n    > y = base.rsqrtf( -4.0 )\n    NaN\n    > y = base.rsqrtf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.rsqrt, base.sqrtf\n","base.sargs2multislice":"\nbase.sargs2multislice( str )\n    Creates a MultiSlice object from a comma-separated list of string-serialized\n    MultiSlice constructor arguments.\n\n    The function returns `null` if provided an invalid string.\n\n    Parameters\n    ----------\n    str: string\n        Input string containing constructor arguments.\n\n    Returns\n    -------\n    s: MultiSlice|null\n        MultiSlice instance (or null).\n\n    Examples\n    --------\n    > var s = new base.sargs2multislice( 'null,null,null' );\n    > s.data\n    [ null, null, null ]\n    > s = new base.sargs2multislice( '10,Slice(0,10,1),null' );\n    > s.data\n    [ 10, <Slice>, null ]\n\n    See Also\n    --------\n    base.args2multislice, base.seq2multislice\n","base.scalar2ndarray":"\nbase.scalar2ndarray( value, dtype, order )\n    Returns a zero-dimensional ndarray containing a provided scalar value.\n\n    If `value` is a number and `dtype` is a complex number data type, the\n    function returns a zero-dimensional ndarray containing a complex number\n    whose real component equals the provided scalar value and whose imaginary\n    component is zero.\n\n    Parameters\n    ----------\n    value: any\n        Scalar value.\n\n    dtype: string\n        Data type.\n\n    order: string\n        Memory layout (either 'row-major' or 'column-major').\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var x = base.scalar2ndarray( 1.0, 'float64', 'row-major' )\n    <ndarray>\n    > var sh = x.shape\n    []\n    > var dt = x.dtype\n    'float64'\n    > var v = x.get()\n    1.0\n\n    See Also\n    --------\n    array, base.ndarray, ndarray\n","base.secd":"\nbase.secd( x )\n    Computes the secant of an angle measured in degrees.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in degrees).\n\n    Returns\n    -------\n    y: number\n        Secant.\n\n    Examples\n    --------\n    > var y = base.secd( 1.0 )\n    ~1.0\n    > y = base.secd( PI )\n    ~1.0\n    > y = base.secd( -PI )\n    ~1.0\n    > y = base.secd( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cosd, base.cos\n","base.seq2multislice":"\nbase.seq2multislice( str, shape, strict )\n    Converts a multidimensional subsequence string to a MultiSlice object.\n\n    A multidimensional subsequence string is a comma-separated list of single-\n    dimension indexing expressions (i.e., integers and/or subsequence strings).\n\n    For example, the following\n\n      2\n      :\n      2:\n      :10\n      2:10\n      ::-1\n      10:2:-1\n      :2:\n      2:10:\n      2::2\n      :10:2\n      :, :, :\n      1, 2, 3\n      0:10, 1:20:2, ::-1\n      ...\n      :, ..., 2\n\n    are all valid multidimensional subsequence strings.\n\n    Providing a single nonnegative integer `i` as a single-dimension index\n    indexes the same elements as the subsequence `i:i+1`.\n\n    Providing a single negative integer `i` as a single-dimension index indexes\n    the same elements as the subsequence `n+i:n+i+i`, where `n` is the dimension\n    size.\n\n    While integers index the same elements as equivalent subsequences, providing\n    an integer as a single-dimension index indicates to reduce the number of\n    dimensions by one (e.g., if the provided shape corresponds to an array\n    having rank 2, then rank(A)-1 == rank(A['0,:'])).\n\n    In contrast, providing a subsequence indicates to retain a respective\n    dimension (e.g., if the provided shape corresponds to an array having rank\n    2, then rank(A) == rank(A[':,:'])).\n\n    A multidimensional subsequence string can only contain **one** ellipsis\n    ('...') operator. An ellipsis indicates to apply ':' to each dimension\n    necessary to index all dimensions (e.g., if A has rank 4, A['1:,...,2:5']\n    equals A['1:,:,:,2:5']).\n\n    Except in the case of providing a single ellipsis, the number of single-\n    dimension indexing expressions must equal the number of dimensions in the\n    input shape.\n\n    The function returns an error object if provided an invalid subsequence\n    string.\n\n    In strict mode, the function returns an error object if a single-dimension\n    index expression which exceeds index bounds.\n\n    A returned error object is a plain object having the following properties:\n\n    - code: error code.\n\n    A returned error object may have one of the following error codes:\n\n    - ERR_SLICE_INVALID_SUBSEQUENCE: a subsequence string is invalid.\n    - ERR_SLICE_INVALID_INCREMENT: a subsequence string must have a non-zero\n      increment.\n    - ERR_SLICE_OUT_OF_BOUNDS: a subsequence string resolves to a slice\n      exceeding index bounds.\n    - ERR_SLICE_TOO_MANY_DIMENSIONS: a subsequence string has more dimensions\n      than the provided shape.\n    - ERR_SLICE_INSUFFICIENT_DIMENSIONS: a subsequence string has too few\n      dimensions.\n    - ERR_SLICE_INVALID_ELLIPSIS: a subsequence string must only contain at most\n      one ellipsis.\n\n    Parameters\n    ----------\n    str: string\n        Subsequence string.\n\n    shape: Array<integer>\n        Maximum allowed slice shape.\n\n    strict: boolean\n        Boolean indicating whether to enforce strict bounds checking.\n\n    Returns\n    -------\n    s: MultiSlice|Object\n        MultiSlice instance or an error object.\n\n    Examples\n    --------\n    > var s = new base.seq2multislice( '1:10', [ 10 ], false );\n    > s.data\n    [ <Slice> ]\n    > s = new base.seq2multislice( '4,2:5:2,:', [ 10, 10, 10 ], false );\n    > s.data\n    [ 4, <Slice>, <Slice> ]\n\n    See Also\n    --------\n    base.seq2slice, base.sargs2multislice\n","base.seq2slice":"\nbase.seq2slice( str, len, strict )\n    Converts a subsequence string to a Slice object.\n\n    A subsequence string has the following format:\n\n      <start>:<stop>:<increment>\n\n    If an increment is not specified, the default increment is one. An increment\n    of zero is not allowed.\n\n    The start index is inclusive.\n\n    The stop index is exclusive.\n\n    Both start and stop indices are optional. If not provided, the start and\n    stop indices default to index extremes. Which extremes correspond to which\n    index depends on whether the increment is positive or negative.\n\n    Both start and stop indices can be negative; in which case, the\n    corresponding index is resolved by subtracting the respective value from the\n    provided length.\n\n    Both start and stop indices can use the 'end' keyword (e.g., 'end-2::2',\n    'end-3:', etc), which supports basic subtraction and division.\n\n    The 'end' keyword resolves to the provided length. Thus, ':-1' is equivalent\n    to ':end-1', ':-2' is equivalent to ':end-2', and so on and so forth. The\n    exception is when performing a division operation when the increment is less\n    than zero; in which case, 'end' is equal to 'len-1' in order to preserve\n    user expectations when 'end/d' equals a whole number and slicing from right-\n    to-left. The result from a division operation is rounded down to the nearest\n    integer value.\n\n    In non-strict mode, the resolved slice start is clamped to the slice index\n    bounds [0, len).\n\n    In non-strict mode, Tte resolved slice end is upper bound clamped to the\n    provided length (i.e., one greater than the last possible index).\n\n    When the increment is negative, the resolved slice end value may be `null`,\n    thus indicating that a non-empty slice should include the first index.\n\n    The function ensures that results satisfy the convention that ':n' combined\n    with 'n:' is equivalent to ':' (i.e., selecting all elements).\n\n    When the provided length is zero, the function always returns a slice object\n    equivalent to '0:0:<increment>'.\n\n    The function returns an error object if provided an invalid subsequence\n    string.\n\n    In strict mode, the function returns an error object if provided a\n    subsequence string which exceeds index bounds.\n\n    A returned error object is a plain object having the following properties:\n\n    - code: error code.\n\n    A returned error object may have one of the following error codes:\n\n    - ERR_SLICE_INVALID_SUBSEQUENCE: a subsequence string is invalid.\n    - ERR_SLICE_INVALID_INCREMENT: a subsequence string must have a non-zero\n      increment.\n    - ERR_SLICE_OUT_OF_BOUNDS: a subsequence string resolves to a slice\n      exceeding index bounds.\n\n    Parameters\n    ----------\n    str: string\n        Subsequence string.\n\n    len: integer\n        Maximum number of elements allowed in the slice.\n\n    strict: boolean\n        Boolean indicating whether to enforce strict bounds checking.\n\n    Returns\n    -------\n    s: Slice|Object\n        Slice instance or an error object.\n\n    Examples\n    --------\n    > var s = new base.seq2slice( '1:10', 10, false );\n    > s.start\n    1\n    > s.stop\n    10\n    > s.step\n    1\n    > s = new base.seq2slice( '2:5:2', 10, false );\n    > s.start\n    2\n    > s.stop\n    5\n    > s.step\n    2\n\n    See Also\n    --------\n    base.seq2multislice, base.slice2seq\n","base.setHighWord":"\nbase.setHighWord( x, high )\n    Sets the more significant 32 bits of a double-precision floating-point\n    number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    high: integer\n        Unsigned 32-bit integer to replace the higher order word of `x`.\n\n    Returns\n    -------\n    out: number\n        Double having the same lower order word as `x`.\n\n    Examples\n    --------\n    // Set the higher order bits of `+infinity` to return `1`:\n    > var high = 1072693248 >>> 0;\n    > var y = base.setHighWord( PINF, high )\n    1.0\n\n    See Also\n    --------\n    base.getHighWord, base.setLowWord\n","base.setLowWord":"\nbase.setLowWord( x, low )\n    Sets the less significant 32 bits of a double-precision floating-point\n    number.\n\n    Setting the lower order bits of `NaN` or positive or negative infinity will\n    return `NaN`, as `NaN` is defined as a double whose exponent bit sequence is\n    all ones and whose fraction can be any bit sequence except all zeros.\n    Positive and negative infinity are defined as doubles with an exponent bit\n    sequence equal to all ones and a fraction equal to all zeros. Hence,\n    changing the less significant bits of positive and negative infinity\n    converts each value to `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    low: integer\n        Unsigned 32-bit integer to replace the lower order word of `x`.\n\n    Returns\n    -------\n    out: number\n        Double having the same higher order word as `x`.\n\n    Examples\n    --------\n    > var low = 5 >>> 0;\n    > var x = 3.14e201;\n    > var y = base.setLowWord( x, low )\n    3.139998651394392e+201\n\n    // Special cases:\n    > var low = 12345678;\n    > var y = base.setLowWord( PINF, low )\n    NaN\n    > y = base.setLowWord( NINF, low )\n    NaN\n    > y = base.setLowWord( NaN, low )\n    NaN\n\n    See Also\n    --------\n    base.getLowWord, base.setHighWord\n","base.sici":"\nbase.sici( x )\n    Computes the sine and cosine integrals.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    out: Array<number>\n        Sine and cosine integrals.\n\n    Examples\n    --------\n    > var y = base.sici( 3.0 )\n    [ ~1.849, ~0.12 ]\n    > y = base.sici( 0.0 )\n    [ 0.0, -Infinity ]\n    > y = base.sici( -9.0 )\n    [ ~-1.665, ~0.055 ]\n    > y = base.sici( NaN )\n    [ NaN, NaN ]\n\n\nbase.sici.assign( x, out, stride, offset )\n    Computes the sine and cosine integrals and assigns results to a provided\n    output array.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Sine and cosine integrals.\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var y = base.sici.assign( 3.0, out, 1, 0 )\n    <Float64Array>[ ~1.849, ~0.12 ]\n    > var bool = ( y === out )\n    true\n","base.sici.assign":"\nbase.sici.assign( x, out, stride, offset )\n    Computes the sine and cosine integrals and assigns results to a provided\n    output array.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Sine and cosine integrals.\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var y = base.sici.assign( 3.0, out, 1, 0 )\n    <Float64Array>[ ~1.849, ~0.12 ]\n    > var bool = ( y === out )\n    true","base.signbit":"\nbase.signbit( x )\n    Returns a boolean indicating if the sign bit is on (true) or off (false).\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if sign bit is on or off.\n\n    Examples\n    --------\n    > var bool = base.signbit( 4.0 )\n    false\n    > bool = base.signbit( -9.14e-34 )\n    true\n    > bool = base.signbit( 0.0 )\n    false\n    > bool = base.signbit( -0.0 )\n    true\n\n    See Also\n    --------\n    base.signbitf\n","base.signbitf":"\nbase.signbitf( x )\n    Returns a boolean indicating if the sign bit is on (true) or off (false).\n\n    Parameters\n    ----------\n    x: float\n        Single-precision floating-point number.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if sign bit is on or off.\n\n    Examples\n    --------\n    > var bool = base.signbitf( base.float64ToFloat32( 4.0 ) )\n    false\n    > bool = base.signbitf( base.float64ToFloat32( -9.14e-34 ) )\n    true\n    > bool = base.signbitf( 0.0 )\n    false\n    > bool = base.signbitf( -0.0 )\n    true\n\n    See Also\n    --------\n    base.signbit\n","base.significandf":"\nbase.significandf( x )\n    Returns an integer corresponding to the significand of a single-precision\n    floating-point number.\n\n    Parameters\n    ----------\n    x: float\n        Single-precision floating-point number.\n\n    Returns\n    -------\n    out: integer\n        Significand.\n\n    Examples\n    --------\n    > var s = base.significandf( base.float64ToFloat32( 3.14e34 ) )\n    4293751\n    > s = base.significandf( base.float64ToFloat32( 3.14e-34 ) )\n    5288021\n    > s = base.significandf( base.float64ToFloat32( -3.14 ) )\n    4781507\n    > s = base.significandf( 0.0 )\n    0\n    > s = base.significandf( NaN )\n    4194304\n\n","base.signum":"\nbase.signum( x )\n    Evaluates the signum function for a double-precision floating-point number.\n\n    Value | Sign\n    ----- | -----\n    x > 0 |    +1\n    x < 0 |    -1\n        0 |     0\n       -0 |    -0\n      NaN |   NaN\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    sign: number\n        Function value.\n\n    Examples\n    --------\n    > var sign = base.signum( -5.0 )\n    -1.0\n    > sign = base.signum( 5.0 )\n    1.0\n    > sign = base.signum( -0.0 )\n    -0.0\n    > sign = base.signum( 0.0 )\n    0.0\n    > sign = base.signum( NaN )\n    NaN\n\n","base.signumf":"\nbase.signumf( x )\n    Evaluates the signum function for a single-precision floating-point number.\n\n    Value | Sign\n    ----- | -----\n    x > 0 |    +1\n    x < 0 |    -1\n        0 |     0\n       -0 |    -0\n      NaN |   NaN\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    sign: number\n        Function value.\n\n    Examples\n    --------\n    > var sign = base.signumf( -5.0 )\n    -1.0\n    > sign = base.signumf( 5.0 )\n    1.0\n    > sign = base.signumf( -0.0 )\n    -0.0\n    > sign = base.signumf( 0.0 )\n    0.0\n    > sign = base.signumf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.signum\n","base.sin":"\nbase.sin( x )\n    Computes the sine of a number.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Sine.\n\n    Examples\n    --------\n    > var y = base.sin( 0.0 )\n    ~0.0\n    > y = base.sin( PI/2.0 )\n    ~1.0\n    > y = base.sin( -PI/6.0 )\n    ~-0.5\n    > y = base.sin( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cos, base.sinpi, base.tan\n","base.sinc":"\nbase.sinc( x )\n    Computes the normalized cardinal sine of a number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Cardinal sine.\n\n    Examples\n    --------\n    > var y = base.sinc( 0.5 )\n    ~0.637\n    > y = base.sinc( -1.2 )\n    ~-0.156\n    > y = base.sinc( 0.0 )\n    1.0\n    > y = base.sinc( NaN )\n    NaN\n\n    See Also\n    --------\n    base.sin\n","base.sincos":"\nbase.sincos( x )\n    Simultaneously computes the sine and cosine of a number.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: Array<number>\n        Sine and cosine.\n\n    Examples\n    --------\n    > var y = base.sincos( 0.0 )\n    [ ~0.0, ~1.0 ]\n    > y = base.sincos( PI/2.0 )\n    [ ~1.0, ~0.0 ]\n    > y = base.sincos( -PI/6.0 )\n    [ ~-0.5, ~0.866 ]\n    > y = base.sincos( NaN )\n    [ NaN, NaN ]\n\n\nbase.sincos( x, out, stride, offset )\n    Simultaneously computes the sine and cosine of a number and assigns\n    results to a provided output array.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Sine and cosine.\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var v = base.sincos.assign( 0.0, out, 1, 0 )\n    <Float64Array>[ ~0.0, ~1.0 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.cos, base.sin, base.sincospi","base.sincospi":"\nbase.sincospi( x )\n    Simultaneously computes the sine and cosine of a number times π.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: Array<number>\n        Two-element array containing sin(πx) and cos(πx).\n\n    Examples\n    --------\n    > var y = base.sincospi( 0.0 )\n    [ 0.0, 1.0 ]\n    > y = base.sincospi( 0.5 )\n    [ 1.0, 0.0 ]\n    > y = base.sincospi( 0.1 )\n    [ ~0.309, ~0.951 ]\n    > y = base.sincospi( NaN )\n    [ NaN, NaN ]\n\n\nbase.sincospi.assign( x, out, stride, offset )\n    Simultaneously computes the sine and cosine of a number times π and\n    assigns results to a provided output array.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Two-element array containing sin(πx) and cos(πx).\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var v = base.sincospi.assign( 0.0, out, 1, 0 )\n    <Float64Array>[ 0.0, 1.0 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.cospi, base.sincos, base.sinpi","base.sincospi.assign":"\nbase.sincospi.assign( x, out, stride, offset )\n    Simultaneously computes the sine and cosine of a number times π and\n    assigns results to a provided output array.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Two-element array containing sin(πx) and cos(πx).\n\n    Examples\n    --------\n    > var out = new Float64Array( 2 );\n    > var v = base.sincospi.assign( 0.0, out, 1, 0 )\n    <Float64Array>[ 0.0, 1.0 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.cospi, base.sincos, base.sinpi","base.sinh":"\nbase.sinh( x )\n    Computes the hyperbolic sine of a double-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Hyperbolic sine.\n\n    Examples\n    --------\n    > var y = base.sinh( 0.0 )\n    0.0\n    > y = base.sinh( 2.0 )\n    ~3.627\n    > y = base.sinh( -2.0 )\n    ~-3.627\n    > y = base.sinh( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cosh, base.sin, base.tanh\n","base.sinpi":"\nbase.sinpi( x )\n    Computes the value of `sin(πx)`.\n\n    The function computes `sin(πx)` more accurately than the obvious approach,\n    especially for large `x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.sinpi( 0.0 )\n    0.0\n    > y = base.sinpi( 0.5 )\n    1.0\n    > y = base.sinpi( 0.9 )\n    ~0.309\n    > y = base.sinpi( NaN )\n    NaN\n\n    See Also\n    --------\n    base.sin\n","base.slice2seq":"\nbase.slice2seq( slice )\n    Converts a Slice object to a subsequence string.\n\n    Parameters\n    ----------\n    slice: Slice\n        Input slice.\n\n    Returns\n    -------\n    out: string\n        Subsequence string.\n\n    Examples\n    --------\n    > var out = base.slice2seq( new Slice( 1, 10, 1 ) )\n    '1:10:1'\n    > out = base.slice2seq( new Slice( null, 10 ) )\n    ':10'\n\n    See Also\n    --------\n    base.seq2slice\n","base.sliceLength":"\nbase.sliceLength( slice )\n    Returns the number of elements in a normalized slice.\n\n    Parameters\n    ----------\n    slice: Slice\n        Input normalized slice object.\n\n    Returns\n    -------\n    len: integer\n        Number of elements.\n\n    Examples\n    --------\n    > var s = new Slice( 1, 10, 1 );\n    > base.sliceLength( s )\n    9\n\n    See Also\n    --------\n    base.sliceNonReducedDimensions, base.sliceReducedDimensions, base.sliceShape\n","base.sliceNonReducedDimensions":"\nbase.sliceNonReducedDimensions( slice )\n    Returns a list of non-reduced dimensions in an un-normalized multi-slice.\n\n    Parameters\n    ----------\n    slice: MultiSlice\n        Input slice object.\n\n    Returns\n    -------\n    out: Array<integer>\n        Dimension indices.\n\n    Examples\n    --------\n    > var s = new MultiSlice( 1, 3, null );\n    > var out = base.sliceNonReducedDimensions( s )\n    [ 2 ]\n\n    See Also\n    --------\n    base.sliceLength, base.sliceReducedDimensions, base.sliceShape\n","base.sliceReducedDimensions":"\nbase.sliceReducedDimensions( slice )\n    Returns a list of reduced dimensions in an un-normalized multi-slice.\n\n    Parameters\n    ----------\n    slice: MultiSlice\n        Input slice object.\n\n    Returns\n    -------\n    out: Array<integer>\n        Dimension indices.\n\n    Examples\n    --------\n    > var s = new MultiSlice( 1, 3, null );\n    > var out = base.sliceReducedDimensions( s )\n    [ 0, 1 ]\n\n    See Also\n    --------\n    base.sliceLength, base.sliceNonReducedDimensions, base.sliceShape\n","base.sliceShape":"\nbase.sliceShape( slice )\n    Returns the shape of a normalized multi-slice.\n\n    Parameters\n    ----------\n    slice: MultiSlice\n        Input normalized multi-slice object.\n\n    Returns\n    -------\n    sh: Array<integer>\n        Slice shape.\n\n    Examples\n    --------\n    > var s = new Slice( 1, 10, 1 );\n    > var ms = new MultiSlice( s, s );\n    > base.sliceShape( ms )\n    [ 9, 9 ]\n\n    See Also\n    --------\n    base.sliceLength, base.sliceNonReducedDimensions, base.sliceReducedDimensions\n","base.snakecase":"\nbase.snakecase( str )\n    Converts a string to snake case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Snake-cased string.\n\n    Examples\n    --------\n    > var out = base.snakecase( 'Hello World!' )\n    'hello_world'\n    > out = base.snakecase( 'I am a tiny little teapot' )\n    'i_am_a_tiny_little_teapot'\n\n    See Also\n    --------\n    base.camelcase, base.lowercase, base.stickycase, base.uppercase","base.spence":"\nbase.spence( x )\n    Evaluates Spence's function, which is also known as the dilogarithm.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.spence( 3.0 )\n    ~-1.437\n    > y = base.spence( 0.0 )\n    ~1.645\n    > y = base.spence( -9.0 )\n    NaN\n    > y = base.spence( NaN )\n    NaN\n\n","base.sqrt":"\nbase.sqrt( x )\n    Computes the principal square root of a double-precision floating-point\n    number.\n\n    For `x < 0`, the principal square root is not defined.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Principal square root.\n\n    Examples\n    --------\n    > var y = base.sqrt( 4.0 )\n    2.0\n    > y = base.sqrt( 9.0 )\n    3.0\n    > y = base.sqrt( 0.0 )\n    0.0\n    > y = base.sqrt( -4.0 )\n    NaN\n    > y = base.sqrt( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cbrt, base.rsqrt\n","base.sqrt1pm1":"\nbase.sqrt1pm1( x )\n    Computes the principal square root of `1+x` minus one.\n\n    This function is more accurate than the obvious approach for small `x`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Square root of `1+x` minus one.\n\n    Examples\n    --------\n    > var y = base.sqrt1pm1( 3.0 )\n    1.0\n    > y = base.sqrt1pm1( 0.5 )\n    ~0.225\n    > y = base.sqrt1pm1( 0.02 )\n    ~0.01\n    > y = base.sqrt1pm1( -0.5 )\n    ~-0.293\n    > y = base.sqrt1pm1( -1.1 )\n    NaN\n    > y = base.sqrt1pm1( NaN )\n    NaN\n\n    See Also\n    --------\n    base.sqrt\n","base.sqrtf":"\nbase.sqrtf( x )\n    Computes the principal square root of a single-precision floating-point\n    number.\n\n    For `x < 0`, the principal square root is not defined.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Principal square root.\n\n    Examples\n    --------\n    > var y = base.sqrtf( 4.0 )\n    2.0\n    > y = base.sqrtf( 9.0 )\n    3.0\n    > y = base.sqrtf( 0.0 )\n    0.0\n    > y = base.sqrtf( -4.0 )\n    NaN\n    > y = base.sqrtf( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cbrtf, base.rsqrtf, base.sqrt\n","base.sqrtpi":"\nbase.sqrtpi( x )\n    Computes the principal square root of the product of π and a positive\n    double-precision floating-point number.\n\n    For `x < 0`, the square root is not defined.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Principal square root of the product of π and the input value.\n\n    Examples\n    --------\n    > var y = base.sqrtpi( 4.0 )\n    ~3.5449\n    > y = base.sqrtpi( 10.0 )\n    ~5.60499\n    > y = base.sqrtpi( 0.0 )\n    0.0\n    > y = base.sqrtpi( -4.0 )\n    NaN\n    > y = base.sqrtpi( NaN )\n    NaN\n\n    See Also\n    --------\n    base.sqrt","base.startcase":"\nbase.startcase( str )\n    Capitalizes the first letter of each word in an input string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        String containing words where each first letter is capitalized.\n\n    Examples\n    --------\n    > var out = base.startcase( 'beep boop' )\n    'Beep Boop'\n\n    See Also\n    --------\n    base.capitalize, base.lowercase, base.uppercase\n","base.startsWith":"\nbase.startsWith( str, search, position )\n    Tests if a string starts with the characters of another string.\n\n    If provided an empty search string, the function always returns `true`.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search string.\n\n    position: integer\n        Position at which to start searching for `search`. If less than `0`, the\n        start position is determined relative to the end of the input string.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a string starts with the characters of\n        another string.\n\n    Examples\n    --------\n    > var bool = base.startsWith( 'Beep', 'Be', 0 )\n    true\n    > bool = base.startsWith( 'Beep', 'ep', 0 )\n    false\n    > bool = base.startsWith( 'Beep', 'ee', 1 )\n    true\n    > bool = base.startsWith( 'Beep', 'ee', -3 )\n    true\n    > bool = base.startsWith( 'Beep', '', 0 )\n    true\n\n    See Also\n    --------\n    base.endsWith\n","base.stickycase":"\nbase.stickycase( str[, p] )\n    Converts a string to sticky case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n \n    p: number\n        Probability of capitalization.\n\n    Returns\n    -------\n    out: string\n        Sticky-cased string.\n\n    Examples\n    --------\n    > var out = base.stickycase( 'Hello World!' )\n    <string>\n\n    > out = base.stickycase( 'I am a tiny little teapot' )\n    <string>\n    See Also\n    --------\n    base.camelcase, base.lowercase, base.snakecase, base.uppercase\n","base.strided.binary":"\nbase.strided.binary( arrays, shape, strides, fcn )\n    Applies a binary callback to strided input array elements and assigns\n    results to elements in a strided output array.\n\n    The `shape` and `strides` parameters determine which elements in the strided\n    input and output arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing two strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    fcn: Function\n        Binary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1 ];\n    > function f( x, y ) { return x + y; };\n    > base.strided.binary( [ x, y, z ], shape, strides, f );\n    > z\n    <Float64Array>[ 2.0, 4.0, 6.0, 8.0 ]\n\n\nbase.strided.binary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a binary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing two strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Binary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1 ];\n    > var offsets = [ 0, 0, 0 ];\n    > function f( x, y ) { return x + y; };\n    > base.strided.binary.ndarray( [ x, y, z ], shape, strides, offsets, f );\n    > z\n    <Float64Array>[ 2.0, 4.0, 6.0, 8.0 ]\n\n    See Also\n    --------\n    base.strided.dmap2, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap2, base.strided.ternary, base.strided.unary\n","base.strided.binary.ndarray":"\nbase.strided.binary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a binary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing two strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Binary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1 ];\n    > var offsets = [ 0, 0, 0 ];\n    > function f( x, y ) { return x + y; };\n    > base.strided.binary.ndarray( [ x, y, z ], shape, strides, offsets, f );\n    > z\n    <Float64Array>[ 2.0, 4.0, 6.0, 8.0 ]\n\n    See Also\n    --------\n    base.strided.dmap2, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap2, base.strided.ternary, base.strided.unary","base.strided.binaryDtypeSignatures":"\nbase.strided.binaryDtypeSignatures( dtypes1, dtypes2, dtypes3[, options] )\n    Generates a list of binary interface signatures from strided array data\n    types.\n\n    The function returns a strided array having a stride length of `3` (i.e.,\n    every `3` elements define a binary interface signature).\n\n    For each signature (i.e., set of three consecutive non-overlapping strided\n    array elements), the first two elements are the input data types and the\n    third element is the return data type.\n\n    All signatures follow type promotion rules.\n\n    Parameters\n    ----------\n    dtypes1: ArrayLike<any>\n        List of supported data types for the first input argument.\n\n    dtypes2: ArrayLike<any>\n        List of supported data types for the second input argument.\n\n    dtypes3: ArrayLike<any>\n        List of supported data types for the output value.\n\n    options: Object (optional)\n        Options.\n\n    options.enums: boolean (optional)\n        Boolean flag indicating whether to return signatures as a list of data\n        type enumeration constants. Default: false.\n\n    Returns\n    -------\n    out: Array\n        Strided array containing binary interface signatures.\n\n    Examples\n    --------\n    > var dt = strided.dataTypes();\n    > var out = base.strided.binaryDtypeSignatures( dt, dt, dt )\n    [...]\n\n    See Also\n    --------\n    base.strided.binarySignatureCallbacks\n","base.strided.binarySignatureCallbacks":"\nbase.strided.binarySignatureCallbacks( table, signatures )\n    Assigns callbacks to binary interfaces according to type promotion rules.\n\n    Parameters\n    ----------\n    table: Object\n        Object mapping callbacks to data types.\n\n    table.default: Function\n        Default callback.\n\n    table.complex64: Function\n        Callback to be invoked when input arrays promote to single-precision\n        complex floating-point numbers.\n\n    table.complex128: Function\n        Callback to be invoked when input arrays promote to double precision\n        complex floating-point numbers.\n\n    signatures: ArrayLike<any>\n        Strided array containing binary interface signatures.\n\n    Returns\n    -------\n    out: Array<Function>\n        List of callbacks, one per signature.\n\n    Examples\n    --------\n    > var dt = strided.dataTypes();\n    > var sigs = base.strided.binaryDtypeSignatures( dt, dt, dt );\n    > var t = {\n    ...     'default': base.add,\n    ...     'complex64': base.caddf,\n    ...     'complex128': base.cadd\n    ... };\n    > var out = base.strided.binarySignatureCallbacks( t, sigs )\n    [...]\n\n    See Also\n    --------\n    base.strided.binaryDtypeSignatures\n","base.strided.ccopy":"\nbase.strided.ccopy( N, x, strideX, y, strideY )\n    Copies values from one complex single-precision floating-point vector to\n    another complex single-precision floating-point vector.\n\n    The `N` and stride parameters determine how values from `x` are copied into\n    `y`.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Complex64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Complex64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n    > base.strided.ccopy( x.length, x, 1, y, 1 );\n    > var z = y.get( 0 );\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    2.0\n\n    // Advanced indexing:\n    > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n    > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.ccopy( 2, x, -2, y, 1 );\n    > z = y.get( 0 );\n    > re = realf( z )\n    5.0\n    > im = imagf( z )\n    6.0\n\n    // Using typed array views:\n    > var x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n    > var y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.ccopy( 2, x1, -2, y1, 1 );\n    > z = y0.get( 2 );\n    > re = realf( z )\n    7.0\n    > im = imagf( z )\n    8.0\n\n\nbase.strided.ccopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Copies values from one complex single-precision floating-point vector to\n    another complex single-precision floating-point vector using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Complex64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Complex64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n    > base.strided.ccopy.ndarray( x.length, x, 1, 0, y, 1, 0 );\n    > var z = y.get( 0 );\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    2.0\n\n    // Advanced indexing:\n    > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n    > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.ccopy.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\n    > z = y.get( y.length-1 );\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    4.0\n\n    See Also\n    --------\n    base.strided.cswap\n","base.strided.ccopy.ndarray":"\nbase.strided.ccopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Copies values from one complex single-precision floating-point vector to\n    another complex single-precision floating-point vector using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Complex64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Complex64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n    > base.strided.ccopy.ndarray( x.length, x, 1, 0, y, 1, 0 );\n    > var z = y.get( 0 );\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    2.0\n\n    // Advanced indexing:\n    > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n    > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.ccopy.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\n    > z = y.get( y.length-1 );\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    4.0\n\n    See Also\n    --------\n    base.strided.cswap","base.strided.cmap":"\nbase.strided.cmap( N, x, strideX, y, strideY, fcn )\n    Applies a unary function to a single-precision complex floating-point\n    strided input array and assigns results to a single-precision complex\n    floating-point strided output array.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Complex64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Complex64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n    > var x = new Complex64Array( xbuf );\n    > var y = new Complex64Array( x.length );\n    > base.strided.cmap( x.length, x, 1, y, 1, base.cidentityf );\n    > var v = y.get( 0 )\n    <Complex64>\n    > var re = real( v )\n    1.0\n    > var im = imag( v )\n    2.0\n\n    // Using `N` and stride parameters:\n    > y = new Complex64Array( x.length );\n    > base.strided.cmap( 2, x, 2, y, -1, base.cidentityf );\n    > v = y.get( 0 )\n    <Complex64>\n    > re = real( v )\n    5.0\n    > im = imag( v )\n    6.0\n\n    // Using view offsets:\n    > var x0 = new Complex64Array( xbuf );\n    > var y0 = new Complex64Array( x0.length );\n    > var x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.cmap( 2, x1, -2, y1, 1, base.cidentityf );\n    > v = y1.get( 0 )\n    <Complex64>\n    > re = real( v )\n    7.0\n    > im = imag( v )\n    8.0\n\n\nbase.strided.cmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n    Applies a unary function to a single-precision complex floating-point\n    strided input array and assigns results to a single-precision complex\n    floating-point strided output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Complex64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Complex64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n    > var x = new Complex64Array( xbuf );\n    > var y = new Complex64Array( x.length );\n    > base.strided.cmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentityf );\n    > var v = y.get( 0 )\n    <Complex64>\n    > var re = real( v )\n    1.0\n    > var im = imag( v )\n    2.0\n\n    // Advanced indexing:\n    > x = new Complex64Array( xbuf );\n    > y = new Complex64Array( x.length );\n    > base.strided.cmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentityf );\n    > v = y.get( y.length-1 )\n    <Complex64>\n    > re = real( v )\n    3.0\n    > im = imag( v )\n    4.0\n\n    See Also\n    --------\n    base.strided.zmap, base.strided.unary\n","base.strided.cmap.ndarray":"\nbase.strided.cmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n    Applies a unary function to a single-precision complex floating-point\n    strided input array and assigns results to a single-precision complex\n    floating-point strided output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Complex64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Complex64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n    > var x = new Complex64Array( xbuf );\n    > var y = new Complex64Array( x.length );\n    > base.strided.cmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentityf );\n    > var v = y.get( 0 )\n    <Complex64>\n    > var re = real( v )\n    1.0\n    > var im = imag( v )\n    2.0\n\n    // Advanced indexing:\n    > x = new Complex64Array( xbuf );\n    > y = new Complex64Array( x.length );\n    > base.strided.cmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentityf );\n    > v = y.get( y.length-1 )\n    <Complex64>\n    > re = real( v )\n    3.0\n    > im = imag( v )\n    4.0\n\n    See Also\n    --------\n    base.strided.zmap, base.strided.unary","base.strided.cswap":"\nbase.strided.cswap( N, x, strideX, y, strideY )\n    Interchanges two complex single-precision floating-point vectors.\n\n    The `N` and stride parameters determine how values from `x` are swapped with\n    values from `y`.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the vectors are unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Complex64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Complex64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n    > base.strided.cswap( x.length, x, 1, y, 1 );\n    > var z = y.get( 0 );\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    2.0\n    > z = x.get( 0 );\n    > re = realf( z )\n    6.0\n    > im = imagf( z )\n    7.0\n\n    // Advanced indexing:\n    > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n    > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.cswap( 2, x, -2, y, 1 );\n    > z = y.get( 0 );\n    > re = realf( z )\n    5.0\n    > im = imagf( z )\n    6.0\n    > z = x.get( 0 );\n    > re = realf( z )\n    0.0\n    > im = imagf( z )\n    0.0\n\n    // Using typed array views:\n    > var x0 = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n    > var y0 = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Complex64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Complex64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.cswap( 2, x1, -2, y1, 1 );\n    > z = y0.get( 2 );\n    > re = realf( z )\n    7.0\n    > im = imagf( z )\n    8.0\n    > z = x0.get( 1 );\n    > re = realf( z )\n    0.0\n    > im = imagf( z )\n    0.0\n\n\nbase.strided.cswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Interchanges two complex single-precision floating-point vectors using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Complex64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Complex64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n    > base.strided.cswap.ndarray( x.length, x, 1, 0, y, 1, 0 );\n    > var z = y.get( 0 );\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    2.0\n    > z = x.get( 0 );\n    > re = realf( z )\n    6.0\n    > im = imagf( z )\n    7.0\n\n    // Advanced indexing:\n    > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n    > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.cswap.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\n    > z = y.get( y.length-1 );\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    4.0\n    > z = x.get( 1 );\n    > re = realf( z )\n    0.0\n    > im = imagf( z )\n    0.0\n\n    See Also\n    --------\n    base.strided.ccopy\n","base.strided.cswap.ndarray":"\nbase.strided.cswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Interchanges two complex single-precision floating-point vectors using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Complex64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Complex64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Complex64Array( [ 6.0, 7.0, 8.0, 9.0 ] );\n    > base.strided.cswap.ndarray( x.length, x, 1, 0, y, 1, 0 );\n    > var z = y.get( 0 );\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    2.0\n    > z = x.get( 0 );\n    > re = realf( z )\n    6.0\n    > im = imagf( z )\n    7.0\n\n    // Advanced indexing:\n    > x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ] );\n    > y = new Complex64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.cswap.ndarray( 2, x, 2, 1, y, -1, y.length-1 );\n    > z = y.get( y.length-1 );\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    4.0\n    > z = x.get( 1 );\n    > re = realf( z )\n    0.0\n    > im = imagf( z )\n    0.0\n\n    See Also\n    --------\n    base.strided.ccopy","base.strided.cumax":"\nbase.strided.cumax( N, x, strideX, y, strideY )\n    Computes the cumulative maximum of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cumax( x.length, x, 1, y, 1 )\n    [ 1.0, 1.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cumax( N, x, 2, y, 2 )\n    [ -2.0, 0.0, 1.0, 0.0, 2.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.cumax( N, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 2.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 2.0, 2.0 ]\n\nbase.strided.cumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum of a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, 1.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cumax.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumin, base.strided.dcumax, base.strided.scumax\n","base.strided.cumax.ndarray":"\nbase.strided.cumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum of a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, 1.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cumax.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    [ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumin, base.strided.dcumax, base.strided.scumax","base.strided.cumaxabs":"\nbase.strided.cumaxabs( N, x, strideX, y, strideY )\n    Computes the cumulative maximum absolute value of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cumaxabs( x.length, x, 1, y, 1 )\n    [ 1.0, 2.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cumaxabs( N, x, 2, y, 2 )\n    [ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.cumaxabs( N, x1, 2, y1, 1 )\n    <Float64Array>[ 2.0, 2.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\nbase.strided.cumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum absolute value of a strided array using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, 2.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cumax, base.strided.cuminabs, base.strided.dcumaxabs, base.strided.scumaxabs\n","base.strided.cumaxabs.ndarray":"\nbase.strided.cumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum absolute value of a strided array using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, 2.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    [ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cumax, base.strided.cuminabs, base.strided.dcumaxabs, base.strided.scumaxabs","base.strided.cumin":"\nbase.strided.cumin( N, x, strideX, y, strideY )\n    Computes the cumulative minimum of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cumin( x.length, x, 1, y, 1 )\n    [ 1.0, -2.0, -2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cumin( N, x, 2, y, 2 )\n    [ -2.0, 0.0, -2.0, 0.0, -2.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.cumin( N, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, -2.0, -2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\nbase.strided.cumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum of a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, -2.0, -2.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumax, base.strided.dcumin, base.strided.scumin\n","base.strided.cumin.ndarray":"\nbase.strided.cumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum of a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, -2.0, -2.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    [ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumax, base.strided.dcumin, base.strided.scumin","base.strided.cuminabs":"\nbase.strided.cuminabs( N, x, strideX, y, strideY )\n    Computes the cumulative minimum absolute value of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cuminabs( x.length, x, 1, y, 1 )\n    [ 1.0, 1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cuminabs( N, x, 2, y, 2 )\n    [ 2.0, 0.0, 1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.cuminabs( N, x1, 2, y1, 1 )\n    <Float64Array>[ 2.0, 2.0, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 1.0 ]\n\nbase.strided.cuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum absolute value of a strided array using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, 1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cumaxabs, base.strided.cumin, base.strided.dcuminabs, base.strided.scuminabs\n","base.strided.cuminabs.ndarray":"\nbase.strided.cuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum absolute value of a strided array using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.cuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, 1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.cuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    [ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cumaxabs, base.strided.cumin, base.strided.dcuminabs, base.strided.scuminabs","base.strided.dabs":"\nbase.strided.dabs( N, x, strideX, y, strideY )\n    Computes the absolute value for each element in a double-precision floating-\n    point strided array `x` and assigns the results to elements in a double-\n    precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dabs( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dabs( N, x, 2, y, -1 )\n    <Float64Array>[ 3.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dabs( N, x1, -2, y1, 1 )\n    <Float64Array>[ 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the absolute value for each element in a double-precision floating-\n    point strided array `x` and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    strided.abs, base.strided.dabs2, base.strided.sabs\n","base.strided.dabs.ndarray":"\nbase.strided.dabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the absolute value for each element in a double-precision floating-\n    point strided array `x` and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    strided.abs, base.strided.dabs2, base.strided.sabs","base.strided.dabs2":"\nbase.strided.dabs2( N, x, strideX, y, strideY )\n    Computes the squared absolute value for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dabs2( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.0, 4.0, 9.0, 16.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dabs2( N, x, 2, y, -1 )\n    <Float64Array>[ 9.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dabs2( N, x1, -2, y1, 1 )\n    <Float64Array>[ 16.0, 4.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 16.0, 4.0 ]\n\n\nbase.strided.dabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the squared absolute value for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 4.0, 9.0, 16.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 16.0, 4.0 ]\n\n    See Also\n    --------\n    strided.abs2, base.strided.dabs, base.strided.sabs2\n","base.strided.dabs2.ndarray":"\nbase.strided.dabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the squared absolute value for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 4.0, 9.0, 16.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 16.0, 4.0 ]\n\n    See Also\n    --------\n    strided.abs2, base.strided.dabs, base.strided.sabs2","base.strided.dapx":"\nbase.strided.dapx( N, alpha, x, strideX )\n    Adds a scalar constant to each element in a double-precision floating-point\n    strided array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns the strided array unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dapx( x.length, 5.0, x, 1 )\n    <Float64Array>[ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dapx( 3, 5.0, x, 2 )\n    <Float64Array>[ 3.0, 1.0, 8.0, -5.0, 9.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dapx( 3, 5.0, x1, 2 )\n    <Float64Array>[ 3.0, 3.0, 1.0, 5.0, -1.0 ]\n    > x0\n    <Float64Array>[ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n\nbase.strided.dapx.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each element in a double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dapx.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float64Array>[ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.dapx.ndarray( 3, 5.0, x, 2, 1 )\n    <Float64Array>[ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n    See Also\n    --------\n    base.strided.gapx, base.strided.sapx\n","base.strided.dapx.ndarray":"\nbase.strided.dapx.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each element in a double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dapx.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float64Array>[ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.dapx.ndarray( 3, 5.0, x, 2, 1 )\n    <Float64Array>[ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n    See Also\n    --------\n    base.strided.gapx, base.strided.sapx","base.strided.dapxsum":"\nbase.strided.dapxsum( N, alpha, x, strideX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsum( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dapxsum( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dapxsum( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.dapxsum.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dapxsum.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumpw, base.strided.dsum, base.strided.gapxsum, base.strided.sapxsum\n","base.strided.dapxsum.ndarray":"\nbase.strided.dapxsum.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dapxsum.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumpw, base.strided.dsum, base.strided.gapxsum, base.strided.sapxsum","base.strided.dapxsumkbn":"\nbase.strided.dapxsumkbn( N, alpha, x, strideX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using an improved Kahan–Babuška\n    algorithm.\n\n    The `N` and stride parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumkbn( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dapxsumkbn( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dapxsumkbn( 3, 5.0, x1, 2)\n    14.0\n\n\nbase.strided.dapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using an improved Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.dsumkbn, base.strided.gapxsumkbn, base.strided.sapxsumkbn\n","base.strided.dapxsumkbn.ndarray":"\nbase.strided.dapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using an improved Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.dsumkbn, base.strided.gapxsumkbn, base.strided.sapxsumkbn","base.strided.dapxsumkbn2":"\nbase.strided.dapxsumkbn2( N, alpha, x, strideX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using a second-order iterative\n    Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumkbn2( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dapxsumkbn2( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dapxsumkbn2( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.dapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using a second-order iterative\n    Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.dsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsumkbn2\n","base.strided.dapxsumkbn2.ndarray":"\nbase.strided.dapxsumkbn2.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using a second-order iterative\n    Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.dsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsumkbn2","base.strided.dapxsumors":"\nbase.strided.dapxsumors( N, alpha, x, strideX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using ordinary recursive summation.\n\n    The `N` and stride parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumors( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dapxsumors( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dapxsumors( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.dapxsumors.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using ordinary recursive summation\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.dsumors, base.strided.gapxsumors, base.strided.sapxsumors\n","base.strided.dapxsumors.ndarray":"\nbase.strided.dapxsumors.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using ordinary recursive summation\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dapxsumors.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.dsumors, base.strided.gapxsumors, base.strided.sapxsumors","base.strided.dapxsumpw":"\nbase.strided.dapxsumpw( N, alpha, x, strideX )\n    Adds a scalar constant to each double-precision floating-point strided array\n    element and computes the sum using pairwise summation.\n\n    The `N` and stride parameters determine which elements in\n    the strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumpw( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dapxsumpw( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dapxsumpw( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.dapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a constant to each double-precision floating-point strided array\n    element and computes the sum using pairwise summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.dsumpw, base.strided.gapxsumpw, base.strided.sapxsumpw\n","base.strided.dapxsumpw.ndarray":"\nbase.strided.dapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a constant to each double-precision floating-point strided array\n    element and computes the sum using pairwise summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.dsumpw, base.strided.gapxsumpw, base.strided.sapxsumpw","base.strided.dasum":"\nbase.strided.dasum( N, x, stride )\n    Computes the sum of the absolute values.\n\n    The sum of absolute values corresponds to the *L1* norm.\n\n    The `N` and `stride` parameters determine which elements in `x` are used to\n    compute the sum.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the function returns `0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    sum: number\n        Sum of absolute values.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n    > var s = base.strided.dasum( x.length, x, 1 )\n    15.0\n\n    // Sum every other value:\n    > s = base.strided.dasum( 3, x, 2 )\n    9.0\n\n    // Use view offset; e.g., starting at 2nd element:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > s = base.strided.dasum( 3, x1, 2 )\n    12.0\n\n\nbase.strided.dasum.ndarray( N, x, stride, offset )\n    Computes the sum of absolute values using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    sum: number\n        Sum of absolute values.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n    > var s = base.strided.dasum.ndarray( x.length, x, 1, 0 )\n    15.0\n\n    // Sum the last three elements:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > s = base.strided.dasum.ndarray( 3, x, -1, x.length-1 )\n    15.0\n\n    See Also\n    --------\n    base.strided.daxpy, base.strided.gasum, base.strided.sasum, base.strided.dsum\n","base.strided.dasum.ndarray":"\nbase.strided.dasum.ndarray( N, x, stride, offset )\n    Computes the sum of absolute values using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    sum: number\n        Sum of absolute values.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n    > var s = base.strided.dasum.ndarray( x.length, x, 1, 0 )\n    15.0\n\n    // Sum the last three elements:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > s = base.strided.dasum.ndarray( 3, x, -1, x.length-1 )\n    15.0\n\n    See Also\n    --------\n    base.strided.daxpy, base.strided.gasum, base.strided.sasum, base.strided.dsum","base.strided.dasumpw":"\nbase.strided.dasumpw( N, x, strideX )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements using pairwise summation.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dasumpw( x.length, x, 1 )\n    5.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var stride = 2;\n    > base.strided.dasumpw( 3, x, stride )\n    5.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > stride = 2;\n    > base.strided.dasumpw( 3, x1, stride )\n    5.0\n\n\nbase.strided.dasumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements using pairwise summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dasumpw.ndarray( x.length, x, 1, 0 )\n    5.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dasumpw.ndarray( 3, x, 2, 1 )\n    5.0\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.dsumpw, base.strided.gasumpw, base.strided.sasumpw\n","base.strided.dasumpw.ndarray":"\nbase.strided.dasumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements using pairwise summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dasumpw.ndarray( x.length, x, 1, 0 )\n    5.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dasumpw.ndarray( 3, x, 2, 1 )\n    5.0\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.dsumpw, base.strided.gasumpw, base.strided.sasumpw","base.strided.daxpy":"\nbase.strided.daxpy( N, alpha, x, strideX, y, strideY )\n    Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > var alpha = 5.0;\n    > base.strided.daxpy( x.length, alpha, x, 1, y, 1 )\n    <Float64Array>[ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > base.strided.daxpy( 3, alpha, x, 2, y, -1 )\n    <Float64Array>[ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.daxpy( 3, 5.0, x1, -2, y1, 1 )\n    <Float64Array>[ 40.0, 31.0, 22.0 ]\n    > y0\n    <Float64Array>[ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.strided.daxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n    Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > var alpha = 5.0;\n    > base.strided.daxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.daxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.gaxpy, base.strided.saxpy\n","base.strided.daxpy.ndarray":"\nbase.strided.daxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n    Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > var alpha = 5.0;\n    > base.strided.daxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.daxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.gaxpy, base.strided.saxpy","base.strided.dcbrt":"\nbase.strided.dcbrt( N, x, strideX, y, strideY )\n    Computes the cube root of each element in a double-precision floating-point\n    strided array `x` and assigns the results to elements in a double-precision\n    floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dcbrt( x.length, x, 1, y, 1 )\n    <Float64Array>[ 0.0, 1.0, 2.0, 3.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dcbrt( N, x, 2, y, -1 )\n    <Float64Array>[ 2.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dcbrt( N, x1, -2, y1, 1 )\n    <Float64Array>[ 3.0, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.dcbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cube root of each element in a double-precision floating-point\n    strided array `x` and assigns the results to elements in a double-precision\n    floating-point strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dcbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, 1.0, 2.0, 3.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dcbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n    See Also\n    --------\n    strided.cbrt, base.strided.dsqrt, base.strided.scbrt\n","base.strided.dcbrt.ndarray":"\nbase.strided.dcbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cube root of each element in a double-precision floating-point\n    strided array `x` and assigns the results to elements in a double-precision\n    floating-point strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dcbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, 1.0, 2.0, 3.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dcbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n    See Also\n    --------\n    strided.cbrt, base.strided.dsqrt, base.strided.scbrt","base.strided.dceil":"\nbase.strided.dceil( N, x, strideX, y, strideY )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward positive infinity and assigns the results to elements in a double-\n    precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dceil( x.length, x, 1, y, 1 )\n    <Float64Array>[ 2.0, 3.0, -3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dceil( N, x, 2, y, -1 )\n    <Float64Array>[ -3.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dceil( N, x1, -2, y1, 1 )\n    <Float64Array>[ 4.0, 3.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.dceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward positive infinity and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 2.0, 3.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n    See Also\n    --------\n    strided.ceil, base.strided.dfloor, base.strided.dtrunc, base.strided.sceil\n","base.strided.dceil.ndarray":"\nbase.strided.dceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward positive infinity and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 2.0, 3.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n    See Also\n    --------\n    strided.ceil, base.strided.dfloor, base.strided.dtrunc, base.strided.sceil","base.strided.dcopy":"\nbase.strided.dcopy( N, x, strideX, y, strideY )\n    Copies values from `x` into `y`.\n\n    The `N` and stride parameters determine how values from `x` are copied into\n    `y`.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.dcopy( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.dcopy( 3, x, -2, y, 1 )\n    <Float64Array>[ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n    // Using typed array views:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dcopy( 3, x1, -2, y1, 1 )\n    <Float64Array>[ 6.0, 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.dcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Copies values from `x` into `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.dcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dswap, base.strided.gcopy, base.strided.scopy\n","base.strided.dcopy.ndarray":"\nbase.strided.dcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Copies values from `x` into `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.dcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.dcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dswap, base.strided.gcopy, base.strided.scopy","base.strided.dcumax":"\nbase.strided.dcumax( N, x, strideX, y, strideY )\n    Computes the cumulative maximum of double-precision floating-point strided\n    array elements.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumax( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.0, 1.0, 2.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcumax( 3, x, 2, y, 2 )\n    <Float64Array>[ -2.0, 0.0, 1.0, 0.0, 2.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dcumax( 3, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 2.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 2.0, 2.0 ]\n\n\nbase.strided.dcumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum of double-precision floating-point strided\n    array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 1.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumax, base.strided.dcumin, base.strided.scumax\n","base.strided.dcumax.ndarray":"\nbase.strided.dcumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum of double-precision floating-point strided\n    array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 1.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumax, base.strided.dcumin, base.strided.scumax","base.strided.dcumaxabs":"\nbase.strided.dcumaxabs( N, x, strideX, y, strideY )\n    Computes the cumulative maximum absolute value of double-precision floating-\n    point strided array elements.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumaxabs( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.0, 2.0, 2.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcumaxabs( 3, x, 2, y, 2 )\n    <Float64Array>[ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dcumaxabs( 3, x1, 2, y1, 1 )\n    <Float64Array>[ 2.0, 2.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n\nbase.strided.dcumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum absolute value of double-precision floating-\n    point strided array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cumaxabs, base.strided.dcumax, base.strided.dcuminabs, base.strided.scumaxabs\n","base.strided.dcumaxabs.ndarray":"\nbase.strided.dcumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum absolute value of double-precision floating-\n    point strided array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcumaxabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cumaxabs, base.strided.dcumax, base.strided.dcuminabs, base.strided.scumaxabs","base.strided.dcumin":"\nbase.strided.dcumin( N, x, strideX, y, strideY )\n    Computes the cumulative minimum of double-precision floating-point strided\n    array elements.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumin( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.0, -2.0, -2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcumin( 3, x, 2, y, 2 )\n    <Float64Array>[ -2.0, 0.0, -2.0, 0.0, -2.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dcumin( 3, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, -2.0, -2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n\nbase.strided.dcumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum of double-precision floating-point strided\n    array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -2.0, -2.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumin, base.strided.dcumax, base.strided.scumin\n","base.strided.dcumin.ndarray":"\nbase.strided.dcumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum of double-precision floating-point strided\n    array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -2.0, -2.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcumin.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumin, base.strided.dcumax, base.strided.scumin","base.strided.dcuminabs":"\nbase.strided.dcuminabs( N, x, strideX, y, strideY )\n    Computes the cumulative minimum absolute value of double-precision floating-\n    point strided array elements.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcuminabs( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.0, 1.0, 1.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcuminabs( 3, x, 2, y, 2 )\n    <Float64Array>[ 2.0, 0.0, 1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dcuminabs( 3, x1, 2, y1, 1 )\n    <Float64Array>[ 2.0, 2.0, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 1.0 ]\n\n\nbase.strided.dcuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum absolute value of double-precision floating-\n    point strided array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cuminabs, base.strided.dcumaxabs, base.strided.dcumin, base.strided.scuminabs\n","base.strided.dcuminabs.ndarray":"\nbase.strided.dcuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum absolute value of double-precision floating-\n    point strided array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcuminabs.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cuminabs, base.strided.dcumaxabs, base.strided.dcumin, base.strided.scuminabs","base.strided.dcusum":"\nbase.strided.dcusum( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements.\n\n    The `N` and stride parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusum( x.length, 0.0, x, 1, y, 1 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusum( 3, 0.0, x, 2, y, 2 )\n    <Float64Array>[ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dcusum( 3, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumpw, base.strided.gcusum, base.strided.scusum\n","base.strided.dcusum.ndarray":"\nbase.strided.dcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumpw, base.strided.gcusum, base.strided.scusum","base.strided.dcusumkbn":"\nbase.strided.dcusumkbn( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using an improved Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumkbn( x.length, 0.0, x, 1, y, 1 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumkbn( 3, 0.0, x, 2, y, 2 )\n    <Float64Array>[ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dcusumkbn( 3, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusumkbn, base.strided.scusumkbn\n","base.strided.dcusumkbn.ndarray":"\nbase.strided.dcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusumkbn, base.strided.scusumkbn","base.strided.dcusumkbn2":"\nbase.strided.dcusumkbn2( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of double-precision floating-point strided\n    array elements using a second-order iterative Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumkbn2( x.length, 0.0, x, 1, y, 1 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumkbn2( 3, 0.0, x, 2, y, 2 )\n    <Float64Array>[ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dcusumkbn2( 3, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of double-precision floating-point strided\n    array elements using a second-order iterative Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusumkbn2, base.strided.scusumkbn2\n","base.strided.dcusumkbn2.ndarray":"\nbase.strided.dcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of double-precision floating-point strided\n    array elements using a second-order iterative Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusumkbn2, base.strided.scusumkbn2","base.strided.dcusumors":"\nbase.strided.dcusumors( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using ordinary recursive summation.\n\n    The `N` and stride parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumors( x.length, 0.0, x, 1, y, 1 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumors( 3, 0.0, x, 2, y, 2 )\n    <Float64Array>[ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dcusumors( 3, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using ordinary recursive summation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusumors, base.strided.scusumors\n","base.strided.dcusumors.ndarray":"\nbase.strided.dcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using ordinary recursive summation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusumors, base.strided.scusumors","base.strided.dcusumpw":"\nbase.strided.dcusumpw( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using pairwise summation.\n\n    The `N` and stride parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumpw( x.length, 0.0, x, 1, y, 1 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumpw( 3, 0.0, x, 2, y, 2 )\n    <Float64Array>[ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dcusumpw( 3, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.dcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusumpw, base.strided.scusumpw\n","base.strided.dcusumpw.ndarray":"\nbase.strided.dcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float64Array( x.length );\n    > base.strided.dcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float64Array( x.length );\n    > base.strided.dcusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusumpw, base.strided.scusumpw","base.strided.ddeg2rad":"\nbase.strided.ddeg2rad( N, x, strideX, y, strideY )\n    Converts each element in a double-precision floating-point strided array `x`\n    from degrees to radians and assigns the results to elements in a double-\n    precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.ddeg2rad( x.length, x, 1, y, 1 )\n    <Float64Array>[ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.ddeg2rad( N, x, 2, y, -1 )\n    <Float64Array>[ ~0.785, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.ddeg2rad( N, x1, -2, y1, 1 )\n    <Float64Array>[ ~1.047, ~0.524 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.ddeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Converts each element in a double-precision floating-point strided array `x`\n    from degrees to radians and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.ddeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.ddeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n    See Also\n    --------\n    strided.deg2rad, base.strided.sdeg2rad\n","base.strided.ddeg2rad.ndarray":"\nbase.strided.ddeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Converts each element in a double-precision floating-point strided array `x`\n    from degrees to radians and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.ddeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.ddeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n    See Also\n    --------\n    strided.deg2rad, base.strided.sdeg2rad","base.strided.ddot":"\nbase.strided.ddot( N, x, strideX, y, strideY )\n    Computes the dot product of two double-precision floating-point vectors.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: number\n        Dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var out = base.strided.ddot( x.length, x, 1, y, 1 )\n    -5.0\n\n    // Strides:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > out = base.strided.ddot( 3, x, 2, y, -1 )\n    9.0\n\n    // Using view offsets:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n    > out = base.strided.ddot( 3, x1, -2, y1, 1 )\n    128.0\n\n\nbase.strided.ddot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the dot product of two double-precision floating-point vectors\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing based on a starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: number\n        Dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var out = base.strided.ddot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    -5.0\n\n    // Strides:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > out = base.strided.ddot.ndarray( 3, x, 2, 0, y, 2, 0 )\n    9.0\n\n    // Using offset indices:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > out = base.strided.ddot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n    128.0\n\n    See Also\n    --------\n    base.strided.dsdot, base.strided.gdot, base.strided.sdot, base.strided.sdsdot, ddot\n","base.strided.ddot.ndarray":"\nbase.strided.ddot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the dot product of two double-precision floating-point vectors\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing based on a starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: number\n        Dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var out = base.strided.ddot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    -5.0\n\n    // Strides:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > out = base.strided.ddot.ndarray( 3, x, 2, 0, y, 2, 0 )\n    9.0\n\n    // Using offset indices:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > out = base.strided.ddot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n    128.0\n\n    See Also\n    --------\n    base.strided.dsdot, base.strided.gdot, base.strided.sdot, base.strided.sdsdot, ddot","base.strided.dfill":"\nbase.strided.dfill( N, alpha, x, strideX )\n    Fills a double-precision floating-point strided array with a specified\n    scalar value.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dfill( x.length, 5.0, x, 1 )\n    <Float64Array>[ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dfill( 3, 5.0, x, 2 )\n    <Float64Array>[ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dfill( 3, 5.0, x1, 2 )\n    <Float64Array>[ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n    > x0\n    <Float64Array>[ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.dfill.ndarray( N, alpha, x, strideX, offsetX )\n    Fills a double-precision floating-point strided array with a specified\n    scalar value using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dfill.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float64Array>[ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.dfill.ndarray( 3, 5.0, x, 2, 1 )\n    <Float64Array>[ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n    See Also\n    --------\n    base.strided.gfill, base.strided.sfill\n","base.strided.dfill.ndarray":"\nbase.strided.dfill.ndarray( N, alpha, x, strideX, offsetX )\n    Fills a double-precision floating-point strided array with a specified\n    scalar value using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dfill.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float64Array>[ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.dfill.ndarray( 3, 5.0, x, 2, 1 )\n    <Float64Array>[ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n    See Also\n    --------\n    base.strided.gfill, base.strided.sfill","base.strided.dfloor":"\nbase.strided.dfloor( N, x, strideX, y, strideY )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward negative infinity and assigns the results to elements in a double-\n    precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dfloor( x.length, x, 1, y, 1 )\n    <Float64Array>[ -2.0, 1.0, 3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dfloor( N, x, 2, y, -1 )\n    <Float64Array>[ 3.0, -2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dfloor( N, x1, -2, y1, 1 )\n    <Float64Array>[ 4.0, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 1.0 ]\n\n\nbase.strided.dfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward negative infinity and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ -2.0, 1.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dceil, base.strided.dtrunc, strided.floor, base.strided.sfloor\n","base.strided.dfloor.ndarray":"\nbase.strided.dfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward negative infinity and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ -2.0, 1.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dceil, base.strided.dtrunc, strided.floor, base.strided.sfloor","base.strided.dinv":"\nbase.strided.dinv( N, x, strideX, y, strideY )\n    Computes the multiplicative inverse for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dinv( x.length, x, 1, y, 1 )\n    <Float64Array>[ -0.05, -1.0, 0.5, 0.25 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dinv( N, x, 2, y, -1 )\n    <Float64Array>[ 0.5, -0.05, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dinv( N, x1, -2, y1, 1 )\n    <Float64Array>[ 0.25, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.dinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the multiplicative inverse for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ -0.05, -1.0, 0.5, 0.25 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n    See Also\n    --------\n    strided.inv, base.strided.sinv\n","base.strided.dinv.ndarray":"\nbase.strided.dinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the multiplicative inverse for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ -0.05, -1.0, 0.5, 0.25 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n    See Also\n    --------\n    strided.inv, base.strided.sinv","base.strided.dmap":"\nbase.strided.dmap( N, x, strideX, y, strideY, fcn )\n    Applies a unary function to a double-precision floating-point strided input\n    array and assigns results to a double-precision floating-point strided\n    output array.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap( x.length, x, 1, y, 1, base.identity )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap( 2, x, 2, y, -1, base.identity )\n    <Float64Array>[ 3.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmap( 2, x1, -2, y1, 1, base.identity )\n    <Float64Array>[ 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n    Applies a unary function to a double-precision floating-point strided input\n    array and assigns results to a double-precision floating-point strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identity )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identity )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.smap, base.strided.unary\n","base.strided.dmap.ndarray":"\nbase.strided.dmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n    Applies a unary function to a double-precision floating-point strided input\n    array and assigns results to a double-precision floating-point strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identity )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identity )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.smap, base.strided.unary","base.strided.dmap2":"\nbase.strided.dmap2( N, x, sx, y, sy, z, sz, fcn )\n    Applies a binary function to double-precision floating-point strided input\n    arrays and assigns results to a double-precision floating-point strided\n    output array.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    z: Float64Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float64Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap2( x.length, x, 1, y, 1, z, 1, base.add )\n    <Float64Array>[ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Using `N` and stride parameters:\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap2( 2, x, 2, y, -1, z, 1, base.add )\n    <Float64Array>[ 3.0, 4.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmap2( 2, x1, -2, y1, 1, z1, 1, base.add )\n    <Float64Array>[ 7.0, 6.0 ]\n    > z0\n    <Float64Array>[ 0.0, 0.0, 7.0, 6.0 ]\n\n\nbase.strided.dmap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Float64Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float64Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.add )\n    <Float64Array>[ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.add )\n    <Float64Array>[ 0.0, 6.0, 7.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.smap2, base.strided.binary\n","base.strided.dmap2.ndarray":"\nbase.strided.dmap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Float64Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float64Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.add )\n    <Float64Array>[ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.add )\n    <Float64Array>[ 0.0, 6.0, 7.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.smap2, base.strided.binary","base.strided.dmax":"\nbase.strided.dmax( N, x, strideX )\n    Computes the maximum value of a double-precision floating-point strided\n    array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmax( x.length, x, 1 )\n    2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dmax( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dmax( 3, x1, 2 )\n    2.0\n\n\nbase.strided.dmax.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a double-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmax.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dmax.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dnanmax, base.strided.max, base.strided.smax\n","base.strided.dmax.ndarray":"\nbase.strided.dmax.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a double-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmax.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dmax.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dnanmax, base.strided.max, base.strided.smax","base.strided.dmaxabs":"\nbase.strided.dmaxabs( N, x, strideX )\n    Computes the maximum absolute value of a double-precision floating-point\n    strided array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmaxabs( x.length, x, 1 )\n    2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dmaxabs( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dmaxabs( 3, x1, 2 )\n    2.0\n\n\nbase.strided.dmaxabs.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmaxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dmaxabs.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dminabs, base.strided.dnanmaxabs, base.strided.maxabs, base.strided.smaxabs\n","base.strided.dmaxabs.ndarray":"\nbase.strided.dmaxabs.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmaxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dmaxabs.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dminabs, base.strided.dnanmaxabs, base.strided.maxabs, base.strided.smaxabs","base.strided.dmaxabssorted":"\nbase.strided.dmaxabssorted( N, x, strideX )\n    Computes the maximum absolute value of a sorted double-precision floating-\n    point strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n    > base.strided.dmaxabssorted( x.length, x, 1 )\n    3.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dmaxabssorted( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dmaxabssorted( 3, x1, 2 )\n    3.0\n\n\nbase.strided.dmaxabssorted.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a sorted double-precision floating-\n    point strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n    > base.strided.dmaxabssorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.dmaxabssorted.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmaxabs, base.strided.dmaxsorted, base.strided.smaxabssorted\n","base.strided.dmaxabssorted.ndarray":"\nbase.strided.dmaxabssorted.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a sorted double-precision floating-\n    point strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0 ] );\n    > base.strided.dmaxabssorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.dmaxabssorted.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmaxabs, base.strided.dmaxsorted, base.strided.smaxabssorted","base.strided.dmaxsorted":"\nbase.strided.dmaxsorted( N, x, strideX )\n    Computes the maximum value of a sorted double-precision floating-point\n    strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dmaxsorted( x.length, x, 1 )\n    3.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dmaxsorted( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dmaxsorted( 3, x1, 2 )\n    3.0\n\n\nbase.strided.dmaxsorted.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dmaxsorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.dmaxsorted.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dminsorted, base.strided.maxsorted, base.strided.smaxsorted\n","base.strided.dmaxsorted.ndarray":"\nbase.strided.dmaxsorted.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dmaxsorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.dmaxsorted.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dminsorted, base.strided.maxsorted, base.strided.smaxsorted","base.strided.dmean":"\nbase.strided.dmean( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmean( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dmean( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmean( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.mean, base.strided.smean\n","base.strided.dmean.ndarray":"\nbase.strided.dmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.mean, base.strided.smean","base.strided.dmeankbn":"\nbase.strided.dmeankbn( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeankbn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dmeankbn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmeankbn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dmeankbn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeankbn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeankbn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.meankbn, base.strided.smeankbn\n","base.strided.dmeankbn.ndarray":"\nbase.strided.dmeankbn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeankbn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeankbn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.meankbn, base.strided.smeankbn","base.strided.dmeankbn2":"\nbase.strided.dmeankbn2( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a second-order iterative Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeankbn2( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dmeankbn2( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmeankbn2( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dmeankbn2.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeankbn2.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeankbn2.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.meankbn2, base.strided.smeankbn2\n","base.strided.dmeankbn2.ndarray":"\nbase.strided.dmeankbn2.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeankbn2.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeankbn2.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.meankbn2, base.strided.smeankbn2","base.strided.dmeanli":"\nbase.strided.dmeanli( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanli( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dmeanli( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmeanli( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dmeanli.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanli.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanli.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dmeanlipw, base.strided.smeanli\n","base.strided.dmeanli.ndarray":"\nbase.strided.dmeanli.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanli.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanli.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dmeanlipw, base.strided.smeanli","base.strided.dmeanlipw":"\nbase.strided.dmeanlipw( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm with pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanlipw( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dmeanlipw( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmeanlipw( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dmeanlipw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm with pairwise summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanlipw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanlipw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dmeanli, base.strided.dmeanpw, base.strided.smeanlipw\n","base.strided.dmeanlipw.ndarray":"\nbase.strided.dmeanlipw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm with pairwise summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanlipw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanlipw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dmeanli, base.strided.dmeanpw, base.strided.smeanlipw","base.strided.dmeanors":"\nbase.strided.dmeanors( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using ordinary recursive summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanors( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dmeanors( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmeanors( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dnanmeanors, base.strided.meanors, base.strided.smeanors\n","base.strided.dmeanors.ndarray":"\nbase.strided.dmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dnanmeanors, base.strided.meanors, base.strided.smeanors","base.strided.dmeanpn":"\nbase.strided.dmeanpn( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a two-pass error correction algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanpn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dmeanpn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmeanpn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a two-pass error correction algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dnanmeanpn, base.strided.meanpn, base.strided.smeanpn\n","base.strided.dmeanpn.ndarray":"\nbase.strided.dmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a two-pass error correction algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dnanmeanpn, base.strided.meanpn, base.strided.smeanpn","base.strided.dmeanpw":"\nbase.strided.dmeanpw( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanpw( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dmeanpw( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmeanpw( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dmeanpw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanpw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanpw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dnanmeanpw, base.strided.meanpw, base.strided.smeanpw\n","base.strided.dmeanpw.ndarray":"\nbase.strided.dmeanpw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanpw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanpw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dnanmeanpw, base.strided.meanpw, base.strided.smeanpw","base.strided.dmeanstdev":"\nbase.strided.dmeanstdev( N, c, x, strideX, out, strideOut )\n    Computes the mean and standard deviation of a double-precision floating-\n    point strided array.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns a mean and standard deviation equal to\n    `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanstdev( x.length, 1, x, 1, out, 1 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > out = new Float64Array( 2 );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanstdev( N, 1, x, 2, out, 1 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanstdev( N, 1, x1, 2, out, 1 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\nbase.strided.dmeanstdev.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the mean and standard deviation of a double-precision floating-\n    point strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanstdev.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanstdev.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dmeanvar, base.strided.dstdev\n","base.strided.dmeanstdev.ndarray":"\nbase.strided.dmeanstdev.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the mean and standard deviation of a double-precision floating-\n    point strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanstdev.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanstdev.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dmeanvar, base.strided.dstdev","base.strided.dmeanstdevpn":"\nbase.strided.dmeanstdevpn( N, c, x, strideX, out, strideOut )\n    Computes the mean and standard deviation of a double-precision floating-\n    point strided array using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns a mean and standard deviation equal to\n    `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanstdevpn( x.length, 1, x, 1, out, 1 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > out = new Float64Array( 2 );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanstdevpn( N, 1, x, 2, out, 1 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanstdevpn( N, 1, x1, 2, out, 1 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\nbase.strided.dmeanstdevpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the mean and standard deviation of a double-precision floating-\n    point strided array using a two-pass algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanstdevpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanstdevpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.dmeanstdev, base.strided.dmeanvarpn, base.strided.dstdevpn\n","base.strided.dmeanstdevpn.ndarray":"\nbase.strided.dmeanstdevpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the mean and standard deviation of a double-precision floating-\n    point strided array using a two-pass algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanstdevpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanstdevpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~2.0817 ]\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.dmeanstdev, base.strided.dmeanvarpn, base.strided.dstdevpn","base.strided.dmeanvar":"\nbase.strided.dmeanvar( N, c, x, strideX, out, strideOut )\n    Computes the mean and variance of a double-precision floating-point strided\n    array.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns a mean and variance equal to `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanvar( x.length, 1, x, 1, out, 1 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > out = new Float64Array( 2 );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanvar( N, 1, x, 2, out, 1 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanvar( N, 1, x1, 2, out, 1 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\nbase.strided.dmeanvar.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the mean and variance of a double-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanvar.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanvar.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dvariance\n","base.strided.dmeanvar.ndarray":"\nbase.strided.dmeanvar.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the mean and variance of a double-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanvar.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanvar.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dvariance","base.strided.dmeanvarpn":"\nbase.strided.dmeanvarpn( N, c, x, strideX, out, strideOut )\n    Computes the mean and variance of a double-precision floating-point strided\n    array using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns a mean and variance equal to `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanvarpn( x.length, 1, x, 1, out, 1 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > out = new Float64Array( 2 );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanvarpn( N, 1, x, 2, out, 1 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanvarpn( N, 1, x1, 2, out, 1 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\nbase.strided.dmeanvarpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the mean and variance of a double-precision floating-point strided\n    array using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanvarpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanvarpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.dmeanstdevpn, base.strided.dmeanvar, base.strided.dvariancepn\n","base.strided.dmeanvarpn.ndarray":"\nbase.strided.dmeanvarpn.ndarray( N, c, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the mean and variance of a double-precision floating-point strided\n    array using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    c: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dmeanvarpn.ndarray( x.length, 1, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dmeanvarpn.ndarray( N, 1, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ ~0.3333, ~4.3333 ]\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.dmeanstdevpn, base.strided.dmeanvar, base.strided.dvariancepn","base.strided.dmeanwd":"\nbase.strided.dmeanwd( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanwd( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dmeanwd( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmeanwd( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dnanmeanwd, base.strided.meanwd, base.strided.smeanwd\n","base.strided.dmeanwd.ndarray":"\nbase.strided.dmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dnanmeanwd, base.strided.meanwd, base.strided.smeanwd","base.strided.dmediansorted":"\nbase.strided.dmediansorted( N, x, strideX )\n    Computes the median value of a sorted double-precision floating-point\n    strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dmediansorted( x.length, x, 1 )\n    2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dmediansorted( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dmediansorted( 3, x1, 2 )\n    2.0\n\n\nbase.strided.dmediansorted.ndarray( N, x, strideX, offsetX )\n    Computes the median value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.dmediansorted.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.mediansorted, base.strided.smediansorted\n","base.strided.dmediansorted.ndarray":"\nbase.strided.dmediansorted.ndarray( N, x, strideX, offsetX )\n    Computes the median value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dmediansorted.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.dmediansorted.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.mediansorted, base.strided.smediansorted","base.strided.dmidrange":"\nbase.strided.dmidrange( N, x, strideX )\n    Computes the mid-range of a double-precision floating-point strided array.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Mid-range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmidrange( x.length, x, 1 )\n    0.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dmidrange( 3, x, 2 )\n    0.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dmidrange( 3, x1, 2 )\n    0.0\n\n\nbase.strided.dmidrange.ndarray( N, x, strideX, offsetX )\n    Computes the mid-range of a double-precision floating-point strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Mid-range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmidrange.ndarray( x.length, x, 1, 0 )\n    0.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dmidrange.ndarray( 3, x, 2, 1 )\n    0.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dmean, base.strided.dmin, base.strided.drange, base.strided.smidrange\n","base.strided.dmidrange.ndarray":"\nbase.strided.dmidrange.ndarray( N, x, strideX, offsetX )\n    Computes the mid-range of a double-precision floating-point strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Mid-range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmidrange.ndarray( x.length, x, 1, 0 )\n    0.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dmidrange.ndarray( 3, x, 2, 1 )\n    0.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dmean, base.strided.dmin, base.strided.drange, base.strided.smidrange","base.strided.dmin":"\nbase.strided.dmin( N, x, strideX )\n    Computes the minimum value of a double-precision floating-point strided\n    array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmin( x.length, x, 1 )\n    -2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dmin( 3, x, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dmin( N, x1, stride )\n    -2.0\n\n\nbase.strided.dmin.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a double-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dmin.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dnanmin, base.strided.min, base.strided.smin\n","base.strided.dmin.ndarray":"\nbase.strided.dmin.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a double-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dmin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dmin.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dnanmin, base.strided.min, base.strided.smin","base.strided.dminabs":"\nbase.strided.dminabs( N, x, strideX )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dminabs( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dminabs( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dminabs( 3, x1, 2 )\n    1.0\n\n\nbase.strided.dminabs.ndarray( N, x, strideX, offsetX )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dminabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dminabs.ndarray( 3, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dmaxabs, base.strided.dnanminabs, base.strided.minabs, base.strided.sminabs\n","base.strided.dminabs.ndarray":"\nbase.strided.dminabs.ndarray( N, x, strideX, offsetX )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dminabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dminabs.ndarray( 3, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dmaxabs, base.strided.dnanminabs, base.strided.minabs, base.strided.sminabs","base.strided.dminsorted":"\nbase.strided.dminsorted( N, x, strideX )\n    Computes the minimum value of a sorted double-precision floating-point\n    strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dminsorted( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dminsorted( 3, x, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dminsorted( 3, x1, 2 )\n    -2.0\n\n\nbase.strided.dminsorted.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dminsorted.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.dminsorted.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dmaxsorted, base.strided.minsorted, base.strided.sminsorted\n","base.strided.dminsorted.ndarray":"\nbase.strided.dminsorted.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.dminsorted.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.dminsorted.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dmaxsorted, base.strided.minsorted, base.strided.sminsorted","base.strided.dmskabs":"\nbase.strided.dmskabs( N, x, sx, m, sm, y, sy )\n    Computes the absolute value for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ 2.0, 1.0, 0.0, 5.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskabs( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ 5.0, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 5.0, 1.0 ]\n\n\nbase.strided.dmskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the absolute value for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 2.0, 1.0, 0.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 5.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dabs, base.strided.dmskabs2, base.strided.smskabs\n","base.strided.dmskabs.ndarray":"\nbase.strided.dmskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the absolute value for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 2.0, 1.0, 0.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 5.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dabs, base.strided.dmskabs2, base.strided.smskabs","base.strided.dmskabs2":"\nbase.strided.dmskabs2( N, x, sx, m, sm, y, sy )\n    Computes the squared absolute value for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point\n    strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs2( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ 4.0, 1.0, 0.0, 25.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs2( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, 4.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskabs2( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ 25.0, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 25.0, 1.0 ]\n\n\nbase.strided.dmskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the squared absolute value for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point\n    strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 4.0, 1.0, 0.0, 25.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 25.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dabs2, base.strided.dmskabs, base.strided.smskabs2\n","base.strided.dmskabs2.ndarray":"\nbase.strided.dmskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the squared absolute value for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point\n    strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 4.0, 1.0, 0.0, 25.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 25.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dabs2, base.strided.dmskabs, base.strided.smskabs2","base.strided.dmskcbrt":"\nbase.strided.dmskcbrt( N, x, sx, m, sm, y, sy )\n    Computes the cube root for each element in a double-precision floating-point\n    strided array `x` according to a strided mask array and assigns the results\n    to elements in a double-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskcbrt( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ 0.0, 1.0, 0.0, 3.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskcbrt( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskcbrt( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ 3.0, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.dmskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the cube root for each element in a double-precision floating-point\n    strided array `x` according to a strided mask array and assigns the results\n    to elements in a double-precision floating-point strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, 1.0, 0.0, 3.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dcbrt, base.strided.dmsksqrt, base.strided.smskcbrt\n","base.strided.dmskcbrt.ndarray":"\nbase.strided.dmskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the cube root for each element in a double-precision floating-point\n    strided array `x` according to a strided mask array and assigns the results\n    to elements in a double-precision floating-point strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, 1.0, 0.0, 3.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dcbrt, base.strided.dmsksqrt, base.strided.smskcbrt","base.strided.dmskceil":"\nbase.strided.dmskceil( N, x, sx, m, sm, y, sy )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward positive infinity according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskceil( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ 2.0, 3.0, 0.0, 4.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskceil( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskceil( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ 4.0, 3.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.dmskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward positive infinity according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 2.0, 3.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n    See Also\n    --------\n    base.strided.dceil, base.strided.dmskfloor, base.strided.dmsktrunc, base.strided.smskceil\n","base.strided.dmskceil.ndarray":"\nbase.strided.dmskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward positive infinity according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 2.0, 3.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n    See Also\n    --------\n    base.strided.dceil, base.strided.dmskfloor, base.strided.dmsktrunc, base.strided.smskceil","base.strided.dmskdeg2rad":"\nbase.strided.dmskdeg2rad( N, x, sx, m, sm, y, sy )\n    Converts each element in a double-precision floating-point strided array `x`\n    from degrees to radians according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskdeg2rad( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ 0.0, ~0.524, 0.0, ~1.047 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskdeg2rad( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ ~1.047, ~0.524 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.dmskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Converts each element in a double-precision floating-point strided array `x`\n    from degrees to radians according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, ~0.524, 0.0, ~1.047 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n    See Also\n    --------\n    base.strided.ddeg2rad, base.strided.dmskdeg2rad, base.strided.smskdeg2rad\n","base.strided.dmskdeg2rad.ndarray":"\nbase.strided.dmskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Converts each element in a double-precision floating-point strided array `x`\n    from degrees to radians according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, ~0.524, 0.0, ~1.047 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n    See Also\n    --------\n    base.strided.ddeg2rad, base.strided.dmskdeg2rad, base.strided.smskdeg2rad","base.strided.dmskfloor":"\nbase.strided.dmskfloor( N, x, sx, m, sm, y, sy )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward negative infinity according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskfloor( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskfloor( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskfloor( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dmskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward negative infinity according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dfloor, base.strided.dmskceil, base.strided.dmsktrunc, base.strided.smskfloor\n","base.strided.dmskfloor.ndarray":"\nbase.strided.dmskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward negative infinity according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dfloor, base.strided.dmskceil, base.strided.dmsktrunc, base.strided.smskfloor","base.strided.dmskinv":"\nbase.strided.dmskinv( N, x, sx, m, sm, y, sy )\n    Computes the multiplicative inverse for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskinv( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ -0.05, -1.0, 0.0, 0.25 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskinv( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, -0.05, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskinv( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ 0.25, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.dmskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the multiplicative inverse for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ -0.05, -1.0, 0.0, 0.25 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dinv, base.strided.smskinv\n","base.strided.dmskinv.ndarray":"\nbase.strided.dmskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the multiplicative inverse for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ -0.05, -1.0, 0.0, 0.25 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dinv, base.strided.smskinv","base.strided.dmskmap":"\nbase.strided.dmskmap( N, x, sx, m, sm, y, sy, fcn )\n    Applies a unary function to a double-precision floating-point strided input\n    array according to a strided mask array and assigns results to a double-\n    precision floating-point strided output array.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskmap( x.length, x, 1, m, 1, y, 1, base.identity )\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskmap( 2, x, 2, m, 2, y, -1, base.identity )\n    <Float64Array>[ 0.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\n    <Float64Array>[ 0.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, 2.0 ]\n\n\nbase.strided.dmskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n    Applies a unary function to a double-precision floating-point strided input\n    array according to a strided mask array and assigns results to a double-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n    <Float64Array>[ 0.0, 0.0, 4.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmap, base.strided.dmskmap2, base.strided.mskunary, base.strided.smskmap\n","base.strided.dmskmap.ndarray":"\nbase.strided.dmskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n    Applies a unary function to a double-precision floating-point strided input\n    array according to a strided mask array and assigns results to a double-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n    <Float64Array>[ 0.0, 0.0, 4.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmap, base.strided.dmskmap2, base.strided.mskunary, base.strided.smskmap","base.strided.dmskmap2":"\nbase.strided.dmskmap2( N, x, sx, y, sy, m, sm, z, sz, fcn )\n    Applies a binary function to double-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a double-\n    precision floating-point strided output array.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    z: Float64Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float64Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.dmskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.add )\n    <Float64Array>[ 2.0, 4.0, 0.0, 8.0 ]\n\n    // Using `N` and stride parameters:\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.add )\n    <Float64Array>[ 0.0, 3.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.add )\n    <Float64Array>[ 0.0, 6.0 ]\n    > z0\n    <Float64Array>[ 0.0, 0.0, 0.0, 6.0 ]\n\n\nbase.strided.dmskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n    Applies a binary function to double-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a double-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    z: Float64Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float64Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.dmskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.add )\n    <Float64Array>[ 2.0, 4.0, 0.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.dmskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.add )\n    <Float64Array>[ 0.0, 0.0, 7.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmap2, base.strided.dmskmap, base.strided.smskmap2\n","base.strided.dmskmap2.ndarray":"\nbase.strided.dmskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n    Applies a binary function to double-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a double-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    z: Float64Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float64Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.dmskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.add )\n    <Float64Array>[ 2.0, 4.0, 0.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.dmskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.add )\n    <Float64Array>[ 0.0, 0.0, 7.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmap2, base.strided.dmskmap, base.strided.smskmap2","base.strided.dmskmax":"\nbase.strided.dmskmax( N, x, strideX, mask, strideMask )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask.\n\n    The `N` and stride parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.dmskmax( x.length, x, 1, mask, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.dmskmax( 3, x, 2, mask, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dmskmax( 3, x1, 2, mask1, 2 )\n    2.0\n\n\nbase.strided.dmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.dmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dmskmin, base.strided.dnanmax, base.strided.dnanmskmax, base.strided.mskmax, base.strided.smskmax\n","base.strided.dmskmax.ndarray":"\nbase.strided.dmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.dmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.dmskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dmskmin, base.strided.dnanmax, base.strided.dnanmskmax, base.strided.mskmax, base.strided.smskmax","base.strided.dmskmin":"\nbase.strided.dmskmin( N, x, strideX, mask, strideMask )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.dmskmin( x.length, x, 1, mask, 1 )\n    -2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.dmskmin( 3, x, 2, mask, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dmskmin( 3, x1, 2, mask1, 2 )\n    -2.0\n\n\nbase.strided.dmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.dmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dmskmax, base.strided.dnanmin, base.strided.dnanmskmin, base.strided.mskmin, base.strided.smskmin\n","base.strided.dmskmin.ndarray":"\nbase.strided.dmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.dmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.dmskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dmskmax, base.strided.dnanmin, base.strided.dnanmskmin, base.strided.mskmin, base.strided.smskmin","base.strided.dmskramp":"\nbase.strided.dmskramp( N, x, sx, m, sm, y, sy )\n    Evaluates the ramp function for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskramp( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ 1.1, 2.5, 0.0, 4.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskramp( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, 1.1, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskramp( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ 4.0, 2.5 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.5 ]\n\n\nbase.strided.dmskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Evaluates the ramp function for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.1, 2.5, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.5 ]\n\n    See Also\n    --------\n    base.strided.dramp, base.strided.smskramp\n","base.strided.dmskramp.ndarray":"\nbase.strided.dmskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Evaluates the ramp function for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.1, 2.5, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.5 ]\n\n    See Also\n    --------\n    base.strided.dramp, base.strided.smskramp","base.strided.dmskrange":"\nbase.strided.dmskrange( N, x, strideX, mask, strideMask )\n    Computes the range of a double-precision floating-point strided array\n    according to a mask.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.dmskrange( x.length, x, 1, mask, 1 )\n    4.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.dmskrange( 3, x, 2, mask, 2 )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dmskrange( 3, x1, 2, mask1, 2 )\n    4.0\n\n\nbase.strided.dmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a double-precision floating-point strided array\n    according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.dmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.dmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dmskmax, base.strided.dmskmin, base.strided.dnanrange, base.strided.drange, base.strided.mskrange, base.strided.smskrange\n","base.strided.dmskrange.ndarray":"\nbase.strided.dmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a double-precision floating-point strided array\n    according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.dmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.dmskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dmskmax, base.strided.dmskmin, base.strided.dnanrange, base.strided.drange, base.strided.mskrange, base.strided.smskrange","base.strided.dmskrsqrt":"\nbase.strided.dmskrsqrt( N, x, sx, m, sm, y, sy )\n    Computes the reciprocal square root for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskrsqrt( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ Infinity, 0.5, 0.0, ~0.289 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskrsqrt( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, Infinity, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ ~0.289, 0.5 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.dmskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the reciprocal square root for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ Infinity, 0.5, 0.0, ~0.289 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n    See Also\n    --------\n    base.strided.dmsksqrt, base.strided.dsqrt, base.strided.smskrsqrt\n","base.strided.dmskrsqrt.ndarray":"\nbase.strided.dmskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the reciprocal square root for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ Infinity, 0.5, 0.0, ~0.289 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n    See Also\n    --------\n    base.strided.dmsksqrt, base.strided.dsqrt, base.strided.smskrsqrt","base.strided.dmsksqrt":"\nbase.strided.dmsksqrt( N, x, sx, m, sm, y, sy )\n    Computes the principal square root for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsksqrt( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ 0.0, 2.0, 0.0, ~3.464 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsksqrt( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmsksqrt( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ ~3.464, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.dmsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the principal square root for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, 2.0, 0.0, ~3.464 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmskcbrt, base.strided.dmskrsqrt, base.strided.dsqrt, base.strided.smsksqrt\n","base.strided.dmsksqrt.ndarray":"\nbase.strided.dmsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the principal square root for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, 2.0, 0.0, ~3.464 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmskcbrt, base.strided.dmskrsqrt, base.strided.dsqrt, base.strided.smsksqrt","base.strided.dmsktrunc":"\nbase.strided.dmsktrunc( N, x, sx, m, sm, y, sy )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward zero according to a strided mask array and assigns the results to\n    elements in a double-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsktrunc( x.length, x, 1, m, 1, y, 1 )\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsktrunc( 2, x, 2, m, 2, y, -1 )\n    <Float64Array>[ 0.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.dmsktrunc( 2, x1, -2, m1, -2, y1, 1 )\n    <Float64Array>[ 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dmsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward zero according to a strided mask array and assigns the results to\n    elements in a double-precision floating-point strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmskceil, base.strided.dmskfloor, base.strided.dtrunc, base.strided.smsktrunc\n","base.strided.dmsktrunc.ndarray":"\nbase.strided.dmsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward zero according to a strided mask array and assigns the results to\n    elements in a double-precision floating-point strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float64Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dmsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmskceil, base.strided.dmskfloor, base.strided.dtrunc, base.strided.smsktrunc","base.strided.dnanasum":"\nbase.strided.dnanasum( N, x, strideX )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements, ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanasum( x.length, x, 1 )\n    5.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.dnanasum( 4, x, 2 )\n    5.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnanasum( 4, x1, 2 )\n    5.0\n\n\nbase.strided.dnanasum.ndarray( N, x, strideX, offsetX )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements, ignoring `NaN` values and using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanasum.ndarray( x.length, x, 1, 0 )\n    5.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnanasum.ndarray( 4, x, 2, 1 )\n    5.0\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.dasumpw","base.strided.dnanasum.ndarray":"\nbase.strided.dnanasum.ndarray( N, x, strideX, offsetX )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements, ignoring `NaN` values and using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanasum.ndarray( x.length, x, 1, 0 )\n    5.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnanasum.ndarray( 4, x, 2, 1 )\n    5.0\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.dasumpw","base.strided.dnanasumors":"\nbase.strided.dnanasumors( N, x, strideX )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements, ignoring `NaN` values and using ordinary\n    recursive summation.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanasumors( x.length, x, 1 )\n    5.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanasumors( N, x, stride )\n    5.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanasumors( N, x1, stride )\n    5.0\n\n\nbase.strided.dnanasumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements, ignoring `NaN` values and using ordinary\n    recursive summation alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanasumors.ndarray( x.length, x, 1, 0 )\n    5.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanasumors.ndarray( N, x, 2, 1 )\n    5.0\n\n    See Also\n    --------\n    base.strided.dnanasum\n","base.strided.dnanasumors.ndarray":"\nbase.strided.dnanasumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements, ignoring `NaN` values and using ordinary\n    recursive summation alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanasumors.ndarray( x.length, x, 1, 0 )\n    5.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanasumors.ndarray( N, x, 2, 1 )\n    5.0\n\n    See Also\n    --------\n    base.strided.dnanasum","base.strided.dnanmax":"\nbase.strided.dnanmax( N, x, strideX )\n    Computes the maximum value of a double-precision floating-point strided\n    array, ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmax( x.length, x, 1 )\n    2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > base.strided.dnanmax( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnanmax( 3, x1, 2 )\n    2.0\n\n\nbase.strided.dnanmax.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a double-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.dnanmax.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanmax.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dnanmin, base.strided.nanmax, base.strided.snanmax\n","base.strided.dnanmax.ndarray":"\nbase.strided.dnanmax.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a double-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.dnanmax.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanmax.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dnanmin, base.strided.nanmax, base.strided.snanmax","base.strided.dnanmaxabs":"\nbase.strided.dnanmaxabs( N, x, strideX )\n    Computes the maximum absolute value of a double-precision floating-point\n    strided array, ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmaxabs( x.length, x, 1 )\n    2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > base.strided.dnanmaxabs( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnanmaxabs( 3, x1, 2 )\n    2.0\n\n\nbase.strided.dnanmaxabs.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a double-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.dnanmaxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanmaxabs.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmaxabs, base.strided.dnanmax, base.strided.dnanminabs, base.strided.nanmaxabs, base.strided.snanmaxabs\n","base.strided.dnanmaxabs.ndarray":"\nbase.strided.dnanmaxabs.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a double-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.dnanmaxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanmaxabs.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmaxabs, base.strided.dnanmax, base.strided.dnanminabs, base.strided.nanmaxabs, base.strided.snanmaxabs","base.strided.dnanmean":"\nbase.strided.dnanmean( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmean( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanmean( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanmean( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dnanmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.nanmean, base.strided.snanmean\n","base.strided.dnanmean.ndarray":"\nbase.strided.dnanmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.nanmean, base.strided.snanmean","base.strided.dnanmeanors":"\nbase.strided.dnanmeanors( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanors( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanmeanors( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanmeanors( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dnanmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanors, base.strided.dnanmean, base.strided.nanmeanors, base.strided.snanmeanors\n","base.strided.dnanmeanors.ndarray":"\nbase.strided.dnanmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanors, base.strided.dnanmean, base.strided.nanmeanors, base.strided.snanmeanors","base.strided.dnanmeanpn":"\nbase.strided.dnanmeanpn( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction\n    algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanpn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanmeanpn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanmeanpn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dnanmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction algorithm\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.dnanmean, base.strided.nanmeanpn, base.strided.snanmeanpn\n","base.strided.dnanmeanpn.ndarray":"\nbase.strided.dnanmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction algorithm\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.dnanmean, base.strided.nanmeanpn, base.strided.snanmeanpn","base.strided.dnanmeanpw":"\nbase.strided.dnanmeanpw( N, x, stride )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanpw( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanmeanpw( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanmeanpw( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dnanmeanpw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using pairwise summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanpw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmeanpw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpw, base.strided.dnanmean\n","base.strided.dnanmeanpw.ndarray":"\nbase.strided.dnanmeanpw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using pairwise summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanpw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmeanpw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpw, base.strided.dnanmean","base.strided.dnanmeanwd":"\nbase.strided.dnanmeanwd( N, x, strideX )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, using Welford's algorithm and ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanwd( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > base.strided.dnanmeanwd( 3, x, 2 )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnanmeanwd( 3, x1, 2 )\n    ~-0.3333\n\n\nbase.strided.dnanmeanwd.ndarray( N, x, strideX, offsetX )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanmeanwd.ndarray( 3, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanwd, base.strided.dnanmean, base.strided.nanmeanwd, base.strided.snanmeanwd\n","base.strided.dnanmeanwd.ndarray":"\nbase.strided.dnanmeanwd.ndarray( N, x, strideX, offsetX )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanmeanwd.ndarray( 3, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanwd, base.strided.dnanmean, base.strided.nanmeanwd, base.strided.snanmeanwd","base.strided.dnanmin":"\nbase.strided.dnanmin( N, x, strideX )\n    Computes the minimum value of a double-precision floating-point strided\n    array, ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanmin( x.length, x, 1 )\n    -2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > base.strided.dnanmin( 3, x, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnanmin( 3, x1, 2 )\n    -2.0\n\n\nbase.strided.dnanmin.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a double-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.dnanmin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanmin.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dnanmax, base.strided.nanmin, base.strided.snanmin\n","base.strided.dnanmin.ndarray":"\nbase.strided.dnanmin.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a double-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.dnanmin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanmin.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.dnanmax, base.strided.nanmin, base.strided.snanmin","base.strided.dnanminabs":"\nbase.strided.dnanminabs( N, x, strideX )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array, ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanminabs( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > base.strided.dnanminabs( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnanminabs( 3, x1, 2 )\n    1.0\n\n\nbase.strided.dnanminabs.ndarray( N, x, strideX, offsetX )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.dnanminabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanminabs.ndarray( 3, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dminabs, base.strided.dnanmaxabs, base.strided.dnanmin, base.strided.nanminabs, base.strided.snanminabs\n","base.strided.dnanminabs.ndarray":"\nbase.strided.dnanminabs.ndarray( N, x, strideX, offsetX )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.dnanminabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanminabs.ndarray( 3, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dminabs, base.strided.dnanmaxabs, base.strided.dnanmin, base.strided.nanminabs, base.strided.snanminabs","base.strided.dnanmskmax":"\nbase.strided.dnanmskmax( N, x, strideX, mask, strideMask )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n    > base.strided.dnanmskmax( x.length, x, 1, mask, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmskmax( N, x, 2, mask, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dnanmskmax( N, x1, 2, mask1, 2 )\n    2.0\n\nbase.strided.dnanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.dnanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmskmax, base.strided.dnanmax, base.strided.dnanmskmin, base.strided.nanmskmax, base.strided.snanmskmax\n","base.strided.dnanmskmax.ndarray":"\nbase.strided.dnanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.dnanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmskmax, base.strided.dnanmax, base.strided.dnanmskmin, base.strided.nanmskmax, base.strided.snanmskmax","base.strided.dnanmskmin":"\nbase.strided.dnanmskmin( N, x, strideX, mask, strideMask )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n    > base.strided.dnanmskmin( x.length, x, 1, mask, 1 )\n    -2.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmskmin( N, x, 2, mask, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dnanmskmin( N, x1, 2, mask1, 2 )\n    -2.0\n\nbase.strided.dnanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.dnanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmskmin, base.strided.dnanmin, base.strided.dnanmskmax, base.strided.nanmskmin, base.strided.snanmskmin\n","base.strided.dnanmskmin.ndarray":"\nbase.strided.dnanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.dnanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmskmin, base.strided.dnanmin, base.strided.dnanmskmax, base.strided.nanmskmin, base.strided.snanmskmin","base.strided.dnanmskrange":"\nbase.strided.dnanmskrange( N, x, strideX, mask, strideMask )\n    Computes the range of a double-precision floating-point strided array\n    according to a mask, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n    > base.strided.dnanmskrange( x.length, x, 1, mask, 1 )\n    4.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmskrange( N, x, 2, mask, 2 )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dnanmskrange( N, x1, 2, mask1, 2 )\n    4.0\n\nbase.strided.dnanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a double-precision floating-point strided array\n    according to a mask, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.dnanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dmskrange, base.strided.dnanrange, base.strided.dnanmskmax, base.strided.dnanmskmin, base.strided.nanmskrange, base.strided.snanmskrange\n","base.strided.dnanmskrange.ndarray":"\nbase.strided.dnanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a double-precision floating-point strided array\n    according to a mask, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.dnanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dmskrange, base.strided.dnanrange, base.strided.dnanmskmax, base.strided.dnanmskmin, base.strided.nanmskrange, base.strided.snanmskrange","base.strided.dnannsum":"\nbase.strided.dnannsum( N, x, strideX, out, strideOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns a sum equal to `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsum( x.length, x, 1, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsum( 4, x, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsum( 4, x1, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n\nbase.strided.dnannsum.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsum.ndarray( x.length, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsum.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.dsum","base.strided.dnannsum.ndarray":"\nbase.strided.dnannsum.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsum.ndarray( x.length, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsum.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.dsum","base.strided.dnannsumkbn":"\nbase.strided.dnannsumkbn( N, x, strideX, out, strideOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns a sum equal to `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn( x.length, x, 1, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn( 4, x, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn( 4, x1, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n\nbase.strided.dnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn.ndarray( 4, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsum, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn, base.strided.gnannsumkbn\n","base.strided.dnannsumkbn.ndarray":"\nbase.strided.dnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn.ndarray( 4, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsum, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn, base.strided.gnannsumkbn","base.strided.dnannsumkbn2":"\nbase.strided.dnannsumkbn2( N, x, strideX, out, strideOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm.\n\n    The `N` and stride parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns a sum equal to `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn2( x.length, x, 1, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn2( 4, x, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn2( 4, x1, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n\nbase.strided.dnannsumkbn2.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn2.ndarray( 4, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn2.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn2\n","base.strided.dnannsumkbn2.ndarray":"\nbase.strided.dnannsumkbn2.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn2.ndarray( 4, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumkbn2.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumors, base.strided.dnannsumpw, base.strided.dsumkbn2","base.strided.dnannsumors":"\nbase.strided.dnannsumors( N, x, strideX, out, strideOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation.\n\n    The `N` and stride parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns a sum equal to `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumors( x.length, x, 1, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumors( 4, x, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumors( 4, x1, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n\nbase.strided.dnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumpw, base.strided.dsumors\n","base.strided.dnannsumors.ndarray":"\nbase.strided.dnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumpw, base.strided.dsumors","base.strided.dnannsumpw":"\nbase.strided.dnannsumpw( N, x, strideX, out, strideOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation.\n\n    The `N` and stride parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns a sum equal to `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumpw( x.length, x, 1, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumpw( 4, x, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumpw( 4, x1, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n\nbase.strided.dnannsumpw.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for the strided array.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumpw.ndarray( x.length, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumpw.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dsumpw\n","base.strided.dnannsumpw.ndarray":"\nbase.strided.dnannsumpw.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for the strided array.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dnannsumpw.ndarray( x.length, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dnannsumpw.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsum, base.strided.dnannsumkbn, base.strided.dnannsumkbn2, base.strided.dnannsumors, base.strided.dsumpw","base.strided.dnanrange":"\nbase.strided.dnanrange( N, x, strideX )\n    Computes the range of a double-precision floating-point strided array,\n    ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanrange( x.length, x, 1 )\n    4.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > base.strided.dnanrange( 3, x, 2 )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnanrange( 3, x1, 2 )\n    4.0\n\n\nbase.strided.dnanrange.ndarray( N, x, strideX, offsetX )\n    Computes the range of a double-precision floating-point strided array,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.dnanrange.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanrange.ndarray( 3, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dnanmax, base.strided.dnanmin, base.strided.drange, base.strided.nanrange, base.strided.snanrange\n","base.strided.dnanrange.ndarray":"\nbase.strided.dnanrange.ndarray( N, x, strideX, offsetX )\n    Computes the range of a double-precision floating-point strided array,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.dnanrange.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.dnanrange.ndarray( 3, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dnanmax, base.strided.dnanmin, base.strided.drange, base.strided.nanrange, base.strided.snanrange","base.strided.dnanstdev":"\nbase.strided.dnanstdev( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdev( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanstdev( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanstdev( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dnanstdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanvariance, base.strided.dstdev, base.strided.nanstdev, base.strided.snanstdev\n","base.strided.dnanstdev.ndarray":"\nbase.strided.dnanstdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanvariance, base.strided.dstdev, base.strided.nanstdev, base.strided.snanstdev","base.strided.dnanstdevch":"\nbase.strided.dnanstdevch( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevch( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanstdevch( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanstdevch( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dnanstdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dnanvariancech, base.strided.dstdevch, base.strided.nanstdevch, base.strided.snanstdevch\n","base.strided.dnanstdevch.ndarray":"\nbase.strided.dnanstdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dnanvariancech, base.strided.dstdevch, base.strided.nanstdevch, base.strided.snanstdevch","base.strided.dnanstdevpn":"\nbase.strided.dnanstdevpn( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevpn( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanstdevpn( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanstdevpn( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dnanstdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.snanstdevpn\n","base.strided.dnanstdevpn.ndarray":"\nbase.strided.dnanstdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.snanstdevpn","base.strided.dnanstdevtk":"\nbase.strided.dnanstdevtk( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevtk( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanstdevtk( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanstdevtk( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dnanstdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.snanstdevtk\n","base.strided.dnanstdevtk.ndarray":"\nbase.strided.dnanstdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.snanstdevtk","base.strided.dnanstdevwd":"\nbase.strided.dnanstdevwd( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevwd( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanstdevwd( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanstdevwd( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dnanstdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.snanstdevwd\n","base.strided.dnanstdevwd.ndarray":"\nbase.strided.dnanstdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.snanstdevwd","base.strided.dnanstdevyc":"\nbase.strided.dnanstdevyc( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass algorithm proposed by\n    Youngs and Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevyc( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanstdevyc( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanstdevyc( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dnanstdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass algorithm proposed by\n    Youngs and Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.snanstdevyc\n","base.strided.dnanstdevyc.ndarray":"\nbase.strided.dnanstdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass algorithm proposed by\n    Youngs and Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanstdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.snanstdevyc","base.strided.dnansum":"\nbase.strided.dnansum( N, x, strideX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansum( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansum( 4, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnansum( 4, x1, 2 )\n    -1.0\n\n\nbase.strided.dnansum.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansum.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.dsum, base.strided.snansum, base.strided.gnansum\n","base.strided.dnansum.ndarray":"\nbase.strided.dnansum.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansum.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.dsum, base.strided.snansum, base.strided.gnansum","base.strided.dnansumkbn":"\nbase.strided.dnansumkbn( N, x, strideX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumkbn( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumkbn( 4, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnansumkbn( 4, x1, 2 )\n    -1.0\n\n\nbase.strided.dnansumkbn.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumkbn.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.snansumkbn\n","base.strided.dnansumkbn.ndarray":"\nbase.strided.dnansumkbn.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumkbn.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.snansumkbn","base.strided.dnansumkbn2":"\nbase.strided.dnansumkbn2( N, x, strideX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm.\n\n    The `N` and stride parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumkbn2( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumkbn2( 4, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnansumkbn2( 4, x1, 2 )\n    -1.0\n\n\nbase.strided.dnansumkbn2.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumkbn2.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.snansumkbn2\n","base.strided.dnansumkbn2.ndarray":"\nbase.strided.dnansumkbn2.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumkbn2.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.dnansumors, base.strided.dnansumpw, base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.snansumkbn2","base.strided.dnansumors":"\nbase.strided.dnansumors( N, x, strideX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumors( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumors( 4, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnansumors( 4, x1, 2 )\n    -1.0\n\n\nbase.strided.dnansumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumors.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumpw, base.strided.dsumors, base.strided.gnansumors, base.strided.snansumors\n","base.strided.dnansumors.ndarray":"\nbase.strided.dnansumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumors.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumpw, base.strided.dsumors, base.strided.gnansumors, base.strided.snansumors","base.strided.dnansumpw":"\nbase.strided.dnansumpw( N, x, strideX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumpw( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumpw( 4, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnansumpw( 4, x1, 2 )\n    -1.0\n\n\nbase.strided.dnansumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumpw.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumors, base.strided.dsumpw, base.strided.gnansumpw, base.strided.snansumpw\n","base.strided.dnansumpw.ndarray":"\nbase.strided.dnansumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnansumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dnansumpw.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.dnansumkbn2, base.strided.dnansumors, base.strided.dsumpw, base.strided.gnansumpw, base.strided.snansumpw","base.strided.dnanvariance":"\nbase.strided.dnanvariance( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariance( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanvariance( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanvariance( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dnanvariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dvariance, base.strided.nanvariance, base.strided.snanvariance\n","base.strided.dnanvariance.ndarray":"\nbase.strided.dnanvariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dvariance, base.strided.nanvariance, base.strided.snanvariance","base.strided.dnanvariancech":"\nbase.strided.dnanvariancech( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancech( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanvariancech( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanvariancech( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dnanvariancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvariancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancech, base.strided.dnanvariance, base.strided.nanvariancech, base.strided.snanvariancech\n","base.strided.dnanvariancech.ndarray":"\nbase.strided.dnanvariancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvariancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancech, base.strided.dnanvariance, base.strided.nanvariancech, base.strided.snanvariancech","base.strided.dnanvariancepn":"\nbase.strided.dnanvariancepn( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancepn( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanvariancepn( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanvariancepn( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dnanvariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancepn, base.strided.dnanvariance, base.strided.nanvariancepn, base.strided.snanvariancepn\n","base.strided.dnanvariancepn.ndarray":"\nbase.strided.dnanvariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancepn, base.strided.dnanvariance, base.strided.nanvariancepn, base.strided.snanvariancepn","base.strided.dnanvariancetk":"\nbase.strided.dnanvariancetk( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancetk( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanvariancetk( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanvariancetk( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dnanvariancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvariancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancetk, base.strided.dnanvariance, base.strided.nanvariancetk, base.strided.snanvariancetk\n","base.strided.dnanvariancetk.ndarray":"\nbase.strided.dnanvariancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvariancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancetk, base.strided.dnanvariance, base.strided.nanvariancetk, base.strided.snanvariancetk","base.strided.dnanvariancewd":"\nbase.strided.dnanvariancewd( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancewd( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanvariancewd( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanvariancewd( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dnanvariancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using Welford's algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvariancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancewd, base.strided.dnanvariance, base.strided.nanvariancewd, base.strided.snanvariancewd\n","base.strided.dnanvariancewd.ndarray":"\nbase.strided.dnanvariancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using Welford's algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvariancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancewd, base.strided.dnanvariance, base.strided.nanvariancewd, base.strided.snanvariancewd","base.strided.dnanvarianceyc":"\nbase.strided.dnanvarianceyc( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n    Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvarianceyc( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dnanvarianceyc( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dnanvarianceyc( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dnanvarianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n    Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvarianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvarianceyc, base.strided.dnanvariance, base.strided.nanvarianceyc, base.strided.snanvarianceyc\n","base.strided.dnanvarianceyc.ndarray":"\nbase.strided.dnanvarianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n    Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dnanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dnanvarianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvarianceyc, base.strided.dnanvariance, base.strided.nanvarianceyc, base.strided.snanvarianceyc","base.strided.dnrm2":"\nbase.strided.dnrm2( N, x, stride )\n    Computes the L2-norm of a double-precision floating-point vector.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    nrm2: number\n        The L2-norm.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dnrm2( x.length, x, 1 )\n    3.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dnrm2( 3, x, 2 )\n    3.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dnrm2( 3, x1, 2 )\n    3.0\n\n\nbase.strided.dnrm2.ndarray( N, x, stride, offset )\n    Computes the L2-norm of a double-precision floating-point vector using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    nrm2: number\n        The L2-norm.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dnrm2.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dnrm2.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.gnrm2, base.strided.snrm2\n","base.strided.dnrm2.ndarray":"\nbase.strided.dnrm2.ndarray( N, x, stride, offset )\n    Computes the L2-norm of a double-precision floating-point vector using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    nrm2: number\n        The L2-norm.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dnrm2.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dnrm2.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.gnrm2, base.strided.snrm2","base.strided.dramp":"\nbase.strided.dramp( N, x, strideX, y, strideY )\n    Evaluates the ramp function for each element in a double-precision floating-\n    point strided array `x` and assigns the results to elements in a double-\n    precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dramp( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.1, 2.5, 0.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dramp( N, x, 2, y, -1 )\n    <Float64Array>[ 0.0, 1.1, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dramp( N, x1, -2, y1, 1 )\n    <Float64Array>[ 4.0, 2.5 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.5 ]\n\n\nbase.strided.dramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Evaluates the ramp function for each element in a double-precision floating-\n    point strided array `x` and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.1, 2.5, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.5 ]\n\n    See Also\n    --------\n    strided.ramp, base.strided.sramp\n","base.strided.dramp.ndarray":"\nbase.strided.dramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Evaluates the ramp function for each element in a double-precision floating-\n    point strided array `x` and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.1, 2.5, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.5 ]\n\n    See Also\n    --------\n    strided.ramp, base.strided.sramp","base.strided.drange":"\nbase.strided.drange( N, x, strideX )\n    Computes the range of a double-precision floating-point strided array.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.drange( x.length, x, 1 )\n    4.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.drange( 3, x, 2 )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > stride = 2;\n    > base.strided.drange( 3, x1, 2 )\n    4.0\n\n\nbase.strided.drange.ndarray( N, x, strideX, offsetX )\n    Computes the range of a double-precision floating-point strided array using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.drange.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.drange.ndarray( 3, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dmin, base.strided.dnanrange, base.strided.range, base.strided.srange\n","base.strided.drange.ndarray":"\nbase.strided.drange.ndarray( N, x, strideX, offsetX )\n    Computes the range of a double-precision floating-point strided array using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.drange.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.drange.ndarray( 3, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.dmin, base.strided.dnanrange, base.strided.range, base.strided.srange","base.strided.drev":"\nbase.strided.drev( N, x, strideX )\n    Reverses a double-precision floating-point strided array in-place.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.drev( x.length, x, 1 )\n    <Float64Array>[ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.drev( 3, x, 2 )\n    <Float64Array>[ 4.0, 1.0, 3.0, -5.0, -2.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.drev( 3, x1, 2 )\n    <Float64Array>[ -6.0, 3.0, -4.0, 5.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n\nbase.strided.drev.ndarray( N, x, strideX, offsetX )\n    Reverses a double-precision floating-point strided array in-place using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.drev.ndarray( x.length, x, 1, 0 )\n    <Float64Array>[ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.drev.ndarray( 3, x, 2, 1 )\n    <Float64Array>[ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.grev, base.strided.srev\n","base.strided.drev.ndarray":"\nbase.strided.drev.ndarray( N, x, strideX, offsetX )\n    Reverses a double-precision floating-point strided array in-place using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.drev.ndarray( x.length, x, 1, 0 )\n    <Float64Array>[ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.drev.ndarray( 3, x, 2, 1 )\n    <Float64Array>[ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.grev, base.strided.srev","base.strided.drsqrt":"\nbase.strided.drsqrt( N, x, strideX, y, strideY )\n    Computes the reciprocal square root for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.drsqrt( x.length, x, 1, y, 1 )\n    <Float64Array>[ Infinity, 0.5, ~0.333, ~0.289 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.drsqrt( N, x, 2, y, -1 )\n    <Float64Array>[ ~0.333, Infinity, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.drsqrt( N, x1, -2, y1, 1 )\n    <Float64Array>[ ~0.289, 0.5 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.drsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the reciprocal square root for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.drsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ Infinity, 0.5, ~0.333, ~0.289 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.drsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n    See Also\n    --------\n    base.strided.dsqrt, strided.rsqrt, base.strided.srsqrt\n","base.strided.drsqrt.ndarray":"\nbase.strided.drsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the reciprocal square root for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.drsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ Infinity, 0.5, ~0.333, ~0.289 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.drsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n    See Also\n    --------\n    base.strided.dsqrt, strided.rsqrt, base.strided.srsqrt","base.strided.dsapxsum":"\nbase.strided.dsapxsum( N, alpha, x, strideX )\n    Adds a scalar constant to each single-precision floating-point strided array\n    element, and computes the sum using extended accumulation and returning\n    an extended precision result.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsapxsum( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dsapxsum( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsapxsum( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.dsapxsum.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each single-precision floating-point strided array\n    element, and computes the sum using pairwise summation with extended\n    accumulation and alternative indexing semantics and returning an extended\n    precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.dssum, base.strided.sapxsum\n","base.strided.dsapxsum.ndarray":"\nbase.strided.dsapxsum.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each single-precision floating-point strided array\n    element, and computes the sum using pairwise summation with extended\n    accumulation and alternative indexing semantics and returning an extended\n    precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.dssum, base.strided.sapxsum","base.strided.dsapxsumpw":"\nbase.strided.dsapxsumpw( N, alpha, x, strideX )\n    Adds a constant to each single-precision floating-point strided array\n    element, and computes the sum using pairwise summation with extended\n    accumulation and returning an extended precision result.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsapxsumpw( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dsapxsumpw( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsapxsumpw( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.dsapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a constant to each single-precision floating-point strided array\n    element, and computes the sum using pairwise summation with extended\n    accumulation and alternative indexing semantics and returning an extended\n    precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumpw, base.strided.dsapxsum, base.strided.dssumpw, base.strided.sapxsumpw\n","base.strided.dsapxsumpw.ndarray":"\nbase.strided.dsapxsumpw.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a constant to each single-precision floating-point strided array\n    element, and computes the sum using pairwise summation with extended\n    accumulation and alternative indexing semantics and returning an extended\n    precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumpw, base.strided.dsapxsum, base.strided.dssumpw, base.strided.sapxsumpw","base.strided.dscal":"\nbase.strided.dscal( N, alpha, x, stride )\n    Multiplies a double-precision floating-point vector `x` by a constant\n    `alpha`.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dscal( x.length, 5.0, x, 1 )\n    <Float64Array>[ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dscal( 3, 5.0, x, 2 )\n    <Float64Array>[ -10.0, 1.0, 15.0, -5.0, 20.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dscal( 3, 5.0, x1, 2 )\n    <Float64Array>[ -10.0, 3.0, -20.0, 5.0, -30.0 ]\n    > x0\n    <Float64Array>[ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n\nbase.strided.dscal.ndarray( N, alpha, x, stride, offset )\n    Multiplies a double-precision floating-point vector `x` by a constant\n    `alpha` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dscal.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float64Array>[ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.dscal.ndarray( 3, 5.0, x, 2, 1 )\n    <Float64Array>[ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n    See Also\n    --------\n    base.strided.daxpy, base.strided.gscal, base.strided.sscal, base.strided.saxpy\n","base.strided.dscal.ndarray":"\nbase.strided.dscal.ndarray( N, alpha, x, stride, offset )\n    Multiplies a double-precision floating-point vector `x` by a constant\n    `alpha` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.dscal.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float64Array>[ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.dscal.ndarray( 3, 5.0, x, 2, 1 )\n    <Float64Array>[ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n    See Also\n    --------\n    base.strided.daxpy, base.strided.gscal, base.strided.sscal, base.strided.saxpy","base.strided.dsdot":"\nbase.strided.dsdot( N, x, strideX, y, strideY )\n    Computes the dot product of two single-precision floating-point vectors with\n    extended accumulation and result.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0` the function returns `0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    dot: number\n        Dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var dot = base.strided.dsdot( x.length, x, 1, y, 1 )\n    -5.0\n\n    // Strides:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > dot = base.strided.dsdot( 3, x, 2, y, -1 )\n    9.0\n\n    // Using view offsets:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n    > dot = base.strided.dsdot( 3, x1, -2, y1, 1 )\n    128.0\n\n\nbase.strided.dsdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the dot product of two single-precision floating-point vectors\n    using alternative indexing semantics and with extended accumulation and\n    result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing based on a starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    dot: number\n        Dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var dot = base.strided.dsdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    -5.0\n\n    // Strides:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > dot = base.strided.dsdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n    9.0\n\n    // Using offset indices:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > dot = base.strided.dsdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n    128.0\n\n    References\n    ----------\n    - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n    Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n    Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n    NY, USA: Association for Computing Machinery: 324–25.\n    doi:10.1145/355841.355848.\n\n    See Also\n    --------\n    base.strided.ddot, base.strided.sdot, base.strided.sdsdot\n","base.strided.dsdot.ndarray":"\nbase.strided.dsdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the dot product of two single-precision floating-point vectors\n    using alternative indexing semantics and with extended accumulation and\n    result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing based on a starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    dot: number\n        Dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var dot = base.strided.dsdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    -5.0\n\n    // Strides:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > dot = base.strided.dsdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n    9.0\n\n    // Using offset indices:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > dot = base.strided.dsdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n    128.0\n\n    References\n    ----------\n    - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n    Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n    Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n    NY, USA: Association for Computing Machinery: 324–25.\n    doi:10.1145/355841.355848.\n\n    See Also\n    --------\n    base.strided.ddot, base.strided.sdot, base.strided.sdsdot","base.strided.dsem":"\nbase.strided.dsem( N, correction, x, stride )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsem( x.length, 1, x, 1 )\n    ~1.20185\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsem( N, 1, x, stride )\n    ~1.20185\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsem( N, 1, x1, stride )\n    ~1.20185\n\nbase.strided.dsem.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsem.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsem.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dstdev\n","base.strided.dsem.ndarray":"\nbase.strided.dsem.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsem.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsem.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dstdev","base.strided.dsemch":"\nbase.strided.dsemch( N, correction, x, stride )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemch( x.length, 1, x, 1 )\n    ~1.20185\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsemch( N, 1, x, stride )\n    ~1.20185\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsemch( N, 1, x1, stride )\n    ~1.20185\n\nbase.strided.dsemch.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass trial mean algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemch.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsemch.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dsem, base.strided.dstdevch\n","base.strided.dsemch.ndarray":"\nbase.strided.dsemch.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass trial mean algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemch.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsemch.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dsem, base.strided.dstdevch","base.strided.dsempn":"\nbase.strided.dsempn( N, correction, x, stride )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsempn( x.length, 1, x, 1 )\n    ~1.20185\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsempn( N, 1, x, stride )\n    ~1.20185\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsempn( N, 1, x1, stride )\n    ~1.20185\n\nbase.strided.dsempn.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a two-pass algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsempn.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsempn.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dsem, base.strided.dstdevpn\n","base.strided.dsempn.ndarray":"\nbase.strided.dsempn.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a two-pass algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsempn.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsempn.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dsem, base.strided.dstdevpn","base.strided.dsemtk":"\nbase.strided.dsemtk( N, correction, x, stride )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemtk( x.length, 1, x, 1 )\n    ~1.20185\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsemtk( N, 1, x, stride )\n    ~1.20185\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsemtk( N, 1, x1, stride )\n    ~1.20185\n\nbase.strided.dsemtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass textbook algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemtk.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsemtk.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dsem, base.strided.dstdevtk\n","base.strided.dsemtk.ndarray":"\nbase.strided.dsemtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass textbook algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemtk.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsemtk.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dsem, base.strided.dstdevtk","base.strided.dsemwd":"\nbase.strided.dsemwd( N, correction, x, stride )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemwd( x.length, 1, x, 1 )\n    ~1.20185\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsemwd( N, 1, x, stride )\n    ~1.20185\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsemwd( N, 1, x1, stride )\n    ~1.20185\n\nbase.strided.dsemwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using Welford's algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemwd.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsemwd.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dsem, base.strided.dstdevwd\n","base.strided.dsemwd.ndarray":"\nbase.strided.dsemwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using Welford's algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemwd.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsemwd.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dsem, base.strided.dstdevwd","base.strided.dsemyc":"\nbase.strided.dsemyc( N, correction, x, stride )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass algorithm proposed by Youngs and\n    Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemyc( x.length, 1, x, 1 )\n    ~1.20185\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsemyc( N, 1, x, stride )\n    ~1.20185\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsemyc( N, 1, x1, stride )\n    ~1.20185\n\nbase.strided.dsemyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass algorithm proposed by Youngs and Cramer\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemyc.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsemyc.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dsem, base.strided.dstdevyc\n","base.strided.dsemyc.ndarray":"\nbase.strided.dsemyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass algorithm proposed by Youngs and Cramer\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Standard error of the mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsemyc.ndarray( x.length, 1, x, 1, 0 )\n    ~1.20185\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsemyc.ndarray( N, 1, x, 2, 1 )\n    ~1.20185\n\n    See Also\n    --------\n    base.strided.dsem, base.strided.dstdevyc","base.strided.dsmean":"\nbase.strided.dsmean( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using extended accumulation and returning an extended precision\n    result.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmean( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsmean( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsmean( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dsmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using extended accumulation and alternative indexing semantics and\n    returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dsnanmean, base.strided.mean, base.strided.sdsmean, base.strided.smean\n","base.strided.dsmean.ndarray":"\nbase.strided.dsmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using extended accumulation and alternative indexing semantics and\n    returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dsnanmean, base.strided.mean, base.strided.sdsmean, base.strided.smean","base.strided.dsmeanors":"\nbase.strided.dsmeanors( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation with extended accumulation and\n    returning an extended precision result.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanors( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsmeanors( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsmeanors( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dsmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation with extended accumulation and\n    alternative indexing semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanors, base.strided.dsmean, base.strided.dsnanmeanors, base.strided.meanors, base.strided.smeanors\n","base.strided.dsmeanors.ndarray":"\nbase.strided.dsmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation with extended accumulation and\n    alternative indexing semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanors, base.strided.dsmean, base.strided.dsnanmeanors, base.strided.meanors, base.strided.smeanors","base.strided.dsmeanpn":"\nbase.strided.dsmeanpn( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a two-pass error correction algorithm with extended accumulation\n    and returning an extended precision result.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanpn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsmeanpn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsmeanpn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dsmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a two-pass error correction algorithm with extended accumulation\n    and alternative indexing semantics and returning an extended precision\n    result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.dsmean, base.strided.dsnanmeanpn, base.strided.meanpn, base.strided.smeanpn\n","base.strided.dsmeanpn.ndarray":"\nbase.strided.dsmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a two-pass error correction algorithm with extended accumulation\n    and alternative indexing semantics and returning an extended precision\n    result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.dsmean, base.strided.dsnanmeanpn, base.strided.meanpn, base.strided.smeanpn","base.strided.dsmeanpw":"\nbase.strided.dsmeanpw( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using pairwise summation with extended accumulation and returning an\n    extended precision result.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanpw( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsmeanpw( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsmeanpw( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dsmeanpw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using pairwise summation with extended accumulation and alternative\n    indexing semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanpw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsmeanpw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpw, base.strided.dsmean, base.strided.meanpw, base.strided.smeanpw\n","base.strided.dsmeanpw.ndarray":"\nbase.strided.dsmeanpw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using pairwise summation with extended accumulation and alternative\n    indexing semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanpw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsmeanpw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpw, base.strided.dsmean, base.strided.meanpw, base.strided.smeanpw","base.strided.dsmeanwd":"\nbase.strided.dsmeanwd( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using Welford's algorithm with extended accumulation and returning an\n    extended precision result.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanwd( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsmeanwd( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsmeanwd( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dsmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using Welford's algorithm with extended accumulation and alternative\n    indexing semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanwd, base.strided.dsmean, base.strided.dsnanmeanwd, base.strided.meanwd, base.strided.smeanwd\n","base.strided.dsmeanwd.ndarray":"\nbase.strided.dsmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using Welford's algorithm with extended accumulation and alternative\n    indexing semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanwd, base.strided.dsmean, base.strided.dsnanmeanwd, base.strided.meanwd, base.strided.smeanwd","base.strided.dsnanmean":"\nbase.strided.dsnanmean( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values, using extended accumulation, and returning an\n    extended precision result.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmean( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsnanmean( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsnanmean( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dsnanmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using extended accumulation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsnanmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.dsmean, base.strided.nanmean, base.strided.sdsnanmean, base.strided.snanmean\n","base.strided.dsnanmean.ndarray":"\nbase.strided.dsnanmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using extended accumulation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsnanmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.dsmean, base.strided.nanmean, base.strided.sdsnanmean, base.strided.snanmean","base.strided.dsnanmeanors":"\nbase.strided.dsnanmeanors( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values, using ordinary recursive summation with\n    extended accumulation, and returning an extended precision result.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmeanors( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsnanmeanors( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsnanmeanors( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dsnanmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation with\n    extended accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsnanmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanors, base.strided.dsmeanors, base.strided.dsnanmean, base.strided.nanmeanors, base.strided.sdsnanmean, base.strided.snanmeanors\n","base.strided.dsnanmeanors.ndarray":"\nbase.strided.dsnanmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation with\n    extended accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsnanmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanors, base.strided.dsmeanors, base.strided.dsnanmean, base.strided.nanmeanors, base.strided.sdsnanmean, base.strided.snanmeanors","base.strided.dsnanmeanpn":"\nbase.strided.dsnanmeanpn( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values, using a two-pass error correction algorithm\n    with extended accumulation, and returning an extended precision result.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmeanpn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsnanmeanpn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsnanmeanpn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dsnanmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction algorithm\n    with extended accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsnanmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanpn, base.strided.dsmeanpn, base.strided.dsnanmean, base.strided.nanmeanpn, base.strided.sdsnanmean, base.strided.snanmeanpn\n","base.strided.dsnanmeanpn.ndarray":"\nbase.strided.dsnanmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction algorithm\n    with extended accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsnanmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanpn, base.strided.dsmeanpn, base.strided.dsnanmean, base.strided.nanmeanpn, base.strided.sdsnanmean, base.strided.snanmeanpn","base.strided.dsnanmeanwd":"\nbase.strided.dsnanmeanwd( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values, using Welford's algorithm with extended\n    accumulation, and returning an extended precision result.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmeanwd( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsnanmeanwd( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsnanmeanwd( N, x1, stride )\n    ~-0.3333\n\nbase.strided.dsnanmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm with extended\n    accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsnanmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanwd, base.strided.dsmeanwd, base.strided.dsnanmean, base.strided.nanmeanwd, base.strided.sdsnanmean, base.strided.snanmeanwd\n","base.strided.dsnanmeanwd.ndarray":"\nbase.strided.dsnanmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm with extended\n    accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnanmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsnanmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanwd, base.strided.dsmeanwd, base.strided.dsnanmean, base.strided.nanmeanwd, base.strided.sdsnanmean, base.strided.snanmeanwd","base.strided.dsnannsumors":"\nbase.strided.dsnannsumors( N, x, strideX, out, strideOut )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using ordinary recursive summation with extended\n    accumulation, and returning an extended precision result.\n\n    The `N` and stride parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns a sum equal to `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dsnannsumors( x.length, x, 1, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dsnannsumors( 4, x, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > out = new Float64Array( 2 );\n    > base.strided.dsnannsumors( N, x1, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\n\nbase.strided.dsnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using ordinary recursive summation with extended\n    accumulation and alternative indexing semantics, and returning an extended\n    precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dsnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dsnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsumors, base.strided.dsnansumors, base.strided.dssumors\n","base.strided.dsnannsumors.ndarray":"\nbase.strided.dsnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using ordinary recursive summation with extended\n    accumulation and alternative indexing semantics, and returning an extended\n    precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Float64Array\n        Output array.\n\n    strideOut: integer\n        Stride length for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Float64Array\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > var out = new Float64Array( 2 );\n    > base.strided.dsnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > out = new Float64Array( 2 );\n    > base.strided.dsnannsumors.ndarray( 4, x, 2, 1, out, 1, 0 )\n    <Float64Array>[ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsumors, base.strided.dsnansumors, base.strided.dssumors","base.strided.dsnansum":"\nbase.strided.dsnansum( N, x, strideX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using extended accumulation, and returning an\n    extended precision result.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnansum( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.dsnansum( 4, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsnansum( 4, x1, 2 )\n    -1.0\n\n\nbase.strided.dsnansum.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using extended accumulation and alternative\n    indexing semantics, and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnansum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsnansum.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnanmean, base.strided.dssum, base.strided.sdsnansum, base.strided.snansum\n","base.strided.dsnansum.ndarray":"\nbase.strided.dsnansum.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using extended accumulation and alternative\n    indexing semantics, and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnansum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsnansum.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnanmean, base.strided.dssum, base.strided.sdsnansum, base.strided.snansum","base.strided.dsnansumors":"\nbase.strided.dsnansumors( N, x, strideX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using ordinary recursive summation with extended\n    accumulation, and returning an extended precision result.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnansumors( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.dsnansumors( 4, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsnansumors( 4, x1, 2 )\n    -1.0\n\n\nbase.strided.dsnansumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation with extended\n    accumulation and alternative indexing semantics, and returning an extended\n    precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnansumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dsnansumors.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnanmeanors, base.strided.dssum, base.strided.dssumors, base.strided.snansumors\n","base.strided.dsnansumors.ndarray":"\nbase.strided.dsnansumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation with extended\n    accumulation and alternative indexing semantics, and returning an extended\n    precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnansumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dsnansumors.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnanmeanors, base.strided.dssum, base.strided.dssumors, base.strided.snansumors","base.strided.dsnansumpw":"\nbase.strided.dsnansumpw( N, x, strideX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using pairwise summation with extended accumulation,\n    and returning an extended precision result.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnansumpw( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.dsnansumpw( 4, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsnansumpw( 4, x1, 2 )\n    -1.0\n\n\nbase.strided.dsnansumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using pairwise summation with extended accumulation\n    and alternative indexing semantics, and returning an extended precision\n    result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnansumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dsnansumpw.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumpw, base.strided.dssum, base.strided.dssumpw, base.strided.snansumpw\n","base.strided.dsnansumpw.ndarray":"\nbase.strided.dsnansumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using pairwise summation with extended accumulation\n    and alternative indexing semantics, and returning an extended precision\n    result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.dsnansumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.dsnansumpw.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumpw, base.strided.dssum, base.strided.dssumpw, base.strided.snansumpw","base.strided.dsort2hp":"\nbase.strided.dsort2hp( N, order, x, strideX, y, strideY )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using heapsort.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided arrays are sorted *in-place* (i.e., the input strided\n    arrays are *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2hp( x.length, 1, x, 1, y, 1 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float64Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsort2hp( N, -1, x, 2, y, 2 )\n    <Float64Array>[ 3.0, -2.0, 1.0, -4.0 ]\n    > y\n    <Float64Array>[ 2.0, 1.0, 0.0, 3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dsort2hp( N, 1, x1, 2, y1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.dsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using heapsort and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float64Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssort2hp\n","base.strided.dsort2hp.ndarray":"\nbase.strided.dsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using heapsort and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float64Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssort2hp","base.strided.dsort2ins":"\nbase.strided.dsort2ins( N, order, x, strideX, y, strideY )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using insertion sort.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^2).\n\n    The algorithm is efficient for *small* strided arrays (typically N <= 20)\n    and is particularly efficient for sorting strided arrays which are already\n    substantially sorted.\n\n    The algorithm is *stable*, meaning that the algorithm does *not* change the\n    order of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided arrays are sorted *in-place* (i.e., the input strided\n    arrays is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2ins( x.length, 1, x, 1, y, 1 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float64Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2ins( 2, -1, x, 2, y, 2 )\n    <Float64Array>[ 3.0, -2.0, 1.0, -4.0 ]\n    > y\n    <Float64Array>[ 2.0, 1.0, 0.0, 3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsort2ins( 2, 1, x1, 2, y1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.dsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using insertion sort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float64Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsortins, base.strided.gsort2ins, base.strided.ssort2ins\n","base.strided.dsort2ins.ndarray":"\nbase.strided.dsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using insertion sort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float64Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsortins, base.strided.gsort2ins, base.strided.ssort2ins","base.strided.dsort2sh":"\nbase.strided.dsort2sh( N, order, x, strideX, y, strideY )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using Shellsort.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^(4/3)).\n\n    The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided arrays are sorted *in-place* (i.e., the input strided\n    arrays are *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2sh( x.length, 1, x, 1, y, 1 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float64Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsort2sh( N, -1, x, 2, y, 2 )\n    <Float64Array>[ 3.0, -2.0, 1.0, -4.0 ]\n    > y\n    <Float64Array>[ 2.0, 1.0, 0.0, 3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dsort2sh( N, 1, x1, 2, y1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.dsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using Shellsort and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float64Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssort2sh\n","base.strided.dsort2sh.ndarray":"\nbase.strided.dsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using Shellsort and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.dsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float64Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssort2sh","base.strided.dsorthp":"\nbase.strided.dsorthp( N, order, x, stride )\n    Sorts a double-precision floating-point strided array using heapsort.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided array is sorted *in-place* (i.e., the input strided array\n    is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.dsorthp( x.length, 1, x, 1 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsorthp( N, -1, x, 2 )\n    <Float64Array>[ 3.0, -2.0, 1.0, -4.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dsorthp( N, 1, x1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.dsorthp.ndarray( N, order, x, stride, offset )\n    Sorts a double-precision floating-point strided array using heapsort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.dsorthp.ndarray( x.length, 1, x, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsorthp.ndarray( N, 1, x, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssorthp\n","base.strided.dsorthp.ndarray":"\nbase.strided.dsorthp.ndarray( N, order, x, stride, offset )\n    Sorts a double-precision floating-point strided array using heapsort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.dsorthp.ndarray( x.length, 1, x, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsorthp.ndarray( N, 1, x, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssorthp","base.strided.dsortins":"\nbase.strided.dsortins( N, order, x, stride )\n    Sorts a double-precision floating-point strided array using insertion sort.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^2).\n\n    The algorithm is efficient for *small* strided arrays (typically N <= 20)\n    and is particularly efficient for sorting strided arrays which are already\n    substantially sorted.\n\n    The algorithm is *stable*, meaning that the algorithm does *not* change the\n    order of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided array is sorted *in-place* (i.e., the input strided array\n    is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.dsortins( x.length, 1, x, 1 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsortins( N, -1, x, 2 )\n    <Float64Array>[ 3.0, -2.0, 1.0, -4.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dsortins( N, 1, x1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.dsortins.ndarray( N, order, x, stride, offset )\n    Sorts a double-precision floating-point strided array using insertion sort\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.dsortins.ndarray( x.length, 1, x, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsortins.ndarray( N, 1, x, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2ins, base.strided.gsortins, base.strided.ssortins\n","base.strided.dsortins.ndarray":"\nbase.strided.dsortins.ndarray( N, order, x, stride, offset )\n    Sorts a double-precision floating-point strided array using insertion sort\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.dsortins.ndarray( x.length, 1, x, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsortins.ndarray( N, 1, x, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2ins, base.strided.gsortins, base.strided.ssortins","base.strided.dsortsh":"\nbase.strided.dsortsh( N, order, x, stride )\n    Sorts a double-precision floating-point strided array using Shellsort.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^(4/3)).\n\n    The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided array is sorted *in-place* (i.e., the input strided array\n    is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.dsortsh( x.length, 1, x, 1 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsortsh( N, -1, x, 2 )\n    <Float64Array>[ 3.0, -2.0, 1.0, -4.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dsortsh( N, 1, x1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.dsortsh.ndarray( N, order, x, stride, offset )\n    Sorts a double-precision floating-point strided array using Shellsort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.dsortsh.ndarray( x.length, 1, x, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsortsh.ndarray( N, 1, x, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssortsh\n","base.strided.dsortsh.ndarray":"\nbase.strided.dsortsh.ndarray( N, order, x, stride, offset )\n    Sorts a double-precision floating-point strided array using Shellsort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float64Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.dsortsh.ndarray( x.length, 1, x, 1, 0 )\n    <Float64Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsortsh.ndarray( N, 1, x, 2, 1 )\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssortsh","base.strided.dsqrt":"\nbase.strided.dsqrt( N, x, strideX, y, strideY )\n    Computes the principal square root for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dsqrt( x.length, x, 1, y, 1 )\n    <Float64Array>[ 0.0, 2.0, 3.0, ~3.464 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dsqrt( N, x, 2, y, -1 )\n    <Float64Array>[ 3.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dsqrt( N, x1, -2, y1, 1 )\n    <Float64Array>[ ~3.464, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.dsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the principal square root for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, 2.0, 3.0, ~3.464 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dcbrt, base.strided.drsqrt, strided.sqrt, base.strided.ssqrt\n","base.strided.dsqrt.ndarray":"\nbase.strided.dsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the principal square root for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 0.0, 2.0, 3.0, ~3.464 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dcbrt, base.strided.drsqrt, strided.sqrt, base.strided.ssqrt","base.strided.dssum":"\nbase.strided.dssum( N, x, strideX )\n    Computes the sum of single-precision floating-point strided array elements\n    using extended accumulation and returning an extended precision result.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dssum( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dssum( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dssum( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.dssum.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements\n    using extended accumulation and alternative indexing semantics and returning\n    an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dssum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dssum.ndarray(3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnansum, base.strided.sdssum, base.strided.ssum, base.strided.dsmean\n","base.strided.dssum.ndarray":"\nbase.strided.dssum.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements\n    using extended accumulation and alternative indexing semantics and returning\n    an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dssum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dssum.ndarray(3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnansum, base.strided.sdssum, base.strided.ssum, base.strided.dsmean","base.strided.dssumors":"\nbase.strided.dssumors( N, x, strideX )\n    Computes the sum of single-precision floating-point strided array elements\n    using ordinary recursive summation with extended accumulation and returning\n    an extended precision result.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dssumors( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dssumors( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dssumors( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.dssumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements\n    using ordinary recursive summation with extended accumulation and\n    alternative indexing semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dssumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dssumors.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnansumors, base.strided.dssum, base.strided.dsumors, base.strided.ssumors\n","base.strided.dssumors.ndarray":"\nbase.strided.dssumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements\n    using ordinary recursive summation with extended accumulation and\n    alternative indexing semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dssumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dssumors.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnansumors, base.strided.dssum, base.strided.dsumors, base.strided.ssumors","base.strided.dssumpw":"\nbase.strided.dssumpw( N, x, strideX )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation with extended accumulation and returning an\n    extended precision result.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dssumpw( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dssumpw( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dssumpw( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.dssumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation with extended accumulation and alternative indexing\n    semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dssumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dssumpw.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnansumpw, base.strided.dssum, base.strided.dsumpw, base.strided.ssumpw\n","base.strided.dssumpw.ndarray":"\nbase.strided.dssumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation with extended accumulation and alternative indexing\n    semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dssumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dssumpw.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnansumpw, base.strided.dssum, base.strided.dsumpw, base.strided.ssumpw","base.strided.dstdev":"\nbase.strided.dstdev( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdev( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dstdev( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dstdev( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dstdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dvariance, base.strided.sstdev, base.strided.stdev\n","base.strided.dstdev.ndarray":"\nbase.strided.dstdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.dvariance, base.strided.sstdev, base.strided.stdev","base.strided.dstdevch":"\nbase.strided.dstdevch( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevch( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dstdevch( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dstdevch( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dstdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevch, base.strided.dstdev, base.strided.dvariancech, base.strided.sstdevch, base.strided.stdevch\n","base.strided.dstdevch.ndarray":"\nbase.strided.dstdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevch, base.strided.dstdev, base.strided.dvariancech, base.strided.sstdevch, base.strided.stdevch","base.strided.dstdevpn":"\nbase.strided.dstdevpn( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevpn( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dstdevpn( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dstdevpn( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dstdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevpn, base.strided.dstdev, base.strided.dvariancepn, base.strided.sstdevpn, base.strided.stdevpn\n","base.strided.dstdevpn.ndarray":"\nbase.strided.dstdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevpn, base.strided.dstdev, base.strided.dvariancepn, base.strided.sstdevpn, base.strided.stdevpn","base.strided.dstdevtk":"\nbase.strided.dstdevtk( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevtk( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dstdevtk( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dstdevtk( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dstdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass textbook algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevtk, base.strided.dstdev, base.strided.dvariancetk, base.strided.sstdevtk, base.strided.stdevtk\n","base.strided.dstdevtk.ndarray":"\nbase.strided.dstdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass textbook algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevtk, base.strided.dstdev, base.strided.dvariancetk, base.strided.sstdevtk, base.strided.stdevtk","base.strided.dstdevwd":"\nbase.strided.dstdevwd( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevwd( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dstdevwd( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dstdevwd( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dstdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevwd, base.strided.dstdev, base.strided.dvariancewd, base.strided.sstdevwd, base.strided.stdevwd\n","base.strided.dstdevwd.ndarray":"\nbase.strided.dstdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevwd, base.strided.dstdev, base.strided.dvariancewd, base.strided.sstdevwd, base.strided.stdevwd","base.strided.dstdevyc":"\nbase.strided.dstdevyc( N, correction, x, stride )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevyc( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dstdevyc( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dstdevyc( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.dstdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevyc, base.strided.dstdev, base.strided.dvarianceyc, base.strided.sstdevyc, base.strided.stdevyc\n","base.strided.dstdevyc.ndarray":"\nbase.strided.dstdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dstdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dstdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevyc, base.strided.dstdev, base.strided.dvarianceyc, base.strided.sstdevyc, base.strided.stdevyc","base.strided.dsum":"\nbase.strided.dsum( N, x, strideX )\n    Computes the sum of double-precision floating-point strided array elements.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsum( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dsum( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsum( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.dsum.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsum.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.dmean, base.strided.dnansum, base.strided.ssum, base.strided.gsum\n","base.strided.dsum.ndarray":"\nbase.strided.dsum.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsum.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.dmean, base.strided.dnansum, base.strided.ssum, base.strided.gsum","base.strided.dsumkbn":"\nbase.strided.dsumkbn( N, x, strideX )\n    Computes the sum of double-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumkbn( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dsumkbn( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsumkbn( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.dsumkbn.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsumkbn.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn, base.strided.ssumkbn\n","base.strided.dsumkbn.ndarray":"\nbase.strided.dsumkbn.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsumkbn.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn, base.strided.ssumkbn","base.strided.dsumkbn2":"\nbase.strided.dsumkbn2( N, x, strideX )\n    Computes the sum of double-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumkbn2( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dsumkbn2( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsumkbn2( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.dsumkbn2.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsumkbn2.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn2, base.strided.dsum, base.strided.dsumkbn, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn2, base.strided.ssumkbn2\n","base.strided.dsumkbn2.ndarray":"\nbase.strided.dsumkbn2.ndarray( N, x, strideX, offsetX )\n    Computes the sum of double-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsumkbn2.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn2, base.strided.dsum, base.strided.dsumkbn, base.strided.dsumors, base.strided.dsumpw, base.strided.gsumkbn2, base.strided.ssumkbn2","base.strided.dsumors":"\nbase.strided.dsumors( N, x, stride )\n    Computes the sum of double-precision floating-point strided array elements\n    using ordinary recursive summation.\n\n    The `N` and `stride` parameters determine which elements in \n    the strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumors( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dsumors( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsumors( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.dsumors.ndarray( N, x, stride, offset )\n    Computes the sum of double-precision floating-point strided array elements\n    using ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsumors.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumors, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumpw, base.strided.gsumors, base.strided.ssumors\n","base.strided.dsumors.ndarray":"\nbase.strided.dsumors.ndarray( N, x, stride, offset )\n    Computes the sum of double-precision floating-point strided array elements\n    using ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsumors.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumors, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumpw, base.strided.gsumors, base.strided.ssumors","base.strided.dsumpw":"\nbase.strided.dsumpw( N, x, stride )\n    Computes the sum of double-precision floating-point strided array elements\n    using pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumpw( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.dsumpw( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.dsumpw( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.dsumpw.ndarray( N, x, stride, offset )\n    Computes the sum of double-precision floating-point strided array elements\n    using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsumpw.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumpw, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.gsumpw, base.strided.ssumpw\n","base.strided.dsumpw.ndarray":"\nbase.strided.dsumpw.ndarray( N, x, stride, offset )\n    Computes the sum of double-precision floating-point strided array elements\n    using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.dsumpw.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumpw, base.strided.dsum, base.strided.dsumkbn2, base.strided.dsumors, base.strided.gsumpw, base.strided.ssumpw","base.strided.dsvariance":"\nbase.strided.dsvariance( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    using extended accumulation and returning an extended precision result.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsvariance( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsvariance( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsvariance( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dsvariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using extended accumulation and alternative indexing semantics and\n    returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsvariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsvariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariance, base.strided.variance, base.strided.svariance\n","base.strided.dsvariance.ndarray":"\nbase.strided.dsvariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using extended accumulation and alternative indexing semantics and\n    returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsvariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsvariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariance, base.strided.variance, base.strided.svariance","base.strided.dsvariancepn":"\nbase.strided.dsvariancepn( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    using a two-pass algorithm with extended accumulation and returning an\n    extended precision result.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsvariancepn( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dsvariancepn( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dsvariancepn( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dsvariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using a two-pass algorithm with extended accumulation and alternative\n    indexing semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsvariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsvariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancepn, base.strided.dsvariance, base.strided.variancepn, base.strided.svariancepn\n","base.strided.dsvariancepn.ndarray":"\nbase.strided.dsvariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using a two-pass algorithm with extended accumulation and alternative\n    indexing semantics and returning an extended precision result.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dsvariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dsvariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancepn, base.strided.dsvariance, base.strided.variancepn, base.strided.svariancepn","base.strided.dswap":"\nbase.strided.dswap( N, x, strideX, y, strideY )\n    Interchanges two double-precision floating-point vectors.\n\n    The `N` and stride parameters determine how values from `x` are swapped\n    with values from `y`.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the vectors are unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Second input array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.dswap( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.dswap( 3, x, -2, y, 1 )\n    <Float64Array>[ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n    // Using typed array views:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.dswap( 3, x1, -2, y1, 1 )\n    <Float64Array>[ 6.0, 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.dswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Interchanges two double-precision floating-point vectors using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Second input array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.dswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.dswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dcopy, base.strided.gswap, base.strided.sswap, dswap\n","base.strided.dswap.ndarray":"\nbase.strided.dswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Interchanges two double-precision floating-point vectors using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Second input array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float64Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.dswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.dswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dcopy, base.strided.gswap, base.strided.sswap, dswap","base.strided.dtrunc":"\nbase.strided.dtrunc( N, x, strideX, y, strideY )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward zero and assigns the results to elements in a double-precision\n    floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dtrunc( x.length, x, 1, y, 1 )\n    <Float64Array>[ 1.0, 2.0, -3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dtrunc( N, x, 2, y, -1 )\n    <Float64Array>[ -3.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dtrunc( N, x1, -2, y1, 1 )\n    <Float64Array>[ 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.dtrunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward zero and assigns the results to elements in a double-precision\n    floating-point strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dtrunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dtrunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dceil, base.strided.dfloor, strided.trunc, base.strided.strunc\n","base.strided.dtrunc.ndarray":"\nbase.strided.dtrunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward zero and assigns the results to elements in a double-precision\n    floating-point strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float64Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.dtrunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dtrunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dceil, base.strided.dfloor, strided.trunc, base.strided.strunc","base.strided.dtypeEnum2Str":"\nbase.strided.dtypeEnum2Str( dtype )\n    Returns the data type string associated with a strided array data type\n    enumeration constant.\n\n    Parameters\n    ----------\n    dtype: integer\n        Data type enumeration constant.\n\n    Returns\n    -------\n    out: string|null\n        Data type string.\n\n    Examples\n    --------\n    > var out = base.strided.dtypeEnum2Str( base.strided.dtypeStr2Enum( 'float64' ) )\n    'float64'\n\n    See Also\n    --------\n    base.strided.dtypeStr2Enum\n","base.strided.dtypeResolveEnum":"\nbase.strided.dtypeResolveEnum( dtype )\n    Returns the enumeration constant associated with a supported strided array\n    data type value.\n\n    Downstream consumers of this function should *not* rely on specific integer\n    values (e.g., `INT8 == 0`). Instead, the function should be used in an\n    opaque manner.\n\n    Parameters\n    ----------\n    dtype: any\n        Data type value.\n\n    Returns\n    -------\n    out: integer|null\n        Enumeration constant.\n\n    Examples\n    --------\n    > var out = base.strided.dtypeResolveEnum( 'float64' )\n    <number>\n    > out = base.strided.dtypeResolveEnum( base.strided.dtypeStr2Enum( 'float64' ) )\n    <number>\n\n    See Also\n    --------\n    base.strided.dtypeResolveStr\n","base.strided.dtypeResolveStr":"\nbase.strided.dtypeResolveStr( dtype )\n    Returns the data type string associated with a supported data type value.\n\n    Parameters\n    ----------\n    dtype: any\n        Data type value.\n\n    Returns\n    -------\n    out: string|null\n        Data type string.\n\n    Examples\n    --------\n    > var out = base.strided.dtypeResolveStr( 'float64' )\n    'float64'\n    > out = base.strided.dtypeResolveStr( base.strided.dtypeStr2Enum( 'float64' ) )\n    'float64'\n\n    See Also\n    --------\n    base.strided.dtypeResolveEnum\n","base.strided.dtypeStr2Enum":"\nbase.strided.dtypeStr2Enum( dtype )\n    Returns the enumeration constant associated with a strided array data type\n    string.\n\n    Downstream consumers of this function should *not* rely on specific integer\n    values (e.g., `INT8 == 0`). Instead, the function should be used in an\n    opaque manner.\n\n    Parameters\n    ----------\n    dtype: string\n        Data type string.\n\n    Returns\n    -------\n    out: integer|null\n        Enumeration constant.\n\n    Examples\n    --------\n    > var out = base.strided.dtypeStr2Enum( 'float64' )\n    <number>\n\n    See Also\n    --------\n    base.strided.dtypeEnum2Str\n","base.strided.dvariance":"\nbase.strided.dvariance( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariance( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dvariance( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dvariance( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dvariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariance, base.strided.dstdev, base.strided.dvarm, base.strided.svariance, base.strided.variance\n","base.strided.dvariance.ndarray":"\nbase.strided.dvariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariance, base.strided.dstdev, base.strided.dvarm, base.strided.svariance, base.strided.variance","base.strided.dvariancech":"\nbase.strided.dvariancech( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancech( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dvariancech( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dvariancech( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dvariancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass trial mean algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvariancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancech, base.strided.dstdevch, base.strided.dvariance, base.strided.svariancech, base.strided.variancech\n","base.strided.dvariancech.ndarray":"\nbase.strided.dvariancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass trial mean algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvariancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancech, base.strided.dstdevch, base.strided.dvariance, base.strided.svariancech, base.strided.variancech","base.strided.dvariancepn":"\nbase.strided.dvariancepn( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancepn( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dvariancepn( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dvariancepn( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dvariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.dvariance, base.strided.svariancepn, base.strided.variancepn\n","base.strided.dvariancepn.ndarray":"\nbase.strided.dvariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancepn, base.strided.dstdevpn, base.strided.dvariance, base.strided.svariancepn, base.strided.variancepn","base.strided.dvariancetk":"\nbase.strided.dvariancetk( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancetk( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dvariancetk( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dvariancetk( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dvariancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass textbook algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvariancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.dvariance, base.strided.svariancetk, base.strided.variancetk\n","base.strided.dvariancetk.ndarray":"\nbase.strided.dvariancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass textbook algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvariancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancetk, base.strided.dstdevtk, base.strided.dvariance, base.strided.svariancetk, base.strided.variancetk","base.strided.dvariancewd":"\nbase.strided.dvariancewd( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancewd( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dvariancewd( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dvariancewd( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dvariancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvariancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.dvariance, base.strided.svariancewd, base.strided.variancewd\n","base.strided.dvariancewd.ndarray":"\nbase.strided.dvariancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvariancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvariancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancewd, base.strided.dstdevwd, base.strided.dvariance, base.strided.svariancewd, base.strided.variancewd","base.strided.dvarianceyc":"\nbase.strided.dvarianceyc( N, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass algorithm proposed by Youngs and Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarianceyc( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.dvarianceyc( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.dvarianceyc( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.dvarianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass algorithm proposed by Youngs and Cramer and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvarianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.dvariance, base.strided.svarianceyc, base.strided.varianceyc\n","base.strided.dvarianceyc.ndarray":"\nbase.strided.dvarianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass algorithm proposed by Youngs and Cramer and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvarianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvarianceyc, base.strided.dstdevyc, base.strided.dvariance, base.strided.svarianceyc, base.strided.varianceyc","base.strided.dvarm":"\nbase.strided.dvarm( N, mean, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mean: number\n        Mean.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarm( x.length, 1.0/3.0, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvarm( N, 1.0/3.0, 1, x, 2 )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dvarm( N, 1.0/3.0, 1, x1, 2 )\n    ~4.3333\n\nbase.strided.dvarm.ndarray( N, mean, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mean: number\n        Mean.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarm.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvarm.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariance\n","base.strided.dvarm.ndarray":"\nbase.strided.dvarm.ndarray( N, mean, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mean: number\n        Mean.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarm.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvarm.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariance","base.strided.dvarmpn":"\nbase.strided.dvarmpn( N, mean, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using Neely's correction algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mean: number\n        Mean.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarmpn( x.length, 1.0/3.0, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvarmpn( N, 1.0/3.0, 1, x, 2 )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dvarmpn( N, 1.0/3.0, 1, x1, 2 )\n    ~4.3333\n\nbase.strided.dvarmpn.ndarray( N, mean, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using Neely's correction algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mean: number\n        Mean.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarmpn.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvarmpn.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvarm\n","base.strided.dvarmpn.ndarray":"\nbase.strided.dvarmpn.ndarray( N, mean, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using Neely's correction algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mean: number\n        Mean.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarmpn.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvarmpn.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvarm","base.strided.dvarmtk":"\nbase.strided.dvarmtk( N, mean, correction, x, stride )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using a one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mean: number\n        Mean.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarmtk( x.length, 1.0/3.0, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvarmtk( N, 1.0/3.0, 1, x, 2 )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.dvarmtk( N, 1.0/3.0, 1, x1, 2 )\n    ~4.3333\n\nbase.strided.dvarmtk.ndarray( N, mean, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mean: number\n        Mean.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarmtk.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvarmtk.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvarm\n","base.strided.dvarmtk.ndarray":"\nbase.strided.dvarmtk.ndarray( N, mean, correction, x, stride, offset )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mean: number\n        Mean.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float64Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.dvarmtk.ndarray( x.length, 1.0/3.0, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.dvarmtk.ndarray( N, 1.0/3.0, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvarm","base.strided.gapx":"\nbase.strided.gapx( N, alpha, x, stride )\n    Adds a constant to each element in a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > var alpha = 5.0;\n    > base.strided.gapx( x.length, alpha, x, 1 )\n    [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > alpha = 5.0;\n    > var stride = 2;\n    > base.strided.gapx( N, alpha, x, stride )\n    [ 3.0, 1.0, 8.0, -5.0, 9.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > alpha = 5.0;\n    > stride = 2;\n    > base.strided.gapx( N, alpha, x1, stride )\n    <Float64Array>[ 3.0, 3.0, 1.0, 5.0, -1.0 ]\n    > x0\n    <Float64Array>[ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\nbase.strided.gapx.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each element in a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > var alpha = 5.0;\n    > base.strided.gapx.ndarray( x.length, alpha, x, 1, 0 )\n    [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > alpha = 5.0;\n    > var stride = 2;\n    > base.strided.gapx.ndarray( N, alpha, x, stride, 1 )\n    [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dapx, base.strided.sapx\n","base.strided.gapx.ndarray":"\nbase.strided.gapx.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each element in a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > var alpha = 5.0;\n    > base.strided.gapx.ndarray( x.length, alpha, x, 1, 0 )\n    [ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > alpha = 5.0;\n    > var stride = 2;\n    > base.strided.gapx.ndarray( N, alpha, x, stride, 1 )\n    [ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dapx, base.strided.sapx","base.strided.gapxsum":"\nbase.strided.gapxsum( N, alpha, x, stride )\n    Adds a constant to each strided array element and computes the sum.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsum( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gapxsum( N, 5.0, x, stride )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gapxsum( N, 5.0, x1, stride )\n    14.0\n\nbase.strided.gapxsum.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each strided array element and computes the sum using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gapxsum.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.gapxsumpw, base.strided.gsum, base.strided.sapxsum\n","base.strided.gapxsum.ndarray":"\nbase.strided.gapxsum.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each strided array element and computes the sum using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gapxsum.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.gapxsumpw, base.strided.gsum, base.strided.sapxsum","base.strided.gapxsumkbn":"\nbase.strided.gapxsumkbn( N, alpha, x, strideX )\n    Adds a scalar constant to each strided array element and computes the sum\n    using an improved Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumkbn( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and stride parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > base.strided.gapxsumkbn( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.gapxsumkbn( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.gapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each strided array element and computes the sum\n    using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > base.strided.gapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumkbn, base.strided.gapxsum, base.strided.gsumkbn, base.strided.sapxsumkbn\n","base.strided.gapxsumkbn.ndarray":"\nbase.strided.gapxsumkbn.ndarray( N, alpha, x, strideX, offsetX )\n    Adds a scalar constant to each strided array element and computes the sum\n    using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Scalar constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > base.strided.gapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumkbn, base.strided.gapxsum, base.strided.gsumkbn, base.strided.sapxsumkbn","base.strided.gapxsumkbn2":"\nbase.strided.gapxsumkbn2( N, alpha, x, stride )\n    Adds a constant to each strided array element and computes the sum using a\n    second-order iterative Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumkbn2( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gapxsumkbn2( N, 5.0, x, stride )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gapxsumkbn2( N, 5.0, x1, stride )\n    14.0\n\nbase.strided.gapxsumkbn2.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each strided array element and computes the sum using a\n    second-order iterative Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gapxsumkbn2.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumkbn2, base.strided.gapxsum, base.strided.gsumkbn2, base.strided.sapxsumkbn2\n","base.strided.gapxsumkbn2.ndarray":"\nbase.strided.gapxsumkbn2.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each strided array element and computes the sum using a\n    second-order iterative Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gapxsumkbn2.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumkbn2, base.strided.gapxsum, base.strided.gsumkbn2, base.strided.sapxsumkbn2","base.strided.gapxsumors":"\nbase.strided.gapxsumors( N, alpha, x, stride )\n    Adds a constant to each strided array element and computes the sum using\n    ordinary recursive summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumors( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gapxsumors( N, 5.0, x, stride )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gapxsumors( N, 5.0, x1, stride )\n    14.0\n\nbase.strided.gapxsumors.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each strided array element and computes the sum using\n    ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gapxsumors.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumors, base.strided.gapxsum, base.strided.gsumors, base.strided.sapxsumors\n","base.strided.gapxsumors.ndarray":"\nbase.strided.gapxsumors.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each strided array element and computes the sum using\n    ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gapxsumors.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumors, base.strided.gapxsum, base.strided.gsumors, base.strided.sapxsumors","base.strided.gapxsumpw":"\nbase.strided.gapxsumpw( N, alpha, x, stride )\n    Adds a constant to each strided array element and computes the sum using\n    pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumpw( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gapxsumpw( N, 5.0, x, stride )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gapxsumpw( N, 5.0, x1, stride )\n    14.0\n\nbase.strided.gapxsumpw.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each strided array element and computes the sum using\n    pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumpw, base.strided.gapxsum, base.strided.gsumpw, base.strided.sapxsumpw\n","base.strided.gapxsumpw.ndarray":"\nbase.strided.gapxsumpw.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each strided array element and computes the sum using\n    pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gapxsumpw.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumpw, base.strided.gapxsum, base.strided.gsumpw, base.strided.sapxsumpw","base.strided.gasum":"\nbase.strided.gasum( N, x, stride )\n    Computes the sum of the absolute values.\n\n    The sum of absolute values corresponds to the *L1* norm.\n\n    The `N` and `stride` parameters determine which elements in `x` are used to\n    compute the sum.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` or `stride` is less than or equal to `0`, the function returns `0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    sum: number\n        Sum of absolute values.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n    > var s = base.strided.gasum( x.length, x, 1 )\n    19.0\n\n    // Sum every other value:\n    > s = base.strided.gasum( 3, x, 2 )\n    10.0\n\n    // Use view offset; e.g., starting at 2nd element:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > s = base.strided.gasum( 3, x1, 2 )\n    12.0\n\n\nbase.strided.gasum.ndarray( N, x, stride, offset )\n    Computes the sum of absolute values using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    sum: number\n        Sum of absolute values.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n    > var s = base.strided.gasum.ndarray( x.length, x, 1, 0 )\n    19.0\n\n    // Sum the last three elements:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > s = base.strided.gasum.ndarray( 3, x, -1, x.length-1 )\n    15.0\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.sasum\n","base.strided.gasum.ndarray":"\nbase.strided.gasum.ndarray( N, x, stride, offset )\n    Computes the sum of absolute values using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    sum: number\n        Sum of absolute values.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];\n    > var s = base.strided.gasum.ndarray( x.length, x, 1, 0 )\n    19.0\n\n    // Sum the last three elements:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > s = base.strided.gasum.ndarray( 3, x, -1, x.length-1 )\n    15.0\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.sasum","base.strided.gasumpw":"\nbase.strided.gasumpw( N, x, stride )\n    Computes the sum of absolute values (L1 norm) of strided array elements\n    using pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.gasumpw( x.length, x, 1 )\n    5.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float64Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gasumpw( N, x, stride )\n    5.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gasumpw( N, x1, stride )\n    5.0\n\nbase.strided.gasumpw.ndarray( N, x, stride, offset )\n    Computes the sum of absolute values (L1 norm) of strided array elements\n    using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.gasumpw.ndarray( x.length, x, 1, 0 )\n    5.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gasumpw.ndarray( N, x, 2, 1 )\n    5.0\n\n    See Also\n    --------\n    base.strided.gasum, base.strided.dasumpw, base.strided.gsumpw, base.strided.sasumpw\n","base.strided.gasumpw.ndarray":"\nbase.strided.gasumpw.ndarray( N, x, stride, offset )\n    Computes the sum of absolute values (L1 norm) of strided array elements\n    using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.gasumpw.ndarray( x.length, x, 1, 0 )\n    5.0\n\n    // Using offset parameter:\n    > var x = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gasumpw.ndarray( N, x, 2, 1 )\n    5.0\n\n    See Also\n    --------\n    base.strided.gasum, base.strided.dasumpw, base.strided.gsumpw, base.strided.sasumpw","base.strided.gaxpy":"\nbase.strided.gaxpy( N, alpha, x, strideX, y, strideY )\n    Multiplies `x` by a constant `alpha` and adds the result to `y`.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n    > base.strided.gaxpy( x.length, 5.0, x, 1, y, 1 )\n    [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n    // Using `N` and stride parameters:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n    > base.strided.gaxpy( 3, 5.0, x, 2, y, -1 )\n    [ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.gaxpy( 3, 5.0, x1, -2, y1, 1 )\n    <Float64Array>[ 40.0, 31.0, 22.0 ]\n    > y0\n    <Float64Array>[ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.strided.gaxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n    Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n    > base.strided.gaxpy.ndarray( x.length, 5.0, x, 1, 0, y, 1, 0 )\n    [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n    > base.strided.gaxpy.ndarray( 3, 5.0, x, 2, 1, y, -1, y.length-1 )\n    [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n    See Also\n    --------\n    base.strided.daxpy, base.strided.saxpy\n","base.strided.gaxpy.ndarray":"\nbase.strided.gaxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n    Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > var y = [ 1.0, 1.0, 1.0, 1.0, 1.0 ];\n    > base.strided.gaxpy.ndarray( x.length, 5.0, x, 1, 0, y, 1, 0 )\n    [ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n    > base.strided.gaxpy.ndarray( 3, 5.0, x, 2, 1, y, -1, y.length-1 )\n    [ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n    See Also\n    --------\n    base.strided.daxpy, base.strided.saxpy","base.strided.gcopy":"\nbase.strided.gcopy( N, x, strideX, y, strideY )\n    Copies values from `x` into `y`.\n\n    The `N` and stride parameters determine how values from `x` are copied into\n    `y`.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: ArrayLikeObject\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n    > base.strided.gcopy( x.length, x, 1, y, 1 )\n    [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n    > base.strided.gcopy( 3, x, -2, y, 1 )\n    [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n    // Using typed array views:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.gcopy( 3, x1, -2, y1, 1 )\n    <Float64Array>[ 6.0, 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.gcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Copies values from `x` into `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: ArrayLikeObject\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n    > base.strided.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n    > base.strided.gcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dcopy, base.strided.scopy\n","base.strided.gcopy.ndarray":"\nbase.strided.gcopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Copies values from `x` into `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: ArrayLikeObject\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n    > base.strided.gcopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n    > base.strided.gcopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dcopy, base.strided.scopy","base.strided.gcusum":"\nbase.strided.gcusum( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of strided array elements.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusum( x.length, 0.0, x, 1, y, 1 )\n    [ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusum( N, 0.0, x, 2, y, 2 )\n    [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gcusum( N, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.gcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusum.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusumpw, base.strided.scusum\n","base.strided.gcusum.ndarray":"\nbase.strided.gcusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusum.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusumpw, base.strided.scusum","base.strided.gcusumkbn":"\nbase.strided.gcusumkbn( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of strided array elements using an improved\n    Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Stride length for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumkbn( x.length, 0.0, x, 1, y, 1 )\n    [ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and stride parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumkbn( 3, 0.0, x, 2, y, 2 )\n    [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.gcusumkbn( 3, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.gcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using an improved\n    Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Stride length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumkbn, base.strided.gcusum, base.strided.gcusumkbn2, base.strided.scusumkbn\n","base.strided.gcusumkbn.ndarray":"\nbase.strided.gcusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using an improved\n    Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Stride length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Stride length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumkbn, base.strided.gcusum, base.strided.gcusumkbn2, base.strided.scusumkbn","base.strided.gcusumkbn2":"\nbase.strided.gcusumkbn2( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of strided array elements using a second-order\n    iterative Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumkbn2( x.length, 0.0, x, 1, y, 1 )\n    [ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumkbn2( N, 0.0, x, 2, y, 2 )\n    [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gcusumkbn2( N, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.gcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using a second-order\n    iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumkbn2.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumkbn2, base.strided.gcusum, base.strided.gcusumkbn, base.strided.scusumkbn2\n","base.strided.gcusumkbn2.ndarray":"\nbase.strided.gcusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using a second-order\n    iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumkbn2.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumkbn2, base.strided.gcusum, base.strided.gcusumkbn, base.strided.scusumkbn2","base.strided.gcusumors":"\nbase.strided.gcusumors( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of strided array elements using ordinary\n    recursive summation.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumors( x.length, 0.0, x, 1, y, 1 )\n    [ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumors( N, 0.0, x, 2, y, 2 )\n    [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gcusumors( N, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.gcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using ordinary\n    recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumors.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumors, base.strided.gcusum, base.strided.gcusumpw, base.strided.scusumors\n","base.strided.gcusumors.ndarray":"\nbase.strided.gcusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using ordinary\n    recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumors.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumors, base.strided.gcusum, base.strided.gcusumpw, base.strided.scusumors","base.strided.gcusumpw":"\nbase.strided.gcusumpw( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of strided array elements using pairwise\n    summation.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumpw( x.length, 0.0, x, 1, y, 1 )\n    [ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumpw( N, 0.0, x, 2, y, 2 )\n    [ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float64Array( x0.length );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gcusumpw( N, 0.0, x1, 2, y1, 1 )\n    <Float64Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\nbase.strided.gcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using pairwise\n    summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumpw.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumpw, base.strided.gcusum, base.strided.scusumpw\n","base.strided.gcusumpw.ndarray":"\nbase.strided.gcusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of strided array elements using pairwise\n    summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > var y = [ 0.0, 0.0, 0.0 ];\n    > base.strided.gcusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float64Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gcusumpw.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumpw, base.strided.gcusum, base.strided.scusumpw","base.strided.gdot":"\nbase.strided.gdot( N, x, strideX, y, strideY )\n    Computes the dot product of two vectors.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: number\n        The dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n    > var y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n    > var out = base.strided.gdot( x.length, x, 1, y, 1 )\n    -5.0\n\n    // Strides:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n    > out = base.strided.gdot( 3, x, 2, y, -1 )\n    9.0\n\n    // Using view offsets:\n    > x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float64Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n    > out = base.strided.gdot( 3, x1, -2, y1, 1 )\n    128.0\n\n\nbase.strided.gdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the dot product of two vectors using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing based on a starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: number\n        The dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n    > var y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n    > var out = base.strided.gdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    -5.0\n\n    // Strides:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n    > out = base.strided.gdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n    9.0\n\n    // Using offset indices:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n    > out = base.strided.gdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n    128.0\n\n    See Also\n    --------\n    base.strided.ddot, base.strided.sdot, gdot\n","base.strided.gdot.ndarray":"\nbase.strided.gdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the dot product of two vectors using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing based on a starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: number\n        The dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n    > var y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n    > var out = base.strided.gdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    -5.0\n\n    // Strides:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ];\n    > out = base.strided.gdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n    9.0\n\n    // Using offset indices:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n    > out = base.strided.gdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n    128.0\n\n    See Also\n    --------\n    base.strided.ddot, base.strided.sdot, gdot","base.strided.gfill":"\nbase.strided.gfill( N, alpha, x, stride )\n    Fills a strided array with a specified scalar value.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: any\n        Constant.\n\n    x: ArrayLikeObject\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: ArrayLikeObject\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.gfill( x.length, 5.0, x, 1 )\n    [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gfill( N, 5.0, x, 2 )\n    [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gfill( N, 5.0, x1, 2 )\n    <Float64Array>[ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n    > x0\n    <Float64Array>[ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.gfill.ndarray( N, alpha, x, stride, offset )\n    Fills a strided array with a specified scalar value using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: any\n        Constant.\n\n    x: ArrayLikeObject\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: ArrayLikeObject\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.gfill.ndarray( x.length, 5.0, x, 1, 0 )\n    [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gfill.ndarray( N, 5.0, x, 2, 1 )\n    [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n    See Also\n    --------\n    base.strided.dfill, base.strided.sfill\n","base.strided.gfill.ndarray":"\nbase.strided.gfill.ndarray( N, alpha, x, stride, offset )\n    Fills a strided array with a specified scalar value using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: any\n        Constant.\n\n    x: ArrayLikeObject\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: ArrayLikeObject\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.gfill.ndarray( x.length, 5.0, x, 1, 0 )\n    [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gfill.ndarray( N, 5.0, x, 2, 1 )\n    [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n    See Also\n    --------\n    base.strided.dfill, base.strided.sfill","base.strided.gfillBy":"\nbase.strided.gfillBy( N, x, stride, clbk[, thisArg] )\n    Fills a strided array according to a provided callback function.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - aidx: array index.\n    - sidx: strided index (offset + aidx*stride).\n    - array: the input array.\n\n    The callback return value is used as the fill value for the current array\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    x: ArrayLikeObject\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function fill() { return 5.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.gfillBy( x.length, x, 1, fill )\n    [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gfillBy( N, x, 2, fill )\n    [ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gfillBy( N, x1, 2, fill )\n    <Float64Array>[ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n    > x0\n    <Float64Array>[ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.gfillBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Fills a strided array according to a provided callback function and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    x: ArrayLikeObject\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function fill() { return 5.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.gfillBy.ndarray( x.length, x, 1, 0, fill )\n    [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gfillBy.ndarray( N, x, 2, 1, fill )\n    [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n    See Also\n    --------\n    base.strided.gfill\n","base.strided.gfillBy.ndarray":"\nbase.strided.gfillBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Fills a strided array according to a provided callback function and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    x: ArrayLikeObject\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function fill() { return 5.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.gfillBy.ndarray( x.length, x, 1, 0, fill )\n    [ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gfillBy.ndarray( N, x, 2, 1, fill )\n    [ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n    See Also\n    --------\n    base.strided.gfill","base.strided.gnannsumkbn":"\nbase.strided.gnannsumkbn( N, x, strideX, out, strideOut )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    an improved Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns a sum equal to `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > var out = [ 0.0, 0 ];\n    > base.strided.gnannsumkbn( x.length, x, 1, out, 1 )\n    [ 1.0, 3 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n    > out = [ 0.0, 0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gnannsumkbn( N, x, 2, out, 1 )\n    [ 1.0, 3 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > out = [ 0.0, 0 ];\n    > base.strided.gnannsumkbn( N, x1, 2, out, 1 )\n    <Float64Array>[ 1.0, 3 ]\n\nbase.strided.gnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > var out = [ 0.0, 0 ];\n    > base.strided.gnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\n    [ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > out = [ 0.0, 0 ];\n    > base.strided.gnannsumkbn.ndarray( N, x, 2, 1, out, 1, 0 )\n    [ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsumkbn\n","base.strided.gnannsumkbn.ndarray":"\nbase.strided.gnannsumkbn.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    strideOut: integer\n        Index increment for `out`.\n\n    offsetOut: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array whose first element is the sum and whose second element is\n        the number of non-NaN elements.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > var out = [ 0.0, 0 ];\n    > base.strided.gnannsumkbn.ndarray( x.length, x, 1, 0, out, 1, 0 )\n    [ 1.0, 3 ]\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > out = [ 0.0, 0 ];\n    > base.strided.gnannsumkbn.ndarray( N, x, 2, 1, out, 1, 0 )\n    [ 1.0, 3 ]\n\n    See Also\n    --------\n    base.strided.dnannsumkbn","base.strided.gnansum":"\nbase.strided.gnansum( N, x, stride )\n    Computes the sum of strided array elements, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansum( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gnansum( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gnansum( N, x1, stride )\n    -1.0\n\nbase.strided.gnansum.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gnansum.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.snansum, base.strided.gsum, base.strided.nanmean\n","base.strided.gnansum.ndarray":"\nbase.strided.gnansum.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gnansum.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.snansum, base.strided.gsum, base.strided.nanmean","base.strided.gnansumkbn":"\nbase.strided.gnansumkbn( N, x, stride )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    an improved Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumkbn( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gnansumkbn( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gnansumkbn( N, x1, stride )\n    -1.0\n\nbase.strided.gnansumkbn.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gnansumkbn.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn, base.strided.snansumkbn\n","base.strided.gnansumkbn.ndarray":"\nbase.strided.gnansumkbn.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    an improved Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gnansumkbn.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn, base.strided.snansumkbn","base.strided.gnansumkbn2":"\nbase.strided.gnansumkbn2( N, x, stride )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    a second-order iterative Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumkbn2( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gnansumkbn2( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gnansumkbn2( N, x1, stride )\n    -1.0\n\nbase.strided.gnansumkbn2.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    a second-order iterative Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gnansumkbn2.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn2, base.strided.gnansum, base.strided.gnansumkbn, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn2, base.strided.snansumkbn2\n","base.strided.gnansumkbn2.ndarray":"\nbase.strided.gnansumkbn2.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    a second-order iterative Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gnansumkbn2.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn2, base.strided.gnansum, base.strided.gnansumkbn, base.strided.gnansumors, base.strided.gnansumpw, base.strided.gsumkbn2, base.strided.snansumkbn2","base.strided.gnansumors":"\nbase.strided.gnansumors( N, x, stride )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    ordinary recursive summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumors( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gnansumors( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gnansumors( N, x1, stride )\n    -1.0\n\nbase.strided.gnansumors.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gnansumors.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumors, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumpw, base.strided.gsumors, base.strided.snansumors\n","base.strided.gnansumors.ndarray":"\nbase.strided.gnansumors.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gnansumors.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumors, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumpw, base.strided.gsumors, base.strided.snansumors","base.strided.gnansumpw":"\nbase.strided.gnansumpw( N, x, stride )\n    Computes the sum of strided array elements, ignoring `NaN` values and\n    pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumpw( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gnansumpw( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gnansumpw( N, x1, stride )\n    -1.0\n\nbase.strided.gnansumpw.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gnansumpw.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumpw, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gsumpw, base.strided.snansumpw\n","base.strided.gnansumpw.ndarray":"\nbase.strided.gnansumpw.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.gnansumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gnansumpw.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumpw, base.strided.gnansum, base.strided.gnansumkbn2, base.strided.gnansumors, base.strided.gsumpw, base.strided.snansumpw","base.strided.gnrm2":"\nbase.strided.gnrm2( N, x, stride )\n    Computes the L2-norm of a vector.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0` or `stride <= 0`, the function returns `0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The L2-norm.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gnrm2( x.length, x, 1 )\n    3.0\n\n    // Using `N` and stride parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > base.strided.gnrm2( 3, x, 2 )\n    3.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.gnrm2( 3, x1, 2 )\n    3.0\n\n\nbase.strided.gnrm2.ndarray( N, x, stride, offset )\n    Computes the L2-norm of a vector using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    nrm2: number\n        The L2-norm.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gnrm2.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > base.strided.gnrm2.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dnrm2, base.strided.snrm2\n","base.strided.gnrm2.ndarray":"\nbase.strided.gnrm2.ndarray( N, x, stride, offset )\n    Computes the L2-norm of a vector using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    nrm2: number\n        The L2-norm.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gnrm2.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > base.strided.gnrm2.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dnrm2, base.strided.snrm2","base.strided.grev":"\nbase.strided.grev( N, x, stride )\n    Reverses a strided array in-place.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: ArrayLikeObject\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.grev( x.length, x, 1 )\n    [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.grev( N, x, 2 )\n    [ 4.0, 1.0, 3.0, -5.0, -2.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.grev( N, x1, 2 )\n    <Float64Array>[ -6.0, 3.0, -4.0, 5.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n\nbase.strided.grev.ndarray( N, x, stride, offset )\n    Reverses a strided array in-place using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: ArrayLikeObject\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.grev.ndarray( x.length, x, 1, 0 )\n    [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.grev.ndarray( N, x, 2, 1 )\n    [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.drev, base.strided.srev\n","base.strided.grev.ndarray":"\nbase.strided.grev.ndarray( N, x, stride, offset )\n    Reverses a strided array in-place using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: ArrayLikeObject\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.grev.ndarray( x.length, x, 1, 0 )\n    [ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.grev.ndarray( N, x, 2, 1 )\n    [ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.drev, base.strided.srev","base.strided.gscal":"\nbase.strided.gscal( N, alpha, x, stride )\n    Multiplies a vector `x` by a constant `alpha`.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `stride <= 0`, the function returns `x` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > var alpha = 5.0;\n    > base.strided.gscal( x.length, alpha, x, 1 )\n    [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.gscal( 3, 5.0, x, 2 )\n    [ -10.0, 1.0, 15.0, -5.0, 20.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.gscal( 3, 5.0, x1, 2 )\n    <Float64Array>[ -10.0, 3.0, -20.0, 5.0, -30.0 ]\n    > x0\n    <Float64Array>[ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n\nbase.strided.gscal.ndarray( N, alpha, x, stride, offset )\n    Multiplies `x` by a constant `alpha` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.gscal.ndarray( x.length, 5.0, x, 1, 0 )\n    [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > base.strided.gscal.ndarray( 3, 5.0, x, 2, 1 )\n    [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n    See Also\n    --------\n    base.strided.dscal, base.strided.gaxpy, base.strided.sscal\n","base.strided.gscal.ndarray":"\nbase.strided.gscal.ndarray( N, alpha, x, stride, offset )\n    Multiplies `x` by a constant `alpha` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.gscal.ndarray( x.length, 5.0, x, 1, 0 )\n    [ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > base.strided.gscal.ndarray( 3, 5.0, x, 2, 1 )\n    [ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n    See Also\n    --------\n    base.strided.dscal, base.strided.gaxpy, base.strided.sscal","base.strided.gsort2hp":"\nbase.strided.gsort2hp( N, order, x, strideX, y, strideY )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using heapsort.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided arrays are sorted *in-place* (i.e., the input strided\n    arrays is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > base.strided.gsort2hp( x.length, 1, x, 1, y, 1 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    [ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsort2hp( N, -1, x, 2, y, 2 )\n    [ 3.0, -2.0, 1.0, -4.0 ]\n    > y\n    [ 2.0, 1.0, 0.0, 3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gsort2hp( N, 1, x1, 2, y1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.gsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using heapsort and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > base.strided.gsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    [ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    [ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssort2hp\n","base.strided.gsort2hp.ndarray":"\nbase.strided.gsort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using heapsort and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > base.strided.gsort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    [ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsort2hp.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    [ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2hp, base.strided.gsorthp, base.strided.ssort2hp","base.strided.gsort2ins":"\nbase.strided.gsort2ins( N, order, x, strideX, y, strideY )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using insertion sort.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^2).\n\n    The algorithm is efficient for *small* strided arrays (typically N <= 20)\n    and is particularly efficient for sorting strided arrays which are already\n    substantially sorted.\n\n    The algorithm is *stable*, meaning that the algorithm does *not* change the\n    order of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided arrays are sorted *in-place* (i.e., the input strided\n    arrays is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > base.strided.gsort2ins( x.length, 1, x, 1, y, 1 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    [ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsort2ins( N, -1, x, 2, y, 2 )\n    [ 3.0, -2.0, 1.0, -4.0 ]\n    > y\n    [ 2.0, 1.0, 0.0, 3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gsort2ins( N, 1, x1, 2, y1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.gsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using insertion sort and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > base.strided.gsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    [ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsort2ins.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    [ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2ins, base.strided.gsortins, base.strided.ssort2ins\n","base.strided.gsort2ins.ndarray":"\nbase.strided.gsort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using insertion sort and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > base.strided.gsort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    [ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsort2ins.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    [ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2ins, base.strided.gsortins, base.strided.ssort2ins","base.strided.gsort2sh":"\nbase.strided.gsort2sh( N, order, x, strideX, y, strideY )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using Shellsort.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^(4/3)).\n\n    The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided arrays are sorted *in-place* (i.e., the input strided\n    arrays is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > base.strided.gsort2sh( x.length, 1, x, 1, y, 1 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    [ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsort2sh( N, -1, x, 2, y, 2 )\n    [ 3.0, -2.0, 1.0, -4.0 ]\n    > y\n    [ 2.0, 1.0, 0.0, 3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gsort2sh( N, 1, x1, 2, y1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\nbase.strided.gsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using Shellsort and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > base.strided.gsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    [ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    [ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssort2sh\n","base.strided.gsort2sh.ndarray":"\nbase.strided.gsort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using Shellsort and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Array<number>|TypedArray\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > base.strided.gsort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    [ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsort2sh.ndarray( N, 1, x, 2, 1, y, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    [ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2sh, base.strided.gsortsh, base.strided.ssort2sh","base.strided.gsorthp":"\nbase.strided.gsorthp( N, order, x, stride )\n    Sorts a strided array using heapsort.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided array is sorted *in-place* (i.e., the input strided array\n    is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > base.strided.gsorthp( x.length, 1, x, 1 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsorthp( N, -1, x, 2 )\n    [ 3.0, -2.0, 1.0, -4.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gsorthp( N, 1, x1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.gsorthp.ndarray( N, order, x, stride, offset )\n    Sorts a strided array using heapsort and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > base.strided.gsorthp.ndarray( x.length, 1, x, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsorthp.ndarray( N, 1, x, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssorthp\n","base.strided.gsorthp.ndarray":"\nbase.strided.gsorthp.ndarray( N, order, x, stride, offset )\n    Sorts a strided array using heapsort and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > base.strided.gsorthp.ndarray( x.length, 1, x, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsorthp.ndarray( N, 1, x, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsorthp, base.strided.gsort2hp, base.strided.ssorthp","base.strided.gsortins":"\nbase.strided.gsortins( N, order, x, stride )\n    Sorts a strided array using insertion sort.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^2).\n\n    The algorithm is efficient for *small* strided arrays (typically N <= 20)\n    and is particularly efficient for sorting strided arrays which are already\n    substantially sorted.\n\n    The algorithm is *stable*, meaning that the algorithm does *not* change the\n    order of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided array is sorted *in-place* (i.e., the input strided array\n    is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > base.strided.gsortins( x.length, 1, x, 1 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsortins( N, -1, x, 2 )\n    [ 3.0, -2.0, 1.0, -4.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gsortins( N, 1, x1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.gsortins.ndarray( N, order, x, stride, offset )\n    Sorts a strided array using insertion sort and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > base.strided.gsortins.ndarray( x.length, 1, x, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsortins.ndarray( N, 1, x, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsortins, base.strided.gsort2ins, base.strided.ssortins\n","base.strided.gsortins.ndarray":"\nbase.strided.gsortins.ndarray( N, order, x, stride, offset )\n    Sorts a strided array using insertion sort and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > base.strided.gsortins.ndarray( x.length, 1, x, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsortins.ndarray( N, 1, x, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsortins, base.strided.gsort2ins, base.strided.ssortins","base.strided.gsortsh":"\nbase.strided.gsortsh( N, order, x, stride )\n    Sorts a strided array using Shellsort.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^(4/3)).\n\n    The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided array is sorted *in-place* (i.e., the input strided array\n    is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > base.strided.gsortsh( x.length, 1, x, 1 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsortsh( N, -1, x, 2 )\n    [ 3.0, -2.0, 1.0, -4.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.gsortsh( N, 1, x1, 2 )\n    <Float64Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float64Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\nbase.strided.gsortsh.ndarray( N, order, x, stride, offset )\n    Sorts a strided array using Shellsort and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > base.strided.gsortsh.ndarray( x.length, 1, x, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsortsh.ndarray( N, 1, x, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssortsh\n","base.strided.gsortsh.ndarray":"\nbase.strided.gsortsh.ndarray( N, order, x, stride, offset )\n    Sorts a strided array using Shellsort and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Array<number>|TypedArray\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > base.strided.gsortsh.ndarray( x.length, 1, x, 1, 0 )\n    [ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsortsh.ndarray( N, 1, x, 2, 1 )\n    [ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsortsh, base.strided.gsort2sh, base.strided.ssortsh","base.strided.gsum":"\nbase.strided.gsum( N, x, stride )\n    Computes the sum of strided array elements.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsum( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gsum( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gsum( N, x1, stride )\n    -1.0\n\nbase.strided.gsum.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsum.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsum, base.strided.gnansum, base.strided.ssum, base.strided.mean\n","base.strided.gsum.ndarray":"\nbase.strided.gsum.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsum.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsum, base.strided.gnansum, base.strided.ssum, base.strided.mean","base.strided.gsumkbn":"\nbase.strided.gsumkbn( N, x, stride )\n    Computes the sum of strided array elements using an improved Kahan–Babuška\n    algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumkbn( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gsumkbn( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gsumkbn( N, x1, stride )\n    -1.0\n\nbase.strided.gsumkbn.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements using an improved Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsumkbn.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn\n","base.strided.gsumkbn.ndarray":"\nbase.strided.gsumkbn.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements using an improved Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsumkbn.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumkbn, base.strided.gnansumkbn, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn","base.strided.gsumkbn2":"\nbase.strided.gsumkbn2( N, x, stride )\n    Computes the sum of strided array elements using a second-order iterative\n    Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumkbn2( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gsumkbn2( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gsumkbn2( N, x1, stride )\n    -1.0\n\nbase.strided.gsumkbn2.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements using a second-order iterative\n    Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsumkbn2.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.gsum, base.strided.gsumkbn, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn2\n","base.strided.gsumkbn2.ndarray":"\nbase.strided.gsumkbn2.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements using a second-order iterative\n    Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsumkbn2.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumkbn2, base.strided.gnansumkbn2, base.strided.gsum, base.strided.gsumkbn, base.strided.gsumors, base.strided.gsumpw, base.strided.ssumkbn2","base.strided.gsumors":"\nbase.strided.gsumors( N, x, stride )\n    Computes the sum of strided array elements using ordinary recursive\n    summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumors( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gsumors( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gsumors( N, x1, stride )\n    -1.0\n\nbase.strided.gsumors.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements using ordinary recursive\n    summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsumors.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumors, base.strided.gnansumors, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumpw, base.strided.ssumors\n","base.strided.gsumors.ndarray":"\nbase.strided.gsumors.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements using ordinary recursive\n    summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsumors.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumors, base.strided.gnansumors, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumpw, base.strided.ssumors","base.strided.gsumpw":"\nbase.strided.gsumpw( N, x, stride )\n    Computes the sum of strided array elements using pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumpw( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.gsumpw( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.gsumpw( N, x1, stride )\n    -1.0\n\nbase.strided.gsumpw.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements using pairwise summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsumpw.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumpw, base.strided.gnansumpw, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.ssumpw\n","base.strided.gsumpw.ndarray":"\nbase.strided.gsumpw.ndarray( N, x, stride, offset )\n    Computes the sum of strided array elements using pairwise summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.gsumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.gsumpw.ndarray( N, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumpw, base.strided.gnansumpw, base.strided.gsum, base.strided.gsumkbn2, base.strided.gsumors, base.strided.ssumpw","base.strided.gswap":"\nbase.strided.gswap( N, x, strideX, y, strideY )\n    Interchanges vectors `x` and `y`.\n\n    The `N` and stride parameters determine how values from `x` are swapped with\n    values from `y`.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the vectors are unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: ArrayLikeObject\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n    > base.strided.gswap( x.length, x, 1, y, 1 )\n    [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n    > base.strided.gswap( 3, x, -2, y, 1 )\n    [ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n    // Using typed array views:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > var y0 = new Float64Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.gswap( 3, x1, -2, y1, 1 )\n    <Float64Array>[ 6.0, 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.gswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Interchanges vectors `x` and `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: ArrayLikeObject\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n    > base.strided.gswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n    > base.strided.gswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dswap, base.strided.gcopy, base.strided.sswap, gswap\n","base.strided.gswap.ndarray":"\nbase.strided.gswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Interchanges vectors `x` and `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: ArrayLikeObject\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: ArrayLikeObject\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > var y = [ 6.0, 7.0, 8.0, 9.0, 10.0 ];\n    > base.strided.gswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    [ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > y = [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ];\n    > base.strided.gswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    [ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dswap, base.strided.gcopy, base.strided.sswap, gswap","base.strided.mapBy":"\nbase.strided.mapBy( N, x, sx, y, sy, fcn, clbk[, thisArg] )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - indices: strided indices (offset + idx*stride).\n    - arrays: input and output arrays.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    fcn: Function\n        Unary function to apply to callback return values.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v * 2.0; };\n    > base.strided.mapBy( x.length, x, 1, y, 1, base.abs, clbk )\n    [ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > base.strided.mapBy( 2, x, 2, y, -1, base.abs, clbk )\n    [ 6.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.mapBy( 2, x1, -2, y1, 1, base.abs, clbk )\n    <Float64Array>[ 8.0, 4.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 8.0, 4.0 ]\n\n\nbase.strided.mapBy.ndarray( N, x, sx, ox, y, sy, oy, fcn, clbk[, thisArg] )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offsest parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply to callback return values.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v * 2.0; };\n    > base.strided.mapBy.ndarray( x.length, x, 1, 0, y, 1, 0, base.abs, clbk )\n    [ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > base.strided.mapBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.abs, clbk )\n    [ 0.0, 0.0, 8.0, 4.0 ]\n\n    See Also\n    --------\n    base.strided.mapBy2, base.strided.unary\n","base.strided.mapBy.ndarray":"\nbase.strided.mapBy.ndarray( N, x, sx, ox, y, sy, oy, fcn, clbk[, thisArg] )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offsest parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply to callback return values.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v * 2.0; };\n    > base.strided.mapBy.ndarray( x.length, x, 1, 0, y, 1, 0, base.abs, clbk )\n    [ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > base.strided.mapBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.abs, clbk )\n    [ 0.0, 0.0, 8.0, 4.0 ]\n\n    See Also\n    --------\n    base.strided.mapBy2, base.strided.unary","base.strided.mapBy2":"\nbase.strided.mapBy2( N, x, sx, y, sy, z, sz, fcn, clbk[, thisArg] )\n    Applies a binary function to each pair of elements retrieved from strided\n    input arrays according to a callback function and assigns results to a\n    strided output array.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided four arguments:\n\n    - values: input array elements.\n    - idx: iteration index.\n    - indices: strided array indices (offset + idx*stride).\n    - arrays: input and output arrays.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    fcn: Function\n        Binary function to apply to callback return values.\n\n    clbk: Function\n        Callback function which returns an array-like object containing two\n        values.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 1.0, 1.0, 2.0, 2.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\n    > base.strided.mapBy2( x.length, x, 1, y, 1, z, 1, base.add, clbk )\n    [ 4.0, -2.0, 10.0, -4.0 ]\n\n    // Using `N` and stride parameters:\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > base.strided.mapBy2( 2, x, 2, y, -1, z, -1, base.add, clbk )\n    [ 8.0, 4.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y0 = new Float64Array( [ 1.0, 1.0, 2.0, 2.0 ] );\n    > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > base.strided.mapBy2( 2, x1, -2, y1, 1, z1, 1, base.add, clbk )\n    <Float64Array>[ -4.0, 0.0 ]\n    > z0\n    <Float64Array>[ 0.0, 0.0, -4.0, 0.0 ]\n\n\nbase.strided.mapBy2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn, clbk[, thisArg] )\n    Applies a binary function to each pair of elements retrieved from strided\n    input arrays according to a callback function and assigns results to a\n    strided output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offsest parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    fcn: Function\n        Binary function to apply to callback return values.\n\n    clbk: Function\n        Callback function which returns an array-like object containing two\n        values.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 1.0, 1.0, 2.0, 2.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\n    > base.strided.mapBy2.ndarray( 4, x, 1, 0, y, 1, 0, z, 1, 0, base.add, clbk )\n    [ 4.0, -2.0, 10.0, -4.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 1.0, 1.0, 2.0, 2.0 ];\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > base.strided.mapBy2.ndarray( 2, x, 2, 1, y, -1, 3, z, 1, 0, base.add, clbk )\n    [ 0.0, -4.0, 0.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.mapBy, base.strided.binary\n","base.strided.mapBy2.ndarray":"\nbase.strided.mapBy2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn, clbk[, thisArg] )\n    Applies a binary function to each pair of elements retrieved from strided\n    input arrays according to a callback function and assigns results to a\n    strided output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offsest parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    fcn: Function\n        Binary function to apply to callback return values.\n\n    clbk: Function\n        Callback function which returns an array-like object containing two\n        values.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 1.0, 1.0, 2.0, 2.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { v[0] *= 2.0; v[1] *= 2.0; return v; };\n    > base.strided.mapBy2.ndarray( 4, x, 1, 0, y, 1, 0, z, 1, 0, base.add, clbk )\n    [ 4.0, -2.0, 10.0, -4.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 1.0, 1.0, 2.0, 2.0 ];\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > base.strided.mapBy2.ndarray( 2, x, 2, 1, y, -1, 3, z, 1, 0, base.add, clbk )\n    [ 0.0, -4.0, 0.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.mapBy, base.strided.binary","base.strided.max":"\nbase.strided.max( N, x, stride )\n    Computes the maximum value of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.max( x.length, x, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.max( N, x, stride )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.max( N, x1, stride )\n    2.0\n\nbase.strided.max.ndarray( N, x, stride, offset )\n    Computes the maximum value of a strided array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.max.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.max.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.min, base.strided.nanmax, base.strided.smax\n","base.strided.max.ndarray":"\nbase.strided.max.ndarray( N, x, stride, offset )\n    Computes the maximum value of a strided array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.max.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.max.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.min, base.strided.nanmax, base.strided.smax","base.strided.maxabs":"\nbase.strided.maxabs( N, x, stride )\n    Computes the maximum absolute value of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.maxabs( x.length, x, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.maxabs( N, x, stride )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.maxabs( N, x1, stride )\n    2.0\n\nbase.strided.maxabs.ndarray( N, x, stride, offset )\n    Computes the maximum absolute value of a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.maxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.maxabs.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmaxabs, base.strided.max, base.strided.minabs, base.strided.nanmaxabs, base.strided.smaxabs\n","base.strided.maxabs.ndarray":"\nbase.strided.maxabs.ndarray( N, x, stride, offset )\n    Computes the maximum absolute value of a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.maxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.maxabs.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmaxabs, base.strided.max, base.strided.minabs, base.strided.nanmaxabs, base.strided.smaxabs","base.strided.maxBy":"\nbase.strided.maxBy( N, x, stride, clbk[, thisArg] )\n    Calculates the maximum value of a strided array via a callback function.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - aidx: array index.\n    - sidx: strided index (offset + aidx*stride).\n    - array: the input array.\n\n    The callback function should return a numeric value.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.maxBy( x.length, x, 1, accessor )\n    8.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.maxBy( N, x, 2, accessor )\n    8.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.maxBy( N, x1, 2, accessor )\n    -4.0\n\nbase.strided.maxBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the maximum value of a strided array via a callback function and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.maxBy.ndarray( x.length, x, 1, 0, accessor )\n    8.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.maxBy.ndarray( N, x, 2, 1, accessor )\n    -4.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.max, base.strided.minBy, base.strided.nanmaxBy, base.strided.smax\n","base.strided.maxBy.ndarray":"\nbase.strided.maxBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the maximum value of a strided array via a callback function and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.maxBy.ndarray( x.length, x, 1, 0, accessor )\n    8.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.maxBy.ndarray( N, x, 2, 1, accessor )\n    -4.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.max, base.strided.minBy, base.strided.nanmaxBy, base.strided.smax","base.strided.maxsorted":"\nbase.strided.maxsorted( N, x, stride )\n    Computes the maximum value of a sorted strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > base.strided.maxsorted( x.length, x, 1 )\n    3.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.maxsorted( N, x, stride )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.maxsorted( N, x1, stride )\n    3.0\n\nbase.strided.maxsorted.ndarray( N, x, stride, offset )\n    Computes the maximum value of a sorted strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > base.strided.maxsorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.maxsorted.ndarray( N, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmaxsorted, base.strided.max, base.strided.minsorted, base.strided.smaxsorted\n","base.strided.maxsorted.ndarray":"\nbase.strided.maxsorted.ndarray( N, x, stride, offset )\n    Computes the maximum value of a sorted strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > base.strided.maxsorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.maxsorted.ndarray( N, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmaxsorted, base.strided.max, base.strided.minsorted, base.strided.smaxsorted","base.strided.maxViewBufferIndex":"\nbase.strided.maxViewBufferIndex( N, stride, offset )\n    Returns the maximum accessible index based on a set of provided strided\n    array parameters.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    stride: integer\n        Stride length.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    idx: integer\n        Minimum accessible index.\n\n    Examples\n    --------\n    > var idx = base.strided.maxViewBufferIndex( 3, 2, 10 )\n    14\n\n","base.strided.mean":"\nbase.strided.mean( N, x, stride )\n    Computes the arithmetic mean of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.mean( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.mean( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.mean( N, x1, stride )\n    ~-0.3333\n\nbase.strided.mean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.mean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.nanmean, base.strided.smean\n","base.strided.mean.ndarray":"\nbase.strided.mean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.mean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.nanmean, base.strided.smean","base.strided.meankbn":"\nbase.strided.meankbn( N, x, stride )\n    Computes the arithmetic mean of a strided array using an improved Kahan–\n    Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.meankbn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.meankbn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.meankbn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.meankbn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using an improved Kahan–\n    Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meankbn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meankbn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeankbn, base.strided.mean, base.strided.smeankbn\n","base.strided.meankbn.ndarray":"\nbase.strided.meankbn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using an improved Kahan–\n    Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meankbn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meankbn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeankbn, base.strided.mean, base.strided.smeankbn","base.strided.meankbn2":"\nbase.strided.meankbn2( N, x, stride )\n    Computes the arithmetic mean of a strided array using a second-order\n    iterative Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.meankbn2( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.meankbn2( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.meankbn2( N, x1, stride )\n    ~-0.3333\n\nbase.strided.meankbn2.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using a second-order\n    iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meankbn2.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meankbn2.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeankbn2, base.strided.mean, base.strided.smeankbn2\n","base.strided.meankbn2.ndarray":"\nbase.strided.meankbn2.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using a second-order\n    iterative Kahan–Babuška algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meankbn2.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meankbn2.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeankbn2, base.strided.mean, base.strided.smeankbn2","base.strided.meanors":"\nbase.strided.meanors( N, x, stride )\n    Computes the arithmetic mean of a strided array using ordinary recursive\n    summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.meanors( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.meanors( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.meanors( N, x1, stride )\n    ~-0.3333\n\nbase.strided.meanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using ordinary recursive\n    summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanors, base.strided.mean, base.strided.nanmeanors, base.strided.smeanors\n","base.strided.meanors.ndarray":"\nbase.strided.meanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using ordinary recursive\n    summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanors, base.strided.mean, base.strided.nanmeanors, base.strided.smeanors","base.strided.meanpn":"\nbase.strided.meanpn( N, x, stride )\n    Computes the arithmetic mean of a strided array using a two-pass error\n    correction algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.meanpn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.meanpn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.meanpn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.meanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using a two-pass error\n    correction algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.mean, base.strided.nanmeanpn, base.strided.smeanpn\n","base.strided.meanpn.ndarray":"\nbase.strided.meanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using a two-pass error\n    correction algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.mean, base.strided.nanmeanpn, base.strided.smeanpn","base.strided.meanpw":"\nbase.strided.meanpw( N, x, stride )\n    Computes the arithmetic mean of a strided array using pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.meanpw( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.meanpw( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.meanpw( N, x1, stride )\n    ~-0.3333\n\nbase.strided.meanpw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using pairwise summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meanpw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meanpw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpw, base.strided.mean, base.strided.smeanpw\n","base.strided.meanpw.ndarray":"\nbase.strided.meanpw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using pairwise summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meanpw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meanpw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpw, base.strided.mean, base.strided.smeanpw","base.strided.meanwd":"\nbase.strided.meanwd( N, x, stride )\n    Computes the arithmetic mean of a strided array using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.meanwd( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.meanwd( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.meanwd( N, x1, stride )\n    ~-0.3333\n\nbase.strided.meanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using Welford's algorithm\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanwd, base.strided.mean, base.strided.nanmeanwd, base.strided.smeanwd\n","base.strided.meanwd.ndarray":"\nbase.strided.meanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array using Welford's algorithm\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, 2.0 ];\n    > base.strided.meanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.meanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanwd, base.strided.mean, base.strided.nanmeanwd, base.strided.smeanwd","base.strided.mediansorted":"\nbase.strided.mediansorted( N, x, stride )\n    Computes the median value of a sorted strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > base.strided.mediansorted( x.length, x, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mediansorted( N, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.mediansorted( N, x1, 2 )\n    2.0\n\nbase.strided.mediansorted.ndarray( N, x, stride, offset )\n    Computes the median value of a sorted strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > base.strided.mediansorted.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mediansorted.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmediansorted, base.strided.mean, base.strided.smediansorted\n","base.strided.mediansorted.ndarray":"\nbase.strided.mediansorted.ndarray( N, x, stride, offset )\n    Computes the median value of a sorted strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > base.strided.mediansorted.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mediansorted.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmediansorted, base.strided.mean, base.strided.smediansorted","base.strided.metaDataProps":"\nbase.strided.metaDataProps( meta, dtypes, obj, bool )\n    Defines non-enumerable read-only properties which expose strided array\n    function meta data.\n\n    Parameters\n    ----------\n    meta: Object\n        Function meta data.\n\n    meta.nargs: integer\n        Total number of arguments (excluding offsets).\n\n    meta.nin: integer\n        Total number of input arrays.\n\n    meta.nout: integer\n        Total number of output arrays.\n\n    dtypes: ArrayLikeObject\n        List of strided array data types.\n\n    obj: Object|Function\n        Object on which to define properties.\n\n    bool: boolean\n        Boolean indicating whether the provided object should describe an\n        \"ndarray\" function interface.\n\n    Returns\n    -------\n    out: Object|Function\n        Object on which properties were defined.\n\n    Examples\n    --------\n    > var meta = { 'nargs': 7, 'nin': 1, 'nout': 1 };\n    > var dt = [ 'float64', 'float64' ];\n    > var obj = {};\n    > base.strided.metaDataProps( meta, dt, obj, false );\n    > obj.nargs\n    7\n    > obj.nin\n    1\n    > obj.nout\n    1\n    > obj.types\n    [...]\n\n","base.strided.min":"\nbase.strided.min( N, x, stride )\n    Computes the minimum value of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.min( x.length, x, 1 )\n    -2.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.min( N, x, stride )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.min( N, x1, stride )\n    -2.0\n\nbase.strided.min.ndarray( N, x, stride, offset )\n    Computes the minimum value of a strided array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.min.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.min.ndarray( N, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.max, base.strided.nanmin, base.strided.smin\n","base.strided.min.ndarray":"\nbase.strided.min.ndarray( N, x, stride, offset )\n    Computes the minimum value of a strided array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.min.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.min.ndarray( N, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.max, base.strided.nanmin, base.strided.smin","base.strided.minabs":"\nbase.strided.minabs( N, x, stride )\n    Computes the minimum absolute value of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.minabs( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.minabs( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.minabs( N, x1, stride )\n    1.0\n\nbase.strided.minabs.ndarray( N, x, stride, offset )\n    Computes the minimum absolute value of a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.minabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.minabs.ndarray( N, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dminabs, base.strided.maxabs, base.strided.min, base.strided.nanminabs, base.strided.sminabs\n","base.strided.minabs.ndarray":"\nbase.strided.minabs.ndarray( N, x, stride, offset )\n    Computes the minimum absolute value of a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.minabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.minabs.ndarray( N, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dminabs, base.strided.maxabs, base.strided.min, base.strided.nanminabs, base.strided.sminabs","base.strided.minBy":"\nbase.strided.minBy( N, x, stride, clbk[, thisArg] )\n    Calculates the minimum value of a strided array via a callback function.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - aidx: array index.\n    - sidx: strided index (offset + aidx*stride).\n    - array: the input array.\n\n    The callback function should return a numeric value.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.minBy( x.length, x, 1, accessor )\n    -10.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.minBy( N, x, 2, accessor )\n    -4.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.minBy( N, x1, 2, accessor )\n    -12.0\n\nbase.strided.minBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the minimum value of a strided array via a callback function and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.minBy.ndarray( x.length, x, 1, 0, accessor )\n    -10.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.minBy.ndarray( N, x, 2, 1, accessor )\n    -12.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.maxBy, base.strided.min, base.strided.nanminBy, base.strided.smin\n","base.strided.minBy.ndarray":"\nbase.strided.minBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the minimum value of a strided array via a callback function and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.minBy.ndarray( x.length, x, 1, 0, accessor )\n    -10.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.minBy.ndarray( N, x, 2, 1, accessor )\n    -12.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.maxBy, base.strided.min, base.strided.nanminBy, base.strided.smin","base.strided.minsorted":"\nbase.strided.minsorted( N, x, stride )\n    Computes the minimum value of a sorted strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > base.strided.minsorted( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.minsorted( N, x, stride )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.minsorted( N, x1, stride )\n    -2.0\n\nbase.strided.minsorted.ndarray( N, x, stride, offset )\n    Computes the minimum value of a sorted strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > base.strided.minsorted.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.minsorted.ndarray( N, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dminsorted, base.strided.maxsorted, base.strided.min, base.strided.sminsorted\n","base.strided.minsorted.ndarray":"\nbase.strided.minsorted.ndarray( N, x, stride, offset )\n    Computes the minimum value of a sorted strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Sorted input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > base.strided.minsorted.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.minsorted.ndarray( N, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dminsorted, base.strided.maxsorted, base.strided.min, base.strided.sminsorted","base.strided.minViewBufferIndex":"\nbase.strided.minViewBufferIndex( N, stride, offset )\n    Returns the minimum accessible index based on a set of provided strided\n    array parameters.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    stride: integer\n        Stride length.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    idx: integer\n        Minimum accessible index.\n\n    Examples\n    --------\n    > var idx = base.strided.minViewBufferIndex( 3, -2, 10 )\n    6\n\n    See Also\n    --------\n    base.strided.offsetView\n","base.strided.mskmax":"\nbase.strided.mskmax( N, x, strideX, mask, strideMask )\n    Computes the maximum value of a strided array according to a mask.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 4.0, 2.0 ];\n    > var mask = [ 0, 0, 1, 0 ];\n    > base.strided.mskmax( x.length, x, 1, mask, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mskmax( N, x, 2, mask, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.mskmax( N, x1, 2, mask1, 2 )\n    2.0\n\nbase.strided.mskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a strided array according to a mask and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n    > var mask = [ 0, 0, 0, 1 ];\n    > base.strided.mskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmskmax, base.strided.max, base.strided.mskmin, base.strided.nanmax, base.strided.smskmax\n","base.strided.mskmax.ndarray":"\nbase.strided.mskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a strided array according to a mask and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n    > var mask = [ 0, 0, 0, 1 ];\n    > base.strided.mskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmskmax, base.strided.max, base.strided.mskmin, base.strided.nanmax, base.strided.smskmax","base.strided.mskmin":"\nbase.strided.mskmin( N, x, strideX, mask, strideMask )\n    Computes the minimum value of a strided array according to a mask.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, -4.0, 2.0 ];\n    > var mask = [ 0, 0, 1, 0 ];\n    > base.strided.mskmin( x.length, x, 1, mask, 1 )\n    -2.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mskmin( N, x, 2, mask, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.mskmin( N, x1, 2, mask1, 2 )\n    -2.0\n\nbase.strided.mskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a strided array according to a mask and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, -4.0 ];\n    > var mask = [ 0, 0, 0, 1 ];\n    > base.strided.mskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmskmin, base.strided.min, base.strided.mskmax, base.strided.nanmin, base.strided.smskmin\n","base.strided.mskmin.ndarray":"\nbase.strided.mskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a strided array according to a mask and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, -4.0 ];\n    > var mask = [ 0, 0, 0, 1 ];\n    > base.strided.mskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmskmin, base.strided.min, base.strided.mskmax, base.strided.nanmin, base.strided.smskmin","base.strided.mskrange":"\nbase.strided.mskrange( N, x, strideX, mask, strideMask )\n    Computes the range of a strided array according to a mask.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 4.0, 2.0 ];\n    > var mask = [ 0, 0, 1, 0 ];\n    > base.strided.mskrange( x.length, x, 1, mask, 1 )\n    4.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mskrange( N, x, 2, mask, 2 )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.mskrange( N, x1, 2, mask1, 2 )\n    4.0\n\nbase.strided.mskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a strided array according to a mask and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n    > var mask = [ 0, 0, 0, 1 ];\n    > base.strided.mskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dmskrange, base.strided.range, base.strided.mskmax, base.strided.mskmin, base.strided.nanrange, base.strided.smskrange\n","base.strided.mskrange.ndarray":"\nbase.strided.mskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a strided array according to a mask and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, 4.0 ];\n    > var mask = [ 0, 0, 0, 1 ];\n    > base.strided.mskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.mskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dmskrange, base.strided.range, base.strided.mskmax, base.strided.mskmin, base.strided.nanrange, base.strided.smskrange","base.strided.mskunary":"\nbase.strided.mskunary( arrays, shape, strides, fcn )\n    Applies a unary callback to elements in a strided input array according to\n    elements in a strided mask array and assigns results to elements in a\n    strided output array.\n\n    The `shape` and `strides` parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided input array, a strided mask\n        array, and one strided output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided arrays.\n\n    fcn: Function\n        Unary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1 ];\n    > base.strided.mskunary( [ x, m, y ], shape, strides, base.abs );\n    > y\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n\nbase.strided.mskunary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a unary callback to elements in a strided input array according to\n    elements in a strided mask array, and assigns results to elements in a\n    strided output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided input array, a strided mask\n        array, and one strided output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided arrays.\n\n    fcn: Function\n        Unary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1 ];\n    > var offsets = [ 0, 0, 0 ];\n    > base.strided.mskunary.ndarray( [ x, m, y ], shape, strides, offsets, base.abs );\n    > y\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    See Also\n    --------\n    base.strided.dmskmap, base.strided.smskmap, base.strided.unary\n","base.strided.mskunary.ndarray":"\nbase.strided.mskunary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a unary callback to elements in a strided input array according to\n    elements in a strided mask array, and assigns results to elements in a\n    strided output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided input array, a strided mask\n        array, and one strided output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided arrays.\n\n    fcn: Function\n        Unary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1 ];\n    > var offsets = [ 0, 0, 0 ];\n    > base.strided.mskunary.ndarray( [ x, m, y ], shape, strides, offsets, base.abs );\n    > y\n    <Float64Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    See Also\n    --------\n    base.strided.dmskmap, base.strided.smskmap, base.strided.unary","base.strided.mskunaryDtypeSignatures":"\nbase.strided.mskunaryDtypeSignatures( dtypes1, dtypes2[, options] )\n    Generates a list of masked unary interface signatures from strided array\n    data types.\n\n    The function returns a strided array having a stride length of three (i.e.,\n    every three elements define a masked unary interface signature).\n\n    For each signature (i.e., set of three consecutive non-overlapping strided\n    array elements), the first element is the input data type, the second\n    element is the mask data type, and the last element is the return data type.\n\n    All signatures follow type promotion rules.\n\n    The mask array data type is always `uint8`.\n\n    Parameters\n    ----------\n    dtypes1: ArrayLike<any>\n        List of supported data types for the input argument.\n\n    dtypes2: ArrayLike<any>\n        List of supported data types for the output argument.\n\n    options: Object (optional)\n        Options.\n\n    options.enums: boolean (optional)\n        Boolean flag indicating whether to return signatures as a list of data\n        type enumeration constants. Default: false.\n\n    Returns\n    -------\n    out: Array\n        Strided array containing masked unary interface signatures.\n\n    Examples\n    --------\n    > var dt = strided.dataTypes();\n    > var out = base.strided.mskunaryDtypeSignatures( dt, dt )\n    [...]\n\n    See Also\n    --------\n    base.strided.mskunarySignatureCallbacks\n","base.strided.mskunarySignatureCallbacks":"\nbase.strided.mskunarySignatureCallbacks( table, signatures )\n    Assigns callbacks to masked unary interfaces according to type promotion\n    rules.\n\n    Parameters\n    ----------\n    table: Object\n        Object mapping callbacks to data types.\n\n    table.default: Function\n        Default callback.\n\n    table.complex64: Function\n        Callback to be invoked when input arrays promote to single-precision\n        complex floating-point numbers.\n\n    table.complex128: Function\n        Callback to be invoked when input arrays promote to double precision\n        complex floating-point numbers.\n\n    signatures: ArrayLike<any>\n        Strided array containing masked unary interface signatures.\n\n    Returns\n    -------\n    out: Array<Function>\n        List of callbacks, one per signature.\n\n    Examples\n    --------\n    > var dt = strided.dataTypes();\n    > var sigs = base.strided.mskunaryDtypeSignatures( dt, dt );\n    > var t = {\n    ...     'default': base.identity,\n    ...     'complex64': base.cidentityf,\n    ...     'complex128': base.cidentity\n    ... };\n    > var out = base.strided.mskunarySignatureCallbacks( t, sigs )\n    [...]\n\n    See Also\n    --------\n    base.strided.mskunaryDtypeSignatures\n","base.strided.nanmax":"\nbase.strided.nanmax( N, x, stride )\n    Computes the maximum value of a strided array, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmax( x.length, x, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanmax( N, x, stride )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanmax( N, x1, stride )\n    2.0\n\nbase.strided.nanmax.ndarray( N, x, stride, offset )\n    Computes the maximum value of a strided array, ignoring `NaN` values and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmax.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmax.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmax, base.strided.max, base.strided.nanmin, base.strided.snanmax\n","base.strided.nanmax.ndarray":"\nbase.strided.nanmax.ndarray( N, x, stride, offset )\n    Computes the maximum value of a strided array, ignoring `NaN` values and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmax.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmax.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmax, base.strided.max, base.strided.nanmin, base.strided.snanmax","base.strided.nanmaxabs":"\nbase.strided.nanmaxabs( N, x, stride )\n    Computes the maximum absolute value of a strided array, ignoring `NaN`\n    values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmaxabs( x.length, x, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanmaxabs( N, x, stride )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanmaxabs( N, x1, stride )\n    2.0\n\nbase.strided.nanmaxabs.ndarray( N, x, stride, offset )\n    Computes the maximum absolute value of a strided array, ignoring `NaN`\n    values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmaxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmaxabs.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmaxabs, base.strided.maxabs, base.strided.nanmax, base.strided.nanminabs, base.strided.snanmaxabs\n","base.strided.nanmaxabs.ndarray":"\nbase.strided.nanmaxabs.ndarray( N, x, stride, offset )\n    Computes the maximum absolute value of a strided array, ignoring `NaN`\n    values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmaxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmaxabs.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmaxabs, base.strided.maxabs, base.strided.nanmax, base.strided.nanminabs, base.strided.snanmaxabs","base.strided.nanmaxBy":"\nbase.strided.nanmaxBy( N, x, stride, clbk[, thisArg] )\n    Calculates the maximum value of a strided array via a callback function,\n    ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - aidx: array index.\n    - sidx: strided index (offset + aidx*stride).\n    - array: the input array.\n\n    The callback function should return a numeric value.\n\n    If the callback function returns `NaN`, the value is ignored.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n    > base.strided.nanmaxBy( x.length, x, 1, accessor )\n    8.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmaxBy( N, x, 2, accessor )\n    8.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanmaxBy( N, x1, 2, accessor )\n    -4.0\n\nbase.strided.nanmaxBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the maximum value of a strided array via a callback function,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n    > base.strided.nanmaxBy.ndarray( x.length, x, 1, 0, accessor )\n    8.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmaxBy.ndarray( N, x, 2, 1, accessor )\n    -4.0\n\n    See Also\n    --------\n    base.strided.dnanmax, base.strided.maxBy, base.strided.nanmax, base.strided.nanminBy, base.strided.snanmax\n","base.strided.nanmaxBy.ndarray":"\nbase.strided.nanmaxBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the maximum value of a strided array via a callback function,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n    > base.strided.nanmaxBy.ndarray( x.length, x, 1, 0, accessor )\n    8.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmaxBy.ndarray( N, x, 2, 1, accessor )\n    -4.0\n\n    See Also\n    --------\n    base.strided.dnanmax, base.strided.maxBy, base.strided.nanmax, base.strided.nanminBy, base.strided.snanmax","base.strided.nanmean":"\nbase.strided.nanmean( N, x, stride )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmean( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanmean( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanmean( N, x1, stride )\n    ~-0.3333\n\nbase.strided.nanmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.mean, base.strided.snanmean\n","base.strided.nanmean.ndarray":"\nbase.strided.nanmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.mean, base.strided.snanmean","base.strided.nanmeanors":"\nbase.strided.nanmeanors( N, x, stride )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using ordinary recursive summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmeanors( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanmeanors( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanmeanors( N, x1, stride )\n    ~-0.3333\n\nbase.strided.nanmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanors, base.strided.meanors, base.strided.nanmean, base.strided.snanmeanors\n","base.strided.nanmeanors.ndarray":"\nbase.strided.nanmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanors, base.strided.meanors, base.strided.nanmean, base.strided.snanmeanors","base.strided.nanmeanpn":"\nbase.strided.nanmeanpn( N, x, stride )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using a two-pass error correction algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmeanpn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanmeanpn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanmeanpn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.nanmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using a two-pass error correction algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanpn, base.strided.meanpn, base.strided.nanmean, base.strided.snanmeanpn\n","base.strided.nanmeanpn.ndarray":"\nbase.strided.nanmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using a two-pass error correction algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanpn, base.strided.meanpn, base.strided.nanmean, base.strided.snanmeanpn","base.strided.nanmeanwd":"\nbase.strided.nanmeanwd( N, x, stride )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmeanwd( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanmeanwd( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanmeanwd( N, x1, stride )\n    ~-0.3333\n\nbase.strided.nanmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanwd, base.strided.meanwd, base.strided.nanmean, base.strided.snanmeanwd\n","base.strided.nanmeanwd.ndarray":"\nbase.strided.nanmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x =[ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanwd, base.strided.meanwd, base.strided.nanmean, base.strided.snanmeanwd","base.strided.nanmin":"\nbase.strided.nanmin( N, x, stride )\n    Computes the minimum value of a strided array, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmin( x.length, x, 1 )\n    -2.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanmin( N, x, stride )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanmin( N, x1, stride )\n    -2.0\n\nbase.strided.nanmin.ndarray( N, x, stride, offset )\n    Computes the minimum value of a strided array, ignoring `NaN` values and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmin.ndarray( N, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dnanmin, base.strided.min, base.strided.nanmax, base.strided.snanmin\n","base.strided.nanmin.ndarray":"\nbase.strided.nanmin.ndarray( N, x, stride, offset )\n    Computes the minimum value of a strided array, ignoring `NaN` values and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanmin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmin.ndarray( N, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dnanmin, base.strided.min, base.strided.nanmax, base.strided.snanmin","base.strided.nanminabs":"\nbase.strided.nanminabs( N, x, stride )\n    Computes the minimum absolute value of a strided array, ignoring `NaN`\n    values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanminabs( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanminabs( N, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanminabs( N, x1, stride )\n    1.0\n\nbase.strided.nanminabs.ndarray( N, x, stride, offset )\n    Computes the minimum absolute value of a strided array, ignoring `NaN`\n    values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanminabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanminabs.ndarray( N, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dnanminabs, base.strided.minabs, base.strided.nanmaxabs, base.strided.nanmin, base.strided.snanminabs\n","base.strided.nanminabs.ndarray":"\nbase.strided.nanminabs.ndarray( N, x, stride, offset )\n    Computes the minimum absolute value of a strided array, ignoring `NaN`\n    values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanminabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanminabs.ndarray( N, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dnanminabs, base.strided.minabs, base.strided.nanmaxabs, base.strided.nanmin, base.strided.snanminabs","base.strided.nanminBy":"\nbase.strided.nanminBy( N, x, stride, clbk[, thisArg] )\n    Calculates the minimum value of a strided array via a callback function,\n    ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - aidx: array index.\n    - sidx: strided index (offset + aidx*stride).\n    - array: the input array.\n\n    The callback function should return a numeric value.\n\n    If the callback function returns `NaN`, the value is ignored.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n    > base.strided.nanminBy( x.length, x, 1, accessor )\n    -10.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, NaN, -3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanminBy( N, x, 2, accessor )\n    -4.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanminBy( N, x1, 2, accessor )\n    -12.0\n\nbase.strided.nanminBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the minimum value of a strided array via a callback function,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n    > base.strided.nanminBy.ndarray( x.length, x, 1, 0, accessor )\n    -10.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanminBy.ndarray( N, x, 2, 1, accessor )\n    -12.0\n\n    See Also\n    --------\n    base.strided.dnanmin, base.strided.minBy, base.strided.nanmaxBy, base.strided.nanmin, base.strided.snanmin\n","base.strided.nanminBy.ndarray":"\nbase.strided.nanminBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the minimum value of a strided array via a callback function,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n    > base.strided.nanminBy.ndarray( x.length, x, 1, 0, accessor )\n    -10.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanminBy.ndarray( N, x, 2, 1, accessor )\n    -12.0\n\n    See Also\n    --------\n    base.strided.dnanmin, base.strided.minBy, base.strided.nanmaxBy, base.strided.nanmin, base.strided.snanmin","base.strided.nanmskmax":"\nbase.strided.nanmskmax( N, x, strideX, mask, strideMask )\n    Computes the maximum value of a strided array according to a mask and\n    ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\n    > var mask = [ 0, 0, 1, 0, 0 ];\n    > base.strided.nanmskmax( x.length, x, 1, mask, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmskmax( N, x, 2, mask, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanmskmax( N, x1, 2, mask1, 2 )\n    2.0\n\nbase.strided.nanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a strided array according to a mask,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n    > var mask = [ 0, 0, 0, 1, 0 ];\n    > base.strided.nanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmskmax, base.strided.mskmax, base.strided.nanmax, base.strided.nanmskmin, base.strided.snanmskmax\n","base.strided.nanmskmax.ndarray":"\nbase.strided.nanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a strided array according to a mask,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n    > var mask = [ 0, 0, 0, 1, 0 ];\n    > base.strided.nanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmskmax, base.strided.mskmax, base.strided.nanmax, base.strided.nanmskmin, base.strided.snanmskmax","base.strided.nanmskmin":"\nbase.strided.nanmskmin( N, x, strideX, mask, strideMask )\n    Computes the minimum value of a strided array according to a mask and\n    ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, -4.0, 2.0, NaN ];\n    > var mask = [ 0, 0, 1, 0, 0 ];\n    > base.strided.nanmskmin( x.length, x, 1, mask, 1 )\n    -2.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmskmin( N, x, 2, mask, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanmskmin( N, x1, 2, mask1, 2 )\n    -2.0\n\nbase.strided.nanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a strided array according to a mask, ignoring\n    `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, -4.0, NaN ];\n    > var mask = [ 0, 0, 0, 1, 0 ];\n    > base.strided.nanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dnanmskmin, base.strided.mskmin, base.strided.nanmin, base.strided.nanmskmax, base.strided.snanmskmin\n","base.strided.nanmskmin.ndarray":"\nbase.strided.nanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a strided array according to a mask, ignoring\n    `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, -4.0, NaN ];\n    > var mask = [ 0, 0, 0, 1, 0 ];\n    > base.strided.nanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dnanmskmin, base.strided.mskmin, base.strided.nanmin, base.strided.nanmskmax, base.strided.snanmskmin","base.strided.nanmskrange":"\nbase.strided.nanmskrange( N, x, strideX, mask, strideMask )\n    Computes the range of a strided array according to a mask and ignoring `NaN`\n    values.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 4.0, 2.0, NaN ];\n    > var mask = [ 0, 0, 1, 0, 0 ];\n    > base.strided.nanmskrange( x.length, x, 1, mask, 1 )\n    4.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmskrange( N, x, 2, mask, 2 )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanmskrange( N, x1, 2, mask1, 2 )\n    4.0\n\nbase.strided.nanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a strided array according to a mask, ignoring `NaN`\n    values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n    > var mask = [ 0, 0, 0, 1, 0 ];\n    > base.strided.nanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dnanmskrange, base.strided.mskrange, base.strided.nanrange, base.strided.nanmskmax, base.strided.nanmskmin, base.strided.snanmskrange\n","base.strided.nanmskrange.ndarray":"\nbase.strided.nanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a strided array according to a mask, ignoring `NaN`\n    values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Array<number>|TypedArray\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0, 4.0, NaN ];\n    > var mask = [ 0, 0, 0, 1, 0 ];\n    > base.strided.nanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ];\n    > mask = [ 0, 0, 0, 0, 0, 0, 1 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dnanmskrange, base.strided.mskrange, base.strided.nanrange, base.strided.nanmskmax, base.strided.nanmskmin, base.strided.snanmskrange","base.strided.nanrange":"\nbase.strided.nanrange( N, x, stride )\n    Computes the range of a strided array, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanrange( x.length, x, 1 )\n    4.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanrange( N, x, stride )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanrange( N, x1, stride )\n    4.0\n\nbase.strided.nanrange.ndarray( N, x, stride, offset )\n    Computes the range of a strided array, ignoring `NaN` values and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanrange.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanrange.ndarray( N, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dnanrange, base.strided.nanmax, base.strided.nanmin, base.strided.range, base.strided.snanrange\n","base.strided.nanrange.ndarray":"\nbase.strided.nanrange.ndarray( N, x, stride, offset )\n    Computes the range of a strided array, ignoring `NaN` values and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanrange.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanrange.ndarray( N, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dnanrange, base.strided.nanmax, base.strided.nanmin, base.strided.range, base.strided.snanrange","base.strided.nanrangeBy":"\nbase.strided.nanrangeBy( N, x, stride, clbk[, thisArg] )\n    Calculates the range of a strided array via a callback function, ignoring\n    `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - aidx: array index.\n    - sidx: strided index (offset + aidx*stride).\n    - array: the input array.\n\n    The callback function should return a numeric value.\n\n    If the callback function returns `NaN`, the value is ignored.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n    > base.strided.nanrangeBy( x.length, x, 1, accessor )\n    18.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0, 1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanrangeBy( N, x, 2, accessor )\n    14.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanrangeBy( N, x1, 2, accessor )\n    8.0\n\nbase.strided.nanrangeBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the range of a strided array via a callback function, ignoring\n    `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n    > base.strided.nanrangeBy.ndarray( x.length, x, 1, 0, accessor )\n    18.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanrangeBy.ndarray( N, x, 2, 1, accessor )\n    8.0\n\n    See Also\n    --------\n    base.strided.dnanrange, base.strided.nanmaxBy, base.strided.nanminBy, base.strided.nanrange, base.strided.rangeBy, base.strided.snanrange\n","base.strided.nanrangeBy.ndarray":"\nbase.strided.nanrangeBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the range of a strided array via a callback function, ignoring\n    `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, NaN, -1.0, -3.0 ];\n    > base.strided.nanrangeBy.ndarray( x.length, x, 1, 0, accessor )\n    18.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanrangeBy.ndarray( N, x, 2, 1, accessor )\n    8.0\n\n    See Also\n    --------\n    base.strided.dnanrange, base.strided.nanmaxBy, base.strided.nanminBy, base.strided.nanrange, base.strided.rangeBy, base.strided.snanrange","base.strided.nanstdev":"\nbase.strided.nanstdev( N, correction, x, stride )\n    Computes the standard deviation of a strided array ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdev( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdev( N, 1, x, 2 )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanstdev( N, 1, x1, 2 )\n    ~2.0817\n\nbase.strided.nanstdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.nanvariance, base.strided.snanstdev, base.strided.stdev\n","base.strided.nanstdev.ndarray":"\nbase.strided.nanstdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.nanvariance, base.strided.snanstdev, base.strided.stdev","base.strided.nanstdevch":"\nbase.strided.nanstdevch( N, correction, x, stride )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevch( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevch( N, 1, x, 2 )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanstdevch( N, 1, x1, 2 )\n    ~2.0817\n\nbase.strided.nanstdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass trial mean algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevch, base.strided.nanvariancech, base.strided.nanstdev, base.strided.snanstdevch, base.strided.stdevch\n","base.strided.nanstdevch.ndarray":"\nbase.strided.nanstdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass trial mean algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevch, base.strided.nanvariancech, base.strided.nanstdev, base.strided.snanstdevch, base.strided.stdevch","base.strided.nanstdevpn":"\nbase.strided.nanstdevpn( N, correction, x, stride )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevpn( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevpn( N, 1, x, 2 )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanstdevpn( N, 1, x1, 2 )\n    ~2.0817\n\nbase.strided.nanstdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevpn, base.strided.nanvariancepn, base.strided.nanstdev, base.strided.snanstdevpn, base.strided.stdevpn\n","base.strided.nanstdevpn.ndarray":"\nbase.strided.nanstdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevpn, base.strided.nanvariancepn, base.strided.nanstdev, base.strided.snanstdevpn, base.strided.stdevpn","base.strided.nanstdevtk":"\nbase.strided.nanstdevtk( N, correction, x, stride )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevtk( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevtk( N, 1, x, 2 )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanstdevtk( N, 1, x1, 2 )\n    ~2.0817\n\nbase.strided.nanstdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass textbook algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevtk, base.strided.nanvariancetk, base.strided.nanstdev, base.strided.snanstdevtk, base.strided.stdevtk\n","base.strided.nanstdevtk.ndarray":"\nbase.strided.nanstdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass textbook algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevtk, base.strided.nanvariancetk, base.strided.nanstdev, base.strided.snanstdevtk, base.strided.stdevtk","base.strided.nanstdevwd":"\nbase.strided.nanstdevwd( N, correction, x, stride )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevwd( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevwd( N, 1, x, 2 )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanstdevwd( N, 1, x1, 2 )\n    ~2.0817\n\nbase.strided.nanstdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevwd, base.strided.nanvariancewd, base.strided.nanstdev, base.strided.snanstdevwd, base.strided.stdevwd\n","base.strided.nanstdevwd.ndarray":"\nbase.strided.nanstdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevwd, base.strided.nanvariancewd, base.strided.nanstdev, base.strided.snanstdevwd, base.strided.stdevwd","base.strided.nanstdevyc":"\nbase.strided.nanstdevyc( N, correction, x, stride )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass algorithm proposed by Youngs and Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevyc( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevyc( N, 1, x, 2 )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.nanstdevyc( N, 1, x1, 2 )\n    ~2.0817\n\nbase.strided.nanstdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass algorithm proposed by Youngs and Cramer and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevyc, base.strided.nanvarianceyc, base.strided.nanstdev, base.strided.snanstdevyc, base.strided.stdevyc\n","base.strided.nanstdevyc.ndarray":"\nbase.strided.nanstdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass algorithm proposed by Youngs and Cramer and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanstdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevyc, base.strided.nanvarianceyc, base.strided.nanstdev, base.strided.snanstdevyc, base.strided.stdevyc","base.strided.nanvariance":"\nbase.strided.nanvariance( N, correction, x, stride )\n    Computes the variance of a strided array ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariance( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanvariance( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanvariance( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.nanvariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariance, base.strided.nanstdev, base.strided.snanvariance, base.strided.variance\n","base.strided.nanvariance.ndarray":"\nbase.strided.nanvariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariance, base.strided.nanstdev, base.strided.snanvariance, base.strided.variance","base.strided.nanvariancech":"\nbase.strided.nanvariancech( N, correction, x, stride )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancech( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanvariancech( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanvariancech( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.nanvariancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass trial mean algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvariancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancech, base.strided.nanstdevch, base.strided.nanvariance, base.strided.snanvariancech, base.strided.variancech\n","base.strided.nanvariancech.ndarray":"\nbase.strided.nanvariancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass trial mean algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvariancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancech, base.strided.nanstdevch, base.strided.nanvariance, base.strided.snanvariancech, base.strided.variancech","base.strided.nanvariancepn":"\nbase.strided.nanvariancepn( N, correction, x, stride )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancepn( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanvariancepn( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanvariancepn( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.nanvariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancepn, base.strided.nanstdevpn, base.strided.nanvariance, base.strided.snanvariancepn, base.strided.variancepn\n","base.strided.nanvariancepn.ndarray":"\nbase.strided.nanvariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancepn, base.strided.nanstdevpn, base.strided.nanvariance, base.strided.snanvariancepn, base.strided.variancepn","base.strided.nanvariancetk":"\nbase.strided.nanvariancetk( N, correction, x, stride )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancetk( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanvariancetk( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanvariancetk( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.nanvariancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass textbook algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvariancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancetk, base.strided.nanstdevtk, base.strided.nanvariance, base.strided.snanvariancetk, base.strided.variancetk\n","base.strided.nanvariancetk.ndarray":"\nbase.strided.nanvariancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass textbook algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvariancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancetk, base.strided.nanstdevtk, base.strided.nanvariance, base.strided.snanvariancetk, base.strided.variancetk","base.strided.nanvariancewd":"\nbase.strided.nanvariancewd( N, correction, x, stride )\n    Computes the variance of a strided array ignoring `NaN` values and using\n    Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancewd( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanvariancewd( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanvariancewd( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.nanvariancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using\n    Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvariancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancewd, base.strided.nanstdevwd, base.strided.nanvariance, base.strided.snanvariancewd, base.strided.variancewd\n","base.strided.nanvariancewd.ndarray":"\nbase.strided.nanvariancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using\n    Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvariancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancewd, base.strided.nanstdevwd, base.strided.nanvariance, base.strided.snanvariancewd, base.strided.variancewd","base.strided.nanvarianceyc":"\nbase.strided.nanvarianceyc( N, correction, x, stride )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass algorithm proposed by Youngs and Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvarianceyc( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.nanvarianceyc( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.nanvarianceyc( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.nanvarianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass algorithm proposed by Youngs and Cramer and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvarianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvarianceyc, base.strided.nanstdevyc, base.strided.nanvariance, base.strided.snanvarianceyc, base.strided.varianceyc\n","base.strided.nanvarianceyc.ndarray":"\nbase.strided.nanvarianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass algorithm proposed by Youngs and Cramer and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, NaN, 2.0 ];\n    > base.strided.nanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.nanvarianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvarianceyc, base.strided.nanstdevyc, base.strided.nanvariance, base.strided.snanvarianceyc, base.strided.varianceyc","base.strided.nullary":"\nbase.strided.nullary( arrays, shape, strides, fcn )\n    Applies a nullary callback and assigns results to elements in a strided\n    output array.\n\n    The `shape` and `strides` parameters determine which elements in the strided\n    output array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride length for the strided output\n        array.\n\n    fcn: Function\n        Nullary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1 ];\n    > var fcn = constantFunction( 3.0 );\n    > base.strided.nullary( [ x ], shape, strides, fcn );\n    > x\n    <Float64Array>[ 3.0, 3.0, 3.0, 3.0 ]\n\n\nbase.strided.nullary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a nullary callback and assigns results to elements in a strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride length for the strided output\n        array.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting index (i.e., index offset) for\n        the strided output array.\n\n    fcn: Function\n        Nullary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1 ];\n    > var offsets = [ 0 ];\n    > var fcn = constantFunction( 3.0 );\n    > base.strided.nullary.ndarray( [ x ], shape, strides, offsets, fcn );\n    > x\n    <Float64Array>[ 3.0, 3.0, 3.0, 3.0 ]\n\n    See Also\n    --------\n    base.strided.binary, base.strided.quaternary, base.strided.quinary, base.strided.ternary, base.strided.unary\n","base.strided.nullary.ndarray":"\nbase.strided.nullary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a nullary callback and assigns results to elements in a strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride length for the strided output\n        array.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting index (i.e., index offset) for\n        the strided output array.\n\n    fcn: Function\n        Nullary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1 ];\n    > var offsets = [ 0 ];\n    > var fcn = constantFunction( 3.0 );\n    > base.strided.nullary.ndarray( [ x ], shape, strides, offsets, fcn );\n    > x\n    <Float64Array>[ 3.0, 3.0, 3.0, 3.0 ]\n\n    See Also\n    --------\n    base.strided.binary, base.strided.quaternary, base.strided.quinary, base.strided.ternary, base.strided.unary","base.strided.offsetView":"\nbase.strided.offsetView( x, offset )\n    Returns a typed array view having the same data type as a provided input\n    typed array and starting at a specified index offset.\n\n    Parameters\n    ----------\n    x: TypedArray\n        Input array.\n\n    offset: integer\n        Starting index of the view relative to the input array.\n\n    Returns\n    -------\n    out: TypedArray\n        Typed array view having the same data type as the input array.\n\n    Examples\n    --------\n    > var x = new Float64Array( 10 );\n    > var out = base.strided.offsetView( x, 0 )\n    <Float64Array>\n    > var bool = ( out.buffer === x.buffer )\n    true\n\n    See Also\n    --------\n    base.strided.minViewBufferIndex\n","base.strided.quaternary":"\nbase.strided.quaternary( arrays, shape, strides, fcn )\n    Applies a quaternary callback to strided input array elements and assigns\n    results to elements in a strided output array.\n\n    The `shape` and `strides` parameters determine which elements in the strided\n    input and output arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing four strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    fcn: Function\n        Quaternary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1, 1, 1 ];\n    > function f( x, y, z, w ) { return x + y + z + w; };\n    > base.strided.quaternary( [ x, y, z, w, u ], shape, strides, f );\n    > u\n    <Float64Array>[ 4.0, 8.0, 12.0, 16.0 ]\n\n\nbase.strided.quaternary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a quaternary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing four strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Quaternary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1, 1, 1 ];\n    > var offsets = [ 0, 0, 0, 0, 0 ];\n    > function f( x, y, z, w ) { return x + y + z + w; };\n    > base.strided.quaternary.ndarray( [ x, y, z, w, u ], shape, strides, offsets, f );\n    > u\n    <Float64Array>[ 4.0, 8.0, 12.0, 16.0 ]\n\n    See Also\n    --------\n    base.strided.binary, base.strided.nullary, base.strided.quinary, base.strided.ternary, base.strided.unary\n","base.strided.quaternary.ndarray":"\nbase.strided.quaternary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a quaternary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing four strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Quaternary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var u = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1, 1, 1 ];\n    > var offsets = [ 0, 0, 0, 0, 0 ];\n    > function f( x, y, z, w ) { return x + y + z + w; };\n    > base.strided.quaternary.ndarray( [ x, y, z, w, u ], shape, strides, offsets, f );\n    > u\n    <Float64Array>[ 4.0, 8.0, 12.0, 16.0 ]\n\n    See Also\n    --------\n    base.strided.binary, base.strided.nullary, base.strided.quinary, base.strided.ternary, base.strided.unary","base.strided.quinary":"\nbase.strided.quinary( arrays, shape, strides, fcn )\n    Applies a quinary callback to strided input array elements and assigns\n    results to elements in a strided output array.\n\n    The `shape` and `strides` parameters determine which elements in the strided\n    input and output arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing five strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    fcn: Function\n        Quinary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1, 1, 1, 1 ];\n    > function f( x, y, z, w, u ) { return x + y + z + w + u; };\n    > base.strided.quinary( [ x, y, z, w, u, v ], shape, strides, f );\n    > v\n    <Float64Array>[ 5.0, 10.0, 15.0, 20.0 ]\n\n\nbase.strided.quinary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a quinary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing five strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Quinary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1, 1, 1, 1 ];\n    > var offsets = [ 0, 0, 0, 0, 0, 0 ];\n    > function f( x, y, z, w, u ) { return x + y + z + w + u; };\n    > base.strided.quinary.ndarray( [ x, y, z, w, u, v ], shape, strides, offsets, f );\n    > v\n    <Float64Array>[ 5.0, 10.0, 15.0, 20.0 ]\n\n    See Also\n    --------\n    base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.ternary, base.strided.unary\n","base.strided.quinary.ndarray":"\nbase.strided.quinary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a quinary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing five strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Quinary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var w = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var u = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var v = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1, 1, 1, 1 ];\n    > var offsets = [ 0, 0, 0, 0, 0, 0 ];\n    > function f( x, y, z, w, u ) { return x + y + z + w + u; };\n    > base.strided.quinary.ndarray( [ x, y, z, w, u, v ], shape, strides, offsets, f );\n    > v\n    <Float64Array>[ 5.0, 10.0, 15.0, 20.0 ]\n\n    See Also\n    --------\n    base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.ternary, base.strided.unary","base.strided.range":"\nbase.strided.range( N, x, stride )\n    Computes the range of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.range( x.length, x, 1 )\n    4.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.range( N, x, stride )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.range( N, x1, stride )\n    4.0\n\nbase.strided.range.ndarray( N, x, stride, offset )\n    Computes the range of a strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.range.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.range.ndarray( N, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.drange, base.strided.max, base.strided.min, base.strided.nanrange, base.strided.srange\n","base.strided.range.ndarray":"\nbase.strided.range.ndarray( N, x, stride, offset )\n    Computes the range of a strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.range.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.range.ndarray( N, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.drange, base.strided.max, base.strided.min, base.strided.nanrange, base.strided.srange","base.strided.rangeBy":"\nbase.strided.rangeBy( N, x, stride, clbk[, thisArg] )\n    Calculates the range of a strided array via a callback function.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - aidx: array index.\n    - sidx: strided index (offset + aidx*stride).\n    - array: the input array.\n\n    The callback function should return a numeric value.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.rangeBy( x.length, x, 1, accessor )\n    18.0\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.rangeBy( N, x, 2, accessor )\n    12.0\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.rangeBy( N, x1, 2, accessor )\n    8.0\n\nbase.strided.rangeBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the range of a strided array via a callback function and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.rangeBy.ndarray( x.length, x, 1, 0, accessor )\n    18.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.rangeBy.ndarray( N, x, 2, 1, accessor )\n    8.0\n\n    See Also\n    --------\n    base.strided.drange, base.strided.maxBy, base.strided.minBy, base.strided.nanrangeBy, base.strided.range, base.strided.srange\n","base.strided.rangeBy.ndarray":"\nbase.strided.rangeBy.ndarray( N, x, stride, offset, clbk[, thisArg] )\n    Calculates the range of a strided array via a callback function and using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > function accessor( v ) { return v * 2.0; };\n    > var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ];\n    > base.strided.rangeBy.ndarray( x.length, x, 1, 0, accessor )\n    18.0\n\n    // Using an index offset:\n    > x = [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.rangeBy.ndarray( N, x, 2, 1, accessor )\n    8.0\n\n    See Also\n    --------\n    base.strided.drange, base.strided.maxBy, base.strided.minBy, base.strided.nanrangeBy, base.strided.range, base.strided.srange","base.strided.reinterpretComplex":"\nbase.strided.reinterpretComplex( x, offset )\n    Returns a real-valued floating-point array view of a complex-valued\n    floating-point array having the same precision.\n\n    Parameters\n    ----------\n    x: Complex128Array|Complex64Array\n        Input array.\n\n    offset: integer\n        Starting index of the view relative to the input array.\n\n    Returns\n    -------\n    out: Float64Array|Float32Array\n        Real-valued floating-point array view.\n\n    Examples\n    --------\n    > var x = new Complex128Array( 10 );\n    > var out = base.strided.reinterpretComplex( x, 0 )\n    <Float64Array>\n    > var bool = ( out.buffer === x.buffer )\n    true\n    > x = new Complex64Array( 10 );\n    > out = base.strided.reinterpretComplex( x, 0 )\n    <Float32Array>\n    > bool = ( out.buffer === x.buffer )\n    true\n\n    See Also\n    --------\n    base.strided.reinterpretComplex128, base.strided.reinterpretComplex64\n","base.strided.reinterpretComplex64":"\nbase.strided.reinterpretComplex64( x, offset )\n    Returns a Float32Array view of a Complex64Array.\n\n    Parameters\n    ----------\n    x: Complex64Array\n        Input array.\n\n    offset: integer\n        Starting index of the view relative to the Complex64Array.\n\n    Returns\n    -------\n    out: Float32Array\n        Float32Array view.\n\n    Examples\n    --------\n    > var x = new Complex64Array( 10 );\n    > var out = base.strided.reinterpretComplex64( x, 0 )\n    <Float32Array>\n    > var bool = ( out.buffer === x.buffer )\n    true\n\n    See Also\n    --------\n    base.strided.reinterpretComplex, base.strided.reinterpretComplex128\n","base.strided.reinterpretComplex128":"\nbase.strided.reinterpretComplex128( x, offset )\n    Returns a Float64Array view of a Complex128Array.\n\n    Parameters\n    ----------\n    x: Complex128Array\n        Input array.\n\n    offset: integer\n        Starting index of the view relative to the Complex128Array.\n\n    Returns\n    -------\n    out: Float64Array\n        Float64Array view.\n\n    Examples\n    --------\n    > var x = new Complex128Array( 10 );\n    > var out = base.strided.reinterpretComplex128( x, 0 )\n    <Float64Array>\n    > var bool = ( out.buffer === x.buffer )\n    true\n\n    See Also\n    --------\n    base.strided.reinterpretComplex, base.strided.reinterpretComplex64\n","base.strided.sabs":"\nbase.strided.sabs( N, x, strideX, y, strideY )\n    Computes the absolute value for each element in a single-precision floating-\n    point strided array `x` and assigns the results to elements in a single-\n    precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sabs( x.length, x, 1, y, 1 )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sabs( N, x, 2, y, -1 )\n    <Float32Array>[ 3.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.sabs( N, x1, -2, y1, 1 )\n    <Float32Array>[ 4.0, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.sabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the absolute value for each element in a single-precision floating-\n    point strided array `x` and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    strided.abs, base.strided.dabs, base.strided.sabs2\n","base.strided.sabs.ndarray":"\nbase.strided.sabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the absolute value for each element in a single-precision floating-\n    point strided array `x` and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    strided.abs, base.strided.dabs, base.strided.sabs2","base.strided.sabs2":"\nbase.strided.sabs2( N, x, strideX, y, strideY )\n    Computes the squared absolute value for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sabs2( x.length, x, 1, y, 1 )\n    <Float32Array>[ 1.0, 4.0, 9.0, 16.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sabs2( N, x, 2, y, -1 )\n    <Float32Array>[ 9.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.sabs2( N, x1, -2, y1, 1 )\n    <Float32Array>[ 16.0, 4.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 16.0, 4.0 ]\n\n\nbase.strided.sabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the squared absolute value for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 4.0, 9.0, 16.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 16.0, 4.0 ]\n\n    See Also\n    --------\n    strided.abs2, base.strided.dabs2, base.strided.sabs\n","base.strided.sabs2.ndarray":"\nbase.strided.sabs2.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the squared absolute value for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sabs2.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 4.0, 9.0, 16.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sabs2.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 16.0, 4.0 ]\n\n    See Also\n    --------\n    strided.abs2, base.strided.dabs2, base.strided.sabs","base.strided.sapx":"\nbase.strided.sapx( N, alpha, x, stride )\n    Adds a constant to each element in a single-precision floating-point strided\n    array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns the strided array unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sapx( x.length, 5.0, x, 1 )\n    <Float32Array>[ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sapx( 3, 5.0, x, 2 )\n    <Float32Array>[ 3.0, 1.0, 8.0, -5.0, 9.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sapx( 3, 5.0, x1, 2 )\n    <Float32Array>[ 3.0, 3.0, 1.0, 5.0, -1.0 ]\n    > x0\n    <Float32Array>[ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n\nbase.strided.sapx.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each element in a single-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sapx.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float32Array>[ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.sapx.ndarray( 3, 5.0, x, 2, 1 )\n    <Float32Array>[ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dapx, base.strided.gapx\n","base.strided.sapx.ndarray":"\nbase.strided.sapx.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each element in a single-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sapx.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float32Array>[ 3.0, 6.0, 8.0, 0.0, 9.0, 4.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.sapx.ndarray( 3, 5.0, x, 2, 1 )\n    <Float32Array>[ 1.0, 3.0, 3.0, 1.0, 5.0, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dapx, base.strided.gapx","base.strided.sapxsum":"\nbase.strided.sapxsum( N, alpha, x, stride )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum.\n\n    The `N` and stride parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsum( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.sapxsum( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sapxsum( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.sapxsum.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sapxsum.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.gapxsum, base.strided.sapxsumpw, base.strided.ssum\n","base.strided.sapxsum.ndarray":"\nbase.strided.sapxsum.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sapxsum.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsum, base.strided.gapxsum, base.strided.sapxsumpw, base.strided.ssum","base.strided.sapxsumkbn":"\nbase.strided.sapxsumkbn( N, alpha, x, stride )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using an improved Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumkbn( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.sapxsumkbn( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sapxsumkbn( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.sapxsumkbn.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumkbn, base.strided.gapxsumkbn, base.strided.sapxsum, base.strided.ssumkbn\n","base.strided.sapxsumkbn.ndarray":"\nbase.strided.sapxsumkbn.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumkbn.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sapxsumkbn.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumkbn, base.strided.gapxsumkbn, base.strided.sapxsum, base.strided.ssumkbn","base.strided.sapxsumkbn2":"\nbase.strided.sapxsumkbn2( N, alpha, x, stride )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using a second-order iterative Kahan–Babuška\n    algorithm.\n\n    The `N` and `stride` parameters determine which elements in the \n    strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumkbn2( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.sapxsumkbn2( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sapxsumkbn2( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.sapxsumkbn2.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsum, base.strided.ssumkbn2\n","base.strided.sapxsumkbn2.ndarray":"\nbase.strided.sapxsumkbn2.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumkbn2.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sapxsumkbn2.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumkbn2, base.strided.gapxsumkbn2, base.strided.sapxsum, base.strided.ssumkbn2","base.strided.sapxsumors":"\nbase.strided.sapxsumors( N, alpha, x, stride )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using ordinary recursive summation.\n\n    The `N` and `stride` parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumors( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sapxsumors( N, 5.0, x, stride )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sapxsumors( N, 5.0, x1, stride )\n    14.0\n\n\nbase.strided.sapxsumors.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using ordinary recursive summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sapxsumors.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumors, base.strided.gapxsumors, base.strided.sapxsum, base.strided.ssumors\n","base.strided.sapxsumors.ndarray":"\nbase.strided.sapxsumors.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using ordinary recursive summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumors.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sapxsumors.ndarray( N, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumors, base.strided.gapxsumors, base.strided.sapxsum, base.strided.ssumors","base.strided.sapxsumpw":"\nbase.strided.sapxsumpw( N, alpha, x, stride )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using pairwise summation.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumpw( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var stride = 2;\n    > base.strided.sapxsumpw( 3, 5.0, x, stride )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > stride = 2;\n    > base.strided.sapxsumpw( 3, 5.0, x1, stride )\n    14.0\n\n\nbase.strided.sapxsumpw.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using pairwise summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumpw, base.strided.gapxsumpw, base.strided.sapxsum, base.strided.ssumpw\n","base.strided.sapxsumpw.ndarray":"\nbase.strided.sapxsumpw.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using pairwise summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dapxsumpw, base.strided.gapxsumpw, base.strided.sapxsum, base.strided.ssumpw","base.strided.sasum":"\nbase.strided.sasum( N, x, stride )\n    Computes the sum of the absolute values.\n\n    The sum of absolute values corresponds to the *L1* norm.\n\n    The `N` and stride parameters determine which elements in `x` are used to\n    compute the sum.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the function returns `0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    sum: float\n        Sum of absolute values.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n    > var s = base.strided.sasum( x.length, x, 1 )\n    15.0\n\n    // Sum every other value:\n    > s = base.strided.sasum( 3, x, 2 )\n    9.0\n\n    // Use view offset; e.g., starting at 2nd element:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > s = base.strided.sasum( 3, x1, 2 )\n    12.0\n\n\nbase.strided.sasum.ndarray( N, x, stride, offset )\n    Computes the sum of absolute values using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    sum: float\n        Sum of absolute values.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n    > var s = base.strided.sasum.ndarray( x.length, x, 1, 0 )\n    15.0\n\n    // Sum the last three elements:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > s = base.strided.sasum.ndarray( 3, x, -1, x.length-1 )\n    15.0\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.gasum\n","base.strided.sasum.ndarray":"\nbase.strided.sasum.ndarray( N, x, stride, offset )\n    Computes the sum of absolute values using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    sum: float\n        Sum of absolute values.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0 ] );\n    > var s = base.strided.sasum.ndarray( x.length, x, 1, 0 )\n    15.0\n\n    // Sum the last three elements:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > s = base.strided.sasum.ndarray( 3, x, -1, x.length-1 )\n    15.0\n\n    See Also\n    --------\n    base.strided.dasum, base.strided.gasum","base.strided.sasumpw":"\nbase.strided.sasumpw( N, x, stride )\n    Computes the sum of absolute values (L1 norm) of single-precision floating-\n    point strided array elements using pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in the strided \n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sasumpw( x.length, x, 1 )\n    5.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.sasumpw( 3, x, 2 )\n    5.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sasumpw( 3, x1, 2 )\n    5.0\n\n\nbase.strided.sasumpw.ndarray( N, x, stride, offset )\n    Computes the sum of absolute values (L1 norm) of single-precision floating-\n    point strided array elements using pairwise summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sasumpw.ndarray( x.length, x, 1, 0 )\n    5.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sasumpw.ndarray( 3, x, 2, 1 )\n    5.0\n\n    See Also\n    --------\n    base.strided.sasum, base.strided.dasumpw, base.strided.gasumpw, base.strided.ssumpw\n","base.strided.sasumpw.ndarray":"\nbase.strided.sasumpw.ndarray( N, x, stride, offset )\n    Computes the sum of absolute values (L1 norm) of single-precision floating-\n    point strided array elements using pairwise summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sasumpw.ndarray( x.length, x, 1, 0 )\n    5.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sasumpw.ndarray( 3, x, 2, 1 )\n    5.0\n\n    See Also\n    --------\n    base.strided.sasum, base.strided.dasumpw, base.strided.gasumpw, base.strided.ssumpw","base.strided.saxpy":"\nbase.strided.saxpy( N, alpha, x, strideX, y, strideY )\n    Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `alpha == 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > var alpha = 5.0;\n    > base.strided.saxpy( x.length, alpha, x, 1, y, 1 )\n    <Float32Array>[ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > base.strided.saxpy( 3, alpha, x, 2, y, -1 )\n    <Float32Array>[ 26.0, 16.0, 6.0, 1.0, 1.0, 1.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.saxpy( 3, 5.0, x1, -2, y1, 1 )\n    <Float32Array>[ 40.0, 31.0, 22.0 ]\n    > y0\n    <Float32Array>[ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n\nbase.strided.saxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n    Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > var alpha = 5.0;\n    > base.strided.saxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.saxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n    See Also\n    --------\n    base.strided.daxpy, base.strided.gaxpy\n","base.strided.saxpy.ndarray":"\nbase.strided.saxpy.ndarray( N, alpha, x, strideX, offsetX, y, strideY, offsetY )\n    Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > var alpha = 5.0;\n    > base.strided.saxpy.ndarray( x.length, alpha, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 6.0, 11.0, 16.0, 21.0, 26.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.saxpy.ndarray( 3, alpha, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 7.0, 8.0, 9.0, 40.0, 31.0, 22.0 ]\n\n    See Also\n    --------\n    base.strided.daxpy, base.strided.gaxpy","base.strided.scbrt":"\nbase.strided.scbrt( N, x, strideX, y, strideY )\n    Computes the cube root of each element in a single-precision floating-point \n    strided array `x` and assigns the results to elements in a single-precision \n    floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.scbrt( x.length, x, 1, y, 1 )\n    <Float32Array>[ 0.0, 1.0, 2.0, 3.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.scbrt( N, x, 2, y, -1 )\n    <Float32Array>[ 2.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.scbrt( N, x1, -2, y1, 1 )\n    <Float32Array>[ 3.0, 1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.scbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cube root of each element in a single-precision floating-point \n    strided array `x` and assigns the results to elements in a single-precision \n    floating-point strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.scbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, 1.0, 2.0, 3.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.scbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dcbrt, strided.cbrt, base.strided.ssqrt\n","base.strided.scbrt.ndarray":"\nbase.strided.scbrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cube root of each element in a single-precision floating-point \n    strided array `x` and assigns the results to elements in a single-precision \n    floating-point strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.scbrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, 1.0, 2.0, 3.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.scbrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dcbrt, strided.cbrt, base.strided.ssqrt","base.strided.sceil":"\nbase.strided.sceil( N, x, strideX, y, strideY )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward positive infinity and assigns the results to elements in a single-\n    precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sceil( x.length, x, 1, y, 1 )\n    <Float32Array>[ 2.0, 3.0, -3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sceil( N, x, 2, y, -1 )\n    <Float32Array>[ -3.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.sceil( N, x1, -2, y1, 1 )\n    <Float32Array>[ 4.0, 3.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.sceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward positive infinity and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 2.0, 3.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n    See Also\n    --------\n    strided.ceil, base.strided.dceil, base.strided.sfloor, base.strided.strunc\n","base.strided.sceil.ndarray":"\nbase.strided.sceil.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward positive infinity and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sceil.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 2.0, 3.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sceil.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n    See Also\n    --------\n    strided.ceil, base.strided.dceil, base.strided.sfloor, base.strided.strunc","base.strided.scopy":"\nbase.strided.scopy( N, x, strideX, y, strideY )\n    Copies values from `x` into `y`.\n\n    The `N` and stride parameters determine how values from `x` are copied\n    into `y`.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.scopy( x.length, x, 1, y, 1 )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.scopy( 3, x, -2, y, 1 )\n    <Float32Array>[ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n    // Using typed array views:\n    > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.scopy( 3, x1, -2, y1, 1 )\n    <Float32Array>[ 6.0, 4.0, 2.0 ]\n    > y0\n    <Float32Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.scopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Copies values from `x` into `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.scopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dcopy, base.strided.gcopy, base.strided.sswap\n","base.strided.scopy.ndarray":"\nbase.strided.scopy.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Copies values from `x` into `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.scopy.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.scopy.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dcopy, base.strided.gcopy, base.strided.sswap","base.strided.scumax":"\nbase.strided.scumax( N, x, strideX, y, strideY )\n    Computes the cumulative maximum of single-precision floating-point strided\n    array elements.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scumax( x.length, x, 1, y, 1 )\n    <Float32Array>[ 1.0, 1.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scumax( 3, x, 2, y, 2 )\n    <Float32Array>[ -2.0, 0.0, 1.0, 0.0, 2.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float32Array( x0.length );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.scumax( 3, x1, 2, y1, 1 )\n    <Float32Array>[ -2.0, 2.0, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.0, -2.0, 2.0, 2.0 ]\n\n\nbase.strided.scumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum of single-precision floating-point strided\n    array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 1.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumax, base.strided.dcumax, base.strided.scumin\n","base.strided.scumax.ndarray":"\nbase.strided.scumax.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum of single-precision floating-point strided\n    array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Stride Length for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scumax.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 1.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scumax.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumax, base.strided.dcumax, base.strided.scumin","base.strided.scumaxabs":"\nbase.strided.scumaxabs( N, x, strideX, y, strideY )\n    Computes the cumulative maximum absolute value of single-precision floating-\n    point strided array elements.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scumaxabs( x.length, x, 1, y, 1 )\n    <Float32Array>[ 1.0, 2.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.scumaxabs( N, x, 2, y, 2 )\n    <Float32Array>[ 2.0, 0.0, 2.0, 0.0, 2.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float32Array( x0.length );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.scumaxabs( N, x1, 2, y1, 1 )\n    <Float32Array>[ 2.0, 2.0, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\nbase.strided.scumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum absolute value of single-precision floating-\n    point strided array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.scumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cumaxabs, base.strided.dcumaxabs, base.strided.scumax, base.strided.scuminabs\n","base.strided.scumaxabs.ndarray":"\nbase.strided.scumaxabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative maximum absolute value of single-precision floating-\n    point strided array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.scumaxabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cumaxabs, base.strided.dcumaxabs, base.strided.scumax, base.strided.scuminabs","base.strided.scumin":"\nbase.strided.scumin( N, x, strideX, y, strideY )\n    Computes the cumulative minimum of single-precision floating-point strided\n    array elements.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scumin( x.length, x, 1, y, 1 )\n    <Float32Array>[ 1.0, -2.0, -2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.scumin( N, x, 2, y, 2 )\n    <Float32Array>[ -2.0, 0.0, -2.0, 0.0, -2.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float32Array( x0.length );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.scumin( N, x1, 2, y1, 1 )\n    <Float32Array>[ -2.0, -2.0, -2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\nbase.strided.scumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum of single-precision floating-point strided\n    array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -2.0, -2.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.scumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumin, base.strided.dcumin, base.strided.scumax\n","base.strided.scumin.ndarray":"\nbase.strided.scumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum of single-precision floating-point strided\n    array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scumin.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -2.0, -2.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.scumin.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -2.0, -2.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.cumin, base.strided.dcumin, base.strided.scumax","base.strided.scuminabs":"\nbase.strided.scuminabs( N, x, strideX, y, strideY )\n    Computes the cumulative minimum absolute value of single-precision floating-\n    point strided array elements.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scuminabs( x.length, x, 1, y, 1 )\n    <Float32Array>[ 1.0, 1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.scuminabs( N, x, 2, y, 2 )\n    <Float32Array>[ 2.0, 0.0, 1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float32Array( x0.length );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.scuminabs( N, x1, 2, y1, 1 )\n    <Float32Array>[ 2.0, 2.0, 1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.0, 2.0, 2.0, 1.0 ]\n\nbase.strided.scuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum absolute value of single-precision floating-\n    point strided array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.scuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cuminabs, base.strided.dcuminabs, base.strided.scumaxabs, base.strided.scumin\n","base.strided.scuminabs.ndarray":"\nbase.strided.scuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative minimum absolute value of single-precision floating-\n    point strided array elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.scuminabs.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, 1.0, 2.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.cuminabs, base.strided.dcuminabs, base.strided.scumaxabs, base.strided.scumin","base.strided.scusum":"\nbase.strided.scusum( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements.\n\n    The `N` and `stride` parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusum( x.length, 0.0, x, 1, y, 1 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusum( 3, 0.0, x, 2, y, 2 )\n    <Float32Array>[ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float32Array( x0.length );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.scusum( 3, 0.0, x1, 2, y1, 1 )\n    <Float32Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusum, base.strided.scusumpw\n","base.strided.scusum.ndarray":"\nbase.strided.scusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusum.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusum, base.strided.gcusum, base.strided.scusumpw","base.strided.scusumkbn":"\nbase.strided.scusumkbn( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using an improved Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumkbn( x.length, 0.0, x, 1, y, 1 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumkbn( 3, 0.0, x, 2, y, 2 )\n    <Float32Array>[ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float32Array( x0.length );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.scusumkbn( N, 0.0, x1, 2, y1, 1 )\n    <Float32Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumkbn, base.strided.gcusumkbn, base.strided.scusum, base.strided.scusumkbn2\n","base.strided.scusumkbn.ndarray":"\nbase.strided.scusumkbn.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumkbn.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumkbn.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumkbn, base.strided.gcusumkbn, base.strided.scusum, base.strided.scusumkbn2","base.strided.scusumkbn2":"\nbase.strided.scusumkbn2( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of single-precision floating-point strided \n    array elements using a second-order iterative Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use \n    a typed array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumkbn2( x.length, 0.0, x, 1, y, 1 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumkbn2( 3, 0.0, x, 2, y, 2 )\n    <Float32Array>[ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float32Array( x0.length );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.scusumkbn2( N, 0.0, x1, 2, y1, 1 )\n    <Float32Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of single-precision floating-point strided\n    array elements using a second-order iterative Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameter supports indexing semantics\n    based on starting indices.\n\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n\n    See Also\n    --------\n    base.strided.dcusumkbn2, base.strided.gcusumkbn2, base.strided.scusum, base.strided.scusumkbn\n","base.strided.scusumkbn2.ndarray":"\nbase.strided.scusumkbn2.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of single-precision floating-point strided\n    array elements using a second-order iterative Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameter supports indexing semantics\n    based on starting indices.\n\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumkbn2.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumkbn2.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n\n    See Also\n    --------\n    base.strided.dcusumkbn2, base.strided.gcusumkbn2, base.strided.scusum, base.strided.scusumkbn","base.strided.scusumors":"\nbase.strided.scusumors( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using ordinary recursive summation.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n     are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumors( x.length, 0.0, x, 1, y, 1 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumors( 3, 0.0, x, 2, y, 2 )\n    <Float32Array>[ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float32Array( x0.length );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.scusumors( 3, 0.0, x1, 2, y1, 1 )\n    <Float32Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using ordinary recursive summation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumors, base.strided.gcusumors, base.strided.scusum\n","base.strided.scusumors.ndarray":"\nbase.strided.scusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using ordinary recursive summation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumors.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumors, base.strided.gcusumors, base.strided.scusum","base.strided.scusumpw":"\nbase.strided.scusumpw( N, sum, x, strideX, y, strideY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using pairwise summation.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `y` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumpw( x.length, 0.0, x, 1, y, 1 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumpw( 3, 0.0, x, 2, y, 2 )\n    <Float32Array>[ -2.0, 0.0, -1.0, 0.0, 1.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var y0 = new Float32Array( x0.length );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.scusumpw( 3, 0.0, x1, 2, y1, 1 )\n    <Float32Array>[ -2.0, 0.0, -1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.0, -2.0, 0.0, -1.0 ]\n\n\nbase.strided.scusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumpw, base.strided.gcusumpw, base.strided.scusum\n","base.strided.scusumpw.ndarray":"\nbase.strided.scusumpw.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sum: number\n        Initial sum.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Output array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > var y = new Float32Array( x.length );\n    > base.strided.scusumpw.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, -1.0, 1.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > y = new Float32Array( x.length );\n    > base.strided.scusumpw.ndarray( 3, 0.0, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, -1.0, 0.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dcusumpw, base.strided.gcusumpw, base.strided.scusum","base.strided.sdeg2rad":"\nbase.strided.sdeg2rad( N, x, strideX, y, strideY )\n    Converts each element in a single-precision floating-point strided array `x`\n    from degrees to radians and assigns the results to elements in a single-\n    precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sdeg2rad( x.length, x, 1, y, 1 )\n    <Float32Array>[ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sdeg2rad( N, x, 2, y, -1 )\n    <Float32Array>[ ~0.785, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.sdeg2rad( N, x1, -2, y1, 1 )\n    <Float32Array>[ ~1.047, ~0.524 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.sdeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Converts each element in a single-precision floating-point strided array `x`\n    from degrees to radians and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sdeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sdeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n    See Also\n    --------\n    base.strided.ddeg2rad, strided.deg2rad\n","base.strided.sdeg2rad.ndarray":"\nbase.strided.sdeg2rad.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Converts each element in a single-precision floating-point strided array `x`\n    from degrees to radians and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sdeg2rad.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, ~0.524, ~0.785, ~1.047 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sdeg2rad.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n    See Also\n    --------\n    base.strided.ddeg2rad, strided.deg2rad","base.strided.sdot":"\nbase.strided.sdot( N, x, strideX, y, strideY )\n    Computes the dot product of two single-precision floating-point vectors.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: float\n        The dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var out = base.strided.sdot( x.length, x, 1, y, 1 )\n    -5.0\n\n    // Strides:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > out = base.strided.sdot( 3, x, 2, y, -1 )\n    9.0\n\n    // Using view offsets:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n    > out = base.strided.sdot( 3, x1, -2, y1, 1 )\n    128.0\n\n\nbase.strided.sdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the dot product of two single-precision floating-point vectors\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing based on a starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: float\n        The dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var out = base.strided.sdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    -5.0\n\n    // Strides:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > out = base.strided.sdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n    9.0\n\n    // Using offset indices:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > out = base.strided.sdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n    128.0\n\n    See Also\n    --------\n    base.strided.ddot, base.strided.dsdot, base.strided.sdsdot, sdot\n","base.strided.sdot.ndarray":"\nbase.strided.sdot.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the dot product of two single-precision floating-point vectors\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing based on a starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: float\n        The dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var out = base.strided.sdot.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    -5.0\n\n    // Strides:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > out = base.strided.sdot.ndarray( 3, x, 2, 0, y, 2, 0 )\n    9.0\n\n    // Using offset indices:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > out = base.strided.sdot.ndarray( 3, x, -2, x.length-1, y, 1, 3 )\n    128.0\n\n    See Also\n    --------\n    base.strided.ddot, base.strided.dsdot, base.strided.sdsdot, sdot","base.strided.sdsapxsum":"\nbase.strided.sdsapxsum( N, alpha, x, stride )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using extended accumulation.\n\n    The `N` and `stride` parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsapxsum( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.sdsapxsum( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sdsapxsum( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.sdsapxsum.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using extended accumulation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sdsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dsapxsum, base.strided.sapxsum, base.strided.sdssum\n","base.strided.sdsapxsum.ndarray":"\nbase.strided.sdsapxsum.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using extended accumulation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsapxsum.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sdsapxsum.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dsapxsum, base.strided.sapxsum, base.strided.sdssum","base.strided.sdsapxsumpw":"\nbase.strided.sdsapxsumpw( N, alpha, x, stride )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using pairwise summation with extended\n    accumulation.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsapxsumpw( x.length, 5.0, x, 1 )\n    16.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.sdsapxsumpw( 3, 5.0, x, 2 )\n    16.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sdsapxsumpw( 3, 5.0, x1, 2 )\n    14.0\n\n\nbase.strided.sdsapxsumpw.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using pairwise summation with extended\n    accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sdsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dsapxsumpw, base.strided.sapxsumpw, base.strided.sdsapxsum, base.strided.sdssumpw","base.strided.sdsapxsumpw.ndarray":"\nbase.strided.sdsapxsumpw.ndarray( N, alpha, x, stride, offset )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using pairwise summation with extended\n    accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsapxsumpw.ndarray( x.length, 5.0, x, 1, 0 )\n    16.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sdsapxsumpw.ndarray( 3, 5.0, x, 2, 1 )\n    14.0\n\n    See Also\n    --------\n    base.strided.dsapxsumpw, base.strided.sapxsumpw, base.strided.sdsapxsum, base.strided.sdssumpw","base.strided.sdsdot":"\nbase.strided.sdsdot( N, scalar, x, strideX, y, strideY )\n    Computes the dot product of two single-precision floating-point vectors with\n    extended accumulation.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0` the function returns the provided scalar constant.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    scalar: number\n        Scalar constant added to dot product.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    out: number\n        The dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var out = base.strided.sdsdot( x.length, 0.0, x, 1, y, 1 )\n    -5.0\n\n    // Strides:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > out = base.strided.sdsdot( 3, 0.0, x, 2, y, -1 )\n    9.0\n\n    // Using view offsets:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float32Array( x.buffer, x.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y.buffer, y.BYTES_PER_ELEMENT*3 );\n    > out = base.strided.sdsdot( 3, 0.0, x1, -2, y1, 1 )\n    128.0\n\n\nbase.strided.sdsdot.ndarray( N, scalar, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the dot product of two single-precision floating-point vectors\n    using alternative indexing semantics and with extended accumulation.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing based on a starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    scalar: number\n        Scalar constant added to dot product.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: number\n        The dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var out = base.strided.sdsdot.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    -5.0\n\n    // Strides:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > out = base.strided.sdsdot.ndarray( 3, 0.0, x, 2, 0, y, 2, 0 )\n    9.0\n\n    // Using offset indices:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > out = base.strided.sdsdot.ndarray( 3, 0.0, x, -2, x.length-1, y, 1, 3 )\n    128.0\n\n    References\n    ----------\n    - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n    Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n    Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n    NY, USA: Association for Computing Machinery: 324–25.\n    doi:10.1145/355841.355848.\n\n    See Also\n    --------\n    base.strided.ddot, base.strided.dsdot, base.strided.sdot\n","base.strided.sdsdot.ndarray":"\nbase.strided.sdsdot.ndarray( N, scalar, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the dot product of two single-precision floating-point vectors\n    using alternative indexing semantics and with extended accumulation.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing based on a starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    scalar: number\n        Scalar constant added to dot product.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    out: number\n        The dot product.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var y = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var out = base.strided.sdsdot.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 )\n    -5.0\n\n    // Strides:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );\n    > out = base.strided.sdsdot.ndarray( 3, 0.0, x, 2, 0, y, 2, 0 )\n    9.0\n\n    // Using offset indices:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > out = base.strided.sdsdot.ndarray( 3, 0.0, x, -2, x.length-1, y, 1, 3 )\n    128.0\n\n    References\n    ----------\n    - Lawson, Charles L., Richard J. Hanson, Fred T. Krogh, and David Ronald\n    Kincaid. 1979. \"Algorithm 539: Basic Linear Algebra Subprograms for Fortran\n    Usage [F1].\" *ACM Transactions on Mathematical Software* 5 (3). New York,\n    NY, USA: Association for Computing Machinery: 324–25.\n    doi:10.1145/355841.355848.\n\n    See Also\n    --------\n    base.strided.ddot, base.strided.dsdot, base.strided.sdot","base.strided.sdsmean":"\nbase.strided.sdsmean( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using extended accumulation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsmean( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sdsmean( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sdsmean( N, x1, stride )\n    ~-0.3333\n\nbase.strided.sdsmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using extended accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sdsmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsnanmean, base.strided.smean\n","base.strided.sdsmean.ndarray":"\nbase.strided.sdsmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using extended accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sdsmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsnanmean, base.strided.smean","base.strided.sdsmeanors":"\nbase.strided.sdsmeanors( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation with extended accumulation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsmeanors( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sdsmeanors( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sdsmeanors( N, x1, stride )\n    ~-0.3333\n\nbase.strided.sdsmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation with extended accumulation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sdsmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.sdsmean, base.strided.sdsnanmeanors\n","base.strided.sdsmeanors.ndarray":"\nbase.strided.sdsmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation with extended accumulation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdsmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sdsmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.sdsmean, base.strided.sdsnanmeanors","base.strided.sdsnanmean":"\nbase.strided.sdsnanmean( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using extended accumulation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnanmean( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sdsnanmean( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sdsnanmean( N, x1, stride )\n    ~-0.3333\n\nbase.strided.sdsnanmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using extended accumulation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnanmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sdsnanmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.dsnanmean, base.strided.nanmean, base.strided.sdsmean, base.strided.snanmean\n","base.strided.sdsnanmean.ndarray":"\nbase.strided.sdsnanmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using extended accumulation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnanmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sdsnanmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.dsnanmean, base.strided.nanmean, base.strided.sdsmean, base.strided.snanmean","base.strided.sdsnanmeanors":"\nbase.strided.sdsnanmeanors( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation with\n    extended accumulation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnanmeanors( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sdsnanmeanors( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sdsnanmeanors( N, x1, stride )\n    ~-0.3333\n\nbase.strided.sdsnanmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation with\n    extended accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnanmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sdsnanmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.sdsmeanors, base.strided.sdsnanmean\n","base.strided.sdsnanmeanors.ndarray":"\nbase.strided.sdsnanmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation with\n    extended accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnanmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sdsnanmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.sdsmeanors, base.strided.sdsnanmean","base.strided.sdsnansum":"\nbase.strided.sdsnansum( N, x, stride )\n    Computes the sum of single-precision floating-point strided array\n    elements, ignore `NaN` values and using extended accumulation.\n\n    The `N` and `stride` parameters determine which elements in the\n    strided array are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnansum( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > var stride = 2;\n    > base.strided.sdsnansum( 4, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > stride = 2;\n    > base.strided.sdsnansum( 4, x1, stride )\n    -1.0\n\n\nbase.strided.sdsnansum.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using extended accumulation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnansum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.sdsnansum.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnansum, base.strided.dnansum, base.strided.gnansum, base.strided.sdssum, base.strided.snansum\n","base.strided.sdsnansum.ndarray":"\nbase.strided.sdsnansum.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using extended accumulation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnansum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.sdsnansum.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnansum, base.strided.dnansum, base.strided.gnansum, base.strided.sdssum, base.strided.snansum","base.strided.sdsnansumpw":"\nbase.strided.sdsnansumpw( N, x, stride )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation with extended\n    accumulation.\n\n    The `N` and `stride` parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnansumpw( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.sdsnansumpw( 4, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sdsnansumpw( 4, x1, 2 )\n    -1.0\n\n\nbase.strided.sdsnansumpw.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation with extended\n    accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnansumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.sdsnansumpw.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnansumpw, base.strided.dnansumpw, base.strided.gnansumpw, base.strided.sdsnansum, base.strided.sdssumpw, base.strided.snansumpw\n","base.strided.sdsnansumpw.ndarray":"\nbase.strided.sdsnansumpw.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation with extended\n    accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.sdsnansumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.sdsnansumpw.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsnansumpw, base.strided.dnansumpw, base.strided.gnansumpw, base.strided.sdsnansum, base.strided.sdssumpw, base.strided.snansumpw","base.strided.sdssum":"\nbase.strided.sdssum( N, x, stride )\n    Computes the sum of single-precision floating-point strided array elements\n    using extended accumulation.\n\n    The `N` and stride parameters determine which elements in \n    the strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdssum( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var stride = 2;\n    > base.strided.sdssum( 3, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > stride = 2;\n    > base.strided.sdssum( 3, x1, stride )\n    -1.0\n\n\nbase.strided.sdssum.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements\n    using extended accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdssum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sdssum.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dssum, base.strided.dsum, base.strided.sdsnansum, base.strided.ssum, base.strided.gsum\n","base.strided.sdssum.ndarray":"\nbase.strided.sdssum.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements\n    using extended accumulation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdssum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sdssum.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dssum, base.strided.dsum, base.strided.sdsnansum, base.strided.ssum, base.strided.gsum","base.strided.sdssumpw":"\nbase.strided.sdssumpw( N, x, stride )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation with extended accumulation.\n\n    The `N` and stride parameters determine which elements in the strided\n    array are accessed are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset,\n    use a typed array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdssumpw( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var stride = 2;\n    > base.strided.sdssumpw( 3, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > stride = 2;\n    > base.strided.sdssumpw( 3, x1, stride )\n    -1.0\n\n\nbase.strided.sdssumpw.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation with extended accumulation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdssumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sdssumpw.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dssumpw, base.strided.dsumpw, base.strided.sdsnansumpw, base.strided.sdssum, base.strided.ssumpw, base.strided.gsumpw\n","base.strided.sdssumpw.ndarray":"\nbase.strided.sdssumpw.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation with extended accumulation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sdssumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sdssumpw.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dssumpw, base.strided.dsumpw, base.strided.sdsnansumpw, base.strided.sdssum, base.strided.ssumpw, base.strided.gsumpw","base.strided.sfill":"\nbase.strided.sfill( N, alpha, x, strideX )\n    Fills a single-precision floating-point strided array with a specified\n    scalar value.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sfill( x.length, 5.0, x, 1 )\n    <Float32Array>[ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sfill( 3, 5.0, x, 2 )\n    <Float32Array>[ 5.0, 1.0, 5.0, -5.0, 5.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sfill( 3, 5.0, x1, 2 )\n    <Float32Array>[ 5.0, 3.0, 5.0, 5.0, 5.0 ]\n    > x0\n    <Float32Array>[ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n\nbase.strided.sfill.ndarray( N, alpha, x, strideX, offsetX )\n    Fills a single-precision floating-point strided array with a specified\n    scalar value using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sfill.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float32Array>[ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.sfill.ndarray( 3, 5.0, x, 2, 1 )\n    <Float32Array>[ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n    See Also\n    --------\n    base.strided.dfill, base.strided.gfill\n","base.strided.sfill.ndarray":"\nbase.strided.sfill.ndarray( N, alpha, x, strideX, offsetX )\n    Fills a single-precision floating-point strided array with a specified\n    scalar value using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sfill.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float32Array>[ 5.0, 5.0, 5.0, 5.0, 5.0, 5.0, 5.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.sfill.ndarray( 3, 5.0, x, 2, 1 )\n    <Float32Array>[ 1.0, 5.0, 3.0, 5.0, 5.0, 5.0 ]\n\n    See Also\n    --------\n    base.strided.dfill, base.strided.gfill","base.strided.sfloor":"\nbase.strided.sfloor( N, x, strideX, y, strideY )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward negative infinity and assigns the results to elements in a single-\n    precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sfloor( x.length, x, 1, y, 1 )\n    <Float32Array>[ -2.0, 1.0, 3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sfloor( N, x, 2, y, -1 )\n    <Float32Array>[ 3.0, -2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.sfloor( N, x1, -2, y1, 1 )\n    <Float32Array>[ 4.0, 1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 4.0, 1.0 ]\n\n\nbase.strided.sfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward negative infinity and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ -2.0, 1.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dfloor, strided.floor, base.strided.sceil, base.strided.strunc\n","base.strided.sfloor.ndarray":"\nbase.strided.sfloor.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward negative infinity and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sfloor.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ -2.0, 1.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -1.1, 1.1, 3.8, 4.5 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sfloor.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dfloor, strided.floor, base.strided.sceil, base.strided.strunc","base.strided.sinv":"\nbase.strided.sinv( N, x, strideX, y, strideY )\n    Computes the multiplicative inverse for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sinv( x.length, x, 1, y, 1 )\n    <Float32Array>[ ~-0.05, -1.0, 0.5, 0.25 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sinv( N, x, 2, y, -1 )\n    <Float32Array>[ 0.5, ~-0.05, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.sinv( N, x1, -2, y1, 1 )\n    <Float32Array>[ 0.25, -1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.sinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the multiplicative inverse for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ ~-0.05, -1.0, 0.5, 0.25 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dinv, strided.inv\n","base.strided.sinv.ndarray":"\nbase.strided.sinv.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the multiplicative inverse for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sinv.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ ~-0.05, -1.0, 0.5, 0.25 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sinv.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dinv, strided.inv","base.strided.smap":"\nbase.strided.smap( N, x, strideX, y, strideY, fcn )\n    Applies a unary function to a single-precision floating-point strided input\n    array and assigns results to a single-precision floating-point strided\n    output array.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap( x.length, x, 1, y, 1, base.identityf )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap( 2, x, 2, y, -1, base.identityf )\n    <Float32Array>[ 3.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smap( 2, x1, -2, y1, 1, base.identityf )\n    <Float32Array>[ 4.0, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n    Applies a unary function to a single-precision floating-point strided input\n    array and assigns results to a single-precision floating-point strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identityf )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identityf )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmap, base.strided.unary\n","base.strided.smap.ndarray":"\nbase.strided.smap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n    Applies a unary function to a single-precision floating-point strided input\n    array and assigns results to a single-precision floating-point strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap.ndarray( x.length, x, 1, 0, y, 1, 0, base.identityf )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.identityf )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmap, base.strided.unary","base.strided.smap2":"\nbase.strided.smap2( N, x, sx, y, sy, z, sz, fcn )\n    Applies a binary function to single-precision floating-point strided input\n    arrays and assigns results to a single-precision floating-point strided\n    output array.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    z: Float32Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float32Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap2( x.length, x, 1, y, 1, z, 1, base.addf )\n    <Float32Array>[ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Using `N` and stride parameters:\n    > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap2( 2, x, 2, y, -1, z, 1, base.addf )\n    <Float32Array>[ 3.0, 4.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smap2( 2, x1, -2, y1, 1, z1, 1, base.addf )\n    <Float32Array>[ 7.0, 6.0 ]\n    > z0\n    <Float32Array>[ 0.0, 0.0, 7.0, 6.0 ]\n\n\nbase.strided.smap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n    Applies a binary function to single-precision floating-point strided input\n    arrays and assigns results to a single-precision floating-point strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Float32Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float32Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.addf )\n    <Float32Array>[ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.addf )\n    <Float32Array>[ 0.0, 6.0, 7.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmap2, base.strided.binary\n","base.strided.smap2.ndarray":"\nbase.strided.smap2.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, fcn )\n    Applies a binary function to single-precision floating-point strided input\n    arrays and assigns results to a single-precision floating-point strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Float32Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float32Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap2.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, base.addf )\n    <Float32Array>[ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smap2.ndarray( 2, x, 2, 1, y, -1, y.length-1, z, 1, 1, base.addf )\n    <Float32Array>[ 0.0, 6.0, 7.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmap2, base.strided.binary","base.strided.smax":"\nbase.strided.smax( N, x, strideX )\n    Computes the maximum value of a single-precision floating-point strided\n    array.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smax( x.length, x, 1 )\n    2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.smax( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.smax( 3, x1, 2 )\n    2.0\n\n\nbase.strided.smax.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a single-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smax.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smax.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.max, base.strided.smin, base.strided.snanmax\n","base.strided.smax.ndarray":"\nbase.strided.smax.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a single-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smax.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smax.ndarray( N, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmax, base.strided.max, base.strided.smin, base.strided.snanmax","base.strided.smaxabs":"\nbase.strided.smaxabs( N, x, strideX )\n    Computes the maximum absolute value of a single-precision floating-point\n    strided array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smaxabs( x.length, x, 1 )\n    2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.smaxabs( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.smaxabs( 3, x1, 2 )\n    2.0\n\n\nbase.strided.smaxabs.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smaxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.smaxabs.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmaxabs, base.strided.maxabs, base.strided.smax, base.strided.sminabs, base.strided.snanmaxabs\n","base.strided.smaxabs.ndarray":"\nbase.strided.smaxabs.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smaxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.smaxabs.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmaxabs, base.strided.maxabs, base.strided.smax, base.strided.sminabs, base.strided.snanmaxabs","base.strided.smaxabssorted":"\nbase.strided.smaxabssorted( N, x, strideX )\n    Computes the maximum absolute value of a sorted single-precision floating-\n    point strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n    > base.strided.smaxabssorted( x.length, x, 1 )\n    3.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.smaxabssorted( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.smaxabssorted( 3, x1, 2 )\n    3.0\n\n\nbase.strided.smaxabssorted.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a sorted single-precision floating-\n    point strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n    > base.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.smaxabssorted.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmaxabssorted, base.strided.smaxabs, base.strided.smaxsorted\n","base.strided.smaxabssorted.ndarray":"\nbase.strided.smaxabssorted.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a sorted single-precision floating-\n    point strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -1.0, -2.0, -3.0 ] );\n    > base.strided.smaxabssorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.smaxabssorted.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmaxabssorted, base.strided.smaxabs, base.strided.smaxsorted","base.strided.smaxsorted":"\nbase.strided.smaxsorted( N, x, strideX )\n    Computes the maximum value of a sorted single-precision floating-point\n    strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.smaxsorted( x.length, x, 1 )\n    3.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.smaxsorted( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.smaxsorted( 3, x1, 2 )\n    3.0\n\n\nbase.strided.smaxsorted.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.smaxsorted.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmaxsorted, base.strided.maxsorted, base.strided.smax, base.strided.sminsorted\n","base.strided.smaxsorted.ndarray":"\nbase.strided.smaxsorted.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.smaxsorted.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.smaxsorted.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dmaxsorted, base.strided.maxsorted, base.strided.smax, base.strided.sminsorted","base.strided.smean":"\nbase.strided.smean( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smean( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.smean( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.smean( N, x1, stride )\n    ~-0.3333\n\nbase.strided.smean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsmean, base.strided.snanmean\n","base.strided.smean.ndarray":"\nbase.strided.smean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmean, base.strided.dsmean, base.strided.mean, base.strided.sdsmean, base.strided.snanmean","base.strided.smeankbn":"\nbase.strided.smeankbn( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeankbn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.smeankbn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.smeankbn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.smeankbn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeankbn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeankbn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeankbn, base.strided.meankbn, base.strided.smean\n","base.strided.smeankbn.ndarray":"\nbase.strided.smeankbn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeankbn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeankbn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeankbn, base.strided.meankbn, base.strided.smean","base.strided.smeankbn2":"\nbase.strided.smeankbn2( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a second-order iterative Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeankbn2( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.smeankbn2( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.smeankbn2( N, x1, stride )\n    ~-0.3333\n\nbase.strided.smeankbn2.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeankbn2.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeankbn2.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeankbn2, base.strided.meankbn2, base.strided.smean\n","base.strided.smeankbn2.ndarray":"\nbase.strided.smeankbn2.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeankbn2.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeankbn2.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeankbn2, base.strided.meankbn2, base.strided.smean","base.strided.smeanli":"\nbase.strided.smeanli( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanli( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.smeanli( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.smeanli( N, x1, stride )\n    ~-0.3333\n\nbase.strided.smeanli.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanli.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanli.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanli, base.strided.smean, base.strided.smeanlipw\n","base.strided.smeanli.ndarray":"\nbase.strided.smeanli.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanli.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanli.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanli, base.strided.smean, base.strided.smeanlipw","base.strided.smeanlipw":"\nbase.strided.smeanlipw( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm with pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanlipw( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.smeanlipw( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.smeanlipw( N, x1, stride )\n    ~-0.3333\n\nbase.strided.smeanlipw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm with pairwise summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanlipw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanlipw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanlipw, base.strided.smean, base.strided.smeanli\n","base.strided.smeanlipw.ndarray":"\nbase.strided.smeanlipw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm with pairwise summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanlipw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanlipw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanlipw, base.strided.smean, base.strided.smeanli","base.strided.smeanors":"\nbase.strided.smeanors( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanors( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.smeanors( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.smeanors( N, x1, stride )\n    ~-0.3333\n\nbase.strided.smeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanors, base.strided.meanors, base.strided.smean, base.strided.snanmeanors\n","base.strided.smeanors.ndarray":"\nbase.strided.smeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanors, base.strided.meanors, base.strided.smean, base.strided.snanmeanors","base.strided.smeanpn":"\nbase.strided.smeanpn( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a two-pass error correction algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanpn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.smeanpn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.smeanpn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.smeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a two-pass error correction algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.meanpn, base.strided.smean, base.strided.snanmeanpn\n","base.strided.smeanpn.ndarray":"\nbase.strided.smeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a two-pass error correction algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpn, base.strided.meanpn, base.strided.smean, base.strided.snanmeanpn","base.strided.smeanpw":"\nbase.strided.smeanpw( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using pairwise summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanpw( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.smeanpw( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.smeanpw( N, x1, stride )\n    ~-0.3333\n\nbase.strided.smeanpw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanpw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanpw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpw, base.strided.meanpw, base.strided.smean\n","base.strided.smeanpw.ndarray":"\nbase.strided.smeanpw.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanpw.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanpw.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanpw, base.strided.meanpw, base.strided.smean","base.strided.smeanwd":"\nbase.strided.smeanwd( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanwd( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.smeanwd( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.smeanwd( N, x1, stride )\n    ~-0.3333\n\nbase.strided.smeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanwd, base.strided.meanwd, base.strided.smean, base.strided.snanmeanwd\n","base.strided.smeanwd.ndarray":"\nbase.strided.smeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.smeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dmeanwd, base.strided.meanwd, base.strided.smean, base.strided.snanmeanwd","base.strided.smediansorted":"\nbase.strided.smediansorted( N, x, strideX )\n    Computes the median value of a sorted single-precision floating-point\n    strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    strideX: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.smediansorted( x.length, x, 1 )\n    2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.smediansorted( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.smediansorted( 3, x1, 2 )\n    2.0\n\n\nbase.strided.smediansorted.ndarray( N, x, strideX, offsetX )\n    Computes the median value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    strideX: integer\n        Index increment.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.smediansorted.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.smediansorted.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmediansorted, base.strided.mediansorted, base.strided.smean\n","base.strided.smediansorted.ndarray":"\nbase.strided.smediansorted.ndarray( N, x, strideX, offsetX )\n    Computes the median value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    strideX: integer\n        Index increment.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Median value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.smediansorted.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.smediansorted.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmediansorted, base.strided.mediansorted, base.strided.smean","base.strided.smidrange":"\nbase.strided.smidrange( N, x, strideX )\n    Computes the mid-range of a single-precision floating-point strided array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Mid-range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smidrange( x.length, x, 1 )\n    0.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.smidrange( 3, x, 2 )\n    0.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.smidrange( 3, x1, 2 )\n    0.0\n\n\nbase.strided.smidrange.ndarray( N, x, strideX, offsetX )\n    Computes the mid-range of a single-precision floating-point strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Mid-range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smidrange.ndarray( x.length, x, 1, 0 )\n    0.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.smidrange.ndarray( 3, x, 2, 1 )\n    0.0\n\n    See Also\n    --------\n    base.strided.dmidrange, base.strided.smax, base.strided.smean, base.strided.smin, base.strided.srange\n","base.strided.smidrange.ndarray":"\nbase.strided.smidrange.ndarray( N, x, strideX, offsetX )\n    Computes the mid-range of a single-precision floating-point strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Mid-range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smidrange.ndarray( x.length, x, 1, 0 )\n    0.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.smidrange.ndarray( 3, x, 2, 1 )\n    0.0\n\n    See Also\n    --------\n    base.strided.dmidrange, base.strided.smax, base.strided.smean, base.strided.smin, base.strided.srange","base.strided.smin":"\nbase.strided.smin( N, x, strideX )\n    Computes the minimum value of a single-precision floating-point strided\n    array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smin( x.length, x, 1 )\n    -2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.smin( 3, x, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.smin( 3, x1, 2 )\n    -2.0\n\n\nbase.strided.smin.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a single-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.smin.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.min, base.strided.smax, base.strided.snanmin\n","base.strided.smin.ndarray":"\nbase.strided.smin.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a single-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.smin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.smin.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmin, base.strided.min, base.strided.smax, base.strided.snanmin","base.strided.sminabs":"\nbase.strided.sminabs( N, x, strideX )\n    Computes the minimum absolute value of a single-precision floating-point\n    strided array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sminabs( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.sminabs( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sminabs( 3, x1, 2 )\n    1.0\n\n\nbase.strided.sminabs.ndarray( N, x, strideX, offsetX )\n    Computes the minimum absolute value of a single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sminabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sminabs.ndarray( 3, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dminabs, base.strided.minabs, base.strided.smaxabs, base.strided.smin, base.strided.snanminabs\n","base.strided.sminabs.ndarray":"\nbase.strided.sminabs.ndarray( N, x, strideX, offsetX )\n    Computes the minimum absolute value of a single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sminabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.sminabs.ndarray( 3, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dminabs, base.strided.minabs, base.strided.smaxabs, base.strided.smin, base.strided.snanminabs","base.strided.sminsorted":"\nbase.strided.sminsorted( N, x, strideX )\n    Computes the minimum value of a sorted single-precision floating-point\n    strided array.\n\n    The input strided array must be sorted in either strictly ascending or\n    descending order.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.sminsorted( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.sminsorted( 3, x, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sminsorted( 3, x1, 2 )\n    -2.0\n\n\nbase.strided.sminsorted.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.sminsorted.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.sminsorted.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dminsorted, base.strided.minsorted, base.strided.smaxsorted, base.strided.smin\n","base.strided.sminsorted.ndarray":"\nbase.strided.sminsorted.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Sorted input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > base.strided.sminsorted.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, 3.0 ] );\n    > base.strided.sminsorted.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dminsorted, base.strided.minsorted, base.strided.smaxsorted, base.strided.smin","base.strided.smskabs":"\nbase.strided.smskabs( N, x, sx, m, sm, y, sy )\n    Computes the absolute value for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ 2.0, 1.0, 0.0, 5.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskabs( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ 5.0, 1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 5.0, 1.0 ]\n\n\nbase.strided.smskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the absolute value for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 2.0, 1.0, 0.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 5.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dmskabs, base.strided.sabs, base.strided.smskabs2\n","base.strided.smskabs.ndarray":"\nbase.strided.smskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the absolute value for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 2.0, 1.0, 0.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 5.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dmskabs, base.strided.sabs, base.strided.smskabs2","base.strided.smskabs2":"\nbase.strided.smskabs2( N, x, sx, m, sm, y, sy )\n    Computes the squared absolute value for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point\n    strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs2( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ 4.0, 1.0, 0.0, 25.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs2( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, 4.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskabs2( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ 25.0, 1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 25.0, 1.0 ]\n\n\nbase.strided.smskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the squared absolute value for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point\n    strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 4.0, 1.0, 0.0, 25.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 25.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dmskabs2, base.strided.sabs2, base.strided.smskabs\n","base.strided.smskabs2.ndarray":"\nbase.strided.smskabs2.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the squared absolute value for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point\n    strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs2.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 4.0, 1.0, 0.0, 25.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -2.0, 1.0, -3.0, -5.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskabs2.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 25.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dmskabs2, base.strided.sabs2, base.strided.smskabs","base.strided.smskcbrt":"\nbase.strided.smskcbrt( N, x, sx, m, sm, y, sy )\n    Computes the cube root for each element in a single-precision floating-point\n    strided array `x` according to a strided mask array and assigns the results\n    to elements in a single-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskcbrt( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ 0.0, 1.0, 0.0, 3.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskcbrt( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskcbrt( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ 3.0, 1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n\nbase.strided.smskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the cube root for each element in a single-precision floating-point\n    strided array `x` according to a strided mask array and assigns the results\n    to elements in a single-precision floating-point strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, 1.0, 0.0, 3.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dmskcbrt, base.strided.scbrt, base.strided.ssqrt\n","base.strided.smskcbrt.ndarray":"\nbase.strided.smskcbrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the cube root for each element in a single-precision floating-point\n    strided array `x` according to a strided mask array and assigns the results\n    to elements in a single-precision floating-point strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskcbrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, 1.0, 0.0, 3.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskcbrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dmskcbrt, base.strided.scbrt, base.strided.ssqrt","base.strided.smskceil":"\nbase.strided.smskceil( N, x, sx, m, sm, y, sy )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward positive infinity according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskceil( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ 2.0, 3.0, 0.0, 4.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskceil( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskceil( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ 4.0, 3.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n\nbase.strided.smskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward positive infinity according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 2.0, 3.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n    See Also\n    --------\n    base.strided.dmskceil, base.strided.sceil, base.strided.smskfloor, base.strided.smsktrunc\n","base.strided.smskceil.ndarray":"\nbase.strided.smskceil.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward positive infinity according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskceil.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 2.0, 3.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskceil.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n    See Also\n    --------\n    base.strided.dmskceil, base.strided.sceil, base.strided.smskfloor, base.strided.smsktrunc","base.strided.smskdeg2rad":"\nbase.strided.smskdeg2rad( N, x, sx, m, sm, y, sy )\n    Converts each element in a single-precision floating-point strided array `x`\n    from degrees to radians according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskdeg2rad( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ 0.0, ~0.524, 0.0, ~1.047 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskdeg2rad( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskdeg2rad( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ ~1.047, ~0.524 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n\nbase.strided.smskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Converts each element in a single-precision floating-point strided array `x`\n    from degrees to radians according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, ~0.524, 0.0, ~1.047 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n    See Also\n    --------\n    base.strided.dmskdeg2rad, base.strided.sdeg2rad\n","base.strided.smskdeg2rad.ndarray":"\nbase.strided.smskdeg2rad.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Converts each element in a single-precision floating-point strided array `x`\n    from degrees to radians according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskdeg2rad.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, ~0.524, 0.0, ~1.047 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 30.0, 45.0, 60.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskdeg2rad.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~1.047, ~0.524 ]\n\n    See Also\n    --------\n    base.strided.dmskdeg2rad, base.strided.sdeg2rad","base.strided.smskfloor":"\nbase.strided.smskfloor( N, x, sx, m, sm, y, sy )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward negative infinity according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskfloor( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskfloor( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskfloor( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ 4.0, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward negative infinity according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmskfloor, base.strided.sfloor, base.strided.smskceil, base.strided.smsktrunc\n","base.strided.smskfloor.ndarray":"\nbase.strided.smskfloor.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward negative infinity according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskfloor.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskfloor.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmskfloor, base.strided.sfloor, base.strided.smskceil, base.strided.smsktrunc","base.strided.smskinv":"\nbase.strided.smskinv( N, x, sx, m, sm, y, sy )\n    Computes the multiplicative inverse for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskinv( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ ~-0.05, -1.0, 0.0, 0.25 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskinv( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, ~-0.05, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskinv( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ 0.25, -1.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n\nbase.strided.smskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the multiplicative inverse for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ ~-0.05, -1.0, 0.0, 0.25 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dinv, base.strided.dmskinv\n","base.strided.smskinv.ndarray":"\nbase.strided.smskinv.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the multiplicative inverse for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskinv.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ ~-0.05, -1.0, 0.0, 0.25 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskinv.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dinv, base.strided.dmskinv","base.strided.smskmap":"\nbase.strided.smskmap( N, x, sx, m, sm, y, sy, fcn )\n    Applies a unary function to a single-precision floating-point strided input\n    array according to a strided mask array and assigns results to a single-\n    precision floating-point strided output array.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskmap( x.length, x, 1, m, 1, y, 1, base.identity )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskmap( 2, x, 2, m, 2, y, -1, base.identity )\n    <Float32Array>[ 0.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskmap( 2, x1, -2, m1, 1, y1, 1, base.identity )\n    <Float32Array>[ 0.0, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 0.0, 2.0 ]\n\n\nbase.strided.smskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n    Applies a unary function to a single-precision floating-point strided input\n    array according to a strided mask array and assigns results to a single-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n    <Float32Array>[ 0.0, 0.0, 4.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmskmap, base.strided.mskunary, base.strided.smap, base.strided.smskmap2\n","base.strided.smskmap.ndarray":"\nbase.strided.smskmap.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy, fcn )\n    Applies a unary function to a single-precision floating-point strided input\n    array according to a strided mask array and assigns results to a single-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskmap.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0, base.identity )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskmap.ndarray( 2, x, 2, 1, m, 1, 2, y, -1, y.length-1, base.identity )\n    <Float32Array>[ 0.0, 0.0, 4.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmskmap, base.strided.mskunary, base.strided.smap, base.strided.smskmap2","base.strided.smskmap2":"\nbase.strided.smskmap2( N, x, sx, y, sy, m, sm, z, sz, fcn )\n    Applies a binary function to single-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a single-\n    precision floating-point strided output array.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    z: Float32Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float32Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.smskmap2( x.length, x, 1, y, 1, m, 1, z, 1, base.addf )\n    <Float32Array>[ 2.0, 4.0, 0.0, 8.0 ]\n\n    // Using `N` and stride parameters:\n    > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskmap2( 2, x, 2, y, -1, m, 2, z, -1, base.addf )\n    <Float32Array>[ 0.0, 3.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float32Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskmap2( 2, x1, -2, y1, 1, m1, 1, z1, 1, base.addf )\n    <Float32Array>[ 0.0, 6.0 ]\n    > z0\n    <Float32Array>[ 0.0, 0.0, 0.0, 6.0 ]\n\n\nbase.strided.smskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n    Applies a binary function to single-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a single-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    z: Float32Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float32Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.smskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.addf )\n    <Float32Array>[ 2.0, 4.0, 0.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.smskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.addf )\n    <Float32Array>[ 0.0, 0.0, 7.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmskmap2, base.strided.smap2, base.strided.smskmap\n","base.strided.smskmap2.ndarray":"\nbase.strided.smskmap2.ndarray( N, x, sx, ox, y, sy, oy, m, sm, om, z, sz, oz, fcn )\n    Applies a binary function to single-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a single-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    z: Float32Array\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    fcn: Function\n        Binary function to apply.\n\n    Returns\n    -------\n    z: Float32Array\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.smskmap2.ndarray( 4, x, 1, 0, y, 1, 0, m, 1, 0, z, 1, 0, base.addf )\n    <Float32Array>[ 2.0, 4.0, 0.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > y = new Float32Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.smskmap2.ndarray( 2, x, 2, 1, y, -1, 3, m, 1, 2, z, -1, 3, base.addf )\n    <Float32Array>[ 0.0, 0.0, 7.0, 0.0 ]\n\n    See Also\n    --------\n    base.strided.dmskmap2, base.strided.smap2, base.strided.smskmap","base.strided.smskmax":"\nbase.strided.smskmax( N, x, strideX, mask, strideMask )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.smskmax( x.length, x, 1, mask, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.smskmax( 3, x, 2, mask, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > base.strided.smskmax( 3, x1, 2, mask1, 2 )\n    2.0\n\n\nbase.strided.smskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.smskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmskmax, base.strided.mskmax, base.strided.smax, base.strided.smskmin, base.strided.snanmax, base.strided.snanmskmax\n","base.strided.smskmax.ndarray":"\nbase.strided.smskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.smskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.smskmax.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dmskmax, base.strided.mskmax, base.strided.smax, base.strided.smskmin, base.strided.snanmax, base.strided.snanmskmax","base.strided.smskmin":"\nbase.strided.smskmin( N, x, strideX, mask, strideMask )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.smskmin( x.length, x, 1, mask, 1 )\n    -2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.smskmin( 3, x, 2, mask, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > base.strided.smskmin( 3, x1, 2, mask1, 2 )\n    -2.0\n\n\nbase.strided.smskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.smskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmskmin, base.strided.mskmin, base.strided.smin, base.strided.smskmax, base.strided.snanmin, base.strided.snanmskmin\n","base.strided.smskmin.ndarray":"\nbase.strided.smskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.smskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.smskmin.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dmskmin, base.strided.mskmin, base.strided.smin, base.strided.smskmax, base.strided.snanmin, base.strided.snanmskmin","base.strided.smskramp":"\nbase.strided.smskramp( N, x, sx, m, sm, y, sy )\n    Evaluates the ramp function for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskramp( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskramp( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskramp( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ 4.0, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Evaluates the ramp function for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmskramp, base.strided.sramp\n","base.strided.smskramp.ndarray":"\nbase.strided.smskramp.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Evaluates the ramp function for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskramp.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskramp.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmskramp, base.strided.sramp","base.strided.smskrange":"\nbase.strided.smskrange( N, x, strideX, mask, strideMask )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > base.strided.smskrange( x.length, x, 1, mask, 1 )\n    4.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.smskrange( 3, x, 2, mask, 2 )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > base.strided.smskrange( 3, x1, 2, mask1, 2 )\n    4.0\n\n\nbase.strided.smskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.smskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dmskrange, base.strided.mskrange, base.strided.smskmax, base.strided.smskmin, base.strided.snanrange, base.strided.srange\n","base.strided.smskrange.ndarray":"\nbase.strided.smskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Stride Length for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0 ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1 ] );\n    > base.strided.smskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > base.strided.smskrange.ndarray( 3, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dmskrange, base.strided.mskrange, base.strided.smskmax, base.strided.smskmin, base.strided.snanrange, base.strided.srange","base.strided.smskrsqrt":"\nbase.strided.smskrsqrt( N, x, sx, m, sm, y, sy )\n    Computes the reciprocal square root for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskrsqrt( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ Infinity, 0.5, 0.0, ~0.289 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskrsqrt( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, Infinity, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smskrsqrt( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ ~0.289, 0.5 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.smskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the reciprocal square root for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ Infinity, 0.5, 0.0, ~0.289 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n    See Also\n    --------\n    base.strided.dmskrsqrt, base.strided.smsksqrt, base.strided.srsqrt\n","base.strided.smskrsqrt.ndarray":"\nbase.strided.smskrsqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the reciprocal square root for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskrsqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ Infinity, 0.5, 0.0, ~0.289 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smskrsqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n    See Also\n    --------\n    base.strided.dmskrsqrt, base.strided.smsksqrt, base.strided.srsqrt","base.strided.smsksqrt":"\nbase.strided.smsksqrt( N, x, sx, m, sm, y, sy )\n    Computes the principal square root for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsksqrt( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ 0.0, 2.0, 0.0, ~3.464 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsksqrt( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smsksqrt( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ ~3.464, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.smsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the principal square root for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, 2.0, 0.0, ~3.464 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmsksqrt, base.strided.smskcbrt, base.strided.smskrsqrt, base.strided.srsqrt\n","base.strided.smsksqrt.ndarray":"\nbase.strided.smsksqrt.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Computes the principal square root for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsksqrt.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, 2.0, 0.0, ~3.464 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsksqrt.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmsksqrt, base.strided.smskcbrt, base.strided.smskrsqrt, base.strided.srsqrt","base.strided.smsktrunc":"\nbase.strided.smsktrunc( N, x, sx, m, sm, y, sy )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward zero according to a strided mask array and assigns the results to\n    elements in a single-precision floating-point strided array `y`.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    m: Uint8Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsktrunc( x.length, x, 1, m, 1, y, 1 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsktrunc( 2, x, 2, m, 2, y, -1 )\n    <Float32Array>[ 0.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m0 = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var m1 = new Uint8Array( m0.buffer, m0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.smsktrunc( 2, x1, -2, m1, -2, y1, 1 )\n    <Float32Array>[ 4.0, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.smsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward zero according to a strided mask array and assigns the results to\n    elements in a single-precision floating-point strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmsktrunc, base.strided.smskceil, base.strided.smskfloor, base.strided.strunc\n","base.strided.smsktrunc.ndarray":"\nbase.strided.smsktrunc.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward zero according to a strided mask array and assigns the results to\n    elements in a single-precision floating-point strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    m: Float32Array\n        Mask array.\n\n    sm: integer\n        Index increment for `m`.\n\n    om: integer\n        Starting index for `m`.\n\n    y: Float32Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsktrunc.ndarray( x.length, x, 1, 0, m, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > m = new Uint8Array( [ 0, 0, 1, 0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.smsktrunc.ndarray( 2, x, 2, 1, m, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dmsktrunc, base.strided.smskceil, base.strided.smskfloor, base.strided.strunc","base.strided.snanmax":"\nbase.strided.snanmax( N, x, strideX )\n    Computes the maximum value of a single-precision floating-point strided\n    array, ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmax( x.length, x, 1 )\n    2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > base.strided.snanmax( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.snanmax( 3, x1, 2 )\n    2.0\n\n\nbase.strided.snanmax.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a single-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.snanmax.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.snanmax.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmax, base.strided.nanmax, base.strided.smax, base.strided.snanmin\n","base.strided.snanmax.ndarray":"\nbase.strided.snanmax.ndarray( N, x, strideX, offsetX )\n    Computes the maximum value of a single-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.snanmax.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.snanmax.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmax, base.strided.nanmax, base.strided.smax, base.strided.snanmin","base.strided.snanmaxabs":"\nbase.strided.snanmaxabs( N, x, strideX )\n    Computes the maximum absolute value of a single-precision floating-point\n    strided array, ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmaxabs( x.length, x, 1 )\n    2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > base.strided.snanmaxabs( 3, x, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.snanmaxabs( 3, x1, 2 )\n    2.0\n\n\nbase.strided.snanmaxabs.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a single-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.snanmaxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.snanmaxabs.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmaxabs, base.strided.nanmaxabs, base.strided.smaxabs, base.strided.snanmax, base.strided.snanminabs\n","base.strided.snanmaxabs.ndarray":"\nbase.strided.snanmaxabs.ndarray( N, x, strideX, offsetX )\n    Computes the maximum absolute value of a single-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Maximum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.snanmaxabs.ndarray( x.length, x, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.snanmaxabs.ndarray( 3, x, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmaxabs, base.strided.nanmaxabs, base.strided.smaxabs, base.strided.snanmax, base.strided.snanminabs","base.strided.snanmean":"\nbase.strided.snanmean( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmean( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.snanmean( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.snanmean( N, x1, stride )\n    ~-0.3333\n\nbase.strided.snanmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.smean, base.strided.nanmean\n","base.strided.snanmean.ndarray":"\nbase.strided.snanmean.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmean.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmean.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmean, base.strided.smean, base.strided.nanmean","base.strided.snanmeanors":"\nbase.strided.snanmeanors( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmeanors( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.snanmeanors( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.snanmeanors( N, x1, stride )\n    ~-0.3333\n\nbase.strided.snanmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanors, base.strided.nanmeanors, base.strided.smeanors, base.strided.snanmean\n","base.strided.snanmeanors.ndarray":"\nbase.strided.snanmeanors.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmeanors.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmeanors.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanors, base.strided.nanmeanors, base.strided.smeanors, base.strided.snanmean","base.strided.snanmeanpn":"\nbase.strided.snanmeanpn( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction\n    algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmeanpn( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.snanmeanpn( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.snanmeanpn( N, x1, stride )\n    ~-0.3333\n\nbase.strided.snanmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction algorithm\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanpn, base.strided.nanmeanpn, base.strided.smeanpn, base.strided.snanmean\n","base.strided.snanmeanpn.ndarray":"\nbase.strided.snanmeanpn.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction algorithm\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmeanpn.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmeanpn.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanpn, base.strided.nanmeanpn, base.strided.smeanpn, base.strided.snanmean","base.strided.snanmeanwd":"\nbase.strided.snanmeanwd( N, x, stride )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmeanwd( x.length, x, 1 )\n    ~0.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.snanmeanwd( N, x, stride )\n    ~0.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.snanmeanwd( N, x1, stride )\n    ~-0.3333\n\nbase.strided.snanmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanwd, base.strided.nanmeanwd, base.strided.smeanwd, base.strided.snanmean\n","base.strided.snanmeanwd.ndarray":"\nbase.strided.snanmeanwd.ndarray( N, x, stride, offset )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The arithmetic mean.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmeanwd.ndarray( x.length, x, 1, 0 )\n    ~0.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmeanwd.ndarray( N, x, 2, 1 )\n    ~-0.3333\n\n    See Also\n    --------\n    base.strided.dnanmeanwd, base.strided.nanmeanwd, base.strided.smeanwd, base.strided.snanmean","base.strided.snanmin":"\nbase.strided.snanmin( N, x, strideX )\n    Computes the minimum value of a single-precision floating-point strided\n    array, ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanmin( x.length, x, 1 )\n    -2.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > base.strided.snanmin( 3, x, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.snanmin( 3, x1, 2 )\n    -2.0\n\n\nbase.strided.snanmin.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a single-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.snanmin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.snanmin.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dnanmin, base.strided.nanmin, base.strided.smin, base.strided.snanmax\n","base.strided.snanmin.ndarray":"\nbase.strided.snanmin.ndarray( N, x, strideX, offsetX )\n    Computes the minimum value of a single-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.snanmin.ndarray( x.length, x, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.snanmin.ndarray( 3, x, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dnanmin, base.strided.nanmin, base.strided.smin, base.strided.snanmax","base.strided.snanminabs":"\nbase.strided.snanminabs( N, x, strideX )\n    Computes the minimum absolute value of a single-precision floating-point\n    strided array, ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanminabs( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > base.strided.snanminabs( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.snanminabs( 3, x1, 2 )\n    1.0\n\n\nbase.strided.snanminabs.ndarray( N, x, strideX, offsetX )\n    Computes the minimum absolute value of a single-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.snanminabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.snanminabs.ndarray( 3, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dnanminabs, base.strided.nanminabs, base.strided.sminabs, base.strided.snanmaxabs, base.strided.snanmin\n","base.strided.snanminabs.ndarray":"\nbase.strided.snanminabs.ndarray( N, x, strideX, offsetX )\n    Computes the minimum absolute value of a single-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Minimum absolute value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.snanminabs.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.snanminabs.ndarray( 3, x, 2, 1 )\n    1.0\n\n    See Also\n    --------\n    base.strided.dnanminabs, base.strided.nanminabs, base.strided.sminabs, base.strided.snanmaxabs, base.strided.snanmin","base.strided.snanmskmax":"\nbase.strided.snanmskmax( N, x, strideX, mask, strideMask )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n    > base.strided.snanmskmax( x.length, x, 1, mask, 1 )\n    2.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmskmax( N, x, 2, mask, 2 )\n    2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.snanmskmax( N, x1, 2, mask1, 2 )\n    2.0\n\nbase.strided.snanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.snanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmskmax, base.strided.nanmskmax, base.strided.smskmax, base.strided.snanmax, base.strided.snanmskmin\n","base.strided.snanmskmax.ndarray":"\nbase.strided.snanmskmax.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.snanmskmax.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    2.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmskmax.ndarray( N, x, 2, 1, mask, 2, 1 )\n    2.0\n\n    See Also\n    --------\n    base.strided.dnanmskmax, base.strided.nanmskmax, base.strided.smskmax, base.strided.snanmax, base.strided.snanmskmin","base.strided.snanmskmin":"\nbase.strided.snanmskmin( N, x, strideX, mask, strideMask )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, -4.0, 2.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n    > base.strided.snanmskmin( x.length, x, 1, mask, 1 )\n    -2.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmskmin( N, x, 2, mask, 2 )\n    -2.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.snanmskmin( N, x1, 2, mask1, 2 )\n    -2.0\n\nbase.strided.snanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.snanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dnanmskmin, base.strided.nanmskmin, base.strided.smskmin, base.strided.snanmin, base.strided.snanmskmax\n","base.strided.snanmskmin.ndarray":"\nbase.strided.snanmskmin.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, -4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.snanmskmin.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    -2.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, -4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmskmin.ndarray( N, x, 2, 1, mask, 2, 1 )\n    -2.0\n\n    See Also\n    --------\n    base.strided.dnanmskmin, base.strided.nanmskmin, base.strided.smskmin, base.strided.snanmin, base.strided.snanmskmax","base.strided.snanmskrange":"\nbase.strided.snanmskrange( N, x, strideX, mask, strideMask )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask, ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements are accessed at\n    runtime.\n\n    Indexing is relative to the first index. To introduce offsets, use a typed\n    array views.\n\n    If a `mask` array element is `0`, the corresponding element in `x` is\n    considered valid and included in computation.\n\n    If a `mask` array element is `1`, the corresponding element in `x` is\n    considered invalid/missing and excluded from computation.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );\n    > base.strided.snanmskrange( x.length, x, 1, mask, 1 )\n    4.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmskrange( N, x, 2, mask, 2 )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.snanmskrange( N, x1, 2, mask1, 2 )\n    4.0\n\nbase.strided.snanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.snanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dnanmskrange, base.strided.nanmskrange, base.strided.smskrange, base.strided.snanrange, base.strided.snanmskmax, base.strided.snanmskmin\n","base.strided.snanmskrange.ndarray":"\nbase.strided.snanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask, ignoring `NaN` values and using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    mask: Uint8Array\n        Mask array.\n\n    strideMask: integer\n        Index increment for `mask`.\n\n    offsetMask: integer\n        Starting index for `mask`.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, 4.0, NaN ] );\n    > var mask = new Uint8Array( [ 0, 0, 0, 1, 0 ] );\n    > base.strided.snanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, 4.0 ] );\n    > mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dnanmskrange, base.strided.nanmskrange, base.strided.smskrange, base.strided.snanrange, base.strided.snanmskmax, base.strided.snanmskmin","base.strided.snanrange":"\nbase.strided.snanrange( N, x, strideX )\n    Computes the range of a single-precision floating-point strided array,\n    ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanrange( x.length, x, 1 )\n    4.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN ] );\n    > base.strided.snanrange( 3, x, 2 )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.snanrange( 3, x1, 2 )\n    4.0\n\n\nbase.strided.snanrange.ndarray( N, x, strideX, offsetX )\n    Computes the range of a single-precision floating-point strided array,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.snanrange.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.snanrange.ndarray( 3, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dnanrange, base.strided.nanrange, base.strided.snanmax, base.strided.snanmin, base.strided.srange\n","base.strided.snanrange.ndarray":"\nbase.strided.snanrange.ndarray( N, x, strideX, offsetX )\n    Computes the range of a single-precision floating-point strided array,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0, NaN ] );\n    > base.strided.snanrange.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN ] );\n    > base.strided.snanrange.ndarray( 3, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.dnanrange, base.strided.nanrange, base.strided.snanmax, base.strided.snanmin, base.strided.srange","base.strided.snanstdev":"\nbase.strided.snanstdev( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdev( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.snanstdev( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.snanstdev( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.snanstdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.nanstdev, base.strided.snanvariance, base.strided.sstdev\n","base.strided.snanstdev.ndarray":"\nbase.strided.snanstdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdev, base.strided.nanstdev, base.strided.snanvariance, base.strided.sstdev","base.strided.snanstdevch":"\nbase.strided.snanstdevch( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevch( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.snanstdevch( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.snanstdevch( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.snanstdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevch, base.strided.nanstdevch, base.strided.snanstdev, base.strided.snanvariancech, base.strided.sstdevch\n","base.strided.snanstdevch.ndarray":"\nbase.strided.snanstdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevch, base.strided.nanstdevch, base.strided.snanstdev, base.strided.snanvariancech, base.strided.sstdevch","base.strided.snanstdevpn":"\nbase.strided.snanstdevpn( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevpn( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.snanstdevpn( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.snanstdevpn( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.snanstdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevpn, base.strided.nanstdevpn, base.strided.snanstdev, base.strided.snanvariancepn, base.strided.sstdevpn\n","base.strided.snanstdevpn.ndarray":"\nbase.strided.snanstdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevpn, base.strided.nanstdevpn, base.strided.snanstdev, base.strided.snanvariancepn, base.strided.sstdevpn","base.strided.snanstdevtk":"\nbase.strided.snanstdevtk( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevtk( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.snanstdevtk( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.snanstdevtk( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.snanstdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevtk, base.strided.nanstdevtk, base.strided.snanstdev, base.strided.snanvariancetk, base.strided.sstdevtk\n","base.strided.snanstdevtk.ndarray":"\nbase.strided.snanstdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevtk, base.strided.nanstdevtk, base.strided.snanstdev, base.strided.snanvariancetk, base.strided.sstdevtk","base.strided.snanstdevwd":"\nbase.strided.snanstdevwd( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevwd( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.snanstdevwd( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.snanstdevwd( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.snanstdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevwd, base.strided.nanstdevwd, base.strided.snanstdev, base.strided.snanvariancewd, base.strided.sstdevwd\n","base.strided.snanstdevwd.ndarray":"\nbase.strided.snanstdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevwd, base.strided.nanstdevwd, base.strided.snanstdev, base.strided.snanvariancewd, base.strided.sstdevwd","base.strided.snanstdevyc":"\nbase.strided.snanstdevyc( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass algorithm proposed by\n    Youngs and Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevyc( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.snanstdevyc( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.snanstdevyc( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.snanstdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass algorithm proposed by\n    Youngs and Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevyc, base.strided.nanstdevyc, base.strided.snanstdev, base.strided.snanvarianceyc, base.strided.sstdevyc\n","base.strided.snanstdevyc.ndarray":"\nbase.strided.snanstdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass algorithm proposed by\n    Youngs and Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanstdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanstdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dnanstdevyc, base.strided.nanstdevyc, base.strided.snanstdev, base.strided.snanvarianceyc, base.strided.sstdevyc","base.strided.snansum":"\nbase.strided.snansum( N, x, stride )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansum( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.snansum( 4, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.snansum( 4, x1, 2 )\n    -1.0\n\n\nbase.strided.snansum.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.snansum.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.gnansum, base.strided.snanmean, base.strided.ssum\n","base.strided.snansum.ndarray":"\nbase.strided.snansum.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.snansum.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansum, base.strided.gnansum, base.strided.snanmean, base.strided.ssum","base.strided.snansumkbn":"\nbase.strided.snansumkbn( N, x, stride )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n\n    The `N` and stride parameters determine which elements in the strided \n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, \n    use a typed array view. \n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumkbn( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > var stride = 2;\n    > base.strided.snansumkbn( 4, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > stride = 2;\n    > base.strided.snansumkbn( 4, x1, stride )\n    -1.0\n\n\nbase.strided.snansumkbn.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.snansumkbn.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn, base.strided.gnansumkbn, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn\n","base.strided.snansumkbn.ndarray":"\nbase.strided.snansumkbn.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.snansumkbn.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn, base.strided.gnansumkbn, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn","base.strided.snansumkbn2":"\nbase.strided.snansumkbn2( N, x, stride )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset,\n    use a typed array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumkbn2( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > var stride = 2;\n    > base.strided.snansumkbn2( 4, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > stride = 2;\n    > base.strided.snansumkbn2( 4, x1, stride )\n    -1.0\n\n\nbase.strided.snansumkbn2.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.snansumkbn2.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn2, base.strided.gnansumkbn2, base.strided.snansum, base.strided.snansumkbn, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn2\n","base.strided.snansumkbn2.ndarray":"\nbase.strided.snansumkbn2.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.snansumkbn2.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumkbn2, base.strided.gnansumkbn2, base.strided.snansum, base.strided.snansumkbn, base.strided.snansumors, base.strided.snansumpw, base.strided.ssumkbn2","base.strided.snansumors":"\nbase.strided.snansumors( N, x, strideX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumors( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > var stride = 2;\n    > base.strided.snansumors( 4, x, stride )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > stride = 2;\n    > base.strided.snansumors( 4, x1, stride )\n    -1.0\n\n\nbase.strided.snansumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.snansumors.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumors, base.strided.gnansumors, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumpw, base.strided.ssumors\n","base.strided.snansumors.ndarray":"\nbase.strided.snansumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.snansumors.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumors, base.strided.gnansumors, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumpw, base.strided.ssumors","base.strided.snansumpw":"\nbase.strided.snansumpw( N, x, strideX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumpw( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0, NaN, NaN ] );\n    > base.strided.snansumpw( 4, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.snansumpw( 4, x1, 2 )\n    -1.0\n\n\nbase.strided.snansumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.snansumpw.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumpw, base.strided.gnansumpw, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.ssumpw\n","base.strided.snansumpw.ndarray":"\nbase.strided.snansumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snansumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0, NaN, NaN ] );\n    > base.strided.snansumpw.ndarray( 4, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dnansumpw, base.strided.gnansumpw, base.strided.snansum, base.strided.snansumkbn2, base.strided.snansumors, base.strided.ssumpw","base.strided.snanvariance":"\nbase.strided.snanvariance( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariance( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariance( N, 1, x, 2 )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.snanvariance( N, 1, x1, 2 )\n    ~4.3333\n\nbase.strided.snanvariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariance, base.strided.nanvariance, base.strided.snanstdev, base.strided.svariance\n","base.strided.snanvariance.ndarray":"\nbase.strided.snanvariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariance, base.strided.nanvariance, base.strided.snanstdev, base.strided.svariance","base.strided.snanvariancech":"\nbase.strided.snanvariancech( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancech( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancech( N, 1, x, 2 )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.snanvariancech( N, 1, x1, 2 )\n    ~4.3333\n\nbase.strided.snanvariancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancech, base.strided.nanvariancech, base.strided.snanstdevch, base.strided.snanvariance, base.strided.svariancech\n","base.strided.snanvariancech.ndarray":"\nbase.strided.snanvariancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancech, base.strided.nanvariancech, base.strided.snanstdevch, base.strided.snanvariance, base.strided.svariancech","base.strided.snanvariancepn":"\nbase.strided.snanvariancepn( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancepn( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancepn( N, 1, x, 2 )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.snanvariancepn( N, 1, x1, 2 )\n    ~4.3333\n\nbase.strided.snanvariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancepn, base.strided.nanvariancepn, base.strided.snanstdevpn, base.strided.snanvariance, base.strided.svariancepn\n","base.strided.snanvariancepn.ndarray":"\nbase.strided.snanvariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancepn, base.strided.nanvariancepn, base.strided.snanstdevpn, base.strided.snanvariance, base.strided.svariancepn","base.strided.snanvariancetk":"\nbase.strided.snanvariancetk( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancetk( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancetk( N, 1, x, 2 )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.snanvariancetk( N, 1, x1, 2 )\n    ~4.3333\n\nbase.strided.snanvariancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancetk, base.strided.nanvariancetk, base.strided.snanstdevtk, base.strided.snanvariance, base.strided.svariancetk\n","base.strided.snanvariancetk.ndarray":"\nbase.strided.snanvariancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancetk, base.strided.nanvariancetk, base.strided.snanstdevtk, base.strided.snanvariance, base.strided.svariancetk","base.strided.snanvariancewd":"\nbase.strided.snanvariancewd( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancewd( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancewd( N, 1, x, 2 )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.snanvariancewd( N, 1, x1, 2 )\n    ~4.3333\n\nbase.strided.snanvariancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using Welford's algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancewd, base.strided.nanvariancewd, base.strided.snanstdevwd, base.strided.snanvariance, base.strided.svariancewd\n","base.strided.snanvariancewd.ndarray":"\nbase.strided.snanvariancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using Welford's algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvariancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvariancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvariancewd, base.strided.nanvariancewd, base.strided.snanstdevwd, base.strided.snanvariance, base.strided.svariancewd","base.strided.snanvarianceyc":"\nbase.strided.snanvarianceyc( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n    Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    If every indexed element is `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvarianceyc( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvarianceyc( N, 1, x, 2 )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.snanvarianceyc( N, 1, x1, 2 )\n    ~4.3333\n\nbase.strided.snanvarianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n    Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvarianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvarianceyc, base.strided.nanvarianceyc, base.strided.snanstdevyc, base.strided.snanvariance, base.strided.svarianceyc\n","base.strided.snanvarianceyc.ndarray":"\nbase.strided.snanvarianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n    Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `n - c` where `c` corresponds to the\n        provided degrees of freedom adjustment and `n` corresponds to the number\n        of non-`NaN` indexed elements. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );\n    > base.strided.snanvarianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.snanvarianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dnanvarianceyc, base.strided.nanvarianceyc, base.strided.snanstdevyc, base.strided.snanvariance, base.strided.svarianceyc","base.strided.snrm2":"\nbase.strided.snrm2( N, x, stride )\n    Computes the L2-norm of a single-precision floating-point vector.\n\n    The `N` and `stride` parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0` the function returns `0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: float\n        The L2-norm.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.snrm2( x.length, x, 1 )\n    3.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.snrm2( 3, x, 2 )\n    3.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.snrm2( 3, x1, 2 )\n    3.0\n\n\nbase.strided.snrm2.ndarray( N, x, stride, offset )\n    Computes the L2-norm of a single-precision floating-point vector using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The L2-norm.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.snrm2.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.snrm2.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dnrm2, base.strided.gnrm2\n","base.strided.snrm2.ndarray":"\nbase.strided.snrm2.ndarray( N, x, stride, offset )\n    Computes the L2-norm of a single-precision floating-point vector using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: float\n        The L2-norm.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.snrm2.ndarray( x.length, x, 1, 0 )\n    3.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.snrm2.ndarray( 3, x, 2, 1 )\n    3.0\n\n    See Also\n    --------\n    base.strided.dnrm2, base.strided.gnrm2","base.strided.sramp":"\nbase.strided.sramp( N, x, strideX, y, strideY )\n    Evaluates the ramp function for each element in a single-precision floating-\n    point strided array `x` and assigns the results to elements in a single-\n    precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sramp( x.length, x, 1, y, 1 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sramp( N, x, 2, y, -1 )\n    <Float32Array>[ 0.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.sramp( N, x1, -2, y1, 1 )\n    <Float32Array>[ 4.0, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.sramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Evaluates the ramp function for each element in a single-precision floating-\n    point strided array `x` and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dramp, strided.ramp\n","base.strided.sramp.ndarray":"\nbase.strided.sramp.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Evaluates the ramp function for each element in a single-precision floating-\n    point strided array `x` and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.sramp.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, -3.0, 4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sramp.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dramp, strided.ramp","base.strided.srange":"\nbase.strided.srange( N, x, strideX )\n    Computes the range of a single-precision floating-point strided array.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.srange( x.length, x, 1 )\n    4.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.srange( 3, x, 2 )\n    4.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.srange( 3, x1, 2 )\n    4.0\n\n\nbase.strided.srange.ndarray( N, x, strideX, offsetX )\n    Computes the range of a single-precision floating-point strided array using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.srange.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.srange.ndarray( 3, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.drange, base.strided.smax, base.strided.smin, base.strided.snanrange, base.strided.range\n","base.strided.srange.ndarray":"\nbase.strided.srange.ndarray( N, x, strideX, offsetX )\n    Computes the range of a single-precision floating-point strided array using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride Length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Range.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.srange.ndarray( x.length, x, 1, 0 )\n    4.0\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.srange.ndarray( 3, x, 2, 1 )\n    4.0\n\n    See Also\n    --------\n    base.strided.drange, base.strided.smax, base.strided.smin, base.strided.snanrange, base.strided.range","base.strided.srev":"\nbase.strided.srev( N, x, stride )\n    Reverses a single-precision floating-point strided array in-place.\n\n    The `N` and `stride` parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.srev( x.length, x, 1 )\n    <Float32Array>[ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.srev( 3, x, 2 )\n    <Float32Array>[ 4.0, 1.0, 3.0, -5.0, -2.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.srev( 3, x1, 2 )\n    <Float32Array>[ -6.0, 3.0, -4.0, 5.0, -2.0 ]\n    > x0\n    <Float32Array>[ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n\nbase.strided.srev.ndarray( N, x, stride, offset )\n    Reverses a single-precision floating-point strided array in-place using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.srev.ndarray( x.length, x, 1, 0 )\n    <Float32Array>[ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.srev.ndarray( 3, x, 2, 1 )\n    <Float32Array>[ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.drev, base.strided.grev\n","base.strided.srev.ndarray":"\nbase.strided.srev.ndarray( N, x, stride, offset )\n    Reverses a single-precision floating-point strided array in-place using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.srev.ndarray( x.length, x, 1, 0 )\n    <Float32Array>[ -3.0, -1.0, 4.0, -5.0, 3.0, 1.0, -2.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.srev.ndarray( 3, x, 2, 1 )\n    <Float32Array>[ 1.0, -6.0, 3.0, -4.0, 5.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.drev, base.strided.grev","base.strided.srsqrt":"\nbase.strided.srsqrt( N, x, strideX, y, strideY )\n    Computes the reciprocal square root for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.srsqrt( x.length, x, 1, y, 1 )\n    <Float32Array>[ 1.0, 0.5, ~0.333, ~0.289 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.srsqrt( N, x, 2, y, -1 )\n    <Float32Array>[ ~0.333, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.srsqrt( N, x1, -2, y1, 1 )\n    <Float32Array>[ ~0.289, 0.5 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nbase.strided.srsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the reciprocal square root for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.srsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 0.5, ~0.333, ~0.289 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.srsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n    See Also\n    --------\n    base.strided.drsqrt, strided.rsqrt, base.strided.ssqrt\n","base.strided.srsqrt.ndarray":"\nbase.strided.srsqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the reciprocal square root for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.srsqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 0.5, ~0.333, ~0.289 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.srsqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n    See Also\n    --------\n    base.strided.drsqrt, strided.rsqrt, base.strided.ssqrt","base.strided.sscal":"\nbase.strided.sscal( N, alpha, x, stride )\n    Multiplies a single-precision floating-point vector `x` by a constant\n    `alpha`.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0`, the function returns `x` unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sscal( x.length, 5.0, x, 1 )\n    <Float32Array>[ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sscal( 3, 5.0, x, 2 )\n    <Float32Array>[ -10.0, 1.0, 15.0, -5.0, 20.0, -1.0, -3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.sscal( 3, 5.0, x1, 2 )\n    <Float32Array>[ -10.0, 3.0, -20.0, 5.0, -30.0 ]\n    > x0\n    <Float32Array>[ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n\nbase.strided.sscal.ndarray( N, alpha, x, stride, offset )\n    Multiplies a single-precision floating-point vector `x` by a constant\n    `alpha` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sscal.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float32Array>[ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.sscal.ndarray( 3, 5.0, x, 2, 1 )\n    <Float32Array>[ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n    See Also\n    --------\n    base.strided.daxpy, base.strided.dscal, base.strided.gscal, base.strided.saxpy\n","base.strided.sscal.ndarray":"\nbase.strided.sscal.ndarray( N, alpha, x, stride, offset )\n    Multiplies a single-precision floating-point vector `x` by a constant\n    `alpha` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: number\n        Constant.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ -2.0, 1.0, 3.0, -5.0, 4.0, -1.0, -3.0 ] );\n    > base.strided.sscal.ndarray( x.length, 5.0, x, 1, 0 )\n    <Float32Array>[ -10.0, 5.0, 15.0, -25.0, 20.0, -5.0, -15.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );\n    > base.strided.sscal.ndarray( 3, 5.0, x, 2, 1 )\n    <Float32Array>[ 1.0, -10.0, 3.0, -20.0, 5.0, -30.0 ]\n\n    See Also\n    --------\n    base.strided.daxpy, base.strided.dscal, base.strided.gscal, base.strided.saxpy","base.strided.ssort2hp":"\nbase.strided.ssort2hp( N, order, x, strideX, y, strideY )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using heapsort.\n\n    The `N` and `stride` parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided arrays are sorted *in-place* (i.e., the input strided\n    arrays are *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2hp( x.length, 1, x, 1, y, 1 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float32Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2hp( 2, -1, x, 2, y, 2 )\n    <Float32Array>[ 3.0, -2.0, 1.0, -4.0 ]\n    > y\n    <Float32Array>[ 2.0, 1.0, 0.0, 3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n    > base.strided.ssort2hp( 2, 1, x1, 2, y1, 2 )\n    <Float32Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.ssort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using heapsort and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float32Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2hp.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float32Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2hp, base.strided.gsort2hp, base.strided.ssorthp\n","base.strided.ssort2hp.ndarray":"\nbase.strided.ssort2hp.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using heapsort and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2hp.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float32Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2hp.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float32Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2hp, base.strided.gsort2hp, base.strided.ssorthp","base.strided.ssort2ins":"\nbase.strided.ssort2ins( N, order, x, strideX, y, strideY )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using insertion sort.\n\n    The `N` and stride parameters determine which elements in the strided\n    arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function leaves the strided arrays\n    are unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^2).\n\n    The algorithm is efficient for *small* strided arrays (typically N <= 20)\n    and is particularly efficient for sorting strided arrays which are already\n    substantially sorted.\n\n    The algorithm is *stable*, meaning that the algorithm does *not* change the\n    order of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided arrays are sorted *in-place* (i.e., the input strided\n    arrays is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    x: Float32Array\n        First input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2ins( x.length, 1, x, 1, y, 1 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float32Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2ins( 2, -1, x, 2, y, 2 )\n    <Float32Array>[ 3.0, -2.0, 1.0, -4.0 ]\n    > y\n    <Float32Array>[ 2.0, 1.0, 0.0, 3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n    > base.strided.ssort2ins( 2, 1, x1, 2, y1, 2 )\n    <Float32Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.ssort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using insertion sort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float32Array\n        First input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float32Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float32Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2ins, base.strided.gsort2ins, base.strided.ssortins\n","base.strided.ssort2ins.ndarray":"\nbase.strided.ssort2ins.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using insertion sort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float32Array\n        First input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2ins.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float32Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2ins.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float32Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2ins, base.strided.gsort2ins, base.strided.ssortins","base.strided.ssort2sh":"\nbase.strided.ssort2sh( N, order, x, strideX, y, strideY )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using Shellsort.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function leaves `x` and `y` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^(4/3)).\n\n    The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided arrays are sorted *in-place* (i.e., the input strided\n    arrays are *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2sh( x.length, 1, x, 1, y, 1 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float32Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2sh( 2, -1, x, 2, y, 2 )\n    <Float32Array>[ 3.0, -2.0, 1.0, -4.0 ]\n    > y\n    <Float32Array>[ 2.0, 1.0, 0.0, 3.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y0 = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*1 );\n    > base.strided.ssort2sh( 2, 1, x1, 2, y1, 2 )\n    <Float32Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n\nbase.strided.ssort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using Shellsort and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float32Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2sh.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float32Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2sh, base.strided.gsort2sh, base.strided.ssortsh\n","base.strided.ssort2sh.ndarray":"\nbase.strided.ssort2sh.ndarray( N, order, x, strideX, offsetX, y, strideY, offsetY )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using Shellsort and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a starting\n    index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index of `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index of `y`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2sh.ndarray( x.length, 1, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n    > y\n    <Float32Array>[ 3.0, 1.0, 0.0, 2.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > y = new Float32Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > base.strided.ssort2sh.ndarray( 2, 1, x, 2, 1, y, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n    > y\n    <Float32Array>[ 0.0, 3.0, 2.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dsort2sh, base.strided.gsort2sh, base.strided.ssortsh","base.strided.ssorthp":"\nbase.strided.ssorthp( N, order, x, stride )\n    Sorts a single-precision floating-point strided array using heapsort.\n\n    The `N` and stride parameters determine which elements in the strided\n    array are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function returns the strided\n    array unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and time complexity O(N log2 N).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided array is sorted *in-place* (i.e., the input strided array\n    is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts the strided array in\n        decreasing order. If `order > 0`, the function sorts the strided array\n        in increasing order.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for the strided array.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array the strided array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssorthp( x.length, 1, x, 1 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssorthp( 2, -1, x, 2 )\n    <Float32Array>[ 3.0, -2.0, 1.0, -4.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.ssorthp( 2, 1, x1, 2 )\n    <Float32Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.ssorthp.ndarray( N, order, x, stride, offset )\n    Sorts a single-precision floating-point strided array using heapsort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts the strided array in\n        decreasing order. If `order > 0`, the function sorts the strided array\n        in increasing order.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for the strided array.\n\n    offset: integer\n        Starting index of the strided array.\n\n    Returns\n    -------\n    x: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssorthp.ndarray( x.length, 1, x, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssorthp.ndarray( 2, 1, x, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsorthp, base.strided.gsorthp, base.strided.ssort2hp\n","base.strided.ssorthp.ndarray":"\nbase.strided.ssorthp.ndarray( N, order, x, stride, offset )\n    Sorts a single-precision floating-point strided array using heapsort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts the strided array in\n        decreasing order. If `order > 0`, the function sorts the strided array\n        in increasing order.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for the strided array.\n\n    offset: integer\n        Starting index of the strided array.\n\n    Returns\n    -------\n    x: Float32Array\n        Output array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssorthp.ndarray( x.length, 1, x, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssorthp.ndarray( 2, 1, x, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsorthp, base.strided.gsorthp, base.strided.ssort2hp","base.strided.ssortins":"\nbase.strided.ssortins( N, order, x, stride )\n    Sorts a single-precision floating-point strided array using insertion sort.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^2).\n\n    The algorithm is efficient for *small* strided arrays (typically N <= 20)\n    and is particularly efficient for sorting strided arrays which are already\n    substantially sorted.\n\n    The algorithm is *stable*, meaning that the algorithm does *not* change the\n    order of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided array is sorted *in-place* (i.e., the input strided array\n    is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortins( x.length, 1, x, 1 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortins( 2, -1, x, 2 )\n    <Float32Array>[ 3.0, -2.0, 1.0, -4.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.ssortins( 2, 1, x1, 2 )\n    <Float32Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.ssortins.ndarray( N, order, x, stride, offset )\n    Sorts a single-precision floating-point strided array using insertion sort\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortins.ndarray( x.length, 1, x, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortins.ndarray( 2, 1, x, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsortins, base.strided.gsortins, base.strided.ssort2ins\n","base.strided.ssortins.ndarray":"\nbase.strided.ssortins.ndarray( N, order, x, stride, offset )\n    Sorts a single-precision floating-point strided array using insertion sort\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortins.ndarray( x.length, 1, x, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortins.ndarray( 2, 1, x, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsortins, base.strided.gsortins, base.strided.ssort2ins","base.strided.ssortsh":"\nbase.strided.ssortsh( N, order, x, stride )\n    Sorts a single-precision floating-point strided array using Shellsort.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N <= 0` or `order == 0`, the function returns `x` unchanged.\n\n    The algorithm distinguishes between `-0` and `+0`. When sorted in increasing\n    order, `-0` is sorted before `+0`. When sorted in decreasing order, `-0` is\n    sorted after `+0`.\n\n    The algorithm sorts `NaN` values to the end. When sorted in increasing\n    order, `NaN` values are sorted last. When sorted in decreasing order, `NaN`\n    values are sorted first.\n\n    The algorithm has space complexity O(1) and worst case time complexity\n    O(N^(4/3)).\n\n    The algorithm is efficient for *shorter* strided arrays (typically N <= 50).\n\n    The algorithm is *unstable*, meaning that the algorithm may change the order\n    of strided array elements which are equal or equivalent (e.g., `NaN`\n    values).\n\n    The input strided array is sorted *in-place* (i.e., the input strided array\n    is *mutated*).\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortsh( x.length, 1, x, 1 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortsh( 2, -1, x, 2 )\n    <Float32Array>[ 3.0, -2.0, 1.0, -4.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.ssortsh( 2, 1, x1, 2 )\n    <Float32Array>[ -4.0, 3.0, -2.0 ]\n    > x0\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n\nbase.strided.ssortsh.ndarray( N, order, x, stride, offset )\n    Sorts a single-precision floating-point strided array using Shellsort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortsh.ndarray( x.length, 1, x, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortsh.ndarray( 2, 1, x, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsortsh, base.strided.gsortsh, base.strided.ssort2sh\n","base.strided.ssortsh.ndarray":"\nbase.strided.ssortsh.ndarray( N, order, x, stride, offset )\n    Sorts a single-precision floating-point strided array using Shellsort and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    order: number\n        Sort order. If `order < 0`, the function sorts `x` in decreasing order.\n        If `order > 0`, the function sorts `x` in increasing order.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment for `x`.\n\n    offset: integer\n        Starting index of `x`.\n\n    Returns\n    -------\n    x: Float32Array\n        Input array `x`.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortsh.ndarray( x.length, 1, x, 1, 0 )\n    <Float32Array>[ -4.0, -2.0, 1.0, 3.0 ]\n\n    // Using an index offset:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > base.strided.ssortsh.ndarray( 2, 1, x, 2, 1 )\n    <Float32Array>[ 1.0, -4.0, 3.0, -2.0 ]\n\n    See Also\n    --------\n    base.strided.dsortsh, base.strided.gsortsh, base.strided.ssort2sh","base.strided.ssqrt":"\nbase.strided.ssqrt( N, x, strideX, y, strideY )\n    Computes the principal square root for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.ssqrt( x.length, x, 1, y, 1 )\n    <Float32Array>[ 0.0, 2.0, 3.0, ~3.464 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.ssqrt( N, x, 2, y, -1 )\n    <Float32Array>[ 3.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.ssqrt( N, x1, -2, y1, 1 )\n    <Float32Array>[ ~3.464, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nbase.strided.ssqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the principal square root for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.ssqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, 2.0, 3.0, ~3.464 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.ssqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dsqrt, base.strided.scbrt, strided.sqrt, base.strided.srsqrt\n","base.strided.ssqrt.ndarray":"\nbase.strided.ssqrt.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Computes the principal square root for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.ssqrt.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 0.0, 2.0, 3.0, ~3.464 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.ssqrt.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dsqrt, base.strided.scbrt, strided.sqrt, base.strided.srsqrt","base.strided.sstdev":"\nbase.strided.sstdev( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdev( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sstdev( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sstdev( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.sstdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdev, base.strided.snanstdev, base.strided.stdev, base.strided.svariance\n","base.strided.sstdev.ndarray":"\nbase.strided.sstdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdev, base.strided.snanstdev, base.strided.stdev, base.strided.svariance","base.strided.sstdevch":"\nbase.strided.sstdevch( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevch( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sstdevch( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sstdevch( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.sstdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevch, base.strided.snanstdevch, base.strided.sstdev, base.strided.stdevch, base.strided.svariancech\n","base.strided.sstdevch.ndarray":"\nbase.strided.sstdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevch, base.strided.snanstdevch, base.strided.sstdev, base.strided.stdevch, base.strided.svariancech","base.strided.sstdevpn":"\nbase.strided.sstdevpn( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevpn( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sstdevpn( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sstdevpn( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.sstdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevpn, base.strided.snanstdevpn, base.strided.sstdev, base.strided.stdevpn, base.strided.svariancepn\n","base.strided.sstdevpn.ndarray":"\nbase.strided.sstdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevpn, base.strided.snanstdevpn, base.strided.sstdev, base.strided.stdevpn, base.strided.svariancepn","base.strided.sstdevtk":"\nbase.strided.sstdevtk( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevtk( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sstdevtk( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sstdevtk( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.sstdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass textbook algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevtk, base.strided.snanstdevtk, base.strided.sstdev, base.strided.stdevtk, base.strided.svariancetk\n","base.strided.sstdevtk.ndarray":"\nbase.strided.sstdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass textbook algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevtk, base.strided.snanstdevtk, base.strided.sstdev, base.strided.stdevtk, base.strided.svariancetk","base.strided.sstdevwd":"\nbase.strided.sstdevwd( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevwd( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sstdevwd( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sstdevwd( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.sstdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevwd, base.strided.snanstdevwd, base.strided.sstdev, base.strided.stdevwd, base.strided.svariancewd\n","base.strided.sstdevwd.ndarray":"\nbase.strided.sstdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevwd, base.strided.snanstdevwd, base.strided.sstdev, base.strided.stdevwd, base.strided.svariancewd","base.strided.sstdevyc":"\nbase.strided.sstdevyc( N, correction, x, stride )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevyc( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.sstdevyc( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.sstdevyc( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.sstdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevyc, base.strided.snanstdevyc, base.strided.sstdev, base.strided.stdevyc, base.strided.svarianceyc\n","base.strided.sstdevyc.ndarray":"\nbase.strided.sstdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.sstdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.sstdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevyc, base.strided.snanstdevyc, base.strided.sstdev, base.strided.stdevyc, base.strided.svarianceyc","base.strided.ssum":"\nbase.strided.ssum( N, x, stride )\n    Computes the sum of single-precision floating-point strided array elements.\n\n    The `N` and `stride` parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssum( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.ssum( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.ssum( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.ssum.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.ssum.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsum, base.strided.smean, base.strided.snansum, base.strided.gsum\n","base.strided.ssum.ndarray":"\nbase.strided.ssum.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssum.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.ssum.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsum, base.strided.smean, base.strided.snansum, base.strided.gsum","base.strided.ssumkbn":"\nbase.strided.ssumkbn( N, x, stride )\n    Computes the sum of single-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumkbn( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.ssumkbn( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.ssumkbn( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.ssumkbn.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.ssumkbn.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumkbn, base.strided.gsumkbn, base.strided.snansumkbn, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors, base.strided.ssumpw\n","base.strided.ssumkbn.ndarray":"\nbase.strided.ssumkbn.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumkbn.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.ssumkbn.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumkbn, base.strided.gsumkbn, base.strided.snansumkbn, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors, base.strided.ssumpw","base.strided.ssumkbn2":"\nbase.strided.ssumkbn2( N, x, stride )\n    Computes the sum of single-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm.\n\n    The `N` and `stride` parameters determine which elements in  the strided\n    array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumkbn2( x.length, x, 1 )\n    1.0\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.ssumkbn2( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.ssumkbn2( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.ssumkbn2.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.ssumkbn2.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumkbn2, base.strided.gsumkbn2, base.strided.snansumkbn2, base.strided.ssum, base.strided.ssumkbn, base.strided.ssumors, base.strided.ssumpw\n","base.strided.ssumkbn2.ndarray":"\nbase.strided.ssumkbn2.ndarray( N, x, stride, offset )\n    Computes the sum of single-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumkbn2.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.ssumkbn2.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumkbn2, base.strided.gsumkbn2, base.strided.snansumkbn2, base.strided.ssum, base.strided.ssumkbn, base.strided.ssumors, base.strided.ssumpw","base.strided.ssumors":"\nbase.strided.ssumors( N, x, strideX )\n    Computes the sum of single-precision floating-point strided array elements\n    using ordinary recursive summation.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumors( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.ssumors( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.ssumors( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.ssumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements\n    using ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.ssumors.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumors, base.strided.gsumors, base.strided.snansumors, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumpw\n","base.strided.ssumors.ndarray":"\nbase.strided.ssumors.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements\n    using ordinary recursive summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumors.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.ssumors.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumors, base.strided.gsumors, base.strided.snansumors, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumpw","base.strided.ssumpw":"\nbase.strided.ssumpw( N, x, strideX )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation.\n\n    The `N` and stride parameters determine which elements in the strided array\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `0.0`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumpw( x.length, x, 1 )\n    1.0\n\n    // Using `N` and stride parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > base.strided.ssumpw( 3, x, 2 )\n    1.0\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > base.strided.ssumpw( 3, x1, 2 )\n    -1.0\n\n\nbase.strided.ssumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.ssumpw.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumpw, base.strided.gsumpw, base.strided.snansumpw, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors\n","base.strided.ssumpw.ndarray":"\nbase.strided.ssumpw.ndarray( N, x, strideX, offsetX )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Stride length.\n\n    offsetX: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        Sum.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.ssumpw.ndarray( x.length, x, 1, 0 )\n    1.0\n\n    // Using offset parameter:\n    > x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > base.strided.ssumpw.ndarray( 3, x, 2, 1 )\n    -1.0\n\n    See Also\n    --------\n    base.strided.dsumpw, base.strided.gsumpw, base.strided.snansumpw, base.strided.ssum, base.strided.ssumkbn2, base.strided.ssumors","base.strided.sswap":"\nbase.strided.sswap( N, x, strideX, y, strideY )\n    Interchanges two single-precision floating-point vectors.\n\n    The `N` and stride parameters determine how values from `x` are swapped\n    with values from `y`.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the vectors are unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Second input array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.sswap( x.length, x, 1, y, 1 )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.sswap( 3, x, -2, y, 1 )\n    <Float32Array>[ 5.0, 3.0, 1.0, 10.0, 11.0, 12.0 ]\n\n    // Using typed array views:\n    > var x0 = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > var y0 = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 );\n    > base.strided.sswap( 3, x1, -2, y1, 1 )\n    <Float32Array>[ 6.0, 4.0, 2.0 ]\n    > y0\n    <Float32Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n\nbase.strided.sswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Interchanges two single-precision floating-point vectors using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Second input array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.sswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.sswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dswap, base.strided.gswap, base.strided.scopy, sswap\n","base.strided.sswap.ndarray":"\nbase.strided.sswap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Interchanges two single-precision floating-point vectors using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        First input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Second input array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Second input array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );\n    > var y = new Float32Array( [ 6.0, 7.0, 8.0, 9.0, 10.0 ] );\n    > base.strided.sswap.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );\n    > y = new Float32Array( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );\n    > base.strided.sswap.ndarray( 3, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 7.0, 8.0, 9.0, 6.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dswap, base.strided.gswap, base.strided.scopy, sswap","base.strided.stdev":"\nbase.strided.stdev( N, correction, x, stride )\n    Computes the standard deviation of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdev( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.stdev( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.stdev( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.stdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdev, base.strided.nanstdev, base.strided.sstdev, base.strided.variance\n","base.strided.stdev.ndarray":"\nbase.strided.stdev.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdev.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdev.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdev, base.strided.nanstdev, base.strided.sstdev, base.strided.variance","base.strided.stdevch":"\nbase.strided.stdevch( N, correction, x, stride )\n    Computes the standard deviation of a strided array using a one-pass trial\n    mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevch( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.stdevch( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.stdevch( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.stdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using a one-pass trial\n    mean algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevch, base.strided.nanstdevch, base.strided.sstdevch, base.strided.stdev, base.strided.variancech\n","base.strided.stdevch.ndarray":"\nbase.strided.stdevch.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using a one-pass trial\n    mean algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevch.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdevch.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevch, base.strided.nanstdevch, base.strided.sstdevch, base.strided.stdev, base.strided.variancech","base.strided.stdevpn":"\nbase.strided.stdevpn( N, correction, x, stride )\n    Computes the standard deviation of a strided array using a two-pass\n    algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevpn( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.stdevpn( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.stdevpn( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.stdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using a two-pass\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.sstdevpn, base.strided.stdev, base.strided.variancepn\n","base.strided.stdevpn.ndarray":"\nbase.strided.stdevpn.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using a two-pass\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevpn.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdevpn.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevpn, base.strided.nanstdevpn, base.strided.sstdevpn, base.strided.stdev, base.strided.variancepn","base.strided.stdevtk":"\nbase.strided.stdevtk( N, correction, x, stride )\n    Computes the standard deviation of a strided array using a one-pass textbook\n    algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevtk( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.stdevtk( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.stdevtk( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.stdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using a one-pass textbook\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.sstdevtk, base.strided.stdev, base.strided.variancetk\n","base.strided.stdevtk.ndarray":"\nbase.strided.stdevtk.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using a one-pass textbook\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevtk.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdevtk.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevtk, base.strided.nanstdevtk, base.strided.sstdevtk, base.strided.stdev, base.strided.variancetk","base.strided.stdevwd":"\nbase.strided.stdevwd( N, correction, x, stride )\n    Computes the standard deviation of a strided array using Welford's\n    algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevwd( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.stdevwd( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.stdevwd( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.stdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using Welford's algorithm\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.sstdevwd, base.strided.stdev, base.strided.variancewd\n","base.strided.stdevwd.ndarray":"\nbase.strided.stdevwd.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using Welford's algorithm\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevwd.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdevwd.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevwd, base.strided.nanstdevwd, base.strided.sstdevwd, base.strided.stdev, base.strided.variancewd","base.strided.stdevyc":"\nbase.strided.stdevyc( N, correction, x, stride )\n    Computes the standard deviation of a strided array using a one-pass\n    algorithm proposed by Youngs and Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevyc( x.length, 1, x, 1 )\n    ~2.0817\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.stdevyc( N, 1, x, stride )\n    ~2.0817\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.stdevyc( N, 1, x1, stride )\n    ~2.0817\n\nbase.strided.stdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using a one-pass\n    algorithm proposed by Youngs and Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.sstdevyc, base.strided.stdev, base.strided.varianceyc\n","base.strided.stdevyc.ndarray":"\nbase.strided.stdevyc.ndarray( N, correction, x, stride, offset )\n    Computes the standard deviation of a strided array using a one-pass\n    algorithm proposed by Youngs and Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the standard deviation according to `N - c` where `c` corresponds to\n        the provided degrees of freedom adjustment. When computing the standard\n        deviation of a population, setting this parameter to `0` is the standard\n        choice (i.e., the provided array contains data constituting an entire\n        population). When computing the corrected sample standard deviation,\n        setting this parameter to `1` is the standard choice (i.e., the provided\n        array contains data sampled from a larger population; this is commonly\n        referred to as Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The standard deviation.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.stdevyc.ndarray( x.length, 1, x, 1, 0 )\n    ~2.0817\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.stdevyc.ndarray( N, 1, x, 2, 1 )\n    ~2.0817\n\n    See Also\n    --------\n    base.strided.dstdevyc, base.strided.nanstdevyc, base.strided.sstdevyc, base.strided.stdev, base.strided.varianceyc","base.strided.strunc":"\nbase.strided.strunc( N, x, strideX, y, strideY )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward zero and assigns the results to elements in a single-precision\n    floating-point strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.strunc( x.length, x, 1, y, 1 )\n    <Float32Array>[ 1.0, 2.0, -3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > var N = base.floor( x.length / 2 );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.strunc( N, x, 2, y, -1 )\n    <Float32Array>[ -3.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y0 = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > N = base.floor( x0.length / 2 );\n    > base.strided.strunc( N, x1, -2, y1, 1 )\n    <Float32Array>[ 4.0, 2.0 ]\n    > y0\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nbase.strided.strunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward zero and assigns the results to elements in a single-precision\n    floating-point strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.strunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.strunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dtrunc, base.strided.sceil, base.strided.sfloor, strided.trunc\n","base.strided.strunc.ndarray":"\nbase.strided.strunc.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward zero and assigns the results to elements in a single-precision\n    floating-point strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float32Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Float32Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: Float32Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > base.strided.strunc.ndarray( x.length, x, 1, 0, y, 1, 0 )\n    <Float32Array>[ 1.0, 2.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float32Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.strunc.ndarray( N, x, 2, 1, y, -1, y.length-1 )\n    <Float32Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    base.strided.dtrunc, base.strided.sceil, base.strided.sfloor, strided.trunc","base.strided.svariance":"\nbase.strided.svariance( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariance( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.svariance( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.svariance( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.svariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariance, base.strided.snanvariance, base.strided.sstdev, base.strided.variance\n","base.strided.svariance.ndarray":"\nbase.strided.svariance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svariance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariance, base.strided.snanvariance, base.strided.sstdev, base.strided.variance","base.strided.svariancech":"\nbase.strided.svariancech( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass trial mean algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancech( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.svariancech( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.svariancech( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.svariancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass trial mean algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svariancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancech, base.strided.snanvariancech, base.strided.sstdevch, base.strided.svariance, base.strided.variancech\n","base.strided.svariancech.ndarray":"\nbase.strided.svariancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass trial mean algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svariancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancech, base.strided.snanvariancech, base.strided.sstdevch, base.strided.svariance, base.strided.variancech","base.strided.svariancepn":"\nbase.strided.svariancepn( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancepn( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.svariancepn( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.svariancepn( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.svariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancepn, base.strided.snanvariancepn, base.strided.sstdevpn, base.strided.svariance, base.strided.variancepn\n","base.strided.svariancepn.ndarray":"\nbase.strided.svariancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using a two-pass algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svariancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancepn, base.strided.snanvariancepn, base.strided.sstdevpn, base.strided.svariance, base.strided.variancepn","base.strided.svariancetk":"\nbase.strided.svariancetk( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass textbook algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancetk( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.svariancetk( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.svariancetk( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.svariancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass textbook algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svariancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancetk, base.strided.snanvariancetk, base.strided.sstdevtk, base.strided.svariance, base.strided.variancetk\n","base.strided.svariancetk.ndarray":"\nbase.strided.svariancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass textbook algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svariancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancetk, base.strided.snanvariancetk, base.strided.sstdevtk, base.strided.svariance, base.strided.variancetk","base.strided.svariancewd":"\nbase.strided.svariancewd( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancewd( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.svariancewd( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.svariancewd( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.svariancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svariancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancewd, base.strided.snanvariancewd, base.strided.sstdevwd, base.strided.svariance, base.strided.variancewd\n","base.strided.svariancewd.ndarray":"\nbase.strided.svariancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using Welford's algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svariancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svariancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancewd, base.strided.snanvariancewd, base.strided.sstdevwd, base.strided.svariance, base.strided.variancewd","base.strided.svarianceyc":"\nbase.strided.svarianceyc( N, correction, x, stride )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass algorithm proposed by Youngs and Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svarianceyc( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = new Float32Array( [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.svarianceyc( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.svarianceyc( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.svarianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass algorithm proposed by Youngs and Cramer and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svarianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svarianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvarianceyc, base.strided.snanvarianceyc, base.strided.sstdevyc, base.strided.svariance, base.strided.varianceyc\n","base.strided.svarianceyc.ndarray":"\nbase.strided.svarianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass algorithm proposed by Youngs and Cramer and alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Float32Array\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );\n    > base.strided.svarianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = new Float32Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var N = base.floor( x.length / 2 );\n    > base.strided.svarianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvarianceyc, base.strided.snanvarianceyc, base.strided.sstdevyc, base.strided.svariance, base.strided.varianceyc","base.strided.ternary":"\nbase.strided.ternary( arrays, shape, strides, fcn )\n    Applies a ternary callback to strided input array elements and assigns\n    results to elements in a strided output array.\n\n    The `shape` and `strides` parameters determine which elements in the strided\n    input and output arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing three strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    fcn: Function\n        Ternary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1, 1 ];\n    > function f( x, y, z ) { return x + y + z; };\n    > base.strided.ternary( [ x, y, z, w ], shape, strides, f );\n    > w\n    <Float64Array>[ 3.0, 6.0, 9.0, 12.0 ]\n\n\nbase.strided.ternary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a ternary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing three strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Ternary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1, 1 ];\n    > var offsets = [ 0, 0, 0, 0 ];\n    > function f( x, y, z ) { return x + y + z; };\n    > base.strided.ternary.ndarray( [ x, y, z, w ], shape, strides, offsets, f );\n    > w\n    <Float64Array>[ 3.0, 6.0, 9.0, 12.0 ]\n\n    See Also\n    --------\n    base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.unary\n","base.strided.ternary.ndarray":"\nbase.strided.ternary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a ternary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing three strided input arrays and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Ternary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var w = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1, 1, 1 ];\n    > var offsets = [ 0, 0, 0, 0 ];\n    > function f( x, y, z ) { return x + y + z; };\n    > base.strided.ternary.ndarray( [ x, y, z, w ], shape, strides, offsets, f );\n    > w\n    <Float64Array>[ 3.0, 6.0, 9.0, 12.0 ]\n\n    See Also\n    --------\n    base.strided.binary, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.unary","base.strided.unary":"\nbase.strided.unary( arrays, shape, strides, fcn )\n    Applies a unary callback to elements in a strided input array and assigns\n    results to elements in a strided output array.\n\n    The `shape` and `strides` parameters determine which elements in the strided\n    input and output arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided input array and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    fcn: Function\n        Unary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1 ];\n    > base.strided.unary( [ x, y ], shape, strides, base.abs );\n    > y\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n\nbase.strided.unary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a unary callback to elements in a strided input array and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided input array and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Unary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1 ];\n    > var offsets = [ 0, 0 ];\n    > base.strided.unary.ndarray( [ x, y ], shape, strides, offsets, base.abs );\n    > y\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    See Also\n    --------\n    base.strided.unary, base.strided.dmap, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap, base.strided.ternary\n","base.strided.unary.ndarray":"\nbase.strided.unary.ndarray( arrays, shape, strides, offsets, fcn )\n    Applies a unary callback to elements in a strided input array and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsets` parameter supports indexing semantics based on\n    starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided input array and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Unary callback.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var shape = [ x.length ];\n    > var strides = [ 1, 1 ];\n    > var offsets = [ 0, 0 ];\n    > base.strided.unary.ndarray( [ x, y ], shape, strides, offsets, base.abs );\n    > y\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    See Also\n    --------\n    base.strided.unary, base.strided.dmap, base.strided.nullary, base.strided.quaternary, base.strided.quinary, base.strided.smap, base.strided.ternary","base.strided.unaryBy":"\nbase.strided.unaryBy( arrays, shape, strides, fcn, clbk[, thisArg] )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array.\n\n    The shape and stride parameters determine which elements in the strided\n    input and output arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - indices: strided indices (offset + idx*stride).\n    - arrays: input and output arrays.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided input array and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    fcn: Function\n        Unary function to apply to callback return values.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > var sh = [ x.length ];\n    > var st = [ 1, 1 ];\n    > function clbk( v ) { return v * 2.0; };\n    > base.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\n    > y\n    [ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Using shape and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > sh = [ 2 ];\n    > st = [ 2, -1 ];\n    > base.strided.unaryBy( [ x, y ], sh, st, base.abs, clbk );\n    > y\n    [ 6.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > sh = [ 2 ];\n    > st = [ -2, 1 ];\n    > base.strided.unaryBy( [ x1, y1 ], sh, st, base.abs, clbk );\n    > y1\n    <Float64Array>[ 8.0, 4.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 8.0, 4.0 ]\n\n\nbase.strided.unaryBy.ndarray( arrays, shape, strides, offsets, fcn, clbk[, thisArg] )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offsest parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided input array and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Unary function to apply to callback return values.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > var sh = [ x.length ];\n    > var st = [ 1, 1 ];\n    > var o = [ 0, 0 ];\n    > function clbk( v ) { return v * 2.0; };\n    > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n    > y\n    [ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > sh = [ 2 ];\n    > st = [ 2, -1 ];\n    > o = [ 1, y.length-1 ];\n    > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n    > y\n    [ 0.0, 0.0, 8.0, 4.0 ]\n\n    See Also\n    --------\n    base.strided.mapBy, base.strided.unary\n","base.strided.unaryBy.ndarray":"\nbase.strided.unaryBy.ndarray( arrays, shape, strides, offsets, fcn, clbk[, thisArg] )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offsest parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    arrays: ArrayLikeObject<ArrayLikeObject>\n        Array-like object containing one strided input array and one strided\n        output array.\n\n    shape: ArrayLikeObject<integer>\n        Array-like object containing a single element, the number of indexed\n        elements.\n\n    strides: ArrayLikeObject<integer>\n        Array-like object containing the stride lengths for the strided input\n        and output arrays.\n\n    offsets: ArrayLikeObject<integer>\n        Array-like object containing the starting indices (i.e., index offsets)\n        for the strided input and output arrays.\n\n    fcn: Function\n        Unary function to apply to callback return values.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > var sh = [ x.length ];\n    > var st = [ 1, 1 ];\n    > var o = [ 0, 0 ];\n    > function clbk( v ) { return v * 2.0; };\n    > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n    > y\n    [ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > sh = [ 2 ];\n    > st = [ 2, -1 ];\n    > o = [ 1, y.length-1 ];\n    > base.strided.unaryBy.ndarray( [ x, y ], sh, st, o, base.abs, clbk );\n    > y\n    [ 0.0, 0.0, 8.0, 4.0 ]\n\n    See Also\n    --------\n    base.strided.mapBy, base.strided.unary","base.strided.unaryDtypeSignatures":"\nbase.strided.unaryDtypeSignatures( dtypes1, dtypes2[, options] )\n    Generates a list of unary interface signatures from strided array data\n    types.\n\n    The function returns a strided array having a stride length of two (i.e.,\n    every two elements define a unary interface signature).\n\n    For each signature (i.e., set of two consecutive non-overlapping strided\n    array elements), the first element is the input data type and the second\n    element is the return data type.\n\n    All signatures follow type promotion rules.\n\n    Parameters\n    ----------\n    dtypes1: ArrayLike<any>\n        List of supported data types for the input argument.\n\n    dtypes2: ArrayLike<any>\n        List of supported data types for the output argument.\n\n    options: Object (optional)\n        Options.\n\n    options.enums: boolean (optional)\n        Boolean flag indicating whether to return signatures as a list of data\n        type enumeration constants. Default: false.\n\n    Returns\n    -------\n    out: Array\n        Strided array containing unary interface signatures.\n\n    Examples\n    --------\n    > var dt = strided.dataTypes();\n    > var out = base.strided.unaryDtypeSignatures( dt, dt )\n    [...]\n\n    See Also\n    --------\n    base.strided.unarySignatureCallbacks\n","base.strided.unarySignatureCallbacks":"\nbase.strided.unarySignatureCallbacks( table, signatures )\n    Assigns callbacks to unary interfaces according to type promotion rules.\n\n    Parameters\n    ----------\n    table: Object\n        Object mapping callbacks to data types.\n\n    table.default: Function\n        Default callback.\n\n    table.complex64: Function\n        Callback to be invoked when input arrays promote to single-precision\n        complex floating-point numbers.\n\n    table.complex128: Function\n        Callback to be invoked when input arrays promote to double precision\n        complex floating-point numbers.\n\n    signatures: ArrayLike<any>\n        Strided array containing unary interface signatures.\n\n    Returns\n    -------\n    out: Array<Function>\n        List of callbacks, one per signature.\n\n    Examples\n    --------\n    > var dt = strided.dataTypes();\n    > var sigs = base.strided.unaryDtypeSignatures( dt, dt );\n    > var t = {\n    ...     'default': base.identity,\n    ...     'complex64': base.cidentityf,\n    ...     'complex128': base.cidentity\n    ... };\n    > var out = base.strided.unarySignatureCallbacks( t, sigs )\n    [...]\n\n    See Also\n    --------\n    base.strided.unaryDtypeSignatures\n","base.strided.variance":"\nbase.strided.variance( N, correction, x, stride )\n    Computes the variance of a strided array.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variance( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.variance( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.variance( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.variance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.variance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariance, base.strided.nanvariance, base.strided.stdev, base.strided.svariance\n","base.strided.variance.ndarray":"\nbase.strided.variance.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variance.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.variance.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariance, base.strided.nanvariance, base.strided.stdev, base.strided.svariance","base.strided.variancech":"\nbase.strided.variancech( N, correction, x, stride )\n    Computes the variance of a strided array using a one-pass trial mean\n    algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancech( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.variancech( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.variancech( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.variancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using a one-pass trial mean\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.variancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancech, base.strided.nanvariancech, base.strided.stdevch, base.strided.variance\n","base.strided.variancech.ndarray":"\nbase.strided.variancech.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using a one-pass trial mean\n    algorithm and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancech.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.variancech.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancech, base.strided.nanvariancech, base.strided.stdevch, base.strided.variance","base.strided.variancepn":"\nbase.strided.variancepn( N, correction, x, stride )\n    Computes the variance of a strided array using a two-pass algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancepn( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.variancepn( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.variancepn( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.variancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using a two-pass algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.variancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancepn, base.strided.nanvariancepn, base.strided.stdevpn, base.strided.variance\n","base.strided.variancepn.ndarray":"\nbase.strided.variancepn.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using a two-pass algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancepn.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.variancepn.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancepn, base.strided.nanvariancepn, base.strided.stdevpn, base.strided.variance","base.strided.variancetk":"\nbase.strided.variancetk( N, correction, x, stride )\n    Computes the variance of a strided array using a one-pass textbook\n    algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancetk( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.variancetk( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.variancetk( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.variancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using a one-pass textbook algorithm\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.variancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancetk, base.strided.nanvariancetk, base.strided.stdevtk, base.strided.variance\n","base.strided.variancetk.ndarray":"\nbase.strided.variancetk.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using a one-pass textbook algorithm\n    and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancetk.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.variancetk.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancetk, base.strided.nanvariancetk, base.strided.stdevtk, base.strided.variance","base.strided.variancewd":"\nbase.strided.variancewd( N, correction, x, stride )\n    Computes the variance of a strided array using Welford's algorithm.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancewd( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.variancewd( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.variancewd( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.variancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using Welford's algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.variancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancewd, base.strided.nanvariancewd, base.strided.stdevwd, base.strided.variance\n","base.strided.variancewd.ndarray":"\nbase.strided.variancewd.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using Welford's algorithm and\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.variancewd.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.variancewd.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvariancewd, base.strided.nanvariancewd, base.strided.stdevwd, base.strided.variance","base.strided.varianceyc":"\nbase.strided.varianceyc( N, correction, x, stride )\n    Computes the variance of a strided array using a one-pass algorithm proposed\n    by Youngs and Cramer.\n\n    The `N` and `stride` parameters determine which elements in `x` are accessed\n    at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use a typed\n    array view.\n\n    If `N <= 0`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.varianceyc( x.length, 1, x, 1 )\n    ~4.3333\n\n    // Using `N` and `stride` parameters:\n    > x = [ -2.0, 1.0, 1.0, -5.0, 2.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > var stride = 2;\n    > base.strided.varianceyc( N, 1, x, stride )\n    ~4.3333\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > N = base.floor( x0.length / 2 );\n    > stride = 2;\n    > base.strided.varianceyc( N, 1, x1, stride )\n    ~4.3333\n\nbase.strided.varianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using a one-pass algorithm proposed\n    by Youngs and Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.varianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.varianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvarianceyc, base.strided.nanvarianceyc, base.strided.stdevyc, base.strided.variance\n","base.strided.varianceyc.ndarray":"\nbase.strided.varianceyc.ndarray( N, correction, x, stride, offset )\n    Computes the variance of a strided array using a one-pass algorithm proposed\n    by Youngs and Cramer and alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offset` parameter supports indexing semantics based on a\n    starting index.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    correction: number\n        Degrees of freedom adjustment. Setting this parameter to a value other\n        than `0` has the effect of adjusting the divisor during the calculation\n        of the variance according to `N - c` where `c` corresponds to the\n        provided degrees of freedom adjustment. When computing the variance of a\n        population, setting this parameter to `0` is the standard choice (i.e.,\n        the provided array contains data constituting an entire population).\n        When computing the unbiased sample variance, setting this parameter to\n        `1` is the standard choice (i.e., the provided array contains data\n        sampled from a larger population; this is commonly referred to as\n        Bessel's correction).\n\n    x: Array<number>|TypedArray\n        Input array.\n\n    stride: integer\n        Index increment.\n\n    offset: integer\n        Starting index.\n\n    Returns\n    -------\n    out: number\n        The variance.\n\n    Examples\n    --------\n    // Standard Usage:\n    > var x = [ 1.0, -2.0, 2.0 ];\n    > base.strided.varianceyc.ndarray( x.length, 1, x, 1, 0 )\n    ~4.3333\n\n    // Using offset parameter:\n    > var x = [ 1.0, -2.0, 3.0, 2.0, 5.0, -1.0 ];\n    > var N = base.floor( x.length / 2 );\n    > base.strided.varianceyc.ndarray( N, 1, x, 2, 1 )\n    ~4.3333\n\n    See Also\n    --------\n    base.strided.dvarianceyc, base.strided.nanvarianceyc, base.strided.stdevyc, base.strided.variance","base.strided.zmap":"\nbase.strided.zmap( N, x, strideX, y, strideY, fcn )\n    Applies a unary function to a double-precision complex floating-point\n    strided input array and assigns results to a double-precision complex\n    floating-point strided output array.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex128Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    y: Complex128Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Complex128Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n    > var x = new Complex128Array( xbuf );\n    > var y = new Complex128Array( x.length );\n    > base.strided.zmap( x.length, x, 1, y, 1, base.cidentity );\n    > var v = y.get( 0 )\n    <Complex128>\n    > var re = real( v )\n    1.0\n    > var im = imag( v )\n    2.0\n\n    // Using `N` and stride parameters:\n    > y = new Complex128Array( x.length );\n    > base.strided.zmap( 2, x, 2, y, -1, base.cidentity );\n    > v = y.get( 0 )\n    <Complex128>\n    > re = real( v )\n    5.0\n    > im = imag( v )\n    6.0\n\n    // Using view offsets:\n    > var x0 = new Complex128Array( xbuf );\n    > var y0 = new Complex128Array( x0.length );\n    > var x1 = new Complex128Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Complex128Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > base.strided.zmap( 2, x1, -2, y1, 1, base.cidentity );\n    > v = y1.get( 0 )\n    <Complex128>\n    > re = real( v )\n    7.0\n    > im = imag( v )\n    8.0\n\n\nbase.strided.zmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n    Applies a unary function to a double-precision complex floating-point\n    strided input array and assigns results to a double-precision complex\n    floating-point strided output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex128Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Complex128Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Complex128Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n    > var x = new Complex128Array( xbuf );\n    > var y = new Complex128Array( x.length );\n    > base.strided.zmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentity );\n    > var v = y.get( 0 )\n    <Complex128>\n    > var re = real( v )\n    1.0\n    > var im = imag( v )\n    2.0\n\n    // Advanced indexing:\n    > x = new Complex128Array( xbuf );\n    > y = new Complex128Array( x.length );\n    > base.strided.zmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentity );\n    > v = y.get( y.length-1 )\n    <Complex128>\n    > re = real( v )\n    3.0\n    > im = imag( v )\n    4.0\n\n    See Also\n    --------\n    base.strided.cmap, base.strided.unary\n","base.strided.zmap.ndarray":"\nbase.strided.zmap.ndarray( N, x, strideX, offsetX, y, strideY, offsetY, fcn )\n    Applies a unary function to a double-precision complex floating-point\n    strided input array and assigns results to a double-precision complex\n    floating-point strided output array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Complex128Array\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    y: Complex128Array\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    fcn: Function\n        Unary function to apply.\n\n    Returns\n    -------\n    y: Complex128Array\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var xbuf = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0 ];\n    > var x = new Complex128Array( xbuf );\n    > var y = new Complex128Array( x.length );\n    > base.strided.zmap.ndarray( x.length, x, 1, 0, y, 1, 0, base.cidentity );\n    > var v = y.get( 0 )\n    <Complex128>\n    > var re = real( v )\n    1.0\n    > var im = imag( v )\n    2.0\n\n    // Advanced indexing:\n    > x = new Complex128Array( xbuf );\n    > y = new Complex128Array( x.length );\n    > base.strided.zmap.ndarray( 2, x, 2, 1, y, -1, y.length-1, base.cidentity );\n    > v = y.get( y.length-1 )\n    <Complex128>\n    > re = real( v )\n    3.0\n    > im = imag( v )\n    4.0\n\n    See Also\n    --------\n    base.strided.cmap, base.strided.unary","base.str2multislice":"\nbase.str2multislice( str )\n    Parses a string-serialized MultiSlice object.\n\n    The function returns `null` if provided an invalid string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    s: MultiSlice|null\n        MultiSlice instance (or null).\n\n    Examples\n    --------\n    > var s = new base.str2multislice( 'MultiSlice(null,null,null)' );\n    > s.data\n    [ null, null, null ]\n    > s = new base.str2multislice( 'MultiSlice(10,Slice(0,10,1),null)' );\n    > s.data\n    [ 10, <Slice>, null ]\n\n    See Also\n    --------\n    base.str2slice\n","base.str2slice":"\nbase.str2slice( str )\n    Parses a string-serialized Slice object.\n\n    The function returns `null` if provided an invalid string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    s: Slice|null\n        Slice instance (or null).\n\n    Examples\n    --------\n    > var s = new base.str2slice( 'Slice(1,10,1)' );\n    > s.start\n    1\n    > s.stop\n    10\n    > s.step\n    1\n    > s = new base.str2slice( 'Slice(2,5,2)' );\n    > s.start\n    2\n    > s.stop\n    5\n    > s.step\n    2\n\n    See Also\n    --------\n    base.str2multislice\n","base.sub":"\nbase.sub( x, y )\n    Subtracts two double-precision floating-point numbers `x` and `y`.\n\n    Parameters\n    ----------\n    x: number\n        First input value.\n\n    y: number\n        Second input value.\n\n    Returns\n    -------\n    z: number\n        Result.\n\n    Examples\n    --------\n    > var v = base.sub( -1.0, 5.0 )\n    -6.0\n    > v = base.sub( 2.0, 5.0 )\n    -3.0\n    > v = base.sub( 0.0, 5.0 )\n    -5.0\n    > v = base.sub( -0.0, 0.0 )\n    -0.0\n    > v = base.sub( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.add, base.div, base.mul\n","base.subf":"\nbase.subf( x, y )\n    Subtracts two single-precision floating-point numbers `x` and `y`.\n\n    Parameters\n    ----------\n    x: number\n        First input value.\n\n    y: number\n        Second input value.\n\n    Returns\n    -------\n    z: number\n        Result.\n\n    Examples\n    --------\n    > var v = base.subf( -1.0, 5.0 )\n    -6.0\n    > v = base.subf( 2.0, 5.0 )\n    -3.0\n    > v = base.subf( 0.0, 5.0 )\n    -5.0\n    > v = base.subf( -0.0, 0.0 )\n    -0.0\n    > v = base.subf( NaN, NaN )\n    NaN\n\n    See Also\n    --------\n    base.addf, base.divf, base.mulf, base.sub\n","base.sumSeries":"\nbase.sumSeries( generator[, options] )\n    Sum the elements of the series given by the supplied function.\n\n    Parameters\n    ----------\n    generator: Function\n        Series function.\n\n    options: Object (optional)\n        Options.\n\n    options.maxTerms: integer (optional)\n        Maximum number of terms to be added. Default: `1000000`.\n\n    options.tolerance: number (optional)\n        Further terms are only added as long as the next term is greater than\n        the current term times the tolerance. Default: `2.22e-16`.\n\n    options.initialValue: number (optional)\n        Initial value of the resulting sum. Default: `0`.\n\n    Returns\n    -------\n    out: number\n        Sum of series terms.\n\n    Examples\n    --------\n    // Using an ES6 generator function:\n    > function* geometricSeriesGenerator( x ) {\n    ...     var exponent = 0;\n    ...     while ( true ) {\n    ...         yield Math.pow( x, exponent );\n    ...         exponent += 1;\n    ...     }\n    ... };\n    > var gen = geometricSeriesGenerator( 0.9 );\n    > var out = base.sumSeries( gen )\n    10\n\n    // Using a closure:\n    > function geometricSeriesClosure( x ) {\n    ...     var exponent = -1;\n    ...     return function() {\n    ...         exponent += 1;\n    ...         return Math.pow( x, exponent );\n    ...     };\n    ... };\n    > gen = geometricSeriesClosure( 0.9 );\n    > out = base.sumSeries( gen )\n    10\n\n    // Setting an initial value for the sum:\n    > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'initialValue': 1 } )\n    3\n    // Changing the maximum number of terms to be summed:\n    > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'maxTerms': 10 } )\n    ~1.998 // Infinite sum is 2\n\n    // Adjusting the used tolerance:\n    > out = base.sumSeries( geometricSeriesGenerator( 0.5 ), { 'tolerance': 1e-3 } )\n    ~1.998\n\n","base.tan":"\nbase.tan( x )\n    Computes the tangent of a number.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Tangent.\n\n    Examples\n    --------\n    > var y = base.tan( 0.0 )\n    ~0.0\n    > y = base.tan( -PI/4.0 )\n    ~-1.0\n    > y = base.tan( PI/4.0 )\n    ~1.0\n    > y = base.tan( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cos, base.sin\n","base.tand":"\nbase.tand( x )\n    Computes the tangent of an angle measured in degrees.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in degrees).\n\n    Returns\n    -------\n    y: number\n        Tangent.\n\n    Examples\n    --------\n    > var y = base.tand( 0.0 )\n    0.0\n    > y = base.tand( 90.0 )\n    Infinity\n    > y = base.tand( 60.0 )\n    ~1.73\n    > y = base.tand( NaN )\n    NaN\n\n    See Also\n    --------\n    base.tan, base.cosd\n","base.tanh":"\nbase.tanh( x )\n    Computes the hyperbolic tangent of a double-precision floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Hyperbolic tangent.\n\n    Examples\n    --------\n    > var y = base.tanh( 0.0 )\n    0.0\n    > var y = base.tanh( -0.0 )\n    -0.0\n    > y = base.tanh( 2.0 )\n    ~0.964\n    > y = base.tanh( -2.0 )\n    ~-0.964\n    > y = base.tanh( NaN )\n    NaN\n\n    See Also\n    --------\n    base.cosh, base.sinh, base.tan\n","base.toBinaryString":"\nbase.toBinaryString( x )\n    Returns a string giving the literal bit representation of a double-precision\n    floating-point number.\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    Returns\n    -------\n    bstr: string\n        Bit representation.\n\n    Examples\n    --------\n    > var str = base.toBinaryString( 4.0 )\n    '0100000000010000000000000000000000000000000000000000000000000000'\n    > str = base.toBinaryString( PI )\n    '0100000000001001001000011111101101010100010001000010110100011000'\n    > str = base.toBinaryString( -1.0e308 )\n    '1111111111100001110011001111001110000101111010111100100010100000'\n    > str = base.toBinaryString( -3.14e-320 )\n    '1000000000000000000000000000000000000000000000000001100011010011'\n    > str = base.toBinaryString( 5.0e-324 )\n    '0000000000000000000000000000000000000000000000000000000000000001'\n    > str = base.toBinaryString( 0.0 )\n    '0000000000000000000000000000000000000000000000000000000000000000'\n    > str = base.toBinaryString( -0.0 )\n    '1000000000000000000000000000000000000000000000000000000000000000'\n    > str = base.toBinaryString( NaN )\n    '0111111111111000000000000000000000000000000000000000000000000000'\n    > str = base.toBinaryString( PINF )\n    '0111111111110000000000000000000000000000000000000000000000000000'\n    > str = base.toBinaryString( NINF )\n    '1111111111110000000000000000000000000000000000000000000000000000'\n\n    See Also\n    --------\n    base.fromBinaryString, base.toBinaryStringf\n","base.toBinaryStringf":"\nbase.toBinaryStringf( x )\n    Returns a string giving the literal bit representation of a single-precision\n    floating-point number.\n\n    Parameters\n    ----------\n    x: float\n        Single-precision floating-point number.\n\n    Returns\n    -------\n    str: string\n        Bit representation.\n\n    Examples\n    --------\n    > var str = base.toBinaryStringf( base.float64ToFloat32( 4.0 ) )\n    '01000000100000000000000000000000'\n    > str = base.toBinaryStringf( base.float64ToFloat32( PI ) )\n    '01000000010010010000111111011011'\n    > str = base.toBinaryStringf( base.float64ToFloat32( -1.0e38 ) )\n    '11111110100101100111011010011001'\n    > str = base.toBinaryStringf( base.float64ToFloat32( -3.14e-39 ) )\n    '10000000001000100011000100001011'\n    > str = base.toBinaryStringf( base.float64ToFloat32( 1.4e-45 ) )\n    '00000000000000000000000000000001'\n    > str = base.toBinaryStringf( 0.0 )\n    '00000000000000000000000000000000'\n    > str = base.toBinaryStringf( -0.0 )\n    '10000000000000000000000000000000'\n    > str = base.toBinaryStringf( NaN )\n    '01111111110000000000000000000000'\n    > str = base.toBinaryStringf( FLOAT32_PINF )\n    '01111111100000000000000000000000'\n    > str = base.toBinaryStringf( FLOAT32_NINF )\n    '11111111100000000000000000000000'\n\n    See Also\n    --------\n    base.fromBinaryStringf, base.toBinaryString\n","base.toBinaryStringUint8":"\nbase.toBinaryStringUint8( x )\n    Returns a string giving the literal bit representation of an unsigned 8-bit\n    integer.\n\n    Except for typed arrays, JavaScript does not provide native user support for\n    unsigned 8-bit integers. According to the ECMAScript standard, `number`\n    values correspond to double-precision floating-point numbers. While this\n    function is intended for unsigned 8-bit integers, the function will accept\n    floating-point values and represent the values as if they are unsigned 8-bit\n    integers. Accordingly, care should be taken to ensure that only nonnegative\n    integer values less than `256` (`2^8`) are provided.\n\n    Parameters\n    ----------\n    x: integer\n        Input value.\n\n    Returns\n    -------\n    str: string\n        Bit representation.\n\n    Examples\n    --------\n    > var a = new Uint8Array( [ 1, 4, 9 ] );\n    > var str = base.toBinaryStringUint8( a[ 0 ] )\n    '00000001'\n    > str = base.toBinaryStringUint8( a[ 1 ] )\n    '00000100'\n    > str = base.toBinaryStringUint8( a[ 2 ] )\n    '00001001'\n\n    See Also\n    --------\n    base.toBinaryString\n","base.toBinaryStringUint16":"\nbase.toBinaryStringUint16( x )\n    Returns a string giving the literal bit representation of an unsigned 16-bit\n    integer.\n\n    Except for typed arrays, JavaScript does not provide native user support for\n    unsigned 16-bit integers. According to the ECMAScript standard, `number`\n    values correspond to double-precision floating-point numbers. While this\n    function is intended for unsigned 16-bit integers, the function will accept\n    floating-point values and represent the values as if they are unsigned\n    16-bit integers. Accordingly, care should be taken to ensure that only\n    nonnegative integer values less than `65536` (`2^16`) are provided.\n\n    Parameters\n    ----------\n    x: integer\n        Input value.\n\n    Returns\n    -------\n    str: string\n        Bit representation.\n\n    Examples\n    --------\n    > var a = new Uint16Array( [ 1, 4, 9 ] );\n    > var str = base.toBinaryStringUint16( a[ 0 ] )\n    '0000000000000001'\n    > str = base.toBinaryStringUint16( a[ 1 ] )\n    '0000000000000100'\n    > str = base.toBinaryStringUint16( a[ 2 ] )\n    '0000000000001001'\n\n    See Also\n    --------\n    base.toBinaryString\n","base.toBinaryStringUint32":"\nbase.toBinaryStringUint32( x )\n    Returns a string giving the literal bit representation of an unsigned 32-bit\n    integer.\n\n    Except for typed arrays, JavaScript does not provide native user support for\n    unsigned 32-bit integers. According to the ECMAScript standard, `number`\n    values correspond to double-precision floating-point numbers. While this\n    function is intended for unsigned 32-bit integers, the function will accept\n    floating-point values and represent the values as if they are unsigned\n    32-bit integers. Accordingly, care should be taken to ensure that only\n    nonnegative integer values less than `4,294,967,296` (`2^32`) are provided.\n\n    Parameters\n    ----------\n    x: integer\n        Input value.\n\n    Returns\n    -------\n    str: string\n        Bit representation.\n\n    Examples\n    --------\n    > var a = new Uint32Array( [ 1, 4, 9 ] );\n    > var str = base.toBinaryStringUint32( a[ 0 ] )\n    '00000000000000000000000000000001'\n    > str = base.toBinaryStringUint32( a[ 1 ] )\n    '00000000000000000000000000000100'\n    > str = base.toBinaryStringUint32( a[ 2 ] )\n    '00000000000000000000000000001001'\n\n    See Also\n    --------\n    base.toBinaryString\n","base.toWordf":"\nbase.toWordf( x )\n    Returns an unsigned 32-bit integer corresponding to the IEEE 754 binary\n    representation of a single-precision floating-point number.\n\n    Parameters\n    ----------\n    x: float\n        Single-precision floating-point number.\n\n    Returns\n    -------\n    out: integer\n        Unsigned 32-bit integer.\n\n    Examples\n    --------\n    > var f32 = base.float64ToFloat32( 1.337 )\n    1.3370000123977661\n    > var w = base.toWordf( f32 )\n    1068180177\n\n    See Also\n    --------\n    base.fromWordf, base.toWords\n","base.toWords":"\nbase.toWords( x )\n    Splits a double-precision floating-point number into a higher order word\n    (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n\n    When provided a destination object, the function returns an array with two\n    elements: a higher order word and a lower order word, respectively. The\n    lower order word contains the less significant bits, while the higher order\n    word contains the more significant bits and includes the exponent and sign.\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    Returns\n    -------\n    out: Array<integer>\n        Higher and lower order words.\n\n    Examples\n    --------\n    > var w = base.toWords( 3.14e201 )\n    [ 1774486211, 2479577218 ]\n\n\nbase.toWords.assign( x, out, stride, offset )\n    Splits a double-precision floating-point number into a higher order word\n    (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer)\n    and assigns results to a provided output array.\n\n    When provided a destination object, the function returns an array with two\n    elements: a higher order word and a lower order word, respectively. The\n    lower order word contains the less significant bits, while the higher order\n    word contains the more significant bits and includes the exponent and sign.\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Higher and lower order words.\n\n    Examples\n    --------\n    > var out = new Uint32Array( 2 );\n    > var w = base.toWords.assign( 3.14e201, out, 1, 0 )\n    <Uint32Array>[ 1774486211, 2479577218 ]\n    > var bool = ( w === out )\n    true\n\n    See Also\n    --------\n    base.fromWords, base.toWordf","base.toWords.assign":"\nbase.toWords.assign( x, out, stride, offset )\n    Splits a double-precision floating-point number into a higher order word\n    (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer)\n    and assigns results to a provided output array.\n\n    When provided a destination object, the function returns an array with two\n    elements: a higher order word and a lower order word, respectively. The\n    lower order word contains the less significant bits, while the higher order\n    word contains the more significant bits and includes the exponent and sign.\n\n    Parameters\n    ----------\n    x: number\n        Double-precision floating-point number.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Higher and lower order words.\n\n    Examples\n    --------\n    > var out = new Uint32Array( 2 );\n    > var w = base.toWords.assign( 3.14e201, out, 1, 0 )\n    <Uint32Array>[ 1774486211, 2479577218 ]\n    > var bool = ( w === out )\n    true\n\n    See Also\n    --------\n    base.fromWords, base.toWordf","base.transpose":"\nbase.transpose( x )\n    Transposes a matrix (or a stack of matrices).\n\n    The returned ndarray is a *view* of the input ndarray. Accordingly, writing\n    to the original ndarray will mutate the returned ndarray and vice versa.\n    While powerful, this can lead to subtle bugs. In general, one should handle\n    the returned ndarray as read-only.\n\n    If provided an ndarray with fewer than two dimensions, the function raises\n    an exception.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n    <ndarray>\n    > var sh = x.shape\n    [ 2, 3 ]\n    > var y = base.transpose( x )\n    <ndarray>\n    > sh = y.shape\n    [ 3, 2 ]\n    > var bool = ( x.data === y.data )\n    true\n    > bool = ( x.get( 0, 1 ) === y.get( 1, 0 ) )\n    true\n\n    See Also\n    --------\n    ndarray\n","base.tribonacci":"\nbase.tribonacci( n )\n    Computes the nth Tribonacci number.\n\n    Tribonacci numbers follow the recurrence relation\n\n      F_n = F_{n-1} + F_{n-2} + F_{n-3}\n\n    with seed values F_0 = 0, F_1 = 0, and F_2 = 1.\n\n    If `n` is greater than `63`, the function returns `NaN`, as larger\n    Tribonacci numbers cannot be accurately represented due to limitations of\n    double-precision floating-point format.\n\n    If not provided a nonnegative integer value, the function returns `NaN`.\n\n    If provided `NaN`, the function returns `NaN`.\n\n    Parameters\n    ----------\n    n: integer\n        Input value.\n\n    Returns\n    -------\n    y: integer\n        Tribonacci number.\n\n    Examples\n    --------\n    > var y = base.tribonacci( 0 )\n    0\n    > y = base.tribonacci( 1 )\n    0\n    > y = base.tribonacci( 2 )\n    1\n    > y = base.tribonacci( 3 )\n    1\n    > y = base.tribonacci( 4 )\n    2\n    > y = base.tribonacci( 64 )\n    NaN\n    > y = base.tribonacci( NaN )\n    NaN\n\n    See Also\n    --------\n    base.fibonacci\n","base.trigamma":"\nbase.trigamma( x )\n    Evaluates the trigamma function.\n\n    If `x` is `0` or a negative `integer`, the `function` returns `NaN`.\n\n    If provided `NaN`, the `function` returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.trigamma( -2.5 )\n    ~9.539\n    > y = base.trigamma( 1.0 )\n    ~1.645\n    > y = base.trigamma( 10.0 )\n    ~0.105\n    > y = base.trigamma( NaN )\n    NaN\n    > y = base.trigamma( -1.0 )\n    NaN\n\n    See Also\n    --------\n    base.digamma, base.gamma\n","base.trim":"\nbase.trim( str )\n    Trims whitespace from the beginning and end of a `string`.\n\n    \"Whitespace\" is defined as the following characters:\n\n    - \\f\n    - \\n\n    - \\r\n    - \\t\n    - \\v\n    - \\u0020\n    - \\u00a0\n    - \\u1680\n    - \\u2000-\\u200a\n    - \\u2028\n    - \\u2029\n    - \\u202f\n    - \\u205f\n    - \\u3000\n    - \\ufeff\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Trimmed string.\n\n    Examples\n    --------\n    > var out = base.trim( ' \\t\\t\\n  Beep \\r\\n\\t  ' )\n    'Beep'\n\n    See Also\n    --------\n    base.leftTrim, base.rightTrim\n","base.trunc":"\nbase.trunc( x )\n    Rounds a double-precision floating-point number toward zero.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.trunc( 3.14 )\n    3.0\n    > y = base.trunc( -4.2 )\n    -4.0\n    > y = base.trunc( -4.6 )\n    -4.0\n    > y = base.trunc( 9.5 )\n    9.0\n    > y = base.trunc( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceil, base.floor, base.round\n","base.trunc2":"\nbase.trunc2( x )\n    Rounds a numeric value to the nearest power of two toward zero.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.trunc2( 3.14 )\n    2.0\n    > y = base.trunc2( -4.2 )\n    -4.0\n    > y = base.trunc2( -4.6 )\n    -4.0\n    > y = base.trunc2( 9.5 )\n    8.0\n    > y = base.trunc2( 13.0 )\n    8.0\n    > y = base.trunc2( -13.0 )\n    -8.0\n    > y = base.trunc2( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceil2, base.floor2, base.round2, base.trunc, base.trunc10\n","base.trunc10":"\nbase.trunc10( x )\n    Rounds a numeric value to the nearest power of ten toward zero.\n\n    The function may not return accurate results for subnormals due to a general\n    loss in precision.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.trunc10( 3.14 )\n    1.0\n    > y = base.trunc10( -4.2 )\n    -1.0\n    > y = base.trunc10( -4.6 )\n    -1.0\n    > y = base.trunc10( 9.5 )\n    1.0\n    > y = base.trunc10( 13.0 )\n    10.0\n    > y = base.trunc10( -13.0 )\n    -10.0\n    > y = base.trunc10( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceil10, base.floor10, base.round10, base.trunc, base.trunc2\n","base.truncateMiddle":"\nbase.truncateMiddle( str, len, seq )\n    Truncates the middle UTF-16 code units of a string to return a string\n    having a specified length.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    len: integer\n        Output string length.\n\n    seq: string\n        Custom replacement sequence.\n\n    Returns\n    -------\n    out: string\n        Truncated string.\n\n    Examples\n    --------\n    > var str = 'beep boop';\n    > var out = base.truncateMiddle( str, 5, '...' )\n    'b...p'\n    > out = base.truncateMiddle( str, 5, '|' )\n    'be|op'\n","base.truncb":"\nbase.truncb( x, n, b )\n    Rounds a numeric value to the nearest multiple of `b^n` toward zero.\n\n    Due to floating-point rounding error, rounding may not be exact.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Integer power.\n\n    b: integer\n        Base.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    // Round to 4 decimal places:\n    > var y = base.truncb( 3.14159, -4, 10 )\n    3.1415\n\n    // If `n = 0` or `b = 1`, standard round behavior:\n    > y = base.truncb( 3.14159, 0, 2 )\n    3.0\n\n    // Round to nearest multiple of two toward zero:\n    > y = base.truncb( 5.0, 1, 2 )\n    4.0\n\n    See Also\n    --------\n    base.ceilb, base.floorb, base.roundb, base.trunc, base.truncn\n","base.truncf":"\nbase.truncf( x )\n    Rounds a single-precision floating-point number toward zero.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.truncf( 3.14 )\n    3.0\n    > y = base.truncf( -4.2 )\n    -4.0\n    > y = base.truncf( -4.6 )\n    -4.0\n    > y = base.truncf( 9.5 )\n    9.0\n    > y = base.truncf( -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.ceilf, base.floorf, base.trunc\n","base.truncn":"\nbase.truncn( x, n )\n    Rounds a numeric value to the nearest multiple of `10^n` toward zero.\n\n    When operating on floating-point numbers in bases other than `2`, rounding\n    to specified digits can be inexact.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Integer power of 10.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    // Round to 4 decimal places:\n    > var y = base.truncn( 3.14159, -4 )\n    3.1415\n\n    // If `n = 0`, standard round behavior:\n    > y = base.truncn( 3.14159, 0 )\n    3.0\n\n    // Round to nearest thousand:\n    > y = base.truncn( 12368.0, 3 )\n    12000.0\n\n\n    See Also\n    --------\n    base.ceiln, base.floorn, base.roundn, base.trunc, base.truncb\n","base.truncsd":"\nbase.truncsd( x, n, b )\n    Rounds a numeric value to the nearest number toward zero with `n`\n    significant figures.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    n: integer\n        Number of significant figures. Must be greater than 0.\n\n    b: integer\n        Base. Must be greater than 0.\n\n    Returns\n    -------\n    y: number\n        Rounded value.\n\n    Examples\n    --------\n    > var y = base.truncsd( 3.14159, 5, 10 )\n    3.1415\n    > y = base.truncsd( 3.14159, 1, 10 )\n    3.0\n    > y = base.truncsd( 12368.0, 2, 10 )\n    12000.0\n    > y = base.truncsd( 0.0313, 2, 2 )\n    0.03125\n\n    See Also\n    --------\n    base.ceilsd, base.floorsd, base.roundsd, base.trunc\n","base.uint32ToInt32":"\nbase.uint32ToInt32( x )\n    Converts an unsigned 32-bit integer to a signed 32-bit integer.\n\n    Parameters\n    ----------\n    x: integer\n        Unsigned 32-bit integer.\n\n    Returns\n    -------\n    out: integer\n        Signed 32-bit integer.\n\n    Examples\n    --------\n    > var y = base.uint32ToInt32( base.float64ToUint32( 4294967295 ) )\n    -1\n    > y = base.uint32ToInt32( base.float64ToUint32( 3 ) )\n    3\n\n","base.umul":"\nbase.umul( a, b )\n    Performs C-like multiplication of two unsigned 32-bit integers.\n\n    Parameters\n    ----------\n    a: integer\n        Unsigned 32-bit integer.\n\n    b: integer\n        Unsigned 32-bit integer.\n\n    Returns\n    -------\n    out: integer\n        Product.\n\n    Examples\n    --------\n    > var v = base.umul( 10>>>0, 4>>>0 )\n    40\n\n    See Also\n    --------\n    base.imul\n","base.umuldw":"\nbase.umuldw( a, b )\n    Multiplies two unsigned 32-bit integers and returns an array of two unsigned\n    32-bit integers which represents the unsigned 64-bit integer product.\n\n    When computing the product of 32-bit integer values in double-precision\n    floating-point format (the default JavaScript numeric data type), computing\n    the double word product is necessary in order to avoid exceeding the maximum\n    safe double-precision floating-point integer value.\n\n    Parameters\n    ----------\n    a: integer\n        Unsigned 32-bit integer.\n\n    b: integer\n        Unsigned 32-bit integer.\n\n    Returns\n    -------\n    out: Array<number>\n        Double word product (in big endian order; i.e., the first element\n        corresponds to the most significant bits and the second element to the\n        least significant bits).\n\n    Examples\n    --------\n    > var v = base.umuldw( 1, 10 )\n    [ 0, 10 ]\n\n\nbase.umuldw.assign( a, b, out, stride, offset )\n    Multiplies two unsigned 32-bit integers and assigns results representing\n    the unsigned 64-bit integer product to a provided output array.\n\n    When computing the product of 32-bit integer values in double-precision\n    floating-point format (the default JavaScript numeric data type), computing\n    the double word product is necessary in order to avoid exceeding the maximum\n    safe double-precision floating-point integer value.\n\n    Parameters\n    ----------\n    a: integer\n        Unsigned 32-bit integer.\n\n    b: integer\n        Unsigned 32-bit integer.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Double word product (in big endian order; i.e., the first element\n        corresponds to the most significant bits and the second element to the\n        least significant bits).\n\n    Examples\n    --------\n    > var out = [ 0, 0 ];\n    > var v = base.umuldw.assign( 1, 10, out, 1, 0 )\n    [ 0, 10 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.imuldw, base.umul\n","base.umuldw.assign":"\nbase.umuldw.assign( a, b, out, stride, offset )\n    Multiplies two unsigned 32-bit integers and assigns results representing\n    the unsigned 64-bit integer product to a provided output array.\n\n    When computing the product of 32-bit integer values in double-precision\n    floating-point format (the default JavaScript numeric data type), computing\n    the double word product is necessary in order to avoid exceeding the maximum\n    safe double-precision floating-point integer value.\n\n    Parameters\n    ----------\n    a: integer\n        Unsigned 32-bit integer.\n\n    b: integer\n        Unsigned 32-bit integer.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    stride: integer\n        Output array stride.\n\n    offset: integer\n        Output array index offset.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Double word product (in big endian order; i.e., the first element\n        corresponds to the most significant bits and the second element to the\n        least significant bits).\n\n    Examples\n    --------\n    > var out = [ 0, 0 ];\n    > var v = base.umuldw.assign( 1, 10, out, 1, 0 )\n    [ 0, 10 ]\n    > var bool = ( v === out )\n    true\n\n    See Also\n    --------\n    base.imuldw, base.umul","base.uncapitalize":"\nbase.uncapitalize( str )\n    Lowercases the first character of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Uncapitalized string.\n\n    Examples\n    --------\n    > var out = base.uncapitalize( 'Beep' )\n    'beep'\n    > out = base.uncapitalize( 'bOOp' )\n    'bOOp'\n\n    See Also\n    --------\n    base.capitalize\n","base.uppercase":"\nbase.uppercase( str )\n    Converts a string to uppercase.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Uppercase string.\n\n    Examples\n    --------\n    > var out = base.uppercase( 'bEEp' )\n    'BEEP'\n\n    See Also\n    --------\n    base.lowercase\n","base.vercos":"\nbase.vercos( x )\n    Computes the versed cosine.\n\n    The versed cosine is defined as `1 + cos(x)`.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Versed cosine.\n\n    Examples\n    --------\n    > var y = base.vercos( 3.14 )\n    ~0.0\n    > y = base.vercos( -4.2 )\n    ~0.5097\n    > y = base.vercos( -4.6 )\n    ~0.8878\n    > y = base.vercos( 9.5 )\n    ~0.0028\n    > y = base.vercos( -0.0 )\n    2.0\n\n    See Also\n    --------\n    base.cos, base.versin\n","base.versin":"\nbase.versin( x )\n    Computes the versed sine.\n\n    The versed sine is defined as `1 - cos(x)`.\n\n    Parameters\n    ----------\n    x: number\n        Input value (in radians).\n\n    Returns\n    -------\n    y: number\n        Versed sine.\n\n    Examples\n    --------\n    > var y = base.versin( 3.14 )\n    ~2.0\n    > y = base.versin( -4.2 )\n    ~1.490\n    > y = base.versin( -4.6 )\n    ~1.112\n    > y = base.versin( 9.5 )\n    ~1.997\n    > y = base.versin( -0.0 )\n    0.0\n\n    See Also\n    --------\n    base.cos, base.sin, base.vercos\n","base.wrap":"\nbase.wrap( v, min, max )\n    Wraps a value on the half-open interval `[min,max)`.\n\n    The function does not distinguish between positive and negative zero. Where\n    appropriate, the function returns positive zero.\n\n    If provided `NaN` for any argument, the function returns `NaN`.\n\n    Parameters\n    ----------\n    v: number\n        Value to wrap.\n\n    min: number\n        Minimum value.\n\n    max: number\n        Maximum value.\n\n    Returns\n    -------\n    y: number\n        Wrapped value.\n\n    Examples\n    --------\n    > var y = base.wrap( 3.14, 0.0, 5.0 )\n    3.14\n    > y = base.wrap( -3.14, 0.0, 5.0 )\n    ~1.86\n    > y = base.wrap( 3.14, 0.0, 3.0 )\n    ~0.14\n    > y = base.wrap( -0.0, 0.0, 5.0 )\n    0.0\n    > y = base.wrap( 0.0, -3.14, -0.0 )\n    -3.14\n    > y = base.wrap( NaN, 0.0, 5.0 )\n    NaN\n\n    See Also\n    --------\n    base.clamp\n","base.xlog1py":"\nbase.xlog1py( x, y )\n    Computes `x * ln(y+1)` so that the result is `0` if `x = 0`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    y: number\n        Input value.\n\n    Returns\n    -------\n    out: number\n        Function value.\n\n    Examples\n    --------\n    > var out = base.xlog1py( 3.0, 2.0 )\n    ~3.296\n    > out = base.xlog1py( 1.5, 5.9 )\n    ~2.897\n    > out = base.xlog1py( 0.9, 1.0 )\n    ~0.624\n    > out = base.xlog1py( 1.0, 0.0 )\n    0.0\n    > out = base.xlog1py( 0.0, -2.0 )\n    0.0\n    > out = base.xlog1py( 1.5, NaN )\n    NaN\n    > out = base.xlog1py( 0.0, NaN )\n    NaN\n    > out = base.xlog1py( NaN, 2.3 )\n    NaN\n\n    See Also\n    --------\n    base.log1p, base.xlogy\n","base.xlogy":"\nbase.xlogy( x, y )\n    Computes `x * ln(y)` so that the result is `0` if `x = 0`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    y: number\n        Input value.\n\n    Returns\n    -------\n    out: number\n        Function value.\n\n    Examples\n    --------\n    > var out = base.xlogy( 3.0, 2.0 )\n    ~2.079\n    > out = base.xlogy( 1.5, 5.9 )\n    ~2.662\n    > out = base.xlogy( 0.9, 1.0 )\n    0.0\n    > out = base.xlogy( 0.0, -2.0 )\n    0.0\n    > out = base.xlogy( 1.5, NaN )\n    NaN\n    > out = base.xlogy( 0.0, NaN )\n    NaN\n    > out = base.xlogy( NaN, 2.3 )\n    NaN\n\n    See Also\n    --------\n    base.ln, base.xlog1py\n","base.zeta":"\nbase.zeta( s )\n    Evaluates the Riemann zeta function as a function of a real variable `s`.\n\n    Parameters\n    ----------\n    s: number\n        Input value.\n\n    Returns\n    -------\n    y: number\n        Function value.\n\n    Examples\n    --------\n    > var y = base.zeta( 1.1 )\n    ~10.584\n    > y = base.zeta( -4.0 )\n    0.0\n    > y = base.zeta( 70.0 )\n    1.0\n    > y = base.zeta( 0.5 )\n    ~-1.46\n    > y = base.zeta( NaN )\n    NaN\n\n    // Evaluate at a pole:\n    > y = base.zeta( 1.0 )\n    NaN\n\n","BERNDT_CPS_WAGES_1985":"\nBERNDT_CPS_WAGES_1985()\n    Returns a random sample of 534 workers from the Current Population Survey\n    (CPS) from 1985, including their wages and and other characteristics.\n\n    Each array element has the following eleven fields:\n\n    - education: number of years of education.\n    - south: indicator variable for southern region (1 if a person lives in the\n    South; 0 if a person does not live in the South).\n    - gender: gender of the person.\n    - experience: number of years of work experience.\n    - union: indicator variable for union membership (1 if union member; 0 if\n    not a union member).\n    - wage: wage (in dollars per hour).\n    - age: age (in years).\n    - race: ethnicity/race (white, hispanic, and other).\n    - occupation: occupational category (management, sales, clerical, service,\n    professional, and other).\n    - sector: sector (other, manufacturing, or construction).\n    - married: marital status (0 if unmarried; 1 if married).\n\n    Based on residual plots, wages were log-transformed to stabilize the\n    variance.\n\n    Returns\n    -------\n    out: Array<Object>\n        CPS data.\n\n    Examples\n    --------\n    > var data = BERNDT_CPS_WAGES_1985()\n    [ {...}, {...}, ... ]\n\n    References\n    ----------\n    - Berndt, Ernst R. 1991. _The Practice of Econometrics_. Addison Wesley\n    Longman Publishing Co.\n\n","bifurcate":"\nbifurcate( collection, [options,] filter )\n    Splits values into two groups.\n\n    If an element in `filter` is truthy, then the corresponding element in the\n    input collection belongs to the first group; otherwise, the collection\n    element belongs to the second group.\n\n    If provided an empty collection, the function returns an empty array.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection to group. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Options.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `indices`, indices are returned; if\n        `*`, both indices and values are returned. Default: 'values'.\n\n    filter: Array|TypedArray|Object\n        A collection indicating which group an element in the input collection\n        belongs to. If an element in `filter` is truthy, the corresponding\n        element in `collection` belongs to the first group; otherwise, the\n        collection element belongs to the second group. If provided an object,\n        the object must be array-like (excluding strings and functions).\n\n    Returns\n    -------\n    out: Array<Array>|Array\n        Group results.\n\n    Examples\n    --------\n    > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n    > var f = [ true, true, false, true ];\n    > var out = bifurcate( collection, f )\n    [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n    > f = [ 1, 1, 0, 1 ];\n    > out = bifurcate( collection, f )\n    [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n    // Output group results as indices:\n    > f = [ true, true, false, true ];\n    > var opts = { 'returns': 'indices' };\n    > out = bifurcate( collection, opts, f )\n    [ [ 0, 1, 3 ], [ 2 ] ]\n\n    // Output group results as index-element pairs:\n    > opts = { 'returns': '*' };\n    > out = bifurcate( collection, opts, f )\n    [ [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], [ [2, 'foo'] ] ]\n\n    See Also\n    --------\n    bifurcateBy, bifurcateOwn, group\n","bifurcateBy":"\nbifurcateBy( collection, [options,] predicate )\n    Splits values into two groups according to a predicate function.\n\n    When invoked, the predicate function is provided two arguments:\n\n    - value: collection value.\n    - index: collection index.\n\n    If a predicate function returns a truthy value, a collection value is\n    placed in the first group; otherwise, a collection value is placed in the\n    second group.\n\n    If provided an empty collection, the function returns an empty array.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection to group. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Options.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `indices`, indices are returned; if\n        `*`, both indices and values are returned. Default: 'values'.\n\n    predicate: Function\n        Predicate function indicating which group an element in the input\n        collection belongs to.\n\n    Returns\n    -------\n    out: Array<Array>|Array\n        Group results.\n\n    Examples\n    --------\n    > function predicate( v ) { return v[ 0 ] === 'b'; };\n    > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n    > var out = bifurcateBy( collection, predicate )\n    [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n    // Output group results as indices:\n    > var opts = { 'returns': 'indices' };\n    > out = bifurcateBy( collection, opts, predicate )\n    [ [ 0, 1, 3 ], [ 2 ] ]\n\n    // Output group results as index-value pairs:\n    > opts = { 'returns': '*' };\n    > out = bifurcateBy( collection, opts, predicate )\n    [ [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], [ [2, 'foo' ] ] ]\n\n    See Also\n    --------\n    bifurcate, groupBy\n","bifurcateByAsync":"\nbifurcateByAsync( collection, [options,] predicate, done )\n    Splits values into two groups according to a predicate function.\n\n    When invoked, the predicate function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If the\n    predicate function accepts two arguments, the predicate function is\n    provided:\n\n    - value\n    - next\n\n    If the predicate function accepts three arguments, the predicate function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other predicate function signature, the predicate function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - group: value group.\n\n    If an predicate function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    If a predicate function calls the `next` callback with a truthy group value,\n    a collection value is placed in the first group; otherwise, a collection\n    value is placed in the second group.\n\n    If provided an empty collection, the function calls the `done` callback with\n    an empty array as the second argument.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `indices`, indices are returned; if\n        `*`, both indices and values are returned. Default: 'values'.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        Predicate function indicating which group an element in the input\n        collection belongs to.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function predicate( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > bifurcateByAsync( arr, predicate, done )\n    1000\n    2500\n    3000\n    [ [ 1000, 3000 ], [ 2500 ] ]\n\n    // Output group results as indices:\n    > var opts = { 'returns': 'indices' };\n    > bifurcateByAsync( arr, opts, predicate, done )\n    1000\n    2500\n    3000\n    [ [ 2, 0 ], [ 1 ] ]\n\n    // Output group results as index-value pairs:\n    > opts = { 'returns': '*' };\n    > bifurcateByAsync( arr, opts, predicate, done )\n    1000\n    2500\n    3000\n    [ [ [ 2, 1000 ], [ 0, 3000 ] ], [ [ 1, 2500 ] ] ]\n\n    // Limit number of concurrent invocations:\n    > function predicate( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 3000, 2500, 1000 ];\n    > bifurcateByAsync( arr, opts, predicate, done )\n    2500\n    3000\n    1000\n    [ [ 3000, 1000 ], [ 2500 ] ]\n\n    // Process sequentially:\n    > function predicate( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 3000, 2500, 1000 ];\n    > bifurcateByAsync( arr, opts, predicate, done )\n    3000\n    2500\n    1000\n    [ [ 3000, 1000 ], [ 2500 ] ]\n\n\nbifurcateByAsync.factory( [options,] predicate )\n    Returns a function which splits values into two groups according to an\n    predicate function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `indices`, indices are returned; if\n        `*`, both indices and values are returned. Default: 'values'.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        Predicate function indicating which group an element in the input\n        collection belongs to.\n\n    Returns\n    -------\n    out: Function\n        A function which splits values into two groups.\n\n    Examples\n    --------\n    > function predicate( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = bifurcateByAsync.factory( opts, predicate );\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    [ [ 3000, 1000 ], [ 2500 ] ]\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    [ [ 2000, 1000 ], [ 1500 ] ]\n\n    See Also\n    --------\n    bifurcateBy, groupByAsync\n","bifurcateByAsync.factory":"\nbifurcateByAsync.factory( [options,] predicate )\n    Returns a function which splits values into two groups according to an\n    predicate function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `indices`, indices are returned; if\n        `*`, both indices and values are returned. Default: 'values'.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        Predicate function indicating which group an element in the input\n        collection belongs to.\n\n    Returns\n    -------\n    out: Function\n        A function which splits values into two groups.\n\n    Examples\n    --------\n    > function predicate( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = bifurcateByAsync.factory( opts, predicate );\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    [ [ 3000, 1000 ], [ 2500 ] ]\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    [ [ 2000, 1000 ], [ 1500 ] ]\n\n    See Also\n    --------\n    bifurcateBy, groupByAsync","bifurcateIn":"\nbifurcateIn( obj, [options,] predicate )\n    Splits values into two groups according to a predicate function.\n\n    When invoked, the predicate function is provided two arguments:\n\n    - value: object value.\n    - key: object key.\n\n    If a predicate function returns a truthy value, a value is placed in the\n    first group; otherwise, a value is placed in the second group.\n\n    If provided an empty object with no prototype, the function returns an empty\n    array.\n\n    The function iterates over an object's own and inherited properties.\n\n    Key iteration order is *not* guaranteed, and, thus, result order is *not*\n    guaranteed.\n\n    Parameters\n    ----------\n    obj: Object|Array|TypedArray\n        Input object to group.\n\n    options: Object (optional)\n        Options.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `keys`, keys are returned; if `*`,\n        both keys and values are returned. Default: 'values'.\n\n    predicate: Function\n        Predicate function indicating which group a value in the input object\n        belongs to.\n\n    Returns\n    -------\n    out: Array<Array>|Array\n        Group results.\n\n    Examples\n    --------\n    > function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\n    > Foo.prototype = Object.create( null );\n    > Foo.prototype.c = 'foo';\n    > Foo.prototype.d = 'bar';\n    > var obj = new Foo();\n    > function predicate( v ) { return v[ 0 ] === 'b'; };\n    > var out = bifurcateIn( obj, predicate )\n    [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n    // Output group results as keys:\n    > var opts = { 'returns': 'keys' };\n    > out = bifurcateIn( obj, opts, predicate )\n    [ [ 'a', 'b', 'd' ], [ 'c' ] ]\n\n    // Output group results as key-value pairs:\n    > opts = { 'returns': '*' };\n    > out = bifurcateIn( obj, opts, predicate )\n    [ [ ['a', 'beep'], ['b', 'boop'], ['d', 'bar'] ], [ ['c', 'foo' ] ] ]\n\n    See Also\n    --------\n    bifurcate, bifurcateBy, bifurcateOwn, groupIn\n","bifurcateOwn":"\nbifurcateOwn( obj, [options,] predicate )\n    Splits values into two groups according to a predicate function.\n\n    When invoked, the predicate function is provided two arguments:\n\n    - value: object value.\n    - key: object key.\n\n    If a predicate function returns a truthy value, a value is placed in the\n    first group; otherwise, a value is placed in the second group.\n\n    If provided an empty object, the function returns an empty array.\n\n    The function iterates over an object's own properties.\n\n    Key iteration order is *not* guaranteed, and, thus, result order is *not*\n    guaranteed.\n\n    Parameters\n    ----------\n    obj: Object|Array|TypedArray\n        Input object to group.\n\n    options: Object (optional)\n        Options.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `keys`, keys are returned; if `*`,\n        both keys and values are returned. Default: 'values'.\n\n    predicate: Function\n        Predicate function indicating which group a value in the input object\n        belongs to.\n\n    Returns\n    -------\n    out: Array<Array>|Array\n        Group results.\n\n    Examples\n    --------\n    > function predicate( v ) { return v[ 0 ] === 'b'; };\n    > var obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\n    > var out = bifurcateOwn( obj, predicate )\n    [ [ 'beep', 'boop', 'bar' ], [ 'foo' ] ]\n\n    // Output group results as keys:\n    > var opts = { 'returns': 'keys' };\n    > out = bifurcateOwn( obj, opts, predicate )\n    [ [ 'a', 'b', 'd' ], [ 'c' ] ]\n\n    // Output group results as key-value pairs:\n    > opts = { 'returns': '*' };\n    > out = bifurcateOwn( obj, opts, predicate )\n    [ [ ['a', 'beep'], ['b', 'boop'], ['d', 'bar'] ], [ ['c', 'foo' ] ] ]\n\n    See Also\n    --------\n    bifurcate, bifurcateBy, bifurcateIn, groupOwn\n","BigInt":"\nBigInt( value )\n    Returns a BigInt.\n\n    Unlike conventional constructors, this function does **not** support the\n    `new` keyword.\n\n    This function is only supported in environments which support BigInts.\n\n    Parameters\n    ----------\n    value: integer|string\n        Value of the BigInt.\n\n    Returns\n    -------\n    out: BigInt\n        BigInt.\n\n    Examples\n    --------\n    > var v = ( BigInt ) ? BigInt( '1' ) : null\n\n\nTODO: document properties/methods\n\n","binomialTest":"\nbinomialTest( x[, n][, options] )\n    Computes an exact test for the success probability in a Bernoulli\n    experiment.\n\n    The returned object comes with a `.print()` method which when invoked will\n    print a formatted output of the results of the hypothesis test.\n\n    Parameters\n    ----------\n    x: (number|Array<number>)\n        Number of successes or two-element array with successes and failures.\n\n    n: Array<number> (optional)\n        Total number of observations.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.alternative: string (optional)\n        Indicates whether the alternative hypothesis is that the mean of `x` is\n        larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n        `mu` (`two-sided`). Default: `'two-sided'`.\n\n    options.p: number (optional)\n        Hypothesized probability under the null hypothesis. Default: `0.5`.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Used significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Sample proportion.\n\n    out.ci: Array<number>\n        1-alpha confidence interval for the success probability.\n\n    out.nullValue: number\n        Assumed success probability under H0.\n\n    out.alternative: string\n        Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n    out.method: string\n        Name of test.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    > var out = binomialTest( 682, 925 )\n    {\n        'pValue': ~3.544e-49,\n        'statistic': ~0.737\n        // ...\n    }\n\n    > out = binomialTest( [ 682, 925 - 682 ] )\n    {\n        'pValue': ~3.544e-49,\n        'statistic': ~0.737\n        // ...\n    }\n\n    > out = binomialTest( 21, 40, {\n    ...     'p': 0.4,\n    ...     'alternative': 'greater'\n    ... })\n    {\n        'pValue': ~0.074,\n        'statistic': 0.525\n        // ...\n    }\n\n","Boolean":"\nBoolean( value )\n    Returns a boolean.\n\n    When invoked without `new`,\n\n    - if provided `false`, `null`, `undefined`, `-0`, `0`, `NaN`, or an empty\n      string, the function returns `false`.\n    - if provided any other value, including an empty object, an empty array,\n      the string `'false'`, or a `Boolean` object (including a `Boolean` object\n      whose value is `false`), the function returns `true`.\n\n    When invoked with `new`, the constructor returns a `Boolean` object, which\n    is an object wrapper for a primitive boolean value. The value of the\n    returned `Boolean` object follows the same conversion semantics as when the\n    constructor is invoked without `new`.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    out: boolean|Boolean\n        Boolean primitive or object.\n\n    Examples\n    --------\n    > var b = new Boolean( null )\n    <Boolean>\n    > b = Boolean( null )\n    false\n    > b = Boolean( [] )\n    true\n\nBoolean.prototype.toString()\n    Returns a string representing the `Boolean` object.\n\n    Returns\n    -------\n    out: string\n        String representation.\n\n    Examples\n    --------\n    > var b = new Boolean( true )\n    <Boolean>\n    > b.toString()\n    'true'\n\nBoolean.prototype.valueOf()\n    Returns the primitive value of a `Boolean` object.\n\n    Returns\n    -------\n    out: boolean\n        Boolean primitive.\n\n    Examples\n    --------\n    > var b = new Boolean( true )\n    <Boolean>\n    > b.valueOf()\n    true\n\n","Boolean.prototype.toString":"\nBoolean.prototype.toString()\n    Returns a string representing the `Boolean` object.\n\n    Returns\n    -------\n    out: string\n        String representation.\n\n    Examples\n    --------\n    > var b = new Boolean( true )\n    <Boolean>\n    > b.toString()\n    'true'","Boolean.prototype.valueOf":"\nBoolean.prototype.valueOf()\n    Returns the primitive value of a `Boolean` object.\n\n    Returns\n    -------\n    out: boolean\n        Boolean primitive.\n\n    Examples\n    --------\n    > var b = new Boolean( true )\n    <Boolean>\n    > b.valueOf()\n    true","BooleanArray":"\nBooleanArray()\n    A Boolean array.\n\n    Returns\n    -------\n    out: BooleanArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new BooleanArray()\n    <BooleanArray>\n\n\nBooleanArray( length )\n    Creates a boolean array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: BooleanArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 10 )\n    <BooleanArray>\n    > var len = arr.length\n    10\n\n\nBooleanArray( booleanarray )\n    Creates a boolean array from another boolean array.\n\n    Parameters\n    ----------\n    booleanarray: BooleanArray\n        Boolean array from which to generate another boolean array.\n\n    Returns\n    -------\n    out: BooleanArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new BooleanArray( [ true, false, false, true ] )\n    <BooleanArray>\n    > var arr2 = new BooleanArray( arr1 )\n    <BooleanArray>\n    > var len = arr2.length\n    4\n\n\nBooleanArray( typedarray )\n    Creates a boolean array from a typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate boolean array.\n\n    Returns\n    -------\n    out: BooleanArray\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new Uint8Array( [ 1, 0, 0, 1 ] )\n    <Uint8Array>\n    > var arr = new BooleanArray( buf )\n    <BooleanArray>\n    > var len = arr.length\n    4\n\n\nBooleanArray( obj )\n    Creates a boolean array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a boolean array.\n\n    Returns\n    -------\n    out: BooleanArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new BooleanArray( [ true, false, false, true ] )\n    <BooleanArray>\n    > var len = arr1.length\n    4\n    > var arr2 = new BooleanArray( [ {}, null, '', 4 ] );\n    > len = arr2.length\n    4\n\n\nBooleanArray( buffer[, byteOffset[, length]] )\n    Returns a boolean array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: BooleanArray\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 240 );\n    > var arr1 = new BooleanArray( buf )\n    <BooleanArray>\n    > var len = arr1.length\n    240\n    > var arr2 = new BooleanArray( buf, 8 )\n    <BooleanArray>\n    > len = arr2.length\n    232\n    > var arr3 = new BooleanArray( buf, 8, 20 )\n    <BooleanArray>\n    > len = arr3.length\n    20\n\n\nBooleanArray.from( src[, clbk[, thisArg]] )\n    Creates a new boolean array from an array-like object or an iterable.\n\n    A callback function is provided two arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    clbk: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: BooleanArray\n        A typed array.\n\n    Examples\n    --------\n    > function map( v ) { return !v };\n    > var src = [ true, false ];\n    > var arr = BooleanArray.from( src, map )\n    <BooleanArray>\n    > var len = arr.length\n    2\n    > var v = arr.get( 0 )\n    false\n    > v = arr.get( 1 )\n    true\n\n\nBooleanArray.of( element0[, element1[, ...elementN]] )\n    Creates a new boolean array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: bool\n        Array element.\n\n    element1: bool (optional)\n        Array element.\n\n    elementN: ...bool (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: BooleanArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = BooleanArray.of( true, false, false, true )\n    <BooleanArray>\n    > var len = arr.length\n    4\n\n\nBooleanArray.BYTES_PER_ELEMENT\n    The size of each array element in bytes.\n\n    Examples\n    --------\n    > var nbytes = BooleanArray.BYTES_PER_ELEMENT\n    1\n\n\nBooleanArray.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > var str = BooleanArray.name\n    'BooleanArray'\n\n\nBooleanArray.prototype.buffer\n    Pointer to the underlying data buffer.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 2 )\n    <BooleanArray>\n    > var buf = arr.buffer\n    <ArrayBuffer>\n\n\nBooleanArray.prototype.byteLength\n    Size of the array in bytes.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 10 )\n    <BooleanArray>\n    > var nbytes = arr.byteLength\n    10\n\n\nBooleanArray.prototype.byteOffset\n    Offset (in bytes) of the array from the start of its underlying\n    ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 10 )\n    <BooleanArray>\n    > var offset = arr.byteOffset\n    0\n    > var buf = new ArrayBuffer( 240 );\n    > arr = new BooleanArray( buf, 64 )\n    <BooleanArray>\n    > offset = arr.byteOffset\n    64\n\n\nBooleanArray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 10 )\n    <BooleanArray>\n    > arr.BYTES_PER_ELEMENT\n    1\n\n\nBooleanArray.prototype.length\n    The number of array elements.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 10 )\n    <BooleanArray>\n    > var len = arr.length\n    10\n\n\nBooleanArray.prototype.at( i )\n    Returns an array element located at integer position (index) `i`, with\n    support for noth nonnegative and negative integer positions.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n\n    Returns\n    -------\n    out: boolean|void\n        An array element.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, false, true ] )\n    <BooleanArray>\n    > var v = arr.at( 1 )\n    false\n    > v = arr.at( -1 )\n    true\n\n\nBooleanArray.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n    \n    start: integer\n        Source start index position.\n    \n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: BooleanArray\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, false, true ] )\n    <BooleanArray>\n    > arr.copyWithin( 0, 2 )\n    <BooleanArray>\n    > var v = arr.get( 0 )\n    false\n    > v = arr.get( 1 )\n    true\n\n\nBooleanArray.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var it = arr.entries();\n    > var v = it.next().value\n    [ 0, true ]\n    > v = it.next().value\n    [ 1, false ]\n    > v = it.next().value\n    [ 2, true ]\n    > var bool = it.next().done\n    true\n\n\nBooleanArray.prototype.every( predicate[, thisArg] )\n    Returns a boolean indicating whether all elements in the array pass a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all elements pass the test.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ true, true, true ] )\n    <BooleanArray>\n    > var bool = arr.every( predicate )\n    true\n\n\nBooleanArray.prototype.fill( value[, start[, end]] )\n    Returns a modified typed array filled with a fill value.\n\n    Parameters\n    ----------\n    value: boolean\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: BooleanArray\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new BooleanArray( 3 )\n    <BooleanArray>\n    > arr.fill( true );\n    > var v = arr.get( 0 )\n    true\n    > v = arr.get( 1 )\n    true\n    > v = arr.get( 2 )\n    true\n\n\nBooleanArray.prototype.filter( predicate[, thisArg] )\n    Returns a new array containing the elements of an array which pass a test\n    implemented by a predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: BooleanArray\n        A new typed array.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( v === true ); };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.filter( predicate )\n    <BooleanArray>\n    > var len = out.length\n    2\n    > var v = out.get( 0 )\n    true\n    > v = out.get( 1 )\n    true\n\n\nBooleanArray.prototype.find( predicate[, thisArg] )\n    Returns the first element in an array for which a predicate function returns\n    a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: boolean|void\n        Array element or `undefined`.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var v = arr.find( predicate )\n    true\n\n\nBooleanArray.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var idx = arr.findIndex( predicate )\n    0\n\n\nBooleanArray.prototype.findLast( predicate[, thisArg] )\n    Returns the last element in an array for which a predicate function returns\n    a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: boolean|void\n        Array element or `undefined`.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var v = arr.findLast( predicate )\n    true\n\n\nBooleanArray.prototype.findLastIndex( predicate[, thisArg] )\n    Returns the index of the last element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var idx = arr.findLastIndex( predicate )\n    2\n\n\nBooleanArray.prototype.forEach( clbk[, thisArg] )\n    Invokes a function once for each array element.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Examples\n    --------\n    > var str = '%';\n    > function clbk( v ) { str += v.toString() + '%'; };\n    > var arr = new BooleanArray( [ true, false, false, true ] )\n    <BooleanArray>\n    > arr.forEach( clbk );\n    > str\n    '%true%false%false%true%'\n\n\nBooleanArray.prototype.get( i )\n    Returns an array element located at integer position (index) `i`.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n\n    Returns\n    -------\n    out: boolean|void\n        Array element or `undefined`.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 10 )\n    <BooleanArray>\n    > arr.set( true, 0 );\n    > var v = arr.get( 0 )\n    true\n\n\nBooleanArray.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a provided value.\n\n    Parameters\n    ----------\n    searchElement: boolean\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true, true, true ] )\n    <BooleanArray>\n    > var bool = arr.includes( true )\n    true\n    > bool = arr.includes( false, 3 )\n    false\n\n\nBooleanArray.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the first index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: boolean\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true, true, true ] )\n    <BooleanArray>\n    > var idx = arr.indexOf( true )\n    0\n    > idx = arr.indexOf( false, 3 )\n    -1\n\n\nBooleanArray.prototype.join( [separator] )\n    Returns a new string by concatenating all array elements separated by a\n    separator string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        Separator string. Default: ','.\n\n    Returns\n    -------\n    out: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var str = arr.join()\n    'true,false,true'\n    > str = arr.join( '|' )\n    'true|false|true'\n\n\nBooleanArray.prototype.keys()\n    Returns an iterator for iterating over each index key in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array index keys.\n    \n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false ] )\n    <BooleanArray>\n    > var it = arr.keys();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().done\n    true\n\n\nBooleanArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the last index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: boolean\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: out.length-1.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, true, true, false, true ] )\n    <BooleanArray>\n    > var idx = arr.lastIndexOf( false )\n    3\n    > idx = arr.lastIndexOf( false, 2 )\n    -1\n\n\nBooleanArray.prototype.map( clbk[, thisArg] )\n    Returns a new array with each element being the result of a provided\n    callback function.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: BooleanArray\n        A new typed array.\n\n    Examples\n    --------\n    > function invert( v ) { return !v; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.map( invert )\n    <BooleanArray>\n    > var v = out.get( 0 )\n    false\n    > v = out.get( 1 )\n    true\n    > v = out.get( 2 )\n    false\n\n\nBooleanArray.prototype.reduce( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in order, passing\n    in the return value from the calculation on the preceding element and\n    returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.\n\n    initialValue: any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: any\n        Accumulated result.\n\n    Examples\n    --------\n    > function reducer( acc, v ) { return ( acc && v ); };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.reduce( reducer )\n    false\n\n\nBooleanArray.prototype.reduceRight( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in reverse order,\n    passing in the return value from the calculation on the preceding element\n    and returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.\n\n    initialValue: any (optional)\n        Initial accumulation value.\n    \n    Returns\n    -------\n    out: any\n        Accumulated result.\n    \n    Examples\n    --------\n    > function reducer( acc, v ) { return ( acc && v ); };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.reduceRight( reducer )\n    false\n\n\nBooleanArray.prototype.reverse()\n    Reverses the array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: BooleanArray\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, false ] )\n    <BooleanArray>\n    > arr.reverse();\n    > var v = arr.get( 0 )\n    false\n    > v = arr.get( 1 )\n    false\n    > v = arr.get( 2 )\n    true\n\n\nBooleanArray.prototype.set( v[, i] )\n    Sets one or more array elements.\n\n    If provided a single argument, the method sets array elements starting at\n    position (index) `i = 0`. To set elements starting elsewhere in the array,\n    provide an index argument `i`.\n\n    To set one or more array elements, provide an array-like object containing\n    truthy and falsy values.\n\n    Parameters\n    ----------\n    v: bool|BooleanArray|ArrayLikeObject\n        Boolean value or Boolean value array.\n\n    i: integer (optional)\n        Array index at which to start setting elements. Default: 0.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 2 )\n    <BooleanArray>\n    > arr.set( false );\n    > var v = arr.get( 0 )\n    false\n    > arr.set( true, 1 );\n    > v = arr.get( 1 )\n    true\n\n\nBooleanArray.prototype.slice( [start[, end]] )\n    Copies a portion of a typed array to a new typed array.\n\n    Parameters\n    ----------\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: BooleanArray\n        New typed array.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true, false, true ] )\n    <BooleanArray>\n    > var out = arr.slice( 1 )\n    <BooleanArray>\n    > var len = out.length\n    4\n    > var v = out.get( 0 )\n    false\n    > v = out.get( 1 )\n    true\n\n\nBooleanArray.prototype.some( predicate[, thisArg] )\n    Returns a boolean indicating whether at least one element passes a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one element passes the test.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ false, true, false ] )\n    <BooleanArray>\n    > var bool = arr.some( predicate )\n    true\n\n\nBooleanArray.prototype.sort( [compareFunction] )\n    Sorts an array in-place.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first boolean value for comparison.\n    - b: second boolean value for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Comparison function.\n\n    Returns\n    -------\n    out: BooleanArray\n        Modified array.\n\n    Examples\n    --------\n    > function compare( a, b ) { return a === true ? -1 : 1; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > arr.sort( compare );\n    > var v = arr.get( 0 )\n    true\n    > v = arr.get( 1 )\n    true\n    > v = arr.get( 2 )\n    false\n\n\nBooleanArray.prototype.subarray( [begin[, end]] )\n    Creates a new typed array view over the same underlying `ArrayBuffer` and\n    with the same underlying data type as the host array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: BooleanArray\n        New typed array view.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true, false, true ] )\n    <BooleanArray>\n    > var out = arr.subarray( 1, 3 )\n    <BooleanArray>\n    > var len = out.length\n    2\n    > var v = out.get( 0 )\n    false\n    > v = out.get( 1 )\n    true\n\n\nBooleanArray.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array (optional)\n        Locale identifier(s).\n    \n    options: Object (optional)\n        An object containing serialization options.\n    \n    Returns\n    -------\n    str: string\n        Local-specific string.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var str = arr.toLocaleString()\n    'true,false,true'\n\n\nBooleanArray.prototype.toReversed()\n    Returns a new typed array containing the elements in reversed order.\n\n    Returns\n    -------\n    out: BooleanArray\n        New typed array.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, false ] )\n    <BooleanArray>\n    > var out = arr.toReversed()\n    <BooleanArray>\n    > var v = out.get( 0 )\n    false\n    > v = out.get( 1 )\n    false\n    > v = out.get( 2 )\n    true\n\n\nBooleanArray.prototype.toSorted( [compareFunction] )\n    Returns a new typed array containing the elements in sorted order.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first boolean value for comparison.\n    - b: second boolean value for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Comparison function.\n\n    Returns\n    -------\n    out: BooleanArray\n        New typed array.\n\n    Examples\n    --------\n    > function compare( a, b ) { return a === true ? -1 : 1; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.toSorted( compare );\n    > var v = out.get( 0 )\n    true\n    > v = out.get( 1 )\n    true\n    > v = out.get( 2 )\n    false\n\n\nBooleanArray.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    out: string\n        String serialization of the array.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var str = arr.toString()\n    'true,false,true'\n\n\nBooleanArray.prototype.values()\n    Returns an iterator for iterating over each value in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array values.\n    \n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false ] )\n    <BooleanArray>\n    > var it = arr.values();\n    > var v = it.next().value\n    true\n    > v = it.next().value\n    false\n    > var bool = it.next().done\n    true\n\n\nBooleanArray.prototype.with( index, value )\n    Returns a new typed array with the element at a provided index replaced\n    with a provided value.\n\n    Parameters\n    ----------\n    index: integer\n        Element index.\n    \n    value: boolean\n        Element value.  \n\n    Returns\n    -------\n    out: BooleanArray\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.with( 0, false )\n    <BooleanArray>\n    > var v = out.get( 0 )\n    false\n\n\n    See Also\n    --------\n    ArrayBuffer","BooleanArray.from":"\nBooleanArray.from( src[, clbk[, thisArg]] )\n    Creates a new boolean array from an array-like object or an iterable.\n\n    A callback function is provided two arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    clbk: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: BooleanArray\n        A typed array.\n\n    Examples\n    --------\n    > function map( v ) { return !v };\n    > var src = [ true, false ];\n    > var arr = BooleanArray.from( src, map )\n    <BooleanArray>\n    > var len = arr.length\n    2\n    > var v = arr.get( 0 )\n    false\n    > v = arr.get( 1 )\n    true","BooleanArray.of":"\nBooleanArray.of( element0[, element1[, ...elementN]] )\n    Creates a new boolean array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: bool\n        Array element.\n\n    element1: bool (optional)\n        Array element.\n\n    elementN: ...bool (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: BooleanArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = BooleanArray.of( true, false, false, true )\n    <BooleanArray>\n    > var len = arr.length\n    4","BooleanArray.BYTES_PER_ELEMENT":"\nBooleanArray.BYTES_PER_ELEMENT\n    The size of each array element in bytes.\n\n    Examples\n    --------\n    > var nbytes = BooleanArray.BYTES_PER_ELEMENT\n    1","BooleanArray.name":"\nBooleanArray.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > var str = BooleanArray.name\n    'BooleanArray'","BooleanArray.prototype.buffer":"\nBooleanArray.prototype.buffer\n    Pointer to the underlying data buffer.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 2 )\n    <BooleanArray>\n    > var buf = arr.buffer\n    <ArrayBuffer>","BooleanArray.prototype.byteLength":"\nBooleanArray.prototype.byteLength\n    Size of the array in bytes.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 10 )\n    <BooleanArray>\n    > var nbytes = arr.byteLength\n    10","BooleanArray.prototype.byteOffset":"\nBooleanArray.prototype.byteOffset\n    Offset (in bytes) of the array from the start of its underlying\n    ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 10 )\n    <BooleanArray>\n    > var offset = arr.byteOffset\n    0\n    > var buf = new ArrayBuffer( 240 );\n    > arr = new BooleanArray( buf, 64 )\n    <BooleanArray>\n    > offset = arr.byteOffset\n    64","BooleanArray.prototype.BYTES_PER_ELEMENT":"\nBooleanArray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 10 )\n    <BooleanArray>\n    > arr.BYTES_PER_ELEMENT\n    1","BooleanArray.prototype.length":"\nBooleanArray.prototype.length\n    The number of array elements.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 10 )\n    <BooleanArray>\n    > var len = arr.length\n    10","BooleanArray.prototype.at":"\nBooleanArray.prototype.at( i )\n    Returns an array element located at integer position (index) `i`, with\n    support for noth nonnegative and negative integer positions.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n\n    Returns\n    -------\n    out: boolean|void\n        An array element.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, false, true ] )\n    <BooleanArray>\n    > var v = arr.at( 1 )\n    false\n    > v = arr.at( -1 )\n    true","BooleanArray.prototype.copyWithin":"\nBooleanArray.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n    \n    start: integer\n        Source start index position.\n    \n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: BooleanArray\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, false, true ] )\n    <BooleanArray>\n    > arr.copyWithin( 0, 2 )\n    <BooleanArray>\n    > var v = arr.get( 0 )\n    false\n    > v = arr.get( 1 )\n    true","BooleanArray.prototype.entries":"\nBooleanArray.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var it = arr.entries();\n    > var v = it.next().value\n    [ 0, true ]\n    > v = it.next().value\n    [ 1, false ]\n    > v = it.next().value\n    [ 2, true ]\n    > var bool = it.next().done\n    true","BooleanArray.prototype.every":"\nBooleanArray.prototype.every( predicate[, thisArg] )\n    Returns a boolean indicating whether all elements in the array pass a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all elements pass the test.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ true, true, true ] )\n    <BooleanArray>\n    > var bool = arr.every( predicate )\n    true","BooleanArray.prototype.fill":"\nBooleanArray.prototype.fill( value[, start[, end]] )\n    Returns a modified typed array filled with a fill value.\n\n    Parameters\n    ----------\n    value: boolean\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: BooleanArray\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new BooleanArray( 3 )\n    <BooleanArray>\n    > arr.fill( true );\n    > var v = arr.get( 0 )\n    true\n    > v = arr.get( 1 )\n    true\n    > v = arr.get( 2 )\n    true","BooleanArray.prototype.filter":"\nBooleanArray.prototype.filter( predicate[, thisArg] )\n    Returns a new array containing the elements of an array which pass a test\n    implemented by a predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: BooleanArray\n        A new typed array.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( v === true ); };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.filter( predicate )\n    <BooleanArray>\n    > var len = out.length\n    2\n    > var v = out.get( 0 )\n    true\n    > v = out.get( 1 )\n    true","BooleanArray.prototype.find":"\nBooleanArray.prototype.find( predicate[, thisArg] )\n    Returns the first element in an array for which a predicate function returns\n    a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: boolean|void\n        Array element or `undefined`.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var v = arr.find( predicate )\n    true","BooleanArray.prototype.findIndex":"\nBooleanArray.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var idx = arr.findIndex( predicate )\n    0","BooleanArray.prototype.findLast":"\nBooleanArray.prototype.findLast( predicate[, thisArg] )\n    Returns the last element in an array for which a predicate function returns\n    a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: boolean|void\n        Array element or `undefined`.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var v = arr.findLast( predicate )\n    true","BooleanArray.prototype.findLastIndex":"\nBooleanArray.prototype.findLastIndex( predicate[, thisArg] )\n    Returns the index of the last element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var idx = arr.findLastIndex( predicate )\n    2","BooleanArray.prototype.forEach":"\nBooleanArray.prototype.forEach( clbk[, thisArg] )\n    Invokes a function once for each array element.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Examples\n    --------\n    > var str = '%';\n    > function clbk( v ) { str += v.toString() + '%'; };\n    > var arr = new BooleanArray( [ true, false, false, true ] )\n    <BooleanArray>\n    > arr.forEach( clbk );\n    > str\n    '%true%false%false%true%'","BooleanArray.prototype.get":"\nBooleanArray.prototype.get( i )\n    Returns an array element located at integer position (index) `i`.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n\n    Returns\n    -------\n    out: boolean|void\n        Array element or `undefined`.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 10 )\n    <BooleanArray>\n    > arr.set( true, 0 );\n    > var v = arr.get( 0 )\n    true","BooleanArray.prototype.includes":"\nBooleanArray.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a provided value.\n\n    Parameters\n    ----------\n    searchElement: boolean\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true, true, true ] )\n    <BooleanArray>\n    > var bool = arr.includes( true )\n    true\n    > bool = arr.includes( false, 3 )\n    false","BooleanArray.prototype.indexOf":"\nBooleanArray.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the first index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: boolean\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true, true, true ] )\n    <BooleanArray>\n    > var idx = arr.indexOf( true )\n    0\n    > idx = arr.indexOf( false, 3 )\n    -1","BooleanArray.prototype.join":"\nBooleanArray.prototype.join( [separator] )\n    Returns a new string by concatenating all array elements separated by a\n    separator string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        Separator string. Default: ','.\n\n    Returns\n    -------\n    out: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var str = arr.join()\n    'true,false,true'\n    > str = arr.join( '|' )\n    'true|false|true'","BooleanArray.prototype.keys":"\nBooleanArray.prototype.keys()\n    Returns an iterator for iterating over each index key in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array index keys.\n    \n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false ] )\n    <BooleanArray>\n    > var it = arr.keys();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().done\n    true","BooleanArray.prototype.lastIndexOf":"\nBooleanArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the last index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: boolean\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: out.length-1.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, true, true, false, true ] )\n    <BooleanArray>\n    > var idx = arr.lastIndexOf( false )\n    3\n    > idx = arr.lastIndexOf( false, 2 )\n    -1","BooleanArray.prototype.map":"\nBooleanArray.prototype.map( clbk[, thisArg] )\n    Returns a new array with each element being the result of a provided\n    callback function.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: BooleanArray\n        A new typed array.\n\n    Examples\n    --------\n    > function invert( v ) { return !v; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.map( invert )\n    <BooleanArray>\n    > var v = out.get( 0 )\n    false\n    > v = out.get( 1 )\n    true\n    > v = out.get( 2 )\n    false","BooleanArray.prototype.reduce":"\nBooleanArray.prototype.reduce( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in order, passing\n    in the return value from the calculation on the preceding element and\n    returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.\n\n    initialValue: any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: any\n        Accumulated result.\n\n    Examples\n    --------\n    > function reducer( acc, v ) { return ( acc && v ); };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.reduce( reducer )\n    false","BooleanArray.prototype.reduceRight":"\nBooleanArray.prototype.reduceRight( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in reverse order,\n    passing in the return value from the calculation on the preceding element\n    and returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.\n\n    initialValue: any (optional)\n        Initial accumulation value.\n    \n    Returns\n    -------\n    out: any\n        Accumulated result.\n    \n    Examples\n    --------\n    > function reducer( acc, v ) { return ( acc && v ); };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.reduceRight( reducer )\n    false","BooleanArray.prototype.reverse":"\nBooleanArray.prototype.reverse()\n    Reverses the array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: BooleanArray\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, false ] )\n    <BooleanArray>\n    > arr.reverse();\n    > var v = arr.get( 0 )\n    false\n    > v = arr.get( 1 )\n    false\n    > v = arr.get( 2 )\n    true","BooleanArray.prototype.set":"\nBooleanArray.prototype.set( v[, i] )\n    Sets one or more array elements.\n\n    If provided a single argument, the method sets array elements starting at\n    position (index) `i = 0`. To set elements starting elsewhere in the array,\n    provide an index argument `i`.\n\n    To set one or more array elements, provide an array-like object containing\n    truthy and falsy values.\n\n    Parameters\n    ----------\n    v: bool|BooleanArray|ArrayLikeObject\n        Boolean value or Boolean value array.\n\n    i: integer (optional)\n        Array index at which to start setting elements. Default: 0.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( 2 )\n    <BooleanArray>\n    > arr.set( false );\n    > var v = arr.get( 0 )\n    false\n    > arr.set( true, 1 );\n    > v = arr.get( 1 )\n    true","BooleanArray.prototype.slice":"\nBooleanArray.prototype.slice( [start[, end]] )\n    Copies a portion of a typed array to a new typed array.\n\n    Parameters\n    ----------\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: BooleanArray\n        New typed array.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true, false, true ] )\n    <BooleanArray>\n    > var out = arr.slice( 1 )\n    <BooleanArray>\n    > var len = out.length\n    4\n    > var v = out.get( 0 )\n    false\n    > v = out.get( 1 )\n    true","BooleanArray.prototype.some":"\nBooleanArray.prototype.some( predicate[, thisArg] )\n    Returns a boolean indicating whether at least one element passes a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one element passes the test.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === true; };\n    > var arr = new BooleanArray( [ false, true, false ] )\n    <BooleanArray>\n    > var bool = arr.some( predicate )\n    true","BooleanArray.prototype.sort":"\nBooleanArray.prototype.sort( [compareFunction] )\n    Sorts an array in-place.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first boolean value for comparison.\n    - b: second boolean value for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Comparison function.\n\n    Returns\n    -------\n    out: BooleanArray\n        Modified array.\n\n    Examples\n    --------\n    > function compare( a, b ) { return a === true ? -1 : 1; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > arr.sort( compare );\n    > var v = arr.get( 0 )\n    true\n    > v = arr.get( 1 )\n    true\n    > v = arr.get( 2 )\n    false","BooleanArray.prototype.subarray":"\nBooleanArray.prototype.subarray( [begin[, end]] )\n    Creates a new typed array view over the same underlying `ArrayBuffer` and\n    with the same underlying data type as the host array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: BooleanArray\n        New typed array view.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true, false, true ] )\n    <BooleanArray>\n    > var out = arr.subarray( 1, 3 )\n    <BooleanArray>\n    > var len = out.length\n    2\n    > var v = out.get( 0 )\n    false\n    > v = out.get( 1 )\n    true","BooleanArray.prototype.toLocaleString":"\nBooleanArray.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array (optional)\n        Locale identifier(s).\n    \n    options: Object (optional)\n        An object containing serialization options.\n    \n    Returns\n    -------\n    str: string\n        Local-specific string.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var str = arr.toLocaleString()\n    'true,false,true'","BooleanArray.prototype.toReversed":"\nBooleanArray.prototype.toReversed()\n    Returns a new typed array containing the elements in reversed order.\n\n    Returns\n    -------\n    out: BooleanArray\n        New typed array.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, false ] )\n    <BooleanArray>\n    > var out = arr.toReversed()\n    <BooleanArray>\n    > var v = out.get( 0 )\n    false\n    > v = out.get( 1 )\n    false\n    > v = out.get( 2 )\n    true","BooleanArray.prototype.toSorted":"\nBooleanArray.prototype.toSorted( [compareFunction] )\n    Returns a new typed array containing the elements in sorted order.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first boolean value for comparison.\n    - b: second boolean value for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Comparison function.\n\n    Returns\n    -------\n    out: BooleanArray\n        New typed array.\n\n    Examples\n    --------\n    > function compare( a, b ) { return a === true ? -1 : 1; };\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.toSorted( compare );\n    > var v = out.get( 0 )\n    true\n    > v = out.get( 1 )\n    true\n    > v = out.get( 2 )\n    false","BooleanArray.prototype.toString":"\nBooleanArray.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    out: string\n        String serialization of the array.\n\n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var str = arr.toString()\n    'true,false,true'","BooleanArray.prototype.values":"\nBooleanArray.prototype.values()\n    Returns an iterator for iterating over each value in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array values.\n    \n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false ] )\n    <BooleanArray>\n    > var it = arr.values();\n    > var v = it.next().value\n    true\n    > v = it.next().value\n    false\n    > var bool = it.next().done\n    true","BooleanArray.prototype.with":"\nBooleanArray.prototype.with( index, value )\n    Returns a new typed array with the element at a provided index replaced\n    with a provided value.\n\n    Parameters\n    ----------\n    index: integer\n        Element index.\n    \n    value: boolean\n        Element value.  \n\n    Returns\n    -------\n    out: BooleanArray\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new BooleanArray( [ true, false, true ] )\n    <BooleanArray>\n    > var out = arr.with( 0, false )\n    <BooleanArray>\n    > var v = out.get( 0 )\n    false\n\n\n    See Also\n    --------\n    ArrayBuffer","broadcastArray":"\nbroadcastArray( x, shape )\n    Broadcasts an ndarray to a specified shape.\n\n    The returned array is a read-only view on the input array data buffer. The\n    view is typically *not* contiguous. As more than one element of a returned\n    view may refer to the same memory location, writing to the input array may\n    affect multiple elements. If you need to write to the input array, copy the\n    input array before broadcasting.\n\n    The function throws an error if a provided ndarray is incompatible with a\n    provided shape.\n\n    The function always returns a new ndarray instance even if the input ndarray\n    shape and the desired shape are the same.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    shape: ArrayLikeObject\n        Desired shape.\n\n    Returns\n    -------\n    out: ndarray\n        Broadcasted array.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n    <ndarray>\n    > var sh = x.shape\n    [ 2, 2 ]\n    > var y = broadcastArray( x, [ 3, 2, 2 ] )\n    <ndarray>\n    > sh = y.shape\n    [ 3, 2, 2 ]\n    > var v = y.get( 0, 0, 0 )\n    1\n    > v = y.get( 0, 0, 1 )\n    2\n    > v = y.get( 0, 1, 0 )\n    3\n    > v = y.get( 0, 1, 1 )\n    4\n    > v = y.get( 1, 0, 0 )\n    1\n    > v = y.get( 1, 1, 0 )\n    3\n    > v = y.get( 2, 0, 0 )\n    1\n    > v = y.get( 2, 1, 1 )\n    4\n\n    See Also\n    --------\n    array, broadcastArrays, ndarray, maybeBroadcastArray\n","broadcastArrays":"\nbroadcastArrays( ...arrays )\n    Broadcasts ndarrays to a common shape.\n\n    The function supports two (mutually exclusive) means of providing ndarray\n    arguments:\n\n    1. Providing a single array containing ndarray arguments.\n    2. Providing ndarray arguments as separate arguments.\n\n    The returned arrays are read-only views on their respective underlying\n    array data buffers. The views are typically **not** contiguous. As more\n    than one element of a returned view may refer to the same memory location,\n    writing to a view may affect multiple elements. If you need to write to an\n    input array, copy the array before broadcasting.\n\n    The function throws an error if provided broadcast-incompatible ndarrays.\n\n    The function always returns new ndarray instances even if an input ndarray\n    and the broadcasted shape are the same.\n\n    Parameters\n    ----------\n    arrays: ...ndarray|ArrayLikeObject<ndarray>\n        Array arguments.\n\n    Returns\n    -------\n    out: Array<ndarray>\n        Broadcasted arrays.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n    <ndarray>\n    > var sh = x.shape\n    [ 2, 2 ]\n    > var y = ndzeros( [ 3, 2, 2 ] )\n    <ndarray>\n    > var out = broadcastArrays( [ x, y ] )\n    [ <ndarray>, <ndarray> ]\n\n    // Retrieve the broadcasted \"x\" array:\n    > var bx = out[ 0 ]\n    <ndarray>\n    > sh = bx.shape\n    [ 3, 2, 2 ]\n\n    // Retrieve broadcasted elements...\n    > var v = bx.get( 0, 0, 0 )\n    1\n    > v = bx.get( 0, 0, 1 )\n    2\n    > v = bx.get( 0, 1, 0 )\n    3\n    > v = bx.get( 0, 1, 1 )\n    4\n    > v = bx.get( 1, 0, 0 )\n    1\n    > v = bx.get( 1, 1, 0 )\n    3\n    > v = bx.get( 2, 0, 0 )\n    1\n    > v = bx.get( 2, 1, 1 )\n    4\n\n    See Also\n    --------\n    array, broadcastArray, ndarray, maybeBroadcastArrays\n","Buffer":"\nBuffer\n    Buffer constructor.\n\n\nBuffer( size )\n    Allocates a buffer having a specified number of bytes.\n\n    Parameters\n    ----------\n    size: integer\n        Number of bytes to allocate.\n\n    Returns\n    -------\n    out: Buffer\n        Buffer instance.\n\n    Examples\n    --------\n    > var b = new Buffer( 4 )\n    <Buffer>\n\n\nBuffer( buffer )\n    Copies buffer data to a new Buffer instance.\n\n    Parameters\n    ----------\n    buffer: Buffer\n        Buffer to copy from.\n\n    Returns\n    -------\n    out: Buffer\n        Buffer instance.\n\n    Examples\n    --------\n    > var b1 = new Buffer( [ 1, 2, 3, 4 ] );\n    > var b2 = new Buffer( b1 )\n    <Buffer>[ 1, 2, 3, 4 ]\n\n\nBuffer( array )\n    Allocates a buffer using an array of octets.\n\n    Parameters\n    ----------\n    array: Array\n        Array of octets.\n\n    Returns\n    -------\n    out: Buffer\n        Buffer instance.\n\n    Examples\n    --------\n    > var b = new Buffer( [ 1, 2, 3, 4 ] )\n    <Buffer>[ 1, 2, 3, 4 ]\n\n\nBuffer( str[, encoding] )\n    Allocates a buffer containing a provided string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    encoding: string (optional)\n        Character encoding. Default: 'utf8'.\n\n    Returns\n    -------\n    out: Buffer\n        Buffer instance.\n\n    Examples\n    --------\n    > var b = new Buffer( 'beep boop' )\n    <Buffer>\n\n\nTODO: add methods and properties\n\n\n    See Also\n    --------\n    ArrayBuffer\n","buffer2json":"\nbuffer2json( buffer )\n    Returns a JSON representation of a buffer.\n\n    Parameters\n    ----------\n    buffer: Buffer\n        Buffer to serialize.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    out.type: string\n        Value type. The assigned value is always \"Buffer\".\n\n    out.data: Array\n        Buffer data.\n\n    Examples\n    --------\n    > var buf = new allocUnsafe( 2 );\n    > buf[ 0 ] = 1;\n    > buf[ 1 ] = 2;\n    > var json = buffer2json( buf )\n    { 'type': 'Buffer', 'data': [ 1, 2 ] }\n\n    See Also\n    --------\n    typedarray2json, reviveBuffer\n","BYTE_ORDER":"\nBYTE_ORDER\n    Platform byte order.\n\n    Possible values:\n\n    - 'little-endian'\n    - 'big-endian'\n    - 'mixed-endian'\n    - 'unknown'\n\n    Examples\n    --------\n    > BYTE_ORDER\n    <string>\n\n    See Also\n    --------\n    IS_BIG_ENDIAN, IS_LITTLE_ENDIAN\n","camelcase":"\ncamelcase( str )\n    Converts a string to camel case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Camel-cased string.\n\n    Examples\n    --------\n    > var out = camelcase( 'Hello World!' )\n    'helloWorld'\n    > out = camelcase( 'beep boop' )\n    'beepBoop'\n\n    See Also\n    --------\n    constantcase, kebabcase, pascalcase, snakecase","capitalize":"\ncapitalize( str )\n    Capitalizes the first character in a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Capitalized string.\n\n    Examples\n    --------\n    > var out = capitalize( 'beep' )\n    'Beep'\n    > out = capitalize( 'Boop' )\n    'Boop'\n\n    See Also\n    --------\n    uncapitalize, uppercase\n","capitalizeKeys":"\ncapitalizeKeys( obj )\n    Converts the first letter of each object key to uppercase.\n\n    The function only transforms own properties. Hence, the function does not\n    transform inherited properties.\n\n    The function shallow copies key values.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > var obj = { 'aa': 1, 'bb': 2 };\n    > var out = capitalizeKeys( obj )\n    { 'Aa': 1, 'Bb': 2 }\n\n    See Also\n    --------\n    uncapitalizeKeys, uppercaseKeys\n","CATALAN":"\nCATALAN\n    Catalan's constant.\n\n    Examples\n    --------\n    > CATALAN\n    0.915965594177219\n\n","CBRT_EPS":"\nCBRT_EPS\n    Cube root of double-precision floating-point epsilon.\n\n    Examples\n    --------\n    > CBRT_EPS\n    0.0000060554544523933395\n\n    See Also\n    --------\n    EPS, SQRT_EPS\n","CDC_NCHS_US_BIRTHS_1969_1988":"\nCDC_NCHS_US_BIRTHS_1969_1988()\n    Returns US birth data from 1969 to 1988, as provided by the Center for\n    Disease Control and Prevention's National Center for Health Statistics.\n\n    Returns\n    -------\n    out: Array<Object>\n        Birth data.\n\n    Examples\n    --------\n    > var data = CDC_NCHS_US_BIRTHS_1969_1988()\n    [ {...}, ... ]\n\n    See Also\n    --------\n    CDC_NCHS_US_BIRTHS_1994_2003, SSA_US_BIRTHS_2000_2014\n","CDC_NCHS_US_BIRTHS_1994_2003":"\nCDC_NCHS_US_BIRTHS_1994_2003()\n    Returns US birth data from 1994 to 2003, as provided by the Center for\n    Disease Control and Prevention's National Center for Health Statistics.\n\n    Returns\n    -------\n    out: Array<Object>\n        Birth data.\n\n    Examples\n    --------\n    > var data = CDC_NCHS_US_BIRTHS_1994_2003()\n    [ {...}, ... ]\n\n    See Also\n    --------\n    CDC_NCHS_US_BIRTHS_1969_1988, SSA_US_BIRTHS_2000_2014\n","CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013":"\nCDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n    Returns US infant mortality data, by race, from 1915 to 2013, as provided by\n    the Center for Disease Control and Prevention's National Center for Health\n    Statistics.\n\n    All birth data by race before 1980 are based on race of the child. Starting\n    in 1980, birth data by race are based on race of the mother. Birth data are\n    used to calculate infant mortality rate.\n\n    Returns\n    -------\n    out: Array<Object>\n        Infant mortality data.\n\n    Examples\n    --------\n    > var data = CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n    { 'black': [...], 'white': [...] }\n\n","chdir":"\nchdir( path )\n    Changes the current working directory.\n\n    If unable to set the current working directory (e.g., due to a non-existent\n    path), the function returns an error; otherwise, the function returns\n    `null`.\n\n    Parameters\n    ----------\n    path: string\n        Desired working directory.\n\n    Returns\n    -------\n    err: Error|null\n        Error object or null.\n\n    Examples\n    --------\n    > var err = chdir( '/path/to/current/working/directory' )\n\n    See Also\n    --------\n    cwd\n","chi2gof":"\nchi2gof( x, y[, ...args][, options] )\n    Performs a chi-square goodness-of-fit test.\n\n    A chi-square goodness-of-fit test is computed for the null hypothesis that\n    the values of `x` come from the discrete probability distribution specified\n    by `y`.\n\n    The second argument can either be expected frequencies, population\n    probabilities summing to one, or a discrete probability distribution name to\n    test against.\n\n    When providing a discrete probability distribution name, distribution\n    parameters *must* be supplied as additional arguments.\n\n    The function returns an object containing the test statistic, p-value, and\n    decision.\n\n    By default, the p-value is computed using a chi-square distribution with\n    `k-1` degrees of freedom, where `k` is the length of `x`.\n\n    If provided distribution arguments are estimated (e.g., via maximum\n    likelihood estimation), the degrees of freedom should be corrected. Set the\n    `ddof` option to use `k-1-n` degrees of freedom, where `n` is the degrees of\n    freedom adjustment.\n\n    The chi-square approximation may be incorrect if the observed or expected\n    frequencies in each category are too small. Common practice is to require\n    frequencies greater than five.\n\n    Instead of relying on chi-square approximation to calculate the p-value, one\n    can use Monte Carlo simulation. When the `simulate` option is `true`, the\n    simulation is performed by re-sampling from the discrete probability\n    distribution specified by `y`.\n\n    Parameters\n    ----------\n    x: ndarray|Array<number>|TypedArray\n        Observation frequencies.\n\n    y: ndarray|Array<number>|TypedArray|string\n        Expected frequencies, population probabilities, or a discrete\n        probability distribution name.\n\n    args: ...number (optional)\n        Distribution parameters. Distribution parameters will be passed to a\n        probability mass function (PMF) as arguments.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Significance level of the hypothesis test. Must be on the interval\n        [0,1]. Default: 0.05.\n\n    options.ddof: number (optional)\n        Delta degrees of freedom adjustment. Default: 0.\n\n    options.simulate: boolean (optional)\n        Boolean indicating whether to calculate p-values by Monte Carlo\n        simulation. The simulation is performed by re-sampling from the discrete\n        distribution specified by `y`. Default: false.\n\n    options.iterations: number (optional)\n        Number of Monte Carlo iterations. Default: 500.\n\n    Returns\n    -------\n    out: Object\n        Test results object.\n\n    out.alpha: number\n        Significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        Test p-value.\n\n    out.statistic: number\n        Test statistic.\n\n    out.df: number|null\n        Degrees of freedom.\n\n    out.method: string\n        Test name.\n\n    out.toString: Function\n        Serializes results as formatted output.\n\n    out.toJSON: Function\n        Serializes results as JSON.\n\n    Examples\n    --------\n    // Provide expected probabilities...\n    > var x = [ 89, 37, 30, 28, 2 ];\n    > var p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\n    > var out = chi2gof( x, p );\n    > var o = out.toJSON()\n    { 'pValue': ~0.0406, 'statistic': ~9.9901, ... }\n    > out.toString()\n\n    // Set significance level...\n    > var opts = { 'alpha': 0.01 };\n    > out = chi2gof( x, p, opts );\n    > out.toString()\n\n    // Calculate the test p-value via Monte Carlo simulation...\n    > x = [ 89, 37, 30, 28, 2 ];\n    > p = [ 0.40, 0.20, 0.20, 0.15, 0.05 ];\n    > opts = { 'simulate': true, 'iterations': 1000 };\n    > out = chi2gof( x, p, opts );\n    > out.toString()\n\n    // Verify that data comes from Poisson distribution...\n    > var lambda = 3.0;\n    > var rpois = base.random.poisson.factory( lambda );\n    > var len = 400;\n    > x = [];\n    > for ( var i = 0; i < len; i++ ) { x.push( rpois() ); };\n\n    // Generate a frequency table...\n    > var freqs = new Int32Array( len );\n    > for ( i = 0; i < len; i++ ) { freqs[ x[ i ] ] += 1; };\n    > out = chi2gof( freqs, 'poisson', lambda );\n    > out.toString()\n\n","chi2test":"\nchi2test( x[, options] )\n    Performs a chi-square independence test.\n\n    For a two-way contingency table, the function computes a chi-square\n    independence test for the null hypothesis that the joint distribution of the\n    cell counts is the product of the row and column marginals (i.e. that the\n    row and column variables are independent).\n\n    The chi-square approximation may be incorrect if the observed or expected\n    frequencies in each category are too small. Common practice is to require\n    frequencies greater than five. The Yates' continuity correction is enabled\n    by default for 2x2 tables to account for this, although it tends to\n    over-correct.\n\n    The function returns an object containing the test statistic, p-value, and\n    decision.\n\n    Parameters\n    ----------\n    x: ndarray|Array<Collection<number>>\n        Two-way table of observed frequencies.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Significance level of the hypothesis test. Must be on the interval\n        [0,1]. Default: 0.05.\n\n    options.correct: boolean (optional)\n        Boolean indicating whether to use Yates' continuity correction when\n        provided a 2x2 contingency table. Default: true.\n\n    Returns\n    -------\n    out: Object\n        Test results object.\n\n    out.alpha: number\n        Significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        Test p-value.\n\n    out.statistic: number\n        Test statistic.\n\n    out.df: number\n        Degrees of freedom.\n\n    out.expected: ndarray\n        Expected frequencies.\n\n    out.method: string\n        Test name.\n\n    out.toString: Function\n        Serializes results as formatted output.\n\n    out.toJSON: Function\n        Serializes results as JSON.\n\n    Examples\n    --------\n    > var x = [ [ 20, 30 ], [ 30, 20 ] ];\n    > var out = chi2test( x );\n    > var o = out.toJSON()\n    { 'rejected': false, 'pValue': ~0.072, 'statistic': 3.24, ... }\n    > out.toString()\n\n    // Set significance level...\n    > var opts = { 'alpha': 0.1 };\n    > out = chi2test( x, opts );\n    > o = out.toJSON()\n    { 'rejected': true, 'pValue': ~0.072, 'statistic': 3.24, ... }\n    > out.toString()\n\n    // Disable Yates' continuity correction (primarily used with small counts):\n    > opts = { 'correct': false };\n    > out = chi2test( x, opts );\n    > out.toString()\n\n","circarray2iterator":"\ncircarray2iterator( src[, options][, mapFcn[, thisArg]] )\n    Returns an iterator which repeatedly iterates over the elements of an array-\n    like object.\n\n    When invoked, an input function is provided four arguments:\n\n    - value: iterated value.\n    - index: iterated value index.\n    - n: iteration count.\n    - src: source array-like object.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an array's `@@iterator` method, regardless of whether this method is\n    defined. To convert an array to an implementation defined iterator, invoke\n    this method directly.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Array-like object from which to create the iterator.\n\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    options.dir: integer (optional)\n        Iteration direction. If set to `-1`, an iterator iterates over elements\n        from right-to-left. Default: 1.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = circarray2iterator( [ 1, 2, 3, 4 ] );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    array2iterator, stridedarray2iterator\n","circularArrayStream":"\ncircularArrayStream( src[, options] )\n    Creates a readable stream from an array-like object which repeatedly\n    iterates over the provided value's elements.\n\n    In object mode, `null` is a reserved value. If an array contains `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or filter `null` values\n    prior to invocation.\n\n    In binary mode, if an array contains `undefined` values, the stream will\n    emit an error. Consider providing a custom serialization function or\n    filtering `undefined` values prior to invocation.\n\n    If a serialization function fails to return a string or Buffer, the stream\n    emits an error.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Source value.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing the stream.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize streamed\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    options.dir: integer (optional)\n        Iteration direction. If set to `-1`, a stream iterates over elements\n        from right-to-left. Default: 1.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 15 };\n    > var s = circularArrayStream( [ 1, 2, 3 ], opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\ncircularArrayStream.factory( [options] )\n    Returns a function for creating readable streams from array-like objects\n    which repeatedly iterate over the elements of provided values.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing streaming.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize streamed\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    options.dir: integer (optional)\n        Iteration direction. If set to `-1`, a stream iterates over elements\n        from right-to-left. Default: 1.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = circularArrayStream.factory( opts );\n\n\ncircularArrayStream.objectMode( src[, options] )\n    Returns an \"objectMode\" readable stream from an array-like object which\n    repeatedly iterates over a provided value's elements.\n\n    In object mode, `null` is a reserved value. If an array contains `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or filter `null` values\n    prior to invocation.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Source value.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before pausing streaming.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    options.dir: integer (optional)\n        Iteration direction. If set to `-1`, a stream iterates over elements\n        from right-to-left. Default: 1.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 15 };\n    > var s = circularArrayStream.objectMode( [ 1, 2, 3 ], opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    arrayStream, iteratorStream, stridedArrayStream\n","circularArrayStream.factory":"\ncircularArrayStream.factory( [options] )\n    Returns a function for creating readable streams from array-like objects\n    which repeatedly iterate over the elements of provided values.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing streaming.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize streamed\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    options.dir: integer (optional)\n        Iteration direction. If set to `-1`, a stream iterates over elements\n        from right-to-left. Default: 1.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = circularArrayStream.factory( opts );","circularArrayStream.objectMode":"\ncircularArrayStream.objectMode( src[, options] )\n    Returns an \"objectMode\" readable stream from an array-like object which\n    repeatedly iterates over a provided value's elements.\n\n    In object mode, `null` is a reserved value. If an array contains `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or filter `null` values\n    prior to invocation.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Source value.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before pausing streaming.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    options.dir: integer (optional)\n        Iteration direction. If set to `-1`, a stream iterates over elements\n        from right-to-left. Default: 1.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 15 };\n    > var s = circularArrayStream.objectMode( [ 1, 2, 3 ], opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    arrayStream, iteratorStream, stridedArrayStream","CircularBuffer":"\nCircularBuffer( buffer )\n    Circular buffer constructor.\n\n    Parameters\n    ----------\n    buffer: integer|ArrayLike\n        Buffer size or an array-like object to use as the underlying buffer.\n\n    Returns\n    -------\n    buf: Object\n        Circular buffer data structure.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.push( 'foo' );\n    > b.push( 'bar' );\n    > b.push( 'beep' );\n    > b.length\n    3\n    > b.count\n    3\n    > b.push( 'boop' )\n    'foo'\n\n\nCircularBuffer.prototype.clear()\n    Clears a buffer.\n\n    Returns\n    -------\n    out: Object\n        Circular buffer instance.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.push( 'foo' );\n    > b.push( 'bar' );\n    > b.push( 'beep' );\n    > b.count\n    3\n    > b.clear();\n    > b.count\n    0\n\n\nCircularBuffer.prototype.count\n    Read-only property returning the number of elements currently in the buffer.\n\n    Returns\n    -------\n    out: integer\n        Number of elements currently in the buffer.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.count\n    0\n    > b.push( 'foo' );\n    > b.count\n    1\n    > b.push( 'bar' );\n    > b.count\n    2\n\n\nCircularBuffer.prototype.full\n    Read-only property returning a boolean indicating whether a circular buffer\n    is full.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether a circular buffer is full.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.full\n    false\n    > b.push( 'foo' );\n    > b.push( 'bar' );\n    > b.push( 'beep' );\n    > b.full\n    true\n\n\nCircularBuffer.prototype.iterator( [niters] )\n    Returns an iterator for iterating over a circular buffer.\n\n    A returned iterator does not iterate over partially full buffers.\n\n    Parameters\n    ----------\n    niters: integer (optional)\n        Number of iterations. Default: infinity.\n\n    Returns\n    -------\n    out: Iterator\n        Iterator.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.push( 'foo' );\n    > b.push( 'bar' );\n    > b.push( 'beep' );\n    > b.push( 'boop' );\n    > var it = b.iterator( b.length );\n    > var v = it.next().value\n    'bar'\n    > v = it.next().value\n    'beep'\n    > v = it.next().value\n    'boop'\n    > var bool = it.next().done\n    true\n\n\nCircularBuffer.prototype.length\n    Read-only property returning the buffer length (i.e., capacity).\n\n    Returns\n    -------\n    out: integer\n        Buffer length.\n\n    Examples\n    --------\n    > var b = CircularBuffer( [ 0, 0, 0 ] );\n    > var len = b.length\n    3\n\n\nCircularBuffer.prototype.push( value )\n    Adds a value to a circular buffer.\n\n    Parameters\n    ----------\n    value: any\n        Value to add.\n\n    Returns\n    -------\n    out: any\n        Removed element (or undefined).\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.push( 'foo' )\n    undefined\n    > b.push( 'bar' )\n    undefined\n    > b.push( 'beep' )\n    undefined\n    > b.push( 'boop' )\n    'foo'\n\n\nCircularBuffer.prototype.toArray()\n    Returns an array of circular buffer values.\n\n    Returns\n    -------\n    out: Array\n        Circular buffer values.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.push( 'foo' );\n    > b.push( 'bar' );\n    > b.push( 'beep' );\n    > b.push( 'boop' );\n    > var vals = b.toArray()\n    [ 'bar', 'beep', 'boop' ]\n\n\nCircularBuffer.prototype.toJSON()\n    Serializes a circular buffer as JSON.\n\n    Returns\n    -------\n    out: Object\n        Serialized circular buffer.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.push( 'foo' );\n    > b.push( 'bar' );\n    > b.push( 'beep' );\n    > b.push( 'boop' );\n    > var o = b.toJSON()\n    {'type':'circular-buffer','length':3,'data':['bar','beep','boop']}\n\n    See Also\n    --------\n    FIFO, Stack\n","CircularBuffer.prototype.clear":"\nCircularBuffer.prototype.clear()\n    Clears a buffer.\n\n    Returns\n    -------\n    out: Object\n        Circular buffer instance.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.push( 'foo' );\n    > b.push( 'bar' );\n    > b.push( 'beep' );\n    > b.count\n    3\n    > b.clear();\n    > b.count\n    0","CircularBuffer.prototype.count":"\nCircularBuffer.prototype.count\n    Read-only property returning the number of elements currently in the buffer.\n\n    Returns\n    -------\n    out: integer\n        Number of elements currently in the buffer.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.count\n    0\n    > b.push( 'foo' );\n    > b.count\n    1\n    > b.push( 'bar' );\n    > b.count\n    2","CircularBuffer.prototype.full":"\nCircularBuffer.prototype.full\n    Read-only property returning a boolean indicating whether a circular buffer\n    is full.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether a circular buffer is full.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.full\n    false\n    > b.push( 'foo' );\n    > b.push( 'bar' );\n    > b.push( 'beep' );\n    > b.full\n    true","CircularBuffer.prototype.iterator":"\nCircularBuffer.prototype.iterator( [niters] )\n    Returns an iterator for iterating over a circular buffer.\n\n    A returned iterator does not iterate over partially full buffers.\n\n    Parameters\n    ----------\n    niters: integer (optional)\n        Number of iterations. Default: infinity.\n\n    Returns\n    -------\n    out: Iterator\n        Iterator.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.push( 'foo' );\n    > b.push( 'bar' );\n    > b.push( 'beep' );\n    > b.push( 'boop' );\n    > var it = b.iterator( b.length );\n    > var v = it.next().value\n    'bar'\n    > v = it.next().value\n    'beep'\n    > v = it.next().value\n    'boop'\n    > var bool = it.next().done\n    true","CircularBuffer.prototype.length":"\nCircularBuffer.prototype.length\n    Read-only property returning the buffer length (i.e., capacity).\n\n    Returns\n    -------\n    out: integer\n        Buffer length.\n\n    Examples\n    --------\n    > var b = CircularBuffer( [ 0, 0, 0 ] );\n    > var len = b.length\n    3","CircularBuffer.prototype.push":"\nCircularBuffer.prototype.push( value )\n    Adds a value to a circular buffer.\n\n    Parameters\n    ----------\n    value: any\n        Value to add.\n\n    Returns\n    -------\n    out: any\n        Removed element (or undefined).\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.push( 'foo' )\n    undefined\n    > b.push( 'bar' )\n    undefined\n    > b.push( 'beep' )\n    undefined\n    > b.push( 'boop' )\n    'foo'","CircularBuffer.prototype.toArray":"\nCircularBuffer.prototype.toArray()\n    Returns an array of circular buffer values.\n\n    Returns\n    -------\n    out: Array\n        Circular buffer values.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.push( 'foo' );\n    > b.push( 'bar' );\n    > b.push( 'beep' );\n    > b.push( 'boop' );\n    > var vals = b.toArray()\n    [ 'bar', 'beep', 'boop' ]","CircularBuffer.prototype.toJSON":"\nCircularBuffer.prototype.toJSON()\n    Serializes a circular buffer as JSON.\n\n    Returns\n    -------\n    out: Object\n        Serialized circular buffer.\n\n    Examples\n    --------\n    > var b = CircularBuffer( 3 );\n    > b.push( 'foo' );\n    > b.push( 'bar' );\n    > b.push( 'beep' );\n    > b.push( 'boop' );\n    > var o = b.toJSON()\n    {'type':'circular-buffer','length':3,'data':['bar','beep','boop']}\n\n    See Also\n    --------\n    FIFO, Stack","close":"\nclose( fd, clbk )\n    Asynchronously closes a file descriptor, so that the file descriptor no\n    longer refers to any file and may be reused.\n\n    Parameters\n    ----------\n    fd: integer\n        File descriptor.\n\n    clbk: Function\n        Callback to invoke upon closing a file descriptor.\n\n    Examples\n    --------\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     }\n    ... };\n    > var fd = open.sync( './beep/boop.js', 'r+' );\n    > if ( !isError( fd ) ) { close( fd, done ); };\n\n\nclose.sync( fd )\n    Synchronously closes a file descriptor.\n\n    Parameters\n    ----------\n    fd: integer\n        File descriptor.\n\n    Returns\n    -------\n    out: Error|void\n        If an error occurs, an error object; otherwise, undefined.\n\n    Examples\n    --------\n    > var fd = open.sync( './beep/boop.js', 'r+' );\n    > if ( !isError( fd ) ) { close.sync( fd ); };\n\n    See Also\n    --------\n    exists, open, readFile\n","close.sync":"\nclose.sync( fd )\n    Synchronously closes a file descriptor.\n\n    Parameters\n    ----------\n    fd: integer\n        File descriptor.\n\n    Returns\n    -------\n    out: Error|void\n        If an error occurs, an error object; otherwise, undefined.\n\n    Examples\n    --------\n    > var fd = open.sync( './beep/boop.js', 'r+' );\n    > if ( !isError( fd ) ) { close.sync( fd ); };\n\n    See Also\n    --------\n    exists, open, readFile","CMUDICT":"\nCMUDICT( [options] )\n    Returns datasets from the Carnegie Mellon Pronouncing Dictionary (CMUdict).\n\n    Data includes the following:\n\n    - dict: the main pronouncing dictionary.\n    - phones: manners of articulation for each sound.\n    - symbols: complete list of ARPABET symbols used by the dictionary.\n    - vp: verbal pronunciations of punctuation marks.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.data: string (optional)\n        Dataset name.\n\n    Returns\n    -------\n    out: Object|Array\n        CMUdict dataset.\n\n    Examples\n    --------\n    > var data = CMUDICT();\n    > var dict = data.dict\n    {...}\n    > var phones = data.phones\n    {...}\n    > var symbols = data.symbols\n    [...]\n    > var vp = data.vp\n    {...}\n\n","codePointAt":"\ncodePointAt( str, idx[, backward] )\n    Returns a Unicode code point from a string at a specified position.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    idx: integer\n        Position. If less than `0`, the string position is determined relative\n        to the end of the input string.\n\n    backward: boolean (optional)\n        Backward iteration for low surrogates. Default: false.\n\n    Returns\n    -------\n    out: integer\n        Unicode code point.\n\n    Examples\n    --------\n    > var out = codePointAt( 'last man standing', 4 )\n    32\n    > out = codePointAt( 'presidential election', 8, true )\n    116\n    > out = codePointAt( 'अनुच्छेद', 2 )\n    2369\n    > out = codePointAt( '🌷', 1, true )\n    127799\n\n    See Also\n    --------\n    fromCodePoint","commonKeys":"\ncommonKeys( obj1, obj2[, ...obj] )\n    Returns the common own property names of two or more objects.\n\n    Parameters\n    ----------\n    obj1: any\n        First object.\n\n    obj2: any\n        Second object.\n\n    obj: ...any (optional)\n        Additional objects.\n\n    Returns\n    -------\n    out: Array<string>\n        Common keys of objects.\n\n    Examples\n    --------\n    > var obj1 = { 'a': 1, 'b': 2 };\n    > var obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\n    > var keys = commonKeys( obj1, obj2 )\n    [ 'a', 'b' ]\n\n    See Also\n    --------\n    commonKeysIn, objectKeys","commonKeysIn":"\ncommonKeysIn( obj1, obj2[, ...obj] )\n    Returns the common own and inherited property names of two or more objects.\n\n    Parameters\n    ----------\n    obj1: any\n        First object.\n\n    obj2: any\n        Second object.\n\n    obj: ...any (optional)\n        Additional objects.\n\n    Returns\n    -------\n    out: Array<string>\n        Common keys.\n\n    Examples\n    --------\n    > var obj1 = { 'a': 1, 'b': 2 };\n    > var obj2 = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\n    > var keys = commonKeysIn( obj1, obj2 )\n    [ 'a', 'b' ]\n\n    See Also\n    --------\n    commonKeys, keysIn","complex":"\ncomplex( real, imag[, dtype] )\n    Creates a complex number.\n\n    The function supports the following data types:\n\n    - float64\n    - float32\n\n    Parameters\n    ----------\n    real: number\n        Real component.\n\n    imag: number\n        Imaginary component.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    z: Complex\n        Complex number.\n\n    Examples\n    --------\n    > var z = complex( 5.0, 3.0, 'float64' )\n    <Complex128>\n    > z = complex( 5.0, 3.0, 'float32' )\n    <Complex64>\n\n    See Also\n    --------\n    Complex128, Complex64\n","Complex64":"\nComplex64( real, imag )\n    64-bit complex number constructor.\n\n    Both the real and imaginary components are stored as single-precision\n    floating-point numbers.\n\n    Parameters\n    ----------\n    real: number\n        Real component.\n\n    imag: number\n        Imaginary component.\n\n    Returns\n    -------\n    z: Complex64\n        64-bit complex number.\n\n    z.re: number\n        Read-only property returning the real component.\n\n    z.im: number\n        Read-only property returning the imaginary component.\n\n    Examples\n    --------\n    > var z = new Complex64( 5.0, 3.0 )\n    <Complex64>\n    > z.re\n    5.0\n    > z.im\n    3.0\n\n\nComplex64.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n\n    Returns\n    -------\n    v: integer\n        Size (in bytes) of each component.\n\n    Examples\n    --------\n    > var s = Complex64.BYTES_PER_ELEMENT\n    4\n\n\nComplex64.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n\n    Returns\n    -------\n    s: integer\n        Size (in bytes) of each component.\n\n    Examples\n    --------\n    > var z = new Complex64( 5.0, 3.0 )\n    <Complex64>\n    > var s = z.BYTES_PER_ELEMENT\n    4\n\n\nComplex64.prototype.byteLength\n    Length (in bytes) of a complex number.\n\n    Returns\n    -------\n    len: integer\n        Length (in bytes) of a complex number.\n\n    Examples\n    --------\n    > var z = new Complex64( 5.0, 3.0 )\n    <Complex64>\n    > var s = z.byteLength\n    8\n\n    See Also\n    --------\n    complex, Complex128\n","Complex64.BYTES_PER_ELEMENT":"\nComplex64.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n\n    Returns\n    -------\n    v: integer\n        Size (in bytes) of each component.\n\n    Examples\n    --------\n    > var s = Complex64.BYTES_PER_ELEMENT\n    4","Complex64.prototype.BYTES_PER_ELEMENT":"\nComplex64.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n\n    Returns\n    -------\n    s: integer\n        Size (in bytes) of each component.\n\n    Examples\n    --------\n    > var z = new Complex64( 5.0, 3.0 )\n    <Complex64>\n    > var s = z.BYTES_PER_ELEMENT\n    4","Complex64.prototype.byteLength":"\nComplex64.prototype.byteLength\n    Length (in bytes) of a complex number.\n\n    Returns\n    -------\n    len: integer\n        Length (in bytes) of a complex number.\n\n    Examples\n    --------\n    > var z = new Complex64( 5.0, 3.0 )\n    <Complex64>\n    > var s = z.byteLength\n    8\n\n    See Also\n    --------\n    complex, Complex128","COMPLEX64_NAN":"\nCOMPLEX64_NAN\n    Canonical single-precision complex floating-point NaN.\n\n    Examples\n    --------\n    > COMPLEX64_NAN\n    <Complex64>\n\n    See Also\n    --------\n    COMPLEX128_NAN\n","COMPLEX64_NUM_BYTES":"\nCOMPLEX64_NUM_BYTES\n    Size (in bytes) of a 64-bit complex number.\n\n    Examples\n    --------\n    > COMPLEX64_NUM_BYTES\n    8\n\n    See Also\n    --------\n    COMPLEX128_NUM_BYTES, FLOAT32_NUM_BYTES\n","COMPLEX64_ZERO":"\nCOMPLEX64_ZERO\n    Single-precision complex floating-point zero.\n\n    Examples\n    --------\n    > COMPLEX64_ZERO\n    <Complex64>\n\n    See Also\n    --------\n    COMPLEX128_ZERO\n","Complex64Array":"\nComplex64Array()\n    A 64-bit complex number array.\n\n    Returns\n    -------\n    out: Complex64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Complex64Array()\n    <Complex64Array>\n\n\nComplex64Array( length )\n    Creates a 64-bit complex number array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: Complex64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 10 )\n    <Complex64Array>\n    > var len = arr.length\n    10\n\n\nComplex64Array( complexarray )\n    Creates a 64-bit complex number array from another complex number array.\n\n    Parameters\n    ----------\n    complexarray: Complex64Array\n        Complex array from which to generate another complex array.\n\n    Returns\n    -------\n    out: Complex64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var arr2 = new Complex64Array( arr1 )\n    <Complex64Array>\n    > var len = arr2.length\n    2\n\n\nComplex64Array( typedarray )\n    Creates a 64-bit complex number array from a typed array\n    containing interleaved real and imaginary components.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate complex array.\n\n    Returns\n    -------\n    out: Complex64Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new Float32Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Float32Array>\n    > var arr = new Complex64Array( buf )\n    <Complex64Array>\n    > var len = arr.length\n    2\n\n\nComplex64Array( obj )\n    Creates a 64-bit complex number array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a complex array.\n\n    Returns\n    -------\n    out: Complex64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var len = arr1.length\n    2\n    > var buf = [ new Complex64( 1.0, -1.0 ), new Complex64( 2.0, -2.0 )];\n    > var arr2 = new Complex64Array( buf )\n    <Complex64Array>\n    > len = arr2.length\n    2\n\n\nComplex64Array( buffer[, byteOffset[, length]] )\n    Returns a 64-bit complex number array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Complex64Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 240 );\n    > var arr1 = new Complex64Array( buf )\n    <Complex64Array>\n    > var len = arr1.length\n    30\n    > var arr2 = new Complex64Array( buf, 8 )\n    <Complex64Array>\n    > len = arr2.length\n    29\n    > var arr3 = new Complex64Array( buf, 8, 20 )\n    <Complex64Array>\n    > len = arr3.length\n    20\n\n\nComplex64Array.from( src[, clbk[, thisArg]] )\n    Creates a new 64-bit complex number array from an array-like object or an\n    iterable.\n\n    A callback function is provided two arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    clbk: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n    \n    Returns\n    -------\n    out: Complex64Array\n        A typed array.\n    \n    Examples\n    --------\n    > function clbkFcn( v ) { return v * 2.0 };\n    > var arr = Complex64Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\n    <Complex64Array>\n    > var len = arr.length\n    2\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    -2.0\n\n\nComplex64Array.of( element0[, element1[, ...elementN]] )\n    Creates a new 64-bit complex number array from a variable number of\n    arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Complex64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Complex64Array.of( 1.0, -1.0, 2.0, -2.0 )\n    <Complex64Array>\n    > var len = arr.length\n    2\n    > var z1 = new Complex64( 1.0, -1.0 );\n    > var z2 = new Complex64( 2.0, -2.0 );\n    > arr = Complex64Array.of( z1, z2 )\n    <Complex64Array>\n    > len = arr.length\n    2\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    -1.0\n\n\nComplex64Array.BYTES_PER_ELEMENT\n    The size of each array element in bytes.\n\n    Examples\n    --------\n    > var nbytes = Complex64Array.BYTES_PER_ELEMENT\n    8\n\n\nComplex64Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > var str = Complex64Array.name\n    'Complex64Array'\n\n\nComplex64Array.prototype.buffer\n    Pointer to the underlying data buffer.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 2 )\n    <Complex64Array>\n    > var buf = arr.buffer\n    <ArrayBuffer>\n\n\nComplex64Array.prototype.byteLength\n    Length of the array in bytes.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 10 )\n    <Complex64Array>\n    > var nbytes = arr.byteLength\n    80\n\n\nComplex64Array.prototype.byteOffset\n    Offset (in bytes) of the array from the start of its underlying\n    ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 5 )\n    <Complex64Array>\n    > var offset = arr.byteOffset\n    0\n    > var buf = new ArrayBuffer( 240 );\n    > arr = new Complex64Array( buf, 64 )\n    <Complex64Array>\n    > offset = arr.byteOffset\n    64\n\n\nComplex64Array.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 10 )\n    <Complex64Array>\n    > arr.BYTES_PER_ELEMENT\n    8\n\n\nComplex64Array.prototype.length\n    The number of array elements.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 10 )\n    <Complex64Array>\n    > var len = arr.length\n    10\n\n\nComplex64Array.prototype.at( i )\n    Returns an array element located at integer position (index) `i`, with\n    support for noth nonnegative and negative integer positions.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n\n    Returns\n    -------\n    out: Complex64|void\n        An array element.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var z = arr.at( 1 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    -2.0\n\n\nComplex64Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n    \n    start: integer\n        Source start index position.\n    \n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Complex64Array\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex64Array>\n    > arr.copyWithin( 0, 2 )\n    <Complex64Array>\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    -3.0\n\n\nComplex64Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var it = arr.entries();\n    > var v = it.next().value\n    [ 0, <Complex64> ]\n    > var re = realf( v[ 1 ] )\n    1.0\n    > var im = imagf( v[ 1 ] )\n    -1.0\n    > v = it.next().value\n    [ 1, <Complex64> ]\n    > re = realf( v[ 1 ] )\n    2.0\n    > im = imagf( v[ 1 ] )\n    -2.0\n    > v = it.next().value\n    [ 2, <Complex64> ]\n    > re = realf( v[ 1 ] )\n    3.0\n    > im = imagf( v[ 1 ] )\n    -3.0\n    > var bool = it.next().done\n    true\n\n\nComplex64Array.prototype.every( predicate[, thisArg] )\n    Returns a boolean indicating whether all elements in the array pass a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all elements pass the test.\n\n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) > 0.0 ); };\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var bool = arr.every( predicate )\n    true\n\n\nComplex64Array.prototype.fill( value[, start[, end]] )\n    Returns a modified typed array filled with a fill value.\n\n    Parameters\n    ----------\n    value: Complex64\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Complex64Array\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( 3 )\n    <Complex64Array>\n    > arr.fill( new Complex64( 1.0, 1.0 ) );\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    1.0\n    > z = arr.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    1.0\n    > im = imagf( z )\n    1.0\n    > z = arr.get( 2 )\n    <Complex64>\n    > re = realf( z )\n    1.0\n    > im = imagf( z )\n    1.0\n\n\nComplex64Array.prototype.filter( predicate[, thisArg] )\n    Returns a new array containing the elements of an array which pass a test\n    implemented by a predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Complex64Array\n        A new typed array.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var out = arr.filter( predicate )\n    <Complex64Array>\n    > var len = out.length\n    1\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    2.0\n\n\nComplex64Array.prototype.find( predicate[, thisArg] )\n    Returns the first element in an array for which a predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    out: Complex64|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var z = arr.find( predicate )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    1.0\n\n\nComplex64Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var idx = arr.findIndex( predicate )\n    0\n\n\nComplex64Array.prototype.findLast( predicate[, thisArg] )\n    Returns the last element in an array for which a predicate function returns\n    a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.  \n    \n    Returns\n    -------\n    out: Complex64|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var z = arr.findLast( predicate )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    2.0\n\n\nComplex64Array.prototype.findLastIndex( predicate[, thisArg] )\n    Returns the index of the last element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var idx = arr.findLastIndex( predicate )\n    1\n\n\nComplex64Array.prototype.forEach( clbk[, thisArg] )\n    Invokes a function once for each array element.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Examples\n    --------\n    > var str = '%';\n    > function clbk( v ) { str += v.toString() + '%'; };\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > arr.forEach( clbk );\n    > str\n    '%1 - 1i%2 - 2i%'\n\n\nComplex64Array.prototype.get( i )\n    Returns an array element located at integer position (index) `i`.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n    \n    Returns\n    -------\n    out: Complex64|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var z = arr.get( 1 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    -2.0\n\n\nComplex64Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a provided value.\n\n    Parameters\n    ----------\n    searchElement: Complex64\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n    \n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex64Array>\n    > var bool = arr.includes( new Complex64( 3.0, -3.0 ) )\n    true\n    > bool = arr.includes( new Complex64( 3.0, -3.0 ), 3 )\n    false\n\n\nComplex64Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the first index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: Complex64\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex64Array>\n    > var idx = arr.indexOf( new Complex64( 3.0, -3.0 ) )\n    2\n    > idx = arr.indexOf( new Complex64( 3.0, -3.0 ), 3 )\n    -1\n\n\nComplex64Array.prototype.join( [separator] )\n    Returns a new string by concatenating all array elements separated by a\n    separator string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        Separator string. Default: ','.\n    \n    Returns\n    -------\n    out: string\n        Array serialized as a string.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var str = arr.join()\n    '1 - 1i,2 - 2i'\n    > str = arr.join( '/' )\n    '1 - 1i/2 - 2i'\n\n\nComplex64Array.prototype.keys()\n    Returns an iterator for iterating over each index key in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array index keys.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var it = arr.keys();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().done\n    true\n\n\nComplex64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the last index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: Complex64\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: out.length-1.\n    \n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex64Array>\n    > var idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ) )\n    3\n    > idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ), 2 )\n    0\n\n\nComplex64Array.prototype.map( clbk[, thisArg] )\n    Returns a new array with each element being the result of a provided\n    callback function.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Complex64Array\n        A new typed array.\n    \n    Examples\n    --------\n    > function clbk( v ) { return v; };\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var out = arr.map( clbk )\n    <Complex64Array>\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    -1.0\n    > z = out.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    -2.0\n\n\nComplex64Array.prototype.reduce( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in order, passing\n    in the return value from the calculation on the preceding element and\n    returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.    \n\n    initialValue: any (optional)\n        Initial accumulation value.\n    \n    Returns\n    -------\n    out: any\n        Accumulated result.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var z = arr.reduce( base.caddf )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    -3.0\n\n\nComplex64Array.prototype.reduceRight( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in reverse order,\n    passing in the return value from the calculation on the preceding element\n    and returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.\n\n    initialValue: any (optional)\n        Initial accumulation value.\n    \n    Returns\n    -------\n    out: any\n        Accumulated result.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var z = arr.reduceRight( base.caddf )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    -3.0\n\n\nComplex64Array.prototype.reverse()\n    Reverses the array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Complex64Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > arr.reverse();\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    -3.0\n    > z = arr.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    -2.0\n    > z = arr.get( 2 )\n    <Complex64>\n    > re = realf( z )\n    1.0\n    > im = imagf( z )\n    -1.0\n\n\nComplex64Array.prototype.set( z[, i] )\n    Sets one or more array elements.\n\n    If provided a single argument, the method sets array elements starting at\n    position (index) `i = 0`. To set elements starting elsewhere in the array,\n    provide an index argument `i`.\n\n    To set one or more array elements, provide an array-like object containing\n    either complex numbers or interleaved real and imaginary components.\n\n    Parameters\n    ----------\n    z: Complex64|Complex64Array|ArrayLikeObject\n        Complex number or complex number array.\n\n    i: integer (optional)\n        Array index at which to start setting elements. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 2 )\n    <Complex64Array>\n    > arr.set( new Complex64( 1.0, -1.0 ) );\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    -1.0\n    > arr.set( new Complex64( 2.0, -2.0 ), 1 );\n    > z = arr.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    -2.0\n\n\nComplex64Array.prototype.slice( [start[, end]] )\n    Copies a portion of a typed array to a new typed array.\n\n    Parameters\n    ----------\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n    \n    Returns\n    -------\n    out: Complex64Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var out = arr.slice( 1 )\n    <Complex64Array>\n    > var len = out.length\n    2\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    -2.0\n    > z = out.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    -3.0\n\n\nComplex64Array.prototype.some( predicate[, thisArg] )\n    Returns a boolean indicating whether at least one element passes a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n    \n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one element passes the test.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var bool = arr.some( predicate )\n    true\n\n\nComplex64Array.prototype.sort( compareFunction )\n    Sorts an array in-place.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first element for comparison.\n    - b: second element for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFunction: Function\n        Comparison function.\n    \n    Returns\n    -------\n    out: Complex64Array\n        Modified array.\n    \n    Examples\n    --------\n    > function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\n    > var arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex64Array>\n    > arr.sort( compare );\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    -1.0\n    > z = arr.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    -2.0\n    > z = arr.get( 2 )\n    <Complex64>\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    -3.0\n\n\nComplex64Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array view over the same underlying `ArrayBuffer` and\n    with the same underlying data type as the host array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Complex64Array\n        New typed array view.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex64Array>\n    > var out = arr.subarray( 1, 3 )\n    <Complex64Array>\n    > var len = out.length\n    2\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    -2.0\n    > z = out.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    -3.0\n\n\nComplex64Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array (optional)\n        Locale identifier(s).\n    \n    options: Object (optional)\n        An object containing serialization options.\n    \n    Returns\n    -------\n    str: string\n        Local-specific string.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0 ] )\n    <Complex64Array>\n    > var str = arr.toLocaleString()\n    '1 + 1i,2 + 2i'\n\n\nComplex64Array.prototype.toReversed()\n    Returns a new typed array containing the elements in reversed order.\n\n    Returns\n    -------\n    out: Complex64Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\n    <Complex64Array>\n    > var out = arr.toReversed()\n    <Complex64Array>\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    3.0\n    > z = out.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    2.0\n    > z = out.get( 2 )\n    <Complex64>\n    > re = realf( z )\n    1.0\n    > im = imagf( z )\n    1.0\n\n\nComplex64Array.prototype.toSorted( compareFcn )\n    Returns a new typed array containing the elements in sorted order.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first element for comparison.\n    - b: second element for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFcn: Function\n        Comparison function.\n    \n    Returns\n    -------\n    out: Complex64Array\n        New typed array.\n    \n    Examples\n    --------\n    > function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\n    > var arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex64Array>\n    > var out = arr.toSorted( compare );\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    -1.0\n    > z = out.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    -2.0\n    > z = out.get( 2 )\n    <Complex64>\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    -3.0\n\n\nComplex64Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        String serialization of the array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\n    <Complex64Array>\n    > var str = arr.toString()\n    '1 + 1i,2 - 2i,3 + 3i'\n\n\nComplex64Array.prototype.values()\n    Returns an iterator for iterating over each value in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array values.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var it = arr.values();\n    > var v = it.next().value\n    <Complex64>\n    > var re = realf( v )\n    1.0\n    > var im = imagf( v )\n    -1.0\n    > v = it.next().value\n    <Complex64>\n    > re = realf( v )\n    2.0\n    > im = imagf( v )\n    -2.0\n    > var bool = it.next().done\n    true\n\n\nComplex64Array.prototype.with( index, value )\n    Returns a new typed array with the element at a provided index replaced\n    with a provided value.\n\n    Parameters\n    ----------\n    index: integer\n        Element index.\n    \n    value: Complex64\n        Element value.  \n\n    Returns\n    -------\n    out: Complex64Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n    <Complex64Array>\n    > var z = out.get( 1 )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    -3.0\n\n\n    See Also\n    --------\n    Complex128Array, complex, Complex64","Complex64Array.from":"\nComplex64Array.from( src[, clbk[, thisArg]] )\n    Creates a new 64-bit complex number array from an array-like object or an\n    iterable.\n\n    A callback function is provided two arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    clbk: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n    \n    Returns\n    -------\n    out: Complex64Array\n        A typed array.\n    \n    Examples\n    --------\n    > function clbkFcn( v ) { return v * 2.0 };\n    > var arr = Complex64Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\n    <Complex64Array>\n    > var len = arr.length\n    2\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    -2.0","Complex64Array.of":"\nComplex64Array.of( element0[, element1[, ...elementN]] )\n    Creates a new 64-bit complex number array from a variable number of\n    arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Complex64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Complex64Array.of( 1.0, -1.0, 2.0, -2.0 )\n    <Complex64Array>\n    > var len = arr.length\n    2\n    > var z1 = new Complex64( 1.0, -1.0 );\n    > var z2 = new Complex64( 2.0, -2.0 );\n    > arr = Complex64Array.of( z1, z2 )\n    <Complex64Array>\n    > len = arr.length\n    2\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    -1.0","Complex64Array.BYTES_PER_ELEMENT":"\nComplex64Array.BYTES_PER_ELEMENT\n    The size of each array element in bytes.\n\n    Examples\n    --------\n    > var nbytes = Complex64Array.BYTES_PER_ELEMENT\n    8","Complex64Array.name":"\nComplex64Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > var str = Complex64Array.name\n    'Complex64Array'","Complex64Array.prototype.buffer":"\nComplex64Array.prototype.buffer\n    Pointer to the underlying data buffer.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 2 )\n    <Complex64Array>\n    > var buf = arr.buffer\n    <ArrayBuffer>","Complex64Array.prototype.byteLength":"\nComplex64Array.prototype.byteLength\n    Length of the array in bytes.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 10 )\n    <Complex64Array>\n    > var nbytes = arr.byteLength\n    80","Complex64Array.prototype.byteOffset":"\nComplex64Array.prototype.byteOffset\n    Offset (in bytes) of the array from the start of its underlying\n    ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 5 )\n    <Complex64Array>\n    > var offset = arr.byteOffset\n    0\n    > var buf = new ArrayBuffer( 240 );\n    > arr = new Complex64Array( buf, 64 )\n    <Complex64Array>\n    > offset = arr.byteOffset\n    64","Complex64Array.prototype.BYTES_PER_ELEMENT":"\nComplex64Array.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 10 )\n    <Complex64Array>\n    > arr.BYTES_PER_ELEMENT\n    8","Complex64Array.prototype.length":"\nComplex64Array.prototype.length\n    The number of array elements.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 10 )\n    <Complex64Array>\n    > var len = arr.length\n    10","Complex64Array.prototype.at":"\nComplex64Array.prototype.at( i )\n    Returns an array element located at integer position (index) `i`, with\n    support for noth nonnegative and negative integer positions.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n\n    Returns\n    -------\n    out: Complex64|void\n        An array element.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var z = arr.at( 1 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    -2.0","Complex64Array.prototype.copyWithin":"\nComplex64Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n    \n    start: integer\n        Source start index position.\n    \n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Complex64Array\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex64Array>\n    > arr.copyWithin( 0, 2 )\n    <Complex64Array>\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    -3.0","Complex64Array.prototype.entries":"\nComplex64Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var it = arr.entries();\n    > var v = it.next().value\n    [ 0, <Complex64> ]\n    > var re = realf( v[ 1 ] )\n    1.0\n    > var im = imagf( v[ 1 ] )\n    -1.0\n    > v = it.next().value\n    [ 1, <Complex64> ]\n    > re = realf( v[ 1 ] )\n    2.0\n    > im = imagf( v[ 1 ] )\n    -2.0\n    > v = it.next().value\n    [ 2, <Complex64> ]\n    > re = realf( v[ 1 ] )\n    3.0\n    > im = imagf( v[ 1 ] )\n    -3.0\n    > var bool = it.next().done\n    true","Complex64Array.prototype.every":"\nComplex64Array.prototype.every( predicate[, thisArg] )\n    Returns a boolean indicating whether all elements in the array pass a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all elements pass the test.\n\n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) > 0.0 ); };\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var bool = arr.every( predicate )\n    true","Complex64Array.prototype.fill":"\nComplex64Array.prototype.fill( value[, start[, end]] )\n    Returns a modified typed array filled with a fill value.\n\n    Parameters\n    ----------\n    value: Complex64\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Complex64Array\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( 3 )\n    <Complex64Array>\n    > arr.fill( new Complex64( 1.0, 1.0 ) );\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    1.0\n    > z = arr.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    1.0\n    > im = imagf( z )\n    1.0\n    > z = arr.get( 2 )\n    <Complex64>\n    > re = realf( z )\n    1.0\n    > im = imagf( z )\n    1.0","Complex64Array.prototype.filter":"\nComplex64Array.prototype.filter( predicate[, thisArg] )\n    Returns a new array containing the elements of an array which pass a test\n    implemented by a predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Complex64Array\n        A new typed array.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var out = arr.filter( predicate )\n    <Complex64Array>\n    > var len = out.length\n    1\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    2.0","Complex64Array.prototype.find":"\nComplex64Array.prototype.find( predicate[, thisArg] )\n    Returns the first element in an array for which a predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    out: Complex64|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var z = arr.find( predicate )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    1.0","Complex64Array.prototype.findIndex":"\nComplex64Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var idx = arr.findIndex( predicate )\n    0","Complex64Array.prototype.findLast":"\nComplex64Array.prototype.findLast( predicate[, thisArg] )\n    Returns the last element in an array for which a predicate function returns\n    a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.  \n    \n    Returns\n    -------\n    out: Complex64|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var z = arr.findLast( predicate )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    2.0","Complex64Array.prototype.findLastIndex":"\nComplex64Array.prototype.findLastIndex( predicate[, thisArg] )\n    Returns the index of the last element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var idx = arr.findLastIndex( predicate )\n    1","Complex64Array.prototype.forEach":"\nComplex64Array.prototype.forEach( clbk[, thisArg] )\n    Invokes a function once for each array element.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Examples\n    --------\n    > var str = '%';\n    > function clbk( v ) { str += v.toString() + '%'; };\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > arr.forEach( clbk );\n    > str\n    '%1 - 1i%2 - 2i%'","Complex64Array.prototype.get":"\nComplex64Array.prototype.get( i )\n    Returns an array element located at integer position (index) `i`.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n    \n    Returns\n    -------\n    out: Complex64|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var z = arr.get( 1 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    -2.0","Complex64Array.prototype.includes":"\nComplex64Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a provided value.\n\n    Parameters\n    ----------\n    searchElement: Complex64\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n    \n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex64Array>\n    > var bool = arr.includes( new Complex64( 3.0, -3.0 ) )\n    true\n    > bool = arr.includes( new Complex64( 3.0, -3.0 ), 3 )\n    false","Complex64Array.prototype.indexOf":"\nComplex64Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the first index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: Complex64\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex64Array>\n    > var idx = arr.indexOf( new Complex64( 3.0, -3.0 ) )\n    2\n    > idx = arr.indexOf( new Complex64( 3.0, -3.0 ), 3 )\n    -1","Complex64Array.prototype.join":"\nComplex64Array.prototype.join( [separator] )\n    Returns a new string by concatenating all array elements separated by a\n    separator string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        Separator string. Default: ','.\n    \n    Returns\n    -------\n    out: string\n        Array serialized as a string.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var str = arr.join()\n    '1 - 1i,2 - 2i'\n    > str = arr.join( '/' )\n    '1 - 1i/2 - 2i'","Complex64Array.prototype.keys":"\nComplex64Array.prototype.keys()\n    Returns an iterator for iterating over each index key in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array index keys.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var it = arr.keys();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().done\n    true","Complex64Array.prototype.lastIndexOf":"\nComplex64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the last index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: Complex64\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: out.length-1.\n    \n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex64Array>\n    > var idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ) )\n    3\n    > idx = arr.lastIndexOf( new Complex64( 1.0, -1.0 ), 2 )\n    0","Complex64Array.prototype.map":"\nComplex64Array.prototype.map( clbk[, thisArg] )\n    Returns a new array with each element being the result of a provided\n    callback function.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Complex64Array\n        A new typed array.\n    \n    Examples\n    --------\n    > function clbk( v ) { return v; };\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var out = arr.map( clbk )\n    <Complex64Array>\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    -1.0\n    > z = out.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    -2.0","Complex64Array.prototype.reduce":"\nComplex64Array.prototype.reduce( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in order, passing\n    in the return value from the calculation on the preceding element and\n    returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.    \n\n    initialValue: any (optional)\n        Initial accumulation value.\n    \n    Returns\n    -------\n    out: any\n        Accumulated result.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var z = arr.reduce( base.caddf )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    -3.0","Complex64Array.prototype.reduceRight":"\nComplex64Array.prototype.reduceRight( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in reverse order,\n    passing in the return value from the calculation on the preceding element\n    and returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.\n\n    initialValue: any (optional)\n        Initial accumulation value.\n    \n    Returns\n    -------\n    out: any\n        Accumulated result.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var z = arr.reduceRight( base.caddf )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    -3.0","Complex64Array.prototype.reverse":"\nComplex64Array.prototype.reverse()\n    Reverses the array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Complex64Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > arr.reverse();\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    -3.0\n    > z = arr.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    -2.0\n    > z = arr.get( 2 )\n    <Complex64>\n    > re = realf( z )\n    1.0\n    > im = imagf( z )\n    -1.0","Complex64Array.prototype.set":"\nComplex64Array.prototype.set( z[, i] )\n    Sets one or more array elements.\n\n    If provided a single argument, the method sets array elements starting at\n    position (index) `i = 0`. To set elements starting elsewhere in the array,\n    provide an index argument `i`.\n\n    To set one or more array elements, provide an array-like object containing\n    either complex numbers or interleaved real and imaginary components.\n\n    Parameters\n    ----------\n    z: Complex64|Complex64Array|ArrayLikeObject\n        Complex number or complex number array.\n\n    i: integer (optional)\n        Array index at which to start setting elements. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( 2 )\n    <Complex64Array>\n    > arr.set( new Complex64( 1.0, -1.0 ) );\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    -1.0\n    > arr.set( new Complex64( 2.0, -2.0 ), 1 );\n    > z = arr.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    -2.0","Complex64Array.prototype.slice":"\nComplex64Array.prototype.slice( [start[, end]] )\n    Copies a portion of a typed array to a new typed array.\n\n    Parameters\n    ----------\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n    \n    Returns\n    -------\n    out: Complex64Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var out = arr.slice( 1 )\n    <Complex64Array>\n    > var len = out.length\n    2\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    -2.0\n    > z = out.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    -3.0","Complex64Array.prototype.some":"\nComplex64Array.prototype.some( predicate[, thisArg] )\n    Returns a boolean indicating whether at least one element passes a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n    \n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one element passes the test.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( realf( v ) === imagf( v ) ); };\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex64Array>\n    > var bool = arr.some( predicate )\n    true","Complex64Array.prototype.sort":"\nComplex64Array.prototype.sort( compareFunction )\n    Sorts an array in-place.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first element for comparison.\n    - b: second element for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFunction: Function\n        Comparison function.\n    \n    Returns\n    -------\n    out: Complex64Array\n        Modified array.\n    \n    Examples\n    --------\n    > function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\n    > var arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex64Array>\n    > arr.sort( compare );\n    > var z = arr.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    -1.0\n    > z = arr.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    -2.0\n    > z = arr.get( 2 )\n    <Complex64>\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    -3.0","Complex64Array.prototype.subarray":"\nComplex64Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array view over the same underlying `ArrayBuffer` and\n    with the same underlying data type as the host array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Complex64Array\n        New typed array view.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex64Array>\n    > var out = arr.subarray( 1, 3 )\n    <Complex64Array>\n    > var len = out.length\n    2\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    2.0\n    > var im = imagf( z )\n    -2.0\n    > z = out.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    -3.0","Complex64Array.prototype.toLocaleString":"\nComplex64Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array (optional)\n        Locale identifier(s).\n    \n    options: Object (optional)\n        An object containing serialization options.\n    \n    Returns\n    -------\n    str: string\n        Local-specific string.\n\n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0 ] )\n    <Complex64Array>\n    > var str = arr.toLocaleString()\n    '1 + 1i,2 + 2i'","Complex64Array.prototype.toReversed":"\nComplex64Array.prototype.toReversed()\n    Returns a new typed array containing the elements in reversed order.\n\n    Returns\n    -------\n    out: Complex64Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\n    <Complex64Array>\n    > var out = arr.toReversed()\n    <Complex64Array>\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    3.0\n    > z = out.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    2.0\n    > z = out.get( 2 )\n    <Complex64>\n    > re = realf( z )\n    1.0\n    > im = imagf( z )\n    1.0","Complex64Array.prototype.toSorted":"\nComplex64Array.prototype.toSorted( compareFcn )\n    Returns a new typed array containing the elements in sorted order.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first element for comparison.\n    - b: second element for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFcn: Function\n        Comparison function.\n    \n    Returns\n    -------\n    out: Complex64Array\n        New typed array.\n    \n    Examples\n    --------\n    > function compare( a, b ) { return ( realf( a ) - realf( b ) ); };\n    > var arr = new Complex64Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex64Array>\n    > var out = arr.toSorted( compare );\n    > var z = out.get( 0 )\n    <Complex64>\n    > var re = realf( z )\n    1.0\n    > var im = imagf( z )\n    -1.0\n    > z = out.get( 1 )\n    <Complex64>\n    > re = realf( z )\n    2.0\n    > im = imagf( z )\n    -2.0\n    > z = out.get( 2 )\n    <Complex64>\n    > re = realf( z )\n    3.0\n    > im = imagf( z )\n    -3.0","Complex64Array.prototype.toString":"\nComplex64Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        String serialization of the array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\n    <Complex64Array>\n    > var str = arr.toString()\n    '1 + 1i,2 - 2i,3 + 3i'","Complex64Array.prototype.values":"\nComplex64Array.prototype.values()\n    Returns an iterator for iterating over each value in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array values.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var it = arr.values();\n    > var v = it.next().value\n    <Complex64>\n    > var re = realf( v )\n    1.0\n    > var im = imagf( v )\n    -1.0\n    > v = it.next().value\n    <Complex64>\n    > re = realf( v )\n    2.0\n    > im = imagf( v )\n    -2.0\n    > var bool = it.next().done\n    true","Complex64Array.prototype.with":"\nComplex64Array.prototype.with( index, value )\n    Returns a new typed array with the element at a provided index replaced\n    with a provided value.\n\n    Parameters\n    ----------\n    index: integer\n        Element index.\n    \n    value: Complex64\n        Element value.  \n\n    Returns\n    -------\n    out: Complex64Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex64Array>\n    > var out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n    <Complex64Array>\n    > var z = out.get( 1 )\n    <Complex64>\n    > var re = realf( z )\n    3.0\n    > var im = imagf( z )\n    -3.0\n\n\n    See Also\n    --------\n    Complex128Array, complex, Complex64","Complex128":"\nComplex128( real, imag )\n    128-bit complex number constructor.\n\n    Both the real and imaginary components are stored as double-precision\n    floating-point numbers.\n\n    Parameters\n    ----------\n    real: number\n        Real component.\n\n    imag: number\n        Imaginary component.\n\n    Returns\n    -------\n    z: Complex128\n        128-bit complex number.\n\n    z.re: number\n        Read-only property returning the real component.\n\n    z.im: number\n        Read-only property returning the imaginary component.\n\n\nComplex128.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n\n    Returns\n    -------\n    v: integer\n        Size (in bytes) of each component.\n\n    Examples\n    --------\n    > var s = Complex128.BYTES_PER_ELEMENT\n    8\n\n\nComplex128.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n\n    Returns\n    -------\n    s: integer\n        Size (in bytes) of each component.\n\n    Examples\n    --------\n    > var z = new Complex128( 5.0, 3.0 )\n    <Complex128>\n    > var s = z.BYTES_PER_ELEMENT\n    8\n\n\nComplex128.prototype.byteLength\n    Length (in bytes) of a complex number.\n\n    Returns\n    -------\n    len: integer\n        Length (in bytes) of a complex number.\n\n    Examples\n    --------\n    > var z = new Complex128( 5.0, 3.0 )\n    <Complex128>\n    > var s = z.byteLength\n    16\n\n    See Also\n    --------\n    complex, Complex64\n","Complex128.BYTES_PER_ELEMENT":"\nComplex128.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n\n    Returns\n    -------\n    v: integer\n        Size (in bytes) of each component.\n\n    Examples\n    --------\n    > var s = Complex128.BYTES_PER_ELEMENT\n    8","Complex128.prototype.BYTES_PER_ELEMENT":"\nComplex128.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n\n    Returns\n    -------\n    s: integer\n        Size (in bytes) of each component.\n\n    Examples\n    --------\n    > var z = new Complex128( 5.0, 3.0 )\n    <Complex128>\n    > var s = z.BYTES_PER_ELEMENT\n    8","Complex128.prototype.byteLength":"\nComplex128.prototype.byteLength\n    Length (in bytes) of a complex number.\n\n    Returns\n    -------\n    len: integer\n        Length (in bytes) of a complex number.\n\n    Examples\n    --------\n    > var z = new Complex128( 5.0, 3.0 )\n    <Complex128>\n    > var s = z.byteLength\n    16\n\n    See Also\n    --------\n    complex, Complex64","COMPLEX128_NAN":"\nCOMPLEX128_NAN\n    Canonical double-precision complex floating-point NaN.\n\n    Examples\n    --------\n    > COMPLEX128_NAN\n    <Complex128>\n\n    See Also\n    --------\n    COMPLEX64_NAN\n","COMPLEX128_NUM_BYTES":"\nCOMPLEX128_NUM_BYTES\n    Size (in bytes) of a 128-bit complex number.\n\n    Examples\n    --------\n    > COMPLEX128_NUM_BYTES\n    16\n\n    See Also\n    --------\n    COMPLEX64_NUM_BYTES, FLOAT64_NUM_BYTES\n","COMPLEX128_ZERO":"\nCOMPLEX128_ZERO\n    Double-precision complex floating-point zero.\n\n    Examples\n    --------\n    > COMPLEX128_ZERO\n    <Complex128>\n\n    See Also\n    --------\n    COMPLEX64_ZERO\n","Complex128Array":"\nComplex128Array()\n    A 128-bit complex number array.\n\n    Returns\n    -------\n    out: Complex128Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Complex128Array()\n    <Complex128Array>\n\n\nComplex128Array( length )\n    Creates a 128-bit complex number array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: Complex128Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 10 )\n    <Complex128Array>\n    > var len = arr.length\n    10\n\n\nComplex128Array( complexarray )\n    Creates a 64-bit complex number array from another complex number array.\n\n    Parameters\n    ----------\n    complexarray: Complex128Array\n        Complex array from which to generate another complex array.\n\n    Returns\n    -------\n    out: Complex128Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var arr2 = new Complex128Array( arr1 )\n    <Complex128Array>\n    > var len = arr2.length\n    2\n\n\nComplex128Array( typedarray )\n    Creates a 128-bit complex number array from a typed array\n    containing interleaved real and imaginary components.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate a complex array.\n\n    Returns\n    -------\n    out: Complex128Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new Float64Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Float64Array>\n    > var arr = new Complex128Array( buf )\n    <Complex128Array>\n    > var len = arr.length\n    2\n\n\nComplex128Array( obj )\n    Creates a 128-bit complex number array from an array-like object or \n    iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a complex array.\n\n    Returns\n    -------\n    out: Complex128Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var len = arr1.length\n    2\n    > var buf = [ new Complex128( 1.0, -1.0 ), new Complex128( 2.0, -2.0 ) ];\n    > var arr2 = new Complex128Array( buf )\n    <Complex128Array>\n    > len = arr2.length\n    2\n\n\nComplex128Array( buffer[, byteOffset[, length]] )\n    Returns a 128-bit complex number array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Complex128Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 480 );\n    > var arr1 = new Complex128Array( buf )\n    <Complex128Array>\n    > var len = arr1.length\n    30\n    > var arr2 = new Complex128Array( buf, 16 )\n    <Complex128Array>\n    > len = arr2.length\n    29\n    > var arr3 = new Complex128Array( buf, 16, 20 )\n    <Complex128Array>\n    > len = arr3.length\n    20\n\n\nComplex128Array.from( src[, clbk[, thisArg]] )\n    Creates a new 128-bit complex number array from an array-like object or an\n    iterable.\n\n    A callback function is provided two arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    clbk: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n    \n    Returns\n    -------\n    out: Complex128Array\n        A typed array.\n    \n    Examples\n    --------\n    > function clbkFcn( v ) { return v * 2.0 };\n    > var arr = Complex128Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\n    <Complex128Array>\n    > var len = arr.length\n    2\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    -2.0\n\n\nComplex128Array.of( element0[, element1[, ...elementN]] )\n    Creates a new 128-bit complex number array from a variable number of\n    arguments.\n\n    Parameters\n    ----------\n    element0: number|ComplexLike\n        Array element.\n\n    element1: number |ComplexLike(optional)\n        Array element.\n\n    elementN: ...number|ComplexLike (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Complex128Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Complex128Array.of( 1.0, -1.0, 2.0, -2.0 )\n    <Complex128Array>\n    > var len = arr.length\n    2\n    > var z1 = new Complex128( 1.0, -1.0 );\n    > var z2 = new Complex128( 2.0, -2.0 );\n    > arr = Complex128Array.of( z1, z2 )\n    <Complex128Array>\n    > len = arr.length\n    2\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    -1.0\n\n\nComplex128Array.BYTES_PER_ELEMENT\n    The size of each array element in bytes.\n\n    Examples\n    --------\n    > var nbytes = Complex128Array.BYTES_PER_ELEMENT\n    16\n\n\nComplex128Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > var str = Complex128Array.name\n    'Complex128Array'\n\n\nComplex128Array.prototype.buffer\n    Pointer to the underlying data buffer.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 2 )\n    <Complex128Array>\n    > var buf = arr.buffer\n    <ArrayBuffer>\n\n\nComplex128Array.prototype.byteLength\n    Length of the array in bytes.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 10 )\n    <Complex128Array>\n    > var nbytes = arr.byteLength\n    160\n\n\nComplex128Array.prototype.byteOffset\n    Offset (in bytes) of the array from the start of its underlying\n    ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 10 )\n    <Complex128Array>\n    > var offset = arr.byteOffset\n    0\n    > var buf = new ArrayBuffer( 480 );\n    > arr = new Complex128Array( buf, 128 )\n    <Complex128Array>\n    > offset = arr.byteOffset\n    128\n\n\nComplex128Array.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 10 )\n    <Complex128Array>\n    > arr.BYTES_PER_ELEMENT\n    16\n\n\nComplex128Array.prototype.length\n    The number of array elements.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 10 )\n    <Complex128Array>\n    > var len = arr.length\n    10\n\n\nComplex128Array.prototype.at( i )\n    Returns an array element located at integer position (index) `i`, with\n    support for both nonnegative and negative integer positions.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n\n    Returns\n    -------\n    out: Complex128|void\n        An array element.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var z = arr.at( 1 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    -2.0\n\n\nComplex128Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n    \n    start: integer\n        Source start index position.\n    \n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Complex128Array\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex128Array>\n    > arr.copyWithin( 0, 2 )\n    <Complex128Array>\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    -3.0\n\n\nComplex128Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var it = arr.entries();\n    > var v = it.next().value\n    [ 0, <Complex128> ]\n    > var re = real( v[ 1 ] )\n    1.0\n    > var im = imag( v[ 1 ] )\n    -1.0\n    > v = it.next().value\n    [ 1, <Complex128> ]\n    > re = real( v[ 1 ] )\n    2.0\n    > im = imag( v[ 1 ] )\n    -2.0\n    > v = it.next().value\n    [ 2, <Complex128> ]\n    > re = real( v[ 1 ] )\n    3.0\n    > im = imag( v[ 1 ] )\n    -3.0\n    > var bool = it.next().done\n    true\n\n\nComplex128Array.prototype.every( predicate[, thisArg] )\n    Returns a boolean indicating whether all elements in the array pass a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all elements pass the test.\n\n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) > 0.0 ); };\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var bool = arr.every( predicate )\n    true\n\n\nComplex128Array.prototype.fill( value[, start[, end]] )\n    Returns a modified typed array filled with a fill value.\n\n    Parameters\n    ----------\n    value: Complex128\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Complex128Array\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( 3 )\n    <Complex128Array>\n    > arr.fill( new Complex128( 1.0, 1.0 ) );\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    1.0\n    > z = arr.get( 1 )\n    <Complex128>\n    > re = real( z )\n    1.0\n    > im = imag( z )\n    1.0\n    > z = arr.get( 2 )\n    <Complex128>\n    > re = real( z )\n    1.0\n    > im = imag( z )\n    1.0\n\n\nComplex128Array.prototype.filter( predicate[, thisArg] )\n    Returns a new array containing the elements of an array which pass a test\n    implemented by a predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Complex128Array\n        A new typed array.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var out = arr.filter( predicate )\n    <Complex128Array>\n    > var len = out.length\n    1\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    2.0\n\n\nComplex128Array.prototype.find( predicate[, thisArg] )\n    Returns the first element in an array for which a predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    out: Complex128|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var z = arr.find( predicate )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    1.0\n\n\nComplex128Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var idx = arr.findIndex( predicate )\n    0\n\n\nComplex128Array.prototype.findLast( predicate[, thisArg] )\n    Returns the last element in an array for which a predicate function returns\n    a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.  \n    \n    Returns\n    -------\n    out: Complex128|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var z = arr.findLast( predicate )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    2.0\n\n\nComplex128Array.prototype.findLastIndex( predicate[, thisArg] )\n    Returns the index of the last element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var idx = arr.findLastIndex( predicate )\n    1\n\n\nComplex128Array.prototype.forEach( clbk[, thisArg] )\n    Invokes a function once for each array element.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Examples\n    --------\n    > var str = '%';\n    > function clbk( v ) { str += v.toString() + '%'; };\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > arr.forEach( clbk );\n    > str\n    '%1 - 1i%2 - 2i%'\n\n\nComplex128Array.prototype.get( i )\n    Returns an array element located at integer position (index) `i`.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n    \n    Returns\n    -------\n    out: Complex128|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var z = arr.get( 1 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    -2.0\n\n\nComplex128Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a provided value.\n\n    Parameters\n    ----------\n    searchElement: Complex128\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n    \n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex128Array>\n    > var bool = arr.includes( new Complex128( 3.0, -3.0 ) )\n    true\n    > bool = arr.includes( new Complex128( 3.0, -3.0 ), 3 )\n    false\n\n\nComplex128Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the first index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: Complex128\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex128Array>\n    > var idx = arr.indexOf( new Complex128( 3.0, -3.0 ) )\n    2\n    > idx = arr.indexOf( new Complex128( 3.0, -3.0 ), 3 )\n    -1\n\n\nComplex128Array.prototype.join( [separator] )\n    Returns a new string by concatenating all array elements separated by a\n    separator string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        Separator string. Default: ','.\n    \n    Returns\n    -------\n    out: string\n        Array serialized as a string.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var str = arr.join()\n    '1 - 1i,2 - 2i'\n    > str = arr.join( '/' )\n    '1 - 1i/2 - 2i'\n\n\nComplex128Array.prototype.keys()\n    Returns an iterator for iterating over each index key in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array index keys.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var it = arr.keys();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().done\n    true\n\n\nComplex128Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the last index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: Complex128\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: out.length-1.\n    \n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex128Array>\n    > var idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ) )\n    3\n    > idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ), 2 )\n    0\n\n\nComplex128Array.prototype.map( clbk[, thisArg] )\n    Returns a new array with each element being the result of a provided\n    callback function.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Complex128Array\n        A new typed array.\n    \n    Examples\n    --------\n    > function clbk( v ) { return v; };\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var out = arr.map( clbk )\n    <Complex128Array>\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    -1.0\n    > z = out.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    -2.0\n\n\nComplex128Array.prototype.reduce( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in order, passing\n    in the return value from the calculation on the preceding element and\n    returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.    \n\n    initialValue: any (optional)\n        Initial accumulation value.\n    \n    Returns\n    -------\n    out: any\n        Accumulated result.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var z = arr.reduce( base.cadd )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    -3.0\n\n\nComplex128Array.prototype.reduceRight( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in reverse order,\n    passing in the return value from the calculation on the preceding element\n    and returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.\n\n    initialValue: any (optional)\n        Initial accumulation value.\n    \n    Returns\n    -------\n    out: any\n        Accumulated result.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var z = arr.reduceRight( base.cadd )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    -3.0\n\n\nComplex128Array.prototype.reverse()\n    Reverses the array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Complex128Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > arr.reverse();\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    -3.0\n    > z = arr.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    -2.0\n    > z = arr.get( 2 )\n    <Complex128>\n    > re = real( z )\n    1.0\n    > im = imag( z )\n    -1.0\n\n\nComplex128Array.prototype.set( z[, i] )\n    Sets one or more array elements.\n\n    If provided a single argument, the method sets array elements starting at\n    position (index) `i = 0`. To set elements starting elsewhere in the array,\n    provide an index argument `i`.\n\n    To set one or more array elements, provide an array-like object containing\n    either complex numbers or interleaved real and imaginary components.\n\n    Parameters\n    ----------\n    z: Complex128|Complex128Array|ArrayLikeObject\n        Complex number or complex number array.\n\n    i: integer (optional)\n        Array index at which to start setting elements. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 2 )\n    <Complex128Array>\n    > arr.set( new Complex128( 1.0, -1.0 ) );\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    -1.0\n    > arr.set( new Complex128( 2.0, -2.0 ), 1 );\n    > z = arr.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    -2.0\n\n\nComplex128Array.prototype.slice( [start[, end]] )\n    Copies a portion of a typed array to a new typed array.\n\n    Parameters\n    ----------\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n    \n    Returns\n    -------\n    out: Complex128Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var out = arr.slice( 1 )\n    <Complex128Array>\n    > var len = out.length\n    2\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    -2.0\n    > z = out.get( 1 )\n    <Complex128>\n    > re = real( z )\n    3.0\n    > im = imag( z )\n    -3.0\n\n\nComplex128Array.prototype.some( predicate[, thisArg] )\n    Returns a boolean indicating whether at least one element passes a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n    \n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one element passes the test.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var bool = arr.some( predicate )\n    true\n\n\nComplex128Array.prototype.sort( compareFunction )\n    Sorts an array in-place.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first element for comparison.\n    - b: second element for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFunction: Function\n        Comparison function.\n    \n    Returns\n    -------\n    out: Complex128Array\n        Modified array.\n    \n    Examples\n    --------\n    > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n    > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex128Array>\n    > arr.sort( compare );\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    -1.0\n    > z = arr.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    -2.0\n    > z = arr.get( 2 )\n    <Complex128>\n    > re = real( z )\n    3.0\n    > im = imag( z )\n    -3.0\n\n\nComplex128Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array view over the same underlying `ArrayBuffer` and\n    with the same underlying data type as the host array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Complex128Array\n        New typed array view.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex128Array>\n    > var out = arr.subarray( 1, 3 )\n    <Complex128Array>\n    > var len = out.length\n    2\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    -2.0\n    > z = out.get( 1 )\n    <Complex128>\n    > re = real( z )\n    3.0\n    > im = imag( z )\n    -3.0\n\n\nComplex128Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array (optional)\n        Locale identifier(s).\n    \n    options: Object (optional)\n        An object containing serialization options.\n    \n    Returns\n    -------\n    str: string\n        Local-specific string.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0 ] )\n    <Complex128Array>\n    > var str = arr.toLocaleString()\n    '1 + 1i,2 + 2i'\n\n\nComplex128Array.prototype.toReversed()\n    Returns a new typed array containing the elements in reversed order.\n\n    Returns\n    -------\n    out: Complex128Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\n    <Complex128Array>\n    > var out = arr.toReversed()\n    <Complex128Array>\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    3.0\n    > z = out.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    2.0\n    > z = out.get( 2 )\n    <Complex128>\n    > re = real( z )\n    1.0\n    > im = imag( z )\n    1.0\n\n\nComplex128Array.prototype.toSorted( compareFcn )\n    Returns a new typed array containing the elements in sorted order.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first element for comparison.\n    - b: second element for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFcn: Function\n        Comparison function.\n    \n    Returns\n    -------\n    out: Complex128Array\n        New typed array.\n    \n    Examples\n    --------\n    > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n    > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex128Array>\n    > var out = arr.toSorted( compare );\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    -1.0\n    > z = out.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    -2.0\n    > z = out.get( 2 )\n    <Complex128>\n    > re = real( z )\n    3.0\n    > im = imag( z )\n    -3.0\n\n\nComplex128Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        String serialization of the array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\n    <Complex128Array>\n    > var str = arr.toString()\n    '1 + 1i,2 - 2i,3 + 3i'\n\n\nComplex128Array.prototype.values()\n    Returns an iterator for iterating over each value in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array values.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var it = arr.values();\n    > var v = it.next().value\n    <Complex128>\n    > var re = real( v )\n    1.0\n    > var im = imag( v )\n    -1.0\n    > v = it.next().value\n    <Complex128>\n    > re = real( v )\n    2.0\n    > im = imag( v )\n    -2.0\n    > var bool = it.next().done\n    true\n\n\nComplex128Array.prototype.with( index, value )\n    Returns a new typed array with the element at a provided index replaced\n    with a provided value.\n\n    Parameters\n    ----------\n    index: integer\n        Element index.\n    \n    value: Complex128\n        Element value.  \n\n    Returns\n    -------\n    out: Complex128Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n    <Complex128Array>\n    > var z = out.get( 1 )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    -3.0\n\n\n    See Also\n    --------\n    Complex64Array, complex, Complex128","Complex128Array.from":"\nComplex128Array.from( src[, clbk[, thisArg]] )\n    Creates a new 128-bit complex number array from an array-like object or an\n    iterable.\n\n    A callback function is provided two arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    clbk: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n    \n    Returns\n    -------\n    out: Complex128Array\n        A typed array.\n    \n    Examples\n    --------\n    > function clbkFcn( v ) { return v * 2.0 };\n    > var arr = Complex128Array.from( [ 1.0, -1.0, 2.0, -2.0 ], clbkFcn )\n    <Complex128Array>\n    > var len = arr.length\n    2\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    -2.0","Complex128Array.of":"\nComplex128Array.of( element0[, element1[, ...elementN]] )\n    Creates a new 128-bit complex number array from a variable number of\n    arguments.\n\n    Parameters\n    ----------\n    element0: number|ComplexLike\n        Array element.\n\n    element1: number |ComplexLike(optional)\n        Array element.\n\n    elementN: ...number|ComplexLike (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Complex128Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Complex128Array.of( 1.0, -1.0, 2.0, -2.0 )\n    <Complex128Array>\n    > var len = arr.length\n    2\n    > var z1 = new Complex128( 1.0, -1.0 );\n    > var z2 = new Complex128( 2.0, -2.0 );\n    > arr = Complex128Array.of( z1, z2 )\n    <Complex128Array>\n    > len = arr.length\n    2\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    -1.0","Complex128Array.BYTES_PER_ELEMENT":"\nComplex128Array.BYTES_PER_ELEMENT\n    The size of each array element in bytes.\n\n    Examples\n    --------\n    > var nbytes = Complex128Array.BYTES_PER_ELEMENT\n    16","Complex128Array.name":"\nComplex128Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > var str = Complex128Array.name\n    'Complex128Array'","Complex128Array.prototype.buffer":"\nComplex128Array.prototype.buffer\n    Pointer to the underlying data buffer.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 2 )\n    <Complex128Array>\n    > var buf = arr.buffer\n    <ArrayBuffer>","Complex128Array.prototype.byteLength":"\nComplex128Array.prototype.byteLength\n    Length of the array in bytes.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 10 )\n    <Complex128Array>\n    > var nbytes = arr.byteLength\n    160","Complex128Array.prototype.byteOffset":"\nComplex128Array.prototype.byteOffset\n    Offset (in bytes) of the array from the start of its underlying\n    ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 10 )\n    <Complex128Array>\n    > var offset = arr.byteOffset\n    0\n    > var buf = new ArrayBuffer( 480 );\n    > arr = new Complex128Array( buf, 128 )\n    <Complex128Array>\n    > offset = arr.byteOffset\n    128","Complex128Array.prototype.BYTES_PER_ELEMENT":"\nComplex128Array.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 10 )\n    <Complex128Array>\n    > arr.BYTES_PER_ELEMENT\n    16","Complex128Array.prototype.length":"\nComplex128Array.prototype.length\n    The number of array elements.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 10 )\n    <Complex128Array>\n    > var len = arr.length\n    10","Complex128Array.prototype.at":"\nComplex128Array.prototype.at( i )\n    Returns an array element located at integer position (index) `i`, with\n    support for both nonnegative and negative integer positions.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n\n    Returns\n    -------\n    out: Complex128|void\n        An array element.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var z = arr.at( 1 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    -2.0","Complex128Array.prototype.copyWithin":"\nComplex128Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n    \n    start: integer\n        Source start index position.\n    \n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Complex128Array\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex128Array>\n    > arr.copyWithin( 0, 2 )\n    <Complex128Array>\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    -3.0","Complex128Array.prototype.entries":"\nComplex128Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var it = arr.entries();\n    > var v = it.next().value\n    [ 0, <Complex128> ]\n    > var re = real( v[ 1 ] )\n    1.0\n    > var im = imag( v[ 1 ] )\n    -1.0\n    > v = it.next().value\n    [ 1, <Complex128> ]\n    > re = real( v[ 1 ] )\n    2.0\n    > im = imag( v[ 1 ] )\n    -2.0\n    > v = it.next().value\n    [ 2, <Complex128> ]\n    > re = real( v[ 1 ] )\n    3.0\n    > im = imag( v[ 1 ] )\n    -3.0\n    > var bool = it.next().done\n    true","Complex128Array.prototype.every":"\nComplex128Array.prototype.every( predicate[, thisArg] )\n    Returns a boolean indicating whether all elements in the array pass a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all elements pass the test.\n\n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) > 0.0 ); };\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var bool = arr.every( predicate )\n    true","Complex128Array.prototype.fill":"\nComplex128Array.prototype.fill( value[, start[, end]] )\n    Returns a modified typed array filled with a fill value.\n\n    Parameters\n    ----------\n    value: Complex128\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Complex128Array\n        Modified array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( 3 )\n    <Complex128Array>\n    > arr.fill( new Complex128( 1.0, 1.0 ) );\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    1.0\n    > z = arr.get( 1 )\n    <Complex128>\n    > re = real( z )\n    1.0\n    > im = imag( z )\n    1.0\n    > z = arr.get( 2 )\n    <Complex128>\n    > re = real( z )\n    1.0\n    > im = imag( z )\n    1.0","Complex128Array.prototype.filter":"\nComplex128Array.prototype.filter( predicate[, thisArg] )\n    Returns a new array containing the elements of an array which pass a test\n    implemented by a predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Complex128Array\n        A new typed array.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var out = arr.filter( predicate )\n    <Complex128Array>\n    > var len = out.length\n    1\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    2.0","Complex128Array.prototype.find":"\nComplex128Array.prototype.find( predicate[, thisArg] )\n    Returns the first element in an array for which a predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    out: Complex128|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var z = arr.find( predicate )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    1.0","Complex128Array.prototype.findIndex":"\nComplex128Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var idx = arr.findIndex( predicate )\n    0","Complex128Array.prototype.findLast":"\nComplex128Array.prototype.findLast( predicate[, thisArg] )\n    Returns the last element in an array for which a predicate function returns\n    a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.  \n    \n    Returns\n    -------\n    out: Complex128|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var z = arr.findLast( predicate )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    2.0","Complex128Array.prototype.findLastIndex":"\nComplex128Array.prototype.findLastIndex( predicate[, thisArg] )\n    Returns the index of the last element in an array for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var idx = arr.findLastIndex( predicate )\n    1","Complex128Array.prototype.forEach":"\nComplex128Array.prototype.forEach( clbk[, thisArg] )\n    Invokes a function once for each array element.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Execution context.\n    \n    Examples\n    --------\n    > var str = '%';\n    > function clbk( v ) { str += v.toString() + '%'; };\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > arr.forEach( clbk );\n    > str\n    '%1 - 1i%2 - 2i%'","Complex128Array.prototype.get":"\nComplex128Array.prototype.get( i )\n    Returns an array element located at integer position (index) `i`.\n\n    If provided an index outside the array index range, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    i: integer\n        Element index.\n    \n    Returns\n    -------\n    out: Complex128|void\n        Array element or `undefined`.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var z = arr.get( 1 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    -2.0","Complex128Array.prototype.includes":"\nComplex128Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a provided value.\n\n    Parameters\n    ----------\n    searchElement: Complex128\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n    \n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex128Array>\n    > var bool = arr.includes( new Complex128( 3.0, -3.0 ) )\n    true\n    > bool = arr.includes( new Complex128( 3.0, -3.0 ), 3 )\n    false","Complex128Array.prototype.indexOf":"\nComplex128Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the first index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: Complex128\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex128Array>\n    > var idx = arr.indexOf( new Complex128( 3.0, -3.0 ) )\n    2\n    > idx = arr.indexOf( new Complex128( 3.0, -3.0 ), 3 )\n    -1","Complex128Array.prototype.join":"\nComplex128Array.prototype.join( [separator] )\n    Returns a new string by concatenating all array elements separated by a\n    separator string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        Separator string. Default: ','.\n    \n    Returns\n    -------\n    out: string\n        Array serialized as a string.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var str = arr.join()\n    '1 - 1i,2 - 2i'\n    > str = arr.join( '/' )\n    '1 - 1i/2 - 2i'","Complex128Array.prototype.keys":"\nComplex128Array.prototype.keys()\n    Returns an iterator for iterating over each index key in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array index keys.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var it = arr.keys();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().done\n    true","Complex128Array.prototype.lastIndexOf":"\nComplex128Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the last index at which a given element can be found.\n\n    If method does not find a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: Complex128\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index at which to start the search. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: out.length-1.\n    \n    Returns\n    -------\n    out: integer\n        Array index or `-1`.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex128Array>\n    > var idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ) )\n    3\n    > idx = arr.lastIndexOf( new Complex128( 1.0, -1.0 ), 2 )\n    0","Complex128Array.prototype.map":"\nComplex128Array.prototype.map( clbk[, thisArg] )\n    Returns a new array with each element being the result of a provided\n    callback function.\n\n    A callback function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    clbk: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Complex128Array\n        A new typed array.\n    \n    Examples\n    --------\n    > function clbk( v ) { return v; };\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var out = arr.map( clbk )\n    <Complex128Array>\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    -1.0\n    > z = out.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    -2.0","Complex128Array.prototype.reduce":"\nComplex128Array.prototype.reduce( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in order, passing\n    in the return value from the calculation on the preceding element and\n    returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.    \n\n    initialValue: any (optional)\n        Initial accumulation value.\n    \n    Returns\n    -------\n    out: any\n        Accumulated result.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var z = arr.reduce( base.cadd )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    -3.0","Complex128Array.prototype.reduceRight":"\nComplex128Array.prototype.reduceRight( reducerFn[, initialValue] )\n    Applies a provided function to each element of the array, in reverse order,\n    passing in the return value from the calculation on the preceding element\n    and returning the accumulated result upon completion.\n\n    A reducer function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    reducerFn: Function\n        Function to apply to each array element.\n\n    initialValue: any (optional)\n        Initial accumulation value.\n    \n    Returns\n    -------\n    out: any\n        Accumulated result.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var z = arr.reduceRight( base.cadd )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    -3.0","Complex128Array.prototype.reverse":"\nComplex128Array.prototype.reverse()\n    Reverses the array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Complex128Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > arr.reverse();\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    -3.0\n    > z = arr.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    -2.0\n    > z = arr.get( 2 )\n    <Complex128>\n    > re = real( z )\n    1.0\n    > im = imag( z )\n    -1.0","Complex128Array.prototype.set":"\nComplex128Array.prototype.set( z[, i] )\n    Sets one or more array elements.\n\n    If provided a single argument, the method sets array elements starting at\n    position (index) `i = 0`. To set elements starting elsewhere in the array,\n    provide an index argument `i`.\n\n    To set one or more array elements, provide an array-like object containing\n    either complex numbers or interleaved real and imaginary components.\n\n    Parameters\n    ----------\n    z: Complex128|Complex128Array|ArrayLikeObject\n        Complex number or complex number array.\n\n    i: integer (optional)\n        Array index at which to start setting elements. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( 2 )\n    <Complex128Array>\n    > arr.set( new Complex128( 1.0, -1.0 ) );\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    -1.0\n    > arr.set( new Complex128( 2.0, -2.0 ), 1 );\n    > z = arr.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    -2.0","Complex128Array.prototype.slice":"\nComplex128Array.prototype.slice( [start[, end]] )\n    Copies a portion of a typed array to a new typed array.\n\n    Parameters\n    ----------\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n    \n    Returns\n    -------\n    out: Complex128Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var out = arr.slice( 1 )\n    <Complex128Array>\n    > var len = out.length\n    2\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    -2.0\n    > z = out.get( 1 )\n    <Complex128>\n    > re = real( z )\n    3.0\n    > im = imag( z )\n    -3.0","Complex128Array.prototype.some":"\nComplex128Array.prototype.some( predicate[, thisArg] )\n    Returns a boolean indicating whether at least one element passes a test.\n\n    A predicate function is provided the following arguments:\n\n    - value: current array element.\n    - index: current array element index.\n    - arr: the array on which the method was called.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n    \n    thisArg: Any (optional)\n        Execution context.\n    \n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one element passes the test.\n    \n    Examples\n    --------\n    > function predicate( v ) { return ( real( v ) === imag( v ) ); };\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, 2.0, 3.0, -3.0 ] )\n    <Complex128Array>\n    > var bool = arr.some( predicate )\n    true","Complex128Array.prototype.sort":"\nComplex128Array.prototype.sort( compareFunction )\n    Sorts an array in-place.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first element for comparison.\n    - b: second element for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFunction: Function\n        Comparison function.\n    \n    Returns\n    -------\n    out: Complex128Array\n        Modified array.\n    \n    Examples\n    --------\n    > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n    > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex128Array>\n    > arr.sort( compare );\n    > var z = arr.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    -1.0\n    > z = arr.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    -2.0\n    > z = arr.get( 2 )\n    <Complex128>\n    > re = real( z )\n    3.0\n    > im = imag( z )\n    -3.0","Complex128Array.prototype.subarray":"\nComplex128Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array view over the same underlying `ArrayBuffer` and\n    with the same underlying data type as the host array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Complex128Array\n        New typed array view.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0, 3.0, -3.0, 4.0, -4.0 ] )\n    <Complex128Array>\n    > var out = arr.subarray( 1, 3 )\n    <Complex128Array>\n    > var len = out.length\n    2\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    2.0\n    > var im = imag( z )\n    -2.0\n    > z = out.get( 1 )\n    <Complex128>\n    > re = real( z )\n    3.0\n    > im = imag( z )\n    -3.0","Complex128Array.prototype.toLocaleString":"\nComplex128Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array (optional)\n        Locale identifier(s).\n    \n    options: Object (optional)\n        An object containing serialization options.\n    \n    Returns\n    -------\n    str: string\n        Local-specific string.\n\n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0 ] )\n    <Complex128Array>\n    > var str = arr.toLocaleString()\n    '1 + 1i,2 + 2i'","Complex128Array.prototype.toReversed":"\nComplex128Array.prototype.toReversed()\n    Returns a new typed array containing the elements in reversed order.\n\n    Returns\n    -------\n    out: Complex128Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, 2.0, 3.0, 3.0 ] )\n    <Complex128Array>\n    > var out = arr.toReversed()\n    <Complex128Array>\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    3.0\n    > z = out.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    2.0\n    > z = out.get( 2 )\n    <Complex128>\n    > re = real( z )\n    1.0\n    > im = imag( z )\n    1.0","Complex128Array.prototype.toSorted":"\nComplex128Array.prototype.toSorted( compareFcn )\n    Returns a new typed array containing the elements in sorted order.\n\n    A comparison function determines the order of the array elements. The\n    function is provided two arguments:\n\n    - a: first element for comparison.\n    - b: second element for comparison.\n\n    The function should return a value less than zero if `a` comes before `b`,\n    a value greater than zero if `a` comes after `b`, and zero if `a` and `b`\n    are equivalent.\n\n    Parameters\n    ----------\n    compareFcn: Function\n        Comparison function.\n    \n    Returns\n    -------\n    out: Complex128Array\n        New typed array.\n    \n    Examples\n    --------\n    > function compare( a, b ) { return ( real( a ) - real( b ) ); };\n    > var arr = new Complex128Array( [ 2.0, -2.0, 3.0, -3.0, 1.0, -1.0 ] )\n    <Complex128Array>\n    > var out = arr.toSorted( compare );\n    > var z = out.get( 0 )\n    <Complex128>\n    > var re = real( z )\n    1.0\n    > var im = imag( z )\n    -1.0\n    > z = out.get( 1 )\n    <Complex128>\n    > re = real( z )\n    2.0\n    > im = imag( z )\n    -2.0\n    > z = out.get( 2 )\n    <Complex128>\n    > re = real( z )\n    3.0\n    > im = imag( z )\n    -3.0","Complex128Array.prototype.toString":"\nComplex128Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        String serialization of the array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, 1.0, 2.0, -2.0, 3.0, 3.0 ] )\n    <Complex128Array>\n    > var str = arr.toString()\n    '1 + 1i,2 - 2i,3 + 3i'","Complex128Array.prototype.values":"\nComplex128Array.prototype.values()\n    Returns an iterator for iterating over each value in a typed array.\n\n    Returns\n    -------\n    iterator: Iterator\n        Iterator for iterating over array values.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var it = arr.values();\n    > var v = it.next().value\n    <Complex128>\n    > var re = real( v )\n    1.0\n    > var im = imag( v )\n    -1.0\n    > v = it.next().value\n    <Complex128>\n    > re = real( v )\n    2.0\n    > im = imag( v )\n    -2.0\n    > var bool = it.next().done\n    true","Complex128Array.prototype.with":"\nComplex128Array.prototype.with( index, value )\n    Returns a new typed array with the element at a provided index replaced\n    with a provided value.\n\n    Parameters\n    ----------\n    index: integer\n        Element index.\n    \n    value: Complex128\n        Element value.  \n\n    Returns\n    -------\n    out: Complex128Array\n        New typed array.\n    \n    Examples\n    --------\n    > var arr = new Complex128Array( [ 1.0, -1.0, 2.0, -2.0 ] )\n    <Complex128Array>\n    > var out = arr.with( 1, new Complex64( 3.0, -3.0 ) )\n    <Complex128Array>\n    > var z = out.get( 1 )\n    <Complex128>\n    > var re = real( z )\n    3.0\n    > var im = imag( z )\n    -3.0\n\n\n    See Also\n    --------\n    Complex64Array, complex, Complex128","complexarray":"\ncomplexarray( [dtype] )\n    Creates a complex typed array.\n\n    The function supports the following data types:\n\n    - complex128: double-precision complex floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n\n    The default typed array data type is `complex128`.\n\n    Parameters\n    ----------\n    dtype: string (optional)\n        Data type. Default: 'complex128'.\n\n    Returns\n    -------\n    out: ComplexArray\n        A complex number typed array.\n\n    Examples\n    --------\n    > var arr = complexarray()\n    <Complex128Array>\n    > arr = complexarray( 'complex64' )\n    <Complex64Array>\n\n\ncomplexarray( length[, dtype] )\n    Returns a complex number typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Array length.\n\n    dtype: string (optional)\n        Data type. Default: 'complex128'.\n\n    Returns\n    -------\n    out: ComplexArray\n        A complex number typed array.\n\n    Examples\n    --------\n    > var arr = complexarray( 5 )\n    <Complex128Array>\n    > arr = complexarray( 5, 'complex64' )\n    <Complex64Array>\n\n\ncomplexarray( complexarray[, dtype] )\n    Creates a complex number typed array from another complex number typed\n    array.\n\n    Parameters\n    ----------\n    complexarray: ComplexArray\n        Complex number typed array from which to generate another complex number\n        typed array.\n\n    dtype: string (optional)\n        Data type. Default: 'complex128'.\n\n    Returns\n    -------\n    out: ComplexArray\n        A complex number typed array.\n\n    Examples\n    --------\n    > var arr1 = complexarray( [ 0.5, 0.5, 0.5, 0.5 ] );\n    > var arr2 = complexarray( arr1, 'complex64' )\n    <Complex64Array>\n\n\ncomplexarray( obj[, dtype] )\n    Creates a complex number typed array from an array-like object or iterable.\n\n    If an array-like object contains interleaved real and imaginary components,\n    the array-like object must have a length which is a multiple of two.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate an array.\n\n    dtype: string (optional)\n        Data type. Default: 'complex128'.\n\n    Returns\n    -------\n    out: ComplexArray\n        A complex number typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 0.5, 0.5, 0.5, 0.5 ];\n    > var arr2 = complexarray( arr1, 'complex64' )\n    <Complex64Array>\n\n\ncomplexarray( buffer[, byteOffset[, length]][, dtype] )\n    Returns a complex number typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first array element.\n        Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    dtype: string (optional)\n        Data type. Default: 'complex128'.\n\n    Returns\n    -------\n    out: ComplexArray\n        A complex number typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 64 );\n    > var arr = complexarray( buf, 0, 8, 'complex64' )\n    <Complex64Array>\n\n    See Also\n    --------\n    typedarray, realarray\n","complexarrayCtors":"\ncomplexarrayCtors( dtype )\n    Returns a complex typed array constructor.\n\n    The function returns constructors for the following data types:\n\n    - complex64: single-precision floating-point complex numbers.\n    - complex128: double-precision floating-point complex numbers.\n\n    Parameters\n    ----------\n    dtype: string\n        Data type.\n\n    Returns\n    -------\n    out: Function|null\n        Complex typed array constructor.\n\n    Examples\n    --------\n    > var ctor = complexarrayCtors( 'complex64' )\n    <Function>\n    > ctor = complexarrayCtors( 'float32' )\n    null\n\n    See Also\n    --------\n    arrayCtors, typedarrayCtors, realarrayCtors\n","complexarrayDataTypes":"\ncomplexarrayDataTypes()\n    Returns a list of complex typed array data types.\n\n    Returns\n    -------\n    out: Array<string>\n        List of complex typed array data types.\n\n    Examples\n    --------\n    > var out = complexarrayDataTypes()\n    <Array>\n\n    See Also\n    --------\n    arrayDataTypes, typedarrayDataTypes, realarrayDataTypes, ndarrayDataTypes\n","complexCtors":"\ncomplexCtors( dtype )\n    Returns a complex number constructor.\n\n    The function returns constructors for the following data types:\n\n    - complex64: single-precision complex floating-point numbers.\n    - complex128: double-precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    dtype: string\n        Data type.\n\n    Returns\n    -------\n    out: Function|null\n        Constructor.\n\n    Examples\n    --------\n    > var ctor = complexCtors( 'complex128' )\n    <Function>\n    > ctor = complexCtors( 'complex' )\n    null\n\n    See Also\n    --------\n    complexarrayCtors\n","complexDataType":"\ncomplexDataType( value )\n    Returns the data type of a complex number object.\n\n    If provided an argument having an unknown or unsupported type, the function\n    returns `null`.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    out: string|null\n        Data type.\n\n    Examples\n    --------\n    > var v = new Complex128( 1.0, 2.0 );\n    > var dt = complexDataType( v )\n    'complex128'\n    > dt = complexDataType( 'beep' )\n    null\n\n    See Also\n    --------\n    arrayDataType\n","complexDataTypes":"\ncomplexDataTypes()\n    Returns a list of complex number data types.\n\n    The output array contains the following data types:\n\n    - complex64: single-precision complex floating-point numbers.\n    - complex128: double-precision complex floating-point numbers.\n\n    Returns\n    -------\n    out: Array<string>\n        List of complex number data types.\n\n    Examples\n    --------\n    > var out = complexDataTypes()\n    <Array>\n\n    See Also\n    --------\n    complexarrayDataTypes\n","complexPromotionRules":"\ncomplexPromotionRules( [dtype1, dtype2] )\n    Returns the complex number data type with the smallest size and closest\n    \"kind\" to which data types can be safely cast.\n\n    If not provided data types, the function returns a type promotion table.\n\n    If a data type to which data types can be safely cast does *not* exist (or\n    is not supported), the function returns `-1`.\n\n    If provided an unrecognized data type, the function returns `null`.\n\n    Parameters\n    ----------\n    dtype1: string (optional)\n        Data type.\n\n    dtype2: string (optional)\n        Data type.\n\n    Returns\n    -------\n    out: Object|string|integer|null\n        Promotion rule(s).\n\n    Examples\n    --------\n    > var out = complexPromotionRules( 'complex128', 'complex64' )\n    'complex128'\n\n    See Also\n    --------\n    arrayPromotionRules, ndarrayPromotionRules\n","compose":"\ncompose( ...f )\n    Function composition.\n\n    Returns a composite function. Starting from the right, the composite\n    function evaluates each function and passes the result as an argument\n    to the next function. The result of the leftmost function is the result\n    of the whole.\n\n    Notes:\n\n    - Only the rightmost function is explicitly permitted to accept multiple\n      arguments. All other functions are evaluated as unary functions.\n    - The function will throw if provided fewer than two input arguments.\n\n    Parameters\n    ----------\n    f: ...Function\n        Functions to compose.\n\n    Returns\n    -------\n    out: Function\n        Composite function.\n\n    Examples\n    --------\n    > function a( x ) {\n    ...    return 2 * x;\n    ... }\n    > function b( x ) {\n    ...    return x + 3;\n    ... }\n    > function c( x ) {\n    ...    return x / 5;\n    ... }\n    > var f = compose( c, b, a );\n    > var z = f( 6 )\n    3\n\n    See Also\n    --------\n    composeAsync\n","composeAsync":"\ncomposeAsync( ...f )\n    Function composition.\n\n    Returns a composite function. Starting from the right, the composite\n    function evaluates each function and passes the result as the first argument\n    of the next function. The result of the leftmost function is the result\n    of the whole.\n\n    The last argument for each provided function is a `next` callback which\n    should be invoked upon function completion. The callback accepts two\n    arguments:\n\n    - error: error argument.\n    - result: function result.\n\n    If a composed function calls the `next` callback with a truthy `error`\n    argument, the composite function suspends execution and immediately calls\n    the `done` callback for subsequent `error` handling.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Only the rightmost function is explicitly permitted to accept multiple\n    arguments. All other functions are evaluated as binary functions.\n\n    The function will throw if provided fewer than two input arguments.\n\n    Parameters\n    ----------\n    f: ...Function\n        Functions to compose.\n\n    Returns\n    -------\n    out: Function\n        Composite function.\n\n    Examples\n    --------\n    > function a( x, next ) {\n    ...    setTimeout( onTimeout, 0 );\n    ...    function onTimeout() {\n    ...        next( null, 2*x );\n    ...    }\n    ... };\n    > function b( x, next ) {\n    ...    setTimeout( onTimeout, 0 );\n    ...    function onTimeout() {\n    ...        next( null, x+3 );\n    ...    }\n    ... };\n    > function c( x, next ) {\n    ...    setTimeout( onTimeout, 0 );\n    ...    function onTimeout() {\n    ...        next( null, x/5 );\n    ...    }\n    ... };\n    > var f = composeAsync( c, b, a );\n    > function done( error, result ) {\n    ...    if ( error ) {\n    ...        throw error;\n    ...    }\n    ...    console.log( result );\n    ... };\n    > f( 6, done )\n    3\n\n    See Also\n    --------\n    compose\n","configdir":"\nconfigdir( [p] )\n    Returns a directory for user-specific configuration files.\n\n    On Windows platforms, the function first checks for a `LOCALAPPDATA`\n    environment variable before checking for an `APPDATA` environment variable.\n    This means that machine specific user configuration files have precedence\n    over roaming user configuration files.\n\n    On non-Windows platforms, if the function is unable to locate the current\n    user's `home` directory, the function returns `null`. Similarly, on Windows\n    platforms, if the function is unable to locate an application data\n    directory, the function also returns `null`.\n\n    Parameters\n    ----------\n    p: string (optional)\n        Path to append to a base directory.\n\n    Returns\n    -------\n    out: string|null\n        Directory.\n\n    Examples\n    --------\n    > var dir = configdir()\n    e.g., '/Users/<username>/Library/Preferences'\n    > dir = configdir( 'appname/config' )\n    e.g., '/Users/<username>/Library/Preferences/appname/config'\n\n    See Also\n    --------\n    homedir, tmpdir\n","conj":"\nconj( z )\n    Returns the complex conjugate of a double-precision complex floating-point\n    number.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Complex128\n        Complex conjugate.\n\n    Examples\n    --------\n    > var z = new Complex128( 5.0, 3.0 );\n    > z.toString()\n    '5 + 3i'\n    > var v = conj( z );\n    > v.toString()\n    '5 - 3i'\n\n    See Also\n    --------\n    imag, real, reim\n","conjf":"\nconjf( z )\n    Returns the complex conjugate of a single-precision complex floating-point\n    number.\n\n    Parameters\n    ----------\n    z: Complex64\n        Complex number.\n\n    Returns\n    -------\n    out: Complex64\n        Complex conjugate.\n\n    Examples\n    --------\n    > var z = new Complex64( 5.0, 3.0 );\n    > z.toString()\n    '5 + 3i'\n    > var v = conjf( z );\n    > v.toString()\n    '5 - 3i'\n\n    See Also\n    --------\n    conj, imagf, realf, reimf\n","constantcase":"\nconstantcase( str )\n    Converts a string to constant case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Constant-cased string.\n\n    Examples\n    --------\n    > var out = constantcase( 'Hello World!' )\n    'HELLO_WORLD'\n    > out = constantcase( 'I am a tiny little teapot' )\n    'I_AM_A_TINY_LITTLE_TEAPOT'\n\n    See Also\n    --------\n    camelcase, kebabcase, pascalcase, snakecase","constantFunction":"\nconstantFunction( val )\n    Creates a function which always returns the same value.\n\n    Notes:\n\n    - When provided an object reference, the returned `function` always returns\n      the same reference.\n\n    Parameters\n    ----------\n    val: any\n        Value to always return.\n\n    Returns\n    -------\n    out: Function\n        Constant function.\n\n    Examples\n    --------\n    > var fcn = constantFunction( 3.14 );\n    > var v = fcn()\n    3.14\n    > v = fcn()\n    3.14\n    > v = fcn()\n    3.14\n\n    See Also\n    --------\n    argumentFunction, identity\n","constantStream":"\nconstantStream( value[, options] )\n    Returns a readable stream which always streams the same value.\n\n    In object mode, `null` is a reserved value. If provided `null`, the\n    returned stream will prematurely end.\n\n    Parameters\n    ----------\n    value: string|Buffer|Uint8Array|any\n        Value to stream.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing streaming.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = constantStream( 'beep', opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nconstantStream.factory( [value, ][options] )\n    Returns a function for creating readable streams which always stream the\n    same value.\n\n    If provided a value to stream, the returned function returns readable always\n    streams the provided value.\n\n    If not provided a value to stream, the returned function requires that a\n    value be provided at each invocation.\n\n    If provided only one argument and that argument is an object (either empty\n    or not containing any recognized options properties), the function treats\n    the argument as a value to be streamed, not as an options argument.\n\n    Parameters\n    ----------\n    value: string|Buffer|Uint8Array|any (optional)\n        Value to stream.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing streaming.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = constantStream.factory( opts );\n\n\nconstantStream.objectMode( value[, options] )\n    Returns an \"objectMode\" readable stream which always streams the same value.\n\n    In object mode, `null` is a reserved value. If provided `null`, the\n    returned stream will prematurely end.\n\n    Parameters\n    ----------\n    value: any\n        Value to stream.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before pausing streaming.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = constantStream.objectMode( 3.14, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    arrayStream, iteratorStream\n","constantStream.factory":"\nconstantStream.factory( [value, ][options] )\n    Returns a function for creating readable streams which always stream the\n    same value.\n\n    If provided a value to stream, the returned function returns readable always\n    streams the provided value.\n\n    If not provided a value to stream, the returned function requires that a\n    value be provided at each invocation.\n\n    If provided only one argument and that argument is an object (either empty\n    or not containing any recognized options properties), the function treats\n    the argument as a value to be streamed, not as an options argument.\n\n    Parameters\n    ----------\n    value: string|Buffer|Uint8Array|any (optional)\n        Value to stream.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing streaming.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = constantStream.factory( opts );","constantStream.objectMode":"\nconstantStream.objectMode( value[, options] )\n    Returns an \"objectMode\" readable stream which always streams the same value.\n\n    In object mode, `null` is a reserved value. If provided `null`, the\n    returned stream will prematurely end.\n\n    Parameters\n    ----------\n    value: any\n        Value to stream.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before pausing streaming.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = constantStream.objectMode( 3.14, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    arrayStream, iteratorStream","constructorName":"\nconstructorName( val )\n    Determines the name of a value's constructor.\n\n    Parameters\n    ----------\n    val: any\n        Input value.\n\n    Returns\n    -------\n    out: string\n        Name of a value's constructor.\n\n    Examples\n    --------\n    > var v = constructorName( 'a' )\n    'String'\n    > v = constructorName( {} )\n    'Object'\n    > v = constructorName( true )\n    'Boolean'\n\n    See Also\n    --------\n    functionName\n","contains":"\ncontains( val, searchValue[, position] )\n    Tests if an array-like value contains a search value.\n\n    When `val` is a string, the function checks whether the characters of the\n    search string are found in the input string. The search is case-sensitive.\n\n    When `val` is an array-like object, the function checks whether the input\n    array contains an element strictly equal to the specified search value.\n\n    For strings, this function is modeled after `String.prototype.includes`,\n    part of the ECMAScript 6 specification. This function is different from a\n    call to `String.prototype.includes.call` insofar as type-checking is\n    performed for all arguments.\n\n    The function does not distinguish between positive and negative zero.\n\n    If `position < 0`, the search is performed for the entire input array or\n    string.\n\n\n    Parameters\n    ----------\n    val: ArrayLike\n        Input value.\n\n    searchValue: any\n        Value to search for.\n\n    position: integer (optional)\n        Position at which to start searching for `searchValue`. Default: `0`.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an input value contains another value.\n\n    Examples\n    --------\n    > var bool = contains( 'Hello World', 'World' )\n    true\n    > bool = contains( 'Hello World', 'world' )\n    false\n    > bool = contains( [ 1, 2, 3, 4 ], 2 )\n    true\n    > bool = contains( [ NaN, 2, 3, 4 ], NaN )\n    true\n\n    // Supply a position:\n    > bool = contains( 'Hello World', 'Hello', 6 )\n    false\n    > bool = contains( [ true, NaN, false ], true, 1 )\n    false\n\n","convertArray":"\nconvertArray( arr, dtype )\n    Converts an input array to an array of a different data type.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject\n        Array to convert.\n\n    dtype: string\n        Output data type.\n\n    Returns\n    -------\n    out: Array|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var arr = [ 1.0, 2.0, 3.0, 4.0 ];\n    > var out = convertArray( arr, 'float32' )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    See Also\n    --------\n    convertArraySame\n","convertArraySame":"\nconvertArraySame( x, y )\n    Converts an input array to the same data type as a second input array.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject\n        Array to convert.\n\n    y: Array|TypedArray\n        Array having desired output data type.\n\n    Returns\n    -------\n    out: Array|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n    > var y = new Float32Array( 0 );\n    > var out = convertArraySame( x, y )\n    <Float32Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    See Also\n    --------\n    convertArray\n","convertPath":"\nconvertPath( from, to )\n    Converts between POSIX and Windows paths.\n\n    Parameters\n    ----------\n    from: string\n        Input path.\n\n    to: string\n        Output path convention: 'win32', 'mixed', or 'posix'.\n\n    Returns\n    -------\n    out: string\n        Converted path.\n\n    Examples\n    --------\n    > var out = convertPath( '/c/foo/bar/beep.c', 'win32' )\n    'c:\\\\foo\\\\bar\\\\beep.c'\n    > out = convertPath( '/c/foo/bar/beep.c', 'mixed' )\n    'c:/foo/bar/beep.c'\n    > out = convertPath( '/c/foo/bar/beep.c', 'posix' )\n    '/c/foo/bar/beep.c'\n    > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'win32' )\n    'C:\\\\\\\\foo\\\\bar\\\\beep.c'\n    > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'mixed' )\n    'C:/foo/bar/beep.c'\n    > out = convertPath( 'C:\\\\\\\\foo\\\\bar\\\\beep.c', 'posix' )\n    '/c/foo/bar/beep.c'\n\n","copy":"\ncopy( value[, level] )\n    Copy or deep clone a value to an arbitrary depth.\n\n    The implementation can handle circular references.\n\n    If a `Number`, `String`, or `Boolean` object is encountered, the value is\n    cloned as a primitive. This behavior is intentional.\n\n    For objects, the implementation only copies enumerable keys and their\n    associated property descriptors.\n\n    The implementation only checks whether basic `Objects`, `Arrays`, and class\n    instances are extensible, sealed, and/or frozen.\n\n    Functions are not cloned; their reference is copied.\n\n    The implementation supports custom error types which are `Error` instances\n    (e.g., ES2015 subclasses).\n\n    Support for copying class instances is inherently fragile. Any instances\n    with privileged access to variables (e.g., within closures) cannot be\n    cloned. This stated, basic copying of class instances is supported. Provided\n    an environment which supports ES5, the implementation is greedy and performs\n    a deep clone of any arbitrary class instance and its properties. The\n    implementation assumes that the concept of `level` applies only to the class\n    instance reference, but not to its internal state.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    level: integer (optional)\n         Copy depth. Default: Infinity.\n\n    Returns\n    -------\n    out: any\n        Value copy.\n\n    Examples\n    --------\n    > var value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\n    > var out = copy( value )\n    [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ]\n    > var bool = ( value[ 0 ].c === out[ 0 ].c )\n    false\n\n    // Set the `level` option to limit the copy depth:\n    > value = [ { 'a': 1, 'b': true, 'c': [ 1, 2, 3 ] } ];\n    > out = copy( value, 1 );\n    > bool = ( value[ 0 ] === out[ 0 ] )\n    true\n    > bool = ( value[ 0 ].c === out[ 0 ].c )\n    true\n\n\n    See Also\n    --------\n    merge\n","copyBuffer":"\ncopyBuffer( buffer )\n    Copies buffer data to a new Buffer instance.\n\n    Parameters\n    ----------\n    buffer: Buffer\n        Buffer to copy from.\n\n    Returns\n    -------\n    out: Buffer\n        Buffer instance.\n\n    Examples\n    --------\n    > var b1 = array2buffer( [ 1, 2, 3, 4 ] );\n    > var b2 = copyBuffer( b1 )\n    <Buffer>[ 1, 2, 3, 4 ]\n\n    See Also\n    --------\n    allocUnsafe, Buffer\n","countBy":"\ncountBy( collection, [options,] indicator )\n    Groups values according to an indicator function and returns group counts.\n\n    When invoked, the indicator function is provided two arguments:\n\n    - value: collection value.\n    - index: collection index.\n\n    The value returned by an indicator function should be a value which can be\n    serialized as an object key.\n\n    If provided an empty collection, the function returns an empty object.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection to group. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Options.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    indicator: Function\n        Indicator function specifying which group an element in the input\n        collection belongs to.\n\n    Returns\n    -------\n    out: Object\n        Group results.\n\n    Examples\n    --------\n    > function indicator( v ) {\n    ...     if ( v[ 0 ] === 'b' ) {\n    ...         return 'b';\n    ...     }\n    ...     return 'other';\n    ... };\n    > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n    > var out = countBy( collection, indicator )\n    { 'b': 3, 'other': 1 }\n\n    See Also\n    --------\n    group, groupBy\n","countByAsync":"\ncountByAsync( collection, [options,] indicator, done )\n    Groups values according to an indicator function and returns group counts.\n\n    When invoked, the indicator function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If the\n    indicator function accepts two arguments, the indicator function is\n    provided:\n\n    - value\n    - next\n\n    If the indicator function accepts three arguments, the indicator function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other indicator function signature, the indicator function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - group: value group.\n\n    If an indicator function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    If provided an empty collection, the function calls the `done` callback with\n    an empty object as the second argument.\n\n    The `group` returned by an indicator function should be a value which can be\n    serialized as an object key.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    indicator: Function\n        Indicator function specifying which group an element in the input\n        collection belongs to.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > countByAsync( arr, indicator, done )\n    1000\n    2500\n    3000\n    { \"even\": 2, \"odd\": 1 }\n\n    // Limit number of concurrent invocations:\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 3000, 2500, 1000 ];\n    > countByAsync( arr, opts, indicator, done )\n    2500\n    3000\n    1000\n    { \"even\": 2, \"odd\": 1 }\n\n    // Process sequentially:\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 3000, 2500, 1000 ];\n    > countByAsync( arr, opts, indicator, done )\n    3000\n    2500\n    1000\n    { \"even\": 2, \"odd\": 1 }\n\n\ncountByAsync.factory( [options,] indicator )\n    Returns a function which groups values according to an indicator function\n    and returns group counts.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    indicator: Function\n        Indicator function specifying which group an element in the input\n        collection belongs to.\n\n    Returns\n    -------\n    out: Function\n        A function which groups values and returns group counts.\n\n    Examples\n    --------\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = countByAsync.factory( opts, indicator );\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    { \"even\": 2, \"odd\": 1 }\n    > arr = [ 2000, 1500, 1000, 500 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    500\n    { \"even\": 2, \"odd\": 2 }\n\n    See Also\n    --------\n    countBy, groupByAsync, tabulateByAsync\n","countByAsync.factory":"\ncountByAsync.factory( [options,] indicator )\n    Returns a function which groups values according to an indicator function\n    and returns group counts.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    indicator: Function\n        Indicator function specifying which group an element in the input\n        collection belongs to.\n\n    Returns\n    -------\n    out: Function\n        A function which groups values and returns group counts.\n\n    Examples\n    --------\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = countByAsync.factory( opts, indicator );\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    { \"even\": 2, \"odd\": 1 }\n    > arr = [ 2000, 1500, 1000, 500 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    500\n    { \"even\": 2, \"odd\": 2 }\n\n    See Also\n    --------\n    countBy, groupByAsync, tabulateByAsync","currentYear":"\ncurrentYear()\n    Returns the current year.\n\n    Returns\n    -------\n    out: integer\n        Current year.\n\n    Examples\n    --------\n    > var y = currentYear()\n    <number>\n\n    See Also\n    --------\n    isCurrentYear\n","curry":"\ncurry( fcn[, arity][, thisArg] )\n    Transforms a function into a sequence of functions each accepting a single\n    argument.\n\n    Until return value resolution, each invocation returns a new partially\n    applied curry function.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to curry.\n\n    arity: integer (optional)\n        Number of parameters. Default: `fcn.length`.\n\n    thisArg: any (optional)\n        Evaluation context.\n\n    Returns\n    -------\n    out: Function\n        Curry function.\n\n    Examples\n    --------\n    > function add( x, y ) { return x + y; };\n    > var f = curry( add );\n    > var sum = f( 2 )( 3 )\n    5\n\n    // Supply arity:\n    > function add() { return arguments[ 0 ] + arguments[ 1 ]; };\n    > f = curry( add, 2 );\n    > sum = f( 2 )( 3 )\n    5\n\n    // Provide function context:\n    > var obj = {\n    ...     'name': 'Ada',\n    ...     'greet': function greet( word1, word2 ) {\n    ...        return word1 + ' ' + word2 + ', ' + this.name + '!'\n    ...     }\n    ... };\n    > f = curry( obj.greet, obj );\n    > var str = f( 'Hello' )( 'there' )\n    'Hello there, Ada!'\n\n    See Also\n    --------\n    curryRight, uncurry, uncurryRight\n","curryRight":"\ncurryRight( fcn[, arity][, thisArg] )\n    Transforms a function into a sequence of functions each accepting a single\n    argument.\n\n    Until return value resolution, each invocation returns a new partially\n    applied curry function.\n\n    This function applies arguments starting from the right.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to curry.\n\n    arity: integer (optional)\n        Number of parameters. Default: `fcn.length`.\n\n    thisArg: any (optional)\n        Evaluation context.\n\n    Returns\n    -------\n    out: Function\n        Curry function.\n\n    Examples\n    --------\n    > function add( x, y ) { return x + y; };\n    > var f = curryRight( add );\n    > var sum = f( 2 )( 3 )\n    5\n\n    // Supply arity:\n    > function add() { return arguments[ 0 ] + arguments[ 1 ]; };\n    > f = curryRight( add, 2 );\n    > sum = f( 2 )( 3 )\n    5\n\n    // Provide function context:\n    > var obj = {\n    ...     'name': 'Ada',\n    ...     'greet': function greet( word1, word2 ) {\n    ...         return word1 + ' ' + word2 + ', ' + this.name + '!'\n    ...     }\n    ... };\n    > f = curryRight( obj.greet, obj );\n    > var str = f( 'there' )( 'Hello' )\n    'Hello there, Ada!'\n\n    See Also\n    --------\n    curry, uncurry, uncurryRight\n","cwd":"\ncwd()\n    Returns the current working directory.\n\n    Returns\n    -------\n    path: string\n        Current working directory of the process.\n\n    Examples\n    --------\n    > var dir = cwd()\n    '/path/to/current/working/directory'\n\n    See Also\n    --------\n    chdir\n","DALE_CHALL_NEW":"\nDALE_CHALL_NEW()\n    Returns a list of familiar English words.\n\n    Returns\n    -------\n    out: Array<string>\n        List of familiar English words.\n\n    Examples\n    --------\n    > var list = DALE_CHALL_NEW()\n    [ 'a', 'able', 'aboard', 'about', 'above', ... ]\n\n    References\n    ----------\n    - Chall, Jeanne Sternlicht, and Edgar Dale. 1995. *Readability revisited:\n    the new Dale-Chall readability formula*. Brookline Books.\n    <https://books.google.com/books?id=2nbuAAAAMAAJ>.\n\n","datasets":"\ndatasets( name[, options] )\n    Returns a dataset.\n\n    The function forwards provided options to the dataset interface specified\n    by `name`.\n\n    Parameters\n    ----------\n    name: string\n        Dataset name.\n\n    options: Object (optional)\n        Function options.\n\n    Returns\n    -------\n    out: any\n        Dataset.\n\n    Examples\n    --------\n    > var out = datasets( 'MONTH_NAMES_EN' )\n    [ 'January', 'February', ... ]\n    > var opts = { 'data': 'cities' };\n    > out = datasets( 'MINARD_NAPOLEONS_MARCH', opts )\n    [ {...}, {...}, ... ]\n\n","DataView":"\nDataView( buffer[, byteOffset[, byteLength]] )\n    Returns a data view representing a provided array buffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer|SharedArrayBuffer\n        Array buffer.\n\n    byteOffset: integer (optional)\n        Offset (in bytes) to the first byte in the array buffer for the new view\n        to reference. Default: 0.\n\n    byteLength: integer (optional)\n        Number of elements in the byte array. If not provided, the view's length\n        will equal the buffer's length.\n\n    Returns\n    -------\n    out: DataView\n        A data view.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 5 )\n    <ArrayBuffer>\n    > var dv = new DataView( buf )\n    <DataView>\n\n\nDataView.prototype.buffer\n    Read-only property which returns the underyling array buffer.\n\n    Examples\n    --------\n    > var buf1 = new ArrayBuffer( 5 );\n    > var dv = new DataView( buf1 );\n    > var buf2 = dv.buffer\n    <ArrayBuffer>\n    > var b = ( buf1 === buf2 )\n    true\n\n\nDataView.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the view.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 5 );\n    > var dv = new DataView( buf );\n    > dv.byteLength\n    5\n\n\nDataView.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the view to the\n    start of the underlying array buffer.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 5 );\n    > var dv = new DataView( buf, 2 );\n    > dv.byteLength\n    3\n    > dv.byteOffset\n    2\n\n\nTODO: document properties/methods\n\n\n    See Also\n    --------\n    ArrayBuffer, typedarray\n","DataView.prototype.buffer":"\nDataView.prototype.buffer\n    Read-only property which returns the underyling array buffer.\n\n    Examples\n    --------\n    > var buf1 = new ArrayBuffer( 5 );\n    > var dv = new DataView( buf1 );\n    > var buf2 = dv.buffer\n    <ArrayBuffer>\n    > var b = ( buf1 === buf2 )\n    true","DataView.prototype.byteLength":"\nDataView.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the view.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 5 );\n    > var dv = new DataView( buf );\n    > dv.byteLength\n    5","DataView.prototype.byteOffset":"\nDataView.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the view to the\n    start of the underlying array buffer.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 5 );\n    > var dv = new DataView( buf, 2 );\n    > dv.byteLength\n    3\n    > dv.byteOffset\n    2","datespace":"\ndatespace( start, stop[, length][ , options] )\n    Generates an array of linearly spaced dates.\n\n    Parameters\n    ----------\n    start: number\n        Start time as either a `Date` object, Unix timestamp, JavaScript\n        timestamp, or date string.\n\n    stop: number\n        Stop time as either a `Date` object, Unix timestamp, JavaScript\n        timestamp, or date string.\n\n    length: integer (optional)\n        Length of output array. Default: `100`.\n\n    options: Object (optional)\n        Options.\n\n    options.round: string (optional)\n        Specifies how sub-millisecond times should be rounded:\n        [ 'floor', 'ceil', 'round' ]. Default: 'floor'.\n\n    Returns\n    -------\n    arr: Array\n        Array of dates.\n\n    Examples\n    --------\n    > var stop = '2014-12-02T07:00:54.973Z';\n    > var start = new Date( stop ) - 60000;\n    > var arr = datespace( start, stop, 6 )\n    [...]\n\n    // Equivalent of Math.ceil():\n    > var opts = { 'round': 'ceil' };\n    > arr = datespace( 1417503655000, 1417503655001, 3, opts )\n    [...]\n\n    See Also\n    --------\n    linspace, logspace\n","dayOfQuarter":"\ndayOfQuarter( [month[, day, year]] )\n    Returns the day of the quarter.\n\n    By default, the function returns the day of the quarter for the current date\n    (according to local time). To determine the day of the quarter for a\n    particular day, provide `month`, `day`, and `year` arguments.\n\n    A `month` may be either a month's integer value, three letter abbreviation,\n    or full name (case insensitive).\n\n    The function also accepts a `Date` object.\n\n    Parameters\n    ----------\n    month: string|integer|Date (optional)\n        Month (or `Date`).\n\n    day: integer (optional)\n        Day.\n\n    year: integer (optional)\n        Year.\n\n    Returns\n    -------\n    out: integer\n        Day of the quarter.\n\n    Examples\n    --------\n    > var day = dayOfQuarter()\n    <number>\n    > day = dayOfQuarter( new Date() )\n    <number>\n    > day = dayOfQuarter( 12, 31, 2017 )\n    92\n\n    // Other ways to supply month:\n    > day = dayOfQuarter( 'dec', 31, 2017 )\n    92\n    > day = dayOfQuarter( 'december', 31, 2017 )\n    92\n\n    See Also\n    --------\n    dayOfYear\n","dayOfYear":"\ndayOfYear( [month[, day, year]] )\n    Returns the day of the year.\n\n    By default, the function returns the day of the year for the current date\n    (according to local time). To determine the day of the year for a particular\n    day, provide `month`, `day`, and `year` arguments.\n\n    A `month` may be either a month's integer value, three letter abbreviation,\n    or full name (case insensitive).\n\n    The function also accepts a `Date` object.\n\n    Parameters\n    ----------\n    month: string|integer|Date (optional)\n        Month (or `Date`).\n\n    day: integer (optional)\n        Day.\n\n    year: integer (optional)\n        Year.\n\n    Returns\n    -------\n    out: integer\n        Day of the year.\n\n    Examples\n    --------\n    > var day = dayOfYear()\n    <number>\n    > day = dayOfYear( new Date() )\n    <number>\n    > day = dayOfYear( 12, 31, 2016 )\n    366\n\n    // Other ways to supply month:\n    > day = dayOfYear( 'dec', 31, 2016 )\n    366\n    > day = dayOfYear( 'december', 31, 2016 )\n    366\n\n    See Also\n    --------\n    dayOfQuarter\n","daysInMonth":"\ndaysInMonth( [month[, year]] )\n    Returns the number of days in a month.\n\n    By default, the function returns the number of days in the current month\n    of the current year (according to local time). To determine the number of\n    days for a particular month and year, provide `month` and `year` arguments.\n\n    A `month` may be either a month's integer value, three letter abbreviation,\n    or full name (case insensitive).\n\n    The function's return value is a generalization and does **not** take into\n    account inaccuracies due to daylight savings conventions, crossing\n    timezones, or other complications with time and dates.\n\n    Parameters\n    ----------\n    month: string|integer|Date (optional)\n        Month (or `Date`).\n\n    year: integer (optional)\n        Year.\n\n    Returns\n    -------\n    out: integer\n        Days in a month.\n\n    Examples\n    --------\n    > var num = daysInMonth()\n    <number>\n    > num = daysInMonth( 2 )\n    <number>\n    > num = daysInMonth( 2, 2016 )\n    29\n    > num = daysInMonth( 2, 2017 )\n    28\n\n    // Other ways to supply month:\n    > num = daysInMonth( 'feb', 2016 )\n    29\n    > num = daysInMonth( 'february', 2016 )\n    29\n\n    See Also\n    --------\n    daysInYear\n","daysInYear":"\ndaysInYear( [value] )\n    Returns the number of days in a year according to the Gregorian calendar.\n\n    By default, the function returns the number of days in the current year\n    (according to local time). To determine the number of days for a particular\n    year, provide either a year or a `Date` object.\n\n    The function's return value is a generalization and does **not** take into\n    account inaccuracies due to daylight savings conventions, crossing\n    timezones, or other complications with time and dates.\n\n    Parameters\n    ----------\n    value: integer|Date (optional)\n        Year or `Date` object.\n\n    Returns\n    -------\n    out: integer\n        Number of days in a year.\n\n    Examples\n    --------\n    > var num = daysInYear()\n    <number>\n    > num = daysInYear( 2016 )\n    366\n    > num = daysInYear( 2017 )\n    365\n\n    See Also\n    --------\n    daysInMonth\n","ddot":"\nddot( x, y[, dim] )\n    Computes the dot product of two double-precision floating-point vectors.\n\n    If provided at least one input array having more than one dimension, the\n    input arrays are broadcasted to a common shape.\n\n    For multi-dimensional input arrays, the function performs batched\n    computation, such that the function computes the dot product for each pair\n    of vectors in `x` and `y` according to the specified dimension index.\n\n    The size of the contracted dimension must be the same for both input arrays.\n\n    The function resolves the dimension index for which to compute the dot\n    product *before* broadcasting.\n\n    If provided empty vectors, the dot product is `0`.\n\n    Parameters\n    ----------\n    x: ndarray\n        First input array. Must have a 'float64' data type. Must have at least\n        one dimension and be broadcast-compatible with the second input array.\n\n    y: ndarray\n        Second input array. Must have a 'float64' data type. Must have at least\n        one dimension and be broadcast-compatible with the first input array.\n\n    dim: integer (optional)\n        Dimension index for which to compute the dot product. Must be a negative\n        integer. Negative indices are resolved relative to the last array\n        dimension, with the last dimension corresponding to `-1`. Default: -1.\n\n    Returns\n    -------\n    out: ndarray\n        The dot product. The output array has the same data type as the input\n        arrays and has a shape which is determined by broadcasting and excludes\n        the contracted dimension.\n\n    Examples\n    --------\n    > var xbuf = new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var x = array( xbuf );\n    > var ybuf = new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var y = array( ybuf );\n    > var z = ddot( x, y )\n    <ndarray>\n    > z.get()\n    -5.0\n\n    See Also\n    --------\n    base.strided.ddot, gdot, sdot\n","debugSinkStream":"\ndebugSinkStream( [options,] [clbk] )\n    Returns a writable stream for debugging stream pipelines.\n\n    If the `DEBUG` environment variable is not set, no data is logged.\n\n    Providing a `name` option is *strongly* encouraged, as the `DEBUG`\n    environment variable can be used to filter debuggers.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Debug namespace.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to encode strings as `Buffer` objects before writing\n        data to a returned stream. Default: true.\n\n    options.defaultEncoding: string (optional)\n        Default encoding when not explicitly specified when writing data.\n        Default: 'utf8'.\n\n    clbk: Function (optional)\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: WritableStream\n        Writable stream.\n\n    Examples\n    --------\n    > var s = debugSinkStream( { 'name': 'foo' } );\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();\n\n\ndebugSinkStream.factory( [options] )\n    Returns a function for creating writable streams for debugging stream\n    pipelines.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to encode strings as `Buffer` objects before writing\n        data to a returned stream. Default: true.\n\n    options.defaultEncoding: string (optional)\n        Default encoding when not explicitly specified when writing data.\n        Default: 'utf8'.\n\n    Returns\n    -------\n    createStream( name[, clbk] ): Function\n        Function for creating writable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = debugSinkStream.factory( opts );\n\n\ndebugSinkStream.objectMode( [options,] [clbk] )\n    Returns an \"objectMode\" writable stream for debugging stream pipelines.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Debug namespace.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to encode strings as `Buffer` objects before writing\n        data to a returned stream. Default: true.\n\n    options.defaultEncoding: string (optional)\n        Default encoding when not explicitly specified when writing data.\n        Default: 'utf8'.\n\n    clbk: Function (optional)\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: WritableStream\n        Writable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > var s = debugSinkStream.objectMode( { 'name': 'foo' } );\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();\n\n    See Also\n    --------\n    debugStream, inspectSinkStream\n","debugSinkStream.factory":"\ndebugSinkStream.factory( [options] )\n    Returns a function for creating writable streams for debugging stream\n    pipelines.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to encode strings as `Buffer` objects before writing\n        data to a returned stream. Default: true.\n\n    options.defaultEncoding: string (optional)\n        Default encoding when not explicitly specified when writing data.\n        Default: 'utf8'.\n\n    Returns\n    -------\n    createStream( name[, clbk] ): Function\n        Function for creating writable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = debugSinkStream.factory( opts );","debugSinkStream.objectMode":"\ndebugSinkStream.objectMode( [options,] [clbk] )\n    Returns an \"objectMode\" writable stream for debugging stream pipelines.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Debug namespace.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to encode strings as `Buffer` objects before writing\n        data to a returned stream. Default: true.\n\n    options.defaultEncoding: string (optional)\n        Default encoding when not explicitly specified when writing data.\n        Default: 'utf8'.\n\n    clbk: Function (optional)\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: WritableStream\n        Writable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > var s = debugSinkStream.objectMode( { 'name': 'foo' } );\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();\n\n    See Also\n    --------\n    debugStream, inspectSinkStream","debugStream":"\ndebugStream( [options,] [clbk] )\n    Returns a transform stream for debugging stream pipelines.\n\n    If the `DEBUG` environment variable is not set, no data is logged.\n\n    Providing a `name` option is *strongly* encouraged, as the `DEBUG`\n    environment variable can be used to filter debuggers.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Debug namespace.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    clbk: Function (optional)\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream.\n\n    Examples\n    --------\n    > var s = debugStream( { 'name': 'foo' } );\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();\n\n\ndebugStream.factory( [options] )\n    Returns a function for creating transform streams for debugging stream\n    pipelines.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    createStream( name[, clbk] ): Function\n        Function for creating transform streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = debugStream.factory( opts );\n\n\ndebugStream.objectMode( [options,] [clbk] )\n    Returns an \"objectMode\" transform stream for debugging stream pipelines.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Debug namespace.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    clbk: Function (optional)\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > var s = debugStream.objectMode( { 'name': 'foo' } );\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();\n\n    See Also\n    --------\n    debugSinkStream, inspectStream\n","debugStream.factory":"\ndebugStream.factory( [options] )\n    Returns a function for creating transform streams for debugging stream\n    pipelines.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    createStream( name[, clbk] ): Function\n        Function for creating transform streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = debugStream.factory( opts );","debugStream.objectMode":"\ndebugStream.objectMode( [options,] [clbk] )\n    Returns an \"objectMode\" transform stream for debugging stream pipelines.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Debug namespace.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    clbk: Function (optional)\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > var s = debugStream.objectMode( { 'name': 'foo' } );\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();\n\n    See Also\n    --------\n    debugSinkStream, inspectStream","decorateAfter":"\ndecorateAfter( fcn, arity, after[, thisArg] )\n    Decorates a provided function such that the function's return value is\n    provided as an argument to another function.\n\n    Decorators are intended to be transparent, meaning that, when interfacing\n    with an API, the decorated API should have the same signature (i.e., number\n    of parameters) as the decorated function.\n\n    Thus, a typical value for `arity` is `fcn.length`. This function does not\n    require equality, however, and the `arity` argument is allowed to diverge\n    from that of the decorated function. Specifying a differing `arity` does\n    *not* affect function evaluation behavior, as the returned function passes\n    all provided arguments to the decorated function.\n\n    If the `after` function returns `undefined`, the returned decorator returns\n    the return value of the decorated function `fcn`; otherwise, the returned\n    decorator returns the return value of `after`.\n\n    The returned decorator supports an `arity` less than or equal to `10` (i.e.,\n    the maximum arity of the returned function is `10`). For an arity greater\n    than `10`, the returned function has an arity equal to `0`. While this\n    violates strict notions of a decorator, for all practical purposes, this is\n    unlikely to be an issue, as the vast majority of functions have fewer than\n    `10` parameters and the need for explicitly checking function length is\n    relatively uncommon.\n\n    Common use cases for decorating a function with additional actions *after*\n    invocation include logging, capturing invocation statistics, and validating\n    return values.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to decorate.\n\n    arity: integer\n        Number of parameters.\n\n    after: Function\n        Function with which to invoke the return value of the decorated\n        function.\n\n    thisArg: any (optional)\n        Evaluation context for `after`.\n\n    Returns\n    -------\n    out: Function\n        Decorator function.\n\n    Examples\n    --------\n    > function f( v ) { return -v; };\n    > var fcn = decorateAfter( base.abs, 1, f );\n    > var v = fcn( -5 )\n    -5\n    > v = fcn( 5 )\n    -5\n\n\ndecorateAfter.factory( fcn, arity, after[, thisArg] )\n    Uses code generation to decorate a provided function such that the\n    function's return value is provided as an argument to another function.\n\n    Code generation may be problematic in browser contexts enforcing a strict\n    content security policy] (CSP). If running in or targeting an environment\n    with a CSP, avoid using code generation.\n\n    For non-native functions, the function supports returning a decorator whose\n    API exactly matches the API of the decorated function, including function\n    length and parameter names.\n\n    For native functions, due to how native functions serialize to strings, the\n    function generates placeholder parameter names, which are unlikely to match\n    the canonical parameter names. Using placeholder parameter names ensures\n    that the length of the decorator (i.e., number of parameters) matches the\n    decorated function and, except in scenarios involving function source code\n    inspection, will not affect runtime behavior.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to decorate.\n\n    arity: integer\n        Number of parameters.\n\n    after: Function\n        Function with which to invoke the return value of the decorated\n        function.\n\n    thisArg: any (optional)\n        Evaluation context for `after`.\n\n    Returns\n    -------\n    out: Function\n        Decorator function.\n\n    Examples\n    --------\n    > function f( v ) { return -v; };\n    > var fcn = decorateAfter.factory( base.abs, 1, f );\n    > var v = fcn( -5 )\n    -5\n    > v = fcn( 5 )\n    -5\n\n","decorateAfter.factory":"\ndecorateAfter.factory( fcn, arity, after[, thisArg] )\n    Uses code generation to decorate a provided function such that the\n    function's return value is provided as an argument to another function.\n\n    Code generation may be problematic in browser contexts enforcing a strict\n    content security policy] (CSP). If running in or targeting an environment\n    with a CSP, avoid using code generation.\n\n    For non-native functions, the function supports returning a decorator whose\n    API exactly matches the API of the decorated function, including function\n    length and parameter names.\n\n    For native functions, due to how native functions serialize to strings, the\n    function generates placeholder parameter names, which are unlikely to match\n    the canonical parameter names. Using placeholder parameter names ensures\n    that the length of the decorator (i.e., number of parameters) matches the\n    decorated function and, except in scenarios involving function source code\n    inspection, will not affect runtime behavior.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to decorate.\n\n    arity: integer\n        Number of parameters.\n\n    after: Function\n        Function with which to invoke the return value of the decorated\n        function.\n\n    thisArg: any (optional)\n        Evaluation context for `after`.\n\n    Returns\n    -------\n    out: Function\n        Decorator function.\n\n    Examples\n    --------\n    > function f( v ) { return -v; };\n    > var fcn = decorateAfter.factory( base.abs, 1, f );\n    > var v = fcn( -5 )\n    -5\n    > v = fcn( 5 )\n    -5","deepEqual":"\ndeepEqual( a, b )\n    Tests for deep equality between two values.\n\n    Parameters\n    ----------\n    a: any\n        First comparison value.\n\n    b: any\n        Second comparison value.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating if `a` is deep equal to `b`.\n\n    Examples\n    --------\n    > var bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, 3 ] )\n    true\n\n    > bool = deepEqual( [ 1, 2, 3 ], [ 1, 2, '3' ] )\n    false\n\n    > bool = deepEqual( { 'a': 2 }, { 'a': [ 2 ] } )\n    false\n\n    See Also\n    --------\n    isStrictEqual, isSameValue\n","deepGet":"\ndeepGet( obj, path[, options] )\n    Returns a nested property value.\n\n    Parameters\n    ----------\n    obj: ObjectLike\n        Input object.\n\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    out: any\n        Nested property value.\n\n    Examples\n    --------\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var val = deepGet( obj, 'a.b.c' )\n    'd'\n\n    // Specify a custom separator via the `sep` option:\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var val = deepGet( obj, 'a/b/c', { 'sep': '/' } )\n    'd'\n\ndeepGet.factory( path[, options] )\n    Creates a reusable deep get function.\n\n    Parameters\n    ----------\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    out: Function\n        Deep get factory.\n\n    Examples\n    --------\n    > var dget = deepGet.factory( 'a/b/c', { 'sep': '/' } );\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var val = dget( obj )\n    'd'\n\n    See Also\n    --------\n    deepPluck, deepSet\n","deepGet.factory":"\ndeepGet.factory( path[, options] )\n    Creates a reusable deep get function.\n\n    Parameters\n    ----------\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    out: Function\n        Deep get factory.\n\n    Examples\n    --------\n    > var dget = deepGet.factory( 'a/b/c', { 'sep': '/' } );\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var val = dget( obj )\n    'd'\n\n    See Also\n    --------\n    deepPluck, deepSet","deepHasOwnProp":"\ndeepHasOwnProp( value, path[, options] )\n    Returns a boolean indicating whether an object contains a nested key path.\n\n    The function tests for \"own\" properties and will return `false` for\n    inherited properties.\n\n    Value arguments other than `null` or `undefined` are coerced to objects.\n\n    Key path array elements are coerced to strings.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object has a specified path.\n\n    Examples\n    --------\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var bool = deepHasOwnProp( obj, 'a.b.c' )\n    true\n\n    // Specify a custom separator via the `sep` option:\n    > obj = { 'a': { 'b': { 'c': 'd' } } };\n    > bool = deepHasOwnProp( obj, 'a/b/c', { 'sep': '/' } )\n    true\n\ndeepHasOwnProp.factory( path[, options] )\n    Returns a function which tests whether an object contains a nested key path.\n\n    The returned function tests for \"own\" properties and will return `false` for\n    inherited properties.\n\n    Parameters\n    ----------\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    out: Function\n        Function which tests whether an object contains a nested key path.\n\n    Examples\n    --------\n    > var has = deepHasOwnProp.factory( 'a/b/c', { 'sep': '/' } );\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var bool = has( obj )\n    true\n\n    See Also\n    --------\n    deepHasProp, hasOwnProp, deepGet, deepPluck, deepSet\n","deepHasOwnProp.factory":"\ndeepHasOwnProp.factory( path[, options] )\n    Returns a function which tests whether an object contains a nested key path.\n\n    The returned function tests for \"own\" properties and will return `false` for\n    inherited properties.\n\n    Parameters\n    ----------\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    out: Function\n        Function which tests whether an object contains a nested key path.\n\n    Examples\n    --------\n    > var has = deepHasOwnProp.factory( 'a/b/c', { 'sep': '/' } );\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var bool = has( obj )\n    true\n\n    See Also\n    --------\n    deepHasProp, hasOwnProp, deepGet, deepPluck, deepSet","deepHasProp":"\ndeepHasProp( value, path[, options] )\n    Returns a boolean indicating whether an object contains a nested key path,\n    either own or inherited.\n\n    Value arguments other than `null` or `undefined` are coerced to objects.\n\n    Key path array elements are coerced to strings.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object has a specified path.\n\n    Examples\n    --------\n    > function Foo() { return this; };\n    > Foo.prototype.b = { 'c': 'd' };\n    > var obj = { 'a': new Foo() };\n    > var bool = deepHasProp( obj, 'a.b.c' )\n    true\n\n    // Specify a custom separator via the `sep` option:\n    > bool = deepHasProp( obj, 'a/b/c', { 'sep': '/' } )\n    true\n\ndeepHasProp.factory( path[, options] )\n    Returns a function which tests whether an object contains a nested key path,\n    either own or inherited.\n\n    Parameters\n    ----------\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    out: Function\n        Function which tests whether an object contains a nested key path.\n\n    Examples\n    --------\n    > function Foo() { return this; };\n    > Foo.prototype.b = { 'c': 'd' };\n    > var has = deepHasProp.factory( 'a/b/c', { 'sep': '/' } );\n    > var obj = { 'a': new Foo() };\n    > var bool = has( obj )\n    true\n\n    See Also\n    --------\n    deepHasOwnProp, hasOwnProp, deepGet, deepPluck, deepSet\n","deepHasProp.factory":"\ndeepHasProp.factory( path[, options] )\n    Returns a function which tests whether an object contains a nested key path,\n    either own or inherited.\n\n    Parameters\n    ----------\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    out: Function\n        Function which tests whether an object contains a nested key path.\n\n    Examples\n    --------\n    > function Foo() { return this; };\n    > Foo.prototype.b = { 'c': 'd' };\n    > var has = deepHasProp.factory( 'a/b/c', { 'sep': '/' } );\n    > var obj = { 'a': new Foo() };\n    > var bool = has( obj )\n    true\n\n    See Also\n    --------\n    deepHasOwnProp, hasOwnProp, deepGet, deepPluck, deepSet","deepPluck":"\ndeepPluck( arr, path[, options] )\n    Extracts a nested property value from each element of an object array.\n\n    If a key path does not exist, the function sets the plucked value as\n    `undefined`.\n\n    Extracted values are not cloned.\n\n    Parameters\n    ----------\n    arr: Array\n        Source array.\n\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to return a new data structure. Default:\n        true.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    out: Array\n        Destination array.\n\n    Examples\n    --------\n    > var arr = [\n    ...     { 'a': { 'b': { 'c': 1 } } },\n    ...     { 'a': { 'b': { 'c': 2 } } }\n    ... ];\n    > var out = deepPluck( arr, 'a.b.c' )\n    [ 1, 2 ]\n    > arr = [\n    ...     { 'a': [ 0, 1, 2 ] },\n    ...     { 'a': [ 3, 4, 5 ] }\n    ... ];\n    > out = deepPluck( arr, [ 'a', 1 ] )\n    [ 1, 4 ]\n\n    See Also\n    --------\n    deepGet, deepSet\n","deepSet":"\ndeepSet( obj, path, value[, options] )\n    Sets a nested property value.\n\n    Parameters\n    ----------\n    obj: ObjectLike\n        Input object.\n\n    path: string|Array\n        Key path.\n\n    value: any\n        Value to set.\n\n    options: Object (optional)\n        Options.\n\n    options.create: boolean (optional)\n        Boolean indicating whether to create a path if the key path does not\n        already exist. Default: false.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if the property was successfully set.\n\n    Examples\n    --------\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var bool = deepSet( obj, 'a.b.c', 'beep' )\n    true\n\n    // Specify an alternative separator via the sep option:\n    > obj = { 'a': { 'b': { 'c': 'd' } } };\n    > bool = deepSet( obj, 'a/b/c', 'beep', { 'sep': '/' } );\n    > obj\n    { 'a': { 'b': { 'c': 'beep' } } }\n\n    // To create a key path which does not exist, set the create option to true:\n    > bool = deepSet( obj, 'a.e.c', 'boop', { 'create': true } );\n    > obj\n    { 'a': { 'b': { 'c': 'beep' }, 'e': { 'c': 'boop' } } }\n\n\ndeepSet.factory( path[, options] )\n    Creates a reusable deep set function.\n\n    Parameters\n    ----------\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.create: boolean (optional)\n        Boolean indicating whether to create a path if the key path does not\n        already exist. Default: false.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    out: Function\n        Deep get function.\n\n    Examples\n    --------\n    > var dset = deepSet.factory( 'a/b/c', {\n    ...     'create': true,\n    ...     'sep': '/'\n    ... });\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var bool = dset( obj, 'beep' )\n    true\n    > obj\n    { 'a': { 'b': { 'c': 'beep' } } }\n\n    See Also\n    --------\n    deepGet, deepPluck\n","deepSet.factory":"\ndeepSet.factory( path[, options] )\n    Creates a reusable deep set function.\n\n    Parameters\n    ----------\n    path: string|Array\n        Key path.\n\n    options: Object (optional)\n        Options.\n\n    options.create: boolean (optional)\n        Boolean indicating whether to create a path if the key path does not\n        already exist. Default: false.\n\n    options.sep: string (optional)\n        Key path separator. Default: '.'.\n\n    Returns\n    -------\n    out: Function\n        Deep get function.\n\n    Examples\n    --------\n    > var dset = deepSet.factory( 'a/b/c', {\n    ...     'create': true,\n    ...     'sep': '/'\n    ... });\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var bool = dset( obj, 'beep' )\n    true\n    > obj\n    { 'a': { 'b': { 'c': 'beep' } } }\n\n    See Also\n    --------\n    deepGet, deepPluck","defineMemoizedProperty":"\ndefineMemoizedProperty( obj, prop, descriptor )\n    Defines a memoized object property.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    descriptor: Object\n        Property descriptor.\n\n    descriptor.configurable: boolean (optional)\n        Boolean indicating if property descriptor can be changed and if the\n        property can be deleted from the provided object. Default: false.\n\n    descriptor.enumerable: boolean (optional)\n        Boolean indicating if the property shows up when enumerating object\n        properties. Default: false.\n\n    descriptor.writable: boolean (optional)\n        Boolean indicating if the value associated with the property can be\n        changed with an assignment operator. Default: false.\n\n    descriptor.value: Function\n        Synchronous function whose return value will be memoized and set as the\n        property value.\n\n    Examples\n    --------\n    > var obj = {};\n    > function foo() {\n    ...     return 'bar';\n    ... };\n    > defineMemoizedProperty( obj, 'foo', {\n    ...     'configurable': false,\n    ...     'enumerable': true,\n    ...     'writable': false,\n    ...     'value': foo\n    ... });\n    > obj.foo\n    'bar'\n\n    See Also\n    --------\n    setMemoizedReadOnly, defineProperty\n","defineProperties":"\ndefineProperties( obj, properties )\n    Defines (and/or modifies) object properties.\n\n    The second argument is an object whose own enumerable property values are\n    descriptors for the properties to be defined or modified.\n\n    Property descriptors come in two flavors: data descriptors and accessor\n    descriptors. A data descriptor is a property that has a value, which may or\n    may not be writable. An accessor descriptor is a property described by a\n    getter-setter function pair. A descriptor must be one of these two flavors\n    and cannot be both.\n\n    A property descriptor has the following optional properties:\n\n    - configurable: boolean indicating if property descriptor can be changed and\n    if the property can be deleted from the provided object. Default: false.\n\n    - enumerable: boolean indicating if the property shows up when enumerating\n    object properties. Default: false.\n\n    - writable: boolean indicating if the value associated with the property can\n    be changed with an assignment operator. Default: false.\n\n    - value: property value.\n\n    - get: function which serves as a getter for the property, or, if no getter,\n    undefined. When the property is accessed, a getter function is called\n    without arguments and with the `this` context set to the object through\n    which the property is accessed (which may not be the object on which the\n    property is defined due to inheritance). The return value will be used as\n    the property value. Default: undefined.\n\n    - set: function which serves as a setter for the property, or, if no setter,\n    undefined. When assigning a property value, a setter function is called with\n    one argument (the value being assigned to the property) and with the `this`\n    context set to the object through which the property is assigned. Default: undefined.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the properties.\n\n    properties: Object\n        Object with property descriptors.\n\n    Returns\n    -------\n    obj: Object\n        Object on which properties were defined (and/or modified).\n\n    Examples\n    --------\n    > var obj = {};\n    > defineProperties( obj, {\n    ...     'foo': {\n    ...         'value': 'bar',\n    ...         'writable': false,\n    ...         'configurable': false,\n    ...         'enumerable': true\n    ...     },\n    ...     'baz': {\n    ...         'value': 13\n    ...     }\n    ... });\n    > obj.foo\n    'bar'\n    > obj.baz\n    13\n\n    See Also\n    --------\n    defineProperty, setReadOnly\n","defineProperty":"\ndefineProperty( obj, prop, descriptor )\n    Defines (or modifies) an object property.\n\n    Property descriptors come in two flavors: data descriptors and accessor\n    descriptors. A data descriptor is a property that has a value, which may or\n    may not be writable. An accessor descriptor is a property described by a\n    getter-setter function pair. A descriptor must be one of these two flavors\n    and cannot be both.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    descriptor: Object\n        Property descriptor.\n\n    descriptor.configurable: boolean (optional)\n        Boolean indicating if property descriptor can be changed and if the\n        property can be deleted from the provided object. Default: false.\n\n    descriptor.enumerable: boolean (optional)\n        Boolean indicating if the property shows up when enumerating object\n        properties. Default: false.\n\n    descriptor.writable: boolean (optional)\n        Boolean indicating if the value associated with the property can be\n        changed with an assignment operator. Default: false.\n\n    descriptor.value: any (optional)\n        Property value.\n\n    descriptor.get: Function|void (optional)\n        Function which serves as a getter for the property, or, if no getter,\n        undefined. When the property is accessed, a getter function is called\n        without arguments and with the `this` context set to the object through\n        which the property is accessed (which may not be the object on which the\n        property is defined due to inheritance). The return value will be used\n        as the property value. Default: undefined.\n\n    descriptor.set: Function|void (optional)\n        Function which serves as a setter for the property, or, if no setter,\n        undefined. When assigning a property value, a setter function is called\n        with one argument (the value being assigned to the property) and with\n        the `this` context set to the object through which the property is\n        assigned. Default: undefined.\n\n    Returns\n    -------\n    obj: Object\n        Object on which the property was defined (or modified).\n\n    Examples\n    --------\n    > var obj = {};\n    > defineProperty( obj, 'foo', {\n    ...     'value': 'bar',\n    ...     'enumerable': true,\n    ...     'writable': false\n    ... });\n    > obj.foo = 'boop';\n    > obj\n    { 'foo': 'bar' }\n\n    See Also\n    --------\n    defineProperties, setReadOnly\n","dirname":"\ndirname( path )\n    Returns a directory name.\n\n    Parameters\n    ----------\n    path: string\n        Path.\n\n    Returns\n    -------\n    out: string\n        Directory name.\n\n    Examples\n    --------\n    > var dir = dirname( './foo/bar/index.js' )\n    './foo/bar'\n\n    See Also\n    --------\n    extname\n","dotcase":"\ndotcase( str )\n    Converts a string to dot case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Dot-cased string.\n\n    Examples\n    --------\n    > var out = dotcase( 'Hello World!' )\n    'hello.world'\n    > out = dotcase( 'beep boop' )\n    'beep.boop'\n\n    See Also\n    --------\n    camelcase, kebabcase, pascalcase, snakecase","DoublyLinkedList":"\nDoublyLinkedList()\n    Doubly linked list constructor.\n\n    Returns\n    -------\n    list: Object\n        Doubly linked list.\n\n    list.clear: Function\n        Clears the list.\n\n    list.first: Function\n        Returns the first list node. If the list is empty, the returned value is\n        `undefined`.\n\n    list.insert: Function\n        Inserts a value after a provided list node. For its third argument, the\n        method accepts a location: 'before' or 'after'. Default: 'after'.\n\n    list.iterator: Function\n        Returns an iterator for iterating over a list. If an environment\n        supports Symbol.iterator, the returned iterator is iterable. Note that,\n        in order to prevent confusion arising from list mutation during\n        iteration, a returned iterator **always** iterates over a list\n        \"snapshot\", which is defined as the list of list elements at the time\n        of the method's invocation. For its sole argument, the method accepts a\n        direction: 'forward' or 'reverse'. Default: 'forward'.\n\n    list.last: Function\n        Returns the last list node. If the list is empty, the returned value is\n        `undefined`.\n\n    list.length: integer\n        List length.\n\n    list.pop: Function\n        Removes and returns the last list value. If the list is empty, the\n        returned value is `undefined`.\n\n    list.push: Function\n        Adds a value to the end of the list.\n\n    list.remove: Function\n        Removes a list node from the list.\n\n    list.shift: Function\n        Removes and returns the first list value. If the list is empty, the\n        returned value is `undefined`.\n\n    list.toArray: Function\n        Returns an array of list values.\n\n    list.toJSON: Function\n        Serializes a list as JSON.\n\n    list.unshift: Function\n        Adds a value to the beginning of the list.\n\n    Examples\n    --------\n    > var list = DoublyLinkedList();\n    > list.push( 'foo' ).push( 'bar' );\n    > list.length\n    2\n    > list.pop()\n    'bar'\n    > list.length\n    1\n    > list.pop()\n    'foo'\n    > list.length\n    0\n\n    See Also\n    --------\n    LinkedList, Stack\n","doUntil":"\ndoUntil( fcn, predicate[, thisArg] )\n    Invokes a function until a test condition is true.\n\n    The condition is evaluated *after* executing the provided function; thus,\n    `fcn` *always* executes at least once.\n\n    When invoked, both the predicate function and the function to invoke are\n    provided a single argument:\n\n    - i: iteration number (starting from zero).\n\n    Parameters\n    ----------\n    fcn: Function\n        The function to invoke.\n\n    predicate: Function\n        The predicate function which indicates whether to stop invoking a\n        function.\n\n    thisArg: any (optional)\n        Execution context for the invoked function.\n\n    Examples\n    --------\n    > function predicate( i ) { return ( i >= 5 ); };\n    > function beep( i ) { console.log( 'boop: %d', i ); };\n    > doUntil( beep, predicate )\n    boop: 0\n    boop: 1\n    boop: 2\n    boop: 3\n    boop: 4\n\n    See Also\n    --------\n    doUntilAsync, doUntilEach, doWhile, until, whilst\n","doUntilAsync":"\ndoUntilAsync( fcn, predicate, done[, thisArg] )\n    Invokes a function until a test condition is true.\n\n    The condition is evaluated *after* executing the provided function; thus,\n    `fcn` *always* executes at least once.\n\n    The function to invoke is provided two arguments:\n\n    - i: iteration number (starting from zero).\n    - next: a callback which must be invoked before proceeding to the next\n      iteration.\n\n    The first argument of the `next` callback is an `error` argument. If `fcn`\n    calls the `next` callback with a truthy `error` argument, the function\n    suspends execution and immediately calls the `done` callback for subsequent\n    `error` handling.\n\n    The predicate function is provided two arguments:\n\n    - i: iteration number (starting from one).\n    - clbk: a callback indicating whether to invoke `fcn`.\n\n    The `clbk` function accepts two arguments:\n\n    - error: error argument.\n    - bool: test result.\n\n    If the test result is falsy, the function continues invoking `fcn`;\n    otherwise, the function invokes the `done` callback.\n\n    The `done` callback is invoked with an `error` argument and any arguments\n    passed to the final `next` callback.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Parameters\n    ----------\n    fcn: Function\n        The function to invoke.\n\n    predicate: Function\n        The predicate function which indicates whether to continue invoking a\n        function.\n\n    done: Function\n        Callback to invoke upon completion.\n\n    thisArg: any (optional)\n        Execution context for the invoked function.\n\n    Examples\n    --------\n    > function fcn( i, next ) {\n    ...     setTimeout( onTimeout, i );\n    ...     function onTimeout() {\n    ...         next( null, 'boop'+i );\n    ...     }\n    ... };\n    > function predicate( i, clbk ) { clbk( null, i >= 5 ); };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > doUntilAsync( fcn, predicate, done )\n    boop: 4\n\n    See Also\n    --------\n    doUntil, doWhileAsync, untilAsync, whileAsync\n","doUntilEach":"\ndoUntilEach( collection, fcn, predicate[, thisArg] )\n    Until a test condition is true, invokes a function for each element in a\n    collection.\n\n    The condition is evaluated *after* executing the provided function; thus,\n    `fcn` *always* executes at least once.\n\n    When invoked, both the predicate function and the function to apply are\n    provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    If provided an empty collection, both `value` and `index` are `undefined`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    predicate: Function\n        The predicate function which indicates whether to stop iterating over a\n        collection.\n\n    thisArg: any (optional)\n        Execution context for the applied function.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function predicate( v ) { return v !== v; };\n    > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n    > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n    > doUntilEach( arr, logger, predicate )\n    0: 1\n    1: 2\n    2: 3\n    3: 4\n    4: NaN\n\n    See Also\n    --------\n    doUntilEachRight, doWhileEach, untilEach\n","doUntilEachRight":"\ndoUntilEachRight( collection, fcn, predicate[, thisArg] )\n    Until a test condition is true, invokes a function for each element in a\n    collection, iterating from right to left.\n\n    The condition is evaluated *after* executing the provided function; thus,\n    `fcn` *always* executes at least once.\n\n    When invoked, both the predicate function and the function to apply are\n    provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    If provided an empty collection, both `value` and `index` are `undefined`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    predicate: Function\n        The predicate function which indicates whether to stop iterating over a\n        collection.\n\n    thisArg: any (optional)\n        Execution context for the applied function.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function predicate( v ) { return v !== v; };\n    > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n    > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n    > doUntilEachRight( arr, logger, predicate )\n    5: 5\n    4: 4\n    3: 3\n    2: 2\n    1: NaN\n\n    See Also\n    --------\n    doUntilEach, doWhileEachRight, untilEachRight\n","doWhile":"\ndoWhile( fcn, predicate[, thisArg] )\n    Invokes a function while a test condition is true.\n\n    The condition is evaluated *after* executing the provided function; thus,\n    `fcn` *always* executes at least once.\n\n    When invoked, both the predicate function and the function to invoke are\n    provided a single argument:\n\n    - i: iteration number (starting from zero).\n\n    Parameters\n    ----------\n    fcn: Function\n        The function to invoke.\n\n    predicate: Function\n        The predicate function which indicates whether to continue invoking a\n        function.\n\n    thisArg: any (optional)\n        Execution context for the invoked function.\n\n    Examples\n    --------\n    > function predicate( i ) { return ( i < 5 ); };\n    > function beep( i ) { console.log( 'boop: %d', i ); };\n    > doWhile( beep, predicate )\n    boop: 0\n    boop: 1\n    boop: 2\n    boop: 3\n    boop: 4\n\n    See Also\n    --------\n    doUntil, doWhileAsync, doWhileEach, until, whilst\n","doWhileAsync":"\ndoWhileAsync( fcn, predicate, done[, thisArg] )\n    Invokes a function while a test condition is true.\n\n    The condition is evaluated *after* executing the provided function; thus,\n    `fcn` *always* executes at least once.\n\n    The function to invoke is provided two arguments:\n\n    - i: iteration number (starting from zero).\n    - next: a callback which must be invoked before proceeding to the next\n      iteration.\n\n    The first argument of the `next` callback is an `error` argument. If `fcn`\n    calls the `next` callback with a truthy `error` argument, the function\n    suspends execution and immediately calls the `done` callback for subsequent\n    `error` handling.\n\n    The predicate function is provided two arguments:\n\n    - i: iteration number (starting from one).\n    - clbk: a callback indicating whether to invoke `fcn`.\n\n    The `clbk` function accepts two arguments:\n\n    - error: error argument.\n    - bool: test result.\n\n    If the test result is truthy, the function continues invoking `fcn`;\n    otherwise, the function invokes the `done` callback.\n\n    The `done` callback is invoked with an `error` argument and any arguments\n    passed to the final `next` callback.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Parameters\n    ----------\n    fcn: Function\n        The function to invoke.\n\n    predicate: Function\n        The predicate function which indicates whether to continue invoking a\n        function.\n\n    done: Function\n        Callback to invoke upon completion.\n\n    thisArg: any (optional)\n        Execution context for the invoked function.\n\n    Examples\n    --------\n    > function fcn( i, next ) {\n    ...     setTimeout( onTimeout, i );\n    ...     function onTimeout() {\n    ...         next( null, 'boop'+i );\n    ...     }\n    ... };\n    > function predicate( i, clbk ) { clbk( null, i < 5 ); };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > doWhileAsync( fcn, predicate, done )\n    boop: 4\n\n    See Also\n    --------\n    doUntilAsync, doWhile, untilAsync, whileAsync\n","doWhileEach":"\ndoWhileEach( collection, fcn, predicate[, thisArg] )\n    While a test condition is true, invokes a function for each element in a\n    collection.\n\n    The condition is evaluated *after* executing the provided function; thus,\n    `fcn` *always* executes at least once.\n\n    When invoked, both the predicate function and the function to apply are\n    provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    If provided an empty collection, both `value` and `index` are `undefined`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    predicate: Function\n        The predicate function which indicates whether to continue iterating\n        over a collection.\n\n    thisArg: any (optional)\n        Execution context for the applied function.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === v; };\n    > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n    > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n    > doWhileEach( arr, logger, predicate )\n    0: 1\n    1: 2\n    2: 3\n    3: 4\n    4: NaN\n\n    See Also\n    --------\n    doUntilEach, doWhileEachRight, whileEach\n","doWhileEachRight":"\ndoWhileEachRight( collection, fcn, predicate[, thisArg] )\n    While a test condition is true, invokes a function for each element in a\n    collection, iterating from right to left.\n\n    The condition is evaluated *after* executing the provided function; thus,\n    `fcn` *always* executes at least once.\n\n    When invoked, both the predicate function and the function to apply are\n    provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    If provided an empty collection, both `value` and `index` are `undefined`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    predicate: Function\n        The predicate function which indicates whether to continue iterating\n        over a collection.\n\n    thisArg: any (optional)\n        Execution context for the applied function.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === v; };\n    > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n    > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n    > doWhileEachRight( arr, logger, predicate )\n    5: 5\n    4: 4\n    3: 3\n    2: 2\n    1: NaN\n\n    See Also\n    --------\n    doUntilEachRight, doWhileEach, whileEachRight\n","dswap":"\ndswap( x, y[, dim] )\n    Interchanges two double-precision floating-point vectors.\n\n    For multi-dimensional input arrays, the function performs batched\n    computation, such that the function interchanges each pair of vectors in `x`\n    and `y` according to the specified dimension index.\n\n    Both input arrays must have the same shape.\n\n    Parameters\n    ----------\n    x: ndarray\n        First input array. Must have a 'float64' data type. Must have at least\n        one dimension and must have the same shape as the second input array.\n\n    y: ndarray\n        Second input array. Must have a 'float64' data type. Must have at least\n        one dimension and must have the same shape as the first input array.\n\n    dim: integer (optional)\n        Dimension index along which to interchange vectors. Must be a negative\n        integer. Negative indices are resolved relative to the last array\n        dimension, with the last dimension corresponding to `-1`. Default: -1.\n\n    Returns\n    -------\n    y: ndarray\n        The second input array `y`.\n\n    Examples\n    --------\n    > var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n    > var y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n    > dswap( x, y );\n    > x.data\n    <Float64Array>[ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n    > y.data\n    <Float64Array>[ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dswap, gswap, sswap\n","E":"\nE\n    Euler's number.\n\n    Examples\n    --------\n    > E\n    2.718281828459045\n\n","EMOJI":"\nEMOJI()\n    Returns an emoji database.\n\n    Returns\n    -------\n    out: Array\n        Emoji database.\n\n    Examples\n    --------\n    > var data = EMOJI()\n    [ {...}, ... ]\n\n    See Also\n    --------\n    EMOJI_CODE_PICTO, EMOJI_PICTO_CODE\n","EMOJI_CODE_PICTO":"\nEMOJI_CODE_PICTO()\n    Returns an object mapping emoji codes to pictographs.\n\n    Returns\n    -------\n    out: Object\n        An object mapping emoji codes to pictographs.\n\n    Examples\n    --------\n    > var out = EMOJI_CODE_PICTO()\n\n    See Also\n    --------\n    EMOJI, EMOJI_PICTO_CODE\n","EMOJI_PICTO_CODE":"\nEMOJI_PICTO_CODE()\n    Returns an object mapping emoji pictographs to codes.\n\n    Returns\n    -------\n    out: Object\n        An object mapping emoji pictographs to codes.\n\n    Examples\n    --------\n    > var out = EMOJI_PICTO_CODE()\n\n    See Also\n    --------\n    EMOJI, EMOJI_CODE_PICTO\n","emptyStream":"\nemptyStream( [options] )\n    Returns an \"empty\" readable stream.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var s = emptyStream();\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nemptyStream.factory( [options] )\n    Returns a function for creating empty readable streams.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true };\n    > var createStream = emptyStream.factory( opts );\n\n\nemptyStream.objectMode()\n    Returns an \"objectMode\" empty readable stream.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var s = emptyStream.objectMode();\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    constantStream\n","emptyStream.factory":"\nemptyStream.factory( [options] )\n    Returns a function for creating empty readable streams.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true };\n    > var createStream = emptyStream.factory( opts );","emptyStream.objectMode":"\nemptyStream.objectMode()\n    Returns an \"objectMode\" empty readable stream.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var s = emptyStream.objectMode();\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    constantStream","endsWith":"\nendsWith( str, search[, len] )\n    Tests if a string ends with the characters of another string.\n\n    If provided an empty search string, the function always returns `true`.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search string.\n\n    len: integer (optional)\n        Substring length. Restricts the search to a substring within the input\n        string beginning from the leftmost character. If provided a negative\n        value, `len` indicates to ignore the last `len` characters, returning\n        the same output as `str.length + len`. Default: `str.length`.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a string ends with the characters of another\n        string.\n\n    Examples\n    --------\n    > var bool = endsWith( 'beep', 'ep' )\n    true\n    > bool = endsWith( 'Beep', 'op' )\n    false\n    > bool = endsWith( 'Beep', 'ee', 3 )\n    true\n    > bool = endsWith( 'Beep', 'ee', -1 )\n    true\n    > bool = endsWith( 'beep', '' )\n    true\n\n    See Also\n    --------\n    startsWith\n","enumerableProperties":"\nenumerableProperties( value )\n    Returns an array of an object's own enumerable property names and symbols.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    props: Array\n        List of an object's own enumerable properties.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var props = enumerableProperties( obj )\n    [ 'beep' ]\n\n    See Also\n    --------\n    enumerablePropertiesIn, enumerablePropertySymbols, inheritedEnumerableProperties, objectKeys, nonEnumerableProperties, properties\n","enumerablePropertiesIn":"\nenumerablePropertiesIn( value )\n    Returns an array of an object's own and inherited enumerable property names\n    and symbols.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    props: Array\n        List of an object's own and inherited enumerable property names and\n        symbols.\n\n    Examples\n    --------\n    > var props = enumerablePropertiesIn( [] )\n\n    See Also\n    --------\n    enumerableProperties, enumerablePropertySymbolsIn, inheritedEnumerableProperties, keysIn, nonEnumerablePropertiesIn, propertiesIn\n","enumerablePropertySymbols":"\nenumerablePropertySymbols( value )\n    Returns an array of an object's own enumerable symbol properties.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's own enumerable symbol properties.\n\n    Examples\n    --------\n    > var obj = {};\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = true;\n    > desc.writable = true;\n    > desc.value = 'boop';\n    > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n    > defineProperty( obj, sym, desc );\n    > var symbols = enumerablePropertySymbols( obj )\n\n    See Also\n    --------\n    enumerablePropertySymbolsIn, inheritedEnumerablePropertySymbols, objectKeys, nonEnumerablePropertySymbols, propertySymbols\n","enumerablePropertySymbolsIn":"\nenumerablePropertySymbolsIn( value )\n    Returns an array of an object's own and inherited enumerable symbol\n    properties.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's own and inherited enumerable symbol properties.\n\n    Examples\n    --------\n    > var obj = {};\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = true;\n    > desc.writable = true;\n    > desc.value = 'boop';\n    > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n    > defineProperty( obj, sym, desc );\n    > var symbols = enumerablePropertySymbolsIn( obj )\n\n    See Also\n    --------\n    enumerablePropertySymbols, inheritedEnumerablePropertySymbols, keysIn, nonEnumerablePropertySymbolsIn, propertySymbolsIn\n","ENV":"\nENV\n    An object containing the user environment.\n\n    Examples\n    --------\n    > var user = ENV.USER\n    <string>\n\n    See Also\n    --------\n    ARGV\n","EPS":"\nEPS\n    Difference between one and the smallest value greater than one that can be\n    represented as a double-precision floating-point number.\n\n    Examples\n    --------\n    > EPS\n    2.220446049250313e-16\n\n    See Also\n    --------\n    FLOAT32_EPS\n","error2json":"\nerror2json( error )\n    Returns a JSON representation of an error object.\n\n    The following built-in error types are supported:\n\n    - Error\n    - URIError\n    - ReferenceError\n    - SyntaxError\n    - RangeError\n    - EvalError\n    - TypeError\n\n    The JSON object is guaranteed to have the following properties:\n\n    - type: error type.\n    - message: error message.\n\n    The only standardized cross-platform property is `message`. Depending on the\n    platform, the following properties *may* be present:\n\n    - name: error name.\n    - stack: stack trace.\n    - code: error code (Node.js system errors).\n    - errno: error code string (Node.js system errors).\n    - syscall: string representing the failed system call (Node.js system\n      errors).\n\n    The function also serializes all enumerable properties.\n\n    The implementation supports custom error types and sets the `type` field to\n    the closest built-in error type.\n\n    Parameters\n    ----------\n    error: Error\n        Error to serialize.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var err = new Error( 'beep' );\n    > var json = error2json( err )\n    <Object>\n\n    See Also\n    --------\n    reviveError\n","EULERGAMMA":"\nEULERGAMMA\n    The Euler-Mascheroni constant.\n\n    Examples\n    --------\n    > EULERGAMMA\n    0.5772156649015329\n\n","every":"\nevery( collection )\n    Tests whether all elements in a collection are truthy.\n\n    The function immediately returns upon encountering a falsy value.\n\n    If provided an empty collection, the function returns `true`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if all elements are truthy; otherwise, the\n        function returns `false`.\n\n    Examples\n    --------\n    > var arr = [ 1, 1, 1, 1, 1 ];\n    > var bool = every( arr )\n    true\n\n    See Also\n    --------\n    any, everyBy, forEach, none, some\n","everyBy":"\neveryBy( collection, predicate[, thisArg ] )\n    Tests whether all elements in a collection pass a test implemented by a\n    predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    The function immediately returns upon encountering a non-truthy return\n    value.\n\n    If provided an empty collection, the function returns `true`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns a truthy\n        value for all elements; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function positive( v ) { return ( v > 0 ); };\n    > var arr = [ 1, 2, 3, 4 ];\n    > var bool = everyBy( arr, positive )\n    true\n\n    See Also\n    --------\n    anyBy, everyByRight, forEach, noneBy, someBy\n","everyByAsync":"\neveryByAsync( collection, [options,] predicate, done )\n    Tests whether all elements in a collection pass a test implemented by a\n    predicate function.\n\n    When invoked, the predicate function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If the\n    predicate function accepts two arguments, the predicate function is\n    provided:\n\n    - value\n    - next\n\n    If the predicate function accepts three arguments, the predicate function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other predicate function signature, the predicate function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - result: test result.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    The function immediately returns upon encountering a non-truthy `result`\n    value and calls the `done` callback with `null` as the first argument and\n    `false` as the second argument.\n\n    If all elements succeed, the function calls the `done` callback with `null`\n    as the first argument and `true` as the second argument.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, true );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > everyByAsync( arr, predicate, done )\n    1000\n    2500\n    3000\n    true\n\n    // Limit number of concurrent invocations:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, true );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 3000, 2500, 1000 ];\n    > everyByAsync( arr, opts, predicate, done )\n    2500\n    3000\n    1000\n    true\n\n    // Process sequentially:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, true );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 3000, 2500, 1000 ];\n    > everyByAsync( arr, opts, predicate, done )\n    3000\n    2500\n    1000\n    true\n\n\neveryByAsync.factory( [options,] predicate )\n    Returns a function which tests whether all elements in a collection pass a\n    test implemented by a predicate function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, true );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = everyByAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n\n    See Also\n    --------\n    anyByAsync, everyBy, everyByRightAsync, forEachAsync, noneByAsync, someByAsync\n","everyByAsync.factory":"\neveryByAsync.factory( [options,] predicate )\n    Returns a function which tests whether all elements in a collection pass a\n    test implemented by a predicate function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, true );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = everyByAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n\n    See Also\n    --------\n    anyByAsync, everyBy, everyByRightAsync, forEachAsync, noneByAsync, someByAsync","everyByRight":"\neveryByRight( collection, predicate[, thisArg ] )\n    Tests whether all elements in a collection pass a test implemented by a\n    predicate function, iterating from right to left.\n\n    The predicate function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    The function immediately returns upon encountering a non-truthy return\n    value.\n\n    If provided an empty collection, the function returns `true`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns a truthy\n        value for all elements; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function positive( v ) { return ( v > 0 ); };\n    > var arr = [ 1, 2, 3, 4 ];\n    > var bool = everyByRight( arr, positive )\n    true\n\n    See Also\n    --------\n    anyBy, every, everyBy, forEachRight, noneByRight, someByRight\n","everyByRightAsync":"\neveryByRightAsync( collection, [options,] predicate, done )\n    Tests whether all elements in a collection pass a test implemented by a\n    predicate function, iterating from right to left.\n\n    When invoked, the predicate function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If the\n    predicate function accepts two arguments, the predicate function is\n    provided:\n\n    - value\n    - next\n\n    If the predicate function accepts three arguments, the predicate function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other predicate function signature, the predicate function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - result: test result.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    The function immediately returns upon encountering a non-truthy `result`\n    value and calls the `done` callback with `null` as the first argument and\n    `false` as the second argument.\n\n    If all elements succeed, the function calls the `done` callback with `null`\n    as the first argument and `true` as the second argument.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, true );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > everyByRightAsync( arr, predicate, done )\n    1000\n    2500\n    3000\n    true\n\n    // Limit number of concurrent invocations:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, true );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 1000, 2500, 3000 ];\n    > everyByRightAsync( arr, opts, predicate, done )\n    2500\n    3000\n    1000\n    true\n\n    // Process sequentially:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, true );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 1000, 2500, 3000 ];\n    > everyByRightAsync( arr, opts, predicate, done )\n    3000\n    2500\n    1000\n    true\n\n\neveryByRightAsync.factory( [options,] predicate )\n    Returns a function which tests whether all elements in a collection pass a\n    test implemented by a predicate function, iterating from right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, true );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = everyByRightAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n\n    See Also\n    --------\n    anyByRightAsync, everyByAsync, everyByRight, forEachRightAsync, noneByRightAsync, someByRightAsync\n","everyByRightAsync.factory":"\neveryByRightAsync.factory( [options,] predicate )\n    Returns a function which tests whether all elements in a collection pass a\n    test implemented by a predicate function, iterating from right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, true );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = everyByRightAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n\n    See Also\n    --------\n    anyByRightAsync, everyByAsync, everyByRight, forEachRightAsync, noneByRightAsync, someByRightAsync","everyInBy":"\neveryInBy( object, predicate[, thisArg ] )\n   Test whether all properties (own and inherited) of an object pass a\n   test implemented by a predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: object value.\n    - key: object key.\n    - object: the input object.\n\n    The function immediately returns upon encountering a non-truthy return\n    value.\n\n    If provided an empty object, the function returns `true`.\n\n    Parameters\n    ----------\n    object: Object\n        Input object over which to iterate.\n\n    predicate: Function\n        Test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns a truthy\n        value for all elements; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function positive( v ) { return ( v > 0 ); };\n    > var o = {a: 1, b: 2, c: 3};\n    > var bool = everyInBy( o, positive )\n    true\n\n    See Also\n    --------\n    anyInBy, noneInBy, someInBy, everyBy, everyOwnBy\n","everyOwnBy":"\neveryOwnBy( object, predicate[, thisArg ] )\n    Tests whether every own property of an object pass a test implemented by a\n    predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: property value.\n    - index: property key.\n    - object: the input object.\n\n    The function immediately returns upon encountering a non-truthy return\n    value.\n\n    If provided an empty object, the function returns `true`.\n\n    Parameters\n    ----------\n    object: Object\n        Input object.\n\n    predicate: Function\n        Test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns a truthy\n        value for all elements; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function positive( v ) { return ( v > 0 ); };\n    > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n    > var bool = everyOwnBy( obj, positive )\n    true\n\n    See Also\n    --------\n    anyOwnBy, everyInBy, noneOwnBy, someOwnBy, everyBy\n","evil":"\nevil( str )\n    Alias for `eval` global.\n\n    A reference to `eval` is treated differently by the compiler. For example,\n    when evaluating code containing block-scoped declarations  (e.g., `let`,\n    `const`, `function`, `class`), the compiler may throw an `error` complaining\n    that block-scoped declarations are not yet supported outside of\n    `strict mode`. One possible workaround is to include `\"use strict\";` in the\n    evaluated code.\n\n    Parameters\n    ----------\n    str: string\n        Code to evaluate.\n\n    Returns\n    -------\n    out: any\n        Returned value if applicable.\n\n    Examples\n    --------\n    > var v = evil( '5*4*3*2*1' )\n    120\n\n","EXEC_PATH":"\nEXEC_PATH\n    Absolute pathname of the executable which started the current Node.js\n    process.\n\n    Examples\n    --------\n    > EXEC_PATH\n    <string>\n\n","exists":"\nexists( path, clbk )\n    Asynchronously tests whether a path exists on the filesystem.\n\n    Parameters\n    ----------\n    path: string|Buffer\n        Path to test.\n\n    clbk: Function\n        Callback to invoke after testing for path existence. A callback may\n        accept a single argument, a boolean indicating whether a path exists, or\n        two arguments, an error argument and a boolean, matching the error-first\n        callback convention used in most asynchronous Node.js APIs.\n\n    Examples\n    --------\n    > function done( error, bool ) { console.log( bool ); };\n    > exists( './beep/boop', done );\n\n\nexists.sync( path )\n    Synchronously tests whether a path exists on the filesystem.\n\n    Parameters\n    ----------\n    path: string|Buffer\n        Path to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the path exists.\n\n    Examples\n    --------\n    > var bool = exists.sync( './beep/boop' )\n    <boolean>\n\n    See Also\n    --------\n    readFile, readDir\n","exists.sync":"\nexists.sync( path )\n    Synchronously tests whether a path exists on the filesystem.\n\n    Parameters\n    ----------\n    path: string|Buffer\n        Path to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether the path exists.\n\n    Examples\n    --------\n    > var bool = exists.sync( './beep/boop' )\n    <boolean>\n\n    See Also\n    --------\n    readFile, readDir","expandAcronyms":"\nexpandAcronyms( str )\n    Expands acronyms in a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        String with expanded acronyms.\n\n    Examples\n    --------\n    > var str = 'LOL, this is fun. I am ROFL.';\n    > var out = expandAcronyms( str )\n    'laughing out loud, this is fun. I am rolling on the floor laughing.'\n\n    > str = 'brb, I need to check my mail. thx!';\n    > out = expandAcronyms( str )\n    'be right back, I need to check my mail. thanks!'\n\n    See Also\n    --------\n    expandContractions\n","expandContractions":"\nexpandContractions( str )\n    Expands all contractions to their formal equivalents.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        String with expanded contractions.\n\n    Examples\n    --------\n    > var str = 'I won\\'t be able to get y\\'all out of this one.';\n    > var out = expandContractions( str )\n    'I will not be able to get you all out of this one.'\n\n    > str = 'It oughtn\\'t to be my fault, because, you know, I didn\\'t know';\n    > out = expandContractions( str )\n    'It ought not to be my fault, because, you know, I did not know'\n\n","extname":"\nextname( filename )\n    Returns a filename extension.\n\n    Parameters\n    ----------\n    filename: string\n        Filename.\n\n    Returns\n    -------\n    ext: string\n        Filename extension.\n\n    Examples\n    --------\n    > var ext = extname( 'index.js' )\n    '.js'\n\n    See Also\n    --------\n    dirname\n","FancyArray":"\nFancyArray( dtype, buffer, shape, strides, offset, order[, options] )\n    Returns a FancyArray instance.\n\n    A FancyArray is an ndarray which supports slicing via indexing expressions.\n\n    A FancyArray is an ndarray instance and supports all ndarray options,\n    attributes, and methods. A FancyArray can be consumed by any API which\n    supports ndarray instances.\n\n    Indexing expressions provide a convenient and powerful means for creating\n    and operating on ndarray views; however, their use does entail a performance\n    cost. Indexing expressions are best suited for interactive use and\n    scripting. For performance critical applications, prefer equivalent\n    functional APIs supporting ndarray instances.\n\n    In older JavaScript environments which do not support Proxy objects, the use\n    of indexing expressions is not supported.\n\n    Parameters\n    ----------\n    dtype: string\n        Underlying data type.\n\n    buffer: ArrayLikeObject|TypedArray|Buffer\n        Data buffer. A data buffer must be an array-like object (i.e., have a\n        `length` property). For data buffers which are not indexed collections\n        (i.e., collections which cannot support direct index access, such as\n        `buffer[ index ]`; e.g., Complex64Array, Complex128Array, etc), a data\n        buffer should provide `#.get( idx )` and `#.set( v[, idx] )` methods.\n        Note that, for `set` methods, the value to set should be the first\n        argument, followed by the linear index, similar to the native typed\n        array `set` method.\n\n    shape: ArrayLikeObject<integer>\n        Array shape.\n\n    strides: ArrayLikeObject<integer>\n        Array strides.\n\n    offset: integer\n        Index offset.\n\n    order: string\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran-style).\n\n    options: Object (optional)\n        Options.\n\n    options.mode: string (optional)\n        Specifies how to handle indices which exceed array dimensions. If equal\n        to 'throw', an ndarray instance throws an error when an index exceeds\n        array dimensions. If equal to 'normalize', an ndarray instance\n        normalizes negative indices and throws an error when an index exceeds\n        array dimensions. If equal to 'wrap', an ndarray instance wraps around\n        indices exceeding array dimensions using modulo arithmetic. If equal to\n        'clamp', an ndarray instance sets an index exceeding array dimensions\n        to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n    options.submode: Array<string> (optional)\n        Specifies how to handle subscripts which exceed array dimensions. If a\n        mode for a corresponding dimension is equal to 'throw', an ndarray\n        instance throws an error when a subscript exceeds array dimensions. If\n        equal to 'normalize', an ndarray instance normalizes negative\n        subscripts and throws an error when a subscript exceeds array\n        dimensions. If equal to 'wrap', an ndarray instance wraps around\n        subscripts exceeding array dimensions using modulo arithmetic. If equal\n        to 'clamp', an ndarray instance sets a subscript exceeding array\n        dimensions to either `0` (minimum index) or the maximum index. If the\n        number of modes is fewer than the number of dimensions, the function\n        recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether an array should be read-only. Default: false.\n\n    Returns\n    -------\n    ndarray: FancyArray\n        FancyArray instance.\n\n    Examples\n    --------\n    // Create a new instance...\n    > var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\n    > var d = [ 2, 2 ]; // shape\n    > var s = [ 2, 1 ]; // strides\n    > var o = 0; // index offset\n    > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' )\n    <FancyArray>\n\n    // Get an element using subscripts:\n    > var v = arr.get( 1, 1 )\n    4.0\n\n    // Get an element using a linear index:\n    > v = arr.iget( 3 )\n    4.0\n\n    // Set an element using subscripts:\n    > arr.set( 1, 1, 40.0 );\n    > arr.get( 1, 1 )\n    40.0\n\n    // Set an element using a linear index:\n    > arr.iset( 3, 99.0 );\n    > arr.get( 1, 1 )\n    99.0\n\n\nFancyArray.prototype.byteLength\n    Size (in bytes) of the array (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of the array.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.byteLength\n    32\n\n\nFancyArray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.BYTES_PER_ELEMENT\n    8\n\n\nFancyArray.prototype.data\n    Pointer to the underlying data buffer.\n\n    Returns\n    -------\n    buf: ArrayLikeObject|TypedArray|Buffer\n        Underlying data buffer.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var buf = arr.data\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n\nFancyArray.prototype.dtype\n    Underlying data type.\n\n    Returns\n    -------\n    dtype: string\n        Underlying data type.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var dt = arr.dtype\n    'float64'\n\n\nFancyArray.prototype.flags\n    Meta information, such as information concerning the memory layout of the\n    array.\n\n    Returns\n    -------\n    flags: Object\n        Info object.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var fl = arr.flags\n    {...}\n\n\nFancyArray.prototype.length\n    Length of the array (i.e., number of elements).\n\n    Returns\n    -------\n    len: integer\n        Array length.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var len = arr.length\n    4\n\n\nFancyArray.prototype.ndims\n    Number of dimensions.\n\n    Returns\n    -------\n    ndims: integer\n        Number of dimensions.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var n = arr.ndims\n    2\n\n\nFancyArray.prototype.offset\n    Index offset which specifies the buffer index at which to start iterating\n    over array elements.\n\n    Returns\n    -------\n    offset: integer\n        Index offset.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.offset\n    0\n\n\nFancyArray.prototype.order\n    Array order.\n\n    The array order is either row-major (C-style) or column-major (Fortran-\n    style).\n\n    Returns\n    -------\n    order: string\n        Array order.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var ord = arr.order\n    'row-major'\n\n\nFancyArray.prototype.shape\n    Array shape.\n\n    Returns\n    -------\n    shape: Array\n        Array shape.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var sh = arr.shape\n    [ 2, 2 ]\n\n\nFancyArray.prototype.strides\n    Index strides which specify how to access data along corresponding array\n    dimensions.\n\n    Returns\n    -------\n    strides: Array\n        Index strides.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var st = arr.strides\n    [ 2, 1 ]\n\n\nFancyArray.prototype.get( ...idx )\n    Returns an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.get( 1, 1 )\n    4.0\n\n\nFancyArray.prototype.iget( idx )\n    Returns an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the input argument is ignored and, for clarity,\n    should not be provided.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.iget( 3 )\n    4.0\n\n\nFancyArray.prototype.set( ...idx, v )\n    Sets an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: FancyArray\n        FancyArray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > arr.set( 1, 1, -4.0 );\n    > arr.get( 1, 1 )\n    -4.0\n\n\nFancyArray.prototype.iset( idx, v )\n    Sets an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the first, and only, argument should be the\n    value to set.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: FancyArray\n        FancyArray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > arr.iset( 3, -4.0 );\n    > arr.iget( 3 )\n    -4.0\n\n\nFancyArray.prototype.toString()\n    Serializes a FancyArray as a string.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    str: string\n        Serialized ndarray string.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toString()\n    '...'\n\n\nFancyArray.prototype.toJSON()\n    Serializes a FancyArray as a JSON object.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toJSON()\n    {...}\n\n    See Also\n    --------\n    array, ndarray\n","FancyArray.prototype.byteLength":"\nFancyArray.prototype.byteLength\n    Size (in bytes) of the array (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of the array.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.byteLength\n    32","FancyArray.prototype.BYTES_PER_ELEMENT":"\nFancyArray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.BYTES_PER_ELEMENT\n    8","FancyArray.prototype.data":"\nFancyArray.prototype.data\n    Pointer to the underlying data buffer.\n\n    Returns\n    -------\n    buf: ArrayLikeObject|TypedArray|Buffer\n        Underlying data buffer.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var buf = arr.data\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]","FancyArray.prototype.dtype":"\nFancyArray.prototype.dtype\n    Underlying data type.\n\n    Returns\n    -------\n    dtype: string\n        Underlying data type.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var dt = arr.dtype\n    'float64'","FancyArray.prototype.flags":"\nFancyArray.prototype.flags\n    Meta information, such as information concerning the memory layout of the\n    array.\n\n    Returns\n    -------\n    flags: Object\n        Info object.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var fl = arr.flags\n    {...}","FancyArray.prototype.length":"\nFancyArray.prototype.length\n    Length of the array (i.e., number of elements).\n\n    Returns\n    -------\n    len: integer\n        Array length.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var len = arr.length\n    4","FancyArray.prototype.ndims":"\nFancyArray.prototype.ndims\n    Number of dimensions.\n\n    Returns\n    -------\n    ndims: integer\n        Number of dimensions.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var n = arr.ndims\n    2","FancyArray.prototype.offset":"\nFancyArray.prototype.offset\n    Index offset which specifies the buffer index at which to start iterating\n    over array elements.\n\n    Returns\n    -------\n    offset: integer\n        Index offset.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.offset\n    0","FancyArray.prototype.order":"\nFancyArray.prototype.order\n    Array order.\n\n    The array order is either row-major (C-style) or column-major (Fortran-\n    style).\n\n    Returns\n    -------\n    order: string\n        Array order.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var ord = arr.order\n    'row-major'","FancyArray.prototype.shape":"\nFancyArray.prototype.shape\n    Array shape.\n\n    Returns\n    -------\n    shape: Array\n        Array shape.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var sh = arr.shape\n    [ 2, 2 ]","FancyArray.prototype.strides":"\nFancyArray.prototype.strides\n    Index strides which specify how to access data along corresponding array\n    dimensions.\n\n    Returns\n    -------\n    strides: Array\n        Index strides.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var st = arr.strides\n    [ 2, 1 ]","FancyArray.prototype.get":"\nFancyArray.prototype.get( ...idx )\n    Returns an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.get( 1, 1 )\n    4.0","FancyArray.prototype.iget":"\nFancyArray.prototype.iget( idx )\n    Returns an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the input argument is ignored and, for clarity,\n    should not be provided.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.iget( 3 )\n    4.0","FancyArray.prototype.set":"\nFancyArray.prototype.set( ...idx, v )\n    Sets an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: FancyArray\n        FancyArray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > arr.set( 1, 1, -4.0 );\n    > arr.get( 1, 1 )\n    -4.0","FancyArray.prototype.iset":"\nFancyArray.prototype.iset( idx, v )\n    Sets an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the first, and only, argument should be the\n    value to set.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: FancyArray\n        FancyArray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'float64', b, d, s, o, 'row-major' );\n    > arr.iset( 3, -4.0 );\n    > arr.iget( 3 )\n    -4.0","FancyArray.prototype.toString":"\nFancyArray.prototype.toString()\n    Serializes a FancyArray as a string.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    str: string\n        Serialized ndarray string.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toString()\n    '...'","FancyArray.prototype.toJSON":"\nFancyArray.prototype.toJSON()\n    Serializes a FancyArray as a JSON object.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = FancyArray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toJSON()\n    {...}\n\n    See Also\n    --------\n    array, ndarray","fastmath.abs":"\nfastmath.abs( x )\n    Computes an absolute value.\n\n    This implementation is not IEEE 754 compliant. If provided `-0`, the\n    function returns `-0`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    out: number\n        Absolute value.\n\n    Examples\n    --------\n    > var v = fastmath.abs( -1.0 )\n    1.0\n    > v = fastmath.abs( 2.0 )\n    2.0\n    > v = fastmath.abs( 0.0 )\n    0.0\n    > v = fastmath.abs( -0.0 )\n    -0.0\n    > v = fastmath.abs( NaN )\n    NaN\n\n    See Also\n    --------\n    base.abs\n","fastmath.acosh":"\nfastmath.acosh( x )\n    Computes the hyperbolic arccosine of a number.\n\n    The domain of `x` is restricted to `[1,+infinity)`. If `x < 1`, the function\n    will return `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    out: number\n        Hyperbolic arccosine (in radians).\n\n    Examples\n    --------\n    > var v = fastmath.acosh( 1.0 )\n    0.0\n    > v = fastmath.acosh( 2.0 )\n    ~1.317\n    > v = fastmath.acosh( NaN )\n    NaN\n\n    // The function overflows for large `x`:\n    > v = fastmath.acosh( 1.0e308 )\n    Infinity\n\n    See Also\n    --------\n    base.acosh\n","fastmath.ampbm":"\nfastmath.ampbm( x, y )\n    Computes the hypotenuse using the alpha max plus beta min algorithm.\n\n    The algorithm computes only an approximation.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Hypotenuse.\n\n    Examples\n    --------\n    > var h = fastmath.ampbm( 5.0, 12.0 )\n    ~13.514\n\n\nfastmath.ampbm.factory( alpha, beta, [nonnegative[, ints]] )\n    Returns a function to compute a hypotenuse using the alpha max plus beta min\n    algorithm.\n\n    Parameters\n    ----------\n    alpha: number\n        Alpha.\n\n    beta: number\n        Beta.\n\n    nonnegative: boolean (optional)\n        Boolean indicating whether input values are always nonnegative.\n\n    ints: boolean (optional)\n        Boolean indicating whether input values are always 32-bit integers.\n\n    Returns\n    -------\n    fcn: Function\n        Function to compute a hypotenuse.\n\n    Examples\n    --------\n    > var hypot = fastmath.ampbm.factory( 1.0, 0.5 )\n    <Function>\n\n    See Also\n    --------\n    base.hypot\n","fastmath.ampbm.factory":"\nfastmath.ampbm.factory( alpha, beta, [nonnegative[, ints]] )\n    Returns a function to compute a hypotenuse using the alpha max plus beta min\n    algorithm.\n\n    Parameters\n    ----------\n    alpha: number\n        Alpha.\n\n    beta: number\n        Beta.\n\n    nonnegative: boolean (optional)\n        Boolean indicating whether input values are always nonnegative.\n\n    ints: boolean (optional)\n        Boolean indicating whether input values are always 32-bit integers.\n\n    Returns\n    -------\n    fcn: Function\n        Function to compute a hypotenuse.\n\n    Examples\n    --------\n    > var hypot = fastmath.ampbm.factory( 1.0, 0.5 )\n    <Function>\n\n    See Also\n    --------\n    base.hypot","fastmath.asinh":"\nfastmath.asinh( x )\n    Computes the hyperbolic arcsine of a number.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    out: number\n        Hyperbolic arcsine (in radians).\n\n    Examples\n    --------\n    > var v = fastmath.asinh( 0.0 )\n    0.0\n    > v = fastmath.asinh( 2.0 )\n    ~1.444\n    > v = fastmath.asinh( -2.0 )\n    ~-1.444\n    > v = fastmath.asinh( NaN )\n    NaN\n\n    // The function overflows for large `x`:\n    > v = fastmath.asinh( 1.0e200 )\n    Infinity\n\n    // The function underflows for small `x`:\n    > v = fastmath.asinh( 1.0e-50 )\n    0.0\n\n    See Also\n    --------\n    base.asinh\n","fastmath.atanh":"\nfastmath.atanh( x )\n    Computes the hyperbolic arctangent of a number.\n\n    The domain of `x` is restricted to `[-1,1]`. If `|x| > 1`, the function\n    returns `NaN`.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    Returns\n    -------\n    out: number\n        Hyperbolic arctangent (in radians).\n\n    Examples\n    --------\n    > var v = fastmath.atanh( 0.0 )\n    0.0\n    > v = fastmath.atanh( 0.9 )\n    ~1.472\n    > v = fastmath.atanh( 1.0 )\n    Infinity\n    > v = fastmath.atanh( -1.0 )\n    -Infinity\n    > v = fastmath.atanh( NaN )\n    NaN\n\n    // The function underflows for small `x`:\n    > v = fastmath.atanh( 1.0e-17 )\n    0.0\n\n    See Also\n    --------\n    base.atanh\n","fastmath.hypot":"\nfastmath.hypot( x, y )\n    Computes the hypotenuse.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Hypotenuse.\n\n    Examples\n    --------\n    > var h = fastmath.hypot( -5.0, 12.0 )\n    13.0\n\n    // For a sufficiently large `x` and/or `y`, the function overflows:\n    > h = fastmath.hypot( 1.0e154, 1.0e154 )\n    Infinity\n\n    // For sufficiently small `x` and/or `y`, the function underflows:\n    > h = fastmath.hypot( 1e-200, 1.0e-200 )\n    0.0\n\n    See Also\n    --------\n    base.hypot\n","fastmath.log2Uint32":"\nfastmath.log2Uint32( x )\n    Returns an approximate binary logarithm (base two) of an unsigned 32-bit\n    integer `x`.\n\n    This function provides a performance boost when requiring only approximate\n    computations for integer arguments.\n\n    For high-precision applications, this function is never suitable.\n\n    Parameters\n    ----------\n    x: uinteger\n        Input value.\n\n    Returns\n    -------\n    out: uinteger\n        Integer binary logarithm (base two).\n\n    Examples\n    --------\n    > var v = fastmath.log2Uint32( 4 >>> 0 )\n    2\n    > v = fastmath.log2Uint32( 8 >>> 0 )\n    3\n    > v = fastmath.log2Uint32( 9 >>> 0 )\n    3\n\n    See Also\n    --------\n    base.log2\n","fastmath.max":"\nfastmath.max( x, y )\n    Returns the maximum value.\n\n    The function ignores the sign of `0` and does not check for `NaN` arguments.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    > var v = fastmath.max( 3.14, 4.2 )\n    4.2\n    > v = fastmath.max( 3.14, NaN )\n    NaN\n    > v = fastmath.max( NaN, 3.14 )\n    3.14\n    > v = fastmath.max( -0.0, +0.0 )\n    +0.0\n    > v = fastmath.max( +0.0, -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.max\n","fastmath.min":"\nfastmath.min( x, y )\n    Returns the minimum value.\n\n    The function ignores the sign of `0` and does not check for `NaN` arguments.\n\n    Parameters\n    ----------\n    x: number\n        First number.\n\n    y: number\n        Second number.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    > var v = fastmath.min( 3.14, 4.2 )\n    3.14\n    > v = fastmath.min( 3.14, NaN )\n    NaN\n    > v = fastmath.min( NaN, 3.14 )\n    3.14\n    > v = fastmath.min( -0.0, +0.0 )\n    +0.0\n    > v = fastmath.min( +0.0, -0.0 )\n    -0.0\n\n    See Also\n    --------\n    base.min\n","fastmath.powint":"\nfastmath.powint( x, y )\n    Evaluates the exponential function given a signed 32-bit integer exponent.\n\n    This function is not recommended for high-precision applications due to\n    error accumulation.\n\n    If provided a negative exponent, the function first computes the reciprocal\n    of the base and then evaluates the exponential function. This can introduce\n    significant error.\n\n    Parameters\n    ----------\n    x: number\n        Base.\n\n    y: integer\n        Signed 32-bit integer exponent.\n\n    Returns\n    -------\n    out: number\n        Function value.\n\n    Examples\n    --------\n    > var v = fastmath.powint( 2.0, 3 )\n    8.0\n    > v = fastmath.powint( 3.14, 0 )\n    1.0\n    > v = fastmath.powint( 2.0, -2 )\n    0.25\n    > v = fastmath.powint( 0.0, 0 )\n    1.0\n    > v = fastmath.powint( -3.14, 1 )\n    -3.14\n    > v = fastmath.powint( NaN, 0 )\n    NaN\n\n    See Also\n    --------\n    base.pow\n","fastmath.sqrtUint32":"\nfastmath.sqrtUint32( x )\n    Returns an approximate square root of an unsigned 32-bit integer `x`.\n\n    Prefer hardware `sqrt` over a software implementation.\n\n    When using a software `sqrt`, this function provides a performance boost\n    when an application requires only approximate computations for integer\n    arguments.\n\n    For applications requiring high-precision, this function is never suitable.\n\n    Parameters\n    ----------\n    x: uinteger\n        Input value.\n\n    Returns\n    -------\n    out: uinteger\n        Integer square root.\n\n    Examples\n    --------\n    > var v = fastmath.sqrtUint32( 9 >>> 0 )\n    3\n    > v = fastmath.sqrtUint32( 2 >>> 0 )\n    1\n    > v = fastmath.sqrtUint32( 3 >>> 0 )\n    1\n    > v = fastmath.sqrtUint32( 0 >>> 0 )\n    0\n\n    See Also\n    --------\n    base.sqrt\n","FEMALE_FIRST_NAMES_EN":"\nFEMALE_FIRST_NAMES_EN()\n    Returns a list of common female first names in English speaking countries.\n\n    Returns\n    -------\n    out: Array<string>\n        List of common female first names.\n\n    Examples\n    --------\n    > var list = FEMALE_FIRST_NAMES_EN()\n    [ 'Aaren', 'Aarika', 'Abagael', 'Abagail', ... ]\n\n    References\n    ----------\n    - Ward, Grady. 2002. \"Moby Word II.\" <http://www.gutenberg.org/files/3201/\n    3201.txt>.\n\n    See Also\n    --------\n    MALE_FIRST_NAMES_EN\n","FIFO":"\nFIFO()\n    First-in-first-out (FIFO) queue constructor.\n\n    Returns\n    -------\n    queue: Object\n        First-in-first-out queue.\n\n    queue.clear: Function\n        Clears the queue.\n\n    queue.first: Function\n        Returns the \"oldest\" queue value (i.e., the value which is \"first-out\").\n        If the queue is empty, the returned value is `undefined`.\n\n    queue.iterator: Function\n        Returns an iterator for iterating over a queue. If an environment\n        supports Symbol.iterator, the returned iterator is iterable. Note that,\n        in order to prevent confusion arising from queue mutation during\n        iteration, a returned iterator **always** iterates over a queue\n        \"snapshot\", which is defined as the list of queue elements at the time\n        of the method's invocation.\n\n    queue.last: Function\n        Returns the \"newest\" queue value (i.e., the value which is \"last-out\").\n        If the queue is empty, the returned value is `undefined`.\n\n    queue.length: integer\n        Queue length.\n\n    queue.pop: Function\n        Removes and returns the current \"first-out\" value from the queue. If the\n        queue is empty, the returned value is `undefined`.\n\n    queue.push: Function\n        Adds a value to the queue.\n\n    queue.toArray: Function\n        Returns an array of queue values.\n\n    queue.toJSON: Function\n        Serializes a queue as JSON.\n\n    Examples\n    --------\n    > var q = FIFO();\n    > q.push( 'foo' ).push( 'bar' );\n    > q.length\n    2\n    > q.pop()\n    'foo'\n    > q.length\n    1\n    > q.pop()\n    'bar'\n    > q.length\n    0\n\n    See Also\n    --------\n    Stack\n","filledarray":"\nfilledarray( [dtype] )\n    Creates a filled array.\n\n    Parameters\n    ----------\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = filledarray()\n    <Float64Array>\n    > arr = filledarray( 'float32' )\n    <Float32Array>\n\n\nfilledarray( value, length[, dtype] )\n    Returns a filled array having a specified length.\n\n    Parameters\n    ----------\n    value: any\n        Fill value.\n\n    length: integer\n        Array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = filledarray( 1.0, 5 )\n    <Float64Array>[ 1.0, 1.0, 1.0, 1.0, 1.0 ]\n    > arr = filledarray( 1, 5, 'int32' )\n    <Int32Array>[ 1, 1, 1, 1, 1 ]\n\n\nfilledarray( value, array[, dtype] )\n    Creates a filled array from another array (or array-like object).\n\n    Parameters\n    ----------\n    value: any\n        Fill value.\n\n    array: ArrayLikeObject\n        Array from which to generate another array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr1 = filledarray( 2.0, [ 0.5, 0.5, 0.5 ] )\n    <Float64Array>[ 2.0, 2.0, 2.0 ]\n    > var arr2 = filledarray( 1.0, arr1, 'float32' )\n    <Float32Array>[ 1.0, 1.0, 1.0 ]\n\n\nfilledarray( value, iterable[, dtype] )\n    Creates a filled array from an iterable.\n\n    Parameters\n    ----------\n    value: any\n        Fill value.\n\n    iterable: Iterable\n        Iterable from which to generate an array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr1 = iterConstant( 3.0, {'iter': 3} );\n    > var arr2 = filledarray( 1.0, arr1, 'float32' )\n    <Float32Array>[ 1.0, 1.0, 1.0 ]\n\n\nfilledarray( value, buffer[, byteOffset[, length]][, dtype] )\n    Returns a filled typed array view of an ArrayBuffer.\n\n    The 'generic' array data type is *not* supported.\n\n    Parameters\n    ----------\n    value: any\n        Fill value.\n\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 16 );\n    > var arr = filledarray( 1.0, buf, 0, 4, 'float32' )\n    <Float32Array>[ 1.0, 1.0, 1.0, 1.0 ]\n\n    See Also\n    --------\n    filledarrayBy, typedarray\n","filledarrayBy":"\nfilledarrayBy( [dtype] )\n    Creates a filled array.\n\n    Parameters\n    ----------\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr = filledarrayBy()\n    <Float64Array>\n    > arr = filledarrayBy( 'float32' )\n    <Float32Array>\n\n\nfilledarrayBy( length[, dtype], clbk[, thisArg] )\n    Returns a filled array according to a provided callback function and having\n    a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > function clbk() { return 1.0; };\n    > var arr = filledarrayBy( 5, clbk )\n    <Float64Array>[ 1.0, 1.0, 1.0, 1.0, 1.0 ]\n    > arr = filledarrayBy( 5, 'int32', clbk )\n    <Int32Array>[ 1, 1, 1, 1, 1 ]\n\n\nfilledarrayBy( array[, dtype], clbk[, thisArg] )\n    Creates a filled array from another array (or array-like object) according\n    to a provided callback function.\n\n    Parameters\n    ----------\n    array: ArrayLikeObject\n        Array from which to generate another array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr1 = filledarrayBy( [ 0.5, 0.5, 0.5 ], constantFunction( 2.0 ) )\n    <Float64Array>[ 2.0, 2.0, 2.0 ]\n    > var arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\n    <Float32Array>[ 1.0, 1.0, 1.0 ]\n\n\nfilledarrayBy( iterable[, dtype], clbk[, thisArg] )\n    Creates a filled array from an iterable according to a provided callback\n    function.\n\n    Parameters\n    ----------\n    iterable: Iterable\n        Iterable from which to generate an array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: TypedArray|Array\n        Output array.\n\n    Examples\n    --------\n    > var arr1 = iterConstant( 3.0, {'iter': 3} );\n    > var arr2 = filledarrayBy( arr1, 'float32', constantFunction( 1.0 ) )\n    <Float32Array>[ 1.0, 1.0, 1.0 ]\n\n\nfilledarrayBy( buffer[, byteOffset[, length]][, dtype], clbk[, thisArg] )\n    Returns a filled typed array view of an ArrayBuffer according to a provided\n    callback function.\n\n    The 'generic' array data type is *not* supported.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 16 );\n    > var arr = filledarrayBy( buf, 0, 4, 'float32', constantFunction( 1.0 ) )\n    <Float32Array>[ 1.0, 1.0, 1.0, 1.0 ]\n\n    See Also\n    --------\n    filledarray, typedarray\n","filterArguments":"\nfilterArguments( fcn, predicate[, thisArg] )\n    Returns a function that applies arguments to a provided function according\n    to a predicate function.\n\n    Only those arguments in which the predicate function returns a truthy value\n    are applied to a provided function.\n\n    The predicate function is provided the following arguments:\n\n    - value: argument value.\n    - index: argument index.\n\n    Parameters\n    ----------\n    fcn: Function\n        Input function.\n\n    predicate: Function\n        Predicate function.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Function\n        Function wrapper.\n\n    Examples\n    --------\n    > function foo( a, b ) { return [ a, b ]; };\n    > function predicate( v ) { return ( v !== 2 ); };\n    > var bar = filterArguments( foo, predicate );\n    > var out = bar( 1, 2, 3 )\n    [ 1, 3 ]\n\n    See Also\n    --------\n    maskArguments, rejectArguments, reorderArguments, reverseArguments\n","find":"\nfind( arr, [options,] clbk )\n    Finds elements in an array-like object that satisfy a test condition.\n\n    Parameters\n    ----------\n    arr: Array|TypedArray|string\n        Object from which elements will be tested.\n\n    options: Object (optional)\n        Options.\n\n    options.k: integer (optional)\n        Limits the number of returned elements. The sign determines the\n        direction in which to search. If set to a negative integer, the function\n        searches from last element to first element. Default: arr.length.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `indices`, indices are returned; if\n        `*`, both indices and values are returned. Default: 'indices'.\n\n    clbk: Function\n        Function invoked for each array element. If the return value is truthy,\n        the value is considered to have satisfied the test condition.\n\n    Returns\n    -------\n    out: Array\n        Array of indices, element values, or arrays of index-value pairs.\n\n    Examples\n    --------\n    > var data = [ 30, 20, 50, 60, 10 ];\n    > function condition( val ) { return val > 20; };\n    > var vals = find( data, condition )\n    [ 0, 2, 3 ]\n\n    // Limit number of results:\n    > data = [ 30, 20, 50, 60, 10 ];\n    > var opts = { 'k': 2, 'returns': 'values' };\n    > vals = find( data, opts, condition )\n    [ 30, 50 ]\n\n    // Return both indices and values as index-value pairs:\n    > data = [ 30, 20, 50, 60, 10 ];\n    > opts = { 'k': -2, 'returns': '*' };\n    > vals = find( data, opts, condition )\n    [ [ 3, 60 ], [ 2, 50 ] ]\n\n","firstChar":"\nfirstChar( str[, n][, options] )\n    Returns the first character(s) of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer (optional)\n        Number of characters to return. Default: 1.\n\n    options: Object (optional)\n        Options.\n\n    options.mode: string (optional)\n        Type of characters to return. The following modes are supported:\n\n        - grapheme: grapheme clusters. Appropriate for strings containing visual\n          characters which can span multiple Unicode code points (e.g., emoji).\n        - code_point: Unicode code points. Appropriate for strings containing\n          visual characters which are comprised of more than one Unicode code\n          unit (e.g., ideographic symbols and punctuation and mathematical\n          alphanumerics).\n        - code_unit': UTF-16 code units. Appropriate for strings containing\n          visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n          common characters, such as those from the Latin, Greek, and Cyrillic\n          alphabets).\n\n        Default: 'grapheme'.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = firstChar( 'beep' )\n    'b'\n    > out = firstChar( 'Boop', 1 )\n    'B'\n    > out = firstChar( 'foo bar', 5 )\n    'foo b'\n\n    See Also\n    --------\n    removeFirst, last\n","FIVETHIRTYEIGHT_FFQ":"\nFIVETHIRTYEIGHT_FFQ()\n    Returns FiveThirtyEight reader responses to a food frequency questionnaire\n    (FFQ).\n\n    Returns\n    -------\n    out: Array<Object>\n        FiveThirtyEight reader responses to a food frequency questionnaire\n        (FFQ).\n\n    Examples\n    --------\n    > var data = FIVETHIRTYEIGHT_FFQ()\n    [ {...}, ... ]\n\n    References\n    ----------\n    - Aschwanden, Christie. 2016. \"You Can't Trust What You Read About\n    Nutrition.\" <https://fivethirtyeight.com/features/you-cant-trust-what-you-\n    read-about-nutrition/>.\n\n    * If you use the data for publication or third party consumption, please\n    cite the listed reference.\n\n","flattenArray":"\nflattenArray( arr[, options] )\n    Flattens an array.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject\n        Input array.\n\n    options: Object (optional)\n        Options.\n\n    options.depth: integer (optional)\n        Maximum depth to flatten.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to deep copy array elements. Default: false.\n\n    Returns\n    -------\n    out: Array\n        Flattened array.\n\n    Examples\n    --------\n    > var arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n    > var out = flattenArray( arr )\n    [ 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n    // Set the maximum depth:\n    > arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n    > out = flattenArray( arr, { 'depth': 2 } )\n    [ 1, 2, 3, [ 4, [ 5 ], 6 ], 7, 8, 9 ]\n    > var bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n    true\n\n    // Deep copy:\n    > arr = [ 1, [ 2, [ 3, [ 4, [ 5 ], 6 ], 7 ], 8 ], 9 ];\n    > out = flattenArray( arr, { 'depth': 2, 'copy': true } )\n    [ 1, 2, 3, [ 4, [ 5 ], 6 ], 7, 8, 9 ]\n    > bool = ( arr[ 1 ][ 1 ][ 1 ] === out[ 3 ] )\n    false\n\n\nflattenArray.factory( dims[, options] )\n    Returns a function for flattening arrays having specified dimensions.\n\n    The returned function does not validate that input arrays actually have the\n    specified dimensions.\n\n    Parameters\n    ----------\n    dims: ArrayLike<integer>\n        Dimensions.\n\n    options: Object (optional)\n        Options.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to deep copy array elements. Default: false.\n\n    Returns\n    -------\n    fcn: Function\n        Flatten function.\n\n    Examples\n    --------\n    > var flatten = flattenArray.factory( [ 2, 2 ], {\n    ...     'copy': false\n    ... });\n    > var out = flatten( [ [ 1, 2 ], [ 3, 4 ] ] )\n    [ 1, 2, 3, 4 ]\n    > out = flatten( [ [ 5, 6 ], [ 7, 8 ] ] )\n    [ 5, 6, 7, 8 ]\n\n    See Also\n    --------\n    flattenObject\n","flattenArray.factory":"\nflattenArray.factory( dims[, options] )\n    Returns a function for flattening arrays having specified dimensions.\n\n    The returned function does not validate that input arrays actually have the\n    specified dimensions.\n\n    Parameters\n    ----------\n    dims: ArrayLike<integer>\n        Dimensions.\n\n    options: Object (optional)\n        Options.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to deep copy array elements. Default: false.\n\n    Returns\n    -------\n    fcn: Function\n        Flatten function.\n\n    Examples\n    --------\n    > var flatten = flattenArray.factory( [ 2, 2 ], {\n    ...     'copy': false\n    ... });\n    > var out = flatten( [ [ 1, 2 ], [ 3, 4 ] ] )\n    [ 1, 2, 3, 4 ]\n    > out = flatten( [ [ 5, 6 ], [ 7, 8 ] ] )\n    [ 5, 6, 7, 8 ]\n\n    See Also\n    --------\n    flattenObject","flattenObject":"\nflattenObject( obj[, options] )\n    Flattens an object.\n\n    Parameters\n    ----------\n    obj: ObjectLike\n        Object to flatten.\n\n    options: Object (optional)\n        Options.\n\n    options.depth: integer (optional)\n        Maximum depth to flatten.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to deep copy. Default: false.\n\n    options.flattenArrays: boolean (optional)\n        Boolean indicating whether to flatten arrays. Default: false.\n\n    options.delimiter: string (optional)\n        Key path delimiter. Default: '.'.\n\n    Returns\n    -------\n    out: ObjectLike\n        Flattened object.\n\n    Examples\n    --------\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var out = flattenObject( obj )\n    { 'a.b.c': 'd' }\n\n    // Set the `depth` option to flatten to a specified depth:\n    > obj = { 'a': { 'b': { 'c': 'd' } } };\n    > out = flattenObject( obj, { 'depth': 1 } )\n    { 'a.b': { 'c': 'd' } }\n    > var bool = ( obj.a.b === out[ 'a.b' ] )\n    true\n\n    // Set the `delimiter` option:\n    > obj = { 'a': { 'b': { 'c': 'd' } } };\n    > out = flattenObject( obj, { 'delimiter': '-|-' } )\n    { 'a-|-b-|-c': 'd' }\n\n    // Flatten arrays:\n    > obj = { 'a': { 'b': [ 1, 2, 3 ] } };\n    > out = flattenObject( obj, { 'flattenArrays': true } )\n    { 'a.b.0': 1, 'a.b.1': 2, 'a.b.2': 3 }\n\n\nflattenObject.factory( [options] )\n    Returns a function to flatten an object.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.depth: integer (optional)\n        Maximum depth to flatten.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to deep copy. Default: false.\n\n    options.flattenArrays: boolean (optional)\n        Boolean indicating whether to flatten arrays. Default: false.\n\n    options.delimiter: string (optional)\n        Key path delimiter. Default: '.'.\n\n    Returns\n    -------\n    fcn: Function\n        Flatten function.\n\n    Examples\n    --------\n    > var flatten = flattenObject.factory({\n    ...     'depth': 1,\n    ...     'copy': true,\n    ...     'delimiter': '|'\n    ... });\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var out = flatten( obj )\n    { 'a|b': { 'c': 'd' } }\n\n    See Also\n    --------\n    flattenArray\n","flattenObject.factory":"\nflattenObject.factory( [options] )\n    Returns a function to flatten an object.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.depth: integer (optional)\n        Maximum depth to flatten.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to deep copy. Default: false.\n\n    options.flattenArrays: boolean (optional)\n        Boolean indicating whether to flatten arrays. Default: false.\n\n    options.delimiter: string (optional)\n        Key path delimiter. Default: '.'.\n\n    Returns\n    -------\n    fcn: Function\n        Flatten function.\n\n    Examples\n    --------\n    > var flatten = flattenObject.factory({\n    ...     'depth': 1,\n    ...     'copy': true,\n    ...     'delimiter': '|'\n    ... });\n    > var obj = { 'a': { 'b': { 'c': 'd' } } };\n    > var out = flatten( obj )\n    { 'a|b': { 'c': 'd' } }\n\n    See Also\n    --------\n    flattenArray","flignerTest":"\nflignerTest( ...x[, options] )\n    Computes the Fligner-Killeen test for equal variances.\n\n    Parameters\n    ----------\n    x: ...Array\n        Measured values.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.groups: Array (optional)\n        Array of group indicators.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.method: string\n        Name of test.\n\n    out.df: Object\n        Degrees of freedom.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    // Data from Hollander & Wolfe (1973), p. 116:\n    > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n    > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n    > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n    > var out = flignerTest( x, y, z )\n\n    > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n    ...     3.8, 2.7, 4.0, 2.4,\n    ...     2.8, 3.4, 3.7, 2.2, 2.0\n    ... ];\n    > var groups = [\n    ...     'a', 'a', 'a', 'a', 'a',\n    ...     'b', 'b', 'b', 'b',\n    ...     'c', 'c', 'c', 'c', 'c'\n    ... ];\n    > out = flignerTest( arr, { 'groups': groups } )\n\n    See Also\n    --------\n    bartlettTest\n","FLOAT_WORD_ORDER":"\nFLOAT_WORD_ORDER\n    Platform float word order.\n\n    Possible values:\n\n    - 'little-endian'\n    - 'big-endian'\n    - 'unknown'\n\n    Examples\n    --------\n    > FLOAT_WORD_ORDER\n    <string>\n\n    See Also\n    --------\n    BYTE_ORDER\n","FLOAT16_CBRT_EPS":"\nFLOAT16_CBRT_EPS\n    Cube root of half-precision floating-point epsilon.\n\n    Examples\n    --------\n    > FLOAT16_CBRT_EPS\n    0.09921256574801247\n\n    See Also\n    --------\n    FLOAT16_EPS, FLOAT16_SQRT_EPS, FLOAT32_CBRT_EPS, CBRT_EPS\n","FLOAT16_EPS":"\nFLOAT16_EPS\n    Difference between one and the smallest value greater than one that can be\n    represented as a half-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT16_EPS\n    0.0009765625\n\n    See Also\n    --------\n    FLOAT32_EPS, EPS\n","FLOAT16_EXPONENT_BIAS":"\nFLOAT16_EXPONENT_BIAS\n    The bias of a half-precision floating-point number's exponent.\n\n    Examples\n    --------\n    > FLOAT16_EXPONENT_BIAS\n    15\n\n    See Also\n    --------\n    FLOAT32_EXPONENT_BIAS, FLOAT64_EXPONENT_BIAS\n","FLOAT16_MAX":"\nFLOAT16_MAX\n    Maximum half-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT16_MAX\n    65504.0\n\n    See Also\n    --------\n    FLOAT32_MAX, FLOAT64_MAX\n","FLOAT16_MAX_SAFE_INTEGER":"\nFLOAT16_MAX_SAFE_INTEGER\n    Maximum safe half-precision floating-point integer.\n\n    The maximum safe half-precision floating-point integer is given by\n    `2^11 - 1`.\n\n    Examples\n    --------\n    > FLOAT16_MAX_SAFE_INTEGER\n    2047\n\n    See Also\n    --------\n    FLOAT16_MIN_SAFE_INTEGER, FLOAT32_MAX_SAFE_INTEGER, FLOAT64_MAX_SAFE_INTEGER\n","FLOAT16_MIN_SAFE_INTEGER":"\nFLOAT16_MIN_SAFE_INTEGER\n    Minimum safe half-precision floating-point integer.\n\n    The minimum safe half-precision floating-point integer is given by\n    `-(2^11 - 1)`.\n\n    Examples\n    --------\n    > FLOAT16_MIN_SAFE_INTEGER\n    -2047\n\n    See Also\n    --------\n    FLOAT16_MAX_SAFE_INTEGER, FLOAT32_MIN_SAFE_INTEGER, FLOAT64_MIN_SAFE_INTEGER\n","FLOAT16_NINF":"\nFLOAT16_NINF\n    Half-precision floating-point negative infinity.\n\n    Examples\n    --------\n    > FLOAT16_NINF\n    -Infinity\n\n    See Also\n    --------\n    FLOAT16_PINF, FLOAT32_NINF, NINF\n","FLOAT16_NUM_BYTES":"\nFLOAT16_NUM_BYTES\n    Size (in bytes) of a half-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT16_NUM_BYTES\n    2\n\n    See Also\n    --------\n    FLOAT32_NUM_BYTES, FLOAT64_NUM_BYTES\n","FLOAT16_PINF":"\nFLOAT16_PINF\n    Half-precision floating-point positive infinity.\n\n    Examples\n    --------\n    > FLOAT16_PINF\n    Infinity\n\n    See Also\n    --------\n    FLOAT16_NINF, FLOAT32_PINF, PINF\n","FLOAT16_PRECISION":"\nFLOAT16_PRECISION\n    Effective number of bits in the significand of a half-precision floating-\n    point number.\n\n    The effective number of bits is `10` significand bits plus `1` hidden bit.\n\n    Examples\n    --------\n    > FLOAT16_PRECISION\n    11\n\n    See Also\n    --------\n    FLOAT32_PRECISION, FLOAT64_PRECISION\n","FLOAT16_SMALLEST_NORMAL":"\nFLOAT16_SMALLEST_NORMAL\n    Smallest positive normalized half-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT16_SMALLEST_NORMAL\n    6.103515625e-5\n\n    See Also\n    --------\n    FLOAT16_SMALLEST_SUBNORMAL, FLOAT32_SMALLEST_NORMAL, FLOAT64_SMALLEST_NORMAL\n","FLOAT16_SMALLEST_SUBNORMAL":"\nFLOAT16_SMALLEST_SUBNORMAL\n    Smallest positive denormalized half-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT16_SMALLEST_SUBNORMAL\n    5.960464477539063e-8\n\n    See Also\n    --------\n    FLOAT16_SMALLEST_NORMAL, FLOAT32_SMALLEST_SUBNORMAL, FLOAT64_SMALLEST_SUBNORMAL\n","FLOAT16_SQRT_EPS":"\nFLOAT16_SQRT_EPS\n    Square root of half-precision floating-point epsilon.\n\n    Examples\n    --------\n    > FLOAT16_SQRT_EPS\n    0.03125\n\n    See Also\n    --------\n    FLOAT16_EPS, FLOAT32_SQRT_EPS, SQRT_EPS\n","FLOAT32_ABS_MASK":"\nFLOAT32_ABS_MASK\n    Mask for excluding the sign bit of a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_ABS_MASK\n    2147483647\n    > base.toBinaryStringUint32( FLOAT32_ABS_MASK )\n    '01111111111111111111111111111111'\n\n    See Also\n    --------\n    FLOAT32_EXPONENT_MASK, FLOAT32_SIGN_MASK, FLOAT32_SIGNIFICAND_MASK\n","FLOAT32_CBRT_EPS":"\nFLOAT32_CBRT_EPS\n    Cube root of single-precision floating-point epsilon.\n\n    Examples\n    --------\n    > FLOAT32_CBRT_EPS\n    0.004921566694974899\n\n    See Also\n    --------\n    FLOAT32_EPS, FLOAT32_SQRT_EPS, CBRT_EPS\n","FLOAT32_E":"\nFLOAT32_E\n    Euler's number.\n\n    Examples\n    --------\n    > FLOAT32_E\n    2.7182817459106445\n\n    See Also\n    --------\n    E\n","FLOAT32_EPS":"\nFLOAT32_EPS\n    Difference between one and the smallest value greater than one that can be\n    represented as a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_EPS\n    1.1920928955078125e-7\n\n    See Also\n    --------\n    EPS\n","FLOAT32_EXPONENT_BIAS":"\nFLOAT32_EXPONENT_BIAS\n    The bias of a single-precision floating-point number's exponent.\n\n    Examples\n    --------\n    > FLOAT32_EXPONENT_BIAS\n    127\n\n    See Also\n    --------\n    FLOAT16_EXPONENT_BIAS, FLOAT64_EXPONENT_BIAS\n","FLOAT32_EXPONENT_MASK":"\nFLOAT32_EXPONENT_MASK\n    Mask for the exponent of a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_EXPONENT_MASK\n    2139095040\n    > base.toBinaryStringUint32( FLOAT32_EXPONENT_MASK )\n    '01111111100000000000000000000000'\n\n    See Also\n    --------\n    FLOAT32_SIGN_MASK, FLOAT32_SIGNIFICAND_MASK, FLOAT32_ABS_MASK\n","FLOAT32_FOURTH_PI":"\nFLOAT32_FOURTH_PI\n    One fourth times the mathematical constant `π`.\n\n    Examples\n    --------\n    > FLOAT32_FOURTH_PI\n    7.853981852531433e-1\n\n    See Also\n    --------\n    FLOAT32_HALF_PI, FLOAT32_PI, FLOAT32_TWO_PI\n","FLOAT32_HALF_LN_TWO":"\nFLOAT32_HALF_LN_TWO\n    One half times the natural logarithm of 2 as a single-precision\n    floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_HALF_LN_TWO\n    0.3465735912322998\n\n    See Also\n    --------\n    HALF_LN2\n","FLOAT32_HALF_PI":"\nFLOAT32_HALF_PI\n    One half times the mathematical constant `π`.\n\n    Examples\n    --------\n    > FLOAT32_HALF_PI\n    1.5707963705062866\n\n    See Also\n    --------\n    FLOAT32_FOURTH_PI, FLOAT32_PI, FLOAT32_TWO_PI\n","FLOAT32_LN_HALF":"\nFLOAT32_LN_HALF\n    Natural logarithm of `1/2` as a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_LN_HALF\n    -0.6931471824645996\n\n    See Also\n    --------\n    LN_HALF\n","FLOAT32_LN_PI":"\nFLOAT32_LN_PI\n    Natural logarithm of the mathematical constant `π` as a single-precision\n    floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_LN_PI\n    1.1447298526763916\n\n    See Also\n    --------\n    FLOAT32_PI, LN_PI\n","FLOAT32_LN_TEN":"\nFLOAT32_LN_TEN\n    Natural logarithm of `10` as a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_LN_TEN\n     2.3025851249694824\n\n    See Also\n    --------\n    FLOAT32_LN_TWO, LN10\n","FLOAT32_LN_TWO":"\nFLOAT32_LN_TWO\n    Natural logarithm of `2` as a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_LN_TWO\n    0.6931471824645996\n\n    See Also\n    --------\n    FLOAT32_LN_TEN, LN2\n","FLOAT32_MAX":"\nFLOAT32_MAX\n    Maximum single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_MAX\n    3.4028234663852886e+38\n\n    See Also\n    --------\n    FLOAT16_MAX, FLOAT64_MAX\n","FLOAT32_MAX_BASE2_EXPONENT":"\nFLOAT32_MAX_BASE2_EXPONENT\n    The maximum biased base 2 exponent for a single-precision floating-point\n    number.\n\n    Examples\n    --------\n    > FLOAT32_MAX_BASE2_EXPONENT\n    127\n\n    See Also\n    --------\n    FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE2_EXPONENT\n","FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL\n    The maximum biased base 2 exponent for a subnormal single-precision\n    floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL\n    -127\n\n    See Also\n    --------\n    FLOAT32_MAX_BASE2_EXPONENT, FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n","FLOAT32_MAX_BASE10_EXPONENT":"\nFLOAT32_MAX_BASE10_EXPONENT\n    The maximum base 10 exponent for a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_MAX_BASE10_EXPONENT\n    38\n\n    See Also\n    --------\n    FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE10_EXPONENT\n","FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL\n    The maximum base 10 exponent for a subnormal single-precision floating-point\n    number.\n\n    Examples\n    --------\n    > FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL\n    -38\n\n    See Also\n    --------\n    FLOAT32_MAX_BASE10_EXPONENT, FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n","FLOAT32_MAX_SAFE_FIBONACCI":"\nFLOAT32_MAX_SAFE_FIBONACCI\n    Maximum safe Fibonacci number when stored in single-precision floating-point\n    format.\n\n    Examples\n    --------\n    > FLOAT32_MAX_SAFE_FIBONACCI\n    14930352\n\n    See Also\n    --------\n    FLOAT64_MAX_SAFE_FIBONACCI\n","FLOAT32_MAX_SAFE_INTEGER":"\nFLOAT32_MAX_SAFE_INTEGER\n    Maximum safe single-precision floating-point integer.\n\n    The maximum safe single-precision floating-point integer is given by\n    `2^24 - 1`.\n\n    Examples\n    --------\n    > FLOAT32_MAX_SAFE_INTEGER\n    16777215\n\n    See Also\n    --------\n    FLOAT16_MAX_SAFE_INTEGER, FLOAT32_MIN_SAFE_INTEGER, FLOAT64_MAX_SAFE_INTEGER\n","FLOAT32_MAX_SAFE_NTH_FACTORIAL":"\nFLOAT32_MAX_SAFE_NTH_FACTORIAL\n    Maximum safe nth factorial when stored in single-precision floating-\n    point format.\n\n    Examples\n    --------\n    > FLOAT32_MAX_SAFE_NTH_FACTORIAL\n    34\n\n","FLOAT32_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT32_MAX_SAFE_NTH_FIBONACCI\n    Maximum safe nth Fibonacci number when stored in single-precision floating-\n    point format.\n\n    Examples\n    --------\n    > FLOAT32_MAX_SAFE_NTH_FIBONACCI\n    36\n\n    See Also\n    --------\n    FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT32_MAX_SAFE_NTH_LUCAS":"\nFLOAT32_MAX_SAFE_NTH_LUCAS\n    Maximum safe nth Lucas number when stored in single-precision floating-point\n    format.\n\n    Examples\n    --------\n    > FLOAT32_MAX_SAFE_NTH_LUCAS\n    34\n\n    See Also\n    --------\n    FLOAT64_MAX_SAFE_NTH_LUCAS\n","FLOAT32_MIN_BASE2_EXPONENT":"\nFLOAT32_MIN_BASE2_EXPONENT\n    The minimum biased base 2 exponent for a normalized single-precision\n    floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_MIN_BASE2_EXPONENT\n    -126\n\n    See Also\n    --------\n    FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL\n    The minimum biased base 2 exponent for a subnormal single-precision\n    floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL\n    -149\n\n    See Also\n    --------\n    FLOAT32_MIN_BASE2_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT32_MIN_BASE10_EXPONENT":"\nFLOAT32_MIN_BASE10_EXPONENT\n    The minimum base 10 exponent for a normal single-precision floating-\n    point number.\n\n    Examples\n    --------\n    > FLOAT32_MIN_BASE10_EXPONENT\n    -37\n\n    See Also\n    --------\n    FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT\n","FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL\n    The minimum base 10 exponent for a subnormal single-precision floating-\n    point number.\n\n    Examples\n    --------\n    > FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL\n    -45\n\n    See Also\n    --------\n    FLOAT32_MIN_BASE10_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT32_MIN_SAFE_INTEGER":"\nFLOAT32_MIN_SAFE_INTEGER\n    Minimum safe single-precision floating-point integer.\n\n    The minimum safe single-precision floating-point integer is given by\n    `-(2^24 - 1)`.\n\n    Examples\n    --------\n    > FLOAT32_MIN_SAFE_INTEGER\n    -16777215\n\n    See Also\n    --------\n    FLOAT16_MIN_SAFE_INTEGER, FLOAT32_MAX_SAFE_INTEGER, FLOAT64_MIN_SAFE_INTEGER\n","FLOAT32_NAN":"\nFLOAT32_NAN\n    Single-precision floating-point NaN.\n\n    Examples\n    --------\n    > FLOAT32_NAN\n    NaN\n\n    See Also\n    --------\n    NAN\n","FLOAT32_NINF":"\nFLOAT32_NINF\n    Single-precision floating-point negative infinity.\n\n    Examples\n    --------\n    > FLOAT32_NINF\n    -Infinity\n\n    See Also\n    --------\n    FLOAT32_PINF, NINF\n","FLOAT32_NUM_BYTES":"\nFLOAT32_NUM_BYTES\n    Size (in bytes) of a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_NUM_BYTES\n    4\n\n    See Also\n    --------\n    FLOAT16_NUM_BYTES, FLOAT64_NUM_BYTES\n","FLOAT32_PHI":"\nFLOAT32_PHI\n    Golden ratio.\n\n    Examples\n    --------\n    > FLOAT32_PHI\n    1.6180340051651\n\n    See Also\n    --------\n    PHI\n","FLOAT32_PI":"\nFLOAT32_PI\n    The mathematical constant `π`.\n\n    Examples\n    --------\n    > FLOAT32_PI\n    3.1415927410125732\n\n    See Also\n    --------\n    FLOAT32_FOURTH_PI, FLOAT32_HALF_PI, FLOAT32_TWO_PI\n","FLOAT32_PINF":"\nFLOAT32_PINF\n    Single-precision floating-point positive infinity.\n\n    Examples\n    --------\n    > FLOAT32_PINF\n    Infinity\n\n    See Also\n    --------\n    FLOAT32_NINF, PINF\n","FLOAT32_PRECISION":"\nFLOAT32_PRECISION\n    Effective number of bits in the significand of a single-precision floating-\n    point number.\n\n    The effective number of bits is `23` significand bits plus `1` hidden bit.\n\n    Examples\n    --------\n    > FLOAT32_PRECISION\n    24\n\n    See Also\n    --------\n    FLOAT16_PRECISION, FLOAT64_PRECISION\n","FLOAT32_SIGN_MASK":"\nFLOAT32_SIGN_MASK\n    Mask for the sign bit of a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_SIGN_MASK\n    2147483648\n    > base.toBinaryStringUint32( FLOAT32_SIGN_MASK )\n    '10000000000000000000000000000000'\n\n    See Also\n    --------\n    FLOAT32_EXPONENT_MASK, FLOAT32_SIGNIFICAND_MASK, FLOAT32_ABS_MASK\n","FLOAT32_SIGNIFICAND_MASK":"\nFLOAT32_SIGNIFICAND_MASK\n    Mask for the significand of a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_SIGNIFICAND_MASK\n    8388607\n    > base.toBinaryStringUint32( FLOAT32_SIGNIFICAND_MASK )\n    '00000000011111111111111111111111'\n\n    See Also\n    --------\n    FLOAT32_EXPONENT_MASK, FLOAT32_SIGN_MASK, FLOAT32_ABS_MASK\n","FLOAT32_SMALLEST_NORMAL":"\nFLOAT32_SMALLEST_NORMAL\n    Smallest positive normalized single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_SMALLEST_NORMAL\n    1.1754943508222875e-38\n\n    See Also\n    --------\n    FLOAT32_SMALLEST_SUBNORMAL, FLOAT64_SMALLEST_NORMAL\n","FLOAT32_SMALLEST_SUBNORMAL":"\nFLOAT32_SMALLEST_SUBNORMAL\n    Smallest positive denormalized single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_SMALLEST_SUBNORMAL\n    1.401298464324817e-45\n\n    See Also\n    --------\n    FLOAT32_SMALLEST_NORMAL, FLOAT64_SMALLEST_SUBNORMAL\n","FLOAT32_SQRT_EPS":"\nFLOAT32_SQRT_EPS\n    Square root of single-precision floating-point epsilon.\n\n    Examples\n    --------\n    > FLOAT32_SQRT_EPS\n    0.0003452669770922512\n\n    See Also\n    --------\n    FLOAT32_EPS, SQRT_EPS\n","FLOAT32_SQRT_HALF":"\nFLOAT32_SQRT_HALF\n    Square root of `1/2` as a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_SQRT_HALF\n    0.7071067690849304\n\n    See Also\n    --------\n    SQRT_HALF\n","FLOAT32_SQRT_HALF_PI":"\nFLOAT32_SQRT_HALF_PI\n    Square root of `π` divided by `2` as a single-precision \n    floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_SQRT_HALF_PI\n    1.2533141374588013\n\n    See Also\n    --------\n    SQRT_HALF_PI","FLOAT32_SQRT_PHI":"\nFLOAT32_SQRT_PHI\n    Square root of the golden ratio as a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_SQRT_PHI\n    1.272019624710083\n\n    See Also\n    --------\n    SQRT_PHI\n","FLOAT32_SQRT_PI":"\nFLOAT32_SQRT_PI\n    Square root of the mathematical constant `π` as a single-precision\n    floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_SQRT_PI\n    1.7724539041519165\n\n    See Also\n    --------\n    FLOAT32_PI, SQRT_PI\n","FLOAT32_SQRT_THREE":"\nFLOAT32_SQRT_THREE\n    Square root of `3` as a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_SQRT_THREE\n    1.7320507764816284\n\n    See Also\n    --------\n    FLOAT32_SQRT_TWO, SQRT_THREE\n","FLOAT32_SQRT_TWO":"\nFLOAT32_SQRT_TWO\n    Square root of `2` as a single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_SQRT_TWO\n    1.4142135381698608\n\n    See Also\n    --------\n    FLOAT32_SQRT_THREE, SQRT_TWO\n","FLOAT32_SQRT_TWO_PI":"\nFLOAT32_SQRT_TWO_PI\n    Square root of the `π` times `2` as single-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT32_SQRT_TWO_PI\n    2.5066282749176025\n\n    See Also\n    --------\n    FLOAT32_PI, FLOAT32_TWO_PI, SQRT_TWO_PI\n","FLOAT32_TWO_PI":"\nFLOAT32_TWO_PI\n    The mathematical constant `π` times `2`.\n\n    Examples\n    --------\n    > FLOAT32_TWO_PI\n    6.2831854820251465\n\n    See Also\n    --------\n    FLOAT32_FOURTH_PI, FLOAT32_HALF_PI, FLOAT32_PI\n","Float32Array":"\nFloat32Array()\n    A typed array constructor which returns a typed array representing an array\n    of single-precision floating-point numbers in the platform byte order.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Float32Array()\n    <Float32Array>\n\n\nFloat32Array( length )\n    Returns a typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( 5 )\n    <Float32Array>[ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat32Array( typedarray )\n    Creates a typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float64Array( [ 0.5, 0.5, 0.5 ] );\n    > var arr2 = new Float32Array( arr1 )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]\n\n\nFloat32Array( obj )\n    Creates a typed array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a typed array.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 0.5, 0.5, 0.5 ];\n    > var arr2 = new Float32Array( arr1 )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]\n\n\nFloat32Array( buffer[, byteOffset[, length]] )\n    Returns a typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 16 );\n    > var arr = new Float32Array( buf, 0, 4 )\n    <Float32Array>[ 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat32Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2.0; };\n    > var arr = Float32Array.from( [ 1.0, -1.0 ], mapFcn )\n    <Float32Array>[ 2.0, -2.0 ]\n\n\nFloat32Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Float32Array.of( 2.0, -2.0 )\n    <Float32Array>[ 2.0, -2.0 ]\n\n\nFloat32Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Float32Array.BYTES_PER_ELEMENT\n    4\n\n\nFloat32Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Float32Array.name\n    'Float32Array'\n\n\nFloat32Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>\n\n\nFloat32Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( 5 );\n    > arr.byteLength\n    20\n\n\nFloat32Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Float32Array( 5 );\n    > arr.byteOffset\n    0\n\n\nFloat32Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Float32Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    4\n\n\nFloat32Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Float32Array( 5 );\n    > arr.length\n    5\n\n\nFloat32Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Float32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    2.0\n    > arr[ 4 ]\n    -2.0\n\n\nFloat32Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1.0 ]\n    > it.next().value\n    [ 1, -1.0 ]\n    > it.next().done\n    true\n\n\nFloat32Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > function predicate( v ) { return ( v >= 0.0 ); };\n    > arr.every( predicate )\n    false\n\n\nFloat32Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Float32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > arr.fill( 2.0 );\n    > arr[ 0 ]\n    2.0\n    > arr[ 1 ]\n    2.0\n\n\nFloat32Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v >= 0.0 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2\n\n\nFloat32Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > var v = arr.find( predicate )\n    -1.0\n\n\nFloat32Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > var idx = arr.findIndex( predicate )\n    2\n\n\nFloat32Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:1 1:0 2:-1 '\n\n\nFloat32Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > var bool = arr.includes( 2.0 )\n    false\n    > bool = arr.includes( -1.0 )\n    true\n\n\nFloat32Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > var idx = arr.indexOf( 2.0 )\n    -1\n    > idx = arr.indexOf( -1.0 )\n    2\n\n\nFloat32Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > arr.join( '|' )\n    '1|0|-1'\n\n\nFloat32Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true\n\n\nFloat32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n    > var idx = arr.lastIndexOf( 2.0 )\n    -1\n    > idx = arr.lastIndexOf( 0.0 )\n    3\n\n\nFloat32Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( v ) { return v * 2.0; };\n    > var arr2 = arr1.map( fcn )\n    <Float32Array>[ 2.0, 0.0, -2.0 ]\n\n\nFloat32Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0.0 )\n    2.0\n\n\nFloat32Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0.0 )\n    2.0\n\n\nFloat32Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Float32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] )\n    <Float32Array>\n    > arr.reverse()\n    <Float32Array>[ -1.0, 0.0, 1.0 ]\n\n\nFloat32Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > arr.set( [ -2.0, 2.0 ], 1 );\n    > arr[ 1 ]\n    -2.0\n    > arr[ 2 ]\n    2.0\n\n\nFloat32Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    0.0\n    > arr2[ 1 ]\n    -1.0\n\n\nFloat32Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > arr.some( predicate )\n    true\n\n\nFloat32Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Float32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n    > arr.sort()\n    <Float32Array>[ -2.0, -1.0, 0.0, 1.0, 2.0 ]\n\n\nFloat32Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Float32Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Float32Array>[ 0.0, 2.0, -2.0 ]\n\n\nFloat32Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n    > arr.toLocaleString()\n    '1,-1,0'\n\n\nFloat32Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n    > arr.toString()\n    '1,-1,0'\n\n\nFloat32Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > it = arr.values();\n    > it.next().value\n    1.0\n    > it.next().value\n    -1.0\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Float32Array.from":"\nFloat32Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2.0; };\n    > var arr = Float32Array.from( [ 1.0, -1.0 ], mapFcn )\n    <Float32Array>[ 2.0, -2.0 ]","Float32Array.of":"\nFloat32Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Float32Array.of( 2.0, -2.0 )\n    <Float32Array>[ 2.0, -2.0 ]","Float32Array.BYTES_PER_ELEMENT":"\nFloat32Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Float32Array.BYTES_PER_ELEMENT\n    4","Float32Array.name":"\nFloat32Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Float32Array.name\n    'Float32Array'","Float32Array.prototype.buffer":"\nFloat32Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>","Float32Array.prototype.byteLength":"\nFloat32Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( 5 );\n    > arr.byteLength\n    20","Float32Array.prototype.byteOffset":"\nFloat32Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Float32Array( 5 );\n    > arr.byteOffset\n    0","Float32Array.prototype.BYTES_PER_ELEMENT":"\nFloat32Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Float32Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    4","Float32Array.prototype.length":"\nFloat32Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Float32Array( 5 );\n    > arr.length\n    5","Float32Array.prototype.copyWithin":"\nFloat32Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Float32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    2.0\n    > arr[ 4 ]\n    -2.0","Float32Array.prototype.entries":"\nFloat32Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1.0 ]\n    > it.next().value\n    [ 1, -1.0 ]\n    > it.next().done\n    true","Float32Array.prototype.every":"\nFloat32Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > function predicate( v ) { return ( v >= 0.0 ); };\n    > arr.every( predicate )\n    false","Float32Array.prototype.fill":"\nFloat32Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Float32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > arr.fill( 2.0 );\n    > arr[ 0 ]\n    2.0\n    > arr[ 1 ]\n    2.0","Float32Array.prototype.filter":"\nFloat32Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v >= 0.0 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2","Float32Array.prototype.find":"\nFloat32Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > var v = arr.find( predicate )\n    -1.0","Float32Array.prototype.findIndex":"\nFloat32Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > var idx = arr.findIndex( predicate )\n    2","Float32Array.prototype.forEach":"\nFloat32Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:1 1:0 2:-1 '","Float32Array.prototype.includes":"\nFloat32Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > var bool = arr.includes( 2.0 )\n    false\n    > bool = arr.includes( -1.0 )\n    true","Float32Array.prototype.indexOf":"\nFloat32Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > var idx = arr.indexOf( 2.0 )\n    -1\n    > idx = arr.indexOf( -1.0 )\n    2","Float32Array.prototype.join":"\nFloat32Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > arr.join( '|' )\n    '1|0|-1'","Float32Array.prototype.keys":"\nFloat32Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true","Float32Array.prototype.lastIndexOf":"\nFloat32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n    > var idx = arr.lastIndexOf( 2.0 )\n    -1\n    > idx = arr.lastIndexOf( 0.0 )\n    3","Float32Array.prototype.map":"\nFloat32Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( v ) { return v * 2.0; };\n    > var arr2 = arr1.map( fcn )\n    <Float32Array>[ 2.0, 0.0, -2.0 ]","Float32Array.prototype.reduce":"\nFloat32Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0.0 )\n    2.0","Float32Array.prototype.reduceRight":"\nFloat32Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0.0 )\n    2.0","Float32Array.prototype.reverse":"\nFloat32Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Float32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] )\n    <Float32Array>\n    > arr.reverse()\n    <Float32Array>[ -1.0, 0.0, 1.0 ]","Float32Array.prototype.set":"\nFloat32Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > arr.set( [ -2.0, 2.0 ], 1 );\n    > arr[ 1 ]\n    -2.0\n    > arr[ 2 ]\n    2.0","Float32Array.prototype.slice":"\nFloat32Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Float32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float32Array( [ 1.0, 0.0, -1.0 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    0.0\n    > arr2[ 1 ]\n    -1.0","Float32Array.prototype.some":"\nFloat32Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > arr.some( predicate )\n    true","Float32Array.prototype.sort":"\nFloat32Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Float32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n    > arr.sort()\n    <Float32Array>[ -2.0, -1.0, 0.0, 1.0, 2.0 ]","Float32Array.prototype.subarray":"\nFloat32Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Float32Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Float32Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Float32Array>[ 0.0, 2.0, -2.0 ]","Float32Array.prototype.toLocaleString":"\nFloat32Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n    > arr.toLocaleString()\n    '1,-1,0'","Float32Array.prototype.toString":"\nFloat32Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0, 0.0 ] );\n    > arr.toString()\n    '1,-1,0'","Float32Array.prototype.values":"\nFloat32Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Float32Array( [ 1.0, -1.0 ] );\n    > it = arr.values();\n    > it.next().value\n    1.0\n    > it.next().value\n    -1.0\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","FLOAT64_EXPONENT_BIAS":"\nFLOAT64_EXPONENT_BIAS\n    The bias of a double-precision floating-point number's exponent.\n\n    Examples\n    --------\n    > FLOAT64_EXPONENT_BIAS\n    1023\n\n    See Also\n    --------\n    FLOAT16_EXPONENT_BIAS, FLOAT32_EXPONENT_BIAS\n","FLOAT64_HIGH_WORD_ABS_MASK":"\nFLOAT64_HIGH_WORD_ABS_MASK\n    High word mask for excluding the sign bit of a double-precision floating-\n    point number.\n\n    Examples\n    --------\n    > FLOAT64_HIGH_WORD_ABS_MASK\n    2147483647\n    > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_ABS_MASK )\n    '01111111111111111111111111111111'\n\n    See Also\n    --------\n    FLOAT64_HIGH_WORD_SIGN_MASK, FLOAT64_HIGH_WORD_EXPONENT_MASK, FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n","FLOAT64_HIGH_WORD_EXPONENT_MASK":"\nFLOAT64_HIGH_WORD_EXPONENT_MASK\n    High word mask for the exponent of a double-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT64_HIGH_WORD_EXPONENT_MASK\n    2146435072\n    > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_EXPONENT_MASK )\n    '01111111111100000000000000000000'\n\n    See Also\n    --------\n    FLOAT64_HIGH_WORD_SIGNIFICAND_MASK, FLOAT64_HIGH_WORD_SIGN_MASK, FLOAT64_HIGH_WORD_ABS_MASK\n","FLOAT64_HIGH_WORD_SIGN_MASK":"\nFLOAT64_HIGH_WORD_SIGN_MASK\n    High word mask for the sign bit of a double-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT64_HIGH_WORD_SIGN_MASK\n    2147483648\n    > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGN_MASK )\n    '10000000000000000000000000000000'\n\n    See Also\n    --------\n    FLOAT64_HIGH_WORD_EXPONENT_MASK, FLOAT64_HIGH_WORD_SIGNIFICAND_MASK, FLOAT64_HIGH_WORD_ABS_MASK\n","FLOAT64_HIGH_WORD_SIGNIFICAND_MASK":"\nFLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n    High word mask for the significand of a double-precision floating-point\n    number.\n\n    Examples\n    --------\n    > FLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n    1048575\n    > base.toBinaryStringUint32( FLOAT64_HIGH_WORD_SIGNIFICAND_MASK )\n    '00000000000011111111111111111111'\n\n    See Also\n    --------\n    FLOAT64_HIGH_WORD_EXPONENT_MASK, FLOAT64_HIGH_WORD_SIGN_MASK, FLOAT64_HIGH_WORD_ABS_MASK\n","FLOAT64_MAX":"\nFLOAT64_MAX\n    Maximum double-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT64_MAX\n    1.7976931348623157e+308\n\n    See Also\n    --------\n    FLOAT16_MAX, FLOAT32_MAX\n","FLOAT64_MAX_BASE2_EXPONENT":"\nFLOAT64_MAX_BASE2_EXPONENT\n    The maximum biased base 2 exponent for a double-precision floating-point\n    number.\n\n    Examples\n    --------\n    > FLOAT64_MAX_BASE2_EXPONENT\n    1023\n\n    See Also\n    --------\n    FLOAT64_MAX_BASE10_EXPONENT, FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n    The maximum biased base 2 exponent for a subnormal double-precision\n    floating-point number.\n\n    Examples\n    --------\n    > FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n    -1023\n\n    See Also\n    --------\n    FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE2_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_BASE10_EXPONENT":"\nFLOAT64_MAX_BASE10_EXPONENT\n    The maximum base 10 exponent for a double-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT64_MAX_BASE10_EXPONENT\n    308\n\n    See Also\n    --------\n    FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MAX_BASE2_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT\n","FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n    The maximum base 10 exponent for a subnormal double-precision floating-point\n    number.\n\n    Examples\n    --------\n    > FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n    -308\n\n    See Also\n    --------\n    FLOAT64_MAX_BASE10_EXPONENT, FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n","FLOAT64_MAX_LN":"\nFLOAT64_MAX_LN\n    Natural logarithm of the maximum double-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT64_MAX_LN\n    709.782712893384\n\n    See Also\n    --------\n    FLOAT64_MIN_LN\n","FLOAT64_MAX_SAFE_FIBONACCI":"\nFLOAT64_MAX_SAFE_FIBONACCI\n    Maximum safe Fibonacci number when stored in double-precision floating-point\n    format.\n\n    Examples\n    --------\n    > FLOAT64_MAX_SAFE_FIBONACCI\n    8944394323791464\n\n    See Also\n    --------\n    FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT64_MAX_SAFE_INTEGER":"\nFLOAT64_MAX_SAFE_INTEGER\n    Maximum safe double-precision floating-point integer.\n\n    The maximum safe double-precision floating-point integer is given by\n    `2^53 - 1`.\n\n    Examples\n    --------\n    > FLOAT64_MAX_SAFE_INTEGER\n    9007199254740991\n\n    See Also\n    --------\n    FLOAT16_MAX_SAFE_INTEGER, FLOAT32_MAX_SAFE_INTEGER, FLOAT64_MIN_SAFE_INTEGER\n","FLOAT64_MAX_SAFE_LUCAS":"\nFLOAT64_MAX_SAFE_LUCAS\n    Maximum safe Lucas number when stored in double-precision floating-point\n    format.\n\n    Examples\n    --------\n    > FLOAT64_MAX_SAFE_LUCAS\n    7639424778862807\n\n    See Also\n    --------\n    FLOAT64_MAX_SAFE_FIBONACCI, FLOAT64_MAX_SAFE_NTH_LUCAS\n","FLOAT64_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT64_MAX_SAFE_NTH_FIBONACCI\n    Maximum safe nth Fibonacci number when stored in double-precision floating-\n    point format.\n\n    Examples\n    --------\n    > FLOAT64_MAX_SAFE_NTH_FIBONACCI\n    78\n\n    See Also\n    --------\n    FLOAT64_MAX_SAFE_FIBONACCI\n","FLOAT64_MAX_SAFE_NTH_LUCAS":"\nFLOAT64_MAX_SAFE_NTH_LUCAS\n    Maximum safe nth Lucas number when stored in double-precision floating-point\n    format.\n\n    Examples\n    --------\n    > FLOAT64_MAX_SAFE_NTH_LUCAS\n    76\n\n    See Also\n    --------\n    FLOAT64_MAX_SAFE_LUCAS, FLOAT64_MAX_SAFE_NTH_FIBONACCI\n","FLOAT64_MIN_BASE2_EXPONENT":"\nFLOAT64_MIN_BASE2_EXPONENT\n    The minimum biased base 2 exponent for a normalized double-precision\n    floating-point number.\n\n    Examples\n    --------\n    > FLOAT64_MIN_BASE2_EXPONENT\n    -1022\n\n    See Also\n    --------\n    FLOAT64_MAX_BASE2_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n    The minimum biased base 2 exponent for a subnormal double-precision\n    floating-point number.\n\n    Examples\n    --------\n    > FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n    -1074\n\n    See Also\n    --------\n    FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MIN_BASE10_EXPONENT":"\nFLOAT64_MIN_BASE10_EXPONENT\n    The minimum base 10 exponent for a normalized double-precision floating-\n    point number.\n\n    Examples\n    --------\n    > FLOAT64_MIN_BASE10_EXPONENT\n    -308\n\n    See Also\n    --------\n    FLOAT64_MAX_BASE10_EXPONENT, FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE2_EXPONENT\n","FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n    The minimum base 10 exponent for a subnormal double-precision floating-\n    point number.\n\n    Examples\n    --------\n    > FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n    -324\n\n    See Also\n    --------\n    FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL, FLOAT64_MIN_BASE10_EXPONENT, FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n","FLOAT64_MIN_LN":"\nFLOAT64_MIN_LN\n    Natural logarithm of the smallest normalized double-precision floating-point\n    number.\n\n    Examples\n    --------\n    > FLOAT64_MIN_LN\n    -708.3964185322641\n\n    See Also\n    --------\n    FLOAT64_MAX_LN\n","FLOAT64_MIN_SAFE_INTEGER":"\nFLOAT64_MIN_SAFE_INTEGER\n    Minimum safe double-precision floating-point integer.\n\n    The minimum safe double-precision floating-point integer is given by\n    `-(2^53 - 1)`.\n\n    Examples\n    --------\n    > FLOAT64_MIN_SAFE_INTEGER\n    -9007199254740991\n\n    See Also\n    --------\n    FLOAT16_MIN_SAFE_INTEGER, FLOAT32_MIN_SAFE_INTEGER, FLOAT64_MAX_SAFE_INTEGER\n","FLOAT64_NUM_BYTES":"\nFLOAT64_NUM_BYTES\n    Size (in bytes) of a double-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT64_NUM_BYTES\n    8\n\n    See Also\n    --------\n    FLOAT16_NUM_BYTES, FLOAT32_NUM_BYTES\n","FLOAT64_PRECISION":"\nFLOAT64_PRECISION\n    Effective number of bits in the significand of a double-precision floating-\n    point number.\n\n    The effective number of bits is `52` significand bits plus `1` hidden bit.\n\n    Examples\n    --------\n    > FLOAT64_PRECISION\n    53\n\n    See Also\n    --------\n    FLOAT16_PRECISION, FLOAT32_PRECISION\n","FLOAT64_SMALLEST_NORMAL":"\nFLOAT64_SMALLEST_NORMAL\n    Smallest positive normalized double-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT64_SMALLEST_NORMAL\n    2.2250738585072014e-308\n\n    See Also\n    --------\n    FLOAT32_SMALLEST_NORMAL, FLOAT64_SMALLEST_SUBNORMAL\n","FLOAT64_SMALLEST_SUBNORMAL":"\nFLOAT64_SMALLEST_SUBNORMAL\n    Smallest positive denormalized double-precision floating-point number.\n\n    Examples\n    --------\n    > FLOAT64_SMALLEST_SUBNORMAL\n    4.940656458412465e-324\n\n    See Also\n    --------\n    FLOAT32_SMALLEST_SUBNORMAL, FLOAT64_SMALLEST_NORMAL\n","Float64Array":"\nFloat64Array()\n    A typed array constructor which returns a typed array representing an array\n    of double-precision floating-point numbers in the platform byte order.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Float64Array()\n    <Float64Array>\n\n\nFloat64Array( length )\n    Returns a typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 5 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat64Array( typedarray )\n    Creates a typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float32Array( [ 0.5, 0.5, 0.5 ] );\n    > var arr2 = new Float64Array( arr1 )\n    <Float64Array>[ 0.5, 0.5, 0.5 ]\n\n\nFloat64Array( obj )\n    Creates a typed array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a typed array.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 0.5, 0.5, 0.5 ];\n    > var arr2 = new Float64Array( arr1 )\n    <Float64Array>[ 0.5, 0.5, 0.5 ]\n\n\nFloat64Array( buffer[, byteOffset[, length]] )\n    Returns a typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 32 );\n    > var arr = new Float64Array( buf, 0, 4 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 0.0 ]\n\n\nFloat64Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2.0; };\n    > var arr = Float64Array.from( [ 1.0, -1.0 ], mapFcn )\n    <Float64Array>[ 2.0, -2.0 ]\n\n\nFloat64Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Float64Array.of( 2.0, -2.0 )\n    <Float64Array>[ 2.0, -2.0 ]\n\n\nFloat64Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Float64Array.BYTES_PER_ELEMENT\n    8\n\n\nFloat64Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Float64Array.name\n    'Float64Array'\n\n\nFloat64Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>\n\n\nFloat64Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 5 );\n    > arr.byteLength\n    40\n\n\nFloat64Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 5 );\n    > arr.byteOffset\n    0\n\n\nFloat64Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    8\n\n\nFloat64Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 5 );\n    > arr.length\n    5\n\n\nFloat64Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Float64Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    2.0\n    > arr[ 4 ]\n    -2.0\n\n\nFloat64Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1.0 ]\n    > it.next().value\n    [ 1, -1.0 ]\n    > it.next().done\n    true\n\n\nFloat64Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > function predicate( v ) { return ( v >= 0.0 ); };\n    > arr.every( predicate )\n    false\n\n\nFloat64Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Float64Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > arr.fill( 2.0 );\n    > arr[ 0 ]\n    2.0\n    > arr[ 1 ]\n    2.0\n\n\nFloat64Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v >= 0.0 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2\n\n\nFloat64Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > var v = arr.find( predicate )\n    -1.0\n\n\nFloat64Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > var idx = arr.findIndex( predicate )\n    2\n\n\nFloat64Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:1 1:0 2:-1 '\n\n\nFloat64Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > var bool = arr.includes( 2.0 )\n    false\n    > bool = arr.includes( -1.0 )\n    true\n\n\nFloat64Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > var idx = arr.indexOf( 2.0 )\n    -1\n    > idx = arr.indexOf( -1.0 )\n    2\n\n\nFloat64Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > arr.join( '|' )\n    '1|0|-1'\n\n\nFloat64Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true\n\n\nFloat64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n    > var idx = arr.lastIndexOf( 2.0 )\n    -1\n    > idx = arr.lastIndexOf( 0.0 )\n    3\n\n\nFloat64Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( v ) { return v * 2.0; };\n    > var arr2 = arr1.map( fcn )\n    <Float64Array>[ 2.0, 0.0, -2.0 ]\n\n\nFloat64Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0.0 )\n    2.0\n\n\nFloat64Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0.0 )\n    2.0\n\n\nFloat64Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Float64Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] )\n    <Float64Array>\n    > arr.reverse()\n    <Float64Array>[ -1.0, 0.0, 1.0 ]\n\n\nFloat64Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > arr.set( [ -2.0, 2.0 ], 1 );\n    > arr[ 1 ]\n    -2.0\n    > arr[ 2 ]\n    2.0\n\n\nFloat64Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    0.0\n    > arr2[ 1 ]\n    -1.0\n\n\nFloat64Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > arr.some( predicate )\n    true\n\n\nFloat64Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Float64Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n    > arr.sort()\n    <Float64Array>[ -2.0, -1.0, 0.0, 1.0, 2.0 ]\n\n\nFloat64Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Float64Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Float64Array>[ 0.0, 2.0, -2.0 ]\n\n\nFloat64Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n    > arr.toLocaleString()\n    '1,-1,0'\n\n\nFloat64Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n    > arr.toString()\n    '1,-1,0'\n\n\nFloat64Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > it = arr.values();\n    > it.next().value\n    1.0\n    > it.next().value\n    -1.0\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Float64Array.from":"\nFloat64Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2.0; };\n    > var arr = Float64Array.from( [ 1.0, -1.0 ], mapFcn )\n    <Float64Array>[ 2.0, -2.0 ]","Float64Array.of":"\nFloat64Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Float64Array.of( 2.0, -2.0 )\n    <Float64Array>[ 2.0, -2.0 ]","Float64Array.BYTES_PER_ELEMENT":"\nFloat64Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Float64Array.BYTES_PER_ELEMENT\n    8","Float64Array.name":"\nFloat64Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Float64Array.name\n    'Float64Array'","Float64Array.prototype.buffer":"\nFloat64Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>","Float64Array.prototype.byteLength":"\nFloat64Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 5 );\n    > arr.byteLength\n    40","Float64Array.prototype.byteOffset":"\nFloat64Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 5 );\n    > arr.byteOffset\n    0","Float64Array.prototype.BYTES_PER_ELEMENT":"\nFloat64Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    8","Float64Array.prototype.length":"\nFloat64Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 5 );\n    > arr.length\n    5","Float64Array.prototype.copyWithin":"\nFloat64Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Float64Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    2.0\n    > arr[ 4 ]\n    -2.0","Float64Array.prototype.entries":"\nFloat64Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1.0 ]\n    > it.next().value\n    [ 1, -1.0 ]\n    > it.next().done\n    true","Float64Array.prototype.every":"\nFloat64Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > function predicate( v ) { return ( v >= 0.0 ); };\n    > arr.every( predicate )\n    false","Float64Array.prototype.fill":"\nFloat64Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Float64Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > arr.fill( 2.0 );\n    > arr[ 0 ]\n    2.0\n    > arr[ 1 ]\n    2.0","Float64Array.prototype.filter":"\nFloat64Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v >= 0.0 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2","Float64Array.prototype.find":"\nFloat64Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > var v = arr.find( predicate )\n    -1.0","Float64Array.prototype.findIndex":"\nFloat64Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > var idx = arr.findIndex( predicate )\n    2","Float64Array.prototype.forEach":"\nFloat64Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:1 1:0 2:-1 '","Float64Array.prototype.includes":"\nFloat64Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > var bool = arr.includes( 2.0 )\n    false\n    > bool = arr.includes( -1.0 )\n    true","Float64Array.prototype.indexOf":"\nFloat64Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > var idx = arr.indexOf( 2.0 )\n    -1\n    > idx = arr.indexOf( -1.0 )\n    2","Float64Array.prototype.join":"\nFloat64Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > arr.join( '|' )\n    '1|0|-1'","Float64Array.prototype.keys":"\nFloat64Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true","Float64Array.prototype.lastIndexOf":"\nFloat64Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n    > var idx = arr.lastIndexOf( 2.0 )\n    -1\n    > idx = arr.lastIndexOf( 0.0 )\n    3","Float64Array.prototype.map":"\nFloat64Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( v ) { return v * 2.0; };\n    > var arr2 = arr1.map( fcn )\n    <Float64Array>[ 2.0, 0.0, -2.0 ]","Float64Array.prototype.reduce":"\nFloat64Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0.0 )\n    2.0","Float64Array.prototype.reduceRight":"\nFloat64Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0.0 )\n    2.0","Float64Array.prototype.reverse":"\nFloat64Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Float64Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] )\n    <Float64Array>\n    > arr.reverse()\n    <Float64Array>[ -1.0, 0.0, 1.0 ]","Float64Array.prototype.set":"\nFloat64Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > arr.set( [ -2.0, 2.0 ], 1 );\n    > arr[ 1 ]\n    -2.0\n    > arr[ 2 ]\n    2.0","Float64Array.prototype.slice":"\nFloat64Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Float64Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Float64Array( [ 1.0, 0.0, -1.0 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    0.0\n    > arr2[ 1 ]\n    -1.0","Float64Array.prototype.some":"\nFloat64Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > arr.some( predicate )\n    true","Float64Array.prototype.sort":"\nFloat64Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Float64Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n    > arr.sort()\n    <Float64Array>[ -2.0, -1.0, 0.0, 1.0, 2.0 ]","Float64Array.prototype.subarray":"\nFloat64Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Float64Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Float64Array( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Float64Array>[ 0.0, 2.0, -2.0 ]","Float64Array.prototype.toLocaleString":"\nFloat64Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n    > arr.toLocaleString()\n    '1,-1,0'","Float64Array.prototype.toString":"\nFloat64Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0, 0.0 ] );\n    > arr.toString()\n    '1,-1,0'","Float64Array.prototype.values":"\nFloat64Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Float64Array( [ 1.0, -1.0 ] );\n    > it = arr.values();\n    > it.next().value\n    1.0\n    > it.next().value\n    -1.0\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","forEach":"\nforEach( collection, fcn[, thisArg] )\n    Invokes a function for each element in a collection.\n\n    When invoked, the input function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n    > var arr = [ 1, 2, 3, 4 ];\n    > forEach( arr, logger )\n    0: 1\n    1: 2\n    2: 3\n    3: 4\n\n    See Also\n    --------\n    forEachAsync, forEachRight\n","forEachAsync":"\nforEachAsync( collection, [options,] fcn, done )\n    Invokes a function once for each element in a collection.\n\n    When invoked, `fcn` is provided a maximum of four arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If `fcn`\n    accepts two arguments, `fcn` is provided:\n\n    - value\n    - next\n\n    If `fcn` accepts three arguments, `fcn` is provided:\n\n    - value\n    - index\n    - next\n\n    For every other `fcn` signature, `fcn` is provided all four arguments.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function onDuration( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next();\n    ...     }\n    ... };\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( 'Done.' );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > forEachAsync( arr, onDuration, done )\n    1000\n    2500\n    3000\n    Done.\n\n    // Limit number of concurrent invocations:\n    > function onDuration( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next();\n    ...     }\n    ... };\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( 'Done.' );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 3000, 2500, 1000 ];\n    > forEachAsync( arr, opts, onDuration, done )\n    2500\n    3000\n    1000\n    Done.\n\n    // Process sequentially:\n    > function onDuration( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next();\n    ...     }\n    ... };\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( 'Done.' );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 3000, 2500, 1000 ];\n    > forEachAsync( arr, opts, onDuration, done )\n    3000\n    2500\n    1000\n    Done.\n\n\nforEachAsync.factory( [options,] fcn )\n    Returns a function which invokes a function once for each element in a\n    collection.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function onDuration( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next();\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = forEachAsync.factory( opts, onDuration );\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( 'Done.' );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    Done.\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    Done.\n\n    See Also\n    --------\n    forEach, forEachRightAsync\n","forEachAsync.factory":"\nforEachAsync.factory( [options,] fcn )\n    Returns a function which invokes a function once for each element in a\n    collection.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function onDuration( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next();\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = forEachAsync.factory( opts, onDuration );\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( 'Done.' );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    Done.\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    Done.\n\n    See Also\n    --------\n    forEach, forEachRightAsync","forEachChar":"\nforEachChar( str, [options,] clbk[, thisArg] )\n    Invokes a function for each character in a string.\n\n    When invoked, the provided function is provided three arguments:\n\n    - value: character.\n    - index: starting character index.\n    - str: input string.\n\n    Parameters\n    ----------\n    str: string\n        Input string over which to iterate.\n\n    options: Object (optional)\n        Options.\n\n    options.mode: string (optional)\n        Type of characters over which to iterate. The following modes are\n        supported:\n\n        - grapheme: grapheme clusters. Appropriate for strings containing visual\n          characters which can span multiple Unicode code points (e.g., emoji).\n        - code_point: Unicode code points. Appropriate for strings containing\n          visual characters which are comprised of more than one Unicode code\n          unit (e.g., ideographic symbols and punctuation and mathematical\n          alphanumerics).\n        - code_unit': UTF-16 code units. Appropriate for strings containing\n          visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n          common characters, such as those from the Latin, Greek, and Cyrillic\n          alphabets).\n\n        Default: 'grapheme'.\n\n    clbk: Function\n        The function to invoke for each character in the input string.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: string\n        Input string.\n\n    Examples\n    --------\n    > var n = 0;\n    > function fcn() { n += 1; };\n    > forEachChar( 'hello world!', fcn );\n    > n\n    12\n\n    See Also\n    --------\n    forEach\n","forEachRight":"\nforEachRight( collection, fcn[, thisArg] )\n    Invokes a function for each element in a collection, iterating from right to\n    left.\n\n    When invoked, the input function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n    > var arr = [ 1, 2, 3, 4 ];\n    > forEachRight( arr, logger )\n    3: 4\n    2: 3\n    1: 2\n    0: 1\n\n    See Also\n    --------\n    forEach, forEachRightAsync\n","forEachRightAsync":"\nforEachRightAsync( collection, [options,] fcn, done )\n    Invokes a function once for each element in a collection, iterating from\n    right to left.\n\n    When invoked, `fcn` is provided a maximum of four arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If `fcn`\n    accepts two arguments, `fcn` is provided:\n\n    - value\n    - next\n\n    If `fcn` accepts three arguments, `fcn` is provided:\n\n    - value\n    - index\n    - next\n\n    For every other `fcn` signature, `fcn` is provided all four arguments.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function onDuration( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next();\n    ...     }\n    ... };\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( 'Done.' );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > forEachRightAsync( arr, onDuration, done )\n    1000\n    2500\n    3000\n    Done.\n\n    // Limit number of concurrent invocations:\n    > function onDuration( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next();\n    ...     }\n    ... };\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( 'Done.' );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 1000, 2500, 3000 ];\n    > forEachRightAsync( arr, opts, onDuration, done )\n    2500\n    3000\n    1000\n    Done.\n\n    // Process sequentially:\n    > function onDuration( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next();\n    ...     }\n    ... };\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( 'Done.' );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 1000, 2500, 3000 ];\n    > forEachRightAsync( arr, opts, onDuration, done )\n    3000\n    2500\n    1000\n    Done.\n\n\nforEachRightAsync.factory( [options,] fcn )\n    Returns a function which invokes a function once for each element in a\n    collection, iterating from right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function onDuration( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next();\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = forEachRightAsync.factory( opts, onDuration );\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( 'Done.' );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    Done.\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    Done.\n\n    See Also\n    --------\n    forEachAsync, forEachRight\n","forEachRightAsync.factory":"\nforEachRightAsync.factory( [options,] fcn )\n    Returns a function which invokes a function once for each element in a\n    collection, iterating from right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function onDuration( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next();\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = forEachRightAsync.factory( opts, onDuration );\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( 'Done.' );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    Done.\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    Done.\n\n    See Also\n    --------\n    forEachAsync, forEachRight","forIn":"\nforIn( obj, fcn[, thisArg] )\n    Invokes a function for each own and inherited enumerable property of an\n    object.\n\n    When invoked, the function is provided three arguments:\n\n    - value: object property value.\n    - key: object property.\n    - obj: the input object.\n\n    To terminate iteration before visiting all properties, the provided function\n    must explicitly return `false`.\n\n    Property iteration order is *not* guaranteed.\n\n    Parameters\n    ----------\n    obj: Object\n        Input object, including arrays, typed arrays, and other collections.\n\n    fcn: Function\n        The function to invoke for each own enumerable property.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Object\n        Input object.\n\n    Examples\n    --------\n    > function logger( v, k ) { console.log( '%s: %d', k, v ); };\n    > function Foo() { return this; };\n    > Foo.prototype.beep = 'boop';\n    > var obj = new Foo();\n    > forIn( obj, logger )\n    beep: boop\n\n    See Also\n    --------\n    forEach, forOwn\n","format":"\nformat( str, ...args )\n    Insert supplied variable values into a format string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    args: ...any\n        Variable values.\n\n    Returns\n    -------\n    out: string\n        Formatted string.\n\n    Examples\n    --------\n    > var out = format( 'Hello, %s!', 'World' )\n    'Hello, World!'\n\n    > out = format( '%s %s', 'Hello', 'World' )\n    'Hello World'\n\n    > out = format( 'Pi: %.2f', PI )\n    'Pi: 3.14'\n\n","forOwn":"\nforOwn( obj, fcn[, thisArg] )\n    Invokes a function for each own enumerable property of an object.\n\n    When invoked, the function is provided three arguments:\n\n    - value: object property value.\n    - key: object property.\n    - obj: the input object.\n\n    To terminate iteration before visiting all properties, the provided function\n    must explicitly return `false`.\n\n    The function determines the list of own enumerable properties *before*\n    invoking the provided function. Hence, any modifications made to the input\n    object *after* calling this function (such as adding and removing\n    properties) will *not* affect the list of visited properties.\n\n    Property iteration order is *not* guaranteed.\n\n    Parameters\n    ----------\n    obj: Object\n        Input object, including arrays, typed arrays, and other collections.\n\n    fcn: Function\n        The function to invoke for each own enumerable property.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Object\n        Input object.\n\n    Examples\n    --------\n    > function logger( v, k ) { console.log( '%s: %d', k, v ); };\n    > var obj = { 'a': 1, 'b': 2, 'c': 3, 'd': 4 };\n    > forOwn( obj, logger )\n    a: 1\n    b: 2\n    c: 3\n    d: 4\n\n    See Also\n    --------\n    forEach, forIn\n","FOURTH_PI":"\nFOURTH_PI\n    One fourth times the mathematical constant `π`.\n\n    Examples\n    --------\n    > FOURTH_PI\n    7.85398163397448309616e-1\n\n    See Also\n    --------\n    PI\n","FOURTH_ROOT_EPS":"\nFOURTH_ROOT_EPS\n    Fourth root of double-precision floating-point epsilon.\n\n    Examples\n    --------\n    > FOURTH_ROOT_EPS\n    0.0001220703125\n\n    See Also\n    --------\n    EPS\n","FRB_SF_WAGE_RIGIDITY":"\nFRB_SF_WAGE_RIGIDITY()\n    Returns wage rates for U.S. workers that have not changed jobs within the\n    year.\n\n    Each array element has the following fields:\n\n    - date: collection date (month/day/year; e.g., 01/01/1980).\n    - all_workers: wage rates for hourly and non-hourly workers.\n    - hourly_workers: wage rates for hourly workers.\n    - non_hourly_workers: wage rates for non-hourly workers.\n    - less_than_high_school: wage rates for workers with less than a high school\n      education.\n    - high_school: wage rates for workers with a high school education.\n    - some_college: wage rates for workers with some college education.\n    - college: wage rates for workers with a college education.\n    - construction: wage rates for workers in the construction industry.\n    - finance: wage rates for workers in the finance industry.\n    - manufacturing: wage rates for workers in the manufacturing industry.\n\n    Returns\n    -------\n    out: Array<Object>\n        Wage rates.\n\n    Examples\n    --------\n    > var data = FRB_SF_WAGE_RIGIDITY()\n    [ {...}, {...}, ... ]\n\n    References\n    ----------\n    - Federal Reserve Bank of San Francisco. 2017. \"Wage Rigidity.\" <http://www.\n    frbsf.org/economic-research/indicators-data/nominal-wage-rigidity/>.\n\n","fromCodePoint":"\nfromCodePoint( ...pt )\n    Creates a string from a sequence of Unicode code points.\n\n    In addition to multiple arguments, the function also supports providing an\n    array-like object as a single argument containing a sequence of Unicode code\n    points.\n\n    Parameters\n    ----------\n    pt: ...integer\n        Sequence of Unicode code points.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = fromCodePoint( 9731 )\n    '☃'\n    > out = fromCodePoint( [ 9731 ] )\n    '☃'\n    > out = fromCodePoint( 97, 98, 99 )\n    'abc'\n    > out = fromCodePoint( [ 97, 98, 99 ] )\n    'abc'\n\n    See Also\n    --------\n    codePointAt\n","Function":"\nFunction( [...argNames,] body )\n    Returns a Function object.\n\n    Argument names must be strings corresponding to valid JavaScript parameters\n    (i.e., a plain identifier, or, in environments supporting such parameters, a\n    rest parameter or destructured parameter, optionally with a default).\n\n    Parameters\n    ----------\n    argNames: ...any (optional)\n        Parameter names.\n\n    body: string\n        Function body.\n\n    Returns\n    -------\n    fcn: Function\n        Function object.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f( 1, 2 )\n    3\n\n\nFunction.prototype.apply( thisArg, args )\n    Calls a function with a given `this` value and arguments provided as an\n    array (or array-like object).\n\n    Parameters\n    ----------\n    thisArg: any\n        Value to use as `this` when executing the function.\n\n    args: Array\n        Array of arguments to pass to the function.\n\n    Returns\n    -------\n    out: any\n        Function return value.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.apply( null, [ 1, 2 ] )\n    3\n\nFunction.prototype.call( thisArg, ...args )\n    Calls a function with a given `this` value and arguments provided\n    individually.\n\n    Parameters\n    ----------\n    thisArg: any\n        Value to use as `this` when executing the function.\n\n    args: ...any\n        Arguments to pass to the function.\n\n    Returns\n    -------\n    out: any\n        Function return value.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.call( null, 1, 2 )\n    3\n\nFunction.prototype.bind( thisArg, ...args )\n    Creates a new function which, when called, has its `this` keyword set to the\n    provided value, with a given sequence of arguments preceding any provided\n    when the new function is called.\n\n    Parameters\n    ----------\n    thisArg: any\n        Value to use as `this` when executing the function.\n\n    args: ...any\n        Arguments to pass to the function.\n\n    Returns\n    -------\n    fcn: Function\n        Bound function.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > var g = f.bind( null, 1 );\n    > g( 2 )\n    3\n\nFunction.prototype.toString()\n    Returns a string representation of the function.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.toString()\n    'function anonymous( x, y ) { return x + y; }'\n\nFunction.prototype.length\n    The number of arguments expected by the function.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.length\n    2\n\nFunction.prototype.name\n    The name of the function.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.name\n    'anonymous'\n\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.name = 'add';\n    > f.name\n    'add'\n\nFunction.prototype.prototype\n    The prototype of the function.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.prototype\n    {}\n\n","Function.prototype.apply":"\nFunction.prototype.apply( thisArg, args )\n    Calls a function with a given `this` value and arguments provided as an\n    array (or array-like object).\n\n    Parameters\n    ----------\n    thisArg: any\n        Value to use as `this` when executing the function.\n\n    args: Array\n        Array of arguments to pass to the function.\n\n    Returns\n    -------\n    out: any\n        Function return value.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.apply( null, [ 1, 2 ] )\n    3","Function.prototype.call":"\nFunction.prototype.call( thisArg, ...args )\n    Calls a function with a given `this` value and arguments provided\n    individually.\n\n    Parameters\n    ----------\n    thisArg: any\n        Value to use as `this` when executing the function.\n\n    args: ...any\n        Arguments to pass to the function.\n\n    Returns\n    -------\n    out: any\n        Function return value.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.call( null, 1, 2 )\n    3","Function.prototype.bind":"\nFunction.prototype.bind( thisArg, ...args )\n    Creates a new function which, when called, has its `this` keyword set to the\n    provided value, with a given sequence of arguments preceding any provided\n    when the new function is called.\n\n    Parameters\n    ----------\n    thisArg: any\n        Value to use as `this` when executing the function.\n\n    args: ...any\n        Arguments to pass to the function.\n\n    Returns\n    -------\n    fcn: Function\n        Bound function.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > var g = f.bind( null, 1 );\n    > g( 2 )\n    3","Function.prototype.toString":"\nFunction.prototype.toString()\n    Returns a string representation of the function.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.toString()\n    'function anonymous( x, y ) { return x + y; }'","Function.prototype.length":"\nFunction.prototype.length\n    The number of arguments expected by the function.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.length\n    2","Function.prototype.name":"\nFunction.prototype.name\n    The name of the function.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.name\n    'anonymous'\n\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.name = 'add';\n    > f.name\n    'add'","Function.prototype.prototype":"\nFunction.prototype.prototype\n    The prototype of the function.\n\n    Examples\n    --------\n    > var f = new Function( 'x', 'y', 'return x + y' );\n    > f.prototype\n    {}","function2string":"\nfunction2string( fcn )\n    Returns a string representing the source code of a provided function.\n\n    If called on built-in functions, functions created by `Function#bind()`, or\n    other non-JavaScript functions, the function returns a \"native\" function\n    string similar to the following:\n\n      \"function foo() { [native code] }\"\n\n    For intrinsic object methods and functions, `foo` is the initial name of the\n    function.\n\n    If called on a function created by the `Function` constructor, the function\n    returns the source code of a synthesized function declaration having the\n    name \"anonymous\" and using the provided parameters and function body.\n\n    Starting in ES2018, the ECMAScript specification requires that the returned\n    string contain the exact same source code as it was declared, including any\n    whitespace and/or comments. If the host is unable to access the source code,\n    the specification requires that the returned string be the native function\n    string.\n\n    Parameters\n    ----------\n    fcn: Function\n        Input function.\n\n    Returns\n    -------\n    out: string\n        String representing the function's source code.\n\n    Examples\n    --------\n    > function2string( base.erf )\n    <string>\n\n    See Also\n    --------\n    Function\n","functionName":"\nfunctionName( fcn )\n    Returns the name of a function.\n\n    If provided an anonymous function, the function returns an empty `string` or\n    the string `\"anonymous\"`.\n\n\n    Parameters\n    ----------\n    fcn: Function\n        Input function.\n\n    Returns\n    -------\n    out: string\n        Function name.\n\n    Examples\n    --------\n    > var v = functionName( String )\n    'String'\n    > v = functionName( function foo(){} )\n    'foo'\n    > v = functionName( function(){} )\n    '' || 'anonymous'\n\n    See Also\n    --------\n    constructorName\n","functionSequence":"\nfunctionSequence( ...fcn )\n    Returns a pipeline function.\n\n    Starting from the left, the pipeline function evaluates each function and\n    passes the result as an argument to the next function. The result of the\n    rightmost function is the result of the whole.\n\n    Only the leftmost function is explicitly permitted to accept multiple\n    arguments. All other functions are evaluated as unary functions.\n\n    Parameters\n    ----------\n    fcn: ...Function\n        Functions to evaluate in sequential order.\n\n    Returns\n    -------\n    out: Function\n        Pipeline function.\n\n    Examples\n    --------\n    > function a( x ) { return 2 * x; };\n    > function b( x ) { return x + 3; };\n    > function c( x ) { return x / 5; };\n    > var f = functionSequence( a, b, c );\n    > var z = f( 6 )\n    3\n\n    See Also\n    --------\n    compose, functionSequenceAsync\n","functionSequenceAsync":"\nfunctionSequenceAsync( ...fcn )\n    Returns a pipeline function.\n\n    Starting from the left, the pipeline function evaluates each function and\n    passes the result as the first argument of the next function. The result of\n    the rightmost function is the result of the whole.\n\n    The last argument for each provided function is a `next` callback which\n    should be invoked upon function completion. The callback accepts two\n    arguments:\n\n    - error: error argument.\n    - result: function result.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the pipeline function suspends execution and immediately calls the\n    `done` callback for subsequent `error` handling.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Only the leftmost function is explicitly permitted to accept multiple\n    arguments. All other functions are evaluated as binary functions.\n\n    The function will throw if provided fewer than two input arguments.\n\n    Parameters\n    ----------\n    fcn: ...Function\n        Functions to evaluate in sequential order.\n\n    Returns\n    -------\n    out: Function\n        Pipeline function.\n\n    Examples\n    --------\n    > function a( x, next ) {\n    ...    setTimeout( onTimeout, 0 );\n    ...    function onTimeout() {\n    ...        next( null, 2*x );\n    ...    }\n    ... };\n    > function b( x, next ) {\n    ...    setTimeout( onTimeout, 0 );\n    ...    function onTimeout() {\n    ...        next( null, x+3 );\n    ...    }\n    ... };\n    > function c( x, next ) {\n    ...    setTimeout( onTimeout, 0 );\n    ...    function onTimeout() {\n    ...        next( null, x/5 );\n    ...    }\n    ... };\n    > var f = functionSequenceAsync( a, b, c );\n    > function done( error, result ) {\n    ...    if ( error ) {\n    ...        throw error;\n    ...    }\n    ...    console.log( result );\n    ... };\n    > f( 6, done )\n    3\n\n    See Also\n    --------\n    composeAsync, functionSequence\n","GAMMA_LANCZOS_G":"\nGAMMA_LANCZOS_G\n    Arbitrary constant `g` to be used in Lanczos approximation functions.\n\n    Examples\n    --------\n    > GAMMA_LANCZOS_G\n    10.900511\n\n","gdot":"\ngdot( x, y )\n    Computes the dot product of two vectors.\n\n    In general, for best performance, especially for large vectors, provide\n    1-dimensional ndarrays whose underlying data type is either 'float64' or\n    'float32'.\n\n    If provided empty vectors, the function returns `0.0`.\n\n    Parameters\n    ----------\n    x: ndarray|ArrayLikeObject\n        First input array.\n\n    y: ndarray|ArrayLikeObject\n        Second input array.\n\n    Returns\n    -------\n    dot: number\n        The dot product.\n\n    Examples\n    --------\n    // Using ndarrays...\n    > var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n    > var y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n    > gdot( x, y )\n    -5.0\n\n    // Using array-like objects...\n    > x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n    > y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n    > gdot( x, y )\n    -5.0\n\n    See Also\n    --------\n    base.strided.gdot, ddot, sdot\n","getegid":"\ngetegid()\n    Returns the effective numeric group identity of the calling process.\n\n    The function only returns an effective group identity on POSIX platforms.\n    For all other platforms (e.g., Windows and Android), the function returns\n    `null`.\n\n    Returns\n    -------\n    id: integer|null\n        Effective numeric group identity.\n\n    Examples\n    --------\n    > var gid = getegid()\n\n    See Also\n    --------\n    geteuid, getgid, getuid\n","geteuid":"\ngeteuid()\n    Returns the effective numeric user identity of the calling process.\n\n    The function only returns an effective user identity on POSIX platforms. For\n    all other platforms (e.g., Windows and Android), the function returns\n    `null`.\n\n    Returns\n    -------\n    id: integer|null\n        Effective numeric user identity.\n\n    Examples\n    --------\n    > var uid = geteuid()\n\n    See Also\n    --------\n    getegid, getgid, getuid\n","getgid":"\ngetgid()\n    Returns the numeric group identity of the calling process.\n\n    The function only returns a group identity on POSIX platforms. For all other\n    platforms (e.g., Windows and Android), the function returns `null`.\n\n    Returns\n    -------\n    id: integer|null\n        Numeric group identity.\n\n    Examples\n    --------\n    > var gid = getgid()\n\n    See Also\n    --------\n    getegid, geteuid, getuid\n","getGlobal":"\ngetGlobal( [codegen] )\n    Returns the global object.\n\n    Parameters\n    ----------\n    codegen: boolean (optional)\n        Boolean indicating whether to use code generation to resolve the global\n        object. Code generation is the *most* reliable means for resolving the\n        global object; however, using code generation may violate content\n        security policies (CSPs). Default: false.\n\n    Returns\n    -------\n    global: Object\n        Global object.\n\n    Examples\n    --------\n    > var g = getGlobal()\n    {...}\n\n","getPrototypeOf":"\ngetPrototypeOf( value )\n    Returns the prototype of a provided object.\n\n    In contrast to the native `Object.getPrototypeOf`, this function does not\n    throw when provided `null` or `undefined`. Instead, similar to when provided\n    any value with *no* inherited properties, the function returns `null`.\n\n    Value arguments other than `null` or `undefined` are coerced to objects.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    out: Object|null\n        Prototype.\n\n    Examples\n    --------\n    > var proto = getPrototypeOf( {} )\n    {}\n\n    See Also\n    --------\n    isPrototypeOf\n","getuid":"\ngetuid()\n    Returns the numeric user identity of the calling process.\n\n    The function only returns a user identity on POSIX platforms. For all other\n    platforms (e.g., Windows and Android), the function returns `null`.\n\n    Returns\n    -------\n    id: integer|null\n        Numeric user identity.\n\n    Examples\n    --------\n    > var uid = getuid()\n\n    See Also\n    --------\n    getegid, geteuid, getgid\n","GLAISHER":"\nGLAISHER\n    Glaisher-Kinkelin constant.\n\n    Examples\n    --------\n    > GLAISHER\n    1.2824271291006226\n\n","graphemeClusters2iterator":"\ngraphemeClusters2iterator( src[, mapFcn[, thisArg]] )\n    Returns an iterator which iterates over each grapheme cluster in a string.\n\n    When invoked, an input function is provided three arguments:\n\n    - value: grapheme cluster.\n    - index: iterated value index.\n    - src: source string.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke a string's `@@iterator` method, regardless of whether this method is\n    defined. To convert a string to an implementation defined iterator, invoke\n    this method directly.\n\n    Parameters\n    ----------\n    src: string\n        String from which to create the iterator.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = graphemeClusters2iterator( '🌷🍕' );\n    > var v = it.next().value\n    '🌷'\n    > v = it.next().value\n    '🍕'\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    array2iterator, graphemeClusters2iteratorRight\n","graphemeClusters2iteratorRight":"\ngraphemeClusters2iteratorRight( src[, mapFcn[, thisArg]] )\n    Returns an iterator which iterates from right to left over each grapheme\n    cluster in a string.\n\n    When invoked, an input function is provided three arguments:\n\n    - value: grapheme cluster.\n    - index: iterated value index.\n    - src: source string.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke a string's `@@iterator` method, regardless of whether this method is\n    defined. To convert a string to an implementation defined iterator, invoke\n    this method directly.\n\n    Parameters\n    ----------\n    src: string\n        String from which to create the iterator.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = graphemeClusters2iteratorRight( '🌷🍕' );\n    > var v = it.next().value\n    '🍕'\n    > v = it.next().value\n    '🌷'\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    array2iteratorRight, graphemeClusters2iterator\n","group":"\ngroup( collection, [options,] groups )\n    Groups values as arrays associated with distinct keys.\n\n    If provided an empty collection, the function returns an empty object.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection to group. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Options.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `indices`, indices are returned; if\n        `*`, both indices and values are returned. Default: 'values'.\n\n    groups: Array|TypedArray|Object\n        A collection defining which group an element in the input collection\n        belongs to. Each value in `groups` should resolve to a value which can\n        be serialized as an object key. If provided an object, the object must\n        be array-like (excluding strings and functions).\n\n    Returns\n    -------\n    out: Object\n        Group results.\n\n    Examples\n    --------\n    > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n    > var groups = [ 'b', 'b', 'f', 'b' ];\n    > var out = group( collection, groups )\n    { 'b': [ 'beep', 'boop', 'bar' ], 'f': [ 'foo' ] }\n    > groups = [ 1, 1, 2, 1 ];\n    > out = group( collection, groups )\n    { '1': [ 'beep', 'boop', 'bar' ], '2': [ 'foo' ] }\n\n    // Output group results as indices:\n    > groups = [ 'b', 'b', 'f', 'b' ];\n    > var opts = { 'returns': 'indices' };\n    > out = group( collection, opts, groups )\n    { 'b': [ 0, 1, 3 ], 'f': [ 2 ] }\n\n    // Output group results as index-element pairs:\n    > opts = { 'returns': '*' };\n    > out = group( collection, opts, groups )\n    { 'b': [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], 'f': [ [2, 'foo'] ] }\n\n    See Also\n    --------\n    bifurcate, countBy, groupBy\n","groupBy":"\ngroupBy( collection, [options,] indicator )\n    Groups values according to an indicator function.\n\n    When invoked, the indicator function is provided two arguments:\n\n    - value: collection value.\n    - index: collection index.\n\n    The value returned by an indicator function should be a value which can be\n    serialized as an object key.\n\n    If provided an empty collection, the function returns an empty object.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection to group. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Options.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `indices`, indices are returned; if\n        `*`, both indices and values are returned. Default: 'values'.\n\n    indicator: Function\n        Indicator function specifying which group an element in the input\n        collection belongs to.\n\n    Returns\n    -------\n    out: Object\n        Group results.\n\n    Examples\n    --------\n    > function indicator( v ) {\n    ...     if ( v[ 0 ] === 'b' ) {\n    ...         return 'b';\n    ...     }\n    ...     return 'other';\n    ... };\n    > var collection = [ 'beep', 'boop', 'foo', 'bar' ];\n    > var out = groupBy( collection, indicator )\n    { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n    // Output group results as indices:\n    > var opts = { 'returns': 'indices' };\n    > out = groupBy( collection, opts, indicator )\n    { 'b': [ 0, 1, 3 ], 'other': [ 2 ] }\n\n    // Output group results as index-value pairs:\n    > opts = { 'returns': '*' };\n    > out = groupBy( collection, opts, indicator )\n    { 'b': [ [0, 'beep'], [1, 'boop'], [3, 'bar'] ], 'other': [ [2, 'foo' ] ] }\n\n    See Also\n    --------\n    bifurcateBy, countBy, group\n","groupByAsync":"\ngroupByAsync( collection, [options,] indicator, done )\n    Groups values according to an indicator function.\n\n    When invoked, the indicator function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If the\n    indicator function accepts two arguments, the indicator function is\n    provided:\n\n    - value\n    - next\n\n    If the indicator function accepts three arguments, the indicator function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other indicator function signature, the indicator function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - group: value group.\n\n    If an indicator function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    If provided an empty collection, the function calls the `done` callback with\n    an empty object as the second argument.\n\n    The `group` returned by an indicator function should be a value which can be\n    serialized as an object key.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `indices`, indices are returned; if\n        `*`, both indices and values are returned. Default: 'values'.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    indicator: Function\n        Indicator function specifying which group an element in the input\n        collection belongs to.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > groupByAsync( arr, indicator, done )\n    1000\n    2500\n    3000\n    { \"true\": [ 1000, 3000 ], \"false\": [ 2500 ] }\n\n    // Output group results as indices:\n    > var opts = { 'returns': 'indices' };\n    > groupByAsync( arr, opts, indicator, done )\n    1000\n    2500\n    3000\n    { \"true\": [ 2, 0 ], \"false\": [ 1 ] }\n\n    // Output group results as index-value pairs:\n    > opts = { 'returns': '*' };\n    > groupByAsync( arr, opts, indicator, done )\n    1000\n    2500\n    3000\n    { \"true\": [ [ 2, 1000 ], [ 0, 3000 ] ], \"false\": [ [ 1, 2500 ] ] }\n\n    // Limit number of concurrent invocations:\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 3000, 2500, 1000 ];\n    > groupByAsync( arr, opts, indicator, done )\n    2500\n    3000\n    1000\n    { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n\n    // Process sequentially:\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 3000, 2500, 1000 ];\n    > groupByAsync( arr, opts, indicator, done )\n    3000\n    2500\n    1000\n    { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n\n\ngroupByAsync.factory( [options,] indicator )\n    Returns a function which groups values according to an indicator function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `indices`, indices are returned; if\n        `*`, both indices and values are returned. Default: 'values'.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    indicator: Function\n        Indicator function specifying which group an element in the input\n        collection belongs to.\n\n    Returns\n    -------\n    out: Function\n        A group-by function.\n\n    Examples\n    --------\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = groupByAsync.factory( opts, indicator );\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    { \"true\": [ 2000, 1000 ], \"false\": [ 1500 ] }\n\n    See Also\n    --------\n    bifurcateByAsync, countByAsync, groupBy\n","groupByAsync.factory":"\ngroupByAsync.factory( [options,] indicator )\n    Returns a function which groups values according to an indicator function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `indices`, indices are returned; if\n        `*`, both indices and values are returned. Default: 'values'.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    indicator: Function\n        Indicator function specifying which group an element in the input\n        collection belongs to.\n\n    Returns\n    -------\n    out: Function\n        A group-by function.\n\n    Examples\n    --------\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = groupByAsync.factory( opts, indicator );\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    { \"true\": [ 3000, 1000 ], \"false\": [ 2500 ] }\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    { \"true\": [ 2000, 1000 ], \"false\": [ 1500 ] }\n\n    See Also\n    --------\n    bifurcateByAsync, countByAsync, groupBy","groupIn":"\ngroupIn( obj, [options,] indicator )\n    Group values according to an indicator function.\n\n    When invoked, the indicator function is provided two arguments:\n\n    - value: object value.\n    - key: object key.\n\n    The value returned by an indicator function should be a value which can be\n    serialized as an object key.\n\n    If provided an empty object with no prototype, the function returns an empty\n    object.\n\n    The function iterates over an object's own and inherited properties.\n\n    Key iteration order is *not* guaranteed, and, thus, result order is *not*\n    guaranteed.\n\n    Parameters\n    ----------\n    obj: Object|Array|TypedArray\n        Input object to group.\n\n    options: Object (optional)\n        Options.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `keys`, keys are returned; if `*`,\n        both keys and values are returned. Default: 'values'.\n\n    indicator: Function\n        Indicator function indicating which group a value in the input object\n        belongs to.\n\n    Returns\n    -------\n    out: Object\n        Group results.\n\n    Examples\n    --------\n    > function indicator( v ) {\n    ...     if ( v[ 0 ] === 'b' ) {\n    ...         return 'b';\n    ...     }\n    ...     return 'other';\n    ... };\n    > function Foo() { this.a = 'beep'; this.b = 'boop'; return this; };\n    > Foo.prototype = Object.create( null );\n    > Foo.prototype.c = 'foo';\n    > Foo.prototype.d = 'bar';\n    > var obj = new Foo();\n    > var out = groupIn( obj, indicator )\n    { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n    // Output group results as keys:\n    > var opts = { 'returns': 'keys' };\n    > out = groupIn( obj, opts, indicator )\n    { 'b': [ 'a', 'b', 'd' ], 'other': [ 'c' ] }\n\n    // Output group results as key-value pairs:\n    > opts = { 'returns': '*' };\n    > out = groupIn( obj, opts, indicator )\n    { 'b': [['a','beep'], ['b','boop'], ['d','bar']], 'other': [['c','foo' ]] }\n\n    See Also\n    --------\n    bifurcateIn, groupBy, groupOwn\n","groupOwn":"\ngroupOwn( obj, [options,] indicator )\n    Group values according to an indicator function.\n\n    When invoked, the indicator function is provided two arguments:\n\n    - value: object value.\n    - key: object key.\n\n    The value returned by an indicator function should be a value which can be\n    serialized as an object key.\n\n    If provided an empty object, the function returns an empty object.\n\n    The function iterates over an object's own properties.\n\n    Key iteration order is *not* guaranteed, and, thus, result order is *not*\n    guaranteed.\n\n    Parameters\n    ----------\n    obj: Object|Array|TypedArray\n        Input object to group.\n\n    options: Object (optional)\n        Options.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    options.returns: string (optional)\n        If `values`, values are returned; if `keys`, keys are returned; if `*`,\n        both keys and values are returned. Default: 'values'.\n\n    indicator: Function\n        Indicator function indicating which group a value in the input object\n        belongs to.\n\n    Returns\n    -------\n    out: Object\n        Group results.\n\n    Examples\n    --------\n    > function indicator( v ) {\n    ...     if ( v[ 0 ] === 'b' ) {\n    ...         return 'b';\n    ...     }\n    ...     return 'other';\n    ... };\n    > var obj = { 'a': 'beep', 'b': 'boop', 'c': 'foo', 'd': 'bar' };\n    > var out = groupOwn( obj, indicator )\n    { 'b': [ 'beep', 'boop', 'bar' ], 'other': [ 'foo' ] }\n\n    // Output group results as keys:\n    > var opts = { 'returns': 'keys' };\n    > out = groupOwn( obj, opts, indicator )\n    { 'b': [ 'a', 'b', 'd' ], 'other': [ 'c' ] }\n\n    // Output group results as key-value pairs:\n    > opts = { 'returns': '*' };\n    > out = groupOwn( obj, opts, indicator )\n    { 'b': [['a','beep'], ['b','boop'], ['d','bar']], 'other': [['c','foo' ]] }\n\n    See Also\n    --------\n    bifurcateOwn, group, groupBy\n","gswap":"\ngswap( x, y )\n    Interchanges two vectors.\n\n    In general, for best performance, especially for large vectors, provide\n    1-dimensional ndarrays whose underlying data type is either 'float64' or\n    'float32'.\n\n    Parameters\n    ----------\n    x: ndarray|ArrayLikeObject\n        First input array.\n\n    y: ndarray|ArrayLikeObject\n        Second input array.\n\n    Returns\n    -------\n    y: ndarray\n        The second input array `y`.\n\n    Examples\n    --------\n    // Using ndarrays...\n    > var x = array( new Float64Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n    > var y = array( new Float64Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n    > gswap( x, y );\n    > x.data\n    <Float64Array>[ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n    > y.data\n    <Float64Array>[ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n    // Using array-like objects...\n    > x = [ 4.0, 2.0, -3.0, 5.0, -1.0 ];\n    > y = [ 2.0, 6.0, -1.0, -4.0, 8.0 ];\n    > gswap( x, y );\n    > x\n    [ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n    > y\n    [ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n    See Also\n    --------\n    base.strided.gswap, dswap, sswap\n","HALF_LN2":"\nHALF_LN2\n    One half times the natural logarithm of `2`.\n\n    Examples\n    --------\n    > HALF_LN2\n    3.46573590279972654709e-01\n\n    See Also\n    --------\n    LN2\n","HALF_PI":"\nHALF_PI\n    One half times the mathematical constant `π`.\n\n    Examples\n    --------\n    > HALF_PI\n    1.5707963267948966\n\n    See Also\n    --------\n    PI\n","HARRISON_BOSTON_HOUSE_PRICES":"\nHARRISON_BOSTON_HOUSE_PRICES()\n    Returns a dataset derived from information collected by the US Census\n    Service concerning housing in Boston, Massachusetts (1978).\n\n    The data consists of 14 attributes:\n\n    - crim: per capita crime rate by town.\n    - zn: proportion of residential land zoned for lots over 25,000 square feet.\n    - indus: proportion of non-retail business acres per town.\n    - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise).\n    - nox: nitric oxides concentration (parts per 10 million).\n    - rm: average number of rooms per dwelling.\n    - age: proportion of owner-occupied units built prior to 1940.\n    - dis: weighted distances to five Boston employment centers.\n    - rad: index of accessibility to radial highways.\n    - tax: full-value property-tax rate per $10,000.\n    - ptratio: pupil-teacher ratio by town.\n    - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town.\n    - lstat: percent lower status of the population.\n    - medv: median value of owner-occupied homes in $1000's.\n\n    The dataset can be used to predict two dependent variables: 1) nitrous oxide\n    level and 2) median home value.\n\n    The median home value field seems to be censored at 50.00 (corresponding to\n    a median value of $50,000). Censoring is suggested by the fact that the\n    highest median value of exactly $50,000 is reported in 16 cases, while 15\n    cases have values between $40,000 and $50,000. Values are rounded to the\n    nearest hundred. Harrison and Rubinfeld do not, however, mention any\n    censoring.\n\n    Additionally, as documented by Gilley and Pace (1996), the dataset contains\n    eight miscoded median values.\n\n    Returns\n    -------\n    out: Array<Object>\n        Boston house prices.\n\n    Examples\n    --------\n    > var data = HARRISON_BOSTON_HOUSE_PRICES()\n    [ {...}, {...}, ... ]\n\n    References\n    ----------\n    - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n    the demand for clean air.\" _Journal of Environmental Economics and\n    Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n    - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n    Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n    doi:10.1006/jeem.1996.0052.\n\n    See Also\n    --------\n    HARRISON_BOSTON_HOUSE_PRICES_CORRECTED, PACE_BOSTON_HOUSE_PRICES\n","HARRISON_BOSTON_HOUSE_PRICES_CORRECTED":"\nHARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n    Returns a (corrected) dataset derived from information collected by the US\n    Census Service concerning housing in Boston, Massachusetts (1978).\n\n    The data consists of 15 attributes:\n\n    - crim: per capita crime rate by town.\n    - zn: proportion of residential land zoned for lots over 25,000 square feet.\n    - indus: proportion of non-retail business acres per town.\n    - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise).\n    - nox: nitric oxides concentration (parts per 10 million).\n    - rm: average number of rooms per dwelling.\n    - age: proportion of owner-occupied units built prior to 1940.\n    - dis: weighted distances to five Boston employment centers.\n    - rad: index of accessibility to radial highways.\n    - tax: full-value property-tax rate per $10,000.\n    - ptratio: pupil-teacher ratio by town.\n    - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town\n    - lstat: percent lower status of the population.\n    - medv: median value of owner-occupied homes in $1000's.\n    - cmedv: corrected median value of owner-occupied homes in $1000's.\n\n    The dataset can be used to predict two dependent variables: 1) nitrous oxide\n    level and 2) median home value.\n\n    The median home value field seems to be censored at 50.00 (corresponding to\n    a median value of $50,000). Censoring is suggested by the fact that the\n    highest median value of exactly $50,000 is reported in 16 cases, while 15\n    cases have values between $40,000 and $50,000. Values are rounded to the\n    nearest hundred. Harrison and Rubinfeld do not, however, mention any\n    censoring.\n\n    The dataset contains eight corrections to miscoded median values, as\n    documented by Gilley and Pace (1996).\n\n    Returns\n    -------\n    out: Array<Object>\n        Boston house prices.\n\n    Examples\n    --------\n    > var data = HARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n    [ {...}, {...}, ... ]\n\n    References\n    ----------\n    - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n    the demand for clean air.\" _Journal of Environmental Economics and\n    Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n    - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n    Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n    doi:10.1006/jeem.1996.0052.\n\n    See Also\n    --------\n    HARRISON_BOSTON_HOUSE_PRICES, PACE_BOSTON_HOUSE_PRICES\n","hasArrayBufferSupport":"\nhasArrayBufferSupport()\n    Tests for native `ArrayBuffer` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `ArrayBuffer` support.\n\n    Examples\n    --------\n    > var bool = hasArrayBufferSupport()\n    <boolean>\n\n    See Also\n    --------\n    hasFloat32ArraySupport, hasFloat64ArraySupport, hasInt16ArraySupport, hasInt32ArraySupport, hasInt8ArraySupport, hasNodeBufferSupport, hasSharedArrayBufferSupport, hasUint16ArraySupport, hasUint32ArraySupport, hasUint8ArraySupport, hasUint8ClampedArraySupport\n","hasArrowFunctionSupport":"\nhasArrowFunctionSupport()\n    Tests whether an environment supports native arrow functions.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment support arrow functions.\n\n    Examples\n    --------\n    > var bool = hasArrowFunctionSupport()\n    <boolean>\n\n","hasAsyncAwaitSupport":"\nhasAsyncAwaitSupport()\n    Tests for native `async`/`await` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has native `async`/`await` support.\n\n    Examples\n    --------\n    > var bool = hasAsyncAwaitSupport()\n    <boolean>\n\n","hasAsyncIteratorSymbolSupport":"\nhasAsyncIteratorSymbolSupport()\n    Tests for native `Symbol.asyncIterator` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has native `Symbol.asyncIterator`\n        support.\n\n    Examples\n    --------\n    > var bool = hasAsyncIteratorSymbolSupport()\n    <boolean>\n\n    See Also\n    --------\n    hasIteratorSymbolSupport, hasSymbolSupport\n","hasAtobSupport":"\nhasAtobSupport()\n    Tests for native `atob` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `atob` support.\n\n    Examples\n    --------\n    > var bool = hasAtobSupport()\n    <boolean>\n\n    See Also\n    --------\n    hasBtoaSupport\n","hasBigInt64ArraySupport":"\nhasBigInt64ArraySupport()\n    Tests for native `BigInt64Array` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `BigInt64Array` support.\n\n    Examples\n    --------\n    > var bool = hasBigInt64ArraySupport()\n    <boolean>\n\n    See Also\n    --------\n    hasBigIntSupport, hasBigUint64ArraySupport\n","hasBigIntSupport":"\nhasBigIntSupport()\n    Tests for native `BigInt` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has native `BigInt` support.\n\n    Examples\n    --------\n    > var bool = hasBigIntSupport()\n    <boolean>\n\n","hasBigUint64ArraySupport":"\nhasBigUint64ArraySupport()\n    Tests for native `BigUint64Array` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `BigUint64Array` support.\n\n    Examples\n    --------\n    > var bool = hasBigUint64ArraySupport()\n    <boolean>\n\n    See Also\n    --------\n    hasBigIntSupport, hasBigInt64ArraySupport\n","hasBtoaSupport":"\nhasBtoaSupport()\n    Tests for native `btoa` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `btoa` support.\n\n    Examples\n    --------\n    > var bool = hasBtoaSupport()\n    <boolean>\n\n    See Also\n    --------\n    hasAtobSupport\n","hasClassSupport":"\nhasClassSupport()\n    Tests for native `class` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has native `class` support.\n\n    Examples\n    --------\n    > var bool = hasClassSupport()\n    <boolean>\n\n","hasDataViewSupport":"\nhasDataViewSupport()\n    Tests for native `DataView` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `DataView` support.\n\n    Examples\n    --------\n    > var bool = hasDataViewSupport()\n    <boolean>\n\n    See Also\n    --------\n    hasArrayBufferSupport\n","hasDefinePropertiesSupport":"\nhasDefinePropertiesSupport()\n    Tests for `Object.defineProperties` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Object.defineProperties`\n        support.\n\n    Examples\n    --------\n    > var bool = hasDefinePropertiesSupport()\n    <boolean>\n\n    See Also\n    --------\n    hasDefinePropertySupport\n","hasDefinePropertySupport":"\nhasDefinePropertySupport()\n    Tests for `Object.defineProperty` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Object.defineProperty`\n        support.\n\n    Examples\n    --------\n    > var bool = hasDefinePropertySupport()\n    <boolean>\n\n    See Also\n    --------\n    hasDefinePropertiesSupport\n","hasFloat32ArraySupport":"\nhasFloat32ArraySupport()\n    Tests for native `Float32Array` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Float32Array` support.\n\n    Examples\n    --------\n    > var bool = hasFloat32ArraySupport()\n    <boolean>\n\n","hasFloat64ArraySupport":"\nhasFloat64ArraySupport()\n    Tests for native `Float64Array` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Float64Array` support.\n\n    Examples\n    --------\n    > var bool = hasFloat64ArraySupport()\n    <boolean>\n\n","hasFunctionNameSupport":"\nhasFunctionNameSupport()\n    Tests for native function `name` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has function `name` support.\n\n    Examples\n    --------\n    > var bool = hasFunctionNameSupport()\n    <boolean>\n\n","hasGeneratorSupport":"\nhasGeneratorSupport()\n    Tests whether an environment supports native generator functions.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment support generator functions.\n\n    Examples\n    --------\n    > var bool = hasGeneratorSupport()\n    <boolean>\n\n","hasGlobalThisSupport":"\nhasGlobalThisSupport()\n    Tests for `globalThis` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `globalThis` support.\n\n    Examples\n    --------\n    > var bool = hasGlobalThisSupport()\n    <boolean>\n\n    See Also\n    --------\n    getGlobal\n","hasInt8ArraySupport":"\nhasInt8ArraySupport()\n    Tests for native `Int8Array` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Int8Array` support.\n\n    Examples\n    --------\n    > var bool = hasInt8ArraySupport()\n    <boolean>\n\n","hasInt16ArraySupport":"\nhasInt16ArraySupport()\n    Tests for native `Int16Array` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Int16Array` support.\n\n    Examples\n    --------\n    > var bool = hasInt16ArraySupport()\n    <boolean>\n\n","hasInt32ArraySupport":"\nhasInt32ArraySupport()\n    Tests for native `Int32Array` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Int32Array` support.\n\n    Examples\n    --------\n    > var bool = hasInt32ArraySupport()\n    <boolean>\n\n","hasIteratorSymbolSupport":"\nhasIteratorSymbolSupport()\n    Tests for native `Symbol.iterator` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has native `Symbol.iterator`\n        support.\n\n    Examples\n    --------\n    > var bool = hasIteratorSymbolSupport()\n    <boolean>\n\n    See Also\n    --------\n    hasAsyncIteratorSymbolSupport, hasSymbolSupport\n","hasMapSupport":"\nhasMapSupport()\n    Tests for native `Map` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Map` support.\n\n    Examples\n    --------\n    > var bool = hasMapSupport()\n    <boolean>\n\n","hasNodeBufferSupport":"\nhasNodeBufferSupport()\n    Tests for native `Buffer` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Buffer` support.\n\n    Examples\n    --------\n    > var bool = hasNodeBufferSupport()\n    <boolean>\n\n","hasOwnProp":"\nhasOwnProp( value, property )\n    Tests if an object has a specified property.\n\n    In contrast to the native `Object.prototype.hasOwnProperty`, this function\n    does not throw when provided `null` or `undefined`. Instead, the function\n    returns `false`.\n\n    Value arguments other than `null` or `undefined` are coerced to objects.\n\n    Property arguments are coerced to strings.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object has a specified property.\n\n    Examples\n    --------\n    > var beep = { 'boop': true };\n    > var bool = hasOwnProp( beep, 'boop' )\n    true\n    > bool = hasOwnProp( beep, 'bop' )\n    false\n\n    See Also\n    --------\n    hasProp\n","hasProp":"\nhasProp( value, property )\n    Tests if an object has a specified property, either own or inherited.\n\n    Value arguments other than `null` or `undefined` are coerced to objects.\n\n    Non-symbol property arguments are coerced to strings.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object has a specified property.\n\n    Examples\n    --------\n    > var beep = { 'boop': true };\n    > var bool = hasProp( beep, 'boop' )\n    true\n    > bool = hasProp( beep, 'toString' )\n    true\n    > bool = hasProp( beep, 'bop' )\n    false\n\n    See Also\n    --------\n    hasOwnProp\n","hasProxySupport":"\nhasProxySupport()\n    Tests whether an environment has native `Proxy` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has native `Proxy` support.\n\n    Examples\n    --------\n    > var bool = hasProxySupport()\n    <boolean>\n\n","hasSetSupport":"\nhasSetSupport()\n    Tests for native `Set` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has native `Set` support.\n\n    Examples\n    --------\n    > var bool = hasSetSupport()\n    <boolean>\n\n","hasSharedArrayBufferSupport":"\nhasSharedArrayBufferSupport()\n    Tests for native `SharedArrayBuffer` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `SharedArrayBuffer` support.\n\n    Examples\n    --------\n    > var bool = hasSharedArrayBufferSupport()\n    <boolean>\n\n    See Also\n    --------\n    hasArrayBufferSupport, hasFloat32ArraySupport, hasFloat64ArraySupport, hasInt16ArraySupport, hasInt32ArraySupport, hasInt8ArraySupport, hasNodeBufferSupport, hasUint16ArraySupport, hasUint32ArraySupport, hasUint8ArraySupport, hasUint8ClampedArraySupport\n","hasSymbolSupport":"\nhasSymbolSupport()\n    Tests for native `Symbol` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has native `Symbol` support.\n\n    Examples\n    --------\n    > var bool = hasSymbolSupport()\n    <boolean>\n\n    See Also\n    --------\n    hasIteratorSymbolSupport\n","hasToStringTagSupport":"\nhasToStringTagSupport()\n    Tests for native `toStringTag` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `toStringTag` support.\n\n    Examples\n    --------\n    > var bool = hasToStringTagSupport()\n    <boolean>\n\n","hasUint8ArraySupport":"\nhasUint8ArraySupport()\n    Tests for native `Uint8Array` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Uint8Array` support.\n\n    Examples\n    --------\n    > var bool = hasUint8ArraySupport()\n    <boolean>\n\n","hasUint8ClampedArraySupport":"\nhasUint8ClampedArraySupport()\n    Tests for native `Uint8ClampedArray` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Uint8ClampedArray` support.\n\n    Examples\n    --------\n    > var bool = hasUint8ClampedArraySupport()\n    <boolean>\n\n","hasUint16ArraySupport":"\nhasUint16ArraySupport()\n    Tests for native `Uint16Array` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Uint16Array` support.\n\n    Examples\n    --------\n    > var bool = hasUint16ArraySupport()\n    <boolean>\n\n","hasUint32ArraySupport":"\nhasUint32ArraySupport()\n    Tests for native `Uint32Array` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `Uint32Array` support.\n\n    Examples\n    --------\n    > var bool = hasUint32ArraySupport()\n    <boolean>\n\n","hasUTF16SurrogatePairAt":"\nhasUTF16SurrogatePairAt( str, pos )\n    Tests if a position in a string marks the start of a UTF-16 surrogate pair.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    pos: integer\n        Position.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether surrogate pair exists at specified position.\n\n    Examples\n    --------\n    > var out = hasUTF16SurrogatePairAt( '🌷', 0 )\n    true\n    > out = hasUTF16SurrogatePairAt( '🌷', 1 )\n    false\n\n","hasWeakMapSupport":"\nhasWeakMapSupport()\n    Tests for native `WeakMap` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `WeakMap` support.\n\n    Examples\n    --------\n    > var bool = hasWeakMapSupport()\n    <boolean>\n\n","hasWeakSetSupport":"\nhasWeakSetSupport()\n    Tests for native `WeakSet` support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has `WeakSet` support.\n\n    Examples\n    --------\n    > var bool = hasWeakSetSupport()\n    <boolean>\n\n","hasWebAssemblySupport":"\nhasWebAssemblySupport()\n    Tests for native WebAssembly support.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an environment has native WebAssembly support.\n\n    Examples\n    --------\n    > var bool = hasWebAssemblySupport()\n    <boolean>\n\n","headercase":"\nheadercase( str )\n    Converts a string to HTTP header case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        HTTP header-cased string.\n\n    Examples\n    --------\n    > var out = headercase( 'Hello World!' )\n    'Hello-World'\n    > out = headercase( 'beep boop' )\n    'Beep-Boop'\n\n    See Also\n    --------\n    camelcase, kebabcase, pascalcase, snakecase","HERNDON_VENUS_SEMIDIAMETERS":"\nHERNDON_VENUS_SEMIDIAMETERS()\n    Returns fifteen observations of the vertical semidiameter of Venus, made by\n    Lieutenant Herndon, with the meridian circle at Washington, in the year\n    1846.\n\n    This dataset is a classic dataset commonly used in examples demonstrating\n    outlier detection.\n\n    Returns\n    -------\n    out: Array<number>\n        Observations.\n\n    Examples\n    --------\n    > var d = HERNDON_VENUS_SEMIDIAMETERS()\n    [ -0.30, -0.44, ..., 0.39, 0.10 ]\n\n    References\n    ----------\n    - Chauvenet, William. 1868. _A Manual of Spherical and Practical Astronomy_.\n    5th ed. Vol. 5. London, England: Trübner & Co.\n    - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n    Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n    of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n    - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n    Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n    00401706.1969.10490657.\n    - Tietjen, Gary L., and Roger H. Moore. 1972. \"Some Grubbs-Type Statistics\n    for the Detection of Several Outliers.\" _Technometrics_ 14 (3). Taylor &\n    Francis: 583–97. doi:10.1080/00401706.1972.10488948.\n\n","homedir":"\nhomedir()\n    Returns the current user's home directory.\n\n    If unable to locate a home directory, the function returns `null`.\n\n    Returns\n    -------\n    out: string|null\n        Home directory.\n\n    Examples\n    --------\n    > var home = homedir()\n    e.g., '/Users/<username>'\n\n    See Also\n    --------\n    configdir, tmpdir\n","HOURS_IN_DAY":"\nHOURS_IN_DAY\n    Number of hours in a day.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var days = 3.14;\n    > var hrs = days * HOURS_IN_DAY\n    75.36\n\n    See Also\n    --------\n    HOURS_IN_WEEK\n","HOURS_IN_WEEK":"\nHOURS_IN_WEEK\n    Number of hours in a week.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var wks = 3.14;\n    > var hrs = wks * HOURS_IN_WEEK\n    527.52\n\n    See Also\n    --------\n    HOURS_IN_DAY\n","hoursInMonth":"\nhoursInMonth( [month[, year]] )\n    Returns the number of hours in a month.\n\n    By default, the function returns the number of hours in the current month of\n    the current year (according to local time). To determine the number of hours\n    for a particular month and year, provide `month` and `year` arguments.\n\n    A `month` may be either a month's integer value, three letter abbreviation,\n    or full name (case insensitive).\n\n    The function's return value is a generalization and does **not** take into\n    account inaccuracies due to daylight savings conventions, crossing\n    timezones, or other complications with time and dates.\n\n    Parameters\n    ----------\n    month: string|Date|integer (optional)\n        Month.\n\n    year: integer (optional)\n        Year.\n\n    Returns\n    -------\n    out: integer\n        Hours in a month.\n\n    Examples\n    --------\n    > var num = hoursInMonth()\n    <number>\n    > num = hoursInMonth( 2 )\n    <number>\n    > num = hoursInMonth( 2, 2016 )\n    696\n    > num = hoursInMonth( 2, 2017 )\n    672\n\n    // Other ways to supply month:\n    > num = hoursInMonth( 'feb', 2016 )\n    696\n    > num = hoursInMonth( 'february', 2016 )\n    696\n\n    See Also\n    --------\n    hoursInYear\n","hoursInYear":"\nhoursInYear( [value] )\n    Returns the number of hours in a year according to the Gregorian calendar.\n\n    By default, the function returns the number of hours in the current year\n    (according to local time). To determine the number of hours for a particular\n    year, provide either a year or a `Date` object.\n\n    The function's return value is a generalization and does **not** take into\n    account inaccuracies due to daylight savings conventions, crossing\n    timezones, or other complications with time and dates.\n\n    Parameters\n    ----------\n    value: integer|Date (optional)\n        Year or `Date` object.\n\n    Returns\n    -------\n    out: integer\n        Number of hours in a year.\n\n    Examples\n    --------\n    > var num = hoursInYear()\n    <number>\n    > num = hoursInYear( 2016 )\n    8784\n    > num = hoursInYear( 2017 )\n    8760\n\n    See Also\n    --------\n    hoursInMonth\n","httpServer":"\nhttpServer( [options,] [requestListener] )\n    Returns a function to create an HTTP server.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.port: integer (optional)\n        Server port. Default: `0` (i.e., randomly assigned).\n\n    options.maxport: integer (optional)\n        Max server port when port hunting. Default: `maxport = port`.\n\n    options.hostname: string (optional)\n        Server hostname.\n\n    options.address: string (optional)\n        Server address. Default: `'127.0.0.1'`.\n\n    requestListener: Function (optional)\n        Request callback.\n\n    Returns\n    -------\n    createServer: Function\n        Function to create an HTTP server.\n\n    Examples\n    --------\n    // Basic usage:\n    > var createServer = httpServer()\n    <Function>\n\n    // Provide a request callback:\n    > function onRequest( request, response ) {\n    ...    console.log( request.url );\n    ...    response.end( 'OK' );\n    ... };\n    > createServer = httpServer( onRequest )\n    <Function>\n\n    // Specify a specific port:\n    > var opts = { 'port': 7331 };\n    > createServer = httpServer( opts )\n    <Function>\n\n\ncreateServer( done )\n    Creates an HTTP server.\n\n    Parameters\n    ----------\n    done: Function\n        Callback to invoke after creating a server.\n\n    Examples\n    --------\n    > function done( error, server ) {\n    ...    if ( error ) {\n    ...        throw error;\n    ...    }\n    ...    console.log( 'Success!' );\n    ...    server.close();\n    ... };\n    > var createServer = httpServer();\n    > createServer( done );\n\n","identity":"\nidentity( x )\n    Identity function.\n\n    Parameters\n    ----------\n    x: any\n        Input value.\n\n    Returns\n    -------\n    out: any\n        Input value.\n\n    Examples\n    --------\n    > var v = identity( 3.14 )\n    3.14\n\n    See Also\n    --------\n    constantFunction\n","ifelse":"\nifelse( bool, x, y )\n    If a condition is truthy, returns `x`; otherwise, returns `y`.\n\n    Parameters\n    ----------\n    bool: boolean\n        Condition.\n\n    x: any\n        Value to return if a condition is truthy.\n\n    y: any\n        Value to return if a condition is falsy.\n\n    Returns\n    -------\n    z: any\n        Either `x` or `y`.\n\n    Examples\n    --------\n    > var z = ifelse( true, 1.0, -1.0 )\n    1.0\n    > z = ifelse( false, 1.0, -1.0 )\n    -1.0\n\n    See Also\n    --------\n    ifelseAsync, ifthen\n","ifelseAsync":"\nifelseAsync( predicate, x, y, done )\n    If a predicate function returns a truthy value, returns `x`; otherwise,\n    returns `y`.\n\n    A predicate function is provided a single argument:\n\n    - clbk: callback to invoke upon predicate completion.\n\n    The callback function accepts two arguments:\n\n    - error: error object.\n    - bool: condition used to determine whether to invoke `x` or `y`.\n\n    The `done` callback is invoked upon function completion and is provided at\n    most two arguments:\n\n    - error: error object.\n    - result: either `x` or `y`.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function.\n\n    x: any\n        Value to return if a condition is truthy.\n\n    y: any\n        Value to return if a condition is falsy.\n\n    done: Function\n        Callback to invoke upon completion.\n\n    Examples\n    --------\n    > function predicate( clbk ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         clbk( null, true );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > ifelseAsync( predicate, 'beep', 'boop', done )\n    'beep'\n\n    See Also\n    --------\n    ifthenAsync, ifelse\n","ifthen":"\nifthen( bool, x, y )\n    If a condition is truthy, invoke `x`; otherwise, invoke `y`.\n\n    Parameters\n    ----------\n    bool: boolean\n        Condition.\n\n    x: Function\n        Function to invoke if a condition is truthy.\n\n    y: Function\n        Function to invoke if a condition is falsy.\n\n    Returns\n    -------\n    z: any\n        Return value of either `x` or `y`.\n\n    Examples\n    --------\n    > function x() { return 1.0; };\n    > function y() { return -1.0; };\n    > var z = ifthen( true, x, y )\n    1.0\n    > z = ifthen( false, x, y )\n    -1.0\n\n    See Also\n    --------\n    ifthenAsync, ifelse\n","ifthenAsync":"\nifthenAsync( predicate, x, y, done )\n    If a predicate function returns a truthy value, invokes `x`; otherwise,\n    invokes `y`.\n\n    The predicate function is provided a single argument:\n\n    - clbk: callback to invoke upon predicate function completion.\n\n    The predicate function callback accepts two arguments:\n\n    - error: error object.\n    - bool: condition used to determine whether to invoke `x` or `y`.\n\n    Both `x` and `y` are provided a single argument:\n\n    - clbk: callback to invoke upon function completion.\n\n    The callback function accepts any number of arguments, with the first\n    argument reserved for providing an error.\n\n    If the error argument is falsy, the `done` callback is invoked with its\n    first argument as `null` and all other provided arguments.\n\n    If the error argument is truthy, the `done` callback is invoked with only an\n    error argument.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function.\n\n    x: Function\n        Function to invoke if a condition is truthy.\n\n    y: Function\n        Function to invoke if a condition is falsy.\n\n    done: Function\n        Callback to invoke upon completion.\n\n    Examples\n    --------\n    > function predicate( clbk ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         clbk( null, false );\n    ...     }\n    ... };\n    > function x( clbk ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         clbk( null, 'beep' );\n    ...     }\n    ... };\n    > function y( clbk ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         clbk( null, 'boop' );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > ifthenAsync( predicate, x, y, done )\n    'boop'\n\n    See Also\n    --------\n    ifelseAsync, ifthen\n","imag":"\nimag( z )\n    Returns the imaginary component of a double-precision complex floating-point\n    number.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    im: number\n        Imaginary component.\n\n    Examples\n    --------\n    > var z = new Complex128( 5.0, 3.0 );\n    > var im = imag( z )\n    3.0\n\n    See Also\n    --------\n    real, reim\n","imagf":"\nimagf( z )\n    Returns the imaginary component of a single-precision complex floating-point\n    number.\n\n    Parameters\n    ----------\n    z: Complex64\n        Complex number.\n\n    Returns\n    -------\n    im: number\n        Imaginary component.\n\n    Examples\n    --------\n    > var z = new Complex64( 5.0, 3.0 );\n    > var im = imagf( z )\n    3.0\n\n    See Also\n    --------\n    imag, realf, reimf\n","IMG_ACANTHUS_MOLLIS":"\nIMG_ACANTHUS_MOLLIS()\n    Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n    print *Acanthus mollis*.\n\n    Returns\n    -------\n    out: Buffer\n        Image data.\n\n    Examples\n    --------\n    > var img = IMG_ACANTHUS_MOLLIS()\n    <Buffer>\n\n    References\n    ----------\n    - Blossfeldt, Karl. 1928. *Acanthus mollis*. <http://www.getty.edu/art/\n    collection/objects/35443/karl-blossfeldt-acanthus-mollis-german-1928/>.\n\n    * Digital image courtesy of the Getty's Open Content Program. While there\n    are no restrictions or conditions on the use of open content images, the\n    Getty would appreciate a gratis copy of any scholarly publications in which\n    the images are reproduced in order to maintain the collection bibliography.\n    Copies may be sent to the attention of:\n\n      Open Content Program\n      Registrar's Office\n      The J. Paul Getty Museum\n      1200 Getty Center Drive, Suite 1000\n      Los Angeles, CA 90049\n\n    See Also\n    --------\n    IMG_ALLIUM_OREOPHILUM\n","IMG_AIRPLANE_FROM_ABOVE":"\nIMG_AIRPLANE_FROM_ABOVE()\n    Returns a `Buffer` containing image data of Fédèle Azari's gelatin silver\n    print of an airplane, viewed from above looking down.\n\n    Returns\n    -------\n    out: Buffer\n        Image data.\n\n    Examples\n    --------\n    > var img = IMG_AIRPLANE_FROM_ABOVE()\n    <Buffer>\n\n    References\n    ----------\n    - Azari, Fédèle. 1929. (no title). <http://www.getty.edu/art/collection/\n    objects/134512/fedele-azari-airplane-viewed-from-above-looking-down-italian-\n    1914-1929/>.\n\n    * Digital image courtesy of the Getty's Open Content Program. While there\n    are no restrictions or conditions on the use of open content images, the\n    Getty would appreciate a gratis copy of any scholarly publications in which\n    the images are reproduced in order to maintain the collection bibliography.\n    Copies may be sent to the attention of:\n\n      Open Content Program\n      Registrar's Office\n      The J. Paul Getty Museum\n      1200 Getty Center Drive, Suite 1000\n      Los Angeles, CA 90049\n\n","IMG_ALLIUM_OREOPHILUM":"\nIMG_ALLIUM_OREOPHILUM()\n    Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n    print *Allium ostrowskianum*.\n\n    Returns\n    -------\n    out: Buffer\n        Image data.\n\n    Examples\n    --------\n    > var img = IMG_ALLIUM_OREOPHILUM()\n    <Buffer>\n\n    References\n    ----------\n    - Blossfeldt, Karl. 1928. *Allium ostrowskianum*. <http://www.getty.edu/art/\n    collection/objects/35448/karl-blossfeldt-allium-ostrowskianum-\n    knoblauchpflanze-german-1928/>.\n\n    * Digital image courtesy of the Getty's Open Content Program. While there\n    are no restrictions or conditions on the use of open content images, the\n    Getty would appreciate a gratis copy of any scholarly publications in which\n    the images are reproduced in order to maintain the collection bibliography.\n    Copies may be sent to the attention of:\n\n      Open Content Program\n      Registrar's Office\n      The J. Paul Getty Museum\n      1200 Getty Center Drive, Suite 1000\n      Los Angeles, CA 90049\n\n    See Also\n    --------\n    IMG_ACANTHUS_MOLLIS\n","IMG_BLACK_CANYON":"\nIMG_BLACK_CANYON()\n    Returns a `Buffer` containing image data of Timothy H. O'Sullivan's albumen\n    silver print *Black Cañon, Colorado River, From Camp 8, Looking Above*.\n\n    Returns\n    -------\n    out: Buffer\n        Image data.\n\n    Examples\n    --------\n    > var img = IMG_BLACK_CANYON()\n    <Buffer>\n\n    References\n    ----------\n    - O'Sullivan, Timothy H. 1871. *Black Cañon, Colorado River, From Camp 8,\n    Looking Above*. <http://www.getty.edu/art/collection/objects/40209/timothy-\n    h-o'sullivan-black-canon-colorado-river-from-camp-8-looking-above-american-\n    1871/>.\n\n    * Digital image courtesy of the Getty's Open Content Program. While there\n    are no restrictions or conditions on the use of open content images, the\n    Getty would appreciate a gratis copy of any scholarly publications in which\n    the images are reproduced in order to maintain the collection bibliography.\n    Copies may be sent to the attention of:\n\n      Open Content Program\n      Registrar's Office\n      The J. Paul Getty Museum\n      1200 Getty Center Drive, Suite 1000\n      Los Angeles, CA 90049\n\n","IMG_DUST_BOWL_HOME":"\nIMG_DUST_BOWL_HOME()\n    Returns a `Buffer` containing image data of Dorothea Lange's gelatin silver\n    print of an abandoned Dust Bowl home.\n\n    Returns\n    -------\n    out: Buffer\n        Image data.\n\n    Examples\n    --------\n    > var img = IMG_DUST_BOWL_HOME()\n    <Buffer>\n\n    References\n    ----------\n    - Lange, Dorothea. 1940. *Abandoned Dust Bowl Home*. <http://www.getty.edu/\n    art/collection/objects/128362/dorothea-lange-abandoned-dust-bowl-home-\n    american-about-1935-1940/>.\n\n    * Digital image courtesy of the Getty's Open Content Program. While there\n    are no restrictions or conditions on the use of open content images, the\n    Getty would appreciate a gratis copy of any scholarly publications in which\n    the images are reproduced in order to maintain the collection bibliography.\n    Copies may be sent to the attention of:\n\n      Open Content Program\n      Registrar's Office\n      The J. Paul Getty Museum\n      1200 Getty Center Drive, Suite 1000\n      Los Angeles, CA 90049\n\n","IMG_FRENCH_ALPINE_LANDSCAPE":"\nIMG_FRENCH_ALPINE_LANDSCAPE()\n    Returns a `Buffer` containing image data of Adolphe Braun's carbon print of\n    a French alpine landscape.\n\n    Returns\n    -------\n    out: Buffer\n        Image data.\n\n    Examples\n    --------\n    > var img = IMG_FRENCH_ALPINE_LANDSCAPE()\n    <Buffer>\n\n    References\n    ----------\n    - Braun, Adolphe. 1870. (no title). <http://www.getty.edu/art/collection/\n    objects/54324/adolphe-braun-alpine-landscape-french-1865-1870/>.\n\n    * Digital image courtesy of the Getty's Open Content Program. While there\n    are no restrictions or conditions on the use of open content images, the\n    Getty would appreciate a gratis copy of any scholarly publications in which\n    the images are reproduced in order to maintain the collection bibliography.\n    Copies may be sent to the attention of:\n\n      Open Content Program\n      Registrar's Office\n      The J. Paul Getty Museum\n      1200 Getty Center Drive, Suite 1000\n      Los Angeles, CA 90049\n\n","IMG_LOCOMOTION_HOUSE_CAT":"\nIMG_LOCOMOTION_HOUSE_CAT()\n    Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n    collotype of a house cat (24 views).\n\n    Returns\n    -------\n    out: Buffer\n        Image data.\n\n    Examples\n    --------\n    > var img = IMG_LOCOMOTION_HOUSE_CAT()\n    <Buffer>\n\n    References\n    ----------\n    - Muybridge, Eadweard J. 1887. *Animal Locomotion*. <http://www.getty.edu/\n    art/collection/objects/40918/eadweard-j-muybridge-animal-locomotion-american\n    -1887/>.\n\n    * Digital image courtesy of the Getty's Open Content Program. While there\n    are no restrictions or conditions on the use of open content images, the\n    Getty would appreciate a gratis copy of any scholarly publications in which\n    the images are reproduced in order to maintain the collection bibliography.\n    Copies may be sent to the attention of:\n\n      Open Content Program\n      Registrar's Office\n      The J. Paul Getty Museum\n      1200 Getty Center Drive, Suite 1000\n      Los Angeles, CA 90049\n\n    See Also\n    --------\n    IMG_LOCOMOTION_NUDE_MALE\n","IMG_LOCOMOTION_NUDE_MALE":"\nIMG_LOCOMOTION_NUDE_MALE()\n    Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n    collotype of a nude male moving in place (48 views).\n\n    Returns\n    -------\n    out: Buffer\n        Image data.\n\n    Examples\n    --------\n    > var img = IMG_LOCOMOTION_NUDE_MALE()\n    <Buffer>\n\n    References\n    ----------\n    - Muybridge, Eadweard J. 1887. *Animal Locomotion*. <http://www.getty.edu/\n    art/collection/objects/40918/eadweard-j-muybridge-animal-locomotion-american\n    -1887/>.\n\n    * Digital image courtesy of the Getty's Open Content Program. While there\n    are no restrictions or conditions on the use of open content images, the\n    Getty would appreciate a gratis copy of any scholarly publications in which\n    the images are reproduced in order to maintain the collection bibliography.\n    Copies may be sent to the attention of:\n\n      Open Content Program\n      Registrar's Office\n      The J. Paul Getty Museum\n      1200 Getty Center Drive, Suite 1000\n      Los Angeles, CA 90049\n\n    See Also\n    --------\n    IMG_LOCOMOTION_HOUSE_CAT\n","IMG_MARCH_PASTORAL":"\nIMG_MARCH_PASTORAL()\n    Returns a `Buffer` containing image data of Peter Henry Emerson's\n    photogravure of sheep in a pastoral setting.\n\n    Returns\n    -------\n    out: Buffer\n        Image data.\n\n    Examples\n    --------\n    > var img = IMG_MARCH_PASTORAL()\n    <Buffer>\n\n    References\n    ----------\n    - Emerson, Peter Henry. 1888. *A March Pastoral*. <http://www.getty.edu/art/\n    collection/objects/141994/peter-henry-emerson-a-march-pastoral-suffolk-\n    british-1888/>.\n\n    * Digital image courtesy of the Getty's Open Content Program. While there\n    are no restrictions or conditions on the use of open content images, the\n    Getty would appreciate a gratis copy of any scholarly publications in which\n    the images are reproduced in order to maintain the collection bibliography.\n    Copies may be sent to the attention of:\n\n      Open Content Program\n      Registrar's Office\n      The J. Paul Getty Museum\n      1200 Getty Center Drive, Suite 1000\n      Los Angeles, CA 90049\n\n","IMG_NAGASAKI_BOATS":"\nIMG_NAGASAKI_BOATS()\n    Returns a `Buffer` containing image data of Felice Beato's albumen silver\n    print of boats in a river in Nagasaki.\n\n    Returns\n    -------\n    out: Buffer\n        Image data.\n\n    Examples\n    --------\n    > var img = IMG_NAGASAKI_BOATS()\n    <Buffer>\n\n    References\n    ----------\n    - Beato, Felice. 1865. (no title). <http://www.getty.edu/art/collection/\n    objects/241797/felice-beato-boats-in-river-nagasaki-british-about-1865/>.\n\n    * Digital image courtesy of the Getty's Open Content Program. While there\n    are no restrictions or conditions on the use of open content images, the\n    Getty would appreciate a gratis copy of any scholarly publications in which\n    the images are reproduced in order to maintain the collection bibliography.\n    Copies may be sent to the attention of:\n\n      Open Content Program\n      Registrar's Office\n      The J. Paul Getty Museum\n      1200 Getty Center Drive, Suite 1000\n      Los Angeles, CA 90049\n\n","incrapcorr":"\nincrapcorr( [mx, my] )\n    Returns an accumulator function which incrementally computes the absolute\n    value of the sample Pearson product-moment correlation coefficient.\n\n    If provided values, the accumulator function returns an updated accumulated\n    value. If not provided values, the accumulator function returns the current\n    accumulated value.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    mx: number (optional)\n        Known mean.\n\n    my: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrapcorr();\n    > var ar = accumulator()\n    null\n    > ar = accumulator( 2.0, 1.0 )\n    0.0\n    > ar = accumulator( -5.0, 3.14 )\n    ~1.0\n    > ar = accumulator()\n    ~1.0\n\n    See Also\n    --------\n    incrmapcorr, incrpcorr, incrpcorr2\n","incrBinaryClassification":"\nincrBinaryClassification( N[, options] )\n    Returns an accumulator function which incrementally performs binary\n    classification using stochastic gradient descent (SGD).\n\n    If provided a feature vector and response value, the accumulator function\n    updates a binary classification model and returns updated model\n    coefficients.\n\n    If not provided a feature vector and response value, the accumulator\n    function returns the current model coefficients.\n\n    Stochastic gradient descent is sensitive to the scaling of the features. One\n    is advised to either scale each feature to `[0,1]` or `[-1,1]` or to\n    transform the features into z-scores with zero mean and unit variance. One\n    should keep in mind that the same scaling has to be applied to training data\n    in order to obtain accurate predictions.\n\n    In general, the more data provided to an accumulator, the more reliable the\n    model predictions.\n\n    Parameters\n    ----------\n    N: integer\n        Number of features.\n\n    options: Object (optional)\n        Function options.\n\n    options.intercept: boolean (optional)\n        Boolean indicating whether to include an intercept. Default: true.\n\n    options.lambda: number (optional)\n        Regularization parameter. Default: 1.0e-4.\n\n    options.learningRate: ArrayLike (optional)\n        Learning rate function and associated (optional) parameters. The first\n        array element specifies the learning rate function and must be one of\n        the following:\n\n        - ['constant', ...]: constant learning rate function. To set the\n        learning rate, provide a second array element. By default, when the\n        learn rate function is 'constant', the learning rate is set to 0.02.\n\n        - ['basic']: basic learning rate function according to the formula\n        `10/(10+t)` where `t` is the current iteration.\n\n        - ['invscaling', ...]: inverse scaling learning rate function according\n        to the formula `eta0/pow(t, power_t)` where `eta0` is the initial\n        learning rate and `power_t` is the exponent controlling how quickly the\n        learning rate decreases. To set the initial learning rate, provide a\n        second array element. By default, the initial learning rate is 0.02. To\n        set the exponent, provide a third array element. By default, the\n        exponent is 0.5.\n\n        - ['pegasos']: Pegasos learning rate function according to the formula\n        `1/(lambda*t)` where `t` is the current iteration and `lambda` is the\n        regularization parameter.\n\n        Default: ['basic'].\n\n    options.loss: string (optional)\n        Loss function. Must be one of the following:\n\n        - hinge: hinge loss function. Corresponds to a soft-margin linear\n        Support Vector Machine (SVM), which can handle non-linearly separable\n        data.\n\n        - log: logistic loss function. Corresponds to Logistic Regression.\n\n        - modifiedHuber: Huber loss function variant for classification.\n\n        - perceptron: hinge loss function without a margin. Corresponds to the\n        original Perceptron by Rosenblatt.\n\n        - squaredHinge: squared hinge loss function SVM (L2-SVM).\n\n        Default: 'log'.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    acc.predict: Function\n        Predicts response values for one ore more observation vectors. Provide a\n        second argument to specify the prediction type. Must be one of the\n        following: 'label', 'probability', or 'linear'. Default: 'label'.\n\n        Note that the probability prediction type is only compatible with 'log'\n        and 'modifiedHuber' loss functions.\n\n    Examples\n    --------\n    // Create an accumulator:\n    > var opts = {};\n    > opts.intercept = true;\n    > opts.lambda = 1.0e-5;\n    > var acc = incrBinaryClassification( 3, opts );\n\n    // Update the model:\n    > var buf = new Float64Array( [ 2.3, 1.0, 5.0 ] );\n    > var x = array( buf );\n    > var coefs = acc( x, 1 )\n    <ndarray>\n\n    // Create a new observation vector:\n    > buf = new Float64Array( [ 2.3, 5.3, 8.6 ] );\n    > x = array( buf );\n\n    // Predict the response value:\n    > var yhat = acc.predict( x )\n    <ndarray>\n\n    See Also\n    --------\n    incrSGDRegression\n","incrcount":"\nincrcount()\n    Returns an accumulator function which incrementally updates a count.\n\n    If provided a value, the accumulator function returns an updated count. If\n    not provided a value, the accumulator function returns the current count.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrcount();\n    > var v = accumulator()\n    0\n    > v = accumulator( 2.0 )\n    1\n    > v = accumulator( -5.0 )\n    2\n    > v = accumulator()\n    2\n\n    See Also\n    --------\n    incrmean, incrsum, incrsummary\n","incrcovariance":"\nincrcovariance( [mx, my] )\n    Returns an accumulator function which incrementally computes an unbiased\n    sample covariance.\n\n    If provided values, the accumulator function returns an updated unbiased\n    sample covariance. If not provided values, the accumulator function returns\n    the current unbiased sample covariance.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    mx: number (optional)\n        Known mean.\n\n    my: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrcovariance();\n    > var v = accumulator()\n    null\n    > v = accumulator( 2.0, 1.0 )\n    0.0\n    > v = accumulator( -5.0, 3.14 )\n    ~-7.49\n    > v = accumulator()\n    ~-7.49\n\n    See Also\n    --------\n    incrmcovariance, incrpcorr, incrvariance\n","incrcovmat":"\nincrcovmat( out[, means] )\n    Returns an accumulator function which incrementally computes an unbiased\n    sample covariance matrix.\n\n    If provided a data vector, the accumulator function returns an updated\n    unbiased sample covariance matrix. If not provided a data vector, the\n    accumulator function returns the current unbiased sample covariance matrix.\n\n    Parameters\n    ----------\n    out: integer|ndarray\n        Order of the covariance matrix or a square 2-dimensional ndarray for\n        storing the covariance matrix.\n\n    means: ndarray (optional)\n        Known means.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrcovmat( 2 );\n    > var out = accumulator()\n    <ndarray>\n    > var buf = new Float64Array( 2 );\n    > var shape = [ 2 ];\n    > var strides = [ 1 ];\n    > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n    > v.set( 0, 2.0 );\n    > v.set( 1, 1.0 );\n    > out = accumulator( v )\n    <ndarray>\n    > v.set( 0, -5.0 );\n    > v.set( 1, 3.14 );\n    > out = accumulator( v )\n    <ndarray>\n    > out = accumulator()\n    <ndarray>\n\n    See Also\n    --------\n    incrcovariance, incrpcorrmat\n","incrcv":"\nincrcv( [mean] )\n    Returns an accumulator function which incrementally computes the coefficient\n    of variation (CV).\n\n    If provided a value, the accumulator function returns an updated accumulated\n    value. If not provided a value, the accumulator function returns the current\n    accumulated value.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    mean: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrcv();\n    > var cv = accumulator()\n    null\n    > cv = accumulator( 2.0 )\n    0.0\n    > cv = accumulator( 1.0 )\n    ~0.47\n    > cv = accumulator()\n    ~0.47\n\n    See Also\n    --------\n    incrmean, incrmcv, incrstdev, incrvmr\n","increwmean":"\nincrewmean( α )\n    Returns an accumulator function which incrementally computes an\n    exponentially weighted mean, where α is a smoothing factor between 0 and 1.\n\n    If provided a value, the accumulator function returns an updated mean. If\n    not provided a value, the accumulator function returns the current mean.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    α: number\n        Smoothing factor (value between 0 and 1).\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = increwmean( 0.5 );\n    > var v = accumulator()\n    null\n    > v = accumulator( 2.0 )\n    2.0\n    > v = accumulator( -5.0 )\n    -1.5\n    > v = accumulator()\n    -1.5\n\n    See Also\n    --------\n    increwvariance, incrmean, incrmmean, incrwmean\n","increwstdev":"\nincrewstdev( α )\n    Returns an accumulator function which incrementally computes an\n    exponentially weighted standard deviation, where α is a smoothing factor\n    between 0 and 1.\n\n    If provided a value, the accumulator function returns an updated standard\n    deviation. If not provided a value, the accumulator function returns the\n    current standard deviation.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    α: number\n        Smoothing factor (value between 0 and 1).\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = increwstdev( 0.5 );\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    0.0\n    > s = accumulator( -5.0 )\n    3.5\n    > s = accumulator()\n    3.5\n\n    See Also\n    --------\n    increwvariance, incrmstdev, incrstdev\n","increwvariance":"\nincrewvariance( α )\n    Returns an accumulator function which incrementally computes an\n    exponentially weighted variance, where α is a smoothing factor between 0 and\n    1.\n\n    If provided a value, the accumulator function returns an updated variance.\n    If not provided a value, the accumulator function returns the current\n    variance.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    α: number\n        Smoothing factor (value between 0 and 1).\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = increwvariance( 0.5 );\n    > var v = accumulator()\n    null\n    > v = accumulator( 2.0 )\n    0.0\n    > v = accumulator( -5.0 )\n    12.25\n    > v = accumulator()\n    12.25\n\n    See Also\n    --------\n    increwmean, increwstdev, incrvariance, incrmvariance\n","incrgmean":"\nincrgmean()\n    Returns an accumulator function which incrementally computes a geometric\n    mean.\n\n    If provided a value, the accumulator function returns an updated geometric\n    mean. If not provided a value, the accumulator function returns the current\n    geometric mean.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    If provided a negative value, the accumulated value is `NaN` for all future\n    invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrgmean();\n    > var v = accumulator()\n    null\n    > v = accumulator( 2.0 )\n    2.0\n    > v = accumulator( 5.0 )\n    ~3.16\n    > v = accumulator()\n    ~3.16\n\n    See Also\n    --------\n    incrhmean, incrmean, incrmgmean, incrsummary\n","incrgrubbs":"\nincrgrubbs( [options] )\n    Returns an accumulator function which incrementally performs Grubbs' test\n    for detecting outliers.\n\n    Grubbs' test assumes that data is normally distributed. Accordingly, one\n    should first verify that the data can be reasonably approximated by a normal\n    distribution before applying the Grubbs' test.\n\n    If provided a value, the accumulator function returns updated test results.\n    If not provided a value, the accumulator function returns the current test\n    results.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the test statistic is `NaN` for all future invocations.\n\n    The accumulator must be provided *at least* three data points before\n    performing Grubbs' test. Until at least three data points are provided, the\n    accumulator returns `null`.\n\n    The accumulator function returns an object having the following fields:\n\n    - rejected: boolean indicating whether the null hypothesis should be\n    rejected.\n    - alpha: significance level.\n    - criticalValue: critical value.\n    - statistic: test statistic.\n    - df: degrees of freedom.\n    - mean: sample mean.\n    - sd: corrected sample standard deviation.\n    - min: minimum value.\n    - max: maximum value.\n    - alt: alternative hypothesis.\n    - method: method name.\n    - print: method for pretty-printing test output.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.alpha: number (optional)\n        Significance level. Default: 0.05.\n\n    options.alternative: string (optional)\n        Alternative hypothesis. The option may be one of the following values:\n\n        - 'two-sided': test whether the minimum or maximum value is an outlier.\n        - 'min': test whether the minimum value is an outlier.\n        - 'max': test whether the maximum value is an outlier.\n\n        Default: 'two-sided'.\n\n    options.init: integer (optional)\n        Number of data points the accumulator should use to compute initial\n        statistics *before* testing for an outlier. Until the accumulator is\n        provided the number of data points specified by this option, the\n        accumulator returns `null`. Default: 100.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var acc = incrgrubbs();\n    > var res = acc()\n    null\n    > for ( var i = 0; i < 200; i++ ) {\n    ...     res = acc( base.random.normal( 10.0, 5.0 ) );\n    ... };\n    > res.print()\n\n    References\n    ----------\n    - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n    Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n    of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n    - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n    Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n    00401706.1969.10490657.\n\n    See Also\n    --------\n    incrmgrubbs\n","incrhmean":"\nincrhmean()\n    Returns an accumulator function which incrementally computes a harmonic\n    mean.\n\n    If provided a value, the accumulator function returns an updated harmonic\n    mean. If not provided a value, the accumulator function returns the current\n    harmonic mean.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrhmean();\n    > var v = accumulator()\n    null\n    > v = accumulator( 2.0 )\n    2.0\n    > v = accumulator( 5.0 )\n    ~2.86\n    > v = accumulator()\n    ~2.86\n\n    See Also\n    --------\n    incrgmean, incrmean, incrmhmean, incrsummary\n","incrkmeans":"\nincrkmeans( k[, ndims][, options] )\n    Returns an accumulator function which incrementally partitions data into `k`\n    clusters.\n\n    If not provided initial centroids, the accumulator caches data vectors for\n    subsequent centroid initialization. Until an accumulator computes initial\n    centroids, an accumulator returns `null`.\n\n    Once an accumulator has initial centroids (either provided or computed), if\n    provided a data vector, the accumulator function returns updated cluster\n    results. If not provided a data vector, the accumulator function returns the\n    current cluster results.\n\n    Cluster results are comprised of the following:\n\n    - centroids: a `k x ndims` matrix containing centroid locations. Each\n      centroid is the component-wise mean of the data points assigned to a\n      centroid's corresponding cluster.\n    - stats: a `k x 4` matrix containing cluster statistics.\n\n    Cluster statistics consists of the following columns:\n\n    - 0: number of data points assigned to a cluster.\n    - 1: total within-cluster sum of squared distances.\n    - 2: arithmetic mean of squared distances.\n    - 3: corrected sample standard deviation of squared distances.\n\n    Because an accumulator incrementally partitions data, one should *not*\n    expect cluster statistics to match similar statistics had provided data been\n    analyzed via a batch algorithm. In an incremental context, data points which\n    would not be considered part of a particular cluster when analyzed via a\n    batch algorithm may contribute to that cluster's statistics when analyzed\n    incrementally.\n\n    In general, the more data provided to an accumulator, the more reliable the\n    cluster statistics.\n\n    Parameters\n    ----------\n    k: integer|ndarray\n        Number of clusters or a `k x ndims` matrix containing initial centroids.\n\n    ndims: integer (optional)\n        Number of dimensions. This argument must accompany an integer-valued\n        first argument.\n\n    options: Object (optional)\n        Function options.\n\n    options.metric: string (optional)\n        Distance metric. Must be one of the following: 'euclidean', 'cosine', or\n        'correlation'. Default: 'euclidean'.\n\n    options.init: ArrayLike (optional)\n        Centroid initialization method and associated (optional) parameters. The\n        first array element specifies the initialization method and must be one\n        of the following: 'kmeans++', 'sample', or 'forgy'. The second array\n        element specifies the number of data points to use when calculating\n        initial centroids. When performing kmeans++ initialization, the third\n        array element specifies the number of trials to perform when randomly\n        selecting candidate centroids. Typically, more trials is correlated with\n        initial centroids which lead to better clustering; however, a greater\n        number of trials increases computational overhead. Default: ['kmeans++',\n        k, 2+⌊ln(k)⌋ ].\n\n    options.normalize: boolean (optional)\n        Boolean indicating whether to normalize incoming data. This option is\n        only relevant for non-Euclidean distance metrics. If set to `true`, an\n        accumulator partitioning data based on cosine distance normalizes\n        provided data to unit Euclidean length. If set to `true`, an accumulator\n        partitioning data based on correlation distance first centers provided\n        data and then normalizes data dimensions to have zero mean and unit\n        variance. If this option is set to `false` and the metric is either\n        cosine or correlation distance, then incoming data *must* already be\n        normalized. Default: true.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy incoming data to prevent mutation\n        during normalization. Default: true.\n\n    options.seed: any (optional)\n        PRNG seed. Setting this option is useful when wanting reproducible\n        initial centroids.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    acc.predict: Function\n        Predicts centroid assignment for each data point in a provided matrix.\n        To specify an output vector, provide a 1-dimensional ndarray as the\n        first argument. Each element in the returned vector corresponds to a\n        predicted cluster index for a respective data point.\n\n    Examples\n    --------\n    > var accumulator = incrkmeans( 5, 2 );\n    > var buf = new Float64Array( 2 );\n    > var shape = [ 2 ];\n    > var strides = [ 1 ];\n    > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n    > v.set( 0, 2.0 );\n    > v.set( 1, 1.0 );\n    > out = accumulator( v );\n    > v.set( 0, -5.0 );\n    > v.set( 1, 3.14 );\n    > out = accumulator( v );\n\n","incrkurtosis":"\nincrkurtosis()\n    Returns an accumulator function which incrementally computes a corrected\n    sample excess kurtosis.\n\n    If provided a value, the accumulator function returns an updated corrected\n    sample excess kurtosis. If not provided a value, the accumulator function\n    returns the current corrected sample excess kurtosis.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrkurtosis();\n    > var v = accumulator( 2.0 )\n    null\n    > v = accumulator( 2.0 )\n    null\n    > v = accumulator( -4.0 )\n    null\n    > v = accumulator( -4.0 )\n    -6.0\n\n    See Also\n    --------\n    incrmean, incrskewness, incrstdev, incrsummary, incrvariance\n","incrmaape":"\nincrmaape()\n    Returns an accumulator function which incrementally computes the mean\n    arctangent absolute percentage error (MAAPE).\n\n    If provided input values, the accumulator function returns an updated mean\n    arctangent absolute percentage error. If not provided input values, the\n    accumulator function returns the current mean arctangent absolute percentage\n    error.\n\n    Note that, unlike the mean absolute percentage error (MAPE), the mean\n    arctangent absolute percentage error is expressed in radians on the interval\n    [0,π/2].\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmaape();\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    ~0.3218\n    > m = accumulator( 5.0, 2.0 )\n    ~0.6523\n    > m = accumulator()\n    ~0.6523\n\n    See Also\n    --------\n    incrmae, incrmape, incrmean, incrmmaape\n","incrmae":"\nincrmae()\n    Returns an accumulator function which incrementally computes the mean\n    absolute error (MAE).\n\n    If provided input values, the accumulator function returns an updated mean\n    absolute error. If not provided input values, the accumulator function\n    returns the current mean absolute error.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmae();\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    1.0\n    > m = accumulator( -5.0, 2.0 )\n    4.0\n    > m = accumulator()\n    4.0\n\n    See Also\n    --------\n    incrmape, incrme, incrmean, incrmmae\n","incrmapcorr":"\nincrmapcorr( W[, mx, my] )\n    Returns an accumulator function which incrementally computes a moving\n    sample absolute Pearson product-moment correlation coefficient.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving sample absolute correlation coefficient.\n\n    If provided values, the accumulator function returns an updated moving\n    sample absolute correlation coefficient. If not provided values, the\n    accumulator function returns the current moving sample absolute correlation\n    coefficient.\n\n    As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n    returned values are calculated from smaller sample sizes. Until the window\n    is full, each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    mx: number (optional)\n        Known mean.\n\n    my: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmapcorr( 3 );\n    > var ar = accumulator()\n    null\n    > ar = accumulator( 2.0, 1.0 )\n    0.0\n    > ar = accumulator( -5.0, 3.14 )\n    ~1.0\n    > ar = accumulator( 3.0, -1.0 )\n    ~0.925\n    > ar = accumulator( 5.0, -9.5 )\n    ~0.863\n    > ar = accumulator()\n    ~0.863\n\n    See Also\n    --------\n    incrapcorr, incrmpcorr, incrmpcorr2\n","incrmape":"\nincrmape()\n    Returns an accumulator function which incrementally computes the mean\n    absolute percentage error (MAPE).\n\n    If provided input values, the accumulator function returns an updated mean\n    absolute percentage error. If not provided input values, the accumulator\n    function returns the current mean absolute percentage error.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmape();\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    ~33.33\n    > m = accumulator( 5.0, 2.0 )\n    ~91.67\n    > m = accumulator()\n    ~91.67\n\n    See Also\n    --------\n    incrmaape, incrmae, incrmean, incrmmape\n","incrmax":"\nincrmax()\n    Returns an accumulator function which incrementally computes a maximum\n    value.\n\n    If provided a value, the accumulator function returns an updated maximum\n    value. If not provided a value, the accumulator function returns the current\n    maximum value.\n\n    If provided `NaN`, the maximum value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmax();\n    > var m = accumulator()\n    null\n    > m = accumulator( 3.14 )\n    3.14\n    > m = accumulator( -5.0 )\n    3.14\n    > m = accumulator( 10.1 )\n    10.1\n    > m = accumulator()\n    10.1\n\n    See Also\n    --------\n    incrmidrange, incrmin, incrmmax, incrrange, incrsummary\n","incrmaxabs":"\nincrmaxabs()\n    Returns an accumulator function which incrementally computes a maximum\n    absolute value.\n\n    If provided a value, the accumulator function returns an updated maximum\n    absolute value. If not provided a value, the accumulator function returns\n    the current maximum absolute value.\n\n    If provided `NaN`, the maximum value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmaxabs();\n    > var m = accumulator()\n    null\n    > m = accumulator( 3.14 )\n    3.14\n    > m = accumulator( -5.0 )\n    5.0\n    > m = accumulator( 10.1 )\n    10.1\n    > m = accumulator()\n    10.1\n\n    See Also\n    --------\n    incrmax, incrminabs, incrmmaxabs\n","incrmcovariance":"\nincrmcovariance( W[, mx, my] )\n    Returns an accumulator function which incrementally computes a moving\n    unbiased sample covariance.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving unbiased sample covariance.\n\n    If provided values, the accumulator function returns an updated moving\n    unbiased sample covariance. If not provided values, the accumulator function\n    returns the current moving unbiased sample covariance.\n\n    As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n    returned values are calculated from smaller sample sizes. Until the window\n    is full, each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    mx: number (optional)\n        Known mean.\n\n    my: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmcovariance( 3 );\n    > var v = accumulator()\n    null\n    > v = accumulator( 2.0, 1.0 )\n    0.0\n    > v = accumulator( -5.0, 3.14 )\n    ~-7.49\n    > v = accumulator( 3.0, -1.0 )\n    -8.35\n    > v = accumulator( 5.0, -9.5 )\n    -29.42\n    > v = accumulator()\n    -29.42\n\n    See Also\n    --------\n    incrcovariance, incrmpcorr, incrmvariance\n","incrmcv":"\nincrmcv( W[, mean] )\n    Returns an accumulator function which incrementally computes a moving\n    coefficient of variation (CV).\n\n    The `W` parameter defines the number of values over which to compute the\n    moving coefficient of variation.\n\n    If provided a value, the accumulator function returns an updated moving\n    coefficient of variation. If not provided a value, the accumulator function\n    returns the current moving coefficient of variation.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    mean: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmcv( 3 );\n    > var cv = accumulator()\n    null\n    > cv = accumulator( 2.0 )\n    0.0\n    > cv = accumulator( 1.0 )\n    ~0.47\n    > cv = accumulator( 3.0 )\n    0.5\n    > cv = accumulator( 7.0 )\n    ~0.83\n    > cv = accumulator()\n    ~0.83\n\n    See Also\n    --------\n    incrcv, incrmmean, incrmstdev, incrmvmr\n","incrmda":"\nincrmda()\n    Returns an accumulator function which incrementally computes the mean\n    directional accuracy (MDA).\n\n    If provided input values, the accumulator function returns an updated mean\n    directional accuracy. If not provided input values, the accumulator function\n    returns the current mean directional accuracy.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmda();\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    1.0\n    > m = accumulator( -5.0, 4.0 )\n    0.5\n    > m = accumulator()\n    0.5\n\n    See Also\n    --------\n    incrmape, incrmmda\n","incrme":"\nincrme()\n    Returns an accumulator function which incrementally computes the mean error\n    (ME).\n\n    If provided input values, the accumulator function returns an updated mean\n    error. If not provided input values, the accumulator function returns the\n    current mean error.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrme();\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    1.0\n    > m = accumulator( -5.0, 2.0 )\n    4.0\n    > m = accumulator()\n    4.0\n\n    See Also\n    --------\n    incrmae, incrmean, incrmme\n","incrmean":"\nincrmean()\n    Returns an accumulator function which incrementally computes an arithmetic\n    mean.\n\n    If provided a value, the accumulator function returns an updated mean. If\n    not provided a value, the accumulator function returns the current mean.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmean();\n    > var mu = accumulator()\n    null\n    > mu = accumulator( 2.0 )\n    2.0\n    > mu = accumulator( -5.0 )\n    -1.5\n    > mu = accumulator()\n    -1.5\n\n    See Also\n    --------\n    incrmidrange, incrmmean, incrstdev, incrsum, incrsummary, incrvariance\n","incrmeanabs":"\nincrmeanabs()\n    Returns an accumulator function which incrementally computes an arithmetic\n    mean of absolute values.\n\n    If provided a value, the accumulator function returns an updated mean. If\n    not provided a value, the accumulator function returns the current mean.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmeanabs();\n    > var mu = accumulator()\n    null\n    > mu = accumulator( 2.0 )\n    2.0\n    > mu = accumulator( -5.0 )\n    3.5\n    > mu = accumulator()\n    3.5\n\n    See Also\n    --------\n    incrmean, incrmmeanabs, incrsumabs\n","incrmeanabs2":"\nincrmeanabs2()\n    Returns an accumulator function which incrementally computes an arithmetic\n    mean of squared absolute values.\n\n    If provided a value, the accumulator function returns an updated mean. If\n    not provided a value, the accumulator function returns the current mean.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmeanabs2();\n    > var mu = accumulator()\n    null\n    > mu = accumulator( 2.0 )\n    4.0\n    > mu = accumulator( -5.0 )\n    14.5\n    > mu = accumulator()\n    14.5\n\n    See Also\n    --------\n    incrmean, incrmeanabs, incrmmeanabs2, incrsumabs2\n","incrmeanstdev":"\nincrmeanstdev( [out] )\n    Returns an accumulator function which incrementally computes an arithmetic\n    mean and corrected sample standard deviation.\n\n    If provided a value, the accumulator function returns updated accumulated\n    values. If not provided a value, the accumulator function returns the\n    current accumulated values.\n\n    If provided `NaN`, the accumulated values are equal to `NaN` for all future\n    invocations.\n\n    Parameters\n    ----------\n    out: Array|TypedArray (optional)\n        Output array.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmeanstdev();\n    > var ms = accumulator()\n    null\n    > ms = accumulator( 2.0 )\n    [ 2.0, 0.0 ]\n    > ms = accumulator( -5.0 )\n    [ -1.5, ~4.95 ]\n    > ms = accumulator( 3.0 )\n    [ 0.0, ~4.36 ]\n    > ms = accumulator( 5.0 )\n    [ 1.25, ~4.35 ]\n    > ms = accumulator()\n    [ 1.25, ~4.35 ]\n\n    See Also\n    --------\n    incrmean, incrmeanvar, incrmmeanstdev, incrstdev\n","incrmeanvar":"\nincrmeanvar( [out] )\n    Returns an accumulator function which incrementally computes an arithmetic\n    mean and unbiased sample variance.\n\n    If provided a value, the accumulator function returns updated accumulated\n    values. If not provided a value, the accumulator function returns the\n    current accumulated values.\n\n    If provided `NaN`, the accumulated values are equal to `NaN` for all future\n    invocations.\n\n    Parameters\n    ----------\n    out: Array|TypedArray (optional)\n        Output array.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmeanvar();\n    > var mv = accumulator()\n    null\n    > mv = accumulator( 2.0 )\n    [ 2.0, 0.0 ]\n    > mv = accumulator( -5.0 )\n    [ -1.5, 24.5 ]\n    > mv = accumulator( 3.0 )\n    [ 0.0, 19.0 ]\n    > mv = accumulator( 5.0 )\n    [ 1.25, ~18.92 ]\n    > mv = accumulator()\n    [ 1.25, ~18.92 ]\n\n    See Also\n    --------\n    incrmean, incrmeanstdev, incrmmeanvar, incrvariance\n","incrmgmean":"\nincrmgmean( W )\n    Returns an accumulator function which incrementally computes a moving\n    geometric mean.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving geometric mean.\n\n    If provided a value, the accumulator function returns an updated moving\n    geometric mean. If not provided a value, the accumulator function returns\n    the current moving geometric mean.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmgmean( 3 );\n    > var v = accumulator()\n    null\n    > v = accumulator( 2.0 )\n    2.0\n    > v = accumulator( 5.0 )\n    ~3.16\n    > v = accumulator( 3.0 )\n    ~3.11\n    > v = accumulator( 5.0 )\n    ~4.22\n    > v = accumulator()\n    ~4.22\n\n    See Also\n    --------\n    incrgmean, incrmhmean, incrmmean\n","incrmgrubbs":"\nincrmgrubbs( W[, options] )\n    Returns an accumulator function which incrementally performs a moving\n    Grubbs' test for detecting outliers.\n\n    Grubbs' test assumes that data is normally distributed. Accordingly, one\n    should first verify that the data can be reasonably approximated by a normal\n    distribution before applying the Grubbs' test.\n\n    The `W` parameter defines the number of values over which to perform Grubbs'\n    test. The minimum window size is 3.\n\n    If provided a value, the accumulator function returns updated test results.\n    If not provided a value, the accumulator function returns the current test\n    results.\n\n    Until provided `W` values, the accumulator function returns `null`.\n\n    The accumulator function returns an object having the following fields:\n\n    - rejected: boolean indicating whether the null hypothesis should be\n    rejected.\n    - alpha: significance level.\n    - criticalValue: critical value.\n    - statistic: test statistic.\n    - df: degrees of freedom.\n    - mean: sample mean.\n    - sd: corrected sample standard deviation.\n    - min: minimum value.\n    - max: maximum value.\n    - alt: alternative hypothesis.\n    - method: method name.\n    - print: method for pretty-printing test output.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    options: Object (optional)\n        Function options.\n\n    options.alpha: number (optional)\n        Significance level. Default: 0.05.\n\n    options.alternative: string (optional)\n        Alternative hypothesis. The option may be one of the following values:\n\n        - 'two-sided': test whether the minimum or maximum value is an outlier.\n        - 'min': test whether the minimum value is an outlier.\n        - 'max': test whether the maximum value is an outlier.\n\n        Default: 'two-sided'.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var acc = incrmgrubbs( 20 );\n    > var res = acc()\n    null\n    > for ( var i = 0; i < 200; i++ ) {\n    ...     res = acc( base.random.normal( 10.0, 5.0 ) );\n    ... };\n    > res.print()\n\n    References\n    ----------\n    - Grubbs, Frank E. 1950. \"Sample Criteria for Testing Outlying\n    Observations.\" _The Annals of Mathematical Statistics_ 21 (1). The Institute\n    of Mathematical Statistics: 27–58. doi:10.1214/aoms/1177729885.\n    - Grubbs, Frank E. 1969. \"Procedures for Detecting Outlying Observations in\n    Samples.\" _Technometrics_ 11 (1). Taylor & Francis: 1–21. doi:10.1080/\n    00401706.1969.10490657.\n\n    See Also\n    --------\n    incrgrubbs\n","incrmhmean":"\nincrmhmean( W )\n    Returns an accumulator function which incrementally computes a moving\n    harmonic mean.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving harmonic mean.\n\n    If provided a value, the accumulator function returns an updated moving\n    harmonic mean. If not provided a value, the accumulator function returns the\n    current moving harmonic mean.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmhmean( 3 );\n    > var v = accumulator()\n    null\n    > v = accumulator( 2.0 )\n    2.0\n    > v = accumulator( 5.0 )\n    ~2.86\n    > v = accumulator( 3.0 )\n    ~2.90\n    > v = accumulator( 5.0 )\n    ~4.09\n    > v = accumulator()\n    ~4.09\n\n    See Also\n    --------\n    incrhmean, incrmgmean, incrmmean\n","incrmidrange":"\nincrmidrange()\n    Returns an accumulator function which incrementally computes a mid-range.\n\n    The mid-range is the arithmetic mean of maximum and minimum values.\n    Accordingly, the mid-range is the midpoint of the range and a measure of\n    central tendency.\n\n    If provided a value, the accumulator function returns an updated mid-range.\n    If not provided a value, the accumulator function returns the current mid-\n    range.\n\n    If provided `NaN`, the mid-range is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmidrange();\n    > var v = accumulator()\n    null\n    > v = accumulator( 3.14 )\n    3.14\n    > v = accumulator( -5.0 )\n    ~-0.93\n    > v = accumulator( 10.1 )\n    2.55\n    > v = accumulator()\n    2.55\n\n    See Also\n    --------\n    incrmean, incrmax, incrmin, incrrange, incrsummary\n","incrmin":"\nincrmin()\n    Returns an accumulator function which incrementally computes a minimum\n    value.\n\n    If provided a value, the accumulator function returns an updated minimum\n    value. If not provided a value, the accumulator function returns the current\n    minimum value.\n\n    If provided `NaN`, the minimum value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmin();\n    > var m = accumulator()\n    null\n    > m = accumulator( 3.14 )\n    3.14\n    > m = accumulator( -5.0 )\n    -5.0\n    > m = accumulator( 10.1 )\n    -5.0\n    > m = accumulator()\n    -5.0\n\n    See Also\n    --------\n    incrmax, incrmidrange, incrmmin, incrrange, incrsummary\n","incrminabs":"\nincrminabs()\n    Returns an accumulator function which incrementally computes a minimum\n    absolute value.\n\n    If provided a value, the accumulator function returns an updated minimum\n    absolute value. If not provided a value, the accumulator function returns\n    the current minimum absolute value.\n\n    If provided `NaN`, the minimum value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrminabs();\n    > var m = accumulator()\n    null\n    > m = accumulator( 3.14 )\n    3.14\n    > m = accumulator( -5.0 )\n    3.14\n    > m = accumulator( 10.1 )\n    3.14\n    > m = accumulator()\n    3.14\n\n    See Also\n    --------\n    incrmaxabs, incrmin, incrmminabs\n","incrminmax":"\nincrminmax( [out] )\n    Returns an accumulator function which incrementally computes a minimum and\n    maximum.\n\n    If provided a value, the accumulator function returns an updated minimum and\n    maximum. If not provided a value, the accumulator function returns the\n    current minimum and maximum.\n\n    If provided `NaN`, the minimum and maximum values are equal to `NaN` for all\n    future invocations.\n\n    Parameters\n    ----------\n    out: Array|TypedArray (optional)\n        Output array.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrminmax();\n    > var mm = accumulator()\n    null\n    > mm = accumulator( 2.0 )\n    [ 2.0, 2.0 ]\n    > mm = accumulator( -5.0 )\n    [ -5.0, 2.0 ]\n    > mm = accumulator( 3.0 )\n    [ -5.0, 3.0 ]\n    > mm = accumulator( 5.0 )\n    [ -5.0, 5.0 ]\n    > mm = accumulator()\n    [ -5.0, 5.0 ]\n\n    See Also\n    --------\n    incrmax, incrmin, incrmminmax, incrrange\n","incrminmaxabs":"\nincrminmaxabs( [out] )\n    Returns an accumulator function which incrementally computes a minimum and\n    maximum absolute value.\n\n    If provided a value, the accumulator function returns an updated minimum and\n    maximum. If not provided a value, the accumulator function returns the\n    current minimum and maximum.\n\n    If provided `NaN`, the minimum and maximum values are equal to `NaN` for all\n    future invocations.\n\n    Parameters\n    ----------\n    out: Array|TypedArray (optional)\n        Output array.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrminmaxabs();\n    > var mm = accumulator()\n    null\n    > mm = accumulator( 2.0 )\n    [ 2.0, 2.0 ]\n    > mm = accumulator( -5.0 )\n    [ 2.0, 5.0 ]\n    > mm = accumulator( 3.0 )\n    [ 2.0, 5.0 ]\n    > mm = accumulator( 5.0 )\n    [ 2.0, 5.0 ]\n    > mm = accumulator()\n    [ 2.0, 5.0 ]\n\n    See Also\n    --------\n    incrmaxabs, incrminabs, incrminmax, incrmminmaxabs\n","incrmmaape":"\nincrmmaape( W )\n    Returns an accumulator function which incrementally computes a moving\n    mean arctangent absolute percentage error (MAAPE).\n\n    The `W` parameter defines the number of values over which to compute the\n    moving mean arctangent absolute percentage error.\n\n    If provided input values, the accumulator function returns an updated moving\n    mean arctangent absolute percentage error. If not provided input values, the\n    accumulator function returns the current moving mean arctangent absolute\n    percentage error.\n\n    Note that, unlike the mean absolute percentage error (MAPE), the mean\n    arctangent absolute percentage error is expressed in radians on the interval\n    [0,π/2].\n\n    As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n    returned values are calculated from smaller sample sizes. Until the window\n    is full, each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmaape( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    ~0.32\n    > m = accumulator( 5.0, 2.0 )\n    ~0.65\n    > m = accumulator( 3.0, 2.0 )\n    ~0.59\n    > m = accumulator( 2.0, 5.0 )\n    ~0.66\n    > m = accumulator()\n    ~0.66\n\n    See Also\n    --------\n    incrmaape, incrmmape, incrmmpe, incrmmean\n","incrmmae":"\nincrmmae( W )\n    Returns an accumulator function which incrementally computes a moving\n    mean absolute error (MAE).\n\n    The `W` parameter defines the number of values over which to compute the\n    moving mean absolute error.\n\n    If provided a value, the accumulator function returns an updated moving\n    mean absolute error. If not provided a value, the accumulator function\n    returns the current moving mean absolute error.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmae( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    1.0\n    > m = accumulator( -5.0, 2.0 )\n    4.0\n    > m = accumulator( 3.0, 2.0 )\n    3.0\n    > m = accumulator( 5.0, -2.0 )\n    5.0\n    > m = accumulator()\n    5.0\n\n    See Also\n    --------\n    incrmae, incrmme, incrmmean\n","incrmmape":"\nincrmmape( W )\n    Returns an accumulator function which incrementally computes a moving\n    mean absolute percentage error (MAPE).\n\n    The `W` parameter defines the number of values over which to compute the\n    moving mean absolute percentage error.\n\n    If provided input values, the accumulator function returns an updated moving\n    mean absolute percentage error. If not provided input values, the\n    accumulator function returns the current moving mean absolute percentage\n    error.\n\n    As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n    returned values are calculated from smaller sample sizes. Until the window\n    is full, each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmape( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    ~33.33\n    > m = accumulator( 5.0, 2.0 )\n    ~91.67\n    > m = accumulator( 3.0, 2.0 )\n    ~77.78\n    > m = accumulator( 2.0, 5.0 )\n    ~86.67\n    > m = accumulator()\n    ~86.67\n\n    See Also\n    --------\n    incrmape, incrmmaape, incrmmpe, incrmmean\n","incrmmax":"\nincrmmax( W )\n    Returns an accumulator function which incrementally computes a moving\n    maximum value.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving maximum.\n\n    If provided a value, the accumulator function returns an updated moving\n    maximum. If not provided a value, the accumulator function returns the\n    current moving maximum.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmax( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0 )\n    2.0\n    > m = accumulator( -5.0 )\n    2.0\n    > m = accumulator( 3.0 )\n    3.0\n    > m = accumulator( 5.0 )\n    5.0\n    > m = accumulator()\n    5.0\n\n    See Also\n    --------\n    incrmax, incrmmidrange, incrmmin, incrmrange, incrmsummary\n","incrmmaxabs":"\nincrmmaxabs( W )\n    Returns an accumulator function which incrementally computes a moving\n    maximum absolute value.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving maximum absolute value.\n\n    If provided a value, the accumulator function returns an updated moving\n    maximum absolute value. If not provided a value, the accumulator function\n    returns the current moving maximum absolute value.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmaxabs( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0 )\n    2.0\n    > m = accumulator( -5.0 )\n    5.0\n    > m = accumulator( 3.0 )\n    5.0\n    > m = accumulator( 5.0 )\n    5.0\n    > m = accumulator()\n    5.0\n\n    See Also\n    --------\n    incrmaxabs, incrmmax, incrmminabs\n","incrmmda":"\nincrmmda( W )\n    Returns an accumulator function which incrementally computes a moving\n    mean directional accuracy (MDA).\n\n    The `W` parameter defines the number of values over which to compute the\n    moving mean directional accuracy.\n\n    If provided input values, the accumulator function returns an updated moving\n    mean directional accuracy. If not provided input values, the accumulator\n    function returns the current moving mean directional accuracy.\n\n    As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n    returned values are calculated from smaller sample sizes. Until the window\n    is full, each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmda( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    1.0\n    > m = accumulator( 5.0, 2.0 )\n    0.5\n    > m = accumulator( 3.0, 2.0 )\n    ~0.33\n    > m = accumulator( 4.0, 5.0 )\n    ~0.33\n    > m = accumulator()\n    ~0.33\n\n    See Also\n    --------\n    incrmda, incrmmape\n","incrmme":"\nincrmme( W )\n    Returns an accumulator function which incrementally computes a moving\n    mean error (ME).\n\n    The `W` parameter defines the number of values over which to compute the\n    moving mean error.\n\n    If provided a value, the accumulator function returns an updated moving\n    mean error. If not provided a value, the accumulator function returns the\n    current moving mean error.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmme( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    1.0\n    > m = accumulator( -5.0, 2.0 )\n    4.0\n    > m = accumulator( 3.0, 2.0 )\n    ~2.33\n    > m = accumulator( 5.0, -2.0 )\n    ~-0.33\n    > m = accumulator()\n    ~-0.33\n\n    See Also\n    --------\n    incrme, incrmmae, incrmmean\n","incrmmean":"\nincrmmean( W )\n    Returns an accumulator function which incrementally computes a moving\n    arithmetic mean.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving mean.\n\n    If provided a value, the accumulator function returns an updated moving\n    mean. If not provided a value, the accumulator function returns the current\n    moving mean.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmean( 3 );\n    > var mu = accumulator()\n    null\n    > mu = accumulator( 2.0 )\n    2.0\n    > mu = accumulator( -5.0 )\n    -1.5\n    > mu = accumulator( 3.0 )\n    0.0\n    > mu = accumulator( 5.0 )\n    1.0\n    > mu = accumulator()\n    1.0\n\n    See Also\n    --------\n    incrmean, incrmsum, incrmstdev, incrmsummary, incrmvariance\n","incrmmeanabs":"\nincrmmeanabs( W )\n    Returns an accumulator function which incrementally computes a moving\n    arithmetic mean of absolute values.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving mean.\n\n    If provided a value, the accumulator function returns an updated moving\n    mean. If not provided a value, the accumulator function returns the current\n    moving mean.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmeanabs( 3 );\n    > var mu = accumulator()\n    null\n    > mu = accumulator( 2.0 )\n    2.0\n    > mu = accumulator( -5.0 )\n    3.5\n    > mu = accumulator( 3.0 )\n    ~3.33\n    > mu = accumulator( 5.0 )\n    ~4.33\n    > mu = accumulator()\n    ~4.33\n\n    See Also\n    --------\n    incrmeanabs, incrmmean, incrmsumabs\n","incrmmeanabs2":"\nincrmmeanabs2( W )\n    Returns an accumulator function which incrementally computes a moving\n    arithmetic mean of squared absolute values.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving mean.\n\n    If provided a value, the accumulator function returns an updated moving\n    mean. If not provided a value, the accumulator function returns the current\n    moving mean.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmeanabs2( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0 )\n    4.0\n    > m = accumulator( -5.0 )\n    14.5\n    > m = accumulator( 3.0 )\n    ~12.67\n    > m = accumulator( 5.0 )\n    ~19.67\n    > m = accumulator()\n    ~19.67\n\n    See Also\n    --------\n    incrmeanabs2, incrmmeanabs, incrmsumabs2\n","incrmmeanstdev":"\nincrmmeanstdev( [out,] W )\n    Returns an accumulator function which incrementally computes a moving\n    arithmetic mean and corrected sample standard deviation.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving arithmetic mean and corrected sample standard deviation.\n\n    If provided a value, the accumulator function returns updated accumulated\n    values. If not provided a value, the accumulator function returns the\n    current moving accumulated values.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    accumulated values are calculated from smaller sample sizes. Until the\n    window is full, each returned accumulated value is calculated from all\n    provided values.\n\n    Parameters\n    ----------\n    out: Array|TypedArray (optional)\n        Output array.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmeanstdev( 3 );\n    > var v = accumulator()\n    null\n    > v = accumulator( 2.0 )\n    [ 2.0, 0.0 ]\n    > v = accumulator( -5.0 )\n    [ -1.5, ~4.95 ]\n    > v = accumulator( 3.0 )\n    [ 0.0, ~4.36 ]\n    > v = accumulator( 5.0 )\n    [ 1.0, ~5.29 ]\n    > v = accumulator()\n    [ 1.0, ~5.29 ]\n\n    See Also\n    --------\n    incrmeanstdev, incrmmean, incrmmeanvar, incrmstdev\n","incrmmeanvar":"\nincrmmeanvar( [out,] W )\n    Returns an accumulator function which incrementally computes a moving\n    arithmetic mean and unbiased sample variance.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving arithmetic mean and unbiased sample variance.\n\n    If provided a value, the accumulator function returns updated accumulated\n    values. If not provided a value, the accumulator function returns the\n    current moving accumulated values.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    accumulated values are calculated from smaller sample sizes. Until the\n    window is full, each returned accumulated value is calculated from all\n    provided values.\n\n    Parameters\n    ----------\n    out: Array|TypedArray (optional)\n        Output array.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmeanvar( 3 );\n    > var v = accumulator()\n    null\n    > v = accumulator( 2.0 )\n    [ 2.0, 0.0 ]\n    > v = accumulator( -5.0 )\n    [ -1.5, 24.5 ]\n    > v = accumulator( 3.0 )\n    [ 0.0, 19.0 ]\n    > v = accumulator( 5.0 )\n    [ 1.0, 28.0 ]\n    > v = accumulator()\n    [ 1.0, 28.0 ]\n\n    See Also\n    --------\n    incrmeanvar, incrmmean, incrmmeanstdev, incrmvariance\n","incrmmidrange":"\nincrmmidrange( W )\n    Returns an accumulator function which incrementally computes a moving mid-\n    range.\n\n    The mid-range is the arithmetic mean of maximum and minimum values.\n    Accordingly, the mid-range is the midpoint of the range and a measure of\n    central tendency.\n\n    The `W` parameter defines the number of values over which to compute\n    the moving mid-range.\n\n    If provided a value, the accumulator function returns an updated moving mid-\n    range. If not provided a value, the accumulator function returns the current\n    moving mid-range.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmidrange( 3 );\n    > var mr = accumulator()\n    null\n    > mr = accumulator( 2.0 )\n    2.0\n    > mr = accumulator( -5.0 )\n    -1.5\n    > mr = accumulator( 3.0 )\n    -1.0\n    > mr = accumulator( 5.0 )\n    0.0\n    > mr = accumulator()\n    0.0\n\n    See Also\n    --------\n    incrmmean, incrmmax, incrmmin, incrmrange\n","incrmmin":"\nincrmmin( W )\n    Returns an accumulator function which incrementally computes a moving\n    minimum value.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving minimum.\n\n    If provided a value, the accumulator function returns an updated moving\n    minimum. If not provided a value, the accumulator function returns the\n    current moving minimum.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmin( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0 )\n    2.0\n    > m = accumulator( -5.0 )\n    -5.0\n    > m = accumulator( 3.0 )\n    -5.0\n    > m = accumulator( 5.0 )\n    -5.0\n    > m = accumulator()\n    -5.0\n\n    See Also\n    --------\n    incrmin, incrmmax, incrmmidrange, incrmrange, incrmsummary\n","incrmminabs":"\nincrmminabs( W )\n    Returns an accumulator function which incrementally computes a moving\n    minimum absolute value.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving minimum absolute value.\n\n    If provided a value, the accumulator function returns an updated moving\n    minimum absolute value. If not provided a value, the accumulator function\n    returns the current moving minimum absolute value.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmminabs( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0 )\n    2.0\n    > m = accumulator( -5.0 )\n    2.0\n    > m = accumulator( 3.0 )\n    2.0\n    > m = accumulator( 5.0 )\n    3.0\n    > m = accumulator()\n    3.0\n\n    See Also\n    --------\n    incrminabs, incrmmaxabs, incrmmin\n","incrmminmax":"\nincrmminmax( [out,] W )\n    Returns an accumulator function which incrementally computes a moving\n    minimum and maximum.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving minimum and maximum.\n\n    If provided a value, the accumulator function returns an updated moving\n    minimum and maximum. If not provided a value, the accumulator function\n    returns the current moving minimum and maximum.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    minimum and maximum values are calculated from smaller sample sizes. Until\n    the window is full, each returned minimum and maximum is calculated from all\n    provided values.\n\n    Parameters\n    ----------\n    out: Array|TypedArray (optional)\n        Output array.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmminmax( 3 );\n    > var mm = accumulator()\n    null\n    > mm = accumulator( 2.0 )\n    [ 2.0, 2.0 ]\n    > mm = accumulator( -5.0 )\n    [ -5.0, 2.0 ]\n    > mm = accumulator( 3.0 )\n    [ -5.0, 3.0 ]\n    > mm = accumulator( 5.0 )\n    [ -5.0, 5.0 ]\n    > mm = accumulator()\n    [ -5.0, 5.0 ]\n\n    See Also\n    --------\n    incrmax, incrmin, incrmmax, incrminmax, incrmmin, incrmrange\n","incrmminmaxabs":"\nincrmminmaxabs( [out,] W )\n    Returns an accumulator function which incrementally computes moving minimum\n    and maximum absolute values.\n\n    The `W` parameter defines the number of values over which to compute moving\n    minimum and maximum absolute values.\n\n    If provided a value, the accumulator function returns an updated moving\n    minimum and maximum. If not provided a value, the accumulator function\n    returns the current moving minimum and maximum.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    minimum and maximum values are calculated from smaller sample sizes. Until\n    the window is full, each returned minimum and maximum is calculated from all\n    provided values.\n\n    Parameters\n    ----------\n    out: Array|TypedArray (optional)\n        Output array.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmminmaxabs( 3 );\n    > var mm = accumulator()\n    null\n    > mm = accumulator( 2.0 )\n    [ 2.0, 2.0 ]\n    > mm = accumulator( -5.0 )\n    [ 2.0, 5.0 ]\n    > mm = accumulator( 3.0 )\n    [ 2.0, 5.0 ]\n    > mm = accumulator( 5.0 )\n    [ 3.0, 5.0 ]\n    > mm = accumulator()\n    [ 3.0, 5.0 ]\n\n    See Also\n    --------\n    incrminmaxabs, incrmmax, incrmmaxabs, incrmmin, incrmminabs, incrmminmax\n","incrmmpe":"\nincrmmpe( W )\n    Returns an accumulator function which incrementally computes a moving\n    mean percentage error (MPE).\n\n    The `W` parameter defines the number of values over which to compute the\n    moving mean percentage error.\n\n    If provided input values, the accumulator function returns an updated moving\n    mean percentage error. If not provided input values, the accumulator\n    function returns the current moving mean percentage error.\n\n    As `W` (f,a) pairs are needed to fill the window buffer, the first `W-1`\n    returned values are calculated from smaller sample sizes. Until the window\n    is full, each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmpe( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    ~33.33\n    > m = accumulator( 5.0, 2.0 )\n    ~-58.33\n    > m = accumulator( 3.0, 2.0 )\n    ~-55.56\n    > m = accumulator( 2.0, 5.0 )\n    ~-46.67\n    > m = accumulator()\n    ~-46.67\n\n    See Also\n    --------\n    incrmmape, incrmme, incrmpe\n","incrmmse":"\nincrmmse( W )\n    Returns an accumulator function which incrementally computes a moving mean\n    squared error (MSE).\n\n    The `W` parameter defines the number of values over which to compute the\n    moving mean squared error.\n\n    If provided a value, the accumulator function returns an updated moving mean\n    squared error. If not provided a value, the accumulator function returns the\n    current moving mean squared error.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmmse( 3 );\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    1.0\n    > m = accumulator( -5.0, 2.0 )\n    25.0\n    > m = accumulator( 3.0, 2.0 )\n    17.0\n    > m = accumulator( 5.0, -2.0 )\n    33.0\n    > m = accumulator()\n    33.0\n\n    See Also\n    --------\n    incrmrmse, incrmrss, incrmse\n","incrmpcorr":"\nincrmpcorr( W[, mx, my] )\n    Returns an accumulator function which incrementally computes a moving\n    sample Pearson product-moment correlation coefficient.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving sample correlation coefficient.\n\n    If provided values, the accumulator function returns an updated moving\n    sample correlation coefficient. If not provided values, the accumulator\n    function returns the current moving sample correlation coefficient.\n\n    As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n    returned values are calculated from smaller sample sizes. Until the window\n    is full, each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    mx: number (optional)\n        Known mean.\n\n    my: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmpcorr( 3 );\n    > var r = accumulator()\n    null\n    > r = accumulator( 2.0, 1.0 )\n    0.0\n    > r = accumulator( -5.0, 3.14 )\n    ~-1.0\n    > r = accumulator( 3.0, -1.0 )\n    ~-0.925\n    > r = accumulator( 5.0, -9.5 )\n    ~-0.863\n    > r = accumulator()\n    ~-0.863\n\n    See Also\n    --------\n    incrmcovariance, incrmpcorrdist, incrpcorr\n","incrmpcorr2":"\nincrmpcorr2( W[, mx, my] )\n    Returns an accumulator function which incrementally computes a moving\n    squared sample Pearson product-moment correlation coefficient.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving squared sample correlation coefficient.\n\n    If provided values, the accumulator function returns an updated moving\n    squared sample correlation coefficient. If not provided values, the\n    accumulator function returns the current moving squared sample correlation\n    coefficient.\n\n    As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n    returned values are calculated from smaller sample sizes. Until the window\n    is full, each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    mx: number (optional)\n        Known mean.\n\n    my: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmpcorr2( 3 );\n    > var r2 = accumulator()\n    null\n    > r2 = accumulator( 2.0, 1.0 )\n    0.0\n    > r2 = accumulator( -5.0, 3.14 )\n    ~1.0\n    > r2 = accumulator( 3.0, -1.0 )\n    ~0.86\n    > r2 = accumulator( 5.0, -9.5 )\n    ~0.74\n    > r2 = accumulator()\n    ~0.74\n\n    See Also\n    --------\n    incrmapcorr, incrmpcorr, incrpcorr2\n","incrmpcorrdist":"\nincrmpcorrdist( W[, mx, my] )\n    Returns an accumulator function which incrementally computes a moving\n    sample Pearson product-moment correlation distance.\n\n    The correlation distance is defined as one minus the Pearson product-moment\n    correlation coefficient and, thus, resides on the interval [0,2].\n\n    However, due to limitations inherent in representing numeric values using\n    floating-point format (i.e., the inability to represent numeric values with\n    infinite precision), the correlation distance between perfectly correlated\n    random variables may *not* be `0` or `2`. In fact, the correlation distance\n    is *not* guaranteed to be strictly on the interval [0,2]. Any computed\n    distance should, however, be within floating-point roundoff error.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving sample correlation distance.\n\n    If provided values, the accumulator function returns an updated moving\n    sample correlation distance. If not provided values, the accumulator\n    function returns the current moving sample correlation distance.\n\n    As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n    returned values are calculated from smaller sample sizes. Until the window\n    is full, each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    mx: number (optional)\n        Known mean.\n\n    my: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmpcorrdist( 3 );\n    > var d = accumulator()\n    null\n    > d = accumulator( 2.0, 1.0 )\n    1.0\n    > d = accumulator( -5.0, 3.14 )\n    ~2.0\n    > d = accumulator( 3.0, -1.0 )\n    ~1.925\n    > d = accumulator( 5.0, -9.5 )\n    ~1.863\n    > d = accumulator()\n    ~1.863\n\n    See Also\n    --------\n    incrmpcorr, incrpcorrdist\n","incrmpe":"\nincrmpe()\n    Returns an accumulator function which incrementally computes the mean\n    percentage error (MPE).\n\n    If provided input values, the accumulator function returns an updated mean\n    percentage error. If not provided input values, the accumulator function\n    returns the current mean percentage error.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmpe();\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    ~33.33\n    > m = accumulator( 5.0, 2.0 )\n    ~-58.33\n    > m = accumulator()\n    ~-58.33\n\n    See Also\n    --------\n    incrmape, incrme, incrmmpe\n","incrmprod":"\nincrmprod( W )\n    Returns an accumulator function which incrementally computes a moving\n    product.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving product.\n\n    If provided a value, the accumulator function returns an updated moving\n    product. If not provided a value, the accumulator function returns the\n    current moving product.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    For accumulations over large windows or accumulations of large numbers, care\n    should be taken to prevent overflow. Note, however, that overflow/underflow\n    may be transient, as the accumulator does not use a double-precision\n    floating-point number to store an accumulated product. Instead, the\n    accumulator splits an accumulated product into a normalized fraction and\n    exponent and updates each component separately. Doing so guards against a\n    loss in precision.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmprod( 3 );\n    > var p = accumulator()\n    null\n    > p = accumulator( 2.0 )\n    2.0\n    > p = accumulator( -5.0 )\n    -10.0\n    > p = accumulator( 3.0 )\n    -30.0\n    > p = accumulator( 5.0 )\n    -75.0\n    > p = accumulator()\n    -75.0\n\n    See Also\n    --------\n    incrmsum, incrprod\n","incrmrange":"\nincrmrange( W )\n    Returns an accumulator function which incrementally computes a moving range.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving range.\n\n    If provided a value, the accumulator function returns an updated moving\n    range. If not provided a value, the accumulator function returns the current\n    moving range.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmrange( 3 );\n    > var r = accumulator()\n    null\n    > r = accumulator( 2.0 )\n    0.0\n    > r = accumulator( -5.0 )\n    7.0\n    > r = accumulator( 3.0 )\n    8.0\n    > r = accumulator( 5.0 )\n    10.0\n    > r = accumulator()\n    10.0\n\n    See Also\n    --------\n    incrmmax, incrmmean, incrmmin, incrmsummary, incrrange\n","incrmrmse":"\nincrmrmse( W )\n    Returns an accumulator function which incrementally computes a moving root\n    mean squared error (RMSE).\n\n    The `W` parameter defines the number of values over which to compute the\n    moving root mean squared error.\n\n    If provided a value, the accumulator function returns an updated moving root\n    mean squared error. If not provided a value, the accumulator function\n    returns the current moving root mean squared error.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmrmse( 3 );\n    > var r = accumulator()\n    null\n    > r = accumulator( 2.0, 3.0 )\n    1.0\n    > r = accumulator( -5.0, 2.0 )\n    5.0\n    > r = accumulator( 3.0, 2.0 )\n    ~4.12\n    > r = accumulator( 5.0, -2.0 )\n    ~5.74\n    > r = accumulator()\n    ~5.74\n\n    See Also\n    --------\n    incrmmse, incrmrss, incrrmse\n","incrmrss":"\nincrmrss( W )\n    Returns an accumulator function which incrementally computes a moving\n    residual sum of squares (RSS).\n\n    The `W` parameter defines the number of values over which to compute the\n    moving residual sum of squares.\n\n    If provided a value, the accumulator function returns an updated moving\n    residual sum of squares. If not provided a value, the accumulator function\n    returns the current moving residual sum of squares.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmrss( 3 );\n    > var r = accumulator()\n    null\n    > r = accumulator( 2.0, 3.0 )\n    1.0\n    > r = accumulator( -5.0, 2.0 )\n    50.0\n    > r = accumulator( 3.0, 2.0 )\n    51.0\n    > r = accumulator( 5.0, -2.0 )\n    99.0\n    > r = accumulator()\n    99.0\n\n    See Also\n    --------\n    incrrss, incrmmse, incrmrmse\n","incrmse":"\nincrmse()\n    Returns an accumulator function which incrementally computes the mean\n    squared error (MSE).\n\n    If provided input values, the accumulator function returns an updated mean\n    squared error. If not provided input values, the accumulator function\n    returns the current mean squared error.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmse();\n    > var m = accumulator()\n    null\n    > m = accumulator( 2.0, 3.0 )\n    1.0\n    > m = accumulator( -5.0, 2.0 )\n    25.0\n    > m = accumulator()\n    25.0\n\n    See Also\n    --------\n    incrmmse, incrrmse, incrrss\n","incrmstdev":"\nincrmstdev( W[, mean] )\n    Returns an accumulator function which incrementally computes a moving\n    corrected sample standard deviation.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving corrected sample standard deviation.\n\n    If provided a value, the accumulator function returns an updated moving\n    corrected sample standard deviation. If not provided a value, the\n    accumulator function returns the current moving corrected sample standard\n    deviation.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    mean: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmstdev( 3 );\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    0.0\n    > s = accumulator( -5.0 )\n    ~4.95\n    > s = accumulator( 3.0 )\n    ~4.36\n    > s = accumulator( 5.0 )\n    ~5.29\n    > s = accumulator()\n    ~5.29\n\n    See Also\n    --------\n    incrmmean, incrmsummary, incrmvariance, incrstdev\n","incrmsum":"\nincrmsum( W )\n    Returns an accumulator function which incrementally computes a moving sum.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving sum.\n\n    If provided a value, the accumulator function returns an updated moving sum.\n    If not provided a value, the accumulator function returns the current moving\n    sum.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmsum( 3 );\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    2.0\n    > s = accumulator( -5.0 )\n    -3.0\n    > s = accumulator( 3.0 )\n    0.0\n    > s = accumulator( 5.0 )\n    3.0\n    > s = accumulator()\n    3.0\n\n    See Also\n    --------\n    incrmmean, incrmsummary, incrsum\n","incrmsumabs":"\nincrmsumabs( W )\n    Returns an accumulator function which incrementally computes a moving sum of\n    absolute values.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving sum.\n\n    If provided a value, the accumulator function returns an updated moving sum.\n    If not provided a value, the accumulator function returns the current moving\n    sum.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmsumabs( 3 );\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    2.0\n    > s = accumulator( -5.0 )\n    7.0\n    > s = accumulator( 3.0 )\n    10.0\n    > s = accumulator( -5.0 )\n    13.0\n    > s = accumulator()\n    13.0\n\n    See Also\n    --------\n    incrmmeanabs, incrmsum, incrsum, incrsumabs\n","incrmsumabs2":"\nincrmsumabs2( W )\n    Returns an accumulator function which incrementally computes a moving sum of\n    squared absolute values.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving sum.\n\n    If provided a value, the accumulator function returns an updated moving sum.\n    If not provided a value, the accumulator function returns the current moving\n    sum.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmsumabs2( 3 );\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    4.0\n    > s = accumulator( -5.0 )\n    29.0\n    > s = accumulator( 3.0 )\n    38.0\n    > s = accumulator( -5.0 )\n    59.0\n    > s = accumulator()\n    59.0\n\n    See Also\n    --------\n    incrmmeanabs2, incrmsumabs, incrsumabs, incrsumabs2\n","incrmsummary":"\nincrmsummary( W )\n    Returns an accumulator function which incrementally computes a moving\n    statistical summary.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving statistical summary.\n\n    If provided a value, the accumulator function returns an updated moving\n    statistical summary. If not provided a value, the accumulator function\n    returns the current moving statistical summary.\n\n    The returned summary is an object containing the following fields:\n\n    - window: window size.\n    - sum: sum.\n    - mean: arithmetic mean.\n    - variance: unbiased sample variance.\n    - stdev: corrected sample standard deviation.\n    - min: minimum value.\n    - max: maximum value.\n    - range: range.\n    - midrange: arithmetic mean of the minimum and maximum values.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    summaries are calculated from smaller sample sizes. Until the window is\n    full, each returned summary is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmsummary( 3 );\n    > var s = accumulator()\n    {}\n    > s = accumulator( 2.0 )\n    {...}\n    > s = accumulator( -5.0 )\n    {...}\n    > s = accumulator()\n    {...}\n\n    See Also\n    --------\n    incrmmean, incrmstdev, incrmsum, incrmvariance, incrsummary\n","incrmsumprod":"\nincrmsumprod( W )\n    Returns an accumulator function which incrementally computes a moving sum of\n    products.\n\n    The `W` parameter defines the number of (x,y) pairs over which to compute\n    the moving sum of products.\n\n    If provided input values, the accumulator function returns an updated moving\n    sum. If not provided input values, the accumulator function returns the\n    current moving sum.\n\n    As `W` (x,y) pairs are needed to fill the window buffer, the first `W-1`\n    returned values are calculated from smaller sample sizes. Until the window\n    is full, each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmsumprod( 3 );\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0, 3.0 )\n    6.0\n    > s = accumulator( -5.0, 2.0 )\n    -4.0\n    > s = accumulator( 3.0, -2.0 )\n    -10.0\n    > s = accumulator( 5.0, 3.0 )\n    -1.0\n    > s = accumulator()\n    -1.0\n\n    See Also\n    --------\n    incrmprod, incrmsum, incrsumprod\n","incrmvariance":"\nincrmvariance( W[, mean] )\n    Returns an accumulator function which incrementally computes a moving\n    unbiased sample variance.\n\n    The `W` parameter defines the number of values over which to compute the\n    moving unbiased sample variance.\n\n    If provided a value, the accumulator function returns an updated moving\n    unbiased sample variance. If not provided a value, the accumulator function\n    returns the current moving unbiased sample variance.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    mean: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmvariance( 3 );\n    > var s2 = accumulator()\n    null\n    > s2 = accumulator( 2.0 )\n    0.0\n    > s2 = accumulator( -5.0 )\n    24.5\n    > s2 = accumulator( 3.0 )\n    19.0\n    > s2 = accumulator( 5.0 )\n    28.0\n    > s2 = accumulator()\n    28.0\n\n    See Also\n    --------\n    incrmmean, incrmstdev, incrmsummary, incrvariance\n","incrmvmr":"\nincrmvmr( W[, mean] )\n    Returns an accumulator function which incrementally computes a moving\n    variance-to-mean (VMR).\n\n    The `W` parameter defines the number of values over which to compute the\n    moving variance-to-mean ratio.\n\n    If provided a value, the accumulator function returns an updated moving\n    variance-to-mean ratio. If not provided a value, the accumulator function\n    returns the current moving variance-to-mean ratio.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all provided values.\n\n    Parameters\n    ----------\n    W: integer\n        Window size.\n\n    mean: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrmvmr( 3 );\n    > var F = accumulator()\n    null\n    > F = accumulator( 2.0 )\n    0.0\n    > F = accumulator( 1.0 )\n    ~0.33\n    > F = accumulator( 3.0 )\n    0.5\n    > F = accumulator( 7.0 )\n    ~2.55\n    > F = accumulator()\n    ~2.55\n\n    See Also\n    --------\n    incrmmean, incrmvariance, incrvmr\n","incrnancount":"\nincrnancount()\n    Returns an accumulator function which incrementally updates a count,\n    ignoring `NaN` values.\n\n    If provided a value, the accumulator function returns an updated count. If\n    not provided a value, the accumulator function returns the current count.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrnancount();\n    > var v = accumulator()\n    0\n    > v = accumulator( 2.0 )\n    1\n    > v = accumulator( -5.0 )\n    2\n    > v = accumulator()\n    2\n\n    See Also\n    --------\n    incrnansum\n","incrnansum":"\nincrnansum()\n    Returns an accumulator function which incrementally computes a sum, ignoring\n    `NaN` values.\n\n    If provided a value, the accumulator function returns an updated sum. If not\n    provided a value, the accumulator function returns the current sum.\n\n    For long running accumulations or accumulations of large numbers, care\n    should be taken to prevent overflow.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrnansum();\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    2.0\n    > s = accumulator( NaN )\n    2.0\n    > s = accumulator( -5.0 )\n    -3.0\n    > s = accumulator()\n    -3.0\n\n    See Also\n    --------\n    incrnansumabs, incrsum\n","incrnansumabs":"\nincrnansumabs()\n    Returns an accumulator function which incrementally computes a sum of\n    absolute values, ignoring NaN values.\n\n    If provided a value, the accumulator function returns an updated sum. If not\n    provided a value, the accumulator function returns the current sum.\n\n    For long running accumulations or accumulations of large numbers, care\n    should be taken to prevent overflow.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrnansumabs();\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    2.0\n    > s = accumulator( NaN )\n    2.0\n    > s = accumulator( -5.0 )\n    7.0\n    > s = accumulator()\n    7.0\n\n    See Also\n    --------\n    incrnansum, incrnansumabs2, incrsumabs\n","incrnansumabs2":"\nincrnansumabs2()\n    Returns an accumulator function which incrementally computes a sum of\n    squared absolute values, ignoring NaN values.\n\n    If provided a value, the accumulator function returns an updated sum. If not\n    provided a value, the accumulator function returns the current sum.\n\n    For long running accumulations or accumulations of large numbers, care\n    should be taken to prevent overflow.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrnansumabs2();\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    4.0\n    > s = accumulator( NaN )\n    4.0\n    > s = accumulator( -5.0 )\n    29.0\n    > s = accumulator()\n    29.0\n\n    See Also\n    --------\n    incrnansum, incrnansumabs, incrsumabs2\n","incrpcorr":"\nincrpcorr( [mx, my] )\n    Returns an accumulator function which incrementally computes a sample\n    Pearson product-moment correlation coefficient.\n\n    If provided values, the accumulator function returns an updated sample\n    correlation coefficient. If not provided values, the accumulator function\n    returns the current sample correlation coefficient.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    mx: number (optional)\n        Known mean.\n\n    my: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrpcorr();\n    > var r = accumulator()\n    null\n    > r = accumulator( 2.0, 1.0 )\n    0.0\n    > r = accumulator( -5.0, 3.14 )\n    ~-1.0\n    > r = accumulator()\n    ~-1.0\n\n    See Also\n    --------\n    incrcovariance, incrmpcorr, incrsummary\n","incrpcorr2":"\nincrpcorr2( [mx, my] )\n    Returns an accumulator function which incrementally computes the squared\n    sample Pearson product-moment correlation coefficient.\n\n    If provided values, the accumulator function returns an updated accumulated\n    value. If not provided values, the accumulator function returns the current\n    accumulated value.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    mx: number (optional)\n        Known mean.\n\n    my: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrpcorr2();\n    > var r2 = accumulator()\n    null\n    > r2 = accumulator( 2.0, 1.0 )\n    0.0\n    > r2 = accumulator( -5.0, 3.14 )\n    ~1.0\n    > r2 = accumulator()\n    ~1.0\n\n    See Also\n    --------\n    incrapcorr, incrmpcorr2, incrpcorr\n","incrpcorrdist":"\nincrpcorrdist( [mx, my] )\n    Returns an accumulator function which incrementally computes a sample\n    Pearson product-moment correlation distance.\n\n    The correlation distance is defined as one minus the Pearson product-moment\n    correlation coefficient and, thus, resides on the interval [0,2].\n\n    If provided values, the accumulator function returns an updated sample\n    correlation distance. If not provided values, the accumulator function\n    returns the current sample correlation distance.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    mx: number (optional)\n        Known mean.\n\n    my: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrpcorrdist();\n    > var d = accumulator()\n    null\n    > d = accumulator( 2.0, 1.0 )\n    1.0\n    > d = accumulator( -5.0, 3.14 )\n    ~2.0\n    > d = accumulator()\n    ~2.0\n\n    See Also\n    --------\n    incrcovariance, incrpcorr, incrsummary\n","incrpcorrdistmat":"\nincrpcorrdistmat( out[, means] )\n    Returns an accumulator function which incrementally computes a sample\n    Pearson product-moment correlation distance matrix.\n\n    If provided a data vector, the accumulator function returns an updated\n    sample correlation distance matrix. If not provided a data vector, the\n    accumulator function returns the current sample correlation distance matrix.\n\n    Due to limitations inherent in representing numeric values using floating-\n    point format (i.e., the inability to represent numeric values with infinite\n    precision), the correlation distance between perfectly correlated random\n    variables may *not* be `0` or `2`. In fact, the correlation distance is\n    *not* guaranteed to be strictly on the interval [0,2]. Any computed distance\n    should, however, be within floating-point roundoff error.\n\n    Parameters\n    ----------\n    out: integer|ndarray\n        Order of the correlation distance matrix or a square 2-dimensional\n        ndarray for storing the correlation distance matrix.\n\n    means: ndarray (optional)\n        Known means.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrpcorrdistmat( 2 );\n    > var out = accumulator()\n    <ndarray>\n    > var buf = new Float64Array( 2 );\n    > var shape = [ 2 ];\n    > var strides = [ 1 ];\n    > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n    > v.set( 0, 2.0 );\n    > v.set( 1, 1.0 );\n    > out = accumulator( v )\n    <ndarray>\n    > v.set( 0, -5.0 );\n    > v.set( 1, 3.14 );\n    > out = accumulator( v )\n    <ndarray>\n    > out = accumulator()\n    <ndarray>\n\n    See Also\n    --------\n    incrpcorrdist, incrpcorrmat\n","incrpcorrmat":"\nincrpcorrmat( out[, means] )\n    Returns an accumulator function which incrementally computes a sample\n    Pearson product-moment correlation matrix.\n\n    If provided a data vector, the accumulator function returns an updated\n    sample correlation matrix. If not provided a data vector, the accumulator\n    function returns the current sample correlation matrix.\n\n    Parameters\n    ----------\n    out: integer|ndarray\n        Order of the correlation matrix or a square 2-dimensional ndarray for\n        storing the correlation matrix.\n\n    means: ndarray (optional)\n        Known means.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrpcorrmat( 2 );\n    > var out = accumulator()\n    <ndarray>\n    > var buf = new Float64Array( 2 );\n    > var shape = [ 2 ];\n    > var strides = [ 1 ];\n    > var v = ndarray( 'float64', buf, shape, strides, 0, 'row-major' );\n    > v.set( 0, 2.0 );\n    > v.set( 1, 1.0 );\n    > out = accumulator( v )\n    <ndarray>\n    > v.set( 0, -5.0 );\n    > v.set( 1, 3.14 );\n    > out = accumulator( v )\n    <ndarray>\n    > out = accumulator()\n    <ndarray>\n\n    See Also\n    --------\n    incrcovmat, incrpcorr, incrpcorrdistmat\n","incrprod":"\nincrprod()\n    Returns an accumulator function which incrementally computes a product.\n\n    If provided a value, the accumulator function returns an updated product. If\n    not provided a value, the accumulator function returns the current product.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    For long running accumulations or accumulations of large numbers, care\n    should be taken to prevent overflow. Note, however, that overflow/underflow\n    may be transient, as the accumulator does not use a double-precision\n    floating-point number to store an accumulated product. Instead, the\n    accumulator splits an accumulated product into a normalized fraction and\n    exponent and updates each component separately. Doing so guards against a\n    loss in precision.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrprod();\n    > var v = accumulator()\n    null\n    > v = accumulator( 2.0 )\n    2.0\n    > v = accumulator( -5.0 )\n    -10.0\n    > v = accumulator()\n    -10.0\n\n    See Also\n    --------\n    incrmprod, incrsum, incrsummary\n","incrrange":"\nincrrange()\n    Returns an accumulator function which incrementally computes a range.\n\n    If provided a value, the accumulator function returns an updated range. If\n    not provided a value, the accumulator function returns the current range.\n\n    If provided `NaN`, the range is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrrange();\n    > var v = accumulator()\n    null\n    > v = accumulator( -2.0 )\n    0.0\n    > v = accumulator( 1.0 )\n    3.0\n    > v = accumulator( 3.0 )\n    5.0\n    > v = accumulator()\n    5.0\n\n    See Also\n    --------\n    incrmax, incrmean, incrmin, incrmrange, incrsummary\n","incrrmse":"\nincrrmse()\n    Returns an accumulator function which incrementally computes the root mean\n    squared error (RMSE).\n\n    If provided input values, the accumulator function returns an updated root\n    mean squared error. If not provided input values, the accumulator function\n    returns the current root mean squared error.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrrmse();\n    > var r = accumulator()\n    null\n    > r = accumulator( 2.0, 3.0 )\n    1.0\n    > r = accumulator( -5.0, 2.0 )\n    5.0\n    > r = accumulator()\n    5.0\n\n    See Also\n    --------\n    incrmrmse, incrmse, incrrss\n","incrrss":"\nincrrss()\n    Returns an accumulator function which incrementally computes the residual\n    sum of squares (RSS).\n\n    If provided input values, the accumulator function returns an updated\n    residual sum of squares. If not provided input values, the accumulator\n    function returns the current residual sum of squares.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrrss();\n    > var r = accumulator()\n    null\n    > r = accumulator( 2.0, 3.0 )\n    1.0\n    > r = accumulator( -5.0, 2.0 )\n    50.0\n    > r = accumulator()\n    50.0\n\n    See Also\n    --------\n    incrmrss, incrmse, incrrmse\n","incrskewness":"\nincrskewness()\n    Returns an accumulator function which incrementally computes a corrected\n    sample skewness.\n\n    If provided a value, the accumulator function returns an updated corrected\n    sample skewness. If not provided a value, the accumulator function returns\n    the current corrected sample skewness.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrskewness();\n    > var v = accumulator( 2.0 )\n    null\n    > v = accumulator( -5.0 )\n    null\n    > v = accumulator( -10.0 )\n    ~0.492\n    > v = accumulator()\n    ~0.492\n\n    See Also\n    --------\n    incrkurtosis, incrmean, incrstdev, incrsummary, incrvariance\n","incrspace":"\nincrspace( start, stop[, increment] )\n    Generates a linearly spaced numeric array using a provided increment.\n\n    If an `increment` is not provided, the default `increment` is `1`.\n\n    The output array is guaranteed to include the `start` value but does not\n    include the `stop` value.\n\n    Parameters\n    ----------\n    start: number\n        First array value.\n\n    stop: number\n        Array element bound.\n\n    increment: number (optional)\n        Increment. Default: `1`.\n\n    Returns\n    -------\n    arr: Array\n        Linearly spaced numeric array.\n\n    Examples\n    --------\n    > var arr = incrspace( 0, 11, 2 )\n    [ 0, 2, 4, 6, 8, 10 ]\n\n    See Also\n    --------\n    linspace, logspace\n","incrstdev":"\nincrstdev( [mean] )\n    Returns an accumulator function which incrementally computes a corrected\n    sample standard deviation.\n\n    If provided a value, the accumulator function returns an updated corrected\n    sample standard deviation. If not provided a value, the accumulator function\n    returns the current corrected sample standard deviation.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    mean: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrstdev();\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    0.0\n    > s = accumulator( -5.0 )\n    ~4.95\n    > s = accumulator()\n    ~4.95\n\n    See Also\n    --------\n    incrkurtosis, incrmean, incrmstdev, incrskewness, incrsummary, incrvariance\n","incrsum":"\nincrsum()\n    Returns an accumulator function which incrementally computes a sum.\n\n    If provided a value, the accumulator function returns an updated sum. If not\n    provided a value, the accumulator function returns the current sum.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    For long running accumulations or accumulations of large numbers, care\n    should be taken to prevent overflow.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrsum();\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    2.0\n    > s = accumulator( -5.0 )\n    -3.0\n    > s = accumulator()\n    -3.0\n\n    See Also\n    --------\n    incrcount, incrmean, incrmsum, incrprod, incrsummary\n","incrsumabs":"\nincrsumabs()\n    Returns an accumulator function which incrementally computes a sum of\n    absolute values.\n\n    If provided a value, the accumulator function returns an updated sum. If not\n    provided a value, the accumulator function returns the current sum.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    For long running accumulations or accumulations of large numbers, care\n    should be taken to prevent overflow.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrsumabs();\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    2.0\n    > s = accumulator( -5.0 )\n    7.0\n    > s = accumulator()\n    7.0\n\n    See Also\n    --------\n    incrmeanabs, incrmsumabs, incrsum\n","incrsumabs2":"\nincrsumabs2()\n    Returns an accumulator function which incrementally computes a sum of\n    squared absolute values.\n\n    If provided a value, the accumulator function returns an updated sum. If not\n    provided a value, the accumulator function returns the current sum.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    For long running accumulations or accumulations of large numbers, care\n    should be taken to prevent overflow.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrsumabs2();\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0 )\n    4.0\n    > s = accumulator( -5.0 )\n    29.0\n    > s = accumulator()\n    29.0\n\n    See Also\n    --------\n    incrmeanabs2, incrmsumabs2, incrsumabs\n","incrsummary":"\nincrsummary()\n    Returns an accumulator function which incrementally computes a statistical\n    summary.\n\n    If provided a value, the accumulator function returns an updated summary. If\n    not provided a value, the accumulator function returns the current summary.\n\n    The returned summary is an object containing the following fields:\n\n    - count: count.\n    - max: maximum value.\n    - min: minimum value.\n    - range: range.\n    - midrange: mid-range.\n    - sum: sum.\n    - mean: arithmetic mean.\n    - variance: unbiased sample variance.\n    - stdev: corrected sample standard deviation.\n    - skewness: corrected sample skewness.\n    - kurtosis: corrected sample excess kurtosis.\n\n    For long running accumulations or accumulations of large numbers, care\n    should be taken to prevent overflow.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrsummary();\n    > var s = accumulator()\n    {}\n    > s = accumulator( 2.0 )\n    {...}\n    > s = accumulator( -5.0 )\n    {...}\n    > s = accumulator()\n    {...}\n\n    See Also\n    --------\n    incrcount, incrkurtosis, incrmax, incrmean, incrmidrange, incrmin, incrmsummary, incrrange, incrskewness, incrstdev, incrsum, incrvariance\n","incrsumprod":"\nincrsumprod()\n    Returns an accumulator function which incrementally computes a sum of\n    products.\n\n    If provided input values, the accumulator function returns an updated sum.\n    If not provided input values, the accumulator function returns the current\n    sum.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    For long running accumulations or accumulations of large numbers, care\n    should be taken to prevent overflow.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrsumprod();\n    > var s = accumulator()\n    null\n    > s = accumulator( 2.0, 3.0 )\n    6.0\n    > s = accumulator( -5.0, 2.0 )\n    -4.0\n    > s = accumulator()\n    -4.0\n\n    See Also\n    --------\n    incrmsumprod, incrprod, incrsum\n","incrvariance":"\nincrvariance( [mean] )\n    Returns an accumulator function which incrementally computes an unbiased\n    sample variance.\n\n    If provided a value, the accumulator function returns an updated unbiased\n    sample variance. If not provided a value, the accumulator function returns\n    the current unbiased sample variance.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    mean: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrvariance();\n    > var s2 = accumulator()\n    null\n    > s2 = accumulator( 2.0 )\n    0.0\n    > s2 = accumulator( -5.0 )\n    24.5\n    > s2 = accumulator()\n    24.5\n\n    See Also\n    --------\n    incrkurtosis, incrmean, incrmstdev, incrskewness, incrstdev, incrsummary\n","incrvmr":"\nincrvmr( [mean] )\n    Returns an accumulator function which incrementally computes a variance-to-\n    mean ratio (VMR).\n\n    If provided a value, the accumulator function returns an updated accumulated\n    value. If not provided a value, the accumulator function returns the current\n    accumulated value.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    Parameters\n    ----------\n    mean: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrvmr();\n    > var D = accumulator()\n    null\n    > D = accumulator( 2.0 )\n    0.0\n    > D = accumulator( 1.0 )\n    ~0.33\n    > D = accumulator()\n    ~0.33\n\n    See Also\n    --------\n    incrmean, incrmvmr, incrvariance\n","incrwmean":"\nincrwmean()\n    Returns an accumulator function which incrementally computes a weighted\n    arithmetic mean.\n\n    If provided arguments, the accumulator function returns an updated weighted\n    mean. If not provided arguments, the accumulator function returns the\n    current weighted mean.\n\n    If provided `NaN` or a value which, when used in computations, results in\n    `NaN`, the accumulated value is `NaN` for all future invocations.\n\n    The accumulator function accepts two arguments:\n\n    - x: value.\n    - w: weight.\n\n    Returns\n    -------\n    acc: Function\n        Accumulator function.\n\n    Examples\n    --------\n    > var accumulator = incrwmean();\n    > var mu = accumulator()\n    null\n    > mu = accumulator( 2.0, 1.0 )\n    2.0\n    > mu = accumulator( 2.0, 0.5 )\n    2.0\n    > mu = accumulator( 3.0, 1.5 )\n    2.5\n    > mu = accumulator()\n    2.5\n\n    See Also\n    --------\n    increwmean, incrmean, incrmmean\n","ind2sub":"\nind2sub( shape, idx[, options] )\n    Converts a linear index to an array of subscripts.\n\n    Parameters\n    ----------\n    shape: ArrayLike\n        Array shape.\n\n    idx: integer\n        Linear index.\n\n    options: Object (optional)\n        Options.\n\n    options.order: string (optional)\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran style). Default: 'row-major'.\n\n    options.mode: string (optional)\n        Specifies how to handle a linear index which exceeds array dimensions.\n        If equal to 'throw', the function throws an error when a linear index\n        exceeds array dimensions. If equal to 'normalize', the function\n        normalizes negative linear indices and throws an error when a linear\n        index exceeds array dimensions. If equal to 'wrap', the function wraps\n        around a linear index exceeding array dimensions using modulo\n        arithmetic. If equal to 'clamp', the function sets a linear index\n        exceeding array dimensions to either `0` (minimum linear index) or the\n        maximum linear index. Default: 'throw'.\n\n    Returns\n    -------\n    out: Array<integer>\n        Subscripts.\n\n    Examples\n    --------\n    > var d = [ 3, 3, 3 ];\n    > var s = ind2sub( d, 17 )\n    [ 1, 2, 2 ]\n\n\nind2sub.assign( shape, idx[, options], out )\n    Converts a linear index to an array of subscripts and assigns results to a\n    provided output array.\n\n    Parameters\n    ----------\n    shape: ArrayLike\n        Array shape.\n\n    idx: integer\n        Linear index.\n\n    options: Object (optional)\n        Options.\n\n    options.order: string (optional)\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran style). Default: 'row-major'.\n\n    options.mode: string (optional)\n        Specifies how to handle a linear index which exceeds array dimensions.\n        If equal to 'throw', the function throws an error when a linear index\n        exceeds array dimensions. If equal to 'normalize', the function\n        normalizes negative linear indices and throws an error when a linear\n        index exceeds array dimensions. If equal to 'wrap', the function wraps\n        around a linear index exceeding array dimensions using modulo\n        arithmetic. If equal to 'clamp', the function sets a linear index\n        exceeding array dimensions to either `0` (minimum linear index) or the\n        maximum linear index. Default: 'throw'.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Subscripts.\n\n    Examples\n    --------\n    > var d = [ 3, 3, 3 ];\n    > var out = [ 0, 0, 0 ];\n    > var s = ind2sub.assign( d, 17, out )\n    [ 1, 2, 2 ]\n    > var bool = ( s === out )\n    true\n\n    See Also\n    --------\n    array, ndarray, sub2ind\n","ind2sub.assign":"\nind2sub.assign( shape, idx[, options], out )\n    Converts a linear index to an array of subscripts and assigns results to a\n    provided output array.\n\n    Parameters\n    ----------\n    shape: ArrayLike\n        Array shape.\n\n    idx: integer\n        Linear index.\n\n    options: Object (optional)\n        Options.\n\n    options.order: string (optional)\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran style). Default: 'row-major'.\n\n    options.mode: string (optional)\n        Specifies how to handle a linear index which exceeds array dimensions.\n        If equal to 'throw', the function throws an error when a linear index\n        exceeds array dimensions. If equal to 'normalize', the function\n        normalizes negative linear indices and throws an error when a linear\n        index exceeds array dimensions. If equal to 'wrap', the function wraps\n        around a linear index exceeding array dimensions using modulo\n        arithmetic. If equal to 'clamp', the function sets a linear index\n        exceeding array dimensions to either `0` (minimum linear index) or the\n        maximum linear index. Default: 'throw'.\n\n    out: Array|TypedArray|Object\n        Output array.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Subscripts.\n\n    Examples\n    --------\n    > var d = [ 3, 3, 3 ];\n    > var out = [ 0, 0, 0 ];\n    > var s = ind2sub.assign( d, 17, out )\n    [ 1, 2, 2 ]\n    > var bool = ( s === out )\n    true\n\n    See Also\n    --------\n    array, ndarray, sub2ind","indexOf":"\nindexOf( arr, searchElement[, fromIndex] )\n    Returns the first index at which a given element can be found.\n\n    Search is performed using *strict equality* comparison.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Array-like object.\n\n    searchElement: any\n        Element to find.\n\n    fromIndex: integer (optional)\n        Starting index (if negative, the start index is determined relative to\n        last element).\n\n    Returns\n    -------\n    out: integer\n        Index or -1.\n\n    Examples\n    --------\n    // Basic usage:\n    > var arr = [ 4, 3, 2, 1 ];\n    > var idx = indexOf( arr, 3 )\n    1\n    > arr = [ 4, 3, 2, 1 ];\n    > idx = indexOf( arr, 5 )\n    -1\n\n    // Using a `fromIndex`:\n    > arr = [ 1, 2, 3, 4, 5, 2, 6 ];\n    > idx = indexOf( arr, 2, 3 )\n    5\n\n    // `fromIndex` which exceeds `array` length:\n    > arr = [ 1, 2, 3, 4, 2, 5 ];\n    > idx = indexOf( arr, 2, 10 )\n    -1\n\n    // Negative `fromIndex`:\n    > arr = [ 1, 2, 3, 4, 5, 2, 6, 2 ];\n    > idx = indexOf( arr, 2, -4 )\n    5\n    > idx = indexOf( arr, 2, -1 )\n    7\n\n    // Negative `fromIndex` exceeding input `array` length:\n    > arr = [ 1, 2, 3, 4, 5, 2, 6 ];\n    > idx = indexOf( arr, 2, -10 )\n    1\n\n    // Array-like objects:\n    > var str = 'bebop';\n    > idx = indexOf( str, 'o' )\n    3\n\n","inherit":"\ninherit( ctor, superCtor )\n    Prototypical inheritance by replacing the prototype of one constructor with\n    the prototype of another constructor.\n\n    This function is not designed to work with ES2015/ES6 classes. For\n    ES2015/ES6 classes, use `class` with `extends`.\n\n    Parameters\n    ----------\n    ctor: Object|Function\n        Constructor which will inherit.\n\n    superCtor: Object|Function\n        Super (parent) constructor.\n\n    Returns\n    -------\n    out: Object|Function\n        Child constructor.\n\n    Examples\n    --------\n    // Create a parent constructor:\n    > function Foo() { return this; };\n    > Foo.prototype.beep = function beep() { return 'boop'; };\n\n    // Create a child constructor:\n    > function Bar() { Foo.call( this ); return this; };\n\n    // Setup inheritance:\n    > inherit( Bar, Foo );\n    > var bar = new Bar();\n    > var v = bar.beep()\n    'boop'\n\n","inheritedEnumerableProperties":"\ninheritedEnumerableProperties( value[, level] )\n    Returns an array of an object's inherited enumerable property names and\n    symbols.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    props: Array\n        List of an object's inherited enumerable properties.\n\n    Examples\n    --------\n    > var props = inheritedEnumerableProperties( {} )\n\n    See Also\n    --------\n    enumerableProperties, enumerablePropertiesIn, inheritedEnumerablePropertySymbols, inheritedKeys, inheritedNonEnumerableProperties, inheritedProperties\n","inheritedEnumerablePropertySymbols":"\ninheritedEnumerablePropertySymbols( value[, level] )\n    Returns an array of an object's inherited enumerable symbol properties.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's inherited enumerable symbol properties.\n\n    Examples\n    --------\n    > var symbols = inheritedEnumerablePropertySymbols( [] )\n\n    See Also\n    --------\n    enumerableProperties, enumerablePropertySymbols, inheritedKeys, nonEnumerablePropertySymbols, nonEnumerablePropertySymbolsIn, propertySymbols\n","inheritedKeys":"\ninheritedKeys( value[, level] )\n    Returns an array of an object's inherited enumerable property names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's inherited enumerable property names.\n\n    Examples\n    --------\n    > var keys = inheritedKeys( {} )\n\n    See Also\n    --------\n    objectKeys, keysIn, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedNonEnumerableProperties":"\ninheritedNonEnumerableProperties( value[, level] )\n    Returns an array of an object's inherited non-enumerable property names and\n    symbols.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    props: Array\n        List of an object's inherited non-enumerable properties.\n\n    Examples\n    --------\n    > var props = inheritedNonEnumerableProperties( {} )\n\n    See Also\n    --------\n    inheritedEnumerableProperties, inheritedNonEnumerablePropertyNames, inheritedNonEnumerablePropertySymbols, inheritedKeys, nonEnumerableProperties, nonEnumerablePropertiesIn, properties\n","inheritedNonEnumerablePropertyNames":"\ninheritedNonEnumerablePropertyNames( value[, level] )\n    Returns an array of an object's inherited non-enumerable property names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's inherited non-enumerable property names.\n\n    Examples\n    --------\n    > var keys = inheritedNonEnumerablePropertyNames( {} )\n\n    See Also\n    --------\n    inheritedNonEnumerableProperties, inheritedNonEnumerablePropertySymbols, objectKeys, nonEnumerablePropertyNames, nonEnumerablePropertyNamesIn, nonEnumerablePropertySymbols, propertyNames\n","inheritedNonEnumerablePropertySymbols":"\ninheritedNonEnumerablePropertySymbols( value[, level] )\n    Returns an array of an object's inherited non-enumerable symbol properties.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's inherited non-enumerable symbol properties.\n\n    Examples\n    --------\n    > var symbols = inheritedNonEnumerablePropertySymbols( [] )\n\n    See Also\n    --------\n    inheritedNonEnumerableProperties, inheritedNonEnumerablePropertyNames, nonEnumerableProperties, nonEnumerablePropertyNames, nonEnumerablePropertySymbols, nonEnumerablePropertySymbolsIn, propertySymbols\n","inheritedProperties":"\ninheritedProperties( value[, level] )\n    Returns an array of an object's inherited property names and symbols.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's inherited property names and symbols.\n\n    Examples\n    --------\n    > var symbols = inheritedProperties( [] )\n\n    See Also\n    --------\n    properties, propertiesIn, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedPropertyDescriptor":"\ninheritedPropertyDescriptor( value, property[, level] )\n    Returns a property descriptor for an object's inherited property.\n\n    If provided `null` or `undefined` or provided a non-existent property, the\n    function returns `null`.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    property: string|symbol\n        Property name.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    desc: Object|null\n        Property descriptor.\n\n    Examples\n    --------\n    > var desc = inheritedPropertyDescriptor( {}, 'toString' )\n    {...}\n\n    See Also\n    --------\n    propertyDescriptor, propertyDescriptorIn, inheritedKeys, inheritedPropertyDescriptors, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedPropertyDescriptors":"\ninheritedPropertyDescriptors( value[, level] )\n    Returns an object's inherited property descriptors.\n\n    If provided `null` or `undefined`, the function returns an empty object.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    desc: Object\n        An object's inherited property descriptors.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var desc = inheritedPropertyDescriptors( obj )\n    { 'foo': {...}, ... }\n\n    See Also\n    --------\n    propertyDescriptors, propertyDescriptorsIn, inheritedKeys, inheritedPropertyNames, inheritedPropertySymbols\n","inheritedPropertyNames":"\ninheritedPropertyNames( value[, level] )\n    Returns an array of an object's inherited enumerable and non-enumerable\n    property names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's inherited enumerable and non-enumerable property\n        names.\n\n    Examples\n    --------\n    > var keys = inheritedPropertyNames( [] )\n\n    See Also\n    --------\n    inheritedKeys, inheritedPropertyDescriptors, inheritedPropertySymbols, propertyNames, propertyNamesIn\n","inheritedPropertySymbols":"\ninheritedPropertySymbols( value[, level] )\n    Returns an array of an object's inherited symbol properties.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's inherited symbol properties.\n\n    Examples\n    --------\n    > var symbols = inheritedPropertySymbols( [] )\n\n    See Also\n    --------\n    inheritedKeys, inheritedPropertyDescriptors, inheritedPropertyNames, propertySymbols, propertySymbolsIn\n","inheritedWritableProperties":"\ninheritedWritableProperties( value[, level] )\n    Returns an array of an object's inherited writable property names and\n    symbols.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    props: Array\n        List of an object's inherited writable properties.\n\n    Examples\n    --------\n    > var props = inheritedWritableProperties( {} )\n\n    See Also\n    --------\n    inheritedWritablePropertyNames, inheritedWritablePropertySymbols, writableProperties, writablePropertiesIn, properties\n","inheritedWritablePropertyNames":"\ninheritedWritablePropertyNames( value[, level] )\n    Returns an array of an object's inherited writable property names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's inherited writable property names.\n\n    Examples\n    --------\n    > var keys = inheritedWritablePropertyNames( {} )\n\n    See Also\n    --------\n    inheritedWritablePropertySymbols, writablePropertyNames, writablePropertyNamesIn, properties\n","inheritedWritablePropertySymbols":"\ninheritedWritablePropertySymbols( value[, level] )\n    Returns an array of an object's inherited writable symbol properties.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    level: integer (optional)\n        Inheritance level.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's inherited writable symbol properties.\n\n    Examples\n    --------\n    > var symbols = inheritedWritablePropertySymbols( [] )\n\n    See Also\n    --------\n    inheritedWritablePropertyNames, writablePropertySymbols, writablePropertySymbolsIn, properties\n","inmap":"\ninmap( collection, fcn[, thisArg] )\n    Invokes a function for each element in a collection and updates the\n    collection in-place.\n\n    When invoked, the input function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection. If provided an object, the object must be array-like\n        (excluding strings and functions).\n\n    fcn: Function\n        Function to invoke for each element in the input collection. The\n        function's return value is used to update the collection in-place.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function foo( v, i ) { return v * i; };\n    > var arr = [ 1.0, 2.0, 3.0 ];\n    > var out = inmap( arr, foo )\n    [ 0.0, 2.0, 6.0 ]\n    > var bool = ( out === arr )\n    true\n\n    See Also\n    --------\n    forEach, inmapRight, map\n","inmapAsync":"\ninmapAsync( collection, [options,] fcn, done )\n    Invokes a function once for each element in a collection and updates a\n    collection in-place.\n\n    When invoked, `fcn` is provided a maximum of four arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If `fcn`\n    accepts two arguments, `fcn` is provided:\n\n    - value\n    - next\n\n    If `fcn` accepts three arguments, `fcn` is provided:\n\n    - value\n    - index\n    - next\n\n    For every other `fcn` signature, `fcn` is provided all four arguments.\n\n    The `next` callback accepts two arguments:\n\n    - error: error argument.\n    - result: value used to update the collection.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling. Note, however, that the function\n    may have mutated an input collection during prior invocations, resulting in\n    a partially mutated collection.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function fcn( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, value*index );\n    ...     }\n    ... };\n    > function done( error, collection ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( collection === arr );\n    ...     console.log( collection );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > inmapAsync( arr, fcn, done )\n    1000\n    2500\n    3000\n    true\n    [ 0, 2500, 2000 ]\n\n    // Limit number of concurrent invocations:\n    > function fcn( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, value*index );\n    ...     }\n    ... };\n    > function done( error, collection ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( collection === arr );\n    ...     console.log( collection );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 3000, 2500, 1000 ];\n    > inmapAsync( arr, opts, fcn, done )\n    2500\n    3000\n    1000\n    true\n    [ 0, 2500, 2000 ]\n\n    // Process sequentially:\n    > function fcn( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, value*index );\n    ...     }\n    ... };\n    > function done( error, collection ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( collection === arr );\n    ...     console.log( collection );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 3000, 2500, 1000 ];\n    > inmapAsync( arr, opts, fcn, done )\n    3000\n    2500\n    1000\n    true\n    [ 0, 2500, 2000 ]\n\n\ninmapAsync.factory( [options,] fcn )\n    Returns a function which invokes a function once for each element in a\n    collection and updates a collection in-place.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function fcn( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, value*index );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = inmapAsync.factory( opts, fcn );\n    > function done( error, collection ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( collection === arr );\n    ...     console.log( collection );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    [ 0, 2500, 2000 ]\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n    [ 0, 1500, 2000 ]\n\n    See Also\n    --------\n    forEachAsync, inmapRightAsync, inmap\n","inmapAsync.factory":"\ninmapAsync.factory( [options,] fcn )\n    Returns a function which invokes a function once for each element in a\n    collection and updates a collection in-place.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function fcn( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, value*index );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = inmapAsync.factory( opts, fcn );\n    > function done( error, collection ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( collection === arr );\n    ...     console.log( collection );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    [ 0, 2500, 2000 ]\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n    [ 0, 1500, 2000 ]\n\n    See Also\n    --------\n    forEachAsync, inmapRightAsync, inmap","inmapRight":"\ninmapRight( collection, fcn[, thisArg] )\n    Invokes a function for each element in a collection and updates the\n    collection in-place, iterating from right to left.\n\n    When invoked, the input function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection. If provided an object, the object must be array-like\n        (excluding strings and functions).\n\n    fcn: Function\n        Function to invoke for each element in the input collection. The\n        function's return value is used to update the collection in-place.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function foo( v, i ) { console.log( '%s: %d', i, v ); return v * i; };\n    > var arr = [ 1.0, 2.0, 3.0 ];\n    > var out = inmapRight( arr, foo )\n    2: 3.0\n    1: 2.0\n    0: 1.0\n    [ 0.0, 2.0, 6.0 ]\n    > var bool = ( out === arr )\n    true\n\n    See Also\n    --------\n    forEachRight, inmap, mapRight\n","inmapRightAsync":"\ninmapRightAsync( collection, [options,] fcn, done )\n    Invokes a function once for each element in a collection and updates a\n    collection in-place, iterating from right to left.\n\n    When invoked, `fcn` is provided a maximum of four arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If `fcn`\n    accepts two arguments, `fcn` is provided:\n\n    - value\n    - next\n\n    If `fcn` accepts three arguments, `fcn` is provided:\n\n    - value\n    - index\n    - next\n\n    For every other `fcn` signature, `fcn` is provided all four arguments.\n\n    The `next` callback accepts two arguments:\n\n    - error: error argument.\n    - result: value used to update the collection.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling. Note, however, that the function\n    may have mutated an input collection during prior invocations, resulting in\n    a partially mutated collection.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function fcn( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, value*index );\n    ...     }\n    ... };\n    > function done( error, collection ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( collection === arr );\n    ...     console.log( collection );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > inmapRightAsync( arr, fcn, done )\n    1000\n    2500\n    3000\n    true\n    [ 0, 2500, 6000 ]\n\n    // Limit number of concurrent invocations:\n    > function fcn( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, value*index );\n    ...     }\n    ... };\n    > function done( error, collection ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( collection === arr );\n    ...     console.log( collection );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 1000, 2500, 3000 ];\n    > inmapRightAsync( arr, opts, fcn, done )\n    2500\n    3000\n    1000\n    true\n    [ 0, 2500, 6000 ]\n\n    // Process sequentially:\n    > function fcn( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, value*index );\n    ...     }\n    ... };\n    > function done( error, collection ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( collection === arr );\n    ...     console.log( collection );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 1000, 2500, 3000 ];\n    > inmapRightAsync( arr, opts, fcn, done )\n    3000\n    2500\n    1000\n    true\n    [ 0, 2500, 6000 ]\n\n\ninmapRightAsync.factory( [options,] fcn )\n    Returns a function which invokes a function once for each element in a\n    collection and updates a collection in-place, iterating from right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function fcn( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, value*index );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = inmapRightAsync.factory( opts, fcn );\n    > function done( error, collection ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( collection === arr );\n    ...     console.log( collection );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    [ 0, 2500, 6000 ]\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n    [ 0, 1500, 4000 ]\n\n    See Also\n    --------\n    forEachRightAsync, inmapAsync, inmapRight\n","inmapRightAsync.factory":"\ninmapRightAsync.factory( [options,] fcn )\n    Returns a function which invokes a function once for each element in a\n    collection and updates a collection in-place, iterating from right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function fcn( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, value*index );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = inmapRightAsync.factory( opts, fcn );\n    > function done( error, collection ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( collection === arr );\n    ...     console.log( collection );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    [ 0, 2500, 6000 ]\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n    [ 0, 1500, 4000 ]\n\n    See Also\n    --------\n    forEachRightAsync, inmapAsync, inmapRight","inspectSinkStream":"\ninspectSinkStream( [options,] clbk )\n    Returns a writable stream for inspecting stream data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to encode strings as `Buffer` objects before writing\n        data to a returned stream. Default: true.\n\n    options.defaultEncoding: string (optional)\n        Default encoding when not explicitly specified when writing data.\n        Default: 'utf8'.\n\n    clbk: Function\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: WritableStream\n        Writable stream.\n\n    Examples\n    --------\n    > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n    > var s = inspectSinkStream( clbk );\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();\n\n\ninspectSinkStream.factory( [options] )\n    Returns a function for creating writable streams for inspecting stream data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to encode strings as `Buffer` objects before writing\n        data to a returned stream. Default: true.\n\n    options.defaultEncoding: string (optional)\n        Default encoding when not explicitly specified when writing data.\n        Default: 'utf8'.\n\n    Returns\n    -------\n    createStream( clbk ): Function\n        Function for creating writable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = inspectSinkStream.factory( opts );\n    > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n    > var s = createStream( clbk );\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();\n\n\ninspectSinkStream.objectMode( [options,] clbk )\n    Returns an \"objectMode\" writable stream for inspecting stream data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to encode strings as `Buffer` objects before writing\n        data to a returned stream. Default: true.\n\n    options.defaultEncoding: string (optional)\n        Default encoding when not explicitly specified when writing data.\n        Default: 'utf8'.\n\n    clbk: Function\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: WritableStream\n        Writable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n    > var s = inspectSinkStream.objectMode( clbk );\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();\n\n    See Also\n    --------\n    debugSinkStream, inspectStream\n","inspectSinkStream.factory":"\ninspectSinkStream.factory( [options] )\n    Returns a function for creating writable streams for inspecting stream data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to encode strings as `Buffer` objects before writing\n        data to a returned stream. Default: true.\n\n    options.defaultEncoding: string (optional)\n        Default encoding when not explicitly specified when writing data.\n        Default: 'utf8'.\n\n    Returns\n    -------\n    createStream( clbk ): Function\n        Function for creating writable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = inspectSinkStream.factory( opts );\n    > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n    > var s = createStream( clbk );\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();","inspectSinkStream.objectMode":"\ninspectSinkStream.objectMode( [options,] clbk )\n    Returns an \"objectMode\" writable stream for inspecting stream data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to encode strings as `Buffer` objects before writing\n        data to a returned stream. Default: true.\n\n    options.defaultEncoding: string (optional)\n        Default encoding when not explicitly specified when writing data.\n        Default: 'utf8'.\n\n    clbk: Function\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: WritableStream\n        Writable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n    > var s = inspectSinkStream.objectMode( clbk );\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();\n\n    See Also\n    --------\n    debugSinkStream, inspectStream","inspectStream":"\ninspectStream( [options,] clbk )\n    Returns a transform stream for inspecting stream data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    clbk: Function\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream.\n\n    Examples\n    --------\n    > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n    > var s = inspectStream( clbk );\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();\n\n\ninspectStream.factory( [options] )\n    Returns a function for creating transform streams for inspecting stream\n    data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    createStream( clbk ): Function\n        Function for creating transform streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = inspectStream.factory( opts );\n    > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n    > var s = createStream( clbk );\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();\n\n\ninspectStream.objectMode( [options,] clbk )\n    Returns an \"objectMode\" transform stream for inspecting stream data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    clbk: Function\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n    > var s = inspectStream.objectMode( clbk );\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();\n\n    See Also\n    --------\n    debugStream\n","inspectStream.factory":"\ninspectStream.factory( [options] )\n    Returns a function for creating transform streams for inspecting stream\n    data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    createStream( clbk ): Function\n        Function for creating transform streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = inspectStream.factory( opts );\n    > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n    > var s = createStream( clbk );\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();","inspectStream.objectMode":"\ninspectStream.objectMode( [options,] clbk )\n    Returns an \"objectMode\" transform stream for inspecting stream data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    clbk: Function\n        Callback to invoke upon receiving data.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function clbk( chunk, idx ) { console.log( chunk.toString() ); };\n    > var s = inspectStream.objectMode( clbk );\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();\n\n    See Also\n    --------\n    debugStream","instanceOf":"\ninstanceOf( value, constructor )\n    Tests whether a value has in its prototype chain a specified constructor as\n    a prototype property.\n\n    While the prototype of an `object` created using object literal notion is\n    `undefined`, the function returns `true` when provided an `object` literal\n    and the `Object` constructor. This maintains consistent behavior with the\n    `instanceof` operator.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    constructor: Function\n        Constructor.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is an instance of a provided constructor.\n\n    Examples\n    --------\n    > var bool = instanceOf( [], Array )\n    true\n    > bool = instanceOf( {}, Object )\n    true\n    > bool = instanceOf( null, Object )\n    false\n\n    See Also\n    --------\n    isPrototypeOf, constructorName, inherit, typeOf\n","INT8_MAX":"\nINT8_MAX\n    Maximum signed 8-bit integer.\n\n    The maximum signed 8-bit integer is given by `2^7 - 1`.\n\n    Examples\n    --------\n    > INT8_MAX\n    127\n\n    See Also\n    --------\n    INT8_MIN\n","INT8_MIN":"\nINT8_MIN\n    Minimum signed 8-bit integer.\n\n    The minimum signed 8-bit integer is given by `-(2^7)`.\n\n    Examples\n    --------\n    > INT8_MIN\n    -128\n\n    See Also\n    --------\n    INT8_MAX\n","INT8_NUM_BYTES":"\nINT8_NUM_BYTES\n    Size (in bytes) of an 8-bit signed integer.\n\n    Examples\n    --------\n    > INT8_NUM_BYTES\n    1\n\n    See Also\n    --------\n    INT16_NUM_BYTES, INT32_NUM_BYTES, UINT8_NUM_BYTES\n","Int8Array":"\nInt8Array()\n    A typed array constructor which returns a typed array representing an array\n    of twos-complement 8-bit signed integers in the platform byte order.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Int8Array()\n    <Int8Array>\n\n\nInt8Array( length )\n    Returns a typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( 5 )\n    <Int8Array>[ 0, 0, 0, 0, 0 ]\n\n\nInt8Array( typedarray )\n    Creates a typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n    > var arr2 = new Int8Array( arr1 )\n    <Int8Array>[ 5, 5, 5 ]\n\n\nInt8Array( obj )\n    Creates a typed array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a typed array.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 5.0, 5.0, 5.0 ];\n    > var arr2 = new Int8Array( arr1 )\n    <Int8Array>[ 5, 5, 5 ]\n\n\nInt8Array( buffer[, byteOffset[, length]] )\n    Returns a typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 4 );\n    > var arr = new Int8Array( buf, 0, 4 )\n    <Int8Array>[ 0, 0, 0, 0 ]\n\n\nInt8Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Int8Array.from( [ 1, 2 ], mapFcn )\n    <Int8Array>[ 2, 4 ]\n\n\nInt8Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Int8Array.of( 1, 2 )\n    <Int8Array>[ 1, 2 ]\n\n\nInt8Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Int8Array.BYTES_PER_ELEMENT\n    1\n\n\nInt8Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Int8Array.name\n    'Int8Array'\n\n\nInt8Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>\n\n\nInt8Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( 5 );\n    > arr.byteLength\n    5\n\n\nInt8Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Int8Array( 5 );\n    > arr.byteOffset\n    0\n\n\nInt8Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Int8Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    1\n\n\nInt8Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Int8Array( 5 );\n    > arr.length\n    5\n\n\nInt8Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Int8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2\n\n\nInt8Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true\n\n\nInt8Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false\n\n\nInt8Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Int8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3\n\n\nInt8Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2\n\n\nInt8Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3\n\n\nInt8Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2\n\n\nInt8Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '\n\n\nInt8Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true\n\n\nInt8Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2\n\n\nInt8Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'\n\n\nInt8Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true\n\n\nInt8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3\n\n\nInt8Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Int8Array>[ 2, 4, 6 ]\n\n\nInt8Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14\n\n\nInt8Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14\n\n\nInt8Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Int8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] )\n    <Int8Array>\n    > arr.reverse()\n    <Int8Array>[ 3, 2, 1 ]\n\n\nInt8Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4\n\n\nInt8Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3\n\n\nInt8Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true\n\n\nInt8Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Int8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Int8Array>[ 0, 1, 1, 2, 2 ]\n\n\nInt8Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int8Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Int8Array>[ 3, 4, 5 ]\n\n\nInt8Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'\n\n\nInt8Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'\n\n\nInt8Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Int8Array.from":"\nInt8Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Int8Array.from( [ 1, 2 ], mapFcn )\n    <Int8Array>[ 2, 4 ]","Int8Array.of":"\nInt8Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Int8Array.of( 1, 2 )\n    <Int8Array>[ 1, 2 ]","Int8Array.BYTES_PER_ELEMENT":"\nInt8Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Int8Array.BYTES_PER_ELEMENT\n    1","Int8Array.name":"\nInt8Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Int8Array.name\n    'Int8Array'","Int8Array.prototype.buffer":"\nInt8Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>","Int8Array.prototype.byteLength":"\nInt8Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( 5 );\n    > arr.byteLength\n    5","Int8Array.prototype.byteOffset":"\nInt8Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Int8Array( 5 );\n    > arr.byteOffset\n    0","Int8Array.prototype.BYTES_PER_ELEMENT":"\nInt8Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Int8Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    1","Int8Array.prototype.length":"\nInt8Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Int8Array( 5 );\n    > arr.length\n    5","Int8Array.prototype.copyWithin":"\nInt8Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Int8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2","Int8Array.prototype.entries":"\nInt8Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true","Int8Array.prototype.every":"\nInt8Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false","Int8Array.prototype.fill":"\nInt8Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Int8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3","Int8Array.prototype.filter":"\nInt8Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2","Int8Array.prototype.find":"\nInt8Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3","Int8Array.prototype.findIndex":"\nInt8Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2","Int8Array.prototype.forEach":"\nInt8Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '","Int8Array.prototype.includes":"\nInt8Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true","Int8Array.prototype.indexOf":"\nInt8Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2","Int8Array.prototype.join":"\nInt8Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'","Int8Array.prototype.keys":"\nInt8Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true","Int8Array.prototype.lastIndexOf":"\nInt8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3","Int8Array.prototype.map":"\nInt8Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Int8Array>[ 2, 4, 6 ]","Int8Array.prototype.reduce":"\nInt8Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14","Int8Array.prototype.reduceRight":"\nInt8Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14","Int8Array.prototype.reverse":"\nInt8Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Int8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] )\n    <Int8Array>\n    > arr.reverse()\n    <Int8Array>[ 3, 2, 1 ]","Int8Array.prototype.set":"\nInt8Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4","Int8Array.prototype.slice":"\nInt8Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int8Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3","Int8Array.prototype.some":"\nInt8Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true","Int8Array.prototype.sort":"\nInt8Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Int8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Int8Array>[ 0, 1, 1, 2, 2 ]","Int8Array.prototype.subarray":"\nInt8Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int8Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Int8Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Int8Array>[ 3, 4, 5 ]","Int8Array.prototype.toLocaleString":"\nInt8Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'","Int8Array.prototype.toString":"\nInt8Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'","Int8Array.prototype.values":"\nInt8Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Int8Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","INT16_MAX":"\nINT16_MAX\n    Maximum signed 16-bit integer.\n\n    The maximum signed 16-bit integer is given by `2^15 - 1`.\n\n    Examples\n    --------\n    > INT16_MAX\n    32767\n\n    See Also\n    --------\n    INT16_MIN\n","INT16_MIN":"\nINT16_MIN\n    Minimum signed 16-bit integer.\n\n    The minimum signed 16-bit integer is given by `-(2^15)`.\n\n    Examples\n    --------\n    > INT16_MIN\n    -32768\n\n    See Also\n    --------\n    INT16_MAX\n","INT16_NUM_BYTES":"\nINT16_NUM_BYTES\n    Size (in bytes) of a 16-bit signed integer.\n\n    Examples\n    --------\n    > INT16_NUM_BYTES\n    2\n\n    See Also\n    --------\n    INT32_NUM_BYTES, INT8_NUM_BYTES, UINT16_NUM_BYTES\n","Int16Array":"\nInt16Array()\n    A typed array constructor which returns a typed array representing an array\n    of twos-complement 16-bit signed integers in the platform byte order.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Int16Array()\n    <Int16Array>\n\n\nInt16Array( length )\n    Returns a typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( 5 )\n    <Int16Array>[ 0, 0, 0, 0, 0 ]\n\n\nInt16Array( typedarray )\n    Creates a typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n    > var arr2 = new Int16Array( arr1 )\n    <Int16Array>[ 5, 5, 5 ]\n\n\nInt16Array( obj )\n    Creates a typed array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a typed array.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 5.0, 5.0, 5.0 ];\n    > var arr2 = new Int16Array( arr1 )\n    <Int16Array>[ 5, 5, 5 ]\n\n\nInt16Array( buffer[, byteOffset[, length]] )\n    Returns a typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 8 );\n    > var arr = new Int16Array( buf, 0, 4 )\n    <Int16Array>[ 0, 0, 0, 0 ]\n\n\nInt16Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Int16Array.from( [ 1, 2 ], mapFcn )\n    <Int16Array>[ 2, 4 ]\n\n\nInt16Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Int16Array.of( 1, 2 )\n    <Int16Array>[ 1, 2 ]\n\n\nInt16Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Int16Array.BYTES_PER_ELEMENT\n    2\n\n\nInt16Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Int16Array.name\n    'Int16Array'\n\n\nInt16Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>\n\n\nInt16Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( 5 );\n    > arr.byteLength\n    10\n\n\nInt16Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Int16Array( 5 );\n    > arr.byteOffset\n    0\n\n\nInt16Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Int16Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    2\n\n\nInt16Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Int16Array( 5 );\n    > arr.length\n    5\n\n\nInt16Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Int16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2\n\n\nInt16Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true\n\n\nInt16Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false\n\n\nInt16Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Int16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3\n\n\nInt16Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2\n\n\nInt16Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3\n\n\nInt16Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2\n\n\nInt16Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '\n\n\nInt16Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true\n\n\nInt16Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2\n\n\nInt16Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'\n\n\nInt16Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true\n\n\nInt16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3\n\n\nInt16Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Int16Array>[ 2, 4, 6 ]\n\n\nInt16Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14\n\n\nInt16Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14\n\n\nInt16Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Int16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] )\n    <Int16Array>\n    > arr.reverse()\n    <Int16Array>[ 3, 2, 1 ]\n\n\nInt16Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4\n\n\nInt16Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3\n\n\nInt16Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true\n\n\nInt16Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Int16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Int16Array>[ 0, 1, 1, 2, 2 ]\n\n\nInt16Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int16Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Int16Array>[ 3, 4, 5 ]\n\n\nInt16Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'\n\n\nInt16Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'\n\n\nInt16Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Int16Array.from":"\nInt16Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Int16Array.from( [ 1, 2 ], mapFcn )\n    <Int16Array>[ 2, 4 ]","Int16Array.of":"\nInt16Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Int16Array.of( 1, 2 )\n    <Int16Array>[ 1, 2 ]","Int16Array.BYTES_PER_ELEMENT":"\nInt16Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Int16Array.BYTES_PER_ELEMENT\n    2","Int16Array.name":"\nInt16Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Int16Array.name\n    'Int16Array'","Int16Array.prototype.buffer":"\nInt16Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>","Int16Array.prototype.byteLength":"\nInt16Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( 5 );\n    > arr.byteLength\n    10","Int16Array.prototype.byteOffset":"\nInt16Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Int16Array( 5 );\n    > arr.byteOffset\n    0","Int16Array.prototype.BYTES_PER_ELEMENT":"\nInt16Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Int16Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    2","Int16Array.prototype.length":"\nInt16Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Int16Array( 5 );\n    > arr.length\n    5","Int16Array.prototype.copyWithin":"\nInt16Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Int16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2","Int16Array.prototype.entries":"\nInt16Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true","Int16Array.prototype.every":"\nInt16Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false","Int16Array.prototype.fill":"\nInt16Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Int16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3","Int16Array.prototype.filter":"\nInt16Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2","Int16Array.prototype.find":"\nInt16Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3","Int16Array.prototype.findIndex":"\nInt16Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2","Int16Array.prototype.forEach":"\nInt16Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '","Int16Array.prototype.includes":"\nInt16Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true","Int16Array.prototype.indexOf":"\nInt16Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2","Int16Array.prototype.join":"\nInt16Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'","Int16Array.prototype.keys":"\nInt16Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true","Int16Array.prototype.lastIndexOf":"\nInt16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3","Int16Array.prototype.map":"\nInt16Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Int16Array>[ 2, 4, 6 ]","Int16Array.prototype.reduce":"\nInt16Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14","Int16Array.prototype.reduceRight":"\nInt16Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14","Int16Array.prototype.reverse":"\nInt16Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Int16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] )\n    <Int16Array>\n    > arr.reverse()\n    <Int16Array>[ 3, 2, 1 ]","Int16Array.prototype.set":"\nInt16Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4","Int16Array.prototype.slice":"\nInt16Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int16Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3","Int16Array.prototype.some":"\nInt16Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true","Int16Array.prototype.sort":"\nInt16Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Int16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Int16Array>[ 0, 1, 1, 2, 2 ]","Int16Array.prototype.subarray":"\nInt16Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int16Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Int16Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Int16Array>[ 3, 4, 5 ]","Int16Array.prototype.toLocaleString":"\nInt16Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'","Int16Array.prototype.toString":"\nInt16Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'","Int16Array.prototype.values":"\nInt16Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Int16Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","INT32_MAX":"\nINT32_MAX\n    Maximum signed 32-bit integer.\n\n    The maximum signed 32-bit integer is given by `2^31 - 1`.\n\n    Examples\n    --------\n    > INT32_MAX\n    2147483647\n\n    See Also\n    --------\n    INT32_MIN\n","INT32_MIN":"\nINT32_MIN\n    Minimum signed 32-bit integer.\n\n    The minimum signed 32-bit integer is given by `-(2^31)`.\n\n    Examples\n    --------\n    > INT32_MIN\n    -2147483648\n\n    See Also\n    --------\n    INT32_MAX\n","INT32_NUM_BYTES":"\nINT32_NUM_BYTES\n    Size (in bytes) of a 32-bit signed integer.\n\n    Examples\n    --------\n    > INT32_NUM_BYTES\n    4\n\n    See Also\n    --------\n    INT16_NUM_BYTES, INT8_NUM_BYTES, UINT32_NUM_BYTES\n","Int32Array":"\nInt32Array()\n    A typed array constructor which returns a typed array representing an array\n    of twos-complement 32-bit signed integers in the platform byte order.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Int32Array()\n    <Int32Array>\n\n\nInt32Array( length )\n    Returns a typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( 5 )\n    <Int32Array>[ 0, 0, 0, 0, 0 ]\n\n\nInt32Array( typedarray )\n    Creates a typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int16Array( [ 5, 5, 5 ] );\n    > var arr2 = new Int32Array( arr1 )\n    <Int32Array>[ 5, 5, 5 ]\n\n\nInt32Array( obj )\n    Creates a typed array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a typed array.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 5.0, 5.0, 5.0 ];\n    > var arr2 = new Int32Array( arr1 )\n    <Int32Array>[ 5, 5, 5 ]\n\n\nInt32Array( buffer[, byteOffset[, length]] )\n    Returns a typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 16 );\n    > var arr = new Int32Array( buf, 0, 4 )\n    <Int32Array>[ 0, 0, 0, 0 ]\n\n\nInt32Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Int32Array.from( [ 1, 2 ], mapFcn )\n    <Int32Array>[ 2, 4 ]\n\n\nInt32Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Int32Array.of( 1, 2 )\n    <Int32Array>[ 1, 2 ]\n\n\nInt32Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Int32Array.BYTES_PER_ELEMENT\n    4\n\n\nInt32Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Int32Array.name\n    'Int32Array'\n\n\nInt32Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>\n\n\nInt32Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( 5 );\n    > arr.byteLength\n    20\n\n\nInt32Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Int32Array( 5 );\n    > arr.byteOffset\n    0\n\n\nInt32Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Int32Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    4\n\n\nInt32Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Int32Array( 5 );\n    > arr.length\n    5\n\n\nInt32Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Int32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2\n\n\nInt32Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true\n\n\nInt32Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false\n\n\nInt32Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Int32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3\n\n\nInt32Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2\n\n\nInt32Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3\n\n\nInt32Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2\n\n\nInt32Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '\n\n\nInt32Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true\n\n\nInt32Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2\n\n\nInt32Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'\n\n\nInt32Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true\n\n\nInt32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3\n\n\nInt32Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Int32Array>[ 2, 4, 6 ]\n\n\nInt32Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14\n\n\nInt32Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14\n\n\nInt32Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Int32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] )\n    <Int32Array>\n    > arr.reverse()\n    <Int32Array>[ 3, 2, 1 ]\n\n\nInt32Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4\n\n\nInt32Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3\n\n\nInt32Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true\n\n\nInt32Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Int32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Int32Array>[ 0, 1, 1, 2, 2 ]\n\n\nInt32Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int32Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Int32Array>[ 3, 4, 5 ]\n\n\nInt32Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'\n\n\nInt32Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'\n\n\nInt32Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Int32Array.from":"\nInt32Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Int32Array.from( [ 1, 2 ], mapFcn )\n    <Int32Array>[ 2, 4 ]","Int32Array.of":"\nInt32Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Int32Array.of( 1, 2 )\n    <Int32Array>[ 1, 2 ]","Int32Array.BYTES_PER_ELEMENT":"\nInt32Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Int32Array.BYTES_PER_ELEMENT\n    4","Int32Array.name":"\nInt32Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Int32Array.name\n    'Int32Array'","Int32Array.prototype.buffer":"\nInt32Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>","Int32Array.prototype.byteLength":"\nInt32Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( 5 );\n    > arr.byteLength\n    20","Int32Array.prototype.byteOffset":"\nInt32Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Int32Array( 5 );\n    > arr.byteOffset\n    0","Int32Array.prototype.BYTES_PER_ELEMENT":"\nInt32Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Int32Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    4","Int32Array.prototype.length":"\nInt32Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Int32Array( 5 );\n    > arr.length\n    5","Int32Array.prototype.copyWithin":"\nInt32Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Int32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2","Int32Array.prototype.entries":"\nInt32Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true","Int32Array.prototype.every":"\nInt32Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false","Int32Array.prototype.fill":"\nInt32Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Int32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3","Int32Array.prototype.filter":"\nInt32Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2","Int32Array.prototype.find":"\nInt32Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3","Int32Array.prototype.findIndex":"\nInt32Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2","Int32Array.prototype.forEach":"\nInt32Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '","Int32Array.prototype.includes":"\nInt32Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true","Int32Array.prototype.indexOf":"\nInt32Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2","Int32Array.prototype.join":"\nInt32Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'","Int32Array.prototype.keys":"\nInt32Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true","Int32Array.prototype.lastIndexOf":"\nInt32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3","Int32Array.prototype.map":"\nInt32Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Int32Array>[ 2, 4, 6 ]","Int32Array.prototype.reduce":"\nInt32Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14","Int32Array.prototype.reduceRight":"\nInt32Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14","Int32Array.prototype.reverse":"\nInt32Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Int32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] )\n    <Int32Array>\n    > arr.reverse()\n    <Int32Array>[ 3, 2, 1 ]","Int32Array.prototype.set":"\nInt32Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4","Int32Array.prototype.slice":"\nInt32Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3","Int32Array.prototype.some":"\nInt32Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true","Int32Array.prototype.sort":"\nInt32Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Int32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Int32Array>[ 0, 1, 1, 2, 2 ]","Int32Array.prototype.subarray":"\nInt32Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Int32Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Int32Array>[ 3, 4, 5 ]","Int32Array.prototype.toLocaleString":"\nInt32Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'","Int32Array.prototype.toString":"\nInt32Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'","Int32Array.prototype.values":"\nInt32Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Int32Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","IS_BIG_ENDIAN":"\nIS_BIG_ENDIAN\n    Boolean indicating if the environment is big endian.\n\n    Examples\n    --------\n    > IS_BIG_ENDIAN\n    <boolean>\n\n    See Also\n    --------\n    IS_LITTLE_ENDIAN\n","IS_BROWSER":"\nIS_BROWSER\n    Boolean indicating if the runtime is a web browser.\n\n    Examples\n    --------\n    > IS_BROWSER\n    <boolean>\n\n","IS_DARWIN":"\nIS_DARWIN\n    Boolean indicating if the current process is running on Darwin.\n\n    Examples\n    --------\n    > IS_DARWIN\n    <boolean>\n\n","IS_DOCKER":"\nIS_DOCKER\n    Boolean indicating if the process is running in a Docker container.\n\n    Examples\n    --------\n    > IS_DOCKER\n    <boolean>\n\n","IS_ELECTRON":"\nIS_ELECTRON\n    Boolean indicating if the runtime is Electron.\n\n    Examples\n    --------\n    > IS_ELECTRON\n    <boolean>\n\n    See Also\n    --------\n    IS_ELECTRON_MAIN, IS_ELECTRON_RENDERER\n","IS_ELECTRON_MAIN":"\nIS_ELECTRON_MAIN\n    Boolean indicating if the runtime is the main Electron process.\n\n    Examples\n    --------\n    > IS_ELECTRON_MAIN\n    <boolean>\n\n    See Also\n    --------\n    IS_ELECTRON, IS_ELECTRON_RENDERER\n","IS_ELECTRON_RENDERER":"\nIS_ELECTRON_RENDERER\n    Boolean indicating if the runtime is the Electron renderer process.\n\n    Examples\n    --------\n    > IS_ELECTRON_RENDERER\n    <boolean>\n\n    See Also\n    --------\n    IS_ELECTRON, IS_ELECTRON_MAIN\n","IS_LITTLE_ENDIAN":"\nIS_LITTLE_ENDIAN\n    Boolean indicating if the environment is little endian.\n\n    Examples\n    --------\n    > IS_LITTLE_ENDIAN\n    <boolean>\n\n    See Also\n    --------\n    IS_BIG_ENDIAN\n","IS_MOBILE":"\nIS_MOBILE\n    Boolean indicating if the current environment is a mobile device.\n\n    Examples\n    --------\n    > IS_MOBILE\n    <boolean>\n\n","IS_NODE":"\nIS_NODE\n    Boolean indicating if the runtime is Node.js.\n\n    Examples\n    --------\n    > IS_NODE\n    <boolean>\n\n","IS_TOUCH_DEVICE":"\nIS_TOUCH_DEVICE\n    Boolean indicating if the current environment is a touch device.\n\n    Examples\n    --------\n    > IS_TOUCH_DEVICE\n    <boolean>\n\n","IS_WEB_WORKER":"\nIS_WEB_WORKER\n    Boolean indicating if the runtime is a web worker.\n\n    Examples\n    --------\n    > IS_WEB_WORKER\n    <boolean>\n\n","IS_WINDOWS":"\nIS_WINDOWS\n    Boolean indicating if the current process is running on Windows.\n\n    Examples\n    --------\n    > IS_WINDOWS\n    <boolean>\n\n","isAbsoluteHttpURI":"\nisAbsoluteHttpURI( value )\n    Tests whether a value is an absolute HTTP(S) URI.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether a value is an absolute HTTP(S) URI.\n\n    Examples\n    --------\n    > var bool = isAbsoluteHttpURI( 'http://example.com/' )\n    true\n    > bool = isAbsoluteHttpURI( 'example.com' )\n    false\n    > bool = isAbsoluteHttpURI( 'foo@bar.com' )\n    false\n\n    See Also\n    --------\n    isAbsoluteURI","isAbsolutePath":"\nisAbsolutePath( value )\n    Tests if a value is an absolute path.\n\n    Function behavior is platform-specific. On Windows platforms, the function\n    is equal to `.win32()`. On POSIX platforms, the function is equal to\n    `.posix()`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is an absolute path.\n\n    Examples\n    --------\n    // Windows environment:\n    > var bool = isAbsolutePath( 'C:\\\\foo\\\\bar\\\\baz' )\n    true\n\n    // POSIX environment:\n    > bool = isAbsolutePath( '/foo/bar/baz' )\n    true\n\n\nisAbsolutePath.posix( value )\n    Tests if a value is a POSIX absolute path.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is a POSIX absolute path.\n\n    Examples\n    --------\n    > var bool = isAbsolutePath.posix( '/foo/bar/baz' )\n    true\n    > bool = isAbsolutePath.posix( 'foo/bar/baz' )\n    false\n\n\nisAbsolutePath.win32( value )\n    Tests if a value is a Windows absolute path.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is a Windows absolute path.\n\n    Examples\n    --------\n    > var bool = isAbsolutePath.win32( 'C:\\\\foo\\\\bar\\\\baz' )\n    true\n    > bool = isAbsolutePath.win32( 'foo\\\\bar\\\\baz' )\n    false\n\n    See Also\n    --------\n    isRelativePath\n","isAbsolutePath.posix":"\nisAbsolutePath.posix( value )\n    Tests if a value is a POSIX absolute path.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is a POSIX absolute path.\n\n    Examples\n    --------\n    > var bool = isAbsolutePath.posix( '/foo/bar/baz' )\n    true\n    > bool = isAbsolutePath.posix( 'foo/bar/baz' )\n    false","isAbsolutePath.win32":"\nisAbsolutePath.win32( value )\n    Tests if a value is a Windows absolute path.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is a Windows absolute path.\n\n    Examples\n    --------\n    > var bool = isAbsolutePath.win32( 'C:\\\\foo\\\\bar\\\\baz' )\n    true\n    > bool = isAbsolutePath.win32( 'foo\\\\bar\\\\baz' )\n    false\n\n    See Also\n    --------\n    isRelativePath","isAbsoluteURI":"\nisAbsoluteURI( value )\n    Tests whether a value is an absolute URI.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether a value is an absolute URI.\n\n    Examples\n    --------\n    > var bool = isAbsoluteURI( 'http://example.com/' )\n    true\n    > bool = isAbsoluteURI( 'example.com' )\n    false\n    > bool = isAbsoluteURI( 'foo@bar.com' )\n    false\n\n    See Also\n    --------\n    isRelativeURI","isAccessorArray":"\nisAccessorArray( value )\n    Tests if a value is an array-like object supporting the accessor (get/set)\n    protocol.\n\n    An accessor array is defined as an array, typed array, or an array-like\n    object (excluding strings and functions) having `get` and `set` methods for\n    accessing array elements.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an accessor array.\n\n    Examples\n    --------\n    > var bool = isAccessorArray( new Complex64Array( 10 ) )\n    true\n    > bool = isAccessorArray( [] )\n    false\n    > bool = isAccessorArray( { 'length': 0 } )\n    false\n    > bool = isAccessorArray( {} )\n    false\n\n    See Also\n    --------\n    isArrayLike, isArrayLikeObject, isCollection\n","isAccessorProperty":"\nisAccessorProperty( value, property )\n    Tests if an object's own property has an accessor descriptor.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own property has an accessor\n        descriptor.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.get = function getter() { return 'beep'; };\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isAccessorProperty( obj, 'boop' )\n    false\n    > bool = isAccessorProperty( obj, 'beep' )\n    true\n\n    See Also\n    --------\n    hasOwnProp, isAccessorPropertyIn, isDataProperty\n","isAccessorPropertyIn":"\nisAccessorPropertyIn( value, property )\n    Tests if an object's own or inherited property has an accessor descriptor.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own or inherited property has an\n        accessor descriptor.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.get = function getter() { return 'beep'; };\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isAccessorPropertyIn( obj, 'boop' )\n    false\n    > bool = isAccessorPropertyIn( obj, 'beep' )\n    true\n\n    See Also\n    --------\n    hasProp, isAccessorProperty, isDataPropertyIn\n","isAlphagram":"\nisAlphagram( value )\n    Tests if a value is an alphagram (i.e., a sequence of characters arranged in\n    alphabetical order).\n\n    The function first checks that an input value is a string before validating\n    that the value is an alphagram. For non-string values, the function returns\n    `false`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an alphagram.\n\n    Examples\n    --------\n    > var out = isAlphagram( 'beep' )\n    true\n    > out = isAlphagram( 'zba' )\n    false\n    > out = isAlphagram( '' )\n    false\n\n    See Also\n    --------\n    isAnagram\n","isAlphaNumeric":"\nisAlphaNumeric( str )\n    Tests whether a string contains only alphanumeric characters.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a string contains only alphanumeric\n        characters.\n\n    Examples\n    --------\n    > var bool = isAlphaNumeric( 'abc0123456789' )\n    true\n    > bool = isAlphaNumeric( 'abcdef' )\n    true\n    > bool = isAlphaNumeric( '0xff' )\n    true\n    > bool = isAlphaNumeric( '' )\n    false\n\n    See Also\n    --------\n    isDigitString\n","isAnagram":"\nisAnagram( str, value )\n    Tests if a value is an anagram.\n\n    Parameters\n    ----------\n    str: string\n        Comparison string.\n\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an anagram.\n\n    Examples\n    --------\n    > var str1 = 'I am a weakish speller';\n    > var str2 = 'William Shakespeare';\n    > var bool = isAnagram( str1, str2 )\n    true\n    > bool = isAnagram( 'bat', 'tabba' )\n    false\n\n    See Also\n    --------\n    isAlphagram\n","isArguments":"\nisArguments( value )\n    Tests if a value is an arguments object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an arguments object.\n\n    Examples\n    --------\n    > function foo() { return arguments; };\n    > var bool = isArguments( foo() )\n    true\n    > bool = isArguments( [] )\n    false\n\n","isArray":"\nisArray( value )\n    Tests if a value is an array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array.\n\n    Examples\n    --------\n    > var bool = isArray( [] )\n    true\n    > bool = isArray( {} )\n    false\n\n    See Also\n    --------\n    isArrayLike\n","isArrayArray":"\nisArrayArray( value )\n    Tests if a value is an array of arrays.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array of arrays.\n\n    Examples\n    --------\n    > var bool = isArrayArray( [ [], [] ] )\n    true\n    > bool = isArrayArray( [ {}, {} ] )\n    false\n    > bool = isArrayArray( [] )\n    false\n\n","isArrayBuffer":"\nisArrayBuffer( value )\n    Tests if a value is an ArrayBuffer.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an ArrayBuffer.\n\n    Examples\n    --------\n    > var bool = isArrayBuffer( new ArrayBuffer( 10 ) )\n    true\n    > bool = isArrayBuffer( [] )\n    false\n\n    See Also\n    --------\n    isSharedArrayBuffer, isTypedArray\n","isArrayBufferView":"\nisArrayBufferView( value )\n    Tests if a value is a `ArrayBuffer` view.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a `ArrayBuffer` view.\n\n    Examples\n    --------\n    > var bool = isArrayBufferView( new Int8Array() )\n    true\n    > bool = isArrayBufferView( [] )\n    false\n\n    See Also\n    --------\n    isDataView, isTypedArray\n","isArrayLength":"\nisArrayLength( value )\n    Tests if a value is a valid array length.\n\n    A valid length property for an Array instance is any integer value on the\n    interval [0, 2^32-1].\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a valid array length.\n\n    Examples\n    --------\n    > var bool = isArrayLength( 5 )\n    true\n    > bool = isArrayLength( 2.0e200 )\n    false\n    > bool = isArrayLength( -3.14 )\n    false\n    > bool = isArrayLength( null )\n    false\n\n    See Also\n    --------\n    isArray\n","isArrayLike":"\nisArrayLike( value )\n    Tests if a value is array-like.\n\n    If provided a string, the function returns `true`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is array-like.\n\n    Examples\n    --------\n    > var bool = isArrayLike( [] )\n    true\n    > bool = isArrayLike( { 'length': 10 } )\n    true\n    > bool = isArrayLike( 'beep' )\n    true\n    > bool = isArrayLike( null )\n    false\n\n    See Also\n    --------\n    isArray, isArrayLikeObject, isCollection\n","isArrayLikeObject":"\nisArrayLikeObject( value )\n    Tests if a value is an array-like object.\n\n    If provided a string, the function returns `false`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object.\n\n    Examples\n    --------\n    > var bool = isArrayLikeObject( [] )\n    true\n    > bool = isArrayLikeObject( { 'length': 10 } )\n    true\n    > bool = isArrayLikeObject( 'beep' )\n    false\n\n    See Also\n    --------\n    isArray, isArrayLike, isCollection\n","isArrowFunction":"\nisArrowFunction( value )\n    Tests if a value is an arrow function.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an arrow function.\n\n    Examples\n    --------\n    > function beep() {};\n    > var bool = isArrowFunction( beep )\n    false\n    > bool = isArrowFunction( {} )\n    false\n\n","isASCII":"\nisASCII( str )\n    Tests whether a character belongs to the ASCII character set and whether\n    this is true for all characters in a provided string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a string has all ASCII characters.\n\n    Examples\n    --------\n    > var str = 'beep boop';\n    > var bool = isASCII( str )\n    true\n    > bool = isASCII( fromCodePoint( 130 ) )\n    false\n\n    See Also\n    --------\n    isString\n","isBetween":"\nisBetween( value, a, b[, left, right] )\n    Tests if a value is between two values.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    a: any\n        Left comparison value.\n\n    b: any\n        Right comparison value.\n\n    left: string (optional)\n        Indicates whether the left comparison value is inclusive. Must be either\n        'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n    right: string (optional)\n        Indicates whether the right comparison value is inclusive. Must be\n        either 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is between two values.\n\n    Examples\n    --------\n    > var bool = isBetween( 3.14, 3.0, 4.0 )\n    true\n    > bool = isBetween( 3.0, 3.0, 4.0 )\n    true\n    > bool = isBetween( 4.0, 3.0, 4.0 )\n    true\n    > bool = isBetween( 3.0, 3.14, 4.0 )\n    false\n    > bool = isBetween( 3.14, 3.14, 4.0, 'open', 'closed' )\n    false\n    > bool = isBetween( 3.14, 3.0, 3.14, 'closed', 'open' )\n    false\n\n    See Also\n    --------\n    isBetweenArray\n","isBetweenArray":"\nisBetweenArray( value, a, b[, left, right] )\n    Tests if a value is an array-like object where every element is between two\n    values.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    a: any\n        Left comparison value.\n\n    b: any\n        Right comparison value.\n\n    left: string (optional)\n        Indicates whether the left comparison value is inclusive. Must be either\n        'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n    right: string (optional)\n        Indicates whether the right comparison value is inclusive. Must be\n        either 'closed' or 'open'. Default: 'closed' (i.e., inclusive).\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object where every\n        element is between two values.\n\n    Examples\n    --------\n    > var arr = [ 3.0, 3.14, 4.0 ];\n    > var bool = isBetweenArray( arr, 3.0, 4.0 )\n    true\n    > bool = isBetweenArray( arr, 3.14, 4.0 )\n    false\n    > bool = isBetweenArray( arr, 3.0, 3.14 )\n    false\n    > bool = isBetweenArray( arr, 3.0, 4.0, 'open', 'closed' )\n    false\n    > bool = isBetweenArray( arr, 3.0, 4.0, 'closed', 'open' )\n    false\n\n    See Also\n    --------\n    isBetween\n","isBigInt":"\nisBigInt( value )\n    Tests if a value is a BigInt.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a BigInt.\n\n    Examples\n    --------\n    > var bool = isBigInt( BigInt( '1' ) )\n    true\n    > bool = isBigInt( Object( BigInt( '1' ) ) )\n    true\n    > bool = isBigInt( {} )\n    false\n    > bool = isBigInt( null )\n    false\n    > bool = isBigInt( true )\n    false\n\n","isBigInt64Array":"\nisBigInt64Array( value )\n    Tests if a value is a BigInt64Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a BigInt64Array.\n\n    Examples\n    --------\n    > var bool = isBigInt64Array( new BigInt64Array( 10 ) )\n    true\n    > bool = isBigInt64Array( [] )\n    false\n\n    See Also\n    --------\n    isBigUint64Array\n","isBigUint64Array":"\nisBigUint64Array( value )\n    Tests if a value is a BigUint64Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a BigUint64Array.\n\n    Examples\n    --------\n    > var bool = isBigUint64Array( new BigUint64Array( 10 ) )\n    true\n    > bool = isBigUint64Array( [] )\n    false\n\n    See Also\n    --------\n    isBigInt64Array\n","isBinaryString":"\nisBinaryString( value )\n    Tests if a value is a binary string.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a binary string.\n\n    Examples\n    --------\n    > var bool = isBinaryString( '1000101' )\n    true\n    > bool = isBinaryString( 'beep' )\n    false\n    > bool = isBinaryString( '' )\n    false\n\n    See Also\n    --------\n    isString\n","isBlankString":"\nisBlankString( value )\n    Tests if a value is a blank string (i.e., an empty string or a string\n    consisting only of whitespace characters).\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a blank string.\n\n    Examples\n    --------\n    > var bool = isBlankString( '   ' )\n    true\n    > bool = isBlankString( 'beep' )\n    false\n    > bool = isBlankString( null )\n    false\n\n    See Also\n    --------\n    isString, isEmptyString\n","isBoolean":"\nisBoolean( value )\n    Tests if a value is a boolean.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a boolean.\n\n    Examples\n    --------\n    > var bool = isBoolean( false )\n    true\n    > bool = isBoolean( new Boolean( false ) )\n    true\n\n\nisBoolean.isPrimitive( value )\n    Tests if a value is a boolean primitive.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a boolean primitive.\n\n    Examples\n    --------\n    > var bool = isBoolean.isPrimitive( true )\n    true\n    > bool = isBoolean.isPrimitive( false )\n    true\n    > bool = isBoolean.isPrimitive( new Boolean( true ) )\n    false\n\n\nisBoolean.isObject( value )\n    Tests if a value is a boolean object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a boolean object.\n\n    Examples\n    --------\n    > var bool = isBoolean.isObject( true )\n    false\n    > bool = isBoolean.isObject( new Boolean( false ) )\n    true\n\n","isBoolean.isPrimitive":"\nisBoolean.isPrimitive( value )\n    Tests if a value is a boolean primitive.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a boolean primitive.\n\n    Examples\n    --------\n    > var bool = isBoolean.isPrimitive( true )\n    true\n    > bool = isBoolean.isPrimitive( false )\n    true\n    > bool = isBoolean.isPrimitive( new Boolean( true ) )\n    false","isBoolean.isObject":"\nisBoolean.isObject( value )\n    Tests if a value is a boolean object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a boolean object.\n\n    Examples\n    --------\n    > var bool = isBoolean.isObject( true )\n    false\n    > bool = isBoolean.isObject( new Boolean( false ) )\n    true","isBooleanArray":"\nisBooleanArray( value )\n    Tests if a value is an array-like object of booleans.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object of booleans.\n\n    Examples\n    --------\n    > var bool = isBooleanArray( [ true, false, true ] )\n    true\n    > bool = isBooleanArray( [ true, 'abc', false ] )\n    false\n\n\nisBooleanArray.primitives( value )\n    Tests if a value is an array-like object containing only boolean primitives.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        boolean primitives.\n\n    Examples\n    --------\n    > var bool = isBooleanArray.primitives( [ true, false ] )\n    true\n    > bool = isBooleanArray.primitives( [ false, new Boolean( true ) ] )\n    false\n\n\nisBooleanArray.objects( value )\n    Tests if a value is an array-like object containing only Boolean objects.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        Boolean objects.\n\n    Examples\n    --------\n    > var bool = isBooleanArray.objects( [ new Boolean( false ), true ] )\n    false\n    > bool = isBooleanArray.objects( [ new Boolean( false ), new Boolean( true ) ] )\n    true\n\n","isBooleanArray.primitives":"\nisBooleanArray.primitives( value )\n    Tests if a value is an array-like object containing only boolean primitives.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        boolean primitives.\n\n    Examples\n    --------\n    > var bool = isBooleanArray.primitives( [ true, false ] )\n    true\n    > bool = isBooleanArray.primitives( [ false, new Boolean( true ) ] )\n    false","isBooleanArray.objects":"\nisBooleanArray.objects( value )\n    Tests if a value is an array-like object containing only Boolean objects.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        Boolean objects.\n\n    Examples\n    --------\n    > var bool = isBooleanArray.objects( [ new Boolean( false ), true ] )\n    false\n    > bool = isBooleanArray.objects( [ new Boolean( false ), new Boolean( true ) ] )\n    true","isBoxedPrimitive":"\nisBoxedPrimitive( value )\n    Tests if a value is a JavaScript boxed primitive.\n\n    Boxed primitive objects can be created with one of the following:\n\n    - new Boolean()\n    - new Number()\n    - new String()\n    - Object( Symbol() ) (ES6/ES2015)\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a JavaScript boxed primitive.\n\n    Examples\n    --------\n    > var bool = isBoxedPrimitive( new Boolean( false ) )\n    true\n    > bool = isBoxedPrimitive( true )\n    false\n\n    See Also\n    --------\n    isPrimitive\n","isBuffer":"\nisBuffer( value )\n    Tests if a value is a Buffer instance.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Buffer instance.\n\n    Examples\n    --------\n    > var bool = isBuffer( new Buffer( 'beep' ) )\n    true\n    > bool = isBuffer( new Buffer( [ 1, 2, 3, 4 ] ) )\n    true\n    > bool = isBuffer( {} )\n    false\n    > bool = isBuffer( [] )\n    false\n\n","isCamelcase":"\nisCamelcase( value )\n    Tests if a value is a camelcase string.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a camelcase string.\n\n    Examples\n    --------\n    > var bool = isCamelcase( 'helloWorld' )\n    true\n    > bool = isCamelcase( 'hello world' )\n    false\n\n    See Also\n    --------\n    isString, isConstantcase","isCapitalized":"\nisCapitalized( value )\n    Tests if a value is a string having an uppercase first character.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a string with an uppercase first\n        character.\n\n    Examples\n    --------\n    > var bool = isCapitalized( 'Hello' )\n    true\n    > bool = isCapitalized( 'world' )\n    false\n\n    See Also\n    --------\n    isString\n","isCentrosymmetricMatrix":"\nisCentrosymmetricMatrix( value )\n    Tests if a value is a matrix which is symmetric about its center.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a centrosymmetric matrix.\n\n    Examples\n    --------\n    > var buf = [ 2, 1, 1, 2 ];\n    > var M = ndarray( 'generic', buf, [ 2, 2 ], [ 2, 1 ], 0, 'row-major' );\n    > var bool = isCentrosymmetricMatrix( M )\n    true\n    > bool = isCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isCentrosymmetricMatrix( 3.14 )\n    false\n    > bool = isCentrosymmetricMatrix( {} )\n    false\n\n    See Also\n    --------\n    isMatrixLike, isSquareMatrix, isSymmetricMatrix\n","isCircular":"\nisCircular( value )\n    Tests if an object-like value contains a circular reference.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an object-like value contains a circular\n        reference.\n\n    Examples\n    --------\n    > var obj = { 'beep': 'boop' };\n    > obj.self = obj;\n    > var bool = isCircular( obj )\n    true\n    > bool = isCircular( {} )\n    false\n    > bool = isCircular( null )\n    false\n\n    See Also\n    --------\n    isCircularArray, isCircularPlainObject\n","isCircularArray":"\nisCircularArray( value )\n    Tests if a value is an array containing a circular reference.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array containing a\n        circular reference.\n\n    Examples\n    --------\n    > var arr = [ 1, 2, 3 ];\n    > arr.push( arr );\n    > var bool = isCircularArray( arr )\n    true\n    > bool = isCircularArray( [] )\n    false\n    > bool = isCircularArray( null )\n    false\n\n    See Also\n    --------\n    isCircular, isCircularPlainObject\n","isCircularPlainObject":"\nisCircularPlainObject( value )\n    Tests if a value is a plain object containing a circular reference.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a plain object containing a\n        circular reference.\n\n    Examples\n    --------\n    > var obj = { 'beep': 'boop' };\n    > obj.self = obj;\n    > var bool = isCircularPlainObject( obj )\n    true\n    > bool = isCircularPlainObject( {} )\n    false\n    > bool = isCircularPlainObject( null )\n    false\n\n    See Also\n    --------\n    isCircular, isCircularArray\n","isClass":"\nisClass( value )\n    Tests if a value is a class.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a class.\n\n    Examples\n    --------\n    > var bool = isClass( class Person {} )\n    true\n    > bool = isClass( function Person() {} )\n    false\n    > bool = isClass( {} )\n    false\n    > bool = isClass( null )\n    false\n    > bool = isClass( true )\n    false\n","isCollection":"\nisCollection( value )\n    Tests if a value is a collection.\n\n    A collection is defined as an array, typed array, or an array-like object\n    (excluding strings and functions).\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a collection.\n\n    Examples\n    --------\n    > var bool = isCollection( [] )\n    true\n    > bool = isCollection( { 'length': 0 } )\n    true\n    > bool = isCollection( {} )\n    false\n\n    See Also\n    --------\n    isArrayLike, isArrayLikeObject\n","isComplex":"\nisComplex( value )\n    Tests if a value is a 64-bit or 128-bit complex number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 64-bit or 128-bit complex\n        number.\n\n    Examples\n    --------\n    > var bool = isComplex( new Complex64( 2.0, 2.0 ) )\n    true\n    > bool = isComplex( new Complex128( 3.0, 1.0 ) )\n    true\n    > bool = isComplex( 3.14 )\n    false\n    > bool = isComplex( {} )\n    false\n\n    See Also\n    --------\n    isComplex64, isComplex128\n","isComplex64":"\nisComplex64( value )\n    Tests if a value is a 64-bit complex number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 64-bit complex number.\n\n    Examples\n    --------\n    > var bool = isComplex64( new Complex64( 2.0, 2.0 ) )\n    true\n    > bool = isComplex64( new Complex128( 3.0, 1.0 ) )\n    false\n    > bool = isComplex64( 3.14 )\n    false\n    > bool = isComplex64( {} )\n    false\n\n    See Also\n    --------\n    isComplex, isComplex128\n","isComplex64Array":"\nisComplex64Array( value )\n    Tests if a value is a Complex64Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Complex64Array.\n\n    Examples\n    --------\n    > var bool = isComplex64Array( new Complex64Array( 10 ) )\n    true\n    > bool = isComplex64Array( [] )\n    false\n\n    See Also\n    --------\n    isComplex, isComplex64, isComplex128Array, isComplexTypedArray\n","isComplex64MatrixLike":"\nisComplex64MatrixLike( value )\n    Tests if a value is a 2-dimensional ndarray-like object containing single-\n    precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 2-dimensional ndarray-like\n        object containing single-precision complex floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n    > M.ndims = 2;\n    > M.shape = [ 2, 2 ];\n    > M.strides = [ 2, 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'complex64';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isComplex64MatrixLike( M )\n    true\n    > bool = isComplex64MatrixLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isComplex64MatrixLike( 3.14 )\n    false\n    > bool = isComplex64MatrixLike( {} )\n    false\n\n    See Also\n    --------\n    isComplex128MatrixLike, isndarrayLike, isMatrixLike\n","isComplex64ndarrayLike":"\nisComplex64ndarrayLike( value )\n    Tests if a value is an ndarray-like object containing single-precision\n    complex floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an ndarray-like object containing\n        single-precision complex floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n    > M.ndims = 2;\n    > M.shape = [ 2, 2 ];\n    > M.strides = [ 2, 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'complex64';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isComplex64ndarrayLike( M )\n    true\n    > bool = isComplex64ndarrayLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isComplex64ndarrayLike( 3.14 )\n    false\n    > bool = isComplex64ndarrayLike( {} )\n    false\n\n    See Also\n    --------\n    isComplex128ndarrayLike, isndarrayLike\n","isComplex64VectorLike":"\nisComplex64VectorLike( value )\n    Tests if a value is a 1-dimensional ndarray-like object containing single-\n    precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 1-dimensional ndarray-like\n        object containing single-precision complex floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Complex64Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n    > M.ndims = 1;\n    > M.shape = [ 4 ];\n    > M.strides = [ 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'complex64';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isComplex64VectorLike( M )\n    true\n    > bool = isComplex64VectorLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isComplex64VectorLike( 3.14 )\n    false\n    > bool = isComplex64VectorLike( {} )\n    false\n\n    See Also\n    --------\n    isComplex128VectorLike, isndarrayLike, isVectorLike\n","isComplex128":"\nisComplex128( value )\n    Tests if a value is a 128-bit complex number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 128-bit complex number.\n\n    Examples\n    --------\n    > var bool = isComplex128( new Complex128( 3.0, 1.0 ) )\n    true\n    > bool = isComplex128( new Complex64( 2.0, 2.0 ) )\n    false\n    > bool = isComplex128( 3.14 )\n    false\n    > bool = isComplex128( {} )\n    false\n\n    See Also\n    --------\n    isComplex, isComplex64\n","isComplex128Array":"\nisComplex128Array( value )\n    Tests if a value is a Complex128Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Complex128Array.\n\n    Examples\n    --------\n    > var bool = isComplex128Array( new Complex128Array( 10 ) )\n    true\n    > bool = isComplex128Array( [] )\n    false\n\n    See Also\n    --------\n    isComplex, isComplex128, isComplex64Array, isComplexTypedArray\n","isComplex128MatrixLike":"\nisComplex128MatrixLike( value )\n    Tests if a value is a 2-dimensional ndarray-like object containing double-\n    precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 2-dimensional ndarray-like\n        object containing double-precision complex floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n    > M.ndims = 2;\n    > M.shape = [ 2, 2 ];\n    > M.strides = [ 2, 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'complex128';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isComplex128MatrixLike( M )\n    true\n    > bool = isComplex128MatrixLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isComplex128MatrixLike( 3.14 )\n    false\n    > bool = isComplex128MatrixLike( {} )\n    false\n\n    See Also\n    --------\n    isComplex64MatrixLike, isndarrayLike, isMatrixLike\n","isComplex128ndarrayLike":"\nisComplex128ndarrayLike( value )\n    Tests if a value is an ndarray-like object containing double-precision\n    complex floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an ndarray-like object containing\n        double-precision complex floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n    > M.ndims = 2;\n    > M.shape = [ 2, 2 ];\n    > M.strides = [ 2, 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'complex128';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isComplex128ndarrayLike( M )\n    true\n    > bool = isComplex128ndarrayLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isComplex128ndarrayLike( 3.14 )\n    false\n    > bool = isComplex128ndarrayLike( {} )\n    false\n\n    See Also\n    --------\n    isComplex64ndarrayLike, isndarrayLike\n","isComplex128VectorLike":"\nisComplex128VectorLike( value )\n    Tests if a value is a 1-dimensional ndarray-like object containing double-\n    precision complex floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 1-dimensional ndarray-like\n        object containing double-precision complex floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Complex128Array( [ 0, 0, 0, 0, 0, 0, 0, 0 ] );\n    > M.ndims = 1;\n    > M.shape = [ 4 ];\n    > M.strides = [ 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'complex128';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isComplex128VectorLike( M )\n    true\n    > bool = isComplex128VectorLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isComplex128VectorLike( 3.14 )\n    false\n    > bool = isComplex128VectorLike( {} )\n    false\n\n    See Also\n    --------\n    isComplex64VectorLike, isndarrayLike, isVectorLike\n","isComplexLike":"\nisComplexLike( value )\n    Tests if a value is a complex number-like object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a complex number-like object.\n\n    Examples\n    --------\n    > var bool = isComplexLike( new Complex64( 2.0, 2.0 ) )\n    true\n    > bool = isComplexLike( new Complex128( 3.0, 1.0 ) )\n    true\n    > bool = isComplexLike( 3.14 )\n    false\n    > bool = isComplexLike( {} )\n    false\n\n    See Also\n    --------\n    isComplex, isComplex64, isComplex128\n","isComplexTypedArray":"\nisComplexTypedArray( value )\n    Tests if a value is a complex typed array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a complex typed array.\n\n    Examples\n    --------\n    > var bool = isComplexTypedArray( new Complex64Array( 10 ) )\n    true\n\n    See Also\n    --------\n    isComplex, isComplex64Array, isComplex128Array\n","isComplexTypedArrayLike":"\nisComplexTypedArrayLike( value )\n    Tests if a value is complex-typed-array-like.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is complex-typed-array-like.\n\n    Examples\n    --------\n    > var bool = isComplexTypedArrayLike( new Complex128Array() )\n    true\n    > bool = isComplexTypedArrayLike({\n    ...    'length': 10,\n    ...    'byteOffset': 0,\n    ...    'byteLength': 10,\n    ...    'BYTES_PER_ELEMENT': 4,\n    ...    'get': function get() {},\n    ...    'set': function set() {}\n    ... })\n    true\n\n    See Also\n    --------\n    isComplexLike, isComplexTypedArray, isComplex64Array, isComplex128Array\n","isComposite":"\nisComposite( value )\n    Tests if a value is a composite number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a composite number.\n\n    Examples\n    --------\n    > var bool = isComposite( 4.0 )\n    true\n    > bool = isComposite( new Number( 4.0 ) )\n    true\n    > bool = isComposite( 3.14 )\n    false\n    > bool = isComposite( -4.0 )\n    false\n    > bool = isComposite( null )\n    false\n\n\nisComposite.isPrimitive( value )\n    Tests if a value is a number primitive which is a composite number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a\n        composite number.\n\n    Examples\n    --------\n    > var bool = isComposite.isPrimitive( 4.0 )\n    true\n    > bool = isComposite.isPrimitive( new Number( 4.0 ) )\n    false\n\n\nisComposite.isObject( value )\n    Tests if a value is a number object having a value which is a composite\n    number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a composite number.\n\n    Examples\n    --------\n    > var bool = isComposite.isObject( 4.0 )\n    false\n    > bool = isComposite.isObject( new Number( 4.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger, isNumber, isPrime\n","isComposite.isPrimitive":"\nisComposite.isPrimitive( value )\n    Tests if a value is a number primitive which is a composite number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a\n        composite number.\n\n    Examples\n    --------\n    > var bool = isComposite.isPrimitive( 4.0 )\n    true\n    > bool = isComposite.isPrimitive( new Number( 4.0 ) )\n    false","isComposite.isObject":"\nisComposite.isObject( value )\n    Tests if a value is a number object having a value which is a composite\n    number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a composite number.\n\n    Examples\n    --------\n    > var bool = isComposite.isObject( 4.0 )\n    false\n    > bool = isComposite.isObject( new Number( 4.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger, isNumber, isPrime","isConfigurableProperty":"\nisConfigurableProperty( value, property )\n    Tests if an object's own property is configurable.\n\n    A property is configurable if the property may be deleted or its descriptor\n    may be changed.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own property is configurable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = true;\n    > desc.writable = true;\n    > desc.value = true;\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isConfigurableProperty( obj, 'boop' )\n    true\n    > bool = isConfigurableProperty( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    isConfigurablePropertyIn, isEnumerableProperty, isReadableProperty, isWritableProperty\n","isConfigurablePropertyIn":"\nisConfigurablePropertyIn( value, property )\n    Tests if an object's own or inherited property is configurable.\n\n    A property is configurable if the property may be deleted or its descriptor\n    may be changed.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own or inherited property is\n        configurable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = true;\n    > desc.writable = true;\n    > desc.value = true;\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isConfigurablePropertyIn( obj, 'boop' )\n    true\n    > bool = isConfigurablePropertyIn( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    isConfigurableProperty, isEnumerablePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isConstantcase":"\nisConstantcase( value )\n    Tests if a value is a constantcase string.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a constantcase string.\n\n    Examples\n    --------\n    > var bool = isConstantcase( 'BEEP_BOOP' )\n    true\n    > bool = isConstantcase( 'BEEP and BOOP' )\n    false\n\n    See Also\n    --------\n    isString, isCamelcase","isCubeNumber":"\nisCubeNumber( value )\n    Tests if a value is a cube number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a cube number.\n\n    Examples\n    --------\n    > var bool = isCubeNumber( 8.0 )\n    true\n    > bool = isCubeNumber( new Number( 8.0 ) )\n    true\n    > bool = isCubeNumber( 3.14 )\n    false\n    > bool = isCubeNumber( -5.0 )\n    false\n    > bool = isCubeNumber( null )\n    false\n\n\nisCubeNumber.isPrimitive( value )\n    Tests if a value is a number primitive which is a cube number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a cube\n        number.\n\n    Examples\n    --------\n    > var bool = isCubeNumber.isPrimitive( 8.0 )\n    true\n    > bool = isCubeNumber.isPrimitive( new Number( 8.0 ) )\n    false\n\n\nisCubeNumber.isObject( value )\n    Tests if a value is a number object having a value which is a cube number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a cube number.\n\n    Examples\n    --------\n    > var bool = isCubeNumber.isObject( 8.0 )\n    false\n    > bool = isCubeNumber.isObject( new Number( 8.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger, isNumber, isSquareNumber\n","isCubeNumber.isPrimitive":"\nisCubeNumber.isPrimitive( value )\n    Tests if a value is a number primitive which is a cube number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a cube\n        number.\n\n    Examples\n    --------\n    > var bool = isCubeNumber.isPrimitive( 8.0 )\n    true\n    > bool = isCubeNumber.isPrimitive( new Number( 8.0 ) )\n    false","isCubeNumber.isObject":"\nisCubeNumber.isObject( value )\n    Tests if a value is a number object having a value which is a cube number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a cube number.\n\n    Examples\n    --------\n    > var bool = isCubeNumber.isObject( 8.0 )\n    false\n    > bool = isCubeNumber.isObject( new Number( 8.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger, isNumber, isSquareNumber","isCurrentYear":"\nisCurrentYear( value )\n    Tests if a value is the current year.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether a value is the current year.\n\n    Examples\n    --------\n    > var bool = isCurrentYear( new Date() )\n    true\n    > bool = isCurrentYear( currentYear() )\n    true\n    > bool = isCurrentYear( 2021 )\n    false\n    > bool = isCurrentYear( null )\n    false\n\n","isDataProperty":"\nisDataProperty( value, property )\n    Tests if an object's own property has a data descriptor.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own property has a data descriptor.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.get = function getter() { return 'beep'; };\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isDataProperty( obj, 'boop' )\n    true\n    > bool = isDataProperty( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    hasOwnProp, isAccessorProperty, isDataPropertyIn\n","isDataPropertyIn":"\nisDataPropertyIn( value, property )\n    Tests if an object's own or inherited property has a data descriptor.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own or inherited property has a data\n        descriptor.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.get = function getter() { return 'beep'; };\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isDataPropertyIn( obj, 'boop' )\n    true\n    > bool = isDataPropertyIn( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    hasProp, isAccessorPropertyIn, isDataProperty\n","isDataView":"\nisDataView( value )\n    Tests if a value is a DataView.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a DataView.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 10 );\n    > var bool = isDataView( new DataView( buf ) )\n    true\n    > bool = isDataView( [] )\n    false\n\n    See Also\n    --------\n    isArrayBuffer, isTypedArray\n","isDateObject":"\nisDateObject( value )\n    Tests if a value is a Date object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Date object.\n\n    Examples\n    --------\n    > var bool = isDateObject( new Date() )\n    true\n    > bool = isDateObject( '2017-01-01' )\n    false\n\n","isDateObjectArray":"\nisDateObjectArray( value )\n    Tests if a value is an array-like object containing only Date objects.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if value is an array-like object containing only Date\n        objects.\n\n    Examples\n    --------\n    > var bool = isDateObjectArray( [ new Date(), new Date() ] )\n    true\n    > bool = isDateObjectArray( [ {}, {} ] )\n    false\n    > bool = isDateObjectArray( [ new Date(), '2011-01-01' ] )\n    false\n    > bool = isDateObjectArray( [] )\n    false\n\n    See Also\n    --------\n    isDateObject\n","isDigitString":"\nisDigitString( str )\n    Tests whether a string contains only numeric digits.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a string contains only numeric digits.\n\n    Examples\n    --------\n    > var bool = isDigitString( '0123456789' )\n    true\n    > bool = isDigitString( 'abcdef' )\n    false\n    > bool = isDigitString( '0xff' )\n    false\n    > bool = isDigitString( '' )\n    false\n\n    See Also\n    --------\n    isHexString, isString\n","isDomainName":"\nisDomainName( value )\n    Tests if a value is a domain name.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a domain name.\n\n    Examples\n    --------\n    > var bool = isDomainName( 'example.com' )\n    true\n    > bool = isDomainName( 'foo@bar.com' )\n    false\n","isDurationString":"\nisDurationString( value )\n    Tests if a value is a duration string.\n\n    The function validates that a value is a string. For all other types, the\n    function returns `false`.\n\n    A duration string is a string containing a sequence of time units. A time\n    unit is a non-negative integer followed by a unit identifier. The following\n    unit identifiers are supported:\n\n    - d: days.\n    - h: hours.\n    - m: minutes.\n    - s: seconds.\n    - ms: milliseconds.\n\n    For example, the string `1m3s10ms` is a duration string containing three\n    time units: `1m` (1 minute), `3s` (3 seconds), and `10ms` (10 milliseconds).\n    The string `60m` is a duration string containing a single time unit: `60m`\n    (60 minutes). Time units must be supplied in descending order of magnitude\n    (i.e., days, hours, minutes, seconds, milliseconds).\n\n    Duration strings are case insensitive. For example, the string `1M3S10MS` is\n    equivalent to `1m3s10ms`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a duration string.\n\n    Examples\n    --------\n    > var bool = isDurationString( '1d' )\n    true\n    > bool = isDurationString( '1h' )\n    true\n    > bool = isDurationString( 'beep' )\n    false\n","isEmailAddress":"\nisEmailAddress( value )\n    Tests if a value is an email address.\n\n    Validation is not rigorous. *9* RFCs relate to email addresses, and\n    accounting for all of them is a fool's errand. The function performs the\n    simplest validation; i.e., requiring at least one `@` symbol.\n\n    For rigorous validation, send a confirmation email. If the email bounces,\n    consider the email invalid.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an email address.\n\n    Examples\n    --------\n    > var bool = isEmailAddress( 'beep@boop.com' )\n    true\n    > bool = isEmailAddress( 'beep' )\n    false\n    > bool = isEmailAddress( null )\n    false\n\n","isEmptyArray":"\nisEmptyArray( value )\n    Tests if a value is an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is an empty array.\n\n    Examples\n    --------\n    > var bool = isEmptyArray( [] )\n    true\n    > bool = isEmptyArray( [ 1, 2, 3 ] )\n    false\n    > bool = isEmptyArray( {} )\n    false\n\n    See Also\n    --------\n    isArray, isEmptyArrayLikeObject, isEmptyCollection\n","isEmptyArrayLikeObject":"\nisEmptyArrayLikeObject( value )\n    Tests if a value is an empty array-like object.\n\n    If provided a string, the function returns `false`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an empty array-like object.\n\n    Examples\n    --------\n    > var bool = isEmptyArrayLikeObject( [] )\n    true\n    > bool = isEmptyArrayLikeObject( { 'length': 0 } )\n    true\n    > bool = isEmptyArrayLikeObject( '' )\n    false\n\n    See Also\n    --------\n    isArrayLikeObject, isEmptyArray, isEmptyCollection\n","isEmptyCollection":"\nisEmptyCollection( value )\n    Tests if a value is an empty collection.\n\n    A collection is defined as an array, typed array, or an array-like object\n    (excluding strings and functions).\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is an empty collection.\n\n    Examples\n    --------\n    > var bool = isEmptyCollection( [] )\n    true\n    > bool = isEmptyCollection( { 'length': 0 } )\n    true\n    > bool = isEmptyCollection( [ 1, 2, 3 ] )\n    false\n    > bool = isEmptyCollection( {} )\n    false\n\n    See Also\n    --------\n    isCollection, isEmptyArray, isEmptyArrayLikeObject\n","isEmptyObject":"\nisEmptyObject( value )\n    Tests if a value is an empty object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is an empty object.\n\n    Examples\n    --------\n    > var bool = isEmptyObject( {} )\n    true\n    > bool = isEmptyObject( { 'beep': 'boop' } )\n    false\n    > bool = isEmptyObject( [] )\n    false\n\n    See Also\n    --------\n    isObject, isPlainObject\n","isEmptyString":"\nisEmptyString( value )\n    Tests if a value is an empty string.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is an empty string.\n\n    Examples\n    --------\n    > var bool = isEmptyString( '' )\n    true\n    > bool = isEmptyString( new String( '' ) )\n    true\n    > bool = isEmptyString( 'beep' )\n    false\n    > bool = isEmptyString( [] )\n    false\n\n\nisEmptyString.isPrimitive( value )\n    Tests if a value is an empty string primitive.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an empty string primitive.\n\n    Examples\n    --------\n    > var bool = isEmptyString.isPrimitive( '' )\n    true\n    > bool = isEmptyString.isPrimitive( new String( '' ) )\n    false\n\n\nisEmptyString.isObject( value )\n    Tests if a value is an empty `String` object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an empty `String` object.\n\n    Examples\n    --------\n    > var bool = isEmptyString.isObject( new String( '' ) )\n    true\n    > bool = isEmptyString.isObject( '' )\n    false\n\n    See Also\n    --------\n    isString\n","isEmptyString.isPrimitive":"\nisEmptyString.isPrimitive( value )\n    Tests if a value is an empty string primitive.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an empty string primitive.\n\n    Examples\n    --------\n    > var bool = isEmptyString.isPrimitive( '' )\n    true\n    > bool = isEmptyString.isPrimitive( new String( '' ) )\n    false","isEmptyString.isObject":"\nisEmptyString.isObject( value )\n    Tests if a value is an empty `String` object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an empty `String` object.\n\n    Examples\n    --------\n    > var bool = isEmptyString.isObject( new String( '' ) )\n    true\n    > bool = isEmptyString.isObject( '' )\n    false\n\n    See Also\n    --------\n    isString","isEnumerableProperty":"\nisEnumerableProperty( value, property )\n    Tests if an object's own property is enumerable.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own property is enumerable.\n\n    Examples\n    --------\n    > var beep = { 'boop': true };\n    > var bool = isEnumerableProperty( beep, 'boop' )\n    true\n    > bool = isEnumerableProperty( beep, 'hasOwnProperty' )\n    false\n\n    See Also\n    --------\n    isConfigurableProperty, isEnumerablePropertyIn, isNonEnumerableProperty, isReadableProperty, isWritableProperty\n","isEnumerablePropertyIn":"\nisEnumerablePropertyIn( value, property )\n    Tests if an object's own or inherited property is enumerable.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own or inherited property is\n        enumerable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = true;\n    > desc.enumerable = false;\n    > desc.writable = true;\n    > desc.value = true;\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isEnumerablePropertyIn( obj, 'boop' )\n    true\n    > bool = isEnumerablePropertyIn( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    isConfigurablePropertyIn, isEnumerableProperty, isNonEnumerablePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isEqualArray":"\nisEqualArray( v1, v2 )\n    Tests if two arguments are both generic arrays and have equal values.\n\n    The function performs strict equality comparison; thus, the function treats\n    `-0` and `+0` as equal and `NaNs` as distinct.\n\n    Parameters\n    ----------\n    v1: any\n        First input value.\n\n    v2: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are equal.\n\n    Examples\n    --------\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > var y = [ 1.0, 2.0, 3.0 ];\n    > var bool = isEqualArray( x, y )\n    true\n\n    > x = [ NaN, NaN, NaN ];\n    > y = [ NaN, NaN, NaN ];\n    > bool = isEqualArray( x, y )\n    false\n\n    See Also\n    --------\n    isArray, isSameArray\n","isError":"\nisError( value )\n    Tests if a value is an Error object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an Error object.\n\n    Examples\n    --------\n    > var bool = isError( new Error( 'beep' ) )\n    true\n    > bool = isError( {} )\n    false\n\n","isEvalError":"\nisEvalError( value )\n    Tests if a value is an EvalError object.\n\n    This function should *not* be considered robust. While the function should\n    always return `true` if provided an EvalError (or a descendant) object,\n    false positives may occur due to the fact that the EvalError constructor\n    inherits from Error and has no internal class of its own. Hence, EvalError\n    impersonation is possible.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an EvalError object.\n\n    Examples\n    --------\n    > var bool = isEvalError( new EvalError( 'beep' ) )\n    true\n    > bool = isEvalError( {} )\n    false\n\n    See Also\n    --------\n    isError\n","isEven":"\nisEven( value )\n    Tests if a value is an even number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether is an even number.\n\n    Examples\n    --------\n    > var bool = isEven( 4.0 )\n    true\n    > bool = isEven( new Number( 4.0 ) )\n    true\n    > bool = isEven( 3.0 )\n    false\n    > bool = isEven( -3.14 )\n    false\n    > bool = isEven( null )\n    false\n\n\nisEven.isPrimitive( value )\n    Tests if a value is a number primitive that is an even number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive that is an even\n        number.\n\n    Examples\n    --------\n    > var bool = isEven.isPrimitive( -4.0 )\n    true\n    > bool = isEven.isPrimitive( new Number( -4.0 ) )\n    false\n\n\nisEven.isObject( value )\n    Tests if a value is a number object that is an even number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object that is an even\n        number.\n\n    Examples\n    --------\n    > var bool = isEven.isObject( 4.0 )\n    false\n    > bool = isEven.isObject( new Number( 4.0 ) )\n    true\n\n    See Also\n    --------\n    isOdd\n","isEven.isPrimitive":"\nisEven.isPrimitive( value )\n    Tests if a value is a number primitive that is an even number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive that is an even\n        number.\n\n    Examples\n    --------\n    > var bool = isEven.isPrimitive( -4.0 )\n    true\n    > bool = isEven.isPrimitive( new Number( -4.0 ) )\n    false","isEven.isObject":"\nisEven.isObject( value )\n    Tests if a value is a number object that is an even number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object that is an even\n        number.\n\n    Examples\n    --------\n    > var bool = isEven.isObject( 4.0 )\n    false\n    > bool = isEven.isObject( new Number( 4.0 ) )\n    true\n\n    See Also\n    --------\n    isOdd","isFalsy":"\nisFalsy( value )\n    Tests if a value is a value which translates to `false` when evaluated in a\n    boolean context.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is falsy.\n\n    Examples\n    --------\n    > var bool = isFalsy( false )\n    true\n    > bool = isFalsy( '' )\n    true\n    > bool = isFalsy( 0 )\n    true\n    > bool = isFalsy( null )\n    true\n    > bool = isFalsy( void 0 )\n    true\n    > bool = isFalsy( NaN )\n    true\n    > bool = isFalsy( {} )\n    false\n    > bool = isFalsy( [] )\n    false\n\n    See Also\n    --------\n    isFalsyArray, isTruthy\n","isFalsyArray":"\nisFalsyArray( value )\n    Tests if a value is an array-like object containing only falsy values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only falsy values.\n\n    Examples\n    --------\n    > var bool = isFalsyArray( [ null, '' ] )\n    true\n    > bool = isFalsyArray( [ {}, [] ] )\n    false\n    > bool = isFalsyArray( [] )\n    false\n\n    See Also\n    --------\n    isFalsy, isTruthyArray\n","isFinite":"\nisFinite( value )\n    Tests if a value is a finite number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a finite number.\n\n    Examples\n    --------\n    > var bool = isFinite( 5.0 )\n    true\n    > bool = isFinite( new Number( 5.0 ) )\n    true\n    > bool = isFinite( 1.0/0.0 )\n    false\n    > bool = isFinite( null )\n    false\n\n\nisFinite.isPrimitive( value )\n    Tests if a value is a number primitive having a finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number primitive having a finite\n        value.\n\n    Examples\n    --------\n    > var bool = isFinite.isPrimitive( -3.0 )\n    true\n    > bool = isFinite.isPrimitive( new Number( -3.0 ) )\n    false\n\n\nisFinite.isObject( value )\n    Tests if a value is a number object having a finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number object having a finite\n        value.\n\n    Examples\n    --------\n    > var bool = isFinite.isObject( 3.0 )\n    false\n    > bool = isFinite.isObject( new Number( 3.0 ) )\n    true\n\n    See Also\n    --------\n    isFiniteArray, isInfinite\n","isFinite.isPrimitive":"\nisFinite.isPrimitive( value )\n    Tests if a value is a number primitive having a finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number primitive having a finite\n        value.\n\n    Examples\n    --------\n    > var bool = isFinite.isPrimitive( -3.0 )\n    true\n    > bool = isFinite.isPrimitive( new Number( -3.0 ) )\n    false","isFinite.isObject":"\nisFinite.isObject( value )\n    Tests if a value is a number object having a finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number object having a finite\n        value.\n\n    Examples\n    --------\n    > var bool = isFinite.isObject( 3.0 )\n    false\n    > bool = isFinite.isObject( new Number( 3.0 ) )\n    true\n\n    See Also\n    --------\n    isFiniteArray, isInfinite","isFiniteArray":"\nisFiniteArray( value )\n    Tests if a value is an array-like object of finite numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object of finite\n        numbers.\n\n    Examples\n    --------\n    > var bool = isFiniteArray( [ -3.0, new Number(0.0), 2.0 ] )\n    true\n    > bool = isFiniteArray( [ -3.0, 1.0/0.0 ] )\n    false\n\n\nisFiniteArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive finite\n    numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only primitive finite numbers.\n\n    Examples\n    --------\n    > var bool = isFiniteArray.primitives( [ -1.0, 10.0 ] )\n    true\n    > bool = isFiniteArray.primitives( [ -1.0, 0.0, 5.0 ] )\n    true\n    > bool = isFiniteArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false\n\n\nisFiniteArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having finite values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only number objects having finite values.\n\n    Examples\n    --------\n    > var bool = isFiniteArray.objects( [ new Number(1.0), new Number(3.0) ] )\n    true\n    > bool = isFiniteArray.objects( [ -1.0, 0.0, 3.0 ] )\n    false\n    > bool = isFiniteArray.objects( [ 3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isFinite, isInfinite\n","isFiniteArray.primitives":"\nisFiniteArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive finite\n    numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only primitive finite numbers.\n\n    Examples\n    --------\n    > var bool = isFiniteArray.primitives( [ -1.0, 10.0 ] )\n    true\n    > bool = isFiniteArray.primitives( [ -1.0, 0.0, 5.0 ] )\n    true\n    > bool = isFiniteArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false","isFiniteArray.objects":"\nisFiniteArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having finite values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only number objects having finite values.\n\n    Examples\n    --------\n    > var bool = isFiniteArray.objects( [ new Number(1.0), new Number(3.0) ] )\n    true\n    > bool = isFiniteArray.objects( [ -1.0, 0.0, 3.0 ] )\n    false\n    > bool = isFiniteArray.objects( [ 3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isFinite, isInfinite","isFloat32Array":"\nisFloat32Array( value )\n    Tests if a value is a Float32Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Float32Array.\n\n    Examples\n    --------\n    > var bool = isFloat32Array( new Float32Array( 10 ) )\n    true\n    > bool = isFloat32Array( [] )\n    false\n\n    See Also\n    --------\n    isFloat64Array\n","isFloat32MatrixLike":"\nisFloat32MatrixLike( value )\n    Tests if a value is a 2-dimensional ndarray-like object containing single-\n    precision floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 2-dimensional ndarray-like\n        object containing single-precision floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Float32Array( [ 0, 0, 0, 0 ] );\n    > M.ndims = 2;\n    > M.shape = [ 2, 2 ];\n    > M.strides = [ 2, 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'float32';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isFloat32MatrixLike( M )\n    true\n    > bool = isFloat32MatrixLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isFloat32MatrixLike( 3.14 )\n    false\n    > bool = isFloat32MatrixLike( {} )\n    false\n\n    See Also\n    --------\n    isFloat64MatrixLike, isndarrayLike, isMatrixLike\n","isFloat32ndarrayLike":"\nisFloat32ndarrayLike( value )\n    Tests if a value is an ndarray-like object containing single-precision\n    floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an ndarray-like object containing\n        single-precision floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Float32Array( [ 0, 0, 0, 0 ] );\n    > M.ndims = 2;\n    > M.shape = [ 2, 2 ];\n    > M.strides = [ 2, 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'float32';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isFloat32ndarrayLike( M )\n    true\n    > bool = isFloat32ndarrayLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isFloat32ndarrayLike( 3.14 )\n    false\n    > bool = isFloat32ndarrayLike( {} )\n    false\n\n    See Also\n    --------\n    isFloat64ndarrayLike, isndarrayLike\n","isFloat32VectorLike":"\nisFloat32VectorLike( value )\n    Tests if a value is a 1-dimensional ndarray-like object containing single-\n    precision floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 1-dimensional ndarray-like\n        object containing single-precision floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Float32Array( [ 0, 0, 0, 0 ] );\n    > M.ndims = 1;\n    > M.shape = [ 4 ];\n    > M.strides = [ 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'float32';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isFloat32VectorLike( M )\n    true\n    > bool = isFloat32VectorLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isFloat32VectorLike( 3.14 )\n    false\n    > bool = isFloat32VectorLike( {} )\n    false\n\n    See Also\n    --------\n    isFloat64VectorLike, isndarrayLike, isVectorLike\n","isFloat64Array":"\nisFloat64Array( value )\n    Tests if a value is a Float64Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Float64Array.\n\n    Examples\n    --------\n    > var bool = isFloat64Array( new Float64Array( 10 ) )\n    true\n    > bool = isFloat64Array( [] )\n    false\n\n    See Also\n    --------\n    isFloat32Array\n","isFloat64MatrixLike":"\nisFloat64MatrixLike( value )\n    Tests if a value is a 2-dimensional ndarray-like object containing double-\n    precision floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 2-dimensional ndarray-like\n        object containing double-precision floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Float64Array( [ 0, 0, 0, 0 ] );\n    > M.ndims = 2;\n    > M.shape = [ 2, 2 ];\n    > M.strides = [ 2, 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'float64';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isFloat64MatrixLike( M )\n    true\n    > bool = isFloat64MatrixLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isFloat64MatrixLike( 3.14 )\n    false\n    > bool = isFloat64MatrixLike( {} )\n    false\n\n    See Also\n    --------\n    isFloat32MatrixLike, isndarrayLike, isMatrixLike\n","isFloat64ndarrayLike":"\nisFloat64ndarrayLike( value )\n    Tests if a value is an ndarray-like object containing double-precision\n    floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an ndarray-like object containing\n        double-precision floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Float64Array( [ 0, 0, 0, 0 ] );\n    > M.ndims = 2;\n    > M.shape = [ 2, 2 ];\n    > M.strides = [ 2, 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'float64';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isFloat64ndarrayLike( M )\n    true\n    > bool = isFloat64ndarrayLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isFloat64ndarrayLike( 3.14 )\n    false\n    > bool = isFloat64ndarrayLike( {} )\n    false\n\n    See Also\n    --------\n    isFloat32ndarrayLike, isndarrayLike\n","isFloat64VectorLike":"\nisFloat64VectorLike( value )\n    Tests if a value is a 1-dimensional ndarray-like object containing double-\n    precision floating-point numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 1-dimensional ndarray-like\n        object containing double-precision floating-point numbers.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = new Float64Array( [ 0, 0, 0, 0 ] );\n    > M.ndims = 1;\n    > M.shape = [ 4 ];\n    > M.strides = [ 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'float64';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isFloat64VectorLike( M )\n    true\n    > bool = isFloat64VectorLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isFloat64VectorLike( 3.14 )\n    false\n    > bool = isFloat64VectorLike( {} )\n    false\n\n    See Also\n    --------\n    isFloat32VectorLike, isndarrayLike, isVectorLike\n","isFunction":"\nisFunction( value )\n    Tests if a value is a function.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a function.\n\n    Examples\n    --------\n    > function beep() {};\n    > var bool = isFunction( beep )\n    true\n    > bool = isFunction( {} )\n    false\n\n","isFunctionArray":"\nisFunctionArray( value )\n    Tests if a value is an array-like object containing only functions.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        functions.\n\n    Examples\n    --------\n    > function beep() {};\n    > function boop() {};\n    > var bool = isFunctionArray( [ beep, boop ] )\n    true\n    > bool = isFunctionArray( [ {}, beep ] )\n    false\n    > bool = isFunctionArray( [] )\n    false\n\n    See Also\n    --------\n    isArray\n","isGeneratorObject":"\nisGeneratorObject( value )\n    Tests if a value is a generator object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a generator object.\n\n    Examples\n    --------\n    > function* generateID() {\n    ...     var idx = 0;\n    ...     while ( idx < idx+1 ) {\n    ...         yield idx;\n    ...         idx += 1;\n    ...     }\n    ... };\n    > var bool = isGeneratorObject( generateID() )\n    true\n    > bool = isGeneratorObject( generateID )\n    false\n    > bool = isGeneratorObject( {} )\n    false\n    > bool = isGeneratorObject( null )\n    false\n\n    See Also\n    --------\n    hasGeneratorSupport, isGeneratorObjectLike\n","isGeneratorObjectLike":"\nisGeneratorObjectLike( value )\n    Tests if a value is generator object-like.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is generator object-like.\n\n    Examples\n    --------\n    > var obj = {\n    ...     'next': function noop() {},\n    ...     'return': function noop() {},\n    ...     'throw': function noop() {}\n    ... };\n    > var bool = isGeneratorObjectLike( obj )\n    true\n    > bool = isGeneratorObjectLike( {} )\n    false\n    > bool = isGeneratorObjectLike( null )\n    false\n\n    See Also\n    --------\n    hasGeneratorSupport, isGeneratorObject\n","isgzipBuffer":"\nisgzipBuffer( value )\n    Tests if a value is a gzip buffer.\n\n    A gzip buffer is defined as either a Node.js Buffer or Uint8Array which\n    contains a 10-byte header, a body containing the compressed payload, and an\n    8-byte footer containing a CRC-32 checksum and the length of the original\n    uncompressed data, modulo 2^32.\n\n    This function only examines the 10-byte header to ensure the header includes\n    the expected magic number and compression method. The function does not\n    perform an integrity check.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a gzip buffer.\n\n    Examples\n    --------\n    > var buf = new Uint8Array( 20 );\n    > buf[ 0 ] = 31;  // 0x1f => magic number\n    > buf[ 1 ] = 139; // 0x8b\n    > buf[ 2 ] = 8;   // 0x08 => compression method\n    > var bool = isgzipBuffer( buf )\n    true\n    > bool = isgzipBuffer( [] )\n    false\n\n    See Also\n    --------\n    isBuffer, isUint8Array\n","isHexString":"\nisHexString( str )\n    Tests whether a string contains only hexadecimal digits.\n\n    The function does not recognize `x` (as in the standard `0x` prefix).\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a string contains only hexadecimal digits.\n\n    Examples\n    --------\n    > var bool = isHexString( '0123456789abcdefABCDEF' )\n    true\n    > bool = isHexString( '0xffffff' )\n    false\n    > bool = isHexString( 'x' )\n    false\n    > bool = isHexString( '' )\n    false\n\n    See Also\n    --------\n    isString\n","isInfinite":"\nisInfinite( value )\n    Tests if a value is an infinite number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an infinite number.\n\n    Examples\n    --------\n    > var bool = isInfinite( 1.0/0.0 )\n    true\n    > bool = isInfinite( new Number( -1.0/0.0 ) )\n    true\n    > bool = isInfinite( 5.0 )\n    false\n    > bool = isInfinite( '1.0/0.0' )\n    false\n\n\nisInfinite.isPrimitive( value )\n    Tests if a value is a number primitive having an infinite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number primitive having an\n        infinite value.\n\n    Examples\n    --------\n    > var bool = isInfinite.isPrimitive( -1.0/0.0 )\n    true\n    > bool = isInfinite.isPrimitive( new Number( -1.0/0.0 ) )\n    false\n\n\nisInfinite.isObject( value )\n    Tests if a value is a number object having an infinite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number object having an infinite\n        value.\n\n    Examples\n    --------\n    > var bool = isInfinite.isObject( 1.0/0.0 )\n    false\n    > bool = isInfinite.isObject( new Number( 1.0/0.0 ) )\n    true\n\n    See Also\n    --------\n    isFinite\n","isInfinite.isPrimitive":"\nisInfinite.isPrimitive( value )\n    Tests if a value is a number primitive having an infinite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number primitive having an\n        infinite value.\n\n    Examples\n    --------\n    > var bool = isInfinite.isPrimitive( -1.0/0.0 )\n    true\n    > bool = isInfinite.isPrimitive( new Number( -1.0/0.0 ) )\n    false","isInfinite.isObject":"\nisInfinite.isObject( value )\n    Tests if a value is a number object having an infinite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number object having an infinite\n        value.\n\n    Examples\n    --------\n    > var bool = isInfinite.isObject( 1.0/0.0 )\n    false\n    > bool = isInfinite.isObject( new Number( 1.0/0.0 ) )\n    true\n\n    See Also\n    --------\n    isFinite","isInheritedProperty":"\nisInheritedProperty( value, property )\n    Tests if an object has an inherited property.\n\n    Value arguments other than `null` or `undefined` are coerced to objects.\n\n    Non-symbol property arguments are coerced to strings.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object has an inherited property.\n\n    Examples\n    --------\n    > var beep = { 'boop': true };\n    > var bool = isInheritedProperty( beep, 'boop' )\n    false\n    > bool = isInheritedProperty( beep, 'toString' )\n    true\n    > bool = isInheritedProperty( beep, 'bop' )\n    false\n\n    See Also\n    --------\n    hasOwnProp, hasProp\n","isInt8Array":"\nisInt8Array( value )\n    Tests if a value is an Int8Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an Int8Array.\n\n    Examples\n    --------\n    > var bool = isInt8Array( new Int8Array( 10 ) )\n    true\n    > bool = isInt8Array( [] )\n    false\n\n    See Also\n    --------\n    isInt16Array, isInt32Array\n","isInt16Array":"\nisInt16Array( value )\n    Tests if a value is an Int16Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an Int16Array.\n\n    Examples\n    --------\n    > var bool = isInt16Array( new Int16Array( 10 ) )\n    true\n    > bool = isInt16Array( [] )\n    false\n\n    See Also\n    --------\n    isInt32Array, isInt8Array\n","isInt32Array":"\nisInt32Array( value )\n    Tests if a value is an Int32Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an Int32Array.\n\n    Examples\n    --------\n    > var bool = isInt32Array( new Int32Array( 10 ) )\n    true\n    > bool = isInt32Array( [] )\n    false\n\n    See Also\n    --------\n    isInt16Array, isInt8Array\n","isInteger":"\nisInteger( value )\n    Tests if a value is an integer.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an integer.\n\n    Examples\n    --------\n    > var bool = isInteger( 5.0 )\n    true\n    > bool = isInteger( new Number( 5.0 ) )\n    true\n    > bool = isInteger( -3.14 )\n    false\n    > bool = isInteger( null )\n    false\n\n\nisInteger.isPrimitive( value )\n    Tests if a value is a number primitive having an integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having an integer\n        value.\n\n    Examples\n    --------\n    > var bool = isInteger.isPrimitive( -3.0 )\n    true\n    > bool = isInteger.isPrimitive( new Number( -3.0 ) )\n    false\n\n\nisInteger.isObject( value )\n    Tests if a value is a number object having an integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having an integer\n        value.\n\n    Examples\n    --------\n    > var bool = isInteger.isObject( 3.0 )\n    false\n    > bool = isInteger.isObject( new Number( 3.0 ) )\n    true\n\n    See Also\n    --------\n    isNumber\n","isInteger.isPrimitive":"\nisInteger.isPrimitive( value )\n    Tests if a value is a number primitive having an integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having an integer\n        value.\n\n    Examples\n    --------\n    > var bool = isInteger.isPrimitive( -3.0 )\n    true\n    > bool = isInteger.isPrimitive( new Number( -3.0 ) )\n    false","isInteger.isObject":"\nisInteger.isObject( value )\n    Tests if a value is a number object having an integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having an integer\n        value.\n\n    Examples\n    --------\n    > var bool = isInteger.isObject( 3.0 )\n    false\n    > bool = isInteger.isObject( new Number( 3.0 ) )\n    true\n\n    See Also\n    --------\n    isNumber","isIntegerArray":"\nisIntegerArray( value )\n    Tests if a value is an array-like object of integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object of integer\n        values.\n\n    Examples\n    --------\n    > var bool = isIntegerArray( [ -3.0, new Number(0.0), 2.0 ] )\n    true\n    > bool = isIntegerArray( [ -3.0, '3.0' ] )\n    false\n\n\nisIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive integer\n    values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only primitive integer values.\n\n    Examples\n    --------\n    > var bool = isIntegerArray.primitives( [ -1.0, 10.0 ] )\n    true\n    > bool = isIntegerArray.primitives( [ -1.0, 0.0, 5.0 ] )\n    true\n    > bool = isIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false\n\n\nisIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only number objects having integer values.\n\n    Examples\n    --------\n    > var bool = isIntegerArray.objects( [ new Number(1.0), new Number(3.0) ] )\n    true\n    > bool = isIntegerArray.objects( [ -1.0, 0.0, 3.0 ] )\n    false\n    > bool = isIntegerArray.objects( [ 3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray\n","isIntegerArray.primitives":"\nisIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive integer\n    values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only primitive integer values.\n\n    Examples\n    --------\n    > var bool = isIntegerArray.primitives( [ -1.0, 10.0 ] )\n    true\n    > bool = isIntegerArray.primitives( [ -1.0, 0.0, 5.0 ] )\n    true\n    > bool = isIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false","isIntegerArray.objects":"\nisIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only number objects having integer values.\n\n    Examples\n    --------\n    > var bool = isIntegerArray.objects( [ new Number(1.0), new Number(3.0) ] )\n    true\n    > bool = isIntegerArray.objects( [ -1.0, 0.0, 3.0 ] )\n    false\n    > bool = isIntegerArray.objects( [ 3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray","isIterableLike":"\nisIterableLike( value )\n    Tests if a value is iterable-like.\n\n    In order to be iterable, an object must implement the @@iterator method,\n    which, when called, returns an iterator protocol-compliant object.\n\n    An iterator protocol-compliant object is an object having a `next` method\n    which adheres to the iterator protocol.\n\n    As full iterator compliance is impossible to achieve without evaluating an\n    iterator, this function checks *only* for interface compliance.\n\n    In environments lacking Symbol.iterator support, this function always\n    returns `false`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is iterable-like.\n\n    Examples\n    --------\n    > var bool = isIterableLike( [ 1, 2, 3 ] )\n    <boolean>\n    > bool = isIterableLike( {} )\n    false\n    > bool = isIterableLike( null )\n    false\n\n    See Also\n    --------\n    isIteratorLike\n","isIteratorLike":"\nisIteratorLike( value )\n    Tests if a value is iterator-like.\n\n    An iterator protocol-compliant object is an object having a `next` method\n    which adheres to the iterator protocol.\n\n    As full iterator compliance is impossible to achieve without evaluating an\n    iterator, this function checks *only* for interface compliance.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is iterator-like.\n\n    Examples\n    --------\n    > var obj = {\n    ...     'next': function noop() {}\n    ... };\n    > var bool = isIteratorLike( obj )\n    true\n    > bool = isIteratorLike( {} )\n    false\n    > bool = isIteratorLike( null )\n    false\n\n    See Also\n    --------\n    isIterableLike\n","isJSON":"\nisJSON( value )\n    Tests if a value is a parseable JSON string.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a parseable JSON string.\n\n    Examples\n    --------\n    > var bool = isJSON( '{\"a\":5}' )\n    true\n    > bool = isJSON( '{a\":5}' )\n    false\n\n","isKebabcase":"\nisKebabcase( value )\n    Tests if a value is a string in kebab case.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a string in kebab case.\n\n    Examples\n    --------\n    > var bool = isKebabcase( 'beep-boop' )\n    true\n    > bool = isKebabcase( 'BEEP_BOOP' )\n    false\n\n    See Also\n    --------\n    isString","isLeapYear":"\nisLeapYear( value )\n    Tests whether a value corresponds to a leap year in the Gregorian calendar.\n\n    A leap year is defined as any year which is exactly divisible by 4, except\n    for years which are exactly divisible by 100 and not by 400. In this\n    definition, 100 corresponds to years marking a new century, and 400\n    corresponds to the length of the *leap cycle*.\n\n    If not provided any arguments, the function returns a boolean indicating\n    if the current year (according to local time) is a leap year.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value corresponds to a leap year.\n\n    Examples\n    --------\n    > var bool = isLeapYear( new Date() )\n    <boolean>\n    > bool = isLeapYear( 1996 )\n    true\n    > bool = isLeapYear( 2001 )\n    false\n\n","isLocalhost":"\nisLocalhost( value )\n    Tests whether a value is a localhost hostname.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a localhost hostname.\n\n    Examples\n    --------\n    > var bool = isLocalhost( 'localhost' )\n    true\n    > bool = isLocalhost( '127.0.0.1' )\n    true\n    > bool = isLocalhost( 'stdlib.io' )\n    false\n","isLowercase":"\nisLowercase( value )\n    Tests if a value is a lowercase string.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a lowercase string.\n\n    Examples\n    --------\n    > var bool = isLowercase( 'hello' )\n    true\n    > bool = isLowercase( 'World' )\n    false\n\n    See Also\n    --------\n    isString, isUppercase\n","isMatrixLike":"\nisMatrixLike( value )\n    Tests if a value is a 2-dimensional ndarray-like object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 2-dimensional ndarray-like\n        object.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = [ 0, 0, 0, 0 ];\n    > M.ndims = 2;\n    > M.shape = [ 2, 2 ];\n    > M.strides = [ 2, 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'generic';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isMatrixLike( M )\n    true\n    > bool = isMatrixLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isMatrixLike( 3.14 )\n    false\n    > bool = isMatrixLike( {} )\n    false\n\n    See Also\n    --------\n    isArray, isArrayLike, isndarrayLike, isTypedArrayLike, isVectorLike\n","isMethod":"\nisMethod( value, property )\n    Tests if an object has a specified method name.\n\n    Value arguments other than `null` or `undefined` are coerced to objects.\n\n    Property arguments are coerced to strings.\n\n    The function only searches own properties.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object has a specified method name.\n\n    Examples\n    --------\n    > var beep = { 'boop': function beep() { return 'beep'; } };\n    > var bool = isMethod( beep, 'boop' )\n    true\n    > bool = isMethod( beep, 'toString' )\n    false\n\n    See Also\n    --------\n    hasOwnProp, isFunction, isMethodIn\n","isMethodIn":"\nisMethodIn( value, property )\n    Tests if an object has a specified method name, either own or inherited.\n\n    Value arguments other than `null` or `undefined` are coerced to objects.\n\n    Non-symbol property arguments are coerced to strings.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object has a specified method name.\n\n    Examples\n    --------\n    > var beep = { 'boop': true };\n    > var bool = isMethodIn( beep, 'toString' )\n    true\n    > bool = isMethodIn( beep, 'boop' )\n    false\n    > bool = isMethodIn( beep, 'bop' )\n    false\n\n    See Also\n    --------\n    hasProp, isFunction, isMethod\n","isMultiSlice":"\nisMultiSlice( value )\n    Tests if a value is a MultiSlice object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a MultiSlice object.\n\n    Examples\n    --------\n    > var bool = isMultiSlice( new MultiSlice() )\n    true\n    > bool = isMultiSlice( 3.14 )\n    false\n    > bool = isMultiSlice( {} )\n    false\n\n    See Also\n    --------\n    isSlice, MultiSlice\n","isNamedTypedTupleLike":"\nisNamedTypedTupleLike( value )\n    Tests if a value is named typed tuple-like.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is named typed tuple-like.\n\n    Examples\n    --------\n    > var Point = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = new Point();\n    > var bool = isNamedTypedTupleLike( p )\n    true\n    > bool = isNamedTypedTupleLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isNamedTypedTupleLike( 3.14 )\n    false\n    > bool = isNamedTypedTupleLike( {} )\n    false\n\n    See Also\n    --------\n    namedtypedtuple\n","isnan":"\nisnan( value )\n    Tests if a value is NaN.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is NaN.\n\n    Examples\n    --------\n    > var bool = isnan( NaN )\n    true\n    > bool = isnan( new Number( NaN ) )\n    true\n    > bool = isnan( 3.14 )\n    false\n    > bool = isnan( null )\n    false\n\n\nisnan.isPrimitive( value )\n    Tests if a value is a NaN number primitive.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a NaN number primitive.\n\n    Examples\n    --------\n    > var bool = isnan.isPrimitive( NaN )\n    true\n    > bool = isnan.isPrimitive( 3.14 )\n    false\n    > bool = isnan.isPrimitive( new Number( NaN ) )\n    false\n\n\nisnan.isObject( value )\n    Tests if a value is a number object having a value of NaN.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value of\n        NaN.\n\n    Examples\n    --------\n    > var bool = isnan.isObject( NaN )\n    false\n    > bool = isnan.isObject( new Number( NaN ) )\n    true\n\n    See Also\n    --------\n    isNumber\n","isnan.isPrimitive":"\nisnan.isPrimitive( value )\n    Tests if a value is a NaN number primitive.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a NaN number primitive.\n\n    Examples\n    --------\n    > var bool = isnan.isPrimitive( NaN )\n    true\n    > bool = isnan.isPrimitive( 3.14 )\n    false\n    > bool = isnan.isPrimitive( new Number( NaN ) )\n    false","isnan.isObject":"\nisnan.isObject( value )\n    Tests if a value is a number object having a value of NaN.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value of\n        NaN.\n\n    Examples\n    --------\n    > var bool = isnan.isObject( NaN )\n    false\n    > bool = isnan.isObject( new Number( NaN ) )\n    true\n\n    See Also\n    --------\n    isNumber","isNaNArray":"\nisNaNArray( value )\n    Tests if a value is an array-like object containing only NaN values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        NaN values.\n\n    Examples\n    --------\n    > var bool = isNaNArray( [ NaN, NaN, NaN ] )\n    true\n    > bool = isNaNArray( [ NaN, 2 ] )\n    false\n\n\nisNaNArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive NaN\n    values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive NaN values.\n\n    Examples\n    --------\n    > var bool = isNaNArray.primitives( [ NaN, new Number( NaN ) ] )\n    false\n    > bool = isNaNArray.primitives( [ NaN, NaN, NaN ] )\n    true\n\n\nisNaNArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having NaN values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having NaN values.\n\n    Examples\n    --------\n    > var bool = isNaNArray.objects( [ new Number( NaN ), new Number( NaN ) ] )\n    true\n    > bool = isNaNArray.objects( [ NaN, new Number( NaN ), new Number( NaN ) ] )\n    false\n    > bool = isNaNArray.objects( [ NaN, NaN, NaN ] )\n    false\n\n    See Also\n    --------\n    isnan\n","isNaNArray.primitives":"\nisNaNArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive NaN\n    values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive NaN values.\n\n    Examples\n    --------\n    > var bool = isNaNArray.primitives( [ NaN, new Number( NaN ) ] )\n    false\n    > bool = isNaNArray.primitives( [ NaN, NaN, NaN ] )\n    true","isNaNArray.objects":"\nisNaNArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having NaN values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having NaN values.\n\n    Examples\n    --------\n    > var bool = isNaNArray.objects( [ new Number( NaN ), new Number( NaN ) ] )\n    true\n    > bool = isNaNArray.objects( [ NaN, new Number( NaN ), new Number( NaN ) ] )\n    false\n    > bool = isNaNArray.objects( [ NaN, NaN, NaN ] )\n    false\n\n    See Also\n    --------\n    isnan","isNativeFunction":"\nisNativeFunction( value )\n    Tests if a value is a native function.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a native function.\n\n    Examples\n    --------\n    > var bool = isNativeFunction( Date )\n    true\n    > function beep() {};\n    > bool = isNativeFunction( beep )\n    false\n    > bool = isNativeFunction( {} )\n    false\n\n    See Also\n    --------\n    isFunction\n","isndarrayLike":"\nisndarrayLike( value )\n    Tests if a value is ndarray-like.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is ndarray-like.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = [ 0, 0, 0, 0 ];\n    > M.ndims = 2;\n    > M.shape = [ 2, 2 ];\n    > M.strides = [ 2, 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'generic';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isndarrayLike( M )\n    true\n    > bool = isndarrayLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isndarrayLike( 3.14 )\n    false\n    > bool = isndarrayLike( {} )\n    false\n\n    See Also\n    --------\n    isArray, isArrayLike, isMatrixLike, isTypedArrayLike, isVectorLike\n","isndarrayLikeWithDataType":"\nisndarrayLikeWithDataType( value, dtype )\n    Tests if a value is an ndarray-like object having a specified data type.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    dtype: any\n        Data type value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an ndarray-like object having a\n        specified data type.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = [ 0, 0, 0, 0 ];\n    > M.ndims = 2;\n    > M.shape = [ 2, 2 ];\n    > M.strides = [ 2, 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'generic';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isndarrayLikeWithDataType( M, 'generic' )\n    true\n    > bool = isndarrayLikeWithDataType( [ 1, 2, 3, 4 ], 'generic' )\n    false\n    > bool = isndarrayLikeWithDataType( 3.14, 'generic' )\n    false\n    > bool = isndarrayLikeWithDataType( {}, 'generic' )\n    false\n\n    See Also\n    --------\n    isndarrayLike\n","isNegativeFinite":"\nisNegativeFinite( value )\n    Tests if a value is a finite negative number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a finite negative number.\n\n    Examples\n    --------\n    > var bool = isNegativeFinite( -5.0 )\n    true\n    > bool = isNegativeFinite( new Number( -5.0 ) )\n    true\n    > bool = isNegativeFinite( -3.14 )\n    true\n    > bool = isNegativeFinite( 5.0 )\n    false\n    > bool = isNegativeFinite( null )\n    false\n    > bool = isNegativeFinite( -1.0/0.0 )\n    false\n    > bool = isNegativeFinite( new Number( -1.0/0.0 ) )\n    false\n\n\nisNegativeFinite.isPrimitive( value )\n    Tests if a value is a number primitive having a finite negative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number primitive having a finite\n        negative value.\n\n    Examples\n    --------\n    > var bool = isNegativeFinite.isPrimitive( -3.0 )\n    true\n    > bool = isNegativeFinite.isPrimitive( new Number( -3.0 ) )\n    false\n    > var bool = isNegativeFinite.isPrimitive( -1.0/0.0 )\n    false\n    > bool = isNegativeFinite.isPrimitive( new Number( -1.0/0.0 ) )\n    false\n\n\nisNegativeFinite.isObject( value )\n    Tests if a value is a number object having a finite negative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number object having a finite\n        negative value.\n\n    Examples\n    --------\n    > var bool = isNegativeFinite.isObject( -3.0 )\n    false\n    > bool = isNegativeFinite.isObject( new Number( -3.0 ) )\n    true\n    > bool = isNegativeFinite.isObject( -1.0/0.0 )\n    false\n    > bool = isNegativeFinite.isObject( new Number( -1.0/0.0 ) )\n    false\n\n    See Also\n    --------\n    isFinite, isNegativeNumber, isPositiveFinite\n","isNegativeFinite.isPrimitive":"\nisNegativeFinite.isPrimitive( value )\n    Tests if a value is a number primitive having a finite negative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number primitive having a finite\n        negative value.\n\n    Examples\n    --------\n    > var bool = isNegativeFinite.isPrimitive( -3.0 )\n    true\n    > bool = isNegativeFinite.isPrimitive( new Number( -3.0 ) )\n    false\n    > var bool = isNegativeFinite.isPrimitive( -1.0/0.0 )\n    false\n    > bool = isNegativeFinite.isPrimitive( new Number( -1.0/0.0 ) )\n    false","isNegativeFinite.isObject":"\nisNegativeFinite.isObject( value )\n    Tests if a value is a number object having a finite negative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number object having a finite\n        negative value.\n\n    Examples\n    --------\n    > var bool = isNegativeFinite.isObject( -3.0 )\n    false\n    > bool = isNegativeFinite.isObject( new Number( -3.0 ) )\n    true\n    > bool = isNegativeFinite.isObject( -1.0/0.0 )\n    false\n    > bool = isNegativeFinite.isObject( new Number( -1.0/0.0 ) )\n    false\n\n    See Also\n    --------\n    isFinite, isNegativeNumber, isPositiveFinite","isNegativeInteger":"\nisNegativeInteger( value )\n    Tests if a value is a negative integer.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a negative integer.\n\n    Examples\n    --------\n    > var bool = isNegativeInteger( -5.0 )\n    true\n    > bool = isNegativeInteger( new Number( -5.0 ) )\n    true\n    > bool = isNegativeInteger( 5.0 )\n    false\n    > bool = isNegativeInteger( -3.14 )\n    false\n    > bool = isNegativeInteger( null )\n    false\n\n\nisNegativeInteger.isPrimitive( value )\n    Tests if a value is a number primitive having a negative integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a negative\n        integer value.\n\n    Examples\n    --------\n    > var bool = isNegativeInteger.isPrimitive( -3.0 )\n    true\n    > bool = isNegativeInteger.isPrimitive( new Number( -3.0 ) )\n    false\n\n\nisNegativeInteger.isObject( value )\n    Tests if a value is a number object having a negative integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a negative\n        integer value.\n\n    Examples\n    --------\n    > var bool = isNegativeInteger.isObject( -3.0 )\n    false\n    > bool = isNegativeInteger.isObject( new Number( -3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger\n","isNegativeInteger.isPrimitive":"\nisNegativeInteger.isPrimitive( value )\n    Tests if a value is a number primitive having a negative integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a negative\n        integer value.\n\n    Examples\n    --------\n    > var bool = isNegativeInteger.isPrimitive( -3.0 )\n    true\n    > bool = isNegativeInteger.isPrimitive( new Number( -3.0 ) )\n    false","isNegativeInteger.isObject":"\nisNegativeInteger.isObject( value )\n    Tests if a value is a number object having a negative integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a negative\n        integer value.\n\n    Examples\n    --------\n    > var bool = isNegativeInteger.isObject( -3.0 )\n    false\n    > bool = isNegativeInteger.isObject( new Number( -3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger","isNegativeIntegerArray":"\nisNegativeIntegerArray( value )\n    Tests if a value is an array-like object containing only negative integers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        negative integers.\n\n    Examples\n    --------\n    > var bool = isNegativeIntegerArray( [ -3.0, new Number(-3.0) ] )\n    true\n    > bool = isNegativeIntegerArray( [ -3.0, '-3.0' ] )\n    false\n\n\nisNegativeIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only negative primitive\n    integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        negative primitive integer values.\n\n    Examples\n    --------\n    > var bool = isNegativeIntegerArray.primitives( [ -1.0, -10.0 ] )\n    true\n    > bool = isNegativeIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNegativeIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false\n\n\nisNegativeIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having negative integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having negative integer values.\n\n    Examples\n    --------\n    > var bool = isNegativeIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n    true\n    > bool = isNegativeIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNegativeIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray\n","isNegativeIntegerArray.primitives":"\nisNegativeIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only negative primitive\n    integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        negative primitive integer values.\n\n    Examples\n    --------\n    > var bool = isNegativeIntegerArray.primitives( [ -1.0, -10.0 ] )\n    true\n    > bool = isNegativeIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNegativeIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false","isNegativeIntegerArray.objects":"\nisNegativeIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having negative integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having negative integer values.\n\n    Examples\n    --------\n    > var bool = isNegativeIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n    true\n    > bool = isNegativeIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNegativeIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray","isNegativeNumber":"\nisNegativeNumber( value )\n    Tests if a value is a negative number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a negative number.\n\n    Examples\n    --------\n    > var bool = isNegativeNumber( -5.0 )\n    true\n    > bool = isNegativeNumber( new Number( -5.0 ) )\n    true\n    > bool = isNegativeNumber( -3.14 )\n    true\n    > bool = isNegativeNumber( 5.0 )\n    false\n    > bool = isNegativeNumber( null )\n    false\n\n\nisNegativeNumber.isPrimitive( value )\n    Tests if a value is a number primitive having a negative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a negative\n        value.\n\n    Examples\n    --------\n    > var bool = isNegativeNumber.isPrimitive( -3.0 )\n    true\n    > bool = isNegativeNumber.isPrimitive( new Number( -3.0 ) )\n    false\n\n\nisNegativeNumber.isObject( value )\n    Tests if a value is a number object having a negative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a negative\n        value.\n\n    Examples\n    --------\n    > var bool = isNegativeNumber.isObject( -3.0 )\n    false\n    > bool = isNegativeNumber.isObject( new Number( -3.0 ) )\n    true\n\n    See Also\n    --------\n    isNumber\n","isNegativeNumber.isPrimitive":"\nisNegativeNumber.isPrimitive( value )\n    Tests if a value is a number primitive having a negative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a negative\n        value.\n\n    Examples\n    --------\n    > var bool = isNegativeNumber.isPrimitive( -3.0 )\n    true\n    > bool = isNegativeNumber.isPrimitive( new Number( -3.0 ) )\n    false","isNegativeNumber.isObject":"\nisNegativeNumber.isObject( value )\n    Tests if a value is a number object having a negative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a negative\n        value.\n\n    Examples\n    --------\n    > var bool = isNegativeNumber.isObject( -3.0 )\n    false\n    > bool = isNegativeNumber.isObject( new Number( -3.0 ) )\n    true\n\n    See Also\n    --------\n    isNumber","isNegativeNumberArray":"\nisNegativeNumberArray( value )\n    Tests if a value is an array-like object containing only negative numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        negative numbers.\n\n    Examples\n    --------\n    > var bool = isNegativeNumberArray( [ -3.0, new Number(-3.0) ] )\n    true\n    > bool = isNegativeNumberArray( [ -3.0, '-3.0' ] )\n    false\n\n\nisNegativeNumberArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive negative\n    numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive negative numbers.\n\n    Examples\n    --------\n    > var bool = isNegativeNumberArray.primitives( [ -1.0, -10.0 ] )\n    true\n    > bool = isNegativeNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNegativeNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false\n\n\nisNegativeNumberArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having negative number values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having negative number values.\n\n    Examples\n    --------\n    > var bool = isNegativeNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n    true\n    > bool = isNegativeNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNegativeNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray\n","isNegativeNumberArray.primitives":"\nisNegativeNumberArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive negative\n    numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive negative numbers.\n\n    Examples\n    --------\n    > var bool = isNegativeNumberArray.primitives( [ -1.0, -10.0 ] )\n    true\n    > bool = isNegativeNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNegativeNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false","isNegativeNumberArray.objects":"\nisNegativeNumberArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having negative number values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having negative number values.\n\n    Examples\n    --------\n    > var bool = isNegativeNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n    true\n    > bool = isNegativeNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNegativeNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray","isNegativeZero":"\nisNegativeZero( value )\n    Tests if a value is negative zero.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is negative zero.\n\n    Examples\n    --------\n    > var bool = isNegativeZero( -0.0 )\n    true\n    > bool = isNegativeZero( new Number( -0.0 ) )\n    true\n    > bool = isNegativeZero( -3.14 )\n    false\n    > bool = isNegativeZero( 0.0 )\n    false\n    > bool = isNegativeZero( null )\n    false\n\n\nisNegativeZero.isPrimitive( value )\n    Tests if a value is a number primitive equal to negative zero.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number primitive equal to\n        negative zero.\n\n    Examples\n    --------\n    > var bool = isNegativeZero.isPrimitive( -0.0 )\n    true\n    > bool = isNegativeZero.isPrimitive( new Number( -0.0 ) )\n    false\n\n\nisNegativeZero.isObject( value )\n    Tests if a value is a number object having a value equal to negative zero.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number object having a value\n        equal to negative zero.\n\n    Examples\n    --------\n    > var bool = isNegativeZero.isObject( -0.0 )\n    false\n    > bool = isNegativeZero.isObject( new Number( -0.0 ) )\n    true\n\n    See Also\n    --------\n    isNumber, isPositiveZero\n","isNegativeZero.isPrimitive":"\nisNegativeZero.isPrimitive( value )\n    Tests if a value is a number primitive equal to negative zero.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number primitive equal to\n        negative zero.\n\n    Examples\n    --------\n    > var bool = isNegativeZero.isPrimitive( -0.0 )\n    true\n    > bool = isNegativeZero.isPrimitive( new Number( -0.0 ) )\n    false","isNegativeZero.isObject":"\nisNegativeZero.isObject( value )\n    Tests if a value is a number object having a value equal to negative zero.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number object having a value\n        equal to negative zero.\n\n    Examples\n    --------\n    > var bool = isNegativeZero.isObject( -0.0 )\n    false\n    > bool = isNegativeZero.isObject( new Number( -0.0 ) )\n    true\n\n    See Also\n    --------\n    isNumber, isPositiveZero","isNodeBuiltin":"\nisNodeBuiltin( str )\n    Tests whether a string matches a Node.js built-in module name.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a string matches a Node.js built-in module\n        name.\n\n    Examples\n    --------\n    > var bool = isNodeBuiltin( 'cluster' )\n    true\n    > bool = isNodeBuiltin( 'crypto' )\n    true\n    > bool = isNodeBuiltin( 'fs-extra' )\n    false\n    > bool = isNodeBuiltin( '' )\n    false\n\n","isNodeDuplexStreamLike":"\nisNodeDuplexStreamLike( value )\n    Tests if a value is Node duplex stream-like.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is Node duplex stream-like.\n\n    Examples\n    --------\n    > var Stream = require( 'stream' ).Duplex;\n    > s = new Stream();\n    > var bool = isNodeDuplexStreamLike( s )\n    true\n    > bool = isNodeDuplexStreamLike( {} )\n    false\n\n    See Also\n    --------\n    isNodeStreamLike\n","isNodeReadableStreamLike":"\nisNodeReadableStreamLike( value )\n    Tests if a value is Node readable stream-like.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is Node readable stream-like.\n\n    Examples\n    --------\n    > var Stream = require( 'stream' ).Readable;\n    > s = new Stream();\n    > var bool = isNodeReadableStreamLike( s )\n    true\n    > bool = isNodeReadableStreamLike( {} )\n    false\n\n    See Also\n    --------\n    isNodeStreamLike\n","isNodeREPL":"\nisNodeREPL()\n    Returns a boolean indicating if running in a Node.js REPL environment.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if running in a Node.js REPL environment.\n\n    Examples\n    --------\n    > var bool = isNodeREPL()\n    <boolean>\n\n","isNodeStreamLike":"\nisNodeStreamLike( value )\n    Tests if a value is Node stream-like.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is Node stream-like.\n\n    Examples\n    --------\n    > var Stream = require( 'stream' ).Stream;\n    > s = new Stream();\n    > var bool = isNodeStreamLike( s )\n    true\n    > bool = isNodeStreamLike( {} )\n    false\n\n","isNodeTransformStreamLike":"\nisNodeTransformStreamLike( value )\n    Tests if a value is Node transform stream-like.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is Node transform stream-like.\n\n    Examples\n    --------\n    > var Stream = require( 'stream' ).Transform;\n    > s = new Stream();\n    > var bool = isNodeTransformStreamLike( s )\n    true\n    > bool = isNodeTransformStreamLike( {} )\n    false\n\n    See Also\n    --------\n    isNodeStreamLike\n","isNodeWritableStreamLike":"\nisNodeWritableStreamLike( value )\n    Tests if a value is Node writable stream-like.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is Node writable stream-like.\n\n    Examples\n    --------\n    > var Stream = require( 'stream' ).Writable;\n    > s = new Stream();\n    > var bool = isNodeWritableStreamLike( s )\n    true\n    > bool = isNodeWritableStreamLike( {} )\n    false\n\n    See Also\n    --------\n    isNodeStreamLike\n","isNonConfigurableProperty":"\nisNonConfigurableProperty( value, property )\n    Tests if an object's own property is non-configurable.\n\n    A non-configurable property is a property which cannot be deleted and whose\n    descriptor cannot be changed.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own property is non-configurable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = true;\n    > desc.writable = true;\n    > desc.value = 'beep';\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isNonConfigurableProperty( obj, 'boop' )\n    false\n    > bool = isNonConfigurableProperty( obj, 'beep' )\n    true\n\n    See Also\n    --------\n    isConfigurableProperty, isEnumerableProperty, isNonConfigurablePropertyIn, isNonEnumerableProperty, isReadableProperty, isWritableProperty\n","isNonConfigurablePropertyIn":"\nisNonConfigurablePropertyIn( value, property )\n    Tests if an object's own or inherited property is non-configurable.\n\n    A non-configurable property is a property which cannot be deleted and whose\n    descriptor cannot be changed.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own or inherited property is non-\n        configurable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = true;\n    > desc.writable = true;\n    > desc.value = true;\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isNonConfigurablePropertyIn( obj, 'boop' )\n    false\n    > bool = isNonConfigurablePropertyIn( obj, 'beep' )\n    true\n\n    See Also\n    --------\n    isConfigurablePropertyIn, isEnumerablePropertyIn, isNonConfigurableProperty, isNonEnumerablePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isNonEnumerableProperty":"\nisNonEnumerableProperty( value, property )\n    Tests if an object's own property is non-enumerable.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own property is non-enumerable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.writable = true;\n    > desc.value = 'beep';\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isNonEnumerableProperty( obj, 'boop' )\n    false\n    > bool = isNonEnumerableProperty( obj, 'beep' )\n    true\n\n    See Also\n    --------\n    isConfigurableProperty, isEnumerableProperty, isNonConfigurableProperty, isNonEnumerablePropertyIn, isReadableProperty, isWritableProperty\n","isNonEnumerablePropertyIn":"\nisNonEnumerablePropertyIn( value, property )\n    Tests if an object's own or inherited property is non-enumerable.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own or inherited property is non-\n        enumerable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = true;\n    > desc.enumerable = false;\n    > desc.writable = true;\n    > desc.value = true;\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isNonEnumerablePropertyIn( obj, 'boop' )\n    false\n    > bool = isNonEnumerablePropertyIn( obj, 'beep' )\n    true\n\n    See Also\n    --------\n    isConfigurablePropertyIn, isEnumerablePropertyIn, isNonConfigurablePropertyIn, isNonEnumerableProperty, isReadablePropertyIn, isWritablePropertyIn\n","isNonNegativeFinite":"\nisNonNegativeFinite( value )\n    Tests if a value is a nonnegative finite number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a nonnegative finite number.\n\n    Examples\n    --------\n    > var bool = isNonNegativeFinite( 5.0 )\n    true\n    > bool = isNonNegativeFinite( new Number( 5.0 ) )\n    true\n    > bool = isNonNegativeFinite( 3.14 )\n    true\n    > bool = isNonNegativeFinite( -5.0 )\n    false\n    > bool = isNonNegativeFinite( null )\n    false\n    > bool = isNonNegativeFinite( PINF )\n    false\n\n\nisNonNegativeFinite.isPrimitive( value )\n    Tests if a value is a number primitive having a nonnegative finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonnegative finite value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeFinite.isPrimitive( 3.0 )\n    true\n    > bool = isNonNegativeFinite.isPrimitive( new Number( 3.0 ) )\n    false\n\n\nisNonNegativeFinite.isObject( value )\n    Tests if a value is a number object having a nonnegative finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a \n        nonnegative finite value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeFinite.isObject( 3.0 )\n    false\n    > bool = isNonNegativeFinite.isObject( new Number( 3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isFinite, isNonNegativeNumber, isNumber\n","isNonNegativeFinite.isPrimitive":"\nisNonNegativeFinite.isPrimitive( value )\n    Tests if a value is a number primitive having a nonnegative finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonnegative finite value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeFinite.isPrimitive( 3.0 )\n    true\n    > bool = isNonNegativeFinite.isPrimitive( new Number( 3.0 ) )\n    false","isNonNegativeFinite.isObject":"\nisNonNegativeFinite.isObject( value )\n    Tests if a value is a number object having a nonnegative finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a \n        nonnegative finite value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeFinite.isObject( 3.0 )\n    false\n    > bool = isNonNegativeFinite.isObject( new Number( 3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isFinite, isNonNegativeNumber, isNumber","isNonNegativeInteger":"\nisNonNegativeInteger( value )\n    Tests if a value is a nonnegative integer.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a nonnegative integer.\n\n    Examples\n    --------\n    > var bool = isNonNegativeInteger( 5.0 )\n    true\n    > bool = isNonNegativeInteger( new Number( 5.0 ) )\n    true\n    > bool = isNonNegativeInteger( 3.14 )\n    false\n    > bool = isNonNegativeInteger( -5.0 )\n    false\n    > bool = isNonNegativeInteger( null )\n    false\n\n\nisNonNegativeInteger.isPrimitive( value )\n    Tests if a value is a number primitive having a nonnegative integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonnegative integer value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeInteger.isPrimitive( 3.0 )\n    true\n    > bool = isNonNegativeInteger.isPrimitive( new Number( 3.0 ) )\n    false\n\n\nisNonNegativeInteger.isObject( value )\n    Tests if a value is a number object having a nonnegative integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a nonnegative\n        integer value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeInteger.isObject( 3.0 )\n    false\n    > bool = isNonNegativeInteger.isObject( new Number( 3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger, isNonNegativeNumber, isNumber\n","isNonNegativeInteger.isPrimitive":"\nisNonNegativeInteger.isPrimitive( value )\n    Tests if a value is a number primitive having a nonnegative integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonnegative integer value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeInteger.isPrimitive( 3.0 )\n    true\n    > bool = isNonNegativeInteger.isPrimitive( new Number( 3.0 ) )\n    false","isNonNegativeInteger.isObject":"\nisNonNegativeInteger.isObject( value )\n    Tests if a value is a number object having a nonnegative integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a nonnegative\n        integer value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeInteger.isObject( 3.0 )\n    false\n    > bool = isNonNegativeInteger.isObject( new Number( 3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger, isNonNegativeNumber, isNumber","isNonNegativeIntegerArray":"\nisNonNegativeIntegerArray( value )\n    Tests if a value is an array-like object containing only nonnegative\n    integers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        nonnegative integers.\n\n    Examples\n    --------\n    > var bool = isNonNegativeIntegerArray( [ 3.0, new Number(3.0) ] )\n    true\n    > bool = isNonNegativeIntegerArray( [ 3.0, '3.0' ] )\n    false\n\n\nisNonNegativeIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only nonnegative\n    primitive integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        nonnegative primitive integer values.\n\n    Examples\n    --------\n    > var bool = isNonNegativeIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n    true\n    > bool = isNonNegativeIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n    false\n\n\nisNonNegativeIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having nonnegative integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having nonnegative integer values.\n\n    Examples\n    --------\n    > var bool = isNonNegativeIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n    true\n    > bool = isNonNegativeIntegerArray.objects( [ 1.0, 0.0, 10.0 ] )\n    false\n    > bool = isNonNegativeIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray\n","isNonNegativeIntegerArray.primitives":"\nisNonNegativeIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only nonnegative\n    primitive integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        nonnegative primitive integer values.\n\n    Examples\n    --------\n    > var bool = isNonNegativeIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n    true\n    > bool = isNonNegativeIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n    false","isNonNegativeIntegerArray.objects":"\nisNonNegativeIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having nonnegative integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having nonnegative integer values.\n\n    Examples\n    --------\n    > var bool = isNonNegativeIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n    true\n    > bool = isNonNegativeIntegerArray.objects( [ 1.0, 0.0, 10.0 ] )\n    false\n    > bool = isNonNegativeIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray","isNonNegativeNumber":"\nisNonNegativeNumber( value )\n    Tests if a value is a nonnegative number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a nonnegative number.\n\n    Examples\n    --------\n    > var bool = isNonNegativeNumber( 5.0 )\n    true\n    > bool = isNonNegativeNumber( new Number( 5.0 ) )\n    true\n    > bool = isNonNegativeNumber( 3.14 )\n    true\n    > bool = isNonNegativeNumber( -5.0 )\n    false\n    > bool = isNonNegativeNumber( null )\n    false\n\n\nisNonNegativeNumber.isPrimitive( value )\n    Tests if a value is a number primitive having a nonnegative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonnegative value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeNumber.isPrimitive( 3.0 )\n    true\n    > bool = isNonNegativeNumber.isPrimitive( new Number( 3.0 ) )\n    false\n\n\nisNonNegativeNumber.isObject( value )\n    Tests if a value is a number object having a nonnegative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a nonnegative\n        value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeNumber.isObject( 3.0 )\n    false\n    > bool = isNonNegativeNumber.isObject( new Number( 3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isNonNegativeFinite, isNonNegativeInteger, isNumber\n","isNonNegativeNumber.isPrimitive":"\nisNonNegativeNumber.isPrimitive( value )\n    Tests if a value is a number primitive having a nonnegative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonnegative value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeNumber.isPrimitive( 3.0 )\n    true\n    > bool = isNonNegativeNumber.isPrimitive( new Number( 3.0 ) )\n    false","isNonNegativeNumber.isObject":"\nisNonNegativeNumber.isObject( value )\n    Tests if a value is a number object having a nonnegative value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a nonnegative\n        value.\n\n    Examples\n    --------\n    > var bool = isNonNegativeNumber.isObject( 3.0 )\n    false\n    > bool = isNonNegativeNumber.isObject( new Number( 3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isNonNegativeFinite, isNonNegativeInteger, isNumber","isNonNegativeNumberArray":"\nisNonNegativeNumberArray( value )\n    Tests if a value is an array-like object containing only nonnegative\n    numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        nonnegative numbers.\n\n    Examples\n    --------\n    > var bool = isNonNegativeNumberArray( [ 3.0, new Number(3.0) ] )\n    true\n    > bool = isNonNegativeNumberArray( [ 3.0, '3.0' ] )\n    false\n\n\nisNonNegativeNumberArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive\n    nonnegative numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive nonnegative numbers.\n\n    Examples\n    --------\n    > var bool = isNonNegativeNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n    true\n    > bool = isNonNegativeNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n    false\n\n\nisNonNegativeNumberArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having nonnegative number values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having nonnegative number values.\n\n    Examples\n    --------\n    > var bool = isNonNegativeNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n    true\n    > bool = isNonNegativeNumberArray.objects( [ 1.0, 0.0, 10.0 ] )\n    false\n    > bool = isNonNegativeNumberArray.objects( [ 3.0, new Number(1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray\n","isNonNegativeNumberArray.primitives":"\nisNonNegativeNumberArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive\n    nonnegative numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive nonnegative numbers.\n\n    Examples\n    --------\n    > var bool = isNonNegativeNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n    true\n    > bool = isNonNegativeNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n    false","isNonNegativeNumberArray.objects":"\nisNonNegativeNumberArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having nonnegative number values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having nonnegative number values.\n\n    Examples\n    --------\n    > var bool = isNonNegativeNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n    true\n    > bool = isNonNegativeNumberArray.objects( [ 1.0, 0.0, 10.0 ] )\n    false\n    > bool = isNonNegativeNumberArray.objects( [ 3.0, new Number(1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray","isNonPositiveFinite":"\nisNonPositiveFinite( value )\n    Tests if a value is a nonpositive finite number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a nonpositive finite number.\n\n    Examples\n    --------\n    > var bool = isNonPositiveFinite( -5.0 )\n    true\n    > bool = isNonPositiveFinite( new Number( -5.0 ) )\n    true\n    > bool = isNonPositiveFinite( -3.14 )\n    true\n    > bool = isNonPositiveFinite( 5.0 )\n    false\n    > bool = isNonPositiveFinite( null )\n    false\n\n\nisNonPositiveFinite.isPrimitive( value )\n    Tests if a value is a number primitive having a nonpositive finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonpositive finite value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveFinite.isPrimitive( -3.0 )\n    true\n    > bool = isNonPositiveFinite.isPrimitive( new Number( -3.0 ) )\n    false\n\n\nisNonPositiveFinite.isObject( value )\n    Tests if a value is a number object having a nonpositive finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a nonpositive\n        finite value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveFinite.isObject( -3.0 )\n    false\n    > bool = isNonPositiveFinite.isObject( new Number( -3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isFinite, isNonPositiveNumber\n","isNonPositiveFinite.isPrimitive":"\nisNonPositiveFinite.isPrimitive( value )\n    Tests if a value is a number primitive having a nonpositive finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonpositive finite value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveFinite.isPrimitive( -3.0 )\n    true\n    > bool = isNonPositiveFinite.isPrimitive( new Number( -3.0 ) )\n    false","isNonPositiveFinite.isObject":"\nisNonPositiveFinite.isObject( value )\n    Tests if a value is a number object having a nonpositive finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a nonpositive\n        finite value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveFinite.isObject( -3.0 )\n    false\n    > bool = isNonPositiveFinite.isObject( new Number( -3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isFinite, isNonPositiveNumber","isNonPositiveInteger":"\nisNonPositiveInteger( value )\n    Tests if a value is a nonpositive integer.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a nonpositive integer.\n\n    Examples\n    --------\n    > var bool = isNonPositiveInteger( -5.0 )\n    true\n    > bool = isNonPositiveInteger( new Number( -5.0 ) )\n    true\n    > bool = isNonPositiveInteger( 5.0 )\n    false\n    > bool = isNonPositiveInteger( -3.14 )\n    false\n    > bool = isNonPositiveInteger( null )\n    false\n\n\nisNonPositiveInteger.isPrimitive( value )\n    Tests if a value is a number primitive having a nonpositive integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonpositive integer value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveInteger.isPrimitive( -3.0 )\n    true\n    > bool = isNonPositiveInteger.isPrimitive( new Number( -3.0 ) )\n    false\n\n\nisNonPositiveInteger.isObject( value )\n    Tests if a value is a number object having a nonpositive integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a nonpositive\n        integer value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveInteger.isObject( -3.0 )\n    false\n    > bool = isNonPositiveInteger.isObject( new Number( -3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger\n","isNonPositiveInteger.isPrimitive":"\nisNonPositiveInteger.isPrimitive( value )\n    Tests if a value is a number primitive having a nonpositive integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonpositive integer value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveInteger.isPrimitive( -3.0 )\n    true\n    > bool = isNonPositiveInteger.isPrimitive( new Number( -3.0 ) )\n    false","isNonPositiveInteger.isObject":"\nisNonPositiveInteger.isObject( value )\n    Tests if a value is a number object having a nonpositive integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a nonpositive\n        integer value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveInteger.isObject( -3.0 )\n    false\n    > bool = isNonPositiveInteger.isObject( new Number( -3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger","isNonPositiveIntegerArray":"\nisNonPositiveIntegerArray( value )\n    Tests if a value is an array-like object containing only nonpositive\n    integers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        nonpositive integers.\n\n    Examples\n    --------\n    > var bool = isNonPositiveIntegerArray( [ -3.0, new Number(-3.0) ] )\n    true\n    > bool = isNonPositiveIntegerArray( [ -3.0, '-3.0' ] )\n    false\n\n\nisNonPositiveIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only nonpositive\n    primitive integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        nonpositive primitive integer values.\n\n    Examples\n    --------\n    > var bool = isNonPositiveIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n    true\n    > bool = isNonPositiveIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false\n\n\nisNonPositiveIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having nonpositive integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having nonpositive integer values.\n\n    Examples\n    --------\n    > var bool = isNonPositiveIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n    true\n    > bool = isNonPositiveIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNonPositiveIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray\n","isNonPositiveIntegerArray.primitives":"\nisNonPositiveIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only nonpositive\n    primitive integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        nonpositive primitive integer values.\n\n    Examples\n    --------\n    > var bool = isNonPositiveIntegerArray.primitives( [ -1.0, 0.0, -10.0 ] )\n    true\n    > bool = isNonPositiveIntegerArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false","isNonPositiveIntegerArray.objects":"\nisNonPositiveIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having nonpositive integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having nonpositive integer values.\n\n    Examples\n    --------\n    > var bool = isNonPositiveIntegerArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n    true\n    > bool = isNonPositiveIntegerArray.objects( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNonPositiveIntegerArray.objects( [ -3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray","isNonPositiveNumber":"\nisNonPositiveNumber( value )\n    Tests if a value is a nonpositive number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a nonpositive number.\n\n    Examples\n    --------\n    > var bool = isNonPositiveNumber( -5.0 )\n    true\n    > bool = isNonPositiveNumber( new Number( -5.0 ) )\n    true\n    > bool = isNonPositiveNumber( -3.14 )\n    true\n    > bool = isNonPositiveNumber( 5.0 )\n    false\n    > bool = isNonPositiveNumber( null )\n    false\n\n\nisNonPositiveNumber.isPrimitive( value )\n    Tests if a value is a number primitive having a nonpositive value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonpositive value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveNumber.isPrimitive( -3.0 )\n    true\n    > bool = isNonPositiveNumber.isPrimitive( new Number( -3.0 ) )\n    false\n\n\nisNonPositiveNumber.isObject( value )\n    Tests if a value is a number object having a nonpositive value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a nonpositive\n        value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveNumber.isObject( -3.0 )\n    false\n    > bool = isNonPositiveNumber.isObject( new Number( -3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isNumber\n","isNonPositiveNumber.isPrimitive":"\nisNonPositiveNumber.isPrimitive( value )\n    Tests if a value is a number primitive having a nonpositive value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        nonpositive value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveNumber.isPrimitive( -3.0 )\n    true\n    > bool = isNonPositiveNumber.isPrimitive( new Number( -3.0 ) )\n    false","isNonPositiveNumber.isObject":"\nisNonPositiveNumber.isObject( value )\n    Tests if a value is a number object having a nonpositive value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a nonpositive\n        value.\n\n    Examples\n    --------\n    > var bool = isNonPositiveNumber.isObject( -3.0 )\n    false\n    > bool = isNonPositiveNumber.isObject( new Number( -3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isNumber","isNonPositiveNumberArray":"\nisNonPositiveNumberArray( value )\n    Tests if a value is an array-like object containing only nonpositive\n    numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        nonpositive numbers.\n\n    Examples\n    --------\n    > var bool = isNonPositiveNumberArray( [ -3.0, new Number(-3.0) ] )\n    true\n    > bool = isNonPositiveNumberArray( [ -3.0, '-3.0' ] )\n    false\n\n\nisNonPositiveNumberArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive\n    nonpositive numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive nonpositive numbers.\n\n    Examples\n    --------\n    > var bool = isNonPositiveNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n    true\n    > bool = isNonPositiveNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false\n\n\nisNonPositiveNumberArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having nonpositive number values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having nonpositive number values.\n\n    Examples\n    --------\n    > var bool = isNonPositiveNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n    true\n    > bool = isNonPositiveNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNonPositiveNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray\n","isNonPositiveNumberArray.primitives":"\nisNonPositiveNumberArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive\n    nonpositive numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive nonpositive numbers.\n\n    Examples\n    --------\n    > var bool = isNonPositiveNumberArray.primitives( [ -1.0, 0.0, -10.0 ] )\n    true\n    > bool = isNonPositiveNumberArray.primitives( [ -3.0, new Number(-1.0) ] )\n    false","isNonPositiveNumberArray.objects":"\nisNonPositiveNumberArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having nonpositive number values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having nonpositive number values.\n\n    Examples\n    --------\n    > var bool = isNonPositiveNumberArray.objects( [ new Number(-1.0), new Number(-10.0) ] )\n    true\n    > bool = isNonPositiveNumberArray.objects( [ -1.0, 0.0, -10.0 ] )\n    false\n    > bool = isNonPositiveNumberArray.objects( [ -3.0, new Number(-1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray","isNonSymmetricMatrix":"\nisNonSymmetricMatrix( value )\n    Tests if a value is a non-symmetric matrix.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a non-symmetric matrix.\n\n    Examples\n    --------\n    > var buf = [ 1, 2, 3, 4 ];\n    > var sh = [ 2, 2 ];\n    > var st = [ 2, 1 ];\n    > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n    > var bool = isNonSymmetricMatrix( M )\n    true\n    > bool = isNonSymmetricMatrix( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isNonSymmetricMatrix( 3.14 )\n    false\n    > bool = isNonSymmetricMatrix( {} )\n    false\n\n    See Also\n    --------\n    isMatrixLike, isSquareMatrix, isSymmetricMatrix\n","isNull":"\nisNull( value )\n    Tests if a value is null.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is null.\n\n    Examples\n    --------\n    > var bool = isNull( null )\n    true\n    > bool = isNull( true )\n    false\n\n    See Also\n    --------\n    isUndefined, isUndefinedOrNull\n","isNullArray":"\nisNullArray( value )\n    Tests if a value is an array-like object containing only null values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        null values.\n\n    Examples\n    --------\n    > var bool = isNullArray( [ null, null, null ] )\n    true\n    > bool = isNullArray( [ NaN, 2, null ] )\n    false\n\n    See Also\n    --------\n    isArray, isNull\n","isNumber":"\nisNumber( value )\n    Tests if a value is a number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number.\n\n    Examples\n    --------\n    > var bool = isNumber( 3.14 )\n    true\n    > bool = isNumber( new Number( 3.14 ) )\n    true\n    > bool = isNumber( NaN )\n    true\n    > bool = isNumber( null )\n    false\n\n\nisNumber.isPrimitive( value )\n    Tests if a value is a number primitive.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive.\n\n    Examples\n    --------\n    > var bool = isNumber.isPrimitive( 3.14 )\n    true\n    > bool = isNumber.isPrimitive( NaN )\n    true\n    > bool = isNumber.isPrimitive( new Number( 3.14 ) )\n    false\n\n\nisNumber.isObject( value )\n    Tests if a value is a `Number` object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a `Number` object.\n\n    Examples\n    --------\n    > var bool = isNumber.isObject( 3.14 )\n    false\n    > bool = isNumber.isObject( new Number( 3.14 ) )\n    true\n\n","isNumber.isPrimitive":"\nisNumber.isPrimitive( value )\n    Tests if a value is a number primitive.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive.\n\n    Examples\n    --------\n    > var bool = isNumber.isPrimitive( 3.14 )\n    true\n    > bool = isNumber.isPrimitive( NaN )\n    true\n    > bool = isNumber.isPrimitive( new Number( 3.14 ) )\n    false","isNumber.isObject":"\nisNumber.isObject( value )\n    Tests if a value is a `Number` object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a `Number` object.\n\n    Examples\n    --------\n    > var bool = isNumber.isObject( 3.14 )\n    false\n    > bool = isNumber.isObject( new Number( 3.14 ) )\n    true","isNumberArray":"\nisNumberArray( value )\n    Tests if a value is an array-like object containing only numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        numbers.\n\n    Examples\n    --------\n    > var bool = isNumberArray( [ 1, 2, 3 ] )\n    true\n    > bool = isNumberArray( [ '1', 2, 3 ] )\n    false\n\n\nisNumberArray.primitives( value )\n    Tests if a value is an array-like object containing only number primitives.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number primitives.\n\n    Examples\n    --------\n    > var arr = [ 1, 2, 3 ];\n    > var bool = isNumberArray.primitives( arr )\n    true\n    > arr = [ 1, new Number( 2 ) ];\n    > bool = isNumberArray.primitives( arr )\n    false\n\n\nisNumberArray.objects( value )\n    Tests if a value is an array-like object containing only `Number` objects.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        `Number` objects.\n\n    Examples\n    --------\n    > var arr = [ new Number( 1 ), new Number( 2 ) ];\n    > var bool = isNumberArray.objects( arr )\n    true\n    > arr = [ new Number( 1 ), 2 ];\n    > bool = isNumberArray.objects( arr )\n    false\n\n    See Also\n    --------\n    isArray, isNumber, isNumericArray\n","isNumberArray.primitives":"\nisNumberArray.primitives( value )\n    Tests if a value is an array-like object containing only number primitives.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number primitives.\n\n    Examples\n    --------\n    > var arr = [ 1, 2, 3 ];\n    > var bool = isNumberArray.primitives( arr )\n    true\n    > arr = [ 1, new Number( 2 ) ];\n    > bool = isNumberArray.primitives( arr )\n    false","isNumberArray.objects":"\nisNumberArray.objects( value )\n    Tests if a value is an array-like object containing only `Number` objects.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        `Number` objects.\n\n    Examples\n    --------\n    > var arr = [ new Number( 1 ), new Number( 2 ) ];\n    > var bool = isNumberArray.objects( arr )\n    true\n    > arr = [ new Number( 1 ), 2 ];\n    > bool = isNumberArray.objects( arr )\n    false\n\n    See Also\n    --------\n    isArray, isNumber, isNumericArray","isNumericArray":"\nisNumericArray( value )\n    Tests if a value is a numeric array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is a numeric array.\n\n    Examples\n    --------\n    > var bool = isNumericArray( new Int8Array( 10 ) )\n    true\n    > bool = isNumericArray( [ 1, 2, 3 ] )\n    true\n    > bool = isNumericArray( [ '1', '2', '3' ] )\n    false\n\n    See Also\n    --------\n    isArray, isNumberArray, isTypedArray\n\n","isObject":"\nisObject( value )\n    Tests if a value is an object; e.g., `{}`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an object.\n\n    Examples\n    --------\n    > var bool = isObject( {} )\n    true\n    > bool = isObject( true )\n    false\n\n    See Also\n    --------\n    isObjectLike, isPlainObject\n","isObjectArray":"\nisObjectArray( value )\n    Tests if a value is an array-like object containing only objects.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        objects.\n\n    Examples\n    --------\n    > var bool = isObjectArray( [ {}, new Number(3.0) ] )\n    true\n    > bool = isObjectArray( [ {}, { 'beep': 'boop' } ] )\n    true\n    > bool = isObjectArray( [ {}, '3.0' ] )\n    false\n\n    See Also\n    --------\n    isArray, isObject\n","isObjectLike":"\nisObjectLike( value )\n    Tests if a value is object-like.\n\n    Return values are the same as would be obtained using the built-in `typeof`\n    operator except that `null` is not considered an object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is object-like.\n\n    Examples\n    --------\n    > var bool = isObjectLike( {} )\n    true\n    > bool = isObjectLike( [] )\n    true\n    > bool = isObjectLike( null )\n    false\n\n    See Also\n    --------\n    isObject, isPlainObject\n","isOdd":"\nisOdd( value )\n    Tests if a value is an odd number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an odd number.\n\n    Examples\n    --------\n    > var bool = isOdd( 5.0 )\n    true\n    > bool = isOdd( new Number( 5.0 ) )\n    true\n    > bool = isOdd( 4.0 )\n    false\n    > bool = isOdd( new Number( 4.0 ) )\n    false\n    > bool = isOdd( -3.14 )\n    false\n    > bool = isOdd( null )\n    false\n\nisOdd.isPrimitive( value )\n    Tests if a value is a number primitive that is an odd number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive that is an odd\n        number.\n\n    Examples\n    --------\n    > var bool = isOdd.isPrimitive( -5.0 )\n    true\n    > bool = isOdd.isPrimitive( new Number( -5.0 ) )\n    false\n\n\nisOdd.isObject( value )\n    Tests if a value is a number object that has an odd number value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object that has an odd\n        number value.\n\n    Examples\n    --------\n    > var bool = isOdd.isObject( 5.0 )\n    false\n    > bool = isOdd.isObject( new Number( 5.0 ) )\n    true\n\n    See Also\n    --------\n    isEven\n","isOdd.isPrimitive":"\nisOdd.isPrimitive( value )\n    Tests if a value is a number primitive that is an odd number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive that is an odd\n        number.\n\n    Examples\n    --------\n    > var bool = isOdd.isPrimitive( -5.0 )\n    true\n    > bool = isOdd.isPrimitive( new Number( -5.0 ) )\n    false","isOdd.isObject":"\nisOdd.isObject( value )\n    Tests if a value is a number object that has an odd number value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object that has an odd\n        number value.\n\n    Examples\n    --------\n    > var bool = isOdd.isObject( 5.0 )\n    false\n    > bool = isOdd.isObject( new Number( 5.0 ) )\n    true\n\n    See Also\n    --------\n    isEven","isoWeeksInYear":"\nisoWeeksInYear( [year] )\n    Returns the number of ISO weeks in a year according to the Gregorian\n    calendar.\n\n    By default, the function returns the number of ISO weeks in the current year\n    (according to local time). To determine the number of ISO weeks for a\n    particular year, provide either a year or a `Date` object.\n\n    Parameters\n    ----------\n    year: integer (optional)\n        Year.\n\n    Returns\n    -------\n    out: integer\n        Number of ISO weeks in a year.\n\n    Examples\n    --------\n    > var num = isoWeeksInYear()\n    <number>\n    > num = isoWeeksInYear( 2015 )\n    53\n    > num = isoWeeksInYear( 2017 )\n    52\n\n","isPascalcase":"\nisPascalcase( value )\n    Tests if a value is a string in Pascal case.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a string in Pascal case.\n\n    Examples\n    --------\n    > var bool = isPascalcase( 'HelloWorld' )\n    true\n    > bool = isPascalcase( 'hello-world' )\n    false\n\n    See Also\n    --------\n    isString","isPersymmetricMatrix":"\nisPersymmetricMatrix( value )\n    Tests if a value is a square matrix which is symmetric about its\n    antidiagonal.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a persymmetric matrix.\n\n    Examples\n    --------\n    > var buf = [ 1, 2, 3, 1 ];\n    > var sh = [ 2, 2 ];\n    > var st = [ 2, 1 ];\n    > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n    > var bool = isPersymmetricMatrix( M )\n    true\n    > bool = isPersymmetricMatrix( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isPersymmetricMatrix( 3.14 )\n    false\n    > bool = isPersymmetricMatrix( {} )\n    false\n\n    See Also\n    --------\n    isMatrixLike, isSquareMatrix, isSymmetricMatrix\n","isPlainObject":"\nisPlainObject( value )\n    Tests if a value is a plain object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a plain object.\n\n    Examples\n    --------\n    > var bool = isPlainObject( {} )\n    true\n    > bool = isPlainObject( null )\n    false\n\n    See Also\n    --------\n    isObject\n","isPlainObjectArray":"\nisPlainObjectArray( value )\n    Tests if a value is an array-like object containing only plain objects.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        plain objects.\n\n    Examples\n    --------\n    > var bool = isPlainObjectArray( [ {}, { 'beep': 'boop' } ] )\n    true\n    > bool = isPlainObjectArray( [ {}, new Number(3.0) ] )\n    false\n    > bool = isPlainObjectArray( [ {}, '3.0' ] )\n    false\n\n    See Also\n    --------\n    isArray, isPlainObject\n","isPositiveFinite":"\nisPositiveFinite( value )\n    Tests if a value is a positive finite number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a positive finite number.\n\n    Examples\n    --------\n    > var bool = isPositiveFinite( 5.0 )\n    true\n    > bool = isPositiveFinite( new Number( 5.0 ) )\n    true\n    > bool = isPositiveFinite( 3.14 )\n    true\n    > bool = isPositiveFinite( -5.0 )\n    false\n    > var bool = isPositiveFinite( 1.0/0.0 )\n    false\n    > bool = isPositiveFinite( new Number( 1.0/0.0 ) )\n    false\n    > bool = isPositiveFinite( null )\n    false\n\n\nisPositiveFinite.isPrimitive( value )\n    Tests if a value is a number primitive having a positive finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is a number primitive having a positive\n        finite value.\n\n    Examples\n    --------\n    > var bool = isPositiveFinite.isPrimitive( 3.0 )\n    true\n    > var bool = isPositiveFinite.isPrimitive( 1.0/0.0 )\n    false\n    > bool = isPositiveFinite.isPrimitive( new Number( 3.0 ) )\n    false\n\n\nisPositiveFinite.isObject( value )\n    Tests if a value is a number object having a positive finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a positive\n        finite value.\n\n    Examples\n    --------\n    > var bool = isPositiveFinite.isObject( 3.0 )\n    false\n    > bool = isPositiveFinite.isObject( new Number( 3.0 ) )\n    true\n    > bool = isPositiveFinite.isObject( new Number( 1.0/0.0 ) )\n    false\n\n\n    See Also\n    --------\n    isFinite, isPositiveNumber\n","isPositiveFinite.isPrimitive":"\nisPositiveFinite.isPrimitive( value )\n    Tests if a value is a number primitive having a positive finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a value is a number primitive having a positive\n        finite value.\n\n    Examples\n    --------\n    > var bool = isPositiveFinite.isPrimitive( 3.0 )\n    true\n    > var bool = isPositiveFinite.isPrimitive( 1.0/0.0 )\n    false\n    > bool = isPositiveFinite.isPrimitive( new Number( 3.0 ) )\n    false","isPositiveFinite.isObject":"\nisPositiveFinite.isObject( value )\n    Tests if a value is a number object having a positive finite value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a positive\n        finite value.\n\n    Examples\n    --------\n    > var bool = isPositiveFinite.isObject( 3.0 )\n    false\n    > bool = isPositiveFinite.isObject( new Number( 3.0 ) )\n    true\n    > bool = isPositiveFinite.isObject( new Number( 1.0/0.0 ) )\n    false\n\n\n    See Also\n    --------\n    isFinite, isPositiveNumber","isPositiveInteger":"\nisPositiveInteger( value )\n    Tests if a value is a positive integer.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a positive integer.\n\n    Examples\n    --------\n    > var bool = isPositiveInteger( 5.0 )\n    true\n    > bool = isPositiveInteger( new Number( 5.0 ) )\n    true\n    > bool = isPositiveInteger( 3.14 )\n    false\n    > bool = isPositiveInteger( -5.0 )\n    false\n    > bool = isPositiveInteger( null )\n    false\n\n\nisPositiveInteger.isPrimitive( value )\n    Tests if a value is a number primitive having a positive integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        positive integer value.\n\n    Examples\n    --------\n    > var bool = isPositiveInteger.isPrimitive( 3.0 )\n    true\n    > bool = isPositiveInteger.isPrimitive( new Number( 3.0 ) )\n    false\n\n\nisPositiveInteger.isObject( value )\n    Tests if a value is a number object having a positive integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a positive\n        integer value.\n\n    Examples\n    --------\n    > var bool = isPositiveInteger.isObject( 3.0 )\n    false\n    > bool = isPositiveInteger.isObject( new Number( 3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger\n","isPositiveInteger.isPrimitive":"\nisPositiveInteger.isPrimitive( value )\n    Tests if a value is a number primitive having a positive integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a\n        positive integer value.\n\n    Examples\n    --------\n    > var bool = isPositiveInteger.isPrimitive( 3.0 )\n    true\n    > bool = isPositiveInteger.isPrimitive( new Number( 3.0 ) )\n    false","isPositiveInteger.isObject":"\nisPositiveInteger.isObject( value )\n    Tests if a value is a number object having a positive integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a positive\n        integer value.\n\n    Examples\n    --------\n    > var bool = isPositiveInteger.isObject( 3.0 )\n    false\n    > bool = isPositiveInteger.isObject( new Number( 3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger","isPositiveIntegerArray":"\nisPositiveIntegerArray( value )\n    Tests if a value is an array-like object containing only positive integers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        positive integers.\n\n    Examples\n    --------\n    > var bool = isPositiveIntegerArray( [ 3.0, new Number(3.0) ] )\n    true\n    > bool = isPositiveIntegerArray( [ 3.0, '3.0' ] )\n    false\n\n\nisPositiveIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only positive primitive\n    integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        positive primitive integer values.\n\n    Examples\n    --------\n    > var bool = isPositiveIntegerArray.primitives( [ 1.0, 10.0 ] )\n    true\n    > bool = isPositiveIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n    false\n    > bool = isPositiveIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n    false\n\n\nisPositiveIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having positive integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having positive integer values.\n\n    Examples\n    --------\n    > var bool = isPositiveIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n    true\n    > bool = isPositiveIntegerArray.objects( [ 1.0, 2.0, 10.0 ] )\n    false\n    > bool = isPositiveIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray, isInteger, isPositiveInteger\n","isPositiveIntegerArray.primitives":"\nisPositiveIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only positive primitive\n    integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        positive primitive integer values.\n\n    Examples\n    --------\n    > var bool = isPositiveIntegerArray.primitives( [ 1.0, 10.0 ] )\n    true\n    > bool = isPositiveIntegerArray.primitives( [ 1.0, 0.0, 10.0 ] )\n    false\n    > bool = isPositiveIntegerArray.primitives( [ 3.0, new Number(1.0) ] )\n    false","isPositiveIntegerArray.objects":"\nisPositiveIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having positive integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having positive integer values.\n\n    Examples\n    --------\n    > var bool = isPositiveIntegerArray.objects( [ new Number(1.0), new Number(10.0) ] )\n    true\n    > bool = isPositiveIntegerArray.objects( [ 1.0, 2.0, 10.0 ] )\n    false\n    > bool = isPositiveIntegerArray.objects( [ 3.0, new Number(1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray, isInteger, isPositiveInteger","isPositiveNumber":"\nisPositiveNumber( value )\n    Tests if a value is a positive number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a positive number.\n\n    Examples\n    --------\n    > var bool = isPositiveNumber( 5.0 )\n    true\n    > bool = isPositiveNumber( new Number( 5.0 ) )\n    true\n    > bool = isPositiveNumber( 3.14 )\n    true\n    > bool = isPositiveNumber( -5.0 )\n    false\n    > bool = isPositiveNumber( null )\n    false\n\n\nisPositiveNumber.isPrimitive( value )\n    Tests if a value is a number primitive having a positive value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a positive\n        value.\n\n    Examples\n    --------\n    > var bool = isPositiveNumber.isPrimitive( 3.0 )\n    true\n    > bool = isPositiveNumber.isPrimitive( new Number( 3.0 ) )\n    false\n\n\nisPositiveNumber.isObject( value )\n    Tests if a value is a number object having a positive value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a positive\n        value.\n\n    Examples\n    --------\n    > var bool = isPositiveNumber.isObject( 3.0 )\n    false\n    > bool = isPositiveNumber.isObject( new Number( 3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isNumber\n","isPositiveNumber.isPrimitive":"\nisPositiveNumber.isPrimitive( value )\n    Tests if a value is a number primitive having a positive value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a positive\n        value.\n\n    Examples\n    --------\n    > var bool = isPositiveNumber.isPrimitive( 3.0 )\n    true\n    > bool = isPositiveNumber.isPrimitive( new Number( 3.0 ) )\n    false","isPositiveNumber.isObject":"\nisPositiveNumber.isObject( value )\n    Tests if a value is a number object having a positive value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a positive\n        value.\n\n    Examples\n    --------\n    > var bool = isPositiveNumber.isObject( 3.0 )\n    false\n    > bool = isPositiveNumber.isObject( new Number( 3.0 ) )\n    true\n\n\n    See Also\n    --------\n    isNumber","isPositiveNumberArray":"\nisPositiveNumberArray( value )\n    Tests if a value is an array-like object containing only positive numbers.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        positive numbers.\n\n    Examples\n    --------\n    > var bool = isPositiveNumberArray( [ 3.0, new Number(3.0) ] )\n    true\n    > bool = isPositiveNumberArray( [ 3.0, '3.0' ] )\n    false\n\n\nisPositiveNumberArray.primitives( value )\n    Tests if a value is an array-like object containing only positive primitive\n    number values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        positive primitive number values.\n\n    Examples\n    --------\n    > var bool = isPositiveNumberArray.primitives( [ 1.0, 10.0 ] )\n    true\n    > bool = isPositiveNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n    false\n    > bool = isPositiveNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n    false\n\n\nisPositiveNumberArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having positive values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having positive values.\n\n    Examples\n    --------\n    > var bool = isPositiveNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n    true\n    > bool = isPositiveNumberArray.objects( [ 1.0, 2.0, 10.0 ] )\n    false\n    > bool = isPositiveNumberArray.objects( [ 3.0, new Number(1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray, isNumber, isPositiveNumber\n","isPositiveNumberArray.primitives":"\nisPositiveNumberArray.primitives( value )\n    Tests if a value is an array-like object containing only positive primitive\n    number values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        positive primitive number values.\n\n    Examples\n    --------\n    > var bool = isPositiveNumberArray.primitives( [ 1.0, 10.0 ] )\n    true\n    > bool = isPositiveNumberArray.primitives( [ 1.0, 0.0, 10.0 ] )\n    false\n    > bool = isPositiveNumberArray.primitives( [ 3.0, new Number(1.0) ] )\n    false","isPositiveNumberArray.objects":"\nisPositiveNumberArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having positive values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having positive values.\n\n    Examples\n    --------\n    > var bool = isPositiveNumberArray.objects( [ new Number(1.0), new Number(10.0) ] )\n    true\n    > bool = isPositiveNumberArray.objects( [ 1.0, 2.0, 10.0 ] )\n    false\n    > bool = isPositiveNumberArray.objects( [ 3.0, new Number(1.0) ] )\n    false\n\n    See Also\n    --------\n    isArray, isNumber, isPositiveNumber","isPositiveZero":"\nisPositiveZero( value )\n    Tests if a value is positive zero.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is positive zero.\n\n    Examples\n    --------\n    > var bool = isPositiveZero( 0.0 )\n    true\n    > bool = isPositiveZero( new Number( 0.0 ) )\n    true\n    > bool = isPositiveZero( -3.14 )\n    false\n    > bool = isPositiveZero( -0.0 )\n    false\n    > bool = isPositiveZero( null )\n    false\n\n\nisPositiveZero.isPrimitive( value )\n    Tests if a value is a number primitive equal to positive zero.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number primitive equal to\n        positive zero.\n\n    Examples\n    --------\n    > var bool = isPositiveZero.isPrimitive( 0.0 )\n    true\n    > bool = isPositiveZero.isPrimitive( new Number( 0.0 ) )\n    false\n\n\nisPositiveZero.isObject( value )\n    Tests if a value is a number object having a value equal to positive zero.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number object having a value\n        equal to positive zero.\n\n    Examples\n    --------\n    > var bool = isPositiveZero.isObject( 0.0 )\n    false\n    > bool = isPositiveZero.isObject( new Number( 0.0 ) )\n    true\n\n    See Also\n    --------\n    isNumber, isNegativeZero\n","isPositiveZero.isPrimitive":"\nisPositiveZero.isPrimitive( value )\n    Tests if a value is a number primitive equal to positive zero.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number primitive equal to\n        positive zero.\n\n    Examples\n    --------\n    > var bool = isPositiveZero.isPrimitive( 0.0 )\n    true\n    > bool = isPositiveZero.isPrimitive( new Number( 0.0 ) )\n    false","isPositiveZero.isObject":"\nisPositiveZero.isObject( value )\n    Tests if a value is a number object having a value equal to positive zero.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a number object having a value\n        equal to positive zero.\n\n    Examples\n    --------\n    > var bool = isPositiveZero.isObject( 0.0 )\n    false\n    > bool = isPositiveZero.isObject( new Number( 0.0 ) )\n    true\n\n    See Also\n    --------\n    isNumber, isNegativeZero","isPrime":"\nisPrime( value )\n    Tests if a value is a prime number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a prime number.\n\n    Examples\n    --------\n    > var bool = isPrime( 5.0 )\n    true\n    > bool = isPrime( new Number( 5.0 ) )\n    true\n    > bool = isPrime( 3.14 )\n    false\n    > bool = isPrime( -5.0 )\n    false\n    > bool = isPrime( null )\n    false\n\n\nisPrime.isPrimitive( value )\n    Tests if a value is a number primitive which is a prime number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a prime\n        number.\n\n    Examples\n    --------\n    > var bool = isPrime.isPrimitive( 5.0 )\n    true\n    > bool = isPrime.isPrimitive( new Number( 5.0 ) )\n    false\n\n\nisPrime.isObject( value )\n    Tests if a value is a number object having a value which is a prime number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a prime number.\n\n    Examples\n    --------\n    > var bool = isPrime.isObject( 5.0 )\n    false\n    > bool = isPrime.isObject( new Number( 5.0 ) )\n    true\n\n\n    See Also\n    --------\n    isComposite, isInteger, isNumber\n","isPrime.isPrimitive":"\nisPrime.isPrimitive( value )\n    Tests if a value is a number primitive which is a prime number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a prime\n        number.\n\n    Examples\n    --------\n    > var bool = isPrime.isPrimitive( 5.0 )\n    true\n    > bool = isPrime.isPrimitive( new Number( 5.0 ) )\n    false","isPrime.isObject":"\nisPrime.isObject( value )\n    Tests if a value is a number object having a value which is a prime number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a prime number.\n\n    Examples\n    --------\n    > var bool = isPrime.isObject( 5.0 )\n    false\n    > bool = isPrime.isObject( new Number( 5.0 ) )\n    true\n\n\n    See Also\n    --------\n    isComposite, isInteger, isNumber","isPrimitive":"\nisPrimitive( value )\n    Tests if a value is a JavaScript primitive.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a JavaScript primitive.\n\n    Examples\n    --------\n    > var bool = isPrimitive( true )\n    true\n    > bool = isPrimitive( {} )\n    false\n\n    See Also\n    --------\n    isBoxedPrimitive\n","isPrimitiveArray":"\nisPrimitiveArray( value )\n    Tests if a value is an array-like object containing only JavaScript\n    primitives.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        JavaScript primitives.\n\n    Examples\n    --------\n    > var bool = isPrimitiveArray( [ '3', 2, null ] )\n    true\n    > bool = isPrimitiveArray( [ {}, 2, 1 ] )\n    false\n    > bool = isPrimitiveArray( [ new String('abc'), '3.0' ] )\n    false\n\n    See Also\n    --------\n    isArray, isPrimitive\n","isPRNGLike":"\nisPRNGLike( value )\n    Tests if a value is PRNG-like.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is PRNG-like.\n\n    Examples\n    --------\n    > var bool = isPRNGLike( base.random.randu )\n    true\n    > bool = isPRNGLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isPRNGLike( 3.14 )\n    false\n    > bool = isPRNGLike( {} )\n    false\n\n","isProbability":"\nisProbability( value )\n    Tests if a value is a probability.\n\n    A probability is defined as a numeric value on the interval [0,1].\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a probability.\n\n    Examples\n    --------\n    > var bool = isProbability( 0.5 )\n    true\n    > bool = isProbability( new Number( 0.5 ) )\n    true\n    > bool = isProbability( 3.14 )\n    false\n    > bool = isProbability( -5.0 )\n    false\n    > bool = isProbability( null )\n    false\n\n\nisProbability.isPrimitive( value )\n    Tests if a value is a number primitive which is a probability.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a\n        probability.\n\n    Examples\n    --------\n    > var bool = isProbability.isPrimitive( 0.3 )\n    true\n    > bool = isProbability.isPrimitive( new Number( 0.3 ) )\n    false\n\n\nisProbability.isObject( value )\n    Tests if a value is a number object having a value which is a probability.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a probability.\n\n    Examples\n    --------\n    > var bool = isProbability.isObject( 0.77 )\n    false\n    > bool = isProbability.isObject( new Number( 0.77 ) )\n    true\n\n\n    See Also\n    --------\n    isNumber\n","isProbability.isPrimitive":"\nisProbability.isPrimitive( value )\n    Tests if a value is a number primitive which is a probability.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a\n        probability.\n\n    Examples\n    --------\n    > var bool = isProbability.isPrimitive( 0.3 )\n    true\n    > bool = isProbability.isPrimitive( new Number( 0.3 ) )\n    false","isProbability.isObject":"\nisProbability.isObject( value )\n    Tests if a value is a number object having a value which is a probability.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a probability.\n\n    Examples\n    --------\n    > var bool = isProbability.isObject( 0.77 )\n    false\n    > bool = isProbability.isObject( new Number( 0.77 ) )\n    true\n\n\n    See Also\n    --------\n    isNumber","isProbabilityArray":"\nisProbabilityArray( value )\n    Tests if a value is an array-like object containing only probabilities.\n\n    A probability is defined as a numeric value on the interval [0,1].\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        probabilities.\n\n    Examples\n    --------\n    > var bool = isProbabilityArray( [ 0.5, new Number(0.8) ] )\n    true\n    > bool = isProbabilityArray( [ 0.8, 1.2 ] )\n    false\n    > bool = isProbabilityArray( [ 0.8, '0.2' ] )\n    false\n\n\nisProbabilityArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive\n    probabilities.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive probabilities.\n\n    Examples\n    --------\n    > var bool = isProbabilityArray.primitives( [ 1.0, 0.0, 0.5 ] )\n    true\n    > bool = isProbabilityArray.primitives( [ 0.3, new Number(0.4) ] )\n    false\n\n\nisProbabilityArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having probability values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having probability values.\n\n    Examples\n    --------\n    > var bool = isProbabilityArray.objects( [ new Number(0.7), new Number(1.0) ] )\n    true\n    > bool = isProbabilityArray.objects( [ 1.0, 0.0, new Number(0.7) ] )\n    false\n\n    See Also\n    --------\n    isArray, isProbability\n","isProbabilityArray.primitives":"\nisProbabilityArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive\n    probabilities.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive probabilities.\n\n    Examples\n    --------\n    > var bool = isProbabilityArray.primitives( [ 1.0, 0.0, 0.5 ] )\n    true\n    > bool = isProbabilityArray.primitives( [ 0.3, new Number(0.4) ] )\n    false","isProbabilityArray.objects":"\nisProbabilityArray.objects( value )\n    Tests if a value is an array-like object containing only number objects\n    having probability values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        number objects having probability values.\n\n    Examples\n    --------\n    > var bool = isProbabilityArray.objects( [ new Number(0.7), new Number(1.0) ] )\n    true\n    > bool = isProbabilityArray.objects( [ 1.0, 0.0, new Number(0.7) ] )\n    false\n\n    See Also\n    --------\n    isArray, isProbability","isPropertyKey":"\nisPropertyKey( value )\n    Tests whether a value is a property key.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether value is a property key.\n\n    Examples\n    --------\n    > var out = isPropertyKey( 'foo' )\n    true\n    > out = isPropertyKey( 1 )\n    true\n    > out = isPropertyKey( true )\n    false\n\n    See Also\n    --------\n    isString, isSymbol, isNonNegativeInteger, hasOwnProp, hasProp","isPrototypeOf":"\nisPrototypeOf( value, proto )\n    Tests if an object's prototype chain contains a provided prototype.\n\n    The function returns `false` if provided a primitive value.\n\n    This function is generally more robust than the `instanceof` operator (e.g.,\n    where inheritance is performed without using constructors).\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    proto: Object|Function\n        Prototype.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if a provided prototype exists in a prototype chain.\n\n    Examples\n    --------\n    > function Foo() { return this; };\n    > function Bar() { return this; };\n    > inherit( Bar, Foo );\n    > var bar = new Bar();\n    > var bool = isPrototypeOf( bar, Foo.prototype )\n    true\n\n    See Also\n    --------\n    getPrototypeOf\n","isRaggedNestedArray":"\nisRaggedNestedArray( value )\n    Tests if a value is a ragged nested array. \n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a ragged nested array.\n\n    Examples\n    --------\n    > var bool = isRaggedNestedArray( [ [ 1, 2, 3 ], [ 4, 5 ] ] )\n    true\n    > bool = isRaggedNestedArray( [ [ 1, 2, 3 ], [ 4, 5, 6 ] ] )\n    false\n    > bool = isRaggedNestedArray( 'beep' )\n    false\n\n","isRangeError":"\nisRangeError( value )\n    Tests if a value is a RangeError object.\n\n    This function should *not* be considered robust. While the function should\n    always return `true` if provided a RangeError (or a descendant) object,\n    false positives may occur due to the fact that the RangeError constructor\n    inherits from Error and has no internal class of its own. Hence, RangeError\n    impersonation is possible.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a RangeError object.\n\n    Examples\n    --------\n    > var bool = isRangeError( new RangeError( 'beep' ) )\n    true\n    > bool = isRangeError( {} )\n    false\n\n    See Also\n    --------\n    isError\n","isReadableProperty":"\nisReadableProperty( value, property )\n    Tests if an object's own property is readable.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own property is readable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.set = function setter( v ) { obj.boop = v; };\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isReadableProperty( obj, 'boop' )\n    true\n    > bool = isReadableProperty( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    isReadOnlyProperty, isReadWriteProperty, isReadablePropertyIn, isWritableProperty\n","isReadablePropertyIn":"\nisReadablePropertyIn( value, property )\n    Tests if an object's own or inherited property is readable.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own or inherited property is readable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.set = function setter( v ) { obj.boop = v; };\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isReadablePropertyIn( obj, 'boop' )\n    true\n    > bool = isReadablePropertyIn( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    isReadOnlyPropertyIn, isReadWritePropertyIn, isReadableProperty, isWritablePropertyIn\n","isReadOnlyProperty":"\nisReadOnlyProperty( value, property )\n    Tests if an object's own property is read-only.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own property is read-only.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = true;\n    > desc.writable = false;\n    > desc.value = true;\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isReadOnlyProperty( obj, 'boop' )\n    true\n    > bool = isReadOnlyProperty( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    isReadOnlyPropertyIn, isReadWriteProperty, isReadableProperty, isWritableProperty\n","isReadOnlyPropertyIn":"\nisReadOnlyPropertyIn( value, property )\n    Tests if an object's own or inherited property is read-only.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own or inherited property is read-\n        only.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = true;\n    > desc.writable = false;\n    > desc.value = true;\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isReadOnlyPropertyIn( obj, 'boop' )\n    true\n    > bool = isReadOnlyPropertyIn( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    isReadOnlyProperty, isReadWritePropertyIn, isReadablePropertyIn, isWritablePropertyIn\n","isReadWriteProperty":"\nisReadWriteProperty( value, property )\n    Tests if an object's own property is readable and writable.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own property is readable and writable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.set = function setter( v ) { obj.boop = v; };\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isReadWriteProperty( obj, 'boop' )\n    true\n    > bool = isReadWriteProperty( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    isReadOnlyProperty, isReadWritePropertyIn, isReadableProperty, isWritableProperty\n","isReadWritePropertyIn":"\nisReadWritePropertyIn( value, property )\n    Tests if an object's own or inherited property is readable and writable.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own or inherited property is readable\n        and writable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.set = function setter( v ) { obj.boop = v; };\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isReadWritePropertyIn( obj, 'boop' )\n    true\n    > bool = isReadWritePropertyIn( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    isReadOnlyPropertyIn, isReadWriteProperty, isReadablePropertyIn, isWritablePropertyIn\n","isReferenceError":"\nisReferenceError( value )\n    Tests if a value is a ReferenceError object.\n\n    This function should *not* be considered robust. While the function should\n    always return `true` if provided a ReferenceError (or a descendant)\n    object, false positives may occur due to the fact that the ReferenceError\n    constructor inherits from Error and has no internal class of its own.\n    Hence, ReferenceError impersonation is possible.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a ReferenceError object.\n\n    Examples\n    --------\n    > var bool = isReferenceError( new ReferenceError( 'beep' ) )\n    true\n    > bool = isReferenceError( {} )\n    false\n\n    See Also\n    --------\n    isError\n","isRegExp":"\nisRegExp( value )\n    Tests if a value is a regular expression.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a regular expression.\n\n    Examples\n    --------\n    > var bool = isRegExp( /\\.+/ )\n    true\n    > bool = isRegExp( {} )\n    false\n\n","isRegExpString":"\nisRegExpString( value )\n    Tests if a value is a regular expression string.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a regular expression string.\n\n    Examples\n    --------\n    > var bool = isRegExpString( '/beep/' )\n    true\n    > bool = isRegExpString( 'beep' )\n    false\n    > bool = isRegExpString( '' )\n    false\n    > bool = isRegExpString( null )\n    false\n\n    See Also\n    --------\n    isRegExp\n","isRelativePath":"\nisRelativePath( value )\n    Tests if a value is a relative path.\n\n    Function behavior is platform-specific. On Windows platforms, the function\n    is equal to `.win32()`. On POSIX platforms, the function is equal to\n    `.posix()`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a relative path.\n\n    Examples\n    --------\n    // Windows environments:\n    > var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\n    true\n\n    // POSIX environments:\n    > bool = isRelativePath( './foo/bar/baz' )\n    true\n\n\nisRelativePath.posix( value )\n    Tests if a value is a POSIX relative path.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a POSIX relative path.\n\n    Examples\n    --------\n    > var bool = isRelativePath.posix( './foo/bar/baz' )\n    true\n    > bool = isRelativePath.posix( '/foo/../bar/baz' )\n    false\n\n\nisRelativePath.win32( value )\n    Tests if a value is a Windows relative path.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Windows relative path.\n\n    Examples\n    --------\n    > var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\n    true\n    > bool = isRelativePath( 'C:\\\\foo\\\\..\\\\bar\\\\baz' )\n    false\n\n    See Also\n    --------\n    isAbsolutePath\n","isRelativePath.posix":"\nisRelativePath.posix( value )\n    Tests if a value is a POSIX relative path.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a POSIX relative path.\n\n    Examples\n    --------\n    > var bool = isRelativePath.posix( './foo/bar/baz' )\n    true\n    > bool = isRelativePath.posix( '/foo/../bar/baz' )\n    false","isRelativePath.win32":"\nisRelativePath.win32( value )\n    Tests if a value is a Windows relative path.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Windows relative path.\n\n    Examples\n    --------\n    > var bool = isRelativePath( 'foo\\\\bar\\\\baz' )\n    true\n    > bool = isRelativePath( 'C:\\\\foo\\\\..\\\\bar\\\\baz' )\n    false\n\n    See Also\n    --------\n    isAbsolutePath","isRelativeURI":"\nisRelativeURI( value )\n    Tests whether a value is a relative URI.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether a value is a relative URI.\n\n    Examples\n    --------\n    > var bool = isRelativeURI( '/images/example.png' )\n    true\n    > bool = isRelativeURI( 'http://www.example.com' )\n    false\n    > bool = isRelativeURI( null )\n    false\n\n    See Also\n    --------\n    isURI","isSafeInteger":"\nisSafeInteger( value )\n    Tests if a value is a safe integer.\n\n    An integer valued number is \"safe\" when the number can be exactly\n    represented as a double-precision floating-point number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a safe integer.\n\n    Examples\n    --------\n    > var bool = isSafeInteger( 5.0 )\n    true\n    > bool = isSafeInteger( new Number( 5.0 ) )\n    true\n    > bool = isSafeInteger( 2.0e200 )\n    false\n    > bool = isSafeInteger( -3.14 )\n    false\n    > bool = isSafeInteger( null )\n    false\n\n\nisSafeInteger.isPrimitive( value )\n    Tests if a value is a number primitive having a safe integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a safe\n        integer value.\n\n    Examples\n    --------\n    > var bool = isSafeInteger.isPrimitive( -3.0 )\n    true\n    > bool = isSafeInteger.isPrimitive( new Number( -3.0 ) )\n    false\n\n\nisSafeInteger.isObject( value )\n    Tests if a value is a `Number` object having a safe integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a `Number` object having a safe\n        integer value.\n\n    Examples\n    --------\n    > var bool = isSafeInteger.isObject( 3.0 )\n    false\n    > bool = isSafeInteger.isObject( new Number( 3.0 ) )\n    true\n\n    See Also\n    --------\n    isInteger, isNumber\n","isSafeInteger.isPrimitive":"\nisSafeInteger.isPrimitive( value )\n    Tests if a value is a number primitive having a safe integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive having a safe\n        integer value.\n\n    Examples\n    --------\n    > var bool = isSafeInteger.isPrimitive( -3.0 )\n    true\n    > bool = isSafeInteger.isPrimitive( new Number( -3.0 ) )\n    false","isSafeInteger.isObject":"\nisSafeInteger.isObject( value )\n    Tests if a value is a `Number` object having a safe integer value.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a `Number` object having a safe\n        integer value.\n\n    Examples\n    --------\n    > var bool = isSafeInteger.isObject( 3.0 )\n    false\n    > bool = isSafeInteger.isObject( new Number( 3.0 ) )\n    true\n\n    See Also\n    --------\n    isInteger, isNumber","isSafeIntegerArray":"\nisSafeIntegerArray( value )\n    Tests if a value is an array-like object containing only safe integers.\n\n    An integer valued number is \"safe\" when the number can be exactly\n    represented as a double-precision floating-point number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing\n        only safe integers.\n\n    Examples\n    --------\n    > var arr = [ -3.0, new Number(0.0), 2.0 ];\n    > var bool = isSafeIntegerArray( arr )\n    true\n    > arr = [ -3.0, '3.0' ];\n    > bool = isSafeIntegerArray( arr )\n    false\n\n\nisSafeIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive safe\n    integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive safe integer values.\n\n    Examples\n    --------\n    > var arr = [ -1.0, 10.0 ];\n    > var bool = isSafeIntegerArray.primitives( arr )\n    true\n    > arr = [ -1.0, 0.0, 5.0 ];\n    > bool = isSafeIntegerArray.primitives( arr )\n    true\n    > arr = [ -3.0, new Number(-1.0) ];\n    > bool = isSafeIntegerArray.primitives( arr )\n    false\n\n\nisSafeIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only `Number` objects\n    having safe integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        `Number` objects having safe integer values.\n\n    Examples\n    --------\n    > var arr = [ new Number(1.0), new Number(3.0) ];\n    > var bool = isSafeIntegerArray.objects( arr )\n    true\n    > arr = [ -1.0, 0.0, 3.0 ];\n    > bool = isSafeIntegerArray.objects( arr )\n    false\n    > arr = [ 3.0, new Number(-1.0) ];\n    > bool = isSafeIntegerArray.objects( arr )\n    false\n\n    See Also\n    --------\n    isArray, isSafeInteger\n","isSafeIntegerArray.primitives":"\nisSafeIntegerArray.primitives( value )\n    Tests if a value is an array-like object containing only primitive safe\n    integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        primitive safe integer values.\n\n    Examples\n    --------\n    > var arr = [ -1.0, 10.0 ];\n    > var bool = isSafeIntegerArray.primitives( arr )\n    true\n    > arr = [ -1.0, 0.0, 5.0 ];\n    > bool = isSafeIntegerArray.primitives( arr )\n    true\n    > arr = [ -3.0, new Number(-1.0) ];\n    > bool = isSafeIntegerArray.primitives( arr )\n    false","isSafeIntegerArray.objects":"\nisSafeIntegerArray.objects( value )\n    Tests if a value is an array-like object containing only `Number` objects\n    having safe integer values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array-like object containing only\n        `Number` objects having safe integer values.\n\n    Examples\n    --------\n    > var arr = [ new Number(1.0), new Number(3.0) ];\n    > var bool = isSafeIntegerArray.objects( arr )\n    true\n    > arr = [ -1.0, 0.0, 3.0 ];\n    > bool = isSafeIntegerArray.objects( arr )\n    false\n    > arr = [ 3.0, new Number(-1.0) ];\n    > bool = isSafeIntegerArray.objects( arr )\n    false\n\n    See Also\n    --------\n    isArray, isSafeInteger","isSameArray":"\nisSameArray( v1, v2 )\n    Tests if two arguments are both generic arrays and have the same values.\n\n    The function differs from the `===` operator in that the function treats\n    `-0` and `+0` as distinct and `NaNs` as the same.\n\n    Parameters\n    ----------\n    v1: any\n        First input value.\n\n    v2: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are the same.\n\n    Examples\n    --------\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > var y = [ 1.0, 2.0, 3.0 ];\n    > var bool = isSameArray( x, y )\n    true\n\n    > x = [ NaN, NaN, NaN ];\n    > y = [ NaN, NaN, NaN ];\n    > bool = isSameArray( x, y )\n    true\n\n    See Also\n    --------\n    isArray, isEqualArray, isSameArrayLike, isSameValue\n","isSameArrayLike":"\nisSameArrayLike( v1, v2 )\n    Tests if two arguments are both array-like and have the same values.\n\n    The function differs from the `===` operator in that the function treats\n    `-0` and `+0` as distinct and `NaNs` as the same.\n\n    Parameters\n    ----------\n    v1: any\n        First input value.\n\n    v2: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are the same.\n\n    Examples\n    --------\n    > var x = [ 1.0, 2.0, 3.0 ];\n    > var y = [ 1.0, 2.0, 3.0 ];\n    > var bool = isSameArrayLike( x, y )\n    true\n\n    > x = [ NaN, NaN, NaN ];\n    > y = [ NaN, NaN, NaN ];\n    > bool = isSameArrayLike( x, y )\n    true\n\n    See Also\n    --------\n    isArrayLike, isSameArray, isSameValue\n","isSameComplex64":"\nisSameComplex64( v1, v2 )\n    Tests if two arguments are both single-precision complex floating-point\n    numbers and have the same value.\n\n    The function differs from the `===` operator in that the function treats\n    `-0` and `+0` as distinct and `NaNs` as the same.\n\n    Parameters\n    ----------\n    v1: any\n        First input value.\n\n    v2: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are the same.\n\n    Examples\n    --------\n    > var x = new Complex64( 1.0, 2.0 );\n    > var y = new Complex64( 1.0, 2.0 );\n    > var bool = isSameComplex64( x, y )\n    true\n\n    > x = new Complex64( NaN, NaN );\n    > y = new Complex64( NaN, NaN );\n    > bool = isSameComplex64( x, y )\n    true\n\n    See Also\n    --------\n    isComplex64, isSameComplex128, isSameValue\n","isSameComplex64Array":"\nisSameComplex64Array( v1, v2 )\n    Tests if two arguments are both Complex64Arrays and have the same values.\n\n    The function differs from the `===` operator in that the function treats\n    `-0` and `+0` as distinct and `NaNs` as the same.\n\n    Parameters\n    ----------\n    v1: any\n        First input value.\n\n    v2: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are the same.\n\n    Examples\n    --------\n    > var x = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var bool = isSameComplex64Array( x, y )\n    true\n\n    > x = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\n    > y = new Complex64Array( [ NaN, NaN, NaN, NaN ] );\n    > bool = isSameComplex64Array( x, y )\n    true\n\n    See Also\n    --------\n    isComplex64Array, isSameComplex128Array, isSameFloat32Array, isSameValue\n","isSameComplex128":"\nisSameComplex128( v1, v2 )\n    Tests if two arguments are both double-precision complex floating-point\n    numbers and have the same value.\n\n    The function differs from the `===` operator in that the function treats\n    `-0` and `+0` as distinct and `NaNs` as the same.\n\n    Parameters\n    ----------\n    v1: any\n        First input value.\n\n    v2: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are the same.\n\n    Examples\n    --------\n    > var x = new Complex128( 1.0, 2.0 );\n    > var y = new Complex128( 1.0, 2.0 );\n    > var bool = isSameComplex128( x, y )\n    true\n\n    > x = new Complex128( NaN, NaN );\n    > y = new Complex128( NaN, NaN );\n    > bool = isSameComplex128( x, y )\n    true\n\n    See Also\n    --------\n    isComplex128, isSameComplex64, isSameValue\n","isSameComplex128Array":"\nisSameComplex128Array( v1, v2 )\n    Tests if two arguments are both Complex128Arrays and have the same values.\n\n    The function differs from the `===` operator in that the function treats\n    `-0` and `+0` as distinct and `NaNs` as the same.\n\n    Parameters\n    ----------\n    v1: any\n        First input value.\n\n    v2: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are the same.\n\n    Examples\n    --------\n    > var x = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var bool = isSameComplex128Array( x, y )\n    true\n\n    > x = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\n    > y = new Complex128Array( [ NaN, NaN, NaN, NaN ] );\n    > bool = isSameComplex128Array( x, y )\n    true\n\n    See Also\n    --------\n    isComplex128Array, isSameComplex64Array, isSameFloat64Array, isSameValue\n","isSameDateObject":"\nisSameDateObject( d1, d2 )\n    Tests if two values are both Date objects corresponding \n    to the same date and time.\n\n    Parameters\n    ----------\n    d1: any\n        First input value.\n    d2: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether both values are Date objects \n        corresponding to the same date and time.\n\n    Examples\n    --------\n    > var d1 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\n    > var d2 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\n    > var bool = isSameDateObject( d1, d2 )\n    true\n    > var d1 = new Date( 2024, 11, 31, 23, 59, 59, 999 );\n    > var d2 = new Date( 2024, 11, 31, 23, 59, 59, 78 );\n    > var bool = isSameDateObject( d1, d2 )\n    false\n \n    See Also\n    --------\n    isDateObject, isSameValue\n","isSameFloat32Array":"\nisSameFloat32Array( v1, v2 )\n    Tests if two arguments are both Float32Arrays and have the same values.\n\n    The function differs from the `===` operator in that the function treats\n    `-0` and `+0` as distinct and `NaNs` as the same.\n\n    Parameters\n    ----------\n    v1: any\n        First input value.\n\n    v2: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are the same.\n\n    Examples\n    --------\n    > var x = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > var y = new Float32Array( [ 1.0, 2.0, 3.0 ] );\n    > var bool = isSameFloat32Array( x, y )\n    true\n\n    > x = new Float32Array( [ NaN, NaN, NaN ] );\n    > y = new Float32Array( [ NaN, NaN, NaN ] );\n    > bool = isSameFloat32Array( x, y )\n    true\n\n    See Also\n    --------\n    isSameFloat64Array, isSameValue\n","isSameFloat64Array":"\nisSameFloat64Array( v1, v2 )\n    Tests if two arguments are both Float64Arrays and have the same values.\n\n    The function differs from the `===` operator in that the function treats\n    `-0` and `+0` as distinct and `NaNs` as the same.\n\n    Parameters\n    ----------\n    v1: any\n        First input value.\n\n    v2: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are the same.\n\n    Examples\n    --------\n    > var x = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0 ] );\n    > var bool = isSameFloat64Array( x, y )\n    true\n\n    > x = new Float64Array( [ NaN, NaN, NaN ] );\n    > y = new Float64Array( [ NaN, NaN, NaN ] );\n    > bool = isSameFloat64Array( x, y )\n    true\n\n    See Also\n    --------\n    isSameFloat32Array, isSameValue\n","isSameNativeClass":"\nisSameNativeClass( a, b )\n    Tests if two arguments have the same native class.\n\n    Parameters\n    ----------\n    a: any\n        First input value.\n\n    b: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments have the same native class.\n\n    Examples\n    --------\n    > var bool = isSameNativeClass( 3.14, new Number( 3.14 ) )\n    true\n    > bool = isSameNativeClass( 'beep', 'boop' )\n    true\n    > bool = isSameNativeClass( {}, [] )\n    false\n\n    See Also\n    --------\n    isSameType, isSameValue, isStrictEqual\n","isSameType":"\nisSameType( a, b )\n    Tests if two arguments have the same type.\n\n    The function uses the `typeof` operator to test for the same type.\n\n    Parameters\n    ----------\n    a: any\n        First input value.\n\n    b: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments have the same type.\n\n    Examples\n    --------\n    > var bool = isSameType( true, true )\n    true\n    > bool = isSameType( {}, [] )\n    true\n    > bool = isSameType( 3.12, -3.12 )\n    true\n    > bool = isSameType( 0.0, '0.0' )\n    false\n\n    See Also\n    --------\n    isSameNativeClass, isSameValue, isStrictEqual\n","isSameValue":"\nisSameValue( a, b )\n    Tests if two arguments are the same value.\n\n    The function differs from the `===` operator in that the function treats\n    `-0` and `+0` as distinct and `NaNs` as the same.\n\n    Parameters\n    ----------\n    a: any\n        First input value.\n\n    b: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are the same value.\n\n    Examples\n    --------\n    > var bool = isSameValue( true, true )\n    true\n    > bool = isSameValue( {}, {} )\n    false\n    > bool = isSameValue( -0.0, -0.0 )\n    true\n    > bool = isSameValue( -0.0, 0.0 )\n    false\n    > bool = isSameValue( NaN, NaN )\n    true\n\n    See Also\n    --------\n    isSameValueZero, isStrictEqual\n","isSameValueZero":"\nisSameValueZero( a, b )\n    Tests if two arguments are the same value.\n\n    The function differs from the `===` operator in that the function treats\n    `NaNs` as the same.\n\n    Parameters\n    ----------\n    a: any\n        First input value.\n\n    b: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are the same value.\n\n    Examples\n    --------\n    > var bool = isSameValueZero( true, true )\n    true\n    > bool = isSameValueZero( {}, {} )\n    false\n    > bool = isSameValueZero( -0.0, -0.0 )\n    true\n    > bool = isSameValueZero( -0.0, 0.0 )\n    true\n    > bool = isSameValueZero( NaN, NaN )\n    true\n\n    See Also\n    --------\n    isSameValue, isStrictEqual\n","isSemVer":"\nisSemVer( value )\n    Tests if a value is a semantic version string.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether a provided value is a semantic version\n        string.\n\n    Examples\n    --------\n    > var bool = isSemVer( '1.0.0' )\n    true\n    > bool = isSemVer( '1.0.0-alpha.1' )\n    true\n    > bool = isSemVer( '0.1' )\n    false\n    > bool = isSemVer( null )\n    false\n","isSharedArrayBuffer":"\nisSharedArrayBuffer( value )\n    Tests if a value is a SharedArrayBuffer.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a SharedArrayBuffer.\n\n    Examples\n    --------\n    // Assuming an environment supports SharedArrayBuffer...\n    > var bool = isSharedArrayBuffer( new SharedArrayBuffer( 10 ) )\n    true\n    > bool = isSharedArrayBuffer( [] )\n    false\n\n    See Also\n    --------\n    isArrayBuffer, isTypedArray\n","isSkewCentrosymmetricMatrix":"\nisSkewCentrosymmetricMatrix( value )\n    Tests if a value is a skew-centrosymmetric matrix.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a skew-centrosymmetric matrix.\n\n    Examples\n    --------\n    > var buf = [ 2, 1, -1, -2 ];\n    > var sh = [ 2, 2 ];\n    > var st = [ 2, 1 ];\n    > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n    > var bool = isSkewCentrosymmetricMatrix( M )\n    true\n    > bool = isSkewCentrosymmetricMatrix( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isSkewCentrosymmetricMatrix( 3.14 )\n    false\n    > bool = isSkewCentrosymmetricMatrix( {} )\n    false\n\n    See Also\n    --------\n    isCentrosymmetricMatrix, isMatrixLike, isSkewSymmetricMatrix\n","isSkewPersymmetricMatrix":"\nisSkewPersymmetricMatrix( value )\n    Tests if a value is a skew-persymmetric matrix.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a skew-persymmetric matrix.\n\n    Examples\n    --------\n    > var buf = [ 1, 0, 0, -1 ];\n    > var sh = [ 2, 2 ];\n    > var st = [ 2, 1 ];\n    > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n    > var bool = isSkewPersymmetricMatrix( M )\n    true\n    > bool = isSkewPersymmetricMatrix( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isSkewPersymmetricMatrix( 3.14 )\n    false\n    > bool = isSkewPersymmetricMatrix( {} )\n    false\n\n    See Also\n    --------\n    isMatrixLike, isPersymmetricMatrix, isSkewSymmetricMatrix\n","isSkewSymmetricMatrix":"\nisSkewSymmetricMatrix( value )\n    Tests if a value is a skew-symmetric (or antisymmetric) matrix.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a skew-symmetric matrix.\n\n    Examples\n    --------\n    > var buf = [ 0, -1, 1, 0 ];\n    > var sh = [ 2, 2 ];\n    > var st = [ 2, 1 ];\n    > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n    > var bool = isSkewSymmetricMatrix( M )\n    true\n    > bool = isSkewSymmetricMatrix( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isSkewSymmetricMatrix( 3.14 )\n    false\n    > bool = isSkewSymmetricMatrix( {} )\n    false\n\n    See Also\n    --------\n    isMatrixLike, isSkewSymmetricMatrix, isSquareMatrix\n","isSlice":"\nisSlice( value )\n    Tests if a value is a Slice object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a Slice object.\n\n    Examples\n    --------\n    > var bool = isSlice( new Slice( 10 ) )\n    true\n    > bool = isSlice( 3.14 )\n    false\n    > bool = isSlice( {} )\n    false\n\n    See Also\n    --------\n    isMultiSlice, Slice\n","isSnakecase":"\nisSnakecase( value )\n    Tests if a value is a string in snake case.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a string in snake case.\n\n    Examples\n    --------\n    > var bool = isSnakecase( 'hello_world' )\n    true\n    > bool = isSnakecase( 'Hello World' )\n    false\n\n    See Also\n    --------\n    isString","isSquareMatrix":"\nisSquareMatrix( value )\n    Tests if a value is a 2-dimensional ndarray-like object having equal\n    dimensions.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 2-dimensional ndarray-like\n        object having equal dimensions.\n\n    Examples\n    --------\n    > var buf = [ 0, 0, 0, 0 ];\n    > var sh = [ 2, 2 ];\n    > var st = [ 2, 1 ];\n    > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n    > var bool = isSquareMatrix( M )\n    true\n    > bool = isSquareMatrix( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isSquareMatrix( 3.14 )\n    false\n    > bool = isSquareMatrix( {} )\n    false\n\n    See Also\n    --------\n    isMatrixLike, isSymmetricMatrix\n","isSquareNumber":"\nisSquareNumber( value )\n    Tests if a value is a square number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a square number.\n\n    Examples\n    --------\n    > var bool = isSquareNumber( 4.0 )\n    true\n    > bool = isSquareNumber( new Number( 4.0 ) )\n    true\n    > bool = isSquareNumber( 3.14 )\n    false\n    > bool = isSquareNumber( -5.0 )\n    false\n    > bool = isSquareNumber( null )\n    false\n\n\nisSquareNumber.isPrimitive( value )\n    Tests if a value is a number primitive which is a square number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a\n        square number.\n\n    Examples\n    --------\n    > var bool = isSquareNumber.isPrimitive( 4.0 )\n    true\n    > bool = isSquareNumber.isPrimitive( new Number( 4.0 ) )\n    false\n\n\nisSquareNumber.isObject( value )\n    Tests if a value is a number object having a value which is a square number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a square number.\n\n    Examples\n    --------\n    > var bool = isSquareNumber.isObject( 4.0 )\n    false\n    > bool = isSquareNumber.isObject( new Number( 4.0 ) )\n    true\n\n\n    See Also\n    --------\n    isCubeNumber, isInteger, isNumber, isTriangularNumber\n","isSquareNumber.isPrimitive":"\nisSquareNumber.isPrimitive( value )\n    Tests if a value is a number primitive which is a square number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a\n        square number.\n\n    Examples\n    --------\n    > var bool = isSquareNumber.isPrimitive( 4.0 )\n    true\n    > bool = isSquareNumber.isPrimitive( new Number( 4.0 ) )\n    false","isSquareNumber.isObject":"\nisSquareNumber.isObject( value )\n    Tests if a value is a number object having a value which is a square number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a square number.\n\n    Examples\n    --------\n    > var bool = isSquareNumber.isObject( 4.0 )\n    false\n    > bool = isSquareNumber.isObject( new Number( 4.0 ) )\n    true\n\n\n    See Also\n    --------\n    isCubeNumber, isInteger, isNumber, isTriangularNumber","isSquareTriangularNumber":"\nisSquareTriangularNumber( value )\n    Tests if a value is a square triangular number.\n\n    Return values are not reliable for numbers greater than 1125899906842624.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a square triangular number.\n\n    Examples\n    --------\n    > var bool = isSquareTriangularNumber( 36.0 )\n    true\n    > bool = isSquareTriangularNumber( new Number( 36.0 ) )\n    true\n    > bool = isSquareTriangularNumber( 3.14 )\n    false\n    > bool = isSquareTriangularNumber( -5.0 )\n    false\n    > bool = isSquareTriangularNumber( null )\n    false\n\n\nisSquareTriangularNumber.isPrimitive( value )\n    Tests if a value is a number primitive which is a square triangular number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a\n        square triangular number.\n\n    Examples\n    --------\n    > var bool = isSquareTriangularNumber.isPrimitive( 36.0 )\n    true\n    > bool = isSquareTriangularNumber.isPrimitive( new Number( 36.0 ) )\n    false\n\n\nisSquareTriangularNumber.isObject( value )\n    Tests if a value is a number object having a value which is a square\n    triangular number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a square triangular number.\n\n    Examples\n    --------\n    > var bool = isSquareTriangularNumber.isObject( 36.0 )\n    false\n    > bool = isSquareTriangularNumber.isObject( new Number( 36.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger, isNumber, isSquareNumber, isTriangularNumber\n","isSquareTriangularNumber.isPrimitive":"\nisSquareTriangularNumber.isPrimitive( value )\n    Tests if a value is a number primitive which is a square triangular number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a\n        square triangular number.\n\n    Examples\n    --------\n    > var bool = isSquareTriangularNumber.isPrimitive( 36.0 )\n    true\n    > bool = isSquareTriangularNumber.isPrimitive( new Number( 36.0 ) )\n    false","isSquareTriangularNumber.isObject":"\nisSquareTriangularNumber.isObject( value )\n    Tests if a value is a number object having a value which is a square\n    triangular number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a square triangular number.\n\n    Examples\n    --------\n    > var bool = isSquareTriangularNumber.isObject( 36.0 )\n    false\n    > bool = isSquareTriangularNumber.isObject( new Number( 36.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger, isNumber, isSquareNumber, isTriangularNumber","isStartcase":"\nisStartcase( value )\n    Tests if a value is a startcase string.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if value is a startcase string.\n\n    Examples\n    --------\n    > var bool = isStartcase( 'Beep Boop' )\n    true\n    > bool = isStartcase( 'Beep and Boop' )\n    false\n\n    See Also\n    --------\n    isString","isStrictEqual":"\nisStrictEqual( a, b )\n    Tests if two arguments are strictly equal.\n\n    The function differs from the `===` operator in that the function treats\n    `-0` and `+0` as distinct.\n\n    Parameters\n    ----------\n    a: any\n        First input value.\n\n    b: any\n        Second input value.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether two arguments are strictly equal.\n\n    Examples\n    --------\n    > var bool = isStrictEqual( true, true )\n    true\n    > bool = isStrictEqual( {}, {} )\n    false\n    > bool = isStrictEqual( -0.0, -0.0 )\n    true\n    > bool = isStrictEqual( -0.0, 0.0 )\n    false\n    > bool = isStrictEqual( NaN, NaN )\n    false\n\n    See Also\n    --------\n    isSameValue\n","isString":"\nisString( value )\n    Tests if a value is a string.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a string.\n\n    Examples\n    --------\n    > var bool = isString( 'beep' )\n    true\n    > bool = isString( new String( 'beep' ) )\n    true\n    > bool = isString( 5 )\n    false\n\n\nisString.isPrimitive( value )\n    Tests if a value is a string primitive.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a string primitive.\n\n    Examples\n    --------\n    > var bool = isString.isPrimitive( 'beep' )\n    true\n    > bool = isString.isPrimitive( new String( 'beep' ) )\n    false\n\n\nisString.isObject( value )\n    Tests if a value is a `String` object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a `String` object.\n\n    Examples\n    --------\n    > var bool = isString.isObject( new String( 'beep' ) )\n    true\n    > bool = isString.isObject( 'beep' )\n    false\n\n","isString.isPrimitive":"\nisString.isPrimitive( value )\n    Tests if a value is a string primitive.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a string primitive.\n\n    Examples\n    --------\n    > var bool = isString.isPrimitive( 'beep' )\n    true\n    > bool = isString.isPrimitive( new String( 'beep' ) )\n    false","isString.isObject":"\nisString.isObject( value )\n    Tests if a value is a `String` object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a `String` object.\n\n    Examples\n    --------\n    > var bool = isString.isObject( new String( 'beep' ) )\n    true\n    > bool = isString.isObject( 'beep' )\n    false","isStringArray":"\nisStringArray( value )\n    Tests if a value is an array of strings.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array of strings.\n\n    Examples\n    --------\n    > var bool = isStringArray( [ 'abc', 'def' ] )\n    true\n    > bool = isStringArray( [ 'abc', 123 ] )\n    false\n\n\nisStringArray.primitives( value )\n    Tests if a value is an array containing only string primitives.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array containing only string\n        primitives.\n\n    Examples\n    --------\n    > var arr = [ 'abc', 'def' ];\n    > var bool = isStringArray.primitives( arr )\n    true\n    > arr = [ 'abc', new String( 'def' ) ];\n    > bool = isStringArray.primitives( arr )\n    false\n\n\nisStringArray.objects( value )\n    Tests if a value is an array containing only `String` objects.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array containing only `String`\n        objects.\n\n    Examples\n    --------\n    > var arr = [ new String( 'ab' ), new String( 'cd' ) ];\n    > var bool = isStringArray.objects( arr )\n    true\n    > arr = [ new String( 'abc' ), 'def' ];\n    > bool = isStringArray.objects( arr )\n    false\n\n    See Also\n    --------\n    isArray, isString\n","isStringArray.primitives":"\nisStringArray.primitives( value )\n    Tests if a value is an array containing only string primitives.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array containing only string\n        primitives.\n\n    Examples\n    --------\n    > var arr = [ 'abc', 'def' ];\n    > var bool = isStringArray.primitives( arr )\n    true\n    > arr = [ 'abc', new String( 'def' ) ];\n    > bool = isStringArray.primitives( arr )\n    false","isStringArray.objects":"\nisStringArray.objects( value )\n    Tests if a value is an array containing only `String` objects.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array containing only `String`\n        objects.\n\n    Examples\n    --------\n    > var arr = [ new String( 'ab' ), new String( 'cd' ) ];\n    > var bool = isStringArray.objects( arr )\n    true\n    > arr = [ new String( 'abc' ), 'def' ];\n    > bool = isStringArray.objects( arr )\n    false\n\n    See Also\n    --------\n    isArray, isString","isSymbol":"\nisSymbol( value )\n    Tests if a value is a symbol.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a symbol.\n\n    Examples\n    --------\n    > var bool = isSymbol( Symbol( 'beep' ) )\n    true\n    > bool = isSymbol( Object( Symbol( 'beep' ) ) )\n    true\n    > bool = isSymbol( {} )\n    false\n    > bool = isSymbol( null )\n    false\n    > bool = isSymbol( true )\n    false\n\n","isSymbolArray":"\nisSymbolArray( value )\n    Tests if a value is an array-like object containing only symbols.\n\n    In pre-ES2015 environments, the function always returns `false`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only symbols.\n\n    Examples\n    --------\n    > var bool = isSymbolArray( [ Symbol( 'beep' ), Symbol( 'boop' ) ] )\n    true\n    > bool = isSymbolArray( Symbol( 'beep' ) )\n    false\n    > bool = isSymbolArray( [] )\n    false\n    > bool = isSymbolArray( {} )\n    false\n    > bool = isSymbolArray( null )\n    false\n    > bool = isSymbolArray( true )\n    false\n\n\nisSymbolArray.primitives( value )\n    Tests if a value is an array-like object containing only `symbol`\n    primitives.\n\n    In pre-ES2015 environments, the function always returns `false`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only `symbol` primitives.\n\n    Examples\n    --------\n    > var bool = isSymbolArray.primitives( [ Symbol( 'beep' ) ] )\n    true\n    > bool = isSymbolArray.primitives( [ Object( Symbol( 'beep' ) ) ] )\n    false\n    > bool = isSymbolArray.primitives( [] )\n    false\n    > bool = isSymbolArray.primitives( {} )\n    false\n    > bool = isSymbolArray.primitives( null )\n    false\n    > bool = isSymbolArray.primitives( true )\n    false\n\n\nisSymbolArray.objects( value )\n    Tests if a value is an array-like object containing only `Symbol`\n    objects.\n\n    In pre-ES2015 environments, the function always returns `false`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only `Symbol` objects.\n\n    Examples\n    --------\n    > var bool = isSymbolArray.objects( [ Object( Symbol( 'beep' ) ) ] )\n    true\n    > bool = isSymbolArray.objects( [ Symbol( 'beep' ) ] )\n    false\n    > bool = isSymbolArray.objects( [] )\n    false\n    > bool = isSymbolArray.objects( {} )\n    false\n    > bool = isSymbolArray.objects( null )\n    false\n    > bool = isSymbolArray.objects( true )\n    false\n\n    See Also\n    --------\n    isArray, isSymbol\n","isSymbolArray.primitives":"\nisSymbolArray.primitives( value )\n    Tests if a value is an array-like object containing only `symbol`\n    primitives.\n\n    In pre-ES2015 environments, the function always returns `false`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only `symbol` primitives.\n\n    Examples\n    --------\n    > var bool = isSymbolArray.primitives( [ Symbol( 'beep' ) ] )\n    true\n    > bool = isSymbolArray.primitives( [ Object( Symbol( 'beep' ) ) ] )\n    false\n    > bool = isSymbolArray.primitives( [] )\n    false\n    > bool = isSymbolArray.primitives( {} )\n    false\n    > bool = isSymbolArray.primitives( null )\n    false\n    > bool = isSymbolArray.primitives( true )\n    false","isSymbolArray.objects":"\nisSymbolArray.objects( value )\n    Tests if a value is an array-like object containing only `Symbol`\n    objects.\n\n    In pre-ES2015 environments, the function always returns `false`.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only `Symbol` objects.\n\n    Examples\n    --------\n    > var bool = isSymbolArray.objects( [ Object( Symbol( 'beep' ) ) ] )\n    true\n    > bool = isSymbolArray.objects( [ Symbol( 'beep' ) ] )\n    false\n    > bool = isSymbolArray.objects( [] )\n    false\n    > bool = isSymbolArray.objects( {} )\n    false\n    > bool = isSymbolArray.objects( null )\n    false\n    > bool = isSymbolArray.objects( true )\n    false\n\n    See Also\n    --------\n    isArray, isSymbol","isSymmetricMatrix":"\nisSymmetricMatrix( value )\n    Tests if a value is a square matrix which equals its transpose.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a symmetric matrix.\n\n    Examples\n    --------\n    > var buf = [ 0, 1, 1, 2 ];\n    > var sh = [ 2, 2 ];\n    > var st = [ 2, 1 ];\n    > var M = ndarray( 'generic', buf, sh, st, 0, 'row-major' );\n    > var bool = isSymmetricMatrix( M )\n    true\n    > bool = isSymmetricMatrix( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isSymmetricMatrix( 3.14 )\n    false\n    > bool = isSymmetricMatrix( {} )\n    false\n\n    See Also\n    --------\n    isMatrixLike, isNonSymmetricMatrix, isSquareMatrix\n","isSyntaxError":"\nisSyntaxError( value )\n    Tests if a value is a SyntaxError object.\n\n    This function should *not* be considered robust. While the function should\n    always return `true` if provided a SyntaxError (or a descendant) object,\n    false positives may occur due to the fact that the SyntaxError constructor\n    inherits from Error and has no internal class of its own. Hence, SyntaxError\n    impersonation is possible.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a SyntaxError object.\n\n    Examples\n    --------\n    > var bool = isSyntaxError( new SyntaxError( 'beep' ) )\n    true\n    > bool = isSyntaxError( {} )\n    false\n\n    See Also\n    --------\n    isError\n","isTriangularNumber":"\nisTriangularNumber( value )\n    Tests if a value is a triangular number.\n\n    Return values are not reliable for numbers greater than 1125899906842624.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a triangular number.\n\n    Examples\n    --------\n    > var bool = isTriangularNumber( 36.0 )\n    true\n    > bool = isTriangularNumber( new Number( 36.0 ) )\n    true\n    > bool = isTriangularNumber( 3.14 )\n    false\n    > bool = isTriangularNumber( -5.0 )\n    false\n    > bool = isTriangularNumber( null )\n    false\n\n\nisTriangularNumber.isPrimitive( value )\n    Tests if a value is a number primitive which is a triangular number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a\n        triangular number.\n\n    Examples\n    --------\n    > var bool = isTriangularNumber.isPrimitive( 36.0 )\n    true\n    > bool = isTriangularNumber.isPrimitive( new Number( 36.0 ) )\n    false\n\n\nisTriangularNumber.isObject( value )\n    Tests if a value is a number object having a value which is a triangular\n    number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a triangular number.\n\n    Examples\n    --------\n    > var bool = isTriangularNumber.isObject( 36.0 )\n    false\n    > bool = isTriangularNumber.isObject( new Number( 36.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger, isNumber, isSquareNumber, isSquareTriangularNumber\n","isTriangularNumber.isPrimitive":"\nisTriangularNumber.isPrimitive( value )\n    Tests if a value is a number primitive which is a triangular number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number primitive which is a\n        triangular number.\n\n    Examples\n    --------\n    > var bool = isTriangularNumber.isPrimitive( 36.0 )\n    true\n    > bool = isTriangularNumber.isPrimitive( new Number( 36.0 ) )\n    false","isTriangularNumber.isObject":"\nisTriangularNumber.isObject( value )\n    Tests if a value is a number object having a value which is a triangular\n    number.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a number object having a value which\n        is a triangular number.\n\n    Examples\n    --------\n    > var bool = isTriangularNumber.isObject( 36.0 )\n    false\n    > bool = isTriangularNumber.isObject( new Number( 36.0 ) )\n    true\n\n\n    See Also\n    --------\n    isInteger, isNumber, isSquareNumber, isSquareTriangularNumber","isTruthy":"\nisTruthy( value )\n    Tests if a value is a value which translates to `true` when evaluated in a\n    boolean context.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is truthy.\n\n    Examples\n    --------\n     > var bool = isTruthy( true )\n    true\n    > bool = isTruthy( {} )\n    true\n    > bool = isTruthy( [] )\n    true\n    > bool = isTruthy( false )\n    false\n    > bool = isTruthy( '' )\n    false\n    > bool = isTruthy( 0 )\n    false\n    > bool = isTruthy( null )\n    false\n    > bool = isTruthy( void 0 )\n    false\n    > bool = isTruthy( NaN )\n    false\n\n    See Also\n    --------\n    isFalsy\n","isTruthyArray":"\nisTruthyArray( value )\n    Tests if a value is an array-like object containing only truthy values.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is an array-like object containing\n        only truthy values.\n\n    Examples\n    --------\n    > var bool = isTruthyArray( [ {}, [] ] )\n    true\n    > bool = isTruthyArray( [ null, '' ] )\n    false\n    > bool = isTruthyArray( [] )\n    false\n\n    See Also\n    --------\n    isFalsyArray, isTruthy\n","isTypedArray":"\nisTypedArray( value )\n    Tests if a value is a typed array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a typed array.\n\n    Examples\n    --------\n    > var bool = isTypedArray( new Int8Array( 10 ) )\n    true\n\n    See Also\n    --------\n    isArray, isTypedArrayLike\n","isTypedArrayLength":"\nisTypedArrayLength( value )\n    Tests if a value is a valid typed array length.\n\n    A valid length property for a typed array instance is any integer value on\n    the interval [0, 2^53-1].\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a valid typed array length.\n\n    Examples\n    --------\n    > var bool = isTypedArrayLength( 5 )\n    true\n    > bool = isTypedArrayLength( 2.0e200 )\n    false\n    > bool = isTypedArrayLength( -3.14 )\n    false\n    > bool = isTypedArrayLength( null )\n    false\n\n    See Also\n    --------\n    isArrayLength, isTypedArray\n","isTypedArrayLike":"\nisTypedArrayLike( value )\n    Tests if a value is typed-array-like.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is typed-array-like.\n\n    Examples\n    --------\n    > var bool = isTypedArrayLike( new Int16Array() )\n    true\n    > bool = isTypedArrayLike({\n    ...    'length': 10,\n    ...    'byteOffset': 0,\n    ...    'byteLength': 10,\n    ...    'BYTES_PER_ELEMENT': 4\n    ... })\n    true\n\n    See Also\n    --------\n    isTypedArray\n","isTypeError":"\nisTypeError( value )\n    Tests if a value is a TypeError object.\n\n    This function should *not* be considered robust. While the function should\n    always return `true` if provided a TypeError (or a descendant) object,\n    false positives may occur due to the fact that the TypeError constructor\n    inherits from Error and has no internal class of its own. Hence, TypeError\n    impersonation is possible.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a TypeError object.\n\n    Examples\n    --------\n    > var bool = isTypeError( new TypeError( 'beep' ) )\n    true\n    > bool = isTypeError( {} )\n    false\n\n    See Also\n    --------\n    isError\n","isUint8Array":"\nisUint8Array( value )\n    Tests if a value is a Uint8Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Uint8Array.\n\n    Examples\n    --------\n    > var bool = isUint8Array( new Uint8Array( 10 ) )\n    true\n    > bool = isUint8Array( [] )\n    false\n\n    See Also\n    --------\n    isTypedArray, isUint16Array, isUint32Array\n","isUint8ClampedArray":"\nisUint8ClampedArray( value )\n    Tests if a value is a Uint8ClampedArray.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Uint8ClampedArray.\n\n    Examples\n    --------\n    > var bool = isUint8ClampedArray( new Uint8ClampedArray( 10 ) )\n    true\n    > bool = isUint8ClampedArray( [] )\n    false\n\n    See Also\n    --------\n    isTypedArray, isUint8Array\n","isUint16Array":"\nisUint16Array( value )\n    Tests if a value is a Uint16Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Uint16Array.\n\n    Examples\n    --------\n    > var bool = isUint16Array( new Uint16Array( 10 ) )\n    true\n    > bool = isUint16Array( [] )\n    false\n\n    See Also\n    --------\n    isTypedArray, isUint32Array, isUint8Array\n","isUint32Array":"\nisUint32Array( value )\n    Tests if a value is a Uint32Array.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a Uint32Array.\n\n    Examples\n    --------\n    > var bool = isUint32Array( new Uint32Array( 10 ) )\n    true\n    > bool = isUint32Array( [] )\n    false\n\n    See Also\n    --------\n    isTypedArray, isUint16Array, isUint8Array\n","isUNCPath":"\nisUNCPath( value )\n    Tests if a value is a UNC path.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a UNC path.\n\n    Examples\n    --------\n    > var bool = isUNCPath( '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz' )\n    true\n    > bool = isUNCPath( '/foo/bar/baz' )\n    false\n\n","isUndefined":"\nisUndefined( value )\n    Tests if a value is undefined.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is undefined.\n\n    Examples\n    --------\n    > var bool = isUndefined( void 0 )\n    true\n    > bool = isUndefined( null )\n    false\n\n    See Also\n    --------\n    isNull, isUndefinedOrNull\n","isUndefinedOrNull":"\nisUndefinedOrNull( value )\n    Tests if a value is undefined or null.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is undefined or null.\n\n    Examples\n    --------\n    > var bool = isUndefinedOrNull( void 0 )\n    true\n    > bool = isUndefinedOrNull( null )\n    true\n    > bool = isUndefinedOrNull( false )\n    false\n\n    See Also\n    --------\n    isNull, isUndefined\n","isUnityProbabilityArray":"\nisUnityProbabilityArray( value )\n    Tests if a value is an array of probabilities that sum to one.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an array of probabilities that sum\n        to one.\n\n    Examples\n    --------\n    > var bool = isUnityProbabilityArray( [ 0.25, 0.5, 0.25 ] )\n    true\n    > bool = isUnityProbabilityArray( new Uint8Array( [ 0, 1 ] ) )\n    true\n    > bool = isUnityProbabilityArray( [ 0.4, 0.4, 0.4 ] )\n    false\n    > bool = isUnityProbabilityArray( [ 3.14, 0.0 ] )\n    false\n\n    See Also\n    --------\n    isProbability, isProbabilityArray\n","isUppercase":"\nisUppercase( value )\n    Tests if a value is an uppercase string.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is an uppercase string.\n\n    Examples\n    --------\n    > var bool = isUppercase( 'HELLO' )\n    true\n    > bool = isUppercase( 'World' )\n    false\n\n    See Also\n    --------\n    isLowercase, isString\n","isURI":"\nisURI( value )\n    Tests if a value is a URI.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a URI.\n\n    Examples\n    --------\n    > var bool = isURI( 'http://google.com' )\n    true\n    > bool = isURI( 'http://localhost/' )\n    true\n    > bool = isURI( 'http://example.w3.org/path%20with%20spaces.html' )\n    true\n    > bool = isURI( 'ftp://ftp.is.co.za/rfc/rfc1808.txt' )\n    true\n\n    // No scheme:\n    > bool = isURI( '' )\n    false\n    > bool = isURI( 'foo@bar' )\n    false\n    > bool = isURI( '://foo/' )\n    false\n\n    // Illegal characters:\n    > bool = isURI( 'http://<foo>' )\n    false\n\n    // Invalid path:\n    > bool = isURI( 'http:////foo.html' )\n    false\n\n    // Incomplete hex escapes:\n    > bool = isURI( 'http://example.w3.org/%a' )\n    false\n\n","isURIError":"\nisURIError( value )\n    Tests if a value is a URIError object.\n\n    This function should *not* be considered robust. While the function should\n    always return `true` if provided a URIError (or a descendant) object,\n    false positives may occur due to the fact that the URIError constructor\n    inherits from Error and has no internal class of its own. Hence, URIError\n    impersonation is possible.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a URIError object.\n\n    Examples\n    --------\n    > var bool = isURIError( new URIError( 'beep' ) )\n    true\n    > bool = isURIError( {} )\n    false\n\n    See Also\n    --------\n    isError\n","isVectorLike":"\nisVectorLike( value )\n    Tests if a value is a 1-dimensional ndarray-like object.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a value is a 1-dimensional ndarray-like\n        object.\n\n    Examples\n    --------\n    > var M = {};\n    > M.data = [ 0, 0, 0, 0 ];\n    > M.ndims = 1;\n    > M.shape = [ 4 ];\n    > M.strides = [ 1 ];\n    > M.offset = 0;\n    > M.order = 'row-major';\n    > M.dtype = 'generic';\n    > M.length = 4;\n    > M.flags = {};\n    > M.get = function get( i, j ) {};\n    > M.set = function set( i, j ) {};\n    > var bool = isVectorLike( M )\n    true\n    > bool = isVectorLike( [ 1, 2, 3, 4 ] )\n    false\n    > bool = isVectorLike( 3.14 )\n    false\n    > bool = isVectorLike( {} )\n    false\n\n    See Also\n    --------\n    isArray, isArrayLike, isMatrixLike, isndarrayLike, isTypedArrayLike\n","isWebAssemblyMemory":"\nisWebAssemblyMemory( value )\n    Tests if a value is a WebAssembly memory instance.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether value is a WebAssembly memory instance.\n\n    Examples\n    --------\n    > var bool = isWebAssemblyMemory( {} )\n    false\n\n    See Also\n    --------\n    hasWebAssemblySupport\n","isWellFormedString":"\nisWellFormedString( str )\n    Tests if a string is well-formed.\n\n    Parameters\n    ----------\n    str: any\n        String to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether str is well-formed.\n\n    Examples\n    --------\n    > var bool = isWellFormedString( '' )\n    true\n\n    > bool = isWellFormedString( new String( '' ) )\n    true\n\n    > bool = isWellFormedString( '\\uDBFF' )\n    false\n\n    > bool = isWellFormedString( '\\uDBFFFF\\uDBFF' )\n    false\n\n    > bool = isWellFormedString( [] )\n    false\n\n    > bool = isWellFormedString( '-5' )\n    true\n\n    > bool = isWellFormedString( null )\n    false\n\n\nisWellFormedString.isPrimitive( str )\n    Tests if a string is a well-formed string primitive.\n\n    Parameters\n    ----------\n    str: any\n        String to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether str is a well-formed string primitive.\n\n    Examples\n    --------\n    > var bool = isWellFormedString.isPrimitive( '' )\n    true\n    > bool = isWellFormedString.isPrimitive( new String( '' ) )\n    false\n\n\nisWellFormedString.isObject( str )\n    Tests if a string is a well-formed string object.\n\n    Parameters\n    ----------\n    str: any\n        String to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether str is a well-formed string object.\n\n    Examples\n    --------\n    > var bool = isWellFormedString.isObject( '' )\n    false\n    > bool = isWellFormedString.isObject( new String( '' ) )\n    true\n\n","isWellFormedString.isPrimitive":"\nisWellFormedString.isPrimitive( str )\n    Tests if a string is a well-formed string primitive.\n\n    Parameters\n    ----------\n    str: any\n        String to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether str is a well-formed string primitive.\n\n    Examples\n    --------\n    > var bool = isWellFormedString.isPrimitive( '' )\n    true\n    > bool = isWellFormedString.isPrimitive( new String( '' ) )\n    false","isWellFormedString.isObject":"\nisWellFormedString.isObject( str )\n    Tests if a string is a well-formed string object.\n\n    Parameters\n    ----------\n    str: any\n        String to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether str is a well-formed string object.\n\n    Examples\n    --------\n    > var bool = isWellFormedString.isObject( '' )\n    false\n    > bool = isWellFormedString.isObject( new String( '' ) )\n    true","isWhitespace":"\nisWhitespace( str )\n    Tests whether a string contains only white space characters.\n\n    A white space character is defined as one of the 25 characters defined as a\n    white space (\"WSpace=Y\",\"WS\") character in the Unicode 9.0 character\n    database, as well as one related white space character without the Unicode\n    character property \"WSpace=Y\" (zero width non-breaking space which was\n    deprecated as of Unicode 3.2).\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a string contains only white space\n        characters.\n\n    Examples\n    --------\n    > var bool = isWhitespace( '       ' )\n    true\n    > bool = isWhitespace( 'abcdef' )\n    false\n    > bool = isWhitespace( '' )\n    false\n\n    See Also\n    --------\n    reWhitespace\n","isWritableProperty":"\nisWritableProperty( value, property )\n    Tests if an object's own property is writable.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own property is writable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.writable = false;\n    > desc.value = 'beep';\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isWritableProperty( obj, 'boop' )\n    true\n    > bool = isWritableProperty( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    isReadableProperty, isReadWriteProperty, isWritablePropertyIn, isWriteOnlyProperty\n","isWritablePropertyIn":"\nisWritablePropertyIn( value, property )\n    Tests if an object's own or inherited property is writable.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own or inherited property is writable.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.writable = false;\n    > desc.value = 'beep';\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isWritablePropertyIn( obj, 'boop' )\n    true\n    > bool = isWritablePropertyIn( obj, 'beep' )\n    false\n\n    See Also\n    --------\n    isReadablePropertyIn, isReadWritePropertyIn, isWritableProperty, isWriteOnlyPropertyIn\n","isWriteOnlyProperty":"\nisWriteOnlyProperty( value, property )\n    Tests if an object's own property is write-only.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own property is write-only.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = true;\n    > desc.set = function setter( v ) { obj.boop = v; };\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isWriteOnlyProperty( obj, 'boop' )\n    false\n    > bool = isWriteOnlyProperty( obj, 'beep' )\n    true\n\n    See Also\n    --------\n    isReadOnlyProperty, isReadWriteProperty, isWritableProperty, isWriteOnlyPropertyIn\n","isWriteOnlyPropertyIn":"\nisWriteOnlyPropertyIn( value, property )\n    Tests if an object's own or inherited property is write-only.\n\n    Parameters\n    ----------\n    value: any\n        Value to test.\n\n    property: any\n        Property to test.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating if an object's own or inherited property is write-\n        only.\n\n    Examples\n    --------\n    > var obj = { 'boop': true };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = true;\n    > desc.set = function setter( v ) { obj.boop = v; };\n    > defineProperty( obj, 'beep', desc );\n    > var bool = isWriteOnlyPropertyIn( obj, 'boop' )\n    false\n    > bool = isWriteOnlyPropertyIn( obj, 'beep' )\n    true\n\n    See Also\n    --------\n    isReadOnlyPropertyIn, isReadWritePropertyIn, isWritablePropertyIn, isWriteOnlyProperty\n","iterAbs":"\niterAbs( iterator )\n    Returns an iterator which iteratively computes the absolute value.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAbs( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.abs, iterAbs2\n","iterAbs2":"\niterAbs2( iterator )\n    Returns an iterator which iteratively computes the squared absolute value.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAbs2( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.abs2, iterAbs\n","iterAcos":"\niterAcos( iterator )\n    Returns an iterator which iteratively computes the arccosine.\n\n    The domain of arccosine is restricted to [-1,1]. If an iterated value is\n    outside of the domain, the returned iterator returns `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAcos( random.iterators.uniform( -1.0, 1.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.acos, iterAcosh, iterAsin, iterAtan\n","iterAcosh":"\niterAcosh( iterator )\n    Returns an iterator which iteratively computes the hyperbolic arccosine.\n\n    The domain of the hyperbolic arccosine is restricted to [1,+infinity). If an\n    iterated value is outside of the domain, the returned iterator returns\n    `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAcosh( random.iterators.uniform( 1.0, 10.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.acosh, iterAcos, iterAsinh, iterAtanh\n","iterAcot":"\niterAcot( iterator )\n    Returns an iterator which iteratively computes the inverse cotangent.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAcot( random.iterators.uniform( -5.0, 5.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.acot, iterAcos, iterAcoth, iterAsin, iterAtan\n","iterAcoth":"\niterAcoth( iterator )\n    Returns an iterator which iteratively computes the inverse hyperbolic\n    cotangent.\n\n    The domain of the inverse hyperbolic cotangent is restricted to (-inf,-1]\n    and [1,inf). If an iterated value is outside of the domain, the returned\n    iterator returns `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAcoth( random.iterators.uniform( 1.0, 10.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.acoth, iterAcosh, iterAcot, iterAsinh, iterAtanh\n","iterAcovercos":"\niterAcovercos( iterator )\n    Returns an iterator which iteratively computes the inverse coversed cosine.\n\n    The domain of inverse coversed cosine is restricted to [-2,0]. If an\n    iterated value is outside of the domain, the returned iterator returns\n    `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAcovercos( random.iterators.uniform( -2.0, 0.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.acovercos, iterAcoversin, iterAvercos, iterCovercos, iterVercos\n","iterAcoversin":"\niterAcoversin( iterator )\n    Returns an iterator which iteratively computes the inverse coversed sine.\n\n    The domain of inverse coversed sine is restricted to [0,2]. If an iterated\n    value is outside of the domain, the returned iterator returns `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAcoversin( random.iterators.uniform( 0.0, 2.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.acoversin, iterAcovercos, iterAversin, iterCoversin, iterVersin\n","iterAdd":"\niterAdd( iter0, ...iterator )\n    Returns an iterator which performs element-wise addition of two or more\n    iterators.\n\n    The length of the returned iterator is equal to the length of the shortest\n    provided iterator. In other words, the returned iterator ends once *one* of\n    the provided iterators ends.\n\n    If provided a numeric value as an iterator argument, the value is broadcast\n    as an infinite iterator which always returns the provided value.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iter0: Object\n        Input iterator.\n\n    iterator: ...Object\n        Iterators to add.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1.0, 2.0 ] );\n    > var it2 = array2iterator( [ 3.0, 4.0 ] );\n    > var it = iterAdd( it1, it2 );\n    > var v = it.next().value\n    4.0\n    > v = it.next().value\n    6.0\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterDivide, iterMultiply, iterSubtract\n","iterAdvance":"\niterAdvance( iterator[, n] )\n    Advances an entire iterator.\n\n    The function *eagerly* advances an input iterator `n` iterations or until\n    the input iterator finishes, whichever comes first.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator to advance.\n\n    n: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Input iterator.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n    > var it = iterAdvance( arr, 4 );\n    > var v = it.next().value\n    1\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterHead, iterSlice\n","iterAhavercos":"\niterAhavercos( iterator )\n    Returns an iterator which iteratively computes the inverse half-value versed\n    cosine.\n\n    The domain of inverse half-value versed cosine is restricted to [0,1]. If\n    an iterated value is outside of the domain, the returned iterator returns\n    `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAhavercos( random.iterators.uniform( 0.0, 1.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.ahavercos, iterAhaversin, iterHavercos, iterVercos\n","iterAhaversin":"\niterAhaversin( iterator )\n    Returns an iterator which iteratively computes the inverse half-value versed\n    sine.\n\n    The domain of inverse half-value versed sine is restricted to [-2,0]. If an\n    iterated value is outside of the domain, the returned iterator returns\n    `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAhaversin( random.iterators.uniform( 0.0, 1.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.ahaversin, iterAhavercos, iterHaversin, iterVersin\n","iterAny":"\niterAny( iterator )\n    Tests whether at least one iterated value is truthy.\n\n    The function immediately returns upon encountering a truthy value.\n\n    If provided an iterator which does not return any iterated values, the\n    function returns `false`.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if a value is truthy; otherwise, the\n        function returns `false`.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n    > var bool = iterAny( arr )\n    true\n\n    See Also\n    --------\n    iterAnyBy, iterEvery, iterForEach, iterNone, iterSome\n","iterAnyBy":"\niterAnyBy( iterator, predicate[, thisArg ] )\n    Tests whether at least one iterated value passes a test implemented by a\n    predicate function.\n\n    The predicate function is provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index.\n\n    The function immediately returns upon encountering a truthy return value.\n\n    If provided an iterator which does not return any iterated values, the\n    function returns `false`.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if a predicate function returns a truthy\n        value for any iterated value. Otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n    > function fcn( v ) { return ( v === 1 ); };\n    > var bool = iterAnyBy( arr, fcn )\n    true\n\n    See Also\n    --------\n    iterAny, iterEveryBy, iterForEach, iterNoneBy, iterSomeBy\n","iterAsin":"\niterAsin( iterator )\n    Returns an iterator which iteratively computes the arcsine.\n\n    The domain of arcsine is restricted to [-1,1]. If an iterated value is\n    outside of the domain, the returned iterator returns `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAsin( random.iterators.uniform( -1.0, 1.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.asin, iterAcos, iterAsinh, iterAtan\n","iterAsinh":"\niterAsinh( iterator )\n    Returns an iterator which iteratively computes the hyperbolic arcsine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAsinh( random.iterators.uniform( -2.0, 2.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.asinh, iterAcosh, iterAsin, iterAtanh\n","iterAtan":"\niterAtan( iterator )\n    Returns an iterator which iteratively computes the arctangent.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAtan( random.iterators.uniform( -2.0, 2.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.atan, iterAcos, iterAsin, iterAtanh\n","iterAtan2":"\niterAtan2( y, x )\n    Returns an iterator which iteratively computes the angle in the plane (in\n    radians) between the positive x-axis and the ray from (0,0) to the point\n    (x,y).\n\n    The length of the returned iterator is equal to the length of the shortest\n    provided iterator. In other words, the returned iterator ends once *one* of\n    the provided iterators ends.\n\n    If provided a numeric value as an iterator argument, the value is broadcast\n    as an infinite iterator which always returns the provided value.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    y: Object|number\n        Input iterator.\n\n    x: Object|number\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = random.iterators.uniform( -2.0, 2.0 );\n    > var y = random.iterators.uniform( -2.0, 2.0 );\n    > var it = iterAtan2( y, x );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.atan2, iterAtan\n","iterAtanh":"\niterAtanh( iterator )\n    Returns an iterator which iteratively computes the hyperbolic arctangent.\n\n    The domain of hyperbolic arctangent is restricted to [-1,1]. If an iterated\n    value is outside of the domain, the returned iterator returns `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAtanh( random.iterators.uniform( -1.0, 1.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.atanh, iterAcosh, iterAsinh, iterAtan\n","iterator2array":"\niterator2array( iterator[, out][, mapFcn[, thisArg]] )\n    Creates (or fills) an array from an iterator.\n\n    When invoked, an input function is provided two arguments:\n\n    - value: iterated value.\n    - index: iterated value index (zero-based).\n\n    If provided an output array, the function fills the output array with\n    iterated values.\n\n    Iteration stops when an output array is full or an iterator finishes;\n    whichever comes first.\n\n    Parameters\n    ----------\n    iterator: Object\n        Source iterator.\n\n    out: ArrayLikeObject (optional)\n        Output array-like object.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var opts = { 'iter': 10 };\n    > var arr = iterator2array( random.iterators.randu( opts ) )\n\n    See Also\n    --------\n    array2iterator, iterator2arrayview\n","iterator2arrayview":"\niterator2arrayview( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )\n    Fills an array-like object view with values returned from an iterator.\n\n    When invoked, an input function is provided three arguments:\n\n    - value: iterated value.\n    - index: destination index (zero-based).\n    - n: iteration index (zero-based).\n\n    Iteration stops when an output array view is full or an iterator finishes;\n    whichever comes first.\n\n    Parameters\n    ----------\n    iterator: Object\n        Source iterator.\n\n    dest: ArrayLikeObject\n        Output array-like object.\n\n    begin: integer (optional)\n        Starting index (inclusive). When negative, determined relative to the\n        last element. Default: 0.\n\n    end: integer (optional)\n        Ending index (non-inclusive). When negative, determined relative to the\n        last element. Default: dest.length.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var it = random.iterators.randu({ 'iter': 10 });\n    > var out = new Float64Array( 20 );\n    > var arr = iterator2arrayview( it, out, 5, 15 )\n\n    See Also\n    --------\n    iterator2array, arrayview2iterator, iterator2arrayviewRight\n","iterator2arrayviewRight":"\niterator2arrayviewRight( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )\n    Fills an array-like object view from right to left with values returned from\n    an iterator.\n\n    When invoked, an input function is provided three arguments:\n\n    - value: iterated value.\n    - index: destination index (zero-based).\n    - n: iteration index (zero-based).\n\n    Iteration stops when an output array view is full or an iterator finishes;\n    whichever comes first.\n\n    Parameters\n    ----------\n    iterator: Object\n        Source iterator.\n\n    dest: ArrayLikeObject\n        Output array-like object.\n\n    begin: integer (optional)\n        Starting index (inclusive). When negative, determined relative to the\n        last element. Default: 0.\n\n    end: integer (optional)\n        Ending index (non-inclusive). When negative, determined relative to the\n        last element. Default: dest.length.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var it = random.iterators.randu({ 'iter': 10 });\n    > var out = new Float64Array( 20 );\n    > var arr = iterator2arrayviewRight( it, out, 5, 15 )\n\n    See Also\n    --------\n    iterator2array, arrayview2iteratorRight, iterator2arrayview\n","iteratorStream":"\niteratorStream( iterator[, options] )\n    Creates a readable stream from an iterator.\n\n    In object mode, `null` is a reserved value. If an iterator generates `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or explicitly map `null`\n    values to a different value by wrapping the provided iterator with another\n    iterator.\n\n    In binary mode, if an iterator generates `undefined` values, the stream will\n    emit an error. Consider providing a custom serialization function or\n    explicitly map `undefined` values to a different value by wrapping the\n    provided iterator with another iterator.\n\n    If a serialization function fails to return a string or Buffer, the stream\n    emits an error.\n\n    Parameters\n    ----------\n    iterator: Object\n        Source iterator.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing iteration.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize iterated\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var it = random.iterators.randu( opts );\n    > var s = iteratorStream( it );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\niteratorStream.factory( [options] )\n    Returns a function for creating readable streams from iterators.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing iteration.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize iterated\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = iteratorStream.factory( opts );\n\n\niteratorStream.objectMode( iterator[, options] )\n    Returns an \"objectMode\" readable stream from an iterator.\n\n    In object mode, `null` is a reserved value. If an iterator generates `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or explicitly map `null`\n    values to a different value by wrapping the provided iterator with another\n    iterator.\n\n    Parameters\n    ----------\n    iterator: Object\n        Source iterator.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before pausing iteration.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var it = random.iterators.randu( opts );\n    > var s = iteratorStream.objectMode( it );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    arrayStream\n","iteratorStream.factory":"\niteratorStream.factory( [options] )\n    Returns a function for creating readable streams from iterators.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing iteration.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize iterated\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = iteratorStream.factory( opts );","iteratorStream.objectMode":"\niteratorStream.objectMode( iterator[, options] )\n    Returns an \"objectMode\" readable stream from an iterator.\n\n    In object mode, `null` is a reserved value. If an iterator generates `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or explicitly map `null`\n    values to a different value by wrapping the provided iterator with another\n    iterator.\n\n    Parameters\n    ----------\n    iterator: Object\n        Source iterator.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before pausing iteration.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var it = random.iterators.randu( opts );\n    > var s = iteratorStream.objectMode( it );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    arrayStream","IteratorSymbol":"\nIteratorSymbol\n    Iterator symbol.\n\n    This symbol specifies the default iterator for an object.\n\n    The symbol is only supported in ES6/ES2015+ environments. For non-supporting\n    environments, the value is `null`.\n\n    Examples\n    --------\n    > var s = IteratorSymbol\n\n    See Also\n    --------\n    Symbol\n","iterAvercos":"\niterAvercos( iterator )\n    Returns an iterator which iteratively computes the inverse versed cosine.\n\n    The domain of inverse versed cosine is restricted to [-2,0]. If an iterated\n    value is outside of the domain, the returned iterator returns `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAvercos( random.iterators.uniform( -2.0, 0.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.avercos, iterAversin, iterVersin\n","iterAversin":"\niterAversin( iterator )\n    Returns an iterator which iteratively computes the inverse versed sine.\n\n    The domain of inverse versed sine is restricted to [0,2]. If an iterated\n    value is outside of the domain, the returned iterator returns `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterAversin( random.iterators.uniform( 0.0, 2.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.aversin, iterAvercos, iterVercos\n","iterawgn":"\niterawgn( iterator, sigma[, options] )\n    Returns an iterator which introduces additive white Gaussian noise (AWGN)\n    with standard deviation `sigma`.\n\n    If an environment supports Symbol.iterator and the provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    sigma: number\n        Standard deviation of the noise.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating pseudorandom numbers\n        drawn from a standard normal distribution. If provided, the `state` and\n        `seed` options are ignored. In order to seed the returned iterator, one\n        must seed the provided `prng` (assuming the provided `prng` is\n        seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function|null\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Pseudorandom random number generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var src = iterSineWave();\n    > var it = iterawgn( src, 0.5 );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterawln, iterawun\n","iterawln":"\niterawln( iterator, sigma[, options] )\n    Returns an iterator which introduces additive white Laplacian noise (AWLN)\n    with standard deviation `sigma`.\n\n    If an environment supports Symbol.iterator and the provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    sigma: number\n        Standard deviation of the noise.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval [0,1). If provided, the\n        `state` and `seed` options are ignored. In order to seed the returned\n        iterator, one must seed the provided `prng` (assuming the provided\n        `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Pseudorandom random number generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var src = iterSineWave();\n    > var it = iterawln( src, 0.5 );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterawgn, iterawun\n","iterawun":"\niterawun( iterator, sigma[, options] )\n    Returns an iterator which introduces additive white uniform noise (AWUN)\n    with standard deviation `sigma`.\n\n    If an environment supports Symbol.iterator and the provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    sigma: number\n        Standard deviation of the noise.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval [0,1). If provided, the\n        `state` and `seed` options are ignored. In order to seed the returned\n        iterator, one must seed the provided `prng` (assuming the provided\n        `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Pseudorandom random number generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var src = iterSineWave();\n    > var it = iterawun( src, 0.5 );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterawgn, iterawln\n","iterBartlettHannPulse":"\niterBartlettHannPulse( [options] )\n    Returns an iterator which generates a Bartlett-Hann pulse waveform.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Pulse period (i.e., the number of iterations until a waveform repeats).\n        Default: 100.\n\n    options.duration: integer (optional)\n        Pulse duration. Must be greater than 2. Default: options.period.\n\n    options.amplitude: number (optional)\n        Amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterBartlettHannPulse();\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterBartlettPulse, iterHannPulse, iterPulse, iterTriangleWave\n","iterBartlettPulse":"\niterBartlettPulse( [options] )\n    Returns an iterator which generates a Bartlett pulse waveform.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Pulse period (i.e., the number of iterations until a waveform repeats).\n        Default: 100.\n\n    options.duration: integer (optional)\n        Pulse duration. Must be greater than 2. Default: options.period.\n\n    options.amplitude: number (optional)\n        Amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterBartlettPulse();\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterBartlettHannPulse, iterPulse, iterTriangleWave\n","iterBesselj0":"\niterBesselj0( iterator )\n    Returns an iterator which iteratively evaluates the Bessel function of the\n    first kind of order zero.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterBesselj0( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.besselj0, iterBesselj1, iterBessely0, iterBessely1\n","iterBesselj1":"\niterBesselj1( iterator )\n    Returns an iterator which iteratively evaluates the Bessel function of the\n    first kind of order one.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterBesselj1( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.besselj1, iterBesselj0, iterBessely0, iterBessely1\n","iterBessely0":"\niterBessely0( iterator )\n    Returns an iterator which iteratively evaluates the Bessel function of the\n    second kind of order zero.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterBessely0( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.bessely0, iterBesselj0, iterBesselj1, iterBessely1\n","iterBessely1":"\niterBessely1( iterator )\n    Returns an iterator which iteratively evaluates the Bessel function of the\n    second kind of order one.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterBessely1( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.bessely1, iterBesselj0, iterBesselj1, iterBessely0\n","iterBeta":"\niterBeta( x, y )\n    Returns an iterator which iteratively evaluates the beta function.\n\n    The length of the returned iterator is equal to the length of the shortest\n    provided iterator. In other words, the returned iterator ends once *one* of\n    the provided iterators ends.\n\n    If provided a numeric value as an iterator argument, the value is broadcast\n    as an infinite iterator which always returns the provided value.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    x: Object|number\n        Input iterator.\n\n    y: Object|number\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = random.iterators.uniform( 0.0, 2.0 );\n    > var y = random.iterators.uniform( 0.0, 2.0 );\n    > var it = iterBeta( x, y );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.beta, iterBetaln\n","iterBetaln":"\niterBetaln( x, y )\n    Returns an iterator which iteratively evaluates the natural logarithm of the\n    beta function.\n\n    The length of the returned iterator is equal to the length of the shortest\n    provided iterator. In other words, the returned iterator ends once *one* of\n    the provided iterators ends.\n\n    If provided a numeric value as an iterator argument, the value is broadcast\n    as an infinite iterator which always returns the provided value.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    x: Object|number\n        Input iterator.\n\n    y: Object|number\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = random.iterators.uniform( 0.0, 2.0 );\n    > var y = random.iterators.uniform( 0.0, 2.0 );\n    > var it = iterBetaln( x, y );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.betaln, iterBeta\n","iterBinet":"\niterBinet( iterator )\n    Returns an iterator which iteratively evaluates Binet's formula extended to\n    real numbers.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterBinet( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.binet\n","iterCbrt":"\niterCbrt( iterator )\n    Returns an iterator which iteratively computes the cube root.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterCbrt( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.cbrt, iterPow, iterSqrt\n","iterCeil":"\niterCeil( iterator )\n    Returns an iterator which rounds each iterated value toward positive\n    infinity.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterCeil( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.ceil, iterFloor, iterRound\n","iterCeil2":"\niterCeil2( iterator )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    two toward positive infinity.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterCeil2( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.ceil2, iterCeil, iterCeil10, iterFloor2, iterRound2\n","iterCeil10":"\niterCeil10( iterator )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    10 toward positive infinity.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterCeil10( random.iterators.uniform( -100.0, 100.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.ceil10, iterCeil, iterCeil2, iterFloor10, iterRound10\n","iterCompositesSeq":"\niterCompositesSeq( [options] )\n    Returns an iterator which generates a sequence of composite numbers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterCompositesSeq();\n    > var v = it.next().value\n    4\n    > v = it.next().value\n    6\n    > v = it.next().value\n    8\n\n    See Also\n    --------\n    iterIntegersSeq, iterPositiveIntegersSeq, iterPrimesSeq\n","iterConcat":"\niterConcat( iter0, ...iterator )\n    Returns an iterator which iterates over the values of two or more iterators.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iter0: Object\n        Input iterator.\n\n    iterator: ...Object\n        Iterators to concatenate.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2 ] );\n    > var it2 = array2iterator( [ 3, 4 ] );\n    > var it = iterConcat( it1, it2 );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    2\n    > v = it.next().value\n    3\n    > v = it.next().value\n    4\n    > var bool = it.next().done\n    true\n\n","iterConstant":"\niterConstant( value[, options] )\n    Returns an iterator which always returns the same value.\n\n    When provided an object reference, the returned iterator always returns the\n    same reference.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    value: any\n        Value to return.\n\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterConstant( 3.14 );\n    > var v = it.next().value\n    3.14\n    > v = it.next().value\n    3.14\n\n    See Also\n    --------\n    constantFunction\n","iterContinuedFraction":"\niterContinuedFraction( iterator[, options] )\n    Evaluates the terms of a continued fraction.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Maximum number of iterations. Default: 1e308.\n\n    options.tol: number (optional)\n        Tolerance at which to terminate further evaluation of the continued\n        fraction. Default: floating-point epsilon.\n\n    Returns\n    -------\n    out: number|null\n        Result.\n\n    Examples\n    --------\n    > var terms = array2iterator( [ 3, 4, 12, 4 ] );\n    > var v = iterContinuedFraction( terms )\n    ~3.245\n\n    See Also\n    --------\n    iterContinuedFractionSeq\n","iterContinuedFractionSeq":"\niterContinuedFractionSeq( x[, options] )\n    Returns an iterator which generates a list of all continued fraction terms\n    which can be obtained given the precision of `x`.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    x: number\n        Input value.\n\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Maximum number of iterations. Default: 1e308.\n\n    options.tol: number (optional)\n        Tolerance at which to terminate further evaluation of the continued\n        fraction. Default: floating-point epsilon.\n\n    options.returns: string (optional)\n        Specifies the type of result to return. Must be one of\n\n        - terms: return continued fraction terms\n        - convergents: return continued fraction convergents\n        - *: return both continued fraction terms and their associated\n          convergents as a two-element array.\n\n        Default: 'terms'.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    // Return continued fraction terms...\n    > var it = iterContinuedFractionSeq( 3.245 );\n    > var v = it.next().value\n    3\n    > v = it.next().value\n    4\n    > v = it.next().value\n    12\n    > v = it.next().value\n    4\n    > var bool = it.next().done\n    true\n\n    // Return continued fraction convergents...\n    > it = iterContinuedFractionSeq( 3.245, { 'returns': 'convergents' } );\n    > v = it.next().value\n    3.0\n    > v = it.next().value\n    3.25\n    > v = it.next().value\n    ~3.2449\n    > v = it.next().value\n    3.245\n    > bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterContinuedFraction\n","iterCos":"\niterCos( iterator )\n    Returns an iterator which iteratively computes the cosine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterCos( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.cos, iterCospi, iterSin, iterTan\n","iterCosh":"\niterCosh( iterator )\n    Returns an iterator which iteratively computes the hyperbolic cosine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -5.0, 5.0 );\n    > var it = iterCosh( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.cosh, iterCos, iterSinh, iterTanh\n","iterCosineWave":"\niterCosineWave( [options] )\n    Returns an iterator which generates a cosine wave.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Period (i.e., the number of iterations before a cosine wave repeats).\n        Default: 10.\n\n    options.amplitude: number (optional)\n        Peak amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterCosineWave();\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterPulse, iterSawtoothWave, iterSineWave, iterSquareWave, iterTriangleWave\n","iterCosm1":"\niterCosm1( iterator )\n    Returns an iterator which iteratively computes `cos(x) - 1`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 6.28 );\n    > var it = iterCosm1( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.cosm1, iterCos\n","iterCospi":"\niterCospi( iterator )\n    Returns an iterator which computes the cosine of each iterated value times\n    π.\n\n    Computes cos(πx) more accurately than cos(pi*x), especially for large x.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterCospi( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.cospi, iterCos\n","iterCounter":"\niterCounter( iterator )\n    Returns an iterator which iteratively computes the number of iterated\n    values.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterCounter( random.iterators.randu() );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    iterLength\n","iterCovercos":"\niterCovercos( iterator )\n    Returns an iterator which iteratively computes the coversed cosine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 6.28 );\n    > var it = iterCovercos( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.covercos, iterCoversin, iterVercos\n","iterCoversin":"\niterCoversin( iterator )\n    Returns an iterator which iteratively computes the coversed sine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 6.28 );\n    > var it = iterCoversin( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.coversin, iterCovercos, iterVersin\n","iterCubesSeq":"\niterCubesSeq( [options] )\n    Returns an iterator which generates a sequence of cubes.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 208063.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterCubesSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().value\n    8\n\n    See Also\n    --------\n    iterFourthPowersSeq, iterSquaresSeq\n","itercugmean":"\nitercugmean( iterator )\n    Returns an iterator which iteratively computes a cumulative geometric mean.\n\n    If provided a negative value, the iterated value is `NaN` for all future\n    invocations.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\n    > var it = itercugmean( arr );\n    > var v = it.next().value\n    2.0\n    > v = it.next().value\n    ~3.16\n    > v = it.next().value\n    ~3.11\n    > v = it.next().value\n    ~3.50\n\n    See Also\n    --------\n    itercuhmean, itercumean\n","itercuhmean":"\nitercuhmean( iterator )\n    Returns an iterator which iteratively computes a cumulative harmonic mean.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, 5.0, 3.0, 5.0 ] );\n    > var it = itercuhmean( arr );\n    > var v = it.next().value\n    2.0\n    > v = it.next().value\n    ~2.86\n    > v = it.next().value\n    ~2.90\n    > v = it.next().value\n    ~3.24\n\n    See Also\n    --------\n    itercugmean, itercumean\n","itercumax":"\nitercumax( iterator )\n    Returns an iterator which iteratively computes a cumulative maximum value.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercumax( arr );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    2.0\n    > m = it.next().value\n    3.0\n    > m = it.next().value\n    5.0\n\n    See Also\n    --------\n    itercumidrange, itercumin, itercurange, itermax\n","itercumaxabs":"\nitercumaxabs( iterator )\n    Returns an iterator which iteratively computes a cumulative maximum absolute\n    value.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercumaxabs( arr );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    5.0\n    > m = it.next().value\n    5.0\n    > m = it.next().value\n    5.0\n\n    See Also\n    --------\n    itercumax, itercuminabs, itermaxabs\n","itercumean":"\nitercumean( iterator )\n    Returns an iterator which iteratively computes a cumulative arithmetic mean.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercumean( arr );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    -1.5\n    > m = it.next().value\n    0.0\n    > m = it.next().value\n    1.25\n\n    See Also\n    --------\n    itercumidrange, itercusum, itermean\n","itercumeanabs":"\nitercumeanabs( iterator )\n    Returns an iterator which iteratively computes a cumulative arithmetic mean\n    of absolute values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercumeanabs( arr );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    3.5\n    > m = it.next().value\n    ~3.33\n    > m = it.next().value\n    3.75\n\n    See Also\n    --------\n    itercumean, itercumeanabs2, itercusumabs, itermeanabs\n","itercumeanabs2":"\nitercumeanabs2( iterator )\n    Returns an iterator which iteratively computes a cumulative arithmetic mean\n    of squared absolute values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercumeanabs2( arr );\n    > var m = it.next().value\n    4.0\n    > m = it.next().value\n    14.5\n    > m = it.next().value\n    ~12.67\n    > m = it.next().value\n    15.75\n\n    See Also\n    --------\n    itercumean, itercumeanabs, itercusumabs2, itermeanabs2\n","itercumidrange":"\nitercumidrange( iterator )\n    Returns an iterator which iteratively computes a cumulative mid-range.\n\n    The mid-range is the arithmetic mean of maximum and minimum values.\n    Accordingly, the mid-range is the midpoint of the range and a measure of\n    central tendency.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercumidrange( arr );\n    > var v = it.next().value\n    2.0\n    > v = it.next().value\n    -1.5\n    > v = it.next().value\n    -1.0\n    > v = it.next().value\n    0.0\n\n    See Also\n    --------\n    itercumean, itercumax, itercumin, itercurange, itermidrange\n","itercumin":"\nitercumin( iterator )\n    Returns an iterator which iteratively computes a cumulative minimum value.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercumin( arr );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    -5.0\n    > m = it.next().value\n    -5.0\n    > m = it.next().value\n    -5.0\n\n    See Also\n    --------\n    itercumax, itercumidrange, itercurange, itermin\n","itercuminabs":"\nitercuminabs( iterator )\n    Returns an iterator which iteratively computes a cumulative minimum absolute\n    value.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercuminabs( arr );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    2.0\n    > m = it.next().value\n    2.0\n    > m = it.next().value\n    2.0\n\n    See Also\n    --------\n    itercumaxabs, itercumin, iterminabs\n","itercuprod":"\nitercuprod( iterator )\n    Returns an iterator which iteratively computes a cumulative product.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercuprod( arr );\n    > var p = it.next().value\n    2.0\n    > p = it.next().value\n    -10.0\n    > p = it.next().value\n    -30.0\n    > p = it.next().value\n    -150.0\n\n    See Also\n    --------\n    itercusum, iterprod\n","itercurange":"\nitercurange( iterator )\n    Returns an iterator which iteratively computes a cumulative range.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercurange( arr );\n    > var r = it.next().value\n    0.0\n    > r = it.next().value\n    7.0\n    > r = it.next().value\n    8.0\n    > r = it.next().value\n    10.0\n\n    See Also\n    --------\n    itercumax, itercumean, itercumin, iterrange\n","itercusum":"\nitercusum( iterator )\n    Returns an iterator which iteratively computes a cumulative sum.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercusum( arr );\n    > var s = it.next().value\n    2.0\n    > s = it.next().value\n    -3.0\n    > s = it.next().value\n    0.0\n    > s = it.next().value\n    5.0\n\n    See Also\n    --------\n    itercumean, itersum, itercuprod\n","itercusumabs":"\nitercusumabs( iterator )\n    Returns an iterator which iteratively computes a cumulative sum of absolute\n    values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercusumabs( arr );\n    > var s = it.next().value\n    2.0\n    > s = it.next().value\n    7.0\n    > s = it.next().value\n    10.0\n    > s = it.next().value\n    15.0\n\n    See Also\n    --------\n    itercumeanabs, itercusum, itersumabs\n","itercusumabs2":"\nitercusumabs2( iterator )\n    Returns an iterator which iteratively computes a cumulative sum of squared\n    absolute values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itercusumabs2( arr );\n    > var s = it.next().value\n    4.0\n    > s = it.next().value\n    29.0\n    > s = it.next().value\n    38.0\n    > s = it.next().value\n    63.0\n\n    See Also\n    --------\n    itercumeanabs2, itercusumabs, itersumabs2\n","iterDatespace":"\niterDatespace( start, stop[, N][, options] )\n    Returns an iterator which returns evenly spaced dates over a specified\n    interval.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    start: integer|string|Date\n        Starting date either as a `Date` object, JavaScript timestamp, or a date\n        string (inclusive).\n\n    stop: integer|string|Date\n        Stopping value either as a `Date` object, JavaScript timestamp, or a\n        date string (inclusive).\n\n    N: integer (optional)\n        Number of values. Default: 100.\n\n    options: Object (optional)\n        Function options.\n\n    options.round: string (optional)\n        Specifies how sub-millisecond times should be rounded. Must be one of\n        the following: 'floor', 'ceil', or 'round'. Default: 'floor'.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var t1 = new Date();\n    > var it = iterDatespace( t1, new Date( t1.getTime()+86400000 ) );\n    > var v = it.next().value\n    <Date>\n    > v = it.next().value\n    <Date>\n\n    See Also\n    --------\n    iterator2array, iterIncrspace, iterLinspace, iterLogspace, iterStep\n","iterDedupe":"\niterDedupe( iterator[, limit] )\n    Returns an iterator which removes consecutive duplicated values.\n\n    `NaN` values are considered distinct.\n\n    Uniqueness is determined according to strict equality. Accordingly, objects\n    are *not* checked for deep equality.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    limit: integer (optional)\n        Number of allowed consecutive duplicates. Default: 1.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\n    > var it = iterDedupe( arr );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    2\n    > v = it.next().value\n    3\n\n    See Also\n    --------\n    iterDedupeBy, iterUnique\n","iterDedupeBy":"\niterDedupeBy( iterator, [limit,] fcn )\n    Returns an iterator which removes consecutive values that resolve to the\n    same value according to a provided function.\n\n    The provided function is provided five arguments:\n\n    - curr: current source iterated value.\n    - sprev: previous source iterated value.\n    - dprev: previous downstream iterated value.\n    - index: source iteration index (zero-based).\n    - acc: previous resolved value.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    limit: integer (optional)\n        Number of allowed consecutive duplicates. Default: 1.\n\n    fcn: Function\n        Function indicating whether an iterated value is a \"duplicate\".\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1, 1, 2, 3, 3 ] );\n    > function fcn( v ) { return v; };\n    > var it = iterDedupeBy( arr, fcn );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    2\n    > v = it.next().value\n    3\n\n    See Also\n    --------\n    iterDedupe, iterUnique\n","iterDeg2rad":"\niterDeg2rad( iterator )\n    Returns an iterator which iteratively converts an angle from degrees to\n    radians.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -360.0, 360.0 );\n    > var it = iterDeg2rad( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.deg2rad, iterRad2deg\n","iterDigamma":"\niterDigamma( iterator )\n    Returns an iterator which iteratively evaluates the digamma function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.01, 5.0 );\n    > var it = iterDigamma( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.digamma, iterGamma, iterTrigamma\n","iterDiracComb":"\niterDiracComb( [options] )\n    Returns an iterator which generates a Dirac comb.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Period (i.e., the number of iterations before a waveform repeats).\n        Default: 10.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterDiracComb();\n    > var v = it.next().value\n    Infinity\n    > v = it.next().value\n    0.0\n\n    See Also\n    --------\n    iterPulse\n","iterDiracDelta":"\niterDiracDelta( iterator )\n    Returns an iterator which iteratively evaluates the Dirac delta function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterDiracDelta( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.diracDelta\n","iterDivide":"\niterDivide( iter0, ...iterator )\n    Returns an iterator which performs element-wise division of two or more\n    iterators.\n\n    The length of the returned iterator is equal to the length of the shortest\n    provided iterator. In other words, the returned iterator ends once *one* of\n    the provided iterators ends.\n\n    If provided a numeric value as an iterator argument, the value is broadcast\n    as an infinite iterator which always returns the provided value.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iter0: Object\n        Input iterator.\n\n    iterator: ...Object\n        Iterators whose values are used as divisors.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 3.0, 2.0 ] );\n    > var it2 = array2iterator( [ 1.0, 4.0 ] );\n    > var it = iterDivide( it1, it2 );\n    > var v = it.next().value\n    3.0\n    > v = it.next().value\n    0.5\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterAdd, iterDivide, iterMultiply\n","iterDoWhileEach":"\niterDoWhileEach( iterator, predicate, fcn[, thisArg] )\n    Returns an iterator which invokes a function for each iterated value before\n    returning the iterated value until either a predicate function returns false\n    or the iterator has iterated over all values.\n\n    The condition is evaluated *after* executing the provided function; thus,\n    `fcn` *always* executes at least once.\n\n    When invoked, both input functions are provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index (zero-based).\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    predicate: Function\n        Function which indicates whether to continue iterating.\n\n    fcn: Function\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === v };\n    > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n    > var it = iterDoWhileEach( random.iterators.randu(), predicate, f );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterDoUntilEach, iterUntilEach, iterWhileEach\n","iterEllipe":"\niterEllipe( iterator )\n    Returns an iterator which iteratively computes the complete elliptic\n    integral of the second kind.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -1.0, 1.0 );\n    > var it = iterEllipe( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.ellipe, iterEllipk\n","iterEllipk":"\niterEllipk( iterator )\n    Returns an iterator which iteratively computes the complete elliptic\n    integral of the first kind.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -1.0, 1.0 );\n    > var it = iterEllipk( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.ellipk, iterEllipe\n","iterEmpty":"\niterEmpty()\n    Returns an empty iterator.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterEmpty();\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterConstant\n","iterErf":"\niterErf( iterator )\n    Returns an iterator which iteratively evaluates the error function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterErf( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.erf, iterErfc, iterErfinv, iterErfcinv\n","iterErfc":"\niterErfc( iterator )\n    Returns an iterator which iteratively evaluates the complementary error\n    function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterErfc( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.erfc, iterErf, iterErfinv, iterErfcinv\n","iterErfcinv":"\niterErfcinv( iterator )\n    Returns an iterator which iteratively evaluates the inverse complementary\n    error function.\n\n    The domain of inverse complementary error function is restricted to [0,2].\n    If an iterated value is outside of the domain, the returned iterator returns\n    `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterErfcinv( random.iterators.uniform( 0.0, 2.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.erfcinv, iterErf, iterErfc, iterErfinv\n","iterErfinv":"\niterErfinv( iterator )\n    Returns an iterator which iteratively evaluates the inverse error function.\n\n    The domain of inverse error function is restricted to [-1,1]. If an iterated\n    value is outside of the domain, the returned iterator returns `NaN`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterErfinv( random.iterators.uniform( -1.0, 1.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.erfinv, iterErf, iterErfc, iterErfcinv\n","iterEta":"\niterEta( iterator )\n    Returns an iterator which iteratively evaluates the Dirichlet eta function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterEta( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.eta\n","iterEvenIntegersSeq":"\niterEvenIntegersSeq( [options] )\n    Returns an iterator which generates an interleaved sequence of even\n    integers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 9007199254740992.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterEvenIntegersSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    2\n    > v = it.next().value\n    -2\n\n    See Also\n    --------\n    iterIntegersSeq, iterOddIntegersSeq\n","iterEvery":"\niterEvery( iterator )\n    Tests whether all iterated values are truthy.\n\n    The function immediately returns upon encountering a falsy value.\n\n    If provided an iterator which does not return any iterated values, the\n    function returns `true`.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `false` if a value is falsy; otherwise, the\n        function returns `true`.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1, 1, 1, 1, 0 ] );\n    > var bool = iterEvery( arr )\n    false\n\n    See Also\n    --------\n    iterAny, iterEveryBy, iterForEach, iterNone, iterSome\n","iterEveryBy":"\niterEveryBy( iterator, predicate[, thisArg ] )\n    Tests whether every iterated value passes a test implemented by a predicate\n    function.\n\n    The predicate function is provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index.\n\n    The function immediately returns upon encountering a falsy return value.\n\n    If provided an iterator which does not return any iterated values, the\n    function returns `true`.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if a predicate function returns a truthy\n        value for all iterated values. Otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\n    > function fcn( v ) { return ( v > 0 ); };\n    > var bool = iterEveryBy( arr, fcn )\n    true\n\n    See Also\n    --------\n    iterAnyBy, iterEvery, iterForEach, iterNoneBy, iterSomeBy\n","iterExp":"\niterExp( iterator )\n    Returns an iterator which iteratively evaluates the natural exponential\n    function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterExp( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.exp, iterExp10, iterExp2, iterExpm1, iterLn\n","iterExp2":"\niterExp2( iterator )\n    Returns an iterator which iteratively evaluates the base `2` exponential\n    function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -50.0, 50.0 );\n    > var it = iterExp2( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.exp2, iterExp, iterExp10, iterLog2\n","iterExp10":"\niterExp10( iterator )\n    Returns an iterator which iteratively evaluates the base `10` exponential\n    function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -50.0, 50.0 );\n    > var it = iterExp10( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.exp10, iterExp, iterExp2, iterLog10\n","iterExpit":"\niterExpit( iterator )\n    Returns an iterator which iteratively evaluates the standard logistic\n    function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 1.0 );\n    > var it = iterExpit( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.expit, iterExp, iterLogit\n","iterExpm1":"\niterExpm1( iterator )\n    Returns an iterator which iteratively computes `exp(x) - 1`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -5.0, 5.0 );\n    > var it = iterExpm1( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.expm1, iterExp, iterExpm1rel\n","iterExpm1rel":"\niterExpm1rel( iterator )\n    Returns an iterator which iteratively evaluates the relative error\n    exponential.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -50.0, 50.0 );\n    > var it = iterExpm1rel( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.expm1rel, iterExp, iterExpm1\n","iterFactorial":"\niterFactorial( iterator )\n    Returns an iterator which iteratively evaluates the factorial function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterFactorial( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.factorial, iterFactorialln\n","iterFactorialln":"\niterFactorialln( iterator )\n    Returns an iterator which iteratively evaluates the natural logarithm of the\n    factorial function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterFactorialln( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.factorialln, iterFactorial\n","iterFactorialsSeq":"\niterFactorialsSeq( [options] )\n    Returns an iterator which generates a sequence of factorials.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterFactorialsSeq();\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    1\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    iterFactorial\n","iterFibonacciSeq":"\niterFibonacciSeq( [options] )\n    Returns an iterator which generates a Fibonacci sequence.\n\n    The returned iterator can only generate the first 79 Fibonacci numbers, as\n    larger Fibonacci numbers cannot be safely represented in double-precision\n    floating-point format.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 79.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterFibonacciSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n\n    See Also\n    --------\n    base.fibonacci, iterLucasSeq, iterNegaFibonacciSeq, iterNonFibonacciSeq\n","iterFifthPowersSeq":"\niterFifthPowersSeq( [options] )\n    Returns an iterator which generates a sequence of fifth powers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 9741.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterFifthPowersSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().value\n    32\n\n    See Also\n    --------\n    iterCubesSeq, iterFourthPowersSeq, iterSquaresSeq\n","iterFill":"\niterFill( iterator, value[, begin[, end]] )\n    Returns an iterator which replaces all values from a provided iterator from\n    a start index to an end index with a static value.\n\n    If `end` exceeds the length of the provided iterator, the returned iterator\n    replaces the subsequence of iterated values starting from `begin` until the\n    last iterated value of the provided iterator.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    value: any\n        Static value.\n\n    begin: integer (optional)\n        Start iteration index (zero-based and inclusive). Default: 0.\n\n    end: integer (optional)\n        End iteration index (zero-based and non-inclusive).\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterFill( random.iterators.randu(), 3.14, 0, 2 );\n    > var r = it.next().value\n    3.14\n    > r = it.next().value\n    3.14\n    > r = it.next().value\n    <number>\n\n","iterFilter":"\niterFilter( iterator, predicate[, thisArg] )\n    Returns an iterator which filters a provided iterator's values according to\n    a predicate function.\n\n    When invoked, the predicate function is provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index (zero-based).\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    predicate: Function\n        Predicate function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > function f( v ) { return ( v > 2 ); };\n    > var it1 = array2iterator( [ 1, 3, 2, 4 ] );\n    > var it2 = iterFilter( it1, f );\n    > var v = it2.next().value\n    3\n    > v = it2.next().value\n    4\n\n    See Also\n    --------\n    iterFilterMap, iterMap, iterReject\n","iterFilterMap":"\niterFilterMap( iterator, fcn[, thisArg] )\n    Returns an iterator which both filters and maps a provided iterator's\n    values.\n\n    When invoked, the callback function is provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index (zero-based).\n\n    If the callback returns `undefined`, the iterator invokes the function for\n    the next value of the provided iterator; otherwise, the iterator returns\n    the callback's return value.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    fcn: Function\n        Callback function which both filters and maps.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > function f( v ) { if ( v > 2 ) { return v * 10 }; };\n    > var it1 = array2iterator( [ 1, 3, 2, 4 ] );\n    > var it2 = iterFilterMap( it1, f );\n    > var v = it2.next().value\n    30\n    > v = it2.next().value\n    40\n\n    See Also\n    --------\n    iterFilter, iterMap\n","iterFirst":"\niterFirst( iterator )\n    Returns the first iterated value.\n\n    The function does *not* consume an entire iterator before returning.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    Returns\n    -------\n    v: any\n        The first iterated value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1, 0, 0, 0, 0 ] );\n    > var v = iterFirst( arr )\n    1\n\n    See Also\n    --------\n    iterHead, iterLast, iterNth\n","iterFlatTopPulse":"\niterFlatTopPulse( [options] )\n    Returns an iterator which generates a flat top pulse waveform.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Pulse period (i.e., the number of iterations until a waveform repeats).\n        Default: 100.\n\n    options.duration: integer (optional)\n        Pulse duration. Must be greater than 2. Default: options.period.\n\n    options.amplitude: number (optional)\n        Amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterFlatTopPulse();\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterPulse\n","iterFloor":"\niterFloor( iterator )\n    Returns an iterator which rounds each iterated value toward negative\n    infinity.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterFloor( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.floor, iterCeil, iterRound\n","iterFloor2":"\niterFloor2( iterator )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    two toward negative infinity.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterFloor2( random.iterators.uniform( -100.0, 100.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.floor2, iterCeil2, iterFloor, iterFloor10, iterRound2\n","iterFloor10":"\niterFloor10( iterator )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    10 toward negative infinity.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterFloor10( random.iterators.uniform( -100.0, 100.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.floor10, iterCeil10, iterFloor, iterFloor2, iterRound10\n","iterFlow":"\niterFlow( methods )\n    Returns a fluent interface iterator constructor with a customized prototype\n    based on provided methods.\n\n    The methods argument should be an object which maps constructor method names\n    to iterator functions.\n\n    Each iterator function should have the following function signature:\n\n      iterFcn( iterator, ...args )\n\n    When a fluent interface iterator method is invoked, the method invokes the\n    corresponding iterator function with an iterator and provided method\n    arguments.\n\n    If an iterator function returns an iterator, the corresponding fluent\n    interface method returns a new fluent interface instance; otherwise, the\n    corresponding fluent interface method returns the iterator function result.\n\n    The iterator function evaluation context is always `null`.\n\n    Iterator functions which return iterators are expected to return iterator\n    protocol-compliant objects (i.e., an object having a `next` method which\n    returns the next iterated value (if one exists) assigned to a `value`\n    property and a `done` property having a boolean value indicating whether the\n    iterator is finished).\n\n    If an environment supports `Symbol.iterator`, the returned constructor\n    returns iterators which are iterable.\n\n    Parameters\n    ----------\n    methods: Object\n        An object mapping method names to iterator functions.\n\n    Returns\n    -------\n    FluentIterator: Function\n        Fluent interface iterator constructor.\n\n    Examples\n    --------\n    > var o = {};\n    > o.head = iterHead;\n    > o.some = iterSome;\n    > var fiter = iterFlow( o )\n\n\nFluentIterator( iterator )\n    Returns a new fluent interface iterator from a source iterator.\n\n    Parameters\n    ----------\n    iterator: Object\n        Source iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Fluent interface iterator.\n\n    Examples\n    --------\n    > var o = {};\n    > o.head = iterHead;\n    > o.some = iterSome;\n    > var fiter = iterFlow( o );\n    > var it = fiter( array2iterator( [ 0, 0, 1, 1, 1 ] ) );\n    > var bool = it.head( 3 ).some( 2 )\n    false\n\n\nFluentIterator.prototype.next()\n    Returns the next iterated value.\n\n    Returns\n    -------\n    out: Object\n        Iterator protocol-compliant object.\n\n    out.value: any (optional)\n        Next iterated value (if one exists).\n\n    out.done: boolean\n        Boolean flag indicating whether the iterator is finished.\n\n    Examples\n    --------\n    > var o = {};\n    > o.head = iterHead;\n    > o.some = iterSome;\n    > var fiter = iterFlow( o );\n    > var it1 = fiter( array2iterator( [ 0, 0, 1, 1, 1 ] ) );\n    > var it2 = it1.head( 3 );\n    > var v = it2.next().value\n    0\n    > v = it2.next().value\n    0\n    > v = it2.next().value\n    1\n\n\nFluentIterator.prototype.return( [value] )\n    Finishes an iterator and returns a provided value.\n\n    Parameters\n    ----------\n    value: any (optional)\n        Value to return.\n\n    Returns\n    -------\n    out: Object\n        Iterator protocol-compliant object.\n\n    out.value: any (optional)\n        Next iterated value (if one exists).\n\n    out.done: boolean\n        Boolean flag indicating whether the iterator is finished.\n\n    Examples\n    --------\n    > var o = {};\n    > o.head = iterHead;\n    > o.some = iterSome;\n    > var fiter = iterFlow( o );\n    > var it1 = fiter( array2iterator( [ 0, 0, 1, 1, 1 ] ) );\n    > var it2 = it1.head( 3 );\n    > var v = it2.next().value\n    0\n    > var bool = it2.return().done\n    true\n    > v = it2.next().value\n    undefined\n\n    See Also\n    --------\n    iterPipeline\n","iterForEach":"\niterForEach( iterator, fcn[, thisArg] )\n    Returns an iterator which invokes a function for each iterated value before\n    returning the iterated value.\n\n    When invoked, the input function is provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index (zero-based).\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    fcn: Function\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n    > var it = iterForEach( random.iterators.randu(), f );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterMap\n","iterFourthPowersSeq":"\niterFourthPowersSeq( [options] )\n    Returns an iterator which generates a sequence of fourth powers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 9741.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterFourthPowersSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().value\n    16\n\n    See Also\n    --------\n    iterCubesSeq, iterFifthPowersSeq, iterSquaresSeq\n","iterFresnelc":"\niterFresnelc( iterator )\n    Returns an iterator which iteratively computes the Fresnel integral C(x).\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 10.0 );\n    > var it = iterFresnelc( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.fresnelc, iterFresnels\n","iterFresnels":"\niterFresnels( iterator )\n    Returns an iterator which iteratively computes the Fresnel integral S(x).\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 10.0 );\n    > var it = iterFresnels( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.fresnels, iterFresnelc\n","iterGamma":"\niterGamma( iterator )\n    Returns an iterator which iteratively evaluates the gamma function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterGamma( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.gamma, iterGamma1pm1, iterGammaln\n","iterGamma1pm1":"\niterGamma1pm1( iterator )\n    Returns an iterator which iteratively computes `gamma(x+1) - 1` without\n    cancellation errors for small `x`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -5.0, 5.0 );\n    > var it = iterGamma1pm1( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.gamma1pm1, iterGamma\n","iterGammaln":"\niterGammaln( iterator )\n    Returns an iterator which iteratively evaluates the natural logarithm of the\n    gamma function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterGammaln( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.gammaln, iterGamma\n","iterHacovercos":"\niterHacovercos( iterator )\n    Returns an iterator which iteratively computes the half-value coversed\n    cosine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 6.28 );\n    > var it = iterHacovercos( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.hacovercos, iterCovercos, iterHacoversin\n","iterHacoversin":"\niterHacoversin( iterator )\n    Returns an iterator which iteratively computes the half-value coversed sine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 6.28 );\n    > var it = iterHacoversin( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.hacoversin, iterCoversin, iterHacovercos\n","iterHannPulse":"\niterHannPulse( [options] )\n    Returns an iterator which generates a Hann pulse waveform.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Pulse period (i.e., the number of iterations until a waveform repeats).\n        Default: 100.\n\n    options.duration: integer (optional)\n        Pulse duration. Must be greater than 2. Default: options.period.\n\n    options.amplitude: number (optional)\n        Amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterHannPulse();\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterBartlettHannPulse, iterPulse, iterSineWave\n","iterHavercos":"\niterHavercos( iterator )\n    Returns an iterator which iteratively computes the half-value versed cosine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 6.28 );\n    > var it = iterHavercos( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.havercos, iterHaversin, iterVercos\n","iterHaversin":"\niterHaversin( iterator )\n    Returns an iterator which iteratively computes the half-value versed sine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 6.28 );\n    > var it = iterHaversin( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.haversin, iterHavercos, iterVersin\n","iterHead":"\niterHead( iterator, n )\n    Returns an iterator which returns the first `n` values of a provided\n    iterator.\n\n    If a provided iterator only generates `m` values and `m` is less than `n`,\n    the returned iterator only returns `m` values.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    n: integer\n        Number of values.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterHead( random.iterators.randu(), 5 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterFirst, iterSlice\n","iterIncrspace":"\niterIncrspace( start, stop[, increment] )\n    Returns an iterator which returns evenly spaced numbers according to a\n    specified increment.\n\n    Beware that values which follow the starting value are subject to floating-\n    point rounding errors.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    start: number\n        Starting value (inclusive).\n\n    stop: number\n        Stopping value (exclusive).\n\n    increment: number (optional)\n        Increment. Default: 1.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterIncrspace( 0, 101, 2 );\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    iterator2array, iterDatespace, iterLinspace, iterLogspace, iterStep, iterUnitspace\n","iterIntegersSeq":"\niterIntegersSeq( [options] )\n    Returns an iterator which generates an interleaved integer sequence.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 18014398509481984.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterIntegersSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().value\n    -1\n\n    See Also\n    --------\n    iterNegativeIntegersSeq, iterNonNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterPositiveIntegersSeq\n","iterIntersection":"\niterIntersection( iter0, ...iterator )\n    Returns an iterator which returns the intersection of two or more iterators.\n\n    Value \"uniqueness\" is determined according to strict equality.\n\n    A returned iterator internally buffers unique values and, thus, has O(N)\n    memory requirements, where `N` is the length of the first iterator.\n\n    Do *not* provide iterators having infinite length.\n\n    If an environment supports Symbol.iterator and all provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iter0: Object\n        Input iterator.\n\n    iterator: ...Object\n        Input iterators.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n    > var it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\n    > var it = iterIntersection( it1, it2 );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    2\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterIntersectionByHash, iterUnion, iterUnique\n","iterIntersectionByHash":"\niterIntersectionByHash( iter0, ...iterator, hashFcn[, thisArg] )\n    Returns an iterator which returns the intersection of two or more iterators\n    according to a hash function.\n\n    An iterated value is considered \"unique\" if the hash function returns a\n    unique hash value for that iterated value. Beware that this *may* result in\n    unexpected behavior. Namely, only the first iterated value mapping to a\n    particular hash function result is returned, even if subsequent values,\n    while mapping to the same hash, are different. Accordingly, iteration order\n    *does* matter.\n\n    A returned iterator internally buffers unique hashes, along with the *first*\n    iterated value resolving to a hash, and, thus, has O(N) memory requirements,\n    where `N` is the length of the first iterator.\n\n    Do *not* provide iterators having infinite length.\n\n    If an environment supports Symbol.iterator and all provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iter0: Object\n        Input iterator.\n\n    iterator: ...Object\n        Input iterators.\n\n    hashFcn: Function\n        Hash function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n    > var it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\n    > function f( v ) { return v.toString(); };\n    > var it = iterIntersectionByHash( it1, it2, f );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    2\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterIntersection, iterUniqueByHash\n","iterInv":"\niterInv( iterator )\n    Returns an iterator which iteratively computes the multiplicative inverse.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterInv( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.inv, iterPow\n","iterLanczosPulse":"\niterLanczosPulse( [options] )\n    Returns an iterator which generates a Lanczos pulse waveform.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Pulse period (i.e., the number of iterations until a waveform repeats).\n        Default: 100.\n\n    options.duration: integer (optional)\n        Pulse duration. Must be greater than 2. Default: options.period.\n\n    options.amplitude: number (optional)\n        Amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterLanczosPulse();\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterPulse, iterPeriodicSinc\n","iterLast":"\niterLast( iterator )\n    Consumes an entire iterator and returns the last iterated value.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    Returns\n    -------\n    v: any\n        The last iterated value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n    > var v = iterLast( arr )\n    1\n\n    See Also\n    --------\n    iterFirst, iterNth\n","iterLength":"\niterLength( iterator )\n    Consumes an entire iterator and returns the number of iterated values.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    Returns\n    -------\n    len: integer\n        Iterator length.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n    > var len = iterLength( arr )\n    5\n\n    See Also\n    --------\n    iterCounter\n","iterLinspace":"\niterLinspace( start, stop[, N] )\n    Returns an iterator which returns evenly spaced numbers over a specified\n    interval.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    start: number\n        Starting value (inclusive).\n\n    stop: number\n        Stopping value (inclusive).\n\n    N: integer (optional)\n        Number of values. Default: 100.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterLinspace( 0, 99, 100 );\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n\n    See Also\n    --------\n    iterator2array, iterDatespace, iterIncrspace, iterLogspace, iterStep, iterUnitspace\n","iterLn":"\niterLn( iterator )\n    Returns an iterator which iteratively evaluates the natural logarithm.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterLn( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.ln, iterExp, iterLog10, iterLog1p, iterLog2\n","iterLog":"\niterLog( x, b )\n    Returns an iterator which iteratively computes the base `b` logarithm.\n\n    For negative `b` or `x` iterated values, the returned iterator returns\n    `NaN`.\n\n    The length of the returned iterator is equal to the length of the shortest\n    provided iterator. In other words, the returned iterator ends once *one* of\n    the provided iterators ends.\n\n    If provided a numeric value as an iterator argument, the value is broadcast\n    as an infinite iterator which always returns the provided value.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    x: Object|number\n        Input iterator.\n\n    b: Object|number\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = random.iterators.uniform( 0.0, 100.0 );\n    > var y = random.iterators.uniform( 0.0, 10.0 );\n    > var it = iterLog( x, y );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.log, iterLog10, iterLog1p, iterLog2, iterPow\n","iterLog1mexp":"\niterLog1mexp( iterator )\n    Returns an iterator which iteratively evaluates the natural logarithm of\n    `1-exp(-|x|)`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterLog1mexp( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.log1mexp, iterLog, iterLog1p, iterLog1pexp, iterPow\n","iterLog1p":"\niterLog1p( iterator )\n    Returns an iterator which iteratively evaluates the natural logarithm of\n    `1+x`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterLog1p( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.log1p, iterLog, iterLog10, iterLog2, iterPow\n","iterLog1pexp":"\niterLog1pexp( iterator )\n    Returns an iterator which iteratively evaluates the natural logarithm of\n    `1+exp(x)`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterLog1pexp( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.log1pexp, iterLog, iterLog1p, iterLog1mexp, iterPow\n","iterLog2":"\niterLog2( iterator )\n    Returns an iterator which iteratively evaluates the binary logarithm.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterLog2( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.log2, iterLog, iterLog10, iterLog1p, iterPow\n","iterLog10":"\niterLog10( iterator )\n    Returns an iterator which iteratively evaluates the common logarithm\n    (logarithm with base 10).\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterLog10( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.log10, iterLog, iterLog1p, iterLog2, iterPow\n","iterLogit":"\niterLogit( iterator )\n    Returns an iterator which iteratively evaluates the logit function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 1.0 );\n    > var it = iterLogit( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.logit\n","iterLogspace":"\niterLogspace( start, stop[, N][, options] )\n    Returns an iterator which returns evenly spaced numbers on a log scale.\n\n    In linear space, the sequence starts at `base` raised to the power of\n    `start` and ends with `base` raised to the power of `stop`.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    start: number\n        Exponent of starting value.\n\n    stop: number\n        Exponent of stopping value.\n\n    N: integer (optional)\n        Number of values. Default: 100.\n\n    options: Object (optional)\n        Function options.\n\n    options.base: number (optional)\n        Base of log space. Default: 10.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterLogspace( 0, 3, 4 );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    10\n\n    See Also\n    --------\n    iterator2array, iterDatespace, iterIncrspace, iterLinspace, iterStep\n","iterLucasSeq":"\niterLucasSeq( [options] )\n    Returns an iterator which generates a Lucas sequence.\n\n    The returned iterator can only generate the first 77 Lucas numbers, as\n    larger Lucas numbers cannot be safely represented in double-precision\n    floating-point format.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 77.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterLucasSeq();\n    > var v = it.next().value\n    2\n    > v = it.next().value\n    1\n\n    See Also\n    --------\n    base.lucas, iterFibonacciSeq, iterNegaLucasSeq\n","iterMap":"\niterMap( iterator, fcn[, thisArg] )\n    Returns an iterator which invokes a function for each iterated value.\n\n    When invoked, the input function is provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index (zero-based).\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    fcn: Function\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > function f( v ) { return v * 10.0; };\n    > var it = iterMap( random.iterators.randu(), f );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterFilter, iterFilterMap, iterForEach, iterReject\n","iterMapN":"\niterMapN( iter0, ...iterator, fcn[, thisArg] )\n    Returns an iterator which transforms iterated values from two or more\n    iterators by applying the iterated values as arguments to a provided\n    function.\n\n    When invoked, the callback function is provided `N+1` arguments, where `N`\n    is the number of provided iterators and the last argument is the iteration\n    index:\n\n    - ...value: iterated values.\n    - index: iteration index (zero-based).\n\n    The length of the returned iterator is equal to the length of the shortest\n    provided iterator. In other words, the returned iterator ends once *one* of\n    the provided iterators ends.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iter0: Object\n        Input iterator.\n\n    iterator: ...Object\n        Iterators.\n\n    fcn: Function\n        Function to invoke with iterated values.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1.0, 2.0 ] );\n    > var it2 = array2iterator( [ 3.0, 4.0 ] );\n    > function fcn( x, y ) { return x + y; };\n    > var it = iterMapN( it1, it2, fcn );\n    > var v = it.next().value\n    4.0\n    > v = it.next().value\n    6.0\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterMap\n","itermax":"\nitermax( iterator )\n    Computes the maximum value of all iterated values.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Maximum value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var m = itermax( arr )\n    3.0\n\n    See Also\n    --------\n    itermidrange, itermin, itermmax, iterrange\n","itermaxabs":"\nitermaxabs( iterator )\n    Computes the maximum absolute value of all iterated values.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Maximum absolute value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var m = itermaxabs( arr )\n    4.0\n\n    See Also\n    --------\n    itermax, iterminabs, itermmaxabs\n","itermean":"\nitermean( iterator )\n    Computes an arithmetic mean over all iterated values.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Arithmetic mean.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var m = itermean( arr )\n    2.5\n\n    See Also\n    --------\n    itermidrange, itermmean, iterstdev, itersum, itervariance\n","itermeanabs":"\nitermeanabs( iterator )\n    Computes an arithmetic mean of absolute values for all iterated values.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Arithmetic mean of absolute values.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\n    > var m = itermeanabs( arr )\n    2.5\n\n    See Also\n    --------\n    itermean, itermmeanabs, itersumabs\n","itermeanabs2":"\nitermeanabs2( iterator )\n    Computes an arithmetic mean of squared absolute values for all iterated\n    values.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Arithmetic mean of squared absolute values.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\n    > var m = itermeanabs2( arr )\n    7.5\n\n    See Also\n    --------\n    itermean, itermeanabs, itermmeanabs2, itersumabs2\n","itermidrange":"\nitermidrange( iterator )\n    Computes the mid-range of all iterated values.\n\n    The mid-range is the arithmetic mean of maximum and minimum values.\n    Accordingly, the mid-range is the midpoint of the range and a measure of\n    central tendency.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Mid-range.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var v = itermidrange( arr )\n    -0.5\n\n    See Also\n    --------\n    itermean, itermax, itermin, iterrange\n","itermin":"\nitermin( iterator )\n    Computes the minimum value of all iterated values.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Minimum value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1.0, -2.0, -3.0, 4.0 ] );\n    > var m = itermin( arr )\n    -3.0\n\n    See Also\n    --------\n    itermax, itermidrange, itermmin, iterrange\n","iterminabs":"\niterminabs( iterator )\n    Computes the minimum absolute value of all iterated values.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Minimum absolute value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var m = iterminabs( arr )\n    1.0\n\n    See Also\n    --------\n    itermaxabs, itermin, itermminabs\n","itermmax":"\nitermmax( iterator, W )\n    Returns an iterator which iteratively computes a moving maximum value.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving maximum value.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermmax( arr, 3 );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    2.0\n    > m = it.next().value\n    3.0\n    > m = it.next().value\n    5.0\n\n    See Also\n    --------\n    itermax, itermmidrange, itermmin, itermrange\n","itermmaxabs":"\nitermmaxabs( iterator, W )\n    Returns an iterator which iteratively computes a moving maximum absolute\n    value.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving maximum absolute value.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermmaxabs( arr, 3 );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    5.0\n    > m = it.next().value\n    5.0\n    > m = it.next().value\n    5.0\n\n    See Also\n    --------\n    itermaxabs, itermmax, itermminabs\n","itermmean":"\nitermmean( iterator, W )\n    Returns an iterator which iteratively computes a moving arithmetic mean.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving mean.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermmean( arr, 3 );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    -1.5\n    > m = it.next().value\n    0.0\n    > m = it.next().value\n    1.0\n\n    See Also\n    --------\n    itermean, itermsum\n","itermmeanabs":"\nitermmeanabs( iterator, W )\n    Returns an iterator which iteratively computes a moving arithmetic mean of\n    absolute values.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving mean of absolute values.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermmeanabs( arr, 3 );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    3.5\n    > m = it.next().value\n    ~3.33\n    > m = it.next().value\n    ~4.33\n\n    See Also\n    --------\n    itermeanabs, itermmean, itermsumabs\n","itermmeanabs2":"\nitermmeanabs2( iterator, W )\n    Returns an iterator which iteratively computes a moving arithmetic mean of\n    squared absolute values.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving mean of squared absolute values.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermmeanabs2( arr, 3 );\n    > var m = it.next().value\n    4.0\n    > m = it.next().value\n    14.5\n    > m = it.next().value\n    ~12.67\n    > m = it.next().value\n    ~19.67\n\n    See Also\n    --------\n    itermeanabs2, itermmeanabs, itermsumabs2\n","itermmidrange":"\nitermmidrange( iterator, W )\n    Returns an iterator which iteratively computes a moving mid-range.\n\n    The mid-range is the arithmetic mean of maximum and minimum values.\n    Accordingly, the mid-range is the midpoint of the range and a measure of\n    central tendency.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving mid-range.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermmidrange( arr, 3 );\n    > var v = it.next().value\n    2.0\n    > v = it.next().value\n    -1.5\n    > v = it.next().value\n    -1.0\n    > v = it.next().value\n    0.0\n\n    See Also\n    --------\n    itermidrange, itermmean, itermmax, itermmin, itermrange\n","itermmin":"\nitermmin( iterator, W )\n    Returns an iterator which iteratively computes a moving minimum value.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving minimum value.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermmin( arr, 3 );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    -5.0\n    > m = it.next().value\n    -5.0\n    > m = it.next().value\n    -5.0\n\n    See Also\n    --------\n    itermin, itermmax, itermmidrange, itermrange\n","itermminabs":"\nitermminabs( iterator, W )\n    Returns an iterator which iteratively computes a moving minimum absolute\n    value.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving minimum absolute value.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermminabs( arr, 3 );\n    > var m = it.next().value\n    2.0\n    > m = it.next().value\n    2.0\n    > m = it.next().value\n    2.0\n    > m = it.next().value\n    3.0\n\n    See Also\n    --------\n    iterminabs, itermmaxabs, itermmin\n","iterMod":"\niterMod( iter0, ...iterator )\n    Returns an iterator which performs an element-wise modulo operation of two\n    or more iterators.\n\n    The length of the returned iterator is equal to the length of the shortest\n    provided iterator. In other words, the returned iterator ends once *one* of\n    the provided iterators ends.\n\n    If provided a numeric value as an iterator argument, the value is broadcast\n    as an infinite iterator which always returns the provided value.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iter0: Object\n        Input iterator.\n\n    iterator: ...Object\n        Iterators whose values are used as divisors.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 3.0, 2.0 ] );\n    > var it2 = array2iterator( [ 1.0, 4.0 ] );\n    > var it = iterMod( it1, it2 );\n    > var v = it.next().value\n    0.0\n    > v = it.next().value\n    2.0\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterDivide\n","itermprod":"\nitermprod( iterator, W )\n    Returns an iterator which iteratively computes a moving product.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving product.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermprod( arr, 3 );\n    > var p = it.next().value\n    2.0\n    > p = it.next().value\n    -10.0\n    > p = it.next().value\n    -30.0\n    > p = it.next().value\n    -75.0\n\n    See Also\n    --------\n    itermsum, iterprod\n","itermrange":"\nitermrange( iterator, W )\n    Returns an iterator which iteratively computes a moving range.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving range.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermrange( arr, 3 );\n    > var m = it.next().value\n    0.0\n    > m = it.next().value\n    7.0\n    > m = it.next().value\n    8.0\n    > m = it.next().value\n    10.0\n\n    See Also\n    --------\n    itermmax, itermmean, itermmin, iterrange\n","itermsum":"\nitermsum( iterator, W )\n    Returns an iterator which iteratively computes a moving sum.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving sum.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator and the provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermsum( arr, 3 );\n    > var s = it.next().value\n    2.0\n    > s = it.next().value\n    -3.0\n    > s = it.next().value\n    0.0\n    > s = it.next().value\n    3.0\n\n    See Also\n    --------\n    itermmean, itersum\n","itermsumabs":"\nitermsumabs( iterator, W )\n    Returns an iterator which iteratively computes a moving sum of absolute\n    values.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving sum.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermsumabs( arr, 3 );\n    > var s = it.next().value\n    2.0\n    > s = it.next().value\n    7.0\n    > s = it.next().value\n    10.0\n    > s = it.next().value\n    13.0\n\n    See Also\n    --------\n    itermmeanabs, itermsum, itersum, itersumabs\n","itermsumabs2":"\nitermsumabs2( iterator, W )\n    Returns an iterator which iteratively computes a moving sum of squared\n    absolute values.\n\n    The `W` parameter defines the number of iterated values over which to\n    compute the moving sum.\n\n    As `W` values are needed to fill the window buffer, the first `W-1` returned\n    values are calculated from smaller sample sizes. Until the window is full,\n    each returned value is calculated from all previously iterated values.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    W: integer\n        Window size.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0, 3.0, 5.0 ] );\n    > var it = itermsumabs2( arr, 3 );\n    > var s = it.next().value\n    4.0\n    > s = it.next().value\n    29.0\n    > s = it.next().value\n    38.0\n    > s = it.next().value\n    59.0\n\n    See Also\n    --------\n    itermmeanabs2, itermsumabs, itersumabs, itersumabs2\n","iterMultiply":"\niterMultiply( iter0, ...iterator )\n    Returns an iterator which performs element-wise multiplication of two or\n    more iterators.\n\n    The length of the returned iterator is equal to the length of the shortest\n    provided iterator. In other words, the returned iterator ends once *one* of\n    the provided iterators ends.\n\n    If provided a numeric value as an iterator argument, the value is broadcast\n    as an infinite iterator which always returns the provided value.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iter0: Object\n        Input iterator.\n\n    iterator: ...Object\n        Iterators to multiply.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1.0, 2.0 ] );\n    > var it2 = array2iterator( [ 3.0, 4.0 ] );\n    > var it = iterMultiply( it1, it2 );\n    > var v = it.next().value\n    3.0\n    > v = it.next().value\n    8.0\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterAdd, iterDivide, iterSubtract\n","iterNegaFibonacciSeq":"\niterNegaFibonacciSeq( [options] )\n    Returns an iterator which generates a negaFibonacci sequence.\n\n    The returned iterator can only generate the first 79 negaFibonacci numbers,\n    as larger negaFibonacci numbers cannot be safely represented in double-\n    precision floating-point format.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 79.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterNegaFibonacciSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n\n    See Also\n    --------\n    base.negafibonacci, iterFibonacciSeq, iterNonFibonacciSeq\n","iterNegaLucasSeq":"\niterNegaLucasSeq( [options] )\n    Returns an iterator which generates a negaLucas sequence.\n\n    The returned iterator can only generate the first 77 negaLucas numbers, as\n    larger negaLucas numbers cannot be safely represented in double-precision\n    floating-point format.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 77.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterNegaLucasSeq();\n    > var v = it.next().value\n    2\n    > v = it.next().value\n    -1\n\n    See Also\n    --------\n    base.negalucas, iterLucasSeq, iterNegaFibonacciSeq\n","iterNegativeEvenIntegersSeq":"\niterNegativeEvenIntegersSeq( [options] )\n    Returns an iterator which generates a sequence of negative even integers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 4503599627370496.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterNegativeEvenIntegersSeq();\n    > var v = it.next().value\n    -2\n    > v = it.next().value\n    -4\n\n    See Also\n    --------\n    iterEvenIntegersSeq, iterIntegersSeq, iterNegativeIntegersSeq, iterNegativeOddIntegersSeq, iterPositiveEvenIntegersSeq, iterNonPositiveEvenIntegersSeq\n","iterNegativeIntegersSeq":"\niterNegativeIntegersSeq( [options] )\n    Returns an iterator which generates a negative integer sequence.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 9007199254740991.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterNegativeIntegersSeq();\n    > var v = it.next().value\n    -1\n    > v = it.next().value\n    -2\n\n    See Also\n    --------\n    iterIntegersSeq, iterNonNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterPositiveIntegersSeq\n","iterNegativeOddIntegersSeq":"\niterNegativeOddIntegersSeq( [options] )\n    Returns an iterator which generates a sequence of negative odd integers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 4503599627370496.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterNegativeOddIntegersSeq();\n    > var v = it.next().value\n    -1\n    > v = it.next().value\n    -3\n\n    See Also\n    --------\n    iterOddIntegersSeq, iterIntegersSeq, iterNegativeIntegersSeq, iterNegativeEvenIntegersSeq, iterPositiveOddIntegersSeq\n","iterNone":"\niterNone( iterator )\n    Tests whether all iterated values are falsy.\n\n    The function immediately returns upon encountering a truthy value.\n\n    If provided an iterator which does not return any iterated values, the\n    function returns `true`.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `false` if a value is truthy; otherwise, the\n        function returns `true`.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 0, 0, 0, 0, 1 ] );\n    > var bool = iterNone( arr )\n    false\n\n    See Also\n    --------\n    iterAny, iterEvery, iterForEach, iterNoneBy, iterSome\n","iterNoneBy":"\niterNoneBy( iterator, predicate[, thisArg ] )\n    Tests whether every iterated value fails a test implemented by a predicate\n    function.\n\n    The predicate function is provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index.\n\n    The function immediately returns upon encountering a truthy return value.\n\n    If provided an iterator which does not return any iterated values, the\n    function returns `true`.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if a predicate function returns a falsy\n        value for all iterated values. Otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1, 1, 1, 1, 1 ] );\n    > function fcn( v ) { return ( v <= 0 ); };\n    > var bool = iterNoneBy( arr, fcn )\n    true\n\n    See Also\n    --------\n    iterAnyBy, iterEveryBy, iterForEach, iterNone, iterSomeBy\n","iterNonFibonacciSeq":"\niterNonFibonacciSeq( [options] )\n    Returns an iterator which generates a non-Fibonacci integer sequence.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterNonFibonacciSeq();\n    > var v = it.next().value\n    4\n    > v = it.next().value\n    6\n\n    See Also\n    --------\n    base.nonfibonacci, iterFibonacciSeq\n","iterNonNegativeEvenIntegersSeq":"\niterNonNegativeEvenIntegersSeq( [options] )\n    Returns an iterator which generates a sequence of nonnegative even integers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 4503599627370497.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterNonNegativeEvenIntegersSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    iterEvenIntegersSeq, iterIntegersSeq, iterNonNegativeIntegersSeq, iterNonPositiveEvenIntegersSeq, iterPositiveEvenIntegersSeq\n","iterNonNegativeIntegersSeq":"\niterNonNegativeIntegersSeq( [options] )\n    Returns an iterator which generates a nonnegative integer sequence.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 9007199254740992.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterNonNegativeIntegersSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n\n    See Also\n    --------\n    iterIntegersSeq, iterNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterPositiveIntegersSeq\n","iterNonPositiveEvenIntegersSeq":"\niterNonPositiveEvenIntegersSeq( [options] )\n    Returns an iterator which generates a sequence of nonpositive even integers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 4503599627370497.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterNonPositiveEvenIntegersSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    -2\n\n    See Also\n    --------\n    iterEvenIntegersSeq, iterIntegersSeq, iterNonNegativeEvenIntegersSeq, iterNonPositiveIntegersSeq, iterNegativeEvenIntegersSeq\n","iterNonPositiveIntegersSeq":"\niterNonPositiveIntegersSeq( [options] )\n    Returns an iterator which generates a nonpositive integer sequence.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 9007199254740992.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterNonPositiveIntegersSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    -1\n\n    See Also\n    --------\n    iterIntegersSeq, iterNegativeIntegersSeq, iterNonNegativeIntegersSeq, iterPositiveIntegersSeq\n","iterNonSquaresSeq":"\niterNonSquaresSeq( [options] )\n    Returns an iterator which generates a sequence of nonsquares.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 9007199349647256.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterNonSquaresSeq();\n    > var v = it.next().value\n    2\n    > v = it.next().value\n    3\n    > v = it.next().value\n    5\n\n    See Also\n    --------\n    iterCubesSeq, iterSquaresSeq\n","iterNth":"\niterNth( iterator, n )\n    Returns the nth iterated value.\n\n    If `n` exceeds the total number of iterations, the function returns\n    `undefined`.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    n: integer\n        Iteration number.\n\n    Returns\n    -------\n    v: any\n        The nth iterated value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 0, 0, 1, 0, 0 ] );\n    > var v = iterNth( arr, 3 )\n    1\n\n    See Also\n    --------\n    iterFirst, iterLast\n","iterOddIntegersSeq":"\niterOddIntegersSeq( [options] )\n    Returns an iterator which generates an interleaved sequence of odd integers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 9007199254740992.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterOddIntegersSeq();\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    -1\n    > v = it.next().value\n    3\n\n    See Also\n    --------\n    iterEvenIntegersSeq, iterIntegersSeq\n","iterPeriodicSinc":"\niterPeriodicSinc( n[, options] )\n    Returns an iterator which generates a periodic sinc waveform.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    n: integer\n        Order.\n\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Period (i.e., the number of iterations before a waveform repeats).\n        Default: 100.\n\n    options.amplitude: number (optional)\n        Peak amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterPeriodicSinc( 7 );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterSineWave\n","iterPipeline":"\niterPipeline( iterFcn[, ...iterFcn] )\n    Returns an iterator pipeline.\n\n    Parameters\n    ----------\n    iterFcn: Function|Array\n        Iterator function or an array of iterator functions.\n\n    iterFcn: ...Function (optional)\n        Iterator functions.\n\n    Returns\n    -------\n    fcn( src ): Function\n        Iterator pipeline which accepts a single argument, a source iterator.\n\n    Examples\n    --------\n    > var it1 = iterThunk( iterHead, 100 );\n    > function f( r ) { return ( r > 0.95 ); };\n    > var it2 = iterThunk( iterSomeBy, 5, f );\n    > var p = iterPipeline( it1, it2 );\n    > var bool = p( random.iterators.randu() )\n    <boolean>\n\n    See Also\n    --------\n    iterFlow, iterThunk\n","iterPop":"\niterPop( iterator[, clbk[, thisArg]] )\n    Returns an iterator which skips the last value of a provided iterator.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    clbk: Function (optional)\n        Callback to invoke with the skipped value.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2 ] );\n    > var it2 = iterPop( it1 );\n    > var v = it2.next().value\n    1\n    > var bool = it2.next().done\n    true\n\n    See Also\n    --------\n    iterPush, iterShift, iterSlice\n","iterPositiveEvenIntegersSeq":"\niterPositiveEvenIntegersSeq( [options] )\n    Returns an iterator which generates a sequence of positive even integers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 4503599627370496.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterPositiveEvenIntegersSeq();\n    > var v = it.next().value\n    2\n    > v = it.next().value\n    4\n\n    See Also\n    --------\n    iterEvenIntegersSeq, iterIntegersSeq, iterNegativeEvenIntegersSeq, iterNonNegativeEvenIntegersSeq, iterPositiveIntegersSeq, iterPositiveOddIntegersSeq\n","iterPositiveIntegersSeq":"\niterPositiveIntegersSeq( [options] )\n    Returns an iterator which generates a positive integer sequence.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 9007199254740991.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterPositiveIntegersSeq();\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    iterNonNegativeIntegersSeq, iterNonPositiveIntegersSeq, iterNegativeIntegersSeq\n","iterPositiveOddIntegersSeq":"\niterPositiveOddIntegersSeq( [options] )\n    Returns an iterator which generates a sequence of positive odd integers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 4503599627370496.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterPositiveOddIntegersSeq();\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    3\n\n    See Also\n    --------\n    iterOddIntegersSeq, iterIntegersSeq, iterNegativeOddIntegersSeq, iterPositiveEvenIntegersSeq, iterPositiveIntegersSeq\n","iterPow":"\niterPow( base, exponent )\n    Returns an iterator which iteratively evaluates the exponential function.\n\n    The length of the returned iterator is equal to the length of the shortest\n    provided iterator. In other words, the returned iterator ends once *one* of\n    the provided iterators ends.\n\n    If provided a numeric value as an iterator argument, the value is broadcast\n    as an infinite iterator which always returns the provided value.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    base: Object|number\n        Input iterator.\n\n    exponent: Object|number\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = random.iterators.uniform( 0.0, 2.0 );\n    > var y = random.iterators.uniform( -2.0, 2.0 );\n    > var it = iterPow( x, y );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.pow, iterExp, iterLog\n","iterPrimesSeq":"\niterPrimesSeq( [options] )\n    Returns an iterator which generates a sequence of prime numbers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 245181918813464.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterPrimesSeq();\n    > var v = it.next().value\n    2\n    > v = it.next().value\n    3\n    > v = it.next().value\n    5\n\n    See Also\n    --------\n    iterCompositesSeq, iterIntegersSeq, iterPositiveIntegersSeq\n","iterprod":"\niterprod( iterator )\n    Computes the product of all iterated values.\n\n    For iterators which can generate many values or which may output large\n    numbers, care should be taken to prevent overflow.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Product.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var s = iterprod( arr )\n    24.0\n\n    See Also\n    --------\n    itermprod, itersum\n","iterPulse":"\niterPulse( [options] )\n    Returns an iterator which generates a pulse waveform.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Pulse period (i.e., the number of iterations until a waveform repeats).\n        Default: 10.\n\n    options.duration: integer (optional)\n        Pulse duration (i.e., the number of consecutive iterations of maximum\n        amplitude during one period). Default: floor(options.period/2).\n\n    options.min: number (optional)\n        Minimum amplitude. Default: 0.0.\n\n    options.max: number (optional)\n        Maximum amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterPulse();\n    > var v = it.next().value\n    1.0\n    > v = it.next().value\n    1.0\n\n    See Also\n    --------\n    iterSawtoothWave, iterSineWave, iterSquareWave, iterTriangleWave\n","iterPush":"\niterPush( iterator, ...items )\n    Returns an iterator which appends additional values to the end of a provided\n    iterator.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    items: ...any\n        Items to append.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2 ] );\n    > var it2 = iterPush( it1, 3, 4 );\n    > var v = it2.next().value\n    1\n    > v = it2.next().value\n    2\n    > v = it2.next().value\n    3\n    > v = it2.next().value\n    4\n    > var bool = it2.next().done\n    true\n\n    See Also\n    --------\n    iterConcat, iterUnshift\n","iterRad2deg":"\niterRad2deg( iterator )\n    Returns an iterator which iteratively converts an angle from radians to\n    degrees.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 6.28 );\n    > var it = iterRad2deg( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.rad2deg, iterDeg2rad\n","iterRamp":"\niterRamp( iterator )\n    Returns an iterator which iteratively evaluates the ramp function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterRamp( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.ramp\n","iterrange":"\niterrange( iterator )\n    Computes the range of all iterated values.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Range.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var v = iterrange( arr )\n    7.0\n\n    See Also\n    --------\n    itermax, itermean, itermin, itermrange\n","iterReject":"\niterReject( iterator, predicate[, thisArg] )\n    Returns an iterator which rejects a provided iterator's values according to\n    a predicate function.\n\n    When invoked, the predicate function is provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index (zero-based).\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    predicate: Function\n        Predicate function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > function f( v ) { return ( v > 2 ); };\n    > var it1 = array2iterator( [ 1, 3, 2, 4 ] );\n    > var it2 = iterReject( it1, f );\n    > var v = it2.next().value\n    1\n    > v = it2.next().value\n    2\n\n    See Also\n    --------\n    iterFilter, iterMap\n","iterReplicate":"\niterReplicate( iterator, n )\n    Returns an iterator which replicates each iterated value `n` times.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    n: integer\n        Number of times each iterated value is replicated.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2, 3, 4 ] );\n    > var it2 = iterReplicate( it1, 2 );\n    > var v = it2.next().value\n    1\n    > v = it2.next().value\n    1\n    > v = it2.next().value\n    2\n    > v = it2.next().value\n    2\n\n    See Also\n    --------\n    iterReplicateBy\n","iterReplicateBy":"\niterReplicateBy( iterator, fcn[, thisArg] )\n    Returns an iterator which replicates each iterated value according to a\n    provided function.\n\n    The callback function is provided three arguments:\n\n    - value: iterated value.\n    - index: source iteration index (zero-based).\n    - n: iteration index (zero-based).\n\n    The callback function is invoked *once* per iterated value of the provided\n    iterator.\n\n    The callback function *must* return an integer value. If the return value is\n    less than or equal to zero, the returned iterator skips an iterated value\n    and invokes the callback for the next iterated value of the provided\n    iterator.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    fcn: Function\n        Function which returns the number of times an iterated value should be\n        replicated.\n\n    thisArg: any (optional)\n        Callback function execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2, 3, 4 ] );\n    > function f( v, i ) { return i + 1; };\n    > var it2 = iterReplicateBy( it1, f );\n    > var v = it2.next().value\n    1\n    > v = it2.next().value\n    2\n    > v = it2.next().value\n    2\n    > v = it2.next().value\n    3\n    > v = it2.next().value\n    3\n    > v = it2.next().value\n    3\n    > v = it2.next().value\n    4\n\n    See Also\n    --------\n    iterReplicate\n","iterRound":"\niterRound( iterator )\n    Returns an iterator which rounds each iterated value to the nearest integer.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterRound( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.round, iterCeil, iterFloor, iterTrunc\n","iterRound2":"\niterRound2( iterator )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    two on a linear scale.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterRound2( random.iterators.uniform( -100.0, 100.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.round2, iterCeil2, iterFloor2, iterRound, iterRound10, iterTrunc2\n","iterRound10":"\niterRound10( iterator )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    10 on a linear scale.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterRound10( random.iterators.uniform( -100.0, 100.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.round10, iterCeil10, iterFloor10, iterRound, iterRound2, iterTrunc10\n","iterRsqrt":"\niterRsqrt( iterator )\n    Returns an iterator which iteratively computes the reciprocal (inverse)\n    square root.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterRsqrt( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.rsqrt, iterSqrt\n","iterSawtoothWave":"\niterSawtoothWave( [options] )\n    Returns an iterator which generates a sawtooth wave.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Period (i.e., the number of iterations before a waveform repeats).\n        Default: 10.\n\n    options.amplitude: number (optional)\n        Peak amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterSawtoothWave();\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterPulse, iterSineWave, iterSquareWave, iterTriangleWave\n","iterShift":"\niterShift( iterator[, clbk[, thisArg]] )\n    Returns an iterator which skips the first value of a provided iterator.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    clbk: Function (optional)\n        Callback to invoke with the skipped value.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2 ] );\n    > var it2 = iterShift( it1 );\n    > var v = it2.next().value\n    2\n    > var bool = it2.next().done\n    true\n\n    See Also\n    --------\n    iterPop, iterSlice, iterUnshift\n","iterSignum":"\niterSignum( iterator )\n    Returns an iterator which iteratively evaluates the signum function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterSignum( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.signum\n","iterSin":"\niterSin( iterator )\n    Returns an iterator which iteratively computes the sine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterSin( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.sin, iterCos, iterSinpi, iterTan\n","iterSinc":"\niterSinc( iterator )\n    Returns an iterator which iteratively computes the normalized cardinal sine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -5.0, 5.0 );\n    > var it = iterSinc( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.sinc, iterSin\n","iterSineWave":"\niterSineWave( [options] )\n    Returns an iterator which generates a sine wave.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Period (i.e., the number of iterations before a sine wave repeats).\n        Default: 10.\n\n    options.amplitude: number (optional)\n        Peak amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterSineWave();\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterCosineWave, iterPulse, iterSawtoothWave, iterSquareWave, iterTriangleWave\n","iterSinh":"\niterSinh( iterator )\n    Returns an iterator which iteratively evaluates the hyperbolic sine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -5.0, 5.0 );\n    > var it = iterSinh( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.sinh, iterCosh, iterTanh\n","iterSinpi":"\niterSinpi( iterator )\n    Returns an iterator which computes the sine of each iterated value times π.\n\n    Computes sin(πx) more accurately than sin(pi*x), especially for large x.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterSinpi( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.sinpi, iterSin\n","iterSlice":"\niterSlice( iterator[, begin[, end]] )\n    Returns an iterator which returns a subsequence of iterated values from a\n    provided iterator.\n\n    If `end` exceeds the length of the provided iterator, the returned iterator\n    returns the subsequence of iterated values starting from `begin` until the\n    last iterated value of the provided iterator.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    begin: integer (optional)\n        Start iteration index (zero-based and inclusive). Default: 0.\n\n    end: integer (optional)\n        End iteration index (zero-based and non-inclusive).\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterSlice( random.iterators.randu(), 5, 10 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterFirst, iterHead\n","iterSome":"\niterSome( iterator, n )\n    Tests whether at least `n` iterated values are truthy.\n\n    The function immediately returns upon finding `n` truthy values.\n\n    If provided an iterator which does not return any iterated values, the\n    function returns `false`.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    n: number\n        Minimum number of truthy elements.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if an iterator returns at least `n` truthy\n        elements; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\n    > var bool = iterSome( arr, 3 )\n    true\n\n    See Also\n    --------\n    iterAny, iterEvery, iterForEach, iterNone, iterSomeBy\n","iterSomeBy":"\niterSomeBy( iterator, n, predicate[, thisArg ] )\n    Tests whether at least `n` iterated values pass a test implemented by a\n    predicate function.\n\n    The predicate function is provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index.\n\n    The function immediately returns upon encountering `n` truthy return values.\n\n    If provided an iterator which does not return any iterated values, the\n    function returns `false`.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator over which to iterate.\n\n    n: integer\n        Minimum number of successful values.\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if a predicate function returns a truthy\n        value for at least `n` iterated values. Otherwise, the function returns\n        `false`.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1, 1, 0, 0, 1 ] );\n    > function fcn( v ) { return ( v > 0 ); };\n    > var bool = iterSomeBy( arr, 3, fcn )\n    true\n\n    See Also\n    --------\n    iterAnyBy, iterEveryBy, iterForEach, iterNoneBy, iterSome\n","iterSpence":"\niterSpence( iterator )\n    Returns an iterator which iteratively evaluates Spence's function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 100.0 );\n    > var it = iterSpence( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.spence\n","iterSqrt":"\niterSqrt( iterator )\n    Returns an iterator which iteratively computes the principal square root.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterSqrt( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.sqrt, iterCbrt, iterRsqrt\n","iterSqrt1pm1":"\niterSqrt1pm1( iterator )\n    Returns an iterator which iteratively computes `sqrt(1+x) - 1` more \n    accurately for small `x`.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 100.0 );\n    > var it = iterSqrt1pm1( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.sqrt1pm1, iterSqrt\n","iterSquaredTriangularSeq":"\niterSquaredTriangularSeq( [options] )\n    Returns an iterator which generates a sequence of squared triangular\n    numbers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 11585.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterSquaredTriangularSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().value\n    9\n\n    See Also\n    --------\n    iterTriangularSeq\n","iterSquaresSeq":"\niterSquaresSeq( [options] )\n    Returns an iterator which generates a sequence of squares.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 94906265.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterSquaresSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().value\n    4\n\n    See Also\n    --------\n    iterCubesSeq, iterNonSquaresSeq\n","iterSquareWave":"\niterSquareWave( [options] )\n    Returns an iterator which generates a square wave.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Period (i.e., the number of iterations before a square wave repeats).\n        This must be an even integer in order to ensure a 50% duty cycle.\n        Default: 10.\n\n    options.min: number (optional)\n        Minimum amplitude. Default: -1.0.\n\n    options.max: number (optional)\n        Maximum amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterSquareWave();\n    > var v = it.next().value\n    1.0\n    > v = it.next().value\n    1.0\n\n    See Also\n    --------\n    iterPulse, iterSawtoothWave, iterSineWave, iterTriangleWave\n","iterstdev":"\niterstdev( iterator[, mean] )\n    Computes a correct sample standard deviation over all iterated values.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    mean: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    out: number|null\n        Corrected sample standard deviation.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0 ] );\n    > var m = iterstdev( arr )\n    ~4.95\n\n    See Also\n    --------\n    itermean, itervariance\n","iterStep":"\niterStep( start, increment[, N] )\n    Returns an iterator which returns a sequence of numbers according to a\n    specified increment.\n\n    Beware that values which follow the starting value are subject to floating-\n    point rounding errors.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    start: number\n        Starting value (inclusive).\n\n    increment: number\n        Increment.\n\n    N: number (optional)\n        Number of values. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterStep( 0, 2, 10 );\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    iterator2array, iterDatespace, iterIncrspace, iterLinspace, iterLogspace, iterUnitspace\n","iterStrided":"\niterStrided( iterator, stride[, offset[, eager]] )\n    Returns an iterator which steps by a specified amount.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    stride: integer\n        Stride (i.e., step amount).\n\n    offset: integer (optional)\n        Index of the first iterated value. Default: 0.\n\n    eager: boolean (optional)\n        Boolean indicating whether to eagerly advance the input iterator when\n        provided a non-zero offset. Default: false.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\n    > var it = iterStrided( arr, 2, 1 );\n    > var r = it.next().value\n    1\n    > r = it.next().value\n    3\n\n    See Also\n    --------\n    iterAdvance, iterNth, iterStridedBy\n","iterStridedBy":"\niterStridedBy( iterator, fcn[, offset[, eager]][, thisArg] )\n    Returns an iterator which steps according to a provided callback function.\n\n    When invoked, the input function is provided four arguments:\n\n    - value: iterated value.\n    - i: input iteration index (zero-based).\n    - n: output (strided) iteration index (zero-based).\n    - curr: current stride.\n\n    The return value of the input function specifies the next stride.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    fcn: Function\n        Stride function (i.e., a function which returns the step amount).\n\n    offset: integer (optional)\n        Index of the first iterated value. Default: 0.\n\n    eager: boolean (optional)\n        Boolean indicating whether to eagerly advance the input iterator when\n        provided a non-zero offset. Default: false.\n\n    thisArg: any (optional)\n        Stride function execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 0, 1, 2, 3, 4, 5, 6 ] );\n    > function stride( v, i ) { return (i % 10)+1; };\n    > var it = iterStridedBy( arr, stride );\n    > var r = it.next().value\n    0\n    > r = it.next().value\n    1\n    > r = it.next().value\n    3\n\n    See Also\n    --------\n    iterAdvance, iterNth, iterStrided\n","iterSubtract":"\niterSubtract( iter0, ...iterator )\n    Returns an iterator which performs element-wise subtraction of two or more\n    iterators.\n\n    The length of the returned iterator is equal to the length of the shortest\n    provided iterator. In other words, the returned iterator ends once *one* of\n    the provided iterators ends.\n\n    If provided a numeric value as an iterator argument, the value is broadcast\n    as an infinite iterator which always returns the provided value.\n\n    If an environment supports Symbol.iterator and provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iter0: Object\n        Input iterator.\n\n    iterator: ...Object\n        Iterators to subtract.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1.0, 5.0 ] );\n    > var it2 = array2iterator( [ 3.0, 4.0 ] );\n    > var it = iterSubtract( it1, it2 );\n    > var v = it.next().value\n    -2.0\n    > v = it.next().value\n    1.0\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterAdd, iterDivide, iterMultiply\n","itersum":"\nitersum( iterator )\n    Computes the sum of all iterated values.\n\n    For iterators which can generate many values or which may output large\n    numbers, care should be taken to prevent overflow.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Sum.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var s = itersum( arr )\n    10.0\n\n    See Also\n    --------\n    itermean, itermsum, iterprod\n","itersumabs":"\nitersumabs( iterator )\n    Computes the sum of absolute values for all iterated values.\n\n    For iterators which can generate many values or which may output large\n    numbers, care should be taken to prevent overflow.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Sum of absolute values.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\n    > var s = itersumabs( arr )\n    10.0\n\n    See Also\n    --------\n    itermeanabs, itermsumabs, itersum\n","itersumabs2":"\nitersumabs2( iterator )\n    Computes the sum of squared absolute values for all iterated values.\n\n    For iterators which can generate many values or which may output large\n    numbers, care should be taken to prevent overflow.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    out: number|null\n        Sum of squared absolute values.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ -1.0, 2.0, -3.0, 4.0 ] );\n    > var s = itersumabs2( arr )\n    30.0\n\n    See Also\n    --------\n    itermeanabs2, itermsumabs2, itersumabs\n","iterTan":"\niterTan( iterator )\n    Returns an iterator which iteratively evaluates the tangent.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -1.57, 1.57 );\n    > var it = iterTan( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.tan, iterCos, iterSin\n","iterTanh":"\niterTanh( iterator )\n    Returns an iterator which iteratively evaluates the hyperbolic tangent.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( -4.0, 4.0 );\n    > var it = iterTanh( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.tanh, iterCosh, iterSinh, iterTan\n","iterThunk":"\niterThunk( iterFcn[, ...args] )\n    Returns an iterator \"thunk\".\n\n    A provided iterator function should have the following function signature:\n\n      iterFcn( iterator, ...args )\n\n    The returned function expects a single argument, an iterator.\n\n    This function is useful within the context of iterator pipelines as a means\n    to defer execution until a pipeline is ready for data flow.\n\n    Parameters\n    ----------\n    iterFcn: Function\n        Iterator function.\n\n    args: ...any (optional)\n        Function arguments.\n\n    Returns\n    -------\n    fcn( iter ): Function\n        Function which accepts a single argument, an iterator, and invokes a\n        previously provided iterator function with the provided iterator and any\n        previously provided arguments.\n\n    Examples\n    --------\n    > var fcn = iterThunk( iterSome, 3 );\n    > var arr = array2iterator( [ 0, 0, 1, 1, 1 ] );\n    > var bool = fcn( arr )\n    true\n\n    See Also\n    --------\n    iterPipeline\n","iterTriangleWave":"\niterTriangleWave( [options] )\n    Returns an iterator which generates a triangle wave.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.period: integer (optional)\n        Period (i.e., the number of iterations before a waveform repeats).\n        Default: 10.\n\n    options.amplitude: number (optional)\n        Peak amplitude. Default: 1.0.\n\n    options.offset: integer (optional)\n        Phase offset (in units of iterations; zero-based). A negative offset\n        translates the waveform to the left. A positive offset translates a\n        waveform to the right. Default: 0.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 1e308.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterTriangleWave();\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterPulse, iterSawtoothWave, iterSineWave, iterSquareWave\n","iterTriangularSeq":"\niterTriangularSeq( [options] )\n    Returns an iterator which generates a sequence of triangular numbers.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 134217727.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterTriangularSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n    > v = it.next().value\n    3\n\n    See Also\n    --------\n    iterSquaredTriangularSeq\n","iterTribonnaciSeq":"\niterTribonnaciSeq( [options] )\n    Returns an iterator which generates a Tribonacci sequence.\n    \n    The returned iterator can only generate the first 64 Tribonacci numbers, as\n    larger Tribonacci numbers cannot be safely represented in double-precision\n    floating-point format.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.iter: integer (optional)\n        Number of iterations. Default: 64.\n\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant\n        object has the next\n        iterated value (if one exists) and a\n        boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n\n    Examples\n    --------\n    > var it = iterTribonnaciSeq();\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    0\n\n    See Also\n    --------\n    base.tribonacci, base.fibonacci, iterLucasSeq\n","iterTrigamma":"\niterTrigamma( iterator )\n    Returns an iterator which iteratively evaluates the trigamma function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.01, 50.0 );\n    > var it = iterTrigamma( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.trigamma, iterDigamma, iterGamma\n","iterTrunc":"\niterTrunc( iterator )\n    Returns an iterator which rounds each iterated value toward zero.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterTrunc( random.iterators.randu() );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.trunc, iterCeil, iterFloor, iterRound\n","iterTrunc2":"\niterTrunc2( iterator )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    two toward zero.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterTrunc2( random.iterators.uniform( -100.0, 100.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.trunc2, iterCeil2, iterFloor2, iterRound2, iterTrunc\n","iterTrunc10":"\niterTrunc10( iterator )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    10 toward zero.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterTrunc10( random.iterators.uniform( -100.0, 100.0 ) );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.trunc10, iterCeil10, iterFloor10, iterRound10, iterTrunc\n","iterUnion":"\niterUnion( iter0, ...iterator )\n    Returns an iterator which returns the union of two or more iterators.\n\n    Value \"uniqueness\" is determined according to strict equality.\n\n    A returned iterator internally buffers unique values and, thus, has O(N)\n    memory requirements, where `N` is the total number of source iterator\n    values.\n\n    If an environment supports Symbol.iterator and all provided iterators are\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iter0: Object\n        Input iterator.\n\n    iterator: ...Object\n        Input iterators.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n    > var it2 = array2iterator( [ 1, 2, 5, 2, 3 ] );\n    > var it = iterUnion( it1, it2 );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    2\n    > v = it.next().value\n    4\n    > v = it.next().value\n    5\n    > v = it.next().value\n    3\n    > var bool = it.next().done\n    true\n\n    See Also\n    --------\n    iterIntersection, iterUnique\n","iterUnique":"\niterUnique( iterator )\n    Returns an iterator which returns unique values.\n\n    Value \"uniqueness\" is determined according to strict equality.\n\n    A returned iterator internally buffers unique values and, thus, has O(N)\n    memory requirements.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n    > var it2 = iterUnique( it1 );\n    > var v = it2.next().value\n    1\n    > v = it2.next().value\n    2\n    > v = it2.next().value\n    4\n    > var bool = it2.next().done\n    true\n\n    See Also\n    --------\n    iterUniqueBy, iterUniqueByHash\n","iterUniqueBy":"\niterUniqueBy( iterator, predicate[, thisArg] )\n    Returns an iterator which returns unique values according to a predicate\n    function.\n\n    A returned iterator internally buffers unique values and, thus, has O(N)\n    memory requirements.\n\n    A predicate function is invoked for each iterated value against each value\n    in an internal buffer consisting of previously identified unique values.\n    Thus, as the number of unique values grows, so, too, does the number of\n    predicate function invocations per iterated value.\n\n    An iterated value is considered \"unique\" if the predicate function returns\n    truthy values for all comparisons of the iterated value with each value in\n    the internal buffer.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    predicate: Function\n        A binary function with parameters `a` and `b` corresponding to iterated\n        values. If the values are the same, the function should return `false`\n        (i.e., non-unique); otherwise, if the values are distinct, the function\n        should return `true` (i.e., unique).\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n    > function f( a, b ) { return ( a !== b ); };\n    > var it2 = iterUniqueBy( it1, f );\n    > var v = it2.next().value\n    1\n    > v = it2.next().value\n    2\n    > v = it2.next().value\n    4\n    > var bool = it2.next().done\n    true\n\n    See Also\n    --------\n    iterUnique, iterUniqueByHash\n","iterUniqueByHash":"\niterUniqueByHash( iterator, hashFcn[, thisArg] )\n    Returns an iterator which returns unique values according to a hash\n    function.\n\n    A returned iterator internally buffers unique hashes and, thus, has O(N)\n    memory requirements.\n\n    An iterated value is considered \"unique\" if the hash function returns a\n    unique hash value for that iterated value. Beware that this *may* result in\n    unexpected behavior. Namely, only the first iterated value mapping to a\n    particular hash function result is returned, even if subsequent values,\n    while mapping to the same hash, are different. Accordingly, iteration order\n    *does* matter.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    hashFcn: Function\n        Hash function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2, 1, 2, 4 ] );\n    > function f( v ) { return v.toString(); };\n    > var it2 = iterUniqueByHash( it1, f );\n    > var v = it2.next().value\n    1\n    > v = it2.next().value\n    2\n    > v = it2.next().value\n    4\n    > var bool = it2.next().done\n    true\n\n    See Also\n    --------\n    iterUnique, iterUniqueBy\n","iterUnitspace":"\niterUnitspace( start[, stop] )\n    Returns an iterator which returns numbers incremented by one.\n\n    The iterator stops once the `stop` value is exceeded.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    start: number\n        Starting value (inclusive).\n\n    stop: number (optional)\n        Stopping value. Default: +infinity.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = iterUnitspace( 0, 99 );\n    > var v = it.next().value\n    0\n    > v = it.next().value\n    1\n\n    See Also\n    --------\n    iterator2array, iterIncrspace, iterLinspace, iterStep\n","iterUnshift":"\niterUnshift( iterator, ...items )\n    Returns an iterator which prepends values to the beginning of a provided\n    iterator.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    items: ...any\n        Items to prepend.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it1 = array2iterator( [ 1, 2 ] );\n    > var it2 = iterUnshift( it1, 3, 4 );\n    > var v = it2.next().value\n    3\n    > v = it2.next().value\n    4\n    > v = it2.next().value\n    1\n    > v = it2.next().value\n    2\n    > var bool = it2.next().done\n    true\n\n    See Also\n    --------\n    iterConcat, iterPush, iterShift\n","iterUntilEach":"\niterUntilEach( iterator, predicate, fcn[, thisArg] )\n    Returns an iterator which invokes a function for each iterated value before\n    returning the iterated value until either a predicate function returns true\n    or the iterator has iterated over all values.\n\n    When invoked, both input functions are provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index (zero-based).\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    predicate: Function\n        Function which indicates whether to continue iterating.\n\n    fcn: Function\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > function predicate( v ) { return v !== v };\n    > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n    > var it = iterUntilEach( random.iterators.randu(), predicate, f );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterWhileEach\n","itervariance":"\nitervariance( iterator[, mean] )\n    Computes an unbiased sample variance over all iterated values.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    mean: number (optional)\n        Known mean.\n\n    Returns\n    -------\n    out: number|null\n        Unbiased sample variance.\n\n    Examples\n    --------\n    > var arr = array2iterator( [ 2.0, -5.0 ] );\n    > var s2 = itervariance( arr )\n    24.5\n\n    See Also\n    --------\n    itermean, iterstdev\n","iterVercos":"\niterVercos( iterator )\n    Returns an iterator which iteratively computes the versed cosine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 6.28 );\n    > var it = iterVercos( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.vercos, iterCos, iterSin, iterVersin\n","iterVersin":"\niterVersin( iterator )\n    Returns an iterator which iteratively computes the versed sine.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 0.0, 6.28 );\n    > var it = iterVersin( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.versin, iterCos, iterSin, iterVercos\n","iterWhileEach":"\niterWhileEach( iterator, predicate, fcn[, thisArg] )\n    Returns an iterator which invokes a function for each iterated value before\n    returning the iterated value until either a predicate function returns false\n    or the iterator has iterated over all values.\n\n    When invoked, both input functions are provided two arguments:\n\n    - value: iterated value.\n    - index: iteration index (zero-based).\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    predicate: Function\n        Function which indicates whether to continue iterating.\n\n    fcn: Function\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === v };\n    > function f( v ) { if ( v !== v ) { throw new Error( 'beep' ); } };\n    > var it = iterWhileEach( random.iterators.randu(), predicate, f );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    iterUntilEach\n","iterZeta":"\niterZeta( iterator )\n    Returns an iterator which iteratively evaluates the Riemann zeta function.\n\n    If an environment supports Symbol.iterator and a provided iterator is\n    iterable, the returned iterator is iterable.\n\n    Parameters\n    ----------\n    iterator: Object\n        Input iterator.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var r = random.iterators.uniform( 1.1, 50.0 );\n    > var it = iterZeta( r );\n    > var v = it.next().value\n    <number>\n    > v = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.zeta\n","joinStream":"\njoinStream( [options] )\n    Returns a transform stream which joins streamed data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. Default: '\\n'.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream.\n\n    Examples\n    --------\n    > var s = joinStream();\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();\n\n\njoinStream.factory( [options] )\n    Returns a function for creating transform streams for joined streamed data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. Default: '\\n'.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    createStream: Function\n        Function for creating transform streams.\n\n    Examples\n    --------\n    > var opts = { 'highWaterMark': 64 };\n    > var createStream = joinStream.factory( opts );\n    > var s = createStream();\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();\n\n\njoinStream.objectMode( [options] )\n    Returns an \"objectMode\" transform stream for joining streamed data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. Default: '\\n'.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > var s = joinStream.objectMode();\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();\n\n    See Also\n    --------\n    splitStream\n","joinStream.factory":"\njoinStream.factory( [options] )\n    Returns a function for creating transform streams for joined streamed data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. Default: '\\n'.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    createStream: Function\n        Function for creating transform streams.\n\n    Examples\n    --------\n    > var opts = { 'highWaterMark': 64 };\n    > var createStream = joinStream.factory( opts );\n    > var s = createStream();\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();","joinStream.objectMode":"\njoinStream.objectMode( [options] )\n    Returns an \"objectMode\" transform stream for joining streamed data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. Default: '\\n'.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.readableObjectMode: boolean (optional)\n        Specifies whether the readable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > var s = joinStream.objectMode();\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();\n\n    See Also\n    --------\n    splitStream","kde2d":"\nkde2d( x, y[, options] )\n    Two-dimensional kernel density estimation.\n\n    Parameters\n    ----------\n    x: Array<number>\n        Array of x values.\n\n    y: Array<number>\n        Array of y values.\n\n    options: Object (optional)\n        Function options.\n\n    options.h: number (optional)\n        Array of length two containing the bandwidth values for x and y.\n\n    options.n: number (optional)\n        Number of partitions on the x- and y-axes. Default: `25`.\n\n    options.xMin: number (optional)\n        Lower limit of x.\n\n    options.xMax: number (optional)\n        Upper limit of x.\n\n    options.yMin: number (optional)\n        Lower limit of y.\n\n    options.yMax: number (optional)\n        Upper limit of y.\n\n    options.kernel: string|Function\n        A string or function to specifying the used kernel function. Default:\n        `'gaussian'`.\n\n    Returns\n    -------\n    out: Object\n        Object containing the density estimates (`z`) along grid points (`x` and\n        `y` values).\n\n    Examples\n    --------\n    > var x = [ 1, 3, 5, 6, 21, 23, 16, 17, 20, 10 ];\n    > var y = [ 0.40, 0.20, 0.20, 0.15, 0.05, 0.55, 0.6, 0.33, 0.8, 0.41 ];\n    > var out = kde2d( x, y )\n    { 'x': [1, ... ], 'y': [0.05, ...], 'z': ndarray{Float64Array[0.031, ...] }\n\n","kebabcase":"\nkebabcase( str )\n    Converts a string to kebab case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Kebab-cased string.\n\n    Examples\n    --------\n    > var out = kebabcase( 'Hello World!' )\n    'hello-world'\n    > out = kebabcase( 'I am a tiny little teapot' )\n    'i-am-a-tiny-little-teapot'\n\n    See Also\n    --------\n    camelcase, constantcase, pascalcase, snakecase","keyBy":"\nkeyBy( collection, fcn[, thisArg] )\n    Converts a collection to an object whose keys are determined by a provided\n    function and whose values are the collection values.\n\n    When invoked, the input function is provided two arguments:\n\n    - value: collection value.\n    - index: collection index.\n\n    If more than one element in a collection resolves to the same key, the key\n    value is the collection element which last resolved to the key.\n\n    Object values are shallow copies.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Object\n        Output object.\n\n    Examples\n    --------\n    > function toKey( v ) { return v.a; };\n    > var arr = [ { 'a': 1 }, { 'a': 2 } ];\n    > keyBy( arr, toKey )\n    { '1': { 'a': 1 }, '2': { 'a': 2 } }\n\n    See Also\n    --------\n    forEach\n","keyByRight":"\nkeyByRight( collection, fcn[, thisArg] )\n    Converts a collection to an object whose keys are determined by a provided\n    function and whose values are the collection values, iterating from right to\n    left.\n\n    When invoked, the input function is provided two arguments:\n\n    - value: collection value.\n    - index: collection index.\n\n    If more than one element in a collection resolves to the same key, the key\n    value is the collection element which last resolved to the key.\n\n    Object values are shallow copies.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: Object\n        Output object.\n\n    Examples\n    --------\n    > function toKey( v ) { return v.a; };\n    > var arr = [ { 'a': 1 }, { 'a': 2 } ];\n    > keyByRight( arr, toKey )\n    { '2': { 'a': 2 }, '1': { 'a': 1 } }\n\n    See Also\n    --------\n    forEachRight, keyBy\n","keysIn":"\nkeysIn( obj )\n    Returns an array of an object's own and inherited enumerable property\n    names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    Parameters\n    ----------\n    obj: any\n        Input value.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's own and inherited enumerable property names.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var keys = keysIn( obj )\n    e.g., [ 'beep', 'foo' ]\n\n    See Also\n    --------\n    objectEntriesIn, objectKeys, objectValuesIn\n","kruskalTest":"\nkruskalTest( ...x[, options] )\n    Computes the Kruskal-Wallis test for equal medians.\n\n    Parameters\n    ----------\n    x: ...Array\n        Measured values.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.groups: Array (optional)\n        Array of group indicators.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.method: string\n        Name of test.\n\n    out.df: Object\n        Degrees of freedom.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    // Data from Hollander & Wolfe (1973), p. 116:\n    > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n    > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n    > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n    > var out = kruskalTest( x, y, z )\n\n    > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n    ...     3.8, 2.7, 4.0, 2.4,\n    ...     2.8, 3.4, 3.7, 2.2, 2.0\n    ... ];\n    > var groups = [\n    ...     'a', 'a', 'a', 'a', 'a',\n    ...     'b', 'b', 'b', 'b',\n    ...     'c', 'c', 'c', 'c', 'c'\n    ... ];\n    > out = kruskalTest( arr, { 'groups': groups } )\n\n","kstest":"\nkstest( x, y[, ...params][, options] )\n    Computes a Kolmogorov-Smirnov goodness-of-fit test.\n\n    For a numeric array or typed array `x`, a Kolmogorov-Smirnov goodness-of-fit\n    is computed for the null hypothesis that the values of `x` come from the\n    distribution specified by `y`. `y` can be either a string with the name of\n    the distribution to test against, or a function.\n\n    In the latter case, `y` is expected to be the cumulative distribution\n    function (CDF) of the distribution to test against, with its first parameter\n    being the value at which to evaluate the CDF and the remaining parameters\n    constituting the parameters of the distribution. The parameters of the\n    distribution are passed as additional arguments after `y` from `kstest` to\n    the chosen CDF. The function returns an object holding the calculated test\n    statistic `statistic` and the `pValue` of the test.\n\n    The returned object comes with a `.print()` method which when invoked will\n    print a formatted output of the hypothesis test results.\n\n    Parameters\n    ----------\n    x: Array<number>\n        Input array holding numeric values.\n\n    y: Function|string\n        Either a CDF function or a string denoting the name of a distribution.\n\n    params: ...number (optional)\n        Distribution parameters passed to reference CDF.\n\n    options: Object (optional)\n        Function options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.sorted: boolean (optional)\n        Boolean indicating if the input array is already in sorted order.\n        Default: `false`.\n\n    options.alternative: string (optional)\n        Either `two-sided`, `less` or `greater`. Indicates whether the\n        alternative hypothesis is that the true distribution of `x` is not equal\n        to the reference distribution specified by `y` (`two-sided`), whether it\n        is `less` than the reference distribution or `greater` than the\n        reference distribution. Default: `'two-sided'`.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Used significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.alternative: string\n        Used test alternative. Either `two-sided`, `less` or `greater`.\n\n    out.method: string\n        Name of test.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    // Verify that data is drawn from a normal distribution:\n    > var rnorm = base.random.normal.factory({ 'seed': 4839 } );\n    > var x = new Array( 100 );\n    > for ( var i = 0; i < 100; i++ ) { x[ i ] = rnorm( 3.0, 1.0 ); }\n\n    // Test against N(0,1)\n    > var out = kstest( x, 'normal', 0.0, 1.0 )\n    { pValue: 0.0, statistic: 0.847, ... }\n\n    // Test against N(3,1)\n    > out = kstest( x, 'normal', 3.0, 1.0 )\n    { pValue: 0.6282, statistic: 0.0733, ... }\n\n    // Verify that data is drawn from a uniform distribution:\n    > runif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } )\n    > x = new Array( 100 );\n    > for ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\n    > out = kstest( x, 'uniform', 0.0, 1.0 )\n    { pValue: ~0.703, statistic: ~0.069, ... }\n\n    // Print output:\n    > out.print()\n    Kolmogorov-Smirnov goodness-of-fit test.\n\n    Null hypothesis: the CDF of `x` is equal equal to the reference CDF.\n\n        pValue: 0.7039\n        statistic: 0.0689\n\n    Test Decision: Fail to reject null in favor of alternative at 5%\n    significance level\n\n    // Set custom significance level:\n    > out = kstest( x, 'uniform', 0.0, 1.0, { 'alpha': 0.1 } )\n    { pValue: ~0.7039, statistic: ~0.069, ... }\n\n    // Carry out one-sided hypothesis tests:\n    > runif = base.random.uniform.factory( 0.0, 1.0, { 'seed': 8798 } );\n    > x = new Array( 100 );\n    > for ( i = 0; i < x.length; i++ ) { x[ i ] = runif(); }\n    > out = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'less' } )\n    { pValue: ~0.358, statistic: ~0.07, ... }\n    > out = kstest( x, 'uniform', 0.0, 1.0, { 'alternative': 'greater' } )\n    { pValue: ~0.907, statistic: ~0.02, ... }\n\n    // Set `sorted` option to true when data is in increasing order:\n    > x = [ 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9 ];\n    > out = kstest( x, 'uniform', 0.0, 1.0, { 'sorted': true } )\n    { pValue: ~1, statistic: 0.1, ... }\n\n","last":"\nlast( str[, n][, options] )\n    Returns the last character(s) of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer (optional)\n        Number of characters to return. Default: 1.\n\n    options: Object (optional)\n        Options.\n\n    options.mode: string (optional)\n        Type of characters to return. The following modes are supported:\n\n        - grapheme: grapheme clusters. Appropriate for strings containing visual\n          characters which can span multiple Unicode code points (e.g., emoji).\n        - code_point: Unicode code points. Appropriate for strings containing\n          visual characters which are comprised of more than one Unicode code\n          unit (e.g., ideographic symbols and punctuation and mathematical\n          alphanumerics).\n        - code_unit': UTF-16 code units. Appropriate for strings containing\n          visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n          common characters, such as those from the Latin, Greek, and Cyrillic\n          alphabets).\n\n        Default: 'grapheme'.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var out = last( 'beep' )\n    'p'\n    > out = last( 'Boop', 2 )\n    'op'\n    > out = last( 'foo bar', 3 )\n    'bar'\n\n    See Also\n    --------\n    firstChar\n","leveneTest":"\nleveneTest( x[, ...y[, options]] )\n    Computes Levene's test for equal variances.\n\n    Parameters\n    ----------\n    x: Array<number>\n        Measured values.\n\n    y: ...Array<number> (optional)\n        Measured values.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.groups: Array (optional)\n        Array of group indicators.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.method: string\n        Name of test.\n\n    out.df: Array\n        Degrees of freedom.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    // Data from Hollander & Wolfe (1973), p. 116:\n    > var x = [ 2.9, 3.0, 2.5, 2.6, 3.2 ];\n    > var y = [ 3.8, 2.7, 4.0, 2.4 ];\n    > var z = [ 2.8, 3.4, 3.7, 2.2, 2.0 ];\n\n    > var out = leveneTest( x, y, z )\n\n    > var arr = [ 2.9, 3.0, 2.5, 2.6, 3.2,\n    ...     3.8, 2.7, 4.0, 2.4,\n    ...     2.8, 3.4, 3.7, 2.2, 2.0\n    ... ];\n    > var groups = [\n    ...     'a', 'a', 'a', 'a', 'a',\n    ...     'b', 'b', 'b', 'b',\n    ...     'c', 'c', 'c', 'c', 'c'\n    ... ];\n    > out = leveneTest( arr, { 'groups': groups } )\n\n    See Also\n    --------\n    vartest, bartlettTest\n","LinkedList":"\nLinkedList()\n    Linked list constructor.\n\n    Returns\n    -------\n    list: Object\n        Linked list.\n\n    list.clear: Function\n        Clears the list.\n\n    list.first: Function\n        Returns the last node. If the list is empty, the returned value is\n        `undefined`.\n\n    list.insert: Function\n        Inserts a value after a provided list node.\n\n    list.iterator: Function\n        Returns an iterator for iterating over a list. If an environment\n        supports Symbol.iterator, the returned iterator is iterable. Note that,\n        in order to prevent confusion arising from list mutation during\n        iteration, a returned iterator **always** iterates over a list\n        \"snapshot\", which is defined as the list of list elements at the time\n        of the method's invocation.\n\n    list.last: Function\n        Returns the last list node. If the list is empty, the returned value is\n        `undefined`.\n\n    list.length: integer\n        List length.\n\n    list.pop: Function\n        Removes and returns the last list value. If the list is empty, the\n        returned value is `undefined`.\n\n    list.push: Function\n        Adds a value to the end of the list.\n\n    list.remove: Function\n        Removes a list node from the list.\n\n    list.shift: Function\n        Removes and returns the first list value. If the list is empty, the\n        returned value is `undefined`.\n\n    list.toArray: Function\n        Returns an array of list values.\n\n    list.toJSON: Function\n        Serializes a list as JSON.\n\n    list.unshift: Function\n        Adds a value to the beginning of the list.\n\n    Examples\n    --------\n    > var list = LinkedList();\n    > list.push( 'foo' ).push( 'bar' );\n    > list.length\n    2\n    > list.pop()\n    'bar'\n    > list.length\n    1\n    > list.pop()\n    'foo'\n    > list.length\n    0\n\n    See Also\n    --------\n    DoublyLinkedList, Stack\n","linspace":"\nlinspace( start, stop, length[, options] )\n    Generates a linearly spaced array over a specified interval.\n\n    If the specified length is zero, the function returns an empty array.\n\n    If the specified length is one, the function returns an array containing\n    `stop`, but not `start`, when `endpoint` is true; otherwise, the function\n    returns an array containing `start`, but not `stop`.\n\n    For real-valued `start` and `stop`, if `start` is less than `stop`, the\n    output array will contain ascending values, and, if `start` is greater than\n    `stop`, the output array will contain descending values.\n\n    When the output array length is greater than one and `endpoint` is true, the\n    output array is guaranteed to include the `start` and `stop` values. Beware,\n    however, that values between `start` and `stop` are subject to floating-\n    point rounding errors.\n\n    If both `start` and `stop` are real-valued, the output array data type may\n    be any floating-point data type or 'generic'. However, if either `start` or\n    `stop` are complex numbers, the output array type must be a complex\n    floating-point data type or 'generic'.\n\n    When writing to a complex floating-point output array, real-valued `start`\n    and `stop` values are treated as complex numbers having a real component\n    equaling the provided value and having an imaginary component equaling zero.\n\n    When generating linearly spaced complex floating-point numbers, the real and\n    imaginary components are generated separately.\n\n    Parameters\n    ----------\n    start: number|ComplexLike\n        Start of interval.\n\n    stop: number|ComplexLike\n        End of interval.\n\n    length: integer\n        Length of output array.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Must be a floating-point data type or 'generic'.\n         If both `start` and `stop` are the same type (either 'float64',\n         'complex64', or 'complex128'), the default output array data type is\n         the same type as the input values (either 'float64', 'complex64', or\n         'complex128', respectively). Otherwise, the default output array data\n         type is 'complex128'.\n\n    options.endpoint: boolean (optional)\n        Boolean indicating whether to include the `stop` value in the output\n        array. If false, the function generates `length + 1` linearly spaced\n        values over the interval `[start, stop]` and only writes `length` values\n        to the output array, thus excluding `stop` from the output array.\n        Accordingly, for a fixed `length`, the spacing between adjacent values\n        in the output array changes depending on the value of `endpoint`.\n        Default: true.\n\n    Returns\n    -------\n    arr: Array\n        Linearly spaced array.\n\n    Examples\n    --------\n    > var arr = linspace( 0.0, 100.0, 6 )\n    <Float64Array>[ 0.0, 20.0, 40.0, 60.0, 80.0, 100.0 ]\n    > arr = linspace( 0.0, 100.0, 5, { 'endpoint': false } )\n    <Float64Array>[ 0.0, 20.0, 40.0, 60.0, 80.0 ]\n    > arr = linspace( 0.0, 100.0, 6, { 'dtype': 'generic' } )\n    [ 0.0, 20.0, 40.0, 60.0, 80.0, 100.0 ]\n\n\nlinspace.assign( start, stop, out[, options] )\n    Generates a linearly spaced sequence over a specified interval and assigns\n    the results to a provided output array.\n\n    If the provided output array is empty, the function returns the provided\n    output array unchanged.\n\n    If the provided output array contains a single element, the function writes\n    the `stop` value, but not `start`, when `endpoint` is true; otherwise, the\n    function writes the `start` value, but not `stop`.\n\n    Parameters\n    ----------\n    start: number|ComplexLike\n        Start of interval.\n\n    stop: number|ComplexLike\n        End of interval.\n\n    out: ArrayLikeObject\n        Output array.\n\n    options: Object (optional)\n        Options.\n\n    options.endpoint: boolean (optional)\n        Boolean indicating whether to include the `stop` value in the output\n        array. If false, the function generates `N+1` linearly spaced values\n        (where `N` is the length of the provided output array) over the interval\n        `[start, stop]` and only writes `N` values to the output array, thus\n        excluding `stop` from the output array. Accordingly, for a fixed `N`,\n        the spacing between adjacent values in the output array changes\n        depending on the value of `endpoint`. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var arr = [ 0, 0, 0, 0, 0, 0 ];\n    > var out = linspace.assign( 0, 100, arr )\n    [ 0, 20, 40, 60, 80, 100 ]\n    > var bool = ( arr === out )\n    true\n    > arr = [ 0, 0, 0, 0, 0 ];\n    > out = linspace.assign( 0, 100, arr, { 'endpoint': false } )\n    [ 0, 20, 40, 60, 80 ]\n\n    See Also\n    --------\n    incrspace, logspace\n","linspace.assign":"\nlinspace.assign( start, stop, out[, options] )\n    Generates a linearly spaced sequence over a specified interval and assigns\n    the results to a provided output array.\n\n    If the provided output array is empty, the function returns the provided\n    output array unchanged.\n\n    If the provided output array contains a single element, the function writes\n    the `stop` value, but not `start`, when `endpoint` is true; otherwise, the\n    function writes the `start` value, but not `stop`.\n\n    Parameters\n    ----------\n    start: number|ComplexLike\n        Start of interval.\n\n    stop: number|ComplexLike\n        End of interval.\n\n    out: ArrayLikeObject\n        Output array.\n\n    options: Object (optional)\n        Options.\n\n    options.endpoint: boolean (optional)\n        Boolean indicating whether to include the `stop` value in the output\n        array. If false, the function generates `N+1` linearly spaced values\n        (where `N` is the length of the provided output array) over the interval\n        `[start, stop]` and only writes `N` values to the output array, thus\n        excluding `stop` from the output array. Accordingly, for a fixed `N`,\n        the spacing between adjacent values in the output array changes\n        depending on the value of `endpoint`. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var arr = [ 0, 0, 0, 0, 0, 0 ];\n    > var out = linspace.assign( 0, 100, arr )\n    [ 0, 20, 40, 60, 80, 100 ]\n    > var bool = ( arr === out )\n    true\n    > arr = [ 0, 0, 0, 0, 0 ];\n    > out = linspace.assign( 0, 100, arr, { 'endpoint': false } )\n    [ 0, 20, 40, 60, 80 ]\n\n    See Also\n    --------\n    incrspace, logspace","LIU_NEGATIVE_OPINION_WORDS_EN":"\nLIU_NEGATIVE_OPINION_WORDS_EN()\n    Returns a list of negative opinion words.\n\n    A word's appearance in a sentence does *not* necessarily imply a positive or\n    negative opinion.\n\n    The list includes misspelled words. Their presence is intentional, as such\n    misspellings frequently occur in social media content.\n\n    Returns\n    -------\n    out: Array<string>\n        List of negative opinion words.\n\n    Examples\n    --------\n    > var list = LIU_NEGATIVE_OPINION_WORDS_EN()\n    [ '2-faced', '2-faces', 'abnormal', 'abolish', ... ]\n\n    References\n    ----------\n    - Hu, Minqing, and Bing Liu. 2004. \"Mining and Summarizing Customer\n    Reviews.\" In *Proceedings of the Tenth Acm Sigkdd International Conference\n    on Knowledge Discovery and Data Mining*, 168–77. KDD '04. New York, NY, USA:\n    ACM. doi:10.1145/1014052.1014073.\n    - Liu, Bing, Minqing Hu, and Junsheng Cheng. 2005. \"Opinion Observer:\n    Analyzing and Comparing Opinions on the Web.\" In *Proceedings of the 14th\n    International Conference on World Wide Web*, 342–51. WWW '05. New York, NY,\n    USA: ACM. doi:10.1145/1060745.1060797.\n\n    * If you use the list for publication or third party consumption, please\n    cite one of the listed references.\n\n    See Also\n    --------\n    LIU_POSITIVE_OPINION_WORDS_EN\n","LIU_POSITIVE_OPINION_WORDS_EN":"\nLIU_POSITIVE_OPINION_WORDS_EN()\n    Returns a list of positive opinion words.\n\n    A word's appearance in a sentence does *not* necessarily imply a positive or\n    negative opinion.\n\n    The list includes misspelled words. Their presence is intentional, as such\n    misspellings frequently occur in social media content.\n\n    Returns\n    -------\n    out: Array<string>\n        List of positive opinion words.\n\n    Examples\n    --------\n    > var list = LIU_POSITIVE_OPINION_WORDS_EN()\n    [ 'a+', 'abound', 'abounds', 'abundance', ... ]\n\n    References\n    ----------\n    - Hu, Minqing, and Bing Liu. 2004. 'Mining and Summarizing Customer\n    Reviews.' In *Proceedings of the Tenth Acm Sigkdd International Conference\n    on Knowledge Discovery and Data Mining*, 168–77. KDD '04. New York, NY, USA:\n    ACM. doi:10.1145/1014052.1014073.\n    - Liu, Bing, Minqing Hu, and Junsheng Cheng. 2005. 'Opinion Observer:\n    Analyzing and Comparing Opinions on the Web.' In *Proceedings of the 14th\n    International Conference on World Wide Web*, 342–51. WWW '05. New York, NY,\n    USA: ACM. doi:10.1145/1060745.1060797.\n\n    * If you use the list for publication or third party consumption, please\n    cite one of the listed references.\n\n    See Also\n    --------\n    LIU_NEGATIVE_OPINION_WORDS_EN\n","LN_HALF":"\nLN_HALF\n    Natural logarithm of `1/2`.\n\n    Examples\n    --------\n    > LN_HALF\n    -0.6931471805599453\n\n","LN_PI":"\nLN_PI\n    Natural logarithm of the mathematical constant `π`.\n\n    Examples\n    --------\n    > LN_PI\n    1.1447298858494002\n\n    See Also\n    --------\n    PI\n","LN_SQRT_TWO_PI":"\nLN_SQRT_TWO_PI\n    Natural logarithm of the square root of `2π`.\n\n    Examples\n    --------\n    > LN_SQRT_TWO_PI\n    0.9189385332046728\n\n    See Also\n    --------\n    PI\n","LN_TWO_PI":"\nLN_TWO_PI\n    Natural logarithm of `2π`.\n\n    Examples\n    --------\n    > LN_TWO_PI\n    1.8378770664093456\n\n    See Also\n    --------\n    TWO_PI\n","LN2":"\nLN2\n    Natural logarithm of `2`.\n\n    Examples\n    --------\n    > LN2\n    0.6931471805599453\n\n    See Also\n    --------\n    LN10\n","LN10":"\nLN10\n    Natural logarithm of `10`.\n\n    Examples\n    --------\n    > LN10\n    2.302585092994046\n\n    See Also\n    --------\n    LN2\n","LOG2E":"\nLOG2E\n    Base 2 logarithm of Euler's number.\n\n    Examples\n    --------\n    > LOG2E\n    1.4426950408889634\n\n    See Also\n    --------\n    E, LOG10E\n","LOG10E":"\nLOG10E\n    Base 10 logarithm of Euler's number.\n\n    Examples\n    --------\n    > LOG10E\n    0.4342944819032518\n\n    See Also\n    --------\n    E, LOG2E\n","logspace":"\nlogspace( a, b[, length] )\n    Generates a logarithmically spaced numeric array between `10^a` and `10^b`.\n\n    If a `length` is not provided, the default output array length is `10`.\n\n    The output array includes the values `10^a` and `10^b`.\n\n    Parameters\n    ----------\n    a: number\n        Exponent of start value.\n\n    b: number\n        Exponent of end value.\n\n    length: integer (optional)\n        Length of output array. Default: `10`.\n\n    Returns\n    -------\n    arr: Array\n        Logarithmically spaced numeric array.\n\n    Examples\n    --------\n    > var arr = logspace( 0, 2, 6 )\n    [ 1, ~2.5, ~6.31, ~15.85, ~39.81, 100 ]\n\n    See Also\n    --------\n    incrspace, linspace\n","lowercase":"\nlowercase( str )\n    Converts a string to lowercase.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Lowercase string.\n\n    Examples\n    --------\n    > var out = lowercase( 'bEEp' )\n    'beep'\n\n    See Also\n    --------\n    uncapitalize, uppercase\n","lowercaseKeys":"\nlowercaseKeys( obj )\n    Converts each object key to lowercase.\n\n    The function only transforms own properties. Hence, the function does not\n    transform inherited properties.\n\n    The function shallow copies key values.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > var obj = { 'A': 1, 'B': 2 };\n    > var out = lowercaseKeys( obj )\n    { 'a': 1, 'b': 2 }\n\n    See Also\n    --------\n    uncapitalizeKeys, uppercaseKeys\n","lowess":"\nlowess( x, y[, options] )\n    Locally-weighted polynomial regression via the LOWESS algorithm.\n\n    Parameters\n    ----------\n    x: Array<number>\n        x-axis values (abscissa values).\n\n    y: Array<number>\n        Corresponding y-axis values (ordinate values).\n\n    options: Object (optional)\n        Function options.\n\n    options.f: number (optional)\n        Positive number specifying the smoothing span, i.e., the proportion of\n        points which influence smoothing at each value. Larger values\n        correspond to more smoothing. Default: `2/3`.\n\n    options.nsteps: number (optional)\n        Number of iterations in the robust fit (fewer iterations translates to\n        faster function execution). If set to zero, the nonrobust fit is\n        returned. Default: `3`.\n\n    options.delta: number (optional)\n        Nonnegative number which may be used to reduce the number of\n        computations. Default: 1/100th of the range of `x`.\n\n    options.sorted: boolean (optional)\n        Boolean indicating if the input array `x` is sorted. Default: `false`.\n\n    Returns\n    -------\n    out: Object\n        Object with ordered x-values and fitted values.\n\n    Examples\n    --------\n    > var x = new Float64Array( 100 );\n    > var y = new Float64Array( x.length );\n    > for ( var i = 0; i < x.length; i++ ) {\n    ...     x[ i ] = i;\n    ...     y[ i ] = ( 0.5*i ) + ( 10.0*base.random.randn() );\n    ... }\n    > var out = lowess( x, y );\n    > var yhat = out.y;\n\n    > var h = Plot( [ x, x ], [ y, yhat ] );\n    > h.lineStyle = [ 'none', '-' ];\n    > h.symbols = [ 'closed-circle', 'none' ];\n\n    > h.view( 'window' );\n\n","lpad":"\nlpad( str, len[, pad] )\n    Left pads a string such that the padded string has a length of at least\n    `len`.\n\n    An output string is not guaranteed to have a length of exactly `len`, but to\n    have a length of at least `len`. To generate a padded string having a length\n    equal to `len`, post-process a padded string by trimming off excess\n    characters.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    len: integer\n        Minimum string length.\n\n    pad: string (optional)\n        String used to pad. Default: ' '.\n\n    Returns\n    -------\n    out: string\n        Padded string.\n\n    Examples\n    --------\n    > var out = lpad( 'a', 5 )\n    '    a'\n    > out = lpad( 'beep', 10, 'b' )\n    'bbbbbbbeep'\n    > out = lpad( 'boop', 12, 'beep' )\n    'beepbeepboop'\n\n    See Also\n    --------\n    pad, rpad\n","ltrim":"\nltrim( str )\n    Trims whitespace from the beginning of a string.\n\n    \"Whitespace\" is defined as the following characters:\n\n    - \\f\n    - \\n\n    - \\r\n    - \\t\n    - \\v\n    - \\u0020\n    - \\u00a0\n    - \\u1680\n    - \\u2000-\\u200a\n    - \\u2028\n    - \\u2029\n    - \\u202f\n    - \\u205f\n    - \\u3000\n    - \\ufeff\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Trimmed string.\n\n    Examples\n    --------\n    > var out = ltrim( ' \\r\\n\\t  Beep \\t\\t\\n  ' )\n    'Beep \\t\\t\\n  '\n\n    See Also\n    --------\n    trim, rtrim\n","ltrimN":"\nltrimN( str, n[, chars] )\n    Trims `n` characters from the beginning of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of characters to trim.\n\n    chars: Array<string>|string (optional)\n        Characters to trim. Default: whitespace characters.\n\n    Returns\n    -------\n    out: string\n        Trimmed string.\n\n    Examples\n    --------\n    > var out = ltrimN( '  abc  ', 2 )\n    'abc  '\n    > var out = ltrimN( '!!!abc!!!', 2, '!' )\n    '!abc!!!'\n\n    See Also\n    --------\n    rtrimN, trim","MALE_FIRST_NAMES_EN":"\nMALE_FIRST_NAMES_EN()\n    Returns a list of common male first names in English speaking countries.\n\n    Returns\n    -------\n    out: Array<string>\n        List of common male first names.\n\n    Examples\n    --------\n    > var list = MALE_FIRST_NAMES_EN()\n    [ 'Aaron', 'Ab', 'Abba', 'Abbe', ... ]\n\n    References\n    ----------\n    - Ward, Grady. 2002. 'Moby Word II.' <http://www.gutenberg.org/files/3201/\n    3201.txt>.\n\n    See Also\n    --------\n    FEMALE_FIRST_NAMES_EN\n","map":"\nmap( arr, fcn[, thisArg] )\n    Applies a function to each element in an array and assigns the result to an\n    element in a new array.\n\n    The applied function is provided the following arguments:\n\n    - value: array element.\n    - index: element index.\n    - arr: input array.\n\n    The returned output array always has a \"generic\" data type. For example, if\n    provided an array-like object, the function returns a generic array. If\n    provided an ndarray, the function returns an ndarray having a \"generic\" data\n    type.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject|ndarray\n        Input array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.abs, 1 );\n    > var arr = [ -1, -2, -3, -4, -5, -6 ];\n    > var out = map( arr, f )\n    [ 1, 2, 3, 4, 5, 6 ]\n\n    // ndarray:\n    > arr = array( arr, { 'shape': [ 2, 3 ] } );\n    > out = map( arr, f );\n    > var v = out.get( 1, 1 )\n    5\n\n\nmap.assign( arr, out, fcn[, thisArg] )\n    Applies a function to each element in an array and assigns the result to an\n    element in an output array.\n\n    The applied function is provided the following arguments:\n\n    - value: array element.\n    - index: element index.\n    - arr: input array.\n\n    Input and output arrays must be either both array-like objects or both\n    ndarray-like objects.\n\n    If input and output arrays are array-like objects, the arrays must have the\n    same number of elements.\n\n    If input and output arrays are both ndarray-like objects, the arrays *must*\n    be broadcast compatible.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject|ndarray\n        Input array.\n\n    out: ArrayLikeObject|ndarray\n        Output array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.abs, 1 );\n    > var arr = [ -1, -2, -3, -4, -5, -6 ];\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > map.assign( arr, out, f );\n    > out\n    [ 1, 2, 3, 4, 5, 6 ]\n\n    // ndarray:\n    > var opts = { 'shape': [ 2, 3 ] };\n    > arr = array( arr, opts );\n    > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n    > map.assign( arr, out, f );\n    > var v = out.get( 1, 1 )\n    5\n\n    See Also\n    --------\n    mapRight, reduce\n","map.assign":"\nmap.assign( arr, out, fcn[, thisArg] )\n    Applies a function to each element in an array and assigns the result to an\n    element in an output array.\n\n    The applied function is provided the following arguments:\n\n    - value: array element.\n    - index: element index.\n    - arr: input array.\n\n    Input and output arrays must be either both array-like objects or both\n    ndarray-like objects.\n\n    If input and output arrays are array-like objects, the arrays must have the\n    same number of elements.\n\n    If input and output arrays are both ndarray-like objects, the arrays *must*\n    be broadcast compatible.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject|ndarray\n        Input array.\n\n    out: ArrayLikeObject|ndarray\n        Output array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.abs, 1 );\n    > var arr = [ -1, -2, -3, -4, -5, -6 ];\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > map.assign( arr, out, f );\n    > out\n    [ 1, 2, 3, 4, 5, 6 ]\n\n    // ndarray:\n    > var opts = { 'shape': [ 2, 3 ] };\n    > arr = array( arr, opts );\n    > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n    > map.assign( arr, out, f );\n    > var v = out.get( 1, 1 )\n    5\n\n    See Also\n    --------\n    mapRight, reduce","map2":"\nmap2( x, y, fcn[, thisArg] )\n    Applies a function to elements in two input arrays and assigns the results\n    to a new array.\n\n    The applied function is provided the following arguments:\n\n    - v1: element from first input array.\n    - v2: element from second input array.\n    - idx: element index.\n    - arrays: input arrays.\n\n    The returned output array always has a \"generic\" data type. For example, if\n    provided an array-like object, the function returns a generic array. If\n    provided an ndarray, the function returns an ndarray having a \"generic\" data\n    type.\n\n    Input arrays must be either both array-like objects or both ndarray-like\n    objects.\n\n    If input arrays are array-like objects, the arrays must have the same number\n    of elements.\n\n    If input arrays are ndarray-like objects, the arrays must be broadcast\n    compatible.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject|ndarray\n        First input array.\n\n    y: ArrayLikeObject|ndarray\n        Second input array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.add, 2 );\n    > var x = [ 1, 2, 3, 4, 5, 6 ];\n    > var y = [ 1, 1, 1, 1, 1, 1 ];\n    > var out = map2( x, y, f )\n    [ 2, 3, 4, 5, 6, 7 ]\n\n    // ndarray:\n    > x = array( x, { 'shape': [ 2, 3 ] } );\n    > y = array( y, { 'shape': [ 2, 3 ] } );\n    > out = map2( x, y, f );\n    > var v = out.get( 1, 1 )\n    6\n\n\nmap2.assign( x, y, out, fcn[, thisArg] )\n    Applies a function to elements in two input arrays and assigns the results\n    to an output array.\n\n    The applied function is provided the following arguments:\n\n    - v1: element from first input array.\n    - v2: element from second input array.\n    - idx: element index.\n    - arrays: input arrays.\n\n    Input and output arrays must be either all array-like objects or all\n    ndarray-like objects.\n\n    If input and output arrays are array-like objects, the arrays must have the\n    same number of elements.\n\n    If input and output arrays are ndarray-like objects, the arrays must be\n    broadcast compatible.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject|ndarray\n        First input array.\n\n    y: ArrayLikeObject|ndarray\n        Second input array.\n\n    out: ArrayLikeObject|ndarray\n        Output array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.add, 2 );\n    > var x = [ 1, 2, 3, 4, 5, 6 ];\n    > var y = [ 1, 1, 1, 1, 1, 1 ];\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > map2.assign( x, y, out, f );\n    > out\n    [ 2, 3, 4, 5, 6, 7 ]\n\n    // ndarray:\n    > var opts = { 'shape': [ 2, 3 ] };\n    > x = array( x, opts );\n    > y = array( y, opts );\n    > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n    > map2.assign( x, y, out, f );\n    > var v = out.get( 1, 1 )\n    6\n\n    See Also\n    --------\n    map\n","map2.assign":"\nmap2.assign( x, y, out, fcn[, thisArg] )\n    Applies a function to elements in two input arrays and assigns the results\n    to an output array.\n\n    The applied function is provided the following arguments:\n\n    - v1: element from first input array.\n    - v2: element from second input array.\n    - idx: element index.\n    - arrays: input arrays.\n\n    Input and output arrays must be either all array-like objects or all\n    ndarray-like objects.\n\n    If input and output arrays are array-like objects, the arrays must have the\n    same number of elements.\n\n    If input and output arrays are ndarray-like objects, the arrays must be\n    broadcast compatible.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject|ndarray\n        First input array.\n\n    y: ArrayLikeObject|ndarray\n        Second input array.\n\n    out: ArrayLikeObject|ndarray\n        Output array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.add, 2 );\n    > var x = [ 1, 2, 3, 4, 5, 6 ];\n    > var y = [ 1, 1, 1, 1, 1, 1 ];\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > map2.assign( x, y, out, f );\n    > out\n    [ 2, 3, 4, 5, 6, 7 ]\n\n    // ndarray:\n    > var opts = { 'shape': [ 2, 3 ] };\n    > x = array( x, opts );\n    > y = array( y, opts );\n    > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n    > map2.assign( x, y, out, f );\n    > var v = out.get( 1, 1 )\n    6\n\n    See Also\n    --------\n    map","map2d":"\nmap2d( arr, fcn[, thisArg] )\n    Applies a function to each nested element in an array of arrays and assigns\n    the result to a nested element in a new array of arrays.\n\n    The applied function is provided the following arguments:\n\n    - value: array element.\n    - indices: current array element indices.\n    - arr: input array.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject<ArrayLikeObject>\n        Input array of arrays.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array<Array>\n        Array of arrays.\n\n    Examples\n    --------\n    > var f = naryFunction( base.abs, 1 );\n    > var arr = [ [ -1, -2, -3 ], [ -4, -5, -6 ] ];\n    > var out = map2d( arr, f );\n    > out[ 0 ]\n    [ 1, 2, 3 ]\n    > out[ 1 ]\n    [ 4, 5, 6 ]\n\n    See Also\n    --------\n    map, map3d, map4d, map5d, reduce2d\n","map2Right":"\nmap2Right( x, y, fcn[, thisArg] )\n    Applies a function to elements in two input arrays while iterating from\n    right to left and assigns the results to a new array.\n\n    The applied function is provided the following arguments:\n\n    - v1: element from first input array.\n    - v2: element from second input array.\n    - idx: element index.\n    - arrays: input arrays.\n\n    The returned output array always has a \"generic\" data type. For example, if\n    provided an array-like object, the function returns a generic array. If\n    provided an ndarray, the function returns an ndarray having a \"generic\" data\n    type.\n\n    Input arrays must be either both array-like objects or both ndarray-like\n    objects.\n\n    If input arrays are array-like objects, the arrays must have the same number\n    of elements.\n\n    If input arrays are ndarray-like objects, the arrays must be broadcast\n    compatible.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject|ndarray\n        First input array.\n\n    y: ArrayLikeObject|ndarray\n        Second input array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.add, 2 );\n    > var x = [ 1, 2, 3, 4, 5, 6 ];\n    > var y = [ 1, 1, 1, 1, 1, 1 ];\n    > var out = map2Right( x, y, f )\n    [ 2, 3, 4, 5, 6, 7 ]\n\n    // ndarray:\n    > x = array( x, { 'shape': [ 2, 3 ] } );\n    > y = array( y, { 'shape': [ 2, 3 ] } );\n    > out = map2Right( x, y, f );\n    > var v = out.get( 1, 1 )\n    6\n\n\nmap2Right.assign( x, y, out, fcn[, thisArg] )\n    Applies a function to elements in two input arrays while iterating from\n    right to left and assigns the results to an output array.\n\n    The applied function is provided the following arguments:\n\n    - v1: element from first input array.\n    - v2: element from second input array.\n    - idx: element index.\n    - arrays: input arrays.\n\n    Input and output arrays must be either all array-like objects or all\n    ndarray-like objects.\n\n    If input and output arrays are array-like objects, the arrays must have the\n    same number of elements.\n\n    If input and output arrays are ndarray-like objects, the arrays must be\n    broadcast compatible.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject|ndarray\n        First input array.\n\n    y: ArrayLikeObject|ndarray\n        Second input array.\n\n    out: ArrayLikeObject|ndarray\n        Output array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.add, 2 );\n    > var x = [ 1, 2, 3, 4, 5, 6 ];\n    > var y = [ 1, 1, 1, 1, 1, 1 ];\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > map2Right.assign( x, y, out, f );\n    > out\n    [ 2, 3, 4, 5, 6, 7 ]\n\n    // ndarray:\n    > var opts = { 'shape': [ 2, 3 ] };\n    > x = array( x, opts );\n    > y = array( y, opts );\n    > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n    > map2Right.assign( x, y, out, f );\n    > var v = out.get( 1, 1 )\n    6\n\n    See Also\n    --------\n    mapRight, map2\n","map2Right.assign":"\nmap2Right.assign( x, y, out, fcn[, thisArg] )\n    Applies a function to elements in two input arrays while iterating from\n    right to left and assigns the results to an output array.\n\n    The applied function is provided the following arguments:\n\n    - v1: element from first input array.\n    - v2: element from second input array.\n    - idx: element index.\n    - arrays: input arrays.\n\n    Input and output arrays must be either all array-like objects or all\n    ndarray-like objects.\n\n    If input and output arrays are array-like objects, the arrays must have the\n    same number of elements.\n\n    If input and output arrays are ndarray-like objects, the arrays must be\n    broadcast compatible.\n\n    Parameters\n    ----------\n    x: ArrayLikeObject|ndarray\n        First input array.\n\n    y: ArrayLikeObject|ndarray\n        Second input array.\n\n    out: ArrayLikeObject|ndarray\n        Output array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.add, 2 );\n    > var x = [ 1, 2, 3, 4, 5, 6 ];\n    > var y = [ 1, 1, 1, 1, 1, 1 ];\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > map2Right.assign( x, y, out, f );\n    > out\n    [ 2, 3, 4, 5, 6, 7 ]\n\n    // ndarray:\n    > var opts = { 'shape': [ 2, 3 ] };\n    > x = array( x, opts );\n    > y = array( y, opts );\n    > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n    > map2Right.assign( x, y, out, f );\n    > var v = out.get( 1, 1 )\n    6\n\n    See Also\n    --------\n    mapRight, map2","map3d":"\nmap3d( arr, fcn[, thisArg] )\n    Applies a function to each nested element in a three-dimensional nested\n    array and assigns the result to a nested element in a new three-dimensional\n    nested array.\n\n    The applied function is provided the following arguments:\n\n    - value: array element.\n    - indices: current array element indices.\n    - arr: input array.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject<ArrayLikeObject<ArrayLikeObject>>\n        Input three-dimensional nested array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array<Array<Array>>\n        Three-dimensional nested array.\n\n    Examples\n    --------\n    > var f = naryFunction( base.abs, 1 );\n    > var arr = [ [ [ -1, -2, -3 ] ], [ [ -4, -5, -6 ] ] ];\n    > var out = map3d( arr, f );\n    > out[ 0 ][ 0 ]\n    [ 1, 2, 3 ]\n    > out[ 1 ][ 0 ]\n    [ 4, 5, 6 ]\n\n    See Also\n    --------\n    map, map2d, map4d, map5d\n","map4d":"\nmap4d( arr, fcn[, thisArg] )\n    Applies a function to each nested element in a four-dimensional nested array\n    and assigns the result to a nested element in a new four-dimensional nested\n    array.\n\n    The applied function is provided the following arguments:\n\n    - value: array element.\n    - indices: current array element indices.\n    - arr: input array.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject<ArrayLikeObject>\n        Input four-dimensional nested array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array<Array<Array<Array>>>\n        Four-dimensional nested array.\n\n    Examples\n    --------\n    > var f = naryFunction( base.abs, 1 );\n    > var arr = [ [ [ [ -1, -2, -3 ] ] ], [ [ [ -4, -5, -6 ] ] ] ];\n    > var out = map4d( arr, f );\n    > out[ 0 ][ 0 ][ 0 ]\n    [ 1, 2, 3 ]\n    > out[ 1 ][ 0 ][ 0 ]\n    [ 4, 5, 6 ]\n\n    See Also\n    --------\n    map, map2d, map3d, map5d\n","map5d":"\nmap5d( arr, fcn[, thisArg] )\n    Applies a function to each nested element in a five-dimensional nested array\n    and assigns the result to a nested element in a new five-dimensional nested\n    array.\n\n    The applied function is provided the following arguments:\n\n    - value: array element.\n    - indices: current array element indices.\n    - arr: input array.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject<ArrayLikeObject>\n        Input five-dimensional nested array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array<Array<Array<Array<Array>>>>\n        Five-dimensional nested array.\n\n    Examples\n    --------\n    > var f = naryFunction( base.abs, 1 );\n    > var arr = [ [ [ [ [ -1, -2, -3 ] ] ] ], [ [ [ [ -4, -5, -6 ] ] ] ] ];\n    > var out = map5d( arr, f );\n    > out[ 0 ][ 0 ][ 0 ][ 0 ]\n    [ 1, 2, 3 ]\n    > out[ 1 ][ 0 ][ 0 ][ 0 ]\n    [ 4, 5, 6 ]\n\n    See Also\n    --------\n    map, map2d, map3d, map4d\n","mapArguments":"\nmapArguments( fcn, clbk[, thisArg] )\n    Returns a function that applies arguments to a provided function after\n    transforming arguments according to a callback function.\n\n    The callback function is provided the following arguments:\n\n    - value: argument value.\n    - index: argument index.\n\n    Parameters\n    ----------\n    fcn: Function\n        Input function.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Function\n        Function wrapper.\n\n    Examples\n    --------\n    > function foo( a, b, c ) { return [ a, b, c ]; };\n    > function clbk( v ) { return v * 2; };\n    > var bar = mapArguments( foo, clbk );\n    > var out = bar( 1, 2, 3 )\n    [ 2, 4, 6 ]\n\n    See Also\n    --------\n    filterArguments\n","mapFun":"\nmapFun( fcn, n[, thisArg] )\n    Invokes a function `n` times and returns an array of accumulated function\n    return values.\n\n    The invoked function is provided a single argument: the invocation index\n    (zero-based).\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke.\n\n    n: integer\n        Number of times to invoke a function.\n\n    thisArg: any (optional)\n        Function execution context.\n\n    Returns\n    -------\n    out: Array\n        Array of accumulated function return values.\n\n    Examples\n    --------\n    > function fcn( i ) { return i; };\n    > var arr = mapFun( fcn, 5 )\n    [ 0, 1, 2, 3, 4 ]\n\n    See Also\n    --------\n    mapFunAsync\n","mapFunAsync":"\nmapFunAsync( fcn, n, [options,] done )\n    Invokes a function `n` times and returns an array of accumulated function\n    return values.\n\n    For each iteration, the provided function is invoked with two arguments:\n\n    - index: invocation index (starting from zero).\n    - next: callback to be invoked upon function completion.\n\n    The `next` callback accepts two arguments:\n\n    - error: error argument.\n    - result: function result.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke.\n\n    n: integer\n        Number of times to invoke a function.\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to allow only one pending invocation at a\n        time. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    done: Function\n        A callback invoked upon executing a provided function `n` times or upon\n        encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function fcn( i, next ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         next( null, i );\n    ...     }\n    ... };\n    > function done( error, arr ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( arr );\n    ... };\n    > mapFunAsync( fcn, 10, done )\n    [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n    // Limit number of concurrent invocations:\n    > function fcn( i, next ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         next( null, i );\n    ...     }\n    ... };\n    > function done( error, arr ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( arr );\n    ... };\n    > var opts = { 'limit': 2 };\n    > mapFunAsync( fcn, 10, opts, done )\n    [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n    // Sequential invocation:\n    > function fcn( i, next ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         next( null, i );\n    ...     }\n    ... };\n    > function done( error, arr ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( arr );\n    ... };\n    > var opts = { 'series': true };\n    > mapFunAsync( fcn, 10, opts, done )\n    [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n\nmapFunAsync.factory( [options,] fcn )\n    Returns a function which invokes a function `n` times and returns an array\n    of accumulated function return values.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to allow only one pending invocation at a\n        time. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        Function to invoke.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function `n` times and returns an array of\n        accumulated function return values.\n\n    Examples\n    --------\n    > function fcn( i, next ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         next( null, i );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = mapFunAsync.factory( opts, fcn );\n    > function done( error, arr ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( arr );\n    ... };\n    > f( 10, done )\n    [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n    See Also\n    --------\n    mapFun\n","mapFunAsync.factory":"\nmapFunAsync.factory( [options,] fcn )\n    Returns a function which invokes a function `n` times and returns an array\n    of accumulated function return values.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to allow only one pending invocation at a\n        time. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        Function to invoke.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function `n` times and returns an array of\n        accumulated function return values.\n\n    Examples\n    --------\n    > function fcn( i, next ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         next( null, i );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = mapFunAsync.factory( opts, fcn );\n    > function done( error, arr ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( arr );\n    ... };\n    > f( 10, done )\n    [ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9 ]\n\n    See Also\n    --------\n    mapFun","mapKeys":"\nmapKeys( obj, transform )\n    Maps keys from one object to a new object having the same values.\n\n    The transform function is provided three arguments:\n\n    - key: object key.\n    - value: object value corresponding to `key`.\n    - obj: the input object.\n\n    The value returned by a transform function should be a value which can be\n    serialized as an object key.\n\n    The function only maps own properties. Hence, the function does not map\n    inherited properties.\n\n    The function shallow copies key values.\n\n    Key iteration order is *not* guaranteed.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    transform: Function\n        Transform function. Return values specify the keys of the output object.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > function transform( key, value ) { return key + value; };\n    > var obj = { 'a': 1, 'b': 2 };\n    > var out = mapKeys( obj, transform )\n    { 'a1': 1, 'b2': 2 }\n\n    See Also\n    --------\n    mapValues\n","mapKeysAsync":"\nmapKeysAsync( obj, [options,] transform, done )\n    Maps keys from one object to a new object having the same values.\n\n    When invoked, `transform` is provided a maximum of four arguments:\n\n    - key: object key.\n    - value: object value corresponding to `key`.\n    - obj: the input object.\n    - next: a callback to be invoked after processing an object `key`.\n\n    The actual number of provided arguments depends on function length. If\n    `transform` accepts two arguments, `transform` is provided:\n\n    - key\n    - next\n\n    If `transform` accepts three arguments, `transform` is provided:\n\n    - key\n    - value\n    - next\n\n    For every other `transform` signature, `transform` is provided all four\n    arguments.\n\n    The `next` callback accepts two arguments:\n\n    - error: error argument.\n    - key: transformed key.\n\n    If a `transform` function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    The key returned by a transform function should be a value which can be\n    serialized as an object key.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function only maps own properties. Hence, the function does not map\n    inherited properties.\n\n    The function shallow copies key values.\n\n    Key iteration and insertion order are *not* guaranteed.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each property sequentially.\n        Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    transform: Function\n        Transform function. Returned values specify the keys of the output\n        object.\n\n    done: Function\n        A callback invoked either upon processing all own properties or upon\n        encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function transform( key, value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         next( null, key+':'+value );\n    ...     }\n    ... };\n    > function done( error, out ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( out );\n    ... };\n    > var obj = { 'a': 1, 'b': 2 };\n    > mapKeysAsync( obj, transform, done )\n    { 'a:1': 1, 'b:2': 2 }\n\n    // Limit number of concurrent invocations:\n    > function transform( key, value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         next( null, key+':'+value );\n    ...     }\n    ... };\n    > function done( error, out ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( out );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n    > mapKeysAsync( obj, opts, transform, done )\n    { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n\n    // Process sequentially:\n    > function transform( key, value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         next( null, key+':'+value );\n    ...     }\n    ... };\n    > function done( error, out ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( out );\n    ... };\n    > var opts = { 'series': true };\n    > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n    > mapKeysAsync( obj, opts, transform, done )\n    { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n\n\nmapKeysAsync.factory( [options,] transform )\n    Returns a function which maps keys from one object to a new object having\n    the same values.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each property sequentially.\n        Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    transform: Function\n        Transform function. Returned values specify the keys of the output\n        object.\n\n    Returns\n    -------\n    out: Function\n        A function which maps keys from one object to a new object having the\n        same values.\n\n    Examples\n    --------\n    > function transform( key, value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         next( null, key+':'+value );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = mapKeysAsync.factory( opts, transform );\n    > function done( error, out ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( out );\n    ... };\n    > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n    > f( obj, done )\n    { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n    > obj = { 'beep': 'boop' };\n    > f( obj, done )\n    { 'beep:boop': 'beep' }\n\n    See Also\n    --------\n    mapKeys, mapValuesAsync\n","mapKeysAsync.factory":"\nmapKeysAsync.factory( [options,] transform )\n    Returns a function which maps keys from one object to a new object having\n    the same values.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each property sequentially.\n        Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    transform: Function\n        Transform function. Returned values specify the keys of the output\n        object.\n\n    Returns\n    -------\n    out: Function\n        A function which maps keys from one object to a new object having the\n        same values.\n\n    Examples\n    --------\n    > function transform( key, value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         next( null, key+':'+value );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = mapKeysAsync.factory( opts, transform );\n    > function done( error, out ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( out );\n    ... };\n    > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n    > f( obj, done )\n    { 'a:1': 1, 'b:2': 2, 'c:3': 3 }\n    > obj = { 'beep': 'boop' };\n    > f( obj, done )\n    { 'beep:boop': 'beep' }\n\n    See Also\n    --------\n    mapKeys, mapValuesAsync","mapReduce":"\nmapReduce( arr, initial, mapper, reducer[, thisArg] )\n    Performs a map-reduce operation for each element in an array and returns the\n    accumulated result.\n\n    When invoked, the mapping function is provided three arguments:\n\n    - value: array element.\n    - index: element index.\n    - arr: input array.\n\n    When invoked, the reducing function is provided four arguments:\n\n    - accumulator: accumulated value.\n    - value: result after applying the mapping function to the current array\n      element.\n    - index: element index.\n    - arr: input array.\n\n    If provided an empty array, the function returns the initial value.\n\n    When provided an ndarray, the function performs a single-pass map-reduce\n    operation over the entire input ndarray (i.e., higher-order ndarray\n    dimensions are flattened to a single-dimension).\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject|ndarray\n        Input array.\n\n    initial: any\n        Accumulator value used in the first invocation of the reduction\n        function.\n\n    mapper: Function\n        Mapping function.\n\n    reducer: Function\n        Reducing function.\n\n    thisArg: any (optional)\n        Execution context for the reducing function.\n\n    Returns\n    -------\n    out: any\n        Accumulated result.\n\n    Examples\n    --------\n    // array-like object:\n    > var f1 = naryFunction( base.abs, 1 );\n    > var f2 = naryFunction( base.add, 2 );\n    > var arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\n    > var out = mapReduce( arr, 0.0, f1, f2 )\n    21.0\n\n    // ndarray:\n    > arr = array( arr, { 'shape': [ 2, 3 ] } );\n    > out = mapReduce( arr, 0.0, f1, f2 )\n    21.0\n\n    See Also\n    --------\n    map, mapReduceRight, reduce\n","mapReduceRight":"\nmapReduceRight( arr, initial, mapper, reducer[, thisArg] )\n    Performs a map-reduce operation for each element in an array while iterating\n    from right to left and returns the accumulated result.\n\n    When invoked, the mapping function is provided three arguments:\n\n    - value: array element.\n    - index: element index.\n    - arr: input array.\n\n    When invoked, the reducing function is provided four arguments:\n\n    - accumulator: accumulated value.\n    - value: result after applying the mapping function to the current array\n      element.\n    - index: element index.\n    - arr: input array.\n\n    If provided an empty array, the function returns the initial value.\n\n    When provided an ndarray, the function performs a single-pass map-reduce\n    operation over the entire input ndarray (i.e., higher-order ndarray\n    dimensions are flattened to a single-dimension).\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject|ndarray\n        Input array.\n\n    initial: any\n        Accumulator value used in the first invocation of the reduction\n        function.\n\n    mapper: Function\n        Mapping function.\n\n    reducer: Function\n        Reducing function.\n\n    thisArg: any (optional)\n        Execution context for the reducing function.\n\n    Returns\n    -------\n    out: any\n        Accumulated result.\n\n    Examples\n    --------\n    // array-like object:\n    > var f1 = naryFunction( base.abs, 1 );\n    > var f2 = naryFunction( base.add, 2 );\n    > var arr = [ -1.0, -2.0, -3.0, -4.0, -5.0, -6.0 ];\n    > var out = mapReduceRight( arr, 0.0, f1, f2 )\n    21.0\n\n    // ndarray:\n    > arr = array( arr, { 'shape': [ 2, 3 ] } );\n    > out = mapReduceRight( arr, 0.0, f1, f2 )\n    21.0\n\n    See Also\n    --------\n    mapRight, mapReduce, reduceRight\n","mapRight":"\nmapRight( arr, fcn[, thisArg] )\n    Applies a function to each element in an array and assigns the result to an\n    element in a new array, iterating from right to left.\n\n    The applied function is provided the following arguments:\n\n    - value: array element.\n    - index: element index.\n    - arr: input array.\n\n    The returned output array always has a \"generic\" data type. For example, if\n    provided an array-like object, the function returns a generic array. If\n    provided an ndarray, the function returns an ndarray having a \"generic\" data\n    type.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject|ndarray\n        Input array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.abs, 1 );\n    > var arr = [ -1, -2, -3, -4, -5, -6 ];\n    > var out = mapRight( arr, f )\n    [ 1, 2, 3, 4, 5, 6 ]\n\n    // ndarray:\n    > arr = array( arr, { 'shape': [ 2, 3 ] } );\n    > out = mapRight( arr, f );\n    > var v = out.get( 1, 1 )\n    5\n\n\nmapRight.assign( arr, out, fcn[, thisArg] )\n    Applies a function to each element in an array and assigns the result to an\n    element in an output array, iterating from right to left.\n\n    The applied function is provided the following arguments:\n\n    - value: array element.\n    - index: element index.\n    - arr: input array.\n\n    Input and output arrays must be either both array-like objects or both\n    ndarray-like objects.\n\n    If input and output arrays are array-like objects, the arrays must have the\n    same number of elements.\n\n    If input and output arrays are both ndarray-like objects, the arrays *must*\n    be broadcast compatible.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject|ndarray\n        Input array.\n\n    out: ArrayLikeObject|ndarray\n        Output array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.abs, 1 );\n    > var arr = [ -1, -2, -3, -4, -5, -6 ];\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > mapRight.assign( arr, out, f );\n    > out\n    [ 1, 2, 3, 4, 5, 6 ]\n\n    // ndarray:\n    > var opts = { 'shape': [ 2, 3 ] };\n    > arr = array( arr, opts );\n    > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n    > mapRight.assign( arr, out, f );\n    > var v = out.get( 1, 1 )\n    5\n\n    See Also\n    --------\n    map, reduce\n","mapRight.assign":"\nmapRight.assign( arr, out, fcn[, thisArg] )\n    Applies a function to each element in an array and assigns the result to an\n    element in an output array, iterating from right to left.\n\n    The applied function is provided the following arguments:\n\n    - value: array element.\n    - index: element index.\n    - arr: input array.\n\n    Input and output arrays must be either both array-like objects or both\n    ndarray-like objects.\n\n    If input and output arrays are array-like objects, the arrays must have the\n    same number of elements.\n\n    If input and output arrays are both ndarray-like objects, the arrays *must*\n    be broadcast compatible.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject|ndarray\n        Input array.\n\n    out: ArrayLikeObject|ndarray\n        Output array.\n\n    fcn: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array|ndarray\n        Output array.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.abs, 1 );\n    > var arr = [ -1, -2, -3, -4, -5, -6 ];\n    > var out = [ 0, 0, 0, 0, 0, 0 ];\n    > mapRight.assign( arr, out, f );\n    > out\n    [ 1, 2, 3, 4, 5, 6 ]\n\n    // ndarray:\n    > var opts = { 'shape': [ 2, 3 ] };\n    > arr = array( arr, opts );\n    > out = array( [ 0, 0, 0, 0, 0, 0 ], opts );\n    > mapRight.assign( arr, out, f );\n    > var v = out.get( 1, 1 )\n    5\n\n    See Also\n    --------\n    map, reduce","mapValues":"\nmapValues( obj, transform )\n    Maps values from one object to a new object having the same keys.\n\n    The transform function is provided three arguments:\n\n    - value: object value corresponding to `key`.\n    - key: object key.\n    - obj: the input object.\n\n    The function only maps values from own properties. Hence, the function does\n    not map inherited properties.\n\n    The function shallow copies key values.\n\n    Key iteration order is *not* guaranteed.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    transform: Function\n        Transform function. Return values are the key values of the output\n        object.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > function transform( value, key ) { return key + value; };\n    > var obj = { 'a': 1, 'b': 2 };\n    > var out = mapValues( obj, transform )\n    { 'a': 'a1', 'b': 'b2' }\n\n    See Also\n    --------\n    mapKeys, omitBy, pickBy\n","mapValuesAsync":"\nmapValuesAsync( obj, [options,] transform, done )\n    Maps values from one object to a new object having the same keys.\n\n    When invoked, `transform` is provided a maximum of four arguments:\n\n    - value: object value corresponding to `key`.\n    - key: object key.\n    - obj: the input object.\n    - next: a callback to be invoked after processing an object `value`.\n\n    The actual number of provided arguments depends on function length. If\n    `transform` accepts two arguments, `transform` is provided:\n\n    - value\n    - next\n\n    If `transform` accepts three arguments, `transform` is provided:\n\n    - value\n    - key\n    - next\n\n    For every other `transform` signature, `transform` is provided all four\n    arguments.\n\n    The `next` callback accepts two arguments:\n\n    - error: error argument.\n    - value: transformed value.\n\n    If a `transform` function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function only maps values from own properties. Hence, the function does\n    not map inherited properties.\n\n    The function shallow copies key values.\n\n    Key iteration and insertion order are *not* guaranteed.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each property sequentially.\n        Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    transform: Function\n        Transform function. Return values are the key values of the output\n        object.\n\n    done: Function\n        A callback invoked either upon processing all own properties or upon\n        encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function transform( value, key, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         next( null, key+':'+value );\n    ...     }\n    ... };\n    > function done( error, out ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( out );\n    ... };\n    > var obj = { 'a': 1, 'b': 2 };\n    > mapValuesAsync( obj, transform, done )\n    { 'a': 'a:1', 'b': 'b:2' }\n\n    // Limit number of concurrent invocations:\n    > function transform( value, key, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         next( null, key+':'+value );\n    ...     }\n    ... };\n    > function done( error, out ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( out );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n    > mapValuesAsync( obj, opts, transform, done )\n    { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n\n    // Process sequentially:\n    > function transform( value, key, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         next( null, key+':'+value );\n    ...     }\n    ... };\n    > function done( error, out ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( out );\n    ... };\n    > var opts = { 'series': true };\n    > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n    > mapValuesAsync( obj, opts, transform, done )\n    { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n\n\nmapValuesAsync.factory( [options,] transform )\n    Returns a function which maps values from one object to a new object having\n    the same keys.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each property sequentially.\n        Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    transform: Function\n        Transform function. Return values are the key values of the output\n        object.\n\n    Returns\n    -------\n    out: Function\n        A function which maps values from one object to a new object having the\n        same keys.\n\n    Examples\n    --------\n    > function transform( value, key, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         next( null, key+':'+value );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = mapValuesAsync.factory( opts, transform );\n    > function done( error, out ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( out );\n    ... };\n    > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n    > f( obj, done )\n    { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n    > obj = { 'beep': 'boop' };\n    > f( obj, done )\n    { 'beep': 'beep:boop' }\n\n    See Also\n    --------\n    mapKeysAsync, mapValues\n","mapValuesAsync.factory":"\nmapValuesAsync.factory( [options,] transform )\n    Returns a function which maps values from one object to a new object having\n    the same keys.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each property sequentially.\n        Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    transform: Function\n        Transform function. Return values are the key values of the output\n        object.\n\n    Returns\n    -------\n    out: Function\n        A function which maps values from one object to a new object having the\n        same keys.\n\n    Examples\n    --------\n    > function transform( value, key, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         next( null, key+':'+value );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = mapValuesAsync.factory( opts, transform );\n    > function done( error, out ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( out );\n    ... };\n    > var obj = { 'a': 1, 'b': 2, 'c': 3 };\n    > f( obj, done )\n    { 'a': 'a:1', 'b': 'b:2', 'c': 'c:3' }\n    > obj = { 'beep': 'boop' };\n    > f( obj, done )\n    { 'beep': 'beep:boop' }\n\n    See Also\n    --------\n    mapKeysAsync, mapValues","maskArguments":"\nmaskArguments( fcn, mask[, thisArg] )\n    Returns a function that applies arguments to a provided function according\n    to a specified mask.\n\n    Only those arguments having a truthy mask value are applied to a provided\n    function.\n\n    Parameters\n    ----------\n    fcn: Function\n        Input function.\n\n    mask: ArrayLikeObject\n        Mask array.\n\n    thisArg: any (optional)\n        Function context.\n\n    Returns\n    -------\n    out: Function\n        Function wrapper.\n\n    Examples\n    --------\n    > function foo( a, b ) { return [ a, b ]; };\n    > var bar = maskArguments( foo, [ 1, 0, 1 ] );\n    > var out = bar( 1, 2, 3 )\n    [ 1, 3 ]\n\n    See Also\n    --------\n    filterArguments, rejectArguments, reorderArguments, reverseArguments\n","MAX_ARRAY_LENGTH":"\nMAX_ARRAY_LENGTH\n    Maximum length for a generic array.\n\n    Examples\n    --------\n    > MAX_ARRAY_LENGTH\n    4294967295\n\n    See Also\n    --------\n    MAX_TYPED_ARRAY_LENGTH\n","MAX_TYPED_ARRAY_LENGTH":"\nMAX_TYPED_ARRAY_LENGTH\n    Maximum length for a typed array.\n\n    Examples\n    --------\n    > MAX_TYPED_ARRAY_LENGTH\n    9007199254740991\n\n    See Also\n    --------\n    MAX_ARRAY_LENGTH\n","maybeBroadcastArray":"\nmaybeBroadcastArray( x, shape )\n    Broadcasts an ndarray to a specified shape if and only if the specified\n    shape differs from the provided ndarray's shape.\n\n    If a provided ndarray has the same shape as the specified shape, the\n    function returns the provided ndarray.\n\n    If a provided ndarray has a different (broadcast compatible) shape than the\n    specified shape, the function returns a new *read-only* ndarray view of the\n    provided ndarray's data. The view is typically *not* contiguous. As more\n    than one element of a returned view may refer to the same memory location,\n    writing to the input ndarray may affect multiple elements. If you need to\n    write to the input ndarray, copy the input ndarray before broadcasting.\n\n    The function throws an error if a provided ndarray is incompatible with a\n    provided shape.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    shape: ArrayLikeObject\n        Desired shape.\n\n    Returns\n    -------\n    out: ndarray\n        Broadcasted array.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n    <ndarray>\n    > var sh = x.shape\n    [ 2, 2 ]\n    > var y = maybeBroadcastArray( x, [ 3, 2, 2 ] )\n    <ndarray>\n    > sh = y.shape\n    [ 3, 2, 2 ]\n    > var v = y.get( 0, 0, 0 )\n    1\n    > v = y.get( 0, 0, 1 )\n    2\n    > v = y.get( 0, 1, 0 )\n    3\n    > v = y.get( 0, 1, 1 )\n    4\n    > v = y.get( 1, 0, 0 )\n    1\n    > v = y.get( 1, 1, 0 )\n    3\n    > v = y.get( 2, 0, 0 )\n    1\n    > v = y.get( 2, 1, 1 )\n    4\n\n    See Also\n    --------\n    array, ndarray, broadcastArray, maybeBroadcastArrays\n","maybeBroadcastArrays":"\nmaybeBroadcastArrays( ...arrays )\n    Broadcasts ndarrays to a common shape.\n\n    The function supports two (mutually exclusive) means of providing ndarray\n    arguments:\n\n    1. Providing a single array containing ndarray arguments.\n    2. Providing ndarray arguments as separate arguments.\n\n    If a provided ndarray has a shape matching the common shape, the function\n    returns the provided ndarray.\n\n    If a provided ndarray has a different (broadcast compatible) shape than the\n    common shape, the function returns a new *read-only* ndarray view of the\n    provided ndarray's data. The view is typically *not* contiguous. As more\n    than one element of a returned view may refer to the same memory location,\n    writing to a view may affect multiple elements. If you need to write to an\n    input ndarray, copy the input ndarray before broadcasting.\n\n    The function throws an error if a provided broadcast-incompatible ndarrays.\n\n    Parameters\n    ----------\n    arrays: ...ndarray|ArrayLikeObject<ndarray>\n        Array arguments.\n\n    Returns\n    -------\n    out: Array<ndarray>\n        Broadcasted arrays.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n    <ndarray>\n    > var sh = x.shape\n    [ 2, 2 ]\n    > var y = ndzeros( [ 3, 2, 2 ] )\n    <ndarray>\n    > var out = maybeBroadcastArrays( [ x, y ] )\n    [ <ndarray>, <ndarray> ]\n\n    // Retrieve the broadcasted \"x\" array:\n    > var bx = out[ 0 ]\n    <ndarray>\n    > sh = bx.shape\n    [ 3, 2, 2 ]\n\n    // Retrieve broadcasted elements...\n    > var v = bx.get( 0, 0, 0 )\n    1\n    > v = bx.get( 0, 0, 1 )\n    2\n    > v = bx.get( 0, 1, 0 )\n    3\n    > v = bx.get( 0, 1, 1 )\n    4\n    > v = bx.get( 1, 0, 0 )\n    1\n    > v = bx.get( 1, 1, 0 )\n    3\n    > v = bx.get( 2, 0, 0 )\n    1\n    > v = bx.get( 2, 1, 1 )\n    4\n\n    See Also\n    --------\n    array, ndarray, broadcastArrays, maybeBroadcastArray\n","memoize":"\nmemoize( fcn[, hashFunction] )\n    Returns a memoized function.\n\n    The function does not set the `length` property of the returned function.\n    Accordingly, the returned function `length` is always zero.\n\n    The evaluation context is always `null`.\n\n    The function serializes provided arguments as a string and stores results\n    using the string as an identifier. To use a custom hash function, provide a\n    hash function argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to memoize.\n\n    hashFunction: Function (optional)\n        Function to map a set of arguments to a single value identifying that\n        set.\n\n    Returns\n    -------\n    out: Function\n        Memoized function.\n\n    Examples\n    --------\n    > function factorial( n ) {\n    ...     var prod;\n    ...     var i;\n    ...     prod = 1;\n    ...     for ( i = n; i > 1; i-- ) {\n    ...         prod *= i;\n    ...     }\n    ...     return prod;\n    ... };\n    > var memoized = memoize( factorial );\n    > var v = memoized( 5 )\n    120\n    > v = memoized( 5 )\n    120\n\n","merge":"\nmerge( target, ...source )\n    Merges objects into a target object.\n\n    The target object is mutated.\n\n    Only plain objects are merged and extended. Other values/types are either\n    deep copied or assigned.\n\n    Support for deep merging class instances is inherently fragile.\n\n    `Number`, `String`, and `Boolean` objects are merged as primitives.\n\n    Functions are not deep copied.\n\n    Parameters\n    ----------\n    target: Object\n        Target object.\n\n    source: ...Object\n        Source objects (i.e., objects to be merged into the target object).\n\n    Returns\n    -------\n    out: Object\n        Merged (target) object.\n\n    Examples\n    --------\n    > var target = { 'a': 'beep' };\n    > var source = { 'a': 'boop', 'b': 'bap' };\n    > var out = merge( target, source )\n    { 'a': 'boop', 'b': 'bap' }\n    > var bool = ( out === target )\n    true\n\n\nmerge.factory( options )\n    Returns a function for merging and extending objects.\n\n    Parameters\n    ----------\n    options: Object\n        Options.\n\n    options.level: integer (optional)\n        Merge level. Default: Infinity.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to deep copy merged values. Deep copying\n        prevents shared references and source object mutation. Default: true.\n\n    options.override: boolean|Function (optional)\n        Defines the merge strategy. If `true`, source object values will always\n        override target object values. If `false`, source values never override\n        target values (useful for adding, but not overwriting, properties). To\n        define a custom merge strategy, provide a function. Default: true.\n\n    options.extend: boolean (optional)\n        Boolean indicating whether new properties can be added to the target\n        object. If `false`, only shared properties are merged. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function which can be used to merge objects.\n\n    Examples\n    --------\n    > var opts = {\n    ...     'level': 100,\n    ...     'copy': true,\n    ...     'override': true,\n    ...     'extend': true\n    ... };\n    > var merge = merge.factory( opts )\n    <Function>\n\n    // Set the `level` option to limit the merge depth:\n    > merge = merge.factory( { 'level': 2 } );\n    > var target = {\n    ...     '1': { 'a': 'beep', '2': { '3': null, 'b': [ 5, 6, 7 ] } }\n    ... };\n    > var source = {\n    ...     '1': { 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } }\n    ... };\n    > var out = merge( target, source )\n    { '1': { 'a': 'beep', 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } } }\n\n    // Set the `copy` option to `false` to allow shared references:\n    > merge = merge.factory( { 'copy': false } );\n    > target = {};\n    > source = { 'a': [ 1, 2, 3 ] };\n    > out = merge( target, source );\n    > var bool = ( out.a === source.a )\n    true\n\n    // Set the `override` option to `false` to preserve existing properties:\n    > merge = merge.factory( { 'override': false } );\n    > target = { 'a': 'beep', 'b': 'boop' };\n    > source = { 'a': null, 'c': 'bop' };\n    > out = merge( target, source )\n    { 'a': 'beep', 'b': 'boop', 'c': 'bop' }\n\n    // Define a custom merge strategy:\n    > function strategy( a, b, key ) {\n    ...     // a => target value\n    ...     // b => source value\n    ...     // key => object key\n    ...     if ( key === 'a' ) {\n    ...         return b;\n    ...     }\n    ...     if ( key === 'b' ) {\n    ...         return a;\n    ...     }\n    ...     return 'bebop';\n    ... };\n    > merge = merge.factory( { 'override': strategy } );\n    > target = { 'a': 'beep', 'b': 'boop', 'c': 1234 };\n    > source = { 'a': null, 'b': {}, 'c': 'bop' };\n    > out = merge( target, source )\n    { 'a': null, 'b': 'boop', 'c': 'bebop' }\n\n    // Prevent non-existent properties from being added to the target object:\n    > merge = merge.factory( { 'extend': false } );\n    > target = { 'a': 'beep', 'b': 'boop' };\n    > source = { 'b': 'hello', 'c': 'world' };\n    > out = merge( target, source )\n    { 'a': 'beep', 'b': 'hello' }\n\n    See Also\n    --------\n    copy\n","merge.factory":"\nmerge.factory( options )\n    Returns a function for merging and extending objects.\n\n    Parameters\n    ----------\n    options: Object\n        Options.\n\n    options.level: integer (optional)\n        Merge level. Default: Infinity.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to deep copy merged values. Deep copying\n        prevents shared references and source object mutation. Default: true.\n\n    options.override: boolean|Function (optional)\n        Defines the merge strategy. If `true`, source object values will always\n        override target object values. If `false`, source values never override\n        target values (useful for adding, but not overwriting, properties). To\n        define a custom merge strategy, provide a function. Default: true.\n\n    options.extend: boolean (optional)\n        Boolean indicating whether new properties can be added to the target\n        object. If `false`, only shared properties are merged. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function which can be used to merge objects.\n\n    Examples\n    --------\n    > var opts = {\n    ...     'level': 100,\n    ...     'copy': true,\n    ...     'override': true,\n    ...     'extend': true\n    ... };\n    > var merge = merge.factory( opts )\n    <Function>\n\n    // Set the `level` option to limit the merge depth:\n    > merge = merge.factory( { 'level': 2 } );\n    > var target = {\n    ...     '1': { 'a': 'beep', '2': { '3': null, 'b': [ 5, 6, 7 ] } }\n    ... };\n    > var source = {\n    ...     '1': { 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } }\n    ... };\n    > var out = merge( target, source )\n    { '1': { 'a': 'beep', 'b': 'boop', '2': { '3': [ 1, 2, 3 ] } } }\n\n    // Set the `copy` option to `false` to allow shared references:\n    > merge = merge.factory( { 'copy': false } );\n    > target = {};\n    > source = { 'a': [ 1, 2, 3 ] };\n    > out = merge( target, source );\n    > var bool = ( out.a === source.a )\n    true\n\n    // Set the `override` option to `false` to preserve existing properties:\n    > merge = merge.factory( { 'override': false } );\n    > target = { 'a': 'beep', 'b': 'boop' };\n    > source = { 'a': null, 'c': 'bop' };\n    > out = merge( target, source )\n    { 'a': 'beep', 'b': 'boop', 'c': 'bop' }\n\n    // Define a custom merge strategy:\n    > function strategy( a, b, key ) {\n    ...     // a => target value\n    ...     // b => source value\n    ...     // key => object key\n    ...     if ( key === 'a' ) {\n    ...         return b;\n    ...     }\n    ...     if ( key === 'b' ) {\n    ...         return a;\n    ...     }\n    ...     return 'bebop';\n    ... };\n    > merge = merge.factory( { 'override': strategy } );\n    > target = { 'a': 'beep', 'b': 'boop', 'c': 1234 };\n    > source = { 'a': null, 'b': {}, 'c': 'bop' };\n    > out = merge( target, source )\n    { 'a': null, 'b': 'boop', 'c': 'bebop' }\n\n    // Prevent non-existent properties from being added to the target object:\n    > merge = merge.factory( { 'extend': false } );\n    > target = { 'a': 'beep', 'b': 'boop' };\n    > source = { 'b': 'hello', 'c': 'world' };\n    > out = merge( target, source )\n    { 'a': 'beep', 'b': 'hello' }\n\n    See Also\n    --------\n    copy","MILLISECONDS_IN_DAY":"\nMILLISECONDS_IN_DAY\n    Number of milliseconds in a day.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var days = 3.14;\n    > var ms = days * MILLISECONDS_IN_DAY\n    271296000\n\n","MILLISECONDS_IN_HOUR":"\nMILLISECONDS_IN_HOUR\n    Number of milliseconds in an hour.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var hrs = 3.14;\n    > var ms = hrs * MILLISECONDS_IN_HOUR\n    11304000\n\n","MILLISECONDS_IN_MINUTE":"\nMILLISECONDS_IN_MINUTE\n    Number of milliseconds in a minute.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies arising due to complications with time and dates.\n\n    Examples\n    --------\n    > var mins = 3.14;\n    > var ms = mins * MILLISECONDS_IN_MINUTE\n    188400\n\n","MILLISECONDS_IN_SECOND":"\nMILLISECONDS_IN_SECOND\n    Number of milliseconds in a second.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies arising due to complications with time and dates.\n\n    Examples\n    --------\n    > var secs = 3.14;\n    > var ms = secs * MILLISECONDS_IN_SECOND\n    3140\n\n","MILLISECONDS_IN_WEEK":"\nMILLISECONDS_IN_WEEK\n    Number of milliseconds in a week.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var weeks = 3.14;\n    > var ms = weeks * MILLISECONDS_IN_WEEK\n    1899072000\n\n","MINARD_NAPOLEONS_MARCH":"\nMINARD_NAPOLEONS_MARCH( [options] )\n    Returns data for Charles Joseph Minard's cartographic depiction of\n    Napoleon's Russian campaign of 1812.\n\n    Data includes the following:\n\n    - army: army size.\n    - cities: cities.\n    - labels: map labels.\n    - temperature: temperature during the army's return from Russia.\n    - rivers: river data.\n\n    Temperatures are on the Réaumur scale. Multiply each temperature by `1.25`\n    to convert to Celsius.\n\n    River data is formatted as GeoJSON.\n\n    River data is incomplete, with portions of rivers missing.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.data: string (optional)\n        Dataset name.\n\n    Returns\n    -------\n    out: Object|Array<Object>\n        Minard's data.\n\n    Examples\n    --------\n    > var data = MINARD_NAPOLEONS_MARCH();\n    > var army = data.army\n    [...]\n    > var cities = data.cities\n    [...]\n    > var labels = data.labels\n    [...]\n    > var river = data.river\n    {...}\n    > var t = data.temperature\n    [...]\n\n    References\n    ----------\n    - Minard, Charles Joseph. 1869. *Tableaux graphiques et cartes figuratives*.\n    Ecole nationale des ponts et chaussées.\n    - Wilkinson, Leland. 2005. *The Grammar of Graphics*. Springer-Verlag New\n    York. doi:10.1007/0-387-28695-0.\n\n","MINUTES_IN_DAY":"\nMINUTES_IN_DAY\n    Number of minutes in a day.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var days = 3.14;\n    > var mins = days * MINUTES_IN_DAY\n    4521.6\n\n","MINUTES_IN_HOUR":"\nMINUTES_IN_HOUR\n    Number of minutes in an hour.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var hrs = 3.14;\n    > var mins = hrs * MINUTES_IN_HOUR\n    188.4\n\n","MINUTES_IN_WEEK":"\nMINUTES_IN_WEEK\n    Number of minutes in a week.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var wks = 3.14;\n    > var mins = wks * MINUTES_IN_WEEK\n    31651.2\n\n","minutesInMonth":"\nminutesInMonth( [month[, year]] )\n    Returns the number of minutes in a month.\n\n    By default, the function returns the number of minutes in the current month\n    of the current year (according to local time). To determine the number of\n    minutes for a particular month and year, provide `month` and `year`\n    arguments.\n\n    A `month` may be either a month's integer value, three letter abbreviation,\n    or full name (case insensitive).\n\n    The function's return value is a generalization and does **not** take into\n    account inaccuracies due to daylight savings conventions, crossing\n    timezones, or other complications with time and dates.\n\n    Parameters\n    ----------\n    month: string|Date|integer (optional)\n        Month.\n\n    year: integer (optional)\n        Year.\n\n    Returns\n    -------\n    out: integer\n        Minutes in a month.\n\n    Examples\n    --------\n    > var num = minutesInMonth()\n    <number>\n    > num = minutesInMonth( 2 )\n    <number>\n    > num = minutesInMonth( 2, 2016 )\n    41760\n    > num = minutesInMonth( 2, 2017 )\n    40320\n\n    // Other ways to supply month:\n    > num = minutesInMonth( 'feb', 2016 )\n    41760\n    > num = minutesInMonth( 'february', 2016 )\n    41760\n\n    See Also\n    --------\n    minutesInYear\n","minutesInYear":"\nminutesInYear( [value] )\n    Returns the number of minutes in a year according to the Gregorian calendar.\n\n    By default, the function returns the number of minutes in the current year\n    (according to local time). To determine the number of minutes for a\n    particular year, provide either a year or a `Date` object.\n\n    The function's return value is a generalization and does **not** take into\n    account inaccuracies due to daylight savings conventions, crossing\n    timezones, or other complications with time and dates.\n\n    Parameters\n    ----------\n    value: integer|Date (optional)\n        Year or `Date` object.\n\n    Returns\n    -------\n    out: integer\n        Number of minutes in a year.\n\n    Examples\n    --------\n    > var num = minutesInYear()\n    <number>\n    > num = minutesInYear( 2016 )\n    527040\n    > num = minutesInYear( 2017 )\n    525600\n\n    See Also\n    --------\n    minutesInMonth\n","MOBY_DICK":"\nMOBY_DICK()\n    Returns the text of Moby Dick by Herman Melville.\n\n    Each array element has the following fields:\n\n    - chapter: book chapter (number or identifier).\n    - title: chapter title (if available; otherwise, empty).\n    - text: chapter text.\n\n    Returns\n    -------\n    out: Array<Object>\n        Book text.\n\n    Examples\n    --------\n    > var data = MOBY_DICK()\n    [ {...}, {...}, ... ]\n\n","MONTH_NAMES_EN":"\nMONTH_NAMES_EN()\n    Returns a list of month names (English).\n\n    Returns\n    -------\n    out: Array<string>\n        List of month names.\n\n    Examples\n    --------\n    > var list = MONTH_NAMES_EN()\n    [ 'January', 'February', 'March', 'April', ... ]\n\n","MONTHS_IN_YEAR":"\nMONTHS_IN_YEAR\n    Number of months in a year.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var yrs = 3.14;\n    > var mons = yrs * MONTHS_IN_YEAR\n    37.68\n\n","moveProperty":"\nmoveProperty( source, prop, target )\n    Moves a property from one object to another object.\n\n    The property is deleted from the source object and the property's descriptor\n    is preserved during transfer.\n\n    If a source property is not configurable, the function throws an error, as\n    the property cannot be deleted from the source object.\n\n    Parameters\n    ----------\n    source: Object\n        Source object.\n\n    prop: string\n        Property to move.\n\n    target: Object\n        Target object.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether operation was successful.\n\n    Examples\n    --------\n    > var obj1 = { 'a': 'b' };\n    > var obj2 = {};\n    > var bool = moveProperty( obj1, 'a', obj2 )\n    true\n    > bool = moveProperty( obj1, 'c', obj2 )\n    false\n\n","MultiSlice":"\nMultiSlice( ...slice )\n    Returns a multi-slice.\n\n    Parameters\n    ----------\n    ...slice: Slice|integer|null|undefined\n        Slice arguments.\n\n    Returns\n    -------\n    s: MultiSlice\n        MultiSlice instance.\n\n    Examples\n    --------\n    > var s = new Slice( 2, 10 );\n    > var ms = new MultiSlice( 2, s, 1 );\n\n\nMultiSlice.prototype.ndims\n    Read-only property returning the number of slice dimensions.\n\n    Returns\n    -------\n    ndims: integer\n        Number of slice dimensions.\n\n    Examples\n    --------\n    > var s = new Slice( 2, 10 );\n    > var ms = new MultiSlice( 2, s, 1 );\n    > ms.ndims\n    3\n\n\nMultiSlice.prototype.data\n    Read-only property returning the slice data.\n\n    Returns\n    -------\n    data: Array<Slice|integer|null>\n        Slice data.\n\n    Examples\n    --------\n    > var s = new Slice( 2, 10 );\n    > var ms = new MultiSlice( 2, s, 1 );\n    > ms.data\n    [ 2, <Slice>, 1 ]\n\n\nMultiSlice.prototype.toString()\n    Serializes a multi-slice as a string.\n\n    Returns\n    -------\n    str: string\n        Serialized multi-slice string.\n\n    Examples\n    --------\n    > var s = new Slice( 2, 10 );\n    > var ms = new MultiSlice( 2, s, 1 );\n    > ms.toString()\n    'MultiSlice(2,Slice(2,10,null),1)'\n\n\nMultiSlice.prototype.toJSON()\n    Serializes a multi-slice as a JSON object.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var s = new Slice( 2, 10, 1 );\n    > var ms = new MultiSlice( 2, s );\n    > ms.toJSON()\n    {'type':'MultiSlice','data':[2,{'type':'Slice','data':[2,10,1]}]}\n\n    See Also\n    --------\n    ndarray, Slice\n","MultiSlice.prototype.ndims":"\nMultiSlice.prototype.ndims\n    Read-only property returning the number of slice dimensions.\n\n    Returns\n    -------\n    ndims: integer\n        Number of slice dimensions.\n\n    Examples\n    --------\n    > var s = new Slice( 2, 10 );\n    > var ms = new MultiSlice( 2, s, 1 );\n    > ms.ndims\n    3","MultiSlice.prototype.data":"\nMultiSlice.prototype.data\n    Read-only property returning the slice data.\n\n    Returns\n    -------\n    data: Array<Slice|integer|null>\n        Slice data.\n\n    Examples\n    --------\n    > var s = new Slice( 2, 10 );\n    > var ms = new MultiSlice( 2, s, 1 );\n    > ms.data\n    [ 2, <Slice>, 1 ]","MultiSlice.prototype.toString":"\nMultiSlice.prototype.toString()\n    Serializes a multi-slice as a string.\n\n    Returns\n    -------\n    str: string\n        Serialized multi-slice string.\n\n    Examples\n    --------\n    > var s = new Slice( 2, 10 );\n    > var ms = new MultiSlice( 2, s, 1 );\n    > ms.toString()\n    'MultiSlice(2,Slice(2,10,null),1)'","MultiSlice.prototype.toJSON":"\nMultiSlice.prototype.toJSON()\n    Serializes a multi-slice as a JSON object.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var s = new Slice( 2, 10, 1 );\n    > var ms = new MultiSlice( 2, s );\n    > ms.toJSON()\n    {'type':'MultiSlice','data':[2,{'type':'Slice','data':[2,10,1]}]}\n\n    See Also\n    --------\n    ndarray, Slice","namedtypedtuple":"\nnamedtypedtuple( fields[, options] )\n    Returns a named typed tuple factory.\n\n    Named tuples assign a property name, and thus a meaning, to each position in\n    a tuple and allow for more readable, self-documenting code.\n\n    Named typed tuples can be used wherever typed arrays are used, with the\n    added benefit that they allow accessing fields by both field name and\n    position index.\n\n    Named typed tuples may be one the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754).\n    - float32: single-precision floating-point numbers (IEEE 754).\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n\n    Parameters\n    ----------\n    fields: Array<string>\n        Field (property) names.\n\n    options: Object (optional)\n        Function options.\n\n    options.dtype: string (optional)\n        Default tuple data type. If a data type is not provided to a named typed\n        tuple factory, this option specifies the underlying tuple data type.\n        Default: 'float64'.\n\n    options.name: string (optional)\n        Tuple name. Default: 'tuple'.\n\n    Returns\n    -------\n    factory: Function\n        Named typed tuple factory.\n\n    Examples\n    --------\n    > var opts = {};\n    > opts.name = 'Point';\n    > var factory = namedtypedtuple( [ 'x', 'y' ], opts );\n    > var tuple = factory();\n\n\nfactory()\n    Returns a named typed tuple of the default data type.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > p = factory();\n    > p.x\n    0.0\n    > p.y\n    0.0\n    > p[ 0 ]\n    0.0\n    > p[ 1 ]\n    0.0\n\n\nfactory( dtype )\n    Returns a named typed tuple of the specified data type.\n\n    Parameters\n    ----------\n    dtype: string\n        Tuple data type.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > p = factory( 'int32' );\n    > p.x\n    0\n    > p.y\n    0\n    > p[ 0 ]\n    0\n    > p[ 1 ]\n    0\n\n\nfactory( typedarray[, dtype] )\n    Creates a named typed tuple from a typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate a named typed tuple.\n\n    dtype: string (optional)\n        Tuple data type.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > p = factory( Float64Array[ 1.0, -1.0 ] );\n    > p.x\n    1.0\n    > p.y\n    -1.0\n    > p[ 0 ]\n    1.0\n    > p[ 1 ]\n    -1.0\n\n\nfactory( obj[, dtype] )\n    Creates a named typed tuple from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a named typed\n        tuple.\n\n    dtype: string (optional)\n        Tuple data type.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > p = factory( [ 1, -1 ], 'int32' );\n    > p.x\n    1\n    > p.y\n    -1\n    > p[ 0 ]\n    1\n    > p[ 1 ]\n    -1\n\n\nfactory( buffer[, byteOffset][, dtype] )\n    Returns a named typed tuple view of an ArrayBuffer.\n\n    The view length equals the number of tuple fields.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first tuple element.\n        Default: 0.\n\n    dtype: string (optional)\n        Tuple data type.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var buf = new ArrayBuffer( 16 );\n    > var p = factory( buf, 4, 'float32' );\n    > p.x\n    0.0\n    > p.y\n    0.0\n    > p[ 0 ]\n    0.0\n    > p[ 1 ]\n    0.0\n\n\nfactory.from( src[, map[, thisArg]] )\n    Creates a new named typed tuple from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n    - field: tuple field.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of tuple elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > function mapFcn( v ) { return v * 2.0; };\n    > var p = factory.from( [ 1.0, -1.0 ], mapFcn );\n    > p.x\n    2.0\n    > p.y\n    -2.0\n    > p[ 0 ]\n    2.0\n    > p[ 1 ]\n    -2.0\n\n\nfactory.fromObject( obj[, map[, thisArg]] )\n    Creates a new named typed tuple from an object containing tuple fields.\n\n    A callback is provided the following arguments:\n\n    - value: source object tuple field value.\n    - field: source object tuple field name.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    map: Function (optional)\n        Callback to invoke for each source object tuple field.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory.fromObject( { 'x': 2.0, 'y': -2.0 } );\n    > p.x\n    2.0\n    > p.y\n    -2.0\n    > p[ 0 ]\n    2.0\n    > p[ 1 ]\n    -2.0\n\n\nfactory.of( element0[, element1[, ...elementN]] )\n    Creates a new named typed tuple from a variable number of arguments.\n\n    The number of arguments *must* equal the number of tuple fields.\n\n    Parameters\n    ----------\n    element0: number\n        Tuple element.\n\n    element1: number (optional)\n        Tuple element.\n\n    elementN: number (optional)\n        Tuple elements.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory.of( 2.0, -2.0 );\n    > p.x\n    2.0\n    > p.y\n    -2.0\n    > p[ 0 ]\n    2.0\n    > p[ 1 ]\n    -2.0\n\n\ntuple.BYTES_PER_ELEMENT\n    Size (in bytes) of each tuple element.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > p.BYTES_PER_ELEMENT\n    8\n\n\ntuple.buffer\n    Pointer to the underlying data buffer.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > p.buffer\n    <ArrayBuffer>\n\n\ntuple.byteLength\n    Length (in bytes) of the tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > p.byteLength\n    16\n\n\ntuple.byteOffset\n    Offset (in bytes) of a tuple from the start of its underlying ArrayBuffer.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > p.byteOffset\n    0\n\n\ntuple.length\n    Tuple length (i.e., number of elements).\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > p.length\n    2\n\n\ntuple.name\n    Tuple name.\n\n    Examples\n    --------\n    > var opts = { 'name': 'Point' };\n    > var factory = namedtypedtuple( [ 'x', 'y' ], opts );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > p.name\n    'Point'\n\n\ntuple.fields\n    Returns the list of tuple fields.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > p.fields\n    [ 'x', 'y' ]\n\n\ntuple.orderedFields\n    Returns the list of tuple fields in index order.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > p[ 0 ]\n    1.0\n    > p.sort();\n    > p[ 0 ]\n    -1.0\n    > p.fields\n    [ 'x', 'y' ]\n    > p.orderedFields\n    [ 'y', 'x' ]\n\n\ntuple.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the tuple starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: tuple.length.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Modified tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n    > var p = factory( [ 2.0, -2.0, 1.0, -1.0, 1.0 ] );\n    > p.copyWithin( 3, 0, 2 );\n    > p.w\n    2.0\n    > p.v\n    -2.0\n\n\ntuple.entries()\n    Returns an iterator for iterating over tuple key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over tuple key-value pairs.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > it = p.entries();\n    > it.next().value\n    [ 0, 'x', 1.0 ]\n    > it.next().value\n    [ 1, 'y', -1.0 ]\n    > it.next().done\n    true\n\n\ntuple.every( predicate[, thisArg] )\n    Tests whether all tuple elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: tuple element.\n    - index: tuple index.\n    - field: tuple field name.\n    - tuple: tuple on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests tuple elements. If a predicate function\n        returns a truthy value, a tuple element passes; otherwise, a tuple\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all tuple elements pass.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > function predicate( v ) { return ( v >= 0.0 ); };\n    > p.every( predicate )\n    false\n\n\ntuple.fieldOf( searchElement[, fromIndex] )\n    Returns the field of the first tuple element strictly equal to a search\n    element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `undefined`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Tuple index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last tuple element.\n        Default: 0.\n\n    Returns\n    -------\n    field: string|undefined\n        Tuple field.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > var f = p.fieldOf( 2.0 )\n    undefined\n    > f = p.fieldOf( -1.0 )\n    'z'\n\n\ntuple.fill( value[, start[, end]] )\n    Fills a tuple from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last tuple element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last tuple element. Default: tuple.length.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Modified tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > p.fill( 2.0 );\n    > p.x\n    2.0\n    > p.y\n    2.0\n\n\ntuple.filter( predicate[, thisArg] )\n    Creates a new tuple which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: tuple element.\n    - index: tuple index.\n    - field: tuple field name.\n    - tuple: tuple on which the method is invoked.\n\n    The returned tuple has the same data type as the host tuple.\n\n    If a predicate function does not return a truthy value for any tuple\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters tuple elements. If a predicate function\n        returns a truthy value, a tuple element is included in the output tuple;\n        otherwise, a tuple element is not included in the output tuple.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    tuple: TypedArray\n        A new named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v >= 0.0 ); };\n    > var p2 = p1.filter( predicate );\n    > p2.fields\n    [ 'x', 'y' ]\n\n\ntuple.find( predicate[, thisArg] )\n    Returns the first tuple element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: tuple element.\n    - index: tuple index.\n    - field: tuple field name.\n    - tuple: tuple on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests tuple elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Tuple element.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > var v = p.find( predicate )\n    -1.0\n\n\ntuple.findField( predicate[, thisArg] )\n    Returns the field of the first tuple element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: tuple element.\n    - index: tuple index.\n    - field: tuple field name.\n    - tuple: tuple on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests tuple elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    field: string|undefined\n        Tuple field.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > var f = p.findField( predicate )\n    'z'\n\n\ntuple.findIndex( predicate[, thisArg] )\n    Returns the index of the first tuple element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: tuple element.\n    - index: tuple index.\n    - field: tuple field name.\n    - tuple: tuple on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests tuple elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Tuple index.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > var idx = p.findIndex( predicate )\n    2\n\n\ntuple.forEach( fcn[, thisArg] )\n    Invokes a callback for each tuple element.\n\n    A provided function is provided the following arguments:\n\n    - value: tuple element.\n    - index: tuple index.\n    - field: tuple field name.\n    - tuple: tuple on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each tuple element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1, 0, -1 ], 'int32' );\n    > var str = ' ';\n    > function fcn( v, i, f ) { str += f + '=' + v + ' '; };\n    > p.forEach( fcn );\n    > str\n    ' x=1 y=0 z=-1 '\n\n\ntuple.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether a tuple includes a search element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Tuple index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last tuple element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a tuple includes a search element.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > var bool = p.includes( 2.0 )\n    false\n    > bool = p.includes( -1.0 )\n    true\n\n\ntuple.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first tuple element strictly equal to a search\n    element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Tuple index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last tuple element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Tuple index.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > var idx = p.indexOf( 2.0 )\n    -1\n    > idx = p.indexOf( -1.0 )\n    2\n\n\ntuple.ind2key( ind )\n    Converts a tuple index to a field name.\n\n    If provided an out-of-bounds index, the method returns `undefined`.\n\n    Parameters\n    ----------\n    ind: integer\n        Tuple index. If less than zero, the method resolves the index relative\n        to the last tuple element.\n\n    Returns\n    -------\n    field: string|undefined\n        Field name.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > p.ind2key( 1 )\n    'y'\n    > p.ind2key( 100 )\n    undefined\n\n\ntuple.join( [separator] )\n    Serializes a tuple by joining all tuple elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating tuple elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Tuple serialized as a string.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1, 0, -1 ], 'int32' );\n    > p.join( '|' )\n    '1|0|-1'\n\n\ntuple.keys()\n    Returns an iterator for iterating over tuple keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over tuple keys.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > it = p.keys();\n    > it.next().value\n    [ 0, 'x' ]\n    > it.next().value\n    [ 1, 'y' ]\n    > it.next().done\n    true\n\n\ntuple.key2ind( field )\n    Converts a field name to a tuple index.\n\n    If provided an unknown field name, the method returns `-1`.\n\n    Parameters\n    ----------\n    field: string\n        Tuple field name.\n\n    Returns\n    -------\n    idx: integer\n        Tuple index.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > p.key2ind( 'y' )\n    1\n\n\ntuple.lastFieldOf( searchElement[, fromIndex] )\n    Returns the field of the last tuple element strictly equal to a search\n    element.\n\n    The method iterates from the last tuple element to the first tuple element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `undefined`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Tuple index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last tuple element.\n        Default: -1.\n\n    Returns\n    -------\n    field: string|undefined\n        Tuple field.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n    > var f = p.lastFieldOf( 2.0 )\n    undefined\n    > f = p.lastFieldOf( 0.0 )\n    'w'\n\n\ntuple.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last tuple element strictly equal to a search\n    element.\n\n    The method iterates from the last tuple element to the first tuple element.\n\n    The method does not distinguish between signed and unsigned zero.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Tuple index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last tuple element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Tuple index.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0, 0.0, 1.0 ] );\n    > var idx = p.lastIndexOf( 2.0 )\n    -1\n    > idx = p.lastIndexOf( 0.0 )\n    3\n\n\ntuple.map( fcn[, thisArg] )\n    Maps each tuple element to an element in a new tuple.\n\n    A provided function is provided the following arguments:\n\n    - value: tuple element.\n    - index: tuple index.\n    - field: tuple field name.\n    - tuple: tuple on which the method is invoked.\n\n    The returned tuple has the same data type as the host tuple.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps tuple elements to elements in the new tuple.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    tuple: TypedArray\n        A new named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( v ) { return v * 2.0; };\n    > var p2 = p1.map( fcn );\n    > p2.x\n    2.0\n    > p2.y\n    0.0\n    > p2.z\n    -2.0\n\n\ntuple.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in a tuple and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current tuple element.\n    - index: index of the current tuple element.\n    - field: field name corresponding to the current tuple element.\n    - tuple: tuple on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first tuple element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first tuple element as the first argument and the second tuple\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = p.reduce( fcn, 0.0 )\n    2.0\n\n\ntuple.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in a tuple and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current tuple element.\n    - index: index of the current tuple element.\n    - field: field name corresponding to the current tuple element.\n    - tuple: tuple on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last tuple element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last tuple element as the first argument and the second-to-last\n    tuple element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = p.reduceRight( fcn, 0.0 )\n    2.0\n\n\ntuple.reverse()\n    Reverses a tuple *in-place*.\n\n    This method mutates the tuple on which the method is invoked.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Modified tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > p[ 0 ]\n    1.0\n    > p.x\n    1.0\n    > p.reverse();\n    > p[ 0 ]\n    -1.0\n    > p.x\n    1.0\n\n\ntuple.set( arr[, offset] )\n    Sets tuple elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing tuple values to set.\n\n    offset: integer (optional)\n        Tuple index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, 0.0, -1.0 ] );\n    > p[ 1 ]\n    0.0\n    > p.y\n    0.0\n    > p.set( [ -2.0, 2.0 ], 1 );\n    > p[ 1 ]\n    -2.0\n    > p.y\n    -2.0\n    > p[ 2 ]\n    2.0\n    > p.z\n    2.0\n\n\ntuple.slice( [begin[, end]] )\n    Copies tuple elements to a new tuple with the same underlying data type as\n    the host tuple.\n\n    If the method is unable to resolve indices to a non-empty tuple subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last tuple element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last tuple element. Default: tuple.length.\n\n    Returns\n    -------\n    tuple: TypedArray\n        A new named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p1 = factory( [ 1.0, 0.0, -1.0 ] );\n    > p1.fields\n    [ 'x', 'y', 'z' ]\n    > var p2 = p1.slice( 1 );\n    > p2.fields\n    [ 'y', 'z' ]\n    > p2.y\n    0.0\n    > p2.z\n    -1.0\n\n\ntuple.some( predicate[, thisArg] )\n    Tests whether at least one tuple element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: tuple element.\n    - index: tuple index.\n    - field: tuple field name.\n    - tuple: tuple on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests tuple elements. If a predicate function\n        returns a truthy value, a tuple element passes; otherwise, a tuple\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one tuple element passes.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > function predicate( v ) { return ( v < 0.0 ); };\n    > p.some( predicate )\n    true\n\n\ntuple.sort( [compareFunction] )\n    Sorts a tuple *in-place*.\n\n    Sorting a tuple does *not* affect field assignments. Accessing a tuple field\n    before and after sorting will always return the same tuple element. However,\n    this behavior is generally not true when accessing tuple elements according\n    to tuple index. In summary, sorting affects index order but not field\n    assignments.\n\n    The comparison function is provided two tuple elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the tuple on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    tuple: TypedArray\n        Modified tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n    > var p = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n    > p.sort();\n    > p.orderedFields\n    [ 'v', 'y', 'z', 'x', 'w' ]\n    > p[ 0 ]\n    -2.0\n    > p.x\n    1.0\n    > p[ 1 ]\n    -1.0\n    > p.y\n    -1.0\n    > p.key2ind( 'x' )\n    3\n\n\ntuple.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host tuple.\n\n    If the method is unable to resolve indices to a non-empty tuple subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last tuple element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last tuple element. Default: tuple.length.\n\n    Returns\n    -------\n    arr: TypedArray\n        A new typed array view.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n    > var p = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n    > var arr = p.subarray( 2 )\n    <Float64Array>[ 0.0, 2.0, -2.0 ]\n    > arr.length\n    3\n\n\ntuple.subtuple( [begin[, end]] )\n    Creates a new named typed tuple over the same underlying ArrayBuffer and\n    with the same underlying data type as the host tuple.\n\n    If the function is unable to resolve indices to a non-empty tuple\n    subsequence, the function returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last tuple element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last tuple element. Default: tuple.length.\n\n    Returns\n    -------\n    tuple: TypedArray|null\n        A new named typed tuple.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z', 'w', 'v' ] );\n    > var p1 = factory( [ 1.0, -1.0, 0.0, 2.0, -2.0 ] );\n    > var p2 = p1.subtuple( 2 );\n    > p2.fields\n    [ 'z', 'w', 'v' ]\n    > p2[ 0 ]\n    0.0\n    > p2.z\n    0.0\n    > p2[ 1 ]\n    2.0\n    > p2.w\n    2.0\n    > p2[ 2 ]\n    -2.0\n    > p2.v\n    -2.0\n    > p2.length\n    3\n\n\ntuple.toJSON()\n    Serializes a tuple as JSON.\n\n    Returns\n    -------\n    obj: Object\n        A tuple JSON representation.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, -1.0, 0.0 ] );\n    > p.toJSON()\n    { 'x': 1.0, 'y': -1.0, 'z': 0.0 }\n\n\ntuple.toLocaleString( [locales[, options]] )\n    Serializes a tuple as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ] );\n    > var p = factory( [ 1.0, -1.0, 0.0 ], 'int32' );\n    > p.toLocaleString()\n    '1,-1,0'\n\n\ntuple.toString()\n    Serializes a tuple as a string.\n\n    Returns\n    -------\n    str: string\n        A tuple string representation.\n\n    Examples\n    --------\n    > opts = { 'name': 'Point' };\n    > var factory = namedtypedtuple( [ 'x', 'y', 'z' ], opts );\n    > var p = factory( [ 1.0, -1.0, 0.0 ] );\n    > p.toString()\n    'Point(x=1, y=-1, z=0)'\n\n\ntuple.values()\n    Returns an iterator for iterating over tuple elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over tuple elements.\n\n    Examples\n    --------\n    > var factory = namedtypedtuple( [ 'x', 'y' ] );\n    > var p = factory( [ 1.0, -1.0 ] );\n    > it = p.values();\n    > it.next().value\n    1.0\n    > it.next().value\n    -1.0\n    > it.next().done\n    true\n\n    See Also\n    --------\n    typedarray\n","NAN":"\nNAN\n    Double-precision floating-point NaN.\n\n    Examples\n    --------\n    > NAN\n    NaN\n\n    See Also\n    --------\n    FLOAT32_NAN\n","naryFunction":"\nnaryFunction( fcn, arity[, thisArg] )\n    Returns a function that applies a specified number of arguments to a\n    provided function.\n\n    The returned function *always* invokes the wrapped function with a specified\n    number of arguments, even when the returned function is provided fewer\n    arguments.\n\n    The value for the missing arguments is equal to `undefined`.\n\n    Parameters\n    ----------\n    fcn: Function\n        Input function.\n\n    arity: integer\n        Number of arguments.\n\n    thisArg: any (optional)\n        Function context.\n\n    Returns\n    -------\n    out: Function\n        Function wrapper.\n\n    Examples\n    --------\n    > function foo( a, b, c ) { return [ a, b, c ]; };\n    > var bar = naryFunction( foo, 2 );\n    > var out = bar( 1, 2, 3 )\n    [ 1, 2, undefined ]\n\n    See Also\n    --------\n    maskArguments, pickArguments\n","nativeClass":"\nnativeClass( value )\n    Returns a string value indicating a specification defined classification of\n    an object.\n\n    The function is *not* robust for ES2015+ environments. In ES2015+,\n    `Symbol.toStringTag` allows overriding the default description of an object.\n    While measures are taken to uncover the default description, such measures\n    can be thwarted. While this function remains useful for type-checking, be\n    aware that value impersonation is possible. Where possible, prefer functions\n    tailored to checking for particular value types, as specialized functions\n    are better equipped to address `Symbol.toStringTag`.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    out: string\n        String value indicating a specification defined classification of the\n        input value.\n\n    Examples\n    --------\n    > var str = nativeClass( 'a' )\n    '[object String]'\n    > str = nativeClass( 5 )\n    '[object Number]'\n    > function Beep(){};\n    > str = nativeClass( new Beep() )\n    '[object Object]'\n\n    See Also\n    --------\n    constructorName, typeOf\n","ndarray":"\nndarray( dtype, buffer, shape, strides, offset, order[, options] )\n    Returns an ndarray.\n\n    Parameters\n    ----------\n    dtype: string\n        Underlying data type.\n\n    buffer: ArrayLikeObject|TypedArray|Buffer\n        Data buffer. A data buffer must be an array-like object (i.e., have a\n        `length` property). For data buffers which are not indexed collections\n        (i.e., collections which cannot support direct index access, such as\n        `buffer[ index ]`; e.g., Complex64Array, Complex128Array, etc), a data\n        buffer should provide `#.get( idx )` and `#.set( v[, idx] )` methods.\n        Note that, for `set` methods, the value to set should be the first\n        argument, followed by the linear index, similar to the native typed\n        array `set` method.\n\n    shape: ArrayLikeObject<integer>\n        Array shape.\n\n    strides: ArrayLikeObject<integer>\n        Array strides.\n\n    offset: integer\n        Index offset.\n\n    order: string\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran-style).\n\n    options: Object (optional)\n        Options.\n\n    options.mode: string (optional)\n        Specifies how to handle indices which exceed array dimensions. If equal\n        to 'throw', an ndarray instance throws an error when an index exceeds\n        array dimensions. If equal to 'normalize', an ndarray instance\n        normalizes negative indices and throws an error when an index exceeds\n        array dimensions. If equal to 'wrap', an ndarray instance wraps around\n        indices exceeding array dimensions using modulo arithmetic. If equal to\n        'clamp', an ndarray instance sets an index exceeding array dimensions\n        to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n    options.submode: Array<string> (optional)\n        Specifies how to handle subscripts which exceed array dimensions. If a\n        mode for a corresponding dimension is equal to 'throw', an ndarray\n        instance throws an error when a subscript exceeds array dimensions. If\n        equal to 'normalize', an ndarray instance normalizes negative\n        subscripts and throws an error when a subscript exceeds array\n        dimensions. If equal to 'wrap', an ndarray instance wraps around\n        subscripts exceeding array dimensions using modulo arithmetic. If equal\n        to 'clamp', an ndarray instance sets a subscript exceeding array\n        dimensions to either `0` (minimum index) or the maximum index. If the\n        number of modes is fewer than the number of dimensions, the function\n        recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether an array should be read-only. Default: false.\n\n    Returns\n    -------\n    ndarray: ndarray\n        ndarray instance.\n\n    Examples\n    --------\n    // Create a new instance...\n    > var b = [ 1.0, 2.0, 3.0, 4.0 ]; // underlying data buffer\n    > var d = [ 2, 2 ]; // shape\n    > var s = [ 2, 1 ]; // strides\n    > var o = 0; // index offset\n    > var arr = ndarray( 'generic', b, d, s, o, 'row-major' )\n    <ndarray>\n\n    // Get an element using subscripts:\n    > var v = arr.get( 1, 1 )\n    4.0\n\n    // Get an element using a linear index:\n    > v = arr.iget( 3 )\n    4.0\n\n    // Set an element using subscripts:\n    > arr.set( 1, 1, 40.0 );\n    > arr.get( 1, 1 )\n    40.0\n\n    // Set an element using a linear index:\n    > arr.iset( 3, 99.0 );\n    > arr.get( 1, 1 )\n    99.0\n\n\nndarray.prototype.byteLength\n    Size (in bytes) of the array (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of the array.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.byteLength\n    32\n\n\nndarray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.BYTES_PER_ELEMENT\n    8\n\n\nndarray.prototype.data\n    Pointer to the underlying data buffer.\n\n    Returns\n    -------\n    buf: ArrayLikeObject|TypedArray|Buffer\n        Underlying data buffer.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var buf = arr.data\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n\nndarray.prototype.dtype\n    Underlying data type.\n\n    Returns\n    -------\n    dtype: string\n        Underlying data type.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var dt = arr.dtype\n    'float64'\n\n\nndarray.prototype.flags\n    Meta information, such as information concerning the memory layout of the\n    array.\n\n    Returns\n    -------\n    flags: Object\n        Info object.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var fl = arr.flags\n    {...}\n\n\nndarray.prototype.length\n    Length of the array (i.e., number of elements).\n\n    Returns\n    -------\n    len: integer\n        Array length.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var len = arr.length\n    4\n\n\nndarray.prototype.ndims\n    Number of dimensions.\n\n    Returns\n    -------\n    ndims: integer\n        Number of dimensions.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var n = arr.ndims\n    2\n\n\nndarray.prototype.offset\n    Index offset which specifies the buffer index at which to start iterating\n    over array elements.\n\n    Returns\n    -------\n    offset: integer\n        Index offset.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.offset\n    0\n\n\nndarray.prototype.order\n    Array order.\n\n    The array order is either row-major (C-style) or column-major (Fortran-\n    style).\n\n    Returns\n    -------\n    order: string\n        Array order.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var ord = arr.order\n    'row-major'\n\n\nndarray.prototype.shape\n    Array shape.\n\n    Returns\n    -------\n    shape: Array\n        Array shape.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sh = arr.shape\n    [ 2, 2 ]\n\n\nndarray.prototype.strides\n    Index strides which specify how to access data along corresponding array\n    dimensions.\n\n    Returns\n    -------\n    strides: Array\n        Index strides.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var st = arr.strides\n    [ 2, 1 ]\n\n\nndarray.prototype.get( ...idx )\n    Returns an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.get( 1, 1 )\n    4.0\n\n\nndarray.prototype.iget( idx )\n    Returns an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the input argument is ignored and, for clarity,\n    should not be provided.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.iget( 3 )\n    4.0\n\n\nndarray.prototype.set( ...idx, v )\n    Sets an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: ndarray\n        ndarray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > arr.set( 1, 1, -4.0 );\n    > arr.get( 1, 1 )\n    -4.0\n\n\nndarray.prototype.iset( idx, v )\n    Sets an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the first, and only, argument should be the\n    value to set.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: ndarray\n        ndarray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > arr.iset( 3, -4.0 );\n    > arr.iget( 3 )\n    -4.0\n\n\nndarray.prototype.toString()\n    Serializes an ndarray as a string.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    str: string\n        Serialized ndarray string.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toString()\n    '...'\n\n\nndarray.prototype.toJSON()\n    Serializes an ndarray as a JSON object.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toJSON()\n    {...}\n\n    See Also\n    --------\n    array, FancyArray\n","ndarray.prototype.byteLength":"\nndarray.prototype.byteLength\n    Size (in bytes) of the array (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of the array.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.byteLength\n    32","ndarray.prototype.BYTES_PER_ELEMENT":"\nndarray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element (if known).\n\n    Returns\n    -------\n    size: integer|null\n        Size (in bytes) of each array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sz = arr.BYTES_PER_ELEMENT\n    8","ndarray.prototype.data":"\nndarray.prototype.data\n    Pointer to the underlying data buffer.\n\n    Returns\n    -------\n    buf: ArrayLikeObject|TypedArray|Buffer\n        Underlying data buffer.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var buf = arr.data\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]","ndarray.prototype.dtype":"\nndarray.prototype.dtype\n    Underlying data type.\n\n    Returns\n    -------\n    dtype: string\n        Underlying data type.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var dt = arr.dtype\n    'float64'","ndarray.prototype.flags":"\nndarray.prototype.flags\n    Meta information, such as information concerning the memory layout of the\n    array.\n\n    Returns\n    -------\n    flags: Object\n        Info object.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var fl = arr.flags\n    {...}","ndarray.prototype.length":"\nndarray.prototype.length\n    Length of the array (i.e., number of elements).\n\n    Returns\n    -------\n    len: integer\n        Array length.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var len = arr.length\n    4","ndarray.prototype.ndims":"\nndarray.prototype.ndims\n    Number of dimensions.\n\n    Returns\n    -------\n    ndims: integer\n        Number of dimensions.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var n = arr.ndims\n    2","ndarray.prototype.offset":"\nndarray.prototype.offset\n    Index offset which specifies the buffer index at which to start iterating\n    over array elements.\n\n    Returns\n    -------\n    offset: integer\n        Index offset.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.offset\n    0","ndarray.prototype.order":"\nndarray.prototype.order\n    Array order.\n\n    The array order is either row-major (C-style) or column-major (Fortran-\n    style).\n\n    Returns\n    -------\n    order: string\n        Array order.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var ord = arr.order\n    'row-major'","ndarray.prototype.shape":"\nndarray.prototype.shape\n    Array shape.\n\n    Returns\n    -------\n    shape: Array\n        Array shape.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var sh = arr.shape\n    [ 2, 2 ]","ndarray.prototype.strides":"\nndarray.prototype.strides\n    Index strides which specify how to access data along corresponding array\n    dimensions.\n\n    Returns\n    -------\n    strides: Array\n        Index strides.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var st = arr.strides\n    [ 2, 1 ]","ndarray.prototype.get":"\nndarray.prototype.get( ...idx )\n    Returns an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.get( 1, 1 )\n    4.0","ndarray.prototype.iget":"\nndarray.prototype.iget( idx )\n    Returns an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the input argument is ignored and, for clarity,\n    should not be provided.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    Returns\n    -------\n    out: any\n        Array element.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > var v = arr.iget( 3 )\n    4.0","ndarray.prototype.set":"\nndarray.prototype.set( ...idx, v )\n    Sets an array element specified according to provided subscripts.\n\n    The number of provided subscripts should equal the number of dimensions.\n\n    For zero-dimensional arrays, no indices should be provided.\n\n    Parameters\n    ----------\n    idx: ...integer\n        Subscripts.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: ndarray\n        ndarray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > arr.set( 1, 1, -4.0 );\n    > arr.get( 1, 1 )\n    -4.0","ndarray.prototype.iset":"\nndarray.prototype.iset( idx, v )\n    Sets an array element located at a specified linear index.\n\n    For zero-dimensional arrays, the first, and only, argument should be the\n    value to set.\n\n    Parameters\n    ----------\n    idx: integer\n        Linear index.\n\n    v: any\n        Value to set.\n\n    Returns\n    -------\n    out: ndarray\n        ndarray instance.\n\n    Examples\n    --------\n    > var b = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'float64', b, d, s, o, 'row-major' );\n    > arr.iset( 3, -4.0 );\n    > arr.iget( 3 )\n    -4.0","ndarray.prototype.toString":"\nndarray.prototype.toString()\n    Serializes an ndarray as a string.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    str: string\n        Serialized ndarray string.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toString()\n    '...'","ndarray.prototype.toJSON":"\nndarray.prototype.toJSON()\n    Serializes an ndarray as a JSON object.\n\n    This method does **not** serialize data outside of the buffer region defined\n    by the array configuration.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var b = [ 1, 2, 3, 4 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var arr = ndarray( 'generic', b, d, s, o, 'row-major' );\n    > arr.toJSON()\n    {...}\n\n    See Also\n    --------\n    array, FancyArray","ndarray2array":"\nndarray2array( x )\n    Converts an ndarray to a generic array.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    Returns\n    -------\n    out: Array|Array<Array>\n        Generic array (which may include nested arrays).\n\n    Examples\n    --------\n    > var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > var out = ndarray2array( arr )\n    [ [ 1, 2 ], [ 3, 4 ] ]\n\n    See Also\n    --------\n    array, ndarray, ndarray2json\n","ndarray2fancy":"\nndarray2fancy( x[, options] )\n    Converts an ndarray to an object supporting fancy indexing.\n\n    An ndarray supporting fancy indexing is an ndarray which supports slicing\n    via indexing expressions for both retrieval and assignment.\n\n    A fancy ndarray can be consumed by any API which supports ndarray instances.\n\n    A fancy ndarray shares the *same* data as the provided input ndarray. Hence,\n    any mutations to the returned ndarray will affect the underlying input\n    ndarray and vice versa.\n\n    A fancy ndarray supports indexing using positive and negative integers (both\n    numeric literals and strings), Slice and MultiSlice instances, subsequence\n    expressions, mask ndarrays, boolean ndarrays, and integer ndarrays.\n\n    A fancy ndarray supports all properties and methods of the input ndarray,\n    and, thus, a fancy ndarray can be consumed by any API which supports\n    ndarray-like objects.\n\n    For operations returning a new ndarray (e.g., when slicing or invoking an\n    instance method), a fancy ndarray returns a new fancy ndarray having the\n    same configuration as specified by provided options.\n\n    Indexing expressions provide a convenient and powerful means for creating\n    and operating on ndarray views; however, their use does entail a performance\n    cost. Indexing expressions are best suited for interactive use and\n    scripting. For performance critical applications, prefer equivalent\n    functional APIs supporting ndarray instances.\n\n    Fancy ndarrays support broadcasting in which assigned scalars and ndarrays\n    are repeated (without additional memory allocation) to match the dimensions\n    of a target ndarray instance.\n\n    When assigning ndarrays to slices, the ndarray on the right-hand-side must\n    be broadcast-compatible with dimensions implied by the slice.\n\n    Fancy ndarrays support (mostly) safe casts (i.e., any cast which can be\n    performed without overflow or loss of precision, with the exception of\n    floating-point ndarrays which are also allowed to downcast from higher\n    precision to lower precision).\n\n    When attempting to perform an unsafe cast, fancy ndarrays will raise an\n    exception.\n\n    When assigning a real-valued scalar to a complex number ndarray, a fancy\n    ndarray will cast the real-valued scalar to a complex number argument having\n    an imaginary component equal to zero.\n\n    In older JavaScript environments which do not support Proxy objects, the use\n    of indexing expressions is not supported.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking. Default:\n        false.\n\n    options.cache: Object (optional)\n        Cache for resolving ndarray index objects. Must have a 'get' method\n        which accepts a single argument: a string identifier associated with an\n        ndarray index. If an ndarray index associated with a provided identifier\n        exists, the 'get' method should return an object having the following\n        properties:\n\n        - data: the underlying index ndarray.\n        - type: the index type. Must be either 'mask', 'bool', or 'int'.\n        - kind: the index kind. Must be either '', 'cartesian', or 'linear'.\n        - dtype: the data type of the underlying ndarray.\n\n        If an ndarray index is not associated with a provided identifier, the\n        'get' method should return `null`.\n\n        Default: `ndindex`.\n\n    Returns\n    -------\n    out: ndarray\n        Output ndarray supporting fancy indexing.\n\n    Examples\n    --------\n    // Create a normal ndarray...\n    > var b = [ 1.0, 2.0, 3.0, 4.0 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var x = ndarray( 'generic', b, d, s, o, 'row-major' );\n\n    // Convert to a fancy ndarray:\n    > var arr = ndarray2fancy( x );\n\n    // Get an element using subscripts:\n    > var v = arr.get( 1, 1 )\n    4.0\n\n    // Get an element using a linear index:\n    > v = arr.iget( 3 )\n    4.0\n\n    // Set an element using subscripts:\n    > arr.set( 1, 1, 40.0 );\n    > arr.get( 1, 1 )\n    40.0\n\n    // Set an element using a linear index:\n    > arr.iset( 3, 99.0 );\n    > arr.get( 1, 1 )\n    99.0\n\n\nndarray2fancy.factory( [options] )\n    Returns a function for converting an ndarray to an object supporting fancy\n    indexing.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking by default.\n        Default: false.\n\n    options.cache: Object (optional)\n        Cache for resolving ndarray index objects. Must have a 'get' method\n        which accepts a single argument: a string identifier associated with an\n        ndarray index. If an ndarray index associated with a provided identifier\n        exists, the 'get' method should return an object having the following\n        properties:\n\n        - data: the underlying index ndarray.\n        - type: the index type. Must be either 'mask', 'bool', or 'int'.\n        - kind: the index kind. Must be either '', 'cartesian', or 'linear'.\n        - dtype: the data type of the underlying ndarray.\n\n        If an ndarray index is not associated with a provided identifier, the\n        'get' method should return `null`.\n\n        Default: `ndindex`.\n\n    Returns\n    -------\n    fcn: Function\n        Function for converting an ndarray to an object supporting fancy\n        indexing.\n\n    Examples\n    --------\n    // Create a normal ndarray...\n    > var b = [ 1.0, 2.0, 3.0, 4.0 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var x = ndarray( 'generic', b, d, s, o, 'row-major' );\n\n    // Create a function for converting ndarrays to fancy ndarrays:\n    > var f = ndarray2fancy.factory();\n\n    // Convert the normal ndarray to a fancy ndarray:\n    > var y = f( x );\n\n\nndarray2fancy.idx( x[, options] )\n    Wraps a provided ndarray as an ndarray index object.\n\n    For documentation and usage, see `ndindex`.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.persist: boolean (optional)\n        Boolean indicating whether to continue persisting an index object after\n        first usage. Default: false.\n\n    options.kind: string (optional)\n        Specifies whether a provided ndarray is a specialized input ndarray\n        \"kind\". This option is only applicable for integer input ndarrays. Must\n        be one of the following:\n\n        - cartesian: a provided input ndarray contains Cartesian indices.\n        - linear: a provided input ndarray contains indices representing\n          locations in linear memory.\n\n        Default: ''.\n\n    Returns\n    -------\n    out: ndarrayIndex\n        ndarray index instance.\n\n    Examples\n    --------\n    > var opts = { 'dtype': 'int32' };\n    > var buf = new Int32Array( [ 1, 2, 3, 4 ] );\n    > var arr = array( buf, opts );\n    > var idx = ndarray2fancy.idx( arr );\n\n    See Also\n    --------\n    array2fancy, array, ndarray, FancyArray\n","ndarray2fancy.factory":"\nndarray2fancy.factory( [options] )\n    Returns a function for converting an ndarray to an object supporting fancy\n    indexing.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking by default.\n        Default: false.\n\n    options.cache: Object (optional)\n        Cache for resolving ndarray index objects. Must have a 'get' method\n        which accepts a single argument: a string identifier associated with an\n        ndarray index. If an ndarray index associated with a provided identifier\n        exists, the 'get' method should return an object having the following\n        properties:\n\n        - data: the underlying index ndarray.\n        - type: the index type. Must be either 'mask', 'bool', or 'int'.\n        - kind: the index kind. Must be either '', 'cartesian', or 'linear'.\n        - dtype: the data type of the underlying ndarray.\n\n        If an ndarray index is not associated with a provided identifier, the\n        'get' method should return `null`.\n\n        Default: `ndindex`.\n\n    Returns\n    -------\n    fcn: Function\n        Function for converting an ndarray to an object supporting fancy\n        indexing.\n\n    Examples\n    --------\n    // Create a normal ndarray...\n    > var b = [ 1.0, 2.0, 3.0, 4.0 ];\n    > var d = [ 2, 2 ];\n    > var s = [ 2, 1 ];\n    > var o = 0;\n    > var x = ndarray( 'generic', b, d, s, o, 'row-major' );\n\n    // Create a function for converting ndarrays to fancy ndarrays:\n    > var f = ndarray2fancy.factory();\n\n    // Convert the normal ndarray to a fancy ndarray:\n    > var y = f( x );","ndarray2fancy.idx":"\nndarray2fancy.idx( x[, options] )\n    Wraps a provided ndarray as an ndarray index object.\n\n    For documentation and usage, see `ndindex`.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.persist: boolean (optional)\n        Boolean indicating whether to continue persisting an index object after\n        first usage. Default: false.\n\n    options.kind: string (optional)\n        Specifies whether a provided ndarray is a specialized input ndarray\n        \"kind\". This option is only applicable for integer input ndarrays. Must\n        be one of the following:\n\n        - cartesian: a provided input ndarray contains Cartesian indices.\n        - linear: a provided input ndarray contains indices representing\n          locations in linear memory.\n\n        Default: ''.\n\n    Returns\n    -------\n    out: ndarrayIndex\n        ndarray index instance.\n\n    Examples\n    --------\n    > var opts = { 'dtype': 'int32' };\n    > var buf = new Int32Array( [ 1, 2, 3, 4 ] );\n    > var arr = array( buf, opts );\n    > var idx = ndarray2fancy.idx( arr );\n\n    See Also\n    --------\n    array2fancy, array, ndarray, FancyArray","ndarray2json":"\nndarray2json( x )\n    Serializes an ndarray as a JSON object.\n\n    This function does *not* serialize data outside of the buffer region defined\n    by the ndarray view.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    Returns\n    -------\n    out: Object\n        JSON object.\n\n    Examples\n    --------\n    > var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > var out = ndarray2json( arr )\n    {...}\n\n    See Also\n    --------\n    array, ndarray, ndarray2array\n","ndarrayCastingModes":"\nndarrayCastingModes()\n    Returns a list of ndarray casting modes.\n\n    The output array contains the following modes:\n\n    - 'none': only allow casting between identical types.\n    - 'equiv': allow casting between identical and byte swapped types.\n    - 'safe': only allow \"safe\" casts.\n    - 'mostly-safe': allow \"safe\" casts and, for floating-point data types,\n      downcasts.\n    - 'same-kind': allow \"safe\" casts and casts within the same kind (e.g.,\n      between signed integers or between floats).\n    - 'unsafe': allow casting between all types (including between integers and\n      floats).\n\n    Returns\n    -------\n    out: Array<string>\n        List of ndarray casting modes.\n\n    Examples\n    --------\n    > var out = ndarrayCastingModes()\n    [ 'none', 'equiv', 'safe', 'mostly-safe', 'same-kind', 'unsafe' ]\n\n    See Also\n    --------\n    array, ndarray\n","ndarrayDataBuffer":"\nndarrayDataBuffer( x )\n    Returns the underlying data buffer of a provided ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Underlying data buffer.\n\n    Examples\n    --------\n    > var opts = { 'dtype': 'float64' };\n    > var out = ndarrayDataBuffer( ndzeros( [ 3, 3, 3 ], opts ) )\n    <Float64Array>\n\n    See Also\n    --------\n    array, ndarray, ndarrayDataType\n","ndarrayDataType":"\nndarrayDataType( x )\n    Returns the data type of a provided ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    Returns\n    -------\n    dt: string\n        Data type.\n\n    Examples\n    --------\n    > var opts = { 'dtype': 'float64' };\n    > var dt = ndarrayDataType( ndzeros( [ 3, 3, 3 ], opts ) )\n    'float64'\n\n    See Also\n    --------\n    array, ndarray, ndarrayDataTypes\n","ndarrayDataTypes":"\nndarrayDataTypes( [kind] )\n    Returns a list of ndarray data types.\n\n    When not provided a data type \"kind\", the function returns an array\n    containing the following data types:\n\n    - float32: single-precision floating-point numbers.\n    - float64: double-precision floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - complex128: double-precision complex floating-point numbers.\n    - bool: boolean values.\n    - generic: values of any type.\n    - int16: signed 16-bit integers.\n    - int32: signed 32-bit integers.\n    - int8: signed 8-bit integers.\n    - uint16: unsigned 16-bit integers.\n    - uint32: unsigned 32-bit integers.\n    - uint8: unsigned 8-bit integers.\n    - uint8c: unsigned clamped 8-bit integers.\n    - binary: binary.\n\n    The function supports the following data type \"kinds\":\n\n    - floating_point: floating-point data types.\n    - real_floating_point: real-valued floating-point data types.\n    - complex_floating_point: complex-valued floating-point data types.\n    - boolean: boolean data types.\n    - integer: integer data types.\n    - signed_integer: signed integer data types.\n    - unsigned_integer: unsigned integer data types.\n    - real: real-valued data types.\n    - numeric: numeric data types.\n    - typed: typed data types.\n    - all: all data types.\n\n    Additionally, the function supports extending the \"kinds\" listed above by\n    appending a '_and_generic' suffix to the kind name (e.g., real_and_generic).\n\n    Parameters\n    ----------\n    kind: string (optional)\n        Data type kind.\n\n    Returns\n    -------\n    out: Array<string>\n        List of ndarray data types.\n\n    Examples\n    --------\n    > var out = ndarrayDataTypes()\n    [...]\n    > out = ndarrayDataTypes( 'floating_point' )\n    [...]\n    > out = ndarrayDataTypes( 'floating_point_and_generic' )\n    [...]\n\n    See Also\n    --------\n    arrayDataTypes, array, ndarray, typedarrayDataTypes\n","ndarrayDispatch":"\nndarrayDispatch( fcns, types, data, nargs, nin, nout )\n    Returns an ndarray function interface which performs multiple dispatch.\n\n    An ndarray function interface has the following signature:\n\n      f( x, y, ... )\n\n    where\n\n    - x: ndarray.\n    - y: ndarray.\n    - ...: additional ndarrays.\n\n    The number of parameters is derived from `nargs`, the number of input\n    ndarrays is derived from `nin`, and the number of output ndarrays is derived\n    from `nout`.\n\n    Parameters\n    ----------\n    fcns: Function|ArrayLikeObject<Function>\n        List of ndarray functions. An ndarray function should have the following\n        signature:\n\n          f( arrays, data )\n\n        where\n\n        - arrays: array containing input and output ndarrays.\n        - data: ndarray function data (e.g., a callback).\n\n        For convenience, a single ndarray function may be provided which will be\n        invoked whenever the ndarray argument data types match a sequence of\n        types in `types`. Providing a single ndarray function is particularly\n        convenient for the case where, regardless of array data types,\n        traversing arrays remains the same, but the ndarray function `data`\n        differs (e.g., callbacks which differ based on the array data types).\n\n    types: ArrayLikeObject\n        One-dimensional list of ndarray argument data types.\n\n    data: ArrayLikeObject|null\n        ndarray function data (e.g., callbacks). If `null`, a returned ndarray\n        function interface does **not** provide a `data` argument to an invoked\n        ndarray function.\n\n    nargs: integer\n        Total number of ndarray function interface arguments.\n\n    nin: integer\n        Number of input ndarrays.\n\n    nout: integer\n        Number of output ndarrays.\n\n    Returns\n    -------\n    fcn: Function\n        ndarray function interface.\n\n    Examples\n    --------\n    // Define ndarray argument data types:\n    > var t = [ 'float64', 'float64', 'float32', 'float32' ];\n\n    // Define a list of ndarray function data (callbacks):\n    > var d = [ base.abs, base.absf ];\n\n    // Create an ndarray function interface for applying unary callbacks:\n    > var f = ndarrayDispatch( base.ndarrayUnary, t, d, 2, 1, 1 );\n\n    // Create an input ndarray:\n    > var xbuf = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var x = ndarray( 'float64', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );\n\n    // Create an output ndarray:\n    > var ybuf = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var y = ndarray( 'float64', ybuf, [ 4 ], [ 1 ], 0, 'row-major' );\n\n    // Compute the element-wise absolute value:\n    > f( x, y );\n    > ybuf\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    See Also\n    --------\n    array, ndarray\n","ndarrayFlag":"\nndarrayFlag( x, name )\n    Returns a specified flag for a provided ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    name: string|symbol\n        Flag name.\n\n    Returns\n    -------\n    out: any\n        Flag value.\n\n    Examples\n    --------\n    > var out = ndarrayFlag( ndzeros( [ 3, 3, 3 ] ), 'READONLY' )\n    <boolean>\n\n    See Also\n    --------\n    array, ndarray, ndarrayFlags\n","ndarrayFlags":"\nndarrayFlags( x )\n    Returns the flags of a provided ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    Returns\n    -------\n    out: Object\n        Flags.\n\n    Examples\n    --------\n    > var out = ndarrayFlags( ndzeros( [ 3, 3, 3 ] ) )\n    {...}\n\n    See Also\n    --------\n    array, ndarray, ndarrayFlag\n","ndarrayIndexModes":"\nndarrayIndexModes()\n    Returns a list of ndarray index modes.\n\n    The output array contains the following modes:\n\n    - throw: specifies that a function should throw an error when an index is\n    outside a restricted interval.\n    - normalize: specifies that a function should normalize negative indices and\n    throw an error when an index is outside a restricted interval.\n    - wrap: specifies that a function should wrap around an index using modulo\n    arithmetic.\n    - clamp: specifies that a function should set an index less than zero to\n    zero (minimum index) and set an index greater than a maximum index value to\n    the maximum possible index.\n\n    Returns\n    -------\n    out: Array<string>\n        List of ndarray index modes.\n\n    Examples\n    --------\n    > var out = ndarrayIndexModes()\n    [ 'throw', 'normalize', 'clamp', 'wrap' ]\n\n    See Also\n    --------\n    array, ndarray\n","ndarraylike2ndarray":"\nndarraylike2ndarray( x[, options] )\n    Converts an ndarray-like object to an ndarray.\n\n    If provided a read-only ndarray, the function returns a read-only ndarray.\n\n    Parameters\n    ----------\n    x: ndarrayLike\n        Input ndarray-like object.\n\n    options: Object (optional)\n        Options.\n\n    options.mode: string (optional)\n        Specifies how to handle indices which exceed array dimensions. If equal\n        to 'throw', an ndarray instance throws an error when an index exceeds\n        array dimensions. If equal to 'normalize', an ndarray instance\n        normalizes negative indices and throws an error when an index exceeds\n        array dimensions. If equal to 'wrap', an ndarray instance wraps around\n        indices exceeding array dimensions using modulo arithmetic. If equal to\n        'clamp', an ndarray instance sets an index exceeding array dimensions\n        to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n    options.submode: Array<string> (optional)\n        Specifies how to handle subscripts which exceed array dimensions. If a\n        mode for a corresponding dimension is equal to 'throw', an ndarray\n        instance throws an error when a subscript exceeds array dimensions. If\n        equal to 'normalize', an ndarray instance normalizes negative\n        subscripts and throws an error when a subscript exceeds array\n        dimensions. If equal to 'wrap', an ndarray instance wraps around\n        subscripts exceeding array dimensions using modulo arithmetic. If equal\n        to 'clamp', an ndarray instance sets a subscript exceeding array\n        dimensions to either `0` (minimum index) or the maximum index. If the\n        number of modes is fewer than the number of dimensions, the function\n        recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether an array should be read-only.\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var arr = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > var out = ndarraylike2ndarray( arr )\n    <ndarray>\n\n    See Also\n    --------\n    array, ndarray, ndemptyLike, ndzerosLike\n","ndarrayMinDataType":"\nndarrayMinDataType( value )\n    Returns the minimum ndarray data type of the closest \"kind\" necessary for\n    storing a provided scalar value.\n\n    The function does *not* provide precision guarantees for non-integer-valued\n    numbers. In other words, the function returns the smallest possible\n    floating-point (i.e., inexact) data type for storing numbers having\n    decimals.\n\n    Parameters\n    ----------\n    value: any\n        Scalar value.\n\n    Returns\n    -------\n    dt: string\n        ndarray data type.\n\n    Examples\n    --------\n    > var dt = ndarrayMinDataType( 3.141592653589793 )\n    'float32'\n    > dt = ndarrayMinDataType( 3 )\n    'uint8'\n    > dt = ndarrayMinDataType( -3 )\n    'int8'\n    > dt = ndarrayMinDataType( '-3' )\n    'generic'\n\n    See Also\n    --------\n    ndarrayDataTypes, ndarrayPromotionRules, ndarraySafeCasts\n","ndarrayMostlySafeCasts":"\nndarrayMostlySafeCasts( [dtype] )\n    Returns a list of ndarray data types to which a provided ndarray data type\n    can be safely cast and, for floating-point data types, can be downcast.\n\n    If not provided an ndarray data type, the function returns a casting table.\n\n    If provided an unrecognized ndarray data type, the function returns `null`.\n\n    Parameters\n    ----------\n    dtype: any (optional)\n        ndarray data type value.\n\n    Returns\n    -------\n    out: Object|Array<string>|null\n        ndarray data types to which a data type can be cast.\n\n    Examples\n    --------\n    > var out = ndarrayMostlySafeCasts( 'float32' )\n    <Array>\n\n    See Also\n    --------\n    ndarrayCastingModes, ndarrayDataTypes, ndarraySafeCasts, ndarraySameKindCasts\n","ndarrayNextDataType":"\nndarrayNextDataType( [dtype] )\n    Returns the next larger ndarray data type of the same kind.\n\n    If not provided a data type, the function returns a table.\n\n    If a data type does not have a next larger data type or the next larger type\n    is not supported, the function returns `-1`.\n\n    If provided an unrecognized data type, the function returns `null`.\n\n    Parameters\n    ----------\n    dtype: any (optional)\n        ndarray data type value.\n\n    Returns\n    -------\n    out: Object|string|integer|null\n        Next larger type(s).\n\n    Examples\n    --------\n    > var out = ndarrayNextDataType( 'float32' )\n    'float64'\n\n    See Also\n    --------\n    ndarrayDataTypes, ndarrayPromotionRules, ndarraySafeCasts\n","ndarrayOffset":"\nndarrayOffset( x )\n    Returns the index offset specifying the underlying buffer index of the first\n    iterated ndarray element.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    Returns\n    -------\n    n: integer\n        Index offset.\n\n    Examples\n    --------\n    > var n = ndarrayOffset( ndzeros( [ 3, 3, 3 ] ) )\n    0\n\n    See Also\n    --------\n    array, ndarray, ndarrayShape, ndarrayStrides\n","ndarrayOrder":"\nndarrayOrder( x )\n    Returns the layout order of a provided ndarray.\n\n    If unable to resolve a layout order, the function returns `null`.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    Returns\n    -------\n    out: string|null\n        Layout order.\n\n    Examples\n    --------\n    > var opts = { 'order': 'row-major' };\n    > var dt = ndarrayOrder( ndzeros( [ 3, 3, 3 ], opts ) )\n    'row-major'\n\n    See Also\n    --------\n    array, ndarray, ndarrayOrders, ndarrayShape, ndarrayStrides\n","ndarrayOrders":"\nndarrayOrders()\n    Returns a list of ndarray orders.\n\n    The output array contains the following orders:\n\n    - row-major: row-major (C-style) order.\n    - column-major: column-major (Fortran-style) order.\n\n    Returns\n    -------\n    out: Array<string>\n        List of ndarray orders.\n\n    Examples\n    --------\n    > var out = ndarrayOrders()\n    [ 'row-major', 'column-major' ]\n\n    See Also\n    --------\n    array, ndarray\n","ndarrayPromotionRules":"\nndarrayPromotionRules( [dtype1, dtype2] )\n    Returns the ndarray data type with the smallest size and closest \"kind\" to\n    which ndarray data types can be safely cast.\n\n    If not provided data types, the function returns a type promotion table.\n\n    If a data type to which data types can be safely cast does *not* exist (or\n    is not supported), the function returns `-1`.\n\n    If provided an unrecognized data type, the function returns `null`.\n\n    Parameters\n    ----------\n    dtype1: any (optional)\n        ndarray data type value.\n\n    dtype2: any (optional)\n        ndarray data type value.\n\n    Returns\n    -------\n    out: Object|string|integer|null\n        Promotion rule(s).\n\n    Examples\n    --------\n    > var out = ndarrayPromotionRules( 'float32', 'int32' )\n    'float64'\n\n    See Also\n    --------\n    ndarrayCastingModes, ndarrayDataTypes, ndarraySafeCasts\n","ndarraySafeCasts":"\nndarraySafeCasts( [dtype] )\n    Returns a list of ndarray data types to which a provided ndarray data type\n    can be safely cast.\n\n    If not provided an ndarray data type, the function returns a casting table.\n\n    If provided an unrecognized ndarray data type, the function returns `null`.\n\n    Parameters\n    ----------\n    dtype: any (optional)\n        ndarray data type value.\n\n    Returns\n    -------\n    out: Object|Array<string>|null\n        ndarray data types to which a data type can be safely cast.\n\n    Examples\n    --------\n    > var out = ndarraySafeCasts( 'float32' )\n    <Array>\n\n    See Also\n    --------\n    ndarrayCastingModes, ndarrayDataTypes, ndarraySameKindCasts\n","ndarraySameKindCasts":"\nndarraySameKindCasts( [dtype] )\n    Returns a list of ndarray data types to which a provided ndarray data type\n    can be safely cast or cast within the same \"kind\".\n\n    If not provided an ndarray data type, the function returns a casting table.\n\n    If provided an unrecognized ndarray data type, the function returns `null`.\n\n    Parameters\n    ----------\n    dtype: any (optional)\n        ndarray data type value.\n\n    Returns\n    -------\n    out: Object|Array<string>|null\n        ndarray data types to which a data type can be safely cast or cast\n        within the same \"kind\".\n\n    Examples\n    --------\n    > var out = ndarraySameKindCasts( 'float32' )\n    <Array>\n\n    See Also\n    --------\n    ndarrayCastingModes, ndarrayDataTypes, ndarraySafeCasts\n","ndarrayShape":"\nndarrayShape( x )\n    Returns the shape of a provided ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    Returns\n    -------\n    out: Array<integer>\n        Shape.\n\n    Examples\n    --------\n    > var out = ndarrayShape( ndzeros( [ 3, 3, 3 ] ) )\n    [ 3, 3, 3 ]\n\n    See Also\n    --------\n    array, ndarray, ndarrayOffset, ndarrayStrides\n","ndarrayStride":"\nndarrayStride( x, dim )\n    Returns the stride along a specified dimension for a provided ndarray.\n\n    A \"stride\" is the linear distance (i.e., number of elements) between\n    adjacent elements along a specified dimension.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    dim: integer\n        Dimension index. If less than zero, the index is resolved relative to\n        the last dimension, with the last dimension corresponding to the value\n        `-1`.\n\n    Returns\n    -------\n    out: integer\n        Stride.\n\n    Examples\n    --------\n    > var out = ndarrayStride( ndzeros( [ 3, 3, 3 ] ), 0 )\n    9\n\n    See Also\n    --------\n    array, ndarray, ndarrayOffset, ndarrayOrder, ndarrayShape, ndarrayStrides\n","ndarrayStrides":"\nndarrayStrides( x )\n    Returns the strides of a provided ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    Returns\n    -------\n    out: Array<integer>\n        Strides.\n\n    Examples\n    --------\n    > var out = ndarrayStrides( ndzeros( [ 3, 3, 3 ] ) )\n    [ 9, 3, 1 ]\n\n    See Also\n    --------\n    array, ndarray, ndarrayOffset, ndarrayOrder, ndarrayShape\n","ndat":"\nndat( x[, ...indices] )\n    Returns an ndarray element.\n\n    Negative indices are resolved relative to the last element along the\n    respective dimension, with the last element corresponding to `-1`.\n\n    If provided out-of-bounds indices, the function always returns `undefined`.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    indices: ...integer (optional)\n        Index arguments. The number of index arguments must equal the number of\n        dimensions.\n\n    Returns\n    -------\n    out: any\n        Element value.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > ndat( x, 0, 1 )\n    2\n    > ndat( x, 1, 0 )\n    3\n\n    See Also\n    --------\n    array, ndslice\n","ndempty":"\nndempty( shape[, options] )\n    Returns an uninitialized ndarray having a specified shape and data type.\n\n    In browser environments, the function always returns zero-filled ndarrays.\n\n    If `dtype` is 'generic', the function always returns a zero-filled ndarray.\n\n    For returned ndarrays whose underlying memory is *not* initialized, memory\n    contents are unknown and may contain *sensitive* data.\n\n    Parameters\n    ----------\n    shape: ArrayLikeObject<integer>|integer\n        Array shape.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Underlying data type. Default: 'float64'.\n\n    options.order: string (optional)\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran-style). Default: 'row-major'.\n\n    options.mode: string (optional)\n        Specifies how to handle indices which exceed array dimensions. If equal\n        to 'throw', an ndarray instance throws an error when an index exceeds\n        array dimensions. If equal to 'normalize', an ndarray instance\n        normalizes negative indices and throws an error when an index exceeds\n        array dimensions. If equal to 'wrap', an ndarray instance wraps around\n        indices exceeding array dimensions using modulo arithmetic. If equal to\n        'clamp', an ndarray instance sets an index exceeding array dimensions\n        to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n    options.submode: Array<string> (optional)\n        Specifies how to handle subscripts which exceed array dimensions. If a\n        mode for a corresponding dimension is equal to 'throw', an ndarray\n        instance throws an error when a subscript exceeds array dimensions. If\n        equal to 'normalize', an ndarray instance normalizes negative\n        subscripts and throws an error when a subscript exceeds array\n        dimensions. If equal to 'wrap', an ndarray instance wraps around\n        subscripts exceeding array dimensions using modulo arithmetic. If equal\n        to 'clamp', an ndarray instance sets a subscript exceeding array\n        dimensions to either `0` (minimum index) or the maximum index. If the\n        number of modes is fewer than the number of dimensions, the function\n        recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var arr = ndempty( [ 2, 2 ] )\n    <ndarray>\n    > var sh = arr.shape\n    [ 2, 2 ]\n    > var dt = arr.dtype\n    'float64'\n\n    See Also\n    --------\n    ndemptyLike, ndzeros\n","ndemptyLike":"\nndemptyLike( x[, options] )\n    Returns an uninitialized ndarray having the same shape and data type as a\n    provided input ndarray.\n\n    The function infers the following attributes from the input array:\n\n    - shape: array shape.\n    - dtype: underlying array data type.\n    - order: whether the array order is row-major (C-style) or column-major\n      (Fortran-style).\n\n    In browser environments, the function always returns zero-filled ndarrays.\n\n    If `dtype` is 'generic', the function always returns a zero-filled ndarray.\n\n    For returned ndarrays whose underlying memory is *not* initialized, memory\n    contents are unknown and may contain *sensitive* data.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    options: Object (optional)\n        Options.\n\n    options.shape: ArrayLikeObject<integer>|integer (optional)\n        Array shape. Overrides the input array's inferred shape.\n\n    options.dtype: string (optional)\n        Array data type. Overrides the input array's inferred data type.\n\n    options.order: string (optional)\n        Array order (either 'row-major' (C-style) or 'column-major' (Fortran-\n        style)). Overrides the input array's inferred order.\n\n    options.mode: string (optional)\n        Specifies how to handle indices which exceed array dimensions. If equal\n        to 'throw', an ndarray instance throws an error when an index exceeds\n        array dimensions. If equal to 'normalize', an ndarray instance\n        normalizes negative indices and throws an error when an index exceeds\n        array dimensions. If equal to 'wrap', an ndarray instance wraps around\n        indices exceeding array dimensions using modulo arithmetic. If equal to\n        'clamp', an ndarray instance sets an index exceeding array dimensions\n        to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n    options.submode: Array<string> (optional)\n        Specifies how to handle subscripts which exceed array dimensions. If a\n        mode for a corresponding dimension is equal to 'throw', an ndarray\n        instance throws an error when a subscript exceeds array dimensions. If\n        equal to 'normalize', an ndarray instance normalizes negative\n        subscripts and throws an error when a subscript exceeds array\n        dimensions. If equal to 'wrap', an ndarray instance wraps around\n        subscripts exceeding array dimensions using modulo arithmetic. If equal\n        to 'clamp', an ndarray instance sets a subscript exceeding array\n        dimensions to either `0` (minimum index) or the maximum index. If the\n        number of modes is fewer than the number of dimensions, the function\n        recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n    <ndarray>\n    > var sh = x.shape\n    [ 2, 2 ]\n    > var dt = x.dtype\n    'float64'\n    > var y = ndemptyLike( x )\n    <ndarray>\n    > sh = y.shape\n    [ 2, 2 ]\n    > dt = y.dtype\n    'float64'\n\n    See Also\n    --------\n    ndempty, ndzerosLike\n","ndfilter":"\nndfilter( x[, options], predicate[, thisArg] )\n    Returns a shallow copy of an ndarray containing only those elements which\n    pass a test implemented by a predicate function.\n\n    The predicate function is provided the following arguments:\n\n    - value: current array element.\n    - indices: current array element indices.\n    - arr: the input ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.dtype: string (optional)\n        Output ndarray data type. Overrides using the input array's inferred\n        data type.\n\n    options.order: string (optional)\n        Index iteration order. By default, the function iterates over elements\n        according to the layout order of the provided array. Accordingly, for\n        row-major input arrays, the last dimension indices increment fastest.\n        For column-major input arrays, the first dimension indices increment\n        fastest. To override the inferred order and ensure that indices\n        increment in a specific manner, regardless of the input array's layout\n        order, explicitly set the iteration order. Note, however, that iterating\n        according to an order which does not match that of the input array may,\n        in some circumstances, result in performance degradation due to cache\n        misses. Must be either 'row-major' or 'column-major'.\n\n    predicate: Function\n        Predicate function.\n\n    thisArg: any (optional)\n        Predicate function execution context.\n\n    Examples\n    --------\n    > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n    > function f( v ) { return v > 2.0; };\n    > var y = ndfilter( x, f );\n    > ndarray2array( y )\n    [ 3.0, 4.0 ]\n\n    See Also\n    --------\n    ndfilterMap, ndmap, ndreject, ndslice","ndfilterMap":"\nndfilterMap( x[, options], fcn[, thisArg] )\n    Filters and maps elements in an input ndarray to elements in a new output\n    ndarray according to a callback function.\n\n    The callback function is provided the following arguments:\n\n    - value: current array element.\n    - indices: current array element indices.\n    - arr: the input ndarray.\n\n    If a provided callback function returns `undefined`, the function skips the\n    respective ndarray element. If the callback function returns a value other\n    than `undefined`, the function stores the callback's return value in the\n    output ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.dtype: string (optional)\n        Output ndarray data type. Overrides using the input array's inferred\n        data type.\n\n    options.order: string (optional)\n        Index iteration order. By default, the function iterates over elements\n        according to the layout order of the provided array. Accordingly, for\n        row-major input arrays, the last dimension indices increment fastest.\n        For column-major input arrays, the first dimension indices increment\n        fastest. To override the inferred order and ensure that indices\n        increment in a specific manner, regardless of the input array's layout\n        order, explicitly set the iteration order. Note, however, that iterating\n        according to an order which does not match that of the input array may,\n        in some circumstances, result in performance degradation due to cache\n        misses. Must be either 'row-major' or 'column-major'.\n\n    fcn: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback function execution context.\n\n    Examples\n    --------\n    > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n    > function f( v ) { if ( v > 2.0 ) { return v * 10.0; } };\n    > var y = ndfilterMap( x, f );\n    > ndarray2array( y )\n    [ 30.0, 40.0 ]\n\n    See Also\n    --------\n    ndfilter, ndmap, ndreject, ndslice","ndforEach":"\nndforEach( x, fcn[, thisArg] )\n    Invokes a callback function once for each ndarray element.\n\n    The callback function is provided the following arguments:\n\n    - value: current array element.\n    - indices: current array element indices.\n    - arr: the input ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    fcn: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback function execution context.\n\n    Examples\n    --------\n    > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n    > function f( v ) { if ( v !== v ) { throw new Error( '...' ); } };\n    > ndforEach( x, f );\n\n    See Also\n    --------\n    ndmap","ndims":"\nndims( x )\n    Returns the number of ndarray dimensions.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    Returns\n    -------\n    n: integer\n        Number of dimensions.\n\n    Examples\n    --------\n    > var n = ndims( ndzeros( [ 3, 3, 3 ] ) )\n    3\n\n    See Also\n    --------\n    array, ndarray, numel, ndarrayShape\n","ndindex":"\nndindex( x[, options] )\n    Wraps a provided array as an ndarray index object.\n\n    ndarray index instances have no explicit functionality; however, they are\n    used by \"fancy\" ndarrays for element retrieval and assignment.\n\n    By default, an instance is invalidated and removed from an internal cache\n    immediately after a consumer resolves the underlying data associated with an\n    instance using the `get` static method. Immediate invalidation and cache\n    removal ensures that references to the underlying ndarray are not the source\n    of memory leaks.\n\n    Because instances leverage an internal cache implementing the Singleton\n    pattern, one must be sure to use the same constructor as consumers. If one\n    uses a different constructor, the consumer will *not* be able to resolve the\n    original wrapped ndarray, as the consumer will attempt to resolve an\n    instance in the wrong internal cache.\n\n    Because non-persisted instances are freed after first use, in order to avoid\n    holding onto memory and to allow garbage collection, one should avoid\n    scenarios in which an instance is never used.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.persist: boolean (optional)\n        Boolean indicating whether to continue persisting an index object after\n        first usage. Default: false.\n\n    options.kind: string (optional)\n        Specifies whether a provided ndarray is a specialized input ndarray\n        \"kind\". This option is only applicable for integer input ndarrays. Must\n        be one of the following:\n\n        - cartesian: a provided input ndarray contains Cartesian indices.\n        - linear: a provided input ndarray contains indices representing\n          locations in linear memory.\n\n        Default: ''.\n\n    Returns\n    -------\n    out: ndindex\n        Index instance.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n\n\nndindex.free( id )\n    Frees the instance associated with a provided identifier.\n\n    Parameters\n    ----------\n    id: string\n        Instance identifier.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an instance was successfully freed.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > ndindex.free( idx.id )\n    <boolean>\n\n\nndindex.get( id )\n    Returns the ndarray associated with the instance having a provided\n    identifier.\n\n    Parameters\n    ----------\n    id: string\n        Instance identifier.\n\n    Returns\n    -------\n    out: Object\n        Object containing ndarray data.\n\n    out.data: ndarray\n        The underlying ndarray associated with the provided identifier.\n\n    out.type: string\n        The type of ndarray index.\n\n    out.dtype: string\n        The data type of the underlying ndarray.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > ndindex.get( idx.id )\n    {...}\n\n\nndindex.cartesianIndex( x[, options] )\n    Returns an ndarray index containing Cartesian indices.\n\n    This is a convenience method for calling `ndindex` with `kind` set to\n    'cartesian'.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.persist: boolean (optional)\n        Boolean indicating whether to continue persisting an index object after\n        first usage. Default: false.\n\n    Returns\n    -------\n    out: ndindex\n        Index instance.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = ndindex.cartesianIndex( x );\n\n\nndindex.linearIndex( x[, options] )\n    Returns an ndarray index for indices representing locations in linear\n    memory.\n\n    This is a convenience method for calling `ndindex` with `kind` set to\n    'linear'.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.persist: boolean (optional)\n        Boolean indicating whether to continue persisting an index object after\n        first usage. Default: false.\n\n    Returns\n    -------\n    out: ndindex\n        Index instance.\n\n    Examples\n    --------\n    > var x = ndempty( [ 5 ], { 'dtype': 'int32' } );\n    > var idx = ndindex.linearIndex( x );\n\n\nndindex.prototype.data\n    Read-only property returning an ndarray view of the underlying index\n    ndarray.\n\n    Returns\n    -------\n    out: ndarray\n        Array data.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.data\n    <ndarray>\n\n\nndindex.prototype.dtype\n    Read-only property returning the underlying data type of the index ndarray.\n\n    Returns\n    -------\n    out: string\n        Array data type.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.dtype\n    'int32'\n\n\nndindex.prototype.id\n    Read-only property returning the unique identifier associated with an\n    instance.\n\n    Returns\n    -------\n    out: string\n        String identifier.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.id\n    <string>\n\n\nndindex.prototype.isCached\n    Read-only property returning a boolean indicating whether an ndarray index\n    is actively cached.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an ndarray index is actively cached.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.isCached\n    true\n\n\nndindex.prototype.kind\n    Read-only property returning the ndarray index kind.\n\n    Returns\n    -------\n    out: string\n        Index kind.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x, { 'kind': 'cartesian' } );\n    > idx.kind\n    'cartesian'\n\n\nndindex.prototype.type\n    Read-only property returning the ndarray index type.\n\n    Returns\n    -------\n    out: string\n        Index type.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.type\n    <string>\n\n\nndindex.prototype.toString()\n    Serializes an instance as a string.\n\n    Returns\n    -------\n    str: string\n        Serialized string.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.toString()\n    <string>\n\n\nndindex.prototype.toJSON()\n    Serializes an instance as a JSON object.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.toJSON()\n    { 'type': 'ndindex', ... }\n\n    See Also\n    --------\n    array, ndarray, FancyArray, ndslice, ndarray2fancy\n","ndindex.free":"\nndindex.free( id )\n    Frees the instance associated with a provided identifier.\n\n    Parameters\n    ----------\n    id: string\n        Instance identifier.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an instance was successfully freed.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > ndindex.free( idx.id )\n    <boolean>","ndindex.get":"\nndindex.get( id )\n    Returns the ndarray associated with the instance having a provided\n    identifier.\n\n    Parameters\n    ----------\n    id: string\n        Instance identifier.\n\n    Returns\n    -------\n    out: Object\n        Object containing ndarray data.\n\n    out.data: ndarray\n        The underlying ndarray associated with the provided identifier.\n\n    out.type: string\n        The type of ndarray index.\n\n    out.dtype: string\n        The data type of the underlying ndarray.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > ndindex.get( idx.id )\n    {...}","ndindex.cartesianIndex":"\nndindex.cartesianIndex( x[, options] )\n    Returns an ndarray index containing Cartesian indices.\n\n    This is a convenience method for calling `ndindex` with `kind` set to\n    'cartesian'.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.persist: boolean (optional)\n        Boolean indicating whether to continue persisting an index object after\n        first usage. Default: false.\n\n    Returns\n    -------\n    out: ndindex\n        Index instance.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = ndindex.cartesianIndex( x );","ndindex.linearIndex":"\nndindex.linearIndex( x[, options] )\n    Returns an ndarray index for indices representing locations in linear\n    memory.\n\n    This is a convenience method for calling `ndindex` with `kind` set to\n    'linear'.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.persist: boolean (optional)\n        Boolean indicating whether to continue persisting an index object after\n        first usage. Default: false.\n\n    Returns\n    -------\n    out: ndindex\n        Index instance.\n\n    Examples\n    --------\n    > var x = ndempty( [ 5 ], { 'dtype': 'int32' } );\n    > var idx = ndindex.linearIndex( x );","ndindex.prototype.data":"\nndindex.prototype.data\n    Read-only property returning an ndarray view of the underlying index\n    ndarray.\n\n    Returns\n    -------\n    out: ndarray\n        Array data.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.data\n    <ndarray>","ndindex.prototype.dtype":"\nndindex.prototype.dtype\n    Read-only property returning the underlying data type of the index ndarray.\n\n    Returns\n    -------\n    out: string\n        Array data type.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.dtype\n    'int32'","ndindex.prototype.id":"\nndindex.prototype.id\n    Read-only property returning the unique identifier associated with an\n    instance.\n\n    Returns\n    -------\n    out: string\n        String identifier.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.id\n    <string>","ndindex.prototype.isCached":"\nndindex.prototype.isCached\n    Read-only property returning a boolean indicating whether an ndarray index\n    is actively cached.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an ndarray index is actively cached.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.isCached\n    true","ndindex.prototype.kind":"\nndindex.prototype.kind\n    Read-only property returning the ndarray index kind.\n\n    Returns\n    -------\n    out: string\n        Index kind.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x, { 'kind': 'cartesian' } );\n    > idx.kind\n    'cartesian'","ndindex.prototype.type":"\nndindex.prototype.type\n    Read-only property returning the ndarray index type.\n\n    Returns\n    -------\n    out: string\n        Index type.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.type\n    <string>","ndindex.prototype.toString":"\nndindex.prototype.toString()\n    Serializes an instance as a string.\n\n    Returns\n    -------\n    str: string\n        Serialized string.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.toString()\n    <string>","ndindex.prototype.toJSON":"\nndindex.prototype.toJSON()\n    Serializes an instance as a JSON object.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var x = ndempty( [ 2, 2 ], { 'dtype': 'int32' } );\n    > var idx = new ndindex( x );\n    > idx.toJSON()\n    { 'type': 'ndindex', ... }\n\n    See Also\n    --------\n    array, ndarray, FancyArray, ndslice, ndarray2fancy","nditerColumnEntries":"\nnditerColumnEntries( x[, options] )\n    Returns an iterator which returns [index, column] pairs for each column in a\n    matrix (or stack of matrices).\n\n    Each returned index is a Cartesian index (i.e., an array of subscripts/\n    dimension indices). A dimension index equal to `null` indicates that all\n    values along the respective dimension are included in the returned ndarray.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    options: Object (optional)\n        Options.\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether returned ndarray views should be read-only.\n        If the input ndarray is read-only, setting this option to `false` raises\n        an exception. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > var it = nditerColumnEntries( x );\n    > var v = it.next().value;\n    > v[ 0 ]\n    [ null, 0 ]\n    > ndarray2array( v[ 1 ] )\n    [ 1, 3 ]\n    > v = it.next().value;\n    > v[ 0 ]\n    [ null, 1 ]\n    > ndarray2array( v[ 1 ] )\n    [ 2, 4 ]\n\n    See Also\n    --------\n    nditerColumns, nditerEntries, nditerRowEntries, ndslice\n","nditerColumns":"\nnditerColumns( x[, options] )\n    Returns an iterator which iterates over each column in a matrix (or stack of\n    matrices).\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray for which to create the iterator.\n\n    options: Object (optional)\n        Options.\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether returned ndarray views should be read-only.\n        If the input ndarray is read-only, setting this option to `false` raises\n        an exception. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > var it = nditerColumns( x );\n    > var v = it.next().value;\n    > ndarray2array( v )\n    [ 1, 3 ]\n    > v = it.next().value;\n    > ndarray2array( v )\n    [ 2, 4 ]\n\n    See Also\n    --------\n    nditerColumnEntries, nditerRows, ndslice\n","nditerEntries":"\nnditerEntries( x[, options] )\n    Returns an iterator which returns [index, value] pairs for each element in a\n    provided ndarray.\n\n    Each returned index is a Cartesian index (i.e., an array of subscripts/\n    dimension indices).\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    options: Object (optional)\n        Options.\n\n    options.order: string (optional)\n        Index iteration order. By default, the returned iterator returns values\n        according to the layout order of the provided array. Accordingly, for\n        row-major input arrays, the last dimension indices increment fastest.\n        For column-major input arrays, the first dimension indices increment\n        fastest. To override the inferred order and ensure that indices\n        increment in a specific manner, regardless of the input array's layout\n        order, explicitly set the iteration order. Note, however, that iterating\n        according to an order which does not match that of the input array may,\n        in some circumstances, result in performance degradation due to cache\n        misses. Must be either 'row-major' or 'column-major'.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > var it = nditerEntries( x );\n    > var v = it.next().value\n    [ [ 0, 0 ], 1 ]\n    > v = it.next().value\n    [ [ 0, 1 ], 2 ]\n\n    See Also\n    --------\n    ndarray, nditerIndices, nditerValues\n","nditerIndices":"\nnditerIndices( shape[, options] )\n    Returns an iterator which returns indices for use indexing into an ndarray\n    having a specified shape.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    shape: Array<integer>\n        Input shape.\n\n    options: Object (optional)\n        Options.\n\n    options.order: string (optional)\n        Index iteration order. By default, the returned iterator iterates over\n        the last dimensions first, thus corresponding to iteration over\n        contiguous data stored in row-major order. Must be either 'row-major'\n        or 'column-major'.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > var it = nditerIndices( x.shape );\n    > var v = it.next().value\n    [ 0, 0 ]\n    > v = it.next().value\n    [ 0, 1 ]\n\n    See Also\n    --------\n    ndarray, nditerEntries, nditerValues\n","nditerInterleaveSubarrays":"\nnditerInterleaveSubarrays( arr, ndims )\n    Returns an iterator which iterates over interleaved subarrays.\n\n    For input ndarrays supporting read-only views, the function returns\n    *read-only* views of interleaved subarrays. As input ndarrays may be\n    broadcasted, a view is typically *not* contiguous. As more than one element\n    of a returned view may refer to the same memory location, writing to a view\n    may affect multiple elements. If you need to write to a subarray, copy the\n    subarray before attempting mutation.\n\n    The function throws an error if a provided broadcast-incompatible ndarrays.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    arr: ArrayLike<ndarray>\n        Input ndarrays. All ndarrays must be broadcast-compatible. After\n        broadcasting, each broadcasted input ndarray must have at least\n        `ndims+1` dimensions.\n\n    ndims: integer\n        Number of dimensions to stack after broadcasting.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n    > var it = nditerInterleaveSubarrays( [ x, x ], 2 );\n    > var v = it.next().value;\n    > ndarray2array( v )\n    [ [ 1, 2 ], [ 3, 4 ] ]\n\n    See Also\n    --------\n    nditerSubarrays, ndslice\n","nditerMatrices":"\nnditerMatrices( x[, options] )\n    Returns an iterator which iterates over each matrix in a stack of matrices.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray for which to create the iterator.\n\n    options: Object (optional)\n        Options.\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether returned ndarray views should be read-only.\n        If the input ndarray is read-only, setting this option to `false` raises\n        an exception. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n    > var it = nditerMatrices( x );\n    > var v = it.next().value;\n    > ndarray2array( v )\n    [ [ 1, 2 ], [ 3, 4 ] ]\n\n    See Also\n    --------\n    nditerColumns, nditerMatrixEntries, nditerRows, ndslice\n","nditerMatrixEntries":"\nnditerMatrixEntries( x[, options] )\n    Returns an iterator which returns [index, matrix] pairs for each matrix in a\n    stack of matrices.\n\n    Each returned index is a Cartesian index (i.e., an array of subscripts/\n    dimension indices). A dimension index equal to `null` indicates that all\n    values along the respective dimension are included in the returned ndarray.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    options: Object (optional)\n        Options.\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether returned ndarray views should be read-only.\n        If the input ndarray is read-only, setting this option to `false` raises\n        an exception. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n    > var it = nditerMatrixEntries( x );\n    > var v = it.next().value;\n    > v[ 0 ]\n    [ 0, null, null ]\n    > ndarray2array( v[ 1 ] )\n    [ [ 1, 2 ], [ 3, 4 ] ]\n\n    See Also\n    --------\n    nditerColumnEntries, nditerEntries, nditerMatrices, nditerRowEntries, ndslice\n","nditerRowEntries":"\nnditerRowEntries( x[, options] )\n    Returns an iterator which returns [index, row] pairs for each row in a\n    matrix (or stack of matrices).\n\n    Each returned index is a Cartesian index (i.e., an array of subscripts/\n    dimension indices). A dimension index equal to `null` indicates that all\n    values along the respective dimension are included in the returned ndarray.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    options: Object (optional)\n        Options.\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether returned ndarray views should be read-only.\n        If the input ndarray is read-only, setting this option to `false` raises\n        an exception. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > var it = nditerRowEntries( x );\n    > var v = it.next().value;\n    > v[ 0 ]\n    [ 0, null ]\n    > ndarray2array( v[ 1 ] )\n    [ 1, 2 ]\n    > v = it.next().value;\n    > v[ 0 ]\n    [ 1, null ]\n    > ndarray2array( v[ 1 ] )\n    [ 3, 4 ]\n\n    See Also\n    --------\n    nditerColumnEntries, nditerEntries, nditerRows, ndslice\n","nditerRows":"\nnditerRows( x[, options] )\n    Returns an iterator which iterates over each row in a matrix (or stack of\n    matrices).\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray for which to create the iterator.\n\n    options: Object (optional)\n        Options.\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether returned ndarray views should be read-only.\n        If the input ndarray is read-only, setting this option to `false` raises\n        an exception. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > var it = nditerRows( x );\n    > var v = it.next().value;\n    > ndarray2array( v )\n    [ 1, 2 ]\n    > v = it.next().value;\n    > ndarray2array( v )\n    [ 3, 4 ]\n\n    See Also\n    --------\n    nditerColumns, nditerRowEntries, ndslice\n","nditerSelectDimension":"\nnditerSelectDimension( x, dim[, options] )\n    Returns an iterator which iterates over each view along a specified\n    dimension.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray for which to create the iterator.\n\n    dim: integer\n        Dimension index. If less than zero, the index is resolved relative to\n        the last dimension, with the last dimension corresponding to the value\n        `-1`.\n\n    options: Object (optional)\n        Options.\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether returned ndarray views should be read-only.\n        If the input ndarray is read-only, setting this option to `false` raises\n        an exception. Default: true.\n\n    options.keepdim: boolean (optional)\n        Boolean indicating whether returned views should include the selected\n        dimension as a singleton dimension. Including the selected dimension as\n        a singleton dimension can be useful when wanting to ensure that returned\n        views remain broadcast compatible with the input ndarray. Default:\n        false.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n    > var it = nditerSelectDimension( x, 0 );\n    > var v = it.next().value;\n    > ndarray2array( v )\n    [ [ 1, 2 ], [ 3, 4 ] ]\n\n    See Also\n    --------\n    nditerColumns, nditerMatrices, nditerRows, ndslice\n","nditerStacks":"\nnditerStacks( x, dims[, options] )\n    Returns an iterator which iterates over each subarray in a stack of\n    subarrays according to a list of specified stack dimensions.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray for which to create the iterator. Must have at least\n        `dims.length+1` dimensions.\n\n    dims: Array<integer>\n        Indices of dimensions to stack. If a dimension index is less than zero,\n        the index is resolved relative to the last dimension, with the last\n        dimension corresponding to the value `-1`. The list of indices must be\n        unique and resolve to dimension indices sorted in ascending order.\n\n    options: Object (optional)\n        Options.\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether returned ndarray views should be read-only.\n        If the input ndarray is read-only, setting this option to `false` raises\n        an exception. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n    > var it = nditerStacks( x, [ 1, 2 ] );\n    > var v = it.next().value;\n    > ndarray2array( v )\n    [ [ 1, 2 ], [ 3, 4 ] ]\n\n    See Also\n    --------\n    nditerColumns, nditerMatrices, nditerRows, nditerSubarrays, ndslice\n","nditerSubarrays":"\nnditerSubarrays( x, ndims[, options] )\n    Returns an iterator which iterates over each subarray in a stack of\n    subarrays.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray for which to create the iterator. Must have at least\n        `ndims+1` dimensions.\n\n    ndims: integer\n        Number of dimensions to stack.\n\n    options: Object (optional)\n        Options.\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether returned ndarray views should be read-only.\n        If the input ndarray is read-only, setting this option to `false` raises\n        an exception. Default: true.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ [ 1, 2 ], [ 3, 4 ] ] ] );\n    > var it = nditerSubarrays( x, 2 );\n    > var v = it.next().value;\n    > ndarray2array( v )\n    [ [ 1, 2 ], [ 3, 4 ] ]\n\n    See Also\n    --------\n    nditerColumns, nditerMatrices, nditerRows, nditerStacks, ndslice\n","nditerValues":"\nnditerValues( x[, options] )\n    Returns an iterator which returns individual elements from a provided\n    ndarray.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an ndarray's `@@iterator` method, regardless of whether this method\n    is defined.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    options: Object (optional)\n        Options.\n\n    options.order: string (optional)\n        Index iteration order. By default, the returned iterator returns values\n        according to the layout order of the provided array. Accordingly, for\n        row-major input arrays, the last dimension indices increment fastest.\n        For column-major input arrays, the first dimension indices increment\n        fastest. To override the inferred order and ensure that indices\n        increment in a specific manner, regardless of the input array's layout\n        order, explicitly set the iteration order. Note, however, that iterating\n        according to an order which does not match that of the input array may,\n        in some circumstances, result in performance degradation due to cache\n        misses. Must be either 'row-major' or 'column-major'.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] );\n    > var it = nditerValues( x );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    ndarray, nditerEntries, nditerIndices\n","ndmap":"\nndmap( x[, options], fcn[, thisArg] )\n    Applies a callback function to elements in an input ndarray and assigns\n    results to elements in a new output ndarray.\n\n    The callback function is provided the following arguments:\n\n    - value: current array element.\n    - indices: current array element indices.\n    - arr: the input ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.dtype: string (optional)\n        Output ndarray data type. Overrides using the input array's inferred\n        data type.\n\n    fcn: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback function execution context.\n\n    Examples\n    --------\n    > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n    > function f( v ) { return v*10.0; };\n    > var y = ndmap( x, f );\n    > ndarray2array( y )\n    [ [ 10.0, 20.0 ], [ 30.0, 40.0 ] ]\n\n    See Also\n    --------\n    ndfilter, ndfilterMap, ndforEach, ndslice","ndreject":"\nndreject( x[, options], predicate[, thisArg] )\n    Returns a shallow copy of an ndarray containing only those elements which\n    fail a test implemented by a predicate function.\n\n    The predicate function is provided the following arguments:\n\n    - value: current array element.\n    - indices: current array element indices.\n    - arr: the input ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    options: Object (optional)\n        Function options.\n\n    options.dtype: string (optional)\n        Output ndarray data type. Overrides using the input array's inferred\n        data type.\n\n    options.order: string (optional)\n        Index iteration order. By default, the function iterates over elements\n        according to the layout order of the provided array. Accordingly, for\n        row-major input arrays, the last dimension indices increment fastest.\n        For column-major input arrays, the first dimension indices increment\n        fastest. To override the inferred order and ensure that indices\n        increment in a specific manner, regardless of the input array's layout\n        order, explicitly set the iteration order. Note, however, that iterating\n        according to an order which does not match that of the input array may,\n        in some circumstances, result in performance degradation due to cache\n        misses. Must be either 'row-major' or 'column-major'.\n\n    predicate: Function\n        Predicate function.\n\n    thisArg: any (optional)\n        Predicate function execution context.\n\n    Examples\n    --------\n    > var x = array( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );\n    > function f( v ) { return v <= 2.0; };\n    > var y = ndreject( x, f );\n    > ndarray2array( y )\n    [ 3.0, 4.0 ]\n\n    See Also\n    --------\n    ndfilter, ndfilterMap, ndmap, ndslice","ndslice":"\nndslice( x, ...s[, options] )\n    Returns a read-only view of an input ndarray.\n\n    The function supports three (mutually exclusive) means of providing slice\n    arguments:\n\n    1. Providing a single MultiSlice object.\n    2. Providing a single array containing slice arguments.\n    3. Providing slice arguments as separate arguments.\n\n    An individual slice argument must be either a Slice, an integer, null, or\n    undefined.\n\n    In all cases, the number of slice dimensions must match the number of array\n    dimensions.\n\n    If providing a MultiSlice object or an array of slice arguments, no other\n    slice arguments should be provided.\n\n    Mixing function invocation styles (e.g., providing multiple MultiSlice\n    objects or providing an array of slice arguments followed by additional\n    slice arguments) is not supported.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    s: ...MultiSlice|Slice|null|undefined|integer|ArrayLike\n        Slice arguments.\n\n    options: Object (optional)\n        Options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking.\n        Default: true.\n\n    Returns\n    -------\n    out: ndarray\n        Output array view.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n    <ndarray>\n    > x.shape\n    [ 2, 2 ]\n    > var s = new MultiSlice( null, 1 )\n    <MultiSlice>\n    > var y = ndslice( x, s )\n    <ndarray>\n    > y.shape\n    [ 2 ]\n    > ndarray2array( y )\n    [ 2, 4 ]\n\n    See Also\n    --------\n    array, ndat, ndarray, ndsliceAssign, ndsliceDimension\n","ndsliceAssign":"\nndsliceAssign( x, y, ...s[, options] )\n    Assigns element values from a broadcasted input ndarray to corresponding\n    elements in an output ndarray view.\n\n    The function supports three (mutually exclusive) means of providing slice\n    arguments:\n\n    1. Providing a single MultiSlice object.\n    2. Providing a single array containing slice arguments.\n    3. Providing slice arguments as separate arguments.\n\n    An individual slice argument must be either a Slice, an integer, null, or\n    undefined.\n\n    In all cases, the number of slice dimensions must match the number of output\n    array dimensions.\n\n    If providing a MultiSlice object or an array of slice arguments, no other\n    slice arguments should be provided.\n\n    Mixing function invocation styles (e.g., providing multiple MultiSlice\n    objects or providing an array of slice arguments followed by additional\n    slice arguments) is not supported.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array. The input array must be broadcast compatible with the\n        output array view and must have a data type which can be safely cast to\n        the output array data type. Floating-point data types (both real and\n        complex) are allowed to downcast to a lower precision data type of the\n        same kind (e.g., element values from a 'float64' input array can be\n        assigned to corresponding elements in a 'float32' output array).\n\n    y: ndarray\n        Output array. The output array must be writable.\n\n    s: ...MultiSlice|Slice|null|undefined|integer|ArrayLike\n        Slice arguments.\n\n    options: Object (optional)\n        Options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking.\n        Default: true.\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var y = ndzeros( [ 2, 2 ] )\n    <ndarray>\n    > var x = scalar2ndarray( 3.0 )\n    <ndarray>\n    > var s = new MultiSlice( null, 1 )\n    <MultiSlice>\n    > var out = ndsliceAssign( x, y, s )\n    <ndarray>\n    > var bool = ( out === y )\n    true\n    > ndarray2array( y )\n    [ [ 0.0, 3.0 ], [ 0.0, 3.0 ] ]\n\n    See Also\n    --------\n    array, ndarray, ndslice\n","ndsliceDimension":"\nndsliceDimension( x, dim, slice[, options] )\n    Returns a read-only view of an input ndarray when sliced along a specified\n    dimension.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    dim: integer\n        Index of dimension to slice. If less than zero, the index is resolved\n        relative to the last dimension, with the last dimension corresponding to\n        the value `-1`.\n\n    slice: Slice|integer|null|undefined\n        Slice object or an integer. If provided `null` or `undefined`, the\n        returned view includes all elements along a specified dimension. If\n        provided an integer less than zero, the corresponding element along the\n        specified dimension is resolved relative to the last element along that\n        dimension. For negative integers, the last element corresponds to the\n        value `-1`.\n\n    options: Object (optional)\n        Options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking.\n        Default: true.\n\n    Returns\n    -------\n    out: ndarray\n        Output array view.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n    <ndarray>\n    > x.shape\n    [ 2, 2 ]\n    > var y = ndsliceDimension( x, 1, 1 )\n    <ndarray>\n    > y.shape\n    [ 2 ]\n    > ndarray2array( y )\n    [ 2, 4 ]\n\n    See Also\n    --------\n    array, ndarray, ndslice, ndsliceDimensionFrom, ndsliceDimensionTo\n","ndsliceDimensionFrom":"\nndsliceDimensionFrom( x, dim, start[, options] )\n    Returns a read-only shifted view of an input ndarray along a specified\n    dimension.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    dim: integer\n        Index of dimension to slice. If less than zero, the index is resolved\n        relative to the last dimension, with the last dimension corresponding to\n        the value `-1`.\n\n    start: integer\n        Starting index (inclusive). If less than zero, the corresponding element\n        along the specified dimension is resolved relative to the last element\n        along that dimension. For negative integers, the last element\n        corresponds to the value `-1`.\n\n    options: Object (optional)\n        Options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking.\n        Default: true.\n\n    Returns\n    -------\n    out: ndarray\n        Output array view.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n    <ndarray>\n    > x.shape\n    [ 2, 2 ]\n    > var y = ndsliceDimensionFrom( x, 1, 1 )\n    <ndarray>\n    > y.shape\n    [ 2, 1 ]\n    > ndarray2array( y )\n    [ [ 2 ], [ 4 ] ]\n\n    See Also\n    --------\n    array, ndarray, ndslice, ndsliceDimension, ndsliceDimensionTo, ndsliceFrom\n","ndsliceDimensionTo":"\nndsliceDimensionTo( x, dim, stop[, options] )\n    Returns a read-only truncated view of an input ndarray along a specified\n    dimension.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    dim: integer\n        Index of dimension to slice. If less than zero, the index is resolved\n        relative to the last dimension, with the last dimension corresponding to\n        the value `-1`.\n\n    stop: integer\n        Ending index (exclusive). If less than zero, the corresponding element\n        along the specified dimension is resolved relative to the last element\n        along that dimension. For negative integers, the last element\n        corresponds to the value `-1`.\n\n    options: Object (optional)\n        Options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking.\n        Default: true.\n\n    Returns\n    -------\n    out: ndarray\n        Output array view.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n    <ndarray>\n    > x.shape\n    [ 2, 2 ]\n    > var y = ndsliceDimensionTo( x, 1, 1 )\n    <ndarray>\n    > y.shape\n    [ 2, 1 ]\n    > ndarray2array( y )\n    [ [ 1 ], [ 3 ] ]\n\n    See Also\n    --------\n    array, ndarray, ndslice, ndsliceDimension, ndsliceDimensionFrom, ndsliceTo\n","ndsliceFrom":"\nndsliceFrom( x, ...start[, options] )\n    Returns a read-only shifted view of an input ndarray.\n\n    The function supports two (mutually exclusive) means of providing starting\n    indices:\n\n    1. Providing a single array containing start arguments.\n    2. Providing start arguments as separate arguments.\n\n    An individual start argument must be either an integer, null, or undefined.\n\n    In all cases, the number of start indices must match the number of array\n    dimensions.\n\n    If providing an array of start arguments, no other start arguments should be\n    provided.\n\n    Mixing function invocation styles (e.g., providing an array of start\n    arguments followed by additional start arguments) is not supported.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    start: ...null|void|integer\n        Starting indices (inclusive). If an element is either `null` or\n        `undefined`, the function returns a view containing all elements along\n        that dimension. A negative integer indicates to resolve a starting index\n        relative to the last element along a corresponding dimension, with the\n        last element having index `-1`.\n\n    options: Object (optional)\n        Options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking.\n        Default: true.\n\n    Returns\n    -------\n    out: ndarray\n        Output array view.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n    <ndarray>\n    > x.shape\n    [ 2, 2 ]\n    > var y = ndsliceFrom( x, 0, 1 )\n    <ndarray>\n    > y.shape\n    [ 2, 1 ]\n    > ndarray2array( y )\n    [ [ 2 ], [ 4 ] ]\n\n    See Also\n    --------\n    array, ndarray, ndslice, ndsliceDimensionFrom, ndsliceTo\n","ndsliceTo":"\nndsliceTo( x, ...stop[, options] )\n    Returns a read-only truncated view of an input ndarray.\n\n    The function supports two (mutually exclusive) means of providing ending\n    indices:\n\n    1. Providing a single array containing stop arguments.\n    2. Providing stop arguments as separate arguments.\n\n    An individual stop argument must be either an integer, null, or undefined.\n\n    In all cases, the number of stop indices must match the number of array\n    dimensions.\n\n    If providing an array of stop arguments, no other stop arguments should be\n    provided.\n\n    Mixing function invocation styles (e.g., providing an array of stop\n    arguments followed by additional stop arguments) is not supported.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    stop: ...null|void|integer\n        Ending indices (exclusive). If an ending index is either `null` or\n        `undefined`, the function returns a view containing all elements along\n        that dimension. A negative integer indicates to resolve an ending index\n        relative to the last element along a corresponding dimension, with the\n        last element having index `-1`.\n\n    options: Object (optional)\n        Options.\n\n    options.strict: boolean (optional)\n        Boolean indicating whether to enforce strict bounds checking.\n        Default: true.\n\n    Returns\n    -------\n    out: ndarray\n        Output array view.\n\n    Examples\n    --------\n    > var x = array( [ [ 1, 2 ], [ 3, 4 ] ] )\n    <ndarray>\n    > x.shape\n    [ 2, 2 ]\n    > var y = ndsliceTo( x, 1, 1 )\n    <ndarray>\n    > y.shape\n    [ 1, 1 ]\n    > ndarray2array( y )\n    [ [ 1 ] ]\n\n    See Also\n    --------\n    array, ndarray, ndslice, ndsliceDimensionTo, ndsliceFrom\n","ndzeros":"\nndzeros( shape[, options] )\n    Returns a zero-filled ndarray having a specified shape and data type.\n\n    Parameters\n    ----------\n    shape: ArrayLikeObject<integer>|integer\n        Array shape.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Underlying data type. Must be a numeric data type or \"generic\". Default:\n        'float64'.\n\n    options.order: string (optional)\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran-style). Default: 'row-major'.\n\n    options.mode: string (optional)\n        Specifies how to handle indices which exceed array dimensions. If equal\n        to 'throw', an ndarray instance throws an error when an index exceeds\n        array dimensions. If equal to 'normalize', an ndarray instance\n        normalizes negative indices and throws an error when an index exceeds\n        array dimensions. If equal to 'wrap', an ndarray instance wraps around\n        indices exceeding array dimensions using modulo arithmetic. If equal to\n        'clamp', an ndarray instance sets an index exceeding array dimensions\n        to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n    options.submode: Array<string> (optional)\n        Specifies how to handle subscripts which exceed array dimensions. If a\n        mode for a corresponding dimension is equal to 'throw', an ndarray\n        instance throws an error when a subscript exceeds array dimensions. If\n        equal to 'normalize', an ndarray instance normalizes negative\n        subscripts and throws an error when a subscript exceeds array\n        dimensions. If equal to 'wrap', an ndarray instance wraps around\n        subscripts exceeding array dimensions using modulo arithmetic. If equal\n        to 'clamp', an ndarray instance sets a subscript exceeding array\n        dimensions to either `0` (minimum index) or the maximum index. If the\n        number of modes is fewer than the number of dimensions, the function\n        recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether an array should be read-only. Default: false.\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var arr = ndzeros( [ 2, 2 ] )\n    <ndarray>\n    > var sh = arr.shape\n    [ 2, 2 ]\n    > var dt = arr.dtype\n    'float64'\n\n    See Also\n    --------\n    ndempty, ndzerosLike\n","ndzerosLike":"\nndzerosLike( x[, options] )\n    Returns a zero-filled ndarray having the same shape and data type as a\n    provided input ndarray.\n\n    The function infers the following attributes from the input array:\n\n    - shape: array shape.\n    - dtype: underlying array data type.\n    - order: whether the array order is row-major (C-style) or column-major\n      (Fortran-style).\n\n    Parameters\n    ----------\n    x: ndarray\n        Input array.\n\n    options: Object (optional)\n        Options.\n\n    options.shape: ArrayLikeObject<integer>|integer (optional)\n        Array shape. Overrides the input array's inferred shape.\n\n    options.dtype: string (optional)\n        Array data type. Overrides the input array's inferred data type.\n\n    options.order: string (optional)\n        Array order (either 'row-major' (C-style) or 'column-major' (Fortran-\n        style)). Overrides the input array's inferred order.\n\n    options.mode: string (optional)\n        Specifies how to handle indices which exceed array dimensions. If equal\n        to 'throw', an ndarray instance throws an error when an index exceeds\n        array dimensions. If equal to 'normalize', an ndarray instance\n        normalizes negative indices and throws an error when an index exceeds\n        array dimensions. If equal to 'wrap', an ndarray instance wraps around\n        indices exceeding array dimensions using modulo arithmetic. If equal to\n        'clamp', an ndarray instance sets an index exceeding array dimensions\n        to either `0` (minimum index) or the maximum index. Default: 'throw'.\n\n    options.submode: Array<string> (optional)\n        Specifies how to handle subscripts which exceed array dimensions. If a\n        mode for a corresponding dimension is equal to 'throw', an ndarray\n        instance throws an error when a subscript exceeds array dimensions. If\n        equal to 'normalize', an ndarray instance normalizes negative\n        subscripts and throws an error when a subscript exceeds array\n        dimensions. If equal to 'wrap', an ndarray instance wraps around\n        subscripts exceeding array dimensions using modulo arithmetic. If equal\n        to 'clamp', an ndarray instance sets a subscript exceeding array\n        dimensions to either `0` (minimum index) or the maximum index. If the\n        number of modes is fewer than the number of dimensions, the function\n        recycles modes using modulo arithmetic. Default: [ options.mode ].\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether an array should be read-only. Default: false.\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var x = base.ndzeros( 'float64', [ 2, 2 ], 'row-major' )\n    <ndarray>\n    > var sh = x.shape\n    [ 2, 2 ]\n    > var dt = x.dtype\n    'float64'\n    > var y = ndzerosLike( x )\n    <ndarray>\n    > sh = y.shape\n    [ 2, 2 ]\n    > dt = y.dtype\n    'float64'\n\n    See Also\n    --------\n    ndemptyLike, ndzeros\n","nextGraphemeClusterBreak":"\nnextGraphemeClusterBreak( str[, fromIndex] )\n    Returns the next extended grapheme cluster break in a string after a\n    specified position.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    fromIndex: integer (optional)\n        Position. Default: 0.\n\n    Returns\n    -------\n    out: integer\n        Next extended grapheme cluster break position.\n\n    Examples\n    --------\n    > var out = nextGraphemeClusterBreak( 'last man standing', 4 )\n    5\n    > out = nextGraphemeClusterBreak( 'presidential election', 8 )\n    9\n    > out = nextGraphemeClusterBreak( 'अनुच्छेद', 1 )\n    3\n    > out = nextGraphemeClusterBreak( '🌷' )\n    -1\n\n    See Also\n    --------\n    numGraphemeClusters, prevGraphemeClusterBreak","nextTick":"\nnextTick( clbk[, ...args] )\n    Adds a callback to the \"next tick queue\".\n\n    The queue is fully drained after the current operation on the JavaScript\n    stack runs to completion and before the event loop is allowed to continue.\n\n    Parameters\n    ----------\n    clbk: Function\n        Callback to invoke.\n\n    ...args: any (optional)\n        Arguments to provide to the callback upon invocation.\n\n    Examples\n    --------\n    > function f() { console.log( 'beep' ); };\n    > nextTick( f )\n\n","NIGHTINGALES_ROSE":"\nNIGHTINGALES_ROSE()\n    Returns data for Nightingale's famous polar area diagram.\n\n    Returns\n    -------\n    out: Array<Object>\n        Nightingale's data.\n\n    Examples\n    --------\n    > var data = NIGHTINGALES_ROSE()\n    [{...}, {...}, ...]\n\n    References\n    ----------\n    - Nightingale, Florence. 1859. *A contribution to the sanitary history of\n    the British army during the late war with Russia*. London, United Kingdom:\n    John W. Parker and Son.<https://curiosity.lib.harvard.edu/contagion/\n    catalog/36-990101646750203941>.\n\n","NINF":"\nNINF\n    Double-precision floating-point negative infinity.\n\n    Examples\n    --------\n    > NINF\n    -Infinity\n\n    See Also\n    --------\n    FLOAT16_NINF, FLOAT32_NINF, PINF\n","NODE_VERSION":"\nNODE_VERSION\n    Node version.\n\n    Examples\n    --------\n    > NODE_VERSION\n    <string>\n\n","none":"\nnone( collection )\n    Tests whether all elements in a collection are falsy.\n\n    The function immediately returns upon encountering a truthy value.\n\n    If provided an empty collection, the function returns `true`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if all elements are falsy; otherwise, the\n        function returns `false`.\n\n    Examples\n    --------\n    > var arr = [ 0, 0, 0, 0, 0 ];\n    > var bool = none( arr )\n    true\n\n    See Also\n    --------\n    any, every, forEach, noneBy, some\n","noneBy":"\nnoneBy( collection, predicate[, thisArg ] )\n    Tests whether all elements in a collection fail a test implemented by a\n    predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    The function immediately returns upon encountering a truthy return value.\n\n    If provided an empty collection, the function returns `true`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns a falsy\n        value for all elements; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function negative( v ) { return ( v < 0 ); };\n    > var arr = [ 1, 2, 3, 4 ];\n    > var bool = noneBy( arr, negative )\n    true\n\n    See Also\n    --------\n    anyBy, everyBy, forEach, none, noneByRight, someBy\n","noneByAsync":"\nnoneByAsync( collection, [options,] predicate, done )\n    Tests whether all elements in a collection fail a test implemented by a\n    predicate function.\n\n    When invoked, the predicate function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If the\n    predicate function accepts two arguments, the predicate function is\n    provided:\n\n    - value\n    - next\n\n    If the predicate function accepts three arguments, the predicate function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other predicate function signature, the predicate function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - result: test result.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    The function immediately returns upon encountering a truthy `result` value\n    and calls the `done` callback with `null` as the first argument and `false`\n    as the second argument.\n\n    If all elements fail, the function calls the `done` callback with `null` as\n    the first argument and `true` as the second argument.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > noneByAsync( arr, predicate, done )\n    1000\n    2500\n    3000\n    true\n\n    // Limit number of concurrent invocations:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 3000, 2500, 1000 ];\n    > noneByAsync( arr, opts, predicate, done )\n    2500\n    3000\n    1000\n    true\n\n    // Process sequentially:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 3000, 2500, 1000 ];\n    > noneByAsync( arr, opts, predicate, done )\n    3000\n    2500\n    1000\n    true\n\n\nnoneByAsync.factory( [options,] predicate )\n    Returns a function which tests whether all elements in a collection fail a\n    test implemented by a predicate function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = noneByAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n\n    See Also\n    --------\n    anyByAsync, everyByAsync, forEachAsync, noneBy, noneByRightAsync, someByAsync\n","noneByAsync.factory":"\nnoneByAsync.factory( [options,] predicate )\n    Returns a function which tests whether all elements in a collection fail a\n    test implemented by a predicate function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = noneByAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n\n    See Also\n    --------\n    anyByAsync, everyByAsync, forEachAsync, noneBy, noneByRightAsync, someByAsync","noneByRight":"\nnoneByRight( collection, predicate[, thisArg ] )\n    Tests whether all elements in a collection fail a test implemented by a\n    predicate function, iterating from right to left.\n\n    The predicate function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    The function immediately returns upon encountering a truthy return value.\n\n    If provided an empty collection, the function returns `true`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns a falsy\n        value for all elements; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function positive( v ) { return ( v > 0 ); };\n    > var arr = [ -1, -2, -3, -4 ];\n    > var bool = noneByRight( arr, positive )\n    true\n\n    See Also\n    --------\n    anyByRight, everyByRight, forEachRight, none, noneBy, someByRight\n","noneByRightAsync":"\nnoneByRightAsync( collection, [options,] predicate, done )\n    Tests whether all elements in a collection fail a test implemented by a\n    predicate function, iterating from right to left.\n\n    When invoked, the predicate function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If the\n    predicate function accepts two arguments, the predicate function is\n    provided:\n\n    - value\n    - next\n\n    If the predicate function accepts three arguments, the predicate function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other predicate function signature, the predicate function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - result: test result.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    The function immediately returns upon encountering a truthy `result` value\n    and calls the `done` callback with `null` as the first argument and `false`\n    as the second argument.\n\n    If all elements fail, the function calls the `done` callback with `null` as\n    the first argument and `true` as the second argument.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > noneByRightAsync( arr, predicate, done )\n    1000\n    2500\n    3000\n    true\n\n    // Limit number of concurrent invocations:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 1000, 2500, 3000 ];\n    > noneByRightAsync( arr, opts, predicate, done )\n    2500\n    3000\n    1000\n    true\n\n    // Process sequentially:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 1000, 2500, 3000 ];\n    > noneByRightAsync( arr, opts, predicate, done )\n    3000\n    2500\n    1000\n    true\n\n\nnoneByRightAsync.factory( [options,] predicate )\n    Returns a function which tests whether all elements in a collection fail a\n    test implemented by a predicate function, iterating from right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = noneByRightAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n\n    See Also\n    --------\n    anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByAsync, noneByRight, someByRightAsync\n","noneByRightAsync.factory":"\nnoneByRightAsync.factory( [options,] predicate )\n    Returns a function which tests whether all elements in a collection fail a\n    test implemented by a predicate function, iterating from right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = noneByRightAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    true\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    true\n\n    See Also\n    --------\n    anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByAsync, noneByRight, someByRightAsync","noneInBy":"\nnoneInBy( object, predicate[, thisArg ] )\n    Tests whether every property in an object fails a test implemented by a\n    predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: object value.\n    - key: object key.\n    - object: the input object.\n\n    The function immediately returns upon encountering a truthy return value.\n\n    If provided an empty object, the function returns `true`.\n\n    Parameters\n    ----------\n    object: Object\n        Input object over which to iterate.\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns a falsy\n        value for all properties; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function negative( v ) { return ( v < 0 ); };\n    > var obj = { 'a': 1, 'b': 2, 'c': 4 };\n    > var bool = noneInBy( obj, negative )\n    true\n\n    See Also\n    --------\n    anyInBy, everyInBy, forIn, noneBy, someInBy\n","nonEnumerableProperties":"\nnonEnumerableProperties( value )\n    Returns an array of an object's own non-enumerable property names and\n    symbols.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    props: Array\n        List of an object's own non-enumerable properties.\n\n    Examples\n    --------\n    > var obj = {};\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.writable = false;\n    > desc.value = 'boop';\n    > defineProperty( obj, 'beep', desc );\n    > var props = nonEnumerableProperties( obj )\n    [ 'beep' ]\n\n    See Also\n    --------\n    enumerableProperties, inheritedNonEnumerableProperties, nonEnumerablePropertiesIn, properties\n","nonEnumerablePropertiesIn":"\nnonEnumerablePropertiesIn( value )\n    Returns an array of an object's own and inherited non-enumerable property\n    names and symbols.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    props: Array\n        List of an object's own and inherited non-enumerable property names and\n        symbols.\n\n    Examples\n    --------\n    > var props = nonEnumerablePropertiesIn( [] )\n\n    See Also\n    --------\n    enumerablePropertiesIn, inheritedNonEnumerableProperties, nonEnumerableProperties, propertiesIn\n","nonEnumerablePropertyNames":"\nnonEnumerablePropertyNames( value )\n    Returns an array of an object's own non-enumerable property names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's own non-enumerable property names.\n\n    Examples\n    --------\n    > var obj = {};\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.writable = true;\n    > desc.value = 'boop';\n    > defineProperty( obj, 'beep', desc );\n    > var keys = nonEnumerablePropertyNames( obj )\n    e.g., [ 'beep', ... ]\n\n    See Also\n    --------\n    objectKeys, inheritedNonEnumerablePropertyNames, nonEnumerablePropertyNamesIn, nonEnumerablePropertySymbols, propertyNames\n","nonEnumerablePropertyNamesIn":"\nnonEnumerablePropertyNamesIn( value )\n    Returns an array of an object's own and inherited non-enumerable property\n    names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's own and inherited non-enumerable property names.\n\n    Examples\n    --------\n    > var obj = {};\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.writable = true;\n    > desc.value = 'boop';\n    > defineProperty( obj, 'beep', desc );\n    > var keys = nonEnumerablePropertyNamesIn( obj )\n    e.g., [ 'beep', ... ]\n\n    See Also\n    --------\n    keysIn, inheritedNonEnumerablePropertyNames, nonEnumerablePropertyNames, propertyNamesIn\n","nonEnumerablePropertySymbols":"\nnonEnumerablePropertySymbols( value )\n    Returns an array of an object's own non-enumerable symbol properties.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's own non-enumerable symbol properties.\n\n    Examples\n    --------\n    > var obj = {};\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.writable = true;\n    > desc.value = 'boop';\n    > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n    > defineProperty( obj, sym, desc );\n    > var symbols = nonEnumerablePropertySymbols( obj )\n\n    See Also\n    --------\n    enumerablePropertySymbols, inheritedNonEnumerablePropertySymbols, nonEnumerablePropertyNames, nonEnumerablePropertySymbolsIn, propertySymbols\n","nonEnumerablePropertySymbolsIn":"\nnonEnumerablePropertySymbolsIn( value )\n    Returns an array of an object's own and inherited non-enumerable symbol\n    properties.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's own and inherited non-enumerable symbol properties.\n\n    Examples\n    --------\n    > var obj = {};\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.writable = true;\n    > desc.value = 'boop';\n    > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n    > defineProperty( obj, sym, desc );\n    > var symbols = nonEnumerablePropertySymbolsIn( obj )\n\n    See Also\n    --------\n    enumerablePropertySymbolsIn, inheritedNonEnumerablePropertySymbols, nonEnumerablePropertyNamesIn, nonEnumerablePropertySymbols, propertySymbolsIn\n","noneOwnBy":"\nnoneOwnBy( object, predicate[, thisArg ] )\n    Tests whether every own property of an object fails a test implemented\n    by a predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: property value.\n    - index: property key.\n    - object: the input object.\n\n    The function immediately returns upon encountering a truthy return value.\n\n    If provided an empty object, the function returns `true`.\n\n    Parameters\n    ----------\n    object: Object\n        Input object.\n\n    predicate: Function\n        Test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if the predicate function returns a falsy\n        value for all own properties; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function isUnderage( v ) { return ( v < 18 ); };\n    > var obj = { 'a': 11, 'b': 12, 'c': 22 };\n    > var bool = noneOwnBy( obj, isUnderage )\n    false\n\n    See Also\n    --------\n    anyOwnBy, everyOwnBy, forOwn, noneBy, someOwnBy\n","nonIndexKeys":"\nnonIndexKeys( obj )\n    Returns an array of an object's own enumerable property names which are not\n    integer indices.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    obj: any\n        Input value.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's own enumerable property names.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; this[0] = 3.14; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var keys = nonIndexKeys( obj )\n    e.g., [ 'beep' ]\n\n    See Also\n    --------\n    objectEntries, objectKeys, objectValues\n","noop":"\nnoop()\n    A function which does nothing.\n\n    Examples\n    --------\n    > noop();\n\n","now":"\nnow()\n    Returns the time in seconds since the epoch.\n\n    The Unix epoch is 00:00:00 UTC on 1 January 1970.\n\n    Returns\n    -------\n    out: integer\n        Time in seconds since the epoch.\n\n    Examples\n    --------\n    > var ts = now()\n    <number>\n\n","NUM_CPUS":"\nNUM_CPUS\n    Number of CPUs.\n\n    In browser environments, the number of CPUs is determined by querying the\n    hardware concurrency API.\n\n    In Node.js environments, the number of CPUs is determined via the `os`\n    module.\n\n    Examples\n    --------\n    > NUM_CPUS\n    <number>\n\n","num2words":"\nnum2words( value[, options] )\n    Converts a number to a word representation.\n\n    Parameters\n    ----------\n    value: integer\n        Input value.\n\n    options: Object (optional)\n        Options.\n\n    options.lang: string (optional)\n        Language code. Supported languages:\n\n        - en: English.\n        - de: German.\n\n        Default: `'en'`.\n\n    Returns\n    -------\n    out: string\n        Word representation of number.\n\n    Examples\n    --------\n    > var out = num2words( 123 )\n    'one hundred twenty-three'\n\n    > out = num2words( 16.31 )\n    'sixteen point three one'\n\n    > out = num2words( 123, { 'lang': 'de' } )\n    'einhundertdreiundzwanzig'\n\n","Number":"\nNumber( value )\n    Returns a Number object.\n\n    This constructor should be used sparingly. Always prefer number primitives.\n\n    Parameters\n    ----------\n    value: number\n        Value to wrap in a Number object.\n\n    Returns\n    -------\n    out: Number\n        Number object.\n\n    Examples\n    --------\n    > var v = new Number( 5 )\n    <Number>\n\n","numel":"\nnumel( x )\n    Returns the number of elements in an ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    Returns\n    -------\n    n: integer\n        Number of elements.\n\n    Examples\n    --------\n    > var n = numel( ndzeros( [ 3, 3, 3 ] ) )\n    27\n\n    See Also\n    --------\n    array, ndarray, numelDimension\n","numelDimension":"\nnumelDimension( x, dim )\n    Returns the size (i.e., number of elements) of a specified dimension for a\n    provided ndarray.\n\n    Parameters\n    ----------\n    x: ndarray\n        Input ndarray.\n\n    dim: integer\n        Dimension index. If less than zero, the index is resolved relative to\n        the last dimension, with the last dimension corresponding to the value\n        `-1`.\n\n    Returns\n    -------\n    out: integer\n        Dimension size.\n\n    Examples\n    --------\n    > var out = numelDimension( ndzeros( [ 4, 2, 3 ] ), 0 )\n    4\n\n    See Also\n    --------\n    array, ndarray, numel\n","numGraphemeClusters":"\nnumGraphemeClusters( str )\n    Returns the number of grapheme clusters in a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Number of grapheme clusters.\n\n    Examples\n    --------\n    > var out = numGraphemeClusters( 'beep' )\n    4\n    > out = numGraphemeClusters( '🌷' )\n    1\n\n    See Also\n    --------\n    nextGraphemeClusterBreak\n","Object":"\nObject( value )\n    Returns an object.\n\n    If provided `null` or `undefined`, the function returns an empty object.\n\n    If provided an existing object, the function returns the input value\n    unchanged.\n\n    Otherwise, if provided any other value (e.g., a number, string, etc), the\n    function will return an object of the corresponding type.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    out: Object\n        Output object.\n\n    Examples\n    --------\n    > var o = new Object( null )\n    {}\n    > o = new Object( 5.0 )\n    <Number>\n    > o = new Object( 'beep' )\n    <String>\n\nObject.assign( target, ...sources )\n    Assigns enumerable and own properties from source objects to a target\n    object.\n\n    Parameters\n    ----------\n    target: Object\n        Target object.\n\n    sources: ...Object\n        Source objects.\n\n    Returns\n    -------\n    out: Object\n        Target object.\n\n    Examples\n    --------\n    > var o = Object.assign( {}, { 'a': 1 }, { 'b': 2 } )\n    { 'a': 1, 'b': 2 }\n\nObject.create( prototype, properties )\n    Creates a new object with a specified prototype object and properties.\n\n    Parameters\n    ----------\n    prototype: Object\n        Prototype object.\n\n    properties: Object\n        Properties object.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > var o = Object.create( {}, { 'a': { 'value': 1 } } )\n    { 'a': 1 }\n\nObject.defineProperties( obj, properties )\n    Defines properties for an object.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    properties: Object\n        Properties object.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.defineProperties( {}, { 'a': { 'value': 1 } } )\n    { 'a': 1 }\n\nObject.defineProperty( obj, key, descriptor )\n    Defines a property for an object.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    key: string\n        Property key.\n\n    descriptor: Object\n        Property descriptor.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.defineProperty( {}, 'a', {\n        'value': 1,\n        'enumerable': true,\n        'configurable': true,\n        'writable': false\n    })\n    { 'a': 1 }\n\nObject.entries( obj )\n    Returns an array of an object's own enumerable string-keyed property\n    [key, value] pairs.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Array\n        Array of [key, value] pairs.\n\n    Examples\n    --------\n    > var o = Object.entries( { 'a': 1, 'b': 2 } )\n    [ [ 'a', 1 ], [ 'b', 2 ] ]\n\nObject.freeze( obj )\n    Freezes an object.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.freeze( { 'a': 1 } )\n    { 'a': 1 }\n\nObject.getOwnPropertyDescriptor( obj, key )\n    Returns an object's own property descriptor.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    key: string\n        Property key.\n\n    Returns\n    -------\n    out: Object\n        Property descriptor.\n\n    Examples\n    --------\n    > var o = Object.getOwnPropertyDescriptor( { 'a': 1 }, 'a' )\n    { 'value': 1, 'enumerable': true, 'configurable': true, 'writable': true }\n\nObject.getOwnPropertyDescriptors( obj )\n    Returns an object's own property descriptors.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Object\n        Property descriptors.\n\n    Examples\n    --------\n    > var o = Object.getOwnPropertyDescriptors( { 'a': 1, 'b': 2 } )\n    {\n        'a': {\n            'value': 1,\n            'enumerable': true,\n            'configurable': true,\n            'writable': true\n        },\n        'b': {\n            'value': 2,\n            'enumerable': true,\n            'configurable': true,\n            'writable': true\n        }\n    }\n\nObject.getOwnPropertyNames( obj )\n    Returns an array of an object's own enumerable and non-enumerable\n    property names.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Array\n        Array of property names.\n\n    Examples\n    --------\n    > var o = Object.getOwnPropertyNames( { 'a': 1, 'b': 2 } )\n    [ 'a', 'b' ]\n\nObject.getOwnPropertySymbols( obj )\n    Returns an array of an object's own enumerable and non-enumerable\n    symbol property names.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Array\n        Array of symbol property names.\n\n    Examples\n    --------\n    > var o = Object.getOwnPropertySymbols( { 'a': 1, 'b': 2 } )\n    []\n\nObject.getPrototypeOf( obj )\n    Returns an object's prototype.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Object\n        Prototype.\n\n    Examples\n    --------\n    > var o = Object.getPrototypeOf( { 'a': 1, 'b': 2 } )\n    <Object>\n\nObject.hasOwn( obj, p )\n    Returns a boolean indicating whether an object has a property with the\n    specified name.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    p: string\n        Property name.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object has a property with the specified\n        name.\n\n    Examples\n    --------\n    > var o = Object.hasOwn( { 'a': 1, 'b': 2 }, 'a' )\n    true\n\nObject.is( value1, value2 )\n    Returns a boolean indicating whether two values are the same value.\n\n    Parameters\n    ----------\n    value1: any\n        First value.\n\n    value2: any\n        Second value.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether two values are the same value.\n\n    Examples\n    --------\n    > var o = Object.is( 1, 1 )\n    true\n    > var o = Object.is( 1, '1' )\n    false\n\nObject.isExtensible( obj )\n    Returns a boolean indicating whether an object is extensible.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object is extensible.\n\n    Examples\n    --------\n    > var o = Object.isExtensible( { 'a': 1 } )\n    true\n\nObject.isFrozen( obj )\n    Returns a boolean indicating whether an object is frozen.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object is frozen.\n\n    Examples\n    --------\n    > var o = Object.isFrozen( { 'a': 1 } )\n    false\n    > var o = Object.isFrozen( Object.freeze( { 'a': 1 } ) )\n    true\n\nObject.isSealed( obj )\n    Returns a boolean indicating whether an object is sealed.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object is sealed.\n\n    Examples\n    --------\n    > var o = Object.isSealed( { 'a': 1 } )\n    false\n    > var o = Object.isSealed( Object.seal( { 'a': 1 } ) )\n    true\n\nObject.keys( obj )\n    Returns an array of an object's own enumerable string-keyed property\n    names.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Array\n        Array of property names.\n\n    Examples\n    --------\n    > var o = Object.keys( { 'a': 1, 'b': 2 } )\n    [ 'a', 'b' ]\n\nObject.preventExtensions( obj )\n    Prevents the addition of new properties to an object.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.preventExtensions( { 'a': 1 } )\n    { 'a': 1 }\n    > o.b = 2;\n    > o\n    { 'a': 1 }\n\nObject.seal( obj )\n    Prevents the addition of new properties to an object and marks all\n    existing properties as non-configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.seal( { 'a': 1 } )\n    { 'a': 1 }\n    > o.b = 2;\n    > o\n    { 'a': 1 }\n    > delete o.a;\n    > o\n    { 'a': 1 }\n\nObject.setPrototypeOf( obj, proto )\n    Sets an object's prototype.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    proto: Object\n        Prototype.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.setPrototypeOf( { 'a': 1 }, { 'b': 2 } )\n    { 'a': 1 }\n    > o.b\n    2\n\nObject.values( obj )\n    Returns an array of an object's own enumerable property values.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Array\n        Array of property values.\n\n    Examples\n    --------\n    > var o = Object.values( { 'a': 1, 'b': 2 } )\n    [ 1, 2 ]\n\nObject.prototype.toLocaleString()\n    Returns a string representing the object.\n\n    Returns\n    -------\n    out: string\n        String representing the object.\n\n    Examples\n    --------\n    > var o = Object.prototype.toLocaleString.call( { 'a': 1, 'b': 2 } )\n    <string>\n\nObject.prototype.toString()\n    Returns a string representing the object.\n\n    Returns\n    -------\n    out: string\n        String representing the object.\n\n    Examples\n    --------\n    > var o = Object.prototype.toString.call( { 'a': 1, 'b': 2 } )\n    <string>\n\nObject.prototype.valueOf()\n    Returns the primitive value of the object.\n\n    Returns\n    -------\n    out: any\n        Primitive value of the object.\n\n    Examples\n    --------\n    > var o = Object.prototype.valueOf.call( { 'a': 1, 'b': 2 } )\n    {}\n\nObject.prototype.hasOwnProperty( p )\n    Returns a boolean indicating whether an object has a property with the\n    specified name.\n\n    Parameters\n    ----------\n    p: string\n        Property name.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object has a property with the specified\n        name.\n\n    Examples\n    --------\n    > var o = Object.prototype.hasOwnProperty.call( { 'a': 1, 'b': 2 }, 'a' )\n    true\n\nObject.prototype.isPrototypeOf( obj )\n    Returns a boolean indicating whether an object exists in another object's\n    prototype chain.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object exists in another object's\n        prototype chain.\n\n    Examples\n    --------\n    > var p = { 'a': 1 };\n    > var o = { '__proto__': p };\n    > var b = o.isPrototypeOf( p );\n    true\n\nObject.prototype.propertyIsEnumerable( p )\n    Returns a boolean indicating whether an object's property is enumerable.\n\n    Parameters\n    ----------\n    p: string\n        Property name.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object's property is enumerable.\n\n    Examples\n    --------\n    > var o = { 'a': 1, 'b': 2 };\n    > var bool = Object.prototype.propertyIsEnumerable.call( o, 'a' )\n    true\n\nObject.prototype.constructor\n    Property whose value is a reference to the constructor function that\n    created the instance object.\n\n    Examples\n    --------\n    > var o = new Object( null );\n    > var ctr = o.constructor;\n    <Object>\n\n","Object.assign":"\nObject.assign( target, ...sources )\n    Assigns enumerable and own properties from source objects to a target\n    object.\n\n    Parameters\n    ----------\n    target: Object\n        Target object.\n\n    sources: ...Object\n        Source objects.\n\n    Returns\n    -------\n    out: Object\n        Target object.\n\n    Examples\n    --------\n    > var o = Object.assign( {}, { 'a': 1 }, { 'b': 2 } )\n    { 'a': 1, 'b': 2 }","Object.create":"\nObject.create( prototype, properties )\n    Creates a new object with a specified prototype object and properties.\n\n    Parameters\n    ----------\n    prototype: Object\n        Prototype object.\n\n    properties: Object\n        Properties object.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > var o = Object.create( {}, { 'a': { 'value': 1 } } )\n    { 'a': 1 }","Object.defineProperties":"\nObject.defineProperties( obj, properties )\n    Defines properties for an object.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    properties: Object\n        Properties object.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.defineProperties( {}, { 'a': { 'value': 1 } } )\n    { 'a': 1 }","Object.defineProperty":"\nObject.defineProperty( obj, key, descriptor )\n    Defines a property for an object.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    key: string\n        Property key.\n\n    descriptor: Object\n        Property descriptor.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.defineProperty( {}, 'a', {\n        'value': 1,\n        'enumerable': true,\n        'configurable': true,\n        'writable': false\n    })\n    { 'a': 1 }","Object.entries":"\nObject.entries( obj )\n    Returns an array of an object's own enumerable string-keyed property\n    [key, value] pairs.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Array\n        Array of [key, value] pairs.\n\n    Examples\n    --------\n    > var o = Object.entries( { 'a': 1, 'b': 2 } )\n    [ [ 'a', 1 ], [ 'b', 2 ] ]","Object.freeze":"\nObject.freeze( obj )\n    Freezes an object.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.freeze( { 'a': 1 } )\n    { 'a': 1 }","Object.getOwnPropertyDescriptor":"\nObject.getOwnPropertyDescriptor( obj, key )\n    Returns an object's own property descriptor.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    key: string\n        Property key.\n\n    Returns\n    -------\n    out: Object\n        Property descriptor.\n\n    Examples\n    --------\n    > var o = Object.getOwnPropertyDescriptor( { 'a': 1 }, 'a' )\n    { 'value': 1, 'enumerable': true, 'configurable': true, 'writable': true }","Object.getOwnPropertyDescriptors":"\nObject.getOwnPropertyDescriptors( obj )\n    Returns an object's own property descriptors.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Object\n        Property descriptors.\n\n    Examples\n    --------\n    > var o = Object.getOwnPropertyDescriptors( { 'a': 1, 'b': 2 } )\n    {\n        'a': {\n            'value': 1,\n            'enumerable': true,\n            'configurable': true,\n            'writable': true\n        },\n        'b': {\n            'value': 2,\n            'enumerable': true,\n            'configurable': true,\n            'writable': true\n        }\n    }","Object.getOwnPropertyNames":"\nObject.getOwnPropertyNames( obj )\n    Returns an array of an object's own enumerable and non-enumerable\n    property names.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Array\n        Array of property names.\n\n    Examples\n    --------\n    > var o = Object.getOwnPropertyNames( { 'a': 1, 'b': 2 } )\n    [ 'a', 'b' ]","Object.getOwnPropertySymbols":"\nObject.getOwnPropertySymbols( obj )\n    Returns an array of an object's own enumerable and non-enumerable\n    symbol property names.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Array\n        Array of symbol property names.\n\n    Examples\n    --------\n    > var o = Object.getOwnPropertySymbols( { 'a': 1, 'b': 2 } )\n    []","Object.getPrototypeOf":"\nObject.getPrototypeOf( obj )\n    Returns an object's prototype.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Object\n        Prototype.\n\n    Examples\n    --------\n    > var o = Object.getPrototypeOf( { 'a': 1, 'b': 2 } )\n    <Object>","Object.hasOwn":"\nObject.hasOwn( obj, p )\n    Returns a boolean indicating whether an object has a property with the\n    specified name.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    p: string\n        Property name.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object has a property with the specified\n        name.\n\n    Examples\n    --------\n    > var o = Object.hasOwn( { 'a': 1, 'b': 2 }, 'a' )\n    true","Object.is":"\nObject.is( value1, value2 )\n    Returns a boolean indicating whether two values are the same value.\n\n    Parameters\n    ----------\n    value1: any\n        First value.\n\n    value2: any\n        Second value.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether two values are the same value.\n\n    Examples\n    --------\n    > var o = Object.is( 1, 1 )\n    true\n    > var o = Object.is( 1, '1' )\n    false","Object.isExtensible":"\nObject.isExtensible( obj )\n    Returns a boolean indicating whether an object is extensible.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object is extensible.\n\n    Examples\n    --------\n    > var o = Object.isExtensible( { 'a': 1 } )\n    true","Object.isFrozen":"\nObject.isFrozen( obj )\n    Returns a boolean indicating whether an object is frozen.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object is frozen.\n\n    Examples\n    --------\n    > var o = Object.isFrozen( { 'a': 1 } )\n    false\n    > var o = Object.isFrozen( Object.freeze( { 'a': 1 } ) )\n    true","Object.isSealed":"\nObject.isSealed( obj )\n    Returns a boolean indicating whether an object is sealed.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object is sealed.\n\n    Examples\n    --------\n    > var o = Object.isSealed( { 'a': 1 } )\n    false\n    > var o = Object.isSealed( Object.seal( { 'a': 1 } ) )\n    true","Object.keys":"\nObject.keys( obj )\n    Returns an array of an object's own enumerable string-keyed property\n    names.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Array\n        Array of property names.\n\n    Examples\n    --------\n    > var o = Object.keys( { 'a': 1, 'b': 2 } )\n    [ 'a', 'b' ]","Object.preventExtensions":"\nObject.preventExtensions( obj )\n    Prevents the addition of new properties to an object.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.preventExtensions( { 'a': 1 } )\n    { 'a': 1 }\n    > o.b = 2;\n    > o\n    { 'a': 1 }","Object.seal":"\nObject.seal( obj )\n    Prevents the addition of new properties to an object and marks all\n    existing properties as non-configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.seal( { 'a': 1 } )\n    { 'a': 1 }\n    > o.b = 2;\n    > o\n    { 'a': 1 }\n    > delete o.a;\n    > o\n    { 'a': 1 }","Object.setPrototypeOf":"\nObject.setPrototypeOf( obj, proto )\n    Sets an object's prototype.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    proto: Object\n        Prototype.\n\n    Returns\n    -------\n    out: Object\n        Object.\n\n    Examples\n    --------\n    > var o = Object.setPrototypeOf( { 'a': 1 }, { 'b': 2 } )\n    { 'a': 1 }\n    > o.b\n    2","Object.values":"\nObject.values( obj )\n    Returns an array of an object's own enumerable property values.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: Array\n        Array of property values.\n\n    Examples\n    --------\n    > var o = Object.values( { 'a': 1, 'b': 2 } )\n    [ 1, 2 ]","Object.prototype.toLocaleString":"\nObject.prototype.toLocaleString()\n    Returns a string representing the object.\n\n    Returns\n    -------\n    out: string\n        String representing the object.\n\n    Examples\n    --------\n    > var o = Object.prototype.toLocaleString.call( { 'a': 1, 'b': 2 } )\n    <string>","Object.prototype.toString":"\nObject.prototype.toString()\n    Returns a string representing the object.\n\n    Returns\n    -------\n    out: string\n        String representing the object.\n\n    Examples\n    --------\n    > var o = Object.prototype.toString.call( { 'a': 1, 'b': 2 } )\n    <string>","Object.prototype.valueOf":"\nObject.prototype.valueOf()\n    Returns the primitive value of the object.\n\n    Returns\n    -------\n    out: any\n        Primitive value of the object.\n\n    Examples\n    --------\n    > var o = Object.prototype.valueOf.call( { 'a': 1, 'b': 2 } )\n    {}","Object.prototype.hasOwnProperty":"\nObject.prototype.hasOwnProperty( p )\n    Returns a boolean indicating whether an object has a property with the\n    specified name.\n\n    Parameters\n    ----------\n    p: string\n        Property name.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object has a property with the specified\n        name.\n\n    Examples\n    --------\n    > var o = Object.prototype.hasOwnProperty.call( { 'a': 1, 'b': 2 }, 'a' )\n    true","Object.prototype.isPrototypeOf":"\nObject.prototype.isPrototypeOf( obj )\n    Returns a boolean indicating whether an object exists in another object's\n    prototype chain.\n\n    Parameters\n    ----------\n    obj: Object\n        Object.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object exists in another object's\n        prototype chain.\n\n    Examples\n    --------\n    > var p = { 'a': 1 };\n    > var o = { '__proto__': p };\n    > var b = o.isPrototypeOf( p );\n    true","Object.prototype.propertyIsEnumerable":"\nObject.prototype.propertyIsEnumerable( p )\n    Returns a boolean indicating whether an object's property is enumerable.\n\n    Parameters\n    ----------\n    p: string\n        Property name.\n\n    Returns\n    -------\n    out: boolean\n        Boolean indicating whether an object's property is enumerable.\n\n    Examples\n    --------\n    > var o = { 'a': 1, 'b': 2 };\n    > var bool = Object.prototype.propertyIsEnumerable.call( o, 'a' )\n    true","Object.prototype.constructor":"\nObject.prototype.constructor\n    Property whose value is a reference to the constructor function that\n    created the instance object.\n\n    Examples\n    --------\n    > var o = new Object( null );\n    > var ctr = o.constructor;\n    <Object>","objectEntries":"\nobjectEntries( obj )\n    Returns an array of an object's own enumerable property `[key, value]`\n    pairs.\n\n    Entry order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic return values.\n\n    Parameters\n    ----------\n    obj: ObjectLike\n        Input object.\n\n    Returns\n    -------\n    arr: Array\n        Array containing key-value pairs.\n\n    Examples\n    --------\n    > var obj = { 'beep': 'boop', 'foo': 'bar' };\n    > var entries = objectEntries( obj )\n    e.g., [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ]\n\n    See Also\n    --------\n    objectEntriesIn, objectFromEntries, objectKeys, objectValues\n","objectEntriesIn":"\nobjectEntriesIn( obj )\n    Returns an array of an object's own and inherited enumerable property\n    `[key, value]` pairs.\n\n    Entry order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic return values.\n\n    Parameters\n    ----------\n    obj: ObjectLike\n        Input object.\n\n    Returns\n    -------\n    arr: Array\n        Array containing key-value pairs.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var entries = objectEntriesIn( obj )\n    e.g., [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ]\n\n    See Also\n    --------\n    objectEntries, objectFromEntries, keysIn, objectValuesIn\n","objectFromEntries":"\nobjectFromEntries( entries )\n    Creates an object from an array of key-value pairs.\n\n    Parameters\n    ----------\n    entries: Array<Array>\n        Input object.\n\n    Returns\n    -------\n    out: Object\n        Object created from `[key, value]` pairs.\n\n    Examples\n    --------\n    > var entries = [ [ 'beep', 'boop' ], [ 'foo', 'bar' ] ];\n    > var obj = objectFromEntries( entries )\n    { 'beep': 'boop', 'foo': 'bar' }\n\n    See Also\n    --------\n    objectEntries\n","objectInverse":"\nobjectInverse( obj[, options] )\n    Inverts an object, such that keys become values and values become keys.\n\n    Beware when providing objects having values which are themselves objects.\n    The function relies on native object serialization (`#toString`) when\n    converting values to keys.\n\n    Insertion order is not guaranteed, as object key enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's keys, thus allowing for\n    deterministic inversion.\n\n    Parameters\n    ----------\n    obj: ObjectLike\n        Input object.\n\n    options: Object (optional)\n        Options.\n\n    options.duplicates: boolean (optional)\n        Boolean indicating whether to store keys mapped to duplicate values in\n        arrays. Default: `true`.\n\n    Returns\n    -------\n    out: Object\n        Inverted object.\n\n    Examples\n    --------\n    // Basic usage:\n    > var obj = { 'a': 'beep', 'b': 'boop' };\n    > var out = objectInverse( obj )\n    { 'beep': 'a', 'boop': 'b' }\n\n    // Duplicate values:\n    > obj = { 'a': 'beep', 'b': 'beep' };\n    > out = objectInverse( obj )\n    { 'beep': [ 'a', 'b' ] }\n\n    // Override duplicate values:\n    > obj = {};\n    > obj.a = 'beep';\n    > obj.b = 'boop';\n    > obj.c = 'beep';\n    > out = objectInverse( obj, { 'duplicates': false } )\n    { 'beep': 'c', 'boop': 'b' }\n\n    See Also\n    --------\n    objectInverseBy\n","objectInverseBy":"\nobjectInverseBy( obj, [options,] transform )\n    Inverts an object, such that keys become values and values become keys,\n    according to a transform function.\n\n    The transform function is provided three arguments:\n\n    - key: object key.\n    - value: object value corresponding to `key`.\n    - obj: the input object.\n\n    The value returned by a transform function should be a value which can be\n    serialized as an object key. Hence, beware when providing objects having\n    values which are themselves objects. The function relies on native object\n    serialization (`#toString`) when converting transform function return values\n    to keys.\n\n    Insertion order is not guaranteed, as object key enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's keys, thus allowing for\n    deterministic inversion.\n\n    Parameters\n    ----------\n    obj: ObjectLike\n        Input object.\n\n    options: Object (optional)\n        Options.\n\n    options.duplicates: boolean (optional)\n        Boolean indicating whether to store keys mapped to duplicate values in\n        arrays. Default: `true`.\n\n    transform: Function\n        Transform function.\n\n    Returns\n    -------\n    out: Object\n        Inverted object.\n\n    Examples\n    --------\n    // Basic usage:\n    > function transform( key, value ) { return key + value; };\n    > var obj = { 'a': 'beep', 'b': 'boop' };\n    > var out = objectInverseBy( obj, transform )\n    { 'abeep': 'a', 'bboop': 'b' }\n\n    // Duplicate values:\n    > function transform( key, value ) { return value; };\n    > obj = { 'a': 'beep', 'b': 'beep' };\n    > out = objectInverseBy( obj, transform )\n    { 'beep': [ 'a', 'b' ] }\n\n    // Override duplicate values:\n    > obj = {};\n    > obj.a = 'beep';\n    > obj.b = 'boop';\n    > obj.c = 'beep';\n    > out = objectInverseBy( obj, { 'duplicates': false }, transform )\n    { 'beep': 'c', 'boop': 'b' }\n\n    See Also\n    --------\n    objectInverse\n","objectKeys":"\nobjectKeys( value )\n    Returns an array of an object's own enumerable property names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's own enumerable property names.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var keys = objectKeys( obj )\n    [ 'beep' ]\n\n    See Also\n    --------\n    objectEntries, keysIn, nonIndexKeys, objectValues\n","objectValues":"\nobjectValues( obj )\n    Returns an array of an object's own enumerable property values.\n\n    Value order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    Parameters\n    ----------\n    obj: ObjectLike\n        Input object.\n\n    Returns\n    -------\n    values: Array\n        Value array.\n\n    Examples\n    --------\n    > var obj = { 'beep': 'boop', 'foo': 'bar' };\n    > var vals = objectValues( obj )\n    e.g., [ 'boop', 'bar' ]\n\n    See Also\n    --------\n    objectEntries, objectKeys\n","objectValuesIn":"\nobjectValuesIn( obj )\n    Returns an array of an object's own and inherited enumerable property\n    values.\n\n    Value order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    Parameters\n    ----------\n    obj: ObjectLike\n        Input object.\n\n    Returns\n    -------\n    values: Array\n        Value array.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var values = objectValuesIn( obj )\n    e.g., [ 'boop', 'bar' ]\n\n    See Also\n    --------\n    objectEntriesIn, keysIn, objectValues\n","omit":"\nomit( obj, keys )\n    Returns a partial object copy excluding specified keys.\n\n    The function returns a shallow copy.\n\n    The function ignores non-existent keys.\n\n    The function only copies own properties. Hence, the function never copies\n    inherited properties.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    keys: string|Array<string>\n        Keys to exclude.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > var obj1 = { 'a': 1, 'b': 2 };\n    > var obj2 = omit( obj1, 'b' )\n    { 'a': 1 }\n\n    See Also\n    --------\n    omitBy\n","omitBy":"\nomitBy( obj, predicate )\n    Returns a partial object copy excluding properties for which a predicate\n    returns a truthy value.\n\n    The function returns a shallow copy.\n\n    The function only copies own properties. Hence, the function never copies\n    inherited properties.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    predicate: Function\n        Predicate function.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > function predicate( key, value ) { return ( value > 1 ); };\n    > var obj1 = { 'a': 1, 'b': 2 };\n    > var obj2 = omitBy( obj1, predicate )\n    { 'a': 1 }\n\n    See Also\n    --------\n    omit\n","open":"\nopen( path[, flags[, mode]], clbk )\n    Asynchronously opens a file.\n\n    Some characters, such as <>:\"/\\|?*, are reserved under Windows.\n    Under NTFS, if the path contains a colon, Node.js will open a file system\n    stream.\n\n    Parameters\n    ----------\n    path: string|Buffer\n        Filename.\n\n    flags: string|number (optional)\n        File system flags. Default: 'r'.\n\n    mode: integer (optional)\n        File mode (permission and sticky bits). This sets the file mode, but\n        only if the file was created. On Windows, only the write permission can\n        be manipulated. Default: 0o666.\n\n    clbk: Function\n        Callback to invoke upon opening a file.\n\n    Examples\n    --------\n    > function onOpen( error, fd ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     } else {\n    ...         close.sync( fd );\n    ...     }\n    ... };\n    > open( './beep/boop.txt', onOpen );\n\n\nopen.sync( path[, flags[, mode]] )\n    Synchronously opens a file.\n\n    Parameters\n    ----------\n    path: string|Buffer\n        Filename.\n\n    flags: string|number (optional)\n        File system flags. Default: 'r'.\n\n    mode: integer (optional)\n        File mode (permission and sticky bits).  This sets the file mode, but\n        only if the file was created. On Windows, only the write permission can\n        be manipulated. Default: 0o666.\n\n    Returns\n    -------\n    fd: Error|integer\n        File descriptor.\n\n    Examples\n    --------\n    > var fd = open.sync( './beep/boop.txt' );\n    > if ( !isError( fd ) ) { close.sync( fd ); };\n\n    See Also\n    --------\n    close, exists, readFile\n","open.sync":"\nopen.sync( path[, flags[, mode]] )\n    Synchronously opens a file.\n\n    Parameters\n    ----------\n    path: string|Buffer\n        Filename.\n\n    flags: string|number (optional)\n        File system flags. Default: 'r'.\n\n    mode: integer (optional)\n        File mode (permission and sticky bits).  This sets the file mode, but\n        only if the file was created. On Windows, only the write permission can\n        be manipulated. Default: 0o666.\n\n    Returns\n    -------\n    fd: Error|integer\n        File descriptor.\n\n    Examples\n    --------\n    > var fd = open.sync( './beep/boop.txt' );\n    > if ( !isError( fd ) ) { close.sync( fd ); };\n\n    See Also\n    --------\n    close, exists, readFile","openURL":"\nopenURL( url )\n    Opens a URL in a user's default browser.\n\n    In a non-browser environment, the function returns an unreferenced child\n    process. In a browser environment, the function returns a reference to a\n    `window` object.\n\n    Parameters\n    ----------\n    url: string\n        URL to open.\n\n    Returns\n    -------\n    out: process|Window\n        Child process or `window` object.\n\n    Examples\n    --------\n    > var out = openURL( 'https://google.com' );\n\n","ordinalize":"\nordinalize( value[, options] )\n    Converts an integer to an ordinal string (e.g., `1st`, `2nd`, etc.).\n\n    Parameters\n    ----------\n    value: string|integer\n        Input value.\n\n    options: Object (optional)\n        Options.\n\n    options.lang: string (optional)\n        Language code. Supported languages:\n\n        - en: English.\n        - es: Spanish.\n        - fin: Finnish.\n        - fr: French.\n        - de: Dutch.\n        - it: Italian.\n        - pt: Portuguese.\n        - swe: Swedish.\n\n        Default: `'en'`.\n\n    options.suffixOnly: boolean (optional)\n        Boolean indicating whether to return only the suffix. Default: `false`.\n\n    options.gender: string (optional)\n       Grammatical gender (used if applicable); must be either 'masculine' or\n       'feminine'. Default: `'masculine'`.\n\n    Returns\n    -------\n    out: string\n        Ordinal string or suffix.\n\n    Examples\n    --------\n    > var out = ordinalize( '1' )\n    '1st'\n    > out = ordinalize( 2, { 'suffixOnly': true } )\n    'nd'\n    > out = ordinalize( '3', { 'lang': 'es' } )\n    '3º'\n\n","PACE_BOSTON_HOUSE_PRICES":"\nPACE_BOSTON_HOUSE_PRICES()\n    Returns a (corrected) dataset derived from information collected by the US\n    Census Service concerning housing in Boston, Massachusetts (1978).\n\n    The data consists of 21 attributes:\n\n    - obs: observation number.\n    - town: town name.\n    - town_id: town identifier.\n    - tract: tract identifier.\n    - lon: longitude.\n    - lat: latitude.\n    - medv: median value of owner-occupied homes in $1000's.\n    - cmedv: corrected median value of owner-occupied homes in $1000's.\n    - crim: per capita crime rate by town.\n    - zn: proportion of residential land zoned for lots over 25,000 square feet.\n    - indus: proportion of non-retail business acres per town.\n    - chas: Charles River dummy variable (1 if tract bounds river; 0 otherwise).\n    - nox: nitric oxides concentration (parts per 10 million).\n    - rm: average number of rooms per dwelling.\n    - age: proportion of owner-occupied units built prior to 1940.\n    - dis: weighted distances to five Boston employment centers.\n    - rad: index of accessibility to radial highways.\n    - tax: full-value property-tax rate per $10,000.\n    - ptratio: pupil-teacher ratio by town.\n    - b: 1000(Bk-0.63)^2 where Bk is the proportion of blacks by town.\n    - lstat: percent lower status of the population.\n\n    The dataset can be used to predict two dependent variables: 1) nitrous oxide\n    level and 2) median home value.\n\n    The median home value field seems to be censored at 50.00 (corresponding to\n    a median value of $50,000). Censoring is suggested by the fact that the\n    highest median value of exactly $50,000 is reported in 16 cases, while 15\n    cases have values between $40,000 and $50,000. Values are rounded to the\n    nearest hundred.\n\n    The dataset contains eight corrections to miscoded median values, as\n    documented by Gilley and Pace (1996).\n\n    The dataset augments the original dataset from Harrison and Rubinfeld (1978)\n    by including geo-referencing and spatial estimation for each observation.\n\n    Returns\n    -------\n    out: Array<Object>\n        Boston house prices.\n\n    Examples\n    --------\n    > var data = PACE_BOSTON_HOUSE_PRICES()\n    [ {...}, {...}, ... ]\n\n    References\n    ----------\n    - Harrison, David, and Daniel L Rubinfeld. 1978. \"Hedonic housing prices and\n    the demand for clean air.\" _Journal of Environmental Economics and\n    Management_ 5 (1): 81–102. doi:10.1016/0095-0696(78)90006-2.\n    - Gilley, Otis W., and R.Kelley Pace. 1996. \"On the Harrison and Rubinfeld\n    Data.\" _Journal of Environmental Economics and Management_ 31 (3): 403–5.\n    doi:10.1006/jeem.1996.0052.\n    - Pace, R. Kelley, and Otis W. Gilley. 1997. \"Using the Spatial\n    Configuration of the Data to Improve Estimation.\" _The Journal of Real\n    Estate Finance and Economics_ 14 (3): 333–40. doi:10.1023/A:1007762613901.\n\n    See Also\n    --------\n    HARRISON_BOSTON_HOUSE_PRICES, HARRISON_BOSTON_HOUSE_PRICES_CORRECTED\n","pad":"\npad( str, len[, options] )\n    Pads a `string` such that the padded `string` has length `len`.\n\n    Any padding which does not evenly divide available space is trimmed such\n    that the returned string length is always `len`.\n\n    If `len < str.length`, the input string is trimmed.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    len: integer\n        Output string length.\n\n    options: Object (optional)\n        Options.\n\n    options.lpad: string (optional)\n        String used to left pad.\n\n    options.rpad: string (optional)\n        String used to right pad.\n\n    options.centerRight: boolean (optional)\n        Boolean indicating whether to center right in the event of a tie.\n        Default: `false` (i.e., center left).\n\n    Returns\n    -------\n    out: string\n        Padded string.\n\n    Examples\n    --------\n    // Standard usage:\n    > var out = pad( 'a', 5 )\n    'a    '\n\n    // Left pad:\n    > out = pad( 'a', 10, { 'lpad': 'b' } )\n    'bbbbbbbbba'\n\n    // Right pad:\n    > out = pad( 'a', 12, { 'rpad': 'b' } )\n    'abbbbbbbbbbb'\n\n    // Center an input string:\n    > var opts = { 'lpad': 'a', 'rpad': 'c' };\n    > out = pad( 'b', 11, opts )\n    'aaaaabccccc'\n\n    // Left center:\n    > opts.centerRight = false;\n    > out = pad( 'b', 10, opts )\n    'aaaabccccc'\n\n    // Right center:\n    > opts.centerRight = true;\n    > out = pad( 'b', 10, opts )\n    'aaaaabcccc'\n\n    // Output string always length `len`:\n    > opts = { 'lpad': 'boop', 'rpad': 'woot' };\n    > out = pad( 'beep', 10, opts )\n    'boobeepwoo'\n\n    // Pad right, trim right:\n    > out = pad( 'beep', 2 )\n    'be'\n\n    // Pad left, trim left:\n    > opts = { 'lpad': 'b' };\n    > out = pad( 'beep', 2, opts )\n    'ep'\n\n    // Pad both, trim both:\n    > opts = { 'lpad': '@', 'rpad': '!' };\n    > out = pad( 'beep', 2, opts )\n    'ee'\n\n    // Pad both, trim both starting from left:\n    > out = pad( 'abcdef', 3, opts )\n    'cde'\n\n    // Pad both, trim both starting from right:\n    > opts.centerRight = true;\n    > out = pad( 'abcdef', 3, opts )\n    'bcd'\n\n    See Also\n    --------\n    lpad, rpad\n","padjust":"\npadjust( pvals, method[, comparisons] )\n    Adjusts supplied p-values for multiple comparisons via a specified method.\n\n    The `method` parameter can be one of the following values:\n\n    - bh: Benjamini-Hochberg procedure controlling the False Discovery\n    Rate (FDR).\n    - bonferroni: Bonferroni correction fixing the family-wise error rate\n    by multiplying the p-values with the number of comparisons. The Bonferroni\n    correction is usually a too conservative adjustment compared to the others.\n    - by: Procedure by Benjamini & Yekutieli for controlling the False\n    Discovery Rate (FDR) under dependence.\n    - holm: Hommel's method controlling family-wise error rate. It is\n    uniformly more powerful than the Bonferroni correction.\n    - hommel: Hommel's method, which is valid when hypothesis tests are\n    independent. It is more expensive to compute than the other methods.\n\n    By default, the number of comparisons for which the p-values should be\n    corrected is equal to the number of provided p-values. Alternatively, it is\n    possible to set `comparisons` to a number greater than the length of\n    `pvals`. In that case, the methods assume `comparisons - pvals.length`\n    unobserved p-values that are greater than all observed p-values (for Holm's\n    method and the Bonferroni correction) or equal to `1` for the remaining\n    methods.\n\n    Parameters\n    ----------\n    pvals: Array<number>\n        P-values to be adjusted.\n\n    method: string\n        Correction method.\n\n    comparisons: integer (optional)\n        Number of comparisons. Default value: `pvals.length`.\n\n    Returns\n    -------\n    out: Array<number>\n        Array containing the corrected p-values.\n\n    Examples\n    --------\n    > var pvalues = [ 0.008, 0.03, 0.123, 0.6, 0.2 ];\n    > var out = padjust( pvalues, 'bh' )\n    [ 0.04, 0.075, ~0.205, 0.6, 0.25 ]\n\n    > out = padjust( pvalues, 'bonferroni' )\n    [ 0.04, 0.15, 0.615, 1.0, 1.0 ]\n\n    > out = padjust( pvalues, 'by' )\n    [ ~0.457, ~0.856, 1.0, 1.0, 1.0 ]\n\n    > out = padjust( pvalues, 'holm' )\n    [ 0.2, 0.6, 1.0, 1.0, 1.0 ]\n\n    > out = padjust( pvalues, 'hommel' )\n    [ 0.16, 0.6, 1.0, 1.0, 1.0 ]\n\n","papply":"\npapply( fcn, ...args )\n    Returns a function of smaller arity by partially applying arguments.\n\n    The implementation does not set the `length` property of the returned\n    function. Accordingly, the returned function `length` is always zero.\n\n    The evaluation context is always `null`.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to partially apply.\n\n    args: ...any\n        Arguments to partially apply.\n\n    Returns\n    -------\n    out: Function\n        Partially applied function.\n\n    Examples\n    --------\n    > function add( x, y ) { return x + y; };\n    > var add2 = papply( add, 2 );\n    > var sum = add2( 3 )\n    5\n\n    See Also\n    --------\n    papplyRight\n","papplyRight":"\npapplyRight( fcn, ...args )\n    Returns a function of smaller arity by partially applying arguments from the\n    right.\n\n    The implementation does not set the `length` property of the returned\n    function. Accordingly, the returned function `length` is always zero.\n\n    The evaluation context is always `null`.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to partially apply.\n\n    args: ...any\n        Arguments to partially apply.\n\n    Returns\n    -------\n    out: Function\n        Partially applied function.\n\n    Examples\n    --------\n    > function say( text, name ) { return text + ', ' + name + '.'; };\n    > var toGrace = papplyRight( say, 'Grace Hopper' );\n    > var str = toGrace( 'Hello' )\n    'Hello, Grace Hopper.'\n    > str = toGrace( 'Thank you' )\n    'Thank you, Grace Hopper.'\n\n    See Also\n    --------\n    papply\n","parallel":"\nparallel( files, [options,] clbk )\n    Executes scripts in parallel.\n\n    Relative file paths are resolved relative to the current working directory.\n\n    Ordered script output does not imply that scripts are executed in order. To\n    preserve script order, execute the scripts sequentially via some other\n    means.\n\n    Parameters\n    ----------\n    files: Array<string>\n        Script file paths.\n\n    options: Object (optional)\n        Options.\n\n    options.cmd: string (optional)\n        Executable file/command. Default: `'node'`.\n\n    options.concurrency: integer (optional)\n        Number of scripts to execute concurrently. Script concurrency cannot\n        exceed the number of scripts. By specifying a concurrency greater than\n        the number of workers, a worker may be executing more than `1` script at\n        any one time. While not likely to be advantageous for synchronous\n        scripts, setting a higher concurrency may be advantageous for scripts\n        performing asynchronous tasks. If the script concurrency is less than\n        the number of workers, the number of workers is reduced to match the\n        specified concurrency. Default: `options.workers`.\n\n    options.workers: integer (optional)\n        Number of workers. Default: number of CPUs minus `1`.\n\n    options.ordered: boolean (optional)\n        Boolean indicating whether to preserve the order of script output. By\n        default, the `stdio` output for each script is interleaved; i.e., the\n        `stdio` output from one script may be interleaved with the `stdio`\n        output from one or more other scripts. To preserve the `stdio` output\n        order for each script, set the `ordered` option to `true`. Default:\n        `false`.\n\n    options.uid: integer (optional)\n        Process user identity.\n\n    options.gid: integer (optional)\n        Process group identity.\n\n    options.maxBuffer: integer (optional)\n        Max child process `stdio` buffer size. This option is only applied when\n        `options.ordered = true`. Default: `200*1024*1024`.\n\n    clbk: Function\n        Callback to invoke after executing all scripts.\n\n    Examples\n    --------\n    > function done( error ) { if ( error ) { throw error; } };\n    > var files = [ './a.js', './b.js' ];\n    > parallel( files, done );\n\n    // Specify the number of workers:\n    > var opts = { 'workers': 8 };\n    > parallel( files, opts, done );\n\n","parseJSON":"\nparseJSON( str[, reviver] )\n    Attempts to parse a string as JSON.\n\n    Function behavior differs from `JSON.parse()` as follows:\n\n    - throws a `TypeError` if provided any value which is not a string.\n    - throws a `TypeError` if provided a `reviver` argument which is not a\n      function.\n    - returns, rather than throws, a `SyntaxError` if unable to parse a string\n      as JSON.\n\n    Parameters\n    ----------\n    str: string\n        String to parse.\n\n    reviver: Function (optional)\n        Transformation function.\n\n    Returns\n    -------\n    out: any|Error\n        Parsed value or an error.\n\n    Examples\n    --------\n    > var obj = parseJSON( '{\"beep\":\"boop\"}' )\n    { 'beep': 'boop' }\n\n    // Provide a reviver:\n    > function reviver( key, value ) {\n    ...     if ( key === '' ) { return value; }\n    ...     if ( key === 'beep' ) { return value; }\n    ... };\n    > var str = '{\"beep\":\"boop\",\"a\":\"b\"}';\n    > var out = parseJSON( str, reviver )\n    { 'beep': 'boop' }\n\n","pascalcase":"\npascalcase( str )\n    Converts a string to Pascal case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Pascal-cased string.\n\n    Examples\n    --------\n    > var out = pascalcase( 'Hello World!' )\n    'HelloWorld'\n    > out = pascalcase( 'beep boop' )\n    'BeepBoop'\n\n    See Also\n    --------\n    camelcase, constantcase, kebabcase, snakecase","PATH_DELIMITER":"\nPATH_DELIMITER\n    Platform-specific path delimiter.\n\n    Examples\n    --------\n    > PATH_DELIMITER\n    <string>\n\n    // POSIX environment:\n    > var path = '/usr/bin:/bin:/usr/sbin';\n    > var parts = path.split( PATH_DELIMITER )\n    [ '/usr/bin', '/bin', '/usr/sbin' ]\n\n    // Windows environment:\n    > path = 'C:\\\\Windows\\\\system32;C:\\\\Windows';\n    > parts = path.split( PATH_DELIMITER )\n    [ 'C:\\\\Windows\\system32', 'C:\\\\Windows' ]\n\n    See Also\n    --------\n    PATH_DELIMITER_POSIX, PATH_DELIMITER_WIN32\n","PATH_DELIMITER_POSIX":"\nPATH_DELIMITER_POSIX\n    POSIX path delimiter.\n\n    Examples\n    --------\n    > PATH_DELIMITER_POSIX\n    ':'\n    > var PATH = '/usr/bin:/bin:/usr/sbin:/sbin:/usr/local/bin';\n    > var paths = PATH.split( PATH_DELIMITER_POSIX )\n    [ '/usr/bin', '/bin', '/usr/sbin', '/sbin', '/usr/local/bin' ]\n\n    See Also\n    --------\n    PATH_DELIMITER, PATH_DELIMITER_WIN32\n","PATH_DELIMITER_WIN32":"\nPATH_DELIMITER_WIN32\n    Windows path delimiter.\n\n    Examples\n    --------\n    > PATH_DELIMITER_WIN32\n    ';'\n    > var PATH = 'C:\\\\Windows\\\\system32;C:\\\\Windows;C:\\\\Program Files\\\\node\\\\';\n    > var paths = PATH.split( PATH_DELIMITER_WIN32 )\n    [ 'C:\\\\Windows\\\\system32', 'C:\\\\Windows', 'C:\\\\Program Files\\\\node\\\\' ]\n\n    See Also\n    --------\n    PATH_DELIMITER, PATH_DELIMITER_POSIX\n","PATH_SEP":"\nPATH_SEP\n    Platform-specific path segment separator.\n\n    Examples\n    --------\n    > PATH_SEP\n    <string>\n\n    // Windows environment:\n    > var parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP )\n    [ 'foo', 'bar', 'baz' ]\n\n    // POSIX environment:\n    > parts = 'foo/bar/baz'.split( PATH_SEP )\n    [ 'foo', 'bar', 'baz' ]\n\n    See Also\n    --------\n    PATH_SEP_POSIX, PATH_SEP_WIN32\n","PATH_SEP_POSIX":"\nPATH_SEP_POSIX\n    POSIX path segment separator.\n\n    Examples\n    --------\n    > PATH_SEP_POSIX\n    '/'\n    > var parts = 'foo/bar/baz'.split( PATH_SEP_POSIX )\n    [ 'foo', 'bar', 'baz' ]\n\n    See Also\n    --------\n    PATH_SEP, PATH_SEP_WIN32\n","PATH_SEP_WIN32":"\nPATH_SEP_WIN32\n    Windows path segment separator.\n\n    Examples\n    --------\n    > PATH_SEP_WIN32\n    '\\\\'\n    > var parts = 'foo\\\\bar\\\\baz'.split( PATH_SEP_WIN32 )\n    [ 'foo', 'bar', 'baz' ]\n\n    See Also\n    --------\n    PATH_SEP, PATH_SEP_POSIX\n","pcorrtest":"\npcorrtest( x, y[, options] )\n    Computes a Pearson product-moment correlation test between paired samples.\n\n    By default, the function performs a t-test for the null hypothesis that the\n    data in arrays or typed arrays `x` and `y` is not correlated. A test against\n    a different population correlation can be carried out by supplying the `rho`\n    option. In this case, a test using the Fisher's z transform is conducted.\n\n    The returned object comes with a `.print()` method which when invoked will\n    print a formatted output of the results of the hypothesis test.\n\n    Parameters\n    ----------\n    x: Array<number>\n        First data array.\n\n    y: Array<number>\n        Second data array.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Nnumber in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.alternative: string (optional)\n        Either `two-sided`, `less` or `greater`. Indicates whether the\n        alternative hypothesis is that `x` has a larger mean than `y`\n        (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n        the same (`two-sided`). Default: `'two-sided'`.\n\n    options.rho: number (optional)\n        Number denoting the correlation under the null hypothesis.\n        Default: `0`.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Used significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.ci: Array<number>\n        1-alpha confidence interval for the Pearson product-moment correlation\n        coefficient. The confidence interval is calculated using Fisher's\n        z-transform.\n\n    out.nullValue: number\n        Assumed correlation under H0 (equal to the supplied `rho` option).\n\n    out.alternative: string\n        Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n    out.method: string\n        Name of test.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    > var rho = 0.5;\n    > var x = new Array( 300 );\n    > var y = new Array( 300 );\n    > for ( var i = 0; i < 300; i++ ) {\n    ...    x[ i ] = base.random.normal( 0.0, 1.0 );\n    ...    y[ i ] = ( rho * x[ i ] ) + base.random.normal( 0.0,\n    ...    base.sqrt( 1.0 - (rho*rho) ) );\n    ... }\n    > var out = pcorrtest( x, y )\n    {\n        alpha: 0.05,\n        rejected: true,\n        pValue: 0,\n        statistic: 10.115805615994121,\n        ci: [ 0.4161679018930295, 0.5853122968949995 ],\n        alternative: 'two-sided',\n        method: 't-test for Pearson correlation coefficient',\n        nullValue: 0,\n        pcorr: 0.505582072355616,\n    }\n\n    // Print output:\n    > var table = out.print()\n    t-test for Pearson correlation coefficient\n\n    Alternative hypothesis: True correlation coefficient is not equal to 0\n\n        pValue: 0\n        statistic: 9.2106\n        95% confidence interval: [0.3776,0.5544]\n\n    Test Decision: Reject null in favor of alternative at 5% significance level\n\n","percentEncode":"\npercentEncode( str )\n    Percent-encodes a UTF-16 encoded string according to RFC 3986.\n\n    Parameters\n    ----------\n    str: string\n        UTF-16 encoded string.\n\n    Returns\n    -------\n    out: string\n        Percent-encoded string.\n\n    Examples\n    --------\n    > var out = percentEncode( '☃' )\n    '%E2%98%83'\n\n","PHI":"\nPHI\n    Golden ratio.\n\n    Examples\n    --------\n    > PHI\n    1.618033988749895\n\n","PI":"\nPI\n    The mathematical constant `π`.\n\n    Examples\n    --------\n    > PI\n    3.141592653589793\n\n    See Also\n    --------\n    TWO_PI\n","PI_SQUARED":"\nPI_SQUARED\n    Square of the mathematical constant `π`.\n\n    Examples\n    --------\n    > PI_SQUARED\n    9.869604401089358\n\n    See Also\n    --------\n    PI\n","pick":"\npick( obj, keys )\n    Returns a partial object copy containing only specified keys.\n\n    If a key does not exist as an own property in a source object, the key is\n    ignored.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    keys: string|Array<string>\n        Keys to copy.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > var obj1 = { 'a': 1, 'b': 2 };\n    > var obj2 = pick( obj1, 'b' )\n    { 'b': 2 }\n\n    See Also\n    --------\n    pickBy\n","pickArguments":"\npickArguments( fcn, indices[, thisArg] )\n    Returns a function that applies specified arguments to a provided function.\n\n    Parameters\n    ----------\n    fcn: Function\n        Input function.\n\n    indices: Array<integer>\n        Argument indices.\n\n    thisArg: any (optional)\n        Function context.\n\n    Returns\n    -------\n    out: Function\n        Function wrapper.\n\n    Examples\n    --------\n    > function foo( a, b ) { return [ a, b ]; };\n    > var bar = pickArguments( foo, [ 0, 2 ] );\n    > var out = bar( 1, 2, 3 )\n    [ 1, 3 ]\n\n    See Also\n    --------\n    reorderArguments, reverseArguments\n","pickBy":"\npickBy( obj, predicate )\n    Returns a partial object copy containing properties for which a predicate\n    returns a truthy value.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    predicate: Function\n        Predicate function.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > function predicate( key, value ) {\n    ...     return ( value > 1 );\n    ... };\n    > var obj1 = { 'a': 1, 'b': 2 };\n    > var obj2 = pickBy( obj1, predicate )\n    { 'b': 2 }\n\n    See Also\n    --------\n    pick\n","PINF":"\nPINF\n    Double-precision floating-point positive infinity.\n\n    Examples\n    --------\n    > PINF\n    Infinity\n\n    See Also\n    --------\n    NINF\n","pkg2alias":"\npkg2alias( pkg )\n    Returns the alias associated with a specified package name.\n\n    The function supports both internal and standalone package names.\n\n    Parameters\n    ----------\n    pkg: string\n        Package name.\n\n    Returns\n    -------\n    out: string|null\n        Alias.\n\n    Examples\n    --------\n    > var v = pkg2alias( '@stdlib/math/base/special/sin' )\n    <string>\n    > v = pkg2alias( '@stdlib/math-base-special-sin' )\n    <string>\n\n    See Also\n    --------\n    alias2pkg, aliases, pkg2related\n","pkg2related":"\npkg2related( pkg )\n    Returns package names related to a specified package name.\n\n    The function supports both internal and standalone package names.\n\n    Parameters\n    ----------\n    pkg: string\n        Package name.\n\n    Returns\n    -------\n    out: Array|null\n        Related package names.\n\n    Examples\n    --------\n    > var v = pkg2related( '@stdlib/math/base/special/sin' )\n    [...]\n    > v = pkg2related( '@stdlib/math-base-special-sin' )\n    [...]\n\n    See Also\n    --------\n    alias2related, aliases, pkg2alias\n","pkg2standalone":"\npkg2standalone( pkg )\n    Returns the standalone package name associated with a provided internal\n    package name.\n\n    Parameters\n    ----------\n    pkg: string\n        Package name.\n\n    Returns\n    -------\n    out: string|null\n        Standalone package name.\n\n    Examples\n    --------\n    > var v = pkg2standalone( '@stdlib/math/base/special/sin' )\n    '@stdlib/math-base-special-sin'\n\n    See Also\n    --------\n    alias2pkg, alias2standalone, aliases, pkg2alias, pkg2related\n","PLATFORM":"\nPLATFORM\n    Platform on which the current process is running.\n\n    Possible values:\n\n    - win32\n    - darwin\n    - linux\n    - freebsd\n    - sunos\n\n    Examples\n    --------\n    > PLATFORM\n    <string>\n\n    See Also\n    --------\n    ARCH\n","plot":"\nplot( [x, y,] [options] )\n    Returns a plot instance for creating 2-dimensional plots.\n\n    `x` and `y` arguments take precedence over `x` and `y` options.\n\n    Parameters\n    ----------\n    x: Array<Array>|Array<TypedArray> (optional)\n        An array of arrays containing x-coordinate values.\n\n    y: Array<Array>|Array<TypedArray> (optional)\n        An array of arrays containing y-coordinate values.\n\n    options: Object (optional)\n        Options.\n\n    options.autoRender: boolean (optional)\n        Boolean indicating whether to re-render on a 'change' event. Default:\n        false.\n\n    options.autoView: boolean (optional)\n        Boolean indicating whether to generate an updated view on a 'render'\n        event. Default: false.\n\n    options.colors: string|Array<string> (optional)\n        Data color(s). Default: 'category10'.\n\n    options.description: string (optional)\n        Plot description.\n\n    options.engine: string (optional)\n        Plot engine. Default: 'svg'.\n\n    options.height: number (optional)\n        Plot height (in pixels). Default: 400.\n\n    options.labels: Array|Array<string> (optional)\n        Data labels.\n\n    options.isDefined: Function (optional)\n        An accessor function indicating whether a datum is defined.\n\n    options.lineStyle: string|Array<string> (optional)\n        Data line style(s). Must be one of: '-', '--', ':', '-.', or 'none'.\n        Default: '-'.\n\n    options.lineOpacity: number|Array<number> (optional)\n        Data line opacity. Must be on the interval [0,1]. Default: 0.9.\n\n    options.lineWidth: integer|Array<integer> (optional)\n        Data line width (in pixels). Default: 2.\n\n    options.paddingBottom: integer (optional)\n        Bottom padding (in pixels). Default: 80.\n\n    options.paddingLeft: integer (optional)\n        Left padding (in pixels). Default: 90.\n\n    options.paddingRight: integer (optional)\n        Right padding (in pixels). Default: 20.\n\n    options.paddingTop: integer (optional)\n        Top padding (in pixels). Default: 80.\n\n    options.renderFormat: string (optional)\n        Plot render format. Must be one of 'vdom' or 'html'. Default: 'vdom'.\n\n    options.symbols: string|Array<string> (optional)\n        Data symbols. Must be one of 'closed-circle', 'open-circle', or 'none'.\n        Default: 'none'.\n\n    options.symbolsOpacity: number|Array<number> (optional)\n        Symbols opacity. Must be on the interval [0,1]. Default: 0.9.\n\n    options.symbolsSize: integer|Array<integer> (optional)\n        Symbols size (in pixels). Default: 6.\n\n    options.title: string (optional)\n        Plot title.\n\n    options.viewer: string (optional)\n        Plot viewer. Must be one of 'browser', 'terminal', 'stdout', 'window',\n        or 'none'. Default: 'none'.\n\n    options.width: number (optional)\n        Plot width (in pixels). Default: 400.\n\n    options.x: Array<Array>|Array<TypedArray> (optional)\n        x-coordinate values.\n\n    options.xAxisOrient: string (optional)\n        x-axis orientation. Must be either 'bottom' or 'top'. Default: 'bottom'.\n\n    options.xLabel: string (optional)\n        x-axis label. Default: 'x'.\n\n    options.xMax: number|null (optional)\n        Maximum value of the x-axis domain. If `null`, the maximum value is\n        calculated from the data. Default: null.\n\n    options.xMin: number|null (optional)\n        Minimum value of the x-axis domain. If `null`, the minimum value is\n        calculated from the data. Default: null.\n\n    options.xNumTicks: integer (optional)\n        Number of x-axis tick marks. Default: 5.\n\n    options.xRug: boolean|Array<boolean> (optional)\n        Boolean flag(s) indicating whether to render one or more rug plots along\n        the x-axis.\n\n    options.xRugOrient: string|Array<string> (optional)\n        x-axis rug plot orientation(s). Must be either 'bottom' or 'top'.\n        Default: 'bottom'.\n\n    options.xRugOpacity: number|Array<number> (optional)\n       x-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n    options.xRugSize: integer|Array<integer> (optional)\n       x-axis rug tick (tassel) size (in pixels). Default: 6.\n\n    options.xScale: string\n       x-axis scale. Default: 'linear'.\n\n    options.xTickFormat: string|null\n       x-axis tick format. Default: null.\n\n    options.y: Array<Array>|Array<TypedArray> (optional)\n        y-coordinate values.\n\n    options.yAxisOrient: string (optional)\n        x-axis orientation. Must be either 'left' or 'right'. Default: 'left'.\n\n    options.yLabel: string (optional)\n        y-axis label. Default: 'y'.\n\n    options.yMax: number|null (optional)\n        Maximum value of the y-axis domain. If `null`, the maximum value is\n        calculated from the data. Default: null.\n\n    options.yMin: number|null (optional)\n        Minimum value of the y-axis domain. If `null`, the minimum value is\n        calculated from the data. Default: null.\n\n    options.yNumTicks: integer (optional)\n        Number of x-axis tick marks. Default: 5.\n\n    options.yRug: boolean|Array<boolean> (optional)\n        Boolean flag(s) indicating whether to render one or more rug plots along\n        the y-axis.\n\n    options.yRugOrient: string|Array<string> (optional)\n        y-axis rug plot orientation(s). Must be either 'left' or 'right'.\n        Default: 'left'.\n\n    options.yRugOpacity: number|Array<number> (optional)\n       y-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n    options.yRugSize: integer|Array<integer> (optional)\n       y-axis rug tick (tassel) size (in pixels). Default: 6.\n\n    options.yScale: string\n       y-axis scale. Default: 'linear'.\n\n    options.yTickFormat: string|null\n       y-axis tick format. Default: null.\n\n    Returns\n    -------\n    plot: Plot\n        Plot instance.\n\n    plot.render()\n        Renders a plot as a virtual DOM tree.\n\n    plot.view( [viewer] )\n        Generates a plot view.\n\n    plot.x\n        x-coordinate values. An assigned value must be an array where each\n        element corresponds to a plotted dataset.\n\n    plot.y\n        y-coordinate values. An assigned value must be an array, where each\n        element corresponds to a plotted dataset.\n\n    plot.labels\n        Data labels. During plot creation, each plotted dataset is assigned a\n        label. If the number of labels is less than the number of plotted\n        datasets, labels are reused using modulo arithmetic.\n\n    plot.isDefined( d, i )\n        An accessor function which defines whether a datum is defined. This\n        accessor is used to define how missing values are encoded. The default\n        behavior is to ignore values which are `NaN`.\n\n    plot.colors\n        Data colors. To set the color all plotted datasets, provide a color\n        name. To specify the colors for each dataset, provide an array of\n        colors. During plot creation, each plotted dataset is assigned one of\n        the provided colors. If the number of colors is less than the number of\n        plotted datasets, colors are reused using modulo arithmetic. Lastly,\n        colors may also be specified by providing the name of a predefined color\n        scheme. The following schemes are supported: 'category10', 'category20',\n        'category20b', and 'category20c'.\n\n    plot.lineStyle\n        Data line style(s). The following line styles are supported: '-' (solid\n        line), '--' (dashed line), ':' (dotted line), '-.' (alternating dashes\n        and dots), and 'none' (no line). To specify the line style for each\n        dataset, provide an array of line styles. During plot creation, each\n        plotted dataset is assigned a line style. If the number of line styles\n        is less than the number of plotted datasets, line styles are reused\n        using modulo arithmetic.\n\n    plot.lineOpacity\n        Data line opacity, where an opacity of `0.0` make a line completely\n        transparent and an opacity of `1.0` makes a line completely opaque. To\n        specify the line opacity for each dataset, provide an array of\n        opacities. During plot creation, each plotted dataset is assigned an\n        opacity. If the number of opacities is less than the number of plotted\n        datasets, opacities are reused using modulo arithmetic.\n\n    plot.lineWidth\n        Data line width(s). To specify the line width for each dataset, provide\n        an array of widths. During plot creation, each plotted dataset is\n        assigned a line width. If the number of line widths is less than the\n        number of plotted datasets, line widths are reused using modulo\n        arithmetic.\n\n    plot.symbols\n        Data symbols. The following symbols are supported: 'closed-circle'\n        (closed circles), 'open-circle' (open circles), and 'none' (no symbols).\n        To specify the symbols used for each dataset, provide an array of\n        symbols. During plot creation, each plotted dataset is assigned a\n        symbol. If the number of symbols is less than the number of plotted\n        datasets, symbols are reused using modulo arithmetic.\n\n    plot.symbolSize\n        Symbols size. To specify the symbols size for each dataset, provide an\n        array of sizes. During plot creation, each plotted dataset is assigned\n        a symbols size. If the number of sizes is less than the number of\n        plotted datasets, sizes are reused using modulo arithmetic.\n\n    plot.symbolsOpacity\n        Symbols opacity, where an opacity of `0.0` makes a symbol completely\n        transparent and an opacity of `1.0` makes a symbol completely opaque. To\n        specify the opacity for each dataset, provide an array of opacities.\n        During plot creation, each plotted dataset is assigned an opacity. If\n        the number of opacities is less than the number of plotted datasets,\n        opacities are reused using modulo arithmetic.\n\n    plot.width\n        Plot width (in pixels).\n\n    plot.height\n        Plot height (in pixels).\n\n    plot.paddingLeft\n        Plot left padding (in pixels). Left padding is typically used to create\n        space for a left-oriented y-axis.\n\n    plot.paddingRight\n        Plot right padding (in pixels). Right padding is typically used to\n        create space for a right-oriented y-axis.\n\n    plot.paddingTop\n        Plot top padding (in pixels). Top padding is typically used to create\n        space for a title or top-oriented x-axis.\n\n    plot.paddingBottom\n        Plot bottom padding (in pixels). Bottom padding is typically used to\n        create space for a bottom-oriented x-axis.\n\n    plot.xMin\n        Minimum value of the x-axis domain. When retrieved, if the value has\n        been set to `null`, the returned value is computed from the `x` data.\n\n    plot.xMax\n        Maximum value of the x-axis domain. When retrieved, if the value has\n        been set to `null`, the returned value is computed from the `x` data.\n\n    plot.yMin\n        Minimum value of the y-axis domain. When retrieved, if the value has\n        been set to `null`, the returned value is computed from the `y` data.\n\n    plot.yMax\n        Maximum value of the y-axis domain. When retrieved, if the value has\n        been set to `null`, the returned value is computed from the `y` data.\n\n    plot.xScale\n        Scale function for mapping values to a coordinate along the x-axis. The\n        following `scales` are supported: 'linear' (linear scale) and 'time'\n        (time scale). When retrieved, the returned value is a scale function.\n\n    plot.yScale\n        Scale function for mapping values to a coordinate along the y-axis. The\n        following `scales` are supported: 'linear' (linear scale) and 'time'\n        (time scale). When retrieved, the returned value is a scale function.\n\n    plot.xTickFormat\n        x-axis tick format (e.g., '%H:%M'). When retrieved, if the value has not\n        been set to `null`, the returned value is a formatting function.\n\n    plot.yTickFormat\n        y-axis tick format (e.g., '%%'). When retrieved, if the value has not\n        been set to `null`, the returned value is a formatting function.\n\n    plot.xNumTicks\n        Number of x-axis tick marks. If the value is set to `null`, the number\n        of tick marks is computed internally.\n\n    plot.yNumTicks\n        Number of y-axis tick marks. If the value is set to `null`, the number\n        of tick marks is computed internally.\n\n    plot.xAxisOrient\n        x-axis orientation. The following orientations are supported: 'bottom'\n        and 'top'.\n\n    plot.yAxisOrient\n        y-axis orientation. The following orientations are supported: 'left' and\n        'right'.\n\n    plot.xRug\n        Boolean flag(s) indicating whether to display a rug plot along the x-\n        axis. To specify the flag for each dataset, provide an array of\n        booleans. During plot creation, each plotted dataset is assigned a flag.\n        If the number of flags is less than the number of plotted datasets,\n        flags are reused using modulo arithmetic.\n\n    plot.yRug\n        Boolean flag(s) indicating whether to display a rug plot along the y-\n        axis. To specify the flag for each dataset, provide an array of\n        booleans. During plot creation, each plotted dataset is assigned a flag.\n        If the number of flags is less than the number of plotted datasets,\n        flags are reused using modulo arithmetic.\n\n    plot.xRugOrient\n        x-axis rug orientation. The following orientations are supported:\n        'bottom' or 'top'. To specify the x-axis rug orientation for each\n        dataset, provide an array of orientations. During plot creation, each\n        plotted dataset is assigned an orientation. If the number of\n        orientations is less than the number of plotted datasets, orientations\n        are reused using modulo arithmetic.\n\n    plot.yRugOrient\n        y-axis rug orientation. The following orientations are supported: 'left'\n        or 'right'. To specify the y-axis rug orientation for each dataset,\n        provide an array of orientations. During plot creation, each plotted\n        dataset is assigned an orientation. If the number of orientations is\n        less than the number of plotted datasets, orientations are reused using\n        modulo arithmetic.\n\n    plot.xRugOpacity\n        x-axis rug opacity, where an opacity of `0.0` makes a rug completely\n        transparent and an opacity of `1.0` makes a rug completely opaque. To\n        specify the x-axis rug opacity for each dataset, provide an array of\n        opacities. During plot creation, each plotted dataset is assigned an\n        opacity. If the number of opacities is less than the number of plotted\n        datasets, opacities are reused using modulo arithmetic.\n\n    plot.yRugOpacity\n        y-axis rug opacity, where an opacity of `0.0` makes a rug completely\n        transparent and an opacity of `1.0` makes a rug completely opaque. To\n        specify the y-axis rug opacity for each dataset, provide an array of\n        opacities. During plot creation, each plotted dataset is assigned an\n        opacity. If the number of opacities is less than the number of plotted\n        datasets, opacities are reused using modulo arithmetic.\n\n    plot.xRugSize\n        x-axis rug tick (tassel) size. To specify the x-axis rug size for each\n        dataset, provide an array of sizes. During plot creation, each plotted\n        dataset is assigned a tick size. If the number of sizes is less than the\n        number of plotted datasets, sizes are reused using modulo arithmetic.\n\n    plot.yRugSize\n        y-axis rug tick (tassel) size. To specify the y-axis rug size for each\n        dataset, provide an array of sizes. During plot creation, each plotted\n        dataset is assigned a tick size. If the number of sizes is less than the\n        number of plotted datasets, sizes are reused using modulo arithmetic.\n\n    plot.description\n        Plot description.\n\n    plot.title\n        Plot title.\n\n    plot.xLabel\n        x-axis label.\n\n    plot.yLabel\n        y-axis label.\n\n    plot.engine\n        Plot rendering engine. The following engines are supported: 'svg'.\n\n    plot.renderFormat\n        Plot render format. The following formats are supported: 'vdom' and\n        'html'.\n\n    plot.autoRender\n        Rendering mode. If `true`, an instance renders on each 'change' event;\n        otherwise, rendering must be triggered manually.\n\n    plot.viewer\n        Plot viewer. The following viewers are supported: 'none', 'stdout',\n        'window', and 'browser'.\n\n    plot.autoView\n        Viewer mode. If `true`, an instance generates an updated view on each\n        'render' event; otherwise, generating a view must be triggered manually.\n\n    plot.graphWidth\n        Computed property corresponding to the expected graph width.\n\n    plot.graphHeight\n        Computed property corresponding to the expected graph height.\n\n    plot.xDomain\n        Computed property corresponding to the x-axis domain.\n\n    plot.yDomain\n        Computed property corresponding to the y-axis domain.\n\n    plot.xRange\n        Computed property corresponding to the x-axis range.\n\n    plot.yRange\n        Computed property correspond to the y-axis range.\n\n    plot.xPos\n        A function which maps values to x-axis coordinate values.\n\n    plot.yPos\n        A function which maps values to y-axis coordinate values.\n\n    Examples\n    --------\n    > var plot = plot()\n    <Plot>\n\n    // Provide plot data at instantiation:\n    > var x = [[0.10, 0.20, 0.30]];\n    > var y = [[0.52, 0.79, 0.64]];\n    > plot = plot( x, y )\n    <Plot>\n\n    See Also\n    --------\n    Plot\n","Plot":"\nPlot( [x, y,] [options] )\n    Returns a plot instance for creating 2-dimensional plots.\n\n    `x` and `y` arguments take precedence over `x` and `y` options.\n\n    Parameters\n    ----------\n    x: Array<Array>|Array<TypedArray> (optional)\n        An array of arrays containing x-coordinate values.\n\n    y: Array<Array>|Array<TypedArray> (optional)\n        An array of arrays containing y-coordinate values.\n\n    options: Object (optional)\n        Options.\n\n    options.autoRender: boolean (optional)\n        Boolean indicating whether to re-render on a 'change' event. Default:\n        false.\n\n    options.autoView: boolean (optional)\n        Boolean indicating whether to generate an updated view on a 'render'\n        event. Default: false.\n\n    options.colors: string|Array<string> (optional)\n        Data color(s). Default: 'category10'.\n\n    options.description: string (optional)\n        Plot description.\n\n    options.engine: string (optional)\n        Plot engine. Default: 'svg'.\n\n    options.height: number (optional)\n        Plot height (in pixels). Default: 400.\n\n    options.labels: Array|Array<string> (optional)\n        Data labels.\n\n    options.isDefined: Function (optional)\n        An accessor function indicating whether a datum is defined.\n\n    options.lineStyle: string|Array<string> (optional)\n        Data line style(s). Must be one of: '-', '--', ':', '-.', or 'none'.\n        Default: '-'.\n\n    options.lineOpacity: number|Array<number> (optional)\n        Data line opacity. Must be on the interval [0,1]. Default: 0.9.\n\n    options.lineWidth: integer|Array<integer> (optional)\n        Data line width (in pixels). Default: 2.\n\n    options.paddingBottom: integer (optional)\n        Bottom padding (in pixels). Default: 80.\n\n    options.paddingLeft: integer (optional)\n        Left padding (in pixels). Default: 90.\n\n    options.paddingRight: integer (optional)\n        Right padding (in pixels). Default: 20.\n\n    options.paddingTop: integer (optional)\n        Top padding (in pixels). Default: 80.\n\n    options.renderFormat: string (optional)\n        Plot render format. Must be one of 'vdom' or 'html'. Default: 'vdom'.\n\n    options.symbols: string|Array<string> (optional)\n        Data symbols. Must be one of 'closed-circle', 'open-circle', or 'none'.\n        Default: 'none'.\n\n    options.symbolsOpacity: number|Array<number> (optional)\n        Symbols opacity. Must be on the interval [0,1]. Default: 0.9.\n\n    options.symbolsSize: integer|Array<integer> (optional)\n        Symbols size (in pixels). Default: 6.\n\n    options.title: string (optional)\n        Plot title.\n\n    options.viewer: string (optional)\n        Plot viewer. Must be one of 'browser', 'terminal', 'stdout', 'window',\n        or 'none'. Default: 'none'.\n\n    options.width: number (optional)\n        Plot width (in pixels). Default: 400.\n\n    options.x: Array<Array>|Array<TypedArray> (optional)\n        x-coordinate values.\n\n    options.xAxisOrient: string (optional)\n        x-axis orientation. Must be either 'bottom' or 'top'. Default: 'bottom'.\n\n    options.xLabel: string (optional)\n        x-axis label. Default: 'x'.\n\n    options.xMax: number|null (optional)\n        Maximum value of the x-axis domain. If `null`, the maximum value is\n        calculated from the data. Default: null.\n\n    options.xMin: number|null (optional)\n        Minimum value of the x-axis domain. If `null`, the minimum value is\n        calculated from the data. Default: null.\n\n    options.xNumTicks: integer (optional)\n        Number of x-axis tick marks. Default: 5.\n\n    options.xRug: boolean|Array<boolean> (optional)\n        Boolean flag(s) indicating whether to render one or more rug plots along\n        the x-axis.\n\n    options.xRugOrient: string|Array<string> (optional)\n        x-axis rug plot orientation(s). Must be either 'bottom' or 'top'.\n        Default: 'bottom'.\n\n    options.xRugOpacity: number|Array<number> (optional)\n       x-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n    options.xRugSize: integer|Array<integer> (optional)\n       x-axis rug tick (tassel) size (in pixels). Default: 6.\n\n    options.xScale: string\n       x-axis scale. Default: 'linear'.\n\n    options.xTickFormat: string|null\n       x-axis tick format. Default: null.\n\n    options.y: Array<Array>|Array<TypedArray> (optional)\n        y-coordinate values.\n\n    options.yAxisOrient: string (optional)\n        x-axis orientation. Must be either 'left' or 'right'. Default: 'left'.\n\n    options.yLabel: string (optional)\n        y-axis label. Default: 'y'.\n\n    options.yMax: number|null (optional)\n        Maximum value of the y-axis domain. If `null`, the maximum value is\n        calculated from the data. Default: null.\n\n    options.yMin: number|null (optional)\n        Minimum value of the y-axis domain. If `null`, the minimum value is\n        calculated from the data. Default: null.\n\n    options.yNumTicks: integer (optional)\n        Number of x-axis tick marks. Default: 5.\n\n    options.yRug: boolean|Array<boolean> (optional)\n        Boolean flag(s) indicating whether to render one or more rug plots along\n        the y-axis.\n\n    options.yRugOrient: string|Array<string> (optional)\n        y-axis rug plot orientation(s). Must be either 'left' or 'right'.\n        Default: 'left'.\n\n    options.yRugOpacity: number|Array<number> (optional)\n       y-axis rug plot opacity. Must be on the interval [0,1]. Default: 0.1.\n\n    options.yRugSize: integer|Array<integer> (optional)\n       y-axis rug tick (tassel) size (in pixels). Default: 6.\n\n    options.yScale: string\n       y-axis scale. Default: 'linear'.\n\n    options.yTickFormat: string|null\n       y-axis tick format. Default: null.\n\n    Returns\n    -------\n    plot: Plot\n        Plot instance.\n\n    plot.render()\n        Renders a plot as a virtual DOM tree.\n\n    plot.view( [viewer] )\n        Generates a plot view.\n\n    plot.x\n        x-coordinate values. An assigned value must be an array where each\n        element corresponds to a plotted dataset.\n\n    plot.y\n        y-coordinate values. An assigned value must be an array, where each\n        element corresponds to a plotted dataset.\n\n    plot.labels\n        Data labels. During plot creation, each plotted dataset is assigned a\n        label. If the number of labels is less than the number of plotted\n        datasets, labels are reused using modulo arithmetic.\n\n    plot.isDefined( d, i )\n        An accessor function which defines whether a datum is defined. This\n        accessor is used to define how missing values are encoded. The default\n        behavior is to ignore values which are `NaN`.\n\n    plot.colors\n        Data colors. To set the color all plotted datasets, provide a color\n        name. To specify the colors for each dataset, provide an array of\n        colors. During plot creation, each plotted dataset is assigned one of\n        the provided colors. If the number of colors is less than the number of\n        plotted datasets, colors are reused using modulo arithmetic. Lastly,\n        colors may also be specified by providing the name of a predefined color\n        scheme. The following schemes are supported: 'category10', 'category20',\n        'category20b', and 'category20c'.\n\n    plot.lineStyle\n        Data line style(s). The following line styles are supported: '-' (solid\n        line), '--' (dashed line), ':' (dotted line), '-.' (alternating dashes\n        and dots), and 'none' (no line). To specify the line style for each\n        dataset, provide an array of line styles. During plot creation, each\n        plotted dataset is assigned a line style. If the number of line styles\n        is less than the number of plotted datasets, line styles are reused\n        using modulo arithmetic.\n\n    plot.lineOpacity\n        Data line opacity, where an opacity of `0.0` make a line completely\n        transparent and an opacity of `1.0` makes a line completely opaque. To\n        specify the line opacity for each dataset, provide an array of\n        opacities. During plot creation, each plotted dataset is assigned an\n        opacity. If the number of opacities is less than the number of plotted\n        datasets, opacities are reused using modulo arithmetic.\n\n    plot.lineWidth\n        Data line width(s). To specify the line width for each dataset, provide\n        an array of widths. During plot creation, each plotted dataset is\n        assigned a line width. If the number of line widths is less than the\n        number of plotted datasets, line widths are reused using modulo\n        arithmetic.\n\n    plot.symbols\n        Data symbols. The following symbols are supported: 'closed-circle'\n        (closed circles), 'open-circle' (open circles), and 'none' (no symbols).\n        To specify the symbols used for each dataset, provide an array of\n        symbols. During plot creation, each plotted dataset is assigned a\n        symbol. If the number of symbols is less than the number of plotted\n        datasets, symbols are reused using modulo arithmetic.\n\n    plot.symbolSize\n        Symbols size. To specify the symbols size for each dataset, provide an\n        array of sizes. During plot creation, each plotted dataset is assigned\n        a symbols size. If the number of sizes is less than the number of\n        plotted datasets, sizes are reused using modulo arithmetic.\n\n    plot.symbolsOpacity\n        Symbols opacity, where an opacity of `0.0` makes a symbol completely\n        transparent and an opacity of `1.0` makes a symbol completely opaque. To\n        specify the opacity for each dataset, provide an array of opacities.\n        During plot creation, each plotted dataset is assigned an opacity. If\n        the number of opacities is less than the number of plotted datasets,\n        opacities are reused using modulo arithmetic.\n\n    plot.width\n        Plot width (in pixels).\n\n    plot.height\n        Plot height (in pixels).\n\n    plot.paddingLeft\n        Plot left padding (in pixels). Left padding is typically used to create\n        space for a left-oriented y-axis.\n\n    plot.paddingRight\n        Plot right padding (in pixels). Right padding is typically used to\n        create space for a right-oriented y-axis.\n\n    plot.paddingTop\n        Plot top padding (in pixels). Top padding is typically used to create\n        space for a title or top-oriented x-axis.\n\n    plot.paddingBottom\n        Plot bottom padding (in pixels). Bottom padding is typically used to\n        create space for a bottom-oriented x-axis.\n\n    plot.xMin\n        Minimum value of the x-axis domain. When retrieved, if the value has\n        been set to `null`, the returned value is computed from the `x` data.\n\n    plot.xMax\n        Maximum value of the x-axis domain. When retrieved, if the value has\n        been set to `null`, the returned value is computed from the `x` data.\n\n    plot.yMin\n        Minimum value of the y-axis domain. When retrieved, if the value has\n        been set to `null`, the returned value is computed from the `y` data.\n\n    plot.yMax\n        Maximum value of the y-axis domain. When retrieved, if the value has\n        been set to `null`, the returned value is computed from the `y` data.\n\n    plot.xScale\n        Scale function for mapping values to a coordinate along the x-axis. The\n        following `scales` are supported: 'linear' (linear scale) and 'time'\n        (time scale). When retrieved, the returned value is a scale function.\n\n    plot.yScale\n        Scale function for mapping values to a coordinate along the y-axis. The\n        following `scales` are supported: 'linear' (linear scale) and 'time'\n        (time scale). When retrieved, the returned value is a scale function.\n\n    plot.xTickFormat\n        x-axis tick format (e.g., '%H:%M'). When retrieved, if the value has not\n        been set to `null`, the returned value is a formatting function.\n\n    plot.yTickFormat\n        y-axis tick format (e.g., '%%'). When retrieved, if the value has not\n        been set to `null`, the returned value is a formatting function.\n\n    plot.xNumTicks\n        Number of x-axis tick marks. If the value is set to `null`, the number\n        of tick marks is computed internally.\n\n    plot.yNumTicks\n        Number of y-axis tick marks. If the value is set to `null`, the number\n        of tick marks is computed internally.\n\n    plot.xAxisOrient\n        x-axis orientation. The following orientations are supported: 'bottom'\n        and 'top'.\n\n    plot.yAxisOrient\n        y-axis orientation. The following orientations are supported: 'left' and\n        'right'.\n\n    plot.xRug\n        Boolean flag(s) indicating whether to display a rug plot along the x-\n        axis. To specify the flag for each dataset, provide an array of\n        booleans. During plot creation, each plotted dataset is assigned a flag.\n        If the number of flags is less than the number of plotted datasets,\n        flags are reused using modulo arithmetic.\n\n    plot.yRug\n        Boolean flag(s) indicating whether to display a rug plot along the y-\n        axis. To specify the flag for each dataset, provide an array of\n        booleans. During plot creation, each plotted dataset is assigned a flag.\n        If the number of flags is less than the number of plotted datasets,\n        flags are reused using modulo arithmetic.\n\n    plot.xRugOrient\n        x-axis rug orientation. The following orientations are supported:\n        'bottom' or 'top'. To specify the x-axis rug orientation for each\n        dataset, provide an array of orientations. During plot creation, each\n        plotted dataset is assigned an orientation. If the number of\n        orientations is less than the number of plotted datasets, orientations\n        are reused using modulo arithmetic.\n\n    plot.yRugOrient\n        y-axis rug orientation. The following orientations are supported: 'left'\n        or 'right'. To specify the y-axis rug orientation for each dataset,\n        provide an array of orientations. During plot creation, each plotted\n        dataset is assigned an orientation. If the number of orientations is\n        less than the number of plotted datasets, orientations are reused using\n        modulo arithmetic.\n\n    plot.xRugOpacity\n        x-axis rug opacity, where an opacity of `0.0` makes a rug completely\n        transparent and an opacity of `1.0` makes a rug completely opaque. To\n        specify the x-axis rug opacity for each dataset, provide an array of\n        opacities. During plot creation, each plotted dataset is assigned an\n        opacity. If the number of opacities is less than the number of plotted\n        datasets, opacities are reused using modulo arithmetic.\n\n    plot.yRugOpacity\n        y-axis rug opacity, where an opacity of `0.0` makes a rug completely\n        transparent and an opacity of `1.0` makes a rug completely opaque. To\n        specify the y-axis rug opacity for each dataset, provide an array of\n        opacities. During plot creation, each plotted dataset is assigned an\n        opacity. If the number of opacities is less than the number of plotted\n        datasets, opacities are reused using modulo arithmetic.\n\n    plot.xRugSize\n        x-axis rug tick (tassel) size. To specify the x-axis rug size for each\n        dataset, provide an array of sizes. During plot creation, each plotted\n        dataset is assigned a tick size. If the number of sizes is less than the\n        number of plotted datasets, sizes are reused using modulo arithmetic.\n\n    plot.yRugSize\n        y-axis rug tick (tassel) size. To specify the y-axis rug size for each\n        dataset, provide an array of sizes. During plot creation, each plotted\n        dataset is assigned a tick size. If the number of sizes is less than the\n        number of plotted datasets, sizes are reused using modulo arithmetic.\n\n    plot.description\n        Plot description.\n\n    plot.title\n        Plot title.\n\n    plot.xLabel\n        x-axis label.\n\n    plot.yLabel\n        y-axis label.\n\n    plot.engine\n        Plot rendering engine. The following engines are supported: 'svg'.\n\n    plot.renderFormat\n        Plot render format. The following formats are supported: 'vdom' and\n        'html'.\n\n    plot.autoRender\n        Rendering mode. If `true`, an instance renders on each 'change' event;\n        otherwise, rendering must be triggered manually.\n\n    plot.viewer\n        Plot viewer. The following viewers are supported: 'none', 'stdout',\n        'window', and 'browser'.\n\n    plot.autoView\n        Viewer mode. If `true`, an instance generates an updated view on each\n        'render' event; otherwise, generating a view must be triggered manually.\n\n    plot.graphWidth\n        Computed property corresponding to the expected graph width.\n\n    plot.graphHeight\n        Computed property corresponding to the expected graph height.\n\n    plot.xDomain\n        Computed property corresponding to the x-axis domain.\n\n    plot.yDomain\n        Computed property corresponding to the y-axis domain.\n\n    plot.xRange\n        Computed property corresponding to the x-axis range.\n\n    plot.yRange\n        Computed property correspond to the y-axis range.\n\n    plot.xPos\n        A function which maps values to x-axis coordinate values.\n\n    plot.yPos\n        A function which maps values to y-axis coordinate values.\n\n    Examples\n    --------\n    > var plot = Plot()\n    <Plot>\n\n    // Provide plot data at instantiation:\n    > var x = [[0.10, 0.20, 0.30]];\n    > var y = [[0.52, 0.79, 0.64]];\n    > plot = Plot( x, y )\n    <Plot>\n\n    See Also\n    --------\n    plot\n","pluck":"\npluck( arr, prop[, options] )\n    Extracts a property value from each element of an object array.\n\n    The function skips `null` and `undefined` array elements.\n\n    Extracted values are not cloned.\n\n    Parameters\n    ----------\n    arr: Array\n        Source array.\n\n    prop: string\n        Property to access.\n\n    options: Object (optional)\n        Options.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to return a new data structure. To mutate the\n        input data structure (e.g., when input values can be discarded or when\n        optimizing memory usage), set the `copy` option to `false`. Default:\n        true.\n\n    Returns\n    -------\n    out: Array\n        Destination array.\n\n    Examples\n    --------\n    > var arr = [\n    ...     { 'a': 1, 'b': 2 },\n    ...     { 'a': 0.5, 'b': 3 }\n    ... ];\n    > var out = pluck( arr, 'a' )\n    [ 1, 0.5 ]\n\n    > arr = [\n    ...     { 'a': 1, 'b': 2 },\n    ...     { 'a': 0.5, 'b': 3 }\n    ... ];\n    > out = pluck( arr, 'a', { 'copy': false } )\n    [ 1, 0.5 ]\n    > var bool = ( arr[ 0 ] === out[ 0 ] )\n    true\n\n    See Also\n    --------\n    deepPluck, pick\n","pop":"\npop( collection )\n    Removes and returns the last element of a collection.\n\n    The function returns an array with two elements: the shortened collection\n    and the removed element.\n\n    If the input collection is a typed array whose length is greater than `0`,\n    the first return value does not equal the input reference.\n\n    For purposes of generality, always treat the output collection as distinct\n    from the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        A collection. If the collection is an `Object`, the value should be\n        array-like.\n\n    Returns\n    -------\n    out: Array\n        Updated collection and the removed item.\n\n    Examples\n    --------\n    // Arrays:\n    > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > var out = pop( arr )\n    [ [ 1.0, 2.0, 3.0, 4.0 ], 5.0 ]\n\n    // Typed arrays:\n    > arr = new Float64Array( [ 1.0, 2.0 ] );\n    > out = pop( arr )\n    [ <Float64Array>[ 1.0 ], 2.0 ]\n\n    // Array-like object:\n    > arr = { 'length': 2, '0': 1.0, '1': 2.0 };\n    > out = pop( arr )\n    [ { 'length': 1, '0': 1.0 }, 2.0 ]\n\n    See Also\n    --------\n    push, shift, unshift\n","porterStemmer":"\nporterStemmer( word )\n    Extracts the stem of a given word.\n\n    Parameters\n    ----------\n    word: string\n        Input word.\n\n    Returns\n    -------\n    out: string\n        Word stem.\n\n    Examples\n    --------\n    > var out = porterStemmer( 'walking' )\n    'walk'\n    > out = porterStemmer( 'walked' )\n    'walk'\n    > out = porterStemmer( 'walks' )\n    'walk'\n    > out = porterStemmer( '' )\n    ''\n\n","prepend":"\nprepend( collection1, collection2 )\n    Adds the elements of one collection to the beginning of another collection.\n\n    If the input collection is a typed array, the output value does not equal\n    the input reference and the underlying `ArrayBuffer` may *not* be the same\n    as the `ArrayBuffer` belonging to the input view.\n\n    For purposes of generality, always treat the output collection as distinct\n    from the input collection.\n\n    Parameters\n    ----------\n    collection1: Array|TypedArray|Object\n        A collection. If the collection is an `Object`, the collection should be\n        array-like.\n\n    collection2: Array|TypedArray|Object\n        A collection containing the elements to add. If the collection is an\n        `Object`, the collection should be array-like.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Updated collection.\n\n    Examples\n    --------\n    // Arrays:\n    > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > arr = prepend( arr, [ 6.0, 7.0 ] )\n    [ 6.0, 7.0, 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Typed arrays:\n    > arr = new Float64Array( [ 1.0, 2.0 ] );\n    > arr = prepend( arr, [ 3.0, 4.0 ] )\n    <Float64Array>[ 3.0, 4.0, 1.0, 2.0 ]\n\n    // Array-like object:\n    > arr = { 'length': 1, '0': 1.0 };\n    > arr = prepend( arr, [ 2.0, 3.0 ] )\n    { 'length': 3, '0': 2.0, '1': 3.0, '2': 1.0 }\n\n    See Also\n    --------\n    append, unshift\n","prevGraphemeClusterBreak":"\nprevGraphemeClusterBreak( str[, fromIndex] )\n    Returns the previous extended grapheme cluster break in a string before a\n    specified position.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    fromIndex: integer (optional)\n        Position. Default: str.length-1.\n\n    Returns\n    -------\n    out: integer\n        Previous extended grapheme cluster break position.\n\n    Examples\n    --------\n    > var out = prevGraphemeClusterBreak( 'last man standing', 4 )\n    3\n    > out = prevGraphemeClusterBreak( 'presidential election', 8 )\n    7\n    > out = prevGraphemeClusterBreak( 'अनुच्छेद', 2 )\n    0\n    > out = prevGraphemeClusterBreak( '🌷', 1 )\n    -1\n\n    See Also\n    --------\n    numGraphemeClusters, nextGraphemeClusterBreak","PRIMES_100K":"\nPRIMES_100K()\n    Returns an array containing the first 100,000 prime numbers.\n\n    Returns\n    -------\n    out: Array<number>\n        List of primes.\n\n    Examples\n    --------\n    > var list = PRIMES_100K()\n    [ 2, 3, 5, ... ]\n\n    See Also\n    --------\n    iterPrimesSeq\n","properties":"\nproperties( value )\n    Returns an array of an object's own enumerable and non-enumerable property\n    names and symbols.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    props: Array\n        List of an object's own enumerable and non-enumerable properties.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var props = properties( obj )\n    [ 'beep' ]\n\n    See Also\n    --------\n    defineProperties, inheritedProperties, propertiesIn, propertyNames, propertySymbols\n","propertiesIn":"\npropertiesIn( value )\n    Returns an array of an object's own and inherited property names and\n    symbols.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    props: Array\n        List of an object's own and inherited property names and symbols.\n\n    Examples\n    --------\n    > var props = propertiesIn( [] )\n\n    See Also\n    --------\n    defineProperties, inheritedProperties, properties, propertyNamesIn, propertySymbolsIn\n","propertyDescriptor":"\npropertyDescriptor( value, property )\n    Returns a property descriptor for an object's own property.\n\n    If provided `null` or `undefined` or provided a non-existent property, the\n    function returns `null`.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    property: string|symbol\n        Property name.\n\n    Returns\n    -------\n    desc: Object|null\n        Property descriptor.\n\n    Examples\n    --------\n    > var obj = { 'a': 'b' };\n    > var desc = propertyDescriptor( obj, 'a' )\n    {...}\n\n    See Also\n    --------\n    hasOwnProp, defineProperty, propertyDescriptorIn, propertyDescriptors\n","propertyDescriptorIn":"\npropertyDescriptorIn( value, property )\n    Returns a property descriptor for an object's own or inherited property.\n\n    If provided `null` or `undefined` or provided a non-existent property, the\n    function returns `null`.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    property: string|symbol\n        Property name.\n\n    Returns\n    -------\n    desc: Object|null\n        Property descriptor.\n\n    Examples\n    --------\n    > var obj = { 'a': 'b' };\n    > var desc = propertyDescriptorIn( obj, 'a' )\n    {...}\n\n    See Also\n    --------\n    hasProp, defineProperty, propertyDescriptor, propertyDescriptorsIn\n","propertyDescriptors":"\npropertyDescriptors( value )\n    Returns an object's own property descriptors.\n\n    If provided `null` or `undefined`, the function returns an empty object.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    desc: Object\n        Property descriptors.\n\n    Examples\n    --------\n    > var obj = { 'a': 'b' };\n    > var desc = propertyDescriptors( obj )\n    { 'a': {...} }\n\n    See Also\n    --------\n    defineProperty, defineProperties, propertyDescriptor, propertyDescriptorsIn, propertyNames, propertySymbols\n","propertyDescriptorsIn":"\npropertyDescriptorsIn( value )\n    Returns an object's own and inherited property descriptors.\n\n    If provided `null` or `undefined`, the function returns an empty object.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    desc: Object\n        An object's own and inherited property descriptors.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var desc = propertyDescriptorsIn( obj )\n    { 'beep': {...}, 'foo': {...}, ... }\n\n    See Also\n    --------\n    defineProperties, propertyDescriptorIn, propertyDescriptors, propertyNamesIn, propertySymbolsIn\n","propertyNames":"\npropertyNames( value )\n    Returns an array of an object's own enumerable and non-enumerable property\n    names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's own enumerable and non-enumerable property names.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var keys = propertyNames( obj )\n    [ 'beep' ]\n\n    See Also\n    --------\n    objectKeys, nonEnumerablePropertyNames, propertyNamesIn, propertySymbols\n","propertyNamesIn":"\npropertyNamesIn( value )\n    Returns an array of an object's own and inherited enumerable and non-\n    enumerable property names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's own and inherited enumerable and non-enumerable\n        property names.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var keys = propertyNamesIn( obj )\n    e.g., [ 'beep', 'foo', ... ]\n\n    See Also\n    --------\n    objectKeys, nonEnumerablePropertyNamesIn, propertyNames, propertySymbolsIn\n","propertySymbols":"\npropertySymbols( value )\n    Returns an array of an object's own symbol properties.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's own symbol properties.\n\n    Examples\n    --------\n    > var s = propertySymbols( {} )\n\n    See Also\n    --------\n    propertyNames, propertySymbolsIn\n","propertySymbolsIn":"\npropertySymbolsIn( value )\n    Returns an array of an object's own and inherited symbol properties.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's own and inherited symbol properties.\n\n    Examples\n    --------\n    > var s = propertySymbolsIn( [] )\n\n    See Also\n    --------\n    propertyNamesIn, propertySymbols\n","Proxy":"\nProxy( target, handlers )\n    Returns a proxy object implementing custom behavior for specified object\n    operations.\n\n    The following \"traps\" are supported:\n\n    - getPrototypeOf( target )\n        Trap for `Object.getPrototypeOf()`. Can be used to intercept the\n        `instanceof` operator. The method must return an object or `null`.\n\n    - setPrototypeOf( target, prototype )\n        Trap for `Object.setPrototypeOf()`. The method must return a boolean\n        indicating if prototype successfully set.\n\n    - isExtensible( target )\n        Trap for `Object.isExtensible()`. The method must return a boolean.\n\n    - preventExtensions( target )\n        Trap for `Object.preventExtensions()`. The method must return a boolean.\n\n    - getOwnPropertyDescriptor( target, property )\n        Trap for `Object.getOwnPropertyDescriptor()`. The method must return an\n        object or `undefined`.\n\n    - defineProperty( target, property, descriptor )\n        Trap for `Object.defineProperty()`. The method must return a boolean\n        indicating whether the operation succeeded.\n\n    - has( target, property )\n        Trap for the `in` operator. The method must return a boolean.\n\n    - get( target, property, receiver )\n        Trap for retrieving property values. The method can return any value.\n\n    - set( target, property, value, receiver )\n        Trap for setting property values. The method should return a boolean\n        indicating whether assignment succeeded.\n\n    - deleteProperty( target, property )\n        Trap for the `delete` operator. The method must return a boolean\n        indicating whether operation succeeded.\n\n    - ownKeys( target )\n        Trap for `Object.keys`, `Object.getOwnPropertyNames()`, and\n        `Object.getOwnPropertySymbols()`. The method must return an enumerable\n        object.\n\n    - apply( target, thisArg, argumentsList )\n        Trap for a function call. The method can return any value.\n\n    - construct( target, argumentsList, newTarget )\n        Trap for the `new` operator. The method must return an object.\n\n    All traps are optional. If a trap is not defined, the default behavior is to\n    forward the operation to the target.\n\n    Parameters\n    ----------\n    target: Object\n        Object which the proxy virtualizes.\n\n    handlers: Object\n        Object whose properties are functions which define the behavior of the\n        proxy when performing operations.\n\n    Returns\n    -------\n    p: Object\n        Proxy object.\n\n    Examples\n    --------\n    > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n    > var h = { 'get': get };\n    > var p = new Proxy( {}, h );\n    > p.a = 3.14;\n    > p.a\n    6.28\n\n\nProxy.revocable( target, handlers )\n    Returns a revocable proxy object.\n\n    Parameters\n    ----------\n    target: Object\n        Object which the proxy virtualizes.\n\n    handlers: Object\n        Object whose properties are functions which define the behavior of the\n        proxy when performing operations.\n\n    Returns\n    -------\n    p: Object\n        Revocable proxy object.\n\n    p.proxy: Object\n        Proxy object.\n\n    p.revoke: Function\n        Invalidates a proxy, rendering a proxy object unusable.\n\n    Examples\n    --------\n    > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n    > var h = { 'get': get };\n    > var p = Proxy.revocable( {}, h );\n    > p.proxy.a = 3.14;\n    > p.proxy.a\n    6.28\n    > p.revoke();\n\n","Proxy.revocable":"\nProxy.revocable( target, handlers )\n    Returns a revocable proxy object.\n\n    Parameters\n    ----------\n    target: Object\n        Object which the proxy virtualizes.\n\n    handlers: Object\n        Object whose properties are functions which define the behavior of the\n        proxy when performing operations.\n\n    Returns\n    -------\n    p: Object\n        Revocable proxy object.\n\n    p.proxy: Object\n        Proxy object.\n\n    p.revoke: Function\n        Invalidates a proxy, rendering a proxy object unusable.\n\n    Examples\n    --------\n    > function get( obj, prop ) { return obj[ prop ] * 2.0 };\n    > var h = { 'get': get };\n    > var p = Proxy.revocable( {}, h );\n    > p.proxy.a = 3.14;\n    > p.proxy.a\n    6.28\n    > p.revoke();","push":"\npush( collection, ...items )\n    Adds one or more elements to the end of a collection.\n\n    If the input collection is a typed array, the output value does not equal\n    the input reference and the underlying `ArrayBuffer` may *not* be the same\n    as the `ArrayBuffer` belonging to the input view.\n\n    For purposes of generality, always treat the output collection as distinct\n    from the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        A collection. If the collection is an `Object`, the collection should be\n        array-like.\n\n    items: ...any\n        Items to add.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Updated collection.\n\n    Examples\n    --------\n    // Arrays:\n    > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > arr = push( arr, 6.0, 7.0 )\n    [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0 ]\n\n    // Typed arrays:\n    > arr = new Float64Array( [ 1.0, 2.0 ] );\n    > arr = push( arr, 3.0, 4.0 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Array-like object:\n    > arr = { 'length': 0 };\n    > arr = push( arr, 1.0, 2.0 )\n    { 'length': 2, '0': 1.0, '1': 2.0 }\n\n    See Also\n    --------\n    pop, shift, unshift\n","quarterOfYear":"\nquarterOfYear( [month] )\n    Returns the quarter of the year.\n\n    By default, the function returns the quarter of the year for the current\n    month in the current year (according to local time). To determine the\n    quarter for a particular month, provide either a month or a `Date`\n    object.\n\n    A `month` may be either a month's integer value, three letter abbreviation,\n    or full name (case insensitive).\n\n    Parameters\n    ----------\n    month: integer|string|Date (optional)\n        Month (or `Date`).\n\n    Returns\n    -------\n    out: integer\n        Quarter of the year.\n\n    Examples\n    --------\n    > var q = quarterOfYear( new Date() )\n    <number>\n    > q = quarterOfYear( 4 )\n    2\n    > q = quarterOfYear( 'June' )\n    2\n\n    // Other ways to supply month:\n    > q = quarterOfYear( 'April' )\n    2\n    > q = quarterOfYear( 'apr' )\n    2\n\n    See Also\n    --------\n    dayOfYear\n","random.array.arcsine":"\nrandom.array.arcsine( len, a, b[, options] )\n    Returns an array containing pseudorandom numbers drawn from an arcsine\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.arcsine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.arcsine.assign( a, b, out )\n    Fills an array with pseudorandom numbers drawn from an arcsine distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.arcsine.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.arcsine.factory( [a, b, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an arcsine distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.arcsine.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.arcsine.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.arcsine.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.arcsine.PRNG;\n\n\nrandom.array.arcsine.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.arcsine.seed;\n\n\nrandom.array.arcsine.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.arcsine.seedLength;\n\n\nrandom.array.arcsine.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.arcsine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.arcsine.state\n    <Uint32Array>\n\n    > out = random.array.arcsine( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.arcsine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.arcsine.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.arcsine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.arcsine.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.arcsine.stateLength;\n\n\nrandom.array.arcsine.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.arcsine.byteLength;\n\n    See Also\n    --------\n    base.random.arcsine, random.strided.arcsine\n","random.array.arcsine.assign":"\nrandom.array.arcsine.assign( a, b, out )\n    Fills an array with pseudorandom numbers drawn from an arcsine distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.arcsine.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.arcsine.factory":"\nrandom.array.arcsine.factory( [a, b, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an arcsine distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.arcsine.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.arcsine.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.arcsine.PRNG":"\nrandom.array.arcsine.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.arcsine.PRNG;","random.array.arcsine.seed":"\nrandom.array.arcsine.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.arcsine.seed;","random.array.arcsine.seedLength":"\nrandom.array.arcsine.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.arcsine.seedLength;","random.array.arcsine.state":"\nrandom.array.arcsine.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.arcsine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.arcsine.state\n    <Uint32Array>\n\n    > out = random.array.arcsine( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.arcsine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.arcsine.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.arcsine( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.arcsine.stateLength":"\nrandom.array.arcsine.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.arcsine.stateLength;","random.array.arcsine.byteLength":"\nrandom.array.arcsine.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.arcsine.byteLength;\n\n    See Also\n    --------\n    base.random.arcsine, random.strided.arcsine","random.array.bernoulli":"\nrandom.array.bernoulli( len, p[, options] )\n    Returns an array containing pseudorandom numbers drawn from a Bernoulli\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.bernoulli( 3, 0.5 )\n    <Float64Array>\n\n\nrandom.array.bernoulli.assign( p, out )\n    Fills an array with pseudorandom numbers drawn from a Bernoulli\n    distribution.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.bernoulli.assign( 0.5, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.bernoulli.factory( [p, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Bernoulli distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.bernoulli.factory();\n    > var out = fcn( 3, 0.5 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.bernoulli.factory( 0.5 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.bernoulli.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.bernoulli.PRNG;\n\n\nrandom.array.bernoulli.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.bernoulli.seed;\n\n\nrandom.array.bernoulli.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.bernoulli.seedLength;\n\n\nrandom.array.bernoulli.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.bernoulli( 3, 0.5 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.bernoulli.state\n    <Uint32Array>\n\n    > out = random.array.bernoulli( 3, 0.5 )\n    <Float64Array>\n    > out = random.array.bernoulli( 3, 0.5 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.bernoulli.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.bernoulli( 3, 0.5 )\n    <Float64Array>\n\n\nrandom.array.bernoulli.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.bernoulli.stateLength;\n\n\nrandom.array.bernoulli.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.bernoulli.byteLength;\n\n    See Also\n    --------\n    base.random.bernoulli, random.strided.bernoulli\n","random.array.bernoulli.assign":"\nrandom.array.bernoulli.assign( p, out )\n    Fills an array with pseudorandom numbers drawn from a Bernoulli\n    distribution.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.bernoulli.assign( 0.5, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.bernoulli.factory":"\nrandom.array.bernoulli.factory( [p, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Bernoulli distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.bernoulli.factory();\n    > var out = fcn( 3, 0.5 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.bernoulli.factory( 0.5 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.bernoulli.PRNG":"\nrandom.array.bernoulli.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.bernoulli.PRNG;","random.array.bernoulli.seed":"\nrandom.array.bernoulli.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.bernoulli.seed;","random.array.bernoulli.seedLength":"\nrandom.array.bernoulli.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.bernoulli.seedLength;","random.array.bernoulli.state":"\nrandom.array.bernoulli.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.bernoulli( 3, 0.5 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.bernoulli.state\n    <Uint32Array>\n\n    > out = random.array.bernoulli( 3, 0.5 )\n    <Float64Array>\n    > out = random.array.bernoulli( 3, 0.5 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.bernoulli.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.bernoulli( 3, 0.5 )\n    <Float64Array>","random.array.bernoulli.stateLength":"\nrandom.array.bernoulli.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.bernoulli.stateLength;","random.array.bernoulli.byteLength":"\nrandom.array.bernoulli.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.bernoulli.byteLength;\n\n    See Also\n    --------\n    base.random.bernoulli, random.strided.bernoulli","random.array.beta":"\nrandom.array.beta( len, alpha, beta[, options] )\n    Returns an array containing pseudorandom numbers drawn from a beta\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    alpha: number\n        First shape parameter.\n\n    beta: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.beta( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.beta.assign( alpha, beta, out )\n    Fills an array with pseudorandom numbers drawn from a beta distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        First shape parameter.\n\n    beta: number\n        Second shape parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.beta.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.beta.factory( [alpha, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a beta distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        First shape parameter.\n\n    beta: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.beta.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.beta.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.beta.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.beta.PRNG;\n\n\nrandom.array.beta.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.beta.seed;\n\n\nrandom.array.beta.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.beta.seedLength;\n\n\nrandom.array.beta.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.beta( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.beta.state\n    <Uint32Array>\n\n    > out = random.array.beta( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.beta( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.beta.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.beta( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.beta.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.beta.stateLength;\n\n\nrandom.array.beta.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.beta.byteLength;\n\n    See Also\n    --------\n    base.random.beta, random.strided.beta\n","random.array.beta.assign":"\nrandom.array.beta.assign( alpha, beta, out )\n    Fills an array with pseudorandom numbers drawn from a beta distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        First shape parameter.\n\n    beta: number\n        Second shape parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.beta.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.beta.factory":"\nrandom.array.beta.factory( [alpha, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a beta distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        First shape parameter.\n\n    beta: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.beta.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.beta.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.beta.PRNG":"\nrandom.array.beta.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.beta.PRNG;","random.array.beta.seed":"\nrandom.array.beta.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.beta.seed;","random.array.beta.seedLength":"\nrandom.array.beta.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.beta.seedLength;","random.array.beta.state":"\nrandom.array.beta.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.beta( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.beta.state\n    <Uint32Array>\n\n    > out = random.array.beta( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.beta( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.beta.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.beta( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.beta.stateLength":"\nrandom.array.beta.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.beta.stateLength;","random.array.beta.byteLength":"\nrandom.array.beta.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.beta.byteLength;\n\n    See Also\n    --------\n    base.random.beta, random.strided.beta","random.array.betaprime":"\nrandom.array.betaprime( len, alpha, beta[, options] )\n    Returns an array containing pseudorandom numbers drawn from a beta prime\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    alpha: number\n        First shape parameter.\n\n    beta: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.betaprime( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.betaprime.assign( alpha, beta, out )\n    Fills an array with pseudorandom numbers drawn from a beta prime\n    distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        First shape parameter.\n\n    beta: number\n        Second shape parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.betaprime.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.betaprime.factory( [alpha, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a beta prime distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        First shape parameter.\n\n    beta: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.betaprime.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.betaprime.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.betaprime.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.betaprime.PRNG;\n\n\nrandom.array.betaprime.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.betaprime.seed;\n\n\nrandom.array.betaprime.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.betaprime.seedLength;\n\n\nrandom.array.betaprime.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.betaprime( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.betaprime.state\n    <Uint32Array>\n\n    > out = random.array.betaprime( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.betaprime( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.betaprime.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.betaprime( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.betaprime.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.betaprime.stateLength;\n\n\nrandom.array.betaprime.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.betaprime.byteLength;\n\n    See Also\n    --------\n    base.random.betaprime, random.strided.betaprime\n","random.array.betaprime.assign":"\nrandom.array.betaprime.assign( alpha, beta, out )\n    Fills an array with pseudorandom numbers drawn from a beta prime\n    distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        First shape parameter.\n\n    beta: number\n        Second shape parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.betaprime.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.betaprime.factory":"\nrandom.array.betaprime.factory( [alpha, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a beta prime distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        First shape parameter.\n\n    beta: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.betaprime.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.betaprime.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.betaprime.PRNG":"\nrandom.array.betaprime.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.betaprime.PRNG;","random.array.betaprime.seed":"\nrandom.array.betaprime.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.betaprime.seed;","random.array.betaprime.seedLength":"\nrandom.array.betaprime.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.betaprime.seedLength;","random.array.betaprime.state":"\nrandom.array.betaprime.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.betaprime( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.betaprime.state\n    <Uint32Array>\n\n    > out = random.array.betaprime( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.betaprime( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.betaprime.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.betaprime( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.betaprime.stateLength":"\nrandom.array.betaprime.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.betaprime.stateLength;","random.array.betaprime.byteLength":"\nrandom.array.betaprime.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.betaprime.byteLength;\n\n    See Also\n    --------\n    base.random.betaprime, random.strided.betaprime","random.array.binomial":"\nrandom.array.binomial( len, n, p[, options] )\n    Returns an array containing pseudorandom numbers drawn from a binomial\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    n: number\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.binomial( 3, 17, 0.5 )\n    <Float64Array>\n\n\nrandom.array.binomial.assign( n, p, out )\n    Fills an array with pseudorandom numbers drawn from a binomial distribution.\n\n    Parameters\n    ----------\n    n: number\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.binomial.assign( 17, 0.5, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.binomial.factory( [n, p, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a binomial distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    n: number (optional)\n        Number of trials.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.binomial.factory();\n    > var out = fcn( 3, 17, 0.5 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.binomial.factory( 17, 0.5 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.binomial.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.binomial.PRNG;\n\n\nrandom.array.binomial.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.binomial.seed;\n\n\nrandom.array.binomial.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.binomial.seedLength;\n\n\nrandom.array.binomial.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.binomial( 3, 17, 0.5 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.binomial.state\n    <Uint32Array>\n\n    > out = random.array.binomial( 3, 17, 0.5 )\n    <Float64Array>\n    > out = random.array.binomial( 3, 17, 0.5 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.binomial.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.binomial( 3, 17, 0.5 )\n    <Float64Array>\n\n\nrandom.array.binomial.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.binomial.stateLength;\n\n\nrandom.array.binomial.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.binomial.byteLength;\n\n    See Also\n    --------\n    random.array.negativeBinomial, base.random.binomial\n","random.array.binomial.assign":"\nrandom.array.binomial.assign( n, p, out )\n    Fills an array with pseudorandom numbers drawn from a binomial distribution.\n\n    Parameters\n    ----------\n    n: number\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.binomial.assign( 17, 0.5, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.binomial.factory":"\nrandom.array.binomial.factory( [n, p, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a binomial distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    n: number (optional)\n        Number of trials.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.binomial.factory();\n    > var out = fcn( 3, 17, 0.5 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.binomial.factory( 17, 0.5 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.binomial.PRNG":"\nrandom.array.binomial.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.binomial.PRNG;","random.array.binomial.seed":"\nrandom.array.binomial.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.binomial.seed;","random.array.binomial.seedLength":"\nrandom.array.binomial.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.binomial.seedLength;","random.array.binomial.state":"\nrandom.array.binomial.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.binomial( 3, 17, 0.5 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.binomial.state\n    <Uint32Array>\n\n    > out = random.array.binomial( 3, 17, 0.5 )\n    <Float64Array>\n    > out = random.array.binomial( 3, 17, 0.5 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.binomial.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.binomial( 3, 17, 0.5 )\n    <Float64Array>","random.array.binomial.stateLength":"\nrandom.array.binomial.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.binomial.stateLength;","random.array.binomial.byteLength":"\nrandom.array.binomial.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.binomial.byteLength;\n\n    See Also\n    --------\n    random.array.negativeBinomial, base.random.binomial","random.array.cauchy":"\nrandom.array.cauchy( len, x0, gamma[, options] )\n    Returns an array containing pseudorandom numbers drawn from a Cauchy\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    x0: number\n        Location parameter.\n\n    gamma: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.cauchy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.cauchy.assign( x0, gamma, out )\n    Fills an array with pseudorandom numbers drawn from a Cauchy distribution.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    gamma: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.cauchy.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.cauchy.factory( [x0, gamma, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Cauchy distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    x0: number (optional)\n        Location parameter.\n\n    gamma: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.cauchy.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.cauchy.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.cauchy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.cauchy.PRNG;\n\n\nrandom.array.cauchy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.cauchy.seed;\n\n\nrandom.array.cauchy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.cauchy.seedLength;\n\n\nrandom.array.cauchy.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.cauchy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.cauchy.state\n    <Uint32Array>\n\n    > out = random.array.cauchy( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.cauchy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.cauchy.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.cauchy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.cauchy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.cauchy.stateLength;\n\n\nrandom.array.cauchy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.cauchy.byteLength;\n\n    See Also\n    --------\n    base.random.cauchy\n","random.array.cauchy.assign":"\nrandom.array.cauchy.assign( x0, gamma, out )\n    Fills an array with pseudorandom numbers drawn from a Cauchy distribution.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    gamma: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.cauchy.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.cauchy.factory":"\nrandom.array.cauchy.factory( [x0, gamma, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Cauchy distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    x0: number (optional)\n        Location parameter.\n\n    gamma: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.cauchy.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.cauchy.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.cauchy.PRNG":"\nrandom.array.cauchy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.cauchy.PRNG;","random.array.cauchy.seed":"\nrandom.array.cauchy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.cauchy.seed;","random.array.cauchy.seedLength":"\nrandom.array.cauchy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.cauchy.seedLength;","random.array.cauchy.state":"\nrandom.array.cauchy.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.cauchy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.cauchy.state\n    <Uint32Array>\n\n    > out = random.array.cauchy( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.cauchy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.cauchy.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.cauchy( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.cauchy.stateLength":"\nrandom.array.cauchy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.cauchy.stateLength;","random.array.cauchy.byteLength":"\nrandom.array.cauchy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.cauchy.byteLength;\n\n    See Also\n    --------\n    base.random.cauchy","random.array.chi":"\nrandom.array.chi( len, k[, options] )\n    Returns an array containing pseudorandom numbers drawn from a chi\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    k: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.chi( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.chi.assign( k, out )\n    Fills an array with pseudorandom numbers drawn from a chi distribution.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.chi.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.chi.factory( [k, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a chi distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.chi.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.chi.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.chi.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.chi.PRNG;\n\n\nrandom.array.chi.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.chi.seed;\n\n\nrandom.array.chi.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.chi.seedLength;\n\n\nrandom.array.chi.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.chi( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.chi.state\n    <Uint32Array>\n\n    > out = random.array.chi( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.chi( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.chi.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.chi( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.chi.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.chi.stateLength;\n\n\nrandom.array.chi.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.chi.byteLength;\n\n    See Also\n    --------\n    base.random.chi, random.strided.chi\n","random.array.chi.assign":"\nrandom.array.chi.assign( k, out )\n    Fills an array with pseudorandom numbers drawn from a chi distribution.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.chi.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.chi.factory":"\nrandom.array.chi.factory( [k, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a chi distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.chi.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.chi.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.chi.PRNG":"\nrandom.array.chi.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.chi.PRNG;","random.array.chi.seed":"\nrandom.array.chi.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.chi.seed;","random.array.chi.seedLength":"\nrandom.array.chi.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.chi.seedLength;","random.array.chi.state":"\nrandom.array.chi.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.chi( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.chi.state\n    <Uint32Array>\n\n    > out = random.array.chi( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.chi( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.chi.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.chi( 3, 2.0 )\n    <Float64Array>","random.array.chi.stateLength":"\nrandom.array.chi.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.chi.stateLength;","random.array.chi.byteLength":"\nrandom.array.chi.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.chi.byteLength;\n\n    See Also\n    --------\n    base.random.chi, random.strided.chi","random.array.chisquare":"\nrandom.array.chisquare( len, k[, options] )\n    Returns an array containing pseudorandom numbers drawn from a chi-square\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    k: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.chisquare( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.chisquare.assign( k, out )\n    Fills an array with pseudorandom numbers drawn from a chi-square\n    distribution.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.chisquare.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.chisquare.factory( [k, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a chi-square distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.chisquare.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.chisquare.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.chisquare.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.chisquare.PRNG;\n\n\nrandom.array.chisquare.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.chisquare.seed;\n\n\nrandom.array.chisquare.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.chisquare.seedLength;\n\n\nrandom.array.chisquare.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.chisquare( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.chisquare.state\n    <Uint32Array>\n\n    > out = random.array.chisquare( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.chisquare( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.chisquare.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.chisquare( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.chisquare.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.chisquare.stateLength;\n\n\nrandom.array.chisquare.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.chisquare.byteLength;\n\n    See Also\n    --------\n    base.random.chisquare, random.strided.chisquare\n","random.array.chisquare.assign":"\nrandom.array.chisquare.assign( k, out )\n    Fills an array with pseudorandom numbers drawn from a chi-square\n    distribution.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.chisquare.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.chisquare.factory":"\nrandom.array.chisquare.factory( [k, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a chi-square distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.chisquare.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.chisquare.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.chisquare.PRNG":"\nrandom.array.chisquare.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.chisquare.PRNG;","random.array.chisquare.seed":"\nrandom.array.chisquare.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.chisquare.seed;","random.array.chisquare.seedLength":"\nrandom.array.chisquare.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.chisquare.seedLength;","random.array.chisquare.state":"\nrandom.array.chisquare.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.chisquare( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.chisquare.state\n    <Uint32Array>\n\n    > out = random.array.chisquare( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.chisquare( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.chisquare.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.chisquare( 3, 2.0 )\n    <Float64Array>","random.array.chisquare.stateLength":"\nrandom.array.chisquare.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.chisquare.stateLength;","random.array.chisquare.byteLength":"\nrandom.array.chisquare.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.chisquare.byteLength;\n\n    See Also\n    --------\n    base.random.chisquare, random.strided.chisquare","random.array.cosine":"\nrandom.array.cosine( len, mu, s[, options] )\n    Returns an array containing pseudorandom numbers drawn from a raised cosine\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    mu: number\n        Mean.\n\n    s: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.cosine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.cosine.assign( mu, s, out )\n    Fills an array with pseudorandom numbers drawn from a raised cosine\n    distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Mean.\n\n    s: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.cosine.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.cosine.factory( [mu, s, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a raised cosine distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Mean.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.cosine.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.cosine.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.cosine.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.cosine.PRNG;\n\n\nrandom.array.cosine.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.cosine.seed;\n\n\nrandom.array.cosine.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.cosine.seedLength;\n\n\nrandom.array.cosine.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.cosine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.cosine.state\n    <Uint32Array>\n\n    > out = random.array.cosine( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.cosine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.cosine.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.cosine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.cosine.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.cosine.stateLength;\n\n\nrandom.array.cosine.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.cosine.byteLength;\n\n    See Also\n    --------\n    base.random.cosine, random.strided.cosine\n","random.array.cosine.assign":"\nrandom.array.cosine.assign( mu, s, out )\n    Fills an array with pseudorandom numbers drawn from a raised cosine\n    distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Mean.\n\n    s: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.cosine.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.cosine.factory":"\nrandom.array.cosine.factory( [mu, s, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a raised cosine distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Mean.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.cosine.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.cosine.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.cosine.PRNG":"\nrandom.array.cosine.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.cosine.PRNG;","random.array.cosine.seed":"\nrandom.array.cosine.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.cosine.seed;","random.array.cosine.seedLength":"\nrandom.array.cosine.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.cosine.seedLength;","random.array.cosine.state":"\nrandom.array.cosine.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.cosine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.cosine.state\n    <Uint32Array>\n\n    > out = random.array.cosine( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.cosine( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.cosine.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.cosine( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.cosine.stateLength":"\nrandom.array.cosine.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.cosine.stateLength;","random.array.cosine.byteLength":"\nrandom.array.cosine.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.cosine.byteLength;\n\n    See Also\n    --------\n    base.random.cosine, random.strided.cosine","random.array.discreteUniform":"\nrandom.array.discreteUniform( len, a, b[, options] )\n    Returns an array containing pseudorandom numbers drawn from a discrete\n    uniform distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.discreteUniform( 3, -10, 10 )\n    <Float64Array>\n\n\nrandom.array.discreteUniform.assign( a, b, out )\n    Fills an array with pseudorandom numbers drawn from a discrete uniform\n    distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.discreteUniform.assign( -10, 10, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.discreteUniform.factory( [a, b, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a discrete uniform distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom integers. If provided, the `state` and `seed`\n        options are ignored. In order to seed the returned pseudorandom number\n        generator, one must seed the provided `prng` (assuming the provided\n        `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n        properties specifying the minimum and maximum possible pseudorandom\n        integers.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.discreteUniform.factory();\n    > var out = fcn( 3, -10, 10 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.discreteUniform.factory( -10, 10 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.discreteUniform.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.discreteUniform.PRNG;\n\n\nrandom.array.discreteUniform.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.discreteUniform.seed;\n\n\nrandom.array.discreteUniform.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.discreteUniform.seedLength;\n\n\nrandom.array.discreteUniform.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.discreteUniform( 3, -10, 10 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.discreteUniform.state\n    <Uint32Array>\n\n    > out = random.array.discreteUniform( 3, -10, 10 )\n    <Float64Array>\n    > out = random.array.discreteUniform( 3, -10, 10 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.discreteUniform.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.discreteUniform( 3, -10, 10 )\n    <Float64Array>\n\n\nrandom.array.discreteUniform.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.discreteUniform.stateLength;\n\n\nrandom.array.discreteUniform.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.discreteUniform.byteLength;\n\n    See Also\n    --------\n    random.array.uniform, base.random.discreteUniform, random.strided.discreteUniform\n","random.array.discreteUniform.assign":"\nrandom.array.discreteUniform.assign( a, b, out )\n    Fills an array with pseudorandom numbers drawn from a discrete uniform\n    distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.discreteUniform.assign( -10, 10, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.discreteUniform.factory":"\nrandom.array.discreteUniform.factory( [a, b, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a discrete uniform distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom integers. If provided, the `state` and `seed`\n        options are ignored. In order to seed the returned pseudorandom number\n        generator, one must seed the provided `prng` (assuming the provided\n        `prng` is seedable). The provided PRNG must have `MIN` and `MAX`\n        properties specifying the minimum and maximum possible pseudorandom\n        integers.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.discreteUniform.factory();\n    > var out = fcn( 3, -10, 10 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.discreteUniform.factory( -10, 10 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.discreteUniform.PRNG":"\nrandom.array.discreteUniform.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.discreteUniform.PRNG;","random.array.discreteUniform.seed":"\nrandom.array.discreteUniform.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.discreteUniform.seed;","random.array.discreteUniform.seedLength":"\nrandom.array.discreteUniform.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.discreteUniform.seedLength;","random.array.discreteUniform.state":"\nrandom.array.discreteUniform.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.discreteUniform( 3, -10, 10 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.discreteUniform.state\n    <Uint32Array>\n\n    > out = random.array.discreteUniform( 3, -10, 10 )\n    <Float64Array>\n    > out = random.array.discreteUniform( 3, -10, 10 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.discreteUniform.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.discreteUniform( 3, -10, 10 )\n    <Float64Array>","random.array.discreteUniform.stateLength":"\nrandom.array.discreteUniform.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.discreteUniform.stateLength;","random.array.discreteUniform.byteLength":"\nrandom.array.discreteUniform.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.discreteUniform.byteLength;\n\n    See Also\n    --------\n    random.array.uniform, base.random.discreteUniform, random.strided.discreteUniform","random.array.erlang":"\nrandom.array.erlang( len, k, lambda[, options] )\n    Returns an array containing pseudorandom numbers drawn from an Erlang\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    k: number\n        Shape parameter.\n\n    lambda: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.erlang( 3, 2, 5.0 )\n    <Float64Array>\n\n\nrandom.array.erlang.assign( k, lambda, out )\n    Fills an array with pseudorandom numbers drawn from an Erlang distribution.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    lambda: number\n        Rate parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.erlang.assign( 2, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.erlang.factory( [k, lambda, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an Erlang distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Shape parameter.\n\n    lambda: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.erlang.factory();\n    > var out = fcn( 3, 2, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.erlang.factory( 2, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.erlang.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.erlang.PRNG;\n\n\nrandom.array.erlang.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.erlang.seed;\n\n\nrandom.array.erlang.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.erlang.seedLength;\n\n\nrandom.array.erlang.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.erlang( 3, 2, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.erlang.state\n    <Uint32Array>\n\n    > out = random.array.erlang( 3, 2, 5.0 )\n    <Float64Array>\n    > out = random.array.erlang( 3, 2, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.erlang.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.erlang( 3, 2, 5.0 )\n    <Float64Array>\n\n\nrandom.array.erlang.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.erlang.stateLength;\n\n\nrandom.array.erlang.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.erlang.byteLength;\n\n    See Also\n    --------\n    base.random.erlang\n","random.array.erlang.assign":"\nrandom.array.erlang.assign( k, lambda, out )\n    Fills an array with pseudorandom numbers drawn from an Erlang distribution.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    lambda: number\n        Rate parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.erlang.assign( 2, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.erlang.factory":"\nrandom.array.erlang.factory( [k, lambda, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an Erlang distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Shape parameter.\n\n    lambda: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.erlang.factory();\n    > var out = fcn( 3, 2, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.erlang.factory( 2, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.erlang.PRNG":"\nrandom.array.erlang.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.erlang.PRNG;","random.array.erlang.seed":"\nrandom.array.erlang.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.erlang.seed;","random.array.erlang.seedLength":"\nrandom.array.erlang.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.erlang.seedLength;","random.array.erlang.state":"\nrandom.array.erlang.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.erlang( 3, 2, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.erlang.state\n    <Uint32Array>\n\n    > out = random.array.erlang( 3, 2, 5.0 )\n    <Float64Array>\n    > out = random.array.erlang( 3, 2, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.erlang.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.erlang( 3, 2, 5.0 )\n    <Float64Array>","random.array.erlang.stateLength":"\nrandom.array.erlang.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.erlang.stateLength;","random.array.erlang.byteLength":"\nrandom.array.erlang.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.erlang.byteLength;\n\n    See Also\n    --------\n    base.random.erlang","random.array.exponential":"\nrandom.array.exponential( len, lambda[, options] )\n    Returns an array containing pseudorandom numbers drawn from an exponential\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    lambda: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.exponential( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.exponential.assign( lambda, out )\n    Fills an array with pseudorandom numbers drawn from an exponential\n    distribution.\n\n    Parameters\n    ----------\n    lambda: number\n        Rate parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.exponential.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.exponential.factory( [lambda, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an exponential distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    lambda: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.exponential.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.exponential.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.exponential.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.exponential.PRNG;\n\n\nrandom.array.exponential.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.exponential.seed;\n\n\nrandom.array.exponential.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.exponential.seedLength;\n\n\nrandom.array.exponential.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.exponential( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.exponential.state\n    <Uint32Array>\n\n    > out = random.array.exponential( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.exponential( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.exponential.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.exponential( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.exponential.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.exponential.stateLength;\n\n\nrandom.array.exponential.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.exponential.byteLength;\n\n    See Also\n    --------\n    base.random.exponential, random.strided.exponential\n","random.array.exponential.assign":"\nrandom.array.exponential.assign( lambda, out )\n    Fills an array with pseudorandom numbers drawn from an exponential\n    distribution.\n\n    Parameters\n    ----------\n    lambda: number\n        Rate parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.exponential.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.exponential.factory":"\nrandom.array.exponential.factory( [lambda, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an exponential distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    lambda: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.exponential.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.exponential.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.exponential.PRNG":"\nrandom.array.exponential.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.exponential.PRNG;","random.array.exponential.seed":"\nrandom.array.exponential.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.exponential.seed;","random.array.exponential.seedLength":"\nrandom.array.exponential.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.exponential.seedLength;","random.array.exponential.state":"\nrandom.array.exponential.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.exponential( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.exponential.state\n    <Uint32Array>\n\n    > out = random.array.exponential( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.exponential( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.exponential.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.exponential( 3, 2.0 )\n    <Float64Array>","random.array.exponential.stateLength":"\nrandom.array.exponential.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.exponential.stateLength;","random.array.exponential.byteLength":"\nrandom.array.exponential.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.exponential.byteLength;\n\n    See Also\n    --------\n    base.random.exponential, random.strided.exponential","random.array.f":"\nrandom.array.f( len, d1, d2[, options] )\n    Returns an array containing pseudorandom numbers drawn from an F\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    d1: number\n        Degrees of freedom.\n\n    d2: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.f( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.f.assign( d1, d2, out )\n    Fills an array with pseudorandom numbers drawn from an F distribution.\n\n    Parameters\n    ----------\n    d1: number\n        Degrees of freedom.\n\n    d2: number\n        Degrees of freedom.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.f.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.f.factory( [d1, d2, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an F distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    d1: number (optional)\n        Degrees of freedom.\n\n    d2: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.f.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.f.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.f.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.f.PRNG;\n\n\nrandom.array.f.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.f.seed;\n\n\nrandom.array.f.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.f.seedLength;\n\n\nrandom.array.f.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.f( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.f.state\n    <Uint32Array>\n\n    > out = random.array.f( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.f( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.f.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.f( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.f.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.f.stateLength;\n\n\nrandom.array.f.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.f.byteLength;\n\n    See Also\n    --------\n    base.random.f\n","random.array.f.assign":"\nrandom.array.f.assign( d1, d2, out )\n    Fills an array with pseudorandom numbers drawn from an F distribution.\n\n    Parameters\n    ----------\n    d1: number\n        Degrees of freedom.\n\n    d2: number\n        Degrees of freedom.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.f.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.f.factory":"\nrandom.array.f.factory( [d1, d2, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an F distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    d1: number (optional)\n        Degrees of freedom.\n\n    d2: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.f.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.f.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.f.PRNG":"\nrandom.array.f.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.f.PRNG;","random.array.f.seed":"\nrandom.array.f.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.f.seed;","random.array.f.seedLength":"\nrandom.array.f.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.f.seedLength;","random.array.f.state":"\nrandom.array.f.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.f( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.f.state\n    <Uint32Array>\n\n    > out = random.array.f( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.f( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.f.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.f( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.f.stateLength":"\nrandom.array.f.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.f.stateLength;","random.array.f.byteLength":"\nrandom.array.f.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.f.byteLength;\n\n    See Also\n    --------\n    base.random.f","random.array.frechet":"\nrandom.array.frechet( len, alpha, s, m[, options] )\n    Returns an array containing pseudorandom numbers drawn from a Fréchet\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    alpha: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n\nrandom.array.frechet.assign( alpha, s, m, out )\n    Fills an array with pseudorandom numbers drawn from a Fréchet distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.frechet.assign( 2.0, 5.0, 3.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.frechet.factory( [alpha, s, m, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Fréchet distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        Shape parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    m: number (optional)\n        Location parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.frechet.factory();\n    > var out = fcn( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.frechet.factory( 2.0, 5.0, 3.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.frechet.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.frechet.PRNG;\n\n\nrandom.array.frechet.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.frechet.seed;\n\n\nrandom.array.frechet.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.frechet.seedLength;\n\n\nrandom.array.frechet.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.frechet.state\n    <Uint32Array>\n\n    > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n    > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.frechet.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n\nrandom.array.frechet.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.frechet.stateLength;\n\n\nrandom.array.frechet.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.frechet.byteLength;\n\n    See Also\n    --------\n    base.random.frechet\n","random.array.frechet.assign":"\nrandom.array.frechet.assign( alpha, s, m, out )\n    Fills an array with pseudorandom numbers drawn from a Fréchet distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.frechet.assign( 2.0, 5.0, 3.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.frechet.factory":"\nrandom.array.frechet.factory( [alpha, s, m, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Fréchet distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        Shape parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    m: number (optional)\n        Location parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.frechet.factory();\n    > var out = fcn( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.frechet.factory( 2.0, 5.0, 3.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.frechet.PRNG":"\nrandom.array.frechet.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.frechet.PRNG;","random.array.frechet.seed":"\nrandom.array.frechet.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.frechet.seed;","random.array.frechet.seedLength":"\nrandom.array.frechet.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.frechet.seedLength;","random.array.frechet.state":"\nrandom.array.frechet.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.frechet.state\n    <Uint32Array>\n\n    > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n    > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.frechet.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.frechet( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>","random.array.frechet.stateLength":"\nrandom.array.frechet.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.frechet.stateLength;","random.array.frechet.byteLength":"\nrandom.array.frechet.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.frechet.byteLength;\n\n    See Also\n    --------\n    base.random.frechet","random.array.gamma":"\nrandom.array.gamma( len, alpha, beta[, options] )\n    Returns an array containing pseudorandom numbers drawn from a gamma\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    alpha: number\n        Shape parameter.\n\n    beta: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.gamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.gamma.assign( alpha, beta, out )\n    Fills an array with pseudorandom numbers drawn from a gamma distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        Shape parameter.\n\n    beta: number\n        Rate parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.gamma.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.gamma.factory( [alpha, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a gamma distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        Shape parameter.\n\n    beta: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.gamma.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.gamma.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.gamma.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.gamma.PRNG;\n\n\nrandom.array.gamma.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.gamma.seed;\n\n\nrandom.array.gamma.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.gamma.seedLength;\n\n\nrandom.array.gamma.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.gamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.gamma.state\n    <Uint32Array>\n\n    > out = random.array.gamma( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.gamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.gamma.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.gamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.gamma.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.gamma.stateLength;\n\n\nrandom.array.gamma.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.gamma.byteLength;\n\n    See Also\n    --------\n    base.random.gamma, random.strided.gamma\n","random.array.gamma.assign":"\nrandom.array.gamma.assign( alpha, beta, out )\n    Fills an array with pseudorandom numbers drawn from a gamma distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        Shape parameter.\n\n    beta: number\n        Rate parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.gamma.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.gamma.factory":"\nrandom.array.gamma.factory( [alpha, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a gamma distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        Shape parameter.\n\n    beta: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.gamma.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.gamma.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.gamma.PRNG":"\nrandom.array.gamma.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.gamma.PRNG;","random.array.gamma.seed":"\nrandom.array.gamma.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.gamma.seed;","random.array.gamma.seedLength":"\nrandom.array.gamma.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.gamma.seedLength;","random.array.gamma.state":"\nrandom.array.gamma.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.gamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.gamma.state\n    <Uint32Array>\n\n    > out = random.array.gamma( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.gamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.gamma.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.gamma( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.gamma.stateLength":"\nrandom.array.gamma.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.gamma.stateLength;","random.array.gamma.byteLength":"\nrandom.array.gamma.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.gamma.byteLength;\n\n    See Also\n    --------\n    base.random.gamma, random.strided.gamma","random.array.geometric":"\nrandom.array.geometric( len, p[, options] )\n    Returns an array containing pseudorandom numbers drawn from a geometric\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.geometric( 3, 0.01 )\n    <Float64Array>\n\n\nrandom.array.geometric.assign( p, out )\n    Fills an array with pseudorandom numbers drawn from a geometric\n    distribution.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.geometric.assign( 0.01, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.geometric.factory( [p, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a geometric distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.geometric.factory();\n    > var out = fcn( 3, 0.01 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.geometric.factory( 0.01 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.geometric.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.geometric.PRNG;\n\n\nrandom.array.geometric.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.geometric.seed;\n\n\nrandom.array.geometric.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.geometric.seedLength;\n\n\nrandom.array.geometric.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.geometric( 3, 0.01 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.geometric.state\n    <Uint32Array>\n\n    > out = random.array.geometric( 3, 0.01 )\n    <Float64Array>\n    > out = random.array.geometric( 3, 0.01 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.geometric.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.geometric( 3, 0.01 )\n    <Float64Array>\n\n\nrandom.array.geometric.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.geometric.stateLength;\n\n\nrandom.array.geometric.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.geometric.byteLength;\n\n    See Also\n    --------\n    base.random.geometric, random.strided.geometric\n","random.array.geometric.assign":"\nrandom.array.geometric.assign( p, out )\n    Fills an array with pseudorandom numbers drawn from a geometric\n    distribution.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.geometric.assign( 0.01, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.geometric.factory":"\nrandom.array.geometric.factory( [p, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a geometric distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.geometric.factory();\n    > var out = fcn( 3, 0.01 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.geometric.factory( 0.01 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.geometric.PRNG":"\nrandom.array.geometric.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.geometric.PRNG;","random.array.geometric.seed":"\nrandom.array.geometric.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.geometric.seed;","random.array.geometric.seedLength":"\nrandom.array.geometric.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.geometric.seedLength;","random.array.geometric.state":"\nrandom.array.geometric.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.geometric( 3, 0.01 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.geometric.state\n    <Uint32Array>\n\n    > out = random.array.geometric( 3, 0.01 )\n    <Float64Array>\n    > out = random.array.geometric( 3, 0.01 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.geometric.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.geometric( 3, 0.01 )\n    <Float64Array>","random.array.geometric.stateLength":"\nrandom.array.geometric.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.geometric.stateLength;","random.array.geometric.byteLength":"\nrandom.array.geometric.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.geometric.byteLength;\n\n    See Also\n    --------\n    base.random.geometric, random.strided.geometric","random.array.gumbel":"\nrandom.array.gumbel( len, mu, beta[, options] )\n    Returns an array containing pseudorandom numbers drawn from a Gumbel\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    mu: number\n        Mean.\n\n    beta: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.gumbel( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.gumbel.assign( mu, beta, out )\n    Fills an array with pseudorandom numbers drawn from a Gumbel distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Mean.\n\n    beta: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.gumbel.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.gumbel.factory( [mu, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Gumbel distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Mean.\n\n    beta: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.gumbel.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.gumbel.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.gumbel.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.gumbel.PRNG;\n\n\nrandom.array.gumbel.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.gumbel.seed;\n\n\nrandom.array.gumbel.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.gumbel.seedLength;\n\n\nrandom.array.gumbel.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.gumbel( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.gumbel.state\n    <Uint32Array>\n\n    > out = random.array.gumbel( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.gumbel( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.gumbel.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.gumbel( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.gumbel.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.gumbel.stateLength;\n\n\nrandom.array.gumbel.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.gumbel.byteLength;\n\n    See Also\n    --------\n    base.random.gumbel\n","random.array.gumbel.assign":"\nrandom.array.gumbel.assign( mu, beta, out )\n    Fills an array with pseudorandom numbers drawn from a Gumbel distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Mean.\n\n    beta: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.gumbel.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.gumbel.factory":"\nrandom.array.gumbel.factory( [mu, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Gumbel distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Mean.\n\n    beta: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.gumbel.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.gumbel.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.gumbel.PRNG":"\nrandom.array.gumbel.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.gumbel.PRNG;","random.array.gumbel.seed":"\nrandom.array.gumbel.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.gumbel.seed;","random.array.gumbel.seedLength":"\nrandom.array.gumbel.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.gumbel.seedLength;","random.array.gumbel.state":"\nrandom.array.gumbel.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.gumbel( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.gumbel.state\n    <Uint32Array>\n\n    > out = random.array.gumbel( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.gumbel( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.gumbel.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.gumbel( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.gumbel.stateLength":"\nrandom.array.gumbel.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.gumbel.stateLength;","random.array.gumbel.byteLength":"\nrandom.array.gumbel.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.gumbel.byteLength;\n\n    See Also\n    --------\n    base.random.gumbel","random.array.hypergeometric":"\nrandom.array.hypergeometric( len, N, K, n[, options] )\n    Returns an array containing pseudorandom numbers drawn from a hypergeometric\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    N: number\n        Population size.\n\n    K: number\n        Subpopulation size.\n\n    n: number\n        Number of draws.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.hypergeometric( 3, 20, 10, 7 )\n    <Float64Array>\n\n\nrandom.array.hypergeometric.assign( N, K, n, out )\n    Fills an array with pseudorandom numbers drawn from a hypergeometric\n    distribution.\n\n    Parameters\n    ----------\n    N: number\n        Population size.\n\n    K: number\n        Subpopulation size.\n\n    n: number\n        Number of draws.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.hypergeometric.assign( 20, 10, 7, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.hypergeometric.factory( [N, K, n, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a hypergeometric distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    N: number (optional)\n        Population size.\n\n    K: number (optional)\n        Subpopulation size.\n\n    n: number (optional)\n        Number of draws.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.hypergeometric.factory();\n    > var out = fcn( 3, 20, 10, 7 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.hypergeometric.factory( 20, 10, 7 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.hypergeometric.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.hypergeometric.PRNG;\n\n\nrandom.array.hypergeometric.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.hypergeometric.seed;\n\n\nrandom.array.hypergeometric.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.hypergeometric.seedLength;\n\n\nrandom.array.hypergeometric.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.hypergeometric( 3, 20, 10, 7 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.hypergeometric.state\n    <Uint32Array>\n\n    > out = random.array.hypergeometric( 3, 20, 10, 7 )\n    <Float64Array>\n    > out = random.array.hypergeometric( 3, 20, 10, 7 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.hypergeometric.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.hypergeometric( 3, 20, 10, 7 )\n    <Float64Array>\n\n\nrandom.array.hypergeometric.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.hypergeometric.stateLength;\n\n\nrandom.array.hypergeometric.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.hypergeometric.byteLength;\n\n    See Also\n    --------\n    base.random.hypergeometric\n","random.array.hypergeometric.assign":"\nrandom.array.hypergeometric.assign( N, K, n, out )\n    Fills an array with pseudorandom numbers drawn from a hypergeometric\n    distribution.\n\n    Parameters\n    ----------\n    N: number\n        Population size.\n\n    K: number\n        Subpopulation size.\n\n    n: number\n        Number of draws.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.hypergeometric.assign( 20, 10, 7, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.hypergeometric.factory":"\nrandom.array.hypergeometric.factory( [N, K, n, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a hypergeometric distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    N: number (optional)\n        Population size.\n\n    K: number (optional)\n        Subpopulation size.\n\n    n: number (optional)\n        Number of draws.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.hypergeometric.factory();\n    > var out = fcn( 3, 20, 10, 7 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.hypergeometric.factory( 20, 10, 7 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.hypergeometric.PRNG":"\nrandom.array.hypergeometric.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.hypergeometric.PRNG;","random.array.hypergeometric.seed":"\nrandom.array.hypergeometric.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.hypergeometric.seed;","random.array.hypergeometric.seedLength":"\nrandom.array.hypergeometric.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.hypergeometric.seedLength;","random.array.hypergeometric.state":"\nrandom.array.hypergeometric.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.hypergeometric( 3, 20, 10, 7 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.hypergeometric.state\n    <Uint32Array>\n\n    > out = random.array.hypergeometric( 3, 20, 10, 7 )\n    <Float64Array>\n    > out = random.array.hypergeometric( 3, 20, 10, 7 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.hypergeometric.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.hypergeometric( 3, 20, 10, 7 )\n    <Float64Array>","random.array.hypergeometric.stateLength":"\nrandom.array.hypergeometric.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.hypergeometric.stateLength;","random.array.hypergeometric.byteLength":"\nrandom.array.hypergeometric.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.hypergeometric.byteLength;\n\n    See Also\n    --------\n    base.random.hypergeometric","random.array.invgamma":"\nrandom.array.invgamma( len, alpha, beta[, options] )\n    Returns an array containing pseudorandom numbers drawn from an inverse gamma\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    alpha: number\n        Shape parameter.\n\n    beta: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.invgamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.invgamma.assign( alpha, beta, out )\n    Fills an array with pseudorandom numbers drawn from an inverse gamma\n    distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        Shape parameter.\n\n    beta: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.invgamma.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.invgamma.factory( [alpha, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an inverse gamma distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        Shape parameter.\n\n    beta: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.invgamma.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.invgamma.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.invgamma.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.invgamma.PRNG;\n\n\nrandom.array.invgamma.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.invgamma.seed;\n\n\nrandom.array.invgamma.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.invgamma.seedLength;\n\n\nrandom.array.invgamma.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.invgamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.invgamma.state\n    <Uint32Array>\n\n    > out = random.array.invgamma( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.invgamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.invgamma.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.invgamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.invgamma.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.invgamma.stateLength;\n\n\nrandom.array.invgamma.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.invgamma.byteLength;\n\n    See Also\n    --------\n    base.random.invgamma, random.strided.invgamma\n","random.array.invgamma.assign":"\nrandom.array.invgamma.assign( alpha, beta, out )\n    Fills an array with pseudorandom numbers drawn from an inverse gamma\n    distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        Shape parameter.\n\n    beta: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.invgamma.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.invgamma.factory":"\nrandom.array.invgamma.factory( [alpha, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an inverse gamma distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        Shape parameter.\n\n    beta: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.invgamma.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.invgamma.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.invgamma.PRNG":"\nrandom.array.invgamma.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.invgamma.PRNG;","random.array.invgamma.seed":"\nrandom.array.invgamma.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.invgamma.seed;","random.array.invgamma.seedLength":"\nrandom.array.invgamma.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.invgamma.seedLength;","random.array.invgamma.state":"\nrandom.array.invgamma.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.invgamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.invgamma.state\n    <Uint32Array>\n\n    > out = random.array.invgamma( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.invgamma( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.invgamma.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.invgamma( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.invgamma.stateLength":"\nrandom.array.invgamma.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.invgamma.stateLength;","random.array.invgamma.byteLength":"\nrandom.array.invgamma.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.invgamma.byteLength;\n\n    See Also\n    --------\n    base.random.invgamma, random.strided.invgamma","random.array.kumaraswamy":"\nrandom.array.kumaraswamy( len, a, b[, options] )\n    Returns an array containing pseudorandom numbers drawn from Kumaraswamy's\n    double bounded distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.kumaraswamy.assign( a, b, out )\n    Fills an array with pseudorandom numbers drawn from Kumaraswamy's double\n    bounded distribution.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.kumaraswamy.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.kumaraswamy.factory( [a, b, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from Kumaraswamy's double bounded distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    a: number (optional)\n        First shape parameter.\n\n    b: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.kumaraswamy.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.kumaraswamy.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.kumaraswamy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.kumaraswamy.PRNG;\n\n\nrandom.array.kumaraswamy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.kumaraswamy.seed;\n\n\nrandom.array.kumaraswamy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.kumaraswamy.seedLength;\n\n\nrandom.array.kumaraswamy.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.kumaraswamy.state\n    <Uint32Array>\n\n    > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.kumaraswamy.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.kumaraswamy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.kumaraswamy.stateLength;\n\n\nrandom.array.kumaraswamy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.kumaraswamy.byteLength;\n\n    See Also\n    --------\n    base.random.kumaraswamy\n","random.array.kumaraswamy.assign":"\nrandom.array.kumaraswamy.assign( a, b, out )\n    Fills an array with pseudorandom numbers drawn from Kumaraswamy's double\n    bounded distribution.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.kumaraswamy.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.kumaraswamy.factory":"\nrandom.array.kumaraswamy.factory( [a, b, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from Kumaraswamy's double bounded distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    a: number (optional)\n        First shape parameter.\n\n    b: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.kumaraswamy.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.kumaraswamy.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.kumaraswamy.PRNG":"\nrandom.array.kumaraswamy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.kumaraswamy.PRNG;","random.array.kumaraswamy.seed":"\nrandom.array.kumaraswamy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.kumaraswamy.seed;","random.array.kumaraswamy.seedLength":"\nrandom.array.kumaraswamy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.kumaraswamy.seedLength;","random.array.kumaraswamy.state":"\nrandom.array.kumaraswamy.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.kumaraswamy.state\n    <Uint32Array>\n\n    > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.kumaraswamy.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.kumaraswamy( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.kumaraswamy.stateLength":"\nrandom.array.kumaraswamy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.kumaraswamy.stateLength;","random.array.kumaraswamy.byteLength":"\nrandom.array.kumaraswamy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.kumaraswamy.byteLength;\n\n    See Also\n    --------\n    base.random.kumaraswamy","random.array.laplace":"\nrandom.array.laplace( len, mu, b[, options] )\n    Returns an array containing pseudorandom numbers drawn from a Laplace\n    (double exponential) distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    mu: number\n        Mean.\n\n    b: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.laplace( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.laplace.assign( mu, b, out )\n    Fills an array with pseudorandom numbers drawn from a Laplace (double\n    exponential) distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Mean.\n\n    b: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.laplace.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.laplace.factory( [mu, b, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Laplace (double exponential) distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Mean.\n\n    b: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.laplace.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.laplace.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.laplace.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.laplace.PRNG;\n\n\nrandom.array.laplace.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.laplace.seed;\n\n\nrandom.array.laplace.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.laplace.seedLength;\n\n\nrandom.array.laplace.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.laplace( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.laplace.state\n    <Uint32Array>\n\n    > out = random.array.laplace( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.laplace( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.laplace.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.laplace( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.laplace.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.laplace.stateLength;\n\n\nrandom.array.laplace.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.laplace.byteLength;\n\n    See Also\n    --------\n    base.random.laplace\n","random.array.laplace.assign":"\nrandom.array.laplace.assign( mu, b, out )\n    Fills an array with pseudorandom numbers drawn from a Laplace (double\n    exponential) distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Mean.\n\n    b: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.laplace.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.laplace.factory":"\nrandom.array.laplace.factory( [mu, b, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Laplace (double exponential) distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Mean.\n\n    b: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.laplace.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.laplace.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.laplace.PRNG":"\nrandom.array.laplace.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.laplace.PRNG;","random.array.laplace.seed":"\nrandom.array.laplace.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.laplace.seed;","random.array.laplace.seedLength":"\nrandom.array.laplace.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.laplace.seedLength;","random.array.laplace.state":"\nrandom.array.laplace.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.laplace( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.laplace.state\n    <Uint32Array>\n\n    > out = random.array.laplace( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.laplace( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.laplace.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.laplace( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.laplace.stateLength":"\nrandom.array.laplace.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.laplace.stateLength;","random.array.laplace.byteLength":"\nrandom.array.laplace.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.laplace.byteLength;\n\n    See Also\n    --------\n    base.random.laplace","random.array.levy":"\nrandom.array.levy( len, mu, c[, options] )\n    Returns an array containing pseudorandom numbers drawn from a Lévy\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    mu: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.levy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.levy.assign( mu, c, out )\n    Fills an array with pseudorandom numbers drawn from a Lévy distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.levy.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.levy.factory( [mu, c, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Lévy distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Location parameter.\n\n    c: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.levy.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.levy.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.levy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.levy.PRNG;\n\n\nrandom.array.levy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.levy.seed;\n\n\nrandom.array.levy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.levy.seedLength;\n\n\nrandom.array.levy.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.levy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.levy.state\n    <Uint32Array>\n\n    > out = random.array.levy( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.levy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.levy.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.levy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.levy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.levy.stateLength;\n\n\nrandom.array.levy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.levy.byteLength;\n\n    See Also\n    --------\n    base.random.levy\n","random.array.levy.assign":"\nrandom.array.levy.assign( mu, c, out )\n    Fills an array with pseudorandom numbers drawn from a Lévy distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Location parameter.\n\n    c: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.levy.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.levy.factory":"\nrandom.array.levy.factory( [mu, c, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Lévy distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Location parameter.\n\n    c: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.levy.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.levy.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.levy.PRNG":"\nrandom.array.levy.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.levy.PRNG;","random.array.levy.seed":"\nrandom.array.levy.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.levy.seed;","random.array.levy.seedLength":"\nrandom.array.levy.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.levy.seedLength;","random.array.levy.state":"\nrandom.array.levy.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.levy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.levy.state\n    <Uint32Array>\n\n    > out = random.array.levy( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.levy( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.levy.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.levy( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.levy.stateLength":"\nrandom.array.levy.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.levy.stateLength;","random.array.levy.byteLength":"\nrandom.array.levy.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.levy.byteLength;\n\n    See Also\n    --------\n    base.random.levy","random.array.logistic":"\nrandom.array.logistic( len, mu, s[, options] )\n    Returns an array containing pseudorandom numbers drawn from a logistic\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    mu: number\n        Mean parameter.\n\n    s: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.logistic( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.logistic.assign( mu, s, out )\n    Fills an array with pseudorandom numbers drawn from a logistic distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Mean parameter.\n\n    s: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.logistic.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.logistic.factory( [mu, s, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a logistic distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Mean parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.logistic.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.logistic.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.logistic.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.logistic.PRNG;\n\n\nrandom.array.logistic.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.logistic.seed;\n\n\nrandom.array.logistic.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.logistic.seedLength;\n\n\nrandom.array.logistic.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.logistic( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.logistic.state\n    <Uint32Array>\n\n    > out = random.array.logistic( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.logistic( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.logistic.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.logistic( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.logistic.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.logistic.stateLength;\n\n\nrandom.array.logistic.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.logistic.byteLength;\n\n    See Also\n    --------\n    base.random.logistic\n","random.array.logistic.assign":"\nrandom.array.logistic.assign( mu, s, out )\n    Fills an array with pseudorandom numbers drawn from a logistic distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Mean parameter.\n\n    s: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.logistic.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.logistic.factory":"\nrandom.array.logistic.factory( [mu, s, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a logistic distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Mean parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.logistic.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.logistic.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.logistic.PRNG":"\nrandom.array.logistic.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.logistic.PRNG;","random.array.logistic.seed":"\nrandom.array.logistic.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.logistic.seed;","random.array.logistic.seedLength":"\nrandom.array.logistic.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.logistic.seedLength;","random.array.logistic.state":"\nrandom.array.logistic.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.logistic( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.logistic.state\n    <Uint32Array>\n\n    > out = random.array.logistic( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.logistic( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.logistic.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.logistic( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.logistic.stateLength":"\nrandom.array.logistic.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.logistic.stateLength;","random.array.logistic.byteLength":"\nrandom.array.logistic.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.logistic.byteLength;\n\n    See Also\n    --------\n    base.random.logistic","random.array.lognormal":"\nrandom.array.lognormal( len, mu, sigma[, options] )\n    Returns an array containing pseudorandom numbers drawn from a lognormal\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    mu: number\n        Location parameter.\n\n    sigma: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.lognormal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.lognormal.assign( mu, sigma, out )\n    Fills an array with pseudorandom numbers drawn from a lognormal\n    distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Location parameter.\n\n    sigma: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.lognormal.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.lognormal.factory( [mu, sigma, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a lognormal distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Location parameter.\n\n    sigma: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.lognormal.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.lognormal.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.lognormal.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.lognormal.PRNG;\n\n\nrandom.array.lognormal.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.lognormal.seed;\n\n\nrandom.array.lognormal.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.lognormal.seedLength;\n\n\nrandom.array.lognormal.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.lognormal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.lognormal.state\n    <Uint32Array>\n\n    > out = random.array.lognormal( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.lognormal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.lognormal.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.lognormal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.lognormal.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.lognormal.stateLength;\n\n\nrandom.array.lognormal.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.lognormal.byteLength;\n\n    See Also\n    --------\n    base.random.lognormal, random.strided.lognormal\n","random.array.lognormal.assign":"\nrandom.array.lognormal.assign( mu, sigma, out )\n    Fills an array with pseudorandom numbers drawn from a lognormal\n    distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Location parameter.\n\n    sigma: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.lognormal.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.lognormal.factory":"\nrandom.array.lognormal.factory( [mu, sigma, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a lognormal distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Location parameter.\n\n    sigma: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.lognormal.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.lognormal.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.lognormal.PRNG":"\nrandom.array.lognormal.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.lognormal.PRNG;","random.array.lognormal.seed":"\nrandom.array.lognormal.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.lognormal.seed;","random.array.lognormal.seedLength":"\nrandom.array.lognormal.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.lognormal.seedLength;","random.array.lognormal.state":"\nrandom.array.lognormal.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.lognormal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.lognormal.state\n    <Uint32Array>\n\n    > out = random.array.lognormal( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.lognormal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.lognormal.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.lognormal( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.lognormal.stateLength":"\nrandom.array.lognormal.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.lognormal.stateLength;","random.array.lognormal.byteLength":"\nrandom.array.lognormal.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.lognormal.byteLength;\n\n    See Also\n    --------\n    base.random.lognormal, random.strided.lognormal","random.array.minstd":"\nrandom.array.minstd( len[, options] )\n    Returns an array containing pseudorandom integers on the interval\n    `[1, 2147483646]`.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.minstd( 3 )\n    <Float64Array>\n\n\nrandom.array.minstd.normalized( len[, options] )\n    Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.minstd.normalized( 3 )\n    <Float64Array>\n\n\nrandom.array.minstd.factory( [options] )\n    Returns a function for creating arrays containing pseudorandom numbers\n    generated using a linear congruential pseudorandom number generator (LCG).\n\n    The returned function and its attached `normalized` method accept the\n    following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.idtype: string (optional)\n        Default output array data type when generating integers. Default:\n        'float64'.\n\n    options.ndtype: string (optional)\n        Default output array data type when generating normalized numbers.\n        Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.minstd.factory();\n    > var out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.minstd.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.minstd.PRNG;\n\n\nrandom.array.minstd.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.minstd.seed;\n\n\nrandom.array.minstd.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.minstd.seedLength;\n\n\nrandom.array.minstd.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.minstd( 3 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.minstd.state;\n\n    > out = random.array.minstd( 3 )\n    <Float64Array>\n    > out = random.array.minstd( 3 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.minstd.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.minstd( 3 )\n    <Float64Array>\n\n\nrandom.array.minstd.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.minstd.stateLength;\n\n\nrandom.array.minstd.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.minstd.byteLength;\n\n    See Also\n    --------\n    random.array.minstdShuffle, random.array.randu, base.random.minstd, random.strided.minstd\n","random.array.minstd.normalized":"\nrandom.array.minstd.normalized( len[, options] )\n    Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.minstd.normalized( 3 )\n    <Float64Array>","random.array.minstd.factory":"\nrandom.array.minstd.factory( [options] )\n    Returns a function for creating arrays containing pseudorandom numbers\n    generated using a linear congruential pseudorandom number generator (LCG).\n\n    The returned function and its attached `normalized` method accept the\n    following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.idtype: string (optional)\n        Default output array data type when generating integers. Default:\n        'float64'.\n\n    options.ndtype: string (optional)\n        Default output array data type when generating normalized numbers.\n        Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.minstd.factory();\n    > var out = fcn( 3 )\n    <Float64Array>","random.array.minstd.PRNG":"\nrandom.array.minstd.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.minstd.PRNG;","random.array.minstd.seed":"\nrandom.array.minstd.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.minstd.seed;","random.array.minstd.seedLength":"\nrandom.array.minstd.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.minstd.seedLength;","random.array.minstd.state":"\nrandom.array.minstd.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.minstd( 3 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.minstd.state;\n\n    > out = random.array.minstd( 3 )\n    <Float64Array>\n    > out = random.array.minstd( 3 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.minstd.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.minstd( 3 )\n    <Float64Array>","random.array.minstd.stateLength":"\nrandom.array.minstd.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.minstd.stateLength;","random.array.minstd.byteLength":"\nrandom.array.minstd.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.minstd.byteLength;\n\n    See Also\n    --------\n    random.array.minstdShuffle, random.array.randu, base.random.minstd, random.strided.minstd","random.array.minstdShuffle":"\nrandom.array.minstdShuffle( len[, options] )\n    Returns an array containing pseudorandom integers on the interval\n    `[1, 2147483646]`.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.minstdShuffle( 3 )\n    <Float64Array>\n\n\nrandom.array.minstdShuffle.normalized( len[, options] )\n    Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.minstdShuffle.normalized( 3 )\n    <Float64Array>\n\n\nrandom.array.minstdShuffle.factory( [options] )\n    Returns a function for creating arrays containing pseudorandom numbers\n    generated using a linear congruential pseudorandom number generator (LCG)\n    whose output is shuffled.\n\n    The returned function and its attached `normalized` method accept the\n    following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.idtype: string (optional)\n        Default output array data type when generating integers. Default:\n        'float64'.\n\n    options.ndtype: string (optional)\n        Default output array data type when generating normalized numbers.\n        Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.minstdShuffle.factory();\n    > var out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.minstdShuffle.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.minstdShuffle.PRNG;\n\n\nrandom.array.minstdShuffle.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.minstdShuffle.seed;\n\n\nrandom.array.minstdShuffle.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.minstdShuffle.seedLength;\n\n\nrandom.array.minstdShuffle.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.minstdShuffle( 3 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.minstdShuffle.state;\n\n    > out = random.array.minstdShuffle( 3 )\n    <Float64Array>\n    > out = random.array.minstdShuffle( 3 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.minstdShuffle.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.minstdShuffle( 3 )\n    <Float64Array>\n\n\nrandom.array.minstdShuffle.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.minstdShuffle.stateLength;\n\n\nrandom.array.minstdShuffle.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.minstdShuffle.byteLength;\n\n    See Also\n    --------\n    random.array.minstd, random.array.randu, base.random.minstdShuffle, random.strided.minstdShuffle\n","random.array.minstdShuffle.normalized":"\nrandom.array.minstdShuffle.normalized( len[, options] )\n    Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.minstdShuffle.normalized( 3 )\n    <Float64Array>","random.array.minstdShuffle.factory":"\nrandom.array.minstdShuffle.factory( [options] )\n    Returns a function for creating arrays containing pseudorandom numbers\n    generated using a linear congruential pseudorandom number generator (LCG)\n    whose output is shuffled.\n\n    The returned function and its attached `normalized` method accept the\n    following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.idtype: string (optional)\n        Default output array data type when generating integers. Default:\n        'float64'.\n\n    options.ndtype: string (optional)\n        Default output array data type when generating normalized numbers.\n        Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.minstdShuffle.factory();\n    > var out = fcn( 3 )\n    <Float64Array>","random.array.minstdShuffle.PRNG":"\nrandom.array.minstdShuffle.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.minstdShuffle.PRNG;","random.array.minstdShuffle.seed":"\nrandom.array.minstdShuffle.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.minstdShuffle.seed;","random.array.minstdShuffle.seedLength":"\nrandom.array.minstdShuffle.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.minstdShuffle.seedLength;","random.array.minstdShuffle.state":"\nrandom.array.minstdShuffle.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.minstdShuffle( 3 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.minstdShuffle.state;\n\n    > out = random.array.minstdShuffle( 3 )\n    <Float64Array>\n    > out = random.array.minstdShuffle( 3 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.minstdShuffle.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.minstdShuffle( 3 )\n    <Float64Array>","random.array.minstdShuffle.stateLength":"\nrandom.array.minstdShuffle.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.minstdShuffle.stateLength;","random.array.minstdShuffle.byteLength":"\nrandom.array.minstdShuffle.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.minstdShuffle.byteLength;\n\n    See Also\n    --------\n    random.array.minstd, random.array.randu, base.random.minstdShuffle, random.strided.minstdShuffle","random.array.mt19937":"\nrandom.array.mt19937( len[, options] )\n    Returns an array containing pseudorandom integers on the interval\n    `[0, 4294967295]`.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.mt19937( 3 )\n    <Float64Array>\n\n\nrandom.array.mt19937.normalized( len[, options] )\n    Returns an array containing pseudorandom numbers on the interval `[0, 1)`\n    with 53-bit precision.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.mt19937.normalized( 3 )\n    <Float64Array>\n\n\nrandom.array.mt19937.factory( [options] )\n    Returns a function for creating arrays containing pseudorandom numbers\n    generated using a 32-bit Mersenne Twister pseudorandom number generator.\n\n    The returned function and its attached `normalized` method accept the\n    following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.idtype: string (optional)\n        Default output array data type when generating integers. Default:\n        'float64'.\n\n    options.ndtype: string (optional)\n        Default output array data type when generating normalized numbers.\n        Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.mt19937.factory();\n    > var out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.mt19937.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.mt19937.PRNG;\n\n\nrandom.array.mt19937.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.mt19937.seed;\n\n\nrandom.array.mt19937.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.mt19937.seedLength;\n\n\nrandom.array.mt19937.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.mt19937( 3 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.mt19937.state;\n\n    > out = random.array.mt19937( 3 )\n    <Float64Array>\n    > out = random.array.mt19937( 3 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.mt19937.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.mt19937( 3 )\n    <Float64Array>\n\n\nrandom.array.mt19937.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.mt19937.stateLength;\n\n\nrandom.array.mt19937.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.mt19937.byteLength;\n\n    See Also\n    --------\n    random.array.randu, base.random.mt19937, random.strided.mt19937\n","random.array.mt19937.normalized":"\nrandom.array.mt19937.normalized( len[, options] )\n    Returns an array containing pseudorandom numbers on the interval `[0, 1)`\n    with 53-bit precision.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.mt19937.normalized( 3 )\n    <Float64Array>","random.array.mt19937.factory":"\nrandom.array.mt19937.factory( [options] )\n    Returns a function for creating arrays containing pseudorandom numbers\n    generated using a 32-bit Mersenne Twister pseudorandom number generator.\n\n    The returned function and its attached `normalized` method accept the\n    following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.idtype: string (optional)\n        Default output array data type when generating integers. Default:\n        'float64'.\n\n    options.ndtype: string (optional)\n        Default output array data type when generating normalized numbers.\n        Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.mt19937.factory();\n    > var out = fcn( 3 )\n    <Float64Array>","random.array.mt19937.PRNG":"\nrandom.array.mt19937.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.mt19937.PRNG;","random.array.mt19937.seed":"\nrandom.array.mt19937.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.mt19937.seed;","random.array.mt19937.seedLength":"\nrandom.array.mt19937.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.mt19937.seedLength;","random.array.mt19937.state":"\nrandom.array.mt19937.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.mt19937( 3 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.mt19937.state;\n\n    > out = random.array.mt19937( 3 )\n    <Float64Array>\n    > out = random.array.mt19937( 3 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.mt19937.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.mt19937( 3 )\n    <Float64Array>","random.array.mt19937.stateLength":"\nrandom.array.mt19937.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.mt19937.stateLength;","random.array.mt19937.byteLength":"\nrandom.array.mt19937.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.mt19937.byteLength;\n\n    See Also\n    --------\n    random.array.randu, base.random.mt19937, random.strided.mt19937","random.array.negativeBinomial":"\nrandom.array.negativeBinomial( len, r, p[, options] )\n    Returns an array containing pseudorandom numbers drawn from a negative\n    binomial distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.negativeBinomial( 3, 10, 0.5 )\n    <Float64Array>\n\n\nrandom.array.negativeBinomial.assign( r, p, out )\n    Fills an array with pseudorandom numbers drawn from a negative binomial\n    distribution.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.negativeBinomial.assign( 10, 0.5, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.negativeBinomial.factory( [r, p, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a negative binomial distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    r: number (optional)\n        Number of successes until experiment is stopped.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.negativeBinomial.factory();\n    > var out = fcn( 3, 10, 0.5 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.negativeBinomial.factory( 10, 0.5 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.negativeBinomial.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.negativeBinomial.PRNG;\n\n\nrandom.array.negativeBinomial.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.negativeBinomial.seed;\n\n\nrandom.array.negativeBinomial.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.negativeBinomial.seedLength;\n\n\nrandom.array.negativeBinomial.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.negativeBinomial( 3, 10, 0.5 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.negativeBinomial.state\n    <Uint32Array>\n\n    > out = random.array.negativeBinomial( 3, 10, 0.5 )\n    <Float64Array>\n    > out = random.array.negativeBinomial( 3, 10, 0.5 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.negativeBinomial.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.negativeBinomial( 3, 10, 0.5 )\n    <Float64Array>\n\n\nrandom.array.negativeBinomial.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.negativeBinomial.stateLength;\n\n\nrandom.array.negativeBinomial.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.negativeBinomial.byteLength;\n\n    See Also\n    --------\n    random.array.binomial, base.random.negativeBinomial\n","random.array.negativeBinomial.assign":"\nrandom.array.negativeBinomial.assign( r, p, out )\n    Fills an array with pseudorandom numbers drawn from a negative binomial\n    distribution.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.negativeBinomial.assign( 10, 0.5, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.negativeBinomial.factory":"\nrandom.array.negativeBinomial.factory( [r, p, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a negative binomial distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    r: number (optional)\n        Number of successes until experiment is stopped.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.negativeBinomial.factory();\n    > var out = fcn( 3, 10, 0.5 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.negativeBinomial.factory( 10, 0.5 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.negativeBinomial.PRNG":"\nrandom.array.negativeBinomial.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.negativeBinomial.PRNG;","random.array.negativeBinomial.seed":"\nrandom.array.negativeBinomial.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.negativeBinomial.seed;","random.array.negativeBinomial.seedLength":"\nrandom.array.negativeBinomial.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.negativeBinomial.seedLength;","random.array.negativeBinomial.state":"\nrandom.array.negativeBinomial.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.negativeBinomial( 3, 10, 0.5 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.negativeBinomial.state\n    <Uint32Array>\n\n    > out = random.array.negativeBinomial( 3, 10, 0.5 )\n    <Float64Array>\n    > out = random.array.negativeBinomial( 3, 10, 0.5 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.negativeBinomial.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.negativeBinomial( 3, 10, 0.5 )\n    <Float64Array>","random.array.negativeBinomial.stateLength":"\nrandom.array.negativeBinomial.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.negativeBinomial.stateLength;","random.array.negativeBinomial.byteLength":"\nrandom.array.negativeBinomial.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.negativeBinomial.byteLength;\n\n    See Also\n    --------\n    random.array.binomial, base.random.negativeBinomial","random.array.normal":"\nrandom.array.normal( len, mu, sigma[, options] )\n    Returns an array containing pseudorandom numbers drawn from a normal\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    mu: number\n        Mean.\n\n    sigma: number\n        Standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.normal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.normal.assign( mu, sigma, out )\n    Fills an array with pseudorandom numbers drawn from a normal distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Mean.\n\n    sigma: number\n        Standard deviation.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.normal.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.normal.factory( [mu, sigma, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a normal distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Mean.\n\n    sigma: number (optional)\n        Standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.normal.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.normal.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.normal.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.normal.PRNG;\n\n\nrandom.array.normal.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.normal.seed;\n\n\nrandom.array.normal.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.normal.seedLength;\n\n\nrandom.array.normal.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.normal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.normal.state\n    <Uint32Array>\n\n    > out = random.array.normal( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.normal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.normal.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.normal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.normal.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.normal.stateLength;\n\n\nrandom.array.normal.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.normal.byteLength;\n\n    See Also\n    --------\n    base.random.normal, random.strided.normal\n","random.array.normal.assign":"\nrandom.array.normal.assign( mu, sigma, out )\n    Fills an array with pseudorandom numbers drawn from a normal distribution.\n\n    Parameters\n    ----------\n    mu: number\n        Mean.\n\n    sigma: number\n        Standard deviation.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.normal.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.normal.factory":"\nrandom.array.normal.factory( [mu, sigma, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a normal distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    mu: number (optional)\n        Mean.\n\n    sigma: number (optional)\n        Standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.normal.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.normal.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.normal.PRNG":"\nrandom.array.normal.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.normal.PRNG;","random.array.normal.seed":"\nrandom.array.normal.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.normal.seed;","random.array.normal.seedLength":"\nrandom.array.normal.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.normal.seedLength;","random.array.normal.state":"\nrandom.array.normal.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.normal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.normal.state\n    <Uint32Array>\n\n    > out = random.array.normal( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.normal( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.normal.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.normal( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.normal.stateLength":"\nrandom.array.normal.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.normal.stateLength;","random.array.normal.byteLength":"\nrandom.array.normal.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.normal.byteLength;\n\n    See Also\n    --------\n    base.random.normal, random.strided.normal","random.array.pareto1":"\nrandom.array.pareto1( len, alpha, beta[, options] )\n    Returns an array containing pseudorandom numbers drawn from a Pareto (Type\n    I) distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    alpha: number\n        Shape parameter.\n\n    beta: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.pareto1( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.pareto1.assign( alpha, beta, out )\n    Fills an array with pseudorandom numbers drawn from a Pareto (Type I)\n    distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        Shape parameter.\n\n    beta: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.pareto1.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.pareto1.factory( [alpha, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Pareto (Type I) distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        Shape parameter.\n\n    beta: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.pareto1.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.pareto1.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.pareto1.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.pareto1.PRNG;\n\n\nrandom.array.pareto1.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.pareto1.seed;\n\n\nrandom.array.pareto1.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.pareto1.seedLength;\n\n\nrandom.array.pareto1.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.pareto1( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.pareto1.state\n    <Uint32Array>\n\n    > out = random.array.pareto1( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.pareto1( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.pareto1.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.pareto1( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.pareto1.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.pareto1.stateLength;\n\n\nrandom.array.pareto1.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.pareto1.byteLength;\n\n    See Also\n    --------\n    base.random.pareto1\n","random.array.pareto1.assign":"\nrandom.array.pareto1.assign( alpha, beta, out )\n    Fills an array with pseudorandom numbers drawn from a Pareto (Type I)\n    distribution.\n\n    Parameters\n    ----------\n    alpha: number\n        Shape parameter.\n\n    beta: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.pareto1.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.pareto1.factory":"\nrandom.array.pareto1.factory( [alpha, beta, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Pareto (Type I) distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    alpha: number (optional)\n        Shape parameter.\n\n    beta: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.pareto1.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.pareto1.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.pareto1.PRNG":"\nrandom.array.pareto1.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.pareto1.PRNG;","random.array.pareto1.seed":"\nrandom.array.pareto1.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.pareto1.seed;","random.array.pareto1.seedLength":"\nrandom.array.pareto1.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.pareto1.seedLength;","random.array.pareto1.state":"\nrandom.array.pareto1.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.pareto1( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.pareto1.state\n    <Uint32Array>\n\n    > out = random.array.pareto1( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.pareto1( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.pareto1.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.pareto1( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.pareto1.stateLength":"\nrandom.array.pareto1.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.pareto1.stateLength;","random.array.pareto1.byteLength":"\nrandom.array.pareto1.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.pareto1.byteLength;\n\n    See Also\n    --------\n    base.random.pareto1","random.array.poisson":"\nrandom.array.poisson( len, lambda[, options] )\n    Returns an array containing pseudorandom numbers drawn from a Poisson\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    lambda: number\n        Mean parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.poisson( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.poisson.assign( lambda, out )\n    Fills an array with pseudorandom numbers drawn from a Poisson distribution.\n\n    Parameters\n    ----------\n    lambda: number\n        Mean parameter.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.poisson.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.poisson.factory( [lambda, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Poisson distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    lambda: number (optional)\n        Mean parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.poisson.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.poisson.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.poisson.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.poisson.PRNG;\n\n\nrandom.array.poisson.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.poisson.seed;\n\n\nrandom.array.poisson.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.poisson.seedLength;\n\n\nrandom.array.poisson.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.poisson( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.poisson.state\n    <Uint32Array>\n\n    > out = random.array.poisson( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.poisson( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.poisson.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.poisson( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.poisson.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.poisson.stateLength;\n\n\nrandom.array.poisson.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.poisson.byteLength;\n\n    See Also\n    --------\n    base.random.poisson, random.strided.poisson\n","random.array.poisson.assign":"\nrandom.array.poisson.assign( lambda, out )\n    Fills an array with pseudorandom numbers drawn from a Poisson distribution.\n\n    Parameters\n    ----------\n    lambda: number\n        Mean parameter.\n\n    out: Array<number>|TypedArray\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.poisson.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.poisson.factory":"\nrandom.array.poisson.factory( [lambda, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Poisson distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    lambda: number (optional)\n        Mean parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.poisson.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.poisson.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.poisson.PRNG":"\nrandom.array.poisson.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.poisson.PRNG;","random.array.poisson.seed":"\nrandom.array.poisson.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.poisson.seed;","random.array.poisson.seedLength":"\nrandom.array.poisson.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.poisson.seedLength;","random.array.poisson.state":"\nrandom.array.poisson.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.poisson( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.poisson.state\n    <Uint32Array>\n\n    > out = random.array.poisson( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.poisson( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.poisson.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.poisson( 3, 2.0 )\n    <Float64Array>","random.array.poisson.stateLength":"\nrandom.array.poisson.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.poisson.stateLength;","random.array.poisson.byteLength":"\nrandom.array.poisson.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.poisson.byteLength;\n\n    See Also\n    --------\n    base.random.poisson, random.strided.poisson","random.array.randu":"\nrandom.array.randu( len[, options] )\n    Returns an array containing uniformly distributed pseudorandom numbers\n    between 0 and 1.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.randu( 3 )\n    <Float64Array>\n\n\nrandom.array.randu.factory( [options] )\n    Returns a function for creating arrays containing uniformly distributed\n    pseudorandom numbers between 0 and 1.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: `'mt19937'`.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.randu.factory();\n    > var out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.randu.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.randu.PRNG;\n\n\nrandom.array.randu.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.randu.seed;\n\n\nrandom.array.randu.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.randu.seedLength;\n\n\nrandom.array.randu.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.randu( 3 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.randu.state;\n\n    > out = random.array.randu( 3 )\n    <Float64Array>\n    > out = random.array.randu( 3 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.randu.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.randu( 3 )\n    <Float64Array>\n\n\nrandom.array.randu.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.randu.stateLength;\n\n\nrandom.array.randu.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.randu.byteLength;\n\n    See Also\n    --------\n    random.array.uniform, base.random.randu, random.strided.randu\n","random.array.randu.factory":"\nrandom.array.randu.factory( [options] )\n    Returns a function for creating arrays containing uniformly distributed\n    pseudorandom numbers between 0 and 1.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: `'mt19937'`.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.randu.factory();\n    > var out = fcn( 3 )\n    <Float64Array>","random.array.randu.PRNG":"\nrandom.array.randu.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.randu.PRNG;","random.array.randu.seed":"\nrandom.array.randu.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.randu.seed;","random.array.randu.seedLength":"\nrandom.array.randu.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.randu.seedLength;","random.array.randu.state":"\nrandom.array.randu.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.randu( 3 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.randu.state;\n\n    > out = random.array.randu( 3 )\n    <Float64Array>\n    > out = random.array.randu( 3 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.randu.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.randu( 3 )\n    <Float64Array>","random.array.randu.stateLength":"\nrandom.array.randu.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.randu.stateLength;","random.array.randu.byteLength":"\nrandom.array.randu.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.randu.byteLength;\n\n    See Also\n    --------\n    random.array.uniform, base.random.randu, random.strided.randu","random.array.rayleigh":"\nrandom.array.rayleigh( len, sigma[, options] )\n    Returns an array containing pseudorandom numbers drawn from a Rayleigh\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    sigma: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.rayleigh( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.rayleigh.assign( sigma, out )\n    Fills an array with pseudorandom numbers drawn from a Rayleigh distribution.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.rayleigh.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.rayleigh.factory( [sigma, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Rayleigh distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    sigma: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.rayleigh.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.rayleigh.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.rayleigh.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.rayleigh.PRNG;\n\n\nrandom.array.rayleigh.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.rayleigh.seed;\n\n\nrandom.array.rayleigh.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.rayleigh.seedLength;\n\n\nrandom.array.rayleigh.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.rayleigh( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.rayleigh.state\n    <Uint32Array>\n\n    > out = random.array.rayleigh( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.rayleigh( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.rayleigh.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.rayleigh( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.rayleigh.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.rayleigh.stateLength;\n\n\nrandom.array.rayleigh.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.rayleigh.byteLength;\n\n    See Also\n    --------\n    base.random.rayleigh, random.strided.rayleigh\n","random.array.rayleigh.assign":"\nrandom.array.rayleigh.assign( sigma, out )\n    Fills an array with pseudorandom numbers drawn from a Rayleigh distribution.\n\n    Parameters\n    ----------\n    sigma: number\n        Scale parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.rayleigh.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.rayleigh.factory":"\nrandom.array.rayleigh.factory( [sigma, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Rayleigh distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    sigma: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.rayleigh.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.rayleigh.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.rayleigh.PRNG":"\nrandom.array.rayleigh.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.rayleigh.PRNG;","random.array.rayleigh.seed":"\nrandom.array.rayleigh.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.rayleigh.seed;","random.array.rayleigh.seedLength":"\nrandom.array.rayleigh.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.rayleigh.seedLength;","random.array.rayleigh.state":"\nrandom.array.rayleigh.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.rayleigh( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.rayleigh.state\n    <Uint32Array>\n\n    > out = random.array.rayleigh( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.rayleigh( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.rayleigh.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.rayleigh( 3, 2.0 )\n    <Float64Array>","random.array.rayleigh.stateLength":"\nrandom.array.rayleigh.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.rayleigh.stateLength;","random.array.rayleigh.byteLength":"\nrandom.array.rayleigh.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.rayleigh.byteLength;\n\n    See Also\n    --------\n    base.random.rayleigh, random.strided.rayleigh","random.array.t":"\nrandom.array.t( len, v[, options] )\n    Returns an array containing pseudorandom numbers drawn from a Student's t\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    v: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.t( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.t.assign( v, out )\n    Fills an array with pseudorandom numbers drawn from a Student's t\n    distribution.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.t.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.t.factory( [v, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Student's t distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    v: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.t.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.t.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.t.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.t.PRNG;\n\n\nrandom.array.t.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.t.seed;\n\n\nrandom.array.t.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.t.seedLength;\n\n\nrandom.array.t.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.t( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.t.state\n    <Uint32Array>\n\n    > out = random.array.t( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.t( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.t.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.t( 3, 2.0 )\n    <Float64Array>\n\n\nrandom.array.t.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.t.stateLength;\n\n\nrandom.array.t.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.t.byteLength;\n\n    See Also\n    --------\n    base.random.t, random.strided.t\n","random.array.t.assign":"\nrandom.array.t.assign( v, out )\n    Fills an array with pseudorandom numbers drawn from a Student's t\n    distribution.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.t.assign( 2.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.t.factory":"\nrandom.array.t.factory( [v, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Student's t distribution.\n\n    If provided a distribution parameter, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided a distribution parameter, the returned function requires\n    that distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    v: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.t.factory();\n    > var out = fcn( 3, 2.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.t.factory( 2.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.t.PRNG":"\nrandom.array.t.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.t.PRNG;","random.array.t.seed":"\nrandom.array.t.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.t.seed;","random.array.t.seedLength":"\nrandom.array.t.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.t.seedLength;","random.array.t.state":"\nrandom.array.t.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.t( 3, 2.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.t.state\n    <Uint32Array>\n\n    > out = random.array.t( 3, 2.0 )\n    <Float64Array>\n    > out = random.array.t( 3, 2.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.t.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.t( 3, 2.0 )\n    <Float64Array>","random.array.t.stateLength":"\nrandom.array.t.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.t.stateLength;","random.array.t.byteLength":"\nrandom.array.t.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.t.byteLength;\n\n    See Also\n    --------\n    base.random.t, random.strided.t","random.array.triangular":"\nrandom.array.triangular( len, a, b, c[, options] )\n    Returns an array containing pseudorandom numbers drawn from a triangular\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n\nrandom.array.triangular.assign( a, b, c, out )\n    Fills an array with pseudorandom numbers drawn from a triangular\n    distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.triangular.assign( 2.0, 5.0, 3.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.triangular.factory( [a, b, c, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a triangular distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    c: number (optional)\n        Mode.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.triangular.factory();\n    > var out = fcn( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.triangular.factory( 2.0, 5.0, 3.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.triangular.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.triangular.PRNG;\n\n\nrandom.array.triangular.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.triangular.seed;\n\n\nrandom.array.triangular.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.triangular.seedLength;\n\n\nrandom.array.triangular.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.triangular.state\n    <Uint32Array>\n\n    > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n    > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.triangular.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n\nrandom.array.triangular.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.triangular.stateLength;\n\n\nrandom.array.triangular.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.triangular.byteLength;\n\n    See Also\n    --------\n    base.random.triangular\n","random.array.triangular.assign":"\nrandom.array.triangular.assign( a, b, c, out )\n    Fills an array with pseudorandom numbers drawn from a triangular\n    distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.triangular.assign( 2.0, 5.0, 3.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.triangular.factory":"\nrandom.array.triangular.factory( [a, b, c, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a triangular distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    c: number (optional)\n        Mode.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.triangular.factory();\n    > var out = fcn( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.triangular.factory( 2.0, 5.0, 3.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.triangular.PRNG":"\nrandom.array.triangular.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.triangular.PRNG;","random.array.triangular.seed":"\nrandom.array.triangular.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.triangular.seed;","random.array.triangular.seedLength":"\nrandom.array.triangular.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.triangular.seedLength;","random.array.triangular.state":"\nrandom.array.triangular.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.triangular.state\n    <Uint32Array>\n\n    > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n    > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.triangular.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.triangular( 3, 2.0, 5.0, 3.0 )\n    <Float64Array>","random.array.triangular.stateLength":"\nrandom.array.triangular.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.triangular.stateLength;","random.array.triangular.byteLength":"\nrandom.array.triangular.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.triangular.byteLength;\n\n    See Also\n    --------\n    base.random.triangular","random.array.uniform":"\nrandom.array.uniform( len, a, b[, options] )\n    Returns an array containing pseudorandom numbers drawn from a continuous\n    uniform distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.uniform( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.uniform.assign( a, b, out )\n    Fills an array with pseudorandom numbers drawn from a continuous uniform\n    distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.uniform.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.uniform.factory( [a, b, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a continuous uniform distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.uniform.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.uniform.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.uniform.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.uniform.PRNG;\n\n\nrandom.array.uniform.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.uniform.seed;\n\n\nrandom.array.uniform.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.uniform.seedLength;\n\n\nrandom.array.uniform.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.uniform( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.uniform.state\n    <Uint32Array>\n\n    > out = random.array.uniform( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.uniform( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.uniform.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.uniform( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.uniform.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.uniform.stateLength;\n\n\nrandom.array.uniform.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.uniform.byteLength;\n\n    See Also\n    --------\n    random.array.discreteUniform, base.random.uniform, random.strided.uniform\n","random.array.uniform.assign":"\nrandom.array.uniform.assign( a, b, out )\n    Fills an array with pseudorandom numbers drawn from a continuous uniform\n    distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.uniform.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.uniform.factory":"\nrandom.array.uniform.factory( [a, b, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a continuous uniform distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.uniform.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.uniform.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.uniform.PRNG":"\nrandom.array.uniform.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.uniform.PRNG;","random.array.uniform.seed":"\nrandom.array.uniform.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.uniform.seed;","random.array.uniform.seedLength":"\nrandom.array.uniform.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.uniform.seedLength;","random.array.uniform.state":"\nrandom.array.uniform.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.uniform( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.uniform.state\n    <Uint32Array>\n\n    > out = random.array.uniform( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.uniform( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.uniform.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.uniform( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.uniform.stateLength":"\nrandom.array.uniform.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.uniform.stateLength;","random.array.uniform.byteLength":"\nrandom.array.uniform.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.uniform.byteLength;\n\n    See Also\n    --------\n    random.array.discreteUniform, base.random.uniform, random.strided.uniform","random.array.weibull":"\nrandom.array.weibull( len, k, lambda[, options] )\n    Returns an array containing pseudorandom numbers drawn from a Weibull\n    distribution.\n\n    Parameters\n    ----------\n    len: integer\n        Output array length.\n\n    k: number\n        Scale parameter.\n\n    lambda: number\n        Shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var out = random.array.weibull( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.weibull.assign( k, lambda, out )\n    Fills an array with pseudorandom numbers drawn from a Weibull distribution.\n\n    Parameters\n    ----------\n    k: number\n        Scale parameter.\n\n    lambda: number\n        Shape parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.weibull.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true\n\n\nrandom.array.weibull.factory( [k, lambda, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Weibull distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Scale parameter.\n\n    lambda: number (optional)\n        Shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.weibull.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.weibull.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>\n\n\nrandom.array.weibull.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.weibull.PRNG;\n\n\nrandom.array.weibull.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.weibull.seed;\n\n\nrandom.array.weibull.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.weibull.seedLength;\n\n\nrandom.array.weibull.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.weibull( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.weibull.state\n    <Uint32Array>\n\n    > out = random.array.weibull( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.weibull( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.weibull.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.weibull( 3, 2.0, 5.0 )\n    <Float64Array>\n\n\nrandom.array.weibull.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.weibull.stateLength;\n\n\nrandom.array.weibull.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.weibull.byteLength;\n\n    See Also\n    --------\n    base.random.weibull, random.strided.weibull\n","random.array.weibull.assign":"\nrandom.array.weibull.assign( k, lambda, out )\n    Fills an array with pseudorandom numbers drawn from a Weibull distribution.\n\n    Parameters\n    ----------\n    k: number\n        Scale parameter.\n\n    lambda: number\n        Shape parameter.\n\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Returns\n    -------\n    out: Array<number>|Float64Array|Float32Array\n        Output array.\n\n    Examples\n    --------\n    > var x = azeros( 3, 'float64' );\n    > var out = random.array.weibull.assign( 2.0, 5.0, x )\n    <Float64Array>\n    > var bool = ( out === x )\n    true","random.array.weibull.factory":"\nrandom.array.weibull.factory( [k, lambda, ][options] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Weibull distribution.\n\n    If provided distribution parameters, the returned function returns random\n    variates drawn from the specified distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    The returned function accepts the following options:\n\n    - dtype: output array data type. This overrides the default output array\n    data type.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Scale parameter.\n\n    lambda: number (optional)\n        Shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.dtype: string (optional)\n        Default output array data type. Default: 'float64'.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating arrays.\n\n    Examples\n    --------\n    > var fcn = random.array.weibull.factory();\n    > var out = fcn( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Provide distribution parameters:\n    > fcn = random.array.weibull.factory( 2.0, 5.0 );\n    > out = fcn( 3 )\n    <Float64Array>","random.array.weibull.PRNG":"\nrandom.array.weibull.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.array.weibull.PRNG;","random.array.weibull.seed":"\nrandom.array.weibull.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.array.weibull.seed;","random.array.weibull.seedLength":"\nrandom.array.weibull.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.array.weibull.seedLength;","random.array.weibull.state":"\nrandom.array.weibull.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = random.array.weibull( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Get a copy of the current state:\n    > var state = random.array.weibull.state\n    <Uint32Array>\n\n    > out = random.array.weibull( 3, 2.0, 5.0 )\n    <Float64Array>\n    > out = random.array.weibull( 3, 2.0, 5.0 )\n    <Float64Array>\n\n    // Set the state:\n    > random.array.weibull.state = state;\n\n    // Regenerate a previous array:\n    > out = random.array.weibull( 3, 2.0, 5.0 )\n    <Float64Array>","random.array.weibull.stateLength":"\nrandom.array.weibull.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.array.weibull.stateLength;","random.array.weibull.byteLength":"\nrandom.array.weibull.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.array.weibull.byteLength;\n\n    See Also\n    --------\n    base.random.weibull, random.strided.weibull","random.iterators.arcsine":"\nrandom.iterators.arcsine( a, b[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from an\n    arcsine distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.arcsine( 0.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.arcsine\n","random.iterators.bernoulli":"\nrandom.iterators.bernoulli( p[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Bernoulli distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.bernoulli( 0.3 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.bernoulli\n","random.iterators.beta":"\nrandom.iterators.beta( α, β[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    beta distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    The function throws an error if `α <= 0` or `β <= 0`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.beta( 1.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.beta\n","random.iterators.betaprime":"\nrandom.iterators.betaprime( α, β[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    beta prime distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    The function throws an error if `α <= 0` or `β <= 0`.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.betaprime( 1.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.betaprime\n","random.iterators.binomial":"\nrandom.iterators.binomial( n, p[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    binomial distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.binomial( 10, 0.3 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.binomial\n","random.iterators.boxMuller":"\nrandom.iterators.boxMuller( [options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    standard normal distribution using the Box-Muller transform.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.boxMuller();\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.boxMuller\n","random.iterators.cauchy":"\nrandom.iterators.cauchy( x0, Ɣ[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Cauchy distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    Ɣ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.seed: any\n        Pseudorandom number generator seed.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.cauchy( 0.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.cauchy\n","random.iterators.chi":"\nrandom.iterators.chi( k[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a chi\n    distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.chi( 1.5 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.chi\n","random.iterators.chisquare":"\nrandom.iterators.chisquare( k[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    chi-square distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.chisquare( 1.5 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.chisquare\n","random.iterators.cosine":"\nrandom.iterators.cosine( μ, s[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a raised\n    cosine distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.cosine( 0.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.cosine\n","random.iterators.discreteUniform":"\nrandom.iterators.discreteUniform( a, b[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    discrete uniform distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom integers. If provided, the `state` and `seed`\n        options are ignored. In order to seed the returned iterator, one must\n        seed the provided `prng` (assuming the provided `prng` is seedable). The\n        provided PRNG must have `MIN` and `MAX` properties specifying the\n        minimum and maximum possible pseudorandom integers.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.discreteUniform( 0, 3 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.discreteUniform\n","random.iterators.erlang":"\nrandom.iterators.erlang( k, λ[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from an Erlang\n    distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If `k` is not a positive integer or `λ <= 0`, the function throws an error.\n\n    Parameters\n    ----------\n    k: integer\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.erlang( 1, 1.5 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.erlang\n","random.iterators.exponential":"\nrandom.iterators.exponential( λ[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from an\n    exponential distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.exponential( 1.5 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.exponential\n","random.iterators.f":"\nrandom.iterators.f( d1, d2[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from an F\n    distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    The function throws an error if `d1 <= 0` or `d2 <= 0`.\n\n    Parameters\n    ----------\n    d1: number\n        Degrees of freedom.\n\n    d2: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.f( 1.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.f\n","random.iterators.frechet":"\nrandom.iterators.frechet( α, s, m[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Fréchet\n    distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    The function throws an error if `α <= 0` or `s <= 0`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.frechet( 1.0, 1.0, 0.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.frechet\n","random.iterators.gamma":"\nrandom.iterators.gamma( α, β[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a gamma\n    distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    The function throws an error if `α <= 0` or `β <= 0`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.gamma( 1.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.gamma\n","random.iterators.geometric":"\nrandom.iterators.geometric( p[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    geometric distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.geometric( 0.3 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.geometric\n","random.iterators.gumbel":"\nrandom.iterators.gumbel( μ, β[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Gumbel\n    distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.gumbel( 0.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.gumbel\n","random.iterators.hypergeometric":"\nrandom.iterators.hypergeometric( N, K, n[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    hypergeometric distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    `N`, `K`, and `n` must all be nonnegative integers; otherwise, the function\n    throws an error.\n\n    If `n > N` or `K > N`, the function throws an error.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.hypergeometric( 20, 10, 7 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.hypergeometric\n","random.iterators.improvedZiggurat":"\nrandom.iterators.improvedZiggurat( [options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    standard normal distribution using the Improved Ziggurat algorithm.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.improvedZiggurat();\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.improvedZiggurat\n","random.iterators.invgamma":"\nrandom.iterators.invgamma( α, β[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from an\n    inverse gamma distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    The function throws an error if `α <= 0` or `β <= 0`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.invgamma( 1.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.invgamma\n","random.iterators.kumaraswamy":"\nrandom.iterators.kumaraswamy( a, b[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Kumaraswamy's double bounded distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    The function throws an error if `a <= 0` or `b <= 0`.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.kumaraswamy( 1.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.kumaraswamy\n","random.iterators.laplace":"\nrandom.iterators.laplace( μ, b[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Laplace\n    (double exponential) distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    b: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.laplace( 0.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.laplace\n","random.iterators.levy":"\nrandom.iterators.levy( μ, c[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Lévy\n    distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    c: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.levy( 0.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.levy\n","random.iterators.logistic":"\nrandom.iterators.logistic( μ, s[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    logistic distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    s: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.logistic( 0.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.logistic\n","random.iterators.lognormal":"\nrandom.iterators.lognormal( μ, σ[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    lognormal distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.lognormal( 0.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.lognormal\n","random.iterators.minstd":"\nrandom.iterators.minstd( [options] )\n    Returns an iterator for generating pseudorandom integers on the interval\n    `[1, 2147483646]`.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    This pseudorandom number generator (PRNG) is a linear congruential\n    pseudorandom number generator (LCG) based on Park and Miller.\n\n    The generator has a period of approximately `2.1e9`.\n\n    An LCG is fast and uses little memory. On the other hand, because the\n    generator is a simple LCG, the generator has recognized shortcomings. By\n    today's PRNG standards, the generator's period is relatively short. More\n    importantly, the \"randomness quality\" of the generator's output is lacking.\n    These defects make the generator unsuitable, for example, in Monte Carlo\n    simulations and in cryptographic applications.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing positive signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.seed: Int32Array\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer\n        Length of generator seed.\n\n    iterator.state: Int32Array\n        Generator state.\n\n    iterator.stateLength: integer\n        Length of generator state.\n\n    iterator.byteLength: integer\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.minstd();\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.minstd, random.iterators.minstdShuffle, random.iterators.mt19937, random.iterators.randi, random.iterators.randu\n","random.iterators.minstdShuffle":"\nrandom.iterators.minstdShuffle( [options] )\n    Returns an iterator for generating pseudorandom integers on the interval\n    `[1, 2147483646]`.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    This pseudorandom number generator (PRNG) is a linear congruential\n    pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n    Durham algorithm. The shuffle step considerably strengthens the \"randomness\n    quality\" of a simple LCG's output.\n\n    The generator has a period of approximately `2.1e9`.\n\n    An LCG is fast and uses little memory. On the other hand, because the\n    generator is a simple LCG, the generator has recognized shortcomings. By\n    today's PRNG standards, the generator's period is relatively short. In\n    general, this generator is unsuitable for Monte Carlo simulations and\n    cryptographic applications.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing positive signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.seed: Int32Array\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer\n        Length of generator seed.\n\n    iterator.state: Int32Array\n        Generator state.\n\n    iterator.stateLength: integer\n        Length of generator state.\n\n    iterator.byteLength: integer\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.minstdShuffle();\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.minstdShuffle, random.iterators.minstd, random.iterators.mt19937, random.iterators.randi, random.iterators.randu\n","random.iterators.mt19937":"\nrandom.iterators.mt19937( [options] )\n    Returns an iterator for generating pseudorandom integers on the interval\n    `[1, 4294967295]`.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    This pseudorandom number generator (PRNG) is a 32-bit Mersenne Twister\n    pseudorandom number generator.\n\n    The PRNG is *not* a cryptographically secure PRNG.\n\n    The PRNG has a period of 2^19937 - 1.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.seed: Uint32Array\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer\n        Length of generator seed.\n\n    iterator.state: Uint32Array\n        Generator state.\n\n    iterator.stateLength: integer\n        Length of generator state.\n\n    iterator.byteLength: integer\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.mt19937();\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.mt19937, random.iterators.minstd, random.iterators.minstdShuffle, random.iterators.randi, random.iterators.randu\n","random.iterators.negativeBinomial":"\nrandom.iterators.negativeBinomial( r, p[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    negative binomial distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.negativeBinomial( 10, 0.3 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.negativeBinomial\n","random.iterators.normal":"\nrandom.iterators.normal( μ, σ[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a normal\n    distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    σ: number\n        Standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.normal( 0.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.normal\n","random.iterators.pareto1":"\nrandom.iterators.pareto1( α, β[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Pareto\n    (Type I) distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    The function throws an error if `α <= 0` or `β <= 0`.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.pareto1( 1.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.pareto1\n","random.iterators.poisson":"\nrandom.iterators.poisson( λ[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Poisson\n    distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    λ: number\n        Mean.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.poisson( 1.5 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.poisson\n","random.iterators.randi":"\nrandom.iterators.randi( [options] )\n    Create an iterator for generating pseudorandom numbers having integer\n    values.\n\n    The default underlying pseudorandom number generator (PRNG) *may* change in\n    the future. If exact reproducibility is required, either explicitly specify\n    a PRNG via the `name` option or use an underlying PRNG directly.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: `'mt19937'`.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: any\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer\n        Length of generator seed.\n\n    iterator.state: any\n        Generator state.\n\n    iterator.stateLength: integer\n        Length of generator state.\n\n    iterator.byteLength: integer\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.randi();\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.randi, random.iterators.randu\n","random.iterators.randn":"\nrandom.iterators.randn( [options] )\n    Create an iterator for generating pseudorandom numbers drawn from a standard\n    normal distribution.\n\n    The default underlying pseudorandom number generator (PRNG) *may* change in\n    the future. If exact reproducibility is required, either explicitly specify\n    a PRNG via the `name` option or use an underlying PRNG directly.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - improved-ziggurat: improved ziggurat method.\n        - box-muller: Box-Muller transform.\n\n        Default: `'improved-ziggurat'`.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.randn();\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.randn\n","random.iterators.randu":"\nrandom.iterators.randu( [options] )\n    Create an iterator for generating uniformly distributed pseudorandom numbers\n    between 0 and 1.\n\n    The default underlying pseudorandom number generator (PRNG) *may* change in\n    the future. If exact reproducibility is required, either explicitly specify\n    a PRNG via the `name` option or use an underlying PRNG directly.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: `'mt19937'`.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: any\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer\n        Length of generator seed.\n\n    iterator.state: any\n        Generator state.\n\n    iterator.stateLength: integer\n        Length of generator state.\n\n    iterator.byteLength: integer\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.randu();\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.randu, random.iterators.randi\n","random.iterators.rayleigh":"\nrandom.iterators.rayleigh( σ[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Rayleigh distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.rayleigh( 1.5 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.rayleigh\n","random.iterators.t":"\nrandom.iterators.t( v[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Student's t distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.t( 1.5 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.t\n","random.iterators.triangular":"\nrandom.iterators.triangular( a, b, c[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    triangular distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.triangular( 0.0, 1.0, 0.3 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.triangular\n","random.iterators.uniform":"\nrandom.iterators.uniform( a, b[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    continuous uniform distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.uniform( 0.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.uniform\n","random.iterators.weibull":"\nrandom.iterators.weibull( k, λ[, options] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Weibull distribution.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    The function throws an error if `k <= 0` or `λ <= 0`.\n\n    Parameters\n    ----------\n    k: number\n        Scale parameter.\n\n    λ: number\n        Shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    iterator.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    iterator.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    iterator.seedLength: integer|null\n        Length of generator seed.\n\n    iterator.state: Uint32Array|null\n        Generator state.\n\n    iterator.stateLength: integer|null\n        Length of generator state.\n\n    iterator.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var it = random.iterators.weibull( 1.0, 1.0 );\n    > var r = it.next().value\n    <number>\n    > r = it.next().value\n    <number>\n\n    See Also\n    --------\n    base.random.weibull\n","random.streams.arcsine":"\nrandom.streams.arcsine( a, b[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from an\n    arcsine distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.arcsine( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.arcsine.factory( [a, b, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an arcsine distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.arcsine.factory( opts );\n\n\nrandom.streams.arcsine.objectMode( a, b[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an arcsine distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.arcsine.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.arcsine, random.iterators.arcsine\n","random.streams.arcsine.factory":"\nrandom.streams.arcsine.factory( [a, b, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an arcsine distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.arcsine.factory( opts );","random.streams.arcsine.objectMode":"\nrandom.streams.arcsine.objectMode( a, b[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an arcsine distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.arcsine.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.arcsine, random.iterators.arcsine","random.streams.bernoulli":"\nrandom.streams.bernoulli( p[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Bernoulli distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.bernoulli( 0.5, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.bernoulli.factory( [p, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Bernoulli distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.bernoulli.factory( opts );\n\n\nrandom.streams.bernoulli.objectMode( p[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Bernoulli distribution.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.bernoulli.objectMode( 0.3, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.bernoulli, random.iterators.bernoulli\n","random.streams.bernoulli.factory":"\nrandom.streams.bernoulli.factory( [p, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Bernoulli distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.bernoulli.factory( opts );","random.streams.bernoulli.objectMode":"\nrandom.streams.bernoulli.objectMode( p[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Bernoulli distribution.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.bernoulli.objectMode( 0.3, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.bernoulli, random.iterators.bernoulli","random.streams.beta":"\nrandom.streams.beta( α, β[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    beta distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.beta( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.beta.factory( [α, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a beta distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        First shape parameter.\n\n    β: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.beta.factory( opts );\n\n\nrandom.streams.beta.objectMode( α, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a beta distribution.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.beta.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.beta, random.iterators.beta\n","random.streams.beta.factory":"\nrandom.streams.beta.factory( [α, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a beta distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        First shape parameter.\n\n    β: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.beta.factory( opts );","random.streams.beta.objectMode":"\nrandom.streams.beta.objectMode( α, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a beta distribution.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.beta.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.beta, random.iterators.beta","random.streams.betaprime":"\nrandom.streams.betaprime( α, β[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    beta prime distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.betaprime( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.betaprime.factory( [α, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a beta prime distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        First shape parameter.\n\n    β: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.betaprime.factory( opts );\n\n\nrandom.streams.betaprime.objectMode( α, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a beta prime distribution.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.betaprime.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.betaprime, random.iterators.betaprime\n","random.streams.betaprime.factory":"\nrandom.streams.betaprime.factory( [α, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a beta prime distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        First shape parameter.\n\n    β: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.betaprime.factory( opts );","random.streams.betaprime.objectMode":"\nrandom.streams.betaprime.objectMode( α, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a beta prime distribution.\n\n    Parameters\n    ----------\n    α: number\n        First shape parameter.\n\n    β: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.betaprime.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.betaprime, random.iterators.betaprime","random.streams.binomial":"\nrandom.streams.binomial( n, p[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    binomial distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.binomial( 20, 0.5, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.binomial.factory( [n, p, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a binomial distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    n: integer (optional)\n        Number of trials.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.binomial.factory( opts );\n\n\nrandom.streams.binomial.objectMode( n, p[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a binomial distribution.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.binomial.objectMode( 20, 0.5, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.binomial, random.iterators.binomial\n","random.streams.binomial.factory":"\nrandom.streams.binomial.factory( [n, p, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a binomial distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    n: integer (optional)\n        Number of trials.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.binomial.factory( opts );","random.streams.binomial.objectMode":"\nrandom.streams.binomial.objectMode( n, p[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a binomial distribution.\n\n    Parameters\n    ----------\n    n: integer\n        Number of trials.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.binomial.objectMode( 20, 0.5, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.binomial, random.iterators.binomial","random.streams.boxMuller":"\nrandom.streams.boxMuller( [options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    standard normal distribution using the Box-Muller transform.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.boxMuller( opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.boxMuller.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a standard normal distribution using the Box-Muller\n    transform.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.boxMuller.factory( opts );\n\n\nrandom.streams.boxMuller.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a standard normal distribution using the Box-Muller transform.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.boxMuller.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.boxMuller, random.iterators.boxMuller, random.streams.improvedZiggurat, random.streams.randn\n","random.streams.boxMuller.factory":"\nrandom.streams.boxMuller.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a standard normal distribution using the Box-Muller\n    transform.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.boxMuller.factory( opts );","random.streams.boxMuller.objectMode":"\nrandom.streams.boxMuller.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a standard normal distribution using the Box-Muller transform.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.boxMuller.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.boxMuller, random.iterators.boxMuller, random.streams.improvedZiggurat, random.streams.randn","random.streams.cauchy":"\nrandom.streams.cauchy( x0, γ[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Cauchy distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    γ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.cauchy( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.cauchy.factory( [x0, γ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Cauchy distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    x0: number (optional)\n        Location parameter.\n\n    γ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.cauchy.factory( opts );\n\n\nrandom.streams.cauchy.objectMode( x0, γ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Cauchy distribution.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    γ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.cauchy.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.cauchy, random.iterators.cauchy\n","random.streams.cauchy.factory":"\nrandom.streams.cauchy.factory( [x0, γ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Cauchy distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    x0: number (optional)\n        Location parameter.\n\n    γ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.cauchy.factory( opts );","random.streams.cauchy.objectMode":"\nrandom.streams.cauchy.objectMode( x0, γ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Cauchy distribution.\n\n    Parameters\n    ----------\n    x0: number\n        Location parameter.\n\n    γ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.cauchy.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.cauchy, random.iterators.cauchy","random.streams.chi":"\nrandom.streams.chi( k[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    chi distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.chi( 3.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.chi.factory( [k, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a chi distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.chi.factory( opts );\n\n\nrandom.streams.chi.objectMode( k[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a chi distribution.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.chi.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.chi, random.iterators.chi\n","random.streams.chi.factory":"\nrandom.streams.chi.factory( [k, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a chi distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.chi.factory( opts );","random.streams.chi.objectMode":"\nrandom.streams.chi.objectMode( k[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a chi distribution.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.chi.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.chi, random.iterators.chi","random.streams.chisquare":"\nrandom.streams.chisquare( k[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    chi-square distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.chisquare( 3.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.chisquare.factory( [k, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a chi-square distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.chisquare.factory( opts );\n\n\nrandom.streams.chisquare.objectMode( k[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a chi-square distribution.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.chisquare.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.chisquare, random.iterators.chisquare\n","random.streams.chisquare.factory":"\nrandom.streams.chisquare.factory( [k, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a chi-square distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.chisquare.factory( opts );","random.streams.chisquare.objectMode":"\nrandom.streams.chisquare.objectMode( k[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a chi-square distribution.\n\n    Parameters\n    ----------\n    k: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.chisquare.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.chisquare, random.iterators.chisquare","random.streams.cosine":"\nrandom.streams.cosine( μ, s[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    raised cosine distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.cosine( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.cosine.factory( [μ, s, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a raised cosine distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.cosine.factory( opts );\n\n\nrandom.streams.cosine.objectMode( μ, s[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a raised cosine distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.cosine.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.cosine, random.iterators.cosine\n","random.streams.cosine.factory":"\nrandom.streams.cosine.factory( [μ, s, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a raised cosine distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.cosine.factory( opts );","random.streams.cosine.objectMode":"\nrandom.streams.cosine.objectMode( μ, s[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a raised cosine distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    s: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.cosine.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.cosine, random.iterators.cosine","random.streams.discreteUniform":"\nrandom.streams.discreteUniform( a, b[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    discrete uniform distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.discreteUniform( 2, 5, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.discreteUniform.factory( [a, b, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a discrete uniform distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    a: integer (optional)\n        Minimum support.\n\n    b: integer (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.discreteUniform.factory( opts );\n\n\nrandom.streams.discreteUniform.objectMode( a, b[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a discrete uniform distribution.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.discreteUniform.objectMode( 2, 5, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.discreteUniform, random.iterators.discreteUniform\n","random.streams.discreteUniform.factory":"\nrandom.streams.discreteUniform.factory( [a, b, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a discrete uniform distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    a: integer (optional)\n        Minimum support.\n\n    b: integer (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.discreteUniform.factory( opts );","random.streams.discreteUniform.objectMode":"\nrandom.streams.discreteUniform.objectMode( a, b[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a discrete uniform distribution.\n\n    Parameters\n    ----------\n    a: integer\n        Minimum support.\n\n    b: integer\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.discreteUniform.objectMode( 2, 5, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.discreteUniform, random.iterators.discreteUniform","random.streams.erlang":"\nrandom.streams.erlang( k, λ[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from an\n    Erlang distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    k: integer\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.erlang( 2, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.erlang.factory( [k, λ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an Erlang distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Shape parameter.\n\n    λ: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.erlang.factory( opts );\n\n\nrandom.streams.erlang.objectMode( k, λ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an Erlang distribution.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.erlang.objectMode( 2, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.erlang, random.iterators.erlang\n","random.streams.erlang.factory":"\nrandom.streams.erlang.factory( [k, λ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an Erlang distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Shape parameter.\n\n    λ: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.erlang.factory( opts );","random.streams.erlang.objectMode":"\nrandom.streams.erlang.objectMode( k, λ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an Erlang distribution.\n\n    Parameters\n    ----------\n    k: number\n        Shape parameter.\n\n    λ: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.erlang.objectMode( 2, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.erlang, random.iterators.erlang","random.streams.exponential":"\nrandom.streams.exponential( λ[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from an\n    exponential distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.exponential( 3.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.exponential.factory( [λ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an exponential distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    λ: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.exponential.factory( opts );\n\n\nrandom.streams.exponential.objectMode( λ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an exponential distribution.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.exponential.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.exponential, random.iterators.exponential\n","random.streams.exponential.factory":"\nrandom.streams.exponential.factory( [λ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an exponential distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    λ: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.exponential.factory( opts );","random.streams.exponential.objectMode":"\nrandom.streams.exponential.objectMode( λ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an exponential distribution.\n\n    Parameters\n    ----------\n    λ: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.exponential.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.exponential, random.iterators.exponential","random.streams.f":"\nrandom.streams.f( d1, d2[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from an\n    F distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    d1: number\n        Degrees of freedom.\n\n    d2: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.f( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.f.factory( [d1, d2, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an F distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    d1: number (optional)\n        Degrees of freedom.\n\n    d2: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.f.factory( opts );\n\n\nrandom.streams.f.objectMode( d1, d2[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an F distribution.\n\n    Parameters\n    ----------\n    d1: number\n        Degrees of freedom.\n\n    d2: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.f.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.f, random.iterators.f\n","random.streams.f.factory":"\nrandom.streams.f.factory( [d1, d2, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an F distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    d1: number (optional)\n        Degrees of freedom.\n\n    d2: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.f.factory( opts );","random.streams.f.objectMode":"\nrandom.streams.f.objectMode( d1, d2[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an F distribution.\n\n    Parameters\n    ----------\n    d1: number\n        Degrees of freedom.\n\n    d2: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.f.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.f, random.iterators.f","random.streams.frechet":"\nrandom.streams.frechet( α, s, m[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Fréchet distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.frechet( 2.0, 5.0, 3.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.frechet.factory( [α, s, m,][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Fréchet distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    m: number (optional)\n        Location parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.frechet.factory( opts );\n\n\nrandom.streams.frechet.objectMode( α, s, m[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Fréchet distribution.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.frechet.objectMode( 2.0, 5.0, 3.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.frechet, random.iterators.frechet\n","random.streams.frechet.factory":"\nrandom.streams.frechet.factory( [α, s, m,][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Fréchet distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    s: number (optional)\n        Scale parameter.\n\n    m: number (optional)\n        Location parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.frechet.factory( opts );","random.streams.frechet.objectMode":"\nrandom.streams.frechet.objectMode( α, s, m[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Fréchet distribution.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    s: number\n        Scale parameter.\n\n    m: number\n        Location parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.frechet.objectMode( 2.0, 5.0, 3.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.frechet, random.iterators.frechet","random.streams.gamma":"\nrandom.streams.gamma( α, β[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    gamma distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.gamma( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.gamma.factory( [α, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a gamma distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.gamma.factory( opts );\n\n\nrandom.streams.gamma.objectMode( α, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a gamma distribution.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.gamma.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.gamma, random.iterators.gamma\n","random.streams.gamma.factory":"\nrandom.streams.gamma.factory( [α, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a gamma distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.gamma.factory( opts );","random.streams.gamma.objectMode":"\nrandom.streams.gamma.objectMode( α, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a gamma distribution.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Rate parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.gamma.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.gamma, random.iterators.gamma","random.streams.geometric":"\nrandom.streams.geometric( p[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    geometric distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.geometric( 0.5, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.geometric.factory( [p, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a geometric distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.geometric.factory( opts );\n\n\nrandom.streams.geometric.objectMode( p[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a geometric distribution.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.geometric.objectMode( 0.3, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.geometric, random.iterators.geometric\n","random.streams.geometric.factory":"\nrandom.streams.geometric.factory( [p, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a geometric distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.geometric.factory( opts );","random.streams.geometric.objectMode":"\nrandom.streams.geometric.objectMode( p[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a geometric distribution.\n\n    Parameters\n    ----------\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.geometric.objectMode( 0.3, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.geometric, random.iterators.geometric","random.streams.gumbel":"\nrandom.streams.gumbel( μ, β[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Gumbel distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.gumbel( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.gumbel.factory( [μ, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Gumbel distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.gumbel.factory( opts );\n\n\nrandom.streams.gumbel.objectMode( μ, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Gumbel distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.gumbel.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.gumbel, random.iterators.gumbel\n","random.streams.gumbel.factory":"\nrandom.streams.gumbel.factory( [μ, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Gumbel distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.gumbel.factory( opts );","random.streams.gumbel.objectMode":"\nrandom.streams.gumbel.objectMode( μ, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Gumbel distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.gumbel.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.gumbel, random.iterators.gumbel","random.streams.hypergeometric":"\nrandom.streams.hypergeometric( N, K, n[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    hypergeometric distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.hypergeometric( 5, 3, 2, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.hypergeometric.factory( [N, K, n,][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a hypergeometric distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    N: integer (optional)\n        Population size.\n\n    K: integer (optional)\n        Subpopulation size.\n\n    n: integer (optional)\n        Number of draws.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.hypergeometric.factory( opts );\n\n\nrandom.streams.hypergeometric.objectMode( N, K, n[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a hypergeometric distribution.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.hypergeometric.objectMode( 5, 3, 2, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.hypergeometric, random.iterators.hypergeometric\n","random.streams.hypergeometric.factory":"\nrandom.streams.hypergeometric.factory( [N, K, n,][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a hypergeometric distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    N: integer (optional)\n        Population size.\n\n    K: integer (optional)\n        Subpopulation size.\n\n    n: integer (optional)\n        Number of draws.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.hypergeometric.factory( opts );","random.streams.hypergeometric.objectMode":"\nrandom.streams.hypergeometric.objectMode( N, K, n[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a hypergeometric distribution.\n\n    Parameters\n    ----------\n    N: integer\n        Population size.\n\n    K: integer\n        Subpopulation size.\n\n    n: integer\n        Number of draws.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.hypergeometric.objectMode( 5, 3, 2, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.hypergeometric, random.iterators.hypergeometric","random.streams.improvedZiggurat":"\nrandom.streams.improvedZiggurat( [options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    standard normal distribution using the Improved Ziggurat algorithm.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.improvedZiggurat( opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.improvedZiggurat.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a standard normal distribution using the Improved\n    Ziggurat algorithm.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.improvedZiggurat.factory( opts );\n\n\nrandom.streams.improvedZiggurat.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a standard normal distribution using the Improved Ziggurat\n    algorithm.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.improvedZiggurat.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.improvedZiggurat, random.iterators.improvedZiggurat, random.streams.boxMuller, random.streams.randn\n","random.streams.improvedZiggurat.factory":"\nrandom.streams.improvedZiggurat.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a standard normal distribution using the Improved\n    Ziggurat algorithm.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.improvedZiggurat.factory( opts );","random.streams.improvedZiggurat.objectMode":"\nrandom.streams.improvedZiggurat.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a standard normal distribution using the Improved Ziggurat\n    algorithm.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.improvedZiggurat.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.improvedZiggurat, random.iterators.improvedZiggurat, random.streams.boxMuller, random.streams.randn","random.streams.invgamma":"\nrandom.streams.invgamma( α, β[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from an\n    inverse gamma distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.invgamma( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.invgamma.factory( [α, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an inverse gamma distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.invgamma.factory( opts );\n\n\nrandom.streams.invgamma.objectMode( α, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an inverse gamma distribution.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.invgamma.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.invgamma, random.iterators.invgamma\n","random.streams.invgamma.factory":"\nrandom.streams.invgamma.factory( [α, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an inverse gamma distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.invgamma.factory( opts );","random.streams.invgamma.objectMode":"\nrandom.streams.invgamma.objectMode( α, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an inverse gamma distribution.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.invgamma.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.invgamma, random.iterators.invgamma","random.streams.kumaraswamy":"\nrandom.streams.kumaraswamy( a, b[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Kumaraswamy's double bounded distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.kumaraswamy( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.kumaraswamy.factory( [a, b, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Kumaraswamy's double bounded distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        First shape parameter.\n\n    b: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.kumaraswamy.factory( opts );\n\n\nrandom.streams.kumaraswamy.objectMode( a, b[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Kumaraswamy's double bounded distribution.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.kumaraswamy.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.kumaraswamy, random.iterators.kumaraswamy\n","random.streams.kumaraswamy.factory":"\nrandom.streams.kumaraswamy.factory( [a, b, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Kumaraswamy's double bounded distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        First shape parameter.\n\n    b: number (optional)\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.kumaraswamy.factory( opts );","random.streams.kumaraswamy.objectMode":"\nrandom.streams.kumaraswamy.objectMode( a, b[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Kumaraswamy's double bounded distribution.\n\n    Parameters\n    ----------\n    a: number\n        First shape parameter.\n\n    b: number\n        Second shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.kumaraswamy.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.kumaraswamy, random.iterators.kumaraswamy","random.streams.laplace":"\nrandom.streams.laplace( μ, b[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Laplace (double exponential) distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    b: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.laplace( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.laplace.factory( [μ, b, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Laplace (double exponential) distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    b: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.laplace.factory( opts );\n\n\nrandom.streams.laplace.objectMode( μ, b[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Laplace (double exponential) distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    b: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.laplace.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.laplace, random.iterators.laplace\n","random.streams.laplace.factory":"\nrandom.streams.laplace.factory( [μ, b, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Laplace (double exponential) distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    b: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.laplace.factory( opts );","random.streams.laplace.objectMode":"\nrandom.streams.laplace.objectMode( μ, b[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Laplace (double exponential) distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    b: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.laplace.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.laplace, random.iterators.laplace","random.streams.levy":"\nrandom.streams.levy( μ, c[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Lévy distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    c: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.levy( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.levy.factory( [μ, c, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Lévy distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    c: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.levy.factory( opts );\n\n\nrandom.streams.levy.objectMode( μ, c[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Lévy distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    c: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.levy.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.levy, random.iterators.levy\n","random.streams.levy.factory":"\nrandom.streams.levy.factory( [μ, c, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Lévy distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    c: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.levy.factory( opts );","random.streams.levy.objectMode":"\nrandom.streams.levy.objectMode( μ, c[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Lévy distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    c: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.levy.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.levy, random.iterators.levy","random.streams.logistic":"\nrandom.streams.logistic( μ, s[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    logistic distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    s: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.logistic( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.logistic.factory( [μ, s, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a logistic distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.logistic.factory( opts );\n\n\nrandom.streams.logistic.objectMode( μ, s[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a logistic distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    s: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.logistic.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.logistic, random.iterators.logistic\n","random.streams.logistic.factory":"\nrandom.streams.logistic.factory( [μ, s, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a logistic distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    s: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.logistic.factory( opts );","random.streams.logistic.objectMode":"\nrandom.streams.logistic.objectMode( μ, s[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a logistic distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    s: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.logistic.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.logistic, random.iterators.logistic","random.streams.lognormal":"\nrandom.streams.lognormal( μ, σ[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    lognormal distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.lognormal( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.lognormal.factory( [μ, σ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a lognormal distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter.\n\n    σ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.lognormal.factory( opts );\n\n\nrandom.streams.lognormal.objectMode( μ, σ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a lognormal distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.lognormal.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.lognormal, random.iterators.lognormal\n","random.streams.lognormal.factory":"\nrandom.streams.lognormal.factory( [μ, σ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a lognormal distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Location parameter.\n\n    σ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.lognormal.factory( opts );","random.streams.lognormal.objectMode":"\nrandom.streams.lognormal.objectMode( μ, σ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a lognormal distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Location parameter.\n\n    σ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.lognormal.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.lognormal, random.iterators.lognormal","random.streams.minstd":"\nrandom.streams.minstd( [options] )\n    Returns a readable stream for generating pseudorandom numbers on the\n    interval `[1, 2147483646]`.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    The underlying pseudorandom number generator (PRNG) is a linear congruential\n    pseudorandom number generator (LCG) based on Park and Miller.\n\n    The generator has a period of approximately `2.1e9`.\n\n    An LCG is fast and uses little memory. On the other hand, because the\n    generator is a simple LCG, the generator has recognized shortcomings. By\n    today's PRNG standards, the generator's period is relatively short. More\n    importantly, the \"randomness quality\" of the generator's output is lacking.\n    These defects make the generator unsuitable, for example, in Monte Carlo\n    simulations and in cryptographic applications.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.seed: Int32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Int32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.minstd( opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.minstd.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers on the interval `[1, 2147483646]`.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.minstd.factory( opts );\n\n\nrandom.streams.minstd.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    on the interval `[1, 2147483646]`.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.seed: Int32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Int32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.minstd.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.minstd, random.iterators.minstd, random.streams.minstdShuffle, random.streams.mt19937, random.streams.randi, random.streams.randu\n","random.streams.minstd.factory":"\nrandom.streams.minstd.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers on the interval `[1, 2147483646]`.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.minstd.factory( opts );","random.streams.minstd.objectMode":"\nrandom.streams.minstd.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    on the interval `[1, 2147483646]`.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.seed: Int32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Int32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.minstd.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.minstd, random.iterators.minstd, random.streams.minstdShuffle, random.streams.mt19937, random.streams.randi, random.streams.randu","random.streams.minstdShuffle":"\nrandom.streams.minstdShuffle( [options] )\n    Returns a readable stream for generating pseudorandom numbers on the\n    interval `[1, 2147483646]`.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    The underlying pseudorandom number generator (PRNG) is a linear congruential\n    pseudorandom number generator (LCG) whose output is shuffled using the Bays-\n    Durham algorithm. The shuffle step considerably strengthens the \"randomness\n    quality\" of a simple LCG's output.\n\n    The generator has a period of approximately `2.1e9`.\n\n    An LCG is fast and uses little memory. On the other hand, because the\n    generator is a simple LCG, the generator has recognized shortcomings. By\n    today's PRNG standards, the generator's period is relatively short. In\n    general, this generator is unsuitable for Monte Carlo simulations and\n    cryptographic applications.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.seed: Int32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Int32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.minstdShuffle( opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.minstdShuffle.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers on the interval `[1, 2147483646]`.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.minstdShuffle.factory( opts );\n\n\nrandom.streams.minstdShuffle.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    on the interval `[1, 2147483646]`.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.seed: Int32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Int32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.minstdShuffle.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstd, random.streams.mt19937, random.streams.randi, random.streams.randu\n","random.streams.minstdShuffle.factory":"\nrandom.streams.minstdShuffle.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers on the interval `[1, 2147483646]`.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.minstdShuffle.factory( opts );","random.streams.minstdShuffle.objectMode":"\nrandom.streams.minstdShuffle.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    on the interval `[1, 2147483646]`.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing signed 32-bit integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.seed: Int32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Int32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.minstdShuffle.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.minstdShuffle, random.iterators.minstdShuffle, random.streams.minstd, random.streams.mt19937, random.streams.randi, random.streams.randu","random.streams.mt19937":"\nrandom.streams.mt19937( [options] )\n    Returns a readable stream for generating pseudorandom numbers on the\n    interval `[1, 4294967295]`.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    The underlying pseudorandom number generator (PRNG) is a 32-bit Mersenne\n    Twister pseudorandom number generator.\n\n    The PRNG is *not* a cryptographically secure PRNG.\n\n    The PRNG has a period of 2^19937 - 1.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.mt19937( opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.mt19937.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers on the interval `[1, 4294967295]`.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.mt19937.factory( opts );\n\n\nrandom.streams.mt19937.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    on the interval `[1, 4294967295]`.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.mt19937.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.mt19937, random.iterators.mt19937, random.streams.minstd, random.streams.minstdShuffle, random.streams.randi, random.streams.randu\n","random.streams.mt19937.factory":"\nrandom.streams.mt19937.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers on the interval `[1, 4294967295]`.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.mt19937.factory( opts );","random.streams.mt19937.objectMode":"\nrandom.streams.mt19937.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    on the interval `[1, 4294967295]`.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.normalized: boolean (optional)\n        Boolean indicating whether to return pseudorandom numbers on the\n        interval `[0,1)`.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.mt19937.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.mt19937, random.iterators.mt19937, random.streams.minstd, random.streams.minstdShuffle, random.streams.randi, random.streams.randu","random.streams.negativeBinomial":"\nrandom.streams.negativeBinomial( r, p[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    negative binomial distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    r: number\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.negativeBinomial( 20.0, 0.5, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.negativeBinomial.factory( [r, p, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a negative binomial distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    r: number (optional)\n        Number of successes until experiment is stopped.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.negativeBinomial.factory( opts );\n\n\nrandom.streams.negativeBinomial.objectMode( r, p[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a negative binomial distribution.\n\n    Parameters\n    ----------\n    r: integer\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.negativeBinomial.objectMode( 20.0, 0.5, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.negativeBinomial, random.iterators.negativeBinomial\n","random.streams.negativeBinomial.factory":"\nrandom.streams.negativeBinomial.factory( [r, p, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a negative binomial distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    r: number (optional)\n        Number of successes until experiment is stopped.\n\n    p: number (optional)\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.negativeBinomial.factory( opts );","random.streams.negativeBinomial.objectMode":"\nrandom.streams.negativeBinomial.objectMode( r, p[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a negative binomial distribution.\n\n    Parameters\n    ----------\n    r: integer\n        Number of successes until experiment is stopped.\n\n    p: number\n        Success probability.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.negativeBinomial.objectMode( 20.0, 0.5, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.negativeBinomial, random.iterators.negativeBinomial","random.streams.normal":"\nrandom.streams.normal( μ, σ[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    normal distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    σ: number\n        Standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.normal( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.normal.factory( [μ, σ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a normal distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    σ: number (optional)\n        Standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.normal.factory( opts );\n\n\nrandom.streams.normal.objectMode( μ, σ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a normal distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    σ: number\n        Standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.normal.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.normal, random.iterators.normal\n","random.streams.normal.factory":"\nrandom.streams.normal.factory( [μ, σ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a normal distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    μ: number (optional)\n        Mean.\n\n    σ: number (optional)\n        Standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.normal.factory( opts );","random.streams.normal.objectMode":"\nrandom.streams.normal.objectMode( μ, σ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a normal distribution.\n\n    Parameters\n    ----------\n    μ: number\n        Mean.\n\n    σ: number\n        Standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.normal.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.normal, random.iterators.normal","random.streams.pareto1":"\nrandom.streams.pareto1( α, β[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Pareto (Type I) distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.pareto1( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.pareto1.factory( [α, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Pareto (Type I) distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.pareto1.factory( opts );\n\n\nrandom.streams.pareto1.objectMode( α, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Pareto (Type I) distribution.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.pareto1.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.pareto1, random.iterators.pareto1\n","random.streams.pareto1.factory":"\nrandom.streams.pareto1.factory( [α, β, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Pareto (Type I) distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    α: number (optional)\n        Shape parameter.\n\n    β: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.pareto1.factory( opts );","random.streams.pareto1.objectMode":"\nrandom.streams.pareto1.objectMode( α, β[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Pareto (Type I) distribution.\n\n    Parameters\n    ----------\n    α: number\n        Shape parameter.\n\n    β: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.pareto1.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.pareto1, random.iterators.pareto1","random.streams.poisson":"\nrandom.streams.poisson( λ[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Poisson distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    λ: number\n        Mean.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.poisson( 3.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.poisson.factory( [λ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Poisson distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    λ: number (optional)\n        Mean.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.poisson.factory( opts );\n\n\nrandom.streams.poisson.objectMode( λ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Poisson distribution.\n\n    Parameters\n    ----------\n    λ: number\n        Mean.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.poisson.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.poisson, random.iterators.poisson\n","random.streams.poisson.factory":"\nrandom.streams.poisson.factory( [λ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Poisson distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    λ: number (optional)\n        Mean.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.poisson.factory( opts );","random.streams.poisson.objectMode":"\nrandom.streams.poisson.objectMode( λ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Poisson distribution.\n\n    Parameters\n    ----------\n    λ: number\n        Mean.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.poisson.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.poisson, random.iterators.poisson","random.streams.randi":"\nrandom.streams.randi( [options] )\n    Returns a readable stream for generating pseudorandom numbers having integer\n    values.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    The default underlying pseudorandom number generator (PRNG) *may* change in\n    the future. If exact reproducibility is required, either explicitly specify\n    a PRNG via the `name` option or use an underlying PRNG directly.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: any\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer\n        Length of generator seed.\n\n    stream.state: any\n        Generator state.\n\n    stream.stateLength: integer\n        Length of generator state.\n\n    stream.byteLength: integer\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.randi( opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.randi.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers having integer values.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.randi.factory( opts );\n\n\nrandom.streams.randi.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    having integer values.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: any\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer\n        Length of generator seed.\n\n    stream.state: any\n        Generator state.\n\n    stream.stateLength: integer\n        Length of generator state.\n\n    stream.byteLength: integer\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.randi.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.randi, random.iterators.randi, random.streams.randu\n","random.streams.randi.factory":"\nrandom.streams.randi.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers having integer values.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.randi.factory( opts );","random.streams.randi.objectMode":"\nrandom.streams.randi.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    having integer values.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: any\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer\n        Length of generator seed.\n\n    stream.state: any\n        Generator state.\n\n    stream.stateLength: integer\n        Length of generator state.\n\n    stream.byteLength: integer\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.randi.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.randi, random.iterators.randi, random.streams.randu","random.streams.randn":"\nrandom.streams.randn( [options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    standard normal distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    The default underlying pseudorandom number generator (PRNG) *may* change in\n    the future. If exact reproducibility is required, either explicitly specify\n    a PRNG via the `name` option or use an underlying PRNG directly.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - improved-ziggurat: improved ziggurat method.\n        - box-muller: Box-Muller transform.\n\n        Default: 'improved-ziggurat'.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.randn( opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.randn.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a standard normal distribution.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - improved-ziggurat: improved ziggurat method.\n        - box-muller: Box-Muller transform.\n\n        Default: 'improved-ziggurat'.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.randn.factory( opts );\n\n\nrandom.streams.randn.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a standard normal distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - improved-ziggurat: improved ziggurat method.\n        - box-muller: Box-Muller transform.\n\n        Default: 'improved-ziggurat'.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.randn.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.randn, random.iterators.randn, random.streams.boxMuller, random.streams.improvedZiggurat\n","random.streams.randn.factory":"\nrandom.streams.randn.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a standard normal distribution.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - improved-ziggurat: improved ziggurat method.\n        - box-muller: Box-Muller transform.\n\n        Default: 'improved-ziggurat'.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.randn.factory( opts );","random.streams.randn.objectMode":"\nrandom.streams.randn.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a standard normal distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - improved-ziggurat: improved ziggurat method.\n        - box-muller: Box-Muller transform.\n\n        Default: 'improved-ziggurat'.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.randn.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.randn, random.iterators.randn, random.streams.boxMuller, random.streams.improvedZiggurat","random.streams.randu":"\nrandom.streams.randu( [options] )\n    Returns a readable stream for generating uniformly distributed pseudorandom\n    numbers between 0 and 1.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    The default underlying pseudorandom number generator (PRNG) *may* change in\n    the future. If exact reproducibility is required, either explicitly specify\n    a PRNG via the `name` option or use an underlying PRNG directly.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: any\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer\n        Length of generator seed.\n\n    stream.state: any\n        Generator state.\n\n    stream.stateLength: integer\n        Length of generator state.\n\n    stream.byteLength: integer\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.randu( opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.randu.factory( [options] )\n    Returns a function for creating readable streams which generate uniformly\n    distributed pseudorandom numbers between 0 and 1.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.randu.factory( opts );\n\n\nrandom.streams.randu.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating uniformly distributed\n    pseudorandom numbers between 0 and 1.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: any\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer\n        Length of generator seed.\n\n    stream.state: any\n        Generator state.\n\n    stream.stateLength: integer\n        Length of generator state.\n\n    stream.byteLength: integer\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.randu.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.randu, random.iterators.randu, random.streams.randi\n","random.streams.randu.factory":"\nrandom.streams.randu.factory( [options] )\n    Returns a function for creating readable streams which generate uniformly\n    distributed pseudorandom numbers between 0 and 1.\n\n    Parameters\n    ----------\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.randu.factory( opts );","random.streams.randu.objectMode":"\nrandom.streams.randu.objectMode( [options] )\n    Returns an \"objectMode\" readable stream for generating uniformly distributed\n    pseudorandom numbers between 0 and 1.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: 'mt19937'.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: any\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer\n        Length of generator seed.\n\n    stream.state: any\n        Generator state.\n\n    stream.stateLength: integer\n        Length of generator state.\n\n    stream.byteLength: integer\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.randu.objectMode( opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.randu, random.iterators.randu, random.streams.randi","random.streams.rayleigh":"\nrandom.streams.rayleigh( σ[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Rayleigh distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.rayleigh( 3.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.rayleigh.factory( [σ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Rayleigh distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    σ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.rayleigh.factory( opts );\n\n\nrandom.streams.rayleigh.objectMode( σ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Rayleigh distribution.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.rayleigh.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.rayleigh, random.iterators.rayleigh\n","random.streams.rayleigh.factory":"\nrandom.streams.rayleigh.factory( [σ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Rayleigh distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    σ: number (optional)\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.rayleigh.factory( opts );","random.streams.rayleigh.objectMode":"\nrandom.streams.rayleigh.objectMode( σ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Rayleigh distribution.\n\n    Parameters\n    ----------\n    σ: number\n        Scale parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.rayleigh.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.rayleigh, random.iterators.rayleigh","random.streams.t":"\nrandom.streams.t( v[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Student's t distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.t( 3.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.t.factory( [v, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Student's t distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    v: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.t.factory( opts );\n\n\nrandom.streams.t.objectMode( v[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Student's t distribution.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.t.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.t, random.iterators.t\n","random.streams.t.factory":"\nrandom.streams.t.factory( [v, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Student's t distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    v: number (optional)\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.t.factory( opts );","random.streams.t.objectMode":"\nrandom.streams.t.objectMode( v[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Student's t distribution.\n\n    Parameters\n    ----------\n    v: number\n        Degrees of freedom.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.t.objectMode( 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.t, random.iterators.t","random.streams.triangular":"\nrandom.streams.triangular( a, b, c[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    triangular distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.triangular( 2.0, 5.0, 4.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.triangular.factory( [a, b, c, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a triangular distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    c: number (optional)\n        Mode.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.triangular.factory( opts );\n\n\nrandom.streams.triangular.objectMode( a, b, c[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a triangular distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.triangular.objectMode( 2.0, 5.0, 4.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.triangular, random.iterators.triangular\n","random.streams.triangular.factory":"\nrandom.streams.triangular.factory( [a, b, c, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a triangular distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    c: number (optional)\n        Mode.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.triangular.factory( opts );","random.streams.triangular.objectMode":"\nrandom.streams.triangular.objectMode( a, b, c[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a triangular distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    c: number\n        Mode.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.triangular.objectMode( 2.0, 5.0, 4.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.triangular, random.iterators.triangular","random.streams.uniform":"\nrandom.streams.uniform( a, b[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    uniform distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.uniform( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.uniform.factory( [a, b, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a uniform distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.uniform.factory( opts );\n\n\nrandom.streams.uniform.objectMode( a, b[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a uniform distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.uniform.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.uniform, random.iterators.uniform\n","random.streams.uniform.factory":"\nrandom.streams.uniform.factory( [a, b, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a uniform distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    a: number (optional)\n        Minimum support.\n\n    b: number (optional)\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.uniform.factory( opts );","random.streams.uniform.objectMode":"\nrandom.streams.uniform.objectMode( a, b[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a uniform distribution.\n\n    Parameters\n    ----------\n    a: number\n        Minimum support.\n\n    b: number\n        Maximum support.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.uniform.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.uniform, random.iterators.uniform","random.streams.weibull":"\nrandom.streams.weibull( k, λ[, options] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Weibull distribution.\n\n    In addition to standard readable stream events, the returned stream emits a\n    'state' event after internally generating `siter` pseudorandom numbers,\n    which is useful when wanting to deterministically capture a stream's\n    underlying PRNG state.\n\n    Parameters\n    ----------\n    k: number\n        Scale parameter.\n\n    λ: number\n        Shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.weibull( 2.0, 5.0, opts );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nrandom.streams.weibull.factory( [k, λ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Weibull distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Scale parameter.\n\n    λ: number (optional)\n        Shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.weibull.factory( opts );\n\n\nrandom.streams.weibull.objectMode( k, λ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Weibull distribution.\n\n    Parameters\n    ----------\n    k: number\n        Scale parameter.\n\n    λ: number\n        Shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.weibull.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.weibull, random.iterators.weibull\n","random.streams.weibull.factory":"\nrandom.streams.weibull.factory( [k, λ, ][options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Weibull distribution.\n\n    If provided distribution parameters, the returned function returns readable\n    streams which generate pseudorandom numbers drawn from the specified\n    distribution.\n\n    If not provided distribution parameters, the returned function requires that\n    distribution parameters be provided at each invocation.\n\n    Parameters\n    ----------\n    k: number (optional)\n        Scale parameter.\n\n    λ: number (optional)\n        Shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = random.streams.weibull.factory( opts );","random.streams.weibull.objectMode":"\nrandom.streams.weibull.objectMode( k, λ[, options] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Weibull distribution.\n\n    Parameters\n    ----------\n    k: number\n        Scale parameter.\n\n    λ: number\n        Shape parameter.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to generate additional pseudorandom numbers.\n\n    options.iter: integer (optional)\n        Number of iterations.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned iterator, one must seed the provided `prng` (assuming the\n        provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned iterator has exclusive control over\n        its internal state. Default: true.\n\n    options.siter: integer (optional)\n        Number of iterations after which to emit the PRNG state. Default: 1e308.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    stream.PRNG: Function\n        Underlying pseudorandom number generator.\n\n    stream.seed: Uint32Array|null\n        Pseudorandom number generator seed.\n\n    stream.seedLength: integer|null\n        Length of generator seed.\n\n    stream.state: Uint32Array|null\n        Generator state.\n\n    stream.stateLength: integer|null\n        Length of generator state.\n\n    stream.byteLength: integer|null\n        Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var opts = { 'iter': 10 };\n    > var s = random.streams.weibull.objectMode( 2.0, 5.0, opts );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    base.random.weibull, random.iterators.weibull","random.strided.arcsine":"\nrandom.strided.arcsine( N, a, sa, b, sb, out, so[, options] )\n    Fills a strided array with pseudorandom numbers drawn from an arcsine\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    a: ArrayLikeObject\n        Minimum support.\n\n    sa: integer\n        Index increment for `a`.\n\n    b: ArrayLikeObject\n        Maximum support.\n\n    sb: integer\n        Index increment for `b`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 0.0, 1.0, 5 );\n    > var b = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.arcsine( out.length, a, 1, b, 1, out, 1 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 0.0, 1.0, 6 );\n    > b = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.arcsine( 3, a, -2, b, 1, out, 1 )\n    [...]\n\n\nrandom.strided.arcsine.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from an arcsine\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    a: ArrayLikeObject\n        Minimum support.\n\n    sa: integer\n        Index increment for `a`.\n\n    oa: integer\n        Starting index for `a`.\n\n    b: ArrayLikeObject\n        Maximum support.\n\n    sb: integer\n        Index increment for `b`.\n\n    ob: integer\n        Starting index for `b`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 0.0, 1.0, 5 );\n    > var b = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.arcsine.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 0.0, 1.0, 6 );\n    > b = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.arcsine.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.arcsine, random.array.arcsine\n","random.strided.arcsine.ndarray":"\nrandom.strided.arcsine.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from an arcsine\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    a: ArrayLikeObject\n        Minimum support.\n\n    sa: integer\n        Index increment for `a`.\n\n    oa: integer\n        Starting index for `a`.\n\n    b: ArrayLikeObject\n        Maximum support.\n\n    sb: integer\n        Index increment for `b`.\n\n    ob: integer\n        Starting index for `b`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 0.0, 1.0, 5 );\n    > var b = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.arcsine.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 0.0, 1.0, 6 );\n    > b = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.arcsine.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.arcsine, random.array.arcsine","random.strided.bernoulli":"\nrandom.strided.bernoulli( N, p, sp, out, so )\n    Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    p: ArrayLikeObject\n        Success probability.\n\n    sp: integer\n        Index increment for `p`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.bernoulli.ndarray( N, p, sp, op, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    p: ArrayLikeObject\n        Success probability.\n\n    sp: integer\n        Index increment for `p`.\n\n    op: integer\n        Starting index for `p`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.bernoulli.ndarray( out.length, [ 0.5 ], 0, 0, out, 1, 0 )\n    [...]\n\n\nrandom.strided.bernoulli.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Bernoulli distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.bernoulli.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 0.5 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.bernoulli.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.bernoulli.PRNG;\n\n\nrandom.strided.bernoulli.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.bernoulli.seed;\n\n\nrandom.strided.bernoulli.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.bernoulli.seedLength;\n\n\nrandom.strided.bernoulli.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.bernoulli.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.bernoulli.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.bernoulli.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.bernoulli.stateLength;\n\n\nrandom.strided.bernoulli.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.bernoulli.byteLength;\n\n    See Also\n    --------\n    base.random.bernoulli, random.array.bernoulli\n","random.strided.bernoulli.ndarray":"\nrandom.strided.bernoulli.ndarray( N, p, sp, op, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    p: ArrayLikeObject\n        Success probability.\n\n    sp: integer\n        Index increment for `p`.\n\n    op: integer\n        Starting index for `p`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.bernoulli.ndarray( out.length, [ 0.5 ], 0, 0, out, 1, 0 )\n    [...]","random.strided.bernoulli.factory":"\nrandom.strided.bernoulli.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Bernoulli distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.bernoulli.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 0.5 ], 0, out, 1 )\n    [...]","random.strided.bernoulli.PRNG":"\nrandom.strided.bernoulli.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.bernoulli.PRNG;","random.strided.bernoulli.seed":"\nrandom.strided.bernoulli.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.bernoulli.seed;","random.strided.bernoulli.seedLength":"\nrandom.strided.bernoulli.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.bernoulli.seedLength;","random.strided.bernoulli.state":"\nrandom.strided.bernoulli.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.bernoulli.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.bernoulli.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.bernoulli( out.length, [ 0.5 ], 0, out, 1 )\n    [...]","random.strided.bernoulli.stateLength":"\nrandom.strided.bernoulli.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.bernoulli.stateLength;","random.strided.bernoulli.byteLength":"\nrandom.strided.bernoulli.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.bernoulli.byteLength;\n\n    See Also\n    --------\n    base.random.bernoulli, random.array.bernoulli","random.strided.beta":"\nrandom.strided.beta( N, alpha, sa, beta, sb, out, so[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a beta\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        First shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    beta: ArrayLikeObject\n        Second shape parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.beta( out.length, a, 1, b, 1, out, 1 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.beta( 3, a, -2, b, 1, out, 1 )\n    [...]\n\n\nrandom.strided.beta.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a beta\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        First shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    oa: integer\n        Starting index for `alpha`.\n\n    beta: ArrayLikeObject\n        Second shape parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    ob: integer\n        Starting index for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.beta.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.beta.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.beta, random.array.beta\n","random.strided.beta.ndarray":"\nrandom.strided.beta.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a beta\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        First shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    oa: integer\n        Starting index for `alpha`.\n\n    beta: ArrayLikeObject\n        Second shape parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    ob: integer\n        Starting index for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.beta.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.beta.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.beta, random.array.beta","random.strided.betaprime":"\nrandom.strided.betaprime( N, alpha, sa, beta, sb, out, so[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a beta prime\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        First shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    beta: ArrayLikeObject\n        Second shape parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.betaprime( out.length, a, 1, b, 1, out, 1 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.betaprime( 3, a, -2, b, 1, out, 1 )\n    [...]\n\n\nrandom.strided.betaprime.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a beta prime\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        First shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    oa: integer\n        Starting index for `alpha`.\n\n    beta: ArrayLikeObject\n        Second shape parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    ob: integer\n        Starting index for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.betaprime.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.betaprime.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.betaprime, random.array.betaprime\n","random.strided.betaprime.ndarray":"\nrandom.strided.betaprime.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a beta prime\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        First shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    oa: integer\n        Starting index for `alpha`.\n\n    beta: ArrayLikeObject\n        Second shape parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    ob: integer\n        Starting index for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.betaprime.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.betaprime.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.betaprime, random.array.betaprime","random.strided.chi":"\nrandom.strided.chi( N, k, sk, out, so )\n    Fills a strided array with pseudorandom numbers drawn from a chi\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    k: ArrayLikeObject\n        Degrees of freedom.\n\n    sk: integer\n        Index increment for `k`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.chi.ndarray( N, k, sk, ok, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a chi\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    k: ArrayLikeObject\n        Degrees of freedom.\n\n    sk: integer\n        Index increment for `k`.\n\n    ok: integer\n        Starting index for `k`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.chi.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]\n\n\nrandom.strided.chi.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a chi distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.chi.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.chi.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.chi.PRNG;\n\n\nrandom.strided.chi.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.chi.seed;\n\n\nrandom.strided.chi.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.chi.seedLength;\n\n\nrandom.strided.chi.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.chi.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.chi.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.chi.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.chi.stateLength;\n\n\nrandom.strided.chi.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.chi.byteLength;\n\n    See Also\n    --------\n    base.random.chi, random.array.chi\n","random.strided.chi.ndarray":"\nrandom.strided.chi.ndarray( N, k, sk, ok, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a chi\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    k: ArrayLikeObject\n        Degrees of freedom.\n\n    sk: integer\n        Index increment for `k`.\n\n    ok: integer\n        Starting index for `k`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.chi.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]","random.strided.chi.factory":"\nrandom.strided.chi.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a chi distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.chi.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.chi.PRNG":"\nrandom.strided.chi.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.chi.PRNG;","random.strided.chi.seed":"\nrandom.strided.chi.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.chi.seed;","random.strided.chi.seedLength":"\nrandom.strided.chi.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.chi.seedLength;","random.strided.chi.state":"\nrandom.strided.chi.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.chi.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.chi.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.chi( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.chi.stateLength":"\nrandom.strided.chi.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.chi.stateLength;","random.strided.chi.byteLength":"\nrandom.strided.chi.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.chi.byteLength;\n\n    See Also\n    --------\n    base.random.chi, random.array.chi","random.strided.chisquare":"\nrandom.strided.chisquare( N, k, sk, out, so )\n    Fills a strided array with pseudorandom numbers drawn from a chi-square\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    k: ArrayLikeObject\n        Degrees of freedom.\n\n    sk: integer\n        Index increment for `k`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.chisquare.ndarray( N, k, sk, ok, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a chi-square\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    k: ArrayLikeObject\n        Degrees of freedom.\n\n    sk: integer\n        Index increment for `k`.\n\n    ok: integer\n        Starting index for `k`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.chisquare.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]\n\n\nrandom.strided.chisquare.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a chi-square distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.chisquare.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.chisquare.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.chisquare.PRNG;\n\n\nrandom.strided.chisquare.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.chisquare.seed;\n\n\nrandom.strided.chisquare.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.chisquare.seedLength;\n\n\nrandom.strided.chisquare.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.chisquare.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.chisquare.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.chisquare.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.chisquare.stateLength;\n\n\nrandom.strided.chisquare.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.chisquare.byteLength;\n\n    See Also\n    --------\n    base.random.chisquare, random.array.chisquare\n","random.strided.chisquare.ndarray":"\nrandom.strided.chisquare.ndarray( N, k, sk, ok, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a chi-square\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    k: ArrayLikeObject\n        Degrees of freedom.\n\n    sk: integer\n        Index increment for `k`.\n\n    ok: integer\n        Starting index for `k`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.chisquare.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]","random.strided.chisquare.factory":"\nrandom.strided.chisquare.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a chi-square distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.chisquare.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.chisquare.PRNG":"\nrandom.strided.chisquare.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.chisquare.PRNG;","random.strided.chisquare.seed":"\nrandom.strided.chisquare.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.chisquare.seed;","random.strided.chisquare.seedLength":"\nrandom.strided.chisquare.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.chisquare.seedLength;","random.strided.chisquare.state":"\nrandom.strided.chisquare.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.chisquare.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.chisquare.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.chisquare( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.chisquare.stateLength":"\nrandom.strided.chisquare.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.chisquare.stateLength;","random.strided.chisquare.byteLength":"\nrandom.strided.chisquare.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.chisquare.byteLength;\n\n    See Also\n    --------\n    base.random.chisquare, random.array.chisquare","random.strided.cosine":"\nrandom.strided.cosine( N, mu, sm, s, ss, out, so[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a cosine\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mu: ArrayLikeObject\n        Mean.\n\n    sm: integer\n        Index increment for `mu`.\n\n    s: ArrayLikeObject\n        Scale parameter.\n\n    ss: integer\n        Index increment for `s`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var mu = linspace( 0.0, 1.0, 5 );\n    > var s = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.cosine( out.length, mu, 1, s, 1, out, 1 )\n    [...]\n\n    // Advanced indexing:\n    > mu = linspace( 0.0, 1.0, 6 );\n    > s = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.cosine( 3, mu, -2, s, 1, out, 1 )\n    [...]\n\n\nrandom.strided.cosine.ndarray( N, mu, sm, om, s, ss, os, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a cosine\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mu: ArrayLikeObject\n        Mean.\n\n    sm: integer\n        Index increment for `mu`.\n\n    om: integer\n        Starting index for `mu`.\n\n    s: ArrayLikeObject\n        Scale parameter.\n\n    ss: integer\n        Index increment for `s`.\n\n    os: integer\n        Starting index for `s`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var mu = linspace( 0.0, 1.0, 5 );\n    > var s = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.cosine.ndarray( out.length, mu, 1, 0, s, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > mu = linspace( 0.0, 1.0, 6 );\n    > s = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.cosine.ndarray( 3, mu, 2, 1, s, -1, s.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.cosine, random.array.cosine\n","random.strided.cosine.ndarray":"\nrandom.strided.cosine.ndarray( N, mu, sm, om, s, ss, os, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a cosine\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mu: ArrayLikeObject\n        Mean.\n\n    sm: integer\n        Index increment for `mu`.\n\n    om: integer\n        Starting index for `mu`.\n\n    s: ArrayLikeObject\n        Scale parameter.\n\n    ss: integer\n        Index increment for `s`.\n\n    os: integer\n        Starting index for `s`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var mu = linspace( 0.0, 1.0, 5 );\n    > var s = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.cosine.ndarray( out.length, mu, 1, 0, s, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > mu = linspace( 0.0, 1.0, 6 );\n    > s = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.cosine.ndarray( 3, mu, 2, 1, s, -1, s.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.cosine, random.array.cosine","random.strided.discreteUniform":"\nrandom.strided.discreteUniform( N, a, sa, b, sb, out, so[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a discrete\n    uniform distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    a: ArrayLikeObject\n        Minimum support.\n\n    sa: integer\n        Index increment for `a`.\n\n    b: ArrayLikeObject\n        Maximum support.\n\n    sb: integer\n        Index increment for `b`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = [ -10, -5, 0, 5, 10 ];\n    > var b = [ 20, 20, 20, 20, 20 ];\n    > var out = azeros( 5, 'generic' );\n    > random.strided.discreteUniform( out.length, a, 1, b, 1, out, 1 )\n    [...]\n\n    // Advanced indexing:\n    > a = [ -10, -5, 0, 5, 10, 15 ];\n    > b = [ 20, 20, 20, 20, 20, 20 ];\n    > out = azeros( 6, 'generic' );\n    > random.strided.discreteUniform( 3, a, -2, b, 1, out, 1 )\n    [...]\n\n\nrandom.strided.discreteUniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a discrete\n    uniform distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    a: ArrayLikeObject\n        Minimum support.\n\n    sa: integer\n        Index increment for `a`.\n\n    oa: integer\n        Starting index for `a`.\n\n    b: ArrayLikeObject\n        Maximum support.\n\n    sb: integer\n        Index increment for `b`.\n\n    ob: integer\n        Starting index for `b`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = [ -10, -5, 0, 5, 10 ];\n    > var b = [ 20, 20, 20, 20, 20 ];\n    > var out = azeros( 5, 'generic' );\n    > random.strided.discreteUniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = [ -10, -5, 0, 5, 10, 15 ];\n    > b = [ 20, 20, 20, 20, 20, 20 ];\n    > out = azeros( 6, 'generic' );\n    > random.strided.discreteUniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.discreteUniform, random.array.discreteUniform, random.strided.uniform\n","random.strided.discreteUniform.ndarray":"\nrandom.strided.discreteUniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a discrete\n    uniform distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    a: ArrayLikeObject\n        Minimum support.\n\n    sa: integer\n        Index increment for `a`.\n\n    oa: integer\n        Starting index for `a`.\n\n    b: ArrayLikeObject\n        Maximum support.\n\n    sb: integer\n        Index increment for `b`.\n\n    ob: integer\n        Starting index for `b`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = [ -10, -5, 0, 5, 10 ];\n    > var b = [ 20, 20, 20, 20, 20 ];\n    > var out = azeros( 5, 'generic' );\n    > random.strided.discreteUniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = [ -10, -5, 0, 5, 10, 15 ];\n    > b = [ 20, 20, 20, 20, 20, 20 ];\n    > out = azeros( 6, 'generic' );\n    > random.strided.discreteUniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.discreteUniform, random.array.discreteUniform, random.strided.uniform","random.strided.exponential":"\nrandom.strided.exponential( N, lambda, sl, out, so )\n    Fills a strided array with pseudorandom numbers drawn from an exponential\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    lambda: ArrayLikeObject\n        Rate parameter.\n\n    sl: integer\n        Index increment for `lambda`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.exponential.ndarray( N, lambda, sl, ol, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from an exponential\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    lambda: ArrayLikeObject\n        Rate parameter.\n\n    sl: integer\n        Index increment for `lambda`.\n\n    ol: integer\n        Starting index for `lambda`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.exponential.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]\n\n\nrandom.strided.exponential.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from an exponential distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.exponential.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.exponential.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.exponential.PRNG;\n\n\nrandom.strided.exponential.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.exponential.seed;\n\n\nrandom.strided.exponential.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.exponential.seedLength;\n\n\nrandom.strided.exponential.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.exponential.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.exponential.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.exponential.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.exponential.stateLength;\n\n\nrandom.strided.exponential.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.exponential.byteLength;\n\n    See Also\n    --------\n    base.random.exponential, random.array.exponential\n","random.strided.exponential.ndarray":"\nrandom.strided.exponential.ndarray( N, lambda, sl, ol, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from an exponential\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    lambda: ArrayLikeObject\n        Rate parameter.\n\n    sl: integer\n        Index increment for `lambda`.\n\n    ol: integer\n        Starting index for `lambda`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.exponential.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]","random.strided.exponential.factory":"\nrandom.strided.exponential.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from an exponential distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.exponential.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.exponential.PRNG":"\nrandom.strided.exponential.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.exponential.PRNG;","random.strided.exponential.seed":"\nrandom.strided.exponential.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.exponential.seed;","random.strided.exponential.seedLength":"\nrandom.strided.exponential.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.exponential.seedLength;","random.strided.exponential.state":"\nrandom.strided.exponential.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.exponential.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.exponential.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.exponential( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.exponential.stateLength":"\nrandom.strided.exponential.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.exponential.stateLength;","random.strided.exponential.byteLength":"\nrandom.strided.exponential.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.exponential.byteLength;\n\n    See Also\n    --------\n    base.random.exponential, random.array.exponential","random.strided.gamma":"\nrandom.strided.gamma( N, alpha, sa, beta, sb, out, so[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a gamma\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        Shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    beta: ArrayLikeObject\n        Rate parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.gamma( out.length, a, 1, b, 1, out, 1 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.gamma( 3, a, -2, b, 1, out, 1 )\n    [...]\n\n\nrandom.strided.gamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a gamma\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        Shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    oa: integer\n        Starting index for `alpha`.\n\n    beta: ArrayLikeObject\n        Rate parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    ob: integer\n        Starting index for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.gamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.gamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.gamma, random.array.gamma\n","random.strided.gamma.ndarray":"\nrandom.strided.gamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a gamma\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        Shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    oa: integer\n        Starting index for `alpha`.\n\n    beta: ArrayLikeObject\n        Rate parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    ob: integer\n        Starting index for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.gamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.gamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.gamma, random.array.gamma","random.strided.geometric":"\nrandom.strided.geometric( N, p, sp, out, so )\n    Fills a strided array with pseudorandom numbers drawn from a geometric\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    p: ArrayLikeObject\n        Success probability.\n\n    sp: integer\n        Index increment for `p`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.geometric.ndarray( N, p, sp, op, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a geometric\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    p: ArrayLikeObject\n        Success probability.\n\n    sp: integer\n        Index increment for `p`.\n\n    op: integer\n        Starting index for `p`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.geometric.ndarray( out.length, [ 0.01 ], 0, 0, out, 1, 0 )\n    [...]\n\n\nrandom.strided.geometric.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a geometric distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.geometric.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 0.01 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.geometric.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.geometric.PRNG;\n\n\nrandom.strided.geometric.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.geometric.seed;\n\n\nrandom.strided.geometric.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.geometric.seedLength;\n\n\nrandom.strided.geometric.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.geometric.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.geometric.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.geometric.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.geometric.stateLength;\n\n\nrandom.strided.geometric.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.geometric.byteLength;\n\n    See Also\n    --------\n    base.random.geometric, random.array.geometric\n","random.strided.geometric.ndarray":"\nrandom.strided.geometric.ndarray( N, p, sp, op, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a geometric\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    p: ArrayLikeObject\n        Success probability.\n\n    sp: integer\n        Index increment for `p`.\n\n    op: integer\n        Starting index for `p`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.geometric.ndarray( out.length, [ 0.01 ], 0, 0, out, 1, 0 )\n    [...]","random.strided.geometric.factory":"\nrandom.strided.geometric.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a geometric distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.geometric.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 0.01 ], 0, out, 1 )\n    [...]","random.strided.geometric.PRNG":"\nrandom.strided.geometric.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.geometric.PRNG;","random.strided.geometric.seed":"\nrandom.strided.geometric.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.geometric.seed;","random.strided.geometric.seedLength":"\nrandom.strided.geometric.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.geometric.seedLength;","random.strided.geometric.state":"\nrandom.strided.geometric.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.geometric.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.geometric.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.geometric( out.length, [ 0.01 ], 0, out, 1 )\n    [...]","random.strided.geometric.stateLength":"\nrandom.strided.geometric.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.geometric.stateLength;","random.strided.geometric.byteLength":"\nrandom.strided.geometric.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.geometric.byteLength;\n\n    See Also\n    --------\n    base.random.geometric, random.array.geometric","random.strided.invgamma":"\nrandom.strided.invgamma( N, alpha, sa, beta, sb, out, so[, options] )\n    Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        Shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    beta: ArrayLikeObject\n        Scale parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.invgamma( out.length, a, 1, b, 1, out, 1 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.invgamma( 3, a, -2, b, 1, out, 1 )\n    [...]\n\n\nrandom.strided.invgamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        Shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    oa: integer\n        Starting index for `alpha`.\n\n    beta: ArrayLikeObject\n        Scale parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    ob: integer\n        Starting index for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.invgamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.invgamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.invgamma, random.array.invgamma\n","random.strided.invgamma.ndarray":"\nrandom.strided.invgamma.ndarray( N, alpha, sa, oa, beta, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    alpha: ArrayLikeObject\n        Shape parameter.\n\n    sa: integer\n        Index increment for `alpha`.\n\n    oa: integer\n        Starting index for `alpha`.\n\n    beta: ArrayLikeObject\n        Scale parameter.\n\n    sb: integer\n        Index increment for `beta`.\n\n    ob: integer\n        Starting index for `beta`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.invgamma.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.invgamma.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.invgamma, random.array.invgamma","random.strided.lognormal":"\nrandom.strided.lognormal( N, mu, sm, sigma, ss, out, so[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a lognormal\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mu: ArrayLikeObject\n        Location parameter.\n\n    sm: integer\n        Index increment for `mu`.\n\n    sigma: ArrayLikeObject\n        Scale parameter.\n\n    ss: integer\n        Index increment for `sigma`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var mu = linspace( 0.0, 1.0, 5 );\n    > var sigma = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.lognormal( out.length, mu, 1, sigma, 1, out, 1 )\n    [...]\n\n    // Advanced indexing:\n    > mu = linspace( 0.0, 1.0, 6 );\n    > sigma = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.lognormal( 3, mu, -2, sigma, 1, out, 1 )\n    [...]\n\n\nrandom.strided.lognormal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a lognormal\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mu: ArrayLikeObject\n        Location parameter.\n\n    sm: integer\n        Index increment for `mu`.\n\n    om: integer\n        Starting index for `mu`.\n\n    sigma: ArrayLikeObject\n        Scale parameter.\n\n    ss: integer\n        Index increment for `sigma`.\n\n    os: integer\n        Starting index for `sigma`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var mu = linspace( 0.0, 1.0, 5 );\n    > var sigma = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.lognormal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > mu = linspace( 0.0, 1.0, 6 );\n    > sigma = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.lognormal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.lognormal, random.array.lognormal\n","random.strided.lognormal.ndarray":"\nrandom.strided.lognormal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a lognormal\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mu: ArrayLikeObject\n        Location parameter.\n\n    sm: integer\n        Index increment for `mu`.\n\n    om: integer\n        Starting index for `mu`.\n\n    sigma: ArrayLikeObject\n        Scale parameter.\n\n    ss: integer\n        Index increment for `sigma`.\n\n    os: integer\n        Starting index for `sigma`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var mu = linspace( 0.0, 1.0, 5 );\n    > var sigma = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.lognormal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > mu = linspace( 0.0, 1.0, 6 );\n    > sigma = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.lognormal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.lognormal, random.array.lognormal","random.strided.minstd":"\nrandom.strided.minstd( N, out, so[, options] )\n    Fills a strided array with pseudorandom integers between 1 and 2147483646\n    (inclusive).\n\n    The `N` and stride parameters determine which elements in the provided\n    strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstd( out.length, out, 1 )\n    [...]\n\n\nrandom.strided.minstd.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom integers between 1 and 2147483646\n    (inclusive) using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstd.ndarray( out.length, out, 1, 0 )\n    [...]\n\n\nrandom.strided.minstd.normalized( N, out, so[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstd.normalized( out.length, out, 1 )\n    [...]\n\n\nrandom.strided.minstd.normalized.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1 using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstd.normalized.ndarray( out.length, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.minstd, random.array.minstd, random.strided.minstdShuffle, random.strided.randu\n","random.strided.minstd.ndarray":"\nrandom.strided.minstd.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom integers between 1 and 2147483646\n    (inclusive) using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstd.ndarray( out.length, out, 1, 0 )\n    [...]","random.strided.minstd.normalized":"\nrandom.strided.minstd.normalized( N, out, so[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstd.normalized( out.length, out, 1 )\n    [...]","random.strided.minstd.normalized.ndarray":"\nrandom.strided.minstd.normalized.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1 using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstd.normalized.ndarray( out.length, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.minstd, random.array.minstd, random.strided.minstdShuffle, random.strided.randu","random.strided.minstdShuffle":"\nrandom.strided.minstdShuffle( N, out, so[, options] )\n    Fills a strided array with pseudorandom integers between 1 and 2147483646\n    (inclusive).\n\n    The `N` and stride parameters determine which elements in the provided\n    strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstdShuffle( out.length, out, 1 )\n    [...]\n\n\nrandom.strided.minstdShuffle.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom integers between 1 and 2147483646\n    (inclusive) using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstdShuffle.ndarray( out.length, out, 1, 0 )\n    [...]\n\n\nrandom.strided.minstdShuffle.normalized( N, out, so[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstdShuffle.normalized( out.length, out, 1 )\n    [...]\n\n\nrandom.strided.minstdShuffle.normalized.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1 using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstdShuffle.normalized.ndarray( out.length, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.minstdShuffle, random.array.minstdShuffle, random.strided.minstd, random.strided.randu\n","random.strided.minstdShuffle.ndarray":"\nrandom.strided.minstdShuffle.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom integers between 1 and 2147483646\n    (inclusive) using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstdShuffle.ndarray( out.length, out, 1, 0 )\n    [...]","random.strided.minstdShuffle.normalized":"\nrandom.strided.minstdShuffle.normalized( N, out, so[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstdShuffle.normalized( out.length, out, 1 )\n    [...]","random.strided.minstdShuffle.normalized.ndarray":"\nrandom.strided.minstdShuffle.normalized.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1 using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        signed 32-bit integer on the interval `[1, 2147483646]` or, for\n        arbitrary length seeds, an array-like object containing signed 32-bit\n        integers.\n\n    options.state: Int32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.minstdShuffle.normalized.ndarray( out.length, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.minstdShuffle, random.array.minstdShuffle, random.strided.minstd, random.strided.randu","random.strided.mt19937":"\nrandom.strided.mt19937( N, out, so[, options] )\n    Fills a strided array with pseudorandom integers between 0 and 4294967295\n    (inclusive).\n\n    The `N` and stride parameters determine which elements in the provided\n    strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.mt19937( out.length, out, 1 )\n    [...]\n\n\nrandom.strided.mt19937.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom integers between 0 and 4294967295\n    (inclusive) using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.mt19937.ndarray( out.length, out, 1, 0 )\n    [...]\n\n\nrandom.strided.mt19937.normalized( N, out, so[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.mt19937.normalized( out.length, out, 1 )\n    [...]\n\n\nrandom.strided.mt19937.normalized.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1 using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.mt19937.normalized.ndarray( out.length, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.mt19937, random.array.mt19937, random.strided.randu\n","random.strided.mt19937.ndarray":"\nrandom.strided.mt19937.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom integers between 0 and 4294967295\n    (inclusive) using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.mt19937.ndarray( out.length, out, 1, 0 )\n    [...]","random.strided.mt19937.normalized":"\nrandom.strided.mt19937.normalized( N, out, so[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.mt19937.normalized( out.length, out, 1 )\n    [...]","random.strided.mt19937.normalized.ndarray":"\nrandom.strided.mt19937.normalized.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers between 0 and 1 using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.mt19937.normalized.ndarray( out.length, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.mt19937, random.array.mt19937, random.strided.randu","random.strided.normal":"\nrandom.strided.normal( N, mu, sm, sigma, ss, out, so[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a normal\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mu: ArrayLikeObject\n        Mean.\n\n    sm: integer\n        Index increment for `mu`.\n\n    sigma: ArrayLikeObject\n        Standard deviation.\n\n    ss: integer\n        Index increment for `sigma`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var mu = linspace( 0.0, 1.0, 5 );\n    > var sigma = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.normal( out.length, mu, 1, sigma, 1, out, 1 )\n    [...]\n\n    // Advanced indexing:\n    > mu = linspace( 0.0, 1.0, 6 );\n    > sigma = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.normal( 3, mu, -2, sigma, 1, out, 1 )\n    [...]\n\n\nrandom.strided.normal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a normal\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mu: ArrayLikeObject\n        Mean.\n\n    sm: integer\n        Index increment for `mu`.\n\n    om: integer\n        Starting index for `mu`.\n\n    sigma: ArrayLikeObject\n        Standard deviation.\n\n    ss: integer\n        Index increment for `sigma`.\n\n    os: integer\n        Starting index for `sigma`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var mu = linspace( 0.0, 1.0, 5 );\n    > var sigma = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.normal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > mu = linspace( 0.0, 1.0, 6 );\n    > sigma = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.normal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.normal, random.array.normal\n","random.strided.normal.ndarray":"\nrandom.strided.normal.ndarray( N, mu, sm, om, sigma, ss, os, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a normal\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    mu: ArrayLikeObject\n        Mean.\n\n    sm: integer\n        Index increment for `mu`.\n\n    om: integer\n        Starting index for `mu`.\n\n    sigma: ArrayLikeObject\n        Standard deviation.\n\n    ss: integer\n        Index increment for `sigma`.\n\n    os: integer\n        Starting index for `sigma`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var mu = linspace( 0.0, 1.0, 5 );\n    > var sigma = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.normal.ndarray( out.length, mu, 1, 0, sigma, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > mu = linspace( 0.0, 1.0, 6 );\n    > sigma = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.normal.ndarray( 3, mu, 2, 1, sigma, -1, sigma.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.normal, random.array.normal","random.strided.poisson":"\nrandom.strided.poisson( N, lambda, sl, out, so )\n    Fills a strided array with pseudorandom numbers drawn from a Poisson\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    lambda: ArrayLikeObject\n        Mean parameter.\n\n    sl: integer\n        Index increment for `lambda`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.poisson.ndarray( N, lambda, sl, ol, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a Poisson\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    lambda: ArrayLikeObject\n        Mean parameter.\n\n    sl: integer\n        Index increment for `lambda`.\n\n    ol: integer\n        Starting index for `lambda`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.poisson.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]\n\n\nrandom.strided.poisson.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Poisson distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.poisson.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.poisson.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.poisson.PRNG;\n\n\nrandom.strided.poisson.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.poisson.seed;\n\n\nrandom.strided.poisson.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.poisson.seedLength;\n\n\nrandom.strided.poisson.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.poisson.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.poisson.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.poisson.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.poisson.stateLength;\n\n\nrandom.strided.poisson.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.poisson.byteLength;\n\n    See Also\n    --------\n    base.random.poisson, random.array.poisson\n","random.strided.poisson.ndarray":"\nrandom.strided.poisson.ndarray( N, lambda, sl, ol, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a Poisson\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    lambda: ArrayLikeObject\n        Mean parameter.\n\n    sl: integer\n        Index increment for `lambda`.\n\n    ol: integer\n        Starting index for `lambda`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.poisson.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]","random.strided.poisson.factory":"\nrandom.strided.poisson.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Poisson distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.poisson.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.poisson.PRNG":"\nrandom.strided.poisson.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.poisson.PRNG;","random.strided.poisson.seed":"\nrandom.strided.poisson.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.poisson.seed;","random.strided.poisson.seedLength":"\nrandom.strided.poisson.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.poisson.seedLength;","random.strided.poisson.state":"\nrandom.strided.poisson.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.poisson.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.poisson.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.poisson( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.poisson.stateLength":"\nrandom.strided.poisson.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.poisson.stateLength;","random.strided.poisson.byteLength":"\nrandom.strided.poisson.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.poisson.byteLength;\n\n    See Also\n    --------\n    base.random.poisson, random.array.poisson","random.strided.randu":"\nrandom.strided.randu( N, out, so[, options] )\n    Fills a strided array with uniformly distributed pseudorandom numbers\n    between 0 and 1.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided array are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: `'mt19937'`.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.randu( out.length, out, 1 )\n    [...]\n\n\nrandom.strided.randu.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with uniformly distributed pseudorandom numbers\n    between 0 and 1 using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: `'mt19937'`.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.randu.ndarray( out.length, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.randu, random.array.randu, random.strided.uniform\n","random.strided.randu.ndarray":"\nrandom.strided.randu.ndarray( N, out, so, oo[, options] )\n    Fills a strided array with uniformly distributed pseudorandom numbers\n    between 0 and 1 using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.name: string (optional)\n        Name of a supported pseudorandom number generator (PRNG), which will\n        serve as the underlying source of pseudorandom numbers. The following\n        PRNGs are supported:\n\n        - mt19937: 32-bit Mersenne Twister.\n        - minstd: linear congruential PRNG based on Park and Miller.\n        - minstd-shuffle: linear congruential PRNG whose output is shuffled.\n\n        Default: `'mt19937'`.\n\n    options.seed: any (optional)\n        Pseudorandom number generator seed. Valid seed values vary according to\n        the underlying PRNG.\n\n    options.state: any (optional)\n        Pseudorandom number generator state. Valid state values vary according\n        to the underling PRNG. If provided, the `seed` option is ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.randu.ndarray( out.length, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.randu, random.array.randu, random.strided.uniform","random.strided.rayleigh":"\nrandom.strided.rayleigh( N, sigma, ss, out, so )\n    Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sigma: ArrayLikeObject\n        Scale parameter.\n\n    ss: integer\n        Index increment for `sigma`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.rayleigh.ndarray( N, sigma, ss, os, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sigma: ArrayLikeObject\n        Scale parameter.\n\n    ss: integer\n        Index increment for `sigma`.\n\n    os: integer\n        Starting index for `sigma`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.rayleigh.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]\n\n\nrandom.strided.rayleigh.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Rayleigh distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.rayleigh.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.rayleigh.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.rayleigh.PRNG;\n\n\nrandom.strided.rayleigh.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.rayleigh.seed;\n\n\nrandom.strided.rayleigh.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.rayleigh.seedLength;\n\n\nrandom.strided.rayleigh.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.rayleigh.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.rayleigh.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.rayleigh.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.rayleigh.stateLength;\n\n\nrandom.strided.rayleigh.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.rayleigh.byteLength;\n\n    See Also\n    --------\n    base.random.rayleigh, random.array.rayleigh\n","random.strided.rayleigh.ndarray":"\nrandom.strided.rayleigh.ndarray( N, sigma, ss, os, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    sigma: ArrayLikeObject\n        Scale parameter.\n\n    ss: integer\n        Index increment for `sigma`.\n\n    os: integer\n        Starting index for `sigma`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.rayleigh.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]","random.strided.rayleigh.factory":"\nrandom.strided.rayleigh.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Rayleigh distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.rayleigh.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.rayleigh.PRNG":"\nrandom.strided.rayleigh.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.rayleigh.PRNG;","random.strided.rayleigh.seed":"\nrandom.strided.rayleigh.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.rayleigh.seed;","random.strided.rayleigh.seedLength":"\nrandom.strided.rayleigh.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.rayleigh.seedLength;","random.strided.rayleigh.state":"\nrandom.strided.rayleigh.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.rayleigh.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.rayleigh.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.rayleigh( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.rayleigh.stateLength":"\nrandom.strided.rayleigh.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.rayleigh.stateLength;","random.strided.rayleigh.byteLength":"\nrandom.strided.rayleigh.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.rayleigh.byteLength;\n\n    See Also\n    --------\n    base.random.rayleigh, random.array.rayleigh","random.strided.t":"\nrandom.strided.t( N, v, sv, out, so )\n    Fills a strided array with pseudorandom numbers drawn from a Student's t-\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    v: ArrayLikeObject\n        Degrees of freedom.\n\n    sv: integer\n        Index increment for `v`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.t.ndarray( N, v, sv, ov, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a Student's t-\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    v: ArrayLikeObject\n        Degrees of freedom.\n\n    sv: integer\n        Index increment for `v`.\n\n    ov: integer\n        Starting index for `v`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.t.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]\n\n\nrandom.strided.t.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Student's t-distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.t.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.t.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.t.PRNG;\n\n\nrandom.strided.t.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.t.seed;\n\n\nrandom.strided.t.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.t.seedLength;\n\n\nrandom.strided.t.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.t.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.t.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n\nrandom.strided.t.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.t.stateLength;\n\n\nrandom.strided.t.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.t.byteLength;\n\n    See Also\n    --------\n    base.random.t, random.array.t\n","random.strided.t.ndarray":"\nrandom.strided.t.ndarray( N, v, sv, ov, out, so, oo )\n    Fills a strided array with pseudorandom numbers drawn from a Student's t-\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    v: ArrayLikeObject\n        Degrees of freedom.\n\n    sv: integer\n        Index increment for `v`.\n\n    ov: integer\n        Starting index for `v`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    > var out = azeros( 5, 'generic' );\n    > random.strided.t.ndarray( out.length, [ 2.0 ], 0, 0, out, 1, 0 )\n    [...]","random.strided.t.factory":"\nrandom.strided.t.factory( [options] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Student's t-distribution.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        returned pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that a returned generator has exclusive control over\n        its internal state. Default: true.\n\n    Returns\n    -------\n    fcn: Function\n        Function for filling strided arrays.\n\n    Examples\n    --------\n    > var fcn = random.strided.t.factory();\n    > var out = azeros( 5, 'generic' );\n    > fcn( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.t.PRNG":"\nrandom.strided.t.PRNG\n    Underlying pseudorandom number generator.\n\n    Examples\n    --------\n    > var prng = random.strided.t.PRNG;","random.strided.t.seed":"\nrandom.strided.t.seed\n    Pseudorandom number generator seed.\n\n    Examples\n    --------\n    > var seed = random.strided.t.seed;","random.strided.t.seedLength":"\nrandom.strided.t.seedLength\n    Length of generator seed.\n\n    Examples\n    --------\n    > var len = random.strided.t.seedLength;","random.strided.t.state":"\nrandom.strided.t.state\n    Generator state.\n\n    Examples\n    --------\n    > var out = azeros( 3, 'generic' );\n    > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Get a copy of the current state:\n    > var state = random.strided.t.state\n    <Uint32Array>\n\n    // Advance the generator state:\n    > out = azeros( 3, 'generic' );\n    > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n    > out = azeros( 3, 'generic' );\n    > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n    [...]\n\n    // Set the state:\n    > random.strided.t.state = state;\n\n    // Regenerate previous generated values:\n    > out = azeros( 3, 'generic' );\n    > random.strided.t( out.length, [ 2.0 ], 0, out, 1 )\n    [...]","random.strided.t.stateLength":"\nrandom.strided.t.stateLength\n    Length of generator state.\n\n    Examples\n    --------\n    > var len = random.strided.t.stateLength;","random.strided.t.byteLength":"\nrandom.strided.t.byteLength\n    Size (in bytes) of generator state.\n\n    Examples\n    --------\n    > var sz = random.strided.t.byteLength;\n\n    See Also\n    --------\n    base.random.t, random.array.t","random.strided.uniform":"\nrandom.strided.uniform( N, a, sa, b, sb, out, so[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a continuous\n    uniform distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    a: ArrayLikeObject\n        Minimum support.\n\n    sa: integer\n        Index increment for `a`.\n\n    b: ArrayLikeObject\n        Maximum support.\n\n    sb: integer\n        Index increment for `b`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 0.0, 1.0, 5 );\n    > var b = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.uniform( out.length, a, 1, b, 1, out, 1 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 0.0, 1.0, 6 );\n    > b = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.uniform( 3, a, -2, b, 1, out, 1 )\n    [...]\n\n\nrandom.strided.uniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a continuous\n    uniform distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    a: ArrayLikeObject\n        Minimum support.\n\n    sa: integer\n        Index increment for `a`.\n\n    oa: integer\n        Starting index for `a`.\n\n    b: ArrayLikeObject\n        Maximum support.\n\n    sb: integer\n        Index increment for `b`.\n\n    ob: integer\n        Starting index for `b`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 0.0, 1.0, 5 );\n    > var b = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.uniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 0.0, 1.0, 6 );\n    > b = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.uniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.uniform, random.array.uniform, random.strided.discreteUniform\n","random.strided.uniform.ndarray":"\nrandom.strided.uniform.ndarray( N, a, sa, oa, b, sb, ob, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a continuous\n    uniform distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    a: ArrayLikeObject\n        Minimum support.\n\n    sa: integer\n        Index increment for `a`.\n\n    oa: integer\n        Starting index for `a`.\n\n    b: ArrayLikeObject\n        Maximum support.\n\n    sb: integer\n        Index increment for `b`.\n\n    ob: integer\n        Starting index for `b`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 0.0, 1.0, 5 );\n    > var b = linspace( 2.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.uniform.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 0.0, 1.0, 6 );\n    > b = linspace( 2.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.uniform.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.uniform, random.array.uniform, random.strided.discreteUniform","random.strided.weibull":"\nrandom.strided.weibull( N, k, sk, lambda, sl, out, so[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a Weibull\n    distribution.\n\n    The `N` and stride parameters determine which elements in the provided\n    strided arrays are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    If `N` is less than or equal to `0`, the output strided array is left\n    unchanged.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    k: ArrayLikeObject\n        Scale parameter.\n\n    sk: integer\n        Index increment for `k`.\n\n    lambda: ArrayLikeObject\n        Shape parameter.\n\n    sl: integer\n        Index increment for `lambda`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.weibull( out.length, a, 1, b, 1, out, 1 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.weibull( 3, a, -2, b, 1, out, 1 )\n    [...]\n\n\nrandom.strided.weibull.ndarray( N, k, sk, ok, lambda, sl, ol, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a Weibull\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    k: ArrayLikeObject\n        Scale parameter.\n\n    sk: integer\n        Index increment for `k`.\n\n    ok: integer\n        Starting index for `k`.\n\n    lambda: ArrayLikeObject\n        Shape parameter.\n\n    sl: integer\n        Index increment for `lambda`.\n\n    ol: integer\n        Starting index for `lambda`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.weibull.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.weibull.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.weibull, random.array.weibull\n","random.strided.weibull.ndarray":"\nrandom.strided.weibull.ndarray( N, k, sk, ok, lambda, sl, ol, out, so, oo[, options] )\n    Fills a strided array with pseudorandom numbers drawn from a Weibull\n    distribution using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    k: ArrayLikeObject\n        Scale parameter.\n\n    sk: integer\n        Index increment for `k`.\n\n    ok: integer\n        Starting index for `k`.\n\n    lambda: ArrayLikeObject\n        Shape parameter.\n\n    sl: integer\n        Index increment for `lambda`.\n\n    ol: integer\n        Starting index for `lambda`.\n\n    out: ArrayLikeObject\n        Output array.\n\n    so: integer\n        Index increment for `out`.\n\n    oo: integer\n        Starting index for `out`.\n\n    options: Object (optional)\n        Options.\n\n    options.prng: Function (optional)\n        Pseudorandom number generator (PRNG) for generating uniformly\n        distributed pseudorandom numbers on the interval `[0,1)`. If provided,\n        the `state` and `seed` options are ignored. In order to seed the\n        underlying pseudorandom number generator, one must seed the provided\n        `prng` (assuming the provided `prng` is seedable).\n\n    options.seed: integer|ArrayLikeObject<integer> (optional)\n        Pseudorandom number generator seed. The seed may be either a positive\n        unsigned 32-bit integer or, for arbitrary length seeds, an array-like\n        object containing unsigned 32-bit integers.\n\n    options.state: Uint32Array (optional)\n        Pseudorandom number generator state. If provided, the `seed` option is\n        ignored.\n\n    options.copy: boolean (optional)\n        Boolean indicating whether to copy a provided pseudorandom number\n        generator state. Setting this option to `false` allows sharing state\n        between two or more pseudorandom number generators. Setting this option\n        to `true` ensures that the underlying generator has exclusive control\n        over its internal state. Default: true.\n\n    Returns\n    -------\n    out: ArrayLikeObject\n        Output array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var a = linspace( 1.0, 5.0, 5 );\n    > var b = linspace( 1.0, 5.0, 5 );\n    > var out = azeros( 5, 'generic' );\n    > random.strided.weibull.ndarray( out.length, a, 1, 0, b, 1, 0, out, 1, 0 )\n    [...]\n\n    // Advanced indexing:\n    > a = linspace( 1.0, 5.0, 6 );\n    > b = linspace( 1.0, 5.0, 6 );\n    > out = azeros( 6, 'generic' );\n    > random.strided.weibull.ndarray( 3, a, 2, 1, b, -1, b.length-1, out, 1, 0 )\n    [...]\n\n    See Also\n    --------\n    base.random.weibull, random.array.weibull","ranks":"\nranks( arr[, options] )\n    Computes the sample ranks for the values of an array-like object.\n\n    When all elements of the `array` are different, the ranks are uniquely\n    determined. When there are equal elements (called *ties*), the `method`\n    option determines how they are handled. The default, `'average'`, replaces\n    the ranks of the ties by their mean. Other possible options are `'min'` and\n    `'max'`, which replace the ranks of the ties by their minimum and maximum,\n    respectively. `'dense'` works like `'min'`, with the difference that the\n    next highest element after a tie is assigned the next smallest integer.\n    Finally, `ordinal` gives each element in `arr` a distinct rank, according to\n    the position they appear in.\n\n    The `missing` option is used to specify how to handle missing data.\n    By default, `NaN` or `null` are treated as missing values. `'last'`specifies\n    that missing values are placed last, `'first'` that the are assigned the\n    lowest ranks and `'remove'` means that they are removed from the array\n    before the ranks are calculated.\n\n    Parameters\n    ----------\n    arr: Array<number>\n        Input values.\n\n    options: Object (optional)\n        Function options.\n\n    options.method (optional)\n        Method name determining how ties are treated (`average`, `min`, `max`,\n        `dense`, or `ordinal`). Default: `'average'`.\n\n    options.missing (optional)\n        Determines where missing values go (`first`, `last`, or `remove`).\n        Default: `'last'`.\n\n    options.encoding (optional)\n        Array of values encoding missing values. Default: `[ null, NaN ]`.\n\n    Returns\n    -------\n    out: Array\n        Array containing the computed ranks for the elements of the input array.\n\n    Examples\n    --------\n    > var arr = [ 1.1, 2.0, 3.5, 0.0, 2.4 ] ;\n    > var out = ranks( arr )\n    [ 2, 3, 5, 1, 4 ]\n\n    // Ties are averaged:\n    > arr =  [ 2, 2, 1, 4, 3 ];\n    > out = ranks( arr )\n    [ 2.5, 2.5, 1, 5, 4 ]\n\n    // Missing values are placed last:\n    > arr = [ null, 2, 2, 1, 4, 3, NaN, NaN ];\n    > out = ranks( arr )\n    [ 6, 2.5, 2.5, 1, 5, 4, 7 ,8 ]\n\n","readDir":"\nreadDir( path, clbk )\n    Asynchronously reads the contents of a directory.\n\n    Parameters\n    ----------\n    path: string|Buffer\n        Directory path.\n\n    clbk: Function\n        Callback to invoke after reading directory contents.\n\n    Examples\n    --------\n    > function onRead( error, data ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     } else {\n    ...         console.log( data );\n    ...     }\n    ... };\n    > readDir( './beep/boop', onRead );\n\n\nreadDir.sync( path )\n    Synchronously reads the contents of a directory.\n\n    Parameters\n    ----------\n    path: string|Buffer\n        Directory path.\n\n    Returns\n    -------\n    out: Error|Array|Array<string>\n        Directory contents.\n\n    Examples\n    --------\n    > var out = readDir.sync( './beep/boop' );\n\n    See Also\n    --------\n    exists, readFile\n","readDir.sync":"\nreadDir.sync( path )\n    Synchronously reads the contents of a directory.\n\n    Parameters\n    ----------\n    path: string|Buffer\n        Directory path.\n\n    Returns\n    -------\n    out: Error|Array|Array<string>\n        Directory contents.\n\n    Examples\n    --------\n    > var out = readDir.sync( './beep/boop' );\n\n    See Also\n    --------\n    exists, readFile","readFile":"\nreadFile( file[, options], clbk )\n    Asynchronously reads the entire contents of a file.\n\n    If provided an encoding, the function returns a string. Otherwise, the\n    function returns a Buffer object.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. Default: null.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    clbk: Function\n        Callback to invoke upon reading file contents.\n\n    Examples\n    --------\n    > function onRead( error, data ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     } else {\n    ...         console.log( data );\n    ...     }\n    ... };\n    > readFile( './beep/boop.js', onRead );\n\n\nreadFile.sync( file[, options] )\n    Synchronously reads the entire contents of a file.\n\n    If provided an encoding, the function returns a string. Otherwise, the\n    function returns a Buffer object.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. Default: null.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    Returns\n    -------\n    out: Error|Buffer|string\n        File contents.\n\n    Examples\n    --------\n    > var out = readFile.sync( './beep/boop.js' );\n\n    See Also\n    --------\n    exists, open, readDir, readJSON, writeFile\n","readFile.sync":"\nreadFile.sync( file[, options] )\n    Synchronously reads the entire contents of a file.\n\n    If provided an encoding, the function returns a string. Otherwise, the\n    function returns a Buffer object.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. Default: null.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    Returns\n    -------\n    out: Error|Buffer|string\n        File contents.\n\n    Examples\n    --------\n    > var out = readFile.sync( './beep/boop.js' );\n\n    See Also\n    --------\n    exists, open, readDir, readJSON, writeFile","readFileList":"\nreadFileList( filepaths[, options], clbk )\n    Asynchronously reads the entire contents of each file in a file list.\n\n    If a provided an encoding, the function returns file contents as strings.\n    Otherwise, the function returns Buffer objects.\n\n    Each file is represented by an object with the following fields:\n\n    - file: file path.\n    - data: file contents as either a Buffer or string.\n\n    Parameters\n    ----------\n    filepaths: Array<string>\n        Filepaths.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. Default: null.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    clbk: Function\n        Callback to invoke upon reading file contents.\n\n    Examples\n    --------\n    > function onRead( error, data ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     } else {\n    ...         console.log( data );\n    ...     }\n    ... };\n    > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n    > readFileList( filepaths, onRead );\n\n\nreadFileList.sync( filepaths[, options] )\n    Synchronously reads the entire contents of each file in a file list.\n\n    If a provided an encoding, the function returns file contents as strings.\n    Otherwise, the function returns Buffer objects.\n\n    Parameters\n    ----------\n    filepaths: Array<string>\n        Filepaths.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. Default: null.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    Returns\n    -------\n    out: Error|Array|Array<string>\n        File contents.\n\n    out[ i ].file: string\n        File path.\n\n    out[ i ].data: Buffer|string\n        File contents.\n\n    Examples\n    --------\n    > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n    > var out = readFileList.sync( filepaths );\n\n","readFileList.sync":"\nreadFileList.sync( filepaths[, options] )\n    Synchronously reads the entire contents of each file in a file list.\n\n    If a provided an encoding, the function returns file contents as strings.\n    Otherwise, the function returns Buffer objects.\n\n    Parameters\n    ----------\n    filepaths: Array<string>\n        Filepaths.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. Default: null.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    Returns\n    -------\n    out: Error|Array|Array<string>\n        File contents.\n\n    out[ i ].file: string\n        File path.\n\n    out[ i ].data: Buffer|string\n        File contents.\n\n    Examples\n    --------\n    > var filepaths = [ './beep/boop.txt', './foo/bar.txt' ];\n    > var out = readFileList.sync( filepaths );","readJSON":"\nreadJSON( file[, options], clbk )\n    Asynchronously reads a file as JSON.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. If the encoding option is set to `utf8` and the file has a\n        UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n        attempting to parse as JSON. Default: null.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    options.reviver: Function (optional)\n        JSON transformation function.\n\n    clbk: Function\n        Callback to invoke upon reading file contents.\n\n    Examples\n    --------\n    > function onRead( error, data ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     } else {\n    ...         console.log( data );\n    ...     }\n    ... };\n    > readJSON( './beep/boop.json', onRead );\n\n\nreadJSON.sync( file[, options] )\n    Synchronously reads a file as JSON.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. If the encoding option is set to `utf8` and the file has a\n        UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n        attempting to parse as JSON. Default: null.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    options.reviver: Function (optional)\n        JSON transformation function.\n\n    Returns\n    -------\n    out: Error|JSON\n        File contents.\n\n    Examples\n    --------\n    > var out = readJSON.sync( './beep/boop.json' );\n\n    See Also\n    --------\n    readFile\n","readJSON.sync":"\nreadJSON.sync( file[, options] )\n    Synchronously reads a file as JSON.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. If the encoding option is set to `utf8` and the file has a\n        UTF-8 byte order mark (BOM), the byte order mark is *removed* before\n        attempting to parse as JSON. Default: null.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    options.reviver: Function (optional)\n        JSON transformation function.\n\n    Returns\n    -------\n    out: Error|JSON\n        File contents.\n\n    Examples\n    --------\n    > var out = readJSON.sync( './beep/boop.json' );\n\n    See Also\n    --------\n    readFile","readWASM":"\nreadWASM( file[, options], clbk )\n    Asynchronously reads a file as WebAssembly.\n\n    The function returns file contents as a Uint8Array.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    options: Object (optional)\n        Options.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    clbk: Function\n        Callback to invoke upon reading file contents.\n\n    Examples\n    --------\n    > function onRead( error, data ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     } else {\n    ...         console.log( data );\n    ...     }\n    ... };\n    > readWASM( './beep/boop.wasm', onRead );\n\n\nreadWASM.sync( file[, options] )\n    Synchronously reads a file as WebAssembly.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    options: Object (optional)\n        Options.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    Returns\n    -------\n    out: Error|Uint8Array\n        File contents.\n\n    Examples\n    --------\n    > var out = readWASM.sync( './beep/boop.wasm' );\n\n    See Also\n    --------\n    readFile\n","readWASM.sync":"\nreadWASM.sync( file[, options] )\n    Synchronously reads a file as WebAssembly.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    options: Object (optional)\n        Options.\n\n    options.flag: string (optional)\n        Flag. Default: 'r'.\n\n    Returns\n    -------\n    out: Error|Uint8Array\n        File contents.\n\n    Examples\n    --------\n    > var out = readWASM.sync( './beep/boop.wasm' );\n\n    See Also\n    --------\n    readFile","real":"\nreal( z )\n    Returns the real component of a double-precision complex floating-point\n    number.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    re: number\n        Real component.\n\n    Examples\n    --------\n    > var z = new Complex128( 5.0, 3.0 );\n    > var re = real( z )\n    5.0\n\n    See Also\n    --------\n    imag, reim\n","realarray":"\nrealarray( [dtype] )\n    Creates a typed array.\n\n    The function supports the following data types:\n\n    - float64: double-precision floating-point numbers (IEEE 754).\n    - float32: single-precision floating-point numbers (IEEE 754).\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n\n    The default typed array data type is `float64`.\n\n    Parameters\n    ----------\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = realarray()\n    <Float64Array>\n    > arr = realarray( 'float32' )\n    <Float32Array>\n\n\nrealarray( length[, dtype] )\n    Returns a typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = realarray( 5 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n    > arr = realarray( 5, 'int32' )\n    <Int32Array>[ 0, 0, 0, 0, 0 ]\n\n\nrealarray( typedarray[, dtype] )\n    Creates a typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = realarray( [ 0.5, 0.5, 0.5 ] );\n    > var arr2 = realarray( arr1, 'float32' )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]\n\n\nrealarray( obj[, dtype] )\n    Creates a typed array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a typed array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 0.5, 0.5, 0.5 ];\n    > var arr2 = realarray( arr1, 'float32' )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]\n\n\nrealarray( buffer[, byteOffset[, length]][, dtype] )\n    Returns a typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 16 );\n    > var arr = realarray( buf, 0, 4, 'float32' )\n    <Float32Array>[ 0.0, 0.0, 0.0, 0.0 ]\n\n    See Also\n    --------\n    Float64Array, Float32Array, Int32Array, Uint32Array, Int16Array, Uint16Array, Int8Array, Uint8Array, Uint8ClampedArray\n","realarrayCtors":"\nrealarrayCtors( dtype )\n    Returns a typed array constructor.\n\n    The function returns constructors for the following data types:\n\n    - float32: single-precision floating-point numbers.\n    - float64: double-precision floating-point numbers.\n    - int16: signed 16-bit integers.\n    - int32: signed 32-bit integers.\n    - int8: signed 8-bit integers.\n    - uint16: unsigned 16-bit integers.\n    - uint32: unsigned 32-bit integers.\n    - uint8: unsigned 8-bit integers.\n    - uint8c: unsigned clamped 8-bit integers.\n\n    Parameters\n    ----------\n    dtype: string\n        Data type.\n\n    Returns\n    -------\n    out: Function|null\n        Typed array constructor.\n\n    Examples\n    --------\n    > var ctor = realarrayCtors( 'float64' )\n    <Function>\n    > ctor = realarrayCtors( 'float' )\n    null\n\n    See Also\n    --------\n    arrayCtors, complexarrayCtors\n","realarrayDataTypes":"\nrealarrayDataTypes()\n    Returns a list of typed array real-valued data types.\n\n    Returns\n    -------\n    out: Array<string>\n        List of typed array data types.\n\n    Examples\n    --------\n    > var out = realarrayDataTypes()\n    <Array>\n\n    See Also\n    --------\n    arrayDataTypes, complexarrayDataTypes\n","realf":"\nrealf( z )\n    Returns the real component of a single-precision complex floating-point\n    number.\n\n    Parameters\n    ----------\n    z: Complex64\n        Complex number.\n\n    Returns\n    -------\n    re: number\n        Real component.\n\n    Examples\n    --------\n    > var z = new Complex64( 5.0, 3.0 );\n    > var re = realf( z )\n    5.0\n\n    See Also\n    --------\n    imagf, real, reimf\n","realmax":"\nrealmax( dtype )\n    Returns the maximum finite value capable of being represented by a numeric\n    real type.\n\n    The following numeric real types are supported:\n\n    - float64: double-precision floating-point numbers.\n    - float32: single-precision floating-point numbers.\n    - float16: half-precision floating-point numbers.\n\n    Parameters\n    ----------\n    dtype: string\n        Numeric type.\n\n    Returns\n    -------\n    out: number\n        Maximum finite value.\n\n    Examples\n    --------\n    > var m = realmax( 'float16' )\n    65504.0\n    > m = realmax( 'float32' )\n    3.4028234663852886e+38\n\n    See Also\n    --------\n    realmin, typemax\n","realmin":"\nrealmin( dtype )\n    Returns the smallest positive normal value capable of being represented by a\n    numeric real type.\n\n    The following numeric real types are supported:\n\n    - float64: double-precision floating-point numbers.\n    - float32: single-precision floating-point numbers.\n    - float16: half-precision floating-point numbers.\n\n    Parameters\n    ----------\n    dtype: string\n        Numeric type.\n\n    Returns\n    -------\n    out: number\n        Smallest finite normal value.\n\n    Examples\n    --------\n    > var m = realmin( 'float16' )\n    0.00006103515625\n    > m = realmin( 'float32' )\n    1.1754943508222875e-38\n\n    See Also\n    --------\n    realmax, typemin\n","reBasename":"\nreBasename( [platform] )\n    Returns a regular expression to capture the last part of a path.\n\n    The regular expression is platform-dependent. If the current process is\n    running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n    `*.REGEXP_POSIX`.\n\n    Parameters\n    ----------\n    platform: string (optional)\n        Path platform (either `posix` or `win32`).\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reBasename()\n    <RegExp>\n    > var RE_POSIX = reBasename( 'posix' );\n    > var RE_WIN32 = reBasename( 'win32' );\n    > var str = RE.toString();\n    > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n    true\n\n\nreBasename.REGEXP\n    Regular expression to capture the last part of a POSIX path.\n\n    Examples\n    --------\n    > var RE = reBasename.REGEXP\n    <RegExp>\n\n\nreBasename.REGEXP_POSIX\n    Regular expression to capture the last part of a POSIX path.\n\n    Examples\n    --------\n    > var base = reBasename.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n    'index.js'\n\n\nreBasename.REGEXP_WIN32\n    Regular expression to capture the last part of a Windows path.\n\n    Examples\n    --------\n    > var base = reBasename.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    'index.js'\n\n    See Also\n    --------\n    reBasenamePosix, reBasenameWindows\n","reBasename.REGEXP":"\nreBasename.REGEXP\n    Regular expression to capture the last part of a POSIX path.\n\n    Examples\n    --------\n    > var RE = reBasename.REGEXP\n    <RegExp>","reBasename.REGEXP_POSIX":"\nreBasename.REGEXP_POSIX\n    Regular expression to capture the last part of a POSIX path.\n\n    Examples\n    --------\n    > var base = reBasename.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n    'index.js'","reBasename.REGEXP_WIN32":"\nreBasename.REGEXP_WIN32\n    Regular expression to capture the last part of a Windows path.\n\n    Examples\n    --------\n    > var base = reBasename.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    'index.js'\n\n    See Also\n    --------\n    reBasenamePosix, reBasenameWindows","reBasenamePosix":"\nreBasenamePosix()\n    Returns a regular expression to capture the last part of a POSIX path.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE_BASENAME_POSIX = reBasenamePosix();\n    > var base = RE_BASENAME_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n    'index.js'\n    > base = RE_BASENAME_POSIX.exec( './foo/bar/.gitignore' )[ 1 ]\n    '.gitignore'\n    > base = RE_BASENAME_POSIX.exec( 'foo/file.pdf' )[ 1 ]\n    'file.pdf'\n    > base = RE_BASENAME_POSIX.exec( '/foo/bar/file' )[ 1 ]\n    'file'\n    > base = RE_BASENAME_POSIX.exec( 'index.js' )[ 1 ]\n    'index.js'\n    > base = RE_BASENAME_POSIX.exec( '.' )[ 1 ]\n    '.'\n    > base = RE_BASENAME_POSIX.exec( './' )[ 1 ]\n    '.'\n    > base = RE_BASENAME_POSIX.exec( '' )[ 1 ]\n    ''\n\n\nreBasenamePosix.REGEXP\n    Regular expression to capture the last part of a POSIX path.\n\n    Examples\n    --------\n    > var base = reBasenamePosix.REGEXP.exec( 'foo/bar/index.js' )[ 1 ]\n    'index.js'\n\n    See Also\n    --------\n    reBasename, reBasenameWindows\n","reBasenamePosix.REGEXP":"\nreBasenamePosix.REGEXP\n    Regular expression to capture the last part of a POSIX path.\n\n    Examples\n    --------\n    > var base = reBasenamePosix.REGEXP.exec( 'foo/bar/index.js' )[ 1 ]\n    'index.js'\n\n    See Also\n    --------\n    reBasename, reBasenameWindows","reBasenameWindows":"\nreBasenameWindows()\n    Returns a regular expression to capture the last part of a Windows path.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE_BASENAME_WINDOWS = reBasenameWindows();\n    > var base = RE_BASENAME_WINDOWS.exec( '\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    'index.js'\n    > base = RE_BASENAME_WINDOWS.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n    '.gitignore'\n    > base = RE_BASENAME_WINDOWS.exec( 'foo\\\\file.pdf' )[ 1 ]\n    'file.pdf'\n    > base = RE_BASENAME_WINDOWS.exec( 'foo\\\\bar\\\\file' )[ 1 ]\n    'file'\n    > base = RE_BASENAME_WINDOWS.exec( 'index.js' )[ 1 ]\n    'index.js'\n    > base = RE_BASENAME_WINDOWS.exec( '.' )[ 1 ]\n    '.'\n    > base = RE_BASENAME_WINDOWS.exec( '' )[ 1 ]\n    ''\n\n\nreBasenameWindows.REGEXP\n    Regular expression to capture the last part of a Windows path.\n\n    Examples\n    --------\n    > var match = reBasenameWindows.REGEXP.exec( 'foo\\\\file.pdf' )[ 1 ]\n    'file.pdf'\n\n    See Also\n    --------\n    reBasename, reBasenamePosix\n","reBasenameWindows.REGEXP":"\nreBasenameWindows.REGEXP\n    Regular expression to capture the last part of a Windows path.\n\n    Examples\n    --------\n    > var match = reBasenameWindows.REGEXP.exec( 'foo\\\\file.pdf' )[ 1 ]\n    'file.pdf'\n\n    See Also\n    --------\n    reBasename, reBasenamePosix","reColorHexadecimal":"\nreColorHexadecimal( [mode] )\n    Returns a regular expression to match a hexadecimal color.\n\n    Parameters\n    ----------\n    mode: string (optional)\n        Color format (`full`, `shorthand`, or `either`).\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reColorHexadecimal();\n    > var bool = RE.test( 'ffffff' )\n    true\n    > bool = RE.test( '000' )\n    false\n    > bool = RE.test( 'beep' )\n    false\n\n\nreColorHexadecimal.REGEXP\n    Regular expression to match a full hexadecimal color.\n\n    Examples\n    --------\n    > var bool = reColorHexadecimal.REGEXP.test( 'ffffff' )\n    true\n    > bool = reColorHexadecimal.REGEXP.test( '000' )\n    false\n    > bool = reColorHexadecimal.REGEXP.test( 'beep' )\n    false\n\n\nreColorHexadecimal.REGEXP_SHORTHAND\n    Regular expression to match a shorthand hexadecimal color.\n\n    Examples\n    --------\n    > var bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'ffffff' )\n    false\n    > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( '000' )\n    true\n    > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'beep' )\n    false\n\n\nreColorHexadecimal.REGEXP_EITHER\n    Regular expression to match either a shorthand or full length hexadecimal\n    color.\n\n    Examples\n    --------\n    > var bool = reColorHexadecimal.REGEXP_EITHER.test( 'ffffff' )\n    true\n    > bool = reColorHexadecimal.REGEXP_EITHER.test( '000' )\n    true\n    > bool = reColorHexadecimal.REGEXP_EITHER.test( 'beep' )\n    false\n\n","reColorHexadecimal.REGEXP":"\nreColorHexadecimal.REGEXP\n    Regular expression to match a full hexadecimal color.\n\n    Examples\n    --------\n    > var bool = reColorHexadecimal.REGEXP.test( 'ffffff' )\n    true\n    > bool = reColorHexadecimal.REGEXP.test( '000' )\n    false\n    > bool = reColorHexadecimal.REGEXP.test( 'beep' )\n    false","reColorHexadecimal.REGEXP_SHORTHAND":"\nreColorHexadecimal.REGEXP_SHORTHAND\n    Regular expression to match a shorthand hexadecimal color.\n\n    Examples\n    --------\n    > var bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'ffffff' )\n    false\n    > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( '000' )\n    true\n    > bool = reColorHexadecimal.REGEXP_SHORTHAND.test( 'beep' )\n    false","reColorHexadecimal.REGEXP_EITHER":"\nreColorHexadecimal.REGEXP_EITHER\n    Regular expression to match either a shorthand or full length hexadecimal\n    color.\n\n    Examples\n    --------\n    > var bool = reColorHexadecimal.REGEXP_EITHER.test( 'ffffff' )\n    true\n    > bool = reColorHexadecimal.REGEXP_EITHER.test( '000' )\n    true\n    > bool = reColorHexadecimal.REGEXP_EITHER.test( 'beep' )\n    false","reDecimalNumber":"\nreDecimalNumber( [options] )\n    Returns a regular expression to match a decimal number.\n\n    A leading digit is not required.\n\n    A decimal point and at least one trailing digit is required.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.flags: string (optional)\n        Regular expression flags. Default: ''.\n\n    options.capture: boolean (optional)\n        Boolean indicating whether to create a capture group for the match.\n        Default: false.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reDecimalNumber();\n    > var bool = RE.test( '1.234' )\n    true\n    > bool = RE.test( '-1.234' )\n    true\n    > bool = RE.test( '0.0' )\n    true\n    > bool = RE.test( '.0' )\n    true\n    > bool = RE.test( '0' )\n    false\n    > bool = RE.test( 'beep' )\n    false\n\n    // Create a RegExp to capture all decimal numbers:\n    > var re = reDecimalNumber({ 'flags': 'g' });\n    > var str = '1.234 5.6, 7.8';\n    > var out = str.match( re )\n    [ '1.234', '5.6', '7.8' ]\n\n\nreDecimalNumber.REGEXP\n    Regular expression to match a decimal number.\n\n    A leading digit is not required.\n\n    A decimal point and at least one trailing digit is required.\n\n    Examples\n    --------\n    > var RE = reDecimalNumber.REGEXP;\n    > var bool = RE.test( '1.234' )\n    true\n    > bool = RE.test( '-1.234' )\n    true\n\n\nreDecimalNumber.REGEXP_CAPTURE\n    Regular expression to capture a decimal number.\n\n    A leading digit is not required.\n\n    A decimal point and at least one trailing digit is required.\n\n    Examples\n    --------\n    > var RE = reDecimalNumber.REGEXP_CAPTURE;\n    > var str = '1.02';\n    > var out = replace( str, RE, '$1 x $1' )\n    '1.02 x 1.02'\n","reDecimalNumber.REGEXP":"\nreDecimalNumber.REGEXP\n    Regular expression to match a decimal number.\n\n    A leading digit is not required.\n\n    A decimal point and at least one trailing digit is required.\n\n    Examples\n    --------\n    > var RE = reDecimalNumber.REGEXP;\n    > var bool = RE.test( '1.234' )\n    true\n    > bool = RE.test( '-1.234' )\n    true","reDecimalNumber.REGEXP_CAPTURE":"\nreDecimalNumber.REGEXP_CAPTURE\n    Regular expression to capture a decimal number.\n\n    A leading digit is not required.\n\n    A decimal point and at least one trailing digit is required.\n\n    Examples\n    --------\n    > var RE = reDecimalNumber.REGEXP_CAPTURE;\n    > var str = '1.02';\n    > var out = replace( str, RE, '$1 x $1' )\n    '1.02 x 1.02'","reDirname":"\nreDirname( [platform] )\n    Returns a regular expression to capture a path dirname.\n\n    The regular expression is platform-dependent. If the current process is\n    running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n    `*.REGEXP_POSIX`.\n\n    Parameters\n    ----------\n    platform: string (optional)\n        Path platform (either `posix` or `win32`).\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reDirname()\n    <RegExp>\n    > var RE_POSIX = reDirname( 'posix' );\n    > var dir = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n    '/foo/bar'\n    > var RE_WIN32 = reDirname( 'win32' );\n    > dir = RE_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    'C:\\foo\\bar'\n    > var str = RE.toString();\n    > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n    true\n\n\nreDirname.REGEXP\n    Regular expression to capture a path dirname.\n\n    Examples\n    --------\n    > var RE = reDirname.REGEXP\n    <RegExp>\n\n\nreDirname.REGEXP_POSIX\n    Regular expression to capture a POSIX path dirname.\n\n    Examples\n    --------\n    > var dir = reDirname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n    '/foo/bar'\n\n\nreDirname.REGEXP_WIN32\n    Regular expression to capture a Windows path dirname.\n\n    Examples\n    --------\n    > var dir = reDirname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    'C:\\foo\\bar'\n\n    See Also\n    --------\n    reDirnamePosix, reDirnameWindows, dirname\n","reDirname.REGEXP":"\nreDirname.REGEXP\n    Regular expression to capture a path dirname.\n\n    Examples\n    --------\n    > var RE = reDirname.REGEXP\n    <RegExp>","reDirname.REGEXP_POSIX":"\nreDirname.REGEXP_POSIX\n    Regular expression to capture a POSIX path dirname.\n\n    Examples\n    --------\n    > var dir = reDirname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n    '/foo/bar'","reDirname.REGEXP_WIN32":"\nreDirname.REGEXP_WIN32\n    Regular expression to capture a Windows path dirname.\n\n    Examples\n    --------\n    > var dir = reDirname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    'C:\\foo\\bar'\n\n    See Also\n    --------\n    reDirnamePosix, reDirnameWindows, dirname","reDirnamePosix":"\nreDirnamePosix()\n    Returns a regular expression to capture a POSIX path dirname.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reDirnamePosix();\n    > var dir = RE.exec( '/foo/bar/index.js' )[ 1 ]\n    '/foo/bar'\n    > dir = RE.exec( './foo/bar/.gitignore' )[ 1 ]\n    './foo/bar'\n    > dir = RE.exec( 'foo/file.pdf' )[ 1 ]\n    'foo'\n    > dir = RE.exec( '/foo/bar/file' )[ 1 ]\n    '/foo/bar'\n    > dir = RE.exec( 'index.js' )[ 1 ]\n    ''\n    > dir = RE.exec( '.' )[ 1 ]\n    '.'\n    > dir = RE.exec( './' )[ 1 ]\n    '.'\n    > dir = RE.exec( '' )[ 1 ]\n    ''\n\n\nreDirnamePosix.REGEXP\n    Regular expression to capture a POSIX path dirname.\n\n    Examples\n    --------\n    > var ext = reDirnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n    '/foo/bar'\n\n    See Also\n    --------\n    reDirname, reDirnameWindows, dirname\n","reDirnamePosix.REGEXP":"\nreDirnamePosix.REGEXP\n    Regular expression to capture a POSIX path dirname.\n\n    Examples\n    --------\n    > var ext = reDirnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n    '/foo/bar'\n\n    See Also\n    --------\n    reDirname, reDirnameWindows, dirname","reDirnameWindows":"\nreDirnameWindows()\n    Returns a regular expression to capture a Windows path dirname.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reDirnameWindows();\n    > var dir = RE.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n    'foo\\bar'\n    > dir = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n    'C:\\foo\\bar'\n    > dir = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\n    'foo'\n    > dir = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\n    '\\foo\\bar'\n    > dir = RE.exec( 'index.js' )[ 1 ]\n    ''\n    > dir = RE.exec( '' )[ 1 ]\n    ''\n\n\nreDirnameWindows.REGEXP\n    Regular expression to capture a Windows path dirname.\n\n    Examples\n    --------\n    > var dir = reDirnameWindows.REGEXP.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n    'foo\\bar'\n\n    See Also\n    --------\n    reDirname, reDirnamePosix, dirname\n","reDirnameWindows.REGEXP":"\nreDirnameWindows.REGEXP\n    Regular expression to capture a Windows path dirname.\n\n    Examples\n    --------\n    > var dir = reDirnameWindows.REGEXP.exec( 'foo\\\\bar\\\\index.js' )[ 1 ]\n    'foo\\bar'\n\n    See Also\n    --------\n    reDirname, reDirnamePosix, dirname","reduce":"\nreduce( arr, initial, reducer[, thisArg] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    When invoked, the reduction function is provided four arguments:\n\n    - accumulator: accumulated value.\n    - value: array element.\n    - index: element index.\n    - arr: input array.\n\n    If provided an empty array, the function returns the initial value.\n\n    When provided an ndarray, the function performs a reduction over the entire\n    input ndarray (i.e., higher-order ndarray dimensions are flattened to a\n    single-dimension).\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject|ndarray\n        Input array.\n\n    initial: any\n        Accumulator value used in the first invocation of the reduction\n        function.\n\n    reducer: Function\n        Function to invoke for each element in the input array.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: any\n        Accumulated result.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.add, 2 );\n    > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > var out = reduce( arr, 0.0, f )\n    21.0\n\n    // ndarray:\n    > arr = array( arr, { 'shape': [ 2, 3 ] } );\n    > out = reduce( arr, 0.0, f )\n    21.0\n\n    See Also\n    --------\n    forEach, map, reduceAsync, reduceRight\n","reduce2d":"\nreduce2d( arr, initial, reducer[, thisArg] )\n    Reduces the number of dimensions by one of a two-dimensional nested array by\n    applying a function against an accumulator and each element along the\n    innermost dimension and returning the accumulation results as a one-\n    dimensional array.\n\n    The applied function is provided the following arguments:\n\n    - accumulator: accumulated value.\n    - value: array element.\n    - indices: current array element indices.\n    - arr: input array.\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject<ArrayLikeObject>\n        Input array of arrays.\n\n    initial: ArrayLikeObject\n        Initial values. Must have a length equal to the size of the outermost\n        input array dimension.\n\n    reducer: Function\n        Function to apply.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Array\n        Accumulation results.\n\n    Examples\n    --------\n    > var f = naryFunction( base.add, 2 );\n    > var arr = [ [ 1, 2, 3 ], [ 4, 5, 6 ] ];\n    > var out = reduce2d( arr, [ 0, 0 ], f )\n    [ 6, 15 ]\n\n    See Also\n    --------\n    map2d, reduce\n","reduceAsync":"\nreduceAsync( collection, initial, [options,] reducer, done )\n    Applies a function against an accumulator and each element in a collection\n    and returns the accumulated result.\n\n    When invoked, `reducer` is provided a maximum of five arguments:\n\n    - accumulator: accumulated value.\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If\n    `reducer` accepts three arguments, `reducer` is provided:\n\n    - accumulator\n    - value\n    - next\n\n    If `reducer` accepts four arguments, `reducer` is provided:\n\n    - accumulator\n    - value\n    - index\n    - next\n\n    For every other `reducer` signature, `reducer` is provided all five\n    arguments.\n\n    The `next` callback accepts two arguments:\n\n    - error: error argument.\n    - accumulator: accumulated value.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    If provided an empty collection, the function invokes the `done` callback\n    with the `initial` value as the second argument.\n\n    The function does not skip `undefined` elements.\n\n    When processing collection elements concurrently, *beware* of race\n    conditions when updating an accumulator. This is especially true when an\n    accumulator is a primitive (e.g., a number). In general, prefer object\n    accumulators.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    initial: any\n        Accumulator value used in the first invocation of the reduction\n        function.\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: true.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    reducer: Function\n        The function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function fcn( acc, value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         acc.sum += value;\n    ...         next( null, acc );\n    ...     }\n    ... };\n    > function done( error, acc ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( acc.sum );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > var acc = { 'sum': 0 };\n    > reduceAsync( arr, acc, fcn, done )\n    3000\n    2500\n    1000\n    6500\n\n    // Limit number of concurrent invocations:\n    > function fcn( acc, value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         acc.sum += value;\n    ...         next( null, acc );\n    ...     }\n    ... };\n    > function done( error, acc ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( acc.sum );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 3000, 2500, 1000 ];\n    > var acc = { 'sum': 0 };\n    > reduceAsync( arr, acc, opts, fcn, done )\n    2500\n    3000\n    1000\n    6500\n\n    // Process concurrently:\n    > function fcn( acc, value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         acc.sum += value;\n    ...         next( null, acc );\n    ...     }\n    ... };\n    > function done( error, acc ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( acc.sum );\n    ... };\n    > var opts = { 'series': false };\n    > var arr = [ 3000, 2500, 1000 ];\n    > var acc = { 'sum': 0 };\n    > reduceAsync( arr, acc, opts, fcn, done )\n    1000\n    2500\n    3000\n    6500\n\n\nreduceAsync.factory( [options,] fcn )\n    Returns a function which applies a function against an accumulator and each\n    element in a collection and returns the accumulated result.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: true.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function fcn( acc, value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         acc.sum += value;\n    ...         next( null, acc );\n    ...     }\n    ... };\n    > var opts = { 'series': false };\n    > var f = reduceAsync.factory( opts, fcn );\n    > function done( error, acc ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( acc.sum );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > var acc = { 'sum': 0 };\n    > f( arr, acc, done )\n    1000\n    2500\n    3000\n    6500\n    > acc = { 'sum': 0 };\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, acc, done )\n    1000\n    1500\n    2000\n    4500\n\n    See Also\n    --------\n    forEachAsync, reduce, reduceRightAsync\n","reduceAsync.factory":"\nreduceAsync.factory( [options,] fcn )\n    Returns a function which applies a function against an accumulator and each\n    element in a collection and returns the accumulated result.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: true.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function fcn( acc, value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         acc.sum += value;\n    ...         next( null, acc );\n    ...     }\n    ... };\n    > var opts = { 'series': false };\n    > var f = reduceAsync.factory( opts, fcn );\n    > function done( error, acc ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( acc.sum );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > var acc = { 'sum': 0 };\n    > f( arr, acc, done )\n    1000\n    2500\n    3000\n    6500\n    > acc = { 'sum': 0 };\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, acc, done )\n    1000\n    1500\n    2000\n    4500\n\n    See Also\n    --------\n    forEachAsync, reduce, reduceRightAsync","reduceRight":"\nreduceRight( arr, initial, reducer[, thisArg] )\n    Applies a function against an accumulator and each element in an array while\n    iterating from right to left and returns the accumulated result.\n\n    When invoked, the reduction function is provided four arguments:\n\n    - accumulator: accumulated value.\n    - value: array element.\n    - index: element index.\n    - arr: input array.\n\n    If provided an empty array, the function returns the initial value.\n\n    When provided an ndarray, the function performs a reduction over the entire\n    input ndarray (i.e., higher-order ndarray dimensions are flattened to a\n    single-dimension).\n\n    Parameters\n    ----------\n    arr: ArrayLikeObject|ndarray\n        Input array.\n\n    initial: any\n        Accumulator value used in the first invocation of the reduction\n        function.\n\n    reducer: Function\n        Function to invoke for each element in the input array.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    out: any\n        Accumulated result.\n\n    Examples\n    --------\n    // array-like object:\n    > var f = naryFunction( base.add, 2 );\n    > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ];\n    > var out = reduceRight( arr, 0.0, f )\n    21.0\n\n    // ndarray:\n    > arr = array( arr, { 'shape': [ 2, 3 ] } );\n    > out = reduceRight( arr, 0.0, f )\n    21.0\n\n    See Also\n    --------\n    forEachRight, mapRight, reduce, reduceRightAsync\n","reduceRightAsync":"\nreduceRightAsync( collection, initial, [options,] reducer, done )\n    Applies a function against an accumulator and each element in a collection\n    and returns the accumulated result, iterating from right to left.\n\n    When invoked, `reducer` is provided a maximum of five arguments:\n\n    - accumulator: accumulated value.\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If\n    `reducer` accepts three arguments, `reducer` is provided:\n\n    - accumulator\n    - value\n    - next\n\n    If `reducer` accepts four arguments, `reducer` is provided:\n\n    - accumulator\n    - value\n    - index\n    - next\n\n    For every other `reducer` signature, `reducer` is provided all five\n    arguments.\n\n    The `next` callback accepts two arguments:\n\n    - error: error argument.\n    - accumulator: accumulated value.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    If provided an empty collection, the function invokes the `done` callback\n    with the `initial` value as the second argument.\n\n    The function does not skip `undefined` elements.\n\n    When processing collection elements concurrently, *beware* of race\n    conditions when updating an accumulator. This is especially true when an\n    accumulator is a primitive (e.g., a number). In general, prefer object\n    accumulators.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    initial: any\n        Accumulator value used in the first invocation of the reduction\n        function.\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: true.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    reducer: Function\n        The function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function fcn( acc, value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         acc.sum += value;\n    ...         next( null, acc );\n    ...     }\n    ... };\n    > function done( error, acc ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( acc.sum );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > var acc = { 'sum': 0 };\n    > reduceRightAsync( arr, acc, fcn, done )\n    3000\n    2500\n    1000\n    6500\n\n    // Limit number of concurrent invocations:\n    > function fcn( acc, value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         acc.sum += value;\n    ...         next( null, acc );\n    ...     }\n    ... };\n    > function done( error, acc ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( acc.sum );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 1000, 2500, 3000 ];\n    > var acc = { 'sum': 0 };\n    > reduceRightAsync( arr, acc, opts, fcn, done )\n    2500\n    3000\n    1000\n    6500\n\n    // Process concurrently:\n    > function fcn( acc, value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         acc.sum += value;\n    ...         next( null, acc );\n    ...     }\n    ... };\n    > function done( error, acc ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( acc.sum );\n    ... };\n    > var opts = { 'series': false };\n    > var arr = [ 1000, 2500, 3000 ];\n    > var acc = { 'sum': 0 };\n    > reduceRightAsync( arr, acc, opts, fcn, done )\n    1000\n    2500\n    3000\n    6500\n\n\nreduceRightAsync.factory( [options,] fcn )\n    Returns a function which applies a function against an accumulator and each\n    element in a collection and returns the accumulated result, iterating from\n    right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: true.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function fcn( acc, value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         acc.sum += value;\n    ...         next( null, acc );\n    ...     }\n    ... };\n    > var opts = { 'series': false };\n    > var f = reduceRightAsync.factory( opts, fcn );\n    > function done( error, acc ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( acc.sum );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > var acc = { 'sum': 0 };\n    > f( arr, acc, done )\n    1000\n    2500\n    3000\n    6500\n    > acc = { 'sum': 0 };\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, acc, done )\n    1000\n    1500\n    2000\n    4500\n\n    See Also\n    --------\n    forEachRightAsync, reduceAsync, reduceRight\n","reduceRightAsync.factory":"\nreduceRightAsync.factory( [options,] fcn )\n    Returns a function which applies a function against an accumulator and each\n    element in a collection and returns the accumulated result, iterating from\n    right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: true.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which invokes a function for each element in a collection.\n\n    Examples\n    --------\n    > function fcn( acc, value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         acc.sum += value;\n    ...         next( null, acc );\n    ...     }\n    ... };\n    > var opts = { 'series': false };\n    > var f = reduceRightAsync.factory( opts, fcn );\n    > function done( error, acc ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( acc.sum );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > var acc = { 'sum': 0 };\n    > f( arr, acc, done )\n    1000\n    2500\n    3000\n    6500\n    > acc = { 'sum': 0 };\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, acc, done )\n    1000\n    1500\n    2000\n    4500\n\n    See Also\n    --------\n    forEachRightAsync, reduceAsync, reduceRight","reDurationString":"\nreDurationString()\n    Returns a regular expression to match a duration string.\n\n    A duration string is a string containing a sequence of time units. A time\n    unit is a nonnegative integer followed by a unit identifier. The following\n    unit identifiers are supported:\n\n    - d: days.\n    - h: hours.\n    - m: minutes.\n    - s: seconds.\n    - ms: milliseconds.\n\n    For example, the string `1m3s10ms` is a duration string containing three\n    time units: `1m` (1 minute), `3s` (3 seconds), and `10ms` (10 milliseconds).\n    The string `60m` is a duration string containing a single time unit: `60m`\n    (60 minutes). Time units must be supplied in descending order of magnitude\n    (i.e., days, hours, minutes, seconds, milliseconds).\n\n    Duration strings are case insensitive. For example, the string `1M3S10MS` is\n    equivalent to `1m3s10ms`.\n\n    The regular expression captures the following groups:\n\n    1. The days component.\n    2. The hours component.\n    3. The minutes component.\n    4. The seconds component.\n    5. The milliseconds component.\n\n    Returns\n    -------\n    re: RegExp: Regular expression\n        Regular expression to match a duration string.\n\n    Examples\n    --------\n    > var RE = reDurationString();\n    > var parts = RE.exec( '3d2ms' )\n    [...]\n    > parts = RE.exec( '4h3m20s' )\n    [...]\n\n\nreDurationString.REGEXP\n    Regular expression to match a duration string.\n\n    Examples\n    --------\n    > var bool = reDurationString.REGEXP.test( '3d2ms' )\n    true\n    > bool = reDurationString.REGEXP.test( 'foo' )\n    false\n","reDurationString.REGEXP":"\nreDurationString.REGEXP\n    Regular expression to match a duration string.\n\n    Examples\n    --------\n    > var bool = reDurationString.REGEXP.test( '3d2ms' )\n    true\n    > bool = reDurationString.REGEXP.test( 'foo' )\n    false","reEOL":"\nreEOL( [options] )\n    Regular expression to match a newline character sequence: /\\r?\\n/.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.flags: string (optional)\n        Regular expression flags. Default: ''.\n\n    options.capture: boolean (optional)\n        Boolean indicating whether to create a capture group for the match.\n        Default: false.\n\n    Returns\n    -------\n    regexp: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE_EOL = reEOL();\n    > var bool = RE_EOL.test( '\\n' )\n    true\n    > bool = RE_EOL.test( '\\r\\n' )\n    true\n    > bool = RE_EOL.test( '\\\\r\\\\n' )\n    false\n\nreEOL.REGEXP\n    Regular expression to match a newline character sequence: /\\r?\\n/.\n\n    Examples\n    --------\n    > var bool = reEOL.REGEXP.test( 'abc' )\n    false\n\nreEOL.REGEXP_CAPTURE\n    Regular expression to capture a newline character sequence: /\\r?\\n/.\n\n    Examples\n    --------\n    > var parts = reEOL.REGEXP_CAPTURE.exec( '\\n' )\n    [ '\\n', '\\n' ]\n\n","reEOL.REGEXP":"\nreEOL.REGEXP\n    Regular expression to match a newline character sequence: /\\r?\\n/.\n\n    Examples\n    --------\n    > var bool = reEOL.REGEXP.test( 'abc' )\n    false","reEOL.REGEXP_CAPTURE":"\nreEOL.REGEXP_CAPTURE\n    Regular expression to capture a newline character sequence: /\\r?\\n/.\n\n    Examples\n    --------\n    > var parts = reEOL.REGEXP_CAPTURE.exec( '\\n' )\n    [ '\\n', '\\n' ]","reExtendedLengthPath":"\nreExtendedLengthPath()\n    Returns a regular expression to test if a string is an extended-length path.\n\n    Extended-length paths are Windows paths which begin with `\\\\?\\`.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reExtendedLengthPath();\n    > var path = '\\\\\\\\?\\\\C:\\\\foo\\\\bar';\n    > var bool = RE.test( path )\n    true\n    > path = '\\\\\\\\?\\\\UNC\\\\server\\\\share';\n    > bool = RE.test( path )\n    true\n    > path = 'C:\\\\foo\\\\bar';\n    > bool = RE.test( path )\n    false\n    > path = '/c/foo/bar';\n    > bool = RE.test( path )\n    false\n    > path = '/foo/bar';\n    > bool = RE.test( path )\n    false\n\n\nreExtendedLengthPath.REGEXP\n    Regular expression to test if a string is an extended-length path.\n\n    Examples\n    --------\n    > var bool = reExtendedLengthPath.REGEXP.test( 'C:\\\\foo\\\\bar' )\n    false\n\n","reExtendedLengthPath.REGEXP":"\nreExtendedLengthPath.REGEXP\n    Regular expression to test if a string is an extended-length path.\n\n    Examples\n    --------\n    > var bool = reExtendedLengthPath.REGEXP.test( 'C:\\\\foo\\\\bar' )\n    false","reExtname":"\nreExtname( [platform] )\n    Returns a regular expression to capture a filename extension.\n\n    The regular expression is platform-dependent. If the current process is\n    running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n    `*.REGEXP_POSIX`.\n\n    Parameters\n    ----------\n    platform: string (optional)\n        Path platform (either `posix` or `win32`).\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reExtname()\n    <RegExp>\n    > var RE_POSIX = reExtname( 'posix' );\n    > var ext = RE_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n    '.js'\n    > var RE_WIN32 = reExtname( 'win32' );\n    > ext = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    '.js'\n    > var str = RE.toString();\n    > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n    true\n\n\nreExtname.REGEXP\n    Regular expression to capture a filename extension.\n\n    Examples\n    --------\n    > var RE = reExtname.REGEXP\n    <RegExp>\n\n\nreExtname.REGEXP_POSIX\n    Regular expression to capture a POSIX filename extension.\n\n    Examples\n    --------\n    > var ext = reExtname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n    '.js'\n\n\nreExtname.REGEXP_WIN32\n    Regular expression to capture a Windows filename extension.\n\n    Examples\n    --------\n    > var ext = reExtname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    '.js'\n\n    See Also\n    --------\n    reExtnamePosix, reExtnameWindows, extname\n","reExtname.REGEXP":"\nreExtname.REGEXP\n    Regular expression to capture a filename extension.\n\n    Examples\n    --------\n    > var RE = reExtname.REGEXP\n    <RegExp>","reExtname.REGEXP_POSIX":"\nreExtname.REGEXP_POSIX\n    Regular expression to capture a POSIX filename extension.\n\n    Examples\n    --------\n    > var ext = reExtname.REGEXP_POSIX.exec( '/foo/bar/index.js' )[ 1 ]\n    '.js'","reExtname.REGEXP_WIN32":"\nreExtname.REGEXP_WIN32\n    Regular expression to capture a Windows filename extension.\n\n    Examples\n    --------\n    > var ext = reExtname.REGEXP_WIN32.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    '.js'\n\n    See Also\n    --------\n    reExtnamePosix, reExtnameWindows, extname","reExtnamePosix":"\nreExtnamePosix\n    Returns a regular expression to capture a POSIX filename extension.\n\n    When executed against dotfile filenames (e.g., `.gitignore`), the regular\n    expression does not capture the basename as a filename extension.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reExtnamePosix();\n    > var ext = RE.exec( '/foo/bar/index.js' )[ 1 ]\n    '.js'\n    > ext = RE.exec( './foo/bar/.gitignore' )[ 1 ]\n    ''\n    > ext = RE.exec( 'foo/file.pdf' )[ 1 ]\n    '.pdf'\n    > ext = RE.exec( '/foo/bar/file' )[ 1 ]\n    ''\n    > ext = RE.exec( 'index.js' )[ 1 ]\n    '.js'\n    > ext = RE.exec( '.' )[ 1 ]\n    ''\n    > ext = RE.exec( './' )[ 1 ]\n    ''\n    > ext = RE.exec( '' )[ 1 ]\n    ''\n\n\nreExtnamePosix.REGEXP\n    Regular expression to capture a POSIX filename extension.\n\n    Examples\n    --------\n    > var ext = reExtnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n    '.js'\n\n    See Also\n    --------\n    reExtname, reExtnameWindows, extname\n","reExtnamePosix.REGEXP":"\nreExtnamePosix.REGEXP\n    Regular expression to capture a POSIX filename extension.\n\n    Examples\n    --------\n    > var ext = reExtnamePosix.REGEXP.exec( '/foo/bar/index.js' )[ 1 ]\n    '.js'\n\n    See Also\n    --------\n    reExtname, reExtnameWindows, extname","reExtnameWindows":"\nreExtnameWindows\n    Returns a regular expression to capture a Windows filename extension.\n\n    When executed against dotfile filenames (e.g., `.gitignore`), the regular\n    expression does not capture the basename as a filename extension.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reExtnameWindows();\n    > var ext = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    '.js'\n    > ext = RE.exec( 'C:\\\\foo\\\\bar\\\\.gitignore' )[ 1 ]\n    ''\n    > ext = RE.exec( 'foo\\\\file.pdf' )[ 1 ]\n    '.pdf'\n    > ext = RE.exec( '\\\\foo\\\\bar\\\\file' )[ 1 ]\n    ''\n    > ext = RE.exec( 'beep\\\\boop.' )[ 1 ]\n    '.'\n    > ext = RE.exec( 'index.js' )[ 1 ]\n    '.js'\n    > ext = RE.exec( '' )[ 1 ]\n    ''\n\n\nreExtnameWindows.REGEXP\n    Regular expression to capture a Windows filename extension.\n\n    Examples\n    --------\n    > var ext = reExtnameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    '.js'\n\n    See Also\n    --------\n    reExtname, reExtnamePosix, extname\n","reExtnameWindows.REGEXP":"\nreExtnameWindows.REGEXP\n    Regular expression to capture a Windows filename extension.\n\n    Examples\n    --------\n    > var ext = reExtnameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' )[ 1 ]\n    '.js'\n\n    See Also\n    --------\n    reExtname, reExtnamePosix, extname","reFilename":"\nreFilename( [platform] )\n    Regular expression to split a filename.\n\n    The regular expression is platform-dependent. If the current process is\n    running on Windows, the regular expression is `*.REGEXP_WIN32`; otherwise,\n    `*.REGEXP_POSIX`.\n\n    Parameters\n    ----------\n    platform: string (optional)\n        Path platform (either `posix` or `win32`).\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reFilename()\n    <RegExp>\n    > var RE_POSIX = reFilename( 'posix' );\n    > var parts = RE_POSIX.exec( '/foo/bar/index.js' ).slice()\n    <Array>\n    > var RE_WIN32 = reFilename( 'win32' );\n    > parts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n    <Array>\n    > var str = RE.toString();\n    > var bool = ( str === RE_POSIX.toString() || str === RE_WIN32.toString() )\n    true\n\n\nreFilename.REGEXP\n    Regular expression to split a filename.\n\n    Examples\n    --------\n    > var RE = reFilename.REGEXP\n    <RegExp>\n\n\nreFilename.REGEXP_POSIX\n    Regular expression to split a POSIX filename.\n\n    When executed, the regular expression splits a POSIX filename into the\n    following parts:\n\n    - input value\n    - root\n    - dirname\n    - basename\n    - extname\n\n    Examples\n    --------\n    > var f = '/foo/bar/index.js';\n    > var parts = reFilename.REGEXP_POSIX.exec( f ).slice()\n    [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n\n\nreFilename.REGEXP_WIN32\n    Regular expression to split a Windows filename.\n\n    When executed, the regular expression splits a Windows filename into the\n    following parts:\n\n    - input value\n    - device\n    - slash\n    - dirname\n    - basename\n    - extname\n\n    Examples\n    --------\n    > var f = 'C:\\\\foo\\\\bar\\\\index.js';\n    > var parts = reFilename.REGEXP_WIN32.exec( f ).slice()\n    [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n    See Also\n    --------\n    reFilenamePosix, reFilenameWindows\n","reFilename.REGEXP":"\nreFilename.REGEXP\n    Regular expression to split a filename.\n\n    Examples\n    --------\n    > var RE = reFilename.REGEXP\n    <RegExp>","reFilename.REGEXP_POSIX":"\nreFilename.REGEXP_POSIX\n    Regular expression to split a POSIX filename.\n\n    When executed, the regular expression splits a POSIX filename into the\n    following parts:\n\n    - input value\n    - root\n    - dirname\n    - basename\n    - extname\n\n    Examples\n    --------\n    > var f = '/foo/bar/index.js';\n    > var parts = reFilename.REGEXP_POSIX.exec( f ).slice()\n    [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]","reFilename.REGEXP_WIN32":"\nreFilename.REGEXP_WIN32\n    Regular expression to split a Windows filename.\n\n    When executed, the regular expression splits a Windows filename into the\n    following parts:\n\n    - input value\n    - device\n    - slash\n    - dirname\n    - basename\n    - extname\n\n    Examples\n    --------\n    > var f = 'C:\\\\foo\\\\bar\\\\index.js';\n    > var parts = reFilename.REGEXP_WIN32.exec( f ).slice()\n    [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n    See Also\n    --------\n    reFilenamePosix, reFilenameWindows","reFilenamePosix":"\nreFilenamePosix()\n    Returns a regular expression to split a POSIX filename.\n\n    When executed, the regular expression splits a POSIX filename into the\n    following parts:\n\n    - input value\n    - root\n    - dirname\n    - basename\n    - extname\n\n    When executed against dotfile filenames (e.g., `.gitignore`), the regular\n    expression does not capture the basename as a filename extension.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reFilenamePosix();\n    > var parts = RE.exec( '/foo/bar/index.js' ).slice()\n    [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n    > parts = RE.exec( './foo/bar/.gitignore' ).slice()\n    [ './foo/bar/.gitignore', '', './foo/bar/', '.gitignore', '' ]\n    > parts = RE.exec( 'foo/file.pdf' ).slice()\n    [ 'foo/file.pdf', '', 'foo/', 'file.pdf', '.pdf' ]\n    > parts = RE.exec( '/foo/bar/file' ).slice()\n    [ '/foo/bar/file', '/', 'foo/bar/', 'file', '' ]\n    > parts = RE.exec( 'index.js' ).slice()\n    [ 'index.js', '', '', 'index.js', '.js' ]\n    > parts = RE.exec( '.' ).slice()\n    [ '.', '', '', '.', '' ]\n    > parts = RE.exec( './' ).slice()\n    [ './', '', ..., '.', '' ]\n    > parts = RE.exec( '' ).slice()\n    [ '', '', '', '', '' ]\n\n\nreFilenamePosix.REGEXP\n    Regular expression to split a POSIX filename.\n\n    Examples\n    --------\n    > var parts = reFilenamePosix.REGEXP.exec( '/foo/bar/index.js' ).slice()\n    [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n\n    See Also\n    --------\n    reFilename, reFilenameWindows\n","reFilenamePosix.REGEXP":"\nreFilenamePosix.REGEXP\n    Regular expression to split a POSIX filename.\n\n    Examples\n    --------\n    > var parts = reFilenamePosix.REGEXP.exec( '/foo/bar/index.js' ).slice()\n    [ '/foo/bar/index.js', '/', 'foo/bar/', 'index.js', '.js' ]\n\n    See Also\n    --------\n    reFilename, reFilenameWindows","reFilenameWindows":"\nreFilenameWindows()\n    Returns a regular expression to split a Windows filename.\n\n    When executed, the regular expression splits a Windows filename into the\n    following parts:\n\n    - input value\n    - device\n    - slash\n    - dirname\n    - basename\n    - extname\n\n    When executed against dotfile filenames (e.g., `.gitignore`), the regular\n    expression does not capture the basename as a filename extension.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reFilenameWindows();\n    > var parts = RE.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n    [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n    > parts = RE.exec( '\\\\foo\\\\bar\\\\.gitignore' ).slice()\n    [ '\\\\foo\\\\bar\\\\.gitignore', '', '\\\\', 'foo\\\\bar\\\\', '.gitignore', '' ]\n    > parts = RE.exec( 'foo\\\\file.pdf' ).slice()\n    [ 'foo\\\\file.pdf', '', '', 'foo\\\\', 'file.pdf', '.pdf' ]\n    > parts = RE.exec( '\\\\foo\\\\bar\\\\file' ).slice()\n    [ '\\\\foo\\\\bar\\\\file', '', '\\\\', 'foo\\\\bar\\\\', 'file', '' ]\n    > parts = RE.exec( 'index.js' ).slice()\n    [ 'index.js', '', '', '', 'index.js', '.js' ]\n    > parts = RE.exec( '.' ).slice()\n    [ '.', '', '', '', '.', '' ]\n    > parts = RE.exec( './' ).slice()\n    [ './', '', ..., '.', '' ]\n    > parts = RE.exec( '' ).slice()\n    [ '', '', '', '', '', '' ]\n\n\nreFilenameWindows.REGEXP\n    Regular expression to split a Windows filename.\n\n    Examples\n    --------\n    > var parts = reFilenameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n    [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n    See Also\n    --------\n    reFilename, reFilenamePosix","reFilenameWindows.REGEXP":"\nreFilenameWindows.REGEXP\n    Regular expression to split a Windows filename.\n\n    Examples\n    --------\n    > var parts = reFilenameWindows.REGEXP.exec( 'C:\\\\foo\\\\bar\\\\index.js' ).slice()\n    [ 'C:\\\\foo\\\\bar\\\\index.js', 'C:', '\\\\', 'foo\\\\bar\\\\', 'index.js', '.js' ]\n\n    See Also\n    --------\n    reFilename, reFilenamePosix","reFromString":"\nreFromString( str )\n    Parses a regular expression string and returns a new regular expression.\n\n    Provided strings should be properly escaped.\n\n    If unable to parse a string as a regular expression, the function returns\n    `null`.\n\n    Parameters\n    ----------\n    str: string\n        Regular expression string.\n\n    Returns\n    -------\n    out: RegExp|null\n        Regular expression or null.\n\n    Examples\n    --------\n    > var re = reFromString( '/beep/' )\n    /beep/\n    > re = reFromString( '/beep' )\n    null\n\n","reFunctionName":"\nreFunctionName()\n    Return a regular expression to capture a function name.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE_FUNCTION_NAME = reFunctionName();\n    > function beep() { return 'boop'; };\n    > var name = RE_FUNCTION_NAME.exec( beep.toString() )[ 1 ]\n    'beep'\n    > name = RE_FUNCTION_NAME.exec( function () {} )[ 1 ]\n    ''\n\n\nreFunctionName.REGEXP\n    Regular expression to capture a function name.\n\n    Examples\n    --------\n    > var str = reFunctionName.REGEXP.exec( Math.sqrt.toString() )[ 1 ]\n    'sqrt'\n\n    See Also\n    --------\n    functionName\n","reFunctionName.REGEXP":"\nreFunctionName.REGEXP\n    Regular expression to capture a function name.\n\n    Examples\n    --------\n    > var str = reFunctionName.REGEXP.exec( Math.sqrt.toString() )[ 1 ]\n    'sqrt'\n\n    See Also\n    --------\n    functionName","regexp2json":"\nregexp2json( re )\n    Returns a JSON representation of a regular expression.\n\n    Parameters\n    ----------\n    re: RegExp\n        Regular expression to serialize.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n        \n    out.type: string\n        Value type. The assigned value is always 'RegExp'.\n        \n    out.pattern: string\n        Regular expression pattern.\n        \n    out.flags: string\n        Regular expression flags.\n\n    Examples\n    --------\n    > var json = regexp2json( /ab+c/ )\n    {...}\n\n    See Also\n    --------\n    reviveRegExp    \n","reim":"\nreim( z )\n    Returns the real and imaginary components of a double-precision complex\n    floating-point number.\n\n    Parameters\n    ----------\n    z: Complex128\n        Complex number.\n\n    Returns\n    -------\n    out: Float64Array\n        Array containing the real and imaginary components, respectively.\n\n    Examples\n    --------\n    > var z = new Complex128( 5.0, 3.0 );\n    > var out = reim( z )\n    <Float64Array>[ 5.0, 3.0 ]\n\n    See Also\n    --------\n    imag, real\n","reimf":"\nreimf( z )\n    Returns the real and imaginary components of a single-precision complex\n    floating-point number.\n\n    Parameters\n    ----------\n    z: Complex64\n        Complex number.\n\n    Returns\n    -------\n    out: Float32Array\n        Array containing the real and imaginary components, respectively.\n\n    Examples\n    --------\n    > var z = new Complex64( 5.0, 3.0 );\n    > var out = reimf( z )\n    <Float32Array>[ 5.0, 3.0 ]\n\n    See Also\n    --------\n    imagf, realf, reim\n","rejectArguments":"\nrejectArguments( fcn, predicate[, thisArg] )\n    Returns a function that applies arguments to a provided function according\n    to a predicate function.\n\n    Only those arguments in which the predicate function returns a falsy value\n    are applied to a provided function.\n\n    The predicate function is provided the following arguments:\n\n    - value: argument value.\n    - index: argument index.\n\n    Parameters\n    ----------\n    fcn: Function\n        Input function.\n\n    predicate: Function\n        Predicate function.\n\n    thisArg: any (optional)\n        Input function context.\n\n    Returns\n    -------\n    out: Function\n        Function wrapper.\n\n    Examples\n    --------\n    > function foo( a, b ) { return [ a, b ]; };\n    > function predicate( v ) { return ( v === 2 ); };\n    > var bar = rejectArguments( foo, predicate );\n    > var out = bar( 1, 2, 3 )\n    [ 1, 3 ]\n\n    See Also\n    --------\n    filterArguments, maskArguments\n","removeFirst":"\nremoveFirst( str[, n][, options] )\n    Removes the first character(s) of a `string`.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer (optional)\n        Number of characters to remove. Default: 1.\n\n    options: Object (optional)\n        Options.\n\n    options.mode: string (optional)\n        Type of characters to return. The following modes are supported:\n\n        - grapheme: grapheme clusters. Appropriate for strings containing visual\n          characters which can span multiple Unicode code points (e.g., emoji).\n        - code_point: Unicode code points. Appropriate for strings containing\n          visual characters which are comprised of more than one Unicode code\n          unit (e.g., ideographic symbols and punctuation and mathematical\n          alphanumerics).\n        - code_unit': UTF-16 code units. Appropriate for strings containing\n          visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n          common characters, such as those from the Latin, Greek, and Cyrillic\n          alphabets).\n\n        Default: 'grapheme'.\n\n    Returns\n    -------\n    out: string\n        Updated string.\n\n    Examples\n    --------\n    > var out = removeFirst( 'beep' )\n    'eep'\n    > out = removeFirst( 'Boop' )\n    'oop'\n    > out = removeFirst( 'foo bar', 4 )\n    'bar'\n\n    See Also\n    --------\n    removeLast\n","removeLast":"\nremoveLast( str[, n][, options] )\n    Removes the last character(s) of a `string`.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer (optional)\n        Number of characters to remove. Default: 1.\n\n    options: Object (optional)\n        Options.\n\n    options.mode: string (optional)\n        Type of characters to remove. The following modes are supported:\n\n        - grapheme: grapheme clusters. Appropriate for strings containing visual\n          characters which can span multiple Unicode code points (e.g., emoji).\n        - code_point: Unicode code points. Appropriate for strings containing\n          visual characters which are comprised of more than one Unicode code\n          unit (e.g., ideographic symbols and punctuation and mathematical\n          alphanumerics).\n        - code_unit': UTF-16 code units. Appropriate for strings containing\n          visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n          common characters, such as those from the Latin, Greek, and Cyrillic\n          alphabets).\n\n        Default: 'grapheme'.\n\n    Returns\n    -------\n    out: string\n        Updated string.\n\n    Examples\n    --------\n    > var out = removeLast( 'beep' )\n    'bee'\n    > out = removeLast( 'Boop' )\n    'Boo'\n    > out = removeLast( 'foo bar', 4 )\n    'foo'\n\n    See Also\n    --------\n    removeFirst\n","removePunctuation":"\nremovePunctuation( str )\n    Removes punctuation characters from a `string`.\n\n    The function removes the following characters:\n\n    - Apostrophe: `\n    - Braces : { }\n    - Brackets: [ ]\n    - Colon: :\n    - Comma: ,\n    - Exclamation Mark: !\n    - Fraction Slash: /\n    - Guillemets: < >\n    - Parentheses: ( )\n    - Period: .\n    - Semicolon: ;\n    - Tilde: ~\n    - Vertical Bar: |\n    - Question Mark: ?\n    - Quotation Marks: ' \"\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        String with punctuation characters removed.\n\n    Examples\n    --------\n    > var str = 'Sun Tzu said: \"A leader leads by example not by force.\"';\n    > var out = removePunctuation( str )\n    'Sun Tzu said A leader leads by example not by force'\n\n    > str = 'This function removes these characters: `{}[]:,!/<>().;~|?\\'\"';\n    > out = removePunctuation( str )\n    'This function removes these characters '\n\n","removeUTF8BOM":"\nremoveUTF8BOM( str )\n    Removes a UTF-8 byte order mark (BOM) from the beginning of a `string`.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        String with BOM removed.\n\n    Examples\n    --------\n    > var out = removeUTF8BOM( '\\ufeffbeep' )\n    'beep'\n\n","removeWords":"\nremoveWords( str, words[, ignoreCase] )\n    Removes all occurrences of the given words from a `string`.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    words: Array<string>\n        Array of words to be removed.\n\n    ignoreCase: boolean (optional)\n        Boolean indicating whether to perform a case-insensitive operation.\n        Default: `false`.\n\n    Returns\n    -------\n    out: string\n        String with words removed.\n\n    Examples\n    --------\n    > var out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ] )\n    'beep  Foo bar'\n\n    // Case-insensitive:\n    > out = removeWords( 'beep boop Foo bar', [ 'boop', 'foo' ], true )\n    'beep   bar'\n\n","rename":"\nrename( oldPath, newPath, clbk )\n    Asynchronously renames a file.\n\n    The old path can specify a directory. In this case, the new path must either\n    not exist, or it must specify an empty directory.\n\n    The old pathname should not name an ancestor directory of the new pathname.\n\n    If the old path points to the pathname of a file that is not a directory,\n    the new path should not point to the pathname of a directory.\n\n    Write access permission is required for both the directory containing the\n    old path and the directory containing the new path.\n\n    If the link named by the new path exists, the new path is removed and the\n    old path is renamed to the new path. The link named by the new path will\n    remain visible to other threads throughout the renaming operation and refer\n    to either the file referred to by the new path or to the file referred to by\n    the old path before the operation began.\n\n    If the old path and the new path resolve to either the same existing\n    directory entry or to different directory entries for the same existing\n    file, no action is taken, and no error is returned.\n\n    If the old path points to a pathname of a symbolic link, the symbolic link\n    is renamed. If the new path points to a pathname of a symbolic link, the\n    symbolic link is removed.\n\n    If a link named by the new path exists and the file's link count becomes 0\n    when it is removed and no process has the file open, the space occupied by\n    the file is freed and the file is no longer accessible. If one or more\n    processes have the file open when the last link is removed, the link is\n    removed before the function returns, but the removal of file contents is\n    postponed until all references to the file are closed.\n\n    Parameters\n    ----------\n    oldPath: string|Buffer\n        Old path.\n\n    newPath: string|Buffer\n        New path.\n\n    clbk: Function\n        Callback to invoke upon renaming a file.\n\n    Examples\n    --------\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     }\n    ... };\n    > rename( './beep/boop.txt', './beep/foo.txt', done );\n\n\nrename.sync( oldPath, newPath )\n    Synchronously renames a file.\n\n    Parameters\n    ----------\n    oldPath: string|Buffer\n        Old path.\n\n    newPath: string|Buffer\n        New path.\n\n    Returns\n    -------\n    err: Error|null\n        Error object or null.\n\n    Examples\n    --------\n    > var err = rename.sync( './beep/boop.txt', './beep/foo.txt' );\n\n    See Also\n    --------\n    exists, readFile, writeFile, unlink\n","rename.sync":"\nrename.sync( oldPath, newPath )\n    Synchronously renames a file.\n\n    Parameters\n    ----------\n    oldPath: string|Buffer\n        Old path.\n\n    newPath: string|Buffer\n        New path.\n\n    Returns\n    -------\n    err: Error|null\n        Error object or null.\n\n    Examples\n    --------\n    > var err = rename.sync( './beep/boop.txt', './beep/foo.txt' );\n\n    See Also\n    --------\n    exists, readFile, writeFile, unlink","reNativeFunction":"\nreNativeFunction()\n    Returns a regular expression to match a native function.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reNativeFunction();\n    > var bool = RE.test( Date.toString() )\n    true\n    > bool = RE.test( (function noop() {}).toString() )\n    false\n\n\nreNativeFunction.REGEXP\n    Regular expression to match a native function.\n\n    Examples\n    --------\n    > var bool = reNativeFunction.REGEXP.test( Date.toString() )\n    true\n    > bool = reNativeFunction.REGEXP.test( (function noop() {}).toString() )\n    false\n\n    See Also\n    --------\n    reFunctionName, functionName\n","reNativeFunction.REGEXP":"\nreNativeFunction.REGEXP\n    Regular expression to match a native function.\n\n    Examples\n    --------\n    > var bool = reNativeFunction.REGEXP.test( Date.toString() )\n    true\n    > bool = reNativeFunction.REGEXP.test( (function noop() {}).toString() )\n    false\n\n    See Also\n    --------\n    reFunctionName, functionName","reorderArguments":"\nreorderArguments( fcn, indices[, thisArg] )\n    Returns a function that invokes a provided function with reordered\n    arguments.\n\n    Parameters\n    ----------\n    fcn: Function\n        Input function.\n\n    indices: Array<integer>\n        Argument indices.\n\n    thisArg: any (optional)\n        Function context.\n\n    Returns\n    -------\n    out: Function\n        Function with reordered arguments.\n\n    Examples\n    --------\n    > function foo( a, b, c ) { return [ a, b, c ]; };\n    > var bar = reorderArguments( foo, [ 2, 0, 1 ] );\n    > var out = bar( 1, 2, 3 )\n    [ 3, 1, 2 ]\n\n    See Also\n    --------\n    maskArguments, reverseArguments\n","repeat":"\nrepeat( str, n )\n    Repeats a string `n` times and returns the concatenated result.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of repetitions.\n\n    Returns\n    -------\n    out: string\n        Repeated string.\n\n    Examples\n    --------\n    > var out = repeat( 'a', 5 )\n    'aaaaa'\n    > out = repeat( '', 100 )\n    ''\n    > out = repeat( 'beep', 0 )\n    ''\n\n    See Also\n    --------\n    pad\n","replace":"\nreplace( str, search, newval )\n    Replaces search occurrences with a replacement string.\n\n    When provided a string as the search value, the function replaces *all*\n    occurrences. To remove only the first match, use a regular expression.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string|RegExp\n        Search expression.\n\n    newval: string|Function\n        Replacement value or function.\n\n    Returns\n    -------\n    out: string\n        String containing replacement(s).\n\n    Examples\n    --------\n    // Standard usage:\n    > var out = replace( 'beep', 'e', 'o' )\n    'boop'\n\n    // Replacer function:\n    > function replacer( match, p1 ) { return '/'+p1+'/'; };\n    > var str = 'Oranges and lemons';\n    > out = replace( str, /([^\\s]+)/gi, replacer )\n    '/Oranges/ /and/ /lemons/'\n\n    // Replace only first match:\n    > out = replace( 'beep', /e/, 'o' )\n    'boep'\n\n","replaceBefore":"\nreplaceBefore( str, search, replacement )\n    Replaces the substring before the first occurrence of a specified search\n    string. \n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search string.\n    \n    replacement: string\n        Replacement string.\n\n    Returns\n    -------\n    out: string\n        Output string.\n\n    Examples\n    --------\n    > var str = 'beep boop';\n    > var out = replaceBefore( str, ' ', 'foo' )\n    'foo boop'\n    > out = replaceBefore( str, 'o', 'foo' )\n    'foooop'\n\n","reRegExp":"\nreRegExp()\n    Returns a regular expression to parse a regular expression string.\n\n    Regular expression strings should be escaped.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reRegExp();\n    > var bool = RE.test( '/^beep$/' )\n    true\n    > bool = RE.test( '/boop' )\n    false\n\n    // Escape regular expression strings:\n    > bool = RE.test( '/^\\/([^\\/]+)\\/(.*)$/' )\n    false\n    > bool = RE.test( '/^\\\\/([^\\\\/]+)\\\\/(.*)$/' )\n    true\n\n\nreRegExp.REGEXP\n    Regular expression to parse a regular expression string.\n\n    Examples\n    --------\n    > var bool = reRegExp.REGEXP.test( '/^beep$/' )\n    true\n    > bool = reRegExp.REGEXP.test( '/boop' )\n    false\n\n    See Also\n    --------\n    reFromString\n","reRegExp.REGEXP":"\nreRegExp.REGEXP\n    Regular expression to parse a regular expression string.\n\n    Examples\n    --------\n    > var bool = reRegExp.REGEXP.test( '/^beep$/' )\n    true\n    > bool = reRegExp.REGEXP.test( '/boop' )\n    false\n\n    See Also\n    --------\n    reFromString","rescape":"\nrescape( str )\n    Escapes a regular expression string.\n\n    Parameters\n    ----------\n    str: string\n        Regular expression string.\n\n    Returns\n    -------\n    out: string\n        Escaped string.\n\n    Examples\n    --------\n    > var str = rescape( '[A-Z]*' )\n    '\\\\[A\\\\-Z\\\\]\\\\*'\n\n","reSemVer":"\nreSemVer()\n    Returns a regular expression to match a semantic version string.\n\n    Returns\n    -------\n    out: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE_SEMVER = reSemVer()\n    <RegExp>\n    > var bool = RE_SEMVER.test( '1.0.0' )\n    true\n    > bool = RE_SEMVER.test( '1.0.0-alpha.1' )\n    true\n    > bool = RE_SEMVER.test( 'abc' )\n    false\n    > bool = RE_SEMVER.test( '1.0.0-alpha.1+build.1' )\n    true\n\n\nreSemVer.REGEXP\n    Regular expression to match a semantic version string.\n\n    Examples\n    --------\n    > var bool = reSemVer.REGEXP.test( '1.0.0' )\n    true\n    > bool = reSemVer.REGEXP.test( '-1.0.0-alpha.1' )\n    false\n\n\n    See Also\n    --------\n    isSemVer","reSemVer.REGEXP":"\nreSemVer.REGEXP\n    Regular expression to match a semantic version string.\n\n    Examples\n    --------\n    > var bool = reSemVer.REGEXP.test( '1.0.0' )\n    true\n    > bool = reSemVer.REGEXP.test( '-1.0.0-alpha.1' )\n    false\n\n\n    See Also\n    --------\n    isSemVer","resolveParentPath":"\nresolveParentPath( path[, options], clbk )\n    Asynchronously resolves a path by walking parent directories.\n\n    If unable to resolve a path, the function returns `null` as the path result.\n\n    Parameters\n    ----------\n    path: string\n        Path to resolve.\n\n    options: Object (optional)\n        Options.\n\n    options.dir: string (optional)\n        Base directory from which to search. Default: current working directory.\n\n    clbk: Function\n        Callback to invoke after resolving a path.\n\n    Examples\n    --------\n    > function onPath( error, path ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     } else {\n    ...         console.log( path );\n    ...     }\n    ... };\n    > resolveParentPath( 'package.json', onPath );\n\n\nresolveParentPath.sync( path[, options] )\n    Synchronously resolves a path by walking parent directories.\n\n    Parameters\n    ----------\n    path: string\n        Path to resolve.\n\n    options: Object (optional)\n        Options.\n\n    options.dir: string (optional)\n        Base directory from which to search. Default: current working directory.\n\n    Returns\n    -------\n    out: string|null\n        Resolved path.\n\n    Examples\n    --------\n    > var out = resolveParentPath.sync( 'package.json' );\n\n    See Also\n    --------\n    resolveParentPathBy\n","resolveParentPath.sync":"\nresolveParentPath.sync( path[, options] )\n    Synchronously resolves a path by walking parent directories.\n\n    Parameters\n    ----------\n    path: string\n        Path to resolve.\n\n    options: Object (optional)\n        Options.\n\n    options.dir: string (optional)\n        Base directory from which to search. Default: current working directory.\n\n    Returns\n    -------\n    out: string|null\n        Resolved path.\n\n    Examples\n    --------\n    > var out = resolveParentPath.sync( 'package.json' );\n\n    See Also\n    --------\n    resolveParentPathBy","resolveParentPathBy":"\nresolveParentPathBy( path[, options], predicate, clbk )\n    Asynchronously resolves a path according to a predicate function by walking\n    parent directories.\n\n    When invoked, the predicate function is provided two arguments:\n\n    - path: a resolved path.\n    - next: a callback to be invoked after processing a resolved path.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - result: test result.\n\n    If a provided predicate function calls the `next` callback with a truthy\n    `error` argument, the function suspends execution and immediately calls the\n    `done` callback for subsequent `error` handling.\n\n    The function immediately returns upon encountering a non-falsy `result`\n    value and calls the `done` callback with `null` as the first argument and\n    the resolved path as the second argument.\n\n    If unable to resolve a path, the function returns `null` as the path result.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Parameters\n    ----------\n    path: string\n        Path to resolve.\n\n    options: Object (optional)\n        Options.\n\n    options.dir: string (optional)\n        Base directory from which to search. Default: current working directory.\n\n    predicate: Function\n        The test function to invoke for each resolved path.\n\n    clbk: Function\n        Callback to invoke after resolving a path.\n\n    Examples\n    --------\n    > function predicate( path, next ) {\n    ...     setTimeout( onTimeout, path );\n    ...     function onTimeout() {\n    ...         console.log( path );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function onPath( error, path ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     } else {\n    ...         console.log( path );\n    ...     }\n    ... };\n    > resolveParentPathBy( 'package.json', predicate, onPath );\n\n\nresolveParentPathBy.sync( path[, options], predicate )\n    Synchronously resolves a path according to a predicate function by walking\n    parent directories.\n\n    The predicate function is provided one argument:\n\n    - path: a resolved path.\n\n    The function immediately returns upon encountering a truthy return value.\n\n    If unable to resolve a path, the function returns `null` as the path result.\n\n    Parameters\n    ----------\n    path: string\n        Path to resolve.\n\n    options: Object (optional)\n        Options.\n\n    options.dir: string (optional)\n        Base directory from which to search. Default: current working directory.\n\n    predicate: Function\n        The test function to invoke for each resolved path.\n\n    Returns\n    -------\n    out: string|null\n        Resolved path.\n\n    Examples\n    --------\n    > function predicate() { return false; };\n    > var out = resolveParentPathBy.sync( 'package.json', predicate );\n\n    See Also\n    --------\n    resolveParentPath\n","resolveParentPathBy.sync":"\nresolveParentPathBy.sync( path[, options], predicate )\n    Synchronously resolves a path according to a predicate function by walking\n    parent directories.\n\n    The predicate function is provided one argument:\n\n    - path: a resolved path.\n\n    The function immediately returns upon encountering a truthy return value.\n\n    If unable to resolve a path, the function returns `null` as the path result.\n\n    Parameters\n    ----------\n    path: string\n        Path to resolve.\n\n    options: Object (optional)\n        Options.\n\n    options.dir: string (optional)\n        Base directory from which to search. Default: current working directory.\n\n    predicate: Function\n        The test function to invoke for each resolved path.\n\n    Returns\n    -------\n    out: string|null\n        Resolved path.\n\n    Examples\n    --------\n    > function predicate() { return false; };\n    > var out = resolveParentPathBy.sync( 'package.json', predicate );\n\n    See Also\n    --------\n    resolveParentPath","reUncPath":"\nreUncPath()\n    Return a regular expression to parse a UNC path.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reUncPath();\n    > var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\n    > var bool = RE.test( path )\n    true\n    > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\n    > bool = RE.test( path )\n    true\n    > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a';\n    > bool = RE.test( path )\n    true\n    > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz';\n    > bool = RE.test( path )\n    true\n    > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar';\n    > bool = RE.test( path )\n    true\n    > path = '\\\\\\\\server\\\\share\\\\foo';\n    > bool = RE.test( path )\n    true\n    > path = '\\\\\\\\server\\\\share';\n    > bool = RE.test( path )\n    true\n    > path = '\\\\\\\\server\\\\\\\\share';\n    > bool = RE.test( path )\n    false\n    > path = '\\\\\\\\\\\\\\\\server\\\\share';\n    > bool = RE.test( path )\n    false\n    > path = 'beep boop \\\\\\\\server\\\\share';\n    > bool = RE.test( path )\n    false\n    > path = '\\\\\\\\server';\n    > bool = RE.test( path )\n    false\n    > path = '\\\\';\n    > bool = RE.test( path )\n    false\n    > path = '';\n    > bool = RE.test( path )\n    false\n    > path = '\\\\\\\\server\\\\share\\\\';\n    > bool = RE.test( path )\n    false\n    > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:';\n    > bool = RE.test( path )\n    false\n    > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:';\n    > bool = RE.test( path )\n    false\n    > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::';\n    > bool = RE.test( path )\n    false\n    > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b:c';\n    > bool = RE.test( path )\n    false\n    > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\';\n    > bool = RE.test( path )\n    false\n    > path = '//server/share';\n    > bool = RE.test( path )\n    false\n    > path = '/foo/bar';\n    > bool = RE.test( path )\n    false\n    > path = 'foo/bar';\n    > bool = RE.test( path )\n    false\n    > path = './foo/bar';\n    > bool = RE.test( path )\n    false\n    > path = '/foo/../bar';\n    > bool = RE.test( path )\n    false\n\n\nreUncPath.REGEXP\n    Regular expression to parse a UNC path.\n\n    Examples\n    --------\n    > var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\n    > var bool = reUncPath.REGEXP.test( path )\n    true\n    > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\n    > bool = reUncPath.REGEXP.test( path )\n    true\n\n    See Also\n    --------\n    isUNCPath\n","reUncPath.REGEXP":"\nreUncPath.REGEXP\n    Regular expression to parse a UNC path.\n\n    Examples\n    --------\n    > var path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz:a:b';\n    > var bool = reUncPath.REGEXP.test( path )\n    true\n    > path = '\\\\\\\\server\\\\share\\\\foo\\\\bar\\\\baz::b';\n    > bool = reUncPath.REGEXP.test( path )\n    true\n\n    See Also\n    --------\n    isUNCPath","reUtf16SurrogatePair":"\nreUtf16SurrogatePair()\n    Returns a regular expression to match a UTF-16 surrogate pair.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reUtf16SurrogatePair();\n    > var bool = RE.test( 'abc\\uD800\\uDC00def' )\n    true\n    > bool = RE.test( 'abcdef' )\n    false\n\n\nreUtf16SurrogatePair.REGEXP\n    Regular expression to match a UTF-16 surrogate pair.\n\n    Examples\n    --------\n    > var RE = reUtf16SurrogatePair.REGEXP;\n    > var bool = RE.test( 'abc\\uD800\\uDC00def' )\n    true\n    > bool = RE.test( 'abcdef' )\n    false\n\n    See Also\n    --------\n    reUtf16UnpairedSurrogate","reUtf16SurrogatePair.REGEXP":"\nreUtf16SurrogatePair.REGEXP\n    Regular expression to match a UTF-16 surrogate pair.\n\n    Examples\n    --------\n    > var RE = reUtf16SurrogatePair.REGEXP;\n    > var bool = RE.test( 'abc\\uD800\\uDC00def' )\n    true\n    > bool = RE.test( 'abcdef' )\n    false\n\n    See Also\n    --------\n    reUtf16UnpairedSurrogate","reUtf16UnpairedSurrogate":"\nreUtf16UnpairedSurrogate()\n    Returns a regular expression to match an unpaired UTF-16 surrogate.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reUtf16UnpairedSurrogate();\n    > var bool = RE.test( 'abc' )\n    false\n    > bool = RE.test( '\\uD800' )\n    true\n\n\nreUtf16UnpairedSurrogate.REGEXP\n    Regular expression to match an unpaired UTF-16 surrogate.\n\n    Examples\n    --------\n    > var RE = reUtf16UnpairedSurrogate.REGEXP;\n    > var bool = RE.test( 'abc' )\n    false\n    > bool = RE.test( '\\uD800' )\n    true\n\n    See Also\n    --------\n    reUtf16SurrogatePair","reUtf16UnpairedSurrogate.REGEXP":"\nreUtf16UnpairedSurrogate.REGEXP\n    Regular expression to match an unpaired UTF-16 surrogate.\n\n    Examples\n    --------\n    > var RE = reUtf16UnpairedSurrogate.REGEXP;\n    > var bool = RE.test( 'abc' )\n    false\n    > bool = RE.test( '\\uD800' )\n    true\n\n    See Also\n    --------\n    reUtf16SurrogatePair","reverseArguments":"\nreverseArguments( fcn[, thisArg] )\n    Returns a function that invokes a provided function with arguments in\n    reverse order.\n\n    Parameters\n    ----------\n    fcn: Function\n        Input function.\n\n    thisArg: any (optional)\n        Function context.\n\n    Returns\n    -------\n    out: Function\n        Function with reversed arguments.\n\n    Examples\n    --------\n    > function foo( a, b, c ) { return [ a, b, c ]; };\n    > var bar = reverseArguments( foo );\n    > var out = bar( 1, 2, 3 )\n    [ 3, 2, 1 ]\n\n    See Also\n    --------\n    maskArguments, reorderArguments\n","reverseString":"\nreverseString( str[, options] )\n    Reverses a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    options: Object (optional)\n        Options.\n\n    options.mode: string (optional)\n        Type of characters to reverse. The following modes are supported:\n\n        - grapheme: grapheme clusters. Appropriate for strings containing visual\n          characters which can span multiple Unicode code points (e.g., emoji).\n        - code_point: Unicode code points. Appropriate for strings containing\n          visual characters which are comprised of more than one Unicode code\n          unit (e.g., ideographic symbols and punctuation and mathematical\n          alphanumerics).\n        - code_unit': UTF-16 code units. Appropriate for strings containing\n          visual characters drawn from the basic multilingual plane (BMP) (e.g.,\n          common characters, such as those from the Latin, Greek, and Cyrillic\n          alphabets).\n\n        Default: 'grapheme'.\n\n    Returns\n    -------\n    out: string\n        Reversed string.\n\n    Examples\n    --------\n    > var out = reverseString( 'foo' )\n    'oof'\n    > out = reverseString( 'abcdef' )\n    'fedcba'\n\n","reviveBasePRNG":"\nreviveBasePRNG( key, value )\n    Revives a JSON-serialized pseudorandom number generator (PRNG).\n\n    Parameters\n    ----------\n    key: string\n        Key.\n\n    value: any\n        Value.\n\n    Returns\n    -------\n    out: any\n        Value or PRNG.\n\n    Examples\n    --------\n    > var str = JSON.stringify( base.random.mt19937 );\n    > var r = parseJSON( str, reviveBasePRNG )\n    <Function>\n\n","reviveBuffer":"\nreviveBuffer( key, value )\n    Revives a JSON-serialized Buffer.\n\n    The serialization format for a Buffer is an object having the following\n    fields:\n\n    - type: value type (Buffer).\n    - data: buffer data as an array of integers.\n\n    Parameters\n    ----------\n    key: string\n        Key.\n\n    value: any\n        Value.\n\n    Returns\n    -------\n    out: any\n        Value or Buffer.\n\n    Examples\n    --------\n    > var str = '{\"type\":\"Buffer\",\"data\":[5,3]}';\n    > var buf = parseJSON( str, reviveBuffer )\n    <Buffer>[ 5, 3 ]\n\n    See Also\n    --------\n    buffer2json\n","reviveComplex":"\nreviveComplex( key, value )\n    Revives a JSON-serialized complex number.\n\n    The serialization format for complex numbers is an object having the\n    following fields:\n\n    - type: complex number type (e.g., \"Complex128\", \"Complex64\").\n    - re: real component (number).\n    - im: imaginary component (number).\n\n    Parameters\n    ----------\n    key: string\n        Key.\n\n    value: any\n        Value.\n\n    Returns\n    -------\n    out: any\n        Value or complex number.\n\n    Examples\n    --------\n    > var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\n    > var z = parseJSON( str, reviveComplex )\n    <Complex128>\n\n    See Also\n    --------\n    Complex128, Complex64, reviveComplex128, reviveComplex64\n","reviveComplex64":"\nreviveComplex64( key, value )\n    Revives a JSON-serialized 64-bit complex number.\n\n    Parameters\n    ----------\n    key: string\n        Key.\n\n    value: any\n        Value.\n\n    Returns\n    -------\n    out: any\n        Value or complex number.\n\n    Examples\n    --------\n    > var str = '{\"type\":\"Complex64\",\"re\":5,\"im\":3}';\n    > var z = parseJSON( str, reviveComplex64 )\n    <Complex64>\n\n    See Also\n    --------\n    Complex64, reviveComplex128, reviveComplex\n","reviveComplex128":"\nreviveComplex128( key, value )\n    Revives a JSON-serialized 128-bit complex number.\n\n    Parameters\n    ----------\n    key: string\n        Key.\n\n    value: any\n        Value.\n\n    Returns\n    -------\n    out: any\n        Value or complex number.\n\n    Examples\n    --------\n    > var str = '{\"type\":\"Complex128\",\"re\":5,\"im\":3}';\n    > var z = parseJSON( str, reviveComplex128 )\n    <Complex128>\n\n    See Also\n    --------\n    Complex128, reviveComplex64, reviveComplex\n","reviveError":"\nreviveError( key, value )\n    Revives a JSON-serialized error object.\n\n    The following built-in error types are supported:\n\n    - Error\n    - URIError\n    - ReferenceError\n    - SyntaxError\n    - RangeError\n    - EvalError\n    - TypeError\n\n    Parameters\n    ----------\n    key: string\n        Key.\n\n    value: any\n        Value.\n\n    Returns\n    -------\n    out: any\n        Value or error object.\n\n    Examples\n    --------\n    > var str = '{\"type\":\"TypeError\",\"message\":\"beep\"}';\n    > var err = JSON.parse( str, reviveError )\n    <TypeError>\n\n    See Also\n    --------\n    error2json\n","reviveRegExp":"\nreviveRegExp( key, value )\n    Revives a JSON-serialized regular expression.\n\n    The serialization format for a regular expression is an object having the\n    following fields:\n\n    - type: value type (RegExp).\n    - pattern: regular expression pattern.\n    - flags: regular expression flags.\n\n    Parameters\n    ----------\n    key: string\n        Key.\n\n    value: any\n        Value.\n\n    Returns\n    -------\n    out: any\n        Value or regular expression.\n\n    Examples\n    --------\n    > var str = '{\"type\":\"RegExp\",\"pattern\":\"ab+c\",\"flags\":\"\"}';\n    > var v = parseJSON( str, reviveRegExp )\n    <RegExp>\n\n    See Also\n    --------\n    regexp2json","reviveTypedArray":"\nreviveTypedArray( key, value )\n    Revives a JSON-serialized typed array.\n\n    The serialization format for typed array is an object having the following\n    fields:\n\n    - type: typed array type (e.g., \"Float64Array\", \"Int8Array\").\n    - data: typed array data as an array of numbers.\n\n    Parameters\n    ----------\n    key: string\n        Key.\n\n    value: any\n        Value.\n\n    Returns\n    -------\n    out: any\n        Value or typed array.\n\n    Examples\n    --------\n    > var str = '{\"type\":\"Float64Array\",\"data\":[5,3]}';\n    > var arr = parseJSON( str, reviveTypedArray )\n    <Float64Array>[ 5.0, 3.0 ]\n\n    See Also\n    --------\n    typedarray2json\n","reWhitespace":"\nreWhitespace( [options] )\n    Returns a regular expression to match a white space character.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.flags: string (optional)\n        Regular expression flags. Default: ''.\n\n    options.capture: boolean (optional)\n        Boolean indicating whether to wrap a regular expression matching a white\n        space character with a capture group. Default: false.\n\n    Returns\n    -------\n    re: RegExp\n        Regular expression.\n\n    Examples\n    --------\n    > var RE = reWhitespace();\n    > var bool = RE.test( '\\n' )\n    true\n    > bool = RE.test( ' ' )\n    true\n    > bool = RE.test( 'a' )\n    false\n\n\nreWhitespace.REGEXP\n    Regular expression to match a white space character.\n\n    Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n    characters in the Unicode 9.0 character database.\n\n    Matches one related white space character without the Unicode character\n    property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n    of Unicode 3.2).\n\n    Examples\n    --------\n    > var RE = reWhitespace.REGEXP;\n    > var bool = RE.test( '\\n' )\n    true\n    > bool = RE.test( ' ' )\n    true\n    > bool = RE.test( 'a' )\n    false\n\n\nreWhitespace.REGEXP_CAPTURE\n    Regular expression to capture white space characters.\n\n    Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n    characters in the Unicode 9.0 character database.\n\n    Matches one related white space character without the Unicode character\n    property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n    of Unicode 3.2).\n\n    Examples\n    --------\n    > var RE = reWhitespace.REGEXP_CAPTURE;\n    > var str = 'Duplicate capture';\n    > var out = replace( str, RE, '$1$1' )\n    'Duplicate  capture'\n\n    See Also\n    --------\n    isWhitespace","reWhitespace.REGEXP":"\nreWhitespace.REGEXP\n    Regular expression to match a white space character.\n\n    Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n    characters in the Unicode 9.0 character database.\n\n    Matches one related white space character without the Unicode character\n    property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n    of Unicode 3.2).\n\n    Examples\n    --------\n    > var RE = reWhitespace.REGEXP;\n    > var bool = RE.test( '\\n' )\n    true\n    > bool = RE.test( ' ' )\n    true\n    > bool = RE.test( 'a' )\n    false","reWhitespace.REGEXP_CAPTURE":"\nreWhitespace.REGEXP_CAPTURE\n    Regular expression to capture white space characters.\n\n    Matches the 25 characters defined as white space (\"WSpace=Y\",\"WS\")\n    characters in the Unicode 9.0 character database.\n\n    Matches one related white space character without the Unicode character\n    property \"WSpace=Y\" (zero width non-breaking space which was deprecated as\n    of Unicode 3.2).\n\n    Examples\n    --------\n    > var RE = reWhitespace.REGEXP_CAPTURE;\n    > var str = 'Duplicate capture';\n    > var out = replace( str, RE, '$1$1' )\n    'Duplicate  capture'\n\n    See Also\n    --------\n    isWhitespace","rpad":"\nrpad( str, len[, pad] )\n    Right pads a `string` such that the padded `string` has a length of at least\n    `len`.\n\n    An output string is not guaranteed to have a length of exactly `len`, but to\n    have a length of at least `len`. To generate a padded string having a length\n    equal to `len`, post-process a padded string by trimming off excess\n    characters.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    len: integer\n        Minimum string length.\n\n    pad: string (optional)\n        String used to pad. Default: ' '.\n\n    Returns\n    -------\n    out: string\n        Padded string.\n\n    Examples\n    --------\n    > var out = rpad( 'a', 5 )\n    'a    '\n    > out = rpad( 'beep', 10, 'p' )\n    'beeppppppp'\n    > out = rpad( 'beep', 12, 'boop' )\n    'beepboopboop'\n\n    See Also\n    --------\n    lpad, pad\n","rtrim":"\nrtrim( str )\n    Trims whitespace from the end of a string.\n\n    \"Whitespace\" is defined as the following characters:\n\n    - \\f\n    - \\n\n    - \\r\n    - \\t\n    - \\v\n    - \\u0020\n    - \\u00a0\n    - \\u1680\n    - \\u2000-\\u200a\n    - \\u2028\n    - \\u2029\n    - \\u202f\n    - \\u205f\n    - \\u3000\n    - \\ufeff\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Trimmed string.\n\n    Examples\n    --------\n    > var out = rtrim( ' \\t\\t\\n  Beep \\r\\n\\t  ' )\n    ' \\t\\t\\n  Beep'\n\n    See Also\n    --------\n    ltrim, trim\n","rtrimN":"\nrtrimN( str, n[, chars] )\n    Trims `n` characters from the end of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    n: integer\n        Number of characters to trim.\n\n    chars: Array<string>|string (optional)\n        Characters to trim. Default: whitespace characters.\n\n    Returns\n    -------\n    out: string\n        Trimmed string.\n\n    Examples\n    --------\n    > var out = rtrimN( '  abc  ', 2 )\n    '  abc'\n    > var out = rtrimN( '!!!abc!!!', 2, '!' )\n    '!!!abc!'\n\n    See Also\n    --------\n    ltrimN, trim","safeintmax":"\nsafeintmax( dtype )\n    Returns the maximum safe integer capable of being represented by a numeric\n    real type.\n\n    The following numeric real types are supported:\n\n    - float64: double-precision floating-point numbers.\n    - float32: single-precision floating-point numbers.\n    - float16: half-precision floating-point numbers.\n\n    Parameters\n    ----------\n    dtype: string\n        Numeric type.\n\n    Returns\n    -------\n    out: integer\n        Maximum safe integer.\n\n    Examples\n    --------\n    > var m = safeintmax( 'float16' )\n    2047\n    > m = safeintmax( 'float32' )\n    16777215\n\n    See Also\n    --------\n    safeintmin, realmax, typemax\n","safeintmin":"\nsafeintmin( dtype )\n    Returns the minimum safe integer capable of being represented by a numeric\n    real type.\n\n    The following numeric real types are supported:\n\n    - float64: double-precision floating-point numbers.\n    - float32: single-precision floating-point numbers.\n    - float16: half-precision floating-point numbers.\n\n    Parameters\n    ----------\n    dtype: string\n        Numeric type.\n\n    Returns\n    -------\n    out: integer\n        Minimum safe integer.\n\n    Examples\n    --------\n    > var m = safeintmin( 'float16' )\n    -2047\n    > m = safeintmin( 'float32' )\n    -16777215\n\n    See Also\n    --------\n    safeintmax, realmin, typemin\n","sample":"\nsample( x[, options] )\n    Samples elements from an array-like object.\n\n    Parameters\n    ----------\n    x: ArrayLike\n        Array-like object from which to sample.\n\n    options: Object (optional)\n        Options.\n\n    options.size: integer (optional)\n        Sample size. By default, the function returns an array having the same\n        length as `x`. Specify the `size` option to generate a sample of a\n        different size.\n\n    options.probs: Array<number> (optional)\n        Element probabilities. By default, the probability of sampling an\n        element is the same for all elements. To assign elements different\n        probabilities, set the `probs` option. The `probs` option must be a\n        numeric array consisting of nonnegative values which sum to one. When\n        sampling without replacement, note that the `probs` option denotes the\n        initial element probabilities which are then updated after each draw.\n\n    options.replace: boolean (optional)\n        Boolean indicating whether to sample with replacement. If the `replace`\n        option is set to `false`, the `size` option cannot be an integer larger\n        than the number of elements in `x`. Default: `true`.\n\n    Returns\n    -------\n    out: Array\n        Sample.\n\n    Examples\n    --------\n    > var out = sample( 'abc' )\n    e.g., [ 'a', 'a', 'b' ]\n    > out = sample( [ 3, 6, 9 ] )\n    e.g., [ 3, 9, 6 ]\n    > var bool = ( out.length === 3 )\n    true\n\n    > out = sample( [ 3, null, NaN, 'abc', function(){} ] )\n    e.g., [ 3, 'abc', null, 3, null ]\n\n    // Set sample size:\n    > out = sample( [ 3, 6, 9 ], { 'size': 10 } )\n    e.g., [ 6, 3, 9, 9, 9, 6, 9, 6, 9, 3 ]\n    > out = sample( [ 0, 1 ], { 'size': 20 } )\n    e.g., [ 0, 0, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 0 ]\n\n    // Draw without replacement:\n    > out = sample( [ 1, 2, 3, 4, 5, 6 ], { 'replace': false, 'size': 3 } )\n    e.g., [ 6, 1, 5 ]\n    > out = sample( [ 0, 1 ], { 'replace': false } )\n    e.g., [ 0, 1 ]\n\n    // Assigning non-uniform element probabilities:\n    > var x = [ 1, 2, 3, 4, 5, 6 ];\n    > var probs = [ 0.1, 0.1, 0.1, 0.1, 0.1, 0.5 ];\n    > out = sample( x, { 'probs': probs } )\n    e.g., [ 5, 6, 6, 5, 6, 4 ]\n    > out = sample( x, { 'probs': probs, 'size': 3, 'replace': false } )\n    e.g., [ 6, 4, 1 ]\n\n\nsample.factory( [pool, ][options] )\n    Returns a function to sample elements from an array-like object.\n\n    If provided an array-like object `pool`, the returned function will always\n    sample from the supplied object.\n\n    Parameters\n    ----------\n    pool: ArrayLike (optional)\n        Array-like object from which to sample.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer (optional)\n        Integer-valued seed.\n\n    options.size: integer (optional)\n        Sample size.\n\n    options.replace: boolean (optional)\n        Boolean indicating whether to sample with replacement. Default: `true`.\n\n    options.mutate: boolean (optional)\n        Boolean indicating whether to mutate the `pool` when sampling without\n        replacement. If a population from which to sample is provided, the\n        underlying `pool` remains by default constant for each function\n        invocation. To mutate the `pool` by permanently removing observations\n        when sampling without replacement, set the `mutate` option to `true`.\n        The returned function returns `null` after all population units are\n        exhausted. Default: `false`.\n\n    Returns\n    -------\n    fcn: Function\n        Function to sample elements from an array-like object.\n\n    Examples\n    --------\n    // Set a seed:\n    > var mysample = sample.factory({ 'seed': 232 } );\n    > var out = mysample( 'abcdefg' )\n    e.g., [ 'g', 'd', 'g', 'f', 'c', 'e', 'f' ]\n\n    // Provide `pool` and set a seed plus a default sample size:\n    > var pool = [ 1, 2, 3, 4, 5, 6 ];\n    > mysample = sample.factory( pool, { 'seed': 232, 'size': 2 } );\n    > out = mysample()\n    e.g., [ 6, 4 ]\n    > out = mysample()\n    e.g., [ 6, 5 ]\n\n    // Mutate the `pool`:\n    > var opts = { 'seed': 474, 'size': 3, 'mutate': true, 'replace': false };\n    > pool = [ 1, 2, 3, 4, 5, 6 ];\n    > mysample = sample.factory( pool, opts );\n    > out = mysample()\n    e.g., [ 4, 3, 6 ]\n    > out = mysample()\n    e.g., [ 1, 5, 2 ]\n    > out = mysample()\n    null\n\n    // Override default `size` parameter when invoking created function:\n    > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n    > out = mysample()\n    e.g., [ 1, 1 ]\n    > out = mysample({ 'size': 10 })\n    e.g, [ 0, 1, 1, 1, 0, 1, 0, 0, 1, 1 ]\n\n    // Sample with and without replacement:\n    > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n    > out = mysample()\n    e.g., [ 1, 1 ]\n    > out = mysample({ 'replace': false })\n    e.g., [ 0, 1 ] or [ 1, 0 ]\n    > out = mysample()\n    e.g., [ 1, 1 ]\n\n","sample.factory":"\nsample.factory( [pool, ][options] )\n    Returns a function to sample elements from an array-like object.\n\n    If provided an array-like object `pool`, the returned function will always\n    sample from the supplied object.\n\n    Parameters\n    ----------\n    pool: ArrayLike (optional)\n        Array-like object from which to sample.\n\n    options: Object (optional)\n        Options.\n\n    options.seed: integer (optional)\n        Integer-valued seed.\n\n    options.size: integer (optional)\n        Sample size.\n\n    options.replace: boolean (optional)\n        Boolean indicating whether to sample with replacement. Default: `true`.\n\n    options.mutate: boolean (optional)\n        Boolean indicating whether to mutate the `pool` when sampling without\n        replacement. If a population from which to sample is provided, the\n        underlying `pool` remains by default constant for each function\n        invocation. To mutate the `pool` by permanently removing observations\n        when sampling without replacement, set the `mutate` option to `true`.\n        The returned function returns `null` after all population units are\n        exhausted. Default: `false`.\n\n    Returns\n    -------\n    fcn: Function\n        Function to sample elements from an array-like object.\n\n    Examples\n    --------\n    // Set a seed:\n    > var mysample = sample.factory({ 'seed': 232 } );\n    > var out = mysample( 'abcdefg' )\n    e.g., [ 'g', 'd', 'g', 'f', 'c', 'e', 'f' ]\n\n    // Provide `pool` and set a seed plus a default sample size:\n    > var pool = [ 1, 2, 3, 4, 5, 6 ];\n    > mysample = sample.factory( pool, { 'seed': 232, 'size': 2 } );\n    > out = mysample()\n    e.g., [ 6, 4 ]\n    > out = mysample()\n    e.g., [ 6, 5 ]\n\n    // Mutate the `pool`:\n    > var opts = { 'seed': 474, 'size': 3, 'mutate': true, 'replace': false };\n    > pool = [ 1, 2, 3, 4, 5, 6 ];\n    > mysample = sample.factory( pool, opts );\n    > out = mysample()\n    e.g., [ 4, 3, 6 ]\n    > out = mysample()\n    e.g., [ 1, 5, 2 ]\n    > out = mysample()\n    null\n\n    // Override default `size` parameter when invoking created function:\n    > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n    > out = mysample()\n    e.g., [ 1, 1 ]\n    > out = mysample({ 'size': 10 })\n    e.g, [ 0, 1, 1, 1, 0, 1, 0, 0, 1, 1 ]\n\n    // Sample with and without replacement:\n    > mysample = sample.factory( [ 0, 1 ], { 'size': 2 } );\n    > out = mysample()\n    e.g., [ 1, 1 ]\n    > out = mysample({ 'replace': false })\n    e.g., [ 0, 1 ] or [ 1, 0 ]\n    > out = mysample()\n    e.g., [ 1, 1 ]","SAVOY_STOPWORDS_FIN":"\nSAVOY_STOPWORDS_FIN()\n    Returns a list of Finnish stop words.\n\n    Returns\n    -------\n    out: Array<string>\n        List of stop words.\n\n    Examples\n    --------\n    > var list = SAVOY_STOPWORDS_FIN()\n    [ 'aiemmin', 'aika', 'aikaa', ... ]\n\n    References\n    ----------\n    - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n    <http://members.unine.ch/jacques.savoy/clef/>.\n\n","SAVOY_STOPWORDS_FR":"\nSAVOY_STOPWORDS_FR()\n    Returns a list of French stop words.\n\n    Returns\n    -------\n    out: Array<string>\n        List of stop words.\n\n    Examples\n    --------\n    > var list = SAVOY_STOPWORDS_FR()\n    [ 'a', 'à', 'â', 'abord', ... ]\n\n    References\n    ----------\n    - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n    <http://members.unine.ch/jacques.savoy/clef/>.\n\n","SAVOY_STOPWORDS_GER":"\nSAVOY_STOPWORDS_GER()\n    Returns a list of German stop words.\n\n    Returns\n    -------\n    out: Array<string>\n        List of stop words.\n\n    Examples\n    --------\n    > var list = SAVOY_STOPWORDS_GER()\n    [ 'a', 'ab', 'aber', 'ach', ... ]\n\n    References\n    ----------\n    - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n    <http://members.unine.ch/jacques.savoy/clef/>.\n\n","SAVOY_STOPWORDS_IT":"\nSAVOY_STOPWORDS_IT()\n    Returns a list of Italian stop words.\n\n    Returns\n    -------\n    out: Array<string>\n        List of stop words.\n\n    Examples\n    --------\n    > var list = SAVOY_STOPWORDS_IT()\n    [ 'a', 'abbastanza', 'accidenti', 'ad', ... ]\n\n    References\n    ----------\n    - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n    <http://members.unine.ch/jacques.savoy/clef/>.\n\n","SAVOY_STOPWORDS_POR":"\nSAVOY_STOPWORDS_POR()\n    Returns a list of Portuguese stop words.\n\n    Returns\n    -------\n    out: Array<string>\n        List of stop words.\n\n    Examples\n    --------\n    > var list = SAVOY_STOPWORDS_POR()\n    [ 'aiemmin', 'aika', 'aikaa', ... ]\n\n    References\n    ----------\n    - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n    <http://members.unine.ch/jacques.savoy/clef/>.\n\n","SAVOY_STOPWORDS_SP":"\nSAVOY_STOPWORDS_SP()\n    Returns a list of Spanish stop words.\n\n    Returns\n    -------\n    out: Array<string>\n        List of stop words.\n\n    Examples\n    --------\n    > var list = SAVOY_STOPWORDS_SP()\n    [ 'a', 'acuerdo', 'adelante', 'ademas', ... ]\n\n    References\n    ----------\n    - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n    <http://members.unine.ch/jacques.savoy/clef/>.\n\n","SAVOY_STOPWORDS_SWE":"\nSAVOY_STOPWORDS_SWE()\n    Returns a list of Swedish stop words.\n\n    Returns\n    -------\n    out: Array<string>\n        List of stop words.\n\n    Examples\n    --------\n    > var list = SAVOY_STOPWORDS_SWE()\n    [ 'aderton', 'adertonde', 'adjö', ... ]\n\n    References\n    ----------\n    - Savoy, Jacques. 2005. \"IR Multilingual Resources at UniNE.\"\n    <http://members.unine.ch/jacques.savoy/clef/>.\n\n","scalar2array":"\nscalar2array( value[, dtype] )\n    Returns a single-element array containing a provided scalar value.\n\n    If `value` is a number and `dtype` is a complex number data type, the\n    function returns a complex number array containing a complex number whose\n    real component equals the provided scalar value and whose imaginary\n    component is zero.\n\n    Parameters\n    ----------\n    value: any\n        Scalar value.\n\n    dtype: string (optional)\n        Data type. If not provided and `value`\n\n        - is a number, the default data type is the default real-valued\n          floating-point data type.\n        - is a boolean, the default data type is the default boolean data type.\n        - is a complex number object of a known complex data type, the data type\n          is the same as the provided value.\n        - is a complex number object of an unknown data type, the default data\n          type is the default complex-valued floating-point data type.\n        - is any other value type, the default data type is 'generic'.\n\n    Returns\n    -------\n    out: Array|TypedArray\n        Output array.\n\n    Examples\n    --------\n    > var x = scalar2array( 1.0 )\n    <Float64Array>[ 1.0 ]\n\n    See Also\n    --------\n    iterator2array\n","scalar2ndarray":"\nscalar2ndarray( value[, options] )\n    Returns a zero-dimensional ndarray containing a provided scalar value.\n\n    If `value` is a number and `options.dtype` is a complex number data type,\n    the function returns a zero-dimensional ndarray containing a complex number\n    whose real component equals the provided scalar value and whose imaginary\n    component is zero.\n\n    Parameters\n    ----------\n    value: any\n        Scalar value.\n\n    options: Object (optional)\n        Options.\n\n    options.dtype: string (optional)\n        Data type. If not provided and `value`\n\n        - is a number, the default data type is the default real-valued\n          floating-point data type.\n        - is a boolean, the default data type is the default boolean data type.\n        - is a complex number object of a known complex data type, the data type\n          is the same as the provided value.\n        - is a complex number object of an unknown data type, the default data\n          type is the default complex-valued floating-point data type.\n        - is any other value type, the default data type is 'generic'.\n\n    options.order: string (optional)\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran-style). Default: 'row-major'.\n\n    options.readonly: boolean (optional)\n        Boolean indicating whether an array should be read-only. Default: false.\n\n    Returns\n    -------\n    out: ndarray\n        Output array.\n\n    Examples\n    --------\n    > var x = scalar2ndarray( 1.0 )\n    <ndarray>\n    > var sh = x.shape\n    []\n    > var dt = x.dtype\n    'float64'\n    > var v = x.get()\n    1.0\n\n    See Also\n    --------\n    array, ndarray\n","sdot":"\nsdot( x, y[, dim] )\n    Computes the dot product of two single-precision floating-point vectors.\n\n    If provided at least one input array having more than one dimension, the\n    input arrays are broadcasted to a common shape.\n\n    For multi-dimensional input arrays, the function performs batched\n    computation, such that the function computes the dot product for each pair\n    of vectors in `x` and `y` according to the specified dimension index.\n\n    The size of the contracted dimension must be the same for both input arrays.\n\n    The function resolves the dimension index for which to compute the dot\n    product *before* broadcasting.\n\n    If provided empty vectors, the dot product is `0`.\n\n    Parameters\n    ----------\n    x: ndarray\n        First input array. Must have a 'float32' data type. Must have at least\n        one dimension and be broadcast-compatible with the second input array.\n\n    y: ndarray\n        Second input array. Must have a 'float32' data type. Must have at least\n        one dimension and be broadcast-compatible with the first input array.\n\n    dim: integer (optional)\n        Dimension index for which to compute the dot product. Must be a negative\n        integer. Negative indices are resolved relative to the last array\n        dimension, with the last dimension corresponding to `-1`. Default: -1.\n\n    Returns\n    -------\n    out: ndarray\n        The dot product. The output array has the same data type as the input\n        arrays and has a shape which is determined by broadcasting and excludes\n        the contracted dimension.\n\n    Examples\n    --------\n    > var xbuf = new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );\n    > var x = array( xbuf );\n    > var ybuf = new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] );\n    > var y = array( ybuf );\n    > var z = sdot( x, y )\n    <ndarray>\n    > z.get()\n    -5.0\n\n    See Also\n    --------\n    base.strided.sdot, ddot, gdot\n","SECONDS_IN_DAY":"\nSECONDS_IN_DAY\n    Number of seconds in a day.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var days = 3.14;\n    > var secs = days * SECONDS_IN_DAY\n    271296\n\n","SECONDS_IN_HOUR":"\nSECONDS_IN_HOUR\n    Number of seconds in an hour.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var hrs = 3.14;\n    > var secs = hrs * SECONDS_IN_HOUR\n    11304\n\n","SECONDS_IN_MINUTE":"\nSECONDS_IN_MINUTE\n    Number of seconds in a minute.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies arising due to complications with time and dates.\n\n    Examples\n    --------\n    > var mins = 3.14;\n    > var secs = mins * SECONDS_IN_MINUTE\n    188.4\n\n","SECONDS_IN_WEEK":"\nSECONDS_IN_WEEK\n    Number of seconds in a week.\n\n    The value is a generalization and does **not** take into account\n    inaccuracies due to daylight savings conventions, crossing timezones, or\n    other complications with time and dates.\n\n    Examples\n    --------\n    > var wks = 3.14;\n    > var secs = wks * SECONDS_IN_WEEK\n    1899072\n\n","secondsInMonth":"\nsecondsInMonth( [month[, year]] )\n    Returns the number of seconds in a month.\n\n    By default, the function returns the number of seconds in the current month\n    of the current year (according to local time). To determine the number of\n    seconds for a particular month and year, provide `month` and `year`\n    arguments.\n\n    A `month` may be either a month's integer value, three letter abbreviation,\n    or full name (case insensitive).\n\n    The function's return value is a generalization and does **not** take into\n    account inaccuracies due to daylight savings conventions, crossing\n    timezones, or other complications with time and dates.\n\n    Parameters\n    ----------\n    month: string|Date|integer (optional)\n        Month.\n\n    year: integer (optional)\n        Year.\n\n    Returns\n    -------\n    out: integer\n        Seconds in a month.\n\n    Examples\n    --------\n    > var num = secondsInMonth()\n    <number>\n    > num = secondsInMonth( 2 )\n    <number>\n    > num = secondsInMonth( 2, 2016 )\n    2505600\n    > num = secondsInMonth( 2, 2017 )\n    2419200\n\n    // Other ways to supply month:\n    > num = secondsInMonth( 'feb', 2016 )\n    2505600\n    > num = secondsInMonth( 'february', 2016 )\n    2505600\n\n    See Also\n    --------\n    secondsInYear\n","secondsInYear":"\nsecondsInYear( [value] )\n    Returns the number of seconds in a year according to the Gregorian calendar.\n\n    By default, the function returns the number of seconds in the current year\n    (according to local time). To determine the number of seconds for a\n    particular year, provide either a year or a `Date` object.\n\n    The function's return value is a generalization and does **not** take into\n    account inaccuracies due to daylight savings conventions, crossing\n    timezones, or other complications with time and dates.\n\n    Parameters\n    ----------\n    value: integer|Date (optional)\n        Year or `Date` object.\n\n    Returns\n    -------\n    out: integer\n        Number of seconds in a year.\n\n    Examples\n    --------\n    > var num = secondsInYear()\n    <number>\n    > num = secondsInYear( 2016 )\n    31622400\n    > num = secondsInYear( 2017 )\n    31536000\n\n    See Also\n    --------\n    secondsInMonth\n","sentencize":"\nsentencize( str )\n    Splits a string into an array of sentences.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: Array\n        Array of sentences.\n\n    Examples\n    --------\n    > var out = sentencize( 'Hello Mrs. Maple, could you call me back?' )\n    [ 'Hello Mrs. Maple, could you call me back?' ]\n\n    > out = sentencize( 'Hello World! How are you?' )\n    [ 'Hello World!', 'How are you?' ]\n\n    See Also\n    --------\n    tokenize\n","seq2slice":"\nseq2slice( str, len, strict )\n    Converts a subsequence string to a Slice object.\n\n    A subsequence string has the following format:\n\n      <start>:<stop>:<increment>\n\n    If an increment is not specified, the default increment is one. An increment\n    of zero is not allowed.\n\n    The start index is inclusive.\n\n    The stop index is exclusive.\n\n    Both start and stop indices are optional. If not provided, the start and\n    stop indices default to index extremes. Which extremes correspond to which\n    index depends on whether the increment is positive or negative.\n\n    Both start and stop indices can be negative; in which case, the\n    corresponding index is resolved by subtracting the respective value from the\n    provided length.\n\n    Both start and stop indices can use the 'end' keyword (e.g., 'end-2::2',\n    'end-3:', etc), which supports basic subtraction and division.\n\n    The 'end' keyword resolves to the provided length. Thus, ':-1' is equivalent\n    to ':end-1', ':-2' is equivalent to ':end-2', and so on and so forth. The\n    exception is when performing a division operation when the increment is less\n    than zero; in which case, 'end' is equal to 'len-1' in order to preserve\n    user expectations when 'end/d' equals a whole number and slicing from right-\n    to-left. The result from a division operation is rounded down to the nearest\n    integer value.\n\n    In non-strict mode, the resolved slice start is clamped to the slice index\n    bounds [0, len).\n\n    In non-strict mode, Tte resolved slice end is upper bound clamped to the\n    provided length (i.e., one greater than the last possible index).\n\n    When the increment is negative, the resolved slice end value may be `null`,\n    thus indicating that a non-empty slice should include the first index.\n\n    The function ensures that results satisfy the convention that ':n' combined\n    with 'n:' is equivalent to ':' (i.e., selecting all elements).\n\n    When the provided length is zero, the function always returns a slice object\n    equivalent to '0:0:<increment>'.\n\n    Parameters\n    ----------\n    str: string\n        Subsequence string.\n\n    len: integer\n        Maximum number of elements allowed in the slice.\n\n    strict: boolean\n        Boolean indicating whether to enforce strict bounds checking.\n\n    Returns\n    -------\n    s: Slice\n        Slice instance.\n\n    Examples\n    --------\n    > var s = new seq2slice( '1:10', 10, false );\n    > s.start\n    1\n    > s.stop\n    10\n    > s.step\n    1\n    > s = new seq2slice( '2:5:2', 10, false );\n    > s.start\n    2\n    > s.stop\n    5\n    > s.step\n    2\n\n    See Also\n    --------\n    Slice\n","setConfigurableReadOnly":"\nsetConfigurableReadOnly( obj, prop, value )\n    Defines a configurable read-only property.\n\n    Configurable read-only properties are enumerable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    value: any\n        Value to set.\n\n    Examples\n    --------\n    > var obj = {};\n    > setConfigurableReadOnly( obj, 'foo', 'bar' );\n    > obj.foo = 'boop';\n    > obj\n    { 'foo': 'bar' }\n\n    See Also\n    --------\n    setConfigurableReadOnlyAccessor, setConfigurableReadWriteAccessor, defineProperty, setReadOnly\n","setConfigurableReadOnlyAccessor":"\nsetConfigurableReadOnlyAccessor( obj, prop, getter )\n    Defines a configurable read-only accessor.\n\n    Configurable read-only accessors are enumerable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    getter: Function\n        Get accessor.\n\n    Examples\n    --------\n    > var obj = {};\n    > function getter() { return 'bar'; };\n    > setConfigurableReadOnlyAccessor( obj, 'foo', getter );\n    > obj.foo\n    'bar'\n\n    See Also\n    --------\n    setConfigurableReadOnly, setConfigurableReadWriteAccessor, setConfigurableWriteOnlyAccessor, defineProperty, setReadOnlyAccessor\n","setConfigurableReadWriteAccessor":"\nsetConfigurableReadWriteAccessor( obj, prop, getter, setter )\n    Defines a configurable property having read-write accessors.\n\n    Configurable read-write accessors are enumerable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    getter: Function\n        Get accessor.\n\n    setter: Function\n        Set accessor.\n\n    Examples\n    --------\n    > var obj = {};\n    > var name = 'bar';\n    > function getter() { return name + ' foo'; };\n    > function setter( v ) { name = v; };\n    > setConfigurableReadWriteAccessor( obj, 'foo', getter, setter );\n    > obj.foo\n    'bar foo'\n    > obj.foo = 'beep';\n    > obj.foo\n    'beep foo'\n\n    See Also\n    --------\n    setConfigurableReadOnly, setConfigurableReadOnlyAccessor, setConfigurableWriteOnlyAccessor, defineProperty, setReadWriteAccessor\n","setConfigurableWriteOnlyAccessor":"\nsetConfigurableWriteOnlyAccessor( obj, prop, setter )\n    Defines a configurable write-only accessor.\n\n    Configurable write-only accessors are enumerable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    setter: Function\n        Set accessor.\n\n    Examples\n    --------\n    > var obj = {};\n    > var val = '';\n    > function setter( v ) { val = v; };\n    > setConfigurableWriteOnlyAccessor( obj, 'foo', setter );\n    > obj.foo = 'bar';\n    > val\n    'bar'\n\n    See Also\n    --------\n    setConfigurableReadOnly, setConfigurableReadOnlyAccessor, setConfigurableReadWriteAccessor, defineProperty, setWriteOnlyAccessor\n","setMemoizedConfigurableReadOnly":"\nsetMemoizedConfigurableReadOnly( obj, prop, fcn )\n    Defines a configurable memoized read-only object property.\n\n    Configurable read-only properties are enumerable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    fcn: Function\n        Synchronous function whose return value will be memoized and set as the\n        property value.\n\n    Examples\n    --------\n    > var obj = {};\n    > function foo() { return 'bar'; };\n    > setMemoizedConfigurableReadOnly( obj, 'foo', foo );\n    > obj.foo\n    'bar'\n\n    See Also\n    --------\n    setConfigurableReadOnly, setMemoizedReadOnly, setReadOnly\n","setMemoizedReadOnly":"\nsetMemoizedReadOnly( obj, prop, fcn )\n    Defines a memoized read-only object property.\n\n    Read-only properties are enumerable and non-configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    fcn: Function\n        Synchronous function whose return value will be memoized and set as the\n        property value.\n\n    Examples\n    --------\n    > var obj = {};\n    > function foo() { return 'bar'; };\n    > setMemoizedReadOnly( obj, 'foo', foo );\n    > obj.foo\n    'bar'\n\n    See Also\n    --------\n    defineMemoizedProperty, setReadOnly\n","setNonEnumerableProperty":"\nsetNonEnumerableProperty( obj, prop, value )\n    Defines a non-enumerable property.\n\n    Non-enumerable properties are writable and configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    value: any\n        Value to set.\n\n    Examples\n    --------\n    > var obj = {};\n    > setNonEnumerableProperty( obj, 'foo', 'bar' );\n    > obj.foo\n    'bar'\n    > objectKeys( obj )\n    []\n\n    See Also\n    --------\n    setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnly\n","setNonEnumerableReadOnly":"\nsetNonEnumerableReadOnly( obj, prop, value )\n    Defines a non-enumerable read-only property.\n\n    Non-enumerable read-only properties are non-configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    value: any\n        Value to set.\n\n    Examples\n    --------\n    > var obj = {};\n    > setNonEnumerableReadOnly( obj, 'foo', 'bar' );\n    > obj.foo = 'boop';\n    > obj\n    { 'foo': 'bar' }\n\n    See Also\n    --------\n    setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnly\n","setNonEnumerableReadOnlyAccessor":"\nsetNonEnumerableReadOnlyAccessor( obj, prop, getter )\n    Defines a non-enumerable read-only accessor.\n\n    Non-enumerable read-only accessors are non-configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    getter: Function\n        Get accessor.\n\n    Examples\n    --------\n    > var obj = {};\n    > function getter() { return 'bar'; };\n    > setNonEnumerableReadOnlyAccessor( obj, 'foo', getter );\n    > obj.foo\n    'bar'\n\n    See Also\n    --------\n    setNonEnumerableProperty, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setNonEnumerableWriteOnlyAccessor, setReadOnlyAccessor\n","setNonEnumerableReadWriteAccessor":"\nsetNonEnumerableReadWriteAccessor( obj, prop, getter, setter )\n    Defines a non-enumerable property having read-write accessors.\n\n    Non-enumerable read-write accessors are non-configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    getter: Function\n        Get accessor.\n\n    setter: Function\n        Set accessor.\n\n    Examples\n    --------\n    > var obj = {};\n    > var name = 'bar';\n    > function getter() { return name + ' foo'; };\n    > function setter( v ) { name = v; };\n    > setNonEnumerableReadWriteAccessor( obj, 'foo', getter, setter );\n    > obj.foo\n    'bar foo'\n    > obj.foo = 'beep';\n    > obj.foo\n    'beep foo'\n\n    See Also\n    --------\n    setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableWriteOnlyAccessor, setReadWriteAccessor\n","setNonEnumerableWriteOnlyAccessor":"\nsetNonEnumerableWriteOnlyAccessor( obj, prop, setter )\n    Defines a non-enumerable write-only accessor.\n\n    Non-enumerable write-only accessors are non-configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    setter: Function\n        Set accessor.\n\n    Examples\n    --------\n    > var obj = {};\n    > var val = '';\n    > function setter( v ) { val = v; };\n    > setNonEnumerableWriteOnlyAccessor( obj, 'foo', setter );\n    > obj.foo = 'bar';\n    > val\n    'bar'\n\n    See Also\n    --------\n    setNonEnumerableProperty, setNonEnumerableReadOnlyAccessor, setNonEnumerableReadOnly, setNonEnumerableReadWriteAccessor, setWriteOnlyAccessor\n","setReadOnly":"\nsetReadOnly( obj, prop, value )\n    Defines a read-only property.\n\n    Read-only properties are enumerable and non-configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    value: any\n        Value to set.\n\n    Examples\n    --------\n    > var obj = {};\n    > setReadOnly( obj, 'foo', 'bar' );\n    > obj.foo = 'boop';\n    > obj\n    { 'foo': 'bar' }\n\n    See Also\n    --------\n    setReadOnlyAccessor, setReadWriteAccessor, setWriteOnlyAccessor\n","setReadOnlyAccessor":"\nsetReadOnlyAccessor( obj, prop, getter )\n    Defines a read-only accessor.\n\n    Read-only accessors are enumerable and non-configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    getter: Function\n        Get accessor.\n\n    Examples\n    --------\n    > var obj = {};\n    > function getter() { return 'bar'; };\n    > setReadOnlyAccessor( obj, 'foo', getter );\n    > obj.foo\n    'bar'\n\n    See Also\n    --------\n    setReadOnly, setReadWriteAccessor, setWriteOnlyAccessor\n","setReadWriteAccessor":"\nsetReadWriteAccessor( obj, prop, getter, setter )\n    Defines a property having read-write accessors.\n\n    Read-write accessors are enumerable and non-configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    getter: Function\n        Get accessor.\n\n    setter: Function\n        Set accessor.\n\n    Examples\n    --------\n    > var obj = {};\n    > var name = 'bar';\n    > function getter() { return name + ' foo'; };\n    > function setter( v ) { name = v; };\n    > setReadWriteAccessor( obj, 'foo', getter, setter );\n    > obj.foo\n    'bar foo'\n    > obj.foo = 'beep';\n    > obj.foo\n    'beep foo'\n\n    See Also\n    --------\n    setReadOnly, setReadOnlyAccessor, setWriteOnlyAccessor\n","setWriteOnlyAccessor":"\nsetWriteOnlyAccessor( obj, prop, setter )\n    Defines a write-only accessor.\n\n    Write-only accessors are enumerable and non-configurable.\n\n    Parameters\n    ----------\n    obj: Object\n        Object on which to define the property.\n\n    prop: string|symbol\n        Property name.\n\n    setter: Function\n        Set accessor.\n\n    Examples\n    --------\n    > var obj = {};\n    > var val = '';\n    > function setter( v ) { val = v; };\n    > setWriteOnlyAccessor( obj, 'foo', setter );\n    > obj.foo = 'bar';\n    > val\n    'bar'\n\n    See Also\n    --------\n    setReadOnly, setReadOnlyAccessor, setReadWriteAccessor\n","SharedArrayBuffer":"\nSharedArrayBuffer( size )\n    Returns a shared array buffer having a specified number of bytes.\n\n    A shared array buffer behaves similarly to a non-shared array buffer, except\n    that a shared array buffer allows creating views of memory shared between\n    threads.\n\n    Buffer contents are initialized to 0.\n\n    If an environment does not support shared array buffers, the function throws\n    an error.\n\n    Parameters\n    ----------\n    size: integer\n        Number of bytes.\n\n    Returns\n    -------\n    out: SharedArrayBuffer\n        A shared array buffer.\n\n    Examples\n    --------\n    // Assuming an environment supports SharedArrayBuffers...\n    > var buf = new SharedArrayBuffer( 5 )\n    <SharedArrayBuffer>\n\n\nSharedArrayBuffer.length\n    Number of input arguments the constructor accepts.\n\n    Examples\n    --------\n    > SharedArrayBuffer.length\n    1\n\n\nSharedArrayBuffer.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the array buffer.\n\n    Examples\n    --------\n    // Assuming an environment supports SharedArrayBuffers...\n    > var buf = new SharedArrayBuffer( 5 );\n    > buf.byteLength\n    5\n\n\nSharedArrayBuffer.prototype.slice( [start[, end]] )\n    Copies the bytes of a shared array buffer to a new shared array buffer.\n\n    Parameters\n    ----------\n    start: integer (optional)\n        Index at which to start copying buffer contents (inclusive). If\n        negative, the index is relative to the end of the buffer.\n\n    end: integer (optional)\n        Index at which to stop copying buffer contents (exclusive). If negative,\n        the index is relative to the end of the buffer.\n\n    Returns\n    -------\n    out: SharedArrayBuffer\n        A new shared array buffer whose contents have been copied from the\n        calling shared array buffer.\n\n    Examples\n    --------\n    // Assuming an environment supports SharedArrayBuffers...\n    > var b1 = new SharedArrayBuffer( 10 );\n    > var b2 = b1.slice( 2, 6 );\n    > var bool = ( b1 === b2 )\n    false\n    > b2.byteLength\n    4\n\n    See Also\n    --------\n    Buffer, ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","SharedArrayBuffer.length":"\nSharedArrayBuffer.length\n    Number of input arguments the constructor accepts.\n\n    Examples\n    --------\n    > SharedArrayBuffer.length\n    1","SharedArrayBuffer.prototype.byteLength":"\nSharedArrayBuffer.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the array buffer.\n\n    Examples\n    --------\n    // Assuming an environment supports SharedArrayBuffers...\n    > var buf = new SharedArrayBuffer( 5 );\n    > buf.byteLength\n    5","SharedArrayBuffer.prototype.slice":"\nSharedArrayBuffer.prototype.slice( [start[, end]] )\n    Copies the bytes of a shared array buffer to a new shared array buffer.\n\n    Parameters\n    ----------\n    start: integer (optional)\n        Index at which to start copying buffer contents (inclusive). If\n        negative, the index is relative to the end of the buffer.\n\n    end: integer (optional)\n        Index at which to stop copying buffer contents (exclusive). If negative,\n        the index is relative to the end of the buffer.\n\n    Returns\n    -------\n    out: SharedArrayBuffer\n        A new shared array buffer whose contents have been copied from the\n        calling shared array buffer.\n\n    Examples\n    --------\n    // Assuming an environment supports SharedArrayBuffers...\n    > var b1 = new SharedArrayBuffer( 10 );\n    > var b2 = b1.slice( 2, 6 );\n    > var bool = ( b1 === b2 )\n    false\n    > b2.byteLength\n    4\n\n    See Also\n    --------\n    Buffer, ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array, Uint8ClampedArray","shift":"\nshift( collection )\n    Removes and returns the first element of a collection.\n\n    The function returns an array with two elements: the shortened collection\n    and the removed element.\n\n    If the input collection is a typed array whose length is greater than `0`,\n    the first return value does not equal the input reference.\n\n    For purposes of generality, always treat the output collection as distinct\n    from the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        A collection. If the collection is an `Object`, the value should be\n        array-like.\n\n    Returns\n    -------\n    out: Array\n        Updated collection and the removed item.\n\n    Examples\n    --------\n    // Arrays:\n    > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > var out = shift( arr )\n    [ [ 2.0, 3.0, 4.0, 5.0 ], 1.0 ]\n\n    // Typed arrays:\n    > arr = new Float64Array( [ 1.0, 2.0 ] );\n    > out = shift( arr )\n    [ <Float64Array>[ 2.0 ], 1.0 ]\n\n    // Array-like object:\n    > arr = { 'length': 2, '0': 1.0, '1': 2.0 };\n    > out = shift( arr )\n    [ { 'length': 1, '0': 2.0 }, 1.0 ]\n\n    See Also\n    --------\n    pop, push, unshift\n","shuffle":"\nshuffle( arr[, options] )\n    Shuffles elements of an array-like object.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Array-like object to shuffle.\n\n    options: Object (optional)\n        Options.\n\n    options.copy: string (optional)\n        String indicating whether to return a copy (`deep`,`shallow` or `none`).\n        Default: `'shallow'`.\n\n    Returns\n    -------\n    out: ArrayLike\n        Shuffled array-like object.\n\n    Examples\n    --------\n    > var data = [ 1, 2, 3 ];\n    > var out = shuffle( data )\n    e.g., [ 3, 1, 2 ]\n    > out = shuffle( data, { 'copy': 'none' } );\n    > var bool = ( data === out )\n    true\n\n\nshuffle.factory( [options] )\n    Returns a function to shuffle elements of array-like objects.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer (optional)\n        Integer-valued seed.\n\n    options.copy: string (optional)\n        String indicating whether to return a copy (`deep`,`shallow` or `none`).\n        Default: `'shallow'`.\n\n    Returns\n    -------\n    fcn: Function\n        Shuffle function.\n\n    Examples\n    --------\n    > var myshuffle = shuffle.factory();\n\n    // Set a seed:\n    > myshuffle = shuffle.factory({ 'seed': 239 });\n    > var arr = [ 0, 1, 2, 3, 4 ];\n    > var out = myshuffle( arr )\n    e.g., [ 3, 4, 1, 0, 2 ]\n\n    // Use a different copy strategy:\n    > myshuffle = shuffle.factory({ 'copy': 'none', 'seed': 867 });\n\n    // Created shuffle function mutates input array by default:\n    > arr = [ 1, 2, 3, 4, 5, 6 ];\n    > out = myshuffle( arr );\n    > var bool = ( arr === out )\n    true\n    // Default option can be overridden:\n    > arr = [ 1, 2, 3, 4 ];\n    > out = myshuffle( arr, { 'copy': 'shallow' } );\n    > bool = ( arr === out )\n    false\n\n    See Also\n    --------\n    sample\n","shuffle.factory":"\nshuffle.factory( [options] )\n    Returns a function to shuffle elements of array-like objects.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.seed: integer (optional)\n        Integer-valued seed.\n\n    options.copy: string (optional)\n        String indicating whether to return a copy (`deep`,`shallow` or `none`).\n        Default: `'shallow'`.\n\n    Returns\n    -------\n    fcn: Function\n        Shuffle function.\n\n    Examples\n    --------\n    > var myshuffle = shuffle.factory();\n\n    // Set a seed:\n    > myshuffle = shuffle.factory({ 'seed': 239 });\n    > var arr = [ 0, 1, 2, 3, 4 ];\n    > var out = myshuffle( arr )\n    e.g., [ 3, 4, 1, 0, 2 ]\n\n    // Use a different copy strategy:\n    > myshuffle = shuffle.factory({ 'copy': 'none', 'seed': 867 });\n\n    // Created shuffle function mutates input array by default:\n    > arr = [ 1, 2, 3, 4, 5, 6 ];\n    > out = myshuffle( arr );\n    > var bool = ( arr === out )\n    true\n    // Default option can be overridden:\n    > arr = [ 1, 2, 3, 4 ];\n    > out = myshuffle( arr, { 'copy': 'shallow' } );\n    > bool = ( arr === out )\n    false\n\n    See Also\n    --------\n    sample","sizeOf":"\nsizeOf( dtype )\n    Returns the size (in bytes) of the canonical binary representation of a\n    specified numeric type.\n\n    The following numeric types are supported:\n\n    - float64: double-precision floating-point numbers.\n    - float32: single-precision floating-point numbers.\n    - float16: half-precision floating-point numbers.\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n    - complex128: 128-bit complex numbers.\n    - complex64: 64-bit complex numbers.\n\n    Parameters\n    ----------\n    dtype: string\n        Numeric type.\n\n    Returns\n    -------\n    out: number\n        Size (in bytes).\n\n    Examples\n    --------\n    > var s = sizeOf( 'int8' )\n    1\n    > s = sizeOf( 'uint32' )\n    4\n\n    See Also\n    --------\n    realmax, typemax\n","Slice":"\nSlice( [stop] )\n    Returns a Slice.\n\n    Parameters\n    ----------\n    stop: integer|null|undefined (optional)\n        Ending index (exclusive).\n\n    Returns\n    -------\n    s: Slice\n        Slice instance.\n\n    Examples\n    --------\n    > var s = new Slice();\n    > s = new Slice( 10 );\n\n\nSlice( start, stop[, step] )\n    Returns a Slice.\n\n    Parameters\n    ----------\n    start: integer|null|undefined\n        Starting index (inclusive).\n\n    stop: integer|null|undefined\n        Ending index (exclusive).\n\n    step: integer|null|undefined (optional)\n        Index increment. A numeric index increment argument should be a non-zero\n        integer value. Default: null.\n\n    Returns\n    -------\n    s: Slice\n        Slice instance.\n\n    Examples\n    --------\n    > var s = new Slice( 2, 10 );\n    > s = new Slice( 2, 10, 1 );\n\n\nSlice.prototype.start\n    Read-only property returning the starting slice index.\n\n    Returns\n    -------\n    start: integer|null\n        Starting index.\n\n    Examples\n    --------\n    > var s = new Slice( 10 );\n    > s.start\n    null\n    > s = new Slice( 2, 10 );\n    > s.start\n    2\n\n\nSlice.prototype.stop\n    Read-only property returning the ending slice index.\n\n    Returns\n    -------\n    stop: integer|null\n        Ending index.\n\n    Examples\n    --------\n    > var s = new Slice( 10 );\n    > s.stop\n    10\n    > s = new Slice( 2, 10 );\n    > s.stop\n    10\n\n\nSlice.prototype.step\n    Read-only property returning the index increment.\n\n    Returns\n    -------\n    step: integer|null\n        Index increment.\n\n    Examples\n    --------\n    > var s = new Slice( 10 );\n    > s.step\n    null\n    > s = new Slice( 2, 10 );\n    > s.step\n    null\n    > s = new Slice( 2, 10, 1 );\n    > s.step\n    1\n\n\nSlice.prototype.toString()\n    Serializes a Slice as a string.\n\n    Returns\n    -------\n    str: string\n        Serialized Slice string.\n\n    Examples\n    --------\n    > var s = new Slice( 10 );\n    > s.toString()\n    'Slice(null,10,null)'\n    > s = new Slice( 2, 10, 1 );\n    > s.toString()\n    'Slice(2,10,1)'\n\n\nSlice.prototype.toJSON()\n    Serializes a Slice as a JSON object.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var s = new Slice( 10 );\n    > s.toJSON()\n    { 'type': 'Slice', 'data': [ null, 10, null ] }\n    > s = new Slice( 2, 10, 1 );\n    > s.toJSON()\n    { 'type': 'Slice', 'data': [ 2, 10, 1 ] }\n\n    See Also\n    --------\n    ndarray, MultiSlice\n","Slice.prototype.start":"\nSlice.prototype.start\n    Read-only property returning the starting slice index.\n\n    Returns\n    -------\n    start: integer|null\n        Starting index.\n\n    Examples\n    --------\n    > var s = new Slice( 10 );\n    > s.start\n    null\n    > s = new Slice( 2, 10 );\n    > s.start\n    2","Slice.prototype.stop":"\nSlice.prototype.stop\n    Read-only property returning the ending slice index.\n\n    Returns\n    -------\n    stop: integer|null\n        Ending index.\n\n    Examples\n    --------\n    > var s = new Slice( 10 );\n    > s.stop\n    10\n    > s = new Slice( 2, 10 );\n    > s.stop\n    10","Slice.prototype.step":"\nSlice.prototype.step\n    Read-only property returning the index increment.\n\n    Returns\n    -------\n    step: integer|null\n        Index increment.\n\n    Examples\n    --------\n    > var s = new Slice( 10 );\n    > s.step\n    null\n    > s = new Slice( 2, 10 );\n    > s.step\n    null\n    > s = new Slice( 2, 10, 1 );\n    > s.step\n    1","Slice.prototype.toString":"\nSlice.prototype.toString()\n    Serializes a Slice as a string.\n\n    Returns\n    -------\n    str: string\n        Serialized Slice string.\n\n    Examples\n    --------\n    > var s = new Slice( 10 );\n    > s.toString()\n    'Slice(null,10,null)'\n    > s = new Slice( 2, 10, 1 );\n    > s.toString()\n    'Slice(2,10,1)'","Slice.prototype.toJSON":"\nSlice.prototype.toJSON()\n    Serializes a Slice as a JSON object.\n\n    Returns\n    -------\n    obj: Object\n        JSON object.\n\n    Examples\n    --------\n    > var s = new Slice( 10 );\n    > s.toJSON()\n    { 'type': 'Slice', 'data': [ null, 10, null ] }\n    > s = new Slice( 2, 10, 1 );\n    > s.toJSON()\n    { 'type': 'Slice', 'data': [ 2, 10, 1 ] }\n\n    See Also\n    --------\n    ndarray, MultiSlice","snakecase":"\nsnakecase( str )\n    Converts a string to snake case.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Snake-cased string.\n\n    Examples\n    --------\n    > var out = snakecase( 'Hello World!' )\n    'hello_world'\n    > out = snakecase( 'I am a tiny little teapot' )\n    'i_am_a_tiny_little_teapot'\n\n    See Also\n    --------\n    camelcase, constantcase, kebabcase, pascalcase","some":"\nsome( collection, n )\n    Tests whether at least `n` elements in a collection are truthy.\n\n    The function immediately returns upon finding `n` truthy elements.\n\n    If provided an empty collection, the function returns `false`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    n: number\n        Minimum number of truthy elements.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if a collection contains at least `n` truthy\n        elements; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > var arr = [ 0, 0, 1, 2, 3 ];\n    > var bool = some( arr, 3 )\n    true\n\n    See Also\n    --------\n    any, every, forEach, none, someBy\n","someBy":"\nsomeBy( collection, n, predicate[, thisArg ] )\n    Tests whether a collection contains at least `n` elements which pass a test\n    implemented by a predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    The function immediately returns upon finding `n` successful elements.\n\n    If provided an empty collection, the function returns `false`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    n: number\n        Minimum number of successful elements.\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if a collection contains at least `n`\n        successful elements; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function negative( v ) { return ( v < 0 ); };\n    > var arr = [ 1, 2, -3, 4, -1 ];\n    > var bool = someBy( arr, 2, negative )\n    true\n\n    See Also\n    --------\n    anyBy, everyBy, forEach, noneBy, someByAsync, someByRight\n","someByAsync":"\nsomeByAsync( collection, n, [options,] predicate, done )\n    Tests whether a collection contains at least `n` elements which pass a test\n    implemented by a predicate function.\n\n    When invoked, the predicate function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If the\n    predicate function accepts two arguments, the predicate function is\n    provided:\n\n    - value\n    - next\n\n    If the predicate function accepts three arguments, the predicate function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other predicate function signature, the predicate function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - result: test result.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    The function immediately returns upon receiving `n` non-falsy `result`\n    values and calls the `done` callback with `null` as the first argument and\n    `true` as the second argument.\n\n    If all elements fail, the function calls the `done` callback with `null`\n    as the first argument and `false` as the second argument.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    n: number\n        Minimum number of successful elements.\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > someByAsync( arr, 2, predicate, done )\n    1000\n    2500\n    3000\n    false\n\n    // Limit number of concurrent invocations:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 3000, 2500, 1000 ];\n    > someByAsync( arr, 2, opts, predicate, done )\n    2500\n    3000\n    1000\n    false\n\n    // Process sequentially:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 3000, 2500, 1000 ];\n    > someByAsync( arr, 2, opts, predicate, done )\n    3000\n    2500\n    1000\n    false\n\n\nsomeByAsync.factory( [options,] predicate )\n    Returns a function which tests whether a collection contains at least `n`\n    elements which pass a test implemented by a predicate function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = someByAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, 2, done )\n    3000\n    2500\n    1000\n    false\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, 2, done )\n    2000\n    1500\n    1000\n    false\n\n    See Also\n    --------\n    anyByAsync, everyByAsync, forEachAsync, noneByAsync, someBy, someByRightAsync\n","someByAsync.factory":"\nsomeByAsync.factory( [options,] predicate )\n    Returns a function which tests whether a collection contains at least `n`\n    elements which pass a test implemented by a predicate function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = someByAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 3000, 2500, 1000 ];\n    > f( arr, 2, done )\n    3000\n    2500\n    1000\n    false\n    > arr = [ 2000, 1500, 1000 ];\n    > f( arr, 2, done )\n    2000\n    1500\n    1000\n    false\n\n    See Also\n    --------\n    anyByAsync, everyByAsync, forEachAsync, noneByAsync, someBy, someByRightAsync","someByRight":"\nsomeByRight( collection, n, predicate[, thisArg ] )\n    Tests whether a collection contains at least `n` elements which pass a test\n    implemented by a predicate function, iterating from right to left.\n\n    The predicate function is provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    The function immediately returns upon finding `n` successful elements.\n\n    If provided an empty collection, the function returns `false`.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    n: number\n        Minimum number of successful elements.\n\n    predicate: Function\n        The test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if a collection contains at least `n`\n        successful elements; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function negative( v ) { return ( v < 0 ); };\n    > var arr = [ -1, 1, -2, 3, 4 ];\n    > var bool = someByRight( arr, 2, negative )\n    true\n\n    See Also\n    --------\n    anyByRight, everyByRight, forEachRight, noneByRight, someBy, someByRightAsync\n","someByRightAsync":"\nsomeByRightAsync( collection, n, [options,] predicate, done )\n    Tests whether a collection contains at least `n` elements which pass a test\n    implemented by a predicate function, iterating from right to left.\n\n    When invoked, the predicate function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection value.\n\n    The actual number of provided arguments depends on function length. If the\n    predicate function accepts two arguments, the predicate function is\n    provided:\n\n    - value\n    - next\n\n    If the predicate function accepts three arguments, the predicate function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other predicate function signature, the predicate function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - result: test result.\n\n    If a provided function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    The function immediately returns upon receiving `n` non-falsy `result`\n    values and calls the `done` callback with `null` as the first argument and\n    `true` as the second argument.\n\n    If all elements fail, the function calls the `done` callback with `null`\n    as the first argument and `false` as the second argument.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    n: number\n        Minimum number of successful elements.\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > someByRightAsync( arr, 2, predicate, done )\n    1000\n    2500\n    3000\n    false\n\n    // Limit number of concurrent invocations:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 1000, 2500, 3000 ];\n    > someByRightAsync( arr, 2, opts, predicate, done )\n    2500\n    3000\n    1000\n    false\n\n    // Process sequentially:\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 1000, 2500, 3000 ];\n    > someByRightAsync( arr, 2, opts, predicate, done )\n    3000\n    2500\n    1000\n    false\n\n\nsomeByRightAsync.factory( [options,] predicate )\n    Returns a function which tests whether a collection contains at least `n`\n    elements which pass a test implemented by a predicate function, iterating\n    from right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = someByRightAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, 2, done )\n    3000\n    2500\n    1000\n    false\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, 2, done )\n    2000\n    1500\n    1000\n    false\n\n    See Also\n    --------\n    anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByAsync, someByRight\n","someByRightAsync.factory":"\nsomeByRightAsync.factory( [options,] predicate )\n    Returns a function which tests whether a collection contains at least `n`\n    elements which pass a test implemented by a predicate function, iterating\n    from right to left.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    predicate: Function\n        The test function to invoke for each element in a collection.\n\n    Returns\n    -------\n    out: Function\n        A function which tests each element in a collection.\n\n    Examples\n    --------\n    > function predicate( value, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, false );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = someByRightAsync.factory( opts, predicate );\n    > function done( error, bool ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( bool );\n    ... };\n    > var arr = [ 1000, 2500, 3000 ];\n    > f( arr, 2, done )\n    3000\n    2500\n    1000\n    false\n    > arr = [ 1000, 1500, 2000 ];\n    > f( arr, 2, done )\n    2000\n    1500\n    1000\n    false\n\n    See Also\n    --------\n    anyByRightAsync, everyByRightAsync, forEachRightAsync, noneByRightAsync, someByAsync, someByRight","someInBy":"\nsomeInBy( obj, n, predicate[, thisArg ] )\n    Tests whether an object contains at least `n` properties\n    (own and inherited) which pass a test\n    implemented by a predicate function.\n\n    The predicate function is provided three arguments:\n\n    - value: object value.\n    - key: object key.\n    - obj: the input object.\n\n    The function immediately returns upon finding `n` successful properties.\n\n    If provided an empty object, the function returns `false`.\n\n    Parameters\n    ----------\n    obj: Object\n        Input object over which to iterate.\n\n    n: number\n        Minimum number of successful properties.\n\n    predicate: Function\n        Test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if an object contains at least `n`\n        successful properties; otherwise, the function returns `false`.\n\n    Examples\n    --------\n    > function negative( v ) { return ( v < 0 ); };\n    > var obj = { 'a': 1, 'b': 2, 'c': -3, 'd': 4, 'e': -1 };\n    > var bool = someInBy( obj, 2, negative )\n    true\n\n    See Also\n    --------\n    anyInBy, everyInBy, someBy, someOwnBy","someOwnBy":"\nsomeOwnBy( obj, n, predicate[, thisArg ] )\n    Tests whether some `own` properties of a provided object\n    satisfy a predicate function for at least `n` properties.\n\n    The predicate function is provided three arguments:\n\n    - value: object value.\n    - key: object key.\n    - obj: the input object.\n\n    The function immediately returns upon finding `n` successful properties.\n\n    If provided an empty object, the function returns `false`.\n\n    Parameters\n    ----------\n    obj: Object\n        Input object over which to iterate.\n\n    n: number\n        Minimum number of successful properties.\n\n    predicate: Function\n        Test function.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    bool: boolean\n        The function returns `true` if an object's own properties satisfy a\n        predicate for at least `n` properties; otherwise, the function\n        returns `false`.\n\n    Examples\n    --------\n    > function negative( v ) { return ( v < 0 ); };\n    > var obj = { a: 1, b: 2, c: -3, d: 4, e: -1 };\n    > var bool = someOwnBy( obj, 2, negative )\n    true\n\n    See Also\n    --------\n    anyOwnBy, everyOwnBy, someBy, someInBy","SOTU":"\nSOTU( [options] )\n    Returns State of the Union (SOTU) addresses.\n\n    Each State of the Union address is represented by an object with the\n    following fields:\n\n    - year: speech year.\n    - name: President name.\n    - party: the President's political party.\n    - text: speech text.\n\n    The following political parties are recognized:\n\n    - Democratic\n    - Republican\n    - Democratic-Republican\n    - Federalist\n    - National Union\n    - Whig\n    - Whig & Democratic\n    - none\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.name: String|Array<string> (optional)\n        President name(s).\n\n    options.party: String|Array<string> (optional)\n        Political party (or parties).\n\n    options.year: integer|Array<integer> (optional)\n        Year(s).\n\n    options.range: Array<integer> (optional)\n        Two-element array specifying a year range.\n\n    Returns\n    -------\n    out: Array<Object>\n        State of the Union addresses.\n\n    Examples\n    --------\n    > var out = SOTU()\n    [ {...}, {...}, ... ]\n\n    // Retrieve addresses by one or more Presidents...\n    > var opts = { 'name': 'Barack Obama' };\n    > out = SOTU( opts )\n    [ {...}, {...}, ... ]\n\n    // Retrieve addresses by one or more political parties...\n    > opts = { 'party': [ 'Democratic', 'Federalist' ] };\n    > out = SOTU( opts )\n    [ {...}, {...}, ... ]\n\n    // Retrieve addresses from one or more years...\n    > opts = { 'year': [ 2008, 2009, 2011 ] };\n    > out = SOTU( opts )\n    [ {...}, {...}, {...} ]\n\n    // Retrieve addresses from a range of consecutive years...\n    > opts = { 'range': [ 2008, 2016 ] }\n    > out = SOTU( opts )\n    [ {...}, {...}, ... ]\n\n","SPACHE_REVISED":"\nSPACHE_REVISED()\n    Returns a list of simple American-English words (revised Spache).\n\n    Returns\n    -------\n    out: Array<string>\n        List of simple American-English words.\n\n    Examples\n    --------\n    > var list = SPACHE_REVISED()\n    [ 'a', 'able', 'about', 'above', ... ]\n\n    References\n    ----------\n    - Spache, George. 1953. \"A New Readability Formula for Primary-Grade Reading\n    Materials.\" *The Elementary School Journal* 53 (7): 410–13. doi:10.1086/\n    458513.\n    - Klare, George R. 1974. \"Assessing Readability.\" *Reading Research\n    Quarterly* 10 (1). Wiley, International Reading Association: 62–102.\n    <http://www.jstor.org/stable/747086>.\n    - Stone, Clarence R. 1956. \"Measuring Difficulty of Primary Reading\n    Material: A Constructive Criticism of Spache's Measure.\" *The Elementary\n    School Journal* 57 (1). University of Chicago Press: 36–41.\n    <http://www.jstor.org/stable/999700>.\n    - Perera, Katherine. 2012. \"The assessment of linguistic difficulty in\n    reading material.\" In *Linguistics and the Teacher*, edited by Ronald\n    Carter, 101–13. Routledge Library Editions: Education. Taylor & Francis.\n    <https://books.google.com/books?id=oNXFQ9Gn6XIC>.\n\n","SPAM_ASSASSIN":"\nSPAM_ASSASSIN()\n    Returns the Spam Assassin public mail corpus.\n\n    Each array element has the following fields:\n\n    - id: message id (relative to message group).\n    - group: message group.\n    - checksum: object containing checksum info.\n    - text: message text (including headers).\n\n    The message group may be one of the following:\n\n    - easy-ham-1: easier to detect non-spam e-mails (2500 messages).\n    - easy-ham-2: easier to detect non-spam e-mails collected at a later date\n      (1400 messages).\n    - hard-ham-1: harder to detect non-spam e-mails (250 messages).\n    - spam-1: spam e-mails (500 messages).\n    - spam-2: spam e-mails collected at a later date (1396 messages).\n\n    The checksum object contains the following fields:\n\n    - type: checksum type (e.g., MD5).\n    - value: checksum value.\n\n    Returns\n    -------\n    out: Array<Object>\n        Corpus.\n\n    Examples\n    --------\n    > var data = SPAM_ASSASSIN()\n    [ {...}, {...}, ... ]\n\n","SparklineBase":"\nSparklineBase( [data,] [options] )\n    Returns a Sparkline instance.\n\n    This constructor is a base Sparkline constructor from which constructors\n    tailored to generating particular types of Sparkline graphics should be\n    derived.\n\n    At a minimum, descendants should implement a private `_render()` method\n    which will be automatically invoked by the public `render()` method.\n\n    The `data` argument takes precedence over the `data` option.\n\n    Parameters\n    ----------\n    data: ArrayLike|ndarray (optional)\n        Sparkline data.\n\n    options: Object (optional)\n        Options.\n\n    options.autoRender: boolean (optional)\n        Boolean indicating whether to re-render on a 'change' event. Default:\n        false.\n\n    options.bufferSize: integer|null (optional)\n        Data buffer size. If provided, data is kept in a first-in first-out\n        (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n    options.data: ArrayLike|ndarray (optional)\n        Sparkline data.\n\n    options.description: string (optional)\n        Sparkline description.\n\n    options.isDefined: Function (optional)\n        An accessor function indicating whether a datum is defined.\n\n    options.label: string (optional)\n        Data label.\n\n    Returns\n    -------\n    sparkline: Sparkline\n        Sparkline instance.\n\n    sparkline.autoRender\n        Rendering mode. If `true`, an instance renders on each 'change' event;\n        otherwise, rendering must be triggered manually.\n\n    sparkline.bufferSize\n        Data buffer size.\n\n    sparkline.description\n        Sparkline description.\n\n    sparkline.data\n        Sparkline data.\n\n    sparkline.label\n        Data label.\n\n    sparkline.isDefined( d, i )\n        An accessor function which defines whether a datum is defined. This\n        accessor is used to define how missing values are encoded. The default\n        behavior is to ignore values which are `NaN`.\n\n    sparkline.render()\n        Renders a sparkline. This method calls `_render()` which must be\n        implemented by instances and child classes. The default behavior is\n        throw an error.\n\n    Examples\n    --------\n    > var sparkline = new SparklineBase()\n    <Sparkline>\n\n    // Provide sparkline data at instantiation:\n    > var data = [ 1, 2, 3 ];\n    > sparkline = new SparklineBase( data )\n    <Sparkline>\n\n    See Also\n    --------\n    plot, Plot, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeWinLossChartSparkline\n","sparsearray2iterator":"\nsparsearray2iterator( src[, mapFcn[, thisArg]] )\n    Returns an iterator which iterates over the elements of a sparse array-like\n    object.\n\n    The returned iterator skips elements which are undefined.\n\n    When invoked, an input function is provided three arguments:\n\n    - value: iterated value.\n    - index: iterated value index.\n    - src: source array-like object.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an array's `@@iterator` method, regardless of whether this method is\n    defined. To convert an array to an implementation defined iterator, invoke\n    this method directly.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Sparse array-like object from which to create the iterator.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = sparsearray2iterator( [ 1, , 3, 4 ] );\n    > var v = it.next().value\n    1\n    > v = it.next().value\n    3\n\n    See Also\n    --------\n    iterator2array, array2iterator, sparsearray2iteratorRight\n","sparsearray2iteratorRight":"\nsparsearray2iteratorRight( src[, mapFcn[, thisArg]] )\n    Returns an iterator which iterates from right to left over the elements of a\n    sparse array-like object.\n\n    The returned iterator skips elements which are undefined.\n\n    When invoked, an input function is provided three arguments:\n\n    - value: iterated value.\n    - index: iterated value index.\n    - src: source array-like object.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an array's `@@iterator` method, regardless of whether this method is\n    defined. To convert an array to an implementation defined iterator, invoke\n    this method directly.\n\n    Parameters\n    ----------\n    src: ArrayLikeObject\n        Sparse array-like object from which to create the iterator.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = sparsearray2iteratorRight( [ 1, 2, , 4 ] );\n    > var v = it.next().value\n    4\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    iterator2array, array2iteratorRight, sparsearray2iterator\n","splitStream":"\nsplitStream( [options] )\n    Returns a transform stream which splits streamed data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Separator used to split streamed data. A separator may be either a\n        regular expression or a string. A separator which is a regular\n        expression containing a matching group will result in the separator\n        being retained in the output stream.Default: /\\r?\\n/.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.writableObjectMode: boolean (optional)\n        Specifies whether the writable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream.\n\n    Examples\n    --------\n    > var s = splitStream();\n    > s.write( 'a\\nb\\nc' );\n    > s.end();\n\n\nsplitStream.factory( [options] )\n    Returns a function for creating transform streams for splitting streamed\n    data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Separator used to split streamed data. A separator may be either a\n        regular expression or a string. A separator which is a regular\n        expression containing a matching group will result in the separator\n        being retained in the output stream. Default: /\\r?\\n/.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.writableObjectMode: boolean (optional)\n        Specifies whether the writable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    createStream: Function\n        Function for creating transform streams.\n\n    Examples\n    --------\n    > var opts = { 'highWaterMark': 64 };\n    > var createStream = splitStream.factory( opts );\n    > var s = createStream();\n    > s.write( 'a\\nb\\nc' );\n    > s.end();\n\n\nsplitStream.objectMode( [options] )\n    Returns an \"objectMode\" transform stream for splitting streamed data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Separator used to split streamed data. A separator may be either a\n        regular expression or a string. A separator which is a regular\n        expression containing a matching group will result in the separator\n        being retained in the output stream. Default: /\\r?\\n/.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.writableObjectMode: boolean (optional)\n        Specifies whether the writable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > var s = splitStream.objectMode();\n    > s.write( 'a\\nb\\c' );\n    > s.end();\n\n    See Also\n    --------\n    joinStream\n","splitStream.factory":"\nsplitStream.factory( [options] )\n    Returns a function for creating transform streams for splitting streamed\n    data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Separator used to split streamed data. A separator may be either a\n        regular expression or a string. A separator which is a regular\n        expression containing a matching group will result in the separator\n        being retained in the output stream. Default: /\\r?\\n/.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.writableObjectMode: boolean (optional)\n        Specifies whether the writable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    createStream: Function\n        Function for creating transform streams.\n\n    Examples\n    --------\n    > var opts = { 'highWaterMark': 64 };\n    > var createStream = splitStream.factory( opts );\n    > var s = createStream();\n    > s.write( 'a\\nb\\nc' );\n    > s.end();","splitStream.objectMode":"\nsplitStream.objectMode( [options] )\n    Returns an \"objectMode\" transform stream for splitting streamed data.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.sep: string (optional)\n        Separator used to split streamed data. A separator may be either a\n        regular expression or a string. A separator which is a regular\n        expression containing a matching group will result in the separator\n        being retained in the output stream. Default: /\\r?\\n/.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.writableObjectMode: boolean (optional)\n        Specifies whether the writable side should be in \"objectMode\". Default:\n        false.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > var s = splitStream.objectMode();\n    > s.write( 'a\\nb\\c' );\n    > s.end();\n\n    See Also\n    --------\n    joinStream","SQRT_EPS":"\nSQRT_EPS\n    Square root of double-precision floating-point epsilon.\n\n    Examples\n    --------\n    > SQRT_EPS\n    0.14901161193847656e-7\n\n    See Also\n    --------\n    EPS\n","SQRT_HALF":"\nSQRT_HALF\n    Square root of `1/2`.\n\n    Examples\n    --------\n    > SQRT_HALF\n    0.7071067811865476\n\n    See Also\n    --------\n    LN_HALF\n","SQRT_HALF_PI":"\nSQRT_HALF_PI\n    Square root of the mathematical constant `π` divided by `2`.\n\n    Examples\n    --------\n    > SQRT_HALF_PI\n    1.2533141373155003\n\n    See Also\n    --------\n    PI\n","SQRT_PHI":"\nSQRT_PHI\n    Square root of the golden ratio.\n\n    Examples\n    --------\n    > SQRT_PHI\n    1.272019649514069\n\n    See Also\n    --------\n    PHI\n","SQRT_PI":"\nSQRT_PI\n    Square root of the mathematical constant `π`.\n\n    Examples\n    --------\n    > SQRT_PI\n    1.7724538509055160\n\n    See Also\n    --------\n    PI\n","SQRT_THREE":"\nSQRT_THREE\n    Square root of `3`.\n\n    Examples\n    --------\n    > SQRT_THREE\n    1.7320508075688772\n\n","SQRT_TWO":"\nSQRT_TWO\n    Square root of `2`.\n\n    Examples\n    --------\n    > SQRT_TWO\n    1.4142135623730951\n\n    See Also\n    --------\n    LN2\n","SQRT_TWO_PI":"\nSQRT_TWO_PI\n    Square root of the mathematical constant `π` times `2`.\n\n    Examples\n    --------\n    > SQRT_TWO_PI\n    2.5066282746310007\n\n    See Also\n    --------\n    TWO_PI\n","SSA_US_BIRTHS_2000_2014":"\nSSA_US_BIRTHS_2000_2014()\n    Returns US birth data from 2000 to 2014, as provided by the Social Security\n    Administration.\n\n    Returns\n    -------\n    out: Array<Object>\n        Birth data.\n\n    Examples\n    --------\n    > var data = SSA_US_BIRTHS_2000_2014()\n    [ {...}, ... ]\n\n    See Also\n    --------\n    CDC_NCHS_US_BIRTHS_1969_1988, CDC_NCHS_US_BIRTHS_1994_2003\n","sswap":"\nsswap( x, y[, dim] )\n    Interchanges two single-precision floating-point vectors.\n\n    For multi-dimensional input arrays, the function performs batched\n    computation, such that the function interchanges each pair of vectors in `x`\n    and `y` according to the specified dimension index.\n\n    Both input arrays must have the same shape.\n\n    Parameters\n    ----------\n    x: ndarray\n        First input array. Must have a 'float32' data type. Must have at least\n        one dimension and must have the same shape as the second input array.\n\n    y: ndarray\n        Second input array. Must have a 'float32' data type. Must have at least\n        one dimension and must have the same shape as the first input array.\n\n    dim: integer (optional)\n        Dimension index along which to interchange vectors. Must be a negative\n        integer. Negative indices are resolved relative to the last array\n        dimension, with the last dimension corresponding to `-1`. Default: -1.\n\n    Returns\n    -------\n    y: ndarray\n        The second input array `y`.\n\n    Examples\n    --------\n    > var x = array( new Float32Array( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] ) );\n    > var y = array( new Float32Array( [ 2.0, 6.0, -1.0, -4.0, 8.0 ] ) );\n    > sswap( x, y );\n    > x.data\n    <Float32Array>[ 2.0, 6.0, -1.0, -4.0, 8.0 ]\n    > y.data\n    <Float32Array>[ 4.0, 2.0, -3.0, 5.0, -1.0 ]\n\n    See Also\n    --------\n    base.strided.sswap, dswap, gswap\n","Stack":"\nStack()\n    Stack constructor.\n\n    A stack is also referred to as a \"last-in-first-out\" queue.\n\n    Returns\n    -------\n    stack: Object\n        Stack data structure.\n\n    stack.clear: Function\n        Clears the stack.\n\n    stack.first: Function\n        Returns the \"newest\" stack value (i.e., the value which is \"first-out\").\n        If the stack is empty, the returned value is `undefined`.\n\n    stack.iterator: Function\n        Returns an iterator for iterating over a stack. If an environment\n        supports Symbol.iterator, the returned iterator is iterable. Note that,\n        in order to prevent confusion arising from stack mutation during\n        iteration, a returned iterator **always** iterates over a stack\n        \"snapshot\", which is defined as the list of stack elements at the time\n        of the method's invocation.\n\n    stack.last: Function\n        Returns the \"oldest\" stack value (i.e., the value which is \"last-out\").\n        If the stack is empty, the returned value is `undefined`.\n\n    stack.length: integer\n        Stack length.\n\n    stack.pop: Function\n        Removes and returns the current \"first-out\" value from the stack. If the\n        stack is empty, the returned value is `undefined`.\n\n    stack.push: Function\n        Adds a value to the stack.\n\n    stack.toArray: Function\n        Returns an array of stack values.\n\n    stack.toJSON: Function\n        Serializes a stack as JSON.\n\n    Examples\n    --------\n    > var s = Stack();\n    > s.push( 'foo' ).push( 'bar' );\n    > s.length\n    2\n    > s.pop()\n    'bar'\n    > s.length\n    1\n    > s.pop()\n    'foo'\n    > s.length\n    0\n\n    See Also\n    --------\n    FIFO\n","standalone2pkg":"\nstandalone2pkg( pkg )\n    Returns the internal package name associated with a provided standalone\n    package name.\n\n    Parameters\n    ----------\n    pkg: string\n        Standalone package name.\n\n    Returns\n    -------\n    out: string|null\n        Internal package name.\n\n    Examples\n    --------\n    > var v = standalone2pkg( '@stdlib/math-base-special-sin' )\n    '@stdlib/math/base/special/sin'\n\n    See Also\n    --------\n    alias2standalone, pkg2alias, pkg2standalone\n","STANDARD_CARD_DECK":"\nSTANDARD_CARD_DECK()\n    Returns a string array containing two or three letter abbreviations for each\n    card in a standard 52-card deck.\n\n    Abbreviation format: <card><suit>\n\n    Cards: A, 2, 3, 4, 5, 6, 7, 8, 9, 10, J, Q, K, where\n\n    - A: ace\n    - J: jack\n    - Q: queen\n    - K: king\n\n    Suit abbreviations:\n\n    - C: clubs\n    - D: diamonds\n    - H: hearts\n    - S: spades\n\n    Returns\n    -------\n    out: Array<string>\n        List of cards.\n\n    Examples\n    --------\n    > var list = STANDARD_CARD_DECK()\n    [ 'AC', '2C', '3C', ... ]\n\n","startcase":"\nstartcase( str )\n    Capitalizes the first letter of each word in an input string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        String containing words where each first letter is capitalized.\n\n    Examples\n    --------\n    > var out = startcase( 'beep boop' )\n    'Beep Boop'\n\n    See Also\n    --------\n    lowercase, uppercase\n","startsWith":"\nstartsWith( str, search[, position] )\n    Tests if a string starts with the characters of another string.\n\n    If provided an empty search string, the function always returns `true`.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search string.\n\n    position: integer (optional)\n        Position at which to start searching for `search`. If less than `0`, the\n        start position is determined relative to the end of the input string.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether a string starts with the characters of\n        another string.\n\n    Examples\n    --------\n    > var bool = startsWith( 'Beep', 'Be' )\n    true\n    > bool = startsWith( 'Beep', 'ep' )\n    false\n    > bool = startsWith( 'Beep', 'ee', 1 )\n    true\n    > bool = startsWith( 'Beep', 'ee', -3 )\n    true\n    > bool = startsWith( 'Beep', '' )\n    true\n\n    See Also\n    --------\n    endsWith\n","STOPWORDS_EN":"\nSTOPWORDS_EN()\n    Returns a list of English stop words.\n\n    Returns\n    -------\n    out: Array<string>\n        List of stop words.\n\n    Examples\n    --------\n    > var list = STOPWORDS_EN()\n    [ 'a', 'about', 'above', 'across', ... ]\n\n","strided.abs":"\nstrided.abs( N, dtypeX, x, strideX, dtypeY, y, strideY )\n    Computes the absolute value for each element in a strided array `x` and\n    assigns the results to elements in a strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs( x.length, 'float64', x, 1, 'float64', y, 1 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs( 2, x, 2, y, -1 )\n    <Float64Array>[ 3.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.abs( 2, 'float64', x1, -2, 'float64', y1, 1 )\n    <Float64Array>[ 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nstrided.abs.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the absolute value for each element in a strided array `x` and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    strided.abs2, base.strided.dabs, base.strided.sabs\n","strided.abs.ndarray":"\nstrided.abs.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the absolute value for each element in a strided array `x` and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    strided.abs2, base.strided.dabs, base.strided.sabs","strided.abs2":"\nstrided.abs2( N, dtypeX, x, strideX, dtypeY, y, strideY )\n    Computes the squared absolute value for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs2( x.length, 'float64', x, 1, 'float64', y, 1 )\n    <Float64Array>[ 4.0, 1.0, 9.0, 25.0 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs2( 2, 'float64', x, 2, 'float64', y, -1 )\n    <Float64Array>[ 9.0, 4.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.abs2( 2, 'float64', x1, -2, 'float64', y1, 1 )\n    <Float64Array>[ 25.0, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 25.0, 1.0 ]\n\n\nstrided.abs2.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the squared absolute value for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs2.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 4.0, 1.0, 9.0, 25.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs2.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 25.0, 1.0 ]\n\n    See Also\n    --------\n    strided.abs, base.strided.dabs2, base.strided.sabs2\n","strided.abs2.ndarray":"\nstrided.abs2.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the squared absolute value for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs2.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 4.0, 1.0, 9.0, 25.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.abs2.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 25.0, 1.0 ]\n\n    See Also\n    --------\n    strided.abs, base.strided.dabs2, base.strided.sabs2","strided.abs2By":"\nstrided.abs2By( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the squared absolute value of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -1.0, -2.0, -3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.abs2By( x.length, x, 1, y, 1, clbk )\n    [ 1.0, 4.0, 9.0, 16.0 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.abs2By( 2, x, 2, y, -1, clbk )\n    [ 9.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.abs2By( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ 16.0, 4.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 16.0, 4.0 ]\n\n\nstrided.abs2By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the squared absolute value of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -1.0, -2.0, -3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.abs2By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 1.0, 4.0, 9.0, 16.0 ]\n\n    // Advanced indexing:\n    > x = [ -1.0, -2.0, -3.0, -4.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.abs2By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, 16.0, 4.0 ]\n\n    See Also\n    --------\n    strided.absBy, strided.abs2\n","strided.abs2By.ndarray":"\nstrided.abs2By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the squared absolute value of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -1.0, -2.0, -3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.abs2By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 1.0, 4.0, 9.0, 16.0 ]\n\n    // Advanced indexing:\n    > x = [ -1.0, -2.0, -3.0, -4.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.abs2By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, 16.0, 4.0 ]\n\n    See Also\n    --------\n    strided.absBy, strided.abs2","strided.absBy":"\nstrided.absBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the absolute value of each element retrieved from a strided input\n    array `x` via a callback function and assigns each result to an element in a\n    strided output array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v * 2.0; };\n    > strided.absBy( x.length, x, 1, y, 1, clbk )\n    [ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.absBy( 2, x, 2, y, -1, clbk )\n    [ 6.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.absBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ 8.0, 4.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 8.0, 4.0 ]\n\n\nstrided.absBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the absolute value of each element retrieved from a strided input\n    array `x` via a callback function and assigns each result to an element in a\n    strided output array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v * 2.0; };\n    > strided.absBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.absBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, 8.0, 4.0 ]\n\n    See Also\n    --------\n    strided.abs, strided.abs2By\n","strided.absBy.ndarray":"\nstrided.absBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the absolute value of each element retrieved from a strided input\n    array `x` via a callback function and assigns each result to an element in a\n    strided output array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v * 2.0; };\n    > strided.absBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 2.0, 4.0, 6.0, 8.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, -2.0, 3.0, -4.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.absBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, 8.0, 4.0 ]\n\n    See Also\n    --------\n    strided.abs, strided.abs2By","strided.acosBy":"\nstrided.acosBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the arccosine of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 0.707, 0.866, -0.707 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acosBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, ~0.786, ~0.524, ~2.356 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acosBy( 2, x, 2, y, -1, clbk )\n    [ ~0.524, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 0.707, 0.866, -0.707 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.acosBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~2.356, ~0.786 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~2.356, ~0.786 ]\n\n\nstrided.acosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the arccosine of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 0.707, 0.866, -0.707 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~0.786, ~0.524, ~2.356 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 0.707, 0.866, -0.707 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~2.356, ~0.786 ]\n\n","strided.acosBy.ndarray":"\nstrided.acosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the arccosine of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 0.707, 0.866, -0.707 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~0.786, ~0.524, ~2.356 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 0.707, 0.866, -0.707 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~2.356, ~0.786 ]","strided.acoshBy":"\nstrided.acoshBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the hyperbolic arccosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 1.5, 2.0, 2.5 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acoshBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, ~0.962, ~1.317, ~1.567 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acoshBy( 2, x, 2, y, -1, clbk )\n    [ ~1.317, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 1.5, 2.0, 2.5 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.acoshBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~1.567, ~0.962 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~1.567, ~0.962 ]\n\n\nstrided.acoshBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the hyperbolic arccosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 1.5, 2.0, 2.5 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acoshBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~0.962, ~1.317, ~1.567 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 1.5, 2.0, 2.5 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acoshBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~1.567, ~0.962 ]\n\n","strided.acoshBy.ndarray":"\nstrided.acoshBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the hyperbolic arccosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 1.5, 2.0, 2.5 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acoshBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~0.962, ~1.317, ~1.567 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 1.5, 2.0, 2.5 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acoshBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~1.567, ~0.962 ]","strided.acotBy":"\nstrided.acotBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the inverse cotangent of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -2.5, -1.5, -0.5, 0.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acotBy( x.length, x, 1, y, 1, clbk )\n    [ ~-0.381, ~-0.588, ~-1.107, ~1.571 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acotBy( 2, x, 2, y, -1, clbk )\n    [ ~-1.107, ~-0.381, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -2.5, -1.5, -0.5, 0.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.acotBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~1.571, ~-0.588 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~1.571, ~-0.588 ]\n\n\nstrided.acotBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse cotangent of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -2.5, -1.5, -0.5, 0.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acotBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ ~-0.381, ~-0.588, ~-1.107, ~1.571 ]\n\n    // Advanced indexing:\n    > x = [ -2.5, -1.5, -0.5, 0.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acotBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~1.571, ~-0.588 ]\n\n","strided.acotBy.ndarray":"\nstrided.acotBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse cotangent of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -2.5, -1.5, -0.5, 0.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acotBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ ~-0.381, ~-0.588, ~-1.107, ~1.571 ]\n\n    // Advanced indexing:\n    > x = [ -2.5, -1.5, -0.5, 0.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acotBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~1.571, ~-0.588 ]","strided.acothBy":"\nstrided.acothBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the inverse hyperbolic cotangent of each element retrieved from an\n    input strided array `x` via a callback function and assigns each result to\n    an element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -5.0, -4.0, -3.0, -1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acothBy( x.length, x, 1, y, 1, clbk )\n    [ ~-0.203, ~-0.255, ~-0.347, -Infinity ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acothBy( 2, x, 2, y, -1, clbk )\n    [ ~-0.347, ~-0.203, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -5.0, -4.0, -3.0, -1.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.acothBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ -Infinity, ~-0.255 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, -Infinity, ~-0.255 ]\n\n\nstrided.acothBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse hyperbolic cotangent of each element retrieved from an\n    input strided array `x` via a callback function and assigns each result to\n    an element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -5.0, -4.0, -3.0, -1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acothBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ ~-0.203, ~-0.255, ~-0.347, -Infinity ]\n\n    // Advanced indexing:\n    > x = [ -5.0, -4.0, -3.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acothBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, -Infinity, ~-0.255 ]\n\n","strided.acothBy.ndarray":"\nstrided.acothBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse hyperbolic cotangent of each element retrieved from an\n    input strided array `x` via a callback function and assigns each result to\n    an element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ -5.0, -4.0, -3.0, -1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acothBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ ~-0.203, ~-0.255, ~-0.347, -Infinity ]\n\n    // Advanced indexing:\n    > x = [ -5.0, -4.0, -3.0, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acothBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, -Infinity, ~-0.255 ]","strided.acovercosBy":"\nstrided.acovercosBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the inverse coversed cosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acovercosBy( x.length, x, 1, y, 1, clbk )\n    [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acovercosBy( 2, x, 2, y, -1, clbk )\n    [ ~0.524, ~1.571, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, -1.57, -0.5, -1.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.acovercosBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ 0.0, ~-0.607 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, ~-0.607 ]\n\n\nstrided.acovercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse coversed cosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acovercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -1.57, -0.5, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acovercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, 0.0, ~-0.607 ]\n\n","strided.acovercosBy.ndarray":"\nstrided.acovercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse coversed cosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acovercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -1.57, -0.5, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acovercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, 0.0, ~-0.607 ]","strided.acoversinBy":"\nstrided.acoversinBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the inverse coversed sine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acoversinBy( x.length, x, 1, y, 1, clbk )\n    [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acoversinBy( 2, x, 2, y, -1, clbk )\n    [ ~0.524, ~1.571, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.acoversinBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ 0.0, ~-0.607 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.0, ~-0.607 ]\n\n\nstrided.acoversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse coversed sine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acoversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.57, 0.5, 1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acoversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, 0.0, ~-0.607 ]\n\n","strided.acoversinBy.ndarray":"\nstrided.acoversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse coversed sine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.acoversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ ~1.571, ~-0.607, ~0.524, 0.0 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.57, 0.5, 1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.acoversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, 0.0, ~-0.607 ]","strided.add":"\nstrided.add( N, dx, x, sx, dy, y, sy, dz, z, sz )\n    Adds each element in a strided array `x` to a corresponding element in a\n    strided array `y` and assigns the results to elements in a strided array\n    `z`.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dx: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    dy: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    dz: any\n        Data type for `z`.\n\n    z: ArrayLikeObject\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    Returns\n    -------\n    z: ArrayLikeObject\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var dt = 'float64';\n    > strided.add( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\n    <Float64Array>[ -1.0, 3.0, 6.0, -1.0 ]\n\n    // Using `N` and stride parameters:\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.add( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\n    <Float64Array>[ 1.0, 4.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > strided.add( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\n    <Float64Array>[ -2.0, 5.0 ]\n    > z0\n    <Float64Array>[ 0.0, 0.0, -2.0, 5.0 ]\n\n\nstrided.add.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n    Adds each element in a strided array `x` to a corresponding element in a\n    strided array `y` and assigns the results to elements in a strided array\n    `z` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dx: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    dy: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    dz: any\n        Data type for `z`.\n\n    z: ArrayLikeObject\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    Returns\n    -------\n    z: ArrayLikeObject\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var dt = 'float64';\n    > strided.add.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n    <Float64Array>[ -1.0, 3.0, 6.0, -1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.add.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n    <Float64Array>[ 0.0, 5.0, -2.0, 0.0 ]\n\n    See Also\n    --------\n    strided.mul, strided.sub\n","strided.add.ndarray":"\nstrided.add.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n    Adds each element in a strided array `x` to a corresponding element in a\n    strided array `y` and assigns the results to elements in a strided array\n    `z` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dx: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    dy: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    dz: any\n        Data type for `z`.\n\n    z: ArrayLikeObject\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    Returns\n    -------\n    z: ArrayLikeObject\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var dt = 'float64';\n    > strided.add.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n    <Float64Array>[ -1.0, 3.0, 6.0, -1.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.add.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n    <Float64Array>[ 0.0, 5.0, -2.0, 0.0 ]\n\n    See Also\n    --------\n    strided.mul, strided.sub","strided.addBy":"\nstrided.addBy( N, x, sx, y, sy, z, sz, clbk[, thisArg] )\n    Performs element-wise addition of two strided arrays via a callback function\n    and assigns each result to an element in an output strided array.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided four arguments:\n\n    - values: input array elements.\n    - idx: iteration index.\n    - indices: strided array indices (offset + idx*stride).\n    - arrays: input and output arrays.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n    > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( values ) { return values; };\n    > strided.addBy( x.length, x, 1, y, 1, z, 1, clbk )\n    [ 12.0, 14.0, 16.0, 18.0 ]\n\n    // Using `N` and stride parameters:\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.addBy( 2, x, 2, y, -1, z, 1, clbk )\n    [ 13.0, 14.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\n    > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > strided.addBy( 2, x1, -2, y1, 1, z1, 1, clbk )\n    <Float64Array>[ 17.0, 16.0 ]\n    > z0\n    <Float64Array>[ 0.0, 0.0, 17.0, 16.0 ]\n\n\nstrided.addBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n    Performs element-wise addition of two strided arrays via a callback function\n    and assigns each result to an element in an output strided array using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n    > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( values ) { return values; };\n    > strided.addBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n    [ 12.0, 14.0, 16.0, 18.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0 ];\n    > y = [ 11.0, 12.0, 13.0, 14.0 ];\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > var oy = y.length - 1;\n    > var oz = z.length - 1;\n    > strided.addBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n    [ 0.0, 0.0, 17.0, 16.0 ]\n\n    See Also\n    --------\n    strided.add, strided.mulBy, strided.subBy\n","strided.addBy.ndarray":"\nstrided.addBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n    Performs element-wise addition of two strided arrays via a callback function\n    and assigns each result to an element in an output strided array using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n    > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( values ) { return values; };\n    > strided.addBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n    [ 12.0, 14.0, 16.0, 18.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0 ];\n    > y = [ 11.0, 12.0, 13.0, 14.0 ];\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > var oy = y.length - 1;\n    > var oz = z.length - 1;\n    > strided.addBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n    [ 0.0, 0.0, 17.0, 16.0 ]\n\n    See Also\n    --------\n    strided.add, strided.mulBy, strided.subBy","strided.ahavercosBy":"\nstrided.ahavercosBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the inverse half-value versed cosine of each element retrieved from\n    an input strided array `x` via a callback function and assigns each result\n    to an element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.ahavercosBy( x.length, x, 1, y, 1, clbk )\n    [ ~3.142, ~1.571, 0.0, ~2.094 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.ahavercosBy( 2, x, 2, y, -1, clbk )\n    [ 0.0, ~3.142, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 0.5, 1.0, 0.25 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.ahavercosBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~2.094, ~1.571 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~2.094, ~1.571 ]\n\n\nstrided.ahavercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse half-value versed cosine of each element retrieved from\n    an input strided array `x` via a callback function and assigns each result\n    to an element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.ahavercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ ~3.142, ~1.571, 0.0, ~2.094 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 0.5, 1.0, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.ahavercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~2.094, ~1.571 ]\n\n    See Also\n    --------\n    strided.ahaversinBy\n","strided.ahavercosBy.ndarray":"\nstrided.ahavercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse half-value versed cosine of each element retrieved from\n    an input strided array `x` via a callback function and assigns each result\n    to an element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.ahavercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ ~3.142, ~1.571, 0.0, ~2.094 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 0.5, 1.0, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.ahavercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~2.094, ~1.571 ]\n\n    See Also\n    --------\n    strided.ahaversinBy","strided.ahaversinBy":"\nstrided.ahaversinBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the inverse half-value versed sine of each element retrieved from\n    an input strided array `x` via a callback function and assigns each result\n    to an element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.ahaversinBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, ~1.571, ~3.142, ~1.047 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.ahaversinBy( 2, x, 2, y, -1, clbk )\n    [ ~3.142, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 0.5, 1.0, 0.25 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.ahaversinBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~1.047, ~1.571 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~1.047, ~1.571 ]\n\n\nstrided.ahaversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse half-value versed sine of each element retrieved from\n    an input strided array `x` via a callback function and assigns each result\n    to an element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.ahaversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~1.571, ~3.142, ~1.047 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 0.5, 1.0, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.ahaversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~1.047, ~1.571 ]\n\n    See Also\n    --------\n    strided.ahavercosBy\n","strided.ahaversinBy.ndarray":"\nstrided.ahaversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse half-value versed sine of each element retrieved from\n    an input strided array `x` via a callback function and assigns each result\n    to an element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 0.5, 1.0, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.ahaversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~1.571, ~3.142, ~1.047 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 0.5, 1.0, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.ahaversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~1.047, ~1.571 ]\n\n    See Also\n    --------\n    strided.ahavercosBy","strided.asinBy":"\nstrided.asinBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the arcsine of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.asinBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, ~-0.524, ~1.571, ~-0.253 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.asinBy( 2, x, 2, y, -1, clbk )\n    [ ~1.571, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, -0.5, 1.0, -0.25 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.asinBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~-0.253, ~-0.524 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~-0.253, ~-0.524 ]\n\n\nstrided.asinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the arcsine of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.asinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~-0.524, ~1.571, ~-0.253 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -0.5, 1.0, -0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.asinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.253, ~-0.524 ]\n\n    See Also\n    --------\n    strided.asinhBy\n","strided.asinBy.ndarray":"\nstrided.asinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the arcsine of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.asinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~-0.524, ~1.571, ~-0.253 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -0.5, 1.0, -0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.asinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.253, ~-0.524 ]\n\n    See Also\n    --------\n    strided.asinhBy","strided.asinhBy":"\nstrided.asinhBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the hyperbolic arcsine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.0, 2.0, -2.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.asinhBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, 0.0, ~1.444, ~-1.444 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.asinhBy( 2, x, 2, y, -1, clbk )\n    [ ~1.444, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, -0.0, 2.0, -2.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.asinhBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~-1.444, 0.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~-1.444, 0.0 ]\n\n\nstrided.asinhBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the hyperbolic arcsine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.0, 2.0, -2.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.asinhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, 0.0, ~1.444, ~-1.444 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -0.0, 2.0, -2.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.asinhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-1.444, 0.0 ]\n\n    See Also\n    --------\n    strided.asinBy\n","strided.asinhBy.ndarray":"\nstrided.asinhBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the hyperbolic arcsine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.0, 2.0, -2.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.asinhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, 0.0, ~1.444, ~-1.444 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -0.0, 2.0, -2.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.asinhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-1.444, 0.0 ]\n\n    See Also\n    --------\n    strided.asinBy","strided.atanBy":"\nstrided.atanBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the arctangent of each element retrieved from an input strided\n    array `x` via a callback function and assigns each result to an element in\n    an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.5, 1.0, -1.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.atanBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, ~-0.464, ~0.785, ~-0.896 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.atanBy( 2, x, 2, y, -1, clbk )\n    [ ~0.785, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, -0.5, 1.0, -1.25 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.atanBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~-0.896, ~-0.464 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~-0.896, ~-0.464 ]\n\n\nstrided.atanBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the arctangent of each element retrieved from an input strided\n    array `x` via a callback function and assigns each result to an element in\n    an output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.5, 1.0, -1.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.atanBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~-0.464, ~0.785, ~-0.896 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -0.5, 1.0, -1.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.atanBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.896, ~-0.464 ]\n\n    See Also\n    --------\n    strided.atanhBy\n","strided.atanBy.ndarray":"\nstrided.atanBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the arctangent of each element retrieved from an input strided\n    array `x` via a callback function and assigns each result to an element in\n    an output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.5, 1.0, -1.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.atanBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~-0.464, ~0.785, ~-0.896 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -0.5, 1.0, -1.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.atanBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.896, ~-0.464 ]\n\n    See Also\n    --------\n    strided.atanhBy","strided.atanhBy":"\nstrided.atanhBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the hyperbolic arctangent of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.atanhBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, ~-0.549, Infinity, ~-0.255 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.atanhBy( 2, x, 2, y, -1, clbk )\n    [ Infinity, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, -0.5, 1.0, -0.25 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.atanhBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~-0.255, ~-0.549 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~-0.255, ~-0.549 ]\n\n\nstrided.atanhBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the hyperbolic arctangent of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.atanhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~-0.549, Infinity, ~-0.255 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -0.5, 1.0, -0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.atanhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.255, ~-0.549 ]\n\n    See Also\n    --------\n    strided.atanBy\n","strided.atanhBy.ndarray":"\nstrided.atanhBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the hyperbolic arctangent of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -0.5, 1.0, -0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.atanhBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~-0.549, Infinity, ~-0.255 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -0.5, 1.0, -0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.atanhBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.255, ~-0.549 ]\n\n    See Also\n    --------\n    strided.atanBy","strided.avercosBy":"\nstrided.avercosBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the inverse versed cosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.avercosBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.avercosBy( 2, x, 2, y, -1, clbk )\n    [ ~1.047, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, -1.57, -0.5, -1.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.avercosBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~1.571, ~2.177 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~1.571, ~2.177 ]\n\n\nstrided.avercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse versed cosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.avercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -1.57, -0.5, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.avercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~1.571, ~2.177 ]\n\n","strided.avercosBy.ndarray":"\nstrided.avercosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse versed cosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, -1.57, -0.5, -1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.avercosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, -1.57, -0.5, -1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.avercosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~1.571, ~2.177 ]","strided.aversinBy":"\nstrided.aversinBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the inverse versed sine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.aversinBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.aversinBy( 2, x, 2, y, -1, clbk )\n    [ ~1.047, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 1.57, 0.5, 1.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.aversinBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~1.571, ~2.177 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~1.571, ~2.177 ]\n\n\nstrided.aversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse versed sine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.aversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.57, 0.5, 1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.aversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~1.571, ~2.177 ]\n\n","strided.aversinBy.ndarray":"\nstrided.aversinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the inverse versed sine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.57, 0.5, 1.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.aversinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~2.177, ~1.047, ~1.571 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.57, 0.5, 1.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.aversinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~1.571, ~2.177 ]","strided.besselj0By":"\nstrided.besselj0By( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the Bessel function of the first kind of order zero for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.besselj0By( x.length, x, 1, y, 1, clbk )\n    [ 1.0, ~0.765, ~0.998, ~0.984 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.besselj0By( 2, x, 2, y, -1, clbk )\n    [ ~0.998, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.besselj0By( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~0.984, ~0.765 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~0.984, ~0.765 ]\n\n\nstrided.besselj0By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the Bessel function of the first kind of order zero for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.besselj0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 1.0, ~0.765, ~0.998, ~0.984 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.besselj0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~0.984, ~0.765 ]\n\n    See Also\n    --------\n    strided.besselj1By, strided.bessely0By, strided.bessely1By\n","strided.besselj0By.ndarray":"\nstrided.besselj0By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the Bessel function of the first kind of order zero for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.besselj0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 1.0, ~0.765, ~0.998, ~0.984 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.besselj0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~0.984, ~0.765 ]\n\n    See Also\n    --------\n    strided.besselj1By, strided.bessely0By, strided.bessely1By","strided.besselj1By":"\nstrided.besselj1By( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the Bessel function of the first kind of order one for each element\n    retrieved from an input strided array `x` via a callback function and\n    assigns each result to an element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.besselj1By( x.length, x, 1, y, 1, clbk )\n    [ 0.0, ~0.44, ~0.05, ~0.124 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.besselj1By( 2, x, 2, y, -1, clbk )\n    [ ~0.05, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.besselj1By( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~0.124, ~0.44 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~0.124, ~0.44 ]\n\n\nstrided.besselj1By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the Bessel function of the first kind of order one for each element\n    retrieved from an input strided array `x` via a callback function and\n    assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.besselj1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~0.44, ~0.05, ~0.124 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.besselj1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~0.124, ~0.44 ]\n\n    See Also\n    --------\n    strided.besselj0By, strided.bessely0By, strided.bessely1By\n","strided.besselj1By.ndarray":"\nstrided.besselj1By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the Bessel function of the first kind of order one for each element\n    retrieved from an input strided array `x` via a callback function and\n    assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.besselj1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~0.44, ~0.05, ~0.124 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.besselj1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~0.124, ~0.44 ]\n\n    See Also\n    --------\n    strided.besselj0By, strided.bessely0By, strided.bessely1By","strided.bessely0By":"\nstrided.bessely0By( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the Bessel function of the second kind of order zero for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.bessely0By( x.length, x, 1, y, 1, clbk )\n    [ -Infinity, ~0.088, ~-1.534, ~-0.932 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.bessely0By( 2, x, 2, y, -1, clbk )\n    [ ~-1.534, -Infinity, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.bessely0By( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~-0.932, ~0.088 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~-0.932, ~0.088 ]\n\n\nstrided.bessely0By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the Bessel function of the second kind of order zero for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.bessely0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ -Infinity, ~0.088, ~-1.534, ~-0.932 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.bessely0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.932, ~0.088 ]\n\n    See Also\n    --------\n    strided.besselj0By, strided.besselj1By, strided.bessely1By\n","strided.bessely0By.ndarray":"\nstrided.bessely0By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the Bessel function of the second kind of order zero for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.bessely0By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ -Infinity, ~0.088, ~-1.534, ~-0.932 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.bessely0By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.932, ~0.088 ]\n\n    See Also\n    --------\n    strided.besselj0By, strided.besselj1By, strided.bessely1By","strided.bessely1By":"\nstrided.bessely1By( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the Bessel function of the second kind of order one for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.bessely1By( x.length, x, 1, y, 1, clbk )\n    [ -Infinity, ~-0.781, ~-6.459, ~-2.704 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.bessely1By( 2, x, 2, y, -1, clbk )\n    [ ~-6.459, -Infinity, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 1.0, 0.1, 0.25 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.bessely1By( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~-2.704, ~-0.781 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~-2.704, ~-0.781 ]\n\n\nstrided.bessely1By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the Bessel function of the second kind of order one for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.bessely1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ -Infinity, ~-0.781, ~-6.459, ~-2.704 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.bessely1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-2.704, ~-0.781 ]\n\n    See Also\n    --------\n    strided.besselj0By, strided.besselj1By, strided.bessely0By\n","strided.bessely1By.ndarray":"\nstrided.bessely1By.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the Bessel function of the second kind of order one for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.bessely1By.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ -Infinity, ~-0.781, ~-6.459, ~-2.704 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 0.1, 0.25 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.bessely1By.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-2.704, ~-0.781 ]\n\n    See Also\n    --------\n    strided.besselj0By, strided.besselj1By, strided.bessely0By","strided.binetBy":"\nstrided.binetBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Evaluates Binet's formula extended to real numbers for each element\n    retrieved from an input strided array `x` via a callback function and\n    assigns each result to an element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.binetBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, 1.0, 1.0, 2.0 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.binetBy( 2, x, 2, y, -1, clbk )\n    [ 1.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 1.0, 2.0, 3.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.binetBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ 2.0, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 2.0, 1.0 ]\n\n\nstrided.binetBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Evaluates Binet's formula extended to real numbers for each element\n    retrieved from an input strided array `x` via a callback function and\n    assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.binetBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, 1.0, 1.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 2.0, 3.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.binetBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, 2.0, 1.0 ]\n\n","strided.binetBy.ndarray":"\nstrided.binetBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Evaluates Binet's formula extended to real numbers for each element\n    retrieved from an input strided array `x` via a callback function and\n    assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 2.0, 3.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.binetBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, 1.0, 1.0, 2.0 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 2.0, 3.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.binetBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, 2.0, 1.0 ]","strided.cbrt":"\nstrided.cbrt( N, dtypeX, x, strideX, dtypeY, y, strideY )\n    Computes the cube root of each element in a strided array `x` and assigns\n    the results to elements in a strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.cbrt( x.length, 'float64', x, 1, 'float64', y, 1 )\n    <Float64Array>[ 0.0, 1.0, 2.0, 3.0 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.cbrt( 2, 'float64', x, 2, 'float64', y, -1 )\n    <Float64Array>[ 2.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.cbrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\n    <Float64Array>[ 3.0, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n\nstrided.cbrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the cube root of each element in a strided array `x` and assigns\n    the results to elements in a strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.cbrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 0.0, 1.0, 2.0, 3.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.cbrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dcbrt, base.strided.scbrt, strided.sqrt\n","strided.cbrt.ndarray":"\nstrided.cbrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the cube root of each element in a strided array `x` and assigns\n    the results to elements in a strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.cbrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 0.0, 1.0, 2.0, 3.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 1.0, 8.0, 27.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.cbrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 3.0, 1.0 ]\n\n    See Also\n    --------\n    base.strided.dcbrt, base.strided.scbrt, strided.sqrt","strided.cbrtBy":"\nstrided.cbrtBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the cube root of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 9.0, -27.0, 81.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.cbrtBy( x.length, x, 1, y, 1, clbk )\n    [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.cbrtBy( 2, x, 2, y, -1, clbk )\n    [ -3.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.cbrtBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~4.327, ~2.08 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~4.327, ~2.08 ]\n\n\nstrided.cbrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the cube root of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 9.0, -27.0, 81.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.cbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 9.0, -27.0, 81.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.cbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~4.327, ~2.08 ]\n\n    See Also\n    --------\n    strided.cbrt\n","strided.cbrtBy.ndarray":"\nstrided.cbrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the cube root of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 9.0, -27.0, 81.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.cbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 1.0, ~2.08, -3.0, ~4.327 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 9.0, -27.0, 81.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.cbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~4.327, ~2.08 ]\n\n    See Also\n    --------\n    strided.cbrt","strided.ceil":"\nstrided.ceil( N, dtypeX, x, strideX, dtypeY, y, strideY )\n    Rounds each element in a strided array `x` toward positive infinity and\n    assigns the results to elements in a strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ceil( x.length, 'float64', x, 1, 'float64', y, 1 )\n    <Float64Array>[ 2.0, 3.0, -3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ceil( 2, 'float64', x, 2, 'float64', y, -1 )\n    <Float64Array>[ -3.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.ceil( 2, 'float64', x1, -2, 'float64', y1, 1 )\n    <Float64Array>[ 4.0, 3.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n\nstrided.ceil.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Rounds each element in a strided array `x` toward positive infinity and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ceil.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 2.0, 3.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ceil.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n    See Also\n    --------\n    base.strided.dceil, strided.floor, strided.trunc, base.strided.sceil\n","strided.ceil.ndarray":"\nstrided.ceil.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Rounds each element in a strided array `x` toward positive infinity and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ceil.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 2.0, 3.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ceil.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 3.0 ]\n\n    See Also\n    --------\n    base.strided.dceil, strided.floor, strided.trunc, base.strided.sceil","strided.cosBy":"\nstrided.cosBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the cosine for each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.cosBy( x.length, x, 1, y, 1, clbk )\n    [ 1.0, ~-1.0, ~-1.0, ~-0.839 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.cosBy( 2, x, 2, y, -1, clbk )\n    [ ~-1.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 3.14, -3.14, 10.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.cosBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~-0.839, ~-1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~-0.839, ~-1.0 ]\n\n\nstrided.cosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the cosine for each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.cosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 1.0, ~-1.0, ~-1.0, ~-0.839 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 3.14, -3.14, 10.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.cosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.839, ~-1.0 ]\n\n","strided.cosBy.ndarray":"\nstrided.cosBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the cosine for each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.cosBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 1.0, ~-1.0, ~-1.0, ~-0.839 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 3.14, -3.14, 10.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.cosBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.839, ~-1.0 ]","strided.deg2rad":"\nstrided.deg2rad( N, dtypeX, x, strideX, dtypeY, y, strideY )\n    Converts each element in a strided array `x` from degrees to radians and\n    assigns the results to elements in a strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.deg2rad( x.length, 'float64', x, 1, 'float64', y, 1 )\n    <Float64Array>[ 0.0, ~0.524, ~0.785, ~1.571 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.deg2rad( 2, 'float64', x, 2, 'float64', y, -1 )\n    <Float64Array>[ ~0.785, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.deg2rad( 2, 'float64', x1, -2, 'float64', y1, 1 )\n    <Float64Array>[ ~1.571, ~0.524 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~1.571, ~0.524 ]\n\n\nstrided.deg2rad.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Converts each element in a strided array `x` from degrees to radians and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.deg2rad.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 0.0, ~0.524, ~0.785, ~1.571 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.deg2rad.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~1.571, ~0.524 ]\n\n    See Also\n    --------\n    base.strided.ddeg2rad, base.strided.sdeg2rad\n","strided.deg2rad.ndarray":"\nstrided.deg2rad.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Converts each element in a strided array `x` from degrees to radians and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.deg2rad.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 0.0, ~0.524, ~0.785, ~1.571 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 30.0, 45.0, 90.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.deg2rad.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~1.571, ~0.524 ]\n\n    See Also\n    --------\n    base.strided.ddeg2rad, base.strided.sdeg2rad","strided.dataTypes":"\nstrided.dataTypes()\n    Returns a list of strided array data types.\n\n    The output array contains the following data types:\n\n    - binary: binary.\n    - bool: boolean values.\n    - complex64: single-precision complex floating-point numbers.\n    - complex128: double-precision complex floating-point numbers.\n    - float32: single-precision floating-point numbers.\n    - float64: double-precision floating-point numbers.\n    - generic: values of any type.\n    - int16: signed 16-bit integers.\n    - int32: signed 32-bit integers.\n    - int8: signed 8-bit integers.\n    - uint16: unsigned 16-bit integers.\n    - uint32: unsigned 32-bit integers.\n    - uint8: unsigned 8-bit integers.\n    - uint8c: unsigned clamped 8-bit integers.\n\n    Returns\n    -------\n    out: Array<string>\n        List of strided array data types.\n\n    Examples\n    --------\n    > var out = strided.dataTypes()\n    <Array>\n\n","strided.dcbrtBy":"\nstrided.dcbrtBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the cube root of each element retrieved from an input double-\n    precision floating-point strided array via a callback function and assigns\n    each result to an element in an output double-precision floating-point\n    strided array.\n\n    The `N` and stride parameters determine which strided array elements are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - indices: strided array indices (offset + idx*stride).\n    - arrays: input and output arrays.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Float64Array\n        Destination array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > function clbk( v ) { return v; };\n    > strided.dcbrtBy( x.length, x, 1, y, 1, clbk )\n    <Float64Array>[ 1.0, ~2.08, -3.0, ~4.327 ]\n\n    // Using `N` and stride parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.dcbrtBy( 2, x, 2, y, -1, clbk )\n    <Float64Array>[ -3.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.dcbrtBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~4.327, ~2.08 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~4.327, ~2.08 ]\n\n\nstrided.dcbrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the cube root of each element retrieved from an input double-\n    precision floating-point strided array via a callback function and assigns\n    each result to an element in an output double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - indices: strided array indices (offset + idx*stride).\n    - arrays: input and output arrays.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Float64Array\n        Destination array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > function clbk( v ) { return v; };\n    > strided.dcbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    <Float64Array>[ 1.0, ~2.08, -3.0, ~4.327 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.dcbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    <Float64Array>[ 0.0, 0.0, ~4.327, ~2.08 ]\n\n    See Also\n    --------\n    strided.cbrt\n","strided.dcbrtBy.ndarray":"\nstrided.dcbrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the cube root of each element retrieved from an input double-\n    precision floating-point strided array via a callback function and assigns\n    each result to an element in an output double-precision floating-point\n    strided array using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    The callback function is provided four arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - indices: strided array indices (offset + idx*stride).\n    - arrays: input and output arrays.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Float64Array\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Float64Array\n        Destination array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Float64Array\n        Destination array.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > function clbk( v ) { return v; };\n    > strided.dcbrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    <Float64Array>[ 1.0, ~2.08, -3.0, ~4.327 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.0, 9.0, -27.0, 81.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.dcbrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    <Float64Array>[ 0.0, 0.0, ~4.327, ~2.08 ]\n\n    See Also\n    --------\n    strided.cbrt","strided.dispatch":"\nstrided.dispatch( fcns, types, data, nargs, nin, nout )\n    Returns a strided array function interface which performs multiple dispatch.\n\n    Without offsets, a strided array function interface has the following\n    signature:\n\n      f( N, dtypeX, x, strideX, dtypeY, y, strideY, ... )\n\n    where\n\n    - N: number of indexed elements.\n    - dtypeX: data type for `x`.\n    - x: strided array.\n    - strideX: index increment for `x`.\n    - dtypeY: data type for `y`.\n    - y: strided array.\n    - strideY: index increment for `y`.\n    - ...: additional strided arrays, data types, and associated strides.\n\n    The number of parameters is derived from `nargs`, the number of input\n    strided arrays is derived from `nin`, and the number of output strided\n    arrays is derived from `nout`.\n\n    Without offsets, the number of parameters must obey the following relation:\n\n      nargs = 3*(nout+nin) + 1\n\n    With offsets, the number of parameters must obey the following relation:\n\n      nargs = 4*(nout+nin) + 1\n\n    With offsets, a strided array function interface has the following\n    signature:\n\n      f( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY, ... )\n\n    where\n\n    - N: number of indexed elements.\n    - dtypeX: data type for `x`.\n    - x: strided array.\n    - strideX: index increment for `x`.\n    - offsetX: starting index for `x`.\n    - dtypeY: data type for `y`.\n    - y: strided array.\n    - strideY: index increment for `y`.\n    - offsetY: starting index for `y`.\n    - ...: additional strided arrays and associated data types, strides, and\n      offsets.\n\n    The choice of which strided array function interface to return depends on\n    the use case. The former is suitable for typed array views; while the latter\n    affords alternative indexing semantics more suitable for n-dimensional\n    arrays (ndarrays).\n\n    Parameters\n    ----------\n    fcns: Function|ArrayLikeObject<Function>\n        List of strided array functions. Without offsets, a strided array\n        function should have the following signature:\n\n          f( arrays, shape, strides, data )\n\n        where\n\n        - arrays: array containing strided input and output arrays.\n        - shape: array containing a single element, the number of indexed\n          elements.\n        - strides: array containing the stride lengths for the strided input and\n          output arrays.\n        - data: strided array function data (e.g., a callback).\n\n        With offsets, a strided array function should have the following\n        signature:\n\n          f( arrays, shape, strides, offsets, data )\n\n        where\n\n        - offsets: array containing the starting indices (i.e., index offsets)\n          for the strided input and output arrays.\n\n        For convenience, a single strided array function may be provided which\n        will be invoked whenever the strided array argument data types match a\n        sequence of types in `types`. Providing a single strided array function\n        is particularly convenient for the case where, regardless of array data\n        types, traversing arrays remains the same, but the strided array\n        function `data` differs (e.g., callbacks which differ based on the array\n        data types).\n\n    types: ArrayLikeObject\n        One-dimensional list of strided array argument data types.\n\n    data: ArrayLikeObject|null\n        Strided array function data (e.g., callbacks). If `null`, a returned\n        strided array function interface does **not** provide a `data` argument\n        to an invoked strided array function.\n\n    nargs: integer\n        Total number of strided array function interface arguments (including\n        data types, strides, and offsets).\n\n    nin: integer\n        Number of input strided arrays.\n\n    nout: integer\n        Number of output strided arrays.\n\n    Returns\n    -------\n    fcn: Function\n        Strided array function interface.\n\n    Examples\n    --------\n    // Define strided array argument data types:\n    > var t = [ 'float64', 'float64', 'float32', 'float32' ];\n\n    // Define a list of strided array function data (callbacks):\n    > var d = [ base.abs, base.absf ];\n\n    // Create a strided array function interface for applying unary callbacks:\n    > var f = strided.dispatch( base.strided.unary, t, d, 7, 1, 1 );\n\n    // Create an input strided array:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n    // Create an output strided array:\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n    // Compute the element-wise absolute value:\n    > f( x.length, 'float64', x, 1, 'float64', y, 1 );\n    > y\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Create a strided array function interface supporting offsets:\n    > f = strided.dispatch( base.strided.unary.ndarray, t, d, 9, 1, 1 );\n\n    // Create an input strided array:\n    > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n    // Create an output strided array:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n    // Compute the element-wise absolute value starting from the third element:\n    > f( 2, 'float64', x, 1, 2, 'float64', y, 1, 2 );\n    > y\n    <Float64Array>[ 0.0, 0.0, 3.0, 4.0 ]\n\n","strided.dispatchBy":"\nstrided.dispatchBy( fcns, types, data, nargs, nin, nout )\n    Returns a strided array function interface which accepts a callback function\n    and performs multiple dispatch.\n\n    Without offsets, a strided array function interface has the following\n    signature:\n\n      f( N, dx, x, sx, dy, y, sy, ..., clbk[, thisArg] )\n\n    where\n\n    - N: number of indexed elements.\n    - dx: data type for `x`.\n    - x: strided array.\n    - sx: index increment for `x`.\n    - dy: data type for `y`.\n    - y: strided array.\n    - sy: index increment for `y`.\n    - ...: additional strided arrays, data types, and associated strides.\n    - clbk: callback function.\n    - thisArg: callback function execution context.\n\n    The number of parameters is derived from `nargs`, the number of input\n    strided arrays is derived from `nin`, and the number of output strided\n    arrays is derived from `nout`.\n\n    Without offsets, the number of parameters must obey the following relation:\n\n      nargs = 3*(nout+nin) + 2\n\n    With offsets, the number of parameters must obey the following relation:\n\n      nargs = 4*(nout+nin) + 2\n\n    With offsets, a strided array function interface has the following\n    signature:\n\n      f( N, dx, x, sx, ox, dy, y, sy, oy, ..., clbk[, thisArg] )\n\n    where\n\n    - N: number of indexed elements.\n    - dx: data type for `x`.\n    - x: strided array.\n    - sx: index increment for `x`.\n    - ox: starting index for `x`.\n    - dy: data type for `y`.\n    - y: strided array.\n    - sy: index increment for `y`.\n    - oy: starting index for `y`.\n    - ...: additional strided arrays and associated data types, strides, and\n      offsets.\n    - clbk: callback function.\n    - thisArg: callback function execution context.\n\n    The choice of which strided array function interface to return depends on\n    the use case. The former is suitable for typed array views; while the latter\n    affords alternative indexing semantics more suitable for n-dimensional\n    arrays (ndarrays).\n\n    Parameters\n    ----------\n    fcns: Function|ArrayLikeObject<Function>\n        List of strided array functions. Without offsets, a strided array\n        function should have the following signature:\n\n          f( arrays, shape, strides, data, clbk, thisArg )\n\n        where\n\n        - arrays: array containing strided input and output arrays.\n        - shape: array containing a single element, the number of indexed\n          elements.\n        - strides: array containing the stride lengths for the strided input and\n          output arrays.\n        - data: strided array function data (e.g., a callback).\n        - clbk: callback function.\n        - thisArg: callback function execution context.\n\n        With offsets, a strided array function should have the following\n        signature:\n\n          f( arrays, shape, strides, offsets, data, clbk, thisArg )\n\n        where\n\n        - offsets: array containing the starting indices (i.e., index offsets)\n          for the strided input and output arrays.\n\n        For convenience, a single strided array function may be provided which\n        will be invoked whenever the strided array argument data types match a\n        sequence of types in `types`. Providing a single strided array function\n        is particularly convenient for the case where, regardless of array data\n        types, traversing arrays remains the same, but the strided array\n        function `data` differs (e.g., callbacks which differ based on the array\n        data types).\n\n    types: ArrayLikeObject\n        One-dimensional list of strided array argument data types.\n\n    data: ArrayLikeObject|null\n        Strided array function data (e.g., callbacks). If `null`, a returned\n        strided array function interface does **not** provide a `data` argument\n        to an invoked strided array function.\n\n    nargs: integer\n        Total number of strided array function interface arguments (including\n        data types, strides, offsets, and the callback function).\n\n    nin: integer\n        Number of input strided arrays.\n\n    nout: integer\n        Number of output strided arrays.\n\n    Returns\n    -------\n    fcn: Function\n        Strided array function interface.\n\n    Examples\n    --------\n    // Define strided array argument data types:\n    > var t = [ 'float64', 'float64', 'float32', 'float32' ];\n\n    // Define a list of strided array function data (callbacks):\n    > var d = [ base.abs, base.absf ];\n\n    // Create a strided array function interface for applying unary callbacks:\n    > var f = strided.dispatchBy( base.strided.unaryBy, t, d, 8, 1, 1 );\n\n    // Create an input strided array:\n    > var x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n    // Create an output strided array:\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n    // Compute the element-wise absolute value:\n    > f( x.length, 'float64', x, 1, 'float64', y, 1, base.identity );\n    > y\n    <Float64Array>[ 1.0, 2.0, 3.0, 4.0 ]\n\n    // Create a strided array function interface supporting offsets:\n    > f = strided.dispatchBy( base.strided.unary.ndarray, t, d, 10, 1, 1 );\n\n    // Create an input strided array:\n    > x = new Float64Array( [ -1.0, -2.0, -3.0, -4.0 ] );\n\n    // Create an output strided array:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n\n    // Compute the element-wise absolute value starting from the third element:\n    > f( 2, 'float64', x, 1, 2, 'float64', y, 1, 2, base.identity );\n    > y\n    <Float64Array>[ 0.0, 0.0, 3.0, 4.0 ]\n\n    See Also\n    --------\n    strided.dispatch\n","strided.floor":"\nstrided.floor( N, dtypeX, x, strideX, dtypeY, y, strideY )\n    Rounds each element in a strided array `x` toward negative infinity and\n    assigns the results to elements in a strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.floor( x.length, 'float64', x, 1, 'float64', y, 1 )\n    <Float64Array>[ -2.0, 2.0, -4.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.floor( 2, 'float64', x, 2, 'float64', y, -1 )\n    <Float64Array>[ -4.0, -2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.floor( 2, 'float64', x1, -2, 'float64', y1, 1 )\n    <Float64Array>[ 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nstrided.floor.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Rounds each element in a strided array `x` toward negative infinity and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.floor.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ -2.0, 2.0, -4.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.floor.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    strided.ceil, base.strided.dfloor, strided.trunc, base.strided.sfloor\n","strided.floor.ndarray":"\nstrided.floor.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Rounds each element in a strided array `x` toward negative infinity and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.floor.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ -2.0, 2.0, -4.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -1.5, 2.3, -3.9, 4.2 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.floor.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    strided.ceil, base.strided.dfloor, strided.trunc, base.strided.sfloor","strided.inv":"\nstrided.inv( N, dtypeX, x, strideX, dtypeY, y, strideY )\n    Computes the multiplicative inverse for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.inv( x.length, 'float64', x, 1, 'float64', y, 1 )\n    <Float64Array>[ -0.05, -1.0, 0.5, 0.25 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.inv( 2, 'float64', x, 2, 'float64', y, -1 )\n    <Float64Array>[ 0.5, -0.05, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.inv( 2, 'float64', x1, -2, 'float64', y1, 1 )\n    <Float64Array>[ 0.25, -1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n\nstrided.inv.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the multiplicative inverse for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.inv.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ -0.05, -1.0, 0.5, 0.25 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.inv.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dinv, base.strided.sinv\n","strided.inv.ndarray":"\nstrided.inv.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the multiplicative inverse for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.inv.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ -0.05, -1.0, 0.5, 0.25 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -20.0, -1.0, 2.0, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.inv.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 0.25, -1.0 ]\n\n    See Also\n    --------\n    base.strided.dinv, base.strided.sinv","strided.mul":"\nstrided.mul( N, dx, x, sx, dy, y, sy, dz, z, sz )\n    Multiplies each element in a strided array `x` to a corresponding element in\n    a strided array `y` and assigns the results to elements in a strided array\n    `z`.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dx: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    dy: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    dz: any\n        Data type for `z`.\n\n    z: ArrayLikeObject\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    Returns\n    -------\n    z: ArrayLikeObject\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var dt = 'float64';\n    > strided.mul( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\n    <Float64Array>[ -2.0, 2.0, 9.0, -20.0 ]\n\n    // Using `N` and stride parameters:\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.mul( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\n    <Float64Array>[ -6.0, 3.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > strided.mul( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\n    <Float64Array>[ -15.0, 4.0 ]\n    > z0\n    <Float64Array>[ 0.0, 0.0, -15.0, 4.0 ]\n\n\nstrided.mul.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n    Multiplies each element in a strided array `x` to a corresponding element in\n    a strided array `y` and assigns the results to elements in a strided array\n    `z` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dx: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    dy: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    dz: any\n        Data type for `z`.\n\n    z: ArrayLikeObject\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    Returns\n    -------\n    z: ArrayLikeObject\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var dt = 'float64';\n    > strided.mul.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n    <Float64Array>[ -2.0, 2.0, 9.0, -20.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.mul.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n    <Float64Array>[ 0.0, 4.0, -15.0, 0.0 ]\n\n    See Also\n    --------\n    strided.add, strided.sub\n","strided.mul.ndarray":"\nstrided.mul.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n    Multiplies each element in a strided array `x` to a corresponding element in\n    a strided array `y` and assigns the results to elements in a strided array\n    `z` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dx: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    dy: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    dz: any\n        Data type for `z`.\n\n    z: ArrayLikeObject\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    Returns\n    -------\n    z: ArrayLikeObject\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var dt = 'float64';\n    > strided.mul.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n    <Float64Array>[ -2.0, 2.0, 9.0, -20.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.mul.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n    <Float64Array>[ 0.0, 4.0, -15.0, 0.0 ]\n\n    See Also\n    --------\n    strided.add, strided.sub","strided.mulBy":"\nstrided.mulBy( N, x, sx, y, sy, z, sz, clbk[, thisArg] )\n    Performs element-wise multiplication of two strided arrays via a callback\n    function and assigns each result to an element in an output strided array.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided four arguments:\n\n    - values: input array elements.\n    - idx: iteration index.\n    - indices: strided array indices (offset + idx*stride).\n    - arrays: input and output arrays.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n    > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( values ) { return values; };\n    > strided.mulBy( x.length, x, 1, y, 1, z, 1, clbk )\n    [ 11.0, 24.0, 39.0, 56.0 ]\n\n    // Using `N` and stride parameters:\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.mulBy( 2, x, 2, y, -1, z, 1, clbk )\n    [ 12.0, 33.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var y0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\n    > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > strided.mulBy( 2, x1, -2, y1, 1, z1, 1, clbk )\n    <Float64Array>[ 52.0, 28.0 ]\n    > z0\n    <Float64Array>[ 0.0, 0.0, 52.0, 28.0 ]\n\n\nstrided.mulBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n    Performs element-wise multiplication of two strided arrays via a callback\n    function and assigns each result to an element in an output strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n    > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( values ) { return values; };\n    > strided.mulBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n    [ 11.0, 24.0, 39.0, 56.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0 ];\n    > y = [ 11.0, 12.0, 13.0, 14.0 ];\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > var oy = y.length - 1;\n    > var oz = z.length - 1;\n    > strided.mulBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n    [ 0.0, 0.0, 52.0, 28.0 ]\n\n    See Also\n    --------\n    strided.mul, strided.addBy, strided.subBy\n","strided.mulBy.ndarray":"\nstrided.mulBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n    Performs element-wise multiplication of two strided arrays via a callback\n    function and assigns each result to an element in an output strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 1.0, 2.0, 3.0, 4.0 ];\n    > var y = [ 11.0, 12.0, 13.0, 14.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( values ) { return values; };\n    > strided.mulBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n    [ 11.0, 24.0, 39.0, 56.0 ]\n\n    // Advanced indexing:\n    > x = [ 1.0, 2.0, 3.0, 4.0 ];\n    > y = [ 11.0, 12.0, 13.0, 14.0 ];\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > var oy = y.length - 1;\n    > var oz = z.length - 1;\n    > strided.mulBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n    [ 0.0, 0.0, 52.0, 28.0 ]\n\n    See Also\n    --------\n    strided.mul, strided.addBy, strided.subBy","strided.ramp":"\nstrided.ramp( N, dtypeX, x, strideX, dtypeY, y, strideY )\n    Evaluates the ramp function for each element in a strided array `x` and\n    assigns the results to elements in a strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ramp( x.length, 'float64', x, 1, 'float64', y, 1 )\n    <Float64Array>[ 1.1, 2.5, 0.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ramp( 2, 'float64', x, 2, 'float64', y, -1 )\n    <Float64Array>[ 0.0, 1.1, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.ramp( 2, 'float64', x1, -2, 'float64', y1, 1 )\n    <Float64Array>[ 4.0, 2.5 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.5 ]\n\n\nstrided.ramp.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Evaluates the ramp function for each element in a strided array `x` and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ramp.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 1.1, 2.5, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ramp.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.5 ]\n\n    See Also\n    --------\n    base.strided.dramp, base.strided.sramp\n","strided.ramp.ndarray":"\nstrided.ramp.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Evaluates the ramp function for each element in a strided array `x` and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ramp.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 1.1, 2.5, 0.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.ramp.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.5 ]\n\n    See Also\n    --------\n    base.strided.dramp, base.strided.sramp","strided.rsqrt":"\nstrided.rsqrt( N, dtypeX, x, strideX, dtypeY, y, strideY )\n    Computes the reciprocal square root for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.rsqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\n    <Float64Array>[ Infinity, 0.5, ~0.333, ~0.289 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.rsqrt( 2, 'float64', x, 2, 'float64', y, -1 )\n    <Float64Array>[ ~0.333, Infinity, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.rsqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\n    <Float64Array>[ ~0.289, 0.5 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n\nstrided.rsqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the reciprocal square root for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.rsqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ Infinity, 0.5, ~0.333, ~0.289 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.rsqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n    See Also\n    --------\n    base.strided.drsqrt, strided.sqrt, base.strided.srsqrt\n","strided.rsqrt.ndarray":"\nstrided.rsqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the reciprocal square root for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.rsqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ Infinity, 0.5, ~0.333, ~0.289 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.rsqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~0.289, 0.5 ]\n\n    See Also\n    --------\n    base.strided.drsqrt, strided.sqrt, base.strided.srsqrt","strided.sinBy":"\nstrided.sinBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the sine of each element retrieved from an input strided array `x`\n    via a callback function and assigns each result to an element in an output\n    strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.sinBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, ~0.002, ~-0.002, ~-0.544 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.sinBy( 2, x, 2, y, -1, clbk )\n    [ ~-0.002, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 3.14, -3.14, 10.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.sinBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~-0.544, ~0.002 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~-0.544, ~0.002 ]\n\n\nstrided.sinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the sine of each element retrieved from an input strided array `x`\n    via a callback function and assigns each result to an element in an output\n    strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.sinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~0.002, ~-0.002, ~-0.544 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 3.14, -3.14, 10.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.sinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.544, ~0.002 ]\n\n","strided.sinBy.ndarray":"\nstrided.sinBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the sine of each element retrieved from an input strided array `x`\n    via a callback function and assigns each result to an element in an output\n    strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 3.14, -3.14, 10.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.sinBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, ~0.002, ~-0.002, ~-0.544 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 3.14, -3.14, 10.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.sinBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~-0.544, ~0.002 ]","strided.sqrt":"\nstrided.sqrt( N, dtypeX, x, strideX, dtypeY, y, strideY )\n    Computes the principal square root for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.sqrt( x.length, 'float64', x, 1, 'float64', y, 1 )\n    <Float64Array>[ 0.0, 2.0, 3.0, ~3.464 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.sqrt( 2, 'float64', x, 2, 'float64', y, -1 )\n    <Float64Array>[ 3.0, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.sqrt( 2, 'float64', x1, -2, 'float64', y1, 1 )\n    <Float64Array>[ ~3.464, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n\nstrided.sqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the principal square root for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.sqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 0.0, 2.0, 3.0, ~3.464 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.sqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n    See Also\n    --------\n    strided.cbrt, base.strided.dsqrt, strided.rsqrt, base.strided.ssqrt\n","strided.sqrt.ndarray":"\nstrided.sqrt.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Computes the principal square root for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.sqrt.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 0.0, 2.0, 3.0, ~3.464 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 0.0, 4.0, 9.0, 12.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.sqrt.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, ~3.464, 2.0 ]\n\n    See Also\n    --------\n    strided.cbrt, base.strided.dsqrt, strided.rsqrt, base.strided.ssqrt","strided.sqrtBy":"\nstrided.sqrtBy( N, x, sx, y, sy, clbk[, thisArg] )\n    Computes the principal square root for each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n\n    The `N` and stride parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided six arguments:\n\n    - value: array element.\n    - idx: iteration index.\n    - xi: strided index (offsetX + idx*sx).\n    - yi: strided index (offsetY + idx*sy).\n    - x: the input array.\n    - y: the destination array.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 122.0, 50.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.sqrtBy( x.length, x, 1, y, 1, clbk )\n    [ 0.0, 1.0, ~11.045, ~7.071 ]\n\n    // Using `N` and stride parameters:\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.sqrtBy( 2, x, 2, y, -1, clbk )\n    [ ~11.045, 0.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 0.0, 1.0, 122.0, 50.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.sqrtBy( 2, x1, -2, y1, 1, clbk )\n    <Float64Array>[ ~7.071, 1.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, ~7.071, 1.0 ]\n\n\nstrided.sqrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the principal square root for each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 122.0, 50.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.sqrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, 1.0, ~11.045, ~7.071 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 122.0, 50.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.sqrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~7.071, 1.0 ]\n\n    See Also\n    --------\n    strided.sqrt\n","strided.sqrtBy.ndarray":"\nstrided.sqrtBy.ndarray( N, x, sx, ox, y, sy, oy, clbk[, thisArg] )\n    Computes the principal square root for each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    y: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 0.0, 1.0, 122.0, 50.0 ];\n    > var y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( v ) { return v; };\n    > strided.sqrtBy.ndarray( x.length, x, 1, 0, y, 1, 0, clbk )\n    [ 0.0, 1.0, ~11.045, ~7.071 ]\n\n    // Advanced indexing:\n    > x = [ 0.0, 1.0, 122.0, 50.0 ];\n    > y = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.sqrtBy.ndarray( 2, x, 2, 1, y, -1, y.length-1, clbk )\n    [ 0.0, 0.0, ~7.071, 1.0 ]\n\n    See Also\n    --------\n    strided.sqrt","strided.sub":"\nstrided.sub( N, dx, x, sx, dy, y, sy, dz, z, sz )\n    Subtracts each element in a strided array `x` to a corresponding element in\n    a strided array `y` and assigns the results to elements in a strided array\n    `z`.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dx: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    dy: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    dz: any\n        Data type for `z`.\n\n    z: ArrayLikeObject\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    Returns\n    -------\n    z: ArrayLikeObject\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var dt = 'float64';\n    > strided.sub( x.length, dt, x, 1, dt, y, 1, dt, z, 1 )\n    <Float64Array>[ -3.0, -1.0, 0.0, -9.0 ]\n\n    // Using `N` and stride parameters:\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.sub( 2, dt, x, 2, dt, y, -2, dt, z, 1 )\n    <Float64Array>[ -5.0, 2.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y0 = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > strided.sub( 2, dt, x1, -2, dt, y1, 1, dt, z1, 1 )\n    <Float64Array>[ -8.0, -3.0 ]\n    > z0\n    <Float64Array>[ 0.0, 0.0, -8.0, -3.0 ]\n\n\nstrided.sub.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n    Subtracts each element in a strided array `x` to a corresponding element in\n    a strided array `y` and assigns the results to elements in a strided array\n    `z` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dx: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    dy: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    dz: any\n        Data type for `z`.\n\n    z: ArrayLikeObject\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    Returns\n    -------\n    z: ArrayLikeObject\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var dt = 'float64';\n    > strided.sub.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n    <Float64Array>[ -3.0, -1.0, 0.0, -9.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.sub.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n    <Float64Array>[ 0.0, -3.0, -8.0, 0.0 ]\n\n    See Also\n    --------\n    strided.add, strided.mul\n","strided.sub.ndarray":"\nstrided.sub.ndarray( N, dx, x, sx, ox, dy, y, sy, oy, dz, z, sz, oz )\n    Subtracts each element in a strided array `x` to a corresponding element in\n    a strided array `y` and assigns the results to elements in a strided array\n    `z` using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dx: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    dy: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Input array.\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    dz: any\n        Data type for `z`.\n\n    z: ArrayLikeObject\n        Destination array.\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    Returns\n    -------\n    z: ArrayLikeObject\n        Input array `z`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > var y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > var z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var dt = 'float64';\n    > strided.sub.ndarray( 4, dt, x, 1, 0, dt, y, 1, 0, dt, z, 1, 0 )\n    <Float64Array>[ -3.0, -1.0, 0.0, -9.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ -2.0, 1.0, 3.0, -5.0 ] );\n    > y = new Float64Array( [ 1.0, 2.0, 3.0, 4.0 ] );\n    > z = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.sub.ndarray( 2, dt, x, 2, 1, dt, y, -1, 3, dt, z, 1, 1 )\n    <Float64Array>[ 0.0, -3.0, -8.0, 0.0 ]\n\n    See Also\n    --------\n    strided.add, strided.mul","strided.subBy":"\nstrided.subBy( N, x, sx, y, sy, z, sz, clbk[, thisArg] )\n    Performs element-wise subtraction of two strided arrays via a callback\n    function and assigns each result to an element in an output strided array.\n\n    The `N` and stride parameters determine which elements in the strided arrays\n    are accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    The callback function is provided four arguments:\n\n    - values: input array elements.\n    - idx: iteration index.\n    - indices: strided array indices (offset + idx*stride).\n    - arrays: input and output arrays.\n\n    If the callback function does not return any value (or equivalently,\n    explicitly returns `undefined`), the value is ignored.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 11.0, 12.0, 13.0, 14.0 ];\n    > var y = [ 8.0, 7.0, 6.0, 5.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( values ) { return values; };\n    > strided.subBy( x.length, x, 1, y, 1, z, 1, clbk )\n    [ 3.0, 5.0, 7.0, 9.0 ]\n\n    // Using `N` and stride parameters:\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > strided.subBy( 2, x, 2, y, -1, z, 1, clbk )\n    [ 4.0, 5.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 11.0, 12.0, 13.0, 14.0 ] );\n    > var y0 = new Float64Array( [ 8.0, 7.0, 6.0, 5.0 ] );\n    > var z0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > var z1 = new Float64Array( z0.buffer, z0.BYTES_PER_ELEMENT*2 );\n    > strided.subBy( 2, x1, -2, y1, 1, z1, 1, clbk )\n    <Float64Array>[ 8.0, 7.0 ]\n    > z0\n    <Float64Array>[ 0.0, 0.0, 8.0, 7.0 ]\n\n\nstrided.subBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n    Performs element-wise subtraction of two strided arrays via a callback\n    function and assigns each result to an element in an output strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 11.0, 12.0, 13.0, 14.0 ];\n    > var y = [ 8.0, 7.0, 6.0, 5.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( values ) { return values; };\n    > strided.subBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n    [ 3.0, 5.0, 7.0, 9.0 ]\n\n    // Advanced indexing:\n    > x = [ 11.0, 12.0, 13.0, 14.0 ];\n    > y = [ 8.0, 7.0, 6.0, 5.0 ];\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > var oy = y.length - 1;\n    > var oz = z.length - 1;\n    > strided.subBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n    [ 0.0, 0.0, 8.0, 7.0 ]\n\n    See Also\n    --------\n    strided.sub, strided.addBy, strided.mulBy\n","strided.subBy.ndarray":"\nstrided.subBy.ndarray( N, x, sx, ox, y, sy, oy, z, sz, oz, clbk[, thisArg] )\n    Performs element-wise subtraction of two strided arrays via a callback\n    function and assigns each result to an element in an output strided array\n    using alternative indexing semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the offset parameters support indexing semantics based on starting\n    indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    x: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sx: integer\n        Index increment for `x`.\n\n    ox: integer\n        Starting index for `x`.\n\n    y: Array|TypedArray|Object\n        Input array/collection. If provided an object, the object must be array-\n        like (excluding strings and functions).\n\n    sy: integer\n        Index increment for `y`.\n\n    oy: integer\n        Starting index for `y`.\n\n    z: Array|TypedArray|Object\n        Destination array/collection. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    sz: integer\n        Index increment for `z`.\n\n    oz: integer\n        Starting index for `z`.\n\n    clbk: Function\n        Callback function.\n\n    thisArg: any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    z: Array|TypedArray|Object\n        Destination array/collection.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = [ 11.0, 12.0, 13.0, 14.0 ];\n    > var y = [ 8.0, 7.0, 6.0, 5.0 ];\n    > var z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > function clbk( values ) { return values; };\n    > strided.subBy.ndarray( x.length, x, 1, 0, y, 1, 0, z, 1, 0, clbk )\n    [ 3.0, 5.0, 7.0, 9.0 ]\n\n    // Advanced indexing:\n    > x = [ 11.0, 12.0, 13.0, 14.0 ];\n    > y = [ 8.0, 7.0, 6.0, 5.0 ];\n    > z = [ 0.0, 0.0, 0.0, 0.0 ];\n    > var oy = y.length - 1;\n    > var oz = z.length - 1;\n    > strided.subBy.ndarray( 2, x, 2, 1, y, -1, oy, z, -1, oz, clbk )\n    [ 0.0, 0.0, 8.0, 7.0 ]\n\n    See Also\n    --------\n    strided.sub, strided.addBy, strided.mulBy","strided.trunc":"\nstrided.trunc( N, dtypeX, x, strideX, dtypeY, y, strideY )\n    Rounds each element in a strided array `x` toward zero and assigns the\n    results to elements in a strided array `y`.\n\n    The `N` and `stride` parameters determine which elements in `x` and `y` are\n    accessed at runtime.\n\n    Indexing is relative to the first index. To introduce an offset, use typed\n    array views.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.trunc( x.length, 'float64', x, 1, 'float64', y, 1 )\n    <Float64Array>[ 1.0, 2.0, -3.0, 4.0 ]\n\n    // Using `N` and `stride` parameters:\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.trunc( 2, 'float64', x, 2, 'float64', y, -1 )\n    <Float64Array>[ -3.0, 1.0, 0.0, 0.0 ]\n\n    // Using view offsets:\n    > var x0 = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 );\n    > var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*2 );\n    > strided.trunc( 2, 'float64', x1, -2, 'float64', y1, 1 )\n    <Float64Array>[ 4.0, 2.0 ]\n    > y0\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n\nstrided.trunc.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Rounds each element in a strided array `x` toward zero and assigns the\n    results to elements in a strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.trunc.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.trunc.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    strided.ceil, base.strided.dtrunc, strided.floor, base.strided.strunc\n","strided.trunc.ndarray":"\nstrided.trunc.ndarray( N, dtypeX, x, strideX, offsetX, dtypeY, y, strideY, offsetY )\n    Rounds each element in a strided array `x` toward zero and assigns the\n    results to elements in a strided array `y` using alternative indexing\n    semantics.\n\n    While typed array views mandate a view offset based on the underlying\n    buffer, the `offsetX` and `offsetY` parameters support indexing semantics\n    based on starting indices.\n\n    Parameters\n    ----------\n    N: integer\n        Number of indexed elements.\n\n    dtypeX: any\n        Data type for `x`.\n\n    x: ArrayLikeObject\n        Input array.\n\n    strideX: integer\n        Index increment for `x`.\n\n    offsetX: integer\n        Starting index for `x`.\n\n    dtypeY: any\n        Data type for `y`.\n\n    y: ArrayLikeObject\n        Destination array.\n\n    strideY: integer\n        Index increment for `y`.\n\n    offsetY: integer\n        Starting index for `y`.\n\n    Returns\n    -------\n    y: ArrayLikeObject\n        Input array `y`.\n\n    Examples\n    --------\n    // Standard usage:\n    > var x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > var y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.trunc.ndarray( x.length, 'float64', x, 1, 0, 'float64', y, 1, 0 )\n    <Float64Array>[ 1.0, 2.0, -3.0, 4.0 ]\n\n    // Advanced indexing:\n    > x = new Float64Array( [ 1.1, 2.5, -3.5, 4.0 ] );\n    > y = new Float64Array( [ 0.0, 0.0, 0.0, 0.0 ] );\n    > strided.trunc.ndarray( 2, 'float64', x, 2, 1, 'float64', y, -1, y.length-1 )\n    <Float64Array>[ 0.0, 0.0, 4.0, 2.0 ]\n\n    See Also\n    --------\n    strided.ceil, base.strided.dtrunc, strided.floor, base.strided.strunc","stridedarray2iterator":"\nstridedarray2iterator( N, src, stride, offset[, mapFcn[, thisArg]] )\n    Returns an iterator which iterates over elements of an array-like object\n    according to specified stride parameters.\n\n    When invoked, an input function is provided four arguments:\n\n    - value: iterated value.\n    - index: iterated value index.\n    - n: iteration count (zero-based).\n    - src: source array-like object.\n\n    If an environment supports Symbol.iterator, the returned iterator is\n    iterable.\n\n    If an environment supports Symbol.iterator, the function explicitly does not\n    invoke an array's `@@iterator` method, regardless of whether this method is\n    defined. To convert an array to an implementation defined iterator, invoke\n    this method directly.\n\n    Parameters\n    ----------\n    N: integer\n        Number of values to iterate.\n\n    src: ArrayLikeObject\n        Array-like object from which to create the iterator.\n\n    stride: integer\n        Stride length.\n\n    offset: integer\n        Starting index.\n\n    mapFcn: Function (optional)\n        Function to invoke for each iterated value.\n\n    thisArg: any (optional)\n        Execution context.\n\n    Returns\n    -------\n    iterator: Object\n        Iterator.\n\n    iterator.next(): Function\n        Returns an iterator protocol-compliant object containing the next\n        iterated value (if one exists) and a boolean flag indicating whether the\n        iterator is finished.\n\n    iterator.return( [value] ): Function\n        Finishes an iterator and returns a provided value.\n\n    Examples\n    --------\n    > var it = stridedarray2iterator( 2, [ 1, 2, 3, 4 ], -2, 3 );\n    > var v = it.next().value\n    4\n    > v = it.next().value\n    2\n\n    See Also\n    --------\n    iterator2array, array2iterator\n","stridedArrayStream":"\nstridedArrayStream( N, buffer, stride, offset[, options] )\n    Creates a readable stream from a strided array-like object.\n\n    In object mode, `null` is a reserved value. If an array contains `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or filter `null` values\n    prior to invocation.\n\n    In binary mode, if an array contains `undefined` values, the stream will\n    emit an error. Consider providing a custom serialization function or\n    filtering `undefined` values prior to invocation.\n\n    If a serialization function fails to return a string or Buffer, the stream\n    emits an error.\n\n    Parameters\n    ----------\n    N: integer\n        Number of values to stream.\n\n    buffer: ArrayLikeObject\n        Array-like object from which to create the stream.\n\n    stride: integer\n        Stride length.\n\n    offset: integer\n        Starting index.\n\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing the stream.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize streamed\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream.\n\n    Examples\n    --------\n    > function fcn( chunk ) { console.log( chunk.toString() ); };\n    > var s = stridedArrayStream( 3, [ 1, 2, 3 ], 1, 0 );\n    > var o = inspectSinkStream( fcn );\n    > s.pipe( o );\n\n\nstridedArrayStream.factory( [options] )\n    Returns a function for creating readable streams from array-like objects.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing streaming.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize streamed\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = stridedArrayStream.factory( opts );\n\n\nstridedArrayStream.objectMode( N, buffer, stride, offset[, options] )\n    Returns an \"objectMode\" readable stream from a strided array-like object.\n\n    In object mode, `null` is a reserved value. If an array contains `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or filter `null` values\n    prior to invocation.\n\n    Parameters\n    ----------\n    N: integer\n        Number of values to stream.\n\n    buffer: ArrayLikeObject\n        Array-like object from which to create the stream.\n\n    stride: integer\n        Stride length.\n\n    offset: integer\n        Starting index.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before pausing streaming.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var s = stridedArrayStream.objectMode( 3, [ 1, 2, 3 ], 1, 0 );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    arrayStream\n","stridedArrayStream.factory":"\nstridedArrayStream.factory( [options] )\n    Returns a function for creating readable streams from array-like objects.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before pausing streaming.\n\n    options.sep: string (optional)\n        Separator used to join streamed data. This option is only applicable\n        when a stream is not in \"objectMode\". Default: '\\n'.\n\n    options.serialize: Function (optional)\n        Serialization function. The default behavior is to serialize streamed\n        values as JSON strings. This option is only applicable when a stream is\n        not in \"objectMode\".\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating readable streams.\n\n    Examples\n    --------\n    > var opts = { 'objectMode': true, 'highWaterMark': 64 };\n    > var createStream = stridedArrayStream.factory( opts );","stridedArrayStream.objectMode":"\nstridedArrayStream.objectMode( N, buffer, stride, offset[, options] )\n    Returns an \"objectMode\" readable stream from a strided array-like object.\n\n    In object mode, `null` is a reserved value. If an array contains `null`\n    values (e.g., as a means to encode missing values), the stream will\n    prematurely end. Consider an alternative encoding or filter `null` values\n    prior to invocation.\n\n    Parameters\n    ----------\n    N: integer\n        Number of values to stream.\n\n    buffer: ArrayLikeObject\n        Array-like object from which to create the stream.\n\n    stride: integer\n        Stride length.\n\n    offset: integer\n        Starting index.\n\n    options: Object (optional)\n        Options.\n\n    options.encoding: string|null (optional)\n        Specifies how Buffer objects should be decoded to strings. Default:\n        null.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of objects to store in an internal buffer\n        before pausing streaming.\n\n    Returns\n    -------\n    stream: ReadableStream\n        Readable stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > function fcn( v ) { console.log( v ); };\n    > var s = stridedArrayStream.objectMode( 3, [ 1, 2, 3 ], 1, 0 );\n    > var o = inspectSinkStream.objectMode( fcn );\n    > s.pipe( o );\n\n    See Also\n    --------\n    arrayStream","string2buffer":"\nstring2buffer( str[, encoding] )\n    Allocates a buffer containing a provided string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    encoding: string (optional)\n        Character encoding. Default: 'utf8'.\n\n    Returns\n    -------\n    out: Buffer\n        Buffer instance.\n\n    Examples\n    --------\n    > var b = string2buffer( 'beep boop' )\n    <Buffer>\n    > b = string2buffer( '7468697320697320612074c3a97374', 'hex' );\n    > b.toString()\n    'this is a tést'\n\n    See Also\n    --------\n    Buffer, array2buffer, arraybuffer2buffer, copyBuffer\n","sub2ind":"\nsub2ind( shape, ...subscript[, options] )\n    Converts subscripts to a linear index.\n\n    Parameters\n    ----------\n    shape: ArrayLike\n        Array shape.\n\n    subscript: ...integer\n        Subscripts.\n\n    options: Object (optional)\n        Options.\n\n    options.order: string (optional)\n        Specifies whether an array is row-major (C-style) or column-major\n        (Fortran style). Default: 'row-major'.\n\n    options.mode: string|Array<string> (optional)\n        Specifies how to handle subscripts which exceed array dimensions. If\n        equal to 'throw', the function throws an error when a subscript exceeds\n        array dimensions. If equal to 'normalize', the function normalizes\n        negative subscripts and throws an error when a subscript exceeds array\n        dimensions. If equal to 'wrap', the function wraps around subscripts\n        exceeding array dimensions using modulo arithmetic. If equal to\n        'clamp', the function sets subscripts exceeding array dimensions to\n        either `0` (minimum index) or the maximum index along a particular\n        dimension. If provided a mode array, each array element specifies the\n        mode for a corresponding array dimension. If provided fewer modes than\n        dimensions, the function recycles modes using modulo arithmetic.\n        Default: [ 'throw' ].\n\n    Returns\n    -------\n    idx: integer\n        Linear index.\n\n    Examples\n    --------\n    > var d = [ 3, 3, 3 ];\n    > var idx = sub2ind( d, 1, 2, 2 )\n    17\n\n    See Also\n    --------\n    array, ndarray, ind2sub\n","substringAfter":"\nsubstringAfter( str, search[, fromIndex] )\n    Returns the part of a string after a specified substring.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search string.\n\n    fromIndex: integer (optional)\n        Index from which to start the search. Default: `0`.\n\n    Returns\n    -------\n    out: string\n        Substring.\n\n    Examples\n    --------\n    > var out = substringAfter( 'Hello World!', 'World' )\n    '!'\n    > out = substringAfter( 'Hello World!', 'Hello ' )\n    'World!'\n    > out = substringAfter( 'Hello World!', 'l', 5 )\n    'd!'\n\n    See Also\n    --------\n    substringBefore, substringBeforeLast, substringAfterLast","substringAfterLast":"\nsubstringAfterLast( str, search[, fromIndex] )\n    Returns the part of a string after the last occurrence of a specified\n    substring.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search value.\n\n    fromIndex: integer (optional)\n        Index of last character to be considered beginning of a match.\n        Default: `str.length`.\n\n    Returns\n    -------\n    out: string\n        Substring.\n\n    Examples\n    --------\n    > var out = substringAfterLast( 'beep boop beep baz', 'beep' )\n    ' baz'\n    > out = substringAfterLast( 'Hello World!', 'Hello ' )\n    'World!'\n    > out = substringAfterLast( 'Hello World!', 'o', 5 )\n    ' World!'\n\n    See Also\n    --------\n    substringBefore, substringBeforeLast, substringAfter","substringBefore":"\nsubstringBefore( str, search )\n    Returns the part of a string before a specified substring.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search string.\n\n    Returns\n    -------\n    out: string\n        Substring.\n\n    Examples\n    --------\n    > var str = 'beep boop';\n    > var out = substringBefore( str, ' ' )\n    'beep'\n    > out = substringBefore( str, 'o' )\n    'beep b'\n\n    See Also\n    --------\n    substringBeforeLast, substringAfter, substringAfterLast","substringBeforeLast":"\nsubstringBeforeLast( str, search )\n    Returns the part of a string before the last occurrence of a specified\n    substring.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    search: string\n        Search value.\n\n    Returns\n    -------\n    out: string\n        Substring.\n\n    Examples\n    --------\n    > var str = 'Beep Boop Beep';\n    > var out = substringBeforeLast( str, 'Beep' )\n    'Beep Boop '\n    > out = substringBeforeLast( str, 'Boop' )\n    'Beep '\n\n    See Also\n    --------\n    substringBefore, substringAfter, substringAfterLast","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n    Returns a dataset consisting of labeled wireless sensor network data set\n    collected from a multi-hop wireless sensor network deployment using TelosB\n    motes.\n\n    Humidity and temperature measurements were collected at 5 second intervals\n    over a six hour period on July 10, 2010.\n\n    Temperature is in degrees Celsius.\n\n    Humidity is temperature corrected relative humidity, ranging from 0-100%.\n\n    The label '0' denotes normal data, and the label '1' denotes an introduced\n    event.\n\n    If a mote was an indoor sensor, the corresponding indicator is '1'. If a\n    mote was an outdoor sensor, the indoor indicator is '0'.\n\n    Returns\n    -------\n    out: Array<Object>\n        Sensor data.\n\n    Examples\n    --------\n    > var data = SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n    [{...}, {...}, ...]\n\n    References\n    ----------\n    - Suthaharan, Shan, Mohammed Alzahrani, Sutharshan Rajasegarar, Christopher\n    Leckie, and Marimuthu Palaniswami. 2010. \"Labelled data collection for\n    anomaly detection in wireless sensor networks.\" In _Proceedings of the Sixth\n    International Conference on Intelligent Sensors, Sensor Networks and\n    Information Processing (ISSNIP 2010)_. Brisbane, Australia: IEEE.\n\n    * If you use the data for publication or third party consumption, please\n    cite the listed reference.\n\n    See Also\n    --------\n    SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK\n","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n    Returns a dataset consisting of labeled wireless sensor network data set\n    collected from a simple single-hop wireless sensor network deployment using\n    TelosB motes.\n\n    Humidity and temperature measurements were collected at 5 second intervals\n    over a six hour period on May 9, 2010.\n\n    Temperature is in degrees Celsius.\n\n    Humidity is temperature corrected relative humidity, ranging from 0-100%.\n\n    The label '0' denotes normal data, and the label '1' denotes an introduced\n    event.\n\n    If a mote was an indoor sensor, the corresponding indicator is '1'. If a\n    mote was an outdoor sensor, the indoor indicator is '0'.\n\n    Returns\n    -------\n    out: Array<Object>\n        Sensor data.\n\n    Examples\n    --------\n    > var data = SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n    [{...}, {...}, ...]\n\n    References\n    ----------\n    - Suthaharan, Shan, Mohammed Alzahrani, Sutharshan Rajasegarar, Christopher\n    Leckie, and Marimuthu Palaniswami. 2010. \"Labelled data collection for\n    anomaly detection in wireless sensor networks.\" In _Proceedings of the Sixth\n    International Conference on Intelligent Sensors, Sensor Networks and\n    Information Processing (ISSNIP 2010)_. Brisbane, Australia: IEEE.\n\n    * If you use the data for publication or third party consumption, please\n    cite the listed reference.\n\n    See Also\n    --------\n    SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK\n","Symbol":"\nSymbol( [description] )\n    Returns a symbol.\n\n    Unlike conventional constructors, this function does **not** support the\n    `new` keyword.\n\n    This function is only supported in environments which support symbols.\n\n    Parameters\n    ----------\n    description: string (optional)\n        Symbol description which can be used for debugging but not to access the\n        symbol itself.\n\n    Returns\n    -------\n    out: symbol\n        Symbol.\n\n    Examples\n    --------\n    > var s = ( Symbol ) ? Symbol( 'beep' ) : null\n\n","tabulate":"\ntabulate( collection )\n    Generates a frequency table.\n\n    The table is an array of arrays where each sub-array corresponds to a unique\n    value in the input collection. Each sub-array is structured as follows:\n\n    - 0: unique value.\n    - 1: value count.\n    - 2: frequency percentage.\n\n    If provided an empty collection, the function returns an empty array.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection to tabulate. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    Returns\n    -------\n    out: Array<Array>|Array\n        Frequency table.\n\n    Examples\n    --------\n    > var collection = [ 'beep', 'boop', 'foo', 'beep' ];\n    > var out = tabulate( collection )\n    [ [ 'beep', 2, 0.5 ], [ 'boop', 1, 0.25 ], [ 'foo', 1, 0.25 ] ]\n\n    See Also\n    --------\n    countBy, groupBy, tabulateBy\n","tabulateBy":"\ntabulateBy( collection, [options,] indicator )\n    Generates a frequency table according to an indicator function.\n\n    When invoked, the indicator function is provided two arguments:\n\n    - value: collection value.\n    - index: collection index.\n\n    The table is an array of arrays where each sub-array corresponds to a unique\n    value in the input collection. Each sub-array is structured as follows:\n\n    - 0: unique value.\n    - 1: value count.\n    - 2: frequency percentage.\n\n    If provided an empty collection, the function returns an empty array.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection to tabulate. If provided an object, the object must be\n        array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Options.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    indicator: Function\n        Indicator function specifying how to categorize a collection element.\n\n    Returns\n    -------\n    out: Array<Array>|Array\n        Frequency table.\n\n    Examples\n    --------\n    > function indicator( value ) { return value[ 0 ]; };\n    > var collection = [ 'beep', 'boop', 'foo', 'beep' ];\n    > var out = tabulateBy( collection, indicator )\n    [ [ 'b', 3, 0.75 ], [ 'f', 1, 0.25 ] ]\n\n    See Also\n    --------\n    countBy, groupBy, tabulate\n","tabulateByAsync":"\ntabulateByAsync( collection, [options,] indicator, done )\n    Generates a frequency table according to an indicator function.\n\n    The table is an array of arrays where each sub-array corresponds to a unique\n    value in the input collection. Each sub-array is structured as follows:\n\n    - 0: unique value.\n    - 1: value count.\n    - 2: frequency percentage.\n\n    When invoked, the indicator function is provided a maximum of four\n    arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n    - next: a callback to be invoked after processing a collection `value`.\n\n    The actual number of provided arguments depends on function length. If the\n    indicator function accepts two arguments, the indicator function is\n    provided:\n\n    - value\n    - next\n\n    If the indicator function accepts three arguments, the indicator function is\n    provided:\n\n    - value\n    - index\n    - next\n\n    For every other indicator function signature, the indicator function is\n    provided all four arguments.\n\n    The `next` callback takes two arguments:\n\n    - error: error argument.\n    - group: value group.\n\n    If an indicator function calls the `next` callback with a truthy `error`\n    argument, the function suspends execution and immediately calls the `done`\n    callback for subsequent `error` handling.\n\n    If provided an empty collection, the function calls the `done` callback with\n    an empty array as the second argument.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    The function does not support dynamic collection resizing.\n\n    The function does not skip `undefined` elements.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    indicator: Function\n        Indicator function specifying how to categorize a collection element.\n\n    done: Function\n        A callback invoked either upon processing all collection elements or\n        upon encountering an error.\n\n    Examples\n    --------\n    // Basic usage:\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) ? 'even': 'odd' );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000, 750 ];\n    > tabulateByAsync( arr, indicator, done )\n    750\n    1000\n    2500\n    3000\n    [ [ 'odd', 2, 0.5 ], [ 'even', 2, 0.5 ] ]\n\n    // Limit number of concurrent invocations:\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var opts = { 'limit': 2 };\n    > var arr = [ 3000, 2500, 1000, 750 ];\n    > tabulateByAsync( arr, opts, indicator, done )\n    2500\n    3000\n    1000\n    750\n    [ [ 'odd', 2, 0.5 ], [ 'even', 2, 0.5 ] ]\n\n    // Process sequentially:\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var opts = { 'series': true };\n    > var arr = [ 3000, 2500, 1000, 750 ];\n    > tabulateByAsync( arr, opts, indicator, done )\n    3000\n    2500\n    1000\n    750\n    [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n\ntabulateByAsync.factory( [options,] indicator )\n    Returns a function which generates a frequency table according to an\n    indicator function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    indicator: Function\n        Indicator function specifying how to categorize a collection element.\n\n    Returns\n    -------\n    out: Function\n        A function which generates a frequency table according to an indicator\n        function.\n\n    Examples\n    --------\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = tabulateByAsync.factory( opts, indicator );\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000, 750 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    750\n    [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n    > arr = [ 2000, 1500, 1000, 750 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    750\n    [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n    See Also\n    --------\n    countByAsync, groupByAsync, tabulateBy\n","tabulateByAsync.factory":"\ntabulateByAsync.factory( [options,] indicator )\n    Returns a function which generates a frequency table according to an\n    indicator function.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.limit: integer (optional)\n        Maximum number of pending invocations. Default: Infinity.\n\n    options.series: boolean (optional)\n        Boolean indicating whether to process each collection element\n        sequentially. Default: false.\n\n    options.thisArg: any (optional)\n        Execution context.\n\n    indicator: Function\n        Indicator function specifying how to categorize a collection element.\n\n    Returns\n    -------\n    out: Function\n        A function which generates a frequency table according to an indicator\n        function.\n\n    Examples\n    --------\n    > function indicator( value, index, next ) {\n    ...     setTimeout( onTimeout, value );\n    ...     function onTimeout() {\n    ...         console.log( value );\n    ...         next( null, ( index%2 === 0 ) ? 'even' : 'odd' );\n    ...     }\n    ... };\n    > var opts = { 'series': true };\n    > var f = tabulateByAsync.factory( opts, indicator );\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > var arr = [ 3000, 2500, 1000, 750 ];\n    > f( arr, done )\n    3000\n    2500\n    1000\n    750\n    [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n    > arr = [ 2000, 1500, 1000, 750 ];\n    > f( arr, done )\n    2000\n    1500\n    1000\n    750\n    [ [ 'even', 2, 0.5 ], [ 'odd', 2, 0.5 ] ]\n\n    See Also\n    --------\n    countByAsync, groupByAsync, tabulateBy","thunk":"\nthunk( fcn[, ...args] )\n    Returns a thunk.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to convert to a thunk.\n\n    args: ...any (optional)\n        Function arguments.\n\n    Returns\n    -------\n    out: Function\n        Thunk.\n\n    Examples\n    --------\n    > var fcn = thunk( base.add, 2, 3 );\n    > var v = fcn()\n    5\n    > v = fcn()\n    5\n\n","tic":"\ntic()\n    Returns a high-resolution time.\n\n    The returned array has the following format: `[seconds, nanoseconds]`.\n\n    Returns\n    -------\n    out: Array<integer>\n        High resolution time.\n\n    Examples\n    --------\n    > var t = tic()\n    [ <number>, <number> ]\n\n    See Also\n    --------\n    toc\n","timeit":"\ntimeit( code, [options,] clbk )\n    Times a snippet.\n\n    If the `asynchronous` option is set to `true`, the implementation assumes\n    that `before`, `after`, and `code` snippets are all asynchronous.\n    Accordingly, these snippets should invoke a `next( [error] )` callback\n    once complete. The implementation wraps the snippet within a function\n    accepting two arguments: `state` and `next`.\n\n    The `state` parameter is simply an empty object which allows the `before`,\n    `after`, and `code` snippets to share state.\n\n    Notes:\n\n    - Snippets always run in strict mode.\n    - Always verify results. Doing so prevents the compiler from performing dead\n      code elimination and other optimization techniques, which would render\n      timing results meaningless.\n    - Executed code is not sandboxed and has access to the global state. You are\n      strongly advised against timing untrusted code. To time untrusted code,\n      do so in an isolated environment (e.g., a separate process with restricted\n      access to both global state and the host environment).\n    - Wrapping asynchronous code does add overhead, but, in most cases, the\n      overhead should be negligible compared to the execution cost of the timed\n      snippet.\n    - When the `asynchronous` option is `true`, ensure that the main `code`\n      snippet is actually asynchronous. If a snippet releases the zalgo, an\n      error complaining about exceeding the maximum call stack size is highly\n      likely.\n    - While many benchmark frameworks calculate various statistics over raw\n      timing results (e.g., mean and standard deviation), do not do this.\n      Instead, consider the fastest time an approximate lower bound for how fast\n      an environment can execute a snippet. Slower times are more likely\n      attributable to other processes interfering with timing accuracy rather\n      than attributable to variability in JavaScript's speed. In which case, the\n      minimum time is most likely the only result of interest. When considering\n      all raw timing results, apply common sense rather than statistics.\n\n    Parameters\n    ----------\n    code: string\n         Snippet to time.\n\n    options: Object (optional)\n        Options.\n\n    options.before: string (optional)\n        Setup code. Default: `''`.\n\n    options.after: string (optional)\n        Cleanup code. Default: `''`.\n\n    options.iterations: integer|null (optional)\n        Number of iterations. If `null`, the number of iterations is determined\n        by trying successive powers of `10` until the total time is at least\n        `0.1` seconds. Default: `1e6`.\n\n    options.repeats: integer (optional)\n        Number of repeats. Default: `3`.\n\n    options.asynchronous: boolean (optional)\n        Boolean indicating whether a snippet is asynchronous. Default: `false`.\n\n    clbk: Function\n        Callback to invoke upon completion.\n\n    Examples\n    --------\n    > var code = 'var x = Math.pow( Math.random(), 3 );';\n    > code += 'if ( x !== x ) {';\n    > code += 'throw new Error( \\'Something went wrong.\\' );';\n    > code += '}';\n    > function done( error, results ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.dir( results );\n    ... };\n    > timeit( code, done )\n    e.g.,\n    {\n        \"iterations\": 1000000,\n        \"repeats\": 3,\n        \"min\": [ 0, 135734733 ],    // [seconds,nanoseconds]\n        \"elapsed\": 0.135734733,     // seconds\n        \"rate\": 7367311.062526641,  // iterations/second\n        \"times\": [                  // raw timing results\n            [ 0, 145641393 ],\n            [ 0, 135734733 ],\n            [ 0, 140462721 ]\n        ]\n    }\n\n","tmpdir":"\ntmpdir()\n    Returns the directory for storing temporary files.\n\n    Returns\n    -------\n    dir: string\n        Directory for temporary files.\n\n    Examples\n    --------\n    > var dir = tmpdir()\n    e.g., '/path/to/temporary/files/directory'\n\n    See Also\n    --------\n    configdir, homedir\n","toc":"\ntoc( time )\n    Returns a high-resolution time difference, where `time` is a two-element\n    array with format `[seconds, nanoseconds]`.\n\n    Similar to `time`, the returned array has format `[seconds, nanoseconds]`.\n\n    Parameters\n    ----------\n    time: Array<integer>\n        High-resolution time.\n\n    Returns\n    -------\n    out: Array<integer>\n        High resolution time difference.\n\n    Examples\n    --------\n    > var start = tic();\n    > var delta = toc( start )\n    [ <number>, <number> ]\n\n    See Also\n    --------\n    tic\n","tokenize":"\ntokenize( str[, keepWhitespace] )\n    Tokenizes a string.\n\n    To include whitespace characters (spaces, tabs, line breaks) in the output\n    array, set `keepWhitespace` to `true`.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    keepWhitespace: boolean (optional)\n        Boolean indicating whether whitespace characters should be returned as\n        part of the token array. Default: `false`.\n\n    Returns\n    -------\n    out: Array\n        Array of tokens.\n\n    Examples\n    --------\n    > var out = tokenize( 'Hello Mrs. Maple, could you call me back?' )\n    [ 'Hello', 'Mrs.', 'Maple', ',', 'could', 'you', 'call', 'me', 'back', '?' ]\n\n    > out = tokenize( 'Hello World!', true )\n    [ 'Hello', ' ', 'World', '!' ]\n\n","transformStream":"\ntransformStream( [options] )\n    Returns a transform stream.\n\n    If a transform function is not provided, the returned stream will be a\n    simple pass through stream.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.transform: Function (optional)\n        Callback to invoke upon receiving a new chunk.\n\n    options.flush: Function (optional)\n        Callback to invoke after receiving all chunks and prior to a stream\n        closing.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to decode strings into Buffer objects when writing.\n        Default: true.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream.\n\n    Examples\n    --------\n    > var s = transformStream();\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();\n\n\ntransformStream.factory( [options] )\n    Returns a function for creating transform streams.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to decode strings into Buffer objects when writing.\n        Default: true.\n\n    Returns\n    -------\n    createStream( transform[, flush] ): Function\n        Function for creating transform streams.\n\n    Examples\n    --------\n    > var opts = { 'highWaterMark': 64 };\n    > var createStream = transformStream.factory( opts );\n    > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n    > var s = createStream( fcn );\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();\n\n\ntransformStream.objectMode( [options] )\n    Returns an \"objectMode\" transform stream.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.transform: Function (optional)\n        Callback to invoke upon receiving a new chunk.\n\n    options.flush: Function (optional)\n        Callback to invoke after receiving all chunks and prior to a stream\n        closing.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to decode strings into Buffer objects when writing.\n        Default: true.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > var s = transformStream.objectMode();\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();\n\n\ntransformStream.ctor( [options] )\n    Returns a custom transform stream constructor.\n\n    If provided `transform` and `flush` options, these methods are bound to the\n    constructor prototype.\n\n    If not provided a transform function, the returned constructor creates\n    simple pass through streams.\n\n    The returned constructor accepts the same options as the constructor\n    factory, *except* for the `transform` and `flush` options, which are not\n    supported.\n\n    Any options provided to the constructor *override* options provided to the\n    constructor factory.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.transform: Function (optional)\n        Callback to invoke upon receiving a new chunk.\n\n    options.flush: Function (optional)\n        Callback to invoke after receiving all chunks and prior to a stream\n        closing.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to decode strings into Buffer objects when writing.\n        Default: true.\n\n    Returns\n    -------\n    ctor: Function\n        Custom transform stream constructor.\n\n    Examples\n    --------\n    > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n    > var opts = { 'highWaterMark': 64, 'transform': fcn };\n    > var customStream = transformStream.ctor( opts );\n    > var s = customStream();\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();\n\n","transformStream.factory":"\ntransformStream.factory( [options] )\n    Returns a function for creating transform streams.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to decode strings into Buffer objects when writing.\n        Default: true.\n\n    Returns\n    -------\n    createStream( transform[, flush] ): Function\n        Function for creating transform streams.\n\n    Examples\n    --------\n    > var opts = { 'highWaterMark': 64 };\n    > var createStream = transformStream.factory( opts );\n    > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n    > var s = createStream( fcn );\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();","transformStream.objectMode":"\ntransformStream.objectMode( [options] )\n    Returns an \"objectMode\" transform stream.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.transform: Function (optional)\n        Callback to invoke upon receiving a new chunk.\n\n    options.flush: Function (optional)\n        Callback to invoke after receiving all chunks and prior to a stream\n        closing.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to decode strings into Buffer objects when writing.\n        Default: true.\n\n    Returns\n    -------\n    stream: TransformStream\n        Transform stream operating in \"objectMode\".\n\n    Examples\n    --------\n    > var s = transformStream.objectMode();\n    > s.write( { 'value': 'a' } );\n    > s.write( { 'value': 'b' } );\n    > s.write( { 'value': 'c' } );\n    > s.end();","transformStream.ctor":"\ntransformStream.ctor( [options] )\n    Returns a custom transform stream constructor.\n\n    If provided `transform` and `flush` options, these methods are bound to the\n    constructor prototype.\n\n    If not provided a transform function, the returned constructor creates\n    simple pass through streams.\n\n    The returned constructor accepts the same options as the constructor\n    factory, *except* for the `transform` and `flush` options, which are not\n    supported.\n\n    Any options provided to the constructor *override* options provided to the\n    constructor factory.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Options.\n\n    options.transform: Function (optional)\n        Callback to invoke upon receiving a new chunk.\n\n    options.flush: Function (optional)\n        Callback to invoke after receiving all chunks and prior to a stream\n        closing.\n\n    options.objectMode: boolean (optional)\n        Specifies whether a stream should operate in \"objectMode\". Default:\n        false.\n\n    options.highWaterMark: integer (optional)\n        Specifies the maximum number of bytes to store in an internal buffer\n        before ceasing to push downstream.\n\n    options.allowHalfOpen: boolean (optional)\n        Specifies whether a stream should remain open even if one side ends.\n        Default: false.\n\n    options.decodeStrings: boolean (optional)\n        Specifies whether to decode strings into Buffer objects when writing.\n        Default: true.\n\n    Returns\n    -------\n    ctor: Function\n        Custom transform stream constructor.\n\n    Examples\n    --------\n    > function fcn( chunk, enc, cb ) { cb( null, chunk.toString()+'-beep' ); };\n    > var opts = { 'highWaterMark': 64, 'transform': fcn };\n    > var customStream = transformStream.ctor( opts );\n    > var s = customStream();\n    > s.write( 'a' );\n    > s.write( 'b' );\n    > s.write( 'c' );\n    > s.end();","trim":"\ntrim( str )\n    Trims whitespace from the beginning and end of a `string`.\n\n    \"Whitespace\" is defined as the following characters:\n\n    - \\f\n    - \\n\n    - \\r\n    - \\t\n    - \\v\n    - \\u0020\n    - \\u00a0\n    - \\u1680\n    - \\u2000-\\u200a\n    - \\u2028\n    - \\u2029\n    - \\u202f\n    - \\u205f\n    - \\u3000\n    - \\ufeff\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Trimmed string.\n\n    Examples\n    --------\n    > var out = trim( ' \\t\\t\\n  Beep \\r\\n\\t  ' )\n    'Beep'\n\n    See Also\n    --------\n    ltrim, pad, rtrim\n","truncate":"\ntruncate( str, len[, ending] )\n    Truncates a string to a specified length.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    len: integer\n        Output string length.\n\n    ending: string (optional)\n        Custom ending. Default: '...'.\n\n    Returns\n    -------\n    out: string\n        Truncated string.\n\n    Examples\n    --------\n    > var str = 'beep boop';\n    > var out = truncate( str, 5 )\n    'be...'\n\n    > out = truncate( str, 5, '|' )\n    'beep|'\n\n    See Also\n    --------\n    truncateMiddle","truncateMiddle":"\ntruncateMiddle( str, len[, seq] )\n    Truncates a string in the middle to a specified length.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    len: integer\n        Output string length.\n\n    seq: string (optional)\n        Custom replacement sequence. Default: '...'.\n\n    Returns\n    -------\n    out: string\n        Truncated string.\n\n    Examples\n    --------\n    > var str = 'beep boop';\n    > var out = truncateMiddle( str, 5 )\n    'b...p'\n\n    > out = truncateMiddle( str, 5, '|' )\n    'be|op'\n\n    See Also\n    --------\n    truncate","trycatch":"\ntrycatch( x, y )\n    If a function does not throw, returns the function return value; otherwise,\n    returns `y`.\n\n    Parameters\n    ----------\n    x: Function\n        Function to try invoking.\n\n    y: any\n        Value to return if a function throws an error.\n\n    Returns\n    -------\n    z: any\n        Either the return value of `x` or the provided argument `y`.\n\n    Examples\n    --------\n    > function x() {\n    ...     if ( base.random.randu() < 0.5 ) {\n    ...         throw new Error( 'beep' );\n    ...     }\n    ...     return 1.0;\n    ... };\n    > var z = trycatch( x, -1.0 )\n    <number>\n\n    See Also\n    --------\n    trycatchAsync, trythen\n","trycatchAsync":"\ntrycatchAsync( x, y, done )\n    If a function does not return an error, invokes a callback with the function\n    result; otherwise, invokes a callback with a value `y`.\n\n    A function `x` is provided a single argument:\n\n    - clbk: callback to invoke upon function completion.\n\n    The callback function accepts two arguments:\n\n    - error: error object.\n    - result: function result.\n\n    The `done` callback is invoked upon function completion and is provided two\n    arguments:\n\n    - error: error object.\n    - result: either the result of `x` or the provided argument `y`.\n\n    If `x` invokes `clbk` with an error argument, the function invokes the\n    `done` callback with both the error and the argument `y`.\n\n    If `x` does not invoke `clbk` with an error argument, the function invokes\n    the `done` callback with a first argument equal to `null` and the function\n    `result`.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Parameters\n    ----------\n    x: Function\n        Function to invoke.\n\n    y: any\n        Value to return if `x` returns an error.\n\n    done: Function\n        Callback to invoke upon completion.\n\n    Examples\n    --------\n    > function x( clbk ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         clbk( new Error( 'beep' ) );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         // process error...\n    ...     }\n    ...     console.log( result );\n    ... };\n    > trycatchAsync( x, 'boop', done )\n    'boop'\n\n    See Also\n    --------\n    trycatch, trythenAsync\n","tryFunction":"\ntryFunction( fcn[, thisArg] )\n    Wraps a function in a try/catch block.\n\n    If provided an asynchronous function, the returned function only traps\n    errors which occur during the current event loop tick.\n\n    If a function throws a literal, the literal is serialized as a string and\n    returned as an `Error` object.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to wrap.\n\n    thisArg: any (optional)\n        Function context.\n\n    Returns\n    -------\n    out: Function\n        Wrapped function.\n\n    Examples\n    --------\n    > function fcn() { throw new Error( 'beep boop' ); };\n    > var f = tryFunction( fcn );\n    > var out = f();\n    > out.message\n    'beep boop'\n\n","tryRequire":"\ntryRequire( id )\n    Wraps `require` in a `try/catch` block.\n\n    This function traps and returns any errors encountered when attempting to\n    require a module.\n\n    Use caution when attempting to resolve a relative path or a local module.\n    This function attempts to resolve a module from its current path. Thus, the\n    function is unable to resolve anything which is not along its search path.\n    For local requires, use an absolute file path.\n\n    Parameters\n    ----------\n    id: string\n        Module id.\n\n    Returns\n    -------\n    out: any|Error\n        Resolved module or an `Error`.\n\n    Examples\n    --------\n    > var out = tryRequire( '_unknown_module_id_' )\n    <Error>\n\n","trythen":"\ntrythen( x, y )\n    If a function does not throw, returns the function return value; otherwise,\n    returns the value returned by a second function `y`.\n\n    The function `y` is provided a single argument:\n\n    - error: the error thrown by `x`.\n\n    Parameters\n    ----------\n    x: Function\n        Function to try invoking.\n\n    y: Function\n        Function to invoke if an initial function throws an error.\n\n    Returns\n    -------\n    z: any\n        The return value of either `x` or `y`.\n\n    Examples\n    --------\n    > function x() {\n    ...     if ( base.random.randu() < 0.5 ) {\n    ...         throw new Error( 'beep' );\n    ...     }\n    ...     return 1.0;\n    ... };\n    > function y() {\n    ...     return -1.0;\n    ... };\n    > var z = trythen( x, y )\n    <number>\n\n    See Also\n    --------\n    trycatch, trythenAsync\n","trythenAsync":"\ntrythenAsync( x, y, done )\n    If a function does not return an error, invokes a callback with the function\n    result; otherwise, invokes a second function `y`.\n\n    A function `x` is provided a single argument:\n\n    - clbk: callback to invoke upon function completion.\n\n    The callback function accepts any number of arguments, with the first\n    argument reserved for providing an error.\n\n    If the error argument is falsy, the function invokes a `done` callback with\n    its first argument as `null` and all other provided arguments.\n\n    If the error argument is truthy, the function invokes a function `y`. The\n    number of arguments provided to `y` depends on the function's length. If `y`\n    is a unary function, `y` is provided a single argument:\n\n    - clbk: callback to invoke upon function completion.\n\n    Otherwise, `y` is provided two arguments:\n\n    - error: the error from `x`.\n    - clbk: callback to invoke upon function completion.\n\n    The callback function accepts any number of arguments, with the first\n    argument reserved for providing an error.\n\n    If the error argument is falsy, the `done` callback is invoked with its\n    first argument equal to `null` and all other arguments provided by `y`.\n\n    If the error argument is truthy, the `done` callback is invoked with only\n    the error argument provided by `y`.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Parameters\n    ----------\n    x: Function\n        Function to invoke.\n\n    y: Function\n        Function to invoke if `x` returns an error.\n\n    done: Function\n        Callback to invoke upon completion.\n\n    Examples\n    --------\n    > function x( clbk ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         clbk( new Error( 'beep' ) );\n    ...     }\n    ... };\n    > function y( clbk ) {\n    ...     setTimeout( onTimeout, 0 );\n    ...     function onTimeout() {\n    ...         clbk( null, 'boop' );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > trythenAsync( x, y, done )\n    'boop'\n\n    See Also\n    --------\n    trycatchAsync, trythen\n","ttest":"\nttest( x[, y][, options] )\n    Computes a one-sample or paired Student's t test.\n\n    When no `y` is supplied, the function performs a one-sample t-test for the\n    null hypothesis that the data in array or typed array `x` is drawn from a\n    normal distribution with mean zero and unknown variance.\n\n    When array or typed array `y` is supplied, the function tests whether the\n    differences `x - y` come from a normal distribution with mean zero and\n    unknown variance via the paired t-test.\n\n    The returned object comes with a `.print()` method which when invoked will\n    print a formatted output of the results of the hypothesis test.\n\n    Parameters\n    ----------\n    x: Array<number>\n        Data array.\n\n    y: Array<number> (optional)\n        Paired data array.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.alternative: string (optional)\n        Indicates whether the alternative hypothesis is that the mean of `x` is\n        larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n        `mu` (`two-sided`). Default: `'two-sided'`.\n\n    options.mu: number (optional)\n        Hypothesized true mean under the null hypothesis. Set this option to\n        test whether the data comes from a distribution with the specified `mu`.\n        Default: `0`.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Used significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.ci: Array<number>\n        1-alpha confidence interval for the mean.\n\n    out.nullValue: number\n        Assumed mean under H0 (or difference in means when `y` is supplied).\n\n    out.alternative: string\n        Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n    out.df: number\n        Degrees of freedom.\n\n    out.mean: number\n        Sample mean of `x` or `x - y`, respectively.\n\n    out.sd: number\n        Standard error of the mean.\n\n    out.method: string\n        Name of test.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    // One-sample t-test:\n    > var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 5776 } );\n    > var x = new Array( 100 );\n    > for ( var i = 0; i < x.length; i++ ) {\n    ...     x[ i ] = rnorm();\n    ... }\n    > var out = ttest( x )\n    {\n        rejected: false,\n        pValue: ~0.722,\n        statistic: ~0.357,\n        ci: [~-0.333,~0.479],\n        // ...\n    }\n\n    // Paired t-test:\n    > rnorm = base.random.normal.factory( 1.0, 2.0, { 'seed': 786 } );\n    > x = new Array( 100 );\n    > var y = new Array( 100 );\n    > for ( i = 0; i < x.length; i++ ) {\n    ...     x[ i ] = rnorm();\n    ...     y[ i ] = rnorm();\n    ... }\n    > out = ttest( x, y )\n    {\n        rejected: false,\n        pValue: ~0.191,\n        statistic: ~1.315,\n        ci: [ ~-0.196, ~0.964 ],\n        // ...\n    }\n\n    // Print formatted output:\n    > var table = out.print()\n    Paired t-test\n\n    Alternative hypothesis: True difference in means is not equal to 0\n\n        pValue: 0.1916\n        statistic: 1.3148\n        df: 99\n        95% confidence interval: [-0.1955,0.9635]\n\n    Test Decision: Fail to reject null in favor of alternative at 5%\n    significance level\n\n    // Choose custom significance level:\n    > var arr = [ 2, 4, 3, 1, 0 ];\n    > out = ttest( arr, { 'alpha': 0.01 } );\n    > table = out.print()\n    One-sample t-test\n\n    Alternative hypothesis: True mean is not equal to 0\n\n        pValue: 0.0474\n        statistic: 2.8284\n        df: 4\n        99% confidence interval: [-1.2556,5.2556]\n\n    Test Decision: Fail to reject null in favor of alternative at 1%\n    significance level\n\n    // Test for a mean equal to five:\n    > arr = [ 4, 4, 6, 6, 5 ];\n    > out = ttest( arr, { 'mu': 5 } )\n    {\n        rejected: false,\n        pValue: 1,\n        statistic: 0,\n        ci: [ ~3.758, ~6.242 ],\n        // ...\n    }\n\n    // Perform one-sided tests:\n    > arr = [ 4, 4, 6, 6, 5 ];\n    > out = ttest( arr, { 'alternative': 'less' } );\n    > table = out.print()\n    One-sample t-test\n\n    Alternative hypothesis: True mean is less than 0\n\n        pValue: 0.9998\n        statistic: 11.1803\n        df: 4\n        95% confidence interval: [-Infinity,5.9534]\n\n    Test Decision: Fail to reject null in favor of alternative at 5%\n    significance level\n\n    > out = ttest( arr, { 'alternative': 'greater' } );\n    > table = out.print()\n    One-sample t-test\n\n    Alternative hypothesis: True mean is greater than 0\n\n        pValue: 0.0002\n        statistic: 11.1803\n        df: 4\n        95% confidence interval: [4.0466,Infinity]\n\n    Test Decision: Reject null in favor of alternative at 5% significance level\n\n    See Also\n    --------\n    ttest2\n","ttest2":"\nttest2( x, y[, options] )\n    Computes a two-sample Student's t test.\n\n    By default, the function performs a two-sample t-test for the null\n    hypothesis that the data in arrays or typed arrays `x` and `y` is\n    independently drawn from normal distributions with equal means.\n\n    The returned object comes with a `.print()` method which when invoked will\n    print a formatted output of the results of the hypothesis test.\n\n    Parameters\n    ----------\n    x: Array<number>\n        First data array.\n\n    y: Array<number>\n        Second data array.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.alternative: string (optional)\n        Either `two-sided`, `less` or `greater`. Indicates whether the\n        alternative hypothesis is that `x` has a larger mean than `y`\n        (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n        the same (`two-sided`). Default: `'two-sided'`.\n\n    options.difference: number (optional)\n        Number denoting the difference in means under the null hypothesis.\n        Default: `0`.\n\n    options.variance: string (optional)\n        String indicating if the test should be conducted under the assumption\n        that the unknown variances of the normal distributions are `equal` or\n        `unequal`. As a default choice, the function carries out the Welch test\n        (using the Satterthwaite approximation for the degrees of freedom),\n        which does not have the requirement that the variances of the underlying\n        distributions are equal. If the equal variances assumption seems\n        warranted, set the option to `equal`. Default: `unequal`.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Used significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.ci: Array<number>\n        1-alpha confidence interval for the mean.\n\n    out.nullValue: number\n        Assumed difference in means under H0.\n\n    out.xmean: number\n        Sample mean of `x`.\n\n    out.ymean: number\n        Sample mean of `y`.\n\n    out.alternative: string\n        Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n    out.df: number\n        Degrees of freedom.\n\n    out.method: string\n        Name of test.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    // Student's sleep data:\n    > var x = [ 0.7, -1.6, -0.2, -1.2, -0.1, 3.4, 3.7, 0.8, 0.0, 2.0 ];\n    > var y = [ 1.9, 0.8, 1.1, 0.1, -0.1, 4.4, 5.5, 1.6, 4.6, 3.4 ];\n    > var out = ttest2( x, y )\n    {\n        rejected: false,\n        pValue: ~0.079,\n        statistic: ~-1.861,\n        ci: [ ~-3.365, ~0.205 ],\n        // ...\n    }\n\n    // Print table output:\n    > var table = out.print()\n    Welch two-sample t-test\n\n    Alternative hypothesis: True difference in means is not equal to 0\n\n        pValue: 0.0794\n        statistic: -1.8608\n        95% confidence interval: [-3.3655,0.2055]\n\n    Test Decision: Fail to reject null in favor of alternative at 5%\n    significance level\n\n    // Choose a different significance level than `0.05`:\n    > out = ttest2( x, y, { 'alpha': 0.1 } );\n    > table = out.print()\n    Welch two-sample t-test\n\n    Alternative hypothesis: True difference in means is not equal to 0\n\n        pValue: 0.0794\n        statistic: -1.8608\n        90% confidence interval: [-3.0534,-0.1066]\n\n    Test Decision: Reject null in favor of alternative at 10% significance level\n\n    // Perform one-sided tests:\n    > out = ttest2( x, y, { 'alternative': 'less' } );\n    > table = out.print()\n    Welch two-sample t-test\n\n    Alternative hypothesis: True difference in means is less than 0\n\n        pValue: 0.0397\n        statistic: -1.8608\n        df: 17.7765\n        95% confidence interval: [-Infinity,-0.1066]\n\n    Test Decision: Reject null in favor of alternative at 5% significance level\n\n    > out = ttest2( x, y, { 'alternative': 'greater' } );\n    > table = out.print()\n    Welch two-sample t-test\n\n    Alternative hypothesis: True difference in means is greater than 0\n\n        pValue: 0.9603\n        statistic: -1.8608\n        df: 17.7765\n        95% confidence interval: [-3.0534,Infinity]\n\n    Test Decision: Fail to reject null in favor of alternative at 5%\n    significance level\n\n    // Run tests with equal variances assumption:\n    > x = [ 2, 3, 1, 4 ];\n    > y = [ 1, 2, 3, 1, 2, 5, 3, 4 ];\n    > out = ttest2( x, y, { 'variance': 'equal' } );\n    > table = out.print()\n    Two-sample t-test\n\n    Alternative hypothesis: True difference in means is not equal to 0\n\n        pValue: 0.8848\n        statistic: -0.1486\n        df: 10\n        95% confidence interval: [-1.9996,1.7496]\n\n    Test Decision: Fail to reject null in favor of alternative at 5%\n    significance level\n\n    // Test for a difference in means besides zero:\n    > var rnorm = base.random.normal.factory({ 'seed': 372 } );\n    > x = new Array( 100 );\n    > for ( i = 0; i < x.length; i++ ) {\n    ...     x[ i ] = rnorm( 2.0, 3.0 );\n    ... }\n    > y = new Array( 100 );\n    > for ( i = 0; i < x.length; i++ ) {\n    ...     y[ i ] = rnorm( 1.0, 3.0 );\n    ... }\n    > out = ttest2( x, y, { 'difference': 1.0, 'variance': 'equal' } )\n    {\n        rejected: false,\n        pValue: ~0.642,\n        statistic: ~-0.466,\n        ci: [ ~-0.0455, ~1.646 ],\n        // ...\n    }\n\n    See Also\n    --------\n    ttest\n","TWO_PI":"\nTWO_PI\n    The mathematical constant `π` times `2`.\n\n    Examples\n    --------\n    > TWO_PI\n    6.283185307179586\n\n    See Also\n    --------\n    PI\n","typedarray":"\ntypedarray( [dtype] )\n    Creates a typed array.\n\n    Parameters\n    ----------\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = typedarray()\n    <Float64Array>\n    > arr = typedarray( 'float32' )\n    <Float32Array>\n\n\ntypedarray( length[, dtype] )\n    Returns a typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = typedarray( 5 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n    > arr = typedarray( 5, 'int32' )\n    <Int32Array>[ 0, 0, 0, 0, 0 ]\n\n\ntypedarray( typedarray[, dtype] )\n    Creates a typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = typedarray( [ 0.5, 0.5, 0.5 ] );\n    > var arr2 = typedarray( arr1, 'float32' )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]\n\n\ntypedarray( obj[, dtype] )\n    Creates a typed array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a typed array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 0.5, 0.5, 0.5 ];\n    > var arr2 = typedarray( arr1, 'float32' )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]\n\n\ntypedarray( buffer[, byteOffset[, length]][, dtype] )\n    Returns a typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 16 );\n    > var arr = typedarray( buf, 0, 4, 'float32' )\n    <Float32Array>[ 0.0, 0.0, 0.0, 0.0 ]\n\n    See Also\n    --------\n    Complex128Array, Complex64Array, Float64Array, Float32Array, Int32Array, Uint32Array, Int16Array, Uint16Array, Int8Array, Uint8Array, Uint8ClampedArray\n","typedarray2json":"\ntypedarray2json( arr )\n    Returns a JSON representation of a typed array.\n\n    The following typed array types are supported:\n\n    - Float64Array\n    - Float32Array\n    - Int32Array\n    - Uint32Array\n    - Int16Array\n    - Uint16Array\n    - Int8Array\n    - Uint8Array\n    - Uint8ClampedArray\n    - Complex64Array\n    - Complex128Array\n    - BooleanArray\n\n    The returned JSON object has the following properties:\n\n    - type: typed array type.\n    - data: typed array data as a generic array.\n\n    The implementation supports custom typed arrays and sets the `type` field to\n    the closest known typed array type.\n\n    Parameters\n    ----------\n    arr: TypedArray\n        Typed array to serialize.\n\n    Returns\n    -------\n    out: Object\n        JSON representation.\n\n    Examples\n    --------\n    > var arr = new Float64Array( 2 );\n    > arr[ 0 ] = 5.0;\n    > arr[ 1 ] = 3.0;\n    > var json = typedarray2json( arr )\n    { 'type': 'Float64Array', 'data': [ 5.0, 3.0 ] }\n\n    See Also\n    --------\n    reviveTypedArray\n","typedarrayCtors":"\ntypedarrayCtors( dtype )\n    Returns a typed array constructor.\n\n    The function returns constructors for the following data types:\n\n    - float32: single-precision floating-point numbers.\n    - float64: double-precision floating-point numbers.\n    - complex64: single-precision complex floating-point numbers.\n    - complex128: double-precision complex floating-point numbers.\n    - bool: boolean values.\n    - int16: signed 16-bit integers.\n    - int32: signed 32-bit integers.\n    - int8: signed 8-bit integers.\n    - uint16: unsigned 16-bit integers.\n    - uint32: unsigned 32-bit integers.\n    - uint8: unsigned 8-bit integers.\n    - uint8c: unsigned clamped 8-bit integers.\n\n    Parameters\n    ----------\n    dtype: string\n        Data type.\n\n    Returns\n    -------\n    out: Function|null\n        Typed array constructor.\n\n    Examples\n    --------\n    > var ctor = typedarrayCtors( 'float64' )\n    <Function>\n    > ctor = typedarrayCtors( 'float' )\n    null\n\n    See Also\n    --------\n    arrayCtors\n","typedarrayDataTypes":"\ntypedarrayDataTypes()\n    Returns a list of typed array data types.\n\n    Returns\n    -------\n    out: Array<string>\n        List of typed array data types.\n\n    Examples\n    --------\n    > var out = typedarrayDataTypes()\n    <Array>\n\n    See Also\n    --------\n    arrayDataTypes, ndarrayDataTypes\n","typedarraypool":"\ntypedarraypool( [dtype] )\n    Returns an uninitialized typed array from a typed array memory pool.\n\n    Memory is **uninitialized**, which means that the contents of a returned\n    typed array may contain sensitive contents.\n\n    Parameters\n    ----------\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr = typedarraypool()\n    <Float64Array>[]\n    > arr = typedarraypool( 'float32' )\n    <Float32Array>[]\n\n\ntypedarraypool( length[, dtype] )\n    Returns an uninitialized typed array having a specified length from a typed\n    array memory pool.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr = typedarraypool( 5 )\n    <Float64Array>\n    > arr = typedarraypool( 5, 'int32' )\n    <Int32Array>\n\n\ntypedarraypool( typedarray[, dtype] )\n    Creates a pooled typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr1 = typedarraypool( [ 0.5, 0.5, 0.5 ] );\n    > var arr2 = typedarraypool( arr1, 'float32' )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool( obj[, dtype] )\n    Creates a pooled typed array from an array-like object.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object from which to generate a typed array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr1 = [ 0.5, 0.5, 0.5 ];\n    > var arr2 = typedarraypool( arr1, 'float32' )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.malloc( [dtype] )\n    Returns an uninitialized typed array from a typed array memory pool.\n\n    This method shares the same security vulnerabilities mentioned above.\n\n    Parameters\n    ----------\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr = typedarraypool.malloc()\n    <Float64Array>\n    > arr = typedarraypool.malloc( 'float32' )\n    <Float32Array>\n\n\ntypedarraypool.malloc( length[, dtype] )\n    Returns a typed array having a specified length from a typed array memory\n    pool.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr = typedarraypool.malloc( 5 )\n    <Float64Array>\n    > arr = typedarraypool.malloc( 5, 'int32' )\n    <Int32Array>\n\n\ntypedarraypool.malloc( typedarray[, dtype] )\n    Creates a pooled typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr1 = typedarraypool.malloc( [ 0.5, 0.5, 0.5 ] );\n    > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.malloc( obj[, dtype] )\n    Creates a pooled typed array from an array-like object.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object from which to generate a typed array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr1 = [ 0.5, 0.5, 0.5 ];\n    > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]\n\n\ntypedarraypool.calloc( [dtype] )\n    Returns a zero-initialized typed array from a typed array memory pool.\n\n    Parameters\n    ----------\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr = typedarraypool.calloc()\n    <Float64Array>[]\n    > arr = typedarraypool.calloc( 'float32' )\n    <Float32Array>[]\n\n\ntypedarraypool.calloc( length[, dtype] )\n    Returns a zero-initialized typed array having a specified length from a\n    typed array memory pool.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr = typedarraypool.calloc( 5 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n    > arr = typedarraypool.calloc( 5, 'int32' )\n    <Int32Array>[ 0, 0, 0, 0, 0 ]\n\n\ntypedarraypool.free( buf )\n    Frees a typed array or typed array buffer for use in a future allocation.\n\n    Parameters\n    ----------\n    buf: TypedArray|ArrayBuffer\n        Typed array or typed array buffer to free.\n\n    Examples\n    --------\n    > var arr = typedarraypool( 5 )\n    <Float64Array>\n    > typedarraypool.free( arr );\n\n\ntypedarraypool.clear()\n    Clears the typed array pool allowing garbage collection of previously\n    allocated (and currently free) array buffers.\n\n    Examples\n    --------\n    > var arr = typedarraypool( 5 )\n    <Float64Array>\n    > typedarraypool.free( arr );\n    > typedarraypool.clear();\n\n\ntypedarraypool.highWaterMark\n    Read-only property returning the pool's high water mark.\n\n    Once a high water mark is reached, typed array allocation fails.\n\n    Examples\n    --------\n    > typedarraypool.highWaterMark\n    <number>\n\n\ntypedarraypool.nbytes\n    Read-only property returning the total number of allocated bytes.\n\n    The returned value is the total accumulated value. Hence, anytime a pool\n    must allocate a new array buffer (i.e., more memory), the pool increments\n    this value.\n\n    The only time this value is decremented is when a pool is cleared.\n\n    This behavior means that, while allocated buffers which are never freed may,\n    in fact, be garbage collected, they continue to count against the high water\n    mark limit.\n\n    Accordingly, you should *always* free allocated buffers in order to prevent\n    the pool from believing that non-freed buffers are continually in use.\n\n    Examples\n    --------\n    > var arr = typedarraypool( 5 )\n    <Float64Array>\n    > typedarraypool.nbytes\n    <number>\n\n\ntypedarraypool.factory( [options] )\n    Creates a typed array pool.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.highWaterMark: integer (optional)\n        Maximum total memory (in bytes) which can be allocated.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating typed arrays from a typed array memory pool.\n\n    Examples\n    --------\n    > var pool = typedarraypool.factory();\n    > var arr1 = pool( 3, 'float64' )\n    <Float64Array>\n\n    See Also\n    --------\n    typedarray\n","typedarraypool.malloc":"\ntypedarraypool.malloc( [dtype] )\n    Returns an uninitialized typed array from a typed array memory pool.\n\n    This method shares the same security vulnerabilities mentioned above.\n\n    Parameters\n    ----------\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr = typedarraypool.malloc()\n    <Float64Array>\n    > arr = typedarraypool.malloc( 'float32' )\n    <Float32Array>typedarraypool.malloc( length[, dtype] )\n    Returns a typed array having a specified length from a typed array memory\n    pool.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr = typedarraypool.malloc( 5 )\n    <Float64Array>\n    > arr = typedarraypool.malloc( 5, 'int32' )\n    <Int32Array>typedarraypool.malloc( typedarray[, dtype] )\n    Creates a pooled typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr1 = typedarraypool.malloc( [ 0.5, 0.5, 0.5 ] );\n    > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]typedarraypool.malloc( obj[, dtype] )\n    Creates a pooled typed array from an array-like object.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object from which to generate a typed array.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr1 = [ 0.5, 0.5, 0.5 ];\n    > var arr2 = typedarraypool.malloc( arr1, 'float32' )\n    <Float32Array>[ 0.5, 0.5, 0.5 ]","typedarraypool.calloc":"\ntypedarraypool.calloc( [dtype] )\n    Returns a zero-initialized typed array from a typed array memory pool.\n\n    Parameters\n    ----------\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr = typedarraypool.calloc()\n    <Float64Array>[]\n    > arr = typedarraypool.calloc( 'float32' )\n    <Float32Array>[]typedarraypool.calloc( length[, dtype] )\n    Returns a zero-initialized typed array having a specified length from a\n    typed array memory pool.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    dtype: string (optional)\n        Data type. Default: 'float64'.\n\n    Returns\n    -------\n    out: TypedArray|null\n        If the function is unable to allocate a typed array from the typed array\n        pool (e.g., due to insufficient memory), the function returns `null`.\n\n    Examples\n    --------\n    > var arr = typedarraypool.calloc( 5 )\n    <Float64Array>[ 0.0, 0.0, 0.0, 0.0, 0.0 ]\n    > arr = typedarraypool.calloc( 5, 'int32' )\n    <Int32Array>[ 0, 0, 0, 0, 0 ]","typedarraypool.free":"\ntypedarraypool.free( buf )\n    Frees a typed array or typed array buffer for use in a future allocation.\n\n    Parameters\n    ----------\n    buf: TypedArray|ArrayBuffer\n        Typed array or typed array buffer to free.\n\n    Examples\n    --------\n    > var arr = typedarraypool( 5 )\n    <Float64Array>\n    > typedarraypool.free( arr );","typedarraypool.clear":"\ntypedarraypool.clear()\n    Clears the typed array pool allowing garbage collection of previously\n    allocated (and currently free) array buffers.\n\n    Examples\n    --------\n    > var arr = typedarraypool( 5 )\n    <Float64Array>\n    > typedarraypool.free( arr );\n    > typedarraypool.clear();","typedarraypool.highWaterMark":"\ntypedarraypool.highWaterMark\n    Read-only property returning the pool's high water mark.\n\n    Once a high water mark is reached, typed array allocation fails.\n\n    Examples\n    --------\n    > typedarraypool.highWaterMark\n    <number>","typedarraypool.nbytes":"\ntypedarraypool.nbytes\n    Read-only property returning the total number of allocated bytes.\n\n    The returned value is the total accumulated value. Hence, anytime a pool\n    must allocate a new array buffer (i.e., more memory), the pool increments\n    this value.\n\n    The only time this value is decremented is when a pool is cleared.\n\n    This behavior means that, while allocated buffers which are never freed may,\n    in fact, be garbage collected, they continue to count against the high water\n    mark limit.\n\n    Accordingly, you should *always* free allocated buffers in order to prevent\n    the pool from believing that non-freed buffers are continually in use.\n\n    Examples\n    --------\n    > var arr = typedarraypool( 5 )\n    <Float64Array>\n    > typedarraypool.nbytes\n    <number>","typedarraypool.factory":"\ntypedarraypool.factory( [options] )\n    Creates a typed array pool.\n\n    Parameters\n    ----------\n    options: Object (optional)\n        Function options.\n\n    options.highWaterMark: integer (optional)\n        Maximum total memory (in bytes) which can be allocated.\n\n    Returns\n    -------\n    fcn: Function\n        Function for creating typed arrays from a typed array memory pool.\n\n    Examples\n    --------\n    > var pool = typedarraypool.factory();\n    > var arr1 = pool( 3, 'float64' )\n    <Float64Array>\n\n    See Also\n    --------\n    typedarray","typemax":"\ntypemax( dtype )\n    Returns the maximum value of a specified numeric type.\n\n    The following numeric types are supported:\n\n    - float64: double-precision floating-point numbers.\n    - float32: single-precision floating-point numbers.\n    - float16: half-precision floating-point numbers.\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n\n    Parameters\n    ----------\n    dtype: string\n        Numeric type.\n\n    Returns\n    -------\n    out: number\n        Maximum value.\n\n    Examples\n    --------\n    > var m = typemax( 'int8' )\n    127\n    > m = typemax( 'uint32' )\n    4294967295\n\n    See Also\n    --------\n    realmax, typemin\n","typemin":"\ntypemin( dtype )\n    Returns the minimum value of a specified numeric type.\n\n    The following numeric types are supported:\n\n    - float64: double-precision floating-point numbers.\n    - float32: single-precision floating-point numbers.\n    - float16: half-precision floating-point numbers.\n    - int32: 32-bit two's complement signed integers.\n    - uint32: 32-bit unsigned integers.\n    - int16: 16-bit two's complement signed integers.\n    - uint16: 16-bit unsigned integers.\n    - int8: 8-bit two's complement signed integers.\n    - uint8: 8-bit unsigned integers.\n    - uint8c: 8-bit unsigned integers clamped to 0-255.\n\n    Parameters\n    ----------\n    dtype: string\n        Numeric type.\n\n    Returns\n    -------\n    out: number\n        Minimum value.\n\n    Examples\n    --------\n    > var m = typemin( 'int8' )\n    -128\n    > m = typemin( 'uint32' )\n    0\n\n    See Also\n    --------\n    realmin, typemax\n","typeOf":"\ntypeOf( value )\n    Determines a value's type.\n\n    The following values are not natively provided in older JavaScript engines:\n\n    - Map\n    - Set\n    - WeakMap\n    - WeakSet\n    - Symbol\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    out: string\n        The value's type.\n\n    Examples\n    --------\n    // Built-ins:\n    > var t = typeOf( 'a' )\n    'string'\n    > t = typeOf( 5 )\n    'number'\n    > t = typeOf( NaN )\n    'number'\n    > t = typeOf( true )\n    'boolean'\n    > t = typeOf( false )\n    'boolean'\n    > t = typeOf( null )\n    'null'\n    > t = typeOf( undefined )\n    'undefined'\n    > t = typeOf( [] )\n    'array'\n    > t = typeOf( {} )\n    'object'\n    > t = typeOf( function noop() {} )\n    'function'\n    > t = typeOf( Symbol( 'beep' ) )\n    'symbol'\n    > t = typeOf( /.+/ )\n    'regexp'\n    > t = typeOf( new String( 'beep' ) )\n    'string'\n    > t = typeOf( new Number( 5 ) )\n    'number'\n    > t = typeOf( new Boolean( false ) )\n    'boolean'\n    > t = typeOf( new Array() )\n    'array'\n    > t = typeOf( new Object() )\n    'object'\n    > t = typeOf( new Int8Array( 10 ) )\n    'int8array'\n    > t = typeOf( new Uint8Array( 10 ) )\n    'uint8array'\n    > t = typeOf( new Uint8ClampedArray( 10 ) )\n    'uint8clampedarray'\n    > t = typeOf( new Int16Array( 10 ) )\n    'int16array'\n    > t = typeOf( new Uint16Array( 10 ) )\n    'uint16array'\n    > t = typeOf( new Int32Array( 10 ) )\n    'int32array'\n    > t = typeOf( new Uint32Array( 10 ) )\n    'uint32array'\n    > t = typeOf( new Float32Array( 10 ) )\n    'float32array'\n    > t = typeOf( new Float64Array( 10 ) )\n    'float64array'\n    > t = typeOf( new ArrayBuffer( 10 ) )\n    'arraybuffer'\n    > t = typeOf( new Date() )\n    'date'\n    > t = typeOf( new RegExp( '.+' ) )\n    'regexp'\n    > t = typeOf( new Map() )\n    'map'\n    > t = typeOf( new Set() )\n    'set'\n    > t = typeOf( new WeakMap() )\n    'weakmap'\n    > t = typeOf( new WeakSet() )\n    'weakset'\n    > t = typeOf( new Error( 'beep' ) )\n    'error'\n    > t = typeOf( new TypeError( 'beep' ) )\n    'typeerror'\n    > t = typeOf( new SyntaxError( 'beep' ) )\n    'syntaxerror'\n    > t = typeOf( new ReferenceError( 'beep' ) )\n    'referenceerror'\n    > t = typeOf( new URIError( 'beep' ) )\n    'urierror'\n    > t = typeOf( new RangeError( 'beep' ) )\n    'rangeerror'\n    > t = typeOf( new EvalError( 'beep' ) )\n    'evalerror'\n    > t = typeOf( Math )\n    'math'\n    > t = typeOf( JSON )\n    'json'\n\n    // Arguments object:\n    > function beep() { return arguments; };\n    > t = typeOf( beep() )\n    'arguments'\n\n    // Node.js Buffer object:\n    > t = typeOf( new Buffer( 10 ) )\n    'buffer'\n\n    // Custom constructor:\n    > function Person() { return this };\n    > t = typeOf( new Person() )\n    'person'\n\n    // Anonymous constructor:\n    > var Foo = function () { return this; };\n    > t = typeOf( new Foo() )\n    '' || 'foo'\n\n    See Also\n    --------\n    constructorName, nativeClass\n","UINT8_MAX":"\nUINT8_MAX\n    Maximum unsigned 8-bit integer.\n\n    The maximum unsigned 8-bit integer is given by `2^8 - 1`.\n\n    Examples\n    --------\n    > UINT8_MAX\n    255\n\n    See Also\n    --------\n    INT8_MAX\n","UINT8_NUM_BYTES":"\nUINT8_NUM_BYTES\n    Size (in bytes) of an 8-bit unsigned integer.\n\n    Examples\n    --------\n    > UINT8_NUM_BYTES\n    1\n\n    See Also\n    --------\n    INT8_NUM_BYTES, UINT16_NUM_BYTES, UINT32_NUM_BYTES\n","Uint8Array":"\nUint8Array()\n    A typed array constructor which returns a typed array representing an array\n    of 8-bit unsigned integers in the platform byte order.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array()\n    <Uint8Array>\n\n\nUint8Array( length )\n    Returns a typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( 5 )\n    <Uint8Array>[ 0, 0, 0, 0, 0 ]\n\n\nUint8Array( typedarray )\n    Creates a typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n    > var arr2 = new Uint8Array( arr1 )\n    <Uint8Array>[ 5, 5, 5 ]\n\n\nUint8Array( obj )\n    Creates a typed array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a typed array.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 5.0, 5.0, 5.0 ];\n    > var arr2 = new Uint8Array( arr1 )\n    <Uint8Array>[ 5, 5, 5 ]\n\n\nUint8Array( buffer[, byteOffset[, length]] )\n    Returns a typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 4 );\n    > var arr = new Uint8Array( buf, 0, 4 )\n    <Uint8Array>[ 0, 0, 0, 0 ]\n\n\nUint8Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Uint8Array.from( [ 1, 2 ], mapFcn )\n    <Uint8Array>[ 2, 4 ]\n\n\nUint8Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Uint8Array.of( 1, 2 )\n    <Uint8Array>[ 1, 2 ]\n\n\nUint8Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Uint8Array.BYTES_PER_ELEMENT\n    1\n\n\nUint8Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Uint8Array.name\n    'Uint8Array'\n\n\nUint8Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>\n\n\nUint8Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( 5 );\n    > arr.byteLength\n    5\n\n\nUint8Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( 5 );\n    > arr.byteOffset\n    0\n\n\nUint8Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    1\n\n\nUint8Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( 5 );\n    > arr.length\n    5\n\n\nUint8Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Uint8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2\n\n\nUint8Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true\n\n\nUint8Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false\n\n\nUint8Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Uint8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3\n\n\nUint8Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2\n\n\nUint8Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3\n\n\nUint8Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2\n\n\nUint8Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '\n\n\nUint8Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true\n\n\nUint8Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2\n\n\nUint8Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'\n\n\nUint8Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true\n\n\nUint8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3\n\n\nUint8Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Uint8Array>[ 2, 4, 6 ]\n\n\nUint8Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14\n\n\nUint8Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14\n\n\nUint8Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Uint8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] )\n    <Uint8Array>\n    > arr.reverse()\n    <Uint8Array>[ 3, 2, 1 ]\n\n\nUint8Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4\n\n\nUint8Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3\n\n\nUint8Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true\n\n\nUint8Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Uint8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Uint8Array>[ 0, 1, 1, 2, 2 ]\n\n\nUint8Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint8Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Uint8Array>[ 3, 4, 5 ]\n\n\nUint8Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'\n\n\nUint8Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'\n\n\nUint8Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8ClampedArray\n","Uint8Array.from":"\nUint8Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Uint8Array.from( [ 1, 2 ], mapFcn )\n    <Uint8Array>[ 2, 4 ]","Uint8Array.of":"\nUint8Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Uint8Array.of( 1, 2 )\n    <Uint8Array>[ 1, 2 ]","Uint8Array.BYTES_PER_ELEMENT":"\nUint8Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Uint8Array.BYTES_PER_ELEMENT\n    1","Uint8Array.name":"\nUint8Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Uint8Array.name\n    'Uint8Array'","Uint8Array.prototype.buffer":"\nUint8Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>","Uint8Array.prototype.byteLength":"\nUint8Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( 5 );\n    > arr.byteLength\n    5","Uint8Array.prototype.byteOffset":"\nUint8Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( 5 );\n    > arr.byteOffset\n    0","Uint8Array.prototype.BYTES_PER_ELEMENT":"\nUint8Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    1","Uint8Array.prototype.length":"\nUint8Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( 5 );\n    > arr.length\n    5","Uint8Array.prototype.copyWithin":"\nUint8Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Uint8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2","Uint8Array.prototype.entries":"\nUint8Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true","Uint8Array.prototype.every":"\nUint8Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false","Uint8Array.prototype.fill":"\nUint8Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Uint8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3","Uint8Array.prototype.filter":"\nUint8Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2","Uint8Array.prototype.find":"\nUint8Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3","Uint8Array.prototype.findIndex":"\nUint8Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2","Uint8Array.prototype.forEach":"\nUint8Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '","Uint8Array.prototype.includes":"\nUint8Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true","Uint8Array.prototype.indexOf":"\nUint8Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2","Uint8Array.prototype.join":"\nUint8Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'","Uint8Array.prototype.keys":"\nUint8Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true","Uint8Array.prototype.lastIndexOf":"\nUint8Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3","Uint8Array.prototype.map":"\nUint8Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Uint8Array>[ 2, 4, 6 ]","Uint8Array.prototype.reduce":"\nUint8Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14","Uint8Array.prototype.reduceRight":"\nUint8Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14","Uint8Array.prototype.reverse":"\nUint8Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Uint8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] )\n    <Uint8Array>\n    > arr.reverse()\n    <Uint8Array>[ 3, 2, 1 ]","Uint8Array.prototype.set":"\nUint8Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4","Uint8Array.prototype.slice":"\nUint8Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint8Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3","Uint8Array.prototype.some":"\nUint8Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true","Uint8Array.prototype.sort":"\nUint8Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Uint8Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Uint8Array>[ 0, 1, 1, 2, 2 ]","Uint8Array.prototype.subarray":"\nUint8Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint8Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Uint8Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Uint8Array>[ 3, 4, 5 ]","Uint8Array.prototype.toLocaleString":"\nUint8Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'","Uint8Array.prototype.toString":"\nUint8Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'","Uint8Array.prototype.values":"\nUint8Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Uint8Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8ClampedArray","Uint8ClampedArray":"\nUint8ClampedArray()\n    A typed array constructor which returns a typed array representing an array\n    of 8-bit unsigned integers in the platform byte order clamped to 0-255.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray()\n    <Uint8ClampedArray>\n\n\nUint8ClampedArray( length )\n    Returns a typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( 5 )\n    <Uint8ClampedArray>[ 0, 0, 0, 0, 0 ]\n\n\nUint8ClampedArray( typedarray )\n    Creates a typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n    > var arr2 = new Uint8ClampedArray( arr1 )\n    <Uint8ClampedArray>[ 5, 5, 5 ]\n\n\nUint8ClampedArray( obj )\n    Creates a typed array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a typed array.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 5.0, 5.0, 5.0 ];\n    > var arr2 = new Uint8ClampedArray( arr1 )\n    <Uint8ClampedArray>[ 5, 5, 5 ]\n\n\nUint8ClampedArray( buffer[, byteOffset[, length]] )\n    Returns a typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 4 );\n    > var arr = new Uint8ClampedArray( buf, 0, 4 )\n    <Uint8ClampedArray>[ 0, 0, 0, 0 ]\n\n\nUint8ClampedArray.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Uint8ClampedArray.from( [ 1, 2 ], mapFcn )\n    <Uint8ClampedArray>[ 2, 4 ]\n\n\nUint8ClampedArray.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Uint8ClampedArray.of( 1, 2 )\n    <Uint8ClampedArray>[ 1, 2 ]\n\n\nUint8ClampedArray.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Uint8ClampedArray.BYTES_PER_ELEMENT\n    1\n\n\nUint8ClampedArray.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Uint8ClampedArray.name\n    'Uint8ClampedArray'\n\n\nUint8ClampedArray.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( 5 );\n    > arr.buffer\n    <ArrayBuffer>\n\n\nUint8ClampedArray.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( 5 );\n    > arr.byteLength\n    5\n\n\nUint8ClampedArray.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( 5 );\n    > arr.byteOffset\n    0\n\n\nUint8ClampedArray.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( 5 );\n    > arr.BYTES_PER_ELEMENT\n    1\n\n\nUint8ClampedArray.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( 5 );\n    > arr.length\n    5\n\n\nUint8ClampedArray.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2\n\n\nUint8ClampedArray.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true\n\n\nUint8ClampedArray.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false\n\n\nUint8ClampedArray.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3\n\n\nUint8ClampedArray.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2\n\n\nUint8ClampedArray.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3\n\n\nUint8ClampedArray.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2\n\n\nUint8ClampedArray.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '\n\n\nUint8ClampedArray.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true\n\n\nUint8ClampedArray.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2\n\n\nUint8ClampedArray.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'\n\n\nUint8ClampedArray.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true\n\n\nUint8ClampedArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3\n\n\nUint8ClampedArray.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Uint8ClampedArray>[ 2, 4, 6 ]\n\n\nUint8ClampedArray.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14\n\n\nUint8ClampedArray.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14\n\n\nUint8ClampedArray.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] )\n    <Uint8ClampedArray>\n    > arr.reverse()\n    <Uint8ClampedArray>[ 3, 2, 1 ]\n\n\nUint8ClampedArray.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4\n\n\nUint8ClampedArray.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3\n\n\nUint8ClampedArray.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true\n\n\nUint8ClampedArray.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Uint8ClampedArray>[ 0, 1, 1, 2, 2 ]\n\n\nUint8ClampedArray.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Uint8ClampedArray>[ 3, 4, 5 ]\n\n\nUint8ClampedArray.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'\n\n\nUint8ClampedArray.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'\n\n\nUint8ClampedArray.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array\n","Uint8ClampedArray.from":"\nUint8ClampedArray.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Uint8ClampedArray.from( [ 1, 2 ], mapFcn )\n    <Uint8ClampedArray>[ 2, 4 ]","Uint8ClampedArray.of":"\nUint8ClampedArray.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Uint8ClampedArray.of( 1, 2 )\n    <Uint8ClampedArray>[ 1, 2 ]","Uint8ClampedArray.BYTES_PER_ELEMENT":"\nUint8ClampedArray.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Uint8ClampedArray.BYTES_PER_ELEMENT\n    1","Uint8ClampedArray.name":"\nUint8ClampedArray.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Uint8ClampedArray.name\n    'Uint8ClampedArray'","Uint8ClampedArray.prototype.buffer":"\nUint8ClampedArray.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( 5 );\n    > arr.buffer\n    <ArrayBuffer>","Uint8ClampedArray.prototype.byteLength":"\nUint8ClampedArray.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( 5 );\n    > arr.byteLength\n    5","Uint8ClampedArray.prototype.byteOffset":"\nUint8ClampedArray.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( 5 );\n    > arr.byteOffset\n    0","Uint8ClampedArray.prototype.BYTES_PER_ELEMENT":"\nUint8ClampedArray.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( 5 );\n    > arr.BYTES_PER_ELEMENT\n    1","Uint8ClampedArray.prototype.length":"\nUint8ClampedArray.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( 5 );\n    > arr.length\n    5","Uint8ClampedArray.prototype.copyWithin":"\nUint8ClampedArray.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2","Uint8ClampedArray.prototype.entries":"\nUint8ClampedArray.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true","Uint8ClampedArray.prototype.every":"\nUint8ClampedArray.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false","Uint8ClampedArray.prototype.fill":"\nUint8ClampedArray.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3","Uint8ClampedArray.prototype.filter":"\nUint8ClampedArray.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2","Uint8ClampedArray.prototype.find":"\nUint8ClampedArray.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3","Uint8ClampedArray.prototype.findIndex":"\nUint8ClampedArray.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2","Uint8ClampedArray.prototype.forEach":"\nUint8ClampedArray.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '","Uint8ClampedArray.prototype.includes":"\nUint8ClampedArray.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true","Uint8ClampedArray.prototype.indexOf":"\nUint8ClampedArray.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2","Uint8ClampedArray.prototype.join":"\nUint8ClampedArray.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'","Uint8ClampedArray.prototype.keys":"\nUint8ClampedArray.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true","Uint8ClampedArray.prototype.lastIndexOf":"\nUint8ClampedArray.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3","Uint8ClampedArray.prototype.map":"\nUint8ClampedArray.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Uint8ClampedArray>[ 2, 4, 6 ]","Uint8ClampedArray.prototype.reduce":"\nUint8ClampedArray.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14","Uint8ClampedArray.prototype.reduceRight":"\nUint8ClampedArray.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14","Uint8ClampedArray.prototype.reverse":"\nUint8ClampedArray.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] )\n    <Uint8ClampedArray>\n    > arr.reverse()\n    <Uint8ClampedArray>[ 3, 2, 1 ]","Uint8ClampedArray.prototype.set":"\nUint8ClampedArray.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4","Uint8ClampedArray.prototype.slice":"\nUint8ClampedArray.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3","Uint8ClampedArray.prototype.some":"\nUint8ClampedArray.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true","Uint8ClampedArray.prototype.sort":"\nUint8ClampedArray.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Uint8ClampedArray>[ 0, 1, 1, 2, 2 ]","Uint8ClampedArray.prototype.subarray":"\nUint8ClampedArray.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint8ClampedArray\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Uint8ClampedArray( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Uint8ClampedArray>[ 3, 4, 5 ]","Uint8ClampedArray.prototype.toLocaleString":"\nUint8ClampedArray.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'","Uint8ClampedArray.prototype.toString":"\nUint8ClampedArray.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'","Uint8ClampedArray.prototype.values":"\nUint8ClampedArray.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Uint8ClampedArray( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint32Array, Uint8Array","UINT16_MAX":"\nUINT16_MAX\n    Maximum unsigned 16-bit integer.\n\n    The maximum unsigned 16-bit integer is given by `2^16 - 1`.\n\n    Examples\n    --------\n    > UINT16_MAX\n    65535\n\n    See Also\n    --------\n    INT16_MAX\n","UINT16_NUM_BYTES":"\nUINT16_NUM_BYTES\n    Size (in bytes) of a 16-bit unsigned integer.\n\n    Examples\n    --------\n    > UINT16_NUM_BYTES\n    2\n\n    See Also\n    --------\n    INT16_NUM_BYTES, UINT32_NUM_BYTES, UINT8_NUM_BYTES\n","Uint16Array":"\nUint16Array()\n    A typed array constructor which returns a typed array representing an array\n    of 16-bit unsigned integers in the platform byte order.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array()\n    <Uint16Array>\n\n\nUint16Array( length )\n    Returns a typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( 5 )\n    <Uint16Array>[ 0, 0, 0, 0, 0 ]\n\n\nUint16Array( typedarray )\n    Creates a typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n    > var arr2 = new Uint16Array( arr1 )\n    <Uint16Array>[ 5, 5, 5 ]\n\n\nUint16Array( obj )\n    Creates a typed array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a typed array.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 5.0, 5.0, 5.0 ];\n    > var arr2 = new Uint16Array( arr1 )\n    <Uint16Array>[ 5, 5, 5 ]\n\n\nUint16Array( buffer[, byteOffset[, length]] )\n    Returns a typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 8 );\n    > var arr = new Uint16Array( buf, 0, 4 )\n    <Uint16Array>[ 0, 0, 0, 0 ]\n\n\nUint16Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Uint16Array.from( [ 1, 2 ], mapFcn )\n    <Uint16Array>[ 2, 4 ]\n\n\nUint16Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Uint16Array.of( 1, 2 )\n    <Uint16Array>[ 1, 2 ]\n\n\nUint16Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Uint16Array.BYTES_PER_ELEMENT\n    2\n\n\nUint16Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Uint16Array.name\n    'Uint16Array'\n\n\nUint16Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>\n\n\nUint16Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( 5 );\n    > arr.byteLength\n    10\n\n\nUint16Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( 5 );\n    > arr.byteOffset\n    0\n\n\nUint16Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    2\n\n\nUint16Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( 5 );\n    > arr.length\n    5\n\n\nUint16Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Uint16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2\n\n\nUint16Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true\n\n\nUint16Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false\n\n\nUint16Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Uint16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3\n\n\nUint16Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2\n\n\nUint16Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3\n\n\nUint16Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2\n\n\nUint16Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '\n\n\nUint16Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true\n\n\nUint16Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2\n\n\nUint16Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'\n\n\nUint16Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true\n\n\nUint16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3\n\n\nUint16Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Uint16Array>[ 2, 4, 6 ]\n\n\nUint16Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14\n\n\nUint16Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14\n\n\nUint16Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Uint16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] )\n    <Uint16Array>\n    > arr.reverse()\n    <Uint16Array>[ 3, 2, 1 ]\n\n\nUint16Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4\n\n\nUint16Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3\n\n\nUint16Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true\n\n\nUint16Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Uint16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Uint16Array>[ 0, 1, 1, 2, 2 ]\n\n\nUint16Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint16Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Uint16Array>[ 3, 4, 5 ]\n\n\nUint16Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'\n\n\nUint16Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'\n\n\nUint16Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint32Array, Uint8Array, Uint8ClampedArray\n","Uint16Array.from":"\nUint16Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Uint16Array.from( [ 1, 2 ], mapFcn )\n    <Uint16Array>[ 2, 4 ]","Uint16Array.of":"\nUint16Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Uint16Array.of( 1, 2 )\n    <Uint16Array>[ 1, 2 ]","Uint16Array.BYTES_PER_ELEMENT":"\nUint16Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Uint16Array.BYTES_PER_ELEMENT\n    2","Uint16Array.name":"\nUint16Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Uint16Array.name\n    'Uint16Array'","Uint16Array.prototype.buffer":"\nUint16Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>","Uint16Array.prototype.byteLength":"\nUint16Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( 5 );\n    > arr.byteLength\n    10","Uint16Array.prototype.byteOffset":"\nUint16Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( 5 );\n    > arr.byteOffset\n    0","Uint16Array.prototype.BYTES_PER_ELEMENT":"\nUint16Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    2","Uint16Array.prototype.length":"\nUint16Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( 5 );\n    > arr.length\n    5","Uint16Array.prototype.copyWithin":"\nUint16Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Uint16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2","Uint16Array.prototype.entries":"\nUint16Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true","Uint16Array.prototype.every":"\nUint16Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false","Uint16Array.prototype.fill":"\nUint16Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Uint16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3","Uint16Array.prototype.filter":"\nUint16Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2","Uint16Array.prototype.find":"\nUint16Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3","Uint16Array.prototype.findIndex":"\nUint16Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2","Uint16Array.prototype.forEach":"\nUint16Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '","Uint16Array.prototype.includes":"\nUint16Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true","Uint16Array.prototype.indexOf":"\nUint16Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2","Uint16Array.prototype.join":"\nUint16Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'","Uint16Array.prototype.keys":"\nUint16Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true","Uint16Array.prototype.lastIndexOf":"\nUint16Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3","Uint16Array.prototype.map":"\nUint16Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Uint16Array>[ 2, 4, 6 ]","Uint16Array.prototype.reduce":"\nUint16Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14","Uint16Array.prototype.reduceRight":"\nUint16Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14","Uint16Array.prototype.reverse":"\nUint16Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Uint16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] )\n    <Uint16Array>\n    > arr.reverse()\n    <Uint16Array>[ 3, 2, 1 ]","Uint16Array.prototype.set":"\nUint16Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4","Uint16Array.prototype.slice":"\nUint16Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint16Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint16Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3","Uint16Array.prototype.some":"\nUint16Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true","Uint16Array.prototype.sort":"\nUint16Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Uint16Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Uint16Array>[ 0, 1, 1, 2, 2 ]","Uint16Array.prototype.subarray":"\nUint16Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint16Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Uint16Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Uint16Array>[ 3, 4, 5 ]","Uint16Array.prototype.toLocaleString":"\nUint16Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'","Uint16Array.prototype.toString":"\nUint16Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'","Uint16Array.prototype.values":"\nUint16Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Uint16Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint32Array, Uint8Array, Uint8ClampedArray","UINT32_MAX":"\nUINT32_MAX\n    Maximum unsigned 32-bit integer.\n\n    The maximum unsigned 32-bit integer is given by `2^32 - 1`.\n\n    Examples\n    --------\n    > UINT32_MAX\n    4294967295\n\n    See Also\n    --------\n    INT32_MAX\n","UINT32_NUM_BYTES":"\nUINT32_NUM_BYTES\n    Size (in bytes) of a 32-bit unsigned integer.\n\n    Examples\n    --------\n    > UINT32_NUM_BYTES\n    4\n\n    See Also\n    --------\n    INT32_NUM_BYTES, UINT16_NUM_BYTES, UINT8_NUM_BYTES\n","Uint32Array":"\nUint32Array()\n    A typed array constructor which returns a typed array representing an array\n    of 32-bit unsigned integers in the platform byte order.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array()\n    <Uint32Array>\n\n\nUint32Array( length )\n    Returns a typed array having a specified length.\n\n    Parameters\n    ----------\n    length: integer\n        Typed array length.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( 5 )\n    <Uint32Array>[ 0, 0, 0, 0, 0 ]\n\n\nUint32Array( typedarray )\n    Creates a typed array from another typed array.\n\n    Parameters\n    ----------\n    typedarray: TypedArray\n        Typed array from which to generate another typed array.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Int32Array( [ 5, 5, 5 ] );\n    > var arr2 = new Uint32Array( arr1 )\n    <Uint32Array>[ 5, 5, 5 ]\n\n\nUint32Array( obj )\n    Creates a typed array from an array-like object or iterable.\n\n    Parameters\n    ----------\n    obj: Object\n        Array-like object or iterable from which to generate a typed array.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = [ 5.0, 5.0, 5.0 ];\n    > var arr2 = new Uint32Array( arr1 )\n    <Uint32Array>[ 5, 5, 5 ]\n\n\nUint32Array( buffer[, byteOffset[, length]] )\n    Returns a typed array view of an ArrayBuffer.\n\n    Parameters\n    ----------\n    buffer: ArrayBuffer\n        Underlying ArrayBuffer.\n\n    byteOffset: integer (optional)\n        Integer byte offset specifying the location of the first typed array\n        element. Default: 0.\n\n    length: integer (optional)\n        View length. If not provided, the view spans from the byteOffset to\n        the end of the underlying ArrayBuffer.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var buf = new ArrayBuffer( 16 );\n    > var arr = new Uint32Array( buf, 0, 4 )\n    <Uint32Array>[ 0, 0, 0, 0 ]\n\n\nUint32Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Uint32Array.from( [ 1, 2 ], mapFcn )\n    <Uint32Array>[ 2, 4 ]\n\n\nUint32Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Uint32Array.of( 1, 2 )\n    <Uint32Array>[ 1, 2 ]\n\n\nUint32Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Uint32Array.BYTES_PER_ELEMENT\n    4\n\n\nUint32Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Uint32Array.name\n    'Uint32Array'\n\n\nUint32Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>\n\n\nUint32Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( 5 );\n    > arr.byteLength\n    20\n\n\nUint32Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( 5 );\n    > arr.byteOffset\n    0\n\n\nUint32Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    4\n\n\nUint32Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( 5 );\n    > arr.length\n    5\n\n\nUint32Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Uint32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2\n\n\nUint32Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true\n\n\nUint32Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false\n\n\nUint32Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Uint32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3\n\n\nUint32Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2\n\n\nUint32Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3\n\n\nUint32Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2\n\n\nUint32Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '\n\n\nUint32Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true\n\n\nUint32Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2\n\n\nUint32Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'\n\n\nUint32Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true\n\n\nUint32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3\n\n\nUint32Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Uint32Array>[ 2, 4, 6 ]\n\n\nUint32Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14\n\n\nUint32Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14\n\n\nUint32Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Uint32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] )\n    <Uint32Array>\n    > arr.reverse()\n    <Uint32Array>[ 3, 2, 1 ]\n\n\nUint32Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4\n\n\nUint32Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3\n\n\nUint32Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true\n\n\nUint32Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Uint32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Uint32Array>[ 0, 1, 1, 2, 2 ]\n\n\nUint32Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint32Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Uint32Array>[ 3, 4, 5 ]\n\n\nUint32Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'\n\n\nUint32Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'\n\n\nUint32Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint8Array, Uint8ClampedArray\n","Uint32Array.from":"\nUint32Array.from( src[, map[, thisArg]] )\n    Creates a new typed array from an array-like object or an iterable.\n\n    A callback is provided the following arguments:\n\n    - value: source value.\n    - index: source index.\n\n    Parameters\n    ----------\n    src: ArrayLike|Iterable\n        Source of array elements.\n\n    map: Function (optional)\n        Callback to invoke for each source element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > function mapFcn( v ) { return v * 2; };\n    > var arr = Uint32Array.from( [ 1, 2 ], mapFcn )\n    <Uint32Array>[ 2, 4 ]","Uint32Array.of":"\nUint32Array.of( element0[, element1[, ...elementN]] )\n    Creates a new typed array from a variable number of arguments.\n\n    Parameters\n    ----------\n    element0: number\n        Array element.\n\n    element1: number (optional)\n        Array element.\n\n    elementN: ...number (optional)\n        Array elements.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr = Uint32Array.of( 1, 2 )\n    <Uint32Array>[ 1, 2 ]","Uint32Array.BYTES_PER_ELEMENT":"\nUint32Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > Uint32Array.BYTES_PER_ELEMENT\n    4","Uint32Array.name":"\nUint32Array.name\n    Typed array constructor name.\n\n    Examples\n    --------\n    > Uint32Array.name\n    'Uint32Array'","Uint32Array.prototype.buffer":"\nUint32Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( 5 );\n    > arr.buffer\n    <ArrayBuffer>","Uint32Array.prototype.byteLength":"\nUint32Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( 5 );\n    > arr.byteLength\n    20","Uint32Array.prototype.byteOffset":"\nUint32Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( 5 );\n    > arr.byteOffset\n    0","Uint32Array.prototype.BYTES_PER_ELEMENT":"\nUint32Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( 5 );\n    > arr.BYTES_PER_ELEMENT\n    4","Uint32Array.prototype.length":"\nUint32Array.prototype.length\n    Read-only property which returns the number of view elements.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( 5 );\n    > arr.length\n    5","Uint32Array.prototype.copyWithin":"\nUint32Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n\n    Parameters\n    ----------\n    target: integer\n        Target start index position.\n\n    start: integer\n        Source start index position.\n\n    end: integer (optional)\n        Source end index position. Default: out.length.\n\n    Returns\n    -------\n    out: Uint32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n    > arr.copyWithin( 3, 0, 2 );\n    > arr[ 3 ]\n    1\n    > arr[ 4 ]\n    2","Uint32Array.prototype.entries":"\nUint32Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array key-value pairs.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > it = arr.entries();\n    > it.next().value\n    [ 0, 1 ]\n    > it.next().value\n    [ 1, 2 ]\n    > it.next().done\n    true","Uint32Array.prototype.every":"\nUint32Array.prototype.every( predicate[, thisArg] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, an array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether all array elements pass.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v <= 1 ); };\n    > arr.every( predicate )\n    false","Uint32Array.prototype.fill":"\nUint32Array.prototype.fill( value[, start[, end]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n\n    Parameters\n    ----------\n    value: number\n        Fill value.\n\n    start: integer (optional)\n        Start index. If less than zero, the start index is resolved relative to\n        the last array element. Default: 0.\n\n    end: integer (optional)\n        End index (non-inclusive). If less than zero, the end index is resolved\n        relative to the last array element. Default: out.length.\n\n    Returns\n    -------\n    out: Uint32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > arr.fill( 3 );\n    > arr[ 0 ]\n    3\n    > arr[ 1 ]\n    3","Uint32Array.prototype.filter":"\nUint32Array.prototype.filter( predicate[, thisArg] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    If a predicate function does not return a truthy value for any array\n    element, the method returns `null`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which filters array elements. If a predicate function\n        returns a truthy value, an array element is included in the output\n        array; otherwise, an array element is not included in the output array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > var arr2 = arr1.filter( predicate );\n    > arr2.length\n    2","Uint32Array.prototype.find":"\nUint32Array.prototype.find( predicate[, thisArg] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `undefined`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    value: number|undefined\n        Array element.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var v = arr.find( predicate )\n    3","Uint32Array.prototype.findIndex":"\nUint32Array.prototype.findIndex( predicate[, thisArg] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    If a predicate function never returns a truthy value, the method returns\n    `-1`.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > function predicate( v ) { return ( v > 2 ); };\n    > var idx = arr.findIndex( predicate )\n    2","Uint32Array.prototype.forEach":"\nUint32Array.prototype.forEach( fcn[, thisArg] )\n    Invokes a callback for each array element.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to invoke for each array element.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 3, 2, 1 ] );\n    > var str = ' ';\n    > function fcn( v, i ) { str += i + ':' + v + ' '; };\n    > arr.forEach( fcn );\n    > str\n    ' 0:3 1:2 2:1 '","Uint32Array.prototype.includes":"\nUint32Array.prototype.includes( searchElement[, fromIndex] )\n    Returns a boolean indicating whether an array includes a search element.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether an array includes a search element.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > var bool = arr.includes( 4 )\n    false\n    > bool = arr.includes( 3 )\n    true","Uint32Array.prototype.indexOf":"\nUint32Array.prototype.indexOf( searchElement[, fromIndex] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: 0.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > var idx = arr.indexOf( 4 )\n    -1\n    > idx = arr.indexOf( 3 )\n    2","Uint32Array.prototype.join":"\nUint32Array.prototype.join( [separator] )\n    Serializes an array by joining all array elements as a string.\n\n    Parameters\n    ----------\n    separator: string (optional)\n        String delineating array elements. Default: ','.\n\n    Returns\n    -------\n    str: string\n        Array serialized as a string.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > arr.join( '|' )\n    '1|2|3'","Uint32Array.prototype.keys":"\nUint32Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array keys.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > it = arr.keys();\n    > it.next().value\n    0\n    > it.next().value\n    1\n    > it.next().done\n    true","Uint32Array.prototype.lastIndexOf":"\nUint32Array.prototype.lastIndexOf( searchElement[, fromIndex] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n\n    The method iterates from the last array element to the first array element.\n\n    If unable to locate a search element, the method returns `-1`.\n\n    Parameters\n    ----------\n    searchElement: number\n        Search element.\n\n    fromIndex: integer (optional)\n        Array index from which to begin searching. If provided a negative value,\n        the method resolves the start index relative to the last array element.\n        Default: -1.\n\n    Returns\n    -------\n    idx: integer\n        Array index.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 0, 2, 0, 1 ] );\n    > var idx = arr.lastIndexOf( 3 )\n    -1\n    > idx = arr.lastIndexOf( 0 )\n    3","Uint32Array.prototype.map":"\nUint32Array.prototype.map( fcn[, thisArg] )\n    Maps each array element to an element in a new typed array.\n\n    A provided function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    The returned array has the same data type as the host array.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function which maps array elements to elements in the new array.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n    > function fcn( v ) { return v * 2; };\n    > var arr2 = arr1.map( fcn )\n    <Uint32Array>[ 2, 4, 6 ]","Uint32Array.prototype.reduce":"\nUint32Array.prototype.reduce( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the first array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the first array element as the first argument and the second array\n    element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduce( fcn, 0 )\n    14","Uint32Array.prototype.reduceRight":"\nUint32Array.prototype.reduceRight( fcn[, initialValue] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n\n    The provided function is provided the following arguments:\n\n    - acc: accumulated result.\n    - value: current array element.\n    - index: index of the current array element.\n    - arr: array on which the method is invoked.\n\n    If provided an initial value, the method invokes a provided function with\n    the initial value as the first argument and the last array element as the\n    second argument.\n\n    If not provided an initial value, the method invokes a provided function\n    with the last array element as the first argument and the second-to-last\n    array element as the second argument.\n\n    Parameters\n    ----------\n    fcn: Function\n        Function to apply.\n\n    initialValue: Any (optional)\n        Initial accumulation value.\n\n    Returns\n    -------\n    out: Any\n        Accumulated result.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > function fcn( acc, v ) { return acc + (v*v); };\n    > var v = arr.reduceRight( fcn, 0 )\n    14","Uint32Array.prototype.reverse":"\nUint32Array.prototype.reverse()\n    Reverses an array *in-place*.\n\n    This method mutates the array on which the method is invoked.\n\n    Returns\n    -------\n    out: Uint32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] )\n    <Uint32Array>\n    > arr.reverse()\n    <Uint32Array>[ 3, 2, 1 ]","Uint32Array.prototype.set":"\nUint32Array.prototype.set( arr[, offset] )\n    Sets array elements.\n\n    Parameters\n    ----------\n    arr: ArrayLike\n        Source array containing array values to set.\n\n    offset: integer (optional)\n        Array index at which to start writing values. Default: 0.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > arr.set( [ 4, 4 ], 1 );\n    > arr[ 1 ]\n    4\n    > arr[ 2 ]\n    4","Uint32Array.prototype.slice":"\nUint32Array.prototype.slice( [begin[, end]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns `null`.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint32Array\n        A typed array.\n\n    Examples\n    --------\n    > var arr1 = new Uint32Array( [ 1, 2, 3 ] );\n    > var arr2 = arr1.slice( 1 );\n    > arr2.length\n    2\n    > arr2[ 0 ]\n    2\n    > arr2[ 1 ]\n    3","Uint32Array.prototype.some":"\nUint32Array.prototype.some( predicate[, thisArg] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n\n    A predicate function is provided the following arguments:\n\n    - value: array element.\n    - index: array index.\n    - arr: array on which the method is invoked.\n\n    Parameters\n    ----------\n    predicate: Function\n        Predicate function which tests array elements. If a predicate function\n        returns a truthy value, a array element passes; otherwise, an array\n        element fails.\n\n    thisArg: Any (optional)\n        Callback execution context.\n\n    Returns\n    -------\n    bool: boolean\n        Boolean indicating whether at least one array element passes.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > function predicate( v ) { return ( v > 1 ); };\n    > arr.some( predicate )\n    true","Uint32Array.prototype.sort":"\nUint32Array.prototype.sort( [compareFunction] )\n    Sorts an array *in-place*.\n\n    The comparison function is provided two array elements per invocation: `a`\n    and `b`.\n\n    The comparison function return value determines the sort order as follows:\n\n    - If the comparison function returns a value less than zero, then the method\n    sorts `a` to an index lower than `b` (i.e., `a` should come *before* `b`).\n\n    - If the comparison function returns a value greater than zero, then the\n    method sorts `a` to an index higher than `b` (i.e., `b` should come *before*\n    `a`).\n\n    - If the comparison function returns zero, then the relative order of `a`\n    and `b` should remain unchanged.\n\n    This method mutates the array on which the method is invoked.\n\n    Parameters\n    ----------\n    compareFunction: Function (optional)\n        Function which specifies the sort order. The default sort order is\n        ascending order.\n\n    Returns\n    -------\n    out: Uint32Array\n        Modified array.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 0, 2, 1 ] );\n    > arr.sort()\n    <Uint32Array>[ 0, 1, 1, 2, 2 ]","Uint32Array.prototype.subarray":"\nUint32Array.prototype.subarray( [begin[, end]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n\n    If the method is unable to resolve indices to a non-empty array subsequence,\n    the method returns an empty typed array.\n\n    Parameters\n    ----------\n    begin: integer (optional)\n        Start element index (inclusive). If less than zero, the start index is\n        resolved relative to the last array element. Default: 0.\n\n    end: integer (optional)\n        End element index (exclusive). If less than zero, the end index is\n        resolved relative to the last array element. Default: arr.length.\n\n    Returns\n    -------\n    out: Uint32Array\n        A new typed array view.\n\n    Examples\n    --------\n    > var arr1 = new Uint32Array( [ 1, 2, 3, 4, 5 ] );\n    > var arr2 = arr1.subarray( 2 )\n    <Uint32Array>[ 3, 4, 5 ]","Uint32Array.prototype.toLocaleString":"\nUint32Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n\n    Parameters\n    ----------\n    locales: string|Array<string> (optional)\n        A BCP 47 language tag, or an array of such tags.\n\n    options: Object (optional)\n        Options.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > arr.toLocaleString()\n    '1,2,3'","Uint32Array.prototype.toString":"\nUint32Array.prototype.toString()\n    Serializes an array as a string.\n\n    Returns\n    -------\n    str: string\n        A typed array string representation.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2, 3 ] );\n    > arr.toString()\n    '1,2,3'","Uint32Array.prototype.values":"\nUint32Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n\n    Returns\n    -------\n    iter: Iterator\n        Iterator for iterating over array elements.\n\n    Examples\n    --------\n    > var arr = new Uint32Array( [ 1, 2 ] );\n    > it = arr.values();\n    > it.next().value\n    1\n    > it.next().value\n    2\n    > it.next().done\n    true\n\n\n    See Also\n    --------\n    ArrayBuffer, Float32Array, Float64Array, Int16Array, Int32Array, Int8Array, Uint16Array, Uint8Array, Uint8ClampedArray","umask":"\numask( [mask,] [options] )\n    Returns the current process mask, if not provided a mask; otherwise, sets\n    the process mask and returns the previous mask.\n\n    A mask is a set of bits, each of which restricts how its corresponding\n    permission is set for newly created files.\n\n    On POSIX platforms, each file has a set of attributes that control who can\n    read, write, or execute that file. Upon creating a file, file permissions\n    must be set to an initial setting. The process mask restricts those\n    permission settings.\n\n    If the mask contains a bit set to \"1\", the corresponding initial file\n    permission is disabled. If the mask contains a bit set to \"0\", the\n    corresponding permission is left to be determined by the requesting process\n    and the system.\n\n    The process mask is thus a filter that removes permissions as a file is\n    created; i.e., each bit set to a \"1\" removes its corresponding permission.\n\n    In octal representation, a mask is a four digit number, e.g., 0077,\n    comprised as follows:\n\n    - 0: special permissions (setuid, setgid, sticky bit)\n    - 0: (u)ser/owner permissions\n    - 7: (g)roup permissions\n    - 7: (o)thers/non-group permissions\n\n    Octal codes correspond to the following permissions:\n\n    - 0: read, write, execute\n    - 1: read, write\n    - 2: read, execute\n    - 3: read\n    - 4: write, execute\n    - 5: write\n    - 6: execute\n    - 7: no permissions\n\n    If provided fewer than four digits, the mask is left-padded with zeros.\n\n    Note, however, that only the last three digits (i.e., the file permissions\n    digits) of the mask are actually used when the mask is applied.\n\n    Permissions can be represented using the following symbolic form:\n\n        u=rwx,g=rwx,o=rwx\n\n    where\n\n    - u: user permissions\n    - g: group permissions\n    - o: other/non-group permissions\n    - r: read\n    - w: write\n    - x: execute\n\n    When setting permissions using symbolic notation, the function accepts a\n    mask expression of the form:\n\n        [<classes>]<operator><symbols>\n\n    where \"classes\" may be a combination of\n\n    - u: user\n    - g: group\n    - o: other/non-group\n    - a: all\n\n    \"symbols\" may be a combination of\n\n    - r: read\n    - w: write\n    - x: execute\n    - X: special execute\n    - s: setuid/gid on execution\n    - t: sticky\n\n    and \"operator\" may be one of\n\n    - +: enable\n    - -: disable\n    - =: enable specified and disable unspecified permissions\n\n    For example,\n\n    - u-w: disable user write permissions\n    - u+w: enable user write permissions\n    - u=w: enable user write permissions and disable user read and execute\n\n    To specify multiple changes, provide a comma-separated list of mask\n    expressions. For example,\n\n        u+rwx,g-x,o=r\n\n    would enable user read, write, and execute permissions, disable group\n    execute permissions, enable other read permissions, and disable other\n    write and execute permissions.\n\n    The `a` class indicates \"all\", which is the same as specifying \"ugo\". This\n    is the default class if a class is omitted when specifying permissions. For\n    example, `+x` is equivalent to `a+x` which is equivalent to `ugo+x` which\n    is equivalent to `u+x,g+x,o+x` and enables execution for all classes.\n\n    Parameters\n    ----------\n    mask: integer|string (optional)\n        Mask or mask expression. If the mask is a string, the mask is assumed to\n        be in symbolic notation.\n\n    options: Object (optional)\n        Options.\n\n    options.symbolic: boolean (optional)\n        Boolean indicating whether to return the mask using symbolic notation.\n\n    Returns\n    -------\n    mask: integer|string\n        Process mask. If provided a mask, the returned value is the previous\n        mask; otherwise, the returned value is the current process mask.\n\n    Examples\n    --------\n    > var mask = umask()\n    <number>\n    > mask = umask( { 'symbolic': true } )\n    <string>\n\n","uncapitalize":"\nuncapitalize( str )\n    Lowercases the first character of a string.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Uncapitalized string.\n\n    Examples\n    --------\n    > var out = uncapitalize( 'Beep' )\n    'beep'\n    > out = uncapitalize( 'bOOp' )\n    'bOOp'\n\n    See Also\n    --------\n    capitalize, lowercase\n","uncapitalizeKeys":"\nuncapitalizeKeys( obj )\n    Converts the first letter of each object key to lowercase.\n\n    The function only transforms own properties. Hence, the function does not\n    transform inherited properties.\n\n    The function shallow copies key values.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > var obj = { 'AA': 1, 'BB': 2 };\n    > var out = uncapitalizeKeys( obj )\n    { 'aA': 1, 'bB': 2 }\n\n    See Also\n    --------\n    capitalizeKeys, lowercaseKeys\n","uncurry":"\nuncurry( fcn[, arity, ][thisArg] )\n    Transforms a curried function into a function invoked with multiple\n    arguments.\n\n    Parameters\n    ----------\n    fcn: Function\n        Curried function.\n\n    arity: integer (optional)\n        Number of parameters.\n\n    thisArg: any (optional)\n        Evaluation context.\n\n    Returns\n    -------\n    out: Function\n        Uncurried function.\n\n    Examples\n    --------\n    > function addX( x ) {\n    ...     return function addY( y ) {\n    ...         return x + y;\n    ...     };\n    ... };\n    > var fcn = uncurry( addX );\n    > var sum = fcn( 2, 3 )\n    5\n\n    // To enforce a fixed number of parameters, provide an `arity` argument:\n    > function add( x ) {\n    ...     return function add( y ) {\n    ...         return x + y;\n    ...     };\n    ... };\n    > fcn = uncurry( add, 2 );\n    > sum = fcn( 9 )\n    <Error>\n\n    // To specify an execution context, provide a `thisArg` argument:\n    > function addX( x ) {\n    ...     this.x = x;\n    ...     return addY;\n    ... };\n    > function addY( y ) {\n    ...     return this.x + y;\n    ... };\n    > fcn = uncurry( addX, {} );\n    > sum = fcn( 2, 3 )\n    5\n\n    See Also\n    --------\n    curry, uncurryRight\n","uncurryRight":"\nuncurryRight( fcn[, arity, ][thisArg] )\n    Transforms a curried function into a function invoked with multiple\n    arguments.\n\n    Provided arguments are applied starting from the right.\n\n    Parameters\n    ----------\n    fcn: Function\n        Curried function.\n\n    arity: integer (optional)\n        Number of parameters.\n\n    thisArg: any (optional)\n        Evaluation context.\n\n    Returns\n    -------\n    out: Function\n        Uncurried function.\n\n    Examples\n    --------\n    > function addX( x ) {\n    ...     return function addY( y ) {\n    ...         return x + y;\n    ...     };\n    ... };\n    > var fcn = uncurryRight( addX );\n    > var sum = fcn( 3, 2 )\n    5\n\n    // To enforce a fixed number of parameters, provide an `arity` argument:\n    > function add( y ) {\n    ...     return function add( x ) {\n    ...         return x + y;\n    ...     };\n    ... };\n    > fcn = uncurryRight( add, 2 );\n    > sum = fcn( 9 )\n    <Error>\n\n    // To specify an execution context, provide a `thisArg` argument:\n    > function addY( y ) {\n    ...     this.y = y;\n    ...     return addX;\n    ... };\n    > function addX( x ) {\n    ...     return x + this.y;\n    ... };\n    > fcn = uncurryRight( addY, {} );\n    > sum = fcn( 3, 2 )\n    5\n\n    See Also\n    --------\n    curry, curryRight, uncurry\n","UNICODE_MAX":"\nUNICODE_MAX\n    Maximum Unicode code point.\n\n    Examples\n    --------\n    > UNICODE_MAX\n    1114111\n\n    See Also\n    --------\n    UNICODE_MAX_BMP\n","UNICODE_MAX_BMP":"\nUNICODE_MAX_BMP\n    Maximum Unicode code point in the Basic Multilingual Plane (BMP).\n\n    Examples\n    --------\n    > UNICODE_MAX_BMP\n    65535\n\n    See Also\n    --------\n    UNICODE_MAX\n","UnicodeColumnChartSparkline":"\nUnicodeColumnChartSparkline( [data,] [options] )\n    Returns a sparkline column chart instance.\n\n    The `data` argument takes precedence over the `data` option.\n\n    Parameters\n    ----------\n    data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options: Object (optional)\n        Options.\n\n    options.autoRender: boolean (optional)\n        Boolean indicating whether to re-render on a 'change' event. Default:\n        false.\n\n    options.bufferSize: integer|null (optional)\n        Data buffer size. If provided, data is kept in a first-in first-out\n        (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n    options.data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options.description: string (optional)\n        Chart description.\n\n    options.infinities: boolean (optional)\n        Boolean indicating whether to encode infinite values. Default: false.\n\n    options.isDefined: Function (optional)\n        An accessor function indicating whether a datum is defined.\n\n    options.label: string (optional)\n        Data label.\n\n    options.yMax: number|null (optional)\n        Maximum value of the y-axis domain. If `null`, the value is computed\n        from the data. Default: null.\n\n    options.yMin: number|null (optional)\n        Minimum value of the y-axis domain. If `null`, the value is computed\n        from the data. Default: null.\n\n    Returns\n    -------\n    chart: ColumnChart\n        Column chart instance.\n\n    chart.autoRender\n        Rendering mode. If `true`, an instance renders on each 'change' event;\n        otherwise, rendering must be triggered manually.\n\n    chart.bufferSize\n        Data buffer size.\n\n    chart.description\n        Chart description.\n\n    chart.data\n        Chart data.\n\n    chart.label\n        Data label.\n\n    chart.infinities\n        Indicates whether to encode infinite values.\n\n    chart.isDefined( d, i )\n        An accessor function which defines whether a datum is defined. This\n        accessor is used to define how missing values are encoded. The default\n        behavior is to ignore values which are `NaN`.\n\n    chart.render()\n        Renders a column chart sparkline.\n\n    chart.yMax\n        Maximum value of the y-axis domain. If set to `null`, when accessed, the\n        returned value is computed from the data.\n\n    chart.yMin\n        Minimum value of the y-axis domain. If set to `null`, when accessed, the\n        returned value is computed from the data.\n\n    Examples\n    --------\n    > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n    > var chart = new UnicodeColumnChartSparkline( data );\n    > chart.render()\n    '▁█▅▃▆▆▅'\n\n    See Also\n    --------\n    plot, Plot, UnicodeSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeLineChartSparkline":"\nUnicodeLineChartSparkline( [data,] [options] )\n    Returns a sparkline line chart instance.\n\n    The `data` argument takes precedence over the `data` option.\n\n    Parameters\n    ----------\n    data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options: Object (optional)\n        Options.\n\n    options.autoRender: boolean (optional)\n        Boolean indicating whether to re-render on a 'change' event. Default:\n        false.\n\n    options.bufferSize: integer|null (optional)\n        Data buffer size. If provided, data is kept in a first-in first-out\n        (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n    options.data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options.description: string (optional)\n        Chart description.\n\n    options.infinities: boolean (optional)\n        Boolean indicating whether to encode infinite values. Default: false.\n\n    options.isDefined: Function (optional)\n        An accessor function indicating whether a datum is defined.\n\n    options.label: string (optional)\n        Data label.\n\n    options.yMax: number|null (optional)\n        Maximum value of the y-axis domain. If `null`, the value is computed\n        from the data. Default: null.\n\n    options.yMin: number|null (optional)\n        Minimum value of the y-axis domain. If `null`, the value is computed\n        from the data. Default: null.\n\n    Returns\n    -------\n    chart: LineChart\n        Line chart instance.\n\n    chart.autoRender\n        Rendering mode. If `true`, an instance renders on each 'change' event;\n        otherwise, rendering must be triggered manually.\n\n    chart.bufferSize\n        Data buffer size.\n\n    chart.description\n        Chart description.\n\n    chart.data\n        Chart data.\n\n    chart.label\n        Data label.\n\n    chart.infinities\n        Indicates whether to encode infinite values.\n\n    chart.isDefined( d, i )\n        An accessor function which defines whether a datum is defined. This\n        accessor is used to define how missing values are encoded. The default\n        behavior is to ignore values which are `NaN`.\n\n    chart.render()\n        Renders a line chart sparkline.\n\n    chart.yMax\n        Maximum value of the y-axis domain. If set to `null`, when accessed, the\n        returned value is computed from the data.\n\n    chart.yMin\n        Minimum value of the y-axis domain. If set to `null`, when accessed, the\n        returned value is computed from the data.\n\n    Examples\n    --------\n    > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n    > var chart = new UnicodeLineChartSparkline( data );\n    > chart.render()\n    '⡈⠑⠢⠔⠒⠒⠒'\n\n    See Also\n    --------\n    plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeSparkline":"\nUnicodeSparkline( [data,] [options] )\n    Returns a Unicode sparkline instance.\n\n    The following chart types are supported:\n\n    - column: column chart (e.g., ▃▆▂▄▁▅▅).\n    - line: line chart (e.g., ⡈⠑⠢⠔⠒⠒⠒).\n    - tristate: tristate chart (e.g., ▄▀──▀▄▄▀).\n    - up-down: up/down chart (e.g., ↓↑↑↑↑↓↓↑).\n    - win-loss: win/loss chart (e.g., ┌╵└┴╵╷╷╵).\n\n    The `data` argument takes precedence over the `data` option.\n\n    Parameters\n    ----------\n    data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options: Object (optional)\n        Options.\n\n    options.autoRender: boolean (optional)\n        Boolean indicating whether to re-render on a 'change' event. Default:\n        false.\n\n    options.bufferSize: integer|null (optional)\n        Data buffer size. If provided, data is kept in a first-in first-out\n        (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n    options.data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options.description: string (optional)\n        Chart description.\n\n    options.infinities: boolean (optional)\n        Boolean indicating whether to encode infinite values. Default: false.\n\n    options.isDefined: Function (optional)\n        An accessor function indicating whether a datum is defined.\n\n    options.label: string (optional)\n        Data label.\n\n    options.type: string (optional)\n        Chart type. Default: 'column'.\n\n    options.yMax: number|null (optional)\n        Maximum value of the y-axis domain. If `null`, the value is computed\n        from the data. Default: null.\n\n    options.yMin: number|null (optional)\n        Minimum value of the y-axis domain. If `null`, the value is computed\n        from the data. Default: null.\n\n    Returns\n    -------\n    chart: ColumnChart\n        Column chart instance.\n\n    chart.autoRender\n        Rendering mode. If `true`, an instance renders on each 'change' event;\n        otherwise, rendering must be triggered manually.\n\n    chart.bufferSize\n        Data buffer size.\n\n    chart.description\n        Chart description.\n\n    chart.data\n        Chart data.\n\n    chart.label\n        Data label.\n\n    chart.infinities\n        Indicates whether to encode infinite values.\n\n    chart.isDefined( d, i )\n        An accessor function which defines whether a datum is defined. This\n        accessor is used to define how missing values are encoded. The default\n        behavior is to ignore values which are `NaN`.\n\n    chart.render()\n        Renders a column chart sparkline.\n\n    chart.type\n        Chart type.\n\n    chart.yMax\n        Maximum value of the y-axis domain. If set to `null`, when accessed, the\n        returned value is computed from the data.\n\n    chart.yMin\n        Minimum value of the y-axis domain. If set to `null`, when accessed, the\n        returned value is computed from the data.\n\n    Examples\n    --------\n    > var data = [ 1.0, 5.0, 3.0, 2.0, 4.0, 4.0, 3.0 ];\n    > var chart = new UnicodeSparkline( data );\n    > chart.render()\n    '▁█▅▃▆▆▅'\n    > chart.type = 'line';\n    > chart.render()\n    '⡈⠑⠢⠔⠒⠒⠒'\n\n    See Also\n    --------\n    plot, Plot, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeTristateChartSparkline":"\nUnicodeTristateChartSparkline( [data,] [options] )\n    Returns a sparkline tristate chart instance.\n\n    In a tristate chart, negative values are encoded as lower blocks, positive\n    values are encoded as upper blocks, and values equal to zero are encoded as\n    middle lines.\n\n    The `data` argument takes precedence over the `data` option.\n\n    Parameters\n    ----------\n    data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options: Object (optional)\n        Options.\n\n    options.autoRender: boolean (optional)\n        Boolean indicating whether to re-render on a 'change' event. Default:\n        false.\n\n    options.bufferSize: integer|null (optional)\n        Data buffer size. If provided, data is kept in a first-in first-out\n        (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n    options.data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options.description: string (optional)\n        Chart description.\n\n    options.isDefined: Function (optional)\n        An accessor function indicating whether a datum is defined.\n\n    options.label: string (optional)\n        Data label.\n\n    Returns\n    -------\n    chart: TristateChart\n        Tristate chart instance.\n\n    chart.autoRender\n        Rendering mode. If `true`, an instance renders on each 'change' event;\n        otherwise, rendering must be triggered manually.\n\n    chart.bufferSize\n        Data buffer size.\n\n    chart.description\n        Chart description.\n\n    chart.data\n        Chart data.\n\n    chart.label\n        Data label.\n\n    chart.isDefined( d, i )\n        An accessor function which defines whether a datum is defined. This\n        accessor is used to define how missing values are encoded. The default\n        behavior is to ignore values which are `NaN`.\n\n    chart.render()\n        Renders a tristate chart sparkline.\n\n    Examples\n    --------\n    > var data = [ -1, 1, 0, 0, 1, -1, -1, 1 ];\n    > var chart = new UnicodeTristateChartSparkline( data );\n    > chart.render()\n    '▄▀──▀▄▄▀'\n\n    See Also\n    --------\n    plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeUpDownChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeUpDownChartSparkline":"\nUnicodeUpDownChartSparkline( [data,] [options] )\n    Returns a sparkline up/down chart instance.\n\n    Glyphs:\n\n    | Value | Glyph |\n    |:-----:|:-----:|\n    |   1   |   ↑   |\n    |   -1  |   ↓   |\n\n    If provided any other value other than 1 or -1, the value is encoded as a\n    missing value.\n\n    The `data` argument takes precedence over the `data` option.\n\n    Parameters\n    ----------\n    data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options: Object (optional)\n        Options.\n\n    options.autoRender: boolean (optional)\n        Boolean indicating whether to re-render on a 'change' event. Default:\n        false.\n\n    options.bufferSize: integer|null (optional)\n        Data buffer size. If provided, data is kept in a first-in first-out\n        (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n    options.data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options.description: string (optional)\n        Chart description.\n\n    options.isDefined: Function (optional)\n        An accessor function indicating whether a datum is defined.\n\n    options.label: string (optional)\n        Data label.\n\n    Returns\n    -------\n    chart: UpDownChart\n        Chart instance.\n\n    chart.autoRender\n        Rendering mode. If `true`, an instance renders on each 'change' event;\n        otherwise, rendering must be triggered manually.\n\n    chart.bufferSize\n        Data buffer size.\n\n    chart.description\n        Chart description.\n\n    chart.data\n        Chart data.\n\n    chart.label\n        Data label.\n\n    chart.isDefined( d, i )\n        An accessor function which defines whether a datum is defined. This\n        accessor is used to define how missing values are encoded. The default\n        behavior is to ignore any values which are not 1 or -1.\n\n    chart.render()\n        Renders an up/down chart sparkline.\n\n    Examples\n    --------\n    > var data = [ -1, 1, 1, 1, 1, -1, -1, 1 ];\n    > var chart = new UnicodeUpDownChartSparkline( data );\n    > chart.render()\n    '↓↑↑↑↑↓↓↑'\n\n    See Also\n    --------\n    plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeWinLossChartSparkline\n","UnicodeWinLossChartSparkline":"\nUnicodeWinLossChartSparkline( [data,] [options] )\n    Returns a sparkline win/loss chart instance.\n\n    Glyphs:\n\n    | Value | Glyph |\n    |:-----:|:-----:|\n    |   1   |   ╵   |\n    |   -1  |   ╷   |\n    |   2   |   └   |\n    |   -2  |   ┌   |\n\n    If a `2` or `-2` is preceded by a `2` or `-2`,\n\n    | Value | Glyph |\n    |:-----:|:-----:|\n    |   2   |   ┴   |\n    |   -2  |   ┬   |\n\n    Based on the win/loss analogy,\n\n    - 1: win away\n    - 2: win at home\n    - -1: loss away\n    - -2: loss at home\n\n    If provided any value other than 1, -1, 2, or -2, the value is encoded as a\n    missing value.\n\n    The `data` argument takes precedence over the `data` option.\n\n    Parameters\n    ----------\n    data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options: Object (optional)\n        Options.\n\n    options.autoRender: boolean (optional)\n        Boolean indicating whether to re-render on a 'change' event. Default:\n        false.\n\n    options.bufferSize: integer|null (optional)\n        Data buffer size. If provided, data is kept in a first-in first-out\n        (FIFO) buffer which cannot exceed the buffer size. Default: +infinity.\n\n    options.data: ArrayLike|ndarray (optional)\n        Chart data.\n\n    options.description: string (optional)\n        Chart description.\n\n    options.isDefined: Function (optional)\n        An accessor function indicating whether a datum is defined.\n\n    options.label: string (optional)\n        Data label.\n\n    Returns\n    -------\n    chart: WinLossChart\n        Chart instance.\n\n    chart.autoRender\n        Rendering mode. If `true`, an instance renders on each 'change' event;\n        otherwise, rendering must be triggered manually.\n\n    chart.bufferSize\n        Data buffer size.\n\n    chart.description\n        Chart description.\n\n    chart.data\n        Chart data.\n\n    chart.label\n        Data label.\n\n    chart.isDefined( d, i )\n        An accessor function which defines whether a datum is defined. This\n        accessor is used to define how missing values are encoded. The default\n        behavior is to ignore any values which are not 1, -1, 2, or -2.\n\n    chart.render()\n        Renders a win/loss chart sparkline.\n\n    Examples\n    --------\n    > var data = [ -2, 1, 2, 2, 1, -1, -1, 1 ];\n    > var chart = new UnicodeWinLossChartSparkline( data );\n    > chart.render()\n    '┌╵└┴╵╷╷╵'\n\n    See Also\n    --------\n    plot, Plot, UnicodeSparkline, UnicodeColumnChartSparkline, UnicodeLineChartSparkline, UnicodeTristateChartSparkline, UnicodeUpDownChartSparkline\n","unlink":"\nunlink( path, clbk )\n    Asynchronously removes a directory entry.\n\n    If a provided path is a symbolic link, the function removes the symbolic\n    link named by the path and does not affect any file or directory named by\n    the contents of the symbolic link.\n\n    Otherwise, the function removes the link named by the provided path and\n    decrements the link count of the file referenced by the link.\n\n    When a file's link count becomes 0 and no process has the file open, the\n    space occupied by the file is freed and the file is no longer accessible.\n\n    If one or more processes have the file open when the last link is removed,\n    the link is removed before the function returns; however, the removal of\n    file contents is postponed until all references to the file are closed.\n\n    If the path refers to a socket, FIFO, or device, processes which have the\n    object open may continue to use it.\n\n    The path argument should *not* be a directory. To remove a directory, use\n    rmdir().\n\n    Parameters\n    ----------\n    path: string|Buffer|integer\n        Entry path.\n\n    clbk: Function\n        Callback to invoke upon removing an entry.\n\n    Examples\n    --------\n    > function done( error ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     }\n    ... };\n    > unlink( './beep/boop.txt', done );\n\n\nunlink.sync( path )\n    Synchronously removes a directory entry.\n\n   Parameters\n    ----------\n    path: string|Buffer|integer\n        Entry path.\n\n    Returns\n    -------\n    out: Error|null\n        Error object or null.\n\n    Examples\n    --------\n    > var out = unlink.sync( './beep/boop.txt' );\n\n    See Also\n    --------\n    exists\n","unlink.sync":"\nunlink.sync( path )\n    Synchronously removes a directory entry.\n\n   Parameters\n    ----------\n    path: string|Buffer|integer\n        Entry path.\n\n    Returns\n    -------\n    out: Error|null\n        Error object or null.\n\n    Examples\n    --------\n    > var out = unlink.sync( './beep/boop.txt' );\n\n    See Also\n    --------\n    exists","unshift":"\nunshift( collection, ...items )\n    Adds one or more elements to the beginning of a collection.\n\n    If the input collection is a typed array, the output value does not equal\n    the input reference and the underlying `ArrayBuffer` may *not* be the same\n    as the `ArrayBuffer` belonging to the input view.\n\n    For purposes of generality, always treat the output collection as distinct\n    from the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        A collection. If the collection is an `Object`, the collection should be\n        array-like.\n\n    items: ...any\n        Items to add.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Updated collection.\n\n    Examples\n    --------\n    // Arrays:\n    > var arr = [ 1.0, 2.0, 3.0, 4.0, 5.0 ];\n    > arr = unshift( arr, 6.0, 7.0 )\n    [ 6.0, 7.0, 1.0, 2.0, 3.0, 4.0, 5.0 ]\n\n    // Typed arrays:\n    > arr = new Float64Array( [ 1.0, 2.0 ] );\n    > arr = unshift( arr, 3.0, 4.0 )\n    <Float64Array>[ 3.0, 4.0, 1.0, 2.0 ]\n\n    // Array-like object:\n    > arr = { 'length': 1, '0': 1.0 };\n    > arr = unshift( arr, 2.0, 3.0 )\n    { 'length': 3, '0': 2.0, '1': 3.0, '2': 1.0 }\n\n    See Also\n    --------\n    pop, push, shift\n","until":"\nuntil( predicate, fcn[, thisArg] )\n    Invokes a function until a test condition is true.\n\n    When invoked, both the predicate function and the function to invoke are\n    provided a single argument:\n\n    - i: iteration number (starting from zero).\n\n    Parameters\n    ----------\n    predicate: Function\n        The predicate function which indicates whether to stop invoking a\n        function.\n\n    fcn: Function\n        The function to invoke.\n\n    thisArg: any (optional)\n        Execution context for the invoked function.\n\n    Examples\n    --------\n    > function predicate( i ) { return ( i >= 5 ); };\n    > function beep( i ) { console.log( 'boop: %d', i ); };\n    > until( predicate, beep )\n    boop: 0\n    boop: 1\n    boop: 2\n    boop: 3\n    boop: 4\n\n    See Also\n    --------\n    doUntil, doWhile, untilAsync, untilEach, whilst\n","untilAsync":"\nuntilAsync( predicate, fcn, done[, thisArg] )\n    Invokes a function until a test condition is true.\n\n    The predicate function is provided two arguments:\n\n    - i: iteration number (starting from zero).\n    - clbk: a callback indicating whether to invoke `fcn`.\n\n    The `clbk` function accepts two arguments:\n\n    - error: error argument.\n    - bool: test result.\n\n    If the test result is falsy, the function invokes `fcn`; otherwise, the\n    function invokes the `done` callback.\n\n    The function to invoke is provided two arguments:\n\n    - i: iteration number (starting from zero).\n    - next: a callback which must be invoked before proceeding to the next\n      iteration.\n\n    The first argument of the `next` callback is an `error` argument. If `fcn`\n    calls the `next` callback with a truthy `error` argument, the function\n    suspends execution and immediately calls the `done` callback for subsequent\n    `error` handling.\n\n    The `done` callback is invoked with an `error` argument and any arguments\n    passed to the final `next` callback.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Parameters\n    ----------\n    predicate: Function\n        The predicate function which indicates whether to continue invoking a\n        function.\n\n    fcn: Function\n        The function to invoke.\n\n    done: Function\n        Callback to invoke upon completion.\n\n    thisArg: any (optional)\n        Execution context for the invoked function.\n\n    Examples\n    --------\n    > function predicate( i, clbk ) { clbk( null, i >= 5 ); };\n    > function fcn( i, next ) {\n    ...     setTimeout( onTimeout, i );\n    ...     function onTimeout() {\n    ...         next( null, 'boop'+i );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > untilAsync( predicate, fcn, done )\n    boop: 4\n\n    See Also\n    --------\n    doUntilAsync, doWhileAsync, until, whileAsync\n","untilEach":"\nuntilEach( collection, predicate, fcn[, thisArg] )\n    Until a test condition is true, invokes a function for each element in a\n    collection.\n\n    When invoked, both the predicate function and the function to apply are\n    provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    predicate: Function\n        The predicate function which indicates whether to stop iterating over a\n        collection.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    thisArg: any (optional)\n        Execution context for the applied function.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function predicate( v ) { return v !== v; };\n    > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n    > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n    > untilEach( arr, predicate, logger )\n    0: 1\n    1: 2\n    2: 3\n    3: 4\n\n    See Also\n    --------\n    untilEachRight, whileEach\n","untilEachRight":"\nuntilEachRight( collection, predicate, fcn[, thisArg] )\n    Until a test condition is true, invokes a function for each element in a\n    collection, iterating from right to left.\n\n    When invoked, both the predicate function and the function to apply are\n    provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    predicate: Function\n        The predicate function which indicates whether to stop iterating over a\n        collection.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    thisArg: any (optional)\n        Execution context for the applied function.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function predicate( v ) { return v !== v; };\n    > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n    > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n    > untilEachRight( arr, predicate, logger )\n    5: 5\n    4: 4\n    3: 3\n    2: 2\n\n    See Also\n    --------\n    untilEach, whileEachRight\n","unzip":"\nunzip( arr[, idx] )\n    Unzips a zipped array (i.e., a nested array of tuples).\n\n    Parameters\n    ----------\n    arr: Array\n        Zipped array.\n\n    idx: Array<number> (optional)\n        Array of indices specifying which tuple elements to unzip.\n\n    Returns\n    -------\n    out: Array\n        Array of unzipped arrays.\n\n    Examples\n    --------\n    // Basic usage:\n    > var arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\n    > var out = unzip( arr )\n    [ [ 1, 2 ], [ 'a', 'b' ], [ 3, 4 ] ]\n\n    // Provide indices:\n    > arr = [ [ 1, 'a', 3 ], [ 2, 'b', 4 ] ];\n    > out = unzip( arr, [ 0, 2 ] )\n    [ [ 1, 2 ], [ 3, 4 ] ]\n\n    See Also\n    --------\n    zip\n","uppercase":"\nuppercase( str )\n    Converts a string to uppercase.\n\n    Parameters\n    ----------\n    str: string\n        Input string.\n\n    Returns\n    -------\n    out: string\n        Uppercase string.\n\n    Examples\n    --------\n    > var out = uppercase( 'bEEp' )\n    'BEEP'\n\n    See Also\n    --------\n    capitalize, lowercase\n","uppercaseKeys":"\nuppercaseKeys( obj )\n    Converts each object key to uppercase.\n\n    The function only transforms own properties. Hence, the function does not\n    transform inherited properties.\n\n    The function shallow copies key values.\n\n    Parameters\n    ----------\n    obj: Object\n        Source object.\n\n    Returns\n    -------\n    out: Object\n        New object.\n\n    Examples\n    --------\n    > var obj = { 'a': 1, 'b': 2 };\n    > var out = uppercaseKeys( obj )\n    { 'A': 1, 'B': 2 }\n\n    See Also\n    --------\n    capitalizeKeys, lowercaseKeys\n","US_STATES_ABBR":"\nUS_STATES_ABBR()\n    Returns a list of US state two-letter abbreviations in alphabetical order\n    according to state name.\n\n    Returns\n    -------\n    out: Array<string>\n        List of US state two-letter abbreviations.\n\n    Examples\n    --------\n    > var list = US_STATES_ABBR()\n    [ 'AL', 'AK', 'AZ', 'AR', ... ]\n\n    See Also\n    --------\n    US_STATES_CAPITALS, US_STATES_NAMES\n","US_STATES_CAPITALS":"\nUS_STATES_CAPITALS()\n    Returns a list of US state capitals in alphabetical order according to state\n    name.\n\n    Returns\n    -------\n    out: Array<string>\n        List of US state capitals.\n\n    Examples\n    --------\n    > var list = US_STATES_CAPITALS()\n    [ 'Montgomery', 'Juneau', 'Phoenix', ... ]\n\n    See Also\n    --------\n    US_STATES_ABBR, US_STATES_CAPITALS_NAMES, US_STATES_NAMES, US_STATES_NAMES_CAPITALS\n","US_STATES_CAPITALS_NAMES":"\nUS_STATES_CAPITALS_NAMES()\n    Returns an object mapping US state capitals to state names.\n\n    Returns\n    -------\n    out: Object\n        An object mapping US state capitals to state names.\n\n    Examples\n    --------\n    > var out = US_STATES_CAPITALS_NAMES()\n    { 'Montgomery': 'Alabama', 'Juneau': 'Alaska', ... }\n\n    See Also\n    --------\n    US_STATES_CAPITALS, US_STATES_NAMES, US_STATES_NAMES_CAPITALS\n","US_STATES_NAMES":"\nUS_STATES_NAMES()\n    Returns a list of US state names in alphabetical order.\n\n    Returns\n    -------\n    out: Array<string>\n        List of US state names.\n\n    Examples\n    --------\n    > var list = US_STATES_NAMES()\n    [ 'Alabama', 'Alaska', 'Arizona', ... ]\n\n    See Also\n    --------\n    US_STATES_ABBR, US_STATES_CAPITALS, US_STATES_CAPITALS_NAMES, US_STATES_NAMES_CAPITALS\n","US_STATES_NAMES_CAPITALS":"\nUS_STATES_NAMES_CAPITALS()\n    Returns an object mapping US state names to state capitals.\n\n    Returns\n    -------\n    out: Object\n        An object mapping US state names to state capitals.\n\n    Examples\n    --------\n    > var out = US_STATES_NAMES_CAPITALS()\n    { 'Alabama': 'Montgomery', 'Alaska': 'Juneau', ... }\n\n    See Also\n    --------\n    US_STATES_CAPITALS, US_STATES_NAMES, US_STATES_NAMES_CAPITALS\n","utf16ToUTF8Array":"\nutf16ToUTF8Array( str )\n    Converts a UTF-16 encoded string to an array of integers using UTF-8\n    encoding.\n\n    The following byte sequences are used to represent a character. The sequence\n    depends on the code point:\n\n        0x00000000 - 0x0000007F:\n            0xxxxxxx\n\n        0x00000080 - 0x000007FF:\n            110xxxxx 10xxxxxx\n\n        0x00000800 - 0x0000FFFF:\n            1110xxxx 10xxxxxx 10xxxxxx\n\n        0x00010000 - 0x001FFFFF:\n            11110xxx 10xxxxxx 10xxxxxx 10xxxxxx\n\n    The `x` bit positions correspond to code point bits.\n\n    Only the shortest possible multi-byte sequence which can represent a code\n    point is used.\n\n    Parameters\n    ----------\n    str: string\n        UTF-16 encoded string.\n\n    Returns\n    -------\n    out: Array\n        Array of integers.\n\n    Examples\n    --------\n    > var str = '☃';\n    > var out = utf16ToUTF8Array( str )\n    [ 226, 152, 131 ]\n\n","vartest":"\nvartest( x, y[, options] )\n    Computes a two-sample F-test for equal variances.\n\n    The returned object comes with a `.print()` method which when invoked will\n    print a formatted output of the results of the hypothesis test.\n\n    Parameters\n    ----------\n    x: Array<number>\n        First data array.\n\n    y: Array<number>\n        Second data array.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.alternative: string (optional)\n        Either `two-sided`, `less` or `greater`.\n\n    options.ratio: number (optional)\n        Positive number denoting the ratio of the two population variances under\n        the null hypothesis. Default: `1`.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Used significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.ci: Array<number>\n        1-alpha confidence interval for the ratio of variances.\n\n    out.nullValue: number\n        Assumed ratio of variances under H0.\n\n    out.xvar: number\n        Sample variance of `x`.\n\n    out.yvar: number\n        Sample variance of `y`.\n\n    out.alternative: string\n        Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n    out.dfX: number\n        Numerator degrees of freedom.\n\n    out.dfY: number\n        Denominator degrees of freedom.\n\n    out.method: string\n        Name of test.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    > var x = [ 610, 610, 550, 590, 565, 570 ];\n    > var y = [ 560, 550, 580, 550, 560, 590, 550, 590 ];\n    > var out = vartest( x, y )\n    {\n        rejected: false,\n        pValue: ~0.399,\n        statistic: ~1.976,\n        ci: [ ~0.374, ~13.542 ],\n        // ...\n    }\n\n    // Print table output:\n    > var table = out.print()\n    F test for comparing two variances\n\n    Alternative hypothesis: True ratio in variances is not equal to 1\n\n        pValue: 0.3992\n        statistic: 1.976\n        variance of x: 617.5 (df of x: 5)\n        variance of y: 312.5 (df of y: 7)\n        95% confidence interval: [0.3739,13.5417]\n\n    Test Decision: Fail to reject null in favor of alternative at 5%\n    significance level\n\n    See Also\n    --------\n    bartlettTest\n","waterfall":"\nwaterfall( fcns, clbk[, thisArg] )\n    Executes functions in series, passing the results of one function as\n    arguments to the next function.\n\n    The last argument applied to each waterfall function is a callback. The\n    callback should be invoked upon a series function completion. The first\n    argument is reserved as an error argument (which can be `null`). Any results\n    which should be passed to the next function in the series should be provided\n    beginning with the second argument.\n\n    If any function calls the provided callback with a truthy `error` argument,\n    the waterfall suspends execution and immediately calls the completion\n    callback for subsequent error handling.\n\n    Execution is *not* guaranteed to be asynchronous. To ensure asynchrony, wrap\n    the completion callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Parameters\n    ----------\n    fcns: Array<Function>\n        Array of functions.\n\n    clbk: Function\n        Callback to invoke upon completion.\n\n    thisArg: any (optional)\n        Function context.\n\n    Examples\n    --------\n    > function foo( next ) { next( null, 'beep' ); };\n    > function bar( str, next ) { console.log( str ); next(); };\n    > function done( error ) { if ( error ) { throw error; } };\n    > var fcns = [ foo, bar ];\n    > waterfall( fcns, done );\n\n\nwaterfall.factory( fcns, clbk[, thisArg] )\n    Returns a reusable waterfall function.\n\n    Parameters\n    ----------\n    fcns: Array<Function>\n        Array of functions.\n\n    clbk: Function\n        Callback to invoke upon completion.\n\n    thisArg: any (optional)\n        Function context.\n\n    Returns\n    -------\n    fcn: Function\n        Waterfall function.\n\n    Examples\n    --------\n    > function foo( next ) { next( null, 'beep' ); };\n    > function bar( str, next ) { console.log( str ); next(); };\n    > function done( error ) { if ( error ) { throw error; } };\n    > var fcns = [ foo, bar ];\n    > var waterfall = waterfall.factory( fcns, done );\n    > waterfall();\n    > waterfall();\n    > waterfall();\n\n","waterfall.factory":"\nwaterfall.factory( fcns, clbk[, thisArg] )\n    Returns a reusable waterfall function.\n\n    Parameters\n    ----------\n    fcns: Array<Function>\n        Array of functions.\n\n    clbk: Function\n        Callback to invoke upon completion.\n\n    thisArg: any (optional)\n        Function context.\n\n    Returns\n    -------\n    fcn: Function\n        Waterfall function.\n\n    Examples\n    --------\n    > function foo( next ) { next( null, 'beep' ); };\n    > function bar( str, next ) { console.log( str ); next(); };\n    > function done( error ) { if ( error ) { throw error; } };\n    > var fcns = [ foo, bar ];\n    > var waterfall = waterfall.factory( fcns, done );\n    > waterfall();\n    > waterfall();\n    > waterfall();","WebAssemblyMemory":"\nWebAssemblyMemory( descriptor )\n    WebAssembly memory constructor.\n\n    Parameters\n    ----------\n    descriptor: Object\n        Memory descriptor object.\n\n    descriptor.initial: integer\n        Initial memory size in units of WebAssembly pages (i.e., 64KiB).\n\n    descriptor.maximum: integer (optional)\n        Maximum memory size in units of WebAssembly pages (i.e., 64KiB).\n\n    descriptor.shared: boolean (optional)\n        Boolean indicating whether the memory is shared. Default: false.\n\n    Returns\n    -------\n    out: Memory\n        WebAssembly memory instance.\n\n    Examples\n    --------\n    > var mem = new WebAssemblyMemory( { 'initial': 0 } )\n    <Memory>\n\n\nWebAssemblyMemory.prototype.buffer\n    Read-only property which returns the ArrayBuffer (or SharedArrayBuffer)\n    referenced by the memory instance.\n\n    Examples\n    --------\n    > var mem = new WebAssemblyMemory( { 'initial': 0 } );\n    > mem.buffer\n    <ArrayBuffer>\n\n\nWebAssemblyMemory.prototype.grow( delta )\n    Increases the size of the memory instance by a specified number of\n    WebAssembly pages (i.e., 64KiB).\n\n    Upon increasing the size, the previous ArrayBuffer is detached, thus\n    invalidating any typed arrays which were views over the previous\n    ArrayBuffer.\n\n    Detachment means that the previous ArrayBuffer byte length becomes zero, and\n    it no longer has bytes accessible to JavaScript.\n\n    ArrayBuffer detachment applies even when `delta` is zero.\n\n    Detachment only applies for non-shared memory instances. For a shared memory\n    instance, the initial buffer (which is a SharedArrayBuffer) will not become\n    detached and, instead, its length will not be updated.\n\n    Accesses to the `buffer` property after growing a SharedArrayBuffer will\n    yield a larger SharedArrayBuffer which may access a larger span of memory\n    than the buffer before growing memory.\n\n    Every SharedArrayBuffer accessed via the `buffer` property will always refer\n    to the start of the same memory address range and thus manipulate the same\n    data.\n\n    Parameters\n    ----------\n    delta: integer\n        Number of WebAssembly pages (i.e., 64KiB) by which to grow the\n        underlying memory.\n\n    Returns\n    -------\n    out: integer\n        Size of the previous memory (in units of pages).\n\n    Examples\n    --------\n    > var mem = new WebAssemblyMemory( { 'initial': 0 } );\n    > mem.grow( 1 )\n    <number>\n\n","WebAssemblyMemory.prototype.buffer":"\nWebAssemblyMemory.prototype.buffer\n    Read-only property which returns the ArrayBuffer (or SharedArrayBuffer)\n    referenced by the memory instance.\n\n    Examples\n    --------\n    > var mem = new WebAssemblyMemory( { 'initial': 0 } );\n    > mem.buffer\n    <ArrayBuffer>","WebAssemblyMemory.prototype.grow":"\nWebAssemblyMemory.prototype.grow( delta )\n    Increases the size of the memory instance by a specified number of\n    WebAssembly pages (i.e., 64KiB).\n\n    Upon increasing the size, the previous ArrayBuffer is detached, thus\n    invalidating any typed arrays which were views over the previous\n    ArrayBuffer.\n\n    Detachment means that the previous ArrayBuffer byte length becomes zero, and\n    it no longer has bytes accessible to JavaScript.\n\n    ArrayBuffer detachment applies even when `delta` is zero.\n\n    Detachment only applies for non-shared memory instances. For a shared memory\n    instance, the initial buffer (which is a SharedArrayBuffer) will not become\n    detached and, instead, its length will not be updated.\n\n    Accesses to the `buffer` property after growing a SharedArrayBuffer will\n    yield a larger SharedArrayBuffer which may access a larger span of memory\n    than the buffer before growing memory.\n\n    Every SharedArrayBuffer accessed via the `buffer` property will always refer\n    to the start of the same memory address range and thus manipulate the same\n    data.\n\n    Parameters\n    ----------\n    delta: integer\n        Number of WebAssembly pages (i.e., 64KiB) by which to grow the\n        underlying memory.\n\n    Returns\n    -------\n    out: integer\n        Size of the previous memory (in units of pages).\n\n    Examples\n    --------\n    > var mem = new WebAssemblyMemory( { 'initial': 0 } );\n    > mem.grow( 1 )\n    <number>","whileAsync":"\nwhileAsync( predicate, fcn, done[, thisArg] )\n    Invokes a function while a test condition is true.\n\n    The predicate function is provided two arguments:\n\n    - i: iteration number (starting from zero).\n    - clbk: a callback indicating whether to invoke `fcn`.\n\n    The `clbk` function accepts two arguments:\n\n    - error: error argument.\n    - bool: test result.\n\n    If the test result is truthy, the function invokes `fcn`; otherwise, the\n    function invokes the `done` callback.\n\n    The function to invoke is provided two arguments:\n\n    - i: iteration number (starting from zero).\n    - next: a callback which must be invoked before proceeding to the next\n      iteration.\n\n    The first argument of the `next` callback is an `error` argument. If `fcn`\n    calls the `next` callback with a truthy `error` argument, the function\n    suspends execution and immediately calls the `done` callback for subsequent\n    `error` handling.\n\n    The `done` callback is invoked with an `error` argument and any arguments\n    passed to the final `next` callback.\n\n    Execution is *not* guaranteed to be asynchronous. To guarantee asynchrony,\n    wrap the `done` callback in a function which either executes at the end of\n    the current stack (e.g., `nextTick`) or during a subsequent turn of the\n    event loop (e.g., `setImmediate`, `setTimeout`).\n\n    Parameters\n    ----------\n    predicate: Function\n        The predicate function which indicates whether to continue invoking a\n        function.\n\n    fcn: Function\n        The function to invoke.\n\n    done: Function\n        Callback to invoke upon completion.\n\n    thisArg: any (optional)\n        Execution context for the invoked function.\n\n    Examples\n    --------\n    > function predicate( i, clbk ) { clbk( null, i < 5 ); };\n    > function fcn( i, next ) {\n    ...     setTimeout( onTimeout, i );\n    ...     function onTimeout() {\n    ...         next( null, 'boop'+i );\n    ...     }\n    ... };\n    > function done( error, result ) {\n    ...     if ( error ) {\n    ...         throw error;\n    ...     }\n    ...     console.log( result );\n    ... };\n    > whileAsync( predicate, fcn, done )\n    boop: 4\n\n    See Also\n    --------\n    doUntilAsync, doWhileAsync, untilAsync, whilst\n","whileEach":"\nwhileEach( collection, predicate, fcn[, thisArg] )\n    While a test condition is true, invokes a function for each element in a\n    collection.\n\n    When invoked, both the predicate function and the function to apply are\n    provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    predicate: Function\n        The predicate function which indicates whether to continue iterating\n        over a collection.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    thisArg: any (optional)\n        Execution context for the applied function.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === v; };\n    > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n    > var arr = [ 1, 2, 3, 4, NaN, 5 ];\n    > whileEach( arr, predicate, logger )\n    0: 1\n    1: 2\n    2: 3\n    3: 4\n\n    See Also\n    --------\n    untilEach, whileEachRight\n","whileEachRight":"\nwhileEachRight( collection, predicate, fcn[, thisArg] )\n    While a test condition is true, invokes a function for each element in a\n    collection, iterating from right to left.\n\n    When invoked, both the predicate function and the function to apply are\n    provided three arguments:\n\n    - value: collection value.\n    - index: collection index.\n    - collection: the input collection.\n\n    Parameters\n    ----------\n    collection: Array|TypedArray|Object\n        Input collection over which to iterate. If provided an object, the\n        object must be array-like (excluding strings and functions).\n\n    predicate: Function\n        The predicate function which indicates whether to continue iterating\n        over a collection.\n\n    fcn: Function\n        The function to invoke for each element in a collection.\n\n    thisArg: any (optional)\n        Execution context for the applied function.\n\n    Returns\n    -------\n    out: Array|TypedArray|Object\n        Input collection.\n\n    Examples\n    --------\n    > function predicate( v ) { return v === v; };\n    > function logger( v, i ) { console.log( '%s: %d', i, v ); };\n    > var arr = [ 1, NaN, 2, 3, 4, 5 ];\n    > whileEachRight( arr, predicate, logger )\n    5: 5\n    4: 4\n    3: 3\n    2: 2\n\n    See Also\n    --------\n    whileEach, untilEachRight\n","whilst":"\nwhilst( predicate, fcn[, thisArg] )\n    Invokes a function while a test condition is true.\n\n    When invoked, both the predicate function and the function to invoke are\n    provided a single argument:\n\n    - i: iteration number (starting from zero).\n\n    Parameters\n    ----------\n    predicate: Function\n        The predicate function which indicates whether to continue invoking a\n        function.\n\n    fcn: Function\n        The function to invoke.\n\n    thisArg: any (optional)\n        Execution context for the invoked function.\n\n    Examples\n    --------\n    > function predicate( i ) { return ( i < 5 ); };\n    > function beep( i ) { console.log( 'boop: %d', i ); };\n    > whilst( predicate, beep )\n    boop: 0\n    boop: 1\n    boop: 2\n    boop: 3\n    boop: 4\n\n    See Also\n    --------\n    doUntil, doWhile, until, whileAsync, whileEach\n","wilcoxon":"\nwilcoxon( x[, y][, options] )\n    Computes a one-sample or paired Wilcoxon signed rank test.\n\n    When no `y` is supplied, the function performs a one-sample  Wilcoxon signed\n    rank test for the null hypothesis that the data is drawn from a symmetric\n    distribution around zero.\n\n    When `y` is supplied, the function tests whether the\n    differences `x - y` come from a symmetric distribution around zero.\n\n    If `x` has less than fifty elements, an exact p-value is computed if there\n    are no zero values or ties. Otherwise, a normal approximation is used.\n\n    The returned object comes with a `.print()` method which when invoked will\n    print a formatted output of the results of the hypothesis test.\n\n    Parameters\n    ----------\n    x: Array<number>|TypedArray\n        Data array.\n\n    y: Array<number>|TypedArray (optional)\n        Paired data array.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.alternative: string (optional)\n        Indicates whether the alternative hypothesis is that the mean of `x` is\n        larger than `mu` (`greater`), smaller than `mu` (`less`), or equal to\n        `mu` (`two-sided`). Default: `'two-sided'`.\n\n    options.correction: boolean (optional)\n        Determines whether to apply continuity correction adjusting the Wilcoxon\n        rank statistic by 0.5 towards the mean when using the normal\n        approximation. Default: `true`.\n\n    options.exact: boolean (optional)\n        Determines whether to force use of the exact distribution instead of a\n        normal approximation when there are more than fifty data points.\n        Default: `false`.\n\n    options.mu: number (optional)\n        Hypothesized true location under the null hypothesis. Set this option to\n        test whether the data comes from a distribution with the specified `mu`.\n        Default: `0`.\n\n    options.zeroMethod: string (optional)\n        Method governing how zero-differences are handled (`pratt`, `wilcox`, or\n        `zsplit`). When set to `pratt`, differences of zero are used to\n        calculate ranks but their ranks are then dropped. When set to `wilcox`,\n        all zero-differences are discarded. When set to `zsplit`, differences of\n        zero are used to rank and their ranks are then split between positive\n        and negative ones. Default: `'wilcox'`.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Used significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.nullValue: number\n        Assumed location parameter under H0.\n\n    out.alternative: string\n        Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n    out.method: string\n        Name of test.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    // One-sample test:\n    > var arr = [ 6, 8, 14, 16, 23, 24, 28, 29, 41, -48, 49, 56, 60, -67, 75 ];\n    > var out = wilcoxon( x )\n    {\n        'rejected': true,\n        'alpha': 0.05,\n        'pValue': 0.04125976562499978,\n        'statistic': 96\n        // ...\n    }\n\n    // Paired test:\n    > runif = base.random.discreteUniform.factory( 1, 5, { 'seed': 786 });\n    > var x = new Array( 100 );\n    > var y = new Array( 100 );\n    > for ( i = 0; i < x.length; i++ ) {\n    ...     x[ i ] = runif();\n    ...     y[ i ] = runif();\n    ... }\n    > out = wilcoxon( x, y )\n    {\n        'rejected': false,\n        'alpha': 0.05,\n        'pValue': 0.21759090963694638,\n        'statistic': 2702.5,\n        // ...\n    }\n\n    // Print formatted output:\n    > var table = out.print()\n    Paired Wilcoxon signed rank test\n\n    Alternative hypothesis: Median of the difference `x - y` is not equal to 0\n\n        pValue: 0.2176\n        statistic: 2702.5\n\n    Test Decision: Fail to reject null in favor of alternative at 5% significance level\n\n\n    // Choose custom significance level:\n    > out = wilcoxon( arr, { 'alpha': 0.01 });\n    > table = out.print()\n    One-Sample Wilcoxon signed rank test\n\n    Alternative hypothesis: Median of `x` is not equal to 0\n\n        pValue: 0.0413\n        statistic: 96\n\n    Test Decision: Fail to reject null in favor of alternative at 1% significance level\n\n\n    // Test for a median equal to ten:\n    > out = wilcoxon( arr, { 'mu': 10 })\n    {\n        'rejected': false,\n        'alpha': 0.05,\n        'pValue': 0.11169650413134602,\n        'statistic': 88.5,\n        'nullValue': 10,\n        // ...\n    }\n\n    // Perform one-sided tests:\n    > out = wilcoxon( arr, { 'alternative': 'less' });\n    > table = out.print()\n    One-Sample Wilcoxon signed rank test\n\n    Alternative hypothesis: Median of `x` is less than 0\n\n        pValue: 0.9823\n        statistic: 96\n\n    Test Decision: Fail to reject null in favor of alternative at 5% significance level\n\n\n    > out = wilcoxon( arr, { 'alternative': 'greater' });\n    > table = out.print()\n    One-Sample Wilcoxon signed rank test\n\n    Alternative hypothesis: Median of `x` is greater than 0\n\n        pValue: 0.0206\n        statistic: 96\n\n    Test Decision: Reject null in favor of alternative at 5% significance level\n\n    See Also\n    --------\n    ttest, ztest\n","writableProperties":"\nwritableProperties( value )\n    Returns an array of an object's own writable property names and symbols.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    props: Array\n        List of an object's own writable properties.\n\n    Examples\n    --------\n    > function Foo() { this.beep = 'boop'; return this; };\n    > Foo.prototype.foo = 'bar';\n    > var obj = new Foo();\n    > var props = writableProperties( obj )\n    [ 'beep' ]\n\n    See Also\n    --------\n    inheritedWritableProperties, writablePropertiesIn, properties\n","writablePropertiesIn":"\nwritablePropertiesIn( value )\n    Returns an array of an object's own and inherited writable property names\n    and symbols.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    props: Array\n        List of an object's own and inherited writable property names and\n        symbols.\n\n    Examples\n    --------\n    > var props = writablePropertiesIn( [] )\n\n    See Also\n    --------\n    inheritedWritableProperties, writableProperties, propertiesIn\n","writablePropertyNames":"\nwritablePropertyNames( value )\n    Returns an array of an object's own writable property names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's own writable property names.\n\n    Examples\n    --------\n    > var obj = { 'a': 'b' };\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = true;\n    > desc.writable = false;\n    > desc.value = 'boop';\n    > defineProperty( obj, 'beep', desc );\n    > var keys = writablePropertyNames( obj )\n    [ 'a' ]\n\n    See Also\n    --------\n    inheritedWritablePropertyNames, writableProperties, writablePropertyNamesIn, writablePropertySymbols, propertyNames\n","writablePropertyNamesIn":"\nwritablePropertyNamesIn( value )\n    Returns an array of an object's own and inherited writable property names.\n\n    Name order is not guaranteed, as object key enumeration is not specified\n    according to the ECMAScript specification. In practice, however, most\n    engines use insertion order to sort an object's keys, thus allowing for\n    deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    keys: Array\n        List of an object's own and inherited writable property names.\n\n    Examples\n    --------\n    > var obj = { 'a': 'b' };\n    > var desc = {};\n    > desc.configurable = true;\n    > desc.enumerable = true;\n    > desc.writable = false;\n    > desc.value = 'boop';\n    > defineProperty( obj, 'beep', desc );\n    > var keys = writablePropertyNamesIn( obj )\n    e.g., [ 'a', ... ]\n\n    See Also\n    --------\n    inheritedWritablePropertyNames, writablePropertiesIn, writablePropertyNames, writablePropertySymbolsIn, propertyNamesIn\n","writablePropertySymbols":"\nwritablePropertySymbols( value )\n    Returns an array of an object's own writable symbol properties.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's own writable symbol properties.\n\n    Examples\n    --------\n    > var obj = {};\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.writable = true;\n    > desc.value = 'boop';\n    > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n    > defineProperty( obj, sym, desc );\n    > var symbols = writablePropertySymbols( obj )\n\n    See Also\n    --------\n    inheritedWritablePropertySymbols, writableProperties, writablePropertyNames, writablePropertySymbolsIn, propertySymbols\n","writablePropertySymbolsIn":"\nwritablePropertySymbolsIn( value )\n    Returns an array of an object's own and inherited writable symbol\n    properties.\n\n    Property order is not guaranteed, as object property enumeration is not\n    specified according to the ECMAScript specification. In practice, however,\n    most engines use insertion order to sort an object's properties, thus\n    allowing for deterministic extraction.\n\n    If provided `null` or `undefined`, the function returns an empty array.\n\n    Parameters\n    ----------\n    value: any\n        Input value.\n\n    Returns\n    -------\n    symbols: Array\n        List of an object's own and inherited writable symbol properties.\n\n    Examples\n    --------\n    > var obj = {};\n    > var desc = {};\n    > desc.configurable = false;\n    > desc.enumerable = false;\n    > desc.writable = true;\n    > desc.value = 'boop';\n    > var sym = ( Symbol ) ? Symbol( 'beep' ) : 'beep';\n    > defineProperty( obj, sym, desc );\n    > var symbols = writablePropertySymbolsIn( obj )\n\n    See Also\n    --------\n    inheritedWritablePropertySymbols, writablePropertiesIn, writablePropertyNamesIn, writablePropertySymbols, propertySymbolsIn\n","writeFile":"\nwriteFile( file, data[, options], clbk )\n    Asynchronously writes data to a file.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    data: string|Buffer\n        Data to write.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. The encoding option is ignored if the data argument is a\n        buffer. Default: 'utf8'.\n\n    options.flag: string (optional)\n        Flag. Default: 'w'.\n\n    options.mode: integer (optional)\n        Mode. Default: 0o666.\n\n    clbk: Function\n        Callback to invoke upon writing data to a file.\n\n    Examples\n    --------\n    > function onWrite( error ) {\n    ...     if ( error ) {\n    ...         console.error( error.message );\n    ...     }\n    ... };\n    > writeFile( './beep/boop.txt', 'beep boop', onWrite );\n\n\nwriteFile.sync( file, data[, options] )\n    Synchronously writes data to a file.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    data: string|Buffer\n        Data to write.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. The encoding option is ignored if the data argument is a\n        buffer. Default: 'utf8'.\n\n    options.flag: string (optional)\n        Flag. Default: 'w'.\n\n    options.mode: integer (optional)\n        Mode. Default: 0o666.\n\n    Returns\n    -------\n    err: Error|null\n        Error object or null.\n\n    Examples\n    --------\n    > var err = writeFile.sync( './beep/boop.txt', 'beep boop' );\n\n    See Also\n    --------\n    exists, readFile\n","writeFile.sync":"\nwriteFile.sync( file, data[, options] )\n    Synchronously writes data to a file.\n\n    Parameters\n    ----------\n    file: string|Buffer|integer\n        Filename or file descriptor.\n\n    data: string|Buffer\n        Data to write.\n\n    options: Object|string (optional)\n        Options. If a string, the value is the encoding.\n\n    options.encoding: string|null (optional)\n        Encoding. The encoding option is ignored if the data argument is a\n        buffer. Default: 'utf8'.\n\n    options.flag: string (optional)\n        Flag. Default: 'w'.\n\n    options.mode: integer (optional)\n        Mode. Default: 0o666.\n\n    Returns\n    -------\n    err: Error|null\n        Error object or null.\n\n    Examples\n    --------\n    > var err = writeFile.sync( './beep/boop.txt', 'beep boop' );\n\n    See Also\n    --------\n    exists, readFile","zip":"\nzip( ...arr[, options] )\n    Generates array tuples from input arrays.\n\n    Parameters\n    ----------\n    arr: ...Array\n        Input arrays to be zipped.\n\n    options: Object (optional)\n        Options.\n\n    options.trunc: boolean (optional)\n        Boolean indicating whether to truncate arrays longer than the shortest\n        input array. Default: `true`.\n\n    options.fill: any (optional)\n        Fill value used for arrays of unequal length. Default: `null`.\n\n    options.arrays: boolean (optional)\n        Boolean indicating whether an input array should be interpreted as an\n        array of arrays to be zipped. Default: `false`.\n\n    Returns\n    -------\n    out: Array\n        Array of arrays.\n\n    Examples\n    --------\n    // Basic usage:\n    > var out = zip( [ 1, 2 ], [ 'a', 'b' ] )\n    [ [ 1, 'a' ], [ 2, 'b' ] ]\n\n    // Turn off truncation:\n    > var opts = { 'trunc': false };\n    > out = zip( [ 1, 2, 3 ], [ 'a', 'b' ], opts )\n    [ [ 1, 'a' ], [ 2, 'b' ], [ 3, null ] ]\n\n    See Also\n    --------\n    unzip\n","ztest":"\nztest( x, sigma[, options] )\n    Computes a one-sample z-test.\n\n    The function performs a one-sample z-test for the null hypothesis that the\n    data in array or typed array `x` is drawn from a normal distribution with\n    mean zero and standard deviation `sigma`.\n\n    The returned object comes with a `.print()` method which when invoked will\n    print a formatted output of the results of the hypothesis test.\n\n    Parameters\n    ----------\n    x: Array<number>\n        Data array.\n\n    sigma: number\n        Known standard deviation.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.alternative: string (optional)\n        Indicates whether the alternative hypothesis is that the mean of `x` is\n        larger than `mu` (`greater`), smaller than `mu` (`less`) or equal to\n        `mu` (`two-sided`). Default: `'two-sided'`.\n\n    options.mu: number (optional)\n        Hypothesized true mean under the null hypothesis. Set this option to\n        test whether the data comes from a distribution with the specified `mu`.\n        Default: `0`.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Used significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.ci: Array<number>\n        1-alpha confidence interval for mean.\n\n    out.nullValue: number\n        Assumed mean value under H0.\n\n    out.sd: number\n        Standard error.\n\n    out.alternative: string\n        Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n    out.method: string\n        Name of test (`One-Sample z-test`).\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    // One-sample z-test:\n    > var rnorm = base.random.normal.factory( 0.0, 2.0, { 'seed': 212 } );\n    > var x = new Array( 100 );\n    > for ( var i = 0; i < x.length; i++ ) {\n    ...     x[ i ] = rnorm();\n    ... }\n    > var out = ztest( x, 2.0 )\n    {\n        alpha: 0.05,\n        rejected: false,\n        pValue: ~0.180,\n        statistic: ~-1.34,\n        ci: [ ~-0.66, ~0.124 ],\n        ...\n    }\n\n    // Choose custom significance level and print output:\n    > arr = [ 2, 4, 3, 1, 0 ];\n    > out = ztest( arr, 2.0, { 'alpha': 0.01 } );\n    > table = out.print()\n    One-sample z-test\n\n    Alternative hypothesis: True mean is not equal to 0\n\n        pValue: 0.0253\n        statistic: 2.2361\n        99% confidence interval: [-0.3039,4.3039]\n\n    Test Decision: Fail to reject null in favor of alternative at 1%\n    significance level\n\n\n    // Test for a mean equal to five:\n    > var arr = [ 4, 4, 6, 6, 5 ];\n    > out = ztest( arr, 1.0, { 'mu': 5 } )\n    {\n        rejected: false,\n        pValue: 1,\n        statistic: 0,\n        ci: [ ~4.123, ~5.877 ],\n        // ...\n    }\n\n    // Perform one-sided tests:\n    > arr = [ 4, 4, 6, 6, 5 ];\n    > out = ztest( arr, 1.0, { 'alternative': 'less' } )\n    {\n        alpha: 0.05,\n        rejected: false,\n        pValue: 1,\n        statistic: 11.180339887498949,\n        ci: [ -Infinity, 5.735600904580115 ],\n        // ...\n    }\n    > out = ztest( arr, 1.0, { 'alternative': 'greater' } )\n    {\n        alpha: 0.05,\n        rejected: true,\n        pValue: 0,\n        statistic: 11.180339887498949,\n        ci: [ 4.264399095419885, Infinity ],\n        //...\n    }\n\n    See Also\n    --------\n    ztest2\n","ztest2":"\nztest2( x, y, sigmax, sigmay[, options] )\n    Computes a two-sample z-test.\n\n    By default, the function performs a two-sample z-test for the null\n    hypothesis that the data in arrays or typed arrays `x` and `y` is\n    independently drawn from normal distributions with equal means and known\n    standard deviations `sigmax` and `sigmay`.\n\n    The returned object comes with a `.print()` method which when invoked will\n    print a formatted output of the results of the hypothesis test.\n\n    Parameters\n    ----------\n    x: Array<number>\n        First data array.\n\n    y: Array<number>\n        Second data array.\n\n    sigmax: number\n        Known standard deviation of first group.\n\n    sigmay: number\n        Known standard deviation of second group.\n\n    options: Object (optional)\n        Options.\n\n    options.alpha: number (optional)\n        Number in the interval `[0,1]` giving the significance level of the\n        hypothesis test. Default: `0.05`.\n\n    options.alternative: string (optional)\n        Either `two-sided`, `less` or `greater`. Indicates whether the\n        alternative hypothesis is that `x` has a larger mean than `y`\n        (`greater`), `x` has a smaller mean than `y` (`less`) or the means are\n        the same (`two-sided`). Default: `'two-sided'`.\n\n    options.difference: number (optional)\n        Number denoting the difference in means under the null hypothesis.\n        Default: `0`.\n\n    Returns\n    -------\n    out: Object\n        Test result object.\n\n    out.alpha: number\n        Used significance level.\n\n    out.rejected: boolean\n        Test decision.\n\n    out.pValue: number\n        p-value of the test.\n\n    out.statistic: number\n        Value of test statistic.\n\n    out.ci: Array<number>\n        1-alpha confidence interval for the mean.\n\n    out.nullValue: number\n        Assumed difference in means under H0.\n\n    out.xmean: number\n        Sample mean of `x`.\n\n    out.ymean: number\n        Sample mean of `y`.\n\n    out.alternative: string\n        Alternative hypothesis (`two-sided`, `less` or `greater`).\n\n    out.method: string\n        Name of test.\n\n    out.print: Function\n        Function to print formatted output.\n\n    Examples\n    --------\n    // Drawn from Normal(0,2):\n    > var x = [ -0.21, 0.14, 1.65, 2.11, -1.86, -0.29, 1.48, 0.81, 0.86, 1.04 ];\n\n    // Drawn from Normal(1,2):\n    > var y = [ -1.53, -2.93, 2.34, -1.15, 2.7, -0.12, 4.22, 1.66, 3.43, 4.66 ];\n    > var out = ztest2( x, y, 2.0, 2.0 )\n    {\n        alpha: 0.05,\n        rejected: false,\n        pValue: ~0.398,\n        statistic: ~-0.844\n        ci: [ ~-2.508, ~0.988 ],\n        alternative: 'two-sided',\n        method: 'Two-sample z-test',\n        nullValue: 0,\n        xmean: ~0.573,\n        ymean: ~1.328\n    }\n\n    // Print table output:\n    > var table = out.print()\n    Two-sample z-test\n\n    Alternative hypothesis: True difference in means is not equal to 0\n\n        pValue: 0.3986\n        statistic: -0.8441\n        95% confidence interval: [-2.508,0.998]\n\n    Test Decision: Fail to reject null in favor of alternative at 5%\n    significance level\n\n    // Choose a different significance level than `0.05`:\n    > out = ztest2( x, y, 2.0, 2.0, { 'alpha': 0.4 } );\n    > table = out.print()\n    Two-sample z-test\n\n    Alternative hypothesis: True difference in means is not equal to 0\n\n        pValue: 0.3986\n        statistic: -0.8441\n        60% confidence interval: [-1.5078,-0.0022]\n\n    Test Decision: Reject null in favor of alternative at 40% significance level\n\n    // Perform one-sided tests:\n    > out = ztest2( x, y, 2.0, 2.0, { 'alternative': 'less' } );\n    > table = out.print()\n    Two-sample z-test\n\n    Alternative hypothesis: True difference in means is less than 0\n\n        pValue: 0.1993\n        statistic: -0.8441\n        95% confidence interval: [-Infinity,0.7162]\n\n    Test Decision: Fail to reject null in favor of alternative at 5%\n    significance level\n\n\n    > out = ztest2( x, y, 2.0, 2.0, { 'alternative': 'greater' } );\n    > table = out.print()\n    Two-sample z-test\n\n    Alternative hypothesis: True difference in means is greater than 0\n\n        pValue: 0.8007\n        statistic: -0.8441\n        95% confidence interval: [-2.2262,Infinity]\n\n    Test Decision: Fail to reject null in favor of alternative at 5%\n    significance level\n\n    // Test for a difference in means besides zero:\n    > var rnorm = base.random.normal.factory({ 'seed': 372 } );\n    > x = new Array( 100 );\n    > for ( i = 0; i < x.length; i++ ) {\n    ...     x[ i ] = rnorm( 2.0, 1.0 );\n    ... }\n    > y = new Array( 100 );\n    ... for ( i = 0; i < x.length; i++ ) {\n    ...     y[ i ] = rnorm( 0.0, 2.0 );\n    ... }\n    > out = ztest2( x, y, 1.0, 2.0, { 'difference': 2.0 } )\n    {\n        rejected: false,\n        pValue: ~0.35,\n        statistic: ~-0.935\n        ci: [ ~1.353, ~2.229 ],\n        // ...\n    }\n\n    See Also\n    --------\n    ztest\n"}
diff --git a/lib/node_modules/@stdlib/repl/info/data/data.csv b/lib/node_modules/@stdlib/repl/info/data/data.csv
index 66d3e355ff10..9d102da0ee01 100644
--- a/lib/node_modules/@stdlib/repl/info/data/data.csv
+++ b/lib/node_modules/@stdlib/repl/info/data/data.csv
@@ -1822,8 +1822,8 @@ base.strided.dnanmeanpn,"\nbase.strided.dnanmeanpn( N:integer, x:Float64Array, s
 base.strided.dnanmeanpn.ndarray,"\nbase.strided.dnanmeanpn.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction algorithm\n    and alternative indexing semantics.\n"
 base.strided.dnanmeanpw,"\nbase.strided.dnanmeanpw( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using pairwise summation.\n"
 base.strided.dnanmeanpw.ndarray,"\nbase.strided.dnanmeanpw.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using pairwise summation and alternative\n    indexing semantics.\n"
-base.strided.dnanmeanwd,"\nbase.strided.dnanmeanwd( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, using Welford's algorithm and ignoring `NaN` values.\n"
-base.strided.dnanmeanwd.ndarray,"\nbase.strided.dnanmeanwd.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n"
+base.strided.dnanmeanwd,"\nbase.strided.dnanmeanwd( N:integer, x:Float64Array, strideX:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, using Welford's algorithm and ignoring `NaN` values.\n"
+base.strided.dnanmeanwd.ndarray,"\nbase.strided.dnanmeanwd.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n"
 base.strided.dnanmin,"\nbase.strided.dnanmin( N:integer, x:Float64Array, strideX:integer )\n    Computes the minimum value of a double-precision floating-point strided\n    array, ignoring `NaN` values.\n"
 base.strided.dnanmin.ndarray,"\nbase.strided.dnanmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the minimum value of a double-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n"
 base.strided.dnanminabs,"\nbase.strided.dnanminabs( N:integer, x:Float64Array, strideX:integer )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array, ignoring `NaN` values.\n"
@@ -2311,16 +2311,16 @@ base.strided.smeanpw,"\nbase.strided.smeanpw( N:integer, x:Float32Array, stride:
 base.strided.smeanpw.ndarray,"\nbase.strided.smeanpw.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using pairwise summation and alternative indexing semantics.\n"
 base.strided.smeanwd,"\nbase.strided.smeanwd( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using Welford's algorithm.\n"
 base.strided.smeanwd.ndarray,"\nbase.strided.smeanwd.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n"
-base.strided.smediansorted,"\nbase.strided.smediansorted( N:integer, x:Float32Array, stride:integer )\n    Computes the median value of a sorted single-precision floating-point\n    strided array.\n"
-base.strided.smediansorted.ndarray,"\nbase.strided.smediansorted.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the median value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n"
+base.strided.smediansorted,"\nbase.strided.smediansorted( N:integer, x:Float32Array, strideX:integer )\n    Computes the median value of a sorted single-precision floating-point\n    strided array.\n"
+base.strided.smediansorted.ndarray,"\nbase.strided.smediansorted.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the median value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n"
 base.strided.smidrange,"\nbase.strided.smidrange( N:integer, x:Float32Array, strideX:integer )\n    Computes the mid-range of a single-precision floating-point strided array.\n"
 base.strided.smidrange.ndarray,"\nbase.strided.smidrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the mid-range of a single-precision floating-point strided array\n    using alternative indexing semantics.\n"
 base.strided.smin,"\nbase.strided.smin( N:integer, x:Float32Array, strideX:integer )\n    Computes the minimum value of a single-precision floating-point strided\n    array.\n"
 base.strided.smin.ndarray,"\nbase.strided.smin.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the minimum value of a single-precision floating-point strided\n    array using alternative indexing semantics.\n"
 base.strided.sminabs,"\nbase.strided.sminabs( N:integer, x:Float32Array, strideX:integer )\n    Computes the minimum absolute value of a single-precision floating-point\n    strided array.\n"
 base.strided.sminabs.ndarray,"\nbase.strided.sminabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the minimum absolute value of a single-precision floating-point\n    strided array using alternative indexing semantics.\n"
-base.strided.sminsorted,"\nbase.strided.sminsorted( N:integer, x:Float32Array, stride:integer )\n    Computes the minimum value of a sorted single-precision floating-point\n    strided array.\n"
-base.strided.sminsorted.ndarray,"\nbase.strided.sminsorted.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the minimum value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n"
+base.strided.sminsorted,"\nbase.strided.sminsorted( N:integer, x:Float32Array, strideX:integer )\n    Computes the minimum value of a sorted single-precision floating-point\n    strided array.\n"
+base.strided.sminsorted.ndarray,"\nbase.strided.sminsorted.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the minimum value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n"
 base.strided.smskabs,"\nbase.strided.smskabs( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Computes the absolute value for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`.\n"
 base.strided.smskabs.ndarray,"\nbase.strided.smskabs.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n  sy:integer, oy:integer )\n    Computes the absolute value for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n"
 base.strided.smskabs2,"\nbase.strided.smskabs2( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Computes the squared absolute value for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point\n    strided array `y`.\n"
diff --git a/lib/node_modules/@stdlib/repl/info/data/data.json b/lib/node_modules/@stdlib/repl/info/data/data.json
index 5586f874860c..1f61e5c2eb50 100644
--- a/lib/node_modules/@stdlib/repl/info/data/data.json
+++ b/lib/node_modules/@stdlib/repl/info/data/data.json
@@ -1 +1 @@
-{"abs":"\nabs( x:ndarray|ArrayLikeObject|number[, options:Object] )\n    Computes the absolute value.\n","abs.assign":"\nabs.assign( x:ndarray|ArrayLikeObject, y:ndarray|ArrayLikeObject )\n    Computes the absolute value and assigns results to a provided output array.\n","acartesianPower":"\nacartesianPower( x:ArrayLikeObject, n:integer )\n    Returns the Cartesian power.\n","acartesianProduct":"\nacartesianProduct( x1:ArrayLikeObject, x2:ArrayLikeObject )\n    Returns the Cartesian product.\n","acartesianSquare":"\nacartesianSquare( x:ArrayLikeObject )\n    Returns the Cartesian square.\n","acronym":"\nacronym( str:string[, options:Object] )\n    Generates an acronym for a given string.\n","aempty":"\naempty( length:integer[, dtype:string] )\n    Creates an uninitialized array having a specified length.\n","aemptyLike":"\naemptyLike( x:TypedArray|Array[, dtype:string] )\n    Creates an uninitialized array having the same length and data type as a\n    provided input array.\n","AFINN_96":"\nAFINN_96()\n    Returns a list of English words rated for valence.\n","AFINN_111":"\nAFINN_111()\n    Returns a list of English words rated for valence.\n","afull":"\nafull( length:integer, value:any[, dtype:string] )\n    Returns a filled array having a specified length.\n","afullLike":"\nafullLike( x:TypedArray|Array[, dtype:string] )\n    Returns a filled array having the same length and data type as a provided\n    input array.\n","alias2pkg":"\nalias2pkg( alias:string )\n    Returns the package name associated with a provided alias.\n","alias2related":"\nalias2related( alias:string )\n    Returns aliases related to a specified alias.\n","alias2standalone":"\nalias2standalone( alias:string )\n    Returns the standalone package name associated with a provided alias.\n","aliases":"\naliases( [namespace:string] )\n    Returns a list of standard library aliases.\n","allocUnsafe":"\nallocUnsafe( size:integer )\n    Allocates a buffer having a specified number of bytes.\n","amskfilter":"\namskfilter( x:Array|TypedArray|Object, mask:Array|TypedArray|Object )\n    Returns a new array by applying a mask to a provided input array.\n","amskput":"\namskput( x:ArrayLikeObject, mask:ArrayLikeObject, values:ArrayLikeObject[, \n  options:Object] )\n    Replaces elements of an array with provided values according to a provided\n    mask array.\n","amskreject":"\namskreject( x:Array|TypedArray|Object, mask:Array|TypedArray|Object )\n    Returns a new array by applying a mask to a provided input array.\n","anans":"\nanans( length:integer[, dtype:string] )\n    Returns an array filled with NaNs and having a specified length.\n","anansLike":"\nanansLike( x:TypedArray|Array[, dtype:string] )\n    Returns an array filled with NaNs and having the same length and data type\n    as a provided input array.\n","anova1":"\nanova1( x:Array<number>, factor:Array[, options:Object] )\n    Performs a one-way analysis of variance.\n","ANSCOMBES_QUARTET":"\nANSCOMBES_QUARTET()\n    Returns Anscombe's quartet.\n","any":"\nany( collection:Array|TypedArray|Object )\n    Tests whether at least one element in a collection is truthy.\n","anyBy":"\nanyBy( collection:Array|TypedArray|Object, predicate:Function[, thisArg:any ] )\n    Tests whether at least one element in a collection passes a test implemented\n    by a predicate function.\n","anyByAsync":"\nanyByAsync( collection:Array|TypedArray|Object, [options:Object,] \n  predicate:Function, done:Function )\n    Tests whether at least one element in a collection passes a test implemented\n    by a predicate function.\n","anyByAsync.factory":"\nanyByAsync.factory( [options:Object,] predicate:Function )\n    Returns a function which tests whether at least one element in a collection\n    passes a test implemented by a predicate function.\n","anyByRight":"\nanyByRight( collection:Array|TypedArray|Object, predicate:Function[, \n  thisArg:any ] )\n    Tests whether at least one element in a collection passes a test implemented\n    by a predicate function, iterating from right to left.\n","anyByRightAsync":"\nanyByRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n  predicate:Function, done:Function )\n    Tests whether at least one element in a collection passes a test implemented\n    by a predicate function, iterating from right to left.\n","anyByRightAsync.factory":"\nanyByRightAsync.factory( [options:Object,] predicate:Function )\n    Returns a function which tests whether at least one element in a collection\n    passes a test implemented by a predicate function, iterating from right to\n    left.\n","anyInBy":"\nanyInBy( object:Object, predicate:Function[, thisArg:any ] )\n    Tests whether at least one value in an object passes a test implemented by\n    a predicate function.\n","anyOwnBy":"\nanyOwnBy( object:Object, predicate:Function[, thisArg:any ] )\n    Tests whether at least one own property of an object passes a\n    test implemented by a predicate function.\n","aones":"\naones( length:integer[, dtype:string] )\n    Returns an array filled with ones and having a specified length.\n","aonesLike":"\naonesLike( x:TypedArray|Array[, dtype:string] )\n    Returns an array filled with ones and having the same length and data type\n    as a provided input array.\n","aoneTo":"\naoneTo( n:integer[, dtype:string] )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from one.\n","aoneToLike":"\naoneToLike( x:TypedArray|Array[, dtype:string] )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from one and having the same length and data type as a provided\n    input array.\n","APERY":"\nAPERY\n    Apéry's constant.\n","aplace":"\naplace( x:ArrayLikeObject, mask:ArrayLikeObject, values:ArrayLikeObject[, \n  options:Object] )\n    Replaces elements of an array with provided values according to a provided\n    mask array.\n","append":"\nappend( collection1:Array|TypedArray|Object, \n  collection2:Array|TypedArray|Object )\n    Adds the elements of one collection to the end of another collection.\n","aput":"\naput( x:ArrayLikeObject, indices:ArrayLikeObject<integer>, \n  values:ArrayLikeObject[, options:Object] )\n    Replaces specified elements of an array with provided values.\n","ARCH":"\nARCH\n    Operating system CPU architecture for which the JavaScript runtime binary\n    was compiled.\n","argumentFunction":"\nargumentFunction( idx:integer )\n    Returns a function which always returns a specified argument.\n","ARGV":"\nARGV\n    An array containing command-line arguments passed when launching the calling\n    process.\n","array":"\narray( [buffer:Array|TypedArray|Buffer|ndarray,] [options:Object] )\n    Returns a multidimensional array.\n","array2buffer":"\narray2buffer( arr:Array<integer> )\n    Allocates a buffer using an octet array.\n","array2fancy":"\narray2fancy( x:Array|TypedArray|Object[, options:Object] )\n    Converts an array to an object supporting fancy indexing.\n","array2fancy.factory":"\narray2fancy.factory( [options:Object] )\n    Returns a function for converting an array to an object supporting fancy\n    indexing.\n","array2fancy.idx":"\narray2fancy.idx( x:Array|TypedArray|Object[, options:Object] )\n    Wraps a provided array as an array index object.\n","array2iterator":"\narray2iterator( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )\n    Returns an iterator which iterates over the elements of an array-like\n    object.\n","array2iteratorRight":"\narray2iteratorRight( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )\n    Returns an iterator which iterates from right to left over the elements of\n    an array-like object.\n","ArrayBuffer":"\nArrayBuffer( size:integer )\n    Returns an array buffer having a specified number of bytes.\n","ArrayBuffer.length":"\nArrayBuffer.length\n    Number of input arguments the constructor accepts.\n","ArrayBuffer.isView":"\nArrayBuffer.isView( arr:any )\n    Returns a boolean indicating if provided an array buffer view.\n","ArrayBuffer.prototype.byteLength":"\nArrayBuffer.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the array buffer.\n","ArrayBuffer.prototype.slice":"\nArrayBuffer.prototype.slice( [start:integer[, end:integer]] )\n    Copies the bytes of an array buffer to a new array buffer.\n","arraybuffer2buffer":"\narraybuffer2buffer( buf:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Allocates a buffer from an ArrayBuffer.\n","arrayCtors":"\narrayCtors( dtype:string )\n    Returns an array constructor.\n","arrayDataType":"\narrayDataType( array:any )\n    Returns the data type of an array.\n","arrayDataTypes":"\narrayDataTypes( [kind:string] )\n    Returns a list of array data types.\n","ArrayIndex":"\nArrayIndex( x:Array|TypedArray|Object[, options:Object] )\n    Wraps a provided array as an array index object.\n","ArrayIndex.free":"\nArrayIndex.free( id:string )\n    Frees the instance associated with a provided identifier.\n","ArrayIndex.get":"\nArrayIndex.get( id:string )\n    Returns the array associated with the instance having a provided identifier.\n","ArrayIndex.prototype.data":"\nArrayIndex.prototype.data\n    Read-only property returning the underlying index array.\n","ArrayIndex.prototype.dtype":"\nArrayIndex.prototype.dtype\n    Read-only property returning the underlying data type of the index array.\n","ArrayIndex.prototype.id":"\nArrayIndex.prototype.id\n    Read-only property returning the unique identifier associated with an\n    instance.\n","ArrayIndex.prototype.isCached":"\nArrayIndex.prototype.isCached\n    Read-only property returning a boolean indicating whether an array index is\n    actively cached.\n","ArrayIndex.prototype.type":"\nArrayIndex.prototype.type\n    Read-only property returning the array index type.\n","ArrayIndex.prototype.toString":"\nArrayIndex.prototype.toString()\n    Serializes an instance as a string.\n","ArrayIndex.prototype.toJSON":"\nArrayIndex.prototype.toJSON()\n    Serializes an instance as a JSON object.\n","arrayMinDataType":"\narrayMinDataType( value:any )\n    Returns the minimum array data type of the closest \"kind\" necessary for\n    storing a provided scalar value.\n","arrayMostlySafeCasts":"\narrayMostlySafeCasts( [dtype:any] )\n    Returns a list of array data types to which a provided array data type can\n    be safely cast and, for floating-point data types, can be downcast.\n","arrayNextDataType":"\narrayNextDataType( [dtype:string] )\n    Returns the next larger array data type of the same kind.\n","arrayPromotionRules":"\narrayPromotionRules( [dtype1:any, dtype2:any] )\n    Returns the array data type with the smallest size and closest \"kind\" to\n    which array data types can be safely cast.\n","arraySafeCasts":"\narraySafeCasts( [dtype:any] )\n    Returns a list of array data types to which a provided array data type can\n    be safely cast.\n","arraySameKindCasts":"\narraySameKindCasts( [dtype:any] )\n    Returns a list of array data types to which a provided array data type can\n    be safely cast or cast within the same \"kind\".\n","arrayShape":"\narrayShape( arr:ArrayLikeObject )\n    Determines array dimensions.\n","arrayStream":"\narrayStream( src:ArrayLikeObject[, options:Object] )\n    Creates a readable stream from an array-like object.\n","arrayStream.factory":"\narrayStream.factory( [options:Object] )\n    Returns a function for creating readable streams from array-like objects.\n","arrayStream.objectMode":"\narrayStream.objectMode( src:ArrayLikeObject[, options:Object] )\n    Returns an \"objectMode\" readable stream from an array-like object.\n","arrayview2iterator":"\narrayview2iterator( src:ArrayLikeObject[, begin:integer[, end:integer]][, \n  mapFcn:Function[, thisArg:any]] )\n    Returns an iterator which iterates over the elements of an array-like object\n    view.\n","arrayview2iteratorRight":"\narrayview2iteratorRight( src:ArrayLikeObject[, begin:integer[, end:integer]][, \n  mapFcn:Function[, thisArg:any]] )\n    Returns an iterator which iterates from right to left over the elements of\n    an array-like object view.\n","aslice":"\naslice( x:ArrayLikeObject[, start:integer[, end:integer]] )\n    Returns a shallow copy of a portion of an array.\n","AsyncIteratorSymbol":"\nAsyncIteratorSymbol\n    Async iterator symbol.\n","atake":"\natake( x:Array|TypedArray|Object, indices:ArrayLikeObject<integer>[, \n  options:Object] )\n    Takes elements from an array.\n","azeros":"\nazeros( length:integer[, dtype:string] )\n    Returns a zero-filled array having a specified length.\n","azerosLike":"\nazerosLike( x:TypedArray|Array[, dtype:string] )\n    Returns a zero-filled array having the same length and data type as a\n    provided input array.\n","azeroTo":"\nazeroTo( n:integer[, dtype:string] )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from zero.\n","azeroToLike":"\nazeroToLike( x:TypedArray|Array[, dtype:string] )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from zero and having the same length and data type as a provided\n    input array.\n","bartlettTest":"\nbartlettTest( ...x:Array[, options:Object] )\n    Computes Bartlett’s test for equal variances.\n","base.abs":"\nbase.abs( x:number )\n    Computes the absolute value of a double-precision floating-point number `x`.\n","base.abs2":"\nbase.abs2( x:number )\n    Computes the squared absolute value of a double-precision floating-point\n    `x`.\n","base.abs2f":"\nbase.abs2f( x:number )\n    Computes the squared absolute value of a single-precision floating-point\n    `x`.\n","base.absdiff":"\nbase.absdiff( x:number, y:number )\n    Computes the absolute difference.\n","base.absf":"\nbase.absf( x:number )\n    Computes the absolute value of a single-precision floating-point number `x`.\n","base.acartesianPower":"\nbase.acartesianPower( x:ArrayLikeObject, n:integer )\n    Returns the Cartesian power.\n","base.acartesianProduct":"\nbase.acartesianProduct( x1:ArrayLikeObject, x2:ArrayLikeObject )\n    Returns the Cartesian product.\n","base.acartesianSquare":"\nbase.acartesianSquare( x:ArrayLikeObject )\n    Returns the Cartesian square.\n","base.acos":"\nbase.acos( x:number )\n    Compute the arccosine of a double-precision floating-point number.\n","base.acosd":"\nbase.acosd( x:number )\n    Computes the arccosine (in degrees) of a double-precision floating-point \n    number.\n","base.acosf":"\nbase.acosf( x:number )\n    Computes the arccosine of a single-precision floating-point number.\n","base.acosh":"\nbase.acosh( x:number )\n    Computes the hyperbolic arccosine of a double-precision floating-point\n    number.\n","base.acot":"\nbase.acot( x:number )\n    Computes the inverse cotangent of a double-precision floating-point number.\n","base.acotd":"\nbase.acotd( x:number )\n    Computes the arccotangent (in degrees) of a double-precision floating-point\n    number.\n","base.acotf":"\nbase.acotf( x:number )\n    Computes the inverse cotangent of a single-precision floating-point number.\n","base.acoth":"\nbase.acoth( x:number )\n    Computes the inverse hyperbolic cotangent of a double-precision floating-\n    point number.\n","base.acovercos":"\nbase.acovercos( x:number )\n    Computes the inverse coversed cosine.\n","base.acoversin":"\nbase.acoversin( x:number )\n    Computes the inverse coversed sine.\n","base.acsc":"\nbase.acsc( x:number )\n    Computes the arccosecant of a number.\n","base.acscd":"\nbase.acscd( x:number )\n    Computes the arccosecant of (in degrees) a double-precision floating-point\n    number.\n","base.acscdf":"\nbase.acscdf( x:number )\n    Computes the arccosecant (in degrees) of a single-precision floating-point\n    number.\n","base.acscf":"\nbase.acscf( x:number )\n    Computes the arccosecant of a single-precision floating-point number.\n","base.acsch":"\nbase.acsch( x:number )\n    Computes the hyperbolic arccosecant of a number.\n","base.add":"\nbase.add( x:number, y:number )\n    Computes the sum of two double-precision floating-point numbers `x` and `y`.\n","base.add3":"\nbase.add3( x:number, y:number, z:number )\n    Computes the sum of three double-precision floating-point numbers.\n","base.add4":"\nbase.add4( x:number, y:number, z:number, w:number )\n    Computes the sum of four double-precision floating-point numbers.\n","base.add5":"\nbase.add5( x:number, y:number, z:number, w:number, u:number )\n    Computes the sum of five double-precision floating-point numbers.\n","base.addf":"\nbase.addf( x:number, y:number )\n    Computes the sum of two single-precision floating-point numbers `x` and `y`.\n","base.afilled":"\nbase.afilled( value:any, len:integer )\n    Returns a filled \"generic\" array.\n","base.afilled2d":"\nbase.afilled2d( value:any, shape:Array<integer> )\n    Returns a filled two-dimensional nested array.\n","base.afilled2dBy":"\nbase.afilled2dBy( shape:Array<integer>, clbk:Function[, thisArg:any] )\n    Returns a filled two-dimensional nested array according to a provided\n    callback function.\n","base.afilled3d":"\nbase.afilled3d( value:any, shape:Array<integer> )\n    Returns a filled three-dimensional nested array.\n","base.afilled3dBy":"\nbase.afilled3dBy( shape:Array<integer>, clbk:Function[, thisArg:any] )\n    Returns a filled three-dimensional nested array according to a provided\n    callback function.\n","base.afilled4d":"\nbase.afilled4d( value:any, shape:Array<integer> )\n    Returns a filled four-dimensional nested array.\n","base.afilled4dBy":"\nbase.afilled4dBy( shape:Array<integer>, clbk:Function[, thisArg:any] )\n    Returns a filled four-dimensional nested array according to a provided\n    callback function.\n","base.afilled5d":"\nbase.afilled5d( value:any, shape:Array<integer> )\n    Returns a filled five-dimensional nested array.\n","base.afilled5dBy":"\nbase.afilled5dBy( shape:Array<integer>, clbk:Function[, thisArg:any] )\n    Returns a filled five-dimensional nested array according to a provided\n    callback function.\n","base.afilledBy":"\nbase.afilledBy( len:integer, clbk:Function[, thisArg:any] )\n    Returns a filled \"generic\" array according to a provided callback function.\n","base.afillednd":"\nbase.afillednd( value:any, shape:Array<integer> )\n    Returns a filled n-dimensional nested array.\n","base.afilledndBy":"\nbase.afilledndBy( shape:Array<integer>, clbk:Function[, thisArg:any] )\n    Returns a filled n-dimensional nested array according to a callback\n    function.\n","base.afilter":"\nbase.afilter( x:Array|TypedArray|Object, predicate:Function[, thisArg:any] )\n    Returns a shallow copy of an array containing only those elements which pass\n    a test implemented by a predicate function.\n","base.afirst":"\nbase.afirst( arr:ArrayLikeObject )\n    Returns the first element of an array-like object.\n","base.aflatten":"\nbase.aflatten( x:Array, shape:Array<integer>, colexicographic:boolean )\n    Flattens an n-dimensional nested array.\n","base.aflatten.assign":"\nbase.aflatten.assign( x:Array, shape:Array<integer>, colexicographic:boolean, \n  out:Collection, stride:integer, offset:integer )\n    Flattens an n-dimensional nested array and assigns elements to a provided\n    output array.\n","base.aflatten2d":"\nbase.aflatten2d( x:Array, shape:Array<integer>, colexicographic:boolean )\n    Flattens a two-dimensional nested array.\n","base.aflatten2d.assign":"\nbase.aflatten2d.assign( x:Array, shape:Array<integer>, colexicographic:boolean, \n  out:Collection, stride:integer, offset:integer )\n    Flattens a two-dimensional nested array and assigns elements to a provided\n    output array.\n","base.aflatten2dBy":"\nbase.aflatten2dBy( x:Array, shape:Array<integer>, colex:boolean, \n  clbk:Function[, thisArg:any] )\n    Flattens a two-dimensional nested array according to a callback function.\n","base.aflatten2dBy.assign":"\nbase.aflatten2dBy.assign( x:Array, shape:Array<integer>, colex:boolean, \n  out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n    Flattens a two-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n","base.aflatten3d":"\nbase.aflatten3d( x:ArrayLikeObject, shape:Array<integer>, \n  colexicographic:boolean )\n    Flattens a three-dimensional nested array.\n","base.aflatten3d.assign":"\nbase.aflatten3d.assign( x:Array, shape:Array<integer>, colexicographic:boolean, \n  out:Collection, stride:integer, offset:integer )\n    Flattens a three-dimensional nested array and assigns elements to a provided\n    output array.\n","base.aflatten3dBy":"\nbase.aflatten3dBy( x:ArrayLikeObject, shape:Array<integer>, colex:boolean, \n  clbk:Function[, thisArg:any] )\n    Flattens a three-dimensional nested array according to a callback function.\n","base.aflatten3dBy.assign":"\nbase.aflatten3dBy.assign( x:Array, shape:Array<integer>, colex:boolean, \n  out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n    Flattens a three-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n","base.aflatten4d":"\nbase.aflatten4d( x:ArrayLikeObject, shape:Array<integer>, \n  colexicographic:boolean )\n    Flattens a four-dimensional nested array.\n","base.aflatten4d.assign":"\nbase.aflatten4d.assign( x:Array, shape:Array<integer>, colexicographic:boolean, \n  out:Collection, stride:integer, offset:integer )\n    Flattens a four-dimensional nested array and assigns elements to a provided\n    output array.\n","base.aflatten4dBy":"\nbase.aflatten4dBy( x:ArrayLikeObject, shape:Array<integer>, colex:boolean, \n  clbk:Function[, thisArg:any] )\n    Flattens a four-dimensional nested array according to a callback function.\n","base.aflatten4dBy.assign":"\nbase.aflatten4dBy.assign( x:Array, shape:Array<integer>, colex:boolean, \n  out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n    Flattens a four-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n","base.aflatten5d":"\nbase.aflatten5d( x:ArrayLikeObject, shape:Array<integer>, \n  colexicographic:boolean )\n    Flattens a five-dimensional nested array.\n","base.aflatten5d.assign":"\nbase.aflatten5d.assign( x:Array, shape:Array<integer>, colexicographic:boolean, \n  out:Collection, stride:integer, offset:integer )\n    Flattens a five-dimensional nested array and assigns elements to a provided\n    output array.\n","base.aflatten5dBy":"\nbase.aflatten5dBy( x:ArrayLikeObject, shape:Array<integer>, colex:boolean, \n  clbk:Function[, thisArg:any] )\n    Flattens a five-dimensional nested array according to a callback function.\n","base.aflatten5dBy.assign":"\nbase.aflatten5dBy.assign( x:Array, shape:Array<integer>, colex:boolean, \n  out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n    Flattens a five-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n","base.aflattenBy":"\nbase.aflattenBy( x:Array, shape:Array<integer>, colex:boolean, clbk:Function[, \n  thisArg:any] )\n    Flattens an n-dimensional nested array according to a callback function.\n","base.aflattenBy.assign":"\nbase.aflattenBy.assign( x:Array, shape:Array<integer>, colex:boolean, \n  out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n    Flattens an n-dimensional nested array according to a callback function and\n    assigns elements to a provided output array.\n","base.afliplr2d":"\nbase.afliplr2d( x:ArrayLikeObject )\n    Reverses the order of elements along the last dimension of a two-dimensional\n    nested input array.\n","base.afliplr3d":"\nbase.afliplr3d( x:ArrayLikeObject )\n    Reverses the order of elements along the last dimension of a three-\n    dimensional nested input array.\n","base.afliplr4d":"\nbase.afliplr4d( x:ArrayLikeObject )\n    Reverses the order of elements along the last dimension of a four-\n    dimensional nested input array.\n","base.afliplr5d":"\nbase.afliplr5d( x:ArrayLikeObject )\n    Reverses the order of elements along the last dimension of a five-\n    dimensional nested input array.\n","base.aflipud2d":"\nbase.aflipud2d( x:ArrayLikeObject )\n    Reverses the order of elements along the first dimension of a two-\n    dimensional nested input array.\n","base.aflipud3d":"\nbase.aflipud3d( x:ArrayLikeObject )\n    Reverses the order of elements along the second-to-last dimension of a\n    three-dimensional nested input array.\n","base.aflipud4d":"\nbase.aflipud4d( x:ArrayLikeObject )\n    Reverses the order of elements along the second-to-last dimension of a four-\n    dimensional nested input array.\n","base.aflipud5d":"\nbase.aflipud5d( x:ArrayLikeObject )\n    Reverses the order of elements along the second-to-last dimension of a five-\n    dimensional nested input array.\n","base.ahavercos":"\nbase.ahavercos( x:number )\n    Computes the inverse half-value versed cosine.\n","base.ahaversin":"\nbase.ahaversin( x:number )\n    Computes the inverse half-value versed sine.\n","base.altcase":"\nbase.altcase( str:string )\n    Converts a string to alternate case.\n","base.aones":"\nbase.aones( len:integer )\n    Returns a \"generic\" array filled with ones.\n","base.aones2d":"\nbase.aones2d( shape:Array<integer> )\n    Returns a two-dimensional nested array filled with ones.\n","base.aones3d":"\nbase.aones3d( shape:Array<integer> )\n    Returns a three-dimensional nested array filled with ones.\n","base.aones4d":"\nbase.aones4d( shape:Array<integer> )\n    Returns a four-dimensional nested array filled with ones.\n","base.aones5d":"\nbase.aones5d( shape:Array<integer> )\n    Returns a five-dimensional nested array filled with ones.\n","base.aonesnd":"\nbase.aonesnd( shape:Array<integer> )\n    Returns an n-dimensional nested array filled with ones.\n","base.aoneTo":"\nbase.aoneTo( n:number )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from one.\n","base.aoneTo.assign":"\nbase.aoneTo.assign( out:ArrayLikeObject, stride:integer, offset:integer )\n    Fills an array with linearly spaced numeric elements which increment by 1\n    starting from one.\n","base.args2multislice":"\nbase.args2multislice( args:Array<Slice|integer|null|undefined> )\n    Creates a MultiSlice object from a list of MultiSlice constructor arguments.\n","base.asec":"\nbase.asec( x:number )\n    Computes the inverse (arc) secant of a number.\n","base.asecd":"\nbase.asecd( x:number )\n    Computes the arcsecant (in degrees) of a double-precision floating-point\n    number.\n","base.asecdf":"\nbase.asecdf( x:number )\n    Computes the arcsecant (in degrees) of a single-precision floating-point\n    number.\n","base.asecf":"\nbase.asecf( x:number )\n    Computes the inverse (arc) secant of a single-precision\n    floating-point number.\n","base.asech":"\nbase.asech( x:number )\n    Computes the hyperbolic arcsecant of a number.\n","base.asin":"\nbase.asin( x:number )\n    Computes the arcsine of a double-precision floating-point number.\n","base.asind":"\nbase.asind( x:number )\n    Computes the arcsine (in degrees) of a double-precision floating-point\n    number.\n","base.asindf":"\nbase.asindf( x:number )\n    Computes the arcsine (in degrees) of a single-precision floating-point\n    number.\n","base.asinf":"\nbase.asinf( x:number )\n    Computes the arcsine of a single-precision floating-point number.\n","base.asinh":"\nbase.asinh( x:number )\n    Computes the hyperbolic arcsine of a double-precision floating-point number.\n","base.atan":"\nbase.atan( x:number )\n    Computes the arctangent of a double-precision floating-point number.\n","base.atan2":"\nbase.atan2( y:number, x:number )\n    Computes the angle in the plane (in radians) between the positive x-axis and\n    the ray from (0,0) to the point (x,y).\n","base.atand":"\nbase.atand( x:number )\n    Computes the arctangent (in degrees) of a double-precision floating-point\n    number.\n","base.atanf":"\nbase.atanf( x:number )\n    Computes the arctangent of a single-precision floating-point number.\n","base.atanh":"\nbase.atanh( x:number )\n    Computes the hyperbolic arctangent of a double-precision floating-point\n    number.\n","base.avercos":"\nbase.avercos( x:number )\n    Computes the inverse versed cosine.\n","base.aversin":"\nbase.aversin( x:number )\n    Computes the inverse versed sine.\n","base.azeros":"\nbase.azeros( len:integer )\n    Returns a zero-filled \"generic\" array.\n","base.azeros2d":"\nbase.azeros2d( shape:Array<integer> )\n    Returns a zero-filled two-dimensional nested array.\n","base.azeros3d":"\nbase.azeros3d( shape:Array<integer> )\n    Returns a zero-filled three-dimensional nested array.\n","base.azeros4d":"\nbase.azeros4d( shape:Array<integer> )\n    Returns a zero-filled four-dimensional nested array.\n","base.azeros5d":"\nbase.azeros5d( shape:Array<integer> )\n    Returns a zero-filled five-dimensional nested array.\n","base.azerosnd":"\nbase.azerosnd( shape:Array<integer> )\n    Returns a zero-filled n-dimensional nested array.\n","base.azeroTo":"\nbase.azeroTo( n:number )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from zero.\n","base.azeroTo.assign":"\nbase.azeroTo.assign( out:ArrayLikeObject, stride:integer, offset:integer )\n    Fills an array with linearly spaced numeric elements which increment by 1\n    starting from zero.\n","base.bernoulli":"\nbase.bernoulli( n:integer )\n    Computes the nth Bernoulli number.\n","base.besselj0":"\nbase.besselj0( x:number )\n    Computes the Bessel function of the first kind of order zero.\n","base.besselj1":"\nbase.besselj1( x:number )\n    Computes the Bessel function of the first kind of order one.\n","base.bessely0":"\nbase.bessely0( x:number )\n    Computes the Bessel function of the second kind of order zero.\n","base.bessely1":"\nbase.bessely1( x:number )\n    Computes the Bessel function of the second kind of order one.\n","base.beta":"\nbase.beta( x:number, y:number )\n    Evaluates the beta function.\n","base.betainc":"\nbase.betainc( x:number, a:number, b:number[, regularized:boolean[, \n  upper:boolean]] )\n    Computes the regularized incomplete beta function.\n","base.betaincinv":"\nbase.betaincinv( p:number, a:number, b:number[, upper:boolean] )\n    Computes the inverse of the lower incomplete beta function.\n","base.betaln":"\nbase.betaln( a:number, b:number )\n    Evaluates the natural logarithm of the beta function.\n","base.binet":"\nbase.binet( x:number )\n    Evaluates Binet's formula extended to real numbers.\n","base.binomcoef":"\nbase.binomcoef( n:integer, k:integer )\n    Computes the binomial coefficient of two integers.\n","base.binomcoefln":"\nbase.binomcoefln( n:integer, k:integer )\n    Computes the natural logarithm of the binomial coefficient of two integers.\n","base.boxcox":"\nbase.boxcox( x:number, lambda:number )\n    Computes a one-parameter Box-Cox transformation.\n","base.boxcox1p":"\nbase.boxcox1p( x:number, lambda:number )\n    Computes a one-parameter Box-Cox transformation of 1+x.\n","base.boxcox1pinv":"\nbase.boxcox1pinv( y:number, lambda:number )\n    Computes the inverse of a one-parameter Box-Cox transformation for 1+x.\n","base.boxcoxinv":"\nbase.boxcoxinv( y:number, lambda:number )\n    Computes the inverse of a one-parameter Box-Cox transformation.\n","base.cabs":"\nbase.cabs( z:Complex128 )\n    Computes the absolute value of a double-precision complex floating-point\n    number.\n","base.cabs2":"\nbase.cabs2( z:Complex128 )\n    Computes the squared absolute value of a double-precision complex floating-\n    point number.\n","base.cabs2f":"\nbase.cabs2f( z:Complex64 )\n    Computes the squared absolute value of a single-precision complex floating-\n    point number.\n","base.cabsf":"\nbase.cabsf( z:Complex64 )\n    Computes the absolute value of a single-precision complex floating-point\n    number.\n","base.cadd":"\nbase.cadd( z1:Complex128, z2:Complex128 )\n    Adds two double-precision complex floating-point numbers.\n","base.caddf":"\nbase.caddf( z1:Complex64, z2:Complex64 )\n    Adds two single-precision complex floating-point numbers.\n","base.camelcase":"\nbase.camelcase( str:string )\n    Converts a string to camel case.\n","base.capitalize":"\nbase.capitalize( str:string )\n    Capitalizes the first character in a string.\n","base.cbrt":"\nbase.cbrt( x:number )\n    Computes the cube root of a double-precision floating-point number.\n","base.cbrtf":"\nbase.cbrtf( x:number )\n    Computes the cube root of a single-precision floating-point number.\n","base.cceil":"\nbase.cceil( z:Complex128 )\n    Rounds each component of a double-precision complex floating-point number\n    toward positive infinity.\n","base.cceilf":"\nbase.cceilf( z:Complex64 )\n    Rounds a single-precision complex floating-point number toward positive\n    infinity.\n","base.cceiln":"\nbase.cceiln( z:Complex128, n:integer )\n    Rounds each component of a double-precision complex number to the nearest\n    multiple of `10^n` toward positive infinity.\n","base.ccis":"\nbase.ccis( z:Complex128 )\n    Evaluates the cis function for a double-precision complex floating-point\n    number.\n","base.cdiv":"\nbase.cdiv( z1:Complex128, z2:Complex128 )\n    Divides two double-precision complex floating-point numbers.\n","base.ceil":"\nbase.ceil( x:number )\n    Rounds a double-precision floating-point number toward positive infinity.\n","base.ceil2":"\nbase.ceil2( x:number )\n    Rounds a numeric value to the nearest power of two toward positive infinity.\n","base.ceil10":"\nbase.ceil10( x:number )\n    Rounds a numeric value to the nearest power of ten toward positive infinity.\n","base.ceilb":"\nbase.ceilb( x:number, n:integer, b:integer )\n    Rounds a numeric value to the nearest multiple of `b^n` toward positive\n    infinity.\n","base.ceilf":"\nbase.ceilf( x:number )\n    Rounds a single-precision floating-point number toward positive infinity.\n","base.ceiln":"\nbase.ceiln( x:number, n:integer )\n    Rounds a numeric value to the nearest multiple of `10^n` toward positive\n    infinity.\n","base.ceilsd":"\nbase.ceilsd( x:number, n:integer, b:integer )\n    Rounds a numeric value to the nearest number toward positive infinity with\n    `n` significant figures.\n","base.cexp":"\nbase.cexp( z:Complex128 )\n    Evaluates the exponential function for a double-precision complex floating-\n    point number.\n","base.cflipsign":"\nbase.cflipsign( z:Complex128, y:number )\n    Returns a double-precision complex floating-point number with the same\n    magnitude as `z` and the sign of `y*z`.\n","base.cflipsignf":"\nbase.cflipsignf( z:Complex64, y:number )\n    Returns a single-precision complex floating-point number with the same\n    magnitude as `z` and the sign of `y*z`.\n","base.cfloor":"\nbase.cfloor( z:Complex128 )\n    Rounds a double-precision complex floating-point number toward negative\n    infinity.\n","base.cfloorn":"\nbase.cfloorn( z:Complex128, n:integer )\n    Rounds each component of a double-precision complex floating-point number\n    to the nearest multiple of `10^n` toward negative infinity.\n","base.cidentity":"\nbase.cidentity( z:Complex128 )\n    Evaluates the identity function for a double-precision complex floating-\n    point number.\n","base.cidentityf":"\nbase.cidentityf( z:Complex64 )\n    Evaluates the identity function for a single-precision complex floating-\n    point number.\n","base.cinv":"\nbase.cinv( z:Complex128 )\n    Computes the inverse of a double-precision complex floating-point number.\n","base.clamp":"\nbase.clamp( v:number, min:number, max:number )\n    Restricts a double-precision floating-point number to a specified range.\n","base.clampf":"\nbase.clampf( v:number, min:number, max:number )\n    Restricts a single-precision floating-point number to a specified range.\n","base.cmul":"\nbase.cmul( z1:Complex128, z2:Complex128 )\n    Multiplies two double-precision complex floating-point numbers.\n","base.cmulf":"\nbase.cmulf( z1:Complex64, z2:Complex64 )\n    Multiplies two single-precision complex floating-point numbers.\n","base.cneg":"\nbase.cneg( z )\n    Negates a double-precision complex floating-point number.\n","base.cnegf":"\nbase.cnegf( z )\n    Negates a single-precision complex floating-point number.\n","base.codePointAt":"\nbase.codePointAt( str:string, idx:integer, backward:boolean )\n    Returns a Unicode code point from a string at a specified position.\n","base.constantcase":"\nbase.constantcase( str:string )\n    Converts a string to constant case.\n","base.continuedFraction":"\nbase.continuedFraction( generator:Function[, options:Object] )\n    Evaluates the continued fraction approximation for the supplied series\n    generator using the modified Lentz algorithm.\n","base.copysign":"\nbase.copysign( x:number, y:number )\n    Returns a double-precision floating-point number with the magnitude of `x`\n    and the sign of `y`.\n","base.copysignf":"\nbase.copysignf( x:number, y:number )\n    Returns a single-precision floating-point number with the magnitude of `x`\n    and the sign of `y`.\n","base.cos":"\nbase.cos( x:number )\n    Computes the cosine of a number.\n","base.cosd":"\nbase.cosd( x:number )\n    Computes the cosine of an angle measured in degrees.\n","base.cosh":"\nbase.cosh( x:number )\n    Computes the hyperbolic cosine of a double-precision floating-point number.\n","base.cosm1":"\nbase.cosm1( x:number )\n    Computes the cosine of a number minus one.\n","base.cospi":"\nbase.cospi( x:number )\n    Computes the value of `cos(πx)`.\n","base.cot":"\nbase.cot( x:number )\n    Computes the cotangent of a number.\n","base.cotd":"\nbase.cotd( x:number )\n    Computes the cotangent of an angle measured in degrees.\n","base.coth":"\nbase.coth( x:number )\n    Computes the hyperbolic cotangent of a number.\n","base.covercos":"\nbase.covercos( x:number )\n    Computes the coversed cosine.\n","base.coversin":"\nbase.coversin( x:number )\n    Computes the coversed sine.\n","base.cphase":"\nbase.cphase( z:Complex128 )\n    Computes the argument of a double-precision complex floating-point number\n    in radians.\n","base.cpolar":"\nbase.cpolar( z:Complex128 )\n    Returns the absolute value and phase of a double-precision complex\n    floating-point number.\n","base.cpolar.assign":"\nbase.cpolar.assign( z:Complex128, out:Array|TypedArray|Object, stride:integer, \n  offset:integer )\n    Returns the absolute value and phase of a double-precision complex\n    floating-point number and assigns results to a provided output array.\n","base.cround":"\nbase.cround( z:Complex128 )\n    Rounds each component of a double-precision complex floating-point number\n    to the nearest integer.\n","base.croundn":"\nbase.croundn( z:Complex128, n:integer )\n    Rounds each component of a double-precision complex floating-point number\n    to the nearest multiple of `10^n`.\n","base.csc":"\nbase.csc( x:number )\n    Computes the cosecant of a number.\n","base.cscd":"\nbase.cscd( x:number )\n    Computes the cosecant of a degree.\n","base.csch":"\nbase.csch( x:number )\n    Computes the hyperbolic cosecant of a number.\n","base.csignum":"\nbase.csignum( z:Complex128 )\n    Evaluates the signum function of a double-precision complex floating-point\n    number.\n","base.csub":"\nbase.csub( z1:Complex128, z2:Complex128 )\n    Subtracts two double-precision complex floating-point numbers.\n","base.csubf":"\nbase.csubf( z1:Complex64, z2:Complex64 )\n    Subtracts two single-precision complex floating-point numbers.\n","base.deg2rad":"\nbase.deg2rad( x:number )\n    Converts an angle from degrees to radians.\n","base.deg2radf":"\nbase.deg2radf( x:number )\n    Converts an angle from degrees to radians (single-precision).\n","base.digamma":"\nbase.digamma( x:number )\n    Evaluates the digamma function.\n","base.diracDelta":"\nbase.diracDelta( x:number )\n    Evaluates the Dirac delta function.\n","base.div":"\nbase.div( x:number, y:number )\n    Divides two double-precision floating-point numbers `x` and `y`.\n","base.divf":"\nbase.divf( x:number, y:number )\n    Divides two single-precision floating-point numbers `x` and `y`.\n","base.dotcase":"\nbase.dotcase( str:string )\n    Converts a string to dot case.\n","base.dists.arcsine.Arcsine":"\nbase.dists.arcsine.Arcsine( [a:number, b:number] )\n    Returns an arcsine distribution object.\n","base.dists.arcsine.cdf":"\nbase.dists.arcsine.cdf( x:number, a:number, b:number )\n    Evaluates the cumulative distribution function (CDF) for an arcsine\n    distribution with minimum support `a` and maximum support `b` at a value\n    `x`.\n","base.dists.arcsine.cdf.factory":"\nbase.dists.arcsine.cdf.factory( a:number, b:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an arcsine distribution with minimum support `a` and maximum support `b`.\n","base.dists.arcsine.entropy":"\nbase.dists.arcsine.entropy( a:number, b:number )\n    Returns the differential entropy of an arcsine distribution (in nats).\n","base.dists.arcsine.kurtosis":"\nbase.dists.arcsine.kurtosis( a:number, b:number )\n    Returns the excess kurtosis of an arcsine distribution.\n","base.dists.arcsine.logcdf":"\nbase.dists.arcsine.logcdf( x:number, a:number, b:number )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for an\n    arcsine distribution with minimum support `a` and maximum support `b` at a\n    value `x`.\n","base.dists.arcsine.logcdf.factory":"\nbase.dists.arcsine.logcdf.factory( a:number, b:number )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of an arcsine distribution with minimum support\n    `a` and maximum support `b`.\n","base.dists.arcsine.logpdf":"\nbase.dists.arcsine.logpdf( x:number, a:number, b:number )\n    Evaluates the logarithm of the probability density function (PDF) for an\n    arcsine distribution with minimum support `a` and maximum support `b` at a\n    value `x`.\n","base.dists.arcsine.logpdf.factory":"\nbase.dists.arcsine.logpdf.factory( a:number, b:number )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of an arcsine distribution with minimum support `a` and\n    maximum support `b`.\n","base.dists.arcsine.mean":"\nbase.dists.arcsine.mean( a:number, b:number )\n    Returns the expected value of an arcsine distribution.\n","base.dists.arcsine.median":"\nbase.dists.arcsine.median( a:number, b:number )\n    Returns the median of an arcsine distribution.\n","base.dists.arcsine.mode":"\nbase.dists.arcsine.mode( a:number, b:number )\n    Returns the mode of an arcsine distribution.\n","base.dists.arcsine.pdf":"\nbase.dists.arcsine.pdf( x:number, a:number, b:number )\n    Evaluates the probability density function (PDF) for an arcsine distribution\n    with minimum support `a` and maximum support `b` at a value `x`.\n","base.dists.arcsine.pdf.factory":"\nbase.dists.arcsine.pdf.factory( a:number, b:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    an arcsine distribution with minimum support `a` and maximum support `b`.\n","base.dists.arcsine.quantile":"\nbase.dists.arcsine.quantile( p:number, a:number, b:number )\n    Evaluates the quantile function for an arcsine distribution with minimum\n    support `a` and maximum support `b` at a probability `p`.\n","base.dists.arcsine.quantile.factory":"\nbase.dists.arcsine.quantile.factory( a:number, b:number )\n    Returns a function for evaluating the quantile function of an arcsine\n    distribution with minimum support `a` and maximum support `b`.\n","base.dists.arcsine.skewness":"\nbase.dists.arcsine.skewness( a:number, b:number )\n    Returns the skewness of an arcsine distribution.\n","base.dists.arcsine.stdev":"\nbase.dists.arcsine.stdev( a:number, b:number )\n    Returns the standard deviation of an arcsine distribution.\n","base.dists.arcsine.variance":"\nbase.dists.arcsine.variance( a:number, b:number )\n    Returns the variance of an arcsine distribution.\n","base.dists.bernoulli.Bernoulli":"\nbase.dists.bernoulli.Bernoulli( [p:number] )\n    Returns a Bernoulli distribution object.\n","base.dists.bernoulli.cdf":"\nbase.dists.bernoulli.cdf( x:number, p:number )\n    Evaluates the cumulative distribution function (CDF) for a Bernoulli\n    distribution with success probability `p` at a value `x`.\n","base.dists.bernoulli.cdf.factory":"\nbase.dists.bernoulli.cdf.factory( p:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.entropy":"\nbase.dists.bernoulli.entropy( p:number )\n    Returns the entropy of a Bernoulli distribution with success probability\n    `p` (in nats).\n","base.dists.bernoulli.kurtosis":"\nbase.dists.bernoulli.kurtosis( p:number )\n    Returns the excess kurtosis of a Bernoulli distribution with success\n    probability `p`.\n","base.dists.bernoulli.mean":"\nbase.dists.bernoulli.mean( p:number )\n    Returns the expected value of a Bernoulli distribution with success\n    probability `p`.\n","base.dists.bernoulli.median":"\nbase.dists.bernoulli.median( p:number )\n    Returns the median of a Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.mgf":"\nbase.dists.bernoulli.mgf( t:number, p:number )\n    Evaluates the moment-generating function (MGF) for a Bernoulli\n    distribution with success probability `p` at a value `t`.\n","base.dists.bernoulli.mgf.factory":"\nbase.dists.bernoulli.mgf.factory( p:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.mode":"\nbase.dists.bernoulli.mode( p:number )\n    Returns the mode of a Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.pmf":"\nbase.dists.bernoulli.pmf( x:number, p:number )\n    Evaluates the probability mass function (PMF) for a Bernoulli distribution\n    with success probability `p` at a value `x`.\n","base.dists.bernoulli.pmf.factory":"\nbase.dists.bernoulli.pmf.factory( p:number )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.quantile":"\nbase.dists.bernoulli.quantile( r:number, p:number )\n    Evaluates the quantile function for a Bernoulli distribution with success\n    probability `p` at a probability `r`.\n","base.dists.bernoulli.quantile.factory":"\nbase.dists.bernoulli.quantile.factory( p:number )\n    Returns a function for evaluating the quantile function of a Bernoulli\n    distribution with success probability `p`.\n","base.dists.bernoulli.skewness":"\nbase.dists.bernoulli.skewness( p:number )\n    Returns the skewness of a Bernoulli distribution with success probability\n    `p`.\n","base.dists.bernoulli.stdev":"\nbase.dists.bernoulli.stdev( p:number )\n    Returns the standard deviation of a Bernoulli distribution with success\n    probability `p`.\n","base.dists.bernoulli.variance":"\nbase.dists.bernoulli.variance( p:number )\n    Returns the variance of a Bernoulli distribution with success probability\n    `p`.\n","base.dists.beta.Beta":"\nbase.dists.beta.Beta( [α:number, β:number] )\n    Returns a beta distribution object.\n","base.dists.beta.cdf":"\nbase.dists.beta.cdf( x:number, α:number, β:number )\n    Evaluates the cumulative distribution function (CDF) for a beta distribution\n    with first shape parameter `α` and second shape parameter `β` at a value\n    `x`.\n","base.dists.beta.cdf.factory":"\nbase.dists.beta.cdf.factory( α:number, β:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a beta distribution with first shape parameter `α` and second shape\n    parameter `β`.\n","base.dists.beta.entropy":"\nbase.dists.beta.entropy( α:number, β:number )\n    Returns the differential entropy of a beta distribution.\n","base.dists.beta.kurtosis":"\nbase.dists.beta.kurtosis( α:number, β:number )\n    Returns the excess kurtosis of a beta distribution.\n","base.dists.beta.logcdf":"\nbase.dists.beta.logcdf( x:number, α:number, β:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a beta distribution with first shape parameter `α` and second\n    shape parameter `β` at a value `x`.\n","base.dists.beta.logcdf.factory":"\nbase.dists.beta.logcdf.factory( α:number, β:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a beta distribution with first shape\n    parameter `α` and second shape parameter `β`.\n","base.dists.beta.logpdf":"\nbase.dists.beta.logpdf( x:number, α:number, β:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a beta distribution with first shape parameter `α` and second shape\n    parameter `β` at a value `x`.\n","base.dists.beta.logpdf.factory":"\nbase.dists.beta.logpdf.factory( α:number, β:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a beta distribution with first shape parameter `α`\n    and second shape parameter `β`.\n","base.dists.beta.mean":"\nbase.dists.beta.mean( α:number, β:number )\n    Returns the expected value of a beta distribution.\n","base.dists.beta.median":"\nbase.dists.beta.median( α:number, β:number )\n    Returns the median of a beta distribution.\n","base.dists.beta.mgf":"\nbase.dists.beta.mgf( t:number, α:number, β:number )\n    Evaluates the moment-generating function (MGF) for a beta distribution with\n    first shape parameter `α` and second shape parameter `β` at a value `t`.\n","base.dists.beta.mgf.factory":"\nbase.dists.beta.mgf.factory( α:number, β:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    beta distribution with first shape parameter `α` and second shape parameter\n    `β`.\n","base.dists.beta.mode":"\nbase.dists.beta.mode( α:number, β:number )\n    Returns the mode of a beta distribution.\n","base.dists.beta.pdf":"\nbase.dists.beta.pdf( x:number, α:number, β:number )\n    Evaluates the probability density function (PDF) for a beta distribution\n    with first shape parameter `α` and second shape parameter `β` at a value\n    `x`.\n","base.dists.beta.pdf.factory":"\nbase.dists.beta.pdf.factory( α:number, β:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a beta distribution with first shape parameter `α` and second shape\n    parameter `β`.\n","base.dists.beta.quantile":"\nbase.dists.beta.quantile( p:number, α:number, β:number )\n    Evaluates the quantile function for a beta distribution with first shape\n    parameter `α` and second shape parameter `β` at a probability `p`.\n","base.dists.beta.quantile.factory":"\nbase.dists.beta.quantile.factory( α:number, β:number )\n    Returns a function for evaluating the quantile function of a beta\n    distribution with first shape parameter `α` and second shape parameter `β`.\n","base.dists.beta.skewness":"\nbase.dists.beta.skewness( α:number, β:number )\n    Returns the skewness of a beta distribution.\n","base.dists.beta.stdev":"\nbase.dists.beta.stdev( α:number, β:number )\n    Returns the standard deviation of a beta distribution.\n","base.dists.beta.variance":"\nbase.dists.beta.variance( α:number, β:number )\n    Returns the variance of a beta distribution.\n","base.dists.betaprime.BetaPrime":"\nbase.dists.betaprime.BetaPrime( [α:number, β:number] )\n    Returns a beta prime distribution object.\n","base.dists.betaprime.cdf":"\nbase.dists.betaprime.cdf( x:number, α:number, β:number )\n    Evaluates the cumulative distribution function (CDF) for a beta prime\n    distribution with first shape parameter `α` and second shape parameter `β`\n    at a value `x`.\n","base.dists.betaprime.cdf.factory":"\nbase.dists.betaprime.cdf.factory( α:number, β:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a beta prime distribution with first shape parameter `α` and second shape\n    parameter `β`.\n","base.dists.betaprime.kurtosis":"\nbase.dists.betaprime.kurtosis( α:number, β:number )\n    Returns the excess kurtosis of a beta prime distribution.\n","base.dists.betaprime.logcdf":"\nbase.dists.betaprime.logcdf( x:number, α:number, β:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a beta prime distribution with first shape parameter `α` and\n    second shape parameter `β` at a value `x`.\n","base.dists.betaprime.logcdf.factory":"\nbase.dists.betaprime.logcdf.factory( α:number, β:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a beta prime distribution with first shape\n    parameter `α` and second shape parameter `β`.\n","base.dists.betaprime.logpdf":"\nbase.dists.betaprime.logpdf( x:number, α:number, β:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a beta prime distribution with first shape parameter `α` and second\n    shape parameter `β` at a value `x`.\n","base.dists.betaprime.logpdf.factory":"\nbase.dists.betaprime.logpdf.factory( α:number, β:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a beta prime distribution with first shape\n    parameter `α` and second shape parameter `β`.\n","base.dists.betaprime.mean":"\nbase.dists.betaprime.mean( α:number, β:number )\n    Returns the expected value of a beta prime distribution.\n","base.dists.betaprime.mode":"\nbase.dists.betaprime.mode( α:number, β:number )\n    Returns the mode of a beta prime distribution.\n","base.dists.betaprime.pdf":"\nbase.dists.betaprime.pdf( x:number, α:number, β:number )\n    Evaluates the probability density function (PDF) for a beta prime\n    distribution  with first shape parameter `α` and second shape parameter `β`\n    at a value `x`.\n","base.dists.betaprime.pdf.factory":"\nbase.dists.betaprime.pdf.factory( α:number, β:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a beta prime distribution with first shape parameter `α` and second shape\n    parameter `β`.\n","base.dists.betaprime.quantile":"\nbase.dists.betaprime.quantile( p:number, α:number, β:number )\n    Evaluates the quantile function for a beta prime distribution with first\n    shape parameter `α` and second shape parameter `β` at a probability `p`.\n","base.dists.betaprime.quantile.factory":"\nbase.dists.betaprime.quantile.factory( α:number, β:number )\n    Returns a function for evaluating the quantile function of a beta prime\n    distribution with first shape parameter `α` and second shape parameter `β`.\n","base.dists.betaprime.skewness":"\nbase.dists.betaprime.skewness( α:number, β:number )\n    Returns the skewness of a beta prime distribution.\n","base.dists.betaprime.stdev":"\nbase.dists.betaprime.stdev( α:number, β:number )\n    Returns the standard deviation of a beta prime distribution.\n","base.dists.betaprime.variance":"\nbase.dists.betaprime.variance( α:number, β:number )\n    Returns the variance of a beta prime distribution.\n","base.dists.binomial.Binomial":"\nbase.dists.binomial.Binomial( [n:integer, p:number] )\n    Returns a binomial distribution object.\n","base.dists.binomial.cdf":"\nbase.dists.binomial.cdf( x:number, n:integer, p:number )\n    Evaluates the cumulative distribution function (CDF) for a binomial\n    distribution with number of trials `n` and success probability `p` at a\n    value `x`.\n","base.dists.binomial.cdf.factory":"\nbase.dists.binomial.cdf.factory( n:integer, p:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a binomial distribution with number of trials `n` and success probability\n    `p`.\n","base.dists.binomial.entropy":"\nbase.dists.binomial.entropy( n:integer, p:number )\n    Returns the entropy of a binomial distribution.\n","base.dists.binomial.kurtosis":"\nbase.dists.binomial.kurtosis( n:integer, p:number )\n    Returns the excess kurtosis of a binomial distribution.\n","base.dists.binomial.logpmf":"\nbase.dists.binomial.logpmf( x:number, n:integer, p:number )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    binomial distribution with number of trials `n` and success probability `p`\n    at a value `x`.\n","base.dists.binomial.logpmf.factory":"\nbase.dists.binomial.logpmf.factory( n:integer, p:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a binomial distribution with number of trials `n` and\n    success probability `p`.\n","base.dists.binomial.mean":"\nbase.dists.binomial.mean( n:integer, p:number )\n    Returns the expected value of a binomial distribution.\n","base.dists.binomial.median":"\nbase.dists.binomial.median( n:integer, p:number )\n    Returns the median of a binomial distribution.\n","base.dists.binomial.mgf":"\nbase.dists.binomial.mgf( t:number, n:integer, p:number )\n    Evaluates the moment-generating function (MGF) for a binomial distribution\n    with number of trials `n` and success probability `p` at a value `t`.\n","base.dists.binomial.mgf.factory":"\nbase.dists.binomial.mgf.factory( n:integer, p:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    binomial distribution with number of trials `n` and success probability `p`.\n","base.dists.binomial.mode":"\nbase.dists.binomial.mode( n:integer, p:number )\n    Returns the mode of a binomial distribution.\n","base.dists.binomial.pmf":"\nbase.dists.binomial.pmf( x:number, n:integer, p:number )\n    Evaluates the probability mass function (PMF) for a binomial distribution\n    with number of trials `n` and success probability `p` at a value `x`.\n","base.dists.binomial.pmf.factory":"\nbase.dists.binomial.pmf.factory( n:integer, p:number )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    binomial distribution with number of trials `n` and success probability `p`.\n","base.dists.binomial.quantile":"\nbase.dists.binomial.quantile( r:number, n:integer, p:number )\n    Evaluates the quantile function for a binomial distribution with number of\n    trials `n` and success probability `p` at a probability `r`.\n","base.dists.binomial.quantile.factory":"\nbase.dists.binomial.quantile.factory( n:integer, p:number )\n    Returns a function for evaluating the quantile function of a binomial\n    distribution with number of trials `n` and success probability `p`.\n","base.dists.binomial.skewness":"\nbase.dists.binomial.skewness( n:integer, p:number )\n    Returns the skewness of a binomial distribution.\n","base.dists.binomial.stdev":"\nbase.dists.binomial.stdev( n:integer, p:number )\n    Returns the standard deviation of a binomial distribution.\n","base.dists.binomial.variance":"\nbase.dists.binomial.variance( n:integer, p:number )\n    Returns the variance of a binomial distribution.\n","base.dists.cauchy.Cauchy":"\nbase.dists.cauchy.Cauchy( [x0:number, Ɣ:number] )\n    Returns a Cauchy distribution object.\n","base.dists.cauchy.cdf":"\nbase.dists.cauchy.cdf( x:number, x0:number, Ɣ:number )\n    Evaluates the cumulative distribution function (CDF) for a Cauchy\n    distribution with location parameter `x0` and scale parameter `Ɣ` at a value\n    `x`.\n","base.dists.cauchy.cdf.factory":"\nbase.dists.cauchy.cdf.factory( x0:number, Ɣ:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Cauchy distribution with location parameter `x0` and scale parameter\n    `Ɣ`.\n","base.dists.cauchy.entropy":"\nbase.dists.cauchy.entropy( x0:number, Ɣ:number )\n    Returns the differential entropy of a Cauchy distribution (in nats).\n","base.dists.cauchy.logcdf":"\nbase.dists.cauchy.logcdf( x:number, x0:number, Ɣ:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (logCDF) for a Cauchy distribution with location parameter `x0` and scale\n    parameter `Ɣ` at a value `x`.\n","base.dists.cauchy.logcdf.factory":"\nbase.dists.cauchy.logcdf.factory( x0:number, Ɣ:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (logCDF) of a Cauchy distribution with location\n    parameter `x0` and scale parameter `Ɣ`.\n","base.dists.cauchy.logpdf":"\nbase.dists.cauchy.logpdf( x:number, x0:number, Ɣ:number )\n    Evaluates the natural logarithm of the probability density function (logPDF)\n    for a Cauchy distribution with location parameter `x0` and scale parameter\n    `Ɣ` at a value `x`.\n","base.dists.cauchy.logpdf.factory":"\nbase.dists.cauchy.logpdf.factory( x0:number, Ɣ:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (logPDF) of a Cauchy distribution with location parameter\n    `x0` and scale parameter `Ɣ`.\n","base.dists.cauchy.median":"\nbase.dists.cauchy.median( x0:number, Ɣ:number )\n    Returns the median of a Cauchy distribution.\n","base.dists.cauchy.mode":"\nbase.dists.cauchy.mode( x0:number, Ɣ:number )\n    Returns the mode of a Cauchy distribution.\n","base.dists.cauchy.pdf":"\nbase.dists.cauchy.pdf( x:number, x0:number, Ɣ:number )\n    Evaluates the probability density function (PDF) for a Cauchy distribution\n    with location parameter `x0` and scale parameter `Ɣ` at a value `x`.\n","base.dists.cauchy.pdf.factory":"\nbase.dists.cauchy.pdf.factory( x0:number, Ɣ:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Cauchy distribution with location parameter `x0` and scale parameter `Ɣ`.\n","base.dists.cauchy.quantile":"\nbase.dists.cauchy.quantile( p:number, x0:number, Ɣ:number )\n    Evaluates the quantile function for a Cauchy distribution with location\n    parameter `x0`  and scale parameter `Ɣ` at a probability `p`.\n","base.dists.cauchy.quantile.factory":"\nbase.dists.cauchy.quantile.factory( x0:number, Ɣ:number )\n    Returns a function for evaluating the quantile function of a Cauchy\n    distribution with location parameter `x0` and scale parameter `Ɣ`.\n","base.dists.chi.cdf":"\nbase.dists.chi.cdf( x:number, k:number )\n    Evaluates the cumulative distribution function (CDF) for a chi distribution\n    with degrees of freedom `k` at a value `x`.\n","base.dists.chi.cdf.factory":"\nbase.dists.chi.cdf.factory( k:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a chi distribution with degrees of freedom `k`.\n","base.dists.chi.Chi":"\nbase.dists.chi.Chi( [k:number] )\n    Returns a chi distribution object.\n","base.dists.chi.entropy":"\nbase.dists.chi.entropy( k:number )\n    Returns the differential entropy of a chi distribution (in nats).\n","base.dists.chi.kurtosis":"\nbase.dists.chi.kurtosis( k:number )\n    Returns the excess kurtosis of a chi distribution.\n","base.dists.chi.logpdf":"\nbase.dists.chi.logpdf( x:number, k:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a chi distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chi.logpdf.factory":"\nbase.dists.chi.logpdf.factory( k:number )\n    Returns a function for evaluating the natural logarithm of the  probability\n    density function (PDF) of a chi distribution with degrees of freedom `k`.\n","base.dists.chi.mean":"\nbase.dists.chi.mean( k:number )\n    Returns the expected value of a chi distribution.\n","base.dists.chi.mode":"\nbase.dists.chi.mode( k:number )\n    Returns the mode of a chi distribution.\n","base.dists.chi.pdf":"\nbase.dists.chi.pdf( x:number, k:number )\n    Evaluates the probability density function (PDF) for a chi distribution with\n    degrees of freedom `k` at a value `x`.\n","base.dists.chi.pdf.factory":"\nbase.dists.chi.pdf.factory( k:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a chi distribution with degrees of freedom `k`.\n","base.dists.chi.quantile":"\nbase.dists.chi.quantile( p:number, k:number )\n    Evaluates the quantile function for a chi distribution with degrees of\n    freedom `k` at a probability `p`.\n","base.dists.chi.quantile.factory":"\nbase.dists.chi.quantile.factory( k:number )\n    Returns a function for evaluating the quantile function of a chi\n    distribution with degrees of freedom `k`.\n","base.dists.chi.skewness":"\nbase.dists.chi.skewness( k:number )\n    Returns the skewness of a chi distribution.\n","base.dists.chi.stdev":"\nbase.dists.chi.stdev( k:number )\n    Returns the standard deviation of a chi distribution.\n","base.dists.chi.variance":"\nbase.dists.chi.variance( k:number )\n    Returns the variance of a chi distribution.\n","base.dists.chisquare.cdf":"\nbase.dists.chisquare.cdf( x:number, k:number )\n    Evaluates the cumulative distribution function (CDF) for a chi-squared\n    distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chisquare.cdf.factory":"\nbase.dists.chisquare.cdf.factory( k:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a chi-squared distribution with degrees of freedom `k`.\n","base.dists.chisquare.ChiSquare":"\nbase.dists.chisquare.ChiSquare( [k:number] )\n    Returns a  chi-squared distribution object.\n","base.dists.chisquare.entropy":"\nbase.dists.chisquare.entropy( k:number )\n    Returns the differential entropy of a chi-squared distribution (in nats).\n","base.dists.chisquare.kurtosis":"\nbase.dists.chisquare.kurtosis( k:number )\n    Returns the excess kurtosis of a chi-squared distribution.\n","base.dists.chisquare.logpdf":"\nbase.dists.chisquare.logpdf( x:number, k:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a chi-squared distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chisquare.logpdf.factory":"\nbase.dists.chisquare.logpdf.factory( k:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a chi-squared distribution with degrees of freedom\n    `k`.\n","base.dists.chisquare.mean":"\nbase.dists.chisquare.mean( k:number )\n    Returns the expected value of a chi-squared distribution.\n","base.dists.chisquare.median":"\nbase.dists.chisquare.median( k:number )\n    Returns the median of a chi-squared distribution.\n","base.dists.chisquare.mgf":"\nbase.dists.chisquare.mgf( t:number, k:number )\n    Evaluates the moment-generating function (MGF) for a chi-squared\n    distribution with degrees of freedom `k` at a value `t`.\n","base.dists.chisquare.mgf.factory":"\nbase.dists.chisquare.mgf.factory( k:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    chi-squared distribution with degrees of freedom `k`.\n","base.dists.chisquare.mode":"\nbase.dists.chisquare.mode( k:number )\n    Returns the mode of a chi-squared distribution.\n","base.dists.chisquare.pdf":"\nbase.dists.chisquare.pdf( x:number, k:number )\n    Evaluates the probability density function (PDF) for a chi-squared\n    distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chisquare.pdf.factory":"\nbase.dists.chisquare.pdf.factory( k:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a chi-squared distribution with degrees of freedom `k`.\n","base.dists.chisquare.quantile":"\nbase.dists.chisquare.quantile( p:number, k:number )\n    Evaluates the quantile function for a chi-squared distribution with degrees\n    of freedom `k` at a probability `p`.\n","base.dists.chisquare.quantile.factory":"\nbase.dists.chisquare.quantile.factory( k:number )\n    Returns a function for evaluating the quantile function of a chi-squared\n    distribution with degrees of freedom `k`.\n","base.dists.chisquare.skewness":"\nbase.dists.chisquare.skewness( k:number )\n    Returns the skewness of a chi-squared distribution.\n","base.dists.chisquare.stdev":"\nbase.dists.chisquare.stdev( k:number )\n    Returns the standard deviation of a chi-squared distribution.\n","base.dists.chisquare.variance":"\nbase.dists.chisquare.variance( k:number )\n    Returns the variance of a chi-squared distribution.\n","base.dists.cosine.cdf":"\nbase.dists.cosine.cdf( x:number, μ:number, s:number )\n    Evaluates the cumulative distribution function (CDF) for a raised cosine\n    distribution with location parameter `μ` and scale parameter `s` at a value\n    `x`.\n","base.dists.cosine.cdf.factory":"\nbase.dists.cosine.cdf.factory( μ:number, s:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a raised cosine distribution with location parameter `μ` and scale\n    parameter `s`.\n","base.dists.cosine.Cosine":"\nbase.dists.cosine.Cosine( [μ:number, s:number] )\n    Returns a raised cosine distribution object.\n","base.dists.cosine.kurtosis":"\nbase.dists.cosine.kurtosis( μ:number, s:number )\n    Returns the excess kurtosis of a raised cosine distribution with location\n    parameter `μ` and scale parameter `s`.\n","base.dists.cosine.logcdf":"\nbase.dists.cosine.logcdf( x:number, μ:number, s:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a raised cosine distribution with location parameter `μ` and scale\n     parameter `s` at a value `x`.\n","base.dists.cosine.logcdf.factory":"\nbase.dists.cosine.logcdf.factory( μ:number, s:number )\n    Returns a function for evaluating the natural logarithm of the  cumulative\n    distribution function (CDF) of a raised cosine distribution with location\n    parameter `μ` and scale parameter `s`.\n","base.dists.cosine.logpdf":"\nbase.dists.cosine.logpdf( x:number, μ:number, s:number )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    raised cosine distribution with location parameter `μ` and scale parameter\n    `s` at a value `x`.\n","base.dists.cosine.logpdf.factory":"\nbase.dists.cosine.logpdf.factory( μ:number, s:number )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a raised cosine distribution with location parameter `μ`\n    and scale parameter `s`.\n","base.dists.cosine.mean":"\nbase.dists.cosine.mean( μ:number, s:number )\n    Returns the expected value of a raised cosine distribution with location\n    parameter `μ` and scale parameter `s`.\n","base.dists.cosine.median":"\nbase.dists.cosine.median( μ:number, s:number )\n    Returns the median of a raised cosine distribution with location parameter\n    `μ` and scale parameter `s`.\n","base.dists.cosine.mgf":"\nbase.dists.cosine.mgf( t:number, μ:number, s:number )\n    Evaluates the moment-generating function (MGF) for a raised cosine\n    distribution with location parameter `μ` and scale parameter `s` at a value\n    `t`.\n","base.dists.cosine.mgf.factory":"\nbase.dists.cosine.mgf.factory( μ:number, s:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    raised cosine distribution with location parameter `μ` and scale parameter\n    `s`.\n","base.dists.cosine.mode":"\nbase.dists.cosine.mode( μ:number, s:number )\n    Returns the mode of a raised cosine distribution with location parameter `μ`\n    and scale parameter `s`.\n","base.dists.cosine.pdf":"\nbase.dists.cosine.pdf( x:number, μ:number, s:number )\n    Evaluates the probability density function (PDF) for a raised cosine\n    distribution with location parameter `μ` and scale parameter `s` at a value\n    `x`.\n","base.dists.cosine.pdf.factory":"\nbase.dists.cosine.pdf.factory( μ:number, s:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a raised cosine distribution with location parameter `μ` and scale parameter\n    `s`.\n","base.dists.cosine.quantile":"\nbase.dists.cosine.quantile( p:number, μ:number, s:number )\n    Evaluates the quantile function for a raised cosine distribution with\n    location parameter `μ` and scale parameter `s` at a probability `p`.\n","base.dists.cosine.quantile.factory":"\nbase.dists.cosine.quantile.factory( μ:number, s:number )\n    Returns a function for evaluating the quantile function of a raised cosine\n    distribution with location parameter `μ` and scale parameter `s`.\n","base.dists.cosine.skewness":"\nbase.dists.cosine.skewness( μ:number, s:number )\n    Returns the skewness of a raised cosine distribution with location parameter\n    `μ` and scale parameter `s`.\n","base.dists.cosine.stdev":"\nbase.dists.cosine.stdev( μ:number, s:number )\n    Returns the standard deviation of a raised cosine distribution with location\n    parameter `μ` and scale parameter `s`.\n","base.dists.cosine.variance":"\nbase.dists.cosine.variance( μ:number, s:number )\n    Returns the variance of a raised cosine distribution with location parameter\n    `μ` and scale parameter `s`.\n","base.dists.degenerate.cdf":"\nbase.dists.degenerate.cdf( x:number, μ:number )\n    Evaluates the cumulative distribution function (CDF) for a degenerate\n    distribution with mean value `μ`.\n","base.dists.degenerate.cdf.factory":"\nbase.dists.degenerate.cdf.factory( μ:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a degenerate distribution centered at a provided mean value.\n","base.dists.degenerate.Degenerate":"\nbase.dists.degenerate.Degenerate( [μ:number] )\n    Returns a degenerate distribution object.\n","base.dists.degenerate.entropy":"\nbase.dists.degenerate.entropy( μ:number )\n    Returns the entropy of a degenerate distribution with constant value `μ`.\n","base.dists.degenerate.logcdf":"\nbase.dists.degenerate.logcdf( x:number, μ:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (logCDF) for a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logcdf.factory":"\nbase.dists.degenerate.logcdf.factory( μ:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (logCDF) of a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpdf":"\nbase.dists.degenerate.logpdf( x:number, μ:number )\n    Evaluates the natural logarithm of the probability density function (logPDF)\n    for a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpdf.factory":"\nbase.dists.degenerate.logpdf.factory( μ:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (logPDF) of a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpmf":"\nbase.dists.degenerate.logpmf( x:number, μ:number )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpmf.factory":"\nbase.dists.degenerate.logpmf.factory( μ:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a degenerate distribution with mean `μ`.\n","base.dists.degenerate.mean":"\nbase.dists.degenerate.mean( μ:number )\n    Returns the expected value of a degenerate distribution with constant value\n    `μ`.\n","base.dists.degenerate.median":"\nbase.dists.degenerate.median( μ:number )\n    Returns the median of a degenerate distribution with constant value `μ`.\n","base.dists.degenerate.mgf":"\nbase.dists.degenerate.mgf( x:number, μ:number )\n    Evaluates the moment-generating function (MGF) for a degenerate distribution\n    with mean `μ`.\n","base.dists.degenerate.mgf.factory":"\nbase.dists.degenerate.mgf.factory( μ:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    degenerate distribution with mean `μ`.\n","base.dists.degenerate.mode":"\nbase.dists.degenerate.mode( μ:number )\n    Returns the mode of a degenerate distribution with constant value `μ`.\n","base.dists.degenerate.pdf":"\nbase.dists.degenerate.pdf( x:number, μ:number )\n    Evaluates the probability density function (PDF) for a degenerate\n    distribution with mean `μ`.\n","base.dists.degenerate.pdf.factory":"\nbase.dists.degenerate.pdf.factory( μ:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a degenerate distribution with mean `μ`.\n","base.dists.degenerate.pmf":"\nbase.dists.degenerate.pmf( x:number, μ:number )\n    Evaluates the probability mass function (PMF) for a degenerate distribution\n    with mean `μ`.\n","base.dists.degenerate.pmf.factory":"\nbase.dists.degenerate.pmf.factory( μ:number )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    degenerate distribution with mean `μ`.\n","base.dists.degenerate.quantile":"\nbase.dists.degenerate.quantile( p:number, μ:number )\n    Evaluates the quantile function for a degenerate distribution with mean `μ`.\n","base.dists.degenerate.quantile.factory":"\nbase.dists.degenerate.quantile.factory( μ:number )\n    Returns a function for evaluating the quantile function of a degenerate\n    distribution with mean `μ`.\n","base.dists.degenerate.stdev":"\nbase.dists.degenerate.stdev( μ:number )\n    Returns the standard deviation of a degenerate distribution with constant\n    value `μ`.\n","base.dists.degenerate.variance":"\nbase.dists.degenerate.variance( μ:number )\n    Returns the variance of a degenerate distribution with constant value `μ`.\n","base.dists.discreteUniform.cdf":"\nbase.dists.discreteUniform.cdf( x:number, a:integer, b:integer )\n    Evaluates the cumulative distribution function (CDF) for a discrete uniform\n    distribution with minimum support `a` and maximum support `b` at a value\n    `x`.\n","base.dists.discreteUniform.cdf.factory":"\nbase.dists.discreteUniform.cdf.factory( a:integer, b:integer )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a discrete uniform distribution with minimum support `a` and maximum\n    support `b`.\n","base.dists.discreteUniform.DiscreteUniform":"\nbase.dists.discreteUniform.DiscreteUniform( [a:integer, b:integer] )\n    Returns a discrete uniform distribution object.\n","base.dists.discreteUniform.entropy":"\nbase.dists.discreteUniform.entropy( a:integer, b:integer )\n    Returns the entropy of a discrete uniform distribution.\n","base.dists.discreteUniform.kurtosis":"\nbase.dists.discreteUniform.kurtosis( a:integer, b:integer )\n    Returns the excess kurtosis of a discrete uniform distribution.\n","base.dists.discreteUniform.logcdf":"\nbase.dists.discreteUniform.logcdf( x:number, a:integer, b:integer )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a discrete uniform distribution with minimum support `a` and\n    maximum support `b` at a value `x`.\n","base.dists.discreteUniform.logcdf.factory":"\nbase.dists.discreteUniform.logcdf.factory( a:integer, b:integer )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a discrete uniform distribution with minimum\n    support `a` and maximum support `b`.\n","base.dists.discreteUniform.logpmf":"\nbase.dists.discreteUniform.logpmf( x:number, a:integer, b:integer )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    discrete uniform distribution with minimum support `a` and maximum support\n    `b` at a value `x`.\n","base.dists.discreteUniform.logpmf.factory":"\nbase.dists.discreteUniform.logpmf.factory( a:integer, b:integer )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a discrete uniform distribution with minimum support\n    `a` and maximum support `b`.\n","base.dists.discreteUniform.mean":"\nbase.dists.discreteUniform.mean( a:integer, b:integer )\n    Returns the expected value of a discrete uniform distribution.\n","base.dists.discreteUniform.median":"\nbase.dists.discreteUniform.median( a:integer, b:integer )\n    Returns the median of a discrete uniform distribution.\n","base.dists.discreteUniform.mgf":"\nbase.dists.discreteUniform.mgf( t:number, a:integer, b:integer )\n    Evaluates the moment-generating function (MGF) for a discrete uniform\n    distribution with minimum support `a` and maximum support `b` at a value\n    `t`.\n","base.dists.discreteUniform.mgf.factory":"\nbase.dists.discreteUniform.mgf.factory( a:integer, b:integer )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a discrete uniform distribution with minimum support `a` and maximum\n    support `b`.\n","base.dists.discreteUniform.pmf":"\nbase.dists.discreteUniform.pmf( x:number, a:integer, b:integer )\n    Evaluates the probability mass function (PMF) for a discrete uniform\n    distribution with minimum support `a` and maximum support `b` at a value\n    `x`.\n","base.dists.discreteUniform.pmf.factory":"\nbase.dists.discreteUniform.pmf.factory( a:integer, b:integer )\n    Returns a function for evaluating the probability mass function (PMF) of\n    a discrete uniform distribution with minimum support `a` and maximum support\n    `b`.\n","base.dists.discreteUniform.quantile":"\nbase.dists.discreteUniform.quantile( p:number, a:integer, b:integer )\n    Evaluates the quantile function for a discrete uniform distribution with\n    minimum support `a` and maximum support `b` at a probability `p`.\n","base.dists.discreteUniform.quantile.factory":"\nbase.dists.discreteUniform.quantile.factory( a:integer, b:integer )\n    Returns a function for evaluating the quantile function of a discrete\n    uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.discreteUniform.skewness":"\nbase.dists.discreteUniform.skewness( a:integer, b:integer )\n    Returns the skewness of a discrete uniform distribution.\n","base.dists.discreteUniform.stdev":"\nbase.dists.discreteUniform.stdev( a:integer, b:integer )\n    Returns the standard deviation of a discrete uniform distribution.\n","base.dists.discreteUniform.variance":"\nbase.dists.discreteUniform.variance( a:integer, b:integer )\n    Returns the variance of a discrete uniform distribution.\n","base.dists.erlang.cdf":"\nbase.dists.erlang.cdf( x:number, k:number, λ:number )\n    Evaluates the cumulative distribution function (CDF) for an Erlang\n    distribution with shape parameter `k` and rate parameter `λ` at a value\n    `x`.\n","base.dists.erlang.cdf.factory":"\nbase.dists.erlang.cdf.factory( k:number, λ:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.entropy":"\nbase.dists.erlang.entropy( k:integer, λ:number )\n    Returns the differential entropy of an Erlang distribution (in nats).\n","base.dists.erlang.Erlang":"\nbase.dists.erlang.Erlang( [k:number, λ:number] )\n    Returns an Erlang distribution object.\n","base.dists.erlang.kurtosis":"\nbase.dists.erlang.kurtosis( k:integer, λ:number )\n    Returns the excess kurtosis of an Erlang distribution.\n","base.dists.erlang.logpdf":"\nbase.dists.erlang.logpdf( x:number, k:number, λ:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for an Erlang distribution with shape parameter `k` and rate parameter `λ`\n    at a value `x`.\n","base.dists.erlang.logpdf.factory":"\nbase.dists.erlang.logpdf.factory( k:number, λ:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of an Erlang distribution with shape parameter `k`\n    and rate parameter `λ`.\n","base.dists.erlang.mean":"\nbase.dists.erlang.mean( k:integer, λ:number )\n    Returns the expected value of an Erlang distribution.\n","base.dists.erlang.mgf":"\nbase.dists.erlang.mgf( t:number, k:number, λ:number )\n    Evaluates the moment-generating function (MGF) for an Erlang distribution\n    with shape parameter `k` and rate parameter `λ` at a value `t`.\n","base.dists.erlang.mgf.factory":"\nbase.dists.erlang.mgf.factory( k:number, λ:number )\n    Returns a function for evaluating the moment-generating function (MGF) of an\n    Erlang distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.mode":"\nbase.dists.erlang.mode( k:integer, λ:number )\n    Returns the mode of an Erlang distribution.\n","base.dists.erlang.pdf":"\nbase.dists.erlang.pdf( x:number, k:number, λ:number )\n    Evaluates the probability density function (PDF) for an Erlang distribution\n    with shape parameter `k` and rate parameter `λ` at a value `x`.\n","base.dists.erlang.pdf.factory":"\nbase.dists.erlang.pdf.factory( k:number, λ:number )\n    Returns a function for evaluating the probability density function (PDF)\n    of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.quantile":"\nbase.dists.erlang.quantile( p:number, k:number, λ:number )\n    Evaluates the quantile function for an Erlang distribution with shape\n    parameter `k` and rate parameter `λ` at a probability `p`.\n","base.dists.erlang.quantile.factory":"\nbase.dists.erlang.quantile.factory( k:number, λ:number )\n    Returns a function for evaluating the quantile function of an Erlang\n    distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.skewness":"\nbase.dists.erlang.skewness( k:integer, λ:number )\n    Returns the skewness of an Erlang distribution.\n","base.dists.erlang.stdev":"\nbase.dists.erlang.stdev( k:integer, λ:number )\n    Returns the standard deviation of an Erlang distribution.\n","base.dists.erlang.variance":"\nbase.dists.erlang.variance( k:integer, λ:number )\n    Returns the variance of an Erlang distribution.\n","base.dists.exponential.cdf":"\nbase.dists.exponential.cdf( x:number, λ:number )\n    Evaluates the cumulative distribution function (CDF) for an exponential\n    distribution with rate parameter `λ` at a value `x`.\n","base.dists.exponential.cdf.factory":"\nbase.dists.exponential.cdf.factory( λ:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    for an exponential distribution with rate parameter `λ`.\n","base.dists.exponential.entropy":"\nbase.dists.exponential.entropy( λ:number )\n    Returns the differential entropy of an exponential distribution.\n","base.dists.exponential.Exponential":"\nbase.dists.exponential.Exponential( [λ:number] )\n    Returns an exponential distribution object.\n","base.dists.exponential.kurtosis":"\nbase.dists.exponential.kurtosis( λ:number )\n    Returns the excess kurtosis of an exponential distribution.\n","base.dists.exponential.logcdf":"\nbase.dists.exponential.logcdf( x:number, λ:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for an exponential distribution with rate parameter `λ` at a value\n    `x`.\n","base.dists.exponential.logcdf.factory":"\nbase.dists.exponential.logcdf.factory( λ:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) for an exponential distribution with rate\n    parameter `λ`.\n","base.dists.exponential.logpdf":"\nbase.dists.exponential.logpdf( x:number, λ:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for an exponential distribution with rate parameter `λ` at a value `x`.\n","base.dists.exponential.logpdf.factory":"\nbase.dists.exponential.logpdf.factory( λ:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) for an exponential distribution with rate parameter\n    `λ`.\n","base.dists.exponential.mean":"\nbase.dists.exponential.mean( λ:number )\n    Returns the expected value of an exponential distribution.\n","base.dists.exponential.median":"\nbase.dists.exponential.median( λ:number )\n    Returns the median of an exponential distribution.\n","base.dists.exponential.mgf":"\nbase.dists.exponential.mgf( t:number, λ:number )\n    Evaluates the moment-generating function (MGF) for an exponential\n    distribution with rate parameter `λ` at a value `t`.\n","base.dists.exponential.mgf.factory":"\nbase.dists.exponential.mgf.factory( λ:number )\n    Returns a function for evaluating the moment-generating function (MGF) for\n    an exponential distribution with rate parameter `λ`.\n","base.dists.exponential.mode":"\nbase.dists.exponential.mode( λ:number )\n    Returns the mode of an exponential distribution.\n","base.dists.exponential.pdf":"\nbase.dists.exponential.pdf( x:number, λ:number )\n    Evaluates the probability density function (PDF) for an exponential\n    distribution with rate parameter `λ` at a value `x`.\n","base.dists.exponential.pdf.factory":"\nbase.dists.exponential.pdf.factory( λ:number )\n    Returns a function for evaluating the probability density function (PDF)\n    for an exponential distribution with rate parameter `λ`.\n","base.dists.exponential.quantile":"\nbase.dists.exponential.quantile( p:number, λ:number )\n    Evaluates the quantile function for an exponential distribution with rate\n    parameter `λ` at a probability `p`.\n","base.dists.exponential.quantile.factory":"\nbase.dists.exponential.quantile.factory( λ:number )\n    Returns a function for evaluating the quantile function for an exponential\n    distribution with rate parameter `λ`.\n","base.dists.exponential.skewness":"\nbase.dists.exponential.skewness( λ:number )\n    Returns the skewness of an exponential distribution.\n","base.dists.exponential.stdev":"\nbase.dists.exponential.stdev( λ:number )\n    Returns the standard deviation of an exponential distribution.\n","base.dists.exponential.variance":"\nbase.dists.exponential.variance( λ:number )\n    Returns the variance of an exponential distribution.\n","base.dists.f.cdf":"\nbase.dists.f.cdf( x:number, d1:number, d2:number )\n    Evaluates the cumulative distribution function (CDF) for an F distribution\n    with numerator degrees of freedom `d1` and denominator degrees of freedom\n    `d2` at a value `x`.\n","base.dists.f.cdf.factory":"\nbase.dists.f.cdf.factory( d1:number, d2:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an F distribution with numerator degrees of freedom `d1` and denominator\n    degrees of freedom `d2`.\n","base.dists.f.entropy":"\nbase.dists.f.entropy( d1:number, d2:number )\n    Returns the differential entropy of an F distribution (in nats).\n","base.dists.f.F":"\nbase.dists.f.F( [d1:number, d2:number] )\n    Returns an F distribution object.\n","base.dists.f.kurtosis":"\nbase.dists.f.kurtosis( d1:number, d2:number )\n    Returns the excess kurtosis of an F distribution.\n","base.dists.f.mean":"\nbase.dists.f.mean( d1:number, d2:number )\n    Returns the expected value of an F distribution.\n","base.dists.f.mode":"\nbase.dists.f.mode( d1:number, d2:number )\n    Returns the mode of an F distribution.\n","base.dists.f.pdf":"\nbase.dists.f.pdf( x:number, d1:number, d2:number )\n    Evaluates the probability density function (PDF) for an F distribution with\n    numerator degrees of freedom `d1` and denominator degrees of freedom `d2` at\n    a value `x`.\n","base.dists.f.pdf.factory":"\nbase.dists.f.pdf.factory( d1:number, d2:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    an F distribution with numerator degrees of freedom `d1` and denominator\n    degrees of freedom `d2`.\n","base.dists.f.quantile":"\nbase.dists.f.quantile( p:number, d1:number, d2:number )\n    Evaluates the quantile function for an F distribution with numerator degrees\n    of freedom `d1` and denominator degrees of freedom `d2` at a probability\n    `p`.\n","base.dists.f.quantile.factory":"\nbase.dists.f.quantile.factory( d1:number, d2:number )\n    Returns a function for evaluating the quantile function of an F distribution\n    with numerator degrees of freedom `d1` and denominator degrees of freedom\n    `d2`.\n","base.dists.f.skewness":"\nbase.dists.f.skewness( d1:number, d2:number )\n    Returns the skewness of an F distribution.\n","base.dists.f.stdev":"\nbase.dists.f.stdev( d1:number, d2:number )\n    Returns the standard deviation of an F distribution.\n","base.dists.f.variance":"\nbase.dists.f.variance( d1:number, d2:number )\n    Returns the variance of an F distribution.\n","base.dists.frechet.cdf":"\nbase.dists.frechet.cdf( x:number, α:number, s:number, m:number )\n    Evaluates the cumulative distribution function (CDF) for a Fréchet\n    distribution with shape parameter `α`, scale parameter `s`, and location\n    `m`.\n","base.dists.frechet.cdf.factory":"\nbase.dists.frechet.cdf.factory( α:number, s:number, m:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n    location `m`.\n","base.dists.frechet.entropy":"\nbase.dists.frechet.entropy( α:number, s:number, m:number )\n    Returns the differential entropy of a Fréchet distribution with shape\n    parameter `α`, scale parameter `s`, and location `m` (in nats).\n","base.dists.frechet.Frechet":"\nbase.dists.frechet.Frechet( [α:number, s:number, m:number] )\n    Returns a Fréchet distribution object.\n","base.dists.frechet.kurtosis":"\nbase.dists.frechet.kurtosis( α:number, s:number, m:number )\n    Returns the excess kurtosis of a Fréchet distribution with shape parameter\n    `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.logcdf":"\nbase.dists.frechet.logcdf( x:number, α:number, s:number, m:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a Fréchet distribution with shape parameter `α`, scale parameter\n    `s`, and location `m`.\n","base.dists.frechet.logcdf.factory":"\nbase.dists.frechet.logcdf.factory( α:number, s:number, m:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Fréchet distribution with shape parameter\n    `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.logpdf":"\nbase.dists.frechet.logpdf( x:number, α:number, s:number, m:number )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n    location `m`.\n","base.dists.frechet.logpdf.factory":"\nbase.dists.frechet.logpdf.factory( α:number, s:number, m:number )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Fréchet distribution with shape parameter `α`, scale\n    parameter `s`, and location `m`.\n","base.dists.frechet.mean":"\nbase.dists.frechet.mean( α:number, s:number, m:number )\n    Returns the expected value of a Fréchet distribution with shape parameter\n    `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.median":"\nbase.dists.frechet.median( α:number, s:number, m:number )\n    Returns the median of a Fréchet distribution with shape parameter\n    `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.mode":"\nbase.dists.frechet.mode( α:number, s:number, m:number )\n    Returns the mode of a Fréchet distribution with shape parameter `α`, scale\n    parameter `s`, and location `m`.\n","base.dists.frechet.pdf":"\nbase.dists.frechet.pdf( x:number, α:number, s:number, m:number )\n    Evaluates the probability density function (PDF) for a Fréchet distribution\n    with shape parameter `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.pdf.factory":"\nbase.dists.frechet.pdf.factory( α:number, s:number, m:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n    location `m`.\n","base.dists.frechet.quantile":"\nbase.dists.frechet.quantile( p:number, α:number, s:number, m:number )\n    Evaluates the quantile function for a Fréchet distribution with shape\n    parameter `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.quantile.factory":"\nbase.dists.frechet.quantile.factory( α:number, s:number, m:number )\n    Returns a function for evaluating the quantile function of a Fréchet\n    distribution with shape parameter `α`, scale parameter `s`, and location\n    `m`.\n","base.dists.frechet.skewness":"\nbase.dists.frechet.skewness( α:number, s:number, m:number )\n    Returns the skewness of a Fréchet distribution with shape parameter `α`,\n    scale parameter `s`, and location `m`.\n","base.dists.frechet.stdev":"\nbase.dists.frechet.stdev( α:number, s:number, m:number )\n    Returns the standard deviation of a Fréchet distribution with shape\n    parameter `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.variance":"\nbase.dists.frechet.variance( α:number, s:number, m:number )\n    Returns the variance of a Fréchet distribution with shape parameter `α`,\n    scale parameter `s`, and location `m`.\n","base.dists.gamma.cdf":"\nbase.dists.gamma.cdf( x:number, α:number, β:number )\n    Evaluates the cumulative distribution function (CDF) for a gamma\n    distribution with shape parameter `α` and rate parameter `β` at a value `x`.\n","base.dists.gamma.cdf.factory":"\nbase.dists.gamma.cdf.factory( α:number, β:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a gamma distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.entropy":"\nbase.dists.gamma.entropy( α:number, β:number )\n    Returns the differential entropy of a gamma distribution.\n","base.dists.gamma.Gamma":"\nbase.dists.gamma.Gamma( [α:number, β:number] )\n    Returns a gamma distribution object.\n","base.dists.gamma.kurtosis":"\nbase.dists.gamma.kurtosis( α:number, β:number )\n    Returns the excess kurtosis of a gamma distribution.\n","base.dists.gamma.logcdf":"\nbase.dists.gamma.logcdf( x:number, α:number, β:number )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    gamma distribution with shape parameter `α` and rate parameter `β` at a\n    value `x`.\n","base.dists.gamma.logcdf.factory":"\nbase.dists.gamma.logcdf.factory( α:number, β:number )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a gamma distribution with shape parameter `α`\n    and rate parameter `β`.\n","base.dists.gamma.logpdf":"\nbase.dists.gamma.logpdf( x:number, α:number, β:number )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    gamma distribution with shape parameter `α` and rate parameter `β` at a\n    value `x`.\n","base.dists.gamma.logpdf.factory":"\nbase.dists.gamma.logpdf.factory( α:number, β:number )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a gamma distribution with shape parameter `α` and rate\n    parameter `β`.\n","base.dists.gamma.mean":"\nbase.dists.gamma.mean( α:number, β:number )\n    Returns the expected value of a gamma distribution.\n","base.dists.gamma.mgf":"\nbase.dists.gamma.mgf( t:number, α:number, β:number )\n    Evaluates the moment-generating function (MGF) for a gamma distribution with\n    shape parameter `α` and rate parameter `β` at a value `t`.\n","base.dists.gamma.mgf.factory":"\nbase.dists.gamma.mgf.factory( α:number, β:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    gamma distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.mode":"\nbase.dists.gamma.mode( α:number, β:number )\n    Returns the mode of a gamma distribution.\n","base.dists.gamma.pdf":"\nbase.dists.gamma.pdf( x:number, α:number, β:number )\n    Evaluates the probability density function (PDF) for a gamma distribution\n    with shape parameter `α` and rate parameter `β` at a value `x`.\n","base.dists.gamma.pdf.factory":"\nbase.dists.gamma.pdf.factory( α:number, β:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a gamma distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.quantile":"\nbase.dists.gamma.quantile( p:number, α:number, β:number )\n    Evaluates the quantile function for a gamma distribution with shape\n    parameter `α` and rate parameter `β` at a probability `p`.\n","base.dists.gamma.quantile.factory":"\nbase.dists.gamma.quantile.factory( α:number, β:number )\n    Returns a function for evaluating the quantile function of a gamma\n    distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.skewness":"\nbase.dists.gamma.skewness( α:number, β:number )\n    Returns the skewness of a gamma distribution.\n","base.dists.gamma.stdev":"\nbase.dists.gamma.stdev( α:number, β:number )\n    Returns the standard deviation of a gamma distribution.\n","base.dists.gamma.variance":"\nbase.dists.gamma.variance( α:number, β:number )\n    Returns the variance of a gamma distribution.\n","base.dists.geometric.cdf":"\nbase.dists.geometric.cdf( x:number, p:number )\n    Evaluates the cumulative distribution function (CDF) for a geometric\n    distribution with success probability `p` at a value `x`.\n","base.dists.geometric.cdf.factory":"\nbase.dists.geometric.cdf.factory( p:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a geometric distribution with success probability `p`.\n","base.dists.geometric.entropy":"\nbase.dists.geometric.entropy( p:number )\n    Returns the entropy of a geometric distribution with success probability\n    `p` (in nats).\n","base.dists.geometric.Geometric":"\nbase.dists.geometric.Geometric( [p:number] )\n    Returns a geometric distribution object.\n","base.dists.geometric.kurtosis":"\nbase.dists.geometric.kurtosis( p:number )\n    Returns the excess kurtosis of a geometric distribution with success\n    probability `p`.\n","base.dists.geometric.logcdf":"\nbase.dists.geometric.logcdf( x:number, p:number )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    geometric distribution with success probability `p` at a value `x`.\n","base.dists.geometric.logcdf.factory":"\nbase.dists.geometric.logcdf.factory( p:number )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a geometric distribution with success\n    probability `p`.\n","base.dists.geometric.logpmf":"\nbase.dists.geometric.logpmf( x:number, p:number )\n    Evaluates the logarithm of the probability mass function (PMF) for a\n    geometric distribution with success probability `p` at a value `x`.\n","base.dists.geometric.logpmf.factory":"\nbase.dists.geometric.logpmf.factory( p:number )\n    Returns a function for evaluating the logarithm of the probability mass\n    function (PMF) of a geometric distribution with success probability `p`.\n","base.dists.geometric.mean":"\nbase.dists.geometric.mean( p:number )\n    Returns the expected value of a geometric distribution with success\n    probability `p`.\n","base.dists.geometric.median":"\nbase.dists.geometric.median( p:number )\n    Returns the median of a geometric distribution with success probability `p`.\n","base.dists.geometric.mgf":"\nbase.dists.geometric.mgf( t:number, p:number )\n    Evaluates the moment-generating function (MGF) for a geometric\n    distribution with success probability `p` at a value `t`.\n","base.dists.geometric.mgf.factory":"\nbase.dists.geometric.mgf.factory( p:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    geometric distribution with success probability `p`.\n","base.dists.geometric.mode":"\nbase.dists.geometric.mode( p:number )\n    Returns the mode of a geometric distribution with success probability `p`.\n","base.dists.geometric.pmf":"\nbase.dists.geometric.pmf( x:number, p:number )\n    Evaluates the probability mass function (PMF) for a geometric distribution\n    with success probability `p` at a value `x`.\n","base.dists.geometric.pmf.factory":"\nbase.dists.geometric.pmf.factory( p:number )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    geometric distribution with success probability `p`.\n","base.dists.geometric.quantile":"\nbase.dists.geometric.quantile( r:number, p:number )\n    Evaluates the quantile function for a geometric distribution with success\n    probability `p` at a probability `r`.\n","base.dists.geometric.quantile.factory":"\nbase.dists.geometric.quantile.factory( p:number )\n    Returns a function for evaluating the quantile function of a geometric\n    distribution with success probability `p`.\n","base.dists.geometric.skewness":"\nbase.dists.geometric.skewness( p:number )\n    Returns the skewness of a geometric distribution with success probability\n    `p`.\n","base.dists.geometric.stdev":"\nbase.dists.geometric.stdev( p:number )\n    Returns the standard deviation of a geometric distribution with success\n    probability `p`.\n","base.dists.geometric.variance":"\nbase.dists.geometric.variance( p:number )\n    Returns the variance of a geometric distribution with success probability\n    `p`.\n","base.dists.gumbel.cdf":"\nbase.dists.gumbel.cdf( x:number, μ:number, β:number )\n    Evaluates the cumulative distribution function (CDF) for a Gumbel\n    distribution with location parameter `μ` and scale parameter `β` at a value\n    `x`.\n","base.dists.gumbel.cdf.factory":"\nbase.dists.gumbel.cdf.factory( μ:number, β:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Gumbel distribution with location parameter `μ` and scale parameter\n    `β`.\n","base.dists.gumbel.entropy":"\nbase.dists.gumbel.entropy( μ:number, β:number )\n    Returns the differential entropy of a Gumbel distribution with location\n    parameter `μ` and scale parameter `β` (in nats).\n","base.dists.gumbel.Gumbel":"\nbase.dists.gumbel.Gumbel( [μ:number, β:number] )\n    Returns a Gumbel distribution object.\n","base.dists.gumbel.kurtosis":"\nbase.dists.gumbel.kurtosis( μ:number, β:number )\n    Returns the excess kurtosis of a Gumbel distribution with location parameter\n    `μ` and scale parameter `β`.\n","base.dists.gumbel.logcdf":"\nbase.dists.gumbel.logcdf( x:number, μ:number, β:number )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n    value `x`.\n","base.dists.gumbel.logcdf.factory":"\nbase.dists.gumbel.logcdf.factory( μ:number, β:number )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Gumbel distribution with location parameter\n    `μ` and scale parameter `β`.\n","base.dists.gumbel.logpdf":"\nbase.dists.gumbel.logpdf( x:number, μ:number, β:number )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n    value `x`.\n","base.dists.gumbel.logpdf.factory":"\nbase.dists.gumbel.logpdf.factory( μ:number, β:number )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Gumbel distribution with location parameter `μ` and\n    scale parameter `β`.\n","base.dists.gumbel.mean":"\nbase.dists.gumbel.mean( μ:number, β:number )\n    Returns the expected value of a Gumbel distribution with location parameter\n    `μ` and scale parameter `β`.\n","base.dists.gumbel.median":"\nbase.dists.gumbel.median( μ:number, β:number )\n    Returns the median of a Gumbel distribution with location parameter `μ` and\n    scale parameter `β`.\n","base.dists.gumbel.mgf":"\nbase.dists.gumbel.mgf( t:number, μ:number, β:number )\n    Evaluates the moment-generating function (MGF) for a Gumbel distribution\n    with location parameter `μ` and scale parameter `β` at a value `t`.\n","base.dists.gumbel.mgf.factory":"\nbase.dists.gumbel.mgf.factory( μ:number, β:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Gumbel distribution with location parameter `μ` and scale parameter `β`.\n","base.dists.gumbel.mode":"\nbase.dists.gumbel.mode( μ:number, β:number )\n    Returns the mode of a Gumbel distribution with location parameter `μ` and\n    scale parameter `β`.\n","base.dists.gumbel.pdf":"\nbase.dists.gumbel.pdf( x:number, μ:number, β:number )\n    Evaluates the probability density function (PDF) for a Gumbel distribution\n    with location parameter `μ` and scale parameter `β` at a value `x`.\n","base.dists.gumbel.pdf.factory":"\nbase.dists.gumbel.pdf.factory( μ:number, β:number )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Gumbel distribution with location parameter `μ` and scale parameter\n    `β`.\n","base.dists.gumbel.quantile":"\nbase.dists.gumbel.quantile( p:number, μ:number, β:number )\n    Evaluates the quantile function for a Gumbel distribution with location\n    parameter `μ` and scale parameter `β` at a probability `p`.\n","base.dists.gumbel.quantile.factory":"\nbase.dists.gumbel.quantile.factory( μ:number, β:number )\n    Returns a function for evaluating the quantile function of a Gumbel\n    distribution with location parameter `μ` and scale parameter `β`.\n","base.dists.gumbel.skewness":"\nbase.dists.gumbel.skewness( μ:number, β:number )\n    Returns the skewness of a Gumbel distribution with location parameter `μ`\n    and scale parameter `β`.\n","base.dists.gumbel.stdev":"\nbase.dists.gumbel.stdev( μ:number, β:number )\n    Returns the standard deviation of a Gumbel distribution with location\n    parameter `μ` and scale parameter `β`.\n","base.dists.gumbel.variance":"\nbase.dists.gumbel.variance( μ:number, β:number )\n    Returns the variance of a Gumbel distribution with location parameter `μ`\n    and scale parameter `β`.\n","base.dists.hypergeometric.cdf":"\nbase.dists.hypergeometric.cdf( x:number, N:integer, K:integer, n:integer )\n    Evaluates the cumulative distribution function (CDF) for a hypergeometric\n    distribution with population size `N`, subpopulation size `K`, and number of\n    draws `n` at a value `x`.\n","base.dists.hypergeometric.cdf.factory":"\nbase.dists.hypergeometric.cdf.factory( N:integer, K:integer, n:integer )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a hypergeometric distribution with population size `N`, subpopulation\n    size `K`, and number of draws `n`.\n","base.dists.hypergeometric.Hypergeometric":"\nbase.dists.hypergeometric.Hypergeometric( [N:integer, K:integer, n:integer] )\n    Returns a hypergeometric distribution object.\n","base.dists.hypergeometric.kurtosis":"\nbase.dists.hypergeometric.kurtosis( N:integer, K:integer, n:integer )\n    Returns the excess kurtosis of a hypergeometric distribution.\n","base.dists.hypergeometric.logpmf":"\nbase.dists.hypergeometric.logpmf( x:number, N:integer, K:integer, n:integer )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    hypergeometric distribution with population size `N`, subpopulation size\n    `K`, and number of draws `n` at a value `x`.\n","base.dists.hypergeometric.logpmf.factory":"\nbase.dists.hypergeometric.logpmf.factory( N:integer, K:integer, n:integer )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a hypergeometric distribution with population size\n    `N`, subpopulation size `K`, and number of draws `n`.\n","base.dists.hypergeometric.mean":"\nbase.dists.hypergeometric.mean( N:integer, K:integer, n:integer )\n    Returns the expected value of a hypergeometric distribution.\n","base.dists.hypergeometric.mode":"\nbase.dists.hypergeometric.mode( N:integer, K:integer, n:integer )\n    Returns the mode of a hypergeometric distribution.\n","base.dists.hypergeometric.pmf":"\nbase.dists.hypergeometric.pmf( x:number, N:integer, K:integer, n:integer )\n    Evaluates the probability mass function (PMF) for a hypergeometric\n    distribution with population size `N`, subpopulation size `K`, and number of\n    draws `n` at a value `x`.\n","base.dists.hypergeometric.pmf.factory":"\nbase.dists.hypergeometric.pmf.factory( N:integer, K:integer, n:integer )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    hypergeometric distribution with population size `N`, subpopulation size\n    `K`, and number of draws `n`.\n","base.dists.hypergeometric.quantile":"\nbase.dists.hypergeometric.quantile( p:number, N:integer, K:integer, n:integer )\n    Evaluates the quantile function for a hypergeometric distribution with\n    population size `N`, subpopulation size `K`, and number of draws `n` at a\n    probability `p`.\n","base.dists.hypergeometric.quantile.factory":"\nbase.dists.hypergeometric.quantile.factory( N:integer, K:integer, n:integer )\n    Returns a function for evaluating the quantile function of a hypergeometric\n    distribution with population size `N`, subpopulation size `K`, and number of\n    draws `n`.\n","base.dists.hypergeometric.skewness":"\nbase.dists.hypergeometric.skewness( N:integer, K:integer, n:integer )\n    Returns the skewness of a hypergeometric distribution.\n","base.dists.hypergeometric.stdev":"\nbase.dists.hypergeometric.stdev( N:integer, K:integer, n:integer )\n    Returns the standard deviation of a hypergeometric distribution.\n","base.dists.hypergeometric.variance":"\nbase.dists.hypergeometric.variance( N:integer, K:integer, n:integer )\n    Returns the variance of a hypergeometric distribution.\n","base.dists.invgamma.cdf":"\nbase.dists.invgamma.cdf( x:number, α:number, β:number )\n    Evaluates the cumulative distribution function (CDF) for an inverse gamma\n    distribution with shape parameter `α` and scale parameter `β` at a value\n    `x`.\n","base.dists.invgamma.cdf.factory":"\nbase.dists.invgamma.cdf.factory( α:number, β:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an inverse gamma distribution with shape parameter `α` and scale\n    parameter `β`.\n","base.dists.invgamma.entropy":"\nbase.dists.invgamma.entropy( α:number, β:number )\n    Returns the differential entropy of an inverse gamma distribution.\n","base.dists.invgamma.InvGamma":"\nbase.dists.invgamma.InvGamma( [α:number, β:number] )\n    Returns an inverse gamma distribution object.\n","base.dists.invgamma.kurtosis":"\nbase.dists.invgamma.kurtosis( α:number, β:number )\n    Returns the excess kurtosis of an inverse gamma distribution.\n","base.dists.invgamma.logpdf":"\nbase.dists.invgamma.logpdf( x:number, α:number, β:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for an inverse gamma distribution with shape parameter `α` and scale\n    parameter `β` at a value `x`.\n","base.dists.invgamma.logpdf.factory":"\nbase.dists.invgamma.logpdf.factory( α:number, β:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) for an inverse gamma distribution with shape\n    parameter `α` and scale parameter `β`.\n","base.dists.invgamma.mean":"\nbase.dists.invgamma.mean( α:number, β:number )\n    Returns the expected value of an inverse gamma distribution.\n","base.dists.invgamma.mode":"\nbase.dists.invgamma.mode( α:number, β:number )\n    Returns the mode of an inverse gamma distribution.\n","base.dists.invgamma.pdf":"\nbase.dists.invgamma.pdf( x:number, α:number, β:number )\n    Evaluates the probability density function (PDF) for an inverse gamma\n    distribution with shape parameter `α` and scale parameter `β` at a value\n    `x`.\n","base.dists.invgamma.pdf.factory":"\nbase.dists.invgamma.pdf.factory( α:number, β:number )\n    Returns a function for evaluating the probability density function (PDF)\n    of an inverse gamma distribution with shape parameter `α` and scale\n    parameter `β`.\n","base.dists.invgamma.quantile":"\nbase.dists.invgamma.quantile( p:number, α:number, β:number )\n    Evaluates the quantile function for an inverse gamma distribution with shape\n    parameter `α` and scale parameter `β` at a probability `p`.\n","base.dists.invgamma.quantile.factory":"\nbase.dists.invgamma.quantile.factory( α:number, β:number )\n    Returns a function for evaluating the quantile function of an inverse gamma\n    distribution with shape parameter `α` and scale parameter `β`.\n","base.dists.invgamma.skewness":"\nbase.dists.invgamma.skewness( α:number, β:number )\n    Returns the skewness of an inverse gamma distribution.\n","base.dists.invgamma.stdev":"\nbase.dists.invgamma.stdev( α:number, β:number )\n    Returns the standard deviation of an inverse gamma distribution.\n","base.dists.invgamma.variance":"\nbase.dists.invgamma.variance( α:number, β:number )\n    Returns the variance of an inverse gamma distribution.\n","base.dists.kumaraswamy.cdf":"\nbase.dists.kumaraswamy.cdf( x:number, a:number, b:number )\n    Evaluates the cumulative distribution function (CDF) for Kumaraswamy's\n    double bounded distribution with first shape parameter `a` and second shape\n    parameter `b` at a value `x`.\n","base.dists.kumaraswamy.cdf.factory":"\nbase.dists.kumaraswamy.cdf.factory( a:number, b:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Kumaraswamy's double bounded distribution with first shape parameter\n    `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.Kumaraswamy":"\nbase.dists.kumaraswamy.Kumaraswamy( [a:number, b:number] )\n    Returns a Kumaraswamy's double bounded distribution object.\n","base.dists.kumaraswamy.kurtosis":"\nbase.dists.kumaraswamy.kurtosis( a:number, b:number )\n    Returns the excess kurtosis of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.logcdf":"\nbase.dists.kumaraswamy.logcdf( x:number, a:number, b:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for Kumaraswamy's double bounded distribution with first shape\n    parameter `a` and second shape parameter `b` at a value `x`.\n","base.dists.kumaraswamy.logcdf.factory":"\nbase.dists.kumaraswamy.logcdf.factory( a:number, b:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Kumaraswamy's double bounded distribution\n    with first shape parameter `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.logpdf":"\nbase.dists.kumaraswamy.logpdf( x:number, a:number, b:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for Kumaraswamy's double bounded distribution with first shape parameter `a`\n    and second shape parameter `b` at a value `x`.\n","base.dists.kumaraswamy.logpdf.factory":"\nbase.dists.kumaraswamy.logpdf.factory( a:number, b:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a Kumaraswamy's double bounded distribution with\n    first shape parameter `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.mean":"\nbase.dists.kumaraswamy.mean( a:number, b:number )\n    Returns the mean of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.median":"\nbase.dists.kumaraswamy.median( a:number, b:number )\n    Returns the median of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.mode":"\nbase.dists.kumaraswamy.mode( a:number, b:number )\n    Returns the mode of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.pdf":"\nbase.dists.kumaraswamy.pdf( x:number, a:number, b:number )\n    Evaluates the probability density function (PDF) for Kumaraswamy's double\n    bounded distribution with first shape parameter `a` and second shape\n    parameter `b` at a value `x`.\n","base.dists.kumaraswamy.pdf.factory":"\nbase.dists.kumaraswamy.pdf.factory( a:number, b:number )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Kumaraswamy's double bounded distribution with first shape parameter\n    `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.quantile":"\nbase.dists.kumaraswamy.quantile( p:number, a:number, b:number )\n    Evaluates the quantile function for a Kumaraswamy's double bounded\n    distribution with first shape parameter `a` and second shape parameter `b`\n    at a probability `p`.\n","base.dists.kumaraswamy.quantile.factory":"\nbase.dists.kumaraswamy.quantile.factory( a:number, b:number )\n    Returns a function for evaluating the quantile function of a Kumaraswamy's\n    double bounded distribution with first shape parameter `a` and second shape\n    parameter `b`.\n","base.dists.kumaraswamy.skewness":"\nbase.dists.kumaraswamy.skewness( a:number, b:number )\n    Returns the skewness of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.stdev":"\nbase.dists.kumaraswamy.stdev( a:number, b:number )\n    Returns the standard deviation of a Kumaraswamy's double bounded\n    distribution.\n","base.dists.kumaraswamy.variance":"\nbase.dists.kumaraswamy.variance( a:number, b:number )\n    Returns the variance of a Kumaraswamy's double bounded distribution.\n","base.dists.laplace.cdf":"\nbase.dists.laplace.cdf( x:number, μ:number, b:number )\n    Evaluates the cumulative distribution function (CDF) for a Laplace\n    distribution with scale parameter `b` and location parameter `μ` at a\n    value `x`.\n","base.dists.laplace.cdf.factory":"\nbase.dists.laplace.cdf.factory( μ:number, b:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Laplace distribution with scale parameter `b` and location parameter\n    `μ`.\n","base.dists.laplace.entropy":"\nbase.dists.laplace.entropy( μ:number, b:number )\n    Returns the differential entropy of a Laplace distribution with location\n    parameter `μ` and scale parameter `b`.\n","base.dists.laplace.kurtosis":"\nbase.dists.laplace.kurtosis( μ:number, b:number )\n    Returns the excess kurtosis of a Laplace distribution with location\n    parameter `μ` and scale parameter `b`.\n","base.dists.laplace.Laplace":"\nbase.dists.laplace.Laplace( [μ:number, b:number] )\n    Returns a Laplace distribution object.\n","base.dists.laplace.logcdf":"\nbase.dists.laplace.logcdf( x:number, μ:number, b:number )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    Laplace distribution with scale parameter `b` and location parameter `μ` at\n    a value `x`.\n","base.dists.laplace.logcdf.factory":"\nbase.dists.laplace.logcdf.factory( μ:number, b:number )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Laplace distribution with scale parameter\n    `b` and location parameter `μ`.\n","base.dists.laplace.logpdf":"\nbase.dists.laplace.logpdf( x:number, μ:number, b:number )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    Laplace distribution with scale parameter `b` and location parameter `μ` at\n    a value `x`.\n","base.dists.laplace.logpdf.factory":"\nbase.dists.laplace.logpdf.factory( μ:number, b:number )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Laplace distribution with scale parameter `b` and\n    location parameter `μ`.\n","base.dists.laplace.mean":"\nbase.dists.laplace.mean( μ:number, b:number )\n    Returns the expected value of a Laplace distribution with location parameter\n    `μ` and scale parameter `b`.\n","base.dists.laplace.median":"\nbase.dists.laplace.median( μ:number, b:number )\n    Returns the median of a Laplace distribution with location parameter `μ` and\n    scale parameter `b`.\n","base.dists.laplace.mgf":"\nbase.dists.laplace.mgf( t:number, μ:number, b:number )\n    Evaluates the moment-generating function (MGF) for a Laplace\n    distribution with scale parameter `b` and location parameter `μ` at a\n    value `t`.\n","base.dists.laplace.mgf.factory":"\nbase.dists.laplace.mgf.factory( μ:number, b:number )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a Laplace distribution with scale parameter `b` and location parameter\n    `μ`.\n","base.dists.laplace.mode":"\nbase.dists.laplace.mode( μ:number, b:number )\n    Returns the mode of a Laplace distribution with location parameter `μ` and\n    scale parameter `b`.\n","base.dists.laplace.pdf":"\nbase.dists.laplace.pdf( x:number, μ:number, b:number )\n    Evaluates the probability density function (PDF) for a Laplace\n    distribution with scale parameter `b` and location parameter `μ` at a\n    value `x`.\n","base.dists.laplace.pdf.factory":"\nbase.dists.laplace.pdf.factory( μ:number, b:number )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Laplace distribution with scale parameter `b` and location parameter\n    `μ`.\n","base.dists.laplace.quantile":"\nbase.dists.laplace.quantile( p:number, μ:number, b:number )\n    Evaluates the quantile function for a Laplace distribution with scale\n    parameter `b` and location parameter `μ` at a probability `p`.\n","base.dists.laplace.quantile.factory":"\nbase.dists.laplace.quantile.factory( μ:number, b:number )\n    Returns a function for evaluating the quantile function of a Laplace\n    distribution with scale parameter `b` and location parameter `μ`.\n","base.dists.laplace.skewness":"\nbase.dists.laplace.skewness( μ:number, b:number )\n    Returns the skewness of a Laplace distribution with location parameter `μ`\n    and scale parameter `b`.\n","base.dists.laplace.stdev":"\nbase.dists.laplace.stdev( μ:number, b:number )\n    Returns the standard deviation of a Laplace distribution with location\n    parameter `μ` and scale parameter `b`.\n","base.dists.laplace.variance":"\nbase.dists.laplace.variance( μ:number, b:number )\n    Returns the variance of a Laplace distribution with location parameter `μ`\n    and scale parameter `b`.\n","base.dists.levy.cdf":"\nbase.dists.levy.cdf( x:number, μ:number, c:number )\n    Evaluates the cumulative distribution function (CDF) for a Lévy distribution\n    with location parameter `μ` and scale parameter `c` at a value `x`.\n","base.dists.levy.cdf.factory":"\nbase.dists.levy.cdf.factory( μ:number, c:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Lévy distribution with location parameter `μ` and scale parameter `c`.\n","base.dists.levy.entropy":"\nbase.dists.levy.entropy( μ:number, c:number )\n    Returns the entropy of a Lévy distribution with location parameter `μ` and\n    scale parameter `c`.\n","base.dists.levy.Levy":"\nbase.dists.levy.Levy( [μ:number, c:number] )\n    Returns a Lévy distribution object.\n","base.dists.levy.logcdf":"\nbase.dists.levy.logcdf( x:number, μ:number, c:number )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    Lévy distribution with location parameter `μ` and scale parameter `c` at a\n    value `x`.\n","base.dists.levy.logcdf.factory":"\nbase.dists.levy.logcdf.factory( μ:number, c:number )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Lévy distribution with location parameter\n    `μ` and scale parameter `c`.\n","base.dists.levy.logpdf":"\nbase.dists.levy.logpdf( x:number, μ:number, c:number )\n    Evaluates the logarithm of the probability density function (PDF) for a Lévy\n    distribution with location parameter `μ` and scale parameter `c` at a value\n    `x`.\n","base.dists.levy.logpdf.factory":"\nbase.dists.levy.logpdf.factory( μ:number, c:number )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Lévy distribution with location parameter `μ` and scale\n    parameter `c`.\n","base.dists.levy.mean":"\nbase.dists.levy.mean( μ:number, c:number )\n    Returns the expected value of a Lévy distribution with location parameter\n    `μ` and scale parameter `c`.\n","base.dists.levy.median":"\nbase.dists.levy.median( μ:number, c:number )\n    Returns the median of a Lévy distribution with location parameter `μ` and\n    scale parameter `c`.\n","base.dists.levy.mode":"\nbase.dists.levy.mode( μ:number, c:number )\n    Returns the mode of a Lévy distribution with location parameter `μ` and\n    scale parameter `c`.\n","base.dists.levy.pdf":"\nbase.dists.levy.pdf( x:number, μ:number, c:number )\n    Evaluates the probability density function (PDF) for a Lévy distribution\n    with location parameter `μ` and scale parameter `c` at a value `x`.\n","base.dists.levy.pdf.factory":"\nbase.dists.levy.pdf.factory( μ:number, c:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Lévy distribution with location parameter `μ` and scale parameter `c`.\n","base.dists.levy.quantile":"\nbase.dists.levy.quantile( p:number, μ:number, c:number )\n    Evaluates the quantile function for a Lévy distribution with location\n    parameter `μ` and scale parameter `c` at a probability `p`.\n","base.dists.levy.quantile.factory":"\nbase.dists.levy.quantile.factory( μ:number, c:number )\n    Returns a function for evaluating the quantile function of a Lévy\n    distribution with location parameter `μ` and scale parameter `c`.\n","base.dists.levy.stdev":"\nbase.dists.levy.stdev( μ:number, c:number )\n    Returns the standard deviation of a Lévy distribution with location\n    parameter `μ` and scale parameter `c`.\n","base.dists.levy.variance":"\nbase.dists.levy.variance( μ:number, c:number )\n    Returns the variance of a Lévy distribution with location parameter `μ` and\n    scale parameter `c`.\n","base.dists.logistic.cdf":"\nbase.dists.logistic.cdf( x:number, μ:number, s:number )\n    Evaluates the cumulative distribution function (CDF) for a logistic\n    distribution with location parameter `μ` and scale parameter `s` at a value\n    `x`.\n","base.dists.logistic.cdf.factory":"\nbase.dists.logistic.cdf.factory( μ:number, s:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a logistic distribution with location parameter `μ` and scale parameter\n    `s`.\n","base.dists.logistic.entropy":"\nbase.dists.logistic.entropy( μ:number, s:number )\n    Returns the entropy of a logistic distribution with location parameter `μ`\n    and scale parameter `s`.\n","base.dists.logistic.kurtosis":"\nbase.dists.logistic.kurtosis( μ:number, s:number )\n    Returns the excess kurtosis of a logistic distribution with location\n    parameter `μ` and scale parameter `s`.\n","base.dists.logistic.logcdf":"\nbase.dists.logistic.logcdf( x:number, μ:number, s:number )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    logistic distribution with location parameter `μ` and scale parameter `s` at\n    a value `x`.\n","base.dists.logistic.logcdf.factory":"\nbase.dists.logistic.logcdf.factory( μ:number, s:number )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Logistic distribution with location\n    parameter `μ` and scale parameter `s`.\n","base.dists.logistic.Logistic":"\nbase.dists.logistic.Logistic( [μ:number, s:number] )\n    Returns a logistic distribution object.\n","base.dists.logistic.logpdf":"\nbase.dists.logistic.logpdf( x:number, μ:number, s:number )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    logistic distribution with location parameter `μ` and scale parameter `s` at\n    a value `x`.\n","base.dists.logistic.logpdf.factory":"\nbase.dists.logistic.logpdf.factory( μ:number, s:number )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Logistic distribution with location parameter `μ` and\n    scale parameter `s`.\n","base.dists.logistic.mean":"\nbase.dists.logistic.mean( μ:number, s:number )\n    Returns the expected value of a logistic distribution with location\n    parameter `μ` and scale parameter `s`.\n","base.dists.logistic.median":"\nbase.dists.logistic.median( μ:number, s:number )\n    Returns the median of a logistic distribution with location parameter `μ`\n    and scale parameter `s`.\n","base.dists.logistic.mgf":"\nbase.dists.logistic.mgf( t:number, μ:number, s:number )\n    Evaluates the moment-generating function (MGF) for a logistic distribution\n    with location parameter `μ` and scale parameter `s` at a value `t`.\n","base.dists.logistic.mgf.factory":"\nbase.dists.logistic.mgf.factory( μ:number, s:number )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a Logistic distribution with location parameter `μ` and scale parameter\n    `s`.\n","base.dists.logistic.mode":"\nbase.dists.logistic.mode( μ:number, s:number )\n    Returns the mode of a logistic distribution with location parameter `μ` and\n    scale parameter `s`.\n","base.dists.logistic.pdf":"\nbase.dists.logistic.pdf( x:number, μ:number, s:number )\n    Evaluates the probability density function (PDF) for a logistic distribution\n    with location parameter `μ` and scale parameter `s` at a value `x`.\n","base.dists.logistic.pdf.factory":"\nbase.dists.logistic.pdf.factory( μ:number, s:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Logistic distribution with location parameter `μ` and scale parameter `s`.\n","base.dists.logistic.quantile":"\nbase.dists.logistic.quantile( p:number, μ:number, s:number )\n    Evaluates the quantile function for a logistic distribution with location\n    parameter `μ` and scale parameter `s` at a probability `p`.\n","base.dists.logistic.quantile.factory":"\nbase.dists.logistic.quantile.factory( μ:number, s:number )\n    Returns a function for evaluating the quantile function of a logistic\n    distribution with location parameter `μ` and scale parameter `s`.\n","base.dists.logistic.skewness":"\nbase.dists.logistic.skewness( μ:number, s:number )\n    Returns the skewness of a logistic distribution with location parameter `μ`\n    and scale parameter `s`.\n","base.dists.logistic.stdev":"\nbase.dists.logistic.stdev( μ:number, s:number )\n    Returns the standard deviation of a logistic distribution with location\n    parameter `μ` and scale parameter `s`.\n","base.dists.logistic.variance":"\nbase.dists.logistic.variance( μ:number, s:number )\n    Returns the variance of a logistic distribution with location parameter `μ`\n    and scale parameter `s`.\n","base.dists.lognormal.cdf":"\nbase.dists.lognormal.cdf( x:number, μ:number, σ:number )\n    Evaluates the cumulative distribution function (CDF) for a lognormal\n    distribution with location parameter `μ` and scale parameter `σ` at a value\n    `x`.\n","base.dists.lognormal.cdf.factory":"\nbase.dists.lognormal.cdf.factory( μ:number, σ:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a lognormal distribution with location parameter `μ` and scale parameter\n    `σ`.\n","base.dists.lognormal.entropy":"\nbase.dists.lognormal.entropy( μ:number, σ:number )\n    Returns the differential entropy of a lognormal distribution with location\n    `μ` and scale `σ` (in nats).\n","base.dists.lognormal.kurtosis":"\nbase.dists.lognormal.kurtosis( μ:number, σ:number )\n    Returns the excess kurtosis of a lognormal distribution with location `μ`\n    and scale `σ`.\n","base.dists.lognormal.LogNormal":"\nbase.dists.lognormal.LogNormal( [μ:number, σ:number] )\n    Returns a lognormal distribution object.\n","base.dists.lognormal.logcdf":"\nbase.dists.lognormal.logcdf( x:number, μ:number, σ:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a lognormal distribution with mean `μ` and standard deviation `σ`\n    at a value `x`.\n","base.dists.lognormal.logcdf.factory":"\nbase.dists.lognormal.logcdf.factory( μ:number, σ:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a lognormal distribution with mean `μ` and\n    standard deviation `σ`.\n","base.dists.lognormal.logpdf":"\nbase.dists.lognormal.logpdf( x:number, μ:number, σ:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a lognormal distribution with location parameter `μ` and scale parameter\n    `σ` at a value `x`.\n","base.dists.lognormal.logpdf.factory":"\nbase.dists.lognormal.logpdf.factory( μ:number, σ:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a lognormal distribution with location parameter\n    `μ` and scale parameter `σ`.\n","base.dists.lognormal.mean":"\nbase.dists.lognormal.mean( μ:number, σ:number )\n    Returns the expected value of a lognormal distribution with location `μ` and\n    scale `σ`.\n","base.dists.lognormal.median":"\nbase.dists.lognormal.median( μ:number, σ:number )\n    Returns the median of a lognormal distribution with location `μ` and scale\n    `σ`.\n","base.dists.lognormal.mode":"\nbase.dists.lognormal.mode( μ:number, σ:number )\n    Returns the mode of a lognormal distribution with location `μ` and scale\n    `σ`.\n","base.dists.lognormal.pdf":"\nbase.dists.lognormal.pdf( x:number, μ:number, σ:number )\n    Evaluates the probability density function (PDF) for a lognormal\n    distribution with location parameter `μ` and scale parameter `σ` at a value\n    `x`.\n","base.dists.lognormal.pdf.factory":"\nbase.dists.lognormal.pdf.factory( μ:number, σ:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a lognormal distribution with location parameter `μ` and scale parameter\n    `σ`.\n","base.dists.lognormal.quantile":"\nbase.dists.lognormal.quantile( p:number, μ:number, σ:number )\n    Evaluates the quantile function for a lognormal distribution with location\n    parameter `μ` and scale parameter `σ` at a probability `p`.\n","base.dists.lognormal.quantile.factory":"\nbase.dists.lognormal.quantile.factory( μ:number, σ:number )\n    Returns a function for evaluating the quantile function of a lognormal\n    distribution with location parameter `μ` and scale parameter `σ`.\n","base.dists.lognormal.skewness":"\nbase.dists.lognormal.skewness( μ:number, σ:number )\n    Returns the skewness of a lognormal distribution with location `μ` and scale\n    `σ`.\n","base.dists.lognormal.stdev":"\nbase.dists.lognormal.stdev( μ:number, σ:number )\n    Returns the standard deviation of a lognormal distribution with location `μ`\n    and scale `σ`.\n","base.dists.lognormal.variance":"\nbase.dists.lognormal.variance( μ:number, σ:number )\n    Returns the variance of a lognormal distribution with location `μ` and scale\n    `σ`.\n","base.dists.negativeBinomial.cdf":"\nbase.dists.negativeBinomial.cdf( x:number, r:number, p:number )\n    Evaluates the cumulative distribution function (CDF) for a negative binomial\n    distribution with number of successes until experiment is stopped `r` and\n    success probability `p` at a value `x`.\n","base.dists.negativeBinomial.cdf.factory":"\nbase.dists.negativeBinomial.cdf.factory( r:number, p:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a negative binomial distribution with number of successes until\n    experiment is stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.kurtosis":"\nbase.dists.negativeBinomial.kurtosis( r:integer, p:number )\n    Returns the excess kurtosis of a negative binomial distribution.\n","base.dists.negativeBinomial.logpmf":"\nbase.dists.negativeBinomial.logpmf( x:number, r:number, p:number )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    negative binomial distribution with number of successes until experiment is\n    stopped `r` and success probability `p` at a value `x`.\n","base.dists.negativeBinomial.logpmf.factory":"\nbase.dists.negativeBinomial.logpmf.factory( r:number, p:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a negative binomial distribution with number of\n    successes until experiment is stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.mean":"\nbase.dists.negativeBinomial.mean( r:integer, p:number )\n    Returns the expected value of a negative binomial distribution.\n","base.dists.negativeBinomial.mgf":"\nbase.dists.negativeBinomial.mgf( x:number, r:number, p:number )\n    Evaluates the moment-generating function (MGF) for a negative binomial\n    distribution with number of successes until experiment is stopped `r` and\n    success probability `p` at a value `t`.\n","base.dists.negativeBinomial.mgf.factory":"\nbase.dists.negativeBinomial.mgf.factory( r:number, p:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    negative binomial distribution with number of successes until experiment is\n    stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.mode":"\nbase.dists.negativeBinomial.mode( r:integer, p:number )\n    Returns the mode of a negative binomial distribution.\n","base.dists.negativeBinomial.NegativeBinomial":"\nbase.dists.negativeBinomial.NegativeBinomial( [r:number, p:number] )\n    Returns a negative binomial distribution object.\n","base.dists.negativeBinomial.pmf":"\nbase.dists.negativeBinomial.pmf( x:number, r:number, p:number )\n    Evaluates the probability mass function (PMF) for a negative binomial\n    distribution with number of successes until experiment is stopped `r` and\n    success probability `p` at a value `x`.\n","base.dists.negativeBinomial.pmf.factory":"\nbase.dists.negativeBinomial.pmf.factory( r:number, p:number )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    negative binomial distribution with number of successes until experiment is\n    stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.quantile":"\nbase.dists.negativeBinomial.quantile( k:number, r:number, p:number )\n    Evaluates the quantile function for a negative binomial distribution with\n    number of successes until experiment is stopped `r` and success probability\n    `p` at a probability `k`.\n","base.dists.negativeBinomial.quantile.factory":"\nbase.dists.negativeBinomial.quantile.factory( r:number, p:number )\n    Returns a function for evaluating the quantile function of a negative\n    binomial distribution with number of successes until experiment is stopped\n    `r` and success probability `p`.\n","base.dists.negativeBinomial.skewness":"\nbase.dists.negativeBinomial.skewness( r:integer, p:number )\n    Returns the skewness of a negative binomial distribution.\n","base.dists.negativeBinomial.stdev":"\nbase.dists.negativeBinomial.stdev( r:integer, p:number )\n    Returns the standard deviation of a negative binomial distribution.\n","base.dists.negativeBinomial.variance":"\nbase.dists.negativeBinomial.variance( r:integer, p:number )\n    Returns the variance of a negative binomial distribution.\n","base.dists.normal.cdf":"\nbase.dists.normal.cdf( x:number, μ:number, σ:number )\n    Evaluates the cumulative distribution function (CDF) for a normal\n    distribution with mean `μ` and standard deviation `σ` at a value `x`.\n","base.dists.normal.cdf.factory":"\nbase.dists.normal.cdf.factory( μ:number, σ:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.entropy":"\nbase.dists.normal.entropy( μ:number, σ:number )\n    Returns the differential entropy of a normal distribution with mean `μ` and\n    standard deviation `σ`.\n","base.dists.normal.kurtosis":"\nbase.dists.normal.kurtosis( μ:number, σ:number )\n    Returns the excess kurtosis of a normal distribution with mean `μ` and\n    standard deviation `σ`.\n","base.dists.normal.logcdf":"\nbase.dists.normal.logcdf( x:number, μ:number, σ:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a normal distribution with mean `μ` and standard deviation `σ` at\n    a value `x`.\n","base.dists.normal.logcdf.factory":"\nbase.dists.normal.logcdf.factory( μ:number, σ:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a normal distribution with mean `μ` and\n    standard deviation `σ`.\n","base.dists.normal.logpdf":"\nbase.dists.normal.logpdf( x:number, μ:number, σ:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a normal distribution with mean `μ` and standard deviation `σ` at a\n    value `x`.\n","base.dists.normal.logpdf.factory":"\nbase.dists.normal.logpdf.factory( μ:number, σ:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a normal distribution with mean `μ` and standard\n    deviation `σ`.\n","base.dists.normal.mean":"\nbase.dists.normal.mean( μ:number, σ:number )\n    Returns the expected value of a normal distribution with mean `μ` and\n    standard deviation `σ`.\n","base.dists.normal.median":"\nbase.dists.normal.median( μ:number, σ:number )\n    Returns the median of a normal distribution with mean `μ` and standard\n    deviation `σ`.\n","base.dists.normal.mgf":"\nbase.dists.normal.mgf( x:number, μ:number, σ:number )\n    Evaluates the moment-generating function (MGF) for a normal distribution\n    with mean `μ` and standard deviation `σ` at a value `t`.\n","base.dists.normal.mgf.factory":"\nbase.dists.normal.mgf.factory( μ:number, σ:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.mode":"\nbase.dists.normal.mode( μ:number, σ:number )\n    Returns the mode of a normal distribution with mean `μ` and standard\n    deviation `σ`.\n","base.dists.normal.Normal":"\nbase.dists.normal.Normal( [μ:number, σ:number] )\n    Returns a normal distribution object.\n","base.dists.normal.pdf":"\nbase.dists.normal.pdf( x:number, μ:number, σ:number )\n    Evaluates the probability density function (PDF) for a normal distribution\n    with mean `μ` and standard deviation `σ` at a value `x`.\n","base.dists.normal.pdf.factory":"\nbase.dists.normal.pdf.factory( μ:number, σ:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.quantile":"\nbase.dists.normal.quantile( p:number, μ:number, σ:number )\n    Evaluates the quantile function for a normal distribution with mean `μ` and\n    standard deviation `σ` at a probability `p`.\n","base.dists.normal.quantile.factory":"\nbase.dists.normal.quantile.factory( μ:number, σ:number )\n    Returns a function for evaluating the quantile function\n    of a normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.skewness":"\nbase.dists.normal.skewness( μ:number, σ:number )\n    Returns the skewness of a normal distribution with mean `μ` and standard\n    deviation `σ`.\n","base.dists.normal.stdev":"\nbase.dists.normal.stdev( μ:number, σ:number )\n    Returns the standard deviation of a normal distribution with mean `μ` and\n    standard deviation `σ`.\n","base.dists.normal.variance":"\nbase.dists.normal.variance( μ:number, σ:number )\n    Returns the variance of a normal distribution with mean `μ` and standard\n    deviation `σ`.\n","base.dists.pareto1.cdf":"\nbase.dists.pareto1.cdf( x:number, α:number, β:number )\n    Evaluates the cumulative distribution function (CDF) for a Pareto (Type I)\n    distribution with shape parameter `α` and scale parameter `β` at a value\n    `x`.\n","base.dists.pareto1.cdf.factory":"\nbase.dists.pareto1.cdf.factory( α:number, β:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Pareto (Type I) distribution with shape parameter `α` and scale\n    parameter `β`.\n","base.dists.pareto1.entropy":"\nbase.dists.pareto1.entropy( α:number, β:number )\n    Returns the differential entropy of a Pareto (Type I) distribution\n    (in nats).\n","base.dists.pareto1.kurtosis":"\nbase.dists.pareto1.kurtosis( α:number, β:number )\n    Returns the excess kurtosis of a Pareto (Type I) distribution.\n","base.dists.pareto1.logcdf":"\nbase.dists.pareto1.logcdf( x:number, α:number, β:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a Pareto (Type I) distribution with shape parameter `α` and scale\n    parameter `β` at a value `x`.\n","base.dists.pareto1.logcdf.factory":"\nbase.dists.pareto1.logcdf.factory( α:number, β:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Pareto (Type I) distribution with shape\n    parameter `α` and scale parameter `β`.\n","base.dists.pareto1.logpdf":"\nbase.dists.pareto1.logpdf( x:number, α:number, β:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a Pareto (Type I) distribution with shape parameter `α` and scale\n    parameter `β` at a value `x`.\n","base.dists.pareto1.logpdf.factory":"\nbase.dists.pareto1.logpdf.factory( α:number, β:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a Pareto (Type I) distribution with shape\n    parameter `α` and scale parameter `β`.\n","base.dists.pareto1.mean":"\nbase.dists.pareto1.mean( α:number, β:number )\n    Returns the expected value of a Pareto (Type I) distribution.\n","base.dists.pareto1.median":"\nbase.dists.pareto1.median( α:number, β:number )\n    Returns the median of a Pareto (Type I) distribution.\n","base.dists.pareto1.mode":"\nbase.dists.pareto1.mode( α:number, β:number )\n    Returns the mode of a Pareto (Type I) distribution.\n","base.dists.pareto1.Pareto1":"\nbase.dists.pareto1.Pareto1( [α:number, β:number] )\n    Returns a Pareto (Type I) distribution object.\n","base.dists.pareto1.pdf":"\nbase.dists.pareto1.pdf( x:number, α:number, β:number )\n    Evaluates the probability density function (PDF) for a Pareto (Type I)\n    distribution with shape parameter `α` and scale parameter `β` at a value\n    `x`.\n","base.dists.pareto1.pdf.factory":"\nbase.dists.pareto1.pdf.factory( α:number, β:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Pareto (Type I) distribution with shape parameter `α` and scale parameter\n    `β`.\n","base.dists.pareto1.quantile":"\nbase.dists.pareto1.quantile( p:number, α:number, β:number )\n    Evaluates the quantile function for a Pareto (Type I) distribution with\n    shape parameter `α` and scale parameter `β` at a probability `p`.\n","base.dists.pareto1.quantile.factory":"\nbase.dists.pareto1.quantile.factory( α:number, β:number )\n    Returns a function for evaluating the quantile function of a Pareto (Type I)\n    distribution with shape parameter `α` and scale parameter `β`.\n","base.dists.pareto1.skewness":"\nbase.dists.pareto1.skewness( α:number, β:number )\n    Returns the skewness of a Pareto (Type I) distribution.\n","base.dists.pareto1.stdev":"\nbase.dists.pareto1.stdev( α:number, β:number )\n    Returns the standard deviation of a Pareto (Type I) distribution.\n","base.dists.pareto1.variance":"\nbase.dists.pareto1.variance( α:number, β:number )\n    Returns the variance of a Pareto (Type I) distribution.\n","base.dists.poisson.cdf":"\nbase.dists.poisson.cdf( x:number, λ:number )\n    Evaluates the cumulative distribution function (CDF) for a Poisson\n    distribution with mean parameter `λ` at a value `x`.\n","base.dists.poisson.cdf.factory":"\nbase.dists.poisson.cdf.factory( λ:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.entropy":"\nbase.dists.poisson.entropy( λ:number )\n    Returns the entropy of a Poisson distribution.\n","base.dists.poisson.kurtosis":"\nbase.dists.poisson.kurtosis( λ:number )\n    Returns the excess kurtosis of a Poisson distribution.\n","base.dists.poisson.logpmf":"\nbase.dists.poisson.logpmf( x:number, λ:number )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    Poisson distribution with mean parameter `λ` at a value `x`.\n","base.dists.poisson.logpmf.factory":"\nbase.dists.poisson.logpmf.factory( λ:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.mean":"\nbase.dists.poisson.mean( λ:number )\n    Returns the expected value of a Poisson distribution.\n","base.dists.poisson.median":"\nbase.dists.poisson.median( λ:number )\n    Returns the median of a Poisson distribution.\n","base.dists.poisson.mgf":"\nbase.dists.poisson.mgf( x:number, λ:number )\n    Evaluates the moment-generating function (MGF) for a Poisson distribution\n    with mean parameter `λ` at a value `x`.\n","base.dists.poisson.mgf.factory":"\nbase.dists.poisson.mgf.factory( λ:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.mode":"\nbase.dists.poisson.mode( λ:number )\n    Returns the mode of a Poisson distribution.\n","base.dists.poisson.pmf":"\nbase.dists.poisson.pmf( x:number, λ:number )\n    Evaluates the probability mass function (PMF) for a Poisson\n    distribution with mean parameter `λ` at a value `x`.\n","base.dists.poisson.pmf.factory":"\nbase.dists.poisson.pmf.factory( λ:number )\n    Returns a function for evaluating the probability mass function (PMF)\n    of a Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.Poisson":"\nbase.dists.poisson.Poisson( [λ:number] )\n    Returns a Poisson distribution object.\n","base.dists.poisson.quantile":"\nbase.dists.poisson.quantile( p:number, λ:number )\n    Evaluates the quantile function for a Poisson distribution with mean\n    parameter `λ` at a probability `p`.\n","base.dists.poisson.quantile.factory":"\nbase.dists.poisson.quantile.factory( λ:number )\n    Returns a function for evaluating the quantile function of a Poisson\n    distribution with mean parameter `λ`.\n","base.dists.poisson.skewness":"\nbase.dists.poisson.skewness( λ:number )\n    Returns the skewness of a Poisson distribution.\n","base.dists.poisson.stdev":"\nbase.dists.poisson.stdev( λ:number )\n    Returns the standard deviation of a Poisson distribution.\n","base.dists.poisson.variance":"\nbase.dists.poisson.variance( λ:number )\n    Returns the variance of a Poisson distribution.\n","base.dists.rayleigh.cdf":"\nbase.dists.rayleigh.cdf( x:number, sigma:number )\n    Evaluates the cumulative distribution function (CDF) for a Rayleigh\n    distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.cdf.factory":"\nbase.dists.rayleigh.cdf.factory( sigma:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.entropy":"\nbase.dists.rayleigh.entropy( σ:number )\n    Returns the differential entropy of a Rayleigh distribution.\n","base.dists.rayleigh.kurtosis":"\nbase.dists.rayleigh.kurtosis( σ:number )\n    Returns the excess kurtosis of a Rayleigh distribution.\n","base.dists.rayleigh.logcdf":"\nbase.dists.rayleigh.logcdf( x:number, sigma:number )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    Rayleigh distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.logcdf.factory":"\nbase.dists.rayleigh.logcdf.factory( sigma:number )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Rayleigh distribution with scale parameter\n    `sigma`.\n","base.dists.rayleigh.logpdf":"\nbase.dists.rayleigh.logpdf( x:number, sigma:number )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    Rayleigh distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.logpdf.factory":"\nbase.dists.rayleigh.logpdf.factory( sigma:number )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.mean":"\nbase.dists.rayleigh.mean( σ:number )\n    Returns the expected value of a Rayleigh distribution.\n","base.dists.rayleigh.median":"\nbase.dists.rayleigh.median( σ:number )\n    Returns the median of a Rayleigh distribution.\n","base.dists.rayleigh.mgf":"\nbase.dists.rayleigh.mgf( t:number, sigma:number )\n    Evaluates the moment-generating function (MGF) for a Rayleigh distribution\n    with scale parameter `sigma` at a value `t`.\n","base.dists.rayleigh.mgf.factory":"\nbase.dists.rayleigh.mgf.factory( sigma:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.mode":"\nbase.dists.rayleigh.mode( σ:number )\n    Returns the mode of a Rayleigh distribution.\n","base.dists.rayleigh.pdf":"\nbase.dists.rayleigh.pdf( x:number, sigma:number )\n    Evaluates the probability density function (PDF) for a Rayleigh\n    distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.pdf.factory":"\nbase.dists.rayleigh.pdf.factory( sigma:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.quantile":"\nbase.dists.rayleigh.quantile( p:number, sigma:number )\n    Evaluates the quantile function for a Rayleigh distribution with scale\n    parameter `sigma` at a probability `p`.\n","base.dists.rayleigh.quantile.factory":"\nbase.dists.rayleigh.quantile.factory( sigma:number )\n    Returns a function for evaluating the quantile function of a Rayleigh\n    distribution with scale parameter `sigma`.\n","base.dists.rayleigh.Rayleigh":"\nbase.dists.rayleigh.Rayleigh( [σ:number] )\n    Returns a Rayleigh distribution object.\n","base.dists.rayleigh.skewness":"\nbase.dists.rayleigh.skewness( σ:number )\n    Returns the skewness of a Rayleigh distribution.\n","base.dists.rayleigh.stdev":"\nbase.dists.rayleigh.stdev( σ:number )\n    Returns the standard deviation of a Rayleigh distribution.\n","base.dists.rayleigh.variance":"\nbase.dists.rayleigh.variance( σ:number )\n    Returns the variance of a Rayleigh distribution.\n","base.dists.signrank.cdf":"\nbase.dists.signrank.cdf( x:number, n:integer )\n    Evaluates the cumulative distribution function (CDF) for the distribution of\n    the Wilcoxon signed rank test statistic with `n` observations.\n","base.dists.signrank.cdf.factory":"\nbase.dists.signrank.cdf.factory( n:integer )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of the distribution of the Wilcoxon signed rank test statistic.\n","base.dists.signrank.pdf":"\nbase.dists.signrank.pdf( x:number, n:integer )\n    Evaluates the probability density function (PDF) for the distribution of\n    the Wilcoxon signed rank test statistic with `n` observations.\n","base.dists.signrank.pdf.factory":"\nbase.dists.signrank.pdf.factory( n:integer )\n    Returns a function for evaluating the probability density function (PDF)\n    of the distribution of the Wilcoxon signed rank test statistic.\n","base.dists.signrank.quantile":"\nbase.dists.signrank.quantile( p:number, n:integer )\n    Evaluates the quantile function for the Wilcoxon signed rank test statistic\n    with `n` observations at a probability `p`.\n","base.dists.signrank.quantile.factory":"\nbase.dists.signrank.quantile.factory( n:integer )\n    Returns a function for evaluating the quantile function of the Wilcoxon\n    signed rank test statistic with `n` observations.\n","base.dists.studentizedRange.cdf":"\nbase.dists.studentizedRange.cdf( x:number, r:number, v:number[, \n  nranges:integer] )\n    Evaluates the cumulative distribution function (CDF) of a studentized range\n    distribution.\n","base.dists.studentizedRange.cdf.factory":"\nbase.dists.studentizedRange.cdf.factory( r:number, v:number[, nranges:integer] )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a studentized range distribution.\n","base.dists.studentizedRange.quantile":"\nbase.dists.studentizedRange.quantile( p:number, r:number, v:number[, \n  nranges:integer] )\n    Evaluates the quantile function for a studentized range distribution.\n","base.dists.studentizedRange.quantile.factory":"\nbase.dists.studentizedRange.quantile.factory( r:number, v:number[, \n  nranges:integer] )\n    Returns a function for evaluating the quantile function of a studentized\n    range distribution.\n","base.dists.t.cdf":"\nbase.dists.t.cdf( x:number, v:number )\n    Evaluates the cumulative distribution function (CDF) for a Student's t\n    distribution with degrees of freedom `v` at a value `x`.\n","base.dists.t.cdf.factory":"\nbase.dists.t.cdf.factory( v:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Student's t distribution with degrees of freedom `v`.\n","base.dists.t.entropy":"\nbase.dists.t.entropy( v:number )\n    Returns the differential entropy of a Student's t distribution.\n","base.dists.t.kurtosis":"\nbase.dists.t.kurtosis( v:number )\n    Returns the excess kurtosis of a Student's t distribution.\n","base.dists.t.logcdf":"\nbase.dists.t.logcdf( x:number, v:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a Student's t distribution with degrees of freedom `v` at a value\n    `x`.\n","base.dists.t.logcdf.factory":"\nbase.dists.t.logcdf.factory( v:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Student's t distribution with degrees of\n    freedom `v`.\n","base.dists.t.logpdf":"\nbase.dists.t.logpdf( x:number, v:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a Student's t distribution with degrees of freedom `v` at a value `x`.\n","base.dists.t.logpdf.factory":"\nbase.dists.t.logpdf.factory( v:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a Student's t distribution with degrees of\n    freedom `v`.\n","base.dists.t.mean":"\nbase.dists.t.mean( v:number )\n    Returns the expected value of a Student's t distribution.\n","base.dists.t.median":"\nbase.dists.t.median( v:number )\n    Returns the median of a Student's t distribution.\n","base.dists.t.mode":"\nbase.dists.t.mode( v:number )\n    Returns the mode of a Student's t distribution.\n","base.dists.t.pdf":"\nbase.dists.t.pdf( x:number, v:number )\n    Evaluates the probability density function (PDF) for a Student's t\n    distribution with degrees of freedom `v` at a value `x`.\n","base.dists.t.pdf.factory":"\nbase.dists.t.pdf.factory( v:number )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Student's t distribution with degrees of freedom `v`.\n","base.dists.t.quantile":"\nbase.dists.t.quantile( p:number, v:number )\n    Evaluates the quantile function for a Student's t distribution with degrees\n    of freedom `v` at a probability `p`.\n","base.dists.t.quantile.factory":"\nbase.dists.t.quantile.factory( v:number )\n    Returns a function for evaluating the quantile function of a Student's t\n    distribution with degrees of freedom `v`.\n","base.dists.t.skewness":"\nbase.dists.t.skewness( v:number )\n    Returns the skewness of a Student's t distribution.\n","base.dists.t.stdev":"\nbase.dists.t.stdev( v:number )\n    Returns the standard deviation of a Student's t distribution.\n","base.dists.t.T":"\nbase.dists.t.T( [v:number] )\n    Returns a Student's t distribution object.\n","base.dists.t.variance":"\nbase.dists.t.variance( v:number )\n    Returns the variance of a Student's t distribution.\n","base.dists.triangular.cdf":"\nbase.dists.triangular.cdf( x:number, a:number, b:number, c:number )\n    Evaluates the cumulative distribution function (CDF) for a triangular\n    distribution with minimum support `a`, maximum support `b`, and mode `c` at\n    a value `x`.\n","base.dists.triangular.cdf.factory":"\nbase.dists.triangular.cdf.factory( a:number, b:number, c:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a triangular distribution with minimum support `a`, maximum support `b`,\n    and mode `c`.\n","base.dists.triangular.entropy":"\nbase.dists.triangular.entropy( a:number, b:number, c:number )\n    Returns the differential entropy of a triangular distribution (in nats).\n","base.dists.triangular.kurtosis":"\nbase.dists.triangular.kurtosis( a:number, b:number, c:number )\n    Returns the excess kurtosis of a triangular distribution.\n","base.dists.triangular.logcdf":"\nbase.dists.triangular.logcdf( x:number, a:number, b:number, c:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a triangular distribution with minimum support `a`, maximum\n    support `b`, and mode `c` at a value `x`.\n","base.dists.triangular.logcdf.factory":"\nbase.dists.triangular.logcdf.factory( a:number, b:number, c:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a triangular distribution with minimum\n    support `a`, maximum support `b`, and mode `c`.\n","base.dists.triangular.logpdf":"\nbase.dists.triangular.logpdf( x:number, a:number, b:number, c:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a triangular distribution with minimum support `a`, maximum support `b`,\n    and mode `c` at a value `x`.\n","base.dists.triangular.logpdf.factory":"\nbase.dists.triangular.logpdf.factory( a:number, b:number, c:number )\n    Returns a function for evaluating the natural logarithm of the  probability\n    density function (PDF) of a triangular distribution with minimum support\n    `a`, maximum support `b`, and mode `c`.\n","base.dists.triangular.mean":"\nbase.dists.triangular.mean( a:number, b:number, c:number )\n    Returns the expected value of a triangular distribution.\n","base.dists.triangular.median":"\nbase.dists.triangular.median( a:number, b:number, c:number )\n    Returns the median of a triangular distribution.\n","base.dists.triangular.mgf":"\nbase.dists.triangular.mgf( t:number, a:number, b:number, c:number )\n    Evaluates the moment-generating function (MGF) for a triangular distribution\n    with minimum support `a`, maximum support `b`, and mode `c` at a value `t`.\n","base.dists.triangular.mgf.factory":"\nbase.dists.triangular.mgf.factory( a:number, b:number, c:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    triangular distribution with minimum support `a`, maximum support `b`, and\n    mode `c`.\n","base.dists.triangular.mode":"\nbase.dists.triangular.mode( a:number, b:number, c:number )\n    Returns the mode of a triangular distribution.\n","base.dists.triangular.pdf":"\nbase.dists.triangular.pdf( x:number, a:number, b:number, c:number )\n    Evaluates the probability density function (PDF) for a triangular\n    distribution with minimum support `a`, maximum support `b`, and mode `c` at\n    a value `x`.\n","base.dists.triangular.pdf.factory":"\nbase.dists.triangular.pdf.factory( a:number, b:number, c:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a triangular distribution with minimum support `a`, maximum support `b`, and\n    mode `c`.\n","base.dists.triangular.quantile":"\nbase.dists.triangular.quantile( p:number, a:number, b:number, c:number )\n    Evaluates the quantile function for a triangular distribution with minimum\n    support `a`, maximum support `b`, and mode `c` at a value `x`.\n","base.dists.triangular.quantile.factory":"\nbase.dists.triangular.quantile.factory( a:number, b:number, c:number )\n    Returns a function for evaluating the quantile function of a triangular\n    distribution with minimum support `a`, maximum support `b`, and mode `c`.\n","base.dists.triangular.skewness":"\nbase.dists.triangular.skewness( a:number, b:number, c:number )\n    Returns the skewness of a triangular distribution.\n","base.dists.triangular.stdev":"\nbase.dists.triangular.stdev( a:number, b:number, c:number )\n    Returns the standard deviation of a triangular distribution.\n","base.dists.triangular.Triangular":"\nbase.dists.triangular.Triangular( [a:number, b:number, c:number] )\n    Returns a triangular distribution object.\n","base.dists.triangular.variance":"\nbase.dists.triangular.variance( a:number, b:number, c:number )\n    Returns the variance of a triangular distribution.\n","base.dists.uniform.cdf":"\nbase.dists.uniform.cdf( x:number, a:number, b:number )\n    Evaluates the cumulative distribution function (CDF) for a uniform\n    distribution with minimum support `a` and maximum support `b` at a value\n    `x`.\n","base.dists.uniform.cdf.factory":"\nbase.dists.uniform.cdf.factory( a:number, b:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.entropy":"\nbase.dists.uniform.entropy( a:number, b:number )\n    Returns the differential entropy of a uniform distribution.\n","base.dists.uniform.kurtosis":"\nbase.dists.uniform.kurtosis( a:number, b:number )\n    Returns the excess kurtosis of a uniform distribution.\n","base.dists.uniform.logcdf":"\nbase.dists.uniform.logcdf( x:number, a:number, b:number )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    uniform distribution with minimum support `a` and maximum support `b` at a\n    value `x`.\n","base.dists.uniform.logcdf.factory":"\nbase.dists.uniform.logcdf.factory( a:number, b:number )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a uniform distribution with minimum support\n    `a` and maximum support `b`.\n","base.dists.uniform.logpdf":"\nbase.dists.uniform.logpdf( x:number, a:number, b:number )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    uniform distribution with minimum support `a` and maximum support `b` at a\n    value `x`.\n","base.dists.uniform.logpdf.factory":"\nbase.dists.uniform.logpdf.factory( a:number, b:number )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a uniform distribution with minimum support `a` and\n    maximum support `b`.\n","base.dists.uniform.mean":"\nbase.dists.uniform.mean( a:number, b:number )\n    Returns the expected value of a uniform distribution.\n","base.dists.uniform.median":"\nbase.dists.uniform.median( a:number, b:number )\n    Returns the median of a uniform distribution.\n","base.dists.uniform.mgf":"\nbase.dists.uniform.mgf( t:number, a:number, b:number )\n    Evaluates the moment-generating function (MGF) for a uniform\n    distribution with minimum support `a` and maximum support `b` at a value\n    `t`.\n","base.dists.uniform.mgf.factory":"\nbase.dists.uniform.mgf.factory( a:number, b:number )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.pdf":"\nbase.dists.uniform.pdf( x:number, a:number, b:number )\n    Evaluates the probability density function (PDF) for a uniform distribution\n    with minimum support `a` and maximum support `b` at a value `x`.\n","base.dists.uniform.pdf.factory":"\nbase.dists.uniform.pdf.factory( a:number, b:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.quantile":"\nbase.dists.uniform.quantile( p:number, a:number, b:number )\n    Evaluates the quantile function for a uniform distribution with minimum\n    support `a` and maximum support `b` at a probability `p`.\n","base.dists.uniform.quantile.factory":"\nbase.dists.uniform.quantile.factory( a:number, b:number )\n    Returns a function for evaluating the quantile function of a uniform\n    distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.skewness":"\nbase.dists.uniform.skewness( a:number, b:number )\n    Returns the skewness of a uniform distribution.\n","base.dists.uniform.stdev":"\nbase.dists.uniform.stdev( a:number, b:number )\n    Returns the standard deviation of a uniform distribution.\n","base.dists.uniform.Uniform":"\nbase.dists.uniform.Uniform( [a:number, b:number] )\n    Returns a uniform distribution object.\n","base.dists.uniform.variance":"\nbase.dists.uniform.variance( a:number, b:number )\n    Returns the variance of a uniform distribution.\n","base.dists.weibull.cdf":"\nbase.dists.weibull.cdf( x:number, k:number, λ:number )\n    Evaluates the cumulative distribution function (CDF) for a Weibull\n    distribution with shape parameter `k` and scale parameter `λ` at a value\n    `x`.\n","base.dists.weibull.cdf.factory":"\nbase.dists.weibull.cdf.factory( k:number, λ:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n","base.dists.weibull.entropy":"\nbase.dists.weibull.entropy( k:number, λ:number )\n    Returns the differential entropy of a Weibull distribution (in nats).\n","base.dists.weibull.kurtosis":"\nbase.dists.weibull.kurtosis( k:number, λ:number )\n    Returns the excess kurtosis of a Weibull distribution.\n","base.dists.weibull.logcdf":"\nbase.dists.weibull.logcdf( x:number, k:number, λ:number )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n    value `x`.\n","base.dists.weibull.logcdf.factory":"\nbase.dists.weibull.logcdf.factory( k:number, λ:number)\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Weibull distribution with scale parameter\n    `λ` and shape parameter `k`.\n","base.dists.weibull.logpdf":"\nbase.dists.weibull.logpdf( x:number, k:number, λ:number )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n    value `x`.\n","base.dists.weibull.logpdf.factory":"\nbase.dists.weibull.logpdf.factory( k:number, λ:number )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Weibull distribution with shape parameter `k` and scale\n    parameter `λ`.\n","base.dists.weibull.mean":"\nbase.dists.weibull.mean( k:number, λ:number )\n    Returns the expected value of a Weibull distribution.\n","base.dists.weibull.median":"\nbase.dists.weibull.median( k:number, λ:number )\n    Returns the median of a Weibull distribution.\n","base.dists.weibull.mgf":"\nbase.dists.weibull.mgf( x:number, k:number, λ:number )\n    Evaluates the moment-generating function (MGF) for a Weibull distribution\n    with shape parameter `k` and scale parameter `λ` at a value `t`.\n","base.dists.weibull.mgf.factory":"\nbase.dists.weibull.mgf.factory( k:number, λ:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Weibull distribution with shape parameter `k` and scale parameter `λ`.\n","base.dists.weibull.mode":"\nbase.dists.weibull.mode( k:number, λ:number )\n    Returns the mode of a Weibull distribution.\n","base.dists.weibull.pdf":"\nbase.dists.weibull.pdf( x:number, k:number, λ:number )\n    Evaluates the probability density function (PDF) for a Weibull distribution\n    with shape parameter `k` and scale parameter `λ` at a value `x`.\n","base.dists.weibull.pdf.factory":"\nbase.dists.weibull.pdf.factory( k:number, λ:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n","base.dists.weibull.quantile":"\nbase.dists.weibull.quantile( p:number, k:number, λ:number )\n    Evaluates the quantile function for a Weibull distribution with scale\n    parameter `k` and shape parameter `λ` at a probability `p`.\n","base.dists.weibull.quantile.factory":"\nbase.dists.weibull.quantile.factory( k:number, λ:number )\n    Returns a function for evaluating the quantile function of a Weibull\n    distribution with scale parameter `k` and shape parameter `λ`.\n","base.dists.weibull.skewness":"\nbase.dists.weibull.skewness( k:number, λ:number )\n    Returns the skewness of a Weibull distribution.\n","base.dists.weibull.stdev":"\nbase.dists.weibull.stdev( k:number, λ:number )\n    Returns the standard deviation of a Weibull distribution.\n","base.dists.weibull.variance":"\nbase.dists.weibull.variance( k:number, λ:number )\n    Returns the variance of a Weibull distribution.\n","base.dists.weibull.Weibull":"\nbase.dists.weibull.Weibull( [k:number, λ:number] )\n    Returns a Weibull distribution object.\n","base.ellipe":"\nbase.ellipe( m:number )\n    Computes the complete elliptic integral of the second kind.\n","base.ellipj":"\nbase.ellipj( u:number, m:number )\n    Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n    amplitude am.\n","base.ellipj.assign":"\nbase.ellipj.assign( u:number, m:number, out:Array|TypedArray|Object, \n  stride:integer, offset:integer )\n    Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n    amplitude am and assigns results to a provided output array.\n","base.ellipj.sn":"\nbase.ellipj.sn( u:number, m:number )\n    Computes the Jacobi elliptic function sn.\n","base.ellipj.cn":"\nbase.ellipj.cn( u:number, m:number )\n    Computes the Jacobi elliptic functions cn.\n","base.ellipj.dn":"\nbase.ellipj.dn( u:number, m:number )\n    Computes the Jacobi elliptic function dn.\n","base.ellipj.am":"\nbase.ellipj.am( u:number, m:number )\n    Computes the Jacobi amplitude am.\n","base.ellipk":"\nbase.ellipk( m:number )\n    Computes the complete elliptic integral of the first kind.\n","base.endsWith":"\nbase.endsWith( str:string, search:string, len:integer )\n    Tests if a string ends with the characters of another string.\n","base.epsdiff":"\nbase.epsdiff( x:number, y:number[, scale:string|Function] )\n    Computes the relative difference of two real numbers in units of double-\n    precision floating-point epsilon.\n","base.erf":"\nbase.erf( x:number )\n    Evaluates the error function.\n","base.erfc":"\nbase.erfc( x:number )\n    Evaluates the complementary error function.\n","base.erfcinv":"\nbase.erfcinv( x:number )\n    Evaluates the inverse complementary error function.\n","base.erfcx":"\nbase.erfcx( x:number )\n    Evaluates the scaled complementary error function.\n","base.erfinv":"\nbase.erfinv( x:number )\n    Evaluates the inverse error function.\n","base.eta":"\nbase.eta( s:number )\n    Evaluates the Dirichlet eta function for a double-precision\n    floating-point number `s`.\n","base.evalpoly":"\nbase.evalpoly( c:Array<number>, x:number )\n    Evaluates a polynomial using double-precision floating-point arithmetic.\n","base.evalpoly.factory":"\nbase.evalpoly.factory( c:Array<number> )\n    Returns a function for evaluating a polynomial using double-precision\n    floating-point arithmetic.\n","base.evalrational":"\nbase.evalrational( P:Array<number>, Q:Array<number>, x:number )\n    Evaluates a rational function using double-precision floating-point\n    arithmetic.\n","base.evalrational.factory":"\nbase.evalrational.factory( P:Array<number>, Q:Array<number> )\n    Returns a function for evaluating a rational function using double-precision\n    floating-point arithmetic.\n","base.exp":"\nbase.exp( x:number )\n    Evaluates the natural exponential function.\n","base.exp2":"\nbase.exp2( x:number )\n    Evaluates the base 2 exponential function.\n","base.exp10":"\nbase.exp10( x:number )\n    Evaluates the base 10 exponential function.\n","base.expit":"\nbase.expit( x:number )\n    Evaluates the standard logistic function.\n","base.expm1":"\nbase.expm1( x:number )\n    Computes `exp(x)-1`, where `exp(x)` is the natural exponential function.\n","base.expm1rel":"\nbase.expm1rel( x:number )\n    Relative error exponential.\n","base.exponent":"\nbase.exponent( x:number )\n    Returns an integer corresponding to the unbiased exponent of a double-\n    precision floating-point number.\n","base.exponentf":"\nbase.exponentf( x:float )\n    Returns an integer corresponding to the unbiased exponent of a single-\n    precision floating-point number.\n","base.factorial":"\nbase.factorial( x:number )\n    Evaluates the factorial of `x`.\n","base.factorial2":"\nbase.factorial2( n:number )\n    Evaluates the double factorial of `n`.\n","base.factorialln":"\nbase.factorialln( x:number )\n    Evaluates the natural logarithm of the factorial of `x`.\n","base.fallingFactorial":"\nbase.fallingFactorial( x:number, n:integer )\n    Computes the falling factorial of `x` and `n`.\n","base.fibonacci":"\nbase.fibonacci( n:integer )\n    Computes the nth Fibonacci number.\n","base.fibonacciIndex":"\nbase.fibonacciIndex( F:integer )\n    Computes the Fibonacci number index.\n","base.fibpoly":"\nbase.fibpoly( n:integer, x:number )\n    Evaluates a Fibonacci polynomial.\n","base.fibpoly.factory":"\nbase.fibpoly.factory( n:integer )\n    Returns a function for evaluating a Fibonacci polynomial.\n","base.firstCodePoint":"\nbase.firstCodePoint( str:string, n:integer )\n    Returns the first `n` Unicode code points of a string.\n","base.firstCodeUnit":"\nbase.firstCodeUnit( str:string, n:integer )\n    Returns the first `n` UTF-16 code units of a string.\n","base.firstGraphemeCluster":"\nbase.firstGraphemeCluster( str:string, n:integer )\n    Returns the first `n` grapheme clusters (i.e., user-perceived characters) of\n    a string.\n","base.flipsign":"\nbase.flipsign( x:number, y:number )\n    Returns a double-precision floating-point number with the magnitude of `x`\n    and the sign of `x*y`.\n","base.flipsignf":"\nbase.flipsignf( x:number, y:number )\n    Returns a single-precision floating-point number with the magnitude of `x`\n    and the sign of `x*y`.\n","base.float32ToInt32":"\nbase.float32ToInt32( x:float )\n    Converts a single-precision floating-point number to a signed 32-bit\n    integer.\n","base.float32ToUint32":"\nbase.float32ToUint32( x:float )\n    Converts a single-precision floating-point number to a unsigned 32-bit\n    integer.\n","base.float64ToFloat32":"\nbase.float64ToFloat32( x:number )\n    Converts a double-precision floating-point number to the nearest single-\n    precision floating-point number.\n","base.float64ToInt32":"\nbase.float64ToInt32( x:number )\n    Converts a double-precision floating-point number to a signed 32-bit\n    integer.\n","base.float64ToInt64Bytes":"\nbase.float64ToInt64Bytes( x:integer )\n    Converts an integer-valued double-precision floating-point number to a\n    signed 64-bit integer byte array according to host byte order (endianness).\n","base.float64ToInt64Bytes.assign":"\nbase.float64ToInt64Bytes.assign( x:integer, out:Array|TypedArray|Object, \n  stride:integer, offset:integer )\n    Converts an integer-valued double-precision floating-point number to a\n    signed 64-bit integer byte array according to host byte order (endianness)\n    and assigns results to a provided output array.\n","base.float64ToUint32":"\nbase.float64ToUint32( x:number )\n    Converts a double-precision floating-point number to a unsigned 32-bit\n    integer.\n","base.floor":"\nbase.floor( x:number )\n    Rounds a double-precision floating-point number toward negative infinity.\n","base.floor2":"\nbase.floor2( x:number )\n    Rounds a numeric value to the nearest power of two toward negative infinity.\n","base.floor10":"\nbase.floor10( x:number )\n    Rounds a numeric value to the nearest power of ten toward negative infinity.\n","base.floorb":"\nbase.floorb( x:number, n:integer, b:integer )\n    Rounds a numeric value to the nearest multiple of `b^n` toward negative\n    infinity.\n","base.floorf":"\nbase.floorf( x:number )\n    Rounds a single-precision floating-point number toward negative infinity.\n","base.floorn":"\nbase.floorn( x:number, n:integer )\n    Rounds a double-precision floating-point number to the nearest multiple of\n    `10^n` toward negative infinity.\n","base.floorsd":"\nbase.floorsd( x:number, n:integer, b:integer )\n    Rounds a numeric value to the nearest number toward negative infinity with\n    `n` significant figures.\n","base.forEachChar":"\nbase.forEachChar( str:string, clbk:Function[, thisArg:any] )\n    Invokes a function for each UTF-16 code unit in a string.\n","base.forEachCodePoint":"\nbase.forEachCodePoint( str:string, clbk:Function[, thisArg:any] )\n    Invokes a function for each Unicode code point in a string.\n","base.forEachCodePointRight":"\nbase.forEachCodePointRight( str:string, clbk:Function[, thisArg:any] )\n    Invokes a function for each Unicode code point in a string, iterating from\n    right to left.\n","base.forEachGraphemeCluster":"\nbase.forEachGraphemeCluster( str:string, clbk:Function[, thisArg:any] )\n    Invokes a function for each grapheme cluster (i.e., user-perceived\n    character) in a string.\n","base.forEachRight":"\nbase.forEachRight( str:string, clbk:Function[, thisArg:any] )\n    Invokes a function for each UTF-16 code unit in a string, iterating from\n    right to left.\n","base.formatInterpolate":"\nbase.formatInterpolate( tokens:Array, ...args:any )\n    Generate string from a token array by interpolating values.\n","base.formatTokenize":"\nbase.formatTokenize( str:string )\n    Tokenize a string into an array of string parts and format identifier\n    objects.\n","base.fresnel":"\nbase.fresnel( x:number )\n    Computes the Fresnel integrals S(x) and C(x).\n","base.fresnel.assign":"\nbase.fresnel.assign( x:number, out:Array<number>, stride:integer, \n  offset:integer )\n    Computes the Fresnel integrals S(x) and C(x) and assigns results to a\n    provided output array.\n","base.fresnelc":"\nbase.fresnelc( x:number )\n    Computes the Fresnel integral C(x).\n","base.fresnels":"\nbase.fresnels( x:number )\n    Computes the Fresnel integral S(x).\n","base.frexp":"\nbase.frexp( x:number )\n    Splits a double-precision floating-point number into a normalized fraction\n    and an integer power of two.\n","base.frexp.assign":"\nbase.frexp.assign( x:number, out:Array<number>, stride:integer, offset:integer )\n    Splits a double-precision floating-point number into a normalized fraction\n    and an integer power of two and assigns results to a provided output array.\n","base.fromBinaryString":"\nbase.fromBinaryString( bstr:string )\n    Creates a double-precision floating-point number from a literal bit\n    representation.\n","base.fromBinaryStringf":"\nbase.fromBinaryStringf( bstr:string )\n    Creates a single-precision floating-point number from an IEEE 754 literal\n    bit representation.\n","base.fromBinaryStringUint8":"\nbase.fromBinaryStringUint8( bstr:string )\n    Creates an unsigned 8-bit integer from a literal bit representation.\n","base.fromBinaryStringUint16":"\nbase.fromBinaryStringUint16( bstr:string )\n    Creates an unsigned 16-bit integer from a literal bit representation.\n","base.fromBinaryStringUint32":"\nbase.fromBinaryStringUint32( bstr:string )\n    Creates an unsigned 32-bit integer from a literal bit representation.\n","base.fromInt64Bytes":"\nbase.fromInt64Bytes( bytes:Array|TypedArray|Object, stride:integer, \n  offset:integer )\n    Converts a signed 64-bit integer byte array to a double-precision floating-\n    point number.\n","base.fromWordf":"\nbase.fromWordf( word:integer )\n    Creates a single-precision floating-point number from an unsigned integer\n    corresponding to an IEEE 754 binary representation.\n","base.fromWords":"\nbase.fromWords( high:integer, low:integer )\n    Creates a double-precision floating-point number from a higher order word\n    (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n","base.gamma":"\nbase.gamma( x:number )\n    Evaluates the gamma function.\n","base.gamma1pm1":"\nbase.gamma1pm1( x:number )\n    Computes `gamma(x+1) - 1` without cancellation errors, where `gamma(x)` is\n    the gamma function.\n","base.gammaDeltaRatio":"\nbase.gammaDeltaRatio( z:number, delta:number )\n    Computes the ratio of two gamma functions.\n","base.gammainc":"\nbase.gammainc( x:number, s:number[, regularized:boolean[, upper:boolean]] )\n    Computes the regularized incomplete gamma function.\n","base.gammaincinv":"\nbase.gammaincinv( p:number, a:number[, upper:boolean] )\n    Computes the inverse of the lower incomplete gamma function.\n","base.gammaLanczosSum":"\nbase.gammaLanczosSum( x:number )\n    Calculates the Lanczos sum for the approximation of the gamma function.\n","base.gammaLanczosSumExpGScaled":"\nbase.gammaLanczosSumExpGScaled( x:number )\n    Calculates the scaled Lanczos sum for the approximation of the gamma\n    function.\n","base.gammaln":"\nbase.gammaln( x:number )\n    Evaluates the natural logarithm of the gamma function.\n","base.gammasgn":"\nbase.gammasgn( x:number )\n    Computes the sign of the gamma function.\n","base.gcd":"\nbase.gcd( a:integer, b:integer )\n    Computes the greatest common divisor (gcd).\n","base.getHighWord":"\nbase.getHighWord( x:number )\n    Returns an unsigned 32-bit integer corresponding to the more significant 32\n    bits of a double-precision floating-point number.\n","base.getLowWord":"\nbase.getLowWord( x:number )\n    Returns an unsigned 32-bit integer corresponding to the less significant 32\n    bits of a double-precision floating-point number.\n","base.hacovercos":"\nbase.hacovercos( x:number )\n    Computes the half-value coversed cosine.\n","base.hacoversin":"\nbase.hacoversin( x:number )\n    Computes the half-value coversed sine.\n","base.havercos":"\nbase.havercos( x:number )\n    Computes the half-value versed cosine.\n","base.haversin":"\nbase.haversin( x:number )\n    Computes the half-value versed sine.\n","base.headercase":"\nbase.headercase( str:string )\n    Converts a string to HTTP header case.\n","base.heaviside":"\nbase.heaviside( x:number[, continuity:string] )\n    Evaluates the Heaviside function.\n","base.hermitepoly":"\nbase.hermitepoly( n:integer, x:number )\n    Evaluates a physicist's Hermite polynomial.\n","base.hermitepoly.factory":"\nbase.hermitepoly.factory( n:integer )\n    Returns a function for evaluating a physicist's Hermite polynomial.\n","base.hypot":"\nbase.hypot( x:number, y:number )\n    Computes the hypotenuse avoiding overflow and underflow.\n","base.hypotf":"\nbase.hypotf( x:number, y:number )\n    Computes the hypotenuse avoiding overflow and underflow (single-precision).\n","base.identity":"\nbase.identity( x:number )\n    Evaluates the identity function for a double-precision floating-point number\n    `x`.\n","base.identityf":"\nbase.identityf( x:number )\n    Evaluates the identity function for a single-precision floating-point number\n    `x`.\n","base.imul":"\nbase.imul( a:integer, b:integer )\n    Performs C-like multiplication of two signed 32-bit integers.\n","base.imuldw":"\nbase.imuldw( a:integer, b:integer )\n    Multiplies two signed 32-bit integers and returns an array of two signed 32-\n    bit integers which represents the signed 64-bit integer product.\n","base.imuldw.assign":"\nbase.imuldw.assign( a:integer, b:integer, out:Array|TypedArray|Object, \n  stride:integer, offset:integer )\n    Multiplies two signed 32-bit integers and assigns results representing the\n    signed 64-bit integer product to a provided output array.\n","base.int2slice":"\nbase.int2slice( value:integer, max:integer, strict:boolean )\n    Converts an integer to a Slice object.\n","base.int32ToUint32":"\nbase.int32ToUint32( x:integer )\n    Converts a signed 32-bit integer to an unsigned 32-bit integer.\n","base.inv":"\nbase.inv( x:number )\n    Computes the multiplicative inverse of a double-precision floating-point\n    number `x`.\n","base.invcase":"\nbase.invcase( str:string )\n    Converts a string to inverse case.\n","base.invf":"\nbase.invf( x:number )\n    Computes the multiplicative inverse of a single-precision floating-point\n    number `x`.\n","base.isComposite":"\nbase.isComposite( x:number )\n    Tests if a number is composite.\n","base.isCoprime":"\nbase.isCoprime( a:number, b:number )\n    Tests if two numbers are coprime.\n","base.isEven":"\nbase.isEven( x:number )\n    Tests if a finite numeric value is an even number.\n","base.isEvenInt32":"\nbase.isEvenInt32( x:integer )\n    Tests if a 32-bit integer is even.\n","base.isFinite":"\nbase.isFinite( x:number )\n    Tests if a double-precision floating-point numeric value is finite.\n","base.isFinitef":"\nbase.isFinitef( x:number )\n    Tests if a single-precision floating-point numeric value is finite.\n","base.isInfinite":"\nbase.isInfinite( x:number )\n    Tests if a double-precision floating-point numeric value is infinite.\n","base.isInfinitef":"\nbase.isInfinitef( x:number )\n    Tests if a single-precision floating-point numeric value is infinite.\n","base.isInteger":"\nbase.isInteger( x:number )\n    Tests if a finite double-precision floating-point number is an integer.\n","base.isnan":"\nbase.isnan( x:number )\n     Tests if a double-precision floating-point numeric value is `NaN`.\n","base.isnanf":"\nbase.isnanf( x:number )\n     Tests if a single-precision floating-point numeric value is `NaN`.\n","base.isNegativeFinite":"\nbase.isNegativeFinite( x:number )\n    Tests if a double-precision floating-point numeric value is a negative\n    finite number.\n","base.isNegativeInteger":"\nbase.isNegativeInteger( x:number )\n    Tests if a finite double-precision floating-point number is a negative\n    integer.\n","base.isNegativeZero":"\nbase.isNegativeZero( x:number )\n    Tests if a double-precision floating-point numeric value is negative zero.\n","base.isNegativeZerof":"\nbase.isNegativeZerof( x:number )\n    Tests if a single-precision floating-point numeric value is negative zero.\n","base.isNonNegativeFinite":"\nbase.isNonNegativeFinite( x:number )\n    Tests if a double-precision floating-point numeric value is a nonnegative\n    finite number.\n","base.isNonNegativeInteger":"\nbase.isNonNegativeInteger( x:number )\n    Tests if a finite double-precision floating-point number is a nonnegative\n    integer.\n","base.isNonPositiveFinite":"\nbase.isNonPositiveFinite( x:number )\n    Tests if a double-precision floating-point numeric value is a nonpositive\n    finite number.\n","base.isNonPositiveInteger":"\nbase.isNonPositiveInteger( x:number )\n    Tests if a finite double-precision floating-point number is a nonpositive\n    integer.\n","base.isOdd":"\nbase.isOdd( x:number )\n    Tests if a finite numeric value is an odd number.\n","base.isOddInt32":"\nbase.isOddInt32( x:integer )\n    Tests if a 32-bit integer is odd.\n","base.isPositiveFinite":"\nbase.isPositiveFinite( x:number )\n    Tests if a double-precision floating-point numeric value is a positive\n    finite number.\n","base.isPositiveInteger":"\nbase.isPositiveInteger( x:number )\n    Tests if a finite double-precision floating-point number is a positive\n    integer.\n","base.isPositiveZero":"\nbase.isPositiveZero( x:number )\n    Tests if a double-precision floating-point numeric value is positive zero.\n","base.isPositiveZerof":"\nbase.isPositiveZerof( x:number )\n    Tests if a single-precision floating-point numeric value is positive zero.\n","base.isPow2Uint32":"\nbase.isPow2Uint32( x:integer )\n    Tests whether an unsigned integer is a power of 2.\n","base.isPrime":"\nbase.isPrime( x:number )\n    Tests if a number is prime.\n","base.isProbability":"\nbase.isProbability( x:number )\n    Tests if a double-precision floating-point number value is a probability.\n","base.isSafeInteger":"\nbase.isSafeInteger( x:number )\n    Tests if a finite double-precision floating-point number is a safe integer.\n","base.kebabcase":"\nbase.kebabcase( str:string )\n    Converts a string to kebab case.\n","base.kernelBetainc":"\nbase.kernelBetainc( x:number, a:number, b:number, regularized:boolean, \n  upper:boolean )\n    Computes the kernel function for the regularized incomplete beta function.\n","base.kernelBetainc.assign":"\nbase.kernelBetainc.assign( x:number, a:number, b:number, regularized:boolean, \n  upper:boolean, out:Array|TypedArray|Object, stride:integer, offset:integer )\n    Computes the kernel function for the regularized incomplete beta function.\n","base.kernelBetaincinv":"\nbase.kernelBetaincinv( a:number, b:number, p:number, q:number )\n    Computes the inverse of the lower incomplete beta function.\n","base.kernelCos":"\nbase.kernelCos( x:number, y:number )\n    Computes the cosine of a double-precision floating-point number on the\n    interval [-π/4, π/4].\n","base.kernelLog1p":"\nbase.kernelLog1p( f:number )\n    Computes `log(1+f) - f` for `1+f` in ~[sqrt(2)/2, sqrt(2)].\n","base.kernelSin":"\nbase.kernelSin( x:number, y:number )\n    Computes the sine of a double-precision floating-point number on [-π/4,π/4].\n","base.kernelTan":"\nbase.kernelTan( x:number, y:number, k:integer )\n    Computes the tangent of a double-precision floating-point number on the\n    interval [-π/4, π/4].\n","base.kroneckerDelta":"\nbase.kroneckerDelta( i:number, j:number )\n    Evaluates the Kronecker delta.\n","base.kroneckerDeltaf":"\nbase.kroneckerDeltaf( i:number, j:number )\n    Evaluates the Kronecker delta (single-precision).\n","base.labs":"\nbase.labs( x:integer )\n    Computes an absolute value of a signed 32-bit integer in two's complement\n    format.\n","base.last":"\nbase.last( str:string, n:integer )\n    Returns the last `n` UTF-16 code units of a string.\n","base.lastCodePoint":"\nbase.lastCodePoint( str:string, n:integer )\n    Returns the last `n` Unicode code points of a string.\n","base.lastGraphemeCluster":"\nbase.lastGraphemeCluster( str:string, n:integer )\n    Returns the last `n` grapheme clusters (i.e., user-perceived characters) of\n    a string.\n","base.lcm":"\nbase.lcm( a:integer, b:integer )\n    Computes the least common multiple (lcm).\n","base.ldexp":"\nbase.ldexp( frac:number, exp:number )\n    Multiplies a double-precision floating-point number by an integer power of\n    two; i.e., `x = frac * 2^exp`.\n","base.leftPad":"\nbase.leftPad( str:string, len:integer, pad:string )\n    Left pads a string such that the padded string has a length of at least\n    `len`.\n","base.leftTrim":"\nbase.leftTrim( str:string )\n    Trims whitespace from the beginning of a string.\n","base.ln":"\nbase.ln( x:number )\n    Evaluates the natural logarithm of a double-precision floating-point number.\n","base.log":"\nbase.log( x:number, b:number )\n    Computes the base `b` logarithm of a double-precision floating-point number.\n","base.log1mexp":"\nbase.log1mexp( x:number )\n    Evaluates the natural logarithm of `1-exp(-|x|)`.\n","base.log1p":"\nbase.log1p( x:number )\n    Evaluates the natural logarithm of `1+x`.\n","base.log1pexp":"\nbase.log1pexp( x:number )\n    Evaluates the natural logarithm of `1+exp(x)`.\n","base.log1pmx":"\nbase.log1pmx( x:number )\n    Evaluates `ln(1+x) - x`.\n","base.log2":"\nbase.log2( x:number )\n    Evaluates the binary logarithm (base two).\n","base.log10":"\nbase.log10( x:number )\n    Evaluates the common logarithm (base 10).\n","base.logaddexp":"\nbase.logaddexp( x:number, y:number )\n    Computes the natural logarithm of `exp(x) + exp(y)`.\n","base.logit":"\nbase.logit( p:number )\n    Evaluates the logit function.\n","base.lowercase":"\nbase.lowercase( str:string )\n    Converts a string to lowercase.\n","base.lucas":"\nbase.lucas( n:integer )\n    Computes the nth Lucas number.\n","base.lucaspoly":"\nbase.lucaspoly( n:integer, x:number )\n    Evaluates a Lucas polynomial.\n","base.lucaspoly.factory":"\nbase.lucaspoly.factory( n:integer )\n    Returns a function for evaluating a Lucas polynomial.\n","base.max":"\nbase.max( x:number, y:number )\n    Returns the maximum value.\n","base.maxabs":"\nbase.maxabs( x:number, y:number )\n    Returns the maximum absolute value.\n","base.maxabsn":"\nbase.maxabsn( [x:number[, y:number[, ...args:number]]] )\n    Returns the maximum absolute value.\n","base.maxn":"\nbase.maxn( [x:number[, y:number[, ...args:number]]] )\n    Returns the maximum value.\n","base.min":"\nbase.min( x:number, y:number )\n    Returns the minimum value.\n","base.minabs":"\nbase.minabs( x:number, y:number )\n    Returns the minimum absolute value.\n","base.minabsn":"\nbase.minabsn( [x:number[, y:number[, ...args:number]]] )\n    Returns the minimum absolute value.\n","base.minmax":"\nbase.minmax( x:number, y:number )\n    Returns the minimum and maximum values.\n","base.minmax.assign":"\nbase.minmax.assign( x:number, y:number, out:Array|TypedArray|Object, \n  stride:integer, offset:integer )\n    Returns the minimum and maximum values and assigns results to a provided\n    output array.\n","base.minmaxabs":"\nbase.minmaxabs( x:number, y:number )\n    Returns the minimum and maximum absolute values.\n","base.minmaxabs.assign":"\nbase.minmaxabs.assign( x:number, y:number, out:Array|TypedArray|Object, \n  stride:integer, offset:integer )\n    Returns the minimum and maximum absolute values.\n","base.minmaxabsn":"\nbase.minmaxabsn( [x:number[, y:number[, ...args:number]]] )\n    Returns the minimum and maximum absolute values.\n","base.minmaxabsn.assign":"\nbase.minmaxabsn.assign( [x:number[, y:number[, ...args:number]]], \n  out:Array|TypedArray|Object, stride:integer, offset:integer )\n    Returns the minimum and maximum absolute values.\n","base.minmaxn":"\nbase.minmaxn( [x:number[, y:number[, ...args:number]]] )\n    Returns the minimum and maximum values.\n","base.minmaxn.assign":"\nbase.minmaxn.assign( [x:number[, y:number[, ...args:number]]], \n  out:Array|TypedArray|Object, stride:integer, offset:integer )\n    Returns the minimum and maximum values and assigns results to a provided\n    output array.\n","base.minn":"\nbase.minn( [x:number[, y:number[, ...args:number]]] )\n    Returns the minimum value.\n","base.modf":"\nbase.modf( x:number )\n    Decomposes a double-precision floating-point number into integral and\n    fractional parts, each having the same type and sign as the input value.\n","base.modf.assign":"\nbase.modf.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n  offset:integer )\n    Decomposes a double-precision floating-point number into integral and\n    fractional parts, each having the same type and sign as the input value,\n    and assigns results to a provided output array.\n","base.mul":"\nbase.mul( x:number, y:number )\n    Multiplies two double-precision floating-point numbers `x` and `y`.\n","base.mulf":"\nbase.mulf( x:number, y:number )\n    Multiplies two single-precision floating-point numbers `x` and `y`.\n","base.ndarray":"\nbase.ndarray( dtype:string, buffer:ArrayLikeObject|TypedArray|Buffer, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  offset:integer, order:string )\n    Returns an ndarray.\n","base.ndarray.prototype.byteLength":"\nbase.ndarray.prototype.byteLength\n    Size (in bytes) of the array (if known).\n","base.ndarray.prototype.BYTES_PER_ELEMENT":"\nbase.ndarray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element (if known).\n","base.ndarray.prototype.data":"\nbase.ndarray.prototype.data\n    Pointer to the underlying data buffer.\n","base.ndarray.prototype.dtype":"\nbase.ndarray.prototype.dtype\n    Underlying data type.\n","base.ndarray.prototype.flags":"\nbase.ndarray.prototype.flags\n    Meta information, such as information concerning the memory layout of the\n    array.\n","base.ndarray.prototype.length":"\nbase.ndarray.prototype.length\n    Length of the array (i.e., number of elements).\n","base.ndarray.prototype.ndims":"\nbase.ndarray.prototype.ndims\n    Number of dimensions.\n","base.ndarray.prototype.offset":"\nbase.ndarray.prototype.offset\n    Index offset which specifies the buffer index at which to start iterating\n    over array elements.\n","base.ndarray.prototype.order: string":"\nbase.ndarray.prototype.order: string\n    Array order.\n","base.ndarray.prototype.shape":"\nbase.ndarray.prototype.shape\n    Array shape.\n","base.ndarray.prototype.strides":"\nbase.ndarray.prototype.strides\n    Index strides which specify how to access data along corresponding array\n    dimensions.\n","base.ndarray.prototype.get":"\nbase.ndarray.prototype.get( ...idx:integer )\n    Returns an array element specified according to provided subscripts.\n","base.ndarray.prototype.iget":"\nbase.ndarray.prototype.iget( idx:integer )\n    Returns an array element located at a specified linear index.\n","base.ndarray.prototype.set":"\nbase.ndarray.prototype.set( ...idx:integer, v:any )\n    Sets an array element specified according to provided subscripts.\n","base.ndarray.prototype.iset":"\nbase.ndarray.prototype.iset( idx:integer, v:any )\n    Sets an array element located at a specified linear index.\n","base.ndarray.prototype.toString":"\nbase.ndarray.prototype.toString()\n    Serializes an ndarray as a string.\n","base.ndarray.prototype.toJSON":"\nbase.ndarray.prototype.toJSON()\n    Serializes an ndarray as a JSON object.\n","base.ndarrayUnary":"\nbase.ndarrayUnary( arrays:ArrayLikeObject<ndarray>, fcn:Function )\n    Applies a unary callback to elements in an input ndarray and assigns results\n    to elements in an output ndarray.\n","base.ndzeros":"\nbase.ndzeros( dtype:string, shape:ArrayLikeObject<integer>, order:string )\n    Returns a zero-filled ndarray having a specified shape and data type.\n","base.ndzerosLike":"\nbase.ndzerosLike( x:ndarray )\n    Returns a zero-filled ndarray having the same shape and data type as a\n    provided input ndarray.\n","base.negafibonacci":"\nbase.negafibonacci( n:integer )\n    Computes the nth negaFibonacci number.\n","base.negalucas":"\nbase.negalucas( n:integer )\n    Computes the nth negaLucas number.\n","base.nonfibonacci":"\nbase.nonfibonacci( n:integer )\n    Computes the nth non-Fibonacci number.\n","base.normalize":"\nbase.normalize( x:number )\n    Returns a normal number and exponent satisfying `x = y * 2^exp` as an array.\n","base.normalize.assign":"\nbase.normalize.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n  offset:integer )\n    Returns a normal number and exponent satisfying `x = y * 2^exp` and assigns\n    results to a provided output array.\n","base.normalizef":"\nbase.normalizef( x:float )\n    Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` as\n    an array.\n","base.normalizef.assign":"\nbase.normalizef.assign( x:float, out:Array|TypedArray|Object, stride:integer, \n  offset:integer )\n    Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` and\n    assigns results to a provided output array.\n","base.normalizeSlice":"\nbase.normalizeSlice( slice:Slice, len:integer, strict:boolean )\n    Returns a normalized Slice object.\n","base.normhermitepoly":"\nbase.normhermitepoly( n:integer, x:number )\n    Evaluates a normalized Hermite polynomial using double-precision floating-\n    point arithmetic.\n","base.normhermitepoly.factory":"\nbase.normhermitepoly.factory( n:integer )\n    Returns a function for evaluating a normalized Hermite polynomial using\n    double-precision floating-point arithmetic.\n","base.pascalcase":"\nbase.pascalcase( str:string )\n    Converts a string to Pascal case.\n","base.pdiff":"\nbase.pdiff( x:number, y:number )\n    Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n    returns `0`.\n","base.pdifff":"\nbase.pdifff( x:number, y:number )\n    Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n    returns `0`.\n","base.percentEncode":"\nbase.percentEncode( str:string )\n    Percent-encodes a UTF-16 encoded string according to RFC 3986.\n","base.polygamma":"\nbase.polygamma( n:integer, x:number )\n    Evaluates the polygamma function of order `n`; i.e., the (n+1)th derivative\n    of the natural logarithm of the gamma function.\n","base.pow":"\nbase.pow( b:number, x:number )\n    Evaluates the exponential function `bˣ`.\n","base.powm1":"\nbase.powm1( b:number, x:number )\n    Evaluates `bˣ - 1`.\n","base.rad2deg":"\nbase.rad2deg( x:number )\n    Converts an angle from radians to degrees.\n","base.rad2degf":"\nbase.rad2degf( x:number )\n    Converts an angle from radians to degrees (single-precision).\n","base.ramp":"\nbase.ramp( x:number )\n    Evaluates the ramp function.\n","base.rampf":"\nbase.rampf( x:number )\n    Evaluates the ramp function (single-precision).\n","base.random.arcsine":"\nbase.random.arcsine( a:number, b:number )\n    Returns a pseudorandom number drawn from an arcsine distribution.\n","base.random.arcsine.factory":"\nbase.random.arcsine.factory( [a:number, b:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an arcsine distribution.\n","base.random.arcsine.NAME":"\nbase.random.arcsine.NAME\n    Generator name.\n","base.random.arcsine.PRNG":"\nbase.random.arcsine.PRNG\n    Underlying pseudorandom number generator.\n","base.random.arcsine.seed":"\nbase.random.arcsine.seed\n    Pseudorandom number generator seed.\n","base.random.arcsine.seedLength":"\nbase.random.arcsine.seedLength\n    Length of generator seed.\n","base.random.arcsine.state":"\nbase.random.arcsine.state\n    Generator state.\n","base.random.arcsine.stateLength":"\nbase.random.arcsine.stateLength\n    Length of generator state.\n","base.random.arcsine.byteLength":"\nbase.random.arcsine.byteLength\n    Size (in bytes) of generator state.\n","base.random.arcsine.toJSON":"\nbase.random.arcsine.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.bernoulli":"\nbase.random.bernoulli( p:number )\n    Returns a pseudorandom number drawn from a Bernoulli distribution.\n","base.random.bernoulli.factory":"\nbase.random.bernoulli.factory( [p:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Bernoulli distribution.\n","base.random.bernoulli.NAME":"\nbase.random.bernoulli.NAME\n    Generator name.\n","base.random.bernoulli.PRNG":"\nbase.random.bernoulli.PRNG\n    Underlying pseudorandom number generator.\n","base.random.bernoulli.seed":"\nbase.random.bernoulli.seed\n    Pseudorandom number generator seed.\n","base.random.bernoulli.seedLength":"\nbase.random.bernoulli.seedLength\n    Length of generator seed.\n","base.random.bernoulli.state":"\nbase.random.bernoulli.state\n    Generator state.\n","base.random.bernoulli.stateLength":"\nbase.random.bernoulli.stateLength\n    Length of generator state.\n","base.random.bernoulli.byteLength":"\nbase.random.bernoulli.byteLength\n    Size (in bytes) of generator state.\n","base.random.bernoulli.toJSON":"\nbase.random.bernoulli.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.beta":"\nbase.random.beta( α:number, β:number )\n    Returns a pseudorandom number drawn from a beta distribution.\n","base.random.beta.factory":"\nbase.random.beta.factory( [α:number, β:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a beta distribution.\n","base.random.beta.NAME":"\nbase.random.beta.NAME\n    Generator name.\n","base.random.beta.PRNG":"\nbase.random.beta.PRNG\n    Underlying pseudorandom number generator.\n","base.random.beta.seed":"\nbase.random.beta.seed\n    Pseudorandom number generator seed.\n","base.random.beta.seedLength":"\nbase.random.beta.seedLength\n    Length of generator seed.\n","base.random.beta.state":"\nbase.random.beta.state\n    Generator state.\n","base.random.beta.stateLength":"\nbase.random.beta.stateLength\n    Length of generator state.\n","base.random.beta.byteLength":"\nbase.random.beta.byteLength\n    Size (in bytes) of generator state.\n","base.random.beta.toJSON":"\nbase.random.beta.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.betaprime":"\nbase.random.betaprime( α:number, β:number )\n    Returns a pseudorandom number drawn from a beta prime distribution.\n","base.random.betaprime.factory":"\nbase.random.betaprime.factory( [α:number, β:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a beta prime distribution.\n","base.random.betaprime.NAME":"\nbase.random.betaprime.NAME\n    Generator name.\n","base.random.betaprime.PRNG":"\nbase.random.betaprime.PRNG\n    Underlying pseudorandom number generator.\n","base.random.betaprime.seed":"\nbase.random.betaprime.seed\n    Pseudorandom number generator seed.\n","base.random.betaprime.seedLength":"\nbase.random.betaprime.seedLength\n    Length of generator seed.\n","base.random.betaprime.state":"\nbase.random.betaprime.state\n    Generator state.\n","base.random.betaprime.stateLength":"\nbase.random.betaprime.stateLength\n    Length of generator state.\n","base.random.betaprime.byteLength":"\nbase.random.betaprime.byteLength\n    Size (in bytes) of generator state.\n","base.random.betaprime.toJSON":"\nbase.random.betaprime.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.binomial":"\nbase.random.binomial( n:integer, p:number )\n    Returns a pseudorandom number drawn from a binomial distribution.\n","base.random.binomial.factory":"\nbase.random.binomial.factory( [n:integer, p:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a binomial distribution.\n","base.random.binomial.NAME":"\nbase.random.binomial.NAME\n    Generator name.\n","base.random.binomial.PRNG":"\nbase.random.binomial.PRNG\n    Underlying pseudorandom number generator.\n","base.random.binomial.seed":"\nbase.random.binomial.seed\n    Pseudorandom number generator seed.\n","base.random.binomial.seedLength":"\nbase.random.binomial.seedLength\n    Length of generator seed.\n","base.random.binomial.state":"\nbase.random.binomial.state\n    Generator state.\n","base.random.binomial.stateLength":"\nbase.random.binomial.stateLength\n    Length of generator state.\n","base.random.binomial.byteLength":"\nbase.random.binomial.byteLength\n    Size of generator state.\n","base.random.binomial.toJSON":"\nbase.random.binomial.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.boxMuller":"\nbase.random.boxMuller()\n    Returns a pseudorandom number drawn from a standard normal distribution.\n","base.random.boxMuller.factory":"\nbase.random.boxMuller.factory( [options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a standard normal distribution.\n","base.random.boxMuller.NAME":"\nbase.random.boxMuller.NAME\n    Generator name.\n","base.random.boxMuller.PRNG":"\nbase.random.boxMuller.PRNG\n    Underlying pseudorandom number generator.\n","base.random.boxMuller.seed":"\nbase.random.boxMuller.seed\n    Pseudorandom number generator seed.\n","base.random.boxMuller.seedLength":"\nbase.random.boxMuller.seedLength\n    Length of generator seed.\n","base.random.boxMuller.state":"\nbase.random.boxMuller.state\n    Generator state.\n","base.random.boxMuller.stateLength":"\nbase.random.boxMuller.stateLength\n    Length of generator state.\n","base.random.boxMuller.byteLength":"\nbase.random.boxMuller.byteLength\n    Size (in bytes) of generator state.\n","base.random.boxMuller.toJSON":"\nbase.random.boxMuller.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.cauchy":"\nbase.random.cauchy( x0:number, Ɣ:number )\n    Returns a pseudorandom number drawn from a Cauchy distribution.\n","base.random.cauchy.factory":"\nbase.random.cauchy.factory( [x0:number, Ɣ:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Cauchy distribution.\n","base.random.cauchy.NAME":"\nbase.random.cauchy.NAME\n    Generator name.\n","base.random.cauchy.PRNG":"\nbase.random.cauchy.PRNG\n    Underlying pseudorandom number generator.\n","base.random.cauchy.seed":"\nbase.random.cauchy.seed\n    Pseudorandom number generator seed.\n","base.random.cauchy.seedLength":"\nbase.random.cauchy.seedLength\n    Length of generator seed.\n","base.random.cauchy.state":"\nbase.random.cauchy.state\n    Generator state.\n","base.random.cauchy.stateLength":"\nbase.random.cauchy.stateLength\n    Length of generator state.\n","base.random.cauchy.byteLength":"\nbase.random.cauchy.byteLength\n    Size (in bytes) of generator state.\n","base.random.cauchy.toJSON":"\nbase.random.cauchy.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.chi":"\nbase.random.chi( k:number )\n    Returns a pseudorandom number drawn from a chi distribution.\n","base.random.chi.factory":"\nbase.random.chi.factory( [k:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a chi distribution.\n","base.random.chi.NAME":"\nbase.random.chi.NAME\n    Generator name.\n","base.random.chi.PRNG":"\nbase.random.chi.PRNG\n    Underlying pseudorandom number generator.\n","base.random.chi.seed":"\nbase.random.chi.seed\n    Pseudorandom number generator seed.\n","base.random.chi.seedLength":"\nbase.random.chi.seedLength\n    Length of generator seed.\n","base.random.chi.state":"\nbase.random.chi.state\n    Generator state.\n","base.random.chi.stateLength":"\nbase.random.chi.stateLength\n    Length of generator state.\n","base.random.chi.byteLength":"\nbase.random.chi.byteLength\n    Size (in bytes) of generator state.\n","base.random.chi.toJSON":"\nbase.random.chi.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.chisquare":"\nbase.random.chisquare( k:number )\n    Returns a pseudorandom number drawn from a chi-square distribution.\n","base.random.chisquare.factory":"\nbase.random.chisquare.factory( [k:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a chi-square distribution.\n","base.random.chisquare.NAME":"\nbase.random.chisquare.NAME\n    Generator name.\n","base.random.chisquare.PRNG":"\nbase.random.chisquare.PRNG\n    Underlying pseudorandom number generator.\n","base.random.chisquare.seed":"\nbase.random.chisquare.seed\n    Pseudorandom number generator seed.\n","base.random.chisquare.seedLength":"\nbase.random.chisquare.seedLength\n    Length of generator seed.\n","base.random.chisquare.state":"\nbase.random.chisquare.state\n    Generator state.\n","base.random.chisquare.stateLength":"\nbase.random.chisquare.stateLength\n    Length of generator state.\n","base.random.chisquare.byteLength":"\nbase.random.chisquare.byteLength\n    Size (in bytes) of generator state.\n","base.random.chisquare.toJSON":"\nbase.random.chisquare.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.cosine":"\nbase.random.cosine( μ:number, s:number )\n    Returns a pseudorandom number drawn from a raised cosine distribution.\n","base.random.cosine.factory":"\nbase.random.cosine.factory( [μ:number, s:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a raised cosine distribution.\n","base.random.cosine.NAME":"\nbase.random.cosine.NAME\n    Generator name.\n","base.random.cosine.PRNG":"\nbase.random.cosine.PRNG\n    Underlying pseudorandom number generator.\n","base.random.cosine.seed":"\nbase.random.cosine.seed\n    Pseudorandom number generator seed.\n","base.random.cosine.seedLength":"\nbase.random.cosine.seedLength\n    Length of generator seed.\n","base.random.cosine.state":"\nbase.random.cosine.state\n    Generator state.\n","base.random.cosine.stateLength":"\nbase.random.cosine.stateLength\n    Length of generator state.\n","base.random.cosine.byteLength":"\nbase.random.cosine.byteLength\n    Size (in bytes) of generator state.\n","base.random.cosine.toJSON":"\nbase.random.cosine.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.discreteUniform":"\nbase.random.discreteUniform( a:integer, b:integer )\n    Returns a pseudorandom number drawn from a discrete uniform distribution.\n","base.random.discreteUniform.factory":"\nbase.random.discreteUniform.factory( [a:integer, b:integer, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a discrete uniform distribution.\n","base.random.discreteUniform.NAME":"\nbase.random.discreteUniform.NAME\n    Generator name.\n","base.random.discreteUniform.PRNG":"\nbase.random.discreteUniform.PRNG\n    Underlying pseudorandom number generator.\n","base.random.discreteUniform.seed":"\nbase.random.discreteUniform.seed\n    Pseudorandom number generator seed.\n","base.random.discreteUniform.seedLength":"\nbase.random.discreteUniform.seedLength\n    Length of generator seed.\n","base.random.discreteUniform.state":"\nbase.random.discreteUniform.state\n    Generator state.\n","base.random.discreteUniform.stateLength":"\nbase.random.discreteUniform.stateLength\n    Length of generator state.\n","base.random.discreteUniform.byteLength":"\nbase.random.discreteUniform.byteLength\n    Size (in bytes) of generator state.\n","base.random.discreteUniform.toJSON":"\nbase.random.discreteUniform.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.erlang":"\nbase.random.erlang( k:integer, λ:number )\n    Returns a pseudorandom number drawn from an Erlang distribution.\n","base.random.erlang.factory":"\nbase.random.erlang.factory( [k:integer, λ:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an Erlang distribution.\n","base.random.erlang.NAME":"\nbase.random.erlang.NAME\n    Generator name.\n","base.random.erlang.PRNG":"\nbase.random.erlang.PRNG\n    Underlying pseudorandom number generator.\n","base.random.erlang.seed":"\nbase.random.erlang.seed\n    Pseudorandom number generator seed.\n","base.random.erlang.seedLength":"\nbase.random.erlang.seedLength\n    Length of generator seed.\n","base.random.erlang.state":"\nbase.random.erlang.state\n    Generator state.\n","base.random.erlang.stateLength":"\nbase.random.erlang.stateLength\n    Length of generator state.\n","base.random.erlang.byteLength":"\nbase.random.erlang.byteLength\n    Size (in bytes) of generator state.\n","base.random.erlang.toJSON":"\nbase.random.erlang.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.exponential":"\nbase.random.exponential( λ:number )\n    Returns a pseudorandom number drawn from an exponential distribution.\n","base.random.exponential.factory":"\nbase.random.exponential.factory( [λ:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an exponential distribution.\n","base.random.exponential.NAME":"\nbase.random.exponential.NAME\n    Generator name.\n","base.random.exponential.PRNG":"\nbase.random.exponential.PRNG\n    Underlying pseudorandom number generator.\n","base.random.exponential.seed":"\nbase.random.exponential.seed\n    Pseudorandom number generator seed.\n","base.random.exponential.seedLength":"\nbase.random.exponential.seedLength\n    Length of generator seed.\n","base.random.exponential.state":"\nbase.random.exponential.state\n    Generator state.\n","base.random.exponential.stateLength":"\nbase.random.exponential.stateLength\n    Length of generator state.\n","base.random.exponential.byteLength":"\nbase.random.exponential.byteLength\n    Size (in bytes) of generator state.\n","base.random.exponential.toJSON":"\nbase.random.exponential.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.f":"\nbase.random.f( d1:number, d2:number )\n    Returns a pseudorandom number drawn from an F distribution.\n","base.random.f.factory":"\nbase.random.f.factory( [d1:number, d2:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an F distribution.\n","base.random.f.NAME":"\nbase.random.f.NAME\n    Generator name.\n","base.random.f.PRNG":"\nbase.random.f.PRNG\n    Underlying pseudorandom number generator.\n","base.random.f.seed":"\nbase.random.f.seed\n    Pseudorandom number generator seed.\n","base.random.f.seedLength":"\nbase.random.f.seedLength\n    Length of generator seed.\n","base.random.f.state":"\nbase.random.f.state\n    Generator state.\n","base.random.f.stateLength":"\nbase.random.f.stateLength\n    Length of generator state.\n","base.random.f.byteLength":"\nbase.random.f.byteLength\n    Size (in bytes) of generator state.\n","base.random.f.toJSON":"\nbase.random.f.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.frechet":"\nbase.random.frechet( α:number, s:number, m:number )\n    Returns a pseudorandom number drawn from a Fréchet distribution.\n","base.random.frechet.factory":"\nbase.random.frechet.factory( [α:number, s:number, m:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a triangular distribution.\n","base.random.frechet.NAME":"\nbase.random.frechet.NAME\n    Generator name.\n","base.random.frechet.PRNG":"\nbase.random.frechet.PRNG\n    Underlying pseudorandom number generator.\n","base.random.frechet.seed":"\nbase.random.frechet.seed\n    Pseudorandom number generator seed.\n","base.random.frechet.seedLength":"\nbase.random.frechet.seedLength\n    Length of generator seed.\n","base.random.frechet.state":"\nbase.random.frechet.state\n    Generator state.\n","base.random.frechet.stateLength":"\nbase.random.frechet.stateLength\n    Length of generator state.\n","base.random.frechet.byteLength":"\nbase.random.frechet.byteLength\n    Size (in bytes) of generator state.\n","base.random.frechet.toJSON":"\nbase.random.frechet.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.gamma":"\nbase.random.gamma( α:number, β:number )\n    Returns a pseudorandom number drawn from a gamma distribution.\n","base.random.gamma.factory":"\nbase.random.gamma.factory( [α:number, β:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a gamma distribution.\n","base.random.gamma.NAME":"\nbase.random.gamma.NAME\n    Generator name.\n","base.random.gamma.PRNG":"\nbase.random.gamma.PRNG\n    Underlying pseudorandom number generator.\n","base.random.gamma.seed":"\nbase.random.gamma.seed\n    Pseudorandom number generator seed.\n","base.random.gamma.seedLength":"\nbase.random.gamma.seedLength\n    Length of generator seed.\n","base.random.gamma.state":"\nbase.random.gamma.state\n    Generator state.\n","base.random.gamma.stateLength":"\nbase.random.gamma.stateLength\n    Length of generator state.\n","base.random.gamma.byteLength":"\nbase.random.gamma.byteLength\n    Size of generator state.\n","base.random.gamma.toJSON":"\nbase.random.gamma.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.geometric":"\nbase.random.geometric( p:number )\n    Returns a pseudorandom number drawn from a geometric distribution.\n","base.random.geometric.factory":"\nbase.random.geometric.factory( [p:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a geometric distribution.\n","base.random.geometric.NAME":"\nbase.random.geometric.NAME\n    Generator name.\n","base.random.geometric.PRNG":"\nbase.random.geometric.PRNG\n    Underlying pseudorandom number generator.\n","base.random.geometric.seed":"\nbase.random.geometric.seed\n    Pseudorandom number generator seed.\n","base.random.geometric.seedLength":"\nbase.random.geometric.seedLength\n    Length of generator seed.\n","base.random.geometric.state":"\nbase.random.geometric.state\n    Generator state.\n","base.random.geometric.stateLength":"\nbase.random.geometric.stateLength\n    Length of generator state.\n","base.random.geometric.byteLength":"\nbase.random.geometric.byteLength\n    Size (in bytes) of generator state.\n","base.random.geometric.toJSON":"\nbase.random.geometric.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.gumbel":"\nbase.random.gumbel( μ:number, β:number )\n    Returns a pseudorandom number drawn from a Gumbel distribution.\n","base.random.gumbel.factory":"\nbase.random.gumbel.factory( [μ:number, β:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Gumbel distribution.\n","base.random.gumbel.NAME":"\nbase.random.gumbel.NAME\n    Generator name.\n","base.random.gumbel.PRNG":"\nbase.random.gumbel.PRNG\n    Underlying pseudorandom number generator.\n","base.random.gumbel.seed":"\nbase.random.gumbel.seed\n    Pseudorandom number generator seed.\n","base.random.gumbel.seedLength":"\nbase.random.gumbel.seedLength\n    Length of generator seed.\n","base.random.gumbel.state":"\nbase.random.gumbel.state\n    Generator state.\n","base.random.gumbel.stateLength":"\nbase.random.gumbel.stateLength\n    Length of generator state.\n","base.random.gumbel.byteLength":"\nbase.random.gumbel.byteLength\n    Size (in bytes) of generator state.\n","base.random.gumbel.toJSON":"\nbase.random.gumbel.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.hypergeometric":"\nbase.random.hypergeometric( N:integer, K:integer, n:integer )\n    Returns a pseudorandom number drawn from a hypergeometric distribution.\n","base.random.hypergeometric.factory":"\nbase.random.hypergeometric.factory( [N:integer, K:integer, n:integer, ]\n  [options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a hypergeometric distribution.\n","base.random.hypergeometric.NAME":"\nbase.random.hypergeometric.NAME\n    Generator name.\n","base.random.hypergeometric.PRNG":"\nbase.random.hypergeometric.PRNG\n    Underlying pseudorandom number generator.\n","base.random.hypergeometric.seed":"\nbase.random.hypergeometric.seed\n    Pseudorandom number generator seed.\n","base.random.hypergeometric.seedLength":"\nbase.random.hypergeometric.seedLength\n    Length of generator seed.\n","base.random.hypergeometric.state":"\nbase.random.hypergeometric.state\n    Generator state.\n","base.random.hypergeometric.stateLength":"\nbase.random.hypergeometric.stateLength\n    Length of generator state.\n","base.random.hypergeometric.byteLength":"\nbase.random.hypergeometric.byteLength\n    Size (in bytes) of generator state.\n","base.random.hypergeometric.toJSON":"\nbase.random.hypergeometric.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.improvedZiggurat":"\nbase.random.improvedZiggurat()\n    Returns a pseudorandom number drawn from a standard normal distribution.\n","base.random.improvedZiggurat.factory":"\nbase.random.improvedZiggurat.factory( [options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a standard normal distribution.\n","base.random.improvedZiggurat.NAME":"\nbase.random.improvedZiggurat.NAME\n    Generator name.\n","base.random.improvedZiggurat.PRNG":"\nbase.random.improvedZiggurat.PRNG\n    Underlying pseudorandom number generator.\n","base.random.improvedZiggurat.seed":"\nbase.random.improvedZiggurat.seed\n    Pseudorandom number generator seed.\n","base.random.improvedZiggurat.seedLength":"\nbase.random.improvedZiggurat.seedLength\n    Length of generator seed.\n","base.random.improvedZiggurat.state":"\nbase.random.improvedZiggurat.state\n    Generator state.\n","base.random.improvedZiggurat.stateLength":"\nbase.random.improvedZiggurat.stateLength\n    Length of generator state.\n","base.random.improvedZiggurat.byteLength":"\nbase.random.improvedZiggurat.byteLength\n    Size (in bytes) of generator state.\n","base.random.improvedZiggurat.toJSON":"\nbase.random.improvedZiggurat.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.invgamma":"\nbase.random.invgamma( α:number, β:number )\n    Returns a pseudorandom number drawn from an inverse gamma distribution.\n","base.random.invgamma.factory":"\nbase.random.invgamma.factory( [α:number, β:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an inverse gamma distribution.\n","base.random.invgamma.NAME":"\nbase.random.invgamma.NAME\n    Generator name.\n","base.random.invgamma.PRNG":"\nbase.random.invgamma.PRNG\n    Underlying pseudorandom number generator.\n","base.random.invgamma.seed":"\nbase.random.invgamma.seed\n    Pseudorandom number generator seed.\n","base.random.invgamma.seedLength":"\nbase.random.invgamma.seedLength\n    Length of generator seed.\n","base.random.invgamma.state":"\nbase.random.invgamma.state\n    Generator state.\n","base.random.invgamma.stateLength":"\nbase.random.invgamma.stateLength\n    Length of generator state.\n","base.random.invgamma.byteLength":"\nbase.random.invgamma.byteLength\n    Size of generator state.\n","base.random.invgamma.toJSON":"\nbase.random.invgamma.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.kumaraswamy":"\nbase.random.kumaraswamy( a:number, b:number )\n    Returns a pseudorandom number drawn from Kumaraswamy's double bounded\n    distribution.\n","base.random.kumaraswamy.factory":"\nbase.random.kumaraswamy.factory( [a:number, b:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from Kumaraswamy's double bounded distribution.\n","base.random.kumaraswamy.NAME":"\nbase.random.kumaraswamy.NAME\n    Generator name.\n","base.random.kumaraswamy.PRNG":"\nbase.random.kumaraswamy.PRNG\n    Underlying pseudorandom number generator.\n","base.random.kumaraswamy.seed":"\nbase.random.kumaraswamy.seed\n    Pseudorandom number generator seed.\n","base.random.kumaraswamy.seedLength":"\nbase.random.kumaraswamy.seedLength\n    Length of generator seed.\n","base.random.kumaraswamy.state":"\nbase.random.kumaraswamy.state\n    Generator state.\n","base.random.kumaraswamy.stateLength":"\nbase.random.kumaraswamy.stateLength\n    Length of generator state.\n","base.random.kumaraswamy.byteLength":"\nbase.random.kumaraswamy.byteLength\n    Size (in bytes) of generator state.\n","base.random.kumaraswamy.toJSON":"\nbase.random.kumaraswamy.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.laplace":"\nbase.random.laplace( μ:number, b:number )\n    Returns a pseudorandom number drawn from a Laplace distribution.\n","base.random.laplace.factory":"\nbase.random.laplace.factory( [μ:number, b:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Laplace distribution.\n","base.random.laplace.NAME":"\nbase.random.laplace.NAME\n    Generator name.\n","base.random.laplace.PRNG":"\nbase.random.laplace.PRNG\n    Underlying pseudorandom number generator.\n","base.random.laplace.seed":"\nbase.random.laplace.seed\n    Pseudorandom number generator seed.\n","base.random.laplace.seedLength":"\nbase.random.laplace.seedLength\n    Length of generator seed.\n","base.random.laplace.state":"\nbase.random.laplace.state\n    Generator state.\n","base.random.laplace.stateLength":"\nbase.random.laplace.stateLength\n    Length of generator state.\n","base.random.laplace.byteLength":"\nbase.random.laplace.byteLength\n    Size (in bytes) of generator state.\n","base.random.laplace.toJSON":"\nbase.random.laplace.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.levy":"\nbase.random.levy( μ:number, c:number )\n    Returns a pseudorandom number drawn from a Lévy distribution.\n","base.random.levy.factory":"\nbase.random.levy.factory( [μ:number, c:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Lévy distribution.\n","base.random.levy.NAME":"\nbase.random.levy.NAME\n    Generator name.\n","base.random.levy.PRNG":"\nbase.random.levy.PRNG\n    Underlying pseudorandom number generator.\n","base.random.levy.seed":"\nbase.random.levy.seed\n    Pseudorandom number generator seed.\n","base.random.levy.seedLength":"\nbase.random.levy.seedLength\n    Length of generator seed.\n","base.random.levy.state":"\nbase.random.levy.state\n    Generator state.\n","base.random.levy.stateLength":"\nbase.random.levy.stateLength\n    Length of generator state.\n","base.random.levy.byteLength":"\nbase.random.levy.byteLength\n    Size (in bytes) of generator state.\n","base.random.levy.toJSON":"\nbase.random.levy.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.logistic":"\nbase.random.logistic( μ:number, s:number )\n    Returns a pseudorandom number drawn from a logistic distribution.\n","base.random.logistic.factory":"\nbase.random.logistic.factory( [μ:number, s:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a logistic distribution.\n","base.random.logistic.NAME":"\nbase.random.logistic.NAME\n    Generator name.\n","base.random.logistic.PRNG":"\nbase.random.logistic.PRNG\n    Underlying pseudorandom number generator.\n","base.random.logistic.seed":"\nbase.random.logistic.seed\n    Pseudorandom number generator seed.\n","base.random.logistic.seedLength":"\nbase.random.logistic.seedLength\n    Length of generator seed.\n","base.random.logistic.state":"\nbase.random.logistic.state\n    Generator state.\n","base.random.logistic.stateLength":"\nbase.random.logistic.stateLength\n    Length of generator state.\n","base.random.logistic.byteLength":"\nbase.random.logistic.byteLength\n    Size (in bytes) of generator state.\n","base.random.logistic.toJSON":"\nbase.random.logistic.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.lognormal":"\nbase.random.lognormal( μ:number, σ:number )\n    Returns a pseudorandom number drawn from a lognormal distribution.\n","base.random.lognormal.factory":"\nbase.random.lognormal.factory( [μ:number, σ:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a lognormal distribution.\n","base.random.lognormal.NAME":"\nbase.random.lognormal.NAME\n    Generator name.\n","base.random.lognormal.PRNG":"\nbase.random.lognormal.PRNG\n    Underlying pseudorandom number generator.\n","base.random.lognormal.seed":"\nbase.random.lognormal.seed\n    Pseudorandom number generator seed.\n","base.random.lognormal.seedLength":"\nbase.random.lognormal.seedLength\n    Length of generator seed.\n","base.random.lognormal.state":"\nbase.random.lognormal.state\n    Generator state.\n","base.random.lognormal.stateLength":"\nbase.random.lognormal.stateLength\n    Length of generator state.\n","base.random.lognormal.byteLength":"\nbase.random.lognormal.byteLength\n    Size (in bytes) of generator state.\n","base.random.lognormal.toJSON":"\nbase.random.lognormal.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.minstd":"\nbase.random.minstd()\n    Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n","base.random.minstd.normalized":"\nbase.random.minstd.normalized()\n    Returns a pseudorandom number on the interval `[0,1)`.\n","base.random.minstd.factory":"\nbase.random.minstd.factory( [options:Object] )\n    Returns a linear congruential pseudorandom number generator (LCG).\n","base.random.minstd.NAME":"\nbase.random.minstd.NAME\n    Generator name.\n","base.random.minstd.MIN":"\nbase.random.minstd.MIN\n    Minimum possible value.\n","base.random.minstd.MAX":"\nbase.random.minstd.MAX\n    Maximum possible value.\n","base.random.minstd.seed":"\nbase.random.minstd.seed\n    Pseudorandom number generator seed.\n","base.random.minstd.seedLength":"\nbase.random.minstd.seedLength\n    Length of generator seed.\n","base.random.minstd.state":"\nbase.random.minstd.state\n    Generator state.\n","base.random.minstd.stateLength":"\nbase.random.minstd.stateLength\n    Length of generator state.\n","base.random.minstd.byteLength":"\nbase.random.minstd.byteLength\n    Size (in bytes) of generator state.\n","base.random.minstd.toJSON":"\nbase.random.minstd.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.minstdShuffle":"\nbase.random.minstdShuffle()\n    Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n","base.random.minstdShuffle.normalized":"\nbase.random.minstdShuffle.normalized()\n    Returns a pseudorandom number on the interval `[0,1)`.\n","base.random.minstdShuffle.factory":"\nbase.random.minstdShuffle.factory( [options:Object] )\n    Returns a linear congruential pseudorandom number generator (LCG) whose\n    output is shuffled.\n","base.random.minstdShuffle.NAME":"\nbase.random.minstdShuffle.NAME\n    Generator name.\n","base.random.minstdShuffle.MIN":"\nbase.random.minstdShuffle.MIN\n    Minimum possible value.\n","base.random.minstdShuffle.MAX":"\nbase.random.minstdShuffle.MAX\n    Maximum possible value.\n","base.random.minstdShuffle.seed":"\nbase.random.minstdShuffle.seed\n    Pseudorandom number generator seed.\n","base.random.minstdShuffle.seedLength":"\nbase.random.minstdShuffle.seedLength\n    Length of generator seed.\n","base.random.minstdShuffle.state":"\nbase.random.minstdShuffle.state\n    Generator state.\n","base.random.minstdShuffle.stateLength":"\nbase.random.minstdShuffle.stateLength\n    Length of generator state.\n","base.random.minstdShuffle.byteLength":"\nbase.random.minstdShuffle.byteLength\n    Size (in bytes) of generator state.\n","base.random.minstdShuffle.toJSON":"\nbase.random.minstdShuffle.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.mt19937":"\nbase.random.mt19937()\n    Returns a pseudorandom integer on the interval `[0, 4294967295]`.\n","base.random.mt19937.normalized":"\nbase.random.mt19937.normalized()\n    Returns a pseudorandom number on the interval `[0,1)` with 53-bit precision.\n","base.random.mt19937.factory":"\nbase.random.mt19937.factory( [options:Object] )\n    Returns a 32-bit Mersenne Twister pseudorandom number generator.\n","base.random.mt19937.NAME":"\nbase.random.mt19937.NAME\n    Generator name.\n","base.random.mt19937.MIN":"\nbase.random.mt19937.MIN\n    Minimum possible value.\n","base.random.mt19937.MAX":"\nbase.random.mt19937.MAX\n    Maximum possible value.\n","base.random.mt19937.seed":"\nbase.random.mt19937.seed\n    Pseudorandom number generator seed.\n","base.random.mt19937.seedLength":"\nbase.random.mt19937.seedLength\n    Length of generator seed.\n","base.random.mt19937.state":"\nbase.random.mt19937.state\n    Generator state.\n","base.random.mt19937.stateLength":"\nbase.random.mt19937.stateLength\n    Length of generator state.\n","base.random.mt19937.byteLength":"\nbase.random.mt19937.byteLength\n    Size (in bytes) of generator state.\n","base.random.mt19937.toJSON":"\nbase.random.mt19937.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.negativeBinomial":"\nbase.random.negativeBinomial( r:number, p:number )\n    Returns a pseudorandom number drawn from a negative binomial distribution.\n","base.random.negativeBinomial.factory":"\nbase.random.negativeBinomial.factory( [r:number, p:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a negative binomial distribution.\n","base.random.negativeBinomial.NAME":"\nbase.random.negativeBinomial.NAME\n    Generator name.\n","base.random.negativeBinomial.PRNG":"\nbase.random.negativeBinomial.PRNG\n    Underlying pseudorandom number generator.\n","base.random.negativeBinomial.seed":"\nbase.random.negativeBinomial.seed\n    Pseudorandom number generator seed.\n","base.random.negativeBinomial.seedLength":"\nbase.random.negativeBinomial.seedLength\n    Length of generator seed.\n","base.random.negativeBinomial.state":"\nbase.random.negativeBinomial.state\n    Generator state.\n","base.random.negativeBinomial.stateLength":"\nbase.random.negativeBinomial.stateLength\n    Length of generator state.\n","base.random.negativeBinomial.byteLength":"\nbase.random.negativeBinomial.byteLength\n    Size (in bytes) of generator state.\n","base.random.negativeBinomial.toJSON":"\nbase.random.negativeBinomial.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.normal":"\nbase.random.normal( μ:number, σ:number )\n    Returns a pseudorandom number drawn from a normal distribution.\n","base.random.normal.factory":"\nbase.random.normal.factory( [μ:number, σ:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a normal distribution.\n","base.random.normal.NAME":"\nbase.random.normal.NAME\n    Generator name.\n","base.random.normal.PRNG":"\nbase.random.normal.PRNG\n    Underlying pseudorandom number generator.\n","base.random.normal.seed":"\nbase.random.normal.seed\n    Pseudorandom number generator seed.\n","base.random.normal.seedLength":"\nbase.random.normal.seedLength\n    Length of generator seed.\n","base.random.normal.state":"\nbase.random.normal.state\n    Generator state.\n","base.random.normal.stateLength":"\nbase.random.normal.stateLength\n    Length of generator state.\n","base.random.normal.byteLength":"\nbase.random.normal.byteLength\n    Size of generator state.\n","base.random.normal.toJSON":"\nbase.random.normal.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.pareto1":"\nbase.random.pareto1( α:number, β:number )\n    Returns a pseudorandom number drawn from a Pareto (Type I) distribution.\n","base.random.pareto1.factory":"\nbase.random.pareto1.factory( [α:number, β:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Pareto (Type I) distribution.\n","base.random.pareto1.NAME":"\nbase.random.pareto1.NAME\n    Generator name.\n","base.random.pareto1.PRNG":"\nbase.random.pareto1.PRNG\n    Underlying pseudorandom number generator.\n","base.random.pareto1.seed":"\nbase.random.pareto1.seed\n    Pseudorandom number generator seed.\n","base.random.pareto1.seedLength":"\nbase.random.pareto1.seedLength\n    Length of generator seed.\n","base.random.pareto1.state":"\nbase.random.pareto1.state\n    Generator state.\n","base.random.pareto1.stateLength":"\nbase.random.pareto1.stateLength\n    Length of generator state.\n","base.random.pareto1.byteLength":"\nbase.random.pareto1.byteLength\n    Size (in bytes) of generator state.\n","base.random.pareto1.toJSON":"\nbase.random.pareto1.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.poisson":"\nbase.random.poisson( λ:number )\n    Returns a pseudorandom number drawn from a Poisson distribution.\n","base.random.poisson.factory":"\nbase.random.poisson.factory( [λ:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Poisson distribution.\n","base.random.poisson.NAME":"\nbase.random.poisson.NAME\n    Generator name.\n","base.random.poisson.PRNG":"\nbase.random.poisson.PRNG\n    Underlying pseudorandom number generator.\n","base.random.poisson.seed":"\nbase.random.poisson.seed\n    Pseudorandom number generator seed.\n","base.random.poisson.seedLength":"\nbase.random.poisson.seedLength\n    Length of generator seed.\n","base.random.poisson.state":"\nbase.random.poisson.state\n    Generator state.\n","base.random.poisson.stateLength":"\nbase.random.poisson.stateLength\n    Length of generator state.\n","base.random.poisson.byteLength":"\nbase.random.poisson.byteLength\n    Size (in bytes) of generator state.\n","base.random.poisson.toJSON":"\nbase.random.poisson.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.randi":"\nbase.random.randi()\n    Returns a pseudorandom number having an integer value.\n","base.random.randi.factory":"\nbase.random.randi.factory( [options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers having integer values.\n","base.random.randi.NAME":"\nbase.random.randi.NAME\n    Generator name.\n","base.random.randi.PRNG":"\nbase.random.randi.PRNG\n    Underlying pseudorandom number generator.\n","base.random.randi.MIN":"\nbase.random.randi.MIN\n    Minimum possible value (specific to underlying PRNG).\n","base.random.randi.MAX":"\nbase.random.randi.MAX\n    Maximum possible value (specific to underlying PRNG).\n","base.random.randi.seed":"\nbase.random.randi.seed\n    Pseudorandom number generator seed.\n","base.random.randi.seedLength":"\nbase.random.randi.seedLength\n    Length of generator seed.\n","base.random.randi.state":"\nbase.random.randi.state\n    Generator state.\n","base.random.randi.stateLength":"\nbase.random.randi.stateLength\n    Length of generator state.\n","base.random.randi.byteLength":"\nbase.random.randi.byteLength\n    Size (in bytes) of generator state.\n","base.random.randi.toJSON":"\nbase.random.randi.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.randn":"\nbase.random.randn()\n    Returns a pseudorandom number drawn from a standard normal distribution.\n","base.random.randn.factory":"\nbase.random.randn.factory( [options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a standard normal distribution.\n","base.random.randn.NAME":"\nbase.random.randn.NAME\n    Generator name.\n","base.random.randn.PRNG":"\nbase.random.randn.PRNG\n    Underlying pseudorandom number generator.\n","base.random.randn.seed":"\nbase.random.randn.seed\n    Pseudorandom number generator seed.\n","base.random.randn.seedLength":"\nbase.random.randn.seedLength\n    Length of generator seed.\n","base.random.randn.state":"\nbase.random.randn.state\n    Generator state.\n","base.random.randn.stateLength":"\nbase.random.randn.stateLength\n    Length of generator state.\n","base.random.randn.byteLength":"\nbase.random.randn.byteLength\n    Size (in bytes) of generator state.\n","base.random.randn.toJSON":"\nbase.random.randn.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.randu":"\nbase.random.randu()\n    Returns a pseudorandom number drawn from a uniform distribution.\n","base.random.randu.factory":"\nbase.random.randu.factory( [options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a uniform distribution.\n","base.random.randu.NAME":"\nbase.random.randu.NAME\n    Generator name.\n","base.random.randu.PRNG":"\nbase.random.randu.PRNG\n    Underlying pseudorandom number generator.\n","base.random.randu.MIN":"\nbase.random.randu.MIN\n    Minimum possible value (specific to underlying PRNG).\n","base.random.randu.MAX":"\nbase.random.randu.MAX\n    Maximum possible value (specific to underlying PRNG).\n","base.random.randu.seed":"\nbase.random.randu.seed\n    Pseudorandom number generator seed.\n","base.random.randu.seedLength":"\nbase.random.randu.seedLength\n    Length of generator seed.\n","base.random.randu.state":"\nbase.random.randu.state\n    Generator state.\n","base.random.randu.stateLength":"\nbase.random.randu.stateLength\n    Length of generator state.\n","base.random.randu.byteLength":"\nbase.random.randu.byteLength\n    Size (in bytes) of generator state.\n","base.random.randu.toJSON":"\nbase.random.randu.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.rayleigh":"\nbase.random.rayleigh( σ:number )\n    Returns a pseudorandom number drawn from a Rayleigh distribution.\n","base.random.rayleigh.factory":"\nbase.random.rayleigh.factory( [σ:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Rayleigh distribution.\n","base.random.rayleigh.NAME":"\nbase.random.rayleigh.NAME\n    Generator name.\n","base.random.rayleigh.PRNG":"\nbase.random.rayleigh.PRNG\n    Underlying pseudorandom number generator.\n","base.random.rayleigh.seed":"\nbase.random.rayleigh.seed\n    Pseudorandom number generator seed.\n","base.random.rayleigh.seedLength":"\nbase.random.rayleigh.seedLength\n    Length of generator seed.\n","base.random.rayleigh.state":"\nbase.random.rayleigh.state\n    Generator state.\n","base.random.rayleigh.stateLength":"\nbase.random.rayleigh.stateLength\n    Length of generator state.\n","base.random.rayleigh.byteLength":"\nbase.random.rayleigh.byteLength\n    Size (in bytes) of generator state.\n","base.random.rayleigh.toJSON":"\nbase.random.rayleigh.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.t":"\nbase.random.t( v:number )\n    Returns a pseudorandom number drawn from a Student's t distribution.\n","base.random.t.factory":"\nbase.random.t.factory( [v:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Student's t distribution.\n","base.random.t.NAME":"\nbase.random.t.NAME\n    Generator name.\n","base.random.t.PRNG":"\nbase.random.t.PRNG\n    Underlying pseudorandom number generator.\n","base.random.t.seed":"\nbase.random.t.seed\n    Pseudorandom number generator seed.\n","base.random.t.seedLength":"\nbase.random.t.seedLength\n    Length of generator seed.\n","base.random.t.state":"\nbase.random.t.state\n    Generator state.\n","base.random.t.stateLength":"\nbase.random.t.stateLength\n    Length of generator state.\n","base.random.t.byteLength":"\nbase.random.t.byteLength\n    Size (in bytes) of generator state.\n","base.random.t.toJSON":"\nbase.random.t.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.triangular":"\nbase.random.triangular( a:number, b:number, c:number )\n    Returns a pseudorandom number drawn from a triangular distribution.\n","base.random.triangular.factory":"\nbase.random.triangular.factory( [a:number, b:number, c:number, ]\n  [options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a triangular distribution.\n","base.random.triangular.NAME":"\nbase.random.triangular.NAME\n    Generator name.\n","base.random.triangular.PRNG":"\nbase.random.triangular.PRNG\n    Underlying pseudorandom number generator.\n","base.random.triangular.seed":"\nbase.random.triangular.seed\n    Pseudorandom number generator seed.\n","base.random.triangular.seedLength":"\nbase.random.triangular.seedLength\n    Length of generator seed.\n","base.random.triangular.state":"\nbase.random.triangular.state\n    Generator state.\n","base.random.triangular.stateLength":"\nbase.random.triangular.stateLength\n    Length of generator state.\n","base.random.triangular.byteLength":"\nbase.random.triangular.byteLength\n    Size (in bytes) of generator state.\n","base.random.triangular.toJSON":"\nbase.random.triangular.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.uniform":"\nbase.random.uniform( a:number, b:number )\n    Returns a pseudorandom number drawn from a continuous uniform distribution.\n","base.random.uniform.factory":"\nbase.random.uniform.factory( [a:number, b:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a continuous uniform distribution.\n","base.random.uniform.NAME":"\nbase.random.uniform.NAME\n    Generator name.\n","base.random.uniform.PRNG":"\nbase.random.uniform.PRNG\n    Underlying pseudorandom number generator.\n","base.random.uniform.seed":"\nbase.random.uniform.seed\n    Pseudorandom number generator seed.\n","base.random.uniform.seedLength":"\nbase.random.uniform.seedLength\n    Length of generator seed.\n","base.random.uniform.state":"\nbase.random.uniform.state\n    Generator state.\n","base.random.uniform.stateLength":"\nbase.random.uniform.stateLength\n    Length of generator state.\n","base.random.uniform.byteLength":"\nbase.random.uniform.byteLength\n    Size (in bytes) of generator state.\n","base.random.uniform.toJSON":"\nbase.random.uniform.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.weibull":"\nbase.random.weibull( k:number, λ:number )\n    Returns a pseudorandom number drawn from a Weibull distribution.\n","base.random.weibull.factory":"\nbase.random.weibull.factory( [k:number, λ:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Weibull distribution.\n","base.random.weibull.NAME":"\nbase.random.weibull.NAME\n    Generator name.\n","base.random.weibull.PRNG":"\nbase.random.weibull.PRNG\n    Underlying pseudorandom number generator.\n","base.random.weibull.seed":"\nbase.random.weibull.seed\n    Pseudorandom number generator seed.\n","base.random.weibull.seedLength":"\nbase.random.weibull.seedLength\n    Length of generator seed.\n","base.random.weibull.state":"\nbase.random.weibull.state\n    Generator state.\n","base.random.weibull.stateLength":"\nbase.random.weibull.stateLength\n    Length of generator state.\n","base.random.weibull.byteLength":"\nbase.random.weibull.byteLength\n    Size (in bytes) of generator state.\n","base.random.weibull.toJSON":"\nbase.random.weibull.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.rcbrt":"\nbase.rcbrt( x:number )\n    Computes the reciprocal cube root of a double-precision floating-point\n    number.\n","base.rcbrtf":"\nbase.rcbrtf( x:number )\n    Computes the reciprocal cube root of a single-precision floating-point\n    number.\n","base.reldiff":"\nbase.reldiff( x:number, y:number[, scale:string|Function] )\n    Computes the relative difference of two real numbers.\n","base.removeFirst":"\nbase.removeFirst( str:string, n:integer )\n    Removes the first `n` UTF-16 code units of a string.\n","base.removeFirstCodePoint":"\nbase.removeFirstCodePoint( str:string, n:integer )\n    Removes the first `n` Unicode code points of a string.\n","base.removeFirstGraphemeCluster":"\nbase.removeFirstGraphemeCluster( str:string, n:integer )\n    Removes the first `n` grapheme clusters (i.e., user-perceived characters)\n    of a string.\n","base.removeLast":"\nbase.removeLast( str:string, n:integer )\n    Removes the last `n` UTF-16 code units of a string.\n","base.removeLastCodePoint":"\nbase.removeLastCodePoint( str:string, n:integer )\n    Removes the last `n` Unicode code points of a string.\n","base.removeLastGraphemeCluster":"\nbase.removeLastGraphemeCluster( str:string, n:integer )\n    Removes the last `n` grapheme clusters (i.e., user-perceived characters)\n    of a string.\n","base.rempio2":"\nbase.rempio2( x:number, y:Array|TypedArray|Object )\n    Computes `x - nπ/2 = r`.\n","base.repeat":"\nbase.repeat( str:string, n:integer )\n    Repeats a string `n` times and returns the concatenated result.\n","base.replace":"\nbase.replace( str:string, search:RegExp, newval:string|Function )\n    Replaces search occurrences with a replacement string.\n","base.replaceAfter":"\nbase.replaceAfter( str:string, search:string, replacement:string, \n  fromIndex:integer )\n    Replaces the substring after the first occurrence of a specified search\n    string.\n","base.replaceAfterLast":"\nbase.replaceAfterLast( str:string, search:string, replacement:string, \n  fromIndex:integer )\n    Replaces the substring after the last occurrence of a specified search\n    string.\n","base.replaceBefore":"\nbase.replaceBefore( str:string, search:string, replacement:string, \n  fromIndex:integer )\n    Replaces the substring before the first occurrence of a specified search\n    string.\n","base.replaceBeforeLast":"\nbase.replaceBeforeLast( str:string, search:string, replacement:string, \n  fromIndex:integer )\n    Replaces the substring before the last occurrence of a specified search\n    string.\n","base.reverse":"\nbase.reverse( str:string )\n    Reverses the UTF-16 code units of a string.\n","base.reverseCodePoints":"\nbase.reverseCodePoints( str:string )\n    Reverses the Unicode code points of a string.\n","base.reverseGraphemeClusters":"\nbase.reverseGraphemeClusters( str:string )\n    Reverses the grapheme clusters (i.e., user-perceived characters) of a\n    string.\n","base.rightPad":"\nbase.rightPad( str:string, len:integer, pad:string )\n    Right pads a string such that the padded string has a length of at least\n    `len`.\n","base.rightTrim":"\nbase.rightTrim( str:string )\n    Trims whitespace from the end of a string.\n","base.risingFactorial":"\nbase.risingFactorial( x:number, n:integer )\n    Computes the rising factorial of `x` and `n`.\n","base.rotl32":"\nbase.rotl32( x:integer, shift:integer )\n    Performs a bitwise rotation to the left.\n","base.rotr32":"\nbase.rotr32( x:integer, shift:integer )\n    Performs a bitwise rotation to the right.\n","base.round":"\nbase.round( x:number )\n    Rounds a numeric value to the nearest integer.\n","base.round2":"\nbase.round2( x:number )\n    Rounds a numeric value to the nearest power of two on a linear scale.\n","base.round10":"\nbase.round10( x:number )\n    Rounds a numeric value to the nearest power of ten on a linear scale.\n","base.roundb":"\nbase.roundb( x:number, n:integer, b:integer )\n    Rounds a numeric value to the nearest multiple of `b^n` on a linear scale.\n","base.roundn":"\nbase.roundn( x:number, n:integer )\n    Rounds a numeric value to the nearest multiple of `10^n`.\n","base.roundsd":"\nbase.roundsd( x:number, n:integer[, b:integer] )\n    Rounds a numeric value to the nearest number with `n` significant figures.\n","base.rsqrt":"\nbase.rsqrt( x:number )\n    Computes the reciprocal square root of a double-precision floating-point\n    number.\n","base.rsqrtf":"\nbase.rsqrtf( x:number )\n    Computes the reciprocal square root of a single-precision floating-point\n    number.\n","base.sargs2multislice":"\nbase.sargs2multislice( str:string )\n    Creates a MultiSlice object from a comma-separated list of string-serialized\n    MultiSlice constructor arguments.\n","base.scalar2ndarray":"\nbase.scalar2ndarray( value:any, dtype:string, order:string )\n    Returns a zero-dimensional ndarray containing a provided scalar value.\n","base.secd":"\nbase.secd( x:number )\n    Computes the secant of an angle measured in degrees.\n","base.seq2multislice":"\nbase.seq2multislice( str:string, shape:Array<integer>, strict:boolean )\n    Converts a multidimensional subsequence string to a MultiSlice object.\n","base.seq2slice":"\nbase.seq2slice( str:string, len:integer, strict:boolean )\n    Converts a subsequence string to a Slice object.\n","base.setHighWord":"\nbase.setHighWord( x:number, high:integer )\n    Sets the more significant 32 bits of a double-precision floating-point\n    number.\n","base.setLowWord":"\nbase.setLowWord( x:number, low:integer )\n    Sets the less significant 32 bits of a double-precision floating-point\n    number.\n","base.sici":"\nbase.sici( x:number )\n    Computes the sine and cosine integrals.\n","base.sici.assign":"\nbase.sici.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n  offset:integer )\n    Computes the sine and cosine integrals and assigns results to a provided\n    output array.\n","base.signbit":"\nbase.signbit( x:number )\n    Returns a boolean indicating if the sign bit is on (true) or off (false).\n","base.signbitf":"\nbase.signbitf( x:float )\n    Returns a boolean indicating if the sign bit is on (true) or off (false).\n","base.significandf":"\nbase.significandf( x:float )\n    Returns an integer corresponding to the significand of a single-precision\n    floating-point number.\n","base.signum":"\nbase.signum( x:number )\n    Evaluates the signum function for a double-precision floating-point number.\n","base.signumf":"\nbase.signumf( x:number )\n    Evaluates the signum function for a single-precision floating-point number.\n","base.sin":"\nbase.sin( x:number )\n    Computes the sine of a number.\n","base.sinc":"\nbase.sinc( x:number )\n    Computes the normalized cardinal sine of a number.\n","base.sincos":"\nbase.sincos( x:number )\n    Simultaneously computes the sine and cosine of a number.\n\nbase.sincos( x:number, out:Array|TypedArray|Object, stride:integer, \n  offset:integer )\n    Simultaneously computes the sine and cosine of a number and assigns\n    results to a provided output array.\n","base.sincospi":"\nbase.sincospi( x:number )\n    Simultaneously computes the sine and cosine of a number times π.\n","base.sincospi.assign":"\nbase.sincospi.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n  offset:integer )\n    Simultaneously computes the sine and cosine of a number times π and\n    assigns results to a provided output array.\n","base.sinh":"\nbase.sinh( x:number )\n    Computes the hyperbolic sine of a double-precision floating-point number.\n","base.sinpi":"\nbase.sinpi( x:number )\n    Computes the value of `sin(πx)`.\n","base.slice2seq":"\nbase.slice2seq( slice:Slice )\n    Converts a Slice object to a subsequence string.\n","base.sliceLength":"\nbase.sliceLength( slice:Slice )\n    Returns the number of elements in a normalized slice.\n","base.sliceNonReducedDimensions":"\nbase.sliceNonReducedDimensions( slice:MultiSlice )\n    Returns a list of non-reduced dimensions in an un-normalized multi-slice.\n","base.sliceReducedDimensions":"\nbase.sliceReducedDimensions( slice:MultiSlice )\n    Returns a list of reduced dimensions in an un-normalized multi-slice.\n","base.sliceShape":"\nbase.sliceShape( slice:MultiSlice )\n    Returns the shape of a normalized multi-slice.\n","base.snakecase":"\nbase.snakecase( str:string )\n    Converts a string to snake case.\n","base.spence":"\nbase.spence( x:number )\n    Evaluates Spence's function, which is also known as the dilogarithm.\n","base.sqrt":"\nbase.sqrt( x:number )\n    Computes the principal square root of a double-precision floating-point\n    number.\n","base.sqrt1pm1":"\nbase.sqrt1pm1( x:number )\n    Computes the principal square root of `1+x` minus one.\n","base.sqrtf":"\nbase.sqrtf( x:number )\n    Computes the principal square root of a single-precision floating-point\n    number.\n","base.sqrtpi":"\nbase.sqrtpi( x:number )\n    Computes the principal square root of the product of π and a positive\n    double-precision floating-point number.\n","base.startcase":"\nbase.startcase( str:string )\n    Capitalizes the first letter of each word in an input string.\n","base.startsWith":"\nbase.startsWith( str:string, search:string, position:integer )\n    Tests if a string starts with the characters of another string.\n","base.stickycase":"\nbase.stickycase( str[, p] )\n    Converts a string to sticky case.\n","base.strided.binary":"\nbase.strided.binary( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  fcn:Function )\n    Applies a binary callback to strided input array elements and assigns\n    results to elements in a strided output array.\n","base.strided.binary.ndarray":"\nbase.strided.binary.ndarray( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  offsets:ArrayLikeObject<integer>, fcn:Function )\n    Applies a binary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n","base.strided.binaryDtypeSignatures":"\nbase.strided.binaryDtypeSignatures( dtypes1:ArrayLike<any>, \n  dtypes2:ArrayLike<any>, dtypes3:ArrayLike<any>[, options:Object] )\n    Generates a list of binary interface signatures from strided array data\n    types.\n","base.strided.binarySignatureCallbacks":"\nbase.strided.binarySignatureCallbacks( table:Object, signatures:ArrayLike<any> )\n    Assigns callbacks to binary interfaces according to type promotion rules.\n","base.strided.ccopy":"\nbase.strided.ccopy( N:integer, x:Complex64Array, strideX:integer, \n  y:Complex64Array, strideY:integer )\n    Copies values from one complex single-precision floating-point vector to\n    another complex single-precision floating-point vector.\n","base.strided.ccopy.ndarray":"\nbase.strided.ccopy.ndarray( N:integer, x:Complex64Array, strideX:integer, \n  offsetX:integer, y:Complex64Array, strideY:integer, offsetY:integer )\n    Copies values from one complex single-precision floating-point vector to\n    another complex single-precision floating-point vector using alternative\n    indexing semantics.\n","base.strided.cmap":"\nbase.strided.cmap( N:integer, x:Complex64Array, strideX:integer, \n  y:Complex64Array, strideY:integer, fcn:Function )\n    Applies a unary function to a single-precision complex floating-point\n    strided input array and assigns results to a single-precision complex\n    floating-point strided output array.\n","base.strided.cmap.ndarray":"\nbase.strided.cmap.ndarray( N:integer, x:Complex64Array, strideX:integer, \n  offsetX:integer, y:Complex64Array, strideY:integer, offsetY:integer, \n  fcn:Function )\n    Applies a unary function to a single-precision complex floating-point\n    strided input array and assigns results to a single-precision complex\n    floating-point strided output array using alternative indexing semantics.\n","base.strided.cswap":"\nbase.strided.cswap( N:integer, x:Complex64Array, strideX:integer, \n  y:Complex64Array, strideY:integer )\n    Interchanges two complex single-precision floating-point vectors.\n","base.strided.cswap.ndarray":"\nbase.strided.cswap.ndarray( N:integer, x:Complex64Array, strideX:integer, \n  offsetX:integer, y:Complex64Array, strideY:integer, offsetY:integer )\n    Interchanges two complex single-precision floating-point vectors using\n    alternative indexing semantics.\n","base.strided.cumax":"\nbase.strided.cumax( N:integer, x:Array|TypedArray, strideX:integer, \n  y:Array|TypedArray, strideY:integer )\n    Computes the cumulative maximum of a strided array.\n","base.strided.cumax.ndarray":"\nbase.strided.cumax.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n  offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n    Computes the cumulative maximum of a strided array using alternative\n    indexing semantics.\n","base.strided.cumaxabs":"\nbase.strided.cumaxabs( N:integer, x:Array|TypedArray, strideX:integer, \n  y:Array|TypedArray, strideY:integer )\n    Computes the cumulative maximum absolute value of a strided array.\n","base.strided.cumaxabs.ndarray":"\nbase.strided.cumaxabs.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n  offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n    Computes the cumulative maximum absolute value of a strided array using\n    alternative indexing semantics.\n","base.strided.cumin":"\nbase.strided.cumin( N:integer, x:Array|TypedArray, strideX:integer, \n  y:Array|TypedArray, strideY:integer )\n    Computes the cumulative minimum of a strided array.\n","base.strided.cumin.ndarray":"\nbase.strided.cumin.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n  offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n    Computes the cumulative minimum of a strided array using alternative\n    indexing semantics.\n","base.strided.cuminabs":"\nbase.strided.cuminabs( N:integer, x:Array|TypedArray, strideX:integer, \n  y:Array|TypedArray, strideY:integer )\n    Computes the cumulative minimum absolute value of a strided array.\n","base.strided.cuminabs.ndarray":"\nbase.strided.cuminabs.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n  offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n    Computes the cumulative minimum absolute value of a strided array using\n    alternative indexing semantics.\n","base.strided.dabs":"\nbase.strided.dabs( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n  strideY:integer )\n    Computes the absolute value for each element in a double-precision floating-\n    point strided array `x` and assigns the results to elements in a double-\n    precision floating-point strided array `y`.\n","base.strided.dabs.ndarray":"\nbase.strided.dabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Computes the absolute value for each element in a double-precision floating-\n    point strided array `x` and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.dabs2":"\nbase.strided.dabs2( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n  strideY:integer )\n    Computes the squared absolute value for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y`.\n","base.strided.dabs2.ndarray":"\nbase.strided.dabs2.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Computes the squared absolute value for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.dapx":"\nbase.strided.dapx( N:integer, alpha:number, x:Float64Array, strideX:integer )\n    Adds a scalar constant to each element in a double-precision floating-point\n    strided array.\n","base.strided.dapx.ndarray":"\nbase.strided.dapx.ndarray( N:integer, alpha:number, x:Float64Array, \n  strideX:integer, offsetX:integer )\n    Adds a scalar constant to each element in a double-precision floating-point\n    strided array using alternative indexing semantics.\n","base.strided.dapxsum":"\nbase.strided.dapxsum( N:integer, alpha:number, x:Float64Array, strideX:integer )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum.\n","base.strided.dapxsum.ndarray":"\nbase.strided.dapxsum.ndarray( N:integer, alpha:number, x:Float64Array, \n  strideX:integer, offsetX:integer )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using alternative indexing semantics.\n","base.strided.dapxsumkbn":"\nbase.strided.dapxsumkbn( N:integer, alpha:number, x:Float64Array, \n  strideX:integer )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using an improved Kahan–Babuška\n    algorithm.\n","base.strided.dapxsumkbn.ndarray":"\nbase.strided.dapxsumkbn.ndarray( N:integer, alpha:number, x:Float64Array, \n  strideX:integer, offsetX:integer )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using an improved Kahan–Babuška\n    algorithm and alternative indexing semantics.\n","base.strided.dapxsumkbn2":"\nbase.strided.dapxsumkbn2( N:integer, alpha:number, x:Float64Array, \n  strideX:integer )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using a second-order iterative\n    Kahan–Babuška algorithm.\n","base.strided.dapxsumkbn2.ndarray":"\nbase.strided.dapxsumkbn2.ndarray( N:integer, alpha:number, x:Float64Array, \n  strideX:integer, offsetX:integer )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using a second-order iterative\n    Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.dapxsumors":"\nbase.strided.dapxsumors( N:integer, alpha:number, x:Float64Array, \n  strideX:integer )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using ordinary recursive summation.\n","base.strided.dapxsumors.ndarray":"\nbase.strided.dapxsumors.ndarray( N:integer, alpha:number, x:Float64Array, \n  strideX:integer, offsetX:integer )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using ordinary recursive summation\n    and alternative indexing semantics.\n","base.strided.dapxsumpw":"\nbase.strided.dapxsumpw( N:integer, alpha:number, x:Float64Array, \n  strideX:integer )\n    Adds a scalar constant to each double-precision floating-point strided array\n    element and computes the sum using pairwise summation.\n","base.strided.dapxsumpw.ndarray":"\nbase.strided.dapxsumpw.ndarray( N:integer, alpha:number, x:Float64Array, \n  strideX:integer, offsetX:integer )\n    Adds a constant to each double-precision floating-point strided array\n    element and computes the sum using pairwise summation and alternative\n    indexing semantics.\n","base.strided.dasum":"\nbase.strided.dasum( N:integer, x:Float64Array, stride:integer )\n    Computes the sum of the absolute values.\n","base.strided.dasum.ndarray":"\nbase.strided.dasum.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the sum of absolute values using alternative indexing semantics.\n","base.strided.dasumpw":"\nbase.strided.dasumpw( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements using pairwise summation.\n","base.strided.dasumpw.ndarray":"\nbase.strided.dasumpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements using pairwise summation and alternative\n    indexing semantics.\n","base.strided.daxpy":"\nbase.strided.daxpy( N:integer, alpha:number, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n","base.strided.daxpy.ndarray":"\nbase.strided.daxpy.ndarray( N:integer, alpha:number, x:Float64Array, \n  strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n  offsetY:integer )\n    Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n    using alternative indexing semantics.\n","base.strided.dcbrt":"\nbase.strided.dcbrt( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n  strideY:integer )\n    Computes the cube root of each element in a double-precision floating-point\n    strided array `x` and assigns the results to elements in a double-precision\n    floating-point strided array `y`.\n","base.strided.dcbrt.ndarray":"\nbase.strided.dcbrt.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Computes the cube root of each element in a double-precision floating-point\n    strided array `x` and assigns the results to elements in a double-precision\n    floating-point strided array `y` using alternative indexing semantics.\n","base.strided.dceil":"\nbase.strided.dceil( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n  strideY:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward positive infinity and assigns the results to elements in a double-\n    precision floating-point strided array `y`.\n","base.strided.dceil.ndarray":"\nbase.strided.dceil.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward positive infinity and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.dcopy":"\nbase.strided.dcopy( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n  strideY:integer )\n    Copies values from `x` into `y`.\n","base.strided.dcopy.ndarray":"\nbase.strided.dcopy.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Copies values from `x` into `y` using alternative indexing semantics.\n","base.strided.dcumax":"\nbase.strided.dcumax( N:integer, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Computes the cumulative maximum of double-precision floating-point strided\n    array elements.\n","base.strided.dcumax.ndarray":"\nbase.strided.dcumax.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Computes the cumulative maximum of double-precision floating-point strided\n    array elements using alternative indexing semantics.\n","base.strided.dcumaxabs":"\nbase.strided.dcumaxabs( N:integer, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Computes the cumulative maximum absolute value of double-precision floating-\n    point strided array elements.\n","base.strided.dcumaxabs.ndarray":"\nbase.strided.dcumaxabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Computes the cumulative maximum absolute value of double-precision floating-\n    point strided array elements using alternative indexing semantics.\n","base.strided.dcumin":"\nbase.strided.dcumin( N:integer, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Computes the cumulative minimum of double-precision floating-point strided\n    array elements.\n","base.strided.dcumin.ndarray":"\nbase.strided.dcumin.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Computes the cumulative minimum of double-precision floating-point strided\n    array elements using alternative indexing semantics.\n","base.strided.dcuminabs":"\nbase.strided.dcuminabs( N:integer, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Computes the cumulative minimum absolute value of double-precision floating-\n    point strided array elements.\n","base.strided.dcuminabs.ndarray":"\nbase.strided.dcuminabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Computes the cumulative minimum absolute value of double-precision floating-\n    point strided array elements using alternative indexing semantics.\n","base.strided.dcusum":"\nbase.strided.dcusum( N:integer, sum:number, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements.\n","base.strided.dcusum.ndarray":"\nbase.strided.dcusum.ndarray( N:integer, sum:number, x:Float64Array, \n  strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using alternative indexing semantics.\n","base.strided.dcusumkbn":"\nbase.strided.dcusumkbn( N:integer, sum:number, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using an improved Kahan–Babuška algorithm.\n","base.strided.dcusumkbn.ndarray":"\nbase.strided.dcusumkbn.ndarray( N:integer, sum:number, x:Float64Array, \n  strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n","base.strided.dcusumkbn2":"\nbase.strided.dcusumkbn2( N:integer, sum:number, x:Float64Array, \n  strideX:integer, y:Float64Array, strideY:integer )\n    Computes the cumulative sum of double-precision floating-point strided\n    array elements using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.dcusumkbn2.ndarray":"\nbase.strided.dcusumkbn2.ndarray( N:integer, sum:number, x:Float64Array, \n  strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of double-precision floating-point strided\n    array elements using a second-order iterative Kahan–Babuška algorithm and\n    alternative indexing semantics.\n","base.strided.dcusumors":"\nbase.strided.dcusumors( N:integer, sum:number, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using ordinary recursive summation.\n","base.strided.dcusumors.ndarray":"\nbase.strided.dcusumors.ndarray( N:integer, sum:number, x:Float64Array, \n  strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using ordinary recursive summation and alternative indexing\n    semantics.\n","base.strided.dcusumpw":"\nbase.strided.dcusumpw( N:integer, sum:number, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using pairwise summation.\n","base.strided.dcusumpw.ndarray":"\nbase.strided.dcusumpw.ndarray( N:integer, sum:number, x:Float64Array, \n  strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using pairwise summation and alternative indexing semantics.\n","base.strided.ddeg2rad":"\nbase.strided.ddeg2rad( N:integer, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Converts each element in a double-precision floating-point strided array `x`\n    from degrees to radians and assigns the results to elements in a double-\n    precision floating-point strided array `y`.\n","base.strided.ddeg2rad.ndarray":"\nbase.strided.ddeg2rad.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Converts each element in a double-precision floating-point strided array `x`\n    from degrees to radians and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.ddot":"\nbase.strided.ddot( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n  strideY:integer )\n    Computes the dot product of two double-precision floating-point vectors.\n","base.strided.ddot.ndarray":"\nbase.strided.ddot.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Computes the dot product of two double-precision floating-point vectors\n    using alternative indexing semantics.\n","base.strided.dfill":"\nbase.strided.dfill( N:integer, alpha:number, x:Float64Array, strideX:integer )\n    Fills a double-precision floating-point strided array with a specified\n    scalar value.\n","base.strided.dfill.ndarray":"\nbase.strided.dfill.ndarray( N:integer, alpha:number, x:Float64Array, \n  strideX:integer, offsetX:integer )\n    Fills a double-precision floating-point strided array with a specified\n    scalar value using alternative indexing semantics.\n","base.strided.dfloor":"\nbase.strided.dfloor( N:integer, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward negative infinity and assigns the results to elements in a double-\n    precision floating-point strided array `y`.\n","base.strided.dfloor.ndarray":"\nbase.strided.dfloor.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward negative infinity and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.dinv":"\nbase.strided.dinv( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n  strideY:integer )\n    Computes the multiplicative inverse for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y`.\n","base.strided.dinv.ndarray":"\nbase.strided.dinv.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Computes the multiplicative inverse for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.dmap":"\nbase.strided.dmap( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n  strideY:integer, fcn:Function )\n    Applies a unary function to a double-precision floating-point strided input\n    array and assigns results to a double-precision floating-point strided\n    output array.\n","base.strided.dmap.ndarray":"\nbase.strided.dmap.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer, \n  fcn:Function )\n    Applies a unary function to a double-precision floating-point strided input\n    array and assigns results to a double-precision floating-point strided\n    output array using alternative indexing semantics.\n","base.strided.dmap2":"\nbase.strided.dmap2( N:integer, x:Float64Array, sx:integer, y:Float64Array, \n  sy:integer, z:Float64Array, sz:integer, fcn:Function )\n    Applies a binary function to double-precision floating-point strided input\n    arrays and assigns results to a double-precision floating-point strided\n    output array.\n","base.strided.dmap2.ndarray":"\nbase.strided.dmap2.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, \n  y:Float64Array, sy:integer, oy:integer, z:Float64Array, sz:integer, \n  oz:integer, fcn:Function )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array using alternative indexing semantics.\n","base.strided.dmax":"\nbase.strided.dmax( N:integer, x:Float64Array, strideX:integer )\n    Computes the maximum value of a double-precision floating-point strided\n    array.\n","base.strided.dmax.ndarray":"\nbase.strided.dmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum value of a double-precision floating-point strided\n    array using alternative indexing semantics.\n","base.strided.dmaxabs":"\nbase.strided.dmaxabs( N:integer, x:Float64Array, strideX:integer )\n    Computes the maximum absolute value of a double-precision floating-point\n    strided array.\n","base.strided.dmaxabs.ndarray":"\nbase.strided.dmaxabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum absolute value of a double-precision floating-point\n    strided array using alternative indexing semantics.\n","base.strided.dmaxabssorted":"\nbase.strided.dmaxabssorted( N:integer, x:Float64Array, strideX:integer )\n    Computes the maximum absolute value of a sorted double-precision floating-\n    point strided array.\n","base.strided.dmaxabssorted.ndarray":"\nbase.strided.dmaxabssorted.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum absolute value of a sorted double-precision floating-\n    point strided array using alternative indexing semantics.\n","base.strided.dmaxsorted":"\nbase.strided.dmaxsorted( N:integer, x:Float64Array, strideX:integer )\n    Computes the maximum value of a sorted double-precision floating-point\n    strided array.\n","base.strided.dmaxsorted.ndarray":"\nbase.strided.dmaxsorted.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n","base.strided.dmean":"\nbase.strided.dmean( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array.\n","base.strided.dmean.ndarray":"\nbase.strided.dmean.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using alternative indexing semantics.\n","base.strided.dmeankbn":"\nbase.strided.dmeankbn( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm.\n","base.strided.dmeankbn.ndarray":"\nbase.strided.dmeankbn.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n","base.strided.dmeankbn2":"\nbase.strided.dmeankbn2( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.dmeankbn2.ndarray":"\nbase.strided.dmeankbn2.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n","base.strided.dmeanli":"\nbase.strided.dmeanli( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm.\n","base.strided.dmeanli.ndarray":"\nbase.strided.dmeanli.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n","base.strided.dmeanlipw":"\nbase.strided.dmeanlipw( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm with pairwise summation.\n","base.strided.dmeanlipw.ndarray":"\nbase.strided.dmeanlipw.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm with pairwise summation and\n    alternative indexing semantics.\n","base.strided.dmeanors":"\nbase.strided.dmeanors( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using ordinary recursive summation.\n","base.strided.dmeanors.ndarray":"\nbase.strided.dmeanors.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using ordinary recursive summation and alternative indexing semantics.\n","base.strided.dmeanpn":"\nbase.strided.dmeanpn( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a two-pass error correction algorithm.\n","base.strided.dmeanpn.ndarray":"\nbase.strided.dmeanpn.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a two-pass error correction algorithm and alternative indexing\n    semantics.\n","base.strided.dmeanpw":"\nbase.strided.dmeanpw( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using pairwise summation.\n","base.strided.dmeanpw.ndarray":"\nbase.strided.dmeanpw.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using pairwise summation and alternative indexing semantics.\n","base.strided.dmeanstdev":"\nbase.strided.dmeanstdev( N:integer, c:number, x:Float64Array, strideX:integer, \n  out:Float64Array, strideOut:integer )\n    Computes the mean and standard deviation of a double-precision floating-\n    point strided array.\n","base.strided.dmeanstdev.ndarray":"\nbase.strided.dmeanstdev.ndarray( N:integer, c:number, x:Float64Array, \n  strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n  offsetOut:integer )\n    Computes the mean and standard deviation of a double-precision floating-\n    point strided array using alternative indexing semantics.\n","base.strided.dmeanstdevpn":"\nbase.strided.dmeanstdevpn( N:integer, c:number, x:Float64Array, \n  strideX:integer, out:Float64Array, strideOut:integer )\n    Computes the mean and standard deviation of a double-precision floating-\n    point strided array using a two-pass algorithm.\n","base.strided.dmeanstdevpn.ndarray":"\nbase.strided.dmeanstdevpn.ndarray( N:integer, c:number, x:Float64Array, \n  strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n  offsetOut:integer )\n    Computes the mean and standard deviation of a double-precision floating-\n    point strided array using a two-pass algorithm and alternative indexing\n    semantics.\n","base.strided.dmeanvar":"\nbase.strided.dmeanvar( N:integer, c:number, x:Float64Array, strideX:integer, \n  out:Float64Array, strideOut:integer )\n    Computes the mean and variance of a double-precision floating-point strided\n    array.\n","base.strided.dmeanvar.ndarray":"\nbase.strided.dmeanvar.ndarray( N:integer, c:number, x:Float64Array, \n  strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n  offsetOut:integer )\n    Computes the mean and variance of a double-precision floating-point strided\n    array using alternative indexing semantics.\n","base.strided.dmeanvarpn":"\nbase.strided.dmeanvarpn( N:integer, c:number, x:Float64Array, strideX:integer, \n  out:Float64Array, strideOut:integer )\n    Computes the mean and variance of a double-precision floating-point strided\n    array using a two-pass algorithm.\n","base.strided.dmeanvarpn.ndarray":"\nbase.strided.dmeanvarpn.ndarray( N:integer, c:number, x:Float64Array, \n  strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n  offsetOut:integer )\n    Computes the mean and variance of a double-precision floating-point strided\n    array using a two-pass algorithm and alternative indexing semantics.\n","base.strided.dmeanwd":"\nbase.strided.dmeanwd( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using Welford's algorithm.\n","base.strided.dmeanwd.ndarray":"\nbase.strided.dmeanwd.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n","base.strided.dmediansorted":"\nbase.strided.dmediansorted( N:integer, x:Float64Array, strideX:integer )\n    Computes the median value of a sorted double-precision floating-point\n    strided array.\n","base.strided.dmediansorted.ndarray":"\nbase.strided.dmediansorted.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the median value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n","base.strided.dmidrange":"\nbase.strided.dmidrange( N:integer, x:Float64Array, strideX:integer )\n    Computes the mid-range of a double-precision floating-point strided array.\n","base.strided.dmidrange.ndarray":"\nbase.strided.dmidrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the mid-range of a double-precision floating-point strided array\n    using alternative indexing semantics.\n","base.strided.dmin":"\nbase.strided.dmin( N:integer, x:Float64Array, strideX:integer )\n    Computes the minimum value of a double-precision floating-point strided\n    array.\n","base.strided.dmin.ndarray":"\nbase.strided.dmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the minimum value of a double-precision floating-point strided\n    array using alternative indexing semantics.\n","base.strided.dminabs":"\nbase.strided.dminabs( N:integer, x:Float64Array, strideX:integer )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array.\n","base.strided.dminabs.ndarray":"\nbase.strided.dminabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array using alternative indexing semantics.\n","base.strided.dminsorted":"\nbase.strided.dminsorted( N:integer, x:Float64Array, strideX:integer )\n    Computes the minimum value of a sorted double-precision floating-point\n    strided array.\n","base.strided.dminsorted.ndarray":"\nbase.strided.dminsorted.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the minimum value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n","base.strided.dmskabs":"\nbase.strided.dmskabs( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Computes the absolute value for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskabs.ndarray":"\nbase.strided.dmskabs.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n  sy:integer, oy:integer )\n    Computes the absolute value for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n","base.strided.dmskabs2":"\nbase.strided.dmskabs2( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Computes the squared absolute value for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point\n    strided array `y`.\n","base.strided.dmskabs2.ndarray":"\nbase.strided.dmskabs2.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n  sy:integer, oy:integer )\n    Computes the squared absolute value for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point\n    strided array `y` using alternative indexing semantics.\n","base.strided.dmskcbrt":"\nbase.strided.dmskcbrt( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Computes the cube root for each element in a double-precision floating-point\n    strided array `x` according to a strided mask array and assigns the results\n    to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskcbrt.ndarray":"\nbase.strided.dmskcbrt.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n  sy:integer, oy:integer )\n    Computes the cube root for each element in a double-precision floating-point\n    strided array `x` according to a strided mask array and assigns the results\n    to elements in a double-precision floating-point strided array `y` using\n    alternative indexing semantics.\n","base.strided.dmskceil":"\nbase.strided.dmskceil( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward positive infinity according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskceil.ndarray":"\nbase.strided.dmskceil.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n  sy:integer, oy:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward positive infinity according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n","base.strided.dmskdeg2rad":"\nbase.strided.dmskdeg2rad( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Converts each element in a double-precision floating-point strided array `x`\n    from degrees to radians according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskdeg2rad.ndarray":"\nbase.strided.dmskdeg2rad.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n  sy:integer, oy:integer )\n    Converts each element in a double-precision floating-point strided array `x`\n    from degrees to radians according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n","base.strided.dmskfloor":"\nbase.strided.dmskfloor( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward negative infinity according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskfloor.ndarray":"\nbase.strided.dmskfloor.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n  sy:integer, oy:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward negative infinity according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n","base.strided.dmskinv":"\nbase.strided.dmskinv( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Computes the multiplicative inverse for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y`.\n","base.strided.dmskinv.ndarray":"\nbase.strided.dmskinv.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n  sy:integer, oy:integer )\n    Computes the multiplicative inverse for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y` using alternative indexing semantics.\n","base.strided.dmskmap":"\nbase.strided.dmskmap( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer, fcn:Function )\n    Applies a unary function to a double-precision floating-point strided input\n    array according to a strided mask array and assigns results to a double-\n    precision floating-point strided output array.\n","base.strided.dmskmap.ndarray":"\nbase.strided.dmskmap.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Uint8Array, sm:integer, om:integer, y:Float64Array, sy:integer, \n  oy:integer, fcn:Function )\n    Applies a unary function to a double-precision floating-point strided input\n    array according to a strided mask array and assigns results to a double-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n","base.strided.dmskmap2":"\nbase.strided.dmskmap2( N:integer, x:Float64Array, sx:integer, y:Float64Array, \n  sy:integer, m:Uint8Array, sm:integer, z:Float64Array, sz:integer, \n  fcn:Function )\n    Applies a binary function to double-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a double-\n    precision floating-point strided output array.\n","base.strided.dmskmap2.ndarray":"\nbase.strided.dmskmap2.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, y:Float64Array, sy:integer, oy:integer, m:Uint8Array, sm:integer, \n  om:integer, z:Float64Array, sz:integer, oz:integer, fcn:Function )\n    Applies a binary function to double-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a double-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n","base.strided.dmskmax":"\nbase.strided.dmskmax( N:integer, x:Float64Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask.\n","base.strided.dmskmax.ndarray":"\nbase.strided.dmskmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n","base.strided.dmskmin":"\nbase.strided.dmskmin( N:integer, x:Float64Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask.\n","base.strided.dmskmin.ndarray":"\nbase.strided.dmskmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n","base.strided.dmskramp":"\nbase.strided.dmskramp( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Evaluates the ramp function for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskramp.ndarray":"\nbase.strided.dmskramp.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n  sy:integer, oy:integer )\n    Evaluates the ramp function for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n","base.strided.dmskrange":"\nbase.strided.dmskrange( N:integer, x:Float64Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the range of a double-precision floating-point strided array\n    according to a mask.\n","base.strided.dmskrange.ndarray":"\nbase.strided.dmskrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the range of a double-precision floating-point strided array\n    according to a mask and using alternative indexing semantics.\n","base.strided.dmskrsqrt":"\nbase.strided.dmskrsqrt( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Computes the reciprocal square root for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y`.\n","base.strided.dmskrsqrt.ndarray":"\nbase.strided.dmskrsqrt.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n  sy:integer, oy:integer )\n    Computes the reciprocal square root for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y` using alternative indexing semantics.\n","base.strided.dmsksqrt":"\nbase.strided.dmsksqrt( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Computes the principal square root for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y`.\n","base.strided.dmsksqrt.ndarray":"\nbase.strided.dmsksqrt.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n  sy:integer, oy:integer )\n    Computes the principal square root for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y` using alternative indexing semantics.\n","base.strided.dmsktrunc":"\nbase.strided.dmsktrunc( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward zero according to a strided mask array and assigns the results to\n    elements in a double-precision floating-point strided array `y`.\n","base.strided.dmsktrunc.ndarray":"\nbase.strided.dmsktrunc.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n  sy:integer, oy:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward zero according to a strided mask array and assigns the results to\n    elements in a double-precision floating-point strided array `y` using\n    alternative indexing semantics.\n","base.strided.dnanasum":"\nbase.strided.dnanasum( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements, ignoring `NaN` values.\n","base.strided.dnanasum.ndarray":"\nbase.strided.dnanasum.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements, ignoring `NaN` values and using alternative\n    indexing semantics.\n","base.strided.dnanasumors":"\nbase.strided.dnanasumors( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements, ignoring `NaN` values and using ordinary\n    recursive summation.\n","base.strided.dnanasumors.ndarray":"\nbase.strided.dnanasumors.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements, ignoring `NaN` values and using ordinary\n    recursive summation alternative indexing semantics.\n","base.strided.dnanmax":"\nbase.strided.dnanmax( N:integer, x:Float64Array, strideX:integer )\n    Computes the maximum value of a double-precision floating-point strided\n    array, ignoring `NaN` values.\n","base.strided.dnanmax.ndarray":"\nbase.strided.dnanmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum value of a double-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanmaxabs":"\nbase.strided.dnanmaxabs( N:integer, x:Float64Array, strideX:integer )\n    Computes the maximum absolute value of a double-precision floating-point\n    strided array, ignoring `NaN` values.\n","base.strided.dnanmaxabs.ndarray":"\nbase.strided.dnanmaxabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum absolute value of a double-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n","base.strided.dnanmean":"\nbase.strided.dnanmean( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values.\n","base.strided.dnanmean.ndarray":"\nbase.strided.dnanmean.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanmeanors":"\nbase.strided.dnanmeanors( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.dnanmeanors.ndarray":"\nbase.strided.dnanmeanors.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation and\n    alternative indexing semantics.\n","base.strided.dnanmeanpn":"\nbase.strided.dnanmeanpn( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction\n    algorithm.\n","base.strided.dnanmeanpn.ndarray":"\nbase.strided.dnanmeanpn.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction algorithm\n    and alternative indexing semantics.\n","base.strided.dnanmeanpw":"\nbase.strided.dnanmeanpw( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using pairwise summation.\n","base.strided.dnanmeanpw.ndarray":"\nbase.strided.dnanmeanpw.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using pairwise summation and alternative\n    indexing semantics.\n","base.strided.dnanmeanwd":"\nbase.strided.dnanmeanwd( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, using Welford's algorithm and ignoring `NaN` values.\n","base.strided.dnanmeanwd.ndarray":"\nbase.strided.dnanmeanwd.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n","base.strided.dnanmin":"\nbase.strided.dnanmin( N:integer, x:Float64Array, strideX:integer )\n    Computes the minimum value of a double-precision floating-point strided\n    array, ignoring `NaN` values.\n","base.strided.dnanmin.ndarray":"\nbase.strided.dnanmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the minimum value of a double-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanminabs":"\nbase.strided.dnanminabs( N:integer, x:Float64Array, strideX:integer )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array, ignoring `NaN` values.\n","base.strided.dnanminabs.ndarray":"\nbase.strided.dnanminabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n","base.strided.dnanmskmax":"\nbase.strided.dnanmskmax( N:integer, x:Float64Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask, ignoring `NaN` values.\n","base.strided.dnanmskmax.ndarray":"\nbase.strided.dnanmskmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n","base.strided.dnanmskmin":"\nbase.strided.dnanmskmin( N:integer, x:Float64Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask, ignoring `NaN` values.\n","base.strided.dnanmskmin.ndarray":"\nbase.strided.dnanmskmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n","base.strided.dnanmskrange":"\nbase.strided.dnanmskrange( N:integer, x:Float64Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the range of a double-precision floating-point strided array\n    according to a mask, ignoring `NaN` values.\n","base.strided.dnanmskrange.ndarray":"\nbase.strided.dnanmskrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the range of a double-precision floating-point strided array\n    according to a mask, ignoring `NaN` values and using alternative indexing\n    semantics.\n","base.strided.dnannsum":"\nbase.strided.dnannsum( N:integer, x:Float64Array, strideX:integer, \n  out:Float64Array, strideOut:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values.\n","base.strided.dnannsum.ndarray":"\nbase.strided.dnannsum.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnannsumkbn":"\nbase.strided.dnannsumkbn( N:integer, x:Float64Array, strideX:integer, \n  out:Float64Array, strideOut:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n","base.strided.dnannsumkbn.ndarray":"\nbase.strided.dnannsumkbn.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n","base.strided.dnannsumkbn2":"\nbase.strided.dnannsumkbn2( N:integer, x:Float64Array, strideX:integer, \n  out:Float64Array, strideOut:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm.\n","base.strided.dnannsumkbn2.ndarray":"\nbase.strided.dnannsumkbn2.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n","base.strided.dnannsumors":"\nbase.strided.dnannsumors( N:integer, x:Float64Array, strideX:integer, \n  out:Float64Array, strideOut:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.dnannsumors.ndarray":"\nbase.strided.dnannsumors.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation and alternative\n    indexing semantics.\n","base.strided.dnannsumpw":"\nbase.strided.dnannsumpw( N:integer, x:Float64Array, strideX:integer, \n  out:Float64Array, strideOut:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation.\n","base.strided.dnannsumpw.ndarray":"\nbase.strided.dnannsumpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation and alternative indexing\n    semantics.\n","base.strided.dnanrange":"\nbase.strided.dnanrange( N:integer, x:Float64Array, strideX:integer )\n    Computes the range of a double-precision floating-point strided array,\n    ignoring `NaN` values.\n","base.strided.dnanrange.ndarray":"\nbase.strided.dnanrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the range of a double-precision floating-point strided array,\n    ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanstdev":"\nbase.strided.dnanstdev( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values.\n","base.strided.dnanstdev.ndarray":"\nbase.strided.dnanstdev.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanstdevch":"\nbase.strided.dnanstdevch( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.dnanstdevch.ndarray":"\nbase.strided.dnanstdevch.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n","base.strided.dnanstdevpn":"\nbase.strided.dnanstdevpn( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.dnanstdevpn.ndarray":"\nbase.strided.dnanstdevpn.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n","base.strided.dnanstdevtk":"\nbase.strided.dnanstdevtk( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.dnanstdevtk.ndarray":"\nbase.strided.dnanstdevtk.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n","base.strided.dnanstdevwd":"\nbase.strided.dnanstdevwd( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using Welford's algorithm.\n","base.strided.dnanstdevwd.ndarray":"\nbase.strided.dnanstdevwd.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n","base.strided.dnanstdevyc":"\nbase.strided.dnanstdevyc( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass algorithm proposed by\n    Youngs and Cramer.\n","base.strided.dnanstdevyc.ndarray":"\nbase.strided.dnanstdevyc.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass algorithm proposed by\n    Youngs and Cramer and alternative indexing semantics.\n","base.strided.dnansum":"\nbase.strided.dnansum( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values.\n","base.strided.dnansum.ndarray":"\nbase.strided.dnansum.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnansumkbn":"\nbase.strided.dnansumkbn( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n","base.strided.dnansumkbn.ndarray":"\nbase.strided.dnansumkbn.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n","base.strided.dnansumkbn2":"\nbase.strided.dnansumkbn2( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm.\n","base.strided.dnansumkbn2.ndarray":"\nbase.strided.dnansumkbn2.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n","base.strided.dnansumors":"\nbase.strided.dnansumors( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.dnansumors.ndarray":"\nbase.strided.dnansumors.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation and alternative\n    indexing semantics.\n","base.strided.dnansumpw":"\nbase.strided.dnansumpw( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation.\n","base.strided.dnansumpw.ndarray":"\nbase.strided.dnansumpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation and alternative indexing\n    semantics.\n","base.strided.dnanvariance":"\nbase.strided.dnanvariance( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values.\n","base.strided.dnanvariance.ndarray":"\nbase.strided.dnanvariance.ndarray( N:integer, correction:number, \n  x:Float64Array, stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanvariancech":"\nbase.strided.dnanvariancech( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.dnanvariancech.ndarray":"\nbase.strided.dnanvariancech.ndarray( N:integer, correction:number, \n  x:Float64Array, stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n","base.strided.dnanvariancepn":"\nbase.strided.dnanvariancepn( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.dnanvariancepn.ndarray":"\nbase.strided.dnanvariancepn.ndarray( N:integer, correction:number, \n  x:Float64Array, stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n","base.strided.dnanvariancetk":"\nbase.strided.dnanvariancetk( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.dnanvariancetk.ndarray":"\nbase.strided.dnanvariancetk.ndarray( N:integer, correction:number, \n  x:Float64Array, stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n","base.strided.dnanvariancewd":"\nbase.strided.dnanvariancewd( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using Welford's algorithm.\n","base.strided.dnanvariancewd.ndarray":"\nbase.strided.dnanvariancewd.ndarray( N:integer, correction:number, \n  x:Float64Array, stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using Welford's algorithm and alternative indexing\n    semantics.\n","base.strided.dnanvarianceyc":"\nbase.strided.dnanvarianceyc( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n    Cramer.\n","base.strided.dnanvarianceyc.ndarray":"\nbase.strided.dnanvarianceyc.ndarray( N:integer, correction:number, \n  x:Float64Array, stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n    Cramer and alternative indexing semantics.\n","base.strided.dnrm2":"\nbase.strided.dnrm2( N:integer, x:Float64Array, stride:integer )\n    Computes the L2-norm of a double-precision floating-point vector.\n","base.strided.dnrm2.ndarray":"\nbase.strided.dnrm2.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the L2-norm of a double-precision floating-point vector using\n    alternative indexing semantics.\n","base.strided.dramp":"\nbase.strided.dramp( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n  strideY:integer )\n    Evaluates the ramp function for each element in a double-precision floating-\n    point strided array `x` and assigns the results to elements in a double-\n    precision floating-point strided array `y`.\n","base.strided.dramp.ndarray":"\nbase.strided.dramp.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Evaluates the ramp function for each element in a double-precision floating-\n    point strided array `x` and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.drange":"\nbase.strided.drange( N:integer, x:Float64Array, strideX:integer )\n    Computes the range of a double-precision floating-point strided array.\n","base.strided.drange.ndarray":"\nbase.strided.drange.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the range of a double-precision floating-point strided array using\n    alternative indexing semantics.\n","base.strided.drev":"\nbase.strided.drev( N:integer, x:Float64Array, strideX:integer )\n    Reverses a double-precision floating-point strided array in-place.\n","base.strided.drev.ndarray":"\nbase.strided.drev.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Reverses a double-precision floating-point strided array in-place using\n    alternative indexing semantics.\n","base.strided.drsqrt":"\nbase.strided.drsqrt( N:integer, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Computes the reciprocal square root for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y`.\n","base.strided.drsqrt.ndarray":"\nbase.strided.drsqrt.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Computes the reciprocal square root for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.dsapxsum":"\nbase.strided.dsapxsum( N:integer, alpha:number, x:Float32Array, \n  strideX:integer )\n    Adds a scalar constant to each single-precision floating-point strided array\n    element, and computes the sum using extended accumulation and returning\n    an extended precision result.\n","base.strided.dsapxsum.ndarray":"\nbase.strided.dsapxsum.ndarray( N:integer, alpha:number, x:Float32Array, \n  strideX:integer, offsetX:integer )\n    Adds a scalar constant to each single-precision floating-point strided array\n    element, and computes the sum using pairwise summation with extended\n    accumulation and alternative indexing semantics and returning an extended\n    precision result.\n","base.strided.dsapxsumpw":"\nbase.strided.dsapxsumpw( N:integer, alpha:number, x:Float32Array, \n  strideX:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element, and computes the sum using pairwise summation with extended\n    accumulation and returning an extended precision result.\n","base.strided.dsapxsumpw.ndarray":"\nbase.strided.dsapxsumpw.ndarray( N:integer, alpha:number, x:Float32Array, \n  strideX:integer, offsetX:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element, and computes the sum using pairwise summation with extended\n    accumulation and alternative indexing semantics and returning an extended\n    precision result.\n","base.strided.dscal":"\nbase.strided.dscal( N:integer, alpha:number, x:Float64Array, stride:integer )\n    Multiplies a double-precision floating-point vector `x` by a constant\n    `alpha`.\n","base.strided.dscal.ndarray":"\nbase.strided.dscal.ndarray( N:integer, alpha:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Multiplies a double-precision floating-point vector `x` by a constant\n    `alpha` using alternative indexing semantics.\n","base.strided.dsdot":"\nbase.strided.dsdot( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer )\n    Computes the dot product of two single-precision floating-point vectors with\n    extended accumulation and result.\n","base.strided.dsdot.ndarray":"\nbase.strided.dsdot.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the dot product of two single-precision floating-point vectors\n    using alternative indexing semantics and with extended accumulation and\n    result.\n","base.strided.dsem":"\nbase.strided.dsem( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array.\n","base.strided.dsem.ndarray":"\nbase.strided.dsem.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using alternative indexing semantics.\n","base.strided.dsemch":"\nbase.strided.dsemch( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass trial mean algorithm.\n","base.strided.dsemch.ndarray":"\nbase.strided.dsemch.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass trial mean algorithm and alternative\n    indexing semantics.\n","base.strided.dsempn":"\nbase.strided.dsempn( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a two-pass algorithm.\n","base.strided.dsempn.ndarray":"\nbase.strided.dsempn.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a two-pass algorithm and alternative indexing\n    semantics.\n","base.strided.dsemtk":"\nbase.strided.dsemtk( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass textbook algorithm.\n","base.strided.dsemtk.ndarray":"\nbase.strided.dsemtk.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass textbook algorithm and alternative\n    indexing semantics.\n","base.strided.dsemwd":"\nbase.strided.dsemwd( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using Welford's algorithm.\n","base.strided.dsemwd.ndarray":"\nbase.strided.dsemwd.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using Welford's algorithm and alternative indexing\n    semantics.\n","base.strided.dsemyc":"\nbase.strided.dsemyc( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass algorithm proposed by Youngs and\n    Cramer.\n","base.strided.dsemyc.ndarray":"\nbase.strided.dsemyc.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass algorithm proposed by Youngs and Cramer\n    and alternative indexing semantics.\n","base.strided.dsmean":"\nbase.strided.dsmean( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using extended accumulation and returning an extended precision\n    result.\n","base.strided.dsmean.ndarray":"\nbase.strided.dsmean.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using extended accumulation and alternative indexing semantics and\n    returning an extended precision result.\n","base.strided.dsmeanors":"\nbase.strided.dsmeanors( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation with extended accumulation and\n    returning an extended precision result.\n","base.strided.dsmeanors.ndarray":"\nbase.strided.dsmeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation with extended accumulation and\n    alternative indexing semantics and returning an extended precision result.\n","base.strided.dsmeanpn":"\nbase.strided.dsmeanpn( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a two-pass error correction algorithm with extended accumulation\n    and returning an extended precision result.\n","base.strided.dsmeanpn.ndarray":"\nbase.strided.dsmeanpn.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a two-pass error correction algorithm with extended accumulation\n    and alternative indexing semantics and returning an extended precision\n    result.\n","base.strided.dsmeanpw":"\nbase.strided.dsmeanpw( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using pairwise summation with extended accumulation and returning an\n    extended precision result.\n","base.strided.dsmeanpw.ndarray":"\nbase.strided.dsmeanpw.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using pairwise summation with extended accumulation and alternative\n    indexing semantics and returning an extended precision result.\n","base.strided.dsmeanwd":"\nbase.strided.dsmeanwd( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using Welford's algorithm with extended accumulation and returning an\n    extended precision result.\n","base.strided.dsmeanwd.ndarray":"\nbase.strided.dsmeanwd.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using Welford's algorithm with extended accumulation and alternative\n    indexing semantics and returning an extended precision result.\n","base.strided.dsnanmean":"\nbase.strided.dsnanmean( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values, using extended accumulation, and returning an\n    extended precision result.\n","base.strided.dsnanmean.ndarray":"\nbase.strided.dsnanmean.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using extended accumulation and alternative\n    indexing semantics.\n","base.strided.dsnanmeanors":"\nbase.strided.dsnanmeanors( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values, using ordinary recursive summation with\n    extended accumulation, and returning an extended precision result.\n","base.strided.dsnanmeanors.ndarray":"\nbase.strided.dsnanmeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation with\n    extended accumulation and alternative indexing semantics.\n","base.strided.dsnanmeanpn":"\nbase.strided.dsnanmeanpn( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values, using a two-pass error correction algorithm\n    with extended accumulation, and returning an extended precision result.\n","base.strided.dsnanmeanpn.ndarray":"\nbase.strided.dsnanmeanpn.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction algorithm\n    with extended accumulation and alternative indexing semantics.\n","base.strided.dsnanmeanwd":"\nbase.strided.dsnanmeanwd( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values, using Welford's algorithm with extended\n    accumulation, and returning an extended precision result.\n","base.strided.dsnanmeanwd.ndarray":"\nbase.strided.dsnanmeanwd.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm with extended\n    accumulation and alternative indexing semantics.\n","base.strided.dsnannsumors":"\nbase.strided.dsnannsumors( N:integer, x:Float32Array, strideX:integer, \n  out:Float64Array, strideOut:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using ordinary recursive summation with extended\n    accumulation, and returning an extended precision result.\n","base.strided.dsnannsumors.ndarray":"\nbase.strided.dsnannsumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using ordinary recursive summation with extended\n    accumulation and alternative indexing semantics, and returning an extended\n    precision result.\n","base.strided.dsnansum":"\nbase.strided.dsnansum( N:integer, x:Float32Array, strideX:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using extended accumulation, and returning an\n    extended precision result.\n","base.strided.dsnansum.ndarray":"\nbase.strided.dsnansum.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using extended accumulation and alternative\n    indexing semantics, and returning an extended precision result.\n","base.strided.dsnansumors":"\nbase.strided.dsnansumors( N:integer, x:Float32Array, strideX:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using ordinary recursive summation with extended\n    accumulation, and returning an extended precision result.\n","base.strided.dsnansumors.ndarray":"\nbase.strided.dsnansumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation with extended\n    accumulation and alternative indexing semantics, and returning an extended\n    precision result.\n","base.strided.dsnansumpw":"\nbase.strided.dsnansumpw( N:integer, x:Float32Array, strideX:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using pairwise summation with extended accumulation,\n    and returning an extended precision result.\n","base.strided.dsnansumpw.ndarray":"\nbase.strided.dsnansumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using pairwise summation with extended accumulation\n    and alternative indexing semantics, and returning an extended precision\n    result.\n","base.strided.dsort2hp":"\nbase.strided.dsort2hp( N:integer, order:number, x:Float64Array, \n  strideX:integer, y:Float64Array, strideY:integer )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using heapsort.\n","base.strided.dsort2hp.ndarray":"\nbase.strided.dsort2hp.ndarray( N:integer, order:number, x:Float64Array, \n  strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n  offsetY:integer )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using heapsort and alternative\n    indexing semantics.\n","base.strided.dsort2ins":"\nbase.strided.dsort2ins( N:integer, order:number, x:Float64Array, \n  strideX:integer, y:Float64Array, strideY:integer )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using insertion sort.\n","base.strided.dsort2ins.ndarray":"\nbase.strided.dsort2ins.ndarray( N:integer, order:number, x:Float64Array, \n  strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n  offsetY:integer )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using insertion sort and\n    alternative indexing semantics.\n","base.strided.dsort2sh":"\nbase.strided.dsort2sh( N:integer, order:number, x:Float64Array, \n  strideX:integer, y:Float64Array, strideY:integer )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using Shellsort.\n","base.strided.dsort2sh.ndarray":"\nbase.strided.dsort2sh.ndarray( N:integer, order:number, x:Float64Array, \n  strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n  offsetY:integer )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using Shellsort and alternative\n    indexing semantics.\n","base.strided.dsorthp":"\nbase.strided.dsorthp( N:integer, order:number, x:Float64Array, stride:integer )\n    Sorts a double-precision floating-point strided array using heapsort.\n","base.strided.dsorthp.ndarray":"\nbase.strided.dsorthp.ndarray( N:integer, order:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Sorts a double-precision floating-point strided array using heapsort and\n    alternative indexing semantics.\n","base.strided.dsortins":"\nbase.strided.dsortins( N:integer, order:number, x:Float64Array, stride:integer )\n    Sorts a double-precision floating-point strided array using insertion sort.\n","base.strided.dsortins.ndarray":"\nbase.strided.dsortins.ndarray( N:integer, order:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Sorts a double-precision floating-point strided array using insertion sort\n    and alternative indexing semantics.\n","base.strided.dsortsh":"\nbase.strided.dsortsh( N:integer, order:number, x:Float64Array, stride:integer )\n    Sorts a double-precision floating-point strided array using Shellsort.\n","base.strided.dsortsh.ndarray":"\nbase.strided.dsortsh.ndarray( N:integer, order:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Sorts a double-precision floating-point strided array using Shellsort and\n    alternative indexing semantics.\n","base.strided.dsqrt":"\nbase.strided.dsqrt( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n  strideY:integer )\n    Computes the principal square root for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y`.\n","base.strided.dsqrt.ndarray":"\nbase.strided.dsqrt.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Computes the principal square root for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.dssum":"\nbase.strided.dssum( N:integer, x:Float32Array, strideX:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using extended accumulation and returning an extended precision result.\n","base.strided.dssum.ndarray":"\nbase.strided.dssum.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using extended accumulation and alternative indexing semantics and returning\n    an extended precision result.\n","base.strided.dssumors":"\nbase.strided.dssumors( N:integer, x:Float32Array, strideX:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using ordinary recursive summation with extended accumulation and returning\n    an extended precision result.\n","base.strided.dssumors.ndarray":"\nbase.strided.dssumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using ordinary recursive summation with extended accumulation and\n    alternative indexing semantics and returning an extended precision result.\n","base.strided.dssumpw":"\nbase.strided.dssumpw( N:integer, x:Float32Array, strideX:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation with extended accumulation and returning an\n    extended precision result.\n","base.strided.dssumpw.ndarray":"\nbase.strided.dssumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation with extended accumulation and alternative indexing\n    semantics and returning an extended precision result.\n","base.strided.dstdev":"\nbase.strided.dstdev( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array.\n","base.strided.dstdev.ndarray":"\nbase.strided.dstdev.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using alternative indexing semantics.\n","base.strided.dstdevch":"\nbase.strided.dstdevch( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm.\n","base.strided.dstdevch.ndarray":"\nbase.strided.dstdevch.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n","base.strided.dstdevpn":"\nbase.strided.dstdevpn( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a two-pass algorithm.\n","base.strided.dstdevpn.ndarray":"\nbase.strided.dstdevpn.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a two-pass algorithm and alternative indexing semantics.\n","base.strided.dstdevtk":"\nbase.strided.dstdevtk( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass textbook algorithm.\n","base.strided.dstdevtk.ndarray":"\nbase.strided.dstdevtk.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass textbook algorithm and alternative indexing\n    semantics.\n","base.strided.dstdevwd":"\nbase.strided.dstdevwd( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using Welford's algorithm.\n","base.strided.dstdevwd.ndarray":"\nbase.strided.dstdevwd.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n","base.strided.dstdevyc":"\nbase.strided.dstdevyc( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.dstdevyc.ndarray":"\nbase.strided.dstdevyc.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer and\n    alternative indexing semantics.\n","base.strided.dsum":"\nbase.strided.dsum( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of double-precision floating-point strided array elements.\n","base.strided.dsum.ndarray":"\nbase.strided.dsum.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using alternative indexing semantics.\n","base.strided.dsumkbn":"\nbase.strided.dsumkbn( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm.\n","base.strided.dsumkbn.ndarray":"\nbase.strided.dsumkbn.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n","base.strided.dsumkbn2":"\nbase.strided.dsumkbn2( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.dsumkbn2.ndarray":"\nbase.strided.dsumkbn2.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n","base.strided.dsumors":"\nbase.strided.dsumors( N:integer, x:Float64Array, stride:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using ordinary recursive summation.\n","base.strided.dsumors.ndarray":"\nbase.strided.dsumors.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using ordinary recursive summation and alternative indexing semantics.\n","base.strided.dsumpw":"\nbase.strided.dsumpw( N:integer, x:Float64Array, stride:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using pairwise summation.\n","base.strided.dsumpw.ndarray":"\nbase.strided.dsumpw.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using pairwise summation and alternative indexing semantics.\n","base.strided.dsvariance":"\nbase.strided.dsvariance( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using extended accumulation and returning an extended precision result.\n","base.strided.dsvariance.ndarray":"\nbase.strided.dsvariance.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using extended accumulation and alternative indexing semantics and\n    returning an extended precision result.\n","base.strided.dsvariancepn":"\nbase.strided.dsvariancepn( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using a two-pass algorithm with extended accumulation and returning an\n    extended precision result.\n","base.strided.dsvariancepn.ndarray":"\nbase.strided.dsvariancepn.ndarray( N:integer, correction:number, \n  x:Float32Array, stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using a two-pass algorithm with extended accumulation and alternative\n    indexing semantics and returning an extended precision result.\n","base.strided.dswap":"\nbase.strided.dswap( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n  strideY:integer )\n    Interchanges two double-precision floating-point vectors.\n","base.strided.dswap.ndarray":"\nbase.strided.dswap.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Interchanges two double-precision floating-point vectors using alternative\n    indexing semantics.\n","base.strided.dtrunc":"\nbase.strided.dtrunc( N:integer, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward zero and assigns the results to elements in a double-precision\n    floating-point strided array `y`.\n","base.strided.dtrunc.ndarray":"\nbase.strided.dtrunc.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward zero and assigns the results to elements in a double-precision\n    floating-point strided array `y` using alternative indexing semantics.\n","base.strided.dtypeEnum2Str":"\nbase.strided.dtypeEnum2Str( dtype:integer )\n    Returns the data type string associated with a strided array data type\n    enumeration constant.\n","base.strided.dtypeResolveEnum":"\nbase.strided.dtypeResolveEnum( dtype:any )\n    Returns the enumeration constant associated with a supported strided array\n    data type value.\n","base.strided.dtypeResolveStr":"\nbase.strided.dtypeResolveStr( dtype:any )\n    Returns the data type string associated with a supported data type value.\n","base.strided.dtypeStr2Enum":"\nbase.strided.dtypeStr2Enum( dtype:string )\n    Returns the enumeration constant associated with a strided array data type\n    string.\n","base.strided.dvariance":"\nbase.strided.dvariance( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array.\n","base.strided.dvariance.ndarray":"\nbase.strided.dvariance.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using alternative indexing semantics.\n","base.strided.dvariancech":"\nbase.strided.dvariancech( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass trial mean algorithm.\n","base.strided.dvariancech.ndarray":"\nbase.strided.dvariancech.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.dvariancepn":"\nbase.strided.dvariancepn( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using a two-pass algorithm.\n","base.strided.dvariancepn.ndarray":"\nbase.strided.dvariancepn.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using a two-pass algorithm and alternative indexing semantics.\n","base.strided.dvariancetk":"\nbase.strided.dvariancetk( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass textbook algorithm.\n","base.strided.dvariancetk.ndarray":"\nbase.strided.dvariancetk.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.dvariancewd":"\nbase.strided.dvariancewd( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using Welford's algorithm.\n","base.strided.dvariancewd.ndarray":"\nbase.strided.dvariancewd.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using Welford's algorithm and alternative indexing semantics.\n","base.strided.dvarianceyc":"\nbase.strided.dvarianceyc( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.dvarianceyc.ndarray":"\nbase.strided.dvarianceyc.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass algorithm proposed by Youngs and Cramer and alternative\n    indexing semantics.\n","base.strided.dvarm":"\nbase.strided.dvarm( N:integer, mean:number, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean.\n","base.strided.dvarm.ndarray":"\nbase.strided.dvarm.ndarray( N:integer, mean:number, correction:number, \n  x:Float64Array, stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using alternative indexing semantics.\n","base.strided.dvarmpn":"\nbase.strided.dvarmpn( N:integer, mean:number, correction:number, \n  x:Float64Array, stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using Neely's correction algorithm.\n","base.strided.dvarmpn.ndarray":"\nbase.strided.dvarmpn.ndarray( N:integer, mean:number, correction:number, \n  x:Float64Array, stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using Neely's correction algorithm and alternative\n    indexing semantics.\n","base.strided.dvarmtk":"\nbase.strided.dvarmtk( N:integer, mean:number, correction:number, \n  x:Float64Array, stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using a one-pass textbook algorithm.\n","base.strided.dvarmtk.ndarray":"\nbase.strided.dvarmtk.ndarray( N:integer, mean:number, correction:number, \n  x:Float64Array, stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n","base.strided.gapx":"\nbase.strided.gapx( N:integer, alpha:number, x:Array|TypedArray, stride:integer )\n    Adds a constant to each element in a strided array.\n","base.strided.gapx.ndarray":"\nbase.strided.gapx.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Adds a constant to each element in a strided array using alternative\n    indexing semantics.\n","base.strided.gapxsum":"\nbase.strided.gapxsum( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer )\n    Adds a constant to each strided array element and computes the sum.\n","base.strided.gapxsum.ndarray":"\nbase.strided.gapxsum.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Adds a constant to each strided array element and computes the sum using\n    alternative indexing semantics.\n","base.strided.gapxsumkbn":"\nbase.strided.gapxsumkbn( N:integer, alpha:number, x:Array|TypedArray, \n  strideX:integer )\n    Adds a scalar constant to each strided array element and computes the sum\n    using an improved Kahan–Babuška algorithm.\n","base.strided.gapxsumkbn.ndarray":"\nbase.strided.gapxsumkbn.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n  strideX:integer, offsetX:integer )\n    Adds a scalar constant to each strided array element and computes the sum\n    using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n","base.strided.gapxsumkbn2":"\nbase.strided.gapxsumkbn2( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer )\n    Adds a constant to each strided array element and computes the sum using a\n    second-order iterative Kahan–Babuška algorithm.\n","base.strided.gapxsumkbn2.ndarray":"\nbase.strided.gapxsumkbn2.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Adds a constant to each strided array element and computes the sum using a\n    second-order iterative Kahan–Babuška algorithm and alternative indexing\n    semantics.\n","base.strided.gapxsumors":"\nbase.strided.gapxsumors( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer )\n    Adds a constant to each strided array element and computes the sum using\n    ordinary recursive summation.\n","base.strided.gapxsumors.ndarray":"\nbase.strided.gapxsumors.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Adds a constant to each strided array element and computes the sum using\n    ordinary recursive summation and alternative indexing semantics.\n","base.strided.gapxsumpw":"\nbase.strided.gapxsumpw( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer )\n    Adds a constant to each strided array element and computes the sum using\n    pairwise summation.\n","base.strided.gapxsumpw.ndarray":"\nbase.strided.gapxsumpw.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Adds a constant to each strided array element and computes the sum using\n    pairwise summation and alternative indexing semantics.\n","base.strided.gasum":"\nbase.strided.gasum( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of the absolute values.\n","base.strided.gasum.ndarray":"\nbase.strided.gasum.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the sum of absolute values using alternative indexing semantics.\n","base.strided.gasumpw":"\nbase.strided.gasumpw( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of absolute values (L1 norm) of strided array elements\n    using pairwise summation.\n","base.strided.gasumpw.ndarray":"\nbase.strided.gasumpw.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the sum of absolute values (L1 norm) of strided array elements\n    using pairwise summation and alternative indexing semantics.\n","base.strided.gaxpy":"\nbase.strided.gaxpy( N:integer, alpha:number, x:Array|TypedArray, \n  strideX:integer, y:Array|TypedArray, strideY:integer )\n    Multiplies `x` by a constant `alpha` and adds the result to `y`.\n","base.strided.gaxpy.ndarray":"\nbase.strided.gaxpy.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n  strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n  offsetY:integer )\n    Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n    alternative indexing semantics.\n","base.strided.gcopy":"\nbase.strided.gcopy( N:integer, x:ArrayLikeObject, strideX:integer, \n  y:ArrayLikeObject, strideY:integer )\n    Copies values from `x` into `y`.\n","base.strided.gcopy.ndarray":"\nbase.strided.gcopy.ndarray( N:integer, x:ArrayLikeObject, strideX:integer, \n  offsetX:integer, y:ArrayLikeObject, strideY:integer, offsetY:integer )\n    Copies values from `x` into `y` using alternative indexing semantics.\n","base.strided.gcusum":"\nbase.strided.gcusum( N:integer, sum:number, x:Array|TypedArray, \n  strideX:integer, y:Array|TypedArray, strideY:integer )\n    Computes the cumulative sum of strided array elements.\n","base.strided.gcusum.ndarray":"\nbase.strided.gcusum.ndarray( N:integer, sum:number, x:Array|TypedArray, \n  strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of strided array elements using alternative\n    indexing semantics.\n","base.strided.gcusumkbn":"\nbase.strided.gcusumkbn( N:integer, sum:number, x:Array|TypedArray, \n  strideX:integer, y:Array|TypedArray, strideY:integer )\n    Computes the cumulative sum of strided array elements using an improved\n    Kahan–Babuška algorithm.\n","base.strided.gcusumkbn.ndarray":"\nbase.strided.gcusumkbn.ndarray( N:integer, sum:number, x:Array|TypedArray, \n  strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of strided array elements using an improved\n    Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gcusumkbn2":"\nbase.strided.gcusumkbn2( N:integer, sum:number, x:Array|TypedArray, \n  strideX:integer, y:Array|TypedArray, strideY:integer )\n    Computes the cumulative sum of strided array elements using a second-order\n    iterative Kahan–Babuška algorithm.\n","base.strided.gcusumkbn2.ndarray":"\nbase.strided.gcusumkbn2.ndarray( N:integer, sum:number, x:Array|TypedArray, \n  strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of strided array elements using a second-order\n    iterative Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gcusumors":"\nbase.strided.gcusumors( N:integer, sum:number, x:Array|TypedArray, \n  strideX:integer, y:Array|TypedArray, strideY:integer )\n    Computes the cumulative sum of strided array elements using ordinary\n    recursive summation.\n","base.strided.gcusumors.ndarray":"\nbase.strided.gcusumors.ndarray( N:integer, sum:number, x:Array|TypedArray, \n  strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of strided array elements using ordinary\n    recursive summation and alternative indexing semantics.\n","base.strided.gcusumpw":"\nbase.strided.gcusumpw( N:integer, sum:number, x:Array|TypedArray, \n  strideX:integer, y:Array|TypedArray, strideY:integer )\n    Computes the cumulative sum of strided array elements using pairwise\n    summation.\n","base.strided.gcusumpw.ndarray":"\nbase.strided.gcusumpw.ndarray( N:integer, sum:number, x:Array|TypedArray, \n  strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of strided array elements using pairwise\n    summation and alternative indexing semantics.\n","base.strided.gdot":"\nbase.strided.gdot( N:integer, x:Array|TypedArray, strideX:integer, \n  y:Array|TypedArray, strideY:integer )\n    Computes the dot product of two vectors.\n","base.strided.gdot.ndarray":"\nbase.strided.gdot.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n  offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n    Computes the dot product of two vectors using alternative indexing\n    semantics.\n","base.strided.gfill":"\nbase.strided.gfill( N:integer, alpha:any, x:ArrayLikeObject, stride:integer )\n    Fills a strided array with a specified scalar value.\n","base.strided.gfill.ndarray":"\nbase.strided.gfill.ndarray( N:integer, alpha:any, x:ArrayLikeObject, \n  stride:integer, offset:integer )\n    Fills a strided array with a specified scalar value using alternative\n    indexing semantics.\n","base.strided.gfillBy":"\nbase.strided.gfillBy( N:integer, x:ArrayLikeObject, stride:integer, \n  clbk:Function[, thisArg:any] )\n    Fills a strided array according to a provided callback function.\n","base.strided.gfillBy.ndarray":"\nbase.strided.gfillBy.ndarray( N:integer, x:ArrayLikeObject, stride:integer, \n  offset:integer, clbk:Function[, thisArg:any] )\n    Fills a strided array according to a provided callback function and using\n    alternative indexing semantics.\n","base.strided.gnannsumkbn":"\nbase.strided.gnannsumkbn( N:integer, x:Array|TypedArray, strideX:integer, \n  out:Array|TypedArray, strideOut:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    an improved Kahan–Babuška algorithm.\n","base.strided.gnannsumkbn.ndarray":"\nbase.strided.gnannsumkbn.ndarray( N:integer, x:Array|TypedArray, \n  strideX:integer, offsetX:integer, out:Array|TypedArray, strideOut:integer, \n  offsetOut:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    an improved Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gnansum":"\nbase.strided.gnansum( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values.\n","base.strided.gnansum.ndarray":"\nbase.strided.gnansum.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    alternative indexing semantics.\n","base.strided.gnansumkbn":"\nbase.strided.gnansumkbn( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    an improved Kahan–Babuška algorithm.\n","base.strided.gnansumkbn.ndarray":"\nbase.strided.gnansumkbn.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    an improved Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gnansumkbn2":"\nbase.strided.gnansumkbn2( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    a second-order iterative Kahan–Babuška algorithm.\n","base.strided.gnansumkbn2.ndarray":"\nbase.strided.gnansumkbn2.ndarray( N:integer, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    a second-order iterative Kahan–Babuška algorithm and alternative indexing\n    semantics.\n","base.strided.gnansumors":"\nbase.strided.gnansumors( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    ordinary recursive summation.\n","base.strided.gnansumors.ndarray":"\nbase.strided.gnansumors.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    ordinary recursive summation and alternative indexing semantics.\n","base.strided.gnansumpw":"\nbase.strided.gnansumpw( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values and\n    pairwise summation.\n","base.strided.gnansumpw.ndarray":"\nbase.strided.gnansumpw.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    pairwise summation and alternative indexing semantics.\n","base.strided.gnrm2":"\nbase.strided.gnrm2( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the L2-norm of a vector.\n","base.strided.gnrm2.ndarray":"\nbase.strided.gnrm2.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the L2-norm of a vector using alternative indexing semantics.\n","base.strided.grev":"\nbase.strided.grev( N:integer, x:ArrayLikeObject, stride:integer )\n    Reverses a strided array in-place.\n","base.strided.grev.ndarray":"\nbase.strided.grev.ndarray( N:integer, x:ArrayLikeObject, stride:integer, \n  offset:integer )\n    Reverses a strided array in-place using alternative indexing semantics.\n","base.strided.gscal":"\nbase.strided.gscal( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer )\n    Multiplies a vector `x` by a constant `alpha`.\n","base.strided.gscal.ndarray":"\nbase.strided.gscal.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Multiplies `x` by a constant `alpha` using alternative indexing semantics.\n","base.strided.gsort2hp":"\nbase.strided.gsort2hp( N:integer, order:number, x:Array|TypedArray, \n  strideX:integer, y:Array|TypedArray, strideY:integer )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using heapsort.\n","base.strided.gsort2hp.ndarray":"\nbase.strided.gsort2hp.ndarray( N:integer, order:number, x:Array|TypedArray, \n  strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n  offsetY:integer )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using heapsort and alternative indexing semantics.\n","base.strided.gsort2ins":"\nbase.strided.gsort2ins( N:integer, order:number, x:Array|TypedArray, \n  strideX:integer, y:Array|TypedArray, strideY:integer )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using insertion sort.\n","base.strided.gsort2ins.ndarray":"\nbase.strided.gsort2ins.ndarray( N:integer, order:number, x:Array|TypedArray, \n  strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n  offsetY:integer )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using insertion sort and alternative indexing semantics.\n","base.strided.gsort2sh":"\nbase.strided.gsort2sh( N:integer, order:number, x:Array|TypedArray, \n  strideX:integer, y:Array|TypedArray, strideY:integer )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using Shellsort.\n","base.strided.gsort2sh.ndarray":"\nbase.strided.gsort2sh.ndarray( N:integer, order:number, x:Array|TypedArray, \n  strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n  offsetY:integer )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using Shellsort and alternative indexing semantics.\n","base.strided.gsorthp":"\nbase.strided.gsorthp( N:integer, order:number, x:Array|TypedArray, \n  stride:integer )\n    Sorts a strided array using heapsort.\n","base.strided.gsorthp.ndarray":"\nbase.strided.gsorthp.ndarray( N:integer, order:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Sorts a strided array using heapsort and alternative indexing semantics.\n","base.strided.gsortins":"\nbase.strided.gsortins( N:integer, order:number, x:Array|TypedArray, \n  stride:integer )\n    Sorts a strided array using insertion sort.\n","base.strided.gsortins.ndarray":"\nbase.strided.gsortins.ndarray( N:integer, order:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Sorts a strided array using insertion sort and alternative indexing\n    semantics.\n","base.strided.gsortsh":"\nbase.strided.gsortsh( N:integer, order:number, x:Array|TypedArray, \n  stride:integer )\n    Sorts a strided array using Shellsort.\n","base.strided.gsortsh.ndarray":"\nbase.strided.gsortsh.ndarray( N:integer, order:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Sorts a strided array using Shellsort and alternative indexing semantics.\n","base.strided.gsum":"\nbase.strided.gsum( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of strided array elements.\n","base.strided.gsum.ndarray":"\nbase.strided.gsum.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the sum of strided array elements using alternative indexing\n    semantics.\n","base.strided.gsumkbn":"\nbase.strided.gsumkbn( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of strided array elements using an improved Kahan–Babuška\n    algorithm.\n","base.strided.gsumkbn.ndarray":"\nbase.strided.gsumkbn.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the sum of strided array elements using an improved Kahan–Babuška\n    algorithm and alternative indexing semantics.\n","base.strided.gsumkbn2":"\nbase.strided.gsumkbn2( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of strided array elements using a second-order iterative\n    Kahan–Babuška algorithm.\n","base.strided.gsumkbn2.ndarray":"\nbase.strided.gsumkbn2.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the sum of strided array elements using a second-order iterative\n    Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gsumors":"\nbase.strided.gsumors( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of strided array elements using ordinary recursive\n    summation.\n","base.strided.gsumors.ndarray":"\nbase.strided.gsumors.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the sum of strided array elements using ordinary recursive\n    summation and alternative indexing semantics.\n","base.strided.gsumpw":"\nbase.strided.gsumpw( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of strided array elements using pairwise summation.\n","base.strided.gsumpw.ndarray":"\nbase.strided.gsumpw.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the sum of strided array elements using pairwise summation and\n    alternative indexing semantics.\n","base.strided.gswap":"\nbase.strided.gswap( N:integer, x:ArrayLikeObject, strideX:integer, \n  y:ArrayLikeObject, strideY:integer )\n    Interchanges vectors `x` and `y`.\n","base.strided.gswap.ndarray":"\nbase.strided.gswap.ndarray( N:integer, x:ArrayLikeObject, strideX:integer, \n  offsetX:integer, y:ArrayLikeObject, strideY:integer, offsetY:integer )\n    Interchanges vectors `x` and `y` using alternative indexing semantics.\n","base.strided.mapBy":"\nbase.strided.mapBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, fcn:Function, clbk:Function[, \n  thisArg:any] )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array.\n","base.strided.mapBy.ndarray":"\nbase.strided.mapBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, fcn:Function, \n  clbk:Function[, thisArg:any] )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array using alternative indexing semantics.\n","base.strided.mapBy2":"\nbase.strided.mapBy2( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, \n  fcn:Function, clbk:Function[, thisArg:any] )\n    Applies a binary function to each pair of elements retrieved from strided\n    input arrays according to a callback function and assigns results to a\n    strided output array.\n","base.strided.mapBy2.ndarray":"\nbase.strided.mapBy2.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  z:Array|TypedArray|Object, sz:integer, oz:integer, fcn:Function, \n  clbk:Function[, thisArg:any] )\n    Applies a binary function to each pair of elements retrieved from strided\n    input arrays according to a callback function and assigns results to a\n    strided output array using alternative indexing semantics.\n","base.strided.max":"\nbase.strided.max( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the maximum value of a strided array.\n","base.strided.max.ndarray":"\nbase.strided.max.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the maximum value of a strided array using alternative indexing\n    semantics.\n","base.strided.maxabs":"\nbase.strided.maxabs( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the maximum absolute value of a strided array.\n","base.strided.maxabs.ndarray":"\nbase.strided.maxabs.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the maximum absolute value of a strided array using alternative\n    indexing semantics.\n","base.strided.maxBy":"\nbase.strided.maxBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n  clbk:Function[, thisArg:any] )\n    Calculates the maximum value of a strided array via a callback function.\n","base.strided.maxBy.ndarray":"\nbase.strided.maxBy.ndarray( N:integer, x:Array|TypedArray|Object, \n  stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n    Calculates the maximum value of a strided array via a callback function and\n    using alternative indexing semantics.\n","base.strided.maxsorted":"\nbase.strided.maxsorted( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the maximum value of a sorted strided array.\n","base.strided.maxsorted.ndarray":"\nbase.strided.maxsorted.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the maximum value of a sorted strided array using alternative\n    indexing semantics.\n","base.strided.maxViewBufferIndex":"\nbase.strided.maxViewBufferIndex( N:integer, stride:integer, offset:integer )\n    Returns the maximum accessible index based on a set of provided strided\n    array parameters.\n","base.strided.mean":"\nbase.strided.mean( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the arithmetic mean of a strided array.\n","base.strided.mean.ndarray":"\nbase.strided.mean.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a strided array using alternative indexing\n    semantics.\n","base.strided.meankbn":"\nbase.strided.meankbn( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the arithmetic mean of a strided array using an improved Kahan–\n    Babuška algorithm.\n","base.strided.meankbn.ndarray":"\nbase.strided.meankbn.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a strided array using an improved Kahan–\n    Babuška algorithm and alternative indexing semantics.\n","base.strided.meankbn2":"\nbase.strided.meankbn2( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the arithmetic mean of a strided array using a second-order\n    iterative Kahan–Babuška algorithm.\n","base.strided.meankbn2.ndarray":"\nbase.strided.meankbn2.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a strided array using a second-order\n    iterative Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.meanors":"\nbase.strided.meanors( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the arithmetic mean of a strided array using ordinary recursive\n    summation.\n","base.strided.meanors.ndarray":"\nbase.strided.meanors.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a strided array using ordinary recursive\n    summation and alternative indexing semantics.\n","base.strided.meanpn":"\nbase.strided.meanpn( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the arithmetic mean of a strided array using a two-pass error\n    correction algorithm.\n","base.strided.meanpn.ndarray":"\nbase.strided.meanpn.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a strided array using a two-pass error\n    correction algorithm and alternative indexing semantics.\n","base.strided.meanpw":"\nbase.strided.meanpw( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the arithmetic mean of a strided array using pairwise summation.\n","base.strided.meanpw.ndarray":"\nbase.strided.meanpw.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a strided array using pairwise summation and\n    alternative indexing semantics.\n","base.strided.meanwd":"\nbase.strided.meanwd( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the arithmetic mean of a strided array using Welford's algorithm.\n","base.strided.meanwd.ndarray":"\nbase.strided.meanwd.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a strided array using Welford's algorithm\n    and alternative indexing semantics.\n","base.strided.mediansorted":"\nbase.strided.mediansorted( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the median value of a sorted strided array.\n","base.strided.mediansorted.ndarray":"\nbase.strided.mediansorted.ndarray( N:integer, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Computes the median value of a sorted strided array using alternative\n    indexing semantics.\n","base.strided.metaDataProps":"\nbase.strided.metaDataProps( meta:Object, dtypes:ArrayLikeObject, \n  obj:Object|Function, bool:boolean )\n    Defines non-enumerable read-only properties which expose strided array\n    function meta data.\n","base.strided.min":"\nbase.strided.min( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the minimum value of a strided array.\n","base.strided.min.ndarray":"\nbase.strided.min.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the minimum value of a strided array using alternative indexing\n    semantics.\n","base.strided.minabs":"\nbase.strided.minabs( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the minimum absolute value of a strided array.\n","base.strided.minabs.ndarray":"\nbase.strided.minabs.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the minimum absolute value of a strided array using alternative\n    indexing semantics.\n","base.strided.minBy":"\nbase.strided.minBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n  clbk:Function[, thisArg:any] )\n    Calculates the minimum value of a strided array via a callback function.\n","base.strided.minBy.ndarray":"\nbase.strided.minBy.ndarray( N:integer, x:Array|TypedArray|Object, \n  stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n    Calculates the minimum value of a strided array via a callback function and\n    using alternative indexing semantics.\n","base.strided.minsorted":"\nbase.strided.minsorted( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the minimum value of a sorted strided array.\n","base.strided.minsorted.ndarray":"\nbase.strided.minsorted.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the minimum value of a sorted strided array using alternative\n    indexing semantics.\n","base.strided.minViewBufferIndex":"\nbase.strided.minViewBufferIndex( N:integer, stride:integer, offset:integer )\n    Returns the minimum accessible index based on a set of provided strided\n    array parameters.\n","base.strided.mskmax":"\nbase.strided.mskmax( N:integer, x:Array|TypedArray, strideX:integer, \n  mask:Array|TypedArray, strideMask:integer )\n    Computes the maximum value of a strided array according to a mask.\n","base.strided.mskmax.ndarray":"\nbase.strided.mskmax.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n  offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n  offsetMask:integer )\n    Computes the maximum value of a strided array according to a mask and using\n    alternative indexing semantics.\n","base.strided.mskmin":"\nbase.strided.mskmin( N:integer, x:Array|TypedArray, strideX:integer, \n  mask:Array|TypedArray, strideMask:integer )\n    Computes the minimum value of a strided array according to a mask.\n","base.strided.mskmin.ndarray":"\nbase.strided.mskmin.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n  offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n  offsetMask:integer )\n    Computes the minimum value of a strided array according to a mask and using\n    alternative indexing semantics.\n","base.strided.mskrange":"\nbase.strided.mskrange( N:integer, x:Array|TypedArray, strideX:integer, \n  mask:Array|TypedArray, strideMask:integer )\n    Computes the range of a strided array according to a mask.\n","base.strided.mskrange.ndarray":"\nbase.strided.mskrange.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n  offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n  offsetMask:integer )\n    Computes the range of a strided array according to a mask and using\n    alternative indexing semantics.\n","base.strided.mskunary":"\nbase.strided.mskunary( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  fcn:Function )\n    Applies a unary callback to elements in a strided input array according to\n    elements in a strided mask array and assigns results to elements in a\n    strided output array.\n","base.strided.mskunary.ndarray":"\nbase.strided.mskunary.ndarray( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  offsets:ArrayLikeObject<integer>, fcn:Function )\n    Applies a unary callback to elements in a strided input array according to\n    elements in a strided mask array, and assigns results to elements in a\n    strided output array using alternative indexing semantics.\n","base.strided.mskunaryDtypeSignatures":"\nbase.strided.mskunaryDtypeSignatures( dtypes1:ArrayLike<any>, \n  dtypes2:ArrayLike<any>[, options:Object] )\n    Generates a list of masked unary interface signatures from strided array\n    data types.\n","base.strided.mskunarySignatureCallbacks":"\nbase.strided.mskunarySignatureCallbacks( table:Object, \n  signatures:ArrayLike<any> )\n    Assigns callbacks to masked unary interfaces according to type promotion\n    rules.\n","base.strided.nanmax":"\nbase.strided.nanmax( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the maximum value of a strided array, ignoring `NaN` values.\n","base.strided.nanmax.ndarray":"\nbase.strided.nanmax.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the maximum value of a strided array, ignoring `NaN` values and\n    using alternative indexing semantics.\n","base.strided.nanmaxabs":"\nbase.strided.nanmaxabs( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the maximum absolute value of a strided array, ignoring `NaN`\n    values.\n","base.strided.nanmaxabs.ndarray":"\nbase.strided.nanmaxabs.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the maximum absolute value of a strided array, ignoring `NaN`\n    values and using alternative indexing semantics.\n","base.strided.nanmaxBy":"\nbase.strided.nanmaxBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n  clbk:Function[, thisArg:any] )\n    Calculates the maximum value of a strided array via a callback function,\n    ignoring `NaN` values.\n","base.strided.nanmaxBy.ndarray":"\nbase.strided.nanmaxBy.ndarray( N:integer, x:Array|TypedArray|Object, \n  stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n    Calculates the maximum value of a strided array via a callback function,\n    ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.nanmean":"\nbase.strided.nanmean( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values.\n","base.strided.nanmean.ndarray":"\nbase.strided.nanmean.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using alternative indexing semantics.\n","base.strided.nanmeanors":"\nbase.strided.nanmeanors( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using ordinary recursive summation.\n","base.strided.nanmeanors.ndarray":"\nbase.strided.nanmeanors.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using ordinary recursive summation and alternative indexing semantics.\n","base.strided.nanmeanpn":"\nbase.strided.nanmeanpn( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using a two-pass error correction algorithm.\n","base.strided.nanmeanpn.ndarray":"\nbase.strided.nanmeanpn.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using a two-pass error correction algorithm and alternative indexing\n    semantics.\n","base.strided.nanmeanwd":"\nbase.strided.nanmeanwd( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using Welford's algorithm.\n","base.strided.nanmeanwd.ndarray":"\nbase.strided.nanmeanwd.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using Welford's algorithm and alternative indexing semantics.\n","base.strided.nanmin":"\nbase.strided.nanmin( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the minimum value of a strided array, ignoring `NaN` values.\n","base.strided.nanmin.ndarray":"\nbase.strided.nanmin.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the minimum value of a strided array, ignoring `NaN` values and\n    using alternative indexing semantics.\n","base.strided.nanminabs":"\nbase.strided.nanminabs( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the minimum absolute value of a strided array, ignoring `NaN`\n    values.\n","base.strided.nanminabs.ndarray":"\nbase.strided.nanminabs.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the minimum absolute value of a strided array, ignoring `NaN`\n    values and using alternative indexing semantics.\n","base.strided.nanminBy":"\nbase.strided.nanminBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n  clbk:Function[, thisArg:any] )\n    Calculates the minimum value of a strided array via a callback function,\n    ignoring `NaN` values.\n","base.strided.nanminBy.ndarray":"\nbase.strided.nanminBy.ndarray( N:integer, x:Array|TypedArray|Object, \n  stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n    Calculates the minimum value of a strided array via a callback function,\n    ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.nanmskmax":"\nbase.strided.nanmskmax( N:integer, x:Array|TypedArray, strideX:integer, \n  mask:Array|TypedArray, strideMask:integer )\n    Computes the maximum value of a strided array according to a mask and\n    ignoring `NaN` values.\n","base.strided.nanmskmax.ndarray":"\nbase.strided.nanmskmax.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n  offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n  offsetMask:integer )\n    Computes the maximum value of a strided array according to a mask,\n    ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.nanmskmin":"\nbase.strided.nanmskmin( N:integer, x:Array|TypedArray, strideX:integer, \n  mask:Array|TypedArray, strideMask:integer )\n    Computes the minimum value of a strided array according to a mask and\n    ignoring `NaN` values.\n","base.strided.nanmskmin.ndarray":"\nbase.strided.nanmskmin.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n  offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n  offsetMask:integer )\n    Computes the minimum value of a strided array according to a mask, ignoring\n    `NaN` values and using alternative indexing semantics.\n","base.strided.nanmskrange":"\nbase.strided.nanmskrange( N:integer, x:Array|TypedArray, strideX:integer, \n  mask:Array|TypedArray, strideMask:integer )\n    Computes the range of a strided array according to a mask and ignoring `NaN`\n    values.\n","base.strided.nanmskrange.ndarray":"\nbase.strided.nanmskrange.ndarray( N:integer, x:Array|TypedArray, \n  strideX:integer, offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n  offsetMask:integer )\n    Computes the range of a strided array according to a mask, ignoring `NaN`\n    values and using alternative indexing semantics.\n","base.strided.nanrange":"\nbase.strided.nanrange( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the range of a strided array, ignoring `NaN` values.\n","base.strided.nanrange.ndarray":"\nbase.strided.nanrange.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the range of a strided array, ignoring `NaN` values and using\n    alternative indexing semantics.\n","base.strided.nanrangeBy":"\nbase.strided.nanrangeBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n  clbk:Function[, thisArg:any] )\n    Calculates the range of a strided array via a callback function, ignoring\n    `NaN` values.\n","base.strided.nanrangeBy.ndarray":"\nbase.strided.nanrangeBy.ndarray( N:integer, x:Array|TypedArray|Object, \n  stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n    Calculates the range of a strided array via a callback function, ignoring\n    `NaN` values and using alternative indexing semantics.\n","base.strided.nanstdev":"\nbase.strided.nanstdev( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values.\n","base.strided.nanstdev.ndarray":"\nbase.strided.nanstdev.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using alternative indexing semantics.\n","base.strided.nanstdevch":"\nbase.strided.nanstdevch( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass trial mean algorithm.\n","base.strided.nanstdevch.ndarray":"\nbase.strided.nanstdevch.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.nanstdevpn":"\nbase.strided.nanstdevpn( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a two-pass algorithm.\n","base.strided.nanstdevpn.ndarray":"\nbase.strided.nanstdevpn.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a two-pass algorithm and alternative indexing semantics.\n","base.strided.nanstdevtk":"\nbase.strided.nanstdevtk( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass textbook algorithm.\n","base.strided.nanstdevtk.ndarray":"\nbase.strided.nanstdevtk.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.nanstdevwd":"\nbase.strided.nanstdevwd( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using Welford's algorithm.\n","base.strided.nanstdevwd.ndarray":"\nbase.strided.nanstdevwd.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using Welford's algorithm and alternative indexing semantics.\n","base.strided.nanstdevyc":"\nbase.strided.nanstdevyc( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.nanstdevyc.ndarray":"\nbase.strided.nanstdevyc.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass algorithm proposed by Youngs and Cramer and alternative\n    indexing semantics.\n","base.strided.nanvariance":"\nbase.strided.nanvariance( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array ignoring `NaN` values.\n","base.strided.nanvariance.ndarray":"\nbase.strided.nanvariance.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using\n    alternative indexing semantics.\n","base.strided.nanvariancech":"\nbase.strided.nanvariancech( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass trial mean algorithm.\n","base.strided.nanvariancech.ndarray":"\nbase.strided.nanvariancech.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.nanvariancepn":"\nbase.strided.nanvariancepn( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    two-pass algorithm.\n","base.strided.nanvariancepn.ndarray":"\nbase.strided.nanvariancepn.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    two-pass algorithm and alternative indexing semantics.\n","base.strided.nanvariancetk":"\nbase.strided.nanvariancetk( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass textbook algorithm.\n","base.strided.nanvariancetk.ndarray":"\nbase.strided.nanvariancetk.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.nanvariancewd":"\nbase.strided.nanvariancewd( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using\n    Welford's algorithm.\n","base.strided.nanvariancewd.ndarray":"\nbase.strided.nanvariancewd.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using\n    Welford's algorithm and alternative indexing semantics.\n","base.strided.nanvarianceyc":"\nbase.strided.nanvarianceyc( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.nanvarianceyc.ndarray":"\nbase.strided.nanvarianceyc.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass algorithm proposed by Youngs and Cramer and alternative indexing\n    semantics.\n","base.strided.nullary":"\nbase.strided.nullary( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  fcn:Function )\n    Applies a nullary callback and assigns results to elements in a strided\n    output array.\n","base.strided.nullary.ndarray":"\nbase.strided.nullary.ndarray( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  offsets:ArrayLikeObject<integer>, fcn:Function )\n    Applies a nullary callback and assigns results to elements in a strided\n    output array using alternative indexing semantics.\n","base.strided.offsetView":"\nbase.strided.offsetView( x:TypedArray, offset:integer )\n    Returns a typed array view having the same data type as a provided input\n    typed array and starting at a specified index offset.\n","base.strided.quaternary":"\nbase.strided.quaternary( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  fcn:Function )\n    Applies a quaternary callback to strided input array elements and assigns\n    results to elements in a strided output array.\n","base.strided.quaternary.ndarray":"\nbase.strided.quaternary.ndarray( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  offsets:ArrayLikeObject<integer>, fcn:Function )\n    Applies a quaternary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n","base.strided.quinary":"\nbase.strided.quinary( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  fcn:Function )\n    Applies a quinary callback to strided input array elements and assigns\n    results to elements in a strided output array.\n","base.strided.quinary.ndarray":"\nbase.strided.quinary.ndarray( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  offsets:ArrayLikeObject<integer>, fcn:Function )\n    Applies a quinary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n","base.strided.range":"\nbase.strided.range( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the range of a strided array.\n","base.strided.range.ndarray":"\nbase.strided.range.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the range of a strided array using alternative indexing semantics.\n","base.strided.rangeBy":"\nbase.strided.rangeBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n  clbk:Function[, thisArg:any] )\n    Calculates the range of a strided array via a callback function.\n","base.strided.rangeBy.ndarray":"\nbase.strided.rangeBy.ndarray( N:integer, x:Array|TypedArray|Object, \n  stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n    Calculates the range of a strided array via a callback function and using\n    alternative indexing semantics.\n","base.strided.reinterpretComplex":"\nbase.strided.reinterpretComplex( x:Complex128Array|Complex64Array, \n  offset:integer )\n    Returns a real-valued floating-point array view of a complex-valued\n    floating-point array having the same precision.\n","base.strided.reinterpretComplex64":"\nbase.strided.reinterpretComplex64( x:Complex64Array, offset:integer )\n    Returns a Float32Array view of a Complex64Array.\n","base.strided.reinterpretComplex128":"\nbase.strided.reinterpretComplex128( x:Complex128Array, offset:integer )\n    Returns a Float64Array view of a Complex128Array.\n","base.strided.sabs":"\nbase.strided.sabs( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer )\n    Computes the absolute value for each element in a single-precision floating-\n    point strided array `x` and assigns the results to elements in a single-\n    precision floating-point strided array `y`.\n","base.strided.sabs.ndarray":"\nbase.strided.sabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the absolute value for each element in a single-precision floating-\n    point strided array `x` and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.sabs2":"\nbase.strided.sabs2( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer )\n    Computes the squared absolute value for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y`.\n","base.strided.sabs2.ndarray":"\nbase.strided.sabs2.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the squared absolute value for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.sapx":"\nbase.strided.sapx( N:integer, alpha:number, x:Float32Array, stride:integer )\n    Adds a constant to each element in a single-precision floating-point strided\n    array.\n","base.strided.sapx.ndarray":"\nbase.strided.sapx.ndarray( N:integer, alpha:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Adds a constant to each element in a single-precision floating-point strided\n    array using alternative indexing semantics.\n","base.strided.sapxsum":"\nbase.strided.sapxsum( N:integer, alpha:number, x:Float32Array, stride:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum.\n","base.strided.sapxsum.ndarray":"\nbase.strided.sapxsum.ndarray( N:integer, alpha:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using alternative indexing semantics.\n","base.strided.sapxsumkbn":"\nbase.strided.sapxsumkbn( N:integer, alpha:number, x:Float32Array, \n  stride:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using an improved Kahan–Babuška algorithm.\n","base.strided.sapxsumkbn.ndarray":"\nbase.strided.sapxsumkbn.ndarray( N:integer, alpha:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n","base.strided.sapxsumkbn2":"\nbase.strided.sapxsumkbn2( N:integer, alpha:number, x:Float32Array, \n  stride:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using a second-order iterative Kahan–Babuška\n    algorithm.\n","base.strided.sapxsumkbn2.ndarray":"\nbase.strided.sapxsumkbn2.ndarray( N:integer, alpha:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n","base.strided.sapxsumors":"\nbase.strided.sapxsumors( N:integer, alpha:number, x:Float32Array, \n  stride:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using ordinary recursive summation.\n","base.strided.sapxsumors.ndarray":"\nbase.strided.sapxsumors.ndarray( N:integer, alpha:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using ordinary recursive summation and\n    alternative indexing semantics.\n","base.strided.sapxsumpw":"\nbase.strided.sapxsumpw( N:integer, alpha:number, x:Float32Array, \n  stride:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using pairwise summation.\n","base.strided.sapxsumpw.ndarray":"\nbase.strided.sapxsumpw.ndarray( N:integer, alpha:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using pairwise summation and alternative\n    indexing semantics.\n","base.strided.sasum":"\nbase.strided.sasum( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of the absolute values.\n","base.strided.sasum.ndarray":"\nbase.strided.sasum.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of absolute values using alternative indexing semantics.\n","base.strided.sasumpw":"\nbase.strided.sasumpw( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of absolute values (L1 norm) of single-precision floating-\n    point strided array elements using pairwise summation.\n","base.strided.sasumpw.ndarray":"\nbase.strided.sasumpw.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of absolute values (L1 norm) of single-precision floating-\n    point strided array elements using pairwise summation and alternative\n    indexing semantics.\n","base.strided.saxpy":"\nbase.strided.saxpy( N:integer, alpha:number, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n","base.strided.saxpy.ndarray":"\nbase.strided.saxpy.ndarray( N:integer, alpha:number, x:Float32Array, \n  strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n  offsetY:integer )\n    Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n    using alternative indexing semantics.\n","base.strided.scbrt":"\nbase.strided.scbrt( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer )\n    Computes the cube root of each element in a single-precision floating-point \n    strided array `x` and assigns the results to elements in a single-precision \n    floating-point strided array `y`.\n","base.strided.scbrt.ndarray":"\nbase.strided.scbrt.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the cube root of each element in a single-precision floating-point \n    strided array `x` and assigns the results to elements in a single-precision \n    floating-point strided array `y` using alternative indexing semantics.\n","base.strided.sceil":"\nbase.strided.sceil( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward positive infinity and assigns the results to elements in a single-\n    precision floating-point strided array `y`.\n","base.strided.sceil.ndarray":"\nbase.strided.sceil.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward positive infinity and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.scopy":"\nbase.strided.scopy( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer )\n    Copies values from `x` into `y`.\n","base.strided.scopy.ndarray":"\nbase.strided.scopy.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Copies values from `x` into `y` using alternative indexing semantics.\n","base.strided.scumax":"\nbase.strided.scumax( N:integer, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Computes the cumulative maximum of single-precision floating-point strided\n    array elements.\n","base.strided.scumax.ndarray":"\nbase.strided.scumax.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the cumulative maximum of single-precision floating-point strided\n    array elements using alternative indexing semantics.\n","base.strided.scumaxabs":"\nbase.strided.scumaxabs( N:integer, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Computes the cumulative maximum absolute value of single-precision floating-\n    point strided array elements.\n","base.strided.scumaxabs.ndarray":"\nbase.strided.scumaxabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the cumulative maximum absolute value of single-precision floating-\n    point strided array elements using alternative indexing semantics.\n","base.strided.scumin":"\nbase.strided.scumin( N:integer, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Computes the cumulative minimum of single-precision floating-point strided\n    array elements.\n","base.strided.scumin.ndarray":"\nbase.strided.scumin.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the cumulative minimum of single-precision floating-point strided\n    array elements using alternative indexing semantics.\n","base.strided.scuminabs":"\nbase.strided.scuminabs( N:integer, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Computes the cumulative minimum absolute value of single-precision floating-\n    point strided array elements.\n","base.strided.scuminabs.ndarray":"\nbase.strided.scuminabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the cumulative minimum absolute value of single-precision floating-\n    point strided array elements using alternative indexing semantics.\n","base.strided.scusum":"\nbase.strided.scusum( N:integer, sum:number, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements.\n","base.strided.scusum.ndarray":"\nbase.strided.scusum.ndarray( N:integer, sum:number, x:Float32Array, \n  strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using alternative indexing semantics.\n","base.strided.scusumkbn":"\nbase.strided.scusumkbn( N:integer, sum:number, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using an improved Kahan–Babuška algorithm.\n","base.strided.scusumkbn.ndarray":"\nbase.strided.scusumkbn.ndarray( N:integer, sum:number, x:Float32Array, \n  strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n","base.strided.scusumkbn2":"\nbase.strided.scusumkbn2( N:integer, sum:number, x:Float32Array, \n  strideX:integer, y:Float32Array, strideY:integer )\n    Computes the cumulative sum of single-precision floating-point strided \n    array elements using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.scusumkbn2.ndarray":"\nbase.strided.scusumkbn2.ndarray( N:integer, sum:number, x:Float32Array, \n  strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of single-precision floating-point strided\n    array elements using a second-order iterative Kahan–Babuška algorithm and\n    alternative indexing semantics.\n","base.strided.scusumors":"\nbase.strided.scusumors( N:integer, sum:number, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using ordinary recursive summation.\n","base.strided.scusumors.ndarray":"\nbase.strided.scusumors.ndarray( N:integer, sum:number, x:Float32Array, \n  strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using ordinary recursive summation and alternative indexing\n    semantics.\n","base.strided.scusumpw":"\nbase.strided.scusumpw( N:integer, sum:number, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using pairwise summation.\n","base.strided.scusumpw.ndarray":"\nbase.strided.scusumpw.ndarray( N:integer, sum:number, x:Float32Array, \n  strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using pairwise summation and alternative indexing semantics.\n","base.strided.sdeg2rad":"\nbase.strided.sdeg2rad( N:integer, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Converts each element in a single-precision floating-point strided array `x`\n    from degrees to radians and assigns the results to elements in a single-\n    precision floating-point strided array `y`.\n","base.strided.sdeg2rad.ndarray":"\nbase.strided.sdeg2rad.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Converts each element in a single-precision floating-point strided array `x`\n    from degrees to radians and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.sdot":"\nbase.strided.sdot( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer )\n    Computes the dot product of two single-precision floating-point vectors.\n","base.strided.sdot.ndarray":"\nbase.strided.sdot.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the dot product of two single-precision floating-point vectors\n    using alternative indexing semantics.\n","base.strided.sdsapxsum":"\nbase.strided.sdsapxsum( N:integer, alpha:number, x:Float32Array, \n  stride:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using extended accumulation.\n","base.strided.sdsapxsum.ndarray":"\nbase.strided.sdsapxsum.ndarray( N:integer, alpha:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using extended accumulation and alternative\n    indexing semantics.\n","base.strided.sdsapxsumpw":"\nbase.strided.sdsapxsumpw( N:integer, alpha:number, x:Float32Array, \n  stride:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using pairwise summation with extended\n    accumulation.\n","base.strided.sdsapxsumpw.ndarray":"\nbase.strided.sdsapxsumpw.ndarray( N:integer, alpha:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using pairwise summation with extended\n    accumulation and alternative indexing semantics.\n","base.strided.sdsdot":"\nbase.strided.sdsdot( N:integer, scalar:number, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Computes the dot product of two single-precision floating-point vectors with\n    extended accumulation.\n","base.strided.sdsdot.ndarray":"\nbase.strided.sdsdot.ndarray( N:integer, scalar:number, x:Float32Array, \n  strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n  offsetY:integer )\n    Computes the dot product of two single-precision floating-point vectors\n    using alternative indexing semantics and with extended accumulation.\n","base.strided.sdsmean":"\nbase.strided.sdsmean( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using extended accumulation.\n","base.strided.sdsmean.ndarray":"\nbase.strided.sdsmean.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using extended accumulation and alternative indexing semantics.\n","base.strided.sdsmeanors":"\nbase.strided.sdsmeanors( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation with extended accumulation.\n","base.strided.sdsmeanors.ndarray":"\nbase.strided.sdsmeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation with extended accumulation and\n    alternative indexing semantics.\n","base.strided.sdsnanmean":"\nbase.strided.sdsnanmean( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using extended accumulation.\n","base.strided.sdsnanmean.ndarray":"\nbase.strided.sdsnanmean.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using extended accumulation and alternative\n    indexing semantics.\n","base.strided.sdsnanmeanors":"\nbase.strided.sdsnanmeanors( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation with\n    extended accumulation.\n","base.strided.sdsnanmeanors.ndarray":"\nbase.strided.sdsnanmeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation with\n    extended accumulation and alternative indexing semantics.\n","base.strided.sdsnansum":"\nbase.strided.sdsnansum( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of single-precision floating-point strided array\n    elements, ignore `NaN` values and using extended accumulation.\n","base.strided.sdsnansum.ndarray":"\nbase.strided.sdsnansum.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using extended accumulation and alternative\n    indexing semantics.\n","base.strided.sdsnansumpw":"\nbase.strided.sdsnansumpw( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation with extended\n    accumulation.\n","base.strided.sdsnansumpw.ndarray":"\nbase.strided.sdsnansumpw.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation with extended\n    accumulation and alternative indexing semantics.\n","base.strided.sdssum":"\nbase.strided.sdssum( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using extended accumulation.\n","base.strided.sdssum.ndarray":"\nbase.strided.sdssum.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using extended accumulation and alternative indexing semantics.\n","base.strided.sdssumpw":"\nbase.strided.sdssumpw( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation with extended accumulation.\n","base.strided.sdssumpw.ndarray":"\nbase.strided.sdssumpw.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation with extended accumulation and alternative indexing\n    semantics.\n","base.strided.sfill":"\nbase.strided.sfill( N:integer, alpha:number, x:Float32Array, strideX:integer )\n    Fills a single-precision floating-point strided array with a specified\n    scalar value.\n","base.strided.sfill.ndarray":"\nbase.strided.sfill.ndarray( N:integer, alpha:number, x:Float32Array, \n  strideX:integer, offsetX:integer )\n    Fills a single-precision floating-point strided array with a specified\n    scalar value using alternative indexing semantics.\n","base.strided.sfloor":"\nbase.strided.sfloor( N:integer, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward negative infinity and assigns the results to elements in a single-\n    precision floating-point strided array `y`.\n","base.strided.sfloor.ndarray":"\nbase.strided.sfloor.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward negative infinity and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.sinv":"\nbase.strided.sinv( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer )\n    Computes the multiplicative inverse for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y`.\n","base.strided.sinv.ndarray":"\nbase.strided.sinv.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the multiplicative inverse for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.smap":"\nbase.strided.smap( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer, fcn:Function )\n    Applies a unary function to a single-precision floating-point strided input\n    array and assigns results to a single-precision floating-point strided\n    output array.\n","base.strided.smap.ndarray":"\nbase.strided.smap.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer, \n  fcn:Function )\n    Applies a unary function to a single-precision floating-point strided input\n    array and assigns results to a single-precision floating-point strided\n    output array using alternative indexing semantics.\n","base.strided.smap2":"\nbase.strided.smap2( N:integer, x:Float32Array, sx:integer, y:Float32Array, \n  sy:integer, z:Float32Array, sz:integer, fcn:Function )\n    Applies a binary function to single-precision floating-point strided input\n    arrays and assigns results to a single-precision floating-point strided\n    output array.\n","base.strided.smap2.ndarray":"\nbase.strided.smap2.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, \n  y:Float32Array, sy:integer, oy:integer, z:Float32Array, sz:integer, \n  oz:integer, fcn:Function )\n    Applies a binary function to single-precision floating-point strided input\n    arrays and assigns results to a single-precision floating-point strided\n    output array using alternative indexing semantics.\n","base.strided.smax":"\nbase.strided.smax( N:integer, x:Float32Array, strideX:integer )\n    Computes the maximum value of a single-precision floating-point strided\n    array.\n","base.strided.smax.ndarray":"\nbase.strided.smax.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum value of a single-precision floating-point strided\n    array using alternative indexing semantics.\n","base.strided.smaxabs":"\nbase.strided.smaxabs( N:integer, x:Float32Array, strideX:integer )\n    Computes the maximum absolute value of a single-precision floating-point\n    strided array.\n","base.strided.smaxabs.ndarray":"\nbase.strided.smaxabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum absolute value of a single-precision floating-point\n    strided array using alternative indexing semantics.\n","base.strided.smaxabssorted":"\nbase.strided.smaxabssorted( N:integer, x:Float32Array, strideX:integer )\n    Computes the maximum absolute value of a sorted single-precision floating-\n    point strided array.\n","base.strided.smaxabssorted.ndarray":"\nbase.strided.smaxabssorted.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum absolute value of a sorted single-precision floating-\n    point strided array using alternative indexing semantics.\n","base.strided.smaxsorted":"\nbase.strided.smaxsorted( N:integer, x:Float32Array, strideX:integer )\n    Computes the maximum value of a sorted single-precision floating-point\n    strided array.\n","base.strided.smaxsorted.ndarray":"\nbase.strided.smaxsorted.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n","base.strided.smean":"\nbase.strided.smean( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array.\n","base.strided.smean.ndarray":"\nbase.strided.smean.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using alternative indexing semantics.\n","base.strided.smeankbn":"\nbase.strided.smeankbn( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm.\n","base.strided.smeankbn.ndarray":"\nbase.strided.smeankbn.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n","base.strided.smeankbn2":"\nbase.strided.smeankbn2( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.smeankbn2.ndarray":"\nbase.strided.smeankbn2.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n","base.strided.smeanli":"\nbase.strided.smeanli( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm.\n","base.strided.smeanli.ndarray":"\nbase.strided.smeanli.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n","base.strided.smeanlipw":"\nbase.strided.smeanlipw( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm with pairwise summation.\n","base.strided.smeanlipw.ndarray":"\nbase.strided.smeanlipw.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm with pairwise summation and\n    alternative indexing semantics.\n","base.strided.smeanors":"\nbase.strided.smeanors( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation.\n","base.strided.smeanors.ndarray":"\nbase.strided.smeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation and alternative indexing semantics.\n","base.strided.smeanpn":"\nbase.strided.smeanpn( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a two-pass error correction algorithm.\n","base.strided.smeanpn.ndarray":"\nbase.strided.smeanpn.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a two-pass error correction algorithm and alternative indexing\n    semantics.\n","base.strided.smeanpw":"\nbase.strided.smeanpw( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using pairwise summation.\n","base.strided.smeanpw.ndarray":"\nbase.strided.smeanpw.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using pairwise summation and alternative indexing semantics.\n","base.strided.smeanwd":"\nbase.strided.smeanwd( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using Welford's algorithm.\n","base.strided.smeanwd.ndarray":"\nbase.strided.smeanwd.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n","base.strided.smediansorted":"\nbase.strided.smediansorted( N:integer, x:Float32Array, stride:integer )\n    Computes the median value of a sorted single-precision floating-point\n    strided array.\n","base.strided.smediansorted.ndarray":"\nbase.strided.smediansorted.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the median value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n","base.strided.smidrange":"\nbase.strided.smidrange( N:integer, x:Float32Array, strideX:integer )\n    Computes the mid-range of a single-precision floating-point strided array.\n","base.strided.smidrange.ndarray":"\nbase.strided.smidrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the mid-range of a single-precision floating-point strided array\n    using alternative indexing semantics.\n","base.strided.smin":"\nbase.strided.smin( N:integer, x:Float32Array, strideX:integer )\n    Computes the minimum value of a single-precision floating-point strided\n    array.\n","base.strided.smin.ndarray":"\nbase.strided.smin.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the minimum value of a single-precision floating-point strided\n    array using alternative indexing semantics.\n","base.strided.sminabs":"\nbase.strided.sminabs( N:integer, x:Float32Array, strideX:integer )\n    Computes the minimum absolute value of a single-precision floating-point\n    strided array.\n","base.strided.sminabs.ndarray":"\nbase.strided.sminabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the minimum absolute value of a single-precision floating-point\n    strided array using alternative indexing semantics.\n","base.strided.sminsorted":"\nbase.strided.sminsorted( N:integer, x:Float32Array, stride:integer )\n    Computes the minimum value of a sorted single-precision floating-point\n    strided array.\n","base.strided.sminsorted.ndarray":"\nbase.strided.sminsorted.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the minimum value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n","base.strided.smskabs":"\nbase.strided.smskabs( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Computes the absolute value for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskabs.ndarray":"\nbase.strided.smskabs.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n  sy:integer, oy:integer )\n    Computes the absolute value for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n","base.strided.smskabs2":"\nbase.strided.smskabs2( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Computes the squared absolute value for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point\n    strided array `y`.\n","base.strided.smskabs2.ndarray":"\nbase.strided.smskabs2.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n  sy:integer, oy:integer )\n    Computes the squared absolute value for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point\n    strided array `y` using alternative indexing semantics.\n","base.strided.smskcbrt":"\nbase.strided.smskcbrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Computes the cube root for each element in a single-precision floating-point\n    strided array `x` according to a strided mask array and assigns the results\n    to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskcbrt.ndarray":"\nbase.strided.smskcbrt.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n  sy:integer, oy:integer )\n    Computes the cube root for each element in a single-precision floating-point\n    strided array `x` according to a strided mask array and assigns the results\n    to elements in a single-precision floating-point strided array `y` using\n    alternative indexing semantics.\n","base.strided.smskceil":"\nbase.strided.smskceil( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward positive infinity according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskceil.ndarray":"\nbase.strided.smskceil.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n  sy:integer, oy:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward positive infinity according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n","base.strided.smskdeg2rad":"\nbase.strided.smskdeg2rad( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Converts each element in a single-precision floating-point strided array `x`\n    from degrees to radians according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskdeg2rad.ndarray":"\nbase.strided.smskdeg2rad.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n  sy:integer, oy:integer )\n    Converts each element in a single-precision floating-point strided array `x`\n    from degrees to radians according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n","base.strided.smskfloor":"\nbase.strided.smskfloor( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward negative infinity according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskfloor.ndarray":"\nbase.strided.smskfloor.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n  sy:integer, oy:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward negative infinity according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n","base.strided.smskinv":"\nbase.strided.smskinv( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Computes the multiplicative inverse for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y`.\n","base.strided.smskinv.ndarray":"\nbase.strided.smskinv.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n  sy:integer, oy:integer )\n    Computes the multiplicative inverse for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y` using alternative indexing semantics.\n","base.strided.smskmap":"\nbase.strided.smskmap( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer, fcn:Function )\n    Applies a unary function to a single-precision floating-point strided input\n    array according to a strided mask array and assigns results to a single-\n    precision floating-point strided output array.\n","base.strided.smskmap.ndarray":"\nbase.strided.smskmap.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Uint8Array, sm:integer, om:integer, y:Float32Array, sy:integer, \n  oy:integer, fcn:Function )\n    Applies a unary function to a single-precision floating-point strided input\n    array according to a strided mask array and assigns results to a single-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n","base.strided.smskmap2":"\nbase.strided.smskmap2( N:integer, x:Float32Array, sx:integer, y:Float32Array, \n  sy:integer, m:Uint8Array, sm:integer, z:Float32Array, sz:integer, \n  fcn:Function )\n    Applies a binary function to single-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a single-\n    precision floating-point strided output array.\n","base.strided.smskmap2.ndarray":"\nbase.strided.smskmap2.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, y:Float32Array, sy:integer, oy:integer, m:Uint8Array, sm:integer, \n  om:integer, z:Float32Array, sz:integer, oz:integer, fcn:Function )\n    Applies a binary function to single-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a single-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n","base.strided.smskmax":"\nbase.strided.smskmax( N:integer, x:Float32Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask.\n","base.strided.smskmax.ndarray":"\nbase.strided.smskmax.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n","base.strided.smskmin":"\nbase.strided.smskmin( N:integer, x:Float32Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask.\n","base.strided.smskmin.ndarray":"\nbase.strided.smskmin.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n","base.strided.smskramp":"\nbase.strided.smskramp( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Evaluates the ramp function for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskramp.ndarray":"\nbase.strided.smskramp.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n  sy:integer, oy:integer )\n    Evaluates the ramp function for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n","base.strided.smskrange":"\nbase.strided.smskrange( N:integer, x:Float32Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask.\n","base.strided.smskrange.ndarray":"\nbase.strided.smskrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask and using alternative indexing semantics.\n","base.strided.smskrsqrt":"\nbase.strided.smskrsqrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Computes the reciprocal square root for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y`.\n","base.strided.smskrsqrt.ndarray":"\nbase.strided.smskrsqrt.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n  sy:integer, oy:integer )\n    Computes the reciprocal square root for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y` using alternative indexing semantics.\n","base.strided.smsksqrt":"\nbase.strided.smsksqrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Computes the principal square root for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y`.\n","base.strided.smsksqrt.ndarray":"\nbase.strided.smsksqrt.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n  sy:integer, oy:integer )\n    Computes the principal square root for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y` using alternative indexing semantics.\n","base.strided.smsktrunc":"\nbase.strided.smsktrunc( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward zero according to a strided mask array and assigns the results to\n    elements in a single-precision floating-point strided array `y`.\n","base.strided.smsktrunc.ndarray":"\nbase.strided.smsktrunc.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n  sy:integer, oy:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward zero according to a strided mask array and assigns the results to\n    elements in a single-precision floating-point strided array `y` using\n    alternative indexing semantics.\n","base.strided.snanmax":"\nbase.strided.snanmax( N:integer, x:Float32Array, strideX:integer )\n    Computes the maximum value of a single-precision floating-point strided\n    array, ignoring `NaN` values.\n","base.strided.snanmax.ndarray":"\nbase.strided.snanmax.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum value of a single-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanmaxabs":"\nbase.strided.snanmaxabs( N:integer, x:Float32Array, strideX:integer )\n    Computes the maximum absolute value of a single-precision floating-point\n    strided array, ignoring `NaN` values.\n","base.strided.snanmaxabs.ndarray":"\nbase.strided.snanmaxabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum absolute value of a single-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n","base.strided.snanmean":"\nbase.strided.snanmean( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values.\n","base.strided.snanmean.ndarray":"\nbase.strided.snanmean.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanmeanors":"\nbase.strided.snanmeanors( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.snanmeanors.ndarray":"\nbase.strided.snanmeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation and\n    alternative indexing semantics.\n","base.strided.snanmeanpn":"\nbase.strided.snanmeanpn( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction\n    algorithm.\n","base.strided.snanmeanpn.ndarray":"\nbase.strided.snanmeanpn.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction algorithm\n    and alternative indexing semantics.\n","base.strided.snanmeanwd":"\nbase.strided.snanmeanwd( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm.\n","base.strided.snanmeanwd.ndarray":"\nbase.strided.snanmeanwd.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n","base.strided.snanmin":"\nbase.strided.snanmin( N:integer, x:Float32Array, strideX:integer )\n    Computes the minimum value of a single-precision floating-point strided\n    array, ignoring `NaN` values.\n","base.strided.snanmin.ndarray":"\nbase.strided.snanmin.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the minimum value of a single-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanminabs":"\nbase.strided.snanminabs( N:integer, x:Float32Array, strideX:integer )\n    Computes the minimum absolute value of a single-precision floating-point\n    strided array, ignoring `NaN` values.\n","base.strided.snanminabs.ndarray":"\nbase.strided.snanminabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the minimum absolute value of a single-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n","base.strided.snanmskmax":"\nbase.strided.snanmskmax( N:integer, x:Float32Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask, ignoring `NaN` values.\n","base.strided.snanmskmax.ndarray":"\nbase.strided.snanmskmax.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n","base.strided.snanmskmin":"\nbase.strided.snanmskmin( N:integer, x:Float32Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask, ignoring `NaN` values.\n","base.strided.snanmskmin.ndarray":"\nbase.strided.snanmskmin.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n","base.strided.snanmskrange":"\nbase.strided.snanmskrange( N:integer, x:Float32Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask, ignoring `NaN` values.\n","base.strided.snanmskrange.ndarray":"\nbase.strided.snanmskrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask, ignoring `NaN` values and using alternative indexing\n    semantics.\n","base.strided.snanrange":"\nbase.strided.snanrange( N:integer, x:Float32Array, strideX:integer )\n    Computes the range of a single-precision floating-point strided array,\n    ignoring `NaN` values.\n","base.strided.snanrange.ndarray":"\nbase.strided.snanrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the range of a single-precision floating-point strided array,\n    ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanstdev":"\nbase.strided.snanstdev( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values.\n","base.strided.snanstdev.ndarray":"\nbase.strided.snanstdev.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and alternative indexing semantics.\n","base.strided.snanstdevch":"\nbase.strided.snanstdevch( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.snanstdevch.ndarray":"\nbase.strided.snanstdevch.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n","base.strided.snanstdevpn":"\nbase.strided.snanstdevpn( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.snanstdevpn.ndarray":"\nbase.strided.snanstdevpn.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n","base.strided.snanstdevtk":"\nbase.strided.snanstdevtk( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.snanstdevtk.ndarray":"\nbase.strided.snanstdevtk.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n","base.strided.snanstdevwd":"\nbase.strided.snanstdevwd( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using Welford's algorithm.\n","base.strided.snanstdevwd.ndarray":"\nbase.strided.snanstdevwd.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n","base.strided.snanstdevyc":"\nbase.strided.snanstdevyc( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass algorithm proposed by\n    Youngs and Cramer.\n","base.strided.snanstdevyc.ndarray":"\nbase.strided.snanstdevyc.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass algorithm proposed by\n    Youngs and Cramer and alternative indexing semantics.\n","base.strided.snansum":"\nbase.strided.snansum( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values.\n","base.strided.snansum.ndarray":"\nbase.strided.snansum.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snansumkbn":"\nbase.strided.snansumkbn( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n","base.strided.snansumkbn.ndarray":"\nbase.strided.snansumkbn.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n","base.strided.snansumkbn2":"\nbase.strided.snansumkbn2( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm.\n","base.strided.snansumkbn2.ndarray":"\nbase.strided.snansumkbn2.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n","base.strided.snansumors":"\nbase.strided.snansumors( N:integer, x:Float32Array, strideX:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.snansumors.ndarray":"\nbase.strided.snansumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation and alternative\n    indexing semantics.\n","base.strided.snansumpw":"\nbase.strided.snansumpw( N:integer, x:Float32Array, strideX:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation.\n","base.strided.snansumpw.ndarray":"\nbase.strided.snansumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation and alternative indexing\n    semantics.\n","base.strided.snanvariance":"\nbase.strided.snanvariance( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values.\n","base.strided.snanvariance.ndarray":"\nbase.strided.snanvariance.ndarray( N:integer, correction:number, \n  x:Float32Array, stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanvariancech":"\nbase.strided.snanvariancech( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.snanvariancech.ndarray":"\nbase.strided.snanvariancech.ndarray( N:integer, correction:number, \n  x:Float32Array, stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n","base.strided.snanvariancepn":"\nbase.strided.snanvariancepn( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.snanvariancepn.ndarray":"\nbase.strided.snanvariancepn.ndarray( N:integer, correction:number, \n  x:Float32Array, stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n","base.strided.snanvariancetk":"\nbase.strided.snanvariancetk( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.snanvariancetk.ndarray":"\nbase.strided.snanvariancetk.ndarray( N:integer, correction:number, \n  x:Float32Array, stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n","base.strided.snanvariancewd":"\nbase.strided.snanvariancewd( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using Welford's algorithm.\n","base.strided.snanvariancewd.ndarray":"\nbase.strided.snanvariancewd.ndarray( N:integer, correction:number, \n  x:Float32Array, stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using Welford's algorithm and alternative indexing\n    semantics.\n","base.strided.snanvarianceyc":"\nbase.strided.snanvarianceyc( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n    Cramer.\n","base.strided.snanvarianceyc.ndarray":"\nbase.strided.snanvarianceyc.ndarray( N:integer, correction:number, \n  x:Float32Array, stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n    Cramer and alternative indexing semantics.\n","base.strided.snrm2":"\nbase.strided.snrm2( N:integer, x:Float32Array, stride:integer )\n    Computes the L2-norm of a single-precision floating-point vector.\n","base.strided.snrm2.ndarray":"\nbase.strided.snrm2.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the L2-norm of a single-precision floating-point vector using\n    alternative indexing semantics.\n","base.strided.sramp":"\nbase.strided.sramp( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer )\n    Evaluates the ramp function for each element in a single-precision floating-\n    point strided array `x` and assigns the results to elements in a single-\n    precision floating-point strided array `y`.\n","base.strided.sramp.ndarray":"\nbase.strided.sramp.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Evaluates the ramp function for each element in a single-precision floating-\n    point strided array `x` and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.srange":"\nbase.strided.srange( N:integer, x:Float32Array, strideX:integer )\n    Computes the range of a single-precision floating-point strided array.\n","base.strided.srange.ndarray":"\nbase.strided.srange.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the range of a single-precision floating-point strided array using\n    alternative indexing semantics.\n","base.strided.srev":"\nbase.strided.srev( N:integer, x:Float32Array, stride:integer )\n    Reverses a single-precision floating-point strided array in-place.\n","base.strided.srev.ndarray":"\nbase.strided.srev.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Reverses a single-precision floating-point strided array in-place using\n    alternative indexing semantics.\n","base.strided.srsqrt":"\nbase.strided.srsqrt( N:integer, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Computes the reciprocal square root for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y`.\n","base.strided.srsqrt.ndarray":"\nbase.strided.srsqrt.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the reciprocal square root for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.sscal":"\nbase.strided.sscal( N:integer, alpha:number, x:Float32Array, stride:integer )\n    Multiplies a single-precision floating-point vector `x` by a constant\n    `alpha`.\n","base.strided.sscal.ndarray":"\nbase.strided.sscal.ndarray( N:integer, alpha:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Multiplies a single-precision floating-point vector `x` by a constant\n    `alpha` using alternative indexing semantics.\n","base.strided.ssort2hp":"\nbase.strided.ssort2hp( N:integer, order:number, x:Float32Array, \n  strideX:integer, y:Float32Array, strideY:integer )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using heapsort.\n","base.strided.ssort2hp.ndarray":"\nbase.strided.ssort2hp.ndarray( N:integer, order:number, x:Float32Array, \n  strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n  offsetY:integer )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using heapsort and alternative\n    indexing semantics.\n","base.strided.ssort2ins":"\nbase.strided.ssort2ins( N:integer, order:number, x:Float32Array, \n  strideX:integer, y:Float32Array, strideY:integer )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using insertion sort.\n","base.strided.ssort2ins.ndarray":"\nbase.strided.ssort2ins.ndarray( N:integer, order:number, x:Float32Array, \n  strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n  offsetY:integer )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using insertion sort and\n    alternative indexing semantics.\n","base.strided.ssort2sh":"\nbase.strided.ssort2sh( N:integer, order:number, x:Float32Array, \n  strideX:integer, y:Float32Array, strideY:integer )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using Shellsort.\n","base.strided.ssort2sh.ndarray":"\nbase.strided.ssort2sh.ndarray( N:integer, order:number, x:Float32Array, \n  strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n  offsetY:integer )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using Shellsort and alternative\n    indexing semantics.\n","base.strided.ssorthp":"\nbase.strided.ssorthp( N:integer, order:number, x:Float32Array, stride:integer )\n    Sorts a single-precision floating-point strided array using heapsort.\n","base.strided.ssorthp.ndarray":"\nbase.strided.ssorthp.ndarray( N:integer, order:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Sorts a single-precision floating-point strided array using heapsort and\n    alternative indexing semantics.\n","base.strided.ssortins":"\nbase.strided.ssortins( N:integer, order:number, x:Float32Array, stride:integer )\n    Sorts a single-precision floating-point strided array using insertion sort.\n","base.strided.ssortins.ndarray":"\nbase.strided.ssortins.ndarray( N:integer, order:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Sorts a single-precision floating-point strided array using insertion sort\n    and alternative indexing semantics.\n","base.strided.ssortsh":"\nbase.strided.ssortsh( N:integer, order:number, x:Float32Array, stride:integer )\n    Sorts a single-precision floating-point strided array using Shellsort.\n","base.strided.ssortsh.ndarray":"\nbase.strided.ssortsh.ndarray( N:integer, order:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Sorts a single-precision floating-point strided array using Shellsort and\n    alternative indexing semantics.\n","base.strided.ssqrt":"\nbase.strided.ssqrt( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer )\n    Computes the principal square root for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y`.\n","base.strided.ssqrt.ndarray":"\nbase.strided.ssqrt.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the principal square root for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.sstdev":"\nbase.strided.sstdev( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array.\n","base.strided.sstdev.ndarray":"\nbase.strided.sstdev.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using alternative indexing semantics.\n","base.strided.sstdevch":"\nbase.strided.sstdevch( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm.\n","base.strided.sstdevch.ndarray":"\nbase.strided.sstdevch.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n","base.strided.sstdevpn":"\nbase.strided.sstdevpn( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a two-pass algorithm.\n","base.strided.sstdevpn.ndarray":"\nbase.strided.sstdevpn.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a two-pass algorithm and alternative indexing semantics.\n","base.strided.sstdevtk":"\nbase.strided.sstdevtk( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass textbook algorithm.\n","base.strided.sstdevtk.ndarray":"\nbase.strided.sstdevtk.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass textbook algorithm and alternative indexing\n    semantics.\n","base.strided.sstdevwd":"\nbase.strided.sstdevwd( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using Welford's algorithm.\n","base.strided.sstdevwd.ndarray":"\nbase.strided.sstdevwd.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n","base.strided.sstdevyc":"\nbase.strided.sstdevyc( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.sstdevyc.ndarray":"\nbase.strided.sstdevyc.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer and\n    alternative indexing semantics.\n","base.strided.ssum":"\nbase.strided.ssum( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of single-precision floating-point strided array elements.\n","base.strided.ssum.ndarray":"\nbase.strided.ssum.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using alternative indexing semantics.\n","base.strided.ssumkbn":"\nbase.strided.ssumkbn( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm.\n","base.strided.ssumkbn.ndarray":"\nbase.strided.ssumkbn.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n","base.strided.ssumkbn2":"\nbase.strided.ssumkbn2( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.ssumkbn2.ndarray":"\nbase.strided.ssumkbn2.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n","base.strided.ssumors":"\nbase.strided.ssumors( N:integer, x:Float32Array, strideX:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using ordinary recursive summation.\n","base.strided.ssumors.ndarray":"\nbase.strided.ssumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using ordinary recursive summation and alternative indexing semantics.\n","base.strided.ssumpw":"\nbase.strided.ssumpw( N:integer, x:Float32Array, strideX:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation.\n","base.strided.ssumpw.ndarray":"\nbase.strided.ssumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation and alternative indexing semantics.\n","base.strided.sswap":"\nbase.strided.sswap( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer )\n    Interchanges two single-precision floating-point vectors.\n","base.strided.sswap.ndarray":"\nbase.strided.sswap.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Interchanges two single-precision floating-point vectors using alternative\n    indexing semantics.\n","base.strided.stdev":"\nbase.strided.stdev( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array.\n","base.strided.stdev.ndarray":"\nbase.strided.stdev.ndarray( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a strided array using alternative\n    indexing semantics.\n","base.strided.stdevch":"\nbase.strided.stdevch( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array using a one-pass trial\n    mean algorithm.\n","base.strided.stdevch.ndarray":"\nbase.strided.stdevch.ndarray( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a strided array using a one-pass trial\n    mean algorithm and alternative indexing semantics.\n","base.strided.stdevpn":"\nbase.strided.stdevpn( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array using a two-pass\n    algorithm.\n","base.strided.stdevpn.ndarray":"\nbase.strided.stdevpn.ndarray( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a strided array using a two-pass\n    algorithm and alternative indexing semantics.\n","base.strided.stdevtk":"\nbase.strided.stdevtk( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array using a one-pass textbook\n    algorithm.\n","base.strided.stdevtk.ndarray":"\nbase.strided.stdevtk.ndarray( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a strided array using a one-pass textbook\n    algorithm and alternative indexing semantics.\n","base.strided.stdevwd":"\nbase.strided.stdevwd( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array using Welford's\n    algorithm.\n","base.strided.stdevwd.ndarray":"\nbase.strided.stdevwd.ndarray( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a strided array using Welford's algorithm\n    and alternative indexing semantics.\n","base.strided.stdevyc":"\nbase.strided.stdevyc( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array using a one-pass\n    algorithm proposed by Youngs and Cramer.\n","base.strided.stdevyc.ndarray":"\nbase.strided.stdevyc.ndarray( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a strided array using a one-pass\n    algorithm proposed by Youngs and Cramer and alternative indexing semantics.\n","base.strided.strunc":"\nbase.strided.strunc( N:integer, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward zero and assigns the results to elements in a single-precision\n    floating-point strided array `y`.\n","base.strided.strunc.ndarray":"\nbase.strided.strunc.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward zero and assigns the results to elements in a single-precision\n    floating-point strided array `y` using alternative indexing semantics.\n","base.strided.svariance":"\nbase.strided.svariance( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array.\n","base.strided.svariance.ndarray":"\nbase.strided.svariance.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using alternative indexing semantics.\n","base.strided.svariancech":"\nbase.strided.svariancech( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass trial mean algorithm.\n","base.strided.svariancech.ndarray":"\nbase.strided.svariancech.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.svariancepn":"\nbase.strided.svariancepn( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using a two-pass algorithm.\n","base.strided.svariancepn.ndarray":"\nbase.strided.svariancepn.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using a two-pass algorithm and alternative indexing semantics.\n","base.strided.svariancetk":"\nbase.strided.svariancetk( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass textbook algorithm.\n","base.strided.svariancetk.ndarray":"\nbase.strided.svariancetk.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.svariancewd":"\nbase.strided.svariancewd( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using Welford's algorithm.\n","base.strided.svariancewd.ndarray":"\nbase.strided.svariancewd.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using Welford's algorithm and alternative indexing semantics.\n","base.strided.svarianceyc":"\nbase.strided.svarianceyc( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.svarianceyc.ndarray":"\nbase.strided.svarianceyc.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass algorithm proposed by Youngs and Cramer and alternative\n    indexing semantics.\n","base.strided.ternary":"\nbase.strided.ternary( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  fcn:Function )\n    Applies a ternary callback to strided input array elements and assigns\n    results to elements in a strided output array.\n","base.strided.ternary.ndarray":"\nbase.strided.ternary.ndarray( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  offsets:ArrayLikeObject<integer>, fcn:Function )\n    Applies a ternary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n","base.strided.unary":"\nbase.strided.unary( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  fcn:Function )\n    Applies a unary callback to elements in a strided input array and assigns\n    results to elements in a strided output array.\n","base.strided.unary.ndarray":"\nbase.strided.unary.ndarray( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  offsets:ArrayLikeObject<integer>, fcn:Function )\n    Applies a unary callback to elements in a strided input array and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n","base.strided.unaryBy":"\nbase.strided.unaryBy( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  fcn:Function, clbk:Function[, thisArg:any] )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array.\n","base.strided.unaryBy.ndarray":"\nbase.strided.unaryBy.ndarray( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  offsets:ArrayLikeObject<integer>, fcn:Function, clbk:Function[, thisArg:any] )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array using alternative indexing semantics.\n","base.strided.unaryDtypeSignatures":"\nbase.strided.unaryDtypeSignatures( dtypes1:ArrayLike<any>, \n  dtypes2:ArrayLike<any>[, options:Object] )\n    Generates a list of unary interface signatures from strided array data\n    types.\n","base.strided.unarySignatureCallbacks":"\nbase.strided.unarySignatureCallbacks( table:Object, signatures:ArrayLike<any> )\n    Assigns callbacks to unary interfaces according to type promotion rules.\n","base.strided.variance":"\nbase.strided.variance( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array.\n","base.strided.variance.ndarray":"\nbase.strided.variance.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array using alternative indexing\n    semantics.\n","base.strided.variancech":"\nbase.strided.variancech( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array using a one-pass trial mean\n    algorithm.\n","base.strided.variancech.ndarray":"\nbase.strided.variancech.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array using a one-pass trial mean\n    algorithm and alternative indexing semantics.\n","base.strided.variancepn":"\nbase.strided.variancepn( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array using a two-pass algorithm.\n","base.strided.variancepn.ndarray":"\nbase.strided.variancepn.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array using a two-pass algorithm and\n    alternative indexing semantics.\n","base.strided.variancetk":"\nbase.strided.variancetk( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array using a one-pass textbook\n    algorithm.\n","base.strided.variancetk.ndarray":"\nbase.strided.variancetk.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array using a one-pass textbook algorithm\n    and alternative indexing semantics.\n","base.strided.variancewd":"\nbase.strided.variancewd( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array using Welford's algorithm.\n","base.strided.variancewd.ndarray":"\nbase.strided.variancewd.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array using Welford's algorithm and\n    alternative indexing semantics.\n","base.strided.varianceyc":"\nbase.strided.varianceyc( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array using a one-pass algorithm proposed\n    by Youngs and Cramer.\n","base.strided.varianceyc.ndarray":"\nbase.strided.varianceyc.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array using a one-pass algorithm proposed\n    by Youngs and Cramer and alternative indexing semantics.\n","base.strided.zmap":"\nbase.strided.zmap( N:integer, x:Complex128Array, strideX:integer, \n  y:Complex128Array, strideY:integer, fcn:Function )\n    Applies a unary function to a double-precision complex floating-point\n    strided input array and assigns results to a double-precision complex\n    floating-point strided output array.\n","base.strided.zmap.ndarray":"\nbase.strided.zmap.ndarray( N:integer, x:Complex128Array, strideX:integer, \n  offsetX:integer, y:Complex128Array, strideY:integer, offsetY:integer, \n  fcn:Function )\n    Applies a unary function to a double-precision complex floating-point\n    strided input array and assigns results to a double-precision complex\n    floating-point strided output array using alternative indexing semantics.\n","base.str2multislice":"\nbase.str2multislice( str:string )\n    Parses a string-serialized MultiSlice object.\n","base.str2slice":"\nbase.str2slice( str:string )\n    Parses a string-serialized Slice object.\n","base.sub":"\nbase.sub( x:number, y:number )\n    Subtracts two double-precision floating-point numbers `x` and `y`.\n","base.subf":"\nbase.subf( x:number, y:number )\n    Subtracts two single-precision floating-point numbers `x` and `y`.\n","base.sumSeries":"\nbase.sumSeries( generator:Function[, options:Object] )\n    Sum the elements of the series given by the supplied function.\n","base.tan":"\nbase.tan( x:number )\n    Computes the tangent of a number.\n","base.tand":"\nbase.tand( x:number )\n    Computes the tangent of an angle measured in degrees.\n","base.tanh":"\nbase.tanh( x:number )\n    Computes the hyperbolic tangent of a double-precision floating-point number.\n","base.toBinaryString":"\nbase.toBinaryString( x:number )\n    Returns a string giving the literal bit representation of a double-precision\n    floating-point number.\n","base.toBinaryStringf":"\nbase.toBinaryStringf( x:float )\n    Returns a string giving the literal bit representation of a single-precision\n    floating-point number.\n","base.toBinaryStringUint8":"\nbase.toBinaryStringUint8( x:integer )\n    Returns a string giving the literal bit representation of an unsigned 8-bit\n    integer.\n","base.toBinaryStringUint16":"\nbase.toBinaryStringUint16( x:integer )\n    Returns a string giving the literal bit representation of an unsigned 16-bit\n    integer.\n","base.toBinaryStringUint32":"\nbase.toBinaryStringUint32( x:integer )\n    Returns a string giving the literal bit representation of an unsigned 32-bit\n    integer.\n","base.toWordf":"\nbase.toWordf( x:float )\n    Returns an unsigned 32-bit integer corresponding to the IEEE 754 binary\n    representation of a single-precision floating-point number.\n","base.toWords":"\nbase.toWords( x:number )\n    Splits a double-precision floating-point number into a higher order word\n    (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n","base.toWords.assign":"\nbase.toWords.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n  offset:integer )\n    Splits a double-precision floating-point number into a higher order word\n    (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer)\n    and assigns results to a provided output array.\n","base.transpose":"\nbase.transpose( x:ndarray )\n    Transposes a matrix (or a stack of matrices).\n","base.tribonacci":"\nbase.tribonacci( n:integer )\n    Computes the nth Tribonacci number.\n","base.trigamma":"\nbase.trigamma( x:number )\n    Evaluates the trigamma function.\n","base.trim":"\nbase.trim( str:string )\n    Trims whitespace from the beginning and end of a `string`.\n","base.trunc":"\nbase.trunc( x:number )\n    Rounds a double-precision floating-point number toward zero.\n","base.trunc2":"\nbase.trunc2( x:number )\n    Rounds a numeric value to the nearest power of two toward zero.\n","base.trunc10":"\nbase.trunc10( x:number )\n    Rounds a numeric value to the nearest power of ten toward zero.\n","base.truncateMiddle":"\nbase.truncateMiddle( str:string, len:integer, seq:string )\n    Truncates the middle UTF-16 code units of a string to return a string\n    having a specified length.\n","base.truncb":"\nbase.truncb( x:number, n:integer, b:integer )\n    Rounds a numeric value to the nearest multiple of `b^n` toward zero.\n","base.truncf":"\nbase.truncf( x:number )\n    Rounds a single-precision floating-point number toward zero.\n","base.truncn":"\nbase.truncn( x:number, n:integer )\n    Rounds a numeric value to the nearest multiple of `10^n` toward zero.\n","base.truncsd":"\nbase.truncsd( x:number, n:integer, b:integer )\n    Rounds a numeric value to the nearest number toward zero with `n`\n    significant figures.\n","base.uint32ToInt32":"\nbase.uint32ToInt32( x:integer )\n    Converts an unsigned 32-bit integer to a signed 32-bit integer.\n","base.umul":"\nbase.umul( a:integer, b:integer )\n    Performs C-like multiplication of two unsigned 32-bit integers.\n","base.umuldw":"\nbase.umuldw( a:integer, b:integer )\n    Multiplies two unsigned 32-bit integers and returns an array of two unsigned\n    32-bit integers which represents the unsigned 64-bit integer product.\n","base.umuldw.assign":"\nbase.umuldw.assign( a:integer, b:integer, out:Array|TypedArray|Object, \n  stride:integer, offset:integer )\n    Multiplies two unsigned 32-bit integers and assigns results representing\n    the unsigned 64-bit integer product to a provided output array.\n","base.uncapitalize":"\nbase.uncapitalize( str:string )\n    Lowercases the first character of a string.\n","base.uppercase":"\nbase.uppercase( str:string )\n    Converts a string to uppercase.\n","base.vercos":"\nbase.vercos( x:number )\n    Computes the versed cosine.\n","base.versin":"\nbase.versin( x:number )\n    Computes the versed sine.\n","base.wrap":"\nbase.wrap( v:number, min:number, max:number )\n    Wraps a value on the half-open interval `[min,max)`.\n","base.xlog1py":"\nbase.xlog1py( x:number, y:number )\n    Computes `x * ln(y+1)` so that the result is `0` if `x = 0`.\n","base.xlogy":"\nbase.xlogy( x:number, y:number )\n    Computes `x * ln(y)` so that the result is `0` if `x = 0`.\n","base.zeta":"\nbase.zeta( s:number )\n    Evaluates the Riemann zeta function as a function of a real variable `s`.\n","BERNDT_CPS_WAGES_1985":"\nBERNDT_CPS_WAGES_1985()\n    Returns a random sample of 534 workers from the Current Population Survey\n    (CPS) from 1985, including their wages and and other characteristics.\n","bifurcate":"\nbifurcate( collection:Array|TypedArray|Object, [options:Object,] \n  filter:Array|TypedArray|Object )\n    Splits values into two groups.\n","bifurcateBy":"\nbifurcateBy( collection:Array|TypedArray|Object, [options:Object,] \n  predicate:Function )\n    Splits values into two groups according to a predicate function.\n","bifurcateByAsync":"\nbifurcateByAsync( collection:Array|TypedArray|Object, [options:Object,] \n  predicate:Function, done:Function )\n    Splits values into two groups according to a predicate function.\n","bifurcateByAsync.factory":"\nbifurcateByAsync.factory( [options:Object,] predicate:Function )\n    Returns a function which splits values into two groups according to an\n    predicate function.\n","bifurcateIn":"\nbifurcateIn( obj:Object|Array|TypedArray, [options:Object,] predicate:Function )\n    Splits values into two groups according to a predicate function.\n","bifurcateOwn":"\nbifurcateOwn( obj:Object|Array|TypedArray, [options:Object,] \n  predicate:Function )\n    Splits values into two groups according to a predicate function.\n","BigInt":"\nBigInt( value:integer|string )\n    Returns a BigInt.\n","binomialTest":"\nbinomialTest( x:(number|Array[, n:Array<number>][, options:Object] )\n    Computes an exact test for the success probability in a Bernoulli\n    experiment.\n","Boolean":"\nBoolean( value:any )\n    Returns a boolean.\n","Boolean.prototype.toString":"\nBoolean.prototype.toString()\n    Returns a string representing the `Boolean` object.\n","Boolean.prototype.valueOf":"\nBoolean.prototype.valueOf()\n    Returns the primitive value of a `Boolean` object.\n","BooleanArray":"\nBooleanArray()\n    A Boolean array.\n\nBooleanArray( length:integer )\n    Creates a boolean array having a specified length.\n\nBooleanArray( booleanarray:BooleanArray )\n    Creates a boolean array from another boolean array.\n\nBooleanArray( typedarray:TypedArray )\n    Creates a boolean array from a typed array.\n\nBooleanArray( obj:Object )\n    Creates a boolean array from an array-like object or iterable.\n\nBooleanArray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a boolean array view of an ArrayBuffer.\n","BooleanArray.from":"\nBooleanArray.from( src:ArrayLike|Iterable[, clbk:Function[, thisArg:Any]] )\n    Creates a new boolean array from an array-like object or an iterable.\n","BooleanArray.of":"\nBooleanArray.of( element0:bool[, element1:bool[, ...elementN:bool]] )\n    Creates a new boolean array from a variable number of arguments.\n","BooleanArray.BYTES_PER_ELEMENT":"\nBooleanArray.BYTES_PER_ELEMENT\n    The size of each array element in bytes.\n","BooleanArray.name":"\nBooleanArray.name\n    Typed array constructor name.\n","BooleanArray.prototype.buffer":"\nBooleanArray.prototype.buffer\n    Pointer to the underlying data buffer.\n","BooleanArray.prototype.byteLength":"\nBooleanArray.prototype.byteLength\n    Size of the array in bytes.\n","BooleanArray.prototype.byteOffset":"\nBooleanArray.prototype.byteOffset\n    Offset (in bytes) of the array from the start of its underlying\n    ArrayBuffer.\n","BooleanArray.prototype.BYTES_PER_ELEMENT":"\nBooleanArray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element.\n","BooleanArray.prototype.length":"\nBooleanArray.prototype.length\n    The number of array elements.\n","BooleanArray.prototype.at":"\nBooleanArray.prototype.at( i:integer )\n    Returns an array element located at integer position (index) `i`, with\n    support for noth nonnegative and negative integer positions.\n","BooleanArray.prototype.copyWithin":"\nBooleanArray.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","BooleanArray.prototype.entries":"\nBooleanArray.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","BooleanArray.prototype.every":"\nBooleanArray.prototype.every( predicate:Function[, thisArg:Any] )\n    Returns a boolean indicating whether all elements in the array pass a test.\n","BooleanArray.prototype.fill":"\nBooleanArray.prototype.fill( value:boolean[, start:integer[, end:integer]] )\n    Returns a modified typed array filled with a fill value.\n","BooleanArray.prototype.filter":"\nBooleanArray.prototype.filter( predicate:Function[, thisArg:Any] )\n    Returns a new array containing the elements of an array which pass a test\n    implemented by a predicate function.\n","BooleanArray.prototype.find":"\nBooleanArray.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first element in an array for which a predicate function returns\n    a truthy value.\n","BooleanArray.prototype.findIndex":"\nBooleanArray.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first element in an array for which a predicate\n    function returns a truthy value.\n","BooleanArray.prototype.findLast":"\nBooleanArray.prototype.findLast( predicate:Function[, thisArg:Any] )\n    Returns the last element in an array for which a predicate function returns\n    a truthy value.\n","BooleanArray.prototype.findLastIndex":"\nBooleanArray.prototype.findLastIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the last element in an array for which a predicate\n    function returns a truthy value.\n","BooleanArray.prototype.forEach":"\nBooleanArray.prototype.forEach( clbk:Function[, thisArg:Any] )\n    Invokes a function once for each array element.\n","BooleanArray.prototype.get":"\nBooleanArray.prototype.get( i:integer )\n    Returns an array element located at integer position (index) `i`.\n","BooleanArray.prototype.includes":"\nBooleanArray.prototype.includes( searchElement:boolean[, fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a provided value.\n","BooleanArray.prototype.indexOf":"\nBooleanArray.prototype.indexOf( searchElement:boolean[, fromIndex:integer] )\n    Returns the first index at which a given element can be found.\n","BooleanArray.prototype.join":"\nBooleanArray.prototype.join( [separator:string] )\n    Returns a new string by concatenating all array elements separated by a\n    separator string.\n","BooleanArray.prototype.keys":"\nBooleanArray.prototype.keys()\n    Returns an iterator for iterating over each index key in a typed array.\n","BooleanArray.prototype.lastIndexOf":"\nBooleanArray.prototype.lastIndexOf( searchElement:boolean[, fromIndex:integer] )\n    Returns the last index at which a given element can be found.\n","BooleanArray.prototype.map":"\nBooleanArray.prototype.map( clbk:Function[, thisArg:Any] )\n    Returns a new array with each element being the result of a provided\n    callback function.\n","BooleanArray.prototype.reduce":"\nBooleanArray.prototype.reduce( reducerFn:Function[, initialValue:any] )\n    Applies a provided function to each element of the array, in order, passing\n    in the return value from the calculation on the preceding element and\n    returning the accumulated result upon completion.\n","BooleanArray.prototype.reduceRight":"\nBooleanArray.prototype.reduceRight( reducerFn:Function[, initialValue:any] )\n    Applies a provided function to each element of the array, in reverse order,\n    passing in the return value from the calculation on the preceding element\n    and returning the accumulated result upon completion.\n","BooleanArray.prototype.reverse":"\nBooleanArray.prototype.reverse()\n    Reverses the array *in-place*.\n","BooleanArray.prototype.set":"\nBooleanArray.prototype.set( v:bool|BooleanArray|ArrayLikeObject[, i:integer] )\n    Sets one or more array elements.\n","BooleanArray.prototype.slice":"\nBooleanArray.prototype.slice( [start:integer[, end:integer]] )\n    Copies a portion of a typed array to a new typed array.\n","BooleanArray.prototype.some":"\nBooleanArray.prototype.some( predicate:Function[, thisArg:Any] )\n    Returns a boolean indicating whether at least one element passes a test.\n","BooleanArray.prototype.sort":"\nBooleanArray.prototype.sort( [compareFunction:Function] )\n    Sorts an array in-place.\n","BooleanArray.prototype.subarray":"\nBooleanArray.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array view over the same underlying `ArrayBuffer` and\n    with the same underlying data type as the host array.\n","BooleanArray.prototype.toLocaleString":"\nBooleanArray.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n","BooleanArray.prototype.toReversed":"\nBooleanArray.prototype.toReversed()\n    Returns a new typed array containing the elements in reversed order.\n","BooleanArray.prototype.toSorted":"\nBooleanArray.prototype.toSorted( [compareFunction:Function] )\n    Returns a new typed array containing the elements in sorted order.\n","BooleanArray.prototype.toString":"\nBooleanArray.prototype.toString()\n    Serializes an array as a string.\n","BooleanArray.prototype.values":"\nBooleanArray.prototype.values()\n    Returns an iterator for iterating over each value in a typed array.\n","BooleanArray.prototype.with":"\nBooleanArray.prototype.with( index, value )\n    Returns a new typed array with the element at a provided index replaced\n    with a provided value.\n","broadcastArray":"\nbroadcastArray( x:ndarray, shape:ArrayLikeObject )\n    Broadcasts an ndarray to a specified shape.\n","broadcastArrays":"\nbroadcastArrays( ...arrays:ndarray|ArrayLikeObject<ndarray> )\n    Broadcasts ndarrays to a common shape.\n","Buffer":"\nBuffer\n\nBuffer( size:integer )\n    Allocates a buffer having a specified number of bytes.\n\nBuffer( buffer:Buffer )\n    Copies buffer data to a new Buffer instance.\n\nBuffer( array:Array )\n    Allocates a buffer using an array of octets.\n\nBuffer( str:string[, encoding:string] )\n    Allocates a buffer containing a provided string.\n","buffer2json":"\nbuffer2json( buffer:Buffer )\n    Returns a JSON representation of a buffer.\n","BYTE_ORDER":"\nBYTE_ORDER\n    Platform byte order.\n","camelcase":"\ncamelcase( str:string )\n    Converts a string to camel case.\n","capitalize":"\ncapitalize( str:string )\n    Capitalizes the first character in a string.\n","capitalizeKeys":"\ncapitalizeKeys( obj:Object )\n    Converts the first letter of each object key to uppercase.\n","CATALAN":"\nCATALAN\n    Catalan's constant.\n","CBRT_EPS":"\nCBRT_EPS\n    Cube root of double-precision floating-point epsilon.\n","CDC_NCHS_US_BIRTHS_1969_1988":"\nCDC_NCHS_US_BIRTHS_1969_1988()\n    Returns US birth data from 1969 to 1988, as provided by the Center for\n    Disease Control and Prevention's National Center for Health Statistics.\n","CDC_NCHS_US_BIRTHS_1994_2003":"\nCDC_NCHS_US_BIRTHS_1994_2003()\n    Returns US birth data from 1994 to 2003, as provided by the Center for\n    Disease Control and Prevention's National Center for Health Statistics.\n","CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013":"\nCDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n    Returns US infant mortality data, by race, from 1915 to 2013, as provided by\n    the Center for Disease Control and Prevention's National Center for Health\n    Statistics.\n","chdir":"\nchdir( path:string )\n    Changes the current working directory.\n","chi2gof":"\nchi2gof( x:ndarray|Array|TypedArray, y:ndarray|Array|TypedArray|string[, \n  ...args:number][, options:Object] )\n    Performs a chi-square goodness-of-fit test.\n","chi2test":"\nchi2test( x:ndarray|Array[, options:Object] )\n    Performs a chi-square independence test.\n","circarray2iterator":"\ncircarray2iterator( src:ArrayLikeObject[, options:Object][, mapFcn:Function[, \n  thisArg:any]] )\n    Returns an iterator which repeatedly iterates over the elements of an array-\n    like object.\n","circularArrayStream":"\ncircularArrayStream( src:ArrayLikeObject[, options:Object] )\n    Creates a readable stream from an array-like object which repeatedly\n    iterates over the provided value's elements.\n","circularArrayStream.factory":"\ncircularArrayStream.factory( [options:Object] )\n    Returns a function for creating readable streams from array-like objects\n    which repeatedly iterate over the elements of provided values.\n","circularArrayStream.objectMode":"\ncircularArrayStream.objectMode( src:ArrayLikeObject[, options:Object] )\n    Returns an \"objectMode\" readable stream from an array-like object which\n    repeatedly iterates over a provided value's elements.\n","CircularBuffer":"\nCircularBuffer( buffer:integer|ArrayLike )\n    Circular buffer constructor.\n","CircularBuffer.prototype.clear":"\nCircularBuffer.prototype.clear()\n    Clears a buffer.\n","CircularBuffer.prototype.count":"\nCircularBuffer.prototype.count\n    Read-only property returning the number of elements currently in the buffer.\n","CircularBuffer.prototype.full":"\nCircularBuffer.prototype.full\n    Read-only property returning a boolean indicating whether a circular buffer\n    is full.\n","CircularBuffer.prototype.iterator":"\nCircularBuffer.prototype.iterator( [niters:integer] )\n    Returns an iterator for iterating over a circular buffer.\n","CircularBuffer.prototype.length":"\nCircularBuffer.prototype.length\n    Read-only property returning the buffer length (i.e., capacity).\n","CircularBuffer.prototype.push":"\nCircularBuffer.prototype.push( value:any )\n    Adds a value to a circular buffer.\n","CircularBuffer.prototype.toArray":"\nCircularBuffer.prototype.toArray()\n    Returns an array of circular buffer values.\n","CircularBuffer.prototype.toJSON":"\nCircularBuffer.prototype.toJSON()\n    Serializes a circular buffer as JSON.\n","close":"\nclose( fd:integer, clbk:Function )\n    Asynchronously closes a file descriptor, so that the file descriptor no\n    longer refers to any file and may be reused.\n","close.sync":"\nclose.sync( fd:integer )\n    Synchronously closes a file descriptor.\n","CMUDICT":"\nCMUDICT( [options:Object] )\n    Returns datasets from the Carnegie Mellon Pronouncing Dictionary (CMUdict).\n","codePointAt":"\ncodePointAt( str:string, idx:integer[, backward:boolean] )\n    Returns a Unicode code point from a string at a specified position.\n","commonKeys":"\ncommonKeys( obj1:any, obj2:any[, ...obj:any] )\n    Returns the common own property names of two or more objects.\n","commonKeysIn":"\ncommonKeysIn( obj1:any, obj2:any[, ...obj:any] )\n    Returns the common own and inherited property names of two or more objects.\n","complex":"\ncomplex( real:number, imag:number[, dtype:string] )\n    Creates a complex number.\n","Complex64":"\nComplex64( real:number, imag:number )\n    64-bit complex number constructor.\n","Complex64.BYTES_PER_ELEMENT":"\nComplex64.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n","Complex64.prototype.BYTES_PER_ELEMENT":"\nComplex64.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n","Complex64.prototype.byteLength":"\nComplex64.prototype.byteLength\n    Length (in bytes) of a complex number.\n","COMPLEX64_NAN":"\nCOMPLEX64_NAN\n    Canonical single-precision complex floating-point NaN.\n","COMPLEX64_NUM_BYTES":"\nCOMPLEX64_NUM_BYTES\n    Size (in bytes) of a 64-bit complex number.\n","COMPLEX64_ZERO":"\nCOMPLEX64_ZERO\n    Single-precision complex floating-point zero.\n","Complex64Array":"\nComplex64Array()\n    A 64-bit complex number array.\n\nComplex64Array( length:integer )\n    Creates a 64-bit complex number array having a specified length.\n\nComplex64Array( complexarray:Complex64Array )\n    Creates a 64-bit complex number array from another complex number array.\n\nComplex64Array( typedarray:TypedArray )\n    Creates a 64-bit complex number array from a typed array\n    containing interleaved real and imaginary components.\n\nComplex64Array( obj:Object )\n    Creates a 64-bit complex number array from an array-like object or iterable.\n\nComplex64Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a 64-bit complex number array view of an ArrayBuffer.\n","Complex64Array.from":"\nComplex64Array.from( src:ArrayLike|Iterable[, clbk:Function[, thisArg:Any]] )\n    Creates a new 64-bit complex number array from an array-like object or an\n    iterable.\n","Complex64Array.of":"\nComplex64Array.of( element0:number[, element1:number[, ...elementN:number]] )\n    Creates a new 64-bit complex number array from a variable number of\n    arguments.\n","Complex64Array.BYTES_PER_ELEMENT":"\nComplex64Array.BYTES_PER_ELEMENT\n    The size of each array element in bytes.\n","Complex64Array.name":"\nComplex64Array.name\n    Typed array constructor name.\n","Complex64Array.prototype.buffer":"\nComplex64Array.prototype.buffer\n    Pointer to the underlying data buffer.\n","Complex64Array.prototype.byteLength":"\nComplex64Array.prototype.byteLength\n    Length of the array in bytes.\n","Complex64Array.prototype.byteOffset":"\nComplex64Array.prototype.byteOffset\n    Offset (in bytes) of the array from the start of its underlying\n    ArrayBuffer.\n","Complex64Array.prototype.BYTES_PER_ELEMENT":"\nComplex64Array.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element.\n","Complex64Array.prototype.length":"\nComplex64Array.prototype.length\n    The number of array elements.\n","Complex64Array.prototype.at":"\nComplex64Array.prototype.at( i:integer )\n    Returns an array element located at integer position (index) `i`, with\n    support for noth nonnegative and negative integer positions.\n","Complex64Array.prototype.copyWithin":"\nComplex64Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","Complex64Array.prototype.entries":"\nComplex64Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","Complex64Array.prototype.every":"\nComplex64Array.prototype.every( predicate:Function[, thisArg:Any] )\n    Returns a boolean indicating whether all elements in the array pass a test.\n","Complex64Array.prototype.fill":"\nComplex64Array.prototype.fill( value:Complex64[, start:integer[, end:integer]] )\n    Returns a modified typed array filled with a fill value.\n","Complex64Array.prototype.filter":"\nComplex64Array.prototype.filter( predicate:Function[, thisArg:Any] )\n    Returns a new array containing the elements of an array which pass a test\n    implemented by a predicate function.\n","Complex64Array.prototype.find":"\nComplex64Array.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first element in an array for which a predicate function\n    returns a truthy value.\n","Complex64Array.prototype.findIndex":"\nComplex64Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first element in an array for which a predicate\n    function returns a truthy value.\n","Complex64Array.prototype.findLast":"\nComplex64Array.prototype.findLast( predicate:Function[, thisArg:Any] )\n    Returns the last element in an array for which a predicate function returns\n    a truthy value.\n","Complex64Array.prototype.findLastIndex":"\nComplex64Array.prototype.findLastIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the last element in an array for which a predicate\n    function returns a truthy value.\n","Complex64Array.prototype.forEach":"\nComplex64Array.prototype.forEach( clbk:Function[, thisArg:Any] )\n    Invokes a function once for each array element.\n","Complex64Array.prototype.get":"\nComplex64Array.prototype.get( i:integer )\n    Returns an array element located at integer position (index) `i`.\n","Complex64Array.prototype.includes":"\nComplex64Array.prototype.includes( searchElement:Complex64[, \n  fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a provided value.\n","Complex64Array.prototype.indexOf":"\nComplex64Array.prototype.indexOf( searchElement:Complex64[, fromIndex:integer] )\n    Returns the first index at which a given element can be found.\n","Complex64Array.prototype.join":"\nComplex64Array.prototype.join( [separator:string] )\n    Returns a new string by concatenating all array elements separated by a\n    separator string.\n","Complex64Array.prototype.keys":"\nComplex64Array.prototype.keys()\n    Returns an iterator for iterating over each index key in a typed array.\n","Complex64Array.prototype.lastIndexOf":"\nComplex64Array.prototype.lastIndexOf( searchElement:Complex64[, \n  fromIndex:integer] )\n    Returns the last index at which a given element can be found.\n","Complex64Array.prototype.map":"\nComplex64Array.prototype.map( clbk:Function[, thisArg:Any] )\n    Returns a new array with each element being the result of a provided\n    callback function.\n","Complex64Array.prototype.reduce":"\nComplex64Array.prototype.reduce( reducerFn:Function[, initialValue:any] )\n    Applies a provided function to each element of the array, in order, passing\n    in the return value from the calculation on the preceding element and\n    returning the accumulated result upon completion.\n","Complex64Array.prototype.reduceRight":"\nComplex64Array.prototype.reduceRight( reducerFn:Function[, initialValue:any] )\n    Applies a provided function to each element of the array, in reverse order,\n    passing in the return value from the calculation on the preceding element\n    and returning the accumulated result upon completion.\n","Complex64Array.prototype.reverse":"\nComplex64Array.prototype.reverse()\n    Reverses the array *in-place*.\n","Complex64Array.prototype.set":"\nComplex64Array.prototype.set( z:Complex64|Complex64Array|ArrayLikeObject[, \n  i:integer] )\n    Sets one or more array elements.\n","Complex64Array.prototype.slice":"\nComplex64Array.prototype.slice( [start:integer[, end:integer]] )\n    Copies a portion of a typed array to a new typed array.\n","Complex64Array.prototype.some":"\nComplex64Array.prototype.some( predicate[, thisArg] )\n    Returns a boolean indicating whether at least one element passes a test.\n","Complex64Array.prototype.sort":"\nComplex64Array.prototype.sort( compareFunction:Function )\n    Sorts an array in-place.\n","Complex64Array.prototype.subarray":"\nComplex64Array.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array view over the same underlying `ArrayBuffer` and\n    with the same underlying data type as the host array.\n","Complex64Array.prototype.toLocaleString":"\nComplex64Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n","Complex64Array.prototype.toReversed":"\nComplex64Array.prototype.toReversed()\n    Returns a new typed array containing the elements in reversed order.\n","Complex64Array.prototype.toSorted":"\nComplex64Array.prototype.toSorted( compareFcn:Function )\n    Returns a new typed array containing the elements in sorted order.\n","Complex64Array.prototype.toString":"\nComplex64Array.prototype.toString()\n    Serializes an array as a string.\n","Complex64Array.prototype.values":"\nComplex64Array.prototype.values()\n    Returns an iterator for iterating over each value in a typed array.\n","Complex64Array.prototype.with":"\nComplex64Array.prototype.with( index, value )\n    Returns a new typed array with the element at a provided index replaced\n    with a provided value.\n","Complex128":"\nComplex128( real:number, imag:number )\n    128-bit complex number constructor.\n","Complex128.BYTES_PER_ELEMENT":"\nComplex128.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n","Complex128.prototype.BYTES_PER_ELEMENT":"\nComplex128.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n","Complex128.prototype.byteLength":"\nComplex128.prototype.byteLength\n    Length (in bytes) of a complex number.\n","COMPLEX128_NAN":"\nCOMPLEX128_NAN\n    Canonical double-precision complex floating-point NaN.\n","COMPLEX128_NUM_BYTES":"\nCOMPLEX128_NUM_BYTES\n    Size (in bytes) of a 128-bit complex number.\n","COMPLEX128_ZERO":"\nCOMPLEX128_ZERO\n    Double-precision complex floating-point zero.\n","Complex128Array":"\nComplex128Array()\n    A 128-bit complex number array.\n\nComplex128Array( length:integer )\n    Creates a 128-bit complex number array having a specified length.\n\nComplex128Array( complexarray:Complex128Array )\n    Creates a 64-bit complex number array from another complex number array.\n\nComplex128Array( typedarray:TypedArray )\n    Creates a 128-bit complex number array from a typed array\n    containing interleaved real and imaginary components.\n\nComplex128Array( obj:Object )\n    Creates a 128-bit complex number array from an array-like object or \n    iterable.\n\nComplex128Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a 128-bit complex number array view of an ArrayBuffer.\n","Complex128Array.from":"\nComplex128Array.from( src:ArrayLike|Iterable[, clbk:Function[, thisArg:Any]] )\n    Creates a new 128-bit complex number array from an array-like object or an\n    iterable.\n","Complex128Array.of":"\nComplex128Array.of( element0:number|ComplexLike[, \n  element1:number |ComplexLike[, ...elementN:number|ComplexLike]] )\n    Creates a new 128-bit complex number array from a variable number of\n    arguments.\n","Complex128Array.BYTES_PER_ELEMENT":"\nComplex128Array.BYTES_PER_ELEMENT\n    The size of each array element in bytes.\n","Complex128Array.name":"\nComplex128Array.name\n    Typed array constructor name.\n","Complex128Array.prototype.buffer":"\nComplex128Array.prototype.buffer\n    Pointer to the underlying data buffer.\n","Complex128Array.prototype.byteLength":"\nComplex128Array.prototype.byteLength\n    Length of the array in bytes.\n","Complex128Array.prototype.byteOffset":"\nComplex128Array.prototype.byteOffset\n    Offset (in bytes) of the array from the start of its underlying\n    ArrayBuffer.\n","Complex128Array.prototype.BYTES_PER_ELEMENT":"\nComplex128Array.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element.\n","Complex128Array.prototype.length":"\nComplex128Array.prototype.length\n    The number of array elements.\n","Complex128Array.prototype.at":"\nComplex128Array.prototype.at( i:integer )\n    Returns an array element located at integer position (index) `i`, with\n    support for both nonnegative and negative integer positions.\n","Complex128Array.prototype.copyWithin":"\nComplex128Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","Complex128Array.prototype.entries":"\nComplex128Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","Complex128Array.prototype.every":"\nComplex128Array.prototype.every( predicate:Function[, thisArg:Any] )\n    Returns a boolean indicating whether all elements in the array pass a test.\n","Complex128Array.prototype.fill":"\nComplex128Array.prototype.fill( value:Complex128[, start:integer[, \n  end:integer]] )\n    Returns a modified typed array filled with a fill value.\n","Complex128Array.prototype.filter":"\nComplex128Array.prototype.filter( predicate:Function[, thisArg:Any] )\n    Returns a new array containing the elements of an array which pass a test\n    implemented by a predicate function.\n","Complex128Array.prototype.find":"\nComplex128Array.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first element in an array for which a predicate function\n    returns a truthy value.\n","Complex128Array.prototype.findIndex":"\nComplex128Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first element in an array for which a predicate\n    function returns a truthy value.\n","Complex128Array.prototype.findLast":"\nComplex128Array.prototype.findLast( predicate:Function[, thisArg:Any] )\n    Returns the last element in an array for which a predicate function returns\n    a truthy value.\n","Complex128Array.prototype.findLastIndex":"\nComplex128Array.prototype.findLastIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the last element in an array for which a predicate\n    function returns a truthy value.\n","Complex128Array.prototype.forEach":"\nComplex128Array.prototype.forEach( clbk:Function[, thisArg:Any] )\n    Invokes a function once for each array element.\n","Complex128Array.prototype.get":"\nComplex128Array.prototype.get( i:integer )\n    Returns an array element located at integer position (index) `i`.\n","Complex128Array.prototype.includes":"\nComplex128Array.prototype.includes( searchElement:Complex128[, \n  fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a provided value.\n","Complex128Array.prototype.indexOf":"\nComplex128Array.prototype.indexOf( searchElement:Complex128[, \n  fromIndex:integer] )\n    Returns the first index at which a given element can be found.\n","Complex128Array.prototype.join":"\nComplex128Array.prototype.join( [separator:string] )\n    Returns a new string by concatenating all array elements separated by a\n    separator string.\n","Complex128Array.prototype.keys":"\nComplex128Array.prototype.keys()\n    Returns an iterator for iterating over each index key in a typed array.\n","Complex128Array.prototype.lastIndexOf":"\nComplex128Array.prototype.lastIndexOf( searchElement:Complex128[, \n  fromIndex:integer] )\n    Returns the last index at which a given element can be found.\n","Complex128Array.prototype.map":"\nComplex128Array.prototype.map( clbk:Function[, thisArg:Any] )\n    Returns a new array with each element being the result of a provided\n    callback function.\n","Complex128Array.prototype.reduce":"\nComplex128Array.prototype.reduce( reducerFn:Function[, initialValue:any] )\n    Applies a provided function to each element of the array, in order, passing\n    in the return value from the calculation on the preceding element and\n    returning the accumulated result upon completion.\n","Complex128Array.prototype.reduceRight":"\nComplex128Array.prototype.reduceRight( reducerFn:Function[, initialValue:any] )\n    Applies a provided function to each element of the array, in reverse order,\n    passing in the return value from the calculation on the preceding element\n    and returning the accumulated result upon completion.\n","Complex128Array.prototype.reverse":"\nComplex128Array.prototype.reverse()\n    Reverses the array *in-place*.\n","Complex128Array.prototype.set":"\nComplex128Array.prototype.set( z:Complex128|Complex128Array|ArrayLikeObject[, \n  i:integer] )\n    Sets one or more array elements.\n","Complex128Array.prototype.slice":"\nComplex128Array.prototype.slice( [start:integer[, end:integer]] )\n    Copies a portion of a typed array to a new typed array.\n","Complex128Array.prototype.some":"\nComplex128Array.prototype.some( predicate[, thisArg] )\n    Returns a boolean indicating whether at least one element passes a test.\n","Complex128Array.prototype.sort":"\nComplex128Array.prototype.sort( compareFunction:Function )\n    Sorts an array in-place.\n","Complex128Array.prototype.subarray":"\nComplex128Array.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array view over the same underlying `ArrayBuffer` and\n    with the same underlying data type as the host array.\n","Complex128Array.prototype.toLocaleString":"\nComplex128Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n","Complex128Array.prototype.toReversed":"\nComplex128Array.prototype.toReversed()\n    Returns a new typed array containing the elements in reversed order.\n","Complex128Array.prototype.toSorted":"\nComplex128Array.prototype.toSorted( compareFcn:Function )\n    Returns a new typed array containing the elements in sorted order.\n","Complex128Array.prototype.toString":"\nComplex128Array.prototype.toString()\n    Serializes an array as a string.\n","Complex128Array.prototype.values":"\nComplex128Array.prototype.values()\n    Returns an iterator for iterating over each value in a typed array.\n","Complex128Array.prototype.with":"\nComplex128Array.prototype.with( index, value )\n    Returns a new typed array with the element at a provided index replaced\n    with a provided value.\n","complexarray":"\ncomplexarray( [dtype:string] )\n    Creates a complex typed array.\n\ncomplexarray( length:integer[, dtype:string] )\n    Returns a complex number typed array having a specified length.\n\ncomplexarray( complexarray:ComplexArray[, dtype:string] )\n    Creates a complex number typed array from another complex number typed\n    array.\n\ncomplexarray( obj:Object[, dtype:string] )\n    Creates a complex number typed array from an array-like object or iterable.\n\ncomplexarray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n  dtype:string] )\n    Returns a complex number typed array view of an ArrayBuffer.\n","complexarrayCtors":"\ncomplexarrayCtors( dtype:string )\n    Returns a complex typed array constructor.\n","complexarrayDataTypes":"\ncomplexarrayDataTypes()\n    Returns a list of complex typed array data types.\n","complexCtors":"\ncomplexCtors( dtype:string )\n    Returns a complex number constructor.\n","complexDataType":"\ncomplexDataType( value:any )\n    Returns the data type of a complex number object.\n","complexDataTypes":"\ncomplexDataTypes()\n    Returns a list of complex number data types.\n","complexPromotionRules":"\ncomplexPromotionRules( [dtype1:string, dtype2:string] )\n    Returns the complex number data type with the smallest size and closest\n    \"kind\" to which data types can be safely cast.\n","compose":"\ncompose( ...f:Function )\n    Function composition.\n","composeAsync":"\ncomposeAsync( ...f:Function )\n    Function composition.\n","configdir":"\nconfigdir( [p:string] )\n    Returns a directory for user-specific configuration files.\n","conj":"\nconj( z:Complex128 )\n    Returns the complex conjugate of a double-precision complex floating-point\n    number.\n","conjf":"\nconjf( z:Complex64 )\n    Returns the complex conjugate of a single-precision complex floating-point\n    number.\n","constantcase":"\nconstantcase( str:string )\n    Converts a string to constant case.\n","constantFunction":"\nconstantFunction( val:any )\n    Creates a function which always returns the same value.\n","constantStream":"\nconstantStream( value:string|Buffer|Uint8Array|any[, options:Object] )\n    Returns a readable stream which always streams the same value.\n","constantStream.factory":"\nconstantStream.factory( [value:string|Buffer|Uint8Array|any, ][options:Object] )\n    Returns a function for creating readable streams which always stream the\n    same value.\n","constantStream.objectMode":"\nconstantStream.objectMode( value:any[, options:Object] )\n    Returns an \"objectMode\" readable stream which always streams the same value.\n","constructorName":"\nconstructorName( val:any )\n    Determines the name of a value's constructor.\n","contains":"\ncontains( val:ArrayLike, searchValue:any[, position:integer] )\n    Tests if an array-like value contains a search value.\n","convertArray":"\nconvertArray( arr:ArrayLikeObject, dtype:string )\n    Converts an input array to an array of a different data type.\n","convertArraySame":"\nconvertArraySame( x:ArrayLikeObject, y:Array|TypedArray )\n    Converts an input array to the same data type as a second input array.\n","convertPath":"\nconvertPath( from:string, to:string )\n    Converts between POSIX and Windows paths.\n","copy":"\ncopy( value:any[, level:integer] )\n    Copy or deep clone a value to an arbitrary depth.\n","copyBuffer":"\ncopyBuffer( buffer:Buffer )\n    Copies buffer data to a new Buffer instance.\n","countBy":"\ncountBy( collection:Array|TypedArray|Object, [options:Object,] \n  indicator:Function )\n    Groups values according to an indicator function and returns group counts.\n","countByAsync":"\ncountByAsync( collection:Array|TypedArray|Object, [options:Object,] \n  indicator:Function, done:Function )\n    Groups values according to an indicator function and returns group counts.\n","countByAsync.factory":"\ncountByAsync.factory( [options:Object,] indicator:Function )\n    Returns a function which groups values according to an indicator function\n    and returns group counts.\n","currentYear":"\ncurrentYear()\n    Returns the current year.\n","curry":"\ncurry( fcn:Function[, arity:integer][, thisArg:any] )\n    Transforms a function into a sequence of functions each accepting a single\n    argument.\n","curryRight":"\ncurryRight( fcn:Function[, arity:integer][, thisArg:any] )\n    Transforms a function into a sequence of functions each accepting a single\n    argument.\n","cwd":"\ncwd()\n    Returns the current working directory.\n","DALE_CHALL_NEW":"\nDALE_CHALL_NEW()\n    Returns a list of familiar English words.\n","datasets":"\ndatasets( name:string[, options:Object] )\n    Returns a dataset.\n","DataView":"\nDataView( buffer:ArrayBuffer|SharedArrayBuffer[, byteOffset:integer[, \n  byteLength:integer]] )\n    Returns a data view representing a provided array buffer.\n","DataView.prototype.buffer":"\nDataView.prototype.buffer\n    Read-only property which returns the underyling array buffer.\n","DataView.prototype.byteLength":"\nDataView.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the view.\n","DataView.prototype.byteOffset":"\nDataView.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the view to the\n    start of the underlying array buffer.\n","datespace":"\ndatespace( start:number, stop:number[, length:integer][ , options:Object] )\n    Generates an array of linearly spaced dates.\n","dayOfQuarter":"\ndayOfQuarter( [month:string|integer|Date[, day:integer, year:integer]] )\n    Returns the day of the quarter.\n","dayOfYear":"\ndayOfYear( [month:string|integer|Date[, day:integer, year:integer]] )\n    Returns the day of the year.\n","daysInMonth":"\ndaysInMonth( [month:string|integer|Date[, year:integer]] )\n    Returns the number of days in a month.\n","daysInYear":"\ndaysInYear( [value:integer|Date] )\n    Returns the number of days in a year according to the Gregorian calendar.\n","ddot":"\nddot( x:ndarray, y:ndarray[, dim:integer] )\n    Computes the dot product of two double-precision floating-point vectors.\n","debugSinkStream":"\ndebugSinkStream( [options:Object,] [clbk:Function] )\n    Returns a writable stream for debugging stream pipelines.\n","debugSinkStream.factory":"\ndebugSinkStream.factory( [options:Object] )\n    Returns a function for creating writable streams for debugging stream\n    pipelines.\n","debugSinkStream.objectMode":"\ndebugSinkStream.objectMode( [options:Object,] [clbk:Function] )\n    Returns an \"objectMode\" writable stream for debugging stream pipelines.\n","debugStream":"\ndebugStream( [options:Object,] [clbk:Function] )\n    Returns a transform stream for debugging stream pipelines.\n","debugStream.factory":"\ndebugStream.factory( [options:Object] )\n    Returns a function for creating transform streams for debugging stream\n    pipelines.\n","debugStream.objectMode":"\ndebugStream.objectMode( [options:Object,] [clbk:Function] )\n    Returns an \"objectMode\" transform stream for debugging stream pipelines.\n","decorateAfter":"\ndecorateAfter( fcn:Function, arity:integer, after:Function[, thisArg:any] )\n    Decorates a provided function such that the function's return value is\n    provided as an argument to another function.\n","decorateAfter.factory":"\ndecorateAfter.factory( fcn:Function, arity:integer, after:Function[, \n  thisArg:any] )\n    Uses code generation to decorate a provided function such that the\n    function's return value is provided as an argument to another function.\n","deepEqual":"\ndeepEqual( a:any, b:any )\n    Tests for deep equality between two values.\n","deepGet":"\ndeepGet( obj:ObjectLike, path:string|Array[, options:Object] )\n    Returns a nested property value.\n","deepGet.factory":"\ndeepGet.factory( path:string|Array[, options:Object] )\n    Creates a reusable deep get function.\n","deepHasOwnProp":"\ndeepHasOwnProp( value:any, path:string|Array[, options:Object] )\n    Returns a boolean indicating whether an object contains a nested key path.\n","deepHasOwnProp.factory":"\ndeepHasOwnProp.factory( path:string|Array[, options:Object] )\n    Returns a function which tests whether an object contains a nested key path.\n","deepHasProp":"\ndeepHasProp( value:any, path:string|Array[, options:Object] )\n    Returns a boolean indicating whether an object contains a nested key path,\n    either own or inherited.\n","deepHasProp.factory":"\ndeepHasProp.factory( path:string|Array[, options:Object] )\n    Returns a function which tests whether an object contains a nested key path,\n    either own or inherited.\n","deepPluck":"\ndeepPluck( arr:Array, path:string|Array[, options:Object] )\n    Extracts a nested property value from each element of an object array.\n","deepSet":"\ndeepSet( obj:ObjectLike, path:string|Array, value:any[, options:Object] )\n    Sets a nested property value.\n","deepSet.factory":"\ndeepSet.factory( path:string|Array[, options:Object] )\n    Creates a reusable deep set function.\n","defineMemoizedProperty":"\ndefineMemoizedProperty( obj:Object, prop:string|symbol, descriptor:Object )\n    Defines a memoized object property.\n","defineProperties":"\ndefineProperties( obj:Object, properties:Object )\n    Defines (and/or modifies) object properties.\n","defineProperty":"\ndefineProperty( obj:Object, prop:string|symbol, descriptor:Object )\n    Defines (or modifies) an object property.\n","dirname":"\ndirname( path:string )\n    Returns a directory name.\n","dotcase":"\ndotcase( str:string )\n    Converts a string to dot case.\n","DoublyLinkedList":"\nDoublyLinkedList()\n    Doubly linked list constructor.\n","doUntil":"\ndoUntil( fcn:Function, predicate:Function[, thisArg:any] )\n    Invokes a function until a test condition is true.\n","doUntilAsync":"\ndoUntilAsync( fcn:Function, predicate:Function, done:Function[, thisArg:any] )\n    Invokes a function until a test condition is true.\n","doUntilEach":"\ndoUntilEach( collection:Array|TypedArray|Object, fcn:Function, \n  predicate:Function[, thisArg:any] )\n    Until a test condition is true, invokes a function for each element in a\n    collection.\n","doUntilEachRight":"\ndoUntilEachRight( collection:Array|TypedArray|Object, fcn:Function, \n  predicate:Function[, thisArg:any] )\n    Until a test condition is true, invokes a function for each element in a\n    collection, iterating from right to left.\n","doWhile":"\ndoWhile( fcn:Function, predicate:Function[, thisArg:any] )\n    Invokes a function while a test condition is true.\n","doWhileAsync":"\ndoWhileAsync( fcn:Function, predicate:Function, done:Function[, thisArg:any] )\n    Invokes a function while a test condition is true.\n","doWhileEach":"\ndoWhileEach( collection:Array|TypedArray|Object, fcn:Function, \n  predicate:Function[, thisArg:any] )\n    While a test condition is true, invokes a function for each element in a\n    collection.\n","doWhileEachRight":"\ndoWhileEachRight( collection:Array|TypedArray|Object, fcn:Function, \n  predicate:Function[, thisArg:any] )\n    While a test condition is true, invokes a function for each element in a\n    collection, iterating from right to left.\n","dswap":"\ndswap( x:ndarray, y:ndarray[, dim:integer] )\n    Interchanges two double-precision floating-point vectors.\n","E":"\nE\n    Euler's number.\n","EMOJI":"\nEMOJI()\n    Returns an emoji database.\n","EMOJI_CODE_PICTO":"\nEMOJI_CODE_PICTO()\n    Returns an object mapping emoji codes to pictographs.\n","EMOJI_PICTO_CODE":"\nEMOJI_PICTO_CODE()\n    Returns an object mapping emoji pictographs to codes.\n","emptyStream":"\nemptyStream( [options:Object] )\n    Returns an \"empty\" readable stream.\n","emptyStream.factory":"\nemptyStream.factory( [options:Object] )\n    Returns a function for creating empty readable streams.\n","emptyStream.objectMode":"\nemptyStream.objectMode()\n    Returns an \"objectMode\" empty readable stream.\n","endsWith":"\nendsWith( str:string, search:string[, len:integer] )\n    Tests if a string ends with the characters of another string.\n","enumerableProperties":"\nenumerableProperties( value:any )\n    Returns an array of an object's own enumerable property names and symbols.\n","enumerablePropertiesIn":"\nenumerablePropertiesIn( value:any )\n    Returns an array of an object's own and inherited enumerable property names\n    and symbols.\n","enumerablePropertySymbols":"\nenumerablePropertySymbols( value:any )\n    Returns an array of an object's own enumerable symbol properties.\n","enumerablePropertySymbolsIn":"\nenumerablePropertySymbolsIn( value:any )\n    Returns an array of an object's own and inherited enumerable symbol\n    properties.\n","ENV":"\nENV\n    An object containing the user environment.\n","EPS":"\nEPS\n    Difference between one and the smallest value greater than one that can be\n    represented as a double-precision floating-point number.\n","error2json":"\nerror2json( error:Error )\n    Returns a JSON representation of an error object.\n","EULERGAMMA":"\nEULERGAMMA\n    The Euler-Mascheroni constant.\n","every":"\nevery( collection:Array|TypedArray|Object )\n    Tests whether all elements in a collection are truthy.\n","everyBy":"\neveryBy( collection:Array|TypedArray|Object, predicate:Function[, \n  thisArg:any ] )\n    Tests whether all elements in a collection pass a test implemented by a\n    predicate function.\n","everyByAsync":"\neveryByAsync( collection:Array|TypedArray|Object, [options:Object,] \n  predicate:Function, done:Function )\n    Tests whether all elements in a collection pass a test implemented by a\n    predicate function.\n","everyByAsync.factory":"\neveryByAsync.factory( [options:Object,] predicate:Function )\n    Returns a function which tests whether all elements in a collection pass a\n    test implemented by a predicate function.\n","everyByRight":"\neveryByRight( collection:Array|TypedArray|Object, predicate:Function[, \n  thisArg:any ] )\n    Tests whether all elements in a collection pass a test implemented by a\n    predicate function, iterating from right to left.\n","everyByRightAsync":"\neveryByRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n  predicate:Function, done:Function )\n    Tests whether all elements in a collection pass a test implemented by a\n    predicate function, iterating from right to left.\n","everyByRightAsync.factory":"\neveryByRightAsync.factory( [options:Object,] predicate:Function )\n    Returns a function which tests whether all elements in a collection pass a\n    test implemented by a predicate function, iterating from right to left.\n","everyInBy":"\neveryInBy( object:Object, predicate:Function[, thisArg:any ] )\n   Test whether all properties (own and inherited) of an object pass a\n   test implemented by a predicate function.\n","everyOwnBy":"\neveryOwnBy( object:Object, predicate:Function[, thisArg:any ] )\n    Tests whether every own property of an object pass a test implemented by a\n    predicate function.\n","evil":"\nevil( str:string )\n    Alias for `eval` global.\n","EXEC_PATH":"\nEXEC_PATH\n    Absolute pathname of the executable which started the current Node.js\n    process.\n","exists":"\nexists( path:string|Buffer, clbk:Function )\n    Asynchronously tests whether a path exists on the filesystem.\n","exists.sync":"\nexists.sync( path:string|Buffer )\n    Synchronously tests whether a path exists on the filesystem.\n","expandAcronyms":"\nexpandAcronyms( str:string )\n    Expands acronyms in a string.\n","expandContractions":"\nexpandContractions( str:string )\n    Expands all contractions to their formal equivalents.\n","extname":"\nextname( filename:string )\n    Returns a filename extension.\n","FancyArray":"\nFancyArray( dtype:string, buffer:ArrayLikeObject|TypedArray|Buffer, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  offset:integer, order:string[, options:Object] )\n    Returns a FancyArray instance.\n","FancyArray.prototype.byteLength":"\nFancyArray.prototype.byteLength\n    Size (in bytes) of the array (if known).\n","FancyArray.prototype.BYTES_PER_ELEMENT":"\nFancyArray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element (if known).\n","FancyArray.prototype.data":"\nFancyArray.prototype.data\n    Pointer to the underlying data buffer.\n","FancyArray.prototype.dtype":"\nFancyArray.prototype.dtype\n    Underlying data type.\n","FancyArray.prototype.flags":"\nFancyArray.prototype.flags\n    Meta information, such as information concerning the memory layout of the\n    array.\n","FancyArray.prototype.length":"\nFancyArray.prototype.length\n    Length of the array (i.e., number of elements).\n","FancyArray.prototype.ndims":"\nFancyArray.prototype.ndims\n    Number of dimensions.\n","FancyArray.prototype.offset":"\nFancyArray.prototype.offset\n    Index offset which specifies the buffer index at which to start iterating\n    over array elements.\n","FancyArray.prototype.order":"\nFancyArray.prototype.order\n    Array order.\n","FancyArray.prototype.shape":"\nFancyArray.prototype.shape\n    Array shape.\n","FancyArray.prototype.strides":"\nFancyArray.prototype.strides\n    Index strides which specify how to access data along corresponding array\n    dimensions.\n","FancyArray.prototype.get":"\nFancyArray.prototype.get( ...idx:integer )\n    Returns an array element specified according to provided subscripts.\n","FancyArray.prototype.iget":"\nFancyArray.prototype.iget( idx:integer )\n    Returns an array element located at a specified linear index.\n","FancyArray.prototype.set":"\nFancyArray.prototype.set( ...idx:integer, v:any )\n    Sets an array element specified according to provided subscripts.\n","FancyArray.prototype.iset":"\nFancyArray.prototype.iset( idx:integer, v:any )\n    Sets an array element located at a specified linear index.\n","FancyArray.prototype.toString":"\nFancyArray.prototype.toString()\n    Serializes a FancyArray as a string.\n","FancyArray.prototype.toJSON":"\nFancyArray.prototype.toJSON()\n    Serializes a FancyArray as a JSON object.\n","fastmath.abs":"\nfastmath.abs( x:number )\n    Computes an absolute value.\n","fastmath.acosh":"\nfastmath.acosh( x:number )\n    Computes the hyperbolic arccosine of a number.\n","fastmath.ampbm":"\nfastmath.ampbm( x:number, y:number )\n    Computes the hypotenuse using the alpha max plus beta min algorithm.\n","fastmath.ampbm.factory":"\nfastmath.ampbm.factory( alpha:number, beta:number, [nonnegative:boolean[, \n  ints:boolean]] )\n    Returns a function to compute a hypotenuse using the alpha max plus beta min\n    algorithm.\n","fastmath.asinh":"\nfastmath.asinh( x:number )\n    Computes the hyperbolic arcsine of a number.\n","fastmath.atanh":"\nfastmath.atanh( x:number )\n    Computes the hyperbolic arctangent of a number.\n","fastmath.hypot":"\nfastmath.hypot( x:number, y:number )\n    Computes the hypotenuse.\n","fastmath.log2Uint32":"\nfastmath.log2Uint32( x:uinteger )\n    Returns an approximate binary logarithm (base two) of an unsigned 32-bit\n    integer `x`.\n","fastmath.max":"\nfastmath.max( x:number, y:number )\n    Returns the maximum value.\n","fastmath.min":"\nfastmath.min( x:number, y:number )\n    Returns the minimum value.\n","fastmath.powint":"\nfastmath.powint( x:number, y:integer )\n    Evaluates the exponential function given a signed 32-bit integer exponent.\n","fastmath.sqrtUint32":"\nfastmath.sqrtUint32( x:uinteger )\n    Returns an approximate square root of an unsigned 32-bit integer `x`.\n","FEMALE_FIRST_NAMES_EN":"\nFEMALE_FIRST_NAMES_EN()\n    Returns a list of common female first names in English speaking countries.\n","FIFO":"\nFIFO()\n    First-in-first-out (FIFO) queue constructor.\n","filledarray":"\nfilledarray( [dtype:string] )\n    Creates a filled array.\n\nfilledarray( value:any, length:integer[, dtype:string] )\n    Returns a filled array having a specified length.\n\nfilledarray( value:any, array:ArrayLikeObject[, dtype:string] )\n    Creates a filled array from another array (or array-like object).\n\nfilledarray( value:any, iterable:Iterable[, dtype:string] )\n    Creates a filled array from an iterable.\n\nfilledarray( value:any, buffer:ArrayBuffer[, byteOffset:integer[, \n  length:integer]][, dtype:string] )\n    Returns a filled typed array view of an ArrayBuffer.\n","filledarrayBy":"\nfilledarrayBy( [dtype:string] )\n    Creates a filled array.\n\nfilledarrayBy( length:integer[, dtype:string], clbk:Function[, thisArg:any] )\n    Returns a filled array according to a provided callback function and having\n    a specified length.\n\nfilledarrayBy( array:ArrayLikeObject[, dtype:string], clbk:Function[, \n  thisArg:any] )\n    Creates a filled array from another array (or array-like object) according\n    to a provided callback function.\n\nfilledarrayBy( iterable:Iterable[, dtype:string], clbk:Function[, thisArg:any] )\n    Creates a filled array from an iterable according to a provided callback\n    function.\n\nfilledarrayBy( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n  dtype:string], clbk:Function[, thisArg:any] )\n    Returns a filled typed array view of an ArrayBuffer according to a provided\n    callback function.\n","filterArguments":"\nfilterArguments( fcn:Function, predicate:Function[, thisArg:any] )\n    Returns a function that applies arguments to a provided function according\n    to a predicate function.\n","find":"\nfind( arr:Array|TypedArray|string, [options:Object,] clbk:Function )\n    Finds elements in an array-like object that satisfy a test condition.\n","firstChar":"\nfirstChar( str:string[, n:integer][, options:Object] )\n    Returns the first character(s) of a string.\n","FIVETHIRTYEIGHT_FFQ":"\nFIVETHIRTYEIGHT_FFQ()\n    Returns FiveThirtyEight reader responses to a food frequency questionnaire\n    (FFQ).\n","flattenArray":"\nflattenArray( arr:ArrayLikeObject[, options:Object] )\n    Flattens an array.\n","flattenArray.factory":"\nflattenArray.factory( dims:ArrayLike<integer>[, options:Object] )\n    Returns a function for flattening arrays having specified dimensions.\n","flattenObject":"\nflattenObject( obj:ObjectLike[, options:Object] )\n    Flattens an object.\n","flattenObject.factory":"\nflattenObject.factory( [options:Object] )\n    Returns a function to flatten an object.\n","flignerTest":"\nflignerTest( ...x:Array[, options:Object] )\n    Computes the Fligner-Killeen test for equal variances.\n","FLOAT_WORD_ORDER":"\nFLOAT_WORD_ORDER\n    Platform float word order.\n","FLOAT16_CBRT_EPS":"\nFLOAT16_CBRT_EPS\n    Cube root of half-precision floating-point epsilon.\n","FLOAT16_EPS":"\nFLOAT16_EPS\n    Difference between one and the smallest value greater than one that can be\n    represented as a half-precision floating-point number.\n","FLOAT16_EXPONENT_BIAS":"\nFLOAT16_EXPONENT_BIAS\n    The bias of a half-precision floating-point number's exponent.\n","FLOAT16_MAX":"\nFLOAT16_MAX\n    Maximum half-precision floating-point number.\n","FLOAT16_MAX_SAFE_INTEGER":"\nFLOAT16_MAX_SAFE_INTEGER\n    Maximum safe half-precision floating-point integer.\n","FLOAT16_MIN_SAFE_INTEGER":"\nFLOAT16_MIN_SAFE_INTEGER\n    Minimum safe half-precision floating-point integer.\n","FLOAT16_NINF":"\nFLOAT16_NINF\n    Half-precision floating-point negative infinity.\n","FLOAT16_NUM_BYTES":"\nFLOAT16_NUM_BYTES\n    Size (in bytes) of a half-precision floating-point number.\n","FLOAT16_PINF":"\nFLOAT16_PINF\n    Half-precision floating-point positive infinity.\n","FLOAT16_PRECISION":"\nFLOAT16_PRECISION\n    Effective number of bits in the significand of a half-precision floating-\n    point number.\n","FLOAT16_SMALLEST_NORMAL":"\nFLOAT16_SMALLEST_NORMAL\n    Smallest positive normalized half-precision floating-point number.\n","FLOAT16_SMALLEST_SUBNORMAL":"\nFLOAT16_SMALLEST_SUBNORMAL\n    Smallest positive denormalized half-precision floating-point number.\n","FLOAT16_SQRT_EPS":"\nFLOAT16_SQRT_EPS\n    Square root of half-precision floating-point epsilon.\n","FLOAT32_ABS_MASK":"\nFLOAT32_ABS_MASK\n    Mask for excluding the sign bit of a single-precision floating-point number.\n","FLOAT32_CBRT_EPS":"\nFLOAT32_CBRT_EPS\n    Cube root of single-precision floating-point epsilon.\n","FLOAT32_E":"\nFLOAT32_E\n    Euler's number.\n","FLOAT32_EPS":"\nFLOAT32_EPS\n    Difference between one and the smallest value greater than one that can be\n    represented as a single-precision floating-point number.\n","FLOAT32_EXPONENT_BIAS":"\nFLOAT32_EXPONENT_BIAS\n    The bias of a single-precision floating-point number's exponent.\n","FLOAT32_EXPONENT_MASK":"\nFLOAT32_EXPONENT_MASK\n    Mask for the exponent of a single-precision floating-point number.\n","FLOAT32_FOURTH_PI":"\nFLOAT32_FOURTH_PI\n    One fourth times the mathematical constant `π`.\n","FLOAT32_HALF_LN_TWO":"\nFLOAT32_HALF_LN_TWO\n    One half times the natural logarithm of 2 as a single-precision\n    floating-point number.\n","FLOAT32_HALF_PI":"\nFLOAT32_HALF_PI\n    One half times the mathematical constant `π`.\n","FLOAT32_LN_HALF":"\nFLOAT32_LN_HALF\n    Natural logarithm of `1/2` as a single-precision floating-point number.\n","FLOAT32_LN_PI":"\nFLOAT32_LN_PI\n    Natural logarithm of the mathematical constant `π` as a single-precision\n    floating-point number.\n","FLOAT32_LN_TEN":"\nFLOAT32_LN_TEN\n    Natural logarithm of `10` as a single-precision floating-point number.\n","FLOAT32_LN_TWO":"\nFLOAT32_LN_TWO\n    Natural logarithm of `2` as a single-precision floating-point number.\n","FLOAT32_MAX":"\nFLOAT32_MAX\n    Maximum single-precision floating-point number.\n","FLOAT32_MAX_BASE2_EXPONENT":"\nFLOAT32_MAX_BASE2_EXPONENT\n    The maximum biased base 2 exponent for a single-precision floating-point\n    number.\n","FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL\n    The maximum biased base 2 exponent for a subnormal single-precision\n    floating-point number.\n","FLOAT32_MAX_BASE10_EXPONENT":"\nFLOAT32_MAX_BASE10_EXPONENT\n    The maximum base 10 exponent for a single-precision floating-point number.\n","FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL\n    The maximum base 10 exponent for a subnormal single-precision floating-point\n    number.\n","FLOAT32_MAX_SAFE_FIBONACCI":"\nFLOAT32_MAX_SAFE_FIBONACCI\n    Maximum safe Fibonacci number when stored in single-precision floating-point\n    format.\n","FLOAT32_MAX_SAFE_INTEGER":"\nFLOAT32_MAX_SAFE_INTEGER\n    Maximum safe single-precision floating-point integer.\n","FLOAT32_MAX_SAFE_NTH_FACTORIAL":"\nFLOAT32_MAX_SAFE_NTH_FACTORIAL\n    Maximum safe nth factorial when stored in single-precision floating-\n    point format.\n","FLOAT32_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT32_MAX_SAFE_NTH_FIBONACCI\n    Maximum safe nth Fibonacci number when stored in single-precision floating-\n    point format.\n","FLOAT32_MAX_SAFE_NTH_LUCAS":"\nFLOAT32_MAX_SAFE_NTH_LUCAS\n    Maximum safe nth Lucas number when stored in single-precision floating-point\n    format.\n","FLOAT32_MIN_BASE2_EXPONENT":"\nFLOAT32_MIN_BASE2_EXPONENT\n    The minimum biased base 2 exponent for a normalized single-precision\n    floating-point number.\n","FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL\n    The minimum biased base 2 exponent for a subnormal single-precision\n    floating-point number.\n","FLOAT32_MIN_BASE10_EXPONENT":"\nFLOAT32_MIN_BASE10_EXPONENT\n    The minimum base 10 exponent for a normal single-precision floating-\n    point number.\n","FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL\n    The minimum base 10 exponent for a subnormal single-precision floating-\n    point number.\n","FLOAT32_MIN_SAFE_INTEGER":"\nFLOAT32_MIN_SAFE_INTEGER\n    Minimum safe single-precision floating-point integer.\n","FLOAT32_NAN":"\nFLOAT32_NAN\n    Single-precision floating-point NaN.\n","FLOAT32_NINF":"\nFLOAT32_NINF\n    Single-precision floating-point negative infinity.\n","FLOAT32_NUM_BYTES":"\nFLOAT32_NUM_BYTES\n    Size (in bytes) of a single-precision floating-point number.\n","FLOAT32_PHI":"\nFLOAT32_PHI\n    Golden ratio.\n","FLOAT32_PI":"\nFLOAT32_PI\n    The mathematical constant `π`.\n","FLOAT32_PINF":"\nFLOAT32_PINF\n    Single-precision floating-point positive infinity.\n","FLOAT32_PRECISION":"\nFLOAT32_PRECISION\n    Effective number of bits in the significand of a single-precision floating-\n    point number.\n","FLOAT32_SIGN_MASK":"\nFLOAT32_SIGN_MASK\n    Mask for the sign bit of a single-precision floating-point number.\n","FLOAT32_SIGNIFICAND_MASK":"\nFLOAT32_SIGNIFICAND_MASK\n    Mask for the significand of a single-precision floating-point number.\n","FLOAT32_SMALLEST_NORMAL":"\nFLOAT32_SMALLEST_NORMAL\n    Smallest positive normalized single-precision floating-point number.\n","FLOAT32_SMALLEST_SUBNORMAL":"\nFLOAT32_SMALLEST_SUBNORMAL\n    Smallest positive denormalized single-precision floating-point number.\n","FLOAT32_SQRT_EPS":"\nFLOAT32_SQRT_EPS\n    Square root of single-precision floating-point epsilon.\n","FLOAT32_SQRT_HALF":"\nFLOAT32_SQRT_HALF\n    Square root of `1/2` as a single-precision floating-point number.\n","FLOAT32_SQRT_HALF_PI":"\nFLOAT32_SQRT_HALF_PI\n    Square root of `π` divided by `2` as a single-precision \n    floating-point number.\n","FLOAT32_SQRT_PHI":"\nFLOAT32_SQRT_PHI\n    Square root of the golden ratio as a single-precision floating-point number.\n","FLOAT32_SQRT_PI":"\nFLOAT32_SQRT_PI\n    Square root of the mathematical constant `π` as a single-precision\n    floating-point number.\n","FLOAT32_SQRT_THREE":"\nFLOAT32_SQRT_THREE\n    Square root of `3` as a single-precision floating-point number.\n","FLOAT32_SQRT_TWO":"\nFLOAT32_SQRT_TWO\n    Square root of `2` as a single-precision floating-point number.\n","FLOAT32_SQRT_TWO_PI":"\nFLOAT32_SQRT_TWO_PI\n    Square root of the `π` times `2` as single-precision floating-point number.\n","FLOAT32_TWO_PI":"\nFLOAT32_TWO_PI\n    The mathematical constant `π` times `2`.\n","Float32Array":"\nFloat32Array()\n    A typed array constructor which returns a typed array representing an array\n    of single-precision floating-point numbers in the platform byte order.\n\nFloat32Array( length:integer )\n    Returns a typed array having a specified length.\n\nFloat32Array( typedarray:TypedArray )\n    Creates a typed array from another typed array.\n\nFloat32Array( obj:Object )\n    Creates a typed array from an array-like object or iterable.\n\nFloat32Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a typed array view of an ArrayBuffer.\n","Float32Array.from":"\nFloat32Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n    Creates a new typed array from an array-like object or an iterable.\n","Float32Array.of":"\nFloat32Array.of( element0:number[, element1:number[, ...elementN:number]] )\n    Creates a new typed array from a variable number of arguments.\n","Float32Array.BYTES_PER_ELEMENT":"\nFloat32Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Float32Array.name":"\nFloat32Array.name\n    Typed array constructor name.\n","Float32Array.prototype.buffer":"\nFloat32Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n","Float32Array.prototype.byteLength":"\nFloat32Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n","Float32Array.prototype.byteOffset":"\nFloat32Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n","Float32Array.prototype.BYTES_PER_ELEMENT":"\nFloat32Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Float32Array.prototype.length":"\nFloat32Array.prototype.length\n    Read-only property which returns the number of view elements.\n","Float32Array.prototype.copyWithin":"\nFloat32Array.prototype.copyWithin( target:integer, start:integer[, \n  end:integer] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","Float32Array.prototype.entries":"\nFloat32Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","Float32Array.prototype.every":"\nFloat32Array.prototype.every( predicate:Function[, thisArg:Any] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n","Float32Array.prototype.fill":"\nFloat32Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n","Float32Array.prototype.filter":"\nFloat32Array.prototype.filter( predicate:Function[, thisArg:Any] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n","Float32Array.prototype.find":"\nFloat32Array.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n","Float32Array.prototype.findIndex":"\nFloat32Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n","Float32Array.prototype.forEach":"\nFloat32Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n    Invokes a callback for each array element.\n","Float32Array.prototype.includes":"\nFloat32Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a search element.\n","Float32Array.prototype.indexOf":"\nFloat32Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n","Float32Array.prototype.join":"\nFloat32Array.prototype.join( [separator:string] )\n    Serializes an array by joining all array elements as a string.\n","Float32Array.prototype.keys":"\nFloat32Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n","Float32Array.prototype.lastIndexOf":"\nFloat32Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n","Float32Array.prototype.map":"\nFloat32Array.prototype.map( fcn:Function[, thisArg:Any] )\n    Maps each array element to an element in a new typed array.\n","Float32Array.prototype.reduce":"\nFloat32Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n","Float32Array.prototype.reduceRight":"\nFloat32Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n","Float32Array.prototype.reverse":"\nFloat32Array.prototype.reverse()\n    Reverses an array *in-place*.\n","Float32Array.prototype.set":"\nFloat32Array.prototype.set( arr:ArrayLike[, offset:integer] )\n    Sets array elements.\n","Float32Array.prototype.slice":"\nFloat32Array.prototype.slice( [begin:integer[, end:integer]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n","Float32Array.prototype.some":"\nFloat32Array.prototype.some( predicate:Function[, thisArg:Any] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n","Float32Array.prototype.sort":"\nFloat32Array.prototype.sort( [compareFunction:Function] )\n    Sorts an array *in-place*.\n","Float32Array.prototype.subarray":"\nFloat32Array.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n","Float32Array.prototype.toLocaleString":"\nFloat32Array.prototype.toLocaleString( [locales:string|Array[, \n  options:Object]] )\n    Serializes an array as a locale-specific string.\n","Float32Array.prototype.toString":"\nFloat32Array.prototype.toString()\n    Serializes an array as a string.\n","Float32Array.prototype.values":"\nFloat32Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n","FLOAT64_EXPONENT_BIAS":"\nFLOAT64_EXPONENT_BIAS\n    The bias of a double-precision floating-point number's exponent.\n","FLOAT64_HIGH_WORD_ABS_MASK":"\nFLOAT64_HIGH_WORD_ABS_MASK\n    High word mask for excluding the sign bit of a double-precision floating-\n    point number.\n","FLOAT64_HIGH_WORD_EXPONENT_MASK":"\nFLOAT64_HIGH_WORD_EXPONENT_MASK\n    High word mask for the exponent of a double-precision floating-point number.\n","FLOAT64_HIGH_WORD_SIGN_MASK":"\nFLOAT64_HIGH_WORD_SIGN_MASK\n    High word mask for the sign bit of a double-precision floating-point number.\n","FLOAT64_HIGH_WORD_SIGNIFICAND_MASK":"\nFLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n    High word mask for the significand of a double-precision floating-point\n    number.\n","FLOAT64_MAX":"\nFLOAT64_MAX\n    Maximum double-precision floating-point number.\n","FLOAT64_MAX_BASE2_EXPONENT":"\nFLOAT64_MAX_BASE2_EXPONENT\n    The maximum biased base 2 exponent for a double-precision floating-point\n    number.\n","FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n    The maximum biased base 2 exponent for a subnormal double-precision\n    floating-point number.\n","FLOAT64_MAX_BASE10_EXPONENT":"\nFLOAT64_MAX_BASE10_EXPONENT\n    The maximum base 10 exponent for a double-precision floating-point number.\n","FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n    The maximum base 10 exponent for a subnormal double-precision floating-point\n    number.\n","FLOAT64_MAX_LN":"\nFLOAT64_MAX_LN\n    Natural logarithm of the maximum double-precision floating-point number.\n","FLOAT64_MAX_SAFE_FIBONACCI":"\nFLOAT64_MAX_SAFE_FIBONACCI\n    Maximum safe Fibonacci number when stored in double-precision floating-point\n    format.\n","FLOAT64_MAX_SAFE_INTEGER":"\nFLOAT64_MAX_SAFE_INTEGER\n    Maximum safe double-precision floating-point integer.\n","FLOAT64_MAX_SAFE_LUCAS":"\nFLOAT64_MAX_SAFE_LUCAS\n    Maximum safe Lucas number when stored in double-precision floating-point\n    format.\n","FLOAT64_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT64_MAX_SAFE_NTH_FIBONACCI\n    Maximum safe nth Fibonacci number when stored in double-precision floating-\n    point format.\n","FLOAT64_MAX_SAFE_NTH_LUCAS":"\nFLOAT64_MAX_SAFE_NTH_LUCAS\n    Maximum safe nth Lucas number when stored in double-precision floating-point\n    format.\n","FLOAT64_MIN_BASE2_EXPONENT":"\nFLOAT64_MIN_BASE2_EXPONENT\n    The minimum biased base 2 exponent for a normalized double-precision\n    floating-point number.\n","FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n    The minimum biased base 2 exponent for a subnormal double-precision\n    floating-point number.\n","FLOAT64_MIN_BASE10_EXPONENT":"\nFLOAT64_MIN_BASE10_EXPONENT\n    The minimum base 10 exponent for a normalized double-precision floating-\n    point number.\n","FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n    The minimum base 10 exponent for a subnormal double-precision floating-\n    point number.\n","FLOAT64_MIN_LN":"\nFLOAT64_MIN_LN\n    Natural logarithm of the smallest normalized double-precision floating-point\n    number.\n","FLOAT64_MIN_SAFE_INTEGER":"\nFLOAT64_MIN_SAFE_INTEGER\n    Minimum safe double-precision floating-point integer.\n","FLOAT64_NUM_BYTES":"\nFLOAT64_NUM_BYTES\n    Size (in bytes) of a double-precision floating-point number.\n","FLOAT64_PRECISION":"\nFLOAT64_PRECISION\n    Effective number of bits in the significand of a double-precision floating-\n    point number.\n","FLOAT64_SMALLEST_NORMAL":"\nFLOAT64_SMALLEST_NORMAL\n    Smallest positive normalized double-precision floating-point number.\n","FLOAT64_SMALLEST_SUBNORMAL":"\nFLOAT64_SMALLEST_SUBNORMAL\n    Smallest positive denormalized double-precision floating-point number.\n","Float64Array":"\nFloat64Array()\n    A typed array constructor which returns a typed array representing an array\n    of double-precision floating-point numbers in the platform byte order.\n\nFloat64Array( length:integer )\n    Returns a typed array having a specified length.\n\nFloat64Array( typedarray:TypedArray )\n    Creates a typed array from another typed array.\n\nFloat64Array( obj:Object )\n    Creates a typed array from an array-like object or iterable.\n\nFloat64Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a typed array view of an ArrayBuffer.\n","Float64Array.from":"\nFloat64Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n    Creates a new typed array from an array-like object or an iterable.\n","Float64Array.of":"\nFloat64Array.of( element0:number[, element1:number[, ...elementN:number]] )\n    Creates a new typed array from a variable number of arguments.\n","Float64Array.BYTES_PER_ELEMENT":"\nFloat64Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Float64Array.name":"\nFloat64Array.name\n    Typed array constructor name.\n","Float64Array.prototype.buffer":"\nFloat64Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n","Float64Array.prototype.byteLength":"\nFloat64Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n","Float64Array.prototype.byteOffset":"\nFloat64Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n","Float64Array.prototype.BYTES_PER_ELEMENT":"\nFloat64Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Float64Array.prototype.length":"\nFloat64Array.prototype.length\n    Read-only property which returns the number of view elements.\n","Float64Array.prototype.copyWithin":"\nFloat64Array.prototype.copyWithin( target:integer, start:integer[, \n  end:integer] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","Float64Array.prototype.entries":"\nFloat64Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","Float64Array.prototype.every":"\nFloat64Array.prototype.every( predicate:Function[, thisArg:Any] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n","Float64Array.prototype.fill":"\nFloat64Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n","Float64Array.prototype.filter":"\nFloat64Array.prototype.filter( predicate:Function[, thisArg:Any] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n","Float64Array.prototype.find":"\nFloat64Array.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n","Float64Array.prototype.findIndex":"\nFloat64Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n","Float64Array.prototype.forEach":"\nFloat64Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n    Invokes a callback for each array element.\n","Float64Array.prototype.includes":"\nFloat64Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a search element.\n","Float64Array.prototype.indexOf":"\nFloat64Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n","Float64Array.prototype.join":"\nFloat64Array.prototype.join( [separator:string] )\n    Serializes an array by joining all array elements as a string.\n","Float64Array.prototype.keys":"\nFloat64Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n","Float64Array.prototype.lastIndexOf":"\nFloat64Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n","Float64Array.prototype.map":"\nFloat64Array.prototype.map( fcn:Function[, thisArg:Any] )\n    Maps each array element to an element in a new typed array.\n","Float64Array.prototype.reduce":"\nFloat64Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n","Float64Array.prototype.reduceRight":"\nFloat64Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n","Float64Array.prototype.reverse":"\nFloat64Array.prototype.reverse()\n    Reverses an array *in-place*.\n","Float64Array.prototype.set":"\nFloat64Array.prototype.set( arr:ArrayLike[, offset:integer] )\n    Sets array elements.\n","Float64Array.prototype.slice":"\nFloat64Array.prototype.slice( [begin:integer[, end:integer]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n","Float64Array.prototype.some":"\nFloat64Array.prototype.some( predicate:Function[, thisArg:Any] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n","Float64Array.prototype.sort":"\nFloat64Array.prototype.sort( [compareFunction:Function] )\n    Sorts an array *in-place*.\n","Float64Array.prototype.subarray":"\nFloat64Array.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n","Float64Array.prototype.toLocaleString":"\nFloat64Array.prototype.toLocaleString( [locales:string|Array[, \n  options:Object]] )\n    Serializes an array as a locale-specific string.\n","Float64Array.prototype.toString":"\nFloat64Array.prototype.toString()\n    Serializes an array as a string.\n","Float64Array.prototype.values":"\nFloat64Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n","forEach":"\nforEach( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n    Invokes a function for each element in a collection.\n","forEachAsync":"\nforEachAsync( collection:Array|TypedArray|Object, [options:Object,] \n  fcn:Function, done:Function )\n    Invokes a function once for each element in a collection.\n","forEachAsync.factory":"\nforEachAsync.factory( [options:Object,] fcn:Function )\n    Returns a function which invokes a function once for each element in a\n    collection.\n","forEachChar":"\nforEachChar( str:string, [options:Object,] clbk:Function[, thisArg:any] )\n    Invokes a function for each character in a string.\n","forEachRight":"\nforEachRight( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n    Invokes a function for each element in a collection, iterating from right to\n    left.\n","forEachRightAsync":"\nforEachRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n  fcn:Function, done:Function )\n    Invokes a function once for each element in a collection, iterating from\n    right to left.\n","forEachRightAsync.factory":"\nforEachRightAsync.factory( [options:Object,] fcn:Function )\n    Returns a function which invokes a function once for each element in a\n    collection, iterating from right to left.\n","forIn":"\nforIn( obj:Object, fcn:Function[, thisArg:any] )\n    Invokes a function for each own and inherited enumerable property of an\n    object.\n","format":"\nformat( str:string, ...args:any )\n    Insert supplied variable values into a format string.\n","forOwn":"\nforOwn( obj:Object, fcn:Function[, thisArg:any] )\n    Invokes a function for each own enumerable property of an object.\n","FOURTH_PI":"\nFOURTH_PI\n    One fourth times the mathematical constant `π`.\n","FOURTH_ROOT_EPS":"\nFOURTH_ROOT_EPS\n    Fourth root of double-precision floating-point epsilon.\n","FRB_SF_WAGE_RIGIDITY":"\nFRB_SF_WAGE_RIGIDITY()\n    Returns wage rates for U.S. workers that have not changed jobs within the\n    year.\n","fromCodePoint":"\nfromCodePoint( ...pt:integer )\n    Creates a string from a sequence of Unicode code points.\n","Function":"\nFunction( [...argNames:any,] body:string )\n    Returns a Function object.\n","Function.prototype.apply":"\nFunction.prototype.apply( thisArg:any, args:Array )\n    Calls a function with a given `this` value and arguments provided as an\n    array (or array-like object).\n","Function.prototype.call":"\nFunction.prototype.call( thisArg:any, ...args:any )\n    Calls a function with a given `this` value and arguments provided\n    individually.\n","Function.prototype.bind":"\nFunction.prototype.bind( thisArg:any, ...args:any )\n    Creates a new function which, when called, has its `this` keyword set to the\n    provided value, with a given sequence of arguments preceding any provided\n    when the new function is called.\n","Function.prototype.toString":"\nFunction.prototype.toString()\n    Returns a string representation of the function.\n","Function.prototype.length":"\nFunction.prototype.length\n    The number of arguments expected by the function.\n","Function.prototype.name":"\nFunction.prototype.name\n    The name of the function.\n","Function.prototype.prototype":"\nFunction.prototype.prototype\n    The prototype of the function.\n","function2string":"\nfunction2string( fcn:Function )\n    Returns a string representing the source code of a provided function.\n","functionName":"\nfunctionName( fcn:Function )\n    Returns the name of a function.\n","functionSequence":"\nfunctionSequence( ...fcn:Function )\n    Returns a pipeline function.\n","functionSequenceAsync":"\nfunctionSequenceAsync( ...fcn:Function )\n    Returns a pipeline function.\n","GAMMA_LANCZOS_G":"\nGAMMA_LANCZOS_G\n    Arbitrary constant `g` to be used in Lanczos approximation functions.\n","gdot":"\ngdot( x:ndarray|ArrayLikeObject, y:ndarray|ArrayLikeObject )\n    Computes the dot product of two vectors.\n","getegid":"\ngetegid()\n    Returns the effective numeric group identity of the calling process.\n","geteuid":"\ngeteuid()\n    Returns the effective numeric user identity of the calling process.\n","getgid":"\ngetgid()\n    Returns the numeric group identity of the calling process.\n","getGlobal":"\ngetGlobal( [codegen:boolean] )\n    Returns the global object.\n","getPrototypeOf":"\ngetPrototypeOf( value:any )\n    Returns the prototype of a provided object.\n","getuid":"\ngetuid()\n    Returns the numeric user identity of the calling process.\n","GLAISHER":"\nGLAISHER\n    Glaisher-Kinkelin constant.\n","graphemeClusters2iterator":"\ngraphemeClusters2iterator( src:string[, mapFcn:Function[, thisArg:any]] )\n    Returns an iterator which iterates over each grapheme cluster in a string.\n","graphemeClusters2iteratorRight":"\ngraphemeClusters2iteratorRight( src:string[, mapFcn:Function[, thisArg:any]] )\n    Returns an iterator which iterates from right to left over each grapheme\n    cluster in a string.\n","group":"\ngroup( collection:Array|TypedArray|Object, [options:Object,] \n  groups:Array|TypedArray|Object )\n    Groups values as arrays associated with distinct keys.\n","groupBy":"\ngroupBy( collection:Array|TypedArray|Object, [options:Object,] \n  indicator:Function )\n    Groups values according to an indicator function.\n","groupByAsync":"\ngroupByAsync( collection:Array|TypedArray|Object, [options:Object,] \n  indicator:Function, done:Function )\n    Groups values according to an indicator function.\n","groupByAsync.factory":"\ngroupByAsync.factory( [options:Object,] indicator:Function )\n    Returns a function which groups values according to an indicator function.\n","groupIn":"\ngroupIn( obj:Object|Array|TypedArray, [options:Object,] indicator:Function )\n    Group values according to an indicator function.\n","groupOwn":"\ngroupOwn( obj:Object|Array|TypedArray, [options:Object,] indicator:Function )\n    Group values according to an indicator function.\n","gswap":"\ngswap( x:ndarray|ArrayLikeObject, y:ndarray|ArrayLikeObject )\n    Interchanges two vectors.\n","HALF_LN2":"\nHALF_LN2\n    One half times the natural logarithm of `2`.\n","HALF_PI":"\nHALF_PI\n    One half times the mathematical constant `π`.\n","HARRISON_BOSTON_HOUSE_PRICES":"\nHARRISON_BOSTON_HOUSE_PRICES()\n    Returns a dataset derived from information collected by the US Census\n    Service concerning housing in Boston, Massachusetts (1978).\n","HARRISON_BOSTON_HOUSE_PRICES_CORRECTED":"\nHARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n    Returns a (corrected) dataset derived from information collected by the US\n    Census Service concerning housing in Boston, Massachusetts (1978).\n","hasArrayBufferSupport":"\nhasArrayBufferSupport()\n    Tests for native `ArrayBuffer` support.\n","hasArrowFunctionSupport":"\nhasArrowFunctionSupport()\n    Tests whether an environment supports native arrow functions.\n","hasAsyncAwaitSupport":"\nhasAsyncAwaitSupport()\n    Tests for native `async`/`await` support.\n","hasAsyncIteratorSymbolSupport":"\nhasAsyncIteratorSymbolSupport()\n    Tests for native `Symbol.asyncIterator` support.\n","hasAtobSupport":"\nhasAtobSupport()\n    Tests for native `atob` support.\n","hasBigInt64ArraySupport":"\nhasBigInt64ArraySupport()\n    Tests for native `BigInt64Array` support.\n","hasBigIntSupport":"\nhasBigIntSupport()\n    Tests for native `BigInt` support.\n","hasBigUint64ArraySupport":"\nhasBigUint64ArraySupport()\n    Tests for native `BigUint64Array` support.\n","hasBtoaSupport":"\nhasBtoaSupport()\n    Tests for native `btoa` support.\n","hasClassSupport":"\nhasClassSupport()\n    Tests for native `class` support.\n","hasDataViewSupport":"\nhasDataViewSupport()\n    Tests for native `DataView` support.\n","hasDefinePropertiesSupport":"\nhasDefinePropertiesSupport()\n    Tests for `Object.defineProperties` support.\n","hasDefinePropertySupport":"\nhasDefinePropertySupport()\n    Tests for `Object.defineProperty` support.\n","hasFloat32ArraySupport":"\nhasFloat32ArraySupport()\n    Tests for native `Float32Array` support.\n","hasFloat64ArraySupport":"\nhasFloat64ArraySupport()\n    Tests for native `Float64Array` support.\n","hasFunctionNameSupport":"\nhasFunctionNameSupport()\n    Tests for native function `name` support.\n","hasGeneratorSupport":"\nhasGeneratorSupport()\n    Tests whether an environment supports native generator functions.\n","hasGlobalThisSupport":"\nhasGlobalThisSupport()\n    Tests for `globalThis` support.\n","hasInt8ArraySupport":"\nhasInt8ArraySupport()\n    Tests for native `Int8Array` support.\n","hasInt16ArraySupport":"\nhasInt16ArraySupport()\n    Tests for native `Int16Array` support.\n","hasInt32ArraySupport":"\nhasInt32ArraySupport()\n    Tests for native `Int32Array` support.\n","hasIteratorSymbolSupport":"\nhasIteratorSymbolSupport()\n    Tests for native `Symbol.iterator` support.\n","hasMapSupport":"\nhasMapSupport()\n    Tests for native `Map` support.\n","hasNodeBufferSupport":"\nhasNodeBufferSupport()\n    Tests for native `Buffer` support.\n","hasOwnProp":"\nhasOwnProp( value:any, property:any )\n    Tests if an object has a specified property.\n","hasProp":"\nhasProp( value:any, property:any )\n    Tests if an object has a specified property, either own or inherited.\n","hasProxySupport":"\nhasProxySupport()\n    Tests whether an environment has native `Proxy` support.\n","hasSetSupport":"\nhasSetSupport()\n    Tests for native `Set` support.\n","hasSharedArrayBufferSupport":"\nhasSharedArrayBufferSupport()\n    Tests for native `SharedArrayBuffer` support.\n","hasSymbolSupport":"\nhasSymbolSupport()\n    Tests for native `Symbol` support.\n","hasToStringTagSupport":"\nhasToStringTagSupport()\n    Tests for native `toStringTag` support.\n","hasUint8ArraySupport":"\nhasUint8ArraySupport()\n    Tests for native `Uint8Array` support.\n","hasUint8ClampedArraySupport":"\nhasUint8ClampedArraySupport()\n    Tests for native `Uint8ClampedArray` support.\n","hasUint16ArraySupport":"\nhasUint16ArraySupport()\n    Tests for native `Uint16Array` support.\n","hasUint32ArraySupport":"\nhasUint32ArraySupport()\n    Tests for native `Uint32Array` support.\n","hasUTF16SurrogatePairAt":"\nhasUTF16SurrogatePairAt( str:string, pos:integer )\n    Tests if a position in a string marks the start of a UTF-16 surrogate pair.\n","hasWeakMapSupport":"\nhasWeakMapSupport()\n    Tests for native `WeakMap` support.\n","hasWeakSetSupport":"\nhasWeakSetSupport()\n    Tests for native `WeakSet` support.\n","hasWebAssemblySupport":"\nhasWebAssemblySupport()\n    Tests for native WebAssembly support.\n","headercase":"\nheadercase( str:string )\n    Converts a string to HTTP header case.\n","HERNDON_VENUS_SEMIDIAMETERS":"\nHERNDON_VENUS_SEMIDIAMETERS()\n    Returns fifteen observations of the vertical semidiameter of Venus, made by\n    Lieutenant Herndon, with the meridian circle at Washington, in the year\n    1846.\n","homedir":"\nhomedir()\n    Returns the current user's home directory.\n","HOURS_IN_DAY":"\nHOURS_IN_DAY\n    Number of hours in a day.\n","HOURS_IN_WEEK":"\nHOURS_IN_WEEK\n    Number of hours in a week.\n","hoursInMonth":"\nhoursInMonth( [month:string|Date|integer[, year:integer]] )\n    Returns the number of hours in a month.\n","hoursInYear":"\nhoursInYear( [value:integer|Date] )\n    Returns the number of hours in a year according to the Gregorian calendar.\n","httpServer":"\nhttpServer( [options:Object,] [requestListener:Function] )\n    Returns a function to create an HTTP server.\n","identity":"\nidentity( x:any )\n    Identity function.\n","ifelse":"\nifelse( bool:boolean, x:any, y:any )\n    If a condition is truthy, returns `x`; otherwise, returns `y`.\n","ifelseAsync":"\nifelseAsync( predicate:Function, x:any, y:any, done:Function )\n    If a predicate function returns a truthy value, returns `x`; otherwise,\n    returns `y`.\n","ifthen":"\nifthen( bool:boolean, x:Function, y:Function )\n    If a condition is truthy, invoke `x`; otherwise, invoke `y`.\n","ifthenAsync":"\nifthenAsync( predicate:Function, x:Function, y:Function, done:Function )\n    If a predicate function returns a truthy value, invokes `x`; otherwise,\n    invokes `y`.\n","imag":"\nimag( z:Complex128 )\n    Returns the imaginary component of a double-precision complex floating-point\n    number.\n","imagf":"\nimagf( z:Complex64 )\n    Returns the imaginary component of a single-precision complex floating-point\n    number.\n","IMG_ACANTHUS_MOLLIS":"\nIMG_ACANTHUS_MOLLIS()\n    Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n    print *Acanthus mollis*.\n","IMG_AIRPLANE_FROM_ABOVE":"\nIMG_AIRPLANE_FROM_ABOVE()\n    Returns a `Buffer` containing image data of Fédèle Azari's gelatin silver\n    print of an airplane, viewed from above looking down.\n","IMG_ALLIUM_OREOPHILUM":"\nIMG_ALLIUM_OREOPHILUM()\n    Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n    print *Allium ostrowskianum*.\n","IMG_BLACK_CANYON":"\nIMG_BLACK_CANYON()\n    Returns a `Buffer` containing image data of Timothy H. O'Sullivan's albumen\n    silver print *Black Cañon, Colorado River, From Camp 8, Looking Above*.\n","IMG_DUST_BOWL_HOME":"\nIMG_DUST_BOWL_HOME()\n    Returns a `Buffer` containing image data of Dorothea Lange's gelatin silver\n    print of an abandoned Dust Bowl home.\n","IMG_FRENCH_ALPINE_LANDSCAPE":"\nIMG_FRENCH_ALPINE_LANDSCAPE()\n    Returns a `Buffer` containing image data of Adolphe Braun's carbon print of\n    a French alpine landscape.\n","IMG_LOCOMOTION_HOUSE_CAT":"\nIMG_LOCOMOTION_HOUSE_CAT()\n    Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n    collotype of a house cat (24 views).\n","IMG_LOCOMOTION_NUDE_MALE":"\nIMG_LOCOMOTION_NUDE_MALE()\n    Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n    collotype of a nude male moving in place (48 views).\n","IMG_MARCH_PASTORAL":"\nIMG_MARCH_PASTORAL()\n    Returns a `Buffer` containing image data of Peter Henry Emerson's\n    photogravure of sheep in a pastoral setting.\n","IMG_NAGASAKI_BOATS":"\nIMG_NAGASAKI_BOATS()\n    Returns a `Buffer` containing image data of Felice Beato's albumen silver\n    print of boats in a river in Nagasaki.\n","incrapcorr":"\nincrapcorr( [mx:number, my:number] )\n    Returns an accumulator function which incrementally computes the absolute\n    value of the sample Pearson product-moment correlation coefficient.\n","incrBinaryClassification":"\nincrBinaryClassification( N:integer[, options:Object] )\n    Returns an accumulator function which incrementally performs binary\n    classification using stochastic gradient descent (SGD).\n","incrcount":"\nincrcount()\n    Returns an accumulator function which incrementally updates a count.\n","incrcovariance":"\nincrcovariance( [mx:number, my:number] )\n    Returns an accumulator function which incrementally computes an unbiased\n    sample covariance.\n","incrcovmat":"\nincrcovmat( out:integer|ndarray[, means:ndarray] )\n    Returns an accumulator function which incrementally computes an unbiased\n    sample covariance matrix.\n","incrcv":"\nincrcv( [mean:number] )\n    Returns an accumulator function which incrementally computes the coefficient\n    of variation (CV).\n","increwmean":"\nincrewmean( α:number )\n    Returns an accumulator function which incrementally computes an\n    exponentially weighted mean, where α is a smoothing factor between 0 and 1.\n","increwstdev":"\nincrewstdev( α:number )\n    Returns an accumulator function which incrementally computes an\n    exponentially weighted standard deviation, where α is a smoothing factor\n    between 0 and 1.\n","increwvariance":"\nincrewvariance( α:number )\n    Returns an accumulator function which incrementally computes an\n    exponentially weighted variance, where α is a smoothing factor between 0 and\n    1.\n","incrgmean":"\nincrgmean()\n    Returns an accumulator function which incrementally computes a geometric\n    mean.\n","incrgrubbs":"\nincrgrubbs( [options:Object] )\n    Returns an accumulator function which incrementally performs Grubbs' test\n    for detecting outliers.\n","incrhmean":"\nincrhmean()\n    Returns an accumulator function which incrementally computes a harmonic\n    mean.\n","incrkmeans":"\nincrkmeans( k:integer|ndarray[, ndims:integer][, options:Object] )\n    Returns an accumulator function which incrementally partitions data into `k`\n    clusters.\n","incrkurtosis":"\nincrkurtosis()\n    Returns an accumulator function which incrementally computes a corrected\n    sample excess kurtosis.\n","incrmaape":"\nincrmaape()\n    Returns an accumulator function which incrementally computes the mean\n    arctangent absolute percentage error (MAAPE).\n","incrmae":"\nincrmae()\n    Returns an accumulator function which incrementally computes the mean\n    absolute error (MAE).\n","incrmapcorr":"\nincrmapcorr( W:integer[, mx:number, my:number] )\n    Returns an accumulator function which incrementally computes a moving\n    sample absolute Pearson product-moment correlation coefficient.\n","incrmape":"\nincrmape()\n    Returns an accumulator function which incrementally computes the mean\n    absolute percentage error (MAPE).\n","incrmax":"\nincrmax()\n    Returns an accumulator function which incrementally computes a maximum\n    value.\n","incrmaxabs":"\nincrmaxabs()\n    Returns an accumulator function which incrementally computes a maximum\n    absolute value.\n","incrmcovariance":"\nincrmcovariance( W:integer[, mx:number, my:number] )\n    Returns an accumulator function which incrementally computes a moving\n    unbiased sample covariance.\n","incrmcv":"\nincrmcv( W:integer[, mean:number] )\n    Returns an accumulator function which incrementally computes a moving\n    coefficient of variation (CV).\n","incrmda":"\nincrmda()\n    Returns an accumulator function which incrementally computes the mean\n    directional accuracy (MDA).\n","incrme":"\nincrme()\n    Returns an accumulator function which incrementally computes the mean error\n    (ME).\n","incrmean":"\nincrmean()\n    Returns an accumulator function which incrementally computes an arithmetic\n    mean.\n","incrmeanabs":"\nincrmeanabs()\n    Returns an accumulator function which incrementally computes an arithmetic\n    mean of absolute values.\n","incrmeanabs2":"\nincrmeanabs2()\n    Returns an accumulator function which incrementally computes an arithmetic\n    mean of squared absolute values.\n","incrmeanstdev":"\nincrmeanstdev( [out:Array|TypedArray] )\n    Returns an accumulator function which incrementally computes an arithmetic\n    mean and corrected sample standard deviation.\n","incrmeanvar":"\nincrmeanvar( [out:Array|TypedArray] )\n    Returns an accumulator function which incrementally computes an arithmetic\n    mean and unbiased sample variance.\n","incrmgmean":"\nincrmgmean( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    geometric mean.\n","incrmgrubbs":"\nincrmgrubbs( W:integer[, options:Object] )\n    Returns an accumulator function which incrementally performs a moving\n    Grubbs' test for detecting outliers.\n","incrmhmean":"\nincrmhmean( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    harmonic mean.\n","incrmidrange":"\nincrmidrange()\n    Returns an accumulator function which incrementally computes a mid-range.\n","incrmin":"\nincrmin()\n    Returns an accumulator function which incrementally computes a minimum\n    value.\n","incrminabs":"\nincrminabs()\n    Returns an accumulator function which incrementally computes a minimum\n    absolute value.\n","incrminmax":"\nincrminmax( [out:Array|TypedArray] )\n    Returns an accumulator function which incrementally computes a minimum and\n    maximum.\n","incrminmaxabs":"\nincrminmaxabs( [out:Array|TypedArray] )\n    Returns an accumulator function which incrementally computes a minimum and\n    maximum absolute value.\n","incrmmaape":"\nincrmmaape( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    mean arctangent absolute percentage error (MAAPE).\n","incrmmae":"\nincrmmae( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    mean absolute error (MAE).\n","incrmmape":"\nincrmmape( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    mean absolute percentage error (MAPE).\n","incrmmax":"\nincrmmax( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    maximum value.\n","incrmmaxabs":"\nincrmmaxabs( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    maximum absolute value.\n","incrmmda":"\nincrmmda( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    mean directional accuracy (MDA).\n","incrmme":"\nincrmme( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    mean error (ME).\n","incrmmean":"\nincrmmean( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    arithmetic mean.\n","incrmmeanabs":"\nincrmmeanabs( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    arithmetic mean of absolute values.\n","incrmmeanabs2":"\nincrmmeanabs2( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    arithmetic mean of squared absolute values.\n","incrmmeanstdev":"\nincrmmeanstdev( [out:Array|TypedArray,] W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    arithmetic mean and corrected sample standard deviation.\n","incrmmeanvar":"\nincrmmeanvar( [out:Array|TypedArray,] W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    arithmetic mean and unbiased sample variance.\n","incrmmidrange":"\nincrmmidrange( W:integer )\n    Returns an accumulator function which incrementally computes a moving mid-\n    range.\n","incrmmin":"\nincrmmin( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    minimum value.\n","incrmminabs":"\nincrmminabs( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    minimum absolute value.\n","incrmminmax":"\nincrmminmax( [out:Array|TypedArray,] W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    minimum and maximum.\n","incrmminmaxabs":"\nincrmminmaxabs( [out:Array|TypedArray,] W:integer )\n    Returns an accumulator function which incrementally computes moving minimum\n    and maximum absolute values.\n","incrmmpe":"\nincrmmpe( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    mean percentage error (MPE).\n","incrmmse":"\nincrmmse( W:integer )\n    Returns an accumulator function which incrementally computes a moving mean\n    squared error (MSE).\n","incrmpcorr":"\nincrmpcorr( W:integer[, mx:number, my:number] )\n    Returns an accumulator function which incrementally computes a moving\n    sample Pearson product-moment correlation coefficient.\n","incrmpcorr2":"\nincrmpcorr2( W:integer[, mx:number, my:number] )\n    Returns an accumulator function which incrementally computes a moving\n    squared sample Pearson product-moment correlation coefficient.\n","incrmpcorrdist":"\nincrmpcorrdist( W:integer[, mx:number, my:number] )\n    Returns an accumulator function which incrementally computes a moving\n    sample Pearson product-moment correlation distance.\n","incrmpe":"\nincrmpe()\n    Returns an accumulator function which incrementally computes the mean\n    percentage error (MPE).\n","incrmprod":"\nincrmprod( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    product.\n","incrmrange":"\nincrmrange( W:integer )\n    Returns an accumulator function which incrementally computes a moving range.\n","incrmrmse":"\nincrmrmse( W:integer )\n    Returns an accumulator function which incrementally computes a moving root\n    mean squared error (RMSE).\n","incrmrss":"\nincrmrss( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    residual sum of squares (RSS).\n","incrmse":"\nincrmse()\n    Returns an accumulator function which incrementally computes the mean\n    squared error (MSE).\n","incrmstdev":"\nincrmstdev( W:integer[, mean:number] )\n    Returns an accumulator function which incrementally computes a moving\n    corrected sample standard deviation.\n","incrmsum":"\nincrmsum( W:integer )\n    Returns an accumulator function which incrementally computes a moving sum.\n","incrmsumabs":"\nincrmsumabs( W:integer )\n    Returns an accumulator function which incrementally computes a moving sum of\n    absolute values.\n","incrmsumabs2":"\nincrmsumabs2( W:integer )\n    Returns an accumulator function which incrementally computes a moving sum of\n    squared absolute values.\n","incrmsummary":"\nincrmsummary( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    statistical summary.\n","incrmsumprod":"\nincrmsumprod( W:integer )\n    Returns an accumulator function which incrementally computes a moving sum of\n    products.\n","incrmvariance":"\nincrmvariance( W:integer[, mean:number] )\n    Returns an accumulator function which incrementally computes a moving\n    unbiased sample variance.\n","incrmvmr":"\nincrmvmr( W:integer[, mean:number] )\n    Returns an accumulator function which incrementally computes a moving\n    variance-to-mean (VMR).\n","incrnancount":"\nincrnancount()\n    Returns an accumulator function which incrementally updates a count,\n    ignoring `NaN` values.\n","incrnansum":"\nincrnansum()\n    Returns an accumulator function which incrementally computes a sum, ignoring\n    `NaN` values.\n","incrnansumabs":"\nincrnansumabs()\n    Returns an accumulator function which incrementally computes a sum of\n    absolute values, ignoring NaN values.\n","incrnansumabs2":"\nincrnansumabs2()\n    Returns an accumulator function which incrementally computes a sum of\n    squared absolute values, ignoring NaN values.\n","incrpcorr":"\nincrpcorr( [mx:number, my:number] )\n    Returns an accumulator function which incrementally computes a sample\n    Pearson product-moment correlation coefficient.\n","incrpcorr2":"\nincrpcorr2( [mx:number, my:number] )\n    Returns an accumulator function which incrementally computes the squared\n    sample Pearson product-moment correlation coefficient.\n","incrpcorrdist":"\nincrpcorrdist( [mx:number, my:number] )\n    Returns an accumulator function which incrementally computes a sample\n    Pearson product-moment correlation distance.\n","incrpcorrdistmat":"\nincrpcorrdistmat( out:integer|ndarray[, means:ndarray] )\n    Returns an accumulator function which incrementally computes a sample\n    Pearson product-moment correlation distance matrix.\n","incrpcorrmat":"\nincrpcorrmat( out:integer|ndarray[, means:ndarray] )\n    Returns an accumulator function which incrementally computes a sample\n    Pearson product-moment correlation matrix.\n","incrprod":"\nincrprod()\n    Returns an accumulator function which incrementally computes a product.\n","incrrange":"\nincrrange()\n    Returns an accumulator function which incrementally computes a range.\n","incrrmse":"\nincrrmse()\n    Returns an accumulator function which incrementally computes the root mean\n    squared error (RMSE).\n","incrrss":"\nincrrss()\n    Returns an accumulator function which incrementally computes the residual\n    sum of squares (RSS).\n","incrskewness":"\nincrskewness()\n    Returns an accumulator function which incrementally computes a corrected\n    sample skewness.\n","incrspace":"\nincrspace( start:number, stop:number[, increment:number] )\n    Generates a linearly spaced numeric array using a provided increment.\n","incrstdev":"\nincrstdev( [mean:number] )\n    Returns an accumulator function which incrementally computes a corrected\n    sample standard deviation.\n","incrsum":"\nincrsum()\n    Returns an accumulator function which incrementally computes a sum.\n","incrsumabs":"\nincrsumabs()\n    Returns an accumulator function which incrementally computes a sum of\n    absolute values.\n","incrsumabs2":"\nincrsumabs2()\n    Returns an accumulator function which incrementally computes a sum of\n    squared absolute values.\n","incrsummary":"\nincrsummary()\n    Returns an accumulator function which incrementally computes a statistical\n    summary.\n","incrsumprod":"\nincrsumprod()\n    Returns an accumulator function which incrementally computes a sum of\n    products.\n","incrvariance":"\nincrvariance( [mean:number] )\n    Returns an accumulator function which incrementally computes an unbiased\n    sample variance.\n","incrvmr":"\nincrvmr( [mean:number] )\n    Returns an accumulator function which incrementally computes a variance-to-\n    mean ratio (VMR).\n","incrwmean":"\nincrwmean()\n    Returns an accumulator function which incrementally computes a weighted\n    arithmetic mean.\n","ind2sub":"\nind2sub( shape:ArrayLike, idx:integer[, options:Object] )\n    Converts a linear index to an array of subscripts.\n","ind2sub.assign":"\nind2sub.assign( shape:ArrayLike, idx:integer[, options:Object], \n  out:Array|TypedArray|Object )\n    Converts a linear index to an array of subscripts and assigns results to a\n    provided output array.\n","indexOf":"\nindexOf( arr:ArrayLike, searchElement:any[, fromIndex:integer] )\n    Returns the first index at which a given element can be found.\n","inherit":"\ninherit( ctor:Object|Function, superCtor:Object|Function )\n    Prototypical inheritance by replacing the prototype of one constructor with\n    the prototype of another constructor.\n","inheritedEnumerableProperties":"\ninheritedEnumerableProperties( value:any[, level:integer] )\n    Returns an array of an object's inherited enumerable property names and\n    symbols.\n","inheritedEnumerablePropertySymbols":"\ninheritedEnumerablePropertySymbols( value:any[, level:integer] )\n    Returns an array of an object's inherited enumerable symbol properties.\n","inheritedKeys":"\ninheritedKeys( value:any[, level:integer] )\n    Returns an array of an object's inherited enumerable property names.\n","inheritedNonEnumerableProperties":"\ninheritedNonEnumerableProperties( value:any[, level:integer] )\n    Returns an array of an object's inherited non-enumerable property names and\n    symbols.\n","inheritedNonEnumerablePropertyNames":"\ninheritedNonEnumerablePropertyNames( value:any[, level:integer] )\n    Returns an array of an object's inherited non-enumerable property names.\n","inheritedNonEnumerablePropertySymbols":"\ninheritedNonEnumerablePropertySymbols( value:any[, level:integer] )\n    Returns an array of an object's inherited non-enumerable symbol properties.\n","inheritedProperties":"\ninheritedProperties( value:any[, level:integer] )\n    Returns an array of an object's inherited property names and symbols.\n","inheritedPropertyDescriptor":"\ninheritedPropertyDescriptor( value:any, property:string|symbol[, \n  level:integer] )\n    Returns a property descriptor for an object's inherited property.\n","inheritedPropertyDescriptors":"\ninheritedPropertyDescriptors( value:any[, level:integer] )\n    Returns an object's inherited property descriptors.\n","inheritedPropertyNames":"\ninheritedPropertyNames( value:any[, level:integer] )\n    Returns an array of an object's inherited enumerable and non-enumerable\n    property names.\n","inheritedPropertySymbols":"\ninheritedPropertySymbols( value:any[, level:integer] )\n    Returns an array of an object's inherited symbol properties.\n","inheritedWritableProperties":"\ninheritedWritableProperties( value:any[, level:integer] )\n    Returns an array of an object's inherited writable property names and\n    symbols.\n","inheritedWritablePropertyNames":"\ninheritedWritablePropertyNames( value:any[, level:integer] )\n    Returns an array of an object's inherited writable property names.\n","inheritedWritablePropertySymbols":"\ninheritedWritablePropertySymbols( value:any[, level:integer] )\n    Returns an array of an object's inherited writable symbol properties.\n","inmap":"\ninmap( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n    Invokes a function for each element in a collection and updates the\n    collection in-place.\n","inmapAsync":"\ninmapAsync( collection:Array|TypedArray|Object, [options:Object,] fcn:Function, \n  done:Function )\n    Invokes a function once for each element in a collection and updates a\n    collection in-place.\n","inmapAsync.factory":"\ninmapAsync.factory( [options:Object,] fcn:Function )\n    Returns a function which invokes a function once for each element in a\n    collection and updates a collection in-place.\n","inmapRight":"\ninmapRight( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n    Invokes a function for each element in a collection and updates the\n    collection in-place, iterating from right to left.\n","inmapRightAsync":"\ninmapRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n  fcn:Function, done:Function )\n    Invokes a function once for each element in a collection and updates a\n    collection in-place, iterating from right to left.\n","inmapRightAsync.factory":"\ninmapRightAsync.factory( [options:Object,] fcn:Function )\n    Returns a function which invokes a function once for each element in a\n    collection and updates a collection in-place, iterating from right to left.\n","inspectSinkStream":"\ninspectSinkStream( [options:Object,] clbk:Function )\n    Returns a writable stream for inspecting stream data.\n","inspectSinkStream.factory":"\ninspectSinkStream.factory( [options:Object] )\n    Returns a function for creating writable streams for inspecting stream data.\n","inspectSinkStream.objectMode":"\ninspectSinkStream.objectMode( [options:Object,] clbk:Function )\n    Returns an \"objectMode\" writable stream for inspecting stream data.\n","inspectStream":"\ninspectStream( [options:Object,] clbk:Function )\n    Returns a transform stream for inspecting stream data.\n","inspectStream.factory":"\ninspectStream.factory( [options:Object] )\n    Returns a function for creating transform streams for inspecting stream\n    data.\n","inspectStream.objectMode":"\ninspectStream.objectMode( [options:Object,] clbk:Function )\n    Returns an \"objectMode\" transform stream for inspecting stream data.\n","instanceOf":"\ninstanceOf( value:any, constructor:Function )\n    Tests whether a value has in its prototype chain a specified constructor as\n    a prototype property.\n","INT8_MAX":"\nINT8_MAX\n    Maximum signed 8-bit integer.\n","INT8_MIN":"\nINT8_MIN\n    Minimum signed 8-bit integer.\n","INT8_NUM_BYTES":"\nINT8_NUM_BYTES\n    Size (in bytes) of an 8-bit signed integer.\n","Int8Array":"\nInt8Array()\n    A typed array constructor which returns a typed array representing an array\n    of twos-complement 8-bit signed integers in the platform byte order.\n\nInt8Array( length:integer )\n    Returns a typed array having a specified length.\n\nInt8Array( typedarray:TypedArray )\n    Creates a typed array from another typed array.\n\nInt8Array( obj:Object )\n    Creates a typed array from an array-like object or iterable.\n\nInt8Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a typed array view of an ArrayBuffer.\n","Int8Array.from":"\nInt8Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n    Creates a new typed array from an array-like object or an iterable.\n","Int8Array.of":"\nInt8Array.of( element0:number[, element1:number[, ...elementN:number]] )\n    Creates a new typed array from a variable number of arguments.\n","Int8Array.BYTES_PER_ELEMENT":"\nInt8Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Int8Array.name":"\nInt8Array.name\n    Typed array constructor name.\n","Int8Array.prototype.buffer":"\nInt8Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n","Int8Array.prototype.byteLength":"\nInt8Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n","Int8Array.prototype.byteOffset":"\nInt8Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n","Int8Array.prototype.BYTES_PER_ELEMENT":"\nInt8Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Int8Array.prototype.length":"\nInt8Array.prototype.length\n    Read-only property which returns the number of view elements.\n","Int8Array.prototype.copyWithin":"\nInt8Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","Int8Array.prototype.entries":"\nInt8Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","Int8Array.prototype.every":"\nInt8Array.prototype.every( predicate:Function[, thisArg:Any] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n","Int8Array.prototype.fill":"\nInt8Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n","Int8Array.prototype.filter":"\nInt8Array.prototype.filter( predicate:Function[, thisArg:Any] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n","Int8Array.prototype.find":"\nInt8Array.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n","Int8Array.prototype.findIndex":"\nInt8Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n","Int8Array.prototype.forEach":"\nInt8Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n    Invokes a callback for each array element.\n","Int8Array.prototype.includes":"\nInt8Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a search element.\n","Int8Array.prototype.indexOf":"\nInt8Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n","Int8Array.prototype.join":"\nInt8Array.prototype.join( [separator:string] )\n    Serializes an array by joining all array elements as a string.\n","Int8Array.prototype.keys":"\nInt8Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n","Int8Array.prototype.lastIndexOf":"\nInt8Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n","Int8Array.prototype.map":"\nInt8Array.prototype.map( fcn:Function[, thisArg:Any] )\n    Maps each array element to an element in a new typed array.\n","Int8Array.prototype.reduce":"\nInt8Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n","Int8Array.prototype.reduceRight":"\nInt8Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n","Int8Array.prototype.reverse":"\nInt8Array.prototype.reverse()\n    Reverses an array *in-place*.\n","Int8Array.prototype.set":"\nInt8Array.prototype.set( arr:ArrayLike[, offset:integer] )\n    Sets array elements.\n","Int8Array.prototype.slice":"\nInt8Array.prototype.slice( [begin:integer[, end:integer]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n","Int8Array.prototype.some":"\nInt8Array.prototype.some( predicate:Function[, thisArg:Any] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n","Int8Array.prototype.sort":"\nInt8Array.prototype.sort( [compareFunction:Function] )\n    Sorts an array *in-place*.\n","Int8Array.prototype.subarray":"\nInt8Array.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n","Int8Array.prototype.toLocaleString":"\nInt8Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n    Serializes an array as a locale-specific string.\n","Int8Array.prototype.toString":"\nInt8Array.prototype.toString()\n    Serializes an array as a string.\n","Int8Array.prototype.values":"\nInt8Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n","INT16_MAX":"\nINT16_MAX\n    Maximum signed 16-bit integer.\n","INT16_MIN":"\nINT16_MIN\n    Minimum signed 16-bit integer.\n","INT16_NUM_BYTES":"\nINT16_NUM_BYTES\n    Size (in bytes) of a 16-bit signed integer.\n","Int16Array":"\nInt16Array()\n    A typed array constructor which returns a typed array representing an array\n    of twos-complement 16-bit signed integers in the platform byte order.\n\nInt16Array( length:integer )\n    Returns a typed array having a specified length.\n\nInt16Array( typedarray:TypedArray )\n    Creates a typed array from another typed array.\n\nInt16Array( obj:Object )\n    Creates a typed array from an array-like object or iterable.\n\nInt16Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a typed array view of an ArrayBuffer.\n","Int16Array.from":"\nInt16Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n    Creates a new typed array from an array-like object or an iterable.\n","Int16Array.of":"\nInt16Array.of( element0:number[, element1:number[, ...elementN:number]] )\n    Creates a new typed array from a variable number of arguments.\n","Int16Array.BYTES_PER_ELEMENT":"\nInt16Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Int16Array.name":"\nInt16Array.name\n    Typed array constructor name.\n","Int16Array.prototype.buffer":"\nInt16Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n","Int16Array.prototype.byteLength":"\nInt16Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n","Int16Array.prototype.byteOffset":"\nInt16Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n","Int16Array.prototype.BYTES_PER_ELEMENT":"\nInt16Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Int16Array.prototype.length":"\nInt16Array.prototype.length\n    Read-only property which returns the number of view elements.\n","Int16Array.prototype.copyWithin":"\nInt16Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","Int16Array.prototype.entries":"\nInt16Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","Int16Array.prototype.every":"\nInt16Array.prototype.every( predicate:Function[, thisArg:Any] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n","Int16Array.prototype.fill":"\nInt16Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n","Int16Array.prototype.filter":"\nInt16Array.prototype.filter( predicate:Function[, thisArg:Any] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n","Int16Array.prototype.find":"\nInt16Array.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n","Int16Array.prototype.findIndex":"\nInt16Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n","Int16Array.prototype.forEach":"\nInt16Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n    Invokes a callback for each array element.\n","Int16Array.prototype.includes":"\nInt16Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a search element.\n","Int16Array.prototype.indexOf":"\nInt16Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n","Int16Array.prototype.join":"\nInt16Array.prototype.join( [separator:string] )\n    Serializes an array by joining all array elements as a string.\n","Int16Array.prototype.keys":"\nInt16Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n","Int16Array.prototype.lastIndexOf":"\nInt16Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n","Int16Array.prototype.map":"\nInt16Array.prototype.map( fcn:Function[, thisArg:Any] )\n    Maps each array element to an element in a new typed array.\n","Int16Array.prototype.reduce":"\nInt16Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n","Int16Array.prototype.reduceRight":"\nInt16Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n","Int16Array.prototype.reverse":"\nInt16Array.prototype.reverse()\n    Reverses an array *in-place*.\n","Int16Array.prototype.set":"\nInt16Array.prototype.set( arr:ArrayLike[, offset:integer] )\n    Sets array elements.\n","Int16Array.prototype.slice":"\nInt16Array.prototype.slice( [begin:integer[, end:integer]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n","Int16Array.prototype.some":"\nInt16Array.prototype.some( predicate:Function[, thisArg:Any] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n","Int16Array.prototype.sort":"\nInt16Array.prototype.sort( [compareFunction:Function] )\n    Sorts an array *in-place*.\n","Int16Array.prototype.subarray":"\nInt16Array.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n","Int16Array.prototype.toLocaleString":"\nInt16Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n    Serializes an array as a locale-specific string.\n","Int16Array.prototype.toString":"\nInt16Array.prototype.toString()\n    Serializes an array as a string.\n","Int16Array.prototype.values":"\nInt16Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n","INT32_MAX":"\nINT32_MAX\n    Maximum signed 32-bit integer.\n","INT32_MIN":"\nINT32_MIN\n    Minimum signed 32-bit integer.\n","INT32_NUM_BYTES":"\nINT32_NUM_BYTES\n    Size (in bytes) of a 32-bit signed integer.\n","Int32Array":"\nInt32Array()\n    A typed array constructor which returns a typed array representing an array\n    of twos-complement 32-bit signed integers in the platform byte order.\n\nInt32Array( length:integer )\n    Returns a typed array having a specified length.\n\nInt32Array( typedarray:TypedArray )\n    Creates a typed array from another typed array.\n\nInt32Array( obj:Object )\n    Creates a typed array from an array-like object or iterable.\n\nInt32Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a typed array view of an ArrayBuffer.\n","Int32Array.from":"\nInt32Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n    Creates a new typed array from an array-like object or an iterable.\n","Int32Array.of":"\nInt32Array.of( element0:number[, element1:number[, ...elementN:number]] )\n    Creates a new typed array from a variable number of arguments.\n","Int32Array.BYTES_PER_ELEMENT":"\nInt32Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Int32Array.name":"\nInt32Array.name\n    Typed array constructor name.\n","Int32Array.prototype.buffer":"\nInt32Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n","Int32Array.prototype.byteLength":"\nInt32Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n","Int32Array.prototype.byteOffset":"\nInt32Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n","Int32Array.prototype.BYTES_PER_ELEMENT":"\nInt32Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Int32Array.prototype.length":"\nInt32Array.prototype.length\n    Read-only property which returns the number of view elements.\n","Int32Array.prototype.copyWithin":"\nInt32Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","Int32Array.prototype.entries":"\nInt32Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","Int32Array.prototype.every":"\nInt32Array.prototype.every( predicate:Function[, thisArg:Any] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n","Int32Array.prototype.fill":"\nInt32Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n","Int32Array.prototype.filter":"\nInt32Array.prototype.filter( predicate:Function[, thisArg:Any] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n","Int32Array.prototype.find":"\nInt32Array.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n","Int32Array.prototype.findIndex":"\nInt32Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n","Int32Array.prototype.forEach":"\nInt32Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n    Invokes a callback for each array element.\n","Int32Array.prototype.includes":"\nInt32Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a search element.\n","Int32Array.prototype.indexOf":"\nInt32Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n","Int32Array.prototype.join":"\nInt32Array.prototype.join( [separator:string] )\n    Serializes an array by joining all array elements as a string.\n","Int32Array.prototype.keys":"\nInt32Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n","Int32Array.prototype.lastIndexOf":"\nInt32Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n","Int32Array.prototype.map":"\nInt32Array.prototype.map( fcn:Function[, thisArg:Any] )\n    Maps each array element to an element in a new typed array.\n","Int32Array.prototype.reduce":"\nInt32Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n","Int32Array.prototype.reduceRight":"\nInt32Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n","Int32Array.prototype.reverse":"\nInt32Array.prototype.reverse()\n    Reverses an array *in-place*.\n","Int32Array.prototype.set":"\nInt32Array.prototype.set( arr:ArrayLike[, offset:integer] )\n    Sets array elements.\n","Int32Array.prototype.slice":"\nInt32Array.prototype.slice( [begin:integer[, end:integer]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n","Int32Array.prototype.some":"\nInt32Array.prototype.some( predicate:Function[, thisArg:Any] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n","Int32Array.prototype.sort":"\nInt32Array.prototype.sort( [compareFunction:Function] )\n    Sorts an array *in-place*.\n","Int32Array.prototype.subarray":"\nInt32Array.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n","Int32Array.prototype.toLocaleString":"\nInt32Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n    Serializes an array as a locale-specific string.\n","Int32Array.prototype.toString":"\nInt32Array.prototype.toString()\n    Serializes an array as a string.\n","Int32Array.prototype.values":"\nInt32Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n","IS_BIG_ENDIAN":"\nIS_BIG_ENDIAN\n    Boolean indicating if the environment is big endian.\n","IS_BROWSER":"\nIS_BROWSER\n    Boolean indicating if the runtime is a web browser.\n","IS_DARWIN":"\nIS_DARWIN\n    Boolean indicating if the current process is running on Darwin.\n","IS_DOCKER":"\nIS_DOCKER\n    Boolean indicating if the process is running in a Docker container.\n","IS_ELECTRON":"\nIS_ELECTRON\n    Boolean indicating if the runtime is Electron.\n","IS_ELECTRON_MAIN":"\nIS_ELECTRON_MAIN\n    Boolean indicating if the runtime is the main Electron process.\n","IS_ELECTRON_RENDERER":"\nIS_ELECTRON_RENDERER\n    Boolean indicating if the runtime is the Electron renderer process.\n","IS_LITTLE_ENDIAN":"\nIS_LITTLE_ENDIAN\n    Boolean indicating if the environment is little endian.\n","IS_MOBILE":"\nIS_MOBILE\n    Boolean indicating if the current environment is a mobile device.\n","IS_NODE":"\nIS_NODE\n    Boolean indicating if the runtime is Node.js.\n","IS_TOUCH_DEVICE":"\nIS_TOUCH_DEVICE\n    Boolean indicating if the current environment is a touch device.\n","IS_WEB_WORKER":"\nIS_WEB_WORKER\n    Boolean indicating if the runtime is a web worker.\n","IS_WINDOWS":"\nIS_WINDOWS\n    Boolean indicating if the current process is running on Windows.\n","isAbsoluteHttpURI":"\nisAbsoluteHttpURI( value:any )\n    Tests whether a value is an absolute HTTP(S) URI.\n","isAbsolutePath":"\nisAbsolutePath( value:any )\n    Tests if a value is an absolute path.\n","isAbsolutePath.posix":"\nisAbsolutePath.posix( value:any )\n    Tests if a value is a POSIX absolute path.\n","isAbsolutePath.win32":"\nisAbsolutePath.win32( value:any )\n    Tests if a value is a Windows absolute path.\n","isAbsoluteURI":"\nisAbsoluteURI( value:any )\n    Tests whether a value is an absolute URI.\n","isAccessorArray":"\nisAccessorArray( value:any )\n    Tests if a value is an array-like object supporting the accessor (get/set)\n    protocol.\n","isAccessorProperty":"\nisAccessorProperty( value:any, property:any )\n    Tests if an object's own property has an accessor descriptor.\n","isAccessorPropertyIn":"\nisAccessorPropertyIn( value:any, property:any )\n    Tests if an object's own or inherited property has an accessor descriptor.\n","isAlphagram":"\nisAlphagram( value:any )\n    Tests if a value is an alphagram (i.e., a sequence of characters arranged in\n    alphabetical order).\n","isAlphaNumeric":"\nisAlphaNumeric( str:string )\n    Tests whether a string contains only alphanumeric characters.\n","isAnagram":"\nisAnagram( str:string, value:any )\n    Tests if a value is an anagram.\n","isArguments":"\nisArguments( value:any )\n    Tests if a value is an arguments object.\n","isArray":"\nisArray( value:any )\n    Tests if a value is an array.\n","isArrayArray":"\nisArrayArray( value:any )\n    Tests if a value is an array of arrays.\n","isArrayBuffer":"\nisArrayBuffer( value:any )\n    Tests if a value is an ArrayBuffer.\n","isArrayBufferView":"\nisArrayBufferView( value:any )\n    Tests if a value is a `ArrayBuffer` view.\n","isArrayLength":"\nisArrayLength( value:any )\n    Tests if a value is a valid array length.\n","isArrayLike":"\nisArrayLike( value:any )\n    Tests if a value is array-like.\n","isArrayLikeObject":"\nisArrayLikeObject( value:any )\n    Tests if a value is an array-like object.\n","isArrowFunction":"\nisArrowFunction( value:any )\n    Tests if a value is an arrow function.\n","isASCII":"\nisASCII( str:string )\n    Tests whether a character belongs to the ASCII character set and whether\n    this is true for all characters in a provided string.\n","isBetween":"\nisBetween( value:any, a:any, b:any[, left:string, right:string] )\n    Tests if a value is between two values.\n","isBetweenArray":"\nisBetweenArray( value:any, a:any, b:any[, left:string, right:string] )\n    Tests if a value is an array-like object where every element is between two\n    values.\n","isBigInt":"\nisBigInt( value:any )\n    Tests if a value is a BigInt.\n","isBigInt64Array":"\nisBigInt64Array( value:any )\n    Tests if a value is a BigInt64Array.\n","isBigUint64Array":"\nisBigUint64Array( value:any )\n    Tests if a value is a BigUint64Array.\n","isBinaryString":"\nisBinaryString( value:any )\n    Tests if a value is a binary string.\n","isBlankString":"\nisBlankString( value:any )\n    Tests if a value is a blank string (i.e., an empty string or a string\n    consisting only of whitespace characters).\n","isBoolean":"\nisBoolean( value:any )\n    Tests if a value is a boolean.\n","isBoolean.isPrimitive":"\nisBoolean.isPrimitive( value:any )\n    Tests if a value is a boolean primitive.\n","isBoolean.isObject":"\nisBoolean.isObject( value:any )\n    Tests if a value is a boolean object.\n","isBooleanArray":"\nisBooleanArray( value:any )\n    Tests if a value is an array-like object of booleans.\n","isBooleanArray.primitives":"\nisBooleanArray.primitives( value:any )\n    Tests if a value is an array-like object containing only boolean primitives.\n","isBooleanArray.objects":"\nisBooleanArray.objects( value:any )\n    Tests if a value is an array-like object containing only Boolean objects.\n","isBoxedPrimitive":"\nisBoxedPrimitive( value:any )\n    Tests if a value is a JavaScript boxed primitive.\n","isBuffer":"\nisBuffer( value:any )\n    Tests if a value is a Buffer instance.\n","isCamelcase":"\nisCamelcase( value:any )\n    Tests if a value is a camelcase string.\n","isCapitalized":"\nisCapitalized( value:any )\n    Tests if a value is a string having an uppercase first character.\n","isCentrosymmetricMatrix":"\nisCentrosymmetricMatrix( value:any )\n    Tests if a value is a matrix which is symmetric about its center.\n","isCircular":"\nisCircular( value:any )\n    Tests if an object-like value contains a circular reference.\n","isCircularArray":"\nisCircularArray( value:any )\n    Tests if a value is an array containing a circular reference.\n","isCircularPlainObject":"\nisCircularPlainObject( value:any )\n    Tests if a value is a plain object containing a circular reference.\n","isClass":"\nisClass( value:any )\n    Tests if a value is a class.\n","isCollection":"\nisCollection( value:any )\n    Tests if a value is a collection.\n","isComplex":"\nisComplex( value:any )\n    Tests if a value is a 64-bit or 128-bit complex number.\n","isComplex64":"\nisComplex64( value:any )\n    Tests if a value is a 64-bit complex number.\n","isComplex64Array":"\nisComplex64Array( value:any )\n    Tests if a value is a Complex64Array.\n","isComplex64MatrixLike":"\nisComplex64MatrixLike( value:any )\n    Tests if a value is a 2-dimensional ndarray-like object containing single-\n    precision complex floating-point numbers.\n","isComplex64ndarrayLike":"\nisComplex64ndarrayLike( value:any )\n    Tests if a value is an ndarray-like object containing single-precision\n    complex floating-point numbers.\n","isComplex64VectorLike":"\nisComplex64VectorLike( value:any )\n    Tests if a value is a 1-dimensional ndarray-like object containing single-\n    precision complex floating-point numbers.\n","isComplex128":"\nisComplex128( value:any )\n    Tests if a value is a 128-bit complex number.\n","isComplex128Array":"\nisComplex128Array( value:any )\n    Tests if a value is a Complex128Array.\n","isComplex128MatrixLike":"\nisComplex128MatrixLike( value:any )\n    Tests if a value is a 2-dimensional ndarray-like object containing double-\n    precision complex floating-point numbers.\n","isComplex128ndarrayLike":"\nisComplex128ndarrayLike( value:any )\n    Tests if a value is an ndarray-like object containing double-precision\n    complex floating-point numbers.\n","isComplex128VectorLike":"\nisComplex128VectorLike( value:any )\n    Tests if a value is a 1-dimensional ndarray-like object containing double-\n    precision complex floating-point numbers.\n","isComplexLike":"\nisComplexLike( value:any )\n    Tests if a value is a complex number-like object.\n","isComplexTypedArray":"\nisComplexTypedArray( value:any )\n    Tests if a value is a complex typed array.\n","isComplexTypedArrayLike":"\nisComplexTypedArrayLike( value:any )\n    Tests if a value is complex-typed-array-like.\n","isComposite":"\nisComposite( value:any )\n    Tests if a value is a composite number.\n","isComposite.isPrimitive":"\nisComposite.isPrimitive( value:any )\n    Tests if a value is a number primitive which is a composite number.\n","isComposite.isObject":"\nisComposite.isObject( value:any )\n    Tests if a value is a number object having a value which is a composite\n    number.\n","isConfigurableProperty":"\nisConfigurableProperty( value:any, property:any )\n    Tests if an object's own property is configurable.\n","isConfigurablePropertyIn":"\nisConfigurablePropertyIn( value:any, property:any )\n    Tests if an object's own or inherited property is configurable.\n","isConstantcase":"\nisConstantcase( value:any )\n    Tests if a value is a constantcase string.\n","isCubeNumber":"\nisCubeNumber( value:any )\n    Tests if a value is a cube number.\n","isCubeNumber.isPrimitive":"\nisCubeNumber.isPrimitive( value:any )\n    Tests if a value is a number primitive which is a cube number.\n","isCubeNumber.isObject":"\nisCubeNumber.isObject( value:any )\n    Tests if a value is a number object having a value which is a cube number.\n","isCurrentYear":"\nisCurrentYear( value:any )\n    Tests if a value is the current year.\n","isDataProperty":"\nisDataProperty( value:any, property:any )\n    Tests if an object's own property has a data descriptor.\n","isDataPropertyIn":"\nisDataPropertyIn( value:any, property:any )\n    Tests if an object's own or inherited property has a data descriptor.\n","isDataView":"\nisDataView( value:any )\n    Tests if a value is a DataView.\n","isDateObject":"\nisDateObject( value:any )\n    Tests if a value is a Date object.\n","isDateObjectArray":"\nisDateObjectArray( value:any )\n    Tests if a value is an array-like object containing only Date objects.\n","isDigitString":"\nisDigitString( str:string )\n    Tests whether a string contains only numeric digits.\n","isDomainName":"\nisDomainName( value:any )\n    Tests if a value is a domain name.\n","isDurationString":"\nisDurationString( value:any )\n    Tests if a value is a duration string.\n","isEmailAddress":"\nisEmailAddress( value:any )\n    Tests if a value is an email address.\n","isEmptyArray":"\nisEmptyArray( value:any )\n    Tests if a value is an empty array.\n","isEmptyArrayLikeObject":"\nisEmptyArrayLikeObject( value:any )\n    Tests if a value is an empty array-like object.\n","isEmptyCollection":"\nisEmptyCollection( value:any )\n    Tests if a value is an empty collection.\n","isEmptyObject":"\nisEmptyObject( value:any )\n    Tests if a value is an empty object.\n","isEmptyString":"\nisEmptyString( value:any )\n    Tests if a value is an empty string.\n","isEmptyString.isPrimitive":"\nisEmptyString.isPrimitive( value:any )\n    Tests if a value is an empty string primitive.\n","isEmptyString.isObject":"\nisEmptyString.isObject( value:any )\n    Tests if a value is an empty `String` object.\n","isEnumerableProperty":"\nisEnumerableProperty( value:any, property:any )\n    Tests if an object's own property is enumerable.\n","isEnumerablePropertyIn":"\nisEnumerablePropertyIn( value:any, property:any )\n    Tests if an object's own or inherited property is enumerable.\n","isEqualArray":"\nisEqualArray( v1:any, v2:any )\n    Tests if two arguments are both generic arrays and have equal values.\n","isError":"\nisError( value:any )\n    Tests if a value is an Error object.\n","isEvalError":"\nisEvalError( value:any )\n    Tests if a value is an EvalError object.\n","isEven":"\nisEven( value:any )\n    Tests if a value is an even number.\n","isEven.isPrimitive":"\nisEven.isPrimitive( value:any )\n    Tests if a value is a number primitive that is an even number.\n","isEven.isObject":"\nisEven.isObject( value:any )\n    Tests if a value is a number object that is an even number.\n","isFalsy":"\nisFalsy( value:any )\n    Tests if a value is a value which translates to `false` when evaluated in a\n    boolean context.\n","isFalsyArray":"\nisFalsyArray( value:any )\n    Tests if a value is an array-like object containing only falsy values.\n","isFinite":"\nisFinite( value:any )\n    Tests if a value is a finite number.\n","isFinite.isPrimitive":"\nisFinite.isPrimitive( value:any )\n    Tests if a value is a number primitive having a finite value.\n","isFinite.isObject":"\nisFinite.isObject( value:any )\n    Tests if a value is a number object having a finite value.\n","isFiniteArray":"\nisFiniteArray( value:any )\n    Tests if a value is an array-like object of finite numbers.\n","isFiniteArray.primitives":"\nisFiniteArray.primitives( value:any )\n    Tests if a value is an array-like object containing only primitive finite\n    numbers.\n","isFiniteArray.objects":"\nisFiniteArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having finite values.\n","isFloat32Array":"\nisFloat32Array( value:any )\n    Tests if a value is a Float32Array.\n","isFloat32MatrixLike":"\nisFloat32MatrixLike( value:any )\n    Tests if a value is a 2-dimensional ndarray-like object containing single-\n    precision floating-point numbers.\n","isFloat32ndarrayLike":"\nisFloat32ndarrayLike( value:any )\n    Tests if a value is an ndarray-like object containing single-precision\n    floating-point numbers.\n","isFloat32VectorLike":"\nisFloat32VectorLike( value:any )\n    Tests if a value is a 1-dimensional ndarray-like object containing single-\n    precision floating-point numbers.\n","isFloat64Array":"\nisFloat64Array( value:any )\n    Tests if a value is a Float64Array.\n","isFloat64MatrixLike":"\nisFloat64MatrixLike( value:any )\n    Tests if a value is a 2-dimensional ndarray-like object containing double-\n    precision floating-point numbers.\n","isFloat64ndarrayLike":"\nisFloat64ndarrayLike( value:any )\n    Tests if a value is an ndarray-like object containing double-precision\n    floating-point numbers.\n","isFloat64VectorLike":"\nisFloat64VectorLike( value:any )\n    Tests if a value is a 1-dimensional ndarray-like object containing double-\n    precision floating-point numbers.\n","isFunction":"\nisFunction( value:any )\n    Tests if a value is a function.\n","isFunctionArray":"\nisFunctionArray( value:any )\n    Tests if a value is an array-like object containing only functions.\n","isGeneratorObject":"\nisGeneratorObject( value:any )\n    Tests if a value is a generator object.\n","isGeneratorObjectLike":"\nisGeneratorObjectLike( value:any )\n    Tests if a value is generator object-like.\n","isgzipBuffer":"\nisgzipBuffer( value:any )\n    Tests if a value is a gzip buffer.\n","isHexString":"\nisHexString( str:string )\n    Tests whether a string contains only hexadecimal digits.\n","isInfinite":"\nisInfinite( value:any )\n    Tests if a value is an infinite number.\n","isInfinite.isPrimitive":"\nisInfinite.isPrimitive( value:any )\n    Tests if a value is a number primitive having an infinite value.\n","isInfinite.isObject":"\nisInfinite.isObject( value:any )\n    Tests if a value is a number object having an infinite value.\n","isInheritedProperty":"\nisInheritedProperty( value:any, property:any )\n    Tests if an object has an inherited property.\n","isInt8Array":"\nisInt8Array( value:any )\n    Tests if a value is an Int8Array.\n","isInt16Array":"\nisInt16Array( value:any )\n    Tests if a value is an Int16Array.\n","isInt32Array":"\nisInt32Array( value:any )\n    Tests if a value is an Int32Array.\n","isInteger":"\nisInteger( value:any )\n    Tests if a value is an integer.\n","isInteger.isPrimitive":"\nisInteger.isPrimitive( value:any )\n    Tests if a value is a number primitive having an integer value.\n","isInteger.isObject":"\nisInteger.isObject( value:any )\n    Tests if a value is a number object having an integer value.\n","isIntegerArray":"\nisIntegerArray( value:any )\n    Tests if a value is an array-like object of integer values.\n","isIntegerArray.primitives":"\nisIntegerArray.primitives( value:any )\n    Tests if a value is an array-like object containing only primitive integer\n    values.\n","isIntegerArray.objects":"\nisIntegerArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having integer values.\n","isIterableLike":"\nisIterableLike( value:any )\n    Tests if a value is iterable-like.\n","isIteratorLike":"\nisIteratorLike( value:any )\n    Tests if a value is iterator-like.\n","isJSON":"\nisJSON( value:any )\n    Tests if a value is a parseable JSON string.\n","isKebabcase":"\nisKebabcase( value:any )\n    Tests if a value is a string in kebab case.\n","isLeapYear":"\nisLeapYear( value:any )\n    Tests whether a value corresponds to a leap year in the Gregorian calendar.\n","isLocalhost":"\nisLocalhost( value:any )\n    Tests whether a value is a localhost hostname.\n","isLowercase":"\nisLowercase( value:any )\n    Tests if a value is a lowercase string.\n","isMatrixLike":"\nisMatrixLike( value:any )\n    Tests if a value is a 2-dimensional ndarray-like object.\n","isMethod":"\nisMethod( value:any, property:any )\n    Tests if an object has a specified method name.\n","isMethodIn":"\nisMethodIn( value:any, property:any )\n    Tests if an object has a specified method name, either own or inherited.\n","isMultiSlice":"\nisMultiSlice( value:any )\n    Tests if a value is a MultiSlice object.\n","isNamedTypedTupleLike":"\nisNamedTypedTupleLike( value:any )\n    Tests if a value is named typed tuple-like.\n","isnan":"\nisnan( value:any )\n    Tests if a value is NaN.\n","isnan.isPrimitive":"\nisnan.isPrimitive( value:any )\n    Tests if a value is a NaN number primitive.\n","isnan.isObject":"\nisnan.isObject( value:any )\n    Tests if a value is a number object having a value of NaN.\n","isNaNArray":"\nisNaNArray( value:any )\n    Tests if a value is an array-like object containing only NaN values.\n","isNaNArray.primitives":"\nisNaNArray.primitives( value:any )\n    Tests if a value is an array-like object containing only primitive NaN\n    values.\n","isNaNArray.objects":"\nisNaNArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having NaN values.\n","isNativeFunction":"\nisNativeFunction( value:any )\n    Tests if a value is a native function.\n","isndarrayLike":"\nisndarrayLike( value:any )\n    Tests if a value is ndarray-like.\n","isndarrayLikeWithDataType":"\nisndarrayLikeWithDataType( value:any, dtype:any )\n    Tests if a value is an ndarray-like object having a specified data type.\n","isNegativeFinite":"\nisNegativeFinite( value:any )\n    Tests if a value is a finite negative number.\n","isNegativeFinite.isPrimitive":"\nisNegativeFinite.isPrimitive( value:any )\n    Tests if a value is a number primitive having a finite negative value.\n","isNegativeFinite.isObject":"\nisNegativeFinite.isObject( value:any )\n    Tests if a value is a number object having a finite negative value.\n","isNegativeInteger":"\nisNegativeInteger( value:any )\n    Tests if a value is a negative integer.\n","isNegativeInteger.isPrimitive":"\nisNegativeInteger.isPrimitive( value:any )\n    Tests if a value is a number primitive having a negative integer value.\n","isNegativeInteger.isObject":"\nisNegativeInteger.isObject( value:any )\n    Tests if a value is a number object having a negative integer value.\n","isNegativeIntegerArray":"\nisNegativeIntegerArray( value:any )\n    Tests if a value is an array-like object containing only negative integers.\n","isNegativeIntegerArray.primitives":"\nisNegativeIntegerArray.primitives( value:any )\n    Tests if a value is an array-like object containing only negative primitive\n    integer values.\n","isNegativeIntegerArray.objects":"\nisNegativeIntegerArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having negative integer values.\n","isNegativeNumber":"\nisNegativeNumber( value:any )\n    Tests if a value is a negative number.\n","isNegativeNumber.isPrimitive":"\nisNegativeNumber.isPrimitive( value:any )\n    Tests if a value is a number primitive having a negative value.\n","isNegativeNumber.isObject":"\nisNegativeNumber.isObject( value:any )\n    Tests if a value is a number object having a negative value.\n","isNegativeNumberArray":"\nisNegativeNumberArray( value:any )\n    Tests if a value is an array-like object containing only negative numbers.\n","isNegativeNumberArray.primitives":"\nisNegativeNumberArray.primitives( value:any )\n    Tests if a value is an array-like object containing only primitive negative\n    numbers.\n","isNegativeNumberArray.objects":"\nisNegativeNumberArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having negative number values.\n","isNegativeZero":"\nisNegativeZero( value:any )\n    Tests if a value is negative zero.\n","isNegativeZero.isPrimitive":"\nisNegativeZero.isPrimitive( value:any )\n    Tests if a value is a number primitive equal to negative zero.\n","isNegativeZero.isObject":"\nisNegativeZero.isObject( value:any )\n    Tests if a value is a number object having a value equal to negative zero.\n","isNodeBuiltin":"\nisNodeBuiltin( str:string )\n    Tests whether a string matches a Node.js built-in module name.\n","isNodeDuplexStreamLike":"\nisNodeDuplexStreamLike( value:any )\n    Tests if a value is Node duplex stream-like.\n","isNodeReadableStreamLike":"\nisNodeReadableStreamLike( value:any )\n    Tests if a value is Node readable stream-like.\n","isNodeREPL":"\nisNodeREPL()\n    Returns a boolean indicating if running in a Node.js REPL environment.\n","isNodeStreamLike":"\nisNodeStreamLike( value:any )\n    Tests if a value is Node stream-like.\n","isNodeTransformStreamLike":"\nisNodeTransformStreamLike( value:any )\n    Tests if a value is Node transform stream-like.\n","isNodeWritableStreamLike":"\nisNodeWritableStreamLike( value:any )\n    Tests if a value is Node writable stream-like.\n","isNonConfigurableProperty":"\nisNonConfigurableProperty( value:any, property:any )\n    Tests if an object's own property is non-configurable.\n","isNonConfigurablePropertyIn":"\nisNonConfigurablePropertyIn( value:any, property:any )\n    Tests if an object's own or inherited property is non-configurable.\n","isNonEnumerableProperty":"\nisNonEnumerableProperty( value:any, property:any )\n    Tests if an object's own property is non-enumerable.\n","isNonEnumerablePropertyIn":"\nisNonEnumerablePropertyIn( value:any, property:any )\n    Tests if an object's own or inherited property is non-enumerable.\n","isNonNegativeFinite":"\nisNonNegativeFinite( value:any )\n    Tests if a value is a nonnegative finite number.\n","isNonNegativeFinite.isPrimitive":"\nisNonNegativeFinite.isPrimitive( value:any )\n    Tests if a value is a number primitive having a nonnegative finite value.\n","isNonNegativeFinite.isObject":"\nisNonNegativeFinite.isObject( value:any )\n    Tests if a value is a number object having a nonnegative finite value.\n","isNonNegativeInteger":"\nisNonNegativeInteger( value:any )\n    Tests if a value is a nonnegative integer.\n","isNonNegativeInteger.isPrimitive":"\nisNonNegativeInteger.isPrimitive( value:any )\n    Tests if a value is a number primitive having a nonnegative integer value.\n","isNonNegativeInteger.isObject":"\nisNonNegativeInteger.isObject( value:any )\n    Tests if a value is a number object having a nonnegative integer value.\n","isNonNegativeIntegerArray":"\nisNonNegativeIntegerArray( value:any )\n    Tests if a value is an array-like object containing only nonnegative\n    integers.\n","isNonNegativeIntegerArray.primitives":"\nisNonNegativeIntegerArray.primitives( value:any )\n    Tests if a value is an array-like object containing only nonnegative\n    primitive integer values.\n","isNonNegativeIntegerArray.objects":"\nisNonNegativeIntegerArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having nonnegative integer values.\n","isNonNegativeNumber":"\nisNonNegativeNumber( value:any )\n    Tests if a value is a nonnegative number.\n","isNonNegativeNumber.isPrimitive":"\nisNonNegativeNumber.isPrimitive( value:any )\n    Tests if a value is a number primitive having a nonnegative value.\n","isNonNegativeNumber.isObject":"\nisNonNegativeNumber.isObject( value:any )\n    Tests if a value is a number object having a nonnegative value.\n","isNonNegativeNumberArray":"\nisNonNegativeNumberArray( value:any )\n    Tests if a value is an array-like object containing only nonnegative\n    numbers.\n","isNonNegativeNumberArray.primitives":"\nisNonNegativeNumberArray.primitives( value:any )\n    Tests if a value is an array-like object containing only primitive\n    nonnegative numbers.\n","isNonNegativeNumberArray.objects":"\nisNonNegativeNumberArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having nonnegative number values.\n","isNonPositiveFinite":"\nisNonPositiveFinite( value:any )\n    Tests if a value is a nonpositive finite number.\n","isNonPositiveFinite.isPrimitive":"\nisNonPositiveFinite.isPrimitive( value:any )\n    Tests if a value is a number primitive having a nonpositive finite value.\n","isNonPositiveFinite.isObject":"\nisNonPositiveFinite.isObject( value:any )\n    Tests if a value is a number object having a nonpositive finite value.\n","isNonPositiveInteger":"\nisNonPositiveInteger( value:any )\n    Tests if a value is a nonpositive integer.\n","isNonPositiveInteger.isPrimitive":"\nisNonPositiveInteger.isPrimitive( value:any )\n    Tests if a value is a number primitive having a nonpositive integer value.\n","isNonPositiveInteger.isObject":"\nisNonPositiveInteger.isObject( value:any )\n    Tests if a value is a number object having a nonpositive integer value.\n","isNonPositiveIntegerArray":"\nisNonPositiveIntegerArray( value:any )\n    Tests if a value is an array-like object containing only nonpositive\n    integers.\n","isNonPositiveIntegerArray.primitives":"\nisNonPositiveIntegerArray.primitives( value:any )\n    Tests if a value is an array-like object containing only nonpositive\n    primitive integer values.\n","isNonPositiveIntegerArray.objects":"\nisNonPositiveIntegerArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having nonpositive integer values.\n","isNonPositiveNumber":"\nisNonPositiveNumber( value:any )\n    Tests if a value is a nonpositive number.\n","isNonPositiveNumber.isPrimitive":"\nisNonPositiveNumber.isPrimitive( value:any )\n    Tests if a value is a number primitive having a nonpositive value.\n","isNonPositiveNumber.isObject":"\nisNonPositiveNumber.isObject( value:any )\n    Tests if a value is a number object having a nonpositive value.\n","isNonPositiveNumberArray":"\nisNonPositiveNumberArray( value:any )\n    Tests if a value is an array-like object containing only nonpositive\n    numbers.\n","isNonPositiveNumberArray.primitives":"\nisNonPositiveNumberArray.primitives( value:any )\n    Tests if a value is an array-like object containing only primitive\n    nonpositive numbers.\n","isNonPositiveNumberArray.objects":"\nisNonPositiveNumberArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having nonpositive number values.\n","isNonSymmetricMatrix":"\nisNonSymmetricMatrix( value:any )\n    Tests if a value is a non-symmetric matrix.\n","isNull":"\nisNull( value:any )\n    Tests if a value is null.\n","isNullArray":"\nisNullArray( value:any )\n    Tests if a value is an array-like object containing only null values.\n","isNumber":"\nisNumber( value:any )\n    Tests if a value is a number.\n","isNumber.isPrimitive":"\nisNumber.isPrimitive( value:any )\n    Tests if a value is a number primitive.\n","isNumber.isObject":"\nisNumber.isObject( value:any )\n    Tests if a value is a `Number` object.\n","isNumberArray":"\nisNumberArray( value:any )\n    Tests if a value is an array-like object containing only numbers.\n","isNumberArray.primitives":"\nisNumberArray.primitives( value:any )\n    Tests if a value is an array-like object containing only number primitives.\n","isNumberArray.objects":"\nisNumberArray.objects( value:any )\n    Tests if a value is an array-like object containing only `Number` objects.\n","isNumericArray":"\nisNumericArray( value:any )\n    Tests if a value is a numeric array.\n","isObject":"\nisObject( value:any )\n    Tests if a value is an object; e.g., `{}`.\n","isObjectArray":"\nisObjectArray( value:any )\n    Tests if a value is an array-like object containing only objects.\n","isObjectLike":"\nisObjectLike( value:any )\n    Tests if a value is object-like.\n","isOdd":"\nisOdd( value:any )\n    Tests if a value is an odd number.\n","isOdd.isPrimitive":"\nisOdd.isPrimitive( value:any )\n    Tests if a value is a number primitive that is an odd number.\n","isOdd.isObject":"\nisOdd.isObject( value:any )\n    Tests if a value is a number object that has an odd number value.\n","isoWeeksInYear":"\nisoWeeksInYear( [year:integer] )\n    Returns the number of ISO weeks in a year according to the Gregorian\n    calendar.\n","isPascalcase":"\nisPascalcase( value:any )\n    Tests if a value is a string in Pascal case.\n","isPersymmetricMatrix":"\nisPersymmetricMatrix( value:any )\n    Tests if a value is a square matrix which is symmetric about its\n    antidiagonal.\n","isPlainObject":"\nisPlainObject( value:any )\n    Tests if a value is a plain object.\n","isPlainObjectArray":"\nisPlainObjectArray( value:any )\n    Tests if a value is an array-like object containing only plain objects.\n","isPositiveFinite":"\nisPositiveFinite( value:any )\n    Tests if a value is a positive finite number.\n","isPositiveFinite.isPrimitive":"\nisPositiveFinite.isPrimitive( value:any )\n    Tests if a value is a number primitive having a positive finite value.\n","isPositiveFinite.isObject":"\nisPositiveFinite.isObject( value:any )\n    Tests if a value is a number object having a positive finite value.\n","isPositiveInteger":"\nisPositiveInteger( value:any )\n    Tests if a value is a positive integer.\n","isPositiveInteger.isPrimitive":"\nisPositiveInteger.isPrimitive( value:any )\n    Tests if a value is a number primitive having a positive integer value.\n","isPositiveInteger.isObject":"\nisPositiveInteger.isObject( value:any )\n    Tests if a value is a number object having a positive integer value.\n","isPositiveIntegerArray":"\nisPositiveIntegerArray( value:any )\n    Tests if a value is an array-like object containing only positive integers.\n","isPositiveIntegerArray.primitives":"\nisPositiveIntegerArray.primitives( value:any )\n    Tests if a value is an array-like object containing only positive primitive\n    integer values.\n","isPositiveIntegerArray.objects":"\nisPositiveIntegerArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having positive integer values.\n","isPositiveNumber":"\nisPositiveNumber( value:any )\n    Tests if a value is a positive number.\n","isPositiveNumber.isPrimitive":"\nisPositiveNumber.isPrimitive( value:any )\n    Tests if a value is a number primitive having a positive value.\n","isPositiveNumber.isObject":"\nisPositiveNumber.isObject( value:any )\n    Tests if a value is a number object having a positive value.\n","isPositiveNumberArray":"\nisPositiveNumberArray( value:any )\n    Tests if a value is an array-like object containing only positive numbers.\n","isPositiveNumberArray.primitives":"\nisPositiveNumberArray.primitives( value:any )\n    Tests if a value is an array-like object containing only positive primitive\n    number values.\n","isPositiveNumberArray.objects":"\nisPositiveNumberArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having positive values.\n","isPositiveZero":"\nisPositiveZero( value:any )\n    Tests if a value is positive zero.\n","isPositiveZero.isPrimitive":"\nisPositiveZero.isPrimitive( value:any )\n    Tests if a value is a number primitive equal to positive zero.\n","isPositiveZero.isObject":"\nisPositiveZero.isObject( value:any )\n    Tests if a value is a number object having a value equal to positive zero.\n","isPrime":"\nisPrime( value:any )\n    Tests if a value is a prime number.\n","isPrime.isPrimitive":"\nisPrime.isPrimitive( value:any )\n    Tests if a value is a number primitive which is a prime number.\n","isPrime.isObject":"\nisPrime.isObject( value:any )\n    Tests if a value is a number object having a value which is a prime number.\n","isPrimitive":"\nisPrimitive( value:any )\n    Tests if a value is a JavaScript primitive.\n","isPrimitiveArray":"\nisPrimitiveArray( value:any )\n    Tests if a value is an array-like object containing only JavaScript\n    primitives.\n","isPRNGLike":"\nisPRNGLike( value:any )\n    Tests if a value is PRNG-like.\n","isProbability":"\nisProbability( value:any )\n    Tests if a value is a probability.\n","isProbability.isPrimitive":"\nisProbability.isPrimitive( value:any )\n    Tests if a value is a number primitive which is a probability.\n","isProbability.isObject":"\nisProbability.isObject( value:any )\n    Tests if a value is a number object having a value which is a probability.\n","isProbabilityArray":"\nisProbabilityArray( value:any )\n    Tests if a value is an array-like object containing only probabilities.\n","isProbabilityArray.primitives":"\nisProbabilityArray.primitives( value:any )\n    Tests if a value is an array-like object containing only primitive\n    probabilities.\n","isProbabilityArray.objects":"\nisProbabilityArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having probability values.\n","isPropertyKey":"\nisPropertyKey( value:any )\n    Tests whether a value is a property key.\n","isPrototypeOf":"\nisPrototypeOf( value:any, proto:Object|Function )\n    Tests if an object's prototype chain contains a provided prototype.\n","isRaggedNestedArray":"\nisRaggedNestedArray( value:any )\n    Tests if a value is a ragged nested array. \n","isRangeError":"\nisRangeError( value:any )\n    Tests if a value is a RangeError object.\n","isReadableProperty":"\nisReadableProperty( value:any, property:any )\n    Tests if an object's own property is readable.\n","isReadablePropertyIn":"\nisReadablePropertyIn( value:any, property:any )\n    Tests if an object's own or inherited property is readable.\n","isReadOnlyProperty":"\nisReadOnlyProperty( value:any, property:any )\n    Tests if an object's own property is read-only.\n","isReadOnlyPropertyIn":"\nisReadOnlyPropertyIn( value:any, property:any )\n    Tests if an object's own or inherited property is read-only.\n","isReadWriteProperty":"\nisReadWriteProperty( value:any, property:any )\n    Tests if an object's own property is readable and writable.\n","isReadWritePropertyIn":"\nisReadWritePropertyIn( value:any, property:any )\n    Tests if an object's own or inherited property is readable and writable.\n","isReferenceError":"\nisReferenceError( value:any )\n    Tests if a value is a ReferenceError object.\n","isRegExp":"\nisRegExp( value:any )\n    Tests if a value is a regular expression.\n","isRegExpString":"\nisRegExpString( value:any )\n    Tests if a value is a regular expression string.\n","isRelativePath":"\nisRelativePath( value:any )\n    Tests if a value is a relative path.\n","isRelativePath.posix":"\nisRelativePath.posix( value:any )\n    Tests if a value is a POSIX relative path.\n","isRelativePath.win32":"\nisRelativePath.win32( value:any )\n    Tests if a value is a Windows relative path.\n","isRelativeURI":"\nisRelativeURI( value:any )\n    Tests whether a value is a relative URI.\n","isSafeInteger":"\nisSafeInteger( value:any )\n    Tests if a value is a safe integer.\n","isSafeInteger.isPrimitive":"\nisSafeInteger.isPrimitive( value:any )\n    Tests if a value is a number primitive having a safe integer value.\n","isSafeInteger.isObject":"\nisSafeInteger.isObject( value:any )\n    Tests if a value is a `Number` object having a safe integer value.\n","isSafeIntegerArray":"\nisSafeIntegerArray( value:any )\n    Tests if a value is an array-like object containing only safe integers.\n","isSafeIntegerArray.primitives":"\nisSafeIntegerArray.primitives( value:any )\n    Tests if a value is an array-like object containing only primitive safe\n    integer values.\n","isSafeIntegerArray.objects":"\nisSafeIntegerArray.objects( value:any )\n    Tests if a value is an array-like object containing only `Number` objects\n    having safe integer values.\n","isSameArray":"\nisSameArray( v1:any, v2:any )\n    Tests if two arguments are both generic arrays and have the same values.\n","isSameArrayLike":"\nisSameArrayLike( v1:any, v2:any )\n    Tests if two arguments are both array-like and have the same values.\n","isSameComplex64":"\nisSameComplex64( v1:any, v2:any )\n    Tests if two arguments are both single-precision complex floating-point\n    numbers and have the same value.\n","isSameComplex64Array":"\nisSameComplex64Array( v1:any, v2:any )\n    Tests if two arguments are both Complex64Arrays and have the same values.\n","isSameComplex128":"\nisSameComplex128( v1:any, v2:any )\n    Tests if two arguments are both double-precision complex floating-point\n    numbers and have the same value.\n","isSameComplex128Array":"\nisSameComplex128Array( v1:any, v2:any )\n    Tests if two arguments are both Complex128Arrays and have the same values.\n","isSameDateObject":"\nisSameDateObject( d1, d2 )\n    Tests if two values are both Date objects corresponding \n    to the same date and time.\n","isSameFloat32Array":"\nisSameFloat32Array( v1:any, v2:any )\n    Tests if two arguments are both Float32Arrays and have the same values.\n","isSameFloat64Array":"\nisSameFloat64Array( v1:any, v2:any )\n    Tests if two arguments are both Float64Arrays and have the same values.\n","isSameNativeClass":"\nisSameNativeClass( a:any, b:any )\n    Tests if two arguments have the same native class.\n","isSameType":"\nisSameType( a:any, b:any )\n    Tests if two arguments have the same type.\n","isSameValue":"\nisSameValue( a:any, b:any )\n    Tests if two arguments are the same value.\n","isSameValueZero":"\nisSameValueZero( a:any, b:any )\n    Tests if two arguments are the same value.\n","isSemVer":"\nisSemVer( value:any )\n    Tests if a value is a semantic version string.\n","isSharedArrayBuffer":"\nisSharedArrayBuffer( value:any )\n    Tests if a value is a SharedArrayBuffer.\n","isSkewCentrosymmetricMatrix":"\nisSkewCentrosymmetricMatrix( value:any )\n    Tests if a value is a skew-centrosymmetric matrix.\n","isSkewPersymmetricMatrix":"\nisSkewPersymmetricMatrix( value:any )\n    Tests if a value is a skew-persymmetric matrix.\n","isSkewSymmetricMatrix":"\nisSkewSymmetricMatrix( value:any )\n    Tests if a value is a skew-symmetric (or antisymmetric) matrix.\n","isSlice":"\nisSlice( value:any )\n    Tests if a value is a Slice object.\n","isSnakecase":"\nisSnakecase( value:any )\n    Tests if a value is a string in snake case.\n","isSquareMatrix":"\nisSquareMatrix( value:any )\n    Tests if a value is a 2-dimensional ndarray-like object having equal\n    dimensions.\n","isSquareNumber":"\nisSquareNumber( value:any )\n    Tests if a value is a square number.\n","isSquareNumber.isPrimitive":"\nisSquareNumber.isPrimitive( value:any )\n    Tests if a value is a number primitive which is a square number.\n","isSquareNumber.isObject":"\nisSquareNumber.isObject( value:any )\n    Tests if a value is a number object having a value which is a square number.\n","isSquareTriangularNumber":"\nisSquareTriangularNumber( value:any )\n    Tests if a value is a square triangular number.\n","isSquareTriangularNumber.isPrimitive":"\nisSquareTriangularNumber.isPrimitive( value:any )\n    Tests if a value is a number primitive which is a square triangular number.\n","isSquareTriangularNumber.isObject":"\nisSquareTriangularNumber.isObject( value:any )\n    Tests if a value is a number object having a value which is a square\n    triangular number.\n","isStartcase":"\nisStartcase( value:any )\n    Tests if a value is a startcase string.\n","isStrictEqual":"\nisStrictEqual( a:any, b:any )\n    Tests if two arguments are strictly equal.\n","isString":"\nisString( value:any )\n    Tests if a value is a string.\n","isString.isPrimitive":"\nisString.isPrimitive( value:any )\n    Tests if a value is a string primitive.\n","isString.isObject":"\nisString.isObject( value:any )\n    Tests if a value is a `String` object.\n","isStringArray":"\nisStringArray( value:any )\n    Tests if a value is an array of strings.\n","isStringArray.primitives":"\nisStringArray.primitives( value:any )\n    Tests if a value is an array containing only string primitives.\n","isStringArray.objects":"\nisStringArray.objects( value:any )\n    Tests if a value is an array containing only `String` objects.\n","isSymbol":"\nisSymbol( value:any )\n    Tests if a value is a symbol.\n","isSymbolArray":"\nisSymbolArray( value:any )\n    Tests if a value is an array-like object containing only symbols.\n","isSymbolArray.primitives":"\nisSymbolArray.primitives( value:any )\n    Tests if a value is an array-like object containing only `symbol`\n    primitives.\n","isSymbolArray.objects":"\nisSymbolArray.objects( value:any )\n    Tests if a value is an array-like object containing only `Symbol`\n    objects.\n","isSymmetricMatrix":"\nisSymmetricMatrix( value:any )\n    Tests if a value is a square matrix which equals its transpose.\n","isSyntaxError":"\nisSyntaxError( value:any )\n    Tests if a value is a SyntaxError object.\n","isTriangularNumber":"\nisTriangularNumber( value:any )\n    Tests if a value is a triangular number.\n","isTriangularNumber.isPrimitive":"\nisTriangularNumber.isPrimitive( value:any )\n    Tests if a value is a number primitive which is a triangular number.\n","isTriangularNumber.isObject":"\nisTriangularNumber.isObject( value:any )\n    Tests if a value is a number object having a value which is a triangular\n    number.\n","isTruthy":"\nisTruthy( value:any )\n    Tests if a value is a value which translates to `true` when evaluated in a\n    boolean context.\n","isTruthyArray":"\nisTruthyArray( value:any )\n    Tests if a value is an array-like object containing only truthy values.\n","isTypedArray":"\nisTypedArray( value:any )\n    Tests if a value is a typed array.\n","isTypedArrayLength":"\nisTypedArrayLength( value:any )\n    Tests if a value is a valid typed array length.\n","isTypedArrayLike":"\nisTypedArrayLike( value:any )\n    Tests if a value is typed-array-like.\n","isTypeError":"\nisTypeError( value:any )\n    Tests if a value is a TypeError object.\n","isUint8Array":"\nisUint8Array( value:any )\n    Tests if a value is a Uint8Array.\n","isUint8ClampedArray":"\nisUint8ClampedArray( value:any )\n    Tests if a value is a Uint8ClampedArray.\n","isUint16Array":"\nisUint16Array( value:any )\n    Tests if a value is a Uint16Array.\n","isUint32Array":"\nisUint32Array( value:any )\n    Tests if a value is a Uint32Array.\n","isUNCPath":"\nisUNCPath( value:any )\n    Tests if a value is a UNC path.\n","isUndefined":"\nisUndefined( value:any )\n    Tests if a value is undefined.\n","isUndefinedOrNull":"\nisUndefinedOrNull( value:any )\n    Tests if a value is undefined or null.\n","isUnityProbabilityArray":"\nisUnityProbabilityArray( value:any )\n    Tests if a value is an array of probabilities that sum to one.\n","isUppercase":"\nisUppercase( value:any )\n    Tests if a value is an uppercase string.\n","isURI":"\nisURI( value:any )\n    Tests if a value is a URI.\n","isURIError":"\nisURIError( value:any )\n    Tests if a value is a URIError object.\n","isVectorLike":"\nisVectorLike( value:any )\n    Tests if a value is a 1-dimensional ndarray-like object.\n","isWebAssemblyMemory":"\nisWebAssemblyMemory( value:any )\n    Tests if a value is a WebAssembly memory instance.\n","isWellFormedString":"\nisWellFormedString( str:any )\n    Tests if a string is well-formed.\n","isWellFormedString.isPrimitive":"\nisWellFormedString.isPrimitive( str:any )\n    Tests if a string is a well-formed string primitive.\n","isWellFormedString.isObject":"\nisWellFormedString.isObject( str:any )\n    Tests if a string is a well-formed string object.\n","isWhitespace":"\nisWhitespace( str:string )\n    Tests whether a string contains only white space characters.\n","isWritableProperty":"\nisWritableProperty( value:any, property:any )\n    Tests if an object's own property is writable.\n","isWritablePropertyIn":"\nisWritablePropertyIn( value:any, property:any )\n    Tests if an object's own or inherited property is writable.\n","isWriteOnlyProperty":"\nisWriteOnlyProperty( value:any, property:any )\n    Tests if an object's own property is write-only.\n","isWriteOnlyPropertyIn":"\nisWriteOnlyPropertyIn( value:any, property:any )\n    Tests if an object's own or inherited property is write-only.\n","iterAbs":"\niterAbs( iterator:Object )\n    Returns an iterator which iteratively computes the absolute value.\n","iterAbs2":"\niterAbs2( iterator:Object )\n    Returns an iterator which iteratively computes the squared absolute value.\n","iterAcos":"\niterAcos( iterator:Object )\n    Returns an iterator which iteratively computes the arccosine.\n","iterAcosh":"\niterAcosh( iterator:Object )\n    Returns an iterator which iteratively computes the hyperbolic arccosine.\n","iterAcot":"\niterAcot( iterator:Object )\n    Returns an iterator which iteratively computes the inverse cotangent.\n","iterAcoth":"\niterAcoth( iterator:Object )\n    Returns an iterator which iteratively computes the inverse hyperbolic\n    cotangent.\n","iterAcovercos":"\niterAcovercos( iterator:Object )\n    Returns an iterator which iteratively computes the inverse coversed cosine.\n","iterAcoversin":"\niterAcoversin( iterator:Object )\n    Returns an iterator which iteratively computes the inverse coversed sine.\n","iterAdd":"\niterAdd( iter0:Object, ...iterator:Object )\n    Returns an iterator which performs element-wise addition of two or more\n    iterators.\n","iterAdvance":"\niterAdvance( iterator:Object[, n:integer] )\n    Advances an entire iterator.\n","iterAhavercos":"\niterAhavercos( iterator:Object )\n    Returns an iterator which iteratively computes the inverse half-value versed\n    cosine.\n","iterAhaversin":"\niterAhaversin( iterator:Object )\n    Returns an iterator which iteratively computes the inverse half-value versed\n    sine.\n","iterAny":"\niterAny( iterator:Object )\n    Tests whether at least one iterated value is truthy.\n","iterAnyBy":"\niterAnyBy( iterator:Object, predicate:Function[, thisArg:any ] )\n    Tests whether at least one iterated value passes a test implemented by a\n    predicate function.\n","iterAsin":"\niterAsin( iterator:Object )\n    Returns an iterator which iteratively computes the arcsine.\n","iterAsinh":"\niterAsinh( iterator:Object )\n    Returns an iterator which iteratively computes the hyperbolic arcsine.\n","iterAtan":"\niterAtan( iterator:Object )\n    Returns an iterator which iteratively computes the arctangent.\n","iterAtan2":"\niterAtan2( y:Object|number, x:Object|number )\n    Returns an iterator which iteratively computes the angle in the plane (in\n    radians) between the positive x-axis and the ray from (0,0) to the point\n    (x,y).\n","iterAtanh":"\niterAtanh( iterator:Object )\n    Returns an iterator which iteratively computes the hyperbolic arctangent.\n","iterator2array":"\niterator2array( iterator:Object[, out:ArrayLikeObject][, mapFcn:Function[, \n  thisArg:any]] )\n    Creates (or fills) an array from an iterator.\n","iterator2arrayview":"\niterator2arrayview( iterator:Object, dest:ArrayLikeObject[, begin:integer[, \n  end:integer]][, mapFcn:Function[, thisArg:any]] )\n    Fills an array-like object view with values returned from an iterator.\n","iterator2arrayviewRight":"\niterator2arrayviewRight( iterator:Object, dest:ArrayLikeObject[, \n  begin:integer[, end:integer]][, mapFcn:Function[, thisArg:any]] )\n    Fills an array-like object view from right to left with values returned from\n    an iterator.\n","iteratorStream":"\niteratorStream( iterator:Object[, options:Object] )\n    Creates a readable stream from an iterator.\n","iteratorStream.factory":"\niteratorStream.factory( [options:Object] )\n    Returns a function for creating readable streams from iterators.\n","iteratorStream.objectMode":"\niteratorStream.objectMode( iterator:Object[, options:Object] )\n    Returns an \"objectMode\" readable stream from an iterator.\n","IteratorSymbol":"\nIteratorSymbol\n    Iterator symbol.\n","iterAvercos":"\niterAvercos( iterator:Object )\n    Returns an iterator which iteratively computes the inverse versed cosine.\n","iterAversin":"\niterAversin( iterator:Object )\n    Returns an iterator which iteratively computes the inverse versed sine.\n","iterawgn":"\niterawgn( iterator:Object, sigma:number[, options:Object] )\n    Returns an iterator which introduces additive white Gaussian noise (AWGN)\n    with standard deviation `sigma`.\n","iterawln":"\niterawln( iterator:Object, sigma:number[, options:Object] )\n    Returns an iterator which introduces additive white Laplacian noise (AWLN)\n    with standard deviation `sigma`.\n","iterawun":"\niterawun( iterator:Object, sigma:number[, options:Object] )\n    Returns an iterator which introduces additive white uniform noise (AWUN)\n    with standard deviation `sigma`.\n","iterBartlettHannPulse":"\niterBartlettHannPulse( [options:Object] )\n    Returns an iterator which generates a Bartlett-Hann pulse waveform.\n","iterBartlettPulse":"\niterBartlettPulse( [options:Object] )\n    Returns an iterator which generates a Bartlett pulse waveform.\n","iterBesselj0":"\niterBesselj0( iterator:Object )\n    Returns an iterator which iteratively evaluates the Bessel function of the\n    first kind of order zero.\n","iterBesselj1":"\niterBesselj1( iterator:Object )\n    Returns an iterator which iteratively evaluates the Bessel function of the\n    first kind of order one.\n","iterBessely0":"\niterBessely0( iterator:Object )\n    Returns an iterator which iteratively evaluates the Bessel function of the\n    second kind of order zero.\n","iterBessely1":"\niterBessely1( iterator:Object )\n    Returns an iterator which iteratively evaluates the Bessel function of the\n    second kind of order one.\n","iterBeta":"\niterBeta( x:Object|number, y:Object|number )\n    Returns an iterator which iteratively evaluates the beta function.\n","iterBetaln":"\niterBetaln( x:Object|number, y:Object|number )\n    Returns an iterator which iteratively evaluates the natural logarithm of the\n    beta function.\n","iterBinet":"\niterBinet( iterator:Object )\n    Returns an iterator which iteratively evaluates Binet's formula extended to\n    real numbers.\n","iterCbrt":"\niterCbrt( iterator:Object )\n    Returns an iterator which iteratively computes the cube root.\n","iterCeil":"\niterCeil( iterator:Object )\n    Returns an iterator which rounds each iterated value toward positive\n    infinity.\n","iterCeil2":"\niterCeil2( iterator:Object )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    two toward positive infinity.\n","iterCeil10":"\niterCeil10( iterator:Object )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    10 toward positive infinity.\n","iterCompositesSeq":"\niterCompositesSeq( [options:Object] )\n    Returns an iterator which generates a sequence of composite numbers.\n","iterConcat":"\niterConcat( iter0:Object, ...iterator:Object )\n    Returns an iterator which iterates over the values of two or more iterators.\n","iterConstant":"\niterConstant( value:any[, options:Object] )\n    Returns an iterator which always returns the same value.\n","iterContinuedFraction":"\niterContinuedFraction( iterator:Object[, options:Object] )\n    Evaluates the terms of a continued fraction.\n","iterContinuedFractionSeq":"\niterContinuedFractionSeq( x:number[, options:Object] )\n    Returns an iterator which generates a list of all continued fraction terms\n    which can be obtained given the precision of `x`.\n","iterCos":"\niterCos( iterator:Object )\n    Returns an iterator which iteratively computes the cosine.\n","iterCosh":"\niterCosh( iterator:Object )\n    Returns an iterator which iteratively computes the hyperbolic cosine.\n","iterCosineWave":"\niterCosineWave( [options:Object] )\n    Returns an iterator which generates a cosine wave.\n","iterCosm1":"\niterCosm1( iterator:Object )\n    Returns an iterator which iteratively computes `cos(x) - 1`.\n","iterCospi":"\niterCospi( iterator:Object )\n    Returns an iterator which computes the cosine of each iterated value times\n    π.\n","iterCounter":"\niterCounter( iterator:Object )\n    Returns an iterator which iteratively computes the number of iterated\n    values.\n","iterCovercos":"\niterCovercos( iterator:Object )\n    Returns an iterator which iteratively computes the coversed cosine.\n","iterCoversin":"\niterCoversin( iterator:Object )\n    Returns an iterator which iteratively computes the coversed sine.\n","iterCubesSeq":"\niterCubesSeq( [options:Object] )\n    Returns an iterator which generates a sequence of cubes.\n","itercugmean":"\nitercugmean( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative geometric mean.\n","itercuhmean":"\nitercuhmean( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative harmonic mean.\n","itercumax":"\nitercumax( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative maximum value.\n","itercumaxabs":"\nitercumaxabs( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative maximum absolute\n    value.\n","itercumean":"\nitercumean( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative arithmetic mean.\n","itercumeanabs":"\nitercumeanabs( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative arithmetic mean\n    of absolute values.\n","itercumeanabs2":"\nitercumeanabs2( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative arithmetic mean\n    of squared absolute values.\n","itercumidrange":"\nitercumidrange( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative mid-range.\n","itercumin":"\nitercumin( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative minimum value.\n","itercuminabs":"\nitercuminabs( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative minimum absolute\n    value.\n","itercuprod":"\nitercuprod( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative product.\n","itercurange":"\nitercurange( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative range.\n","itercusum":"\nitercusum( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative sum.\n","itercusumabs":"\nitercusumabs( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative sum of absolute\n    values.\n","itercusumabs2":"\nitercusumabs2( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative sum of squared\n    absolute values.\n","iterDatespace":"\niterDatespace( start:integer|string|Date, stop:integer|string|Date[, \n  N:integer][, options:Object] )\n    Returns an iterator which returns evenly spaced dates over a specified\n    interval.\n","iterDedupe":"\niterDedupe( iterator:Object[, limit:integer] )\n    Returns an iterator which removes consecutive duplicated values.\n","iterDedupeBy":"\niterDedupeBy( iterator:Object, [limit:integer,] fcn:Function )\n    Returns an iterator which removes consecutive values that resolve to the\n    same value according to a provided function.\n","iterDeg2rad":"\niterDeg2rad( iterator:Object )\n    Returns an iterator which iteratively converts an angle from degrees to\n    radians.\n","iterDigamma":"\niterDigamma( iterator:Object )\n    Returns an iterator which iteratively evaluates the digamma function.\n","iterDiracComb":"\niterDiracComb( [options:Object] )\n    Returns an iterator which generates a Dirac comb.\n","iterDiracDelta":"\niterDiracDelta( iterator:Object )\n    Returns an iterator which iteratively evaluates the Dirac delta function.\n","iterDivide":"\niterDivide( iter0:Object, ...iterator:Object )\n    Returns an iterator which performs element-wise division of two or more\n    iterators.\n","iterDoWhileEach":"\niterDoWhileEach( iterator:Object, predicate:Function, fcn:Function[, \n  thisArg:any] )\n    Returns an iterator which invokes a function for each iterated value before\n    returning the iterated value until either a predicate function returns false\n    or the iterator has iterated over all values.\n","iterEllipe":"\niterEllipe( iterator:Object )\n    Returns an iterator which iteratively computes the complete elliptic\n    integral of the second kind.\n","iterEllipk":"\niterEllipk( iterator:Object )\n    Returns an iterator which iteratively computes the complete elliptic\n    integral of the first kind.\n","iterEmpty":"\niterEmpty()\n    Returns an empty iterator.\n","iterErf":"\niterErf( iterator:Object )\n    Returns an iterator which iteratively evaluates the error function.\n","iterErfc":"\niterErfc( iterator:Object )\n    Returns an iterator which iteratively evaluates the complementary error\n    function.\n","iterErfcinv":"\niterErfcinv( iterator:Object )\n    Returns an iterator which iteratively evaluates the inverse complementary\n    error function.\n","iterErfinv":"\niterErfinv( iterator:Object )\n    Returns an iterator which iteratively evaluates the inverse error function.\n","iterEta":"\niterEta( iterator:Object )\n    Returns an iterator which iteratively evaluates the Dirichlet eta function.\n","iterEvenIntegersSeq":"\niterEvenIntegersSeq( [options:Object] )\n    Returns an iterator which generates an interleaved sequence of even\n    integers.\n","iterEvery":"\niterEvery( iterator:Object )\n    Tests whether all iterated values are truthy.\n","iterEveryBy":"\niterEveryBy( iterator:Object, predicate:Function[, thisArg:any ] )\n    Tests whether every iterated value passes a test implemented by a predicate\n    function.\n","iterExp":"\niterExp( iterator:Object )\n    Returns an iterator which iteratively evaluates the natural exponential\n    function.\n","iterExp2":"\niterExp2( iterator:Object )\n    Returns an iterator which iteratively evaluates the base `2` exponential\n    function.\n","iterExp10":"\niterExp10( iterator:Object )\n    Returns an iterator which iteratively evaluates the base `10` exponential\n    function.\n","iterExpit":"\niterExpit( iterator:Object )\n    Returns an iterator which iteratively evaluates the standard logistic\n    function.\n","iterExpm1":"\niterExpm1( iterator:Object )\n    Returns an iterator which iteratively computes `exp(x) - 1`.\n","iterExpm1rel":"\niterExpm1rel( iterator:Object )\n    Returns an iterator which iteratively evaluates the relative error\n    exponential.\n","iterFactorial":"\niterFactorial( iterator:Object )\n    Returns an iterator which iteratively evaluates the factorial function.\n","iterFactorialln":"\niterFactorialln( iterator:Object )\n    Returns an iterator which iteratively evaluates the natural logarithm of the\n    factorial function.\n","iterFactorialsSeq":"\niterFactorialsSeq( [options:Object] )\n    Returns an iterator which generates a sequence of factorials.\n","iterFibonacciSeq":"\niterFibonacciSeq( [options:Object] )\n    Returns an iterator which generates a Fibonacci sequence.\n","iterFifthPowersSeq":"\niterFifthPowersSeq( [options:Object] )\n    Returns an iterator which generates a sequence of fifth powers.\n","iterFill":"\niterFill( iterator:Object, value:any[, begin:integer[, end:integer]] )\n    Returns an iterator which replaces all values from a provided iterator from\n    a start index to an end index with a static value.\n","iterFilter":"\niterFilter( iterator:Object, predicate:Function[, thisArg:any] )\n    Returns an iterator which filters a provided iterator's values according to\n    a predicate function.\n","iterFilterMap":"\niterFilterMap( iterator:Object, fcn:Function[, thisArg:any] )\n    Returns an iterator which both filters and maps a provided iterator's\n    values.\n","iterFirst":"\niterFirst( iterator:Object )\n    Returns the first iterated value.\n","iterFlatTopPulse":"\niterFlatTopPulse( [options:Object] )\n    Returns an iterator which generates a flat top pulse waveform.\n","iterFloor":"\niterFloor( iterator:Object )\n    Returns an iterator which rounds each iterated value toward negative\n    infinity.\n","iterFloor2":"\niterFloor2( iterator:Object )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    two toward negative infinity.\n","iterFloor10":"\niterFloor10( iterator:Object )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    10 toward negative infinity.\n","iterFlow":"\niterFlow( methods:Object )\n    Returns a fluent interface iterator constructor with a customized prototype\n    based on provided methods.\n","iterForEach":"\niterForEach( iterator:Object, fcn:Function[, thisArg:any] )\n    Returns an iterator which invokes a function for each iterated value before\n    returning the iterated value.\n","iterFourthPowersSeq":"\niterFourthPowersSeq( [options:Object] )\n    Returns an iterator which generates a sequence of fourth powers.\n","iterFresnelc":"\niterFresnelc( iterator:Object )\n    Returns an iterator which iteratively computes the Fresnel integral C(x).\n","iterFresnels":"\niterFresnels( iterator:Object )\n    Returns an iterator which iteratively computes the Fresnel integral S(x).\n","iterGamma":"\niterGamma( iterator:Object )\n    Returns an iterator which iteratively evaluates the gamma function.\n","iterGamma1pm1":"\niterGamma1pm1( iterator:Object )\n    Returns an iterator which iteratively computes `gamma(x+1) - 1` without\n    cancellation errors for small `x`.\n","iterGammaln":"\niterGammaln( iterator:Object )\n    Returns an iterator which iteratively evaluates the natural logarithm of the\n    gamma function.\n","iterHacovercos":"\niterHacovercos( iterator:Object )\n    Returns an iterator which iteratively computes the half-value coversed\n    cosine.\n","iterHacoversin":"\niterHacoversin( iterator:Object )\n    Returns an iterator which iteratively computes the half-value coversed sine.\n","iterHannPulse":"\niterHannPulse( [options:Object] )\n    Returns an iterator which generates a Hann pulse waveform.\n","iterHavercos":"\niterHavercos( iterator:Object )\n    Returns an iterator which iteratively computes the half-value versed cosine.\n","iterHaversin":"\niterHaversin( iterator:Object )\n    Returns an iterator which iteratively computes the half-value versed sine.\n","iterHead":"\niterHead( iterator:Object, n:integer )\n    Returns an iterator which returns the first `n` values of a provided\n    iterator.\n","iterIncrspace":"\niterIncrspace( start:number, stop:number[, increment:number] )\n    Returns an iterator which returns evenly spaced numbers according to a\n    specified increment.\n","iterIntegersSeq":"\niterIntegersSeq( [options:Object] )\n    Returns an iterator which generates an interleaved integer sequence.\n","iterIntersection":"\niterIntersection( iter0:Object, ...iterator:Object )\n    Returns an iterator which returns the intersection of two or more iterators.\n","iterIntersectionByHash":"\niterIntersectionByHash( iter0:Object, ...iterator:Object, hashFcn:Function[, \n  thisArg:any] )\n    Returns an iterator which returns the intersection of two or more iterators\n    according to a hash function.\n","iterInv":"\niterInv( iterator:Object )\n    Returns an iterator which iteratively computes the multiplicative inverse.\n","iterLanczosPulse":"\niterLanczosPulse( [options:Object] )\n    Returns an iterator which generates a Lanczos pulse waveform.\n","iterLast":"\niterLast( iterator:Object )\n    Consumes an entire iterator and returns the last iterated value.\n","iterLength":"\niterLength( iterator:Object )\n    Consumes an entire iterator and returns the number of iterated values.\n","iterLinspace":"\niterLinspace( start:number, stop:number[, N:integer] )\n    Returns an iterator which returns evenly spaced numbers over a specified\n    interval.\n","iterLn":"\niterLn( iterator:Object )\n    Returns an iterator which iteratively evaluates the natural logarithm.\n","iterLog":"\niterLog( x:Object|number, b:Object|number )\n    Returns an iterator which iteratively computes the base `b` logarithm.\n","iterLog1mexp":"\niterLog1mexp( iterator:Object )\n    Returns an iterator which iteratively evaluates the natural logarithm of\n    `1-exp(-|x|)`.\n","iterLog1p":"\niterLog1p( iterator:Object )\n    Returns an iterator which iteratively evaluates the natural logarithm of\n    `1+x`.\n","iterLog1pexp":"\niterLog1pexp( iterator:Object )\n    Returns an iterator which iteratively evaluates the natural logarithm of\n    `1+exp(x)`.\n","iterLog2":"\niterLog2( iterator:Object )\n    Returns an iterator which iteratively evaluates the binary logarithm.\n","iterLog10":"\niterLog10( iterator:Object )\n    Returns an iterator which iteratively evaluates the common logarithm\n    (logarithm with base 10).\n","iterLogit":"\niterLogit( iterator:Object )\n    Returns an iterator which iteratively evaluates the logit function.\n","iterLogspace":"\niterLogspace( start:number, stop:number[, N:integer][, options:Object] )\n    Returns an iterator which returns evenly spaced numbers on a log scale.\n","iterLucasSeq":"\niterLucasSeq( [options:Object] )\n    Returns an iterator which generates a Lucas sequence.\n","iterMap":"\niterMap( iterator:Object, fcn:Function[, thisArg:any] )\n    Returns an iterator which invokes a function for each iterated value.\n","iterMapN":"\niterMapN( iter0:Object, ...iterator:Object, fcn:Function[, thisArg:any] )\n    Returns an iterator which transforms iterated values from two or more\n    iterators by applying the iterated values as arguments to a provided\n    function.\n","itermax":"\nitermax( iterator:Object )\n    Computes the maximum value of all iterated values.\n","itermaxabs":"\nitermaxabs( iterator:Object )\n    Computes the maximum absolute value of all iterated values.\n","itermean":"\nitermean( iterator:Object )\n    Computes an arithmetic mean over all iterated values.\n","itermeanabs":"\nitermeanabs( iterator:Object )\n    Computes an arithmetic mean of absolute values for all iterated values.\n","itermeanabs2":"\nitermeanabs2( iterator:Object )\n    Computes an arithmetic mean of squared absolute values for all iterated\n    values.\n","itermidrange":"\nitermidrange( iterator:Object )\n    Computes the mid-range of all iterated values.\n","itermin":"\nitermin( iterator:Object )\n    Computes the minimum value of all iterated values.\n","iterminabs":"\niterminabs( iterator:Object )\n    Computes the minimum absolute value of all iterated values.\n","itermmax":"\nitermmax( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving maximum value.\n","itermmaxabs":"\nitermmaxabs( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving maximum absolute\n    value.\n","itermmean":"\nitermmean( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving arithmetic mean.\n","itermmeanabs":"\nitermmeanabs( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving arithmetic mean of\n    absolute values.\n","itermmeanabs2":"\nitermmeanabs2( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving arithmetic mean of\n    squared absolute values.\n","itermmidrange":"\nitermmidrange( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving mid-range.\n","itermmin":"\nitermmin( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving minimum value.\n","itermminabs":"\nitermminabs( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving minimum absolute\n    value.\n","iterMod":"\niterMod( iter0:Object, ...iterator:Object )\n    Returns an iterator which performs an element-wise modulo operation of two\n    or more iterators.\n","itermprod":"\nitermprod( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving product.\n","itermrange":"\nitermrange( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving range.\n","itermsum":"\nitermsum( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving sum.\n","itermsumabs":"\nitermsumabs( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving sum of absolute\n    values.\n","itermsumabs2":"\nitermsumabs2( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving sum of squared\n    absolute values.\n","iterMultiply":"\niterMultiply( iter0:Object, ...iterator:Object )\n    Returns an iterator which performs element-wise multiplication of two or\n    more iterators.\n","iterNegaFibonacciSeq":"\niterNegaFibonacciSeq( [options:Object] )\n    Returns an iterator which generates a negaFibonacci sequence.\n","iterNegaLucasSeq":"\niterNegaLucasSeq( [options:Object] )\n    Returns an iterator which generates a negaLucas sequence.\n","iterNegativeEvenIntegersSeq":"\niterNegativeEvenIntegersSeq( [options:Object] )\n    Returns an iterator which generates a sequence of negative even integers.\n","iterNegativeIntegersSeq":"\niterNegativeIntegersSeq( [options:Object] )\n    Returns an iterator which generates a negative integer sequence.\n","iterNegativeOddIntegersSeq":"\niterNegativeOddIntegersSeq( [options:Object] )\n    Returns an iterator which generates a sequence of negative odd integers.\n","iterNone":"\niterNone( iterator:Object )\n    Tests whether all iterated values are falsy.\n","iterNoneBy":"\niterNoneBy( iterator:Object, predicate:Function[, thisArg:any ] )\n    Tests whether every iterated value fails a test implemented by a predicate\n    function.\n","iterNonFibonacciSeq":"\niterNonFibonacciSeq( [options:Object] )\n    Returns an iterator which generates a non-Fibonacci integer sequence.\n","iterNonNegativeEvenIntegersSeq":"\niterNonNegativeEvenIntegersSeq( [options:Object] )\n    Returns an iterator which generates a sequence of nonnegative even integers.\n","iterNonNegativeIntegersSeq":"\niterNonNegativeIntegersSeq( [options:Object] )\n    Returns an iterator which generates a nonnegative integer sequence.\n","iterNonPositiveEvenIntegersSeq":"\niterNonPositiveEvenIntegersSeq( [options:Object] )\n    Returns an iterator which generates a sequence of nonpositive even integers.\n","iterNonPositiveIntegersSeq":"\niterNonPositiveIntegersSeq( [options:Object] )\n    Returns an iterator which generates a nonpositive integer sequence.\n","iterNonSquaresSeq":"\niterNonSquaresSeq( [options:Object] )\n    Returns an iterator which generates a sequence of nonsquares.\n","iterNth":"\niterNth( iterator:Object, n:integer )\n    Returns the nth iterated value.\n","iterOddIntegersSeq":"\niterOddIntegersSeq( [options:Object] )\n    Returns an iterator which generates an interleaved sequence of odd integers.\n","iterPeriodicSinc":"\niterPeriodicSinc( n:integer[, options:Object] )\n    Returns an iterator which generates a periodic sinc waveform.\n","iterPipeline":"\niterPipeline( iterFcn:Function|Array[, ...iterFcn:Function] )\n    Returns an iterator pipeline.\n","iterPop":"\niterPop( iterator:Object[, clbk:Function[, thisArg:any]] )\n    Returns an iterator which skips the last value of a provided iterator.\n","iterPositiveEvenIntegersSeq":"\niterPositiveEvenIntegersSeq( [options:Object] )\n    Returns an iterator which generates a sequence of positive even integers.\n","iterPositiveIntegersSeq":"\niterPositiveIntegersSeq( [options:Object] )\n    Returns an iterator which generates a positive integer sequence.\n","iterPositiveOddIntegersSeq":"\niterPositiveOddIntegersSeq( [options:Object] )\n    Returns an iterator which generates a sequence of positive odd integers.\n","iterPow":"\niterPow( base:Object|number, exponent:Object|number )\n    Returns an iterator which iteratively evaluates the exponential function.\n","iterPrimesSeq":"\niterPrimesSeq( [options:Object] )\n    Returns an iterator which generates a sequence of prime numbers.\n","iterprod":"\niterprod( iterator:Object )\n    Computes the product of all iterated values.\n","iterPulse":"\niterPulse( [options:Object] )\n    Returns an iterator which generates a pulse waveform.\n","iterPush":"\niterPush( iterator:Object, ...items:any )\n    Returns an iterator which appends additional values to the end of a provided\n    iterator.\n","iterRad2deg":"\niterRad2deg( iterator:Object )\n    Returns an iterator which iteratively converts an angle from radians to\n    degrees.\n","iterRamp":"\niterRamp( iterator:Object )\n    Returns an iterator which iteratively evaluates the ramp function.\n","iterrange":"\niterrange( iterator:Object )\n    Computes the range of all iterated values.\n","iterReject":"\niterReject( iterator:Object, predicate:Function[, thisArg:any] )\n    Returns an iterator which rejects a provided iterator's values according to\n    a predicate function.\n","iterReplicate":"\niterReplicate( iterator:Object, n:integer )\n    Returns an iterator which replicates each iterated value `n` times.\n","iterReplicateBy":"\niterReplicateBy( iterator:Object, fcn:Function[, thisArg:any] )\n    Returns an iterator which replicates each iterated value according to a\n    provided function.\n","iterRound":"\niterRound( iterator:Object )\n    Returns an iterator which rounds each iterated value to the nearest integer.\n","iterRound2":"\niterRound2( iterator:Object )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    two on a linear scale.\n","iterRound10":"\niterRound10( iterator:Object )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    10 on a linear scale.\n","iterRsqrt":"\niterRsqrt( iterator:Object )\n    Returns an iterator which iteratively computes the reciprocal (inverse)\n    square root.\n","iterSawtoothWave":"\niterSawtoothWave( [options:Object] )\n    Returns an iterator which generates a sawtooth wave.\n","iterShift":"\niterShift( iterator:Object[, clbk:Function[, thisArg:any]] )\n    Returns an iterator which skips the first value of a provided iterator.\n","iterSignum":"\niterSignum( iterator:Object )\n    Returns an iterator which iteratively evaluates the signum function.\n","iterSin":"\niterSin( iterator:Object )\n    Returns an iterator which iteratively computes the sine.\n","iterSinc":"\niterSinc( iterator:Object )\n    Returns an iterator which iteratively computes the normalized cardinal sine.\n","iterSineWave":"\niterSineWave( [options:Object] )\n    Returns an iterator which generates a sine wave.\n","iterSinh":"\niterSinh( iterator:Object )\n    Returns an iterator which iteratively evaluates the hyperbolic sine.\n","iterSinpi":"\niterSinpi( iterator:Object )\n    Returns an iterator which computes the sine of each iterated value times π.\n","iterSlice":"\niterSlice( iterator:Object[, begin:integer[, end:integer]] )\n    Returns an iterator which returns a subsequence of iterated values from a\n    provided iterator.\n","iterSome":"\niterSome( iterator:Object, n:number )\n    Tests whether at least `n` iterated values are truthy.\n","iterSomeBy":"\niterSomeBy( iterator:Object, n:integer, predicate:Function[, thisArg:any ] )\n    Tests whether at least `n` iterated values pass a test implemented by a\n    predicate function.\n","iterSpence":"\niterSpence( iterator:Object )\n    Returns an iterator which iteratively evaluates Spence's function.\n","iterSqrt":"\niterSqrt( iterator:Object )\n    Returns an iterator which iteratively computes the principal square root.\n","iterSqrt1pm1":"\niterSqrt1pm1( iterator:Object )\n    Returns an iterator which iteratively computes `sqrt(1+x) - 1` more \n    accurately for small `x`.\n","iterSquaredTriangularSeq":"\niterSquaredTriangularSeq( [options:Object] )\n    Returns an iterator which generates a sequence of squared triangular\n    numbers.\n","iterSquaresSeq":"\niterSquaresSeq( [options:Object] )\n    Returns an iterator which generates a sequence of squares.\n","iterSquareWave":"\niterSquareWave( [options:Object] )\n    Returns an iterator which generates a square wave.\n","iterstdev":"\niterstdev( iterator:Object[, mean:number] )\n    Computes a correct sample standard deviation over all iterated values.\n","iterStep":"\niterStep( start:number, increment:number[, N:number] )\n    Returns an iterator which returns a sequence of numbers according to a\n    specified increment.\n","iterStrided":"\niterStrided( iterator:Object, stride:integer[, offset:integer[, \n  eager:boolean]] )\n    Returns an iterator which steps by a specified amount.\n","iterStridedBy":"\niterStridedBy( iterator:Object, fcn:Function[, offset:integer[, \n  eager:boolean]][, thisArg:any] )\n    Returns an iterator which steps according to a provided callback function.\n","iterSubtract":"\niterSubtract( iter0:Object, ...iterator:Object )\n    Returns an iterator which performs element-wise subtraction of two or more\n    iterators.\n","itersum":"\nitersum( iterator:Object )\n    Computes the sum of all iterated values.\n","itersumabs":"\nitersumabs( iterator:Object )\n    Computes the sum of absolute values for all iterated values.\n","itersumabs2":"\nitersumabs2( iterator:Object )\n    Computes the sum of squared absolute values for all iterated values.\n","iterTan":"\niterTan( iterator:Object )\n    Returns an iterator which iteratively evaluates the tangent.\n","iterTanh":"\niterTanh( iterator:Object )\n    Returns an iterator which iteratively evaluates the hyperbolic tangent.\n","iterThunk":"\niterThunk( iterFcn:Function[, ...args:any] )\n    Returns an iterator \"thunk\".\n","iterTriangleWave":"\niterTriangleWave( [options:Object] )\n    Returns an iterator which generates a triangle wave.\n","iterTriangularSeq":"\niterTriangularSeq( [options:Object] )\n    Returns an iterator which generates a sequence of triangular numbers.\n","iterTribonnaciSeq":"\niterTribonnaciSeq( [options:Object] )\n    Returns an iterator which generates a Tribonacci sequence.\n    \n    The returned iterator can only generate the first 64 Tribonacci numbers, as\n    larger Tribonacci numbers cannot be safely represented in double-precision\n    floating-point format.\n","iterTrigamma":"\niterTrigamma( iterator:Object )\n    Returns an iterator which iteratively evaluates the trigamma function.\n","iterTrunc":"\niterTrunc( iterator:Object )\n    Returns an iterator which rounds each iterated value toward zero.\n","iterTrunc2":"\niterTrunc2( iterator:Object )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    two toward zero.\n","iterTrunc10":"\niterTrunc10( iterator:Object )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    10 toward zero.\n","iterUnion":"\niterUnion( iter0:Object, ...iterator:Object )\n    Returns an iterator which returns the union of two or more iterators.\n","iterUnique":"\niterUnique( iterator:Object )\n    Returns an iterator which returns unique values.\n","iterUniqueBy":"\niterUniqueBy( iterator:Object, predicate:Function[, thisArg:any] )\n    Returns an iterator which returns unique values according to a predicate\n    function.\n","iterUniqueByHash":"\niterUniqueByHash( iterator:Object, hashFcn:Function[, thisArg:any] )\n    Returns an iterator which returns unique values according to a hash\n    function.\n","iterUnitspace":"\niterUnitspace( start:number[, stop:number] )\n    Returns an iterator which returns numbers incremented by one.\n","iterUnshift":"\niterUnshift( iterator:Object, ...items:any )\n    Returns an iterator which prepends values to the beginning of a provided\n    iterator.\n","iterUntilEach":"\niterUntilEach( iterator:Object, predicate:Function, fcn:Function[, \n  thisArg:any] )\n    Returns an iterator which invokes a function for each iterated value before\n    returning the iterated value until either a predicate function returns true\n    or the iterator has iterated over all values.\n","itervariance":"\nitervariance( iterator:Object[, mean:number] )\n    Computes an unbiased sample variance over all iterated values.\n","iterVercos":"\niterVercos( iterator:Object )\n    Returns an iterator which iteratively computes the versed cosine.\n","iterVersin":"\niterVersin( iterator:Object )\n    Returns an iterator which iteratively computes the versed sine.\n","iterWhileEach":"\niterWhileEach( iterator:Object, predicate:Function, fcn:Function[, \n  thisArg:any] )\n    Returns an iterator which invokes a function for each iterated value before\n    returning the iterated value until either a predicate function returns false\n    or the iterator has iterated over all values.\n","iterZeta":"\niterZeta( iterator:Object )\n    Returns an iterator which iteratively evaluates the Riemann zeta function.\n","joinStream":"\njoinStream( [options:Object] )\n    Returns a transform stream which joins streamed data.\n","joinStream.factory":"\njoinStream.factory( [options:Object] )\n    Returns a function for creating transform streams for joined streamed data.\n","joinStream.objectMode":"\njoinStream.objectMode( [options:Object] )\n    Returns an \"objectMode\" transform stream for joining streamed data.\n","kde2d":"\nkde2d( x:Array<number>, y:Array<number>[, options:Object] )\n    Two-dimensional kernel density estimation.\n","kebabcase":"\nkebabcase( str:string )\n    Converts a string to kebab case.\n","keyBy":"\nkeyBy( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n    Converts a collection to an object whose keys are determined by a provided\n    function and whose values are the collection values.\n","keyByRight":"\nkeyByRight( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n    Converts a collection to an object whose keys are determined by a provided\n    function and whose values are the collection values, iterating from right to\n    left.\n","keysIn":"\nkeysIn( obj:any )\n    Returns an array of an object's own and inherited enumerable property\n    names.\n","kruskalTest":"\nkruskalTest( ...x:Array[, options:Object] )\n    Computes the Kruskal-Wallis test for equal medians.\n","kstest":"\nkstest( x:Array<number>, y:Function|string[, ...params:number][, \n  options:Object] )\n    Computes a Kolmogorov-Smirnov goodness-of-fit test.\n","last":"\nlast( str:string[, n:integer][, options:Object] )\n    Returns the last character(s) of a string.\n","leveneTest":"\nleveneTest( x:Array<number>[, ...y:Array<number>[, options:Object]] )\n    Computes Levene's test for equal variances.\n","LinkedList":"\nLinkedList()\n    Linked list constructor.\n","linspace":"\nlinspace( start:number|ComplexLike, stop:number|ComplexLike, length:integer[, \n  options:Object] )\n    Generates a linearly spaced array over a specified interval.\n","linspace.assign":"\nlinspace.assign( start:number|ComplexLike, stop:number|ComplexLike, \n  out:ArrayLikeObject[, options:Object] )\n    Generates a linearly spaced sequence over a specified interval and assigns\n    the results to a provided output array.\n","LIU_NEGATIVE_OPINION_WORDS_EN":"\nLIU_NEGATIVE_OPINION_WORDS_EN()\n    Returns a list of negative opinion words.\n","LIU_POSITIVE_OPINION_WORDS_EN":"\nLIU_POSITIVE_OPINION_WORDS_EN()\n    Returns a list of positive opinion words.\n","LN_HALF":"\nLN_HALF\n    Natural logarithm of `1/2`.\n","LN_PI":"\nLN_PI\n    Natural logarithm of the mathematical constant `π`.\n","LN_SQRT_TWO_PI":"\nLN_SQRT_TWO_PI\n    Natural logarithm of the square root of `2π`.\n","LN_TWO_PI":"\nLN_TWO_PI\n    Natural logarithm of `2π`.\n","LN2":"\nLN2\n    Natural logarithm of `2`.\n","LN10":"\nLN10\n    Natural logarithm of `10`.\n","LOG2E":"\nLOG2E\n    Base 2 logarithm of Euler's number.\n","LOG10E":"\nLOG10E\n    Base 10 logarithm of Euler's number.\n","logspace":"\nlogspace( a:number, b:number[, length:integer] )\n    Generates a logarithmically spaced numeric array between `10^a` and `10^b`.\n","lowercase":"\nlowercase( str:string )\n    Converts a string to lowercase.\n","lowercaseKeys":"\nlowercaseKeys( obj:Object )\n    Converts each object key to lowercase.\n","lowess":"\nlowess( x:Array<number>, y:Array<number>[, options:Object] )\n    Locally-weighted polynomial regression via the LOWESS algorithm.\n","lpad":"\nlpad( str:string, len:integer[, pad:string] )\n    Left pads a string such that the padded string has a length of at least\n    `len`.\n","ltrim":"\nltrim( str:string )\n    Trims whitespace from the beginning of a string.\n","ltrimN":"\nltrimN( str:string, n:integer[, chars:Array|string] )\n    Trims `n` characters from the beginning of a string.\n","MALE_FIRST_NAMES_EN":"\nMALE_FIRST_NAMES_EN()\n    Returns a list of common male first names in English speaking countries.\n","map":"\nmap( arr:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n    Applies a function to each element in an array and assigns the result to an\n    element in a new array.\n","map.assign":"\nmap.assign( arr:ArrayLikeObject|ndarray, out:ArrayLikeObject|ndarray, \n  fcn:Function[, thisArg:any] )\n    Applies a function to each element in an array and assigns the result to an\n    element in an output array.\n","map2":"\nmap2( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, fcn:Function[, \n  thisArg:any] )\n    Applies a function to elements in two input arrays and assigns the results\n    to a new array.\n","map2.assign":"\nmap2.assign( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, \n  out:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n    Applies a function to elements in two input arrays and assigns the results\n    to an output array.\n","map2d":"\nmap2d( arr:ArrayLikeObject<ArrayLikeObject>, fcn:Function[, thisArg:any] )\n    Applies a function to each nested element in an array of arrays and assigns\n    the result to a nested element in a new array of arrays.\n","map2Right":"\nmap2Right( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, fcn:Function[, \n  thisArg:any] )\n    Applies a function to elements in two input arrays while iterating from\n    right to left and assigns the results to a new array.\n","map2Right.assign":"\nmap2Right.assign( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, \n  out:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n    Applies a function to elements in two input arrays while iterating from\n    right to left and assigns the results to an output array.\n","map3d":"\nmap3d( arr:ArrayLikeObject<ArrayLikeObject<ArrayLikeObject>>, fcn:Function[, \n  thisArg:any] )\n    Applies a function to each nested element in a three-dimensional nested\n    array and assigns the result to a nested element in a new three-dimensional\n    nested array.\n","map4d":"\nmap4d( arr:ArrayLikeObject<ArrayLikeObject>, fcn:Function[, thisArg:any] )\n    Applies a function to each nested element in a four-dimensional nested array\n    and assigns the result to a nested element in a new four-dimensional nested\n    array.\n","map5d":"\nmap5d( arr:ArrayLikeObject<ArrayLikeObject>, fcn:Function[, thisArg:any] )\n    Applies a function to each nested element in a five-dimensional nested array\n    and assigns the result to a nested element in a new five-dimensional nested\n    array.\n","mapArguments":"\nmapArguments( fcn:Function, clbk:Function[, thisArg:any] )\n    Returns a function that applies arguments to a provided function after\n    transforming arguments according to a callback function.\n","mapFun":"\nmapFun( fcn:Function, n:integer[, thisArg:any] )\n    Invokes a function `n` times and returns an array of accumulated function\n    return values.\n","mapFunAsync":"\nmapFunAsync( fcn:Function, n:integer, [options:Object,] done:Function )\n    Invokes a function `n` times and returns an array of accumulated function\n    return values.\n","mapFunAsync.factory":"\nmapFunAsync.factory( [options:Object,] fcn:Function )\n    Returns a function which invokes a function `n` times and returns an array\n    of accumulated function return values.\n","mapKeys":"\nmapKeys( obj:Object, transform:Function )\n    Maps keys from one object to a new object having the same values.\n","mapKeysAsync":"\nmapKeysAsync( obj:Object, [options:Object,] transform:Function, done:Function )\n    Maps keys from one object to a new object having the same values.\n","mapKeysAsync.factory":"\nmapKeysAsync.factory( [options:Object,] transform:Function )\n    Returns a function which maps keys from one object to a new object having\n    the same values.\n","mapReduce":"\nmapReduce( arr:ArrayLikeObject|ndarray, initial:any, mapper:Function, \n  reducer:Function[, thisArg:any] )\n    Performs a map-reduce operation for each element in an array and returns the\n    accumulated result.\n","mapReduceRight":"\nmapReduceRight( arr:ArrayLikeObject|ndarray, initial:any, mapper:Function, \n  reducer:Function[, thisArg:any] )\n    Performs a map-reduce operation for each element in an array while iterating\n    from right to left and returns the accumulated result.\n","mapRight":"\nmapRight( arr:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n    Applies a function to each element in an array and assigns the result to an\n    element in a new array, iterating from right to left.\n","mapRight.assign":"\nmapRight.assign( arr:ArrayLikeObject|ndarray, out:ArrayLikeObject|ndarray, \n  fcn:Function[, thisArg:any] )\n    Applies a function to each element in an array and assigns the result to an\n    element in an output array, iterating from right to left.\n","mapValues":"\nmapValues( obj:Object, transform:Function )\n    Maps values from one object to a new object having the same keys.\n","mapValuesAsync":"\nmapValuesAsync( obj:Object, [options:Object,] transform:Function, \n  done:Function )\n    Maps values from one object to a new object having the same keys.\n","mapValuesAsync.factory":"\nmapValuesAsync.factory( [options:Object,] transform:Function )\n    Returns a function which maps values from one object to a new object having\n    the same keys.\n","maskArguments":"\nmaskArguments( fcn:Function, mask:ArrayLikeObject[, thisArg:any] )\n    Returns a function that applies arguments to a provided function according\n    to a specified mask.\n","MAX_ARRAY_LENGTH":"\nMAX_ARRAY_LENGTH\n    Maximum length for a generic array.\n","MAX_TYPED_ARRAY_LENGTH":"\nMAX_TYPED_ARRAY_LENGTH\n    Maximum length for a typed array.\n","maybeBroadcastArray":"\nmaybeBroadcastArray( x:ndarray, shape:ArrayLikeObject )\n    Broadcasts an ndarray to a specified shape if and only if the specified\n    shape differs from the provided ndarray's shape.\n","maybeBroadcastArrays":"\nmaybeBroadcastArrays( ...arrays:ndarray|ArrayLikeObject<ndarray> )\n    Broadcasts ndarrays to a common shape.\n","memoize":"\nmemoize( fcn:Function[, hashFunction:Function] )\n    Returns a memoized function.\n","merge":"\nmerge( target:Object, ...source:Object )\n    Merges objects into a target object.\n","merge.factory":"\nmerge.factory( options:Object )\n    Returns a function for merging and extending objects.\n","MILLISECONDS_IN_DAY":"\nMILLISECONDS_IN_DAY\n    Number of milliseconds in a day.\n","MILLISECONDS_IN_HOUR":"\nMILLISECONDS_IN_HOUR\n    Number of milliseconds in an hour.\n","MILLISECONDS_IN_MINUTE":"\nMILLISECONDS_IN_MINUTE\n    Number of milliseconds in a minute.\n","MILLISECONDS_IN_SECOND":"\nMILLISECONDS_IN_SECOND\n    Number of milliseconds in a second.\n","MILLISECONDS_IN_WEEK":"\nMILLISECONDS_IN_WEEK\n    Number of milliseconds in a week.\n","MINARD_NAPOLEONS_MARCH":"\nMINARD_NAPOLEONS_MARCH( [options:Object] )\n    Returns data for Charles Joseph Minard's cartographic depiction of\n    Napoleon's Russian campaign of 1812.\n","MINUTES_IN_DAY":"\nMINUTES_IN_DAY\n    Number of minutes in a day.\n","MINUTES_IN_HOUR":"\nMINUTES_IN_HOUR\n    Number of minutes in an hour.\n","MINUTES_IN_WEEK":"\nMINUTES_IN_WEEK\n    Number of minutes in a week.\n","minutesInMonth":"\nminutesInMonth( [month:string|Date|integer[, year:integer]] )\n    Returns the number of minutes in a month.\n","minutesInYear":"\nminutesInYear( [value:integer|Date] )\n    Returns the number of minutes in a year according to the Gregorian calendar.\n","MOBY_DICK":"\nMOBY_DICK()\n    Returns the text of Moby Dick by Herman Melville.\n","MONTH_NAMES_EN":"\nMONTH_NAMES_EN()\n    Returns a list of month names (English).\n","MONTHS_IN_YEAR":"\nMONTHS_IN_YEAR\n    Number of months in a year.\n","moveProperty":"\nmoveProperty( source:Object, prop:string, target:Object )\n    Moves a property from one object to another object.\n","MultiSlice":"\nMultiSlice( ...slice )\n    Returns a multi-slice.\n","MultiSlice.prototype.ndims":"\nMultiSlice.prototype.ndims\n    Read-only property returning the number of slice dimensions.\n","MultiSlice.prototype.data":"\nMultiSlice.prototype.data\n    Read-only property returning the slice data.\n","MultiSlice.prototype.toString":"\nMultiSlice.prototype.toString()\n    Serializes a multi-slice as a string.\n","MultiSlice.prototype.toJSON":"\nMultiSlice.prototype.toJSON()\n    Serializes a multi-slice as a JSON object.\n","namedtypedtuple":"\nnamedtypedtuple( fields:Array<string>[, options:Object] )\n    Returns a named typed tuple factory.\n","NAN":"\nNAN\n    Double-precision floating-point NaN.\n","naryFunction":"\nnaryFunction( fcn:Function, arity:integer[, thisArg:any] )\n    Returns a function that applies a specified number of arguments to a\n    provided function.\n","nativeClass":"\nnativeClass( value:any )\n    Returns a string value indicating a specification defined classification of\n    an object.\n","ndarray":"\nndarray( dtype:string, buffer:ArrayLikeObject|TypedArray|Buffer, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  offset:integer, order:string[, options:Object] )\n    Returns an ndarray.\n","ndarray.prototype.byteLength":"\nndarray.prototype.byteLength\n    Size (in bytes) of the array (if known).\n","ndarray.prototype.BYTES_PER_ELEMENT":"\nndarray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element (if known).\n","ndarray.prototype.data":"\nndarray.prototype.data\n    Pointer to the underlying data buffer.\n","ndarray.prototype.dtype":"\nndarray.prototype.dtype\n    Underlying data type.\n","ndarray.prototype.flags":"\nndarray.prototype.flags\n    Meta information, such as information concerning the memory layout of the\n    array.\n","ndarray.prototype.length":"\nndarray.prototype.length\n    Length of the array (i.e., number of elements).\n","ndarray.prototype.ndims":"\nndarray.prototype.ndims\n    Number of dimensions.\n","ndarray.prototype.offset":"\nndarray.prototype.offset\n    Index offset which specifies the buffer index at which to start iterating\n    over array elements.\n","ndarray.prototype.order":"\nndarray.prototype.order\n    Array order.\n","ndarray.prototype.shape":"\nndarray.prototype.shape\n    Array shape.\n","ndarray.prototype.strides":"\nndarray.prototype.strides\n    Index strides which specify how to access data along corresponding array\n    dimensions.\n","ndarray.prototype.get":"\nndarray.prototype.get( ...idx:integer )\n    Returns an array element specified according to provided subscripts.\n","ndarray.prototype.iget":"\nndarray.prototype.iget( idx:integer )\n    Returns an array element located at a specified linear index.\n","ndarray.prototype.set":"\nndarray.prototype.set( ...idx:integer, v:any )\n    Sets an array element specified according to provided subscripts.\n","ndarray.prototype.iset":"\nndarray.prototype.iset( idx:integer, v:any )\n    Sets an array element located at a specified linear index.\n","ndarray.prototype.toString":"\nndarray.prototype.toString()\n    Serializes an ndarray as a string.\n","ndarray.prototype.toJSON":"\nndarray.prototype.toJSON()\n    Serializes an ndarray as a JSON object.\n","ndarray2array":"\nndarray2array( x:ndarray )\n    Converts an ndarray to a generic array.\n","ndarray2fancy":"\nndarray2fancy( x:ndarray[, options:Object] )\n    Converts an ndarray to an object supporting fancy indexing.\n","ndarray2fancy.factory":"\nndarray2fancy.factory( [options:Object] )\n    Returns a function for converting an ndarray to an object supporting fancy\n    indexing.\n","ndarray2fancy.idx":"\nndarray2fancy.idx( x:ndarray[, options:Object] )\n    Wraps a provided ndarray as an ndarray index object.\n","ndarray2json":"\nndarray2json( x:ndarray )\n    Serializes an ndarray as a JSON object.\n","ndarrayCastingModes":"\nndarrayCastingModes()\n    Returns a list of ndarray casting modes.\n","ndarrayDataBuffer":"\nndarrayDataBuffer( x:ndarray )\n    Returns the underlying data buffer of a provided ndarray.\n","ndarrayDataType":"\nndarrayDataType( x:ndarray )\n    Returns the data type of a provided ndarray.\n","ndarrayDataTypes":"\nndarrayDataTypes( [kind:string] )\n    Returns a list of ndarray data types.\n","ndarrayDispatch":"\nndarrayDispatch( fcns:Function|ArrayLikeObject<Function>, \n  types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, \n  nout:integer )\n    Returns an ndarray function interface which performs multiple dispatch.\n","ndarrayFlag":"\nndarrayFlag( x:ndarray, name:string|symbol )\n    Returns a specified flag for a provided ndarray.\n","ndarrayFlags":"\nndarrayFlags( x:ndarray )\n    Returns the flags of a provided ndarray.\n","ndarrayIndexModes":"\nndarrayIndexModes()\n    Returns a list of ndarray index modes.\n","ndarraylike2ndarray":"\nndarraylike2ndarray( x:ndarrayLike[, options:Object] )\n    Converts an ndarray-like object to an ndarray.\n","ndarrayMinDataType":"\nndarrayMinDataType( value:any )\n    Returns the minimum ndarray data type of the closest \"kind\" necessary for\n    storing a provided scalar value.\n","ndarrayMostlySafeCasts":"\nndarrayMostlySafeCasts( [dtype:any] )\n    Returns a list of ndarray data types to which a provided ndarray data type\n    can be safely cast and, for floating-point data types, can be downcast.\n","ndarrayNextDataType":"\nndarrayNextDataType( [dtype:any] )\n    Returns the next larger ndarray data type of the same kind.\n","ndarrayOffset":"\nndarrayOffset( x:ndarray )\n    Returns the index offset specifying the underlying buffer index of the first\n    iterated ndarray element.\n","ndarrayOrder":"\nndarrayOrder( x:ndarray )\n    Returns the layout order of a provided ndarray.\n","ndarrayOrders":"\nndarrayOrders()\n    Returns a list of ndarray orders.\n","ndarrayPromotionRules":"\nndarrayPromotionRules( [dtype1:any, dtype2:any] )\n    Returns the ndarray data type with the smallest size and closest \"kind\" to\n    which ndarray data types can be safely cast.\n","ndarraySafeCasts":"\nndarraySafeCasts( [dtype:any] )\n    Returns a list of ndarray data types to which a provided ndarray data type\n    can be safely cast.\n","ndarraySameKindCasts":"\nndarraySameKindCasts( [dtype:any] )\n    Returns a list of ndarray data types to which a provided ndarray data type\n    can be safely cast or cast within the same \"kind\".\n","ndarrayShape":"\nndarrayShape( x:ndarray )\n    Returns the shape of a provided ndarray.\n","ndarrayStride":"\nndarrayStride( x:ndarray, dim:integer )\n    Returns the stride along a specified dimension for a provided ndarray.\n","ndarrayStrides":"\nndarrayStrides( x:ndarray )\n    Returns the strides of a provided ndarray.\n","ndat":"\nndat( x:ndarray[, ...indices:integer] )\n    Returns an ndarray element.\n","ndempty":"\nndempty( shape:ArrayLikeObject<integer>|integer[, options:Object] )\n    Returns an uninitialized ndarray having a specified shape and data type.\n","ndemptyLike":"\nndemptyLike( x:ndarray[, options:Object] )\n    Returns an uninitialized ndarray having the same shape and data type as a\n    provided input ndarray.\n","ndfilter":"\nndfilter( x:ndarray[, options:Object], predicate:Function[, thisArg:any] )\n    Returns a shallow copy of an ndarray containing only those elements which\n    pass a test implemented by a predicate function.\n","ndfilterMap":"\nndfilterMap( x:ndarray[, options:Object], fcn:Function[, thisArg:any] )\n    Filters and maps elements in an input ndarray to elements in a new output\n    ndarray according to a callback function.\n","ndforEach":"\nndforEach( x:ndarray, fcn:Function[, thisArg:any] )\n    Invokes a callback function once for each ndarray element.\n","ndims":"\nndims( x:ndarray )\n    Returns the number of ndarray dimensions.\n","ndindex":"\nndindex( x:ndarray[, options:Object] )\n    Wraps a provided array as an ndarray index object.\n","ndindex.free":"\nndindex.free( id:string )\n    Frees the instance associated with a provided identifier.\n","ndindex.get":"\nndindex.get( id:string )\n    Returns the ndarray associated with the instance having a provided\n    identifier.\n","ndindex.cartesianIndex":"\nndindex.cartesianIndex( x:ndarray[, options:Object] )\n    Returns an ndarray index containing Cartesian indices.\n","ndindex.linearIndex":"\nndindex.linearIndex( x:ndarray[, options:Object] )\n    Returns an ndarray index for indices representing locations in linear\n    memory.\n","ndindex.prototype.data":"\nndindex.prototype.data\n    Read-only property returning an ndarray view of the underlying index\n    ndarray.\n","ndindex.prototype.dtype":"\nndindex.prototype.dtype\n    Read-only property returning the underlying data type of the index ndarray.\n","ndindex.prototype.id":"\nndindex.prototype.id\n    Read-only property returning the unique identifier associated with an\n    instance.\n","ndindex.prototype.isCached":"\nndindex.prototype.isCached\n    Read-only property returning a boolean indicating whether an ndarray index\n    is actively cached.\n","ndindex.prototype.kind":"\nndindex.prototype.kind\n    Read-only property returning the ndarray index kind.\n","ndindex.prototype.type":"\nndindex.prototype.type\n    Read-only property returning the ndarray index type.\n","ndindex.prototype.toString":"\nndindex.prototype.toString()\n    Serializes an instance as a string.\n","ndindex.prototype.toJSON":"\nndindex.prototype.toJSON()\n    Serializes an instance as a JSON object.\n","nditerColumnEntries":"\nnditerColumnEntries( x:ndarray[, options:Object] )\n    Returns an iterator which returns [index, column] pairs for each column in a\n    matrix (or stack of matrices).\n","nditerColumns":"\nnditerColumns( x:ndarray[, options:Object] )\n    Returns an iterator which iterates over each column in a matrix (or stack of\n    matrices).\n","nditerEntries":"\nnditerEntries( x:ndarray[, options:Object] )\n    Returns an iterator which returns [index, value] pairs for each element in a\n    provided ndarray.\n","nditerIndices":"\nnditerIndices( shape:Array<integer>[, options:Object] )\n    Returns an iterator which returns indices for use indexing into an ndarray\n    having a specified shape.\n","nditerInterleaveSubarrays":"\nnditerInterleaveSubarrays( arr:ArrayLike<ndarray>, ndims:integer )\n    Returns an iterator which iterates over interleaved subarrays.\n","nditerMatrices":"\nnditerMatrices( x:ndarray[, options:Object] )\n    Returns an iterator which iterates over each matrix in a stack of matrices.\n","nditerMatrixEntries":"\nnditerMatrixEntries( x:ndarray[, options:Object] )\n    Returns an iterator which returns [index, matrix] pairs for each matrix in a\n    stack of matrices.\n","nditerRowEntries":"\nnditerRowEntries( x:ndarray[, options:Object] )\n    Returns an iterator which returns [index, row] pairs for each row in a\n    matrix (or stack of matrices).\n","nditerRows":"\nnditerRows( x:ndarray[, options:Object] )\n    Returns an iterator which iterates over each row in a matrix (or stack of\n    matrices).\n","nditerSelectDimension":"\nnditerSelectDimension( x:ndarray, dim:integer[, options:Object] )\n    Returns an iterator which iterates over each view along a specified\n    dimension.\n","nditerStacks":"\nnditerStacks( x:ndarray, dims:Array<integer>[, options:Object] )\n    Returns an iterator which iterates over each subarray in a stack of\n    subarrays according to a list of specified stack dimensions.\n","nditerSubarrays":"\nnditerSubarrays( x:ndarray, ndims:integer[, options:Object] )\n    Returns an iterator which iterates over each subarray in a stack of\n    subarrays.\n","nditerValues":"\nnditerValues( x:ndarray[, options:Object] )\n    Returns an iterator which returns individual elements from a provided\n    ndarray.\n","ndmap":"\nndmap( x:ndarray[, options:Object], fcn:Function[, thisArg:any] )\n    Applies a callback function to elements in an input ndarray and assigns\n    results to elements in a new output ndarray.\n","ndreject":"\nndreject( x:ndarray[, options:Object], predicate:Function[, thisArg:any] )\n    Returns a shallow copy of an ndarray containing only those elements which\n    fail a test implemented by a predicate function.\n","ndslice":"\nndslice( x:ndarray, ...s:MultiSlice|Slice|null|undefined|integer|ArrayLike[, \n  options:Object] )\n    Returns a read-only view of an input ndarray.\n","ndsliceAssign":"\nndsliceAssign( x:ndarray, y:ndarray, \n  ...s:MultiSlice|Slice|null|undefined|integer|ArrayLike[, options:Object] )\n    Assigns element values from a broadcasted input ndarray to corresponding\n    elements in an output ndarray view.\n","ndsliceDimension":"\nndsliceDimension( x:ndarray, dim:integer, slice:Slice|integer|null|undefined[, \n  options:Object] )\n    Returns a read-only view of an input ndarray when sliced along a specified\n    dimension.\n","ndsliceDimensionFrom":"\nndsliceDimensionFrom( x:ndarray, dim:integer, start:integer[, options:Object] )\n    Returns a read-only shifted view of an input ndarray along a specified\n    dimension.\n","ndsliceDimensionTo":"\nndsliceDimensionTo( x:ndarray, dim:integer, stop:integer[, options:Object] )\n    Returns a read-only truncated view of an input ndarray along a specified\n    dimension.\n","ndsliceFrom":"\nndsliceFrom( x:ndarray, ...start:null|void|integer[, options:Object] )\n    Returns a read-only shifted view of an input ndarray.\n","ndsliceTo":"\nndsliceTo( x:ndarray, ...stop:null|void|integer[, options:Object] )\n    Returns a read-only truncated view of an input ndarray.\n","ndzeros":"\nndzeros( shape:ArrayLikeObject<integer>|integer[, options:Object] )\n    Returns a zero-filled ndarray having a specified shape and data type.\n","ndzerosLike":"\nndzerosLike( x:ndarray[, options:Object] )\n    Returns a zero-filled ndarray having the same shape and data type as a\n    provided input ndarray.\n","nextGraphemeClusterBreak":"\nnextGraphemeClusterBreak( str:string[, fromIndex:integer] )\n    Returns the next extended grapheme cluster break in a string after a\n    specified position.\n","nextTick":"\nnextTick( clbk[, ...args] )\n    Adds a callback to the \"next tick queue\".\n","NIGHTINGALES_ROSE":"\nNIGHTINGALES_ROSE()\n    Returns data for Nightingale's famous polar area diagram.\n","NINF":"\nNINF\n    Double-precision floating-point negative infinity.\n","NODE_VERSION":"\nNODE_VERSION\n    Node version.\n","none":"\nnone( collection:Array|TypedArray|Object )\n    Tests whether all elements in a collection are falsy.\n","noneBy":"\nnoneBy( collection:Array|TypedArray|Object, predicate:Function[, thisArg:any ] )\n    Tests whether all elements in a collection fail a test implemented by a\n    predicate function.\n","noneByAsync":"\nnoneByAsync( collection:Array|TypedArray|Object, [options:Object,] \n  predicate:Function, done:Function )\n    Tests whether all elements in a collection fail a test implemented by a\n    predicate function.\n","noneByAsync.factory":"\nnoneByAsync.factory( [options:Object,] predicate:Function )\n    Returns a function which tests whether all elements in a collection fail a\n    test implemented by a predicate function.\n","noneByRight":"\nnoneByRight( collection:Array|TypedArray|Object, predicate:Function[, \n  thisArg:any ] )\n    Tests whether all elements in a collection fail a test implemented by a\n    predicate function, iterating from right to left.\n","noneByRightAsync":"\nnoneByRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n  predicate:Function, done:Function )\n    Tests whether all elements in a collection fail a test implemented by a\n    predicate function, iterating from right to left.\n","noneByRightAsync.factory":"\nnoneByRightAsync.factory( [options:Object,] predicate:Function )\n    Returns a function which tests whether all elements in a collection fail a\n    test implemented by a predicate function, iterating from right to left.\n","noneInBy":"\nnoneInBy( object:Object, predicate:Function[, thisArg:any ] )\n    Tests whether every property in an object fails a test implemented by a\n    predicate function.\n","nonEnumerableProperties":"\nnonEnumerableProperties( value:any )\n    Returns an array of an object's own non-enumerable property names and\n    symbols.\n","nonEnumerablePropertiesIn":"\nnonEnumerablePropertiesIn( value:any )\n    Returns an array of an object's own and inherited non-enumerable property\n    names and symbols.\n","nonEnumerablePropertyNames":"\nnonEnumerablePropertyNames( value:any )\n    Returns an array of an object's own non-enumerable property names.\n","nonEnumerablePropertyNamesIn":"\nnonEnumerablePropertyNamesIn( value:any )\n    Returns an array of an object's own and inherited non-enumerable property\n    names.\n","nonEnumerablePropertySymbols":"\nnonEnumerablePropertySymbols( value:any )\n    Returns an array of an object's own non-enumerable symbol properties.\n","nonEnumerablePropertySymbolsIn":"\nnonEnumerablePropertySymbolsIn( value:any )\n    Returns an array of an object's own and inherited non-enumerable symbol\n    properties.\n","noneOwnBy":"\nnoneOwnBy( object:Object, predicate:Function[, thisArg:any ] )\n    Tests whether every own property of an object fails a test implemented\n    by a predicate function.\n","nonIndexKeys":"\nnonIndexKeys( obj:any )\n    Returns an array of an object's own enumerable property names which are not\n    integer indices.\n","noop":"\nnoop()\n    A function which does nothing.\n","now":"\nnow()\n    Returns the time in seconds since the epoch.\n","NUM_CPUS":"\nNUM_CPUS\n    Number of CPUs.\n","num2words":"\nnum2words( value:integer[, options:Object] )\n    Converts a number to a word representation.\n","Number":"\nNumber( value:number )\n    Returns a Number object.\n","numel":"\nnumel( x:ndarray )\n    Returns the number of elements in an ndarray.\n","numelDimension":"\nnumelDimension( x:ndarray, dim:integer )\n    Returns the size (i.e., number of elements) of a specified dimension for a\n    provided ndarray.\n","numGraphemeClusters":"\nnumGraphemeClusters( str:string )\n    Returns the number of grapheme clusters in a string.\n","Object":"\nObject( value:any )\n    Returns an object.\n","Object.assign":"\nObject.assign( target:Object, ...sources:Object )\n    Assigns enumerable and own properties from source objects to a target\n    object.\n","Object.create":"\nObject.create( prototype:Object, properties:Object )\n    Creates a new object with a specified prototype object and properties.\n","Object.defineProperties":"\nObject.defineProperties( obj:Object, properties:Object )\n    Defines properties for an object.\n","Object.defineProperty":"\nObject.defineProperty( obj:Object, key:string, descriptor:Object )\n    Defines a property for an object.\n","Object.entries":"\nObject.entries( obj:Object )\n    Returns an array of an object's own enumerable string-keyed property\n    [key, value] pairs.\n","Object.freeze":"\nObject.freeze( obj:Object )\n    Freezes an object.\n","Object.getOwnPropertyDescriptor":"\nObject.getOwnPropertyDescriptor( obj:Object, key:string )\n    Returns an object's own property descriptor.\n","Object.getOwnPropertyDescriptors":"\nObject.getOwnPropertyDescriptors( obj:Object )\n    Returns an object's own property descriptors.\n","Object.getOwnPropertyNames":"\nObject.getOwnPropertyNames( obj:Object )\n    Returns an array of an object's own enumerable and non-enumerable\n    property names.\n","Object.getOwnPropertySymbols":"\nObject.getOwnPropertySymbols( obj:Object )\n    Returns an array of an object's own enumerable and non-enumerable\n    symbol property names.\n","Object.getPrototypeOf":"\nObject.getPrototypeOf( obj:Object )\n    Returns an object's prototype.\n","Object.hasOwn":"\nObject.hasOwn( obj:Object, p:string )\n    Returns a boolean indicating whether an object has a property with the\n    specified name.\n","Object.is":"\nObject.is( value1:any, value2:any )\n    Returns a boolean indicating whether two values are the same value.\n","Object.isExtensible":"\nObject.isExtensible( obj:Object )\n    Returns a boolean indicating whether an object is extensible.\n","Object.isFrozen":"\nObject.isFrozen( obj:Object )\n    Returns a boolean indicating whether an object is frozen.\n","Object.isSealed":"\nObject.isSealed( obj:Object )\n    Returns a boolean indicating whether an object is sealed.\n","Object.keys":"\nObject.keys( obj:Object )\n    Returns an array of an object's own enumerable string-keyed property\n    names.\n","Object.preventExtensions":"\nObject.preventExtensions( obj:Object )\n    Prevents the addition of new properties to an object.\n","Object.seal":"\nObject.seal( obj:Object )\n    Prevents the addition of new properties to an object and marks all\n    existing properties as non-configurable.\n","Object.setPrototypeOf":"\nObject.setPrototypeOf( obj:Object, proto:Object )\n    Sets an object's prototype.\n","Object.values":"\nObject.values( obj:Object )\n    Returns an array of an object's own enumerable property values.\n","Object.prototype.toLocaleString":"\nObject.prototype.toLocaleString()\n    Returns a string representing the object.\n","Object.prototype.toString":"\nObject.prototype.toString()\n    Returns a string representing the object.\n","Object.prototype.valueOf":"\nObject.prototype.valueOf()\n    Returns the primitive value of the object.\n","Object.prototype.hasOwnProperty":"\nObject.prototype.hasOwnProperty( p:string )\n    Returns a boolean indicating whether an object has a property with the\n    specified name.\n","Object.prototype.isPrototypeOf":"\nObject.prototype.isPrototypeOf( obj:Object )\n    Returns a boolean indicating whether an object exists in another object's\n    prototype chain.\n","Object.prototype.propertyIsEnumerable":"\nObject.prototype.propertyIsEnumerable( p:string )\n    Returns a boolean indicating whether an object's property is enumerable.\n","Object.prototype.constructor":"\nObject.prototype.constructor\n    Property whose value is a reference to the constructor function that\n    created the instance object.\n","objectEntries":"\nobjectEntries( obj:ObjectLike )\n    Returns an array of an object's own enumerable property `[key, value]`\n    pairs.\n","objectEntriesIn":"\nobjectEntriesIn( obj:ObjectLike )\n    Returns an array of an object's own and inherited enumerable property\n    `[key, value]` pairs.\n","objectFromEntries":"\nobjectFromEntries( entries:Array<Array> )\n    Creates an object from an array of key-value pairs.\n","objectInverse":"\nobjectInverse( obj:ObjectLike[, options:Object] )\n    Inverts an object, such that keys become values and values become keys.\n","objectInverseBy":"\nobjectInverseBy( obj:ObjectLike, [options:Object,] transform:Function )\n    Inverts an object, such that keys become values and values become keys,\n    according to a transform function.\n","objectKeys":"\nobjectKeys( value:any )\n    Returns an array of an object's own enumerable property names.\n","objectValues":"\nobjectValues( obj:ObjectLike )\n    Returns an array of an object's own enumerable property values.\n","objectValuesIn":"\nobjectValuesIn( obj:ObjectLike )\n    Returns an array of an object's own and inherited enumerable property\n    values.\n","omit":"\nomit( obj:Object, keys:string|Array )\n    Returns a partial object copy excluding specified keys.\n","omitBy":"\nomitBy( obj:Object, predicate:Function )\n    Returns a partial object copy excluding properties for which a predicate\n    returns a truthy value.\n","open":"\nopen( path:string|Buffer[, flags:string|number[, mode:integer]], clbk:Function )\n    Asynchronously opens a file.\n","open.sync":"\nopen.sync( path:string|Buffer[, flags:string|number[, mode:integer]] )\n    Synchronously opens a file.\n","openURL":"\nopenURL( url:string )\n    Opens a URL in a user's default browser.\n","ordinalize":"\nordinalize( value:string|integer[, options:Object] )\n    Converts an integer to an ordinal string (e.g., `1st`, `2nd`, etc.).\n","PACE_BOSTON_HOUSE_PRICES":"\nPACE_BOSTON_HOUSE_PRICES()\n    Returns a (corrected) dataset derived from information collected by the US\n    Census Service concerning housing in Boston, Massachusetts (1978).\n","pad":"\npad( str:string, len:integer[, options:Object] )\n    Pads a `string` such that the padded `string` has length `len`.\n","padjust":"\npadjust( pvals:Array<number>, method:string[, comparisons:integer] )\n    Adjusts supplied p-values for multiple comparisons via a specified method.\n","papply":"\npapply( fcn:Function, ...args:any )\n    Returns a function of smaller arity by partially applying arguments.\n","papplyRight":"\npapplyRight( fcn:Function, ...args:any )\n    Returns a function of smaller arity by partially applying arguments from the\n    right.\n","parallel":"\nparallel( files:Array<string>, [options:Object,] clbk:Function )\n    Executes scripts in parallel.\n","parseJSON":"\nparseJSON( str:string[, reviver:Function] )\n    Attempts to parse a string as JSON.\n","pascalcase":"\npascalcase( str:string )\n    Converts a string to Pascal case.\n","PATH_DELIMITER":"\nPATH_DELIMITER\n    Platform-specific path delimiter.\n","PATH_DELIMITER_POSIX":"\nPATH_DELIMITER_POSIX\n    POSIX path delimiter.\n","PATH_DELIMITER_WIN32":"\nPATH_DELIMITER_WIN32\n    Windows path delimiter.\n","PATH_SEP":"\nPATH_SEP\n    Platform-specific path segment separator.\n","PATH_SEP_POSIX":"\nPATH_SEP_POSIX\n    POSIX path segment separator.\n","PATH_SEP_WIN32":"\nPATH_SEP_WIN32\n    Windows path segment separator.\n","pcorrtest":"\npcorrtest( x:Array<number>, y:Array<number>[, options:Object] )\n    Computes a Pearson product-moment correlation test between paired samples.\n","percentEncode":"\npercentEncode( str:string )\n    Percent-encodes a UTF-16 encoded string according to RFC 3986.\n","PHI":"\nPHI\n    Golden ratio.\n","PI":"\nPI\n    The mathematical constant `π`.\n","PI_SQUARED":"\nPI_SQUARED\n    Square of the mathematical constant `π`.\n","pick":"\npick( obj:Object, keys:string|Array )\n    Returns a partial object copy containing only specified keys.\n","pickArguments":"\npickArguments( fcn:Function, indices:Array<integer>[, thisArg:any] )\n    Returns a function that applies specified arguments to a provided function.\n","pickBy":"\npickBy( obj:Object, predicate:Function )\n    Returns a partial object copy containing properties for which a predicate\n    returns a truthy value.\n","PINF":"\nPINF\n    Double-precision floating-point positive infinity.\n","pkg2alias":"\npkg2alias( pkg:string )\n    Returns the alias associated with a specified package name.\n","pkg2related":"\npkg2related( pkg:string )\n    Returns package names related to a specified package name.\n","pkg2standalone":"\npkg2standalone( pkg:string )\n    Returns the standalone package name associated with a provided internal\n    package name.\n","PLATFORM":"\nPLATFORM\n    Platform on which the current process is running.\n","plot":"\nplot( [x:Array|Array, y:Array|Array,] [options:Object] )\n    Returns a plot instance for creating 2-dimensional plots.\n","Plot":"\nPlot( [x:Array|Array, y:Array|Array,] [options:Object] )\n    Returns a plot instance for creating 2-dimensional plots.\n","pluck":"\npluck( arr:Array, prop:string[, options:Object] )\n    Extracts a property value from each element of an object array.\n","pop":"\npop( collection:Array|TypedArray|Object )\n    Removes and returns the last element of a collection.\n","porterStemmer":"\nporterStemmer( word:string )\n    Extracts the stem of a given word.\n","prepend":"\nprepend( collection1:Array|TypedArray|Object, \n  collection2:Array|TypedArray|Object )\n    Adds the elements of one collection to the beginning of another collection.\n","prevGraphemeClusterBreak":"\nprevGraphemeClusterBreak( str:string[, fromIndex:integer] )\n    Returns the previous extended grapheme cluster break in a string before a\n    specified position.\n","PRIMES_100K":"\nPRIMES_100K()\n    Returns an array containing the first 100,000 prime numbers.\n","properties":"\nproperties( value:any )\n    Returns an array of an object's own enumerable and non-enumerable property\n    names and symbols.\n","propertiesIn":"\npropertiesIn( value:any )\n    Returns an array of an object's own and inherited property names and\n    symbols.\n","propertyDescriptor":"\npropertyDescriptor( value:any, property:string|symbol )\n    Returns a property descriptor for an object's own property.\n","propertyDescriptorIn":"\npropertyDescriptorIn( value:any, property:string|symbol )\n    Returns a property descriptor for an object's own or inherited property.\n","propertyDescriptors":"\npropertyDescriptors( value:any )\n    Returns an object's own property descriptors.\n","propertyDescriptorsIn":"\npropertyDescriptorsIn( value:any )\n    Returns an object's own and inherited property descriptors.\n","propertyNames":"\npropertyNames( value:any )\n    Returns an array of an object's own enumerable and non-enumerable property\n    names.\n","propertyNamesIn":"\npropertyNamesIn( value:any )\n    Returns an array of an object's own and inherited enumerable and non-\n    enumerable property names.\n","propertySymbols":"\npropertySymbols( value:any )\n    Returns an array of an object's own symbol properties.\n","propertySymbolsIn":"\npropertySymbolsIn( value:any )\n    Returns an array of an object's own and inherited symbol properties.\n","Proxy":"\nProxy( target:Object, handlers:Object )\n    Returns a proxy object implementing custom behavior for specified object\n    operations.\n","Proxy.revocable":"\nProxy.revocable( target:Object, handlers:Object )\n    Returns a revocable proxy object.\n","push":"\npush( collection:Array|TypedArray|Object, ...items:any )\n    Adds one or more elements to the end of a collection.\n","quarterOfYear":"\nquarterOfYear( [month:integer|string|Date] )\n    Returns the quarter of the year.\n","random.array.arcsine":"\nrandom.array.arcsine( len:integer, a:number, b:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from an arcsine\n    distribution.\n","random.array.arcsine.assign":"\nrandom.array.arcsine.assign( a:number, b:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from an arcsine distribution.\n","random.array.arcsine.factory":"\nrandom.array.arcsine.factory( [a:number, b:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an arcsine distribution.\n","random.array.arcsine.PRNG":"\nrandom.array.arcsine.PRNG\n    Underlying pseudorandom number generator.\n","random.array.arcsine.seed":"\nrandom.array.arcsine.seed\n    Pseudorandom number generator seed.\n","random.array.arcsine.seedLength":"\nrandom.array.arcsine.seedLength\n    Length of generator seed.\n","random.array.arcsine.state":"\nrandom.array.arcsine.state\n    Generator state.\n","random.array.arcsine.stateLength":"\nrandom.array.arcsine.stateLength\n    Length of generator state.\n","random.array.arcsine.byteLength":"\nrandom.array.arcsine.byteLength\n    Size (in bytes) of generator state.\n","random.array.bernoulli":"\nrandom.array.bernoulli( len:integer, p:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a Bernoulli\n    distribution.\n","random.array.bernoulli.assign":"\nrandom.array.bernoulli.assign( p:number, out:Array|TypedArray )\n    Fills an array with pseudorandom numbers drawn from a Bernoulli\n    distribution.\n","random.array.bernoulli.factory":"\nrandom.array.bernoulli.factory( [p:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Bernoulli distribution.\n","random.array.bernoulli.PRNG":"\nrandom.array.bernoulli.PRNG\n    Underlying pseudorandom number generator.\n","random.array.bernoulli.seed":"\nrandom.array.bernoulli.seed\n    Pseudorandom number generator seed.\n","random.array.bernoulli.seedLength":"\nrandom.array.bernoulli.seedLength\n    Length of generator seed.\n","random.array.bernoulli.state":"\nrandom.array.bernoulli.state\n    Generator state.\n","random.array.bernoulli.stateLength":"\nrandom.array.bernoulli.stateLength\n    Length of generator state.\n","random.array.bernoulli.byteLength":"\nrandom.array.bernoulli.byteLength\n    Size (in bytes) of generator state.\n","random.array.beta":"\nrandom.array.beta( len:integer, alpha:number, beta:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a beta\n    distribution.\n","random.array.beta.assign":"\nrandom.array.beta.assign( alpha:number, beta:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a beta distribution.\n","random.array.beta.factory":"\nrandom.array.beta.factory( [alpha:number, beta:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a beta distribution.\n","random.array.beta.PRNG":"\nrandom.array.beta.PRNG\n    Underlying pseudorandom number generator.\n","random.array.beta.seed":"\nrandom.array.beta.seed\n    Pseudorandom number generator seed.\n","random.array.beta.seedLength":"\nrandom.array.beta.seedLength\n    Length of generator seed.\n","random.array.beta.state":"\nrandom.array.beta.state\n    Generator state.\n","random.array.beta.stateLength":"\nrandom.array.beta.stateLength\n    Length of generator state.\n","random.array.beta.byteLength":"\nrandom.array.beta.byteLength\n    Size (in bytes) of generator state.\n","random.array.betaprime":"\nrandom.array.betaprime( len:integer, alpha:number, beta:number[, \n  options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a beta prime\n    distribution.\n","random.array.betaprime.assign":"\nrandom.array.betaprime.assign( alpha:number, beta:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a beta prime\n    distribution.\n","random.array.betaprime.factory":"\nrandom.array.betaprime.factory( [alpha:number, beta:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a beta prime distribution.\n","random.array.betaprime.PRNG":"\nrandom.array.betaprime.PRNG\n    Underlying pseudorandom number generator.\n","random.array.betaprime.seed":"\nrandom.array.betaprime.seed\n    Pseudorandom number generator seed.\n","random.array.betaprime.seedLength":"\nrandom.array.betaprime.seedLength\n    Length of generator seed.\n","random.array.betaprime.state":"\nrandom.array.betaprime.state\n    Generator state.\n","random.array.betaprime.stateLength":"\nrandom.array.betaprime.stateLength\n    Length of generator state.\n","random.array.betaprime.byteLength":"\nrandom.array.betaprime.byteLength\n    Size (in bytes) of generator state.\n","random.array.binomial":"\nrandom.array.binomial( len:integer, n:number, p:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a binomial\n    distribution.\n","random.array.binomial.assign":"\nrandom.array.binomial.assign( n:number, p:number, out:Array|TypedArray )\n    Fills an array with pseudorandom numbers drawn from a binomial distribution.\n","random.array.binomial.factory":"\nrandom.array.binomial.factory( [n:number, p:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a binomial distribution.\n","random.array.binomial.PRNG":"\nrandom.array.binomial.PRNG\n    Underlying pseudorandom number generator.\n","random.array.binomial.seed":"\nrandom.array.binomial.seed\n    Pseudorandom number generator seed.\n","random.array.binomial.seedLength":"\nrandom.array.binomial.seedLength\n    Length of generator seed.\n","random.array.binomial.state":"\nrandom.array.binomial.state\n    Generator state.\n","random.array.binomial.stateLength":"\nrandom.array.binomial.stateLength\n    Length of generator state.\n","random.array.binomial.byteLength":"\nrandom.array.binomial.byteLength\n    Size (in bytes) of generator state.\n","random.array.cauchy":"\nrandom.array.cauchy( len:integer, x0:number, gamma:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a Cauchy\n    distribution.\n","random.array.cauchy.assign":"\nrandom.array.cauchy.assign( x0:number, gamma:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a Cauchy distribution.\n","random.array.cauchy.factory":"\nrandom.array.cauchy.factory( [x0:number, gamma:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Cauchy distribution.\n","random.array.cauchy.PRNG":"\nrandom.array.cauchy.PRNG\n    Underlying pseudorandom number generator.\n","random.array.cauchy.seed":"\nrandom.array.cauchy.seed\n    Pseudorandom number generator seed.\n","random.array.cauchy.seedLength":"\nrandom.array.cauchy.seedLength\n    Length of generator seed.\n","random.array.cauchy.state":"\nrandom.array.cauchy.state\n    Generator state.\n","random.array.cauchy.stateLength":"\nrandom.array.cauchy.stateLength\n    Length of generator state.\n","random.array.cauchy.byteLength":"\nrandom.array.cauchy.byteLength\n    Size (in bytes) of generator state.\n","random.array.chi":"\nrandom.array.chi( len:integer, k:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a chi\n    distribution.\n","random.array.chi.assign":"\nrandom.array.chi.assign( k:number, out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a chi distribution.\n","random.array.chi.factory":"\nrandom.array.chi.factory( [k:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a chi distribution.\n","random.array.chi.PRNG":"\nrandom.array.chi.PRNG\n    Underlying pseudorandom number generator.\n","random.array.chi.seed":"\nrandom.array.chi.seed\n    Pseudorandom number generator seed.\n","random.array.chi.seedLength":"\nrandom.array.chi.seedLength\n    Length of generator seed.\n","random.array.chi.state":"\nrandom.array.chi.state\n    Generator state.\n","random.array.chi.stateLength":"\nrandom.array.chi.stateLength\n    Length of generator state.\n","random.array.chi.byteLength":"\nrandom.array.chi.byteLength\n    Size (in bytes) of generator state.\n","random.array.chisquare":"\nrandom.array.chisquare( len:integer, k:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a chi-square\n    distribution.\n","random.array.chisquare.assign":"\nrandom.array.chisquare.assign( k:number, out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a chi-square\n    distribution.\n","random.array.chisquare.factory":"\nrandom.array.chisquare.factory( [k:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a chi-square distribution.\n","random.array.chisquare.PRNG":"\nrandom.array.chisquare.PRNG\n    Underlying pseudorandom number generator.\n","random.array.chisquare.seed":"\nrandom.array.chisquare.seed\n    Pseudorandom number generator seed.\n","random.array.chisquare.seedLength":"\nrandom.array.chisquare.seedLength\n    Length of generator seed.\n","random.array.chisquare.state":"\nrandom.array.chisquare.state\n    Generator state.\n","random.array.chisquare.stateLength":"\nrandom.array.chisquare.stateLength\n    Length of generator state.\n","random.array.chisquare.byteLength":"\nrandom.array.chisquare.byteLength\n    Size (in bytes) of generator state.\n","random.array.cosine":"\nrandom.array.cosine( len:integer, mu:number, s:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a raised cosine\n    distribution.\n","random.array.cosine.assign":"\nrandom.array.cosine.assign( mu:number, s:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a raised cosine\n    distribution.\n","random.array.cosine.factory":"\nrandom.array.cosine.factory( [mu:number, s:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a raised cosine distribution.\n","random.array.cosine.PRNG":"\nrandom.array.cosine.PRNG\n    Underlying pseudorandom number generator.\n","random.array.cosine.seed":"\nrandom.array.cosine.seed\n    Pseudorandom number generator seed.\n","random.array.cosine.seedLength":"\nrandom.array.cosine.seedLength\n    Length of generator seed.\n","random.array.cosine.state":"\nrandom.array.cosine.state\n    Generator state.\n","random.array.cosine.stateLength":"\nrandom.array.cosine.stateLength\n    Length of generator state.\n","random.array.cosine.byteLength":"\nrandom.array.cosine.byteLength\n    Size (in bytes) of generator state.\n","random.array.discreteUniform":"\nrandom.array.discreteUniform( len:integer, a:number, b:number[, \n  options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a discrete\n    uniform distribution.\n","random.array.discreteUniform.assign":"\nrandom.array.discreteUniform.assign( a:number, b:number, out:Array|TypedArray )\n    Fills an array with pseudorandom numbers drawn from a discrete uniform\n    distribution.\n","random.array.discreteUniform.factory":"\nrandom.array.discreteUniform.factory( [a:number, b:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a discrete uniform distribution.\n","random.array.discreteUniform.PRNG":"\nrandom.array.discreteUniform.PRNG\n    Underlying pseudorandom number generator.\n","random.array.discreteUniform.seed":"\nrandom.array.discreteUniform.seed\n    Pseudorandom number generator seed.\n","random.array.discreteUniform.seedLength":"\nrandom.array.discreteUniform.seedLength\n    Length of generator seed.\n","random.array.discreteUniform.state":"\nrandom.array.discreteUniform.state\n    Generator state.\n","random.array.discreteUniform.stateLength":"\nrandom.array.discreteUniform.stateLength\n    Length of generator state.\n","random.array.discreteUniform.byteLength":"\nrandom.array.discreteUniform.byteLength\n    Size (in bytes) of generator state.\n","random.array.erlang":"\nrandom.array.erlang( len:integer, k:number, lambda:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from an Erlang\n    distribution.\n","random.array.erlang.assign":"\nrandom.array.erlang.assign( k:number, lambda:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from an Erlang distribution.\n","random.array.erlang.factory":"\nrandom.array.erlang.factory( [k:number, lambda:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an Erlang distribution.\n","random.array.erlang.PRNG":"\nrandom.array.erlang.PRNG\n    Underlying pseudorandom number generator.\n","random.array.erlang.seed":"\nrandom.array.erlang.seed\n    Pseudorandom number generator seed.\n","random.array.erlang.seedLength":"\nrandom.array.erlang.seedLength\n    Length of generator seed.\n","random.array.erlang.state":"\nrandom.array.erlang.state\n    Generator state.\n","random.array.erlang.stateLength":"\nrandom.array.erlang.stateLength\n    Length of generator state.\n","random.array.erlang.byteLength":"\nrandom.array.erlang.byteLength\n    Size (in bytes) of generator state.\n","random.array.exponential":"\nrandom.array.exponential( len:integer, lambda:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from an exponential\n    distribution.\n","random.array.exponential.assign":"\nrandom.array.exponential.assign( lambda:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from an exponential\n    distribution.\n","random.array.exponential.factory":"\nrandom.array.exponential.factory( [lambda:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an exponential distribution.\n","random.array.exponential.PRNG":"\nrandom.array.exponential.PRNG\n    Underlying pseudorandom number generator.\n","random.array.exponential.seed":"\nrandom.array.exponential.seed\n    Pseudorandom number generator seed.\n","random.array.exponential.seedLength":"\nrandom.array.exponential.seedLength\n    Length of generator seed.\n","random.array.exponential.state":"\nrandom.array.exponential.state\n    Generator state.\n","random.array.exponential.stateLength":"\nrandom.array.exponential.stateLength\n    Length of generator state.\n","random.array.exponential.byteLength":"\nrandom.array.exponential.byteLength\n    Size (in bytes) of generator state.\n","random.array.f":"\nrandom.array.f( len:integer, d1:number, d2:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from an F\n    distribution.\n","random.array.f.assign":"\nrandom.array.f.assign( d1:number, d2:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from an F distribution.\n","random.array.f.factory":"\nrandom.array.f.factory( [d1:number, d2:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an F distribution.\n","random.array.f.PRNG":"\nrandom.array.f.PRNG\n    Underlying pseudorandom number generator.\n","random.array.f.seed":"\nrandom.array.f.seed\n    Pseudorandom number generator seed.\n","random.array.f.seedLength":"\nrandom.array.f.seedLength\n    Length of generator seed.\n","random.array.f.state":"\nrandom.array.f.state\n    Generator state.\n","random.array.f.stateLength":"\nrandom.array.f.stateLength\n    Length of generator state.\n","random.array.f.byteLength":"\nrandom.array.f.byteLength\n    Size (in bytes) of generator state.\n","random.array.frechet":"\nrandom.array.frechet( len:integer, alpha:number, s:number, m:number[, \n  options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a Fréchet\n    distribution.\n","random.array.frechet.assign":"\nrandom.array.frechet.assign( alpha:number, s:number, m:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a Fréchet distribution.\n","random.array.frechet.factory":"\nrandom.array.frechet.factory( [alpha:number, s:number, m:number, ]\n  [options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Fréchet distribution.\n","random.array.frechet.PRNG":"\nrandom.array.frechet.PRNG\n    Underlying pseudorandom number generator.\n","random.array.frechet.seed":"\nrandom.array.frechet.seed\n    Pseudorandom number generator seed.\n","random.array.frechet.seedLength":"\nrandom.array.frechet.seedLength\n    Length of generator seed.\n","random.array.frechet.state":"\nrandom.array.frechet.state\n    Generator state.\n","random.array.frechet.stateLength":"\nrandom.array.frechet.stateLength\n    Length of generator state.\n","random.array.frechet.byteLength":"\nrandom.array.frechet.byteLength\n    Size (in bytes) of generator state.\n","random.array.gamma":"\nrandom.array.gamma( len:integer, alpha:number, beta:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a gamma\n    distribution.\n","random.array.gamma.assign":"\nrandom.array.gamma.assign( alpha:number, beta:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a gamma distribution.\n","random.array.gamma.factory":"\nrandom.array.gamma.factory( [alpha:number, beta:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a gamma distribution.\n","random.array.gamma.PRNG":"\nrandom.array.gamma.PRNG\n    Underlying pseudorandom number generator.\n","random.array.gamma.seed":"\nrandom.array.gamma.seed\n    Pseudorandom number generator seed.\n","random.array.gamma.seedLength":"\nrandom.array.gamma.seedLength\n    Length of generator seed.\n","random.array.gamma.state":"\nrandom.array.gamma.state\n    Generator state.\n","random.array.gamma.stateLength":"\nrandom.array.gamma.stateLength\n    Length of generator state.\n","random.array.gamma.byteLength":"\nrandom.array.gamma.byteLength\n    Size (in bytes) of generator state.\n","random.array.geometric":"\nrandom.array.geometric( len:integer, p:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a geometric\n    distribution.\n","random.array.geometric.assign":"\nrandom.array.geometric.assign( p:number, out:Array|TypedArray )\n    Fills an array with pseudorandom numbers drawn from a geometric\n    distribution.\n","random.array.geometric.factory":"\nrandom.array.geometric.factory( [p:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a geometric distribution.\n","random.array.geometric.PRNG":"\nrandom.array.geometric.PRNG\n    Underlying pseudorandom number generator.\n","random.array.geometric.seed":"\nrandom.array.geometric.seed\n    Pseudorandom number generator seed.\n","random.array.geometric.seedLength":"\nrandom.array.geometric.seedLength\n    Length of generator seed.\n","random.array.geometric.state":"\nrandom.array.geometric.state\n    Generator state.\n","random.array.geometric.stateLength":"\nrandom.array.geometric.stateLength\n    Length of generator state.\n","random.array.geometric.byteLength":"\nrandom.array.geometric.byteLength\n    Size (in bytes) of generator state.\n","random.array.gumbel":"\nrandom.array.gumbel( len:integer, mu:number, beta:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a Gumbel\n    distribution.\n","random.array.gumbel.assign":"\nrandom.array.gumbel.assign( mu:number, beta:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a Gumbel distribution.\n","random.array.gumbel.factory":"\nrandom.array.gumbel.factory( [mu:number, beta:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Gumbel distribution.\n","random.array.gumbel.PRNG":"\nrandom.array.gumbel.PRNG\n    Underlying pseudorandom number generator.\n","random.array.gumbel.seed":"\nrandom.array.gumbel.seed\n    Pseudorandom number generator seed.\n","random.array.gumbel.seedLength":"\nrandom.array.gumbel.seedLength\n    Length of generator seed.\n","random.array.gumbel.state":"\nrandom.array.gumbel.state\n    Generator state.\n","random.array.gumbel.stateLength":"\nrandom.array.gumbel.stateLength\n    Length of generator state.\n","random.array.gumbel.byteLength":"\nrandom.array.gumbel.byteLength\n    Size (in bytes) of generator state.\n","random.array.hypergeometric":"\nrandom.array.hypergeometric( len:integer, N:number, K:number, n:number[, \n  options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a hypergeometric\n    distribution.\n","random.array.hypergeometric.assign":"\nrandom.array.hypergeometric.assign( N:number, K:number, n:number, \n  out:Array|TypedArray )\n    Fills an array with pseudorandom numbers drawn from a hypergeometric\n    distribution.\n","random.array.hypergeometric.factory":"\nrandom.array.hypergeometric.factory( [N:number, K:number, n:number, ]\n  [options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a hypergeometric distribution.\n","random.array.hypergeometric.PRNG":"\nrandom.array.hypergeometric.PRNG\n    Underlying pseudorandom number generator.\n","random.array.hypergeometric.seed":"\nrandom.array.hypergeometric.seed\n    Pseudorandom number generator seed.\n","random.array.hypergeometric.seedLength":"\nrandom.array.hypergeometric.seedLength\n    Length of generator seed.\n","random.array.hypergeometric.state":"\nrandom.array.hypergeometric.state\n    Generator state.\n","random.array.hypergeometric.stateLength":"\nrandom.array.hypergeometric.stateLength\n    Length of generator state.\n","random.array.hypergeometric.byteLength":"\nrandom.array.hypergeometric.byteLength\n    Size (in bytes) of generator state.\n","random.array.invgamma":"\nrandom.array.invgamma( len:integer, alpha:number, beta:number[, \n  options:Object] )\n    Returns an array containing pseudorandom numbers drawn from an inverse gamma\n    distribution.\n","random.array.invgamma.assign":"\nrandom.array.invgamma.assign( alpha:number, beta:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from an inverse gamma\n    distribution.\n","random.array.invgamma.factory":"\nrandom.array.invgamma.factory( [alpha:number, beta:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an inverse gamma distribution.\n","random.array.invgamma.PRNG":"\nrandom.array.invgamma.PRNG\n    Underlying pseudorandom number generator.\n","random.array.invgamma.seed":"\nrandom.array.invgamma.seed\n    Pseudorandom number generator seed.\n","random.array.invgamma.seedLength":"\nrandom.array.invgamma.seedLength\n    Length of generator seed.\n","random.array.invgamma.state":"\nrandom.array.invgamma.state\n    Generator state.\n","random.array.invgamma.stateLength":"\nrandom.array.invgamma.stateLength\n    Length of generator state.\n","random.array.invgamma.byteLength":"\nrandom.array.invgamma.byteLength\n    Size (in bytes) of generator state.\n","random.array.kumaraswamy":"\nrandom.array.kumaraswamy( len:integer, a:number, b:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from Kumaraswamy's\n    double bounded distribution.\n","random.array.kumaraswamy.assign":"\nrandom.array.kumaraswamy.assign( a:number, b:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from Kumaraswamy's double\n    bounded distribution.\n","random.array.kumaraswamy.factory":"\nrandom.array.kumaraswamy.factory( [a:number, b:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from Kumaraswamy's double bounded distribution.\n","random.array.kumaraswamy.PRNG":"\nrandom.array.kumaraswamy.PRNG\n    Underlying pseudorandom number generator.\n","random.array.kumaraswamy.seed":"\nrandom.array.kumaraswamy.seed\n    Pseudorandom number generator seed.\n","random.array.kumaraswamy.seedLength":"\nrandom.array.kumaraswamy.seedLength\n    Length of generator seed.\n","random.array.kumaraswamy.state":"\nrandom.array.kumaraswamy.state\n    Generator state.\n","random.array.kumaraswamy.stateLength":"\nrandom.array.kumaraswamy.stateLength\n    Length of generator state.\n","random.array.kumaraswamy.byteLength":"\nrandom.array.kumaraswamy.byteLength\n    Size (in bytes) of generator state.\n","random.array.laplace":"\nrandom.array.laplace( len:integer, mu:number, b:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a Laplace\n    (double exponential) distribution.\n","random.array.laplace.assign":"\nrandom.array.laplace.assign( mu:number, b:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a Laplace (double\n    exponential) distribution.\n","random.array.laplace.factory":"\nrandom.array.laplace.factory( [mu:number, b:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Laplace (double exponential) distribution.\n","random.array.laplace.PRNG":"\nrandom.array.laplace.PRNG\n    Underlying pseudorandom number generator.\n","random.array.laplace.seed":"\nrandom.array.laplace.seed\n    Pseudorandom number generator seed.\n","random.array.laplace.seedLength":"\nrandom.array.laplace.seedLength\n    Length of generator seed.\n","random.array.laplace.state":"\nrandom.array.laplace.state\n    Generator state.\n","random.array.laplace.stateLength":"\nrandom.array.laplace.stateLength\n    Length of generator state.\n","random.array.laplace.byteLength":"\nrandom.array.laplace.byteLength\n    Size (in bytes) of generator state.\n","random.array.levy":"\nrandom.array.levy( len:integer, mu:number, c:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a Lévy\n    distribution.\n","random.array.levy.assign":"\nrandom.array.levy.assign( mu:number, c:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a Lévy distribution.\n","random.array.levy.factory":"\nrandom.array.levy.factory( [mu:number, c:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Lévy distribution.\n","random.array.levy.PRNG":"\nrandom.array.levy.PRNG\n    Underlying pseudorandom number generator.\n","random.array.levy.seed":"\nrandom.array.levy.seed\n    Pseudorandom number generator seed.\n","random.array.levy.seedLength":"\nrandom.array.levy.seedLength\n    Length of generator seed.\n","random.array.levy.state":"\nrandom.array.levy.state\n    Generator state.\n","random.array.levy.stateLength":"\nrandom.array.levy.stateLength\n    Length of generator state.\n","random.array.levy.byteLength":"\nrandom.array.levy.byteLength\n    Size (in bytes) of generator state.\n","random.array.logistic":"\nrandom.array.logistic( len:integer, mu:number, s:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a logistic\n    distribution.\n","random.array.logistic.assign":"\nrandom.array.logistic.assign( mu:number, s:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a logistic distribution.\n","random.array.logistic.factory":"\nrandom.array.logistic.factory( [mu:number, s:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a logistic distribution.\n","random.array.logistic.PRNG":"\nrandom.array.logistic.PRNG\n    Underlying pseudorandom number generator.\n","random.array.logistic.seed":"\nrandom.array.logistic.seed\n    Pseudorandom number generator seed.\n","random.array.logistic.seedLength":"\nrandom.array.logistic.seedLength\n    Length of generator seed.\n","random.array.logistic.state":"\nrandom.array.logistic.state\n    Generator state.\n","random.array.logistic.stateLength":"\nrandom.array.logistic.stateLength\n    Length of generator state.\n","random.array.logistic.byteLength":"\nrandom.array.logistic.byteLength\n    Size (in bytes) of generator state.\n","random.array.lognormal":"\nrandom.array.lognormal( len:integer, mu:number, sigma:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a lognormal\n    distribution.\n","random.array.lognormal.assign":"\nrandom.array.lognormal.assign( mu:number, sigma:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a lognormal\n    distribution.\n","random.array.lognormal.factory":"\nrandom.array.lognormal.factory( [mu:number, sigma:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a lognormal distribution.\n","random.array.lognormal.PRNG":"\nrandom.array.lognormal.PRNG\n    Underlying pseudorandom number generator.\n","random.array.lognormal.seed":"\nrandom.array.lognormal.seed\n    Pseudorandom number generator seed.\n","random.array.lognormal.seedLength":"\nrandom.array.lognormal.seedLength\n    Length of generator seed.\n","random.array.lognormal.state":"\nrandom.array.lognormal.state\n    Generator state.\n","random.array.lognormal.stateLength":"\nrandom.array.lognormal.stateLength\n    Length of generator state.\n","random.array.lognormal.byteLength":"\nrandom.array.lognormal.byteLength\n    Size (in bytes) of generator state.\n","random.array.minstd":"\nrandom.array.minstd( len:integer[, options:Object] )\n    Returns an array containing pseudorandom integers on the interval\n    `[1, 2147483646]`.\n","random.array.minstd.normalized":"\nrandom.array.minstd.normalized( len:integer[, options:Object] )\n    Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n","random.array.minstd.factory":"\nrandom.array.minstd.factory( [options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers\n    generated using a linear congruential pseudorandom number generator (LCG).\n","random.array.minstd.PRNG":"\nrandom.array.minstd.PRNG\n    Underlying pseudorandom number generator.\n","random.array.minstd.seed":"\nrandom.array.minstd.seed\n    Pseudorandom number generator seed.\n","random.array.minstd.seedLength":"\nrandom.array.minstd.seedLength\n    Length of generator seed.\n","random.array.minstd.state":"\nrandom.array.minstd.state\n    Generator state.\n","random.array.minstd.stateLength":"\nrandom.array.minstd.stateLength\n    Length of generator state.\n","random.array.minstd.byteLength":"\nrandom.array.minstd.byteLength\n    Size (in bytes) of generator state.\n","random.array.minstdShuffle":"\nrandom.array.minstdShuffle( len:integer[, options:Object] )\n    Returns an array containing pseudorandom integers on the interval\n    `[1, 2147483646]`.\n","random.array.minstdShuffle.normalized":"\nrandom.array.minstdShuffle.normalized( len:integer[, options:Object] )\n    Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n","random.array.minstdShuffle.factory":"\nrandom.array.minstdShuffle.factory( [options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers\n    generated using a linear congruential pseudorandom number generator (LCG)\n    whose output is shuffled.\n","random.array.minstdShuffle.PRNG":"\nrandom.array.minstdShuffle.PRNG\n    Underlying pseudorandom number generator.\n","random.array.minstdShuffle.seed":"\nrandom.array.minstdShuffle.seed\n    Pseudorandom number generator seed.\n","random.array.minstdShuffle.seedLength":"\nrandom.array.minstdShuffle.seedLength\n    Length of generator seed.\n","random.array.minstdShuffle.state":"\nrandom.array.minstdShuffle.state\n    Generator state.\n","random.array.minstdShuffle.stateLength":"\nrandom.array.minstdShuffle.stateLength\n    Length of generator state.\n","random.array.minstdShuffle.byteLength":"\nrandom.array.minstdShuffle.byteLength\n    Size (in bytes) of generator state.\n","random.array.mt19937":"\nrandom.array.mt19937( len:integer[, options:Object] )\n    Returns an array containing pseudorandom integers on the interval\n    `[0, 4294967295]`.\n","random.array.mt19937.normalized":"\nrandom.array.mt19937.normalized( len:integer[, options:Object] )\n    Returns an array containing pseudorandom numbers on the interval `[0, 1)`\n    with 53-bit precision.\n","random.array.mt19937.factory":"\nrandom.array.mt19937.factory( [options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers\n    generated using a 32-bit Mersenne Twister pseudorandom number generator.\n","random.array.mt19937.PRNG":"\nrandom.array.mt19937.PRNG\n    Underlying pseudorandom number generator.\n","random.array.mt19937.seed":"\nrandom.array.mt19937.seed\n    Pseudorandom number generator seed.\n","random.array.mt19937.seedLength":"\nrandom.array.mt19937.seedLength\n    Length of generator seed.\n","random.array.mt19937.state":"\nrandom.array.mt19937.state\n    Generator state.\n","random.array.mt19937.stateLength":"\nrandom.array.mt19937.stateLength\n    Length of generator state.\n","random.array.mt19937.byteLength":"\nrandom.array.mt19937.byteLength\n    Size (in bytes) of generator state.\n","random.array.negativeBinomial":"\nrandom.array.negativeBinomial( len:integer, r:number, p:number[, \n  options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a negative\n    binomial distribution.\n","random.array.negativeBinomial.assign":"\nrandom.array.negativeBinomial.assign( r:number, p:number, out:Array|TypedArray )\n    Fills an array with pseudorandom numbers drawn from a negative binomial\n    distribution.\n","random.array.negativeBinomial.factory":"\nrandom.array.negativeBinomial.factory( [r:number, p:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a negative binomial distribution.\n","random.array.negativeBinomial.PRNG":"\nrandom.array.negativeBinomial.PRNG\n    Underlying pseudorandom number generator.\n","random.array.negativeBinomial.seed":"\nrandom.array.negativeBinomial.seed\n    Pseudorandom number generator seed.\n","random.array.negativeBinomial.seedLength":"\nrandom.array.negativeBinomial.seedLength\n    Length of generator seed.\n","random.array.negativeBinomial.state":"\nrandom.array.negativeBinomial.state\n    Generator state.\n","random.array.negativeBinomial.stateLength":"\nrandom.array.negativeBinomial.stateLength\n    Length of generator state.\n","random.array.negativeBinomial.byteLength":"\nrandom.array.negativeBinomial.byteLength\n    Size (in bytes) of generator state.\n","random.array.normal":"\nrandom.array.normal( len:integer, mu:number, sigma:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a normal\n    distribution.\n","random.array.normal.assign":"\nrandom.array.normal.assign( mu:number, sigma:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a normal distribution.\n","random.array.normal.factory":"\nrandom.array.normal.factory( [mu:number, sigma:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a normal distribution.\n","random.array.normal.PRNG":"\nrandom.array.normal.PRNG\n    Underlying pseudorandom number generator.\n","random.array.normal.seed":"\nrandom.array.normal.seed\n    Pseudorandom number generator seed.\n","random.array.normal.seedLength":"\nrandom.array.normal.seedLength\n    Length of generator seed.\n","random.array.normal.state":"\nrandom.array.normal.state\n    Generator state.\n","random.array.normal.stateLength":"\nrandom.array.normal.stateLength\n    Length of generator state.\n","random.array.normal.byteLength":"\nrandom.array.normal.byteLength\n    Size (in bytes) of generator state.\n","random.array.pareto1":"\nrandom.array.pareto1( len:integer, alpha:number, beta:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a Pareto (Type\n    I) distribution.\n","random.array.pareto1.assign":"\nrandom.array.pareto1.assign( alpha:number, beta:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a Pareto (Type I)\n    distribution.\n","random.array.pareto1.factory":"\nrandom.array.pareto1.factory( [alpha:number, beta:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Pareto (Type I) distribution.\n","random.array.pareto1.PRNG":"\nrandom.array.pareto1.PRNG\n    Underlying pseudorandom number generator.\n","random.array.pareto1.seed":"\nrandom.array.pareto1.seed\n    Pseudorandom number generator seed.\n","random.array.pareto1.seedLength":"\nrandom.array.pareto1.seedLength\n    Length of generator seed.\n","random.array.pareto1.state":"\nrandom.array.pareto1.state\n    Generator state.\n","random.array.pareto1.stateLength":"\nrandom.array.pareto1.stateLength\n    Length of generator state.\n","random.array.pareto1.byteLength":"\nrandom.array.pareto1.byteLength\n    Size (in bytes) of generator state.\n","random.array.poisson":"\nrandom.array.poisson( len:integer, lambda:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a Poisson\n    distribution.\n","random.array.poisson.assign":"\nrandom.array.poisson.assign( lambda:number, out:Array|TypedArray )\n    Fills an array with pseudorandom numbers drawn from a Poisson distribution.\n","random.array.poisson.factory":"\nrandom.array.poisson.factory( [lambda:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Poisson distribution.\n","random.array.poisson.PRNG":"\nrandom.array.poisson.PRNG\n    Underlying pseudorandom number generator.\n","random.array.poisson.seed":"\nrandom.array.poisson.seed\n    Pseudorandom number generator seed.\n","random.array.poisson.seedLength":"\nrandom.array.poisson.seedLength\n    Length of generator seed.\n","random.array.poisson.state":"\nrandom.array.poisson.state\n    Generator state.\n","random.array.poisson.stateLength":"\nrandom.array.poisson.stateLength\n    Length of generator state.\n","random.array.poisson.byteLength":"\nrandom.array.poisson.byteLength\n    Size (in bytes) of generator state.\n","random.array.randu":"\nrandom.array.randu( len:integer[, options:Object] )\n    Returns an array containing uniformly distributed pseudorandom numbers\n    between 0 and 1.\n","random.array.randu.factory":"\nrandom.array.randu.factory( [options:Object] )\n    Returns a function for creating arrays containing uniformly distributed\n    pseudorandom numbers between 0 and 1.\n","random.array.randu.PRNG":"\nrandom.array.randu.PRNG\n    Underlying pseudorandom number generator.\n","random.array.randu.seed":"\nrandom.array.randu.seed\n    Pseudorandom number generator seed.\n","random.array.randu.seedLength":"\nrandom.array.randu.seedLength\n    Length of generator seed.\n","random.array.randu.state":"\nrandom.array.randu.state\n    Generator state.\n","random.array.randu.stateLength":"\nrandom.array.randu.stateLength\n    Length of generator state.\n","random.array.randu.byteLength":"\nrandom.array.randu.byteLength\n    Size (in bytes) of generator state.\n","random.array.rayleigh":"\nrandom.array.rayleigh( len:integer, sigma:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a Rayleigh\n    distribution.\n","random.array.rayleigh.assign":"\nrandom.array.rayleigh.assign( sigma:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a Rayleigh distribution.\n","random.array.rayleigh.factory":"\nrandom.array.rayleigh.factory( [sigma:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Rayleigh distribution.\n","random.array.rayleigh.PRNG":"\nrandom.array.rayleigh.PRNG\n    Underlying pseudorandom number generator.\n","random.array.rayleigh.seed":"\nrandom.array.rayleigh.seed\n    Pseudorandom number generator seed.\n","random.array.rayleigh.seedLength":"\nrandom.array.rayleigh.seedLength\n    Length of generator seed.\n","random.array.rayleigh.state":"\nrandom.array.rayleigh.state\n    Generator state.\n","random.array.rayleigh.stateLength":"\nrandom.array.rayleigh.stateLength\n    Length of generator state.\n","random.array.rayleigh.byteLength":"\nrandom.array.rayleigh.byteLength\n    Size (in bytes) of generator state.\n","random.array.t":"\nrandom.array.t( len:integer, v:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a Student's t\n    distribution.\n","random.array.t.assign":"\nrandom.array.t.assign( v:number, out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a Student's t\n    distribution.\n","random.array.t.factory":"\nrandom.array.t.factory( [v:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Student's t distribution.\n","random.array.t.PRNG":"\nrandom.array.t.PRNG\n    Underlying pseudorandom number generator.\n","random.array.t.seed":"\nrandom.array.t.seed\n    Pseudorandom number generator seed.\n","random.array.t.seedLength":"\nrandom.array.t.seedLength\n    Length of generator seed.\n","random.array.t.state":"\nrandom.array.t.state\n    Generator state.\n","random.array.t.stateLength":"\nrandom.array.t.stateLength\n    Length of generator state.\n","random.array.t.byteLength":"\nrandom.array.t.byteLength\n    Size (in bytes) of generator state.\n","random.array.triangular":"\nrandom.array.triangular( len:integer, a:number, b:number, c:number[, \n  options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a triangular\n    distribution.\n","random.array.triangular.assign":"\nrandom.array.triangular.assign( a:number, b:number, c:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a triangular\n    distribution.\n","random.array.triangular.factory":"\nrandom.array.triangular.factory( [a:number, b:number, c:number, ]\n  [options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a triangular distribution.\n","random.array.triangular.PRNG":"\nrandom.array.triangular.PRNG\n    Underlying pseudorandom number generator.\n","random.array.triangular.seed":"\nrandom.array.triangular.seed\n    Pseudorandom number generator seed.\n","random.array.triangular.seedLength":"\nrandom.array.triangular.seedLength\n    Length of generator seed.\n","random.array.triangular.state":"\nrandom.array.triangular.state\n    Generator state.\n","random.array.triangular.stateLength":"\nrandom.array.triangular.stateLength\n    Length of generator state.\n","random.array.triangular.byteLength":"\nrandom.array.triangular.byteLength\n    Size (in bytes) of generator state.\n","random.array.uniform":"\nrandom.array.uniform( len:integer, a:number, b:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a continuous\n    uniform distribution.\n","random.array.uniform.assign":"\nrandom.array.uniform.assign( a:number, b:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a continuous uniform\n    distribution.\n","random.array.uniform.factory":"\nrandom.array.uniform.factory( [a:number, b:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a continuous uniform distribution.\n","random.array.uniform.PRNG":"\nrandom.array.uniform.PRNG\n    Underlying pseudorandom number generator.\n","random.array.uniform.seed":"\nrandom.array.uniform.seed\n    Pseudorandom number generator seed.\n","random.array.uniform.seedLength":"\nrandom.array.uniform.seedLength\n    Length of generator seed.\n","random.array.uniform.state":"\nrandom.array.uniform.state\n    Generator state.\n","random.array.uniform.stateLength":"\nrandom.array.uniform.stateLength\n    Length of generator state.\n","random.array.uniform.byteLength":"\nrandom.array.uniform.byteLength\n    Size (in bytes) of generator state.\n","random.array.weibull":"\nrandom.array.weibull( len:integer, k:number, lambda:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a Weibull\n    distribution.\n","random.array.weibull.assign":"\nrandom.array.weibull.assign( k:number, lambda:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a Weibull distribution.\n","random.array.weibull.factory":"\nrandom.array.weibull.factory( [k:number, lambda:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Weibull distribution.\n","random.array.weibull.PRNG":"\nrandom.array.weibull.PRNG\n    Underlying pseudorandom number generator.\n","random.array.weibull.seed":"\nrandom.array.weibull.seed\n    Pseudorandom number generator seed.\n","random.array.weibull.seedLength":"\nrandom.array.weibull.seedLength\n    Length of generator seed.\n","random.array.weibull.state":"\nrandom.array.weibull.state\n    Generator state.\n","random.array.weibull.stateLength":"\nrandom.array.weibull.stateLength\n    Length of generator state.\n","random.array.weibull.byteLength":"\nrandom.array.weibull.byteLength\n    Size (in bytes) of generator state.\n","random.iterators.arcsine":"\nrandom.iterators.arcsine( a:number, b:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from an\n    arcsine distribution.\n","random.iterators.bernoulli":"\nrandom.iterators.bernoulli( p:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Bernoulli distribution.\n","random.iterators.beta":"\nrandom.iterators.beta( α:number, β:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    beta distribution.\n","random.iterators.betaprime":"\nrandom.iterators.betaprime( α:number, β:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    beta prime distribution.\n","random.iterators.binomial":"\nrandom.iterators.binomial( n:integer, p:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    binomial distribution.\n","random.iterators.boxMuller":"\nrandom.iterators.boxMuller( [options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    standard normal distribution using the Box-Muller transform.\n","random.iterators.cauchy":"\nrandom.iterators.cauchy( x0:number, Ɣ:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Cauchy distribution.\n","random.iterators.chi":"\nrandom.iterators.chi( k:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a chi\n    distribution.\n","random.iterators.chisquare":"\nrandom.iterators.chisquare( k:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    chi-square distribution.\n","random.iterators.cosine":"\nrandom.iterators.cosine( μ:number, s:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a raised\n    cosine distribution.\n","random.iterators.discreteUniform":"\nrandom.iterators.discreteUniform( a:integer, b:integer[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    discrete uniform distribution.\n","random.iterators.erlang":"\nrandom.iterators.erlang( k:integer, λ:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from an Erlang\n    distribution.\n","random.iterators.exponential":"\nrandom.iterators.exponential( λ:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from an\n    exponential distribution.\n","random.iterators.f":"\nrandom.iterators.f( d1:number, d2:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from an F\n    distribution.\n","random.iterators.frechet":"\nrandom.iterators.frechet( α:number, s:number, m:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Fréchet\n    distribution.\n","random.iterators.gamma":"\nrandom.iterators.gamma( α:number, β:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a gamma\n    distribution.\n","random.iterators.geometric":"\nrandom.iterators.geometric( p:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    geometric distribution.\n","random.iterators.gumbel":"\nrandom.iterators.gumbel( μ:number, β:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Gumbel\n    distribution.\n","random.iterators.hypergeometric":"\nrandom.iterators.hypergeometric( N:integer, K:integer, n:integer[, \n  options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    hypergeometric distribution.\n","random.iterators.improvedZiggurat":"\nrandom.iterators.improvedZiggurat( [options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    standard normal distribution using the Improved Ziggurat algorithm.\n","random.iterators.invgamma":"\nrandom.iterators.invgamma( α:number, β:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from an\n    inverse gamma distribution.\n","random.iterators.kumaraswamy":"\nrandom.iterators.kumaraswamy( a:number, b:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Kumaraswamy's double bounded distribution.\n","random.iterators.laplace":"\nrandom.iterators.laplace( μ:number, b:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Laplace\n    (double exponential) distribution.\n","random.iterators.levy":"\nrandom.iterators.levy( μ:number, c:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Lévy\n    distribution.\n","random.iterators.logistic":"\nrandom.iterators.logistic( μ:number, s:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    logistic distribution.\n","random.iterators.lognormal":"\nrandom.iterators.lognormal( μ:number, σ:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    lognormal distribution.\n","random.iterators.minstd":"\nrandom.iterators.minstd( [options:Object] )\n    Returns an iterator for generating pseudorandom integers on the interval\n    `[1, 2147483646]`.\n","random.iterators.minstdShuffle":"\nrandom.iterators.minstdShuffle( [options:Object] )\n    Returns an iterator for generating pseudorandom integers on the interval\n    `[1, 2147483646]`.\n","random.iterators.mt19937":"\nrandom.iterators.mt19937( [options:Object] )\n    Returns an iterator for generating pseudorandom integers on the interval\n    `[1, 4294967295]`.\n","random.iterators.negativeBinomial":"\nrandom.iterators.negativeBinomial( r:number, p:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    negative binomial distribution.\n","random.iterators.normal":"\nrandom.iterators.normal( μ:number, σ:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a normal\n    distribution.\n","random.iterators.pareto1":"\nrandom.iterators.pareto1( α:number, β:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Pareto\n    (Type I) distribution.\n","random.iterators.poisson":"\nrandom.iterators.poisson( λ:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Poisson\n    distribution.\n","random.iterators.randi":"\nrandom.iterators.randi( [options:Object] )\n    Create an iterator for generating pseudorandom numbers having integer\n    values.\n","random.iterators.randn":"\nrandom.iterators.randn( [options:Object] )\n    Create an iterator for generating pseudorandom numbers drawn from a standard\n    normal distribution.\n","random.iterators.randu":"\nrandom.iterators.randu( [options:Object] )\n    Create an iterator for generating uniformly distributed pseudorandom numbers\n    between 0 and 1.\n","random.iterators.rayleigh":"\nrandom.iterators.rayleigh( σ:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Rayleigh distribution.\n","random.iterators.t":"\nrandom.iterators.t( v:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Student's t distribution.\n","random.iterators.triangular":"\nrandom.iterators.triangular( a:number, b:number, c:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    triangular distribution.\n","random.iterators.uniform":"\nrandom.iterators.uniform( a:number, b:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    continuous uniform distribution.\n","random.iterators.weibull":"\nrandom.iterators.weibull( k:number, λ:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Weibull distribution.\n","random.streams.arcsine":"\nrandom.streams.arcsine( a:number, b:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from an\n    arcsine distribution.\n","random.streams.arcsine.factory":"\nrandom.streams.arcsine.factory( [a:number, b:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an arcsine distribution.\n","random.streams.arcsine.objectMode":"\nrandom.streams.arcsine.objectMode( a:number, b:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an arcsine distribution.\n","random.streams.bernoulli":"\nrandom.streams.bernoulli( p:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Bernoulli distribution.\n","random.streams.bernoulli.factory":"\nrandom.streams.bernoulli.factory( [p:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Bernoulli distribution.\n","random.streams.bernoulli.objectMode":"\nrandom.streams.bernoulli.objectMode( p:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Bernoulli distribution.\n","random.streams.beta":"\nrandom.streams.beta( α:number, β:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    beta distribution.\n","random.streams.beta.factory":"\nrandom.streams.beta.factory( [α:number, β:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a beta distribution.\n","random.streams.beta.objectMode":"\nrandom.streams.beta.objectMode( α:number, β:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a beta distribution.\n","random.streams.betaprime":"\nrandom.streams.betaprime( α:number, β:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    beta prime distribution.\n","random.streams.betaprime.factory":"\nrandom.streams.betaprime.factory( [α:number, β:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a beta prime distribution.\n","random.streams.betaprime.objectMode":"\nrandom.streams.betaprime.objectMode( α:number, β:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a beta prime distribution.\n","random.streams.binomial":"\nrandom.streams.binomial( n:integer, p:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    binomial distribution.\n","random.streams.binomial.factory":"\nrandom.streams.binomial.factory( [n:integer, p:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a binomial distribution.\n","random.streams.binomial.objectMode":"\nrandom.streams.binomial.objectMode( n:integer, p:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a binomial distribution.\n","random.streams.boxMuller":"\nrandom.streams.boxMuller( [options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    standard normal distribution using the Box-Muller transform.\n","random.streams.boxMuller.factory":"\nrandom.streams.boxMuller.factory( [options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a standard normal distribution using the Box-Muller\n    transform.\n","random.streams.boxMuller.objectMode":"\nrandom.streams.boxMuller.objectMode( [options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a standard normal distribution using the Box-Muller transform.\n","random.streams.cauchy":"\nrandom.streams.cauchy( x0:number, γ:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Cauchy distribution.\n","random.streams.cauchy.factory":"\nrandom.streams.cauchy.factory( [x0:number, γ:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Cauchy distribution.\n","random.streams.cauchy.objectMode":"\nrandom.streams.cauchy.objectMode( x0:number, γ:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Cauchy distribution.\n","random.streams.chi":"\nrandom.streams.chi( k:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    chi distribution.\n","random.streams.chi.factory":"\nrandom.streams.chi.factory( [k:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a chi distribution.\n","random.streams.chi.objectMode":"\nrandom.streams.chi.objectMode( k:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a chi distribution.\n","random.streams.chisquare":"\nrandom.streams.chisquare( k:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    chi-square distribution.\n","random.streams.chisquare.factory":"\nrandom.streams.chisquare.factory( [k:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a chi-square distribution.\n","random.streams.chisquare.objectMode":"\nrandom.streams.chisquare.objectMode( k:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a chi-square distribution.\n","random.streams.cosine":"\nrandom.streams.cosine( μ:number, s:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    raised cosine distribution.\n","random.streams.cosine.factory":"\nrandom.streams.cosine.factory( [μ:number, s:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a raised cosine distribution.\n","random.streams.cosine.objectMode":"\nrandom.streams.cosine.objectMode( μ:number, s:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a raised cosine distribution.\n","random.streams.discreteUniform":"\nrandom.streams.discreteUniform( a:integer, b:integer[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    discrete uniform distribution.\n","random.streams.discreteUniform.factory":"\nrandom.streams.discreteUniform.factory( [a:integer, b:integer, ]\n  [options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a discrete uniform distribution.\n","random.streams.discreteUniform.objectMode":"\nrandom.streams.discreteUniform.objectMode( a:integer, b:integer[, \n  options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a discrete uniform distribution.\n","random.streams.erlang":"\nrandom.streams.erlang( k:integer, λ:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from an\n    Erlang distribution.\n","random.streams.erlang.factory":"\nrandom.streams.erlang.factory( [k:number, λ:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an Erlang distribution.\n","random.streams.erlang.objectMode":"\nrandom.streams.erlang.objectMode( k:number, λ:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an Erlang distribution.\n","random.streams.exponential":"\nrandom.streams.exponential( λ:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from an\n    exponential distribution.\n","random.streams.exponential.factory":"\nrandom.streams.exponential.factory( [λ:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an exponential distribution.\n","random.streams.exponential.objectMode":"\nrandom.streams.exponential.objectMode( λ:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an exponential distribution.\n","random.streams.f":"\nrandom.streams.f( d1:number, d2:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from an\n    F distribution.\n","random.streams.f.factory":"\nrandom.streams.f.factory( [d1:number, d2:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an F distribution.\n","random.streams.f.objectMode":"\nrandom.streams.f.objectMode( d1:number, d2:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an F distribution.\n","random.streams.frechet":"\nrandom.streams.frechet( α:number, s:number, m:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Fréchet distribution.\n","random.streams.frechet.factory":"\nrandom.streams.frechet.factory( [α:number, s:number, m:number,]\n  [options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Fréchet distribution.\n","random.streams.frechet.objectMode":"\nrandom.streams.frechet.objectMode( α:number, s:number, m:number[, \n  options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Fréchet distribution.\n","random.streams.gamma":"\nrandom.streams.gamma( α:number, β:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    gamma distribution.\n","random.streams.gamma.factory":"\nrandom.streams.gamma.factory( [α:number, β:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a gamma distribution.\n","random.streams.gamma.objectMode":"\nrandom.streams.gamma.objectMode( α:number, β:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a gamma distribution.\n","random.streams.geometric":"\nrandom.streams.geometric( p:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    geometric distribution.\n","random.streams.geometric.factory":"\nrandom.streams.geometric.factory( [p:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a geometric distribution.\n","random.streams.geometric.objectMode":"\nrandom.streams.geometric.objectMode( p:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a geometric distribution.\n","random.streams.gumbel":"\nrandom.streams.gumbel( μ:number, β:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Gumbel distribution.\n","random.streams.gumbel.factory":"\nrandom.streams.gumbel.factory( [μ:number, β:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Gumbel distribution.\n","random.streams.gumbel.objectMode":"\nrandom.streams.gumbel.objectMode( μ:number, β:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Gumbel distribution.\n","random.streams.hypergeometric":"\nrandom.streams.hypergeometric( N:integer, K:integer, n:integer[, \n  options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    hypergeometric distribution.\n","random.streams.hypergeometric.factory":"\nrandom.streams.hypergeometric.factory( [N:integer, K:integer, n:integer,]\n  [options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a hypergeometric distribution.\n","random.streams.hypergeometric.objectMode":"\nrandom.streams.hypergeometric.objectMode( N:integer, K:integer, n:integer[, \n  options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a hypergeometric distribution.\n","random.streams.improvedZiggurat":"\nrandom.streams.improvedZiggurat( [options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    standard normal distribution using the Improved Ziggurat algorithm.\n","random.streams.improvedZiggurat.factory":"\nrandom.streams.improvedZiggurat.factory( [options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a standard normal distribution using the Improved\n    Ziggurat algorithm.\n","random.streams.improvedZiggurat.objectMode":"\nrandom.streams.improvedZiggurat.objectMode( [options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a standard normal distribution using the Improved Ziggurat\n    algorithm.\n","random.streams.invgamma":"\nrandom.streams.invgamma( α:number, β:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from an\n    inverse gamma distribution.\n","random.streams.invgamma.factory":"\nrandom.streams.invgamma.factory( [α:number, β:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an inverse gamma distribution.\n","random.streams.invgamma.objectMode":"\nrandom.streams.invgamma.objectMode( α:number, β:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an inverse gamma distribution.\n","random.streams.kumaraswamy":"\nrandom.streams.kumaraswamy( a:number, b:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Kumaraswamy's double bounded distribution.\n","random.streams.kumaraswamy.factory":"\nrandom.streams.kumaraswamy.factory( [a:number, b:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Kumaraswamy's double bounded distribution.\n","random.streams.kumaraswamy.objectMode":"\nrandom.streams.kumaraswamy.objectMode( a:number, b:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Kumaraswamy's double bounded distribution.\n","random.streams.laplace":"\nrandom.streams.laplace( μ:number, b:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Laplace (double exponential) distribution.\n","random.streams.laplace.factory":"\nrandom.streams.laplace.factory( [μ:number, b:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Laplace (double exponential) distribution.\n","random.streams.laplace.objectMode":"\nrandom.streams.laplace.objectMode( μ:number, b:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Laplace (double exponential) distribution.\n","random.streams.levy":"\nrandom.streams.levy( μ:number, c:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Lévy distribution.\n","random.streams.levy.factory":"\nrandom.streams.levy.factory( [μ:number, c:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Lévy distribution.\n","random.streams.levy.objectMode":"\nrandom.streams.levy.objectMode( μ:number, c:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Lévy distribution.\n","random.streams.logistic":"\nrandom.streams.logistic( μ:number, s:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    logistic distribution.\n","random.streams.logistic.factory":"\nrandom.streams.logistic.factory( [μ:number, s:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a logistic distribution.\n","random.streams.logistic.objectMode":"\nrandom.streams.logistic.objectMode( μ:number, s:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a logistic distribution.\n","random.streams.lognormal":"\nrandom.streams.lognormal( μ:number, σ:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    lognormal distribution.\n","random.streams.lognormal.factory":"\nrandom.streams.lognormal.factory( [μ:number, σ:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a lognormal distribution.\n","random.streams.lognormal.objectMode":"\nrandom.streams.lognormal.objectMode( μ:number, σ:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a lognormal distribution.\n","random.streams.minstd":"\nrandom.streams.minstd( [options:Object] )\n    Returns a readable stream for generating pseudorandom numbers on the\n    interval `[1, 2147483646]`.\n","random.streams.minstd.factory":"\nrandom.streams.minstd.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers on the interval `[1, 2147483646]`.\n","random.streams.minstd.objectMode":"\nrandom.streams.minstd.objectMode( [options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    on the interval `[1, 2147483646]`.\n","random.streams.minstdShuffle":"\nrandom.streams.minstdShuffle( [options:Object] )\n    Returns a readable stream for generating pseudorandom numbers on the\n    interval `[1, 2147483646]`.\n","random.streams.minstdShuffle.factory":"\nrandom.streams.minstdShuffle.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers on the interval `[1, 2147483646]`.\n","random.streams.minstdShuffle.objectMode":"\nrandom.streams.minstdShuffle.objectMode( [options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    on the interval `[1, 2147483646]`.\n","random.streams.mt19937":"\nrandom.streams.mt19937( [options:Object] )\n    Returns a readable stream for generating pseudorandom numbers on the\n    interval `[1, 4294967295]`.\n","random.streams.mt19937.factory":"\nrandom.streams.mt19937.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers on the interval `[1, 4294967295]`.\n","random.streams.mt19937.objectMode":"\nrandom.streams.mt19937.objectMode( [options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    on the interval `[1, 4294967295]`.\n","random.streams.negativeBinomial":"\nrandom.streams.negativeBinomial( r:number, p:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    negative binomial distribution.\n","random.streams.negativeBinomial.factory":"\nrandom.streams.negativeBinomial.factory( [r:number, p:number, ]\n  [options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a negative binomial distribution.\n","random.streams.negativeBinomial.objectMode":"\nrandom.streams.negativeBinomial.objectMode( r:integer, p:number[, \n  options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a negative binomial distribution.\n","random.streams.normal":"\nrandom.streams.normal( μ:number, σ:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    normal distribution.\n","random.streams.normal.factory":"\nrandom.streams.normal.factory( [μ:number, σ:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a normal distribution.\n","random.streams.normal.objectMode":"\nrandom.streams.normal.objectMode( μ:number, σ:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a normal distribution.\n","random.streams.pareto1":"\nrandom.streams.pareto1( α:number, β:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Pareto (Type I) distribution.\n","random.streams.pareto1.factory":"\nrandom.streams.pareto1.factory( [α:number, β:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Pareto (Type I) distribution.\n","random.streams.pareto1.objectMode":"\nrandom.streams.pareto1.objectMode( α:number, β:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Pareto (Type I) distribution.\n","random.streams.poisson":"\nrandom.streams.poisson( λ:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Poisson distribution.\n","random.streams.poisson.factory":"\nrandom.streams.poisson.factory( [λ:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Poisson distribution.\n","random.streams.poisson.objectMode":"\nrandom.streams.poisson.objectMode( λ:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Poisson distribution.\n","random.streams.randi":"\nrandom.streams.randi( [options:Object] )\n    Returns a readable stream for generating pseudorandom numbers having integer\n    values.\n","random.streams.randi.factory":"\nrandom.streams.randi.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers having integer values.\n","random.streams.randi.objectMode":"\nrandom.streams.randi.objectMode( [options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    having integer values.\n","random.streams.randn":"\nrandom.streams.randn( [options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    standard normal distribution.\n","random.streams.randn.factory":"\nrandom.streams.randn.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a standard normal distribution.\n","random.streams.randn.objectMode":"\nrandom.streams.randn.objectMode( [options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a standard normal distribution.\n","random.streams.randu":"\nrandom.streams.randu( [options:Object] )\n    Returns a readable stream for generating uniformly distributed pseudorandom\n    numbers between 0 and 1.\n","random.streams.randu.factory":"\nrandom.streams.randu.factory( [options] )\n    Returns a function for creating readable streams which generate uniformly\n    distributed pseudorandom numbers between 0 and 1.\n","random.streams.randu.objectMode":"\nrandom.streams.randu.objectMode( [options:Object] )\n    Returns an \"objectMode\" readable stream for generating uniformly distributed\n    pseudorandom numbers between 0 and 1.\n","random.streams.rayleigh":"\nrandom.streams.rayleigh( σ:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Rayleigh distribution.\n","random.streams.rayleigh.factory":"\nrandom.streams.rayleigh.factory( [σ:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Rayleigh distribution.\n","random.streams.rayleigh.objectMode":"\nrandom.streams.rayleigh.objectMode( σ:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Rayleigh distribution.\n","random.streams.t":"\nrandom.streams.t( v:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Student's t distribution.\n","random.streams.t.factory":"\nrandom.streams.t.factory( [v:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Student's t distribution.\n","random.streams.t.objectMode":"\nrandom.streams.t.objectMode( v:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Student's t distribution.\n","random.streams.triangular":"\nrandom.streams.triangular( a:number, b:number, c:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    triangular distribution.\n","random.streams.triangular.factory":"\nrandom.streams.triangular.factory( [a:number, b:number, c:number, ]\n  [options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a triangular distribution.\n","random.streams.triangular.objectMode":"\nrandom.streams.triangular.objectMode( a:number, b:number, c:number[, \n  options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a triangular distribution.\n","random.streams.uniform":"\nrandom.streams.uniform( a:number, b:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    uniform distribution.\n","random.streams.uniform.factory":"\nrandom.streams.uniform.factory( [a:number, b:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a uniform distribution.\n","random.streams.uniform.objectMode":"\nrandom.streams.uniform.objectMode( a:number, b:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a uniform distribution.\n","random.streams.weibull":"\nrandom.streams.weibull( k:number, λ:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Weibull distribution.\n","random.streams.weibull.factory":"\nrandom.streams.weibull.factory( [k:number, λ:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Weibull distribution.\n","random.streams.weibull.objectMode":"\nrandom.streams.weibull.objectMode( k:number, λ:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Weibull distribution.\n","random.strided.arcsine":"\nrandom.strided.arcsine( N:integer, a:ArrayLikeObject, sa:integer, \n  b:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from an arcsine\n    distribution.\n","random.strided.arcsine.ndarray":"\nrandom.strided.arcsine.ndarray( N:integer, a:ArrayLikeObject, sa:integer, \n  oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, \n  so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from an arcsine\n    distribution using alternative indexing semantics.\n","random.strided.bernoulli":"\nrandom.strided.bernoulli( N:integer, p:ArrayLikeObject, sp:integer, \n  out:ArrayLikeObject, so:integer )\n    Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n    distribution.\n","random.strided.bernoulli.ndarray":"\nrandom.strided.bernoulli.ndarray( N:integer, p:ArrayLikeObject, sp:integer, \n  op:integer, out:ArrayLikeObject, so:integer, oo:integer )\n    Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n    distribution using alternative indexing semantics.\n","random.strided.bernoulli.factory":"\nrandom.strided.bernoulli.factory( [options:Object] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Bernoulli distribution.\n","random.strided.bernoulli.PRNG":"\nrandom.strided.bernoulli.PRNG\n    Underlying pseudorandom number generator.\n","random.strided.bernoulli.seed":"\nrandom.strided.bernoulli.seed\n    Pseudorandom number generator seed.\n","random.strided.bernoulli.seedLength":"\nrandom.strided.bernoulli.seedLength\n    Length of generator seed.\n","random.strided.bernoulli.state":"\nrandom.strided.bernoulli.state\n    Generator state.\n","random.strided.bernoulli.stateLength":"\nrandom.strided.bernoulli.stateLength\n    Length of generator state.\n","random.strided.bernoulli.byteLength":"\nrandom.strided.bernoulli.byteLength\n    Size (in bytes) of generator state.\n","random.strided.beta":"\nrandom.strided.beta( N:integer, alpha:ArrayLikeObject, sa:integer, \n  beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a beta\n    distribution.\n","random.strided.beta.ndarray":"\nrandom.strided.beta.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n  oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n  out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a beta\n    distribution using alternative indexing semantics.\n","random.strided.betaprime":"\nrandom.strided.betaprime( N:integer, alpha:ArrayLikeObject, sa:integer, \n  beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a beta prime\n    distribution.\n","random.strided.betaprime.ndarray":"\nrandom.strided.betaprime.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n  oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n  out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a beta prime\n    distribution using alternative indexing semantics.\n","random.strided.chi":"\nrandom.strided.chi( N:integer, k:ArrayLikeObject, sk:integer, \n  out:ArrayLikeObject, so:integer )\n    Fills a strided array with pseudorandom numbers drawn from a chi\n    distribution.\n","random.strided.chi.ndarray":"\nrandom.strided.chi.ndarray( N:integer, k:ArrayLikeObject, sk:integer, \n  ok:integer, out:ArrayLikeObject, so:integer, oo:integer )\n    Fills a strided array with pseudorandom numbers drawn from a chi\n    distribution using alternative indexing semantics.\n","random.strided.chi.factory":"\nrandom.strided.chi.factory( [options:Object] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a chi distribution.\n","random.strided.chi.PRNG":"\nrandom.strided.chi.PRNG\n    Underlying pseudorandom number generator.\n","random.strided.chi.seed":"\nrandom.strided.chi.seed\n    Pseudorandom number generator seed.\n","random.strided.chi.seedLength":"\nrandom.strided.chi.seedLength\n    Length of generator seed.\n","random.strided.chi.state":"\nrandom.strided.chi.state\n    Generator state.\n","random.strided.chi.stateLength":"\nrandom.strided.chi.stateLength\n    Length of generator state.\n","random.strided.chi.byteLength":"\nrandom.strided.chi.byteLength\n    Size (in bytes) of generator state.\n","random.strided.chisquare":"\nrandom.strided.chisquare( N:integer, k:ArrayLikeObject, sk:integer, \n  out:ArrayLikeObject, so:integer )\n    Fills a strided array with pseudorandom numbers drawn from a chi-square\n    distribution.\n","random.strided.chisquare.ndarray":"\nrandom.strided.chisquare.ndarray( N:integer, k:ArrayLikeObject, sk:integer, \n  ok:integer, out:ArrayLikeObject, so:integer, oo:integer )\n    Fills a strided array with pseudorandom numbers drawn from a chi-square\n    distribution using alternative indexing semantics.\n","random.strided.chisquare.factory":"\nrandom.strided.chisquare.factory( [options:Object] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a chi-square distribution.\n","random.strided.chisquare.PRNG":"\nrandom.strided.chisquare.PRNG\n    Underlying pseudorandom number generator.\n","random.strided.chisquare.seed":"\nrandom.strided.chisquare.seed\n    Pseudorandom number generator seed.\n","random.strided.chisquare.seedLength":"\nrandom.strided.chisquare.seedLength\n    Length of generator seed.\n","random.strided.chisquare.state":"\nrandom.strided.chisquare.state\n    Generator state.\n","random.strided.chisquare.stateLength":"\nrandom.strided.chisquare.stateLength\n    Length of generator state.\n","random.strided.chisquare.byteLength":"\nrandom.strided.chisquare.byteLength\n    Size (in bytes) of generator state.\n","random.strided.cosine":"\nrandom.strided.cosine( N:integer, mu:ArrayLikeObject, sm:integer, \n  s:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a cosine\n    distribution.\n","random.strided.cosine.ndarray":"\nrandom.strided.cosine.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, \n  om:integer, s:ArrayLikeObject, ss:integer, os:integer, out:ArrayLikeObject, \n  so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a cosine\n    distribution using alternative indexing semantics.\n","random.strided.discreteUniform":"\nrandom.strided.discreteUniform( N:integer, a:ArrayLikeObject, sa:integer, \n  b:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a discrete\n    uniform distribution.\n","random.strided.discreteUniform.ndarray":"\nrandom.strided.discreteUniform.ndarray( N:integer, a:ArrayLikeObject, \n  sa:integer, oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, \n  out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a discrete\n    uniform distribution using alternative indexing semantics.\n","random.strided.exponential":"\nrandom.strided.exponential( N:integer, lambda:ArrayLikeObject, sl:integer, \n  out:ArrayLikeObject, so:integer )\n    Fills a strided array with pseudorandom numbers drawn from an exponential\n    distribution.\n","random.strided.exponential.ndarray":"\nrandom.strided.exponential.ndarray( N:integer, lambda:ArrayLikeObject, \n  sl:integer, ol:integer, out:ArrayLikeObject, so:integer, oo:integer )\n    Fills a strided array with pseudorandom numbers drawn from an exponential\n    distribution using alternative indexing semantics.\n","random.strided.exponential.factory":"\nrandom.strided.exponential.factory( [options:Object] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from an exponential distribution.\n","random.strided.exponential.PRNG":"\nrandom.strided.exponential.PRNG\n    Underlying pseudorandom number generator.\n","random.strided.exponential.seed":"\nrandom.strided.exponential.seed\n    Pseudorandom number generator seed.\n","random.strided.exponential.seedLength":"\nrandom.strided.exponential.seedLength\n    Length of generator seed.\n","random.strided.exponential.state":"\nrandom.strided.exponential.state\n    Generator state.\n","random.strided.exponential.stateLength":"\nrandom.strided.exponential.stateLength\n    Length of generator state.\n","random.strided.exponential.byteLength":"\nrandom.strided.exponential.byteLength\n    Size (in bytes) of generator state.\n","random.strided.gamma":"\nrandom.strided.gamma( N:integer, alpha:ArrayLikeObject, sa:integer, \n  beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a gamma\n    distribution.\n","random.strided.gamma.ndarray":"\nrandom.strided.gamma.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n  oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n  out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a gamma\n    distribution using alternative indexing semantics.\n","random.strided.geometric":"\nrandom.strided.geometric( N:integer, p:ArrayLikeObject, sp:integer, \n  out:ArrayLikeObject, so:integer )\n    Fills a strided array with pseudorandom numbers drawn from a geometric\n    distribution.\n","random.strided.geometric.ndarray":"\nrandom.strided.geometric.ndarray( N:integer, p:ArrayLikeObject, sp:integer, \n  op:integer, out:ArrayLikeObject, so:integer, oo:integer )\n    Fills a strided array with pseudorandom numbers drawn from a geometric\n    distribution using alternative indexing semantics.\n","random.strided.geometric.factory":"\nrandom.strided.geometric.factory( [options:Object] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a geometric distribution.\n","random.strided.geometric.PRNG":"\nrandom.strided.geometric.PRNG\n    Underlying pseudorandom number generator.\n","random.strided.geometric.seed":"\nrandom.strided.geometric.seed\n    Pseudorandom number generator seed.\n","random.strided.geometric.seedLength":"\nrandom.strided.geometric.seedLength\n    Length of generator seed.\n","random.strided.geometric.state":"\nrandom.strided.geometric.state\n    Generator state.\n","random.strided.geometric.stateLength":"\nrandom.strided.geometric.stateLength\n    Length of generator state.\n","random.strided.geometric.byteLength":"\nrandom.strided.geometric.byteLength\n    Size (in bytes) of generator state.\n","random.strided.invgamma":"\nrandom.strided.invgamma( N:integer, alpha:ArrayLikeObject, sa:integer, \n  beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n    distribution.\n","random.strided.invgamma.ndarray":"\nrandom.strided.invgamma.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n  oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n  out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n    distribution using alternative indexing semantics.\n","random.strided.lognormal":"\nrandom.strided.lognormal( N:integer, mu:ArrayLikeObject, sm:integer, \n  sigma:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a lognormal\n    distribution.\n","random.strided.lognormal.ndarray":"\nrandom.strided.lognormal.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, \n  om:integer, sigma:ArrayLikeObject, ss:integer, os:integer, \n  out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a lognormal\n    distribution using alternative indexing semantics.\n","random.strided.minstd":"\nrandom.strided.minstd( N:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom integers between 1 and 2147483646\n    (inclusive).\n","random.strided.minstd.ndarray":"\nrandom.strided.minstd.ndarray( N:integer, out:ArrayLikeObject, so:integer, \n  oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom integers between 1 and 2147483646\n    (inclusive) using alternative indexing semantics.\n","random.strided.minstd.normalized":"\nrandom.strided.minstd.normalized( N:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers between 0 and 1.\n","random.strided.minstd.normalized.ndarray":"\nrandom.strided.minstd.normalized.ndarray( N:integer, out:ArrayLikeObject, \n  so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers between 0 and 1 using\n    alternative indexing semantics.\n","random.strided.minstdShuffle":"\nrandom.strided.minstdShuffle( N:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom integers between 1 and 2147483646\n    (inclusive).\n","random.strided.minstdShuffle.ndarray":"\nrandom.strided.minstdShuffle.ndarray( N:integer, out:ArrayLikeObject, \n  so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom integers between 1 and 2147483646\n    (inclusive) using alternative indexing semantics.\n","random.strided.minstdShuffle.normalized":"\nrandom.strided.minstdShuffle.normalized( N:integer, out:ArrayLikeObject, \n  so:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers between 0 and 1.\n","random.strided.minstdShuffle.normalized.ndarray":"\nrandom.strided.minstdShuffle.normalized.ndarray( N:integer, \n  out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers between 0 and 1 using\n    alternative indexing semantics.\n","random.strided.mt19937":"\nrandom.strided.mt19937( N:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom integers between 0 and 4294967295\n    (inclusive).\n","random.strided.mt19937.ndarray":"\nrandom.strided.mt19937.ndarray( N:integer, out:ArrayLikeObject, so:integer, \n  oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom integers between 0 and 4294967295\n    (inclusive) using alternative indexing semantics.\n","random.strided.mt19937.normalized":"\nrandom.strided.mt19937.normalized( N:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers between 0 and 1.\n","random.strided.mt19937.normalized.ndarray":"\nrandom.strided.mt19937.normalized.ndarray( N:integer, out:ArrayLikeObject, \n  so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers between 0 and 1 using\n    alternative indexing semantics.\n","random.strided.normal":"\nrandom.strided.normal( N:integer, mu:ArrayLikeObject, sm:integer, \n  sigma:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a normal\n    distribution.\n","random.strided.normal.ndarray":"\nrandom.strided.normal.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, \n  om:integer, sigma:ArrayLikeObject, ss:integer, os:integer, \n  out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a normal\n    distribution using alternative indexing semantics.\n","random.strided.poisson":"\nrandom.strided.poisson( N:integer, lambda:ArrayLikeObject, sl:integer, \n  out:ArrayLikeObject, so:integer )\n    Fills a strided array with pseudorandom numbers drawn from a Poisson\n    distribution.\n","random.strided.poisson.ndarray":"\nrandom.strided.poisson.ndarray( N:integer, lambda:ArrayLikeObject, sl:integer, \n  ol:integer, out:ArrayLikeObject, so:integer, oo:integer )\n    Fills a strided array with pseudorandom numbers drawn from a Poisson\n    distribution using alternative indexing semantics.\n","random.strided.poisson.factory":"\nrandom.strided.poisson.factory( [options:Object] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Poisson distribution.\n","random.strided.poisson.PRNG":"\nrandom.strided.poisson.PRNG\n    Underlying pseudorandom number generator.\n","random.strided.poisson.seed":"\nrandom.strided.poisson.seed\n    Pseudorandom number generator seed.\n","random.strided.poisson.seedLength":"\nrandom.strided.poisson.seedLength\n    Length of generator seed.\n","random.strided.poisson.state":"\nrandom.strided.poisson.state\n    Generator state.\n","random.strided.poisson.stateLength":"\nrandom.strided.poisson.stateLength\n    Length of generator state.\n","random.strided.poisson.byteLength":"\nrandom.strided.poisson.byteLength\n    Size (in bytes) of generator state.\n","random.strided.randu":"\nrandom.strided.randu( N:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with uniformly distributed pseudorandom numbers\n    between 0 and 1.\n","random.strided.randu.ndarray":"\nrandom.strided.randu.ndarray( N:integer, out:ArrayLikeObject, so:integer, \n  oo:integer[, options:Object] )\n    Fills a strided array with uniformly distributed pseudorandom numbers\n    between 0 and 1 using alternative indexing semantics.\n","random.strided.rayleigh":"\nrandom.strided.rayleigh( N:integer, sigma:ArrayLikeObject, ss:integer, \n  out:ArrayLikeObject, so:integer )\n    Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n    distribution.\n","random.strided.rayleigh.ndarray":"\nrandom.strided.rayleigh.ndarray( N:integer, sigma:ArrayLikeObject, ss:integer, \n  os:integer, out:ArrayLikeObject, so:integer, oo:integer )\n    Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n    distribution using alternative indexing semantics.\n","random.strided.rayleigh.factory":"\nrandom.strided.rayleigh.factory( [options:Object] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Rayleigh distribution.\n","random.strided.rayleigh.PRNG":"\nrandom.strided.rayleigh.PRNG\n    Underlying pseudorandom number generator.\n","random.strided.rayleigh.seed":"\nrandom.strided.rayleigh.seed\n    Pseudorandom number generator seed.\n","random.strided.rayleigh.seedLength":"\nrandom.strided.rayleigh.seedLength\n    Length of generator seed.\n","random.strided.rayleigh.state":"\nrandom.strided.rayleigh.state\n    Generator state.\n","random.strided.rayleigh.stateLength":"\nrandom.strided.rayleigh.stateLength\n    Length of generator state.\n","random.strided.rayleigh.byteLength":"\nrandom.strided.rayleigh.byteLength\n    Size (in bytes) of generator state.\n","random.strided.t":"\nrandom.strided.t( N:integer, v:ArrayLikeObject, sv:integer, \n  out:ArrayLikeObject, so:integer )\n    Fills a strided array with pseudorandom numbers drawn from a Student's t-\n    distribution.\n","random.strided.t.ndarray":"\nrandom.strided.t.ndarray( N:integer, v:ArrayLikeObject, sv:integer, ov:integer, \n  out:ArrayLikeObject, so:integer, oo:integer )\n    Fills a strided array with pseudorandom numbers drawn from a Student's t-\n    distribution using alternative indexing semantics.\n","random.strided.t.factory":"\nrandom.strided.t.factory( [options:Object] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Student's t-distribution.\n","random.strided.t.PRNG":"\nrandom.strided.t.PRNG\n    Underlying pseudorandom number generator.\n","random.strided.t.seed":"\nrandom.strided.t.seed\n    Pseudorandom number generator seed.\n","random.strided.t.seedLength":"\nrandom.strided.t.seedLength\n    Length of generator seed.\n","random.strided.t.state":"\nrandom.strided.t.state\n    Generator state.\n","random.strided.t.stateLength":"\nrandom.strided.t.stateLength\n    Length of generator state.\n","random.strided.t.byteLength":"\nrandom.strided.t.byteLength\n    Size (in bytes) of generator state.\n","random.strided.uniform":"\nrandom.strided.uniform( N:integer, a:ArrayLikeObject, sa:integer, \n  b:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a continuous\n    uniform distribution.\n","random.strided.uniform.ndarray":"\nrandom.strided.uniform.ndarray( N:integer, a:ArrayLikeObject, sa:integer, \n  oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, \n  so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a continuous\n    uniform distribution using alternative indexing semantics.\n","random.strided.weibull":"\nrandom.strided.weibull( N:integer, k:ArrayLikeObject, sk:integer, \n  lambda:ArrayLikeObject, sl:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a Weibull\n    distribution.\n","random.strided.weibull.ndarray":"\nrandom.strided.weibull.ndarray( N:integer, k:ArrayLikeObject, sk:integer, \n  ok:integer, lambda:ArrayLikeObject, sl:integer, ol:integer, \n  out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a Weibull\n    distribution using alternative indexing semantics.\n","ranks":"\nranks( arr:Array<number>[, options:Object] )\n    Computes the sample ranks for the values of an array-like object.\n","readDir":"\nreadDir( path:string|Buffer, clbk:Function )\n    Asynchronously reads the contents of a directory.\n","readDir.sync":"\nreadDir.sync( path:string|Buffer )\n    Synchronously reads the contents of a directory.\n","readFile":"\nreadFile( file:string|Buffer|integer[, options:Object|string], clbk:Function )\n    Asynchronously reads the entire contents of a file.\n","readFile.sync":"\nreadFile.sync( file:string|Buffer|integer[, options:Object|string] )\n    Synchronously reads the entire contents of a file.\n","readFileList":"\nreadFileList( filepaths:Array<string>[, options:Object|string], clbk:Function )\n    Asynchronously reads the entire contents of each file in a file list.\n","readFileList.sync":"\nreadFileList.sync( filepaths:Array<string>[, options:Object|string] )\n    Synchronously reads the entire contents of each file in a file list.\n","readJSON":"\nreadJSON( file:string|Buffer|integer[, options:Object|string], clbk:Function )\n    Asynchronously reads a file as JSON.\n","readJSON.sync":"\nreadJSON.sync( file:string|Buffer|integer[, options:Object|string] )\n    Synchronously reads a file as JSON.\n","readWASM":"\nreadWASM( file:string|Buffer|integer[, options:Object], clbk:Function )\n    Asynchronously reads a file as WebAssembly.\n","readWASM.sync":"\nreadWASM.sync( file:string|Buffer|integer[, options:Object] )\n    Synchronously reads a file as WebAssembly.\n","real":"\nreal( z:Complex128 )\n    Returns the real component of a double-precision complex floating-point\n    number.\n","realarray":"\nrealarray( [dtype:string] )\n    Creates a typed array.\n\nrealarray( length:integer[, dtype:string] )\n    Returns a typed array having a specified length.\n\nrealarray( typedarray:TypedArray[, dtype:string] )\n    Creates a typed array from another typed array.\n\nrealarray( obj:Object[, dtype:string] )\n    Creates a typed array from an array-like object or iterable.\n\nrealarray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n  dtype:string] )\n    Returns a typed array view of an ArrayBuffer.\n","realarrayCtors":"\nrealarrayCtors( dtype:string )\n    Returns a typed array constructor.\n","realarrayDataTypes":"\nrealarrayDataTypes()\n    Returns a list of typed array real-valued data types.\n","realf":"\nrealf( z:Complex64 )\n    Returns the real component of a single-precision complex floating-point\n    number.\n","realmax":"\nrealmax( dtype:string )\n    Returns the maximum finite value capable of being represented by a numeric\n    real type.\n","realmin":"\nrealmin( dtype:string )\n    Returns the smallest positive normal value capable of being represented by a\n    numeric real type.\n","reBasename":"\nreBasename( [platform:string] )\n    Returns a regular expression to capture the last part of a path.\n","reBasename.REGEXP":"\nreBasename.REGEXP\n    Regular expression to capture the last part of a POSIX path.\n","reBasename.REGEXP_POSIX":"\nreBasename.REGEXP_POSIX\n    Regular expression to capture the last part of a POSIX path.\n","reBasename.REGEXP_WIN32":"\nreBasename.REGEXP_WIN32\n    Regular expression to capture the last part of a Windows path.\n","reBasenamePosix":"\nreBasenamePosix()\n    Returns a regular expression to capture the last part of a POSIX path.\n","reBasenamePosix.REGEXP":"\nreBasenamePosix.REGEXP\n    Regular expression to capture the last part of a POSIX path.\n","reBasenameWindows":"\nreBasenameWindows()\n    Returns a regular expression to capture the last part of a Windows path.\n","reBasenameWindows.REGEXP":"\nreBasenameWindows.REGEXP\n    Regular expression to capture the last part of a Windows path.\n","reColorHexadecimal":"\nreColorHexadecimal( [mode:string] )\n    Returns a regular expression to match a hexadecimal color.\n","reColorHexadecimal.REGEXP":"\nreColorHexadecimal.REGEXP\n    Regular expression to match a full hexadecimal color.\n","reColorHexadecimal.REGEXP_SHORTHAND":"\nreColorHexadecimal.REGEXP_SHORTHAND\n    Regular expression to match a shorthand hexadecimal color.\n","reColorHexadecimal.REGEXP_EITHER":"\nreColorHexadecimal.REGEXP_EITHER\n    Regular expression to match either a shorthand or full length hexadecimal\n    color.\n","reDecimalNumber":"\nreDecimalNumber( [options:Object] )\n    Returns a regular expression to match a decimal number.\n","reDecimalNumber.REGEXP":"\nreDecimalNumber.REGEXP\n    Regular expression to match a decimal number.\n","reDecimalNumber.REGEXP_CAPTURE":"\nreDecimalNumber.REGEXP_CAPTURE\n    Regular expression to capture a decimal number.\n","reDirname":"\nreDirname( [platform:string] )\n    Returns a regular expression to capture a path dirname.\n","reDirname.REGEXP":"\nreDirname.REGEXP\n    Regular expression to capture a path dirname.\n","reDirname.REGEXP_POSIX":"\nreDirname.REGEXP_POSIX\n    Regular expression to capture a POSIX path dirname.\n","reDirname.REGEXP_WIN32":"\nreDirname.REGEXP_WIN32\n    Regular expression to capture a Windows path dirname.\n","reDirnamePosix":"\nreDirnamePosix()\n    Returns a regular expression to capture a POSIX path dirname.\n","reDirnamePosix.REGEXP":"\nreDirnamePosix.REGEXP\n    Regular expression to capture a POSIX path dirname.\n","reDirnameWindows":"\nreDirnameWindows()\n    Returns a regular expression to capture a Windows path dirname.\n","reDirnameWindows.REGEXP":"\nreDirnameWindows.REGEXP\n    Regular expression to capture a Windows path dirname.\n","reduce":"\nreduce( arr:ArrayLikeObject|ndarray, initial:any, reducer:Function[, \n  thisArg:any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n","reduce2d":"\nreduce2d( arr:ArrayLikeObject<ArrayLikeObject>, initial:ArrayLikeObject, \n  reducer:Function[, thisArg:any] )\n    Reduces the number of dimensions by one of a two-dimensional nested array by\n    applying a function against an accumulator and each element along the\n    innermost dimension and returning the accumulation results as a one-\n    dimensional array.\n","reduceAsync":"\nreduceAsync( collection:Array|TypedArray|Object, initial:any, [options:Object,] \n  reducer:Function, done:Function )\n    Applies a function against an accumulator and each element in a collection\n    and returns the accumulated result.\n","reduceAsync.factory":"\nreduceAsync.factory( [options:Object,] fcn:Function )\n    Returns a function which applies a function against an accumulator and each\n    element in a collection and returns the accumulated result.\n","reduceRight":"\nreduceRight( arr:ArrayLikeObject|ndarray, initial:any, reducer:Function[, \n  thisArg:any] )\n    Applies a function against an accumulator and each element in an array while\n    iterating from right to left and returns the accumulated result.\n","reduceRightAsync":"\nreduceRightAsync( collection:Array|TypedArray|Object, initial:any, \n  [options:Object,] reducer:Function, done:Function )\n    Applies a function against an accumulator and each element in a collection\n    and returns the accumulated result, iterating from right to left.\n","reduceRightAsync.factory":"\nreduceRightAsync.factory( [options:Object,] fcn:Function )\n    Returns a function which applies a function against an accumulator and each\n    element in a collection and returns the accumulated result, iterating from\n    right to left.\n","reDurationString":"\nreDurationString()\n    Returns a regular expression to match a duration string.\n","reDurationString.REGEXP":"\nreDurationString.REGEXP\n    Regular expression to match a duration string.\n","reEOL":"\nreEOL( [options:Object] )\n    Regular expression to match a newline character sequence: /\\r?\\n/.\n","reEOL.REGEXP":"\nreEOL.REGEXP\n    Regular expression to match a newline character sequence: /\\r?\\n/.\n","reEOL.REGEXP_CAPTURE":"\nreEOL.REGEXP_CAPTURE\n    Regular expression to capture a newline character sequence: /\\r?\\n/.\n","reExtendedLengthPath":"\nreExtendedLengthPath()\n    Returns a regular expression to test if a string is an extended-length path.\n","reExtendedLengthPath.REGEXP":"\nreExtendedLengthPath.REGEXP\n    Regular expression to test if a string is an extended-length path.\n","reExtname":"\nreExtname( [platform:string] )\n    Returns a regular expression to capture a filename extension.\n","reExtname.REGEXP":"\nreExtname.REGEXP\n    Regular expression to capture a filename extension.\n","reExtname.REGEXP_POSIX":"\nreExtname.REGEXP_POSIX\n    Regular expression to capture a POSIX filename extension.\n","reExtname.REGEXP_WIN32":"\nreExtname.REGEXP_WIN32\n    Regular expression to capture a Windows filename extension.\n","reExtnamePosix":"\nreExtnamePosix\n    Returns a regular expression to capture a POSIX filename extension.\n","reExtnamePosix.REGEXP":"\nreExtnamePosix.REGEXP\n    Regular expression to capture a POSIX filename extension.\n","reExtnameWindows":"\nreExtnameWindows\n    Returns a regular expression to capture a Windows filename extension.\n","reExtnameWindows.REGEXP":"\nreExtnameWindows.REGEXP\n    Regular expression to capture a Windows filename extension.\n","reFilename":"\nreFilename( [platform:string] )\n    Regular expression to split a filename.\n","reFilename.REGEXP":"\nreFilename.REGEXP\n    Regular expression to split a filename.\n","reFilename.REGEXP_POSIX":"\nreFilename.REGEXP_POSIX\n    Regular expression to split a POSIX filename.\n","reFilename.REGEXP_WIN32":"\nreFilename.REGEXP_WIN32\n    Regular expression to split a Windows filename.\n","reFilenamePosix":"\nreFilenamePosix()\n    Returns a regular expression to split a POSIX filename.\n","reFilenamePosix.REGEXP":"\nreFilenamePosix.REGEXP\n    Regular expression to split a POSIX filename.\n","reFilenameWindows":"\nreFilenameWindows()\n    Returns a regular expression to split a Windows filename.\n","reFilenameWindows.REGEXP":"\nreFilenameWindows.REGEXP\n    Regular expression to split a Windows filename.\n","reFromString":"\nreFromString( str:string )\n    Parses a regular expression string and returns a new regular expression.\n","reFunctionName":"\nreFunctionName()\n    Return a regular expression to capture a function name.\n","reFunctionName.REGEXP":"\nreFunctionName.REGEXP\n    Regular expression to capture a function name.\n","regexp2json":"\nregexp2json( re:RegExp )\n    Returns a JSON representation of a regular expression.\n","reim":"\nreim( z:Complex128 )\n    Returns the real and imaginary components of a double-precision complex\n    floating-point number.\n","reimf":"\nreimf( z:Complex64 )\n    Returns the real and imaginary components of a single-precision complex\n    floating-point number.\n","rejectArguments":"\nrejectArguments( fcn:Function, predicate:Function[, thisArg:any] )\n    Returns a function that applies arguments to a provided function according\n    to a predicate function.\n","removeFirst":"\nremoveFirst( str:string[, n:integer][, options:Object] )\n    Removes the first character(s) of a `string`.\n","removeLast":"\nremoveLast( str:string[, n:integer][, options:Object] )\n    Removes the last character(s) of a `string`.\n","removePunctuation":"\nremovePunctuation( str:string )\n    Removes punctuation characters from a `string`.\n","removeUTF8BOM":"\nremoveUTF8BOM( str:string )\n    Removes a UTF-8 byte order mark (BOM) from the beginning of a `string`.\n","removeWords":"\nremoveWords( str:string, words:Array<string>[, ignoreCase:boolean] )\n    Removes all occurrences of the given words from a `string`.\n","rename":"\nrename( oldPath:string|Buffer, newPath:string|Buffer, clbk:Function )\n    Asynchronously renames a file.\n","rename.sync":"\nrename.sync( oldPath:string|Buffer, newPath:string|Buffer )\n    Synchronously renames a file.\n","reNativeFunction":"\nreNativeFunction()\n    Returns a regular expression to match a native function.\n","reNativeFunction.REGEXP":"\nreNativeFunction.REGEXP\n    Regular expression to match a native function.\n","reorderArguments":"\nreorderArguments( fcn:Function, indices:Array<integer>[, thisArg:any] )\n    Returns a function that invokes a provided function with reordered\n    arguments.\n","repeat":"\nrepeat( str:string, n:integer )\n    Repeats a string `n` times and returns the concatenated result.\n","replace":"\nreplace( str:string, search:string|RegExp, newval:string|Function )\n    Replaces search occurrences with a replacement string.\n","replaceBefore":"\nreplaceBefore( str, search, replacement )\n    Replaces the substring before the first occurrence of a specified search\n    string. \n","reRegExp":"\nreRegExp()\n    Returns a regular expression to parse a regular expression string.\n","reRegExp.REGEXP":"\nreRegExp.REGEXP\n    Regular expression to parse a regular expression string.\n","rescape":"\nrescape( str:string )\n    Escapes a regular expression string.\n","reSemVer":"\nreSemVer()\n    Returns a regular expression to match a semantic version string.\n","reSemVer.REGEXP":"\nreSemVer.REGEXP\n    Regular expression to match a semantic version string.\n","resolveParentPath":"\nresolveParentPath( path:string[, options:Object], clbk:Function )\n    Asynchronously resolves a path by walking parent directories.\n","resolveParentPath.sync":"\nresolveParentPath.sync( path:string[, options:Object] )\n    Synchronously resolves a path by walking parent directories.\n","resolveParentPathBy":"\nresolveParentPathBy( path:string[, options:Object], predicate:Function, \n  clbk:Function )\n    Asynchronously resolves a path according to a predicate function by walking\n    parent directories.\n","resolveParentPathBy.sync":"\nresolveParentPathBy.sync( path:string[, options:Object], predicate:Function )\n    Synchronously resolves a path according to a predicate function by walking\n    parent directories.\n","reUncPath":"\nreUncPath()\n    Return a regular expression to parse a UNC path.\n","reUncPath.REGEXP":"\nreUncPath.REGEXP\n    Regular expression to parse a UNC path.\n","reUtf16SurrogatePair":"\nreUtf16SurrogatePair()\n    Returns a regular expression to match a UTF-16 surrogate pair.\n","reUtf16SurrogatePair.REGEXP":"\nreUtf16SurrogatePair.REGEXP\n    Regular expression to match a UTF-16 surrogate pair.\n","reUtf16UnpairedSurrogate":"\nreUtf16UnpairedSurrogate()\n    Returns a regular expression to match an unpaired UTF-16 surrogate.\n","reUtf16UnpairedSurrogate.REGEXP":"\nreUtf16UnpairedSurrogate.REGEXP\n    Regular expression to match an unpaired UTF-16 surrogate.\n","reverseArguments":"\nreverseArguments( fcn:Function[, thisArg:any] )\n    Returns a function that invokes a provided function with arguments in\n    reverse order.\n","reverseString":"\nreverseString( str:string[, options:Object] )\n    Reverses a string.\n","reviveBasePRNG":"\nreviveBasePRNG( key:string, value:any )\n    Revives a JSON-serialized pseudorandom number generator (PRNG).\n","reviveBuffer":"\nreviveBuffer( key:string, value:any )\n    Revives a JSON-serialized Buffer.\n","reviveComplex":"\nreviveComplex( key:string, value:any )\n    Revives a JSON-serialized complex number.\n","reviveComplex64":"\nreviveComplex64( key:string, value:any )\n    Revives a JSON-serialized 64-bit complex number.\n","reviveComplex128":"\nreviveComplex128( key:string, value:any )\n    Revives a JSON-serialized 128-bit complex number.\n","reviveError":"\nreviveError( key:string, value:any )\n    Revives a JSON-serialized error object.\n","reviveRegExp":"\nreviveRegExp( key:string, value:any )\n    Revives a JSON-serialized regular expression.\n","reviveTypedArray":"\nreviveTypedArray( key:string, value:any )\n    Revives a JSON-serialized typed array.\n","reWhitespace":"\nreWhitespace( [options:Object] )\n    Returns a regular expression to match a white space character.\n","reWhitespace.REGEXP":"\nreWhitespace.REGEXP\n    Regular expression to match a white space character.\n","reWhitespace.REGEXP_CAPTURE":"\nreWhitespace.REGEXP_CAPTURE\n    Regular expression to capture white space characters.\n","rpad":"\nrpad( str:string, len:integer[, pad:string] )\n    Right pads a `string` such that the padded `string` has a length of at least\n    `len`.\n","rtrim":"\nrtrim( str:string )\n    Trims whitespace from the end of a string.\n","rtrimN":"\nrtrimN( str:string, n:integer[, chars:Array|string] )\n    Trims `n` characters from the end of a string.\n","safeintmax":"\nsafeintmax( dtype:string )\n    Returns the maximum safe integer capable of being represented by a numeric\n    real type.\n","safeintmin":"\nsafeintmin( dtype:string )\n    Returns the minimum safe integer capable of being represented by a numeric\n    real type.\n","sample":"\nsample( x:ArrayLike[, options:Object] )\n    Samples elements from an array-like object.\n","sample.factory":"\nsample.factory( [pool:ArrayLike, ][options:Object] )\n    Returns a function to sample elements from an array-like object.\n","SAVOY_STOPWORDS_FIN":"\nSAVOY_STOPWORDS_FIN()\n    Returns a list of Finnish stop words.\n","SAVOY_STOPWORDS_FR":"\nSAVOY_STOPWORDS_FR()\n    Returns a list of French stop words.\n","SAVOY_STOPWORDS_GER":"\nSAVOY_STOPWORDS_GER()\n    Returns a list of German stop words.\n","SAVOY_STOPWORDS_IT":"\nSAVOY_STOPWORDS_IT()\n    Returns a list of Italian stop words.\n","SAVOY_STOPWORDS_POR":"\nSAVOY_STOPWORDS_POR()\n    Returns a list of Portuguese stop words.\n","SAVOY_STOPWORDS_SP":"\nSAVOY_STOPWORDS_SP()\n    Returns a list of Spanish stop words.\n","SAVOY_STOPWORDS_SWE":"\nSAVOY_STOPWORDS_SWE()\n    Returns a list of Swedish stop words.\n","scalar2array":"\nscalar2array( value:any[, dtype:string] )\n    Returns a single-element array containing a provided scalar value.\n","scalar2ndarray":"\nscalar2ndarray( value:any[, options:Object] )\n    Returns a zero-dimensional ndarray containing a provided scalar value.\n","sdot":"\nsdot( x:ndarray, y:ndarray[, dim:integer] )\n    Computes the dot product of two single-precision floating-point vectors.\n","SECONDS_IN_DAY":"\nSECONDS_IN_DAY\n    Number of seconds in a day.\n","SECONDS_IN_HOUR":"\nSECONDS_IN_HOUR\n    Number of seconds in an hour.\n","SECONDS_IN_MINUTE":"\nSECONDS_IN_MINUTE\n    Number of seconds in a minute.\n","SECONDS_IN_WEEK":"\nSECONDS_IN_WEEK\n    Number of seconds in a week.\n","secondsInMonth":"\nsecondsInMonth( [month:string|Date|integer[, year:integer]] )\n    Returns the number of seconds in a month.\n","secondsInYear":"\nsecondsInYear( [value:integer|Date] )\n    Returns the number of seconds in a year according to the Gregorian calendar.\n","sentencize":"\nsentencize( str:string )\n    Splits a string into an array of sentences.\n","seq2slice":"\nseq2slice( str:string, len:integer, strict:boolean )\n    Converts a subsequence string to a Slice object.\n","setConfigurableReadOnly":"\nsetConfigurableReadOnly( obj:Object, prop:string|symbol, value:any )\n    Defines a configurable read-only property.\n","setConfigurableReadOnlyAccessor":"\nsetConfigurableReadOnlyAccessor( obj:Object, prop:string|symbol, \n  getter:Function )\n    Defines a configurable read-only accessor.\n","setConfigurableReadWriteAccessor":"\nsetConfigurableReadWriteAccessor( obj:Object, prop:string|symbol, \n  getter:Function, setter:Function )\n    Defines a configurable property having read-write accessors.\n","setConfigurableWriteOnlyAccessor":"\nsetConfigurableWriteOnlyAccessor( obj:Object, prop:string|symbol, \n  setter:Function )\n    Defines a configurable write-only accessor.\n","setMemoizedConfigurableReadOnly":"\nsetMemoizedConfigurableReadOnly( obj:Object, prop:string|symbol, fcn:Function )\n    Defines a configurable memoized read-only object property.\n","setMemoizedReadOnly":"\nsetMemoizedReadOnly( obj:Object, prop:string|symbol, fcn:Function )\n    Defines a memoized read-only object property.\n","setNonEnumerableProperty":"\nsetNonEnumerableProperty( obj:Object, prop:string|symbol, value:any )\n    Defines a non-enumerable property.\n","setNonEnumerableReadOnly":"\nsetNonEnumerableReadOnly( obj:Object, prop:string|symbol, value:any )\n    Defines a non-enumerable read-only property.\n","setNonEnumerableReadOnlyAccessor":"\nsetNonEnumerableReadOnlyAccessor( obj:Object, prop:string|symbol, \n  getter:Function )\n    Defines a non-enumerable read-only accessor.\n","setNonEnumerableReadWriteAccessor":"\nsetNonEnumerableReadWriteAccessor( obj:Object, prop:string|symbol, \n  getter:Function, setter:Function )\n    Defines a non-enumerable property having read-write accessors.\n","setNonEnumerableWriteOnlyAccessor":"\nsetNonEnumerableWriteOnlyAccessor( obj:Object, prop:string|symbol, \n  setter:Function )\n    Defines a non-enumerable write-only accessor.\n","setReadOnly":"\nsetReadOnly( obj:Object, prop:string|symbol, value:any )\n    Defines a read-only property.\n","setReadOnlyAccessor":"\nsetReadOnlyAccessor( obj:Object, prop:string|symbol, getter:Function )\n    Defines a read-only accessor.\n","setReadWriteAccessor":"\nsetReadWriteAccessor( obj:Object, prop:string|symbol, getter:Function, \n  setter:Function )\n    Defines a property having read-write accessors.\n","setWriteOnlyAccessor":"\nsetWriteOnlyAccessor( obj:Object, prop:string|symbol, setter:Function )\n    Defines a write-only accessor.\n","SharedArrayBuffer":"\nSharedArrayBuffer( size:integer )\n    Returns a shared array buffer having a specified number of bytes.\n","SharedArrayBuffer.length":"\nSharedArrayBuffer.length\n    Number of input arguments the constructor accepts.\n","SharedArrayBuffer.prototype.byteLength":"\nSharedArrayBuffer.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the array buffer.\n","SharedArrayBuffer.prototype.slice":"\nSharedArrayBuffer.prototype.slice( [start:integer[, end:integer]] )\n    Copies the bytes of a shared array buffer to a new shared array buffer.\n","shift":"\nshift( collection:Array|TypedArray|Object )\n    Removes and returns the first element of a collection.\n","shuffle":"\nshuffle( arr:ArrayLike[, options:Object] )\n    Shuffles elements of an array-like object.\n","shuffle.factory":"\nshuffle.factory( [options:Object] )\n    Returns a function to shuffle elements of array-like objects.\n","sizeOf":"\nsizeOf( dtype:string )\n    Returns the size (in bytes) of the canonical binary representation of a\n    specified numeric type.\n","Slice":"\nSlice( [stop:integer|null|undefined] )\n    Returns a Slice.\n\nSlice( start:integer|null|undefined, stop:integer|null|undefined[, \n  step:integer|null|undefined] )\n    Returns a Slice.\n","Slice.prototype.start":"\nSlice.prototype.start\n    Read-only property returning the starting slice index.\n","Slice.prototype.stop":"\nSlice.prototype.stop\n    Read-only property returning the ending slice index.\n","Slice.prototype.step":"\nSlice.prototype.step\n    Read-only property returning the index increment.\n","Slice.prototype.toString":"\nSlice.prototype.toString()\n    Serializes a Slice as a string.\n","Slice.prototype.toJSON":"\nSlice.prototype.toJSON()\n    Serializes a Slice as a JSON object.\n","snakecase":"\nsnakecase( str:string )\n    Converts a string to snake case.\n","some":"\nsome( collection:Array|TypedArray|Object, n:number )\n    Tests whether at least `n` elements in a collection are truthy.\n","someBy":"\nsomeBy( collection:Array|TypedArray|Object, n:number, predicate:Function[, \n  thisArg:any ] )\n    Tests whether a collection contains at least `n` elements which pass a test\n    implemented by a predicate function.\n","someByAsync":"\nsomeByAsync( collection:Array|TypedArray|Object, n:number, [options:Object,] \n  predicate:Function, done:Function )\n    Tests whether a collection contains at least `n` elements which pass a test\n    implemented by a predicate function.\n","someByAsync.factory":"\nsomeByAsync.factory( [options:Object,] predicate:Function )\n    Returns a function which tests whether a collection contains at least `n`\n    elements which pass a test implemented by a predicate function.\n","someByRight":"\nsomeByRight( collection:Array|TypedArray|Object, n:number, predicate:Function[, \n  thisArg:any ] )\n    Tests whether a collection contains at least `n` elements which pass a test\n    implemented by a predicate function, iterating from right to left.\n","someByRightAsync":"\nsomeByRightAsync( collection:Array|TypedArray|Object, n:number, \n  [options:Object,] predicate:Function, done:Function )\n    Tests whether a collection contains at least `n` elements which pass a test\n    implemented by a predicate function, iterating from right to left.\n","someByRightAsync.factory":"\nsomeByRightAsync.factory( [options:Object,] predicate:Function )\n    Returns a function which tests whether a collection contains at least `n`\n    elements which pass a test implemented by a predicate function, iterating\n    from right to left.\n","someInBy":"\nsomeInBy( obj:Object, n:number, predicate:Function[, thisArg:any ] )\n    Tests whether an object contains at least `n` properties\n    (own and inherited) which pass a test\n    implemented by a predicate function.\n","someOwnBy":"\nsomeOwnBy( obj:Object, n:number, predicate:Function[, thisArg:any ] )\n    Tests whether some `own` properties of a provided object\n    satisfy a predicate function for at least `n` properties.\n","SOTU":"\nSOTU( [options:Object] )\n    Returns State of the Union (SOTU) addresses.\n","SPACHE_REVISED":"\nSPACHE_REVISED()\n    Returns a list of simple American-English words (revised Spache).\n","SPAM_ASSASSIN":"\nSPAM_ASSASSIN()\n    Returns the Spam Assassin public mail corpus.\n","SparklineBase":"\nSparklineBase( [data:ArrayLike|ndarray,] [options:Object] )\n    Returns a Sparkline instance.\n","sparsearray2iterator":"\nsparsearray2iterator( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )\n    Returns an iterator which iterates over the elements of a sparse array-like\n    object.\n","sparsearray2iteratorRight":"\nsparsearray2iteratorRight( src:ArrayLikeObject[, mapFcn:Function[, \n  thisArg:any]] )\n    Returns an iterator which iterates from right to left over the elements of a\n    sparse array-like object.\n","splitStream":"\nsplitStream( [options:Object] )\n    Returns a transform stream which splits streamed data.\n","splitStream.factory":"\nsplitStream.factory( [options:Object] )\n    Returns a function for creating transform streams for splitting streamed\n    data.\n","splitStream.objectMode":"\nsplitStream.objectMode( [options:Object] )\n    Returns an \"objectMode\" transform stream for splitting streamed data.\n","SQRT_EPS":"\nSQRT_EPS\n    Square root of double-precision floating-point epsilon.\n","SQRT_HALF":"\nSQRT_HALF\n    Square root of `1/2`.\n","SQRT_HALF_PI":"\nSQRT_HALF_PI\n    Square root of the mathematical constant `π` divided by `2`.\n","SQRT_PHI":"\nSQRT_PHI\n    Square root of the golden ratio.\n","SQRT_PI":"\nSQRT_PI\n    Square root of the mathematical constant `π`.\n","SQRT_THREE":"\nSQRT_THREE\n    Square root of `3`.\n","SQRT_TWO":"\nSQRT_TWO\n    Square root of `2`.\n","SQRT_TWO_PI":"\nSQRT_TWO_PI\n    Square root of the mathematical constant `π` times `2`.\n","SSA_US_BIRTHS_2000_2014":"\nSSA_US_BIRTHS_2000_2014()\n    Returns US birth data from 2000 to 2014, as provided by the Social Security\n    Administration.\n","sswap":"\nsswap( x:ndarray, y:ndarray[, dim:integer] )\n    Interchanges two single-precision floating-point vectors.\n","Stack":"\nStack()\n    Stack constructor.\n","standalone2pkg":"\nstandalone2pkg( pkg:string )\n    Returns the internal package name associated with a provided standalone\n    package name.\n","STANDARD_CARD_DECK":"\nSTANDARD_CARD_DECK()\n    Returns a string array containing two or three letter abbreviations for each\n    card in a standard 52-card deck.\n","startcase":"\nstartcase( str:string )\n    Capitalizes the first letter of each word in an input string.\n","startsWith":"\nstartsWith( str:string, search:string[, position:integer] )\n    Tests if a string starts with the characters of another string.\n","STOPWORDS_EN":"\nSTOPWORDS_EN()\n    Returns a list of English stop words.\n","strided.abs":"\nstrided.abs( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  dtypeY:any, y:ArrayLikeObject, strideY:integer )\n    Computes the absolute value for each element in a strided array `x` and\n    assigns the results to elements in a strided array `y`.\n","strided.abs.ndarray":"\nstrided.abs.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, \n  offsetY:integer )\n    Computes the absolute value for each element in a strided array `x` and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n","strided.abs2":"\nstrided.abs2( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  dtypeY:any, y:ArrayLikeObject, strideY:integer )\n    Computes the squared absolute value for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y`.\n","strided.abs2.ndarray":"\nstrided.abs2.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n  strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n  strideY:integer, offsetY:integer )\n    Computes the squared absolute value for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n","strided.abs2By":"\nstrided.abs2By( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the squared absolute value of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n","strided.abs2By.ndarray":"\nstrided.abs2By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the squared absolute value of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing semantics.\n","strided.absBy":"\nstrided.absBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the absolute value of each element retrieved from a strided input\n    array `x` via a callback function and assigns each result to an element in a\n    strided output array `y`.\n","strided.absBy.ndarray":"\nstrided.absBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the absolute value of each element retrieved from a strided input\n    array `x` via a callback function and assigns each result to an element in a\n    strided output array `y` using alternative indexing semantics.\n","strided.acosBy":"\nstrided.acosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the arccosine of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y`.\n","strided.acosBy.ndarray":"\nstrided.acosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the arccosine of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n","strided.acoshBy":"\nstrided.acoshBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the hyperbolic arccosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n","strided.acoshBy.ndarray":"\nstrided.acoshBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the hyperbolic arccosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n","strided.acotBy":"\nstrided.acotBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the inverse cotangent of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n","strided.acotBy.ndarray":"\nstrided.acotBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the inverse cotangent of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n","strided.acothBy":"\nstrided.acothBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the inverse hyperbolic cotangent of each element retrieved from an\n    input strided array `x` via a callback function and assigns each result to\n    an element in an output strided array `y`.\n","strided.acothBy.ndarray":"\nstrided.acothBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the inverse hyperbolic cotangent of each element retrieved from an\n    input strided array `x` via a callback function and assigns each result to\n    an element in an output strided array `y` using alternative indexing\n    semantics.\n","strided.acovercosBy":"\nstrided.acovercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the inverse coversed cosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n","strided.acovercosBy.ndarray":"\nstrided.acovercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the inverse coversed cosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n","strided.acoversinBy":"\nstrided.acoversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the inverse coversed sine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n","strided.acoversinBy.ndarray":"\nstrided.acoversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the inverse coversed sine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n","strided.add":"\nstrided.add( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, \n  y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )\n    Adds each element in a strided array `x` to a corresponding element in a\n    strided array `y` and assigns the results to elements in a strided array\n    `z`.\n","strided.add.ndarray":"\nstrided.add.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, \n  ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, \n  z:ArrayLikeObject, sz:integer, oz:integer )\n    Adds each element in a strided array `x` to a corresponding element in a\n    strided array `y` and assigns the results to elements in a strided array\n    `z` using alternative indexing semantics.\n","strided.addBy":"\nstrided.addBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, \n  clbk:Function[, thisArg:any] )\n    Performs element-wise addition of two strided arrays via a callback function\n    and assigns each result to an element in an output strided array.\n","strided.addBy.ndarray":"\nstrided.addBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, \n  thisArg:any] )\n    Performs element-wise addition of two strided arrays via a callback function\n    and assigns each result to an element in an output strided array using\n    alternative indexing semantics.\n","strided.ahavercosBy":"\nstrided.ahavercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the inverse half-value versed cosine of each element retrieved from\n    an input strided array `x` via a callback function and assigns each result\n    to an element in an output strided array `y`.\n","strided.ahavercosBy.ndarray":"\nstrided.ahavercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the inverse half-value versed cosine of each element retrieved from\n    an input strided array `x` via a callback function and assigns each result\n    to an element in an output strided array `y` using alternative indexing\n    semantics.\n","strided.ahaversinBy":"\nstrided.ahaversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the inverse half-value versed sine of each element retrieved from\n    an input strided array `x` via a callback function and assigns each result\n    to an element in an output strided array `y`.\n","strided.ahaversinBy.ndarray":"\nstrided.ahaversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the inverse half-value versed sine of each element retrieved from\n    an input strided array `x` via a callback function and assigns each result\n    to an element in an output strided array `y` using alternative indexing\n    semantics.\n","strided.asinBy":"\nstrided.asinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the arcsine of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y`.\n","strided.asinBy.ndarray":"\nstrided.asinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the arcsine of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n","strided.asinhBy":"\nstrided.asinhBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the hyperbolic arcsine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n","strided.asinhBy.ndarray":"\nstrided.asinhBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the hyperbolic arcsine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n","strided.atanBy":"\nstrided.atanBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the arctangent of each element retrieved from an input strided\n    array `x` via a callback function and assigns each result to an element in\n    an output strided array `y`.\n","strided.atanBy.ndarray":"\nstrided.atanBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the arctangent of each element retrieved from an input strided\n    array `x` via a callback function and assigns each result to an element in\n    an output strided array `y` using alternative indexing semantics.\n","strided.atanhBy":"\nstrided.atanhBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the hyperbolic arctangent of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n","strided.atanhBy.ndarray":"\nstrided.atanhBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the hyperbolic arctangent of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n","strided.avercosBy":"\nstrided.avercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the inverse versed cosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n","strided.avercosBy.ndarray":"\nstrided.avercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the inverse versed cosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n","strided.aversinBy":"\nstrided.aversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the inverse versed sine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n","strided.aversinBy.ndarray":"\nstrided.aversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the inverse versed sine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n","strided.besselj0By":"\nstrided.besselj0By( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the Bessel function of the first kind of order zero for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y`.\n","strided.besselj0By.ndarray":"\nstrided.besselj0By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the Bessel function of the first kind of order zero for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n","strided.besselj1By":"\nstrided.besselj1By( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the Bessel function of the first kind of order one for each element\n    retrieved from an input strided array `x` via a callback function and\n    assigns each result to an element in an output strided array `y`.\n","strided.besselj1By.ndarray":"\nstrided.besselj1By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the Bessel function of the first kind of order one for each element\n    retrieved from an input strided array `x` via a callback function and\n    assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n","strided.bessely0By":"\nstrided.bessely0By( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the Bessel function of the second kind of order zero for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y`.\n","strided.bessely0By.ndarray":"\nstrided.bessely0By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the Bessel function of the second kind of order zero for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n","strided.bessely1By":"\nstrided.bessely1By( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the Bessel function of the second kind of order one for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y`.\n","strided.bessely1By.ndarray":"\nstrided.bessely1By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the Bessel function of the second kind of order one for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n","strided.binetBy":"\nstrided.binetBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Evaluates Binet's formula extended to real numbers for each element\n    retrieved from an input strided array `x` via a callback function and\n    assigns each result to an element in an output strided array `y`.\n","strided.binetBy.ndarray":"\nstrided.binetBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Evaluates Binet's formula extended to real numbers for each element\n    retrieved from an input strided array `x` via a callback function and\n    assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n","strided.cbrt":"\nstrided.cbrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  dtypeY:any, y:ArrayLikeObject, strideY:integer )\n    Computes the cube root of each element in a strided array `x` and assigns\n    the results to elements in a strided array `y`.\n","strided.cbrt.ndarray":"\nstrided.cbrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n  strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n  strideY:integer, offsetY:integer )\n    Computes the cube root of each element in a strided array `x` and assigns\n    the results to elements in a strided array `y` using alternative indexing\n    semantics.\n","strided.cbrtBy":"\nstrided.cbrtBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the cube root of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y`.\n","strided.cbrtBy.ndarray":"\nstrided.cbrtBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the cube root of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n","strided.ceil":"\nstrided.ceil( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  dtypeY:any, y:ArrayLikeObject, strideY:integer )\n    Rounds each element in a strided array `x` toward positive infinity and\n    assigns the results to elements in a strided array `y`.\n","strided.ceil.ndarray":"\nstrided.ceil.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n  strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n  strideY:integer, offsetY:integer )\n    Rounds each element in a strided array `x` toward positive infinity and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n","strided.cosBy":"\nstrided.cosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the cosine for each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y`.\n","strided.cosBy.ndarray":"\nstrided.cosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the cosine for each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n","strided.deg2rad":"\nstrided.deg2rad( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  dtypeY:any, y:ArrayLikeObject, strideY:integer )\n    Converts each element in a strided array `x` from degrees to radians and\n    assigns the results to elements in a strided array `y`.\n","strided.deg2rad.ndarray":"\nstrided.deg2rad.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n  strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n  strideY:integer, offsetY:integer )\n    Converts each element in a strided array `x` from degrees to radians and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n","strided.dataTypes":"\nstrided.dataTypes()\n    Returns a list of strided array data types.\n","strided.dcbrtBy":"\nstrided.dcbrtBy( N:integer, x:Float64Array, sx:integer, y:Float64Array, \n  sy:integer, clbk:Function[, thisArg:any] )\n    Computes the cube root of each element retrieved from an input double-\n    precision floating-point strided array via a callback function and assigns\n    each result to an element in an output double-precision floating-point\n    strided array.\n","strided.dcbrtBy.ndarray":"\nstrided.dcbrtBy.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, \n  y:Float64Array, sy:integer, oy:integer, clbk:Function[, thisArg:any] )\n    Computes the cube root of each element retrieved from an input double-\n    precision floating-point strided array via a callback function and assigns\n    each result to an element in an output double-precision floating-point\n    strided array using alternative indexing semantics.\n","strided.dispatch":"\nstrided.dispatch( fcns:Function|ArrayLikeObject<Function>, \n  types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, \n  nout:integer )\n    Returns a strided array function interface which performs multiple dispatch.\n","strided.dispatchBy":"\nstrided.dispatchBy( fcns:Function|ArrayLikeObject<Function>, \n  types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, \n  nout:integer )\n    Returns a strided array function interface which accepts a callback function\n    and performs multiple dispatch.\n","strided.floor":"\nstrided.floor( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  dtypeY:any, y:ArrayLikeObject, strideY:integer )\n    Rounds each element in a strided array `x` toward negative infinity and\n    assigns the results to elements in a strided array `y`.\n","strided.floor.ndarray":"\nstrided.floor.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n  strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n  strideY:integer, offsetY:integer )\n    Rounds each element in a strided array `x` toward negative infinity and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n","strided.inv":"\nstrided.inv( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  dtypeY:any, y:ArrayLikeObject, strideY:integer )\n    Computes the multiplicative inverse for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y`.\n","strided.inv.ndarray":"\nstrided.inv.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, \n  offsetY:integer )\n    Computes the multiplicative inverse for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n","strided.mul":"\nstrided.mul( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, \n  y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )\n    Multiplies each element in a strided array `x` to a corresponding element in\n    a strided array `y` and assigns the results to elements in a strided array\n    `z`.\n","strided.mul.ndarray":"\nstrided.mul.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, \n  ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, \n  z:ArrayLikeObject, sz:integer, oz:integer )\n    Multiplies each element in a strided array `x` to a corresponding element in\n    a strided array `y` and assigns the results to elements in a strided array\n    `z` using alternative indexing semantics.\n","strided.mulBy":"\nstrided.mulBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, \n  clbk:Function[, thisArg:any] )\n    Performs element-wise multiplication of two strided arrays via a callback\n    function and assigns each result to an element in an output strided array.\n","strided.mulBy.ndarray":"\nstrided.mulBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, \n  thisArg:any] )\n    Performs element-wise multiplication of two strided arrays via a callback\n    function and assigns each result to an element in an output strided array\n    using alternative indexing semantics.\n","strided.ramp":"\nstrided.ramp( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  dtypeY:any, y:ArrayLikeObject, strideY:integer )\n    Evaluates the ramp function for each element in a strided array `x` and\n    assigns the results to elements in a strided array `y`.\n","strided.ramp.ndarray":"\nstrided.ramp.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n  strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n  strideY:integer, offsetY:integer )\n    Evaluates the ramp function for each element in a strided array `x` and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n","strided.rsqrt":"\nstrided.rsqrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  dtypeY:any, y:ArrayLikeObject, strideY:integer )\n    Computes the reciprocal square root for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y`.\n","strided.rsqrt.ndarray":"\nstrided.rsqrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n  strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n  strideY:integer, offsetY:integer )\n    Computes the reciprocal square root for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n","strided.sinBy":"\nstrided.sinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the sine of each element retrieved from an input strided array `x`\n    via a callback function and assigns each result to an element in an output\n    strided array `y`.\n","strided.sinBy.ndarray":"\nstrided.sinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the sine of each element retrieved from an input strided array `x`\n    via a callback function and assigns each result to an element in an output\n    strided array `y` using alternative indexing semantics.\n","strided.sqrt":"\nstrided.sqrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  dtypeY:any, y:ArrayLikeObject, strideY:integer )\n    Computes the principal square root for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y`.\n","strided.sqrt.ndarray":"\nstrided.sqrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n  strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n  strideY:integer, offsetY:integer )\n    Computes the principal square root for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n","strided.sqrtBy":"\nstrided.sqrtBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the principal square root for each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n","strided.sqrtBy.ndarray":"\nstrided.sqrtBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the principal square root for each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing semantics.\n","strided.sub":"\nstrided.sub( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, \n  y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )\n    Subtracts each element in a strided array `x` to a corresponding element in\n    a strided array `y` and assigns the results to elements in a strided array\n    `z`.\n","strided.sub.ndarray":"\nstrided.sub.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, \n  ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, \n  z:ArrayLikeObject, sz:integer, oz:integer )\n    Subtracts each element in a strided array `x` to a corresponding element in\n    a strided array `y` and assigns the results to elements in a strided array\n    `z` using alternative indexing semantics.\n","strided.subBy":"\nstrided.subBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, \n  clbk:Function[, thisArg:any] )\n    Performs element-wise subtraction of two strided arrays via a callback\n    function and assigns each result to an element in an output strided array.\n","strided.subBy.ndarray":"\nstrided.subBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, \n  thisArg:any] )\n    Performs element-wise subtraction of two strided arrays via a callback\n    function and assigns each result to an element in an output strided array\n    using alternative indexing semantics.\n","strided.trunc":"\nstrided.trunc( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  dtypeY:any, y:ArrayLikeObject, strideY:integer )\n    Rounds each element in a strided array `x` toward zero and assigns the\n    results to elements in a strided array `y`.\n","strided.trunc.ndarray":"\nstrided.trunc.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n  strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n  strideY:integer, offsetY:integer )\n    Rounds each element in a strided array `x` toward zero and assigns the\n    results to elements in a strided array `y` using alternative indexing\n    semantics.\n","stridedarray2iterator":"\nstridedarray2iterator( N:integer, src:ArrayLikeObject, stride:integer, \n  offset:integer[, mapFcn:Function[, thisArg:any]] )\n    Returns an iterator which iterates over elements of an array-like object\n    according to specified stride parameters.\n","stridedArrayStream":"\nstridedArrayStream( N:integer, buffer:ArrayLikeObject, stride:integer, \n  offset:integer[, options:Object] )\n    Creates a readable stream from a strided array-like object.\n","stridedArrayStream.factory":"\nstridedArrayStream.factory( [options:Object] )\n    Returns a function for creating readable streams from array-like objects.\n","stridedArrayStream.objectMode":"\nstridedArrayStream.objectMode( N:integer, buffer:ArrayLikeObject, \n  stride:integer, offset:integer[, options:Object] )\n    Returns an \"objectMode\" readable stream from a strided array-like object.\n","string2buffer":"\nstring2buffer( str:string[, encoding:string] )\n    Allocates a buffer containing a provided string.\n","sub2ind":"\nsub2ind( shape:ArrayLike, ...subscript:integer[, options:Object] )\n    Converts subscripts to a linear index.\n","substringAfter":"\nsubstringAfter( str:string, search:string[, fromIndex:integer] )\n    Returns the part of a string after a specified substring.\n","substringAfterLast":"\nsubstringAfterLast( str:string, search:string[, fromIndex:integer] )\n    Returns the part of a string after the last occurrence of a specified\n    substring.\n","substringBefore":"\nsubstringBefore( str:string, search:string )\n    Returns the part of a string before a specified substring.\n","substringBeforeLast":"\nsubstringBeforeLast( str:string, search:string )\n    Returns the part of a string before the last occurrence of a specified\n    substring.\n","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n    Returns a dataset consisting of labeled wireless sensor network data set\n    collected from a multi-hop wireless sensor network deployment using TelosB\n    motes.\n","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n    Returns a dataset consisting of labeled wireless sensor network data set\n    collected from a simple single-hop wireless sensor network deployment using\n    TelosB motes.\n","Symbol":"\nSymbol( [description:string] )\n    Returns a symbol.\n","tabulate":"\ntabulate( collection:Array|TypedArray|Object )\n    Generates a frequency table.\n","tabulateBy":"\ntabulateBy( collection:Array|TypedArray|Object, [options:Object,] \n  indicator:Function )\n    Generates a frequency table according to an indicator function.\n","tabulateByAsync":"\ntabulateByAsync( collection:Array|TypedArray|Object, [options:Object,] \n  indicator:Function, done:Function )\n    Generates a frequency table according to an indicator function.\n","tabulateByAsync.factory":"\ntabulateByAsync.factory( [options:Object,] indicator:Function )\n    Returns a function which generates a frequency table according to an\n    indicator function.\n","thunk":"\nthunk( fcn:Function[, ...args:any] )\n    Returns a thunk.\n","tic":"\ntic()\n    Returns a high-resolution time.\n","timeit":"\ntimeit( code:string, [options:Object,] clbk:Function )\n    Times a snippet.\n","tmpdir":"\ntmpdir()\n    Returns the directory for storing temporary files.\n","toc":"\ntoc( time:Array<integer> )\n    Returns a high-resolution time difference, where `time` is a two-element\n    array with format `[seconds, nanoseconds]`.\n","tokenize":"\ntokenize( str:string[, keepWhitespace:boolean] )\n    Tokenizes a string.\n","transformStream":"\ntransformStream( [options:Object] )\n    Returns a transform stream.\n","transformStream.factory":"\ntransformStream.factory( [options:Object] )\n    Returns a function for creating transform streams.\n","transformStream.objectMode":"\ntransformStream.objectMode( [options:Object] )\n    Returns an \"objectMode\" transform stream.\n","transformStream.ctor":"\ntransformStream.ctor( [options:Object] )\n    Returns a custom transform stream constructor.\n","trim":"\ntrim( str:string )\n    Trims whitespace from the beginning and end of a `string`.\n","truncate":"\ntruncate( str:string, len:integer[, ending:string] )\n    Truncates a string to a specified length.\n","truncateMiddle":"\ntruncateMiddle( str:string, len:integer[, seq:string] )\n    Truncates a string in the middle to a specified length.\n","trycatch":"\ntrycatch( x:Function, y:any )\n    If a function does not throw, returns the function return value; otherwise,\n    returns `y`.\n","trycatchAsync":"\ntrycatchAsync( x:Function, y:any, done:Function )\n    If a function does not return an error, invokes a callback with the function\n    result; otherwise, invokes a callback with a value `y`.\n","tryFunction":"\ntryFunction( fcn:Function[, thisArg:any] )\n    Wraps a function in a try/catch block.\n","tryRequire":"\ntryRequire( id:string )\n    Wraps `require` in a `try/catch` block.\n","trythen":"\ntrythen( x:Function, y:Function )\n    If a function does not throw, returns the function return value; otherwise,\n    returns the value returned by a second function `y`.\n","trythenAsync":"\ntrythenAsync( x:Function, y:Function, done:Function )\n    If a function does not return an error, invokes a callback with the function\n    result; otherwise, invokes a second function `y`.\n","ttest":"\nttest( x:Array<number>[, y:Array<number>][, options:Object] )\n    Computes a one-sample or paired Student's t test.\n","ttest2":"\nttest2( x:Array<number>, y:Array<number>[, options:Object] )\n    Computes a two-sample Student's t test.\n","TWO_PI":"\nTWO_PI\n    The mathematical constant `π` times `2`.\n","typedarray":"\ntypedarray( [dtype:string] )\n    Creates a typed array.\n\ntypedarray( length:integer[, dtype:string] )\n    Returns a typed array having a specified length.\n\ntypedarray( typedarray:TypedArray[, dtype:string] )\n    Creates a typed array from another typed array.\n\ntypedarray( obj:Object[, dtype:string] )\n    Creates a typed array from an array-like object or iterable.\n\ntypedarray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n  dtype:string] )\n    Returns a typed array view of an ArrayBuffer.\n","typedarray2json":"\ntypedarray2json( arr:TypedArray )\n    Returns a JSON representation of a typed array.\n","typedarrayCtors":"\ntypedarrayCtors( dtype:string )\n    Returns a typed array constructor.\n","typedarrayDataTypes":"\ntypedarrayDataTypes()\n    Returns a list of typed array data types.\n","typedarraypool":"\ntypedarraypool( [dtype:string] )\n    Returns an uninitialized typed array from a typed array memory pool.\n\ntypedarraypool( length:integer[, dtype:string] )\n    Returns an uninitialized typed array having a specified length from a typed\n    array memory pool.\n\ntypedarraypool( typedarray:TypedArray[, dtype:string] )\n    Creates a pooled typed array from another typed array.\n\ntypedarraypool( obj:Object[, dtype:string] )\n    Creates a pooled typed array from an array-like object.\n","typedarraypool.malloc":"\ntypedarraypool.malloc( [dtype:string] )\n    Returns an uninitialized typed array from a typed array memory pool.\n\ntypedarraypool.malloc( length:integer[, dtype:string] )\n    Returns a typed array having a specified length from a typed array memory\n    pool.\n\ntypedarraypool.malloc( typedarray:TypedArray[, dtype:string] )\n    Creates a pooled typed array from another typed array.\n\ntypedarraypool.malloc( obj:Object[, dtype:string] )\n    Creates a pooled typed array from an array-like object.\n","typedarraypool.calloc":"\ntypedarraypool.calloc( [dtype:string] )\n    Returns a zero-initialized typed array from a typed array memory pool.\n\ntypedarraypool.calloc( length:integer[, dtype:string] )\n    Returns a zero-initialized typed array having a specified length from a\n    typed array memory pool.\n","typedarraypool.free":"\ntypedarraypool.free( buf:TypedArray|ArrayBuffer )\n    Frees a typed array or typed array buffer for use in a future allocation.\n","typedarraypool.clear":"\ntypedarraypool.clear()\n    Clears the typed array pool allowing garbage collection of previously\n    allocated (and currently free) array buffers.\n","typedarraypool.highWaterMark":"\ntypedarraypool.highWaterMark\n    Read-only property returning the pool's high water mark.\n","typedarraypool.nbytes":"\ntypedarraypool.nbytes\n    Read-only property returning the total number of allocated bytes.\n","typedarraypool.factory":"\ntypedarraypool.factory( [options:Object] )\n    Creates a typed array pool.\n","typemax":"\ntypemax( dtype:string )\n    Returns the maximum value of a specified numeric type.\n","typemin":"\ntypemin( dtype:string )\n    Returns the minimum value of a specified numeric type.\n","typeOf":"\ntypeOf( value:any )\n    Determines a value's type.\n","UINT8_MAX":"\nUINT8_MAX\n    Maximum unsigned 8-bit integer.\n","UINT8_NUM_BYTES":"\nUINT8_NUM_BYTES\n    Size (in bytes) of an 8-bit unsigned integer.\n","Uint8Array":"\nUint8Array()\n    A typed array constructor which returns a typed array representing an array\n    of 8-bit unsigned integers in the platform byte order.\n\nUint8Array( length:integer )\n    Returns a typed array having a specified length.\n\nUint8Array( typedarray:TypedArray )\n    Creates a typed array from another typed array.\n\nUint8Array( obj:Object )\n    Creates a typed array from an array-like object or iterable.\n\nUint8Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a typed array view of an ArrayBuffer.\n","Uint8Array.from":"\nUint8Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n    Creates a new typed array from an array-like object or an iterable.\n","Uint8Array.of":"\nUint8Array.of( element0:number[, element1:number[, ...elementN:number]] )\n    Creates a new typed array from a variable number of arguments.\n","Uint8Array.BYTES_PER_ELEMENT":"\nUint8Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Uint8Array.name":"\nUint8Array.name\n    Typed array constructor name.\n","Uint8Array.prototype.buffer":"\nUint8Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n","Uint8Array.prototype.byteLength":"\nUint8Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n","Uint8Array.prototype.byteOffset":"\nUint8Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n","Uint8Array.prototype.BYTES_PER_ELEMENT":"\nUint8Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Uint8Array.prototype.length":"\nUint8Array.prototype.length\n    Read-only property which returns the number of view elements.\n","Uint8Array.prototype.copyWithin":"\nUint8Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint8Array.prototype.entries":"\nUint8Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","Uint8Array.prototype.every":"\nUint8Array.prototype.every( predicate:Function[, thisArg:Any] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n","Uint8Array.prototype.fill":"\nUint8Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n","Uint8Array.prototype.filter":"\nUint8Array.prototype.filter( predicate:Function[, thisArg:Any] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n","Uint8Array.prototype.find":"\nUint8Array.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n","Uint8Array.prototype.findIndex":"\nUint8Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n","Uint8Array.prototype.forEach":"\nUint8Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n    Invokes a callback for each array element.\n","Uint8Array.prototype.includes":"\nUint8Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a search element.\n","Uint8Array.prototype.indexOf":"\nUint8Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n","Uint8Array.prototype.join":"\nUint8Array.prototype.join( [separator:string] )\n    Serializes an array by joining all array elements as a string.\n","Uint8Array.prototype.keys":"\nUint8Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n","Uint8Array.prototype.lastIndexOf":"\nUint8Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n","Uint8Array.prototype.map":"\nUint8Array.prototype.map( fcn:Function[, thisArg:Any] )\n    Maps each array element to an element in a new typed array.\n","Uint8Array.prototype.reduce":"\nUint8Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n","Uint8Array.prototype.reduceRight":"\nUint8Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n","Uint8Array.prototype.reverse":"\nUint8Array.prototype.reverse()\n    Reverses an array *in-place*.\n","Uint8Array.prototype.set":"\nUint8Array.prototype.set( arr:ArrayLike[, offset:integer] )\n    Sets array elements.\n","Uint8Array.prototype.slice":"\nUint8Array.prototype.slice( [begin:integer[, end:integer]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n","Uint8Array.prototype.some":"\nUint8Array.prototype.some( predicate:Function[, thisArg:Any] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n","Uint8Array.prototype.sort":"\nUint8Array.prototype.sort( [compareFunction:Function] )\n    Sorts an array *in-place*.\n","Uint8Array.prototype.subarray":"\nUint8Array.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n","Uint8Array.prototype.toLocaleString":"\nUint8Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n    Serializes an array as a locale-specific string.\n","Uint8Array.prototype.toString":"\nUint8Array.prototype.toString()\n    Serializes an array as a string.\n","Uint8Array.prototype.values":"\nUint8Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n","Uint8ClampedArray":"\nUint8ClampedArray()\n    A typed array constructor which returns a typed array representing an array\n    of 8-bit unsigned integers in the platform byte order clamped to 0-255.\n\nUint8ClampedArray( length:integer )\n    Returns a typed array having a specified length.\n\nUint8ClampedArray( typedarray:TypedArray )\n    Creates a typed array from another typed array.\n\nUint8ClampedArray( obj:Object )\n    Creates a typed array from an array-like object or iterable.\n\nUint8ClampedArray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a typed array view of an ArrayBuffer.\n","Uint8ClampedArray.from":"\nUint8ClampedArray.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n    Creates a new typed array from an array-like object or an iterable.\n","Uint8ClampedArray.of":"\nUint8ClampedArray.of( element0:number[, element1:number[, ...elementN:number]] )\n    Creates a new typed array from a variable number of arguments.\n","Uint8ClampedArray.BYTES_PER_ELEMENT":"\nUint8ClampedArray.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Uint8ClampedArray.name":"\nUint8ClampedArray.name\n    Typed array constructor name.\n","Uint8ClampedArray.prototype.buffer":"\nUint8ClampedArray.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n","Uint8ClampedArray.prototype.byteLength":"\nUint8ClampedArray.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n","Uint8ClampedArray.prototype.byteOffset":"\nUint8ClampedArray.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n","Uint8ClampedArray.prototype.BYTES_PER_ELEMENT":"\nUint8ClampedArray.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Uint8ClampedArray.prototype.length":"\nUint8ClampedArray.prototype.length\n    Read-only property which returns the number of view elements.\n","Uint8ClampedArray.prototype.copyWithin":"\nUint8ClampedArray.prototype.copyWithin( target:integer, start:integer[, \n  end:integer] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint8ClampedArray.prototype.entries":"\nUint8ClampedArray.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","Uint8ClampedArray.prototype.every":"\nUint8ClampedArray.prototype.every( predicate:Function[, thisArg:Any] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n","Uint8ClampedArray.prototype.fill":"\nUint8ClampedArray.prototype.fill( value:number[, start:integer[, end:integer]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n","Uint8ClampedArray.prototype.filter":"\nUint8ClampedArray.prototype.filter( predicate:Function[, thisArg:Any] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n","Uint8ClampedArray.prototype.find":"\nUint8ClampedArray.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n","Uint8ClampedArray.prototype.findIndex":"\nUint8ClampedArray.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n","Uint8ClampedArray.prototype.forEach":"\nUint8ClampedArray.prototype.forEach( fcn:Function[, thisArg:Any] )\n    Invokes a callback for each array element.\n","Uint8ClampedArray.prototype.includes":"\nUint8ClampedArray.prototype.includes( searchElement:number[, \n  fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a search element.\n","Uint8ClampedArray.prototype.indexOf":"\nUint8ClampedArray.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n","Uint8ClampedArray.prototype.join":"\nUint8ClampedArray.prototype.join( [separator:string] )\n    Serializes an array by joining all array elements as a string.\n","Uint8ClampedArray.prototype.keys":"\nUint8ClampedArray.prototype.keys()\n    Returns an iterator for iterating over array keys.\n","Uint8ClampedArray.prototype.lastIndexOf":"\nUint8ClampedArray.prototype.lastIndexOf( searchElement:number[, \n  fromIndex:integer] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n","Uint8ClampedArray.prototype.map":"\nUint8ClampedArray.prototype.map( fcn:Function[, thisArg:Any] )\n    Maps each array element to an element in a new typed array.\n","Uint8ClampedArray.prototype.reduce":"\nUint8ClampedArray.prototype.reduce( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n","Uint8ClampedArray.prototype.reduceRight":"\nUint8ClampedArray.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n","Uint8ClampedArray.prototype.reverse":"\nUint8ClampedArray.prototype.reverse()\n    Reverses an array *in-place*.\n","Uint8ClampedArray.prototype.set":"\nUint8ClampedArray.prototype.set( arr:ArrayLike[, offset:integer] )\n    Sets array elements.\n","Uint8ClampedArray.prototype.slice":"\nUint8ClampedArray.prototype.slice( [begin:integer[, end:integer]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n","Uint8ClampedArray.prototype.some":"\nUint8ClampedArray.prototype.some( predicate:Function[, thisArg:Any] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n","Uint8ClampedArray.prototype.sort":"\nUint8ClampedArray.prototype.sort( [compareFunction:Function] )\n    Sorts an array *in-place*.\n","Uint8ClampedArray.prototype.subarray":"\nUint8ClampedArray.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n","Uint8ClampedArray.prototype.toLocaleString":"\nUint8ClampedArray.prototype.toLocaleString( [locales:string|Array[, \n  options:Object]] )\n    Serializes an array as a locale-specific string.\n","Uint8ClampedArray.prototype.toString":"\nUint8ClampedArray.prototype.toString()\n    Serializes an array as a string.\n","Uint8ClampedArray.prototype.values":"\nUint8ClampedArray.prototype.values()\n    Returns an iterator for iterating over array elements.\n","UINT16_MAX":"\nUINT16_MAX\n    Maximum unsigned 16-bit integer.\n","UINT16_NUM_BYTES":"\nUINT16_NUM_BYTES\n    Size (in bytes) of a 16-bit unsigned integer.\n","Uint16Array":"\nUint16Array()\n    A typed array constructor which returns a typed array representing an array\n    of 16-bit unsigned integers in the platform byte order.\n\nUint16Array( length:integer )\n    Returns a typed array having a specified length.\n\nUint16Array( typedarray:TypedArray )\n    Creates a typed array from another typed array.\n\nUint16Array( obj:Object )\n    Creates a typed array from an array-like object or iterable.\n\nUint16Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a typed array view of an ArrayBuffer.\n","Uint16Array.from":"\nUint16Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n    Creates a new typed array from an array-like object or an iterable.\n","Uint16Array.of":"\nUint16Array.of( element0:number[, element1:number[, ...elementN:number]] )\n    Creates a new typed array from a variable number of arguments.\n","Uint16Array.BYTES_PER_ELEMENT":"\nUint16Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Uint16Array.name":"\nUint16Array.name\n    Typed array constructor name.\n","Uint16Array.prototype.buffer":"\nUint16Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n","Uint16Array.prototype.byteLength":"\nUint16Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n","Uint16Array.prototype.byteOffset":"\nUint16Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n","Uint16Array.prototype.BYTES_PER_ELEMENT":"\nUint16Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Uint16Array.prototype.length":"\nUint16Array.prototype.length\n    Read-only property which returns the number of view elements.\n","Uint16Array.prototype.copyWithin":"\nUint16Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint16Array.prototype.entries":"\nUint16Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","Uint16Array.prototype.every":"\nUint16Array.prototype.every( predicate:Function[, thisArg:Any] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n","Uint16Array.prototype.fill":"\nUint16Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n","Uint16Array.prototype.filter":"\nUint16Array.prototype.filter( predicate:Function[, thisArg:Any] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n","Uint16Array.prototype.find":"\nUint16Array.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n","Uint16Array.prototype.findIndex":"\nUint16Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n","Uint16Array.prototype.forEach":"\nUint16Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n    Invokes a callback for each array element.\n","Uint16Array.prototype.includes":"\nUint16Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a search element.\n","Uint16Array.prototype.indexOf":"\nUint16Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n","Uint16Array.prototype.join":"\nUint16Array.prototype.join( [separator:string] )\n    Serializes an array by joining all array elements as a string.\n","Uint16Array.prototype.keys":"\nUint16Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n","Uint16Array.prototype.lastIndexOf":"\nUint16Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n","Uint16Array.prototype.map":"\nUint16Array.prototype.map( fcn:Function[, thisArg:Any] )\n    Maps each array element to an element in a new typed array.\n","Uint16Array.prototype.reduce":"\nUint16Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n","Uint16Array.prototype.reduceRight":"\nUint16Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n","Uint16Array.prototype.reverse":"\nUint16Array.prototype.reverse()\n    Reverses an array *in-place*.\n","Uint16Array.prototype.set":"\nUint16Array.prototype.set( arr:ArrayLike[, offset:integer] )\n    Sets array elements.\n","Uint16Array.prototype.slice":"\nUint16Array.prototype.slice( [begin:integer[, end:integer]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n","Uint16Array.prototype.some":"\nUint16Array.prototype.some( predicate:Function[, thisArg:Any] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n","Uint16Array.prototype.sort":"\nUint16Array.prototype.sort( [compareFunction:Function] )\n    Sorts an array *in-place*.\n","Uint16Array.prototype.subarray":"\nUint16Array.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n","Uint16Array.prototype.toLocaleString":"\nUint16Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n    Serializes an array as a locale-specific string.\n","Uint16Array.prototype.toString":"\nUint16Array.prototype.toString()\n    Serializes an array as a string.\n","Uint16Array.prototype.values":"\nUint16Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n","UINT32_MAX":"\nUINT32_MAX\n    Maximum unsigned 32-bit integer.\n","UINT32_NUM_BYTES":"\nUINT32_NUM_BYTES\n    Size (in bytes) of a 32-bit unsigned integer.\n","Uint32Array":"\nUint32Array()\n    A typed array constructor which returns a typed array representing an array\n    of 32-bit unsigned integers in the platform byte order.\n\nUint32Array( length:integer )\n    Returns a typed array having a specified length.\n\nUint32Array( typedarray:TypedArray )\n    Creates a typed array from another typed array.\n\nUint32Array( obj:Object )\n    Creates a typed array from an array-like object or iterable.\n\nUint32Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a typed array view of an ArrayBuffer.\n","Uint32Array.from":"\nUint32Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n    Creates a new typed array from an array-like object or an iterable.\n","Uint32Array.of":"\nUint32Array.of( element0:number[, element1:number[, ...elementN:number]] )\n    Creates a new typed array from a variable number of arguments.\n","Uint32Array.BYTES_PER_ELEMENT":"\nUint32Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Uint32Array.name":"\nUint32Array.name\n    Typed array constructor name.\n","Uint32Array.prototype.buffer":"\nUint32Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n","Uint32Array.prototype.byteLength":"\nUint32Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n","Uint32Array.prototype.byteOffset":"\nUint32Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n","Uint32Array.prototype.BYTES_PER_ELEMENT":"\nUint32Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Uint32Array.prototype.length":"\nUint32Array.prototype.length\n    Read-only property which returns the number of view elements.\n","Uint32Array.prototype.copyWithin":"\nUint32Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint32Array.prototype.entries":"\nUint32Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","Uint32Array.prototype.every":"\nUint32Array.prototype.every( predicate:Function[, thisArg:Any] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n","Uint32Array.prototype.fill":"\nUint32Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n","Uint32Array.prototype.filter":"\nUint32Array.prototype.filter( predicate:Function[, thisArg:Any] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n","Uint32Array.prototype.find":"\nUint32Array.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n","Uint32Array.prototype.findIndex":"\nUint32Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n","Uint32Array.prototype.forEach":"\nUint32Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n    Invokes a callback for each array element.\n","Uint32Array.prototype.includes":"\nUint32Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a search element.\n","Uint32Array.prototype.indexOf":"\nUint32Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n","Uint32Array.prototype.join":"\nUint32Array.prototype.join( [separator:string] )\n    Serializes an array by joining all array elements as a string.\n","Uint32Array.prototype.keys":"\nUint32Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n","Uint32Array.prototype.lastIndexOf":"\nUint32Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n","Uint32Array.prototype.map":"\nUint32Array.prototype.map( fcn:Function[, thisArg:Any] )\n    Maps each array element to an element in a new typed array.\n","Uint32Array.prototype.reduce":"\nUint32Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n","Uint32Array.prototype.reduceRight":"\nUint32Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n","Uint32Array.prototype.reverse":"\nUint32Array.prototype.reverse()\n    Reverses an array *in-place*.\n","Uint32Array.prototype.set":"\nUint32Array.prototype.set( arr:ArrayLike[, offset:integer] )\n    Sets array elements.\n","Uint32Array.prototype.slice":"\nUint32Array.prototype.slice( [begin:integer[, end:integer]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n","Uint32Array.prototype.some":"\nUint32Array.prototype.some( predicate:Function[, thisArg:Any] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n","Uint32Array.prototype.sort":"\nUint32Array.prototype.sort( [compareFunction:Function] )\n    Sorts an array *in-place*.\n","Uint32Array.prototype.subarray":"\nUint32Array.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n","Uint32Array.prototype.toLocaleString":"\nUint32Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n    Serializes an array as a locale-specific string.\n","Uint32Array.prototype.toString":"\nUint32Array.prototype.toString()\n    Serializes an array as a string.\n","Uint32Array.prototype.values":"\nUint32Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n","umask":"\numask( [mask:integer|string,] [options:Object] )\n    Returns the current process mask, if not provided a mask; otherwise, sets\n    the process mask and returns the previous mask.\n","uncapitalize":"\nuncapitalize( str:string )\n    Lowercases the first character of a string.\n","uncapitalizeKeys":"\nuncapitalizeKeys( obj:Object )\n    Converts the first letter of each object key to lowercase.\n","uncurry":"\nuncurry( fcn:Function[, arity:integer, ][thisArg:any] )\n    Transforms a curried function into a function invoked with multiple\n    arguments.\n","uncurryRight":"\nuncurryRight( fcn:Function[, arity:integer, ][thisArg:any] )\n    Transforms a curried function into a function invoked with multiple\n    arguments.\n","UNICODE_MAX":"\nUNICODE_MAX\n    Maximum Unicode code point.\n","UNICODE_MAX_BMP":"\nUNICODE_MAX_BMP\n    Maximum Unicode code point in the Basic Multilingual Plane (BMP).\n","UnicodeColumnChartSparkline":"\nUnicodeColumnChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n    Returns a sparkline column chart instance.\n","UnicodeLineChartSparkline":"\nUnicodeLineChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n    Returns a sparkline line chart instance.\n","UnicodeSparkline":"\nUnicodeSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n    Returns a Unicode sparkline instance.\n","UnicodeTristateChartSparkline":"\nUnicodeTristateChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n    Returns a sparkline tristate chart instance.\n","UnicodeUpDownChartSparkline":"\nUnicodeUpDownChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n    Returns a sparkline up/down chart instance.\n","UnicodeWinLossChartSparkline":"\nUnicodeWinLossChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n    Returns a sparkline win/loss chart instance.\n","unlink":"\nunlink( path:string|Buffer|integer, clbk:Function )\n    Asynchronously removes a directory entry.\n","unlink.sync":"\nunlink.sync( path:string|Buffer|integer )\n    Synchronously removes a directory entry.\n","unshift":"\nunshift( collection:Array|TypedArray|Object, ...items:any )\n    Adds one or more elements to the beginning of a collection.\n","until":"\nuntil( predicate:Function, fcn:Function[, thisArg:any] )\n    Invokes a function until a test condition is true.\n","untilAsync":"\nuntilAsync( predicate:Function, fcn:Function, done:Function[, thisArg:any] )\n    Invokes a function until a test condition is true.\n","untilEach":"\nuntilEach( collection:Array|TypedArray|Object, predicate:Function, \n  fcn:Function[, thisArg:any] )\n    Until a test condition is true, invokes a function for each element in a\n    collection.\n","untilEachRight":"\nuntilEachRight( collection:Array|TypedArray|Object, predicate:Function, \n  fcn:Function[, thisArg:any] )\n    Until a test condition is true, invokes a function for each element in a\n    collection, iterating from right to left.\n","unzip":"\nunzip( arr:Array[, idx:Array<number>] )\n    Unzips a zipped array (i.e., a nested array of tuples).\n","uppercase":"\nuppercase( str:string )\n    Converts a string to uppercase.\n","uppercaseKeys":"\nuppercaseKeys( obj:Object )\n    Converts each object key to uppercase.\n","US_STATES_ABBR":"\nUS_STATES_ABBR()\n    Returns a list of US state two-letter abbreviations in alphabetical order\n    according to state name.\n","US_STATES_CAPITALS":"\nUS_STATES_CAPITALS()\n    Returns a list of US state capitals in alphabetical order according to state\n    name.\n","US_STATES_CAPITALS_NAMES":"\nUS_STATES_CAPITALS_NAMES()\n    Returns an object mapping US state capitals to state names.\n","US_STATES_NAMES":"\nUS_STATES_NAMES()\n    Returns a list of US state names in alphabetical order.\n","US_STATES_NAMES_CAPITALS":"\nUS_STATES_NAMES_CAPITALS()\n    Returns an object mapping US state names to state capitals.\n","utf16ToUTF8Array":"\nutf16ToUTF8Array( str:string )\n    Converts a UTF-16 encoded string to an array of integers using UTF-8\n    encoding.\n","vartest":"\nvartest( x:Array<number>, y:Array<number>[, options:Object] )\n    Computes a two-sample F-test for equal variances.\n","waterfall":"\nwaterfall( fcns:Array<Function>, clbk:Function[, thisArg:any] )\n    Executes functions in series, passing the results of one function as\n    arguments to the next function.\n","waterfall.factory":"\nwaterfall.factory( fcns:Array<Function>, clbk:Function[, thisArg:any] )\n    Returns a reusable waterfall function.\n","WebAssemblyMemory":"\nWebAssemblyMemory( descriptor:Object )\n    WebAssembly memory constructor.\n","WebAssemblyMemory.prototype.buffer":"\nWebAssemblyMemory.prototype.buffer\n    Read-only property which returns the ArrayBuffer (or SharedArrayBuffer)\n    referenced by the memory instance.\n","WebAssemblyMemory.prototype.grow":"\nWebAssemblyMemory.prototype.grow( delta:integer )\n    Increases the size of the memory instance by a specified number of\n    WebAssembly pages (i.e., 64KiB).\n","whileAsync":"\nwhileAsync( predicate:Function, fcn:Function, done:Function[, thisArg:any] )\n    Invokes a function while a test condition is true.\n","whileEach":"\nwhileEach( collection:Array|TypedArray|Object, predicate:Function, \n  fcn:Function[, thisArg:any] )\n    While a test condition is true, invokes a function for each element in a\n    collection.\n","whileEachRight":"\nwhileEachRight( collection:Array|TypedArray|Object, predicate:Function, \n  fcn:Function[, thisArg:any] )\n    While a test condition is true, invokes a function for each element in a\n    collection, iterating from right to left.\n","whilst":"\nwhilst( predicate:Function, fcn:Function[, thisArg:any] )\n    Invokes a function while a test condition is true.\n","wilcoxon":"\nwilcoxon( x:Array|TypedArray[, y:Array|TypedArray][, options:Object] )\n    Computes a one-sample or paired Wilcoxon signed rank test.\n","writableProperties":"\nwritableProperties( value:any )\n    Returns an array of an object's own writable property names and symbols.\n","writablePropertiesIn":"\nwritablePropertiesIn( value:any )\n    Returns an array of an object's own and inherited writable property names\n    and symbols.\n","writablePropertyNames":"\nwritablePropertyNames( value:any )\n    Returns an array of an object's own writable property names.\n","writablePropertyNamesIn":"\nwritablePropertyNamesIn( value:any )\n    Returns an array of an object's own and inherited writable property names.\n","writablePropertySymbols":"\nwritablePropertySymbols( value:any )\n    Returns an array of an object's own writable symbol properties.\n","writablePropertySymbolsIn":"\nwritablePropertySymbolsIn( value:any )\n    Returns an array of an object's own and inherited writable symbol\n    properties.\n","writeFile":"\nwriteFile( file:string|Buffer|integer, data:string|Buffer[, \n  options:Object|string], clbk:Function )\n    Asynchronously writes data to a file.\n","writeFile.sync":"\nwriteFile.sync( file:string|Buffer|integer, data:string|Buffer[, \n  options:Object|string] )\n    Synchronously writes data to a file.\n","zip":"\nzip( ...arr:Array[, options:Object] )\n    Generates array tuples from input arrays.\n","ztest":"\nztest( x:Array<number>, sigma:number[, options:Object] )\n    Computes a one-sample z-test.\n","ztest2":"\nztest2( x:Array<number>, y:Array<number>, sigmax:number, sigmay:number[, \n  options:Object] )\n    Computes a two-sample z-test.\n"}
+{"abs":"\nabs( x:ndarray|ArrayLikeObject|number[, options:Object] )\n    Computes the absolute value.\n","abs.assign":"\nabs.assign( x:ndarray|ArrayLikeObject, y:ndarray|ArrayLikeObject )\n    Computes the absolute value and assigns results to a provided output array.\n","acartesianPower":"\nacartesianPower( x:ArrayLikeObject, n:integer )\n    Returns the Cartesian power.\n","acartesianProduct":"\nacartesianProduct( x1:ArrayLikeObject, x2:ArrayLikeObject )\n    Returns the Cartesian product.\n","acartesianSquare":"\nacartesianSquare( x:ArrayLikeObject )\n    Returns the Cartesian square.\n","acronym":"\nacronym( str:string[, options:Object] )\n    Generates an acronym for a given string.\n","aempty":"\naempty( length:integer[, dtype:string] )\n    Creates an uninitialized array having a specified length.\n","aemptyLike":"\naemptyLike( x:TypedArray|Array[, dtype:string] )\n    Creates an uninitialized array having the same length and data type as a\n    provided input array.\n","AFINN_96":"\nAFINN_96()\n    Returns a list of English words rated for valence.\n","AFINN_111":"\nAFINN_111()\n    Returns a list of English words rated for valence.\n","afull":"\nafull( length:integer, value:any[, dtype:string] )\n    Returns a filled array having a specified length.\n","afullLike":"\nafullLike( x:TypedArray|Array[, dtype:string] )\n    Returns a filled array having the same length and data type as a provided\n    input array.\n","alias2pkg":"\nalias2pkg( alias:string )\n    Returns the package name associated with a provided alias.\n","alias2related":"\nalias2related( alias:string )\n    Returns aliases related to a specified alias.\n","alias2standalone":"\nalias2standalone( alias:string )\n    Returns the standalone package name associated with a provided alias.\n","aliases":"\naliases( [namespace:string] )\n    Returns a list of standard library aliases.\n","allocUnsafe":"\nallocUnsafe( size:integer )\n    Allocates a buffer having a specified number of bytes.\n","amskfilter":"\namskfilter( x:Array|TypedArray|Object, mask:Array|TypedArray|Object )\n    Returns a new array by applying a mask to a provided input array.\n","amskput":"\namskput( x:ArrayLikeObject, mask:ArrayLikeObject, values:ArrayLikeObject[, \n  options:Object] )\n    Replaces elements of an array with provided values according to a provided\n    mask array.\n","amskreject":"\namskreject( x:Array|TypedArray|Object, mask:Array|TypedArray|Object )\n    Returns a new array by applying a mask to a provided input array.\n","anans":"\nanans( length:integer[, dtype:string] )\n    Returns an array filled with NaNs and having a specified length.\n","anansLike":"\nanansLike( x:TypedArray|Array[, dtype:string] )\n    Returns an array filled with NaNs and having the same length and data type\n    as a provided input array.\n","anova1":"\nanova1( x:Array<number>, factor:Array[, options:Object] )\n    Performs a one-way analysis of variance.\n","ANSCOMBES_QUARTET":"\nANSCOMBES_QUARTET()\n    Returns Anscombe's quartet.\n","any":"\nany( collection:Array|TypedArray|Object )\n    Tests whether at least one element in a collection is truthy.\n","anyBy":"\nanyBy( collection:Array|TypedArray|Object, predicate:Function[, thisArg:any ] )\n    Tests whether at least one element in a collection passes a test implemented\n    by a predicate function.\n","anyByAsync":"\nanyByAsync( collection:Array|TypedArray|Object, [options:Object,] \n  predicate:Function, done:Function )\n    Tests whether at least one element in a collection passes a test implemented\n    by a predicate function.\n","anyByAsync.factory":"\nanyByAsync.factory( [options:Object,] predicate:Function )\n    Returns a function which tests whether at least one element in a collection\n    passes a test implemented by a predicate function.\n","anyByRight":"\nanyByRight( collection:Array|TypedArray|Object, predicate:Function[, \n  thisArg:any ] )\n    Tests whether at least one element in a collection passes a test implemented\n    by a predicate function, iterating from right to left.\n","anyByRightAsync":"\nanyByRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n  predicate:Function, done:Function )\n    Tests whether at least one element in a collection passes a test implemented\n    by a predicate function, iterating from right to left.\n","anyByRightAsync.factory":"\nanyByRightAsync.factory( [options:Object,] predicate:Function )\n    Returns a function which tests whether at least one element in a collection\n    passes a test implemented by a predicate function, iterating from right to\n    left.\n","anyInBy":"\nanyInBy( object:Object, predicate:Function[, thisArg:any ] )\n    Tests whether at least one value in an object passes a test implemented by\n    a predicate function.\n","anyOwnBy":"\nanyOwnBy( object:Object, predicate:Function[, thisArg:any ] )\n    Tests whether at least one own property of an object passes a\n    test implemented by a predicate function.\n","aones":"\naones( length:integer[, dtype:string] )\n    Returns an array filled with ones and having a specified length.\n","aonesLike":"\naonesLike( x:TypedArray|Array[, dtype:string] )\n    Returns an array filled with ones and having the same length and data type\n    as a provided input array.\n","aoneTo":"\naoneTo( n:integer[, dtype:string] )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from one.\n","aoneToLike":"\naoneToLike( x:TypedArray|Array[, dtype:string] )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from one and having the same length and data type as a provided\n    input array.\n","APERY":"\nAPERY\n    Apéry's constant.\n","aplace":"\naplace( x:ArrayLikeObject, mask:ArrayLikeObject, values:ArrayLikeObject[, \n  options:Object] )\n    Replaces elements of an array with provided values according to a provided\n    mask array.\n","append":"\nappend( collection1:Array|TypedArray|Object, \n  collection2:Array|TypedArray|Object )\n    Adds the elements of one collection to the end of another collection.\n","aput":"\naput( x:ArrayLikeObject, indices:ArrayLikeObject<integer>, \n  values:ArrayLikeObject[, options:Object] )\n    Replaces specified elements of an array with provided values.\n","ARCH":"\nARCH\n    Operating system CPU architecture for which the JavaScript runtime binary\n    was compiled.\n","argumentFunction":"\nargumentFunction( idx:integer )\n    Returns a function which always returns a specified argument.\n","ARGV":"\nARGV\n    An array containing command-line arguments passed when launching the calling\n    process.\n","array":"\narray( [buffer:Array|TypedArray|Buffer|ndarray,] [options:Object] )\n    Returns a multidimensional array.\n","array2buffer":"\narray2buffer( arr:Array<integer> )\n    Allocates a buffer using an octet array.\n","array2fancy":"\narray2fancy( x:Array|TypedArray|Object[, options:Object] )\n    Converts an array to an object supporting fancy indexing.\n","array2fancy.factory":"\narray2fancy.factory( [options:Object] )\n    Returns a function for converting an array to an object supporting fancy\n    indexing.\n","array2fancy.idx":"\narray2fancy.idx( x:Array|TypedArray|Object[, options:Object] )\n    Wraps a provided array as an array index object.\n","array2iterator":"\narray2iterator( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )\n    Returns an iterator which iterates over the elements of an array-like\n    object.\n","array2iteratorRight":"\narray2iteratorRight( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )\n    Returns an iterator which iterates from right to left over the elements of\n    an array-like object.\n","ArrayBuffer":"\nArrayBuffer( size:integer )\n    Returns an array buffer having a specified number of bytes.\n","ArrayBuffer.length":"\nArrayBuffer.length\n    Number of input arguments the constructor accepts.\n","ArrayBuffer.isView":"\nArrayBuffer.isView( arr:any )\n    Returns a boolean indicating if provided an array buffer view.\n","ArrayBuffer.prototype.byteLength":"\nArrayBuffer.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the array buffer.\n","ArrayBuffer.prototype.slice":"\nArrayBuffer.prototype.slice( [start:integer[, end:integer]] )\n    Copies the bytes of an array buffer to a new array buffer.\n","arraybuffer2buffer":"\narraybuffer2buffer( buf:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Allocates a buffer from an ArrayBuffer.\n","arrayCtors":"\narrayCtors( dtype:string )\n    Returns an array constructor.\n","arrayDataType":"\narrayDataType( array:any )\n    Returns the data type of an array.\n","arrayDataTypes":"\narrayDataTypes( [kind:string] )\n    Returns a list of array data types.\n","ArrayIndex":"\nArrayIndex( x:Array|TypedArray|Object[, options:Object] )\n    Wraps a provided array as an array index object.\n","ArrayIndex.free":"\nArrayIndex.free( id:string )\n    Frees the instance associated with a provided identifier.\n","ArrayIndex.get":"\nArrayIndex.get( id:string )\n    Returns the array associated with the instance having a provided identifier.\n","ArrayIndex.prototype.data":"\nArrayIndex.prototype.data\n    Read-only property returning the underlying index array.\n","ArrayIndex.prototype.dtype":"\nArrayIndex.prototype.dtype\n    Read-only property returning the underlying data type of the index array.\n","ArrayIndex.prototype.id":"\nArrayIndex.prototype.id\n    Read-only property returning the unique identifier associated with an\n    instance.\n","ArrayIndex.prototype.isCached":"\nArrayIndex.prototype.isCached\n    Read-only property returning a boolean indicating whether an array index is\n    actively cached.\n","ArrayIndex.prototype.type":"\nArrayIndex.prototype.type\n    Read-only property returning the array index type.\n","ArrayIndex.prototype.toString":"\nArrayIndex.prototype.toString()\n    Serializes an instance as a string.\n","ArrayIndex.prototype.toJSON":"\nArrayIndex.prototype.toJSON()\n    Serializes an instance as a JSON object.\n","arrayMinDataType":"\narrayMinDataType( value:any )\n    Returns the minimum array data type of the closest \"kind\" necessary for\n    storing a provided scalar value.\n","arrayMostlySafeCasts":"\narrayMostlySafeCasts( [dtype:any] )\n    Returns a list of array data types to which a provided array data type can\n    be safely cast and, for floating-point data types, can be downcast.\n","arrayNextDataType":"\narrayNextDataType( [dtype:string] )\n    Returns the next larger array data type of the same kind.\n","arrayPromotionRules":"\narrayPromotionRules( [dtype1:any, dtype2:any] )\n    Returns the array data type with the smallest size and closest \"kind\" to\n    which array data types can be safely cast.\n","arraySafeCasts":"\narraySafeCasts( [dtype:any] )\n    Returns a list of array data types to which a provided array data type can\n    be safely cast.\n","arraySameKindCasts":"\narraySameKindCasts( [dtype:any] )\n    Returns a list of array data types to which a provided array data type can\n    be safely cast or cast within the same \"kind\".\n","arrayShape":"\narrayShape( arr:ArrayLikeObject )\n    Determines array dimensions.\n","arrayStream":"\narrayStream( src:ArrayLikeObject[, options:Object] )\n    Creates a readable stream from an array-like object.\n","arrayStream.factory":"\narrayStream.factory( [options:Object] )\n    Returns a function for creating readable streams from array-like objects.\n","arrayStream.objectMode":"\narrayStream.objectMode( src:ArrayLikeObject[, options:Object] )\n    Returns an \"objectMode\" readable stream from an array-like object.\n","arrayview2iterator":"\narrayview2iterator( src:ArrayLikeObject[, begin:integer[, end:integer]][, \n  mapFcn:Function[, thisArg:any]] )\n    Returns an iterator which iterates over the elements of an array-like object\n    view.\n","arrayview2iteratorRight":"\narrayview2iteratorRight( src:ArrayLikeObject[, begin:integer[, end:integer]][, \n  mapFcn:Function[, thisArg:any]] )\n    Returns an iterator which iterates from right to left over the elements of\n    an array-like object view.\n","aslice":"\naslice( x:ArrayLikeObject[, start:integer[, end:integer]] )\n    Returns a shallow copy of a portion of an array.\n","AsyncIteratorSymbol":"\nAsyncIteratorSymbol\n    Async iterator symbol.\n","atake":"\natake( x:Array|TypedArray|Object, indices:ArrayLikeObject<integer>[, \n  options:Object] )\n    Takes elements from an array.\n","azeros":"\nazeros( length:integer[, dtype:string] )\n    Returns a zero-filled array having a specified length.\n","azerosLike":"\nazerosLike( x:TypedArray|Array[, dtype:string] )\n    Returns a zero-filled array having the same length and data type as a\n    provided input array.\n","azeroTo":"\nazeroTo( n:integer[, dtype:string] )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from zero.\n","azeroToLike":"\nazeroToLike( x:TypedArray|Array[, dtype:string] )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from zero and having the same length and data type as a provided\n    input array.\n","bartlettTest":"\nbartlettTest( ...x:Array[, options:Object] )\n    Computes Bartlett’s test for equal variances.\n","base.abs":"\nbase.abs( x:number )\n    Computes the absolute value of a double-precision floating-point number `x`.\n","base.abs2":"\nbase.abs2( x:number )\n    Computes the squared absolute value of a double-precision floating-point\n    `x`.\n","base.abs2f":"\nbase.abs2f( x:number )\n    Computes the squared absolute value of a single-precision floating-point\n    `x`.\n","base.absdiff":"\nbase.absdiff( x:number, y:number )\n    Computes the absolute difference.\n","base.absf":"\nbase.absf( x:number )\n    Computes the absolute value of a single-precision floating-point number `x`.\n","base.acartesianPower":"\nbase.acartesianPower( x:ArrayLikeObject, n:integer )\n    Returns the Cartesian power.\n","base.acartesianProduct":"\nbase.acartesianProduct( x1:ArrayLikeObject, x2:ArrayLikeObject )\n    Returns the Cartesian product.\n","base.acartesianSquare":"\nbase.acartesianSquare( x:ArrayLikeObject )\n    Returns the Cartesian square.\n","base.acos":"\nbase.acos( x:number )\n    Compute the arccosine of a double-precision floating-point number.\n","base.acosd":"\nbase.acosd( x:number )\n    Computes the arccosine (in degrees) of a double-precision floating-point \n    number.\n","base.acosf":"\nbase.acosf( x:number )\n    Computes the arccosine of a single-precision floating-point number.\n","base.acosh":"\nbase.acosh( x:number )\n    Computes the hyperbolic arccosine of a double-precision floating-point\n    number.\n","base.acot":"\nbase.acot( x:number )\n    Computes the inverse cotangent of a double-precision floating-point number.\n","base.acotd":"\nbase.acotd( x:number )\n    Computes the arccotangent (in degrees) of a double-precision floating-point\n    number.\n","base.acotf":"\nbase.acotf( x:number )\n    Computes the inverse cotangent of a single-precision floating-point number.\n","base.acoth":"\nbase.acoth( x:number )\n    Computes the inverse hyperbolic cotangent of a double-precision floating-\n    point number.\n","base.acovercos":"\nbase.acovercos( x:number )\n    Computes the inverse coversed cosine.\n","base.acoversin":"\nbase.acoversin( x:number )\n    Computes the inverse coversed sine.\n","base.acsc":"\nbase.acsc( x:number )\n    Computes the arccosecant of a number.\n","base.acscd":"\nbase.acscd( x:number )\n    Computes the arccosecant of (in degrees) a double-precision floating-point\n    number.\n","base.acscdf":"\nbase.acscdf( x:number )\n    Computes the arccosecant (in degrees) of a single-precision floating-point\n    number.\n","base.acscf":"\nbase.acscf( x:number )\n    Computes the arccosecant of a single-precision floating-point number.\n","base.acsch":"\nbase.acsch( x:number )\n    Computes the hyperbolic arccosecant of a number.\n","base.add":"\nbase.add( x:number, y:number )\n    Computes the sum of two double-precision floating-point numbers `x` and `y`.\n","base.add3":"\nbase.add3( x:number, y:number, z:number )\n    Computes the sum of three double-precision floating-point numbers.\n","base.add4":"\nbase.add4( x:number, y:number, z:number, w:number )\n    Computes the sum of four double-precision floating-point numbers.\n","base.add5":"\nbase.add5( x:number, y:number, z:number, w:number, u:number )\n    Computes the sum of five double-precision floating-point numbers.\n","base.addf":"\nbase.addf( x:number, y:number )\n    Computes the sum of two single-precision floating-point numbers `x` and `y`.\n","base.afilled":"\nbase.afilled( value:any, len:integer )\n    Returns a filled \"generic\" array.\n","base.afilled2d":"\nbase.afilled2d( value:any, shape:Array<integer> )\n    Returns a filled two-dimensional nested array.\n","base.afilled2dBy":"\nbase.afilled2dBy( shape:Array<integer>, clbk:Function[, thisArg:any] )\n    Returns a filled two-dimensional nested array according to a provided\n    callback function.\n","base.afilled3d":"\nbase.afilled3d( value:any, shape:Array<integer> )\n    Returns a filled three-dimensional nested array.\n","base.afilled3dBy":"\nbase.afilled3dBy( shape:Array<integer>, clbk:Function[, thisArg:any] )\n    Returns a filled three-dimensional nested array according to a provided\n    callback function.\n","base.afilled4d":"\nbase.afilled4d( value:any, shape:Array<integer> )\n    Returns a filled four-dimensional nested array.\n","base.afilled4dBy":"\nbase.afilled4dBy( shape:Array<integer>, clbk:Function[, thisArg:any] )\n    Returns a filled four-dimensional nested array according to a provided\n    callback function.\n","base.afilled5d":"\nbase.afilled5d( value:any, shape:Array<integer> )\n    Returns a filled five-dimensional nested array.\n","base.afilled5dBy":"\nbase.afilled5dBy( shape:Array<integer>, clbk:Function[, thisArg:any] )\n    Returns a filled five-dimensional nested array according to a provided\n    callback function.\n","base.afilledBy":"\nbase.afilledBy( len:integer, clbk:Function[, thisArg:any] )\n    Returns a filled \"generic\" array according to a provided callback function.\n","base.afillednd":"\nbase.afillednd( value:any, shape:Array<integer> )\n    Returns a filled n-dimensional nested array.\n","base.afilledndBy":"\nbase.afilledndBy( shape:Array<integer>, clbk:Function[, thisArg:any] )\n    Returns a filled n-dimensional nested array according to a callback\n    function.\n","base.afilter":"\nbase.afilter( x:Array|TypedArray|Object, predicate:Function[, thisArg:any] )\n    Returns a shallow copy of an array containing only those elements which pass\n    a test implemented by a predicate function.\n","base.afirst":"\nbase.afirst( arr:ArrayLikeObject )\n    Returns the first element of an array-like object.\n","base.aflatten":"\nbase.aflatten( x:Array, shape:Array<integer>, colexicographic:boolean )\n    Flattens an n-dimensional nested array.\n","base.aflatten.assign":"\nbase.aflatten.assign( x:Array, shape:Array<integer>, colexicographic:boolean, \n  out:Collection, stride:integer, offset:integer )\n    Flattens an n-dimensional nested array and assigns elements to a provided\n    output array.\n","base.aflatten2d":"\nbase.aflatten2d( x:Array, shape:Array<integer>, colexicographic:boolean )\n    Flattens a two-dimensional nested array.\n","base.aflatten2d.assign":"\nbase.aflatten2d.assign( x:Array, shape:Array<integer>, colexicographic:boolean, \n  out:Collection, stride:integer, offset:integer )\n    Flattens a two-dimensional nested array and assigns elements to a provided\n    output array.\n","base.aflatten2dBy":"\nbase.aflatten2dBy( x:Array, shape:Array<integer>, colex:boolean, \n  clbk:Function[, thisArg:any] )\n    Flattens a two-dimensional nested array according to a callback function.\n","base.aflatten2dBy.assign":"\nbase.aflatten2dBy.assign( x:Array, shape:Array<integer>, colex:boolean, \n  out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n    Flattens a two-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n","base.aflatten3d":"\nbase.aflatten3d( x:ArrayLikeObject, shape:Array<integer>, \n  colexicographic:boolean )\n    Flattens a three-dimensional nested array.\n","base.aflatten3d.assign":"\nbase.aflatten3d.assign( x:Array, shape:Array<integer>, colexicographic:boolean, \n  out:Collection, stride:integer, offset:integer )\n    Flattens a three-dimensional nested array and assigns elements to a provided\n    output array.\n","base.aflatten3dBy":"\nbase.aflatten3dBy( x:ArrayLikeObject, shape:Array<integer>, colex:boolean, \n  clbk:Function[, thisArg:any] )\n    Flattens a three-dimensional nested array according to a callback function.\n","base.aflatten3dBy.assign":"\nbase.aflatten3dBy.assign( x:Array, shape:Array<integer>, colex:boolean, \n  out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n    Flattens a three-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n","base.aflatten4d":"\nbase.aflatten4d( x:ArrayLikeObject, shape:Array<integer>, \n  colexicographic:boolean )\n    Flattens a four-dimensional nested array.\n","base.aflatten4d.assign":"\nbase.aflatten4d.assign( x:Array, shape:Array<integer>, colexicographic:boolean, \n  out:Collection, stride:integer, offset:integer )\n    Flattens a four-dimensional nested array and assigns elements to a provided\n    output array.\n","base.aflatten4dBy":"\nbase.aflatten4dBy( x:ArrayLikeObject, shape:Array<integer>, colex:boolean, \n  clbk:Function[, thisArg:any] )\n    Flattens a four-dimensional nested array according to a callback function.\n","base.aflatten4dBy.assign":"\nbase.aflatten4dBy.assign( x:Array, shape:Array<integer>, colex:boolean, \n  out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n    Flattens a four-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n","base.aflatten5d":"\nbase.aflatten5d( x:ArrayLikeObject, shape:Array<integer>, \n  colexicographic:boolean )\n    Flattens a five-dimensional nested array.\n","base.aflatten5d.assign":"\nbase.aflatten5d.assign( x:Array, shape:Array<integer>, colexicographic:boolean, \n  out:Collection, stride:integer, offset:integer )\n    Flattens a five-dimensional nested array and assigns elements to a provided\n    output array.\n","base.aflatten5dBy":"\nbase.aflatten5dBy( x:ArrayLikeObject, shape:Array<integer>, colex:boolean, \n  clbk:Function[, thisArg:any] )\n    Flattens a five-dimensional nested array according to a callback function.\n","base.aflatten5dBy.assign":"\nbase.aflatten5dBy.assign( x:Array, shape:Array<integer>, colex:boolean, \n  out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n    Flattens a five-dimensional nested array according to a callback function\n    and assigns elements to a provided output array.\n","base.aflattenBy":"\nbase.aflattenBy( x:Array, shape:Array<integer>, colex:boolean, clbk:Function[, \n  thisArg:any] )\n    Flattens an n-dimensional nested array according to a callback function.\n","base.aflattenBy.assign":"\nbase.aflattenBy.assign( x:Array, shape:Array<integer>, colex:boolean, \n  out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n    Flattens an n-dimensional nested array according to a callback function and\n    assigns elements to a provided output array.\n","base.afliplr2d":"\nbase.afliplr2d( x:ArrayLikeObject )\n    Reverses the order of elements along the last dimension of a two-dimensional\n    nested input array.\n","base.afliplr3d":"\nbase.afliplr3d( x:ArrayLikeObject )\n    Reverses the order of elements along the last dimension of a three-\n    dimensional nested input array.\n","base.afliplr4d":"\nbase.afliplr4d( x:ArrayLikeObject )\n    Reverses the order of elements along the last dimension of a four-\n    dimensional nested input array.\n","base.afliplr5d":"\nbase.afliplr5d( x:ArrayLikeObject )\n    Reverses the order of elements along the last dimension of a five-\n    dimensional nested input array.\n","base.aflipud2d":"\nbase.aflipud2d( x:ArrayLikeObject )\n    Reverses the order of elements along the first dimension of a two-\n    dimensional nested input array.\n","base.aflipud3d":"\nbase.aflipud3d( x:ArrayLikeObject )\n    Reverses the order of elements along the second-to-last dimension of a\n    three-dimensional nested input array.\n","base.aflipud4d":"\nbase.aflipud4d( x:ArrayLikeObject )\n    Reverses the order of elements along the second-to-last dimension of a four-\n    dimensional nested input array.\n","base.aflipud5d":"\nbase.aflipud5d( x:ArrayLikeObject )\n    Reverses the order of elements along the second-to-last dimension of a five-\n    dimensional nested input array.\n","base.ahavercos":"\nbase.ahavercos( x:number )\n    Computes the inverse half-value versed cosine.\n","base.ahaversin":"\nbase.ahaversin( x:number )\n    Computes the inverse half-value versed sine.\n","base.altcase":"\nbase.altcase( str:string )\n    Converts a string to alternate case.\n","base.aones":"\nbase.aones( len:integer )\n    Returns a \"generic\" array filled with ones.\n","base.aones2d":"\nbase.aones2d( shape:Array<integer> )\n    Returns a two-dimensional nested array filled with ones.\n","base.aones3d":"\nbase.aones3d( shape:Array<integer> )\n    Returns a three-dimensional nested array filled with ones.\n","base.aones4d":"\nbase.aones4d( shape:Array<integer> )\n    Returns a four-dimensional nested array filled with ones.\n","base.aones5d":"\nbase.aones5d( shape:Array<integer> )\n    Returns a five-dimensional nested array filled with ones.\n","base.aonesnd":"\nbase.aonesnd( shape:Array<integer> )\n    Returns an n-dimensional nested array filled with ones.\n","base.aoneTo":"\nbase.aoneTo( n:number )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from one.\n","base.aoneTo.assign":"\nbase.aoneTo.assign( out:ArrayLikeObject, stride:integer, offset:integer )\n    Fills an array with linearly spaced numeric elements which increment by 1\n    starting from one.\n","base.args2multislice":"\nbase.args2multislice( args:Array<Slice|integer|null|undefined> )\n    Creates a MultiSlice object from a list of MultiSlice constructor arguments.\n","base.asec":"\nbase.asec( x:number )\n    Computes the inverse (arc) secant of a number.\n","base.asecd":"\nbase.asecd( x:number )\n    Computes the arcsecant (in degrees) of a double-precision floating-point\n    number.\n","base.asecdf":"\nbase.asecdf( x:number )\n    Computes the arcsecant (in degrees) of a single-precision floating-point\n    number.\n","base.asecf":"\nbase.asecf( x:number )\n    Computes the inverse (arc) secant of a single-precision\n    floating-point number.\n","base.asech":"\nbase.asech( x:number )\n    Computes the hyperbolic arcsecant of a number.\n","base.asin":"\nbase.asin( x:number )\n    Computes the arcsine of a double-precision floating-point number.\n","base.asind":"\nbase.asind( x:number )\n    Computes the arcsine (in degrees) of a double-precision floating-point\n    number.\n","base.asindf":"\nbase.asindf( x:number )\n    Computes the arcsine (in degrees) of a single-precision floating-point\n    number.\n","base.asinf":"\nbase.asinf( x:number )\n    Computes the arcsine of a single-precision floating-point number.\n","base.asinh":"\nbase.asinh( x:number )\n    Computes the hyperbolic arcsine of a double-precision floating-point number.\n","base.atan":"\nbase.atan( x:number )\n    Computes the arctangent of a double-precision floating-point number.\n","base.atan2":"\nbase.atan2( y:number, x:number )\n    Computes the angle in the plane (in radians) between the positive x-axis and\n    the ray from (0,0) to the point (x,y).\n","base.atand":"\nbase.atand( x:number )\n    Computes the arctangent (in degrees) of a double-precision floating-point\n    number.\n","base.atanf":"\nbase.atanf( x:number )\n    Computes the arctangent of a single-precision floating-point number.\n","base.atanh":"\nbase.atanh( x:number )\n    Computes the hyperbolic arctangent of a double-precision floating-point\n    number.\n","base.avercos":"\nbase.avercos( x:number )\n    Computes the inverse versed cosine.\n","base.aversin":"\nbase.aversin( x:number )\n    Computes the inverse versed sine.\n","base.azeros":"\nbase.azeros( len:integer )\n    Returns a zero-filled \"generic\" array.\n","base.azeros2d":"\nbase.azeros2d( shape:Array<integer> )\n    Returns a zero-filled two-dimensional nested array.\n","base.azeros3d":"\nbase.azeros3d( shape:Array<integer> )\n    Returns a zero-filled three-dimensional nested array.\n","base.azeros4d":"\nbase.azeros4d( shape:Array<integer> )\n    Returns a zero-filled four-dimensional nested array.\n","base.azeros5d":"\nbase.azeros5d( shape:Array<integer> )\n    Returns a zero-filled five-dimensional nested array.\n","base.azerosnd":"\nbase.azerosnd( shape:Array<integer> )\n    Returns a zero-filled n-dimensional nested array.\n","base.azeroTo":"\nbase.azeroTo( n:number )\n    Generates a linearly spaced numeric array whose elements increment by 1\n    starting from zero.\n","base.azeroTo.assign":"\nbase.azeroTo.assign( out:ArrayLikeObject, stride:integer, offset:integer )\n    Fills an array with linearly spaced numeric elements which increment by 1\n    starting from zero.\n","base.bernoulli":"\nbase.bernoulli( n:integer )\n    Computes the nth Bernoulli number.\n","base.besselj0":"\nbase.besselj0( x:number )\n    Computes the Bessel function of the first kind of order zero.\n","base.besselj1":"\nbase.besselj1( x:number )\n    Computes the Bessel function of the first kind of order one.\n","base.bessely0":"\nbase.bessely0( x:number )\n    Computes the Bessel function of the second kind of order zero.\n","base.bessely1":"\nbase.bessely1( x:number )\n    Computes the Bessel function of the second kind of order one.\n","base.beta":"\nbase.beta( x:number, y:number )\n    Evaluates the beta function.\n","base.betainc":"\nbase.betainc( x:number, a:number, b:number[, regularized:boolean[, \n  upper:boolean]] )\n    Computes the regularized incomplete beta function.\n","base.betaincinv":"\nbase.betaincinv( p:number, a:number, b:number[, upper:boolean] )\n    Computes the inverse of the lower incomplete beta function.\n","base.betaln":"\nbase.betaln( a:number, b:number )\n    Evaluates the natural logarithm of the beta function.\n","base.binet":"\nbase.binet( x:number )\n    Evaluates Binet's formula extended to real numbers.\n","base.binomcoef":"\nbase.binomcoef( n:integer, k:integer )\n    Computes the binomial coefficient of two integers.\n","base.binomcoefln":"\nbase.binomcoefln( n:integer, k:integer )\n    Computes the natural logarithm of the binomial coefficient of two integers.\n","base.boxcox":"\nbase.boxcox( x:number, lambda:number )\n    Computes a one-parameter Box-Cox transformation.\n","base.boxcox1p":"\nbase.boxcox1p( x:number, lambda:number )\n    Computes a one-parameter Box-Cox transformation of 1+x.\n","base.boxcox1pinv":"\nbase.boxcox1pinv( y:number, lambda:number )\n    Computes the inverse of a one-parameter Box-Cox transformation for 1+x.\n","base.boxcoxinv":"\nbase.boxcoxinv( y:number, lambda:number )\n    Computes the inverse of a one-parameter Box-Cox transformation.\n","base.cabs":"\nbase.cabs( z:Complex128 )\n    Computes the absolute value of a double-precision complex floating-point\n    number.\n","base.cabs2":"\nbase.cabs2( z:Complex128 )\n    Computes the squared absolute value of a double-precision complex floating-\n    point number.\n","base.cabs2f":"\nbase.cabs2f( z:Complex64 )\n    Computes the squared absolute value of a single-precision complex floating-\n    point number.\n","base.cabsf":"\nbase.cabsf( z:Complex64 )\n    Computes the absolute value of a single-precision complex floating-point\n    number.\n","base.cadd":"\nbase.cadd( z1:Complex128, z2:Complex128 )\n    Adds two double-precision complex floating-point numbers.\n","base.caddf":"\nbase.caddf( z1:Complex64, z2:Complex64 )\n    Adds two single-precision complex floating-point numbers.\n","base.camelcase":"\nbase.camelcase( str:string )\n    Converts a string to camel case.\n","base.capitalize":"\nbase.capitalize( str:string )\n    Capitalizes the first character in a string.\n","base.cbrt":"\nbase.cbrt( x:number )\n    Computes the cube root of a double-precision floating-point number.\n","base.cbrtf":"\nbase.cbrtf( x:number )\n    Computes the cube root of a single-precision floating-point number.\n","base.cceil":"\nbase.cceil( z:Complex128 )\n    Rounds each component of a double-precision complex floating-point number\n    toward positive infinity.\n","base.cceilf":"\nbase.cceilf( z:Complex64 )\n    Rounds a single-precision complex floating-point number toward positive\n    infinity.\n","base.cceiln":"\nbase.cceiln( z:Complex128, n:integer )\n    Rounds each component of a double-precision complex number to the nearest\n    multiple of `10^n` toward positive infinity.\n","base.ccis":"\nbase.ccis( z:Complex128 )\n    Evaluates the cis function for a double-precision complex floating-point\n    number.\n","base.cdiv":"\nbase.cdiv( z1:Complex128, z2:Complex128 )\n    Divides two double-precision complex floating-point numbers.\n","base.ceil":"\nbase.ceil( x:number )\n    Rounds a double-precision floating-point number toward positive infinity.\n","base.ceil2":"\nbase.ceil2( x:number )\n    Rounds a numeric value to the nearest power of two toward positive infinity.\n","base.ceil10":"\nbase.ceil10( x:number )\n    Rounds a numeric value to the nearest power of ten toward positive infinity.\n","base.ceilb":"\nbase.ceilb( x:number, n:integer, b:integer )\n    Rounds a numeric value to the nearest multiple of `b^n` toward positive\n    infinity.\n","base.ceilf":"\nbase.ceilf( x:number )\n    Rounds a single-precision floating-point number toward positive infinity.\n","base.ceiln":"\nbase.ceiln( x:number, n:integer )\n    Rounds a numeric value to the nearest multiple of `10^n` toward positive\n    infinity.\n","base.ceilsd":"\nbase.ceilsd( x:number, n:integer, b:integer )\n    Rounds a numeric value to the nearest number toward positive infinity with\n    `n` significant figures.\n","base.cexp":"\nbase.cexp( z:Complex128 )\n    Evaluates the exponential function for a double-precision complex floating-\n    point number.\n","base.cflipsign":"\nbase.cflipsign( z:Complex128, y:number )\n    Returns a double-precision complex floating-point number with the same\n    magnitude as `z` and the sign of `y*z`.\n","base.cflipsignf":"\nbase.cflipsignf( z:Complex64, y:number )\n    Returns a single-precision complex floating-point number with the same\n    magnitude as `z` and the sign of `y*z`.\n","base.cfloor":"\nbase.cfloor( z:Complex128 )\n    Rounds a double-precision complex floating-point number toward negative\n    infinity.\n","base.cfloorn":"\nbase.cfloorn( z:Complex128, n:integer )\n    Rounds each component of a double-precision complex floating-point number\n    to the nearest multiple of `10^n` toward negative infinity.\n","base.cidentity":"\nbase.cidentity( z:Complex128 )\n    Evaluates the identity function for a double-precision complex floating-\n    point number.\n","base.cidentityf":"\nbase.cidentityf( z:Complex64 )\n    Evaluates the identity function for a single-precision complex floating-\n    point number.\n","base.cinv":"\nbase.cinv( z:Complex128 )\n    Computes the inverse of a double-precision complex floating-point number.\n","base.clamp":"\nbase.clamp( v:number, min:number, max:number )\n    Restricts a double-precision floating-point number to a specified range.\n","base.clampf":"\nbase.clampf( v:number, min:number, max:number )\n    Restricts a single-precision floating-point number to a specified range.\n","base.cmul":"\nbase.cmul( z1:Complex128, z2:Complex128 )\n    Multiplies two double-precision complex floating-point numbers.\n","base.cmulf":"\nbase.cmulf( z1:Complex64, z2:Complex64 )\n    Multiplies two single-precision complex floating-point numbers.\n","base.cneg":"\nbase.cneg( z )\n    Negates a double-precision complex floating-point number.\n","base.cnegf":"\nbase.cnegf( z )\n    Negates a single-precision complex floating-point number.\n","base.codePointAt":"\nbase.codePointAt( str:string, idx:integer, backward:boolean )\n    Returns a Unicode code point from a string at a specified position.\n","base.constantcase":"\nbase.constantcase( str:string )\n    Converts a string to constant case.\n","base.continuedFraction":"\nbase.continuedFraction( generator:Function[, options:Object] )\n    Evaluates the continued fraction approximation for the supplied series\n    generator using the modified Lentz algorithm.\n","base.copysign":"\nbase.copysign( x:number, y:number )\n    Returns a double-precision floating-point number with the magnitude of `x`\n    and the sign of `y`.\n","base.copysignf":"\nbase.copysignf( x:number, y:number )\n    Returns a single-precision floating-point number with the magnitude of `x`\n    and the sign of `y`.\n","base.cos":"\nbase.cos( x:number )\n    Computes the cosine of a number.\n","base.cosd":"\nbase.cosd( x:number )\n    Computes the cosine of an angle measured in degrees.\n","base.cosh":"\nbase.cosh( x:number )\n    Computes the hyperbolic cosine of a double-precision floating-point number.\n","base.cosm1":"\nbase.cosm1( x:number )\n    Computes the cosine of a number minus one.\n","base.cospi":"\nbase.cospi( x:number )\n    Computes the value of `cos(πx)`.\n","base.cot":"\nbase.cot( x:number )\n    Computes the cotangent of a number.\n","base.cotd":"\nbase.cotd( x:number )\n    Computes the cotangent of an angle measured in degrees.\n","base.coth":"\nbase.coth( x:number )\n    Computes the hyperbolic cotangent of a number.\n","base.covercos":"\nbase.covercos( x:number )\n    Computes the coversed cosine.\n","base.coversin":"\nbase.coversin( x:number )\n    Computes the coversed sine.\n","base.cphase":"\nbase.cphase( z:Complex128 )\n    Computes the argument of a double-precision complex floating-point number\n    in radians.\n","base.cpolar":"\nbase.cpolar( z:Complex128 )\n    Returns the absolute value and phase of a double-precision complex\n    floating-point number.\n","base.cpolar.assign":"\nbase.cpolar.assign( z:Complex128, out:Array|TypedArray|Object, stride:integer, \n  offset:integer )\n    Returns the absolute value and phase of a double-precision complex\n    floating-point number and assigns results to a provided output array.\n","base.cround":"\nbase.cround( z:Complex128 )\n    Rounds each component of a double-precision complex floating-point number\n    to the nearest integer.\n","base.croundn":"\nbase.croundn( z:Complex128, n:integer )\n    Rounds each component of a double-precision complex floating-point number\n    to the nearest multiple of `10^n`.\n","base.csc":"\nbase.csc( x:number )\n    Computes the cosecant of a number.\n","base.cscd":"\nbase.cscd( x:number )\n    Computes the cosecant of a degree.\n","base.csch":"\nbase.csch( x:number )\n    Computes the hyperbolic cosecant of a number.\n","base.csignum":"\nbase.csignum( z:Complex128 )\n    Evaluates the signum function of a double-precision complex floating-point\n    number.\n","base.csub":"\nbase.csub( z1:Complex128, z2:Complex128 )\n    Subtracts two double-precision complex floating-point numbers.\n","base.csubf":"\nbase.csubf( z1:Complex64, z2:Complex64 )\n    Subtracts two single-precision complex floating-point numbers.\n","base.deg2rad":"\nbase.deg2rad( x:number )\n    Converts an angle from degrees to radians.\n","base.deg2radf":"\nbase.deg2radf( x:number )\n    Converts an angle from degrees to radians (single-precision).\n","base.digamma":"\nbase.digamma( x:number )\n    Evaluates the digamma function.\n","base.diracDelta":"\nbase.diracDelta( x:number )\n    Evaluates the Dirac delta function.\n","base.div":"\nbase.div( x:number, y:number )\n    Divides two double-precision floating-point numbers `x` and `y`.\n","base.divf":"\nbase.divf( x:number, y:number )\n    Divides two single-precision floating-point numbers `x` and `y`.\n","base.dotcase":"\nbase.dotcase( str:string )\n    Converts a string to dot case.\n","base.dists.arcsine.Arcsine":"\nbase.dists.arcsine.Arcsine( [a:number, b:number] )\n    Returns an arcsine distribution object.\n","base.dists.arcsine.cdf":"\nbase.dists.arcsine.cdf( x:number, a:number, b:number )\n    Evaluates the cumulative distribution function (CDF) for an arcsine\n    distribution with minimum support `a` and maximum support `b` at a value\n    `x`.\n","base.dists.arcsine.cdf.factory":"\nbase.dists.arcsine.cdf.factory( a:number, b:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an arcsine distribution with minimum support `a` and maximum support `b`.\n","base.dists.arcsine.entropy":"\nbase.dists.arcsine.entropy( a:number, b:number )\n    Returns the differential entropy of an arcsine distribution (in nats).\n","base.dists.arcsine.kurtosis":"\nbase.dists.arcsine.kurtosis( a:number, b:number )\n    Returns the excess kurtosis of an arcsine distribution.\n","base.dists.arcsine.logcdf":"\nbase.dists.arcsine.logcdf( x:number, a:number, b:number )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for an\n    arcsine distribution with minimum support `a` and maximum support `b` at a\n    value `x`.\n","base.dists.arcsine.logcdf.factory":"\nbase.dists.arcsine.logcdf.factory( a:number, b:number )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of an arcsine distribution with minimum support\n    `a` and maximum support `b`.\n","base.dists.arcsine.logpdf":"\nbase.dists.arcsine.logpdf( x:number, a:number, b:number )\n    Evaluates the logarithm of the probability density function (PDF) for an\n    arcsine distribution with minimum support `a` and maximum support `b` at a\n    value `x`.\n","base.dists.arcsine.logpdf.factory":"\nbase.dists.arcsine.logpdf.factory( a:number, b:number )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of an arcsine distribution with minimum support `a` and\n    maximum support `b`.\n","base.dists.arcsine.mean":"\nbase.dists.arcsine.mean( a:number, b:number )\n    Returns the expected value of an arcsine distribution.\n","base.dists.arcsine.median":"\nbase.dists.arcsine.median( a:number, b:number )\n    Returns the median of an arcsine distribution.\n","base.dists.arcsine.mode":"\nbase.dists.arcsine.mode( a:number, b:number )\n    Returns the mode of an arcsine distribution.\n","base.dists.arcsine.pdf":"\nbase.dists.arcsine.pdf( x:number, a:number, b:number )\n    Evaluates the probability density function (PDF) for an arcsine distribution\n    with minimum support `a` and maximum support `b` at a value `x`.\n","base.dists.arcsine.pdf.factory":"\nbase.dists.arcsine.pdf.factory( a:number, b:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    an arcsine distribution with minimum support `a` and maximum support `b`.\n","base.dists.arcsine.quantile":"\nbase.dists.arcsine.quantile( p:number, a:number, b:number )\n    Evaluates the quantile function for an arcsine distribution with minimum\n    support `a` and maximum support `b` at a probability `p`.\n","base.dists.arcsine.quantile.factory":"\nbase.dists.arcsine.quantile.factory( a:number, b:number )\n    Returns a function for evaluating the quantile function of an arcsine\n    distribution with minimum support `a` and maximum support `b`.\n","base.dists.arcsine.skewness":"\nbase.dists.arcsine.skewness( a:number, b:number )\n    Returns the skewness of an arcsine distribution.\n","base.dists.arcsine.stdev":"\nbase.dists.arcsine.stdev( a:number, b:number )\n    Returns the standard deviation of an arcsine distribution.\n","base.dists.arcsine.variance":"\nbase.dists.arcsine.variance( a:number, b:number )\n    Returns the variance of an arcsine distribution.\n","base.dists.bernoulli.Bernoulli":"\nbase.dists.bernoulli.Bernoulli( [p:number] )\n    Returns a Bernoulli distribution object.\n","base.dists.bernoulli.cdf":"\nbase.dists.bernoulli.cdf( x:number, p:number )\n    Evaluates the cumulative distribution function (CDF) for a Bernoulli\n    distribution with success probability `p` at a value `x`.\n","base.dists.bernoulli.cdf.factory":"\nbase.dists.bernoulli.cdf.factory( p:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.entropy":"\nbase.dists.bernoulli.entropy( p:number )\n    Returns the entropy of a Bernoulli distribution with success probability\n    `p` (in nats).\n","base.dists.bernoulli.kurtosis":"\nbase.dists.bernoulli.kurtosis( p:number )\n    Returns the excess kurtosis of a Bernoulli distribution with success\n    probability `p`.\n","base.dists.bernoulli.mean":"\nbase.dists.bernoulli.mean( p:number )\n    Returns the expected value of a Bernoulli distribution with success\n    probability `p`.\n","base.dists.bernoulli.median":"\nbase.dists.bernoulli.median( p:number )\n    Returns the median of a Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.mgf":"\nbase.dists.bernoulli.mgf( t:number, p:number )\n    Evaluates the moment-generating function (MGF) for a Bernoulli\n    distribution with success probability `p` at a value `t`.\n","base.dists.bernoulli.mgf.factory":"\nbase.dists.bernoulli.mgf.factory( p:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.mode":"\nbase.dists.bernoulli.mode( p:number )\n    Returns the mode of a Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.pmf":"\nbase.dists.bernoulli.pmf( x:number, p:number )\n    Evaluates the probability mass function (PMF) for a Bernoulli distribution\n    with success probability `p` at a value `x`.\n","base.dists.bernoulli.pmf.factory":"\nbase.dists.bernoulli.pmf.factory( p:number )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    Bernoulli distribution with success probability `p`.\n","base.dists.bernoulli.quantile":"\nbase.dists.bernoulli.quantile( r:number, p:number )\n    Evaluates the quantile function for a Bernoulli distribution with success\n    probability `p` at a probability `r`.\n","base.dists.bernoulli.quantile.factory":"\nbase.dists.bernoulli.quantile.factory( p:number )\n    Returns a function for evaluating the quantile function of a Bernoulli\n    distribution with success probability `p`.\n","base.dists.bernoulli.skewness":"\nbase.dists.bernoulli.skewness( p:number )\n    Returns the skewness of a Bernoulli distribution with success probability\n    `p`.\n","base.dists.bernoulli.stdev":"\nbase.dists.bernoulli.stdev( p:number )\n    Returns the standard deviation of a Bernoulli distribution with success\n    probability `p`.\n","base.dists.bernoulli.variance":"\nbase.dists.bernoulli.variance( p:number )\n    Returns the variance of a Bernoulli distribution with success probability\n    `p`.\n","base.dists.beta.Beta":"\nbase.dists.beta.Beta( [α:number, β:number] )\n    Returns a beta distribution object.\n","base.dists.beta.cdf":"\nbase.dists.beta.cdf( x:number, α:number, β:number )\n    Evaluates the cumulative distribution function (CDF) for a beta distribution\n    with first shape parameter `α` and second shape parameter `β` at a value\n    `x`.\n","base.dists.beta.cdf.factory":"\nbase.dists.beta.cdf.factory( α:number, β:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a beta distribution with first shape parameter `α` and second shape\n    parameter `β`.\n","base.dists.beta.entropy":"\nbase.dists.beta.entropy( α:number, β:number )\n    Returns the differential entropy of a beta distribution.\n","base.dists.beta.kurtosis":"\nbase.dists.beta.kurtosis( α:number, β:number )\n    Returns the excess kurtosis of a beta distribution.\n","base.dists.beta.logcdf":"\nbase.dists.beta.logcdf( x:number, α:number, β:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a beta distribution with first shape parameter `α` and second\n    shape parameter `β` at a value `x`.\n","base.dists.beta.logcdf.factory":"\nbase.dists.beta.logcdf.factory( α:number, β:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a beta distribution with first shape\n    parameter `α` and second shape parameter `β`.\n","base.dists.beta.logpdf":"\nbase.dists.beta.logpdf( x:number, α:number, β:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a beta distribution with first shape parameter `α` and second shape\n    parameter `β` at a value `x`.\n","base.dists.beta.logpdf.factory":"\nbase.dists.beta.logpdf.factory( α:number, β:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a beta distribution with first shape parameter `α`\n    and second shape parameter `β`.\n","base.dists.beta.mean":"\nbase.dists.beta.mean( α:number, β:number )\n    Returns the expected value of a beta distribution.\n","base.dists.beta.median":"\nbase.dists.beta.median( α:number, β:number )\n    Returns the median of a beta distribution.\n","base.dists.beta.mgf":"\nbase.dists.beta.mgf( t:number, α:number, β:number )\n    Evaluates the moment-generating function (MGF) for a beta distribution with\n    first shape parameter `α` and second shape parameter `β` at a value `t`.\n","base.dists.beta.mgf.factory":"\nbase.dists.beta.mgf.factory( α:number, β:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    beta distribution with first shape parameter `α` and second shape parameter\n    `β`.\n","base.dists.beta.mode":"\nbase.dists.beta.mode( α:number, β:number )\n    Returns the mode of a beta distribution.\n","base.dists.beta.pdf":"\nbase.dists.beta.pdf( x:number, α:number, β:number )\n    Evaluates the probability density function (PDF) for a beta distribution\n    with first shape parameter `α` and second shape parameter `β` at a value\n    `x`.\n","base.dists.beta.pdf.factory":"\nbase.dists.beta.pdf.factory( α:number, β:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a beta distribution with first shape parameter `α` and second shape\n    parameter `β`.\n","base.dists.beta.quantile":"\nbase.dists.beta.quantile( p:number, α:number, β:number )\n    Evaluates the quantile function for a beta distribution with first shape\n    parameter `α` and second shape parameter `β` at a probability `p`.\n","base.dists.beta.quantile.factory":"\nbase.dists.beta.quantile.factory( α:number, β:number )\n    Returns a function for evaluating the quantile function of a beta\n    distribution with first shape parameter `α` and second shape parameter `β`.\n","base.dists.beta.skewness":"\nbase.dists.beta.skewness( α:number, β:number )\n    Returns the skewness of a beta distribution.\n","base.dists.beta.stdev":"\nbase.dists.beta.stdev( α:number, β:number )\n    Returns the standard deviation of a beta distribution.\n","base.dists.beta.variance":"\nbase.dists.beta.variance( α:number, β:number )\n    Returns the variance of a beta distribution.\n","base.dists.betaprime.BetaPrime":"\nbase.dists.betaprime.BetaPrime( [α:number, β:number] )\n    Returns a beta prime distribution object.\n","base.dists.betaprime.cdf":"\nbase.dists.betaprime.cdf( x:number, α:number, β:number )\n    Evaluates the cumulative distribution function (CDF) for a beta prime\n    distribution with first shape parameter `α` and second shape parameter `β`\n    at a value `x`.\n","base.dists.betaprime.cdf.factory":"\nbase.dists.betaprime.cdf.factory( α:number, β:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a beta prime distribution with first shape parameter `α` and second shape\n    parameter `β`.\n","base.dists.betaprime.kurtosis":"\nbase.dists.betaprime.kurtosis( α:number, β:number )\n    Returns the excess kurtosis of a beta prime distribution.\n","base.dists.betaprime.logcdf":"\nbase.dists.betaprime.logcdf( x:number, α:number, β:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a beta prime distribution with first shape parameter `α` and\n    second shape parameter `β` at a value `x`.\n","base.dists.betaprime.logcdf.factory":"\nbase.dists.betaprime.logcdf.factory( α:number, β:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a beta prime distribution with first shape\n    parameter `α` and second shape parameter `β`.\n","base.dists.betaprime.logpdf":"\nbase.dists.betaprime.logpdf( x:number, α:number, β:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a beta prime distribution with first shape parameter `α` and second\n    shape parameter `β` at a value `x`.\n","base.dists.betaprime.logpdf.factory":"\nbase.dists.betaprime.logpdf.factory( α:number, β:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a beta prime distribution with first shape\n    parameter `α` and second shape parameter `β`.\n","base.dists.betaprime.mean":"\nbase.dists.betaprime.mean( α:number, β:number )\n    Returns the expected value of a beta prime distribution.\n","base.dists.betaprime.mode":"\nbase.dists.betaprime.mode( α:number, β:number )\n    Returns the mode of a beta prime distribution.\n","base.dists.betaprime.pdf":"\nbase.dists.betaprime.pdf( x:number, α:number, β:number )\n    Evaluates the probability density function (PDF) for a beta prime\n    distribution  with first shape parameter `α` and second shape parameter `β`\n    at a value `x`.\n","base.dists.betaprime.pdf.factory":"\nbase.dists.betaprime.pdf.factory( α:number, β:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a beta prime distribution with first shape parameter `α` and second shape\n    parameter `β`.\n","base.dists.betaprime.quantile":"\nbase.dists.betaprime.quantile( p:number, α:number, β:number )\n    Evaluates the quantile function for a beta prime distribution with first\n    shape parameter `α` and second shape parameter `β` at a probability `p`.\n","base.dists.betaprime.quantile.factory":"\nbase.dists.betaprime.quantile.factory( α:number, β:number )\n    Returns a function for evaluating the quantile function of a beta prime\n    distribution with first shape parameter `α` and second shape parameter `β`.\n","base.dists.betaprime.skewness":"\nbase.dists.betaprime.skewness( α:number, β:number )\n    Returns the skewness of a beta prime distribution.\n","base.dists.betaprime.stdev":"\nbase.dists.betaprime.stdev( α:number, β:number )\n    Returns the standard deviation of a beta prime distribution.\n","base.dists.betaprime.variance":"\nbase.dists.betaprime.variance( α:number, β:number )\n    Returns the variance of a beta prime distribution.\n","base.dists.binomial.Binomial":"\nbase.dists.binomial.Binomial( [n:integer, p:number] )\n    Returns a binomial distribution object.\n","base.dists.binomial.cdf":"\nbase.dists.binomial.cdf( x:number, n:integer, p:number )\n    Evaluates the cumulative distribution function (CDF) for a binomial\n    distribution with number of trials `n` and success probability `p` at a\n    value `x`.\n","base.dists.binomial.cdf.factory":"\nbase.dists.binomial.cdf.factory( n:integer, p:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a binomial distribution with number of trials `n` and success probability\n    `p`.\n","base.dists.binomial.entropy":"\nbase.dists.binomial.entropy( n:integer, p:number )\n    Returns the entropy of a binomial distribution.\n","base.dists.binomial.kurtosis":"\nbase.dists.binomial.kurtosis( n:integer, p:number )\n    Returns the excess kurtosis of a binomial distribution.\n","base.dists.binomial.logpmf":"\nbase.dists.binomial.logpmf( x:number, n:integer, p:number )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    binomial distribution with number of trials `n` and success probability `p`\n    at a value `x`.\n","base.dists.binomial.logpmf.factory":"\nbase.dists.binomial.logpmf.factory( n:integer, p:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a binomial distribution with number of trials `n` and\n    success probability `p`.\n","base.dists.binomial.mean":"\nbase.dists.binomial.mean( n:integer, p:number )\n    Returns the expected value of a binomial distribution.\n","base.dists.binomial.median":"\nbase.dists.binomial.median( n:integer, p:number )\n    Returns the median of a binomial distribution.\n","base.dists.binomial.mgf":"\nbase.dists.binomial.mgf( t:number, n:integer, p:number )\n    Evaluates the moment-generating function (MGF) for a binomial distribution\n    with number of trials `n` and success probability `p` at a value `t`.\n","base.dists.binomial.mgf.factory":"\nbase.dists.binomial.mgf.factory( n:integer, p:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    binomial distribution with number of trials `n` and success probability `p`.\n","base.dists.binomial.mode":"\nbase.dists.binomial.mode( n:integer, p:number )\n    Returns the mode of a binomial distribution.\n","base.dists.binomial.pmf":"\nbase.dists.binomial.pmf( x:number, n:integer, p:number )\n    Evaluates the probability mass function (PMF) for a binomial distribution\n    with number of trials `n` and success probability `p` at a value `x`.\n","base.dists.binomial.pmf.factory":"\nbase.dists.binomial.pmf.factory( n:integer, p:number )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    binomial distribution with number of trials `n` and success probability `p`.\n","base.dists.binomial.quantile":"\nbase.dists.binomial.quantile( r:number, n:integer, p:number )\n    Evaluates the quantile function for a binomial distribution with number of\n    trials `n` and success probability `p` at a probability `r`.\n","base.dists.binomial.quantile.factory":"\nbase.dists.binomial.quantile.factory( n:integer, p:number )\n    Returns a function for evaluating the quantile function of a binomial\n    distribution with number of trials `n` and success probability `p`.\n","base.dists.binomial.skewness":"\nbase.dists.binomial.skewness( n:integer, p:number )\n    Returns the skewness of a binomial distribution.\n","base.dists.binomial.stdev":"\nbase.dists.binomial.stdev( n:integer, p:number )\n    Returns the standard deviation of a binomial distribution.\n","base.dists.binomial.variance":"\nbase.dists.binomial.variance( n:integer, p:number )\n    Returns the variance of a binomial distribution.\n","base.dists.cauchy.Cauchy":"\nbase.dists.cauchy.Cauchy( [x0:number, Ɣ:number] )\n    Returns a Cauchy distribution object.\n","base.dists.cauchy.cdf":"\nbase.dists.cauchy.cdf( x:number, x0:number, Ɣ:number )\n    Evaluates the cumulative distribution function (CDF) for a Cauchy\n    distribution with location parameter `x0` and scale parameter `Ɣ` at a value\n    `x`.\n","base.dists.cauchy.cdf.factory":"\nbase.dists.cauchy.cdf.factory( x0:number, Ɣ:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Cauchy distribution with location parameter `x0` and scale parameter\n    `Ɣ`.\n","base.dists.cauchy.entropy":"\nbase.dists.cauchy.entropy( x0:number, Ɣ:number )\n    Returns the differential entropy of a Cauchy distribution (in nats).\n","base.dists.cauchy.logcdf":"\nbase.dists.cauchy.logcdf( x:number, x0:number, Ɣ:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (logCDF) for a Cauchy distribution with location parameter `x0` and scale\n    parameter `Ɣ` at a value `x`.\n","base.dists.cauchy.logcdf.factory":"\nbase.dists.cauchy.logcdf.factory( x0:number, Ɣ:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (logCDF) of a Cauchy distribution with location\n    parameter `x0` and scale parameter `Ɣ`.\n","base.dists.cauchy.logpdf":"\nbase.dists.cauchy.logpdf( x:number, x0:number, Ɣ:number )\n    Evaluates the natural logarithm of the probability density function (logPDF)\n    for a Cauchy distribution with location parameter `x0` and scale parameter\n    `Ɣ` at a value `x`.\n","base.dists.cauchy.logpdf.factory":"\nbase.dists.cauchy.logpdf.factory( x0:number, Ɣ:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (logPDF) of a Cauchy distribution with location parameter\n    `x0` and scale parameter `Ɣ`.\n","base.dists.cauchy.median":"\nbase.dists.cauchy.median( x0:number, Ɣ:number )\n    Returns the median of a Cauchy distribution.\n","base.dists.cauchy.mode":"\nbase.dists.cauchy.mode( x0:number, Ɣ:number )\n    Returns the mode of a Cauchy distribution.\n","base.dists.cauchy.pdf":"\nbase.dists.cauchy.pdf( x:number, x0:number, Ɣ:number )\n    Evaluates the probability density function (PDF) for a Cauchy distribution\n    with location parameter `x0` and scale parameter `Ɣ` at a value `x`.\n","base.dists.cauchy.pdf.factory":"\nbase.dists.cauchy.pdf.factory( x0:number, Ɣ:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Cauchy distribution with location parameter `x0` and scale parameter `Ɣ`.\n","base.dists.cauchy.quantile":"\nbase.dists.cauchy.quantile( p:number, x0:number, Ɣ:number )\n    Evaluates the quantile function for a Cauchy distribution with location\n    parameter `x0`  and scale parameter `Ɣ` at a probability `p`.\n","base.dists.cauchy.quantile.factory":"\nbase.dists.cauchy.quantile.factory( x0:number, Ɣ:number )\n    Returns a function for evaluating the quantile function of a Cauchy\n    distribution with location parameter `x0` and scale parameter `Ɣ`.\n","base.dists.chi.cdf":"\nbase.dists.chi.cdf( x:number, k:number )\n    Evaluates the cumulative distribution function (CDF) for a chi distribution\n    with degrees of freedom `k` at a value `x`.\n","base.dists.chi.cdf.factory":"\nbase.dists.chi.cdf.factory( k:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a chi distribution with degrees of freedom `k`.\n","base.dists.chi.Chi":"\nbase.dists.chi.Chi( [k:number] )\n    Returns a chi distribution object.\n","base.dists.chi.entropy":"\nbase.dists.chi.entropy( k:number )\n    Returns the differential entropy of a chi distribution (in nats).\n","base.dists.chi.kurtosis":"\nbase.dists.chi.kurtosis( k:number )\n    Returns the excess kurtosis of a chi distribution.\n","base.dists.chi.logpdf":"\nbase.dists.chi.logpdf( x:number, k:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a chi distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chi.logpdf.factory":"\nbase.dists.chi.logpdf.factory( k:number )\n    Returns a function for evaluating the natural logarithm of the  probability\n    density function (PDF) of a chi distribution with degrees of freedom `k`.\n","base.dists.chi.mean":"\nbase.dists.chi.mean( k:number )\n    Returns the expected value of a chi distribution.\n","base.dists.chi.mode":"\nbase.dists.chi.mode( k:number )\n    Returns the mode of a chi distribution.\n","base.dists.chi.pdf":"\nbase.dists.chi.pdf( x:number, k:number )\n    Evaluates the probability density function (PDF) for a chi distribution with\n    degrees of freedom `k` at a value `x`.\n","base.dists.chi.pdf.factory":"\nbase.dists.chi.pdf.factory( k:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a chi distribution with degrees of freedom `k`.\n","base.dists.chi.quantile":"\nbase.dists.chi.quantile( p:number, k:number )\n    Evaluates the quantile function for a chi distribution with degrees of\n    freedom `k` at a probability `p`.\n","base.dists.chi.quantile.factory":"\nbase.dists.chi.quantile.factory( k:number )\n    Returns a function for evaluating the quantile function of a chi\n    distribution with degrees of freedom `k`.\n","base.dists.chi.skewness":"\nbase.dists.chi.skewness( k:number )\n    Returns the skewness of a chi distribution.\n","base.dists.chi.stdev":"\nbase.dists.chi.stdev( k:number )\n    Returns the standard deviation of a chi distribution.\n","base.dists.chi.variance":"\nbase.dists.chi.variance( k:number )\n    Returns the variance of a chi distribution.\n","base.dists.chisquare.cdf":"\nbase.dists.chisquare.cdf( x:number, k:number )\n    Evaluates the cumulative distribution function (CDF) for a chi-squared\n    distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chisquare.cdf.factory":"\nbase.dists.chisquare.cdf.factory( k:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a chi-squared distribution with degrees of freedom `k`.\n","base.dists.chisquare.ChiSquare":"\nbase.dists.chisquare.ChiSquare( [k:number] )\n    Returns a  chi-squared distribution object.\n","base.dists.chisquare.entropy":"\nbase.dists.chisquare.entropy( k:number )\n    Returns the differential entropy of a chi-squared distribution (in nats).\n","base.dists.chisquare.kurtosis":"\nbase.dists.chisquare.kurtosis( k:number )\n    Returns the excess kurtosis of a chi-squared distribution.\n","base.dists.chisquare.logpdf":"\nbase.dists.chisquare.logpdf( x:number, k:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a chi-squared distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chisquare.logpdf.factory":"\nbase.dists.chisquare.logpdf.factory( k:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a chi-squared distribution with degrees of freedom\n    `k`.\n","base.dists.chisquare.mean":"\nbase.dists.chisquare.mean( k:number )\n    Returns the expected value of a chi-squared distribution.\n","base.dists.chisquare.median":"\nbase.dists.chisquare.median( k:number )\n    Returns the median of a chi-squared distribution.\n","base.dists.chisquare.mgf":"\nbase.dists.chisquare.mgf( t:number, k:number )\n    Evaluates the moment-generating function (MGF) for a chi-squared\n    distribution with degrees of freedom `k` at a value `t`.\n","base.dists.chisquare.mgf.factory":"\nbase.dists.chisquare.mgf.factory( k:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    chi-squared distribution with degrees of freedom `k`.\n","base.dists.chisquare.mode":"\nbase.dists.chisquare.mode( k:number )\n    Returns the mode of a chi-squared distribution.\n","base.dists.chisquare.pdf":"\nbase.dists.chisquare.pdf( x:number, k:number )\n    Evaluates the probability density function (PDF) for a chi-squared\n    distribution with degrees of freedom `k` at a value `x`.\n","base.dists.chisquare.pdf.factory":"\nbase.dists.chisquare.pdf.factory( k:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a chi-squared distribution with degrees of freedom `k`.\n","base.dists.chisquare.quantile":"\nbase.dists.chisquare.quantile( p:number, k:number )\n    Evaluates the quantile function for a chi-squared distribution with degrees\n    of freedom `k` at a probability `p`.\n","base.dists.chisquare.quantile.factory":"\nbase.dists.chisquare.quantile.factory( k:number )\n    Returns a function for evaluating the quantile function of a chi-squared\n    distribution with degrees of freedom `k`.\n","base.dists.chisquare.skewness":"\nbase.dists.chisquare.skewness( k:number )\n    Returns the skewness of a chi-squared distribution.\n","base.dists.chisquare.stdev":"\nbase.dists.chisquare.stdev( k:number )\n    Returns the standard deviation of a chi-squared distribution.\n","base.dists.chisquare.variance":"\nbase.dists.chisquare.variance( k:number )\n    Returns the variance of a chi-squared distribution.\n","base.dists.cosine.cdf":"\nbase.dists.cosine.cdf( x:number, μ:number, s:number )\n    Evaluates the cumulative distribution function (CDF) for a raised cosine\n    distribution with location parameter `μ` and scale parameter `s` at a value\n    `x`.\n","base.dists.cosine.cdf.factory":"\nbase.dists.cosine.cdf.factory( μ:number, s:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a raised cosine distribution with location parameter `μ` and scale\n    parameter `s`.\n","base.dists.cosine.Cosine":"\nbase.dists.cosine.Cosine( [μ:number, s:number] )\n    Returns a raised cosine distribution object.\n","base.dists.cosine.kurtosis":"\nbase.dists.cosine.kurtosis( μ:number, s:number )\n    Returns the excess kurtosis of a raised cosine distribution with location\n    parameter `μ` and scale parameter `s`.\n","base.dists.cosine.logcdf":"\nbase.dists.cosine.logcdf( x:number, μ:number, s:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a raised cosine distribution with location parameter `μ` and scale\n     parameter `s` at a value `x`.\n","base.dists.cosine.logcdf.factory":"\nbase.dists.cosine.logcdf.factory( μ:number, s:number )\n    Returns a function for evaluating the natural logarithm of the  cumulative\n    distribution function (CDF) of a raised cosine distribution with location\n    parameter `μ` and scale parameter `s`.\n","base.dists.cosine.logpdf":"\nbase.dists.cosine.logpdf( x:number, μ:number, s:number )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    raised cosine distribution with location parameter `μ` and scale parameter\n    `s` at a value `x`.\n","base.dists.cosine.logpdf.factory":"\nbase.dists.cosine.logpdf.factory( μ:number, s:number )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a raised cosine distribution with location parameter `μ`\n    and scale parameter `s`.\n","base.dists.cosine.mean":"\nbase.dists.cosine.mean( μ:number, s:number )\n    Returns the expected value of a raised cosine distribution with location\n    parameter `μ` and scale parameter `s`.\n","base.dists.cosine.median":"\nbase.dists.cosine.median( μ:number, s:number )\n    Returns the median of a raised cosine distribution with location parameter\n    `μ` and scale parameter `s`.\n","base.dists.cosine.mgf":"\nbase.dists.cosine.mgf( t:number, μ:number, s:number )\n    Evaluates the moment-generating function (MGF) for a raised cosine\n    distribution with location parameter `μ` and scale parameter `s` at a value\n    `t`.\n","base.dists.cosine.mgf.factory":"\nbase.dists.cosine.mgf.factory( μ:number, s:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    raised cosine distribution with location parameter `μ` and scale parameter\n    `s`.\n","base.dists.cosine.mode":"\nbase.dists.cosine.mode( μ:number, s:number )\n    Returns the mode of a raised cosine distribution with location parameter `μ`\n    and scale parameter `s`.\n","base.dists.cosine.pdf":"\nbase.dists.cosine.pdf( x:number, μ:number, s:number )\n    Evaluates the probability density function (PDF) for a raised cosine\n    distribution with location parameter `μ` and scale parameter `s` at a value\n    `x`.\n","base.dists.cosine.pdf.factory":"\nbase.dists.cosine.pdf.factory( μ:number, s:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a raised cosine distribution with location parameter `μ` and scale parameter\n    `s`.\n","base.dists.cosine.quantile":"\nbase.dists.cosine.quantile( p:number, μ:number, s:number )\n    Evaluates the quantile function for a raised cosine distribution with\n    location parameter `μ` and scale parameter `s` at a probability `p`.\n","base.dists.cosine.quantile.factory":"\nbase.dists.cosine.quantile.factory( μ:number, s:number )\n    Returns a function for evaluating the quantile function of a raised cosine\n    distribution with location parameter `μ` and scale parameter `s`.\n","base.dists.cosine.skewness":"\nbase.dists.cosine.skewness( μ:number, s:number )\n    Returns the skewness of a raised cosine distribution with location parameter\n    `μ` and scale parameter `s`.\n","base.dists.cosine.stdev":"\nbase.dists.cosine.stdev( μ:number, s:number )\n    Returns the standard deviation of a raised cosine distribution with location\n    parameter `μ` and scale parameter `s`.\n","base.dists.cosine.variance":"\nbase.dists.cosine.variance( μ:number, s:number )\n    Returns the variance of a raised cosine distribution with location parameter\n    `μ` and scale parameter `s`.\n","base.dists.degenerate.cdf":"\nbase.dists.degenerate.cdf( x:number, μ:number )\n    Evaluates the cumulative distribution function (CDF) for a degenerate\n    distribution with mean value `μ`.\n","base.dists.degenerate.cdf.factory":"\nbase.dists.degenerate.cdf.factory( μ:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a degenerate distribution centered at a provided mean value.\n","base.dists.degenerate.Degenerate":"\nbase.dists.degenerate.Degenerate( [μ:number] )\n    Returns a degenerate distribution object.\n","base.dists.degenerate.entropy":"\nbase.dists.degenerate.entropy( μ:number )\n    Returns the entropy of a degenerate distribution with constant value `μ`.\n","base.dists.degenerate.logcdf":"\nbase.dists.degenerate.logcdf( x:number, μ:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (logCDF) for a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logcdf.factory":"\nbase.dists.degenerate.logcdf.factory( μ:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (logCDF) of a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpdf":"\nbase.dists.degenerate.logpdf( x:number, μ:number )\n    Evaluates the natural logarithm of the probability density function (logPDF)\n    for a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpdf.factory":"\nbase.dists.degenerate.logpdf.factory( μ:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (logPDF) of a degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpmf":"\nbase.dists.degenerate.logpmf( x:number, μ:number )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    degenerate distribution with mean `μ`.\n","base.dists.degenerate.logpmf.factory":"\nbase.dists.degenerate.logpmf.factory( μ:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a degenerate distribution with mean `μ`.\n","base.dists.degenerate.mean":"\nbase.dists.degenerate.mean( μ:number )\n    Returns the expected value of a degenerate distribution with constant value\n    `μ`.\n","base.dists.degenerate.median":"\nbase.dists.degenerate.median( μ:number )\n    Returns the median of a degenerate distribution with constant value `μ`.\n","base.dists.degenerate.mgf":"\nbase.dists.degenerate.mgf( x:number, μ:number )\n    Evaluates the moment-generating function (MGF) for a degenerate distribution\n    with mean `μ`.\n","base.dists.degenerate.mgf.factory":"\nbase.dists.degenerate.mgf.factory( μ:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    degenerate distribution with mean `μ`.\n","base.dists.degenerate.mode":"\nbase.dists.degenerate.mode( μ:number )\n    Returns the mode of a degenerate distribution with constant value `μ`.\n","base.dists.degenerate.pdf":"\nbase.dists.degenerate.pdf( x:number, μ:number )\n    Evaluates the probability density function (PDF) for a degenerate\n    distribution with mean `μ`.\n","base.dists.degenerate.pdf.factory":"\nbase.dists.degenerate.pdf.factory( μ:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a degenerate distribution with mean `μ`.\n","base.dists.degenerate.pmf":"\nbase.dists.degenerate.pmf( x:number, μ:number )\n    Evaluates the probability mass function (PMF) for a degenerate distribution\n    with mean `μ`.\n","base.dists.degenerate.pmf.factory":"\nbase.dists.degenerate.pmf.factory( μ:number )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    degenerate distribution with mean `μ`.\n","base.dists.degenerate.quantile":"\nbase.dists.degenerate.quantile( p:number, μ:number )\n    Evaluates the quantile function for a degenerate distribution with mean `μ`.\n","base.dists.degenerate.quantile.factory":"\nbase.dists.degenerate.quantile.factory( μ:number )\n    Returns a function for evaluating the quantile function of a degenerate\n    distribution with mean `μ`.\n","base.dists.degenerate.stdev":"\nbase.dists.degenerate.stdev( μ:number )\n    Returns the standard deviation of a degenerate distribution with constant\n    value `μ`.\n","base.dists.degenerate.variance":"\nbase.dists.degenerate.variance( μ:number )\n    Returns the variance of a degenerate distribution with constant value `μ`.\n","base.dists.discreteUniform.cdf":"\nbase.dists.discreteUniform.cdf( x:number, a:integer, b:integer )\n    Evaluates the cumulative distribution function (CDF) for a discrete uniform\n    distribution with minimum support `a` and maximum support `b` at a value\n    `x`.\n","base.dists.discreteUniform.cdf.factory":"\nbase.dists.discreteUniform.cdf.factory( a:integer, b:integer )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a discrete uniform distribution with minimum support `a` and maximum\n    support `b`.\n","base.dists.discreteUniform.DiscreteUniform":"\nbase.dists.discreteUniform.DiscreteUniform( [a:integer, b:integer] )\n    Returns a discrete uniform distribution object.\n","base.dists.discreteUniform.entropy":"\nbase.dists.discreteUniform.entropy( a:integer, b:integer )\n    Returns the entropy of a discrete uniform distribution.\n","base.dists.discreteUniform.kurtosis":"\nbase.dists.discreteUniform.kurtosis( a:integer, b:integer )\n    Returns the excess kurtosis of a discrete uniform distribution.\n","base.dists.discreteUniform.logcdf":"\nbase.dists.discreteUniform.logcdf( x:number, a:integer, b:integer )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a discrete uniform distribution with minimum support `a` and\n    maximum support `b` at a value `x`.\n","base.dists.discreteUniform.logcdf.factory":"\nbase.dists.discreteUniform.logcdf.factory( a:integer, b:integer )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a discrete uniform distribution with minimum\n    support `a` and maximum support `b`.\n","base.dists.discreteUniform.logpmf":"\nbase.dists.discreteUniform.logpmf( x:number, a:integer, b:integer )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    discrete uniform distribution with minimum support `a` and maximum support\n    `b` at a value `x`.\n","base.dists.discreteUniform.logpmf.factory":"\nbase.dists.discreteUniform.logpmf.factory( a:integer, b:integer )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a discrete uniform distribution with minimum support\n    `a` and maximum support `b`.\n","base.dists.discreteUniform.mean":"\nbase.dists.discreteUniform.mean( a:integer, b:integer )\n    Returns the expected value of a discrete uniform distribution.\n","base.dists.discreteUniform.median":"\nbase.dists.discreteUniform.median( a:integer, b:integer )\n    Returns the median of a discrete uniform distribution.\n","base.dists.discreteUniform.mgf":"\nbase.dists.discreteUniform.mgf( t:number, a:integer, b:integer )\n    Evaluates the moment-generating function (MGF) for a discrete uniform\n    distribution with minimum support `a` and maximum support `b` at a value\n    `t`.\n","base.dists.discreteUniform.mgf.factory":"\nbase.dists.discreteUniform.mgf.factory( a:integer, b:integer )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a discrete uniform distribution with minimum support `a` and maximum\n    support `b`.\n","base.dists.discreteUniform.pmf":"\nbase.dists.discreteUniform.pmf( x:number, a:integer, b:integer )\n    Evaluates the probability mass function (PMF) for a discrete uniform\n    distribution with minimum support `a` and maximum support `b` at a value\n    `x`.\n","base.dists.discreteUniform.pmf.factory":"\nbase.dists.discreteUniform.pmf.factory( a:integer, b:integer )\n    Returns a function for evaluating the probability mass function (PMF) of\n    a discrete uniform distribution with minimum support `a` and maximum support\n    `b`.\n","base.dists.discreteUniform.quantile":"\nbase.dists.discreteUniform.quantile( p:number, a:integer, b:integer )\n    Evaluates the quantile function for a discrete uniform distribution with\n    minimum support `a` and maximum support `b` at a probability `p`.\n","base.dists.discreteUniform.quantile.factory":"\nbase.dists.discreteUniform.quantile.factory( a:integer, b:integer )\n    Returns a function for evaluating the quantile function of a discrete\n    uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.discreteUniform.skewness":"\nbase.dists.discreteUniform.skewness( a:integer, b:integer )\n    Returns the skewness of a discrete uniform distribution.\n","base.dists.discreteUniform.stdev":"\nbase.dists.discreteUniform.stdev( a:integer, b:integer )\n    Returns the standard deviation of a discrete uniform distribution.\n","base.dists.discreteUniform.variance":"\nbase.dists.discreteUniform.variance( a:integer, b:integer )\n    Returns the variance of a discrete uniform distribution.\n","base.dists.erlang.cdf":"\nbase.dists.erlang.cdf( x:number, k:number, λ:number )\n    Evaluates the cumulative distribution function (CDF) for an Erlang\n    distribution with shape parameter `k` and rate parameter `λ` at a value\n    `x`.\n","base.dists.erlang.cdf.factory":"\nbase.dists.erlang.cdf.factory( k:number, λ:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.entropy":"\nbase.dists.erlang.entropy( k:integer, λ:number )\n    Returns the differential entropy of an Erlang distribution (in nats).\n","base.dists.erlang.Erlang":"\nbase.dists.erlang.Erlang( [k:number, λ:number] )\n    Returns an Erlang distribution object.\n","base.dists.erlang.kurtosis":"\nbase.dists.erlang.kurtosis( k:integer, λ:number )\n    Returns the excess kurtosis of an Erlang distribution.\n","base.dists.erlang.logpdf":"\nbase.dists.erlang.logpdf( x:number, k:number, λ:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for an Erlang distribution with shape parameter `k` and rate parameter `λ`\n    at a value `x`.\n","base.dists.erlang.logpdf.factory":"\nbase.dists.erlang.logpdf.factory( k:number, λ:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of an Erlang distribution with shape parameter `k`\n    and rate parameter `λ`.\n","base.dists.erlang.mean":"\nbase.dists.erlang.mean( k:integer, λ:number )\n    Returns the expected value of an Erlang distribution.\n","base.dists.erlang.mgf":"\nbase.dists.erlang.mgf( t:number, k:number, λ:number )\n    Evaluates the moment-generating function (MGF) for an Erlang distribution\n    with shape parameter `k` and rate parameter `λ` at a value `t`.\n","base.dists.erlang.mgf.factory":"\nbase.dists.erlang.mgf.factory( k:number, λ:number )\n    Returns a function for evaluating the moment-generating function (MGF) of an\n    Erlang distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.mode":"\nbase.dists.erlang.mode( k:integer, λ:number )\n    Returns the mode of an Erlang distribution.\n","base.dists.erlang.pdf":"\nbase.dists.erlang.pdf( x:number, k:number, λ:number )\n    Evaluates the probability density function (PDF) for an Erlang distribution\n    with shape parameter `k` and rate parameter `λ` at a value `x`.\n","base.dists.erlang.pdf.factory":"\nbase.dists.erlang.pdf.factory( k:number, λ:number )\n    Returns a function for evaluating the probability density function (PDF)\n    of an Erlang distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.quantile":"\nbase.dists.erlang.quantile( p:number, k:number, λ:number )\n    Evaluates the quantile function for an Erlang distribution with shape\n    parameter `k` and rate parameter `λ` at a probability `p`.\n","base.dists.erlang.quantile.factory":"\nbase.dists.erlang.quantile.factory( k:number, λ:number )\n    Returns a function for evaluating the quantile function of an Erlang\n    distribution with shape parameter `k` and rate parameter `λ`.\n","base.dists.erlang.skewness":"\nbase.dists.erlang.skewness( k:integer, λ:number )\n    Returns the skewness of an Erlang distribution.\n","base.dists.erlang.stdev":"\nbase.dists.erlang.stdev( k:integer, λ:number )\n    Returns the standard deviation of an Erlang distribution.\n","base.dists.erlang.variance":"\nbase.dists.erlang.variance( k:integer, λ:number )\n    Returns the variance of an Erlang distribution.\n","base.dists.exponential.cdf":"\nbase.dists.exponential.cdf( x:number, λ:number )\n    Evaluates the cumulative distribution function (CDF) for an exponential\n    distribution with rate parameter `λ` at a value `x`.\n","base.dists.exponential.cdf.factory":"\nbase.dists.exponential.cdf.factory( λ:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    for an exponential distribution with rate parameter `λ`.\n","base.dists.exponential.entropy":"\nbase.dists.exponential.entropy( λ:number )\n    Returns the differential entropy of an exponential distribution.\n","base.dists.exponential.Exponential":"\nbase.dists.exponential.Exponential( [λ:number] )\n    Returns an exponential distribution object.\n","base.dists.exponential.kurtosis":"\nbase.dists.exponential.kurtosis( λ:number )\n    Returns the excess kurtosis of an exponential distribution.\n","base.dists.exponential.logcdf":"\nbase.dists.exponential.logcdf( x:number, λ:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for an exponential distribution with rate parameter `λ` at a value\n    `x`.\n","base.dists.exponential.logcdf.factory":"\nbase.dists.exponential.logcdf.factory( λ:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) for an exponential distribution with rate\n    parameter `λ`.\n","base.dists.exponential.logpdf":"\nbase.dists.exponential.logpdf( x:number, λ:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for an exponential distribution with rate parameter `λ` at a value `x`.\n","base.dists.exponential.logpdf.factory":"\nbase.dists.exponential.logpdf.factory( λ:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) for an exponential distribution with rate parameter\n    `λ`.\n","base.dists.exponential.mean":"\nbase.dists.exponential.mean( λ:number )\n    Returns the expected value of an exponential distribution.\n","base.dists.exponential.median":"\nbase.dists.exponential.median( λ:number )\n    Returns the median of an exponential distribution.\n","base.dists.exponential.mgf":"\nbase.dists.exponential.mgf( t:number, λ:number )\n    Evaluates the moment-generating function (MGF) for an exponential\n    distribution with rate parameter `λ` at a value `t`.\n","base.dists.exponential.mgf.factory":"\nbase.dists.exponential.mgf.factory( λ:number )\n    Returns a function for evaluating the moment-generating function (MGF) for\n    an exponential distribution with rate parameter `λ`.\n","base.dists.exponential.mode":"\nbase.dists.exponential.mode( λ:number )\n    Returns the mode of an exponential distribution.\n","base.dists.exponential.pdf":"\nbase.dists.exponential.pdf( x:number, λ:number )\n    Evaluates the probability density function (PDF) for an exponential\n    distribution with rate parameter `λ` at a value `x`.\n","base.dists.exponential.pdf.factory":"\nbase.dists.exponential.pdf.factory( λ:number )\n    Returns a function for evaluating the probability density function (PDF)\n    for an exponential distribution with rate parameter `λ`.\n","base.dists.exponential.quantile":"\nbase.dists.exponential.quantile( p:number, λ:number )\n    Evaluates the quantile function for an exponential distribution with rate\n    parameter `λ` at a probability `p`.\n","base.dists.exponential.quantile.factory":"\nbase.dists.exponential.quantile.factory( λ:number )\n    Returns a function for evaluating the quantile function for an exponential\n    distribution with rate parameter `λ`.\n","base.dists.exponential.skewness":"\nbase.dists.exponential.skewness( λ:number )\n    Returns the skewness of an exponential distribution.\n","base.dists.exponential.stdev":"\nbase.dists.exponential.stdev( λ:number )\n    Returns the standard deviation of an exponential distribution.\n","base.dists.exponential.variance":"\nbase.dists.exponential.variance( λ:number )\n    Returns the variance of an exponential distribution.\n","base.dists.f.cdf":"\nbase.dists.f.cdf( x:number, d1:number, d2:number )\n    Evaluates the cumulative distribution function (CDF) for an F distribution\n    with numerator degrees of freedom `d1` and denominator degrees of freedom\n    `d2` at a value `x`.\n","base.dists.f.cdf.factory":"\nbase.dists.f.cdf.factory( d1:number, d2:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an F distribution with numerator degrees of freedom `d1` and denominator\n    degrees of freedom `d2`.\n","base.dists.f.entropy":"\nbase.dists.f.entropy( d1:number, d2:number )\n    Returns the differential entropy of an F distribution (in nats).\n","base.dists.f.F":"\nbase.dists.f.F( [d1:number, d2:number] )\n    Returns an F distribution object.\n","base.dists.f.kurtosis":"\nbase.dists.f.kurtosis( d1:number, d2:number )\n    Returns the excess kurtosis of an F distribution.\n","base.dists.f.mean":"\nbase.dists.f.mean( d1:number, d2:number )\n    Returns the expected value of an F distribution.\n","base.dists.f.mode":"\nbase.dists.f.mode( d1:number, d2:number )\n    Returns the mode of an F distribution.\n","base.dists.f.pdf":"\nbase.dists.f.pdf( x:number, d1:number, d2:number )\n    Evaluates the probability density function (PDF) for an F distribution with\n    numerator degrees of freedom `d1` and denominator degrees of freedom `d2` at\n    a value `x`.\n","base.dists.f.pdf.factory":"\nbase.dists.f.pdf.factory( d1:number, d2:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    an F distribution with numerator degrees of freedom `d1` and denominator\n    degrees of freedom `d2`.\n","base.dists.f.quantile":"\nbase.dists.f.quantile( p:number, d1:number, d2:number )\n    Evaluates the quantile function for an F distribution with numerator degrees\n    of freedom `d1` and denominator degrees of freedom `d2` at a probability\n    `p`.\n","base.dists.f.quantile.factory":"\nbase.dists.f.quantile.factory( d1:number, d2:number )\n    Returns a function for evaluating the quantile function of an F distribution\n    with numerator degrees of freedom `d1` and denominator degrees of freedom\n    `d2`.\n","base.dists.f.skewness":"\nbase.dists.f.skewness( d1:number, d2:number )\n    Returns the skewness of an F distribution.\n","base.dists.f.stdev":"\nbase.dists.f.stdev( d1:number, d2:number )\n    Returns the standard deviation of an F distribution.\n","base.dists.f.variance":"\nbase.dists.f.variance( d1:number, d2:number )\n    Returns the variance of an F distribution.\n","base.dists.frechet.cdf":"\nbase.dists.frechet.cdf( x:number, α:number, s:number, m:number )\n    Evaluates the cumulative distribution function (CDF) for a Fréchet\n    distribution with shape parameter `α`, scale parameter `s`, and location\n    `m`.\n","base.dists.frechet.cdf.factory":"\nbase.dists.frechet.cdf.factory( α:number, s:number, m:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n    location `m`.\n","base.dists.frechet.entropy":"\nbase.dists.frechet.entropy( α:number, s:number, m:number )\n    Returns the differential entropy of a Fréchet distribution with shape\n    parameter `α`, scale parameter `s`, and location `m` (in nats).\n","base.dists.frechet.Frechet":"\nbase.dists.frechet.Frechet( [α:number, s:number, m:number] )\n    Returns a Fréchet distribution object.\n","base.dists.frechet.kurtosis":"\nbase.dists.frechet.kurtosis( α:number, s:number, m:number )\n    Returns the excess kurtosis of a Fréchet distribution with shape parameter\n    `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.logcdf":"\nbase.dists.frechet.logcdf( x:number, α:number, s:number, m:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a Fréchet distribution with shape parameter `α`, scale parameter\n    `s`, and location `m`.\n","base.dists.frechet.logcdf.factory":"\nbase.dists.frechet.logcdf.factory( α:number, s:number, m:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Fréchet distribution with shape parameter\n    `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.logpdf":"\nbase.dists.frechet.logpdf( x:number, α:number, s:number, m:number )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n    location `m`.\n","base.dists.frechet.logpdf.factory":"\nbase.dists.frechet.logpdf.factory( α:number, s:number, m:number )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Fréchet distribution with shape parameter `α`, scale\n    parameter `s`, and location `m`.\n","base.dists.frechet.mean":"\nbase.dists.frechet.mean( α:number, s:number, m:number )\n    Returns the expected value of a Fréchet distribution with shape parameter\n    `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.median":"\nbase.dists.frechet.median( α:number, s:number, m:number )\n    Returns the median of a Fréchet distribution with shape parameter\n    `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.mode":"\nbase.dists.frechet.mode( α:number, s:number, m:number )\n    Returns the mode of a Fréchet distribution with shape parameter `α`, scale\n    parameter `s`, and location `m`.\n","base.dists.frechet.pdf":"\nbase.dists.frechet.pdf( x:number, α:number, s:number, m:number )\n    Evaluates the probability density function (PDF) for a Fréchet distribution\n    with shape parameter `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.pdf.factory":"\nbase.dists.frechet.pdf.factory( α:number, s:number, m:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Fréchet distribution with shape parameter `α`, scale parameter `s`, and\n    location `m`.\n","base.dists.frechet.quantile":"\nbase.dists.frechet.quantile( p:number, α:number, s:number, m:number )\n    Evaluates the quantile function for a Fréchet distribution with shape\n    parameter `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.quantile.factory":"\nbase.dists.frechet.quantile.factory( α:number, s:number, m:number )\n    Returns a function for evaluating the quantile function of a Fréchet\n    distribution with shape parameter `α`, scale parameter `s`, and location\n    `m`.\n","base.dists.frechet.skewness":"\nbase.dists.frechet.skewness( α:number, s:number, m:number )\n    Returns the skewness of a Fréchet distribution with shape parameter `α`,\n    scale parameter `s`, and location `m`.\n","base.dists.frechet.stdev":"\nbase.dists.frechet.stdev( α:number, s:number, m:number )\n    Returns the standard deviation of a Fréchet distribution with shape\n    parameter `α`, scale parameter `s`, and location `m`.\n","base.dists.frechet.variance":"\nbase.dists.frechet.variance( α:number, s:number, m:number )\n    Returns the variance of a Fréchet distribution with shape parameter `α`,\n    scale parameter `s`, and location `m`.\n","base.dists.gamma.cdf":"\nbase.dists.gamma.cdf( x:number, α:number, β:number )\n    Evaluates the cumulative distribution function (CDF) for a gamma\n    distribution with shape parameter `α` and rate parameter `β` at a value `x`.\n","base.dists.gamma.cdf.factory":"\nbase.dists.gamma.cdf.factory( α:number, β:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a gamma distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.entropy":"\nbase.dists.gamma.entropy( α:number, β:number )\n    Returns the differential entropy of a gamma distribution.\n","base.dists.gamma.Gamma":"\nbase.dists.gamma.Gamma( [α:number, β:number] )\n    Returns a gamma distribution object.\n","base.dists.gamma.kurtosis":"\nbase.dists.gamma.kurtosis( α:number, β:number )\n    Returns the excess kurtosis of a gamma distribution.\n","base.dists.gamma.logcdf":"\nbase.dists.gamma.logcdf( x:number, α:number, β:number )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    gamma distribution with shape parameter `α` and rate parameter `β` at a\n    value `x`.\n","base.dists.gamma.logcdf.factory":"\nbase.dists.gamma.logcdf.factory( α:number, β:number )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a gamma distribution with shape parameter `α`\n    and rate parameter `β`.\n","base.dists.gamma.logpdf":"\nbase.dists.gamma.logpdf( x:number, α:number, β:number )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    gamma distribution with shape parameter `α` and rate parameter `β` at a\n    value `x`.\n","base.dists.gamma.logpdf.factory":"\nbase.dists.gamma.logpdf.factory( α:number, β:number )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a gamma distribution with shape parameter `α` and rate\n    parameter `β`.\n","base.dists.gamma.mean":"\nbase.dists.gamma.mean( α:number, β:number )\n    Returns the expected value of a gamma distribution.\n","base.dists.gamma.mgf":"\nbase.dists.gamma.mgf( t:number, α:number, β:number )\n    Evaluates the moment-generating function (MGF) for a gamma distribution with\n    shape parameter `α` and rate parameter `β` at a value `t`.\n","base.dists.gamma.mgf.factory":"\nbase.dists.gamma.mgf.factory( α:number, β:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    gamma distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.mode":"\nbase.dists.gamma.mode( α:number, β:number )\n    Returns the mode of a gamma distribution.\n","base.dists.gamma.pdf":"\nbase.dists.gamma.pdf( x:number, α:number, β:number )\n    Evaluates the probability density function (PDF) for a gamma distribution\n    with shape parameter `α` and rate parameter `β` at a value `x`.\n","base.dists.gamma.pdf.factory":"\nbase.dists.gamma.pdf.factory( α:number, β:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a gamma distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.quantile":"\nbase.dists.gamma.quantile( p:number, α:number, β:number )\n    Evaluates the quantile function for a gamma distribution with shape\n    parameter `α` and rate parameter `β` at a probability `p`.\n","base.dists.gamma.quantile.factory":"\nbase.dists.gamma.quantile.factory( α:number, β:number )\n    Returns a function for evaluating the quantile function of a gamma\n    distribution with shape parameter `α` and rate parameter `β`.\n","base.dists.gamma.skewness":"\nbase.dists.gamma.skewness( α:number, β:number )\n    Returns the skewness of a gamma distribution.\n","base.dists.gamma.stdev":"\nbase.dists.gamma.stdev( α:number, β:number )\n    Returns the standard deviation of a gamma distribution.\n","base.dists.gamma.variance":"\nbase.dists.gamma.variance( α:number, β:number )\n    Returns the variance of a gamma distribution.\n","base.dists.geometric.cdf":"\nbase.dists.geometric.cdf( x:number, p:number )\n    Evaluates the cumulative distribution function (CDF) for a geometric\n    distribution with success probability `p` at a value `x`.\n","base.dists.geometric.cdf.factory":"\nbase.dists.geometric.cdf.factory( p:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a geometric distribution with success probability `p`.\n","base.dists.geometric.entropy":"\nbase.dists.geometric.entropy( p:number )\n    Returns the entropy of a geometric distribution with success probability\n    `p` (in nats).\n","base.dists.geometric.Geometric":"\nbase.dists.geometric.Geometric( [p:number] )\n    Returns a geometric distribution object.\n","base.dists.geometric.kurtosis":"\nbase.dists.geometric.kurtosis( p:number )\n    Returns the excess kurtosis of a geometric distribution with success\n    probability `p`.\n","base.dists.geometric.logcdf":"\nbase.dists.geometric.logcdf( x:number, p:number )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    geometric distribution with success probability `p` at a value `x`.\n","base.dists.geometric.logcdf.factory":"\nbase.dists.geometric.logcdf.factory( p:number )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a geometric distribution with success\n    probability `p`.\n","base.dists.geometric.logpmf":"\nbase.dists.geometric.logpmf( x:number, p:number )\n    Evaluates the logarithm of the probability mass function (PMF) for a\n    geometric distribution with success probability `p` at a value `x`.\n","base.dists.geometric.logpmf.factory":"\nbase.dists.geometric.logpmf.factory( p:number )\n    Returns a function for evaluating the logarithm of the probability mass\n    function (PMF) of a geometric distribution with success probability `p`.\n","base.dists.geometric.mean":"\nbase.dists.geometric.mean( p:number )\n    Returns the expected value of a geometric distribution with success\n    probability `p`.\n","base.dists.geometric.median":"\nbase.dists.geometric.median( p:number )\n    Returns the median of a geometric distribution with success probability `p`.\n","base.dists.geometric.mgf":"\nbase.dists.geometric.mgf( t:number, p:number )\n    Evaluates the moment-generating function (MGF) for a geometric\n    distribution with success probability `p` at a value `t`.\n","base.dists.geometric.mgf.factory":"\nbase.dists.geometric.mgf.factory( p:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    geometric distribution with success probability `p`.\n","base.dists.geometric.mode":"\nbase.dists.geometric.mode( p:number )\n    Returns the mode of a geometric distribution with success probability `p`.\n","base.dists.geometric.pmf":"\nbase.dists.geometric.pmf( x:number, p:number )\n    Evaluates the probability mass function (PMF) for a geometric distribution\n    with success probability `p` at a value `x`.\n","base.dists.geometric.pmf.factory":"\nbase.dists.geometric.pmf.factory( p:number )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    geometric distribution with success probability `p`.\n","base.dists.geometric.quantile":"\nbase.dists.geometric.quantile( r:number, p:number )\n    Evaluates the quantile function for a geometric distribution with success\n    probability `p` at a probability `r`.\n","base.dists.geometric.quantile.factory":"\nbase.dists.geometric.quantile.factory( p:number )\n    Returns a function for evaluating the quantile function of a geometric\n    distribution with success probability `p`.\n","base.dists.geometric.skewness":"\nbase.dists.geometric.skewness( p:number )\n    Returns the skewness of a geometric distribution with success probability\n    `p`.\n","base.dists.geometric.stdev":"\nbase.dists.geometric.stdev( p:number )\n    Returns the standard deviation of a geometric distribution with success\n    probability `p`.\n","base.dists.geometric.variance":"\nbase.dists.geometric.variance( p:number )\n    Returns the variance of a geometric distribution with success probability\n    `p`.\n","base.dists.gumbel.cdf":"\nbase.dists.gumbel.cdf( x:number, μ:number, β:number )\n    Evaluates the cumulative distribution function (CDF) for a Gumbel\n    distribution with location parameter `μ` and scale parameter `β` at a value\n    `x`.\n","base.dists.gumbel.cdf.factory":"\nbase.dists.gumbel.cdf.factory( μ:number, β:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Gumbel distribution with location parameter `μ` and scale parameter\n    `β`.\n","base.dists.gumbel.entropy":"\nbase.dists.gumbel.entropy( μ:number, β:number )\n    Returns the differential entropy of a Gumbel distribution with location\n    parameter `μ` and scale parameter `β` (in nats).\n","base.dists.gumbel.Gumbel":"\nbase.dists.gumbel.Gumbel( [μ:number, β:number] )\n    Returns a Gumbel distribution object.\n","base.dists.gumbel.kurtosis":"\nbase.dists.gumbel.kurtosis( μ:number, β:number )\n    Returns the excess kurtosis of a Gumbel distribution with location parameter\n    `μ` and scale parameter `β`.\n","base.dists.gumbel.logcdf":"\nbase.dists.gumbel.logcdf( x:number, μ:number, β:number )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n    value `x`.\n","base.dists.gumbel.logcdf.factory":"\nbase.dists.gumbel.logcdf.factory( μ:number, β:number )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Gumbel distribution with location parameter\n    `μ` and scale parameter `β`.\n","base.dists.gumbel.logpdf":"\nbase.dists.gumbel.logpdf( x:number, μ:number, β:number )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    Gumbel distribution with location parameter `μ` and scale parameter `β` at a\n    value `x`.\n","base.dists.gumbel.logpdf.factory":"\nbase.dists.gumbel.logpdf.factory( μ:number, β:number )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Gumbel distribution with location parameter `μ` and\n    scale parameter `β`.\n","base.dists.gumbel.mean":"\nbase.dists.gumbel.mean( μ:number, β:number )\n    Returns the expected value of a Gumbel distribution with location parameter\n    `μ` and scale parameter `β`.\n","base.dists.gumbel.median":"\nbase.dists.gumbel.median( μ:number, β:number )\n    Returns the median of a Gumbel distribution with location parameter `μ` and\n    scale parameter `β`.\n","base.dists.gumbel.mgf":"\nbase.dists.gumbel.mgf( t:number, μ:number, β:number )\n    Evaluates the moment-generating function (MGF) for a Gumbel distribution\n    with location parameter `μ` and scale parameter `β` at a value `t`.\n","base.dists.gumbel.mgf.factory":"\nbase.dists.gumbel.mgf.factory( μ:number, β:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Gumbel distribution with location parameter `μ` and scale parameter `β`.\n","base.dists.gumbel.mode":"\nbase.dists.gumbel.mode( μ:number, β:number )\n    Returns the mode of a Gumbel distribution with location parameter `μ` and\n    scale parameter `β`.\n","base.dists.gumbel.pdf":"\nbase.dists.gumbel.pdf( x:number, μ:number, β:number )\n    Evaluates the probability density function (PDF) for a Gumbel distribution\n    with location parameter `μ` and scale parameter `β` at a value `x`.\n","base.dists.gumbel.pdf.factory":"\nbase.dists.gumbel.pdf.factory( μ:number, β:number )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Gumbel distribution with location parameter `μ` and scale parameter\n    `β`.\n","base.dists.gumbel.quantile":"\nbase.dists.gumbel.quantile( p:number, μ:number, β:number )\n    Evaluates the quantile function for a Gumbel distribution with location\n    parameter `μ` and scale parameter `β` at a probability `p`.\n","base.dists.gumbel.quantile.factory":"\nbase.dists.gumbel.quantile.factory( μ:number, β:number )\n    Returns a function for evaluating the quantile function of a Gumbel\n    distribution with location parameter `μ` and scale parameter `β`.\n","base.dists.gumbel.skewness":"\nbase.dists.gumbel.skewness( μ:number, β:number )\n    Returns the skewness of a Gumbel distribution with location parameter `μ`\n    and scale parameter `β`.\n","base.dists.gumbel.stdev":"\nbase.dists.gumbel.stdev( μ:number, β:number )\n    Returns the standard deviation of a Gumbel distribution with location\n    parameter `μ` and scale parameter `β`.\n","base.dists.gumbel.variance":"\nbase.dists.gumbel.variance( μ:number, β:number )\n    Returns the variance of a Gumbel distribution with location parameter `μ`\n    and scale parameter `β`.\n","base.dists.hypergeometric.cdf":"\nbase.dists.hypergeometric.cdf( x:number, N:integer, K:integer, n:integer )\n    Evaluates the cumulative distribution function (CDF) for a hypergeometric\n    distribution with population size `N`, subpopulation size `K`, and number of\n    draws `n` at a value `x`.\n","base.dists.hypergeometric.cdf.factory":"\nbase.dists.hypergeometric.cdf.factory( N:integer, K:integer, n:integer )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a hypergeometric distribution with population size `N`, subpopulation\n    size `K`, and number of draws `n`.\n","base.dists.hypergeometric.Hypergeometric":"\nbase.dists.hypergeometric.Hypergeometric( [N:integer, K:integer, n:integer] )\n    Returns a hypergeometric distribution object.\n","base.dists.hypergeometric.kurtosis":"\nbase.dists.hypergeometric.kurtosis( N:integer, K:integer, n:integer )\n    Returns the excess kurtosis of a hypergeometric distribution.\n","base.dists.hypergeometric.logpmf":"\nbase.dists.hypergeometric.logpmf( x:number, N:integer, K:integer, n:integer )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    hypergeometric distribution with population size `N`, subpopulation size\n    `K`, and number of draws `n` at a value `x`.\n","base.dists.hypergeometric.logpmf.factory":"\nbase.dists.hypergeometric.logpmf.factory( N:integer, K:integer, n:integer )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a hypergeometric distribution with population size\n    `N`, subpopulation size `K`, and number of draws `n`.\n","base.dists.hypergeometric.mean":"\nbase.dists.hypergeometric.mean( N:integer, K:integer, n:integer )\n    Returns the expected value of a hypergeometric distribution.\n","base.dists.hypergeometric.mode":"\nbase.dists.hypergeometric.mode( N:integer, K:integer, n:integer )\n    Returns the mode of a hypergeometric distribution.\n","base.dists.hypergeometric.pmf":"\nbase.dists.hypergeometric.pmf( x:number, N:integer, K:integer, n:integer )\n    Evaluates the probability mass function (PMF) for a hypergeometric\n    distribution with population size `N`, subpopulation size `K`, and number of\n    draws `n` at a value `x`.\n","base.dists.hypergeometric.pmf.factory":"\nbase.dists.hypergeometric.pmf.factory( N:integer, K:integer, n:integer )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    hypergeometric distribution with population size `N`, subpopulation size\n    `K`, and number of draws `n`.\n","base.dists.hypergeometric.quantile":"\nbase.dists.hypergeometric.quantile( p:number, N:integer, K:integer, n:integer )\n    Evaluates the quantile function for a hypergeometric distribution with\n    population size `N`, subpopulation size `K`, and number of draws `n` at a\n    probability `p`.\n","base.dists.hypergeometric.quantile.factory":"\nbase.dists.hypergeometric.quantile.factory( N:integer, K:integer, n:integer )\n    Returns a function for evaluating the quantile function of a hypergeometric\n    distribution with population size `N`, subpopulation size `K`, and number of\n    draws `n`.\n","base.dists.hypergeometric.skewness":"\nbase.dists.hypergeometric.skewness( N:integer, K:integer, n:integer )\n    Returns the skewness of a hypergeometric distribution.\n","base.dists.hypergeometric.stdev":"\nbase.dists.hypergeometric.stdev( N:integer, K:integer, n:integer )\n    Returns the standard deviation of a hypergeometric distribution.\n","base.dists.hypergeometric.variance":"\nbase.dists.hypergeometric.variance( N:integer, K:integer, n:integer )\n    Returns the variance of a hypergeometric distribution.\n","base.dists.invgamma.cdf":"\nbase.dists.invgamma.cdf( x:number, α:number, β:number )\n    Evaluates the cumulative distribution function (CDF) for an inverse gamma\n    distribution with shape parameter `α` and scale parameter `β` at a value\n    `x`.\n","base.dists.invgamma.cdf.factory":"\nbase.dists.invgamma.cdf.factory( α:number, β:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of an inverse gamma distribution with shape parameter `α` and scale\n    parameter `β`.\n","base.dists.invgamma.entropy":"\nbase.dists.invgamma.entropy( α:number, β:number )\n    Returns the differential entropy of an inverse gamma distribution.\n","base.dists.invgamma.InvGamma":"\nbase.dists.invgamma.InvGamma( [α:number, β:number] )\n    Returns an inverse gamma distribution object.\n","base.dists.invgamma.kurtosis":"\nbase.dists.invgamma.kurtosis( α:number, β:number )\n    Returns the excess kurtosis of an inverse gamma distribution.\n","base.dists.invgamma.logpdf":"\nbase.dists.invgamma.logpdf( x:number, α:number, β:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for an inverse gamma distribution with shape parameter `α` and scale\n    parameter `β` at a value `x`.\n","base.dists.invgamma.logpdf.factory":"\nbase.dists.invgamma.logpdf.factory( α:number, β:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) for an inverse gamma distribution with shape\n    parameter `α` and scale parameter `β`.\n","base.dists.invgamma.mean":"\nbase.dists.invgamma.mean( α:number, β:number )\n    Returns the expected value of an inverse gamma distribution.\n","base.dists.invgamma.mode":"\nbase.dists.invgamma.mode( α:number, β:number )\n    Returns the mode of an inverse gamma distribution.\n","base.dists.invgamma.pdf":"\nbase.dists.invgamma.pdf( x:number, α:number, β:number )\n    Evaluates the probability density function (PDF) for an inverse gamma\n    distribution with shape parameter `α` and scale parameter `β` at a value\n    `x`.\n","base.dists.invgamma.pdf.factory":"\nbase.dists.invgamma.pdf.factory( α:number, β:number )\n    Returns a function for evaluating the probability density function (PDF)\n    of an inverse gamma distribution with shape parameter `α` and scale\n    parameter `β`.\n","base.dists.invgamma.quantile":"\nbase.dists.invgamma.quantile( p:number, α:number, β:number )\n    Evaluates the quantile function for an inverse gamma distribution with shape\n    parameter `α` and scale parameter `β` at a probability `p`.\n","base.dists.invgamma.quantile.factory":"\nbase.dists.invgamma.quantile.factory( α:number, β:number )\n    Returns a function for evaluating the quantile function of an inverse gamma\n    distribution with shape parameter `α` and scale parameter `β`.\n","base.dists.invgamma.skewness":"\nbase.dists.invgamma.skewness( α:number, β:number )\n    Returns the skewness of an inverse gamma distribution.\n","base.dists.invgamma.stdev":"\nbase.dists.invgamma.stdev( α:number, β:number )\n    Returns the standard deviation of an inverse gamma distribution.\n","base.dists.invgamma.variance":"\nbase.dists.invgamma.variance( α:number, β:number )\n    Returns the variance of an inverse gamma distribution.\n","base.dists.kumaraswamy.cdf":"\nbase.dists.kumaraswamy.cdf( x:number, a:number, b:number )\n    Evaluates the cumulative distribution function (CDF) for Kumaraswamy's\n    double bounded distribution with first shape parameter `a` and second shape\n    parameter `b` at a value `x`.\n","base.dists.kumaraswamy.cdf.factory":"\nbase.dists.kumaraswamy.cdf.factory( a:number, b:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Kumaraswamy's double bounded distribution with first shape parameter\n    `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.Kumaraswamy":"\nbase.dists.kumaraswamy.Kumaraswamy( [a:number, b:number] )\n    Returns a Kumaraswamy's double bounded distribution object.\n","base.dists.kumaraswamy.kurtosis":"\nbase.dists.kumaraswamy.kurtosis( a:number, b:number )\n    Returns the excess kurtosis of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.logcdf":"\nbase.dists.kumaraswamy.logcdf( x:number, a:number, b:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for Kumaraswamy's double bounded distribution with first shape\n    parameter `a` and second shape parameter `b` at a value `x`.\n","base.dists.kumaraswamy.logcdf.factory":"\nbase.dists.kumaraswamy.logcdf.factory( a:number, b:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Kumaraswamy's double bounded distribution\n    with first shape parameter `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.logpdf":"\nbase.dists.kumaraswamy.logpdf( x:number, a:number, b:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for Kumaraswamy's double bounded distribution with first shape parameter `a`\n    and second shape parameter `b` at a value `x`.\n","base.dists.kumaraswamy.logpdf.factory":"\nbase.dists.kumaraswamy.logpdf.factory( a:number, b:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a Kumaraswamy's double bounded distribution with\n    first shape parameter `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.mean":"\nbase.dists.kumaraswamy.mean( a:number, b:number )\n    Returns the mean of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.median":"\nbase.dists.kumaraswamy.median( a:number, b:number )\n    Returns the median of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.mode":"\nbase.dists.kumaraswamy.mode( a:number, b:number )\n    Returns the mode of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.pdf":"\nbase.dists.kumaraswamy.pdf( x:number, a:number, b:number )\n    Evaluates the probability density function (PDF) for Kumaraswamy's double\n    bounded distribution with first shape parameter `a` and second shape\n    parameter `b` at a value `x`.\n","base.dists.kumaraswamy.pdf.factory":"\nbase.dists.kumaraswamy.pdf.factory( a:number, b:number )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Kumaraswamy's double bounded distribution with first shape parameter\n    `a` and second shape parameter `b`.\n","base.dists.kumaraswamy.quantile":"\nbase.dists.kumaraswamy.quantile( p:number, a:number, b:number )\n    Evaluates the quantile function for a Kumaraswamy's double bounded\n    distribution with first shape parameter `a` and second shape parameter `b`\n    at a probability `p`.\n","base.dists.kumaraswamy.quantile.factory":"\nbase.dists.kumaraswamy.quantile.factory( a:number, b:number )\n    Returns a function for evaluating the quantile function of a Kumaraswamy's\n    double bounded distribution with first shape parameter `a` and second shape\n    parameter `b`.\n","base.dists.kumaraswamy.skewness":"\nbase.dists.kumaraswamy.skewness( a:number, b:number )\n    Returns the skewness of a Kumaraswamy's double bounded distribution.\n","base.dists.kumaraswamy.stdev":"\nbase.dists.kumaraswamy.stdev( a:number, b:number )\n    Returns the standard deviation of a Kumaraswamy's double bounded\n    distribution.\n","base.dists.kumaraswamy.variance":"\nbase.dists.kumaraswamy.variance( a:number, b:number )\n    Returns the variance of a Kumaraswamy's double bounded distribution.\n","base.dists.laplace.cdf":"\nbase.dists.laplace.cdf( x:number, μ:number, b:number )\n    Evaluates the cumulative distribution function (CDF) for a Laplace\n    distribution with scale parameter `b` and location parameter `μ` at a\n    value `x`.\n","base.dists.laplace.cdf.factory":"\nbase.dists.laplace.cdf.factory( μ:number, b:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Laplace distribution with scale parameter `b` and location parameter\n    `μ`.\n","base.dists.laplace.entropy":"\nbase.dists.laplace.entropy( μ:number, b:number )\n    Returns the differential entropy of a Laplace distribution with location\n    parameter `μ` and scale parameter `b`.\n","base.dists.laplace.kurtosis":"\nbase.dists.laplace.kurtosis( μ:number, b:number )\n    Returns the excess kurtosis of a Laplace distribution with location\n    parameter `μ` and scale parameter `b`.\n","base.dists.laplace.Laplace":"\nbase.dists.laplace.Laplace( [μ:number, b:number] )\n    Returns a Laplace distribution object.\n","base.dists.laplace.logcdf":"\nbase.dists.laplace.logcdf( x:number, μ:number, b:number )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    Laplace distribution with scale parameter `b` and location parameter `μ` at\n    a value `x`.\n","base.dists.laplace.logcdf.factory":"\nbase.dists.laplace.logcdf.factory( μ:number, b:number )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Laplace distribution with scale parameter\n    `b` and location parameter `μ`.\n","base.dists.laplace.logpdf":"\nbase.dists.laplace.logpdf( x:number, μ:number, b:number )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    Laplace distribution with scale parameter `b` and location parameter `μ` at\n    a value `x`.\n","base.dists.laplace.logpdf.factory":"\nbase.dists.laplace.logpdf.factory( μ:number, b:number )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Laplace distribution with scale parameter `b` and\n    location parameter `μ`.\n","base.dists.laplace.mean":"\nbase.dists.laplace.mean( μ:number, b:number )\n    Returns the expected value of a Laplace distribution with location parameter\n    `μ` and scale parameter `b`.\n","base.dists.laplace.median":"\nbase.dists.laplace.median( μ:number, b:number )\n    Returns the median of a Laplace distribution with location parameter `μ` and\n    scale parameter `b`.\n","base.dists.laplace.mgf":"\nbase.dists.laplace.mgf( t:number, μ:number, b:number )\n    Evaluates the moment-generating function (MGF) for a Laplace\n    distribution with scale parameter `b` and location parameter `μ` at a\n    value `t`.\n","base.dists.laplace.mgf.factory":"\nbase.dists.laplace.mgf.factory( μ:number, b:number )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a Laplace distribution with scale parameter `b` and location parameter\n    `μ`.\n","base.dists.laplace.mode":"\nbase.dists.laplace.mode( μ:number, b:number )\n    Returns the mode of a Laplace distribution with location parameter `μ` and\n    scale parameter `b`.\n","base.dists.laplace.pdf":"\nbase.dists.laplace.pdf( x:number, μ:number, b:number )\n    Evaluates the probability density function (PDF) for a Laplace\n    distribution with scale parameter `b` and location parameter `μ` at a\n    value `x`.\n","base.dists.laplace.pdf.factory":"\nbase.dists.laplace.pdf.factory( μ:number, b:number )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Laplace distribution with scale parameter `b` and location parameter\n    `μ`.\n","base.dists.laplace.quantile":"\nbase.dists.laplace.quantile( p:number, μ:number, b:number )\n    Evaluates the quantile function for a Laplace distribution with scale\n    parameter `b` and location parameter `μ` at a probability `p`.\n","base.dists.laplace.quantile.factory":"\nbase.dists.laplace.quantile.factory( μ:number, b:number )\n    Returns a function for evaluating the quantile function of a Laplace\n    distribution with scale parameter `b` and location parameter `μ`.\n","base.dists.laplace.skewness":"\nbase.dists.laplace.skewness( μ:number, b:number )\n    Returns the skewness of a Laplace distribution with location parameter `μ`\n    and scale parameter `b`.\n","base.dists.laplace.stdev":"\nbase.dists.laplace.stdev( μ:number, b:number )\n    Returns the standard deviation of a Laplace distribution with location\n    parameter `μ` and scale parameter `b`.\n","base.dists.laplace.variance":"\nbase.dists.laplace.variance( μ:number, b:number )\n    Returns the variance of a Laplace distribution with location parameter `μ`\n    and scale parameter `b`.\n","base.dists.levy.cdf":"\nbase.dists.levy.cdf( x:number, μ:number, c:number )\n    Evaluates the cumulative distribution function (CDF) for a Lévy distribution\n    with location parameter `μ` and scale parameter `c` at a value `x`.\n","base.dists.levy.cdf.factory":"\nbase.dists.levy.cdf.factory( μ:number, c:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Lévy distribution with location parameter `μ` and scale parameter `c`.\n","base.dists.levy.entropy":"\nbase.dists.levy.entropy( μ:number, c:number )\n    Returns the entropy of a Lévy distribution with location parameter `μ` and\n    scale parameter `c`.\n","base.dists.levy.Levy":"\nbase.dists.levy.Levy( [μ:number, c:number] )\n    Returns a Lévy distribution object.\n","base.dists.levy.logcdf":"\nbase.dists.levy.logcdf( x:number, μ:number, c:number )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    Lévy distribution with location parameter `μ` and scale parameter `c` at a\n    value `x`.\n","base.dists.levy.logcdf.factory":"\nbase.dists.levy.logcdf.factory( μ:number, c:number )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Lévy distribution with location parameter\n    `μ` and scale parameter `c`.\n","base.dists.levy.logpdf":"\nbase.dists.levy.logpdf( x:number, μ:number, c:number )\n    Evaluates the logarithm of the probability density function (PDF) for a Lévy\n    distribution with location parameter `μ` and scale parameter `c` at a value\n    `x`.\n","base.dists.levy.logpdf.factory":"\nbase.dists.levy.logpdf.factory( μ:number, c:number )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Lévy distribution with location parameter `μ` and scale\n    parameter `c`.\n","base.dists.levy.mean":"\nbase.dists.levy.mean( μ:number, c:number )\n    Returns the expected value of a Lévy distribution with location parameter\n    `μ` and scale parameter `c`.\n","base.dists.levy.median":"\nbase.dists.levy.median( μ:number, c:number )\n    Returns the median of a Lévy distribution with location parameter `μ` and\n    scale parameter `c`.\n","base.dists.levy.mode":"\nbase.dists.levy.mode( μ:number, c:number )\n    Returns the mode of a Lévy distribution with location parameter `μ` and\n    scale parameter `c`.\n","base.dists.levy.pdf":"\nbase.dists.levy.pdf( x:number, μ:number, c:number )\n    Evaluates the probability density function (PDF) for a Lévy distribution\n    with location parameter `μ` and scale parameter `c` at a value `x`.\n","base.dists.levy.pdf.factory":"\nbase.dists.levy.pdf.factory( μ:number, c:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Lévy distribution with location parameter `μ` and scale parameter `c`.\n","base.dists.levy.quantile":"\nbase.dists.levy.quantile( p:number, μ:number, c:number )\n    Evaluates the quantile function for a Lévy distribution with location\n    parameter `μ` and scale parameter `c` at a probability `p`.\n","base.dists.levy.quantile.factory":"\nbase.dists.levy.quantile.factory( μ:number, c:number )\n    Returns a function for evaluating the quantile function of a Lévy\n    distribution with location parameter `μ` and scale parameter `c`.\n","base.dists.levy.stdev":"\nbase.dists.levy.stdev( μ:number, c:number )\n    Returns the standard deviation of a Lévy distribution with location\n    parameter `μ` and scale parameter `c`.\n","base.dists.levy.variance":"\nbase.dists.levy.variance( μ:number, c:number )\n    Returns the variance of a Lévy distribution with location parameter `μ` and\n    scale parameter `c`.\n","base.dists.logistic.cdf":"\nbase.dists.logistic.cdf( x:number, μ:number, s:number )\n    Evaluates the cumulative distribution function (CDF) for a logistic\n    distribution with location parameter `μ` and scale parameter `s` at a value\n    `x`.\n","base.dists.logistic.cdf.factory":"\nbase.dists.logistic.cdf.factory( μ:number, s:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a logistic distribution with location parameter `μ` and scale parameter\n    `s`.\n","base.dists.logistic.entropy":"\nbase.dists.logistic.entropy( μ:number, s:number )\n    Returns the entropy of a logistic distribution with location parameter `μ`\n    and scale parameter `s`.\n","base.dists.logistic.kurtosis":"\nbase.dists.logistic.kurtosis( μ:number, s:number )\n    Returns the excess kurtosis of a logistic distribution with location\n    parameter `μ` and scale parameter `s`.\n","base.dists.logistic.logcdf":"\nbase.dists.logistic.logcdf( x:number, μ:number, s:number )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    logistic distribution with location parameter `μ` and scale parameter `s` at\n    a value `x`.\n","base.dists.logistic.logcdf.factory":"\nbase.dists.logistic.logcdf.factory( μ:number, s:number )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Logistic distribution with location\n    parameter `μ` and scale parameter `s`.\n","base.dists.logistic.Logistic":"\nbase.dists.logistic.Logistic( [μ:number, s:number] )\n    Returns a logistic distribution object.\n","base.dists.logistic.logpdf":"\nbase.dists.logistic.logpdf( x:number, μ:number, s:number )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    logistic distribution with location parameter `μ` and scale parameter `s` at\n    a value `x`.\n","base.dists.logistic.logpdf.factory":"\nbase.dists.logistic.logpdf.factory( μ:number, s:number )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Logistic distribution with location parameter `μ` and\n    scale parameter `s`.\n","base.dists.logistic.mean":"\nbase.dists.logistic.mean( μ:number, s:number )\n    Returns the expected value of a logistic distribution with location\n    parameter `μ` and scale parameter `s`.\n","base.dists.logistic.median":"\nbase.dists.logistic.median( μ:number, s:number )\n    Returns the median of a logistic distribution with location parameter `μ`\n    and scale parameter `s`.\n","base.dists.logistic.mgf":"\nbase.dists.logistic.mgf( t:number, μ:number, s:number )\n    Evaluates the moment-generating function (MGF) for a logistic distribution\n    with location parameter `μ` and scale parameter `s` at a value `t`.\n","base.dists.logistic.mgf.factory":"\nbase.dists.logistic.mgf.factory( μ:number, s:number )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a Logistic distribution with location parameter `μ` and scale parameter\n    `s`.\n","base.dists.logistic.mode":"\nbase.dists.logistic.mode( μ:number, s:number )\n    Returns the mode of a logistic distribution with location parameter `μ` and\n    scale parameter `s`.\n","base.dists.logistic.pdf":"\nbase.dists.logistic.pdf( x:number, μ:number, s:number )\n    Evaluates the probability density function (PDF) for a logistic distribution\n    with location parameter `μ` and scale parameter `s` at a value `x`.\n","base.dists.logistic.pdf.factory":"\nbase.dists.logistic.pdf.factory( μ:number, s:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Logistic distribution with location parameter `μ` and scale parameter `s`.\n","base.dists.logistic.quantile":"\nbase.dists.logistic.quantile( p:number, μ:number, s:number )\n    Evaluates the quantile function for a logistic distribution with location\n    parameter `μ` and scale parameter `s` at a probability `p`.\n","base.dists.logistic.quantile.factory":"\nbase.dists.logistic.quantile.factory( μ:number, s:number )\n    Returns a function for evaluating the quantile function of a logistic\n    distribution with location parameter `μ` and scale parameter `s`.\n","base.dists.logistic.skewness":"\nbase.dists.logistic.skewness( μ:number, s:number )\n    Returns the skewness of a logistic distribution with location parameter `μ`\n    and scale parameter `s`.\n","base.dists.logistic.stdev":"\nbase.dists.logistic.stdev( μ:number, s:number )\n    Returns the standard deviation of a logistic distribution with location\n    parameter `μ` and scale parameter `s`.\n","base.dists.logistic.variance":"\nbase.dists.logistic.variance( μ:number, s:number )\n    Returns the variance of a logistic distribution with location parameter `μ`\n    and scale parameter `s`.\n","base.dists.lognormal.cdf":"\nbase.dists.lognormal.cdf( x:number, μ:number, σ:number )\n    Evaluates the cumulative distribution function (CDF) for a lognormal\n    distribution with location parameter `μ` and scale parameter `σ` at a value\n    `x`.\n","base.dists.lognormal.cdf.factory":"\nbase.dists.lognormal.cdf.factory( μ:number, σ:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a lognormal distribution with location parameter `μ` and scale parameter\n    `σ`.\n","base.dists.lognormal.entropy":"\nbase.dists.lognormal.entropy( μ:number, σ:number )\n    Returns the differential entropy of a lognormal distribution with location\n    `μ` and scale `σ` (in nats).\n","base.dists.lognormal.kurtosis":"\nbase.dists.lognormal.kurtosis( μ:number, σ:number )\n    Returns the excess kurtosis of a lognormal distribution with location `μ`\n    and scale `σ`.\n","base.dists.lognormal.LogNormal":"\nbase.dists.lognormal.LogNormal( [μ:number, σ:number] )\n    Returns a lognormal distribution object.\n","base.dists.lognormal.logcdf":"\nbase.dists.lognormal.logcdf( x:number, μ:number, σ:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a lognormal distribution with mean `μ` and standard deviation `σ`\n    at a value `x`.\n","base.dists.lognormal.logcdf.factory":"\nbase.dists.lognormal.logcdf.factory( μ:number, σ:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a lognormal distribution with mean `μ` and\n    standard deviation `σ`.\n","base.dists.lognormal.logpdf":"\nbase.dists.lognormal.logpdf( x:number, μ:number, σ:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a lognormal distribution with location parameter `μ` and scale parameter\n    `σ` at a value `x`.\n","base.dists.lognormal.logpdf.factory":"\nbase.dists.lognormal.logpdf.factory( μ:number, σ:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a lognormal distribution with location parameter\n    `μ` and scale parameter `σ`.\n","base.dists.lognormal.mean":"\nbase.dists.lognormal.mean( μ:number, σ:number )\n    Returns the expected value of a lognormal distribution with location `μ` and\n    scale `σ`.\n","base.dists.lognormal.median":"\nbase.dists.lognormal.median( μ:number, σ:number )\n    Returns the median of a lognormal distribution with location `μ` and scale\n    `σ`.\n","base.dists.lognormal.mode":"\nbase.dists.lognormal.mode( μ:number, σ:number )\n    Returns the mode of a lognormal distribution with location `μ` and scale\n    `σ`.\n","base.dists.lognormal.pdf":"\nbase.dists.lognormal.pdf( x:number, μ:number, σ:number )\n    Evaluates the probability density function (PDF) for a lognormal\n    distribution with location parameter `μ` and scale parameter `σ` at a value\n    `x`.\n","base.dists.lognormal.pdf.factory":"\nbase.dists.lognormal.pdf.factory( μ:number, σ:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a lognormal distribution with location parameter `μ` and scale parameter\n    `σ`.\n","base.dists.lognormal.quantile":"\nbase.dists.lognormal.quantile( p:number, μ:number, σ:number )\n    Evaluates the quantile function for a lognormal distribution with location\n    parameter `μ` and scale parameter `σ` at a probability `p`.\n","base.dists.lognormal.quantile.factory":"\nbase.dists.lognormal.quantile.factory( μ:number, σ:number )\n    Returns a function for evaluating the quantile function of a lognormal\n    distribution with location parameter `μ` and scale parameter `σ`.\n","base.dists.lognormal.skewness":"\nbase.dists.lognormal.skewness( μ:number, σ:number )\n    Returns the skewness of a lognormal distribution with location `μ` and scale\n    `σ`.\n","base.dists.lognormal.stdev":"\nbase.dists.lognormal.stdev( μ:number, σ:number )\n    Returns the standard deviation of a lognormal distribution with location `μ`\n    and scale `σ`.\n","base.dists.lognormal.variance":"\nbase.dists.lognormal.variance( μ:number, σ:number )\n    Returns the variance of a lognormal distribution with location `μ` and scale\n    `σ`.\n","base.dists.negativeBinomial.cdf":"\nbase.dists.negativeBinomial.cdf( x:number, r:number, p:number )\n    Evaluates the cumulative distribution function (CDF) for a negative binomial\n    distribution with number of successes until experiment is stopped `r` and\n    success probability `p` at a value `x`.\n","base.dists.negativeBinomial.cdf.factory":"\nbase.dists.negativeBinomial.cdf.factory( r:number, p:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a negative binomial distribution with number of successes until\n    experiment is stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.kurtosis":"\nbase.dists.negativeBinomial.kurtosis( r:integer, p:number )\n    Returns the excess kurtosis of a negative binomial distribution.\n","base.dists.negativeBinomial.logpmf":"\nbase.dists.negativeBinomial.logpmf( x:number, r:number, p:number )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    negative binomial distribution with number of successes until experiment is\n    stopped `r` and success probability `p` at a value `x`.\n","base.dists.negativeBinomial.logpmf.factory":"\nbase.dists.negativeBinomial.logpmf.factory( r:number, p:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a negative binomial distribution with number of\n    successes until experiment is stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.mean":"\nbase.dists.negativeBinomial.mean( r:integer, p:number )\n    Returns the expected value of a negative binomial distribution.\n","base.dists.negativeBinomial.mgf":"\nbase.dists.negativeBinomial.mgf( x:number, r:number, p:number )\n    Evaluates the moment-generating function (MGF) for a negative binomial\n    distribution with number of successes until experiment is stopped `r` and\n    success probability `p` at a value `t`.\n","base.dists.negativeBinomial.mgf.factory":"\nbase.dists.negativeBinomial.mgf.factory( r:number, p:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    negative binomial distribution with number of successes until experiment is\n    stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.mode":"\nbase.dists.negativeBinomial.mode( r:integer, p:number )\n    Returns the mode of a negative binomial distribution.\n","base.dists.negativeBinomial.NegativeBinomial":"\nbase.dists.negativeBinomial.NegativeBinomial( [r:number, p:number] )\n    Returns a negative binomial distribution object.\n","base.dists.negativeBinomial.pmf":"\nbase.dists.negativeBinomial.pmf( x:number, r:number, p:number )\n    Evaluates the probability mass function (PMF) for a negative binomial\n    distribution with number of successes until experiment is stopped `r` and\n    success probability `p` at a value `x`.\n","base.dists.negativeBinomial.pmf.factory":"\nbase.dists.negativeBinomial.pmf.factory( r:number, p:number )\n    Returns a function for evaluating the probability mass function (PMF) of a\n    negative binomial distribution with number of successes until experiment is\n    stopped `r` and success probability `p`.\n","base.dists.negativeBinomial.quantile":"\nbase.dists.negativeBinomial.quantile( k:number, r:number, p:number )\n    Evaluates the quantile function for a negative binomial distribution with\n    number of successes until experiment is stopped `r` and success probability\n    `p` at a probability `k`.\n","base.dists.negativeBinomial.quantile.factory":"\nbase.dists.negativeBinomial.quantile.factory( r:number, p:number )\n    Returns a function for evaluating the quantile function of a negative\n    binomial distribution with number of successes until experiment is stopped\n    `r` and success probability `p`.\n","base.dists.negativeBinomial.skewness":"\nbase.dists.negativeBinomial.skewness( r:integer, p:number )\n    Returns the skewness of a negative binomial distribution.\n","base.dists.negativeBinomial.stdev":"\nbase.dists.negativeBinomial.stdev( r:integer, p:number )\n    Returns the standard deviation of a negative binomial distribution.\n","base.dists.negativeBinomial.variance":"\nbase.dists.negativeBinomial.variance( r:integer, p:number )\n    Returns the variance of a negative binomial distribution.\n","base.dists.normal.cdf":"\nbase.dists.normal.cdf( x:number, μ:number, σ:number )\n    Evaluates the cumulative distribution function (CDF) for a normal\n    distribution with mean `μ` and standard deviation `σ` at a value `x`.\n","base.dists.normal.cdf.factory":"\nbase.dists.normal.cdf.factory( μ:number, σ:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.entropy":"\nbase.dists.normal.entropy( μ:number, σ:number )\n    Returns the differential entropy of a normal distribution with mean `μ` and\n    standard deviation `σ`.\n","base.dists.normal.kurtosis":"\nbase.dists.normal.kurtosis( μ:number, σ:number )\n    Returns the excess kurtosis of a normal distribution with mean `μ` and\n    standard deviation `σ`.\n","base.dists.normal.logcdf":"\nbase.dists.normal.logcdf( x:number, μ:number, σ:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a normal distribution with mean `μ` and standard deviation `σ` at\n    a value `x`.\n","base.dists.normal.logcdf.factory":"\nbase.dists.normal.logcdf.factory( μ:number, σ:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a normal distribution with mean `μ` and\n    standard deviation `σ`.\n","base.dists.normal.logpdf":"\nbase.dists.normal.logpdf( x:number, μ:number, σ:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a normal distribution with mean `μ` and standard deviation `σ` at a\n    value `x`.\n","base.dists.normal.logpdf.factory":"\nbase.dists.normal.logpdf.factory( μ:number, σ:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a normal distribution with mean `μ` and standard\n    deviation `σ`.\n","base.dists.normal.mean":"\nbase.dists.normal.mean( μ:number, σ:number )\n    Returns the expected value of a normal distribution with mean `μ` and\n    standard deviation `σ`.\n","base.dists.normal.median":"\nbase.dists.normal.median( μ:number, σ:number )\n    Returns the median of a normal distribution with mean `μ` and standard\n    deviation `σ`.\n","base.dists.normal.mgf":"\nbase.dists.normal.mgf( x:number, μ:number, σ:number )\n    Evaluates the moment-generating function (MGF) for a normal distribution\n    with mean `μ` and standard deviation `σ` at a value `t`.\n","base.dists.normal.mgf.factory":"\nbase.dists.normal.mgf.factory( μ:number, σ:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.mode":"\nbase.dists.normal.mode( μ:number, σ:number )\n    Returns the mode of a normal distribution with mean `μ` and standard\n    deviation `σ`.\n","base.dists.normal.Normal":"\nbase.dists.normal.Normal( [μ:number, σ:number] )\n    Returns a normal distribution object.\n","base.dists.normal.pdf":"\nbase.dists.normal.pdf( x:number, μ:number, σ:number )\n    Evaluates the probability density function (PDF) for a normal distribution\n    with mean `μ` and standard deviation `σ` at a value `x`.\n","base.dists.normal.pdf.factory":"\nbase.dists.normal.pdf.factory( μ:number, σ:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.quantile":"\nbase.dists.normal.quantile( p:number, μ:number, σ:number )\n    Evaluates the quantile function for a normal distribution with mean `μ` and\n    standard deviation `σ` at a probability `p`.\n","base.dists.normal.quantile.factory":"\nbase.dists.normal.quantile.factory( μ:number, σ:number )\n    Returns a function for evaluating the quantile function\n    of a normal distribution with mean `μ` and standard deviation `σ`.\n","base.dists.normal.skewness":"\nbase.dists.normal.skewness( μ:number, σ:number )\n    Returns the skewness of a normal distribution with mean `μ` and standard\n    deviation `σ`.\n","base.dists.normal.stdev":"\nbase.dists.normal.stdev( μ:number, σ:number )\n    Returns the standard deviation of a normal distribution with mean `μ` and\n    standard deviation `σ`.\n","base.dists.normal.variance":"\nbase.dists.normal.variance( μ:number, σ:number )\n    Returns the variance of a normal distribution with mean `μ` and standard\n    deviation `σ`.\n","base.dists.pareto1.cdf":"\nbase.dists.pareto1.cdf( x:number, α:number, β:number )\n    Evaluates the cumulative distribution function (CDF) for a Pareto (Type I)\n    distribution with shape parameter `α` and scale parameter `β` at a value\n    `x`.\n","base.dists.pareto1.cdf.factory":"\nbase.dists.pareto1.cdf.factory( α:number, β:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Pareto (Type I) distribution with shape parameter `α` and scale\n    parameter `β`.\n","base.dists.pareto1.entropy":"\nbase.dists.pareto1.entropy( α:number, β:number )\n    Returns the differential entropy of a Pareto (Type I) distribution\n    (in nats).\n","base.dists.pareto1.kurtosis":"\nbase.dists.pareto1.kurtosis( α:number, β:number )\n    Returns the excess kurtosis of a Pareto (Type I) distribution.\n","base.dists.pareto1.logcdf":"\nbase.dists.pareto1.logcdf( x:number, α:number, β:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a Pareto (Type I) distribution with shape parameter `α` and scale\n    parameter `β` at a value `x`.\n","base.dists.pareto1.logcdf.factory":"\nbase.dists.pareto1.logcdf.factory( α:number, β:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Pareto (Type I) distribution with shape\n    parameter `α` and scale parameter `β`.\n","base.dists.pareto1.logpdf":"\nbase.dists.pareto1.logpdf( x:number, α:number, β:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a Pareto (Type I) distribution with shape parameter `α` and scale\n    parameter `β` at a value `x`.\n","base.dists.pareto1.logpdf.factory":"\nbase.dists.pareto1.logpdf.factory( α:number, β:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a Pareto (Type I) distribution with shape\n    parameter `α` and scale parameter `β`.\n","base.dists.pareto1.mean":"\nbase.dists.pareto1.mean( α:number, β:number )\n    Returns the expected value of a Pareto (Type I) distribution.\n","base.dists.pareto1.median":"\nbase.dists.pareto1.median( α:number, β:number )\n    Returns the median of a Pareto (Type I) distribution.\n","base.dists.pareto1.mode":"\nbase.dists.pareto1.mode( α:number, β:number )\n    Returns the mode of a Pareto (Type I) distribution.\n","base.dists.pareto1.Pareto1":"\nbase.dists.pareto1.Pareto1( [α:number, β:number] )\n    Returns a Pareto (Type I) distribution object.\n","base.dists.pareto1.pdf":"\nbase.dists.pareto1.pdf( x:number, α:number, β:number )\n    Evaluates the probability density function (PDF) for a Pareto (Type I)\n    distribution with shape parameter `α` and scale parameter `β` at a value\n    `x`.\n","base.dists.pareto1.pdf.factory":"\nbase.dists.pareto1.pdf.factory( α:number, β:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Pareto (Type I) distribution with shape parameter `α` and scale parameter\n    `β`.\n","base.dists.pareto1.quantile":"\nbase.dists.pareto1.quantile( p:number, α:number, β:number )\n    Evaluates the quantile function for a Pareto (Type I) distribution with\n    shape parameter `α` and scale parameter `β` at a probability `p`.\n","base.dists.pareto1.quantile.factory":"\nbase.dists.pareto1.quantile.factory( α:number, β:number )\n    Returns a function for evaluating the quantile function of a Pareto (Type I)\n    distribution with shape parameter `α` and scale parameter `β`.\n","base.dists.pareto1.skewness":"\nbase.dists.pareto1.skewness( α:number, β:number )\n    Returns the skewness of a Pareto (Type I) distribution.\n","base.dists.pareto1.stdev":"\nbase.dists.pareto1.stdev( α:number, β:number )\n    Returns the standard deviation of a Pareto (Type I) distribution.\n","base.dists.pareto1.variance":"\nbase.dists.pareto1.variance( α:number, β:number )\n    Returns the variance of a Pareto (Type I) distribution.\n","base.dists.poisson.cdf":"\nbase.dists.poisson.cdf( x:number, λ:number )\n    Evaluates the cumulative distribution function (CDF) for a Poisson\n    distribution with mean parameter `λ` at a value `x`.\n","base.dists.poisson.cdf.factory":"\nbase.dists.poisson.cdf.factory( λ:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.entropy":"\nbase.dists.poisson.entropy( λ:number )\n    Returns the entropy of a Poisson distribution.\n","base.dists.poisson.kurtosis":"\nbase.dists.poisson.kurtosis( λ:number )\n    Returns the excess kurtosis of a Poisson distribution.\n","base.dists.poisson.logpmf":"\nbase.dists.poisson.logpmf( x:number, λ:number )\n    Evaluates the natural logarithm of the probability mass function (PMF) for a\n    Poisson distribution with mean parameter `λ` at a value `x`.\n","base.dists.poisson.logpmf.factory":"\nbase.dists.poisson.logpmf.factory( λ:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    mass function (PMF) of a Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.mean":"\nbase.dists.poisson.mean( λ:number )\n    Returns the expected value of a Poisson distribution.\n","base.dists.poisson.median":"\nbase.dists.poisson.median( λ:number )\n    Returns the median of a Poisson distribution.\n","base.dists.poisson.mgf":"\nbase.dists.poisson.mgf( x:number, λ:number )\n    Evaluates the moment-generating function (MGF) for a Poisson distribution\n    with mean parameter `λ` at a value `x`.\n","base.dists.poisson.mgf.factory":"\nbase.dists.poisson.mgf.factory( λ:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.mode":"\nbase.dists.poisson.mode( λ:number )\n    Returns the mode of a Poisson distribution.\n","base.dists.poisson.pmf":"\nbase.dists.poisson.pmf( x:number, λ:number )\n    Evaluates the probability mass function (PMF) for a Poisson\n    distribution with mean parameter `λ` at a value `x`.\n","base.dists.poisson.pmf.factory":"\nbase.dists.poisson.pmf.factory( λ:number )\n    Returns a function for evaluating the probability mass function (PMF)\n    of a Poisson distribution with mean parameter `λ`.\n","base.dists.poisson.Poisson":"\nbase.dists.poisson.Poisson( [λ:number] )\n    Returns a Poisson distribution object.\n","base.dists.poisson.quantile":"\nbase.dists.poisson.quantile( p:number, λ:number )\n    Evaluates the quantile function for a Poisson distribution with mean\n    parameter `λ` at a probability `p`.\n","base.dists.poisson.quantile.factory":"\nbase.dists.poisson.quantile.factory( λ:number )\n    Returns a function for evaluating the quantile function of a Poisson\n    distribution with mean parameter `λ`.\n","base.dists.poisson.skewness":"\nbase.dists.poisson.skewness( λ:number )\n    Returns the skewness of a Poisson distribution.\n","base.dists.poisson.stdev":"\nbase.dists.poisson.stdev( λ:number )\n    Returns the standard deviation of a Poisson distribution.\n","base.dists.poisson.variance":"\nbase.dists.poisson.variance( λ:number )\n    Returns the variance of a Poisson distribution.\n","base.dists.rayleigh.cdf":"\nbase.dists.rayleigh.cdf( x:number, sigma:number )\n    Evaluates the cumulative distribution function (CDF) for a Rayleigh\n    distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.cdf.factory":"\nbase.dists.rayleigh.cdf.factory( sigma:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.entropy":"\nbase.dists.rayleigh.entropy( σ:number )\n    Returns the differential entropy of a Rayleigh distribution.\n","base.dists.rayleigh.kurtosis":"\nbase.dists.rayleigh.kurtosis( σ:number )\n    Returns the excess kurtosis of a Rayleigh distribution.\n","base.dists.rayleigh.logcdf":"\nbase.dists.rayleigh.logcdf( x:number, sigma:number )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    Rayleigh distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.logcdf.factory":"\nbase.dists.rayleigh.logcdf.factory( sigma:number )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Rayleigh distribution with scale parameter\n    `sigma`.\n","base.dists.rayleigh.logpdf":"\nbase.dists.rayleigh.logpdf( x:number, sigma:number )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    Rayleigh distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.logpdf.factory":"\nbase.dists.rayleigh.logpdf.factory( sigma:number )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.mean":"\nbase.dists.rayleigh.mean( σ:number )\n    Returns the expected value of a Rayleigh distribution.\n","base.dists.rayleigh.median":"\nbase.dists.rayleigh.median( σ:number )\n    Returns the median of a Rayleigh distribution.\n","base.dists.rayleigh.mgf":"\nbase.dists.rayleigh.mgf( t:number, sigma:number )\n    Evaluates the moment-generating function (MGF) for a Rayleigh distribution\n    with scale parameter `sigma` at a value `t`.\n","base.dists.rayleigh.mgf.factory":"\nbase.dists.rayleigh.mgf.factory( sigma:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.mode":"\nbase.dists.rayleigh.mode( σ:number )\n    Returns the mode of a Rayleigh distribution.\n","base.dists.rayleigh.pdf":"\nbase.dists.rayleigh.pdf( x:number, sigma:number )\n    Evaluates the probability density function (PDF) for a Rayleigh\n    distribution with scale parameter `sigma` at a value `x`.\n","base.dists.rayleigh.pdf.factory":"\nbase.dists.rayleigh.pdf.factory( sigma:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Rayleigh distribution with scale parameter `sigma`.\n","base.dists.rayleigh.quantile":"\nbase.dists.rayleigh.quantile( p:number, sigma:number )\n    Evaluates the quantile function for a Rayleigh distribution with scale\n    parameter `sigma` at a probability `p`.\n","base.dists.rayleigh.quantile.factory":"\nbase.dists.rayleigh.quantile.factory( sigma:number )\n    Returns a function for evaluating the quantile function of a Rayleigh\n    distribution with scale parameter `sigma`.\n","base.dists.rayleigh.Rayleigh":"\nbase.dists.rayleigh.Rayleigh( [σ:number] )\n    Returns a Rayleigh distribution object.\n","base.dists.rayleigh.skewness":"\nbase.dists.rayleigh.skewness( σ:number )\n    Returns the skewness of a Rayleigh distribution.\n","base.dists.rayleigh.stdev":"\nbase.dists.rayleigh.stdev( σ:number )\n    Returns the standard deviation of a Rayleigh distribution.\n","base.dists.rayleigh.variance":"\nbase.dists.rayleigh.variance( σ:number )\n    Returns the variance of a Rayleigh distribution.\n","base.dists.signrank.cdf":"\nbase.dists.signrank.cdf( x:number, n:integer )\n    Evaluates the cumulative distribution function (CDF) for the distribution of\n    the Wilcoxon signed rank test statistic with `n` observations.\n","base.dists.signrank.cdf.factory":"\nbase.dists.signrank.cdf.factory( n:integer )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of the distribution of the Wilcoxon signed rank test statistic.\n","base.dists.signrank.pdf":"\nbase.dists.signrank.pdf( x:number, n:integer )\n    Evaluates the probability density function (PDF) for the distribution of\n    the Wilcoxon signed rank test statistic with `n` observations.\n","base.dists.signrank.pdf.factory":"\nbase.dists.signrank.pdf.factory( n:integer )\n    Returns a function for evaluating the probability density function (PDF)\n    of the distribution of the Wilcoxon signed rank test statistic.\n","base.dists.signrank.quantile":"\nbase.dists.signrank.quantile( p:number, n:integer )\n    Evaluates the quantile function for the Wilcoxon signed rank test statistic\n    with `n` observations at a probability `p`.\n","base.dists.signrank.quantile.factory":"\nbase.dists.signrank.quantile.factory( n:integer )\n    Returns a function for evaluating the quantile function of the Wilcoxon\n    signed rank test statistic with `n` observations.\n","base.dists.studentizedRange.cdf":"\nbase.dists.studentizedRange.cdf( x:number, r:number, v:number[, \n  nranges:integer] )\n    Evaluates the cumulative distribution function (CDF) of a studentized range\n    distribution.\n","base.dists.studentizedRange.cdf.factory":"\nbase.dists.studentizedRange.cdf.factory( r:number, v:number[, nranges:integer] )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a studentized range distribution.\n","base.dists.studentizedRange.quantile":"\nbase.dists.studentizedRange.quantile( p:number, r:number, v:number[, \n  nranges:integer] )\n    Evaluates the quantile function for a studentized range distribution.\n","base.dists.studentizedRange.quantile.factory":"\nbase.dists.studentizedRange.quantile.factory( r:number, v:number[, \n  nranges:integer] )\n    Returns a function for evaluating the quantile function of a studentized\n    range distribution.\n","base.dists.t.cdf":"\nbase.dists.t.cdf( x:number, v:number )\n    Evaluates the cumulative distribution function (CDF) for a Student's t\n    distribution with degrees of freedom `v` at a value `x`.\n","base.dists.t.cdf.factory":"\nbase.dists.t.cdf.factory( v:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Student's t distribution with degrees of freedom `v`.\n","base.dists.t.entropy":"\nbase.dists.t.entropy( v:number )\n    Returns the differential entropy of a Student's t distribution.\n","base.dists.t.kurtosis":"\nbase.dists.t.kurtosis( v:number )\n    Returns the excess kurtosis of a Student's t distribution.\n","base.dists.t.logcdf":"\nbase.dists.t.logcdf( x:number, v:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a Student's t distribution with degrees of freedom `v` at a value\n    `x`.\n","base.dists.t.logcdf.factory":"\nbase.dists.t.logcdf.factory( v:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a Student's t distribution with degrees of\n    freedom `v`.\n","base.dists.t.logpdf":"\nbase.dists.t.logpdf( x:number, v:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a Student's t distribution with degrees of freedom `v` at a value `x`.\n","base.dists.t.logpdf.factory":"\nbase.dists.t.logpdf.factory( v:number )\n    Returns a function for evaluating the natural logarithm of the probability\n    density function (PDF) of a Student's t distribution with degrees of\n    freedom `v`.\n","base.dists.t.mean":"\nbase.dists.t.mean( v:number )\n    Returns the expected value of a Student's t distribution.\n","base.dists.t.median":"\nbase.dists.t.median( v:number )\n    Returns the median of a Student's t distribution.\n","base.dists.t.mode":"\nbase.dists.t.mode( v:number )\n    Returns the mode of a Student's t distribution.\n","base.dists.t.pdf":"\nbase.dists.t.pdf( x:number, v:number )\n    Evaluates the probability density function (PDF) for a Student's t\n    distribution with degrees of freedom `v` at a value `x`.\n","base.dists.t.pdf.factory":"\nbase.dists.t.pdf.factory( v:number )\n    Returns a function for evaluating the probability density function (PDF)\n    of a Student's t distribution with degrees of freedom `v`.\n","base.dists.t.quantile":"\nbase.dists.t.quantile( p:number, v:number )\n    Evaluates the quantile function for a Student's t distribution with degrees\n    of freedom `v` at a probability `p`.\n","base.dists.t.quantile.factory":"\nbase.dists.t.quantile.factory( v:number )\n    Returns a function for evaluating the quantile function of a Student's t\n    distribution with degrees of freedom `v`.\n","base.dists.t.skewness":"\nbase.dists.t.skewness( v:number )\n    Returns the skewness of a Student's t distribution.\n","base.dists.t.stdev":"\nbase.dists.t.stdev( v:number )\n    Returns the standard deviation of a Student's t distribution.\n","base.dists.t.T":"\nbase.dists.t.T( [v:number] )\n    Returns a Student's t distribution object.\n","base.dists.t.variance":"\nbase.dists.t.variance( v:number )\n    Returns the variance of a Student's t distribution.\n","base.dists.triangular.cdf":"\nbase.dists.triangular.cdf( x:number, a:number, b:number, c:number )\n    Evaluates the cumulative distribution function (CDF) for a triangular\n    distribution with minimum support `a`, maximum support `b`, and mode `c` at\n    a value `x`.\n","base.dists.triangular.cdf.factory":"\nbase.dists.triangular.cdf.factory( a:number, b:number, c:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a triangular distribution with minimum support `a`, maximum support `b`,\n    and mode `c`.\n","base.dists.triangular.entropy":"\nbase.dists.triangular.entropy( a:number, b:number, c:number )\n    Returns the differential entropy of a triangular distribution (in nats).\n","base.dists.triangular.kurtosis":"\nbase.dists.triangular.kurtosis( a:number, b:number, c:number )\n    Returns the excess kurtosis of a triangular distribution.\n","base.dists.triangular.logcdf":"\nbase.dists.triangular.logcdf( x:number, a:number, b:number, c:number )\n    Evaluates the natural logarithm of the cumulative distribution function\n    (CDF) for a triangular distribution with minimum support `a`, maximum\n    support `b`, and mode `c` at a value `x`.\n","base.dists.triangular.logcdf.factory":"\nbase.dists.triangular.logcdf.factory( a:number, b:number, c:number )\n    Returns a function for evaluating the natural logarithm of the cumulative\n    distribution function (CDF) of a triangular distribution with minimum\n    support `a`, maximum support `b`, and mode `c`.\n","base.dists.triangular.logpdf":"\nbase.dists.triangular.logpdf( x:number, a:number, b:number, c:number )\n    Evaluates the natural logarithm of the probability density function (PDF)\n    for a triangular distribution with minimum support `a`, maximum support `b`,\n    and mode `c` at a value `x`.\n","base.dists.triangular.logpdf.factory":"\nbase.dists.triangular.logpdf.factory( a:number, b:number, c:number )\n    Returns a function for evaluating the natural logarithm of the  probability\n    density function (PDF) of a triangular distribution with minimum support\n    `a`, maximum support `b`, and mode `c`.\n","base.dists.triangular.mean":"\nbase.dists.triangular.mean( a:number, b:number, c:number )\n    Returns the expected value of a triangular distribution.\n","base.dists.triangular.median":"\nbase.dists.triangular.median( a:number, b:number, c:number )\n    Returns the median of a triangular distribution.\n","base.dists.triangular.mgf":"\nbase.dists.triangular.mgf( t:number, a:number, b:number, c:number )\n    Evaluates the moment-generating function (MGF) for a triangular distribution\n    with minimum support `a`, maximum support `b`, and mode `c` at a value `t`.\n","base.dists.triangular.mgf.factory":"\nbase.dists.triangular.mgf.factory( a:number, b:number, c:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    triangular distribution with minimum support `a`, maximum support `b`, and\n    mode `c`.\n","base.dists.triangular.mode":"\nbase.dists.triangular.mode( a:number, b:number, c:number )\n    Returns the mode of a triangular distribution.\n","base.dists.triangular.pdf":"\nbase.dists.triangular.pdf( x:number, a:number, b:number, c:number )\n    Evaluates the probability density function (PDF) for a triangular\n    distribution with minimum support `a`, maximum support `b`, and mode `c` at\n    a value `x`.\n","base.dists.triangular.pdf.factory":"\nbase.dists.triangular.pdf.factory( a:number, b:number, c:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a triangular distribution with minimum support `a`, maximum support `b`, and\n    mode `c`.\n","base.dists.triangular.quantile":"\nbase.dists.triangular.quantile( p:number, a:number, b:number, c:number )\n    Evaluates the quantile function for a triangular distribution with minimum\n    support `a`, maximum support `b`, and mode `c` at a value `x`.\n","base.dists.triangular.quantile.factory":"\nbase.dists.triangular.quantile.factory( a:number, b:number, c:number )\n    Returns a function for evaluating the quantile function of a triangular\n    distribution with minimum support `a`, maximum support `b`, and mode `c`.\n","base.dists.triangular.skewness":"\nbase.dists.triangular.skewness( a:number, b:number, c:number )\n    Returns the skewness of a triangular distribution.\n","base.dists.triangular.stdev":"\nbase.dists.triangular.stdev( a:number, b:number, c:number )\n    Returns the standard deviation of a triangular distribution.\n","base.dists.triangular.Triangular":"\nbase.dists.triangular.Triangular( [a:number, b:number, c:number] )\n    Returns a triangular distribution object.\n","base.dists.triangular.variance":"\nbase.dists.triangular.variance( a:number, b:number, c:number )\n    Returns the variance of a triangular distribution.\n","base.dists.uniform.cdf":"\nbase.dists.uniform.cdf( x:number, a:number, b:number )\n    Evaluates the cumulative distribution function (CDF) for a uniform\n    distribution with minimum support `a` and maximum support `b` at a value\n    `x`.\n","base.dists.uniform.cdf.factory":"\nbase.dists.uniform.cdf.factory( a:number, b:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.entropy":"\nbase.dists.uniform.entropy( a:number, b:number )\n    Returns the differential entropy of a uniform distribution.\n","base.dists.uniform.kurtosis":"\nbase.dists.uniform.kurtosis( a:number, b:number )\n    Returns the excess kurtosis of a uniform distribution.\n","base.dists.uniform.logcdf":"\nbase.dists.uniform.logcdf( x:number, a:number, b:number )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    uniform distribution with minimum support `a` and maximum support `b` at a\n    value `x`.\n","base.dists.uniform.logcdf.factory":"\nbase.dists.uniform.logcdf.factory( a:number, b:number )\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a uniform distribution with minimum support\n    `a` and maximum support `b`.\n","base.dists.uniform.logpdf":"\nbase.dists.uniform.logpdf( x:number, a:number, b:number )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    uniform distribution with minimum support `a` and maximum support `b` at a\n    value `x`.\n","base.dists.uniform.logpdf.factory":"\nbase.dists.uniform.logpdf.factory( a:number, b:number )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a uniform distribution with minimum support `a` and\n    maximum support `b`.\n","base.dists.uniform.mean":"\nbase.dists.uniform.mean( a:number, b:number )\n    Returns the expected value of a uniform distribution.\n","base.dists.uniform.median":"\nbase.dists.uniform.median( a:number, b:number )\n    Returns the median of a uniform distribution.\n","base.dists.uniform.mgf":"\nbase.dists.uniform.mgf( t:number, a:number, b:number )\n    Evaluates the moment-generating function (MGF) for a uniform\n    distribution with minimum support `a` and maximum support `b` at a value\n    `t`.\n","base.dists.uniform.mgf.factory":"\nbase.dists.uniform.mgf.factory( a:number, b:number )\n    Returns a function for evaluating the moment-generating function (MGF)\n    of a uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.pdf":"\nbase.dists.uniform.pdf( x:number, a:number, b:number )\n    Evaluates the probability density function (PDF) for a uniform distribution\n    with minimum support `a` and maximum support `b` at a value `x`.\n","base.dists.uniform.pdf.factory":"\nbase.dists.uniform.pdf.factory( a:number, b:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a uniform distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.quantile":"\nbase.dists.uniform.quantile( p:number, a:number, b:number )\n    Evaluates the quantile function for a uniform distribution with minimum\n    support `a` and maximum support `b` at a probability `p`.\n","base.dists.uniform.quantile.factory":"\nbase.dists.uniform.quantile.factory( a:number, b:number )\n    Returns a function for evaluating the quantile function of a uniform\n    distribution with minimum support `a` and maximum support `b`.\n","base.dists.uniform.skewness":"\nbase.dists.uniform.skewness( a:number, b:number )\n    Returns the skewness of a uniform distribution.\n","base.dists.uniform.stdev":"\nbase.dists.uniform.stdev( a:number, b:number )\n    Returns the standard deviation of a uniform distribution.\n","base.dists.uniform.Uniform":"\nbase.dists.uniform.Uniform( [a:number, b:number] )\n    Returns a uniform distribution object.\n","base.dists.uniform.variance":"\nbase.dists.uniform.variance( a:number, b:number )\n    Returns the variance of a uniform distribution.\n","base.dists.weibull.cdf":"\nbase.dists.weibull.cdf( x:number, k:number, λ:number )\n    Evaluates the cumulative distribution function (CDF) for a Weibull\n    distribution with shape parameter `k` and scale parameter `λ` at a value\n    `x`.\n","base.dists.weibull.cdf.factory":"\nbase.dists.weibull.cdf.factory( k:number, λ:number )\n    Returns a function for evaluating the cumulative distribution function (CDF)\n    of a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n","base.dists.weibull.entropy":"\nbase.dists.weibull.entropy( k:number, λ:number )\n    Returns the differential entropy of a Weibull distribution (in nats).\n","base.dists.weibull.kurtosis":"\nbase.dists.weibull.kurtosis( k:number, λ:number )\n    Returns the excess kurtosis of a Weibull distribution.\n","base.dists.weibull.logcdf":"\nbase.dists.weibull.logcdf( x:number, k:number, λ:number )\n    Evaluates the logarithm of the cumulative distribution function (CDF) for a\n    Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n    value `x`.\n","base.dists.weibull.logcdf.factory":"\nbase.dists.weibull.logcdf.factory( k:number, λ:number)\n    Returns a function for evaluating the logarithm of the cumulative\n    distribution function (CDF) of a Weibull distribution with scale parameter\n    `λ` and shape parameter `k`.\n","base.dists.weibull.logpdf":"\nbase.dists.weibull.logpdf( x:number, k:number, λ:number )\n    Evaluates the logarithm of the probability density function (PDF) for a\n    Weibull distribution with shape parameter `k` and scale parameter `λ` at a\n    value `x`.\n","base.dists.weibull.logpdf.factory":"\nbase.dists.weibull.logpdf.factory( k:number, λ:number )\n    Returns a function for evaluating the logarithm of the probability density\n    function (PDF) of a Weibull distribution with shape parameter `k` and scale\n    parameter `λ`.\n","base.dists.weibull.mean":"\nbase.dists.weibull.mean( k:number, λ:number )\n    Returns the expected value of a Weibull distribution.\n","base.dists.weibull.median":"\nbase.dists.weibull.median( k:number, λ:number )\n    Returns the median of a Weibull distribution.\n","base.dists.weibull.mgf":"\nbase.dists.weibull.mgf( x:number, k:number, λ:number )\n    Evaluates the moment-generating function (MGF) for a Weibull distribution\n    with shape parameter `k` and scale parameter `λ` at a value `t`.\n","base.dists.weibull.mgf.factory":"\nbase.dists.weibull.mgf.factory( k:number, λ:number )\n    Returns a function for evaluating the moment-generating function (MGF) of a\n    Weibull distribution with shape parameter `k` and scale parameter `λ`.\n","base.dists.weibull.mode":"\nbase.dists.weibull.mode( k:number, λ:number )\n    Returns the mode of a Weibull distribution.\n","base.dists.weibull.pdf":"\nbase.dists.weibull.pdf( x:number, k:number, λ:number )\n    Evaluates the probability density function (PDF) for a Weibull distribution\n    with shape parameter `k` and scale parameter `λ` at a value `x`.\n","base.dists.weibull.pdf.factory":"\nbase.dists.weibull.pdf.factory( k:number, λ:number )\n    Returns a function for evaluating the probability density function (PDF) of\n    a Weibull distribution with shape parameter `k` and scale parameter `λ`.\n","base.dists.weibull.quantile":"\nbase.dists.weibull.quantile( p:number, k:number, λ:number )\n    Evaluates the quantile function for a Weibull distribution with scale\n    parameter `k` and shape parameter `λ` at a probability `p`.\n","base.dists.weibull.quantile.factory":"\nbase.dists.weibull.quantile.factory( k:number, λ:number )\n    Returns a function for evaluating the quantile function of a Weibull\n    distribution with scale parameter `k` and shape parameter `λ`.\n","base.dists.weibull.skewness":"\nbase.dists.weibull.skewness( k:number, λ:number )\n    Returns the skewness of a Weibull distribution.\n","base.dists.weibull.stdev":"\nbase.dists.weibull.stdev( k:number, λ:number )\n    Returns the standard deviation of a Weibull distribution.\n","base.dists.weibull.variance":"\nbase.dists.weibull.variance( k:number, λ:number )\n    Returns the variance of a Weibull distribution.\n","base.dists.weibull.Weibull":"\nbase.dists.weibull.Weibull( [k:number, λ:number] )\n    Returns a Weibull distribution object.\n","base.ellipe":"\nbase.ellipe( m:number )\n    Computes the complete elliptic integral of the second kind.\n","base.ellipj":"\nbase.ellipj( u:number, m:number )\n    Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n    amplitude am.\n","base.ellipj.assign":"\nbase.ellipj.assign( u:number, m:number, out:Array|TypedArray|Object, \n  stride:integer, offset:integer )\n    Computes the Jacobi elliptic functions sn, cn, and dn and Jacobi\n    amplitude am and assigns results to a provided output array.\n","base.ellipj.sn":"\nbase.ellipj.sn( u:number, m:number )\n    Computes the Jacobi elliptic function sn.\n","base.ellipj.cn":"\nbase.ellipj.cn( u:number, m:number )\n    Computes the Jacobi elliptic functions cn.\n","base.ellipj.dn":"\nbase.ellipj.dn( u:number, m:number )\n    Computes the Jacobi elliptic function dn.\n","base.ellipj.am":"\nbase.ellipj.am( u:number, m:number )\n    Computes the Jacobi amplitude am.\n","base.ellipk":"\nbase.ellipk( m:number )\n    Computes the complete elliptic integral of the first kind.\n","base.endsWith":"\nbase.endsWith( str:string, search:string, len:integer )\n    Tests if a string ends with the characters of another string.\n","base.epsdiff":"\nbase.epsdiff( x:number, y:number[, scale:string|Function] )\n    Computes the relative difference of two real numbers in units of double-\n    precision floating-point epsilon.\n","base.erf":"\nbase.erf( x:number )\n    Evaluates the error function.\n","base.erfc":"\nbase.erfc( x:number )\n    Evaluates the complementary error function.\n","base.erfcinv":"\nbase.erfcinv( x:number )\n    Evaluates the inverse complementary error function.\n","base.erfcx":"\nbase.erfcx( x:number )\n    Evaluates the scaled complementary error function.\n","base.erfinv":"\nbase.erfinv( x:number )\n    Evaluates the inverse error function.\n","base.eta":"\nbase.eta( s:number )\n    Evaluates the Dirichlet eta function for a double-precision\n    floating-point number `s`.\n","base.evalpoly":"\nbase.evalpoly( c:Array<number>, x:number )\n    Evaluates a polynomial using double-precision floating-point arithmetic.\n","base.evalpoly.factory":"\nbase.evalpoly.factory( c:Array<number> )\n    Returns a function for evaluating a polynomial using double-precision\n    floating-point arithmetic.\n","base.evalrational":"\nbase.evalrational( P:Array<number>, Q:Array<number>, x:number )\n    Evaluates a rational function using double-precision floating-point\n    arithmetic.\n","base.evalrational.factory":"\nbase.evalrational.factory( P:Array<number>, Q:Array<number> )\n    Returns a function for evaluating a rational function using double-precision\n    floating-point arithmetic.\n","base.exp":"\nbase.exp( x:number )\n    Evaluates the natural exponential function.\n","base.exp2":"\nbase.exp2( x:number )\n    Evaluates the base 2 exponential function.\n","base.exp10":"\nbase.exp10( x:number )\n    Evaluates the base 10 exponential function.\n","base.expit":"\nbase.expit( x:number )\n    Evaluates the standard logistic function.\n","base.expm1":"\nbase.expm1( x:number )\n    Computes `exp(x)-1`, where `exp(x)` is the natural exponential function.\n","base.expm1rel":"\nbase.expm1rel( x:number )\n    Relative error exponential.\n","base.exponent":"\nbase.exponent( x:number )\n    Returns an integer corresponding to the unbiased exponent of a double-\n    precision floating-point number.\n","base.exponentf":"\nbase.exponentf( x:float )\n    Returns an integer corresponding to the unbiased exponent of a single-\n    precision floating-point number.\n","base.factorial":"\nbase.factorial( x:number )\n    Evaluates the factorial of `x`.\n","base.factorial2":"\nbase.factorial2( n:number )\n    Evaluates the double factorial of `n`.\n","base.factorialln":"\nbase.factorialln( x:number )\n    Evaluates the natural logarithm of the factorial of `x`.\n","base.fallingFactorial":"\nbase.fallingFactorial( x:number, n:integer )\n    Computes the falling factorial of `x` and `n`.\n","base.fibonacci":"\nbase.fibonacci( n:integer )\n    Computes the nth Fibonacci number.\n","base.fibonacciIndex":"\nbase.fibonacciIndex( F:integer )\n    Computes the Fibonacci number index.\n","base.fibpoly":"\nbase.fibpoly( n:integer, x:number )\n    Evaluates a Fibonacci polynomial.\n","base.fibpoly.factory":"\nbase.fibpoly.factory( n:integer )\n    Returns a function for evaluating a Fibonacci polynomial.\n","base.firstCodePoint":"\nbase.firstCodePoint( str:string, n:integer )\n    Returns the first `n` Unicode code points of a string.\n","base.firstCodeUnit":"\nbase.firstCodeUnit( str:string, n:integer )\n    Returns the first `n` UTF-16 code units of a string.\n","base.firstGraphemeCluster":"\nbase.firstGraphemeCluster( str:string, n:integer )\n    Returns the first `n` grapheme clusters (i.e., user-perceived characters) of\n    a string.\n","base.flipsign":"\nbase.flipsign( x:number, y:number )\n    Returns a double-precision floating-point number with the magnitude of `x`\n    and the sign of `x*y`.\n","base.flipsignf":"\nbase.flipsignf( x:number, y:number )\n    Returns a single-precision floating-point number with the magnitude of `x`\n    and the sign of `x*y`.\n","base.float32ToInt32":"\nbase.float32ToInt32( x:float )\n    Converts a single-precision floating-point number to a signed 32-bit\n    integer.\n","base.float32ToUint32":"\nbase.float32ToUint32( x:float )\n    Converts a single-precision floating-point number to a unsigned 32-bit\n    integer.\n","base.float64ToFloat32":"\nbase.float64ToFloat32( x:number )\n    Converts a double-precision floating-point number to the nearest single-\n    precision floating-point number.\n","base.float64ToInt32":"\nbase.float64ToInt32( x:number )\n    Converts a double-precision floating-point number to a signed 32-bit\n    integer.\n","base.float64ToInt64Bytes":"\nbase.float64ToInt64Bytes( x:integer )\n    Converts an integer-valued double-precision floating-point number to a\n    signed 64-bit integer byte array according to host byte order (endianness).\n","base.float64ToInt64Bytes.assign":"\nbase.float64ToInt64Bytes.assign( x:integer, out:Array|TypedArray|Object, \n  stride:integer, offset:integer )\n    Converts an integer-valued double-precision floating-point number to a\n    signed 64-bit integer byte array according to host byte order (endianness)\n    and assigns results to a provided output array.\n","base.float64ToUint32":"\nbase.float64ToUint32( x:number )\n    Converts a double-precision floating-point number to a unsigned 32-bit\n    integer.\n","base.floor":"\nbase.floor( x:number )\n    Rounds a double-precision floating-point number toward negative infinity.\n","base.floor2":"\nbase.floor2( x:number )\n    Rounds a numeric value to the nearest power of two toward negative infinity.\n","base.floor10":"\nbase.floor10( x:number )\n    Rounds a numeric value to the nearest power of ten toward negative infinity.\n","base.floorb":"\nbase.floorb( x:number, n:integer, b:integer )\n    Rounds a numeric value to the nearest multiple of `b^n` toward negative\n    infinity.\n","base.floorf":"\nbase.floorf( x:number )\n    Rounds a single-precision floating-point number toward negative infinity.\n","base.floorn":"\nbase.floorn( x:number, n:integer )\n    Rounds a double-precision floating-point number to the nearest multiple of\n    `10^n` toward negative infinity.\n","base.floorsd":"\nbase.floorsd( x:number, n:integer, b:integer )\n    Rounds a numeric value to the nearest number toward negative infinity with\n    `n` significant figures.\n","base.forEachChar":"\nbase.forEachChar( str:string, clbk:Function[, thisArg:any] )\n    Invokes a function for each UTF-16 code unit in a string.\n","base.forEachCodePoint":"\nbase.forEachCodePoint( str:string, clbk:Function[, thisArg:any] )\n    Invokes a function for each Unicode code point in a string.\n","base.forEachCodePointRight":"\nbase.forEachCodePointRight( str:string, clbk:Function[, thisArg:any] )\n    Invokes a function for each Unicode code point in a string, iterating from\n    right to left.\n","base.forEachGraphemeCluster":"\nbase.forEachGraphemeCluster( str:string, clbk:Function[, thisArg:any] )\n    Invokes a function for each grapheme cluster (i.e., user-perceived\n    character) in a string.\n","base.forEachRight":"\nbase.forEachRight( str:string, clbk:Function[, thisArg:any] )\n    Invokes a function for each UTF-16 code unit in a string, iterating from\n    right to left.\n","base.formatInterpolate":"\nbase.formatInterpolate( tokens:Array, ...args:any )\n    Generate string from a token array by interpolating values.\n","base.formatTokenize":"\nbase.formatTokenize( str:string )\n    Tokenize a string into an array of string parts and format identifier\n    objects.\n","base.fresnel":"\nbase.fresnel( x:number )\n    Computes the Fresnel integrals S(x) and C(x).\n","base.fresnel.assign":"\nbase.fresnel.assign( x:number, out:Array<number>, stride:integer, \n  offset:integer )\n    Computes the Fresnel integrals S(x) and C(x) and assigns results to a\n    provided output array.\n","base.fresnelc":"\nbase.fresnelc( x:number )\n    Computes the Fresnel integral C(x).\n","base.fresnels":"\nbase.fresnels( x:number )\n    Computes the Fresnel integral S(x).\n","base.frexp":"\nbase.frexp( x:number )\n    Splits a double-precision floating-point number into a normalized fraction\n    and an integer power of two.\n","base.frexp.assign":"\nbase.frexp.assign( x:number, out:Array<number>, stride:integer, offset:integer )\n    Splits a double-precision floating-point number into a normalized fraction\n    and an integer power of two and assigns results to a provided output array.\n","base.fromBinaryString":"\nbase.fromBinaryString( bstr:string )\n    Creates a double-precision floating-point number from a literal bit\n    representation.\n","base.fromBinaryStringf":"\nbase.fromBinaryStringf( bstr:string )\n    Creates a single-precision floating-point number from an IEEE 754 literal\n    bit representation.\n","base.fromBinaryStringUint8":"\nbase.fromBinaryStringUint8( bstr:string )\n    Creates an unsigned 8-bit integer from a literal bit representation.\n","base.fromBinaryStringUint16":"\nbase.fromBinaryStringUint16( bstr:string )\n    Creates an unsigned 16-bit integer from a literal bit representation.\n","base.fromBinaryStringUint32":"\nbase.fromBinaryStringUint32( bstr:string )\n    Creates an unsigned 32-bit integer from a literal bit representation.\n","base.fromInt64Bytes":"\nbase.fromInt64Bytes( bytes:Array|TypedArray|Object, stride:integer, \n  offset:integer )\n    Converts a signed 64-bit integer byte array to a double-precision floating-\n    point number.\n","base.fromWordf":"\nbase.fromWordf( word:integer )\n    Creates a single-precision floating-point number from an unsigned integer\n    corresponding to an IEEE 754 binary representation.\n","base.fromWords":"\nbase.fromWords( high:integer, low:integer )\n    Creates a double-precision floating-point number from a higher order word\n    (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n","base.gamma":"\nbase.gamma( x:number )\n    Evaluates the gamma function.\n","base.gamma1pm1":"\nbase.gamma1pm1( x:number )\n    Computes `gamma(x+1) - 1` without cancellation errors, where `gamma(x)` is\n    the gamma function.\n","base.gammaDeltaRatio":"\nbase.gammaDeltaRatio( z:number, delta:number )\n    Computes the ratio of two gamma functions.\n","base.gammainc":"\nbase.gammainc( x:number, s:number[, regularized:boolean[, upper:boolean]] )\n    Computes the regularized incomplete gamma function.\n","base.gammaincinv":"\nbase.gammaincinv( p:number, a:number[, upper:boolean] )\n    Computes the inverse of the lower incomplete gamma function.\n","base.gammaLanczosSum":"\nbase.gammaLanczosSum( x:number )\n    Calculates the Lanczos sum for the approximation of the gamma function.\n","base.gammaLanczosSumExpGScaled":"\nbase.gammaLanczosSumExpGScaled( x:number )\n    Calculates the scaled Lanczos sum for the approximation of the gamma\n    function.\n","base.gammaln":"\nbase.gammaln( x:number )\n    Evaluates the natural logarithm of the gamma function.\n","base.gammasgn":"\nbase.gammasgn( x:number )\n    Computes the sign of the gamma function.\n","base.gcd":"\nbase.gcd( a:integer, b:integer )\n    Computes the greatest common divisor (gcd).\n","base.getHighWord":"\nbase.getHighWord( x:number )\n    Returns an unsigned 32-bit integer corresponding to the more significant 32\n    bits of a double-precision floating-point number.\n","base.getLowWord":"\nbase.getLowWord( x:number )\n    Returns an unsigned 32-bit integer corresponding to the less significant 32\n    bits of a double-precision floating-point number.\n","base.hacovercos":"\nbase.hacovercos( x:number )\n    Computes the half-value coversed cosine.\n","base.hacoversin":"\nbase.hacoversin( x:number )\n    Computes the half-value coversed sine.\n","base.havercos":"\nbase.havercos( x:number )\n    Computes the half-value versed cosine.\n","base.haversin":"\nbase.haversin( x:number )\n    Computes the half-value versed sine.\n","base.headercase":"\nbase.headercase( str:string )\n    Converts a string to HTTP header case.\n","base.heaviside":"\nbase.heaviside( x:number[, continuity:string] )\n    Evaluates the Heaviside function.\n","base.hermitepoly":"\nbase.hermitepoly( n:integer, x:number )\n    Evaluates a physicist's Hermite polynomial.\n","base.hermitepoly.factory":"\nbase.hermitepoly.factory( n:integer )\n    Returns a function for evaluating a physicist's Hermite polynomial.\n","base.hypot":"\nbase.hypot( x:number, y:number )\n    Computes the hypotenuse avoiding overflow and underflow.\n","base.hypotf":"\nbase.hypotf( x:number, y:number )\n    Computes the hypotenuse avoiding overflow and underflow (single-precision).\n","base.identity":"\nbase.identity( x:number )\n    Evaluates the identity function for a double-precision floating-point number\n    `x`.\n","base.identityf":"\nbase.identityf( x:number )\n    Evaluates the identity function for a single-precision floating-point number\n    `x`.\n","base.imul":"\nbase.imul( a:integer, b:integer )\n    Performs C-like multiplication of two signed 32-bit integers.\n","base.imuldw":"\nbase.imuldw( a:integer, b:integer )\n    Multiplies two signed 32-bit integers and returns an array of two signed 32-\n    bit integers which represents the signed 64-bit integer product.\n","base.imuldw.assign":"\nbase.imuldw.assign( a:integer, b:integer, out:Array|TypedArray|Object, \n  stride:integer, offset:integer )\n    Multiplies two signed 32-bit integers and assigns results representing the\n    signed 64-bit integer product to a provided output array.\n","base.int2slice":"\nbase.int2slice( value:integer, max:integer, strict:boolean )\n    Converts an integer to a Slice object.\n","base.int32ToUint32":"\nbase.int32ToUint32( x:integer )\n    Converts a signed 32-bit integer to an unsigned 32-bit integer.\n","base.inv":"\nbase.inv( x:number )\n    Computes the multiplicative inverse of a double-precision floating-point\n    number `x`.\n","base.invcase":"\nbase.invcase( str:string )\n    Converts a string to inverse case.\n","base.invf":"\nbase.invf( x:number )\n    Computes the multiplicative inverse of a single-precision floating-point\n    number `x`.\n","base.isComposite":"\nbase.isComposite( x:number )\n    Tests if a number is composite.\n","base.isCoprime":"\nbase.isCoprime( a:number, b:number )\n    Tests if two numbers are coprime.\n","base.isEven":"\nbase.isEven( x:number )\n    Tests if a finite numeric value is an even number.\n","base.isEvenInt32":"\nbase.isEvenInt32( x:integer )\n    Tests if a 32-bit integer is even.\n","base.isFinite":"\nbase.isFinite( x:number )\n    Tests if a double-precision floating-point numeric value is finite.\n","base.isFinitef":"\nbase.isFinitef( x:number )\n    Tests if a single-precision floating-point numeric value is finite.\n","base.isInfinite":"\nbase.isInfinite( x:number )\n    Tests if a double-precision floating-point numeric value is infinite.\n","base.isInfinitef":"\nbase.isInfinitef( x:number )\n    Tests if a single-precision floating-point numeric value is infinite.\n","base.isInteger":"\nbase.isInteger( x:number )\n    Tests if a finite double-precision floating-point number is an integer.\n","base.isnan":"\nbase.isnan( x:number )\n     Tests if a double-precision floating-point numeric value is `NaN`.\n","base.isnanf":"\nbase.isnanf( x:number )\n     Tests if a single-precision floating-point numeric value is `NaN`.\n","base.isNegativeFinite":"\nbase.isNegativeFinite( x:number )\n    Tests if a double-precision floating-point numeric value is a negative\n    finite number.\n","base.isNegativeInteger":"\nbase.isNegativeInteger( x:number )\n    Tests if a finite double-precision floating-point number is a negative\n    integer.\n","base.isNegativeZero":"\nbase.isNegativeZero( x:number )\n    Tests if a double-precision floating-point numeric value is negative zero.\n","base.isNegativeZerof":"\nbase.isNegativeZerof( x:number )\n    Tests if a single-precision floating-point numeric value is negative zero.\n","base.isNonNegativeFinite":"\nbase.isNonNegativeFinite( x:number )\n    Tests if a double-precision floating-point numeric value is a nonnegative\n    finite number.\n","base.isNonNegativeInteger":"\nbase.isNonNegativeInteger( x:number )\n    Tests if a finite double-precision floating-point number is a nonnegative\n    integer.\n","base.isNonPositiveFinite":"\nbase.isNonPositiveFinite( x:number )\n    Tests if a double-precision floating-point numeric value is a nonpositive\n    finite number.\n","base.isNonPositiveInteger":"\nbase.isNonPositiveInteger( x:number )\n    Tests if a finite double-precision floating-point number is a nonpositive\n    integer.\n","base.isOdd":"\nbase.isOdd( x:number )\n    Tests if a finite numeric value is an odd number.\n","base.isOddInt32":"\nbase.isOddInt32( x:integer )\n    Tests if a 32-bit integer is odd.\n","base.isPositiveFinite":"\nbase.isPositiveFinite( x:number )\n    Tests if a double-precision floating-point numeric value is a positive\n    finite number.\n","base.isPositiveInteger":"\nbase.isPositiveInteger( x:number )\n    Tests if a finite double-precision floating-point number is a positive\n    integer.\n","base.isPositiveZero":"\nbase.isPositiveZero( x:number )\n    Tests if a double-precision floating-point numeric value is positive zero.\n","base.isPositiveZerof":"\nbase.isPositiveZerof( x:number )\n    Tests if a single-precision floating-point numeric value is positive zero.\n","base.isPow2Uint32":"\nbase.isPow2Uint32( x:integer )\n    Tests whether an unsigned integer is a power of 2.\n","base.isPrime":"\nbase.isPrime( x:number )\n    Tests if a number is prime.\n","base.isProbability":"\nbase.isProbability( x:number )\n    Tests if a double-precision floating-point number value is a probability.\n","base.isSafeInteger":"\nbase.isSafeInteger( x:number )\n    Tests if a finite double-precision floating-point number is a safe integer.\n","base.kebabcase":"\nbase.kebabcase( str:string )\n    Converts a string to kebab case.\n","base.kernelBetainc":"\nbase.kernelBetainc( x:number, a:number, b:number, regularized:boolean, \n  upper:boolean )\n    Computes the kernel function for the regularized incomplete beta function.\n","base.kernelBetainc.assign":"\nbase.kernelBetainc.assign( x:number, a:number, b:number, regularized:boolean, \n  upper:boolean, out:Array|TypedArray|Object, stride:integer, offset:integer )\n    Computes the kernel function for the regularized incomplete beta function.\n","base.kernelBetaincinv":"\nbase.kernelBetaincinv( a:number, b:number, p:number, q:number )\n    Computes the inverse of the lower incomplete beta function.\n","base.kernelCos":"\nbase.kernelCos( x:number, y:number )\n    Computes the cosine of a double-precision floating-point number on the\n    interval [-π/4, π/4].\n","base.kernelLog1p":"\nbase.kernelLog1p( f:number )\n    Computes `log(1+f) - f` for `1+f` in ~[sqrt(2)/2, sqrt(2)].\n","base.kernelSin":"\nbase.kernelSin( x:number, y:number )\n    Computes the sine of a double-precision floating-point number on [-π/4,π/4].\n","base.kernelTan":"\nbase.kernelTan( x:number, y:number, k:integer )\n    Computes the tangent of a double-precision floating-point number on the\n    interval [-π/4, π/4].\n","base.kroneckerDelta":"\nbase.kroneckerDelta( i:number, j:number )\n    Evaluates the Kronecker delta.\n","base.kroneckerDeltaf":"\nbase.kroneckerDeltaf( i:number, j:number )\n    Evaluates the Kronecker delta (single-precision).\n","base.labs":"\nbase.labs( x:integer )\n    Computes an absolute value of a signed 32-bit integer in two's complement\n    format.\n","base.last":"\nbase.last( str:string, n:integer )\n    Returns the last `n` UTF-16 code units of a string.\n","base.lastCodePoint":"\nbase.lastCodePoint( str:string, n:integer )\n    Returns the last `n` Unicode code points of a string.\n","base.lastGraphemeCluster":"\nbase.lastGraphemeCluster( str:string, n:integer )\n    Returns the last `n` grapheme clusters (i.e., user-perceived characters) of\n    a string.\n","base.lcm":"\nbase.lcm( a:integer, b:integer )\n    Computes the least common multiple (lcm).\n","base.ldexp":"\nbase.ldexp( frac:number, exp:number )\n    Multiplies a double-precision floating-point number by an integer power of\n    two; i.e., `x = frac * 2^exp`.\n","base.leftPad":"\nbase.leftPad( str:string, len:integer, pad:string )\n    Left pads a string such that the padded string has a length of at least\n    `len`.\n","base.leftTrim":"\nbase.leftTrim( str:string )\n    Trims whitespace from the beginning of a string.\n","base.ln":"\nbase.ln( x:number )\n    Evaluates the natural logarithm of a double-precision floating-point number.\n","base.log":"\nbase.log( x:number, b:number )\n    Computes the base `b` logarithm of a double-precision floating-point number.\n","base.log1mexp":"\nbase.log1mexp( x:number )\n    Evaluates the natural logarithm of `1-exp(-|x|)`.\n","base.log1p":"\nbase.log1p( x:number )\n    Evaluates the natural logarithm of `1+x`.\n","base.log1pexp":"\nbase.log1pexp( x:number )\n    Evaluates the natural logarithm of `1+exp(x)`.\n","base.log1pmx":"\nbase.log1pmx( x:number )\n    Evaluates `ln(1+x) - x`.\n","base.log2":"\nbase.log2( x:number )\n    Evaluates the binary logarithm (base two).\n","base.log10":"\nbase.log10( x:number )\n    Evaluates the common logarithm (base 10).\n","base.logaddexp":"\nbase.logaddexp( x:number, y:number )\n    Computes the natural logarithm of `exp(x) + exp(y)`.\n","base.logit":"\nbase.logit( p:number )\n    Evaluates the logit function.\n","base.lowercase":"\nbase.lowercase( str:string )\n    Converts a string to lowercase.\n","base.lucas":"\nbase.lucas( n:integer )\n    Computes the nth Lucas number.\n","base.lucaspoly":"\nbase.lucaspoly( n:integer, x:number )\n    Evaluates a Lucas polynomial.\n","base.lucaspoly.factory":"\nbase.lucaspoly.factory( n:integer )\n    Returns a function for evaluating a Lucas polynomial.\n","base.max":"\nbase.max( x:number, y:number )\n    Returns the maximum value.\n","base.maxabs":"\nbase.maxabs( x:number, y:number )\n    Returns the maximum absolute value.\n","base.maxabsn":"\nbase.maxabsn( [x:number[, y:number[, ...args:number]]] )\n    Returns the maximum absolute value.\n","base.maxn":"\nbase.maxn( [x:number[, y:number[, ...args:number]]] )\n    Returns the maximum value.\n","base.min":"\nbase.min( x:number, y:number )\n    Returns the minimum value.\n","base.minabs":"\nbase.minabs( x:number, y:number )\n    Returns the minimum absolute value.\n","base.minabsn":"\nbase.minabsn( [x:number[, y:number[, ...args:number]]] )\n    Returns the minimum absolute value.\n","base.minmax":"\nbase.minmax( x:number, y:number )\n    Returns the minimum and maximum values.\n","base.minmax.assign":"\nbase.minmax.assign( x:number, y:number, out:Array|TypedArray|Object, \n  stride:integer, offset:integer )\n    Returns the minimum and maximum values and assigns results to a provided\n    output array.\n","base.minmaxabs":"\nbase.minmaxabs( x:number, y:number )\n    Returns the minimum and maximum absolute values.\n","base.minmaxabs.assign":"\nbase.minmaxabs.assign( x:number, y:number, out:Array|TypedArray|Object, \n  stride:integer, offset:integer )\n    Returns the minimum and maximum absolute values.\n","base.minmaxabsn":"\nbase.minmaxabsn( [x:number[, y:number[, ...args:number]]] )\n    Returns the minimum and maximum absolute values.\n","base.minmaxabsn.assign":"\nbase.minmaxabsn.assign( [x:number[, y:number[, ...args:number]]], \n  out:Array|TypedArray|Object, stride:integer, offset:integer )\n    Returns the minimum and maximum absolute values.\n","base.minmaxn":"\nbase.minmaxn( [x:number[, y:number[, ...args:number]]] )\n    Returns the minimum and maximum values.\n","base.minmaxn.assign":"\nbase.minmaxn.assign( [x:number[, y:number[, ...args:number]]], \n  out:Array|TypedArray|Object, stride:integer, offset:integer )\n    Returns the minimum and maximum values and assigns results to a provided\n    output array.\n","base.minn":"\nbase.minn( [x:number[, y:number[, ...args:number]]] )\n    Returns the minimum value.\n","base.modf":"\nbase.modf( x:number )\n    Decomposes a double-precision floating-point number into integral and\n    fractional parts, each having the same type and sign as the input value.\n","base.modf.assign":"\nbase.modf.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n  offset:integer )\n    Decomposes a double-precision floating-point number into integral and\n    fractional parts, each having the same type and sign as the input value,\n    and assigns results to a provided output array.\n","base.mul":"\nbase.mul( x:number, y:number )\n    Multiplies two double-precision floating-point numbers `x` and `y`.\n","base.mulf":"\nbase.mulf( x:number, y:number )\n    Multiplies two single-precision floating-point numbers `x` and `y`.\n","base.ndarray":"\nbase.ndarray( dtype:string, buffer:ArrayLikeObject|TypedArray|Buffer, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  offset:integer, order:string )\n    Returns an ndarray.\n","base.ndarray.prototype.byteLength":"\nbase.ndarray.prototype.byteLength\n    Size (in bytes) of the array (if known).\n","base.ndarray.prototype.BYTES_PER_ELEMENT":"\nbase.ndarray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element (if known).\n","base.ndarray.prototype.data":"\nbase.ndarray.prototype.data\n    Pointer to the underlying data buffer.\n","base.ndarray.prototype.dtype":"\nbase.ndarray.prototype.dtype\n    Underlying data type.\n","base.ndarray.prototype.flags":"\nbase.ndarray.prototype.flags\n    Meta information, such as information concerning the memory layout of the\n    array.\n","base.ndarray.prototype.length":"\nbase.ndarray.prototype.length\n    Length of the array (i.e., number of elements).\n","base.ndarray.prototype.ndims":"\nbase.ndarray.prototype.ndims\n    Number of dimensions.\n","base.ndarray.prototype.offset":"\nbase.ndarray.prototype.offset\n    Index offset which specifies the buffer index at which to start iterating\n    over array elements.\n","base.ndarray.prototype.order: string":"\nbase.ndarray.prototype.order: string\n    Array order.\n","base.ndarray.prototype.shape":"\nbase.ndarray.prototype.shape\n    Array shape.\n","base.ndarray.prototype.strides":"\nbase.ndarray.prototype.strides\n    Index strides which specify how to access data along corresponding array\n    dimensions.\n","base.ndarray.prototype.get":"\nbase.ndarray.prototype.get( ...idx:integer )\n    Returns an array element specified according to provided subscripts.\n","base.ndarray.prototype.iget":"\nbase.ndarray.prototype.iget( idx:integer )\n    Returns an array element located at a specified linear index.\n","base.ndarray.prototype.set":"\nbase.ndarray.prototype.set( ...idx:integer, v:any )\n    Sets an array element specified according to provided subscripts.\n","base.ndarray.prototype.iset":"\nbase.ndarray.prototype.iset( idx:integer, v:any )\n    Sets an array element located at a specified linear index.\n","base.ndarray.prototype.toString":"\nbase.ndarray.prototype.toString()\n    Serializes an ndarray as a string.\n","base.ndarray.prototype.toJSON":"\nbase.ndarray.prototype.toJSON()\n    Serializes an ndarray as a JSON object.\n","base.ndarrayUnary":"\nbase.ndarrayUnary( arrays:ArrayLikeObject<ndarray>, fcn:Function )\n    Applies a unary callback to elements in an input ndarray and assigns results\n    to elements in an output ndarray.\n","base.ndzeros":"\nbase.ndzeros( dtype:string, shape:ArrayLikeObject<integer>, order:string )\n    Returns a zero-filled ndarray having a specified shape and data type.\n","base.ndzerosLike":"\nbase.ndzerosLike( x:ndarray )\n    Returns a zero-filled ndarray having the same shape and data type as a\n    provided input ndarray.\n","base.negafibonacci":"\nbase.negafibonacci( n:integer )\n    Computes the nth negaFibonacci number.\n","base.negalucas":"\nbase.negalucas( n:integer )\n    Computes the nth negaLucas number.\n","base.nonfibonacci":"\nbase.nonfibonacci( n:integer )\n    Computes the nth non-Fibonacci number.\n","base.normalize":"\nbase.normalize( x:number )\n    Returns a normal number and exponent satisfying `x = y * 2^exp` as an array.\n","base.normalize.assign":"\nbase.normalize.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n  offset:integer )\n    Returns a normal number and exponent satisfying `x = y * 2^exp` and assigns\n    results to a provided output array.\n","base.normalizef":"\nbase.normalizef( x:float )\n    Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` as\n    an array.\n","base.normalizef.assign":"\nbase.normalizef.assign( x:float, out:Array|TypedArray|Object, stride:integer, \n  offset:integer )\n    Returns a normal number `y` and exponent `exp` satisfying `x = y * 2^exp` and\n    assigns results to a provided output array.\n","base.normalizeSlice":"\nbase.normalizeSlice( slice:Slice, len:integer, strict:boolean )\n    Returns a normalized Slice object.\n","base.normhermitepoly":"\nbase.normhermitepoly( n:integer, x:number )\n    Evaluates a normalized Hermite polynomial using double-precision floating-\n    point arithmetic.\n","base.normhermitepoly.factory":"\nbase.normhermitepoly.factory( n:integer )\n    Returns a function for evaluating a normalized Hermite polynomial using\n    double-precision floating-point arithmetic.\n","base.pascalcase":"\nbase.pascalcase( str:string )\n    Converts a string to Pascal case.\n","base.pdiff":"\nbase.pdiff( x:number, y:number )\n    Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n    returns `0`.\n","base.pdifff":"\nbase.pdifff( x:number, y:number )\n    Returns the positive difference between `x` and `y` if `x > y`; otherwise,\n    returns `0`.\n","base.percentEncode":"\nbase.percentEncode( str:string )\n    Percent-encodes a UTF-16 encoded string according to RFC 3986.\n","base.polygamma":"\nbase.polygamma( n:integer, x:number )\n    Evaluates the polygamma function of order `n`; i.e., the (n+1)th derivative\n    of the natural logarithm of the gamma function.\n","base.pow":"\nbase.pow( b:number, x:number )\n    Evaluates the exponential function `bˣ`.\n","base.powm1":"\nbase.powm1( b:number, x:number )\n    Evaluates `bˣ - 1`.\n","base.rad2deg":"\nbase.rad2deg( x:number )\n    Converts an angle from radians to degrees.\n","base.rad2degf":"\nbase.rad2degf( x:number )\n    Converts an angle from radians to degrees (single-precision).\n","base.ramp":"\nbase.ramp( x:number )\n    Evaluates the ramp function.\n","base.rampf":"\nbase.rampf( x:number )\n    Evaluates the ramp function (single-precision).\n","base.random.arcsine":"\nbase.random.arcsine( a:number, b:number )\n    Returns a pseudorandom number drawn from an arcsine distribution.\n","base.random.arcsine.factory":"\nbase.random.arcsine.factory( [a:number, b:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an arcsine distribution.\n","base.random.arcsine.NAME":"\nbase.random.arcsine.NAME\n    Generator name.\n","base.random.arcsine.PRNG":"\nbase.random.arcsine.PRNG\n    Underlying pseudorandom number generator.\n","base.random.arcsine.seed":"\nbase.random.arcsine.seed\n    Pseudorandom number generator seed.\n","base.random.arcsine.seedLength":"\nbase.random.arcsine.seedLength\n    Length of generator seed.\n","base.random.arcsine.state":"\nbase.random.arcsine.state\n    Generator state.\n","base.random.arcsine.stateLength":"\nbase.random.arcsine.stateLength\n    Length of generator state.\n","base.random.arcsine.byteLength":"\nbase.random.arcsine.byteLength\n    Size (in bytes) of generator state.\n","base.random.arcsine.toJSON":"\nbase.random.arcsine.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.bernoulli":"\nbase.random.bernoulli( p:number )\n    Returns a pseudorandom number drawn from a Bernoulli distribution.\n","base.random.bernoulli.factory":"\nbase.random.bernoulli.factory( [p:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Bernoulli distribution.\n","base.random.bernoulli.NAME":"\nbase.random.bernoulli.NAME\n    Generator name.\n","base.random.bernoulli.PRNG":"\nbase.random.bernoulli.PRNG\n    Underlying pseudorandom number generator.\n","base.random.bernoulli.seed":"\nbase.random.bernoulli.seed\n    Pseudorandom number generator seed.\n","base.random.bernoulli.seedLength":"\nbase.random.bernoulli.seedLength\n    Length of generator seed.\n","base.random.bernoulli.state":"\nbase.random.bernoulli.state\n    Generator state.\n","base.random.bernoulli.stateLength":"\nbase.random.bernoulli.stateLength\n    Length of generator state.\n","base.random.bernoulli.byteLength":"\nbase.random.bernoulli.byteLength\n    Size (in bytes) of generator state.\n","base.random.bernoulli.toJSON":"\nbase.random.bernoulli.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.beta":"\nbase.random.beta( α:number, β:number )\n    Returns a pseudorandom number drawn from a beta distribution.\n","base.random.beta.factory":"\nbase.random.beta.factory( [α:number, β:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a beta distribution.\n","base.random.beta.NAME":"\nbase.random.beta.NAME\n    Generator name.\n","base.random.beta.PRNG":"\nbase.random.beta.PRNG\n    Underlying pseudorandom number generator.\n","base.random.beta.seed":"\nbase.random.beta.seed\n    Pseudorandom number generator seed.\n","base.random.beta.seedLength":"\nbase.random.beta.seedLength\n    Length of generator seed.\n","base.random.beta.state":"\nbase.random.beta.state\n    Generator state.\n","base.random.beta.stateLength":"\nbase.random.beta.stateLength\n    Length of generator state.\n","base.random.beta.byteLength":"\nbase.random.beta.byteLength\n    Size (in bytes) of generator state.\n","base.random.beta.toJSON":"\nbase.random.beta.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.betaprime":"\nbase.random.betaprime( α:number, β:number )\n    Returns a pseudorandom number drawn from a beta prime distribution.\n","base.random.betaprime.factory":"\nbase.random.betaprime.factory( [α:number, β:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a beta prime distribution.\n","base.random.betaprime.NAME":"\nbase.random.betaprime.NAME\n    Generator name.\n","base.random.betaprime.PRNG":"\nbase.random.betaprime.PRNG\n    Underlying pseudorandom number generator.\n","base.random.betaprime.seed":"\nbase.random.betaprime.seed\n    Pseudorandom number generator seed.\n","base.random.betaprime.seedLength":"\nbase.random.betaprime.seedLength\n    Length of generator seed.\n","base.random.betaprime.state":"\nbase.random.betaprime.state\n    Generator state.\n","base.random.betaprime.stateLength":"\nbase.random.betaprime.stateLength\n    Length of generator state.\n","base.random.betaprime.byteLength":"\nbase.random.betaprime.byteLength\n    Size (in bytes) of generator state.\n","base.random.betaprime.toJSON":"\nbase.random.betaprime.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.binomial":"\nbase.random.binomial( n:integer, p:number )\n    Returns a pseudorandom number drawn from a binomial distribution.\n","base.random.binomial.factory":"\nbase.random.binomial.factory( [n:integer, p:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a binomial distribution.\n","base.random.binomial.NAME":"\nbase.random.binomial.NAME\n    Generator name.\n","base.random.binomial.PRNG":"\nbase.random.binomial.PRNG\n    Underlying pseudorandom number generator.\n","base.random.binomial.seed":"\nbase.random.binomial.seed\n    Pseudorandom number generator seed.\n","base.random.binomial.seedLength":"\nbase.random.binomial.seedLength\n    Length of generator seed.\n","base.random.binomial.state":"\nbase.random.binomial.state\n    Generator state.\n","base.random.binomial.stateLength":"\nbase.random.binomial.stateLength\n    Length of generator state.\n","base.random.binomial.byteLength":"\nbase.random.binomial.byteLength\n    Size of generator state.\n","base.random.binomial.toJSON":"\nbase.random.binomial.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.boxMuller":"\nbase.random.boxMuller()\n    Returns a pseudorandom number drawn from a standard normal distribution.\n","base.random.boxMuller.factory":"\nbase.random.boxMuller.factory( [options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a standard normal distribution.\n","base.random.boxMuller.NAME":"\nbase.random.boxMuller.NAME\n    Generator name.\n","base.random.boxMuller.PRNG":"\nbase.random.boxMuller.PRNG\n    Underlying pseudorandom number generator.\n","base.random.boxMuller.seed":"\nbase.random.boxMuller.seed\n    Pseudorandom number generator seed.\n","base.random.boxMuller.seedLength":"\nbase.random.boxMuller.seedLength\n    Length of generator seed.\n","base.random.boxMuller.state":"\nbase.random.boxMuller.state\n    Generator state.\n","base.random.boxMuller.stateLength":"\nbase.random.boxMuller.stateLength\n    Length of generator state.\n","base.random.boxMuller.byteLength":"\nbase.random.boxMuller.byteLength\n    Size (in bytes) of generator state.\n","base.random.boxMuller.toJSON":"\nbase.random.boxMuller.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.cauchy":"\nbase.random.cauchy( x0:number, Ɣ:number )\n    Returns a pseudorandom number drawn from a Cauchy distribution.\n","base.random.cauchy.factory":"\nbase.random.cauchy.factory( [x0:number, Ɣ:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Cauchy distribution.\n","base.random.cauchy.NAME":"\nbase.random.cauchy.NAME\n    Generator name.\n","base.random.cauchy.PRNG":"\nbase.random.cauchy.PRNG\n    Underlying pseudorandom number generator.\n","base.random.cauchy.seed":"\nbase.random.cauchy.seed\n    Pseudorandom number generator seed.\n","base.random.cauchy.seedLength":"\nbase.random.cauchy.seedLength\n    Length of generator seed.\n","base.random.cauchy.state":"\nbase.random.cauchy.state\n    Generator state.\n","base.random.cauchy.stateLength":"\nbase.random.cauchy.stateLength\n    Length of generator state.\n","base.random.cauchy.byteLength":"\nbase.random.cauchy.byteLength\n    Size (in bytes) of generator state.\n","base.random.cauchy.toJSON":"\nbase.random.cauchy.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.chi":"\nbase.random.chi( k:number )\n    Returns a pseudorandom number drawn from a chi distribution.\n","base.random.chi.factory":"\nbase.random.chi.factory( [k:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a chi distribution.\n","base.random.chi.NAME":"\nbase.random.chi.NAME\n    Generator name.\n","base.random.chi.PRNG":"\nbase.random.chi.PRNG\n    Underlying pseudorandom number generator.\n","base.random.chi.seed":"\nbase.random.chi.seed\n    Pseudorandom number generator seed.\n","base.random.chi.seedLength":"\nbase.random.chi.seedLength\n    Length of generator seed.\n","base.random.chi.state":"\nbase.random.chi.state\n    Generator state.\n","base.random.chi.stateLength":"\nbase.random.chi.stateLength\n    Length of generator state.\n","base.random.chi.byteLength":"\nbase.random.chi.byteLength\n    Size (in bytes) of generator state.\n","base.random.chi.toJSON":"\nbase.random.chi.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.chisquare":"\nbase.random.chisquare( k:number )\n    Returns a pseudorandom number drawn from a chi-square distribution.\n","base.random.chisquare.factory":"\nbase.random.chisquare.factory( [k:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a chi-square distribution.\n","base.random.chisquare.NAME":"\nbase.random.chisquare.NAME\n    Generator name.\n","base.random.chisquare.PRNG":"\nbase.random.chisquare.PRNG\n    Underlying pseudorandom number generator.\n","base.random.chisquare.seed":"\nbase.random.chisquare.seed\n    Pseudorandom number generator seed.\n","base.random.chisquare.seedLength":"\nbase.random.chisquare.seedLength\n    Length of generator seed.\n","base.random.chisquare.state":"\nbase.random.chisquare.state\n    Generator state.\n","base.random.chisquare.stateLength":"\nbase.random.chisquare.stateLength\n    Length of generator state.\n","base.random.chisquare.byteLength":"\nbase.random.chisquare.byteLength\n    Size (in bytes) of generator state.\n","base.random.chisquare.toJSON":"\nbase.random.chisquare.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.cosine":"\nbase.random.cosine( μ:number, s:number )\n    Returns a pseudorandom number drawn from a raised cosine distribution.\n","base.random.cosine.factory":"\nbase.random.cosine.factory( [μ:number, s:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a raised cosine distribution.\n","base.random.cosine.NAME":"\nbase.random.cosine.NAME\n    Generator name.\n","base.random.cosine.PRNG":"\nbase.random.cosine.PRNG\n    Underlying pseudorandom number generator.\n","base.random.cosine.seed":"\nbase.random.cosine.seed\n    Pseudorandom number generator seed.\n","base.random.cosine.seedLength":"\nbase.random.cosine.seedLength\n    Length of generator seed.\n","base.random.cosine.state":"\nbase.random.cosine.state\n    Generator state.\n","base.random.cosine.stateLength":"\nbase.random.cosine.stateLength\n    Length of generator state.\n","base.random.cosine.byteLength":"\nbase.random.cosine.byteLength\n    Size (in bytes) of generator state.\n","base.random.cosine.toJSON":"\nbase.random.cosine.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.discreteUniform":"\nbase.random.discreteUniform( a:integer, b:integer )\n    Returns a pseudorandom number drawn from a discrete uniform distribution.\n","base.random.discreteUniform.factory":"\nbase.random.discreteUniform.factory( [a:integer, b:integer, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a discrete uniform distribution.\n","base.random.discreteUniform.NAME":"\nbase.random.discreteUniform.NAME\n    Generator name.\n","base.random.discreteUniform.PRNG":"\nbase.random.discreteUniform.PRNG\n    Underlying pseudorandom number generator.\n","base.random.discreteUniform.seed":"\nbase.random.discreteUniform.seed\n    Pseudorandom number generator seed.\n","base.random.discreteUniform.seedLength":"\nbase.random.discreteUniform.seedLength\n    Length of generator seed.\n","base.random.discreteUniform.state":"\nbase.random.discreteUniform.state\n    Generator state.\n","base.random.discreteUniform.stateLength":"\nbase.random.discreteUniform.stateLength\n    Length of generator state.\n","base.random.discreteUniform.byteLength":"\nbase.random.discreteUniform.byteLength\n    Size (in bytes) of generator state.\n","base.random.discreteUniform.toJSON":"\nbase.random.discreteUniform.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.erlang":"\nbase.random.erlang( k:integer, λ:number )\n    Returns a pseudorandom number drawn from an Erlang distribution.\n","base.random.erlang.factory":"\nbase.random.erlang.factory( [k:integer, λ:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an Erlang distribution.\n","base.random.erlang.NAME":"\nbase.random.erlang.NAME\n    Generator name.\n","base.random.erlang.PRNG":"\nbase.random.erlang.PRNG\n    Underlying pseudorandom number generator.\n","base.random.erlang.seed":"\nbase.random.erlang.seed\n    Pseudorandom number generator seed.\n","base.random.erlang.seedLength":"\nbase.random.erlang.seedLength\n    Length of generator seed.\n","base.random.erlang.state":"\nbase.random.erlang.state\n    Generator state.\n","base.random.erlang.stateLength":"\nbase.random.erlang.stateLength\n    Length of generator state.\n","base.random.erlang.byteLength":"\nbase.random.erlang.byteLength\n    Size (in bytes) of generator state.\n","base.random.erlang.toJSON":"\nbase.random.erlang.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.exponential":"\nbase.random.exponential( λ:number )\n    Returns a pseudorandom number drawn from an exponential distribution.\n","base.random.exponential.factory":"\nbase.random.exponential.factory( [λ:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an exponential distribution.\n","base.random.exponential.NAME":"\nbase.random.exponential.NAME\n    Generator name.\n","base.random.exponential.PRNG":"\nbase.random.exponential.PRNG\n    Underlying pseudorandom number generator.\n","base.random.exponential.seed":"\nbase.random.exponential.seed\n    Pseudorandom number generator seed.\n","base.random.exponential.seedLength":"\nbase.random.exponential.seedLength\n    Length of generator seed.\n","base.random.exponential.state":"\nbase.random.exponential.state\n    Generator state.\n","base.random.exponential.stateLength":"\nbase.random.exponential.stateLength\n    Length of generator state.\n","base.random.exponential.byteLength":"\nbase.random.exponential.byteLength\n    Size (in bytes) of generator state.\n","base.random.exponential.toJSON":"\nbase.random.exponential.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.f":"\nbase.random.f( d1:number, d2:number )\n    Returns a pseudorandom number drawn from an F distribution.\n","base.random.f.factory":"\nbase.random.f.factory( [d1:number, d2:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an F distribution.\n","base.random.f.NAME":"\nbase.random.f.NAME\n    Generator name.\n","base.random.f.PRNG":"\nbase.random.f.PRNG\n    Underlying pseudorandom number generator.\n","base.random.f.seed":"\nbase.random.f.seed\n    Pseudorandom number generator seed.\n","base.random.f.seedLength":"\nbase.random.f.seedLength\n    Length of generator seed.\n","base.random.f.state":"\nbase.random.f.state\n    Generator state.\n","base.random.f.stateLength":"\nbase.random.f.stateLength\n    Length of generator state.\n","base.random.f.byteLength":"\nbase.random.f.byteLength\n    Size (in bytes) of generator state.\n","base.random.f.toJSON":"\nbase.random.f.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.frechet":"\nbase.random.frechet( α:number, s:number, m:number )\n    Returns a pseudorandom number drawn from a Fréchet distribution.\n","base.random.frechet.factory":"\nbase.random.frechet.factory( [α:number, s:number, m:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a triangular distribution.\n","base.random.frechet.NAME":"\nbase.random.frechet.NAME\n    Generator name.\n","base.random.frechet.PRNG":"\nbase.random.frechet.PRNG\n    Underlying pseudorandom number generator.\n","base.random.frechet.seed":"\nbase.random.frechet.seed\n    Pseudorandom number generator seed.\n","base.random.frechet.seedLength":"\nbase.random.frechet.seedLength\n    Length of generator seed.\n","base.random.frechet.state":"\nbase.random.frechet.state\n    Generator state.\n","base.random.frechet.stateLength":"\nbase.random.frechet.stateLength\n    Length of generator state.\n","base.random.frechet.byteLength":"\nbase.random.frechet.byteLength\n    Size (in bytes) of generator state.\n","base.random.frechet.toJSON":"\nbase.random.frechet.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.gamma":"\nbase.random.gamma( α:number, β:number )\n    Returns a pseudorandom number drawn from a gamma distribution.\n","base.random.gamma.factory":"\nbase.random.gamma.factory( [α:number, β:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a gamma distribution.\n","base.random.gamma.NAME":"\nbase.random.gamma.NAME\n    Generator name.\n","base.random.gamma.PRNG":"\nbase.random.gamma.PRNG\n    Underlying pseudorandom number generator.\n","base.random.gamma.seed":"\nbase.random.gamma.seed\n    Pseudorandom number generator seed.\n","base.random.gamma.seedLength":"\nbase.random.gamma.seedLength\n    Length of generator seed.\n","base.random.gamma.state":"\nbase.random.gamma.state\n    Generator state.\n","base.random.gamma.stateLength":"\nbase.random.gamma.stateLength\n    Length of generator state.\n","base.random.gamma.byteLength":"\nbase.random.gamma.byteLength\n    Size of generator state.\n","base.random.gamma.toJSON":"\nbase.random.gamma.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.geometric":"\nbase.random.geometric( p:number )\n    Returns a pseudorandom number drawn from a geometric distribution.\n","base.random.geometric.factory":"\nbase.random.geometric.factory( [p:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a geometric distribution.\n","base.random.geometric.NAME":"\nbase.random.geometric.NAME\n    Generator name.\n","base.random.geometric.PRNG":"\nbase.random.geometric.PRNG\n    Underlying pseudorandom number generator.\n","base.random.geometric.seed":"\nbase.random.geometric.seed\n    Pseudorandom number generator seed.\n","base.random.geometric.seedLength":"\nbase.random.geometric.seedLength\n    Length of generator seed.\n","base.random.geometric.state":"\nbase.random.geometric.state\n    Generator state.\n","base.random.geometric.stateLength":"\nbase.random.geometric.stateLength\n    Length of generator state.\n","base.random.geometric.byteLength":"\nbase.random.geometric.byteLength\n    Size (in bytes) of generator state.\n","base.random.geometric.toJSON":"\nbase.random.geometric.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.gumbel":"\nbase.random.gumbel( μ:number, β:number )\n    Returns a pseudorandom number drawn from a Gumbel distribution.\n","base.random.gumbel.factory":"\nbase.random.gumbel.factory( [μ:number, β:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Gumbel distribution.\n","base.random.gumbel.NAME":"\nbase.random.gumbel.NAME\n    Generator name.\n","base.random.gumbel.PRNG":"\nbase.random.gumbel.PRNG\n    Underlying pseudorandom number generator.\n","base.random.gumbel.seed":"\nbase.random.gumbel.seed\n    Pseudorandom number generator seed.\n","base.random.gumbel.seedLength":"\nbase.random.gumbel.seedLength\n    Length of generator seed.\n","base.random.gumbel.state":"\nbase.random.gumbel.state\n    Generator state.\n","base.random.gumbel.stateLength":"\nbase.random.gumbel.stateLength\n    Length of generator state.\n","base.random.gumbel.byteLength":"\nbase.random.gumbel.byteLength\n    Size (in bytes) of generator state.\n","base.random.gumbel.toJSON":"\nbase.random.gumbel.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.hypergeometric":"\nbase.random.hypergeometric( N:integer, K:integer, n:integer )\n    Returns a pseudorandom number drawn from a hypergeometric distribution.\n","base.random.hypergeometric.factory":"\nbase.random.hypergeometric.factory( [N:integer, K:integer, n:integer, ]\n  [options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a hypergeometric distribution.\n","base.random.hypergeometric.NAME":"\nbase.random.hypergeometric.NAME\n    Generator name.\n","base.random.hypergeometric.PRNG":"\nbase.random.hypergeometric.PRNG\n    Underlying pseudorandom number generator.\n","base.random.hypergeometric.seed":"\nbase.random.hypergeometric.seed\n    Pseudorandom number generator seed.\n","base.random.hypergeometric.seedLength":"\nbase.random.hypergeometric.seedLength\n    Length of generator seed.\n","base.random.hypergeometric.state":"\nbase.random.hypergeometric.state\n    Generator state.\n","base.random.hypergeometric.stateLength":"\nbase.random.hypergeometric.stateLength\n    Length of generator state.\n","base.random.hypergeometric.byteLength":"\nbase.random.hypergeometric.byteLength\n    Size (in bytes) of generator state.\n","base.random.hypergeometric.toJSON":"\nbase.random.hypergeometric.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.improvedZiggurat":"\nbase.random.improvedZiggurat()\n    Returns a pseudorandom number drawn from a standard normal distribution.\n","base.random.improvedZiggurat.factory":"\nbase.random.improvedZiggurat.factory( [options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a standard normal distribution.\n","base.random.improvedZiggurat.NAME":"\nbase.random.improvedZiggurat.NAME\n    Generator name.\n","base.random.improvedZiggurat.PRNG":"\nbase.random.improvedZiggurat.PRNG\n    Underlying pseudorandom number generator.\n","base.random.improvedZiggurat.seed":"\nbase.random.improvedZiggurat.seed\n    Pseudorandom number generator seed.\n","base.random.improvedZiggurat.seedLength":"\nbase.random.improvedZiggurat.seedLength\n    Length of generator seed.\n","base.random.improvedZiggurat.state":"\nbase.random.improvedZiggurat.state\n    Generator state.\n","base.random.improvedZiggurat.stateLength":"\nbase.random.improvedZiggurat.stateLength\n    Length of generator state.\n","base.random.improvedZiggurat.byteLength":"\nbase.random.improvedZiggurat.byteLength\n    Size (in bytes) of generator state.\n","base.random.improvedZiggurat.toJSON":"\nbase.random.improvedZiggurat.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.invgamma":"\nbase.random.invgamma( α:number, β:number )\n    Returns a pseudorandom number drawn from an inverse gamma distribution.\n","base.random.invgamma.factory":"\nbase.random.invgamma.factory( [α:number, β:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from an inverse gamma distribution.\n","base.random.invgamma.NAME":"\nbase.random.invgamma.NAME\n    Generator name.\n","base.random.invgamma.PRNG":"\nbase.random.invgamma.PRNG\n    Underlying pseudorandom number generator.\n","base.random.invgamma.seed":"\nbase.random.invgamma.seed\n    Pseudorandom number generator seed.\n","base.random.invgamma.seedLength":"\nbase.random.invgamma.seedLength\n    Length of generator seed.\n","base.random.invgamma.state":"\nbase.random.invgamma.state\n    Generator state.\n","base.random.invgamma.stateLength":"\nbase.random.invgamma.stateLength\n    Length of generator state.\n","base.random.invgamma.byteLength":"\nbase.random.invgamma.byteLength\n    Size of generator state.\n","base.random.invgamma.toJSON":"\nbase.random.invgamma.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.kumaraswamy":"\nbase.random.kumaraswamy( a:number, b:number )\n    Returns a pseudorandom number drawn from Kumaraswamy's double bounded\n    distribution.\n","base.random.kumaraswamy.factory":"\nbase.random.kumaraswamy.factory( [a:number, b:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from Kumaraswamy's double bounded distribution.\n","base.random.kumaraswamy.NAME":"\nbase.random.kumaraswamy.NAME\n    Generator name.\n","base.random.kumaraswamy.PRNG":"\nbase.random.kumaraswamy.PRNG\n    Underlying pseudorandom number generator.\n","base.random.kumaraswamy.seed":"\nbase.random.kumaraswamy.seed\n    Pseudorandom number generator seed.\n","base.random.kumaraswamy.seedLength":"\nbase.random.kumaraswamy.seedLength\n    Length of generator seed.\n","base.random.kumaraswamy.state":"\nbase.random.kumaraswamy.state\n    Generator state.\n","base.random.kumaraswamy.stateLength":"\nbase.random.kumaraswamy.stateLength\n    Length of generator state.\n","base.random.kumaraswamy.byteLength":"\nbase.random.kumaraswamy.byteLength\n    Size (in bytes) of generator state.\n","base.random.kumaraswamy.toJSON":"\nbase.random.kumaraswamy.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.laplace":"\nbase.random.laplace( μ:number, b:number )\n    Returns a pseudorandom number drawn from a Laplace distribution.\n","base.random.laplace.factory":"\nbase.random.laplace.factory( [μ:number, b:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Laplace distribution.\n","base.random.laplace.NAME":"\nbase.random.laplace.NAME\n    Generator name.\n","base.random.laplace.PRNG":"\nbase.random.laplace.PRNG\n    Underlying pseudorandom number generator.\n","base.random.laplace.seed":"\nbase.random.laplace.seed\n    Pseudorandom number generator seed.\n","base.random.laplace.seedLength":"\nbase.random.laplace.seedLength\n    Length of generator seed.\n","base.random.laplace.state":"\nbase.random.laplace.state\n    Generator state.\n","base.random.laplace.stateLength":"\nbase.random.laplace.stateLength\n    Length of generator state.\n","base.random.laplace.byteLength":"\nbase.random.laplace.byteLength\n    Size (in bytes) of generator state.\n","base.random.laplace.toJSON":"\nbase.random.laplace.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.levy":"\nbase.random.levy( μ:number, c:number )\n    Returns a pseudorandom number drawn from a Lévy distribution.\n","base.random.levy.factory":"\nbase.random.levy.factory( [μ:number, c:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Lévy distribution.\n","base.random.levy.NAME":"\nbase.random.levy.NAME\n    Generator name.\n","base.random.levy.PRNG":"\nbase.random.levy.PRNG\n    Underlying pseudorandom number generator.\n","base.random.levy.seed":"\nbase.random.levy.seed\n    Pseudorandom number generator seed.\n","base.random.levy.seedLength":"\nbase.random.levy.seedLength\n    Length of generator seed.\n","base.random.levy.state":"\nbase.random.levy.state\n    Generator state.\n","base.random.levy.stateLength":"\nbase.random.levy.stateLength\n    Length of generator state.\n","base.random.levy.byteLength":"\nbase.random.levy.byteLength\n    Size (in bytes) of generator state.\n","base.random.levy.toJSON":"\nbase.random.levy.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.logistic":"\nbase.random.logistic( μ:number, s:number )\n    Returns a pseudorandom number drawn from a logistic distribution.\n","base.random.logistic.factory":"\nbase.random.logistic.factory( [μ:number, s:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a logistic distribution.\n","base.random.logistic.NAME":"\nbase.random.logistic.NAME\n    Generator name.\n","base.random.logistic.PRNG":"\nbase.random.logistic.PRNG\n    Underlying pseudorandom number generator.\n","base.random.logistic.seed":"\nbase.random.logistic.seed\n    Pseudorandom number generator seed.\n","base.random.logistic.seedLength":"\nbase.random.logistic.seedLength\n    Length of generator seed.\n","base.random.logistic.state":"\nbase.random.logistic.state\n    Generator state.\n","base.random.logistic.stateLength":"\nbase.random.logistic.stateLength\n    Length of generator state.\n","base.random.logistic.byteLength":"\nbase.random.logistic.byteLength\n    Size (in bytes) of generator state.\n","base.random.logistic.toJSON":"\nbase.random.logistic.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.lognormal":"\nbase.random.lognormal( μ:number, σ:number )\n    Returns a pseudorandom number drawn from a lognormal distribution.\n","base.random.lognormal.factory":"\nbase.random.lognormal.factory( [μ:number, σ:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a lognormal distribution.\n","base.random.lognormal.NAME":"\nbase.random.lognormal.NAME\n    Generator name.\n","base.random.lognormal.PRNG":"\nbase.random.lognormal.PRNG\n    Underlying pseudorandom number generator.\n","base.random.lognormal.seed":"\nbase.random.lognormal.seed\n    Pseudorandom number generator seed.\n","base.random.lognormal.seedLength":"\nbase.random.lognormal.seedLength\n    Length of generator seed.\n","base.random.lognormal.state":"\nbase.random.lognormal.state\n    Generator state.\n","base.random.lognormal.stateLength":"\nbase.random.lognormal.stateLength\n    Length of generator state.\n","base.random.lognormal.byteLength":"\nbase.random.lognormal.byteLength\n    Size (in bytes) of generator state.\n","base.random.lognormal.toJSON":"\nbase.random.lognormal.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.minstd":"\nbase.random.minstd()\n    Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n","base.random.minstd.normalized":"\nbase.random.minstd.normalized()\n    Returns a pseudorandom number on the interval `[0,1)`.\n","base.random.minstd.factory":"\nbase.random.minstd.factory( [options:Object] )\n    Returns a linear congruential pseudorandom number generator (LCG).\n","base.random.minstd.NAME":"\nbase.random.minstd.NAME\n    Generator name.\n","base.random.minstd.MIN":"\nbase.random.minstd.MIN\n    Minimum possible value.\n","base.random.minstd.MAX":"\nbase.random.minstd.MAX\n    Maximum possible value.\n","base.random.minstd.seed":"\nbase.random.minstd.seed\n    Pseudorandom number generator seed.\n","base.random.minstd.seedLength":"\nbase.random.minstd.seedLength\n    Length of generator seed.\n","base.random.minstd.state":"\nbase.random.minstd.state\n    Generator state.\n","base.random.minstd.stateLength":"\nbase.random.minstd.stateLength\n    Length of generator state.\n","base.random.minstd.byteLength":"\nbase.random.minstd.byteLength\n    Size (in bytes) of generator state.\n","base.random.minstd.toJSON":"\nbase.random.minstd.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.minstdShuffle":"\nbase.random.minstdShuffle()\n    Returns a pseudorandom integer on the interval `[1, 2147483646]`.\n","base.random.minstdShuffle.normalized":"\nbase.random.minstdShuffle.normalized()\n    Returns a pseudorandom number on the interval `[0,1)`.\n","base.random.minstdShuffle.factory":"\nbase.random.minstdShuffle.factory( [options:Object] )\n    Returns a linear congruential pseudorandom number generator (LCG) whose\n    output is shuffled.\n","base.random.minstdShuffle.NAME":"\nbase.random.minstdShuffle.NAME\n    Generator name.\n","base.random.minstdShuffle.MIN":"\nbase.random.minstdShuffle.MIN\n    Minimum possible value.\n","base.random.minstdShuffle.MAX":"\nbase.random.minstdShuffle.MAX\n    Maximum possible value.\n","base.random.minstdShuffle.seed":"\nbase.random.minstdShuffle.seed\n    Pseudorandom number generator seed.\n","base.random.minstdShuffle.seedLength":"\nbase.random.minstdShuffle.seedLength\n    Length of generator seed.\n","base.random.minstdShuffle.state":"\nbase.random.minstdShuffle.state\n    Generator state.\n","base.random.minstdShuffle.stateLength":"\nbase.random.minstdShuffle.stateLength\n    Length of generator state.\n","base.random.minstdShuffle.byteLength":"\nbase.random.minstdShuffle.byteLength\n    Size (in bytes) of generator state.\n","base.random.minstdShuffle.toJSON":"\nbase.random.minstdShuffle.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.mt19937":"\nbase.random.mt19937()\n    Returns a pseudorandom integer on the interval `[0, 4294967295]`.\n","base.random.mt19937.normalized":"\nbase.random.mt19937.normalized()\n    Returns a pseudorandom number on the interval `[0,1)` with 53-bit precision.\n","base.random.mt19937.factory":"\nbase.random.mt19937.factory( [options:Object] )\n    Returns a 32-bit Mersenne Twister pseudorandom number generator.\n","base.random.mt19937.NAME":"\nbase.random.mt19937.NAME\n    Generator name.\n","base.random.mt19937.MIN":"\nbase.random.mt19937.MIN\n    Minimum possible value.\n","base.random.mt19937.MAX":"\nbase.random.mt19937.MAX\n    Maximum possible value.\n","base.random.mt19937.seed":"\nbase.random.mt19937.seed\n    Pseudorandom number generator seed.\n","base.random.mt19937.seedLength":"\nbase.random.mt19937.seedLength\n    Length of generator seed.\n","base.random.mt19937.state":"\nbase.random.mt19937.state\n    Generator state.\n","base.random.mt19937.stateLength":"\nbase.random.mt19937.stateLength\n    Length of generator state.\n","base.random.mt19937.byteLength":"\nbase.random.mt19937.byteLength\n    Size (in bytes) of generator state.\n","base.random.mt19937.toJSON":"\nbase.random.mt19937.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.negativeBinomial":"\nbase.random.negativeBinomial( r:number, p:number )\n    Returns a pseudorandom number drawn from a negative binomial distribution.\n","base.random.negativeBinomial.factory":"\nbase.random.negativeBinomial.factory( [r:number, p:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a negative binomial distribution.\n","base.random.negativeBinomial.NAME":"\nbase.random.negativeBinomial.NAME\n    Generator name.\n","base.random.negativeBinomial.PRNG":"\nbase.random.negativeBinomial.PRNG\n    Underlying pseudorandom number generator.\n","base.random.negativeBinomial.seed":"\nbase.random.negativeBinomial.seed\n    Pseudorandom number generator seed.\n","base.random.negativeBinomial.seedLength":"\nbase.random.negativeBinomial.seedLength\n    Length of generator seed.\n","base.random.negativeBinomial.state":"\nbase.random.negativeBinomial.state\n    Generator state.\n","base.random.negativeBinomial.stateLength":"\nbase.random.negativeBinomial.stateLength\n    Length of generator state.\n","base.random.negativeBinomial.byteLength":"\nbase.random.negativeBinomial.byteLength\n    Size (in bytes) of generator state.\n","base.random.negativeBinomial.toJSON":"\nbase.random.negativeBinomial.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.normal":"\nbase.random.normal( μ:number, σ:number )\n    Returns a pseudorandom number drawn from a normal distribution.\n","base.random.normal.factory":"\nbase.random.normal.factory( [μ:number, σ:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a normal distribution.\n","base.random.normal.NAME":"\nbase.random.normal.NAME\n    Generator name.\n","base.random.normal.PRNG":"\nbase.random.normal.PRNG\n    Underlying pseudorandom number generator.\n","base.random.normal.seed":"\nbase.random.normal.seed\n    Pseudorandom number generator seed.\n","base.random.normal.seedLength":"\nbase.random.normal.seedLength\n    Length of generator seed.\n","base.random.normal.state":"\nbase.random.normal.state\n    Generator state.\n","base.random.normal.stateLength":"\nbase.random.normal.stateLength\n    Length of generator state.\n","base.random.normal.byteLength":"\nbase.random.normal.byteLength\n    Size of generator state.\n","base.random.normal.toJSON":"\nbase.random.normal.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.pareto1":"\nbase.random.pareto1( α:number, β:number )\n    Returns a pseudorandom number drawn from a Pareto (Type I) distribution.\n","base.random.pareto1.factory":"\nbase.random.pareto1.factory( [α:number, β:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Pareto (Type I) distribution.\n","base.random.pareto1.NAME":"\nbase.random.pareto1.NAME\n    Generator name.\n","base.random.pareto1.PRNG":"\nbase.random.pareto1.PRNG\n    Underlying pseudorandom number generator.\n","base.random.pareto1.seed":"\nbase.random.pareto1.seed\n    Pseudorandom number generator seed.\n","base.random.pareto1.seedLength":"\nbase.random.pareto1.seedLength\n    Length of generator seed.\n","base.random.pareto1.state":"\nbase.random.pareto1.state\n    Generator state.\n","base.random.pareto1.stateLength":"\nbase.random.pareto1.stateLength\n    Length of generator state.\n","base.random.pareto1.byteLength":"\nbase.random.pareto1.byteLength\n    Size (in bytes) of generator state.\n","base.random.pareto1.toJSON":"\nbase.random.pareto1.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.poisson":"\nbase.random.poisson( λ:number )\n    Returns a pseudorandom number drawn from a Poisson distribution.\n","base.random.poisson.factory":"\nbase.random.poisson.factory( [λ:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Poisson distribution.\n","base.random.poisson.NAME":"\nbase.random.poisson.NAME\n    Generator name.\n","base.random.poisson.PRNG":"\nbase.random.poisson.PRNG\n    Underlying pseudorandom number generator.\n","base.random.poisson.seed":"\nbase.random.poisson.seed\n    Pseudorandom number generator seed.\n","base.random.poisson.seedLength":"\nbase.random.poisson.seedLength\n    Length of generator seed.\n","base.random.poisson.state":"\nbase.random.poisson.state\n    Generator state.\n","base.random.poisson.stateLength":"\nbase.random.poisson.stateLength\n    Length of generator state.\n","base.random.poisson.byteLength":"\nbase.random.poisson.byteLength\n    Size (in bytes) of generator state.\n","base.random.poisson.toJSON":"\nbase.random.poisson.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.randi":"\nbase.random.randi()\n    Returns a pseudorandom number having an integer value.\n","base.random.randi.factory":"\nbase.random.randi.factory( [options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers having integer values.\n","base.random.randi.NAME":"\nbase.random.randi.NAME\n    Generator name.\n","base.random.randi.PRNG":"\nbase.random.randi.PRNG\n    Underlying pseudorandom number generator.\n","base.random.randi.MIN":"\nbase.random.randi.MIN\n    Minimum possible value (specific to underlying PRNG).\n","base.random.randi.MAX":"\nbase.random.randi.MAX\n    Maximum possible value (specific to underlying PRNG).\n","base.random.randi.seed":"\nbase.random.randi.seed\n    Pseudorandom number generator seed.\n","base.random.randi.seedLength":"\nbase.random.randi.seedLength\n    Length of generator seed.\n","base.random.randi.state":"\nbase.random.randi.state\n    Generator state.\n","base.random.randi.stateLength":"\nbase.random.randi.stateLength\n    Length of generator state.\n","base.random.randi.byteLength":"\nbase.random.randi.byteLength\n    Size (in bytes) of generator state.\n","base.random.randi.toJSON":"\nbase.random.randi.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.randn":"\nbase.random.randn()\n    Returns a pseudorandom number drawn from a standard normal distribution.\n","base.random.randn.factory":"\nbase.random.randn.factory( [options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a standard normal distribution.\n","base.random.randn.NAME":"\nbase.random.randn.NAME\n    Generator name.\n","base.random.randn.PRNG":"\nbase.random.randn.PRNG\n    Underlying pseudorandom number generator.\n","base.random.randn.seed":"\nbase.random.randn.seed\n    Pseudorandom number generator seed.\n","base.random.randn.seedLength":"\nbase.random.randn.seedLength\n    Length of generator seed.\n","base.random.randn.state":"\nbase.random.randn.state\n    Generator state.\n","base.random.randn.stateLength":"\nbase.random.randn.stateLength\n    Length of generator state.\n","base.random.randn.byteLength":"\nbase.random.randn.byteLength\n    Size (in bytes) of generator state.\n","base.random.randn.toJSON":"\nbase.random.randn.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.randu":"\nbase.random.randu()\n    Returns a pseudorandom number drawn from a uniform distribution.\n","base.random.randu.factory":"\nbase.random.randu.factory( [options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a uniform distribution.\n","base.random.randu.NAME":"\nbase.random.randu.NAME\n    Generator name.\n","base.random.randu.PRNG":"\nbase.random.randu.PRNG\n    Underlying pseudorandom number generator.\n","base.random.randu.MIN":"\nbase.random.randu.MIN\n    Minimum possible value (specific to underlying PRNG).\n","base.random.randu.MAX":"\nbase.random.randu.MAX\n    Maximum possible value (specific to underlying PRNG).\n","base.random.randu.seed":"\nbase.random.randu.seed\n    Pseudorandom number generator seed.\n","base.random.randu.seedLength":"\nbase.random.randu.seedLength\n    Length of generator seed.\n","base.random.randu.state":"\nbase.random.randu.state\n    Generator state.\n","base.random.randu.stateLength":"\nbase.random.randu.stateLength\n    Length of generator state.\n","base.random.randu.byteLength":"\nbase.random.randu.byteLength\n    Size (in bytes) of generator state.\n","base.random.randu.toJSON":"\nbase.random.randu.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.rayleigh":"\nbase.random.rayleigh( σ:number )\n    Returns a pseudorandom number drawn from a Rayleigh distribution.\n","base.random.rayleigh.factory":"\nbase.random.rayleigh.factory( [σ:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Rayleigh distribution.\n","base.random.rayleigh.NAME":"\nbase.random.rayleigh.NAME\n    Generator name.\n","base.random.rayleigh.PRNG":"\nbase.random.rayleigh.PRNG\n    Underlying pseudorandom number generator.\n","base.random.rayleigh.seed":"\nbase.random.rayleigh.seed\n    Pseudorandom number generator seed.\n","base.random.rayleigh.seedLength":"\nbase.random.rayleigh.seedLength\n    Length of generator seed.\n","base.random.rayleigh.state":"\nbase.random.rayleigh.state\n    Generator state.\n","base.random.rayleigh.stateLength":"\nbase.random.rayleigh.stateLength\n    Length of generator state.\n","base.random.rayleigh.byteLength":"\nbase.random.rayleigh.byteLength\n    Size (in bytes) of generator state.\n","base.random.rayleigh.toJSON":"\nbase.random.rayleigh.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.t":"\nbase.random.t( v:number )\n    Returns a pseudorandom number drawn from a Student's t distribution.\n","base.random.t.factory":"\nbase.random.t.factory( [v:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Student's t distribution.\n","base.random.t.NAME":"\nbase.random.t.NAME\n    Generator name.\n","base.random.t.PRNG":"\nbase.random.t.PRNG\n    Underlying pseudorandom number generator.\n","base.random.t.seed":"\nbase.random.t.seed\n    Pseudorandom number generator seed.\n","base.random.t.seedLength":"\nbase.random.t.seedLength\n    Length of generator seed.\n","base.random.t.state":"\nbase.random.t.state\n    Generator state.\n","base.random.t.stateLength":"\nbase.random.t.stateLength\n    Length of generator state.\n","base.random.t.byteLength":"\nbase.random.t.byteLength\n    Size (in bytes) of generator state.\n","base.random.t.toJSON":"\nbase.random.t.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.triangular":"\nbase.random.triangular( a:number, b:number, c:number )\n    Returns a pseudorandom number drawn from a triangular distribution.\n","base.random.triangular.factory":"\nbase.random.triangular.factory( [a:number, b:number, c:number, ]\n  [options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a triangular distribution.\n","base.random.triangular.NAME":"\nbase.random.triangular.NAME\n    Generator name.\n","base.random.triangular.PRNG":"\nbase.random.triangular.PRNG\n    Underlying pseudorandom number generator.\n","base.random.triangular.seed":"\nbase.random.triangular.seed\n    Pseudorandom number generator seed.\n","base.random.triangular.seedLength":"\nbase.random.triangular.seedLength\n    Length of generator seed.\n","base.random.triangular.state":"\nbase.random.triangular.state\n    Generator state.\n","base.random.triangular.stateLength":"\nbase.random.triangular.stateLength\n    Length of generator state.\n","base.random.triangular.byteLength":"\nbase.random.triangular.byteLength\n    Size (in bytes) of generator state.\n","base.random.triangular.toJSON":"\nbase.random.triangular.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.uniform":"\nbase.random.uniform( a:number, b:number )\n    Returns a pseudorandom number drawn from a continuous uniform distribution.\n","base.random.uniform.factory":"\nbase.random.uniform.factory( [a:number, b:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a continuous uniform distribution.\n","base.random.uniform.NAME":"\nbase.random.uniform.NAME\n    Generator name.\n","base.random.uniform.PRNG":"\nbase.random.uniform.PRNG\n    Underlying pseudorandom number generator.\n","base.random.uniform.seed":"\nbase.random.uniform.seed\n    Pseudorandom number generator seed.\n","base.random.uniform.seedLength":"\nbase.random.uniform.seedLength\n    Length of generator seed.\n","base.random.uniform.state":"\nbase.random.uniform.state\n    Generator state.\n","base.random.uniform.stateLength":"\nbase.random.uniform.stateLength\n    Length of generator state.\n","base.random.uniform.byteLength":"\nbase.random.uniform.byteLength\n    Size (in bytes) of generator state.\n","base.random.uniform.toJSON":"\nbase.random.uniform.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.random.weibull":"\nbase.random.weibull( k:number, λ:number )\n    Returns a pseudorandom number drawn from a Weibull distribution.\n","base.random.weibull.factory":"\nbase.random.weibull.factory( [k:number, λ:number, ][options:Object] )\n    Returns a pseudorandom number generator (PRNG) for generating pseudorandom\n    numbers drawn from a Weibull distribution.\n","base.random.weibull.NAME":"\nbase.random.weibull.NAME\n    Generator name.\n","base.random.weibull.PRNG":"\nbase.random.weibull.PRNG\n    Underlying pseudorandom number generator.\n","base.random.weibull.seed":"\nbase.random.weibull.seed\n    Pseudorandom number generator seed.\n","base.random.weibull.seedLength":"\nbase.random.weibull.seedLength\n    Length of generator seed.\n","base.random.weibull.state":"\nbase.random.weibull.state\n    Generator state.\n","base.random.weibull.stateLength":"\nbase.random.weibull.stateLength\n    Length of generator state.\n","base.random.weibull.byteLength":"\nbase.random.weibull.byteLength\n    Size (in bytes) of generator state.\n","base.random.weibull.toJSON":"\nbase.random.weibull.toJSON()\n    Serializes the pseudorandom number generator as a JSON object.\n","base.rcbrt":"\nbase.rcbrt( x:number )\n    Computes the reciprocal cube root of a double-precision floating-point\n    number.\n","base.rcbrtf":"\nbase.rcbrtf( x:number )\n    Computes the reciprocal cube root of a single-precision floating-point\n    number.\n","base.reldiff":"\nbase.reldiff( x:number, y:number[, scale:string|Function] )\n    Computes the relative difference of two real numbers.\n","base.removeFirst":"\nbase.removeFirst( str:string, n:integer )\n    Removes the first `n` UTF-16 code units of a string.\n","base.removeFirstCodePoint":"\nbase.removeFirstCodePoint( str:string, n:integer )\n    Removes the first `n` Unicode code points of a string.\n","base.removeFirstGraphemeCluster":"\nbase.removeFirstGraphemeCluster( str:string, n:integer )\n    Removes the first `n` grapheme clusters (i.e., user-perceived characters)\n    of a string.\n","base.removeLast":"\nbase.removeLast( str:string, n:integer )\n    Removes the last `n` UTF-16 code units of a string.\n","base.removeLastCodePoint":"\nbase.removeLastCodePoint( str:string, n:integer )\n    Removes the last `n` Unicode code points of a string.\n","base.removeLastGraphemeCluster":"\nbase.removeLastGraphemeCluster( str:string, n:integer )\n    Removes the last `n` grapheme clusters (i.e., user-perceived characters)\n    of a string.\n","base.rempio2":"\nbase.rempio2( x:number, y:Array|TypedArray|Object )\n    Computes `x - nπ/2 = r`.\n","base.repeat":"\nbase.repeat( str:string, n:integer )\n    Repeats a string `n` times and returns the concatenated result.\n","base.replace":"\nbase.replace( str:string, search:RegExp, newval:string|Function )\n    Replaces search occurrences with a replacement string.\n","base.replaceAfter":"\nbase.replaceAfter( str:string, search:string, replacement:string, \n  fromIndex:integer )\n    Replaces the substring after the first occurrence of a specified search\n    string.\n","base.replaceAfterLast":"\nbase.replaceAfterLast( str:string, search:string, replacement:string, \n  fromIndex:integer )\n    Replaces the substring after the last occurrence of a specified search\n    string.\n","base.replaceBefore":"\nbase.replaceBefore( str:string, search:string, replacement:string, \n  fromIndex:integer )\n    Replaces the substring before the first occurrence of a specified search\n    string.\n","base.replaceBeforeLast":"\nbase.replaceBeforeLast( str:string, search:string, replacement:string, \n  fromIndex:integer )\n    Replaces the substring before the last occurrence of a specified search\n    string.\n","base.reverse":"\nbase.reverse( str:string )\n    Reverses the UTF-16 code units of a string.\n","base.reverseCodePoints":"\nbase.reverseCodePoints( str:string )\n    Reverses the Unicode code points of a string.\n","base.reverseGraphemeClusters":"\nbase.reverseGraphemeClusters( str:string )\n    Reverses the grapheme clusters (i.e., user-perceived characters) of a\n    string.\n","base.rightPad":"\nbase.rightPad( str:string, len:integer, pad:string )\n    Right pads a string such that the padded string has a length of at least\n    `len`.\n","base.rightTrim":"\nbase.rightTrim( str:string )\n    Trims whitespace from the end of a string.\n","base.risingFactorial":"\nbase.risingFactorial( x:number, n:integer )\n    Computes the rising factorial of `x` and `n`.\n","base.rotl32":"\nbase.rotl32( x:integer, shift:integer )\n    Performs a bitwise rotation to the left.\n","base.rotr32":"\nbase.rotr32( x:integer, shift:integer )\n    Performs a bitwise rotation to the right.\n","base.round":"\nbase.round( x:number )\n    Rounds a numeric value to the nearest integer.\n","base.round2":"\nbase.round2( x:number )\n    Rounds a numeric value to the nearest power of two on a linear scale.\n","base.round10":"\nbase.round10( x:number )\n    Rounds a numeric value to the nearest power of ten on a linear scale.\n","base.roundb":"\nbase.roundb( x:number, n:integer, b:integer )\n    Rounds a numeric value to the nearest multiple of `b^n` on a linear scale.\n","base.roundn":"\nbase.roundn( x:number, n:integer )\n    Rounds a numeric value to the nearest multiple of `10^n`.\n","base.roundsd":"\nbase.roundsd( x:number, n:integer[, b:integer] )\n    Rounds a numeric value to the nearest number with `n` significant figures.\n","base.rsqrt":"\nbase.rsqrt( x:number )\n    Computes the reciprocal square root of a double-precision floating-point\n    number.\n","base.rsqrtf":"\nbase.rsqrtf( x:number )\n    Computes the reciprocal square root of a single-precision floating-point\n    number.\n","base.sargs2multislice":"\nbase.sargs2multislice( str:string )\n    Creates a MultiSlice object from a comma-separated list of string-serialized\n    MultiSlice constructor arguments.\n","base.scalar2ndarray":"\nbase.scalar2ndarray( value:any, dtype:string, order:string )\n    Returns a zero-dimensional ndarray containing a provided scalar value.\n","base.secd":"\nbase.secd( x:number )\n    Computes the secant of an angle measured in degrees.\n","base.seq2multislice":"\nbase.seq2multislice( str:string, shape:Array<integer>, strict:boolean )\n    Converts a multidimensional subsequence string to a MultiSlice object.\n","base.seq2slice":"\nbase.seq2slice( str:string, len:integer, strict:boolean )\n    Converts a subsequence string to a Slice object.\n","base.setHighWord":"\nbase.setHighWord( x:number, high:integer )\n    Sets the more significant 32 bits of a double-precision floating-point\n    number.\n","base.setLowWord":"\nbase.setLowWord( x:number, low:integer )\n    Sets the less significant 32 bits of a double-precision floating-point\n    number.\n","base.sici":"\nbase.sici( x:number )\n    Computes the sine and cosine integrals.\n","base.sici.assign":"\nbase.sici.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n  offset:integer )\n    Computes the sine and cosine integrals and assigns results to a provided\n    output array.\n","base.signbit":"\nbase.signbit( x:number )\n    Returns a boolean indicating if the sign bit is on (true) or off (false).\n","base.signbitf":"\nbase.signbitf( x:float )\n    Returns a boolean indicating if the sign bit is on (true) or off (false).\n","base.significandf":"\nbase.significandf( x:float )\n    Returns an integer corresponding to the significand of a single-precision\n    floating-point number.\n","base.signum":"\nbase.signum( x:number )\n    Evaluates the signum function for a double-precision floating-point number.\n","base.signumf":"\nbase.signumf( x:number )\n    Evaluates the signum function for a single-precision floating-point number.\n","base.sin":"\nbase.sin( x:number )\n    Computes the sine of a number.\n","base.sinc":"\nbase.sinc( x:number )\n    Computes the normalized cardinal sine of a number.\n","base.sincos":"\nbase.sincos( x:number )\n    Simultaneously computes the sine and cosine of a number.\n\nbase.sincos( x:number, out:Array|TypedArray|Object, stride:integer, \n  offset:integer )\n    Simultaneously computes the sine and cosine of a number and assigns\n    results to a provided output array.\n","base.sincospi":"\nbase.sincospi( x:number )\n    Simultaneously computes the sine and cosine of a number times π.\n","base.sincospi.assign":"\nbase.sincospi.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n  offset:integer )\n    Simultaneously computes the sine and cosine of a number times π and\n    assigns results to a provided output array.\n","base.sinh":"\nbase.sinh( x:number )\n    Computes the hyperbolic sine of a double-precision floating-point number.\n","base.sinpi":"\nbase.sinpi( x:number )\n    Computes the value of `sin(πx)`.\n","base.slice2seq":"\nbase.slice2seq( slice:Slice )\n    Converts a Slice object to a subsequence string.\n","base.sliceLength":"\nbase.sliceLength( slice:Slice )\n    Returns the number of elements in a normalized slice.\n","base.sliceNonReducedDimensions":"\nbase.sliceNonReducedDimensions( slice:MultiSlice )\n    Returns a list of non-reduced dimensions in an un-normalized multi-slice.\n","base.sliceReducedDimensions":"\nbase.sliceReducedDimensions( slice:MultiSlice )\n    Returns a list of reduced dimensions in an un-normalized multi-slice.\n","base.sliceShape":"\nbase.sliceShape( slice:MultiSlice )\n    Returns the shape of a normalized multi-slice.\n","base.snakecase":"\nbase.snakecase( str:string )\n    Converts a string to snake case.\n","base.spence":"\nbase.spence( x:number )\n    Evaluates Spence's function, which is also known as the dilogarithm.\n","base.sqrt":"\nbase.sqrt( x:number )\n    Computes the principal square root of a double-precision floating-point\n    number.\n","base.sqrt1pm1":"\nbase.sqrt1pm1( x:number )\n    Computes the principal square root of `1+x` minus one.\n","base.sqrtf":"\nbase.sqrtf( x:number )\n    Computes the principal square root of a single-precision floating-point\n    number.\n","base.sqrtpi":"\nbase.sqrtpi( x:number )\n    Computes the principal square root of the product of π and a positive\n    double-precision floating-point number.\n","base.startcase":"\nbase.startcase( str:string )\n    Capitalizes the first letter of each word in an input string.\n","base.startsWith":"\nbase.startsWith( str:string, search:string, position:integer )\n    Tests if a string starts with the characters of another string.\n","base.stickycase":"\nbase.stickycase( str[, p] )\n    Converts a string to sticky case.\n","base.strided.binary":"\nbase.strided.binary( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  fcn:Function )\n    Applies a binary callback to strided input array elements and assigns\n    results to elements in a strided output array.\n","base.strided.binary.ndarray":"\nbase.strided.binary.ndarray( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  offsets:ArrayLikeObject<integer>, fcn:Function )\n    Applies a binary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n","base.strided.binaryDtypeSignatures":"\nbase.strided.binaryDtypeSignatures( dtypes1:ArrayLike<any>, \n  dtypes2:ArrayLike<any>, dtypes3:ArrayLike<any>[, options:Object] )\n    Generates a list of binary interface signatures from strided array data\n    types.\n","base.strided.binarySignatureCallbacks":"\nbase.strided.binarySignatureCallbacks( table:Object, signatures:ArrayLike<any> )\n    Assigns callbacks to binary interfaces according to type promotion rules.\n","base.strided.ccopy":"\nbase.strided.ccopy( N:integer, x:Complex64Array, strideX:integer, \n  y:Complex64Array, strideY:integer )\n    Copies values from one complex single-precision floating-point vector to\n    another complex single-precision floating-point vector.\n","base.strided.ccopy.ndarray":"\nbase.strided.ccopy.ndarray( N:integer, x:Complex64Array, strideX:integer, \n  offsetX:integer, y:Complex64Array, strideY:integer, offsetY:integer )\n    Copies values from one complex single-precision floating-point vector to\n    another complex single-precision floating-point vector using alternative\n    indexing semantics.\n","base.strided.cmap":"\nbase.strided.cmap( N:integer, x:Complex64Array, strideX:integer, \n  y:Complex64Array, strideY:integer, fcn:Function )\n    Applies a unary function to a single-precision complex floating-point\n    strided input array and assigns results to a single-precision complex\n    floating-point strided output array.\n","base.strided.cmap.ndarray":"\nbase.strided.cmap.ndarray( N:integer, x:Complex64Array, strideX:integer, \n  offsetX:integer, y:Complex64Array, strideY:integer, offsetY:integer, \n  fcn:Function )\n    Applies a unary function to a single-precision complex floating-point\n    strided input array and assigns results to a single-precision complex\n    floating-point strided output array using alternative indexing semantics.\n","base.strided.cswap":"\nbase.strided.cswap( N:integer, x:Complex64Array, strideX:integer, \n  y:Complex64Array, strideY:integer )\n    Interchanges two complex single-precision floating-point vectors.\n","base.strided.cswap.ndarray":"\nbase.strided.cswap.ndarray( N:integer, x:Complex64Array, strideX:integer, \n  offsetX:integer, y:Complex64Array, strideY:integer, offsetY:integer )\n    Interchanges two complex single-precision floating-point vectors using\n    alternative indexing semantics.\n","base.strided.cumax":"\nbase.strided.cumax( N:integer, x:Array|TypedArray, strideX:integer, \n  y:Array|TypedArray, strideY:integer )\n    Computes the cumulative maximum of a strided array.\n","base.strided.cumax.ndarray":"\nbase.strided.cumax.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n  offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n    Computes the cumulative maximum of a strided array using alternative\n    indexing semantics.\n","base.strided.cumaxabs":"\nbase.strided.cumaxabs( N:integer, x:Array|TypedArray, strideX:integer, \n  y:Array|TypedArray, strideY:integer )\n    Computes the cumulative maximum absolute value of a strided array.\n","base.strided.cumaxabs.ndarray":"\nbase.strided.cumaxabs.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n  offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n    Computes the cumulative maximum absolute value of a strided array using\n    alternative indexing semantics.\n","base.strided.cumin":"\nbase.strided.cumin( N:integer, x:Array|TypedArray, strideX:integer, \n  y:Array|TypedArray, strideY:integer )\n    Computes the cumulative minimum of a strided array.\n","base.strided.cumin.ndarray":"\nbase.strided.cumin.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n  offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n    Computes the cumulative minimum of a strided array using alternative\n    indexing semantics.\n","base.strided.cuminabs":"\nbase.strided.cuminabs( N:integer, x:Array|TypedArray, strideX:integer, \n  y:Array|TypedArray, strideY:integer )\n    Computes the cumulative minimum absolute value of a strided array.\n","base.strided.cuminabs.ndarray":"\nbase.strided.cuminabs.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n  offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n    Computes the cumulative minimum absolute value of a strided array using\n    alternative indexing semantics.\n","base.strided.dabs":"\nbase.strided.dabs( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n  strideY:integer )\n    Computes the absolute value for each element in a double-precision floating-\n    point strided array `x` and assigns the results to elements in a double-\n    precision floating-point strided array `y`.\n","base.strided.dabs.ndarray":"\nbase.strided.dabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Computes the absolute value for each element in a double-precision floating-\n    point strided array `x` and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.dabs2":"\nbase.strided.dabs2( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n  strideY:integer )\n    Computes the squared absolute value for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y`.\n","base.strided.dabs2.ndarray":"\nbase.strided.dabs2.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Computes the squared absolute value for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.dapx":"\nbase.strided.dapx( N:integer, alpha:number, x:Float64Array, strideX:integer )\n    Adds a scalar constant to each element in a double-precision floating-point\n    strided array.\n","base.strided.dapx.ndarray":"\nbase.strided.dapx.ndarray( N:integer, alpha:number, x:Float64Array, \n  strideX:integer, offsetX:integer )\n    Adds a scalar constant to each element in a double-precision floating-point\n    strided array using alternative indexing semantics.\n","base.strided.dapxsum":"\nbase.strided.dapxsum( N:integer, alpha:number, x:Float64Array, strideX:integer )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum.\n","base.strided.dapxsum.ndarray":"\nbase.strided.dapxsum.ndarray( N:integer, alpha:number, x:Float64Array, \n  strideX:integer, offsetX:integer )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using alternative indexing semantics.\n","base.strided.dapxsumkbn":"\nbase.strided.dapxsumkbn( N:integer, alpha:number, x:Float64Array, \n  strideX:integer )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using an improved Kahan–Babuška\n    algorithm.\n","base.strided.dapxsumkbn.ndarray":"\nbase.strided.dapxsumkbn.ndarray( N:integer, alpha:number, x:Float64Array, \n  strideX:integer, offsetX:integer )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using an improved Kahan–Babuška\n    algorithm and alternative indexing semantics.\n","base.strided.dapxsumkbn2":"\nbase.strided.dapxsumkbn2( N:integer, alpha:number, x:Float64Array, \n  strideX:integer )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using a second-order iterative\n    Kahan–Babuška algorithm.\n","base.strided.dapxsumkbn2.ndarray":"\nbase.strided.dapxsumkbn2.ndarray( N:integer, alpha:number, x:Float64Array, \n  strideX:integer, offsetX:integer )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using a second-order iterative\n    Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.dapxsumors":"\nbase.strided.dapxsumors( N:integer, alpha:number, x:Float64Array, \n  strideX:integer )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using ordinary recursive summation.\n","base.strided.dapxsumors.ndarray":"\nbase.strided.dapxsumors.ndarray( N:integer, alpha:number, x:Float64Array, \n  strideX:integer, offsetX:integer )\n    Adds a scalar constant to each double-precision floating-point strided\n    array element and computes the sum using ordinary recursive summation\n    and alternative indexing semantics.\n","base.strided.dapxsumpw":"\nbase.strided.dapxsumpw( N:integer, alpha:number, x:Float64Array, \n  strideX:integer )\n    Adds a scalar constant to each double-precision floating-point strided array\n    element and computes the sum using pairwise summation.\n","base.strided.dapxsumpw.ndarray":"\nbase.strided.dapxsumpw.ndarray( N:integer, alpha:number, x:Float64Array, \n  strideX:integer, offsetX:integer )\n    Adds a constant to each double-precision floating-point strided array\n    element and computes the sum using pairwise summation and alternative\n    indexing semantics.\n","base.strided.dasum":"\nbase.strided.dasum( N:integer, x:Float64Array, stride:integer )\n    Computes the sum of the absolute values.\n","base.strided.dasum.ndarray":"\nbase.strided.dasum.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the sum of absolute values using alternative indexing semantics.\n","base.strided.dasumpw":"\nbase.strided.dasumpw( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements using pairwise summation.\n","base.strided.dasumpw.ndarray":"\nbase.strided.dasumpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements using pairwise summation and alternative\n    indexing semantics.\n","base.strided.daxpy":"\nbase.strided.daxpy( N:integer, alpha:number, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n","base.strided.daxpy.ndarray":"\nbase.strided.daxpy.ndarray( N:integer, alpha:number, x:Float64Array, \n  strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n  offsetY:integer )\n    Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n    using alternative indexing semantics.\n","base.strided.dcbrt":"\nbase.strided.dcbrt( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n  strideY:integer )\n    Computes the cube root of each element in a double-precision floating-point\n    strided array `x` and assigns the results to elements in a double-precision\n    floating-point strided array `y`.\n","base.strided.dcbrt.ndarray":"\nbase.strided.dcbrt.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Computes the cube root of each element in a double-precision floating-point\n    strided array `x` and assigns the results to elements in a double-precision\n    floating-point strided array `y` using alternative indexing semantics.\n","base.strided.dceil":"\nbase.strided.dceil( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n  strideY:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward positive infinity and assigns the results to elements in a double-\n    precision floating-point strided array `y`.\n","base.strided.dceil.ndarray":"\nbase.strided.dceil.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward positive infinity and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.dcopy":"\nbase.strided.dcopy( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n  strideY:integer )\n    Copies values from `x` into `y`.\n","base.strided.dcopy.ndarray":"\nbase.strided.dcopy.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Copies values from `x` into `y` using alternative indexing semantics.\n","base.strided.dcumax":"\nbase.strided.dcumax( N:integer, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Computes the cumulative maximum of double-precision floating-point strided\n    array elements.\n","base.strided.dcumax.ndarray":"\nbase.strided.dcumax.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Computes the cumulative maximum of double-precision floating-point strided\n    array elements using alternative indexing semantics.\n","base.strided.dcumaxabs":"\nbase.strided.dcumaxabs( N:integer, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Computes the cumulative maximum absolute value of double-precision floating-\n    point strided array elements.\n","base.strided.dcumaxabs.ndarray":"\nbase.strided.dcumaxabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Computes the cumulative maximum absolute value of double-precision floating-\n    point strided array elements using alternative indexing semantics.\n","base.strided.dcumin":"\nbase.strided.dcumin( N:integer, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Computes the cumulative minimum of double-precision floating-point strided\n    array elements.\n","base.strided.dcumin.ndarray":"\nbase.strided.dcumin.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Computes the cumulative minimum of double-precision floating-point strided\n    array elements using alternative indexing semantics.\n","base.strided.dcuminabs":"\nbase.strided.dcuminabs( N:integer, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Computes the cumulative minimum absolute value of double-precision floating-\n    point strided array elements.\n","base.strided.dcuminabs.ndarray":"\nbase.strided.dcuminabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Computes the cumulative minimum absolute value of double-precision floating-\n    point strided array elements using alternative indexing semantics.\n","base.strided.dcusum":"\nbase.strided.dcusum( N:integer, sum:number, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements.\n","base.strided.dcusum.ndarray":"\nbase.strided.dcusum.ndarray( N:integer, sum:number, x:Float64Array, \n  strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using alternative indexing semantics.\n","base.strided.dcusumkbn":"\nbase.strided.dcusumkbn( N:integer, sum:number, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using an improved Kahan–Babuška algorithm.\n","base.strided.dcusumkbn.ndarray":"\nbase.strided.dcusumkbn.ndarray( N:integer, sum:number, x:Float64Array, \n  strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n","base.strided.dcusumkbn2":"\nbase.strided.dcusumkbn2( N:integer, sum:number, x:Float64Array, \n  strideX:integer, y:Float64Array, strideY:integer )\n    Computes the cumulative sum of double-precision floating-point strided\n    array elements using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.dcusumkbn2.ndarray":"\nbase.strided.dcusumkbn2.ndarray( N:integer, sum:number, x:Float64Array, \n  strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of double-precision floating-point strided\n    array elements using a second-order iterative Kahan–Babuška algorithm and\n    alternative indexing semantics.\n","base.strided.dcusumors":"\nbase.strided.dcusumors( N:integer, sum:number, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using ordinary recursive summation.\n","base.strided.dcusumors.ndarray":"\nbase.strided.dcusumors.ndarray( N:integer, sum:number, x:Float64Array, \n  strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using ordinary recursive summation and alternative indexing\n    semantics.\n","base.strided.dcusumpw":"\nbase.strided.dcusumpw( N:integer, sum:number, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using pairwise summation.\n","base.strided.dcusumpw.ndarray":"\nbase.strided.dcusumpw.ndarray( N:integer, sum:number, x:Float64Array, \n  strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of double-precision floating-point strided array\n    elements using pairwise summation and alternative indexing semantics.\n","base.strided.ddeg2rad":"\nbase.strided.ddeg2rad( N:integer, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Converts each element in a double-precision floating-point strided array `x`\n    from degrees to radians and assigns the results to elements in a double-\n    precision floating-point strided array `y`.\n","base.strided.ddeg2rad.ndarray":"\nbase.strided.ddeg2rad.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Converts each element in a double-precision floating-point strided array `x`\n    from degrees to radians and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.ddot":"\nbase.strided.ddot( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n  strideY:integer )\n    Computes the dot product of two double-precision floating-point vectors.\n","base.strided.ddot.ndarray":"\nbase.strided.ddot.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Computes the dot product of two double-precision floating-point vectors\n    using alternative indexing semantics.\n","base.strided.dfill":"\nbase.strided.dfill( N:integer, alpha:number, x:Float64Array, strideX:integer )\n    Fills a double-precision floating-point strided array with a specified\n    scalar value.\n","base.strided.dfill.ndarray":"\nbase.strided.dfill.ndarray( N:integer, alpha:number, x:Float64Array, \n  strideX:integer, offsetX:integer )\n    Fills a double-precision floating-point strided array with a specified\n    scalar value using alternative indexing semantics.\n","base.strided.dfloor":"\nbase.strided.dfloor( N:integer, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward negative infinity and assigns the results to elements in a double-\n    precision floating-point strided array `y`.\n","base.strided.dfloor.ndarray":"\nbase.strided.dfloor.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward negative infinity and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.dinv":"\nbase.strided.dinv( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n  strideY:integer )\n    Computes the multiplicative inverse for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y`.\n","base.strided.dinv.ndarray":"\nbase.strided.dinv.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Computes the multiplicative inverse for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.dmap":"\nbase.strided.dmap( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n  strideY:integer, fcn:Function )\n    Applies a unary function to a double-precision floating-point strided input\n    array and assigns results to a double-precision floating-point strided\n    output array.\n","base.strided.dmap.ndarray":"\nbase.strided.dmap.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer, \n  fcn:Function )\n    Applies a unary function to a double-precision floating-point strided input\n    array and assigns results to a double-precision floating-point strided\n    output array using alternative indexing semantics.\n","base.strided.dmap2":"\nbase.strided.dmap2( N:integer, x:Float64Array, sx:integer, y:Float64Array, \n  sy:integer, z:Float64Array, sz:integer, fcn:Function )\n    Applies a binary function to double-precision floating-point strided input\n    arrays and assigns results to a double-precision floating-point strided\n    output array.\n","base.strided.dmap2.ndarray":"\nbase.strided.dmap2.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, \n  y:Float64Array, sy:integer, oy:integer, z:Float64Array, sz:integer, \n  oz:integer, fcn:Function )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array using alternative indexing semantics.\n","base.strided.dmax":"\nbase.strided.dmax( N:integer, x:Float64Array, strideX:integer )\n    Computes the maximum value of a double-precision floating-point strided\n    array.\n","base.strided.dmax.ndarray":"\nbase.strided.dmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum value of a double-precision floating-point strided\n    array using alternative indexing semantics.\n","base.strided.dmaxabs":"\nbase.strided.dmaxabs( N:integer, x:Float64Array, strideX:integer )\n    Computes the maximum absolute value of a double-precision floating-point\n    strided array.\n","base.strided.dmaxabs.ndarray":"\nbase.strided.dmaxabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum absolute value of a double-precision floating-point\n    strided array using alternative indexing semantics.\n","base.strided.dmaxabssorted":"\nbase.strided.dmaxabssorted( N:integer, x:Float64Array, strideX:integer )\n    Computes the maximum absolute value of a sorted double-precision floating-\n    point strided array.\n","base.strided.dmaxabssorted.ndarray":"\nbase.strided.dmaxabssorted.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum absolute value of a sorted double-precision floating-\n    point strided array using alternative indexing semantics.\n","base.strided.dmaxsorted":"\nbase.strided.dmaxsorted( N:integer, x:Float64Array, strideX:integer )\n    Computes the maximum value of a sorted double-precision floating-point\n    strided array.\n","base.strided.dmaxsorted.ndarray":"\nbase.strided.dmaxsorted.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n","base.strided.dmean":"\nbase.strided.dmean( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array.\n","base.strided.dmean.ndarray":"\nbase.strided.dmean.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using alternative indexing semantics.\n","base.strided.dmeankbn":"\nbase.strided.dmeankbn( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm.\n","base.strided.dmeankbn.ndarray":"\nbase.strided.dmeankbn.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n","base.strided.dmeankbn2":"\nbase.strided.dmeankbn2( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.dmeankbn2.ndarray":"\nbase.strided.dmeankbn2.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n","base.strided.dmeanli":"\nbase.strided.dmeanli( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm.\n","base.strided.dmeanli.ndarray":"\nbase.strided.dmeanli.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n","base.strided.dmeanlipw":"\nbase.strided.dmeanlipw( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm with pairwise summation.\n","base.strided.dmeanlipw.ndarray":"\nbase.strided.dmeanlipw.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm with pairwise summation and\n    alternative indexing semantics.\n","base.strided.dmeanors":"\nbase.strided.dmeanors( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using ordinary recursive summation.\n","base.strided.dmeanors.ndarray":"\nbase.strided.dmeanors.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using ordinary recursive summation and alternative indexing semantics.\n","base.strided.dmeanpn":"\nbase.strided.dmeanpn( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a two-pass error correction algorithm.\n","base.strided.dmeanpn.ndarray":"\nbase.strided.dmeanpn.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using a two-pass error correction algorithm and alternative indexing\n    semantics.\n","base.strided.dmeanpw":"\nbase.strided.dmeanpw( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using pairwise summation.\n","base.strided.dmeanpw.ndarray":"\nbase.strided.dmeanpw.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using pairwise summation and alternative indexing semantics.\n","base.strided.dmeanstdev":"\nbase.strided.dmeanstdev( N:integer, c:number, x:Float64Array, strideX:integer, \n  out:Float64Array, strideOut:integer )\n    Computes the mean and standard deviation of a double-precision floating-\n    point strided array.\n","base.strided.dmeanstdev.ndarray":"\nbase.strided.dmeanstdev.ndarray( N:integer, c:number, x:Float64Array, \n  strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n  offsetOut:integer )\n    Computes the mean and standard deviation of a double-precision floating-\n    point strided array using alternative indexing semantics.\n","base.strided.dmeanstdevpn":"\nbase.strided.dmeanstdevpn( N:integer, c:number, x:Float64Array, \n  strideX:integer, out:Float64Array, strideOut:integer )\n    Computes the mean and standard deviation of a double-precision floating-\n    point strided array using a two-pass algorithm.\n","base.strided.dmeanstdevpn.ndarray":"\nbase.strided.dmeanstdevpn.ndarray( N:integer, c:number, x:Float64Array, \n  strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n  offsetOut:integer )\n    Computes the mean and standard deviation of a double-precision floating-\n    point strided array using a two-pass algorithm and alternative indexing\n    semantics.\n","base.strided.dmeanvar":"\nbase.strided.dmeanvar( N:integer, c:number, x:Float64Array, strideX:integer, \n  out:Float64Array, strideOut:integer )\n    Computes the mean and variance of a double-precision floating-point strided\n    array.\n","base.strided.dmeanvar.ndarray":"\nbase.strided.dmeanvar.ndarray( N:integer, c:number, x:Float64Array, \n  strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n  offsetOut:integer )\n    Computes the mean and variance of a double-precision floating-point strided\n    array using alternative indexing semantics.\n","base.strided.dmeanvarpn":"\nbase.strided.dmeanvarpn( N:integer, c:number, x:Float64Array, strideX:integer, \n  out:Float64Array, strideOut:integer )\n    Computes the mean and variance of a double-precision floating-point strided\n    array using a two-pass algorithm.\n","base.strided.dmeanvarpn.ndarray":"\nbase.strided.dmeanvarpn.ndarray( N:integer, c:number, x:Float64Array, \n  strideX:integer, offsetX:integer, out:Float64Array, strideOut:integer, \n  offsetOut:integer )\n    Computes the mean and variance of a double-precision floating-point strided\n    array using a two-pass algorithm and alternative indexing semantics.\n","base.strided.dmeanwd":"\nbase.strided.dmeanwd( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using Welford's algorithm.\n","base.strided.dmeanwd.ndarray":"\nbase.strided.dmeanwd.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n","base.strided.dmediansorted":"\nbase.strided.dmediansorted( N:integer, x:Float64Array, strideX:integer )\n    Computes the median value of a sorted double-precision floating-point\n    strided array.\n","base.strided.dmediansorted.ndarray":"\nbase.strided.dmediansorted.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the median value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n","base.strided.dmidrange":"\nbase.strided.dmidrange( N:integer, x:Float64Array, strideX:integer )\n    Computes the mid-range of a double-precision floating-point strided array.\n","base.strided.dmidrange.ndarray":"\nbase.strided.dmidrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the mid-range of a double-precision floating-point strided array\n    using alternative indexing semantics.\n","base.strided.dmin":"\nbase.strided.dmin( N:integer, x:Float64Array, strideX:integer )\n    Computes the minimum value of a double-precision floating-point strided\n    array.\n","base.strided.dmin.ndarray":"\nbase.strided.dmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the minimum value of a double-precision floating-point strided\n    array using alternative indexing semantics.\n","base.strided.dminabs":"\nbase.strided.dminabs( N:integer, x:Float64Array, strideX:integer )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array.\n","base.strided.dminabs.ndarray":"\nbase.strided.dminabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array using alternative indexing semantics.\n","base.strided.dminsorted":"\nbase.strided.dminsorted( N:integer, x:Float64Array, strideX:integer )\n    Computes the minimum value of a sorted double-precision floating-point\n    strided array.\n","base.strided.dminsorted.ndarray":"\nbase.strided.dminsorted.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the minimum value of a sorted double-precision floating-point\n    strided array using alternative indexing semantics.\n","base.strided.dmskabs":"\nbase.strided.dmskabs( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Computes the absolute value for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskabs.ndarray":"\nbase.strided.dmskabs.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n  sy:integer, oy:integer )\n    Computes the absolute value for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n","base.strided.dmskabs2":"\nbase.strided.dmskabs2( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Computes the squared absolute value for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point\n    strided array `y`.\n","base.strided.dmskabs2.ndarray":"\nbase.strided.dmskabs2.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n  sy:integer, oy:integer )\n    Computes the squared absolute value for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point\n    strided array `y` using alternative indexing semantics.\n","base.strided.dmskcbrt":"\nbase.strided.dmskcbrt( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Computes the cube root for each element in a double-precision floating-point\n    strided array `x` according to a strided mask array and assigns the results\n    to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskcbrt.ndarray":"\nbase.strided.dmskcbrt.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n  sy:integer, oy:integer )\n    Computes the cube root for each element in a double-precision floating-point\n    strided array `x` according to a strided mask array and assigns the results\n    to elements in a double-precision floating-point strided array `y` using\n    alternative indexing semantics.\n","base.strided.dmskceil":"\nbase.strided.dmskceil( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward positive infinity according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskceil.ndarray":"\nbase.strided.dmskceil.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n  sy:integer, oy:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward positive infinity according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n","base.strided.dmskdeg2rad":"\nbase.strided.dmskdeg2rad( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Converts each element in a double-precision floating-point strided array `x`\n    from degrees to radians according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskdeg2rad.ndarray":"\nbase.strided.dmskdeg2rad.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n  sy:integer, oy:integer )\n    Converts each element in a double-precision floating-point strided array `x`\n    from degrees to radians according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n","base.strided.dmskfloor":"\nbase.strided.dmskfloor( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward negative infinity according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskfloor.ndarray":"\nbase.strided.dmskfloor.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n  sy:integer, oy:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward negative infinity according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n","base.strided.dmskinv":"\nbase.strided.dmskinv( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Computes the multiplicative inverse for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y`.\n","base.strided.dmskinv.ndarray":"\nbase.strided.dmskinv.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n  sy:integer, oy:integer )\n    Computes the multiplicative inverse for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y` using alternative indexing semantics.\n","base.strided.dmskmap":"\nbase.strided.dmskmap( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer, fcn:Function )\n    Applies a unary function to a double-precision floating-point strided input\n    array according to a strided mask array and assigns results to a double-\n    precision floating-point strided output array.\n","base.strided.dmskmap.ndarray":"\nbase.strided.dmskmap.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Uint8Array, sm:integer, om:integer, y:Float64Array, sy:integer, \n  oy:integer, fcn:Function )\n    Applies a unary function to a double-precision floating-point strided input\n    array according to a strided mask array and assigns results to a double-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n","base.strided.dmskmap2":"\nbase.strided.dmskmap2( N:integer, x:Float64Array, sx:integer, y:Float64Array, \n  sy:integer, m:Uint8Array, sm:integer, z:Float64Array, sz:integer, \n  fcn:Function )\n    Applies a binary function to double-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a double-\n    precision floating-point strided output array.\n","base.strided.dmskmap2.ndarray":"\nbase.strided.dmskmap2.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, y:Float64Array, sy:integer, oy:integer, m:Uint8Array, sm:integer, \n  om:integer, z:Float64Array, sz:integer, oz:integer, fcn:Function )\n    Applies a binary function to double-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a double-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n","base.strided.dmskmax":"\nbase.strided.dmskmax( N:integer, x:Float64Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask.\n","base.strided.dmskmax.ndarray":"\nbase.strided.dmskmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n","base.strided.dmskmin":"\nbase.strided.dmskmin( N:integer, x:Float64Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask.\n","base.strided.dmskmin.ndarray":"\nbase.strided.dmskmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n","base.strided.dmskramp":"\nbase.strided.dmskramp( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Evaluates the ramp function for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`.\n","base.strided.dmskramp.ndarray":"\nbase.strided.dmskramp.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n  sy:integer, oy:integer )\n    Evaluates the ramp function for each element in a double-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a double-precision floating-point strided array `y`\n    using alternative indexing semantics.\n","base.strided.dmskrange":"\nbase.strided.dmskrange( N:integer, x:Float64Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the range of a double-precision floating-point strided array\n    according to a mask.\n","base.strided.dmskrange.ndarray":"\nbase.strided.dmskrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the range of a double-precision floating-point strided array\n    according to a mask and using alternative indexing semantics.\n","base.strided.dmskrsqrt":"\nbase.strided.dmskrsqrt( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Computes the reciprocal square root for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y`.\n","base.strided.dmskrsqrt.ndarray":"\nbase.strided.dmskrsqrt.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n  sy:integer, oy:integer )\n    Computes the reciprocal square root for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y` using alternative indexing semantics.\n","base.strided.dmsksqrt":"\nbase.strided.dmsksqrt( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Computes the principal square root for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y`.\n","base.strided.dmsksqrt.ndarray":"\nbase.strided.dmsksqrt.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n  sy:integer, oy:integer )\n    Computes the principal square root for each element in a double-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a double-precision floating-point strided\n    array `y` using alternative indexing semantics.\n","base.strided.dmsktrunc":"\nbase.strided.dmsktrunc( N:integer, x:Float64Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float64Array, sy:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward zero according to a strided mask array and assigns the results to\n    elements in a double-precision floating-point strided array `y`.\n","base.strided.dmsktrunc.ndarray":"\nbase.strided.dmsktrunc.ndarray( N:integer, x:Float64Array, sx:integer, \n  ox:integer, m:Float64Array, sm:integer, om:integer, y:Float64Array, \n  sy:integer, oy:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward zero according to a strided mask array and assigns the results to\n    elements in a double-precision floating-point strided array `y` using\n    alternative indexing semantics.\n","base.strided.dnanasum":"\nbase.strided.dnanasum( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements, ignoring `NaN` values.\n","base.strided.dnanasum.ndarray":"\nbase.strided.dnanasum.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements, ignoring `NaN` values and using alternative\n    indexing semantics.\n","base.strided.dnanasumors":"\nbase.strided.dnanasumors( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements, ignoring `NaN` values and using ordinary\n    recursive summation.\n","base.strided.dnanasumors.ndarray":"\nbase.strided.dnanasumors.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of absolute values (L1 norm) of double-precision floating-\n    point strided array elements, ignoring `NaN` values and using ordinary\n    recursive summation alternative indexing semantics.\n","base.strided.dnanmax":"\nbase.strided.dnanmax( N:integer, x:Float64Array, strideX:integer )\n    Computes the maximum value of a double-precision floating-point strided\n    array, ignoring `NaN` values.\n","base.strided.dnanmax.ndarray":"\nbase.strided.dnanmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum value of a double-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanmaxabs":"\nbase.strided.dnanmaxabs( N:integer, x:Float64Array, strideX:integer )\n    Computes the maximum absolute value of a double-precision floating-point\n    strided array, ignoring `NaN` values.\n","base.strided.dnanmaxabs.ndarray":"\nbase.strided.dnanmaxabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum absolute value of a double-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n","base.strided.dnanmean":"\nbase.strided.dnanmean( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values.\n","base.strided.dnanmean.ndarray":"\nbase.strided.dnanmean.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanmeanors":"\nbase.strided.dnanmeanors( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.dnanmeanors.ndarray":"\nbase.strided.dnanmeanors.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation and\n    alternative indexing semantics.\n","base.strided.dnanmeanpn":"\nbase.strided.dnanmeanpn( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction\n    algorithm.\n","base.strided.dnanmeanpn.ndarray":"\nbase.strided.dnanmeanpn.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction algorithm\n    and alternative indexing semantics.\n","base.strided.dnanmeanpw":"\nbase.strided.dnanmeanpw( N:integer, x:Float64Array, stride:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using pairwise summation.\n","base.strided.dnanmeanpw.ndarray":"\nbase.strided.dnanmeanpw.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using pairwise summation and alternative\n    indexing semantics.\n","base.strided.dnanmeanwd":"\nbase.strided.dnanmeanwd( N:integer, x:Float64Array, strideX:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, using Welford's algorithm and ignoring `NaN` values.\n","base.strided.dnanmeanwd.ndarray":"\nbase.strided.dnanmeanwd.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the arithmetic mean of a double-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n","base.strided.dnanmin":"\nbase.strided.dnanmin( N:integer, x:Float64Array, strideX:integer )\n    Computes the minimum value of a double-precision floating-point strided\n    array, ignoring `NaN` values.\n","base.strided.dnanmin.ndarray":"\nbase.strided.dnanmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the minimum value of a double-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanminabs":"\nbase.strided.dnanminabs( N:integer, x:Float64Array, strideX:integer )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array, ignoring `NaN` values.\n","base.strided.dnanminabs.ndarray":"\nbase.strided.dnanminabs.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the minimum absolute value of a double-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n","base.strided.dnanmskmax":"\nbase.strided.dnanmskmax( N:integer, x:Float64Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask, ignoring `NaN` values.\n","base.strided.dnanmskmax.ndarray":"\nbase.strided.dnanmskmax.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the maximum value of a double-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n","base.strided.dnanmskmin":"\nbase.strided.dnanmskmin( N:integer, x:Float64Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask, ignoring `NaN` values.\n","base.strided.dnanmskmin.ndarray":"\nbase.strided.dnanmskmin.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the minimum value of a double-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n","base.strided.dnanmskrange":"\nbase.strided.dnanmskrange( N:integer, x:Float64Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the range of a double-precision floating-point strided array\n    according to a mask, ignoring `NaN` values.\n","base.strided.dnanmskrange.ndarray":"\nbase.strided.dnanmskrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the range of a double-precision floating-point strided array\n    according to a mask, ignoring `NaN` values and using alternative indexing\n    semantics.\n","base.strided.dnannsum":"\nbase.strided.dnannsum( N:integer, x:Float64Array, strideX:integer, \n  out:Float64Array, strideOut:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values.\n","base.strided.dnannsum.ndarray":"\nbase.strided.dnannsum.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnannsumkbn":"\nbase.strided.dnannsumkbn( N:integer, x:Float64Array, strideX:integer, \n  out:Float64Array, strideOut:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n","base.strided.dnannsumkbn.ndarray":"\nbase.strided.dnannsumkbn.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n","base.strided.dnannsumkbn2":"\nbase.strided.dnannsumkbn2( N:integer, x:Float64Array, strideX:integer, \n  out:Float64Array, strideOut:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm.\n","base.strided.dnannsumkbn2.ndarray":"\nbase.strided.dnannsumkbn2.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n","base.strided.dnannsumors":"\nbase.strided.dnannsumors( N:integer, x:Float64Array, strideX:integer, \n  out:Float64Array, strideOut:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.dnannsumors.ndarray":"\nbase.strided.dnannsumors.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation and alternative\n    indexing semantics.\n","base.strided.dnannsumpw":"\nbase.strided.dnannsumpw( N:integer, x:Float64Array, strideX:integer, \n  out:Float64Array, strideOut:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation.\n","base.strided.dnannsumpw.ndarray":"\nbase.strided.dnannsumpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation and alternative indexing\n    semantics.\n","base.strided.dnanrange":"\nbase.strided.dnanrange( N:integer, x:Float64Array, strideX:integer )\n    Computes the range of a double-precision floating-point strided array,\n    ignoring `NaN` values.\n","base.strided.dnanrange.ndarray":"\nbase.strided.dnanrange.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the range of a double-precision floating-point strided array,\n    ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanstdev":"\nbase.strided.dnanstdev( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values.\n","base.strided.dnanstdev.ndarray":"\nbase.strided.dnanstdev.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanstdevch":"\nbase.strided.dnanstdevch( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.dnanstdevch.ndarray":"\nbase.strided.dnanstdevch.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n","base.strided.dnanstdevpn":"\nbase.strided.dnanstdevpn( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.dnanstdevpn.ndarray":"\nbase.strided.dnanstdevpn.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n","base.strided.dnanstdevtk":"\nbase.strided.dnanstdevtk( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.dnanstdevtk.ndarray":"\nbase.strided.dnanstdevtk.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n","base.strided.dnanstdevwd":"\nbase.strided.dnanstdevwd( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using Welford's algorithm.\n","base.strided.dnanstdevwd.ndarray":"\nbase.strided.dnanstdevwd.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n","base.strided.dnanstdevyc":"\nbase.strided.dnanstdevyc( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass algorithm proposed by\n    Youngs and Cramer.\n","base.strided.dnanstdevyc.ndarray":"\nbase.strided.dnanstdevyc.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass algorithm proposed by\n    Youngs and Cramer and alternative indexing semantics.\n","base.strided.dnansum":"\nbase.strided.dnansum( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values.\n","base.strided.dnansum.ndarray":"\nbase.strided.dnansum.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnansumkbn":"\nbase.strided.dnansumkbn( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n","base.strided.dnansumkbn.ndarray":"\nbase.strided.dnansumkbn.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n","base.strided.dnansumkbn2":"\nbase.strided.dnansumkbn2( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm.\n","base.strided.dnansumkbn2.ndarray":"\nbase.strided.dnansumkbn2.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n","base.strided.dnansumors":"\nbase.strided.dnansumors( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.dnansumors.ndarray":"\nbase.strided.dnansumors.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation and alternative\n    indexing semantics.\n","base.strided.dnansumpw":"\nbase.strided.dnansumpw( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation.\n","base.strided.dnansumpw.ndarray":"\nbase.strided.dnansumpw.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of double-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation and alternative indexing\n    semantics.\n","base.strided.dnanvariance":"\nbase.strided.dnanvariance( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values.\n","base.strided.dnanvariance.ndarray":"\nbase.strided.dnanvariance.ndarray( N:integer, correction:number, \n  x:Float64Array, stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.dnanvariancech":"\nbase.strided.dnanvariancech( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.dnanvariancech.ndarray":"\nbase.strided.dnanvariancech.ndarray( N:integer, correction:number, \n  x:Float64Array, stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n","base.strided.dnanvariancepn":"\nbase.strided.dnanvariancepn( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.dnanvariancepn.ndarray":"\nbase.strided.dnanvariancepn.ndarray( N:integer, correction:number, \n  x:Float64Array, stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n","base.strided.dnanvariancetk":"\nbase.strided.dnanvariancetk( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.dnanvariancetk.ndarray":"\nbase.strided.dnanvariancetk.ndarray( N:integer, correction:number, \n  x:Float64Array, stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n","base.strided.dnanvariancewd":"\nbase.strided.dnanvariancewd( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using Welford's algorithm.\n","base.strided.dnanvariancewd.ndarray":"\nbase.strided.dnanvariancewd.ndarray( N:integer, correction:number, \n  x:Float64Array, stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using Welford's algorithm and alternative indexing\n    semantics.\n","base.strided.dnanvarianceyc":"\nbase.strided.dnanvarianceyc( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n    Cramer.\n","base.strided.dnanvarianceyc.ndarray":"\nbase.strided.dnanvarianceyc.ndarray( N:integer, correction:number, \n  x:Float64Array, stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n    Cramer and alternative indexing semantics.\n","base.strided.dnrm2":"\nbase.strided.dnrm2( N:integer, x:Float64Array, stride:integer )\n    Computes the L2-norm of a double-precision floating-point vector.\n","base.strided.dnrm2.ndarray":"\nbase.strided.dnrm2.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the L2-norm of a double-precision floating-point vector using\n    alternative indexing semantics.\n","base.strided.dramp":"\nbase.strided.dramp( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n  strideY:integer )\n    Evaluates the ramp function for each element in a double-precision floating-\n    point strided array `x` and assigns the results to elements in a double-\n    precision floating-point strided array `y`.\n","base.strided.dramp.ndarray":"\nbase.strided.dramp.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Evaluates the ramp function for each element in a double-precision floating-\n    point strided array `x` and assigns the results to elements in a double-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.drange":"\nbase.strided.drange( N:integer, x:Float64Array, strideX:integer )\n    Computes the range of a double-precision floating-point strided array.\n","base.strided.drange.ndarray":"\nbase.strided.drange.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the range of a double-precision floating-point strided array using\n    alternative indexing semantics.\n","base.strided.drev":"\nbase.strided.drev( N:integer, x:Float64Array, strideX:integer )\n    Reverses a double-precision floating-point strided array in-place.\n","base.strided.drev.ndarray":"\nbase.strided.drev.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Reverses a double-precision floating-point strided array in-place using\n    alternative indexing semantics.\n","base.strided.drsqrt":"\nbase.strided.drsqrt( N:integer, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Computes the reciprocal square root for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y`.\n","base.strided.drsqrt.ndarray":"\nbase.strided.drsqrt.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Computes the reciprocal square root for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.dsapxsum":"\nbase.strided.dsapxsum( N:integer, alpha:number, x:Float32Array, \n  strideX:integer )\n    Adds a scalar constant to each single-precision floating-point strided array\n    element, and computes the sum using extended accumulation and returning\n    an extended precision result.\n","base.strided.dsapxsum.ndarray":"\nbase.strided.dsapxsum.ndarray( N:integer, alpha:number, x:Float32Array, \n  strideX:integer, offsetX:integer )\n    Adds a scalar constant to each single-precision floating-point strided array\n    element, and computes the sum using pairwise summation with extended\n    accumulation and alternative indexing semantics and returning an extended\n    precision result.\n","base.strided.dsapxsumpw":"\nbase.strided.dsapxsumpw( N:integer, alpha:number, x:Float32Array, \n  strideX:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element, and computes the sum using pairwise summation with extended\n    accumulation and returning an extended precision result.\n","base.strided.dsapxsumpw.ndarray":"\nbase.strided.dsapxsumpw.ndarray( N:integer, alpha:number, x:Float32Array, \n  strideX:integer, offsetX:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element, and computes the sum using pairwise summation with extended\n    accumulation and alternative indexing semantics and returning an extended\n    precision result.\n","base.strided.dscal":"\nbase.strided.dscal( N:integer, alpha:number, x:Float64Array, stride:integer )\n    Multiplies a double-precision floating-point vector `x` by a constant\n    `alpha`.\n","base.strided.dscal.ndarray":"\nbase.strided.dscal.ndarray( N:integer, alpha:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Multiplies a double-precision floating-point vector `x` by a constant\n    `alpha` using alternative indexing semantics.\n","base.strided.dsdot":"\nbase.strided.dsdot( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer )\n    Computes the dot product of two single-precision floating-point vectors with\n    extended accumulation and result.\n","base.strided.dsdot.ndarray":"\nbase.strided.dsdot.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the dot product of two single-precision floating-point vectors\n    using alternative indexing semantics and with extended accumulation and\n    result.\n","base.strided.dsem":"\nbase.strided.dsem( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array.\n","base.strided.dsem.ndarray":"\nbase.strided.dsem.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using alternative indexing semantics.\n","base.strided.dsemch":"\nbase.strided.dsemch( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass trial mean algorithm.\n","base.strided.dsemch.ndarray":"\nbase.strided.dsemch.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass trial mean algorithm and alternative\n    indexing semantics.\n","base.strided.dsempn":"\nbase.strided.dsempn( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a two-pass algorithm.\n","base.strided.dsempn.ndarray":"\nbase.strided.dsempn.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a two-pass algorithm and alternative indexing\n    semantics.\n","base.strided.dsemtk":"\nbase.strided.dsemtk( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass textbook algorithm.\n","base.strided.dsemtk.ndarray":"\nbase.strided.dsemtk.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass textbook algorithm and alternative\n    indexing semantics.\n","base.strided.dsemwd":"\nbase.strided.dsemwd( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using Welford's algorithm.\n","base.strided.dsemwd.ndarray":"\nbase.strided.dsemwd.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using Welford's algorithm and alternative indexing\n    semantics.\n","base.strided.dsemyc":"\nbase.strided.dsemyc( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass algorithm proposed by Youngs and\n    Cramer.\n","base.strided.dsemyc.ndarray":"\nbase.strided.dsemyc.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard error of the mean for a double-precision floating-\n    point strided array using a one-pass algorithm proposed by Youngs and Cramer\n    and alternative indexing semantics.\n","base.strided.dsmean":"\nbase.strided.dsmean( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using extended accumulation and returning an extended precision\n    result.\n","base.strided.dsmean.ndarray":"\nbase.strided.dsmean.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using extended accumulation and alternative indexing semantics and\n    returning an extended precision result.\n","base.strided.dsmeanors":"\nbase.strided.dsmeanors( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation with extended accumulation and\n    returning an extended precision result.\n","base.strided.dsmeanors.ndarray":"\nbase.strided.dsmeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation with extended accumulation and\n    alternative indexing semantics and returning an extended precision result.\n","base.strided.dsmeanpn":"\nbase.strided.dsmeanpn( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a two-pass error correction algorithm with extended accumulation\n    and returning an extended precision result.\n","base.strided.dsmeanpn.ndarray":"\nbase.strided.dsmeanpn.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a two-pass error correction algorithm with extended accumulation\n    and alternative indexing semantics and returning an extended precision\n    result.\n","base.strided.dsmeanpw":"\nbase.strided.dsmeanpw( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using pairwise summation with extended accumulation and returning an\n    extended precision result.\n","base.strided.dsmeanpw.ndarray":"\nbase.strided.dsmeanpw.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using pairwise summation with extended accumulation and alternative\n    indexing semantics and returning an extended precision result.\n","base.strided.dsmeanwd":"\nbase.strided.dsmeanwd( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using Welford's algorithm with extended accumulation and returning an\n    extended precision result.\n","base.strided.dsmeanwd.ndarray":"\nbase.strided.dsmeanwd.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using Welford's algorithm with extended accumulation and alternative\n    indexing semantics and returning an extended precision result.\n","base.strided.dsnanmean":"\nbase.strided.dsnanmean( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values, using extended accumulation, and returning an\n    extended precision result.\n","base.strided.dsnanmean.ndarray":"\nbase.strided.dsnanmean.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using extended accumulation and alternative\n    indexing semantics.\n","base.strided.dsnanmeanors":"\nbase.strided.dsnanmeanors( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values, using ordinary recursive summation with\n    extended accumulation, and returning an extended precision result.\n","base.strided.dsnanmeanors.ndarray":"\nbase.strided.dsnanmeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation with\n    extended accumulation and alternative indexing semantics.\n","base.strided.dsnanmeanpn":"\nbase.strided.dsnanmeanpn( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values, using a two-pass error correction algorithm\n    with extended accumulation, and returning an extended precision result.\n","base.strided.dsnanmeanpn.ndarray":"\nbase.strided.dsnanmeanpn.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction algorithm\n    with extended accumulation and alternative indexing semantics.\n","base.strided.dsnanmeanwd":"\nbase.strided.dsnanmeanwd( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values, using Welford's algorithm with extended\n    accumulation, and returning an extended precision result.\n","base.strided.dsnanmeanwd.ndarray":"\nbase.strided.dsnanmeanwd.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm with extended\n    accumulation and alternative indexing semantics.\n","base.strided.dsnannsumors":"\nbase.strided.dsnannsumors( N:integer, x:Float32Array, strideX:integer, \n  out:Float64Array, strideOut:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using ordinary recursive summation with extended\n    accumulation, and returning an extended precision result.\n","base.strided.dsnannsumors.ndarray":"\nbase.strided.dsnannsumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, out:Float64Array, strideOut:integer, offsetOut:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using ordinary recursive summation with extended\n    accumulation and alternative indexing semantics, and returning an extended\n    precision result.\n","base.strided.dsnansum":"\nbase.strided.dsnansum( N:integer, x:Float32Array, strideX:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using extended accumulation, and returning an\n    extended precision result.\n","base.strided.dsnansum.ndarray":"\nbase.strided.dsnansum.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using extended accumulation and alternative\n    indexing semantics, and returning an extended precision result.\n","base.strided.dsnansumors":"\nbase.strided.dsnansumors( N:integer, x:Float32Array, strideX:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using ordinary recursive summation with extended\n    accumulation, and returning an extended precision result.\n","base.strided.dsnansumors.ndarray":"\nbase.strided.dsnansumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation with extended\n    accumulation and alternative indexing semantics, and returning an extended\n    precision result.\n","base.strided.dsnansumpw":"\nbase.strided.dsnansumpw( N:integer, x:Float32Array, strideX:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using pairwise summation with extended accumulation,\n    and returning an extended precision result.\n","base.strided.dsnansumpw.ndarray":"\nbase.strided.dsnansumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values, using pairwise summation with extended accumulation\n    and alternative indexing semantics, and returning an extended precision\n    result.\n","base.strided.dsort2hp":"\nbase.strided.dsort2hp( N:integer, order:number, x:Float64Array, \n  strideX:integer, y:Float64Array, strideY:integer )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using heapsort.\n","base.strided.dsort2hp.ndarray":"\nbase.strided.dsort2hp.ndarray( N:integer, order:number, x:Float64Array, \n  strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n  offsetY:integer )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using heapsort and alternative\n    indexing semantics.\n","base.strided.dsort2ins":"\nbase.strided.dsort2ins( N:integer, order:number, x:Float64Array, \n  strideX:integer, y:Float64Array, strideY:integer )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using insertion sort.\n","base.strided.dsort2ins.ndarray":"\nbase.strided.dsort2ins.ndarray( N:integer, order:number, x:Float64Array, \n  strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n  offsetY:integer )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using insertion sort and\n    alternative indexing semantics.\n","base.strided.dsort2sh":"\nbase.strided.dsort2sh( N:integer, order:number, x:Float64Array, \n  strideX:integer, y:Float64Array, strideY:integer )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using Shellsort.\n","base.strided.dsort2sh.ndarray":"\nbase.strided.dsort2sh.ndarray( N:integer, order:number, x:Float64Array, \n  strideX:integer, offsetX:integer, y:Float64Array, strideY:integer, \n  offsetY:integer )\n    Simultaneously sorts two double-precision floating-point strided arrays\n    based on the sort order of the first array using Shellsort and alternative\n    indexing semantics.\n","base.strided.dsorthp":"\nbase.strided.dsorthp( N:integer, order:number, x:Float64Array, stride:integer )\n    Sorts a double-precision floating-point strided array using heapsort.\n","base.strided.dsorthp.ndarray":"\nbase.strided.dsorthp.ndarray( N:integer, order:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Sorts a double-precision floating-point strided array using heapsort and\n    alternative indexing semantics.\n","base.strided.dsortins":"\nbase.strided.dsortins( N:integer, order:number, x:Float64Array, stride:integer )\n    Sorts a double-precision floating-point strided array using insertion sort.\n","base.strided.dsortins.ndarray":"\nbase.strided.dsortins.ndarray( N:integer, order:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Sorts a double-precision floating-point strided array using insertion sort\n    and alternative indexing semantics.\n","base.strided.dsortsh":"\nbase.strided.dsortsh( N:integer, order:number, x:Float64Array, stride:integer )\n    Sorts a double-precision floating-point strided array using Shellsort.\n","base.strided.dsortsh.ndarray":"\nbase.strided.dsortsh.ndarray( N:integer, order:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Sorts a double-precision floating-point strided array using Shellsort and\n    alternative indexing semantics.\n","base.strided.dsqrt":"\nbase.strided.dsqrt( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n  strideY:integer )\n    Computes the principal square root for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y`.\n","base.strided.dsqrt.ndarray":"\nbase.strided.dsqrt.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Computes the principal square root for each element in a double-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    double-precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.dssum":"\nbase.strided.dssum( N:integer, x:Float32Array, strideX:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using extended accumulation and returning an extended precision result.\n","base.strided.dssum.ndarray":"\nbase.strided.dssum.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using extended accumulation and alternative indexing semantics and returning\n    an extended precision result.\n","base.strided.dssumors":"\nbase.strided.dssumors( N:integer, x:Float32Array, strideX:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using ordinary recursive summation with extended accumulation and returning\n    an extended precision result.\n","base.strided.dssumors.ndarray":"\nbase.strided.dssumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using ordinary recursive summation with extended accumulation and\n    alternative indexing semantics and returning an extended precision result.\n","base.strided.dssumpw":"\nbase.strided.dssumpw( N:integer, x:Float32Array, strideX:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation with extended accumulation and returning an\n    extended precision result.\n","base.strided.dssumpw.ndarray":"\nbase.strided.dssumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation with extended accumulation and alternative indexing\n    semantics and returning an extended precision result.\n","base.strided.dstdev":"\nbase.strided.dstdev( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array.\n","base.strided.dstdev.ndarray":"\nbase.strided.dstdev.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using alternative indexing semantics.\n","base.strided.dstdevch":"\nbase.strided.dstdevch( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm.\n","base.strided.dstdevch.ndarray":"\nbase.strided.dstdevch.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n","base.strided.dstdevpn":"\nbase.strided.dstdevpn( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a two-pass algorithm.\n","base.strided.dstdevpn.ndarray":"\nbase.strided.dstdevpn.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a two-pass algorithm and alternative indexing semantics.\n","base.strided.dstdevtk":"\nbase.strided.dstdevtk( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass textbook algorithm.\n","base.strided.dstdevtk.ndarray":"\nbase.strided.dstdevtk.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass textbook algorithm and alternative indexing\n    semantics.\n","base.strided.dstdevwd":"\nbase.strided.dstdevwd( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using Welford's algorithm.\n","base.strided.dstdevwd.ndarray":"\nbase.strided.dstdevwd.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n","base.strided.dstdevyc":"\nbase.strided.dstdevyc( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.dstdevyc.ndarray":"\nbase.strided.dstdevyc.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a double-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer and\n    alternative indexing semantics.\n","base.strided.dsum":"\nbase.strided.dsum( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of double-precision floating-point strided array elements.\n","base.strided.dsum.ndarray":"\nbase.strided.dsum.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using alternative indexing semantics.\n","base.strided.dsumkbn":"\nbase.strided.dsumkbn( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm.\n","base.strided.dsumkbn.ndarray":"\nbase.strided.dsumkbn.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n","base.strided.dsumkbn2":"\nbase.strided.dsumkbn2( N:integer, x:Float64Array, strideX:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.dsumkbn2.ndarray":"\nbase.strided.dsumkbn2.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n","base.strided.dsumors":"\nbase.strided.dsumors( N:integer, x:Float64Array, stride:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using ordinary recursive summation.\n","base.strided.dsumors.ndarray":"\nbase.strided.dsumors.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using ordinary recursive summation and alternative indexing semantics.\n","base.strided.dsumpw":"\nbase.strided.dsumpw( N:integer, x:Float64Array, stride:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using pairwise summation.\n","base.strided.dsumpw.ndarray":"\nbase.strided.dsumpw.ndarray( N:integer, x:Float64Array, stride:integer, \n  offset:integer )\n    Computes the sum of double-precision floating-point strided array elements\n    using pairwise summation and alternative indexing semantics.\n","base.strided.dsvariance":"\nbase.strided.dsvariance( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using extended accumulation and returning an extended precision result.\n","base.strided.dsvariance.ndarray":"\nbase.strided.dsvariance.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using extended accumulation and alternative indexing semantics and\n    returning an extended precision result.\n","base.strided.dsvariancepn":"\nbase.strided.dsvariancepn( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using a two-pass algorithm with extended accumulation and returning an\n    extended precision result.\n","base.strided.dsvariancepn.ndarray":"\nbase.strided.dsvariancepn.ndarray( N:integer, correction:number, \n  x:Float32Array, stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using a two-pass algorithm with extended accumulation and alternative\n    indexing semantics and returning an extended precision result.\n","base.strided.dswap":"\nbase.strided.dswap( N:integer, x:Float64Array, strideX:integer, y:Float64Array, \n  strideY:integer )\n    Interchanges two double-precision floating-point vectors.\n","base.strided.dswap.ndarray":"\nbase.strided.dswap.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Interchanges two double-precision floating-point vectors using alternative\n    indexing semantics.\n","base.strided.dtrunc":"\nbase.strided.dtrunc( N:integer, x:Float64Array, strideX:integer, \n  y:Float64Array, strideY:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward zero and assigns the results to elements in a double-precision\n    floating-point strided array `y`.\n","base.strided.dtrunc.ndarray":"\nbase.strided.dtrunc.ndarray( N:integer, x:Float64Array, strideX:integer, \n  offsetX:integer, y:Float64Array, strideY:integer, offsetY:integer )\n    Rounds each element in a double-precision floating-point strided array `x`\n    toward zero and assigns the results to elements in a double-precision\n    floating-point strided array `y` using alternative indexing semantics.\n","base.strided.dtypeEnum2Str":"\nbase.strided.dtypeEnum2Str( dtype:integer )\n    Returns the data type string associated with a strided array data type\n    enumeration constant.\n","base.strided.dtypeResolveEnum":"\nbase.strided.dtypeResolveEnum( dtype:any )\n    Returns the enumeration constant associated with a supported strided array\n    data type value.\n","base.strided.dtypeResolveStr":"\nbase.strided.dtypeResolveStr( dtype:any )\n    Returns the data type string associated with a supported data type value.\n","base.strided.dtypeStr2Enum":"\nbase.strided.dtypeStr2Enum( dtype:string )\n    Returns the enumeration constant associated with a strided array data type\n    string.\n","base.strided.dvariance":"\nbase.strided.dvariance( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array.\n","base.strided.dvariance.ndarray":"\nbase.strided.dvariance.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using alternative indexing semantics.\n","base.strided.dvariancech":"\nbase.strided.dvariancech( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass trial mean algorithm.\n","base.strided.dvariancech.ndarray":"\nbase.strided.dvariancech.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.dvariancepn":"\nbase.strided.dvariancepn( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using a two-pass algorithm.\n","base.strided.dvariancepn.ndarray":"\nbase.strided.dvariancepn.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using a two-pass algorithm and alternative indexing semantics.\n","base.strided.dvariancetk":"\nbase.strided.dvariancetk( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass textbook algorithm.\n","base.strided.dvariancetk.ndarray":"\nbase.strided.dvariancetk.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.dvariancewd":"\nbase.strided.dvariancewd( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using Welford's algorithm.\n","base.strided.dvariancewd.ndarray":"\nbase.strided.dvariancewd.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using Welford's algorithm and alternative indexing semantics.\n","base.strided.dvarianceyc":"\nbase.strided.dvarianceyc( N:integer, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.dvarianceyc.ndarray":"\nbase.strided.dvarianceyc.ndarray( N:integer, correction:number, x:Float64Array, \n  stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    using a one-pass algorithm proposed by Youngs and Cramer and alternative\n    indexing semantics.\n","base.strided.dvarm":"\nbase.strided.dvarm( N:integer, mean:number, correction:number, x:Float64Array, \n  stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean.\n","base.strided.dvarm.ndarray":"\nbase.strided.dvarm.ndarray( N:integer, mean:number, correction:number, \n  x:Float64Array, stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using alternative indexing semantics.\n","base.strided.dvarmpn":"\nbase.strided.dvarmpn( N:integer, mean:number, correction:number, \n  x:Float64Array, stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using Neely's correction algorithm.\n","base.strided.dvarmpn.ndarray":"\nbase.strided.dvarmpn.ndarray( N:integer, mean:number, correction:number, \n  x:Float64Array, stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using Neely's correction algorithm and alternative\n    indexing semantics.\n","base.strided.dvarmtk":"\nbase.strided.dvarmtk( N:integer, mean:number, correction:number, \n  x:Float64Array, stride:integer )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using a one-pass textbook algorithm.\n","base.strided.dvarmtk.ndarray":"\nbase.strided.dvarmtk.ndarray( N:integer, mean:number, correction:number, \n  x:Float64Array, stride:integer, offset:integer )\n    Computes the variance of a double-precision floating-point strided array\n    provided a known mean and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n","base.strided.gapx":"\nbase.strided.gapx( N:integer, alpha:number, x:Array|TypedArray, stride:integer )\n    Adds a constant to each element in a strided array.\n","base.strided.gapx.ndarray":"\nbase.strided.gapx.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Adds a constant to each element in a strided array using alternative\n    indexing semantics.\n","base.strided.gapxsum":"\nbase.strided.gapxsum( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer )\n    Adds a constant to each strided array element and computes the sum.\n","base.strided.gapxsum.ndarray":"\nbase.strided.gapxsum.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Adds a constant to each strided array element and computes the sum using\n    alternative indexing semantics.\n","base.strided.gapxsumkbn":"\nbase.strided.gapxsumkbn( N:integer, alpha:number, x:Array|TypedArray, \n  strideX:integer )\n    Adds a scalar constant to each strided array element and computes the sum\n    using an improved Kahan–Babuška algorithm.\n","base.strided.gapxsumkbn.ndarray":"\nbase.strided.gapxsumkbn.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n  strideX:integer, offsetX:integer )\n    Adds a scalar constant to each strided array element and computes the sum\n    using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n","base.strided.gapxsumkbn2":"\nbase.strided.gapxsumkbn2( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer )\n    Adds a constant to each strided array element and computes the sum using a\n    second-order iterative Kahan–Babuška algorithm.\n","base.strided.gapxsumkbn2.ndarray":"\nbase.strided.gapxsumkbn2.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Adds a constant to each strided array element and computes the sum using a\n    second-order iterative Kahan–Babuška algorithm and alternative indexing\n    semantics.\n","base.strided.gapxsumors":"\nbase.strided.gapxsumors( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer )\n    Adds a constant to each strided array element and computes the sum using\n    ordinary recursive summation.\n","base.strided.gapxsumors.ndarray":"\nbase.strided.gapxsumors.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Adds a constant to each strided array element and computes the sum using\n    ordinary recursive summation and alternative indexing semantics.\n","base.strided.gapxsumpw":"\nbase.strided.gapxsumpw( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer )\n    Adds a constant to each strided array element and computes the sum using\n    pairwise summation.\n","base.strided.gapxsumpw.ndarray":"\nbase.strided.gapxsumpw.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Adds a constant to each strided array element and computes the sum using\n    pairwise summation and alternative indexing semantics.\n","base.strided.gasum":"\nbase.strided.gasum( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of the absolute values.\n","base.strided.gasum.ndarray":"\nbase.strided.gasum.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the sum of absolute values using alternative indexing semantics.\n","base.strided.gasumpw":"\nbase.strided.gasumpw( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of absolute values (L1 norm) of strided array elements\n    using pairwise summation.\n","base.strided.gasumpw.ndarray":"\nbase.strided.gasumpw.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the sum of absolute values (L1 norm) of strided array elements\n    using pairwise summation and alternative indexing semantics.\n","base.strided.gaxpy":"\nbase.strided.gaxpy( N:integer, alpha:number, x:Array|TypedArray, \n  strideX:integer, y:Array|TypedArray, strideY:integer )\n    Multiplies `x` by a constant `alpha` and adds the result to `y`.\n","base.strided.gaxpy.ndarray":"\nbase.strided.gaxpy.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n  strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n  offsetY:integer )\n    Multiplies `x` by a constant `alpha` and adds the result to `y`, with\n    alternative indexing semantics.\n","base.strided.gcopy":"\nbase.strided.gcopy( N:integer, x:ArrayLikeObject, strideX:integer, \n  y:ArrayLikeObject, strideY:integer )\n    Copies values from `x` into `y`.\n","base.strided.gcopy.ndarray":"\nbase.strided.gcopy.ndarray( N:integer, x:ArrayLikeObject, strideX:integer, \n  offsetX:integer, y:ArrayLikeObject, strideY:integer, offsetY:integer )\n    Copies values from `x` into `y` using alternative indexing semantics.\n","base.strided.gcusum":"\nbase.strided.gcusum( N:integer, sum:number, x:Array|TypedArray, \n  strideX:integer, y:Array|TypedArray, strideY:integer )\n    Computes the cumulative sum of strided array elements.\n","base.strided.gcusum.ndarray":"\nbase.strided.gcusum.ndarray( N:integer, sum:number, x:Array|TypedArray, \n  strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of strided array elements using alternative\n    indexing semantics.\n","base.strided.gcusumkbn":"\nbase.strided.gcusumkbn( N:integer, sum:number, x:Array|TypedArray, \n  strideX:integer, y:Array|TypedArray, strideY:integer )\n    Computes the cumulative sum of strided array elements using an improved\n    Kahan–Babuška algorithm.\n","base.strided.gcusumkbn.ndarray":"\nbase.strided.gcusumkbn.ndarray( N:integer, sum:number, x:Array|TypedArray, \n  strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of strided array elements using an improved\n    Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gcusumkbn2":"\nbase.strided.gcusumkbn2( N:integer, sum:number, x:Array|TypedArray, \n  strideX:integer, y:Array|TypedArray, strideY:integer )\n    Computes the cumulative sum of strided array elements using a second-order\n    iterative Kahan–Babuška algorithm.\n","base.strided.gcusumkbn2.ndarray":"\nbase.strided.gcusumkbn2.ndarray( N:integer, sum:number, x:Array|TypedArray, \n  strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of strided array elements using a second-order\n    iterative Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gcusumors":"\nbase.strided.gcusumors( N:integer, sum:number, x:Array|TypedArray, \n  strideX:integer, y:Array|TypedArray, strideY:integer )\n    Computes the cumulative sum of strided array elements using ordinary\n    recursive summation.\n","base.strided.gcusumors.ndarray":"\nbase.strided.gcusumors.ndarray( N:integer, sum:number, x:Array|TypedArray, \n  strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of strided array elements using ordinary\n    recursive summation and alternative indexing semantics.\n","base.strided.gcusumpw":"\nbase.strided.gcusumpw( N:integer, sum:number, x:Array|TypedArray, \n  strideX:integer, y:Array|TypedArray, strideY:integer )\n    Computes the cumulative sum of strided array elements using pairwise\n    summation.\n","base.strided.gcusumpw.ndarray":"\nbase.strided.gcusumpw.ndarray( N:integer, sum:number, x:Array|TypedArray, \n  strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of strided array elements using pairwise\n    summation and alternative indexing semantics.\n","base.strided.gdot":"\nbase.strided.gdot( N:integer, x:Array|TypedArray, strideX:integer, \n  y:Array|TypedArray, strideY:integer )\n    Computes the dot product of two vectors.\n","base.strided.gdot.ndarray":"\nbase.strided.gdot.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n  offsetX:integer, y:Array|TypedArray, strideY:integer, offsetY:integer )\n    Computes the dot product of two vectors using alternative indexing\n    semantics.\n","base.strided.gfill":"\nbase.strided.gfill( N:integer, alpha:any, x:ArrayLikeObject, stride:integer )\n    Fills a strided array with a specified scalar value.\n","base.strided.gfill.ndarray":"\nbase.strided.gfill.ndarray( N:integer, alpha:any, x:ArrayLikeObject, \n  stride:integer, offset:integer )\n    Fills a strided array with a specified scalar value using alternative\n    indexing semantics.\n","base.strided.gfillBy":"\nbase.strided.gfillBy( N:integer, x:ArrayLikeObject, stride:integer, \n  clbk:Function[, thisArg:any] )\n    Fills a strided array according to a provided callback function.\n","base.strided.gfillBy.ndarray":"\nbase.strided.gfillBy.ndarray( N:integer, x:ArrayLikeObject, stride:integer, \n  offset:integer, clbk:Function[, thisArg:any] )\n    Fills a strided array according to a provided callback function and using\n    alternative indexing semantics.\n","base.strided.gnannsumkbn":"\nbase.strided.gnannsumkbn( N:integer, x:Array|TypedArray, strideX:integer, \n  out:Array|TypedArray, strideOut:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    an improved Kahan–Babuška algorithm.\n","base.strided.gnannsumkbn.ndarray":"\nbase.strided.gnannsumkbn.ndarray( N:integer, x:Array|TypedArray, \n  strideX:integer, offsetX:integer, out:Array|TypedArray, strideOut:integer, \n  offsetOut:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    an improved Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gnansum":"\nbase.strided.gnansum( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values.\n","base.strided.gnansum.ndarray":"\nbase.strided.gnansum.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    alternative indexing semantics.\n","base.strided.gnansumkbn":"\nbase.strided.gnansumkbn( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    an improved Kahan–Babuška algorithm.\n","base.strided.gnansumkbn.ndarray":"\nbase.strided.gnansumkbn.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    an improved Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gnansumkbn2":"\nbase.strided.gnansumkbn2( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    a second-order iterative Kahan–Babuška algorithm.\n","base.strided.gnansumkbn2.ndarray":"\nbase.strided.gnansumkbn2.ndarray( N:integer, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    a second-order iterative Kahan–Babuška algorithm and alternative indexing\n    semantics.\n","base.strided.gnansumors":"\nbase.strided.gnansumors( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    ordinary recursive summation.\n","base.strided.gnansumors.ndarray":"\nbase.strided.gnansumors.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    ordinary recursive summation and alternative indexing semantics.\n","base.strided.gnansumpw":"\nbase.strided.gnansumpw( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values and\n    pairwise summation.\n","base.strided.gnansumpw.ndarray":"\nbase.strided.gnansumpw.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the sum of strided array elements, ignoring `NaN` values and using\n    pairwise summation and alternative indexing semantics.\n","base.strided.gnrm2":"\nbase.strided.gnrm2( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the L2-norm of a vector.\n","base.strided.gnrm2.ndarray":"\nbase.strided.gnrm2.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the L2-norm of a vector using alternative indexing semantics.\n","base.strided.grev":"\nbase.strided.grev( N:integer, x:ArrayLikeObject, stride:integer )\n    Reverses a strided array in-place.\n","base.strided.grev.ndarray":"\nbase.strided.grev.ndarray( N:integer, x:ArrayLikeObject, stride:integer, \n  offset:integer )\n    Reverses a strided array in-place using alternative indexing semantics.\n","base.strided.gscal":"\nbase.strided.gscal( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer )\n    Multiplies a vector `x` by a constant `alpha`.\n","base.strided.gscal.ndarray":"\nbase.strided.gscal.ndarray( N:integer, alpha:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Multiplies `x` by a constant `alpha` using alternative indexing semantics.\n","base.strided.gsort2hp":"\nbase.strided.gsort2hp( N:integer, order:number, x:Array|TypedArray, \n  strideX:integer, y:Array|TypedArray, strideY:integer )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using heapsort.\n","base.strided.gsort2hp.ndarray":"\nbase.strided.gsort2hp.ndarray( N:integer, order:number, x:Array|TypedArray, \n  strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n  offsetY:integer )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using heapsort and alternative indexing semantics.\n","base.strided.gsort2ins":"\nbase.strided.gsort2ins( N:integer, order:number, x:Array|TypedArray, \n  strideX:integer, y:Array|TypedArray, strideY:integer )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using insertion sort.\n","base.strided.gsort2ins.ndarray":"\nbase.strided.gsort2ins.ndarray( N:integer, order:number, x:Array|TypedArray, \n  strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n  offsetY:integer )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using insertion sort and alternative indexing semantics.\n","base.strided.gsort2sh":"\nbase.strided.gsort2sh( N:integer, order:number, x:Array|TypedArray, \n  strideX:integer, y:Array|TypedArray, strideY:integer )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using Shellsort.\n","base.strided.gsort2sh.ndarray":"\nbase.strided.gsort2sh.ndarray( N:integer, order:number, x:Array|TypedArray, \n  strideX:integer, offsetX:integer, y:Array|TypedArray, strideY:integer, \n  offsetY:integer )\n    Simultaneously sorts two strided arrays based on the sort order of the first\n    array using Shellsort and alternative indexing semantics.\n","base.strided.gsorthp":"\nbase.strided.gsorthp( N:integer, order:number, x:Array|TypedArray, \n  stride:integer )\n    Sorts a strided array using heapsort.\n","base.strided.gsorthp.ndarray":"\nbase.strided.gsorthp.ndarray( N:integer, order:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Sorts a strided array using heapsort and alternative indexing semantics.\n","base.strided.gsortins":"\nbase.strided.gsortins( N:integer, order:number, x:Array|TypedArray, \n  stride:integer )\n    Sorts a strided array using insertion sort.\n","base.strided.gsortins.ndarray":"\nbase.strided.gsortins.ndarray( N:integer, order:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Sorts a strided array using insertion sort and alternative indexing\n    semantics.\n","base.strided.gsortsh":"\nbase.strided.gsortsh( N:integer, order:number, x:Array|TypedArray, \n  stride:integer )\n    Sorts a strided array using Shellsort.\n","base.strided.gsortsh.ndarray":"\nbase.strided.gsortsh.ndarray( N:integer, order:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Sorts a strided array using Shellsort and alternative indexing semantics.\n","base.strided.gsum":"\nbase.strided.gsum( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of strided array elements.\n","base.strided.gsum.ndarray":"\nbase.strided.gsum.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the sum of strided array elements using alternative indexing\n    semantics.\n","base.strided.gsumkbn":"\nbase.strided.gsumkbn( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of strided array elements using an improved Kahan–Babuška\n    algorithm.\n","base.strided.gsumkbn.ndarray":"\nbase.strided.gsumkbn.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the sum of strided array elements using an improved Kahan–Babuška\n    algorithm and alternative indexing semantics.\n","base.strided.gsumkbn2":"\nbase.strided.gsumkbn2( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of strided array elements using a second-order iterative\n    Kahan–Babuška algorithm.\n","base.strided.gsumkbn2.ndarray":"\nbase.strided.gsumkbn2.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the sum of strided array elements using a second-order iterative\n    Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.gsumors":"\nbase.strided.gsumors( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of strided array elements using ordinary recursive\n    summation.\n","base.strided.gsumors.ndarray":"\nbase.strided.gsumors.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the sum of strided array elements using ordinary recursive\n    summation and alternative indexing semantics.\n","base.strided.gsumpw":"\nbase.strided.gsumpw( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the sum of strided array elements using pairwise summation.\n","base.strided.gsumpw.ndarray":"\nbase.strided.gsumpw.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the sum of strided array elements using pairwise summation and\n    alternative indexing semantics.\n","base.strided.gswap":"\nbase.strided.gswap( N:integer, x:ArrayLikeObject, strideX:integer, \n  y:ArrayLikeObject, strideY:integer )\n    Interchanges vectors `x` and `y`.\n","base.strided.gswap.ndarray":"\nbase.strided.gswap.ndarray( N:integer, x:ArrayLikeObject, strideX:integer, \n  offsetX:integer, y:ArrayLikeObject, strideY:integer, offsetY:integer )\n    Interchanges vectors `x` and `y` using alternative indexing semantics.\n","base.strided.mapBy":"\nbase.strided.mapBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, fcn:Function, clbk:Function[, \n  thisArg:any] )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array.\n","base.strided.mapBy.ndarray":"\nbase.strided.mapBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, fcn:Function, \n  clbk:Function[, thisArg:any] )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array using alternative indexing semantics.\n","base.strided.mapBy2":"\nbase.strided.mapBy2( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, \n  fcn:Function, clbk:Function[, thisArg:any] )\n    Applies a binary function to each pair of elements retrieved from strided\n    input arrays according to a callback function and assigns results to a\n    strided output array.\n","base.strided.mapBy2.ndarray":"\nbase.strided.mapBy2.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  z:Array|TypedArray|Object, sz:integer, oz:integer, fcn:Function, \n  clbk:Function[, thisArg:any] )\n    Applies a binary function to each pair of elements retrieved from strided\n    input arrays according to a callback function and assigns results to a\n    strided output array using alternative indexing semantics.\n","base.strided.max":"\nbase.strided.max( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the maximum value of a strided array.\n","base.strided.max.ndarray":"\nbase.strided.max.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the maximum value of a strided array using alternative indexing\n    semantics.\n","base.strided.maxabs":"\nbase.strided.maxabs( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the maximum absolute value of a strided array.\n","base.strided.maxabs.ndarray":"\nbase.strided.maxabs.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the maximum absolute value of a strided array using alternative\n    indexing semantics.\n","base.strided.maxBy":"\nbase.strided.maxBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n  clbk:Function[, thisArg:any] )\n    Calculates the maximum value of a strided array via a callback function.\n","base.strided.maxBy.ndarray":"\nbase.strided.maxBy.ndarray( N:integer, x:Array|TypedArray|Object, \n  stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n    Calculates the maximum value of a strided array via a callback function and\n    using alternative indexing semantics.\n","base.strided.maxsorted":"\nbase.strided.maxsorted( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the maximum value of a sorted strided array.\n","base.strided.maxsorted.ndarray":"\nbase.strided.maxsorted.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the maximum value of a sorted strided array using alternative\n    indexing semantics.\n","base.strided.maxViewBufferIndex":"\nbase.strided.maxViewBufferIndex( N:integer, stride:integer, offset:integer )\n    Returns the maximum accessible index based on a set of provided strided\n    array parameters.\n","base.strided.mean":"\nbase.strided.mean( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the arithmetic mean of a strided array.\n","base.strided.mean.ndarray":"\nbase.strided.mean.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a strided array using alternative indexing\n    semantics.\n","base.strided.meankbn":"\nbase.strided.meankbn( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the arithmetic mean of a strided array using an improved Kahan–\n    Babuška algorithm.\n","base.strided.meankbn.ndarray":"\nbase.strided.meankbn.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a strided array using an improved Kahan–\n    Babuška algorithm and alternative indexing semantics.\n","base.strided.meankbn2":"\nbase.strided.meankbn2( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the arithmetic mean of a strided array using a second-order\n    iterative Kahan–Babuška algorithm.\n","base.strided.meankbn2.ndarray":"\nbase.strided.meankbn2.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a strided array using a second-order\n    iterative Kahan–Babuška algorithm and alternative indexing semantics.\n","base.strided.meanors":"\nbase.strided.meanors( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the arithmetic mean of a strided array using ordinary recursive\n    summation.\n","base.strided.meanors.ndarray":"\nbase.strided.meanors.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a strided array using ordinary recursive\n    summation and alternative indexing semantics.\n","base.strided.meanpn":"\nbase.strided.meanpn( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the arithmetic mean of a strided array using a two-pass error\n    correction algorithm.\n","base.strided.meanpn.ndarray":"\nbase.strided.meanpn.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a strided array using a two-pass error\n    correction algorithm and alternative indexing semantics.\n","base.strided.meanpw":"\nbase.strided.meanpw( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the arithmetic mean of a strided array using pairwise summation.\n","base.strided.meanpw.ndarray":"\nbase.strided.meanpw.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a strided array using pairwise summation and\n    alternative indexing semantics.\n","base.strided.meanwd":"\nbase.strided.meanwd( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the arithmetic mean of a strided array using Welford's algorithm.\n","base.strided.meanwd.ndarray":"\nbase.strided.meanwd.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a strided array using Welford's algorithm\n    and alternative indexing semantics.\n","base.strided.mediansorted":"\nbase.strided.mediansorted( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the median value of a sorted strided array.\n","base.strided.mediansorted.ndarray":"\nbase.strided.mediansorted.ndarray( N:integer, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Computes the median value of a sorted strided array using alternative\n    indexing semantics.\n","base.strided.metaDataProps":"\nbase.strided.metaDataProps( meta:Object, dtypes:ArrayLikeObject, \n  obj:Object|Function, bool:boolean )\n    Defines non-enumerable read-only properties which expose strided array\n    function meta data.\n","base.strided.min":"\nbase.strided.min( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the minimum value of a strided array.\n","base.strided.min.ndarray":"\nbase.strided.min.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the minimum value of a strided array using alternative indexing\n    semantics.\n","base.strided.minabs":"\nbase.strided.minabs( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the minimum absolute value of a strided array.\n","base.strided.minabs.ndarray":"\nbase.strided.minabs.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the minimum absolute value of a strided array using alternative\n    indexing semantics.\n","base.strided.minBy":"\nbase.strided.minBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n  clbk:Function[, thisArg:any] )\n    Calculates the minimum value of a strided array via a callback function.\n","base.strided.minBy.ndarray":"\nbase.strided.minBy.ndarray( N:integer, x:Array|TypedArray|Object, \n  stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n    Calculates the minimum value of a strided array via a callback function and\n    using alternative indexing semantics.\n","base.strided.minsorted":"\nbase.strided.minsorted( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the minimum value of a sorted strided array.\n","base.strided.minsorted.ndarray":"\nbase.strided.minsorted.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the minimum value of a sorted strided array using alternative\n    indexing semantics.\n","base.strided.minViewBufferIndex":"\nbase.strided.minViewBufferIndex( N:integer, stride:integer, offset:integer )\n    Returns the minimum accessible index based on a set of provided strided\n    array parameters.\n","base.strided.mskmax":"\nbase.strided.mskmax( N:integer, x:Array|TypedArray, strideX:integer, \n  mask:Array|TypedArray, strideMask:integer )\n    Computes the maximum value of a strided array according to a mask.\n","base.strided.mskmax.ndarray":"\nbase.strided.mskmax.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n  offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n  offsetMask:integer )\n    Computes the maximum value of a strided array according to a mask and using\n    alternative indexing semantics.\n","base.strided.mskmin":"\nbase.strided.mskmin( N:integer, x:Array|TypedArray, strideX:integer, \n  mask:Array|TypedArray, strideMask:integer )\n    Computes the minimum value of a strided array according to a mask.\n","base.strided.mskmin.ndarray":"\nbase.strided.mskmin.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n  offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n  offsetMask:integer )\n    Computes the minimum value of a strided array according to a mask and using\n    alternative indexing semantics.\n","base.strided.mskrange":"\nbase.strided.mskrange( N:integer, x:Array|TypedArray, strideX:integer, \n  mask:Array|TypedArray, strideMask:integer )\n    Computes the range of a strided array according to a mask.\n","base.strided.mskrange.ndarray":"\nbase.strided.mskrange.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n  offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n  offsetMask:integer )\n    Computes the range of a strided array according to a mask and using\n    alternative indexing semantics.\n","base.strided.mskunary":"\nbase.strided.mskunary( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  fcn:Function )\n    Applies a unary callback to elements in a strided input array according to\n    elements in a strided mask array and assigns results to elements in a\n    strided output array.\n","base.strided.mskunary.ndarray":"\nbase.strided.mskunary.ndarray( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  offsets:ArrayLikeObject<integer>, fcn:Function )\n    Applies a unary callback to elements in a strided input array according to\n    elements in a strided mask array, and assigns results to elements in a\n    strided output array using alternative indexing semantics.\n","base.strided.mskunaryDtypeSignatures":"\nbase.strided.mskunaryDtypeSignatures( dtypes1:ArrayLike<any>, \n  dtypes2:ArrayLike<any>[, options:Object] )\n    Generates a list of masked unary interface signatures from strided array\n    data types.\n","base.strided.mskunarySignatureCallbacks":"\nbase.strided.mskunarySignatureCallbacks( table:Object, \n  signatures:ArrayLike<any> )\n    Assigns callbacks to masked unary interfaces according to type promotion\n    rules.\n","base.strided.nanmax":"\nbase.strided.nanmax( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the maximum value of a strided array, ignoring `NaN` values.\n","base.strided.nanmax.ndarray":"\nbase.strided.nanmax.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the maximum value of a strided array, ignoring `NaN` values and\n    using alternative indexing semantics.\n","base.strided.nanmaxabs":"\nbase.strided.nanmaxabs( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the maximum absolute value of a strided array, ignoring `NaN`\n    values.\n","base.strided.nanmaxabs.ndarray":"\nbase.strided.nanmaxabs.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the maximum absolute value of a strided array, ignoring `NaN`\n    values and using alternative indexing semantics.\n","base.strided.nanmaxBy":"\nbase.strided.nanmaxBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n  clbk:Function[, thisArg:any] )\n    Calculates the maximum value of a strided array via a callback function,\n    ignoring `NaN` values.\n","base.strided.nanmaxBy.ndarray":"\nbase.strided.nanmaxBy.ndarray( N:integer, x:Array|TypedArray|Object, \n  stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n    Calculates the maximum value of a strided array via a callback function,\n    ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.nanmean":"\nbase.strided.nanmean( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values.\n","base.strided.nanmean.ndarray":"\nbase.strided.nanmean.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using alternative indexing semantics.\n","base.strided.nanmeanors":"\nbase.strided.nanmeanors( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using ordinary recursive summation.\n","base.strided.nanmeanors.ndarray":"\nbase.strided.nanmeanors.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using ordinary recursive summation and alternative indexing semantics.\n","base.strided.nanmeanpn":"\nbase.strided.nanmeanpn( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using a two-pass error correction algorithm.\n","base.strided.nanmeanpn.ndarray":"\nbase.strided.nanmeanpn.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using a two-pass error correction algorithm and alternative indexing\n    semantics.\n","base.strided.nanmeanwd":"\nbase.strided.nanmeanwd( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using Welford's algorithm.\n","base.strided.nanmeanwd.ndarray":"\nbase.strided.nanmeanwd.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a strided array, ignoring `NaN` values and\n    using Welford's algorithm and alternative indexing semantics.\n","base.strided.nanmin":"\nbase.strided.nanmin( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the minimum value of a strided array, ignoring `NaN` values.\n","base.strided.nanmin.ndarray":"\nbase.strided.nanmin.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the minimum value of a strided array, ignoring `NaN` values and\n    using alternative indexing semantics.\n","base.strided.nanminabs":"\nbase.strided.nanminabs( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the minimum absolute value of a strided array, ignoring `NaN`\n    values.\n","base.strided.nanminabs.ndarray":"\nbase.strided.nanminabs.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the minimum absolute value of a strided array, ignoring `NaN`\n    values and using alternative indexing semantics.\n","base.strided.nanminBy":"\nbase.strided.nanminBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n  clbk:Function[, thisArg:any] )\n    Calculates the minimum value of a strided array via a callback function,\n    ignoring `NaN` values.\n","base.strided.nanminBy.ndarray":"\nbase.strided.nanminBy.ndarray( N:integer, x:Array|TypedArray|Object, \n  stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n    Calculates the minimum value of a strided array via a callback function,\n    ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.nanmskmax":"\nbase.strided.nanmskmax( N:integer, x:Array|TypedArray, strideX:integer, \n  mask:Array|TypedArray, strideMask:integer )\n    Computes the maximum value of a strided array according to a mask and\n    ignoring `NaN` values.\n","base.strided.nanmskmax.ndarray":"\nbase.strided.nanmskmax.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n  offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n  offsetMask:integer )\n    Computes the maximum value of a strided array according to a mask,\n    ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.nanmskmin":"\nbase.strided.nanmskmin( N:integer, x:Array|TypedArray, strideX:integer, \n  mask:Array|TypedArray, strideMask:integer )\n    Computes the minimum value of a strided array according to a mask and\n    ignoring `NaN` values.\n","base.strided.nanmskmin.ndarray":"\nbase.strided.nanmskmin.ndarray( N:integer, x:Array|TypedArray, strideX:integer, \n  offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n  offsetMask:integer )\n    Computes the minimum value of a strided array according to a mask, ignoring\n    `NaN` values and using alternative indexing semantics.\n","base.strided.nanmskrange":"\nbase.strided.nanmskrange( N:integer, x:Array|TypedArray, strideX:integer, \n  mask:Array|TypedArray, strideMask:integer )\n    Computes the range of a strided array according to a mask and ignoring `NaN`\n    values.\n","base.strided.nanmskrange.ndarray":"\nbase.strided.nanmskrange.ndarray( N:integer, x:Array|TypedArray, \n  strideX:integer, offsetX:integer, mask:Array|TypedArray, strideMask:integer, \n  offsetMask:integer )\n    Computes the range of a strided array according to a mask, ignoring `NaN`\n    values and using alternative indexing semantics.\n","base.strided.nanrange":"\nbase.strided.nanrange( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the range of a strided array, ignoring `NaN` values.\n","base.strided.nanrange.ndarray":"\nbase.strided.nanrange.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the range of a strided array, ignoring `NaN` values and using\n    alternative indexing semantics.\n","base.strided.nanrangeBy":"\nbase.strided.nanrangeBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n  clbk:Function[, thisArg:any] )\n    Calculates the range of a strided array via a callback function, ignoring\n    `NaN` values.\n","base.strided.nanrangeBy.ndarray":"\nbase.strided.nanrangeBy.ndarray( N:integer, x:Array|TypedArray|Object, \n  stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n    Calculates the range of a strided array via a callback function, ignoring\n    `NaN` values and using alternative indexing semantics.\n","base.strided.nanstdev":"\nbase.strided.nanstdev( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values.\n","base.strided.nanstdev.ndarray":"\nbase.strided.nanstdev.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using alternative indexing semantics.\n","base.strided.nanstdevch":"\nbase.strided.nanstdevch( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass trial mean algorithm.\n","base.strided.nanstdevch.ndarray":"\nbase.strided.nanstdevch.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.nanstdevpn":"\nbase.strided.nanstdevpn( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a two-pass algorithm.\n","base.strided.nanstdevpn.ndarray":"\nbase.strided.nanstdevpn.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a two-pass algorithm and alternative indexing semantics.\n","base.strided.nanstdevtk":"\nbase.strided.nanstdevtk( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass textbook algorithm.\n","base.strided.nanstdevtk.ndarray":"\nbase.strided.nanstdevtk.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.nanstdevwd":"\nbase.strided.nanstdevwd( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using Welford's algorithm.\n","base.strided.nanstdevwd.ndarray":"\nbase.strided.nanstdevwd.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using Welford's algorithm and alternative indexing semantics.\n","base.strided.nanstdevyc":"\nbase.strided.nanstdevyc( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.nanstdevyc.ndarray":"\nbase.strided.nanstdevyc.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the standard deviation of a strided array ignoring `NaN` values and\n    using a one-pass algorithm proposed by Youngs and Cramer and alternative\n    indexing semantics.\n","base.strided.nanvariance":"\nbase.strided.nanvariance( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array ignoring `NaN` values.\n","base.strided.nanvariance.ndarray":"\nbase.strided.nanvariance.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using\n    alternative indexing semantics.\n","base.strided.nanvariancech":"\nbase.strided.nanvariancech( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass trial mean algorithm.\n","base.strided.nanvariancech.ndarray":"\nbase.strided.nanvariancech.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.nanvariancepn":"\nbase.strided.nanvariancepn( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    two-pass algorithm.\n","base.strided.nanvariancepn.ndarray":"\nbase.strided.nanvariancepn.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    two-pass algorithm and alternative indexing semantics.\n","base.strided.nanvariancetk":"\nbase.strided.nanvariancetk( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass textbook algorithm.\n","base.strided.nanvariancetk.ndarray":"\nbase.strided.nanvariancetk.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.nanvariancewd":"\nbase.strided.nanvariancewd( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using\n    Welford's algorithm.\n","base.strided.nanvariancewd.ndarray":"\nbase.strided.nanvariancewd.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using\n    Welford's algorithm and alternative indexing semantics.\n","base.strided.nanvarianceyc":"\nbase.strided.nanvarianceyc( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.nanvarianceyc.ndarray":"\nbase.strided.nanvarianceyc.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array ignoring `NaN` values and using a\n    one-pass algorithm proposed by Youngs and Cramer and alternative indexing\n    semantics.\n","base.strided.nullary":"\nbase.strided.nullary( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  fcn:Function )\n    Applies a nullary callback and assigns results to elements in a strided\n    output array.\n","base.strided.nullary.ndarray":"\nbase.strided.nullary.ndarray( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  offsets:ArrayLikeObject<integer>, fcn:Function )\n    Applies a nullary callback and assigns results to elements in a strided\n    output array using alternative indexing semantics.\n","base.strided.offsetView":"\nbase.strided.offsetView( x:TypedArray, offset:integer )\n    Returns a typed array view having the same data type as a provided input\n    typed array and starting at a specified index offset.\n","base.strided.quaternary":"\nbase.strided.quaternary( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  fcn:Function )\n    Applies a quaternary callback to strided input array elements and assigns\n    results to elements in a strided output array.\n","base.strided.quaternary.ndarray":"\nbase.strided.quaternary.ndarray( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  offsets:ArrayLikeObject<integer>, fcn:Function )\n    Applies a quaternary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n","base.strided.quinary":"\nbase.strided.quinary( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  fcn:Function )\n    Applies a quinary callback to strided input array elements and assigns\n    results to elements in a strided output array.\n","base.strided.quinary.ndarray":"\nbase.strided.quinary.ndarray( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  offsets:ArrayLikeObject<integer>, fcn:Function )\n    Applies a quinary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n","base.strided.range":"\nbase.strided.range( N:integer, x:Array|TypedArray, stride:integer )\n    Computes the range of a strided array.\n","base.strided.range.ndarray":"\nbase.strided.range.ndarray( N:integer, x:Array|TypedArray, stride:integer, \n  offset:integer )\n    Computes the range of a strided array using alternative indexing semantics.\n","base.strided.rangeBy":"\nbase.strided.rangeBy( N:integer, x:Array|TypedArray|Object, stride:integer, \n  clbk:Function[, thisArg:any] )\n    Calculates the range of a strided array via a callback function.\n","base.strided.rangeBy.ndarray":"\nbase.strided.rangeBy.ndarray( N:integer, x:Array|TypedArray|Object, \n  stride:integer, offset:integer, clbk:Function[, thisArg:any] )\n    Calculates the range of a strided array via a callback function and using\n    alternative indexing semantics.\n","base.strided.reinterpretComplex":"\nbase.strided.reinterpretComplex( x:Complex128Array|Complex64Array, \n  offset:integer )\n    Returns a real-valued floating-point array view of a complex-valued\n    floating-point array having the same precision.\n","base.strided.reinterpretComplex64":"\nbase.strided.reinterpretComplex64( x:Complex64Array, offset:integer )\n    Returns a Float32Array view of a Complex64Array.\n","base.strided.reinterpretComplex128":"\nbase.strided.reinterpretComplex128( x:Complex128Array, offset:integer )\n    Returns a Float64Array view of a Complex128Array.\n","base.strided.sabs":"\nbase.strided.sabs( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer )\n    Computes the absolute value for each element in a single-precision floating-\n    point strided array `x` and assigns the results to elements in a single-\n    precision floating-point strided array `y`.\n","base.strided.sabs.ndarray":"\nbase.strided.sabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the absolute value for each element in a single-precision floating-\n    point strided array `x` and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.sabs2":"\nbase.strided.sabs2( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer )\n    Computes the squared absolute value for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y`.\n","base.strided.sabs2.ndarray":"\nbase.strided.sabs2.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the squared absolute value for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.sapx":"\nbase.strided.sapx( N:integer, alpha:number, x:Float32Array, stride:integer )\n    Adds a constant to each element in a single-precision floating-point strided\n    array.\n","base.strided.sapx.ndarray":"\nbase.strided.sapx.ndarray( N:integer, alpha:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Adds a constant to each element in a single-precision floating-point strided\n    array using alternative indexing semantics.\n","base.strided.sapxsum":"\nbase.strided.sapxsum( N:integer, alpha:number, x:Float32Array, stride:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum.\n","base.strided.sapxsum.ndarray":"\nbase.strided.sapxsum.ndarray( N:integer, alpha:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using alternative indexing semantics.\n","base.strided.sapxsumkbn":"\nbase.strided.sapxsumkbn( N:integer, alpha:number, x:Float32Array, \n  stride:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using an improved Kahan–Babuška algorithm.\n","base.strided.sapxsumkbn.ndarray":"\nbase.strided.sapxsumkbn.ndarray( N:integer, alpha:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n","base.strided.sapxsumkbn2":"\nbase.strided.sapxsumkbn2( N:integer, alpha:number, x:Float32Array, \n  stride:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using a second-order iterative Kahan–Babuška\n    algorithm.\n","base.strided.sapxsumkbn2.ndarray":"\nbase.strided.sapxsumkbn2.ndarray( N:integer, alpha:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n","base.strided.sapxsumors":"\nbase.strided.sapxsumors( N:integer, alpha:number, x:Float32Array, \n  stride:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using ordinary recursive summation.\n","base.strided.sapxsumors.ndarray":"\nbase.strided.sapxsumors.ndarray( N:integer, alpha:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using ordinary recursive summation and\n    alternative indexing semantics.\n","base.strided.sapxsumpw":"\nbase.strided.sapxsumpw( N:integer, alpha:number, x:Float32Array, \n  stride:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using pairwise summation.\n","base.strided.sapxsumpw.ndarray":"\nbase.strided.sapxsumpw.ndarray( N:integer, alpha:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using pairwise summation and alternative\n    indexing semantics.\n","base.strided.sasum":"\nbase.strided.sasum( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of the absolute values.\n","base.strided.sasum.ndarray":"\nbase.strided.sasum.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of absolute values using alternative indexing semantics.\n","base.strided.sasumpw":"\nbase.strided.sasumpw( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of absolute values (L1 norm) of single-precision floating-\n    point strided array elements using pairwise summation.\n","base.strided.sasumpw.ndarray":"\nbase.strided.sasumpw.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of absolute values (L1 norm) of single-precision floating-\n    point strided array elements using pairwise summation and alternative\n    indexing semantics.\n","base.strided.saxpy":"\nbase.strided.saxpy( N:integer, alpha:number, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Multiplies a vector `x` by a constant `alpha` and adds the result to `y`.\n","base.strided.saxpy.ndarray":"\nbase.strided.saxpy.ndarray( N:integer, alpha:number, x:Float32Array, \n  strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n  offsetY:integer )\n    Multiplies a vector `x` by a constant `alpha` and adds the result to `y`,\n    using alternative indexing semantics.\n","base.strided.scbrt":"\nbase.strided.scbrt( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer )\n    Computes the cube root of each element in a single-precision floating-point \n    strided array `x` and assigns the results to elements in a single-precision \n    floating-point strided array `y`.\n","base.strided.scbrt.ndarray":"\nbase.strided.scbrt.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the cube root of each element in a single-precision floating-point \n    strided array `x` and assigns the results to elements in a single-precision \n    floating-point strided array `y` using alternative indexing semantics.\n","base.strided.sceil":"\nbase.strided.sceil( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward positive infinity and assigns the results to elements in a single-\n    precision floating-point strided array `y`.\n","base.strided.sceil.ndarray":"\nbase.strided.sceil.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward positive infinity and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.scopy":"\nbase.strided.scopy( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer )\n    Copies values from `x` into `y`.\n","base.strided.scopy.ndarray":"\nbase.strided.scopy.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Copies values from `x` into `y` using alternative indexing semantics.\n","base.strided.scumax":"\nbase.strided.scumax( N:integer, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Computes the cumulative maximum of single-precision floating-point strided\n    array elements.\n","base.strided.scumax.ndarray":"\nbase.strided.scumax.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the cumulative maximum of single-precision floating-point strided\n    array elements using alternative indexing semantics.\n","base.strided.scumaxabs":"\nbase.strided.scumaxabs( N:integer, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Computes the cumulative maximum absolute value of single-precision floating-\n    point strided array elements.\n","base.strided.scumaxabs.ndarray":"\nbase.strided.scumaxabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the cumulative maximum absolute value of single-precision floating-\n    point strided array elements using alternative indexing semantics.\n","base.strided.scumin":"\nbase.strided.scumin( N:integer, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Computes the cumulative minimum of single-precision floating-point strided\n    array elements.\n","base.strided.scumin.ndarray":"\nbase.strided.scumin.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the cumulative minimum of single-precision floating-point strided\n    array elements using alternative indexing semantics.\n","base.strided.scuminabs":"\nbase.strided.scuminabs( N:integer, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Computes the cumulative minimum absolute value of single-precision floating-\n    point strided array elements.\n","base.strided.scuminabs.ndarray":"\nbase.strided.scuminabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the cumulative minimum absolute value of single-precision floating-\n    point strided array elements using alternative indexing semantics.\n","base.strided.scusum":"\nbase.strided.scusum( N:integer, sum:number, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements.\n","base.strided.scusum.ndarray":"\nbase.strided.scusum.ndarray( N:integer, sum:number, x:Float32Array, \n  strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using alternative indexing semantics.\n","base.strided.scusumkbn":"\nbase.strided.scusumkbn( N:integer, sum:number, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using an improved Kahan–Babuška algorithm.\n","base.strided.scusumkbn.ndarray":"\nbase.strided.scusumkbn.ndarray( N:integer, sum:number, x:Float32Array, \n  strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n","base.strided.scusumkbn2":"\nbase.strided.scusumkbn2( N:integer, sum:number, x:Float32Array, \n  strideX:integer, y:Float32Array, strideY:integer )\n    Computes the cumulative sum of single-precision floating-point strided \n    array elements using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.scusumkbn2.ndarray":"\nbase.strided.scusumkbn2.ndarray( N:integer, sum:number, x:Float32Array, \n  strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of single-precision floating-point strided\n    array elements using a second-order iterative Kahan–Babuška algorithm and\n    alternative indexing semantics.\n","base.strided.scusumors":"\nbase.strided.scusumors( N:integer, sum:number, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using ordinary recursive summation.\n","base.strided.scusumors.ndarray":"\nbase.strided.scusumors.ndarray( N:integer, sum:number, x:Float32Array, \n  strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using ordinary recursive summation and alternative indexing\n    semantics.\n","base.strided.scusumpw":"\nbase.strided.scusumpw( N:integer, sum:number, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using pairwise summation.\n","base.strided.scusumpw.ndarray":"\nbase.strided.scusumpw.ndarray( N:integer, sum:number, x:Float32Array, \n  strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n  offsetY:integer )\n    Computes the cumulative sum of single-precision floating-point strided array\n    elements using pairwise summation and alternative indexing semantics.\n","base.strided.sdeg2rad":"\nbase.strided.sdeg2rad( N:integer, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Converts each element in a single-precision floating-point strided array `x`\n    from degrees to radians and assigns the results to elements in a single-\n    precision floating-point strided array `y`.\n","base.strided.sdeg2rad.ndarray":"\nbase.strided.sdeg2rad.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Converts each element in a single-precision floating-point strided array `x`\n    from degrees to radians and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.sdot":"\nbase.strided.sdot( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer )\n    Computes the dot product of two single-precision floating-point vectors.\n","base.strided.sdot.ndarray":"\nbase.strided.sdot.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the dot product of two single-precision floating-point vectors\n    using alternative indexing semantics.\n","base.strided.sdsapxsum":"\nbase.strided.sdsapxsum( N:integer, alpha:number, x:Float32Array, \n  stride:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using extended accumulation.\n","base.strided.sdsapxsum.ndarray":"\nbase.strided.sdsapxsum.ndarray( N:integer, alpha:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using extended accumulation and alternative\n    indexing semantics.\n","base.strided.sdsapxsumpw":"\nbase.strided.sdsapxsumpw( N:integer, alpha:number, x:Float32Array, \n  stride:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using pairwise summation with extended\n    accumulation.\n","base.strided.sdsapxsumpw.ndarray":"\nbase.strided.sdsapxsumpw.ndarray( N:integer, alpha:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Adds a constant to each single-precision floating-point strided array\n    element and computes the sum using pairwise summation with extended\n    accumulation and alternative indexing semantics.\n","base.strided.sdsdot":"\nbase.strided.sdsdot( N:integer, scalar:number, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Computes the dot product of two single-precision floating-point vectors with\n    extended accumulation.\n","base.strided.sdsdot.ndarray":"\nbase.strided.sdsdot.ndarray( N:integer, scalar:number, x:Float32Array, \n  strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n  offsetY:integer )\n    Computes the dot product of two single-precision floating-point vectors\n    using alternative indexing semantics and with extended accumulation.\n","base.strided.sdsmean":"\nbase.strided.sdsmean( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using extended accumulation.\n","base.strided.sdsmean.ndarray":"\nbase.strided.sdsmean.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using extended accumulation and alternative indexing semantics.\n","base.strided.sdsmeanors":"\nbase.strided.sdsmeanors( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation with extended accumulation.\n","base.strided.sdsmeanors.ndarray":"\nbase.strided.sdsmeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation with extended accumulation and\n    alternative indexing semantics.\n","base.strided.sdsnanmean":"\nbase.strided.sdsnanmean( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using extended accumulation.\n","base.strided.sdsnanmean.ndarray":"\nbase.strided.sdsnanmean.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using extended accumulation and alternative\n    indexing semantics.\n","base.strided.sdsnanmeanors":"\nbase.strided.sdsnanmeanors( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation with\n    extended accumulation.\n","base.strided.sdsnanmeanors.ndarray":"\nbase.strided.sdsnanmeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation with\n    extended accumulation and alternative indexing semantics.\n","base.strided.sdsnansum":"\nbase.strided.sdsnansum( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of single-precision floating-point strided array\n    elements, ignore `NaN` values and using extended accumulation.\n","base.strided.sdsnansum.ndarray":"\nbase.strided.sdsnansum.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using extended accumulation and alternative\n    indexing semantics.\n","base.strided.sdsnansumpw":"\nbase.strided.sdsnansumpw( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation with extended\n    accumulation.\n","base.strided.sdsnansumpw.ndarray":"\nbase.strided.sdsnansumpw.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation with extended\n    accumulation and alternative indexing semantics.\n","base.strided.sdssum":"\nbase.strided.sdssum( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using extended accumulation.\n","base.strided.sdssum.ndarray":"\nbase.strided.sdssum.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using extended accumulation and alternative indexing semantics.\n","base.strided.sdssumpw":"\nbase.strided.sdssumpw( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation with extended accumulation.\n","base.strided.sdssumpw.ndarray":"\nbase.strided.sdssumpw.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation with extended accumulation and alternative indexing\n    semantics.\n","base.strided.sfill":"\nbase.strided.sfill( N:integer, alpha:number, x:Float32Array, strideX:integer )\n    Fills a single-precision floating-point strided array with a specified\n    scalar value.\n","base.strided.sfill.ndarray":"\nbase.strided.sfill.ndarray( N:integer, alpha:number, x:Float32Array, \n  strideX:integer, offsetX:integer )\n    Fills a single-precision floating-point strided array with a specified\n    scalar value using alternative indexing semantics.\n","base.strided.sfloor":"\nbase.strided.sfloor( N:integer, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward negative infinity and assigns the results to elements in a single-\n    precision floating-point strided array `y`.\n","base.strided.sfloor.ndarray":"\nbase.strided.sfloor.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward negative infinity and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.sinv":"\nbase.strided.sinv( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer )\n    Computes the multiplicative inverse for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y`.\n","base.strided.sinv.ndarray":"\nbase.strided.sinv.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the multiplicative inverse for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.smap":"\nbase.strided.smap( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer, fcn:Function )\n    Applies a unary function to a single-precision floating-point strided input\n    array and assigns results to a single-precision floating-point strided\n    output array.\n","base.strided.smap.ndarray":"\nbase.strided.smap.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer, \n  fcn:Function )\n    Applies a unary function to a single-precision floating-point strided input\n    array and assigns results to a single-precision floating-point strided\n    output array using alternative indexing semantics.\n","base.strided.smap2":"\nbase.strided.smap2( N:integer, x:Float32Array, sx:integer, y:Float32Array, \n  sy:integer, z:Float32Array, sz:integer, fcn:Function )\n    Applies a binary function to single-precision floating-point strided input\n    arrays and assigns results to a single-precision floating-point strided\n    output array.\n","base.strided.smap2.ndarray":"\nbase.strided.smap2.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, \n  y:Float32Array, sy:integer, oy:integer, z:Float32Array, sz:integer, \n  oz:integer, fcn:Function )\n    Applies a binary function to single-precision floating-point strided input\n    arrays and assigns results to a single-precision floating-point strided\n    output array using alternative indexing semantics.\n","base.strided.smax":"\nbase.strided.smax( N:integer, x:Float32Array, strideX:integer )\n    Computes the maximum value of a single-precision floating-point strided\n    array.\n","base.strided.smax.ndarray":"\nbase.strided.smax.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum value of a single-precision floating-point strided\n    array using alternative indexing semantics.\n","base.strided.smaxabs":"\nbase.strided.smaxabs( N:integer, x:Float32Array, strideX:integer )\n    Computes the maximum absolute value of a single-precision floating-point\n    strided array.\n","base.strided.smaxabs.ndarray":"\nbase.strided.smaxabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum absolute value of a single-precision floating-point\n    strided array using alternative indexing semantics.\n","base.strided.smaxabssorted":"\nbase.strided.smaxabssorted( N:integer, x:Float32Array, strideX:integer )\n    Computes the maximum absolute value of a sorted single-precision floating-\n    point strided array.\n","base.strided.smaxabssorted.ndarray":"\nbase.strided.smaxabssorted.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum absolute value of a sorted single-precision floating-\n    point strided array using alternative indexing semantics.\n","base.strided.smaxsorted":"\nbase.strided.smaxsorted( N:integer, x:Float32Array, strideX:integer )\n    Computes the maximum value of a sorted single-precision floating-point\n    strided array.\n","base.strided.smaxsorted.ndarray":"\nbase.strided.smaxsorted.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n","base.strided.smean":"\nbase.strided.smean( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array.\n","base.strided.smean.ndarray":"\nbase.strided.smean.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using alternative indexing semantics.\n","base.strided.smeankbn":"\nbase.strided.smeankbn( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm.\n","base.strided.smeankbn.ndarray":"\nbase.strided.smeankbn.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n","base.strided.smeankbn2":"\nbase.strided.smeankbn2( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.smeankbn2.ndarray":"\nbase.strided.smeankbn2.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n","base.strided.smeanli":"\nbase.strided.smeanli( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm.\n","base.strided.smeanli.ndarray":"\nbase.strided.smeanli.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n","base.strided.smeanlipw":"\nbase.strided.smeanlipw( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm with pairwise summation.\n","base.strided.smeanlipw.ndarray":"\nbase.strided.smeanlipw.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm with pairwise summation and\n    alternative indexing semantics.\n","base.strided.smeanors":"\nbase.strided.smeanors( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation.\n","base.strided.smeanors.ndarray":"\nbase.strided.smeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using ordinary recursive summation and alternative indexing semantics.\n","base.strided.smeanpn":"\nbase.strided.smeanpn( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a two-pass error correction algorithm.\n","base.strided.smeanpn.ndarray":"\nbase.strided.smeanpn.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using a two-pass error correction algorithm and alternative indexing\n    semantics.\n","base.strided.smeanpw":"\nbase.strided.smeanpw( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using pairwise summation.\n","base.strided.smeanpw.ndarray":"\nbase.strided.smeanpw.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using pairwise summation and alternative indexing semantics.\n","base.strided.smeanwd":"\nbase.strided.smeanwd( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using Welford's algorithm.\n","base.strided.smeanwd.ndarray":"\nbase.strided.smeanwd.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n","base.strided.smediansorted":"\nbase.strided.smediansorted( N:integer, x:Float32Array, strideX:integer )\n    Computes the median value of a sorted single-precision floating-point\n    strided array.\n","base.strided.smediansorted.ndarray":"\nbase.strided.smediansorted.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the median value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n","base.strided.smidrange":"\nbase.strided.smidrange( N:integer, x:Float32Array, strideX:integer )\n    Computes the mid-range of a single-precision floating-point strided array.\n","base.strided.smidrange.ndarray":"\nbase.strided.smidrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the mid-range of a single-precision floating-point strided array\n    using alternative indexing semantics.\n","base.strided.smin":"\nbase.strided.smin( N:integer, x:Float32Array, strideX:integer )\n    Computes the minimum value of a single-precision floating-point strided\n    array.\n","base.strided.smin.ndarray":"\nbase.strided.smin.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the minimum value of a single-precision floating-point strided\n    array using alternative indexing semantics.\n","base.strided.sminabs":"\nbase.strided.sminabs( N:integer, x:Float32Array, strideX:integer )\n    Computes the minimum absolute value of a single-precision floating-point\n    strided array.\n","base.strided.sminabs.ndarray":"\nbase.strided.sminabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the minimum absolute value of a single-precision floating-point\n    strided array using alternative indexing semantics.\n","base.strided.sminsorted":"\nbase.strided.sminsorted( N:integer, x:Float32Array, strideX:integer )\n    Computes the minimum value of a sorted single-precision floating-point\n    strided array.\n","base.strided.sminsorted.ndarray":"\nbase.strided.sminsorted.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the minimum value of a sorted single-precision floating-point\n    strided array using alternative indexing semantics.\n","base.strided.smskabs":"\nbase.strided.smskabs( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Computes the absolute value for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskabs.ndarray":"\nbase.strided.smskabs.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n  sy:integer, oy:integer )\n    Computes the absolute value for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n","base.strided.smskabs2":"\nbase.strided.smskabs2( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Computes the squared absolute value for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point\n    strided array `y`.\n","base.strided.smskabs2.ndarray":"\nbase.strided.smskabs2.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n  sy:integer, oy:integer )\n    Computes the squared absolute value for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point\n    strided array `y` using alternative indexing semantics.\n","base.strided.smskcbrt":"\nbase.strided.smskcbrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Computes the cube root for each element in a single-precision floating-point\n    strided array `x` according to a strided mask array and assigns the results\n    to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskcbrt.ndarray":"\nbase.strided.smskcbrt.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n  sy:integer, oy:integer )\n    Computes the cube root for each element in a single-precision floating-point\n    strided array `x` according to a strided mask array and assigns the results\n    to elements in a single-precision floating-point strided array `y` using\n    alternative indexing semantics.\n","base.strided.smskceil":"\nbase.strided.smskceil( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward positive infinity according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskceil.ndarray":"\nbase.strided.smskceil.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n  sy:integer, oy:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward positive infinity according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n","base.strided.smskdeg2rad":"\nbase.strided.smskdeg2rad( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Converts each element in a single-precision floating-point strided array `x`\n    from degrees to radians according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskdeg2rad.ndarray":"\nbase.strided.smskdeg2rad.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n  sy:integer, oy:integer )\n    Converts each element in a single-precision floating-point strided array `x`\n    from degrees to radians according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n","base.strided.smskfloor":"\nbase.strided.smskfloor( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward negative infinity according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskfloor.ndarray":"\nbase.strided.smskfloor.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n  sy:integer, oy:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward negative infinity according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n","base.strided.smskinv":"\nbase.strided.smskinv( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Computes the multiplicative inverse for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y`.\n","base.strided.smskinv.ndarray":"\nbase.strided.smskinv.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n  sy:integer, oy:integer )\n    Computes the multiplicative inverse for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y` using alternative indexing semantics.\n","base.strided.smskmap":"\nbase.strided.smskmap( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer, fcn:Function )\n    Applies a unary function to a single-precision floating-point strided input\n    array according to a strided mask array and assigns results to a single-\n    precision floating-point strided output array.\n","base.strided.smskmap.ndarray":"\nbase.strided.smskmap.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Uint8Array, sm:integer, om:integer, y:Float32Array, sy:integer, \n  oy:integer, fcn:Function )\n    Applies a unary function to a single-precision floating-point strided input\n    array according to a strided mask array and assigns results to a single-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n","base.strided.smskmap2":"\nbase.strided.smskmap2( N:integer, x:Float32Array, sx:integer, y:Float32Array, \n  sy:integer, m:Uint8Array, sm:integer, z:Float32Array, sz:integer, \n  fcn:Function )\n    Applies a binary function to single-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a single-\n    precision floating-point strided output array.\n","base.strided.smskmap2.ndarray":"\nbase.strided.smskmap2.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, y:Float32Array, sy:integer, oy:integer, m:Uint8Array, sm:integer, \n  om:integer, z:Float32Array, sz:integer, oz:integer, fcn:Function )\n    Applies a binary function to single-precision floating-point strided input\n    arrays according to a strided mask array and assigns results to a single-\n    precision floating-point strided output array using alternative indexing\n    semantics.\n","base.strided.smskmax":"\nbase.strided.smskmax( N:integer, x:Float32Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask.\n","base.strided.smskmax.ndarray":"\nbase.strided.smskmax.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n","base.strided.smskmin":"\nbase.strided.smskmin( N:integer, x:Float32Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask.\n","base.strided.smskmin.ndarray":"\nbase.strided.smskmin.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask and using alternative indexing semantics.\n","base.strided.smskramp":"\nbase.strided.smskramp( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Evaluates the ramp function for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`.\n","base.strided.smskramp.ndarray":"\nbase.strided.smskramp.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n  sy:integer, oy:integer )\n    Evaluates the ramp function for each element in a single-precision floating-\n    point strided array `x` according to a strided mask array and assigns the\n    results to elements in a single-precision floating-point strided array `y`\n    using alternative indexing semantics.\n","base.strided.smskrange":"\nbase.strided.smskrange( N:integer, x:Float32Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask.\n","base.strided.smskrange.ndarray":"\nbase.strided.smskrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask and using alternative indexing semantics.\n","base.strided.smskrsqrt":"\nbase.strided.smskrsqrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Computes the reciprocal square root for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y`.\n","base.strided.smskrsqrt.ndarray":"\nbase.strided.smskrsqrt.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n  sy:integer, oy:integer )\n    Computes the reciprocal square root for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y` using alternative indexing semantics.\n","base.strided.smsksqrt":"\nbase.strided.smsksqrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Computes the principal square root for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y`.\n","base.strided.smsksqrt.ndarray":"\nbase.strided.smsksqrt.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n  sy:integer, oy:integer )\n    Computes the principal square root for each element in a single-precision\n    floating-point strided array `x` according to a strided mask array and\n    assigns the results to elements in a single-precision floating-point strided\n    array `y` using alternative indexing semantics.\n","base.strided.smsktrunc":"\nbase.strided.smsktrunc( N:integer, x:Float32Array, sx:integer, m:Uint8Array, \n  sm:integer, y:Float32Array, sy:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward zero according to a strided mask array and assigns the results to\n    elements in a single-precision floating-point strided array `y`.\n","base.strided.smsktrunc.ndarray":"\nbase.strided.smsktrunc.ndarray( N:integer, x:Float32Array, sx:integer, \n  ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, \n  sy:integer, oy:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward zero according to a strided mask array and assigns the results to\n    elements in a single-precision floating-point strided array `y` using\n    alternative indexing semantics.\n","base.strided.snanmax":"\nbase.strided.snanmax( N:integer, x:Float32Array, strideX:integer )\n    Computes the maximum value of a single-precision floating-point strided\n    array, ignoring `NaN` values.\n","base.strided.snanmax.ndarray":"\nbase.strided.snanmax.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum value of a single-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanmaxabs":"\nbase.strided.snanmaxabs( N:integer, x:Float32Array, strideX:integer )\n    Computes the maximum absolute value of a single-precision floating-point\n    strided array, ignoring `NaN` values.\n","base.strided.snanmaxabs.ndarray":"\nbase.strided.snanmaxabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the maximum absolute value of a single-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n","base.strided.snanmean":"\nbase.strided.snanmean( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values.\n","base.strided.snanmean.ndarray":"\nbase.strided.snanmean.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanmeanors":"\nbase.strided.snanmeanors( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.snanmeanors.ndarray":"\nbase.strided.snanmeanors.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using ordinary recursive summation and\n    alternative indexing semantics.\n","base.strided.snanmeanpn":"\nbase.strided.snanmeanpn( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction\n    algorithm.\n","base.strided.snanmeanpn.ndarray":"\nbase.strided.snanmeanpn.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using a two-pass error correction algorithm\n    and alternative indexing semantics.\n","base.strided.snanmeanwd":"\nbase.strided.snanmeanwd( N:integer, x:Float32Array, stride:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm.\n","base.strided.snanmeanwd.ndarray":"\nbase.strided.snanmeanwd.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the arithmetic mean of a single-precision floating-point strided\n    array, ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n","base.strided.snanmin":"\nbase.strided.snanmin( N:integer, x:Float32Array, strideX:integer )\n    Computes the minimum value of a single-precision floating-point strided\n    array, ignoring `NaN` values.\n","base.strided.snanmin.ndarray":"\nbase.strided.snanmin.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the minimum value of a single-precision floating-point strided\n    array, ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanminabs":"\nbase.strided.snanminabs( N:integer, x:Float32Array, strideX:integer )\n    Computes the minimum absolute value of a single-precision floating-point\n    strided array, ignoring `NaN` values.\n","base.strided.snanminabs.ndarray":"\nbase.strided.snanminabs.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the minimum absolute value of a single-precision floating-point\n    strided array, ignoring `NaN` values and using alternative indexing\n    semantics.\n","base.strided.snanmskmax":"\nbase.strided.snanmskmax( N:integer, x:Float32Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask, ignoring `NaN` values.\n","base.strided.snanmskmax.ndarray":"\nbase.strided.snanmskmax.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the maximum value of a single-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n","base.strided.snanmskmin":"\nbase.strided.snanmskmin( N:integer, x:Float32Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask, ignoring `NaN` values.\n","base.strided.snanmskmin.ndarray":"\nbase.strided.snanmskmin.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the minimum value of a single-precision floating-point strided\n    array according to a mask, ignoring `NaN` values and using alternative\n    indexing semantics.\n","base.strided.snanmskrange":"\nbase.strided.snanmskrange( N:integer, x:Float32Array, strideX:integer, \n  mask:Uint8Array, strideMask:integer )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask, ignoring `NaN` values.\n","base.strided.snanmskrange.ndarray":"\nbase.strided.snanmskrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )\n    Computes the range of a single-precision floating-point strided array\n    according to a mask, ignoring `NaN` values and using alternative indexing\n    semantics.\n","base.strided.snanrange":"\nbase.strided.snanrange( N:integer, x:Float32Array, strideX:integer )\n    Computes the range of a single-precision floating-point strided array,\n    ignoring `NaN` values.\n","base.strided.snanrange.ndarray":"\nbase.strided.snanrange.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the range of a single-precision floating-point strided array,\n    ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanstdev":"\nbase.strided.snanstdev( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values.\n","base.strided.snanstdev.ndarray":"\nbase.strided.snanstdev.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and alternative indexing semantics.\n","base.strided.snanstdevch":"\nbase.strided.snanstdevch( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.snanstdevch.ndarray":"\nbase.strided.snanstdevch.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n","base.strided.snanstdevpn":"\nbase.strided.snanstdevpn( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.snanstdevpn.ndarray":"\nbase.strided.snanstdevpn.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n","base.strided.snanstdevtk":"\nbase.strided.snanstdevtk( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.snanstdevtk.ndarray":"\nbase.strided.snanstdevtk.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n","base.strided.snanstdevwd":"\nbase.strided.snanstdevwd( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using Welford's algorithm.\n","base.strided.snanstdevwd.ndarray":"\nbase.strided.snanstdevwd.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using Welford's algorithm and alternative\n    indexing semantics.\n","base.strided.snanstdevyc":"\nbase.strided.snanstdevyc( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass algorithm proposed by\n    Youngs and Cramer.\n","base.strided.snanstdevyc.ndarray":"\nbase.strided.snanstdevyc.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array ignoring `NaN` values and using a one-pass algorithm proposed by\n    Youngs and Cramer and alternative indexing semantics.\n","base.strided.snansum":"\nbase.strided.snansum( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values.\n","base.strided.snansum.ndarray":"\nbase.strided.snansum.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snansumkbn":"\nbase.strided.snansumkbn( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm.\n","base.strided.snansumkbn.ndarray":"\nbase.strided.snansumkbn.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using an improved Kahan–Babuška algorithm and\n    alternative indexing semantics.\n","base.strided.snansumkbn2":"\nbase.strided.snansumkbn2( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm.\n","base.strided.snansumkbn2.ndarray":"\nbase.strided.snansumkbn2.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using a second-order iterative Kahan–Babuška\n    algorithm and alternative indexing semantics.\n","base.strided.snansumors":"\nbase.strided.snansumors( N:integer, x:Float32Array, strideX:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation.\n","base.strided.snansumors.ndarray":"\nbase.strided.snansumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using ordinary recursive summation and alternative\n    indexing semantics.\n","base.strided.snansumpw":"\nbase.strided.snansumpw( N:integer, x:Float32Array, strideX:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation.\n","base.strided.snansumpw.ndarray":"\nbase.strided.snansumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of single-precision floating-point strided array elements,\n    ignoring `NaN` values and using pairwise summation and alternative indexing\n    semantics.\n","base.strided.snanvariance":"\nbase.strided.snanvariance( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values.\n","base.strided.snanvariance.ndarray":"\nbase.strided.snanvariance.ndarray( N:integer, correction:number, \n  x:Float32Array, stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using alternative indexing semantics.\n","base.strided.snanvariancech":"\nbase.strided.snanvariancech( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass trial mean algorithm.\n","base.strided.snanvariancech.ndarray":"\nbase.strided.snanvariancech.ndarray( N:integer, correction:number, \n  x:Float32Array, stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass trial mean algorithm and\n    alternative indexing semantics.\n","base.strided.snanvariancepn":"\nbase.strided.snanvariancepn( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a two-pass algorithm.\n","base.strided.snanvariancepn.ndarray":"\nbase.strided.snanvariancepn.ndarray( N:integer, correction:number, \n  x:Float32Array, stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a two-pass algorithm and alternative\n    indexing semantics.\n","base.strided.snanvariancetk":"\nbase.strided.snanvariancetk( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass textbook algorithm.\n","base.strided.snanvariancetk.ndarray":"\nbase.strided.snanvariancetk.ndarray( N:integer, correction:number, \n  x:Float32Array, stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass textbook algorithm and\n    alternative indexing semantics.\n","base.strided.snanvariancewd":"\nbase.strided.snanvariancewd( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using Welford's algorithm.\n","base.strided.snanvariancewd.ndarray":"\nbase.strided.snanvariancewd.ndarray( N:integer, correction:number, \n  x:Float32Array, stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using Welford's algorithm and alternative indexing\n    semantics.\n","base.strided.snanvarianceyc":"\nbase.strided.snanvarianceyc( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n    Cramer.\n","base.strided.snanvarianceyc.ndarray":"\nbase.strided.snanvarianceyc.ndarray( N:integer, correction:number, \n  x:Float32Array, stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    ignoring `NaN` values and using a one-pass algorithm proposed by Youngs and\n    Cramer and alternative indexing semantics.\n","base.strided.snrm2":"\nbase.strided.snrm2( N:integer, x:Float32Array, stride:integer )\n    Computes the L2-norm of a single-precision floating-point vector.\n","base.strided.snrm2.ndarray":"\nbase.strided.snrm2.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the L2-norm of a single-precision floating-point vector using\n    alternative indexing semantics.\n","base.strided.sramp":"\nbase.strided.sramp( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer )\n    Evaluates the ramp function for each element in a single-precision floating-\n    point strided array `x` and assigns the results to elements in a single-\n    precision floating-point strided array `y`.\n","base.strided.sramp.ndarray":"\nbase.strided.sramp.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Evaluates the ramp function for each element in a single-precision floating-\n    point strided array `x` and assigns the results to elements in a single-\n    precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.srange":"\nbase.strided.srange( N:integer, x:Float32Array, strideX:integer )\n    Computes the range of a single-precision floating-point strided array.\n","base.strided.srange.ndarray":"\nbase.strided.srange.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the range of a single-precision floating-point strided array using\n    alternative indexing semantics.\n","base.strided.srev":"\nbase.strided.srev( N:integer, x:Float32Array, stride:integer )\n    Reverses a single-precision floating-point strided array in-place.\n","base.strided.srev.ndarray":"\nbase.strided.srev.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Reverses a single-precision floating-point strided array in-place using\n    alternative indexing semantics.\n","base.strided.srsqrt":"\nbase.strided.srsqrt( N:integer, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Computes the reciprocal square root for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y`.\n","base.strided.srsqrt.ndarray":"\nbase.strided.srsqrt.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the reciprocal square root for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.sscal":"\nbase.strided.sscal( N:integer, alpha:number, x:Float32Array, stride:integer )\n    Multiplies a single-precision floating-point vector `x` by a constant\n    `alpha`.\n","base.strided.sscal.ndarray":"\nbase.strided.sscal.ndarray( N:integer, alpha:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Multiplies a single-precision floating-point vector `x` by a constant\n    `alpha` using alternative indexing semantics.\n","base.strided.ssort2hp":"\nbase.strided.ssort2hp( N:integer, order:number, x:Float32Array, \n  strideX:integer, y:Float32Array, strideY:integer )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using heapsort.\n","base.strided.ssort2hp.ndarray":"\nbase.strided.ssort2hp.ndarray( N:integer, order:number, x:Float32Array, \n  strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n  offsetY:integer )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using heapsort and alternative\n    indexing semantics.\n","base.strided.ssort2ins":"\nbase.strided.ssort2ins( N:integer, order:number, x:Float32Array, \n  strideX:integer, y:Float32Array, strideY:integer )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using insertion sort.\n","base.strided.ssort2ins.ndarray":"\nbase.strided.ssort2ins.ndarray( N:integer, order:number, x:Float32Array, \n  strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n  offsetY:integer )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using insertion sort and\n    alternative indexing semantics.\n","base.strided.ssort2sh":"\nbase.strided.ssort2sh( N:integer, order:number, x:Float32Array, \n  strideX:integer, y:Float32Array, strideY:integer )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using Shellsort.\n","base.strided.ssort2sh.ndarray":"\nbase.strided.ssort2sh.ndarray( N:integer, order:number, x:Float32Array, \n  strideX:integer, offsetX:integer, y:Float32Array, strideY:integer, \n  offsetY:integer )\n    Simultaneously sorts two single-precision floating-point strided arrays\n    based on the sort order of the first array using Shellsort and alternative\n    indexing semantics.\n","base.strided.ssorthp":"\nbase.strided.ssorthp( N:integer, order:number, x:Float32Array, stride:integer )\n    Sorts a single-precision floating-point strided array using heapsort.\n","base.strided.ssorthp.ndarray":"\nbase.strided.ssorthp.ndarray( N:integer, order:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Sorts a single-precision floating-point strided array using heapsort and\n    alternative indexing semantics.\n","base.strided.ssortins":"\nbase.strided.ssortins( N:integer, order:number, x:Float32Array, stride:integer )\n    Sorts a single-precision floating-point strided array using insertion sort.\n","base.strided.ssortins.ndarray":"\nbase.strided.ssortins.ndarray( N:integer, order:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Sorts a single-precision floating-point strided array using insertion sort\n    and alternative indexing semantics.\n","base.strided.ssortsh":"\nbase.strided.ssortsh( N:integer, order:number, x:Float32Array, stride:integer )\n    Sorts a single-precision floating-point strided array using Shellsort.\n","base.strided.ssortsh.ndarray":"\nbase.strided.ssortsh.ndarray( N:integer, order:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Sorts a single-precision floating-point strided array using Shellsort and\n    alternative indexing semantics.\n","base.strided.ssqrt":"\nbase.strided.ssqrt( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer )\n    Computes the principal square root for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y`.\n","base.strided.ssqrt.ndarray":"\nbase.strided.ssqrt.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Computes the principal square root for each element in a single-precision\n    floating-point strided array `x` and assigns the results to elements in a\n    single-precision floating-point strided array `y` using alternative indexing\n    semantics.\n","base.strided.sstdev":"\nbase.strided.sstdev( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array.\n","base.strided.sstdev.ndarray":"\nbase.strided.sstdev.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using alternative indexing semantics.\n","base.strided.sstdevch":"\nbase.strided.sstdevch( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm.\n","base.strided.sstdevch.ndarray":"\nbase.strided.sstdevch.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass trial mean algorithm and alternative indexing\n    semantics.\n","base.strided.sstdevpn":"\nbase.strided.sstdevpn( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a two-pass algorithm.\n","base.strided.sstdevpn.ndarray":"\nbase.strided.sstdevpn.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a two-pass algorithm and alternative indexing semantics.\n","base.strided.sstdevtk":"\nbase.strided.sstdevtk( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass textbook algorithm.\n","base.strided.sstdevtk.ndarray":"\nbase.strided.sstdevtk.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass textbook algorithm and alternative indexing\n    semantics.\n","base.strided.sstdevwd":"\nbase.strided.sstdevwd( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using Welford's algorithm.\n","base.strided.sstdevwd.ndarray":"\nbase.strided.sstdevwd.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using Welford's algorithm and alternative indexing semantics.\n","base.strided.sstdevyc":"\nbase.strided.sstdevyc( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.sstdevyc.ndarray":"\nbase.strided.sstdevyc.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a single-precision floating-point strided\n    array using a one-pass algorithm proposed by Youngs and Cramer and\n    alternative indexing semantics.\n","base.strided.ssum":"\nbase.strided.ssum( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of single-precision floating-point strided array elements.\n","base.strided.ssum.ndarray":"\nbase.strided.ssum.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using alternative indexing semantics.\n","base.strided.ssumkbn":"\nbase.strided.ssumkbn( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm.\n","base.strided.ssumkbn.ndarray":"\nbase.strided.ssumkbn.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using an improved Kahan–Babuška algorithm and alternative indexing\n    semantics.\n","base.strided.ssumkbn2":"\nbase.strided.ssumkbn2( N:integer, x:Float32Array, stride:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm.\n","base.strided.ssumkbn2.ndarray":"\nbase.strided.ssumkbn2.ndarray( N:integer, x:Float32Array, stride:integer, \n  offset:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using a second-order iterative Kahan–Babuška algorithm and alternative\n    indexing semantics.\n","base.strided.ssumors":"\nbase.strided.ssumors( N:integer, x:Float32Array, strideX:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using ordinary recursive summation.\n","base.strided.ssumors.ndarray":"\nbase.strided.ssumors.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using ordinary recursive summation and alternative indexing semantics.\n","base.strided.ssumpw":"\nbase.strided.ssumpw( N:integer, x:Float32Array, strideX:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation.\n","base.strided.ssumpw.ndarray":"\nbase.strided.ssumpw.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer )\n    Computes the sum of single-precision floating-point strided array elements\n    using pairwise summation and alternative indexing semantics.\n","base.strided.sswap":"\nbase.strided.sswap( N:integer, x:Float32Array, strideX:integer, y:Float32Array, \n  strideY:integer )\n    Interchanges two single-precision floating-point vectors.\n","base.strided.sswap.ndarray":"\nbase.strided.sswap.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Interchanges two single-precision floating-point vectors using alternative\n    indexing semantics.\n","base.strided.stdev":"\nbase.strided.stdev( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array.\n","base.strided.stdev.ndarray":"\nbase.strided.stdev.ndarray( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a strided array using alternative\n    indexing semantics.\n","base.strided.stdevch":"\nbase.strided.stdevch( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array using a one-pass trial\n    mean algorithm.\n","base.strided.stdevch.ndarray":"\nbase.strided.stdevch.ndarray( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a strided array using a one-pass trial\n    mean algorithm and alternative indexing semantics.\n","base.strided.stdevpn":"\nbase.strided.stdevpn( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array using a two-pass\n    algorithm.\n","base.strided.stdevpn.ndarray":"\nbase.strided.stdevpn.ndarray( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a strided array using a two-pass\n    algorithm and alternative indexing semantics.\n","base.strided.stdevtk":"\nbase.strided.stdevtk( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array using a one-pass textbook\n    algorithm.\n","base.strided.stdevtk.ndarray":"\nbase.strided.stdevtk.ndarray( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a strided array using a one-pass textbook\n    algorithm and alternative indexing semantics.\n","base.strided.stdevwd":"\nbase.strided.stdevwd( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array using Welford's\n    algorithm.\n","base.strided.stdevwd.ndarray":"\nbase.strided.stdevwd.ndarray( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a strided array using Welford's algorithm\n    and alternative indexing semantics.\n","base.strided.stdevyc":"\nbase.strided.stdevyc( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the standard deviation of a strided array using a one-pass\n    algorithm proposed by Youngs and Cramer.\n","base.strided.stdevyc.ndarray":"\nbase.strided.stdevyc.ndarray( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer, offset:integer )\n    Computes the standard deviation of a strided array using a one-pass\n    algorithm proposed by Youngs and Cramer and alternative indexing semantics.\n","base.strided.strunc":"\nbase.strided.strunc( N:integer, x:Float32Array, strideX:integer, \n  y:Float32Array, strideY:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward zero and assigns the results to elements in a single-precision\n    floating-point strided array `y`.\n","base.strided.strunc.ndarray":"\nbase.strided.strunc.ndarray( N:integer, x:Float32Array, strideX:integer, \n  offsetX:integer, y:Float32Array, strideY:integer, offsetY:integer )\n    Rounds each element in a single-precision floating-point strided array `x`\n    toward zero and assigns the results to elements in a single-precision\n    floating-point strided array `y` using alternative indexing semantics.\n","base.strided.svariance":"\nbase.strided.svariance( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array.\n","base.strided.svariance.ndarray":"\nbase.strided.svariance.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using alternative indexing semantics.\n","base.strided.svariancech":"\nbase.strided.svariancech( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass trial mean algorithm.\n","base.strided.svariancech.ndarray":"\nbase.strided.svariancech.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass trial mean algorithm and alternative indexing semantics.\n","base.strided.svariancepn":"\nbase.strided.svariancepn( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using a two-pass algorithm.\n","base.strided.svariancepn.ndarray":"\nbase.strided.svariancepn.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using a two-pass algorithm and alternative indexing semantics.\n","base.strided.svariancetk":"\nbase.strided.svariancetk( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass textbook algorithm.\n","base.strided.svariancetk.ndarray":"\nbase.strided.svariancetk.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass textbook algorithm and alternative indexing semantics.\n","base.strided.svariancewd":"\nbase.strided.svariancewd( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using Welford's algorithm.\n","base.strided.svariancewd.ndarray":"\nbase.strided.svariancewd.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using Welford's algorithm and alternative indexing semantics.\n","base.strided.svarianceyc":"\nbase.strided.svarianceyc( N:integer, correction:number, x:Float32Array, \n  stride:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass algorithm proposed by Youngs and Cramer.\n","base.strided.svarianceyc.ndarray":"\nbase.strided.svarianceyc.ndarray( N:integer, correction:number, x:Float32Array, \n  stride:integer, offset:integer )\n    Computes the variance of a single-precision floating-point strided array\n    using a one-pass algorithm proposed by Youngs and Cramer and alternative\n    indexing semantics.\n","base.strided.ternary":"\nbase.strided.ternary( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  fcn:Function )\n    Applies a ternary callback to strided input array elements and assigns\n    results to elements in a strided output array.\n","base.strided.ternary.ndarray":"\nbase.strided.ternary.ndarray( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  offsets:ArrayLikeObject<integer>, fcn:Function )\n    Applies a ternary callback to strided input array elements and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n","base.strided.unary":"\nbase.strided.unary( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  fcn:Function )\n    Applies a unary callback to elements in a strided input array and assigns\n    results to elements in a strided output array.\n","base.strided.unary.ndarray":"\nbase.strided.unary.ndarray( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  offsets:ArrayLikeObject<integer>, fcn:Function )\n    Applies a unary callback to elements in a strided input array and assigns\n    results to elements in a strided output array using alternative indexing\n    semantics.\n","base.strided.unaryBy":"\nbase.strided.unaryBy( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  fcn:Function, clbk:Function[, thisArg:any] )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array.\n","base.strided.unaryBy.ndarray":"\nbase.strided.unaryBy.ndarray( arrays:ArrayLikeObject<ArrayLikeObject>, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  offsets:ArrayLikeObject<integer>, fcn:Function, clbk:Function[, thisArg:any] )\n    Applies a unary function to each element retrieved from a strided input\n    array according to a callback function and assigns results to a strided\n    output array using alternative indexing semantics.\n","base.strided.unaryDtypeSignatures":"\nbase.strided.unaryDtypeSignatures( dtypes1:ArrayLike<any>, \n  dtypes2:ArrayLike<any>[, options:Object] )\n    Generates a list of unary interface signatures from strided array data\n    types.\n","base.strided.unarySignatureCallbacks":"\nbase.strided.unarySignatureCallbacks( table:Object, signatures:ArrayLike<any> )\n    Assigns callbacks to unary interfaces according to type promotion rules.\n","base.strided.variance":"\nbase.strided.variance( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array.\n","base.strided.variance.ndarray":"\nbase.strided.variance.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array using alternative indexing\n    semantics.\n","base.strided.variancech":"\nbase.strided.variancech( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array using a one-pass trial mean\n    algorithm.\n","base.strided.variancech.ndarray":"\nbase.strided.variancech.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array using a one-pass trial mean\n    algorithm and alternative indexing semantics.\n","base.strided.variancepn":"\nbase.strided.variancepn( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array using a two-pass algorithm.\n","base.strided.variancepn.ndarray":"\nbase.strided.variancepn.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array using a two-pass algorithm and\n    alternative indexing semantics.\n","base.strided.variancetk":"\nbase.strided.variancetk( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array using a one-pass textbook\n    algorithm.\n","base.strided.variancetk.ndarray":"\nbase.strided.variancetk.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array using a one-pass textbook algorithm\n    and alternative indexing semantics.\n","base.strided.variancewd":"\nbase.strided.variancewd( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array using Welford's algorithm.\n","base.strided.variancewd.ndarray":"\nbase.strided.variancewd.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array using Welford's algorithm and\n    alternative indexing semantics.\n","base.strided.varianceyc":"\nbase.strided.varianceyc( N:integer, correction:number, x:Array|TypedArray, \n  stride:integer )\n    Computes the variance of a strided array using a one-pass algorithm proposed\n    by Youngs and Cramer.\n","base.strided.varianceyc.ndarray":"\nbase.strided.varianceyc.ndarray( N:integer, correction:number, \n  x:Array|TypedArray, stride:integer, offset:integer )\n    Computes the variance of a strided array using a one-pass algorithm proposed\n    by Youngs and Cramer and alternative indexing semantics.\n","base.strided.zmap":"\nbase.strided.zmap( N:integer, x:Complex128Array, strideX:integer, \n  y:Complex128Array, strideY:integer, fcn:Function )\n    Applies a unary function to a double-precision complex floating-point\n    strided input array and assigns results to a double-precision complex\n    floating-point strided output array.\n","base.strided.zmap.ndarray":"\nbase.strided.zmap.ndarray( N:integer, x:Complex128Array, strideX:integer, \n  offsetX:integer, y:Complex128Array, strideY:integer, offsetY:integer, \n  fcn:Function )\n    Applies a unary function to a double-precision complex floating-point\n    strided input array and assigns results to a double-precision complex\n    floating-point strided output array using alternative indexing semantics.\n","base.str2multislice":"\nbase.str2multislice( str:string )\n    Parses a string-serialized MultiSlice object.\n","base.str2slice":"\nbase.str2slice( str:string )\n    Parses a string-serialized Slice object.\n","base.sub":"\nbase.sub( x:number, y:number )\n    Subtracts two double-precision floating-point numbers `x` and `y`.\n","base.subf":"\nbase.subf( x:number, y:number )\n    Subtracts two single-precision floating-point numbers `x` and `y`.\n","base.sumSeries":"\nbase.sumSeries( generator:Function[, options:Object] )\n    Sum the elements of the series given by the supplied function.\n","base.tan":"\nbase.tan( x:number )\n    Computes the tangent of a number.\n","base.tand":"\nbase.tand( x:number )\n    Computes the tangent of an angle measured in degrees.\n","base.tanh":"\nbase.tanh( x:number )\n    Computes the hyperbolic tangent of a double-precision floating-point number.\n","base.toBinaryString":"\nbase.toBinaryString( x:number )\n    Returns a string giving the literal bit representation of a double-precision\n    floating-point number.\n","base.toBinaryStringf":"\nbase.toBinaryStringf( x:float )\n    Returns a string giving the literal bit representation of a single-precision\n    floating-point number.\n","base.toBinaryStringUint8":"\nbase.toBinaryStringUint8( x:integer )\n    Returns a string giving the literal bit representation of an unsigned 8-bit\n    integer.\n","base.toBinaryStringUint16":"\nbase.toBinaryStringUint16( x:integer )\n    Returns a string giving the literal bit representation of an unsigned 16-bit\n    integer.\n","base.toBinaryStringUint32":"\nbase.toBinaryStringUint32( x:integer )\n    Returns a string giving the literal bit representation of an unsigned 32-bit\n    integer.\n","base.toWordf":"\nbase.toWordf( x:float )\n    Returns an unsigned 32-bit integer corresponding to the IEEE 754 binary\n    representation of a single-precision floating-point number.\n","base.toWords":"\nbase.toWords( x:number )\n    Splits a double-precision floating-point number into a higher order word\n    (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer).\n","base.toWords.assign":"\nbase.toWords.assign( x:number, out:Array|TypedArray|Object, stride:integer, \n  offset:integer )\n    Splits a double-precision floating-point number into a higher order word\n    (unsigned 32-bit integer) and a lower order word (unsigned 32-bit integer)\n    and assigns results to a provided output array.\n","base.transpose":"\nbase.transpose( x:ndarray )\n    Transposes a matrix (or a stack of matrices).\n","base.tribonacci":"\nbase.tribonacci( n:integer )\n    Computes the nth Tribonacci number.\n","base.trigamma":"\nbase.trigamma( x:number )\n    Evaluates the trigamma function.\n","base.trim":"\nbase.trim( str:string )\n    Trims whitespace from the beginning and end of a `string`.\n","base.trunc":"\nbase.trunc( x:number )\n    Rounds a double-precision floating-point number toward zero.\n","base.trunc2":"\nbase.trunc2( x:number )\n    Rounds a numeric value to the nearest power of two toward zero.\n","base.trunc10":"\nbase.trunc10( x:number )\n    Rounds a numeric value to the nearest power of ten toward zero.\n","base.truncateMiddle":"\nbase.truncateMiddle( str:string, len:integer, seq:string )\n    Truncates the middle UTF-16 code units of a string to return a string\n    having a specified length.\n","base.truncb":"\nbase.truncb( x:number, n:integer, b:integer )\n    Rounds a numeric value to the nearest multiple of `b^n` toward zero.\n","base.truncf":"\nbase.truncf( x:number )\n    Rounds a single-precision floating-point number toward zero.\n","base.truncn":"\nbase.truncn( x:number, n:integer )\n    Rounds a numeric value to the nearest multiple of `10^n` toward zero.\n","base.truncsd":"\nbase.truncsd( x:number, n:integer, b:integer )\n    Rounds a numeric value to the nearest number toward zero with `n`\n    significant figures.\n","base.uint32ToInt32":"\nbase.uint32ToInt32( x:integer )\n    Converts an unsigned 32-bit integer to a signed 32-bit integer.\n","base.umul":"\nbase.umul( a:integer, b:integer )\n    Performs C-like multiplication of two unsigned 32-bit integers.\n","base.umuldw":"\nbase.umuldw( a:integer, b:integer )\n    Multiplies two unsigned 32-bit integers and returns an array of two unsigned\n    32-bit integers which represents the unsigned 64-bit integer product.\n","base.umuldw.assign":"\nbase.umuldw.assign( a:integer, b:integer, out:Array|TypedArray|Object, \n  stride:integer, offset:integer )\n    Multiplies two unsigned 32-bit integers and assigns results representing\n    the unsigned 64-bit integer product to a provided output array.\n","base.uncapitalize":"\nbase.uncapitalize( str:string )\n    Lowercases the first character of a string.\n","base.uppercase":"\nbase.uppercase( str:string )\n    Converts a string to uppercase.\n","base.vercos":"\nbase.vercos( x:number )\n    Computes the versed cosine.\n","base.versin":"\nbase.versin( x:number )\n    Computes the versed sine.\n","base.wrap":"\nbase.wrap( v:number, min:number, max:number )\n    Wraps a value on the half-open interval `[min,max)`.\n","base.xlog1py":"\nbase.xlog1py( x:number, y:number )\n    Computes `x * ln(y+1)` so that the result is `0` if `x = 0`.\n","base.xlogy":"\nbase.xlogy( x:number, y:number )\n    Computes `x * ln(y)` so that the result is `0` if `x = 0`.\n","base.zeta":"\nbase.zeta( s:number )\n    Evaluates the Riemann zeta function as a function of a real variable `s`.\n","BERNDT_CPS_WAGES_1985":"\nBERNDT_CPS_WAGES_1985()\n    Returns a random sample of 534 workers from the Current Population Survey\n    (CPS) from 1985, including their wages and and other characteristics.\n","bifurcate":"\nbifurcate( collection:Array|TypedArray|Object, [options:Object,] \n  filter:Array|TypedArray|Object )\n    Splits values into two groups.\n","bifurcateBy":"\nbifurcateBy( collection:Array|TypedArray|Object, [options:Object,] \n  predicate:Function )\n    Splits values into two groups according to a predicate function.\n","bifurcateByAsync":"\nbifurcateByAsync( collection:Array|TypedArray|Object, [options:Object,] \n  predicate:Function, done:Function )\n    Splits values into two groups according to a predicate function.\n","bifurcateByAsync.factory":"\nbifurcateByAsync.factory( [options:Object,] predicate:Function )\n    Returns a function which splits values into two groups according to an\n    predicate function.\n","bifurcateIn":"\nbifurcateIn( obj:Object|Array|TypedArray, [options:Object,] predicate:Function )\n    Splits values into two groups according to a predicate function.\n","bifurcateOwn":"\nbifurcateOwn( obj:Object|Array|TypedArray, [options:Object,] \n  predicate:Function )\n    Splits values into two groups according to a predicate function.\n","BigInt":"\nBigInt( value:integer|string )\n    Returns a BigInt.\n","binomialTest":"\nbinomialTest( x:(number|Array[, n:Array<number>][, options:Object] )\n    Computes an exact test for the success probability in a Bernoulli\n    experiment.\n","Boolean":"\nBoolean( value:any )\n    Returns a boolean.\n","Boolean.prototype.toString":"\nBoolean.prototype.toString()\n    Returns a string representing the `Boolean` object.\n","Boolean.prototype.valueOf":"\nBoolean.prototype.valueOf()\n    Returns the primitive value of a `Boolean` object.\n","BooleanArray":"\nBooleanArray()\n    A Boolean array.\n\nBooleanArray( length:integer )\n    Creates a boolean array having a specified length.\n\nBooleanArray( booleanarray:BooleanArray )\n    Creates a boolean array from another boolean array.\n\nBooleanArray( typedarray:TypedArray )\n    Creates a boolean array from a typed array.\n\nBooleanArray( obj:Object )\n    Creates a boolean array from an array-like object or iterable.\n\nBooleanArray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a boolean array view of an ArrayBuffer.\n","BooleanArray.from":"\nBooleanArray.from( src:ArrayLike|Iterable[, clbk:Function[, thisArg:Any]] )\n    Creates a new boolean array from an array-like object or an iterable.\n","BooleanArray.of":"\nBooleanArray.of( element0:bool[, element1:bool[, ...elementN:bool]] )\n    Creates a new boolean array from a variable number of arguments.\n","BooleanArray.BYTES_PER_ELEMENT":"\nBooleanArray.BYTES_PER_ELEMENT\n    The size of each array element in bytes.\n","BooleanArray.name":"\nBooleanArray.name\n    Typed array constructor name.\n","BooleanArray.prototype.buffer":"\nBooleanArray.prototype.buffer\n    Pointer to the underlying data buffer.\n","BooleanArray.prototype.byteLength":"\nBooleanArray.prototype.byteLength\n    Size of the array in bytes.\n","BooleanArray.prototype.byteOffset":"\nBooleanArray.prototype.byteOffset\n    Offset (in bytes) of the array from the start of its underlying\n    ArrayBuffer.\n","BooleanArray.prototype.BYTES_PER_ELEMENT":"\nBooleanArray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element.\n","BooleanArray.prototype.length":"\nBooleanArray.prototype.length\n    The number of array elements.\n","BooleanArray.prototype.at":"\nBooleanArray.prototype.at( i:integer )\n    Returns an array element located at integer position (index) `i`, with\n    support for noth nonnegative and negative integer positions.\n","BooleanArray.prototype.copyWithin":"\nBooleanArray.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","BooleanArray.prototype.entries":"\nBooleanArray.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","BooleanArray.prototype.every":"\nBooleanArray.prototype.every( predicate:Function[, thisArg:Any] )\n    Returns a boolean indicating whether all elements in the array pass a test.\n","BooleanArray.prototype.fill":"\nBooleanArray.prototype.fill( value:boolean[, start:integer[, end:integer]] )\n    Returns a modified typed array filled with a fill value.\n","BooleanArray.prototype.filter":"\nBooleanArray.prototype.filter( predicate:Function[, thisArg:Any] )\n    Returns a new array containing the elements of an array which pass a test\n    implemented by a predicate function.\n","BooleanArray.prototype.find":"\nBooleanArray.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first element in an array for which a predicate function returns\n    a truthy value.\n","BooleanArray.prototype.findIndex":"\nBooleanArray.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first element in an array for which a predicate\n    function returns a truthy value.\n","BooleanArray.prototype.findLast":"\nBooleanArray.prototype.findLast( predicate:Function[, thisArg:Any] )\n    Returns the last element in an array for which a predicate function returns\n    a truthy value.\n","BooleanArray.prototype.findLastIndex":"\nBooleanArray.prototype.findLastIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the last element in an array for which a predicate\n    function returns a truthy value.\n","BooleanArray.prototype.forEach":"\nBooleanArray.prototype.forEach( clbk:Function[, thisArg:Any] )\n    Invokes a function once for each array element.\n","BooleanArray.prototype.get":"\nBooleanArray.prototype.get( i:integer )\n    Returns an array element located at integer position (index) `i`.\n","BooleanArray.prototype.includes":"\nBooleanArray.prototype.includes( searchElement:boolean[, fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a provided value.\n","BooleanArray.prototype.indexOf":"\nBooleanArray.prototype.indexOf( searchElement:boolean[, fromIndex:integer] )\n    Returns the first index at which a given element can be found.\n","BooleanArray.prototype.join":"\nBooleanArray.prototype.join( [separator:string] )\n    Returns a new string by concatenating all array elements separated by a\n    separator string.\n","BooleanArray.prototype.keys":"\nBooleanArray.prototype.keys()\n    Returns an iterator for iterating over each index key in a typed array.\n","BooleanArray.prototype.lastIndexOf":"\nBooleanArray.prototype.lastIndexOf( searchElement:boolean[, fromIndex:integer] )\n    Returns the last index at which a given element can be found.\n","BooleanArray.prototype.map":"\nBooleanArray.prototype.map( clbk:Function[, thisArg:Any] )\n    Returns a new array with each element being the result of a provided\n    callback function.\n","BooleanArray.prototype.reduce":"\nBooleanArray.prototype.reduce( reducerFn:Function[, initialValue:any] )\n    Applies a provided function to each element of the array, in order, passing\n    in the return value from the calculation on the preceding element and\n    returning the accumulated result upon completion.\n","BooleanArray.prototype.reduceRight":"\nBooleanArray.prototype.reduceRight( reducerFn:Function[, initialValue:any] )\n    Applies a provided function to each element of the array, in reverse order,\n    passing in the return value from the calculation on the preceding element\n    and returning the accumulated result upon completion.\n","BooleanArray.prototype.reverse":"\nBooleanArray.prototype.reverse()\n    Reverses the array *in-place*.\n","BooleanArray.prototype.set":"\nBooleanArray.prototype.set( v:bool|BooleanArray|ArrayLikeObject[, i:integer] )\n    Sets one or more array elements.\n","BooleanArray.prototype.slice":"\nBooleanArray.prototype.slice( [start:integer[, end:integer]] )\n    Copies a portion of a typed array to a new typed array.\n","BooleanArray.prototype.some":"\nBooleanArray.prototype.some( predicate:Function[, thisArg:Any] )\n    Returns a boolean indicating whether at least one element passes a test.\n","BooleanArray.prototype.sort":"\nBooleanArray.prototype.sort( [compareFunction:Function] )\n    Sorts an array in-place.\n","BooleanArray.prototype.subarray":"\nBooleanArray.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array view over the same underlying `ArrayBuffer` and\n    with the same underlying data type as the host array.\n","BooleanArray.prototype.toLocaleString":"\nBooleanArray.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n","BooleanArray.prototype.toReversed":"\nBooleanArray.prototype.toReversed()\n    Returns a new typed array containing the elements in reversed order.\n","BooleanArray.prototype.toSorted":"\nBooleanArray.prototype.toSorted( [compareFunction:Function] )\n    Returns a new typed array containing the elements in sorted order.\n","BooleanArray.prototype.toString":"\nBooleanArray.prototype.toString()\n    Serializes an array as a string.\n","BooleanArray.prototype.values":"\nBooleanArray.prototype.values()\n    Returns an iterator for iterating over each value in a typed array.\n","BooleanArray.prototype.with":"\nBooleanArray.prototype.with( index, value )\n    Returns a new typed array with the element at a provided index replaced\n    with a provided value.\n","broadcastArray":"\nbroadcastArray( x:ndarray, shape:ArrayLikeObject )\n    Broadcasts an ndarray to a specified shape.\n","broadcastArrays":"\nbroadcastArrays( ...arrays:ndarray|ArrayLikeObject<ndarray> )\n    Broadcasts ndarrays to a common shape.\n","Buffer":"\nBuffer\n\nBuffer( size:integer )\n    Allocates a buffer having a specified number of bytes.\n\nBuffer( buffer:Buffer )\n    Copies buffer data to a new Buffer instance.\n\nBuffer( array:Array )\n    Allocates a buffer using an array of octets.\n\nBuffer( str:string[, encoding:string] )\n    Allocates a buffer containing a provided string.\n","buffer2json":"\nbuffer2json( buffer:Buffer )\n    Returns a JSON representation of a buffer.\n","BYTE_ORDER":"\nBYTE_ORDER\n    Platform byte order.\n","camelcase":"\ncamelcase( str:string )\n    Converts a string to camel case.\n","capitalize":"\ncapitalize( str:string )\n    Capitalizes the first character in a string.\n","capitalizeKeys":"\ncapitalizeKeys( obj:Object )\n    Converts the first letter of each object key to uppercase.\n","CATALAN":"\nCATALAN\n    Catalan's constant.\n","CBRT_EPS":"\nCBRT_EPS\n    Cube root of double-precision floating-point epsilon.\n","CDC_NCHS_US_BIRTHS_1969_1988":"\nCDC_NCHS_US_BIRTHS_1969_1988()\n    Returns US birth data from 1969 to 1988, as provided by the Center for\n    Disease Control and Prevention's National Center for Health Statistics.\n","CDC_NCHS_US_BIRTHS_1994_2003":"\nCDC_NCHS_US_BIRTHS_1994_2003()\n    Returns US birth data from 1994 to 2003, as provided by the Center for\n    Disease Control and Prevention's National Center for Health Statistics.\n","CDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013":"\nCDC_NCHS_US_INFANT_MORTALITY_BW_1915_2013()\n    Returns US infant mortality data, by race, from 1915 to 2013, as provided by\n    the Center for Disease Control and Prevention's National Center for Health\n    Statistics.\n","chdir":"\nchdir( path:string )\n    Changes the current working directory.\n","chi2gof":"\nchi2gof( x:ndarray|Array|TypedArray, y:ndarray|Array|TypedArray|string[, \n  ...args:number][, options:Object] )\n    Performs a chi-square goodness-of-fit test.\n","chi2test":"\nchi2test( x:ndarray|Array[, options:Object] )\n    Performs a chi-square independence test.\n","circarray2iterator":"\ncircarray2iterator( src:ArrayLikeObject[, options:Object][, mapFcn:Function[, \n  thisArg:any]] )\n    Returns an iterator which repeatedly iterates over the elements of an array-\n    like object.\n","circularArrayStream":"\ncircularArrayStream( src:ArrayLikeObject[, options:Object] )\n    Creates a readable stream from an array-like object which repeatedly\n    iterates over the provided value's elements.\n","circularArrayStream.factory":"\ncircularArrayStream.factory( [options:Object] )\n    Returns a function for creating readable streams from array-like objects\n    which repeatedly iterate over the elements of provided values.\n","circularArrayStream.objectMode":"\ncircularArrayStream.objectMode( src:ArrayLikeObject[, options:Object] )\n    Returns an \"objectMode\" readable stream from an array-like object which\n    repeatedly iterates over a provided value's elements.\n","CircularBuffer":"\nCircularBuffer( buffer:integer|ArrayLike )\n    Circular buffer constructor.\n","CircularBuffer.prototype.clear":"\nCircularBuffer.prototype.clear()\n    Clears a buffer.\n","CircularBuffer.prototype.count":"\nCircularBuffer.prototype.count\n    Read-only property returning the number of elements currently in the buffer.\n","CircularBuffer.prototype.full":"\nCircularBuffer.prototype.full\n    Read-only property returning a boolean indicating whether a circular buffer\n    is full.\n","CircularBuffer.prototype.iterator":"\nCircularBuffer.prototype.iterator( [niters:integer] )\n    Returns an iterator for iterating over a circular buffer.\n","CircularBuffer.prototype.length":"\nCircularBuffer.prototype.length\n    Read-only property returning the buffer length (i.e., capacity).\n","CircularBuffer.prototype.push":"\nCircularBuffer.prototype.push( value:any )\n    Adds a value to a circular buffer.\n","CircularBuffer.prototype.toArray":"\nCircularBuffer.prototype.toArray()\n    Returns an array of circular buffer values.\n","CircularBuffer.prototype.toJSON":"\nCircularBuffer.prototype.toJSON()\n    Serializes a circular buffer as JSON.\n","close":"\nclose( fd:integer, clbk:Function )\n    Asynchronously closes a file descriptor, so that the file descriptor no\n    longer refers to any file and may be reused.\n","close.sync":"\nclose.sync( fd:integer )\n    Synchronously closes a file descriptor.\n","CMUDICT":"\nCMUDICT( [options:Object] )\n    Returns datasets from the Carnegie Mellon Pronouncing Dictionary (CMUdict).\n","codePointAt":"\ncodePointAt( str:string, idx:integer[, backward:boolean] )\n    Returns a Unicode code point from a string at a specified position.\n","commonKeys":"\ncommonKeys( obj1:any, obj2:any[, ...obj:any] )\n    Returns the common own property names of two or more objects.\n","commonKeysIn":"\ncommonKeysIn( obj1:any, obj2:any[, ...obj:any] )\n    Returns the common own and inherited property names of two or more objects.\n","complex":"\ncomplex( real:number, imag:number[, dtype:string] )\n    Creates a complex number.\n","Complex64":"\nComplex64( real:number, imag:number )\n    64-bit complex number constructor.\n","Complex64.BYTES_PER_ELEMENT":"\nComplex64.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n","Complex64.prototype.BYTES_PER_ELEMENT":"\nComplex64.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n","Complex64.prototype.byteLength":"\nComplex64.prototype.byteLength\n    Length (in bytes) of a complex number.\n","COMPLEX64_NAN":"\nCOMPLEX64_NAN\n    Canonical single-precision complex floating-point NaN.\n","COMPLEX64_NUM_BYTES":"\nCOMPLEX64_NUM_BYTES\n    Size (in bytes) of a 64-bit complex number.\n","COMPLEX64_ZERO":"\nCOMPLEX64_ZERO\n    Single-precision complex floating-point zero.\n","Complex64Array":"\nComplex64Array()\n    A 64-bit complex number array.\n\nComplex64Array( length:integer )\n    Creates a 64-bit complex number array having a specified length.\n\nComplex64Array( complexarray:Complex64Array )\n    Creates a 64-bit complex number array from another complex number array.\n\nComplex64Array( typedarray:TypedArray )\n    Creates a 64-bit complex number array from a typed array\n    containing interleaved real and imaginary components.\n\nComplex64Array( obj:Object )\n    Creates a 64-bit complex number array from an array-like object or iterable.\n\nComplex64Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a 64-bit complex number array view of an ArrayBuffer.\n","Complex64Array.from":"\nComplex64Array.from( src:ArrayLike|Iterable[, clbk:Function[, thisArg:Any]] )\n    Creates a new 64-bit complex number array from an array-like object or an\n    iterable.\n","Complex64Array.of":"\nComplex64Array.of( element0:number[, element1:number[, ...elementN:number]] )\n    Creates a new 64-bit complex number array from a variable number of\n    arguments.\n","Complex64Array.BYTES_PER_ELEMENT":"\nComplex64Array.BYTES_PER_ELEMENT\n    The size of each array element in bytes.\n","Complex64Array.name":"\nComplex64Array.name\n    Typed array constructor name.\n","Complex64Array.prototype.buffer":"\nComplex64Array.prototype.buffer\n    Pointer to the underlying data buffer.\n","Complex64Array.prototype.byteLength":"\nComplex64Array.prototype.byteLength\n    Length of the array in bytes.\n","Complex64Array.prototype.byteOffset":"\nComplex64Array.prototype.byteOffset\n    Offset (in bytes) of the array from the start of its underlying\n    ArrayBuffer.\n","Complex64Array.prototype.BYTES_PER_ELEMENT":"\nComplex64Array.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element.\n","Complex64Array.prototype.length":"\nComplex64Array.prototype.length\n    The number of array elements.\n","Complex64Array.prototype.at":"\nComplex64Array.prototype.at( i:integer )\n    Returns an array element located at integer position (index) `i`, with\n    support for noth nonnegative and negative integer positions.\n","Complex64Array.prototype.copyWithin":"\nComplex64Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","Complex64Array.prototype.entries":"\nComplex64Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","Complex64Array.prototype.every":"\nComplex64Array.prototype.every( predicate:Function[, thisArg:Any] )\n    Returns a boolean indicating whether all elements in the array pass a test.\n","Complex64Array.prototype.fill":"\nComplex64Array.prototype.fill( value:Complex64[, start:integer[, end:integer]] )\n    Returns a modified typed array filled with a fill value.\n","Complex64Array.prototype.filter":"\nComplex64Array.prototype.filter( predicate:Function[, thisArg:Any] )\n    Returns a new array containing the elements of an array which pass a test\n    implemented by a predicate function.\n","Complex64Array.prototype.find":"\nComplex64Array.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first element in an array for which a predicate function\n    returns a truthy value.\n","Complex64Array.prototype.findIndex":"\nComplex64Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first element in an array for which a predicate\n    function returns a truthy value.\n","Complex64Array.prototype.findLast":"\nComplex64Array.prototype.findLast( predicate:Function[, thisArg:Any] )\n    Returns the last element in an array for which a predicate function returns\n    a truthy value.\n","Complex64Array.prototype.findLastIndex":"\nComplex64Array.prototype.findLastIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the last element in an array for which a predicate\n    function returns a truthy value.\n","Complex64Array.prototype.forEach":"\nComplex64Array.prototype.forEach( clbk:Function[, thisArg:Any] )\n    Invokes a function once for each array element.\n","Complex64Array.prototype.get":"\nComplex64Array.prototype.get( i:integer )\n    Returns an array element located at integer position (index) `i`.\n","Complex64Array.prototype.includes":"\nComplex64Array.prototype.includes( searchElement:Complex64[, \n  fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a provided value.\n","Complex64Array.prototype.indexOf":"\nComplex64Array.prototype.indexOf( searchElement:Complex64[, fromIndex:integer] )\n    Returns the first index at which a given element can be found.\n","Complex64Array.prototype.join":"\nComplex64Array.prototype.join( [separator:string] )\n    Returns a new string by concatenating all array elements separated by a\n    separator string.\n","Complex64Array.prototype.keys":"\nComplex64Array.prototype.keys()\n    Returns an iterator for iterating over each index key in a typed array.\n","Complex64Array.prototype.lastIndexOf":"\nComplex64Array.prototype.lastIndexOf( searchElement:Complex64[, \n  fromIndex:integer] )\n    Returns the last index at which a given element can be found.\n","Complex64Array.prototype.map":"\nComplex64Array.prototype.map( clbk:Function[, thisArg:Any] )\n    Returns a new array with each element being the result of a provided\n    callback function.\n","Complex64Array.prototype.reduce":"\nComplex64Array.prototype.reduce( reducerFn:Function[, initialValue:any] )\n    Applies a provided function to each element of the array, in order, passing\n    in the return value from the calculation on the preceding element and\n    returning the accumulated result upon completion.\n","Complex64Array.prototype.reduceRight":"\nComplex64Array.prototype.reduceRight( reducerFn:Function[, initialValue:any] )\n    Applies a provided function to each element of the array, in reverse order,\n    passing in the return value from the calculation on the preceding element\n    and returning the accumulated result upon completion.\n","Complex64Array.prototype.reverse":"\nComplex64Array.prototype.reverse()\n    Reverses the array *in-place*.\n","Complex64Array.prototype.set":"\nComplex64Array.prototype.set( z:Complex64|Complex64Array|ArrayLikeObject[, \n  i:integer] )\n    Sets one or more array elements.\n","Complex64Array.prototype.slice":"\nComplex64Array.prototype.slice( [start:integer[, end:integer]] )\n    Copies a portion of a typed array to a new typed array.\n","Complex64Array.prototype.some":"\nComplex64Array.prototype.some( predicate[, thisArg] )\n    Returns a boolean indicating whether at least one element passes a test.\n","Complex64Array.prototype.sort":"\nComplex64Array.prototype.sort( compareFunction:Function )\n    Sorts an array in-place.\n","Complex64Array.prototype.subarray":"\nComplex64Array.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array view over the same underlying `ArrayBuffer` and\n    with the same underlying data type as the host array.\n","Complex64Array.prototype.toLocaleString":"\nComplex64Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n","Complex64Array.prototype.toReversed":"\nComplex64Array.prototype.toReversed()\n    Returns a new typed array containing the elements in reversed order.\n","Complex64Array.prototype.toSorted":"\nComplex64Array.prototype.toSorted( compareFcn:Function )\n    Returns a new typed array containing the elements in sorted order.\n","Complex64Array.prototype.toString":"\nComplex64Array.prototype.toString()\n    Serializes an array as a string.\n","Complex64Array.prototype.values":"\nComplex64Array.prototype.values()\n    Returns an iterator for iterating over each value in a typed array.\n","Complex64Array.prototype.with":"\nComplex64Array.prototype.with( index, value )\n    Returns a new typed array with the element at a provided index replaced\n    with a provided value.\n","Complex128":"\nComplex128( real:number, imag:number )\n    128-bit complex number constructor.\n","Complex128.BYTES_PER_ELEMENT":"\nComplex128.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n","Complex128.prototype.BYTES_PER_ELEMENT":"\nComplex128.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each component.\n","Complex128.prototype.byteLength":"\nComplex128.prototype.byteLength\n    Length (in bytes) of a complex number.\n","COMPLEX128_NAN":"\nCOMPLEX128_NAN\n    Canonical double-precision complex floating-point NaN.\n","COMPLEX128_NUM_BYTES":"\nCOMPLEX128_NUM_BYTES\n    Size (in bytes) of a 128-bit complex number.\n","COMPLEX128_ZERO":"\nCOMPLEX128_ZERO\n    Double-precision complex floating-point zero.\n","Complex128Array":"\nComplex128Array()\n    A 128-bit complex number array.\n\nComplex128Array( length:integer )\n    Creates a 128-bit complex number array having a specified length.\n\nComplex128Array( complexarray:Complex128Array )\n    Creates a 64-bit complex number array from another complex number array.\n\nComplex128Array( typedarray:TypedArray )\n    Creates a 128-bit complex number array from a typed array\n    containing interleaved real and imaginary components.\n\nComplex128Array( obj:Object )\n    Creates a 128-bit complex number array from an array-like object or \n    iterable.\n\nComplex128Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a 128-bit complex number array view of an ArrayBuffer.\n","Complex128Array.from":"\nComplex128Array.from( src:ArrayLike|Iterable[, clbk:Function[, thisArg:Any]] )\n    Creates a new 128-bit complex number array from an array-like object or an\n    iterable.\n","Complex128Array.of":"\nComplex128Array.of( element0:number|ComplexLike[, \n  element1:number |ComplexLike[, ...elementN:number|ComplexLike]] )\n    Creates a new 128-bit complex number array from a variable number of\n    arguments.\n","Complex128Array.BYTES_PER_ELEMENT":"\nComplex128Array.BYTES_PER_ELEMENT\n    The size of each array element in bytes.\n","Complex128Array.name":"\nComplex128Array.name\n    Typed array constructor name.\n","Complex128Array.prototype.buffer":"\nComplex128Array.prototype.buffer\n    Pointer to the underlying data buffer.\n","Complex128Array.prototype.byteLength":"\nComplex128Array.prototype.byteLength\n    Length of the array in bytes.\n","Complex128Array.prototype.byteOffset":"\nComplex128Array.prototype.byteOffset\n    Offset (in bytes) of the array from the start of its underlying\n    ArrayBuffer.\n","Complex128Array.prototype.BYTES_PER_ELEMENT":"\nComplex128Array.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element.\n","Complex128Array.prototype.length":"\nComplex128Array.prototype.length\n    The number of array elements.\n","Complex128Array.prototype.at":"\nComplex128Array.prototype.at( i:integer )\n    Returns an array element located at integer position (index) `i`, with\n    support for both nonnegative and negative integer positions.\n","Complex128Array.prototype.copyWithin":"\nComplex128Array.prototype.copyWithin( target, start[, end] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","Complex128Array.prototype.entries":"\nComplex128Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","Complex128Array.prototype.every":"\nComplex128Array.prototype.every( predicate:Function[, thisArg:Any] )\n    Returns a boolean indicating whether all elements in the array pass a test.\n","Complex128Array.prototype.fill":"\nComplex128Array.prototype.fill( value:Complex128[, start:integer[, \n  end:integer]] )\n    Returns a modified typed array filled with a fill value.\n","Complex128Array.prototype.filter":"\nComplex128Array.prototype.filter( predicate:Function[, thisArg:Any] )\n    Returns a new array containing the elements of an array which pass a test\n    implemented by a predicate function.\n","Complex128Array.prototype.find":"\nComplex128Array.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first element in an array for which a predicate function\n    returns a truthy value.\n","Complex128Array.prototype.findIndex":"\nComplex128Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first element in an array for which a predicate\n    function returns a truthy value.\n","Complex128Array.prototype.findLast":"\nComplex128Array.prototype.findLast( predicate:Function[, thisArg:Any] )\n    Returns the last element in an array for which a predicate function returns\n    a truthy value.\n","Complex128Array.prototype.findLastIndex":"\nComplex128Array.prototype.findLastIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the last element in an array for which a predicate\n    function returns a truthy value.\n","Complex128Array.prototype.forEach":"\nComplex128Array.prototype.forEach( clbk:Function[, thisArg:Any] )\n    Invokes a function once for each array element.\n","Complex128Array.prototype.get":"\nComplex128Array.prototype.get( i:integer )\n    Returns an array element located at integer position (index) `i`.\n","Complex128Array.prototype.includes":"\nComplex128Array.prototype.includes( searchElement:Complex128[, \n  fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a provided value.\n","Complex128Array.prototype.indexOf":"\nComplex128Array.prototype.indexOf( searchElement:Complex128[, \n  fromIndex:integer] )\n    Returns the first index at which a given element can be found.\n","Complex128Array.prototype.join":"\nComplex128Array.prototype.join( [separator:string] )\n    Returns a new string by concatenating all array elements separated by a\n    separator string.\n","Complex128Array.prototype.keys":"\nComplex128Array.prototype.keys()\n    Returns an iterator for iterating over each index key in a typed array.\n","Complex128Array.prototype.lastIndexOf":"\nComplex128Array.prototype.lastIndexOf( searchElement:Complex128[, \n  fromIndex:integer] )\n    Returns the last index at which a given element can be found.\n","Complex128Array.prototype.map":"\nComplex128Array.prototype.map( clbk:Function[, thisArg:Any] )\n    Returns a new array with each element being the result of a provided\n    callback function.\n","Complex128Array.prototype.reduce":"\nComplex128Array.prototype.reduce( reducerFn:Function[, initialValue:any] )\n    Applies a provided function to each element of the array, in order, passing\n    in the return value from the calculation on the preceding element and\n    returning the accumulated result upon completion.\n","Complex128Array.prototype.reduceRight":"\nComplex128Array.prototype.reduceRight( reducerFn:Function[, initialValue:any] )\n    Applies a provided function to each element of the array, in reverse order,\n    passing in the return value from the calculation on the preceding element\n    and returning the accumulated result upon completion.\n","Complex128Array.prototype.reverse":"\nComplex128Array.prototype.reverse()\n    Reverses the array *in-place*.\n","Complex128Array.prototype.set":"\nComplex128Array.prototype.set( z:Complex128|Complex128Array|ArrayLikeObject[, \n  i:integer] )\n    Sets one or more array elements.\n","Complex128Array.prototype.slice":"\nComplex128Array.prototype.slice( [start:integer[, end:integer]] )\n    Copies a portion of a typed array to a new typed array.\n","Complex128Array.prototype.some":"\nComplex128Array.prototype.some( predicate[, thisArg] )\n    Returns a boolean indicating whether at least one element passes a test.\n","Complex128Array.prototype.sort":"\nComplex128Array.prototype.sort( compareFunction:Function )\n    Sorts an array in-place.\n","Complex128Array.prototype.subarray":"\nComplex128Array.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array view over the same underlying `ArrayBuffer` and\n    with the same underlying data type as the host array.\n","Complex128Array.prototype.toLocaleString":"\nComplex128Array.prototype.toLocaleString( [locales[, options]] )\n    Serializes an array as a locale-specific string.\n","Complex128Array.prototype.toReversed":"\nComplex128Array.prototype.toReversed()\n    Returns a new typed array containing the elements in reversed order.\n","Complex128Array.prototype.toSorted":"\nComplex128Array.prototype.toSorted( compareFcn:Function )\n    Returns a new typed array containing the elements in sorted order.\n","Complex128Array.prototype.toString":"\nComplex128Array.prototype.toString()\n    Serializes an array as a string.\n","Complex128Array.prototype.values":"\nComplex128Array.prototype.values()\n    Returns an iterator for iterating over each value in a typed array.\n","Complex128Array.prototype.with":"\nComplex128Array.prototype.with( index, value )\n    Returns a new typed array with the element at a provided index replaced\n    with a provided value.\n","complexarray":"\ncomplexarray( [dtype:string] )\n    Creates a complex typed array.\n\ncomplexarray( length:integer[, dtype:string] )\n    Returns a complex number typed array having a specified length.\n\ncomplexarray( complexarray:ComplexArray[, dtype:string] )\n    Creates a complex number typed array from another complex number typed\n    array.\n\ncomplexarray( obj:Object[, dtype:string] )\n    Creates a complex number typed array from an array-like object or iterable.\n\ncomplexarray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n  dtype:string] )\n    Returns a complex number typed array view of an ArrayBuffer.\n","complexarrayCtors":"\ncomplexarrayCtors( dtype:string )\n    Returns a complex typed array constructor.\n","complexarrayDataTypes":"\ncomplexarrayDataTypes()\n    Returns a list of complex typed array data types.\n","complexCtors":"\ncomplexCtors( dtype:string )\n    Returns a complex number constructor.\n","complexDataType":"\ncomplexDataType( value:any )\n    Returns the data type of a complex number object.\n","complexDataTypes":"\ncomplexDataTypes()\n    Returns a list of complex number data types.\n","complexPromotionRules":"\ncomplexPromotionRules( [dtype1:string, dtype2:string] )\n    Returns the complex number data type with the smallest size and closest\n    \"kind\" to which data types can be safely cast.\n","compose":"\ncompose( ...f:Function )\n    Function composition.\n","composeAsync":"\ncomposeAsync( ...f:Function )\n    Function composition.\n","configdir":"\nconfigdir( [p:string] )\n    Returns a directory for user-specific configuration files.\n","conj":"\nconj( z:Complex128 )\n    Returns the complex conjugate of a double-precision complex floating-point\n    number.\n","conjf":"\nconjf( z:Complex64 )\n    Returns the complex conjugate of a single-precision complex floating-point\n    number.\n","constantcase":"\nconstantcase( str:string )\n    Converts a string to constant case.\n","constantFunction":"\nconstantFunction( val:any )\n    Creates a function which always returns the same value.\n","constantStream":"\nconstantStream( value:string|Buffer|Uint8Array|any[, options:Object] )\n    Returns a readable stream which always streams the same value.\n","constantStream.factory":"\nconstantStream.factory( [value:string|Buffer|Uint8Array|any, ][options:Object] )\n    Returns a function for creating readable streams which always stream the\n    same value.\n","constantStream.objectMode":"\nconstantStream.objectMode( value:any[, options:Object] )\n    Returns an \"objectMode\" readable stream which always streams the same value.\n","constructorName":"\nconstructorName( val:any )\n    Determines the name of a value's constructor.\n","contains":"\ncontains( val:ArrayLike, searchValue:any[, position:integer] )\n    Tests if an array-like value contains a search value.\n","convertArray":"\nconvertArray( arr:ArrayLikeObject, dtype:string )\n    Converts an input array to an array of a different data type.\n","convertArraySame":"\nconvertArraySame( x:ArrayLikeObject, y:Array|TypedArray )\n    Converts an input array to the same data type as a second input array.\n","convertPath":"\nconvertPath( from:string, to:string )\n    Converts between POSIX and Windows paths.\n","copy":"\ncopy( value:any[, level:integer] )\n    Copy or deep clone a value to an arbitrary depth.\n","copyBuffer":"\ncopyBuffer( buffer:Buffer )\n    Copies buffer data to a new Buffer instance.\n","countBy":"\ncountBy( collection:Array|TypedArray|Object, [options:Object,] \n  indicator:Function )\n    Groups values according to an indicator function and returns group counts.\n","countByAsync":"\ncountByAsync( collection:Array|TypedArray|Object, [options:Object,] \n  indicator:Function, done:Function )\n    Groups values according to an indicator function and returns group counts.\n","countByAsync.factory":"\ncountByAsync.factory( [options:Object,] indicator:Function )\n    Returns a function which groups values according to an indicator function\n    and returns group counts.\n","currentYear":"\ncurrentYear()\n    Returns the current year.\n","curry":"\ncurry( fcn:Function[, arity:integer][, thisArg:any] )\n    Transforms a function into a sequence of functions each accepting a single\n    argument.\n","curryRight":"\ncurryRight( fcn:Function[, arity:integer][, thisArg:any] )\n    Transforms a function into a sequence of functions each accepting a single\n    argument.\n","cwd":"\ncwd()\n    Returns the current working directory.\n","DALE_CHALL_NEW":"\nDALE_CHALL_NEW()\n    Returns a list of familiar English words.\n","datasets":"\ndatasets( name:string[, options:Object] )\n    Returns a dataset.\n","DataView":"\nDataView( buffer:ArrayBuffer|SharedArrayBuffer[, byteOffset:integer[, \n  byteLength:integer]] )\n    Returns a data view representing a provided array buffer.\n","DataView.prototype.buffer":"\nDataView.prototype.buffer\n    Read-only property which returns the underyling array buffer.\n","DataView.prototype.byteLength":"\nDataView.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the view.\n","DataView.prototype.byteOffset":"\nDataView.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the view to the\n    start of the underlying array buffer.\n","datespace":"\ndatespace( start:number, stop:number[, length:integer][ , options:Object] )\n    Generates an array of linearly spaced dates.\n","dayOfQuarter":"\ndayOfQuarter( [month:string|integer|Date[, day:integer, year:integer]] )\n    Returns the day of the quarter.\n","dayOfYear":"\ndayOfYear( [month:string|integer|Date[, day:integer, year:integer]] )\n    Returns the day of the year.\n","daysInMonth":"\ndaysInMonth( [month:string|integer|Date[, year:integer]] )\n    Returns the number of days in a month.\n","daysInYear":"\ndaysInYear( [value:integer|Date] )\n    Returns the number of days in a year according to the Gregorian calendar.\n","ddot":"\nddot( x:ndarray, y:ndarray[, dim:integer] )\n    Computes the dot product of two double-precision floating-point vectors.\n","debugSinkStream":"\ndebugSinkStream( [options:Object,] [clbk:Function] )\n    Returns a writable stream for debugging stream pipelines.\n","debugSinkStream.factory":"\ndebugSinkStream.factory( [options:Object] )\n    Returns a function for creating writable streams for debugging stream\n    pipelines.\n","debugSinkStream.objectMode":"\ndebugSinkStream.objectMode( [options:Object,] [clbk:Function] )\n    Returns an \"objectMode\" writable stream for debugging stream pipelines.\n","debugStream":"\ndebugStream( [options:Object,] [clbk:Function] )\n    Returns a transform stream for debugging stream pipelines.\n","debugStream.factory":"\ndebugStream.factory( [options:Object] )\n    Returns a function for creating transform streams for debugging stream\n    pipelines.\n","debugStream.objectMode":"\ndebugStream.objectMode( [options:Object,] [clbk:Function] )\n    Returns an \"objectMode\" transform stream for debugging stream pipelines.\n","decorateAfter":"\ndecorateAfter( fcn:Function, arity:integer, after:Function[, thisArg:any] )\n    Decorates a provided function such that the function's return value is\n    provided as an argument to another function.\n","decorateAfter.factory":"\ndecorateAfter.factory( fcn:Function, arity:integer, after:Function[, \n  thisArg:any] )\n    Uses code generation to decorate a provided function such that the\n    function's return value is provided as an argument to another function.\n","deepEqual":"\ndeepEqual( a:any, b:any )\n    Tests for deep equality between two values.\n","deepGet":"\ndeepGet( obj:ObjectLike, path:string|Array[, options:Object] )\n    Returns a nested property value.\n","deepGet.factory":"\ndeepGet.factory( path:string|Array[, options:Object] )\n    Creates a reusable deep get function.\n","deepHasOwnProp":"\ndeepHasOwnProp( value:any, path:string|Array[, options:Object] )\n    Returns a boolean indicating whether an object contains a nested key path.\n","deepHasOwnProp.factory":"\ndeepHasOwnProp.factory( path:string|Array[, options:Object] )\n    Returns a function which tests whether an object contains a nested key path.\n","deepHasProp":"\ndeepHasProp( value:any, path:string|Array[, options:Object] )\n    Returns a boolean indicating whether an object contains a nested key path,\n    either own or inherited.\n","deepHasProp.factory":"\ndeepHasProp.factory( path:string|Array[, options:Object] )\n    Returns a function which tests whether an object contains a nested key path,\n    either own or inherited.\n","deepPluck":"\ndeepPluck( arr:Array, path:string|Array[, options:Object] )\n    Extracts a nested property value from each element of an object array.\n","deepSet":"\ndeepSet( obj:ObjectLike, path:string|Array, value:any[, options:Object] )\n    Sets a nested property value.\n","deepSet.factory":"\ndeepSet.factory( path:string|Array[, options:Object] )\n    Creates a reusable deep set function.\n","defineMemoizedProperty":"\ndefineMemoizedProperty( obj:Object, prop:string|symbol, descriptor:Object )\n    Defines a memoized object property.\n","defineProperties":"\ndefineProperties( obj:Object, properties:Object )\n    Defines (and/or modifies) object properties.\n","defineProperty":"\ndefineProperty( obj:Object, prop:string|symbol, descriptor:Object )\n    Defines (or modifies) an object property.\n","dirname":"\ndirname( path:string )\n    Returns a directory name.\n","dotcase":"\ndotcase( str:string )\n    Converts a string to dot case.\n","DoublyLinkedList":"\nDoublyLinkedList()\n    Doubly linked list constructor.\n","doUntil":"\ndoUntil( fcn:Function, predicate:Function[, thisArg:any] )\n    Invokes a function until a test condition is true.\n","doUntilAsync":"\ndoUntilAsync( fcn:Function, predicate:Function, done:Function[, thisArg:any] )\n    Invokes a function until a test condition is true.\n","doUntilEach":"\ndoUntilEach( collection:Array|TypedArray|Object, fcn:Function, \n  predicate:Function[, thisArg:any] )\n    Until a test condition is true, invokes a function for each element in a\n    collection.\n","doUntilEachRight":"\ndoUntilEachRight( collection:Array|TypedArray|Object, fcn:Function, \n  predicate:Function[, thisArg:any] )\n    Until a test condition is true, invokes a function for each element in a\n    collection, iterating from right to left.\n","doWhile":"\ndoWhile( fcn:Function, predicate:Function[, thisArg:any] )\n    Invokes a function while a test condition is true.\n","doWhileAsync":"\ndoWhileAsync( fcn:Function, predicate:Function, done:Function[, thisArg:any] )\n    Invokes a function while a test condition is true.\n","doWhileEach":"\ndoWhileEach( collection:Array|TypedArray|Object, fcn:Function, \n  predicate:Function[, thisArg:any] )\n    While a test condition is true, invokes a function for each element in a\n    collection.\n","doWhileEachRight":"\ndoWhileEachRight( collection:Array|TypedArray|Object, fcn:Function, \n  predicate:Function[, thisArg:any] )\n    While a test condition is true, invokes a function for each element in a\n    collection, iterating from right to left.\n","dswap":"\ndswap( x:ndarray, y:ndarray[, dim:integer] )\n    Interchanges two double-precision floating-point vectors.\n","E":"\nE\n    Euler's number.\n","EMOJI":"\nEMOJI()\n    Returns an emoji database.\n","EMOJI_CODE_PICTO":"\nEMOJI_CODE_PICTO()\n    Returns an object mapping emoji codes to pictographs.\n","EMOJI_PICTO_CODE":"\nEMOJI_PICTO_CODE()\n    Returns an object mapping emoji pictographs to codes.\n","emptyStream":"\nemptyStream( [options:Object] )\n    Returns an \"empty\" readable stream.\n","emptyStream.factory":"\nemptyStream.factory( [options:Object] )\n    Returns a function for creating empty readable streams.\n","emptyStream.objectMode":"\nemptyStream.objectMode()\n    Returns an \"objectMode\" empty readable stream.\n","endsWith":"\nendsWith( str:string, search:string[, len:integer] )\n    Tests if a string ends with the characters of another string.\n","enumerableProperties":"\nenumerableProperties( value:any )\n    Returns an array of an object's own enumerable property names and symbols.\n","enumerablePropertiesIn":"\nenumerablePropertiesIn( value:any )\n    Returns an array of an object's own and inherited enumerable property names\n    and symbols.\n","enumerablePropertySymbols":"\nenumerablePropertySymbols( value:any )\n    Returns an array of an object's own enumerable symbol properties.\n","enumerablePropertySymbolsIn":"\nenumerablePropertySymbolsIn( value:any )\n    Returns an array of an object's own and inherited enumerable symbol\n    properties.\n","ENV":"\nENV\n    An object containing the user environment.\n","EPS":"\nEPS\n    Difference between one and the smallest value greater than one that can be\n    represented as a double-precision floating-point number.\n","error2json":"\nerror2json( error:Error )\n    Returns a JSON representation of an error object.\n","EULERGAMMA":"\nEULERGAMMA\n    The Euler-Mascheroni constant.\n","every":"\nevery( collection:Array|TypedArray|Object )\n    Tests whether all elements in a collection are truthy.\n","everyBy":"\neveryBy( collection:Array|TypedArray|Object, predicate:Function[, \n  thisArg:any ] )\n    Tests whether all elements in a collection pass a test implemented by a\n    predicate function.\n","everyByAsync":"\neveryByAsync( collection:Array|TypedArray|Object, [options:Object,] \n  predicate:Function, done:Function )\n    Tests whether all elements in a collection pass a test implemented by a\n    predicate function.\n","everyByAsync.factory":"\neveryByAsync.factory( [options:Object,] predicate:Function )\n    Returns a function which tests whether all elements in a collection pass a\n    test implemented by a predicate function.\n","everyByRight":"\neveryByRight( collection:Array|TypedArray|Object, predicate:Function[, \n  thisArg:any ] )\n    Tests whether all elements in a collection pass a test implemented by a\n    predicate function, iterating from right to left.\n","everyByRightAsync":"\neveryByRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n  predicate:Function, done:Function )\n    Tests whether all elements in a collection pass a test implemented by a\n    predicate function, iterating from right to left.\n","everyByRightAsync.factory":"\neveryByRightAsync.factory( [options:Object,] predicate:Function )\n    Returns a function which tests whether all elements in a collection pass a\n    test implemented by a predicate function, iterating from right to left.\n","everyInBy":"\neveryInBy( object:Object, predicate:Function[, thisArg:any ] )\n   Test whether all properties (own and inherited) of an object pass a\n   test implemented by a predicate function.\n","everyOwnBy":"\neveryOwnBy( object:Object, predicate:Function[, thisArg:any ] )\n    Tests whether every own property of an object pass a test implemented by a\n    predicate function.\n","evil":"\nevil( str:string )\n    Alias for `eval` global.\n","EXEC_PATH":"\nEXEC_PATH\n    Absolute pathname of the executable which started the current Node.js\n    process.\n","exists":"\nexists( path:string|Buffer, clbk:Function )\n    Asynchronously tests whether a path exists on the filesystem.\n","exists.sync":"\nexists.sync( path:string|Buffer )\n    Synchronously tests whether a path exists on the filesystem.\n","expandAcronyms":"\nexpandAcronyms( str:string )\n    Expands acronyms in a string.\n","expandContractions":"\nexpandContractions( str:string )\n    Expands all contractions to their formal equivalents.\n","extname":"\nextname( filename:string )\n    Returns a filename extension.\n","FancyArray":"\nFancyArray( dtype:string, buffer:ArrayLikeObject|TypedArray|Buffer, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  offset:integer, order:string[, options:Object] )\n    Returns a FancyArray instance.\n","FancyArray.prototype.byteLength":"\nFancyArray.prototype.byteLength\n    Size (in bytes) of the array (if known).\n","FancyArray.prototype.BYTES_PER_ELEMENT":"\nFancyArray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element (if known).\n","FancyArray.prototype.data":"\nFancyArray.prototype.data\n    Pointer to the underlying data buffer.\n","FancyArray.prototype.dtype":"\nFancyArray.prototype.dtype\n    Underlying data type.\n","FancyArray.prototype.flags":"\nFancyArray.prototype.flags\n    Meta information, such as information concerning the memory layout of the\n    array.\n","FancyArray.prototype.length":"\nFancyArray.prototype.length\n    Length of the array (i.e., number of elements).\n","FancyArray.prototype.ndims":"\nFancyArray.prototype.ndims\n    Number of dimensions.\n","FancyArray.prototype.offset":"\nFancyArray.prototype.offset\n    Index offset which specifies the buffer index at which to start iterating\n    over array elements.\n","FancyArray.prototype.order":"\nFancyArray.prototype.order\n    Array order.\n","FancyArray.prototype.shape":"\nFancyArray.prototype.shape\n    Array shape.\n","FancyArray.prototype.strides":"\nFancyArray.prototype.strides\n    Index strides which specify how to access data along corresponding array\n    dimensions.\n","FancyArray.prototype.get":"\nFancyArray.prototype.get( ...idx:integer )\n    Returns an array element specified according to provided subscripts.\n","FancyArray.prototype.iget":"\nFancyArray.prototype.iget( idx:integer )\n    Returns an array element located at a specified linear index.\n","FancyArray.prototype.set":"\nFancyArray.prototype.set( ...idx:integer, v:any )\n    Sets an array element specified according to provided subscripts.\n","FancyArray.prototype.iset":"\nFancyArray.prototype.iset( idx:integer, v:any )\n    Sets an array element located at a specified linear index.\n","FancyArray.prototype.toString":"\nFancyArray.prototype.toString()\n    Serializes a FancyArray as a string.\n","FancyArray.prototype.toJSON":"\nFancyArray.prototype.toJSON()\n    Serializes a FancyArray as a JSON object.\n","fastmath.abs":"\nfastmath.abs( x:number )\n    Computes an absolute value.\n","fastmath.acosh":"\nfastmath.acosh( x:number )\n    Computes the hyperbolic arccosine of a number.\n","fastmath.ampbm":"\nfastmath.ampbm( x:number, y:number )\n    Computes the hypotenuse using the alpha max plus beta min algorithm.\n","fastmath.ampbm.factory":"\nfastmath.ampbm.factory( alpha:number, beta:number, [nonnegative:boolean[, \n  ints:boolean]] )\n    Returns a function to compute a hypotenuse using the alpha max plus beta min\n    algorithm.\n","fastmath.asinh":"\nfastmath.asinh( x:number )\n    Computes the hyperbolic arcsine of a number.\n","fastmath.atanh":"\nfastmath.atanh( x:number )\n    Computes the hyperbolic arctangent of a number.\n","fastmath.hypot":"\nfastmath.hypot( x:number, y:number )\n    Computes the hypotenuse.\n","fastmath.log2Uint32":"\nfastmath.log2Uint32( x:uinteger )\n    Returns an approximate binary logarithm (base two) of an unsigned 32-bit\n    integer `x`.\n","fastmath.max":"\nfastmath.max( x:number, y:number )\n    Returns the maximum value.\n","fastmath.min":"\nfastmath.min( x:number, y:number )\n    Returns the minimum value.\n","fastmath.powint":"\nfastmath.powint( x:number, y:integer )\n    Evaluates the exponential function given a signed 32-bit integer exponent.\n","fastmath.sqrtUint32":"\nfastmath.sqrtUint32( x:uinteger )\n    Returns an approximate square root of an unsigned 32-bit integer `x`.\n","FEMALE_FIRST_NAMES_EN":"\nFEMALE_FIRST_NAMES_EN()\n    Returns a list of common female first names in English speaking countries.\n","FIFO":"\nFIFO()\n    First-in-first-out (FIFO) queue constructor.\n","filledarray":"\nfilledarray( [dtype:string] )\n    Creates a filled array.\n\nfilledarray( value:any, length:integer[, dtype:string] )\n    Returns a filled array having a specified length.\n\nfilledarray( value:any, array:ArrayLikeObject[, dtype:string] )\n    Creates a filled array from another array (or array-like object).\n\nfilledarray( value:any, iterable:Iterable[, dtype:string] )\n    Creates a filled array from an iterable.\n\nfilledarray( value:any, buffer:ArrayBuffer[, byteOffset:integer[, \n  length:integer]][, dtype:string] )\n    Returns a filled typed array view of an ArrayBuffer.\n","filledarrayBy":"\nfilledarrayBy( [dtype:string] )\n    Creates a filled array.\n\nfilledarrayBy( length:integer[, dtype:string], clbk:Function[, thisArg:any] )\n    Returns a filled array according to a provided callback function and having\n    a specified length.\n\nfilledarrayBy( array:ArrayLikeObject[, dtype:string], clbk:Function[, \n  thisArg:any] )\n    Creates a filled array from another array (or array-like object) according\n    to a provided callback function.\n\nfilledarrayBy( iterable:Iterable[, dtype:string], clbk:Function[, thisArg:any] )\n    Creates a filled array from an iterable according to a provided callback\n    function.\n\nfilledarrayBy( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n  dtype:string], clbk:Function[, thisArg:any] )\n    Returns a filled typed array view of an ArrayBuffer according to a provided\n    callback function.\n","filterArguments":"\nfilterArguments( fcn:Function, predicate:Function[, thisArg:any] )\n    Returns a function that applies arguments to a provided function according\n    to a predicate function.\n","find":"\nfind( arr:Array|TypedArray|string, [options:Object,] clbk:Function )\n    Finds elements in an array-like object that satisfy a test condition.\n","firstChar":"\nfirstChar( str:string[, n:integer][, options:Object] )\n    Returns the first character(s) of a string.\n","FIVETHIRTYEIGHT_FFQ":"\nFIVETHIRTYEIGHT_FFQ()\n    Returns FiveThirtyEight reader responses to a food frequency questionnaire\n    (FFQ).\n","flattenArray":"\nflattenArray( arr:ArrayLikeObject[, options:Object] )\n    Flattens an array.\n","flattenArray.factory":"\nflattenArray.factory( dims:ArrayLike<integer>[, options:Object] )\n    Returns a function for flattening arrays having specified dimensions.\n","flattenObject":"\nflattenObject( obj:ObjectLike[, options:Object] )\n    Flattens an object.\n","flattenObject.factory":"\nflattenObject.factory( [options:Object] )\n    Returns a function to flatten an object.\n","flignerTest":"\nflignerTest( ...x:Array[, options:Object] )\n    Computes the Fligner-Killeen test for equal variances.\n","FLOAT_WORD_ORDER":"\nFLOAT_WORD_ORDER\n    Platform float word order.\n","FLOAT16_CBRT_EPS":"\nFLOAT16_CBRT_EPS\n    Cube root of half-precision floating-point epsilon.\n","FLOAT16_EPS":"\nFLOAT16_EPS\n    Difference between one and the smallest value greater than one that can be\n    represented as a half-precision floating-point number.\n","FLOAT16_EXPONENT_BIAS":"\nFLOAT16_EXPONENT_BIAS\n    The bias of a half-precision floating-point number's exponent.\n","FLOAT16_MAX":"\nFLOAT16_MAX\n    Maximum half-precision floating-point number.\n","FLOAT16_MAX_SAFE_INTEGER":"\nFLOAT16_MAX_SAFE_INTEGER\n    Maximum safe half-precision floating-point integer.\n","FLOAT16_MIN_SAFE_INTEGER":"\nFLOAT16_MIN_SAFE_INTEGER\n    Minimum safe half-precision floating-point integer.\n","FLOAT16_NINF":"\nFLOAT16_NINF\n    Half-precision floating-point negative infinity.\n","FLOAT16_NUM_BYTES":"\nFLOAT16_NUM_BYTES\n    Size (in bytes) of a half-precision floating-point number.\n","FLOAT16_PINF":"\nFLOAT16_PINF\n    Half-precision floating-point positive infinity.\n","FLOAT16_PRECISION":"\nFLOAT16_PRECISION\n    Effective number of bits in the significand of a half-precision floating-\n    point number.\n","FLOAT16_SMALLEST_NORMAL":"\nFLOAT16_SMALLEST_NORMAL\n    Smallest positive normalized half-precision floating-point number.\n","FLOAT16_SMALLEST_SUBNORMAL":"\nFLOAT16_SMALLEST_SUBNORMAL\n    Smallest positive denormalized half-precision floating-point number.\n","FLOAT16_SQRT_EPS":"\nFLOAT16_SQRT_EPS\n    Square root of half-precision floating-point epsilon.\n","FLOAT32_ABS_MASK":"\nFLOAT32_ABS_MASK\n    Mask for excluding the sign bit of a single-precision floating-point number.\n","FLOAT32_CBRT_EPS":"\nFLOAT32_CBRT_EPS\n    Cube root of single-precision floating-point epsilon.\n","FLOAT32_E":"\nFLOAT32_E\n    Euler's number.\n","FLOAT32_EPS":"\nFLOAT32_EPS\n    Difference between one and the smallest value greater than one that can be\n    represented as a single-precision floating-point number.\n","FLOAT32_EXPONENT_BIAS":"\nFLOAT32_EXPONENT_BIAS\n    The bias of a single-precision floating-point number's exponent.\n","FLOAT32_EXPONENT_MASK":"\nFLOAT32_EXPONENT_MASK\n    Mask for the exponent of a single-precision floating-point number.\n","FLOAT32_FOURTH_PI":"\nFLOAT32_FOURTH_PI\n    One fourth times the mathematical constant `π`.\n","FLOAT32_HALF_LN_TWO":"\nFLOAT32_HALF_LN_TWO\n    One half times the natural logarithm of 2 as a single-precision\n    floating-point number.\n","FLOAT32_HALF_PI":"\nFLOAT32_HALF_PI\n    One half times the mathematical constant `π`.\n","FLOAT32_LN_HALF":"\nFLOAT32_LN_HALF\n    Natural logarithm of `1/2` as a single-precision floating-point number.\n","FLOAT32_LN_PI":"\nFLOAT32_LN_PI\n    Natural logarithm of the mathematical constant `π` as a single-precision\n    floating-point number.\n","FLOAT32_LN_TEN":"\nFLOAT32_LN_TEN\n    Natural logarithm of `10` as a single-precision floating-point number.\n","FLOAT32_LN_TWO":"\nFLOAT32_LN_TWO\n    Natural logarithm of `2` as a single-precision floating-point number.\n","FLOAT32_MAX":"\nFLOAT32_MAX\n    Maximum single-precision floating-point number.\n","FLOAT32_MAX_BASE2_EXPONENT":"\nFLOAT32_MAX_BASE2_EXPONENT\n    The maximum biased base 2 exponent for a single-precision floating-point\n    number.\n","FLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT32_MAX_BASE2_EXPONENT_SUBNORMAL\n    The maximum biased base 2 exponent for a subnormal single-precision\n    floating-point number.\n","FLOAT32_MAX_BASE10_EXPONENT":"\nFLOAT32_MAX_BASE10_EXPONENT\n    The maximum base 10 exponent for a single-precision floating-point number.\n","FLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT32_MAX_BASE10_EXPONENT_SUBNORMAL\n    The maximum base 10 exponent for a subnormal single-precision floating-point\n    number.\n","FLOAT32_MAX_SAFE_FIBONACCI":"\nFLOAT32_MAX_SAFE_FIBONACCI\n    Maximum safe Fibonacci number when stored in single-precision floating-point\n    format.\n","FLOAT32_MAX_SAFE_INTEGER":"\nFLOAT32_MAX_SAFE_INTEGER\n    Maximum safe single-precision floating-point integer.\n","FLOAT32_MAX_SAFE_NTH_FACTORIAL":"\nFLOAT32_MAX_SAFE_NTH_FACTORIAL\n    Maximum safe nth factorial when stored in single-precision floating-\n    point format.\n","FLOAT32_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT32_MAX_SAFE_NTH_FIBONACCI\n    Maximum safe nth Fibonacci number when stored in single-precision floating-\n    point format.\n","FLOAT32_MAX_SAFE_NTH_LUCAS":"\nFLOAT32_MAX_SAFE_NTH_LUCAS\n    Maximum safe nth Lucas number when stored in single-precision floating-point\n    format.\n","FLOAT32_MIN_BASE2_EXPONENT":"\nFLOAT32_MIN_BASE2_EXPONENT\n    The minimum biased base 2 exponent for a normalized single-precision\n    floating-point number.\n","FLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT32_MIN_BASE2_EXPONENT_SUBNORMAL\n    The minimum biased base 2 exponent for a subnormal single-precision\n    floating-point number.\n","FLOAT32_MIN_BASE10_EXPONENT":"\nFLOAT32_MIN_BASE10_EXPONENT\n    The minimum base 10 exponent for a normal single-precision floating-\n    point number.\n","FLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT32_MIN_BASE10_EXPONENT_SUBNORMAL\n    The minimum base 10 exponent for a subnormal single-precision floating-\n    point number.\n","FLOAT32_MIN_SAFE_INTEGER":"\nFLOAT32_MIN_SAFE_INTEGER\n    Minimum safe single-precision floating-point integer.\n","FLOAT32_NAN":"\nFLOAT32_NAN\n    Single-precision floating-point NaN.\n","FLOAT32_NINF":"\nFLOAT32_NINF\n    Single-precision floating-point negative infinity.\n","FLOAT32_NUM_BYTES":"\nFLOAT32_NUM_BYTES\n    Size (in bytes) of a single-precision floating-point number.\n","FLOAT32_PHI":"\nFLOAT32_PHI\n    Golden ratio.\n","FLOAT32_PI":"\nFLOAT32_PI\n    The mathematical constant `π`.\n","FLOAT32_PINF":"\nFLOAT32_PINF\n    Single-precision floating-point positive infinity.\n","FLOAT32_PRECISION":"\nFLOAT32_PRECISION\n    Effective number of bits in the significand of a single-precision floating-\n    point number.\n","FLOAT32_SIGN_MASK":"\nFLOAT32_SIGN_MASK\n    Mask for the sign bit of a single-precision floating-point number.\n","FLOAT32_SIGNIFICAND_MASK":"\nFLOAT32_SIGNIFICAND_MASK\n    Mask for the significand of a single-precision floating-point number.\n","FLOAT32_SMALLEST_NORMAL":"\nFLOAT32_SMALLEST_NORMAL\n    Smallest positive normalized single-precision floating-point number.\n","FLOAT32_SMALLEST_SUBNORMAL":"\nFLOAT32_SMALLEST_SUBNORMAL\n    Smallest positive denormalized single-precision floating-point number.\n","FLOAT32_SQRT_EPS":"\nFLOAT32_SQRT_EPS\n    Square root of single-precision floating-point epsilon.\n","FLOAT32_SQRT_HALF":"\nFLOAT32_SQRT_HALF\n    Square root of `1/2` as a single-precision floating-point number.\n","FLOAT32_SQRT_HALF_PI":"\nFLOAT32_SQRT_HALF_PI\n    Square root of `π` divided by `2` as a single-precision \n    floating-point number.\n","FLOAT32_SQRT_PHI":"\nFLOAT32_SQRT_PHI\n    Square root of the golden ratio as a single-precision floating-point number.\n","FLOAT32_SQRT_PI":"\nFLOAT32_SQRT_PI\n    Square root of the mathematical constant `π` as a single-precision\n    floating-point number.\n","FLOAT32_SQRT_THREE":"\nFLOAT32_SQRT_THREE\n    Square root of `3` as a single-precision floating-point number.\n","FLOAT32_SQRT_TWO":"\nFLOAT32_SQRT_TWO\n    Square root of `2` as a single-precision floating-point number.\n","FLOAT32_SQRT_TWO_PI":"\nFLOAT32_SQRT_TWO_PI\n    Square root of the `π` times `2` as single-precision floating-point number.\n","FLOAT32_TWO_PI":"\nFLOAT32_TWO_PI\n    The mathematical constant `π` times `2`.\n","Float32Array":"\nFloat32Array()\n    A typed array constructor which returns a typed array representing an array\n    of single-precision floating-point numbers in the platform byte order.\n\nFloat32Array( length:integer )\n    Returns a typed array having a specified length.\n\nFloat32Array( typedarray:TypedArray )\n    Creates a typed array from another typed array.\n\nFloat32Array( obj:Object )\n    Creates a typed array from an array-like object or iterable.\n\nFloat32Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a typed array view of an ArrayBuffer.\n","Float32Array.from":"\nFloat32Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n    Creates a new typed array from an array-like object or an iterable.\n","Float32Array.of":"\nFloat32Array.of( element0:number[, element1:number[, ...elementN:number]] )\n    Creates a new typed array from a variable number of arguments.\n","Float32Array.BYTES_PER_ELEMENT":"\nFloat32Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Float32Array.name":"\nFloat32Array.name\n    Typed array constructor name.\n","Float32Array.prototype.buffer":"\nFloat32Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n","Float32Array.prototype.byteLength":"\nFloat32Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n","Float32Array.prototype.byteOffset":"\nFloat32Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n","Float32Array.prototype.BYTES_PER_ELEMENT":"\nFloat32Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Float32Array.prototype.length":"\nFloat32Array.prototype.length\n    Read-only property which returns the number of view elements.\n","Float32Array.prototype.copyWithin":"\nFloat32Array.prototype.copyWithin( target:integer, start:integer[, \n  end:integer] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","Float32Array.prototype.entries":"\nFloat32Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","Float32Array.prototype.every":"\nFloat32Array.prototype.every( predicate:Function[, thisArg:Any] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n","Float32Array.prototype.fill":"\nFloat32Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n","Float32Array.prototype.filter":"\nFloat32Array.prototype.filter( predicate:Function[, thisArg:Any] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n","Float32Array.prototype.find":"\nFloat32Array.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n","Float32Array.prototype.findIndex":"\nFloat32Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n","Float32Array.prototype.forEach":"\nFloat32Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n    Invokes a callback for each array element.\n","Float32Array.prototype.includes":"\nFloat32Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a search element.\n","Float32Array.prototype.indexOf":"\nFloat32Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n","Float32Array.prototype.join":"\nFloat32Array.prototype.join( [separator:string] )\n    Serializes an array by joining all array elements as a string.\n","Float32Array.prototype.keys":"\nFloat32Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n","Float32Array.prototype.lastIndexOf":"\nFloat32Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n","Float32Array.prototype.map":"\nFloat32Array.prototype.map( fcn:Function[, thisArg:Any] )\n    Maps each array element to an element in a new typed array.\n","Float32Array.prototype.reduce":"\nFloat32Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n","Float32Array.prototype.reduceRight":"\nFloat32Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n","Float32Array.prototype.reverse":"\nFloat32Array.prototype.reverse()\n    Reverses an array *in-place*.\n","Float32Array.prototype.set":"\nFloat32Array.prototype.set( arr:ArrayLike[, offset:integer] )\n    Sets array elements.\n","Float32Array.prototype.slice":"\nFloat32Array.prototype.slice( [begin:integer[, end:integer]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n","Float32Array.prototype.some":"\nFloat32Array.prototype.some( predicate:Function[, thisArg:Any] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n","Float32Array.prototype.sort":"\nFloat32Array.prototype.sort( [compareFunction:Function] )\n    Sorts an array *in-place*.\n","Float32Array.prototype.subarray":"\nFloat32Array.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n","Float32Array.prototype.toLocaleString":"\nFloat32Array.prototype.toLocaleString( [locales:string|Array[, \n  options:Object]] )\n    Serializes an array as a locale-specific string.\n","Float32Array.prototype.toString":"\nFloat32Array.prototype.toString()\n    Serializes an array as a string.\n","Float32Array.prototype.values":"\nFloat32Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n","FLOAT64_EXPONENT_BIAS":"\nFLOAT64_EXPONENT_BIAS\n    The bias of a double-precision floating-point number's exponent.\n","FLOAT64_HIGH_WORD_ABS_MASK":"\nFLOAT64_HIGH_WORD_ABS_MASK\n    High word mask for excluding the sign bit of a double-precision floating-\n    point number.\n","FLOAT64_HIGH_WORD_EXPONENT_MASK":"\nFLOAT64_HIGH_WORD_EXPONENT_MASK\n    High word mask for the exponent of a double-precision floating-point number.\n","FLOAT64_HIGH_WORD_SIGN_MASK":"\nFLOAT64_HIGH_WORD_SIGN_MASK\n    High word mask for the sign bit of a double-precision floating-point number.\n","FLOAT64_HIGH_WORD_SIGNIFICAND_MASK":"\nFLOAT64_HIGH_WORD_SIGNIFICAND_MASK\n    High word mask for the significand of a double-precision floating-point\n    number.\n","FLOAT64_MAX":"\nFLOAT64_MAX\n    Maximum double-precision floating-point number.\n","FLOAT64_MAX_BASE2_EXPONENT":"\nFLOAT64_MAX_BASE2_EXPONENT\n    The maximum biased base 2 exponent for a double-precision floating-point\n    number.\n","FLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE2_EXPONENT_SUBNORMAL\n    The maximum biased base 2 exponent for a subnormal double-precision\n    floating-point number.\n","FLOAT64_MAX_BASE10_EXPONENT":"\nFLOAT64_MAX_BASE10_EXPONENT\n    The maximum base 10 exponent for a double-precision floating-point number.\n","FLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MAX_BASE10_EXPONENT_SUBNORMAL\n    The maximum base 10 exponent for a subnormal double-precision floating-point\n    number.\n","FLOAT64_MAX_LN":"\nFLOAT64_MAX_LN\n    Natural logarithm of the maximum double-precision floating-point number.\n","FLOAT64_MAX_SAFE_FIBONACCI":"\nFLOAT64_MAX_SAFE_FIBONACCI\n    Maximum safe Fibonacci number when stored in double-precision floating-point\n    format.\n","FLOAT64_MAX_SAFE_INTEGER":"\nFLOAT64_MAX_SAFE_INTEGER\n    Maximum safe double-precision floating-point integer.\n","FLOAT64_MAX_SAFE_LUCAS":"\nFLOAT64_MAX_SAFE_LUCAS\n    Maximum safe Lucas number when stored in double-precision floating-point\n    format.\n","FLOAT64_MAX_SAFE_NTH_FIBONACCI":"\nFLOAT64_MAX_SAFE_NTH_FIBONACCI\n    Maximum safe nth Fibonacci number when stored in double-precision floating-\n    point format.\n","FLOAT64_MAX_SAFE_NTH_LUCAS":"\nFLOAT64_MAX_SAFE_NTH_LUCAS\n    Maximum safe nth Lucas number when stored in double-precision floating-point\n    format.\n","FLOAT64_MIN_BASE2_EXPONENT":"\nFLOAT64_MIN_BASE2_EXPONENT\n    The minimum biased base 2 exponent for a normalized double-precision\n    floating-point number.\n","FLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE2_EXPONENT_SUBNORMAL\n    The minimum biased base 2 exponent for a subnormal double-precision\n    floating-point number.\n","FLOAT64_MIN_BASE10_EXPONENT":"\nFLOAT64_MIN_BASE10_EXPONENT\n    The minimum base 10 exponent for a normalized double-precision floating-\n    point number.\n","FLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL":"\nFLOAT64_MIN_BASE10_EXPONENT_SUBNORMAL\n    The minimum base 10 exponent for a subnormal double-precision floating-\n    point number.\n","FLOAT64_MIN_LN":"\nFLOAT64_MIN_LN\n    Natural logarithm of the smallest normalized double-precision floating-point\n    number.\n","FLOAT64_MIN_SAFE_INTEGER":"\nFLOAT64_MIN_SAFE_INTEGER\n    Minimum safe double-precision floating-point integer.\n","FLOAT64_NUM_BYTES":"\nFLOAT64_NUM_BYTES\n    Size (in bytes) of a double-precision floating-point number.\n","FLOAT64_PRECISION":"\nFLOAT64_PRECISION\n    Effective number of bits in the significand of a double-precision floating-\n    point number.\n","FLOAT64_SMALLEST_NORMAL":"\nFLOAT64_SMALLEST_NORMAL\n    Smallest positive normalized double-precision floating-point number.\n","FLOAT64_SMALLEST_SUBNORMAL":"\nFLOAT64_SMALLEST_SUBNORMAL\n    Smallest positive denormalized double-precision floating-point number.\n","Float64Array":"\nFloat64Array()\n    A typed array constructor which returns a typed array representing an array\n    of double-precision floating-point numbers in the platform byte order.\n\nFloat64Array( length:integer )\n    Returns a typed array having a specified length.\n\nFloat64Array( typedarray:TypedArray )\n    Creates a typed array from another typed array.\n\nFloat64Array( obj:Object )\n    Creates a typed array from an array-like object or iterable.\n\nFloat64Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a typed array view of an ArrayBuffer.\n","Float64Array.from":"\nFloat64Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n    Creates a new typed array from an array-like object or an iterable.\n","Float64Array.of":"\nFloat64Array.of( element0:number[, element1:number[, ...elementN:number]] )\n    Creates a new typed array from a variable number of arguments.\n","Float64Array.BYTES_PER_ELEMENT":"\nFloat64Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Float64Array.name":"\nFloat64Array.name\n    Typed array constructor name.\n","Float64Array.prototype.buffer":"\nFloat64Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n","Float64Array.prototype.byteLength":"\nFloat64Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n","Float64Array.prototype.byteOffset":"\nFloat64Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n","Float64Array.prototype.BYTES_PER_ELEMENT":"\nFloat64Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Float64Array.prototype.length":"\nFloat64Array.prototype.length\n    Read-only property which returns the number of view elements.\n","Float64Array.prototype.copyWithin":"\nFloat64Array.prototype.copyWithin( target:integer, start:integer[, \n  end:integer] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","Float64Array.prototype.entries":"\nFloat64Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","Float64Array.prototype.every":"\nFloat64Array.prototype.every( predicate:Function[, thisArg:Any] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n","Float64Array.prototype.fill":"\nFloat64Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n","Float64Array.prototype.filter":"\nFloat64Array.prototype.filter( predicate:Function[, thisArg:Any] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n","Float64Array.prototype.find":"\nFloat64Array.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n","Float64Array.prototype.findIndex":"\nFloat64Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n","Float64Array.prototype.forEach":"\nFloat64Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n    Invokes a callback for each array element.\n","Float64Array.prototype.includes":"\nFloat64Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a search element.\n","Float64Array.prototype.indexOf":"\nFloat64Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n","Float64Array.prototype.join":"\nFloat64Array.prototype.join( [separator:string] )\n    Serializes an array by joining all array elements as a string.\n","Float64Array.prototype.keys":"\nFloat64Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n","Float64Array.prototype.lastIndexOf":"\nFloat64Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n","Float64Array.prototype.map":"\nFloat64Array.prototype.map( fcn:Function[, thisArg:Any] )\n    Maps each array element to an element in a new typed array.\n","Float64Array.prototype.reduce":"\nFloat64Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n","Float64Array.prototype.reduceRight":"\nFloat64Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n","Float64Array.prototype.reverse":"\nFloat64Array.prototype.reverse()\n    Reverses an array *in-place*.\n","Float64Array.prototype.set":"\nFloat64Array.prototype.set( arr:ArrayLike[, offset:integer] )\n    Sets array elements.\n","Float64Array.prototype.slice":"\nFloat64Array.prototype.slice( [begin:integer[, end:integer]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n","Float64Array.prototype.some":"\nFloat64Array.prototype.some( predicate:Function[, thisArg:Any] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n","Float64Array.prototype.sort":"\nFloat64Array.prototype.sort( [compareFunction:Function] )\n    Sorts an array *in-place*.\n","Float64Array.prototype.subarray":"\nFloat64Array.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n","Float64Array.prototype.toLocaleString":"\nFloat64Array.prototype.toLocaleString( [locales:string|Array[, \n  options:Object]] )\n    Serializes an array as a locale-specific string.\n","Float64Array.prototype.toString":"\nFloat64Array.prototype.toString()\n    Serializes an array as a string.\n","Float64Array.prototype.values":"\nFloat64Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n","forEach":"\nforEach( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n    Invokes a function for each element in a collection.\n","forEachAsync":"\nforEachAsync( collection:Array|TypedArray|Object, [options:Object,] \n  fcn:Function, done:Function )\n    Invokes a function once for each element in a collection.\n","forEachAsync.factory":"\nforEachAsync.factory( [options:Object,] fcn:Function )\n    Returns a function which invokes a function once for each element in a\n    collection.\n","forEachChar":"\nforEachChar( str:string, [options:Object,] clbk:Function[, thisArg:any] )\n    Invokes a function for each character in a string.\n","forEachRight":"\nforEachRight( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n    Invokes a function for each element in a collection, iterating from right to\n    left.\n","forEachRightAsync":"\nforEachRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n  fcn:Function, done:Function )\n    Invokes a function once for each element in a collection, iterating from\n    right to left.\n","forEachRightAsync.factory":"\nforEachRightAsync.factory( [options:Object,] fcn:Function )\n    Returns a function which invokes a function once for each element in a\n    collection, iterating from right to left.\n","forIn":"\nforIn( obj:Object, fcn:Function[, thisArg:any] )\n    Invokes a function for each own and inherited enumerable property of an\n    object.\n","format":"\nformat( str:string, ...args:any )\n    Insert supplied variable values into a format string.\n","forOwn":"\nforOwn( obj:Object, fcn:Function[, thisArg:any] )\n    Invokes a function for each own enumerable property of an object.\n","FOURTH_PI":"\nFOURTH_PI\n    One fourth times the mathematical constant `π`.\n","FOURTH_ROOT_EPS":"\nFOURTH_ROOT_EPS\n    Fourth root of double-precision floating-point epsilon.\n","FRB_SF_WAGE_RIGIDITY":"\nFRB_SF_WAGE_RIGIDITY()\n    Returns wage rates for U.S. workers that have not changed jobs within the\n    year.\n","fromCodePoint":"\nfromCodePoint( ...pt:integer )\n    Creates a string from a sequence of Unicode code points.\n","Function":"\nFunction( [...argNames:any,] body:string )\n    Returns a Function object.\n","Function.prototype.apply":"\nFunction.prototype.apply( thisArg:any, args:Array )\n    Calls a function with a given `this` value and arguments provided as an\n    array (or array-like object).\n","Function.prototype.call":"\nFunction.prototype.call( thisArg:any, ...args:any )\n    Calls a function with a given `this` value and arguments provided\n    individually.\n","Function.prototype.bind":"\nFunction.prototype.bind( thisArg:any, ...args:any )\n    Creates a new function which, when called, has its `this` keyword set to the\n    provided value, with a given sequence of arguments preceding any provided\n    when the new function is called.\n","Function.prototype.toString":"\nFunction.prototype.toString()\n    Returns a string representation of the function.\n","Function.prototype.length":"\nFunction.prototype.length\n    The number of arguments expected by the function.\n","Function.prototype.name":"\nFunction.prototype.name\n    The name of the function.\n","Function.prototype.prototype":"\nFunction.prototype.prototype\n    The prototype of the function.\n","function2string":"\nfunction2string( fcn:Function )\n    Returns a string representing the source code of a provided function.\n","functionName":"\nfunctionName( fcn:Function )\n    Returns the name of a function.\n","functionSequence":"\nfunctionSequence( ...fcn:Function )\n    Returns a pipeline function.\n","functionSequenceAsync":"\nfunctionSequenceAsync( ...fcn:Function )\n    Returns a pipeline function.\n","GAMMA_LANCZOS_G":"\nGAMMA_LANCZOS_G\n    Arbitrary constant `g` to be used in Lanczos approximation functions.\n","gdot":"\ngdot( x:ndarray|ArrayLikeObject, y:ndarray|ArrayLikeObject )\n    Computes the dot product of two vectors.\n","getegid":"\ngetegid()\n    Returns the effective numeric group identity of the calling process.\n","geteuid":"\ngeteuid()\n    Returns the effective numeric user identity of the calling process.\n","getgid":"\ngetgid()\n    Returns the numeric group identity of the calling process.\n","getGlobal":"\ngetGlobal( [codegen:boolean] )\n    Returns the global object.\n","getPrototypeOf":"\ngetPrototypeOf( value:any )\n    Returns the prototype of a provided object.\n","getuid":"\ngetuid()\n    Returns the numeric user identity of the calling process.\n","GLAISHER":"\nGLAISHER\n    Glaisher-Kinkelin constant.\n","graphemeClusters2iterator":"\ngraphemeClusters2iterator( src:string[, mapFcn:Function[, thisArg:any]] )\n    Returns an iterator which iterates over each grapheme cluster in a string.\n","graphemeClusters2iteratorRight":"\ngraphemeClusters2iteratorRight( src:string[, mapFcn:Function[, thisArg:any]] )\n    Returns an iterator which iterates from right to left over each grapheme\n    cluster in a string.\n","group":"\ngroup( collection:Array|TypedArray|Object, [options:Object,] \n  groups:Array|TypedArray|Object )\n    Groups values as arrays associated with distinct keys.\n","groupBy":"\ngroupBy( collection:Array|TypedArray|Object, [options:Object,] \n  indicator:Function )\n    Groups values according to an indicator function.\n","groupByAsync":"\ngroupByAsync( collection:Array|TypedArray|Object, [options:Object,] \n  indicator:Function, done:Function )\n    Groups values according to an indicator function.\n","groupByAsync.factory":"\ngroupByAsync.factory( [options:Object,] indicator:Function )\n    Returns a function which groups values according to an indicator function.\n","groupIn":"\ngroupIn( obj:Object|Array|TypedArray, [options:Object,] indicator:Function )\n    Group values according to an indicator function.\n","groupOwn":"\ngroupOwn( obj:Object|Array|TypedArray, [options:Object,] indicator:Function )\n    Group values according to an indicator function.\n","gswap":"\ngswap( x:ndarray|ArrayLikeObject, y:ndarray|ArrayLikeObject )\n    Interchanges two vectors.\n","HALF_LN2":"\nHALF_LN2\n    One half times the natural logarithm of `2`.\n","HALF_PI":"\nHALF_PI\n    One half times the mathematical constant `π`.\n","HARRISON_BOSTON_HOUSE_PRICES":"\nHARRISON_BOSTON_HOUSE_PRICES()\n    Returns a dataset derived from information collected by the US Census\n    Service concerning housing in Boston, Massachusetts (1978).\n","HARRISON_BOSTON_HOUSE_PRICES_CORRECTED":"\nHARRISON_BOSTON_HOUSE_PRICES_CORRECTED()\n    Returns a (corrected) dataset derived from information collected by the US\n    Census Service concerning housing in Boston, Massachusetts (1978).\n","hasArrayBufferSupport":"\nhasArrayBufferSupport()\n    Tests for native `ArrayBuffer` support.\n","hasArrowFunctionSupport":"\nhasArrowFunctionSupport()\n    Tests whether an environment supports native arrow functions.\n","hasAsyncAwaitSupport":"\nhasAsyncAwaitSupport()\n    Tests for native `async`/`await` support.\n","hasAsyncIteratorSymbolSupport":"\nhasAsyncIteratorSymbolSupport()\n    Tests for native `Symbol.asyncIterator` support.\n","hasAtobSupport":"\nhasAtobSupport()\n    Tests for native `atob` support.\n","hasBigInt64ArraySupport":"\nhasBigInt64ArraySupport()\n    Tests for native `BigInt64Array` support.\n","hasBigIntSupport":"\nhasBigIntSupport()\n    Tests for native `BigInt` support.\n","hasBigUint64ArraySupport":"\nhasBigUint64ArraySupport()\n    Tests for native `BigUint64Array` support.\n","hasBtoaSupport":"\nhasBtoaSupport()\n    Tests for native `btoa` support.\n","hasClassSupport":"\nhasClassSupport()\n    Tests for native `class` support.\n","hasDataViewSupport":"\nhasDataViewSupport()\n    Tests for native `DataView` support.\n","hasDefinePropertiesSupport":"\nhasDefinePropertiesSupport()\n    Tests for `Object.defineProperties` support.\n","hasDefinePropertySupport":"\nhasDefinePropertySupport()\n    Tests for `Object.defineProperty` support.\n","hasFloat32ArraySupport":"\nhasFloat32ArraySupport()\n    Tests for native `Float32Array` support.\n","hasFloat64ArraySupport":"\nhasFloat64ArraySupport()\n    Tests for native `Float64Array` support.\n","hasFunctionNameSupport":"\nhasFunctionNameSupport()\n    Tests for native function `name` support.\n","hasGeneratorSupport":"\nhasGeneratorSupport()\n    Tests whether an environment supports native generator functions.\n","hasGlobalThisSupport":"\nhasGlobalThisSupport()\n    Tests for `globalThis` support.\n","hasInt8ArraySupport":"\nhasInt8ArraySupport()\n    Tests for native `Int8Array` support.\n","hasInt16ArraySupport":"\nhasInt16ArraySupport()\n    Tests for native `Int16Array` support.\n","hasInt32ArraySupport":"\nhasInt32ArraySupport()\n    Tests for native `Int32Array` support.\n","hasIteratorSymbolSupport":"\nhasIteratorSymbolSupport()\n    Tests for native `Symbol.iterator` support.\n","hasMapSupport":"\nhasMapSupport()\n    Tests for native `Map` support.\n","hasNodeBufferSupport":"\nhasNodeBufferSupport()\n    Tests for native `Buffer` support.\n","hasOwnProp":"\nhasOwnProp( value:any, property:any )\n    Tests if an object has a specified property.\n","hasProp":"\nhasProp( value:any, property:any )\n    Tests if an object has a specified property, either own or inherited.\n","hasProxySupport":"\nhasProxySupport()\n    Tests whether an environment has native `Proxy` support.\n","hasSetSupport":"\nhasSetSupport()\n    Tests for native `Set` support.\n","hasSharedArrayBufferSupport":"\nhasSharedArrayBufferSupport()\n    Tests for native `SharedArrayBuffer` support.\n","hasSymbolSupport":"\nhasSymbolSupport()\n    Tests for native `Symbol` support.\n","hasToStringTagSupport":"\nhasToStringTagSupport()\n    Tests for native `toStringTag` support.\n","hasUint8ArraySupport":"\nhasUint8ArraySupport()\n    Tests for native `Uint8Array` support.\n","hasUint8ClampedArraySupport":"\nhasUint8ClampedArraySupport()\n    Tests for native `Uint8ClampedArray` support.\n","hasUint16ArraySupport":"\nhasUint16ArraySupport()\n    Tests for native `Uint16Array` support.\n","hasUint32ArraySupport":"\nhasUint32ArraySupport()\n    Tests for native `Uint32Array` support.\n","hasUTF16SurrogatePairAt":"\nhasUTF16SurrogatePairAt( str:string, pos:integer )\n    Tests if a position in a string marks the start of a UTF-16 surrogate pair.\n","hasWeakMapSupport":"\nhasWeakMapSupport()\n    Tests for native `WeakMap` support.\n","hasWeakSetSupport":"\nhasWeakSetSupport()\n    Tests for native `WeakSet` support.\n","hasWebAssemblySupport":"\nhasWebAssemblySupport()\n    Tests for native WebAssembly support.\n","headercase":"\nheadercase( str:string )\n    Converts a string to HTTP header case.\n","HERNDON_VENUS_SEMIDIAMETERS":"\nHERNDON_VENUS_SEMIDIAMETERS()\n    Returns fifteen observations of the vertical semidiameter of Venus, made by\n    Lieutenant Herndon, with the meridian circle at Washington, in the year\n    1846.\n","homedir":"\nhomedir()\n    Returns the current user's home directory.\n","HOURS_IN_DAY":"\nHOURS_IN_DAY\n    Number of hours in a day.\n","HOURS_IN_WEEK":"\nHOURS_IN_WEEK\n    Number of hours in a week.\n","hoursInMonth":"\nhoursInMonth( [month:string|Date|integer[, year:integer]] )\n    Returns the number of hours in a month.\n","hoursInYear":"\nhoursInYear( [value:integer|Date] )\n    Returns the number of hours in a year according to the Gregorian calendar.\n","httpServer":"\nhttpServer( [options:Object,] [requestListener:Function] )\n    Returns a function to create an HTTP server.\n","identity":"\nidentity( x:any )\n    Identity function.\n","ifelse":"\nifelse( bool:boolean, x:any, y:any )\n    If a condition is truthy, returns `x`; otherwise, returns `y`.\n","ifelseAsync":"\nifelseAsync( predicate:Function, x:any, y:any, done:Function )\n    If a predicate function returns a truthy value, returns `x`; otherwise,\n    returns `y`.\n","ifthen":"\nifthen( bool:boolean, x:Function, y:Function )\n    If a condition is truthy, invoke `x`; otherwise, invoke `y`.\n","ifthenAsync":"\nifthenAsync( predicate:Function, x:Function, y:Function, done:Function )\n    If a predicate function returns a truthy value, invokes `x`; otherwise,\n    invokes `y`.\n","imag":"\nimag( z:Complex128 )\n    Returns the imaginary component of a double-precision complex floating-point\n    number.\n","imagf":"\nimagf( z:Complex64 )\n    Returns the imaginary component of a single-precision complex floating-point\n    number.\n","IMG_ACANTHUS_MOLLIS":"\nIMG_ACANTHUS_MOLLIS()\n    Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n    print *Acanthus mollis*.\n","IMG_AIRPLANE_FROM_ABOVE":"\nIMG_AIRPLANE_FROM_ABOVE()\n    Returns a `Buffer` containing image data of Fédèle Azari's gelatin silver\n    print of an airplane, viewed from above looking down.\n","IMG_ALLIUM_OREOPHILUM":"\nIMG_ALLIUM_OREOPHILUM()\n    Returns a `Buffer` containing image data of Karl Blossfeldt's gelatin silver\n    print *Allium ostrowskianum*.\n","IMG_BLACK_CANYON":"\nIMG_BLACK_CANYON()\n    Returns a `Buffer` containing image data of Timothy H. O'Sullivan's albumen\n    silver print *Black Cañon, Colorado River, From Camp 8, Looking Above*.\n","IMG_DUST_BOWL_HOME":"\nIMG_DUST_BOWL_HOME()\n    Returns a `Buffer` containing image data of Dorothea Lange's gelatin silver\n    print of an abandoned Dust Bowl home.\n","IMG_FRENCH_ALPINE_LANDSCAPE":"\nIMG_FRENCH_ALPINE_LANDSCAPE()\n    Returns a `Buffer` containing image data of Adolphe Braun's carbon print of\n    a French alpine landscape.\n","IMG_LOCOMOTION_HOUSE_CAT":"\nIMG_LOCOMOTION_HOUSE_CAT()\n    Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n    collotype of a house cat (24 views).\n","IMG_LOCOMOTION_NUDE_MALE":"\nIMG_LOCOMOTION_NUDE_MALE()\n    Returns a `Buffer` containing image data of Eadweard J. Muybridge's\n    collotype of a nude male moving in place (48 views).\n","IMG_MARCH_PASTORAL":"\nIMG_MARCH_PASTORAL()\n    Returns a `Buffer` containing image data of Peter Henry Emerson's\n    photogravure of sheep in a pastoral setting.\n","IMG_NAGASAKI_BOATS":"\nIMG_NAGASAKI_BOATS()\n    Returns a `Buffer` containing image data of Felice Beato's albumen silver\n    print of boats in a river in Nagasaki.\n","incrapcorr":"\nincrapcorr( [mx:number, my:number] )\n    Returns an accumulator function which incrementally computes the absolute\n    value of the sample Pearson product-moment correlation coefficient.\n","incrBinaryClassification":"\nincrBinaryClassification( N:integer[, options:Object] )\n    Returns an accumulator function which incrementally performs binary\n    classification using stochastic gradient descent (SGD).\n","incrcount":"\nincrcount()\n    Returns an accumulator function which incrementally updates a count.\n","incrcovariance":"\nincrcovariance( [mx:number, my:number] )\n    Returns an accumulator function which incrementally computes an unbiased\n    sample covariance.\n","incrcovmat":"\nincrcovmat( out:integer|ndarray[, means:ndarray] )\n    Returns an accumulator function which incrementally computes an unbiased\n    sample covariance matrix.\n","incrcv":"\nincrcv( [mean:number] )\n    Returns an accumulator function which incrementally computes the coefficient\n    of variation (CV).\n","increwmean":"\nincrewmean( α:number )\n    Returns an accumulator function which incrementally computes an\n    exponentially weighted mean, where α is a smoothing factor between 0 and 1.\n","increwstdev":"\nincrewstdev( α:number )\n    Returns an accumulator function which incrementally computes an\n    exponentially weighted standard deviation, where α is a smoothing factor\n    between 0 and 1.\n","increwvariance":"\nincrewvariance( α:number )\n    Returns an accumulator function which incrementally computes an\n    exponentially weighted variance, where α is a smoothing factor between 0 and\n    1.\n","incrgmean":"\nincrgmean()\n    Returns an accumulator function which incrementally computes a geometric\n    mean.\n","incrgrubbs":"\nincrgrubbs( [options:Object] )\n    Returns an accumulator function which incrementally performs Grubbs' test\n    for detecting outliers.\n","incrhmean":"\nincrhmean()\n    Returns an accumulator function which incrementally computes a harmonic\n    mean.\n","incrkmeans":"\nincrkmeans( k:integer|ndarray[, ndims:integer][, options:Object] )\n    Returns an accumulator function which incrementally partitions data into `k`\n    clusters.\n","incrkurtosis":"\nincrkurtosis()\n    Returns an accumulator function which incrementally computes a corrected\n    sample excess kurtosis.\n","incrmaape":"\nincrmaape()\n    Returns an accumulator function which incrementally computes the mean\n    arctangent absolute percentage error (MAAPE).\n","incrmae":"\nincrmae()\n    Returns an accumulator function which incrementally computes the mean\n    absolute error (MAE).\n","incrmapcorr":"\nincrmapcorr( W:integer[, mx:number, my:number] )\n    Returns an accumulator function which incrementally computes a moving\n    sample absolute Pearson product-moment correlation coefficient.\n","incrmape":"\nincrmape()\n    Returns an accumulator function which incrementally computes the mean\n    absolute percentage error (MAPE).\n","incrmax":"\nincrmax()\n    Returns an accumulator function which incrementally computes a maximum\n    value.\n","incrmaxabs":"\nincrmaxabs()\n    Returns an accumulator function which incrementally computes a maximum\n    absolute value.\n","incrmcovariance":"\nincrmcovariance( W:integer[, mx:number, my:number] )\n    Returns an accumulator function which incrementally computes a moving\n    unbiased sample covariance.\n","incrmcv":"\nincrmcv( W:integer[, mean:number] )\n    Returns an accumulator function which incrementally computes a moving\n    coefficient of variation (CV).\n","incrmda":"\nincrmda()\n    Returns an accumulator function which incrementally computes the mean\n    directional accuracy (MDA).\n","incrme":"\nincrme()\n    Returns an accumulator function which incrementally computes the mean error\n    (ME).\n","incrmean":"\nincrmean()\n    Returns an accumulator function which incrementally computes an arithmetic\n    mean.\n","incrmeanabs":"\nincrmeanabs()\n    Returns an accumulator function which incrementally computes an arithmetic\n    mean of absolute values.\n","incrmeanabs2":"\nincrmeanabs2()\n    Returns an accumulator function which incrementally computes an arithmetic\n    mean of squared absolute values.\n","incrmeanstdev":"\nincrmeanstdev( [out:Array|TypedArray] )\n    Returns an accumulator function which incrementally computes an arithmetic\n    mean and corrected sample standard deviation.\n","incrmeanvar":"\nincrmeanvar( [out:Array|TypedArray] )\n    Returns an accumulator function which incrementally computes an arithmetic\n    mean and unbiased sample variance.\n","incrmgmean":"\nincrmgmean( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    geometric mean.\n","incrmgrubbs":"\nincrmgrubbs( W:integer[, options:Object] )\n    Returns an accumulator function which incrementally performs a moving\n    Grubbs' test for detecting outliers.\n","incrmhmean":"\nincrmhmean( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    harmonic mean.\n","incrmidrange":"\nincrmidrange()\n    Returns an accumulator function which incrementally computes a mid-range.\n","incrmin":"\nincrmin()\n    Returns an accumulator function which incrementally computes a minimum\n    value.\n","incrminabs":"\nincrminabs()\n    Returns an accumulator function which incrementally computes a minimum\n    absolute value.\n","incrminmax":"\nincrminmax( [out:Array|TypedArray] )\n    Returns an accumulator function which incrementally computes a minimum and\n    maximum.\n","incrminmaxabs":"\nincrminmaxabs( [out:Array|TypedArray] )\n    Returns an accumulator function which incrementally computes a minimum and\n    maximum absolute value.\n","incrmmaape":"\nincrmmaape( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    mean arctangent absolute percentage error (MAAPE).\n","incrmmae":"\nincrmmae( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    mean absolute error (MAE).\n","incrmmape":"\nincrmmape( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    mean absolute percentage error (MAPE).\n","incrmmax":"\nincrmmax( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    maximum value.\n","incrmmaxabs":"\nincrmmaxabs( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    maximum absolute value.\n","incrmmda":"\nincrmmda( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    mean directional accuracy (MDA).\n","incrmme":"\nincrmme( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    mean error (ME).\n","incrmmean":"\nincrmmean( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    arithmetic mean.\n","incrmmeanabs":"\nincrmmeanabs( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    arithmetic mean of absolute values.\n","incrmmeanabs2":"\nincrmmeanabs2( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    arithmetic mean of squared absolute values.\n","incrmmeanstdev":"\nincrmmeanstdev( [out:Array|TypedArray,] W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    arithmetic mean and corrected sample standard deviation.\n","incrmmeanvar":"\nincrmmeanvar( [out:Array|TypedArray,] W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    arithmetic mean and unbiased sample variance.\n","incrmmidrange":"\nincrmmidrange( W:integer )\n    Returns an accumulator function which incrementally computes a moving mid-\n    range.\n","incrmmin":"\nincrmmin( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    minimum value.\n","incrmminabs":"\nincrmminabs( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    minimum absolute value.\n","incrmminmax":"\nincrmminmax( [out:Array|TypedArray,] W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    minimum and maximum.\n","incrmminmaxabs":"\nincrmminmaxabs( [out:Array|TypedArray,] W:integer )\n    Returns an accumulator function which incrementally computes moving minimum\n    and maximum absolute values.\n","incrmmpe":"\nincrmmpe( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    mean percentage error (MPE).\n","incrmmse":"\nincrmmse( W:integer )\n    Returns an accumulator function which incrementally computes a moving mean\n    squared error (MSE).\n","incrmpcorr":"\nincrmpcorr( W:integer[, mx:number, my:number] )\n    Returns an accumulator function which incrementally computes a moving\n    sample Pearson product-moment correlation coefficient.\n","incrmpcorr2":"\nincrmpcorr2( W:integer[, mx:number, my:number] )\n    Returns an accumulator function which incrementally computes a moving\n    squared sample Pearson product-moment correlation coefficient.\n","incrmpcorrdist":"\nincrmpcorrdist( W:integer[, mx:number, my:number] )\n    Returns an accumulator function which incrementally computes a moving\n    sample Pearson product-moment correlation distance.\n","incrmpe":"\nincrmpe()\n    Returns an accumulator function which incrementally computes the mean\n    percentage error (MPE).\n","incrmprod":"\nincrmprod( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    product.\n","incrmrange":"\nincrmrange( W:integer )\n    Returns an accumulator function which incrementally computes a moving range.\n","incrmrmse":"\nincrmrmse( W:integer )\n    Returns an accumulator function which incrementally computes a moving root\n    mean squared error (RMSE).\n","incrmrss":"\nincrmrss( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    residual sum of squares (RSS).\n","incrmse":"\nincrmse()\n    Returns an accumulator function which incrementally computes the mean\n    squared error (MSE).\n","incrmstdev":"\nincrmstdev( W:integer[, mean:number] )\n    Returns an accumulator function which incrementally computes a moving\n    corrected sample standard deviation.\n","incrmsum":"\nincrmsum( W:integer )\n    Returns an accumulator function which incrementally computes a moving sum.\n","incrmsumabs":"\nincrmsumabs( W:integer )\n    Returns an accumulator function which incrementally computes a moving sum of\n    absolute values.\n","incrmsumabs2":"\nincrmsumabs2( W:integer )\n    Returns an accumulator function which incrementally computes a moving sum of\n    squared absolute values.\n","incrmsummary":"\nincrmsummary( W:integer )\n    Returns an accumulator function which incrementally computes a moving\n    statistical summary.\n","incrmsumprod":"\nincrmsumprod( W:integer )\n    Returns an accumulator function which incrementally computes a moving sum of\n    products.\n","incrmvariance":"\nincrmvariance( W:integer[, mean:number] )\n    Returns an accumulator function which incrementally computes a moving\n    unbiased sample variance.\n","incrmvmr":"\nincrmvmr( W:integer[, mean:number] )\n    Returns an accumulator function which incrementally computes a moving\n    variance-to-mean (VMR).\n","incrnancount":"\nincrnancount()\n    Returns an accumulator function which incrementally updates a count,\n    ignoring `NaN` values.\n","incrnansum":"\nincrnansum()\n    Returns an accumulator function which incrementally computes a sum, ignoring\n    `NaN` values.\n","incrnansumabs":"\nincrnansumabs()\n    Returns an accumulator function which incrementally computes a sum of\n    absolute values, ignoring NaN values.\n","incrnansumabs2":"\nincrnansumabs2()\n    Returns an accumulator function which incrementally computes a sum of\n    squared absolute values, ignoring NaN values.\n","incrpcorr":"\nincrpcorr( [mx:number, my:number] )\n    Returns an accumulator function which incrementally computes a sample\n    Pearson product-moment correlation coefficient.\n","incrpcorr2":"\nincrpcorr2( [mx:number, my:number] )\n    Returns an accumulator function which incrementally computes the squared\n    sample Pearson product-moment correlation coefficient.\n","incrpcorrdist":"\nincrpcorrdist( [mx:number, my:number] )\n    Returns an accumulator function which incrementally computes a sample\n    Pearson product-moment correlation distance.\n","incrpcorrdistmat":"\nincrpcorrdistmat( out:integer|ndarray[, means:ndarray] )\n    Returns an accumulator function which incrementally computes a sample\n    Pearson product-moment correlation distance matrix.\n","incrpcorrmat":"\nincrpcorrmat( out:integer|ndarray[, means:ndarray] )\n    Returns an accumulator function which incrementally computes a sample\n    Pearson product-moment correlation matrix.\n","incrprod":"\nincrprod()\n    Returns an accumulator function which incrementally computes a product.\n","incrrange":"\nincrrange()\n    Returns an accumulator function which incrementally computes a range.\n","incrrmse":"\nincrrmse()\n    Returns an accumulator function which incrementally computes the root mean\n    squared error (RMSE).\n","incrrss":"\nincrrss()\n    Returns an accumulator function which incrementally computes the residual\n    sum of squares (RSS).\n","incrskewness":"\nincrskewness()\n    Returns an accumulator function which incrementally computes a corrected\n    sample skewness.\n","incrspace":"\nincrspace( start:number, stop:number[, increment:number] )\n    Generates a linearly spaced numeric array using a provided increment.\n","incrstdev":"\nincrstdev( [mean:number] )\n    Returns an accumulator function which incrementally computes a corrected\n    sample standard deviation.\n","incrsum":"\nincrsum()\n    Returns an accumulator function which incrementally computes a sum.\n","incrsumabs":"\nincrsumabs()\n    Returns an accumulator function which incrementally computes a sum of\n    absolute values.\n","incrsumabs2":"\nincrsumabs2()\n    Returns an accumulator function which incrementally computes a sum of\n    squared absolute values.\n","incrsummary":"\nincrsummary()\n    Returns an accumulator function which incrementally computes a statistical\n    summary.\n","incrsumprod":"\nincrsumprod()\n    Returns an accumulator function which incrementally computes a sum of\n    products.\n","incrvariance":"\nincrvariance( [mean:number] )\n    Returns an accumulator function which incrementally computes an unbiased\n    sample variance.\n","incrvmr":"\nincrvmr( [mean:number] )\n    Returns an accumulator function which incrementally computes a variance-to-\n    mean ratio (VMR).\n","incrwmean":"\nincrwmean()\n    Returns an accumulator function which incrementally computes a weighted\n    arithmetic mean.\n","ind2sub":"\nind2sub( shape:ArrayLike, idx:integer[, options:Object] )\n    Converts a linear index to an array of subscripts.\n","ind2sub.assign":"\nind2sub.assign( shape:ArrayLike, idx:integer[, options:Object], \n  out:Array|TypedArray|Object )\n    Converts a linear index to an array of subscripts and assigns results to a\n    provided output array.\n","indexOf":"\nindexOf( arr:ArrayLike, searchElement:any[, fromIndex:integer] )\n    Returns the first index at which a given element can be found.\n","inherit":"\ninherit( ctor:Object|Function, superCtor:Object|Function )\n    Prototypical inheritance by replacing the prototype of one constructor with\n    the prototype of another constructor.\n","inheritedEnumerableProperties":"\ninheritedEnumerableProperties( value:any[, level:integer] )\n    Returns an array of an object's inherited enumerable property names and\n    symbols.\n","inheritedEnumerablePropertySymbols":"\ninheritedEnumerablePropertySymbols( value:any[, level:integer] )\n    Returns an array of an object's inherited enumerable symbol properties.\n","inheritedKeys":"\ninheritedKeys( value:any[, level:integer] )\n    Returns an array of an object's inherited enumerable property names.\n","inheritedNonEnumerableProperties":"\ninheritedNonEnumerableProperties( value:any[, level:integer] )\n    Returns an array of an object's inherited non-enumerable property names and\n    symbols.\n","inheritedNonEnumerablePropertyNames":"\ninheritedNonEnumerablePropertyNames( value:any[, level:integer] )\n    Returns an array of an object's inherited non-enumerable property names.\n","inheritedNonEnumerablePropertySymbols":"\ninheritedNonEnumerablePropertySymbols( value:any[, level:integer] )\n    Returns an array of an object's inherited non-enumerable symbol properties.\n","inheritedProperties":"\ninheritedProperties( value:any[, level:integer] )\n    Returns an array of an object's inherited property names and symbols.\n","inheritedPropertyDescriptor":"\ninheritedPropertyDescriptor( value:any, property:string|symbol[, \n  level:integer] )\n    Returns a property descriptor for an object's inherited property.\n","inheritedPropertyDescriptors":"\ninheritedPropertyDescriptors( value:any[, level:integer] )\n    Returns an object's inherited property descriptors.\n","inheritedPropertyNames":"\ninheritedPropertyNames( value:any[, level:integer] )\n    Returns an array of an object's inherited enumerable and non-enumerable\n    property names.\n","inheritedPropertySymbols":"\ninheritedPropertySymbols( value:any[, level:integer] )\n    Returns an array of an object's inherited symbol properties.\n","inheritedWritableProperties":"\ninheritedWritableProperties( value:any[, level:integer] )\n    Returns an array of an object's inherited writable property names and\n    symbols.\n","inheritedWritablePropertyNames":"\ninheritedWritablePropertyNames( value:any[, level:integer] )\n    Returns an array of an object's inherited writable property names.\n","inheritedWritablePropertySymbols":"\ninheritedWritablePropertySymbols( value:any[, level:integer] )\n    Returns an array of an object's inherited writable symbol properties.\n","inmap":"\ninmap( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n    Invokes a function for each element in a collection and updates the\n    collection in-place.\n","inmapAsync":"\ninmapAsync( collection:Array|TypedArray|Object, [options:Object,] fcn:Function, \n  done:Function )\n    Invokes a function once for each element in a collection and updates a\n    collection in-place.\n","inmapAsync.factory":"\ninmapAsync.factory( [options:Object,] fcn:Function )\n    Returns a function which invokes a function once for each element in a\n    collection and updates a collection in-place.\n","inmapRight":"\ninmapRight( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n    Invokes a function for each element in a collection and updates the\n    collection in-place, iterating from right to left.\n","inmapRightAsync":"\ninmapRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n  fcn:Function, done:Function )\n    Invokes a function once for each element in a collection and updates a\n    collection in-place, iterating from right to left.\n","inmapRightAsync.factory":"\ninmapRightAsync.factory( [options:Object,] fcn:Function )\n    Returns a function which invokes a function once for each element in a\n    collection and updates a collection in-place, iterating from right to left.\n","inspectSinkStream":"\ninspectSinkStream( [options:Object,] clbk:Function )\n    Returns a writable stream for inspecting stream data.\n","inspectSinkStream.factory":"\ninspectSinkStream.factory( [options:Object] )\n    Returns a function for creating writable streams for inspecting stream data.\n","inspectSinkStream.objectMode":"\ninspectSinkStream.objectMode( [options:Object,] clbk:Function )\n    Returns an \"objectMode\" writable stream for inspecting stream data.\n","inspectStream":"\ninspectStream( [options:Object,] clbk:Function )\n    Returns a transform stream for inspecting stream data.\n","inspectStream.factory":"\ninspectStream.factory( [options:Object] )\n    Returns a function for creating transform streams for inspecting stream\n    data.\n","inspectStream.objectMode":"\ninspectStream.objectMode( [options:Object,] clbk:Function )\n    Returns an \"objectMode\" transform stream for inspecting stream data.\n","instanceOf":"\ninstanceOf( value:any, constructor:Function )\n    Tests whether a value has in its prototype chain a specified constructor as\n    a prototype property.\n","INT8_MAX":"\nINT8_MAX\n    Maximum signed 8-bit integer.\n","INT8_MIN":"\nINT8_MIN\n    Minimum signed 8-bit integer.\n","INT8_NUM_BYTES":"\nINT8_NUM_BYTES\n    Size (in bytes) of an 8-bit signed integer.\n","Int8Array":"\nInt8Array()\n    A typed array constructor which returns a typed array representing an array\n    of twos-complement 8-bit signed integers in the platform byte order.\n\nInt8Array( length:integer )\n    Returns a typed array having a specified length.\n\nInt8Array( typedarray:TypedArray )\n    Creates a typed array from another typed array.\n\nInt8Array( obj:Object )\n    Creates a typed array from an array-like object or iterable.\n\nInt8Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a typed array view of an ArrayBuffer.\n","Int8Array.from":"\nInt8Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n    Creates a new typed array from an array-like object or an iterable.\n","Int8Array.of":"\nInt8Array.of( element0:number[, element1:number[, ...elementN:number]] )\n    Creates a new typed array from a variable number of arguments.\n","Int8Array.BYTES_PER_ELEMENT":"\nInt8Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Int8Array.name":"\nInt8Array.name\n    Typed array constructor name.\n","Int8Array.prototype.buffer":"\nInt8Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n","Int8Array.prototype.byteLength":"\nInt8Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n","Int8Array.prototype.byteOffset":"\nInt8Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n","Int8Array.prototype.BYTES_PER_ELEMENT":"\nInt8Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Int8Array.prototype.length":"\nInt8Array.prototype.length\n    Read-only property which returns the number of view elements.\n","Int8Array.prototype.copyWithin":"\nInt8Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","Int8Array.prototype.entries":"\nInt8Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","Int8Array.prototype.every":"\nInt8Array.prototype.every( predicate:Function[, thisArg:Any] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n","Int8Array.prototype.fill":"\nInt8Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n","Int8Array.prototype.filter":"\nInt8Array.prototype.filter( predicate:Function[, thisArg:Any] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n","Int8Array.prototype.find":"\nInt8Array.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n","Int8Array.prototype.findIndex":"\nInt8Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n","Int8Array.prototype.forEach":"\nInt8Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n    Invokes a callback for each array element.\n","Int8Array.prototype.includes":"\nInt8Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a search element.\n","Int8Array.prototype.indexOf":"\nInt8Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n","Int8Array.prototype.join":"\nInt8Array.prototype.join( [separator:string] )\n    Serializes an array by joining all array elements as a string.\n","Int8Array.prototype.keys":"\nInt8Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n","Int8Array.prototype.lastIndexOf":"\nInt8Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n","Int8Array.prototype.map":"\nInt8Array.prototype.map( fcn:Function[, thisArg:Any] )\n    Maps each array element to an element in a new typed array.\n","Int8Array.prototype.reduce":"\nInt8Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n","Int8Array.prototype.reduceRight":"\nInt8Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n","Int8Array.prototype.reverse":"\nInt8Array.prototype.reverse()\n    Reverses an array *in-place*.\n","Int8Array.prototype.set":"\nInt8Array.prototype.set( arr:ArrayLike[, offset:integer] )\n    Sets array elements.\n","Int8Array.prototype.slice":"\nInt8Array.prototype.slice( [begin:integer[, end:integer]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n","Int8Array.prototype.some":"\nInt8Array.prototype.some( predicate:Function[, thisArg:Any] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n","Int8Array.prototype.sort":"\nInt8Array.prototype.sort( [compareFunction:Function] )\n    Sorts an array *in-place*.\n","Int8Array.prototype.subarray":"\nInt8Array.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n","Int8Array.prototype.toLocaleString":"\nInt8Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n    Serializes an array as a locale-specific string.\n","Int8Array.prototype.toString":"\nInt8Array.prototype.toString()\n    Serializes an array as a string.\n","Int8Array.prototype.values":"\nInt8Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n","INT16_MAX":"\nINT16_MAX\n    Maximum signed 16-bit integer.\n","INT16_MIN":"\nINT16_MIN\n    Minimum signed 16-bit integer.\n","INT16_NUM_BYTES":"\nINT16_NUM_BYTES\n    Size (in bytes) of a 16-bit signed integer.\n","Int16Array":"\nInt16Array()\n    A typed array constructor which returns a typed array representing an array\n    of twos-complement 16-bit signed integers in the platform byte order.\n\nInt16Array( length:integer )\n    Returns a typed array having a specified length.\n\nInt16Array( typedarray:TypedArray )\n    Creates a typed array from another typed array.\n\nInt16Array( obj:Object )\n    Creates a typed array from an array-like object or iterable.\n\nInt16Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a typed array view of an ArrayBuffer.\n","Int16Array.from":"\nInt16Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n    Creates a new typed array from an array-like object or an iterable.\n","Int16Array.of":"\nInt16Array.of( element0:number[, element1:number[, ...elementN:number]] )\n    Creates a new typed array from a variable number of arguments.\n","Int16Array.BYTES_PER_ELEMENT":"\nInt16Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Int16Array.name":"\nInt16Array.name\n    Typed array constructor name.\n","Int16Array.prototype.buffer":"\nInt16Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n","Int16Array.prototype.byteLength":"\nInt16Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n","Int16Array.prototype.byteOffset":"\nInt16Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n","Int16Array.prototype.BYTES_PER_ELEMENT":"\nInt16Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Int16Array.prototype.length":"\nInt16Array.prototype.length\n    Read-only property which returns the number of view elements.\n","Int16Array.prototype.copyWithin":"\nInt16Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","Int16Array.prototype.entries":"\nInt16Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","Int16Array.prototype.every":"\nInt16Array.prototype.every( predicate:Function[, thisArg:Any] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n","Int16Array.prototype.fill":"\nInt16Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n","Int16Array.prototype.filter":"\nInt16Array.prototype.filter( predicate:Function[, thisArg:Any] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n","Int16Array.prototype.find":"\nInt16Array.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n","Int16Array.prototype.findIndex":"\nInt16Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n","Int16Array.prototype.forEach":"\nInt16Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n    Invokes a callback for each array element.\n","Int16Array.prototype.includes":"\nInt16Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a search element.\n","Int16Array.prototype.indexOf":"\nInt16Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n","Int16Array.prototype.join":"\nInt16Array.prototype.join( [separator:string] )\n    Serializes an array by joining all array elements as a string.\n","Int16Array.prototype.keys":"\nInt16Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n","Int16Array.prototype.lastIndexOf":"\nInt16Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n","Int16Array.prototype.map":"\nInt16Array.prototype.map( fcn:Function[, thisArg:Any] )\n    Maps each array element to an element in a new typed array.\n","Int16Array.prototype.reduce":"\nInt16Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n","Int16Array.prototype.reduceRight":"\nInt16Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n","Int16Array.prototype.reverse":"\nInt16Array.prototype.reverse()\n    Reverses an array *in-place*.\n","Int16Array.prototype.set":"\nInt16Array.prototype.set( arr:ArrayLike[, offset:integer] )\n    Sets array elements.\n","Int16Array.prototype.slice":"\nInt16Array.prototype.slice( [begin:integer[, end:integer]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n","Int16Array.prototype.some":"\nInt16Array.prototype.some( predicate:Function[, thisArg:Any] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n","Int16Array.prototype.sort":"\nInt16Array.prototype.sort( [compareFunction:Function] )\n    Sorts an array *in-place*.\n","Int16Array.prototype.subarray":"\nInt16Array.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n","Int16Array.prototype.toLocaleString":"\nInt16Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n    Serializes an array as a locale-specific string.\n","Int16Array.prototype.toString":"\nInt16Array.prototype.toString()\n    Serializes an array as a string.\n","Int16Array.prototype.values":"\nInt16Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n","INT32_MAX":"\nINT32_MAX\n    Maximum signed 32-bit integer.\n","INT32_MIN":"\nINT32_MIN\n    Minimum signed 32-bit integer.\n","INT32_NUM_BYTES":"\nINT32_NUM_BYTES\n    Size (in bytes) of a 32-bit signed integer.\n","Int32Array":"\nInt32Array()\n    A typed array constructor which returns a typed array representing an array\n    of twos-complement 32-bit signed integers in the platform byte order.\n\nInt32Array( length:integer )\n    Returns a typed array having a specified length.\n\nInt32Array( typedarray:TypedArray )\n    Creates a typed array from another typed array.\n\nInt32Array( obj:Object )\n    Creates a typed array from an array-like object or iterable.\n\nInt32Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a typed array view of an ArrayBuffer.\n","Int32Array.from":"\nInt32Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n    Creates a new typed array from an array-like object or an iterable.\n","Int32Array.of":"\nInt32Array.of( element0:number[, element1:number[, ...elementN:number]] )\n    Creates a new typed array from a variable number of arguments.\n","Int32Array.BYTES_PER_ELEMENT":"\nInt32Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Int32Array.name":"\nInt32Array.name\n    Typed array constructor name.\n","Int32Array.prototype.buffer":"\nInt32Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n","Int32Array.prototype.byteLength":"\nInt32Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n","Int32Array.prototype.byteOffset":"\nInt32Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n","Int32Array.prototype.BYTES_PER_ELEMENT":"\nInt32Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Int32Array.prototype.length":"\nInt32Array.prototype.length\n    Read-only property which returns the number of view elements.\n","Int32Array.prototype.copyWithin":"\nInt32Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","Int32Array.prototype.entries":"\nInt32Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","Int32Array.prototype.every":"\nInt32Array.prototype.every( predicate:Function[, thisArg:Any] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n","Int32Array.prototype.fill":"\nInt32Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n","Int32Array.prototype.filter":"\nInt32Array.prototype.filter( predicate:Function[, thisArg:Any] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n","Int32Array.prototype.find":"\nInt32Array.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n","Int32Array.prototype.findIndex":"\nInt32Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n","Int32Array.prototype.forEach":"\nInt32Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n    Invokes a callback for each array element.\n","Int32Array.prototype.includes":"\nInt32Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a search element.\n","Int32Array.prototype.indexOf":"\nInt32Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n","Int32Array.prototype.join":"\nInt32Array.prototype.join( [separator:string] )\n    Serializes an array by joining all array elements as a string.\n","Int32Array.prototype.keys":"\nInt32Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n","Int32Array.prototype.lastIndexOf":"\nInt32Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n","Int32Array.prototype.map":"\nInt32Array.prototype.map( fcn:Function[, thisArg:Any] )\n    Maps each array element to an element in a new typed array.\n","Int32Array.prototype.reduce":"\nInt32Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n","Int32Array.prototype.reduceRight":"\nInt32Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n","Int32Array.prototype.reverse":"\nInt32Array.prototype.reverse()\n    Reverses an array *in-place*.\n","Int32Array.prototype.set":"\nInt32Array.prototype.set( arr:ArrayLike[, offset:integer] )\n    Sets array elements.\n","Int32Array.prototype.slice":"\nInt32Array.prototype.slice( [begin:integer[, end:integer]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n","Int32Array.prototype.some":"\nInt32Array.prototype.some( predicate:Function[, thisArg:Any] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n","Int32Array.prototype.sort":"\nInt32Array.prototype.sort( [compareFunction:Function] )\n    Sorts an array *in-place*.\n","Int32Array.prototype.subarray":"\nInt32Array.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n","Int32Array.prototype.toLocaleString":"\nInt32Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n    Serializes an array as a locale-specific string.\n","Int32Array.prototype.toString":"\nInt32Array.prototype.toString()\n    Serializes an array as a string.\n","Int32Array.prototype.values":"\nInt32Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n","IS_BIG_ENDIAN":"\nIS_BIG_ENDIAN\n    Boolean indicating if the environment is big endian.\n","IS_BROWSER":"\nIS_BROWSER\n    Boolean indicating if the runtime is a web browser.\n","IS_DARWIN":"\nIS_DARWIN\n    Boolean indicating if the current process is running on Darwin.\n","IS_DOCKER":"\nIS_DOCKER\n    Boolean indicating if the process is running in a Docker container.\n","IS_ELECTRON":"\nIS_ELECTRON\n    Boolean indicating if the runtime is Electron.\n","IS_ELECTRON_MAIN":"\nIS_ELECTRON_MAIN\n    Boolean indicating if the runtime is the main Electron process.\n","IS_ELECTRON_RENDERER":"\nIS_ELECTRON_RENDERER\n    Boolean indicating if the runtime is the Electron renderer process.\n","IS_LITTLE_ENDIAN":"\nIS_LITTLE_ENDIAN\n    Boolean indicating if the environment is little endian.\n","IS_MOBILE":"\nIS_MOBILE\n    Boolean indicating if the current environment is a mobile device.\n","IS_NODE":"\nIS_NODE\n    Boolean indicating if the runtime is Node.js.\n","IS_TOUCH_DEVICE":"\nIS_TOUCH_DEVICE\n    Boolean indicating if the current environment is a touch device.\n","IS_WEB_WORKER":"\nIS_WEB_WORKER\n    Boolean indicating if the runtime is a web worker.\n","IS_WINDOWS":"\nIS_WINDOWS\n    Boolean indicating if the current process is running on Windows.\n","isAbsoluteHttpURI":"\nisAbsoluteHttpURI( value:any )\n    Tests whether a value is an absolute HTTP(S) URI.\n","isAbsolutePath":"\nisAbsolutePath( value:any )\n    Tests if a value is an absolute path.\n","isAbsolutePath.posix":"\nisAbsolutePath.posix( value:any )\n    Tests if a value is a POSIX absolute path.\n","isAbsolutePath.win32":"\nisAbsolutePath.win32( value:any )\n    Tests if a value is a Windows absolute path.\n","isAbsoluteURI":"\nisAbsoluteURI( value:any )\n    Tests whether a value is an absolute URI.\n","isAccessorArray":"\nisAccessorArray( value:any )\n    Tests if a value is an array-like object supporting the accessor (get/set)\n    protocol.\n","isAccessorProperty":"\nisAccessorProperty( value:any, property:any )\n    Tests if an object's own property has an accessor descriptor.\n","isAccessorPropertyIn":"\nisAccessorPropertyIn( value:any, property:any )\n    Tests if an object's own or inherited property has an accessor descriptor.\n","isAlphagram":"\nisAlphagram( value:any )\n    Tests if a value is an alphagram (i.e., a sequence of characters arranged in\n    alphabetical order).\n","isAlphaNumeric":"\nisAlphaNumeric( str:string )\n    Tests whether a string contains only alphanumeric characters.\n","isAnagram":"\nisAnagram( str:string, value:any )\n    Tests if a value is an anagram.\n","isArguments":"\nisArguments( value:any )\n    Tests if a value is an arguments object.\n","isArray":"\nisArray( value:any )\n    Tests if a value is an array.\n","isArrayArray":"\nisArrayArray( value:any )\n    Tests if a value is an array of arrays.\n","isArrayBuffer":"\nisArrayBuffer( value:any )\n    Tests if a value is an ArrayBuffer.\n","isArrayBufferView":"\nisArrayBufferView( value:any )\n    Tests if a value is a `ArrayBuffer` view.\n","isArrayLength":"\nisArrayLength( value:any )\n    Tests if a value is a valid array length.\n","isArrayLike":"\nisArrayLike( value:any )\n    Tests if a value is array-like.\n","isArrayLikeObject":"\nisArrayLikeObject( value:any )\n    Tests if a value is an array-like object.\n","isArrowFunction":"\nisArrowFunction( value:any )\n    Tests if a value is an arrow function.\n","isASCII":"\nisASCII( str:string )\n    Tests whether a character belongs to the ASCII character set and whether\n    this is true for all characters in a provided string.\n","isBetween":"\nisBetween( value:any, a:any, b:any[, left:string, right:string] )\n    Tests if a value is between two values.\n","isBetweenArray":"\nisBetweenArray( value:any, a:any, b:any[, left:string, right:string] )\n    Tests if a value is an array-like object where every element is between two\n    values.\n","isBigInt":"\nisBigInt( value:any )\n    Tests if a value is a BigInt.\n","isBigInt64Array":"\nisBigInt64Array( value:any )\n    Tests if a value is a BigInt64Array.\n","isBigUint64Array":"\nisBigUint64Array( value:any )\n    Tests if a value is a BigUint64Array.\n","isBinaryString":"\nisBinaryString( value:any )\n    Tests if a value is a binary string.\n","isBlankString":"\nisBlankString( value:any )\n    Tests if a value is a blank string (i.e., an empty string or a string\n    consisting only of whitespace characters).\n","isBoolean":"\nisBoolean( value:any )\n    Tests if a value is a boolean.\n","isBoolean.isPrimitive":"\nisBoolean.isPrimitive( value:any )\n    Tests if a value is a boolean primitive.\n","isBoolean.isObject":"\nisBoolean.isObject( value:any )\n    Tests if a value is a boolean object.\n","isBooleanArray":"\nisBooleanArray( value:any )\n    Tests if a value is an array-like object of booleans.\n","isBooleanArray.primitives":"\nisBooleanArray.primitives( value:any )\n    Tests if a value is an array-like object containing only boolean primitives.\n","isBooleanArray.objects":"\nisBooleanArray.objects( value:any )\n    Tests if a value is an array-like object containing only Boolean objects.\n","isBoxedPrimitive":"\nisBoxedPrimitive( value:any )\n    Tests if a value is a JavaScript boxed primitive.\n","isBuffer":"\nisBuffer( value:any )\n    Tests if a value is a Buffer instance.\n","isCamelcase":"\nisCamelcase( value:any )\n    Tests if a value is a camelcase string.\n","isCapitalized":"\nisCapitalized( value:any )\n    Tests if a value is a string having an uppercase first character.\n","isCentrosymmetricMatrix":"\nisCentrosymmetricMatrix( value:any )\n    Tests if a value is a matrix which is symmetric about its center.\n","isCircular":"\nisCircular( value:any )\n    Tests if an object-like value contains a circular reference.\n","isCircularArray":"\nisCircularArray( value:any )\n    Tests if a value is an array containing a circular reference.\n","isCircularPlainObject":"\nisCircularPlainObject( value:any )\n    Tests if a value is a plain object containing a circular reference.\n","isClass":"\nisClass( value:any )\n    Tests if a value is a class.\n","isCollection":"\nisCollection( value:any )\n    Tests if a value is a collection.\n","isComplex":"\nisComplex( value:any )\n    Tests if a value is a 64-bit or 128-bit complex number.\n","isComplex64":"\nisComplex64( value:any )\n    Tests if a value is a 64-bit complex number.\n","isComplex64Array":"\nisComplex64Array( value:any )\n    Tests if a value is a Complex64Array.\n","isComplex64MatrixLike":"\nisComplex64MatrixLike( value:any )\n    Tests if a value is a 2-dimensional ndarray-like object containing single-\n    precision complex floating-point numbers.\n","isComplex64ndarrayLike":"\nisComplex64ndarrayLike( value:any )\n    Tests if a value is an ndarray-like object containing single-precision\n    complex floating-point numbers.\n","isComplex64VectorLike":"\nisComplex64VectorLike( value:any )\n    Tests if a value is a 1-dimensional ndarray-like object containing single-\n    precision complex floating-point numbers.\n","isComplex128":"\nisComplex128( value:any )\n    Tests if a value is a 128-bit complex number.\n","isComplex128Array":"\nisComplex128Array( value:any )\n    Tests if a value is a Complex128Array.\n","isComplex128MatrixLike":"\nisComplex128MatrixLike( value:any )\n    Tests if a value is a 2-dimensional ndarray-like object containing double-\n    precision complex floating-point numbers.\n","isComplex128ndarrayLike":"\nisComplex128ndarrayLike( value:any )\n    Tests if a value is an ndarray-like object containing double-precision\n    complex floating-point numbers.\n","isComplex128VectorLike":"\nisComplex128VectorLike( value:any )\n    Tests if a value is a 1-dimensional ndarray-like object containing double-\n    precision complex floating-point numbers.\n","isComplexLike":"\nisComplexLike( value:any )\n    Tests if a value is a complex number-like object.\n","isComplexTypedArray":"\nisComplexTypedArray( value:any )\n    Tests if a value is a complex typed array.\n","isComplexTypedArrayLike":"\nisComplexTypedArrayLike( value:any )\n    Tests if a value is complex-typed-array-like.\n","isComposite":"\nisComposite( value:any )\n    Tests if a value is a composite number.\n","isComposite.isPrimitive":"\nisComposite.isPrimitive( value:any )\n    Tests if a value is a number primitive which is a composite number.\n","isComposite.isObject":"\nisComposite.isObject( value:any )\n    Tests if a value is a number object having a value which is a composite\n    number.\n","isConfigurableProperty":"\nisConfigurableProperty( value:any, property:any )\n    Tests if an object's own property is configurable.\n","isConfigurablePropertyIn":"\nisConfigurablePropertyIn( value:any, property:any )\n    Tests if an object's own or inherited property is configurable.\n","isConstantcase":"\nisConstantcase( value:any )\n    Tests if a value is a constantcase string.\n","isCubeNumber":"\nisCubeNumber( value:any )\n    Tests if a value is a cube number.\n","isCubeNumber.isPrimitive":"\nisCubeNumber.isPrimitive( value:any )\n    Tests if a value is a number primitive which is a cube number.\n","isCubeNumber.isObject":"\nisCubeNumber.isObject( value:any )\n    Tests if a value is a number object having a value which is a cube number.\n","isCurrentYear":"\nisCurrentYear( value:any )\n    Tests if a value is the current year.\n","isDataProperty":"\nisDataProperty( value:any, property:any )\n    Tests if an object's own property has a data descriptor.\n","isDataPropertyIn":"\nisDataPropertyIn( value:any, property:any )\n    Tests if an object's own or inherited property has a data descriptor.\n","isDataView":"\nisDataView( value:any )\n    Tests if a value is a DataView.\n","isDateObject":"\nisDateObject( value:any )\n    Tests if a value is a Date object.\n","isDateObjectArray":"\nisDateObjectArray( value:any )\n    Tests if a value is an array-like object containing only Date objects.\n","isDigitString":"\nisDigitString( str:string )\n    Tests whether a string contains only numeric digits.\n","isDomainName":"\nisDomainName( value:any )\n    Tests if a value is a domain name.\n","isDurationString":"\nisDurationString( value:any )\n    Tests if a value is a duration string.\n","isEmailAddress":"\nisEmailAddress( value:any )\n    Tests if a value is an email address.\n","isEmptyArray":"\nisEmptyArray( value:any )\n    Tests if a value is an empty array.\n","isEmptyArrayLikeObject":"\nisEmptyArrayLikeObject( value:any )\n    Tests if a value is an empty array-like object.\n","isEmptyCollection":"\nisEmptyCollection( value:any )\n    Tests if a value is an empty collection.\n","isEmptyObject":"\nisEmptyObject( value:any )\n    Tests if a value is an empty object.\n","isEmptyString":"\nisEmptyString( value:any )\n    Tests if a value is an empty string.\n","isEmptyString.isPrimitive":"\nisEmptyString.isPrimitive( value:any )\n    Tests if a value is an empty string primitive.\n","isEmptyString.isObject":"\nisEmptyString.isObject( value:any )\n    Tests if a value is an empty `String` object.\n","isEnumerableProperty":"\nisEnumerableProperty( value:any, property:any )\n    Tests if an object's own property is enumerable.\n","isEnumerablePropertyIn":"\nisEnumerablePropertyIn( value:any, property:any )\n    Tests if an object's own or inherited property is enumerable.\n","isEqualArray":"\nisEqualArray( v1:any, v2:any )\n    Tests if two arguments are both generic arrays and have equal values.\n","isError":"\nisError( value:any )\n    Tests if a value is an Error object.\n","isEvalError":"\nisEvalError( value:any )\n    Tests if a value is an EvalError object.\n","isEven":"\nisEven( value:any )\n    Tests if a value is an even number.\n","isEven.isPrimitive":"\nisEven.isPrimitive( value:any )\n    Tests if a value is a number primitive that is an even number.\n","isEven.isObject":"\nisEven.isObject( value:any )\n    Tests if a value is a number object that is an even number.\n","isFalsy":"\nisFalsy( value:any )\n    Tests if a value is a value which translates to `false` when evaluated in a\n    boolean context.\n","isFalsyArray":"\nisFalsyArray( value:any )\n    Tests if a value is an array-like object containing only falsy values.\n","isFinite":"\nisFinite( value:any )\n    Tests if a value is a finite number.\n","isFinite.isPrimitive":"\nisFinite.isPrimitive( value:any )\n    Tests if a value is a number primitive having a finite value.\n","isFinite.isObject":"\nisFinite.isObject( value:any )\n    Tests if a value is a number object having a finite value.\n","isFiniteArray":"\nisFiniteArray( value:any )\n    Tests if a value is an array-like object of finite numbers.\n","isFiniteArray.primitives":"\nisFiniteArray.primitives( value:any )\n    Tests if a value is an array-like object containing only primitive finite\n    numbers.\n","isFiniteArray.objects":"\nisFiniteArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having finite values.\n","isFloat32Array":"\nisFloat32Array( value:any )\n    Tests if a value is a Float32Array.\n","isFloat32MatrixLike":"\nisFloat32MatrixLike( value:any )\n    Tests if a value is a 2-dimensional ndarray-like object containing single-\n    precision floating-point numbers.\n","isFloat32ndarrayLike":"\nisFloat32ndarrayLike( value:any )\n    Tests if a value is an ndarray-like object containing single-precision\n    floating-point numbers.\n","isFloat32VectorLike":"\nisFloat32VectorLike( value:any )\n    Tests if a value is a 1-dimensional ndarray-like object containing single-\n    precision floating-point numbers.\n","isFloat64Array":"\nisFloat64Array( value:any )\n    Tests if a value is a Float64Array.\n","isFloat64MatrixLike":"\nisFloat64MatrixLike( value:any )\n    Tests if a value is a 2-dimensional ndarray-like object containing double-\n    precision floating-point numbers.\n","isFloat64ndarrayLike":"\nisFloat64ndarrayLike( value:any )\n    Tests if a value is an ndarray-like object containing double-precision\n    floating-point numbers.\n","isFloat64VectorLike":"\nisFloat64VectorLike( value:any )\n    Tests if a value is a 1-dimensional ndarray-like object containing double-\n    precision floating-point numbers.\n","isFunction":"\nisFunction( value:any )\n    Tests if a value is a function.\n","isFunctionArray":"\nisFunctionArray( value:any )\n    Tests if a value is an array-like object containing only functions.\n","isGeneratorObject":"\nisGeneratorObject( value:any )\n    Tests if a value is a generator object.\n","isGeneratorObjectLike":"\nisGeneratorObjectLike( value:any )\n    Tests if a value is generator object-like.\n","isgzipBuffer":"\nisgzipBuffer( value:any )\n    Tests if a value is a gzip buffer.\n","isHexString":"\nisHexString( str:string )\n    Tests whether a string contains only hexadecimal digits.\n","isInfinite":"\nisInfinite( value:any )\n    Tests if a value is an infinite number.\n","isInfinite.isPrimitive":"\nisInfinite.isPrimitive( value:any )\n    Tests if a value is a number primitive having an infinite value.\n","isInfinite.isObject":"\nisInfinite.isObject( value:any )\n    Tests if a value is a number object having an infinite value.\n","isInheritedProperty":"\nisInheritedProperty( value:any, property:any )\n    Tests if an object has an inherited property.\n","isInt8Array":"\nisInt8Array( value:any )\n    Tests if a value is an Int8Array.\n","isInt16Array":"\nisInt16Array( value:any )\n    Tests if a value is an Int16Array.\n","isInt32Array":"\nisInt32Array( value:any )\n    Tests if a value is an Int32Array.\n","isInteger":"\nisInteger( value:any )\n    Tests if a value is an integer.\n","isInteger.isPrimitive":"\nisInteger.isPrimitive( value:any )\n    Tests if a value is a number primitive having an integer value.\n","isInteger.isObject":"\nisInteger.isObject( value:any )\n    Tests if a value is a number object having an integer value.\n","isIntegerArray":"\nisIntegerArray( value:any )\n    Tests if a value is an array-like object of integer values.\n","isIntegerArray.primitives":"\nisIntegerArray.primitives( value:any )\n    Tests if a value is an array-like object containing only primitive integer\n    values.\n","isIntegerArray.objects":"\nisIntegerArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having integer values.\n","isIterableLike":"\nisIterableLike( value:any )\n    Tests if a value is iterable-like.\n","isIteratorLike":"\nisIteratorLike( value:any )\n    Tests if a value is iterator-like.\n","isJSON":"\nisJSON( value:any )\n    Tests if a value is a parseable JSON string.\n","isKebabcase":"\nisKebabcase( value:any )\n    Tests if a value is a string in kebab case.\n","isLeapYear":"\nisLeapYear( value:any )\n    Tests whether a value corresponds to a leap year in the Gregorian calendar.\n","isLocalhost":"\nisLocalhost( value:any )\n    Tests whether a value is a localhost hostname.\n","isLowercase":"\nisLowercase( value:any )\n    Tests if a value is a lowercase string.\n","isMatrixLike":"\nisMatrixLike( value:any )\n    Tests if a value is a 2-dimensional ndarray-like object.\n","isMethod":"\nisMethod( value:any, property:any )\n    Tests if an object has a specified method name.\n","isMethodIn":"\nisMethodIn( value:any, property:any )\n    Tests if an object has a specified method name, either own or inherited.\n","isMultiSlice":"\nisMultiSlice( value:any )\n    Tests if a value is a MultiSlice object.\n","isNamedTypedTupleLike":"\nisNamedTypedTupleLike( value:any )\n    Tests if a value is named typed tuple-like.\n","isnan":"\nisnan( value:any )\n    Tests if a value is NaN.\n","isnan.isPrimitive":"\nisnan.isPrimitive( value:any )\n    Tests if a value is a NaN number primitive.\n","isnan.isObject":"\nisnan.isObject( value:any )\n    Tests if a value is a number object having a value of NaN.\n","isNaNArray":"\nisNaNArray( value:any )\n    Tests if a value is an array-like object containing only NaN values.\n","isNaNArray.primitives":"\nisNaNArray.primitives( value:any )\n    Tests if a value is an array-like object containing only primitive NaN\n    values.\n","isNaNArray.objects":"\nisNaNArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having NaN values.\n","isNativeFunction":"\nisNativeFunction( value:any )\n    Tests if a value is a native function.\n","isndarrayLike":"\nisndarrayLike( value:any )\n    Tests if a value is ndarray-like.\n","isndarrayLikeWithDataType":"\nisndarrayLikeWithDataType( value:any, dtype:any )\n    Tests if a value is an ndarray-like object having a specified data type.\n","isNegativeFinite":"\nisNegativeFinite( value:any )\n    Tests if a value is a finite negative number.\n","isNegativeFinite.isPrimitive":"\nisNegativeFinite.isPrimitive( value:any )\n    Tests if a value is a number primitive having a finite negative value.\n","isNegativeFinite.isObject":"\nisNegativeFinite.isObject( value:any )\n    Tests if a value is a number object having a finite negative value.\n","isNegativeInteger":"\nisNegativeInteger( value:any )\n    Tests if a value is a negative integer.\n","isNegativeInteger.isPrimitive":"\nisNegativeInteger.isPrimitive( value:any )\n    Tests if a value is a number primitive having a negative integer value.\n","isNegativeInteger.isObject":"\nisNegativeInteger.isObject( value:any )\n    Tests if a value is a number object having a negative integer value.\n","isNegativeIntegerArray":"\nisNegativeIntegerArray( value:any )\n    Tests if a value is an array-like object containing only negative integers.\n","isNegativeIntegerArray.primitives":"\nisNegativeIntegerArray.primitives( value:any )\n    Tests if a value is an array-like object containing only negative primitive\n    integer values.\n","isNegativeIntegerArray.objects":"\nisNegativeIntegerArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having negative integer values.\n","isNegativeNumber":"\nisNegativeNumber( value:any )\n    Tests if a value is a negative number.\n","isNegativeNumber.isPrimitive":"\nisNegativeNumber.isPrimitive( value:any )\n    Tests if a value is a number primitive having a negative value.\n","isNegativeNumber.isObject":"\nisNegativeNumber.isObject( value:any )\n    Tests if a value is a number object having a negative value.\n","isNegativeNumberArray":"\nisNegativeNumberArray( value:any )\n    Tests if a value is an array-like object containing only negative numbers.\n","isNegativeNumberArray.primitives":"\nisNegativeNumberArray.primitives( value:any )\n    Tests if a value is an array-like object containing only primitive negative\n    numbers.\n","isNegativeNumberArray.objects":"\nisNegativeNumberArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having negative number values.\n","isNegativeZero":"\nisNegativeZero( value:any )\n    Tests if a value is negative zero.\n","isNegativeZero.isPrimitive":"\nisNegativeZero.isPrimitive( value:any )\n    Tests if a value is a number primitive equal to negative zero.\n","isNegativeZero.isObject":"\nisNegativeZero.isObject( value:any )\n    Tests if a value is a number object having a value equal to negative zero.\n","isNodeBuiltin":"\nisNodeBuiltin( str:string )\n    Tests whether a string matches a Node.js built-in module name.\n","isNodeDuplexStreamLike":"\nisNodeDuplexStreamLike( value:any )\n    Tests if a value is Node duplex stream-like.\n","isNodeReadableStreamLike":"\nisNodeReadableStreamLike( value:any )\n    Tests if a value is Node readable stream-like.\n","isNodeREPL":"\nisNodeREPL()\n    Returns a boolean indicating if running in a Node.js REPL environment.\n","isNodeStreamLike":"\nisNodeStreamLike( value:any )\n    Tests if a value is Node stream-like.\n","isNodeTransformStreamLike":"\nisNodeTransformStreamLike( value:any )\n    Tests if a value is Node transform stream-like.\n","isNodeWritableStreamLike":"\nisNodeWritableStreamLike( value:any )\n    Tests if a value is Node writable stream-like.\n","isNonConfigurableProperty":"\nisNonConfigurableProperty( value:any, property:any )\n    Tests if an object's own property is non-configurable.\n","isNonConfigurablePropertyIn":"\nisNonConfigurablePropertyIn( value:any, property:any )\n    Tests if an object's own or inherited property is non-configurable.\n","isNonEnumerableProperty":"\nisNonEnumerableProperty( value:any, property:any )\n    Tests if an object's own property is non-enumerable.\n","isNonEnumerablePropertyIn":"\nisNonEnumerablePropertyIn( value:any, property:any )\n    Tests if an object's own or inherited property is non-enumerable.\n","isNonNegativeFinite":"\nisNonNegativeFinite( value:any )\n    Tests if a value is a nonnegative finite number.\n","isNonNegativeFinite.isPrimitive":"\nisNonNegativeFinite.isPrimitive( value:any )\n    Tests if a value is a number primitive having a nonnegative finite value.\n","isNonNegativeFinite.isObject":"\nisNonNegativeFinite.isObject( value:any )\n    Tests if a value is a number object having a nonnegative finite value.\n","isNonNegativeInteger":"\nisNonNegativeInteger( value:any )\n    Tests if a value is a nonnegative integer.\n","isNonNegativeInteger.isPrimitive":"\nisNonNegativeInteger.isPrimitive( value:any )\n    Tests if a value is a number primitive having a nonnegative integer value.\n","isNonNegativeInteger.isObject":"\nisNonNegativeInteger.isObject( value:any )\n    Tests if a value is a number object having a nonnegative integer value.\n","isNonNegativeIntegerArray":"\nisNonNegativeIntegerArray( value:any )\n    Tests if a value is an array-like object containing only nonnegative\n    integers.\n","isNonNegativeIntegerArray.primitives":"\nisNonNegativeIntegerArray.primitives( value:any )\n    Tests if a value is an array-like object containing only nonnegative\n    primitive integer values.\n","isNonNegativeIntegerArray.objects":"\nisNonNegativeIntegerArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having nonnegative integer values.\n","isNonNegativeNumber":"\nisNonNegativeNumber( value:any )\n    Tests if a value is a nonnegative number.\n","isNonNegativeNumber.isPrimitive":"\nisNonNegativeNumber.isPrimitive( value:any )\n    Tests if a value is a number primitive having a nonnegative value.\n","isNonNegativeNumber.isObject":"\nisNonNegativeNumber.isObject( value:any )\n    Tests if a value is a number object having a nonnegative value.\n","isNonNegativeNumberArray":"\nisNonNegativeNumberArray( value:any )\n    Tests if a value is an array-like object containing only nonnegative\n    numbers.\n","isNonNegativeNumberArray.primitives":"\nisNonNegativeNumberArray.primitives( value:any )\n    Tests if a value is an array-like object containing only primitive\n    nonnegative numbers.\n","isNonNegativeNumberArray.objects":"\nisNonNegativeNumberArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having nonnegative number values.\n","isNonPositiveFinite":"\nisNonPositiveFinite( value:any )\n    Tests if a value is a nonpositive finite number.\n","isNonPositiveFinite.isPrimitive":"\nisNonPositiveFinite.isPrimitive( value:any )\n    Tests if a value is a number primitive having a nonpositive finite value.\n","isNonPositiveFinite.isObject":"\nisNonPositiveFinite.isObject( value:any )\n    Tests if a value is a number object having a nonpositive finite value.\n","isNonPositiveInteger":"\nisNonPositiveInteger( value:any )\n    Tests if a value is a nonpositive integer.\n","isNonPositiveInteger.isPrimitive":"\nisNonPositiveInteger.isPrimitive( value:any )\n    Tests if a value is a number primitive having a nonpositive integer value.\n","isNonPositiveInteger.isObject":"\nisNonPositiveInteger.isObject( value:any )\n    Tests if a value is a number object having a nonpositive integer value.\n","isNonPositiveIntegerArray":"\nisNonPositiveIntegerArray( value:any )\n    Tests if a value is an array-like object containing only nonpositive\n    integers.\n","isNonPositiveIntegerArray.primitives":"\nisNonPositiveIntegerArray.primitives( value:any )\n    Tests if a value is an array-like object containing only nonpositive\n    primitive integer values.\n","isNonPositiveIntegerArray.objects":"\nisNonPositiveIntegerArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having nonpositive integer values.\n","isNonPositiveNumber":"\nisNonPositiveNumber( value:any )\n    Tests if a value is a nonpositive number.\n","isNonPositiveNumber.isPrimitive":"\nisNonPositiveNumber.isPrimitive( value:any )\n    Tests if a value is a number primitive having a nonpositive value.\n","isNonPositiveNumber.isObject":"\nisNonPositiveNumber.isObject( value:any )\n    Tests if a value is a number object having a nonpositive value.\n","isNonPositiveNumberArray":"\nisNonPositiveNumberArray( value:any )\n    Tests if a value is an array-like object containing only nonpositive\n    numbers.\n","isNonPositiveNumberArray.primitives":"\nisNonPositiveNumberArray.primitives( value:any )\n    Tests if a value is an array-like object containing only primitive\n    nonpositive numbers.\n","isNonPositiveNumberArray.objects":"\nisNonPositiveNumberArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having nonpositive number values.\n","isNonSymmetricMatrix":"\nisNonSymmetricMatrix( value:any )\n    Tests if a value is a non-symmetric matrix.\n","isNull":"\nisNull( value:any )\n    Tests if a value is null.\n","isNullArray":"\nisNullArray( value:any )\n    Tests if a value is an array-like object containing only null values.\n","isNumber":"\nisNumber( value:any )\n    Tests if a value is a number.\n","isNumber.isPrimitive":"\nisNumber.isPrimitive( value:any )\n    Tests if a value is a number primitive.\n","isNumber.isObject":"\nisNumber.isObject( value:any )\n    Tests if a value is a `Number` object.\n","isNumberArray":"\nisNumberArray( value:any )\n    Tests if a value is an array-like object containing only numbers.\n","isNumberArray.primitives":"\nisNumberArray.primitives( value:any )\n    Tests if a value is an array-like object containing only number primitives.\n","isNumberArray.objects":"\nisNumberArray.objects( value:any )\n    Tests if a value is an array-like object containing only `Number` objects.\n","isNumericArray":"\nisNumericArray( value:any )\n    Tests if a value is a numeric array.\n","isObject":"\nisObject( value:any )\n    Tests if a value is an object; e.g., `{}`.\n","isObjectArray":"\nisObjectArray( value:any )\n    Tests if a value is an array-like object containing only objects.\n","isObjectLike":"\nisObjectLike( value:any )\n    Tests if a value is object-like.\n","isOdd":"\nisOdd( value:any )\n    Tests if a value is an odd number.\n","isOdd.isPrimitive":"\nisOdd.isPrimitive( value:any )\n    Tests if a value is a number primitive that is an odd number.\n","isOdd.isObject":"\nisOdd.isObject( value:any )\n    Tests if a value is a number object that has an odd number value.\n","isoWeeksInYear":"\nisoWeeksInYear( [year:integer] )\n    Returns the number of ISO weeks in a year according to the Gregorian\n    calendar.\n","isPascalcase":"\nisPascalcase( value:any )\n    Tests if a value is a string in Pascal case.\n","isPersymmetricMatrix":"\nisPersymmetricMatrix( value:any )\n    Tests if a value is a square matrix which is symmetric about its\n    antidiagonal.\n","isPlainObject":"\nisPlainObject( value:any )\n    Tests if a value is a plain object.\n","isPlainObjectArray":"\nisPlainObjectArray( value:any )\n    Tests if a value is an array-like object containing only plain objects.\n","isPositiveFinite":"\nisPositiveFinite( value:any )\n    Tests if a value is a positive finite number.\n","isPositiveFinite.isPrimitive":"\nisPositiveFinite.isPrimitive( value:any )\n    Tests if a value is a number primitive having a positive finite value.\n","isPositiveFinite.isObject":"\nisPositiveFinite.isObject( value:any )\n    Tests if a value is a number object having a positive finite value.\n","isPositiveInteger":"\nisPositiveInteger( value:any )\n    Tests if a value is a positive integer.\n","isPositiveInteger.isPrimitive":"\nisPositiveInteger.isPrimitive( value:any )\n    Tests if a value is a number primitive having a positive integer value.\n","isPositiveInteger.isObject":"\nisPositiveInteger.isObject( value:any )\n    Tests if a value is a number object having a positive integer value.\n","isPositiveIntegerArray":"\nisPositiveIntegerArray( value:any )\n    Tests if a value is an array-like object containing only positive integers.\n","isPositiveIntegerArray.primitives":"\nisPositiveIntegerArray.primitives( value:any )\n    Tests if a value is an array-like object containing only positive primitive\n    integer values.\n","isPositiveIntegerArray.objects":"\nisPositiveIntegerArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having positive integer values.\n","isPositiveNumber":"\nisPositiveNumber( value:any )\n    Tests if a value is a positive number.\n","isPositiveNumber.isPrimitive":"\nisPositiveNumber.isPrimitive( value:any )\n    Tests if a value is a number primitive having a positive value.\n","isPositiveNumber.isObject":"\nisPositiveNumber.isObject( value:any )\n    Tests if a value is a number object having a positive value.\n","isPositiveNumberArray":"\nisPositiveNumberArray( value:any )\n    Tests if a value is an array-like object containing only positive numbers.\n","isPositiveNumberArray.primitives":"\nisPositiveNumberArray.primitives( value:any )\n    Tests if a value is an array-like object containing only positive primitive\n    number values.\n","isPositiveNumberArray.objects":"\nisPositiveNumberArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having positive values.\n","isPositiveZero":"\nisPositiveZero( value:any )\n    Tests if a value is positive zero.\n","isPositiveZero.isPrimitive":"\nisPositiveZero.isPrimitive( value:any )\n    Tests if a value is a number primitive equal to positive zero.\n","isPositiveZero.isObject":"\nisPositiveZero.isObject( value:any )\n    Tests if a value is a number object having a value equal to positive zero.\n","isPrime":"\nisPrime( value:any )\n    Tests if a value is a prime number.\n","isPrime.isPrimitive":"\nisPrime.isPrimitive( value:any )\n    Tests if a value is a number primitive which is a prime number.\n","isPrime.isObject":"\nisPrime.isObject( value:any )\n    Tests if a value is a number object having a value which is a prime number.\n","isPrimitive":"\nisPrimitive( value:any )\n    Tests if a value is a JavaScript primitive.\n","isPrimitiveArray":"\nisPrimitiveArray( value:any )\n    Tests if a value is an array-like object containing only JavaScript\n    primitives.\n","isPRNGLike":"\nisPRNGLike( value:any )\n    Tests if a value is PRNG-like.\n","isProbability":"\nisProbability( value:any )\n    Tests if a value is a probability.\n","isProbability.isPrimitive":"\nisProbability.isPrimitive( value:any )\n    Tests if a value is a number primitive which is a probability.\n","isProbability.isObject":"\nisProbability.isObject( value:any )\n    Tests if a value is a number object having a value which is a probability.\n","isProbabilityArray":"\nisProbabilityArray( value:any )\n    Tests if a value is an array-like object containing only probabilities.\n","isProbabilityArray.primitives":"\nisProbabilityArray.primitives( value:any )\n    Tests if a value is an array-like object containing only primitive\n    probabilities.\n","isProbabilityArray.objects":"\nisProbabilityArray.objects( value:any )\n    Tests if a value is an array-like object containing only number objects\n    having probability values.\n","isPropertyKey":"\nisPropertyKey( value:any )\n    Tests whether a value is a property key.\n","isPrototypeOf":"\nisPrototypeOf( value:any, proto:Object|Function )\n    Tests if an object's prototype chain contains a provided prototype.\n","isRaggedNestedArray":"\nisRaggedNestedArray( value:any )\n    Tests if a value is a ragged nested array. \n","isRangeError":"\nisRangeError( value:any )\n    Tests if a value is a RangeError object.\n","isReadableProperty":"\nisReadableProperty( value:any, property:any )\n    Tests if an object's own property is readable.\n","isReadablePropertyIn":"\nisReadablePropertyIn( value:any, property:any )\n    Tests if an object's own or inherited property is readable.\n","isReadOnlyProperty":"\nisReadOnlyProperty( value:any, property:any )\n    Tests if an object's own property is read-only.\n","isReadOnlyPropertyIn":"\nisReadOnlyPropertyIn( value:any, property:any )\n    Tests if an object's own or inherited property is read-only.\n","isReadWriteProperty":"\nisReadWriteProperty( value:any, property:any )\n    Tests if an object's own property is readable and writable.\n","isReadWritePropertyIn":"\nisReadWritePropertyIn( value:any, property:any )\n    Tests if an object's own or inherited property is readable and writable.\n","isReferenceError":"\nisReferenceError( value:any )\n    Tests if a value is a ReferenceError object.\n","isRegExp":"\nisRegExp( value:any )\n    Tests if a value is a regular expression.\n","isRegExpString":"\nisRegExpString( value:any )\n    Tests if a value is a regular expression string.\n","isRelativePath":"\nisRelativePath( value:any )\n    Tests if a value is a relative path.\n","isRelativePath.posix":"\nisRelativePath.posix( value:any )\n    Tests if a value is a POSIX relative path.\n","isRelativePath.win32":"\nisRelativePath.win32( value:any )\n    Tests if a value is a Windows relative path.\n","isRelativeURI":"\nisRelativeURI( value:any )\n    Tests whether a value is a relative URI.\n","isSafeInteger":"\nisSafeInteger( value:any )\n    Tests if a value is a safe integer.\n","isSafeInteger.isPrimitive":"\nisSafeInteger.isPrimitive( value:any )\n    Tests if a value is a number primitive having a safe integer value.\n","isSafeInteger.isObject":"\nisSafeInteger.isObject( value:any )\n    Tests if a value is a `Number` object having a safe integer value.\n","isSafeIntegerArray":"\nisSafeIntegerArray( value:any )\n    Tests if a value is an array-like object containing only safe integers.\n","isSafeIntegerArray.primitives":"\nisSafeIntegerArray.primitives( value:any )\n    Tests if a value is an array-like object containing only primitive safe\n    integer values.\n","isSafeIntegerArray.objects":"\nisSafeIntegerArray.objects( value:any )\n    Tests if a value is an array-like object containing only `Number` objects\n    having safe integer values.\n","isSameArray":"\nisSameArray( v1:any, v2:any )\n    Tests if two arguments are both generic arrays and have the same values.\n","isSameArrayLike":"\nisSameArrayLike( v1:any, v2:any )\n    Tests if two arguments are both array-like and have the same values.\n","isSameComplex64":"\nisSameComplex64( v1:any, v2:any )\n    Tests if two arguments are both single-precision complex floating-point\n    numbers and have the same value.\n","isSameComplex64Array":"\nisSameComplex64Array( v1:any, v2:any )\n    Tests if two arguments are both Complex64Arrays and have the same values.\n","isSameComplex128":"\nisSameComplex128( v1:any, v2:any )\n    Tests if two arguments are both double-precision complex floating-point\n    numbers and have the same value.\n","isSameComplex128Array":"\nisSameComplex128Array( v1:any, v2:any )\n    Tests if two arguments are both Complex128Arrays and have the same values.\n","isSameDateObject":"\nisSameDateObject( d1, d2 )\n    Tests if two values are both Date objects corresponding \n    to the same date and time.\n","isSameFloat32Array":"\nisSameFloat32Array( v1:any, v2:any )\n    Tests if two arguments are both Float32Arrays and have the same values.\n","isSameFloat64Array":"\nisSameFloat64Array( v1:any, v2:any )\n    Tests if two arguments are both Float64Arrays and have the same values.\n","isSameNativeClass":"\nisSameNativeClass( a:any, b:any )\n    Tests if two arguments have the same native class.\n","isSameType":"\nisSameType( a:any, b:any )\n    Tests if two arguments have the same type.\n","isSameValue":"\nisSameValue( a:any, b:any )\n    Tests if two arguments are the same value.\n","isSameValueZero":"\nisSameValueZero( a:any, b:any )\n    Tests if two arguments are the same value.\n","isSemVer":"\nisSemVer( value:any )\n    Tests if a value is a semantic version string.\n","isSharedArrayBuffer":"\nisSharedArrayBuffer( value:any )\n    Tests if a value is a SharedArrayBuffer.\n","isSkewCentrosymmetricMatrix":"\nisSkewCentrosymmetricMatrix( value:any )\n    Tests if a value is a skew-centrosymmetric matrix.\n","isSkewPersymmetricMatrix":"\nisSkewPersymmetricMatrix( value:any )\n    Tests if a value is a skew-persymmetric matrix.\n","isSkewSymmetricMatrix":"\nisSkewSymmetricMatrix( value:any )\n    Tests if a value is a skew-symmetric (or antisymmetric) matrix.\n","isSlice":"\nisSlice( value:any )\n    Tests if a value is a Slice object.\n","isSnakecase":"\nisSnakecase( value:any )\n    Tests if a value is a string in snake case.\n","isSquareMatrix":"\nisSquareMatrix( value:any )\n    Tests if a value is a 2-dimensional ndarray-like object having equal\n    dimensions.\n","isSquareNumber":"\nisSquareNumber( value:any )\n    Tests if a value is a square number.\n","isSquareNumber.isPrimitive":"\nisSquareNumber.isPrimitive( value:any )\n    Tests if a value is a number primitive which is a square number.\n","isSquareNumber.isObject":"\nisSquareNumber.isObject( value:any )\n    Tests if a value is a number object having a value which is a square number.\n","isSquareTriangularNumber":"\nisSquareTriangularNumber( value:any )\n    Tests if a value is a square triangular number.\n","isSquareTriangularNumber.isPrimitive":"\nisSquareTriangularNumber.isPrimitive( value:any )\n    Tests if a value is a number primitive which is a square triangular number.\n","isSquareTriangularNumber.isObject":"\nisSquareTriangularNumber.isObject( value:any )\n    Tests if a value is a number object having a value which is a square\n    triangular number.\n","isStartcase":"\nisStartcase( value:any )\n    Tests if a value is a startcase string.\n","isStrictEqual":"\nisStrictEqual( a:any, b:any )\n    Tests if two arguments are strictly equal.\n","isString":"\nisString( value:any )\n    Tests if a value is a string.\n","isString.isPrimitive":"\nisString.isPrimitive( value:any )\n    Tests if a value is a string primitive.\n","isString.isObject":"\nisString.isObject( value:any )\n    Tests if a value is a `String` object.\n","isStringArray":"\nisStringArray( value:any )\n    Tests if a value is an array of strings.\n","isStringArray.primitives":"\nisStringArray.primitives( value:any )\n    Tests if a value is an array containing only string primitives.\n","isStringArray.objects":"\nisStringArray.objects( value:any )\n    Tests if a value is an array containing only `String` objects.\n","isSymbol":"\nisSymbol( value:any )\n    Tests if a value is a symbol.\n","isSymbolArray":"\nisSymbolArray( value:any )\n    Tests if a value is an array-like object containing only symbols.\n","isSymbolArray.primitives":"\nisSymbolArray.primitives( value:any )\n    Tests if a value is an array-like object containing only `symbol`\n    primitives.\n","isSymbolArray.objects":"\nisSymbolArray.objects( value:any )\n    Tests if a value is an array-like object containing only `Symbol`\n    objects.\n","isSymmetricMatrix":"\nisSymmetricMatrix( value:any )\n    Tests if a value is a square matrix which equals its transpose.\n","isSyntaxError":"\nisSyntaxError( value:any )\n    Tests if a value is a SyntaxError object.\n","isTriangularNumber":"\nisTriangularNumber( value:any )\n    Tests if a value is a triangular number.\n","isTriangularNumber.isPrimitive":"\nisTriangularNumber.isPrimitive( value:any )\n    Tests if a value is a number primitive which is a triangular number.\n","isTriangularNumber.isObject":"\nisTriangularNumber.isObject( value:any )\n    Tests if a value is a number object having a value which is a triangular\n    number.\n","isTruthy":"\nisTruthy( value:any )\n    Tests if a value is a value which translates to `true` when evaluated in a\n    boolean context.\n","isTruthyArray":"\nisTruthyArray( value:any )\n    Tests if a value is an array-like object containing only truthy values.\n","isTypedArray":"\nisTypedArray( value:any )\n    Tests if a value is a typed array.\n","isTypedArrayLength":"\nisTypedArrayLength( value:any )\n    Tests if a value is a valid typed array length.\n","isTypedArrayLike":"\nisTypedArrayLike( value:any )\n    Tests if a value is typed-array-like.\n","isTypeError":"\nisTypeError( value:any )\n    Tests if a value is a TypeError object.\n","isUint8Array":"\nisUint8Array( value:any )\n    Tests if a value is a Uint8Array.\n","isUint8ClampedArray":"\nisUint8ClampedArray( value:any )\n    Tests if a value is a Uint8ClampedArray.\n","isUint16Array":"\nisUint16Array( value:any )\n    Tests if a value is a Uint16Array.\n","isUint32Array":"\nisUint32Array( value:any )\n    Tests if a value is a Uint32Array.\n","isUNCPath":"\nisUNCPath( value:any )\n    Tests if a value is a UNC path.\n","isUndefined":"\nisUndefined( value:any )\n    Tests if a value is undefined.\n","isUndefinedOrNull":"\nisUndefinedOrNull( value:any )\n    Tests if a value is undefined or null.\n","isUnityProbabilityArray":"\nisUnityProbabilityArray( value:any )\n    Tests if a value is an array of probabilities that sum to one.\n","isUppercase":"\nisUppercase( value:any )\n    Tests if a value is an uppercase string.\n","isURI":"\nisURI( value:any )\n    Tests if a value is a URI.\n","isURIError":"\nisURIError( value:any )\n    Tests if a value is a URIError object.\n","isVectorLike":"\nisVectorLike( value:any )\n    Tests if a value is a 1-dimensional ndarray-like object.\n","isWebAssemblyMemory":"\nisWebAssemblyMemory( value:any )\n    Tests if a value is a WebAssembly memory instance.\n","isWellFormedString":"\nisWellFormedString( str:any )\n    Tests if a string is well-formed.\n","isWellFormedString.isPrimitive":"\nisWellFormedString.isPrimitive( str:any )\n    Tests if a string is a well-formed string primitive.\n","isWellFormedString.isObject":"\nisWellFormedString.isObject( str:any )\n    Tests if a string is a well-formed string object.\n","isWhitespace":"\nisWhitespace( str:string )\n    Tests whether a string contains only white space characters.\n","isWritableProperty":"\nisWritableProperty( value:any, property:any )\n    Tests if an object's own property is writable.\n","isWritablePropertyIn":"\nisWritablePropertyIn( value:any, property:any )\n    Tests if an object's own or inherited property is writable.\n","isWriteOnlyProperty":"\nisWriteOnlyProperty( value:any, property:any )\n    Tests if an object's own property is write-only.\n","isWriteOnlyPropertyIn":"\nisWriteOnlyPropertyIn( value:any, property:any )\n    Tests if an object's own or inherited property is write-only.\n","iterAbs":"\niterAbs( iterator:Object )\n    Returns an iterator which iteratively computes the absolute value.\n","iterAbs2":"\niterAbs2( iterator:Object )\n    Returns an iterator which iteratively computes the squared absolute value.\n","iterAcos":"\niterAcos( iterator:Object )\n    Returns an iterator which iteratively computes the arccosine.\n","iterAcosh":"\niterAcosh( iterator:Object )\n    Returns an iterator which iteratively computes the hyperbolic arccosine.\n","iterAcot":"\niterAcot( iterator:Object )\n    Returns an iterator which iteratively computes the inverse cotangent.\n","iterAcoth":"\niterAcoth( iterator:Object )\n    Returns an iterator which iteratively computes the inverse hyperbolic\n    cotangent.\n","iterAcovercos":"\niterAcovercos( iterator:Object )\n    Returns an iterator which iteratively computes the inverse coversed cosine.\n","iterAcoversin":"\niterAcoversin( iterator:Object )\n    Returns an iterator which iteratively computes the inverse coversed sine.\n","iterAdd":"\niterAdd( iter0:Object, ...iterator:Object )\n    Returns an iterator which performs element-wise addition of two or more\n    iterators.\n","iterAdvance":"\niterAdvance( iterator:Object[, n:integer] )\n    Advances an entire iterator.\n","iterAhavercos":"\niterAhavercos( iterator:Object )\n    Returns an iterator which iteratively computes the inverse half-value versed\n    cosine.\n","iterAhaversin":"\niterAhaversin( iterator:Object )\n    Returns an iterator which iteratively computes the inverse half-value versed\n    sine.\n","iterAny":"\niterAny( iterator:Object )\n    Tests whether at least one iterated value is truthy.\n","iterAnyBy":"\niterAnyBy( iterator:Object, predicate:Function[, thisArg:any ] )\n    Tests whether at least one iterated value passes a test implemented by a\n    predicate function.\n","iterAsin":"\niterAsin( iterator:Object )\n    Returns an iterator which iteratively computes the arcsine.\n","iterAsinh":"\niterAsinh( iterator:Object )\n    Returns an iterator which iteratively computes the hyperbolic arcsine.\n","iterAtan":"\niterAtan( iterator:Object )\n    Returns an iterator which iteratively computes the arctangent.\n","iterAtan2":"\niterAtan2( y:Object|number, x:Object|number )\n    Returns an iterator which iteratively computes the angle in the plane (in\n    radians) between the positive x-axis and the ray from (0,0) to the point\n    (x,y).\n","iterAtanh":"\niterAtanh( iterator:Object )\n    Returns an iterator which iteratively computes the hyperbolic arctangent.\n","iterator2array":"\niterator2array( iterator:Object[, out:ArrayLikeObject][, mapFcn:Function[, \n  thisArg:any]] )\n    Creates (or fills) an array from an iterator.\n","iterator2arrayview":"\niterator2arrayview( iterator:Object, dest:ArrayLikeObject[, begin:integer[, \n  end:integer]][, mapFcn:Function[, thisArg:any]] )\n    Fills an array-like object view with values returned from an iterator.\n","iterator2arrayviewRight":"\niterator2arrayviewRight( iterator:Object, dest:ArrayLikeObject[, \n  begin:integer[, end:integer]][, mapFcn:Function[, thisArg:any]] )\n    Fills an array-like object view from right to left with values returned from\n    an iterator.\n","iteratorStream":"\niteratorStream( iterator:Object[, options:Object] )\n    Creates a readable stream from an iterator.\n","iteratorStream.factory":"\niteratorStream.factory( [options:Object] )\n    Returns a function for creating readable streams from iterators.\n","iteratorStream.objectMode":"\niteratorStream.objectMode( iterator:Object[, options:Object] )\n    Returns an \"objectMode\" readable stream from an iterator.\n","IteratorSymbol":"\nIteratorSymbol\n    Iterator symbol.\n","iterAvercos":"\niterAvercos( iterator:Object )\n    Returns an iterator which iteratively computes the inverse versed cosine.\n","iterAversin":"\niterAversin( iterator:Object )\n    Returns an iterator which iteratively computes the inverse versed sine.\n","iterawgn":"\niterawgn( iterator:Object, sigma:number[, options:Object] )\n    Returns an iterator which introduces additive white Gaussian noise (AWGN)\n    with standard deviation `sigma`.\n","iterawln":"\niterawln( iterator:Object, sigma:number[, options:Object] )\n    Returns an iterator which introduces additive white Laplacian noise (AWLN)\n    with standard deviation `sigma`.\n","iterawun":"\niterawun( iterator:Object, sigma:number[, options:Object] )\n    Returns an iterator which introduces additive white uniform noise (AWUN)\n    with standard deviation `sigma`.\n","iterBartlettHannPulse":"\niterBartlettHannPulse( [options:Object] )\n    Returns an iterator which generates a Bartlett-Hann pulse waveform.\n","iterBartlettPulse":"\niterBartlettPulse( [options:Object] )\n    Returns an iterator which generates a Bartlett pulse waveform.\n","iterBesselj0":"\niterBesselj0( iterator:Object )\n    Returns an iterator which iteratively evaluates the Bessel function of the\n    first kind of order zero.\n","iterBesselj1":"\niterBesselj1( iterator:Object )\n    Returns an iterator which iteratively evaluates the Bessel function of the\n    first kind of order one.\n","iterBessely0":"\niterBessely0( iterator:Object )\n    Returns an iterator which iteratively evaluates the Bessel function of the\n    second kind of order zero.\n","iterBessely1":"\niterBessely1( iterator:Object )\n    Returns an iterator which iteratively evaluates the Bessel function of the\n    second kind of order one.\n","iterBeta":"\niterBeta( x:Object|number, y:Object|number )\n    Returns an iterator which iteratively evaluates the beta function.\n","iterBetaln":"\niterBetaln( x:Object|number, y:Object|number )\n    Returns an iterator which iteratively evaluates the natural logarithm of the\n    beta function.\n","iterBinet":"\niterBinet( iterator:Object )\n    Returns an iterator which iteratively evaluates Binet's formula extended to\n    real numbers.\n","iterCbrt":"\niterCbrt( iterator:Object )\n    Returns an iterator which iteratively computes the cube root.\n","iterCeil":"\niterCeil( iterator:Object )\n    Returns an iterator which rounds each iterated value toward positive\n    infinity.\n","iterCeil2":"\niterCeil2( iterator:Object )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    two toward positive infinity.\n","iterCeil10":"\niterCeil10( iterator:Object )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    10 toward positive infinity.\n","iterCompositesSeq":"\niterCompositesSeq( [options:Object] )\n    Returns an iterator which generates a sequence of composite numbers.\n","iterConcat":"\niterConcat( iter0:Object, ...iterator:Object )\n    Returns an iterator which iterates over the values of two or more iterators.\n","iterConstant":"\niterConstant( value:any[, options:Object] )\n    Returns an iterator which always returns the same value.\n","iterContinuedFraction":"\niterContinuedFraction( iterator:Object[, options:Object] )\n    Evaluates the terms of a continued fraction.\n","iterContinuedFractionSeq":"\niterContinuedFractionSeq( x:number[, options:Object] )\n    Returns an iterator which generates a list of all continued fraction terms\n    which can be obtained given the precision of `x`.\n","iterCos":"\niterCos( iterator:Object )\n    Returns an iterator which iteratively computes the cosine.\n","iterCosh":"\niterCosh( iterator:Object )\n    Returns an iterator which iteratively computes the hyperbolic cosine.\n","iterCosineWave":"\niterCosineWave( [options:Object] )\n    Returns an iterator which generates a cosine wave.\n","iterCosm1":"\niterCosm1( iterator:Object )\n    Returns an iterator which iteratively computes `cos(x) - 1`.\n","iterCospi":"\niterCospi( iterator:Object )\n    Returns an iterator which computes the cosine of each iterated value times\n    π.\n","iterCounter":"\niterCounter( iterator:Object )\n    Returns an iterator which iteratively computes the number of iterated\n    values.\n","iterCovercos":"\niterCovercos( iterator:Object )\n    Returns an iterator which iteratively computes the coversed cosine.\n","iterCoversin":"\niterCoversin( iterator:Object )\n    Returns an iterator which iteratively computes the coversed sine.\n","iterCubesSeq":"\niterCubesSeq( [options:Object] )\n    Returns an iterator which generates a sequence of cubes.\n","itercugmean":"\nitercugmean( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative geometric mean.\n","itercuhmean":"\nitercuhmean( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative harmonic mean.\n","itercumax":"\nitercumax( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative maximum value.\n","itercumaxabs":"\nitercumaxabs( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative maximum absolute\n    value.\n","itercumean":"\nitercumean( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative arithmetic mean.\n","itercumeanabs":"\nitercumeanabs( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative arithmetic mean\n    of absolute values.\n","itercumeanabs2":"\nitercumeanabs2( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative arithmetic mean\n    of squared absolute values.\n","itercumidrange":"\nitercumidrange( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative mid-range.\n","itercumin":"\nitercumin( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative minimum value.\n","itercuminabs":"\nitercuminabs( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative minimum absolute\n    value.\n","itercuprod":"\nitercuprod( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative product.\n","itercurange":"\nitercurange( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative range.\n","itercusum":"\nitercusum( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative sum.\n","itercusumabs":"\nitercusumabs( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative sum of absolute\n    values.\n","itercusumabs2":"\nitercusumabs2( iterator:Object )\n    Returns an iterator which iteratively computes a cumulative sum of squared\n    absolute values.\n","iterDatespace":"\niterDatespace( start:integer|string|Date, stop:integer|string|Date[, \n  N:integer][, options:Object] )\n    Returns an iterator which returns evenly spaced dates over a specified\n    interval.\n","iterDedupe":"\niterDedupe( iterator:Object[, limit:integer] )\n    Returns an iterator which removes consecutive duplicated values.\n","iterDedupeBy":"\niterDedupeBy( iterator:Object, [limit:integer,] fcn:Function )\n    Returns an iterator which removes consecutive values that resolve to the\n    same value according to a provided function.\n","iterDeg2rad":"\niterDeg2rad( iterator:Object )\n    Returns an iterator which iteratively converts an angle from degrees to\n    radians.\n","iterDigamma":"\niterDigamma( iterator:Object )\n    Returns an iterator which iteratively evaluates the digamma function.\n","iterDiracComb":"\niterDiracComb( [options:Object] )\n    Returns an iterator which generates a Dirac comb.\n","iterDiracDelta":"\niterDiracDelta( iterator:Object )\n    Returns an iterator which iteratively evaluates the Dirac delta function.\n","iterDivide":"\niterDivide( iter0:Object, ...iterator:Object )\n    Returns an iterator which performs element-wise division of two or more\n    iterators.\n","iterDoWhileEach":"\niterDoWhileEach( iterator:Object, predicate:Function, fcn:Function[, \n  thisArg:any] )\n    Returns an iterator which invokes a function for each iterated value before\n    returning the iterated value until either a predicate function returns false\n    or the iterator has iterated over all values.\n","iterEllipe":"\niterEllipe( iterator:Object )\n    Returns an iterator which iteratively computes the complete elliptic\n    integral of the second kind.\n","iterEllipk":"\niterEllipk( iterator:Object )\n    Returns an iterator which iteratively computes the complete elliptic\n    integral of the first kind.\n","iterEmpty":"\niterEmpty()\n    Returns an empty iterator.\n","iterErf":"\niterErf( iterator:Object )\n    Returns an iterator which iteratively evaluates the error function.\n","iterErfc":"\niterErfc( iterator:Object )\n    Returns an iterator which iteratively evaluates the complementary error\n    function.\n","iterErfcinv":"\niterErfcinv( iterator:Object )\n    Returns an iterator which iteratively evaluates the inverse complementary\n    error function.\n","iterErfinv":"\niterErfinv( iterator:Object )\n    Returns an iterator which iteratively evaluates the inverse error function.\n","iterEta":"\niterEta( iterator:Object )\n    Returns an iterator which iteratively evaluates the Dirichlet eta function.\n","iterEvenIntegersSeq":"\niterEvenIntegersSeq( [options:Object] )\n    Returns an iterator which generates an interleaved sequence of even\n    integers.\n","iterEvery":"\niterEvery( iterator:Object )\n    Tests whether all iterated values are truthy.\n","iterEveryBy":"\niterEveryBy( iterator:Object, predicate:Function[, thisArg:any ] )\n    Tests whether every iterated value passes a test implemented by a predicate\n    function.\n","iterExp":"\niterExp( iterator:Object )\n    Returns an iterator which iteratively evaluates the natural exponential\n    function.\n","iterExp2":"\niterExp2( iterator:Object )\n    Returns an iterator which iteratively evaluates the base `2` exponential\n    function.\n","iterExp10":"\niterExp10( iterator:Object )\n    Returns an iterator which iteratively evaluates the base `10` exponential\n    function.\n","iterExpit":"\niterExpit( iterator:Object )\n    Returns an iterator which iteratively evaluates the standard logistic\n    function.\n","iterExpm1":"\niterExpm1( iterator:Object )\n    Returns an iterator which iteratively computes `exp(x) - 1`.\n","iterExpm1rel":"\niterExpm1rel( iterator:Object )\n    Returns an iterator which iteratively evaluates the relative error\n    exponential.\n","iterFactorial":"\niterFactorial( iterator:Object )\n    Returns an iterator which iteratively evaluates the factorial function.\n","iterFactorialln":"\niterFactorialln( iterator:Object )\n    Returns an iterator which iteratively evaluates the natural logarithm of the\n    factorial function.\n","iterFactorialsSeq":"\niterFactorialsSeq( [options:Object] )\n    Returns an iterator which generates a sequence of factorials.\n","iterFibonacciSeq":"\niterFibonacciSeq( [options:Object] )\n    Returns an iterator which generates a Fibonacci sequence.\n","iterFifthPowersSeq":"\niterFifthPowersSeq( [options:Object] )\n    Returns an iterator which generates a sequence of fifth powers.\n","iterFill":"\niterFill( iterator:Object, value:any[, begin:integer[, end:integer]] )\n    Returns an iterator which replaces all values from a provided iterator from\n    a start index to an end index with a static value.\n","iterFilter":"\niterFilter( iterator:Object, predicate:Function[, thisArg:any] )\n    Returns an iterator which filters a provided iterator's values according to\n    a predicate function.\n","iterFilterMap":"\niterFilterMap( iterator:Object, fcn:Function[, thisArg:any] )\n    Returns an iterator which both filters and maps a provided iterator's\n    values.\n","iterFirst":"\niterFirst( iterator:Object )\n    Returns the first iterated value.\n","iterFlatTopPulse":"\niterFlatTopPulse( [options:Object] )\n    Returns an iterator which generates a flat top pulse waveform.\n","iterFloor":"\niterFloor( iterator:Object )\n    Returns an iterator which rounds each iterated value toward negative\n    infinity.\n","iterFloor2":"\niterFloor2( iterator:Object )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    two toward negative infinity.\n","iterFloor10":"\niterFloor10( iterator:Object )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    10 toward negative infinity.\n","iterFlow":"\niterFlow( methods:Object )\n    Returns a fluent interface iterator constructor with a customized prototype\n    based on provided methods.\n","iterForEach":"\niterForEach( iterator:Object, fcn:Function[, thisArg:any] )\n    Returns an iterator which invokes a function for each iterated value before\n    returning the iterated value.\n","iterFourthPowersSeq":"\niterFourthPowersSeq( [options:Object] )\n    Returns an iterator which generates a sequence of fourth powers.\n","iterFresnelc":"\niterFresnelc( iterator:Object )\n    Returns an iterator which iteratively computes the Fresnel integral C(x).\n","iterFresnels":"\niterFresnels( iterator:Object )\n    Returns an iterator which iteratively computes the Fresnel integral S(x).\n","iterGamma":"\niterGamma( iterator:Object )\n    Returns an iterator which iteratively evaluates the gamma function.\n","iterGamma1pm1":"\niterGamma1pm1( iterator:Object )\n    Returns an iterator which iteratively computes `gamma(x+1) - 1` without\n    cancellation errors for small `x`.\n","iterGammaln":"\niterGammaln( iterator:Object )\n    Returns an iterator which iteratively evaluates the natural logarithm of the\n    gamma function.\n","iterHacovercos":"\niterHacovercos( iterator:Object )\n    Returns an iterator which iteratively computes the half-value coversed\n    cosine.\n","iterHacoversin":"\niterHacoversin( iterator:Object )\n    Returns an iterator which iteratively computes the half-value coversed sine.\n","iterHannPulse":"\niterHannPulse( [options:Object] )\n    Returns an iterator which generates a Hann pulse waveform.\n","iterHavercos":"\niterHavercos( iterator:Object )\n    Returns an iterator which iteratively computes the half-value versed cosine.\n","iterHaversin":"\niterHaversin( iterator:Object )\n    Returns an iterator which iteratively computes the half-value versed sine.\n","iterHead":"\niterHead( iterator:Object, n:integer )\n    Returns an iterator which returns the first `n` values of a provided\n    iterator.\n","iterIncrspace":"\niterIncrspace( start:number, stop:number[, increment:number] )\n    Returns an iterator which returns evenly spaced numbers according to a\n    specified increment.\n","iterIntegersSeq":"\niterIntegersSeq( [options:Object] )\n    Returns an iterator which generates an interleaved integer sequence.\n","iterIntersection":"\niterIntersection( iter0:Object, ...iterator:Object )\n    Returns an iterator which returns the intersection of two or more iterators.\n","iterIntersectionByHash":"\niterIntersectionByHash( iter0:Object, ...iterator:Object, hashFcn:Function[, \n  thisArg:any] )\n    Returns an iterator which returns the intersection of two or more iterators\n    according to a hash function.\n","iterInv":"\niterInv( iterator:Object )\n    Returns an iterator which iteratively computes the multiplicative inverse.\n","iterLanczosPulse":"\niterLanczosPulse( [options:Object] )\n    Returns an iterator which generates a Lanczos pulse waveform.\n","iterLast":"\niterLast( iterator:Object )\n    Consumes an entire iterator and returns the last iterated value.\n","iterLength":"\niterLength( iterator:Object )\n    Consumes an entire iterator and returns the number of iterated values.\n","iterLinspace":"\niterLinspace( start:number, stop:number[, N:integer] )\n    Returns an iterator which returns evenly spaced numbers over a specified\n    interval.\n","iterLn":"\niterLn( iterator:Object )\n    Returns an iterator which iteratively evaluates the natural logarithm.\n","iterLog":"\niterLog( x:Object|number, b:Object|number )\n    Returns an iterator which iteratively computes the base `b` logarithm.\n","iterLog1mexp":"\niterLog1mexp( iterator:Object )\n    Returns an iterator which iteratively evaluates the natural logarithm of\n    `1-exp(-|x|)`.\n","iterLog1p":"\niterLog1p( iterator:Object )\n    Returns an iterator which iteratively evaluates the natural logarithm of\n    `1+x`.\n","iterLog1pexp":"\niterLog1pexp( iterator:Object )\n    Returns an iterator which iteratively evaluates the natural logarithm of\n    `1+exp(x)`.\n","iterLog2":"\niterLog2( iterator:Object )\n    Returns an iterator which iteratively evaluates the binary logarithm.\n","iterLog10":"\niterLog10( iterator:Object )\n    Returns an iterator which iteratively evaluates the common logarithm\n    (logarithm with base 10).\n","iterLogit":"\niterLogit( iterator:Object )\n    Returns an iterator which iteratively evaluates the logit function.\n","iterLogspace":"\niterLogspace( start:number, stop:number[, N:integer][, options:Object] )\n    Returns an iterator which returns evenly spaced numbers on a log scale.\n","iterLucasSeq":"\niterLucasSeq( [options:Object] )\n    Returns an iterator which generates a Lucas sequence.\n","iterMap":"\niterMap( iterator:Object, fcn:Function[, thisArg:any] )\n    Returns an iterator which invokes a function for each iterated value.\n","iterMapN":"\niterMapN( iter0:Object, ...iterator:Object, fcn:Function[, thisArg:any] )\n    Returns an iterator which transforms iterated values from two or more\n    iterators by applying the iterated values as arguments to a provided\n    function.\n","itermax":"\nitermax( iterator:Object )\n    Computes the maximum value of all iterated values.\n","itermaxabs":"\nitermaxabs( iterator:Object )\n    Computes the maximum absolute value of all iterated values.\n","itermean":"\nitermean( iterator:Object )\n    Computes an arithmetic mean over all iterated values.\n","itermeanabs":"\nitermeanabs( iterator:Object )\n    Computes an arithmetic mean of absolute values for all iterated values.\n","itermeanabs2":"\nitermeanabs2( iterator:Object )\n    Computes an arithmetic mean of squared absolute values for all iterated\n    values.\n","itermidrange":"\nitermidrange( iterator:Object )\n    Computes the mid-range of all iterated values.\n","itermin":"\nitermin( iterator:Object )\n    Computes the minimum value of all iterated values.\n","iterminabs":"\niterminabs( iterator:Object )\n    Computes the minimum absolute value of all iterated values.\n","itermmax":"\nitermmax( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving maximum value.\n","itermmaxabs":"\nitermmaxabs( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving maximum absolute\n    value.\n","itermmean":"\nitermmean( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving arithmetic mean.\n","itermmeanabs":"\nitermmeanabs( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving arithmetic mean of\n    absolute values.\n","itermmeanabs2":"\nitermmeanabs2( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving arithmetic mean of\n    squared absolute values.\n","itermmidrange":"\nitermmidrange( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving mid-range.\n","itermmin":"\nitermmin( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving minimum value.\n","itermminabs":"\nitermminabs( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving minimum absolute\n    value.\n","iterMod":"\niterMod( iter0:Object, ...iterator:Object )\n    Returns an iterator which performs an element-wise modulo operation of two\n    or more iterators.\n","itermprod":"\nitermprod( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving product.\n","itermrange":"\nitermrange( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving range.\n","itermsum":"\nitermsum( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving sum.\n","itermsumabs":"\nitermsumabs( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving sum of absolute\n    values.\n","itermsumabs2":"\nitermsumabs2( iterator:Object, W:integer )\n    Returns an iterator which iteratively computes a moving sum of squared\n    absolute values.\n","iterMultiply":"\niterMultiply( iter0:Object, ...iterator:Object )\n    Returns an iterator which performs element-wise multiplication of two or\n    more iterators.\n","iterNegaFibonacciSeq":"\niterNegaFibonacciSeq( [options:Object] )\n    Returns an iterator which generates a negaFibonacci sequence.\n","iterNegaLucasSeq":"\niterNegaLucasSeq( [options:Object] )\n    Returns an iterator which generates a negaLucas sequence.\n","iterNegativeEvenIntegersSeq":"\niterNegativeEvenIntegersSeq( [options:Object] )\n    Returns an iterator which generates a sequence of negative even integers.\n","iterNegativeIntegersSeq":"\niterNegativeIntegersSeq( [options:Object] )\n    Returns an iterator which generates a negative integer sequence.\n","iterNegativeOddIntegersSeq":"\niterNegativeOddIntegersSeq( [options:Object] )\n    Returns an iterator which generates a sequence of negative odd integers.\n","iterNone":"\niterNone( iterator:Object )\n    Tests whether all iterated values are falsy.\n","iterNoneBy":"\niterNoneBy( iterator:Object, predicate:Function[, thisArg:any ] )\n    Tests whether every iterated value fails a test implemented by a predicate\n    function.\n","iterNonFibonacciSeq":"\niterNonFibonacciSeq( [options:Object] )\n    Returns an iterator which generates a non-Fibonacci integer sequence.\n","iterNonNegativeEvenIntegersSeq":"\niterNonNegativeEvenIntegersSeq( [options:Object] )\n    Returns an iterator which generates a sequence of nonnegative even integers.\n","iterNonNegativeIntegersSeq":"\niterNonNegativeIntegersSeq( [options:Object] )\n    Returns an iterator which generates a nonnegative integer sequence.\n","iterNonPositiveEvenIntegersSeq":"\niterNonPositiveEvenIntegersSeq( [options:Object] )\n    Returns an iterator which generates a sequence of nonpositive even integers.\n","iterNonPositiveIntegersSeq":"\niterNonPositiveIntegersSeq( [options:Object] )\n    Returns an iterator which generates a nonpositive integer sequence.\n","iterNonSquaresSeq":"\niterNonSquaresSeq( [options:Object] )\n    Returns an iterator which generates a sequence of nonsquares.\n","iterNth":"\niterNth( iterator:Object, n:integer )\n    Returns the nth iterated value.\n","iterOddIntegersSeq":"\niterOddIntegersSeq( [options:Object] )\n    Returns an iterator which generates an interleaved sequence of odd integers.\n","iterPeriodicSinc":"\niterPeriodicSinc( n:integer[, options:Object] )\n    Returns an iterator which generates a periodic sinc waveform.\n","iterPipeline":"\niterPipeline( iterFcn:Function|Array[, ...iterFcn:Function] )\n    Returns an iterator pipeline.\n","iterPop":"\niterPop( iterator:Object[, clbk:Function[, thisArg:any]] )\n    Returns an iterator which skips the last value of a provided iterator.\n","iterPositiveEvenIntegersSeq":"\niterPositiveEvenIntegersSeq( [options:Object] )\n    Returns an iterator which generates a sequence of positive even integers.\n","iterPositiveIntegersSeq":"\niterPositiveIntegersSeq( [options:Object] )\n    Returns an iterator which generates a positive integer sequence.\n","iterPositiveOddIntegersSeq":"\niterPositiveOddIntegersSeq( [options:Object] )\n    Returns an iterator which generates a sequence of positive odd integers.\n","iterPow":"\niterPow( base:Object|number, exponent:Object|number )\n    Returns an iterator which iteratively evaluates the exponential function.\n","iterPrimesSeq":"\niterPrimesSeq( [options:Object] )\n    Returns an iterator which generates a sequence of prime numbers.\n","iterprod":"\niterprod( iterator:Object )\n    Computes the product of all iterated values.\n","iterPulse":"\niterPulse( [options:Object] )\n    Returns an iterator which generates a pulse waveform.\n","iterPush":"\niterPush( iterator:Object, ...items:any )\n    Returns an iterator which appends additional values to the end of a provided\n    iterator.\n","iterRad2deg":"\niterRad2deg( iterator:Object )\n    Returns an iterator which iteratively converts an angle from radians to\n    degrees.\n","iterRamp":"\niterRamp( iterator:Object )\n    Returns an iterator which iteratively evaluates the ramp function.\n","iterrange":"\niterrange( iterator:Object )\n    Computes the range of all iterated values.\n","iterReject":"\niterReject( iterator:Object, predicate:Function[, thisArg:any] )\n    Returns an iterator which rejects a provided iterator's values according to\n    a predicate function.\n","iterReplicate":"\niterReplicate( iterator:Object, n:integer )\n    Returns an iterator which replicates each iterated value `n` times.\n","iterReplicateBy":"\niterReplicateBy( iterator:Object, fcn:Function[, thisArg:any] )\n    Returns an iterator which replicates each iterated value according to a\n    provided function.\n","iterRound":"\niterRound( iterator:Object )\n    Returns an iterator which rounds each iterated value to the nearest integer.\n","iterRound2":"\niterRound2( iterator:Object )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    two on a linear scale.\n","iterRound10":"\niterRound10( iterator:Object )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    10 on a linear scale.\n","iterRsqrt":"\niterRsqrt( iterator:Object )\n    Returns an iterator which iteratively computes the reciprocal (inverse)\n    square root.\n","iterSawtoothWave":"\niterSawtoothWave( [options:Object] )\n    Returns an iterator which generates a sawtooth wave.\n","iterShift":"\niterShift( iterator:Object[, clbk:Function[, thisArg:any]] )\n    Returns an iterator which skips the first value of a provided iterator.\n","iterSignum":"\niterSignum( iterator:Object )\n    Returns an iterator which iteratively evaluates the signum function.\n","iterSin":"\niterSin( iterator:Object )\n    Returns an iterator which iteratively computes the sine.\n","iterSinc":"\niterSinc( iterator:Object )\n    Returns an iterator which iteratively computes the normalized cardinal sine.\n","iterSineWave":"\niterSineWave( [options:Object] )\n    Returns an iterator which generates a sine wave.\n","iterSinh":"\niterSinh( iterator:Object )\n    Returns an iterator which iteratively evaluates the hyperbolic sine.\n","iterSinpi":"\niterSinpi( iterator:Object )\n    Returns an iterator which computes the sine of each iterated value times π.\n","iterSlice":"\niterSlice( iterator:Object[, begin:integer[, end:integer]] )\n    Returns an iterator which returns a subsequence of iterated values from a\n    provided iterator.\n","iterSome":"\niterSome( iterator:Object, n:number )\n    Tests whether at least `n` iterated values are truthy.\n","iterSomeBy":"\niterSomeBy( iterator:Object, n:integer, predicate:Function[, thisArg:any ] )\n    Tests whether at least `n` iterated values pass a test implemented by a\n    predicate function.\n","iterSpence":"\niterSpence( iterator:Object )\n    Returns an iterator which iteratively evaluates Spence's function.\n","iterSqrt":"\niterSqrt( iterator:Object )\n    Returns an iterator which iteratively computes the principal square root.\n","iterSqrt1pm1":"\niterSqrt1pm1( iterator:Object )\n    Returns an iterator which iteratively computes `sqrt(1+x) - 1` more \n    accurately for small `x`.\n","iterSquaredTriangularSeq":"\niterSquaredTriangularSeq( [options:Object] )\n    Returns an iterator which generates a sequence of squared triangular\n    numbers.\n","iterSquaresSeq":"\niterSquaresSeq( [options:Object] )\n    Returns an iterator which generates a sequence of squares.\n","iterSquareWave":"\niterSquareWave( [options:Object] )\n    Returns an iterator which generates a square wave.\n","iterstdev":"\niterstdev( iterator:Object[, mean:number] )\n    Computes a correct sample standard deviation over all iterated values.\n","iterStep":"\niterStep( start:number, increment:number[, N:number] )\n    Returns an iterator which returns a sequence of numbers according to a\n    specified increment.\n","iterStrided":"\niterStrided( iterator:Object, stride:integer[, offset:integer[, \n  eager:boolean]] )\n    Returns an iterator which steps by a specified amount.\n","iterStridedBy":"\niterStridedBy( iterator:Object, fcn:Function[, offset:integer[, \n  eager:boolean]][, thisArg:any] )\n    Returns an iterator which steps according to a provided callback function.\n","iterSubtract":"\niterSubtract( iter0:Object, ...iterator:Object )\n    Returns an iterator which performs element-wise subtraction of two or more\n    iterators.\n","itersum":"\nitersum( iterator:Object )\n    Computes the sum of all iterated values.\n","itersumabs":"\nitersumabs( iterator:Object )\n    Computes the sum of absolute values for all iterated values.\n","itersumabs2":"\nitersumabs2( iterator:Object )\n    Computes the sum of squared absolute values for all iterated values.\n","iterTan":"\niterTan( iterator:Object )\n    Returns an iterator which iteratively evaluates the tangent.\n","iterTanh":"\niterTanh( iterator:Object )\n    Returns an iterator which iteratively evaluates the hyperbolic tangent.\n","iterThunk":"\niterThunk( iterFcn:Function[, ...args:any] )\n    Returns an iterator \"thunk\".\n","iterTriangleWave":"\niterTriangleWave( [options:Object] )\n    Returns an iterator which generates a triangle wave.\n","iterTriangularSeq":"\niterTriangularSeq( [options:Object] )\n    Returns an iterator which generates a sequence of triangular numbers.\n","iterTribonnaciSeq":"\niterTribonnaciSeq( [options:Object] )\n    Returns an iterator which generates a Tribonacci sequence.\n    \n    The returned iterator can only generate the first 64 Tribonacci numbers, as\n    larger Tribonacci numbers cannot be safely represented in double-precision\n    floating-point format.\n","iterTrigamma":"\niterTrigamma( iterator:Object )\n    Returns an iterator which iteratively evaluates the trigamma function.\n","iterTrunc":"\niterTrunc( iterator:Object )\n    Returns an iterator which rounds each iterated value toward zero.\n","iterTrunc2":"\niterTrunc2( iterator:Object )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    two toward zero.\n","iterTrunc10":"\niterTrunc10( iterator:Object )\n    Returns an iterator which rounds each iterated value to the nearest power of\n    10 toward zero.\n","iterUnion":"\niterUnion( iter0:Object, ...iterator:Object )\n    Returns an iterator which returns the union of two or more iterators.\n","iterUnique":"\niterUnique( iterator:Object )\n    Returns an iterator which returns unique values.\n","iterUniqueBy":"\niterUniqueBy( iterator:Object, predicate:Function[, thisArg:any] )\n    Returns an iterator which returns unique values according to a predicate\n    function.\n","iterUniqueByHash":"\niterUniqueByHash( iterator:Object, hashFcn:Function[, thisArg:any] )\n    Returns an iterator which returns unique values according to a hash\n    function.\n","iterUnitspace":"\niterUnitspace( start:number[, stop:number] )\n    Returns an iterator which returns numbers incremented by one.\n","iterUnshift":"\niterUnshift( iterator:Object, ...items:any )\n    Returns an iterator which prepends values to the beginning of a provided\n    iterator.\n","iterUntilEach":"\niterUntilEach( iterator:Object, predicate:Function, fcn:Function[, \n  thisArg:any] )\n    Returns an iterator which invokes a function for each iterated value before\n    returning the iterated value until either a predicate function returns true\n    or the iterator has iterated over all values.\n","itervariance":"\nitervariance( iterator:Object[, mean:number] )\n    Computes an unbiased sample variance over all iterated values.\n","iterVercos":"\niterVercos( iterator:Object )\n    Returns an iterator which iteratively computes the versed cosine.\n","iterVersin":"\niterVersin( iterator:Object )\n    Returns an iterator which iteratively computes the versed sine.\n","iterWhileEach":"\niterWhileEach( iterator:Object, predicate:Function, fcn:Function[, \n  thisArg:any] )\n    Returns an iterator which invokes a function for each iterated value before\n    returning the iterated value until either a predicate function returns false\n    or the iterator has iterated over all values.\n","iterZeta":"\niterZeta( iterator:Object )\n    Returns an iterator which iteratively evaluates the Riemann zeta function.\n","joinStream":"\njoinStream( [options:Object] )\n    Returns a transform stream which joins streamed data.\n","joinStream.factory":"\njoinStream.factory( [options:Object] )\n    Returns a function for creating transform streams for joined streamed data.\n","joinStream.objectMode":"\njoinStream.objectMode( [options:Object] )\n    Returns an \"objectMode\" transform stream for joining streamed data.\n","kde2d":"\nkde2d( x:Array<number>, y:Array<number>[, options:Object] )\n    Two-dimensional kernel density estimation.\n","kebabcase":"\nkebabcase( str:string )\n    Converts a string to kebab case.\n","keyBy":"\nkeyBy( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n    Converts a collection to an object whose keys are determined by a provided\n    function and whose values are the collection values.\n","keyByRight":"\nkeyByRight( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )\n    Converts a collection to an object whose keys are determined by a provided\n    function and whose values are the collection values, iterating from right to\n    left.\n","keysIn":"\nkeysIn( obj:any )\n    Returns an array of an object's own and inherited enumerable property\n    names.\n","kruskalTest":"\nkruskalTest( ...x:Array[, options:Object] )\n    Computes the Kruskal-Wallis test for equal medians.\n","kstest":"\nkstest( x:Array<number>, y:Function|string[, ...params:number][, \n  options:Object] )\n    Computes a Kolmogorov-Smirnov goodness-of-fit test.\n","last":"\nlast( str:string[, n:integer][, options:Object] )\n    Returns the last character(s) of a string.\n","leveneTest":"\nleveneTest( x:Array<number>[, ...y:Array<number>[, options:Object]] )\n    Computes Levene's test for equal variances.\n","LinkedList":"\nLinkedList()\n    Linked list constructor.\n","linspace":"\nlinspace( start:number|ComplexLike, stop:number|ComplexLike, length:integer[, \n  options:Object] )\n    Generates a linearly spaced array over a specified interval.\n","linspace.assign":"\nlinspace.assign( start:number|ComplexLike, stop:number|ComplexLike, \n  out:ArrayLikeObject[, options:Object] )\n    Generates a linearly spaced sequence over a specified interval and assigns\n    the results to a provided output array.\n","LIU_NEGATIVE_OPINION_WORDS_EN":"\nLIU_NEGATIVE_OPINION_WORDS_EN()\n    Returns a list of negative opinion words.\n","LIU_POSITIVE_OPINION_WORDS_EN":"\nLIU_POSITIVE_OPINION_WORDS_EN()\n    Returns a list of positive opinion words.\n","LN_HALF":"\nLN_HALF\n    Natural logarithm of `1/2`.\n","LN_PI":"\nLN_PI\n    Natural logarithm of the mathematical constant `π`.\n","LN_SQRT_TWO_PI":"\nLN_SQRT_TWO_PI\n    Natural logarithm of the square root of `2π`.\n","LN_TWO_PI":"\nLN_TWO_PI\n    Natural logarithm of `2π`.\n","LN2":"\nLN2\n    Natural logarithm of `2`.\n","LN10":"\nLN10\n    Natural logarithm of `10`.\n","LOG2E":"\nLOG2E\n    Base 2 logarithm of Euler's number.\n","LOG10E":"\nLOG10E\n    Base 10 logarithm of Euler's number.\n","logspace":"\nlogspace( a:number, b:number[, length:integer] )\n    Generates a logarithmically spaced numeric array between `10^a` and `10^b`.\n","lowercase":"\nlowercase( str:string )\n    Converts a string to lowercase.\n","lowercaseKeys":"\nlowercaseKeys( obj:Object )\n    Converts each object key to lowercase.\n","lowess":"\nlowess( x:Array<number>, y:Array<number>[, options:Object] )\n    Locally-weighted polynomial regression via the LOWESS algorithm.\n","lpad":"\nlpad( str:string, len:integer[, pad:string] )\n    Left pads a string such that the padded string has a length of at least\n    `len`.\n","ltrim":"\nltrim( str:string )\n    Trims whitespace from the beginning of a string.\n","ltrimN":"\nltrimN( str:string, n:integer[, chars:Array|string] )\n    Trims `n` characters from the beginning of a string.\n","MALE_FIRST_NAMES_EN":"\nMALE_FIRST_NAMES_EN()\n    Returns a list of common male first names in English speaking countries.\n","map":"\nmap( arr:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n    Applies a function to each element in an array and assigns the result to an\n    element in a new array.\n","map.assign":"\nmap.assign( arr:ArrayLikeObject|ndarray, out:ArrayLikeObject|ndarray, \n  fcn:Function[, thisArg:any] )\n    Applies a function to each element in an array and assigns the result to an\n    element in an output array.\n","map2":"\nmap2( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, fcn:Function[, \n  thisArg:any] )\n    Applies a function to elements in two input arrays and assigns the results\n    to a new array.\n","map2.assign":"\nmap2.assign( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, \n  out:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n    Applies a function to elements in two input arrays and assigns the results\n    to an output array.\n","map2d":"\nmap2d( arr:ArrayLikeObject<ArrayLikeObject>, fcn:Function[, thisArg:any] )\n    Applies a function to each nested element in an array of arrays and assigns\n    the result to a nested element in a new array of arrays.\n","map2Right":"\nmap2Right( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, fcn:Function[, \n  thisArg:any] )\n    Applies a function to elements in two input arrays while iterating from\n    right to left and assigns the results to a new array.\n","map2Right.assign":"\nmap2Right.assign( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, \n  out:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n    Applies a function to elements in two input arrays while iterating from\n    right to left and assigns the results to an output array.\n","map3d":"\nmap3d( arr:ArrayLikeObject<ArrayLikeObject<ArrayLikeObject>>, fcn:Function[, \n  thisArg:any] )\n    Applies a function to each nested element in a three-dimensional nested\n    array and assigns the result to a nested element in a new three-dimensional\n    nested array.\n","map4d":"\nmap4d( arr:ArrayLikeObject<ArrayLikeObject>, fcn:Function[, thisArg:any] )\n    Applies a function to each nested element in a four-dimensional nested array\n    and assigns the result to a nested element in a new four-dimensional nested\n    array.\n","map5d":"\nmap5d( arr:ArrayLikeObject<ArrayLikeObject>, fcn:Function[, thisArg:any] )\n    Applies a function to each nested element in a five-dimensional nested array\n    and assigns the result to a nested element in a new five-dimensional nested\n    array.\n","mapArguments":"\nmapArguments( fcn:Function, clbk:Function[, thisArg:any] )\n    Returns a function that applies arguments to a provided function after\n    transforming arguments according to a callback function.\n","mapFun":"\nmapFun( fcn:Function, n:integer[, thisArg:any] )\n    Invokes a function `n` times and returns an array of accumulated function\n    return values.\n","mapFunAsync":"\nmapFunAsync( fcn:Function, n:integer, [options:Object,] done:Function )\n    Invokes a function `n` times and returns an array of accumulated function\n    return values.\n","mapFunAsync.factory":"\nmapFunAsync.factory( [options:Object,] fcn:Function )\n    Returns a function which invokes a function `n` times and returns an array\n    of accumulated function return values.\n","mapKeys":"\nmapKeys( obj:Object, transform:Function )\n    Maps keys from one object to a new object having the same values.\n","mapKeysAsync":"\nmapKeysAsync( obj:Object, [options:Object,] transform:Function, done:Function )\n    Maps keys from one object to a new object having the same values.\n","mapKeysAsync.factory":"\nmapKeysAsync.factory( [options:Object,] transform:Function )\n    Returns a function which maps keys from one object to a new object having\n    the same values.\n","mapReduce":"\nmapReduce( arr:ArrayLikeObject|ndarray, initial:any, mapper:Function, \n  reducer:Function[, thisArg:any] )\n    Performs a map-reduce operation for each element in an array and returns the\n    accumulated result.\n","mapReduceRight":"\nmapReduceRight( arr:ArrayLikeObject|ndarray, initial:any, mapper:Function, \n  reducer:Function[, thisArg:any] )\n    Performs a map-reduce operation for each element in an array while iterating\n    from right to left and returns the accumulated result.\n","mapRight":"\nmapRight( arr:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )\n    Applies a function to each element in an array and assigns the result to an\n    element in a new array, iterating from right to left.\n","mapRight.assign":"\nmapRight.assign( arr:ArrayLikeObject|ndarray, out:ArrayLikeObject|ndarray, \n  fcn:Function[, thisArg:any] )\n    Applies a function to each element in an array and assigns the result to an\n    element in an output array, iterating from right to left.\n","mapValues":"\nmapValues( obj:Object, transform:Function )\n    Maps values from one object to a new object having the same keys.\n","mapValuesAsync":"\nmapValuesAsync( obj:Object, [options:Object,] transform:Function, \n  done:Function )\n    Maps values from one object to a new object having the same keys.\n","mapValuesAsync.factory":"\nmapValuesAsync.factory( [options:Object,] transform:Function )\n    Returns a function which maps values from one object to a new object having\n    the same keys.\n","maskArguments":"\nmaskArguments( fcn:Function, mask:ArrayLikeObject[, thisArg:any] )\n    Returns a function that applies arguments to a provided function according\n    to a specified mask.\n","MAX_ARRAY_LENGTH":"\nMAX_ARRAY_LENGTH\n    Maximum length for a generic array.\n","MAX_TYPED_ARRAY_LENGTH":"\nMAX_TYPED_ARRAY_LENGTH\n    Maximum length for a typed array.\n","maybeBroadcastArray":"\nmaybeBroadcastArray( x:ndarray, shape:ArrayLikeObject )\n    Broadcasts an ndarray to a specified shape if and only if the specified\n    shape differs from the provided ndarray's shape.\n","maybeBroadcastArrays":"\nmaybeBroadcastArrays( ...arrays:ndarray|ArrayLikeObject<ndarray> )\n    Broadcasts ndarrays to a common shape.\n","memoize":"\nmemoize( fcn:Function[, hashFunction:Function] )\n    Returns a memoized function.\n","merge":"\nmerge( target:Object, ...source:Object )\n    Merges objects into a target object.\n","merge.factory":"\nmerge.factory( options:Object )\n    Returns a function for merging and extending objects.\n","MILLISECONDS_IN_DAY":"\nMILLISECONDS_IN_DAY\n    Number of milliseconds in a day.\n","MILLISECONDS_IN_HOUR":"\nMILLISECONDS_IN_HOUR\n    Number of milliseconds in an hour.\n","MILLISECONDS_IN_MINUTE":"\nMILLISECONDS_IN_MINUTE\n    Number of milliseconds in a minute.\n","MILLISECONDS_IN_SECOND":"\nMILLISECONDS_IN_SECOND\n    Number of milliseconds in a second.\n","MILLISECONDS_IN_WEEK":"\nMILLISECONDS_IN_WEEK\n    Number of milliseconds in a week.\n","MINARD_NAPOLEONS_MARCH":"\nMINARD_NAPOLEONS_MARCH( [options:Object] )\n    Returns data for Charles Joseph Minard's cartographic depiction of\n    Napoleon's Russian campaign of 1812.\n","MINUTES_IN_DAY":"\nMINUTES_IN_DAY\n    Number of minutes in a day.\n","MINUTES_IN_HOUR":"\nMINUTES_IN_HOUR\n    Number of minutes in an hour.\n","MINUTES_IN_WEEK":"\nMINUTES_IN_WEEK\n    Number of minutes in a week.\n","minutesInMonth":"\nminutesInMonth( [month:string|Date|integer[, year:integer]] )\n    Returns the number of minutes in a month.\n","minutesInYear":"\nminutesInYear( [value:integer|Date] )\n    Returns the number of minutes in a year according to the Gregorian calendar.\n","MOBY_DICK":"\nMOBY_DICK()\n    Returns the text of Moby Dick by Herman Melville.\n","MONTH_NAMES_EN":"\nMONTH_NAMES_EN()\n    Returns a list of month names (English).\n","MONTHS_IN_YEAR":"\nMONTHS_IN_YEAR\n    Number of months in a year.\n","moveProperty":"\nmoveProperty( source:Object, prop:string, target:Object )\n    Moves a property from one object to another object.\n","MultiSlice":"\nMultiSlice( ...slice )\n    Returns a multi-slice.\n","MultiSlice.prototype.ndims":"\nMultiSlice.prototype.ndims\n    Read-only property returning the number of slice dimensions.\n","MultiSlice.prototype.data":"\nMultiSlice.prototype.data\n    Read-only property returning the slice data.\n","MultiSlice.prototype.toString":"\nMultiSlice.prototype.toString()\n    Serializes a multi-slice as a string.\n","MultiSlice.prototype.toJSON":"\nMultiSlice.prototype.toJSON()\n    Serializes a multi-slice as a JSON object.\n","namedtypedtuple":"\nnamedtypedtuple( fields:Array<string>[, options:Object] )\n    Returns a named typed tuple factory.\n","NAN":"\nNAN\n    Double-precision floating-point NaN.\n","naryFunction":"\nnaryFunction( fcn:Function, arity:integer[, thisArg:any] )\n    Returns a function that applies a specified number of arguments to a\n    provided function.\n","nativeClass":"\nnativeClass( value:any )\n    Returns a string value indicating a specification defined classification of\n    an object.\n","ndarray":"\nndarray( dtype:string, buffer:ArrayLikeObject|TypedArray|Buffer, \n  shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, \n  offset:integer, order:string[, options:Object] )\n    Returns an ndarray.\n","ndarray.prototype.byteLength":"\nndarray.prototype.byteLength\n    Size (in bytes) of the array (if known).\n","ndarray.prototype.BYTES_PER_ELEMENT":"\nndarray.prototype.BYTES_PER_ELEMENT\n    Size (in bytes) of each array element (if known).\n","ndarray.prototype.data":"\nndarray.prototype.data\n    Pointer to the underlying data buffer.\n","ndarray.prototype.dtype":"\nndarray.prototype.dtype\n    Underlying data type.\n","ndarray.prototype.flags":"\nndarray.prototype.flags\n    Meta information, such as information concerning the memory layout of the\n    array.\n","ndarray.prototype.length":"\nndarray.prototype.length\n    Length of the array (i.e., number of elements).\n","ndarray.prototype.ndims":"\nndarray.prototype.ndims\n    Number of dimensions.\n","ndarray.prototype.offset":"\nndarray.prototype.offset\n    Index offset which specifies the buffer index at which to start iterating\n    over array elements.\n","ndarray.prototype.order":"\nndarray.prototype.order\n    Array order.\n","ndarray.prototype.shape":"\nndarray.prototype.shape\n    Array shape.\n","ndarray.prototype.strides":"\nndarray.prototype.strides\n    Index strides which specify how to access data along corresponding array\n    dimensions.\n","ndarray.prototype.get":"\nndarray.prototype.get( ...idx:integer )\n    Returns an array element specified according to provided subscripts.\n","ndarray.prototype.iget":"\nndarray.prototype.iget( idx:integer )\n    Returns an array element located at a specified linear index.\n","ndarray.prototype.set":"\nndarray.prototype.set( ...idx:integer, v:any )\n    Sets an array element specified according to provided subscripts.\n","ndarray.prototype.iset":"\nndarray.prototype.iset( idx:integer, v:any )\n    Sets an array element located at a specified linear index.\n","ndarray.prototype.toString":"\nndarray.prototype.toString()\n    Serializes an ndarray as a string.\n","ndarray.prototype.toJSON":"\nndarray.prototype.toJSON()\n    Serializes an ndarray as a JSON object.\n","ndarray2array":"\nndarray2array( x:ndarray )\n    Converts an ndarray to a generic array.\n","ndarray2fancy":"\nndarray2fancy( x:ndarray[, options:Object] )\n    Converts an ndarray to an object supporting fancy indexing.\n","ndarray2fancy.factory":"\nndarray2fancy.factory( [options:Object] )\n    Returns a function for converting an ndarray to an object supporting fancy\n    indexing.\n","ndarray2fancy.idx":"\nndarray2fancy.idx( x:ndarray[, options:Object] )\n    Wraps a provided ndarray as an ndarray index object.\n","ndarray2json":"\nndarray2json( x:ndarray )\n    Serializes an ndarray as a JSON object.\n","ndarrayCastingModes":"\nndarrayCastingModes()\n    Returns a list of ndarray casting modes.\n","ndarrayDataBuffer":"\nndarrayDataBuffer( x:ndarray )\n    Returns the underlying data buffer of a provided ndarray.\n","ndarrayDataType":"\nndarrayDataType( x:ndarray )\n    Returns the data type of a provided ndarray.\n","ndarrayDataTypes":"\nndarrayDataTypes( [kind:string] )\n    Returns a list of ndarray data types.\n","ndarrayDispatch":"\nndarrayDispatch( fcns:Function|ArrayLikeObject<Function>, \n  types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, \n  nout:integer )\n    Returns an ndarray function interface which performs multiple dispatch.\n","ndarrayFlag":"\nndarrayFlag( x:ndarray, name:string|symbol )\n    Returns a specified flag for a provided ndarray.\n","ndarrayFlags":"\nndarrayFlags( x:ndarray )\n    Returns the flags of a provided ndarray.\n","ndarrayIndexModes":"\nndarrayIndexModes()\n    Returns a list of ndarray index modes.\n","ndarraylike2ndarray":"\nndarraylike2ndarray( x:ndarrayLike[, options:Object] )\n    Converts an ndarray-like object to an ndarray.\n","ndarrayMinDataType":"\nndarrayMinDataType( value:any )\n    Returns the minimum ndarray data type of the closest \"kind\" necessary for\n    storing a provided scalar value.\n","ndarrayMostlySafeCasts":"\nndarrayMostlySafeCasts( [dtype:any] )\n    Returns a list of ndarray data types to which a provided ndarray data type\n    can be safely cast and, for floating-point data types, can be downcast.\n","ndarrayNextDataType":"\nndarrayNextDataType( [dtype:any] )\n    Returns the next larger ndarray data type of the same kind.\n","ndarrayOffset":"\nndarrayOffset( x:ndarray )\n    Returns the index offset specifying the underlying buffer index of the first\n    iterated ndarray element.\n","ndarrayOrder":"\nndarrayOrder( x:ndarray )\n    Returns the layout order of a provided ndarray.\n","ndarrayOrders":"\nndarrayOrders()\n    Returns a list of ndarray orders.\n","ndarrayPromotionRules":"\nndarrayPromotionRules( [dtype1:any, dtype2:any] )\n    Returns the ndarray data type with the smallest size and closest \"kind\" to\n    which ndarray data types can be safely cast.\n","ndarraySafeCasts":"\nndarraySafeCasts( [dtype:any] )\n    Returns a list of ndarray data types to which a provided ndarray data type\n    can be safely cast.\n","ndarraySameKindCasts":"\nndarraySameKindCasts( [dtype:any] )\n    Returns a list of ndarray data types to which a provided ndarray data type\n    can be safely cast or cast within the same \"kind\".\n","ndarrayShape":"\nndarrayShape( x:ndarray )\n    Returns the shape of a provided ndarray.\n","ndarrayStride":"\nndarrayStride( x:ndarray, dim:integer )\n    Returns the stride along a specified dimension for a provided ndarray.\n","ndarrayStrides":"\nndarrayStrides( x:ndarray )\n    Returns the strides of a provided ndarray.\n","ndat":"\nndat( x:ndarray[, ...indices:integer] )\n    Returns an ndarray element.\n","ndempty":"\nndempty( shape:ArrayLikeObject<integer>|integer[, options:Object] )\n    Returns an uninitialized ndarray having a specified shape and data type.\n","ndemptyLike":"\nndemptyLike( x:ndarray[, options:Object] )\n    Returns an uninitialized ndarray having the same shape and data type as a\n    provided input ndarray.\n","ndfilter":"\nndfilter( x:ndarray[, options:Object], predicate:Function[, thisArg:any] )\n    Returns a shallow copy of an ndarray containing only those elements which\n    pass a test implemented by a predicate function.\n","ndfilterMap":"\nndfilterMap( x:ndarray[, options:Object], fcn:Function[, thisArg:any] )\n    Filters and maps elements in an input ndarray to elements in a new output\n    ndarray according to a callback function.\n","ndforEach":"\nndforEach( x:ndarray, fcn:Function[, thisArg:any] )\n    Invokes a callback function once for each ndarray element.\n","ndims":"\nndims( x:ndarray )\n    Returns the number of ndarray dimensions.\n","ndindex":"\nndindex( x:ndarray[, options:Object] )\n    Wraps a provided array as an ndarray index object.\n","ndindex.free":"\nndindex.free( id:string )\n    Frees the instance associated with a provided identifier.\n","ndindex.get":"\nndindex.get( id:string )\n    Returns the ndarray associated with the instance having a provided\n    identifier.\n","ndindex.cartesianIndex":"\nndindex.cartesianIndex( x:ndarray[, options:Object] )\n    Returns an ndarray index containing Cartesian indices.\n","ndindex.linearIndex":"\nndindex.linearIndex( x:ndarray[, options:Object] )\n    Returns an ndarray index for indices representing locations in linear\n    memory.\n","ndindex.prototype.data":"\nndindex.prototype.data\n    Read-only property returning an ndarray view of the underlying index\n    ndarray.\n","ndindex.prototype.dtype":"\nndindex.prototype.dtype\n    Read-only property returning the underlying data type of the index ndarray.\n","ndindex.prototype.id":"\nndindex.prototype.id\n    Read-only property returning the unique identifier associated with an\n    instance.\n","ndindex.prototype.isCached":"\nndindex.prototype.isCached\n    Read-only property returning a boolean indicating whether an ndarray index\n    is actively cached.\n","ndindex.prototype.kind":"\nndindex.prototype.kind\n    Read-only property returning the ndarray index kind.\n","ndindex.prototype.type":"\nndindex.prototype.type\n    Read-only property returning the ndarray index type.\n","ndindex.prototype.toString":"\nndindex.prototype.toString()\n    Serializes an instance as a string.\n","ndindex.prototype.toJSON":"\nndindex.prototype.toJSON()\n    Serializes an instance as a JSON object.\n","nditerColumnEntries":"\nnditerColumnEntries( x:ndarray[, options:Object] )\n    Returns an iterator which returns [index, column] pairs for each column in a\n    matrix (or stack of matrices).\n","nditerColumns":"\nnditerColumns( x:ndarray[, options:Object] )\n    Returns an iterator which iterates over each column in a matrix (or stack of\n    matrices).\n","nditerEntries":"\nnditerEntries( x:ndarray[, options:Object] )\n    Returns an iterator which returns [index, value] pairs for each element in a\n    provided ndarray.\n","nditerIndices":"\nnditerIndices( shape:Array<integer>[, options:Object] )\n    Returns an iterator which returns indices for use indexing into an ndarray\n    having a specified shape.\n","nditerInterleaveSubarrays":"\nnditerInterleaveSubarrays( arr:ArrayLike<ndarray>, ndims:integer )\n    Returns an iterator which iterates over interleaved subarrays.\n","nditerMatrices":"\nnditerMatrices( x:ndarray[, options:Object] )\n    Returns an iterator which iterates over each matrix in a stack of matrices.\n","nditerMatrixEntries":"\nnditerMatrixEntries( x:ndarray[, options:Object] )\n    Returns an iterator which returns [index, matrix] pairs for each matrix in a\n    stack of matrices.\n","nditerRowEntries":"\nnditerRowEntries( x:ndarray[, options:Object] )\n    Returns an iterator which returns [index, row] pairs for each row in a\n    matrix (or stack of matrices).\n","nditerRows":"\nnditerRows( x:ndarray[, options:Object] )\n    Returns an iterator which iterates over each row in a matrix (or stack of\n    matrices).\n","nditerSelectDimension":"\nnditerSelectDimension( x:ndarray, dim:integer[, options:Object] )\n    Returns an iterator which iterates over each view along a specified\n    dimension.\n","nditerStacks":"\nnditerStacks( x:ndarray, dims:Array<integer>[, options:Object] )\n    Returns an iterator which iterates over each subarray in a stack of\n    subarrays according to a list of specified stack dimensions.\n","nditerSubarrays":"\nnditerSubarrays( x:ndarray, ndims:integer[, options:Object] )\n    Returns an iterator which iterates over each subarray in a stack of\n    subarrays.\n","nditerValues":"\nnditerValues( x:ndarray[, options:Object] )\n    Returns an iterator which returns individual elements from a provided\n    ndarray.\n","ndmap":"\nndmap( x:ndarray[, options:Object], fcn:Function[, thisArg:any] )\n    Applies a callback function to elements in an input ndarray and assigns\n    results to elements in a new output ndarray.\n","ndreject":"\nndreject( x:ndarray[, options:Object], predicate:Function[, thisArg:any] )\n    Returns a shallow copy of an ndarray containing only those elements which\n    fail a test implemented by a predicate function.\n","ndslice":"\nndslice( x:ndarray, ...s:MultiSlice|Slice|null|undefined|integer|ArrayLike[, \n  options:Object] )\n    Returns a read-only view of an input ndarray.\n","ndsliceAssign":"\nndsliceAssign( x:ndarray, y:ndarray, \n  ...s:MultiSlice|Slice|null|undefined|integer|ArrayLike[, options:Object] )\n    Assigns element values from a broadcasted input ndarray to corresponding\n    elements in an output ndarray view.\n","ndsliceDimension":"\nndsliceDimension( x:ndarray, dim:integer, slice:Slice|integer|null|undefined[, \n  options:Object] )\n    Returns a read-only view of an input ndarray when sliced along a specified\n    dimension.\n","ndsliceDimensionFrom":"\nndsliceDimensionFrom( x:ndarray, dim:integer, start:integer[, options:Object] )\n    Returns a read-only shifted view of an input ndarray along a specified\n    dimension.\n","ndsliceDimensionTo":"\nndsliceDimensionTo( x:ndarray, dim:integer, stop:integer[, options:Object] )\n    Returns a read-only truncated view of an input ndarray along a specified\n    dimension.\n","ndsliceFrom":"\nndsliceFrom( x:ndarray, ...start:null|void|integer[, options:Object] )\n    Returns a read-only shifted view of an input ndarray.\n","ndsliceTo":"\nndsliceTo( x:ndarray, ...stop:null|void|integer[, options:Object] )\n    Returns a read-only truncated view of an input ndarray.\n","ndzeros":"\nndzeros( shape:ArrayLikeObject<integer>|integer[, options:Object] )\n    Returns a zero-filled ndarray having a specified shape and data type.\n","ndzerosLike":"\nndzerosLike( x:ndarray[, options:Object] )\n    Returns a zero-filled ndarray having the same shape and data type as a\n    provided input ndarray.\n","nextGraphemeClusterBreak":"\nnextGraphemeClusterBreak( str:string[, fromIndex:integer] )\n    Returns the next extended grapheme cluster break in a string after a\n    specified position.\n","nextTick":"\nnextTick( clbk[, ...args] )\n    Adds a callback to the \"next tick queue\".\n","NIGHTINGALES_ROSE":"\nNIGHTINGALES_ROSE()\n    Returns data for Nightingale's famous polar area diagram.\n","NINF":"\nNINF\n    Double-precision floating-point negative infinity.\n","NODE_VERSION":"\nNODE_VERSION\n    Node version.\n","none":"\nnone( collection:Array|TypedArray|Object )\n    Tests whether all elements in a collection are falsy.\n","noneBy":"\nnoneBy( collection:Array|TypedArray|Object, predicate:Function[, thisArg:any ] )\n    Tests whether all elements in a collection fail a test implemented by a\n    predicate function.\n","noneByAsync":"\nnoneByAsync( collection:Array|TypedArray|Object, [options:Object,] \n  predicate:Function, done:Function )\n    Tests whether all elements in a collection fail a test implemented by a\n    predicate function.\n","noneByAsync.factory":"\nnoneByAsync.factory( [options:Object,] predicate:Function )\n    Returns a function which tests whether all elements in a collection fail a\n    test implemented by a predicate function.\n","noneByRight":"\nnoneByRight( collection:Array|TypedArray|Object, predicate:Function[, \n  thisArg:any ] )\n    Tests whether all elements in a collection fail a test implemented by a\n    predicate function, iterating from right to left.\n","noneByRightAsync":"\nnoneByRightAsync( collection:Array|TypedArray|Object, [options:Object,] \n  predicate:Function, done:Function )\n    Tests whether all elements in a collection fail a test implemented by a\n    predicate function, iterating from right to left.\n","noneByRightAsync.factory":"\nnoneByRightAsync.factory( [options:Object,] predicate:Function )\n    Returns a function which tests whether all elements in a collection fail a\n    test implemented by a predicate function, iterating from right to left.\n","noneInBy":"\nnoneInBy( object:Object, predicate:Function[, thisArg:any ] )\n    Tests whether every property in an object fails a test implemented by a\n    predicate function.\n","nonEnumerableProperties":"\nnonEnumerableProperties( value:any )\n    Returns an array of an object's own non-enumerable property names and\n    symbols.\n","nonEnumerablePropertiesIn":"\nnonEnumerablePropertiesIn( value:any )\n    Returns an array of an object's own and inherited non-enumerable property\n    names and symbols.\n","nonEnumerablePropertyNames":"\nnonEnumerablePropertyNames( value:any )\n    Returns an array of an object's own non-enumerable property names.\n","nonEnumerablePropertyNamesIn":"\nnonEnumerablePropertyNamesIn( value:any )\n    Returns an array of an object's own and inherited non-enumerable property\n    names.\n","nonEnumerablePropertySymbols":"\nnonEnumerablePropertySymbols( value:any )\n    Returns an array of an object's own non-enumerable symbol properties.\n","nonEnumerablePropertySymbolsIn":"\nnonEnumerablePropertySymbolsIn( value:any )\n    Returns an array of an object's own and inherited non-enumerable symbol\n    properties.\n","noneOwnBy":"\nnoneOwnBy( object:Object, predicate:Function[, thisArg:any ] )\n    Tests whether every own property of an object fails a test implemented\n    by a predicate function.\n","nonIndexKeys":"\nnonIndexKeys( obj:any )\n    Returns an array of an object's own enumerable property names which are not\n    integer indices.\n","noop":"\nnoop()\n    A function which does nothing.\n","now":"\nnow()\n    Returns the time in seconds since the epoch.\n","NUM_CPUS":"\nNUM_CPUS\n    Number of CPUs.\n","num2words":"\nnum2words( value:integer[, options:Object] )\n    Converts a number to a word representation.\n","Number":"\nNumber( value:number )\n    Returns a Number object.\n","numel":"\nnumel( x:ndarray )\n    Returns the number of elements in an ndarray.\n","numelDimension":"\nnumelDimension( x:ndarray, dim:integer )\n    Returns the size (i.e., number of elements) of a specified dimension for a\n    provided ndarray.\n","numGraphemeClusters":"\nnumGraphemeClusters( str:string )\n    Returns the number of grapheme clusters in a string.\n","Object":"\nObject( value:any )\n    Returns an object.\n","Object.assign":"\nObject.assign( target:Object, ...sources:Object )\n    Assigns enumerable and own properties from source objects to a target\n    object.\n","Object.create":"\nObject.create( prototype:Object, properties:Object )\n    Creates a new object with a specified prototype object and properties.\n","Object.defineProperties":"\nObject.defineProperties( obj:Object, properties:Object )\n    Defines properties for an object.\n","Object.defineProperty":"\nObject.defineProperty( obj:Object, key:string, descriptor:Object )\n    Defines a property for an object.\n","Object.entries":"\nObject.entries( obj:Object )\n    Returns an array of an object's own enumerable string-keyed property\n    [key, value] pairs.\n","Object.freeze":"\nObject.freeze( obj:Object )\n    Freezes an object.\n","Object.getOwnPropertyDescriptor":"\nObject.getOwnPropertyDescriptor( obj:Object, key:string )\n    Returns an object's own property descriptor.\n","Object.getOwnPropertyDescriptors":"\nObject.getOwnPropertyDescriptors( obj:Object )\n    Returns an object's own property descriptors.\n","Object.getOwnPropertyNames":"\nObject.getOwnPropertyNames( obj:Object )\n    Returns an array of an object's own enumerable and non-enumerable\n    property names.\n","Object.getOwnPropertySymbols":"\nObject.getOwnPropertySymbols( obj:Object )\n    Returns an array of an object's own enumerable and non-enumerable\n    symbol property names.\n","Object.getPrototypeOf":"\nObject.getPrototypeOf( obj:Object )\n    Returns an object's prototype.\n","Object.hasOwn":"\nObject.hasOwn( obj:Object, p:string )\n    Returns a boolean indicating whether an object has a property with the\n    specified name.\n","Object.is":"\nObject.is( value1:any, value2:any )\n    Returns a boolean indicating whether two values are the same value.\n","Object.isExtensible":"\nObject.isExtensible( obj:Object )\n    Returns a boolean indicating whether an object is extensible.\n","Object.isFrozen":"\nObject.isFrozen( obj:Object )\n    Returns a boolean indicating whether an object is frozen.\n","Object.isSealed":"\nObject.isSealed( obj:Object )\n    Returns a boolean indicating whether an object is sealed.\n","Object.keys":"\nObject.keys( obj:Object )\n    Returns an array of an object's own enumerable string-keyed property\n    names.\n","Object.preventExtensions":"\nObject.preventExtensions( obj:Object )\n    Prevents the addition of new properties to an object.\n","Object.seal":"\nObject.seal( obj:Object )\n    Prevents the addition of new properties to an object and marks all\n    existing properties as non-configurable.\n","Object.setPrototypeOf":"\nObject.setPrototypeOf( obj:Object, proto:Object )\n    Sets an object's prototype.\n","Object.values":"\nObject.values( obj:Object )\n    Returns an array of an object's own enumerable property values.\n","Object.prototype.toLocaleString":"\nObject.prototype.toLocaleString()\n    Returns a string representing the object.\n","Object.prototype.toString":"\nObject.prototype.toString()\n    Returns a string representing the object.\n","Object.prototype.valueOf":"\nObject.prototype.valueOf()\n    Returns the primitive value of the object.\n","Object.prototype.hasOwnProperty":"\nObject.prototype.hasOwnProperty( p:string )\n    Returns a boolean indicating whether an object has a property with the\n    specified name.\n","Object.prototype.isPrototypeOf":"\nObject.prototype.isPrototypeOf( obj:Object )\n    Returns a boolean indicating whether an object exists in another object's\n    prototype chain.\n","Object.prototype.propertyIsEnumerable":"\nObject.prototype.propertyIsEnumerable( p:string )\n    Returns a boolean indicating whether an object's property is enumerable.\n","Object.prototype.constructor":"\nObject.prototype.constructor\n    Property whose value is a reference to the constructor function that\n    created the instance object.\n","objectEntries":"\nobjectEntries( obj:ObjectLike )\n    Returns an array of an object's own enumerable property `[key, value]`\n    pairs.\n","objectEntriesIn":"\nobjectEntriesIn( obj:ObjectLike )\n    Returns an array of an object's own and inherited enumerable property\n    `[key, value]` pairs.\n","objectFromEntries":"\nobjectFromEntries( entries:Array<Array> )\n    Creates an object from an array of key-value pairs.\n","objectInverse":"\nobjectInverse( obj:ObjectLike[, options:Object] )\n    Inverts an object, such that keys become values and values become keys.\n","objectInverseBy":"\nobjectInverseBy( obj:ObjectLike, [options:Object,] transform:Function )\n    Inverts an object, such that keys become values and values become keys,\n    according to a transform function.\n","objectKeys":"\nobjectKeys( value:any )\n    Returns an array of an object's own enumerable property names.\n","objectValues":"\nobjectValues( obj:ObjectLike )\n    Returns an array of an object's own enumerable property values.\n","objectValuesIn":"\nobjectValuesIn( obj:ObjectLike )\n    Returns an array of an object's own and inherited enumerable property\n    values.\n","omit":"\nomit( obj:Object, keys:string|Array )\n    Returns a partial object copy excluding specified keys.\n","omitBy":"\nomitBy( obj:Object, predicate:Function )\n    Returns a partial object copy excluding properties for which a predicate\n    returns a truthy value.\n","open":"\nopen( path:string|Buffer[, flags:string|number[, mode:integer]], clbk:Function )\n    Asynchronously opens a file.\n","open.sync":"\nopen.sync( path:string|Buffer[, flags:string|number[, mode:integer]] )\n    Synchronously opens a file.\n","openURL":"\nopenURL( url:string )\n    Opens a URL in a user's default browser.\n","ordinalize":"\nordinalize( value:string|integer[, options:Object] )\n    Converts an integer to an ordinal string (e.g., `1st`, `2nd`, etc.).\n","PACE_BOSTON_HOUSE_PRICES":"\nPACE_BOSTON_HOUSE_PRICES()\n    Returns a (corrected) dataset derived from information collected by the US\n    Census Service concerning housing in Boston, Massachusetts (1978).\n","pad":"\npad( str:string, len:integer[, options:Object] )\n    Pads a `string` such that the padded `string` has length `len`.\n","padjust":"\npadjust( pvals:Array<number>, method:string[, comparisons:integer] )\n    Adjusts supplied p-values for multiple comparisons via a specified method.\n","papply":"\npapply( fcn:Function, ...args:any )\n    Returns a function of smaller arity by partially applying arguments.\n","papplyRight":"\npapplyRight( fcn:Function, ...args:any )\n    Returns a function of smaller arity by partially applying arguments from the\n    right.\n","parallel":"\nparallel( files:Array<string>, [options:Object,] clbk:Function )\n    Executes scripts in parallel.\n","parseJSON":"\nparseJSON( str:string[, reviver:Function] )\n    Attempts to parse a string as JSON.\n","pascalcase":"\npascalcase( str:string )\n    Converts a string to Pascal case.\n","PATH_DELIMITER":"\nPATH_DELIMITER\n    Platform-specific path delimiter.\n","PATH_DELIMITER_POSIX":"\nPATH_DELIMITER_POSIX\n    POSIX path delimiter.\n","PATH_DELIMITER_WIN32":"\nPATH_DELIMITER_WIN32\n    Windows path delimiter.\n","PATH_SEP":"\nPATH_SEP\n    Platform-specific path segment separator.\n","PATH_SEP_POSIX":"\nPATH_SEP_POSIX\n    POSIX path segment separator.\n","PATH_SEP_WIN32":"\nPATH_SEP_WIN32\n    Windows path segment separator.\n","pcorrtest":"\npcorrtest( x:Array<number>, y:Array<number>[, options:Object] )\n    Computes a Pearson product-moment correlation test between paired samples.\n","percentEncode":"\npercentEncode( str:string )\n    Percent-encodes a UTF-16 encoded string according to RFC 3986.\n","PHI":"\nPHI\n    Golden ratio.\n","PI":"\nPI\n    The mathematical constant `π`.\n","PI_SQUARED":"\nPI_SQUARED\n    Square of the mathematical constant `π`.\n","pick":"\npick( obj:Object, keys:string|Array )\n    Returns a partial object copy containing only specified keys.\n","pickArguments":"\npickArguments( fcn:Function, indices:Array<integer>[, thisArg:any] )\n    Returns a function that applies specified arguments to a provided function.\n","pickBy":"\npickBy( obj:Object, predicate:Function )\n    Returns a partial object copy containing properties for which a predicate\n    returns a truthy value.\n","PINF":"\nPINF\n    Double-precision floating-point positive infinity.\n","pkg2alias":"\npkg2alias( pkg:string )\n    Returns the alias associated with a specified package name.\n","pkg2related":"\npkg2related( pkg:string )\n    Returns package names related to a specified package name.\n","pkg2standalone":"\npkg2standalone( pkg:string )\n    Returns the standalone package name associated with a provided internal\n    package name.\n","PLATFORM":"\nPLATFORM\n    Platform on which the current process is running.\n","plot":"\nplot( [x:Array|Array, y:Array|Array,] [options:Object] )\n    Returns a plot instance for creating 2-dimensional plots.\n","Plot":"\nPlot( [x:Array|Array, y:Array|Array,] [options:Object] )\n    Returns a plot instance for creating 2-dimensional plots.\n","pluck":"\npluck( arr:Array, prop:string[, options:Object] )\n    Extracts a property value from each element of an object array.\n","pop":"\npop( collection:Array|TypedArray|Object )\n    Removes and returns the last element of a collection.\n","porterStemmer":"\nporterStemmer( word:string )\n    Extracts the stem of a given word.\n","prepend":"\nprepend( collection1:Array|TypedArray|Object, \n  collection2:Array|TypedArray|Object )\n    Adds the elements of one collection to the beginning of another collection.\n","prevGraphemeClusterBreak":"\nprevGraphemeClusterBreak( str:string[, fromIndex:integer] )\n    Returns the previous extended grapheme cluster break in a string before a\n    specified position.\n","PRIMES_100K":"\nPRIMES_100K()\n    Returns an array containing the first 100,000 prime numbers.\n","properties":"\nproperties( value:any )\n    Returns an array of an object's own enumerable and non-enumerable property\n    names and symbols.\n","propertiesIn":"\npropertiesIn( value:any )\n    Returns an array of an object's own and inherited property names and\n    symbols.\n","propertyDescriptor":"\npropertyDescriptor( value:any, property:string|symbol )\n    Returns a property descriptor for an object's own property.\n","propertyDescriptorIn":"\npropertyDescriptorIn( value:any, property:string|symbol )\n    Returns a property descriptor for an object's own or inherited property.\n","propertyDescriptors":"\npropertyDescriptors( value:any )\n    Returns an object's own property descriptors.\n","propertyDescriptorsIn":"\npropertyDescriptorsIn( value:any )\n    Returns an object's own and inherited property descriptors.\n","propertyNames":"\npropertyNames( value:any )\n    Returns an array of an object's own enumerable and non-enumerable property\n    names.\n","propertyNamesIn":"\npropertyNamesIn( value:any )\n    Returns an array of an object's own and inherited enumerable and non-\n    enumerable property names.\n","propertySymbols":"\npropertySymbols( value:any )\n    Returns an array of an object's own symbol properties.\n","propertySymbolsIn":"\npropertySymbolsIn( value:any )\n    Returns an array of an object's own and inherited symbol properties.\n","Proxy":"\nProxy( target:Object, handlers:Object )\n    Returns a proxy object implementing custom behavior for specified object\n    operations.\n","Proxy.revocable":"\nProxy.revocable( target:Object, handlers:Object )\n    Returns a revocable proxy object.\n","push":"\npush( collection:Array|TypedArray|Object, ...items:any )\n    Adds one or more elements to the end of a collection.\n","quarterOfYear":"\nquarterOfYear( [month:integer|string|Date] )\n    Returns the quarter of the year.\n","random.array.arcsine":"\nrandom.array.arcsine( len:integer, a:number, b:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from an arcsine\n    distribution.\n","random.array.arcsine.assign":"\nrandom.array.arcsine.assign( a:number, b:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from an arcsine distribution.\n","random.array.arcsine.factory":"\nrandom.array.arcsine.factory( [a:number, b:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an arcsine distribution.\n","random.array.arcsine.PRNG":"\nrandom.array.arcsine.PRNG\n    Underlying pseudorandom number generator.\n","random.array.arcsine.seed":"\nrandom.array.arcsine.seed\n    Pseudorandom number generator seed.\n","random.array.arcsine.seedLength":"\nrandom.array.arcsine.seedLength\n    Length of generator seed.\n","random.array.arcsine.state":"\nrandom.array.arcsine.state\n    Generator state.\n","random.array.arcsine.stateLength":"\nrandom.array.arcsine.stateLength\n    Length of generator state.\n","random.array.arcsine.byteLength":"\nrandom.array.arcsine.byteLength\n    Size (in bytes) of generator state.\n","random.array.bernoulli":"\nrandom.array.bernoulli( len:integer, p:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a Bernoulli\n    distribution.\n","random.array.bernoulli.assign":"\nrandom.array.bernoulli.assign( p:number, out:Array|TypedArray )\n    Fills an array with pseudorandom numbers drawn from a Bernoulli\n    distribution.\n","random.array.bernoulli.factory":"\nrandom.array.bernoulli.factory( [p:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Bernoulli distribution.\n","random.array.bernoulli.PRNG":"\nrandom.array.bernoulli.PRNG\n    Underlying pseudorandom number generator.\n","random.array.bernoulli.seed":"\nrandom.array.bernoulli.seed\n    Pseudorandom number generator seed.\n","random.array.bernoulli.seedLength":"\nrandom.array.bernoulli.seedLength\n    Length of generator seed.\n","random.array.bernoulli.state":"\nrandom.array.bernoulli.state\n    Generator state.\n","random.array.bernoulli.stateLength":"\nrandom.array.bernoulli.stateLength\n    Length of generator state.\n","random.array.bernoulli.byteLength":"\nrandom.array.bernoulli.byteLength\n    Size (in bytes) of generator state.\n","random.array.beta":"\nrandom.array.beta( len:integer, alpha:number, beta:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a beta\n    distribution.\n","random.array.beta.assign":"\nrandom.array.beta.assign( alpha:number, beta:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a beta distribution.\n","random.array.beta.factory":"\nrandom.array.beta.factory( [alpha:number, beta:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a beta distribution.\n","random.array.beta.PRNG":"\nrandom.array.beta.PRNG\n    Underlying pseudorandom number generator.\n","random.array.beta.seed":"\nrandom.array.beta.seed\n    Pseudorandom number generator seed.\n","random.array.beta.seedLength":"\nrandom.array.beta.seedLength\n    Length of generator seed.\n","random.array.beta.state":"\nrandom.array.beta.state\n    Generator state.\n","random.array.beta.stateLength":"\nrandom.array.beta.stateLength\n    Length of generator state.\n","random.array.beta.byteLength":"\nrandom.array.beta.byteLength\n    Size (in bytes) of generator state.\n","random.array.betaprime":"\nrandom.array.betaprime( len:integer, alpha:number, beta:number[, \n  options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a beta prime\n    distribution.\n","random.array.betaprime.assign":"\nrandom.array.betaprime.assign( alpha:number, beta:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a beta prime\n    distribution.\n","random.array.betaprime.factory":"\nrandom.array.betaprime.factory( [alpha:number, beta:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a beta prime distribution.\n","random.array.betaprime.PRNG":"\nrandom.array.betaprime.PRNG\n    Underlying pseudorandom number generator.\n","random.array.betaprime.seed":"\nrandom.array.betaprime.seed\n    Pseudorandom number generator seed.\n","random.array.betaprime.seedLength":"\nrandom.array.betaprime.seedLength\n    Length of generator seed.\n","random.array.betaprime.state":"\nrandom.array.betaprime.state\n    Generator state.\n","random.array.betaprime.stateLength":"\nrandom.array.betaprime.stateLength\n    Length of generator state.\n","random.array.betaprime.byteLength":"\nrandom.array.betaprime.byteLength\n    Size (in bytes) of generator state.\n","random.array.binomial":"\nrandom.array.binomial( len:integer, n:number, p:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a binomial\n    distribution.\n","random.array.binomial.assign":"\nrandom.array.binomial.assign( n:number, p:number, out:Array|TypedArray )\n    Fills an array with pseudorandom numbers drawn from a binomial distribution.\n","random.array.binomial.factory":"\nrandom.array.binomial.factory( [n:number, p:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a binomial distribution.\n","random.array.binomial.PRNG":"\nrandom.array.binomial.PRNG\n    Underlying pseudorandom number generator.\n","random.array.binomial.seed":"\nrandom.array.binomial.seed\n    Pseudorandom number generator seed.\n","random.array.binomial.seedLength":"\nrandom.array.binomial.seedLength\n    Length of generator seed.\n","random.array.binomial.state":"\nrandom.array.binomial.state\n    Generator state.\n","random.array.binomial.stateLength":"\nrandom.array.binomial.stateLength\n    Length of generator state.\n","random.array.binomial.byteLength":"\nrandom.array.binomial.byteLength\n    Size (in bytes) of generator state.\n","random.array.cauchy":"\nrandom.array.cauchy( len:integer, x0:number, gamma:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a Cauchy\n    distribution.\n","random.array.cauchy.assign":"\nrandom.array.cauchy.assign( x0:number, gamma:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a Cauchy distribution.\n","random.array.cauchy.factory":"\nrandom.array.cauchy.factory( [x0:number, gamma:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Cauchy distribution.\n","random.array.cauchy.PRNG":"\nrandom.array.cauchy.PRNG\n    Underlying pseudorandom number generator.\n","random.array.cauchy.seed":"\nrandom.array.cauchy.seed\n    Pseudorandom number generator seed.\n","random.array.cauchy.seedLength":"\nrandom.array.cauchy.seedLength\n    Length of generator seed.\n","random.array.cauchy.state":"\nrandom.array.cauchy.state\n    Generator state.\n","random.array.cauchy.stateLength":"\nrandom.array.cauchy.stateLength\n    Length of generator state.\n","random.array.cauchy.byteLength":"\nrandom.array.cauchy.byteLength\n    Size (in bytes) of generator state.\n","random.array.chi":"\nrandom.array.chi( len:integer, k:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a chi\n    distribution.\n","random.array.chi.assign":"\nrandom.array.chi.assign( k:number, out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a chi distribution.\n","random.array.chi.factory":"\nrandom.array.chi.factory( [k:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a chi distribution.\n","random.array.chi.PRNG":"\nrandom.array.chi.PRNG\n    Underlying pseudorandom number generator.\n","random.array.chi.seed":"\nrandom.array.chi.seed\n    Pseudorandom number generator seed.\n","random.array.chi.seedLength":"\nrandom.array.chi.seedLength\n    Length of generator seed.\n","random.array.chi.state":"\nrandom.array.chi.state\n    Generator state.\n","random.array.chi.stateLength":"\nrandom.array.chi.stateLength\n    Length of generator state.\n","random.array.chi.byteLength":"\nrandom.array.chi.byteLength\n    Size (in bytes) of generator state.\n","random.array.chisquare":"\nrandom.array.chisquare( len:integer, k:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a chi-square\n    distribution.\n","random.array.chisquare.assign":"\nrandom.array.chisquare.assign( k:number, out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a chi-square\n    distribution.\n","random.array.chisquare.factory":"\nrandom.array.chisquare.factory( [k:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a chi-square distribution.\n","random.array.chisquare.PRNG":"\nrandom.array.chisquare.PRNG\n    Underlying pseudorandom number generator.\n","random.array.chisquare.seed":"\nrandom.array.chisquare.seed\n    Pseudorandom number generator seed.\n","random.array.chisquare.seedLength":"\nrandom.array.chisquare.seedLength\n    Length of generator seed.\n","random.array.chisquare.state":"\nrandom.array.chisquare.state\n    Generator state.\n","random.array.chisquare.stateLength":"\nrandom.array.chisquare.stateLength\n    Length of generator state.\n","random.array.chisquare.byteLength":"\nrandom.array.chisquare.byteLength\n    Size (in bytes) of generator state.\n","random.array.cosine":"\nrandom.array.cosine( len:integer, mu:number, s:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a raised cosine\n    distribution.\n","random.array.cosine.assign":"\nrandom.array.cosine.assign( mu:number, s:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a raised cosine\n    distribution.\n","random.array.cosine.factory":"\nrandom.array.cosine.factory( [mu:number, s:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a raised cosine distribution.\n","random.array.cosine.PRNG":"\nrandom.array.cosine.PRNG\n    Underlying pseudorandom number generator.\n","random.array.cosine.seed":"\nrandom.array.cosine.seed\n    Pseudorandom number generator seed.\n","random.array.cosine.seedLength":"\nrandom.array.cosine.seedLength\n    Length of generator seed.\n","random.array.cosine.state":"\nrandom.array.cosine.state\n    Generator state.\n","random.array.cosine.stateLength":"\nrandom.array.cosine.stateLength\n    Length of generator state.\n","random.array.cosine.byteLength":"\nrandom.array.cosine.byteLength\n    Size (in bytes) of generator state.\n","random.array.discreteUniform":"\nrandom.array.discreteUniform( len:integer, a:number, b:number[, \n  options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a discrete\n    uniform distribution.\n","random.array.discreteUniform.assign":"\nrandom.array.discreteUniform.assign( a:number, b:number, out:Array|TypedArray )\n    Fills an array with pseudorandom numbers drawn from a discrete uniform\n    distribution.\n","random.array.discreteUniform.factory":"\nrandom.array.discreteUniform.factory( [a:number, b:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a discrete uniform distribution.\n","random.array.discreteUniform.PRNG":"\nrandom.array.discreteUniform.PRNG\n    Underlying pseudorandom number generator.\n","random.array.discreteUniform.seed":"\nrandom.array.discreteUniform.seed\n    Pseudorandom number generator seed.\n","random.array.discreteUniform.seedLength":"\nrandom.array.discreteUniform.seedLength\n    Length of generator seed.\n","random.array.discreteUniform.state":"\nrandom.array.discreteUniform.state\n    Generator state.\n","random.array.discreteUniform.stateLength":"\nrandom.array.discreteUniform.stateLength\n    Length of generator state.\n","random.array.discreteUniform.byteLength":"\nrandom.array.discreteUniform.byteLength\n    Size (in bytes) of generator state.\n","random.array.erlang":"\nrandom.array.erlang( len:integer, k:number, lambda:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from an Erlang\n    distribution.\n","random.array.erlang.assign":"\nrandom.array.erlang.assign( k:number, lambda:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from an Erlang distribution.\n","random.array.erlang.factory":"\nrandom.array.erlang.factory( [k:number, lambda:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an Erlang distribution.\n","random.array.erlang.PRNG":"\nrandom.array.erlang.PRNG\n    Underlying pseudorandom number generator.\n","random.array.erlang.seed":"\nrandom.array.erlang.seed\n    Pseudorandom number generator seed.\n","random.array.erlang.seedLength":"\nrandom.array.erlang.seedLength\n    Length of generator seed.\n","random.array.erlang.state":"\nrandom.array.erlang.state\n    Generator state.\n","random.array.erlang.stateLength":"\nrandom.array.erlang.stateLength\n    Length of generator state.\n","random.array.erlang.byteLength":"\nrandom.array.erlang.byteLength\n    Size (in bytes) of generator state.\n","random.array.exponential":"\nrandom.array.exponential( len:integer, lambda:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from an exponential\n    distribution.\n","random.array.exponential.assign":"\nrandom.array.exponential.assign( lambda:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from an exponential\n    distribution.\n","random.array.exponential.factory":"\nrandom.array.exponential.factory( [lambda:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an exponential distribution.\n","random.array.exponential.PRNG":"\nrandom.array.exponential.PRNG\n    Underlying pseudorandom number generator.\n","random.array.exponential.seed":"\nrandom.array.exponential.seed\n    Pseudorandom number generator seed.\n","random.array.exponential.seedLength":"\nrandom.array.exponential.seedLength\n    Length of generator seed.\n","random.array.exponential.state":"\nrandom.array.exponential.state\n    Generator state.\n","random.array.exponential.stateLength":"\nrandom.array.exponential.stateLength\n    Length of generator state.\n","random.array.exponential.byteLength":"\nrandom.array.exponential.byteLength\n    Size (in bytes) of generator state.\n","random.array.f":"\nrandom.array.f( len:integer, d1:number, d2:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from an F\n    distribution.\n","random.array.f.assign":"\nrandom.array.f.assign( d1:number, d2:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from an F distribution.\n","random.array.f.factory":"\nrandom.array.f.factory( [d1:number, d2:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an F distribution.\n","random.array.f.PRNG":"\nrandom.array.f.PRNG\n    Underlying pseudorandom number generator.\n","random.array.f.seed":"\nrandom.array.f.seed\n    Pseudorandom number generator seed.\n","random.array.f.seedLength":"\nrandom.array.f.seedLength\n    Length of generator seed.\n","random.array.f.state":"\nrandom.array.f.state\n    Generator state.\n","random.array.f.stateLength":"\nrandom.array.f.stateLength\n    Length of generator state.\n","random.array.f.byteLength":"\nrandom.array.f.byteLength\n    Size (in bytes) of generator state.\n","random.array.frechet":"\nrandom.array.frechet( len:integer, alpha:number, s:number, m:number[, \n  options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a Fréchet\n    distribution.\n","random.array.frechet.assign":"\nrandom.array.frechet.assign( alpha:number, s:number, m:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a Fréchet distribution.\n","random.array.frechet.factory":"\nrandom.array.frechet.factory( [alpha:number, s:number, m:number, ]\n  [options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Fréchet distribution.\n","random.array.frechet.PRNG":"\nrandom.array.frechet.PRNG\n    Underlying pseudorandom number generator.\n","random.array.frechet.seed":"\nrandom.array.frechet.seed\n    Pseudorandom number generator seed.\n","random.array.frechet.seedLength":"\nrandom.array.frechet.seedLength\n    Length of generator seed.\n","random.array.frechet.state":"\nrandom.array.frechet.state\n    Generator state.\n","random.array.frechet.stateLength":"\nrandom.array.frechet.stateLength\n    Length of generator state.\n","random.array.frechet.byteLength":"\nrandom.array.frechet.byteLength\n    Size (in bytes) of generator state.\n","random.array.gamma":"\nrandom.array.gamma( len:integer, alpha:number, beta:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a gamma\n    distribution.\n","random.array.gamma.assign":"\nrandom.array.gamma.assign( alpha:number, beta:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a gamma distribution.\n","random.array.gamma.factory":"\nrandom.array.gamma.factory( [alpha:number, beta:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a gamma distribution.\n","random.array.gamma.PRNG":"\nrandom.array.gamma.PRNG\n    Underlying pseudorandom number generator.\n","random.array.gamma.seed":"\nrandom.array.gamma.seed\n    Pseudorandom number generator seed.\n","random.array.gamma.seedLength":"\nrandom.array.gamma.seedLength\n    Length of generator seed.\n","random.array.gamma.state":"\nrandom.array.gamma.state\n    Generator state.\n","random.array.gamma.stateLength":"\nrandom.array.gamma.stateLength\n    Length of generator state.\n","random.array.gamma.byteLength":"\nrandom.array.gamma.byteLength\n    Size (in bytes) of generator state.\n","random.array.geometric":"\nrandom.array.geometric( len:integer, p:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a geometric\n    distribution.\n","random.array.geometric.assign":"\nrandom.array.geometric.assign( p:number, out:Array|TypedArray )\n    Fills an array with pseudorandom numbers drawn from a geometric\n    distribution.\n","random.array.geometric.factory":"\nrandom.array.geometric.factory( [p:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a geometric distribution.\n","random.array.geometric.PRNG":"\nrandom.array.geometric.PRNG\n    Underlying pseudorandom number generator.\n","random.array.geometric.seed":"\nrandom.array.geometric.seed\n    Pseudorandom number generator seed.\n","random.array.geometric.seedLength":"\nrandom.array.geometric.seedLength\n    Length of generator seed.\n","random.array.geometric.state":"\nrandom.array.geometric.state\n    Generator state.\n","random.array.geometric.stateLength":"\nrandom.array.geometric.stateLength\n    Length of generator state.\n","random.array.geometric.byteLength":"\nrandom.array.geometric.byteLength\n    Size (in bytes) of generator state.\n","random.array.gumbel":"\nrandom.array.gumbel( len:integer, mu:number, beta:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a Gumbel\n    distribution.\n","random.array.gumbel.assign":"\nrandom.array.gumbel.assign( mu:number, beta:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a Gumbel distribution.\n","random.array.gumbel.factory":"\nrandom.array.gumbel.factory( [mu:number, beta:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Gumbel distribution.\n","random.array.gumbel.PRNG":"\nrandom.array.gumbel.PRNG\n    Underlying pseudorandom number generator.\n","random.array.gumbel.seed":"\nrandom.array.gumbel.seed\n    Pseudorandom number generator seed.\n","random.array.gumbel.seedLength":"\nrandom.array.gumbel.seedLength\n    Length of generator seed.\n","random.array.gumbel.state":"\nrandom.array.gumbel.state\n    Generator state.\n","random.array.gumbel.stateLength":"\nrandom.array.gumbel.stateLength\n    Length of generator state.\n","random.array.gumbel.byteLength":"\nrandom.array.gumbel.byteLength\n    Size (in bytes) of generator state.\n","random.array.hypergeometric":"\nrandom.array.hypergeometric( len:integer, N:number, K:number, n:number[, \n  options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a hypergeometric\n    distribution.\n","random.array.hypergeometric.assign":"\nrandom.array.hypergeometric.assign( N:number, K:number, n:number, \n  out:Array|TypedArray )\n    Fills an array with pseudorandom numbers drawn from a hypergeometric\n    distribution.\n","random.array.hypergeometric.factory":"\nrandom.array.hypergeometric.factory( [N:number, K:number, n:number, ]\n  [options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a hypergeometric distribution.\n","random.array.hypergeometric.PRNG":"\nrandom.array.hypergeometric.PRNG\n    Underlying pseudorandom number generator.\n","random.array.hypergeometric.seed":"\nrandom.array.hypergeometric.seed\n    Pseudorandom number generator seed.\n","random.array.hypergeometric.seedLength":"\nrandom.array.hypergeometric.seedLength\n    Length of generator seed.\n","random.array.hypergeometric.state":"\nrandom.array.hypergeometric.state\n    Generator state.\n","random.array.hypergeometric.stateLength":"\nrandom.array.hypergeometric.stateLength\n    Length of generator state.\n","random.array.hypergeometric.byteLength":"\nrandom.array.hypergeometric.byteLength\n    Size (in bytes) of generator state.\n","random.array.invgamma":"\nrandom.array.invgamma( len:integer, alpha:number, beta:number[, \n  options:Object] )\n    Returns an array containing pseudorandom numbers drawn from an inverse gamma\n    distribution.\n","random.array.invgamma.assign":"\nrandom.array.invgamma.assign( alpha:number, beta:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from an inverse gamma\n    distribution.\n","random.array.invgamma.factory":"\nrandom.array.invgamma.factory( [alpha:number, beta:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from an inverse gamma distribution.\n","random.array.invgamma.PRNG":"\nrandom.array.invgamma.PRNG\n    Underlying pseudorandom number generator.\n","random.array.invgamma.seed":"\nrandom.array.invgamma.seed\n    Pseudorandom number generator seed.\n","random.array.invgamma.seedLength":"\nrandom.array.invgamma.seedLength\n    Length of generator seed.\n","random.array.invgamma.state":"\nrandom.array.invgamma.state\n    Generator state.\n","random.array.invgamma.stateLength":"\nrandom.array.invgamma.stateLength\n    Length of generator state.\n","random.array.invgamma.byteLength":"\nrandom.array.invgamma.byteLength\n    Size (in bytes) of generator state.\n","random.array.kumaraswamy":"\nrandom.array.kumaraswamy( len:integer, a:number, b:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from Kumaraswamy's\n    double bounded distribution.\n","random.array.kumaraswamy.assign":"\nrandom.array.kumaraswamy.assign( a:number, b:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from Kumaraswamy's double\n    bounded distribution.\n","random.array.kumaraswamy.factory":"\nrandom.array.kumaraswamy.factory( [a:number, b:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from Kumaraswamy's double bounded distribution.\n","random.array.kumaraswamy.PRNG":"\nrandom.array.kumaraswamy.PRNG\n    Underlying pseudorandom number generator.\n","random.array.kumaraswamy.seed":"\nrandom.array.kumaraswamy.seed\n    Pseudorandom number generator seed.\n","random.array.kumaraswamy.seedLength":"\nrandom.array.kumaraswamy.seedLength\n    Length of generator seed.\n","random.array.kumaraswamy.state":"\nrandom.array.kumaraswamy.state\n    Generator state.\n","random.array.kumaraswamy.stateLength":"\nrandom.array.kumaraswamy.stateLength\n    Length of generator state.\n","random.array.kumaraswamy.byteLength":"\nrandom.array.kumaraswamy.byteLength\n    Size (in bytes) of generator state.\n","random.array.laplace":"\nrandom.array.laplace( len:integer, mu:number, b:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a Laplace\n    (double exponential) distribution.\n","random.array.laplace.assign":"\nrandom.array.laplace.assign( mu:number, b:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a Laplace (double\n    exponential) distribution.\n","random.array.laplace.factory":"\nrandom.array.laplace.factory( [mu:number, b:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Laplace (double exponential) distribution.\n","random.array.laplace.PRNG":"\nrandom.array.laplace.PRNG\n    Underlying pseudorandom number generator.\n","random.array.laplace.seed":"\nrandom.array.laplace.seed\n    Pseudorandom number generator seed.\n","random.array.laplace.seedLength":"\nrandom.array.laplace.seedLength\n    Length of generator seed.\n","random.array.laplace.state":"\nrandom.array.laplace.state\n    Generator state.\n","random.array.laplace.stateLength":"\nrandom.array.laplace.stateLength\n    Length of generator state.\n","random.array.laplace.byteLength":"\nrandom.array.laplace.byteLength\n    Size (in bytes) of generator state.\n","random.array.levy":"\nrandom.array.levy( len:integer, mu:number, c:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a Lévy\n    distribution.\n","random.array.levy.assign":"\nrandom.array.levy.assign( mu:number, c:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a Lévy distribution.\n","random.array.levy.factory":"\nrandom.array.levy.factory( [mu:number, c:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Lévy distribution.\n","random.array.levy.PRNG":"\nrandom.array.levy.PRNG\n    Underlying pseudorandom number generator.\n","random.array.levy.seed":"\nrandom.array.levy.seed\n    Pseudorandom number generator seed.\n","random.array.levy.seedLength":"\nrandom.array.levy.seedLength\n    Length of generator seed.\n","random.array.levy.state":"\nrandom.array.levy.state\n    Generator state.\n","random.array.levy.stateLength":"\nrandom.array.levy.stateLength\n    Length of generator state.\n","random.array.levy.byteLength":"\nrandom.array.levy.byteLength\n    Size (in bytes) of generator state.\n","random.array.logistic":"\nrandom.array.logistic( len:integer, mu:number, s:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a logistic\n    distribution.\n","random.array.logistic.assign":"\nrandom.array.logistic.assign( mu:number, s:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a logistic distribution.\n","random.array.logistic.factory":"\nrandom.array.logistic.factory( [mu:number, s:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a logistic distribution.\n","random.array.logistic.PRNG":"\nrandom.array.logistic.PRNG\n    Underlying pseudorandom number generator.\n","random.array.logistic.seed":"\nrandom.array.logistic.seed\n    Pseudorandom number generator seed.\n","random.array.logistic.seedLength":"\nrandom.array.logistic.seedLength\n    Length of generator seed.\n","random.array.logistic.state":"\nrandom.array.logistic.state\n    Generator state.\n","random.array.logistic.stateLength":"\nrandom.array.logistic.stateLength\n    Length of generator state.\n","random.array.logistic.byteLength":"\nrandom.array.logistic.byteLength\n    Size (in bytes) of generator state.\n","random.array.lognormal":"\nrandom.array.lognormal( len:integer, mu:number, sigma:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a lognormal\n    distribution.\n","random.array.lognormal.assign":"\nrandom.array.lognormal.assign( mu:number, sigma:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a lognormal\n    distribution.\n","random.array.lognormal.factory":"\nrandom.array.lognormal.factory( [mu:number, sigma:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a lognormal distribution.\n","random.array.lognormal.PRNG":"\nrandom.array.lognormal.PRNG\n    Underlying pseudorandom number generator.\n","random.array.lognormal.seed":"\nrandom.array.lognormal.seed\n    Pseudorandom number generator seed.\n","random.array.lognormal.seedLength":"\nrandom.array.lognormal.seedLength\n    Length of generator seed.\n","random.array.lognormal.state":"\nrandom.array.lognormal.state\n    Generator state.\n","random.array.lognormal.stateLength":"\nrandom.array.lognormal.stateLength\n    Length of generator state.\n","random.array.lognormal.byteLength":"\nrandom.array.lognormal.byteLength\n    Size (in bytes) of generator state.\n","random.array.minstd":"\nrandom.array.minstd( len:integer[, options:Object] )\n    Returns an array containing pseudorandom integers on the interval\n    `[1, 2147483646]`.\n","random.array.minstd.normalized":"\nrandom.array.minstd.normalized( len:integer[, options:Object] )\n    Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n","random.array.minstd.factory":"\nrandom.array.minstd.factory( [options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers\n    generated using a linear congruential pseudorandom number generator (LCG).\n","random.array.minstd.PRNG":"\nrandom.array.minstd.PRNG\n    Underlying pseudorandom number generator.\n","random.array.minstd.seed":"\nrandom.array.minstd.seed\n    Pseudorandom number generator seed.\n","random.array.minstd.seedLength":"\nrandom.array.minstd.seedLength\n    Length of generator seed.\n","random.array.minstd.state":"\nrandom.array.minstd.state\n    Generator state.\n","random.array.minstd.stateLength":"\nrandom.array.minstd.stateLength\n    Length of generator state.\n","random.array.minstd.byteLength":"\nrandom.array.minstd.byteLength\n    Size (in bytes) of generator state.\n","random.array.minstdShuffle":"\nrandom.array.minstdShuffle( len:integer[, options:Object] )\n    Returns an array containing pseudorandom integers on the interval\n    `[1, 2147483646]`.\n","random.array.minstdShuffle.normalized":"\nrandom.array.minstdShuffle.normalized( len:integer[, options:Object] )\n    Returns an array containing pseudorandom numbers on the interval `[0, 1)`.\n","random.array.minstdShuffle.factory":"\nrandom.array.minstdShuffle.factory( [options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers\n    generated using a linear congruential pseudorandom number generator (LCG)\n    whose output is shuffled.\n","random.array.minstdShuffle.PRNG":"\nrandom.array.minstdShuffle.PRNG\n    Underlying pseudorandom number generator.\n","random.array.minstdShuffle.seed":"\nrandom.array.minstdShuffle.seed\n    Pseudorandom number generator seed.\n","random.array.minstdShuffle.seedLength":"\nrandom.array.minstdShuffle.seedLength\n    Length of generator seed.\n","random.array.minstdShuffle.state":"\nrandom.array.minstdShuffle.state\n    Generator state.\n","random.array.minstdShuffle.stateLength":"\nrandom.array.minstdShuffle.stateLength\n    Length of generator state.\n","random.array.minstdShuffle.byteLength":"\nrandom.array.minstdShuffle.byteLength\n    Size (in bytes) of generator state.\n","random.array.mt19937":"\nrandom.array.mt19937( len:integer[, options:Object] )\n    Returns an array containing pseudorandom integers on the interval\n    `[0, 4294967295]`.\n","random.array.mt19937.normalized":"\nrandom.array.mt19937.normalized( len:integer[, options:Object] )\n    Returns an array containing pseudorandom numbers on the interval `[0, 1)`\n    with 53-bit precision.\n","random.array.mt19937.factory":"\nrandom.array.mt19937.factory( [options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers\n    generated using a 32-bit Mersenne Twister pseudorandom number generator.\n","random.array.mt19937.PRNG":"\nrandom.array.mt19937.PRNG\n    Underlying pseudorandom number generator.\n","random.array.mt19937.seed":"\nrandom.array.mt19937.seed\n    Pseudorandom number generator seed.\n","random.array.mt19937.seedLength":"\nrandom.array.mt19937.seedLength\n    Length of generator seed.\n","random.array.mt19937.state":"\nrandom.array.mt19937.state\n    Generator state.\n","random.array.mt19937.stateLength":"\nrandom.array.mt19937.stateLength\n    Length of generator state.\n","random.array.mt19937.byteLength":"\nrandom.array.mt19937.byteLength\n    Size (in bytes) of generator state.\n","random.array.negativeBinomial":"\nrandom.array.negativeBinomial( len:integer, r:number, p:number[, \n  options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a negative\n    binomial distribution.\n","random.array.negativeBinomial.assign":"\nrandom.array.negativeBinomial.assign( r:number, p:number, out:Array|TypedArray )\n    Fills an array with pseudorandom numbers drawn from a negative binomial\n    distribution.\n","random.array.negativeBinomial.factory":"\nrandom.array.negativeBinomial.factory( [r:number, p:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a negative binomial distribution.\n","random.array.negativeBinomial.PRNG":"\nrandom.array.negativeBinomial.PRNG\n    Underlying pseudorandom number generator.\n","random.array.negativeBinomial.seed":"\nrandom.array.negativeBinomial.seed\n    Pseudorandom number generator seed.\n","random.array.negativeBinomial.seedLength":"\nrandom.array.negativeBinomial.seedLength\n    Length of generator seed.\n","random.array.negativeBinomial.state":"\nrandom.array.negativeBinomial.state\n    Generator state.\n","random.array.negativeBinomial.stateLength":"\nrandom.array.negativeBinomial.stateLength\n    Length of generator state.\n","random.array.negativeBinomial.byteLength":"\nrandom.array.negativeBinomial.byteLength\n    Size (in bytes) of generator state.\n","random.array.normal":"\nrandom.array.normal( len:integer, mu:number, sigma:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a normal\n    distribution.\n","random.array.normal.assign":"\nrandom.array.normal.assign( mu:number, sigma:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a normal distribution.\n","random.array.normal.factory":"\nrandom.array.normal.factory( [mu:number, sigma:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a normal distribution.\n","random.array.normal.PRNG":"\nrandom.array.normal.PRNG\n    Underlying pseudorandom number generator.\n","random.array.normal.seed":"\nrandom.array.normal.seed\n    Pseudorandom number generator seed.\n","random.array.normal.seedLength":"\nrandom.array.normal.seedLength\n    Length of generator seed.\n","random.array.normal.state":"\nrandom.array.normal.state\n    Generator state.\n","random.array.normal.stateLength":"\nrandom.array.normal.stateLength\n    Length of generator state.\n","random.array.normal.byteLength":"\nrandom.array.normal.byteLength\n    Size (in bytes) of generator state.\n","random.array.pareto1":"\nrandom.array.pareto1( len:integer, alpha:number, beta:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a Pareto (Type\n    I) distribution.\n","random.array.pareto1.assign":"\nrandom.array.pareto1.assign( alpha:number, beta:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a Pareto (Type I)\n    distribution.\n","random.array.pareto1.factory":"\nrandom.array.pareto1.factory( [alpha:number, beta:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Pareto (Type I) distribution.\n","random.array.pareto1.PRNG":"\nrandom.array.pareto1.PRNG\n    Underlying pseudorandom number generator.\n","random.array.pareto1.seed":"\nrandom.array.pareto1.seed\n    Pseudorandom number generator seed.\n","random.array.pareto1.seedLength":"\nrandom.array.pareto1.seedLength\n    Length of generator seed.\n","random.array.pareto1.state":"\nrandom.array.pareto1.state\n    Generator state.\n","random.array.pareto1.stateLength":"\nrandom.array.pareto1.stateLength\n    Length of generator state.\n","random.array.pareto1.byteLength":"\nrandom.array.pareto1.byteLength\n    Size (in bytes) of generator state.\n","random.array.poisson":"\nrandom.array.poisson( len:integer, lambda:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a Poisson\n    distribution.\n","random.array.poisson.assign":"\nrandom.array.poisson.assign( lambda:number, out:Array|TypedArray )\n    Fills an array with pseudorandom numbers drawn from a Poisson distribution.\n","random.array.poisson.factory":"\nrandom.array.poisson.factory( [lambda:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Poisson distribution.\n","random.array.poisson.PRNG":"\nrandom.array.poisson.PRNG\n    Underlying pseudorandom number generator.\n","random.array.poisson.seed":"\nrandom.array.poisson.seed\n    Pseudorandom number generator seed.\n","random.array.poisson.seedLength":"\nrandom.array.poisson.seedLength\n    Length of generator seed.\n","random.array.poisson.state":"\nrandom.array.poisson.state\n    Generator state.\n","random.array.poisson.stateLength":"\nrandom.array.poisson.stateLength\n    Length of generator state.\n","random.array.poisson.byteLength":"\nrandom.array.poisson.byteLength\n    Size (in bytes) of generator state.\n","random.array.randu":"\nrandom.array.randu( len:integer[, options:Object] )\n    Returns an array containing uniformly distributed pseudorandom numbers\n    between 0 and 1.\n","random.array.randu.factory":"\nrandom.array.randu.factory( [options:Object] )\n    Returns a function for creating arrays containing uniformly distributed\n    pseudorandom numbers between 0 and 1.\n","random.array.randu.PRNG":"\nrandom.array.randu.PRNG\n    Underlying pseudorandom number generator.\n","random.array.randu.seed":"\nrandom.array.randu.seed\n    Pseudorandom number generator seed.\n","random.array.randu.seedLength":"\nrandom.array.randu.seedLength\n    Length of generator seed.\n","random.array.randu.state":"\nrandom.array.randu.state\n    Generator state.\n","random.array.randu.stateLength":"\nrandom.array.randu.stateLength\n    Length of generator state.\n","random.array.randu.byteLength":"\nrandom.array.randu.byteLength\n    Size (in bytes) of generator state.\n","random.array.rayleigh":"\nrandom.array.rayleigh( len:integer, sigma:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a Rayleigh\n    distribution.\n","random.array.rayleigh.assign":"\nrandom.array.rayleigh.assign( sigma:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a Rayleigh distribution.\n","random.array.rayleigh.factory":"\nrandom.array.rayleigh.factory( [sigma:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Rayleigh distribution.\n","random.array.rayleigh.PRNG":"\nrandom.array.rayleigh.PRNG\n    Underlying pseudorandom number generator.\n","random.array.rayleigh.seed":"\nrandom.array.rayleigh.seed\n    Pseudorandom number generator seed.\n","random.array.rayleigh.seedLength":"\nrandom.array.rayleigh.seedLength\n    Length of generator seed.\n","random.array.rayleigh.state":"\nrandom.array.rayleigh.state\n    Generator state.\n","random.array.rayleigh.stateLength":"\nrandom.array.rayleigh.stateLength\n    Length of generator state.\n","random.array.rayleigh.byteLength":"\nrandom.array.rayleigh.byteLength\n    Size (in bytes) of generator state.\n","random.array.t":"\nrandom.array.t( len:integer, v:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a Student's t\n    distribution.\n","random.array.t.assign":"\nrandom.array.t.assign( v:number, out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a Student's t\n    distribution.\n","random.array.t.factory":"\nrandom.array.t.factory( [v:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Student's t distribution.\n","random.array.t.PRNG":"\nrandom.array.t.PRNG\n    Underlying pseudorandom number generator.\n","random.array.t.seed":"\nrandom.array.t.seed\n    Pseudorandom number generator seed.\n","random.array.t.seedLength":"\nrandom.array.t.seedLength\n    Length of generator seed.\n","random.array.t.state":"\nrandom.array.t.state\n    Generator state.\n","random.array.t.stateLength":"\nrandom.array.t.stateLength\n    Length of generator state.\n","random.array.t.byteLength":"\nrandom.array.t.byteLength\n    Size (in bytes) of generator state.\n","random.array.triangular":"\nrandom.array.triangular( len:integer, a:number, b:number, c:number[, \n  options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a triangular\n    distribution.\n","random.array.triangular.assign":"\nrandom.array.triangular.assign( a:number, b:number, c:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a triangular\n    distribution.\n","random.array.triangular.factory":"\nrandom.array.triangular.factory( [a:number, b:number, c:number, ]\n  [options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a triangular distribution.\n","random.array.triangular.PRNG":"\nrandom.array.triangular.PRNG\n    Underlying pseudorandom number generator.\n","random.array.triangular.seed":"\nrandom.array.triangular.seed\n    Pseudorandom number generator seed.\n","random.array.triangular.seedLength":"\nrandom.array.triangular.seedLength\n    Length of generator seed.\n","random.array.triangular.state":"\nrandom.array.triangular.state\n    Generator state.\n","random.array.triangular.stateLength":"\nrandom.array.triangular.stateLength\n    Length of generator state.\n","random.array.triangular.byteLength":"\nrandom.array.triangular.byteLength\n    Size (in bytes) of generator state.\n","random.array.uniform":"\nrandom.array.uniform( len:integer, a:number, b:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a continuous\n    uniform distribution.\n","random.array.uniform.assign":"\nrandom.array.uniform.assign( a:number, b:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a continuous uniform\n    distribution.\n","random.array.uniform.factory":"\nrandom.array.uniform.factory( [a:number, b:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a continuous uniform distribution.\n","random.array.uniform.PRNG":"\nrandom.array.uniform.PRNG\n    Underlying pseudorandom number generator.\n","random.array.uniform.seed":"\nrandom.array.uniform.seed\n    Pseudorandom number generator seed.\n","random.array.uniform.seedLength":"\nrandom.array.uniform.seedLength\n    Length of generator seed.\n","random.array.uniform.state":"\nrandom.array.uniform.state\n    Generator state.\n","random.array.uniform.stateLength":"\nrandom.array.uniform.stateLength\n    Length of generator state.\n","random.array.uniform.byteLength":"\nrandom.array.uniform.byteLength\n    Size (in bytes) of generator state.\n","random.array.weibull":"\nrandom.array.weibull( len:integer, k:number, lambda:number[, options:Object] )\n    Returns an array containing pseudorandom numbers drawn from a Weibull\n    distribution.\n","random.array.weibull.assign":"\nrandom.array.weibull.assign( k:number, lambda:number, \n  out:Array|Float64Array|Float32Array )\n    Fills an array with pseudorandom numbers drawn from a Weibull distribution.\n","random.array.weibull.factory":"\nrandom.array.weibull.factory( [k:number, lambda:number, ][options:Object] )\n    Returns a function for creating arrays containing pseudorandom numbers drawn\n    from a Weibull distribution.\n","random.array.weibull.PRNG":"\nrandom.array.weibull.PRNG\n    Underlying pseudorandom number generator.\n","random.array.weibull.seed":"\nrandom.array.weibull.seed\n    Pseudorandom number generator seed.\n","random.array.weibull.seedLength":"\nrandom.array.weibull.seedLength\n    Length of generator seed.\n","random.array.weibull.state":"\nrandom.array.weibull.state\n    Generator state.\n","random.array.weibull.stateLength":"\nrandom.array.weibull.stateLength\n    Length of generator state.\n","random.array.weibull.byteLength":"\nrandom.array.weibull.byteLength\n    Size (in bytes) of generator state.\n","random.iterators.arcsine":"\nrandom.iterators.arcsine( a:number, b:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from an\n    arcsine distribution.\n","random.iterators.bernoulli":"\nrandom.iterators.bernoulli( p:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Bernoulli distribution.\n","random.iterators.beta":"\nrandom.iterators.beta( α:number, β:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    beta distribution.\n","random.iterators.betaprime":"\nrandom.iterators.betaprime( α:number, β:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    beta prime distribution.\n","random.iterators.binomial":"\nrandom.iterators.binomial( n:integer, p:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    binomial distribution.\n","random.iterators.boxMuller":"\nrandom.iterators.boxMuller( [options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    standard normal distribution using the Box-Muller transform.\n","random.iterators.cauchy":"\nrandom.iterators.cauchy( x0:number, Ɣ:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Cauchy distribution.\n","random.iterators.chi":"\nrandom.iterators.chi( k:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a chi\n    distribution.\n","random.iterators.chisquare":"\nrandom.iterators.chisquare( k:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    chi-square distribution.\n","random.iterators.cosine":"\nrandom.iterators.cosine( μ:number, s:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a raised\n    cosine distribution.\n","random.iterators.discreteUniform":"\nrandom.iterators.discreteUniform( a:integer, b:integer[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    discrete uniform distribution.\n","random.iterators.erlang":"\nrandom.iterators.erlang( k:integer, λ:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from an Erlang\n    distribution.\n","random.iterators.exponential":"\nrandom.iterators.exponential( λ:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from an\n    exponential distribution.\n","random.iterators.f":"\nrandom.iterators.f( d1:number, d2:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from an F\n    distribution.\n","random.iterators.frechet":"\nrandom.iterators.frechet( α:number, s:number, m:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Fréchet\n    distribution.\n","random.iterators.gamma":"\nrandom.iterators.gamma( α:number, β:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a gamma\n    distribution.\n","random.iterators.geometric":"\nrandom.iterators.geometric( p:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    geometric distribution.\n","random.iterators.gumbel":"\nrandom.iterators.gumbel( μ:number, β:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Gumbel\n    distribution.\n","random.iterators.hypergeometric":"\nrandom.iterators.hypergeometric( N:integer, K:integer, n:integer[, \n  options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    hypergeometric distribution.\n","random.iterators.improvedZiggurat":"\nrandom.iterators.improvedZiggurat( [options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    standard normal distribution using the Improved Ziggurat algorithm.\n","random.iterators.invgamma":"\nrandom.iterators.invgamma( α:number, β:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from an\n    inverse gamma distribution.\n","random.iterators.kumaraswamy":"\nrandom.iterators.kumaraswamy( a:number, b:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Kumaraswamy's double bounded distribution.\n","random.iterators.laplace":"\nrandom.iterators.laplace( μ:number, b:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Laplace\n    (double exponential) distribution.\n","random.iterators.levy":"\nrandom.iterators.levy( μ:number, c:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Lévy\n    distribution.\n","random.iterators.logistic":"\nrandom.iterators.logistic( μ:number, s:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    logistic distribution.\n","random.iterators.lognormal":"\nrandom.iterators.lognormal( μ:number, σ:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    lognormal distribution.\n","random.iterators.minstd":"\nrandom.iterators.minstd( [options:Object] )\n    Returns an iterator for generating pseudorandom integers on the interval\n    `[1, 2147483646]`.\n","random.iterators.minstdShuffle":"\nrandom.iterators.minstdShuffle( [options:Object] )\n    Returns an iterator for generating pseudorandom integers on the interval\n    `[1, 2147483646]`.\n","random.iterators.mt19937":"\nrandom.iterators.mt19937( [options:Object] )\n    Returns an iterator for generating pseudorandom integers on the interval\n    `[1, 4294967295]`.\n","random.iterators.negativeBinomial":"\nrandom.iterators.negativeBinomial( r:number, p:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    negative binomial distribution.\n","random.iterators.normal":"\nrandom.iterators.normal( μ:number, σ:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a normal\n    distribution.\n","random.iterators.pareto1":"\nrandom.iterators.pareto1( α:number, β:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Pareto\n    (Type I) distribution.\n","random.iterators.poisson":"\nrandom.iterators.poisson( λ:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a Poisson\n    distribution.\n","random.iterators.randi":"\nrandom.iterators.randi( [options:Object] )\n    Create an iterator for generating pseudorandom numbers having integer\n    values.\n","random.iterators.randn":"\nrandom.iterators.randn( [options:Object] )\n    Create an iterator for generating pseudorandom numbers drawn from a standard\n    normal distribution.\n","random.iterators.randu":"\nrandom.iterators.randu( [options:Object] )\n    Create an iterator for generating uniformly distributed pseudorandom numbers\n    between 0 and 1.\n","random.iterators.rayleigh":"\nrandom.iterators.rayleigh( σ:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Rayleigh distribution.\n","random.iterators.t":"\nrandom.iterators.t( v:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Student's t distribution.\n","random.iterators.triangular":"\nrandom.iterators.triangular( a:number, b:number, c:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    triangular distribution.\n","random.iterators.uniform":"\nrandom.iterators.uniform( a:number, b:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    continuous uniform distribution.\n","random.iterators.weibull":"\nrandom.iterators.weibull( k:number, λ:number[, options:Object] )\n    Returns an iterator for generating pseudorandom numbers drawn from a\n    Weibull distribution.\n","random.streams.arcsine":"\nrandom.streams.arcsine( a:number, b:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from an\n    arcsine distribution.\n","random.streams.arcsine.factory":"\nrandom.streams.arcsine.factory( [a:number, b:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an arcsine distribution.\n","random.streams.arcsine.objectMode":"\nrandom.streams.arcsine.objectMode( a:number, b:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an arcsine distribution.\n","random.streams.bernoulli":"\nrandom.streams.bernoulli( p:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Bernoulli distribution.\n","random.streams.bernoulli.factory":"\nrandom.streams.bernoulli.factory( [p:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Bernoulli distribution.\n","random.streams.bernoulli.objectMode":"\nrandom.streams.bernoulli.objectMode( p:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Bernoulli distribution.\n","random.streams.beta":"\nrandom.streams.beta( α:number, β:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    beta distribution.\n","random.streams.beta.factory":"\nrandom.streams.beta.factory( [α:number, β:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a beta distribution.\n","random.streams.beta.objectMode":"\nrandom.streams.beta.objectMode( α:number, β:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a beta distribution.\n","random.streams.betaprime":"\nrandom.streams.betaprime( α:number, β:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    beta prime distribution.\n","random.streams.betaprime.factory":"\nrandom.streams.betaprime.factory( [α:number, β:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a beta prime distribution.\n","random.streams.betaprime.objectMode":"\nrandom.streams.betaprime.objectMode( α:number, β:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a beta prime distribution.\n","random.streams.binomial":"\nrandom.streams.binomial( n:integer, p:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    binomial distribution.\n","random.streams.binomial.factory":"\nrandom.streams.binomial.factory( [n:integer, p:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a binomial distribution.\n","random.streams.binomial.objectMode":"\nrandom.streams.binomial.objectMode( n:integer, p:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a binomial distribution.\n","random.streams.boxMuller":"\nrandom.streams.boxMuller( [options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    standard normal distribution using the Box-Muller transform.\n","random.streams.boxMuller.factory":"\nrandom.streams.boxMuller.factory( [options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a standard normal distribution using the Box-Muller\n    transform.\n","random.streams.boxMuller.objectMode":"\nrandom.streams.boxMuller.objectMode( [options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a standard normal distribution using the Box-Muller transform.\n","random.streams.cauchy":"\nrandom.streams.cauchy( x0:number, γ:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Cauchy distribution.\n","random.streams.cauchy.factory":"\nrandom.streams.cauchy.factory( [x0:number, γ:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Cauchy distribution.\n","random.streams.cauchy.objectMode":"\nrandom.streams.cauchy.objectMode( x0:number, γ:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Cauchy distribution.\n","random.streams.chi":"\nrandom.streams.chi( k:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    chi distribution.\n","random.streams.chi.factory":"\nrandom.streams.chi.factory( [k:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a chi distribution.\n","random.streams.chi.objectMode":"\nrandom.streams.chi.objectMode( k:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a chi distribution.\n","random.streams.chisquare":"\nrandom.streams.chisquare( k:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    chi-square distribution.\n","random.streams.chisquare.factory":"\nrandom.streams.chisquare.factory( [k:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a chi-square distribution.\n","random.streams.chisquare.objectMode":"\nrandom.streams.chisquare.objectMode( k:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a chi-square distribution.\n","random.streams.cosine":"\nrandom.streams.cosine( μ:number, s:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    raised cosine distribution.\n","random.streams.cosine.factory":"\nrandom.streams.cosine.factory( [μ:number, s:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a raised cosine distribution.\n","random.streams.cosine.objectMode":"\nrandom.streams.cosine.objectMode( μ:number, s:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a raised cosine distribution.\n","random.streams.discreteUniform":"\nrandom.streams.discreteUniform( a:integer, b:integer[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    discrete uniform distribution.\n","random.streams.discreteUniform.factory":"\nrandom.streams.discreteUniform.factory( [a:integer, b:integer, ]\n  [options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a discrete uniform distribution.\n","random.streams.discreteUniform.objectMode":"\nrandom.streams.discreteUniform.objectMode( a:integer, b:integer[, \n  options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a discrete uniform distribution.\n","random.streams.erlang":"\nrandom.streams.erlang( k:integer, λ:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from an\n    Erlang distribution.\n","random.streams.erlang.factory":"\nrandom.streams.erlang.factory( [k:number, λ:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an Erlang distribution.\n","random.streams.erlang.objectMode":"\nrandom.streams.erlang.objectMode( k:number, λ:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an Erlang distribution.\n","random.streams.exponential":"\nrandom.streams.exponential( λ:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from an\n    exponential distribution.\n","random.streams.exponential.factory":"\nrandom.streams.exponential.factory( [λ:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an exponential distribution.\n","random.streams.exponential.objectMode":"\nrandom.streams.exponential.objectMode( λ:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an exponential distribution.\n","random.streams.f":"\nrandom.streams.f( d1:number, d2:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from an\n    F distribution.\n","random.streams.f.factory":"\nrandom.streams.f.factory( [d1:number, d2:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an F distribution.\n","random.streams.f.objectMode":"\nrandom.streams.f.objectMode( d1:number, d2:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an F distribution.\n","random.streams.frechet":"\nrandom.streams.frechet( α:number, s:number, m:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Fréchet distribution.\n","random.streams.frechet.factory":"\nrandom.streams.frechet.factory( [α:number, s:number, m:number,]\n  [options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Fréchet distribution.\n","random.streams.frechet.objectMode":"\nrandom.streams.frechet.objectMode( α:number, s:number, m:number[, \n  options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Fréchet distribution.\n","random.streams.gamma":"\nrandom.streams.gamma( α:number, β:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    gamma distribution.\n","random.streams.gamma.factory":"\nrandom.streams.gamma.factory( [α:number, β:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a gamma distribution.\n","random.streams.gamma.objectMode":"\nrandom.streams.gamma.objectMode( α:number, β:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a gamma distribution.\n","random.streams.geometric":"\nrandom.streams.geometric( p:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    geometric distribution.\n","random.streams.geometric.factory":"\nrandom.streams.geometric.factory( [p:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a geometric distribution.\n","random.streams.geometric.objectMode":"\nrandom.streams.geometric.objectMode( p:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a geometric distribution.\n","random.streams.gumbel":"\nrandom.streams.gumbel( μ:number, β:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Gumbel distribution.\n","random.streams.gumbel.factory":"\nrandom.streams.gumbel.factory( [μ:number, β:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Gumbel distribution.\n","random.streams.gumbel.objectMode":"\nrandom.streams.gumbel.objectMode( μ:number, β:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Gumbel distribution.\n","random.streams.hypergeometric":"\nrandom.streams.hypergeometric( N:integer, K:integer, n:integer[, \n  options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    hypergeometric distribution.\n","random.streams.hypergeometric.factory":"\nrandom.streams.hypergeometric.factory( [N:integer, K:integer, n:integer,]\n  [options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a hypergeometric distribution.\n","random.streams.hypergeometric.objectMode":"\nrandom.streams.hypergeometric.objectMode( N:integer, K:integer, n:integer[, \n  options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a hypergeometric distribution.\n","random.streams.improvedZiggurat":"\nrandom.streams.improvedZiggurat( [options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    standard normal distribution using the Improved Ziggurat algorithm.\n","random.streams.improvedZiggurat.factory":"\nrandom.streams.improvedZiggurat.factory( [options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a standard normal distribution using the Improved\n    Ziggurat algorithm.\n","random.streams.improvedZiggurat.objectMode":"\nrandom.streams.improvedZiggurat.objectMode( [options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a standard normal distribution using the Improved Ziggurat\n    algorithm.\n","random.streams.invgamma":"\nrandom.streams.invgamma( α:number, β:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from an\n    inverse gamma distribution.\n","random.streams.invgamma.factory":"\nrandom.streams.invgamma.factory( [α:number, β:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from an inverse gamma distribution.\n","random.streams.invgamma.objectMode":"\nrandom.streams.invgamma.objectMode( α:number, β:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from an inverse gamma distribution.\n","random.streams.kumaraswamy":"\nrandom.streams.kumaraswamy( a:number, b:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Kumaraswamy's double bounded distribution.\n","random.streams.kumaraswamy.factory":"\nrandom.streams.kumaraswamy.factory( [a:number, b:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Kumaraswamy's double bounded distribution.\n","random.streams.kumaraswamy.objectMode":"\nrandom.streams.kumaraswamy.objectMode( a:number, b:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Kumaraswamy's double bounded distribution.\n","random.streams.laplace":"\nrandom.streams.laplace( μ:number, b:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Laplace (double exponential) distribution.\n","random.streams.laplace.factory":"\nrandom.streams.laplace.factory( [μ:number, b:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Laplace (double exponential) distribution.\n","random.streams.laplace.objectMode":"\nrandom.streams.laplace.objectMode( μ:number, b:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Laplace (double exponential) distribution.\n","random.streams.levy":"\nrandom.streams.levy( μ:number, c:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Lévy distribution.\n","random.streams.levy.factory":"\nrandom.streams.levy.factory( [μ:number, c:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Lévy distribution.\n","random.streams.levy.objectMode":"\nrandom.streams.levy.objectMode( μ:number, c:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Lévy distribution.\n","random.streams.logistic":"\nrandom.streams.logistic( μ:number, s:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    logistic distribution.\n","random.streams.logistic.factory":"\nrandom.streams.logistic.factory( [μ:number, s:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a logistic distribution.\n","random.streams.logistic.objectMode":"\nrandom.streams.logistic.objectMode( μ:number, s:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a logistic distribution.\n","random.streams.lognormal":"\nrandom.streams.lognormal( μ:number, σ:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    lognormal distribution.\n","random.streams.lognormal.factory":"\nrandom.streams.lognormal.factory( [μ:number, σ:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a lognormal distribution.\n","random.streams.lognormal.objectMode":"\nrandom.streams.lognormal.objectMode( μ:number, σ:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a lognormal distribution.\n","random.streams.minstd":"\nrandom.streams.minstd( [options:Object] )\n    Returns a readable stream for generating pseudorandom numbers on the\n    interval `[1, 2147483646]`.\n","random.streams.minstd.factory":"\nrandom.streams.minstd.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers on the interval `[1, 2147483646]`.\n","random.streams.minstd.objectMode":"\nrandom.streams.minstd.objectMode( [options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    on the interval `[1, 2147483646]`.\n","random.streams.minstdShuffle":"\nrandom.streams.minstdShuffle( [options:Object] )\n    Returns a readable stream for generating pseudorandom numbers on the\n    interval `[1, 2147483646]`.\n","random.streams.minstdShuffle.factory":"\nrandom.streams.minstdShuffle.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers on the interval `[1, 2147483646]`.\n","random.streams.minstdShuffle.objectMode":"\nrandom.streams.minstdShuffle.objectMode( [options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    on the interval `[1, 2147483646]`.\n","random.streams.mt19937":"\nrandom.streams.mt19937( [options:Object] )\n    Returns a readable stream for generating pseudorandom numbers on the\n    interval `[1, 4294967295]`.\n","random.streams.mt19937.factory":"\nrandom.streams.mt19937.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers on the interval `[1, 4294967295]`.\n","random.streams.mt19937.objectMode":"\nrandom.streams.mt19937.objectMode( [options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    on the interval `[1, 4294967295]`.\n","random.streams.negativeBinomial":"\nrandom.streams.negativeBinomial( r:number, p:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    negative binomial distribution.\n","random.streams.negativeBinomial.factory":"\nrandom.streams.negativeBinomial.factory( [r:number, p:number, ]\n  [options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a negative binomial distribution.\n","random.streams.negativeBinomial.objectMode":"\nrandom.streams.negativeBinomial.objectMode( r:integer, p:number[, \n  options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a negative binomial distribution.\n","random.streams.normal":"\nrandom.streams.normal( μ:number, σ:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    normal distribution.\n","random.streams.normal.factory":"\nrandom.streams.normal.factory( [μ:number, σ:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a normal distribution.\n","random.streams.normal.objectMode":"\nrandom.streams.normal.objectMode( μ:number, σ:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a normal distribution.\n","random.streams.pareto1":"\nrandom.streams.pareto1( α:number, β:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Pareto (Type I) distribution.\n","random.streams.pareto1.factory":"\nrandom.streams.pareto1.factory( [α:number, β:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Pareto (Type I) distribution.\n","random.streams.pareto1.objectMode":"\nrandom.streams.pareto1.objectMode( α:number, β:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Pareto (Type I) distribution.\n","random.streams.poisson":"\nrandom.streams.poisson( λ:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Poisson distribution.\n","random.streams.poisson.factory":"\nrandom.streams.poisson.factory( [λ:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Poisson distribution.\n","random.streams.poisson.objectMode":"\nrandom.streams.poisson.objectMode( λ:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Poisson distribution.\n","random.streams.randi":"\nrandom.streams.randi( [options:Object] )\n    Returns a readable stream for generating pseudorandom numbers having integer\n    values.\n","random.streams.randi.factory":"\nrandom.streams.randi.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers having integer values.\n","random.streams.randi.objectMode":"\nrandom.streams.randi.objectMode( [options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    having integer values.\n","random.streams.randn":"\nrandom.streams.randn( [options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    standard normal distribution.\n","random.streams.randn.factory":"\nrandom.streams.randn.factory( [options] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a standard normal distribution.\n","random.streams.randn.objectMode":"\nrandom.streams.randn.objectMode( [options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a standard normal distribution.\n","random.streams.randu":"\nrandom.streams.randu( [options:Object] )\n    Returns a readable stream for generating uniformly distributed pseudorandom\n    numbers between 0 and 1.\n","random.streams.randu.factory":"\nrandom.streams.randu.factory( [options] )\n    Returns a function for creating readable streams which generate uniformly\n    distributed pseudorandom numbers between 0 and 1.\n","random.streams.randu.objectMode":"\nrandom.streams.randu.objectMode( [options:Object] )\n    Returns an \"objectMode\" readable stream for generating uniformly distributed\n    pseudorandom numbers between 0 and 1.\n","random.streams.rayleigh":"\nrandom.streams.rayleigh( σ:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Rayleigh distribution.\n","random.streams.rayleigh.factory":"\nrandom.streams.rayleigh.factory( [σ:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Rayleigh distribution.\n","random.streams.rayleigh.objectMode":"\nrandom.streams.rayleigh.objectMode( σ:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Rayleigh distribution.\n","random.streams.t":"\nrandom.streams.t( v:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Student's t distribution.\n","random.streams.t.factory":"\nrandom.streams.t.factory( [v:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Student's t distribution.\n","random.streams.t.objectMode":"\nrandom.streams.t.objectMode( v:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Student's t distribution.\n","random.streams.triangular":"\nrandom.streams.triangular( a:number, b:number, c:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    triangular distribution.\n","random.streams.triangular.factory":"\nrandom.streams.triangular.factory( [a:number, b:number, c:number, ]\n  [options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a triangular distribution.\n","random.streams.triangular.objectMode":"\nrandom.streams.triangular.objectMode( a:number, b:number, c:number[, \n  options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a triangular distribution.\n","random.streams.uniform":"\nrandom.streams.uniform( a:number, b:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    uniform distribution.\n","random.streams.uniform.factory":"\nrandom.streams.uniform.factory( [a:number, b:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a uniform distribution.\n","random.streams.uniform.objectMode":"\nrandom.streams.uniform.objectMode( a:number, b:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a uniform distribution.\n","random.streams.weibull":"\nrandom.streams.weibull( k:number, λ:number[, options:Object] )\n    Returns a readable stream for generating pseudorandom numbers drawn from a\n    Weibull distribution.\n","random.streams.weibull.factory":"\nrandom.streams.weibull.factory( [k:number, λ:number, ][options:Object] )\n    Returns a function for creating readable streams which generate pseudorandom\n    numbers drawn from a Weibull distribution.\n","random.streams.weibull.objectMode":"\nrandom.streams.weibull.objectMode( k:number, λ:number[, options:Object] )\n    Returns an \"objectMode\" readable stream for generating pseudorandom numbers\n    drawn from a Weibull distribution.\n","random.strided.arcsine":"\nrandom.strided.arcsine( N:integer, a:ArrayLikeObject, sa:integer, \n  b:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from an arcsine\n    distribution.\n","random.strided.arcsine.ndarray":"\nrandom.strided.arcsine.ndarray( N:integer, a:ArrayLikeObject, sa:integer, \n  oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, \n  so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from an arcsine\n    distribution using alternative indexing semantics.\n","random.strided.bernoulli":"\nrandom.strided.bernoulli( N:integer, p:ArrayLikeObject, sp:integer, \n  out:ArrayLikeObject, so:integer )\n    Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n    distribution.\n","random.strided.bernoulli.ndarray":"\nrandom.strided.bernoulli.ndarray( N:integer, p:ArrayLikeObject, sp:integer, \n  op:integer, out:ArrayLikeObject, so:integer, oo:integer )\n    Fills a strided array with pseudorandom numbers drawn from a Bernoulli\n    distribution using alternative indexing semantics.\n","random.strided.bernoulli.factory":"\nrandom.strided.bernoulli.factory( [options:Object] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Bernoulli distribution.\n","random.strided.bernoulli.PRNG":"\nrandom.strided.bernoulli.PRNG\n    Underlying pseudorandom number generator.\n","random.strided.bernoulli.seed":"\nrandom.strided.bernoulli.seed\n    Pseudorandom number generator seed.\n","random.strided.bernoulli.seedLength":"\nrandom.strided.bernoulli.seedLength\n    Length of generator seed.\n","random.strided.bernoulli.state":"\nrandom.strided.bernoulli.state\n    Generator state.\n","random.strided.bernoulli.stateLength":"\nrandom.strided.bernoulli.stateLength\n    Length of generator state.\n","random.strided.bernoulli.byteLength":"\nrandom.strided.bernoulli.byteLength\n    Size (in bytes) of generator state.\n","random.strided.beta":"\nrandom.strided.beta( N:integer, alpha:ArrayLikeObject, sa:integer, \n  beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a beta\n    distribution.\n","random.strided.beta.ndarray":"\nrandom.strided.beta.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n  oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n  out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a beta\n    distribution using alternative indexing semantics.\n","random.strided.betaprime":"\nrandom.strided.betaprime( N:integer, alpha:ArrayLikeObject, sa:integer, \n  beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a beta prime\n    distribution.\n","random.strided.betaprime.ndarray":"\nrandom.strided.betaprime.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n  oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n  out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a beta prime\n    distribution using alternative indexing semantics.\n","random.strided.chi":"\nrandom.strided.chi( N:integer, k:ArrayLikeObject, sk:integer, \n  out:ArrayLikeObject, so:integer )\n    Fills a strided array with pseudorandom numbers drawn from a chi\n    distribution.\n","random.strided.chi.ndarray":"\nrandom.strided.chi.ndarray( N:integer, k:ArrayLikeObject, sk:integer, \n  ok:integer, out:ArrayLikeObject, so:integer, oo:integer )\n    Fills a strided array with pseudorandom numbers drawn from a chi\n    distribution using alternative indexing semantics.\n","random.strided.chi.factory":"\nrandom.strided.chi.factory( [options:Object] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a chi distribution.\n","random.strided.chi.PRNG":"\nrandom.strided.chi.PRNG\n    Underlying pseudorandom number generator.\n","random.strided.chi.seed":"\nrandom.strided.chi.seed\n    Pseudorandom number generator seed.\n","random.strided.chi.seedLength":"\nrandom.strided.chi.seedLength\n    Length of generator seed.\n","random.strided.chi.state":"\nrandom.strided.chi.state\n    Generator state.\n","random.strided.chi.stateLength":"\nrandom.strided.chi.stateLength\n    Length of generator state.\n","random.strided.chi.byteLength":"\nrandom.strided.chi.byteLength\n    Size (in bytes) of generator state.\n","random.strided.chisquare":"\nrandom.strided.chisquare( N:integer, k:ArrayLikeObject, sk:integer, \n  out:ArrayLikeObject, so:integer )\n    Fills a strided array with pseudorandom numbers drawn from a chi-square\n    distribution.\n","random.strided.chisquare.ndarray":"\nrandom.strided.chisquare.ndarray( N:integer, k:ArrayLikeObject, sk:integer, \n  ok:integer, out:ArrayLikeObject, so:integer, oo:integer )\n    Fills a strided array with pseudorandom numbers drawn from a chi-square\n    distribution using alternative indexing semantics.\n","random.strided.chisquare.factory":"\nrandom.strided.chisquare.factory( [options:Object] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a chi-square distribution.\n","random.strided.chisquare.PRNG":"\nrandom.strided.chisquare.PRNG\n    Underlying pseudorandom number generator.\n","random.strided.chisquare.seed":"\nrandom.strided.chisquare.seed\n    Pseudorandom number generator seed.\n","random.strided.chisquare.seedLength":"\nrandom.strided.chisquare.seedLength\n    Length of generator seed.\n","random.strided.chisquare.state":"\nrandom.strided.chisquare.state\n    Generator state.\n","random.strided.chisquare.stateLength":"\nrandom.strided.chisquare.stateLength\n    Length of generator state.\n","random.strided.chisquare.byteLength":"\nrandom.strided.chisquare.byteLength\n    Size (in bytes) of generator state.\n","random.strided.cosine":"\nrandom.strided.cosine( N:integer, mu:ArrayLikeObject, sm:integer, \n  s:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a cosine\n    distribution.\n","random.strided.cosine.ndarray":"\nrandom.strided.cosine.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, \n  om:integer, s:ArrayLikeObject, ss:integer, os:integer, out:ArrayLikeObject, \n  so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a cosine\n    distribution using alternative indexing semantics.\n","random.strided.discreteUniform":"\nrandom.strided.discreteUniform( N:integer, a:ArrayLikeObject, sa:integer, \n  b:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a discrete\n    uniform distribution.\n","random.strided.discreteUniform.ndarray":"\nrandom.strided.discreteUniform.ndarray( N:integer, a:ArrayLikeObject, \n  sa:integer, oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, \n  out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a discrete\n    uniform distribution using alternative indexing semantics.\n","random.strided.exponential":"\nrandom.strided.exponential( N:integer, lambda:ArrayLikeObject, sl:integer, \n  out:ArrayLikeObject, so:integer )\n    Fills a strided array with pseudorandom numbers drawn from an exponential\n    distribution.\n","random.strided.exponential.ndarray":"\nrandom.strided.exponential.ndarray( N:integer, lambda:ArrayLikeObject, \n  sl:integer, ol:integer, out:ArrayLikeObject, so:integer, oo:integer )\n    Fills a strided array with pseudorandom numbers drawn from an exponential\n    distribution using alternative indexing semantics.\n","random.strided.exponential.factory":"\nrandom.strided.exponential.factory( [options:Object] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from an exponential distribution.\n","random.strided.exponential.PRNG":"\nrandom.strided.exponential.PRNG\n    Underlying pseudorandom number generator.\n","random.strided.exponential.seed":"\nrandom.strided.exponential.seed\n    Pseudorandom number generator seed.\n","random.strided.exponential.seedLength":"\nrandom.strided.exponential.seedLength\n    Length of generator seed.\n","random.strided.exponential.state":"\nrandom.strided.exponential.state\n    Generator state.\n","random.strided.exponential.stateLength":"\nrandom.strided.exponential.stateLength\n    Length of generator state.\n","random.strided.exponential.byteLength":"\nrandom.strided.exponential.byteLength\n    Size (in bytes) of generator state.\n","random.strided.gamma":"\nrandom.strided.gamma( N:integer, alpha:ArrayLikeObject, sa:integer, \n  beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a gamma\n    distribution.\n","random.strided.gamma.ndarray":"\nrandom.strided.gamma.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n  oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n  out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a gamma\n    distribution using alternative indexing semantics.\n","random.strided.geometric":"\nrandom.strided.geometric( N:integer, p:ArrayLikeObject, sp:integer, \n  out:ArrayLikeObject, so:integer )\n    Fills a strided array with pseudorandom numbers drawn from a geometric\n    distribution.\n","random.strided.geometric.ndarray":"\nrandom.strided.geometric.ndarray( N:integer, p:ArrayLikeObject, sp:integer, \n  op:integer, out:ArrayLikeObject, so:integer, oo:integer )\n    Fills a strided array with pseudorandom numbers drawn from a geometric\n    distribution using alternative indexing semantics.\n","random.strided.geometric.factory":"\nrandom.strided.geometric.factory( [options:Object] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a geometric distribution.\n","random.strided.geometric.PRNG":"\nrandom.strided.geometric.PRNG\n    Underlying pseudorandom number generator.\n","random.strided.geometric.seed":"\nrandom.strided.geometric.seed\n    Pseudorandom number generator seed.\n","random.strided.geometric.seedLength":"\nrandom.strided.geometric.seedLength\n    Length of generator seed.\n","random.strided.geometric.state":"\nrandom.strided.geometric.state\n    Generator state.\n","random.strided.geometric.stateLength":"\nrandom.strided.geometric.stateLength\n    Length of generator state.\n","random.strided.geometric.byteLength":"\nrandom.strided.geometric.byteLength\n    Size (in bytes) of generator state.\n","random.strided.invgamma":"\nrandom.strided.invgamma( N:integer, alpha:ArrayLikeObject, sa:integer, \n  beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n    distribution.\n","random.strided.invgamma.ndarray":"\nrandom.strided.invgamma.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, \n  oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, \n  out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from an inverse gamma\n    distribution using alternative indexing semantics.\n","random.strided.lognormal":"\nrandom.strided.lognormal( N:integer, mu:ArrayLikeObject, sm:integer, \n  sigma:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a lognormal\n    distribution.\n","random.strided.lognormal.ndarray":"\nrandom.strided.lognormal.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, \n  om:integer, sigma:ArrayLikeObject, ss:integer, os:integer, \n  out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a lognormal\n    distribution using alternative indexing semantics.\n","random.strided.minstd":"\nrandom.strided.minstd( N:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom integers between 1 and 2147483646\n    (inclusive).\n","random.strided.minstd.ndarray":"\nrandom.strided.minstd.ndarray( N:integer, out:ArrayLikeObject, so:integer, \n  oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom integers between 1 and 2147483646\n    (inclusive) using alternative indexing semantics.\n","random.strided.minstd.normalized":"\nrandom.strided.minstd.normalized( N:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers between 0 and 1.\n","random.strided.minstd.normalized.ndarray":"\nrandom.strided.minstd.normalized.ndarray( N:integer, out:ArrayLikeObject, \n  so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers between 0 and 1 using\n    alternative indexing semantics.\n","random.strided.minstdShuffle":"\nrandom.strided.minstdShuffle( N:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom integers between 1 and 2147483646\n    (inclusive).\n","random.strided.minstdShuffle.ndarray":"\nrandom.strided.minstdShuffle.ndarray( N:integer, out:ArrayLikeObject, \n  so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom integers between 1 and 2147483646\n    (inclusive) using alternative indexing semantics.\n","random.strided.minstdShuffle.normalized":"\nrandom.strided.minstdShuffle.normalized( N:integer, out:ArrayLikeObject, \n  so:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers between 0 and 1.\n","random.strided.minstdShuffle.normalized.ndarray":"\nrandom.strided.minstdShuffle.normalized.ndarray( N:integer, \n  out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers between 0 and 1 using\n    alternative indexing semantics.\n","random.strided.mt19937":"\nrandom.strided.mt19937( N:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom integers between 0 and 4294967295\n    (inclusive).\n","random.strided.mt19937.ndarray":"\nrandom.strided.mt19937.ndarray( N:integer, out:ArrayLikeObject, so:integer, \n  oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom integers between 0 and 4294967295\n    (inclusive) using alternative indexing semantics.\n","random.strided.mt19937.normalized":"\nrandom.strided.mt19937.normalized( N:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers between 0 and 1.\n","random.strided.mt19937.normalized.ndarray":"\nrandom.strided.mt19937.normalized.ndarray( N:integer, out:ArrayLikeObject, \n  so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers between 0 and 1 using\n    alternative indexing semantics.\n","random.strided.normal":"\nrandom.strided.normal( N:integer, mu:ArrayLikeObject, sm:integer, \n  sigma:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a normal\n    distribution.\n","random.strided.normal.ndarray":"\nrandom.strided.normal.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, \n  om:integer, sigma:ArrayLikeObject, ss:integer, os:integer, \n  out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a normal\n    distribution using alternative indexing semantics.\n","random.strided.poisson":"\nrandom.strided.poisson( N:integer, lambda:ArrayLikeObject, sl:integer, \n  out:ArrayLikeObject, so:integer )\n    Fills a strided array with pseudorandom numbers drawn from a Poisson\n    distribution.\n","random.strided.poisson.ndarray":"\nrandom.strided.poisson.ndarray( N:integer, lambda:ArrayLikeObject, sl:integer, \n  ol:integer, out:ArrayLikeObject, so:integer, oo:integer )\n    Fills a strided array with pseudorandom numbers drawn from a Poisson\n    distribution using alternative indexing semantics.\n","random.strided.poisson.factory":"\nrandom.strided.poisson.factory( [options:Object] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Poisson distribution.\n","random.strided.poisson.PRNG":"\nrandom.strided.poisson.PRNG\n    Underlying pseudorandom number generator.\n","random.strided.poisson.seed":"\nrandom.strided.poisson.seed\n    Pseudorandom number generator seed.\n","random.strided.poisson.seedLength":"\nrandom.strided.poisson.seedLength\n    Length of generator seed.\n","random.strided.poisson.state":"\nrandom.strided.poisson.state\n    Generator state.\n","random.strided.poisson.stateLength":"\nrandom.strided.poisson.stateLength\n    Length of generator state.\n","random.strided.poisson.byteLength":"\nrandom.strided.poisson.byteLength\n    Size (in bytes) of generator state.\n","random.strided.randu":"\nrandom.strided.randu( N:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with uniformly distributed pseudorandom numbers\n    between 0 and 1.\n","random.strided.randu.ndarray":"\nrandom.strided.randu.ndarray( N:integer, out:ArrayLikeObject, so:integer, \n  oo:integer[, options:Object] )\n    Fills a strided array with uniformly distributed pseudorandom numbers\n    between 0 and 1 using alternative indexing semantics.\n","random.strided.rayleigh":"\nrandom.strided.rayleigh( N:integer, sigma:ArrayLikeObject, ss:integer, \n  out:ArrayLikeObject, so:integer )\n    Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n    distribution.\n","random.strided.rayleigh.ndarray":"\nrandom.strided.rayleigh.ndarray( N:integer, sigma:ArrayLikeObject, ss:integer, \n  os:integer, out:ArrayLikeObject, so:integer, oo:integer )\n    Fills a strided array with pseudorandom numbers drawn from a Rayleigh\n    distribution using alternative indexing semantics.\n","random.strided.rayleigh.factory":"\nrandom.strided.rayleigh.factory( [options:Object] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Rayleigh distribution.\n","random.strided.rayleigh.PRNG":"\nrandom.strided.rayleigh.PRNG\n    Underlying pseudorandom number generator.\n","random.strided.rayleigh.seed":"\nrandom.strided.rayleigh.seed\n    Pseudorandom number generator seed.\n","random.strided.rayleigh.seedLength":"\nrandom.strided.rayleigh.seedLength\n    Length of generator seed.\n","random.strided.rayleigh.state":"\nrandom.strided.rayleigh.state\n    Generator state.\n","random.strided.rayleigh.stateLength":"\nrandom.strided.rayleigh.stateLength\n    Length of generator state.\n","random.strided.rayleigh.byteLength":"\nrandom.strided.rayleigh.byteLength\n    Size (in bytes) of generator state.\n","random.strided.t":"\nrandom.strided.t( N:integer, v:ArrayLikeObject, sv:integer, \n  out:ArrayLikeObject, so:integer )\n    Fills a strided array with pseudorandom numbers drawn from a Student's t-\n    distribution.\n","random.strided.t.ndarray":"\nrandom.strided.t.ndarray( N:integer, v:ArrayLikeObject, sv:integer, ov:integer, \n  out:ArrayLikeObject, so:integer, oo:integer )\n    Fills a strided array with pseudorandom numbers drawn from a Student's t-\n    distribution using alternative indexing semantics.\n","random.strided.t.factory":"\nrandom.strided.t.factory( [options:Object] )\n    Returns a function for filling strided arrays with pseudorandom numbers\n    drawn from a Student's t-distribution.\n","random.strided.t.PRNG":"\nrandom.strided.t.PRNG\n    Underlying pseudorandom number generator.\n","random.strided.t.seed":"\nrandom.strided.t.seed\n    Pseudorandom number generator seed.\n","random.strided.t.seedLength":"\nrandom.strided.t.seedLength\n    Length of generator seed.\n","random.strided.t.state":"\nrandom.strided.t.state\n    Generator state.\n","random.strided.t.stateLength":"\nrandom.strided.t.stateLength\n    Length of generator state.\n","random.strided.t.byteLength":"\nrandom.strided.t.byteLength\n    Size (in bytes) of generator state.\n","random.strided.uniform":"\nrandom.strided.uniform( N:integer, a:ArrayLikeObject, sa:integer, \n  b:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a continuous\n    uniform distribution.\n","random.strided.uniform.ndarray":"\nrandom.strided.uniform.ndarray( N:integer, a:ArrayLikeObject, sa:integer, \n  oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, \n  so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a continuous\n    uniform distribution using alternative indexing semantics.\n","random.strided.weibull":"\nrandom.strided.weibull( N:integer, k:ArrayLikeObject, sk:integer, \n  lambda:ArrayLikeObject, sl:integer, out:ArrayLikeObject, so:integer[, \n  options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a Weibull\n    distribution.\n","random.strided.weibull.ndarray":"\nrandom.strided.weibull.ndarray( N:integer, k:ArrayLikeObject, sk:integer, \n  ok:integer, lambda:ArrayLikeObject, sl:integer, ol:integer, \n  out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )\n    Fills a strided array with pseudorandom numbers drawn from a Weibull\n    distribution using alternative indexing semantics.\n","ranks":"\nranks( arr:Array<number>[, options:Object] )\n    Computes the sample ranks for the values of an array-like object.\n","readDir":"\nreadDir( path:string|Buffer, clbk:Function )\n    Asynchronously reads the contents of a directory.\n","readDir.sync":"\nreadDir.sync( path:string|Buffer )\n    Synchronously reads the contents of a directory.\n","readFile":"\nreadFile( file:string|Buffer|integer[, options:Object|string], clbk:Function )\n    Asynchronously reads the entire contents of a file.\n","readFile.sync":"\nreadFile.sync( file:string|Buffer|integer[, options:Object|string] )\n    Synchronously reads the entire contents of a file.\n","readFileList":"\nreadFileList( filepaths:Array<string>[, options:Object|string], clbk:Function )\n    Asynchronously reads the entire contents of each file in a file list.\n","readFileList.sync":"\nreadFileList.sync( filepaths:Array<string>[, options:Object|string] )\n    Synchronously reads the entire contents of each file in a file list.\n","readJSON":"\nreadJSON( file:string|Buffer|integer[, options:Object|string], clbk:Function )\n    Asynchronously reads a file as JSON.\n","readJSON.sync":"\nreadJSON.sync( file:string|Buffer|integer[, options:Object|string] )\n    Synchronously reads a file as JSON.\n","readWASM":"\nreadWASM( file:string|Buffer|integer[, options:Object], clbk:Function )\n    Asynchronously reads a file as WebAssembly.\n","readWASM.sync":"\nreadWASM.sync( file:string|Buffer|integer[, options:Object] )\n    Synchronously reads a file as WebAssembly.\n","real":"\nreal( z:Complex128 )\n    Returns the real component of a double-precision complex floating-point\n    number.\n","realarray":"\nrealarray( [dtype:string] )\n    Creates a typed array.\n\nrealarray( length:integer[, dtype:string] )\n    Returns a typed array having a specified length.\n\nrealarray( typedarray:TypedArray[, dtype:string] )\n    Creates a typed array from another typed array.\n\nrealarray( obj:Object[, dtype:string] )\n    Creates a typed array from an array-like object or iterable.\n\nrealarray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n  dtype:string] )\n    Returns a typed array view of an ArrayBuffer.\n","realarrayCtors":"\nrealarrayCtors( dtype:string )\n    Returns a typed array constructor.\n","realarrayDataTypes":"\nrealarrayDataTypes()\n    Returns a list of typed array real-valued data types.\n","realf":"\nrealf( z:Complex64 )\n    Returns the real component of a single-precision complex floating-point\n    number.\n","realmax":"\nrealmax( dtype:string )\n    Returns the maximum finite value capable of being represented by a numeric\n    real type.\n","realmin":"\nrealmin( dtype:string )\n    Returns the smallest positive normal value capable of being represented by a\n    numeric real type.\n","reBasename":"\nreBasename( [platform:string] )\n    Returns a regular expression to capture the last part of a path.\n","reBasename.REGEXP":"\nreBasename.REGEXP\n    Regular expression to capture the last part of a POSIX path.\n","reBasename.REGEXP_POSIX":"\nreBasename.REGEXP_POSIX\n    Regular expression to capture the last part of a POSIX path.\n","reBasename.REGEXP_WIN32":"\nreBasename.REGEXP_WIN32\n    Regular expression to capture the last part of a Windows path.\n","reBasenamePosix":"\nreBasenamePosix()\n    Returns a regular expression to capture the last part of a POSIX path.\n","reBasenamePosix.REGEXP":"\nreBasenamePosix.REGEXP\n    Regular expression to capture the last part of a POSIX path.\n","reBasenameWindows":"\nreBasenameWindows()\n    Returns a regular expression to capture the last part of a Windows path.\n","reBasenameWindows.REGEXP":"\nreBasenameWindows.REGEXP\n    Regular expression to capture the last part of a Windows path.\n","reColorHexadecimal":"\nreColorHexadecimal( [mode:string] )\n    Returns a regular expression to match a hexadecimal color.\n","reColorHexadecimal.REGEXP":"\nreColorHexadecimal.REGEXP\n    Regular expression to match a full hexadecimal color.\n","reColorHexadecimal.REGEXP_SHORTHAND":"\nreColorHexadecimal.REGEXP_SHORTHAND\n    Regular expression to match a shorthand hexadecimal color.\n","reColorHexadecimal.REGEXP_EITHER":"\nreColorHexadecimal.REGEXP_EITHER\n    Regular expression to match either a shorthand or full length hexadecimal\n    color.\n","reDecimalNumber":"\nreDecimalNumber( [options:Object] )\n    Returns a regular expression to match a decimal number.\n","reDecimalNumber.REGEXP":"\nreDecimalNumber.REGEXP\n    Regular expression to match a decimal number.\n","reDecimalNumber.REGEXP_CAPTURE":"\nreDecimalNumber.REGEXP_CAPTURE\n    Regular expression to capture a decimal number.\n","reDirname":"\nreDirname( [platform:string] )\n    Returns a regular expression to capture a path dirname.\n","reDirname.REGEXP":"\nreDirname.REGEXP\n    Regular expression to capture a path dirname.\n","reDirname.REGEXP_POSIX":"\nreDirname.REGEXP_POSIX\n    Regular expression to capture a POSIX path dirname.\n","reDirname.REGEXP_WIN32":"\nreDirname.REGEXP_WIN32\n    Regular expression to capture a Windows path dirname.\n","reDirnamePosix":"\nreDirnamePosix()\n    Returns a regular expression to capture a POSIX path dirname.\n","reDirnamePosix.REGEXP":"\nreDirnamePosix.REGEXP\n    Regular expression to capture a POSIX path dirname.\n","reDirnameWindows":"\nreDirnameWindows()\n    Returns a regular expression to capture a Windows path dirname.\n","reDirnameWindows.REGEXP":"\nreDirnameWindows.REGEXP\n    Regular expression to capture a Windows path dirname.\n","reduce":"\nreduce( arr:ArrayLikeObject|ndarray, initial:any, reducer:Function[, \n  thisArg:any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n","reduce2d":"\nreduce2d( arr:ArrayLikeObject<ArrayLikeObject>, initial:ArrayLikeObject, \n  reducer:Function[, thisArg:any] )\n    Reduces the number of dimensions by one of a two-dimensional nested array by\n    applying a function against an accumulator and each element along the\n    innermost dimension and returning the accumulation results as a one-\n    dimensional array.\n","reduceAsync":"\nreduceAsync( collection:Array|TypedArray|Object, initial:any, [options:Object,] \n  reducer:Function, done:Function )\n    Applies a function against an accumulator and each element in a collection\n    and returns the accumulated result.\n","reduceAsync.factory":"\nreduceAsync.factory( [options:Object,] fcn:Function )\n    Returns a function which applies a function against an accumulator and each\n    element in a collection and returns the accumulated result.\n","reduceRight":"\nreduceRight( arr:ArrayLikeObject|ndarray, initial:any, reducer:Function[, \n  thisArg:any] )\n    Applies a function against an accumulator and each element in an array while\n    iterating from right to left and returns the accumulated result.\n","reduceRightAsync":"\nreduceRightAsync( collection:Array|TypedArray|Object, initial:any, \n  [options:Object,] reducer:Function, done:Function )\n    Applies a function against an accumulator and each element in a collection\n    and returns the accumulated result, iterating from right to left.\n","reduceRightAsync.factory":"\nreduceRightAsync.factory( [options:Object,] fcn:Function )\n    Returns a function which applies a function against an accumulator and each\n    element in a collection and returns the accumulated result, iterating from\n    right to left.\n","reDurationString":"\nreDurationString()\n    Returns a regular expression to match a duration string.\n","reDurationString.REGEXP":"\nreDurationString.REGEXP\n    Regular expression to match a duration string.\n","reEOL":"\nreEOL( [options:Object] )\n    Regular expression to match a newline character sequence: /\\r?\\n/.\n","reEOL.REGEXP":"\nreEOL.REGEXP\n    Regular expression to match a newline character sequence: /\\r?\\n/.\n","reEOL.REGEXP_CAPTURE":"\nreEOL.REGEXP_CAPTURE\n    Regular expression to capture a newline character sequence: /\\r?\\n/.\n","reExtendedLengthPath":"\nreExtendedLengthPath()\n    Returns a regular expression to test if a string is an extended-length path.\n","reExtendedLengthPath.REGEXP":"\nreExtendedLengthPath.REGEXP\n    Regular expression to test if a string is an extended-length path.\n","reExtname":"\nreExtname( [platform:string] )\n    Returns a regular expression to capture a filename extension.\n","reExtname.REGEXP":"\nreExtname.REGEXP\n    Regular expression to capture a filename extension.\n","reExtname.REGEXP_POSIX":"\nreExtname.REGEXP_POSIX\n    Regular expression to capture a POSIX filename extension.\n","reExtname.REGEXP_WIN32":"\nreExtname.REGEXP_WIN32\n    Regular expression to capture a Windows filename extension.\n","reExtnamePosix":"\nreExtnamePosix\n    Returns a regular expression to capture a POSIX filename extension.\n","reExtnamePosix.REGEXP":"\nreExtnamePosix.REGEXP\n    Regular expression to capture a POSIX filename extension.\n","reExtnameWindows":"\nreExtnameWindows\n    Returns a regular expression to capture a Windows filename extension.\n","reExtnameWindows.REGEXP":"\nreExtnameWindows.REGEXP\n    Regular expression to capture a Windows filename extension.\n","reFilename":"\nreFilename( [platform:string] )\n    Regular expression to split a filename.\n","reFilename.REGEXP":"\nreFilename.REGEXP\n    Regular expression to split a filename.\n","reFilename.REGEXP_POSIX":"\nreFilename.REGEXP_POSIX\n    Regular expression to split a POSIX filename.\n","reFilename.REGEXP_WIN32":"\nreFilename.REGEXP_WIN32\n    Regular expression to split a Windows filename.\n","reFilenamePosix":"\nreFilenamePosix()\n    Returns a regular expression to split a POSIX filename.\n","reFilenamePosix.REGEXP":"\nreFilenamePosix.REGEXP\n    Regular expression to split a POSIX filename.\n","reFilenameWindows":"\nreFilenameWindows()\n    Returns a regular expression to split a Windows filename.\n","reFilenameWindows.REGEXP":"\nreFilenameWindows.REGEXP\n    Regular expression to split a Windows filename.\n","reFromString":"\nreFromString( str:string )\n    Parses a regular expression string and returns a new regular expression.\n","reFunctionName":"\nreFunctionName()\n    Return a regular expression to capture a function name.\n","reFunctionName.REGEXP":"\nreFunctionName.REGEXP\n    Regular expression to capture a function name.\n","regexp2json":"\nregexp2json( re:RegExp )\n    Returns a JSON representation of a regular expression.\n","reim":"\nreim( z:Complex128 )\n    Returns the real and imaginary components of a double-precision complex\n    floating-point number.\n","reimf":"\nreimf( z:Complex64 )\n    Returns the real and imaginary components of a single-precision complex\n    floating-point number.\n","rejectArguments":"\nrejectArguments( fcn:Function, predicate:Function[, thisArg:any] )\n    Returns a function that applies arguments to a provided function according\n    to a predicate function.\n","removeFirst":"\nremoveFirst( str:string[, n:integer][, options:Object] )\n    Removes the first character(s) of a `string`.\n","removeLast":"\nremoveLast( str:string[, n:integer][, options:Object] )\n    Removes the last character(s) of a `string`.\n","removePunctuation":"\nremovePunctuation( str:string )\n    Removes punctuation characters from a `string`.\n","removeUTF8BOM":"\nremoveUTF8BOM( str:string )\n    Removes a UTF-8 byte order mark (BOM) from the beginning of a `string`.\n","removeWords":"\nremoveWords( str:string, words:Array<string>[, ignoreCase:boolean] )\n    Removes all occurrences of the given words from a `string`.\n","rename":"\nrename( oldPath:string|Buffer, newPath:string|Buffer, clbk:Function )\n    Asynchronously renames a file.\n","rename.sync":"\nrename.sync( oldPath:string|Buffer, newPath:string|Buffer )\n    Synchronously renames a file.\n","reNativeFunction":"\nreNativeFunction()\n    Returns a regular expression to match a native function.\n","reNativeFunction.REGEXP":"\nreNativeFunction.REGEXP\n    Regular expression to match a native function.\n","reorderArguments":"\nreorderArguments( fcn:Function, indices:Array<integer>[, thisArg:any] )\n    Returns a function that invokes a provided function with reordered\n    arguments.\n","repeat":"\nrepeat( str:string, n:integer )\n    Repeats a string `n` times and returns the concatenated result.\n","replace":"\nreplace( str:string, search:string|RegExp, newval:string|Function )\n    Replaces search occurrences with a replacement string.\n","replaceBefore":"\nreplaceBefore( str, search, replacement )\n    Replaces the substring before the first occurrence of a specified search\n    string. \n","reRegExp":"\nreRegExp()\n    Returns a regular expression to parse a regular expression string.\n","reRegExp.REGEXP":"\nreRegExp.REGEXP\n    Regular expression to parse a regular expression string.\n","rescape":"\nrescape( str:string )\n    Escapes a regular expression string.\n","reSemVer":"\nreSemVer()\n    Returns a regular expression to match a semantic version string.\n","reSemVer.REGEXP":"\nreSemVer.REGEXP\n    Regular expression to match a semantic version string.\n","resolveParentPath":"\nresolveParentPath( path:string[, options:Object], clbk:Function )\n    Asynchronously resolves a path by walking parent directories.\n","resolveParentPath.sync":"\nresolveParentPath.sync( path:string[, options:Object] )\n    Synchronously resolves a path by walking parent directories.\n","resolveParentPathBy":"\nresolveParentPathBy( path:string[, options:Object], predicate:Function, \n  clbk:Function )\n    Asynchronously resolves a path according to a predicate function by walking\n    parent directories.\n","resolveParentPathBy.sync":"\nresolveParentPathBy.sync( path:string[, options:Object], predicate:Function )\n    Synchronously resolves a path according to a predicate function by walking\n    parent directories.\n","reUncPath":"\nreUncPath()\n    Return a regular expression to parse a UNC path.\n","reUncPath.REGEXP":"\nreUncPath.REGEXP\n    Regular expression to parse a UNC path.\n","reUtf16SurrogatePair":"\nreUtf16SurrogatePair()\n    Returns a regular expression to match a UTF-16 surrogate pair.\n","reUtf16SurrogatePair.REGEXP":"\nreUtf16SurrogatePair.REGEXP\n    Regular expression to match a UTF-16 surrogate pair.\n","reUtf16UnpairedSurrogate":"\nreUtf16UnpairedSurrogate()\n    Returns a regular expression to match an unpaired UTF-16 surrogate.\n","reUtf16UnpairedSurrogate.REGEXP":"\nreUtf16UnpairedSurrogate.REGEXP\n    Regular expression to match an unpaired UTF-16 surrogate.\n","reverseArguments":"\nreverseArguments( fcn:Function[, thisArg:any] )\n    Returns a function that invokes a provided function with arguments in\n    reverse order.\n","reverseString":"\nreverseString( str:string[, options:Object] )\n    Reverses a string.\n","reviveBasePRNG":"\nreviveBasePRNG( key:string, value:any )\n    Revives a JSON-serialized pseudorandom number generator (PRNG).\n","reviveBuffer":"\nreviveBuffer( key:string, value:any )\n    Revives a JSON-serialized Buffer.\n","reviveComplex":"\nreviveComplex( key:string, value:any )\n    Revives a JSON-serialized complex number.\n","reviveComplex64":"\nreviveComplex64( key:string, value:any )\n    Revives a JSON-serialized 64-bit complex number.\n","reviveComplex128":"\nreviveComplex128( key:string, value:any )\n    Revives a JSON-serialized 128-bit complex number.\n","reviveError":"\nreviveError( key:string, value:any )\n    Revives a JSON-serialized error object.\n","reviveRegExp":"\nreviveRegExp( key:string, value:any )\n    Revives a JSON-serialized regular expression.\n","reviveTypedArray":"\nreviveTypedArray( key:string, value:any )\n    Revives a JSON-serialized typed array.\n","reWhitespace":"\nreWhitespace( [options:Object] )\n    Returns a regular expression to match a white space character.\n","reWhitespace.REGEXP":"\nreWhitespace.REGEXP\n    Regular expression to match a white space character.\n","reWhitespace.REGEXP_CAPTURE":"\nreWhitespace.REGEXP_CAPTURE\n    Regular expression to capture white space characters.\n","rpad":"\nrpad( str:string, len:integer[, pad:string] )\n    Right pads a `string` such that the padded `string` has a length of at least\n    `len`.\n","rtrim":"\nrtrim( str:string )\n    Trims whitespace from the end of a string.\n","rtrimN":"\nrtrimN( str:string, n:integer[, chars:Array|string] )\n    Trims `n` characters from the end of a string.\n","safeintmax":"\nsafeintmax( dtype:string )\n    Returns the maximum safe integer capable of being represented by a numeric\n    real type.\n","safeintmin":"\nsafeintmin( dtype:string )\n    Returns the minimum safe integer capable of being represented by a numeric\n    real type.\n","sample":"\nsample( x:ArrayLike[, options:Object] )\n    Samples elements from an array-like object.\n","sample.factory":"\nsample.factory( [pool:ArrayLike, ][options:Object] )\n    Returns a function to sample elements from an array-like object.\n","SAVOY_STOPWORDS_FIN":"\nSAVOY_STOPWORDS_FIN()\n    Returns a list of Finnish stop words.\n","SAVOY_STOPWORDS_FR":"\nSAVOY_STOPWORDS_FR()\n    Returns a list of French stop words.\n","SAVOY_STOPWORDS_GER":"\nSAVOY_STOPWORDS_GER()\n    Returns a list of German stop words.\n","SAVOY_STOPWORDS_IT":"\nSAVOY_STOPWORDS_IT()\n    Returns a list of Italian stop words.\n","SAVOY_STOPWORDS_POR":"\nSAVOY_STOPWORDS_POR()\n    Returns a list of Portuguese stop words.\n","SAVOY_STOPWORDS_SP":"\nSAVOY_STOPWORDS_SP()\n    Returns a list of Spanish stop words.\n","SAVOY_STOPWORDS_SWE":"\nSAVOY_STOPWORDS_SWE()\n    Returns a list of Swedish stop words.\n","scalar2array":"\nscalar2array( value:any[, dtype:string] )\n    Returns a single-element array containing a provided scalar value.\n","scalar2ndarray":"\nscalar2ndarray( value:any[, options:Object] )\n    Returns a zero-dimensional ndarray containing a provided scalar value.\n","sdot":"\nsdot( x:ndarray, y:ndarray[, dim:integer] )\n    Computes the dot product of two single-precision floating-point vectors.\n","SECONDS_IN_DAY":"\nSECONDS_IN_DAY\n    Number of seconds in a day.\n","SECONDS_IN_HOUR":"\nSECONDS_IN_HOUR\n    Number of seconds in an hour.\n","SECONDS_IN_MINUTE":"\nSECONDS_IN_MINUTE\n    Number of seconds in a minute.\n","SECONDS_IN_WEEK":"\nSECONDS_IN_WEEK\n    Number of seconds in a week.\n","secondsInMonth":"\nsecondsInMonth( [month:string|Date|integer[, year:integer]] )\n    Returns the number of seconds in a month.\n","secondsInYear":"\nsecondsInYear( [value:integer|Date] )\n    Returns the number of seconds in a year according to the Gregorian calendar.\n","sentencize":"\nsentencize( str:string )\n    Splits a string into an array of sentences.\n","seq2slice":"\nseq2slice( str:string, len:integer, strict:boolean )\n    Converts a subsequence string to a Slice object.\n","setConfigurableReadOnly":"\nsetConfigurableReadOnly( obj:Object, prop:string|symbol, value:any )\n    Defines a configurable read-only property.\n","setConfigurableReadOnlyAccessor":"\nsetConfigurableReadOnlyAccessor( obj:Object, prop:string|symbol, \n  getter:Function )\n    Defines a configurable read-only accessor.\n","setConfigurableReadWriteAccessor":"\nsetConfigurableReadWriteAccessor( obj:Object, prop:string|symbol, \n  getter:Function, setter:Function )\n    Defines a configurable property having read-write accessors.\n","setConfigurableWriteOnlyAccessor":"\nsetConfigurableWriteOnlyAccessor( obj:Object, prop:string|symbol, \n  setter:Function )\n    Defines a configurable write-only accessor.\n","setMemoizedConfigurableReadOnly":"\nsetMemoizedConfigurableReadOnly( obj:Object, prop:string|symbol, fcn:Function )\n    Defines a configurable memoized read-only object property.\n","setMemoizedReadOnly":"\nsetMemoizedReadOnly( obj:Object, prop:string|symbol, fcn:Function )\n    Defines a memoized read-only object property.\n","setNonEnumerableProperty":"\nsetNonEnumerableProperty( obj:Object, prop:string|symbol, value:any )\n    Defines a non-enumerable property.\n","setNonEnumerableReadOnly":"\nsetNonEnumerableReadOnly( obj:Object, prop:string|symbol, value:any )\n    Defines a non-enumerable read-only property.\n","setNonEnumerableReadOnlyAccessor":"\nsetNonEnumerableReadOnlyAccessor( obj:Object, prop:string|symbol, \n  getter:Function )\n    Defines a non-enumerable read-only accessor.\n","setNonEnumerableReadWriteAccessor":"\nsetNonEnumerableReadWriteAccessor( obj:Object, prop:string|symbol, \n  getter:Function, setter:Function )\n    Defines a non-enumerable property having read-write accessors.\n","setNonEnumerableWriteOnlyAccessor":"\nsetNonEnumerableWriteOnlyAccessor( obj:Object, prop:string|symbol, \n  setter:Function )\n    Defines a non-enumerable write-only accessor.\n","setReadOnly":"\nsetReadOnly( obj:Object, prop:string|symbol, value:any )\n    Defines a read-only property.\n","setReadOnlyAccessor":"\nsetReadOnlyAccessor( obj:Object, prop:string|symbol, getter:Function )\n    Defines a read-only accessor.\n","setReadWriteAccessor":"\nsetReadWriteAccessor( obj:Object, prop:string|symbol, getter:Function, \n  setter:Function )\n    Defines a property having read-write accessors.\n","setWriteOnlyAccessor":"\nsetWriteOnlyAccessor( obj:Object, prop:string|symbol, setter:Function )\n    Defines a write-only accessor.\n","SharedArrayBuffer":"\nSharedArrayBuffer( size:integer )\n    Returns a shared array buffer having a specified number of bytes.\n","SharedArrayBuffer.length":"\nSharedArrayBuffer.length\n    Number of input arguments the constructor accepts.\n","SharedArrayBuffer.prototype.byteLength":"\nSharedArrayBuffer.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the array buffer.\n","SharedArrayBuffer.prototype.slice":"\nSharedArrayBuffer.prototype.slice( [start:integer[, end:integer]] )\n    Copies the bytes of a shared array buffer to a new shared array buffer.\n","shift":"\nshift( collection:Array|TypedArray|Object )\n    Removes and returns the first element of a collection.\n","shuffle":"\nshuffle( arr:ArrayLike[, options:Object] )\n    Shuffles elements of an array-like object.\n","shuffle.factory":"\nshuffle.factory( [options:Object] )\n    Returns a function to shuffle elements of array-like objects.\n","sizeOf":"\nsizeOf( dtype:string )\n    Returns the size (in bytes) of the canonical binary representation of a\n    specified numeric type.\n","Slice":"\nSlice( [stop:integer|null|undefined] )\n    Returns a Slice.\n\nSlice( start:integer|null|undefined, stop:integer|null|undefined[, \n  step:integer|null|undefined] )\n    Returns a Slice.\n","Slice.prototype.start":"\nSlice.prototype.start\n    Read-only property returning the starting slice index.\n","Slice.prototype.stop":"\nSlice.prototype.stop\n    Read-only property returning the ending slice index.\n","Slice.prototype.step":"\nSlice.prototype.step\n    Read-only property returning the index increment.\n","Slice.prototype.toString":"\nSlice.prototype.toString()\n    Serializes a Slice as a string.\n","Slice.prototype.toJSON":"\nSlice.prototype.toJSON()\n    Serializes a Slice as a JSON object.\n","snakecase":"\nsnakecase( str:string )\n    Converts a string to snake case.\n","some":"\nsome( collection:Array|TypedArray|Object, n:number )\n    Tests whether at least `n` elements in a collection are truthy.\n","someBy":"\nsomeBy( collection:Array|TypedArray|Object, n:number, predicate:Function[, \n  thisArg:any ] )\n    Tests whether a collection contains at least `n` elements which pass a test\n    implemented by a predicate function.\n","someByAsync":"\nsomeByAsync( collection:Array|TypedArray|Object, n:number, [options:Object,] \n  predicate:Function, done:Function )\n    Tests whether a collection contains at least `n` elements which pass a test\n    implemented by a predicate function.\n","someByAsync.factory":"\nsomeByAsync.factory( [options:Object,] predicate:Function )\n    Returns a function which tests whether a collection contains at least `n`\n    elements which pass a test implemented by a predicate function.\n","someByRight":"\nsomeByRight( collection:Array|TypedArray|Object, n:number, predicate:Function[, \n  thisArg:any ] )\n    Tests whether a collection contains at least `n` elements which pass a test\n    implemented by a predicate function, iterating from right to left.\n","someByRightAsync":"\nsomeByRightAsync( collection:Array|TypedArray|Object, n:number, \n  [options:Object,] predicate:Function, done:Function )\n    Tests whether a collection contains at least `n` elements which pass a test\n    implemented by a predicate function, iterating from right to left.\n","someByRightAsync.factory":"\nsomeByRightAsync.factory( [options:Object,] predicate:Function )\n    Returns a function which tests whether a collection contains at least `n`\n    elements which pass a test implemented by a predicate function, iterating\n    from right to left.\n","someInBy":"\nsomeInBy( obj:Object, n:number, predicate:Function[, thisArg:any ] )\n    Tests whether an object contains at least `n` properties\n    (own and inherited) which pass a test\n    implemented by a predicate function.\n","someOwnBy":"\nsomeOwnBy( obj:Object, n:number, predicate:Function[, thisArg:any ] )\n    Tests whether some `own` properties of a provided object\n    satisfy a predicate function for at least `n` properties.\n","SOTU":"\nSOTU( [options:Object] )\n    Returns State of the Union (SOTU) addresses.\n","SPACHE_REVISED":"\nSPACHE_REVISED()\n    Returns a list of simple American-English words (revised Spache).\n","SPAM_ASSASSIN":"\nSPAM_ASSASSIN()\n    Returns the Spam Assassin public mail corpus.\n","SparklineBase":"\nSparklineBase( [data:ArrayLike|ndarray,] [options:Object] )\n    Returns a Sparkline instance.\n","sparsearray2iterator":"\nsparsearray2iterator( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )\n    Returns an iterator which iterates over the elements of a sparse array-like\n    object.\n","sparsearray2iteratorRight":"\nsparsearray2iteratorRight( src:ArrayLikeObject[, mapFcn:Function[, \n  thisArg:any]] )\n    Returns an iterator which iterates from right to left over the elements of a\n    sparse array-like object.\n","splitStream":"\nsplitStream( [options:Object] )\n    Returns a transform stream which splits streamed data.\n","splitStream.factory":"\nsplitStream.factory( [options:Object] )\n    Returns a function for creating transform streams for splitting streamed\n    data.\n","splitStream.objectMode":"\nsplitStream.objectMode( [options:Object] )\n    Returns an \"objectMode\" transform stream for splitting streamed data.\n","SQRT_EPS":"\nSQRT_EPS\n    Square root of double-precision floating-point epsilon.\n","SQRT_HALF":"\nSQRT_HALF\n    Square root of `1/2`.\n","SQRT_HALF_PI":"\nSQRT_HALF_PI\n    Square root of the mathematical constant `π` divided by `2`.\n","SQRT_PHI":"\nSQRT_PHI\n    Square root of the golden ratio.\n","SQRT_PI":"\nSQRT_PI\n    Square root of the mathematical constant `π`.\n","SQRT_THREE":"\nSQRT_THREE\n    Square root of `3`.\n","SQRT_TWO":"\nSQRT_TWO\n    Square root of `2`.\n","SQRT_TWO_PI":"\nSQRT_TWO_PI\n    Square root of the mathematical constant `π` times `2`.\n","SSA_US_BIRTHS_2000_2014":"\nSSA_US_BIRTHS_2000_2014()\n    Returns US birth data from 2000 to 2014, as provided by the Social Security\n    Administration.\n","sswap":"\nsswap( x:ndarray, y:ndarray[, dim:integer] )\n    Interchanges two single-precision floating-point vectors.\n","Stack":"\nStack()\n    Stack constructor.\n","standalone2pkg":"\nstandalone2pkg( pkg:string )\n    Returns the internal package name associated with a provided standalone\n    package name.\n","STANDARD_CARD_DECK":"\nSTANDARD_CARD_DECK()\n    Returns a string array containing two or three letter abbreviations for each\n    card in a standard 52-card deck.\n","startcase":"\nstartcase( str:string )\n    Capitalizes the first letter of each word in an input string.\n","startsWith":"\nstartsWith( str:string, search:string[, position:integer] )\n    Tests if a string starts with the characters of another string.\n","STOPWORDS_EN":"\nSTOPWORDS_EN()\n    Returns a list of English stop words.\n","strided.abs":"\nstrided.abs( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  dtypeY:any, y:ArrayLikeObject, strideY:integer )\n    Computes the absolute value for each element in a strided array `x` and\n    assigns the results to elements in a strided array `y`.\n","strided.abs.ndarray":"\nstrided.abs.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, \n  offsetY:integer )\n    Computes the absolute value for each element in a strided array `x` and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n","strided.abs2":"\nstrided.abs2( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  dtypeY:any, y:ArrayLikeObject, strideY:integer )\n    Computes the squared absolute value for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y`.\n","strided.abs2.ndarray":"\nstrided.abs2.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n  strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n  strideY:integer, offsetY:integer )\n    Computes the squared absolute value for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n","strided.abs2By":"\nstrided.abs2By( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the squared absolute value of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n","strided.abs2By.ndarray":"\nstrided.abs2By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the squared absolute value of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing semantics.\n","strided.absBy":"\nstrided.absBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the absolute value of each element retrieved from a strided input\n    array `x` via a callback function and assigns each result to an element in a\n    strided output array `y`.\n","strided.absBy.ndarray":"\nstrided.absBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the absolute value of each element retrieved from a strided input\n    array `x` via a callback function and assigns each result to an element in a\n    strided output array `y` using alternative indexing semantics.\n","strided.acosBy":"\nstrided.acosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the arccosine of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y`.\n","strided.acosBy.ndarray":"\nstrided.acosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the arccosine of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n","strided.acoshBy":"\nstrided.acoshBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the hyperbolic arccosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n","strided.acoshBy.ndarray":"\nstrided.acoshBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the hyperbolic arccosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n","strided.acotBy":"\nstrided.acotBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the inverse cotangent of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n","strided.acotBy.ndarray":"\nstrided.acotBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the inverse cotangent of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n","strided.acothBy":"\nstrided.acothBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the inverse hyperbolic cotangent of each element retrieved from an\n    input strided array `x` via a callback function and assigns each result to\n    an element in an output strided array `y`.\n","strided.acothBy.ndarray":"\nstrided.acothBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the inverse hyperbolic cotangent of each element retrieved from an\n    input strided array `x` via a callback function and assigns each result to\n    an element in an output strided array `y` using alternative indexing\n    semantics.\n","strided.acovercosBy":"\nstrided.acovercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the inverse coversed cosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n","strided.acovercosBy.ndarray":"\nstrided.acovercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the inverse coversed cosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n","strided.acoversinBy":"\nstrided.acoversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the inverse coversed sine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n","strided.acoversinBy.ndarray":"\nstrided.acoversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the inverse coversed sine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n","strided.add":"\nstrided.add( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, \n  y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )\n    Adds each element in a strided array `x` to a corresponding element in a\n    strided array `y` and assigns the results to elements in a strided array\n    `z`.\n","strided.add.ndarray":"\nstrided.add.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, \n  ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, \n  z:ArrayLikeObject, sz:integer, oz:integer )\n    Adds each element in a strided array `x` to a corresponding element in a\n    strided array `y` and assigns the results to elements in a strided array\n    `z` using alternative indexing semantics.\n","strided.addBy":"\nstrided.addBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, \n  clbk:Function[, thisArg:any] )\n    Performs element-wise addition of two strided arrays via a callback function\n    and assigns each result to an element in an output strided array.\n","strided.addBy.ndarray":"\nstrided.addBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, \n  thisArg:any] )\n    Performs element-wise addition of two strided arrays via a callback function\n    and assigns each result to an element in an output strided array using\n    alternative indexing semantics.\n","strided.ahavercosBy":"\nstrided.ahavercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the inverse half-value versed cosine of each element retrieved from\n    an input strided array `x` via a callback function and assigns each result\n    to an element in an output strided array `y`.\n","strided.ahavercosBy.ndarray":"\nstrided.ahavercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the inverse half-value versed cosine of each element retrieved from\n    an input strided array `x` via a callback function and assigns each result\n    to an element in an output strided array `y` using alternative indexing\n    semantics.\n","strided.ahaversinBy":"\nstrided.ahaversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the inverse half-value versed sine of each element retrieved from\n    an input strided array `x` via a callback function and assigns each result\n    to an element in an output strided array `y`.\n","strided.ahaversinBy.ndarray":"\nstrided.ahaversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the inverse half-value versed sine of each element retrieved from\n    an input strided array `x` via a callback function and assigns each result\n    to an element in an output strided array `y` using alternative indexing\n    semantics.\n","strided.asinBy":"\nstrided.asinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the arcsine of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y`.\n","strided.asinBy.ndarray":"\nstrided.asinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the arcsine of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n","strided.asinhBy":"\nstrided.asinhBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the hyperbolic arcsine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n","strided.asinhBy.ndarray":"\nstrided.asinhBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the hyperbolic arcsine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n","strided.atanBy":"\nstrided.atanBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the arctangent of each element retrieved from an input strided\n    array `x` via a callback function and assigns each result to an element in\n    an output strided array `y`.\n","strided.atanBy.ndarray":"\nstrided.atanBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the arctangent of each element retrieved from an input strided\n    array `x` via a callback function and assigns each result to an element in\n    an output strided array `y` using alternative indexing semantics.\n","strided.atanhBy":"\nstrided.atanhBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the hyperbolic arctangent of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n","strided.atanhBy.ndarray":"\nstrided.atanhBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the hyperbolic arctangent of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n","strided.avercosBy":"\nstrided.avercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the inverse versed cosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n","strided.avercosBy.ndarray":"\nstrided.avercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the inverse versed cosine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n","strided.aversinBy":"\nstrided.aversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the inverse versed sine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n","strided.aversinBy.ndarray":"\nstrided.aversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the inverse versed sine of each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing\n    semantics.\n","strided.besselj0By":"\nstrided.besselj0By( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the Bessel function of the first kind of order zero for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y`.\n","strided.besselj0By.ndarray":"\nstrided.besselj0By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the Bessel function of the first kind of order zero for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n","strided.besselj1By":"\nstrided.besselj1By( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the Bessel function of the first kind of order one for each element\n    retrieved from an input strided array `x` via a callback function and\n    assigns each result to an element in an output strided array `y`.\n","strided.besselj1By.ndarray":"\nstrided.besselj1By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the Bessel function of the first kind of order one for each element\n    retrieved from an input strided array `x` via a callback function and\n    assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n","strided.bessely0By":"\nstrided.bessely0By( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the Bessel function of the second kind of order zero for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y`.\n","strided.bessely0By.ndarray":"\nstrided.bessely0By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the Bessel function of the second kind of order zero for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n","strided.bessely1By":"\nstrided.bessely1By( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the Bessel function of the second kind of order one for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y`.\n","strided.bessely1By.ndarray":"\nstrided.bessely1By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the Bessel function of the second kind of order one for each\n    element retrieved from an input strided array `x` via a callback function\n    and assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n","strided.binetBy":"\nstrided.binetBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Evaluates Binet's formula extended to real numbers for each element\n    retrieved from an input strided array `x` via a callback function and\n    assigns each result to an element in an output strided array `y`.\n","strided.binetBy.ndarray":"\nstrided.binetBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Evaluates Binet's formula extended to real numbers for each element\n    retrieved from an input strided array `x` via a callback function and\n    assigns each result to an element in an output strided array `y` using\n    alternative indexing semantics.\n","strided.cbrt":"\nstrided.cbrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  dtypeY:any, y:ArrayLikeObject, strideY:integer )\n    Computes the cube root of each element in a strided array `x` and assigns\n    the results to elements in a strided array `y`.\n","strided.cbrt.ndarray":"\nstrided.cbrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n  strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n  strideY:integer, offsetY:integer )\n    Computes the cube root of each element in a strided array `x` and assigns\n    the results to elements in a strided array `y` using alternative indexing\n    semantics.\n","strided.cbrtBy":"\nstrided.cbrtBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the cube root of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y`.\n","strided.cbrtBy.ndarray":"\nstrided.cbrtBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the cube root of each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n","strided.ceil":"\nstrided.ceil( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  dtypeY:any, y:ArrayLikeObject, strideY:integer )\n    Rounds each element in a strided array `x` toward positive infinity and\n    assigns the results to elements in a strided array `y`.\n","strided.ceil.ndarray":"\nstrided.ceil.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n  strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n  strideY:integer, offsetY:integer )\n    Rounds each element in a strided array `x` toward positive infinity and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n","strided.cosBy":"\nstrided.cosBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the cosine for each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y`.\n","strided.cosBy.ndarray":"\nstrided.cosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the cosine for each element retrieved from an input strided array\n    `x` via a callback function and assigns each result to an element in an\n    output strided array `y` using alternative indexing semantics.\n","strided.deg2rad":"\nstrided.deg2rad( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  dtypeY:any, y:ArrayLikeObject, strideY:integer )\n    Converts each element in a strided array `x` from degrees to radians and\n    assigns the results to elements in a strided array `y`.\n","strided.deg2rad.ndarray":"\nstrided.deg2rad.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n  strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n  strideY:integer, offsetY:integer )\n    Converts each element in a strided array `x` from degrees to radians and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n","strided.dataTypes":"\nstrided.dataTypes()\n    Returns a list of strided array data types.\n","strided.dcbrtBy":"\nstrided.dcbrtBy( N:integer, x:Float64Array, sx:integer, y:Float64Array, \n  sy:integer, clbk:Function[, thisArg:any] )\n    Computes the cube root of each element retrieved from an input double-\n    precision floating-point strided array via a callback function and assigns\n    each result to an element in an output double-precision floating-point\n    strided array.\n","strided.dcbrtBy.ndarray":"\nstrided.dcbrtBy.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, \n  y:Float64Array, sy:integer, oy:integer, clbk:Function[, thisArg:any] )\n    Computes the cube root of each element retrieved from an input double-\n    precision floating-point strided array via a callback function and assigns\n    each result to an element in an output double-precision floating-point\n    strided array using alternative indexing semantics.\n","strided.dispatch":"\nstrided.dispatch( fcns:Function|ArrayLikeObject<Function>, \n  types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, \n  nout:integer )\n    Returns a strided array function interface which performs multiple dispatch.\n","strided.dispatchBy":"\nstrided.dispatchBy( fcns:Function|ArrayLikeObject<Function>, \n  types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, \n  nout:integer )\n    Returns a strided array function interface which accepts a callback function\n    and performs multiple dispatch.\n","strided.floor":"\nstrided.floor( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  dtypeY:any, y:ArrayLikeObject, strideY:integer )\n    Rounds each element in a strided array `x` toward negative infinity and\n    assigns the results to elements in a strided array `y`.\n","strided.floor.ndarray":"\nstrided.floor.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n  strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n  strideY:integer, offsetY:integer )\n    Rounds each element in a strided array `x` toward negative infinity and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n","strided.inv":"\nstrided.inv( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  dtypeY:any, y:ArrayLikeObject, strideY:integer )\n    Computes the multiplicative inverse for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y`.\n","strided.inv.ndarray":"\nstrided.inv.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, \n  offsetY:integer )\n    Computes the multiplicative inverse for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n","strided.mul":"\nstrided.mul( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, \n  y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )\n    Multiplies each element in a strided array `x` to a corresponding element in\n    a strided array `y` and assigns the results to elements in a strided array\n    `z`.\n","strided.mul.ndarray":"\nstrided.mul.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, \n  ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, \n  z:ArrayLikeObject, sz:integer, oz:integer )\n    Multiplies each element in a strided array `x` to a corresponding element in\n    a strided array `y` and assigns the results to elements in a strided array\n    `z` using alternative indexing semantics.\n","strided.mulBy":"\nstrided.mulBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, \n  clbk:Function[, thisArg:any] )\n    Performs element-wise multiplication of two strided arrays via a callback\n    function and assigns each result to an element in an output strided array.\n","strided.mulBy.ndarray":"\nstrided.mulBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, \n  thisArg:any] )\n    Performs element-wise multiplication of two strided arrays via a callback\n    function and assigns each result to an element in an output strided array\n    using alternative indexing semantics.\n","strided.ramp":"\nstrided.ramp( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  dtypeY:any, y:ArrayLikeObject, strideY:integer )\n    Evaluates the ramp function for each element in a strided array `x` and\n    assigns the results to elements in a strided array `y`.\n","strided.ramp.ndarray":"\nstrided.ramp.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n  strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n  strideY:integer, offsetY:integer )\n    Evaluates the ramp function for each element in a strided array `x` and\n    assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n","strided.rsqrt":"\nstrided.rsqrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  dtypeY:any, y:ArrayLikeObject, strideY:integer )\n    Computes the reciprocal square root for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y`.\n","strided.rsqrt.ndarray":"\nstrided.rsqrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n  strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n  strideY:integer, offsetY:integer )\n    Computes the reciprocal square root for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n","strided.sinBy":"\nstrided.sinBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the sine of each element retrieved from an input strided array `x`\n    via a callback function and assigns each result to an element in an output\n    strided array `y`.\n","strided.sinBy.ndarray":"\nstrided.sinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the sine of each element retrieved from an input strided array `x`\n    via a callback function and assigns each result to an element in an output\n    strided array `y` using alternative indexing semantics.\n","strided.sqrt":"\nstrided.sqrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  dtypeY:any, y:ArrayLikeObject, strideY:integer )\n    Computes the principal square root for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y`.\n","strided.sqrt.ndarray":"\nstrided.sqrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n  strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n  strideY:integer, offsetY:integer )\n    Computes the principal square root for each element in a strided array `x`\n    and assigns the results to elements in a strided array `y` using alternative\n    indexing semantics.\n","strided.sqrtBy":"\nstrided.sqrtBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )\n    Computes the principal square root for each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y`.\n","strided.sqrtBy.ndarray":"\nstrided.sqrtBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  clbk:Function[, thisArg:any] )\n    Computes the principal square root for each element retrieved from an input\n    strided array `x` via a callback function and assigns each result to an\n    element in an output strided array `y` using alternative indexing semantics.\n","strided.sub":"\nstrided.sub( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, \n  y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )\n    Subtracts each element in a strided array `x` to a corresponding element in\n    a strided array `y` and assigns the results to elements in a strided array\n    `z`.\n","strided.sub.ndarray":"\nstrided.sub.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, \n  ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, \n  z:ArrayLikeObject, sz:integer, oz:integer )\n    Subtracts each element in a strided array `x` to a corresponding element in\n    a strided array `y` and assigns the results to elements in a strided array\n    `z` using alternative indexing semantics.\n","strided.subBy":"\nstrided.subBy( N:integer, x:Array|TypedArray|Object, sx:integer, \n  y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, \n  clbk:Function[, thisArg:any] )\n    Performs element-wise subtraction of two strided arrays via a callback\n    function and assigns each result to an element in an output strided array.\n","strided.subBy.ndarray":"\nstrided.subBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, \n  ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, \n  z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, \n  thisArg:any] )\n    Performs element-wise subtraction of two strided arrays via a callback\n    function and assigns each result to an element in an output strided array\n    using alternative indexing semantics.\n","strided.trunc":"\nstrided.trunc( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, \n  dtypeY:any, y:ArrayLikeObject, strideY:integer )\n    Rounds each element in a strided array `x` toward zero and assigns the\n    results to elements in a strided array `y`.\n","strided.trunc.ndarray":"\nstrided.trunc.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, \n  strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, \n  strideY:integer, offsetY:integer )\n    Rounds each element in a strided array `x` toward zero and assigns the\n    results to elements in a strided array `y` using alternative indexing\n    semantics.\n","stridedarray2iterator":"\nstridedarray2iterator( N:integer, src:ArrayLikeObject, stride:integer, \n  offset:integer[, mapFcn:Function[, thisArg:any]] )\n    Returns an iterator which iterates over elements of an array-like object\n    according to specified stride parameters.\n","stridedArrayStream":"\nstridedArrayStream( N:integer, buffer:ArrayLikeObject, stride:integer, \n  offset:integer[, options:Object] )\n    Creates a readable stream from a strided array-like object.\n","stridedArrayStream.factory":"\nstridedArrayStream.factory( [options:Object] )\n    Returns a function for creating readable streams from array-like objects.\n","stridedArrayStream.objectMode":"\nstridedArrayStream.objectMode( N:integer, buffer:ArrayLikeObject, \n  stride:integer, offset:integer[, options:Object] )\n    Returns an \"objectMode\" readable stream from a strided array-like object.\n","string2buffer":"\nstring2buffer( str:string[, encoding:string] )\n    Allocates a buffer containing a provided string.\n","sub2ind":"\nsub2ind( shape:ArrayLike, ...subscript:integer[, options:Object] )\n    Converts subscripts to a linear index.\n","substringAfter":"\nsubstringAfter( str:string, search:string[, fromIndex:integer] )\n    Returns the part of a string after a specified substring.\n","substringAfterLast":"\nsubstringAfterLast( str:string, search:string[, fromIndex:integer] )\n    Returns the part of a string after the last occurrence of a specified\n    substring.\n","substringBefore":"\nsubstringBefore( str:string, search:string )\n    Returns the part of a string before a specified substring.\n","substringBeforeLast":"\nsubstringBeforeLast( str:string, search:string )\n    Returns the part of a string before the last occurrence of a specified\n    substring.\n","SUTHAHARAN_MULTI_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_MULTI_HOP_SENSOR_NETWORK()\n    Returns a dataset consisting of labeled wireless sensor network data set\n    collected from a multi-hop wireless sensor network deployment using TelosB\n    motes.\n","SUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK":"\nSUTHAHARAN_SINGLE_HOP_SENSOR_NETWORK()\n    Returns a dataset consisting of labeled wireless sensor network data set\n    collected from a simple single-hop wireless sensor network deployment using\n    TelosB motes.\n","Symbol":"\nSymbol( [description:string] )\n    Returns a symbol.\n","tabulate":"\ntabulate( collection:Array|TypedArray|Object )\n    Generates a frequency table.\n","tabulateBy":"\ntabulateBy( collection:Array|TypedArray|Object, [options:Object,] \n  indicator:Function )\n    Generates a frequency table according to an indicator function.\n","tabulateByAsync":"\ntabulateByAsync( collection:Array|TypedArray|Object, [options:Object,] \n  indicator:Function, done:Function )\n    Generates a frequency table according to an indicator function.\n","tabulateByAsync.factory":"\ntabulateByAsync.factory( [options:Object,] indicator:Function )\n    Returns a function which generates a frequency table according to an\n    indicator function.\n","thunk":"\nthunk( fcn:Function[, ...args:any] )\n    Returns a thunk.\n","tic":"\ntic()\n    Returns a high-resolution time.\n","timeit":"\ntimeit( code:string, [options:Object,] clbk:Function )\n    Times a snippet.\n","tmpdir":"\ntmpdir()\n    Returns the directory for storing temporary files.\n","toc":"\ntoc( time:Array<integer> )\n    Returns a high-resolution time difference, where `time` is a two-element\n    array with format `[seconds, nanoseconds]`.\n","tokenize":"\ntokenize( str:string[, keepWhitespace:boolean] )\n    Tokenizes a string.\n","transformStream":"\ntransformStream( [options:Object] )\n    Returns a transform stream.\n","transformStream.factory":"\ntransformStream.factory( [options:Object] )\n    Returns a function for creating transform streams.\n","transformStream.objectMode":"\ntransformStream.objectMode( [options:Object] )\n    Returns an \"objectMode\" transform stream.\n","transformStream.ctor":"\ntransformStream.ctor( [options:Object] )\n    Returns a custom transform stream constructor.\n","trim":"\ntrim( str:string )\n    Trims whitespace from the beginning and end of a `string`.\n","truncate":"\ntruncate( str:string, len:integer[, ending:string] )\n    Truncates a string to a specified length.\n","truncateMiddle":"\ntruncateMiddle( str:string, len:integer[, seq:string] )\n    Truncates a string in the middle to a specified length.\n","trycatch":"\ntrycatch( x:Function, y:any )\n    If a function does not throw, returns the function return value; otherwise,\n    returns `y`.\n","trycatchAsync":"\ntrycatchAsync( x:Function, y:any, done:Function )\n    If a function does not return an error, invokes a callback with the function\n    result; otherwise, invokes a callback with a value `y`.\n","tryFunction":"\ntryFunction( fcn:Function[, thisArg:any] )\n    Wraps a function in a try/catch block.\n","tryRequire":"\ntryRequire( id:string )\n    Wraps `require` in a `try/catch` block.\n","trythen":"\ntrythen( x:Function, y:Function )\n    If a function does not throw, returns the function return value; otherwise,\n    returns the value returned by a second function `y`.\n","trythenAsync":"\ntrythenAsync( x:Function, y:Function, done:Function )\n    If a function does not return an error, invokes a callback with the function\n    result; otherwise, invokes a second function `y`.\n","ttest":"\nttest( x:Array<number>[, y:Array<number>][, options:Object] )\n    Computes a one-sample or paired Student's t test.\n","ttest2":"\nttest2( x:Array<number>, y:Array<number>[, options:Object] )\n    Computes a two-sample Student's t test.\n","TWO_PI":"\nTWO_PI\n    The mathematical constant `π` times `2`.\n","typedarray":"\ntypedarray( [dtype:string] )\n    Creates a typed array.\n\ntypedarray( length:integer[, dtype:string] )\n    Returns a typed array having a specified length.\n\ntypedarray( typedarray:TypedArray[, dtype:string] )\n    Creates a typed array from another typed array.\n\ntypedarray( obj:Object[, dtype:string] )\n    Creates a typed array from an array-like object or iterable.\n\ntypedarray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, \n  dtype:string] )\n    Returns a typed array view of an ArrayBuffer.\n","typedarray2json":"\ntypedarray2json( arr:TypedArray )\n    Returns a JSON representation of a typed array.\n","typedarrayCtors":"\ntypedarrayCtors( dtype:string )\n    Returns a typed array constructor.\n","typedarrayDataTypes":"\ntypedarrayDataTypes()\n    Returns a list of typed array data types.\n","typedarraypool":"\ntypedarraypool( [dtype:string] )\n    Returns an uninitialized typed array from a typed array memory pool.\n\ntypedarraypool( length:integer[, dtype:string] )\n    Returns an uninitialized typed array having a specified length from a typed\n    array memory pool.\n\ntypedarraypool( typedarray:TypedArray[, dtype:string] )\n    Creates a pooled typed array from another typed array.\n\ntypedarraypool( obj:Object[, dtype:string] )\n    Creates a pooled typed array from an array-like object.\n","typedarraypool.malloc":"\ntypedarraypool.malloc( [dtype:string] )\n    Returns an uninitialized typed array from a typed array memory pool.\n\ntypedarraypool.malloc( length:integer[, dtype:string] )\n    Returns a typed array having a specified length from a typed array memory\n    pool.\n\ntypedarraypool.malloc( typedarray:TypedArray[, dtype:string] )\n    Creates a pooled typed array from another typed array.\n\ntypedarraypool.malloc( obj:Object[, dtype:string] )\n    Creates a pooled typed array from an array-like object.\n","typedarraypool.calloc":"\ntypedarraypool.calloc( [dtype:string] )\n    Returns a zero-initialized typed array from a typed array memory pool.\n\ntypedarraypool.calloc( length:integer[, dtype:string] )\n    Returns a zero-initialized typed array having a specified length from a\n    typed array memory pool.\n","typedarraypool.free":"\ntypedarraypool.free( buf:TypedArray|ArrayBuffer )\n    Frees a typed array or typed array buffer for use in a future allocation.\n","typedarraypool.clear":"\ntypedarraypool.clear()\n    Clears the typed array pool allowing garbage collection of previously\n    allocated (and currently free) array buffers.\n","typedarraypool.highWaterMark":"\ntypedarraypool.highWaterMark\n    Read-only property returning the pool's high water mark.\n","typedarraypool.nbytes":"\ntypedarraypool.nbytes\n    Read-only property returning the total number of allocated bytes.\n","typedarraypool.factory":"\ntypedarraypool.factory( [options:Object] )\n    Creates a typed array pool.\n","typemax":"\ntypemax( dtype:string )\n    Returns the maximum value of a specified numeric type.\n","typemin":"\ntypemin( dtype:string )\n    Returns the minimum value of a specified numeric type.\n","typeOf":"\ntypeOf( value:any )\n    Determines a value's type.\n","UINT8_MAX":"\nUINT8_MAX\n    Maximum unsigned 8-bit integer.\n","UINT8_NUM_BYTES":"\nUINT8_NUM_BYTES\n    Size (in bytes) of an 8-bit unsigned integer.\n","Uint8Array":"\nUint8Array()\n    A typed array constructor which returns a typed array representing an array\n    of 8-bit unsigned integers in the platform byte order.\n\nUint8Array( length:integer )\n    Returns a typed array having a specified length.\n\nUint8Array( typedarray:TypedArray )\n    Creates a typed array from another typed array.\n\nUint8Array( obj:Object )\n    Creates a typed array from an array-like object or iterable.\n\nUint8Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a typed array view of an ArrayBuffer.\n","Uint8Array.from":"\nUint8Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n    Creates a new typed array from an array-like object or an iterable.\n","Uint8Array.of":"\nUint8Array.of( element0:number[, element1:number[, ...elementN:number]] )\n    Creates a new typed array from a variable number of arguments.\n","Uint8Array.BYTES_PER_ELEMENT":"\nUint8Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Uint8Array.name":"\nUint8Array.name\n    Typed array constructor name.\n","Uint8Array.prototype.buffer":"\nUint8Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n","Uint8Array.prototype.byteLength":"\nUint8Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n","Uint8Array.prototype.byteOffset":"\nUint8Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n","Uint8Array.prototype.BYTES_PER_ELEMENT":"\nUint8Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Uint8Array.prototype.length":"\nUint8Array.prototype.length\n    Read-only property which returns the number of view elements.\n","Uint8Array.prototype.copyWithin":"\nUint8Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint8Array.prototype.entries":"\nUint8Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","Uint8Array.prototype.every":"\nUint8Array.prototype.every( predicate:Function[, thisArg:Any] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n","Uint8Array.prototype.fill":"\nUint8Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n","Uint8Array.prototype.filter":"\nUint8Array.prototype.filter( predicate:Function[, thisArg:Any] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n","Uint8Array.prototype.find":"\nUint8Array.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n","Uint8Array.prototype.findIndex":"\nUint8Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n","Uint8Array.prototype.forEach":"\nUint8Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n    Invokes a callback for each array element.\n","Uint8Array.prototype.includes":"\nUint8Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a search element.\n","Uint8Array.prototype.indexOf":"\nUint8Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n","Uint8Array.prototype.join":"\nUint8Array.prototype.join( [separator:string] )\n    Serializes an array by joining all array elements as a string.\n","Uint8Array.prototype.keys":"\nUint8Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n","Uint8Array.prototype.lastIndexOf":"\nUint8Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n","Uint8Array.prototype.map":"\nUint8Array.prototype.map( fcn:Function[, thisArg:Any] )\n    Maps each array element to an element in a new typed array.\n","Uint8Array.prototype.reduce":"\nUint8Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n","Uint8Array.prototype.reduceRight":"\nUint8Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n","Uint8Array.prototype.reverse":"\nUint8Array.prototype.reverse()\n    Reverses an array *in-place*.\n","Uint8Array.prototype.set":"\nUint8Array.prototype.set( arr:ArrayLike[, offset:integer] )\n    Sets array elements.\n","Uint8Array.prototype.slice":"\nUint8Array.prototype.slice( [begin:integer[, end:integer]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n","Uint8Array.prototype.some":"\nUint8Array.prototype.some( predicate:Function[, thisArg:Any] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n","Uint8Array.prototype.sort":"\nUint8Array.prototype.sort( [compareFunction:Function] )\n    Sorts an array *in-place*.\n","Uint8Array.prototype.subarray":"\nUint8Array.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n","Uint8Array.prototype.toLocaleString":"\nUint8Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n    Serializes an array as a locale-specific string.\n","Uint8Array.prototype.toString":"\nUint8Array.prototype.toString()\n    Serializes an array as a string.\n","Uint8Array.prototype.values":"\nUint8Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n","Uint8ClampedArray":"\nUint8ClampedArray()\n    A typed array constructor which returns a typed array representing an array\n    of 8-bit unsigned integers in the platform byte order clamped to 0-255.\n\nUint8ClampedArray( length:integer )\n    Returns a typed array having a specified length.\n\nUint8ClampedArray( typedarray:TypedArray )\n    Creates a typed array from another typed array.\n\nUint8ClampedArray( obj:Object )\n    Creates a typed array from an array-like object or iterable.\n\nUint8ClampedArray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a typed array view of an ArrayBuffer.\n","Uint8ClampedArray.from":"\nUint8ClampedArray.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n    Creates a new typed array from an array-like object or an iterable.\n","Uint8ClampedArray.of":"\nUint8ClampedArray.of( element0:number[, element1:number[, ...elementN:number]] )\n    Creates a new typed array from a variable number of arguments.\n","Uint8ClampedArray.BYTES_PER_ELEMENT":"\nUint8ClampedArray.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Uint8ClampedArray.name":"\nUint8ClampedArray.name\n    Typed array constructor name.\n","Uint8ClampedArray.prototype.buffer":"\nUint8ClampedArray.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n","Uint8ClampedArray.prototype.byteLength":"\nUint8ClampedArray.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n","Uint8ClampedArray.prototype.byteOffset":"\nUint8ClampedArray.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n","Uint8ClampedArray.prototype.BYTES_PER_ELEMENT":"\nUint8ClampedArray.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Uint8ClampedArray.prototype.length":"\nUint8ClampedArray.prototype.length\n    Read-only property which returns the number of view elements.\n","Uint8ClampedArray.prototype.copyWithin":"\nUint8ClampedArray.prototype.copyWithin( target:integer, start:integer[, \n  end:integer] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint8ClampedArray.prototype.entries":"\nUint8ClampedArray.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","Uint8ClampedArray.prototype.every":"\nUint8ClampedArray.prototype.every( predicate:Function[, thisArg:Any] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n","Uint8ClampedArray.prototype.fill":"\nUint8ClampedArray.prototype.fill( value:number[, start:integer[, end:integer]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n","Uint8ClampedArray.prototype.filter":"\nUint8ClampedArray.prototype.filter( predicate:Function[, thisArg:Any] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n","Uint8ClampedArray.prototype.find":"\nUint8ClampedArray.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n","Uint8ClampedArray.prototype.findIndex":"\nUint8ClampedArray.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n","Uint8ClampedArray.prototype.forEach":"\nUint8ClampedArray.prototype.forEach( fcn:Function[, thisArg:Any] )\n    Invokes a callback for each array element.\n","Uint8ClampedArray.prototype.includes":"\nUint8ClampedArray.prototype.includes( searchElement:number[, \n  fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a search element.\n","Uint8ClampedArray.prototype.indexOf":"\nUint8ClampedArray.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n","Uint8ClampedArray.prototype.join":"\nUint8ClampedArray.prototype.join( [separator:string] )\n    Serializes an array by joining all array elements as a string.\n","Uint8ClampedArray.prototype.keys":"\nUint8ClampedArray.prototype.keys()\n    Returns an iterator for iterating over array keys.\n","Uint8ClampedArray.prototype.lastIndexOf":"\nUint8ClampedArray.prototype.lastIndexOf( searchElement:number[, \n  fromIndex:integer] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n","Uint8ClampedArray.prototype.map":"\nUint8ClampedArray.prototype.map( fcn:Function[, thisArg:Any] )\n    Maps each array element to an element in a new typed array.\n","Uint8ClampedArray.prototype.reduce":"\nUint8ClampedArray.prototype.reduce( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n","Uint8ClampedArray.prototype.reduceRight":"\nUint8ClampedArray.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n","Uint8ClampedArray.prototype.reverse":"\nUint8ClampedArray.prototype.reverse()\n    Reverses an array *in-place*.\n","Uint8ClampedArray.prototype.set":"\nUint8ClampedArray.prototype.set( arr:ArrayLike[, offset:integer] )\n    Sets array elements.\n","Uint8ClampedArray.prototype.slice":"\nUint8ClampedArray.prototype.slice( [begin:integer[, end:integer]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n","Uint8ClampedArray.prototype.some":"\nUint8ClampedArray.prototype.some( predicate:Function[, thisArg:Any] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n","Uint8ClampedArray.prototype.sort":"\nUint8ClampedArray.prototype.sort( [compareFunction:Function] )\n    Sorts an array *in-place*.\n","Uint8ClampedArray.prototype.subarray":"\nUint8ClampedArray.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n","Uint8ClampedArray.prototype.toLocaleString":"\nUint8ClampedArray.prototype.toLocaleString( [locales:string|Array[, \n  options:Object]] )\n    Serializes an array as a locale-specific string.\n","Uint8ClampedArray.prototype.toString":"\nUint8ClampedArray.prototype.toString()\n    Serializes an array as a string.\n","Uint8ClampedArray.prototype.values":"\nUint8ClampedArray.prototype.values()\n    Returns an iterator for iterating over array elements.\n","UINT16_MAX":"\nUINT16_MAX\n    Maximum unsigned 16-bit integer.\n","UINT16_NUM_BYTES":"\nUINT16_NUM_BYTES\n    Size (in bytes) of a 16-bit unsigned integer.\n","Uint16Array":"\nUint16Array()\n    A typed array constructor which returns a typed array representing an array\n    of 16-bit unsigned integers in the platform byte order.\n\nUint16Array( length:integer )\n    Returns a typed array having a specified length.\n\nUint16Array( typedarray:TypedArray )\n    Creates a typed array from another typed array.\n\nUint16Array( obj:Object )\n    Creates a typed array from an array-like object or iterable.\n\nUint16Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a typed array view of an ArrayBuffer.\n","Uint16Array.from":"\nUint16Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n    Creates a new typed array from an array-like object or an iterable.\n","Uint16Array.of":"\nUint16Array.of( element0:number[, element1:number[, ...elementN:number]] )\n    Creates a new typed array from a variable number of arguments.\n","Uint16Array.BYTES_PER_ELEMENT":"\nUint16Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Uint16Array.name":"\nUint16Array.name\n    Typed array constructor name.\n","Uint16Array.prototype.buffer":"\nUint16Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n","Uint16Array.prototype.byteLength":"\nUint16Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n","Uint16Array.prototype.byteOffset":"\nUint16Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n","Uint16Array.prototype.BYTES_PER_ELEMENT":"\nUint16Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Uint16Array.prototype.length":"\nUint16Array.prototype.length\n    Read-only property which returns the number of view elements.\n","Uint16Array.prototype.copyWithin":"\nUint16Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint16Array.prototype.entries":"\nUint16Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","Uint16Array.prototype.every":"\nUint16Array.prototype.every( predicate:Function[, thisArg:Any] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n","Uint16Array.prototype.fill":"\nUint16Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n","Uint16Array.prototype.filter":"\nUint16Array.prototype.filter( predicate:Function[, thisArg:Any] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n","Uint16Array.prototype.find":"\nUint16Array.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n","Uint16Array.prototype.findIndex":"\nUint16Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n","Uint16Array.prototype.forEach":"\nUint16Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n    Invokes a callback for each array element.\n","Uint16Array.prototype.includes":"\nUint16Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a search element.\n","Uint16Array.prototype.indexOf":"\nUint16Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n","Uint16Array.prototype.join":"\nUint16Array.prototype.join( [separator:string] )\n    Serializes an array by joining all array elements as a string.\n","Uint16Array.prototype.keys":"\nUint16Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n","Uint16Array.prototype.lastIndexOf":"\nUint16Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n","Uint16Array.prototype.map":"\nUint16Array.prototype.map( fcn:Function[, thisArg:Any] )\n    Maps each array element to an element in a new typed array.\n","Uint16Array.prototype.reduce":"\nUint16Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n","Uint16Array.prototype.reduceRight":"\nUint16Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n","Uint16Array.prototype.reverse":"\nUint16Array.prototype.reverse()\n    Reverses an array *in-place*.\n","Uint16Array.prototype.set":"\nUint16Array.prototype.set( arr:ArrayLike[, offset:integer] )\n    Sets array elements.\n","Uint16Array.prototype.slice":"\nUint16Array.prototype.slice( [begin:integer[, end:integer]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n","Uint16Array.prototype.some":"\nUint16Array.prototype.some( predicate:Function[, thisArg:Any] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n","Uint16Array.prototype.sort":"\nUint16Array.prototype.sort( [compareFunction:Function] )\n    Sorts an array *in-place*.\n","Uint16Array.prototype.subarray":"\nUint16Array.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n","Uint16Array.prototype.toLocaleString":"\nUint16Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n    Serializes an array as a locale-specific string.\n","Uint16Array.prototype.toString":"\nUint16Array.prototype.toString()\n    Serializes an array as a string.\n","Uint16Array.prototype.values":"\nUint16Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n","UINT32_MAX":"\nUINT32_MAX\n    Maximum unsigned 32-bit integer.\n","UINT32_NUM_BYTES":"\nUINT32_NUM_BYTES\n    Size (in bytes) of a 32-bit unsigned integer.\n","Uint32Array":"\nUint32Array()\n    A typed array constructor which returns a typed array representing an array\n    of 32-bit unsigned integers in the platform byte order.\n\nUint32Array( length:integer )\n    Returns a typed array having a specified length.\n\nUint32Array( typedarray:TypedArray )\n    Creates a typed array from another typed array.\n\nUint32Array( obj:Object )\n    Creates a typed array from an array-like object or iterable.\n\nUint32Array( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]] )\n    Returns a typed array view of an ArrayBuffer.\n","Uint32Array.from":"\nUint32Array.from( src:ArrayLike|Iterable[, map:Function[, thisArg:Any]] )\n    Creates a new typed array from an array-like object or an iterable.\n","Uint32Array.of":"\nUint32Array.of( element0:number[, element1:number[, ...elementN:number]] )\n    Creates a new typed array from a variable number of arguments.\n","Uint32Array.BYTES_PER_ELEMENT":"\nUint32Array.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Uint32Array.name":"\nUint32Array.name\n    Typed array constructor name.\n","Uint32Array.prototype.buffer":"\nUint32Array.prototype.buffer\n    Read-only property which returns the ArrayBuffer referenced by the typed\n    array.\n","Uint32Array.prototype.byteLength":"\nUint32Array.prototype.byteLength\n    Read-only property which returns the length (in bytes) of the typed array.\n","Uint32Array.prototype.byteOffset":"\nUint32Array.prototype.byteOffset\n    Read-only property which returns the offset (in bytes) of the typed array\n    from the start of its ArrayBuffer.\n","Uint32Array.prototype.BYTES_PER_ELEMENT":"\nUint32Array.prototype.BYTES_PER_ELEMENT\n    Number of bytes per view element.\n","Uint32Array.prototype.length":"\nUint32Array.prototype.length\n    Read-only property which returns the number of view elements.\n","Uint32Array.prototype.copyWithin":"\nUint32Array.prototype.copyWithin( target:integer, start:integer[, end:integer] )\n    Copies a sequence of elements within the array starting at `start` and\n    ending at `end` (non-inclusive) to the position starting at `target`.\n","Uint32Array.prototype.entries":"\nUint32Array.prototype.entries()\n    Returns an iterator for iterating over array key-value pairs.\n","Uint32Array.prototype.every":"\nUint32Array.prototype.every( predicate:Function[, thisArg:Any] )\n    Tests whether all array elements pass a test implemented by a predicate\n    function.\n","Uint32Array.prototype.fill":"\nUint32Array.prototype.fill( value:number[, start:integer[, end:integer]] )\n    Fills an array from a start index to an end index (non-inclusive) with a\n    provided value.\n","Uint32Array.prototype.filter":"\nUint32Array.prototype.filter( predicate:Function[, thisArg:Any] )\n    Creates a new array which includes those elements for which a predicate\n    function returns a truthy value.\n","Uint32Array.prototype.find":"\nUint32Array.prototype.find( predicate:Function[, thisArg:Any] )\n    Returns the first array element for which a provided predicate function\n    returns a truthy value.\n","Uint32Array.prototype.findIndex":"\nUint32Array.prototype.findIndex( predicate:Function[, thisArg:Any] )\n    Returns the index of the first array element for which a provided predicate\n    function returns a truthy value.\n","Uint32Array.prototype.forEach":"\nUint32Array.prototype.forEach( fcn:Function[, thisArg:Any] )\n    Invokes a callback for each array element.\n","Uint32Array.prototype.includes":"\nUint32Array.prototype.includes( searchElement:number[, fromIndex:integer] )\n    Returns a boolean indicating whether an array includes a search element.\n","Uint32Array.prototype.indexOf":"\nUint32Array.prototype.indexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the first array element strictly equal to a search\n    element.\n","Uint32Array.prototype.join":"\nUint32Array.prototype.join( [separator:string] )\n    Serializes an array by joining all array elements as a string.\n","Uint32Array.prototype.keys":"\nUint32Array.prototype.keys()\n    Returns an iterator for iterating over array keys.\n","Uint32Array.prototype.lastIndexOf":"\nUint32Array.prototype.lastIndexOf( searchElement:number[, fromIndex:integer] )\n    Returns the index of the last array element strictly equal to a search\n    element.\n","Uint32Array.prototype.map":"\nUint32Array.prototype.map( fcn:Function[, thisArg:Any] )\n    Maps each array element to an element in a new typed array.\n","Uint32Array.prototype.reduce":"\nUint32Array.prototype.reduce( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result.\n","Uint32Array.prototype.reduceRight":"\nUint32Array.prototype.reduceRight( fcn:Function[, initialValue:Any] )\n    Applies a function against an accumulator and each element in an array and\n    returns the accumulated result, iterating from right to left.\n","Uint32Array.prototype.reverse":"\nUint32Array.prototype.reverse()\n    Reverses an array *in-place*.\n","Uint32Array.prototype.set":"\nUint32Array.prototype.set( arr:ArrayLike[, offset:integer] )\n    Sets array elements.\n","Uint32Array.prototype.slice":"\nUint32Array.prototype.slice( [begin:integer[, end:integer]] )\n    Copies array elements to a new array with the same underlying data type as\n    the host array.\n","Uint32Array.prototype.some":"\nUint32Array.prototype.some( predicate:Function[, thisArg:Any] )\n    Tests whether at least one array element passes a test implemented by a\n    predicate function.\n","Uint32Array.prototype.sort":"\nUint32Array.prototype.sort( [compareFunction:Function] )\n    Sorts an array *in-place*.\n","Uint32Array.prototype.subarray":"\nUint32Array.prototype.subarray( [begin:integer[, end:integer]] )\n    Creates a new typed array over the same underlying ArrayBuffer and with the\n    same underlying data type as the host array.\n","Uint32Array.prototype.toLocaleString":"\nUint32Array.prototype.toLocaleString( [locales:string|Array[, options:Object]] )\n    Serializes an array as a locale-specific string.\n","Uint32Array.prototype.toString":"\nUint32Array.prototype.toString()\n    Serializes an array as a string.\n","Uint32Array.prototype.values":"\nUint32Array.prototype.values()\n    Returns an iterator for iterating over array elements.\n","umask":"\numask( [mask:integer|string,] [options:Object] )\n    Returns the current process mask, if not provided a mask; otherwise, sets\n    the process mask and returns the previous mask.\n","uncapitalize":"\nuncapitalize( str:string )\n    Lowercases the first character of a string.\n","uncapitalizeKeys":"\nuncapitalizeKeys( obj:Object )\n    Converts the first letter of each object key to lowercase.\n","uncurry":"\nuncurry( fcn:Function[, arity:integer, ][thisArg:any] )\n    Transforms a curried function into a function invoked with multiple\n    arguments.\n","uncurryRight":"\nuncurryRight( fcn:Function[, arity:integer, ][thisArg:any] )\n    Transforms a curried function into a function invoked with multiple\n    arguments.\n","UNICODE_MAX":"\nUNICODE_MAX\n    Maximum Unicode code point.\n","UNICODE_MAX_BMP":"\nUNICODE_MAX_BMP\n    Maximum Unicode code point in the Basic Multilingual Plane (BMP).\n","UnicodeColumnChartSparkline":"\nUnicodeColumnChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n    Returns a sparkline column chart instance.\n","UnicodeLineChartSparkline":"\nUnicodeLineChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n    Returns a sparkline line chart instance.\n","UnicodeSparkline":"\nUnicodeSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n    Returns a Unicode sparkline instance.\n","UnicodeTristateChartSparkline":"\nUnicodeTristateChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n    Returns a sparkline tristate chart instance.\n","UnicodeUpDownChartSparkline":"\nUnicodeUpDownChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n    Returns a sparkline up/down chart instance.\n","UnicodeWinLossChartSparkline":"\nUnicodeWinLossChartSparkline( [data:ArrayLike|ndarray,] [options:Object] )\n    Returns a sparkline win/loss chart instance.\n","unlink":"\nunlink( path:string|Buffer|integer, clbk:Function )\n    Asynchronously removes a directory entry.\n","unlink.sync":"\nunlink.sync( path:string|Buffer|integer )\n    Synchronously removes a directory entry.\n","unshift":"\nunshift( collection:Array|TypedArray|Object, ...items:any )\n    Adds one or more elements to the beginning of a collection.\n","until":"\nuntil( predicate:Function, fcn:Function[, thisArg:any] )\n    Invokes a function until a test condition is true.\n","untilAsync":"\nuntilAsync( predicate:Function, fcn:Function, done:Function[, thisArg:any] )\n    Invokes a function until a test condition is true.\n","untilEach":"\nuntilEach( collection:Array|TypedArray|Object, predicate:Function, \n  fcn:Function[, thisArg:any] )\n    Until a test condition is true, invokes a function for each element in a\n    collection.\n","untilEachRight":"\nuntilEachRight( collection:Array|TypedArray|Object, predicate:Function, \n  fcn:Function[, thisArg:any] )\n    Until a test condition is true, invokes a function for each element in a\n    collection, iterating from right to left.\n","unzip":"\nunzip( arr:Array[, idx:Array<number>] )\n    Unzips a zipped array (i.e., a nested array of tuples).\n","uppercase":"\nuppercase( str:string )\n    Converts a string to uppercase.\n","uppercaseKeys":"\nuppercaseKeys( obj:Object )\n    Converts each object key to uppercase.\n","US_STATES_ABBR":"\nUS_STATES_ABBR()\n    Returns a list of US state two-letter abbreviations in alphabetical order\n    according to state name.\n","US_STATES_CAPITALS":"\nUS_STATES_CAPITALS()\n    Returns a list of US state capitals in alphabetical order according to state\n    name.\n","US_STATES_CAPITALS_NAMES":"\nUS_STATES_CAPITALS_NAMES()\n    Returns an object mapping US state capitals to state names.\n","US_STATES_NAMES":"\nUS_STATES_NAMES()\n    Returns a list of US state names in alphabetical order.\n","US_STATES_NAMES_CAPITALS":"\nUS_STATES_NAMES_CAPITALS()\n    Returns an object mapping US state names to state capitals.\n","utf16ToUTF8Array":"\nutf16ToUTF8Array( str:string )\n    Converts a UTF-16 encoded string to an array of integers using UTF-8\n    encoding.\n","vartest":"\nvartest( x:Array<number>, y:Array<number>[, options:Object] )\n    Computes a two-sample F-test for equal variances.\n","waterfall":"\nwaterfall( fcns:Array<Function>, clbk:Function[, thisArg:any] )\n    Executes functions in series, passing the results of one function as\n    arguments to the next function.\n","waterfall.factory":"\nwaterfall.factory( fcns:Array<Function>, clbk:Function[, thisArg:any] )\n    Returns a reusable waterfall function.\n","WebAssemblyMemory":"\nWebAssemblyMemory( descriptor:Object )\n    WebAssembly memory constructor.\n","WebAssemblyMemory.prototype.buffer":"\nWebAssemblyMemory.prototype.buffer\n    Read-only property which returns the ArrayBuffer (or SharedArrayBuffer)\n    referenced by the memory instance.\n","WebAssemblyMemory.prototype.grow":"\nWebAssemblyMemory.prototype.grow( delta:integer )\n    Increases the size of the memory instance by a specified number of\n    WebAssembly pages (i.e., 64KiB).\n","whileAsync":"\nwhileAsync( predicate:Function, fcn:Function, done:Function[, thisArg:any] )\n    Invokes a function while a test condition is true.\n","whileEach":"\nwhileEach( collection:Array|TypedArray|Object, predicate:Function, \n  fcn:Function[, thisArg:any] )\n    While a test condition is true, invokes a function for each element in a\n    collection.\n","whileEachRight":"\nwhileEachRight( collection:Array|TypedArray|Object, predicate:Function, \n  fcn:Function[, thisArg:any] )\n    While a test condition is true, invokes a function for each element in a\n    collection, iterating from right to left.\n","whilst":"\nwhilst( predicate:Function, fcn:Function[, thisArg:any] )\n    Invokes a function while a test condition is true.\n","wilcoxon":"\nwilcoxon( x:Array|TypedArray[, y:Array|TypedArray][, options:Object] )\n    Computes a one-sample or paired Wilcoxon signed rank test.\n","writableProperties":"\nwritableProperties( value:any )\n    Returns an array of an object's own writable property names and symbols.\n","writablePropertiesIn":"\nwritablePropertiesIn( value:any )\n    Returns an array of an object's own and inherited writable property names\n    and symbols.\n","writablePropertyNames":"\nwritablePropertyNames( value:any )\n    Returns an array of an object's own writable property names.\n","writablePropertyNamesIn":"\nwritablePropertyNamesIn( value:any )\n    Returns an array of an object's own and inherited writable property names.\n","writablePropertySymbols":"\nwritablePropertySymbols( value:any )\n    Returns an array of an object's own writable symbol properties.\n","writablePropertySymbolsIn":"\nwritablePropertySymbolsIn( value:any )\n    Returns an array of an object's own and inherited writable symbol\n    properties.\n","writeFile":"\nwriteFile( file:string|Buffer|integer, data:string|Buffer[, \n  options:Object|string], clbk:Function )\n    Asynchronously writes data to a file.\n","writeFile.sync":"\nwriteFile.sync( file:string|Buffer|integer, data:string|Buffer[, \n  options:Object|string] )\n    Synchronously writes data to a file.\n","zip":"\nzip( ...arr:Array[, options:Object] )\n    Generates array tuples from input arrays.\n","ztest":"\nztest( x:Array<number>, sigma:number[, options:Object] )\n    Computes a one-sample z-test.\n","ztest2":"\nztest2( x:Array<number>, y:Array<number>, sigmax:number, sigmay:number[, \n  options:Object] )\n    Computes a two-sample z-test.\n"}
diff --git a/lib/node_modules/@stdlib/repl/signature/data/data.csv b/lib/node_modules/@stdlib/repl/signature/data/data.csv
index ff7316e2b5c4..4fb771cf71de 100644
--- a/lib/node_modules/@stdlib/repl/signature/data/data.csv
+++ b/lib/node_modules/@stdlib/repl/signature/data/data.csv
@@ -1823,8 +1823,8 @@ base.strided.dnanmeanpn,"base.strided.dnanmeanpn( N, x, stride )"
 base.strided.dnanmeanpn.ndarray,"base.strided.dnanmeanpn.ndarray( N, x, stride, offset )"
 base.strided.dnanmeanpw,"base.strided.dnanmeanpw( N, x, stride )"
 base.strided.dnanmeanpw.ndarray,"base.strided.dnanmeanpw.ndarray( N, x, stride, offset )"
-base.strided.dnanmeanwd,"base.strided.dnanmeanwd( N, x, stride )"
-base.strided.dnanmeanwd.ndarray,"base.strided.dnanmeanwd.ndarray( N, x, stride, offset )"
+base.strided.dnanmeanwd,"base.strided.dnanmeanwd( N, x, strideX )"
+base.strided.dnanmeanwd.ndarray,"base.strided.dnanmeanwd.ndarray( N, x, strideX, offsetX )"
 base.strided.dnanmin,"base.strided.dnanmin( N, x, strideX )"
 base.strided.dnanmin.ndarray,"base.strided.dnanmin.ndarray( N, x, strideX, offsetX )"
 base.strided.dnanminabs,"base.strided.dnanminabs( N, x, strideX )"
@@ -2312,16 +2312,16 @@ base.strided.smeanpw,"base.strided.smeanpw( N, x, stride )"
 base.strided.smeanpw.ndarray,"base.strided.smeanpw.ndarray( N, x, stride, offset )"
 base.strided.smeanwd,"base.strided.smeanwd( N, x, stride )"
 base.strided.smeanwd.ndarray,"base.strided.smeanwd.ndarray( N, x, stride, offset )"
-base.strided.smediansorted,"base.strided.smediansorted( N, x, stride )"
-base.strided.smediansorted.ndarray,"base.strided.smediansorted.ndarray( N, x, stride, offset )"
+base.strided.smediansorted,"base.strided.smediansorted( N, x, strideX )"
+base.strided.smediansorted.ndarray,"base.strided.smediansorted.ndarray( N, x, strideX, offsetX )"
 base.strided.smidrange,"base.strided.smidrange( N, x, strideX )"
 base.strided.smidrange.ndarray,"base.strided.smidrange.ndarray( N, x, strideX, offsetX )"
 base.strided.smin,"base.strided.smin( N, x, strideX )"
 base.strided.smin.ndarray,"base.strided.smin.ndarray( N, x, strideX, offsetX )"
 base.strided.sminabs,"base.strided.sminabs( N, x, strideX )"
 base.strided.sminabs.ndarray,"base.strided.sminabs.ndarray( N, x, strideX, offsetX )"
-base.strided.sminsorted,"base.strided.sminsorted( N, x, stride )"
-base.strided.sminsorted.ndarray,"base.strided.sminsorted.ndarray( N, x, stride, offset )"
+base.strided.sminsorted,"base.strided.sminsorted( N, x, strideX )"
+base.strided.sminsorted.ndarray,"base.strided.sminsorted.ndarray( N, x, strideX, offsetX )"
 base.strided.smskabs,"base.strided.smskabs( N, x, sx, m, sm, y, sy )"
 base.strided.smskabs.ndarray,"base.strided.smskabs.ndarray( N, x, sx, ox, m, sm, om, y, sy, oy )"
 base.strided.smskabs2,"base.strided.smskabs2( N, x, sx, m, sm, y, sy )"
diff --git a/lib/node_modules/@stdlib/repl/signature/data/data.json b/lib/node_modules/@stdlib/repl/signature/data/data.json
index 9928c058303a..75bac2a31cef 100644
--- a/lib/node_modules/@stdlib/repl/signature/data/data.json
+++ b/lib/node_modules/@stdlib/repl/signature/data/data.json
@@ -1 +1 @@
-[["abs","abs( x[, options] )"],["abs.assign","abs.assign( x, y )"],["acartesianPower","acartesianPower( x, n )"],["acartesianProduct","acartesianProduct( x1, x2 )"],["acartesianSquare","acartesianSquare( x )"],["acronym","acronym( str[, options] )"],["aempty","aempty( length[, dtype] )"],["aemptyLike","aemptyLike( x[, dtype] )"],["AFINN_96","AFINN_96()"],["AFINN_111","AFINN_111()"],["afull","afull( length, value[, dtype] )"],["afullLike","afullLike( x[, dtype] )"],["alias2pkg","alias2pkg( alias )"],["alias2related","alias2related( alias )"],["alias2standalone","alias2standalone( alias )"],["aliases","aliases( [namespace] )"],["allocUnsafe","allocUnsafe( size )"],["amskfilter","amskfilter( x, mask )"],["amskput","amskput( x, mask, values[, options] )"],["amskreject","amskreject( x, mask )"],["anans","anans( length[, dtype] )"],["anansLike","anansLike( x[, dtype] )"],["anova1","anova1( x, factor[, options] )"],["ANSCOMBES_QUARTET","ANSCOMBES_QUARTET()"],["any","any( collection )"],["anyBy","anyBy( collection, predicate[, thisArg ] )"],["anyByAsync","anyByAsync( collection, [options,] predicate, done )"],["anyByAsync.factory","anyByAsync.factory( [options,] predicate )"],["anyByRight","anyByRight( collection, predicate[, thisArg ] )"],["anyByRightAsync","anyByRightAsync( collection, [options,] predicate, done )"],["anyByRightAsync.factory","anyByRightAsync.factory( [options,] predicate )"],["anyInBy","anyInBy( object, predicate[, thisArg ] )"],["anyOwnBy","anyOwnBy( object, predicate[, thisArg ] )"],["aones","aones( length[, dtype] )"],["aonesLike","aonesLike( x[, dtype] )"],["aoneTo","aoneTo( n[, dtype] )"],["aoneToLike","aoneToLike( x[, dtype] )"],["APERY","APERY"],["aplace","aplace( x, mask, values[, options] )"],["append","append( collection1, collection2 )"],["aput","aput( x, indices, values[, options] )"],["ARCH","ARCH"],["argumentFunction","argumentFunction( idx )"],["ARGV","ARGV"],["array","array( [buffer,] [options] )"],["array2buffer","array2buffer( arr )"],["array2fancy","array2fancy( x[, options] )"],["array2fancy.factory","array2fancy.factory( [options] )"],["array2fancy.idx","array2fancy.idx( x[, options] )"],["array2iterator","array2iterator( src[, mapFcn[, thisArg]] )"],["array2iteratorRight","array2iteratorRight( src[, mapFcn[, thisArg]] )"],["ArrayBuffer","ArrayBuffer( size )"],["ArrayBuffer.length","ArrayBuffer.length"],["ArrayBuffer.isView","ArrayBuffer.isView( arr )"],["ArrayBuffer.prototype.byteLength","ArrayBuffer.prototype.byteLength"],["ArrayBuffer.prototype.slice","ArrayBuffer.prototype.slice( [start[, end]] )"],["arraybuffer2buffer","arraybuffer2buffer( buf[, byteOffset[, length]] )"],["arrayCtors","arrayCtors( dtype )"],["arrayDataType","arrayDataType( array )"],["arrayDataTypes","arrayDataTypes( [kind] )"],["ArrayIndex","ArrayIndex( x[, options] )"],["ArrayIndex.free","ArrayIndex.free( id )"],["ArrayIndex.get","ArrayIndex.get( id )"],["ArrayIndex.prototype.data","ArrayIndex.prototype.data"],["ArrayIndex.prototype.dtype","ArrayIndex.prototype.dtype"],["ArrayIndex.prototype.id","ArrayIndex.prototype.id"],["ArrayIndex.prototype.isCached","ArrayIndex.prototype.isCached"],["ArrayIndex.prototype.type","ArrayIndex.prototype.type"],["ArrayIndex.prototype.toString","ArrayIndex.prototype.toString()"],["ArrayIndex.prototype.toJSON","ArrayIndex.prototype.toJSON()"],["arrayMinDataType","arrayMinDataType( value )"],["arrayMostlySafeCasts","arrayMostlySafeCasts( [dtype] )"],["arrayNextDataType","arrayNextDataType( [dtype] )"],["arrayPromotionRules","arrayPromotionRules( [dtype1, dtype2] )"],["arraySafeCasts","arraySafeCasts( [dtype] )"],["arraySameKindCasts","arraySameKindCasts( [dtype] )"],["arrayShape","arrayShape( arr )"],["arrayStream","arrayStream( src[, options] )"],["arrayStream.factory","arrayStream.factory( [options] )"],["arrayStream.objectMode","arrayStream.objectMode( src[, options] )"],["arrayview2iterator","arrayview2iterator( src[, begin[, end]][, mapFcn[, thisArg]] )"],["arrayview2iteratorRight","arrayview2iteratorRight( src[, begin[, end]][, mapFcn[, thisArg]] )"],["aslice","aslice( x[, start[, end]] )"],["AsyncIteratorSymbol","AsyncIteratorSymbol"],["atake","atake( x, indices[, options] )"],["azeros","azeros( length[, dtype] )"],["azerosLike","azerosLike( x[, dtype] )"],["azeroTo","azeroTo( n[, dtype] )"],["azeroToLike","azeroToLike( x[, dtype] )"],["bartlettTest","bartlettTest( ...x[, options] )"],["base.abs","base.abs( x )"],["base.abs2","base.abs2( x )"],["base.abs2f","base.abs2f( x )"],["base.absdiff","base.absdiff( x, y )"],["base.absf","base.absf( x )"],["base.acartesianPower","base.acartesianPower( x, n )"],["base.acartesianProduct","base.acartesianProduct( x1, x2 )"],["base.acartesianSquare","base.acartesianSquare( x )"],["base.acos","base.acos( x )"],["base.acosd","base.acosd( x )"],["base.acosf","base.acosf( x )"],["base.acosh","base.acosh( x )"],["base.acot","base.acot( x )"],["base.acotd","base.acotd( x )"],["base.acotf","base.acotf( x )"],["base.acoth","base.acoth( x )"],["base.acovercos","base.acovercos( x )"],["base.acoversin","base.acoversin( x )"],["base.acsc","base.acsc( x )"],["base.acscd","base.acscd( x )"],["base.acscdf","base.acscdf( x )"],["base.acscf","base.acscf( x )"],["base.acsch","base.acsch( x )"],["base.add","base.add( x, y )"],["base.add3","base.add3( x, y, z )"],["base.add4","base.add4( x, y, z, w )"],["base.add5","base.add5( x, y, z, w, u )"],["base.addf","base.addf( x, y )"],["base.afilled","base.afilled( value, len )"],["base.afilled2d","base.afilled2d( value, shape )"],["base.afilled2dBy","base.afilled2dBy( shape, clbk[, thisArg] )"],["base.afilled3d","base.afilled3d( value, shape )"],["base.afilled3dBy","base.afilled3dBy( shape, clbk[, thisArg] )"],["base.afilled4d","base.afilled4d( value, shape )"],["base.afilled4dBy","base.afilled4dBy( shape, clbk[, thisArg] )"],["base.afilled5d","base.afilled5d( value, shape )"],["base.afilled5dBy","base.afilled5dBy( shape, clbk[, thisArg] )"],["base.afilledBy","base.afilledBy( len, clbk[, thisArg] )"],["base.afillednd","base.afillednd( value, shape )"],["base.afilledndBy","base.afilledndBy( shape, clbk[, thisArg] )"],["base.afilter","base.afilter( x, predicate[, thisArg] )"],["base.afirst","base.afirst( arr )"],["base.aflatten","base.aflatten( x, shape, colexicographic )"],["base.aflatten.assign","base.aflatten.assign( x, shape, colexicographic, out, stride, offset )"],["base.aflatten2d","base.aflatten2d( x, shape, colexicographic )"],["base.aflatten2d.assign","base.aflatten2d.assign( x, shape, colexicographic, out, stride, offset )"],["base.aflatten2dBy","base.aflatten2dBy( x, shape, colex, clbk[, thisArg] )"],["base.aflatten2dBy.assign","base.aflatten2dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )"],["base.aflatten3d","base.aflatten3d( x, shape, colexicographic 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value )"],["isPositiveNumberArray.primitives","isPositiveNumberArray.primitives( value )"],["isPositiveNumberArray.objects","isPositiveNumberArray.objects( value )"],["isPositiveZero","isPositiveZero( value )"],["isPositiveZero.isPrimitive","isPositiveZero.isPrimitive( value )"],["isPositiveZero.isObject","isPositiveZero.isObject( value )"],["isPrime","isPrime( value )"],["isPrime.isPrimitive","isPrime.isPrimitive( value )"],["isPrime.isObject","isPrime.isObject( value )"],["isPrimitive","isPrimitive( value )"],["isPrimitiveArray","isPrimitiveArray( value )"],["isPRNGLike","isPRNGLike( value )"],["isProbability","isProbability( value )"],["isProbability.isPrimitive","isProbability.isPrimitive( value )"],["isProbability.isObject","isProbability.isObject( value )"],["isProbabilityArray","isProbabilityArray( value )"],["isProbabilityArray.primitives","isProbabilityArray.primitives( value )"],["isProbabilityArray.objects","isProbabilityArray.objects( value 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)"],["isUint8ClampedArray","isUint8ClampedArray( value )"],["isUint16Array","isUint16Array( value )"],["isUint32Array","isUint32Array( value )"],["isUNCPath","isUNCPath( value )"],["isUndefined","isUndefined( value )"],["isUndefinedOrNull","isUndefinedOrNull( value )"],["isUnityProbabilityArray","isUnityProbabilityArray( value )"],["isUppercase","isUppercase( value )"],["isURI","isURI( value )"],["isURIError","isURIError( value )"],["isVectorLike","isVectorLike( value )"],["isWebAssemblyMemory","isWebAssemblyMemory( value )"],["isWellFormedString","isWellFormedString( str )"],["isWellFormedString.isPrimitive","isWellFormedString.isPrimitive( str )"],["isWellFormedString.isObject","isWellFormedString.isObject( str )"],["isWhitespace","isWhitespace( str )"],["isWritableProperty","isWritableProperty( value, property )"],["isWritablePropertyIn","isWritablePropertyIn( value, property )"],["isWriteOnlyProperty","isWriteOnlyProperty( value, property 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mapFcn[, thisArg]] )"],["iterator2arrayviewRight","iterator2arrayviewRight( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )"],["iteratorStream","iteratorStream( iterator[, options] )"],["iteratorStream.factory","iteratorStream.factory( [options] )"],["iteratorStream.objectMode","iteratorStream.objectMode( iterator[, options] )"],["IteratorSymbol","IteratorSymbol"],["iterAvercos","iterAvercos( iterator )"],["iterAversin","iterAversin( iterator )"],["iterawgn","iterawgn( iterator, sigma[, options] )"],["iterawln","iterawln( iterator, sigma[, options] )"],["iterawun","iterawun( iterator, sigma[, options] )"],["iterBartlettHannPulse","iterBartlettHannPulse( [options] )"],["iterBartlettPulse","iterBartlettPulse( [options] )"],["iterBesselj0","iterBesselj0( iterator )"],["iterBesselj1","iterBesselj1( iterator )"],["iterBessely0","iterBessely0( iterator )"],["iterBessely1","iterBessely1( iterator )"],["iterBeta","iterBeta( x, y )"],["iterBetaln","iterBetaln( x, y )"],["iterBinet","iterBinet( iterator )"],["iterCbrt","iterCbrt( iterator )"],["iterCeil","iterCeil( iterator )"],["iterCeil2","iterCeil2( iterator )"],["iterCeil10","iterCeil10( iterator )"],["iterCompositesSeq","iterCompositesSeq( [options] )"],["iterConcat","iterConcat( iter0, ...iterator )"],["iterConstant","iterConstant( value[, options] )"],["iterContinuedFraction","iterContinuedFraction( iterator[, options] )"],["iterContinuedFractionSeq","iterContinuedFractionSeq( x[, options] )"],["iterCos","iterCos( iterator )"],["iterCosh","iterCosh( iterator )"],["iterCosineWave","iterCosineWave( [options] )"],["iterCosm1","iterCosm1( iterator )"],["iterCospi","iterCospi( iterator )"],["iterCounter","iterCounter( iterator )"],["iterCovercos","iterCovercos( iterator )"],["iterCoversin","iterCoversin( iterator )"],["iterCubesSeq","iterCubesSeq( [options] )"],["itercugmean","itercugmean( iterator )"],["itercuhmean","itercuhmean( iterator )"],["itercumax","itercumax( iterator )"],["itercumaxabs","itercumaxabs( iterator )"],["itercumean","itercumean( iterator )"],["itercumeanabs","itercumeanabs( iterator )"],["itercumeanabs2","itercumeanabs2( iterator )"],["itercumidrange","itercumidrange( iterator )"],["itercumin","itercumin( iterator )"],["itercuminabs","itercuminabs( iterator )"],["itercuprod","itercuprod( iterator )"],["itercurange","itercurange( iterator )"],["itercusum","itercusum( iterator )"],["itercusumabs","itercusumabs( iterator )"],["itercusumabs2","itercusumabs2( iterator )"],["iterDatespace","iterDatespace( start, stop[, N][, options] )"],["iterDedupe","iterDedupe( iterator[, limit] )"],["iterDedupeBy","iterDedupeBy( iterator, [limit,] fcn )"],["iterDeg2rad","iterDeg2rad( iterator )"],["iterDigamma","iterDigamma( iterator )"],["iterDiracComb","iterDiracComb( [options] )"],["iterDiracDelta","iterDiracDelta( iterator )"],["iterDivide","iterDivide( iter0, ...iterator )"],["iterDoWhileEach","iterDoWhileEach( iterator, predicate, fcn[, thisArg] )"],["iterEllipe","iterEllipe( iterator )"],["iterEllipk","iterEllipk( iterator )"],["iterEmpty","iterEmpty()"],["iterErf","iterErf( iterator )"],["iterErfc","iterErfc( iterator )"],["iterErfcinv","iterErfcinv( iterator )"],["iterErfinv","iterErfinv( iterator )"],["iterEta","iterEta( iterator )"],["iterEvenIntegersSeq","iterEvenIntegersSeq( [options] )"],["iterEvery","iterEvery( iterator )"],["iterEveryBy","iterEveryBy( iterator, predicate[, thisArg ] )"],["iterExp","iterExp( iterator )"],["iterExp2","iterExp2( iterator )"],["iterExp10","iterExp10( iterator )"],["iterExpit","iterExpit( iterator )"],["iterExpm1","iterExpm1( iterator )"],["iterExpm1rel","iterExpm1rel( iterator )"],["iterFactorial","iterFactorial( iterator )"],["iterFactorialln","iterFactorialln( iterator )"],["iterFactorialsSeq","iterFactorialsSeq( [options] )"],["iterFibonacciSeq","iterFibonacciSeq( [options] )"],["iterFifthPowersSeq","iterFifthPowersSeq( [options] )"],["iterFill","iterFill( iterator, value[, begin[, end]] )"],["iterFilter","iterFilter( iterator, predicate[, thisArg] )"],["iterFilterMap","iterFilterMap( iterator, fcn[, thisArg] )"],["iterFirst","iterFirst( iterator )"],["iterFlatTopPulse","iterFlatTopPulse( [options] )"],["iterFloor","iterFloor( iterator )"],["iterFloor2","iterFloor2( iterator )"],["iterFloor10","iterFloor10( iterator )"],["iterFlow","iterFlow( methods )"],["iterForEach","iterForEach( iterator, fcn[, thisArg] )"],["iterFourthPowersSeq","iterFourthPowersSeq( [options] )"],["iterFresnelc","iterFresnelc( iterator )"],["iterFresnels","iterFresnels( iterator )"],["iterGamma","iterGamma( iterator )"],["iterGamma1pm1","iterGamma1pm1( iterator )"],["iterGammaln","iterGammaln( iterator )"],["iterHacovercos","iterHacovercos( iterator )"],["iterHacoversin","iterHacoversin( iterator )"],["iterHannPulse","iterHannPulse( [options] )"],["iterHavercos","iterHavercos( iterator )"],["iterHaversin","iterHaversin( iterator )"],["iterHead","iterHead( iterator, n )"],["iterIncrspace","iterIncrspace( start, stop[, increment] )"],["iterIntegersSeq","iterIntegersSeq( [options] )"],["iterIntersection","iterIntersection( iter0, ...iterator )"],["iterIntersectionByHash","iterIntersectionByHash( iter0, ...iterator, hashFcn[, thisArg] )"],["iterInv","iterInv( iterator )"],["iterLanczosPulse","iterLanczosPulse( [options] )"],["iterLast","iterLast( iterator )"],["iterLength","iterLength( iterator )"],["iterLinspace","iterLinspace( start, stop[, N] )"],["iterLn","iterLn( iterator )"],["iterLog","iterLog( x, b )"],["iterLog1mexp","iterLog1mexp( iterator )"],["iterLog1p","iterLog1p( iterator )"],["iterLog1pexp","iterLog1pexp( iterator )"],["iterLog2","iterLog2( iterator )"],["iterLog10","iterLog10( iterator )"],["iterLogit","iterLogit( iterator )"],["iterLogspace","iterLogspace( start, stop[, N][, options] )"],["iterLucasSeq","iterLucasSeq( [options] )"],["iterMap","iterMap( iterator, fcn[, thisArg] )"],["iterMapN","iterMapN( iter0, ...iterator, fcn[, thisArg] )"],["itermax","itermax( iterator )"],["itermaxabs","itermaxabs( iterator )"],["itermean","itermean( iterator )"],["itermeanabs","itermeanabs( iterator )"],["itermeanabs2","itermeanabs2( iterator )"],["itermidrange","itermidrange( iterator )"],["itermin","itermin( iterator )"],["iterminabs","iterminabs( iterator )"],["itermmax","itermmax( iterator, W )"],["itermmaxabs","itermmaxabs( iterator, W )"],["itermmean","itermmean( iterator, W )"],["itermmeanabs","itermmeanabs( iterator, W )"],["itermmeanabs2","itermmeanabs2( iterator, W )"],["itermmidrange","itermmidrange( iterator, W )"],["itermmin","itermmin( iterator, W )"],["itermminabs","itermminabs( iterator, W )"],["iterMod","iterMod( iter0, ...iterator )"],["itermprod","itermprod( iterator, W )"],["itermrange","itermrange( iterator, W )"],["itermsum","itermsum( iterator, W )"],["itermsumabs","itermsumabs( iterator, W )"],["itermsumabs2","itermsumabs2( iterator, W )"],["iterMultiply","iterMultiply( iter0, ...iterator )"],["iterNegaFibonacciSeq","iterNegaFibonacciSeq( [options] )"],["iterNegaLucasSeq","iterNegaLucasSeq( [options] )"],["iterNegativeEvenIntegersSeq","iterNegativeEvenIntegersSeq( [options] )"],["iterNegativeIntegersSeq","iterNegativeIntegersSeq( [options] )"],["iterNegativeOddIntegersSeq","iterNegativeOddIntegersSeq( [options] )"],["iterNone","iterNone( iterator )"],["iterNoneBy","iterNoneBy( iterator, predicate[, thisArg ] )"],["iterNonFibonacciSeq","iterNonFibonacciSeq( [options] )"],["iterNonNegativeEvenIntegersSeq","iterNonNegativeEvenIntegersSeq( [options] )"],["iterNonNegativeIntegersSeq","iterNonNegativeIntegersSeq( [options] )"],["iterNonPositiveEvenIntegersSeq","iterNonPositiveEvenIntegersSeq( [options] )"],["iterNonPositiveIntegersSeq","iterNonPositiveIntegersSeq( [options] )"],["iterNonSquaresSeq","iterNonSquaresSeq( [options] )"],["iterNth","iterNth( iterator, n )"],["iterOddIntegersSeq","iterOddIntegersSeq( [options] )"],["iterPeriodicSinc","iterPeriodicSinc( n[, options] )"],["iterPipeline","iterPipeline( iterFcn[, ...iterFcn] )"],["iterPop","iterPop( iterator[, clbk[, thisArg]] )"],["iterPositiveEvenIntegersSeq","iterPositiveEvenIntegersSeq( [options] )"],["iterPositiveIntegersSeq","iterPositiveIntegersSeq( [options] )"],["iterPositiveOddIntegersSeq","iterPositiveOddIntegersSeq( [options] )"],["iterPow","iterPow( base, exponent )"],["iterPrimesSeq","iterPrimesSeq( [options] )"],["iterprod","iterprod( iterator )"],["iterPulse","iterPulse( [options] )"],["iterPush","iterPush( iterator, ...items )"],["iterRad2deg","iterRad2deg( iterator )"],["iterRamp","iterRamp( iterator )"],["iterrange","iterrange( iterator )"],["iterReject","iterReject( iterator, predicate[, thisArg] )"],["iterReplicate","iterReplicate( iterator, n )"],["iterReplicateBy","iterReplicateBy( iterator, fcn[, thisArg] )"],["iterRound","iterRound( iterator )"],["iterRound2","iterRound2( iterator )"],["iterRound10","iterRound10( iterator )"],["iterRsqrt","iterRsqrt( iterator )"],["iterSawtoothWave","iterSawtoothWave( [options] )"],["iterShift","iterShift( iterator[, clbk[, thisArg]] )"],["iterSignum","iterSignum( iterator )"],["iterSin","iterSin( iterator )"],["iterSinc","iterSinc( iterator )"],["iterSineWave","iterSineWave( [options] )"],["iterSinh","iterSinh( iterator )"],["iterSinpi","iterSinpi( iterator )"],["iterSlice","iterSlice( iterator[, begin[, end]] )"],["iterSome","iterSome( iterator, n )"],["iterSomeBy","iterSomeBy( iterator, n, predicate[, thisArg ] )"],["iterSpence","iterSpence( iterator )"],["iterSqrt","iterSqrt( iterator )"],["iterSqrt1pm1","iterSqrt1pm1( iterator )"],["iterSquaredTriangularSeq","iterSquaredTriangularSeq( [options] )"],["iterSquaresSeq","iterSquaresSeq( [options] )"],["iterSquareWave","iterSquareWave( [options] )"],["iterstdev","iterstdev( iterator[, mean] )"],["iterStep","iterStep( start, increment[, N] )"],["iterStrided","iterStrided( iterator, stride[, offset[, eager]] )"],["iterStridedBy","iterStridedBy( iterator, fcn[, offset[, eager]][, thisArg] )"],["iterSubtract","iterSubtract( iter0, ...iterator )"],["itersum","itersum( iterator )"],["itersumabs","itersumabs( iterator )"],["itersumabs2","itersumabs2( iterator )"],["iterTan","iterTan( iterator )"],["iterTanh","iterTanh( iterator )"],["iterThunk","iterThunk( iterFcn[, ...args] )"],["iterTriangleWave","iterTriangleWave( [options] )"],["iterTriangularSeq","iterTriangularSeq( [options] )"],["iterTribonnaciSeq","iterTribonnaciSeq( [options] )"],["iterTrigamma","iterTrigamma( iterator )"],["iterTrunc","iterTrunc( iterator )"],["iterTrunc2","iterTrunc2( iterator )"],["iterTrunc10","iterTrunc10( iterator )"],["iterUnion","iterUnion( iter0, ...iterator )"],["iterUnique","iterUnique( iterator )"],["iterUniqueBy","iterUniqueBy( iterator, predicate[, thisArg] )"],["iterUniqueByHash","iterUniqueByHash( iterator, hashFcn[, thisArg] )"],["iterUnitspace","iterUnitspace( start[, stop] )"],["iterUnshift","iterUnshift( iterator, ...items 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)"],["Uint8ClampedArray.prototype.reduce","Uint8ClampedArray.prototype.reduce( fcn[, initialValue] )"],["Uint8ClampedArray.prototype.reduceRight","Uint8ClampedArray.prototype.reduceRight( fcn[, initialValue] )"],["Uint8ClampedArray.prototype.reverse","Uint8ClampedArray.prototype.reverse()"],["Uint8ClampedArray.prototype.set","Uint8ClampedArray.prototype.set( arr[, offset] )"],["Uint8ClampedArray.prototype.slice","Uint8ClampedArray.prototype.slice( [begin[, end]] )"],["Uint8ClampedArray.prototype.some","Uint8ClampedArray.prototype.some( predicate[, thisArg] )"],["Uint8ClampedArray.prototype.sort","Uint8ClampedArray.prototype.sort( [compareFunction] )"],["Uint8ClampedArray.prototype.subarray","Uint8ClampedArray.prototype.subarray( [begin[, end]] )"],["Uint8ClampedArray.prototype.toLocaleString","Uint8ClampedArray.prototype.toLocaleString( [locales[, options]] )"],["Uint8ClampedArray.prototype.toString","Uint8ClampedArray.prototype.toString()"],["Uint8ClampedArray.prototype.values","Uint8ClampedArray.prototype.values()"],["UINT16_MAX","UINT16_MAX"],["UINT16_NUM_BYTES","UINT16_NUM_BYTES"],["Uint16Array","Uint16Array()"],["Uint16Array","Uint16Array( length )"],["Uint16Array","Uint16Array( typedarray )"],["Uint16Array","Uint16Array( obj )"],["Uint16Array","Uint16Array( buffer[, byteOffset[, length]] )"],["Uint16Array.from","Uint16Array.from( src[, map[, thisArg]] )"],["Uint16Array.of","Uint16Array.of( element0[, element1[, ...elementN]] 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)"],["Uint16Array.prototype.reverse","Uint16Array.prototype.reverse()"],["Uint16Array.prototype.set","Uint16Array.prototype.set( arr[, offset] )"],["Uint16Array.prototype.slice","Uint16Array.prototype.slice( [begin[, end]] )"],["Uint16Array.prototype.some","Uint16Array.prototype.some( predicate[, thisArg] )"],["Uint16Array.prototype.sort","Uint16Array.prototype.sort( [compareFunction] )"],["Uint16Array.prototype.subarray","Uint16Array.prototype.subarray( [begin[, end]] )"],["Uint16Array.prototype.toLocaleString","Uint16Array.prototype.toLocaleString( [locales[, options]] )"],["Uint16Array.prototype.toString","Uint16Array.prototype.toString()"],["Uint16Array.prototype.values","Uint16Array.prototype.values()"],["UINT32_MAX","UINT32_MAX"],["UINT32_NUM_BYTES","UINT32_NUM_BYTES"],["Uint32Array","Uint32Array()"],["Uint32Array","Uint32Array( length )"],["Uint32Array","Uint32Array( typedarray )"],["Uint32Array","Uint32Array( obj )"],["Uint32Array","Uint32Array( buffer[, byteOffset[, length]] 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arr[, idx] )"],["uppercase","uppercase( str )"],["uppercaseKeys","uppercaseKeys( obj )"],["US_STATES_ABBR","US_STATES_ABBR()"],["US_STATES_CAPITALS","US_STATES_CAPITALS()"],["US_STATES_CAPITALS_NAMES","US_STATES_CAPITALS_NAMES()"],["US_STATES_NAMES","US_STATES_NAMES()"],["US_STATES_NAMES_CAPITALS","US_STATES_NAMES_CAPITALS()"],["utf16ToUTF8Array","utf16ToUTF8Array( str )"],["vartest","vartest( x, y[, options] )"],["waterfall","waterfall( fcns, clbk[, thisArg] )"],["waterfall.factory","waterfall.factory( fcns, clbk[, thisArg] )"],["WebAssemblyMemory","WebAssemblyMemory( descriptor )"],["WebAssemblyMemory.prototype.buffer","WebAssemblyMemory.prototype.buffer"],["WebAssemblyMemory.prototype.grow","WebAssemblyMemory.prototype.grow( delta )"],["whileAsync","whileAsync( predicate, fcn, done[, thisArg] )"],["whileEach","whileEach( collection, predicate, fcn[, thisArg] )"],["whileEachRight","whileEachRight( collection, predicate, fcn[, thisArg] )"],["whilst","whilst( predicate, fcn[, thisArg] 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arr )"],["array2fancy","array2fancy( x[, options] )"],["array2fancy.factory","array2fancy.factory( [options] )"],["array2fancy.idx","array2fancy.idx( x[, options] )"],["array2iterator","array2iterator( src[, mapFcn[, thisArg]] )"],["array2iteratorRight","array2iteratorRight( src[, mapFcn[, thisArg]] )"],["ArrayBuffer","ArrayBuffer( size )"],["ArrayBuffer.length","ArrayBuffer.length"],["ArrayBuffer.isView","ArrayBuffer.isView( arr )"],["ArrayBuffer.prototype.byteLength","ArrayBuffer.prototype.byteLength"],["ArrayBuffer.prototype.slice","ArrayBuffer.prototype.slice( [start[, end]] )"],["arraybuffer2buffer","arraybuffer2buffer( buf[, byteOffset[, length]] )"],["arrayCtors","arrayCtors( dtype )"],["arrayDataType","arrayDataType( array )"],["arrayDataTypes","arrayDataTypes( [kind] )"],["ArrayIndex","ArrayIndex( x[, options] )"],["ArrayIndex.free","ArrayIndex.free( id )"],["ArrayIndex.get","ArrayIndex.get( id )"],["ArrayIndex.prototype.data","ArrayIndex.prototype.data"],["ArrayIndex.prototype.dtype","ArrayIndex.prototype.dtype"],["ArrayIndex.prototype.id","ArrayIndex.prototype.id"],["ArrayIndex.prototype.isCached","ArrayIndex.prototype.isCached"],["ArrayIndex.prototype.type","ArrayIndex.prototype.type"],["ArrayIndex.prototype.toString","ArrayIndex.prototype.toString()"],["ArrayIndex.prototype.toJSON","ArrayIndex.prototype.toJSON()"],["arrayMinDataType","arrayMinDataType( value )"],["arrayMostlySafeCasts","arrayMostlySafeCasts( [dtype] )"],["arrayNextDataType","arrayNextDataType( [dtype] )"],["arrayPromotionRules","arrayPromotionRules( [dtype1, dtype2] )"],["arraySafeCasts","arraySafeCasts( [dtype] )"],["arraySameKindCasts","arraySameKindCasts( [dtype] )"],["arrayShape","arrayShape( arr )"],["arrayStream","arrayStream( src[, options] )"],["arrayStream.factory","arrayStream.factory( [options] )"],["arrayStream.objectMode","arrayStream.objectMode( src[, options] )"],["arrayview2iterator","arrayview2iterator( src[, begin[, end]][, mapFcn[, thisArg]] )"],["arrayview2iteratorRight","arrayview2iteratorRight( src[, begin[, end]][, mapFcn[, thisArg]] )"],["aslice","aslice( x[, start[, end]] )"],["AsyncIteratorSymbol","AsyncIteratorSymbol"],["atake","atake( x, indices[, options] )"],["azeros","azeros( length[, dtype] )"],["azerosLike","azerosLike( x[, dtype] )"],["azeroTo","azeroTo( n[, dtype] )"],["azeroToLike","azeroToLike( x[, dtype] )"],["bartlettTest","bartlettTest( ...x[, options] )"],["base.abs","base.abs( x )"],["base.abs2","base.abs2( x )"],["base.abs2f","base.abs2f( x )"],["base.absdiff","base.absdiff( x, y )"],["base.absf","base.absf( x )"],["base.acartesianPower","base.acartesianPower( x, n )"],["base.acartesianProduct","base.acartesianProduct( x1, x2 )"],["base.acartesianSquare","base.acartesianSquare( x )"],["base.acos","base.acos( x )"],["base.acosd","base.acosd( x )"],["base.acosf","base.acosf( x )"],["base.acosh","base.acosh( x )"],["base.acot","base.acot( x )"],["base.acotd","base.acotd( x )"],["base.acotf","base.acotf( x )"],["base.acoth","base.acoth( x )"],["base.acovercos","base.acovercos( x )"],["base.acoversin","base.acoversin( x )"],["base.acsc","base.acsc( x )"],["base.acscd","base.acscd( x )"],["base.acscdf","base.acscdf( x )"],["base.acscf","base.acscf( x )"],["base.acsch","base.acsch( x )"],["base.add","base.add( x, y )"],["base.add3","base.add3( x, y, z )"],["base.add4","base.add4( x, y, z, w )"],["base.add5","base.add5( x, y, z, w, u )"],["base.addf","base.addf( x, y )"],["base.afilled","base.afilled( value, len )"],["base.afilled2d","base.afilled2d( value, shape )"],["base.afilled2dBy","base.afilled2dBy( shape, clbk[, thisArg] )"],["base.afilled3d","base.afilled3d( value, shape )"],["base.afilled3dBy","base.afilled3dBy( shape, clbk[, thisArg] )"],["base.afilled4d","base.afilled4d( value, shape )"],["base.afilled4dBy","base.afilled4dBy( shape, clbk[, thisArg] )"],["base.afilled5d","base.afilled5d( value, shape )"],["base.afilled5dBy","base.afilled5dBy( shape, clbk[, thisArg] )"],["base.afilledBy","base.afilledBy( len, clbk[, thisArg] )"],["base.afillednd","base.afillednd( value, shape )"],["base.afilledndBy","base.afilledndBy( shape, clbk[, thisArg] )"],["base.afilter","base.afilter( x, predicate[, thisArg] )"],["base.afirst","base.afirst( arr )"],["base.aflatten","base.aflatten( x, shape, colexicographic )"],["base.aflatten.assign","base.aflatten.assign( x, shape, colexicographic, out, stride, offset )"],["base.aflatten2d","base.aflatten2d( x, shape, colexicographic )"],["base.aflatten2d.assign","base.aflatten2d.assign( x, shape, colexicographic, out, stride, offset )"],["base.aflatten2dBy","base.aflatten2dBy( x, shape, colex, clbk[, thisArg] )"],["base.aflatten2dBy.assign","base.aflatten2dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )"],["base.aflatten3d","base.aflatten3d( x, shape, colexicographic )"],["base.aflatten3d.assign","base.aflatten3d.assign( x, shape, colexicographic, out, stride, offset )"],["base.aflatten3dBy","base.aflatten3dBy( x, shape, colex, clbk[, thisArg] )"],["base.aflatten3dBy.assign","base.aflatten3dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )"],["base.aflatten4d","base.aflatten4d( x, shape, colexicographic )"],["base.aflatten4d.assign","base.aflatten4d.assign( x, shape, colexicographic, out, stride, offset )"],["base.aflatten4dBy","base.aflatten4dBy( x, shape, colex, clbk[, thisArg] )"],["base.aflatten4dBy.assign","base.aflatten4dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )"],["base.aflatten5d","base.aflatten5d( x, shape, colexicographic )"],["base.aflatten5d.assign","base.aflatten5d.assign( x, shape, colexicographic, out, stride, offset )"],["base.aflatten5dBy","base.aflatten5dBy( x, shape, colex, clbk[, thisArg] )"],["base.aflatten5dBy.assign","base.aflatten5dBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )"],["base.aflattenBy","base.aflattenBy( x, shape, colex, clbk[, thisArg] )"],["base.aflattenBy.assign","base.aflattenBy.assign( x, shape, colex, out, stride, offset, clbk[, thisArg] )"],["base.afliplr2d","base.afliplr2d( x )"],["base.afliplr3d","base.afliplr3d( x )"],["base.afliplr4d","base.afliplr4d( x )"],["base.afliplr5d","base.afliplr5d( x )"],["base.aflipud2d","base.aflipud2d( x )"],["base.aflipud3d","base.aflipud3d( x )"],["base.aflipud4d","base.aflipud4d( x )"],["base.aflipud5d","base.aflipud5d( x )"],["base.ahavercos","base.ahavercos( x )"],["base.ahaversin","base.ahaversin( x )"],["base.altcase","base.altcase( str )"],["base.aones","base.aones( len )"],["base.aones2d","base.aones2d( shape )"],["base.aones3d","base.aones3d( shape )"],["base.aones4d","base.aones4d( shape )"],["base.aones5d","base.aones5d( shape )"],["base.aonesnd","base.aonesnd( shape )"],["base.aoneTo","base.aoneTo( n )"],["base.aoneTo.assign","base.aoneTo.assign( out, stride, offset 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)"],["isPropertyKey","isPropertyKey( value )"],["isPrototypeOf","isPrototypeOf( value, proto )"],["isRaggedNestedArray","isRaggedNestedArray( value )"],["isRangeError","isRangeError( value )"],["isReadableProperty","isReadableProperty( value, property )"],["isReadablePropertyIn","isReadablePropertyIn( value, property )"],["isReadOnlyProperty","isReadOnlyProperty( value, property )"],["isReadOnlyPropertyIn","isReadOnlyPropertyIn( value, property )"],["isReadWriteProperty","isReadWriteProperty( value, property )"],["isReadWritePropertyIn","isReadWritePropertyIn( value, property )"],["isReferenceError","isReferenceError( value )"],["isRegExp","isRegExp( value )"],["isRegExpString","isRegExpString( value )"],["isRelativePath","isRelativePath( value )"],["isRelativePath.posix","isRelativePath.posix( value )"],["isRelativePath.win32","isRelativePath.win32( value )"],["isRelativeURI","isRelativeURI( value )"],["isSafeInteger","isSafeInteger( value 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)"],["isSharedArrayBuffer","isSharedArrayBuffer( value )"],["isSkewCentrosymmetricMatrix","isSkewCentrosymmetricMatrix( value )"],["isSkewPersymmetricMatrix","isSkewPersymmetricMatrix( value )"],["isSkewSymmetricMatrix","isSkewSymmetricMatrix( value )"],["isSlice","isSlice( value )"],["isSnakecase","isSnakecase( value )"],["isSquareMatrix","isSquareMatrix( value )"],["isSquareNumber","isSquareNumber( value )"],["isSquareNumber.isPrimitive","isSquareNumber.isPrimitive( value )"],["isSquareNumber.isObject","isSquareNumber.isObject( value )"],["isSquareTriangularNumber","isSquareTriangularNumber( value )"],["isSquareTriangularNumber.isPrimitive","isSquareTriangularNumber.isPrimitive( value )"],["isSquareTriangularNumber.isObject","isSquareTriangularNumber.isObject( value )"],["isStartcase","isStartcase( value )"],["isStrictEqual","isStrictEqual( a, b )"],["isString","isString( value )"],["isString.isPrimitive","isString.isPrimitive( value )"],["isString.isObject","isString.isObject( value )"],["isStringArray","isStringArray( value )"],["isStringArray.primitives","isStringArray.primitives( value )"],["isStringArray.objects","isStringArray.objects( value )"],["isSymbol","isSymbol( value )"],["isSymbolArray","isSymbolArray( value )"],["isSymbolArray.primitives","isSymbolArray.primitives( value )"],["isSymbolArray.objects","isSymbolArray.objects( value )"],["isSymmetricMatrix","isSymmetricMatrix( value )"],["isSyntaxError","isSyntaxError( value )"],["isTriangularNumber","isTriangularNumber( value )"],["isTriangularNumber.isPrimitive","isTriangularNumber.isPrimitive( value )"],["isTriangularNumber.isObject","isTriangularNumber.isObject( value )"],["isTruthy","isTruthy( value )"],["isTruthyArray","isTruthyArray( value )"],["isTypedArray","isTypedArray( value )"],["isTypedArrayLength","isTypedArrayLength( value )"],["isTypedArrayLike","isTypedArrayLike( value )"],["isTypeError","isTypeError( value )"],["isUint8Array","isUint8Array( value )"],["isUint8ClampedArray","isUint8ClampedArray( value )"],["isUint16Array","isUint16Array( value )"],["isUint32Array","isUint32Array( value )"],["isUNCPath","isUNCPath( value )"],["isUndefined","isUndefined( value )"],["isUndefinedOrNull","isUndefinedOrNull( value )"],["isUnityProbabilityArray","isUnityProbabilityArray( value )"],["isUppercase","isUppercase( value )"],["isURI","isURI( value )"],["isURIError","isURIError( value )"],["isVectorLike","isVectorLike( value )"],["isWebAssemblyMemory","isWebAssemblyMemory( value )"],["isWellFormedString","isWellFormedString( str )"],["isWellFormedString.isPrimitive","isWellFormedString.isPrimitive( str )"],["isWellFormedString.isObject","isWellFormedString.isObject( str )"],["isWhitespace","isWhitespace( str )"],["isWritableProperty","isWritableProperty( value, property )"],["isWritablePropertyIn","isWritablePropertyIn( value, property )"],["isWriteOnlyProperty","isWriteOnlyProperty( value, property )"],["isWriteOnlyPropertyIn","isWriteOnlyPropertyIn( value, property )"],["iterAbs","iterAbs( iterator )"],["iterAbs2","iterAbs2( iterator )"],["iterAcos","iterAcos( iterator )"],["iterAcosh","iterAcosh( iterator )"],["iterAcot","iterAcot( iterator )"],["iterAcoth","iterAcoth( iterator )"],["iterAcovercos","iterAcovercos( iterator )"],["iterAcoversin","iterAcoversin( iterator )"],["iterAdd","iterAdd( iter0, ...iterator )"],["iterAdvance","iterAdvance( iterator[, n] )"],["iterAhavercos","iterAhavercos( iterator )"],["iterAhaversin","iterAhaversin( iterator )"],["iterAny","iterAny( iterator )"],["iterAnyBy","iterAnyBy( iterator, predicate[, thisArg ] )"],["iterAsin","iterAsin( iterator )"],["iterAsinh","iterAsinh( iterator )"],["iterAtan","iterAtan( iterator )"],["iterAtan2","iterAtan2( y, x )"],["iterAtanh","iterAtanh( iterator )"],["iterator2array","iterator2array( iterator[, out][, mapFcn[, thisArg]] )"],["iterator2arrayview","iterator2arrayview( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )"],["iterator2arrayviewRight","iterator2arrayviewRight( iterator, dest[, begin[, end]][, mapFcn[, thisArg]] )"],["iteratorStream","iteratorStream( iterator[, options] )"],["iteratorStream.factory","iteratorStream.factory( [options] )"],["iteratorStream.objectMode","iteratorStream.objectMode( iterator[, options] )"],["IteratorSymbol","IteratorSymbol"],["iterAvercos","iterAvercos( iterator )"],["iterAversin","iterAversin( iterator )"],["iterawgn","iterawgn( iterator, sigma[, options] )"],["iterawln","iterawln( iterator, sigma[, options] )"],["iterawun","iterawun( iterator, sigma[, options] )"],["iterBartlettHannPulse","iterBartlettHannPulse( [options] )"],["iterBartlettPulse","iterBartlettPulse( [options] )"],["iterBesselj0","iterBesselj0( iterator )"],["iterBesselj1","iterBesselj1( iterator )"],["iterBessely0","iterBessely0( iterator )"],["iterBessely1","iterBessely1( iterator )"],["iterBeta","iterBeta( x, y )"],["iterBetaln","iterBetaln( x, y )"],["iterBinet","iterBinet( iterator )"],["iterCbrt","iterCbrt( iterator )"],["iterCeil","iterCeil( iterator )"],["iterCeil2","iterCeil2( iterator )"],["iterCeil10","iterCeil10( iterator )"],["iterCompositesSeq","iterCompositesSeq( [options] )"],["iterConcat","iterConcat( iter0, ...iterator )"],["iterConstant","iterConstant( value[, options] )"],["iterContinuedFraction","iterContinuedFraction( iterator[, options] )"],["iterContinuedFractionSeq","iterContinuedFractionSeq( x[, options] )"],["iterCos","iterCos( iterator )"],["iterCosh","iterCosh( iterator )"],["iterCosineWave","iterCosineWave( [options] )"],["iterCosm1","iterCosm1( iterator )"],["iterCospi","iterCospi( iterator )"],["iterCounter","iterCounter( iterator )"],["iterCovercos","iterCovercos( iterator )"],["iterCoversin","iterCoversin( iterator )"],["iterCubesSeq","iterCubesSeq( [options] )"],["itercugmean","itercugmean( iterator )"],["itercuhmean","itercuhmean( iterator )"],["itercumax","itercumax( iterator )"],["itercumaxabs","itercumaxabs( iterator )"],["itercumean","itercumean( iterator )"],["itercumeanabs","itercumeanabs( iterator )"],["itercumeanabs2","itercumeanabs2( iterator )"],["itercumidrange","itercumidrange( iterator )"],["itercumin","itercumin( iterator )"],["itercuminabs","itercuminabs( iterator )"],["itercuprod","itercuprod( iterator )"],["itercurange","itercurange( iterator )"],["itercusum","itercusum( iterator )"],["itercusumabs","itercusumabs( iterator )"],["itercusumabs2","itercusumabs2( iterator )"],["iterDatespace","iterDatespace( start, stop[, N][, options] )"],["iterDedupe","iterDedupe( iterator[, limit] )"],["iterDedupeBy","iterDedupeBy( iterator, [limit,] fcn )"],["iterDeg2rad","iterDeg2rad( iterator )"],["iterDigamma","iterDigamma( iterator )"],["iterDiracComb","iterDiracComb( [options] )"],["iterDiracDelta","iterDiracDelta( iterator )"],["iterDivide","iterDivide( iter0, ...iterator )"],["iterDoWhileEach","iterDoWhileEach( iterator, predicate, fcn[, thisArg] )"],["iterEllipe","iterEllipe( iterator )"],["iterEllipk","iterEllipk( iterator )"],["iterEmpty","iterEmpty()"],["iterErf","iterErf( iterator )"],["iterErfc","iterErfc( iterator )"],["iterErfcinv","iterErfcinv( iterator )"],["iterErfinv","iterErfinv( iterator )"],["iterEta","iterEta( iterator )"],["iterEvenIntegersSeq","iterEvenIntegersSeq( [options] )"],["iterEvery","iterEvery( iterator )"],["iterEveryBy","iterEveryBy( iterator, predicate[, thisArg ] )"],["iterExp","iterExp( iterator )"],["iterExp2","iterExp2( iterator )"],["iterExp10","iterExp10( iterator )"],["iterExpit","iterExpit( iterator )"],["iterExpm1","iterExpm1( iterator )"],["iterExpm1rel","iterExpm1rel( iterator )"],["iterFactorial","iterFactorial( iterator )"],["iterFactorialln","iterFactorialln( iterator )"],["iterFactorialsSeq","iterFactorialsSeq( [options] )"],["iterFibonacciSeq","iterFibonacciSeq( [options] )"],["iterFifthPowersSeq","iterFifthPowersSeq( [options] )"],["iterFill","iterFill( iterator, value[, begin[, end]] )"],["iterFilter","iterFilter( iterator, predicate[, thisArg] )"],["iterFilterMap","iterFilterMap( iterator, fcn[, thisArg] )"],["iterFirst","iterFirst( iterator )"],["iterFlatTopPulse","iterFlatTopPulse( [options] )"],["iterFloor","iterFloor( iterator )"],["iterFloor2","iterFloor2( iterator )"],["iterFloor10","iterFloor10( iterator )"],["iterFlow","iterFlow( methods )"],["iterForEach","iterForEach( iterator, fcn[, thisArg] )"],["iterFourthPowersSeq","iterFourthPowersSeq( [options] )"],["iterFresnelc","iterFresnelc( iterator )"],["iterFresnels","iterFresnels( iterator )"],["iterGamma","iterGamma( iterator )"],["iterGamma1pm1","iterGamma1pm1( iterator )"],["iterGammaln","iterGammaln( iterator )"],["iterHacovercos","iterHacovercos( iterator )"],["iterHacoversin","iterHacoversin( iterator )"],["iterHannPulse","iterHannPulse( [options] )"],["iterHavercos","iterHavercos( iterator )"],["iterHaversin","iterHaversin( iterator )"],["iterHead","iterHead( iterator, n )"],["iterIncrspace","iterIncrspace( start, stop[, increment] )"],["iterIntegersSeq","iterIntegersSeq( [options] )"],["iterIntersection","iterIntersection( iter0, ...iterator )"],["iterIntersectionByHash","iterIntersectionByHash( iter0, ...iterator, hashFcn[, thisArg] )"],["iterInv","iterInv( iterator )"],["iterLanczosPulse","iterLanczosPulse( [options] )"],["iterLast","iterLast( iterator )"],["iterLength","iterLength( iterator )"],["iterLinspace","iterLinspace( start, stop[, N] )"],["iterLn","iterLn( iterator )"],["iterLog","iterLog( x, b )"],["iterLog1mexp","iterLog1mexp( iterator )"],["iterLog1p","iterLog1p( iterator )"],["iterLog1pexp","iterLog1pexp( iterator )"],["iterLog2","iterLog2( iterator )"],["iterLog10","iterLog10( iterator )"],["iterLogit","iterLogit( iterator )"],["iterLogspace","iterLogspace( start, stop[, N][, options] )"],["iterLucasSeq","iterLucasSeq( [options] )"],["iterMap","iterMap( iterator, fcn[, thisArg] )"],["iterMapN","iterMapN( iter0, ...iterator, fcn[, thisArg] )"],["itermax","itermax( iterator )"],["itermaxabs","itermaxabs( iterator )"],["itermean","itermean( iterator )"],["itermeanabs","itermeanabs( iterator )"],["itermeanabs2","itermeanabs2( iterator )"],["itermidrange","itermidrange( iterator )"],["itermin","itermin( iterator )"],["iterminabs","iterminabs( iterator )"],["itermmax","itermmax( iterator, W )"],["itermmaxabs","itermmaxabs( iterator, W )"],["itermmean","itermmean( iterator, W )"],["itermmeanabs","itermmeanabs( iterator, W )"],["itermmeanabs2","itermmeanabs2( iterator, W )"],["itermmidrange","itermmidrange( iterator, W )"],["itermmin","itermmin( iterator, W )"],["itermminabs","itermminabs( iterator, W )"],["iterMod","iterMod( iter0, ...iterator )"],["itermprod","itermprod( iterator, W )"],["itermrange","itermrange( iterator, W )"],["itermsum","itermsum( iterator, W )"],["itermsumabs","itermsumabs( iterator, W )"],["itermsumabs2","itermsumabs2( iterator, W )"],["iterMultiply","iterMultiply( iter0, ...iterator )"],["iterNegaFibonacciSeq","iterNegaFibonacciSeq( [options] )"],["iterNegaLucasSeq","iterNegaLucasSeq( [options] )"],["iterNegativeEvenIntegersSeq","iterNegativeEvenIntegersSeq( [options] )"],["iterNegativeIntegersSeq","iterNegativeIntegersSeq( [options] )"],["iterNegativeOddIntegersSeq","iterNegativeOddIntegersSeq( [options] )"],["iterNone","iterNone( iterator )"],["iterNoneBy","iterNoneBy( iterator, predicate[, thisArg ] )"],["iterNonFibonacciSeq","iterNonFibonacciSeq( [options] )"],["iterNonNegativeEvenIntegersSeq","iterNonNegativeEvenIntegersSeq( [options] )"],["iterNonNegativeIntegersSeq","iterNonNegativeIntegersSeq( [options] )"],["iterNonPositiveEvenIntegersSeq","iterNonPositiveEvenIntegersSeq( [options] )"],["iterNonPositiveIntegersSeq","iterNonPositiveIntegersSeq( [options] )"],["iterNonSquaresSeq","iterNonSquaresSeq( [options] )"],["iterNth","iterNth( iterator, n )"],["iterOddIntegersSeq","iterOddIntegersSeq( [options] )"],["iterPeriodicSinc","iterPeriodicSinc( n[, options] )"],["iterPipeline","iterPipeline( iterFcn[, ...iterFcn] )"],["iterPop","iterPop( iterator[, clbk[, thisArg]] )"],["iterPositiveEvenIntegersSeq","iterPositiveEvenIntegersSeq( [options] )"],["iterPositiveIntegersSeq","iterPositiveIntegersSeq( [options] )"],["iterPositiveOddIntegersSeq","iterPositiveOddIntegersSeq( [options] )"],["iterPow","iterPow( base, exponent )"],["iterPrimesSeq","iterPrimesSeq( [options] )"],["iterprod","iterprod( iterator )"],["iterPulse","iterPulse( [options] )"],["iterPush","iterPush( iterator, ...items )"],["iterRad2deg","iterRad2deg( iterator )"],["iterRamp","iterRamp( iterator )"],["iterrange","iterrange( iterator )"],["iterReject","iterReject( iterator, predicate[, thisArg] )"],["iterReplicate","iterReplicate( iterator, n )"],["iterReplicateBy","iterReplicateBy( iterator, fcn[, thisArg] )"],["iterRound","iterRound( iterator )"],["iterRound2","iterRound2( iterator )"],["iterRound10","iterRound10( iterator )"],["iterRsqrt","iterRsqrt( iterator )"],["iterSawtoothWave","iterSawtoothWave( [options] )"],["iterShift","iterShift( iterator[, clbk[, thisArg]] )"],["iterSignum","iterSignum( iterator )"],["iterSin","iterSin( iterator )"],["iterSinc","iterSinc( iterator )"],["iterSineWave","iterSineWave( [options] )"],["iterSinh","iterSinh( iterator )"],["iterSinpi","iterSinpi( iterator )"],["iterSlice","iterSlice( iterator[, begin[, end]] )"],["iterSome","iterSome( iterator, n )"],["iterSomeBy","iterSomeBy( iterator, n, predicate[, thisArg ] )"],["iterSpence","iterSpence( iterator )"],["iterSqrt","iterSqrt( iterator )"],["iterSqrt1pm1","iterSqrt1pm1( iterator )"],["iterSquaredTriangularSeq","iterSquaredTriangularSeq( [options] )"],["iterSquaresSeq","iterSquaresSeq( [options] )"],["iterSquareWave","iterSquareWave( [options] )"],["iterstdev","iterstdev( iterator[, mean] )"],["iterStep","iterStep( start, increment[, N] )"],["iterStrided","iterStrided( iterator, stride[, offset[, eager]] )"],["iterStridedBy","iterStridedBy( iterator, fcn[, offset[, eager]][, thisArg] )"],["iterSubtract","iterSubtract( iter0, ...iterator )"],["itersum","itersum( iterator )"],["itersumabs","itersumabs( iterator )"],["itersumabs2","itersumabs2( iterator )"],["iterTan","iterTan( iterator )"],["iterTanh","iterTanh( iterator )"],["iterThunk","iterThunk( iterFcn[, ...args] )"],["iterTriangleWave","iterTriangleWave( [options] )"],["iterTriangularSeq","iterTriangularSeq( [options] )"],["iterTribonnaciSeq","iterTribonnaciSeq( [options] )"],["iterTrigamma","iterTrigamma( iterator )"],["iterTrunc","iterTrunc( iterator )"],["iterTrunc2","iterTrunc2( iterator )"],["iterTrunc10","iterTrunc10( iterator )"],["iterUnion","iterUnion( iter0, ...iterator )"],["iterUnique","iterUnique( iterator )"],["iterUniqueBy","iterUniqueBy( iterator, predicate[, thisArg] )"],["iterUniqueByHash","iterUniqueByHash( iterator, hashFcn[, thisArg] )"],["iterUnitspace","iterUnitspace( start[, stop] )"],["iterUnshift","iterUnshift( iterator, ...items )"],["iterUntilEach","iterUntilEach( iterator, predicate, fcn[, thisArg] )"],["itervariance","itervariance( iterator[, mean] )"],["iterVercos","iterVercos( iterator )"],["iterVersin","iterVersin( iterator )"],["iterWhileEach","iterWhileEach( iterator, predicate, fcn[, thisArg] )"],["iterZeta","iterZeta( iterator )"],["joinStream","joinStream( [options] )"],["joinStream.factory","joinStream.factory( [options] )"],["joinStream.objectMode","joinStream.objectMode( [options] )"],["kde2d","kde2d( x, y[, options] )"],["kebabcase","kebabcase( str )"],["keyBy","keyBy( collection, fcn[, thisArg] )"],["keyByRight","keyByRight( collection, fcn[, thisArg] )"],["keysIn","keysIn( obj )"],["kruskalTest","kruskalTest( ...x[, options] )"],["kstest","kstest( x, y[, ...params][, options] )"],["last","last( str[, n][, options] )"],["leveneTest","leveneTest( x[, ...y[, options]] )"],["LinkedList","LinkedList()"],["linspace","linspace( start, stop, length[, options] )"],["linspace.assign","linspace.assign( start, stop, out[, options] )"],["LIU_NEGATIVE_OPINION_WORDS_EN","LIU_NEGATIVE_OPINION_WORDS_EN()"],["LIU_POSITIVE_OPINION_WORDS_EN","LIU_POSITIVE_OPINION_WORDS_EN()"],["LN_HALF","LN_HALF"],["LN_PI","LN_PI"],["LN_SQRT_TWO_PI","LN_SQRT_TWO_PI"],["LN_TWO_PI","LN_TWO_PI"],["LN2","LN2"],["LN10","LN10"],["LOG2E","LOG2E"],["LOG10E","LOG10E"],["logspace","logspace( a, b[, length] )"],["lowercase","lowercase( str )"],["lowercaseKeys","lowercaseKeys( obj )"],["lowess","lowess( x, y[, options] )"],["lpad","lpad( str, len[, pad] )"],["ltrim","ltrim( str )"],["ltrimN","ltrimN( str, n[, chars] )"],["MALE_FIRST_NAMES_EN","MALE_FIRST_NAMES_EN()"],["map","map( arr, fcn[, thisArg] )"],["map.assign","map.assign( arr, out, fcn[, thisArg] )"],["map2","map2( x, y, fcn[, thisArg] )"],["map2.assign","map2.assign( x, y, out, fcn[, thisArg] )"],["map2d","map2d( arr, fcn[, thisArg] )"],["map2Right","map2Right( x, y, fcn[, thisArg] )"],["map2Right.assign","map2Right.assign( x, y, out, fcn[, thisArg] )"],["map3d","map3d( arr, fcn[, thisArg] )"],["map4d","map4d( arr, fcn[, thisArg] )"],["map5d","map5d( arr, fcn[, thisArg] )"],["mapArguments","mapArguments( fcn, clbk[, thisArg] )"],["mapFun","mapFun( fcn, n[, thisArg] )"],["mapFunAsync","mapFunAsync( fcn, n, [options,] done )"],["mapFunAsync.factory","mapFunAsync.factory( [options,] fcn )"],["mapKeys","mapKeys( obj, transform )"],["mapKeysAsync","mapKeysAsync( obj, [options,] transform, done )"],["mapKeysAsync.factory","mapKeysAsync.factory( [options,] transform )"],["mapReduce","mapReduce( arr, initial, mapper, reducer[, thisArg] )"],["mapReduceRight","mapReduceRight( arr, initial, mapper, reducer[, thisArg] )"],["mapRight","mapRight( arr, fcn[, thisArg] )"],["mapRight.assign","mapRight.assign( arr, out, fcn[, thisArg] )"],["mapValues","mapValues( obj, transform )"],["mapValuesAsync","mapValuesAsync( obj, [options,] transform, done )"],["mapValuesAsync.factory","mapValuesAsync.factory( [options,] transform )"],["maskArguments","maskArguments( fcn, mask[, thisArg] )"],["MAX_ARRAY_LENGTH","MAX_ARRAY_LENGTH"],["MAX_TYPED_ARRAY_LENGTH","MAX_TYPED_ARRAY_LENGTH"],["maybeBroadcastArray","maybeBroadcastArray( x, shape )"],["maybeBroadcastArrays","maybeBroadcastArrays( ...arrays )"],["memoize","memoize( fcn[, hashFunction] )"],["merge","merge( target, ...source )"],["merge.factory","merge.factory( options )"],["MILLISECONDS_IN_DAY","MILLISECONDS_IN_DAY"],["MILLISECONDS_IN_HOUR","MILLISECONDS_IN_HOUR"],["MILLISECONDS_IN_MINUTE","MILLISECONDS_IN_MINUTE"],["MILLISECONDS_IN_SECOND","MILLISECONDS_IN_SECOND"],["MILLISECONDS_IN_WEEK","MILLISECONDS_IN_WEEK"],["MINARD_NAPOLEONS_MARCH","MINARD_NAPOLEONS_MARCH( [options] )"],["MINUTES_IN_DAY","MINUTES_IN_DAY"],["MINUTES_IN_HOUR","MINUTES_IN_HOUR"],["MINUTES_IN_WEEK","MINUTES_IN_WEEK"],["minutesInMonth","minutesInMonth( [month[, year]] )"],["minutesInYear","minutesInYear( [value] )"],["MOBY_DICK","MOBY_DICK()"],["MONTH_NAMES_EN","MONTH_NAMES_EN()"],["MONTHS_IN_YEAR","MONTHS_IN_YEAR"],["moveProperty","moveProperty( source, prop, target )"],["MultiSlice","MultiSlice( ...slice )"],["MultiSlice.prototype.ndims","MultiSlice.prototype.ndims"],["MultiSlice.prototype.data","MultiSlice.prototype.data"],["MultiSlice.prototype.toString","MultiSlice.prototype.toString()"],["MultiSlice.prototype.toJSON","MultiSlice.prototype.toJSON()"],["namedtypedtuple","namedtypedtuple( fields[, options] )"],["NAN","NAN"],["naryFunction","naryFunction( fcn, arity[, thisArg] )"],["nativeClass","nativeClass( value )"],["ndarray","ndarray( dtype, buffer, shape, strides, offset, order[, options] )"],["ndarray.prototype.byteLength","ndarray.prototype.byteLength"],["ndarray.prototype.BYTES_PER_ELEMENT","ndarray.prototype.BYTES_PER_ELEMENT"],["ndarray.prototype.data","ndarray.prototype.data"],["ndarray.prototype.dtype","ndarray.prototype.dtype"],["ndarray.prototype.flags","ndarray.prototype.flags"],["ndarray.prototype.length","ndarray.prototype.length"],["ndarray.prototype.ndims","ndarray.prototype.ndims"],["ndarray.prototype.offset","ndarray.prototype.offset"],["ndarray.prototype.order","ndarray.prototype.order"],["ndarray.prototype.shape","ndarray.prototype.shape"],["ndarray.prototype.strides","ndarray.prototype.strides"],["ndarray.prototype.get","ndarray.prototype.get( ...idx )"],["ndarray.prototype.iget","ndarray.prototype.iget( idx )"],["ndarray.prototype.set","ndarray.prototype.set( ...idx, v )"],["ndarray.prototype.iset","ndarray.prototype.iset( idx, v 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)"],["Uint32Array.from","Uint32Array.from( src[, map[, thisArg]] )"],["Uint32Array.of","Uint32Array.of( element0[, element1[, ...elementN]] )"],["Uint32Array.BYTES_PER_ELEMENT","Uint32Array.BYTES_PER_ELEMENT"],["Uint32Array.name","Uint32Array.name"],["Uint32Array.prototype.buffer","Uint32Array.prototype.buffer"],["Uint32Array.prototype.byteLength","Uint32Array.prototype.byteLength"],["Uint32Array.prototype.byteOffset","Uint32Array.prototype.byteOffset"],["Uint32Array.prototype.BYTES_PER_ELEMENT","Uint32Array.prototype.BYTES_PER_ELEMENT"],["Uint32Array.prototype.length","Uint32Array.prototype.length"],["Uint32Array.prototype.copyWithin","Uint32Array.prototype.copyWithin( target, start[, end] )"],["Uint32Array.prototype.entries","Uint32Array.prototype.entries()"],["Uint32Array.prototype.every","Uint32Array.prototype.every( predicate[, thisArg] )"],["Uint32Array.prototype.fill","Uint32Array.prototype.fill( value[, start[, end]] )"],["Uint32Array.prototype.filter","Uint32Array.prototype.filter( predicate[, thisArg] )"],["Uint32Array.prototype.find","Uint32Array.prototype.find( predicate[, thisArg] )"],["Uint32Array.prototype.findIndex","Uint32Array.prototype.findIndex( predicate[, thisArg] )"],["Uint32Array.prototype.forEach","Uint32Array.prototype.forEach( fcn[, thisArg] )"],["Uint32Array.prototype.includes","Uint32Array.prototype.includes( searchElement[, fromIndex] )"],["Uint32Array.prototype.indexOf","Uint32Array.prototype.indexOf( searchElement[, fromIndex] )"],["Uint32Array.prototype.join","Uint32Array.prototype.join( [separator] )"],["Uint32Array.prototype.keys","Uint32Array.prototype.keys()"],["Uint32Array.prototype.lastIndexOf","Uint32Array.prototype.lastIndexOf( searchElement[, fromIndex] )"],["Uint32Array.prototype.map","Uint32Array.prototype.map( fcn[, thisArg] )"],["Uint32Array.prototype.reduce","Uint32Array.prototype.reduce( fcn[, initialValue] )"],["Uint32Array.prototype.reduceRight","Uint32Array.prototype.reduceRight( fcn[, initialValue] )"],["Uint32Array.prototype.reverse","Uint32Array.prototype.reverse()"],["Uint32Array.prototype.set","Uint32Array.prototype.set( arr[, offset] )"],["Uint32Array.prototype.slice","Uint32Array.prototype.slice( [begin[, end]] )"],["Uint32Array.prototype.some","Uint32Array.prototype.some( predicate[, thisArg] )"],["Uint32Array.prototype.sort","Uint32Array.prototype.sort( [compareFunction] )"],["Uint32Array.prototype.subarray","Uint32Array.prototype.subarray( [begin[, end]] )"],["Uint32Array.prototype.toLocaleString","Uint32Array.prototype.toLocaleString( [locales[, options]] )"],["Uint32Array.prototype.toString","Uint32Array.prototype.toString()"],["Uint32Array.prototype.values","Uint32Array.prototype.values()"],["umask","umask( [mask,] [options] )"],["uncapitalize","uncapitalize( str )"],["uncapitalizeKeys","uncapitalizeKeys( obj )"],["uncurry","uncurry( fcn[, arity, ][thisArg] )"],["uncurryRight","uncurryRight( fcn[, arity, ][thisArg] )"],["UNICODE_MAX","UNICODE_MAX"],["UNICODE_MAX_BMP","UNICODE_MAX_BMP"],["UnicodeColumnChartSparkline","UnicodeColumnChartSparkline( [data,] [options] )"],["UnicodeLineChartSparkline","UnicodeLineChartSparkline( [data,] [options] )"],["UnicodeSparkline","UnicodeSparkline( [data,] [options] )"],["UnicodeTristateChartSparkline","UnicodeTristateChartSparkline( [data,] [options] )"],["UnicodeUpDownChartSparkline","UnicodeUpDownChartSparkline( [data,] [options] )"],["UnicodeWinLossChartSparkline","UnicodeWinLossChartSparkline( [data,] [options] )"],["unlink","unlink( path, clbk )"],["unlink.sync","unlink.sync( path )"],["unshift","unshift( collection, ...items )"],["until","until( predicate, fcn[, thisArg] )"],["untilAsync","untilAsync( predicate, fcn, done[, thisArg] )"],["untilEach","untilEach( collection, predicate, fcn[, thisArg] )"],["untilEachRight","untilEachRight( collection, predicate, fcn[, thisArg] )"],["unzip","unzip( arr[, idx] )"],["uppercase","uppercase( str )"],["uppercaseKeys","uppercaseKeys( obj )"],["US_STATES_ABBR","US_STATES_ABBR()"],["US_STATES_CAPITALS","US_STATES_CAPITALS()"],["US_STATES_CAPITALS_NAMES","US_STATES_CAPITALS_NAMES()"],["US_STATES_NAMES","US_STATES_NAMES()"],["US_STATES_NAMES_CAPITALS","US_STATES_NAMES_CAPITALS()"],["utf16ToUTF8Array","utf16ToUTF8Array( str )"],["vartest","vartest( x, y[, options] )"],["waterfall","waterfall( fcns, clbk[, thisArg] )"],["waterfall.factory","waterfall.factory( fcns, clbk[, thisArg] )"],["WebAssemblyMemory","WebAssemblyMemory( descriptor )"],["WebAssemblyMemory.prototype.buffer","WebAssemblyMemory.prototype.buffer"],["WebAssemblyMemory.prototype.grow","WebAssemblyMemory.prototype.grow( delta )"],["whileAsync","whileAsync( predicate, fcn, done[, thisArg] )"],["whileEach","whileEach( collection, predicate, fcn[, thisArg] )"],["whileEachRight","whileEachRight( collection, predicate, fcn[, thisArg] )"],["whilst","whilst( predicate, fcn[, thisArg] )"],["wilcoxon","wilcoxon( x[, y][, options] )"],["writableProperties","writableProperties( value )"],["writablePropertiesIn","writablePropertiesIn( value )"],["writablePropertyNames","writablePropertyNames( value )"],["writablePropertyNamesIn","writablePropertyNamesIn( value )"],["writablePropertySymbols","writablePropertySymbols( value )"],["writablePropertySymbolsIn","writablePropertySymbolsIn( value )"],["writeFile","writeFile( file, data[, options], clbk )"],["writeFile.sync","writeFile.sync( file, data[, options] )"],["zip","zip( ...arr[, options] )"],["ztest","ztest( x, sigma[, options] )"],["ztest2","ztest2( x, y, sigmax, sigmay[, options] )"]]
diff --git a/lib/node_modules/@stdlib/repl/typed-signature/data/data.csv b/lib/node_modules/@stdlib/repl/typed-signature/data/data.csv
index 4815c0210dc2..7eb782b3127f 100644
--- a/lib/node_modules/@stdlib/repl/typed-signature/data/data.csv
+++ b/lib/node_modules/@stdlib/repl/typed-signature/data/data.csv
@@ -1823,8 +1823,8 @@ base.strided.dnanmeanpn,"base.strided.dnanmeanpn( N:integer, x:Float64Array, str
 base.strided.dnanmeanpn.ndarray,"base.strided.dnanmeanpn.ndarray( N:integer, x:Float64Array, stride:integer, offset:integer )"
 base.strided.dnanmeanpw,"base.strided.dnanmeanpw( N:integer, x:Float64Array, stride:integer )"
 base.strided.dnanmeanpw.ndarray,"base.strided.dnanmeanpw.ndarray( N:integer, x:Float64Array, stride:integer, offset:integer )"
-base.strided.dnanmeanwd,"base.strided.dnanmeanwd( N:integer, x:Float64Array, stride:integer )"
-base.strided.dnanmeanwd.ndarray,"base.strided.dnanmeanwd.ndarray( N:integer, x:Float64Array, stride:integer, offset:integer )"
+base.strided.dnanmeanwd,"base.strided.dnanmeanwd( N:integer, x:Float64Array, strideX:integer )"
+base.strided.dnanmeanwd.ndarray,"base.strided.dnanmeanwd.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )"
 base.strided.dnanmin,"base.strided.dnanmin( N:integer, x:Float64Array, strideX:integer )"
 base.strided.dnanmin.ndarray,"base.strided.dnanmin.ndarray( N:integer, x:Float64Array, strideX:integer, offsetX:integer )"
 base.strided.dnanminabs,"base.strided.dnanminabs( N:integer, x:Float64Array, strideX:integer )"
@@ -2312,16 +2312,16 @@ base.strided.smeanpw,"base.strided.smeanpw( N:integer, x:Float32Array, stride:in
 base.strided.smeanpw.ndarray,"base.strided.smeanpw.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )"
 base.strided.smeanwd,"base.strided.smeanwd( N:integer, x:Float32Array, stride:integer )"
 base.strided.smeanwd.ndarray,"base.strided.smeanwd.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )"
-base.strided.smediansorted,"base.strided.smediansorted( N:integer, x:Float32Array, stride:integer )"
-base.strided.smediansorted.ndarray,"base.strided.smediansorted.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )"
+base.strided.smediansorted,"base.strided.smediansorted( N:integer, x:Float32Array, strideX:integer )"
+base.strided.smediansorted.ndarray,"base.strided.smediansorted.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"
 base.strided.smidrange,"base.strided.smidrange( N:integer, x:Float32Array, strideX:integer )"
 base.strided.smidrange.ndarray,"base.strided.smidrange.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"
 base.strided.smin,"base.strided.smin( N:integer, x:Float32Array, strideX:integer )"
 base.strided.smin.ndarray,"base.strided.smin.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"
 base.strided.sminabs,"base.strided.sminabs( N:integer, x:Float32Array, strideX:integer )"
 base.strided.sminabs.ndarray,"base.strided.sminabs.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"
-base.strided.sminsorted,"base.strided.sminsorted( N:integer, x:Float32Array, stride:integer )"
-base.strided.sminsorted.ndarray,"base.strided.sminsorted.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )"
+base.strided.sminsorted,"base.strided.sminsorted( N:integer, x:Float32Array, strideX:integer )"
+base.strided.sminsorted.ndarray,"base.strided.sminsorted.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"
 base.strided.smskabs,"base.strided.smskabs( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"
 base.strided.smskabs.ndarray,"base.strided.smskabs.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"
 base.strided.smskabs2,"base.strided.smskabs2( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"
diff --git a/lib/node_modules/@stdlib/repl/typed-signature/data/data.json b/lib/node_modules/@stdlib/repl/typed-signature/data/data.json
index 43bfbef6bad3..fb716ce904cc 100644
--- a/lib/node_modules/@stdlib/repl/typed-signature/data/data.json
+++ b/lib/node_modules/@stdlib/repl/typed-signature/data/data.json
@@ -1 +1 @@
-[["abs","abs( x:ndarray|ArrayLikeObject|number[, options:Object] )"],["abs.assign","abs.assign( x:ndarray|ArrayLikeObject, y:ndarray|ArrayLikeObject )"],["acartesianPower","acartesianPower( x:ArrayLikeObject, n:integer )"],["acartesianProduct","acartesianProduct( x1:ArrayLikeObject, x2:ArrayLikeObject )"],["acartesianSquare","acartesianSquare( x:ArrayLikeObject )"],["acronym","acronym( str:string[, options:Object] )"],["aempty","aempty( length:integer[, dtype:string] )"],["aemptyLike","aemptyLike( x:TypedArray|Array[, dtype:string] )"],["AFINN_96","AFINN_96()"],["AFINN_111","AFINN_111()"],["afull","afull( length:integer, value:any[, dtype:string] )"],["afullLike","afullLike( x:TypedArray|Array[, dtype:string] )"],["alias2pkg","alias2pkg( alias:string )"],["alias2related","alias2related( alias:string )"],["alias2standalone","alias2standalone( alias:string )"],["aliases","aliases( [namespace:string] )"],["allocUnsafe","allocUnsafe( size:integer )"],["amskfilter","amskfilter( x:Array|TypedArray|Object, mask:Array|TypedArray|Object )"],["amskput","amskput( x:ArrayLikeObject, mask:ArrayLikeObject, values:ArrayLikeObject[, options:Object] )"],["amskreject","amskreject( x:Array|TypedArray|Object, mask:Array|TypedArray|Object )"],["anans","anans( length:integer[, dtype:string] )"],["anansLike","anansLike( x:TypedArray|Array[, dtype:string] )"],["anova1","anova1( x:Array<number>, factor:Array[, options:Object] )"],["ANSCOMBES_QUARTET","ANSCOMBES_QUARTET()"],["any","any( collection:Array|TypedArray|Object )"],["anyBy","anyBy( collection:Array|TypedArray|Object, predicate:Function[, thisArg:any ] )"],["anyByAsync","anyByAsync( collection:Array|TypedArray|Object, [options:Object,] predicate:Function, done:Function )"],["anyByAsync.factory","anyByAsync.factory( [options:Object,] predicate:Function )"],["anyByRight","anyByRight( collection:Array|TypedArray|Object, predicate:Function[, thisArg:any ] )"],["anyByRightAsync","anyByRightAsync( collection:Array|TypedArray|Object, [options:Object,] predicate:Function, done:Function )"],["anyByRightAsync.factory","anyByRightAsync.factory( [options:Object,] predicate:Function )"],["anyInBy","anyInBy( object:Object, predicate:Function[, thisArg:any ] )"],["anyOwnBy","anyOwnBy( object:Object, predicate:Function[, thisArg:any ] )"],["aones","aones( length:integer[, dtype:string] )"],["aonesLike","aonesLike( x:TypedArray|Array[, dtype:string] )"],["aoneTo","aoneTo( n:integer[, dtype:string] )"],["aoneToLike","aoneToLike( x:TypedArray|Array[, dtype:string] )"],["APERY","APERY"],["aplace","aplace( x:ArrayLikeObject, mask:ArrayLikeObject, values:ArrayLikeObject[, options:Object] )"],["append","append( collection1:Array|TypedArray|Object, collection2:Array|TypedArray|Object )"],["aput","aput( x:ArrayLikeObject, indices:ArrayLikeObject<integer>, values:ArrayLikeObject[, options:Object] )"],["ARCH","ARCH"],["argumentFunction","argumentFunction( idx:integer )"],["ARGV","ARGV"],["array","array( [buffer:Array|TypedArray|Buffer|ndarray,] [options:Object] )"],["array2buffer","array2buffer( arr:Array<integer> )"],["array2fancy","array2fancy( x:Array|TypedArray|Object[, options:Object] )"],["array2fancy.factory","array2fancy.factory( [options:Object] )"],["array2fancy.idx","array2fancy.idx( x:Array|TypedArray|Object[, options:Object] )"],["array2iterator","array2iterator( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )"],["array2iteratorRight","array2iteratorRight( src:ArrayLikeObject[, mapFcn:Function[, thisArg:any]] )"],["ArrayBuffer","ArrayBuffer( size:integer )"],["ArrayBuffer.length","ArrayBuffer.length"],["ArrayBuffer.isView","ArrayBuffer.isView( arr:any )"],["ArrayBuffer.prototype.byteLength","ArrayBuffer.prototype.byteLength"],["ArrayBuffer.prototype.slice","ArrayBuffer.prototype.slice( [start:integer[, end:integer]] )"],["arraybuffer2buffer","arraybuffer2buffer( buf:ArrayBuffer[, byteOffset:integer[, length:integer]] )"],["arrayCtors","arrayCtors( dtype:string )"],["arrayDataType","arrayDataType( array:any )"],["arrayDataTypes","arrayDataTypes( [kind:string] )"],["ArrayIndex","ArrayIndex( x:Array|TypedArray|Object[, options:Object] )"],["ArrayIndex.free","ArrayIndex.free( id:string )"],["ArrayIndex.get","ArrayIndex.get( id:string )"],["ArrayIndex.prototype.data","ArrayIndex.prototype.data"],["ArrayIndex.prototype.dtype","ArrayIndex.prototype.dtype"],["ArrayIndex.prototype.id","ArrayIndex.prototype.id"],["ArrayIndex.prototype.isCached","ArrayIndex.prototype.isCached"],["ArrayIndex.prototype.type","ArrayIndex.prototype.type"],["ArrayIndex.prototype.toString","ArrayIndex.prototype.toString()"],["ArrayIndex.prototype.toJSON","ArrayIndex.prototype.toJSON()"],["arrayMinDataType","arrayMinDataType( value:any )"],["arrayMostlySafeCasts","arrayMostlySafeCasts( [dtype:any] )"],["arrayNextDataType","arrayNextDataType( [dtype:string] )"],["arrayPromotionRules","arrayPromotionRules( [dtype1:any, dtype2:any] )"],["arraySafeCasts","arraySafeCasts( [dtype:any] )"],["arraySameKindCasts","arraySameKindCasts( [dtype:any] )"],["arrayShape","arrayShape( arr:ArrayLikeObject )"],["arrayStream","arrayStream( src:ArrayLikeObject[, options:Object] )"],["arrayStream.factory","arrayStream.factory( [options:Object] )"],["arrayStream.objectMode","arrayStream.objectMode( src:ArrayLikeObject[, options:Object] )"],["arrayview2iterator","arrayview2iterator( src:ArrayLikeObject[, begin:integer[, end:integer]][, mapFcn:Function[, thisArg:any]] )"],["arrayview2iteratorRight","arrayview2iteratorRight( src:ArrayLikeObject[, begin:integer[, end:integer]][, mapFcn:Function[, thisArg:any]] )"],["aslice","aslice( x:ArrayLikeObject[, start:integer[, end:integer]] )"],["AsyncIteratorSymbol","AsyncIteratorSymbol"],["atake","atake( x:Array|TypedArray|Object, indices:ArrayLikeObject<integer>[, options:Object] )"],["azeros","azeros( length:integer[, dtype:string] )"],["azerosLike","azerosLike( x:TypedArray|Array[, dtype:string] )"],["azeroTo","azeroTo( n:integer[, dtype:string] )"],["azeroToLike","azeroToLike( x:TypedArray|Array[, dtype:string] )"],["bartlettTest","bartlettTest( ...x:Array[, options:Object] )"],["base.abs","base.abs( x:number )"],["base.abs2","base.abs2( x:number )"],["base.abs2f","base.abs2f( x:number )"],["base.absdiff","base.absdiff( x:number, y:number )"],["base.absf","base.absf( x:number )"],["base.acartesianPower","base.acartesianPower( x:ArrayLikeObject, n:integer )"],["base.acartesianProduct","base.acartesianProduct( x1:ArrayLikeObject, x2:ArrayLikeObject )"],["base.acartesianSquare","base.acartesianSquare( x:ArrayLikeObject )"],["base.acos","base.acos( x:number )"],["base.acosd","base.acosd( x:number )"],["base.acosf","base.acosf( x:number )"],["base.acosh","base.acosh( x:number )"],["base.acot","base.acot( x:number )"],["base.acotd","base.acotd( x:number )"],["base.acotf","base.acotf( x:number )"],["base.acoth","base.acoth( x:number )"],["base.acovercos","base.acovercos( x:number )"],["base.acoversin","base.acoversin( x:number )"],["base.acsc","base.acsc( x:number )"],["base.acscd","base.acscd( x:number )"],["base.acscdf","base.acscdf( x:number )"],["base.acscf","base.acscf( x:number )"],["base.acsch","base.acsch( x:number )"],["base.add","base.add( x:number, y:number )"],["base.add3","base.add3( x:number, y:number, z:number )"],["base.add4","base.add4( x:number, y:number, z:number, w:number )"],["base.add5","base.add5( x:number, y:number, z:number, w:number, u:number )"],["base.addf","base.addf( x:number, y:number )"],["base.afilled","base.afilled( value:any, len:integer )"],["base.afilled2d","base.afilled2d( value:any, shape:Array<integer> )"],["base.afilled2dBy","base.afilled2dBy( shape:Array<integer>, clbk:Function[, thisArg:any] )"],["base.afilled3d","base.afilled3d( value:any, shape:Array<integer> )"],["base.afilled3dBy","base.afilled3dBy( shape:Array<integer>, clbk:Function[, thisArg:any] )"],["base.afilled4d","base.afilled4d( value:any, shape:Array<integer> )"],["base.afilled4dBy","base.afilled4dBy( shape:Array<integer>, clbk:Function[, thisArg:any] )"],["base.afilled5d","base.afilled5d( value:any, shape:Array<integer> )"],["base.afilled5dBy","base.afilled5dBy( shape:Array<integer>, clbk:Function[, thisArg:any] )"],["base.afilledBy","base.afilledBy( len:integer, clbk:Function[, thisArg:any] )"],["base.afillednd","base.afillednd( value:any, shape:Array<integer> )"],["base.afilledndBy","base.afilledndBy( shape:Array<integer>, clbk:Function[, thisArg:any] )"],["base.afilter","base.afilter( x:Array|TypedArray|Object, predicate:Function[, thisArg:any] )"],["base.afirst","base.afirst( arr:ArrayLikeObject )"],["base.aflatten","base.aflatten( x:Array, shape:Array<integer>, colexicographic:boolean )"],["base.aflatten.assign","base.aflatten.assign( x:Array, shape:Array<integer>, colexicographic:boolean, out:Collection, stride:integer, offset:integer )"],["base.aflatten2d","base.aflatten2d( x:Array, shape:Array<integer>, colexicographic:boolean )"],["base.aflatten2d.assign","base.aflatten2d.assign( x:Array, shape:Array<integer>, colexicographic:boolean, out:Collection, stride:integer, offset:integer )"],["base.aflatten2dBy","base.aflatten2dBy( x:Array, shape:Array<integer>, colex:boolean, clbk:Function[, thisArg:any] )"],["base.aflatten2dBy.assign","base.aflatten2dBy.assign( x:Array, shape:Array<integer>, colex:boolean, out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )"],["base.aflatten3d","base.aflatten3d( x:ArrayLikeObject, shape:Array<integer>, colexicographic:boolean )"],["base.aflatten3d.assign","base.aflatten3d.assign( x:Array, shape:Array<integer>, colexicographic:boolean, out:Collection, stride:integer, offset:integer )"],["base.aflatten3dBy","base.aflatten3dBy( x:ArrayLikeObject, shape:Array<integer>, colex:boolean, clbk:Function[, thisArg:any] )"],["base.aflatten3dBy.assign","base.aflatten3dBy.assign( x:Array, shape:Array<integer>, colex:boolean, out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )"],["base.aflatten4d","base.aflatten4d( x:ArrayLikeObject, shape:Array<integer>, colexicographic:boolean )"],["base.aflatten4d.assign","base.aflatten4d.assign( x:Array, shape:Array<integer>, colexicographic:boolean, out:Collection, stride:integer, offset:integer )"],["base.aflatten4dBy","base.aflatten4dBy( x:ArrayLikeObject, shape:Array<integer>, colex:boolean, clbk:Function[, thisArg:any] )"],["base.aflatten4dBy.assign","base.aflatten4dBy.assign( x:Array, shape:Array<integer>, colex:boolean, out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )"],["base.aflatten5d","base.aflatten5d( x:ArrayLikeObject, shape:Array<integer>, colexicographic:boolean )"],["base.aflatten5d.assign","base.aflatten5d.assign( x:Array, shape:Array<integer>, colexicographic:boolean, out:Collection, stride:integer, offset:integer )"],["base.aflatten5dBy","base.aflatten5dBy( x:ArrayLikeObject, shape:Array<integer>, colex:boolean, clbk:Function[, thisArg:any] )"],["base.aflatten5dBy.assign","base.aflatten5dBy.assign( x:Array, shape:Array<integer>, colex:boolean, out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )"],["base.aflattenBy","base.aflattenBy( x:Array, shape:Array<integer>, colex:boolean, clbk:Function[, thisArg:any] )"],["base.aflattenBy.assign","base.aflattenBy.assign( x:Array, shape:Array<integer>, colex:boolean, out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )"],["base.afliplr2d","base.afliplr2d( x:ArrayLikeObject )"],["base.afliplr3d","base.afliplr3d( x:ArrayLikeObject )"],["base.afliplr4d","base.afliplr4d( x:ArrayLikeObject )"],["base.afliplr5d","base.afliplr5d( x:ArrayLikeObject )"],["base.aflipud2d","base.aflipud2d( x:ArrayLikeObject )"],["base.aflipud3d","base.aflipud3d( x:ArrayLikeObject 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dest:ArrayLikeObject[, begin:integer[, end:integer]][, mapFcn:Function[, thisArg:any]] )"],["iteratorStream","iteratorStream( iterator:Object[, options:Object] )"],["iteratorStream.factory","iteratorStream.factory( [options:Object] )"],["iteratorStream.objectMode","iteratorStream.objectMode( iterator:Object[, options:Object] )"],["IteratorSymbol","IteratorSymbol"],["iterAvercos","iterAvercos( iterator:Object )"],["iterAversin","iterAversin( iterator:Object )"],["iterawgn","iterawgn( iterator:Object, sigma:number[, options:Object] )"],["iterawln","iterawln( iterator:Object, sigma:number[, options:Object] )"],["iterawun","iterawun( iterator:Object, sigma:number[, options:Object] )"],["iterBartlettHannPulse","iterBartlettHannPulse( [options:Object] )"],["iterBartlettPulse","iterBartlettPulse( [options:Object] )"],["iterBesselj0","iterBesselj0( iterator:Object )"],["iterBesselj1","iterBesselj1( iterator:Object )"],["iterBessely0","iterBessely0( iterator:Object 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)"],["iterCounter","iterCounter( iterator:Object )"],["iterCovercos","iterCovercos( iterator:Object )"],["iterCoversin","iterCoversin( iterator:Object )"],["iterCubesSeq","iterCubesSeq( [options:Object] )"],["itercugmean","itercugmean( iterator:Object )"],["itercuhmean","itercuhmean( iterator:Object )"],["itercumax","itercumax( iterator:Object )"],["itercumaxabs","itercumaxabs( iterator:Object )"],["itercumean","itercumean( iterator:Object )"],["itercumeanabs","itercumeanabs( iterator:Object )"],["itercumeanabs2","itercumeanabs2( iterator:Object )"],["itercumidrange","itercumidrange( iterator:Object )"],["itercumin","itercumin( iterator:Object )"],["itercuminabs","itercuminabs( iterator:Object )"],["itercuprod","itercuprod( iterator:Object )"],["itercurange","itercurange( iterator:Object )"],["itercusum","itercusum( iterator:Object )"],["itercusumabs","itercusumabs( iterator:Object )"],["itercusumabs2","itercusumabs2( iterator:Object )"],["iterDatespace","iterDatespace( start:integer|string|Date, stop:integer|string|Date[, N:integer][, options:Object] )"],["iterDedupe","iterDedupe( iterator:Object[, limit:integer] )"],["iterDedupeBy","iterDedupeBy( iterator:Object, [limit:integer,] fcn:Function )"],["iterDeg2rad","iterDeg2rad( iterator:Object )"],["iterDigamma","iterDigamma( iterator:Object )"],["iterDiracComb","iterDiracComb( [options:Object] )"],["iterDiracDelta","iterDiracDelta( iterator:Object )"],["iterDivide","iterDivide( iter0:Object, ...iterator:Object )"],["iterDoWhileEach","iterDoWhileEach( iterator:Object, predicate:Function, fcn:Function[, thisArg:any] )"],["iterEllipe","iterEllipe( iterator:Object )"],["iterEllipk","iterEllipk( iterator:Object )"],["iterEmpty","iterEmpty()"],["iterErf","iterErf( iterator:Object )"],["iterErfc","iterErfc( iterator:Object )"],["iterErfcinv","iterErfcinv( iterator:Object )"],["iterErfinv","iterErfinv( iterator:Object )"],["iterEta","iterEta( iterator:Object )"],["iterEvenIntegersSeq","iterEvenIntegersSeq( [options:Object] )"],["iterEvery","iterEvery( iterator:Object )"],["iterEveryBy","iterEveryBy( iterator:Object, predicate:Function[, thisArg:any ] )"],["iterExp","iterExp( iterator:Object )"],["iterExp2","iterExp2( iterator:Object )"],["iterExp10","iterExp10( iterator:Object )"],["iterExpit","iterExpit( iterator:Object )"],["iterExpm1","iterExpm1( iterator:Object )"],["iterExpm1rel","iterExpm1rel( iterator:Object )"],["iterFactorial","iterFactorial( iterator:Object )"],["iterFactorialln","iterFactorialln( iterator:Object )"],["iterFactorialsSeq","iterFactorialsSeq( [options:Object] )"],["iterFibonacciSeq","iterFibonacciSeq( [options:Object] )"],["iterFifthPowersSeq","iterFifthPowersSeq( [options:Object] )"],["iterFill","iterFill( iterator:Object, value:any[, begin:integer[, end:integer]] )"],["iterFilter","iterFilter( iterator:Object, predicate:Function[, thisArg:any] )"],["iterFilterMap","iterFilterMap( iterator:Object, fcn:Function[, thisArg:any] )"],["iterFirst","iterFirst( iterator:Object )"],["iterFlatTopPulse","iterFlatTopPulse( [options:Object] )"],["iterFloor","iterFloor( iterator:Object )"],["iterFloor2","iterFloor2( iterator:Object )"],["iterFloor10","iterFloor10( iterator:Object )"],["iterFlow","iterFlow( methods:Object )"],["iterForEach","iterForEach( iterator:Object, fcn:Function[, thisArg:any] )"],["iterFourthPowersSeq","iterFourthPowersSeq( [options:Object] )"],["iterFresnelc","iterFresnelc( iterator:Object )"],["iterFresnels","iterFresnels( iterator:Object )"],["iterGamma","iterGamma( iterator:Object )"],["iterGamma1pm1","iterGamma1pm1( iterator:Object )"],["iterGammaln","iterGammaln( iterator:Object )"],["iterHacovercos","iterHacovercos( iterator:Object )"],["iterHacoversin","iterHacoversin( iterator:Object )"],["iterHannPulse","iterHannPulse( [options:Object] )"],["iterHavercos","iterHavercos( iterator:Object )"],["iterHaversin","iterHaversin( iterator:Object )"],["iterHead","iterHead( iterator:Object, n:integer )"],["iterIncrspace","iterIncrspace( start:number, stop:number[, increment:number] )"],["iterIntegersSeq","iterIntegersSeq( [options:Object] )"],["iterIntersection","iterIntersection( iter0:Object, ...iterator:Object )"],["iterIntersectionByHash","iterIntersectionByHash( iter0:Object, ...iterator:Object, hashFcn:Function[, thisArg:any] )"],["iterInv","iterInv( iterator:Object )"],["iterLanczosPulse","iterLanczosPulse( [options:Object] )"],["iterLast","iterLast( iterator:Object )"],["iterLength","iterLength( iterator:Object )"],["iterLinspace","iterLinspace( start:number, stop:number[, N:integer] )"],["iterLn","iterLn( iterator:Object )"],["iterLog","iterLog( x:Object|number, b:Object|number )"],["iterLog1mexp","iterLog1mexp( iterator:Object )"],["iterLog1p","iterLog1p( iterator:Object )"],["iterLog1pexp","iterLog1pexp( iterator:Object )"],["iterLog2","iterLog2( iterator:Object )"],["iterLog10","iterLog10( iterator:Object )"],["iterLogit","iterLogit( iterator:Object )"],["iterLogspace","iterLogspace( start:number, stop:number[, N:integer][, options:Object] )"],["iterLucasSeq","iterLucasSeq( [options:Object] )"],["iterMap","iterMap( iterator:Object, fcn:Function[, thisArg:any] )"],["iterMapN","iterMapN( iter0:Object, ...iterator:Object, fcn:Function[, thisArg:any] )"],["itermax","itermax( iterator:Object )"],["itermaxabs","itermaxabs( iterator:Object )"],["itermean","itermean( iterator:Object )"],["itermeanabs","itermeanabs( iterator:Object )"],["itermeanabs2","itermeanabs2( iterator:Object )"],["itermidrange","itermidrange( iterator:Object )"],["itermin","itermin( iterator:Object )"],["iterminabs","iterminabs( iterator:Object )"],["itermmax","itermmax( iterator:Object, W:integer )"],["itermmaxabs","itermmaxabs( iterator:Object, W:integer )"],["itermmean","itermmean( iterator:Object, W:integer )"],["itermmeanabs","itermmeanabs( iterator:Object, W:integer )"],["itermmeanabs2","itermmeanabs2( iterator:Object, W:integer )"],["itermmidrange","itermmidrange( iterator:Object, W:integer )"],["itermmin","itermmin( iterator:Object, W:integer )"],["itermminabs","itermminabs( iterator:Object, W:integer )"],["iterMod","iterMod( iter0:Object, ...iterator:Object )"],["itermprod","itermprod( iterator:Object, W:integer )"],["itermrange","itermrange( iterator:Object, W:integer )"],["itermsum","itermsum( iterator:Object, W:integer )"],["itermsumabs","itermsumabs( iterator:Object, W:integer )"],["itermsumabs2","itermsumabs2( iterator:Object, W:integer )"],["iterMultiply","iterMultiply( iter0:Object, ...iterator:Object )"],["iterNegaFibonacciSeq","iterNegaFibonacciSeq( [options:Object] )"],["iterNegaLucasSeq","iterNegaLucasSeq( [options:Object] )"],["iterNegativeEvenIntegersSeq","iterNegativeEvenIntegersSeq( [options:Object] )"],["iterNegativeIntegersSeq","iterNegativeIntegersSeq( [options:Object] )"],["iterNegativeOddIntegersSeq","iterNegativeOddIntegersSeq( [options:Object] )"],["iterNone","iterNone( iterator:Object )"],["iterNoneBy","iterNoneBy( iterator:Object, predicate:Function[, thisArg:any ] )"],["iterNonFibonacciSeq","iterNonFibonacciSeq( [options:Object] )"],["iterNonNegativeEvenIntegersSeq","iterNonNegativeEvenIntegersSeq( [options:Object] )"],["iterNonNegativeIntegersSeq","iterNonNegativeIntegersSeq( [options:Object] )"],["iterNonPositiveEvenIntegersSeq","iterNonPositiveEvenIntegersSeq( [options:Object] )"],["iterNonPositiveIntegersSeq","iterNonPositiveIntegersSeq( [options:Object] )"],["iterNonSquaresSeq","iterNonSquaresSeq( [options:Object] )"],["iterNth","iterNth( iterator:Object, n:integer )"],["iterOddIntegersSeq","iterOddIntegersSeq( [options:Object] )"],["iterPeriodicSinc","iterPeriodicSinc( n:integer[, options:Object] )"],["iterPipeline","iterPipeline( iterFcn:Function|Array[, ...iterFcn:Function] )"],["iterPop","iterPop( iterator:Object[, clbk:Function[, thisArg:any]] )"],["iterPositiveEvenIntegersSeq","iterPositiveEvenIntegersSeq( [options:Object] )"],["iterPositiveIntegersSeq","iterPositiveIntegersSeq( [options:Object] )"],["iterPositiveOddIntegersSeq","iterPositiveOddIntegersSeq( [options:Object] )"],["iterPow","iterPow( base:Object|number, exponent:Object|number )"],["iterPrimesSeq","iterPrimesSeq( [options:Object] )"],["iterprod","iterprod( iterator:Object )"],["iterPulse","iterPulse( [options:Object] )"],["iterPush","iterPush( iterator:Object, ...items:any )"],["iterRad2deg","iterRad2deg( iterator:Object )"],["iterRamp","iterRamp( iterator:Object )"],["iterrange","iterrange( iterator:Object )"],["iterReject","iterReject( iterator:Object, predicate:Function[, thisArg:any] )"],["iterReplicate","iterReplicate( iterator:Object, n:integer )"],["iterReplicateBy","iterReplicateBy( iterator:Object, fcn:Function[, thisArg:any] )"],["iterRound","iterRound( iterator:Object )"],["iterRound2","iterRound2( iterator:Object )"],["iterRound10","iterRound10( iterator:Object )"],["iterRsqrt","iterRsqrt( iterator:Object )"],["iterSawtoothWave","iterSawtoothWave( [options:Object] )"],["iterShift","iterShift( iterator:Object[, clbk:Function[, thisArg:any]] )"],["iterSignum","iterSignum( iterator:Object )"],["iterSin","iterSin( iterator:Object )"],["iterSinc","iterSinc( iterator:Object )"],["iterSineWave","iterSineWave( [options:Object] )"],["iterSinh","iterSinh( iterator:Object )"],["iterSinpi","iterSinpi( iterator:Object )"],["iterSlice","iterSlice( iterator:Object[, begin:integer[, end:integer]] )"],["iterSome","iterSome( iterator:Object, n:number )"],["iterSomeBy","iterSomeBy( iterator:Object, n:integer, predicate:Function[, thisArg:any ] )"],["iterSpence","iterSpence( iterator:Object )"],["iterSqrt","iterSqrt( iterator:Object )"],["iterSqrt1pm1","iterSqrt1pm1( iterator:Object )"],["iterSquaredTriangularSeq","iterSquaredTriangularSeq( [options:Object] )"],["iterSquaresSeq","iterSquaresSeq( [options:Object] )"],["iterSquareWave","iterSquareWave( [options:Object] )"],["iterstdev","iterstdev( iterator:Object[, mean:number] )"],["iterStep","iterStep( start:number, increment:number[, N:number] )"],["iterStrided","iterStrided( iterator:Object, stride:integer[, offset:integer[, eager:boolean]] )"],["iterStridedBy","iterStridedBy( iterator:Object, fcn:Function[, offset:integer[, eager:boolean]][, thisArg:any] )"],["iterSubtract","iterSubtract( iter0:Object, ...iterator:Object )"],["itersum","itersum( iterator:Object )"],["itersumabs","itersumabs( iterator:Object )"],["itersumabs2","itersumabs2( iterator:Object )"],["iterTan","iterTan( iterator:Object )"],["iterTanh","iterTanh( iterator:Object )"],["iterThunk","iterThunk( iterFcn:Function[, ...args:any] )"],["iterTriangleWave","iterTriangleWave( [options:Object] )"],["iterTriangularSeq","iterTriangularSeq( [options:Object] )"],["iterTribonnaciSeq","iterTribonnaciSeq( [options:Object] )"],["iterTrigamma","iterTrigamma( iterator:Object )"],["iterTrunc","iterTrunc( iterator:Object )"],["iterTrunc2","iterTrunc2( iterator:Object )"],["iterTrunc10","iterTrunc10( iterator:Object )"],["iterUnion","iterUnion( iter0:Object, ...iterator:Object )"],["iterUnique","iterUnique( iterator:Object )"],["iterUniqueBy","iterUniqueBy( iterator:Object, predicate:Function[, thisArg:any] )"],["iterUniqueByHash","iterUniqueByHash( iterator:Object, hashFcn:Function[, thisArg:any] )"],["iterUnitspace","iterUnitspace( start:number[, stop:number] )"],["iterUnshift","iterUnshift( iterator:Object, ...items:any )"],["iterUntilEach","iterUntilEach( iterator:Object, predicate:Function, fcn:Function[, thisArg:any] )"],["itervariance","itervariance( iterator:Object[, mean:number] )"],["iterVercos","iterVercos( iterator:Object )"],["iterVersin","iterVersin( iterator:Object )"],["iterWhileEach","iterWhileEach( iterator:Object, predicate:Function, fcn:Function[, thisArg:any] )"],["iterZeta","iterZeta( iterator:Object )"],["joinStream","joinStream( [options:Object] )"],["joinStream.factory","joinStream.factory( [options:Object] )"],["joinStream.objectMode","joinStream.objectMode( [options:Object] )"],["kde2d","kde2d( x:Array<number>, y:Array<number>[, options:Object] )"],["kebabcase","kebabcase( str:string )"],["keyBy","keyBy( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )"],["keyByRight","keyByRight( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )"],["keysIn","keysIn( obj:any )"],["kruskalTest","kruskalTest( ...x:Array[, options:Object] )"],["kstest","kstest( x:Array<number>, y:Function|string[, ...params:number][, options:Object] )"],["last","last( str:string[, n:integer][, options:Object] )"],["leveneTest","leveneTest( x:Array<number>[, ...y:Array<number>[, options:Object]] )"],["LinkedList","LinkedList()"],["linspace","linspace( start:number|ComplexLike, stop:number|ComplexLike, length:integer[, options:Object] )"],["linspace.assign","linspace.assign( start:number|ComplexLike, stop:number|ComplexLike, out:ArrayLikeObject[, options:Object] )"],["LIU_NEGATIVE_OPINION_WORDS_EN","LIU_NEGATIVE_OPINION_WORDS_EN()"],["LIU_POSITIVE_OPINION_WORDS_EN","LIU_POSITIVE_OPINION_WORDS_EN()"],["LN_HALF","LN_HALF"],["LN_PI","LN_PI"],["LN_SQRT_TWO_PI","LN_SQRT_TWO_PI"],["LN_TWO_PI","LN_TWO_PI"],["LN2","LN2"],["LN10","LN10"],["LOG2E","LOG2E"],["LOG10E","LOG10E"],["logspace","logspace( a:number, b:number[, length:integer] )"],["lowercase","lowercase( str:string )"],["lowercaseKeys","lowercaseKeys( obj:Object )"],["lowess","lowess( x:Array<number>, y:Array<number>[, options:Object] )"],["lpad","lpad( str:string, len:integer[, pad:string] )"],["ltrim","ltrim( str:string )"],["ltrimN","ltrimN( str:string, n:integer[, chars:Array|string] )"],["MALE_FIRST_NAMES_EN","MALE_FIRST_NAMES_EN()"],["map","map( arr:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )"],["map.assign","map.assign( arr:ArrayLikeObject|ndarray, out:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )"],["map2","map2( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )"],["map2.assign","map2.assign( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, out:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )"],["map2d","map2d( arr:ArrayLikeObject<ArrayLikeObject>, fcn:Function[, thisArg:any] )"],["map2Right","map2Right( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )"],["map2Right.assign","map2Right.assign( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, out:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )"],["map3d","map3d( arr:ArrayLikeObject<ArrayLikeObject<ArrayLikeObject>>, fcn:Function[, thisArg:any] )"],["map4d","map4d( arr:ArrayLikeObject<ArrayLikeObject>, fcn:Function[, thisArg:any] )"],["map5d","map5d( arr:ArrayLikeObject<ArrayLikeObject>, fcn:Function[, thisArg:any] )"],["mapArguments","mapArguments( fcn:Function, clbk:Function[, thisArg:any] )"],["mapFun","mapFun( fcn:Function, n:integer[, thisArg:any] )"],["mapFunAsync","mapFunAsync( fcn:Function, n:integer, [options:Object,] done:Function )"],["mapFunAsync.factory","mapFunAsync.factory( [options:Object,] fcn:Function )"],["mapKeys","mapKeys( obj:Object, transform:Function )"],["mapKeysAsync","mapKeysAsync( obj:Object, [options:Object,] transform:Function, done:Function )"],["mapKeysAsync.factory","mapKeysAsync.factory( [options:Object,] transform:Function )"],["mapReduce","mapReduce( arr:ArrayLikeObject|ndarray, initial:any, mapper:Function, reducer:Function[, thisArg:any] )"],["mapReduceRight","mapReduceRight( arr:ArrayLikeObject|ndarray, initial:any, mapper:Function, reducer:Function[, thisArg:any] )"],["mapRight","mapRight( arr:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )"],["mapRight.assign","mapRight.assign( arr:ArrayLikeObject|ndarray, out:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )"],["mapValues","mapValues( obj:Object, transform:Function )"],["mapValuesAsync","mapValuesAsync( obj:Object, [options:Object,] transform:Function, done:Function )"],["mapValuesAsync.factory","mapValuesAsync.factory( [options:Object,] transform:Function )"],["maskArguments","maskArguments( fcn:Function, mask:ArrayLikeObject[, thisArg:any] )"],["MAX_ARRAY_LENGTH","MAX_ARRAY_LENGTH"],["MAX_TYPED_ARRAY_LENGTH","MAX_TYPED_ARRAY_LENGTH"],["maybeBroadcastArray","maybeBroadcastArray( x:ndarray, shape:ArrayLikeObject )"],["maybeBroadcastArrays","maybeBroadcastArrays( ...arrays:ndarray|ArrayLikeObject<ndarray> )"],["memoize","memoize( fcn:Function[, hashFunction:Function] )"],["merge","merge( target:Object, ...source:Object )"],["merge.factory","merge.factory( options:Object )"],["MILLISECONDS_IN_DAY","MILLISECONDS_IN_DAY"],["MILLISECONDS_IN_HOUR","MILLISECONDS_IN_HOUR"],["MILLISECONDS_IN_MINUTE","MILLISECONDS_IN_MINUTE"],["MILLISECONDS_IN_SECOND","MILLISECONDS_IN_SECOND"],["MILLISECONDS_IN_WEEK","MILLISECONDS_IN_WEEK"],["MINARD_NAPOLEONS_MARCH","MINARD_NAPOLEONS_MARCH( [options:Object] )"],["MINUTES_IN_DAY","MINUTES_IN_DAY"],["MINUTES_IN_HOUR","MINUTES_IN_HOUR"],["MINUTES_IN_WEEK","MINUTES_IN_WEEK"],["minutesInMonth","minutesInMonth( [month:string|Date|integer[, year:integer]] )"],["minutesInYear","minutesInYear( [value:integer|Date] )"],["MOBY_DICK","MOBY_DICK()"],["MONTH_NAMES_EN","MONTH_NAMES_EN()"],["MONTHS_IN_YEAR","MONTHS_IN_YEAR"],["moveProperty","moveProperty( source:Object, prop:string, target:Object )"],["MultiSlice","MultiSlice( ...slice )"],["MultiSlice.prototype.ndims","MultiSlice.prototype.ndims"],["MultiSlice.prototype.data","MultiSlice.prototype.data"],["MultiSlice.prototype.toString","MultiSlice.prototype.toString()"],["MultiSlice.prototype.toJSON","MultiSlice.prototype.toJSON()"],["namedtypedtuple","namedtypedtuple( fields:Array<string>[, options:Object] )"],["NAN","NAN"],["naryFunction","naryFunction( fcn:Function, arity:integer[, thisArg:any] )"],["nativeClass","nativeClass( value:any )"],["ndarray","ndarray( dtype:string, buffer:ArrayLikeObject|TypedArray|Buffer, shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, offset:integer, order:string[, options:Object] )"],["ndarray.prototype.byteLength","ndarray.prototype.byteLength"],["ndarray.prototype.BYTES_PER_ELEMENT","ndarray.prototype.BYTES_PER_ELEMENT"],["ndarray.prototype.data","ndarray.prototype.data"],["ndarray.prototype.dtype","ndarray.prototype.dtype"],["ndarray.prototype.flags","ndarray.prototype.flags"],["ndarray.prototype.length","ndarray.prototype.length"],["ndarray.prototype.ndims","ndarray.prototype.ndims"],["ndarray.prototype.offset","ndarray.prototype.offset"],["ndarray.prototype.order","ndarray.prototype.order"],["ndarray.prototype.shape","ndarray.prototype.shape"],["ndarray.prototype.strides","ndarray.prototype.strides"],["ndarray.prototype.get","ndarray.prototype.get( ...idx:integer )"],["ndarray.prototype.iget","ndarray.prototype.iget( idx:integer )"],["ndarray.prototype.set","ndarray.prototype.set( ...idx:integer, v:any )"],["ndarray.prototype.iset","ndarray.prototype.iset( idx:integer, v:any )"],["ndarray.prototype.toString","ndarray.prototype.toString()"],["ndarray.prototype.toJSON","ndarray.prototype.toJSON()"],["ndarray2array","ndarray2array( x:ndarray )"],["ndarray2fancy","ndarray2fancy( x:ndarray[, options:Object] )"],["ndarray2fancy.factory","ndarray2fancy.factory( [options:Object] )"],["ndarray2fancy.idx","ndarray2fancy.idx( x:ndarray[, options:Object] )"],["ndarray2json","ndarray2json( x:ndarray )"],["ndarrayCastingModes","ndarrayCastingModes()"],["ndarrayDataBuffer","ndarrayDataBuffer( x:ndarray )"],["ndarrayDataType","ndarrayDataType( x:ndarray )"],["ndarrayDataTypes","ndarrayDataTypes( [kind:string] )"],["ndarrayDispatch","ndarrayDispatch( fcns:Function|ArrayLikeObject<Function>, types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, nout:integer )"],["ndarrayFlag","ndarrayFlag( x:ndarray, name:string|symbol )"],["ndarrayFlags","ndarrayFlags( x:ndarray )"],["ndarrayIndexModes","ndarrayIndexModes()"],["ndarraylike2ndarray","ndarraylike2ndarray( x:ndarrayLike[, options:Object] )"],["ndarrayMinDataType","ndarrayMinDataType( value:any )"],["ndarrayMostlySafeCasts","ndarrayMostlySafeCasts( [dtype:any] )"],["ndarrayNextDataType","ndarrayNextDataType( [dtype:any] )"],["ndarrayOffset","ndarrayOffset( x:ndarray )"],["ndarrayOrder","ndarrayOrder( x:ndarray )"],["ndarrayOrders","ndarrayOrders()"],["ndarrayPromotionRules","ndarrayPromotionRules( [dtype1:any, dtype2:any] )"],["ndarraySafeCasts","ndarraySafeCasts( [dtype:any] )"],["ndarraySameKindCasts","ndarraySameKindCasts( [dtype:any] )"],["ndarrayShape","ndarrayShape( x:ndarray )"],["ndarrayStride","ndarrayStride( x:ndarray, dim:integer )"],["ndarrayStrides","ndarrayStrides( x:ndarray )"],["ndat","ndat( x:ndarray[, ...indices:integer] )"],["ndempty","ndempty( shape:ArrayLikeObject<integer>|integer[, options:Object] )"],["ndemptyLike","ndemptyLike( x:ndarray[, options:Object] )"],["ndfilter","ndfilter( x:ndarray[, options:Object], predicate:Function[, thisArg:any] )"],["ndfilterMap","ndfilterMap( x:ndarray[, options:Object], fcn:Function[, thisArg:any] )"],["ndforEach","ndforEach( x:ndarray, fcn:Function[, thisArg:any] )"],["ndims","ndims( x:ndarray )"],["ndindex","ndindex( x:ndarray[, options:Object] )"],["ndindex.free","ndindex.free( id:string )"],["ndindex.get","ndindex.get( id:string )"],["ndindex.cartesianIndex","ndindex.cartesianIndex( x:ndarray[, options:Object] )"],["ndindex.linearIndex","ndindex.linearIndex( x:ndarray[, options:Object] 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)"],["random.streams.minstdShuffle","random.streams.minstdShuffle( [options:Object] )"],["random.streams.minstdShuffle.factory","random.streams.minstdShuffle.factory( [options] )"],["random.streams.minstdShuffle.objectMode","random.streams.minstdShuffle.objectMode( [options:Object] )"],["random.streams.mt19937","random.streams.mt19937( [options:Object] )"],["random.streams.mt19937.factory","random.streams.mt19937.factory( [options] )"],["random.streams.mt19937.objectMode","random.streams.mt19937.objectMode( [options:Object] )"],["random.streams.negativeBinomial","random.streams.negativeBinomial( r:number, p:number[, options:Object] )"],["random.streams.negativeBinomial.factory","random.streams.negativeBinomial.factory( [r:number, p:number, ][options:Object] )"],["random.streams.negativeBinomial.objectMode","random.streams.negativeBinomial.objectMode( r:integer, p:number[, options:Object] )"],["random.streams.normal","random.streams.normal( μ:number, σ:number[, options:Object] )"],["random.streams.normal.factory","random.streams.normal.factory( [μ:number, σ:number, ][options:Object] )"],["random.streams.normal.objectMode","random.streams.normal.objectMode( μ:number, σ:number[, options:Object] )"],["random.streams.pareto1","random.streams.pareto1( α:number, β:number[, options:Object] )"],["random.streams.pareto1.factory","random.streams.pareto1.factory( [α:number, β:number, ][options:Object] )"],["random.streams.pareto1.objectMode","random.streams.pareto1.objectMode( α:number, β:number[, options:Object] )"],["random.streams.poisson","random.streams.poisson( λ:number[, options:Object] )"],["random.streams.poisson.factory","random.streams.poisson.factory( [λ:number, ][options:Object] )"],["random.streams.poisson.objectMode","random.streams.poisson.objectMode( λ:number[, options:Object] )"],["random.streams.randi","random.streams.randi( [options:Object] )"],["random.streams.randi.factory","random.streams.randi.factory( [options] )"],["random.streams.randi.objectMode","random.streams.randi.objectMode( [options:Object] )"],["random.streams.randn","random.streams.randn( [options:Object] )"],["random.streams.randn.factory","random.streams.randn.factory( [options] )"],["random.streams.randn.objectMode","random.streams.randn.objectMode( [options:Object] )"],["random.streams.randu","random.streams.randu( [options:Object] )"],["random.streams.randu.factory","random.streams.randu.factory( [options] )"],["random.streams.randu.objectMode","random.streams.randu.objectMode( [options:Object] )"],["random.streams.rayleigh","random.streams.rayleigh( σ:number[, options:Object] )"],["random.streams.rayleigh.factory","random.streams.rayleigh.factory( [σ:number, ][options:Object] )"],["random.streams.rayleigh.objectMode","random.streams.rayleigh.objectMode( σ:number[, options:Object] )"],["random.streams.t","random.streams.t( v:number[, options:Object] )"],["random.streams.t.factory","random.streams.t.factory( [v:number, ][options:Object] )"],["random.streams.t.objectMode","random.streams.t.objectMode( v:number[, options:Object] )"],["random.streams.triangular","random.streams.triangular( a:number, b:number, c:number[, options:Object] )"],["random.streams.triangular.factory","random.streams.triangular.factory( [a:number, b:number, c:number, ][options:Object] )"],["random.streams.triangular.objectMode","random.streams.triangular.objectMode( a:number, b:number, c:number[, options:Object] )"],["random.streams.uniform","random.streams.uniform( a:number, b:number[, options:Object] )"],["random.streams.uniform.factory","random.streams.uniform.factory( [a:number, b:number, ][options:Object] )"],["random.streams.uniform.objectMode","random.streams.uniform.objectMode( a:number, b:number[, options:Object] )"],["random.streams.weibull","random.streams.weibull( k:number, λ:number[, options:Object] )"],["random.streams.weibull.factory","random.streams.weibull.factory( [k:number, λ:number, ][options:Object] 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)"],["random.strided.bernoulli.PRNG","random.strided.bernoulli.PRNG"],["random.strided.bernoulli.seed","random.strided.bernoulli.seed"],["random.strided.bernoulli.seedLength","random.strided.bernoulli.seedLength"],["random.strided.bernoulli.state","random.strided.bernoulli.state"],["random.strided.bernoulli.stateLength","random.strided.bernoulli.stateLength"],["random.strided.bernoulli.byteLength","random.strided.bernoulli.byteLength"],["random.strided.beta","random.strided.beta( N:integer, alpha:ArrayLikeObject, sa:integer, beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.beta.ndarray","random.strided.beta.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.betaprime","random.strided.betaprime( N:integer, alpha:ArrayLikeObject, sa:integer, beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.betaprime.ndarray","random.strided.betaprime.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.chi","random.strided.chi( N:integer, k:ArrayLikeObject, sk:integer, out:ArrayLikeObject, so:integer )"],["random.strided.chi.ndarray","random.strided.chi.ndarray( N:integer, k:ArrayLikeObject, sk:integer, ok:integer, out:ArrayLikeObject, so:integer, oo:integer )"],["random.strided.chi.factory","random.strided.chi.factory( [options:Object] )"],["random.strided.chi.PRNG","random.strided.chi.PRNG"],["random.strided.chi.seed","random.strided.chi.seed"],["random.strided.chi.seedLength","random.strided.chi.seedLength"],["random.strided.chi.state","random.strided.chi.state"],["random.strided.chi.stateLength","random.strided.chi.stateLength"],["random.strided.chi.byteLength","random.strided.chi.byteLength"],["random.strided.chisquare","random.strided.chisquare( N:integer, k:ArrayLikeObject, sk:integer, out:ArrayLikeObject, so:integer )"],["random.strided.chisquare.ndarray","random.strided.chisquare.ndarray( N:integer, k:ArrayLikeObject, sk:integer, ok:integer, out:ArrayLikeObject, so:integer, oo:integer )"],["random.strided.chisquare.factory","random.strided.chisquare.factory( [options:Object] )"],["random.strided.chisquare.PRNG","random.strided.chisquare.PRNG"],["random.strided.chisquare.seed","random.strided.chisquare.seed"],["random.strided.chisquare.seedLength","random.strided.chisquare.seedLength"],["random.strided.chisquare.state","random.strided.chisquare.state"],["random.strided.chisquare.stateLength","random.strided.chisquare.stateLength"],["random.strided.chisquare.byteLength","random.strided.chisquare.byteLength"],["random.strided.cosine","random.strided.cosine( N:integer, mu:ArrayLikeObject, sm:integer, s:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.cosine.ndarray","random.strided.cosine.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, om:integer, s:ArrayLikeObject, ss:integer, os:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.discreteUniform","random.strided.discreteUniform( N:integer, a:ArrayLikeObject, sa:integer, b:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.discreteUniform.ndarray","random.strided.discreteUniform.ndarray( N:integer, a:ArrayLikeObject, sa:integer, oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.exponential","random.strided.exponential( N:integer, lambda:ArrayLikeObject, sl:integer, out:ArrayLikeObject, so:integer )"],["random.strided.exponential.ndarray","random.strided.exponential.ndarray( N:integer, lambda:ArrayLikeObject, sl:integer, ol:integer, out:ArrayLikeObject, so:integer, oo:integer )"],["random.strided.exponential.factory","random.strided.exponential.factory( [options:Object] )"],["random.strided.exponential.PRNG","random.strided.exponential.PRNG"],["random.strided.exponential.seed","random.strided.exponential.seed"],["random.strided.exponential.seedLength","random.strided.exponential.seedLength"],["random.strided.exponential.state","random.strided.exponential.state"],["random.strided.exponential.stateLength","random.strided.exponential.stateLength"],["random.strided.exponential.byteLength","random.strided.exponential.byteLength"],["random.strided.gamma","random.strided.gamma( N:integer, alpha:ArrayLikeObject, sa:integer, beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.gamma.ndarray","random.strided.gamma.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.geometric","random.strided.geometric( N:integer, p:ArrayLikeObject, sp:integer, out:ArrayLikeObject, so:integer )"],["random.strided.geometric.ndarray","random.strided.geometric.ndarray( N:integer, p:ArrayLikeObject, sp:integer, op:integer, out:ArrayLikeObject, so:integer, oo:integer )"],["random.strided.geometric.factory","random.strided.geometric.factory( [options:Object] )"],["random.strided.geometric.PRNG","random.strided.geometric.PRNG"],["random.strided.geometric.seed","random.strided.geometric.seed"],["random.strided.geometric.seedLength","random.strided.geometric.seedLength"],["random.strided.geometric.state","random.strided.geometric.state"],["random.strided.geometric.stateLength","random.strided.geometric.stateLength"],["random.strided.geometric.byteLength","random.strided.geometric.byteLength"],["random.strided.invgamma","random.strided.invgamma( N:integer, alpha:ArrayLikeObject, sa:integer, beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.invgamma.ndarray","random.strided.invgamma.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.lognormal","random.strided.lognormal( N:integer, mu:ArrayLikeObject, sm:integer, sigma:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.lognormal.ndarray","random.strided.lognormal.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, om:integer, sigma:ArrayLikeObject, ss:integer, os:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.minstd","random.strided.minstd( N:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.minstd.ndarray","random.strided.minstd.ndarray( N:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.minstd.normalized","random.strided.minstd.normalized( N:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.minstd.normalized.ndarray","random.strided.minstd.normalized.ndarray( N:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.minstdShuffle","random.strided.minstdShuffle( N:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.minstdShuffle.ndarray","random.strided.minstdShuffle.ndarray( N:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.minstdShuffle.normalized","random.strided.minstdShuffle.normalized( N:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.minstdShuffle.normalized.ndarray","random.strided.minstdShuffle.normalized.ndarray( N:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.mt19937","random.strided.mt19937( N:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.mt19937.ndarray","random.strided.mt19937.ndarray( N:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.mt19937.normalized","random.strided.mt19937.normalized( N:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.mt19937.normalized.ndarray","random.strided.mt19937.normalized.ndarray( N:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.normal","random.strided.normal( N:integer, mu:ArrayLikeObject, sm:integer, sigma:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.normal.ndarray","random.strided.normal.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, om:integer, sigma:ArrayLikeObject, ss:integer, os:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.poisson","random.strided.poisson( N:integer, lambda:ArrayLikeObject, sl:integer, out:ArrayLikeObject, so:integer )"],["random.strided.poisson.ndarray","random.strided.poisson.ndarray( N:integer, lambda:ArrayLikeObject, sl:integer, ol:integer, out:ArrayLikeObject, so:integer, oo:integer )"],["random.strided.poisson.factory","random.strided.poisson.factory( [options:Object] )"],["random.strided.poisson.PRNG","random.strided.poisson.PRNG"],["random.strided.poisson.seed","random.strided.poisson.seed"],["random.strided.poisson.seedLength","random.strided.poisson.seedLength"],["random.strided.poisson.state","random.strided.poisson.state"],["random.strided.poisson.stateLength","random.strided.poisson.stateLength"],["random.strided.poisson.byteLength","random.strided.poisson.byteLength"],["random.strided.randu","random.strided.randu( N:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.randu.ndarray","random.strided.randu.ndarray( N:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.rayleigh","random.strided.rayleigh( N:integer, sigma:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer 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)"],["random.strided.t.factory","random.strided.t.factory( [options:Object] )"],["random.strided.t.PRNG","random.strided.t.PRNG"],["random.strided.t.seed","random.strided.t.seed"],["random.strided.t.seedLength","random.strided.t.seedLength"],["random.strided.t.state","random.strided.t.state"],["random.strided.t.stateLength","random.strided.t.stateLength"],["random.strided.t.byteLength","random.strided.t.byteLength"],["random.strided.uniform","random.strided.uniform( N:integer, a:ArrayLikeObject, sa:integer, b:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.uniform.ndarray","random.strided.uniform.ndarray( N:integer, a:ArrayLikeObject, sa:integer, oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.weibull","random.strided.weibull( N:integer, k:ArrayLikeObject, sk:integer, lambda:ArrayLikeObject, sl:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.weibull.ndarray","random.strided.weibull.ndarray( N:integer, k:ArrayLikeObject, sk:integer, ok:integer, lambda:ArrayLikeObject, sl:integer, ol:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["ranks","ranks( arr:Array<number>[, options:Object] )"],["readDir","readDir( path:string|Buffer, clbk:Function )"],["readDir.sync","readDir.sync( path:string|Buffer )"],["readFile","readFile( file:string|Buffer|integer[, options:Object|string], clbk:Function )"],["readFile.sync","readFile.sync( file:string|Buffer|integer[, options:Object|string] )"],["readFileList","readFileList( filepaths:Array<string>[, options:Object|string], clbk:Function )"],["readFileList.sync","readFileList.sync( filepaths:Array<string>[, options:Object|string] )"],["readJSON","readJSON( file:string|Buffer|integer[, options:Object|string], clbk:Function )"],["readJSON.sync","readJSON.sync( file:string|Buffer|integer[, options:Object|string] 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)"],["reDirname.REGEXP","reDirname.REGEXP"],["reDirname.REGEXP_POSIX","reDirname.REGEXP_POSIX"],["reDirname.REGEXP_WIN32","reDirname.REGEXP_WIN32"],["reDirnamePosix","reDirnamePosix()"],["reDirnamePosix.REGEXP","reDirnamePosix.REGEXP"],["reDirnameWindows","reDirnameWindows()"],["reDirnameWindows.REGEXP","reDirnameWindows.REGEXP"],["reduce","reduce( arr:ArrayLikeObject|ndarray, initial:any, reducer:Function[, thisArg:any] )"],["reduce2d","reduce2d( arr:ArrayLikeObject<ArrayLikeObject>, initial:ArrayLikeObject, reducer:Function[, thisArg:any] )"],["reduceAsync","reduceAsync( collection:Array|TypedArray|Object, initial:any, [options:Object,] reducer:Function, done:Function )"],["reduceAsync.factory","reduceAsync.factory( [options:Object,] fcn:Function )"],["reduceRight","reduceRight( arr:ArrayLikeObject|ndarray, initial:any, reducer:Function[, thisArg:any] )"],["reduceRightAsync","reduceRightAsync( collection:Array|TypedArray|Object, initial:any, [options:Object,] reducer:Function, done:Function )"],["reduceRightAsync.factory","reduceRightAsync.factory( [options:Object,] fcn:Function )"],["reDurationString","reDurationString()"],["reDurationString.REGEXP","reDurationString.REGEXP"],["reEOL","reEOL( [options:Object] )"],["reEOL.REGEXP","reEOL.REGEXP"],["reEOL.REGEXP_CAPTURE","reEOL.REGEXP_CAPTURE"],["reExtendedLengthPath","reExtendedLengthPath()"],["reExtendedLengthPath.REGEXP","reExtendedLengthPath.REGEXP"],["reExtname","reExtname( [platform:string] )"],["reExtname.REGEXP","reExtname.REGEXP"],["reExtname.REGEXP_POSIX","reExtname.REGEXP_POSIX"],["reExtname.REGEXP_WIN32","reExtname.REGEXP_WIN32"],["reExtnamePosix","reExtnamePosix"],["reExtnamePosix.REGEXP","reExtnamePosix.REGEXP"],["reExtnameWindows","reExtnameWindows"],["reExtnameWindows.REGEXP","reExtnameWindows.REGEXP"],["reFilename","reFilename( [platform:string] 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setter:Function )"],["setMemoizedConfigurableReadOnly","setMemoizedConfigurableReadOnly( obj:Object, prop:string|symbol, fcn:Function )"],["setMemoizedReadOnly","setMemoizedReadOnly( obj:Object, prop:string|symbol, fcn:Function )"],["setNonEnumerableProperty","setNonEnumerableProperty( obj:Object, prop:string|symbol, value:any )"],["setNonEnumerableReadOnly","setNonEnumerableReadOnly( obj:Object, prop:string|symbol, value:any )"],["setNonEnumerableReadOnlyAccessor","setNonEnumerableReadOnlyAccessor( obj:Object, prop:string|symbol, getter:Function )"],["setNonEnumerableReadWriteAccessor","setNonEnumerableReadWriteAccessor( obj:Object, prop:string|symbol, getter:Function, setter:Function )"],["setNonEnumerableWriteOnlyAccessor","setNonEnumerableWriteOnlyAccessor( obj:Object, prop:string|symbol, setter:Function )"],["setReadOnly","setReadOnly( obj:Object, prop:string|symbol, value:any )"],["setReadOnlyAccessor","setReadOnlyAccessor( obj:Object, prop:string|symbol, getter:Function 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clbk:Function[, thisArg:any] )"],["strided.acothBy","strided.acothBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.acothBy.ndarray","strided.acothBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.acovercosBy","strided.acovercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.acovercosBy.ndarray","strided.acovercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.acoversinBy","strided.acoversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.acoversinBy.ndarray","strided.acoversinBy.ndarray( 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)"],["strided.ahavercosBy","strided.ahavercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.ahavercosBy.ndarray","strided.ahavercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.ahaversinBy","strided.ahaversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.ahaversinBy.ndarray","strided.ahaversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.asinBy","strided.asinBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.asinBy.ndarray","strided.asinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.asinhBy","strided.asinhBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.asinhBy.ndarray","strided.asinhBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.atanBy","strided.atanBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.atanBy.ndarray","strided.atanBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.atanhBy","strided.atanhBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.atanhBy.ndarray","strided.atanhBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.avercosBy","strided.avercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.avercosBy.ndarray","strided.avercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.aversinBy","strided.aversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.aversinBy.ndarray","strided.aversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.besselj0By","strided.besselj0By( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.besselj0By.ndarray","strided.besselj0By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.besselj1By","strided.besselj1By( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.besselj1By.ndarray","strided.besselj1By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.bessely0By","strided.bessely0By( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.bessely0By.ndarray","strided.bessely0By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.bessely1By","strided.bessely1By( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.bessely1By.ndarray","strided.bessely1By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.binetBy","strided.binetBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.binetBy.ndarray","strided.binetBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.cbrt","strided.cbrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.cbrt.ndarray","strided.cbrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.cbrtBy","strided.cbrtBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.cbrtBy.ndarray","strided.cbrtBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.ceil","strided.ceil( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.ceil.ndarray","strided.ceil.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.cosBy","strided.cosBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.cosBy.ndarray","strided.cosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.deg2rad","strided.deg2rad( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.deg2rad.ndarray","strided.deg2rad.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.dataTypes","strided.dataTypes()"],["strided.dcbrtBy","strided.dcbrtBy( N:integer, x:Float64Array, sx:integer, y:Float64Array, sy:integer, clbk:Function[, thisArg:any] )"],["strided.dcbrtBy.ndarray","strided.dcbrtBy.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, y:Float64Array, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.dispatch","strided.dispatch( fcns:Function|ArrayLikeObject<Function>, 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dtype:string] )"],["azeroTo","azeroTo( n:integer[, dtype:string] )"],["azeroToLike","azeroToLike( x:TypedArray|Array[, dtype:string] )"],["bartlettTest","bartlettTest( ...x:Array[, options:Object] )"],["base.abs","base.abs( x:number )"],["base.abs2","base.abs2( x:number )"],["base.abs2f","base.abs2f( x:number )"],["base.absdiff","base.absdiff( x:number, y:number )"],["base.absf","base.absf( x:number )"],["base.acartesianPower","base.acartesianPower( x:ArrayLikeObject, n:integer )"],["base.acartesianProduct","base.acartesianProduct( x1:ArrayLikeObject, x2:ArrayLikeObject )"],["base.acartesianSquare","base.acartesianSquare( x:ArrayLikeObject )"],["base.acos","base.acos( x:number )"],["base.acosd","base.acosd( x:number )"],["base.acosf","base.acosf( x:number )"],["base.acosh","base.acosh( x:number )"],["base.acot","base.acot( x:number )"],["base.acotd","base.acotd( x:number )"],["base.acotf","base.acotf( x:number )"],["base.acoth","base.acoth( x:number 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)"],["base.afilled4d","base.afilled4d( value:any, shape:Array<integer> )"],["base.afilled4dBy","base.afilled4dBy( shape:Array<integer>, clbk:Function[, thisArg:any] )"],["base.afilled5d","base.afilled5d( value:any, shape:Array<integer> )"],["base.afilled5dBy","base.afilled5dBy( shape:Array<integer>, clbk:Function[, thisArg:any] )"],["base.afilledBy","base.afilledBy( len:integer, clbk:Function[, thisArg:any] )"],["base.afillednd","base.afillednd( value:any, shape:Array<integer> )"],["base.afilledndBy","base.afilledndBy( shape:Array<integer>, clbk:Function[, thisArg:any] )"],["base.afilter","base.afilter( x:Array|TypedArray|Object, predicate:Function[, thisArg:any] )"],["base.afirst","base.afirst( arr:ArrayLikeObject )"],["base.aflatten","base.aflatten( x:Array, shape:Array<integer>, colexicographic:boolean )"],["base.aflatten.assign","base.aflatten.assign( x:Array, shape:Array<integer>, colexicographic:boolean, out:Collection, stride:integer, offset:integer 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)"],["base.aflatten3dBy.assign","base.aflatten3dBy.assign( x:Array, shape:Array<integer>, colex:boolean, out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )"],["base.aflatten4d","base.aflatten4d( x:ArrayLikeObject, shape:Array<integer>, colexicographic:boolean )"],["base.aflatten4d.assign","base.aflatten4d.assign( x:Array, shape:Array<integer>, colexicographic:boolean, out:Collection, stride:integer, offset:integer )"],["base.aflatten4dBy","base.aflatten4dBy( x:ArrayLikeObject, shape:Array<integer>, colex:boolean, clbk:Function[, thisArg:any] )"],["base.aflatten4dBy.assign","base.aflatten4dBy.assign( x:Array, shape:Array<integer>, colex:boolean, out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )"],["base.aflatten5d","base.aflatten5d( x:ArrayLikeObject, shape:Array<integer>, colexicographic:boolean )"],["base.aflatten5d.assign","base.aflatten5d.assign( x:Array, shape:Array<integer>, colexicographic:boolean, out:Collection, stride:integer, offset:integer )"],["base.aflatten5dBy","base.aflatten5dBy( x:ArrayLikeObject, shape:Array<integer>, colex:boolean, clbk:Function[, thisArg:any] )"],["base.aflatten5dBy.assign","base.aflatten5dBy.assign( x:Array, shape:Array<integer>, colex:boolean, out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )"],["base.aflattenBy","base.aflattenBy( x:Array, shape:Array<integer>, colex:boolean, clbk:Function[, thisArg:any] )"],["base.aflattenBy.assign","base.aflattenBy.assign( x:Array, shape:Array<integer>, colex:boolean, out:Collection, stride:integer, offset:integer, clbk:Function[, thisArg:any] )"],["base.afliplr2d","base.afliplr2d( x:ArrayLikeObject )"],["base.afliplr3d","base.afliplr3d( x:ArrayLikeObject )"],["base.afliplr4d","base.afliplr4d( x:ArrayLikeObject )"],["base.afliplr5d","base.afliplr5d( x:ArrayLikeObject )"],["base.aflipud2d","base.aflipud2d( x:ArrayLikeObject )"],["base.aflipud3d","base.aflipud3d( x:ArrayLikeObject 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)"],["base.asech","base.asech( x:number )"],["base.asin","base.asin( x:number )"],["base.asind","base.asind( x:number )"],["base.asindf","base.asindf( x:number )"],["base.asinf","base.asinf( x:number )"],["base.asinh","base.asinh( x:number )"],["base.atan","base.atan( x:number )"],["base.atan2","base.atan2( y:number, x:number )"],["base.atand","base.atand( x:number )"],["base.atanf","base.atanf( x:number )"],["base.atanh","base.atanh( x:number )"],["base.avercos","base.avercos( x:number )"],["base.aversin","base.aversin( x:number )"],["base.azeros","base.azeros( len:integer )"],["base.azeros2d","base.azeros2d( shape:Array<integer> )"],["base.azeros3d","base.azeros3d( shape:Array<integer> )"],["base.azeros4d","base.azeros4d( shape:Array<integer> )"],["base.azeros5d","base.azeros5d( shape:Array<integer> )"],["base.azerosnd","base.azerosnd( shape:Array<integer> )"],["base.azeroTo","base.azeroTo( n:number )"],["base.azeroTo.assign","base.azeroTo.assign( out:ArrayLikeObject, stride:integer, offset:integer )"],["base.bernoulli","base.bernoulli( n:integer )"],["base.besselj0","base.besselj0( x:number )"],["base.besselj1","base.besselj1( x:number )"],["base.bessely0","base.bessely0( x:number )"],["base.bessely1","base.bessely1( x:number )"],["base.beta","base.beta( x:number, y:number )"],["base.betainc","base.betainc( x:number, a:number, b:number[, regularized:boolean[, upper:boolean]] )"],["base.betaincinv","base.betaincinv( p:number, a:number, b:number[, upper:boolean] )"],["base.betaln","base.betaln( a:number, b:number )"],["base.binet","base.binet( x:number )"],["base.binomcoef","base.binomcoef( n:integer, k:integer )"],["base.binomcoefln","base.binomcoefln( n:integer, k:integer )"],["base.boxcox","base.boxcox( x:number, lambda:number )"],["base.boxcox1p","base.boxcox1p( x:number, lambda:number )"],["base.boxcox1pinv","base.boxcox1pinv( y:number, lambda:number )"],["base.boxcoxinv","base.boxcoxinv( y:number, lambda:number )"],["base.cabs","base.cabs( z:Complex128 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)"],["base.strided.smaxsorted","base.strided.smaxsorted( N:integer, x:Float32Array, strideX:integer )"],["base.strided.smaxsorted.ndarray","base.strided.smaxsorted.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.smean","base.strided.smean( N:integer, x:Float32Array, stride:integer )"],["base.strided.smean.ndarray","base.strided.smean.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )"],["base.strided.smeankbn","base.strided.smeankbn( N:integer, x:Float32Array, stride:integer )"],["base.strided.smeankbn.ndarray","base.strided.smeankbn.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )"],["base.strided.smeankbn2","base.strided.smeankbn2( N:integer, x:Float32Array, stride:integer )"],["base.strided.smeankbn2.ndarray","base.strided.smeankbn2.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )"],["base.strided.smeanli","base.strided.smeanli( N:integer, x:Float32Array, stride:integer 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offset:integer )"],["base.strided.smeanwd","base.strided.smeanwd( N:integer, x:Float32Array, stride:integer )"],["base.strided.smeanwd.ndarray","base.strided.smeanwd.ndarray( N:integer, x:Float32Array, stride:integer, offset:integer )"],["base.strided.smediansorted","base.strided.smediansorted( N:integer, x:Float32Array, strideX:integer )"],["base.strided.smediansorted.ndarray","base.strided.smediansorted.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.smidrange","base.strided.smidrange( N:integer, x:Float32Array, strideX:integer )"],["base.strided.smidrange.ndarray","base.strided.smidrange.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.smin","base.strided.smin( N:integer, x:Float32Array, strideX:integer )"],["base.strided.smin.ndarray","base.strided.smin.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.sminabs","base.strided.sminabs( N:integer, x:Float32Array, strideX:integer )"],["base.strided.sminabs.ndarray","base.strided.sminabs.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.sminsorted","base.strided.sminsorted( N:integer, x:Float32Array, strideX:integer )"],["base.strided.sminsorted.ndarray","base.strided.sminsorted.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer )"],["base.strided.smskabs","base.strided.smskabs( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskabs.ndarray","base.strided.smskabs.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskabs2","base.strided.smskabs2( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskabs2.ndarray","base.strided.smskabs2.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskcbrt","base.strided.smskcbrt( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskcbrt.ndarray","base.strided.smskcbrt.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskceil","base.strided.smskceil( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskceil.ndarray","base.strided.smskceil.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskdeg2rad","base.strided.smskdeg2rad( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskdeg2rad.ndarray","base.strided.smskdeg2rad.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskfloor","base.strided.smskfloor( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskfloor.ndarray","base.strided.smskfloor.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskinv","base.strided.smskinv( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskinv.ndarray","base.strided.smskinv.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskmap","base.strided.smskmap( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer, fcn:Function )"],["base.strided.smskmap.ndarray","base.strided.smskmap.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Uint8Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer, fcn:Function )"],["base.strided.smskmap2","base.strided.smskmap2( N:integer, x:Float32Array, sx:integer, y:Float32Array, sy:integer, m:Uint8Array, sm:integer, z:Float32Array, sz:integer, fcn:Function )"],["base.strided.smskmap2.ndarray","base.strided.smskmap2.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, y:Float32Array, sy:integer, oy:integer, m:Uint8Array, sm:integer, om:integer, z:Float32Array, sz:integer, oz:integer, fcn:Function )"],["base.strided.smskmax","base.strided.smskmax( N:integer, x:Float32Array, strideX:integer, mask:Uint8Array, strideMask:integer )"],["base.strided.smskmax.ndarray","base.strided.smskmax.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )"],["base.strided.smskmin","base.strided.smskmin( N:integer, x:Float32Array, strideX:integer, mask:Uint8Array, strideMask:integer )"],["base.strided.smskmin.ndarray","base.strided.smskmin.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer )"],["base.strided.smskramp","base.strided.smskramp( N:integer, x:Float32Array, sx:integer, m:Uint8Array, sm:integer, y:Float32Array, sy:integer )"],["base.strided.smskramp.ndarray","base.strided.smskramp.ndarray( N:integer, x:Float32Array, sx:integer, ox:integer, m:Float32Array, sm:integer, om:integer, y:Float32Array, sy:integer, oy:integer )"],["base.strided.smskrange","base.strided.smskrange( N:integer, x:Float32Array, strideX:integer, mask:Uint8Array, strideMask:integer )"],["base.strided.smskrange.ndarray","base.strided.smskrange.ndarray( N:integer, x:Float32Array, strideX:integer, offsetX:integer, mask:Uint8Array, strideMask:integer, offsetMask:integer 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value:any )"],["isRelativePath.posix","isRelativePath.posix( value:any )"],["isRelativePath.win32","isRelativePath.win32( value:any )"],["isRelativeURI","isRelativeURI( value:any )"],["isSafeInteger","isSafeInteger( value:any )"],["isSafeInteger.isPrimitive","isSafeInteger.isPrimitive( value:any )"],["isSafeInteger.isObject","isSafeInteger.isObject( value:any )"],["isSafeIntegerArray","isSafeIntegerArray( value:any )"],["isSafeIntegerArray.primitives","isSafeIntegerArray.primitives( value:any )"],["isSafeIntegerArray.objects","isSafeIntegerArray.objects( value:any )"],["isSameArray","isSameArray( v1:any, v2:any )"],["isSameArrayLike","isSameArrayLike( v1:any, v2:any )"],["isSameComplex64","isSameComplex64( v1:any, v2:any )"],["isSameComplex64Array","isSameComplex64Array( v1:any, v2:any )"],["isSameComplex128","isSameComplex128( v1:any, v2:any )"],["isSameComplex128Array","isSameComplex128Array( v1:any, v2:any )"],["isSameDateObject","isSameDateObject( d1, d2 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iterator:Object )"],["iterAcoversin","iterAcoversin( iterator:Object )"],["iterAdd","iterAdd( iter0:Object, ...iterator:Object )"],["iterAdvance","iterAdvance( iterator:Object[, n:integer] )"],["iterAhavercos","iterAhavercos( iterator:Object )"],["iterAhaversin","iterAhaversin( iterator:Object )"],["iterAny","iterAny( iterator:Object )"],["iterAnyBy","iterAnyBy( iterator:Object, predicate:Function[, thisArg:any ] )"],["iterAsin","iterAsin( iterator:Object )"],["iterAsinh","iterAsinh( iterator:Object )"],["iterAtan","iterAtan( iterator:Object )"],["iterAtan2","iterAtan2( y:Object|number, x:Object|number )"],["iterAtanh","iterAtanh( iterator:Object )"],["iterator2array","iterator2array( iterator:Object[, out:ArrayLikeObject][, mapFcn:Function[, thisArg:any]] )"],["iterator2arrayview","iterator2arrayview( iterator:Object, dest:ArrayLikeObject[, begin:integer[, end:integer]][, mapFcn:Function[, thisArg:any]] )"],["iterator2arrayviewRight","iterator2arrayviewRight( iterator:Object, dest:ArrayLikeObject[, begin:integer[, end:integer]][, mapFcn:Function[, thisArg:any]] )"],["iteratorStream","iteratorStream( iterator:Object[, options:Object] )"],["iteratorStream.factory","iteratorStream.factory( [options:Object] )"],["iteratorStream.objectMode","iteratorStream.objectMode( iterator:Object[, options:Object] )"],["IteratorSymbol","IteratorSymbol"],["iterAvercos","iterAvercos( iterator:Object )"],["iterAversin","iterAversin( iterator:Object )"],["iterawgn","iterawgn( iterator:Object, sigma:number[, options:Object] )"],["iterawln","iterawln( iterator:Object, sigma:number[, options:Object] )"],["iterawun","iterawun( iterator:Object, sigma:number[, options:Object] )"],["iterBartlettHannPulse","iterBartlettHannPulse( [options:Object] )"],["iterBartlettPulse","iterBartlettPulse( [options:Object] )"],["iterBesselj0","iterBesselj0( iterator:Object )"],["iterBesselj1","iterBesselj1( iterator:Object )"],["iterBessely0","iterBessely0( iterator:Object 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start:integer|string|Date, stop:integer|string|Date[, N:integer][, options:Object] )"],["iterDedupe","iterDedupe( iterator:Object[, limit:integer] )"],["iterDedupeBy","iterDedupeBy( iterator:Object, [limit:integer,] fcn:Function )"],["iterDeg2rad","iterDeg2rad( iterator:Object )"],["iterDigamma","iterDigamma( iterator:Object )"],["iterDiracComb","iterDiracComb( [options:Object] )"],["iterDiracDelta","iterDiracDelta( iterator:Object )"],["iterDivide","iterDivide( iter0:Object, ...iterator:Object )"],["iterDoWhileEach","iterDoWhileEach( iterator:Object, predicate:Function, fcn:Function[, thisArg:any] )"],["iterEllipe","iterEllipe( iterator:Object )"],["iterEllipk","iterEllipk( iterator:Object )"],["iterEmpty","iterEmpty()"],["iterErf","iterErf( iterator:Object )"],["iterErfc","iterErfc( iterator:Object )"],["iterErfcinv","iterErfcinv( iterator:Object )"],["iterErfinv","iterErfinv( iterator:Object )"],["iterEta","iterEta( iterator:Object )"],["iterEvenIntegersSeq","iterEvenIntegersSeq( [options:Object] )"],["iterEvery","iterEvery( iterator:Object )"],["iterEveryBy","iterEveryBy( iterator:Object, predicate:Function[, thisArg:any ] )"],["iterExp","iterExp( iterator:Object )"],["iterExp2","iterExp2( iterator:Object )"],["iterExp10","iterExp10( iterator:Object )"],["iterExpit","iterExpit( iterator:Object )"],["iterExpm1","iterExpm1( iterator:Object )"],["iterExpm1rel","iterExpm1rel( iterator:Object )"],["iterFactorial","iterFactorial( iterator:Object )"],["iterFactorialln","iterFactorialln( iterator:Object )"],["iterFactorialsSeq","iterFactorialsSeq( [options:Object] )"],["iterFibonacciSeq","iterFibonacciSeq( [options:Object] )"],["iterFifthPowersSeq","iterFifthPowersSeq( [options:Object] )"],["iterFill","iterFill( iterator:Object, value:any[, begin:integer[, end:integer]] )"],["iterFilter","iterFilter( iterator:Object, predicate:Function[, thisArg:any] )"],["iterFilterMap","iterFilterMap( iterator:Object, fcn:Function[, thisArg:any] )"],["iterFirst","iterFirst( iterator:Object )"],["iterFlatTopPulse","iterFlatTopPulse( [options:Object] )"],["iterFloor","iterFloor( iterator:Object )"],["iterFloor2","iterFloor2( iterator:Object )"],["iterFloor10","iterFloor10( iterator:Object )"],["iterFlow","iterFlow( methods:Object )"],["iterForEach","iterForEach( iterator:Object, fcn:Function[, thisArg:any] )"],["iterFourthPowersSeq","iterFourthPowersSeq( [options:Object] )"],["iterFresnelc","iterFresnelc( iterator:Object )"],["iterFresnels","iterFresnels( iterator:Object )"],["iterGamma","iterGamma( iterator:Object )"],["iterGamma1pm1","iterGamma1pm1( iterator:Object )"],["iterGammaln","iterGammaln( iterator:Object )"],["iterHacovercos","iterHacovercos( iterator:Object )"],["iterHacoversin","iterHacoversin( iterator:Object )"],["iterHannPulse","iterHannPulse( [options:Object] )"],["iterHavercos","iterHavercos( iterator:Object )"],["iterHaversin","iterHaversin( iterator:Object )"],["iterHead","iterHead( iterator:Object, n:integer 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)"],["iterLogspace","iterLogspace( start:number, stop:number[, N:integer][, options:Object] )"],["iterLucasSeq","iterLucasSeq( [options:Object] )"],["iterMap","iterMap( iterator:Object, fcn:Function[, thisArg:any] )"],["iterMapN","iterMapN( iter0:Object, ...iterator:Object, fcn:Function[, thisArg:any] )"],["itermax","itermax( iterator:Object )"],["itermaxabs","itermaxabs( iterator:Object )"],["itermean","itermean( iterator:Object )"],["itermeanabs","itermeanabs( iterator:Object )"],["itermeanabs2","itermeanabs2( iterator:Object )"],["itermidrange","itermidrange( iterator:Object )"],["itermin","itermin( iterator:Object )"],["iterminabs","iterminabs( iterator:Object )"],["itermmax","itermmax( iterator:Object, W:integer )"],["itermmaxabs","itermmaxabs( iterator:Object, W:integer )"],["itermmean","itermmean( iterator:Object, W:integer )"],["itermmeanabs","itermmeanabs( iterator:Object, W:integer )"],["itermmeanabs2","itermmeanabs2( iterator:Object, W:integer 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)"],["iterNoneBy","iterNoneBy( iterator:Object, predicate:Function[, thisArg:any ] )"],["iterNonFibonacciSeq","iterNonFibonacciSeq( [options:Object] )"],["iterNonNegativeEvenIntegersSeq","iterNonNegativeEvenIntegersSeq( [options:Object] )"],["iterNonNegativeIntegersSeq","iterNonNegativeIntegersSeq( [options:Object] )"],["iterNonPositiveEvenIntegersSeq","iterNonPositiveEvenIntegersSeq( [options:Object] )"],["iterNonPositiveIntegersSeq","iterNonPositiveIntegersSeq( [options:Object] )"],["iterNonSquaresSeq","iterNonSquaresSeq( [options:Object] )"],["iterNth","iterNth( iterator:Object, n:integer )"],["iterOddIntegersSeq","iterOddIntegersSeq( [options:Object] )"],["iterPeriodicSinc","iterPeriodicSinc( n:integer[, options:Object] )"],["iterPipeline","iterPipeline( iterFcn:Function|Array[, ...iterFcn:Function] )"],["iterPop","iterPop( iterator:Object[, clbk:Function[, thisArg:any]] )"],["iterPositiveEvenIntegersSeq","iterPositiveEvenIntegersSeq( [options:Object] )"],["iterPositiveIntegersSeq","iterPositiveIntegersSeq( [options:Object] )"],["iterPositiveOddIntegersSeq","iterPositiveOddIntegersSeq( [options:Object] )"],["iterPow","iterPow( base:Object|number, exponent:Object|number )"],["iterPrimesSeq","iterPrimesSeq( [options:Object] )"],["iterprod","iterprod( iterator:Object )"],["iterPulse","iterPulse( [options:Object] )"],["iterPush","iterPush( iterator:Object, ...items:any )"],["iterRad2deg","iterRad2deg( iterator:Object )"],["iterRamp","iterRamp( iterator:Object )"],["iterrange","iterrange( iterator:Object )"],["iterReject","iterReject( iterator:Object, predicate:Function[, thisArg:any] )"],["iterReplicate","iterReplicate( iterator:Object, n:integer )"],["iterReplicateBy","iterReplicateBy( iterator:Object, fcn:Function[, thisArg:any] )"],["iterRound","iterRound( iterator:Object )"],["iterRound2","iterRound2( iterator:Object )"],["iterRound10","iterRound10( iterator:Object )"],["iterRsqrt","iterRsqrt( iterator:Object )"],["iterSawtoothWave","iterSawtoothWave( [options:Object] )"],["iterShift","iterShift( iterator:Object[, clbk:Function[, thisArg:any]] )"],["iterSignum","iterSignum( iterator:Object )"],["iterSin","iterSin( iterator:Object )"],["iterSinc","iterSinc( iterator:Object )"],["iterSineWave","iterSineWave( [options:Object] )"],["iterSinh","iterSinh( iterator:Object )"],["iterSinpi","iterSinpi( iterator:Object )"],["iterSlice","iterSlice( iterator:Object[, begin:integer[, end:integer]] )"],["iterSome","iterSome( iterator:Object, n:number )"],["iterSomeBy","iterSomeBy( iterator:Object, n:integer, predicate:Function[, thisArg:any ] )"],["iterSpence","iterSpence( iterator:Object )"],["iterSqrt","iterSqrt( iterator:Object )"],["iterSqrt1pm1","iterSqrt1pm1( iterator:Object )"],["iterSquaredTriangularSeq","iterSquaredTriangularSeq( [options:Object] )"],["iterSquaresSeq","iterSquaresSeq( [options:Object] )"],["iterSquareWave","iterSquareWave( [options:Object] )"],["iterstdev","iterstdev( iterator:Object[, mean:number] )"],["iterStep","iterStep( start:number, increment:number[, N:number] )"],["iterStrided","iterStrided( iterator:Object, stride:integer[, offset:integer[, eager:boolean]] )"],["iterStridedBy","iterStridedBy( iterator:Object, fcn:Function[, offset:integer[, eager:boolean]][, thisArg:any] )"],["iterSubtract","iterSubtract( iter0:Object, ...iterator:Object )"],["itersum","itersum( iterator:Object )"],["itersumabs","itersumabs( iterator:Object )"],["itersumabs2","itersumabs2( iterator:Object )"],["iterTan","iterTan( iterator:Object )"],["iterTanh","iterTanh( iterator:Object )"],["iterThunk","iterThunk( iterFcn:Function[, ...args:any] )"],["iterTriangleWave","iterTriangleWave( [options:Object] )"],["iterTriangularSeq","iterTriangularSeq( [options:Object] )"],["iterTribonnaciSeq","iterTribonnaciSeq( [options:Object] )"],["iterTrigamma","iterTrigamma( iterator:Object )"],["iterTrunc","iterTrunc( iterator:Object )"],["iterTrunc2","iterTrunc2( iterator:Object )"],["iterTrunc10","iterTrunc10( iterator:Object )"],["iterUnion","iterUnion( iter0:Object, ...iterator:Object )"],["iterUnique","iterUnique( iterator:Object )"],["iterUniqueBy","iterUniqueBy( iterator:Object, predicate:Function[, thisArg:any] )"],["iterUniqueByHash","iterUniqueByHash( iterator:Object, hashFcn:Function[, thisArg:any] )"],["iterUnitspace","iterUnitspace( start:number[, stop:number] )"],["iterUnshift","iterUnshift( iterator:Object, ...items:any )"],["iterUntilEach","iterUntilEach( iterator:Object, predicate:Function, fcn:Function[, thisArg:any] )"],["itervariance","itervariance( iterator:Object[, mean:number] )"],["iterVercos","iterVercos( iterator:Object )"],["iterVersin","iterVersin( iterator:Object )"],["iterWhileEach","iterWhileEach( iterator:Object, predicate:Function, fcn:Function[, thisArg:any] )"],["iterZeta","iterZeta( iterator:Object )"],["joinStream","joinStream( [options:Object] )"],["joinStream.factory","joinStream.factory( [options:Object] )"],["joinStream.objectMode","joinStream.objectMode( [options:Object] )"],["kde2d","kde2d( x:Array<number>, y:Array<number>[, options:Object] )"],["kebabcase","kebabcase( str:string )"],["keyBy","keyBy( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )"],["keyByRight","keyByRight( collection:Array|TypedArray|Object, fcn:Function[, thisArg:any] )"],["keysIn","keysIn( obj:any )"],["kruskalTest","kruskalTest( ...x:Array[, options:Object] )"],["kstest","kstest( x:Array<number>, y:Function|string[, ...params:number][, options:Object] )"],["last","last( str:string[, n:integer][, options:Object] )"],["leveneTest","leveneTest( x:Array<number>[, ...y:Array<number>[, options:Object]] )"],["LinkedList","LinkedList()"],["linspace","linspace( start:number|ComplexLike, stop:number|ComplexLike, length:integer[, options:Object] )"],["linspace.assign","linspace.assign( start:number|ComplexLike, stop:number|ComplexLike, out:ArrayLikeObject[, options:Object] )"],["LIU_NEGATIVE_OPINION_WORDS_EN","LIU_NEGATIVE_OPINION_WORDS_EN()"],["LIU_POSITIVE_OPINION_WORDS_EN","LIU_POSITIVE_OPINION_WORDS_EN()"],["LN_HALF","LN_HALF"],["LN_PI","LN_PI"],["LN_SQRT_TWO_PI","LN_SQRT_TWO_PI"],["LN_TWO_PI","LN_TWO_PI"],["LN2","LN2"],["LN10","LN10"],["LOG2E","LOG2E"],["LOG10E","LOG10E"],["logspace","logspace( a:number, b:number[, length:integer] )"],["lowercase","lowercase( str:string )"],["lowercaseKeys","lowercaseKeys( obj:Object )"],["lowess","lowess( x:Array<number>, y:Array<number>[, options:Object] )"],["lpad","lpad( str:string, len:integer[, pad:string] )"],["ltrim","ltrim( str:string )"],["ltrimN","ltrimN( str:string, n:integer[, chars:Array|string] )"],["MALE_FIRST_NAMES_EN","MALE_FIRST_NAMES_EN()"],["map","map( arr:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )"],["map.assign","map.assign( arr:ArrayLikeObject|ndarray, out:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )"],["map2","map2( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )"],["map2.assign","map2.assign( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, out:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )"],["map2d","map2d( arr:ArrayLikeObject<ArrayLikeObject>, fcn:Function[, thisArg:any] )"],["map2Right","map2Right( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )"],["map2Right.assign","map2Right.assign( x:ArrayLikeObject|ndarray, y:ArrayLikeObject|ndarray, out:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )"],["map3d","map3d( arr:ArrayLikeObject<ArrayLikeObject<ArrayLikeObject>>, fcn:Function[, thisArg:any] )"],["map4d","map4d( arr:ArrayLikeObject<ArrayLikeObject>, fcn:Function[, thisArg:any] )"],["map5d","map5d( arr:ArrayLikeObject<ArrayLikeObject>, fcn:Function[, thisArg:any] )"],["mapArguments","mapArguments( fcn:Function, clbk:Function[, thisArg:any] )"],["mapFun","mapFun( fcn:Function, n:integer[, thisArg:any] )"],["mapFunAsync","mapFunAsync( fcn:Function, n:integer, [options:Object,] done:Function )"],["mapFunAsync.factory","mapFunAsync.factory( [options:Object,] fcn:Function )"],["mapKeys","mapKeys( obj:Object, transform:Function )"],["mapKeysAsync","mapKeysAsync( obj:Object, [options:Object,] transform:Function, done:Function )"],["mapKeysAsync.factory","mapKeysAsync.factory( [options:Object,] transform:Function )"],["mapReduce","mapReduce( arr:ArrayLikeObject|ndarray, initial:any, mapper:Function, reducer:Function[, thisArg:any] )"],["mapReduceRight","mapReduceRight( arr:ArrayLikeObject|ndarray, initial:any, mapper:Function, reducer:Function[, thisArg:any] )"],["mapRight","mapRight( arr:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )"],["mapRight.assign","mapRight.assign( arr:ArrayLikeObject|ndarray, out:ArrayLikeObject|ndarray, fcn:Function[, thisArg:any] )"],["mapValues","mapValues( obj:Object, transform:Function )"],["mapValuesAsync","mapValuesAsync( obj:Object, [options:Object,] transform:Function, done:Function 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)"],["MINUTES_IN_DAY","MINUTES_IN_DAY"],["MINUTES_IN_HOUR","MINUTES_IN_HOUR"],["MINUTES_IN_WEEK","MINUTES_IN_WEEK"],["minutesInMonth","minutesInMonth( [month:string|Date|integer[, year:integer]] )"],["minutesInYear","minutesInYear( [value:integer|Date] )"],["MOBY_DICK","MOBY_DICK()"],["MONTH_NAMES_EN","MONTH_NAMES_EN()"],["MONTHS_IN_YEAR","MONTHS_IN_YEAR"],["moveProperty","moveProperty( source:Object, prop:string, target:Object )"],["MultiSlice","MultiSlice( ...slice )"],["MultiSlice.prototype.ndims","MultiSlice.prototype.ndims"],["MultiSlice.prototype.data","MultiSlice.prototype.data"],["MultiSlice.prototype.toString","MultiSlice.prototype.toString()"],["MultiSlice.prototype.toJSON","MultiSlice.prototype.toJSON()"],["namedtypedtuple","namedtypedtuple( fields:Array<string>[, options:Object] )"],["NAN","NAN"],["naryFunction","naryFunction( fcn:Function, arity:integer[, thisArg:any] )"],["nativeClass","nativeClass( value:any )"],["ndarray","ndarray( dtype:string, buffer:ArrayLikeObject|TypedArray|Buffer, shape:ArrayLikeObject<integer>, strides:ArrayLikeObject<integer>, offset:integer, order:string[, options:Object] )"],["ndarray.prototype.byteLength","ndarray.prototype.byteLength"],["ndarray.prototype.BYTES_PER_ELEMENT","ndarray.prototype.BYTES_PER_ELEMENT"],["ndarray.prototype.data","ndarray.prototype.data"],["ndarray.prototype.dtype","ndarray.prototype.dtype"],["ndarray.prototype.flags","ndarray.prototype.flags"],["ndarray.prototype.length","ndarray.prototype.length"],["ndarray.prototype.ndims","ndarray.prototype.ndims"],["ndarray.prototype.offset","ndarray.prototype.offset"],["ndarray.prototype.order","ndarray.prototype.order"],["ndarray.prototype.shape","ndarray.prototype.shape"],["ndarray.prototype.strides","ndarray.prototype.strides"],["ndarray.prototype.get","ndarray.prototype.get( ...idx:integer )"],["ndarray.prototype.iget","ndarray.prototype.iget( idx:integer )"],["ndarray.prototype.set","ndarray.prototype.set( ...idx:integer, v:any )"],["ndarray.prototype.iset","ndarray.prototype.iset( idx:integer, v:any )"],["ndarray.prototype.toString","ndarray.prototype.toString()"],["ndarray.prototype.toJSON","ndarray.prototype.toJSON()"],["ndarray2array","ndarray2array( x:ndarray )"],["ndarray2fancy","ndarray2fancy( x:ndarray[, options:Object] )"],["ndarray2fancy.factory","ndarray2fancy.factory( [options:Object] )"],["ndarray2fancy.idx","ndarray2fancy.idx( x:ndarray[, options:Object] )"],["ndarray2json","ndarray2json( x:ndarray )"],["ndarrayCastingModes","ndarrayCastingModes()"],["ndarrayDataBuffer","ndarrayDataBuffer( x:ndarray )"],["ndarrayDataType","ndarrayDataType( x:ndarray )"],["ndarrayDataTypes","ndarrayDataTypes( [kind:string] )"],["ndarrayDispatch","ndarrayDispatch( fcns:Function|ArrayLikeObject<Function>, types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, nout:integer )"],["ndarrayFlag","ndarrayFlag( x:ndarray, name:string|symbol )"],["ndarrayFlags","ndarrayFlags( x:ndarray 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)"],["ndfilter","ndfilter( x:ndarray[, options:Object], predicate:Function[, thisArg:any] )"],["ndfilterMap","ndfilterMap( x:ndarray[, options:Object], fcn:Function[, thisArg:any] )"],["ndforEach","ndforEach( x:ndarray, fcn:Function[, thisArg:any] )"],["ndims","ndims( x:ndarray )"],["ndindex","ndindex( x:ndarray[, options:Object] )"],["ndindex.free","ndindex.free( id:string )"],["ndindex.get","ndindex.get( id:string )"],["ndindex.cartesianIndex","ndindex.cartesianIndex( x:ndarray[, options:Object] )"],["ndindex.linearIndex","ndindex.linearIndex( x:ndarray[, options:Object] )"],["ndindex.prototype.data","ndindex.prototype.data"],["ndindex.prototype.dtype","ndindex.prototype.dtype"],["ndindex.prototype.id","ndindex.prototype.id"],["ndindex.prototype.isCached","ndindex.prototype.isCached"],["ndindex.prototype.kind","ndindex.prototype.kind"],["ndindex.prototype.type","ndindex.prototype.type"],["ndindex.prototype.toString","ndindex.prototype.toString()"],["ndindex.prototype.toJSON","ndindex.prototype.toJSON()"],["nditerColumnEntries","nditerColumnEntries( x:ndarray[, options:Object] )"],["nditerColumns","nditerColumns( x:ndarray[, options:Object] )"],["nditerEntries","nditerEntries( x:ndarray[, options:Object] )"],["nditerIndices","nditerIndices( shape:Array<integer>[, options:Object] )"],["nditerInterleaveSubarrays","nditerInterleaveSubarrays( arr:ArrayLike<ndarray>, ndims:integer )"],["nditerMatrices","nditerMatrices( x:ndarray[, options:Object] )"],["nditerMatrixEntries","nditerMatrixEntries( x:ndarray[, options:Object] )"],["nditerRowEntries","nditerRowEntries( x:ndarray[, options:Object] )"],["nditerRows","nditerRows( x:ndarray[, options:Object] )"],["nditerSelectDimension","nditerSelectDimension( x:ndarray, dim:integer[, options:Object] )"],["nditerStacks","nditerStacks( x:ndarray, dims:Array<integer>[, options:Object] )"],["nditerSubarrays","nditerSubarrays( x:ndarray, ndims:integer[, options:Object] )"],["nditerValues","nditerValues( x:ndarray[, options:Object] )"],["ndmap","ndmap( x:ndarray[, options:Object], fcn:Function[, thisArg:any] )"],["ndreject","ndreject( x:ndarray[, options:Object], predicate:Function[, thisArg:any] )"],["ndslice","ndslice( x:ndarray, ...s:MultiSlice|Slice|null|undefined|integer|ArrayLike[, options:Object] )"],["ndsliceAssign","ndsliceAssign( x:ndarray, y:ndarray, ...s:MultiSlice|Slice|null|undefined|integer|ArrayLike[, options:Object] )"],["ndsliceDimension","ndsliceDimension( x:ndarray, dim:integer, slice:Slice|integer|null|undefined[, options:Object] )"],["ndsliceDimensionFrom","ndsliceDimensionFrom( x:ndarray, dim:integer, start:integer[, options:Object] )"],["ndsliceDimensionTo","ndsliceDimensionTo( x:ndarray, dim:integer, stop:integer[, options:Object] )"],["ndsliceFrom","ndsliceFrom( x:ndarray, ...start:null|void|integer[, options:Object] )"],["ndsliceTo","ndsliceTo( x:ndarray, ...stop:null|void|integer[, options:Object] )"],["ndzeros","ndzeros( shape:ArrayLikeObject<integer>|integer[, options:Object] )"],["ndzerosLike","ndzerosLike( x:ndarray[, options:Object] )"],["nextGraphemeClusterBreak","nextGraphemeClusterBreak( str:string[, fromIndex:integer] )"],["nextTick","nextTick( clbk[, ...args] )"],["NIGHTINGALES_ROSE","NIGHTINGALES_ROSE()"],["NINF","NINF"],["NODE_VERSION","NODE_VERSION"],["none","none( collection:Array|TypedArray|Object )"],["noneBy","noneBy( collection:Array|TypedArray|Object, predicate:Function[, thisArg:any ] )"],["noneByAsync","noneByAsync( collection:Array|TypedArray|Object, [options:Object,] predicate:Function, done:Function )"],["noneByAsync.factory","noneByAsync.factory( [options:Object,] predicate:Function )"],["noneByRight","noneByRight( collection:Array|TypedArray|Object, predicate:Function[, thisArg:any ] )"],["noneByRightAsync","noneByRightAsync( collection:Array|TypedArray|Object, [options:Object,] predicate:Function, done:Function )"],["noneByRightAsync.factory","noneByRightAsync.factory( [options:Object,] predicate:Function )"],["noneInBy","noneInBy( object:Object, predicate:Function[, thisArg:any ] )"],["nonEnumerableProperties","nonEnumerableProperties( value:any )"],["nonEnumerablePropertiesIn","nonEnumerablePropertiesIn( value:any )"],["nonEnumerablePropertyNames","nonEnumerablePropertyNames( value:any )"],["nonEnumerablePropertyNamesIn","nonEnumerablePropertyNamesIn( value:any )"],["nonEnumerablePropertySymbols","nonEnumerablePropertySymbols( value:any )"],["nonEnumerablePropertySymbolsIn","nonEnumerablePropertySymbolsIn( value:any )"],["noneOwnBy","noneOwnBy( object:Object, predicate:Function[, thisArg:any ] )"],["nonIndexKeys","nonIndexKeys( obj:any )"],["noop","noop()"],["now","now()"],["NUM_CPUS","NUM_CPUS"],["num2words","num2words( value:integer[, options:Object] )"],["Number","Number( value:number )"],["numel","numel( x:ndarray )"],["numelDimension","numelDimension( x:ndarray, dim:integer )"],["numGraphemeClusters","numGraphemeClusters( str:string )"],["Object","Object( value:any )"],["Object.assign","Object.assign( target:Object, ...sources:Object )"],["Object.create","Object.create( prototype:Object, properties:Object )"],["Object.defineProperties","Object.defineProperties( obj:Object, properties:Object )"],["Object.defineProperty","Object.defineProperty( obj:Object, key:string, descriptor:Object )"],["Object.entries","Object.entries( obj:Object )"],["Object.freeze","Object.freeze( obj:Object )"],["Object.getOwnPropertyDescriptor","Object.getOwnPropertyDescriptor( obj:Object, key:string 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][options:Object] )"],["random.streams.t.objectMode","random.streams.t.objectMode( v:number[, options:Object] )"],["random.streams.triangular","random.streams.triangular( a:number, b:number, c:number[, options:Object] )"],["random.streams.triangular.factory","random.streams.triangular.factory( [a:number, b:number, c:number, ][options:Object] )"],["random.streams.triangular.objectMode","random.streams.triangular.objectMode( a:number, b:number, c:number[, options:Object] )"],["random.streams.uniform","random.streams.uniform( a:number, b:number[, options:Object] )"],["random.streams.uniform.factory","random.streams.uniform.factory( [a:number, b:number, ][options:Object] )"],["random.streams.uniform.objectMode","random.streams.uniform.objectMode( a:number, b:number[, options:Object] )"],["random.streams.weibull","random.streams.weibull( k:number, λ:number[, options:Object] )"],["random.streams.weibull.factory","random.streams.weibull.factory( [k:number, λ:number, ][options:Object] )"],["random.streams.weibull.objectMode","random.streams.weibull.objectMode( k:number, λ:number[, options:Object] )"],["random.strided.arcsine","random.strided.arcsine( N:integer, a:ArrayLikeObject, sa:integer, b:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.arcsine.ndarray","random.strided.arcsine.ndarray( N:integer, a:ArrayLikeObject, sa:integer, oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.bernoulli","random.strided.bernoulli( N:integer, p:ArrayLikeObject, sp:integer, out:ArrayLikeObject, so:integer )"],["random.strided.bernoulli.ndarray","random.strided.bernoulli.ndarray( N:integer, p:ArrayLikeObject, sp:integer, op:integer, out:ArrayLikeObject, so:integer, oo:integer )"],["random.strided.bernoulli.factory","random.strided.bernoulli.factory( [options:Object] )"],["random.strided.bernoulli.PRNG","random.strided.bernoulli.PRNG"],["random.strided.bernoulli.seed","random.strided.bernoulli.seed"],["random.strided.bernoulli.seedLength","random.strided.bernoulli.seedLength"],["random.strided.bernoulli.state","random.strided.bernoulli.state"],["random.strided.bernoulli.stateLength","random.strided.bernoulli.stateLength"],["random.strided.bernoulli.byteLength","random.strided.bernoulli.byteLength"],["random.strided.beta","random.strided.beta( N:integer, alpha:ArrayLikeObject, sa:integer, beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.beta.ndarray","random.strided.beta.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.betaprime","random.strided.betaprime( N:integer, alpha:ArrayLikeObject, sa:integer, beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.betaprime.ndarray","random.strided.betaprime.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.chi","random.strided.chi( N:integer, k:ArrayLikeObject, sk:integer, out:ArrayLikeObject, so:integer )"],["random.strided.chi.ndarray","random.strided.chi.ndarray( N:integer, k:ArrayLikeObject, sk:integer, ok:integer, out:ArrayLikeObject, so:integer, oo:integer )"],["random.strided.chi.factory","random.strided.chi.factory( [options:Object] )"],["random.strided.chi.PRNG","random.strided.chi.PRNG"],["random.strided.chi.seed","random.strided.chi.seed"],["random.strided.chi.seedLength","random.strided.chi.seedLength"],["random.strided.chi.state","random.strided.chi.state"],["random.strided.chi.stateLength","random.strided.chi.stateLength"],["random.strided.chi.byteLength","random.strided.chi.byteLength"],["random.strided.chisquare","random.strided.chisquare( N:integer, k:ArrayLikeObject, sk:integer, out:ArrayLikeObject, so:integer )"],["random.strided.chisquare.ndarray","random.strided.chisquare.ndarray( N:integer, k:ArrayLikeObject, sk:integer, ok:integer, out:ArrayLikeObject, so:integer, oo:integer )"],["random.strided.chisquare.factory","random.strided.chisquare.factory( [options:Object] )"],["random.strided.chisquare.PRNG","random.strided.chisquare.PRNG"],["random.strided.chisquare.seed","random.strided.chisquare.seed"],["random.strided.chisquare.seedLength","random.strided.chisquare.seedLength"],["random.strided.chisquare.state","random.strided.chisquare.state"],["random.strided.chisquare.stateLength","random.strided.chisquare.stateLength"],["random.strided.chisquare.byteLength","random.strided.chisquare.byteLength"],["random.strided.cosine","random.strided.cosine( N:integer, mu:ArrayLikeObject, sm:integer, s:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.cosine.ndarray","random.strided.cosine.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, om:integer, s:ArrayLikeObject, ss:integer, os:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.discreteUniform","random.strided.discreteUniform( N:integer, a:ArrayLikeObject, sa:integer, b:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.discreteUniform.ndarray","random.strided.discreteUniform.ndarray( N:integer, a:ArrayLikeObject, sa:integer, oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.exponential","random.strided.exponential( N:integer, lambda:ArrayLikeObject, sl:integer, out:ArrayLikeObject, so:integer )"],["random.strided.exponential.ndarray","random.strided.exponential.ndarray( N:integer, lambda:ArrayLikeObject, sl:integer, ol:integer, out:ArrayLikeObject, so:integer, oo:integer )"],["random.strided.exponential.factory","random.strided.exponential.factory( [options:Object] )"],["random.strided.exponential.PRNG","random.strided.exponential.PRNG"],["random.strided.exponential.seed","random.strided.exponential.seed"],["random.strided.exponential.seedLength","random.strided.exponential.seedLength"],["random.strided.exponential.state","random.strided.exponential.state"],["random.strided.exponential.stateLength","random.strided.exponential.stateLength"],["random.strided.exponential.byteLength","random.strided.exponential.byteLength"],["random.strided.gamma","random.strided.gamma( N:integer, alpha:ArrayLikeObject, sa:integer, beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.gamma.ndarray","random.strided.gamma.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.geometric","random.strided.geometric( N:integer, p:ArrayLikeObject, sp:integer, out:ArrayLikeObject, so:integer )"],["random.strided.geometric.ndarray","random.strided.geometric.ndarray( N:integer, p:ArrayLikeObject, sp:integer, op:integer, out:ArrayLikeObject, so:integer, oo:integer )"],["random.strided.geometric.factory","random.strided.geometric.factory( [options:Object] )"],["random.strided.geometric.PRNG","random.strided.geometric.PRNG"],["random.strided.geometric.seed","random.strided.geometric.seed"],["random.strided.geometric.seedLength","random.strided.geometric.seedLength"],["random.strided.geometric.state","random.strided.geometric.state"],["random.strided.geometric.stateLength","random.strided.geometric.stateLength"],["random.strided.geometric.byteLength","random.strided.geometric.byteLength"],["random.strided.invgamma","random.strided.invgamma( N:integer, alpha:ArrayLikeObject, sa:integer, beta:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.invgamma.ndarray","random.strided.invgamma.ndarray( N:integer, alpha:ArrayLikeObject, sa:integer, oa:integer, beta:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.lognormal","random.strided.lognormal( N:integer, mu:ArrayLikeObject, sm:integer, sigma:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.lognormal.ndarray","random.strided.lognormal.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, om:integer, sigma:ArrayLikeObject, ss:integer, os:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.minstd","random.strided.minstd( N:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.minstd.ndarray","random.strided.minstd.ndarray( N:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.minstd.normalized","random.strided.minstd.normalized( N:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.minstd.normalized.ndarray","random.strided.minstd.normalized.ndarray( N:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.minstdShuffle","random.strided.minstdShuffle( N:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.minstdShuffle.ndarray","random.strided.minstdShuffle.ndarray( N:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.minstdShuffle.normalized","random.strided.minstdShuffle.normalized( N:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.minstdShuffle.normalized.ndarray","random.strided.minstdShuffle.normalized.ndarray( N:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.mt19937","random.strided.mt19937( N:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.mt19937.ndarray","random.strided.mt19937.ndarray( N:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.mt19937.normalized","random.strided.mt19937.normalized( N:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.mt19937.normalized.ndarray","random.strided.mt19937.normalized.ndarray( N:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.normal","random.strided.normal( N:integer, mu:ArrayLikeObject, sm:integer, sigma:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.normal.ndarray","random.strided.normal.ndarray( N:integer, mu:ArrayLikeObject, sm:integer, om:integer, sigma:ArrayLikeObject, ss:integer, os:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.poisson","random.strided.poisson( N:integer, lambda:ArrayLikeObject, sl:integer, out:ArrayLikeObject, so:integer )"],["random.strided.poisson.ndarray","random.strided.poisson.ndarray( N:integer, lambda:ArrayLikeObject, sl:integer, ol:integer, out:ArrayLikeObject, so:integer, oo:integer )"],["random.strided.poisson.factory","random.strided.poisson.factory( [options:Object] )"],["random.strided.poisson.PRNG","random.strided.poisson.PRNG"],["random.strided.poisson.seed","random.strided.poisson.seed"],["random.strided.poisson.seedLength","random.strided.poisson.seedLength"],["random.strided.poisson.state","random.strided.poisson.state"],["random.strided.poisson.stateLength","random.strided.poisson.stateLength"],["random.strided.poisson.byteLength","random.strided.poisson.byteLength"],["random.strided.randu","random.strided.randu( N:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.randu.ndarray","random.strided.randu.ndarray( N:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.rayleigh","random.strided.rayleigh( N:integer, sigma:ArrayLikeObject, ss:integer, out:ArrayLikeObject, so:integer )"],["random.strided.rayleigh.ndarray","random.strided.rayleigh.ndarray( N:integer, sigma:ArrayLikeObject, ss:integer, os:integer, out:ArrayLikeObject, so:integer, oo:integer )"],["random.strided.rayleigh.factory","random.strided.rayleigh.factory( [options:Object] )"],["random.strided.rayleigh.PRNG","random.strided.rayleigh.PRNG"],["random.strided.rayleigh.seed","random.strided.rayleigh.seed"],["random.strided.rayleigh.seedLength","random.strided.rayleigh.seedLength"],["random.strided.rayleigh.state","random.strided.rayleigh.state"],["random.strided.rayleigh.stateLength","random.strided.rayleigh.stateLength"],["random.strided.rayleigh.byteLength","random.strided.rayleigh.byteLength"],["random.strided.t","random.strided.t( N:integer, v:ArrayLikeObject, sv:integer, out:ArrayLikeObject, so:integer )"],["random.strided.t.ndarray","random.strided.t.ndarray( N:integer, v:ArrayLikeObject, sv:integer, ov:integer, out:ArrayLikeObject, so:integer, oo:integer )"],["random.strided.t.factory","random.strided.t.factory( [options:Object] )"],["random.strided.t.PRNG","random.strided.t.PRNG"],["random.strided.t.seed","random.strided.t.seed"],["random.strided.t.seedLength","random.strided.t.seedLength"],["random.strided.t.state","random.strided.t.state"],["random.strided.t.stateLength","random.strided.t.stateLength"],["random.strided.t.byteLength","random.strided.t.byteLength"],["random.strided.uniform","random.strided.uniform( N:integer, a:ArrayLikeObject, sa:integer, b:ArrayLikeObject, sb:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.uniform.ndarray","random.strided.uniform.ndarray( N:integer, a:ArrayLikeObject, sa:integer, oa:integer, b:ArrayLikeObject, sb:integer, ob:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["random.strided.weibull","random.strided.weibull( N:integer, k:ArrayLikeObject, sk:integer, lambda:ArrayLikeObject, sl:integer, out:ArrayLikeObject, so:integer[, options:Object] )"],["random.strided.weibull.ndarray","random.strided.weibull.ndarray( N:integer, k:ArrayLikeObject, sk:integer, ok:integer, lambda:ArrayLikeObject, sl:integer, ol:integer, out:ArrayLikeObject, so:integer, oo:integer[, options:Object] )"],["ranks","ranks( arr:Array<number>[, options:Object] )"],["readDir","readDir( path:string|Buffer, clbk:Function )"],["readDir.sync","readDir.sync( path:string|Buffer )"],["readFile","readFile( file:string|Buffer|integer[, options:Object|string], clbk:Function )"],["readFile.sync","readFile.sync( file:string|Buffer|integer[, options:Object|string] )"],["readFileList","readFileList( filepaths:Array<string>[, options:Object|string], clbk:Function )"],["readFileList.sync","readFileList.sync( filepaths:Array<string>[, options:Object|string] )"],["readJSON","readJSON( file:string|Buffer|integer[, options:Object|string], clbk:Function )"],["readJSON.sync","readJSON.sync( file:string|Buffer|integer[, options:Object|string] )"],["readWASM","readWASM( file:string|Buffer|integer[, options:Object], clbk:Function )"],["readWASM.sync","readWASM.sync( file:string|Buffer|integer[, options:Object] )"],["real","real( z:Complex128 )"],["realarray","realarray( [dtype:string] )"],["realarray","realarray( length:integer[, dtype:string] )"],["realarray","realarray( typedarray:TypedArray[, dtype:string] )"],["realarray","realarray( obj:Object[, dtype:string] )"],["realarray","realarray( buffer:ArrayBuffer[, byteOffset:integer[, length:integer]][, dtype:string] )"],["realarrayCtors","realarrayCtors( dtype:string )"],["realarrayDataTypes","realarrayDataTypes()"],["realf","realf( z:Complex64 )"],["realmax","realmax( dtype:string )"],["realmin","realmin( dtype:string )"],["reBasename","reBasename( [platform:string] 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)"],["reDirname.REGEXP","reDirname.REGEXP"],["reDirname.REGEXP_POSIX","reDirname.REGEXP_POSIX"],["reDirname.REGEXP_WIN32","reDirname.REGEXP_WIN32"],["reDirnamePosix","reDirnamePosix()"],["reDirnamePosix.REGEXP","reDirnamePosix.REGEXP"],["reDirnameWindows","reDirnameWindows()"],["reDirnameWindows.REGEXP","reDirnameWindows.REGEXP"],["reduce","reduce( arr:ArrayLikeObject|ndarray, initial:any, reducer:Function[, thisArg:any] )"],["reduce2d","reduce2d( arr:ArrayLikeObject<ArrayLikeObject>, initial:ArrayLikeObject, reducer:Function[, thisArg:any] )"],["reduceAsync","reduceAsync( collection:Array|TypedArray|Object, initial:any, [options:Object,] reducer:Function, done:Function )"],["reduceAsync.factory","reduceAsync.factory( [options:Object,] fcn:Function )"],["reduceRight","reduceRight( arr:ArrayLikeObject|ndarray, initial:any, reducer:Function[, thisArg:any] )"],["reduceRightAsync","reduceRightAsync( collection:Array|TypedArray|Object, initial:any, [options:Object,] reducer:Function, done:Function )"],["reduceRightAsync.factory","reduceRightAsync.factory( [options:Object,] fcn:Function )"],["reDurationString","reDurationString()"],["reDurationString.REGEXP","reDurationString.REGEXP"],["reEOL","reEOL( [options:Object] )"],["reEOL.REGEXP","reEOL.REGEXP"],["reEOL.REGEXP_CAPTURE","reEOL.REGEXP_CAPTURE"],["reExtendedLengthPath","reExtendedLengthPath()"],["reExtendedLengthPath.REGEXP","reExtendedLengthPath.REGEXP"],["reExtname","reExtname( [platform:string] )"],["reExtname.REGEXP","reExtname.REGEXP"],["reExtname.REGEXP_POSIX","reExtname.REGEXP_POSIX"],["reExtname.REGEXP_WIN32","reExtname.REGEXP_WIN32"],["reExtnamePosix","reExtnamePosix"],["reExtnamePosix.REGEXP","reExtnamePosix.REGEXP"],["reExtnameWindows","reExtnameWindows"],["reExtnameWindows.REGEXP","reExtnameWindows.REGEXP"],["reFilename","reFilename( [platform:string] )"],["reFilename.REGEXP","reFilename.REGEXP"],["reFilename.REGEXP_POSIX","reFilename.REGEXP_POSIX"],["reFilename.REGEXP_WIN32","reFilename.REGEXP_WIN32"],["reFilenamePosix","reFilenamePosix()"],["reFilenamePosix.REGEXP","reFilenamePosix.REGEXP"],["reFilenameWindows","reFilenameWindows()"],["reFilenameWindows.REGEXP","reFilenameWindows.REGEXP"],["reFromString","reFromString( str:string )"],["reFunctionName","reFunctionName()"],["reFunctionName.REGEXP","reFunctionName.REGEXP"],["regexp2json","regexp2json( re:RegExp )"],["reim","reim( z:Complex128 )"],["reimf","reimf( z:Complex64 )"],["rejectArguments","rejectArguments( fcn:Function, predicate:Function[, thisArg:any] )"],["removeFirst","removeFirst( str:string[, n:integer][, options:Object] )"],["removeLast","removeLast( str:string[, n:integer][, options:Object] )"],["removePunctuation","removePunctuation( str:string )"],["removeUTF8BOM","removeUTF8BOM( str:string )"],["removeWords","removeWords( str:string, words:Array<string>[, ignoreCase:boolean] )"],["rename","rename( oldPath:string|Buffer, newPath:string|Buffer, clbk:Function )"],["rename.sync","rename.sync( oldPath:string|Buffer, newPath:string|Buffer )"],["reNativeFunction","reNativeFunction()"],["reNativeFunction.REGEXP","reNativeFunction.REGEXP"],["reorderArguments","reorderArguments( fcn:Function, indices:Array<integer>[, thisArg:any] )"],["repeat","repeat( str:string, n:integer )"],["replace","replace( str:string, search:string|RegExp, newval:string|Function )"],["replaceBefore","replaceBefore( str, search, replacement )"],["reRegExp","reRegExp()"],["reRegExp.REGEXP","reRegExp.REGEXP"],["rescape","rescape( str:string )"],["reSemVer","reSemVer()"],["reSemVer.REGEXP","reSemVer.REGEXP"],["resolveParentPath","resolveParentPath( path:string[, options:Object], clbk:Function )"],["resolveParentPath.sync","resolveParentPath.sync( path:string[, options:Object] )"],["resolveParentPathBy","resolveParentPathBy( path:string[, options:Object], predicate:Function, clbk:Function )"],["resolveParentPathBy.sync","resolveParentPathBy.sync( path:string[, options:Object], predicate:Function )"],["reUncPath","reUncPath()"],["reUncPath.REGEXP","reUncPath.REGEXP"],["reUtf16SurrogatePair","reUtf16SurrogatePair()"],["reUtf16SurrogatePair.REGEXP","reUtf16SurrogatePair.REGEXP"],["reUtf16UnpairedSurrogate","reUtf16UnpairedSurrogate()"],["reUtf16UnpairedSurrogate.REGEXP","reUtf16UnpairedSurrogate.REGEXP"],["reverseArguments","reverseArguments( fcn:Function[, thisArg:any] )"],["reverseString","reverseString( str:string[, options:Object] )"],["reviveBasePRNG","reviveBasePRNG( key:string, value:any )"],["reviveBuffer","reviveBuffer( key:string, value:any )"],["reviveComplex","reviveComplex( key:string, value:any )"],["reviveComplex64","reviveComplex64( key:string, value:any )"],["reviveComplex128","reviveComplex128( key:string, value:any )"],["reviveError","reviveError( key:string, value:any )"],["reviveRegExp","reviveRegExp( key:string, value:any 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)"],["strided.ahavercosBy","strided.ahavercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.ahavercosBy.ndarray","strided.ahavercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.ahaversinBy","strided.ahaversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.ahaversinBy.ndarray","strided.ahaversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.asinBy","strided.asinBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.asinBy.ndarray","strided.asinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.asinhBy","strided.asinhBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.asinhBy.ndarray","strided.asinhBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.atanBy","strided.atanBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.atanBy.ndarray","strided.atanBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.atanhBy","strided.atanhBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.atanhBy.ndarray","strided.atanhBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.avercosBy","strided.avercosBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.avercosBy.ndarray","strided.avercosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.aversinBy","strided.aversinBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.aversinBy.ndarray","strided.aversinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.besselj0By","strided.besselj0By( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.besselj0By.ndarray","strided.besselj0By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.besselj1By","strided.besselj1By( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.besselj1By.ndarray","strided.besselj1By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.bessely0By","strided.bessely0By( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.bessely0By.ndarray","strided.bessely0By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.bessely1By","strided.bessely1By( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.bessely1By.ndarray","strided.bessely1By.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.binetBy","strided.binetBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.binetBy.ndarray","strided.binetBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.cbrt","strided.cbrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.cbrt.ndarray","strided.cbrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.cbrtBy","strided.cbrtBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.cbrtBy.ndarray","strided.cbrtBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.ceil","strided.ceil( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.ceil.ndarray","strided.ceil.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.cosBy","strided.cosBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.cosBy.ndarray","strided.cosBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.deg2rad","strided.deg2rad( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.deg2rad.ndarray","strided.deg2rad.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.dataTypes","strided.dataTypes()"],["strided.dcbrtBy","strided.dcbrtBy( N:integer, x:Float64Array, sx:integer, y:Float64Array, sy:integer, clbk:Function[, thisArg:any] )"],["strided.dcbrtBy.ndarray","strided.dcbrtBy.ndarray( N:integer, x:Float64Array, sx:integer, ox:integer, y:Float64Array, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.dispatch","strided.dispatch( fcns:Function|ArrayLikeObject<Function>, types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, nout:integer )"],["strided.dispatchBy","strided.dispatchBy( fcns:Function|ArrayLikeObject<Function>, types:ArrayLikeObject, data:ArrayLikeObject|null, nargs:integer, nin:integer, nout:integer )"],["strided.floor","strided.floor( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.floor.ndarray","strided.floor.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.inv","strided.inv( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.inv.ndarray","strided.inv.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.mul","strided.mul( N:integer, dx:any, x:ArrayLikeObject, sx:integer, dy:any, y:ArrayLikeObject, sy:integer, dz:any, z:ArrayLikeObject, sz:integer )"],["strided.mul.ndarray","strided.mul.ndarray( N:integer, dx:any, x:ArrayLikeObject, sx:integer, ox:integer, dy:any, y:ArrayLikeObject, sy:integer, oy:integer, dz:any, z:ArrayLikeObject, sz:integer, oz:integer )"],["strided.mulBy","strided.mulBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, z:Array|TypedArray|Object, sz:integer, clbk:Function[, thisArg:any] )"],["strided.mulBy.ndarray","strided.mulBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, z:Array|TypedArray|Object, sz:integer, oz:integer, clbk:Function[, thisArg:any] )"],["strided.ramp","strided.ramp( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.ramp.ndarray","strided.ramp.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.rsqrt","strided.rsqrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.rsqrt.ndarray","strided.rsqrt.ndarray( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, offsetX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer, offsetY:integer )"],["strided.sinBy","strided.sinBy( N:integer, x:Array|TypedArray|Object, sx:integer, y:Array|TypedArray|Object, sy:integer, clbk:Function[, thisArg:any] )"],["strided.sinBy.ndarray","strided.sinBy.ndarray( N:integer, x:Array|TypedArray|Object, sx:integer, ox:integer, y:Array|TypedArray|Object, sy:integer, oy:integer, clbk:Function[, thisArg:any] )"],["strided.sqrt","strided.sqrt( N:integer, dtypeX:any, x:ArrayLikeObject, strideX:integer, dtypeY:any, y:ArrayLikeObject, strideY:integer )"],["strided.sqrt.ndarray","strided.sqrt.ndarray( N:integer, dtypeX:any, 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From dd35147d4a6fe96a4ae15efa036044f806f7c8f7 Mon Sep 17 00:00:00 2001
From: Athan Reines <kgryte@gmail.com>
Date: Sat, 4 Jan 2025 03:01:22 -0800
Subject: [PATCH 87/87] docs: fix comments

---
type: pre_commit_static_analysis_report
description: Results of running static analysis checks when committing changes.
report:
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    status: passed
  - task: lint_editorconfig
    status: passed
  - task: lint_markdown
    status: passed
  - task: lint_package_json
    status: na
  - task: lint_repl_help
    status: na
  - task: lint_javascript_src
    status: na
  - task: lint_javascript_cli
    status: na
  - task: lint_javascript_examples
    status: na
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    status: na
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  - task: lint_r
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  - task: lint_c_examples
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---
---
 lib/node_modules/@stdlib/array/to-fancy/README.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/lib/node_modules/@stdlib/array/to-fancy/README.md b/lib/node_modules/@stdlib/array/to-fancy/README.md
index abb3b16e8c24..e78a9971b8ee 100644
--- a/lib/node_modules/@stdlib/array/to-fancy/README.md
+++ b/lib/node_modules/@stdlib/array/to-fancy/README.md
@@ -37,7 +37,7 @@ var x = [ 1, 2, 3, 4, 5, 6, 7, 8 ];
 // Turn the plain array into a "fancy" array:
 var y = array2fancy( x );
 
-// Select the first 3 elements:
+// Select the first three elements:
 var v = y[ ':3' ];
 // returns [ 1, 2, 3 ]
 
@@ -45,7 +45,7 @@ var v = y[ ':3' ];
 v = y[ '1::2' ];
 // returns [ 2, 4, 6, 8 ]
 
-// Select every other element, in reverse order, starting with the least element:
+// Select every other element, in reverse order, starting with the last element:
 v = y[ '::-2' ];
 // returns [ 8, 6, 4, 2 ]